(y))?(x):(y))\n#endif\n\n#ifndef MIN\n#define MIN(x,y) (((x) < (y))?(x):(y))\n#endif\n\n#define SetTieBreak(a,b) a->C.tiebreak=b \n\n#define MSG1 \"Cannot allocate memory space\"\n#define MSG2 \"Cannot open file\"\n#define SIZE 64\n#define PI 3.1415926536\n#define ROUND(x) ((x < 0)?(int)(x-0.5):(int)(x+0.5))\n#define NIL -1\n#define WHITE 0 \n#define GRAY 1\n#define BLACK 2\n#define INCREASING 1\n#define DECREASING 0\n#define HISTOGRAMSIZE 180\n#define LIFOBREAK 1\n#define FIFOBREAK 0\n#define INTERIOR 0\n#define EXTERIOR 1\n#define HEAP_DAD(i) ((i - 1) / 2)\n#define HEAP_LEFTSON(i) (2 * i + 1)\n#define HEAP_RIGHTSON(i) (2 * i + 2)\n#define BOTH 2\n\n#include \n#include \n#include \n#include \n#include \n#include \n\n/* Common operations functions ************************/\nint NCFgets(char *s, int m, FILE *f); \nint *AllocIntArray(int n);\ndouble *AllocDoubleArray(int n);\nfloat *AllocFloatArray(int n); \nchar *AllocCharArray(int n); /* It allocates 1D array of n characters */\n\n/* Errors functions *********************************/\nvoid Error(char *msg,char *func); \n\n/* Data structures **********************************/\n/* BIC */\ntypedef struct {\n int color;\n int frequency;\n}Property;\n\ntypedef struct {\n unsigned long colorH[SIZE];\n unsigned long lowH[SIZE];\n unsigned long highH[SIZE];\n}VisualFeature;\n\ntypedef struct {\n unsigned char colorH[SIZE];\n unsigned char lowH[SIZE];\n unsigned char highH[SIZE];\n}CompressedVisualFeature;\n\n/* pgm images */\ntypedef struct _image {\n int *val;\n int ncols,nrows;\n int *tbrow;\n} Image;\n\n/* ppm images */\ntypedef struct cimage {\n Image *C[3];\n} CImage;\n\ntypedef struct _FeatureVector1D {\n double *X;\n int n; \n} FeatureVector1D;\n\ntypedef struct _FeatureVector2D {\n double *X;\n double *Y;\n int n; \n} FeatureVector2D;\n\ntypedef struct _curve {\n double *X;\n double *Y;\n int n; \n} Curve;\n\ntypedef struct _curve3d { /* 3D Curve */\n double *X;\n double *Y;\n double *Z;\n int n; \n} Curve3D;\n\ntypedef struct _adjrel {\n int *dx;\n int *dy;\n int n;\n} AdjRel;\n\ntypedef struct _pixel {\n int x,y;\n} Pixel;\n\ntypedef struct{\n int length; /* length of the boundary */\n int *X; /* X values of each boundary point from 0 to length-1 */\n int *Y; /* Y values of each boundary point from 0 to length-1 */\n} boundary_type;\n\ntypedef struct{\n int length; /* length of the boundary */\n int *mean; /* mean value BAS function */\n int *second; \n int *third;\n} representation_type;\n\ntypedef struct _DImage{\n double *val;\n int ncols,nrows;\n int *tbrow;\n} DImage;\n\ntypedef struct _tensorscale{\n DImage *anisotropy;\n DImage *orientation;\n DImage *thickness;\n\n int m_pairs;\n}TensorScale;\n\ntypedef struct _vector{\n float x;\n float y;\n float z;\n} Vector, Point, Vertex;\n\ntypedef struct _node { \n int next; /* next node */\n int prev; /* prev node */\n char color; /* WHITE=0, GRAY=1, BLACK=2 */\n} Node;\n\ntypedef struct _doublylinkedlists {\n Node *elem; /* all possible doubly-linked lists of the circular queue */\n int nelems; /* total number of elements */\n} DoublyLinkedLists; \n\ntypedef struct _circularqueue { \n int *first; /* list of the first elements of each doubly-linked list */\n int *last; /* list of the last elements of each doubly-linked list */\n int nbuckets; /* number of buckets in the circular queue */\n int current; /* current bucket */\n char tiebreak; /* 1 is LIFO, 0 is FIFO (default) */\n} CircularQueue;\n\ntypedef struct _queue { /* Priority queue by Dial implemented as\n proposed by A. Falcao */\n CircularQueue C;\n DoublyLinkedLists L;\n} Queue;\n\ntypedef struct _polynom { /* Polynomial */\n double *coef; /* a0*x^0 + a1*x^1 + ... + an*x^n */ \n int n; /* degree n */\n} Polynom;\n\ntypedef struct _set {\n int elem;\n struct _set *next;\n} Set;\n\ntypedef struct _annimg {\n Image *img;\n Image *grad;\n Image *cost;\n Image *label;\n Image *pred;\n Image *root;\n Set *seed;\n} AnnImg;\n\ntypedef struct _heap {\n int *cost;\n char *color;\n int *pixel;\n int *pos;\n int last;\n int n;\n} Heap;\n\ntypedef struct _adjpxl {\n int *dp;\n int n;\n} AdjPxl;\n\n/*Working with images *****************************/\n\n/* pgm images */\nImage *CreateImage(int ncols,int nrows);\nvoid DestroyImage(Image **img);\nImage *ReadImage(char *filename);\nImage *MBB(Image *img);\nImage *ROI(Image *img, int xl, int yl, int xr, int yr);\nImage *AddFrame(Image *img, int sz, int value);\nvoid SetImage(Image *img, int value);\nvoid WriteImage(Image *img,char *filename);\n\n/* ppm images */\nCImage *CreateCImage(int ncols, int nrows);\nvoid DestroyCImage(CImage **cimg);\nCImage *ReadCImage(char *filename);\n\n/* auxiliary functions ****************************/\nCurve *CreateCurve(int n);\nvoid DestroyCurve(Curve **curve);\nFeatureVector1D *CurveTo1DFeatureVector(Curve *curve);\nFeatureVector1D *CreateFeatureVector1D(int n);\nvoid DestroyFeatureVector1D(FeatureVector1D **desc);\nvoid WriteFeatureVector1D(FeatureVector1D *desc,char *filename);\nAdjRel *CreateAdjRel(int n);\nvoid DestroyAdjRel(AdjRel **A);\nAdjRel *LeftSide(AdjRel *A);\nAdjRel *RightSide(AdjRel *A);\nAdjRel *Circular(float r);\nbool ValidPixel(Image *img, int x, int y);\nbool ValidContPoint(Image *bin, AdjRel *L, AdjRel *R, int p);\nImage *LabelContPixel(Image *bin);\nCurve3D *CreateCurve3D(int n);\nvoid DestroyCurve3D(Curve3D **curve);\nvoid SortCurve3D(Curve3D *curve, int left, int right, char order);\nint PartCurve3D (Curve3D *curve, int left, int right, char order);\nint FFT(int dir, long nn, double *x, double *y);\nImage *LabelContour(Image *bin);\nvoid Warning(char *msg,char *func); \nImage *Scale(Image *img, float Sx, float Sy) ;\nDImage *CreateDImage(int ncols, int nrows);\nvoid DestroyDImage(DImage **dimg);\nvoid DestroyImage(Image **img);\nint MaximumValue(Image *img);\nQueue *CreateQueue(int nbuckets, int nelems);\nvoid DestroyQueue(Queue **Q);\nint EmptyQueue(Queue *Q);\nvoid InsertQueue(Queue *Q, int bucket, int elem);\nint RemoveQueue(Queue *Q);\nvoid UpdateQueue(Queue *Q, int elem, int from, int to);\nvoid ResetQueue(Queue *Q);\nvoid RemoveQueueElem(Queue *Q, int elem, int bucket);\nCurve *SamplePolynom(Polynom *P, double from, double to, int nbins);\nPolynom *CreatePolynom(int degree);\nvoid DestroyPolynom(Polynom **P);\nPolynom *DerivPolynom(Polynom *P);\nPolynom *Regression(Curve *curve, int degree);\nPolynom *MSFractal(Image *bin,int maxdist,int degree,double lower,double higher,int reg,double from,double to);\nAnnImg *Annotate(Image *img, Image *cost, Image *label);\nAdjRel *ComplAdj(AdjRel *A1, AdjRel *A2);\nvoid InsertSet(Set **S, int elem);\nint RemoveSet(Set **S);\nint Seed(Image *pred, int p);\nImage *CompPaths(Image *pred);\nImage *Perimeter(Image *bin);\nCurve3D *Saliences(Image *bin, int maxdist);\nImage *MSSkel(Image *bin, char side);\nvoid DestroyAdjPxl(AdjPxl **N);\nCurve3D *CompSaliences(AnnImg *aimg, int maxcost);\nImage *RemFrame(Image *fimg, int sz);\nAdjPxl *AdjPixels(Image *img, AdjRel *A);\nImage *Abs(Image *img);\nCurve3D *RemSaliencesByAngle(Curve3D *curve,int radius, int angle);\nImage *LabelBinComp(Image *bin, AdjRel *A);\nCurve3D *SkelSaliences(Image *skel, int maxdist, int angle) ;\nImage *Skeleton(Image *msskel, float perc);\nImage *CompMSSkel(AnnImg *aimg);\nvoid iftDilation(AnnImg *aimg, AdjRel *A); /* by Dial */\nvoid InvertXY(Curve *curve);\nCurve *CopyCurve(Curve *curve);\nvoid SortCurve(Curve *curve, int left, int right, char order);\nint PartCurve (Curve *curve, int left, int right, char order);\nCurve *Histogram(Image *img);\nvoid DestroySet(Set **S);\nvoid DeAnnotate(AnnImg **aimg);\nint FrameSize(AdjRel *A);\nvoid Change(int *a, int *b);\nHeap *CreateHeap(int n, int *cost);\nvoid DestroyHeap(Heap **H);\nbool InsertHeap(Heap *H, int pixel);\nbool RemoveHeap(Heap *H, int *pixel);\nvoid GoUpHeap(Heap *H, int i);\nbool IsEmptyHeap(Heap *H);\nbool HeapIsEmpty(Heap *H);\nvoid GoDownHeap(Heap *H, int i);\nbool IsFullHeap(Heap *H);\nvoid GoUpHeap(Heap *H, int i);\nFeatureVector2D *CurveTo2DFeatureVector(Curve *curve);\n/* Descriptor functions ***************************/\n\n/* BIC */\n/* auxiliary functions */\nCurve *BIC(CImage *img);\nvoid Write_visual_features(char *filename,char *dbname, CompressedVisualFeature *cvf);\nCompressedVisualFeature *Extract_visual_features(CImage *img);\ndouble gray_level_BIC(Image *img1, Image *img2);\n\n/* Fourier Descriptor */\n/* auxiliary functions */\ndouble Cabs(double x, double y);\nCurve *Image2Curve(Image *img);\nCurve *FourierDescriptor(Image *img);\n\n/* Moments Invariant */\n/* auxiliary functions */\ndouble MomentPQ(int p, int q, Image *img, int max);\nCurve *MomentInv(Image *img);\nCurve *MomentInvariant(Image *img); // contorno e objeto inteiro\n\n/* BAS */\n/* auxiliary functions */\nCurve *BAS(Image *in,int rsp,int nsamples);\n\n/* Tensor Scale */\n/* auxiliary functions */\nTensorScale *CreateBinaryTensorScale(Image *bin, int m_pairs);\nvoid DestroyTensorScale(TensorScale **ts);\nfloat *TSOrientationHistogram(TensorScale *ts);\nImage *TSEDistTrans(Image *bin);\n\n/* MultiScale Fractal Dimension*/\n/* auxiliary functions */\nCurve *PolynomToFractalCurve(Polynom *P, double lower, double higher, int nbins);\nCurve *ContourMSFractal(Image *in);\n\n/* Contour Saliences */\n/* auxiliary functions */\nCurve3D *SkelCont(Image *bin, int maxdist, int threshold, int angle, char side);\nCurve3D *iftContourSaliences(Image *bin,int threshold_in,int threshold_out,int angle_in,int angle_out);\nCurve *ContourSaliences(Image *in);\nvoid DescInvertXY(FeatureVector2D *desc);\nFeatureVector2D *CreateFeatureVector2D(int n);\ndouble ContSalieDistance(FeatureVector2D *D1, FeatureVector2D *D2);\nFeatureVector2D *CircularRotation(FeatureVector2D *descriptor, double delta);\nvoid DestroyFeatureVector2D(FeatureVector2D **desc);\nvoid SortFeatureVector2D(FeatureVector2D *desc, int left, int right, char order);\nint PartFeatureVector2D (FeatureVector2D *desc, int left, int right, char order);\nvoid WriteFeatureVector2D(FeatureVector2D *desc,char *filename);\nFeatureVector2D *CopyFeatureVector2D(FeatureVector2D *desc);\nvoid DestroyFeatureVector2D(FeatureVector2D **desc);\ndouble Matching(FeatureVector2D *descriptor1, FeatureVector2D *descriptor2, int order);\n\n/* Segment Saliences */\n/* auxiliary functions */\nCurve *SS_ExtractionAlgorithm_(Image *in, int maxdist, int nsamples, int side);\ndouble SS_OCSMatching(FeatureVector1D *fv_1, FeatureVector1D *fv_2);\ndouble SS_OCS(FeatureVector1D *fv1, FeatureVector1D *fv2);\ndouble SS_getMin(double Dist1, double Dist2, double Dist3);\n\n/* call functions *********************************/\n/* BIC */\nFeatureVector1D *BIC_ExtractionAlgorithm(CImage *in); /*BIC extractor*/\ndouble BIC_DistanceAlgorithm(FeatureVector1D *fv1, FeatureVector1D *fv2); /*BIC similarity*/\n\n/* Fourier Descriptor */\nFeatureVector1D *FourierDescriptor_ExtractionAlgorithm(Image *in);/* in is a binary image*/\ndouble Fourier_DistanceAlgorithm(FeatureVector1D *fv1, FeatureVector1D *fv2); /*fourier similarity*/\n\n/* Moments Invariant */\nFeatureVector1D *MomentInvariant_ExtractionAlgorithm(Image *in);/*in is a binary image*/\ndouble MomentInvariant_DistanceAlgorithm(FeatureVector1D *fv1, FeatureVector1D *fv2);\n\n/* BAS */\nFeatureVector1D *BAS_ExtractionAlgorithm(Image *in,int rsp,int nsamples);\ndouble BAS_DistanceAlgorithm(FeatureVector1D *c1, FeatureVector1D *c2);\n\n/* Tensor Scale */\nFeatureVector1D *TensorScale_ExtractionAlgorithm(Image *in);\ndouble TensorScale_DistanceAlgorithm(FeatureVector1D *c1, FeatureVector1D *c2);\n\n/* Multiscale Fractal Dimension */\nFeatureVector1D *MS_ExtractionAlgorithm(Image *img);\ndouble MS_DistanceAlgorithm(FeatureVector1D *fv1, FeatureVector1D *fv2); \n\n/* Contour Saliences */\nFeatureVector2D *CS_ExtractionAlgorithm(Image *img);\ndouble CS_DistanceAlgorithm(FeatureVector2D *descriptor1, FeatureVector2D *descriptor2);\n\n/* Segment Saliences */\nFeatureVector1D *SS_ExtractionAlgorithm(Image *img);\ndouble SS_DistanceAlgorithm(FeatureVector1D *fv1d1, FeatureVector1D *fv1d2);\n\n/* Metrics to measure the similarity between feature vectors*/\ndouble EuclideanDistance(FeatureVector1D *v1, FeatureVector1D *v2);\ndouble L1_Distance(FeatureVector1D *v1, FeatureVector1D *v2);\nfloat TSHistogramMatch(FeatureVector1D *fv1, FeatureVector1D *fv2, int *offset);\ndouble dLog(FeatureVector1D *fv1, FeatureVector1D *fv2);\n\n#endif\n"},{"alpha_fraction":0.7578834891319275,"alphanum_fraction":0.770176351070404,"avg_line_length":38.787235260009766,"blob_id":"0ab1611960a6bc72f0c2c01f46fd8663ea559b1f","content_id":"395b4797c9a810e4972e450f822aedc154f4bf8a","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Text","length_bytes":1871,"license_type":"permissive","max_line_length":88,"num_lines":47,"path":"/MO445-descriptors/readme.txt","repo_name":"RQuispeC/mo805-assignment7","src_encoding":"UTF-8","text":"The purpose of this package is to provide the source code of some\nimage descriptors for the image analysis course (MO445). Each\ndescriptor is represented by a feature vector and a similarity\n(distance) function, and its corresponding paper can be found in the\nsubdirectory docs.\n\nFollow the steps:\n\n1 - Extract the files in MO445.tar.gz.\n\n2 - Go to the folder MO445 and execute the Makefile\n\n3 - Go to the folder examples (MO445/examples), which contains one\nexample file \"test.c\" and two images to execute the program.\n\n4 - Execute the Makefile. It will generate a executable file \"test\"\n\n5 - Run ./test\n\n6 - Some files corresponding to the descriptors will be generated, such as:\n\n- bas_ -> Descriptor Beam Angle Statistics (BAS) (SHAPE)\n- bic_.txt -> Border/Interior Pixel Classification (BIC) (COLOR/TEXTURE)\n- moments_.txt -> Moment Invariants (MI) (SHAPE)\n- fourier_.txt -> Fourier Descriptor (SHAPE)\n- tensorscale_.txt -> Tensor Scale Descriptor (SHAPE)\n- multiscales_.txt -> Multiscale Fractal Dimension (SHAPE)\n- contoursaliences_.txt -> Contour Saliences (SHAPE)\n- segmentsaliences_.txt -> Segment Saliences (SHAPE)\n\nAll descriptors have two basic functions: extraction and\nsimilarity (distance). Example for BAS:\n\n- FeatureVector1D *BAS_ExtractionAlgorithm(Image *in,int rsp,int nsamples);\n- double BAS_DistanceAlgorithm(FeatureVector1D *c1, FeatureVector1D *c2);\n\nThe extraction algorithm extracts the feature vector for an image and\nthe similarity function returns the distance between two images. Fell\nfree to modify the feature vector size.\n\nThe figures and the results obtained can be found in ./figs and\n./results directories, respectively.\n\nIf you have questions, please contact Joao Paulo Papa\n(jpaulo@ic.unicamp.br) or Alexandre Falcao (afalcao@ic.unicamp.br)\n\nEnjoy!\n\n"},{"alpha_fraction":0.7488822937011719,"alphanum_fraction":0.7809240221977234,"avg_line_length":30.20930290222168,"blob_id":"338c081ca6007fced7188e51229c067e05c790c7","content_id":"18c50f51f4c9b90763e183ba2015fea74f1463ba","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":1342,"license_type":"permissive","max_line_length":226,"num_lines":43,"path":"/README.md","repo_name":"RQuispeC/mo805-assignment7","src_encoding":"UTF-8","text":"# Precision vs Recall\nThis repo implements the assignment 7 of [MO805](http://www.ic.unicamp.br/~rtorres/mo805A_19s1/07-assignment.pdf) at UNICAMP.\n\n\n\n# Implemented/Modified scripts\n\n* `convert_mpeg_pgm.py` converts the `.gif` images of `mpeg7/`dataset to `.pgm` and stores them inside `MO445-descriptors/examples/mpeg7_pgm`\n\n* `MO445-descriptors/examples/test.c` extracts Multiscale Fractal Dimension and Segment Saliences features and stores them inside `MO445-descriptors/examples/mpeg7_features`\n\n* `MO445-descriptors/examples/file_name.py` is a small scripts that creates files with the paths and names of `MO445-descriptors/examples/mpeg7_pgm`.\n\n* `precision_recall.py` computes the precision x recall curve and plots it in `precision_recall.png`\n\n# Replicate Results\n\nClone the repository\n\n```\ngit clone https://github.com/RQuispeC/mo805-assignment7.git\n```\n\nThen run all the scripts using the available Makefile\n\n```\ncd mo805-assignment7\nmake\n```\n\n# Prerequisites\n\nThe code was tested under a linux distribution with :\n\n* GCC\n* Python3\n* Numpy\n* MatplotLib\n* PIL\n\n# Notes\n\nI used euclidean distance to compare feacture vectors for both Multiscale fractal and Segment salience descriptors. MO455 code offers a different distance function for Segment salience but euclidean may get better performance.\n"},{"alpha_fraction":0.5056179761886597,"alphanum_fraction":0.6029962301254272,"avg_line_length":18.071428298950195,"blob_id":"d9662fa559a8c53b9f411caafca67e27c4c94b3b","content_id":"1e513a0fdab141c0f9bc14fa409f07345a522af2","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Makefile","length_bytes":267,"license_type":"permissive","max_line_length":61,"num_lines":14,"path":"/MO445-descriptors/examples/Makefile","repo_name":"RQuispeC/mo805-assignment7","src_encoding":"UTF-8","text":"CFLAGS = -Wall -O3\nMO445LIB = -L../lib\nMO445FLAGS = -I../include\nCC=gcc\nFLAGS= -O3 -Wall\n\nall: libMO445 test\n\nlibMO445:\n\t$(MAKE) -C ../\ntest: libMO445 \n\t$(CC) $(MO445FLAGS) test.c $(MO445LIB) -o test -lMO445 -lm\nclean:\n\trm -f *~ test.o test ../lib/*.a ../obj/*.o\n"},{"alpha_fraction":0.605215311050415,"alphanum_fraction":0.6264402866363525,"avg_line_length":19.873416900634766,"blob_id":"543bab6b6825af966db55c15acc121cf76e72131","content_id":"3db79fe9c47bedbb86032481856591b86d25966c","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"C","length_bytes":1649,"license_type":"permissive","max_line_length":52,"num_lines":79,"path":"/MO445-descriptors/examples/test.c","repo_name":"RQuispeC/mo805-assignment7","src_encoding":"UTF-8","text":"#include \"MO445.h\"\n#include \n#include \n\nconst int LIMIT = 1400;\n\nchar* paths[1400];\nchar* names[1400];\nint max_len = 50;\nvoid chomp(char *s){\n\ts[strcspn(s, \"\\n\")] = '\\0';\n}\n\nvoid read_dataset_data(){\n\tFILE *fp;\n\tchar *line = NULL;\n\tsize_t len = 255;\n\tline = malloc(sizeof(char) * max_len);\n\n\tfp = fopen(\"paths.txt\", \"r\");\n\n\tint ind = 0;\n\twhile ((fgets(line, len, fp)) != NULL)\n\t{\n\t\tpaths[ind] = malloc(sizeof(char) * max_len);\n\t\tchomp(line);\n\t\tstrcpy(paths[ind], line);\n\t\t//printf(\"%s\\n\", paths[ind]);\n\t\tind += 1;\n\t}\n\n\tfp = fopen(\"names.txt\", \"r\");\n\n\tind = 0;\n\twhile ((fgets(line, len, fp)) != NULL)\n\t{\n\t\tnames[ind] = malloc(sizeof(char) * max_len);\n\t\tchomp(line);\n\t\tstrcpy(names[ind], line);\n\t\t//printf(\"%s\\n\", names[ind]);\n\t\tind += 1;\n\t}\n\tfree(line);\n}\n\nint main(int argc,char **argv){\n\n\tread_dataset_data();\n\tprintf(\"Loaded data for files\\n\");\n\n\tfor (int i = 0; i < LIMIT; i++){\n\t\tprintf(\"Extracting features of %s\\n\", names[i]);\n\n\t\tImage *img = NULL;\n\t\tFeatureVector1D *fvMS = NULL, *fvSS = NULL;\n\t\tchar *outfile_name = NULL;\n\t\toutfile_name = malloc(sizeof(char) * 3 * max_len);\n\n\t\timg = ReadImage(paths[i]);\n\t\tfvMS = MS_ExtractionAlgorithm(img);\n\t\tstrcpy(outfile_name,\"mpeg7_features/\");\n\t\tstrcat(outfile_name, names[i]);\n\t\tstrcat(outfile_name, \"_MS.txt\");\n\t\tWriteFeatureVector1D(fvMS, outfile_name);\n\n\t\tfvSS = SS_ExtractionAlgorithm(img);\n\t\tstrcpy(outfile_name, \"mpeg7_features/\");\n\t\tstrcat(outfile_name, names[i]);\n\t\tstrcat(outfile_name, \"_SS.txt\");\n\t\tWriteFeatureVector1D(fvSS, outfile_name);\n\n\t\tDestroyFeatureVector1D(&fvSS);\n\t\tDestroyFeatureVector1D(&fvMS);\n\t\tDestroyImage(&img);\n\t}\n\tfprintf(stderr,\"\\n\");\n\n\treturn 0;\n}\n"},{"alpha_fraction":0.6238044500350952,"alphanum_fraction":0.6376195549964905,"avg_line_length":23.102563858032227,"blob_id":"8f555ac62b0b9bf7aa6ea5537272da24455c6189","content_id":"64a10c4fb9cc22fc013002fbe075d6ad892161ef","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":941,"license_type":"permissive","max_line_length":76,"num_lines":39,"path":"/convert_mpeg_pgm.py","repo_name":"RQuispeC/mo805-assignment7","src_encoding":"UTF-8","text":"from PIL import Image\nimport numpy as np\nimport os\nimport os.path as osp\n\ndef to_string(x):\n\treturn [str(i) for i in x]\n\ndef check_binary(x):\n\tfor pixel in x:\n\t\tif pixel != \"0\" and pixel != \"1\":\n\t\t\tprint(\"ERROR\")\n\t\t\treturn\n\ndef convert_numpy_str(x):\n\tstr_x = to_string(x)\n\tcheck_binary(str_x)\n\tans = \" \".join(str_x)\n\treturn ans\n\ndef convert_image_pgm(img, file_path):\n\timg = np.array(img)\n\timg = img // np.max(img)\n\tfile = open(file_path, \"w\")\n\tfile.write(\"P2\\n\")\n\tfile.write(\"{} {}\\n\".format(img.shape[1], img.shape[0]))\n\tfile.write(\"1\\n\")\n\tfor l in img:\n\t\tfile.write(convert_numpy_str(l)+\" \\n\")\n\tfile.close()\n\nif __name__ == '__main__':\n\tfile_names = os.listdir(\"mpeg7/\")\n\tfor file_name in file_names:\n\t\timg = Image.open(osp.join(\"mpeg7/\", file_name))\n\t\tprint(\"Converting \", file_name)\n\t\tout_file_name = file_name[:-3] + \"pgm\"\n\t\tout_dir = osp.join(\"MO445-descriptors/examples/mpeg7_pgm/\", out_file_name)\n\t\tconvert_image_pgm(img, out_dir)\n\n"},{"alpha_fraction":0.4759206771850586,"alphanum_fraction":0.5722379684448242,"avg_line_length":15.571428298950195,"blob_id":"283275dbcac9add0090c21817039915bdf658146","content_id":"f809368cd2a2213890e1b388059a1db11ddd3756","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Makefile","length_bytes":353,"license_type":"permissive","max_line_length":46,"num_lines":21,"path":"/MO445-descriptors/Makefile","repo_name":"RQuispeC/mo805-assignment7","src_encoding":"UTF-8","text":"LIB=./lib\nINCLUDE=./include\nSRC=./src\nOBJ=./obj\nFLAGS= -O3 -Wall\n\nlibMO445: $(LIB)/libMO445.a\n\techo \"libMO445.a built...\"\n\n$(LIB)/libMO445.a: \\\n$(OBJ)/MO445.o \\\n\n\tar csr $(LIB)/libMO445.a \\\n$(OBJ)/MO445.o \\\n\n$(OBJ)/MO445.o: $(SRC)/MO445.c\n\tgcc $(FLAGS) -c $(SRC)/MO445.c -I$(INCLUDE) \\\n\t-o $(OBJ)/MO445.o\n\nclean: \n\trm $(LIB)/lib*.a; rm $(OBJ)/*.o\n\n\n\n\n\n"},{"alpha_fraction":0.5110331773757935,"alphanum_fraction":0.5371482968330383,"avg_line_length":20.825843811035156,"blob_id":"af40a8a3fccf703da8d6f73a316e4bc3f922f025","content_id":"3afcb9e1b54d1ee03943ed29a89c8ec9c480f514","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"C","length_bytes":101514,"license_type":"permissive","max_line_length":106,"num_lines":4651,"path":"/MO445-descriptors/src/MO445.c","repo_name":"RQuispeC/mo805-assignment7","src_encoding":"UTF-8","text":"#include \"MO445.h\"\n\n/* Common operations functions ************************/\nint NCFgets(char *s, int m, FILE *f) {\n while(fgets(s,m,f)!=NULL)\n if (s[0]!='#') return 1;\n return 0;\n}\n\nint *AllocIntArray(int n)\n{\n int *v=NULL;\n v = (int *) calloc(n,sizeof(int));\n if (v == NULL)\n Error(MSG1,\"AllocIntArray\");\n return(v);\n}\n\nfloat *AllocFloatArray(int n)\n{\n float *v=NULL;\n v = (float *) calloc(n,sizeof(float));\n if (v == NULL)\n Error(MSG1,\"AllocFloatArray\");\n return(v);\n}\n\ndouble *AllocDoubleArray(int n)\n{\n double *v=NULL;\n v = (double *) calloc(n,sizeof(double));\n if (v == NULL)\n Error(MSG1,\"AllocDoubleArray\");\n return(v);\n}\n\nchar *AllocCharArray(int n)\n{\n char *v=NULL;\n v = (char *) calloc(n,sizeof(char));\n if (v == NULL)\n Error(MSG1,\"AllocCharArray\");\n return(v);\n}\n\n/* Errors functions *********************************/\nvoid Error(char *msg,char *func){ \n fprintf(stderr,\"Error:%s in %s\\n\",msg,func);\n exit(-1);\n}\n\n/*Working with images *****************************/\n/* pgm images */\nImage *CreateImage(int ncols, int nrows)\n{\n Image *img=NULL;\n int i;\n\n img = (Image *) calloc(1,sizeof(Image));\n if (img == NULL){\n Error(MSG1,\"CreateImage\");\n }\n\n img->val = AllocIntArray(nrows*ncols);\n img->tbrow = AllocIntArray(nrows);\n\n img->tbrow[0]=0;\n for (i=1; i < nrows; i++)\n img->tbrow[i]=img->tbrow[i-1]+ncols;\n img->ncols = ncols;\n img->nrows = nrows;\n \n return(img);\n}\n\nvoid DestroyImage(Image **img){\n Image *aux;\n\n aux = *img;\n if(aux != NULL){\n if (aux->val != NULL) free(aux->val); \n if (aux->tbrow != NULL) free(aux->tbrow);\n free(aux); \n *img = NULL;\n }\n}\n\nImage *ReadImage(char *filename)\n{\n FILE *fp=NULL;\n unsigned char *value=NULL;\n char type[10];\n int i,ncols,nrows,n;\n Image *img=NULL;\n char z[256];\n\n fp = fopen(filename,\"rb\");\n if (fp == NULL){\n fprintf(stderr,\"Cannot open %s\\n\",filename);\n exit(-1);\n }\n fscanf(fp,\"%s\\n\",type);\n if((strcmp(type,\"P5\")==0)){\n NCFgets(z,255,fp);\n sscanf(z,\"%d %d\\n\",&ncols,&nrows);\n n = ncols*nrows;\n NCFgets(z,255,fp);\n sscanf(z,\"%d\\n\",&i);\n value = (unsigned char *)calloc(n,sizeof(unsigned char));\n if (value != NULL){\n fread(value,sizeof(unsigned char),n,fp);\n }else{\n fprintf(stderr,\"Insufficient memory in ReadImage\\n\");\n exit(-1);\n }\n fclose(fp);\n img = CreateImage(ncols,nrows);\n for (i=0; i < n; i++)\n img->val[i]=(int)value[i];\n free(value);\n }else{\n if((strcmp(type,\"P2\")==0)){\n NCFgets(z,255,fp);\n sscanf(z,\"%d %d\\n\",&ncols,&nrows);\n n = ncols*nrows;\n NCFgets(z,255,fp);\n sscanf(z,\"%d\\n\",&i);\n img = CreateImage(ncols,nrows);\n for (i=0; i < n; i++)\n\tfscanf(fp,\"%d\",&img->val[i]);\n fclose(fp);\n }else{\n fprintf(stderr,\"Input image must be P2 or P5\\n\");\n exit(-1);\n }\n }\n\n return(img);\n}\n\nImage *MBB(Image *img)\n{\n int x,y;\n Pixel left,right;\n Image *mbb=NULL;\n \n left.x = img->ncols-1;\n left.y = img->nrows-1;\n right.x = 0;\n right.y = 0;\n \n for (y=0; y < img->nrows; y++)\n for (x=0; x < img->ncols; x++){\n if (img->val[x+img->tbrow[y]] > 0){\n\tif (x < left.x)\n\t left.x = x;\n\tif (y < left.y)\n\t left.y = y;\n\tif (x > right.x)\n\t right.x = x;\n\tif (y > right.y)\n\t right.y = y;\t\n }\n }\n \n mbb = ROI(img,left.x,left.y,right.x,right.y);\n\n return(mbb);\t\n}\n\nImage *ROI(Image *img, int xl, int yl, int xr, int yr)\n{\n int x,y,p,i;\n Image *roi=NULL;\n \n if (ValidPixel(img,xl,yl)&&ValidPixel(img,xr,yr)&&\n (xl <= xr)&&(yl <= yr) )\n {\n roi = CreateImage(xr-xl+1,yr-yl+1);\n i=0;\n for (y=yl; y <= yr; y++)\n\tfor (x=xl; x <= xr; x++){\n\t p = x + img->tbrow[y];\n\t roi->val[i] = img->val[p];\n\t i++;\n\t}\n } \n \n return(roi);\t\n}\n\nImage *AddFrame(Image *img, int sz, int value)\n{\n Image *fimg;\n int y,*dst,*src,nbytes,offset;\n\n fimg = CreateImage(img->ncols+(2*sz),img->nrows+(2*sz));\n SetImage(fimg,value);\n nbytes = sizeof(int)*img->ncols;\n offset = sz+fimg->tbrow[sz];\n for (y=0,src=img->val,dst=fimg->val+offset; y < img->nrows;y++,src+=img->ncols,dst+=fimg->ncols){\n memcpy(dst,src,nbytes);\n }\n return(fimg);\n}\n\nvoid SetImage(Image *img, int value)\n{ \n int i,n;\n n = img->ncols*img->nrows;\n for (i=0; i < n; i++){\n img->val[i]=value;\n }\n}\n\nvoid WriteImage(Image *img,char *filename)\n{\n FILE *fp;\n int i, n, Imax;\n\n fp = fopen(filename,\"wb\");\n if (fp == NULL){\n fprintf(stderr,\"Cannot open %s\\n\",filename);\n exit(-1);\n }\n n = img->ncols*img->nrows;\n if ((Imax=MaximumValue(img))==INT_MAX){\n Warning(\"Image with infinity values\",\"WriteImage\");\n Imax = INT_MIN;\n for (i=0; i < n; i++) \n if ((img->val[i] > Imax)&&(img->val[i]!=INT_MAX))\n\tImax = img->val[i];\n fprintf(fp,\"P2\\n\");\n fprintf(fp,\"%d %d\\n\",img->ncols,img->nrows);\n fprintf(fp,\"%d\\n\",Imax+1);\n } else {\n fprintf(fp,\"P2\\n\");\n fprintf(fp,\"%d %d\\n\",img->ncols,img->nrows);\n if (Imax==0) Imax++;\n fprintf(fp,\"%d\\n\",Imax);\n }\n \n for (i=0; i < n; i++) {\n if (img->val[i]==INT_MAX)\n fprintf(fp,\"%d \",Imax+1);\n else\n fprintf(fp,\"%d \",img->val[i]);\n if (((i+1)%17) == 0)\n fprintf(fp,\"\\n\");\n }\n\n fclose(fp);\n}\n\n/* ppm images */\nCImage *CreateCImage(int ncols, int nrows)\n{\n CImage *cimg=NULL;\n int i;\n\n cimg = (CImage *) calloc(1, sizeof(CImage));\n for (i=0; i < 3; i++) \n cimg->C[i] = CreateImage(ncols,nrows);\n return(cimg);\n}\n\nvoid DestroyCImage(CImage **cimg)\n{\n CImage *tmp;\n int i;\n\n tmp = *cimg;\n if (tmp != NULL) {\n for (i=0; i < 3; i++) \n DestroyImage(&(tmp->C[i]));\n free(tmp);\n *cimg = NULL;\n }\n}\n\nCImage *ReadCImage(char *filename)\n{\n CImage *cimg=NULL;\n FILE *fp=NULL;\n char type[10];\n int i,ncols,nrows,n;\n char z[256];\n\n fp = fopen(filename,\"rb\");\n if (fp == NULL){\n fprintf(stderr,\"Cannot open %s\\n\",filename);\n exit(-1);\n }\n fscanf(fp,\"%s\\n\",type);\n if((strcmp(type,\"P6\")==0)){\n NCFgets(z,255,fp);\n sscanf(z,\"%d %d\\n\",&ncols,&nrows);\n n = ncols*nrows;\n NCFgets(z,255,fp);\n sscanf(z,\"%d\\n\",&i);\n cimg = CreateCImage(ncols,nrows);\n for (i=0; i < n; i++){\n cimg->C[0]->val[i] = fgetc(fp);\n cimg->C[1]->val[i] = fgetc(fp);\n cimg->C[2]->val[i] = fgetc(fp);\n }\n fclose(fp);\n }else{\n fprintf(stderr,\"Input image must be P6\\n\");\n exit(-1);\n }\n\n return(cimg);\n}\n\n/* auxiliary functions ****************************/\nCurve *CreateCurve(int n)\n{\n Curve *curve=NULL;\n\n curve = (Curve *) calloc(1,sizeof(Curve));\n if (curve != NULL) {\n curve->X = AllocDoubleArray(n);\n curve->Y = AllocDoubleArray(n);\n curve->n = n;\n } else {\n Error(MSG1,\"CreateCurve\");\n }\n return(curve);\n}\n\nvoid DestroyCurve(Curve **curve)\n{\n Curve *aux;\n\n aux = *curve;\n if (aux != NULL){\n if (aux->X != NULL) free(aux->X);\n if (aux->Y != NULL) free(aux->Y);\n free(aux);\n *curve = NULL;\n }\n}\n\nFeatureVector1D *CreateFeatureVector1D(int n)\n{\n FeatureVector1D *desc=NULL;\n \n desc = (FeatureVector1D *) calloc(1,sizeof(FeatureVector1D));\n if (desc != NULL) {\n desc->X = AllocDoubleArray(n);\n desc->n = n;\n } else {\n Error(MSG1,\"CreateFeatureVector\");\n }\n return(desc);\n}\n\nFeatureVector1D *CurveTo1DFeatureVector(Curve *curve){\n FeatureVector1D *fv;\n\n fv = CreateFeatureVector1D(curve->n);\n memcpy(fv->X,curve->Y,curve->n*sizeof(double));\n\n return fv;\n}\n\nFeatureVector2D *CurveTo2DFeatureVector(Curve *curve){\n FeatureVector2D *fv;\n\n fv = CreateFeatureVector2D(curve->n);\n memcpy(fv->X,curve->X,curve->n*sizeof(double));\n memcpy(fv->Y,curve->Y,curve->n*sizeof(double));\n\n return fv;\n}\n\nvoid DestroyFeatureVector1D(FeatureVector1D **desc)\n{\n FeatureVector1D *aux;\n \n aux = *desc;\n if (aux != NULL){\n if (aux->X != NULL) {\n free(aux->X);\n }\n free(aux);\n *desc = NULL;\n }\n}\n\nvoid WriteFeatureVector1D(FeatureVector1D *desc,char *filename)\n{\n FILE *fp;\n int i;\n \n fp = fopen(filename,\"w\");\n if (fp == NULL){\n fprintf(stderr,\"Cannot open %s\\n\",filename);\n exit(-1);\n }\n for (i=0; i < desc->n; i++)\n fprintf(fp,\"%f\\n\",desc->X[i]);\n \n fclose(fp);\n}\n\n\nAdjRel *CreateAdjRel(int n)\n{\n AdjRel *A=NULL;\n\n A = (AdjRel *) calloc(1,sizeof(AdjRel));\n if (A != NULL){\n A->dx = AllocIntArray(n);\n A->dy = AllocIntArray(n);\n A->n = n;\n } else {\n Error(MSG1,\"CreateAdjRel\");\n }\n\n return(A);\n}\n\nvoid DestroyAdjRel(AdjRel **A)\n{\n AdjRel *aux;\n\n aux = *A;\n if (aux != NULL){\n if (aux->dx != NULL) free(aux->dx);\n if (aux->dy != NULL) free(aux->dy);\n free(aux);\n *A = NULL;\n } \n}\n\nAdjRel *Circular(float r)\n{\n AdjRel *A=NULL;\n int i,j,k,n,dx,dy,r0,r2,d,i0=0;\n float *da,*dr,aux;\n\n n=0;\n\n r0 = (int)r;\n r2 = (int)(r*r);\n for(dy=-r0;dy<=r0;dy++)\n for(dx=-r0;dx<=r0;dx++)\n if(((dx*dx)+(dy*dy)) <= r2)\n\tn++;\n\t\n A = CreateAdjRel(n);\n i=0;\n for(dy=-r0;dy<=r0;dy++)\n for(dx=-r0;dx<=r0;dx++)\n if(((dx*dx)+(dy*dy)) <= r2){\n\tA->dx[i]=dx;\n\tA->dy[i]=dy;\n\tif ((dx==0)&&(dy==0))\n\t i0 = i;\n\ti++;\n }\n\n da = AllocFloatArray(A->n);\n dr = AllocFloatArray(A->n);\n for (i=0; i < A->n; i++) {\n dx = A->dx[i];\n dy = A->dy[i];\n dr[i] = (float)sqrt((dx*dx) + (dy*dy));\n if (i != i0){ \n da[i] = atan2(-dy,-dx)*180.0/PI;\n if (da[i] < 0.0)\n\tda[i] += 360.0;\n }\n }\n da[i0] = 0.0;\n dr[i0] = 0.0;\n\n aux = da[i0];\n da[i0] = da[0];\n da[0] = aux;\n aux = dr[i0];\n dr[i0] = dr[0];\n dr[0] = aux;\n d = A->dx[i0];\n A->dx[i0] = A->dx[0];\n A->dx[0] = d;\n d = A->dy[i0];\n A->dy[i0] = A->dy[0];\n A->dy[0] = d;\n\n for (i=1; i < A->n-1; i++){\n k = i;\n for (j=i+1; j < A->n; j++)\n if (da[j] < da[k]){\n\tk = j;\n }\n aux = da[i];\n da[i] = da[k];\n da[k] = aux;\n aux = dr[i];\n dr[i] = dr[k];\n dr[k] = aux;\n d = A->dx[i];\n A->dx[i] = A->dx[k];\n A->dx[k] = d;\n d = A->dy[i];\n A->dy[i] = A->dy[k];\n A->dy[k] = d;\n }\n\n for (i=1; i < A->n-1; i++){\n k = i;\n for (j=i+1; j < A->n; j++)\n if ((dr[j] < dr[k])&&(da[j]==da[k])){\n\tk = j;\n }\n aux = dr[i];\n dr[i] = dr[k];\n dr[k] = aux;\n d = A->dx[i];\n A->dx[i] = A->dx[k];\n A->dx[k] = d;\n d = A->dy[i];\n A->dy[i] = A->dy[k];\n A->dy[k] = d;\n }\n\n free(dr);\n free(da);\n\n return(A);\n}\n\nAdjRel *LeftSide(AdjRel *A)\n{\n AdjRel *L=NULL;\n int i;\n float d;\n\n L = CreateAdjRel(A->n);\n for (i=0; i < L->n; i++){\n d = sqrt(A->dx[i]*A->dx[i] + A->dy[i]*A->dy[i]);\n if (d != 0){\n L->dx[i] = ROUND(((float)A->dx[i]/2.0)+((float)A->dy[i]/d));\n L->dy[i] = ROUND(((float)A->dy[i]/2)-((float)A->dx[i]/d));\n }\n }\n \n return(L);\n}\n\n\nAdjRel *RightSide(AdjRel *A)\n{\n AdjRel *R=NULL;\n int i;\n float d;\n\n R = CreateAdjRel(A->n);\n for (i=0; i < R->n; i++){\n d = sqrt(A->dx[i]*A->dx[i] + A->dy[i]*A->dy[i]);\n if (d != 0){\n R->dx[i] = ROUND(((float)A->dx[i]/2.0)-((float)A->dy[i]/d));\n R->dy[i] = ROUND(((float)A->dx[i]/d)+((float)A->dy[i]/2.0));\n }\n }\n\n return(R);\n}\n\nbool ValidContPoint(Image *bin, AdjRel *L, AdjRel *R, int p)\n{\n int i,q,n,left,right;\n Pixel u,v,l,r;\n bool found=false;\n\n u.x = p%bin->ncols;\n u.y = p/bin->ncols;\n n = L->n;\n\n for (i=0; i < n; i++) {\n v.x = u.x + L->dx[i];\n v.y = u.y + L->dy[i];\n if (ValidPixel(bin,v.x,v.y)){\n q = v.x + bin->tbrow[v.y];\n if ((bin->val[q]==1)&&(p!=q)){\n\tl.x = u.x + L->dx[i]; \n\tl.y = u.y + L->dy[i];\n\tr.x = u.x + R->dx[i]; \n\tr.y = u.y + R->dy[i];\t\n\tif (ValidPixel(bin,l.x,l.y))\n\t left = l.x + bin->tbrow[l.y];\n\telse\n\t left = -1;\n\tif (ValidPixel(bin,r.x,r.y))\n\t right = r.x + bin->tbrow[r.y];\n\telse\n\t right = -1;\n\tif (((left!=-1)&&(right!=-1)&&(bin->val[left]!=bin->val[right]))||\n\t ((left==-1)&&(right!=-1)&&(bin->val[right]==1)) ||\n\t ((right==-1)&&(left!=-1)&&(bin->val[left]==1))){\n\t found = true;\n\t break;\n\t}\n }\n }\n }\n \n return(found);\n}\n\nbool ValidPixel(Image *img, int x, int y)\n{\n if ((x >= 0)&&(x < img->ncols)&&\n (y >= 0)&&(y < img->nrows))\n return(true);\n else\n return(false);\n}\n\nImage *LabelContPixel(Image *bin)\n{\n Image *bndr=NULL;\n Image *color=NULL,*pred=NULL,*label=NULL;\n int p=0,q,r,i,j,n,left=0,right=0,*LIFO,last,l;\n AdjRel *A,*L,*R;\n Pixel u,v,w;\n \n A = Circular(1.0);\n n = bin->ncols*bin->nrows;\n bndr = CreateImage(bin->ncols,bin->nrows);\n for (p=0; p < n; p++){\n if (bin->val[p]==1){\n u.x = p%bin->ncols;\n u.y = p/bin->ncols;\n for (i=1; i < A->n; i++){\n\tv.x = u.x + A->dx[i];\n\tv.y = u.y + A->dy[i];\n\tif (ValidPixel(bin,v.x,v.y)){\n\t q = v.x + bin->tbrow[v.y];\n\t if (bin->val[q]==0){\n\t bndr->val[p]=1;\n\t break;\n\t }\n\t} else {\n\t bndr->val[p]=1;\n\t break;\n\t}\n }\n }\n } \n DestroyAdjRel(&A);\n\n A = Circular(1.5);\n L = LeftSide(A);\n R = RightSide(A);\n label = CreateImage(bndr->ncols,bndr->nrows);\n color = CreateImage(bndr->ncols,bndr->nrows);\n pred = CreateImage(bndr->ncols,bndr->nrows);\n n = bndr->ncols*bndr->nrows;\n LIFO = AllocIntArray(n);\n last = NIL;\n for (j=0; j < n; j++){\n if ((bndr->val[j]==1)\n\t&&(color->val[j]!=BLACK)\n\t&&ValidContPoint(bin,L,R,j)){\n last++;\n LIFO[last] = j;\n color->val[j] = GRAY;\n pred->val[j] = j;\n while(last != NIL){\n\tp = LIFO[last]; last--;\t\n\tcolor->val[p]=BLACK;\n\tu.x = p%bndr->ncols;\n\tu.y = p/bndr->ncols;\n\tfor (i=1; i < A->n; i++){\n\t v.x = u.x + A->dx[i];\n\t v.y = u.y + A->dy[i];\n\t if (ValidPixel(bndr,v.x,v.y)){\n\t q = v.x + bndr->tbrow[v.y];\n\t if ((q==j)&&(pred->val[p]!=j)){\n\t last = NIL;\n\t break;\n\t }\n\t \n\t w.x = u.x + L->dx[i]; \n\t w.y = u.y + L->dy[i];\n\t if (ValidPixel(bndr,w.x,w.y))\n\t left = w.x + bndr->tbrow[w.y];\n\t else\n\t left = -1;\n\t w.x = u.x + R->dx[i]; \n\t w.y = u.y + R->dy[i];\n\t if (ValidPixel(bndr,w.x,w.y))\n\t right = w.x + bndr->tbrow[w.y];\n\t else\n\t right = -1;\n\t \n\t if ((bndr->val[q]==1)&&\n\t\t(color->val[q] != BLACK)&&\n\t\t(((left!=-1)&&(right!=-1)&&(bin->val[left]!=bin->val[right]))||\n\t\t ((left==-1)&&(right!=-1)&&(bin->val[right]==1)) ||\n\t\t ((right==-1)&&(left!=-1)&&(bin->val[left]==1)))){ \n\t pred->val[q] = p;\n\t if (color->val[q] == WHITE){\n\t\tlast++;\n\t\tLIFO[last] = q;\n\t\tcolor->val[q]=GRAY;\n\t }\n\t } \n\t }\n\t}\t\n }\n r = p;\n l = 1;\n while(pred->val[p]!=p){\n\tlabel->val[p] = l;\n\tp = pred->val[p];\n\tl++;\n }\n if (r != p) {\n\tlabel->val[p] = l;\n }\n }\n }\n\n DestroyAdjRel(&A);\n DestroyAdjRel(&L);\n DestroyAdjRel(&R);\n DestroyImage(&bndr);\n DestroyImage(&color);\n DestroyImage(&pred);\n free(LIFO);\n return(label);\n}\n\nCurve3D *CreateCurve3D(int n)\n{\n Curve3D *curve=NULL;\n\n curve = (Curve3D *) calloc(1,sizeof(Curve3D));\n if (curve != NULL) {\n curve->X = AllocDoubleArray(n);\n curve->Y = AllocDoubleArray(n);\n curve->Z = AllocDoubleArray(n);\n curve->n = n;\n } else {\n Error(MSG1,\"CreateCurve3D\");\n }\n return(curve);\n}\n\nvoid DestroyCurve3D(Curve3D **curve)\n{\n Curve3D *aux;\n\n aux = *curve;\n if (aux != NULL){\n if (aux->X != NULL) free(aux->X);\n if (aux->Y != NULL) free(aux->Y);\n if (aux->Z != NULL) free(aux->Z);\n free(aux);\n *curve = NULL;\n }\n}\n\nvoid SortCurve3D(Curve3D *curve, int left, int right, char order)\n{\n int pivot;\n \n if (left < right) {\n pivot = PartCurve3D(curve,left,right,order);\n SortCurve3D(curve,left,pivot-1,order);\n SortCurve3D(curve,pivot+1,right,order); \n }\n}\n\nint PartCurve3D (Curve3D *curve, int left, int right, char order)\n{\n double z;\n int i;\n double X,Y,Z;\n \n z = curve->Z[left];\n i = left;\n \n do {\n if (order == INCREASING){\n while ((curve->Z[left] <= z)&&(left <= right)) left++;\n while (curve->Z[right] > z) right--;\n } else { /* order = DECREASING */\n while ((curve->Z[left] >= z)&&(left <= right)) left++;\n while (curve->Z[right] < z) right--;\n }\n if (left < right){\n X = curve->X[left];\n Y = curve->Y[left];\n Z = curve->Z[left];\n curve->X[left] = curve->X[right];\n curve->Y[left] = curve->Y[right];\n curve->Z[left] = curve->Z[right];\n curve->X[right] = X;\n curve->Y[right] = Y;\n curve->Z[right] = Z;\n left++; right--;\n }\n } while (left <= right);\n\n left = i;\n\n if (left != right){\n X = curve->X[left];\n Y = curve->Y[left];\n Z = curve->Z[left];\n curve->X[left] = curve->X[right];\n curve->Y[left] = curve->Y[right];\n curve->Z[left] = curve->Z[right];\n curve->X[right] = X;\n curve->Y[right] = Y;\n curve->Z[right] = Z;\n }\n\n return (right);\n}\n\nint FFT(int dir, long nn, double *x, double *y)\n{\n int m;\n long i,i1,j,k,i2,l,l1,l2;\n double c1,c2,tx,ty,t1,t2,u1,u2,z;\n\n m = (int)(log(nn)/log(2)+.00001);\n \n i2 = nn >> 1;\n j = 0;\n for (i=0;i>= 1;\n }\n j += k;\n }\n\n c1 = -1.0;\n c2 = 0.0;\n l2 = 1;\n for (l=0;lncols*bin->nrows;\n bndr = CreateImage(bin->ncols,bin->nrows);\n for (p=0; p < n; p++){\n if (bin->val[p]==1){\n\t\t \n u.x = p%bin->ncols;\n u.y = p/bin->ncols;\n for (i=1; i < A->n; i++){\n\tv.x = u.x + A->dx[i];\n\tv.y = u.y + A->dy[i];\n\tif (ValidPixel(bin,v.x,v.y)){\n\t q = v.x + bin->tbrow[v.y];\n\t if (bin->val[q]==0){\n\t bndr->val[p]=1;\n\t break;\n\t }\n\t} else {\n\t bndr->val[p]=1;\n\t break;\n\t}\n }\n }\n }\n DestroyAdjRel(&A);\n\n A = Circular(1.5);\n L = LeftSide(A);\n R = RightSide(A);\n label = CreateImage(bndr->ncols,bndr->nrows);\n color = CreateImage(bndr->ncols,bndr->nrows);\n pred = CreateImage(bndr->ncols,bndr->nrows);\n LIFO = AllocIntArray(n);\n last = NIL;\n for (j=0; j < n; j++){\n if ((bndr->val[j]==1)&&\n\t(color->val[j]!=BLACK)&&\n\tValidContPoint(bin,L,R,j)){ \n last++; LIFO[last] = j;\n color->val[j] = GRAY;\n pred->val[j] = j;\n while(last != NIL){\n\tp = LIFO[last];\tlast--;\t\n\tcolor->val[p]=BLACK;\n\tu.x = p%bndr->ncols;\n\tu.y = p/bndr->ncols;\n\tfor (i=1; i < A->n; i++){\n\t v.x = u.x + A->dx[i];\n\t v.y = u.y + A->dy[i];\n\t if (ValidPixel(bndr,v.x,v.y)){\n\t q = v.x + bndr->tbrow[v.y];\n\t if ((q==j)&&(pred->val[p]!=j)){\n\t last = NIL;\n\t break;\n\t }\n\t w.x = u.x + L->dx[i]; \n\t w.y = u.y + L->dy[i];\n\t if (ValidPixel(bndr,w.x,w.y))\n\t left = w.x + bndr->tbrow[w.y];\n\t else\n\t left = -1;\n\t w.x = u.x + R->dx[i]; \n\t w.y = u.y + R->dy[i];\n\t if (ValidPixel(bndr,w.x,w.y))\n\t right = w.x + bndr->tbrow[w.y];\n\t else\n\t right = -1;\n\t \n\t if ((bndr->val[q]==1)&&\n\t\t(color->val[q] != BLACK)&&\n\t\t(((left!=-1)&&(right!=-1)&&(bin->val[left]!=bin->val[right]))||\n\t\t ((left==-1)&&(right!=-1)&&(bin->val[right]==1)) ||\n\t\t ((right==-1)&&(left!=-1)&&(bin->val[left]==1))) ) {\n\t pred->val[q] = p;\n\t if (color->val[q] == WHITE){\n\t\tlast++; LIFO[last] = q;\n\t\tcolor->val[q]=GRAY;\n\t }\n\t } \n\t }\n\t}\t\n }\n r = p;\n while(pred->val[p]!=p){\n\tlabel->val[p] = l;\n\tp = pred->val[p];\n } \n if (r != p){ \n\tlabel->val[p] = l;\n\tl++;\n }\n }\n }\n\n DestroyAdjRel(&A);\n DestroyAdjRel(&L);\n DestroyAdjRel(&R);\n DestroyImage(&bndr);\n DestroyImage(&color);\n DestroyImage(&pred);\n free(LIFO);\n return(label);\n}\n\nvoid Warning(char *msg,char *func){ \n fprintf(stdout,\"Warning:%s in %s\\n\",msg,func);\n}\n\nImage *Scale(Image *img, float Sx, float Sy) \n{\n float S[2][2],x,y,d1,d2,d3,d4,Ix1,Ix2,If;\n Image *scl;\n Pixel u,v,prev,next;\n \n if (Sx == 0.0) Sx = 1.0;\n if (Sy == 0.0) Sy = 1.0;\n\n S[0][0] = 1.0/Sx;\n S[0][1] = 0;\n S[1][0] = 0;\n S[1][1] = 1.0/Sy;\n\n scl = CreateImage((int)(img->ncols*fabs(Sx) + 0.5),(int)(img->nrows*fabs(Sy) + 0.5)); \n\n for (v.y=0; v.y < scl->nrows; v.y++)\n for (v.x=0; v.x < scl->ncols; v.x++){\n x = ((v.x-scl->ncols/2.)*S[0][0] + (v.y-scl->nrows/2.)*S[0][1]) \n\t+ img->ncols/2.;\n y = ((v.x-scl->ncols/2.)*S[1][0] + (v.y-scl->nrows/2.)*S[1][1]) \n\t+ img->nrows/2.;\n u.x = (int)(x+0.5);\n u.y = (int)(y+0.5);\n if (ValidPixel(img,u.x,u.y)){\n\tif (x < u.x) {\n\t next.x = u.x;\n\t prev.x = u.x - 1;\n\t} else {\n\t next.x = u.x + 1;\n\t prev.x = u.x;\n\t}\n\td1 = next.x - x;\n\td2 = x - prev.x;\n\tif (y < u.y) {\n\t next.y = u.y;\n\t prev.y = u.y - 1;\n\t} else {\n\t next.y = u.y + 1;\n\t prev.y = u.y;\n\t}\n\td3 = next.y - y;\n\td4 = y - prev.y;\n\n\tif (ValidPixel(img,prev.x,prev.y)&&ValidPixel(img,next.x,prev.y))\n\t Ix1 = d1*img->val[prev.x+img->tbrow[prev.y]] + \n\t d2*img->val[next.x+img->tbrow[prev.y]];\n\telse\n\t Ix1 = img->val[u.x+img->tbrow[u.y]];\n\n\tif (ValidPixel(img,prev.x,next.y)&&ValidPixel(img,next.x,next.y))\n\t Ix2 = d1*img->val[prev.x+img->tbrow[next.y]] + \n\t d2*img->val[next.x+img->tbrow[next.y]];\n\telse\n\t Ix2 = img->val[u.x+img->tbrow[u.y]];\n\t\n\tIf = d3*Ix1 + d4*Ix2;\n\n\tscl->val[v.x+scl->tbrow[v.y]] = (int)If;\n }\n }\n \n return(scl);\n}\n\nDImage *CreateDImage(int ncols, int nrows)\n{\n DImage *dimg=NULL;\n int i;\n\n dimg = (DImage *) calloc(1,sizeof(DImage));\n if (dimg == NULL){\n Error(MSG1,\"CreateDImage\");\n }\n\n dimg->val = AllocDoubleArray(nrows*ncols);\n dimg->tbrow = AllocIntArray(nrows);\n\n dimg->tbrow[0]=0;\n for (i=1; i < nrows; i++)\n dimg->tbrow[i]=dimg->tbrow[i-1]+ncols;\n dimg->ncols = ncols;\n dimg->nrows = nrows;\n \n return(dimg);\n}\n\nvoid DestroyDImage(DImage **dimg)\n{\n DImage *aux;\n\n aux = *dimg;\n if(aux != NULL){\n if (aux->val != NULL) free(aux->val); \n if (aux->tbrow != NULL) free(aux->tbrow);\n free(aux); \n *dimg = NULL;\n }\n}\n\nImage *CopyImage(Image *img)\n{\n Image *imgc;\n\n imgc = CreateImage(img->ncols,img->nrows);\n memcpy(imgc->val,img->val,img->ncols*img->nrows*sizeof(int));\n \n return(imgc);\n}\n\nint MaximumValue(Image *img)\n{\n unsigned int i, n, r;\n int max;\n\n max = img->val[0];\n n = img->ncols*img->nrows - 1;\n r = n%4;\n n -= r;\n for (i=1; i < n; i+=4) {\n if (img->val[i] > max)\n max = img->val[i];\n if (img->val[i+1] > max)\n max = img->val[i+1];\n if (img->val[i+2] > max)\n max = img->val[i+2];\n if (img->val[i+3] > max)\n max = img->val[i+3];\n }\n while (r != 0) {\n if (img->val[i+r-1] > max)\n max = img->val[i+r-1];\n --r;\n }\n\n return(max);\n}\n\nQueue *CreateQueue(int nbuckets, int nelems)\n{\n Queue *Q=NULL;\n\n Q = (Queue *) malloc(1*sizeof(Queue));\n \n if (Q != NULL) {\n Q->C.first = (int *)malloc(nbuckets * sizeof(int));\n Q->C.last = (int *)malloc(nbuckets * sizeof(int));\n Q->C.nbuckets = nbuckets;\n if ( (Q->C.first != NULL) && (Q->C.last != NULL) ){\n Q->L.elem = (Node *)malloc(nelems*sizeof(Node));\n Q->L.nelems = nelems;\n if (Q->L.elem != NULL){\n\tResetQueue(Q);\n } else\n\tError(MSG1,\"CreateQueue\");\t\n } else\n Error(MSG1,\"CreateQueue\");\n } else \n Error(MSG1,\"CreateQueue\");\n \n return(Q);\n}\n\nvoid DestroyQueue(Queue **Q)\n{\n Queue *aux;\n\n aux = *Q;\n if (aux != NULL) {\n if (aux->C.first != NULL) free(aux->C.first);\n if (aux->C.last != NULL) free(aux->C.last);\n if (aux->L.elem != NULL) free(aux->L.elem);\n free(aux);\n *Q = NULL;\n }\n}\n\nvoid InsertQueue(Queue *Q, int bucket, int elem)\n{\n if (Q->C.first[bucket] == NIL){ \n Q->C.first[bucket] = elem; \n Q->L.elem[elem].prev = NIL;\n }else {\n Q->L.elem[Q->C.last[bucket]].next = elem;\n Q->L.elem[elem].prev = Q->C.last[bucket];\n }\n \n Q->C.last[bucket] = elem;\n Q->L.elem[elem].next = NIL;\n Q->L.elem[elem].color = GRAY;\n}\n\nint RemoveQueue(Queue *Q)\n{\n int elem=NIL, next, prev;\n int last;\n\n /** moves to next element or returns EMPTY queue **/\n if (Q->C.first[Q->C.current] == NIL) {\n last = Q->C.current;\n \n Q->C.current = (Q->C.current + 1) % (Q->C.nbuckets);\n \n while ((Q->C.first[Q->C.current] == NIL) && (Q->C.current != last)) {\n Q->C.current = (Q->C.current + 1) % (Q->C.nbuckets);\n }\n \n if (Q->C.first[Q->C.current] == NIL)\n return NIL;\n }\n\n if (Q->C.tiebreak == LIFOBREAK) {\n elem = Q->C.last[Q->C.current];\n \n prev = Q->L.elem[elem].prev;\n if (prev == NIL) { /* there was a single element in the list */\n Q->C.last[Q->C.current] = Q->C.first[Q->C.current] = NIL; \n }\n else {\n Q->C.last[Q->C.current] = prev;\n Q->L.elem[prev].next = NIL;\n }\n } else { /* Assume FIFO policy for breaking ties */\n elem = Q->C.first[Q->C.current];\n \n next = Q->L.elem[elem].next;\n if (next == NIL) { /* there was a single element in the list */\n Q->C.first[Q->C.current] = Q->C.last[Q->C.current] = NIL; \n }\n else {\n Q->C.first[Q->C.current] = next;\n Q->L.elem[next].prev = NIL;\n }\n }\n\n Q->L.elem[elem].color = BLACK;\n\n return elem;\n}\n\nvoid UpdateQueue(Queue *Q, int elem, int from, int to)\n{\n RemoveQueueElem(Q, elem, from);\n InsertQueue(Q, to, elem);\n}\n\nint EmptyQueue(Queue *Q)\n{\n int last;\n if (Q->C.first[Q->C.current] != NIL)\n return 0;\n \n last = Q->C.current;\n \n Q->C.current = (Q->C.current + 1) % (Q->C.nbuckets);\n \n while ((Q->C.first[Q->C.current] == NIL) && (Q->C.current != last)) {\n Q->C.current = (Q->C.current + 1) % (Q->C.nbuckets); \n }\n \n return (Q->C.first[Q->C.current] == NIL);\n}\n\nvoid ResetQueue(Queue *Q)\n{\n unsigned int i;\n\n Q->C.current = 0;\n SetTieBreak(Q,FIFOBREAK);\n#if defined(__i386__) && (NIL==-1 || NIL==0)\n i = Q->C.nbuckets*sizeof(int);\n memset(Q->C.first, NIL, i);\n memset(Q->C.last, NIL, i);\n memset(Q->L.elem, NIL, Q->L.nelems*sizeof(Node));\n for (i=0; iL.nelems; ++i)\n Q->L.elem[i].color = WHITE;\n#else\n for (i=0; i < Q->C.nbuckets; ++i)\n Q->C.first[i]=Q->C.last[i]=NIL;\n for (i=0; i < Q->L.nelems; ++i) {\n Q->L.elem[i].next = Q->L.elem[i].prev = NIL;\n Q->L.elem[i].color = WHITE;\n }\n#endif\n}\n\nvoid RemoveQueueElem(Queue *Q, int elem, int bucket)\n{\n int prev,next;\n\n prev = Q->L.elem[elem].prev;\n next = Q->L.elem[elem].next;\n \n /* if elem is the first element */\n if (Q->C.first[bucket] == elem) {\n Q->C.first[bucket] = next;\n if (next == NIL) /* elem is also the last one */\n Q->C.last[bucket] = NIL;\n else\n Q->L.elem[next].prev = NIL;\n }\n else{ /* elem is in the middle or it is the last */\n Q->L.elem[prev].next = next;\n if (next == NIL) /* if it is the last */\n Q->C.last[bucket] = prev;\n else \n Q->L.elem[next].prev = prev;\n }\n\n Q->L.elem[elem].color = BLACK;\n}\n\nCurve *SamplePolynom(Polynom *P, double from, double to, int nbins)\n{\n Curve *curve=NULL;\n double x = from,val;\n double inc = (to-from)/nbins;\n int i,p;\n \n if ((from <= to)&&(nbins > 0)) {\n curve = CreateCurve(nbins);\n for (p=0; p < nbins; p++){\n val=0.0;\n for (i=0; i <= P->n; i++)\n\tval += pow(x,i)*P->coef[i];\n curve->X[p] = x;\n curve->Y[p] = val;\n x +=inc;\n }\n }\n return(curve);\n}\n\nPolynom *CreatePolynom(int degree)\n{\n Polynom *P=NULL;\n\n P = (Polynom *) calloc(1,sizeof(Polynom)); \n P->coef = AllocDoubleArray(degree + 1);\n P->n = degree;\n return(P);\n}\n\nvoid DestroyPolynom(Polynom **P)\n{\n Polynom *aux=NULL;\n\n aux = *P;\n if(aux != NULL){\n if(aux->coef != NULL) free(aux->coef);\n free(aux);\n *P = NULL;\n }\n}\n\nPolynom *DerivPolynom(Polynom *P)\n{\n Polynom *D;\n int i,j;\n\n D = CreatePolynom(P->n-1);\n j = 0;\n for (i=1; i <= P->n; i++){\n D->coef[j] = i*P->coef[i];\n j++;\n }\n return(D);\n}\n\n\nPolynom *Regression(Curve *curve, int degree)\n{\n Polynom *P=NULL;\n double *A=NULL,*B=NULL;\n int i,j,k;\n double sum, m;\n\n /* Compute Non-Linear System: A*P=B, where P are the coefficients of\n the polynomial */\n\n A = AllocDoubleArray((degree+1)*(degree+1));\n B = AllocDoubleArray(degree+1);\n\n for (i=1; i<= 2*degree; i++){\n sum = 0.0;\n for (k=0; k < curve->n; k++){\n sum += pow(curve->X[k], i);\n }\n if (i<=degree){\n for (j=0; j<=i; j++){ \n\tA[(i-j) + j*(degree+1)] = sum;\n }\n }\n else {\n for (j= (i-degree); j<= degree; j++){ \n\tA[(i-j) + j*(degree+1)] = sum;\n }\n }\n }\n A[0]= curve->n;\n \n for (i=0; i<=degree; i++){\n sum = 0.0;\n for (k=0; k < curve->n; k++){\n sum += pow(curve->X[k], i)*curve->Y[k];\n }\n B[i] = sum;\n }\n\n /* Gauss's Regression Method */\n\n for(k = 0; k < degree; k++){ /* Triangulation of A */\n for(i = k+1; i<= degree; i++){\n m = A[i*(degree+1)+k]/A[k*(degree+1)+k];\n A[i*(degree+1)+k] = 0.0;\n for (j = k+1; j<= degree; j++){\n\tA[i*(degree+1)+j] = A[i*(degree+1)+j] - m *A[k*(degree+1)+j];\n }\n B[i] = B[i] - m * B[k];\n }\n }\n \n P = CreatePolynom(degree);\n\n P->coef[degree] = B[degree]/A[degree*(degree+1) + degree];\n for(k=degree-1; k>=0; k--){\n sum= 0.0;\n for(j=k+1; j<=degree; j++){\n sum += A[k*(degree+1)+j]*P->coef[j];\n }\n P->coef[k] = (B[k]-sum)/A[k*(degree+1)+k];\n }\n \n free(A);\n free(B);\n \n return(P);\n}\n\nvoid DeAnnotate(AnnImg **aimg)\n{\n AnnImg *aux;\n \n aux = *aimg;\n if (aux != NULL){\n DestroyImage(&(aux->cost));\n DestroyImage(&(aux->label));\n DestroyImage(&(aux->pred));\n DestroySet(&(aux->seed));\n free(aux);\n *aimg = NULL;\n }\n}\n\nPolynom *MSFractal(Image *bin, \n\t\t int maxdist, \n\t\t int degree, \n\t\t double lower, \n\t\t double higher,\n\t\t int reg,\n\t\t double from,\n\t\t double to)\n{\n Curve *hist=NULL,*haux=NULL,*ahist=NULL, *aux_ahist=NULL,*loglog=NULL;\n AnnImg *aimg=NULL;\n AdjRel *A=NULL;\n Image *mbb=NULL,*nbin=NULL;\n Polynom *P=NULL,*D=NULL;\n int n,i,j,maxcost=maxdist*maxdist;\n \n mbb = MBB(bin);\n nbin = AddFrame(mbb,maxdist,0);\n DestroyImage(&mbb);\n\n /* Compute Euclidean IFT */\n\n A = Circular(1.5);\n aimg = Annotate(nbin,NULL,nbin);\n iftDilation(aimg, A);\n DestroyAdjRel(&A);\n\n /* Compute MS Fractal */\n\n hist = Histogram(aimg->cost);\n\n /* Compute non-zero points */\n\n n = 0;\n for (i=1; i < maxcost; i++)\n if (hist->Y[i] != 0)\n n++;\n\n haux = CreateCurve(n);\n j=0;\n for (i=1; i < maxcost; i++)\n if (hist->Y[i] != 0){\n haux->X[j] = log(sqrt((double)i));\n haux->Y[j] = hist->Y[i];\n j++;\n }\n \n /* Accumulate values */\n ahist = CreateCurve(n);\n ahist->X[0] = haux->X[0];\n ahist->Y[0] = haux->Y[0];\n for (i=1; i < n; i++) {\n ahist->X[i] = haux->X[i];\n ahist->Y[i] = ahist->Y[i-1] + haux->Y[i];\n }\n\n /* Compute log(Y) */\n for (i=0; i < n; i++)\n ahist->Y[i] = log((double)ahist->Y[i]);\n \n j=0;\n \n for (i=0; i < n; i++)\n if ((ahist->X[i]>from)&&((ahist->X[i]X[i]>from)&&((ahist->X[i]X[j] = ahist->X[i];\n aux_ahist->Y[j] = ahist->Y[i];\n j++;\n }\n \n \n /* Compute Regression */\n P = Regression(/*ahist*/aux_ahist,degree);\n \n /* Print loglog curve */\n if (reg){\n loglog = SamplePolynom(P,lower, higher, 100);\n }\n \n /* Compute Fractal Curve */\n D = DerivPolynom(P); \n\n DestroyCurve(&hist);\n DestroyCurve(&haux);\n DestroyCurve(&ahist);\n DestroyCurve(&aux_ahist);\n DestroyCurve(&loglog);\n DestroyPolynom(&P);\n DeAnnotate(&aimg);\n DestroyImage(&nbin);\n return(D);\n}\n\nAnnImg *Annotate(Image *img, Image *cost, Image *label)\n{\n AnnImg *aimg=NULL;\n int p,n;\n\n aimg = (AnnImg *) calloc(1,sizeof(AnnImg));\n if (aimg == NULL)\n Error(MSG1,\"Annotate\");\n\n aimg->img = img;\n aimg->cost = CreateImage(img->ncols,img->nrows); \n aimg->label = CreateImage(img->ncols,img->nrows);\n aimg->pred = CreateImage(img->ncols,img->nrows);\n aimg->root = NULL;\n aimg->seed = NULL;\n\n n = img->ncols*img->nrows;\n\n if ((cost == NULL)&&(label == NULL))\n for (p=0; p < n; p++){\n aimg->cost->val[p] = INT_MAX;\n aimg->label->val[p] = 0;\n aimg->pred->val[p] = p;\n }\n else\n if ((cost == NULL)&&(label != NULL))\n for (p=0; p < n; p++){\n\taimg->pred->val[p] = p;\n\tif (label->val[p] > 0) {\n\t aimg->cost->val[p] = 0;\n\t aimg->label->val[p] = label->val[p];\n\t InsertSet(&(aimg->seed),p);\n\t} else {\n\t aimg->cost->val[p] = INT_MAX;\n\t aimg->label->val[p] = 0;\n\t}\n }\n else\n if ((cost != NULL)&&(label == NULL))\n\tfor (p=0; p < n; p++){\n\t aimg->cost->val[p] = cost->val[p];\n\t aimg->label->val[p] = p;\n\t aimg->pred->val[p] = p;\n\t InsertSet(&(aimg->seed),p);\n\t}\n else\n\tif ((cost != NULL)&&(label != NULL))\t\n\t for (p=0; p < n; p++){\n\t aimg->pred->val[p] = p;\n\t aimg->label->val[p] = label->val[p];\n\t if (label->val[p] > 0) {\n\t aimg->cost->val[p] = cost->val[p];\n\t InsertSet(&(aimg->seed),p);\n\t } else { \n\t aimg->cost->val[p] = INT_MAX;\n\t }\n\t }\n \n return(aimg);\n}\n\nvoid InsertSet(Set **S, int elem)\n{\n Set *p=NULL;\n\n p = (Set *) calloc(1,sizeof(Set));\n if (p == NULL) Error(MSG1,\"InsertSet\");\n if (*S == NULL){\n p->elem = elem;\n p->next = NULL;\n }else{\n p->elem = elem;\n p->next = *S;\n }\n *S = p;\n}\n\nint RemoveSet(Set **S)\n{\n Set *p;\n int elem=NIL;\n \n if (*S != NULL){\n p = *S;\n elem = p->elem;\n *S = p->next;\n //printf(\"RemoveSet before free\");\n free(p);\n //printf(\" RemoveSet after free: elem is %d\\n\",elem);\n //if(*S != NULL) printf(\" *S->elem is %d\\n\",(*S)->elem);\n }\n return(elem);\n}\n\nvoid DestroySet(Set **S)\n{\n Set *p;\n while(*S != NULL){\n p = *S;\n *S = p->next;\n free(p);\n }\n}\n\nint FrameSize(AdjRel *A)\n{\n int sz=INT_MIN,i=0;\n\n for (i=0; i < A->n; i++){\n if (fabs(A->dx[i]) > sz) \n sz = fabs(A->dx[i]);\n if (fabs(A->dy[i]) > sz) \n sz = fabs(A->dy[i]);\n }\n return(sz);\n}\n\nAdjRel *ComplAdj(AdjRel *A1, AdjRel *A2)\n{\n AdjRel *A;\n int i,j,n;\n char *subset=NULL;\n\n if (A1->n > A2->n){\n A = A1;\n A1 = A2;\n A2 = A;\n }\n\n A = NULL;\n subset = AllocCharArray(A2->n);\n n = 0;\n for (i=0; i < A1->n; i++) \n for (j=0; j < A2->n; j++)\n if ((A1->dx[i]==A2->dx[j])&&(A1->dy[i]==A2->dy[j])){\t \n\tsubset[j] = 1;\n\tn++;\n\tbreak;\n }\n n = A2->n - n;\n \n if (n == 0) /* A1 == A2 */ \n return(NULL);\n\n A = CreateAdjRel(n);\n j=0;\n for (i=0; i < A2->n; i++) \n if (subset[i] == 0){\n A->dx[j] = A2->dx[i];\n A->dy[j] = A2->dy[i];\n j++;\n }\n\n free(subset);\n\n return(A);\n}\n\nHeap *CreateHeap(int n, int *cost){\n Heap *H=NULL;\n int i;\n\n if (cost == NULL){\n Warning(\"Cannot create heap without cost map\",\"CreateHeap\");\n return(NULL);\n }\n\n H = (Heap *) calloc(1,sizeof(Heap));\n if (H != NULL) {\n H->n = n;\n H->cost = cost;\n H->color = (char *) calloc(n,sizeof(char));\n H->pixel = (int *) calloc(n,sizeof(int));\n H->pos = (int *) calloc(n,sizeof(int));\n H->last = -1;\n if ((H->color == NULL) || (H->pos == NULL) || (H->pixel == NULL))\n Error(MSG1,\"CreateHeap\");\n for (i=0; i < H->n; i++){\n H->color[i]=WHITE;\n H->pos[i]=-1;\n H->pixel[i]=-1;\n } \n } \n else\n Error(MSG1,\"CreateHeap\");\n \n return(H);\n}\n\nvoid DestroyHeap(Heap **H){\n Heap *aux;\n \n aux = *H;\n if (aux != NULL) {\n if (aux->pixel != NULL) free(aux->pixel);\n if (aux->color != NULL) free(aux->color);\n if (aux->pos != NULL) free(aux->pos);\n free(aux);\n *H = NULL;\n }\n}\n\nbool InsertHeap(Heap *H, int pixel){\n if (!IsFullHeap(H)){\n H->last ++;\n H->pixel[H->last] = pixel;\n H->color[pixel] = GRAY;\n H->pos[pixel] = H->last;\n GoUpHeap(H,H->last); \n return(true);\n } else \n return(false);\n}\n\nbool RemoveHeap(Heap *H, int *pixel){\n if (!IsEmptyHeap(H)){\n *pixel = H->pixel[0];\n H->pos[*pixel]=-1;\n H->color[*pixel] = BLACK;\n H->pixel[0] = H->pixel[H->last];\n H->pos[H->pixel[0]] = 0;\n H->last--;\n GoDownHeap(H,0);\n return(true);\n } else \n return(false);\n}\n\nbool IsEmptyHeap(Heap *H){\n if (H->last == -1)\n return(true);\n else\n return(false);\n}\n\nvoid GoDownHeap(Heap *H, int i){\n int least, left=HEAP_LEFTSON(i), right=HEAP_RIGHTSON(i);\n\n if ((left <= H->last)&&(H->cost[H->pixel[left]] < H->cost[H->pixel[i]]))\n least = left;\n else\n least = i;\n\n if ((right <= H->last)&&(H->cost[H->pixel[right]] < H->cost[H->pixel[least]]))\n least = right;\n\n if (least != i){\n Change(&H->pixel[least],&H->pixel[i]);\n H->pos[H->pixel[i]]=i;\n H->pos[H->pixel[least]]=least;\n GoDownHeap(H,least);\n }\n}\n\nbool IsFullHeap(Heap *H){\n if (H->last == (H->n-1))\n return(true);\n else\n return(false);\n}\n\nbool HeapIsEmpty(Heap *H){\n return IsEmptyHeap(H);\n}\n\nvoid Change(int *a, int *b){\n int c; \n c = *a;\n *a = *b;\n *b = c;\n}\n\nvoid GoUpHeap(Heap *H, int i){\n int j = HEAP_DAD(i);\n\n while((i > 0) && (H->cost[H->pixel[j]] > H->cost[H->pixel[i]])){\n Change(&H->pixel[j],&H->pixel[i]);\n H->pos[H->pixel[i]]=i;\n H->pos[H->pixel[j]]=j;\n i = j;\n j = HEAP_DAD(i);\n }\n}\n\nvoid DestroyAdjPxl(AdjPxl **N)\n{\n AdjPxl *aux;\n\n aux = *N;\n if (aux != NULL){\n if (aux->dp != NULL) free(aux->dp);\n free(aux);\n *N = NULL;\n }\n}\n\nImage *CompPaths(Image *pred)\n{\n Image *seed=NULL;\n int p,n;\n\n seed = CopyImage(pred);\n\n n = seed->ncols*seed->nrows;\n for (p=0; p < n; p++) \n seed->val[p] = Seed(seed,p);\n return(seed);\n}\n\nint Seed(Image *pred, int p)\n{\n if (pred->val[p]==p)\n return(p);\n else \n return(Seed(pred,pred->val[p])); \n}\n\nImage *Perimeter(Image *bin)\n{\n int p,n;\n Image *cont,*perim;\n Curve *hist;\n\n cont = LabelContour(bin);\n n = cont->ncols*cont->nrows;\n perim = CreateImage(cont->ncols,cont->nrows);\n hist = Histogram(cont);\n for (p=0; p < n; p++)\n if (cont->val[p] > 0)\n perim->val[p] = hist->Y[cont->val[p]];\n\n DestroyCurve(&hist);\n DestroyImage(&cont);\n\n return(perim);\n}\n\nCurve3D *Saliences(Image *bin, int maxdist) \n{ \n Image *cont=NULL;\n AdjRel *A=NULL;\n AnnImg *aimg=NULL;\n Curve3D *saliences=NULL;\n \n /* Compute Euclidean IFT */\n \n cont = LabelContPixel(bin);\n aimg = Annotate(bin,NULL,cont); \n A = Circular(1.5);\n iftDilation(aimg,A);\n saliences = CompSaliences(aimg, maxdist*maxdist);\n \n DestroyImage(&cont);\n DestroyAdjRel(&A);\n DeAnnotate(&aimg);\n \n return(saliences);\n}\n\nImage *MSSkel(Image *bin, char side)\n{\n Image *msskel,*cont;\n AdjRel *A;\n AnnImg *aimg;\n int p,n;\n\n /* Compute Euclidean IFT */\n\n cont = LabelContPixel(bin);\n aimg = Annotate(bin,NULL,cont); \n A = Circular(1.5);\n n = aimg->img->ncols*aimg->img->nrows;\n switch (side) {\n case INTERIOR:\n for(p = 0; p < n; p++)\n if (aimg->img->val[p] == 0){\n\taimg->cost->val[p] = 0;\n }\n break;\n case EXTERIOR:\n for(p = 0; p < n; p++)\n if (aimg->img->val[p] != 0){\n\taimg->cost->val[p] = 0;\n }\n break;\n case BOTH:\n default: \n ;\n }\n iftDilation(aimg,A);\n DestroyAdjRel(&A);\n DestroyImage(&cont);\n \n /* Compute MS Skeletons */\n\n msskel = CompMSSkel(aimg);\n DeAnnotate(&aimg);\n\n return(msskel);\n}\n\nCurve3D *CompSaliences(AnnImg *aimg, int maxcost)\n{\n Image *cont=NULL;\n double *inter=NULL,*exter=NULL; \n int p,n,i,Lmax;\n Curve3D *saliences=NULL;\n \n n = aimg->img->ncols*aimg->img->nrows;\n cont = CreateImage(aimg->img->ncols,aimg->img->nrows);\n for(p=0;ppred->val[p]==p){\n cont->val[p]=aimg->label->val[p];\n }\n }\n \n Lmax = MaximumValue(aimg->label);\n inter = AllocDoubleArray(Lmax);\n exter = AllocDoubleArray(Lmax);\n \n \n /* Compute influence areas */\n\n for (p=0; p < n; p++){\n if ((aimg->label->val[p] > 0)&&(aimg->cost->val[p] <= maxcost)) {\n if (aimg->img->val[p] != 0){\n\tinter[aimg->label->val[p]-1]++;\n } else {\n\texter[aimg->label->val[p]-1]++;\n }\n }\n }\n \n /* Compute saliences */\n saliences = CreateCurve3D(Lmax);\n \n for (p=0; p < n; p++){\n if (cont->val[p] > 0){\n i = cont->val[p]-1;\n saliences->X[i] = (double)(p%cont->ncols);\n saliences->Y[i] = (double)(p/cont->ncols);\n if (exter[i] > inter[i]){\n\tsaliences->Z[i] = exter[i];\n }else{\n\tif (exter[i] < inter[i]){\n\t saliences->Z[i] = -inter[i];\n\t}else{\n\t saliences->Z[i] = 0.0;\n\t}\n }\n }\n }\n\n DestroyImage(&cont);\n free(inter);\n free(exter);\n\n return(saliences);\n}\n\nImage *RemFrame(Image *fimg, int sz)\n{\n Image *img;\n int y,*dst,*src,nbytes,offset;\n\n img = CreateImage(fimg->ncols-(2*sz),fimg->nrows-(2*sz));\n nbytes = sizeof(int)*img->ncols;\n offset = sz+fimg->tbrow[sz];\n for (y=0,src=fimg->val+offset,dst=img->val; y < img->nrows;y++,src+=fimg->ncols,dst+=img->ncols){\n memcpy(dst,src,nbytes);\n }\n return(img);\n}\n\nAdjPxl *AdjPixels(Image *img, AdjRel *A)\n{\n AdjPxl *N;\n int i;\n\n N = (AdjPxl *) calloc(1,sizeof(AdjPxl));\n if(N != NULL){\n N->dp = AllocIntArray(A->n);\n N->n = A->n;\n for (i=0; i < N->n; i++)\n N->dp[i] = A->dx[i] + img->ncols*A->dy[i];\n }else{\n Error(MSG1,\"AdjPixels\"); \n }\n\n return(N);\n}\n\nImage *Abs(Image *img)\n{\n Image *absimg=NULL;\n int p,n;\n \n n = img->ncols*img->nrows;\n absimg = CreateImage(img->ncols,img->nrows);\n for (p=0; p < n; p++)\n absimg->val[p] = abs(img->val[p]);\n return(absimg);\n}\n\nCurve3D *RemSaliencesByAngle(Curve3D *curve,int radius, int angle)\n{\n Curve3D *scurve;\n double area;\n int i;\n\n scurve = CreateCurve3D(curve->n+1);\n for (i=0; i < curve->n; i++){ \n scurve->X[i] = curve->X[i];\n scurve->Y[i] = curve->Y[i];\n scurve->Z[i] = curve->Z[i];\n }\n \n area = ((double)angle*PI*radius*radius/360.0);\n for (i=0; i < scurve->n; i++){ \n if (fabs(scurve->Z[i]) <= area)\n scurve->Z[i] = 0.0; \n }\n\n return(scurve);\n}\n\nImage *LabelBinComp(Image *bin, AdjRel *A)\n{\n Image *label=NULL,*flabel=NULL,*fbin=NULL;\n int i,j,n,sz,p,q,l=1;\n AdjPxl *N=NULL;\n int *FIFO=NULL;\n int first=0,last=0;\n \n sz = FrameSize(A);\n fbin = AddFrame(bin,sz,INT_MIN);\n flabel = CreateImage(fbin->ncols,fbin->nrows);\n N = AdjPixels(fbin,A);\n n = fbin->ncols*fbin->nrows;\n FIFO = AllocIntArray(n);\n for (j=0; j < n; j++){\n if ((fbin->val[j]==1)&&(flabel->val[j]==0)){\n flabel->val[j]=l;\n FIFO[last]=j; \n last++; \n while(first != last){\n\tp = FIFO[first];\n\tfirst++;\n\tfor (i=1; i < N->n; i++){\n\t q = p + N->dp[i];\n\t if ((fbin->val[q]==1)&&(flabel->val[q] == 0)){\n\t flabel->val[q] = flabel->val[p];\n\t FIFO[last] = q;\n\t last++;\n\t }\n\t}\n }\n l++;\n first=last=0;\n }\n }\n \n label = RemFrame(flabel,sz);\n DestroyAdjPxl(&N);\n DestroyImage(&fbin);\n DestroyImage(&flabel);\n free(FIFO);\n\n return(label);\n}\n\nCurve3D *SkelSaliences(Image *skel, int maxdist, int angle) \n{ \n Image *cont=NULL;\n AdjRel *A=NULL;\n AnnImg *aimg=NULL;\n Curve3D *saliences=NULL;\n Curve3D *auxsalie=NULL;\n\n /* Compute Euclidean IFT */\n A = Circular(0.0);\n cont = LabelBinComp(skel, A);\n aimg = Annotate(skel,NULL,cont);\n DestroyAdjRel(&A); \n\n A = Circular(1.5);\n iftDilation(aimg,A);\n auxsalie = CompSaliences(aimg, maxdist*maxdist);\n saliences = RemSaliencesByAngle(auxsalie,maxdist,angle);\n DestroyImage(&cont);\n DestroyAdjRel(&A);\n DeAnnotate(&aimg);\n DestroyCurve3D(&auxsalie);\n return(saliences);\n}\n\nImage *Skeleton(Image *msskel, float perc)\n{\n Image *skel = NULL;\n int p ,n, thres;\n \n skel = Abs(msskel);\n thres = (int)((MaximumValue(skel)*perc)/100.0); \n n = skel->ncols*skel->nrows;\n for (p=0; p < n; p++)\n if (skel->val[p] >= thres) \n skel->val[p]=1;\n else\n skel->val[p]=0;\n \n return(skel);\n}\n\nImage *CompMSSkel(AnnImg *aimg)\n{\n int i,p,q,n,maxd1,maxd2,d1,d2,MaxD;\n Pixel u,v;\n int sign=1,s2;\n Image *msskel,*cont=NULL,*perim=NULL,*seed=NULL;\n AdjRel *A;\n\n /* Compute MS Skeletons */\n\n cont = LabelContour(aimg->img);\n perim = Perimeter(aimg->img);\n seed = CompPaths(aimg->pred);\n A = Circular(1.0);\n n = aimg->label->ncols*aimg->label->nrows;\n msskel = CreateImage(aimg->label->ncols,aimg->label->nrows);\n\n MaxD = INT_MIN;\n for (p=0; p < n; p++) {\n if (aimg->pred->val[p] != p) { /* It eliminates the countors and\n already takes into account the\n side option */\n u.x = p%aimg->label->ncols;\n u.y = p/aimg->label->ncols;\n maxd1 = maxd2 = INT_MIN;\n for (i=1; i < A->n; i++){\n\tv.x = u.x + A->dx[i];\n\tv.y = u.y + A->dy[i];\n\tif (ValidPixel(aimg->label,v.x,v.y)){\n\t q = v.x + aimg->label->tbrow[v.y];\n\t if (cont->val[seed->val[p]] == cont->val[seed->val[q]]){ \n\t d2 = aimg->label->val[q]-aimg->label->val[p];\n\t s2 = 1;\n\t //\t if (d2 > (perim->val[seed->val[p]]-1-d2)){\n\t if (d2 > (perim->val[seed->val[p]]-d2)){\n\t s2 = -1;\n\t //\t d2 = (perim->val[seed->val[p]]-1-d2);\n\t d2 = (perim->val[seed->val[p]]-d2);\n\t } \n\t if (d2 > maxd2){\n\t maxd2 = d2;\n\t sign = s2;\n\t }\n\t } else {\n\t d1 = cont->val[seed->val[q]] - cont->val[seed->val[p]];\n\t if (d1 > maxd1) \n\t maxd1 = d1;\n\t }\n\t}\n }\n if (maxd1 > 0) {\n\tmsskel->val[p] = INT_MAX;\n } else {\n\tmsskel->val[p] = sign*maxd2;\n\tif (msskel->val[p] > MaxD)\n\t MaxD = msskel->val[p]; \n }\n }\n }\n\n for (p=0; p < n; p++) { /* Set up SKIZ */\n if (msskel->val[p] == INT_MAX)\n msskel->val[p] = MaxD + 1;\n }\n\n DestroyImage(&cont);\n DestroyImage(&perim);\n DestroyImage(&seed);\n DestroyAdjRel(&A);\n\n return(msskel);\n}\n\nvoid iftDilation(AnnImg *aimg, AdjRel *A)\n{\n Image *Dx=NULL,*Dy=NULL;\n Queue *Q=NULL;\n int i,p,q,n,sz;\n Pixel u,v;\n int *sq=NULL,tmp=INT_MAX,dx,dy;\n char *color=NULL;\n\n if (aimg->seed == NULL)\n return;\n\n n = MAX(aimg->img->ncols,aimg->img->nrows);\n sq = AllocIntArray(n);\n for (i=0; i < n; i++) \n sq[i]=i*i;\n\n Dx = CreateImage(aimg->img->ncols,aimg->img->nrows);\n Dy = CreateImage(aimg->img->ncols,aimg->img->nrows);\n n = aimg->img->ncols*aimg->img->nrows;\n color = AllocCharArray(n);\n sz = FrameSize(A);\n Q = CreateQueue(2*sz*(sz+aimg->img->ncols+aimg->img->nrows),n);\n \n while (aimg->seed != NULL){\n p=RemoveSet(&(aimg->seed));\n InsertQueue(Q,aimg->cost->val[p]%Q->C.nbuckets,p);\n color[p]=GRAY;\n }\n\n while(!EmptyQueue(Q)) {\n p=RemoveQueue(Q);\n color[p]=BLACK;\n u.x = p%aimg->img->ncols;\n u.y = p/aimg->img->ncols;\n for (i=1; i < A->n; i++){\n v.x = u.x + A->dx[i];\n v.y = u.y + A->dy[i];\n if (ValidPixel(aimg->img,v.x,v.y)){\n\tq = v.x + aimg->img->tbrow[v.y];\n\tif (color[q] != BLACK){\n\t dx = Dx->val[p] + abs(v.x-u.x);\n\t dy = Dy->val[p] + abs(v.y-u.y);\n\t tmp = sq[dx] + sq[dy];\n\t if (tmp < aimg->cost->val[q])\n\t {\n\t if (color[q] == WHITE){\n\t\tInsertQueue(Q,tmp%Q->C.nbuckets,q);\n\t\tcolor[q]=GRAY;\n\t }else\n\t\tUpdateQueue(Q,q,aimg->cost->val[q]%Q->C.nbuckets,tmp%Q->C.nbuckets);\n\t aimg->cost->val[q] = tmp;\n\t aimg->pred->val[q] = p;\n\t aimg->label->val[q] = aimg->label->val[p];\n\t Dx->val[q] = dx;\n\t Dy->val[q] = dy;\n\t }\n\t}\n } \n }\n }\n free(color);\n free(sq);\n DestroyQueue(&Q);\n DestroyImage(&Dx);\n DestroyImage(&Dy);\n}\n\nCurve *CopyCurve(Curve *curve)\n{\n Curve *curvec;\n\n curvec = CreateCurve(curve->n);\n memcpy(curvec->X,curve->X,curve->n*sizeof(double));\n memcpy(curvec->Y,curve->Y,curve->n*sizeof(double));\n return(curvec);\n}\n\nCurve *Histogram(Image *img)\n{\n int i,p,n,nbins;\n Curve *hist=NULL;\n\n nbins = MaximumValue(img)+1;\n hist = CreateCurve(nbins);\n n = img->ncols*img->nrows;\n for (p=0; p < n; p++)\n hist->Y[img->val[p]]++;\n for (i=0; i < nbins; i++) \n hist->X[i] = i;\n\n return(hist);\n}\n\nvoid SortCurve(Curve *curve, int left, int right, char order)\n{\n int pivot;\n \n if (left < right) {\n pivot = PartCurve(curve,left,right,order);\n SortCurve(curve,left,pivot-1,order);\n SortCurve(curve,pivot+1,right,order); \n }\n}\n\nint PartCurve (Curve *curve, int left, int right, char order)\n{\n double y;\n int i;\n double X,Y;\n \n y = curve->Y[left];\n i = left;\n do {\n if (order == INCREASING){\n while ((curve->Y[left] <= y)&&(left <= right)) left++; \n while (curve->Y[right] > y) right--;\n } else { /* order = DECREASING */\n while ((curve->Y[left] >= y)&&(left <= right)) left++; \n while (curve->Y[right] < y) right--;\n }\n if (left < right){\n X = curve->X[left];\n Y = curve->Y[left];\n curve->X[left] = curve->X[right];\n curve->Y[left] = curve->Y[right];\n curve->X[right] = X;\n curve->Y[right] = Y;\n left++; right--;\n }\n } while (left <= right);\n\n left = i;\n if (left != right){\n X = curve->X[left];\n Y = curve->Y[left];\n curve->X[left] = curve->X[right];\n curve->Y[left] = curve->Y[right];\n curve->X[right] = X;\n curve->Y[right] = Y;\n }\n\n return (right);\n}\n\nvoid InvertXY(Curve *curve)\n{\n double tmp;\n int i;\n for (i=0; in; i++){\n tmp = curve->X[i];\n curve->X[i] = curve->Y[i];\n curve->Y[i] = tmp;\n }\n}\n\n/* Descriptor functions ***************************/\n\n/* BIC */\nint *Quantize_colors(CImage *img, int color_dim){\n unsigned long i;\n unsigned long r, g, b;\n unsigned long fator_g, fator_b;\n int *color, n;\n \n n = img->C[0]->nrows * img->C[0]->ncols; \n\n color = (int *) calloc(n, sizeof(int));\n if(color==NULL){\n printf(\"\\nOut of memory \\n\");\n exit(-1);\n }\n \n fator_g = color_dim;\n fator_b = fator_g*color_dim;\n \n for(i=0; iC[0]->val[i]/256;\n g = color_dim*img->C[1]->val[i]/256;\n b = color_dim*img->C[2]->val[i]/256;\n \n color[i] = (r + fator_g*g + fator_b*b);\n }\n return color;\n}\n\nunsigned char Compute_log(float value){\n unsigned char result;\n \n value = 255. * value;\n if(value==0.) result=0;\n else if(value<1.) result=1;\n else if(value<2.) result=2;\n else if(value<4.) result=3;\n else if(value<8.) result=4;\n else if(value<16.) result=5;\n else if(value<32.) result=6;\n else if(value<64.) result=7;\n else if(value<128.) result=8;\n else result=9;\n \n return result;\n}\n\nvoid Compress_histogram(unsigned char *ch, unsigned long *h, \n\t\t\tunsigned long max, int size){\n int i;\n unsigned char v;\n \n for(i=0; inrows; y++){\n for(x=0L; xncols; x++){\n p = x + img->tbrow[y];\n border=FALSE;\n for (i=1; i < A->n; i++){\n\tv.x = x + A->dx[i];\n\tv.y = y + A->dy[i];\n\tif (ValidPixel(img,v.x,v.y)){\n\t q = v.x + img->tbrow[v.y];\n\t if(ppt[p].color!=ppt[q].color){ \n\t border=TRUE;\n\t break;\n\t }\n\t}\n }\n if(border==FALSE) \n\tppt[p].frequency=LOW;\n else ppt[p].frequency=HIGH;\n }\n }\n DestroyAdjRel(&A);\n}\n\nProperty *Compute_pixels_properties(CImage *img)\n{\n Property *p;\n int *color, i, n;\n \n n = img->C[0]->nrows * img->C[0]->ncols; \n \n p = (Property *) calloc(n, sizeof(Property));\n if(p==NULL){\n printf(\"\\nOut of memory \\n\");\n exit(-1);\n }\n \n color = Quantize_colors(img, 4);\n for(i=0; iC[0], p);\n \n free(color);\n return p;\n}\n\nVisualFeature *Compute_histograms(Property *p, int n){\n VisualFeature *vf = (VisualFeature *) calloc(1,sizeof(VisualFeature));\n unsigned long i;\n \n for(i=0; icolorH[i] = 0;\n vf->lowH[i] = 0;\n vf->highH[i] = 0;\n }\n \n for(i=0; icolorH[p[i].color]++;\n \n if(p[i].frequency==LOW) \n vf->lowH[p[i].color]++;\n else \n vf->highH[p[i].color]++;\n }\n return vf;\n}\n\nCompressedVisualFeature *Compress_histograms(VisualFeature *vf, int npixels)\n{\n CompressedVisualFeature *cvf = (CompressedVisualFeature *) calloc(1,sizeof(CompressedVisualFeature));\n \n Compress_histogram(cvf->colorH, vf->colorH, npixels, SIZE);\n Compress_histogram(cvf->lowH, vf->lowH, npixels, SIZE);\n Compress_histogram(cvf->highH, vf->highH, npixels, SIZE);\n \n return cvf;\n}\n\nvoid Write_visual_features(char *filename,char *dbname, CompressedVisualFeature *cvf)\n{\n FILE *file;\n int i;\n \n if((file = fopen(dbname, \"a+t\")) == NULL)\n {\n fprintf(stderr, \"Can't open %s \\n\", dbname);\n exit(-1);\n }\n \n fprintf(file, \"%s\\t\", filename);\n for(i=0;ilowH[i], cvf->highH[i]);\n }\n fprintf(file, \"\\n\");\n \n fclose(file);\n}\n\nCompressedVisualFeature *Extract_visual_features(CImage *img)\n{\n Property *p;\n VisualFeature *vf;\n CompressedVisualFeature *cvf;\n int npixels;\n \n npixels = img->C[0]->nrows * img->C[0]->ncols;\n \n p = Compute_pixels_properties(img);\n vf = Compute_histograms(p, npixels);\n cvf = Compress_histograms(vf, npixels);\n \n free(p);\n return cvf;\n}\n\nCurve *BIC(CImage *img)\n{\n Property *p;\n VisualFeature *vf;\n CompressedVisualFeature *cvf;\n int i, npixels;\n Curve *curve = CreateCurve(2*SIZE);\n \n npixels = img->C[0]->nrows * img->C[0]->ncols;\n \n p = Compute_pixels_properties(img);\n vf = Compute_histograms(p, npixels);\n cvf = Compress_histograms(vf, npixels);\n \n for (i=0; iX[i] = i;\n curve->Y[i] = cvf->lowH[i];\n curve->X[i+SIZE] = i+SIZE;\n curve->Y[i+SIZE] = cvf->highH[i];\n }\n\n free(p);\n free(vf);\n free(cvf);\n return curve;\n}\n\n\ndouble gray_level_BIC(Image *img1, Image *img2){\n Property *p1, *p2;\n VisualFeature *vf1, *vf2;\n CompressedVisualFeature *cvf1, *cvf2;\n int i, n1, n2;\n double dist;\n\n n1 = img1->nrows * img1->ncols; \n n2 = img2->nrows * img2->ncols; \n\n p1 = (Property *) calloc(n1, sizeof(Property));\n p2 = (Property *) calloc(n2, sizeof(Property));\n\n if((p1==NULL)||(p2==NULL)){\n printf(\"\\nOut of memory \\n\");\n exit(-1);\n }\n \n for(i=0; ival[i];\n }\n for(i=0; ival[i];\n }\n \n Compute_frequency_property(img1,p1);\n Compute_frequency_property(img2,p2);\n \n vf1 = Compute_histograms(p1, n1);\n vf2 = Compute_histograms(p2, n2);\n \n cvf1 = Compress_histograms(vf1, n1);\n cvf2 = Compress_histograms(vf2, n2);\n \n dist = 0.0;\n for (i=0; ilowH[i] - cvf2->lowH[i]);\n dist += fabs(cvf1->highH[i] - cvf2->highH[i]);\n }\n \n free(p1);\n free(p2);\n free(vf1);\n free(vf2);\n free(cvf1);\n free(cvf2);\n return dist;\n}\n\nFeatureVector1D *BIC_ExtractionAlgorithm(CImage *in){\n Curve *curve = NULL;\n FeatureVector1D *fv = NULL;\n curve = BIC(in);\n fv = CurveTo1DFeatureVector(curve);\n \n DestroyCurve(&curve);\n return fv;\n}\n\ndouble BIC_DistanceAlgorithm(FeatureVector1D *fv1, FeatureVector1D *fv2)\n{\n\treturn L1_Distance(fv1, fv2);\n}\n\n/* Fourier Descriptor */\ndouble Cabs(double x, double y) {\n return (sqrt( (x*x) + (y*y)));\n}\n\nCurve *Image2Curve(Image *img) { /* img = binary image */\n Curve3D *curve; //ponto (x,y) e z = ordem no contorno\n Curve *curve2;\n Image *contour = NULL;\n int i;\n int npixels;\n int count = 0;\n int j = 0 ;\n \n contour = LabelContPixel(img);\n npixels = contour->ncols * contour->nrows;\n \n for (i = 0; i < npixels; i++){\n if (contour->val[i]!=0)\n count++;\n }\n \n curve = CreateCurve3D(count+1);\n \n for (i = 0; i < npixels; i++){\n if (contour->val[i]!=0){\n curve->X[j] = i % contour->ncols;\n curve->Y[j] = i / contour->ncols;\n curve->Z[j] = contour->val[i];\n j++;\n }\n } \n \n SortCurve3D(curve, 0, (curve->n - 2), INCREASING);\n \n curve2 = CreateCurve(curve->n);\n for (i=0;in;i++){\n curve2->X[i]=curve->X[i];\n curve2->Y[i]=curve->Y[i];\n }\n \n DestroyCurve3D(&curve);\n DestroyImage(&contour);\n return (curve2);\n}\n\nCurve *FourierDescriptor(Image *img) {\n Curve *c = NULL; \n Curve *curve = NULL;\n Curve *mag = NULL;\n int i;\n int z; /* lixo */\n int tam;\n int nn = 0;\n double normfactor = 0;\n\n curve = Image2Curve(img);\n \n tam = curve->n;\n i = 1;\n nn = tam;\n while(nn != 1) {\n nn >>= 1;\n ++i;\n }\n \n for(; i; i--)\n nn <<= 1;\n \n if (nn < 128)\n nn = 128;\n \n c = CreateCurve(nn);\n \n for (i = 0; i < tam ; i++)\n {\n c->X[i] = (double) curve->X[i];\t\n c->Y[i] = (double) curve->Y[i];\n }\n \n for (i = tam ; i < nn ; i++)\n {\n c->X[i] = 0;\n c->Y[i] = 0;\n }\n \n z = FFT(1, nn,c->X ,c->Y);\n\n mag = CreateCurve(126);\n normfactor = Cabs(c->X[0],c->Y[0]);\n \n for (i = 1; i <= 126; i++)\n {\n mag->X[i-1] = i - 1;\n mag->Y[i-1] = (double) (Cabs(c->X[i],c->Y[i])/normfactor);\n }\n \n DestroyCurve(&c); \n DestroyCurve(&curve); \n return (mag);\n}\n\nFeatureVector1D *FourierDescriptor_ExtractionAlgorithm(Image *in){\n Curve *curve = NULL;\n FeatureVector1D *fv = NULL;\n \n curve = FourierDescriptor(in);\n fv = CurveTo1DFeatureVector(curve);\n \n DestroyCurve(&curve);\n return fv;\n}\n\ndouble Fourier_DistanceAlgorithm(FeatureVector1D *fv1, FeatureVector1D *fv2){\n\treturn EuclideanDistance(fv1, fv2);\n}\n\n/* Moments Invariant */\ndouble MomentPQ(int p, int q, Image *img, int max){\n int i, x, y;\n double sum = 0.0;\n \n for (i = 0; i < img->ncols * img->nrows; i++)\n {\n if (img->val[i] != 0 )\n\t{\n\t x = 1 + i%img->ncols; /* don't do 0^0 */\n\t y = 1 + i/img->ncols; \n\t sum = sum + (pow(x, p) * pow(y,q) * ((double) img->val[i]/max));\n\t}\n }\n \n return (sum);\n}\n\nCurve *MomentInv(Image *img) {\n Curve * curve;\n int i;\n int max;\n \n /* mPQ momentes of order (P+Q) */\n double m00, m01, m10, m11, m20, m02, m12, m21, m03, m30;\n \n /* center moments */\n double xc, yc;\n \n /* normalized central moments (Eta) */\n double n00, n10, n01, n02, n20, n11, n12, n21, n03, n30; \n \n /* invariant moments (Phi) */\n double f1, f2, f3, f4, f5, f6, f7;\n \n float g; /* gamma = (p+q)/2 + 1 */\n \n /* n = Upq/U00 */\n \n max = 0;\n \n for (i = 0; i < img->ncols * img->nrows ; i++)\n {\n if (img->val[i] > max)\n\tmax = img->val[i];\n }\n \n m00 = MomentPQ(0,0, img, max);\n m01 = MomentPQ(0,1, img, max);\n m10 = MomentPQ(1,0, img, max);\n m11 = MomentPQ(1,1, img, max); \n m12 = MomentPQ(1,2, img, max); \n m21 = MomentPQ(2,1, img, max); \n m02 = MomentPQ(0,2, img, max);\n m20 = MomentPQ(2,0, img, max); \n m03 = MomentPQ(0,3, img, max);\n m30 = MomentPQ(3,0, img, max); \n \n xc = (double) m10 / m00;\n yc = (double) m01 / m00;\n \n n00 = 1.0; \n \n n10 = 0.0;\n \n n01 = 0.0;\n \n g = 2.0; \n \n n20 = (double) (m20 - (xc * m10)) / (pow(m00, g));\n \n n02 = (double) (m02 - (yc * m01)) / (pow(m00, g));\n \n n11 = (double) (m11 - (yc * m10)) / (pow(m00, g));\n \n g = 2.5;\n \n n30 = (double) (m30 - (3 * xc * m20) + (2 * (pow(xc,2)) * m10) ) / (pow(m00, g)); \n \n n12 = (double) (m12 - (2 * yc * m11) - (xc * m02) + (2 * pow(yc,2) * m10) ) / (pow(m00, g)) ;\n \n n21 = (double) (m21 - (2 * xc * m11) - (yc * m20) + (2 * pow(xc,2) * m01) ) / (pow(m00, g));\n \n n03 = (double) (m03 - (3 * yc * m02) + (2 * (pow(yc,2)) * m01)) / (pow(m00, g)); \n \n f1 = (double) n20 + n02;\n \n f2 = (double) (pow((n20 - n02),2)) + (4 * (pow(n11,2)));\n \n f3 = (double) (pow((n30 - (3 * n12)),2)) + (pow( ( (3 * n21) - n03),2));\n \n f4 = (double) (pow((n30 + n12),2)) + (pow((n21 + n03),2));\n \n f5 = (double) ((n30 - (3 * n12)) * (n30 + n12) * ((pow((n30 + n12),2)) - (3 * (pow((n21 + n03),2))))) + \n (((3 * n21) - n03) * (n21 + n03) * ((3 * (pow((n30 + n12),2))) - (pow((n21 + n03),2))));\n \n f6 = (double) ((n20 + n02) * ((pow((n30 + n12),2)) - (pow((n21 + n03),2)))) +\n ((4 * n11) * (n30 + n12) * (n21 + n03)); \n \n f7 = (double) (((3 * n21) - n03) * (n30 + n12) * ((pow((n30 + n12),2)) - (3 * (pow((n21 + n03),2))))) +\n (((3 * n12) - n30) * (n21 + n03) * ((3 * (pow((n30 + n12),2))) - (pow((n21 + n03),2))));\n \n curve = CreateCurve(7);\n \n curve->X[0] = 0.0;\n curve->Y[0] = f1;\n \n curve->X[1] = 1.0;\n curve->Y[1] = f2;\n \n curve->X[2] = 2.0; \n curve->Y[2] = f3;\n \n curve->X[3] = 3.0; \n curve->Y[3] = f4;\n \n curve->X[4] = 4.0; \n curve->Y[4] = f5;\n \n curve->X[5] = 5.0; \n curve->Y[5] = f6;\n \n curve->X[6] = 6.0; \n curve->Y[6] = f7;\n\n return (curve);\n}\n\nCurve *MomentInvariant(Image *img) { // contorno e objeto inteiro\n Image *contour = NULL;\n Curve *c1 = NULL;\n Curve *c2 = NULL;\n Curve *curve = NULL;\n int i;\n \n contour = LabelContour(img);\n c1 = MomentInv(contour);\n c2 = MomentInv(img);\n \n curve = CreateCurve(c1->n + c2->n);\n for (i=0; in; i++){\n curve->X[i] = i;\n curve->Y[i] = c1->Y[i];\n }\n for (i=0; in; i++){\n curve->X[i+c1->n] = i + c1->n;\n curve->Y[i+c1->n] = c2->Y[i];\n }\n \n DestroyCurve(&c1);\n DestroyCurve(&c2);\n DestroyImage(&contour);\n \n return (curve); \n}\n\nFeatureVector1D *MomentInvariant_ExtractionAlgorithm(Image *in){\n Curve *curve = NULL;\n FeatureVector1D *fv = NULL;\n \n curve = MomentInvariant(in);\n fv = CurveTo1DFeatureVector(curve);\n\n DestroyCurve(&curve);\n return fv;\n}\n\ndouble MomentInvariant_DistanceAlgorithm(FeatureVector1D *fv1, FeatureVector1D *fv2){\n\treturn 1-EuclideanDistance(fv1, fv2);\n}\n\n/* BAS */\n/*resample curve*/\nrepresentation_type *resample(representation_type *curve, int nsamples)\n{\n representation_type *rcurve;\n Image *img1, *img2;\n int x;\n \n img1= CreateImage(curve->length, 3);\n \n for (x=0; xlength; x++){\n img1->val[x] = curve->mean[x];\n img1->val[x+img1->tbrow[1]] = curve->second[x];\n img1->val[x+img1->tbrow[2]] = curve->third[x];\n }\n \n img2 = Scale(img1, (((float) nsamples)/curve->length), 1);\n \n rcurve = (representation_type *) calloc(1, sizeof(representation_type));\n rcurve->length = nsamples;\n rcurve->mean = (int *) calloc(nsamples, sizeof(int));\n rcurve->second =(int *) calloc(nsamples, sizeof(int));\n rcurve->third = (int *) calloc(nsamples, sizeof(int));\n for (x=0; xmean[x] = img2->val[x];\n rcurve->second[x] = img2->val[x+img2->tbrow[1]];\n rcurve->third[x] = img2->val[x+img2->tbrow[2]];\n }\n \n DestroyImage(&img1);\n DestroyImage(&img2);\n return(rcurve);\n}\n\ndouble find_angle(deltax,deltay)\n int deltax;\n int deltay;\n{\n double angle;\n double pi;\n \n pi=22.0/7.0; \n \n if((deltax==0) && (deltay==0))\n angle=0.0;\n else{\n angle=atan((10.0*abs(deltax))/(10.0*abs(deltay)));\n angle=angle*180.0/pi; \n if((deltax <= 0) && (deltay >= 0)) \n angle=360.0-angle;\n else if((deltax <= 0) && (deltay <=0)) \n angle=180.0 + angle; \n else if((deltax >= 0) && (deltay <=0)) \n angle=180.0 - angle;\n }\n \n return(angle);\n}\n\nrepresentation_type *extract_feature(boun)\n boundary_type *boun;\n{\n representation_type *curve_feature; \n int i,j,x1,x2,x3,y1,y2,y3,curvelength;\n double angle_1,angle_2,curve,total,previous;\n int delta_x, delta_y,mean,second,third;\n int *bearing_array;\n \n curve_feature = (representation_type *) calloc(1, sizeof(representation_type));\n curve_feature->length=boun->length;\n curve_feature->mean= (int *) calloc(boun->length, sizeof(int));\n curve_feature->second=(int *) calloc(boun->length, sizeof(int));\n curve_feature->third=(int *) calloc(boun->length, sizeof(int));\n \n \n curvelength=(int)(boun->length/2);\n bearing_array=(int *) calloc((curvelength-1), sizeof(int));\n for(i=0; ilength; i++){\n total=0.0;\n x1=boun->X[((i-1)+boun->length)%boun->length];\n y1=boun->Y[((i-1)+boun->length)%boun->length];\n x2=boun->X[i];\n y2=boun->Y[i];\n x3=boun->X[((i+1)+boun->length)%boun->length];\n y3=boun->Y[((i+1)+boun->length)%boun->length];\n \n delta_x=x1-x2;\n delta_y=-(y1-y2);\n angle_1=find_angle(delta_x,delta_y);\n delta_x=x3-x2;\n delta_y=-(y3-y2);\n angle_2=find_angle(delta_x,delta_y);\n if(angle_1 >= angle_2)\n curve=angle_1-angle_2;\n else\n curve=360.0 + angle_1-angle_2;\n \n total+=curve;\n bearing_array[0]=(int)curve;\n previous=curve;\n for(j=2; jX[((i-j)+boun->length)%boun->length];\n y1=boun->Y[((i-j)+boun->length)%boun->length];\n x2=boun->X[i];\n y2=boun->Y[i];\n x3=boun->X[((i+j)+boun->length)%boun->length];\n y3=boun->Y[((i+j)+boun->length)%boun->length];\n delta_x=x1-x2;\n delta_y=-(y1-y2);\n angle_1=find_angle(delta_x,delta_y);\n delta_x=x3-x2;\n delta_y=-(y3-y2);\n angle_2=find_angle(delta_x,delta_y);\n if(angle_1 >= angle_2)\n\tcurve=angle_1-angle_2;\n else\n\tcurve=360.0 + angle_1-angle_2;\n \n if(j > 3){\n\tif(((curve-previous) > 180))\n\t curve=curve-360.0;\n\telse\n\t if(((previous-curve) > 180))\n\t curve=curve+360.0;\n }\n \n bearing_array[j-1]=(int)curve; \n total+=curve;\n previous=curve;\n }\n \n mean=(int)(total/(double)(curvelength-1));\n total=0.0;\n for(j=0;jmean[i]=mean;\n curve_feature->second[i]=second;\n curve_feature->third[i]=third;\n } \n free(bearing_array);\n return(curve_feature);\n}\n\nCurve *BAS(Image *in,int rsp,int nsamples){\n Curve *featurevector = NULL;\n Curve *contour = NULL;\n Curve *moment1 = NULL;\n Curve *moment2 = NULL;\n Curve *moment3 = NULL;\n \n boundary_type *bound;\n representation_type *curve, *rcurve;\n int i;\n\n contour = Image2Curve(in);\n bound = (boundary_type *) calloc(1, sizeof(boundary_type));\n bound->length = contour->n;\n bound->X = (int *)calloc(bound->length, sizeof(int));\n bound->Y = (int *)calloc(bound->length, sizeof(int));\n for (i=0; ilength; i++){\n bound->X[i] = (int)contour->X[i];\n bound->Y[i] = (int)contour->Y[i];\n }\n \n curve = extract_feature(bound);\n\n if(rsp == 0)\n {\n \trcurve = resample(curve, curve->length);\n\tnsamples = curve->length;\n }\n else\n\trcurve = resample(curve, nsamples);\n\n moment1 = CreateCurve(nsamples);\n moment2 = CreateCurve(nsamples);\n moment3 = CreateCurve(nsamples);\n \n featurevector = CreateCurve(3*nsamples);\n for (i=0; i<3*nsamples; i++){\n featurevector->X[i] = (double)i;\n }\n \n for (i=0; iX[i]= moment2->X[i]= moment3->X[i]=(double)i;\n featurevector->Y[i] = moment1->Y[i]= (double) rcurve->mean[i];\n featurevector->Y[nsamples+i] = moment2->Y[i]= (double) rcurve->second[i];\n featurevector->Y[2*nsamples+i] = moment3->Y[i]= (double) rcurve->third[i];\n }\n\n free(bound->X);\n free(bound->Y);\n free(bound);\n free(curve->mean);\n free(curve->second);\n free(curve->third);\n free(curve);\n free(rcurve->mean);\n free(rcurve->second);\n free(rcurve->third);\n free(rcurve);\n DestroyCurve(&contour);\n DestroyCurve(&moment1);\n DestroyCurve(&moment2);\n DestroyCurve(&moment3);\n\n return featurevector;\n}\n\nFeatureVector1D *BAS_ExtractionAlgorithm(Image *in,int rsp,int nsamples){\n Curve *curve = NULL;\n FeatureVector1D *fv = NULL;\n \n curve = BAS(in,rsp,nsamples);\n fv = CurveTo1DFeatureVector(curve);\n \n DestroyCurve(&curve);\n return fv;\n}\n\n\nlong min(Dist1,Dist2,Dist3)\n long Dist1;\n long Dist2;\n long Dist3;\n{\n if((Dist1<=Dist2) && (Dist1<=Dist3)) \n return(Dist1);\n else if((Dist2<=Dist1) && (Dist2<=Dist3)) \n return(Dist2);\n /*else if((Dist3<=Dist1) && (Dist3<=Dist2)) */\n return(Dist3);\n}\n\n\nlong Cum_Dist_Optimal(fv1,fv2,dim1,dim2,DISTANCE)\n representation_type fv1;\n representation_type fv2;\n int dim1;\n int dim2;\n long *DISTANCE;\n{\n long temp_dist;\n int i,j;\n int penalty;\n \n penalty=300;\n /* OPTIMAL CORRESPONDENCE OF STRINGS\n */\n DISTANCE[0*(dim2+1)+0]=0;\n for(j=1;j<=dim2;j++)\n DISTANCE[0*(dim2+1)+j]=j * penalty;\n \n for(i=1;i<=dim1;i++)\n DISTANCE[i*(dim2+1)+0]=i * penalty;\n \n for(i=1;i<=dim1;i++)\n for(j=1;j<=dim2;j++)\n if(abs(i-j) < (5)){\n\ttemp_dist=abs(fv1.mean[i-1]-fv2.mean[j-1]) +\n\t abs(fv1.second[i-1]-fv2.second[j-1]) +\n\t abs(fv1.third[i-1]-fv2.third[j-1]);\n\t\n\tDISTANCE[i*(dim2+1)+j]= temp_dist +\n\t min(DISTANCE[(i-1)*(dim2+1)+(j-1)],\n\t DISTANCE[(i-1)*(dim2+1)+(j)] + penalty,\n\t DISTANCE[(i)*(dim2+1)+(j-1)] + penalty); \n }\n return(DISTANCE[(dim1)*(dim2+1)+(dim2)]/dim2);\n}\n\nlong find_distance(representation_type fv1, representation_type fv2,\n\t\t int dim1, int dim2)\n{\n long distance,k,i,j,temp_dist;\n representation_type temp_list1, temp_list2;\n long *DISTANCE;\n \n\tDISTANCE=(long *) calloc((dim1+1)*(dim2+1),sizeof(long));\n \n temp_list1.mean=(int *) calloc(dim2,sizeof(int));\n temp_list1.second=(int *) calloc(dim2,sizeof(int));\n temp_list1.third=(int *) calloc(dim2,sizeof(int));\n temp_list2.mean=(int *) calloc(dim2,sizeof(int));\n temp_list2.second=(int *) calloc(dim2,sizeof(int));\n temp_list2.third=(int *) calloc(dim2,sizeof(int));\n \n temp_dist=10000000;\n \n for(i=0;idistance) temp_dist=distance;\n }\n /***Taking the mirror of fv2 *****/\n \n for(i=0;idistance) temp_dist=distance;\n }\n \n distance=temp_dist;\n \n free(temp_list1.mean);\n free(temp_list1.second);\n free(temp_list1.third);\n free(temp_list2.mean);\n free(temp_list2.second);\n free(temp_list2.third);\n free(DISTANCE);\n return(distance);\n}\n\ndouble BAS_DistanceAlgorithm(FeatureVector1D *c1, FeatureVector1D *c2){\n \n representation_type fv1, fv2;\n int n, m, i;\n long dist;\n \n n = c1->n/3;\n m = c2->n/3;\n fv1.mean=(int *) calloc(n,sizeof(int));\n fv1.second=(int *) calloc(n,sizeof(int));\n fv1.third=(int *) calloc(n,sizeof(int));\n fv2.mean=(int *) calloc(m,sizeof(int));\n fv2.second=(int *) calloc(m,sizeof(int));\n fv2.third=(int *) calloc(m,sizeof(int)); \n \n for (i=0; iX[i];\n fv1.second[i] = (int)c1->X[n + i];\n fv1.third[i] = (int)c1->X[2*n + i];\n }\n\n for (i=0; iX[i];\n fv2.second[i] = (int)c2->X[m + i];\n fv2.third[i] = (int)c2->X[2*m + i];\n }\n \n dist = find_distance(fv1,fv2, n, m);\n \n free(fv1.mean);\n free(fv1.second);\n free(fv1.third);\n free(fv2.mean);\n free(fv2.second);\n free(fv2.third);\n \n return dist;\n}\n\n/* Tensor Scale */\nFeatureVector1D *TensorScale_ExtractionAlgorithm(Image *in){\n\tTensorScale *ts = NULL;\n\tFeatureVector1D *fv = NULL;\n\tfloat *hist = NULL;\n\tint i;\n\t\n\tts = CreateBinaryTensorScale(in,24);\n\thist = TSOrientationHistogram(ts);\n\n\t/*convertendo hist para featurevector1D*/\n\tfv = CreateFeatureVector1D(HISTOGRAMSIZE+1);\n\tfor(i = 0; i < HISTOGRAMSIZE+1; i++)\n\t\tfv->X[i] = hist[i];\n\t\n\tfree(hist);\n\tDestroyTensorScale(&ts);\n\n\treturn fv;\n}\n\nTensorScale *CreateBinaryTensorScale(Image *bin, int m_pairs){\n Image *edt,*edt2,*bin2;\n Point *epsilon;\n TensorScale *ts = NULL;\n Vector *tau;\n int i,j,k,p,v,vi,n;\n float x,y,xc,yc,taux, tauy, aux;\n float a2,b2,b1,teta,u1,v1,u2,v2,aa,acc,wt,w;\n float gSxy, gSy2_x2;\n float sin_teta, cos_teta;\n float *lt_sqrt;\n int d,d1,d2,dmax;\n int ncols,nrows;\n\n ncols = bin->ncols;\n nrows = bin->nrows;\n n = ncols*nrows;\n\n bin2 = CopyImage(bin);\n p = bin2->tbrow[nrows-1];\n for(i=0; ival[i] = 0;\n bin2->val[p+i] = 0;\n }\n for(i=0; itbrow[i];\n bin2->val[p] = 0;\n bin2->val[p+ncols-1] = 0;\n }\n\n //------ Euclidean distance transform ----------------\n edt2 = TSEDistTrans(bin2);\n\n dmax = MaximumValue(edt2);\n lt_sqrt = (float *)malloc((dmax+1)*sizeof(float));\n for(i=0;i<=dmax;i++)\n lt_sqrt[i] = sqrtf((float)i);\n\n edt = CreateImage(ncols,nrows);\n for(p=0; pval[p];\n d = ROUND(lt_sqrt[d]);\n edt->val[p] = d;\n }\n\n //---------------------------------------------------\n\n ts = (TensorScale *)malloc(sizeof(TensorScale));\n ts->orientation = CreateDImage(ncols,nrows);\n ts->anisotropy = CreateDImage(ncols,nrows);\n ts->thickness = CreateDImage(ncols,nrows);\n ts->m_pairs = m_pairs;\n\n tau = (Vector *)malloc(sizeof(Vector)*m_pairs);\n epsilon = (Point *)malloc(sizeof(Point)*m_pairs);\n\n teta = 0.0;\n for(i=0;itbrow[i]+j;\n if(bin2->val[p] == 0) continue;\n\n vi = edt->val[p];\n //--------- Sample lines --------------------------------------\n gSxy = gSy2_x2 = 0.0;\n xc = j+0.5; yc = i+0.5;\n for(k=0;kval[(int)(xc+x) + edt->tbrow[(int)(yc+y)]];\n\t if(d1 == 0)\n\t break;\n\t }\n\t \n\t if(d2==0){\n\t d2 = edt->val[(int)(xc-x) + edt->tbrow[(int)(yc-y)]];\n\t if(d2 == 0)\n\t break;\n\t }\n\n\t d = (d10.0) teta=PI/2.0;\n\telse teta=-PI/2.0;\n }\n else{\n\tteta = atanf((gSxy+gSxy)/gSy2_x2);\n\t\n\tif(gSxy<0.0 && teta<0.0) teta+=PI;\n\telse if(gSxy>0.0 && teta>0.0) teta-=PI;\n\telse if(teta==0.0 && gSy2_x2>0.0) teta=PI;\n }\n teta /= 2.0;\n\n //----------------- A & B ---------------------------------\n b2 = (float)edt2->val[p];\n b1 = lt_sqrt[(int)b2];\n \n acc = wt = 0.0;\n sin_teta = sinf(teta);\n cos_teta = cosf(teta);\n for(k=0;k=b2){\n\t w = (v1<0.0)?(b1+v1):(b1-v1);\n\t acc += w*aa;\n\t wt += w;\n\t }\n\t}\n }\n\n if(wt>0.0)\n\ta2 = acc/wt;\n else\n\ta2 = b2;\n\n aux = 1.0-b2/a2;\n if(aux<0.0) aux = 0.0;\n ts->anisotropy->val[p] = sqrtf(aux);\n ts->thickness->val[p] = b1; //sqrtf(b2);\n\n if(teta<0.0) teta+=(float)PI;\n if(teta>PI) teta = PI;\n teta = PI-teta;\n\n ts->orientation->val[p] = teta;\n }\n }\n\n free(tau);\n free(epsilon);\n free(lt_sqrt);\n DestroyImage(&edt);\n DestroyImage(&edt2);\n DestroyImage(&bin2);\n\n return ts;\n}\n\nvoid DestroyTensorScale(TensorScale **ts){\n if(*ts != NULL){\n DestroyDImage(&((*ts)->orientation));\n DestroyDImage(&((*ts)->anisotropy));\n DestroyDImage(&((*ts)->thickness));\n free(*ts);\n }\n *ts = NULL;\n}\n\nfloat *TSOrientationHistogram(TensorScale *ts){\n float *hist;\n float ratio,sum;\n double an,th;\n int w,h,i,j,p,bin;\n \n ratio = (float)HISTOGRAMSIZE/PI;\n hist = (float *)malloc(sizeof(float)*(HISTOGRAMSIZE+1));\n memset(hist, 0, sizeof(float)*(HISTOGRAMSIZE+1));\n w = ts->anisotropy->ncols;\n h = ts->anisotropy->nrows;\n\n for(i=0; ianisotropy->tbrow[i]+j;\n an = ts->anisotropy->val[p];\n th = ts->thickness->val[p];\n\n if(th>0.0){\n\tbin = ROUND(ts->orientation->val[p]*ratio); \n\thist[bin] += an;\n }\n }\n }\n hist[0] += hist[HISTOGRAMSIZE];\n hist[HISTOGRAMSIZE] = 0.0;\n\n //Normaliza�ao do histograma\n sum = 0.0;\n for(i=0;incols,bin->nrows);\n sq = AllocIntArray(n);\n for (i=0; i < n; i++) \n sq[i]=i*i;\n\n A = Circular(1.5);\n cost = CreateImage(bin->ncols, bin->nrows);\n Dx = CreateImage(bin->ncols,bin->nrows);\n Dy = CreateImage(bin->ncols,bin->nrows); \n n = bin->ncols*bin->nrows;\n Q = CreateQueue(bin->ncols+bin->nrows,n);\n\n for(p = 0; p < n; p++){\n if(bin->val[p] > 0)\n cost->val[p] = INT_MAX;\t \n else{\n cost->val[p]=0; \n InsertQueue(Q,cost->val[p]%Q->C.nbuckets,p);\n }\n }\n \n while(!EmptyQueue(Q)) {\n p = RemoveQueue(Q);\n u.x = p%bin->ncols;\n u.y = p/bin->ncols;\n for (i=1; i < A->n; i++){\n v.x = u.x + A->dx[i];\n v.y = u.y + A->dy[i];\n if(ValidPixel(bin,v.x,v.y)){\n\tq = v.x + bin->tbrow[v.y];\n\tif (cost->val[p] < cost->val[q]){\n\t dx = Dx->val[p] + abs(v.x-u.x);\n\t dy = Dy->val[p] + abs(v.y-u.y);\n\t tmp = sq[dx] + sq[dy];\n\t if (tmp < cost->val[q]){\n\t if (cost->val[q] == INT_MAX)\n\t InsertQueue(Q,tmp%Q->C.nbuckets,q);\n\t else\n\t UpdateQueue(Q,q,cost->val[q]%Q->C.nbuckets,tmp%Q->C.nbuckets);\n\t cost->val[q] = tmp;\n\t Dx->val[q] = dx;\n\t Dy->val[q] = dy;\n\t }\n\t}\n }\n }\n }\n\n free(sq);\n DestroyQueue(&Q);\n DestroyAdjRel(&A);\n DestroyImage(&Dx);\n DestroyImage(&Dy);\n \n return(cost);\n}\n\ndouble TensorScale_DistanceAlgorithm(FeatureVector1D *fv1, FeatureVector1D *fv2){\n\tdouble result;\n\tint offset;\n\n\tresult = (double) TSHistogramMatch(fv1, fv2, &offset);\n\n\treturn (1-result);\n}\n\nfloat TSHistogramMatch(FeatureVector1D *fv1, FeatureVector1D *fv2, int *offset){\n float *newhist;\n float *newh1,*newh2, *hist1, *hist2;\n int i,j,p;\n float max,correlacao;\n float score;\n float dabs,aux;\n //int maxoffset;\n FILE *file1,*file2,*file3;\n\n newhist = (float *)malloc(sizeof(float)*2*HISTOGRAMSIZE);\n newh1=newhist;\n newh2=newhist+HISTOGRAMSIZE;\n\n hist1 = (float *)malloc(sizeof(float)*HISTOGRAMSIZE+1);\n hist2 = (float *)malloc(sizeof(float)*HISTOGRAMSIZE+1);\n \n for(i = 0; i < HISTOGRAMSIZE+1; i++)\n {\n\t hist1[i] = fv1->X[i];\n\t hist2[i] = fv2->X[i];\n }\n\n\n //Ajuste no histograma\n newh1[0] = (2.0*hist1[0]+hist1[HISTOGRAMSIZE-1]+hist1[1])/4.0;\n newh2[0] = (2.0*hist2[0]+hist2[HISTOGRAMSIZE-1]+hist2[1])/4.0;\n for(i=1;imax){\n max=correlacao;\n *offset=i;\n }\n }\n\n file1 = fopen(\"histogram1d.txt\",\"w\");\n file2 = fopen(\"histogram2.txt\",\"w\");\n file3 = fopen(\"histogram1.txt\",\"w\");\n dabs = 0.0;\n for(p=*offset,j=0;jn; i++) \n descriptor->Y[i] = 2.0 - descriptor->Y[i];\n \n return descriptor;\n}\n\nCurve *ContourMSFractal(Image *in)\n{\n Image *cont = NULL;\n Curve *descriptor = NULL;\n Polynom *P;\n double lower = 1.0;\n double higher = 5.0;\n int nbins = 100;\n int degree = 10;\n \n cont = LabelContour(in);\n P = MSFractal(cont, 256, degree, lower, higher, 0, 0.0, 6.0);\n descriptor = PolynomToFractalCurve(P, lower, higher, nbins);\n \n DestroyPolynom(&P);\n DestroyImage(&cont);\n return (descriptor);\n}\n\nFeatureVector1D *MS_ExtractionAlgorithm(Image *img){\n Curve *curve = NULL;\n FeatureVector1D *fv = NULL;\n\n curve = ContourMSFractal(img);\n fv = CurveTo1DFeatureVector(curve);\n \n DestroyCurve(&curve);\n return fv;\n}\n\ndouble MS_DistanceAlgorithm(FeatureVector1D *fv1, FeatureVector1D *fv2){\n\treturn EuclideanDistance(fv1, fv2);\n}\n\n/* Contour Saliences */\nvoid DescInvertXY(FeatureVector2D *desc)\n{\n double tmp;\n int i;\n for (i=0; in; i++){\n tmp = desc->X[i];\n desc->X[i] = desc->Y[i];\n desc->Y[i] = tmp;\n }\n}\n\nFeatureVector2D *CreateFeatureVector2D(int n)\n{\n FeatureVector2D *desc=NULL;\n \n desc = (FeatureVector2D *) calloc(1,sizeof(FeatureVector2D));\n if (desc != NULL) {\n desc->X = AllocDoubleArray(n);\n desc->Y = AllocDoubleArray(n);\n desc->n = n;\n } else {\n Error(MSG1,\"CreateFeatureVector\");\n }\n return(desc);\n}\n\ndouble ContSalieDistance(FeatureVector2D *D1, FeatureVector2D *D2){\n \n int i;\n int n = MIN(D1->n, D2->n);\n double deltaX, dist, eps = 0.2;\n \n dist = 0.0;\n for (i=0; iX[i]-D2->X[i]);\n if (deltaX<=eps){\n dist = dist + sqrt(pow(D1->X[i] - D2->X[i],2)+\n\t\t\t pow(D1->Y[i] - D2->Y[i],2));\n }else\n dist = dist + fabs(D1->Y[i]) + fabs(D2->Y[i]); \n }\n \n for (i=n; in; i++){\n dist = dist + fabs(D1->Y[i]);\n }\n \n for (i=n; in; i++){\n dist = dist + fabs(D2->Y[i]);\n }\n \n return dist;\n}\n\nFeatureVector2D *CircularRotation(FeatureVector2D *descriptor, double delta){\n \n FeatureVector2D *c = CreateFeatureVector2D(descriptor->n);\n int i;\n \n for (i=0; in; i++){\n c->Y[i] = descriptor->X[i] + delta;\n if (c->Y[i]<0.0)\n c->Y[i] = 1.0 + c->Y[i];\n if (c->Y[i]>1.0)\n c->Y[i] = 1.0 - c->Y[i];\n c->X[i] = descriptor->Y[i];\n }\n SortFeatureVector2D(c, 0, (c->n-1), INCREASING);\n DescInvertXY(c);\n return c;\n}\n\nvoid DestroyFeatureVector2D(FeatureVector2D **desc)\n{\n FeatureVector2D *aux;\n \n aux = *desc;\n if (aux != NULL){\n if (aux->X != NULL) free(aux->X);\n if (aux->Y != NULL) free(aux->Y);\n free(aux);\n *desc = NULL;\n }\n}\n\nvoid SortFeatureVector2D(FeatureVector2D *desc, int left, int right, char order)\n{\n int pivot;\n \n if (left < right) {\n pivot = PartFeatureVector2D(desc,left,right,order);\n SortFeatureVector2D(desc,left,pivot-1,order);\n SortFeatureVector2D(desc,pivot+1,right,order); \n }\n}\n\nint PartFeatureVector2D (FeatureVector2D *desc, int left, int right, char order)\n{\n double y;\n int i;\n double X,Y;\n \n y = desc->Y[left];\n i = left;\n \n do {\n if (order == INCREASING){\n while ((desc->Y[left] <= y)&&(left <= right)) left++;\n while (desc->Y[right] > y) right--;\n } else { /* order = DECREASING */\n while ((desc->Y[left] >= y)&&(left <= right)) left++;\n while (desc->Y[right] < y) right--;\n }\n if (left < right){\n X = desc->X[left];\n Y = desc->Y[left];\n desc->X[left] = desc->X[right];\n desc->Y[left] = desc->Y[right];\n desc->X[right] = X;\n desc->Y[right] = Y;\n left++; right--;\n }\n } while (left <= right);\n \n left = i;\n \n if (left != right){\n X = desc->X[left];\n Y = desc->Y[left];\n desc->X[left] = desc->X[right];\n desc->Y[left] = desc->Y[right];\n desc->X[right] = X;\n desc->Y[right] = Y;\n }\n \n return (right);\n}\n\nFeatureVector2D *CopyFeatureVector2D(FeatureVector2D *desc)\n{\n FeatureVector2D *descc;\n \n descc = CreateFeatureVector2D(desc->n);\n memcpy(descc->X,desc->X,desc->n*sizeof(double));\n memcpy(descc->Y,desc->Y,desc->n*sizeof(double));\n \n return(descc);\n}\n\ndouble Matching(FeatureVector2D *descriptor1, FeatureVector2D *descriptor2, int order)\n{\n FeatureVector2D *d1 = NULL;\n FeatureVector2D *d2 = NULL;\n FeatureVector2D *D1 = NULL;\n FeatureVector2D *D2 = NULL;\n double max1, max2;\n double dist, distance = INT_MAX;\n int i,j;\n \n d1 = CopyFeatureVector2D(descriptor1);\n d2 = CopyFeatureVector2D(descriptor2);\n SortFeatureVector2D(d1, 0, (d1->n - 1), order);\n SortFeatureVector2D(d2, 0, (d2->n - 1), order);\n \n max1 = fabs(d1->Y[0]);\n max2 = fabs(d2->Y[0]);\n \n i = 0;\n while ((in)&&\n\t ((fabs(d1->Y[i]) - max1)<=(fabs(0.2* max1)))){\n j = 0;\n while((jn)&&\n\t ((fabs(d2->Y[j]) - max2)<=(fabs(0.2 * max2)))){\n if (d1->Y[i]*d2->Y[j]>0.0){\n\tD1 = CircularRotation(descriptor1, -d1->X[i]);\n\tD2 = CircularRotation(descriptor2, -d2->X[j]);\n\tdist = ContSalieDistance(D1, D2);\n\t//WriteInstance(i, j, descriptor1, descriptor2, d1, d2, D1, D2, -d1->X[i], -d2->X[j], dist);\n\tif (dist < distance)\n\t distance = dist;\n\tDestroyFeatureVector2D(&D1);\n\tDestroyFeatureVector2D(&D2);\n }\n j++;\n }\n i++;\n }\n \n DestroyFeatureVector2D(&d1);\n DestroyFeatureVector2D(&d2);\n return distance;\n}\n\nvoid iftFastDilation(AnnImg *aimg, AdjRel *A)\n{\n Image *Dx=NULL,*Dy=NULL;\n Queue *Q=NULL;\n Heap *H=NULL;\n int i,p,q,n,sz;\n Pixel u,v;\n int *sq=NULL,tmp=INT_MAX,dx,dy;\n bool cuisenaire;\n AdjRel *A8=Circular(1.5),*CA=NULL;\n char *color=NULL;\n\n if (aimg->seed == NULL)\n return;\n \n n = MAX(aimg->img->ncols,aimg->img->nrows);\n sq = AllocIntArray(n);\n for (i=0; i < n; i++) \n sq[i]=i*i;\n \n Dx = CreateImage(aimg->img->ncols,aimg->img->nrows);\n Dy = CreateImage(aimg->img->ncols,aimg->img->nrows);\n n = aimg->img->ncols*aimg->img->nrows;\n color = AllocCharArray(n);\n sz = FrameSize(A);\n Q = CreateQueue(2*sz*(sz+aimg->img->ncols+aimg->img->nrows),n);\n \n /* Compute IFT with 8-Adjacency */\n \n while (aimg->seed != NULL){\n p=RemoveSet(&(aimg->seed));\n InsertQueue(Q,aimg->cost->val[p]%Q->C.nbuckets,p);\n color[p]=GRAY;\n }\n \n while(!EmptyQueue(Q)) {\n p=RemoveQueue(Q);\n color[p]=BLACK;\n u.x = p%aimg->img->ncols;\n u.y = p/aimg->img->ncols;\n cuisenaire=true;\n for (i=1; i < A8->n; i++){\n v.x = u.x + A8->dx[i];\n v.y = u.y + A8->dy[i];\n if (ValidPixel(aimg->img,v.x,v.y)){\n\tq = v.x + aimg->img->tbrow[v.y];\n\tif (color[q] != BLACK){\n\t dx = Dx->val[p] + abs(v.x-u.x);\n\t dy = Dy->val[p] + abs(v.y-u.y);\n\t tmp = sq[dx] + sq[dy];\n\t if (tmp < aimg->cost->val[q]){\n\t if (color[q] == WHITE){\n\t InsertQueue(Q,tmp%Q->C.nbuckets,q);\n\t color[q] = GRAY;\n\t }else\n\t\tUpdateQueue(Q,q,aimg->cost->val[q]%Q->C.nbuckets,tmp%Q->C.nbuckets);\n\t aimg->cost->val[q] = tmp;\n\t aimg->pred->val[q] = p;\n\t aimg->label->val[q] = aimg->label->val[p];\n\t Dx->val[q] = dx;\n\t Dy->val[q] = dy;\n\t cuisenaire = false;\n\t }\n\t} \n } \n }\n if (cuisenaire) \n InsertSet(&(aimg->seed),p); \n }\n \n DestroyQueue(&Q);\n free(color);\n \n /* Compute IFT with Complementary Adjacency */\n \n if (A8->n < A->n) {\n \n CA = ComplAdj(A8,A);\n H = CreateHeap(n,aimg->cost->val);\n\n while (aimg->seed != NULL){\n p=RemoveSet(&(aimg->seed));\n InsertHeap(H,p);\n }\n\n while(!HeapIsEmpty(H)) {\n RemoveHeap(H,&p);\n u.x = p%aimg->img->ncols;\n u.y = p/aimg->img->ncols;\n for (i=0; i < CA->n; i++){\n\tv.x = u.x + CA->dx[i];\n\tv.y = u.y + CA->dy[i];\n\tif (ValidPixel(aimg->img,v.x,v.y)){\n\t q = v.x + aimg->img->tbrow[v.y];\n\t if (color[q]!=BLACK){\n\t dx = Dx->val[p] + abs(v.x-u.x);\n\t dy = Dy->val[p] + abs(v.y-u.y);\n\t tmp = sq[dx] + sq[dy];\n\t if (tmp < aimg->cost->val[q]) \n\t {\n\t\taimg->cost->val[q] = tmp;\n\t\taimg->pred->val[q] = p;\n\t\taimg->label->val[q] = aimg->label->val[p];\n\t\tDx->val[q] = dx;\n\t\tDy->val[q] = dy;\n\t\tif (color[q] == WHITE){\n\t\t InsertHeap(H,q);\n\t\t}else\n\t\t GoUpHeap(H,H->pos[q]);\n\t }\n\t }\n\t} \n }\n }\n DestroyAdjRel(&CA);\n DestroyHeap(&H);\n }\n\n DestroyAdjRel(&A8);\n\n free(sq);\n DestroyImage(&Dx);\n DestroyImage(&Dy);\n}\n\nCurve3D *SkelCont(Image *bin, int maxdist, int threshold, int angle, char side) { \n Image *contour=NULL;\n Image *msskel=NULL;\n Image *skel=NULL;\n Image *bin_skel=NULL;\n AdjRel *A=NULL;\n AnnImg *aimg=NULL;\n Curve3D *contour_salie = NULL;\n Curve3D *skelsaliences = NULL;\n Curve3D *saliences = NULL;\n Pixel left, right;\n int i, j, p, q, n, label, imax, maxcont, max, min, imin, x, y, ne, ni, delta = 3; \n double sum;\n \n contour = LabelContPixel(bin);\n aimg = Annotate(bin,NULL,contour); \n A = Circular(1.5);\n iftFastDilation(aimg,A);\n \n msskel = MSSkel(bin, side);\n skel = Skeleton(msskel, threshold);\n bin_skel = Skeleton(msskel, threshold);\n n = bin->ncols*bin->nrows;\n contour_salie = Saliences(bin, maxdist);\n\n maxcont = MaximumValue(contour);\n\n for (p=0; pval[p]!=0){\n q = Seed(aimg->pred, p);\n label = (aimg->label->val[q] + msskel->val[p]/2 + maxcont)%maxcont;\n skel->val[p] = label;\n if (side == INTERIOR){\n\tif (contour_salie->Z[label-1]<0.0){\n\t max = INT_MIN;\n\t imax = 0;\n\t for (j=-5; j<5; j++){\n\t if (contour_salie->Z[(label-1+j+contour_salie->n)%contour_salie->n] > max){\n\t imax = (label-1+j+contour_salie->n)%contour_salie->n;\n\t max = contour_salie->Z[imax];\n\t }\n\t }\n\t skel->val[p] = imax + 1;\n\t}\n\telse {\n\t skel->val[p] = MAX(label,1);\n\t}\n }\n else{ \n\tif (side == EXTERIOR){\n\t if (contour_salie->Z[label-1]>0.0){\n\t min = INT_MAX;\n\t imin = 0;\n\t for (j=-5; j<5; j++){\n\t if (contour_salie->Z[(label-1+j+contour_salie->n)%contour_salie->n] < min){\n\t\timin = (label-1+j+contour_salie->n)%contour_salie->n;\n\t\tmin = contour_salie->Z[imin];\n\t }\n\t }\n\t skel->val[p] = imin + 1;\n\t }\n\t else {\n\t skel->val[p] = MAX(label, 1);\n\t }\n\t}\n }\n }\n }\n \n skelsaliences = SkelSaliences(bin_skel, maxdist, angle); \n \n if (side==EXTERIOR){\n left.x = bin->ncols-1;\n left.y = bin->nrows-1;\n right.x = 0;\n right.y = 0;\n for (y=0; y < bin->nrows; y++)\n for (x=0; x < bin->ncols; x++){\n\tif (bin->val[x+bin->tbrow[y]] > 0){\n\t if (x < left.x)\n\t left.x = x;\n\t if (y < left.y)\n\t left.y = y;\n\t if (x > right.x)\n\t right.x = x;\n\t if (y > right.y)\n\t right.y = y;\t\n\t}\n }\n \n for (i=0; in; i++){\n if ((skelsaliences->X[i]X[i]>right.x)||\n\t (skelsaliences->Y[i]Y[i]>right.y))\n\tskelsaliences->Z[i] = 0.0;\n }\n }\n \n SortCurve3D(skelsaliences, 0, (skelsaliences->n - 2), DECREASING);\n i=0;\n while (skelsaliences->Z[i]!=0.0)\n i++;\n saliences = CreateCurve3D(i); \n for (i=0; i< saliences->n; i++){\n if (skelsaliences->Z[i]!=0.0){\n p = (int)skelsaliences->X[i]+bin->tbrow[(int)skelsaliences->Y[i]];\n saliences->X[i] = contour_salie->X[skel->val[p]-1];\n saliences->Y[i] = contour_salie->Y[skel->val[p]-1];\n if (side==INTERIOR){\n\tsum = 0.0;\n\tfor (j=-delta; j<=delta; j++){\n\t q = ((skel->val[p]-1) + j + maxcont) % maxcont;\n\t if (contour_salie->Z[q]>0.0)\n\t sum += contour_salie->Z[q];\n\t}\n\tsaliences->Z[i] = sum;\n } \n else{\n\tsum = 0.0;\n\tfor (j=-delta; j<=delta; j++){\n\t q = ((skel->val[p]-1) + j + maxcont) % maxcont;\n\t if (contour_salie->Z[q]<0.0)\n\t sum += contour_salie->Z[q];\n\t}\n\tsaliences->Z[i] = sum;\n }\n } \n }\n\n ne = 0;\n ni = 0;\n for (i=0; in; i++){\n if (saliences->Z[i]>0.0) \n ni += saliences->Z[i];\n else\n if (saliences->Z[i]<0.0) \n\tne += fabs(saliences->Z[i]);\n }\n\n for (i=0; in; i++){\n if (saliences->Z[i]>0.0) \n saliences->Z[i]/=ni;\n else\n if (saliences->Z[i]<0.0) \n\tsaliences->Z[i]/=ne;\n }\n\n \n DestroyImage(&contour);\n DestroyImage(&msskel);\n DestroyImage(&skel);\n DestroyImage(&bin_skel);\n DestroyCurve3D(&contour_salie);\n DestroyCurve3D(&skelsaliences);\n DestroyAdjRel(&A);\n DeAnnotate(&aimg);\n return(saliences);\n\n}\n\nCurve3D *iftContourSaliences(Image *bin,int threshold_in,int threshold_out,int angle_in,int angle_out)\n{\n\n Curve3D *saliences = NULL;\n Curve3D *convex_saliences = NULL;\n Curve3D *concave_saliences = NULL;\n int i;\n int maxdist = 10;\n \n convex_saliences = SkelCont(bin,maxdist,threshold_in, angle_in, INTERIOR);\n concave_saliences = SkelCont(bin, maxdist, threshold_out, angle_out, EXTERIOR);\n saliences = CreateCurve3D(convex_saliences->n + concave_saliences->n);\n for (i=0; in; i++){\n saliences->X[i] = convex_saliences->X[i];\n saliences->Y[i] = convex_saliences->Y[i];\n saliences->Z[i] = convex_saliences->Z[i];\n }\n for (i=convex_saliences->n; in;i++){\n saliences->X[i] = concave_saliences->X[i-convex_saliences->n];\n saliences->Y[i] = concave_saliences->Y[i-convex_saliences->n];\n saliences->Z[i] = concave_saliences->Z[i-convex_saliences->n];\n }\n \n DestroyCurve3D(&convex_saliences);\n DestroyCurve3D(&concave_saliences);\n return saliences;\n}\n\nCurve *ContourSaliences(Image *in)\n{\n Curve3D *saliences = NULL;\n Curve *descriptor = NULL;\n Image *contour = NULL;\n int i, p, max;\n \n contour = LabelContPixel(in);\n saliences = iftContourSaliences(in, 5, 20, 50, 110); \n \n descriptor = CreateCurve(saliences->n);\n max = MaximumValue(contour);\n for (i=0; in; i++){\n descriptor->X[i] = saliences->Z[i];\n p = (int)saliences->X[i]+contour->tbrow[(int)saliences->Y[i]];\n descriptor->Y[i] = (double)(((contour->val[p])-1))/max;\n }\n SortCurve(descriptor, 0, (descriptor->n - 1), INCREASING);\n InvertXY(descriptor); \n \n DestroyCurve3D(&saliences);\n DestroyImage(&contour);\n \n return (descriptor);\n}\n\nvoid WriteFeatureVector2D(FeatureVector2D *desc,char *filename)\n{\n FILE *fp;\n int i;\n \n fp = fopen(filename,\"w\");\n if (fp == NULL){\n fprintf(stderr,\"Cannot open %s\\n\",filename);\n exit(-1);\n }\n for (i=0; i < desc->n; i++)\n fprintf(fp,\"%f\\t%f\\n\",desc->X[i],desc->Y[i]);\n \n fclose(fp);\n}\n\nFeatureVector2D *CS_ExtractionAlgorithm(Image *img){\n Curve *curve = NULL;\n FeatureVector2D *fv = NULL;\n \n curve = ContourSaliences(img);\n fv = CurveTo2DFeatureVector(curve);\n \n DestroyCurve(&curve);\n return fv;\n}\n\ndouble CS_DistanceAlgorithm(FeatureVector2D *descriptor1, FeatureVector2D *descriptor2){\n double convex_distance = INT_MIN;\n double concave_distance = INT_MIN;\n \n convex_distance = Matching(descriptor1, descriptor2, DECREASING);\n concave_distance = Matching(descriptor1, descriptor2, INCREASING);\n return(MIN(convex_distance, concave_distance));\n}\n\n/* Segment Saliences */\nCurve *SS_ExtractionAlgorithm_(Image *in, int maxdist, int nsamples, int side){\n Curve *inner = NULL;\n Curve *outer = NULL;\n Curve *diff = NULL;\n Curve *ninner = NULL;\n Curve *nouter = NULL;\n Curve *ndiff = NULL;\n Curve *output = NULL;\n\n Image *mbb = NULL;\n Image *bin = NULL;\n Image *contour = NULL;\n Image *segments = NULL;\n \n AdjRel *A=NULL;\n AnnImg *aimg= NULL;\n \n int p,i,Lmax, maxcost = maxdist*maxdist;\n double nin, nout, maxin, maxout;\n\n mbb = MBB(in);\n bin = AddFrame(mbb,maxdist,0);\n\n DestroyImage(&mbb);\n \n segments = LabelContPixel(bin);\n\n /* Compute Euclidean IFT */\n contour = LabelContPixel(bin);\n \n aimg = Annotate(bin,NULL,contour); \n A = Circular(1.5);\n iftDilation(aimg,A); \n \n Lmax = MaximumValue(aimg->label);\n //printf(\"Lmax = %d\\n\", Lmax);\n inner = CreateCurve(Lmax);\n outer = CreateCurve(Lmax);\n diff = CreateCurve(Lmax);\n \n for (i=0; iX[i] = inner->X[i] = outer->X[i]= (double)(i*nsamples)/Lmax;\n } \n \n /* Compute influence areas */ \n nin = nout = 0.0;\n for (p=0; p < bin->ncols*bin->nrows; p++){\n if (segments->val[p] != 0){\n segments->val[p]=((((segments->val[p]*nsamples)/Lmax))/*%2*/)+1;\n }\n if ((aimg->label->val[p] > 0)&&(aimg->cost->val[p] <= maxcost)) {\n if (aimg->img->val[p] != 0){\n\tnin++;\n\tinner->Y[aimg->label->val[p]-1]++;\n } else {\n\tnout++;\n\touter->Y[aimg->label->val[p]-1]++;\n }\n }\n }\n \n maxin = INT_MIN;\n maxout = INT_MIN;\n for (i=0; iY[i] > maxin){\n maxin = inner->Y[i];\n }\n if (outer->Y[i] > maxout){\n maxout = outer->Y[i];\n }\n }\n \n for (i=0; iY[i] /= nin;\n outer->Y[i] /= nout;\n diff->Y[i] = outer->Y[i] - inner->Y[i];\n }\n \n ninner = CreateCurve(nsamples);\n nouter = CreateCurve(nsamples);\n ndiff = CreateCurve(nsamples);\n \n for (i=0; iX[i] = nouter->X[i] = ndiff->X[i] = i;\n }\n for (i=0; iY[(int)inner->X[i]] += inner->Y[i];\n nouter->Y[(int)outer->X[i]] += outer->Y[i];\n }\n for (i=0; iY[i] = nouter->Y[i] - ninner->Y[i];\n }\n \n \n if (side == INTERIOR){\n output = CopyCurve(ninner);\n }\n else if (side==EXTERIOR){\n output = CopyCurve(nouter);\n }\n else if (side == BOTH){\n output = CopyCurve(ndiff);\n }\n else{\n printf(\"Invalid \\\"side\\\" option <%d>\\n\", side);\n exit(-1);\n }\n \n DestroyImage(&segments);\n DestroyCurve(&ninner);\n DestroyCurve(&nouter);\n DestroyCurve(&ndiff);\n\n DestroyImage(&contour);\n DestroyAdjRel(&A);\n DeAnnotate(&aimg);\n\n DestroyImage(&bin);\n DestroyImage(&mbb);\n DestroyCurve(&inner);\n DestroyCurve(&outer);\n DestroyCurve(&diff);\n\n return output;\n}\n\nFeatureVector1D *SS_ExtractionAlgorithm(Image *img){\n Curve *curve = NULL;\n FeatureVector1D *fv = NULL;\n \n curve = SS_ExtractionAlgorithm_(img, 5, 100, BOTH);\n fv = CurveTo1DFeatureVector(curve);\n \n DestroyCurve(&curve);\n return fv;\n}\n\n/***************SS SIMILARITY ALGORITHM*********************/\ndouble SS_getMin(double Dist1, double Dist2, double Dist3){\n if((Dist1<=Dist2) && (Dist1<=Dist3)) \n return(Dist1);\n else if((Dist2<=Dist1) && (Dist2<=Dist3)) \n return(Dist2);\n //else if((Dist3<=Dist1) && (Dist3<=Dist2)) \n return(Dist3);\n}\n\ndouble SS_OCS(FeatureVector1D *fv1, FeatureVector1D *fv2){\n \n int i,j, dim1 = fv1->n, dim2 = fv2->n;\n double temp_dist;\n double penalty;\n double *DISTANCE = NULL;\n \n DISTANCE=(double *) calloc((dim1+1)*(dim2+1),sizeof(double));\n\n penalty=20.0;\n /* OPTIMAL CORRESPONDENCE OF STRINGS\n */\n DISTANCE[0*(dim2+1)+0]=0;\n for(j=1;j<=dim2;j++)\n DISTANCE[0*(dim2+1)+j]=j * penalty;\n \n for(i=1;i<=dim1;i++)\n DISTANCE[i*(dim2+1)+0]=i * penalty;\n \n for(i=1;i<=dim1;i++)\n for(j=1;j<=dim2;j++)\n if(abs(i-j) < (5)){\n\ttemp_dist=abs(fv1->X[i-1]-fv2->X[j-1]);\n\t\t\n\tDISTANCE[i*(dim2+1)+j]= temp_dist +\n\t SS_getMin(DISTANCE[(i-1)*(dim2+1)+(j-1)],\n\t\t DISTANCE[(i-1)*(dim2+1)+(j)] + penalty,\n\t\t DISTANCE[(i)*(dim2+1)+(j-1)] + penalty); \n }\n \n temp_dist = DISTANCE[(dim1)*(dim2+1)+(dim2)]/dim2;\n free(DISTANCE);\n \n return temp_dist;\n}\n\ndouble SS_OCSMatching(FeatureVector1D *fv_1, FeatureVector1D *fv_2){\n double distance,temp_dist;\n int i,k;\n FeatureVector1D *temp1, *temp2, *fv1, *fv2;\n \n fv1 = CreateFeatureVector1D(fv_1->n);\n fv2 = CreateFeatureVector1D(fv_2->n);\n for (i = 0; in; i++){\n fv1->X[i] = 100*fv_1->X[i];\n fv2->X[i] = 100*fv_2->X[i];\n }\n \n temp1 = CreateFeatureVector1D(fv2->n);\n temp2 = CreateFeatureVector1D(fv2->n);\n \n temp_dist=INT_MAX; \n for(k=0; kn; k++){\n for(i=0;in;i++){\n temp2->X[i]=fv2->X[(i+k)%fv2->n];\n } \n distance= SS_OCS(fv1,temp2);\n if(temp_dist>distance) \n temp_dist=distance;\n }\n /***Taking the mirror of fv2 *****/\n for(i=0;in;i++){\n temp2->X[i]=fv2->X[(fv2->n-1)-i];\n }\n \n for(k=0; kn; k++){\n for(i=0;in;i++){\n temp1->X[i]= temp2->X[(i+k)%fv2->n];\n }\n distance=SS_OCS(fv1,temp1);\n if(temp_dist>distance) \n temp_dist=distance;\n }\n \n distance=temp_dist;\n DestroyFeatureVector1D(&temp1);\n DestroyFeatureVector1D(&temp2);\n DestroyFeatureVector1D(&fv1);\n DestroyFeatureVector1D(&fv2);\n return(distance);\n}\n\ndouble SS_DistanceAlgorithm(FeatureVector1D *fv1d1, FeatureVector1D *fv1d2){\n \n double dist;\n\n dist = SS_OCSMatching(fv1d1, fv1d2);\n \n return dist;\n}\n\n/* Metrics to measure the similarity between feature vectors*/\ndouble EuclideanDistance(FeatureVector1D *v1, FeatureVector1D *v2) { \n int i;\n double sum = 0.0;\n double z = 0.0;\n \n for (i = 0; i < v1->n ; i++){\n z = v1->X[i] - v2->X[i]; \n sum += z*z;\n }\n sum = sqrtf(sum);\n return (sum);\n}\n\ndouble L1_Distance(FeatureVector1D *v1, FeatureVector1D *v2) { \n int i;\n double sum = 0.0;\n \n for (i = 0; i < v1->n ; i++){\n sum += fabs(v1->X[i] - v2->X[i]); \n }\n return (sum);\n}\n\ndouble dLog(FeatureVector1D *fv1, FeatureVector1D *fv2)\n{\n\tint i;\n\tdouble sum = 0.0;\n\tdouble q,d;\n\t\n\tfor(i = 0; i < fv1->n; i++)\n\t{\n\t\n\t\tif(fv1->X[i] == 0)\n\t\t\tq = 0;\n\t\telse\n\t\t\tif((fv1->X[i] > 0) && (fv1->X[i] <= 1))\n\t\t\t\tq = 1;\n\t\t\telse\n\t\t\t\tq = log10(fv1->X[i])/log10(2);\n\t\tif(fv2->X[i] == 0)\n\t\t\td = 0;\n\t\telse\n\t\t\tif((fv2->X[i] > 0) && (fv2->X[i] <= 1))\n\t\t\t\td = 1;\n\t\t\telse\n\t\t\t\td = log10(fv2->X[i])/log10(2);\n\t\t\n\t\tsum = sum + fabs(q-d);\n\t}\n\n\t\n\treturn sum;\n}\n"},{"alpha_fraction":0.6212624311447144,"alphanum_fraction":0.6378737688064575,"avg_line_length":17.8125,"blob_id":"a6549da711eddf4db3975ba3a5d9bef25c38eb02","content_id":"8c9bbf96d1d4919aecba5b58b14ce72d9f3336a4","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":301,"license_type":"permissive","max_line_length":34,"num_lines":16,"path":"/MO445-descriptors/examples/file_name.py","repo_name":"RQuispeC/mo805-assignment7","src_encoding":"UTF-8","text":"import os\nimport os.path as osp\nimport numpy as np\n\nbase = \"mpeg7_pgm/\"\nfiles_names = os.listdir(base)\nfiles_names.sort()\nf = open(\"names.txt\", \"w\")\nfor l in files_names:\n\tf.write(l[:-4]+ '\\n')\nf.close()\n\nf2 = open(\"paths.txt\", \"w\")\nfor l in files_names:\n\tf2.write(osp.join(base, l)+ '\\n')\nf2.close()\n"},{"alpha_fraction":0.646030068397522,"alphanum_fraction":0.6603707671165466,"avg_line_length":32.64706039428711,"blob_id":"927be9ad849e7f4bcb9b18aaeae8dcd9b9a1ae98","content_id":"5e4518f89ebac6d9f78b6662404a7a457b764f22","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":2859,"license_type":"permissive","max_line_length":136,"num_lines":85,"path":"/precision_recall.py","repo_name":"RQuispeC/mo805-assignment7","src_encoding":"UTF-8","text":"import numpy as np\nimport os.path as osp\nimport matplotlib.pyplot as plt\n\ndef read_file(file_path):\n f = open(file_path, \"r\")\n data = []\n for line in f:\n data.append(line)\n return np.array(data)\n\ndef load_data(names_file, features_dir):\n ms_features = []\n ss_features = []\n ids = []\n names = read_file(names_file)\n names.sort()\n last_class = \"\"\n class_id = 0\n for name in names:\n name = name[:-1] #remove new line end\n ms_file_path = osp.join(features_dir, name + \"_MS.txt\")\n ss_file_path = osp.join(features_dir, name + \"_SS.txt\")\n ms_data = read_file(ms_file_path)\n ss_data = read_file(ss_file_path)\n ms_data = ms_data.astype(np.float)\n ss_data = ss_data.astype(np.float)\n ms_features.append(ms_data)\n ss_features.append(ss_data)\n data_class = name.split(\"-\")[0]\n if data_class != last_class:\n last_class = data_class\n class_id += 1\n ids.append(class_id)\n\n ids = np.array(ids)\n names = np.array(names)\n ms_features = np.array(ms_features)\n ss_features = np.array(ss_features)\n return ids, names, ms_features, ss_features\n\ndef dist(query_features, gallery_features):\n matrix = np.zeros((len(query_features), len(gallery_features)))\n q_pow = np.sum(query_features * query_features, axis = 1)\n g_pow = np.sum(gallery_features * gallery_features, axis = 1)\n prod = 2 * np.dot(query_features, np.transpose(gallery_features))\n matrix += np.transpose(np.tile(q_pow, (len(g_pow), 1)))\n matrix += np.tile(g_pow, (len(q_pow), 1))\n matrix -= prod\n return matrix\n\ndef precision_recall(distmat, q_ids, g_ids, max_rank = 20, gt_samples = 20):\n indices = np.argsort(distmat, axis=1)\n matches = (g_ids[indices] == q_ids[:, np.newaxis]).astype(np.int32)\n cnt = matches.cumsum(axis = 1)[:, :max_rank]\n\n den_precision = np.tile(np.arange(1, max_rank + 1), (len(q_ids), 1))\n den_recall = np.full((len(q_ids), max_rank), gt_samples)\n precision = cnt / den_precision\n recall = cnt / den_recall\n\n precision = np.average(precision, axis = 0)\n recall = np.average(recall, axis = 0)\n return precision, recall\n\nif __name__ == '__main__':\n ids, names, ms_features, ss_features = load_data(\"MO445-descriptors/examples/names.txt\", \"MO445-descriptors/examples/mpeg7_features/\")\n\n max_rank = 1400\n dismat_MS = dist(ms_features, ms_features)\n pms, rms = precision_recall(dismat_MS, ids, ids, max_rank=max_rank)\n\n dismat_SS = dist(ss_features, ss_features)\n pss, rss = precision_recall(dismat_SS, ids, ids, max_rank=max_rank)\n\n print(\"Generating Precision x Recall curve\")\n plt.title('Methods comparison - MO805 - Assignment 7')\n plt.plot(rms, pms, label = 'Multiscale fractal dimension')\n plt.plot(rss, pss, label = 'Segment saliences')\n plt.legend(loc = 'upper right')\n plt.xlim([0, 1])\n plt.ylim([0, 1])\n plt.ylabel('precision')\n plt.xlabel('recall')\n plt.savefig(\"precision_recall.png\")"}],"string":"[\n {\n \"alpha_fraction\": 0.6974790096282959,\n \"alphanum_fraction\": 0.756302535533905,\n \"avg_line_length\": 25.44444465637207,\n \"blob_id\": \"79ffa31d13d084d395573d8dc453f9033b77b035\",\n \"content_id\": \"ea52f9fa344f3d381f4a5cde47047a718517761e\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Makefile\",\n \"length_bytes\": 238,\n \"license_type\": \"permissive\",\n \"max_line_length\": 48,\n \"num_lines\": 9,\n \"path\": \"/Makefile\",\n \"repo_name\": \"RQuispeC/mo805-assignment7\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"all:\\n\\tmkdir MO445-descriptors/examples/mpeg7_pgm\\n\\tmkdir MO445-descriptors/examples/mpeg7_features\\n\\tpython3 convert_mpeg_pgm.py\\n\\tcd MO445-descriptors/examples && \\\\\\n\\tpython3 file_name.py && \\\\\\n\\tmake && \\\\\\n\\t./test\\n\\tpython3 precision_recall.py\\n\"\n },\n {\n \"alpha_fraction\": 0.69065260887146,\n \"alphanum_fraction\": 0.7064155340194702,\n \"avg_line_length\": 28.78403663635254,\n \"blob_id\": \"116a173bfe865c65050d0f9ed4c1129c3fb58414\",\n \"content_id\": \"0f59cd50db6ffd02fd5c009e70111a21c17e019b\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C\",\n \"length_bytes\": 12688,\n \"license_type\": \"permissive\",\n \"max_line_length\": 111,\n \"num_lines\": 426,\n \"path\": \"/MO445-descriptors/include/MO445.h\",\n \"repo_name\": \"RQuispeC/mo805-assignment7\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#ifndef _MO445_H_\\n#define _MO445_H_\\n\\n#define LOW 0\\n#define HIGH 1\\n#ifndef FALSE\\n#define FALSE 0\\n#endif\\n#ifndef TRUE\\n#define TRUE 1\\n#endif\\n\\n#ifndef __cplusplus\\n#ifndef _WIN32\\n#ifndef __cplusplus\\ntypedef enum boolean {false,true} bool;\\n#endif\\n#else\\ntypedef unsigned short ushort;\\n#endif\\n#endif\\n\\n#ifndef MAX\\n#define MAX(x,y) (((x) > (y))?(x):(y))\\n#endif\\n\\n#ifndef MIN\\n#define MIN(x,y) (((x) < (y))?(x):(y))\\n#endif\\n\\n#define SetTieBreak(a,b) a->C.tiebreak=b \\n\\n#define MSG1 \\\"Cannot allocate memory space\\\"\\n#define MSG2 \\\"Cannot open file\\\"\\n#define SIZE 64\\n#define PI 3.1415926536\\n#define ROUND(x) ((x < 0)?(int)(x-0.5):(int)(x+0.5))\\n#define NIL -1\\n#define WHITE 0 \\n#define GRAY 1\\n#define BLACK 2\\n#define INCREASING 1\\n#define DECREASING 0\\n#define HISTOGRAMSIZE 180\\n#define LIFOBREAK 1\\n#define FIFOBREAK 0\\n#define INTERIOR 0\\n#define EXTERIOR 1\\n#define HEAP_DAD(i) ((i - 1) / 2)\\n#define HEAP_LEFTSON(i) (2 * i + 1)\\n#define HEAP_RIGHTSON(i) (2 * i + 2)\\n#define BOTH 2\\n\\n#include \\n#include \\n#include \\n#include \\n#include \\n#include \\n\\n/* Common operations functions ************************/\\nint NCFgets(char *s, int m, FILE *f); \\nint *AllocIntArray(int n);\\ndouble *AllocDoubleArray(int n);\\nfloat *AllocFloatArray(int n); \\nchar *AllocCharArray(int n); /* It allocates 1D array of n characters */\\n\\n/* Errors functions *********************************/\\nvoid Error(char *msg,char *func); \\n\\n/* Data structures **********************************/\\n/* BIC */\\ntypedef struct {\\n int color;\\n int frequency;\\n}Property;\\n\\ntypedef struct {\\n unsigned long colorH[SIZE];\\n unsigned long lowH[SIZE];\\n unsigned long highH[SIZE];\\n}VisualFeature;\\n\\ntypedef struct {\\n unsigned char colorH[SIZE];\\n unsigned char lowH[SIZE];\\n unsigned char highH[SIZE];\\n}CompressedVisualFeature;\\n\\n/* pgm images */\\ntypedef struct _image {\\n int *val;\\n int ncols,nrows;\\n int *tbrow;\\n} Image;\\n\\n/* ppm images */\\ntypedef struct cimage {\\n Image *C[3];\\n} CImage;\\n\\ntypedef struct _FeatureVector1D {\\n double *X;\\n int n; \\n} FeatureVector1D;\\n\\ntypedef struct _FeatureVector2D {\\n double *X;\\n double *Y;\\n int n; \\n} FeatureVector2D;\\n\\ntypedef struct _curve {\\n double *X;\\n double *Y;\\n int n; \\n} Curve;\\n\\ntypedef struct _curve3d { /* 3D Curve */\\n double *X;\\n double *Y;\\n double *Z;\\n int n; \\n} Curve3D;\\n\\ntypedef struct _adjrel {\\n int *dx;\\n int *dy;\\n int n;\\n} AdjRel;\\n\\ntypedef struct _pixel {\\n int x,y;\\n} Pixel;\\n\\ntypedef struct{\\n int length; /* length of the boundary */\\n int *X; /* X values of each boundary point from 0 to length-1 */\\n int *Y; /* Y values of each boundary point from 0 to length-1 */\\n} boundary_type;\\n\\ntypedef struct{\\n int length; /* length of the boundary */\\n int *mean; /* mean value BAS function */\\n int *second; \\n int *third;\\n} representation_type;\\n\\ntypedef struct _DImage{\\n double *val;\\n int ncols,nrows;\\n int *tbrow;\\n} DImage;\\n\\ntypedef struct _tensorscale{\\n DImage *anisotropy;\\n DImage *orientation;\\n DImage *thickness;\\n\\n int m_pairs;\\n}TensorScale;\\n\\ntypedef struct _vector{\\n float x;\\n float y;\\n float z;\\n} Vector, Point, Vertex;\\n\\ntypedef struct _node { \\n int next; /* next node */\\n int prev; /* prev node */\\n char color; /* WHITE=0, GRAY=1, BLACK=2 */\\n} Node;\\n\\ntypedef struct _doublylinkedlists {\\n Node *elem; /* all possible doubly-linked lists of the circular queue */\\n int nelems; /* total number of elements */\\n} DoublyLinkedLists; \\n\\ntypedef struct _circularqueue { \\n int *first; /* list of the first elements of each doubly-linked list */\\n int *last; /* list of the last elements of each doubly-linked list */\\n int nbuckets; /* number of buckets in the circular queue */\\n int current; /* current bucket */\\n char tiebreak; /* 1 is LIFO, 0 is FIFO (default) */\\n} CircularQueue;\\n\\ntypedef struct _queue { /* Priority queue by Dial implemented as\\n proposed by A. Falcao */\\n CircularQueue C;\\n DoublyLinkedLists L;\\n} Queue;\\n\\ntypedef struct _polynom { /* Polynomial */\\n double *coef; /* a0*x^0 + a1*x^1 + ... + an*x^n */ \\n int n; /* degree n */\\n} Polynom;\\n\\ntypedef struct _set {\\n int elem;\\n struct _set *next;\\n} Set;\\n\\ntypedef struct _annimg {\\n Image *img;\\n Image *grad;\\n Image *cost;\\n Image *label;\\n Image *pred;\\n Image *root;\\n Set *seed;\\n} AnnImg;\\n\\ntypedef struct _heap {\\n int *cost;\\n char *color;\\n int *pixel;\\n int *pos;\\n int last;\\n int n;\\n} Heap;\\n\\ntypedef struct _adjpxl {\\n int *dp;\\n int n;\\n} AdjPxl;\\n\\n/*Working with images *****************************/\\n\\n/* pgm images */\\nImage *CreateImage(int ncols,int nrows);\\nvoid DestroyImage(Image **img);\\nImage *ReadImage(char *filename);\\nImage *MBB(Image *img);\\nImage *ROI(Image *img, int xl, int yl, int xr, int yr);\\nImage *AddFrame(Image *img, int sz, int value);\\nvoid SetImage(Image *img, int value);\\nvoid WriteImage(Image *img,char *filename);\\n\\n/* ppm images */\\nCImage *CreateCImage(int ncols, int nrows);\\nvoid DestroyCImage(CImage **cimg);\\nCImage *ReadCImage(char *filename);\\n\\n/* auxiliary functions ****************************/\\nCurve *CreateCurve(int n);\\nvoid DestroyCurve(Curve **curve);\\nFeatureVector1D *CurveTo1DFeatureVector(Curve *curve);\\nFeatureVector1D *CreateFeatureVector1D(int n);\\nvoid DestroyFeatureVector1D(FeatureVector1D **desc);\\nvoid WriteFeatureVector1D(FeatureVector1D *desc,char *filename);\\nAdjRel *CreateAdjRel(int n);\\nvoid DestroyAdjRel(AdjRel **A);\\nAdjRel *LeftSide(AdjRel *A);\\nAdjRel *RightSide(AdjRel *A);\\nAdjRel *Circular(float r);\\nbool ValidPixel(Image *img, int x, int y);\\nbool ValidContPoint(Image *bin, AdjRel *L, AdjRel *R, int p);\\nImage *LabelContPixel(Image *bin);\\nCurve3D *CreateCurve3D(int n);\\nvoid DestroyCurve3D(Curve3D **curve);\\nvoid SortCurve3D(Curve3D *curve, int left, int right, char order);\\nint PartCurve3D (Curve3D *curve, int left, int right, char order);\\nint FFT(int dir, long nn, double *x, double *y);\\nImage *LabelContour(Image *bin);\\nvoid Warning(char *msg,char *func); \\nImage *Scale(Image *img, float Sx, float Sy) ;\\nDImage *CreateDImage(int ncols, int nrows);\\nvoid DestroyDImage(DImage **dimg);\\nvoid DestroyImage(Image **img);\\nint MaximumValue(Image *img);\\nQueue *CreateQueue(int nbuckets, int nelems);\\nvoid DestroyQueue(Queue **Q);\\nint EmptyQueue(Queue *Q);\\nvoid InsertQueue(Queue *Q, int bucket, int elem);\\nint RemoveQueue(Queue *Q);\\nvoid UpdateQueue(Queue *Q, int elem, int from, int to);\\nvoid ResetQueue(Queue *Q);\\nvoid RemoveQueueElem(Queue *Q, int elem, int bucket);\\nCurve *SamplePolynom(Polynom *P, double from, double to, int nbins);\\nPolynom *CreatePolynom(int degree);\\nvoid DestroyPolynom(Polynom **P);\\nPolynom *DerivPolynom(Polynom *P);\\nPolynom *Regression(Curve *curve, int degree);\\nPolynom *MSFractal(Image *bin,int maxdist,int degree,double lower,double higher,int reg,double from,double to);\\nAnnImg *Annotate(Image *img, Image *cost, Image *label);\\nAdjRel *ComplAdj(AdjRel *A1, AdjRel *A2);\\nvoid InsertSet(Set **S, int elem);\\nint RemoveSet(Set **S);\\nint Seed(Image *pred, int p);\\nImage *CompPaths(Image *pred);\\nImage *Perimeter(Image *bin);\\nCurve3D *Saliences(Image *bin, int maxdist);\\nImage *MSSkel(Image *bin, char side);\\nvoid DestroyAdjPxl(AdjPxl **N);\\nCurve3D *CompSaliences(AnnImg *aimg, int maxcost);\\nImage *RemFrame(Image *fimg, int sz);\\nAdjPxl *AdjPixels(Image *img, AdjRel *A);\\nImage *Abs(Image *img);\\nCurve3D *RemSaliencesByAngle(Curve3D *curve,int radius, int angle);\\nImage *LabelBinComp(Image *bin, AdjRel *A);\\nCurve3D *SkelSaliences(Image *skel, int maxdist, int angle) ;\\nImage *Skeleton(Image *msskel, float perc);\\nImage *CompMSSkel(AnnImg *aimg);\\nvoid iftDilation(AnnImg *aimg, AdjRel *A); /* by Dial */\\nvoid InvertXY(Curve *curve);\\nCurve *CopyCurve(Curve *curve);\\nvoid SortCurve(Curve *curve, int left, int right, char order);\\nint PartCurve (Curve *curve, int left, int right, char order);\\nCurve *Histogram(Image *img);\\nvoid DestroySet(Set **S);\\nvoid DeAnnotate(AnnImg **aimg);\\nint FrameSize(AdjRel *A);\\nvoid Change(int *a, int *b);\\nHeap *CreateHeap(int n, int *cost);\\nvoid DestroyHeap(Heap **H);\\nbool InsertHeap(Heap *H, int pixel);\\nbool RemoveHeap(Heap *H, int *pixel);\\nvoid GoUpHeap(Heap *H, int i);\\nbool IsEmptyHeap(Heap *H);\\nbool HeapIsEmpty(Heap *H);\\nvoid GoDownHeap(Heap *H, int i);\\nbool IsFullHeap(Heap *H);\\nvoid GoUpHeap(Heap *H, int i);\\nFeatureVector2D *CurveTo2DFeatureVector(Curve *curve);\\n/* Descriptor functions ***************************/\\n\\n/* BIC */\\n/* auxiliary functions */\\nCurve *BIC(CImage *img);\\nvoid Write_visual_features(char *filename,char *dbname, CompressedVisualFeature *cvf);\\nCompressedVisualFeature *Extract_visual_features(CImage *img);\\ndouble gray_level_BIC(Image *img1, Image *img2);\\n\\n/* Fourier Descriptor */\\n/* auxiliary functions */\\ndouble Cabs(double x, double y);\\nCurve *Image2Curve(Image *img);\\nCurve *FourierDescriptor(Image *img);\\n\\n/* Moments Invariant */\\n/* auxiliary functions */\\ndouble MomentPQ(int p, int q, Image *img, int max);\\nCurve *MomentInv(Image *img);\\nCurve *MomentInvariant(Image *img); // contorno e objeto inteiro\\n\\n/* BAS */\\n/* auxiliary functions */\\nCurve *BAS(Image *in,int rsp,int nsamples);\\n\\n/* Tensor Scale */\\n/* auxiliary functions */\\nTensorScale *CreateBinaryTensorScale(Image *bin, int m_pairs);\\nvoid DestroyTensorScale(TensorScale **ts);\\nfloat *TSOrientationHistogram(TensorScale *ts);\\nImage *TSEDistTrans(Image *bin);\\n\\n/* MultiScale Fractal Dimension*/\\n/* auxiliary functions */\\nCurve *PolynomToFractalCurve(Polynom *P, double lower, double higher, int nbins);\\nCurve *ContourMSFractal(Image *in);\\n\\n/* Contour Saliences */\\n/* auxiliary functions */\\nCurve3D *SkelCont(Image *bin, int maxdist, int threshold, int angle, char side);\\nCurve3D *iftContourSaliences(Image *bin,int threshold_in,int threshold_out,int angle_in,int angle_out);\\nCurve *ContourSaliences(Image *in);\\nvoid DescInvertXY(FeatureVector2D *desc);\\nFeatureVector2D *CreateFeatureVector2D(int n);\\ndouble ContSalieDistance(FeatureVector2D *D1, FeatureVector2D *D2);\\nFeatureVector2D *CircularRotation(FeatureVector2D *descriptor, double delta);\\nvoid DestroyFeatureVector2D(FeatureVector2D **desc);\\nvoid SortFeatureVector2D(FeatureVector2D *desc, int left, int right, char order);\\nint PartFeatureVector2D (FeatureVector2D *desc, int left, int right, char order);\\nvoid WriteFeatureVector2D(FeatureVector2D *desc,char *filename);\\nFeatureVector2D *CopyFeatureVector2D(FeatureVector2D *desc);\\nvoid DestroyFeatureVector2D(FeatureVector2D **desc);\\ndouble Matching(FeatureVector2D *descriptor1, FeatureVector2D *descriptor2, int order);\\n\\n/* Segment Saliences */\\n/* auxiliary functions */\\nCurve *SS_ExtractionAlgorithm_(Image *in, int maxdist, int nsamples, int side);\\ndouble SS_OCSMatching(FeatureVector1D *fv_1, FeatureVector1D *fv_2);\\ndouble SS_OCS(FeatureVector1D *fv1, FeatureVector1D *fv2);\\ndouble SS_getMin(double Dist1, double Dist2, double Dist3);\\n\\n/* call functions *********************************/\\n/* BIC */\\nFeatureVector1D *BIC_ExtractionAlgorithm(CImage *in); /*BIC extractor*/\\ndouble BIC_DistanceAlgorithm(FeatureVector1D *fv1, FeatureVector1D *fv2); /*BIC similarity*/\\n\\n/* Fourier Descriptor */\\nFeatureVector1D *FourierDescriptor_ExtractionAlgorithm(Image *in);/* in is a binary image*/\\ndouble Fourier_DistanceAlgorithm(FeatureVector1D *fv1, FeatureVector1D *fv2); /*fourier similarity*/\\n\\n/* Moments Invariant */\\nFeatureVector1D *MomentInvariant_ExtractionAlgorithm(Image *in);/*in is a binary image*/\\ndouble MomentInvariant_DistanceAlgorithm(FeatureVector1D *fv1, FeatureVector1D *fv2);\\n\\n/* BAS */\\nFeatureVector1D *BAS_ExtractionAlgorithm(Image *in,int rsp,int nsamples);\\ndouble BAS_DistanceAlgorithm(FeatureVector1D *c1, FeatureVector1D *c2);\\n\\n/* Tensor Scale */\\nFeatureVector1D *TensorScale_ExtractionAlgorithm(Image *in);\\ndouble TensorScale_DistanceAlgorithm(FeatureVector1D *c1, FeatureVector1D *c2);\\n\\n/* Multiscale Fractal Dimension */\\nFeatureVector1D *MS_ExtractionAlgorithm(Image *img);\\ndouble MS_DistanceAlgorithm(FeatureVector1D *fv1, FeatureVector1D *fv2); \\n\\n/* Contour Saliences */\\nFeatureVector2D *CS_ExtractionAlgorithm(Image *img);\\ndouble CS_DistanceAlgorithm(FeatureVector2D *descriptor1, FeatureVector2D *descriptor2);\\n\\n/* Segment Saliences */\\nFeatureVector1D *SS_ExtractionAlgorithm(Image *img);\\ndouble SS_DistanceAlgorithm(FeatureVector1D *fv1d1, FeatureVector1D *fv1d2);\\n\\n/* Metrics to measure the similarity between feature vectors*/\\ndouble EuclideanDistance(FeatureVector1D *v1, FeatureVector1D *v2);\\ndouble L1_Distance(FeatureVector1D *v1, FeatureVector1D *v2);\\nfloat TSHistogramMatch(FeatureVector1D *fv1, FeatureVector1D *fv2, int *offset);\\ndouble dLog(FeatureVector1D *fv1, FeatureVector1D *fv2);\\n\\n#endif\\n\"\n },\n {\n \"alpha_fraction\": 0.7578834891319275,\n \"alphanum_fraction\": 0.770176351070404,\n \"avg_line_length\": 38.787235260009766,\n \"blob_id\": \"0ab1611960a6bc72f0c2c01f46fd8663ea559b1f\",\n \"content_id\": \"395b4797c9a810e4972e450f822aedc154f4bf8a\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Text\",\n \"length_bytes\": 1871,\n \"license_type\": \"permissive\",\n \"max_line_length\": 88,\n \"num_lines\": 47,\n \"path\": \"/MO445-descriptors/readme.txt\",\n \"repo_name\": \"RQuispeC/mo805-assignment7\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"The purpose of this package is to provide the source code of some\\nimage descriptors for the image analysis course (MO445). Each\\ndescriptor is represented by a feature vector and a similarity\\n(distance) function, and its corresponding paper can be found in the\\nsubdirectory docs.\\n\\nFollow the steps:\\n\\n1 - Extract the files in MO445.tar.gz.\\n\\n2 - Go to the folder MO445 and execute the Makefile\\n\\n3 - Go to the folder examples (MO445/examples), which contains one\\nexample file \\\"test.c\\\" and two images to execute the program.\\n\\n4 - Execute the Makefile. It will generate a executable file \\\"test\\\"\\n\\n5 - Run ./test\\n\\n6 - Some files corresponding to the descriptors will be generated, such as:\\n\\n- bas_ -> Descriptor Beam Angle Statistics (BAS) (SHAPE)\\n- bic_.txt -> Border/Interior Pixel Classification (BIC) (COLOR/TEXTURE)\\n- moments_.txt -> Moment Invariants (MI) (SHAPE)\\n- fourier_.txt -> Fourier Descriptor (SHAPE)\\n- tensorscale_.txt -> Tensor Scale Descriptor (SHAPE)\\n- multiscales_.txt -> Multiscale Fractal Dimension (SHAPE)\\n- contoursaliences_.txt -> Contour Saliences (SHAPE)\\n- segmentsaliences_.txt -> Segment Saliences (SHAPE)\\n\\nAll descriptors have two basic functions: extraction and\\nsimilarity (distance). Example for BAS:\\n\\n- FeatureVector1D *BAS_ExtractionAlgorithm(Image *in,int rsp,int nsamples);\\n- double BAS_DistanceAlgorithm(FeatureVector1D *c1, FeatureVector1D *c2);\\n\\nThe extraction algorithm extracts the feature vector for an image and\\nthe similarity function returns the distance between two images. Fell\\nfree to modify the feature vector size.\\n\\nThe figures and the results obtained can be found in ./figs and\\n./results directories, respectively.\\n\\nIf you have questions, please contact Joao Paulo Papa\\n(jpaulo@ic.unicamp.br) or Alexandre Falcao (afalcao@ic.unicamp.br)\\n\\nEnjoy!\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.7488822937011719,\n \"alphanum_fraction\": 0.7809240221977234,\n \"avg_line_length\": 30.20930290222168,\n \"blob_id\": \"338c081ca6007fced7188e51229c067e05c790c7\",\n \"content_id\": \"18c50f51f4c9b90763e183ba2015fea74f1463ba\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 1342,\n \"license_type\": \"permissive\",\n \"max_line_length\": 226,\n \"num_lines\": 43,\n \"path\": \"/README.md\",\n \"repo_name\": \"RQuispeC/mo805-assignment7\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# Precision vs Recall\\nThis repo implements the assignment 7 of [MO805](http://www.ic.unicamp.br/~rtorres/mo805A_19s1/07-assignment.pdf) at UNICAMP.\\n\\n\\n\\n# Implemented/Modified scripts\\n\\n* `convert_mpeg_pgm.py` converts the `.gif` images of `mpeg7/`dataset to `.pgm` and stores them inside `MO445-descriptors/examples/mpeg7_pgm`\\n\\n* `MO445-descriptors/examples/test.c` extracts Multiscale Fractal Dimension and Segment Saliences features and stores them inside `MO445-descriptors/examples/mpeg7_features`\\n\\n* `MO445-descriptors/examples/file_name.py` is a small scripts that creates files with the paths and names of `MO445-descriptors/examples/mpeg7_pgm`.\\n\\n* `precision_recall.py` computes the precision x recall curve and plots it in `precision_recall.png`\\n\\n# Replicate Results\\n\\nClone the repository\\n\\n```\\ngit clone https://github.com/RQuispeC/mo805-assignment7.git\\n```\\n\\nThen run all the scripts using the available Makefile\\n\\n```\\ncd mo805-assignment7\\nmake\\n```\\n\\n# Prerequisites\\n\\nThe code was tested under a linux distribution with :\\n\\n* GCC\\n* Python3\\n* Numpy\\n* MatplotLib\\n* PIL\\n\\n# Notes\\n\\nI used euclidean distance to compare feacture vectors for both Multiscale fractal and Segment salience descriptors. MO455 code offers a different distance function for Segment salience but euclidean may get better performance.\\n\"\n },\n {\n \"alpha_fraction\": 0.5056179761886597,\n \"alphanum_fraction\": 0.6029962301254272,\n \"avg_line_length\": 18.071428298950195,\n \"blob_id\": \"d9662fa559a8c53b9f411caafca67e27c4c94b3b\",\n \"content_id\": \"1e513a0fdab141c0f9bc14fa409f07345a522af2\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Makefile\",\n \"length_bytes\": 267,\n \"license_type\": \"permissive\",\n \"max_line_length\": 61,\n \"num_lines\": 14,\n \"path\": \"/MO445-descriptors/examples/Makefile\",\n \"repo_name\": \"RQuispeC/mo805-assignment7\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"CFLAGS = -Wall -O3\\nMO445LIB = -L../lib\\nMO445FLAGS = -I../include\\nCC=gcc\\nFLAGS= -O3 -Wall\\n\\nall: libMO445 test\\n\\nlibMO445:\\n\\t$(MAKE) -C ../\\ntest: libMO445 \\n\\t$(CC) $(MO445FLAGS) test.c $(MO445LIB) -o test -lMO445 -lm\\nclean:\\n\\trm -f *~ test.o test ../lib/*.a ../obj/*.o\\n\"\n },\n {\n \"alpha_fraction\": 0.605215311050415,\n \"alphanum_fraction\": 0.6264402866363525,\n \"avg_line_length\": 19.873416900634766,\n \"blob_id\": \"543bab6b6825af966db55c15acc121cf76e72131\",\n \"content_id\": \"3db79fe9c47bedbb86032481856591b86d25966c\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C\",\n \"length_bytes\": 1649,\n \"license_type\": \"permissive\",\n \"max_line_length\": 52,\n \"num_lines\": 79,\n \"path\": \"/MO445-descriptors/examples/test.c\",\n \"repo_name\": \"RQuispeC/mo805-assignment7\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#include \\\"MO445.h\\\"\\n#include \\n#include \\n\\nconst int LIMIT = 1400;\\n\\nchar* paths[1400];\\nchar* names[1400];\\nint max_len = 50;\\nvoid chomp(char *s){\\n\\ts[strcspn(s, \\\"\\\\n\\\")] = '\\\\0';\\n}\\n\\nvoid read_dataset_data(){\\n\\tFILE *fp;\\n\\tchar *line = NULL;\\n\\tsize_t len = 255;\\n\\tline = malloc(sizeof(char) * max_len);\\n\\n\\tfp = fopen(\\\"paths.txt\\\", \\\"r\\\");\\n\\n\\tint ind = 0;\\n\\twhile ((fgets(line, len, fp)) != NULL)\\n\\t{\\n\\t\\tpaths[ind] = malloc(sizeof(char) * max_len);\\n\\t\\tchomp(line);\\n\\t\\tstrcpy(paths[ind], line);\\n\\t\\t//printf(\\\"%s\\\\n\\\", paths[ind]);\\n\\t\\tind += 1;\\n\\t}\\n\\n\\tfp = fopen(\\\"names.txt\\\", \\\"r\\\");\\n\\n\\tind = 0;\\n\\twhile ((fgets(line, len, fp)) != NULL)\\n\\t{\\n\\t\\tnames[ind] = malloc(sizeof(char) * max_len);\\n\\t\\tchomp(line);\\n\\t\\tstrcpy(names[ind], line);\\n\\t\\t//printf(\\\"%s\\\\n\\\", names[ind]);\\n\\t\\tind += 1;\\n\\t}\\n\\tfree(line);\\n}\\n\\nint main(int argc,char **argv){\\n\\n\\tread_dataset_data();\\n\\tprintf(\\\"Loaded data for files\\\\n\\\");\\n\\n\\tfor (int i = 0; i < LIMIT; i++){\\n\\t\\tprintf(\\\"Extracting features of %s\\\\n\\\", names[i]);\\n\\n\\t\\tImage *img = NULL;\\n\\t\\tFeatureVector1D *fvMS = NULL, *fvSS = NULL;\\n\\t\\tchar *outfile_name = NULL;\\n\\t\\toutfile_name = malloc(sizeof(char) * 3 * max_len);\\n\\n\\t\\timg = ReadImage(paths[i]);\\n\\t\\tfvMS = MS_ExtractionAlgorithm(img);\\n\\t\\tstrcpy(outfile_name,\\\"mpeg7_features/\\\");\\n\\t\\tstrcat(outfile_name, names[i]);\\n\\t\\tstrcat(outfile_name, \\\"_MS.txt\\\");\\n\\t\\tWriteFeatureVector1D(fvMS, outfile_name);\\n\\n\\t\\tfvSS = SS_ExtractionAlgorithm(img);\\n\\t\\tstrcpy(outfile_name, \\\"mpeg7_features/\\\");\\n\\t\\tstrcat(outfile_name, names[i]);\\n\\t\\tstrcat(outfile_name, \\\"_SS.txt\\\");\\n\\t\\tWriteFeatureVector1D(fvSS, outfile_name);\\n\\n\\t\\tDestroyFeatureVector1D(&fvSS);\\n\\t\\tDestroyFeatureVector1D(&fvMS);\\n\\t\\tDestroyImage(&img);\\n\\t}\\n\\tfprintf(stderr,\\\"\\\\n\\\");\\n\\n\\treturn 0;\\n}\\n\"\n },\n {\n \"alpha_fraction\": 0.6238044500350952,\n \"alphanum_fraction\": 0.6376195549964905,\n \"avg_line_length\": 23.102563858032227,\n \"blob_id\": \"8f555ac62b0b9bf7aa6ea5537272da24455c6189\",\n \"content_id\": \"64a10c4fb9cc22fc013002fbe075d6ad892161ef\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 941,\n \"license_type\": \"permissive\",\n \"max_line_length\": 76,\n \"num_lines\": 39,\n \"path\": \"/convert_mpeg_pgm.py\",\n \"repo_name\": \"RQuispeC/mo805-assignment7\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from PIL import Image\\nimport numpy as np\\nimport os\\nimport os.path as osp\\n\\ndef to_string(x):\\n\\treturn [str(i) for i in x]\\n\\ndef check_binary(x):\\n\\tfor pixel in x:\\n\\t\\tif pixel != \\\"0\\\" and pixel != \\\"1\\\":\\n\\t\\t\\tprint(\\\"ERROR\\\")\\n\\t\\t\\treturn\\n\\ndef convert_numpy_str(x):\\n\\tstr_x = to_string(x)\\n\\tcheck_binary(str_x)\\n\\tans = \\\" \\\".join(str_x)\\n\\treturn ans\\n\\ndef convert_image_pgm(img, file_path):\\n\\timg = np.array(img)\\n\\timg = img // np.max(img)\\n\\tfile = open(file_path, \\\"w\\\")\\n\\tfile.write(\\\"P2\\\\n\\\")\\n\\tfile.write(\\\"{} {}\\\\n\\\".format(img.shape[1], img.shape[0]))\\n\\tfile.write(\\\"1\\\\n\\\")\\n\\tfor l in img:\\n\\t\\tfile.write(convert_numpy_str(l)+\\\" \\\\n\\\")\\n\\tfile.close()\\n\\nif __name__ == '__main__':\\n\\tfile_names = os.listdir(\\\"mpeg7/\\\")\\n\\tfor file_name in file_names:\\n\\t\\timg = Image.open(osp.join(\\\"mpeg7/\\\", file_name))\\n\\t\\tprint(\\\"Converting \\\", file_name)\\n\\t\\tout_file_name = file_name[:-3] + \\\"pgm\\\"\\n\\t\\tout_dir = osp.join(\\\"MO445-descriptors/examples/mpeg7_pgm/\\\", out_file_name)\\n\\t\\tconvert_image_pgm(img, out_dir)\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.4759206771850586,\n \"alphanum_fraction\": 0.5722379684448242,\n \"avg_line_length\": 15.571428298950195,\n \"blob_id\": \"283275dbcac9add0090c21817039915bdf658146\",\n \"content_id\": \"f809368cd2a2213890e1b388059a1db11ddd3756\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Makefile\",\n \"length_bytes\": 353,\n \"license_type\": \"permissive\",\n \"max_line_length\": 46,\n \"num_lines\": 21,\n \"path\": \"/MO445-descriptors/Makefile\",\n \"repo_name\": \"RQuispeC/mo805-assignment7\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"LIB=./lib\\nINCLUDE=./include\\nSRC=./src\\nOBJ=./obj\\nFLAGS= -O3 -Wall\\n\\nlibMO445: $(LIB)/libMO445.a\\n\\techo \\\"libMO445.a built...\\\"\\n\\n$(LIB)/libMO445.a: \\\\\\n$(OBJ)/MO445.o \\\\\\n\\n\\tar csr $(LIB)/libMO445.a \\\\\\n$(OBJ)/MO445.o \\\\\\n\\n$(OBJ)/MO445.o: $(SRC)/MO445.c\\n\\tgcc $(FLAGS) -c $(SRC)/MO445.c -I$(INCLUDE) \\\\\\n\\t-o $(OBJ)/MO445.o\\n\\nclean: \\n\\trm $(LIB)/lib*.a; rm $(OBJ)/*.o\\n\\n\\n\\n\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.5110331773757935,\n \"alphanum_fraction\": 0.5371482968330383,\n \"avg_line_length\": 20.825843811035156,\n \"blob_id\": \"af40a8a3fccf703da8d6f73a316e4bc3f922f025\",\n \"content_id\": \"3afcb9e1b54d1ee03943ed29a89c8ec9c480f514\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C\",\n \"length_bytes\": 101514,\n \"license_type\": \"permissive\",\n \"max_line_length\": 106,\n \"num_lines\": 4651,\n \"path\": \"/MO445-descriptors/src/MO445.c\",\n \"repo_name\": \"RQuispeC/mo805-assignment7\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#include \\\"MO445.h\\\"\\n\\n/* Common operations functions ************************/\\nint NCFgets(char *s, int m, FILE *f) {\\n while(fgets(s,m,f)!=NULL)\\n if (s[0]!='#') return 1;\\n return 0;\\n}\\n\\nint *AllocIntArray(int n)\\n{\\n int *v=NULL;\\n v = (int *) calloc(n,sizeof(int));\\n if (v == NULL)\\n Error(MSG1,\\\"AllocIntArray\\\");\\n return(v);\\n}\\n\\nfloat *AllocFloatArray(int n)\\n{\\n float *v=NULL;\\n v = (float *) calloc(n,sizeof(float));\\n if (v == NULL)\\n Error(MSG1,\\\"AllocFloatArray\\\");\\n return(v);\\n}\\n\\ndouble *AllocDoubleArray(int n)\\n{\\n double *v=NULL;\\n v = (double *) calloc(n,sizeof(double));\\n if (v == NULL)\\n Error(MSG1,\\\"AllocDoubleArray\\\");\\n return(v);\\n}\\n\\nchar *AllocCharArray(int n)\\n{\\n char *v=NULL;\\n v = (char *) calloc(n,sizeof(char));\\n if (v == NULL)\\n Error(MSG1,\\\"AllocCharArray\\\");\\n return(v);\\n}\\n\\n/* Errors functions *********************************/\\nvoid Error(char *msg,char *func){ \\n fprintf(stderr,\\\"Error:%s in %s\\\\n\\\",msg,func);\\n exit(-1);\\n}\\n\\n/*Working with images *****************************/\\n/* pgm images */\\nImage *CreateImage(int ncols, int nrows)\\n{\\n Image *img=NULL;\\n int i;\\n\\n img = (Image *) calloc(1,sizeof(Image));\\n if (img == NULL){\\n Error(MSG1,\\\"CreateImage\\\");\\n }\\n\\n img->val = AllocIntArray(nrows*ncols);\\n img->tbrow = AllocIntArray(nrows);\\n\\n img->tbrow[0]=0;\\n for (i=1; i < nrows; i++)\\n img->tbrow[i]=img->tbrow[i-1]+ncols;\\n img->ncols = ncols;\\n img->nrows = nrows;\\n \\n return(img);\\n}\\n\\nvoid DestroyImage(Image **img){\\n Image *aux;\\n\\n aux = *img;\\n if(aux != NULL){\\n if (aux->val != NULL) free(aux->val); \\n if (aux->tbrow != NULL) free(aux->tbrow);\\n free(aux); \\n *img = NULL;\\n }\\n}\\n\\nImage *ReadImage(char *filename)\\n{\\n FILE *fp=NULL;\\n unsigned char *value=NULL;\\n char type[10];\\n int i,ncols,nrows,n;\\n Image *img=NULL;\\n char z[256];\\n\\n fp = fopen(filename,\\\"rb\\\");\\n if (fp == NULL){\\n fprintf(stderr,\\\"Cannot open %s\\\\n\\\",filename);\\n exit(-1);\\n }\\n fscanf(fp,\\\"%s\\\\n\\\",type);\\n if((strcmp(type,\\\"P5\\\")==0)){\\n NCFgets(z,255,fp);\\n sscanf(z,\\\"%d %d\\\\n\\\",&ncols,&nrows);\\n n = ncols*nrows;\\n NCFgets(z,255,fp);\\n sscanf(z,\\\"%d\\\\n\\\",&i);\\n value = (unsigned char *)calloc(n,sizeof(unsigned char));\\n if (value != NULL){\\n fread(value,sizeof(unsigned char),n,fp);\\n }else{\\n fprintf(stderr,\\\"Insufficient memory in ReadImage\\\\n\\\");\\n exit(-1);\\n }\\n fclose(fp);\\n img = CreateImage(ncols,nrows);\\n for (i=0; i < n; i++)\\n img->val[i]=(int)value[i];\\n free(value);\\n }else{\\n if((strcmp(type,\\\"P2\\\")==0)){\\n NCFgets(z,255,fp);\\n sscanf(z,\\\"%d %d\\\\n\\\",&ncols,&nrows);\\n n = ncols*nrows;\\n NCFgets(z,255,fp);\\n sscanf(z,\\\"%d\\\\n\\\",&i);\\n img = CreateImage(ncols,nrows);\\n for (i=0; i < n; i++)\\n\\tfscanf(fp,\\\"%d\\\",&img->val[i]);\\n fclose(fp);\\n }else{\\n fprintf(stderr,\\\"Input image must be P2 or P5\\\\n\\\");\\n exit(-1);\\n }\\n }\\n\\n return(img);\\n}\\n\\nImage *MBB(Image *img)\\n{\\n int x,y;\\n Pixel left,right;\\n Image *mbb=NULL;\\n \\n left.x = img->ncols-1;\\n left.y = img->nrows-1;\\n right.x = 0;\\n right.y = 0;\\n \\n for (y=0; y < img->nrows; y++)\\n for (x=0; x < img->ncols; x++){\\n if (img->val[x+img->tbrow[y]] > 0){\\n\\tif (x < left.x)\\n\\t left.x = x;\\n\\tif (y < left.y)\\n\\t left.y = y;\\n\\tif (x > right.x)\\n\\t right.x = x;\\n\\tif (y > right.y)\\n\\t right.y = y;\\t\\n }\\n }\\n \\n mbb = ROI(img,left.x,left.y,right.x,right.y);\\n\\n return(mbb);\\t\\n}\\n\\nImage *ROI(Image *img, int xl, int yl, int xr, int yr)\\n{\\n int x,y,p,i;\\n Image *roi=NULL;\\n \\n if (ValidPixel(img,xl,yl)&&ValidPixel(img,xr,yr)&&\\n (xl <= xr)&&(yl <= yr) )\\n {\\n roi = CreateImage(xr-xl+1,yr-yl+1);\\n i=0;\\n for (y=yl; y <= yr; y++)\\n\\tfor (x=xl; x <= xr; x++){\\n\\t p = x + img->tbrow[y];\\n\\t roi->val[i] = img->val[p];\\n\\t i++;\\n\\t}\\n } \\n \\n return(roi);\\t\\n}\\n\\nImage *AddFrame(Image *img, int sz, int value)\\n{\\n Image *fimg;\\n int y,*dst,*src,nbytes,offset;\\n\\n fimg = CreateImage(img->ncols+(2*sz),img->nrows+(2*sz));\\n SetImage(fimg,value);\\n nbytes = sizeof(int)*img->ncols;\\n offset = sz+fimg->tbrow[sz];\\n for (y=0,src=img->val,dst=fimg->val+offset; y < img->nrows;y++,src+=img->ncols,dst+=fimg->ncols){\\n memcpy(dst,src,nbytes);\\n }\\n return(fimg);\\n}\\n\\nvoid SetImage(Image *img, int value)\\n{ \\n int i,n;\\n n = img->ncols*img->nrows;\\n for (i=0; i < n; i++){\\n img->val[i]=value;\\n }\\n}\\n\\nvoid WriteImage(Image *img,char *filename)\\n{\\n FILE *fp;\\n int i, n, Imax;\\n\\n fp = fopen(filename,\\\"wb\\\");\\n if (fp == NULL){\\n fprintf(stderr,\\\"Cannot open %s\\\\n\\\",filename);\\n exit(-1);\\n }\\n n = img->ncols*img->nrows;\\n if ((Imax=MaximumValue(img))==INT_MAX){\\n Warning(\\\"Image with infinity values\\\",\\\"WriteImage\\\");\\n Imax = INT_MIN;\\n for (i=0; i < n; i++) \\n if ((img->val[i] > Imax)&&(img->val[i]!=INT_MAX))\\n\\tImax = img->val[i];\\n fprintf(fp,\\\"P2\\\\n\\\");\\n fprintf(fp,\\\"%d %d\\\\n\\\",img->ncols,img->nrows);\\n fprintf(fp,\\\"%d\\\\n\\\",Imax+1);\\n } else {\\n fprintf(fp,\\\"P2\\\\n\\\");\\n fprintf(fp,\\\"%d %d\\\\n\\\",img->ncols,img->nrows);\\n if (Imax==0) Imax++;\\n fprintf(fp,\\\"%d\\\\n\\\",Imax);\\n }\\n \\n for (i=0; i < n; i++) {\\n if (img->val[i]==INT_MAX)\\n fprintf(fp,\\\"%d \\\",Imax+1);\\n else\\n fprintf(fp,\\\"%d \\\",img->val[i]);\\n if (((i+1)%17) == 0)\\n fprintf(fp,\\\"\\\\n\\\");\\n }\\n\\n fclose(fp);\\n}\\n\\n/* ppm images */\\nCImage *CreateCImage(int ncols, int nrows)\\n{\\n CImage *cimg=NULL;\\n int i;\\n\\n cimg = (CImage *) calloc(1, sizeof(CImage));\\n for (i=0; i < 3; i++) \\n cimg->C[i] = CreateImage(ncols,nrows);\\n return(cimg);\\n}\\n\\nvoid DestroyCImage(CImage **cimg)\\n{\\n CImage *tmp;\\n int i;\\n\\n tmp = *cimg;\\n if (tmp != NULL) {\\n for (i=0; i < 3; i++) \\n DestroyImage(&(tmp->C[i]));\\n free(tmp);\\n *cimg = NULL;\\n }\\n}\\n\\nCImage *ReadCImage(char *filename)\\n{\\n CImage *cimg=NULL;\\n FILE *fp=NULL;\\n char type[10];\\n int i,ncols,nrows,n;\\n char z[256];\\n\\n fp = fopen(filename,\\\"rb\\\");\\n if (fp == NULL){\\n fprintf(stderr,\\\"Cannot open %s\\\\n\\\",filename);\\n exit(-1);\\n }\\n fscanf(fp,\\\"%s\\\\n\\\",type);\\n if((strcmp(type,\\\"P6\\\")==0)){\\n NCFgets(z,255,fp);\\n sscanf(z,\\\"%d %d\\\\n\\\",&ncols,&nrows);\\n n = ncols*nrows;\\n NCFgets(z,255,fp);\\n sscanf(z,\\\"%d\\\\n\\\",&i);\\n cimg = CreateCImage(ncols,nrows);\\n for (i=0; i < n; i++){\\n cimg->C[0]->val[i] = fgetc(fp);\\n cimg->C[1]->val[i] = fgetc(fp);\\n cimg->C[2]->val[i] = fgetc(fp);\\n }\\n fclose(fp);\\n }else{\\n fprintf(stderr,\\\"Input image must be P6\\\\n\\\");\\n exit(-1);\\n }\\n\\n return(cimg);\\n}\\n\\n/* auxiliary functions ****************************/\\nCurve *CreateCurve(int n)\\n{\\n Curve *curve=NULL;\\n\\n curve = (Curve *) calloc(1,sizeof(Curve));\\n if (curve != NULL) {\\n curve->X = AllocDoubleArray(n);\\n curve->Y = AllocDoubleArray(n);\\n curve->n = n;\\n } else {\\n Error(MSG1,\\\"CreateCurve\\\");\\n }\\n return(curve);\\n}\\n\\nvoid DestroyCurve(Curve **curve)\\n{\\n Curve *aux;\\n\\n aux = *curve;\\n if (aux != NULL){\\n if (aux->X != NULL) free(aux->X);\\n if (aux->Y != NULL) free(aux->Y);\\n free(aux);\\n *curve = NULL;\\n }\\n}\\n\\nFeatureVector1D *CreateFeatureVector1D(int n)\\n{\\n FeatureVector1D *desc=NULL;\\n \\n desc = (FeatureVector1D *) calloc(1,sizeof(FeatureVector1D));\\n if (desc != NULL) {\\n desc->X = AllocDoubleArray(n);\\n desc->n = n;\\n } else {\\n Error(MSG1,\\\"CreateFeatureVector\\\");\\n }\\n return(desc);\\n}\\n\\nFeatureVector1D *CurveTo1DFeatureVector(Curve *curve){\\n FeatureVector1D *fv;\\n\\n fv = CreateFeatureVector1D(curve->n);\\n memcpy(fv->X,curve->Y,curve->n*sizeof(double));\\n\\n return fv;\\n}\\n\\nFeatureVector2D *CurveTo2DFeatureVector(Curve *curve){\\n FeatureVector2D *fv;\\n\\n fv = CreateFeatureVector2D(curve->n);\\n memcpy(fv->X,curve->X,curve->n*sizeof(double));\\n memcpy(fv->Y,curve->Y,curve->n*sizeof(double));\\n\\n return fv;\\n}\\n\\nvoid DestroyFeatureVector1D(FeatureVector1D **desc)\\n{\\n FeatureVector1D *aux;\\n \\n aux = *desc;\\n if (aux != NULL){\\n if (aux->X != NULL) {\\n free(aux->X);\\n }\\n free(aux);\\n *desc = NULL;\\n }\\n}\\n\\nvoid WriteFeatureVector1D(FeatureVector1D *desc,char *filename)\\n{\\n FILE *fp;\\n int i;\\n \\n fp = fopen(filename,\\\"w\\\");\\n if (fp == NULL){\\n fprintf(stderr,\\\"Cannot open %s\\\\n\\\",filename);\\n exit(-1);\\n }\\n for (i=0; i < desc->n; i++)\\n fprintf(fp,\\\"%f\\\\n\\\",desc->X[i]);\\n \\n fclose(fp);\\n}\\n\\n\\nAdjRel *CreateAdjRel(int n)\\n{\\n AdjRel *A=NULL;\\n\\n A = (AdjRel *) calloc(1,sizeof(AdjRel));\\n if (A != NULL){\\n A->dx = AllocIntArray(n);\\n A->dy = AllocIntArray(n);\\n A->n = n;\\n } else {\\n Error(MSG1,\\\"CreateAdjRel\\\");\\n }\\n\\n return(A);\\n}\\n\\nvoid DestroyAdjRel(AdjRel **A)\\n{\\n AdjRel *aux;\\n\\n aux = *A;\\n if (aux != NULL){\\n if (aux->dx != NULL) free(aux->dx);\\n if (aux->dy != NULL) free(aux->dy);\\n free(aux);\\n *A = NULL;\\n } \\n}\\n\\nAdjRel *Circular(float r)\\n{\\n AdjRel *A=NULL;\\n int i,j,k,n,dx,dy,r0,r2,d,i0=0;\\n float *da,*dr,aux;\\n\\n n=0;\\n\\n r0 = (int)r;\\n r2 = (int)(r*r);\\n for(dy=-r0;dy<=r0;dy++)\\n for(dx=-r0;dx<=r0;dx++)\\n if(((dx*dx)+(dy*dy)) <= r2)\\n\\tn++;\\n\\t\\n A = CreateAdjRel(n);\\n i=0;\\n for(dy=-r0;dy<=r0;dy++)\\n for(dx=-r0;dx<=r0;dx++)\\n if(((dx*dx)+(dy*dy)) <= r2){\\n\\tA->dx[i]=dx;\\n\\tA->dy[i]=dy;\\n\\tif ((dx==0)&&(dy==0))\\n\\t i0 = i;\\n\\ti++;\\n }\\n\\n da = AllocFloatArray(A->n);\\n dr = AllocFloatArray(A->n);\\n for (i=0; i < A->n; i++) {\\n dx = A->dx[i];\\n dy = A->dy[i];\\n dr[i] = (float)sqrt((dx*dx) + (dy*dy));\\n if (i != i0){ \\n da[i] = atan2(-dy,-dx)*180.0/PI;\\n if (da[i] < 0.0)\\n\\tda[i] += 360.0;\\n }\\n }\\n da[i0] = 0.0;\\n dr[i0] = 0.0;\\n\\n aux = da[i0];\\n da[i0] = da[0];\\n da[0] = aux;\\n aux = dr[i0];\\n dr[i0] = dr[0];\\n dr[0] = aux;\\n d = A->dx[i0];\\n A->dx[i0] = A->dx[0];\\n A->dx[0] = d;\\n d = A->dy[i0];\\n A->dy[i0] = A->dy[0];\\n A->dy[0] = d;\\n\\n for (i=1; i < A->n-1; i++){\\n k = i;\\n for (j=i+1; j < A->n; j++)\\n if (da[j] < da[k]){\\n\\tk = j;\\n }\\n aux = da[i];\\n da[i] = da[k];\\n da[k] = aux;\\n aux = dr[i];\\n dr[i] = dr[k];\\n dr[k] = aux;\\n d = A->dx[i];\\n A->dx[i] = A->dx[k];\\n A->dx[k] = d;\\n d = A->dy[i];\\n A->dy[i] = A->dy[k];\\n A->dy[k] = d;\\n }\\n\\n for (i=1; i < A->n-1; i++){\\n k = i;\\n for (j=i+1; j < A->n; j++)\\n if ((dr[j] < dr[k])&&(da[j]==da[k])){\\n\\tk = j;\\n }\\n aux = dr[i];\\n dr[i] = dr[k];\\n dr[k] = aux;\\n d = A->dx[i];\\n A->dx[i] = A->dx[k];\\n A->dx[k] = d;\\n d = A->dy[i];\\n A->dy[i] = A->dy[k];\\n A->dy[k] = d;\\n }\\n\\n free(dr);\\n free(da);\\n\\n return(A);\\n}\\n\\nAdjRel *LeftSide(AdjRel *A)\\n{\\n AdjRel *L=NULL;\\n int i;\\n float d;\\n\\n L = CreateAdjRel(A->n);\\n for (i=0; i < L->n; i++){\\n d = sqrt(A->dx[i]*A->dx[i] + A->dy[i]*A->dy[i]);\\n if (d != 0){\\n L->dx[i] = ROUND(((float)A->dx[i]/2.0)+((float)A->dy[i]/d));\\n L->dy[i] = ROUND(((float)A->dy[i]/2)-((float)A->dx[i]/d));\\n }\\n }\\n \\n return(L);\\n}\\n\\n\\nAdjRel *RightSide(AdjRel *A)\\n{\\n AdjRel *R=NULL;\\n int i;\\n float d;\\n\\n R = CreateAdjRel(A->n);\\n for (i=0; i < R->n; i++){\\n d = sqrt(A->dx[i]*A->dx[i] + A->dy[i]*A->dy[i]);\\n if (d != 0){\\n R->dx[i] = ROUND(((float)A->dx[i]/2.0)-((float)A->dy[i]/d));\\n R->dy[i] = ROUND(((float)A->dx[i]/d)+((float)A->dy[i]/2.0));\\n }\\n }\\n\\n return(R);\\n}\\n\\nbool ValidContPoint(Image *bin, AdjRel *L, AdjRel *R, int p)\\n{\\n int i,q,n,left,right;\\n Pixel u,v,l,r;\\n bool found=false;\\n\\n u.x = p%bin->ncols;\\n u.y = p/bin->ncols;\\n n = L->n;\\n\\n for (i=0; i < n; i++) {\\n v.x = u.x + L->dx[i];\\n v.y = u.y + L->dy[i];\\n if (ValidPixel(bin,v.x,v.y)){\\n q = v.x + bin->tbrow[v.y];\\n if ((bin->val[q]==1)&&(p!=q)){\\n\\tl.x = u.x + L->dx[i]; \\n\\tl.y = u.y + L->dy[i];\\n\\tr.x = u.x + R->dx[i]; \\n\\tr.y = u.y + R->dy[i];\\t\\n\\tif (ValidPixel(bin,l.x,l.y))\\n\\t left = l.x + bin->tbrow[l.y];\\n\\telse\\n\\t left = -1;\\n\\tif (ValidPixel(bin,r.x,r.y))\\n\\t right = r.x + bin->tbrow[r.y];\\n\\telse\\n\\t right = -1;\\n\\tif (((left!=-1)&&(right!=-1)&&(bin->val[left]!=bin->val[right]))||\\n\\t ((left==-1)&&(right!=-1)&&(bin->val[right]==1)) ||\\n\\t ((right==-1)&&(left!=-1)&&(bin->val[left]==1))){\\n\\t found = true;\\n\\t break;\\n\\t}\\n }\\n }\\n }\\n \\n return(found);\\n}\\n\\nbool ValidPixel(Image *img, int x, int y)\\n{\\n if ((x >= 0)&&(x < img->ncols)&&\\n (y >= 0)&&(y < img->nrows))\\n return(true);\\n else\\n return(false);\\n}\\n\\nImage *LabelContPixel(Image *bin)\\n{\\n Image *bndr=NULL;\\n Image *color=NULL,*pred=NULL,*label=NULL;\\n int p=0,q,r,i,j,n,left=0,right=0,*LIFO,last,l;\\n AdjRel *A,*L,*R;\\n Pixel u,v,w;\\n \\n A = Circular(1.0);\\n n = bin->ncols*bin->nrows;\\n bndr = CreateImage(bin->ncols,bin->nrows);\\n for (p=0; p < n; p++){\\n if (bin->val[p]==1){\\n u.x = p%bin->ncols;\\n u.y = p/bin->ncols;\\n for (i=1; i < A->n; i++){\\n\\tv.x = u.x + A->dx[i];\\n\\tv.y = u.y + A->dy[i];\\n\\tif (ValidPixel(bin,v.x,v.y)){\\n\\t q = v.x + bin->tbrow[v.y];\\n\\t if (bin->val[q]==0){\\n\\t bndr->val[p]=1;\\n\\t break;\\n\\t }\\n\\t} else {\\n\\t bndr->val[p]=1;\\n\\t break;\\n\\t}\\n }\\n }\\n } \\n DestroyAdjRel(&A);\\n\\n A = Circular(1.5);\\n L = LeftSide(A);\\n R = RightSide(A);\\n label = CreateImage(bndr->ncols,bndr->nrows);\\n color = CreateImage(bndr->ncols,bndr->nrows);\\n pred = CreateImage(bndr->ncols,bndr->nrows);\\n n = bndr->ncols*bndr->nrows;\\n LIFO = AllocIntArray(n);\\n last = NIL;\\n for (j=0; j < n; j++){\\n if ((bndr->val[j]==1)\\n\\t&&(color->val[j]!=BLACK)\\n\\t&&ValidContPoint(bin,L,R,j)){\\n last++;\\n LIFO[last] = j;\\n color->val[j] = GRAY;\\n pred->val[j] = j;\\n while(last != NIL){\\n\\tp = LIFO[last]; last--;\\t\\n\\tcolor->val[p]=BLACK;\\n\\tu.x = p%bndr->ncols;\\n\\tu.y = p/bndr->ncols;\\n\\tfor (i=1; i < A->n; i++){\\n\\t v.x = u.x + A->dx[i];\\n\\t v.y = u.y + A->dy[i];\\n\\t if (ValidPixel(bndr,v.x,v.y)){\\n\\t q = v.x + bndr->tbrow[v.y];\\n\\t if ((q==j)&&(pred->val[p]!=j)){\\n\\t last = NIL;\\n\\t break;\\n\\t }\\n\\t \\n\\t w.x = u.x + L->dx[i]; \\n\\t w.y = u.y + L->dy[i];\\n\\t if (ValidPixel(bndr,w.x,w.y))\\n\\t left = w.x + bndr->tbrow[w.y];\\n\\t else\\n\\t left = -1;\\n\\t w.x = u.x + R->dx[i]; \\n\\t w.y = u.y + R->dy[i];\\n\\t if (ValidPixel(bndr,w.x,w.y))\\n\\t right = w.x + bndr->tbrow[w.y];\\n\\t else\\n\\t right = -1;\\n\\t \\n\\t if ((bndr->val[q]==1)&&\\n\\t\\t(color->val[q] != BLACK)&&\\n\\t\\t(((left!=-1)&&(right!=-1)&&(bin->val[left]!=bin->val[right]))||\\n\\t\\t ((left==-1)&&(right!=-1)&&(bin->val[right]==1)) ||\\n\\t\\t ((right==-1)&&(left!=-1)&&(bin->val[left]==1)))){ \\n\\t pred->val[q] = p;\\n\\t if (color->val[q] == WHITE){\\n\\t\\tlast++;\\n\\t\\tLIFO[last] = q;\\n\\t\\tcolor->val[q]=GRAY;\\n\\t }\\n\\t } \\n\\t }\\n\\t}\\t\\n }\\n r = p;\\n l = 1;\\n while(pred->val[p]!=p){\\n\\tlabel->val[p] = l;\\n\\tp = pred->val[p];\\n\\tl++;\\n }\\n if (r != p) {\\n\\tlabel->val[p] = l;\\n }\\n }\\n }\\n\\n DestroyAdjRel(&A);\\n DestroyAdjRel(&L);\\n DestroyAdjRel(&R);\\n DestroyImage(&bndr);\\n DestroyImage(&color);\\n DestroyImage(&pred);\\n free(LIFO);\\n return(label);\\n}\\n\\nCurve3D *CreateCurve3D(int n)\\n{\\n Curve3D *curve=NULL;\\n\\n curve = (Curve3D *) calloc(1,sizeof(Curve3D));\\n if (curve != NULL) {\\n curve->X = AllocDoubleArray(n);\\n curve->Y = AllocDoubleArray(n);\\n curve->Z = AllocDoubleArray(n);\\n curve->n = n;\\n } else {\\n Error(MSG1,\\\"CreateCurve3D\\\");\\n }\\n return(curve);\\n}\\n\\nvoid DestroyCurve3D(Curve3D **curve)\\n{\\n Curve3D *aux;\\n\\n aux = *curve;\\n if (aux != NULL){\\n if (aux->X != NULL) free(aux->X);\\n if (aux->Y != NULL) free(aux->Y);\\n if (aux->Z != NULL) free(aux->Z);\\n free(aux);\\n *curve = NULL;\\n }\\n}\\n\\nvoid SortCurve3D(Curve3D *curve, int left, int right, char order)\\n{\\n int pivot;\\n \\n if (left < right) {\\n pivot = PartCurve3D(curve,left,right,order);\\n SortCurve3D(curve,left,pivot-1,order);\\n SortCurve3D(curve,pivot+1,right,order); \\n }\\n}\\n\\nint PartCurve3D (Curve3D *curve, int left, int right, char order)\\n{\\n double z;\\n int i;\\n double X,Y,Z;\\n \\n z = curve->Z[left];\\n i = left;\\n \\n do {\\n if (order == INCREASING){\\n while ((curve->Z[left] <= z)&&(left <= right)) left++;\\n while (curve->Z[right] > z) right--;\\n } else { /* order = DECREASING */\\n while ((curve->Z[left] >= z)&&(left <= right)) left++;\\n while (curve->Z[right] < z) right--;\\n }\\n if (left < right){\\n X = curve->X[left];\\n Y = curve->Y[left];\\n Z = curve->Z[left];\\n curve->X[left] = curve->X[right];\\n curve->Y[left] = curve->Y[right];\\n curve->Z[left] = curve->Z[right];\\n curve->X[right] = X;\\n curve->Y[right] = Y;\\n curve->Z[right] = Z;\\n left++; right--;\\n }\\n } while (left <= right);\\n\\n left = i;\\n\\n if (left != right){\\n X = curve->X[left];\\n Y = curve->Y[left];\\n Z = curve->Z[left];\\n curve->X[left] = curve->X[right];\\n curve->Y[left] = curve->Y[right];\\n curve->Z[left] = curve->Z[right];\\n curve->X[right] = X;\\n curve->Y[right] = Y;\\n curve->Z[right] = Z;\\n }\\n\\n return (right);\\n}\\n\\nint FFT(int dir, long nn, double *x, double *y)\\n{\\n int m;\\n long i,i1,j,k,i2,l,l1,l2;\\n double c1,c2,tx,ty,t1,t2,u1,u2,z;\\n\\n m = (int)(log(nn)/log(2)+.00001);\\n \\n i2 = nn >> 1;\\n j = 0;\\n for (i=0;i>= 1;\\n }\\n j += k;\\n }\\n\\n c1 = -1.0;\\n c2 = 0.0;\\n l2 = 1;\\n for (l=0;lncols*bin->nrows;\\n bndr = CreateImage(bin->ncols,bin->nrows);\\n for (p=0; p < n; p++){\\n if (bin->val[p]==1){\\n\\t\\t \\n u.x = p%bin->ncols;\\n u.y = p/bin->ncols;\\n for (i=1; i < A->n; i++){\\n\\tv.x = u.x + A->dx[i];\\n\\tv.y = u.y + A->dy[i];\\n\\tif (ValidPixel(bin,v.x,v.y)){\\n\\t q = v.x + bin->tbrow[v.y];\\n\\t if (bin->val[q]==0){\\n\\t bndr->val[p]=1;\\n\\t break;\\n\\t }\\n\\t} else {\\n\\t bndr->val[p]=1;\\n\\t break;\\n\\t}\\n }\\n }\\n }\\n DestroyAdjRel(&A);\\n\\n A = Circular(1.5);\\n L = LeftSide(A);\\n R = RightSide(A);\\n label = CreateImage(bndr->ncols,bndr->nrows);\\n color = CreateImage(bndr->ncols,bndr->nrows);\\n pred = CreateImage(bndr->ncols,bndr->nrows);\\n LIFO = AllocIntArray(n);\\n last = NIL;\\n for (j=0; j < n; j++){\\n if ((bndr->val[j]==1)&&\\n\\t(color->val[j]!=BLACK)&&\\n\\tValidContPoint(bin,L,R,j)){ \\n last++; LIFO[last] = j;\\n color->val[j] = GRAY;\\n pred->val[j] = j;\\n while(last != NIL){\\n\\tp = LIFO[last];\\tlast--;\\t\\n\\tcolor->val[p]=BLACK;\\n\\tu.x = p%bndr->ncols;\\n\\tu.y = p/bndr->ncols;\\n\\tfor (i=1; i < A->n; i++){\\n\\t v.x = u.x + A->dx[i];\\n\\t v.y = u.y + A->dy[i];\\n\\t if (ValidPixel(bndr,v.x,v.y)){\\n\\t q = v.x + bndr->tbrow[v.y];\\n\\t if ((q==j)&&(pred->val[p]!=j)){\\n\\t last = NIL;\\n\\t break;\\n\\t }\\n\\t w.x = u.x + L->dx[i]; \\n\\t w.y = u.y + L->dy[i];\\n\\t if (ValidPixel(bndr,w.x,w.y))\\n\\t left = w.x + bndr->tbrow[w.y];\\n\\t else\\n\\t left = -1;\\n\\t w.x = u.x + R->dx[i]; \\n\\t w.y = u.y + R->dy[i];\\n\\t if (ValidPixel(bndr,w.x,w.y))\\n\\t right = w.x + bndr->tbrow[w.y];\\n\\t else\\n\\t right = -1;\\n\\t \\n\\t if ((bndr->val[q]==1)&&\\n\\t\\t(color->val[q] != BLACK)&&\\n\\t\\t(((left!=-1)&&(right!=-1)&&(bin->val[left]!=bin->val[right]))||\\n\\t\\t ((left==-1)&&(right!=-1)&&(bin->val[right]==1)) ||\\n\\t\\t ((right==-1)&&(left!=-1)&&(bin->val[left]==1))) ) {\\n\\t pred->val[q] = p;\\n\\t if (color->val[q] == WHITE){\\n\\t\\tlast++; LIFO[last] = q;\\n\\t\\tcolor->val[q]=GRAY;\\n\\t }\\n\\t } \\n\\t }\\n\\t}\\t\\n }\\n r = p;\\n while(pred->val[p]!=p){\\n\\tlabel->val[p] = l;\\n\\tp = pred->val[p];\\n } \\n if (r != p){ \\n\\tlabel->val[p] = l;\\n\\tl++;\\n }\\n }\\n }\\n\\n DestroyAdjRel(&A);\\n DestroyAdjRel(&L);\\n DestroyAdjRel(&R);\\n DestroyImage(&bndr);\\n DestroyImage(&color);\\n DestroyImage(&pred);\\n free(LIFO);\\n return(label);\\n}\\n\\nvoid Warning(char *msg,char *func){ \\n fprintf(stdout,\\\"Warning:%s in %s\\\\n\\\",msg,func);\\n}\\n\\nImage *Scale(Image *img, float Sx, float Sy) \\n{\\n float S[2][2],x,y,d1,d2,d3,d4,Ix1,Ix2,If;\\n Image *scl;\\n Pixel u,v,prev,next;\\n \\n if (Sx == 0.0) Sx = 1.0;\\n if (Sy == 0.0) Sy = 1.0;\\n\\n S[0][0] = 1.0/Sx;\\n S[0][1] = 0;\\n S[1][0] = 0;\\n S[1][1] = 1.0/Sy;\\n\\n scl = CreateImage((int)(img->ncols*fabs(Sx) + 0.5),(int)(img->nrows*fabs(Sy) + 0.5)); \\n\\n for (v.y=0; v.y < scl->nrows; v.y++)\\n for (v.x=0; v.x < scl->ncols; v.x++){\\n x = ((v.x-scl->ncols/2.)*S[0][0] + (v.y-scl->nrows/2.)*S[0][1]) \\n\\t+ img->ncols/2.;\\n y = ((v.x-scl->ncols/2.)*S[1][0] + (v.y-scl->nrows/2.)*S[1][1]) \\n\\t+ img->nrows/2.;\\n u.x = (int)(x+0.5);\\n u.y = (int)(y+0.5);\\n if (ValidPixel(img,u.x,u.y)){\\n\\tif (x < u.x) {\\n\\t next.x = u.x;\\n\\t prev.x = u.x - 1;\\n\\t} else {\\n\\t next.x = u.x + 1;\\n\\t prev.x = u.x;\\n\\t}\\n\\td1 = next.x - x;\\n\\td2 = x - prev.x;\\n\\tif (y < u.y) {\\n\\t next.y = u.y;\\n\\t prev.y = u.y - 1;\\n\\t} else {\\n\\t next.y = u.y + 1;\\n\\t prev.y = u.y;\\n\\t}\\n\\td3 = next.y - y;\\n\\td4 = y - prev.y;\\n\\n\\tif (ValidPixel(img,prev.x,prev.y)&&ValidPixel(img,next.x,prev.y))\\n\\t Ix1 = d1*img->val[prev.x+img->tbrow[prev.y]] + \\n\\t d2*img->val[next.x+img->tbrow[prev.y]];\\n\\telse\\n\\t Ix1 = img->val[u.x+img->tbrow[u.y]];\\n\\n\\tif (ValidPixel(img,prev.x,next.y)&&ValidPixel(img,next.x,next.y))\\n\\t Ix2 = d1*img->val[prev.x+img->tbrow[next.y]] + \\n\\t d2*img->val[next.x+img->tbrow[next.y]];\\n\\telse\\n\\t Ix2 = img->val[u.x+img->tbrow[u.y]];\\n\\t\\n\\tIf = d3*Ix1 + d4*Ix2;\\n\\n\\tscl->val[v.x+scl->tbrow[v.y]] = (int)If;\\n }\\n }\\n \\n return(scl);\\n}\\n\\nDImage *CreateDImage(int ncols, int nrows)\\n{\\n DImage *dimg=NULL;\\n int i;\\n\\n dimg = (DImage *) calloc(1,sizeof(DImage));\\n if (dimg == NULL){\\n Error(MSG1,\\\"CreateDImage\\\");\\n }\\n\\n dimg->val = AllocDoubleArray(nrows*ncols);\\n dimg->tbrow = AllocIntArray(nrows);\\n\\n dimg->tbrow[0]=0;\\n for (i=1; i < nrows; i++)\\n dimg->tbrow[i]=dimg->tbrow[i-1]+ncols;\\n dimg->ncols = ncols;\\n dimg->nrows = nrows;\\n \\n return(dimg);\\n}\\n\\nvoid DestroyDImage(DImage **dimg)\\n{\\n DImage *aux;\\n\\n aux = *dimg;\\n if(aux != NULL){\\n if (aux->val != NULL) free(aux->val); \\n if (aux->tbrow != NULL) free(aux->tbrow);\\n free(aux); \\n *dimg = NULL;\\n }\\n}\\n\\nImage *CopyImage(Image *img)\\n{\\n Image *imgc;\\n\\n imgc = CreateImage(img->ncols,img->nrows);\\n memcpy(imgc->val,img->val,img->ncols*img->nrows*sizeof(int));\\n \\n return(imgc);\\n}\\n\\nint MaximumValue(Image *img)\\n{\\n unsigned int i, n, r;\\n int max;\\n\\n max = img->val[0];\\n n = img->ncols*img->nrows - 1;\\n r = n%4;\\n n -= r;\\n for (i=1; i < n; i+=4) {\\n if (img->val[i] > max)\\n max = img->val[i];\\n if (img->val[i+1] > max)\\n max = img->val[i+1];\\n if (img->val[i+2] > max)\\n max = img->val[i+2];\\n if (img->val[i+3] > max)\\n max = img->val[i+3];\\n }\\n while (r != 0) {\\n if (img->val[i+r-1] > max)\\n max = img->val[i+r-1];\\n --r;\\n }\\n\\n return(max);\\n}\\n\\nQueue *CreateQueue(int nbuckets, int nelems)\\n{\\n Queue *Q=NULL;\\n\\n Q = (Queue *) malloc(1*sizeof(Queue));\\n \\n if (Q != NULL) {\\n Q->C.first = (int *)malloc(nbuckets * sizeof(int));\\n Q->C.last = (int *)malloc(nbuckets * sizeof(int));\\n Q->C.nbuckets = nbuckets;\\n if ( (Q->C.first != NULL) && (Q->C.last != NULL) ){\\n Q->L.elem = (Node *)malloc(nelems*sizeof(Node));\\n Q->L.nelems = nelems;\\n if (Q->L.elem != NULL){\\n\\tResetQueue(Q);\\n } else\\n\\tError(MSG1,\\\"CreateQueue\\\");\\t\\n } else\\n Error(MSG1,\\\"CreateQueue\\\");\\n } else \\n Error(MSG1,\\\"CreateQueue\\\");\\n \\n return(Q);\\n}\\n\\nvoid DestroyQueue(Queue **Q)\\n{\\n Queue *aux;\\n\\n aux = *Q;\\n if (aux != NULL) {\\n if (aux->C.first != NULL) free(aux->C.first);\\n if (aux->C.last != NULL) free(aux->C.last);\\n if (aux->L.elem != NULL) free(aux->L.elem);\\n free(aux);\\n *Q = NULL;\\n }\\n}\\n\\nvoid InsertQueue(Queue *Q, int bucket, int elem)\\n{\\n if (Q->C.first[bucket] == NIL){ \\n Q->C.first[bucket] = elem; \\n Q->L.elem[elem].prev = NIL;\\n }else {\\n Q->L.elem[Q->C.last[bucket]].next = elem;\\n Q->L.elem[elem].prev = Q->C.last[bucket];\\n }\\n \\n Q->C.last[bucket] = elem;\\n Q->L.elem[elem].next = NIL;\\n Q->L.elem[elem].color = GRAY;\\n}\\n\\nint RemoveQueue(Queue *Q)\\n{\\n int elem=NIL, next, prev;\\n int last;\\n\\n /** moves to next element or returns EMPTY queue **/\\n if (Q->C.first[Q->C.current] == NIL) {\\n last = Q->C.current;\\n \\n Q->C.current = (Q->C.current + 1) % (Q->C.nbuckets);\\n \\n while ((Q->C.first[Q->C.current] == NIL) && (Q->C.current != last)) {\\n Q->C.current = (Q->C.current + 1) % (Q->C.nbuckets);\\n }\\n \\n if (Q->C.first[Q->C.current] == NIL)\\n return NIL;\\n }\\n\\n if (Q->C.tiebreak == LIFOBREAK) {\\n elem = Q->C.last[Q->C.current];\\n \\n prev = Q->L.elem[elem].prev;\\n if (prev == NIL) { /* there was a single element in the list */\\n Q->C.last[Q->C.current] = Q->C.first[Q->C.current] = NIL; \\n }\\n else {\\n Q->C.last[Q->C.current] = prev;\\n Q->L.elem[prev].next = NIL;\\n }\\n } else { /* Assume FIFO policy for breaking ties */\\n elem = Q->C.first[Q->C.current];\\n \\n next = Q->L.elem[elem].next;\\n if (next == NIL) { /* there was a single element in the list */\\n Q->C.first[Q->C.current] = Q->C.last[Q->C.current] = NIL; \\n }\\n else {\\n Q->C.first[Q->C.current] = next;\\n Q->L.elem[next].prev = NIL;\\n }\\n }\\n\\n Q->L.elem[elem].color = BLACK;\\n\\n return elem;\\n}\\n\\nvoid UpdateQueue(Queue *Q, int elem, int from, int to)\\n{\\n RemoveQueueElem(Q, elem, from);\\n InsertQueue(Q, to, elem);\\n}\\n\\nint EmptyQueue(Queue *Q)\\n{\\n int last;\\n if (Q->C.first[Q->C.current] != NIL)\\n return 0;\\n \\n last = Q->C.current;\\n \\n Q->C.current = (Q->C.current + 1) % (Q->C.nbuckets);\\n \\n while ((Q->C.first[Q->C.current] == NIL) && (Q->C.current != last)) {\\n Q->C.current = (Q->C.current + 1) % (Q->C.nbuckets); \\n }\\n \\n return (Q->C.first[Q->C.current] == NIL);\\n}\\n\\nvoid ResetQueue(Queue *Q)\\n{\\n unsigned int i;\\n\\n Q->C.current = 0;\\n SetTieBreak(Q,FIFOBREAK);\\n#if defined(__i386__) && (NIL==-1 || NIL==0)\\n i = Q->C.nbuckets*sizeof(int);\\n memset(Q->C.first, NIL, i);\\n memset(Q->C.last, NIL, i);\\n memset(Q->L.elem, NIL, Q->L.nelems*sizeof(Node));\\n for (i=0; iL.nelems; ++i)\\n Q->L.elem[i].color = WHITE;\\n#else\\n for (i=0; i < Q->C.nbuckets; ++i)\\n Q->C.first[i]=Q->C.last[i]=NIL;\\n for (i=0; i < Q->L.nelems; ++i) {\\n Q->L.elem[i].next = Q->L.elem[i].prev = NIL;\\n Q->L.elem[i].color = WHITE;\\n }\\n#endif\\n}\\n\\nvoid RemoveQueueElem(Queue *Q, int elem, int bucket)\\n{\\n int prev,next;\\n\\n prev = Q->L.elem[elem].prev;\\n next = Q->L.elem[elem].next;\\n \\n /* if elem is the first element */\\n if (Q->C.first[bucket] == elem) {\\n Q->C.first[bucket] = next;\\n if (next == NIL) /* elem is also the last one */\\n Q->C.last[bucket] = NIL;\\n else\\n Q->L.elem[next].prev = NIL;\\n }\\n else{ /* elem is in the middle or it is the last */\\n Q->L.elem[prev].next = next;\\n if (next == NIL) /* if it is the last */\\n Q->C.last[bucket] = prev;\\n else \\n Q->L.elem[next].prev = prev;\\n }\\n\\n Q->L.elem[elem].color = BLACK;\\n}\\n\\nCurve *SamplePolynom(Polynom *P, double from, double to, int nbins)\\n{\\n Curve *curve=NULL;\\n double x = from,val;\\n double inc = (to-from)/nbins;\\n int i,p;\\n \\n if ((from <= to)&&(nbins > 0)) {\\n curve = CreateCurve(nbins);\\n for (p=0; p < nbins; p++){\\n val=0.0;\\n for (i=0; i <= P->n; i++)\\n\\tval += pow(x,i)*P->coef[i];\\n curve->X[p] = x;\\n curve->Y[p] = val;\\n x +=inc;\\n }\\n }\\n return(curve);\\n}\\n\\nPolynom *CreatePolynom(int degree)\\n{\\n Polynom *P=NULL;\\n\\n P = (Polynom *) calloc(1,sizeof(Polynom)); \\n P->coef = AllocDoubleArray(degree + 1);\\n P->n = degree;\\n return(P);\\n}\\n\\nvoid DestroyPolynom(Polynom **P)\\n{\\n Polynom *aux=NULL;\\n\\n aux = *P;\\n if(aux != NULL){\\n if(aux->coef != NULL) free(aux->coef);\\n free(aux);\\n *P = NULL;\\n }\\n}\\n\\nPolynom *DerivPolynom(Polynom *P)\\n{\\n Polynom *D;\\n int i,j;\\n\\n D = CreatePolynom(P->n-1);\\n j = 0;\\n for (i=1; i <= P->n; i++){\\n D->coef[j] = i*P->coef[i];\\n j++;\\n }\\n return(D);\\n}\\n\\n\\nPolynom *Regression(Curve *curve, int degree)\\n{\\n Polynom *P=NULL;\\n double *A=NULL,*B=NULL;\\n int i,j,k;\\n double sum, m;\\n\\n /* Compute Non-Linear System: A*P=B, where P are the coefficients of\\n the polynomial */\\n\\n A = AllocDoubleArray((degree+1)*(degree+1));\\n B = AllocDoubleArray(degree+1);\\n\\n for (i=1; i<= 2*degree; i++){\\n sum = 0.0;\\n for (k=0; k < curve->n; k++){\\n sum += pow(curve->X[k], i);\\n }\\n if (i<=degree){\\n for (j=0; j<=i; j++){ \\n\\tA[(i-j) + j*(degree+1)] = sum;\\n }\\n }\\n else {\\n for (j= (i-degree); j<= degree; j++){ \\n\\tA[(i-j) + j*(degree+1)] = sum;\\n }\\n }\\n }\\n A[0]= curve->n;\\n \\n for (i=0; i<=degree; i++){\\n sum = 0.0;\\n for (k=0; k < curve->n; k++){\\n sum += pow(curve->X[k], i)*curve->Y[k];\\n }\\n B[i] = sum;\\n }\\n\\n /* Gauss's Regression Method */\\n\\n for(k = 0; k < degree; k++){ /* Triangulation of A */\\n for(i = k+1; i<= degree; i++){\\n m = A[i*(degree+1)+k]/A[k*(degree+1)+k];\\n A[i*(degree+1)+k] = 0.0;\\n for (j = k+1; j<= degree; j++){\\n\\tA[i*(degree+1)+j] = A[i*(degree+1)+j] - m *A[k*(degree+1)+j];\\n }\\n B[i] = B[i] - m * B[k];\\n }\\n }\\n \\n P = CreatePolynom(degree);\\n\\n P->coef[degree] = B[degree]/A[degree*(degree+1) + degree];\\n for(k=degree-1; k>=0; k--){\\n sum= 0.0;\\n for(j=k+1; j<=degree; j++){\\n sum += A[k*(degree+1)+j]*P->coef[j];\\n }\\n P->coef[k] = (B[k]-sum)/A[k*(degree+1)+k];\\n }\\n \\n free(A);\\n free(B);\\n \\n return(P);\\n}\\n\\nvoid DeAnnotate(AnnImg **aimg)\\n{\\n AnnImg *aux;\\n \\n aux = *aimg;\\n if (aux != NULL){\\n DestroyImage(&(aux->cost));\\n DestroyImage(&(aux->label));\\n DestroyImage(&(aux->pred));\\n DestroySet(&(aux->seed));\\n free(aux);\\n *aimg = NULL;\\n }\\n}\\n\\nPolynom *MSFractal(Image *bin, \\n\\t\\t int maxdist, \\n\\t\\t int degree, \\n\\t\\t double lower, \\n\\t\\t double higher,\\n\\t\\t int reg,\\n\\t\\t double from,\\n\\t\\t double to)\\n{\\n Curve *hist=NULL,*haux=NULL,*ahist=NULL, *aux_ahist=NULL,*loglog=NULL;\\n AnnImg *aimg=NULL;\\n AdjRel *A=NULL;\\n Image *mbb=NULL,*nbin=NULL;\\n Polynom *P=NULL,*D=NULL;\\n int n,i,j,maxcost=maxdist*maxdist;\\n \\n mbb = MBB(bin);\\n nbin = AddFrame(mbb,maxdist,0);\\n DestroyImage(&mbb);\\n\\n /* Compute Euclidean IFT */\\n\\n A = Circular(1.5);\\n aimg = Annotate(nbin,NULL,nbin);\\n iftDilation(aimg, A);\\n DestroyAdjRel(&A);\\n\\n /* Compute MS Fractal */\\n\\n hist = Histogram(aimg->cost);\\n\\n /* Compute non-zero points */\\n\\n n = 0;\\n for (i=1; i < maxcost; i++)\\n if (hist->Y[i] != 0)\\n n++;\\n\\n haux = CreateCurve(n);\\n j=0;\\n for (i=1; i < maxcost; i++)\\n if (hist->Y[i] != 0){\\n haux->X[j] = log(sqrt((double)i));\\n haux->Y[j] = hist->Y[i];\\n j++;\\n }\\n \\n /* Accumulate values */\\n ahist = CreateCurve(n);\\n ahist->X[0] = haux->X[0];\\n ahist->Y[0] = haux->Y[0];\\n for (i=1; i < n; i++) {\\n ahist->X[i] = haux->X[i];\\n ahist->Y[i] = ahist->Y[i-1] + haux->Y[i];\\n }\\n\\n /* Compute log(Y) */\\n for (i=0; i < n; i++)\\n ahist->Y[i] = log((double)ahist->Y[i]);\\n \\n j=0;\\n \\n for (i=0; i < n; i++)\\n if ((ahist->X[i]>from)&&((ahist->X[i]X[i]>from)&&((ahist->X[i]X[j] = ahist->X[i];\\n aux_ahist->Y[j] = ahist->Y[i];\\n j++;\\n }\\n \\n \\n /* Compute Regression */\\n P = Regression(/*ahist*/aux_ahist,degree);\\n \\n /* Print loglog curve */\\n if (reg){\\n loglog = SamplePolynom(P,lower, higher, 100);\\n }\\n \\n /* Compute Fractal Curve */\\n D = DerivPolynom(P); \\n\\n DestroyCurve(&hist);\\n DestroyCurve(&haux);\\n DestroyCurve(&ahist);\\n DestroyCurve(&aux_ahist);\\n DestroyCurve(&loglog);\\n DestroyPolynom(&P);\\n DeAnnotate(&aimg);\\n DestroyImage(&nbin);\\n return(D);\\n}\\n\\nAnnImg *Annotate(Image *img, Image *cost, Image *label)\\n{\\n AnnImg *aimg=NULL;\\n int p,n;\\n\\n aimg = (AnnImg *) calloc(1,sizeof(AnnImg));\\n if (aimg == NULL)\\n Error(MSG1,\\\"Annotate\\\");\\n\\n aimg->img = img;\\n aimg->cost = CreateImage(img->ncols,img->nrows); \\n aimg->label = CreateImage(img->ncols,img->nrows);\\n aimg->pred = CreateImage(img->ncols,img->nrows);\\n aimg->root = NULL;\\n aimg->seed = NULL;\\n\\n n = img->ncols*img->nrows;\\n\\n if ((cost == NULL)&&(label == NULL))\\n for (p=0; p < n; p++){\\n aimg->cost->val[p] = INT_MAX;\\n aimg->label->val[p] = 0;\\n aimg->pred->val[p] = p;\\n }\\n else\\n if ((cost == NULL)&&(label != NULL))\\n for (p=0; p < n; p++){\\n\\taimg->pred->val[p] = p;\\n\\tif (label->val[p] > 0) {\\n\\t aimg->cost->val[p] = 0;\\n\\t aimg->label->val[p] = label->val[p];\\n\\t InsertSet(&(aimg->seed),p);\\n\\t} else {\\n\\t aimg->cost->val[p] = INT_MAX;\\n\\t aimg->label->val[p] = 0;\\n\\t}\\n }\\n else\\n if ((cost != NULL)&&(label == NULL))\\n\\tfor (p=0; p < n; p++){\\n\\t aimg->cost->val[p] = cost->val[p];\\n\\t aimg->label->val[p] = p;\\n\\t aimg->pred->val[p] = p;\\n\\t InsertSet(&(aimg->seed),p);\\n\\t}\\n else\\n\\tif ((cost != NULL)&&(label != NULL))\\t\\n\\t for (p=0; p < n; p++){\\n\\t aimg->pred->val[p] = p;\\n\\t aimg->label->val[p] = label->val[p];\\n\\t if (label->val[p] > 0) {\\n\\t aimg->cost->val[p] = cost->val[p];\\n\\t InsertSet(&(aimg->seed),p);\\n\\t } else { \\n\\t aimg->cost->val[p] = INT_MAX;\\n\\t }\\n\\t }\\n \\n return(aimg);\\n}\\n\\nvoid InsertSet(Set **S, int elem)\\n{\\n Set *p=NULL;\\n\\n p = (Set *) calloc(1,sizeof(Set));\\n if (p == NULL) Error(MSG1,\\\"InsertSet\\\");\\n if (*S == NULL){\\n p->elem = elem;\\n p->next = NULL;\\n }else{\\n p->elem = elem;\\n p->next = *S;\\n }\\n *S = p;\\n}\\n\\nint RemoveSet(Set **S)\\n{\\n Set *p;\\n int elem=NIL;\\n \\n if (*S != NULL){\\n p = *S;\\n elem = p->elem;\\n *S = p->next;\\n //printf(\\\"RemoveSet before free\\\");\\n free(p);\\n //printf(\\\" RemoveSet after free: elem is %d\\\\n\\\",elem);\\n //if(*S != NULL) printf(\\\" *S->elem is %d\\\\n\\\",(*S)->elem);\\n }\\n return(elem);\\n}\\n\\nvoid DestroySet(Set **S)\\n{\\n Set *p;\\n while(*S != NULL){\\n p = *S;\\n *S = p->next;\\n free(p);\\n }\\n}\\n\\nint FrameSize(AdjRel *A)\\n{\\n int sz=INT_MIN,i=0;\\n\\n for (i=0; i < A->n; i++){\\n if (fabs(A->dx[i]) > sz) \\n sz = fabs(A->dx[i]);\\n if (fabs(A->dy[i]) > sz) \\n sz = fabs(A->dy[i]);\\n }\\n return(sz);\\n}\\n\\nAdjRel *ComplAdj(AdjRel *A1, AdjRel *A2)\\n{\\n AdjRel *A;\\n int i,j,n;\\n char *subset=NULL;\\n\\n if (A1->n > A2->n){\\n A = A1;\\n A1 = A2;\\n A2 = A;\\n }\\n\\n A = NULL;\\n subset = AllocCharArray(A2->n);\\n n = 0;\\n for (i=0; i < A1->n; i++) \\n for (j=0; j < A2->n; j++)\\n if ((A1->dx[i]==A2->dx[j])&&(A1->dy[i]==A2->dy[j])){\\t \\n\\tsubset[j] = 1;\\n\\tn++;\\n\\tbreak;\\n }\\n n = A2->n - n;\\n \\n if (n == 0) /* A1 == A2 */ \\n return(NULL);\\n\\n A = CreateAdjRel(n);\\n j=0;\\n for (i=0; i < A2->n; i++) \\n if (subset[i] == 0){\\n A->dx[j] = A2->dx[i];\\n A->dy[j] = A2->dy[i];\\n j++;\\n }\\n\\n free(subset);\\n\\n return(A);\\n}\\n\\nHeap *CreateHeap(int n, int *cost){\\n Heap *H=NULL;\\n int i;\\n\\n if (cost == NULL){\\n Warning(\\\"Cannot create heap without cost map\\\",\\\"CreateHeap\\\");\\n return(NULL);\\n }\\n\\n H = (Heap *) calloc(1,sizeof(Heap));\\n if (H != NULL) {\\n H->n = n;\\n H->cost = cost;\\n H->color = (char *) calloc(n,sizeof(char));\\n H->pixel = (int *) calloc(n,sizeof(int));\\n H->pos = (int *) calloc(n,sizeof(int));\\n H->last = -1;\\n if ((H->color == NULL) || (H->pos == NULL) || (H->pixel == NULL))\\n Error(MSG1,\\\"CreateHeap\\\");\\n for (i=0; i < H->n; i++){\\n H->color[i]=WHITE;\\n H->pos[i]=-1;\\n H->pixel[i]=-1;\\n } \\n } \\n else\\n Error(MSG1,\\\"CreateHeap\\\");\\n \\n return(H);\\n}\\n\\nvoid DestroyHeap(Heap **H){\\n Heap *aux;\\n \\n aux = *H;\\n if (aux != NULL) {\\n if (aux->pixel != NULL) free(aux->pixel);\\n if (aux->color != NULL) free(aux->color);\\n if (aux->pos != NULL) free(aux->pos);\\n free(aux);\\n *H = NULL;\\n }\\n}\\n\\nbool InsertHeap(Heap *H, int pixel){\\n if (!IsFullHeap(H)){\\n H->last ++;\\n H->pixel[H->last] = pixel;\\n H->color[pixel] = GRAY;\\n H->pos[pixel] = H->last;\\n GoUpHeap(H,H->last); \\n return(true);\\n } else \\n return(false);\\n}\\n\\nbool RemoveHeap(Heap *H, int *pixel){\\n if (!IsEmptyHeap(H)){\\n *pixel = H->pixel[0];\\n H->pos[*pixel]=-1;\\n H->color[*pixel] = BLACK;\\n H->pixel[0] = H->pixel[H->last];\\n H->pos[H->pixel[0]] = 0;\\n H->last--;\\n GoDownHeap(H,0);\\n return(true);\\n } else \\n return(false);\\n}\\n\\nbool IsEmptyHeap(Heap *H){\\n if (H->last == -1)\\n return(true);\\n else\\n return(false);\\n}\\n\\nvoid GoDownHeap(Heap *H, int i){\\n int least, left=HEAP_LEFTSON(i), right=HEAP_RIGHTSON(i);\\n\\n if ((left <= H->last)&&(H->cost[H->pixel[left]] < H->cost[H->pixel[i]]))\\n least = left;\\n else\\n least = i;\\n\\n if ((right <= H->last)&&(H->cost[H->pixel[right]] < H->cost[H->pixel[least]]))\\n least = right;\\n\\n if (least != i){\\n Change(&H->pixel[least],&H->pixel[i]);\\n H->pos[H->pixel[i]]=i;\\n H->pos[H->pixel[least]]=least;\\n GoDownHeap(H,least);\\n }\\n}\\n\\nbool IsFullHeap(Heap *H){\\n if (H->last == (H->n-1))\\n return(true);\\n else\\n return(false);\\n}\\n\\nbool HeapIsEmpty(Heap *H){\\n return IsEmptyHeap(H);\\n}\\n\\nvoid Change(int *a, int *b){\\n int c; \\n c = *a;\\n *a = *b;\\n *b = c;\\n}\\n\\nvoid GoUpHeap(Heap *H, int i){\\n int j = HEAP_DAD(i);\\n\\n while((i > 0) && (H->cost[H->pixel[j]] > H->cost[H->pixel[i]])){\\n Change(&H->pixel[j],&H->pixel[i]);\\n H->pos[H->pixel[i]]=i;\\n H->pos[H->pixel[j]]=j;\\n i = j;\\n j = HEAP_DAD(i);\\n }\\n}\\n\\nvoid DestroyAdjPxl(AdjPxl **N)\\n{\\n AdjPxl *aux;\\n\\n aux = *N;\\n if (aux != NULL){\\n if (aux->dp != NULL) free(aux->dp);\\n free(aux);\\n *N = NULL;\\n }\\n}\\n\\nImage *CompPaths(Image *pred)\\n{\\n Image *seed=NULL;\\n int p,n;\\n\\n seed = CopyImage(pred);\\n\\n n = seed->ncols*seed->nrows;\\n for (p=0; p < n; p++) \\n seed->val[p] = Seed(seed,p);\\n return(seed);\\n}\\n\\nint Seed(Image *pred, int p)\\n{\\n if (pred->val[p]==p)\\n return(p);\\n else \\n return(Seed(pred,pred->val[p])); \\n}\\n\\nImage *Perimeter(Image *bin)\\n{\\n int p,n;\\n Image *cont,*perim;\\n Curve *hist;\\n\\n cont = LabelContour(bin);\\n n = cont->ncols*cont->nrows;\\n perim = CreateImage(cont->ncols,cont->nrows);\\n hist = Histogram(cont);\\n for (p=0; p < n; p++)\\n if (cont->val[p] > 0)\\n perim->val[p] = hist->Y[cont->val[p]];\\n\\n DestroyCurve(&hist);\\n DestroyImage(&cont);\\n\\n return(perim);\\n}\\n\\nCurve3D *Saliences(Image *bin, int maxdist) \\n{ \\n Image *cont=NULL;\\n AdjRel *A=NULL;\\n AnnImg *aimg=NULL;\\n Curve3D *saliences=NULL;\\n \\n /* Compute Euclidean IFT */\\n \\n cont = LabelContPixel(bin);\\n aimg = Annotate(bin,NULL,cont); \\n A = Circular(1.5);\\n iftDilation(aimg,A);\\n saliences = CompSaliences(aimg, maxdist*maxdist);\\n \\n DestroyImage(&cont);\\n DestroyAdjRel(&A);\\n DeAnnotate(&aimg);\\n \\n return(saliences);\\n}\\n\\nImage *MSSkel(Image *bin, char side)\\n{\\n Image *msskel,*cont;\\n AdjRel *A;\\n AnnImg *aimg;\\n int p,n;\\n\\n /* Compute Euclidean IFT */\\n\\n cont = LabelContPixel(bin);\\n aimg = Annotate(bin,NULL,cont); \\n A = Circular(1.5);\\n n = aimg->img->ncols*aimg->img->nrows;\\n switch (side) {\\n case INTERIOR:\\n for(p = 0; p < n; p++)\\n if (aimg->img->val[p] == 0){\\n\\taimg->cost->val[p] = 0;\\n }\\n break;\\n case EXTERIOR:\\n for(p = 0; p < n; p++)\\n if (aimg->img->val[p] != 0){\\n\\taimg->cost->val[p] = 0;\\n }\\n break;\\n case BOTH:\\n default: \\n ;\\n }\\n iftDilation(aimg,A);\\n DestroyAdjRel(&A);\\n DestroyImage(&cont);\\n \\n /* Compute MS Skeletons */\\n\\n msskel = CompMSSkel(aimg);\\n DeAnnotate(&aimg);\\n\\n return(msskel);\\n}\\n\\nCurve3D *CompSaliences(AnnImg *aimg, int maxcost)\\n{\\n Image *cont=NULL;\\n double *inter=NULL,*exter=NULL; \\n int p,n,i,Lmax;\\n Curve3D *saliences=NULL;\\n \\n n = aimg->img->ncols*aimg->img->nrows;\\n cont = CreateImage(aimg->img->ncols,aimg->img->nrows);\\n for(p=0;ppred->val[p]==p){\\n cont->val[p]=aimg->label->val[p];\\n }\\n }\\n \\n Lmax = MaximumValue(aimg->label);\\n inter = AllocDoubleArray(Lmax);\\n exter = AllocDoubleArray(Lmax);\\n \\n \\n /* Compute influence areas */\\n\\n for (p=0; p < n; p++){\\n if ((aimg->label->val[p] > 0)&&(aimg->cost->val[p] <= maxcost)) {\\n if (aimg->img->val[p] != 0){\\n\\tinter[aimg->label->val[p]-1]++;\\n } else {\\n\\texter[aimg->label->val[p]-1]++;\\n }\\n }\\n }\\n \\n /* Compute saliences */\\n saliences = CreateCurve3D(Lmax);\\n \\n for (p=0; p < n; p++){\\n if (cont->val[p] > 0){\\n i = cont->val[p]-1;\\n saliences->X[i] = (double)(p%cont->ncols);\\n saliences->Y[i] = (double)(p/cont->ncols);\\n if (exter[i] > inter[i]){\\n\\tsaliences->Z[i] = exter[i];\\n }else{\\n\\tif (exter[i] < inter[i]){\\n\\t saliences->Z[i] = -inter[i];\\n\\t}else{\\n\\t saliences->Z[i] = 0.0;\\n\\t}\\n }\\n }\\n }\\n\\n DestroyImage(&cont);\\n free(inter);\\n free(exter);\\n\\n return(saliences);\\n}\\n\\nImage *RemFrame(Image *fimg, int sz)\\n{\\n Image *img;\\n int y,*dst,*src,nbytes,offset;\\n\\n img = CreateImage(fimg->ncols-(2*sz),fimg->nrows-(2*sz));\\n nbytes = sizeof(int)*img->ncols;\\n offset = sz+fimg->tbrow[sz];\\n for (y=0,src=fimg->val+offset,dst=img->val; y < img->nrows;y++,src+=fimg->ncols,dst+=img->ncols){\\n memcpy(dst,src,nbytes);\\n }\\n return(img);\\n}\\n\\nAdjPxl *AdjPixels(Image *img, AdjRel *A)\\n{\\n AdjPxl *N;\\n int i;\\n\\n N = (AdjPxl *) calloc(1,sizeof(AdjPxl));\\n if(N != NULL){\\n N->dp = AllocIntArray(A->n);\\n N->n = A->n;\\n for (i=0; i < N->n; i++)\\n N->dp[i] = A->dx[i] + img->ncols*A->dy[i];\\n }else{\\n Error(MSG1,\\\"AdjPixels\\\"); \\n }\\n\\n return(N);\\n}\\n\\nImage *Abs(Image *img)\\n{\\n Image *absimg=NULL;\\n int p,n;\\n \\n n = img->ncols*img->nrows;\\n absimg = CreateImage(img->ncols,img->nrows);\\n for (p=0; p < n; p++)\\n absimg->val[p] = abs(img->val[p]);\\n return(absimg);\\n}\\n\\nCurve3D *RemSaliencesByAngle(Curve3D *curve,int radius, int angle)\\n{\\n Curve3D *scurve;\\n double area;\\n int i;\\n\\n scurve = CreateCurve3D(curve->n+1);\\n for (i=0; i < curve->n; i++){ \\n scurve->X[i] = curve->X[i];\\n scurve->Y[i] = curve->Y[i];\\n scurve->Z[i] = curve->Z[i];\\n }\\n \\n area = ((double)angle*PI*radius*radius/360.0);\\n for (i=0; i < scurve->n; i++){ \\n if (fabs(scurve->Z[i]) <= area)\\n scurve->Z[i] = 0.0; \\n }\\n\\n return(scurve);\\n}\\n\\nImage *LabelBinComp(Image *bin, AdjRel *A)\\n{\\n Image *label=NULL,*flabel=NULL,*fbin=NULL;\\n int i,j,n,sz,p,q,l=1;\\n AdjPxl *N=NULL;\\n int *FIFO=NULL;\\n int first=0,last=0;\\n \\n sz = FrameSize(A);\\n fbin = AddFrame(bin,sz,INT_MIN);\\n flabel = CreateImage(fbin->ncols,fbin->nrows);\\n N = AdjPixels(fbin,A);\\n n = fbin->ncols*fbin->nrows;\\n FIFO = AllocIntArray(n);\\n for (j=0; j < n; j++){\\n if ((fbin->val[j]==1)&&(flabel->val[j]==0)){\\n flabel->val[j]=l;\\n FIFO[last]=j; \\n last++; \\n while(first != last){\\n\\tp = FIFO[first];\\n\\tfirst++;\\n\\tfor (i=1; i < N->n; i++){\\n\\t q = p + N->dp[i];\\n\\t if ((fbin->val[q]==1)&&(flabel->val[q] == 0)){\\n\\t flabel->val[q] = flabel->val[p];\\n\\t FIFO[last] = q;\\n\\t last++;\\n\\t }\\n\\t}\\n }\\n l++;\\n first=last=0;\\n }\\n }\\n \\n label = RemFrame(flabel,sz);\\n DestroyAdjPxl(&N);\\n DestroyImage(&fbin);\\n DestroyImage(&flabel);\\n free(FIFO);\\n\\n return(label);\\n}\\n\\nCurve3D *SkelSaliences(Image *skel, int maxdist, int angle) \\n{ \\n Image *cont=NULL;\\n AdjRel *A=NULL;\\n AnnImg *aimg=NULL;\\n Curve3D *saliences=NULL;\\n Curve3D *auxsalie=NULL;\\n\\n /* Compute Euclidean IFT */\\n A = Circular(0.0);\\n cont = LabelBinComp(skel, A);\\n aimg = Annotate(skel,NULL,cont);\\n DestroyAdjRel(&A); \\n\\n A = Circular(1.5);\\n iftDilation(aimg,A);\\n auxsalie = CompSaliences(aimg, maxdist*maxdist);\\n saliences = RemSaliencesByAngle(auxsalie,maxdist,angle);\\n DestroyImage(&cont);\\n DestroyAdjRel(&A);\\n DeAnnotate(&aimg);\\n DestroyCurve3D(&auxsalie);\\n return(saliences);\\n}\\n\\nImage *Skeleton(Image *msskel, float perc)\\n{\\n Image *skel = NULL;\\n int p ,n, thres;\\n \\n skel = Abs(msskel);\\n thres = (int)((MaximumValue(skel)*perc)/100.0); \\n n = skel->ncols*skel->nrows;\\n for (p=0; p < n; p++)\\n if (skel->val[p] >= thres) \\n skel->val[p]=1;\\n else\\n skel->val[p]=0;\\n \\n return(skel);\\n}\\n\\nImage *CompMSSkel(AnnImg *aimg)\\n{\\n int i,p,q,n,maxd1,maxd2,d1,d2,MaxD;\\n Pixel u,v;\\n int sign=1,s2;\\n Image *msskel,*cont=NULL,*perim=NULL,*seed=NULL;\\n AdjRel *A;\\n\\n /* Compute MS Skeletons */\\n\\n cont = LabelContour(aimg->img);\\n perim = Perimeter(aimg->img);\\n seed = CompPaths(aimg->pred);\\n A = Circular(1.0);\\n n = aimg->label->ncols*aimg->label->nrows;\\n msskel = CreateImage(aimg->label->ncols,aimg->label->nrows);\\n\\n MaxD = INT_MIN;\\n for (p=0; p < n; p++) {\\n if (aimg->pred->val[p] != p) { /* It eliminates the countors and\\n already takes into account the\\n side option */\\n u.x = p%aimg->label->ncols;\\n u.y = p/aimg->label->ncols;\\n maxd1 = maxd2 = INT_MIN;\\n for (i=1; i < A->n; i++){\\n\\tv.x = u.x + A->dx[i];\\n\\tv.y = u.y + A->dy[i];\\n\\tif (ValidPixel(aimg->label,v.x,v.y)){\\n\\t q = v.x + aimg->label->tbrow[v.y];\\n\\t if (cont->val[seed->val[p]] == cont->val[seed->val[q]]){ \\n\\t d2 = aimg->label->val[q]-aimg->label->val[p];\\n\\t s2 = 1;\\n\\t //\\t if (d2 > (perim->val[seed->val[p]]-1-d2)){\\n\\t if (d2 > (perim->val[seed->val[p]]-d2)){\\n\\t s2 = -1;\\n\\t //\\t d2 = (perim->val[seed->val[p]]-1-d2);\\n\\t d2 = (perim->val[seed->val[p]]-d2);\\n\\t } \\n\\t if (d2 > maxd2){\\n\\t maxd2 = d2;\\n\\t sign = s2;\\n\\t }\\n\\t } else {\\n\\t d1 = cont->val[seed->val[q]] - cont->val[seed->val[p]];\\n\\t if (d1 > maxd1) \\n\\t maxd1 = d1;\\n\\t }\\n\\t}\\n }\\n if (maxd1 > 0) {\\n\\tmsskel->val[p] = INT_MAX;\\n } else {\\n\\tmsskel->val[p] = sign*maxd2;\\n\\tif (msskel->val[p] > MaxD)\\n\\t MaxD = msskel->val[p]; \\n }\\n }\\n }\\n\\n for (p=0; p < n; p++) { /* Set up SKIZ */\\n if (msskel->val[p] == INT_MAX)\\n msskel->val[p] = MaxD + 1;\\n }\\n\\n DestroyImage(&cont);\\n DestroyImage(&perim);\\n DestroyImage(&seed);\\n DestroyAdjRel(&A);\\n\\n return(msskel);\\n}\\n\\nvoid iftDilation(AnnImg *aimg, AdjRel *A)\\n{\\n Image *Dx=NULL,*Dy=NULL;\\n Queue *Q=NULL;\\n int i,p,q,n,sz;\\n Pixel u,v;\\n int *sq=NULL,tmp=INT_MAX,dx,dy;\\n char *color=NULL;\\n\\n if (aimg->seed == NULL)\\n return;\\n\\n n = MAX(aimg->img->ncols,aimg->img->nrows);\\n sq = AllocIntArray(n);\\n for (i=0; i < n; i++) \\n sq[i]=i*i;\\n\\n Dx = CreateImage(aimg->img->ncols,aimg->img->nrows);\\n Dy = CreateImage(aimg->img->ncols,aimg->img->nrows);\\n n = aimg->img->ncols*aimg->img->nrows;\\n color = AllocCharArray(n);\\n sz = FrameSize(A);\\n Q = CreateQueue(2*sz*(sz+aimg->img->ncols+aimg->img->nrows),n);\\n \\n while (aimg->seed != NULL){\\n p=RemoveSet(&(aimg->seed));\\n InsertQueue(Q,aimg->cost->val[p]%Q->C.nbuckets,p);\\n color[p]=GRAY;\\n }\\n\\n while(!EmptyQueue(Q)) {\\n p=RemoveQueue(Q);\\n color[p]=BLACK;\\n u.x = p%aimg->img->ncols;\\n u.y = p/aimg->img->ncols;\\n for (i=1; i < A->n; i++){\\n v.x = u.x + A->dx[i];\\n v.y = u.y + A->dy[i];\\n if (ValidPixel(aimg->img,v.x,v.y)){\\n\\tq = v.x + aimg->img->tbrow[v.y];\\n\\tif (color[q] != BLACK){\\n\\t dx = Dx->val[p] + abs(v.x-u.x);\\n\\t dy = Dy->val[p] + abs(v.y-u.y);\\n\\t tmp = sq[dx] + sq[dy];\\n\\t if (tmp < aimg->cost->val[q])\\n\\t {\\n\\t if (color[q] == WHITE){\\n\\t\\tInsertQueue(Q,tmp%Q->C.nbuckets,q);\\n\\t\\tcolor[q]=GRAY;\\n\\t }else\\n\\t\\tUpdateQueue(Q,q,aimg->cost->val[q]%Q->C.nbuckets,tmp%Q->C.nbuckets);\\n\\t aimg->cost->val[q] = tmp;\\n\\t aimg->pred->val[q] = p;\\n\\t aimg->label->val[q] = aimg->label->val[p];\\n\\t Dx->val[q] = dx;\\n\\t Dy->val[q] = dy;\\n\\t }\\n\\t}\\n } \\n }\\n }\\n free(color);\\n free(sq);\\n DestroyQueue(&Q);\\n DestroyImage(&Dx);\\n DestroyImage(&Dy);\\n}\\n\\nCurve *CopyCurve(Curve *curve)\\n{\\n Curve *curvec;\\n\\n curvec = CreateCurve(curve->n);\\n memcpy(curvec->X,curve->X,curve->n*sizeof(double));\\n memcpy(curvec->Y,curve->Y,curve->n*sizeof(double));\\n return(curvec);\\n}\\n\\nCurve *Histogram(Image *img)\\n{\\n int i,p,n,nbins;\\n Curve *hist=NULL;\\n\\n nbins = MaximumValue(img)+1;\\n hist = CreateCurve(nbins);\\n n = img->ncols*img->nrows;\\n for (p=0; p < n; p++)\\n hist->Y[img->val[p]]++;\\n for (i=0; i < nbins; i++) \\n hist->X[i] = i;\\n\\n return(hist);\\n}\\n\\nvoid SortCurve(Curve *curve, int left, int right, char order)\\n{\\n int pivot;\\n \\n if (left < right) {\\n pivot = PartCurve(curve,left,right,order);\\n SortCurve(curve,left,pivot-1,order);\\n SortCurve(curve,pivot+1,right,order); \\n }\\n}\\n\\nint PartCurve (Curve *curve, int left, int right, char order)\\n{\\n double y;\\n int i;\\n double X,Y;\\n \\n y = curve->Y[left];\\n i = left;\\n do {\\n if (order == INCREASING){\\n while ((curve->Y[left] <= y)&&(left <= right)) left++; \\n while (curve->Y[right] > y) right--;\\n } else { /* order = DECREASING */\\n while ((curve->Y[left] >= y)&&(left <= right)) left++; \\n while (curve->Y[right] < y) right--;\\n }\\n if (left < right){\\n X = curve->X[left];\\n Y = curve->Y[left];\\n curve->X[left] = curve->X[right];\\n curve->Y[left] = curve->Y[right];\\n curve->X[right] = X;\\n curve->Y[right] = Y;\\n left++; right--;\\n }\\n } while (left <= right);\\n\\n left = i;\\n if (left != right){\\n X = curve->X[left];\\n Y = curve->Y[left];\\n curve->X[left] = curve->X[right];\\n curve->Y[left] = curve->Y[right];\\n curve->X[right] = X;\\n curve->Y[right] = Y;\\n }\\n\\n return (right);\\n}\\n\\nvoid InvertXY(Curve *curve)\\n{\\n double tmp;\\n int i;\\n for (i=0; in; i++){\\n tmp = curve->X[i];\\n curve->X[i] = curve->Y[i];\\n curve->Y[i] = tmp;\\n }\\n}\\n\\n/* Descriptor functions ***************************/\\n\\n/* BIC */\\nint *Quantize_colors(CImage *img, int color_dim){\\n unsigned long i;\\n unsigned long r, g, b;\\n unsigned long fator_g, fator_b;\\n int *color, n;\\n \\n n = img->C[0]->nrows * img->C[0]->ncols; \\n\\n color = (int *) calloc(n, sizeof(int));\\n if(color==NULL){\\n printf(\\\"\\\\nOut of memory \\\\n\\\");\\n exit(-1);\\n }\\n \\n fator_g = color_dim;\\n fator_b = fator_g*color_dim;\\n \\n for(i=0; iC[0]->val[i]/256;\\n g = color_dim*img->C[1]->val[i]/256;\\n b = color_dim*img->C[2]->val[i]/256;\\n \\n color[i] = (r + fator_g*g + fator_b*b);\\n }\\n return color;\\n}\\n\\nunsigned char Compute_log(float value){\\n unsigned char result;\\n \\n value = 255. * value;\\n if(value==0.) result=0;\\n else if(value<1.) result=1;\\n else if(value<2.) result=2;\\n else if(value<4.) result=3;\\n else if(value<8.) result=4;\\n else if(value<16.) result=5;\\n else if(value<32.) result=6;\\n else if(value<64.) result=7;\\n else if(value<128.) result=8;\\n else result=9;\\n \\n return result;\\n}\\n\\nvoid Compress_histogram(unsigned char *ch, unsigned long *h, \\n\\t\\t\\tunsigned long max, int size){\\n int i;\\n unsigned char v;\\n \\n for(i=0; inrows; y++){\\n for(x=0L; xncols; x++){\\n p = x + img->tbrow[y];\\n border=FALSE;\\n for (i=1; i < A->n; i++){\\n\\tv.x = x + A->dx[i];\\n\\tv.y = y + A->dy[i];\\n\\tif (ValidPixel(img,v.x,v.y)){\\n\\t q = v.x + img->tbrow[v.y];\\n\\t if(ppt[p].color!=ppt[q].color){ \\n\\t border=TRUE;\\n\\t break;\\n\\t }\\n\\t}\\n }\\n if(border==FALSE) \\n\\tppt[p].frequency=LOW;\\n else ppt[p].frequency=HIGH;\\n }\\n }\\n DestroyAdjRel(&A);\\n}\\n\\nProperty *Compute_pixels_properties(CImage *img)\\n{\\n Property *p;\\n int *color, i, n;\\n \\n n = img->C[0]->nrows * img->C[0]->ncols; \\n \\n p = (Property *) calloc(n, sizeof(Property));\\n if(p==NULL){\\n printf(\\\"\\\\nOut of memory \\\\n\\\");\\n exit(-1);\\n }\\n \\n color = Quantize_colors(img, 4);\\n for(i=0; iC[0], p);\\n \\n free(color);\\n return p;\\n}\\n\\nVisualFeature *Compute_histograms(Property *p, int n){\\n VisualFeature *vf = (VisualFeature *) calloc(1,sizeof(VisualFeature));\\n unsigned long i;\\n \\n for(i=0; icolorH[i] = 0;\\n vf->lowH[i] = 0;\\n vf->highH[i] = 0;\\n }\\n \\n for(i=0; icolorH[p[i].color]++;\\n \\n if(p[i].frequency==LOW) \\n vf->lowH[p[i].color]++;\\n else \\n vf->highH[p[i].color]++;\\n }\\n return vf;\\n}\\n\\nCompressedVisualFeature *Compress_histograms(VisualFeature *vf, int npixels)\\n{\\n CompressedVisualFeature *cvf = (CompressedVisualFeature *) calloc(1,sizeof(CompressedVisualFeature));\\n \\n Compress_histogram(cvf->colorH, vf->colorH, npixels, SIZE);\\n Compress_histogram(cvf->lowH, vf->lowH, npixels, SIZE);\\n Compress_histogram(cvf->highH, vf->highH, npixels, SIZE);\\n \\n return cvf;\\n}\\n\\nvoid Write_visual_features(char *filename,char *dbname, CompressedVisualFeature *cvf)\\n{\\n FILE *file;\\n int i;\\n \\n if((file = fopen(dbname, \\\"a+t\\\")) == NULL)\\n {\\n fprintf(stderr, \\\"Can't open %s \\\\n\\\", dbname);\\n exit(-1);\\n }\\n \\n fprintf(file, \\\"%s\\\\t\\\", filename);\\n for(i=0;ilowH[i], cvf->highH[i]);\\n }\\n fprintf(file, \\\"\\\\n\\\");\\n \\n fclose(file);\\n}\\n\\nCompressedVisualFeature *Extract_visual_features(CImage *img)\\n{\\n Property *p;\\n VisualFeature *vf;\\n CompressedVisualFeature *cvf;\\n int npixels;\\n \\n npixels = img->C[0]->nrows * img->C[0]->ncols;\\n \\n p = Compute_pixels_properties(img);\\n vf = Compute_histograms(p, npixels);\\n cvf = Compress_histograms(vf, npixels);\\n \\n free(p);\\n return cvf;\\n}\\n\\nCurve *BIC(CImage *img)\\n{\\n Property *p;\\n VisualFeature *vf;\\n CompressedVisualFeature *cvf;\\n int i, npixels;\\n Curve *curve = CreateCurve(2*SIZE);\\n \\n npixels = img->C[0]->nrows * img->C[0]->ncols;\\n \\n p = Compute_pixels_properties(img);\\n vf = Compute_histograms(p, npixels);\\n cvf = Compress_histograms(vf, npixels);\\n \\n for (i=0; iX[i] = i;\\n curve->Y[i] = cvf->lowH[i];\\n curve->X[i+SIZE] = i+SIZE;\\n curve->Y[i+SIZE] = cvf->highH[i];\\n }\\n\\n free(p);\\n free(vf);\\n free(cvf);\\n return curve;\\n}\\n\\n\\ndouble gray_level_BIC(Image *img1, Image *img2){\\n Property *p1, *p2;\\n VisualFeature *vf1, *vf2;\\n CompressedVisualFeature *cvf1, *cvf2;\\n int i, n1, n2;\\n double dist;\\n\\n n1 = img1->nrows * img1->ncols; \\n n2 = img2->nrows * img2->ncols; \\n\\n p1 = (Property *) calloc(n1, sizeof(Property));\\n p2 = (Property *) calloc(n2, sizeof(Property));\\n\\n if((p1==NULL)||(p2==NULL)){\\n printf(\\\"\\\\nOut of memory \\\\n\\\");\\n exit(-1);\\n }\\n \\n for(i=0; ival[i];\\n }\\n for(i=0; ival[i];\\n }\\n \\n Compute_frequency_property(img1,p1);\\n Compute_frequency_property(img2,p2);\\n \\n vf1 = Compute_histograms(p1, n1);\\n vf2 = Compute_histograms(p2, n2);\\n \\n cvf1 = Compress_histograms(vf1, n1);\\n cvf2 = Compress_histograms(vf2, n2);\\n \\n dist = 0.0;\\n for (i=0; ilowH[i] - cvf2->lowH[i]);\\n dist += fabs(cvf1->highH[i] - cvf2->highH[i]);\\n }\\n \\n free(p1);\\n free(p2);\\n free(vf1);\\n free(vf2);\\n free(cvf1);\\n free(cvf2);\\n return dist;\\n}\\n\\nFeatureVector1D *BIC_ExtractionAlgorithm(CImage *in){\\n Curve *curve = NULL;\\n FeatureVector1D *fv = NULL;\\n curve = BIC(in);\\n fv = CurveTo1DFeatureVector(curve);\\n \\n DestroyCurve(&curve);\\n return fv;\\n}\\n\\ndouble BIC_DistanceAlgorithm(FeatureVector1D *fv1, FeatureVector1D *fv2)\\n{\\n\\treturn L1_Distance(fv1, fv2);\\n}\\n\\n/* Fourier Descriptor */\\ndouble Cabs(double x, double y) {\\n return (sqrt( (x*x) + (y*y)));\\n}\\n\\nCurve *Image2Curve(Image *img) { /* img = binary image */\\n Curve3D *curve; //ponto (x,y) e z = ordem no contorno\\n Curve *curve2;\\n Image *contour = NULL;\\n int i;\\n int npixels;\\n int count = 0;\\n int j = 0 ;\\n \\n contour = LabelContPixel(img);\\n npixels = contour->ncols * contour->nrows;\\n \\n for (i = 0; i < npixels; i++){\\n if (contour->val[i]!=0)\\n count++;\\n }\\n \\n curve = CreateCurve3D(count+1);\\n \\n for (i = 0; i < npixels; i++){\\n if (contour->val[i]!=0){\\n curve->X[j] = i % contour->ncols;\\n curve->Y[j] = i / contour->ncols;\\n curve->Z[j] = contour->val[i];\\n j++;\\n }\\n } \\n \\n SortCurve3D(curve, 0, (curve->n - 2), INCREASING);\\n \\n curve2 = CreateCurve(curve->n);\\n for (i=0;in;i++){\\n curve2->X[i]=curve->X[i];\\n curve2->Y[i]=curve->Y[i];\\n }\\n \\n DestroyCurve3D(&curve);\\n DestroyImage(&contour);\\n return (curve2);\\n}\\n\\nCurve *FourierDescriptor(Image *img) {\\n Curve *c = NULL; \\n Curve *curve = NULL;\\n Curve *mag = NULL;\\n int i;\\n int z; /* lixo */\\n int tam;\\n int nn = 0;\\n double normfactor = 0;\\n\\n curve = Image2Curve(img);\\n \\n tam = curve->n;\\n i = 1;\\n nn = tam;\\n while(nn != 1) {\\n nn >>= 1;\\n ++i;\\n }\\n \\n for(; i; i--)\\n nn <<= 1;\\n \\n if (nn < 128)\\n nn = 128;\\n \\n c = CreateCurve(nn);\\n \\n for (i = 0; i < tam ; i++)\\n {\\n c->X[i] = (double) curve->X[i];\\t\\n c->Y[i] = (double) curve->Y[i];\\n }\\n \\n for (i = tam ; i < nn ; i++)\\n {\\n c->X[i] = 0;\\n c->Y[i] = 0;\\n }\\n \\n z = FFT(1, nn,c->X ,c->Y);\\n\\n mag = CreateCurve(126);\\n normfactor = Cabs(c->X[0],c->Y[0]);\\n \\n for (i = 1; i <= 126; i++)\\n {\\n mag->X[i-1] = i - 1;\\n mag->Y[i-1] = (double) (Cabs(c->X[i],c->Y[i])/normfactor);\\n }\\n \\n DestroyCurve(&c); \\n DestroyCurve(&curve); \\n return (mag);\\n}\\n\\nFeatureVector1D *FourierDescriptor_ExtractionAlgorithm(Image *in){\\n Curve *curve = NULL;\\n FeatureVector1D *fv = NULL;\\n \\n curve = FourierDescriptor(in);\\n fv = CurveTo1DFeatureVector(curve);\\n \\n DestroyCurve(&curve);\\n return fv;\\n}\\n\\ndouble Fourier_DistanceAlgorithm(FeatureVector1D *fv1, FeatureVector1D *fv2){\\n\\treturn EuclideanDistance(fv1, fv2);\\n}\\n\\n/* Moments Invariant */\\ndouble MomentPQ(int p, int q, Image *img, int max){\\n int i, x, y;\\n double sum = 0.0;\\n \\n for (i = 0; i < img->ncols * img->nrows; i++)\\n {\\n if (img->val[i] != 0 )\\n\\t{\\n\\t x = 1 + i%img->ncols; /* don't do 0^0 */\\n\\t y = 1 + i/img->ncols; \\n\\t sum = sum + (pow(x, p) * pow(y,q) * ((double) img->val[i]/max));\\n\\t}\\n }\\n \\n return (sum);\\n}\\n\\nCurve *MomentInv(Image *img) {\\n Curve * curve;\\n int i;\\n int max;\\n \\n /* mPQ momentes of order (P+Q) */\\n double m00, m01, m10, m11, m20, m02, m12, m21, m03, m30;\\n \\n /* center moments */\\n double xc, yc;\\n \\n /* normalized central moments (Eta) */\\n double n00, n10, n01, n02, n20, n11, n12, n21, n03, n30; \\n \\n /* invariant moments (Phi) */\\n double f1, f2, f3, f4, f5, f6, f7;\\n \\n float g; /* gamma = (p+q)/2 + 1 */\\n \\n /* n = Upq/U00 */\\n \\n max = 0;\\n \\n for (i = 0; i < img->ncols * img->nrows ; i++)\\n {\\n if (img->val[i] > max)\\n\\tmax = img->val[i];\\n }\\n \\n m00 = MomentPQ(0,0, img, max);\\n m01 = MomentPQ(0,1, img, max);\\n m10 = MomentPQ(1,0, img, max);\\n m11 = MomentPQ(1,1, img, max); \\n m12 = MomentPQ(1,2, img, max); \\n m21 = MomentPQ(2,1, img, max); \\n m02 = MomentPQ(0,2, img, max);\\n m20 = MomentPQ(2,0, img, max); \\n m03 = MomentPQ(0,3, img, max);\\n m30 = MomentPQ(3,0, img, max); \\n \\n xc = (double) m10 / m00;\\n yc = (double) m01 / m00;\\n \\n n00 = 1.0; \\n \\n n10 = 0.0;\\n \\n n01 = 0.0;\\n \\n g = 2.0; \\n \\n n20 = (double) (m20 - (xc * m10)) / (pow(m00, g));\\n \\n n02 = (double) (m02 - (yc * m01)) / (pow(m00, g));\\n \\n n11 = (double) (m11 - (yc * m10)) / (pow(m00, g));\\n \\n g = 2.5;\\n \\n n30 = (double) (m30 - (3 * xc * m20) + (2 * (pow(xc,2)) * m10) ) / (pow(m00, g)); \\n \\n n12 = (double) (m12 - (2 * yc * m11) - (xc * m02) + (2 * pow(yc,2) * m10) ) / (pow(m00, g)) ;\\n \\n n21 = (double) (m21 - (2 * xc * m11) - (yc * m20) + (2 * pow(xc,2) * m01) ) / (pow(m00, g));\\n \\n n03 = (double) (m03 - (3 * yc * m02) + (2 * (pow(yc,2)) * m01)) / (pow(m00, g)); \\n \\n f1 = (double) n20 + n02;\\n \\n f2 = (double) (pow((n20 - n02),2)) + (4 * (pow(n11,2)));\\n \\n f3 = (double) (pow((n30 - (3 * n12)),2)) + (pow( ( (3 * n21) - n03),2));\\n \\n f4 = (double) (pow((n30 + n12),2)) + (pow((n21 + n03),2));\\n \\n f5 = (double) ((n30 - (3 * n12)) * (n30 + n12) * ((pow((n30 + n12),2)) - (3 * (pow((n21 + n03),2))))) + \\n (((3 * n21) - n03) * (n21 + n03) * ((3 * (pow((n30 + n12),2))) - (pow((n21 + n03),2))));\\n \\n f6 = (double) ((n20 + n02) * ((pow((n30 + n12),2)) - (pow((n21 + n03),2)))) +\\n ((4 * n11) * (n30 + n12) * (n21 + n03)); \\n \\n f7 = (double) (((3 * n21) - n03) * (n30 + n12) * ((pow((n30 + n12),2)) - (3 * (pow((n21 + n03),2))))) +\\n (((3 * n12) - n30) * (n21 + n03) * ((3 * (pow((n30 + n12),2))) - (pow((n21 + n03),2))));\\n \\n curve = CreateCurve(7);\\n \\n curve->X[0] = 0.0;\\n curve->Y[0] = f1;\\n \\n curve->X[1] = 1.0;\\n curve->Y[1] = f2;\\n \\n curve->X[2] = 2.0; \\n curve->Y[2] = f3;\\n \\n curve->X[3] = 3.0; \\n curve->Y[3] = f4;\\n \\n curve->X[4] = 4.0; \\n curve->Y[4] = f5;\\n \\n curve->X[5] = 5.0; \\n curve->Y[5] = f6;\\n \\n curve->X[6] = 6.0; \\n curve->Y[6] = f7;\\n\\n return (curve);\\n}\\n\\nCurve *MomentInvariant(Image *img) { // contorno e objeto inteiro\\n Image *contour = NULL;\\n Curve *c1 = NULL;\\n Curve *c2 = NULL;\\n Curve *curve = NULL;\\n int i;\\n \\n contour = LabelContour(img);\\n c1 = MomentInv(contour);\\n c2 = MomentInv(img);\\n \\n curve = CreateCurve(c1->n + c2->n);\\n for (i=0; in; i++){\\n curve->X[i] = i;\\n curve->Y[i] = c1->Y[i];\\n }\\n for (i=0; in; i++){\\n curve->X[i+c1->n] = i + c1->n;\\n curve->Y[i+c1->n] = c2->Y[i];\\n }\\n \\n DestroyCurve(&c1);\\n DestroyCurve(&c2);\\n DestroyImage(&contour);\\n \\n return (curve); \\n}\\n\\nFeatureVector1D *MomentInvariant_ExtractionAlgorithm(Image *in){\\n Curve *curve = NULL;\\n FeatureVector1D *fv = NULL;\\n \\n curve = MomentInvariant(in);\\n fv = CurveTo1DFeatureVector(curve);\\n\\n DestroyCurve(&curve);\\n return fv;\\n}\\n\\ndouble MomentInvariant_DistanceAlgorithm(FeatureVector1D *fv1, FeatureVector1D *fv2){\\n\\treturn 1-EuclideanDistance(fv1, fv2);\\n}\\n\\n/* BAS */\\n/*resample curve*/\\nrepresentation_type *resample(representation_type *curve, int nsamples)\\n{\\n representation_type *rcurve;\\n Image *img1, *img2;\\n int x;\\n \\n img1= CreateImage(curve->length, 3);\\n \\n for (x=0; xlength; x++){\\n img1->val[x] = curve->mean[x];\\n img1->val[x+img1->tbrow[1]] = curve->second[x];\\n img1->val[x+img1->tbrow[2]] = curve->third[x];\\n }\\n \\n img2 = Scale(img1, (((float) nsamples)/curve->length), 1);\\n \\n rcurve = (representation_type *) calloc(1, sizeof(representation_type));\\n rcurve->length = nsamples;\\n rcurve->mean = (int *) calloc(nsamples, sizeof(int));\\n rcurve->second =(int *) calloc(nsamples, sizeof(int));\\n rcurve->third = (int *) calloc(nsamples, sizeof(int));\\n for (x=0; xmean[x] = img2->val[x];\\n rcurve->second[x] = img2->val[x+img2->tbrow[1]];\\n rcurve->third[x] = img2->val[x+img2->tbrow[2]];\\n }\\n \\n DestroyImage(&img1);\\n DestroyImage(&img2);\\n return(rcurve);\\n}\\n\\ndouble find_angle(deltax,deltay)\\n int deltax;\\n int deltay;\\n{\\n double angle;\\n double pi;\\n \\n pi=22.0/7.0; \\n \\n if((deltax==0) && (deltay==0))\\n angle=0.0;\\n else{\\n angle=atan((10.0*abs(deltax))/(10.0*abs(deltay)));\\n angle=angle*180.0/pi; \\n if((deltax <= 0) && (deltay >= 0)) \\n angle=360.0-angle;\\n else if((deltax <= 0) && (deltay <=0)) \\n angle=180.0 + angle; \\n else if((deltax >= 0) && (deltay <=0)) \\n angle=180.0 - angle;\\n }\\n \\n return(angle);\\n}\\n\\nrepresentation_type *extract_feature(boun)\\n boundary_type *boun;\\n{\\n representation_type *curve_feature; \\n int i,j,x1,x2,x3,y1,y2,y3,curvelength;\\n double angle_1,angle_2,curve,total,previous;\\n int delta_x, delta_y,mean,second,third;\\n int *bearing_array;\\n \\n curve_feature = (representation_type *) calloc(1, sizeof(representation_type));\\n curve_feature->length=boun->length;\\n curve_feature->mean= (int *) calloc(boun->length, sizeof(int));\\n curve_feature->second=(int *) calloc(boun->length, sizeof(int));\\n curve_feature->third=(int *) calloc(boun->length, sizeof(int));\\n \\n \\n curvelength=(int)(boun->length/2);\\n bearing_array=(int *) calloc((curvelength-1), sizeof(int));\\n for(i=0; ilength; i++){\\n total=0.0;\\n x1=boun->X[((i-1)+boun->length)%boun->length];\\n y1=boun->Y[((i-1)+boun->length)%boun->length];\\n x2=boun->X[i];\\n y2=boun->Y[i];\\n x3=boun->X[((i+1)+boun->length)%boun->length];\\n y3=boun->Y[((i+1)+boun->length)%boun->length];\\n \\n delta_x=x1-x2;\\n delta_y=-(y1-y2);\\n angle_1=find_angle(delta_x,delta_y);\\n delta_x=x3-x2;\\n delta_y=-(y3-y2);\\n angle_2=find_angle(delta_x,delta_y);\\n if(angle_1 >= angle_2)\\n curve=angle_1-angle_2;\\n else\\n curve=360.0 + angle_1-angle_2;\\n \\n total+=curve;\\n bearing_array[0]=(int)curve;\\n previous=curve;\\n for(j=2; jX[((i-j)+boun->length)%boun->length];\\n y1=boun->Y[((i-j)+boun->length)%boun->length];\\n x2=boun->X[i];\\n y2=boun->Y[i];\\n x3=boun->X[((i+j)+boun->length)%boun->length];\\n y3=boun->Y[((i+j)+boun->length)%boun->length];\\n delta_x=x1-x2;\\n delta_y=-(y1-y2);\\n angle_1=find_angle(delta_x,delta_y);\\n delta_x=x3-x2;\\n delta_y=-(y3-y2);\\n angle_2=find_angle(delta_x,delta_y);\\n if(angle_1 >= angle_2)\\n\\tcurve=angle_1-angle_2;\\n else\\n\\tcurve=360.0 + angle_1-angle_2;\\n \\n if(j > 3){\\n\\tif(((curve-previous) > 180))\\n\\t curve=curve-360.0;\\n\\telse\\n\\t if(((previous-curve) > 180))\\n\\t curve=curve+360.0;\\n }\\n \\n bearing_array[j-1]=(int)curve; \\n total+=curve;\\n previous=curve;\\n }\\n \\n mean=(int)(total/(double)(curvelength-1));\\n total=0.0;\\n for(j=0;jmean[i]=mean;\\n curve_feature->second[i]=second;\\n curve_feature->third[i]=third;\\n } \\n free(bearing_array);\\n return(curve_feature);\\n}\\n\\nCurve *BAS(Image *in,int rsp,int nsamples){\\n Curve *featurevector = NULL;\\n Curve *contour = NULL;\\n Curve *moment1 = NULL;\\n Curve *moment2 = NULL;\\n Curve *moment3 = NULL;\\n \\n boundary_type *bound;\\n representation_type *curve, *rcurve;\\n int i;\\n\\n contour = Image2Curve(in);\\n bound = (boundary_type *) calloc(1, sizeof(boundary_type));\\n bound->length = contour->n;\\n bound->X = (int *)calloc(bound->length, sizeof(int));\\n bound->Y = (int *)calloc(bound->length, sizeof(int));\\n for (i=0; ilength; i++){\\n bound->X[i] = (int)contour->X[i];\\n bound->Y[i] = (int)contour->Y[i];\\n }\\n \\n curve = extract_feature(bound);\\n\\n if(rsp == 0)\\n {\\n \\trcurve = resample(curve, curve->length);\\n\\tnsamples = curve->length;\\n }\\n else\\n\\trcurve = resample(curve, nsamples);\\n\\n moment1 = CreateCurve(nsamples);\\n moment2 = CreateCurve(nsamples);\\n moment3 = CreateCurve(nsamples);\\n \\n featurevector = CreateCurve(3*nsamples);\\n for (i=0; i<3*nsamples; i++){\\n featurevector->X[i] = (double)i;\\n }\\n \\n for (i=0; iX[i]= moment2->X[i]= moment3->X[i]=(double)i;\\n featurevector->Y[i] = moment1->Y[i]= (double) rcurve->mean[i];\\n featurevector->Y[nsamples+i] = moment2->Y[i]= (double) rcurve->second[i];\\n featurevector->Y[2*nsamples+i] = moment3->Y[i]= (double) rcurve->third[i];\\n }\\n\\n free(bound->X);\\n free(bound->Y);\\n free(bound);\\n free(curve->mean);\\n free(curve->second);\\n free(curve->third);\\n free(curve);\\n free(rcurve->mean);\\n free(rcurve->second);\\n free(rcurve->third);\\n free(rcurve);\\n DestroyCurve(&contour);\\n DestroyCurve(&moment1);\\n DestroyCurve(&moment2);\\n DestroyCurve(&moment3);\\n\\n return featurevector;\\n}\\n\\nFeatureVector1D *BAS_ExtractionAlgorithm(Image *in,int rsp,int nsamples){\\n Curve *curve = NULL;\\n FeatureVector1D *fv = NULL;\\n \\n curve = BAS(in,rsp,nsamples);\\n fv = CurveTo1DFeatureVector(curve);\\n \\n DestroyCurve(&curve);\\n return fv;\\n}\\n\\n\\nlong min(Dist1,Dist2,Dist3)\\n long Dist1;\\n long Dist2;\\n long Dist3;\\n{\\n if((Dist1<=Dist2) && (Dist1<=Dist3)) \\n return(Dist1);\\n else if((Dist2<=Dist1) && (Dist2<=Dist3)) \\n return(Dist2);\\n /*else if((Dist3<=Dist1) && (Dist3<=Dist2)) */\\n return(Dist3);\\n}\\n\\n\\nlong Cum_Dist_Optimal(fv1,fv2,dim1,dim2,DISTANCE)\\n representation_type fv1;\\n representation_type fv2;\\n int dim1;\\n int dim2;\\n long *DISTANCE;\\n{\\n long temp_dist;\\n int i,j;\\n int penalty;\\n \\n penalty=300;\\n /* OPTIMAL CORRESPONDENCE OF STRINGS\\n */\\n DISTANCE[0*(dim2+1)+0]=0;\\n for(j=1;j<=dim2;j++)\\n DISTANCE[0*(dim2+1)+j]=j * penalty;\\n \\n for(i=1;i<=dim1;i++)\\n DISTANCE[i*(dim2+1)+0]=i * penalty;\\n \\n for(i=1;i<=dim1;i++)\\n for(j=1;j<=dim2;j++)\\n if(abs(i-j) < (5)){\\n\\ttemp_dist=abs(fv1.mean[i-1]-fv2.mean[j-1]) +\\n\\t abs(fv1.second[i-1]-fv2.second[j-1]) +\\n\\t abs(fv1.third[i-1]-fv2.third[j-1]);\\n\\t\\n\\tDISTANCE[i*(dim2+1)+j]= temp_dist +\\n\\t min(DISTANCE[(i-1)*(dim2+1)+(j-1)],\\n\\t DISTANCE[(i-1)*(dim2+1)+(j)] + penalty,\\n\\t DISTANCE[(i)*(dim2+1)+(j-1)] + penalty); \\n }\\n return(DISTANCE[(dim1)*(dim2+1)+(dim2)]/dim2);\\n}\\n\\nlong find_distance(representation_type fv1, representation_type fv2,\\n\\t\\t int dim1, int dim2)\\n{\\n long distance,k,i,j,temp_dist;\\n representation_type temp_list1, temp_list2;\\n long *DISTANCE;\\n \\n\\tDISTANCE=(long *) calloc((dim1+1)*(dim2+1),sizeof(long));\\n \\n temp_list1.mean=(int *) calloc(dim2,sizeof(int));\\n temp_list1.second=(int *) calloc(dim2,sizeof(int));\\n temp_list1.third=(int *) calloc(dim2,sizeof(int));\\n temp_list2.mean=(int *) calloc(dim2,sizeof(int));\\n temp_list2.second=(int *) calloc(dim2,sizeof(int));\\n temp_list2.third=(int *) calloc(dim2,sizeof(int));\\n \\n temp_dist=10000000;\\n \\n for(i=0;idistance) temp_dist=distance;\\n }\\n /***Taking the mirror of fv2 *****/\\n \\n for(i=0;idistance) temp_dist=distance;\\n }\\n \\n distance=temp_dist;\\n \\n free(temp_list1.mean);\\n free(temp_list1.second);\\n free(temp_list1.third);\\n free(temp_list2.mean);\\n free(temp_list2.second);\\n free(temp_list2.third);\\n free(DISTANCE);\\n return(distance);\\n}\\n\\ndouble BAS_DistanceAlgorithm(FeatureVector1D *c1, FeatureVector1D *c2){\\n \\n representation_type fv1, fv2;\\n int n, m, i;\\n long dist;\\n \\n n = c1->n/3;\\n m = c2->n/3;\\n fv1.mean=(int *) calloc(n,sizeof(int));\\n fv1.second=(int *) calloc(n,sizeof(int));\\n fv1.third=(int *) calloc(n,sizeof(int));\\n fv2.mean=(int *) calloc(m,sizeof(int));\\n fv2.second=(int *) calloc(m,sizeof(int));\\n fv2.third=(int *) calloc(m,sizeof(int)); \\n \\n for (i=0; iX[i];\\n fv1.second[i] = (int)c1->X[n + i];\\n fv1.third[i] = (int)c1->X[2*n + i];\\n }\\n\\n for (i=0; iX[i];\\n fv2.second[i] = (int)c2->X[m + i];\\n fv2.third[i] = (int)c2->X[2*m + i];\\n }\\n \\n dist = find_distance(fv1,fv2, n, m);\\n \\n free(fv1.mean);\\n free(fv1.second);\\n free(fv1.third);\\n free(fv2.mean);\\n free(fv2.second);\\n free(fv2.third);\\n \\n return dist;\\n}\\n\\n/* Tensor Scale */\\nFeatureVector1D *TensorScale_ExtractionAlgorithm(Image *in){\\n\\tTensorScale *ts = NULL;\\n\\tFeatureVector1D *fv = NULL;\\n\\tfloat *hist = NULL;\\n\\tint i;\\n\\t\\n\\tts = CreateBinaryTensorScale(in,24);\\n\\thist = TSOrientationHistogram(ts);\\n\\n\\t/*convertendo hist para featurevector1D*/\\n\\tfv = CreateFeatureVector1D(HISTOGRAMSIZE+1);\\n\\tfor(i = 0; i < HISTOGRAMSIZE+1; i++)\\n\\t\\tfv->X[i] = hist[i];\\n\\t\\n\\tfree(hist);\\n\\tDestroyTensorScale(&ts);\\n\\n\\treturn fv;\\n}\\n\\nTensorScale *CreateBinaryTensorScale(Image *bin, int m_pairs){\\n Image *edt,*edt2,*bin2;\\n Point *epsilon;\\n TensorScale *ts = NULL;\\n Vector *tau;\\n int i,j,k,p,v,vi,n;\\n float x,y,xc,yc,taux, tauy, aux;\\n float a2,b2,b1,teta,u1,v1,u2,v2,aa,acc,wt,w;\\n float gSxy, gSy2_x2;\\n float sin_teta, cos_teta;\\n float *lt_sqrt;\\n int d,d1,d2,dmax;\\n int ncols,nrows;\\n\\n ncols = bin->ncols;\\n nrows = bin->nrows;\\n n = ncols*nrows;\\n\\n bin2 = CopyImage(bin);\\n p = bin2->tbrow[nrows-1];\\n for(i=0; ival[i] = 0;\\n bin2->val[p+i] = 0;\\n }\\n for(i=0; itbrow[i];\\n bin2->val[p] = 0;\\n bin2->val[p+ncols-1] = 0;\\n }\\n\\n //------ Euclidean distance transform ----------------\\n edt2 = TSEDistTrans(bin2);\\n\\n dmax = MaximumValue(edt2);\\n lt_sqrt = (float *)malloc((dmax+1)*sizeof(float));\\n for(i=0;i<=dmax;i++)\\n lt_sqrt[i] = sqrtf((float)i);\\n\\n edt = CreateImage(ncols,nrows);\\n for(p=0; pval[p];\\n d = ROUND(lt_sqrt[d]);\\n edt->val[p] = d;\\n }\\n\\n //---------------------------------------------------\\n\\n ts = (TensorScale *)malloc(sizeof(TensorScale));\\n ts->orientation = CreateDImage(ncols,nrows);\\n ts->anisotropy = CreateDImage(ncols,nrows);\\n ts->thickness = CreateDImage(ncols,nrows);\\n ts->m_pairs = m_pairs;\\n\\n tau = (Vector *)malloc(sizeof(Vector)*m_pairs);\\n epsilon = (Point *)malloc(sizeof(Point)*m_pairs);\\n\\n teta = 0.0;\\n for(i=0;itbrow[i]+j;\\n if(bin2->val[p] == 0) continue;\\n\\n vi = edt->val[p];\\n //--------- Sample lines --------------------------------------\\n gSxy = gSy2_x2 = 0.0;\\n xc = j+0.5; yc = i+0.5;\\n for(k=0;kval[(int)(xc+x) + edt->tbrow[(int)(yc+y)]];\\n\\t if(d1 == 0)\\n\\t break;\\n\\t }\\n\\t \\n\\t if(d2==0){\\n\\t d2 = edt->val[(int)(xc-x) + edt->tbrow[(int)(yc-y)]];\\n\\t if(d2 == 0)\\n\\t break;\\n\\t }\\n\\n\\t d = (d10.0) teta=PI/2.0;\\n\\telse teta=-PI/2.0;\\n }\\n else{\\n\\tteta = atanf((gSxy+gSxy)/gSy2_x2);\\n\\t\\n\\tif(gSxy<0.0 && teta<0.0) teta+=PI;\\n\\telse if(gSxy>0.0 && teta>0.0) teta-=PI;\\n\\telse if(teta==0.0 && gSy2_x2>0.0) teta=PI;\\n }\\n teta /= 2.0;\\n\\n //----------------- A & B ---------------------------------\\n b2 = (float)edt2->val[p];\\n b1 = lt_sqrt[(int)b2];\\n \\n acc = wt = 0.0;\\n sin_teta = sinf(teta);\\n cos_teta = cosf(teta);\\n for(k=0;k=b2){\\n\\t w = (v1<0.0)?(b1+v1):(b1-v1);\\n\\t acc += w*aa;\\n\\t wt += w;\\n\\t }\\n\\t}\\n }\\n\\n if(wt>0.0)\\n\\ta2 = acc/wt;\\n else\\n\\ta2 = b2;\\n\\n aux = 1.0-b2/a2;\\n if(aux<0.0) aux = 0.0;\\n ts->anisotropy->val[p] = sqrtf(aux);\\n ts->thickness->val[p] = b1; //sqrtf(b2);\\n\\n if(teta<0.0) teta+=(float)PI;\\n if(teta>PI) teta = PI;\\n teta = PI-teta;\\n\\n ts->orientation->val[p] = teta;\\n }\\n }\\n\\n free(tau);\\n free(epsilon);\\n free(lt_sqrt);\\n DestroyImage(&edt);\\n DestroyImage(&edt2);\\n DestroyImage(&bin2);\\n\\n return ts;\\n}\\n\\nvoid DestroyTensorScale(TensorScale **ts){\\n if(*ts != NULL){\\n DestroyDImage(&((*ts)->orientation));\\n DestroyDImage(&((*ts)->anisotropy));\\n DestroyDImage(&((*ts)->thickness));\\n free(*ts);\\n }\\n *ts = NULL;\\n}\\n\\nfloat *TSOrientationHistogram(TensorScale *ts){\\n float *hist;\\n float ratio,sum;\\n double an,th;\\n int w,h,i,j,p,bin;\\n \\n ratio = (float)HISTOGRAMSIZE/PI;\\n hist = (float *)malloc(sizeof(float)*(HISTOGRAMSIZE+1));\\n memset(hist, 0, sizeof(float)*(HISTOGRAMSIZE+1));\\n w = ts->anisotropy->ncols;\\n h = ts->anisotropy->nrows;\\n\\n for(i=0; ianisotropy->tbrow[i]+j;\\n an = ts->anisotropy->val[p];\\n th = ts->thickness->val[p];\\n\\n if(th>0.0){\\n\\tbin = ROUND(ts->orientation->val[p]*ratio); \\n\\thist[bin] += an;\\n }\\n }\\n }\\n hist[0] += hist[HISTOGRAMSIZE];\\n hist[HISTOGRAMSIZE] = 0.0;\\n\\n //Normaliza�ao do histograma\\n sum = 0.0;\\n for(i=0;incols,bin->nrows);\\n sq = AllocIntArray(n);\\n for (i=0; i < n; i++) \\n sq[i]=i*i;\\n\\n A = Circular(1.5);\\n cost = CreateImage(bin->ncols, bin->nrows);\\n Dx = CreateImage(bin->ncols,bin->nrows);\\n Dy = CreateImage(bin->ncols,bin->nrows); \\n n = bin->ncols*bin->nrows;\\n Q = CreateQueue(bin->ncols+bin->nrows,n);\\n\\n for(p = 0; p < n; p++){\\n if(bin->val[p] > 0)\\n cost->val[p] = INT_MAX;\\t \\n else{\\n cost->val[p]=0; \\n InsertQueue(Q,cost->val[p]%Q->C.nbuckets,p);\\n }\\n }\\n \\n while(!EmptyQueue(Q)) {\\n p = RemoveQueue(Q);\\n u.x = p%bin->ncols;\\n u.y = p/bin->ncols;\\n for (i=1; i < A->n; i++){\\n v.x = u.x + A->dx[i];\\n v.y = u.y + A->dy[i];\\n if(ValidPixel(bin,v.x,v.y)){\\n\\tq = v.x + bin->tbrow[v.y];\\n\\tif (cost->val[p] < cost->val[q]){\\n\\t dx = Dx->val[p] + abs(v.x-u.x);\\n\\t dy = Dy->val[p] + abs(v.y-u.y);\\n\\t tmp = sq[dx] + sq[dy];\\n\\t if (tmp < cost->val[q]){\\n\\t if (cost->val[q] == INT_MAX)\\n\\t InsertQueue(Q,tmp%Q->C.nbuckets,q);\\n\\t else\\n\\t UpdateQueue(Q,q,cost->val[q]%Q->C.nbuckets,tmp%Q->C.nbuckets);\\n\\t cost->val[q] = tmp;\\n\\t Dx->val[q] = dx;\\n\\t Dy->val[q] = dy;\\n\\t }\\n\\t}\\n }\\n }\\n }\\n\\n free(sq);\\n DestroyQueue(&Q);\\n DestroyAdjRel(&A);\\n DestroyImage(&Dx);\\n DestroyImage(&Dy);\\n \\n return(cost);\\n}\\n\\ndouble TensorScale_DistanceAlgorithm(FeatureVector1D *fv1, FeatureVector1D *fv2){\\n\\tdouble result;\\n\\tint offset;\\n\\n\\tresult = (double) TSHistogramMatch(fv1, fv2, &offset);\\n\\n\\treturn (1-result);\\n}\\n\\nfloat TSHistogramMatch(FeatureVector1D *fv1, FeatureVector1D *fv2, int *offset){\\n float *newhist;\\n float *newh1,*newh2, *hist1, *hist2;\\n int i,j,p;\\n float max,correlacao;\\n float score;\\n float dabs,aux;\\n //int maxoffset;\\n FILE *file1,*file2,*file3;\\n\\n newhist = (float *)malloc(sizeof(float)*2*HISTOGRAMSIZE);\\n newh1=newhist;\\n newh2=newhist+HISTOGRAMSIZE;\\n\\n hist1 = (float *)malloc(sizeof(float)*HISTOGRAMSIZE+1);\\n hist2 = (float *)malloc(sizeof(float)*HISTOGRAMSIZE+1);\\n \\n for(i = 0; i < HISTOGRAMSIZE+1; i++)\\n {\\n\\t hist1[i] = fv1->X[i];\\n\\t hist2[i] = fv2->X[i];\\n }\\n\\n\\n //Ajuste no histograma\\n newh1[0] = (2.0*hist1[0]+hist1[HISTOGRAMSIZE-1]+hist1[1])/4.0;\\n newh2[0] = (2.0*hist2[0]+hist2[HISTOGRAMSIZE-1]+hist2[1])/4.0;\\n for(i=1;imax){\\n max=correlacao;\\n *offset=i;\\n }\\n }\\n\\n file1 = fopen(\\\"histogram1d.txt\\\",\\\"w\\\");\\n file2 = fopen(\\\"histogram2.txt\\\",\\\"w\\\");\\n file3 = fopen(\\\"histogram1.txt\\\",\\\"w\\\");\\n dabs = 0.0;\\n for(p=*offset,j=0;jn; i++) \\n descriptor->Y[i] = 2.0 - descriptor->Y[i];\\n \\n return descriptor;\\n}\\n\\nCurve *ContourMSFractal(Image *in)\\n{\\n Image *cont = NULL;\\n Curve *descriptor = NULL;\\n Polynom *P;\\n double lower = 1.0;\\n double higher = 5.0;\\n int nbins = 100;\\n int degree = 10;\\n \\n cont = LabelContour(in);\\n P = MSFractal(cont, 256, degree, lower, higher, 0, 0.0, 6.0);\\n descriptor = PolynomToFractalCurve(P, lower, higher, nbins);\\n \\n DestroyPolynom(&P);\\n DestroyImage(&cont);\\n return (descriptor);\\n}\\n\\nFeatureVector1D *MS_ExtractionAlgorithm(Image *img){\\n Curve *curve = NULL;\\n FeatureVector1D *fv = NULL;\\n\\n curve = ContourMSFractal(img);\\n fv = CurveTo1DFeatureVector(curve);\\n \\n DestroyCurve(&curve);\\n return fv;\\n}\\n\\ndouble MS_DistanceAlgorithm(FeatureVector1D *fv1, FeatureVector1D *fv2){\\n\\treturn EuclideanDistance(fv1, fv2);\\n}\\n\\n/* Contour Saliences */\\nvoid DescInvertXY(FeatureVector2D *desc)\\n{\\n double tmp;\\n int i;\\n for (i=0; in; i++){\\n tmp = desc->X[i];\\n desc->X[i] = desc->Y[i];\\n desc->Y[i] = tmp;\\n }\\n}\\n\\nFeatureVector2D *CreateFeatureVector2D(int n)\\n{\\n FeatureVector2D *desc=NULL;\\n \\n desc = (FeatureVector2D *) calloc(1,sizeof(FeatureVector2D));\\n if (desc != NULL) {\\n desc->X = AllocDoubleArray(n);\\n desc->Y = AllocDoubleArray(n);\\n desc->n = n;\\n } else {\\n Error(MSG1,\\\"CreateFeatureVector\\\");\\n }\\n return(desc);\\n}\\n\\ndouble ContSalieDistance(FeatureVector2D *D1, FeatureVector2D *D2){\\n \\n int i;\\n int n = MIN(D1->n, D2->n);\\n double deltaX, dist, eps = 0.2;\\n \\n dist = 0.0;\\n for (i=0; iX[i]-D2->X[i]);\\n if (deltaX<=eps){\\n dist = dist + sqrt(pow(D1->X[i] - D2->X[i],2)+\\n\\t\\t\\t pow(D1->Y[i] - D2->Y[i],2));\\n }else\\n dist = dist + fabs(D1->Y[i]) + fabs(D2->Y[i]); \\n }\\n \\n for (i=n; in; i++){\\n dist = dist + fabs(D1->Y[i]);\\n }\\n \\n for (i=n; in; i++){\\n dist = dist + fabs(D2->Y[i]);\\n }\\n \\n return dist;\\n}\\n\\nFeatureVector2D *CircularRotation(FeatureVector2D *descriptor, double delta){\\n \\n FeatureVector2D *c = CreateFeatureVector2D(descriptor->n);\\n int i;\\n \\n for (i=0; in; i++){\\n c->Y[i] = descriptor->X[i] + delta;\\n if (c->Y[i]<0.0)\\n c->Y[i] = 1.0 + c->Y[i];\\n if (c->Y[i]>1.0)\\n c->Y[i] = 1.0 - c->Y[i];\\n c->X[i] = descriptor->Y[i];\\n }\\n SortFeatureVector2D(c, 0, (c->n-1), INCREASING);\\n DescInvertXY(c);\\n return c;\\n}\\n\\nvoid DestroyFeatureVector2D(FeatureVector2D **desc)\\n{\\n FeatureVector2D *aux;\\n \\n aux = *desc;\\n if (aux != NULL){\\n if (aux->X != NULL) free(aux->X);\\n if (aux->Y != NULL) free(aux->Y);\\n free(aux);\\n *desc = NULL;\\n }\\n}\\n\\nvoid SortFeatureVector2D(FeatureVector2D *desc, int left, int right, char order)\\n{\\n int pivot;\\n \\n if (left < right) {\\n pivot = PartFeatureVector2D(desc,left,right,order);\\n SortFeatureVector2D(desc,left,pivot-1,order);\\n SortFeatureVector2D(desc,pivot+1,right,order); \\n }\\n}\\n\\nint PartFeatureVector2D (FeatureVector2D *desc, int left, int right, char order)\\n{\\n double y;\\n int i;\\n double X,Y;\\n \\n y = desc->Y[left];\\n i = left;\\n \\n do {\\n if (order == INCREASING){\\n while ((desc->Y[left] <= y)&&(left <= right)) left++;\\n while (desc->Y[right] > y) right--;\\n } else { /* order = DECREASING */\\n while ((desc->Y[left] >= y)&&(left <= right)) left++;\\n while (desc->Y[right] < y) right--;\\n }\\n if (left < right){\\n X = desc->X[left];\\n Y = desc->Y[left];\\n desc->X[left] = desc->X[right];\\n desc->Y[left] = desc->Y[right];\\n desc->X[right] = X;\\n desc->Y[right] = Y;\\n left++; right--;\\n }\\n } while (left <= right);\\n \\n left = i;\\n \\n if (left != right){\\n X = desc->X[left];\\n Y = desc->Y[left];\\n desc->X[left] = desc->X[right];\\n desc->Y[left] = desc->Y[right];\\n desc->X[right] = X;\\n desc->Y[right] = Y;\\n }\\n \\n return (right);\\n}\\n\\nFeatureVector2D *CopyFeatureVector2D(FeatureVector2D *desc)\\n{\\n FeatureVector2D *descc;\\n \\n descc = CreateFeatureVector2D(desc->n);\\n memcpy(descc->X,desc->X,desc->n*sizeof(double));\\n memcpy(descc->Y,desc->Y,desc->n*sizeof(double));\\n \\n return(descc);\\n}\\n\\ndouble Matching(FeatureVector2D *descriptor1, FeatureVector2D *descriptor2, int order)\\n{\\n FeatureVector2D *d1 = NULL;\\n FeatureVector2D *d2 = NULL;\\n FeatureVector2D *D1 = NULL;\\n FeatureVector2D *D2 = NULL;\\n double max1, max2;\\n double dist, distance = INT_MAX;\\n int i,j;\\n \\n d1 = CopyFeatureVector2D(descriptor1);\\n d2 = CopyFeatureVector2D(descriptor2);\\n SortFeatureVector2D(d1, 0, (d1->n - 1), order);\\n SortFeatureVector2D(d2, 0, (d2->n - 1), order);\\n \\n max1 = fabs(d1->Y[0]);\\n max2 = fabs(d2->Y[0]);\\n \\n i = 0;\\n while ((in)&&\\n\\t ((fabs(d1->Y[i]) - max1)<=(fabs(0.2* max1)))){\\n j = 0;\\n while((jn)&&\\n\\t ((fabs(d2->Y[j]) - max2)<=(fabs(0.2 * max2)))){\\n if (d1->Y[i]*d2->Y[j]>0.0){\\n\\tD1 = CircularRotation(descriptor1, -d1->X[i]);\\n\\tD2 = CircularRotation(descriptor2, -d2->X[j]);\\n\\tdist = ContSalieDistance(D1, D2);\\n\\t//WriteInstance(i, j, descriptor1, descriptor2, d1, d2, D1, D2, -d1->X[i], -d2->X[j], dist);\\n\\tif (dist < distance)\\n\\t distance = dist;\\n\\tDestroyFeatureVector2D(&D1);\\n\\tDestroyFeatureVector2D(&D2);\\n }\\n j++;\\n }\\n i++;\\n }\\n \\n DestroyFeatureVector2D(&d1);\\n DestroyFeatureVector2D(&d2);\\n return distance;\\n}\\n\\nvoid iftFastDilation(AnnImg *aimg, AdjRel *A)\\n{\\n Image *Dx=NULL,*Dy=NULL;\\n Queue *Q=NULL;\\n Heap *H=NULL;\\n int i,p,q,n,sz;\\n Pixel u,v;\\n int *sq=NULL,tmp=INT_MAX,dx,dy;\\n bool cuisenaire;\\n AdjRel *A8=Circular(1.5),*CA=NULL;\\n char *color=NULL;\\n\\n if (aimg->seed == NULL)\\n return;\\n \\n n = MAX(aimg->img->ncols,aimg->img->nrows);\\n sq = AllocIntArray(n);\\n for (i=0; i < n; i++) \\n sq[i]=i*i;\\n \\n Dx = CreateImage(aimg->img->ncols,aimg->img->nrows);\\n Dy = CreateImage(aimg->img->ncols,aimg->img->nrows);\\n n = aimg->img->ncols*aimg->img->nrows;\\n color = AllocCharArray(n);\\n sz = FrameSize(A);\\n Q = CreateQueue(2*sz*(sz+aimg->img->ncols+aimg->img->nrows),n);\\n \\n /* Compute IFT with 8-Adjacency */\\n \\n while (aimg->seed != NULL){\\n p=RemoveSet(&(aimg->seed));\\n InsertQueue(Q,aimg->cost->val[p]%Q->C.nbuckets,p);\\n color[p]=GRAY;\\n }\\n \\n while(!EmptyQueue(Q)) {\\n p=RemoveQueue(Q);\\n color[p]=BLACK;\\n u.x = p%aimg->img->ncols;\\n u.y = p/aimg->img->ncols;\\n cuisenaire=true;\\n for (i=1; i < A8->n; i++){\\n v.x = u.x + A8->dx[i];\\n v.y = u.y + A8->dy[i];\\n if (ValidPixel(aimg->img,v.x,v.y)){\\n\\tq = v.x + aimg->img->tbrow[v.y];\\n\\tif (color[q] != BLACK){\\n\\t dx = Dx->val[p] + abs(v.x-u.x);\\n\\t dy = Dy->val[p] + abs(v.y-u.y);\\n\\t tmp = sq[dx] + sq[dy];\\n\\t if (tmp < aimg->cost->val[q]){\\n\\t if (color[q] == WHITE){\\n\\t InsertQueue(Q,tmp%Q->C.nbuckets,q);\\n\\t color[q] = GRAY;\\n\\t }else\\n\\t\\tUpdateQueue(Q,q,aimg->cost->val[q]%Q->C.nbuckets,tmp%Q->C.nbuckets);\\n\\t aimg->cost->val[q] = tmp;\\n\\t aimg->pred->val[q] = p;\\n\\t aimg->label->val[q] = aimg->label->val[p];\\n\\t Dx->val[q] = dx;\\n\\t Dy->val[q] = dy;\\n\\t cuisenaire = false;\\n\\t }\\n\\t} \\n } \\n }\\n if (cuisenaire) \\n InsertSet(&(aimg->seed),p); \\n }\\n \\n DestroyQueue(&Q);\\n free(color);\\n \\n /* Compute IFT with Complementary Adjacency */\\n \\n if (A8->n < A->n) {\\n \\n CA = ComplAdj(A8,A);\\n H = CreateHeap(n,aimg->cost->val);\\n\\n while (aimg->seed != NULL){\\n p=RemoveSet(&(aimg->seed));\\n InsertHeap(H,p);\\n }\\n\\n while(!HeapIsEmpty(H)) {\\n RemoveHeap(H,&p);\\n u.x = p%aimg->img->ncols;\\n u.y = p/aimg->img->ncols;\\n for (i=0; i < CA->n; i++){\\n\\tv.x = u.x + CA->dx[i];\\n\\tv.y = u.y + CA->dy[i];\\n\\tif (ValidPixel(aimg->img,v.x,v.y)){\\n\\t q = v.x + aimg->img->tbrow[v.y];\\n\\t if (color[q]!=BLACK){\\n\\t dx = Dx->val[p] + abs(v.x-u.x);\\n\\t dy = Dy->val[p] + abs(v.y-u.y);\\n\\t tmp = sq[dx] + sq[dy];\\n\\t if (tmp < aimg->cost->val[q]) \\n\\t {\\n\\t\\taimg->cost->val[q] = tmp;\\n\\t\\taimg->pred->val[q] = p;\\n\\t\\taimg->label->val[q] = aimg->label->val[p];\\n\\t\\tDx->val[q] = dx;\\n\\t\\tDy->val[q] = dy;\\n\\t\\tif (color[q] == WHITE){\\n\\t\\t InsertHeap(H,q);\\n\\t\\t}else\\n\\t\\t GoUpHeap(H,H->pos[q]);\\n\\t }\\n\\t }\\n\\t} \\n }\\n }\\n DestroyAdjRel(&CA);\\n DestroyHeap(&H);\\n }\\n\\n DestroyAdjRel(&A8);\\n\\n free(sq);\\n DestroyImage(&Dx);\\n DestroyImage(&Dy);\\n}\\n\\nCurve3D *SkelCont(Image *bin, int maxdist, int threshold, int angle, char side) { \\n Image *contour=NULL;\\n Image *msskel=NULL;\\n Image *skel=NULL;\\n Image *bin_skel=NULL;\\n AdjRel *A=NULL;\\n AnnImg *aimg=NULL;\\n Curve3D *contour_salie = NULL;\\n Curve3D *skelsaliences = NULL;\\n Curve3D *saliences = NULL;\\n Pixel left, right;\\n int i, j, p, q, n, label, imax, maxcont, max, min, imin, x, y, ne, ni, delta = 3; \\n double sum;\\n \\n contour = LabelContPixel(bin);\\n aimg = Annotate(bin,NULL,contour); \\n A = Circular(1.5);\\n iftFastDilation(aimg,A);\\n \\n msskel = MSSkel(bin, side);\\n skel = Skeleton(msskel, threshold);\\n bin_skel = Skeleton(msskel, threshold);\\n n = bin->ncols*bin->nrows;\\n contour_salie = Saliences(bin, maxdist);\\n\\n maxcont = MaximumValue(contour);\\n\\n for (p=0; pval[p]!=0){\\n q = Seed(aimg->pred, p);\\n label = (aimg->label->val[q] + msskel->val[p]/2 + maxcont)%maxcont;\\n skel->val[p] = label;\\n if (side == INTERIOR){\\n\\tif (contour_salie->Z[label-1]<0.0){\\n\\t max = INT_MIN;\\n\\t imax = 0;\\n\\t for (j=-5; j<5; j++){\\n\\t if (contour_salie->Z[(label-1+j+contour_salie->n)%contour_salie->n] > max){\\n\\t imax = (label-1+j+contour_salie->n)%contour_salie->n;\\n\\t max = contour_salie->Z[imax];\\n\\t }\\n\\t }\\n\\t skel->val[p] = imax + 1;\\n\\t}\\n\\telse {\\n\\t skel->val[p] = MAX(label,1);\\n\\t}\\n }\\n else{ \\n\\tif (side == EXTERIOR){\\n\\t if (contour_salie->Z[label-1]>0.0){\\n\\t min = INT_MAX;\\n\\t imin = 0;\\n\\t for (j=-5; j<5; j++){\\n\\t if (contour_salie->Z[(label-1+j+contour_salie->n)%contour_salie->n] < min){\\n\\t\\timin = (label-1+j+contour_salie->n)%contour_salie->n;\\n\\t\\tmin = contour_salie->Z[imin];\\n\\t }\\n\\t }\\n\\t skel->val[p] = imin + 1;\\n\\t }\\n\\t else {\\n\\t skel->val[p] = MAX(label, 1);\\n\\t }\\n\\t}\\n }\\n }\\n }\\n \\n skelsaliences = SkelSaliences(bin_skel, maxdist, angle); \\n \\n if (side==EXTERIOR){\\n left.x = bin->ncols-1;\\n left.y = bin->nrows-1;\\n right.x = 0;\\n right.y = 0;\\n for (y=0; y < bin->nrows; y++)\\n for (x=0; x < bin->ncols; x++){\\n\\tif (bin->val[x+bin->tbrow[y]] > 0){\\n\\t if (x < left.x)\\n\\t left.x = x;\\n\\t if (y < left.y)\\n\\t left.y = y;\\n\\t if (x > right.x)\\n\\t right.x = x;\\n\\t if (y > right.y)\\n\\t right.y = y;\\t\\n\\t}\\n }\\n \\n for (i=0; in; i++){\\n if ((skelsaliences->X[i]X[i]>right.x)||\\n\\t (skelsaliences->Y[i]Y[i]>right.y))\\n\\tskelsaliences->Z[i] = 0.0;\\n }\\n }\\n \\n SortCurve3D(skelsaliences, 0, (skelsaliences->n - 2), DECREASING);\\n i=0;\\n while (skelsaliences->Z[i]!=0.0)\\n i++;\\n saliences = CreateCurve3D(i); \\n for (i=0; i< saliences->n; i++){\\n if (skelsaliences->Z[i]!=0.0){\\n p = (int)skelsaliences->X[i]+bin->tbrow[(int)skelsaliences->Y[i]];\\n saliences->X[i] = contour_salie->X[skel->val[p]-1];\\n saliences->Y[i] = contour_salie->Y[skel->val[p]-1];\\n if (side==INTERIOR){\\n\\tsum = 0.0;\\n\\tfor (j=-delta; j<=delta; j++){\\n\\t q = ((skel->val[p]-1) + j + maxcont) % maxcont;\\n\\t if (contour_salie->Z[q]>0.0)\\n\\t sum += contour_salie->Z[q];\\n\\t}\\n\\tsaliences->Z[i] = sum;\\n } \\n else{\\n\\tsum = 0.0;\\n\\tfor (j=-delta; j<=delta; j++){\\n\\t q = ((skel->val[p]-1) + j + maxcont) % maxcont;\\n\\t if (contour_salie->Z[q]<0.0)\\n\\t sum += contour_salie->Z[q];\\n\\t}\\n\\tsaliences->Z[i] = sum;\\n }\\n } \\n }\\n\\n ne = 0;\\n ni = 0;\\n for (i=0; in; i++){\\n if (saliences->Z[i]>0.0) \\n ni += saliences->Z[i];\\n else\\n if (saliences->Z[i]<0.0) \\n\\tne += fabs(saliences->Z[i]);\\n }\\n\\n for (i=0; in; i++){\\n if (saliences->Z[i]>0.0) \\n saliences->Z[i]/=ni;\\n else\\n if (saliences->Z[i]<0.0) \\n\\tsaliences->Z[i]/=ne;\\n }\\n\\n \\n DestroyImage(&contour);\\n DestroyImage(&msskel);\\n DestroyImage(&skel);\\n DestroyImage(&bin_skel);\\n DestroyCurve3D(&contour_salie);\\n DestroyCurve3D(&skelsaliences);\\n DestroyAdjRel(&A);\\n DeAnnotate(&aimg);\\n return(saliences);\\n\\n}\\n\\nCurve3D *iftContourSaliences(Image *bin,int threshold_in,int threshold_out,int angle_in,int angle_out)\\n{\\n\\n Curve3D *saliences = NULL;\\n Curve3D *convex_saliences = NULL;\\n Curve3D *concave_saliences = NULL;\\n int i;\\n int maxdist = 10;\\n \\n convex_saliences = SkelCont(bin,maxdist,threshold_in, angle_in, INTERIOR);\\n concave_saliences = SkelCont(bin, maxdist, threshold_out, angle_out, EXTERIOR);\\n saliences = CreateCurve3D(convex_saliences->n + concave_saliences->n);\\n for (i=0; in; i++){\\n saliences->X[i] = convex_saliences->X[i];\\n saliences->Y[i] = convex_saliences->Y[i];\\n saliences->Z[i] = convex_saliences->Z[i];\\n }\\n for (i=convex_saliences->n; in;i++){\\n saliences->X[i] = concave_saliences->X[i-convex_saliences->n];\\n saliences->Y[i] = concave_saliences->Y[i-convex_saliences->n];\\n saliences->Z[i] = concave_saliences->Z[i-convex_saliences->n];\\n }\\n \\n DestroyCurve3D(&convex_saliences);\\n DestroyCurve3D(&concave_saliences);\\n return saliences;\\n}\\n\\nCurve *ContourSaliences(Image *in)\\n{\\n Curve3D *saliences = NULL;\\n Curve *descriptor = NULL;\\n Image *contour = NULL;\\n int i, p, max;\\n \\n contour = LabelContPixel(in);\\n saliences = iftContourSaliences(in, 5, 20, 50, 110); \\n \\n descriptor = CreateCurve(saliences->n);\\n max = MaximumValue(contour);\\n for (i=0; in; i++){\\n descriptor->X[i] = saliences->Z[i];\\n p = (int)saliences->X[i]+contour->tbrow[(int)saliences->Y[i]];\\n descriptor->Y[i] = (double)(((contour->val[p])-1))/max;\\n }\\n SortCurve(descriptor, 0, (descriptor->n - 1), INCREASING);\\n InvertXY(descriptor); \\n \\n DestroyCurve3D(&saliences);\\n DestroyImage(&contour);\\n \\n return (descriptor);\\n}\\n\\nvoid WriteFeatureVector2D(FeatureVector2D *desc,char *filename)\\n{\\n FILE *fp;\\n int i;\\n \\n fp = fopen(filename,\\\"w\\\");\\n if (fp == NULL){\\n fprintf(stderr,\\\"Cannot open %s\\\\n\\\",filename);\\n exit(-1);\\n }\\n for (i=0; i < desc->n; i++)\\n fprintf(fp,\\\"%f\\\\t%f\\\\n\\\",desc->X[i],desc->Y[i]);\\n \\n fclose(fp);\\n}\\n\\nFeatureVector2D *CS_ExtractionAlgorithm(Image *img){\\n Curve *curve = NULL;\\n FeatureVector2D *fv = NULL;\\n \\n curve = ContourSaliences(img);\\n fv = CurveTo2DFeatureVector(curve);\\n \\n DestroyCurve(&curve);\\n return fv;\\n}\\n\\ndouble CS_DistanceAlgorithm(FeatureVector2D *descriptor1, FeatureVector2D *descriptor2){\\n double convex_distance = INT_MIN;\\n double concave_distance = INT_MIN;\\n \\n convex_distance = Matching(descriptor1, descriptor2, DECREASING);\\n concave_distance = Matching(descriptor1, descriptor2, INCREASING);\\n return(MIN(convex_distance, concave_distance));\\n}\\n\\n/* Segment Saliences */\\nCurve *SS_ExtractionAlgorithm_(Image *in, int maxdist, int nsamples, int side){\\n Curve *inner = NULL;\\n Curve *outer = NULL;\\n Curve *diff = NULL;\\n Curve *ninner = NULL;\\n Curve *nouter = NULL;\\n Curve *ndiff = NULL;\\n Curve *output = NULL;\\n\\n Image *mbb = NULL;\\n Image *bin = NULL;\\n Image *contour = NULL;\\n Image *segments = NULL;\\n \\n AdjRel *A=NULL;\\n AnnImg *aimg= NULL;\\n \\n int p,i,Lmax, maxcost = maxdist*maxdist;\\n double nin, nout, maxin, maxout;\\n\\n mbb = MBB(in);\\n bin = AddFrame(mbb,maxdist,0);\\n\\n DestroyImage(&mbb);\\n \\n segments = LabelContPixel(bin);\\n\\n /* Compute Euclidean IFT */\\n contour = LabelContPixel(bin);\\n \\n aimg = Annotate(bin,NULL,contour); \\n A = Circular(1.5);\\n iftDilation(aimg,A); \\n \\n Lmax = MaximumValue(aimg->label);\\n //printf(\\\"Lmax = %d\\\\n\\\", Lmax);\\n inner = CreateCurve(Lmax);\\n outer = CreateCurve(Lmax);\\n diff = CreateCurve(Lmax);\\n \\n for (i=0; iX[i] = inner->X[i] = outer->X[i]= (double)(i*nsamples)/Lmax;\\n } \\n \\n /* Compute influence areas */ \\n nin = nout = 0.0;\\n for (p=0; p < bin->ncols*bin->nrows; p++){\\n if (segments->val[p] != 0){\\n segments->val[p]=((((segments->val[p]*nsamples)/Lmax))/*%2*/)+1;\\n }\\n if ((aimg->label->val[p] > 0)&&(aimg->cost->val[p] <= maxcost)) {\\n if (aimg->img->val[p] != 0){\\n\\tnin++;\\n\\tinner->Y[aimg->label->val[p]-1]++;\\n } else {\\n\\tnout++;\\n\\touter->Y[aimg->label->val[p]-1]++;\\n }\\n }\\n }\\n \\n maxin = INT_MIN;\\n maxout = INT_MIN;\\n for (i=0; iY[i] > maxin){\\n maxin = inner->Y[i];\\n }\\n if (outer->Y[i] > maxout){\\n maxout = outer->Y[i];\\n }\\n }\\n \\n for (i=0; iY[i] /= nin;\\n outer->Y[i] /= nout;\\n diff->Y[i] = outer->Y[i] - inner->Y[i];\\n }\\n \\n ninner = CreateCurve(nsamples);\\n nouter = CreateCurve(nsamples);\\n ndiff = CreateCurve(nsamples);\\n \\n for (i=0; iX[i] = nouter->X[i] = ndiff->X[i] = i;\\n }\\n for (i=0; iY[(int)inner->X[i]] += inner->Y[i];\\n nouter->Y[(int)outer->X[i]] += outer->Y[i];\\n }\\n for (i=0; iY[i] = nouter->Y[i] - ninner->Y[i];\\n }\\n \\n \\n if (side == INTERIOR){\\n output = CopyCurve(ninner);\\n }\\n else if (side==EXTERIOR){\\n output = CopyCurve(nouter);\\n }\\n else if (side == BOTH){\\n output = CopyCurve(ndiff);\\n }\\n else{\\n printf(\\\"Invalid \\\\\\\"side\\\\\\\" option <%d>\\\\n\\\", side);\\n exit(-1);\\n }\\n \\n DestroyImage(&segments);\\n DestroyCurve(&ninner);\\n DestroyCurve(&nouter);\\n DestroyCurve(&ndiff);\\n\\n DestroyImage(&contour);\\n DestroyAdjRel(&A);\\n DeAnnotate(&aimg);\\n\\n DestroyImage(&bin);\\n DestroyImage(&mbb);\\n DestroyCurve(&inner);\\n DestroyCurve(&outer);\\n DestroyCurve(&diff);\\n\\n return output;\\n}\\n\\nFeatureVector1D *SS_ExtractionAlgorithm(Image *img){\\n Curve *curve = NULL;\\n FeatureVector1D *fv = NULL;\\n \\n curve = SS_ExtractionAlgorithm_(img, 5, 100, BOTH);\\n fv = CurveTo1DFeatureVector(curve);\\n \\n DestroyCurve(&curve);\\n return fv;\\n}\\n\\n/***************SS SIMILARITY ALGORITHM*********************/\\ndouble SS_getMin(double Dist1, double Dist2, double Dist3){\\n if((Dist1<=Dist2) && (Dist1<=Dist3)) \\n return(Dist1);\\n else if((Dist2<=Dist1) && (Dist2<=Dist3)) \\n return(Dist2);\\n //else if((Dist3<=Dist1) && (Dist3<=Dist2)) \\n return(Dist3);\\n}\\n\\ndouble SS_OCS(FeatureVector1D *fv1, FeatureVector1D *fv2){\\n \\n int i,j, dim1 = fv1->n, dim2 = fv2->n;\\n double temp_dist;\\n double penalty;\\n double *DISTANCE = NULL;\\n \\n DISTANCE=(double *) calloc((dim1+1)*(dim2+1),sizeof(double));\\n\\n penalty=20.0;\\n /* OPTIMAL CORRESPONDENCE OF STRINGS\\n */\\n DISTANCE[0*(dim2+1)+0]=0;\\n for(j=1;j<=dim2;j++)\\n DISTANCE[0*(dim2+1)+j]=j * penalty;\\n \\n for(i=1;i<=dim1;i++)\\n DISTANCE[i*(dim2+1)+0]=i * penalty;\\n \\n for(i=1;i<=dim1;i++)\\n for(j=1;j<=dim2;j++)\\n if(abs(i-j) < (5)){\\n\\ttemp_dist=abs(fv1->X[i-1]-fv2->X[j-1]);\\n\\t\\t\\n\\tDISTANCE[i*(dim2+1)+j]= temp_dist +\\n\\t SS_getMin(DISTANCE[(i-1)*(dim2+1)+(j-1)],\\n\\t\\t DISTANCE[(i-1)*(dim2+1)+(j)] + penalty,\\n\\t\\t DISTANCE[(i)*(dim2+1)+(j-1)] + penalty); \\n }\\n \\n temp_dist = DISTANCE[(dim1)*(dim2+1)+(dim2)]/dim2;\\n free(DISTANCE);\\n \\n return temp_dist;\\n}\\n\\ndouble SS_OCSMatching(FeatureVector1D *fv_1, FeatureVector1D *fv_2){\\n double distance,temp_dist;\\n int i,k;\\n FeatureVector1D *temp1, *temp2, *fv1, *fv2;\\n \\n fv1 = CreateFeatureVector1D(fv_1->n);\\n fv2 = CreateFeatureVector1D(fv_2->n);\\n for (i = 0; in; i++){\\n fv1->X[i] = 100*fv_1->X[i];\\n fv2->X[i] = 100*fv_2->X[i];\\n }\\n \\n temp1 = CreateFeatureVector1D(fv2->n);\\n temp2 = CreateFeatureVector1D(fv2->n);\\n \\n temp_dist=INT_MAX; \\n for(k=0; kn; k++){\\n for(i=0;in;i++){\\n temp2->X[i]=fv2->X[(i+k)%fv2->n];\\n } \\n distance= SS_OCS(fv1,temp2);\\n if(temp_dist>distance) \\n temp_dist=distance;\\n }\\n /***Taking the mirror of fv2 *****/\\n for(i=0;in;i++){\\n temp2->X[i]=fv2->X[(fv2->n-1)-i];\\n }\\n \\n for(k=0; kn; k++){\\n for(i=0;in;i++){\\n temp1->X[i]= temp2->X[(i+k)%fv2->n];\\n }\\n distance=SS_OCS(fv1,temp1);\\n if(temp_dist>distance) \\n temp_dist=distance;\\n }\\n \\n distance=temp_dist;\\n DestroyFeatureVector1D(&temp1);\\n DestroyFeatureVector1D(&temp2);\\n DestroyFeatureVector1D(&fv1);\\n DestroyFeatureVector1D(&fv2);\\n return(distance);\\n}\\n\\ndouble SS_DistanceAlgorithm(FeatureVector1D *fv1d1, FeatureVector1D *fv1d2){\\n \\n double dist;\\n\\n dist = SS_OCSMatching(fv1d1, fv1d2);\\n \\n return dist;\\n}\\n\\n/* Metrics to measure the similarity between feature vectors*/\\ndouble EuclideanDistance(FeatureVector1D *v1, FeatureVector1D *v2) { \\n int i;\\n double sum = 0.0;\\n double z = 0.0;\\n \\n for (i = 0; i < v1->n ; i++){\\n z = v1->X[i] - v2->X[i]; \\n sum += z*z;\\n }\\n sum = sqrtf(sum);\\n return (sum);\\n}\\n\\ndouble L1_Distance(FeatureVector1D *v1, FeatureVector1D *v2) { \\n int i;\\n double sum = 0.0;\\n \\n for (i = 0; i < v1->n ; i++){\\n sum += fabs(v1->X[i] - v2->X[i]); \\n }\\n return (sum);\\n}\\n\\ndouble dLog(FeatureVector1D *fv1, FeatureVector1D *fv2)\\n{\\n\\tint i;\\n\\tdouble sum = 0.0;\\n\\tdouble q,d;\\n\\t\\n\\tfor(i = 0; i < fv1->n; i++)\\n\\t{\\n\\t\\n\\t\\tif(fv1->X[i] == 0)\\n\\t\\t\\tq = 0;\\n\\t\\telse\\n\\t\\t\\tif((fv1->X[i] > 0) && (fv1->X[i] <= 1))\\n\\t\\t\\t\\tq = 1;\\n\\t\\t\\telse\\n\\t\\t\\t\\tq = log10(fv1->X[i])/log10(2);\\n\\t\\tif(fv2->X[i] == 0)\\n\\t\\t\\td = 0;\\n\\t\\telse\\n\\t\\t\\tif((fv2->X[i] > 0) && (fv2->X[i] <= 1))\\n\\t\\t\\t\\td = 1;\\n\\t\\t\\telse\\n\\t\\t\\t\\td = log10(fv2->X[i])/log10(2);\\n\\t\\t\\n\\t\\tsum = sum + fabs(q-d);\\n\\t}\\n\\n\\t\\n\\treturn sum;\\n}\\n\"\n },\n {\n \"alpha_fraction\": 0.6212624311447144,\n \"alphanum_fraction\": 0.6378737688064575,\n \"avg_line_length\": 17.8125,\n \"blob_id\": \"a6549da711eddf4db3975ba3a5d9bef25c38eb02\",\n \"content_id\": \"8c9bbf96d1d4919aecba5b58b14ce72d9f3336a4\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 301,\n \"license_type\": \"permissive\",\n \"max_line_length\": 34,\n \"num_lines\": 16,\n \"path\": \"/MO445-descriptors/examples/file_name.py\",\n \"repo_name\": \"RQuispeC/mo805-assignment7\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import os\\nimport os.path as osp\\nimport numpy as np\\n\\nbase = \\\"mpeg7_pgm/\\\"\\nfiles_names = os.listdir(base)\\nfiles_names.sort()\\nf = open(\\\"names.txt\\\", \\\"w\\\")\\nfor l in files_names:\\n\\tf.write(l[:-4]+ '\\\\n')\\nf.close()\\n\\nf2 = open(\\\"paths.txt\\\", \\\"w\\\")\\nfor l in files_names:\\n\\tf2.write(osp.join(base, l)+ '\\\\n')\\nf2.close()\\n\"\n },\n {\n \"alpha_fraction\": 0.646030068397522,\n \"alphanum_fraction\": 0.6603707671165466,\n \"avg_line_length\": 32.64706039428711,\n \"blob_id\": \"927be9ad849e7f4bcb9b18aaeae8dcd9b9a1ae98\",\n \"content_id\": \"5e4518f89ebac6d9f78b6662404a7a457b764f22\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 2859,\n \"license_type\": \"permissive\",\n \"max_line_length\": 136,\n \"num_lines\": 85,\n \"path\": \"/precision_recall.py\",\n \"repo_name\": \"RQuispeC/mo805-assignment7\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import numpy as np\\nimport os.path as osp\\nimport matplotlib.pyplot as plt\\n\\ndef read_file(file_path):\\n f = open(file_path, \\\"r\\\")\\n data = []\\n for line in f:\\n data.append(line)\\n return np.array(data)\\n\\ndef load_data(names_file, features_dir):\\n ms_features = []\\n ss_features = []\\n ids = []\\n names = read_file(names_file)\\n names.sort()\\n last_class = \\\"\\\"\\n class_id = 0\\n for name in names:\\n name = name[:-1] #remove new line end\\n ms_file_path = osp.join(features_dir, name + \\\"_MS.txt\\\")\\n ss_file_path = osp.join(features_dir, name + \\\"_SS.txt\\\")\\n ms_data = read_file(ms_file_path)\\n ss_data = read_file(ss_file_path)\\n ms_data = ms_data.astype(np.float)\\n ss_data = ss_data.astype(np.float)\\n ms_features.append(ms_data)\\n ss_features.append(ss_data)\\n data_class = name.split(\\\"-\\\")[0]\\n if data_class != last_class:\\n last_class = data_class\\n class_id += 1\\n ids.append(class_id)\\n\\n ids = np.array(ids)\\n names = np.array(names)\\n ms_features = np.array(ms_features)\\n ss_features = np.array(ss_features)\\n return ids, names, ms_features, ss_features\\n\\ndef dist(query_features, gallery_features):\\n matrix = np.zeros((len(query_features), len(gallery_features)))\\n q_pow = np.sum(query_features * query_features, axis = 1)\\n g_pow = np.sum(gallery_features * gallery_features, axis = 1)\\n prod = 2 * np.dot(query_features, np.transpose(gallery_features))\\n matrix += np.transpose(np.tile(q_pow, (len(g_pow), 1)))\\n matrix += np.tile(g_pow, (len(q_pow), 1))\\n matrix -= prod\\n return matrix\\n\\ndef precision_recall(distmat, q_ids, g_ids, max_rank = 20, gt_samples = 20):\\n indices = np.argsort(distmat, axis=1)\\n matches = (g_ids[indices] == q_ids[:, np.newaxis]).astype(np.int32)\\n cnt = matches.cumsum(axis = 1)[:, :max_rank]\\n\\n den_precision = np.tile(np.arange(1, max_rank + 1), (len(q_ids), 1))\\n den_recall = np.full((len(q_ids), max_rank), gt_samples)\\n precision = cnt / den_precision\\n recall = cnt / den_recall\\n\\n precision = np.average(precision, axis = 0)\\n recall = np.average(recall, axis = 0)\\n return precision, recall\\n\\nif __name__ == '__main__':\\n ids, names, ms_features, ss_features = load_data(\\\"MO445-descriptors/examples/names.txt\\\", \\\"MO445-descriptors/examples/mpeg7_features/\\\")\\n\\n max_rank = 1400\\n dismat_MS = dist(ms_features, ms_features)\\n pms, rms = precision_recall(dismat_MS, ids, ids, max_rank=max_rank)\\n\\n dismat_SS = dist(ss_features, ss_features)\\n pss, rss = precision_recall(dismat_SS, ids, ids, max_rank=max_rank)\\n\\n print(\\\"Generating Precision x Recall curve\\\")\\n plt.title('Methods comparison - MO805 - Assignment 7')\\n plt.plot(rms, pms, label = 'Multiscale fractal dimension')\\n plt.plot(rss, pss, label = 'Segment saliences')\\n plt.legend(loc = 'upper right')\\n plt.xlim([0, 1])\\n plt.ylim([0, 1])\\n plt.ylabel('precision')\\n plt.xlabel('recall')\\n plt.savefig(\\\"precision_recall.png\\\")\"\n }\n]"},"num_files":{"kind":"number","value":11,"string":"11"}}},{"rowIdx":2025,"cells":{"repo_name":{"kind":"string","value":"poonambisht07/Weatherapp"},"repo_url":{"kind":"string","value":"https://github.com/poonambisht07/Weatherapp"},"snapshot_id":{"kind":"string","value":"025ea11eaea3f01f616d54a00451dca9d2ceb50b"},"revision_id":{"kind":"string","value":"07ec37e4b8f40decec9f6db1cf333266ba55414f"},"directory_id":{"kind":"string","value":"69093d516c0ce0c61f0288ffadb86512baab14ea"},"branch_name":{"kind":"string","value":"refs/heads/main"},"visit_date":{"kind":"string","value":"2023-02-15T03:34:42.184696"},"revision_date":{"kind":"string","value":"2021-01-11T02:59:07"},"committer_date":{"kind":"string","value":"2021-01-11T02:59:07"},"github_id":{"kind":"number","value":328532851,"string":"328,532,851"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.5224999785423279,"alphanum_fraction":0.5400000214576721,"avg_line_length":32.349998474121094,"blob_id":"a4bd17a3d60dd13a78cac9d281cae0f575b27f8f","content_id":"0d67e230ad855c5f17d0e4b848ea23bd9459a5fd","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":2000,"license_type":"no_license","max_line_length":117,"num_lines":60,"path":"/myapp/views.py","repo_name":"poonambisht07/Weatherapp","src_encoding":"UTF-8","text":"import requests\nfrom django.http import HttpResponseRedirect\nfrom django.shortcuts import render, redirect\nfrom .models import *\nfrom datetime import datetime\n\n\n# Create your views here.\ndef index(request):\n url = 'http://api.openweathermap.org/data/2.5/weather?q={}&units=imperial&appid=56a3270c46d91192ec67911b0a20de10'\n \n context = {}\n context['date_time'] = datetime.now().strftime(\" %A, %d %b %Y | %I:%M:%S %p\")\n\n if request.method == \"POST\":\n new_city = request.POST.get('cname').title()\n \n exist_city = City.objects.filter(name=new_city).count()\n if exist_city == 0:\n r = requests.get(url.format(new_city)).json()\n if r['cod'] == 200:\n nr = City.objects.create(name=new_city) \n nr.save()\n \n else:\n context['msg'] = \"City does not exist in the World!\"\n context['col'] = \"alert-danger\"\n else:\n context['msg'] = \"City Already Exists.\"\n context['col'] = \"alert-danger\"\n \n cities = City.objects.all().order_by('-id')\n \n weather_data = []\n \n for city in cities:\n r = requests.get(url.format(city)).json()\n \n city_weather = {\n 'id' : city.id,\n 'city' : city.name,\n 'temperature' : ((r['main']['temp']-32)*5//9),\n 'description' : (r['weather'][0]['description']).title(),\n 'icon' : r['weather'][0]['icon'],\n 'sunrise' :datetime.fromtimestamp(int(r['sys']['sunrise'])).strftime('%I:%M:%S %p'),\n 'sunset' :datetime.fromtimestamp(int(r['sys']['sunset'])).strftime('%I:%M:%S %p') \n }\n \n weather_data.append(city_weather) \n\n context['city_weather'] = weather_data \n print(context)\n \n return render(request, 'index.html', context)\n \n\ndef del_city(request):\n id = request.GET.get('id')\n City.objects.filter(id=id).delete()\n return redirect ('/')"}],"string":"[\n {\n \"alpha_fraction\": 0.5224999785423279,\n \"alphanum_fraction\": 0.5400000214576721,\n \"avg_line_length\": 32.349998474121094,\n \"blob_id\": \"a4bd17a3d60dd13a78cac9d281cae0f575b27f8f\",\n \"content_id\": \"0d67e230ad855c5f17d0e4b848ea23bd9459a5fd\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 2000,\n \"license_type\": \"no_license\",\n \"max_line_length\": 117,\n \"num_lines\": 60,\n \"path\": \"/myapp/views.py\",\n \"repo_name\": \"poonambisht07/Weatherapp\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import requests\\nfrom django.http import HttpResponseRedirect\\nfrom django.shortcuts import render, redirect\\nfrom .models import *\\nfrom datetime import datetime\\n\\n\\n# Create your views here.\\ndef index(request):\\n url = 'http://api.openweathermap.org/data/2.5/weather?q={}&units=imperial&appid=56a3270c46d91192ec67911b0a20de10'\\n \\n context = {}\\n context['date_time'] = datetime.now().strftime(\\\" %A, %d %b %Y | %I:%M:%S %p\\\")\\n\\n if request.method == \\\"POST\\\":\\n new_city = request.POST.get('cname').title()\\n \\n exist_city = City.objects.filter(name=new_city).count()\\n if exist_city == 0:\\n r = requests.get(url.format(new_city)).json()\\n if r['cod'] == 200:\\n nr = City.objects.create(name=new_city) \\n nr.save()\\n \\n else:\\n context['msg'] = \\\"City does not exist in the World!\\\"\\n context['col'] = \\\"alert-danger\\\"\\n else:\\n context['msg'] = \\\"City Already Exists.\\\"\\n context['col'] = \\\"alert-danger\\\"\\n \\n cities = City.objects.all().order_by('-id')\\n \\n weather_data = []\\n \\n for city in cities:\\n r = requests.get(url.format(city)).json()\\n \\n city_weather = {\\n 'id' : city.id,\\n 'city' : city.name,\\n 'temperature' : ((r['main']['temp']-32)*5//9),\\n 'description' : (r['weather'][0]['description']).title(),\\n 'icon' : r['weather'][0]['icon'],\\n 'sunrise' :datetime.fromtimestamp(int(r['sys']['sunrise'])).strftime('%I:%M:%S %p'),\\n 'sunset' :datetime.fromtimestamp(int(r['sys']['sunset'])).strftime('%I:%M:%S %p') \\n }\\n \\n weather_data.append(city_weather) \\n\\n context['city_weather'] = weather_data \\n print(context)\\n \\n return render(request, 'index.html', context)\\n \\n\\ndef del_city(request):\\n id = request.GET.get('id')\\n City.objects.filter(id=id).delete()\\n return redirect ('/')\"\n }\n]"},"num_files":{"kind":"number","value":1,"string":"1"}}},{"rowIdx":2026,"cells":{"repo_name":{"kind":"string","value":"LJJ-CDD/Python_work"},"repo_url":{"kind":"string","value":"https://github.com/LJJ-CDD/Python_work"},"snapshot_id":{"kind":"string","value":"ed2821e6682453052b0ab587492ce6f5c6dff670"},"revision_id":{"kind":"string","value":"cf4a565d07bf07756be492db801c0c78736b0b46"},"directory_id":{"kind":"string","value":"41f1b81ce6ce1cdb11b951b68ab1eadcb196d179"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"string","value":"2023-06-01T13:20:28.687438"},"revision_date":{"kind":"string","value":"2021-06-16T11:15:38"},"committer_date":{"kind":"string","value":"2021-06-16T11:15:38"},"github_id":{"kind":"null"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.5863128900527954,"alphanum_fraction":0.6032794117927551,"avg_line_length":43.57868194580078,"blob_id":"941029810340767d39de84ccb2832b32b5256a42","content_id":"c24d4b2fea19635f11cde6b0dc29bff616819e27","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":9576,"license_type":"no_license","max_line_length":118,"num_lines":197,"path":"/3.RSA_work/main.py","repo_name":"LJJ-CDD/Python_work","src_encoding":"UTF-8","text":"from logging import root\nimport tkinter # 窗体相关\nimport tkinter.messagebox # 实现提示框的组件\nimport tkinter.simpledialog # 对话框\nimport os # 路径\nimport sys # 操作系统交互\nfrom primes import Primes # 生成素数\nimport random\nimport rsa_test\n\ndef get_resource_path(relative_path): # 利用此函数实现资源路径的定位\n if getattr(sys, \"frozen\", False):\n base_path = sys._MEIPASS # 获取临时资源\n else:\n base_path = os.path.abspath(\".\") # 获取当前路径\n return os.path.join(base_path, relative_path) # 绝对路径\n\n#LOGO_PATH = get_resource_path(os.path.join(\"Python_work\\\\3.RSA_work\\\\resources\", \"RSA.ico\")) # 图标文件路径\n#IMAGES_PATH = get_resource_path(os.path.join(\"Python_work\\\\3.RSA_work\\\\resources\", \"Rsa_Icon.png\")) # 图片路径\nLOGO_PATH = get_resource_path(os.path.join(\"resources\", \"RSA.ico\")) # 图标文件路径\nIMAGES_PATH = get_resource_path(os.path.join(\"resources\", \"Rsa_Icon.png\")) # 图片路径\n\nimport tkinter # 导入相关的窗体模块\nclass MainForm: # 定义窗体类\n def __init__(self):\n self.root = tkinter.Tk() # 创建一个窗体\n self.root.title(\"CalculatorText\") # 设置标题\n self.root.iconbitmap(LOGO_PATH) # 设置logo的资源\n self.root.geometry(\"505x195\") # 设置初始化尺寸\n self.root[\"background\"] = \"LightSlateGray\" # 背景色\n #self.photo = tkinter.PhotoImage(file=IMAGES_PATH) # 定义图片组件\n self.root.protocol(\"WM_DELETE_WINDOW\", self.close_handle) # 窗体关闭事件\n\n self.content_P = tkinter.StringVar() # 素数P\n self.content_Q = tkinter.StringVar() # 素数Q\n self.content_expressly = tkinter.StringVar() # 明文\n self.content_ciphertext = tkinter.StringVar() # 密文\n self.content_PK = tkinter.StringVar() # 公钥\n self.content_SK = tkinter.StringVar() # 私钥\n self.content_N1 = tkinter.StringVar() # N1\n self.content_N2 = tkinter.StringVar() # N2\n self.content_E = tkinter.StringVar() # 公钥 E\n self.content_D = tkinter.StringVar() # 私钥 D\n\n self.font_button = (\"微软雅黑\", 10)\n self.font_entry = (\"微软雅黑\", 15)\n self.label_width = 6\n\n ''' 组件 '''\n self.input_frame_1()\n self.input_frame_2()\n self.input_frame_3()\n self.root.mainloop() # 显示窗体\n\n def input_frame_1(self): # 生成公私钥框\n input_frame = tkinter.Frame(self.root, width=50) # 创建容器\n label_P = tkinter.Label(input_frame, text=\"素数P: \", width=self.label_width)\n entry_P = tkinter.Entry(input_frame, \n width=15, font=self.font_entry, textvariable=self.content_P)\n label_Q = tkinter.Label(input_frame, text=\"素数Q: \", width=self.label_width)\n entry_Q = tkinter.Entry(input_frame, \n width=15, font=self.font_entry, textvariable=self.content_Q)\n button_random = tkinter.Button(input_frame, text=\"随机\", fg=\"black\", width=4, font=self.font_button)\n button_random.bind(\"\", lambda event: self.button_handle_random(event)) # 绑定按钮(随机素数)事件\n\n label_PK = tkinter.Label(input_frame, text=\"公钥:\", width=self.label_width)\n entry_pk = tkinter.Entry(input_frame, \n width=22, font=(\"微软雅黑\", 10), textvariable=self.content_PK)\n label_SK = tkinter.Label(input_frame, text=\"私钥:\", width=self.label_width)\n entry_SK = tkinter.Entry(input_frame, \n width=22, font=(\"微软雅黑\", 10), textvariable=self.content_SK)\n button_create = tkinter.Button(input_frame, text=\"生成\", fg=\"black\", width=4, font=self.font_button)\n button_create.bind(\"\", lambda event: self.button_handle_create(event)) # 绑定按钮(生成公私钥)事件\n\n label_P.grid(row=0, column=0)\n entry_P.grid(row=0, column=1)\n label_Q.grid(row=0, column=2)\n entry_Q.grid(row=0, column=3)\n button_random.grid(row=0, column=4)\n\n label_PK.grid(row=1, column=0)\n entry_pk.grid(row=1, column=1)\n label_SK.grid(row=1, column=2)\n entry_SK.grid(row=1, column=3)\n button_create.grid(row=1, column=4)\n\n input_frame.pack()\n\n def input_frame_2(self): # 加密解密框\n input_frame = tkinter.Frame(self.root, width=50) # 创建容器\n label_N1 = tkinter.Label(input_frame, text=\"N1: \", width=self.label_width)\n entry_N1 = tkinter.Entry(input_frame, \n width=15, font=self.font_entry, textvariable=self.content_N1)\n label_E = tkinter.Label(input_frame, text=\"E: \", width=self.label_width)\n entry_E = tkinter.Entry(input_frame, \n width=15, font=self.font_entry, textvariable=self.content_E)\n label_N2 = tkinter.Label(input_frame, text=\"N2: \", width=self.label_width)\n entry_N2 = tkinter.Entry(input_frame, \n width=15, font=self.font_entry, textvariable=self.content_N2)\n label_D = tkinter.Label(input_frame, text=\"D: \", width=self.label_width)\n entry_D = tkinter.Entry(input_frame, \n width=15, font=self.font_entry, textvariable=self.content_D)\n\n button_encryption = tkinter.Button(input_frame, text=\"加密\", fg=\"black\", width=4, font=self.font_button) # 加密\n button_decrypt = tkinter.Button(input_frame, text=\"解密\", fg=\"black\", width=4, font=self.font_button) # 解密\n button_encryption.bind(\"\", lambda event: self.button_handle_encryption(event)) # 绑定按钮(加密)事件\n button_decrypt.bind(\"\", lambda event: self.button_handle_decrypt(event)) # 绑定按钮(解密)事件\n\n label_N1.grid(row=0, column=0)\n entry_N1.grid(row=0, column=1)\n label_E.grid(row=0, column=2)\n entry_E.grid(row=0, column=3)\n button_encryption.grid(row=0, column=4)\n\n label_N2.grid(row=1, column=0)\n entry_N2.grid(row=1, column=1)\n label_D.grid(row=1, column=2)\n entry_D.grid(row=1, column=3)\n button_decrypt.grid(row=1, column=4)\n\n input_frame.pack()\n\n def input_frame_3(self): # 明文和密文框\n input_frame = tkinter.Frame(self.root, width=50) # 创建一个内部容器\n label_expressly = tkinter.Label(input_frame, text=\"明文: \", width=self.label_width)\n label_ciphertext = tkinter.Label(input_frame, text=\"密文: \", width=self.label_width)\n entry_expressly = tkinter.Entry(input_frame, \n width=38, font=self.font_entry, textvariable=self.content_expressly) # 明文\n entry_ciphertext = tkinter.Entry(input_frame, \n width=38, font=self.font_entry, textvariable=self.content_ciphertext) # 密文\n \n label_expressly.grid(row=0, column=0)\n entry_expressly.grid(row=0, column=1)\n label_ciphertext.grid(row=1, column=0)\n entry_ciphertext.grid(row=1, column=1)\n input_frame.pack()\n\n def button_handle_random(self, event): # 按钮(随机素数)事件\n a= Primes(2, 5000, 1000)\n p = random.choice(a)\n q = random.choice(a)\n self.content_P.set(\"%s\" % p)\n self.content_Q.set(\"%s\" % q)\n #print(\"素数p=%s, 素数q=%s\" % (p,q))\n\n def button_handle_create(self, event): # 按钮(生成公私钥)事件\n try:\n content_P = int(self.content_P.get())\n content_Q = int(self.content_Q.get())\n except ValueError:\n tkinter.messagebox.showinfo(title=\"消息提示(只能素数)\", message=\"请输入正确的素数 P 和 Q \")\n else:\n n = content_P * content_Q\n s = (content_P-1) * (content_Q-1)\n e = rsa_test.co_prime(s)\n #print(\"根据e和(p-1)*(q-1))互质得到: e=%s s=%s\" % (e,s))\n d = rsa_test.find_d(e,s)\n #print(\"根据(e*d) 模 ((p-1)*(q-1)) 等于 1 得到 d=\", d)\n\n self.content_PK.set(\"(N1=%s E=%s)\" % (n,e))\n self.content_SK.set(\"(N2=%s D=%s)\" % (n,d))\n self.content_N1.set(\"%s\" % n)\n self.content_N2.set(\"%s\" % n)\n self.content_E.set(\"%s\" % e)\n self.content_D.set(\"%s\" % d)\n\n def button_handle_encryption(self, event): # 按钮(加密)事件\n try:\n content_expressly = int(self.content_expressly.get())\n content_N1= int(self.content_N1.get())\n content_E = int(self.content_E.get())\n except ValueError:\n tkinter.messagebox.showinfo(title=\"消息提示(只能整数)\", message=\"请输入正确的 N1、E、明文\")\n else:\n B = pow(content_expressly,content_E) % content_N1 # 加密\n self.content_ciphertext.set(\"%s\" % B) \n \n def button_handle_decrypt(self, event): # 按钮(解密)事件\n try:\n content_ciphertext = int(self.content_ciphertext.get())\n content_N2= int(self.content_N2.get())\n content_D = int(self.content_D.get())\n except ValueError:\n tkinter.messagebox.showinfo(title=\"消息提示(只能整数)\", message=\"请输入正确的 N2、D、密文\")\n else:\n C = pow(content_ciphertext,content_D) % content_N2 # 解密\n self.content_expressly.set(\"%s\" % C)\n\n def close_handle(self):\n if tkinter.messagebox.askyesnocancel(\"程序关闭确认！\", \"是否确认关闭程序？\"):\n self.root.destroy() # 关闭程序\n\ndef main(): # 主函数 \n MainForm() # 实例化窗体类\n\nif __name__ == \"__main__\":\n main()\n"},{"alpha_fraction":0.5285714268684387,"alphanum_fraction":0.5532467365264893,"avg_line_length":17.35714340209961,"blob_id":"8b3f9ad50677be3d1fa89cd36c10bbe7466f48a7","content_id":"2875efbfa46b52f41df49a981731cb9558ce81ab","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1134,"license_type":"no_license","max_line_length":41,"num_lines":42,"path":"/3.RSA_work/primes.py","repo_name":"LJJ-CDD/Python_work","src_encoding":"UTF-8","text":"'''\n埃氏筛法\n（1）先把1删除（现今数学界1既不是质数也不是合数）\n（2）读取队列中当前最小的数2，然后把2的倍数删去\n（3）读取队列中当前最小的数3，然后把3的倍数删去\n（4）读取队列中当前最小的数5，然后把5的倍数删去\n（5）如上所述直到需求的范围内所有的数均删除或读取\n'''\n\n# 生成一个奇数生成器。\ndef odd_iter():\n n = 1\n while True:\n n = n + 2\n yield n\n\n# 过滤掉n的倍数的数。\ndef not_divisible(n):\n return lambda x: x % n > 0\n\n# 获取当前序列的第一个元素，然后删除后面序列该元素倍数的数，然后构造新序列。\ndef count():\n yield 2\n it = odd_iter()\n while True:\n n = next(it)\n yield n\n it = filter(not_divisible(n), it)\n\n# 获取 start 到 stop 之间的 num 个素数\ndef Primes(start , stop, num):\n primes = []\n k = 0\n for n in count():\n if n > start and n < stop:\n primes.append(n)\n k += 1\n elif n > stop:\n break\n if k==num:\n break\n return primes"},{"alpha_fraction":0.5874528288841248,"alphanum_fraction":0.6075044870376587,"avg_line_length":48.382354736328125,"blob_id":"e6847f32da8ff57452cecc37b4fadae5fd56f641","content_id":"8af312705659d5bf673ca77c84e78993a7d62f4e","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":5727,"license_type":"no_license","max_line_length":119,"num_lines":102,"path":"/3.RSA_work/CalculatorText.py","repo_name":"LJJ-CDD/Python_work","src_encoding":"UTF-8","text":"from logging import root\nimport tkinter # 窗体相关\nimport tkinter.messagebox # 实现提示框的组件\nimport tkinter.simpledialog # 对话框\nimport os # 路径\nimport sys # 操作系统交互\nimport re\nfrom typing import Pattern # 正则\n\nimport rsa_test\n\ndef get_resource_path(relative_path): # 利用此函数实现资源路径的定位\n if getattr(sys, \"frozen\", False):\n base_path = sys._MEIPASS # 获取临时资源\n else:\n base_path = os.path.abspath(\".\") # 获取当前路径\n return os.path.join(base_path, relative_path) # 绝对路径\n\nLOGO_PATH = get_resource_path(os.path.join(\"Python_work\\\\3.RSA_work\\\\resources\", \"RSA.ico\")) # 图标文件路径\nIMAGES_PATH = get_resource_path(os.path.join(\"Python_work\\\\3.RSA_work\\\\resources\", \"Rsa_Icon.png\")) # 图片路径\nEMAIL_PATTERN = r\"[a-zA-Z0-9]\\w+@\\w+\\.(cn|com|com.cn|gov|net)\" # 正则表达式\n#LOGO_PATH = get_resource_path(os.path.join(\"resources\", \"RSA.ico\")) # 图标文件路径\n#IMAGES_PATH = get_resource_path(os.path.join(\"resources\", \"Rsa_Icon.png\")) # 图片路径\n\nimport tkinter # 导入相关的窗体模块\nclass MainForm: # 定义窗体类\n def __init__(self):\n self.root = tkinter.Tk() # 创建一个窗体\n self.root.title(\"CalculatorText\") # 设置标题\n self.root.iconbitmap() # 设置logo的资源\n self.root.geometry(\"231x280\") # 设置初始化尺寸\n self.root[\"background\"] = \"LightSlateGray\" # 背景色\n #self.photo = tkinter.PhotoImage(file=IMAGES_PATH) # 定义图片组件\n #self.root.protocol(\"WM_DELETE_WINDOW\", self.close_handle) # 窗体关闭事件\n\n ''' 组件 '''\n self.button_frame()\n self.input_frame()\n self.root.mainloop() # 显示窗体\n\n def input_frame(self): # 定义输入组\n self.input_frame = tkinter.Frame(self.root, width=20) # 创建一个内部容器\n self.content = tkinter.StringVar() # 修改标签文字\n self.entry = tkinter.Entry(self.input_frame, \n width=14, font=(\"微软雅黑\", 20), textvariable=self.content) # 用entry 控制单行输入\n self.entry.pack(fill=\"x\", expand=1) # x轴全填充\n self.clean = False # 清除标记，每一次计算完成之后清除\n self.input_frame.pack(side=\"top\")\n\n def button_frame(self): # 定义按钮组\n self.button_frame = tkinter.Frame(self.root, width=50) # 创建容器\n self.button_list = [[], [], [], []] # 一共定义了4组组件\n self.button_list[0].append(tkinter.Button(self.button_frame, text=\"1\", fg=\"black\", width=3, font=(\"微软雅黑\", 20)))\n self.button_list[0].append(tkinter.Button(self.button_frame, text=\"2\", fg=\"black\", width=3, font=(\"微软雅黑\", 20)))\n self.button_list[0].append(tkinter.Button(self.button_frame, text=\"3\", fg=\"black\", width=3, font=(\"微软雅黑\", 20)))\n self.button_list[0].append(tkinter.Button(self.button_frame, text=\"+\", fg=\"black\", width=3, font=(\"微软雅黑\", 20)))\n \n self.button_list[1].append(tkinter.Button(self.button_frame, text=\"4\", fg=\"black\", width=3, font=(\"微软雅黑\", 20)))\n self.button_list[1].append(tkinter.Button(self.button_frame, text=\"5\", fg=\"black\", width=3, font=(\"微软雅黑\", 20)))\n self.button_list[1].append(tkinter.Button(self.button_frame, text=\"6\", fg=\"black\", width=3, font=(\"微软雅黑\", 20)))\n self.button_list[1].append(tkinter.Button(self.button_frame, text=\"-\", fg=\"black\", width=3, font=(\"微软雅黑\", 20)))\n \n self.button_list[2].append(tkinter.Button(self.button_frame, text=\"7\", fg=\"black\", width=3, font=(\"微软雅黑\", 20)))\n self.button_list[2].append(tkinter.Button(self.button_frame, text=\"8\", fg=\"black\", width=3, font=(\"微软雅黑\", 20)))\n self.button_list[2].append(tkinter.Button(self.button_frame, text=\"9\", fg=\"black\", width=3, font=(\"微软雅黑\", 20)))\n self.button_list[2].append(tkinter.Button(self.button_frame, text=\"*\", fg=\"black\", width=3, font=(\"微软雅黑\", 20)))\n\n self.button_list[3].append(tkinter.Button(self.button_frame, text=\".\", fg=\"black\", width=3, font=(\"微软雅黑\", 20)))\n self.button_list[3].append(tkinter.Button(self.button_frame, text=\"0\", fg=\"black\", width=3, font=(\"微软雅黑\", 20)))\n self.button_list[3].append(tkinter.Button(self.button_frame, text=\"=\", fg=\"black\", width=3, font=(\"微软雅黑\", 20)))\n self.button_list[3].append(tkinter.Button(self.button_frame, text=\"/\", fg=\"black\", width=3, font=(\"微软雅黑\", 20)))\n \n self.row = 0 # 进行行数的控制\n for group in self.button_list:\n self.column = 0 # 进行列的控制\n for button in group:\n button.bind(\"\", lambda event: self.button_handle(event)) # 绑定事件\n button.grid(row=self.row, column=self.column)\n self.column += 1 # 每次列+1\n self.row += 1\n \n self.button_frame.pack(side=\"bottom\")\n\n def button_handle(self, event):\n oper = event.widget[\"text\"] # 获取组件中的文本\n if self.clean: # 第二次计算\n self.content.set(\"\") # 清除标记中的数据\n self.clean = False # 留给下一次计算输入\n if oper != \"=\": # 意味着计算\n self.entry.insert(\"end\", oper)\n elif oper == \"=\": # 执行运算\n result = 0 # 保存程序的计算结果\n exp = self.entry.get()\n result = eval(exp)\n self.entry.insert(\"end\", \"=%s\" % result) \n self.clean = True\n\ndef main(): # 主函数 \n MainForm() # 实例化窗体类\n\nif __name__ == \"__main__\":\n main()\n"},{"alpha_fraction":0.49096208810806274,"alphanum_fraction":0.559183657169342,"avg_line_length":34,"blob_id":"59d7fd92afbcea116c691d2dcfef095dc2b9dad0","content_id":"255e81daf5c242b1030a945bda8fc44887078ffc","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1847,"license_type":"no_license","max_line_length":194,"num_lines":49,"path":"/1.spider_maoyan/spider_board.py","repo_name":"LJJ-CDD/Python_work","src_encoding":"UTF-8","text":"from urllib import request,parse\nimport random\nimport time\n\nclass MaoYanSpider(object):\n ''' 爬取网页 '''\n def __init__(self, root):\n self.url=\"https://maoyan.com/board/4?offset={}\"\n self.ua_list = [\n 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_11_6) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/77.0.3865.120 Safari/537.36',\n 'Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/535.1 (KHTML, like Gecko) Chrome/14.0.835.163 Safari/535.1',\n 'Mozilla/5.0 (Windows NT 6.1; WOW64; rv:6.0) Gecko/20100101 Firefox/6.0',\n 'Mozilla/4.0 (compatible; MSIE 8.0; Windows NT 6.1; WOW64; Trident/4.0; SLCC2; .NET CLR 2.0.50727; .NET CLR 3.5.30729; .NET CLR 3.0.30729; Media Center PC 6.0; .NET4.0C; InfoPath.3)'\n ]\n #用于记录页数\n self.page = 1\n self.root = root\n\n '''发送请求函数'''\n def get_page(self,url):\n #定义一个headers\n headers={\n 'User-Agent':random.choice(self.ua_list),\n }\n #构造请求头\n req=request.Request(url=url,headers=headers)\n res=request.urlopen(req)\n html=res.read().decode(\"utf-8\")\n # 将获取的html写到本地\n self.parse_page(html)\n\n '''定义一个函数写到本地'''\n def parse_page(self,html):\n filename = self.root + '/第{}页.html'.format(self.page)\n print(filename)\n with open(filename,'w+',encoding='utf-8') as f:\n f.write(html)\n\n '''主函数'''\n def main(self):\n '''拼接url地址'''\n for offset in range(0,60,10):\n url=self.url.format(offset)\n print(url)\n #发送请求 获取响应\n self.get_page(url)\n time.sleep(random.randint(5,8))\n print(\"第%d页爬取完成\"%self.page)\n self.page+=1\n"},{"alpha_fraction":0.5963488817214966,"alphanum_fraction":0.5983772873878479,"avg_line_length":21.454545974731445,"blob_id":"da19e47dcb432ee7d78c28d8e2fac4485f70e7de","content_id":"7420e5a49153bffb664e80d2feba0010149ccfa6","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":521,"license_type":"no_license","max_line_length":41,"num_lines":22,"path":"/2.JSON_analysis/main.py","repo_name":"LJJ-CDD/Python_work","src_encoding":"UTF-8","text":"import os\nimport time\nfrom analysis import JXSpider #解析\nfrom spider_board import TXSpider # 爬取网页\n\ndef judge_os():\n root = os.getcwd()\n root = root + '/招聘信息'\n root = root.replace(os.sep, '/')\n if(not os.path.exists(root)):\n os.mkdir(root) \n return root\n\nif __name__ == '__main__':\n root = judge_os()\n start=time.time()\n spider=TXSpider(root)\n spider.main()\n spider=JXSpider(root)\n spider.main()\n end=time.time()\n print('执行时间%.2f'%(end-start))"},{"alpha_fraction":0.4467253088951111,"alphanum_fraction":0.45698925852775574,"avg_line_length":36.21818161010742,"blob_id":"8e806fe5b3ea78c3fff3c581210d482969823755","content_id":"1bfe2ea47882b00484c00b584b6063f437ddcfd4","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":2174,"license_type":"no_license","max_line_length":110,"num_lines":55,"path":"/1.spider_maoyan/analysis.py","repo_name":"LJJ-CDD/Python_work","src_encoding":"UTF-8","text":"from urllib import request\nimport requests\nimport re\nimport csv\nimport os\n\nclass JieXiBangDanSpider(object):\n ''' 解析榜单 '''\n def __init__(self, root):\n self.root = root\n\n def parse_page(self, html):\n ''' 正则匹配 '''\n pattern = re.compile('.*?.*?' # 图片\n '
.*?class=\"name\">.*?' # 电影名称\n '(.*?).*?' #主演\n 'class=\"releasetime\">(.*?).*?' # 上映时间\n 'class=\"score\">.*?(.*?).*?(.*?)' # 评分\n , re.S) \n r_list = pattern.findall(html)\n self.write_page(r_list)\n\n def write_page(self, r_list):\n ''' 写入csv '''\n filename = self.root + '/maoyan.csv'\n film_list = []\n with open(filename, 'a', encoding='utf-8') as f:\n writer = csv.writer(f)\n for rt in r_list:\n one_film = [\n rt[1].strip(), rt[2].strip()[5:15],rt[3].strip()[5:],rt[4].strip()+rt[5].strip(),rt[0]\n ]\n film_list.append(one_film)\n self.download_image(rt[0], rt[1]) # 下载图片\n writer.writerows(film_list)\n \n def save_image(self, content, name):\n ''' 下载图片 '''\n file_path = '{0}/{1}.{2}'.format(self.root, name, 'jpg')#注意斜杠是/\n if not os.path.exists(file_path):#os.path.exists(file_path)判断文件是否存在，存在返回1，不存在返回0\n with open(file_path, 'wb') as f:\n f.write(content)\n f.close()\n\n def download_image(self, url, name):#保存图片链接\n r = requests.get(url)\n r.raise_for_status()\n self.save_image(r.content, name)\n\n def main(self):\n for i in range(1,6):\n filename = self.root + '/第{}页.html'.format(i)\n f=open(filename,'r',encoding='utf-8')\n html=f.read()\n self.parse_page(html)"},{"alpha_fraction":0.5727580189704895,"alphanum_fraction":0.5922166109085083,"avg_line_length":32.79999923706055,"blob_id":"5ca47b024bb52afcfba767b2148fd1e4bc009983","content_id":"1d7427e815a9a6e7ac092575ac615d6950e18b48","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1224,"license_type":"no_license","max_line_length":168,"num_lines":35,"path":"/2.JSON_analysis/spider_board.py","repo_name":"LJJ-CDD/Python_work","src_encoding":"UTF-8","text":"from fake_useragent import UserAgent\nimport requests\nimport time\nimport random\nclass TXSpider(object):\n '''爬取和写入到本地json'''\n def __init__(self,root):\n self.url='https://careers.tencent.com/tencentcareer/api/post/Query?timestamp=1619657326691&countryId=&cityId=&bgIds=&productId=&categoryId=&parentCategoryId=' \\\n '&attrId=&keyword=&pageIndex={}&pageSize=10&language=zh-cn&area=cn'\n self.headers={\n 'user-agent':UserAgent().random\n }\n self.page=1\n self.root = root\n\n def get_page(self,url):\n res=requests.get(url=url,headers=self.headers)\n html=res.content.decode('utf-8')\n return html\n\n def write_page(self,html):\n '''将json写到本地'''\n filename = self.root + '/第{}页.json'.format(self.page)\n print(filename)\n with open(filename,'w+',encoding='utf-8') as f:\n f.write(html)\n\n def main(self):\n for page in range(1,6):\n url=self.url.format(page)\n html=self.get_page(url)\n self.write_page(html)\n time.sleep(random.randint(3,5))\n print(\"第{}页爬取成功\".format(self.page))\n self.page+=1"},{"alpha_fraction":0.6177605986595154,"alphanum_fraction":0.6196911334991455,"avg_line_length":22.545454025268555,"blob_id":"7c84141679b1ce7d9b9ce8befdcdce8fe5d073b0","content_id":"9f4e84dfccbf7f83a15af0b8a35d955d56fd0fdc","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":542,"license_type":"no_license","max_line_length":47,"num_lines":22,"path":"/1.spider_maoyan/main.py","repo_name":"LJJ-CDD/Python_work","src_encoding":"UTF-8","text":"import os\nimport time\nfrom analysis import JieXiBangDanSpider\nfrom spider_board import MaoYanSpider # 爬取榜单网页\n\ndef judge_os():\n root = os.getcwd()\n root = root + '/榜单'\n root = root.replace(os.sep, '/')\n if(not os.path.exists(root)):\n os.mkdir(root) \n return root\n\nif __name__ == '__main__':\n root = judge_os()\n start=time.time()\n #spider=MaoYanSpider(root)\n #spider.main()\n spider=JieXiBangDanSpider(root)\n spider.main()\n end=time.time()\n print('执行时间%.2f'%(end-start))\n"},{"alpha_fraction":0.5414551496505737,"alphanum_fraction":0.5448392629623413,"avg_line_length":32.79999923706055,"blob_id":"d3567ce844c22a0dbcf2250ea1599043b95cc33e","content_id":"306da3ca37c259090babd41b5b0e9983570be00b","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1226,"license_type":"no_license","max_line_length":104,"num_lines":35,"path":"/2.JSON_analysis/analysis.py","repo_name":"LJJ-CDD/Python_work","src_encoding":"UTF-8","text":"import json\nimport csv\n\nclass JXSpider(object):\n '''将本地json转换为CSV'''\n def __init__(self, root):\n self.root = root\n\n def parse_page(self,json_str):\n '''将json字符串转成python字符串'''\n python_dict=json.loads(json_str)\n python_list=python_dict['Data']['Posts']\n for car in python_list:\n career_dict={}\n career_dict['RecruitPostName']=car['RecruitPostName']\n career_dict['LocationName']=car['LocationName']\n career_dict['Responsibility']= car['Responsibility'].replace('\\n','').replace('\\r','') # 格式化\n self.write_page(career_dict)\n\n def write_page(self, career_dict):\n ''' 写入csv '''\n filename = self.root + '/TX.csv'\n film_list = []\n with open(filename, 'a', encoding='utf-8') as f: \n writer = csv.writer(f)\n for K,V in career_dict.items():\n film_list.append(V)\n writer.writerow(film_list)\n\n def main(self):\n for i in range(1,6):\n filename = self.root + '/第{}页.json'.format(i)\n f=open(filename,'r',encoding='utf-8')\n json_str=f.read()\n self.parse_page(json_str)"},{"alpha_fraction":0.5891246795654297,"alphanum_fraction":0.6010609865188599,"avg_line_length":35.25,"blob_id":"8627baa98307d8bfb8a22ed0e028c0b373f01a71","content_id":"40ba2b1cc945036da9e973561946eb9d8a77a9dd","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":4414,"license_type":"no_license","max_line_length":106,"num_lines":104,"path":"/3.RSA_work/main_test.py","repo_name":"LJJ-CDD/Python_work","src_encoding":"UTF-8","text":"from logging import root\nimport tkinter # 窗体相关\nimport tkinter.messagebox # 实现提示框的组件\nimport tkinter.simpledialog # 对话框\nimport os # 路径\nimport sys # 操作系统交互\nimport re # 正则\n\nimport rsa_test\n\ndef get_resource_path(relative_path): # 利用此函数实现资源路径的定位\n if getattr(sys, \"frozen\", False):\n base_path = sys._MEIPASS # 获取临时资源\n else:\n base_path = os.path.abspath(\".\") # 获取当前路径\n return os.path.join(base_path, relative_path) # 绝对路径\n\nLOGO_PATH = get_resource_path(os.path.join(\"Python_work\\\\3.RSA_work\\\\resources\", \"RSA.ico\")) # 图标文件路径\nIMAGES_PATH = get_resource_path(os.path.join(\"Python_work\\\\3.RSA_work\\\\resources\", \"Rsa_Icon.png\")) # 图片路径\nEMAIL_PATTERN = r\"[a-zA-Z0-9]\\w+@\\w+\\.(cn|com|com.cn|gov|net)\" # 正则表达式\n#LOGO_PATH = get_resource_path(os.path.join(\"resources\", \"RSA.ico\")) # 图标文件路径\n#IMAGES_PATH = get_resource_path(os.path.join(\"resources\", \"Rsa_Icon.png\")) # 图片路径\n\nimport tkinter # 导入相关的窗体模块\nclass MainForm: # 定义窗体类\n def __init__(self):\n self.root = tkinter.Tk() # 创建一个窗体\n self.root.title(\"Liu_RsaText\") # 设置标题\n self.root.iconbitmap() # 设置logo的资源\n self.root.geometry(\"500x300\") # 设置初始化尺寸\n self.root.maxsize(1000, 400) # 设置窗体的最大尺寸\n self.root[\"background\"] = \"LightSlateGray\" # 背景色\n\n self.photo = tkinter.PhotoImage(file=IMAGES_PATH) # 定义图片组件\n self.content = tkinter.StringVar() # 修改标签文字\n self.root.protocol(\"WM_DELETE_WINDOW\", self.close_handle) # 窗体关闭事件\n\n ''' 组件 '''\n #self.label_photo()\n #self.TK_text()\n #self.label_text()\n self.TK_button()\n\n self.root.mainloop() # 显示窗体\n\n def label_text(self):\n # 进行文本标签定义\n Lambda_text = tkinter.Label(self.root, textvariable=self.content, width=200, height=200, \n bg=\"#223011\", fg=\"#ffffff\",font=(\"微软雅黑\", 10), justify=\"right\")\n Lambda_text.pack() # 组件显示\n\n def label_photo(self):\n # 进行文本图片标签定义\n Label_photo = tkinter.Label(self.root, image=self.photo) # 图片标签\n Label_photo.pack() # 标签显示 \n\n def TK_text(self):\n # 定义文本组件窗口\n text = tkinter.Text(self.root, width=50, height=10, font=(\"微软雅黑\", 10))\n #text.image_create(\"end\", image=self.photo)\n text.insert(\"current\", \"请输入正确的Email信息....\") # 默认提示信息\n text.bind(\"\", lambda event :\n self.event_handle_text(event, text, \" \"))\n text.bind(\"\",lambda even: \n self.event_handle_keyboard(even, text))\n text.bind(\"\",lambda even: \n self.event_handle_keyboard(even, text))\n text.pack() # 显示文本组件\n\n def TK_button(self):\n # 定义按钮组件\n button = tkinter.Button(self.root, text=\"Liu\" , image=self.photo,\n compound=\"bottom\", fg=\"black\", font=(\"微软雅黑\", 10)) # 图片文本混合按钮\n button.bind(\"\", lambda event :\n self.event_handle(event, \"Hello World\")) # 事件\n button.pack()\n\n def event_handle(self, event, info):\n # 消息框事件\n input_message = tkinter.simpledialog.askstring(\"提示信息\", \"请输入要显示的信息: \")\n self.label_text()\n tkinter.messagebox.showinfo(title=\"Liu消息提示\", message=input_message)\n \n def event_handle_text(self, event, text, info):\n # 文本删除事件\n text.delete(\"0.0\", \"end\")\n\n def event_handle_keyboard(self, event, text):\n # 获得文本框信息输入事件\n email = text.get(\"0.0\", \"end\")\n if re.match(EMAIL_PATTERN, email, re.I | re.X):\n self.content.set(\"Email邮箱输入正确，内容为: %s\" % email)\n else:\n self.content.set(\"Email数据输入错误!\")\n\n def close_handle(self):\n if tkinter.messagebox.askyesnocancel(\"程序关闭确认！\", \"是否确认关闭程序？\"):\n self.root.destroy() # 关闭程序\n \ndef main(): # 主函数 \n MainForm() # 实例化窗体类\n\nif __name__ == \"__main__\":\n main()\n"}],"string":"[\n {\n \"alpha_fraction\": 0.5863128900527954,\n \"alphanum_fraction\": 0.6032794117927551,\n \"avg_line_length\": 43.57868194580078,\n \"blob_id\": \"941029810340767d39de84ccb2832b32b5256a42\",\n \"content_id\": \"c24d4b2fea19635f11cde6b0dc29bff616819e27\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 9576,\n \"license_type\": \"no_license\",\n \"max_line_length\": 118,\n \"num_lines\": 197,\n \"path\": \"/3.RSA_work/main.py\",\n \"repo_name\": \"LJJ-CDD/Python_work\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from logging import root\\nimport tkinter # 窗体相关\\nimport tkinter.messagebox # 实现提示框的组件\\nimport tkinter.simpledialog # 对话框\\nimport os # 路径\\nimport sys # 操作系统交互\\nfrom primes import Primes # 生成素数\\nimport random\\nimport rsa_test\\n\\ndef get_resource_path(relative_path): # 利用此函数实现资源路径的定位\\n if getattr(sys, \\\"frozen\\\", False):\\n base_path = sys._MEIPASS # 获取临时资源\\n else:\\n base_path = os.path.abspath(\\\".\\\") # 获取当前路径\\n return os.path.join(base_path, relative_path) # 绝对路径\\n\\n#LOGO_PATH = get_resource_path(os.path.join(\\\"Python_work\\\\\\\\3.RSA_work\\\\\\\\resources\\\", \\\"RSA.ico\\\")) # 图标文件路径\\n#IMAGES_PATH = get_resource_path(os.path.join(\\\"Python_work\\\\\\\\3.RSA_work\\\\\\\\resources\\\", \\\"Rsa_Icon.png\\\")) # 图片路径\\nLOGO_PATH = get_resource_path(os.path.join(\\\"resources\\\", \\\"RSA.ico\\\")) # 图标文件路径\\nIMAGES_PATH = get_resource_path(os.path.join(\\\"resources\\\", \\\"Rsa_Icon.png\\\")) # 图片路径\\n\\nimport tkinter # 导入相关的窗体模块\\nclass MainForm: # 定义窗体类\\n def __init__(self):\\n self.root = tkinter.Tk() # 创建一个窗体\\n self.root.title(\\\"CalculatorText\\\") # 设置标题\\n self.root.iconbitmap(LOGO_PATH) # 设置logo的资源\\n self.root.geometry(\\\"505x195\\\") # 设置初始化尺寸\\n self.root[\\\"background\\\"] = \\\"LightSlateGray\\\" # 背景色\\n #self.photo = tkinter.PhotoImage(file=IMAGES_PATH) # 定义图片组件\\n self.root.protocol(\\\"WM_DELETE_WINDOW\\\", self.close_handle) # 窗体关闭事件\\n\\n self.content_P = tkinter.StringVar() # 素数P\\n self.content_Q = tkinter.StringVar() # 素数Q\\n self.content_expressly = tkinter.StringVar() # 明文\\n self.content_ciphertext = tkinter.StringVar() # 密文\\n self.content_PK = tkinter.StringVar() # 公钥\\n self.content_SK = tkinter.StringVar() # 私钥\\n self.content_N1 = tkinter.StringVar() # N1\\n self.content_N2 = tkinter.StringVar() # N2\\n self.content_E = tkinter.StringVar() # 公钥 E\\n self.content_D = tkinter.StringVar() # 私钥 D\\n\\n self.font_button = (\\\"微软雅黑\\\", 10)\\n self.font_entry = (\\\"微软雅黑\\\", 15)\\n self.label_width = 6\\n\\n ''' 组件 '''\\n self.input_frame_1()\\n self.input_frame_2()\\n self.input_frame_3()\\n self.root.mainloop() # 显示窗体\\n\\n def input_frame_1(self): # 生成公私钥框\\n input_frame = tkinter.Frame(self.root, width=50) # 创建容器\\n label_P = tkinter.Label(input_frame, text=\\\"素数P: \\\", width=self.label_width)\\n entry_P = tkinter.Entry(input_frame, \\n width=15, font=self.font_entry, textvariable=self.content_P)\\n label_Q = tkinter.Label(input_frame, text=\\\"素数Q: \\\", width=self.label_width)\\n entry_Q = tkinter.Entry(input_frame, \\n width=15, font=self.font_entry, textvariable=self.content_Q)\\n button_random = tkinter.Button(input_frame, text=\\\"随机\\\", fg=\\\"black\\\", width=4, font=self.font_button)\\n button_random.bind(\\\"\\\", lambda event: self.button_handle_random(event)) # 绑定按钮(随机素数)事件\\n\\n label_PK = tkinter.Label(input_frame, text=\\\"公钥:\\\", width=self.label_width)\\n entry_pk = tkinter.Entry(input_frame, \\n width=22, font=(\\\"微软雅黑\\\", 10), textvariable=self.content_PK)\\n label_SK = tkinter.Label(input_frame, text=\\\"私钥:\\\", width=self.label_width)\\n entry_SK = tkinter.Entry(input_frame, \\n width=22, font=(\\\"微软雅黑\\\", 10), textvariable=self.content_SK)\\n button_create = tkinter.Button(input_frame, text=\\\"生成\\\", fg=\\\"black\\\", width=4, font=self.font_button)\\n button_create.bind(\\\"\\\", lambda event: self.button_handle_create(event)) # 绑定按钮(生成公私钥)事件\\n\\n label_P.grid(row=0, column=0)\\n entry_P.grid(row=0, column=1)\\n label_Q.grid(row=0, column=2)\\n entry_Q.grid(row=0, column=3)\\n button_random.grid(row=0, column=4)\\n\\n label_PK.grid(row=1, column=0)\\n entry_pk.grid(row=1, column=1)\\n label_SK.grid(row=1, column=2)\\n entry_SK.grid(row=1, column=3)\\n button_create.grid(row=1, column=4)\\n\\n input_frame.pack()\\n\\n def input_frame_2(self): # 加密解密框\\n input_frame = tkinter.Frame(self.root, width=50) # 创建容器\\n label_N1 = tkinter.Label(input_frame, text=\\\"N1: \\\", width=self.label_width)\\n entry_N1 = tkinter.Entry(input_frame, \\n width=15, font=self.font_entry, textvariable=self.content_N1)\\n label_E = tkinter.Label(input_frame, text=\\\"E: \\\", width=self.label_width)\\n entry_E = tkinter.Entry(input_frame, \\n width=15, font=self.font_entry, textvariable=self.content_E)\\n label_N2 = tkinter.Label(input_frame, text=\\\"N2: \\\", width=self.label_width)\\n entry_N2 = tkinter.Entry(input_frame, \\n width=15, font=self.font_entry, textvariable=self.content_N2)\\n label_D = tkinter.Label(input_frame, text=\\\"D: \\\", width=self.label_width)\\n entry_D = tkinter.Entry(input_frame, \\n width=15, font=self.font_entry, textvariable=self.content_D)\\n\\n button_encryption = tkinter.Button(input_frame, text=\\\"加密\\\", fg=\\\"black\\\", width=4, font=self.font_button) # 加密\\n button_decrypt = tkinter.Button(input_frame, text=\\\"解密\\\", fg=\\\"black\\\", width=4, font=self.font_button) # 解密\\n button_encryption.bind(\\\"\\\", lambda event: self.button_handle_encryption(event)) # 绑定按钮(加密)事件\\n button_decrypt.bind(\\\"\\\", lambda event: self.button_handle_decrypt(event)) # 绑定按钮(解密)事件\\n\\n label_N1.grid(row=0, column=0)\\n entry_N1.grid(row=0, column=1)\\n label_E.grid(row=0, column=2)\\n entry_E.grid(row=0, column=3)\\n button_encryption.grid(row=0, column=4)\\n\\n label_N2.grid(row=1, column=0)\\n entry_N2.grid(row=1, column=1)\\n label_D.grid(row=1, column=2)\\n entry_D.grid(row=1, column=3)\\n button_decrypt.grid(row=1, column=4)\\n\\n input_frame.pack()\\n\\n def input_frame_3(self): # 明文和密文框\\n input_frame = tkinter.Frame(self.root, width=50) # 创建一个内部容器\\n label_expressly = tkinter.Label(input_frame, text=\\\"明文: \\\", width=self.label_width)\\n label_ciphertext = tkinter.Label(input_frame, text=\\\"密文: \\\", width=self.label_width)\\n entry_expressly = tkinter.Entry(input_frame, \\n width=38, font=self.font_entry, textvariable=self.content_expressly) # 明文\\n entry_ciphertext = tkinter.Entry(input_frame, \\n width=38, font=self.font_entry, textvariable=self.content_ciphertext) # 密文\\n \\n label_expressly.grid(row=0, column=0)\\n entry_expressly.grid(row=0, column=1)\\n label_ciphertext.grid(row=1, column=0)\\n entry_ciphertext.grid(row=1, column=1)\\n input_frame.pack()\\n\\n def button_handle_random(self, event): # 按钮(随机素数)事件\\n a= Primes(2, 5000, 1000)\\n p = random.choice(a)\\n q = random.choice(a)\\n self.content_P.set(\\\"%s\\\" % p)\\n self.content_Q.set(\\\"%s\\\" % q)\\n #print(\\\"素数p=%s, 素数q=%s\\\" % (p,q))\\n\\n def button_handle_create(self, event): # 按钮(生成公私钥)事件\\n try:\\n content_P = int(self.content_P.get())\\n content_Q = int(self.content_Q.get())\\n except ValueError:\\n tkinter.messagebox.showinfo(title=\\\"消息提示(只能素数)\\\", message=\\\"请输入正确的素数 P 和 Q \\\")\\n else:\\n n = content_P * content_Q\\n s = (content_P-1) * (content_Q-1)\\n e = rsa_test.co_prime(s)\\n #print(\\\"根据e和(p-1)*(q-1))互质得到: e=%s s=%s\\\" % (e,s))\\n d = rsa_test.find_d(e,s)\\n #print(\\\"根据(e*d) 模 ((p-1)*(q-1)) 等于 1 得到 d=\\\", d)\\n\\n self.content_PK.set(\\\"(N1=%s E=%s)\\\" % (n,e))\\n self.content_SK.set(\\\"(N2=%s D=%s)\\\" % (n,d))\\n self.content_N1.set(\\\"%s\\\" % n)\\n self.content_N2.set(\\\"%s\\\" % n)\\n self.content_E.set(\\\"%s\\\" % e)\\n self.content_D.set(\\\"%s\\\" % d)\\n\\n def button_handle_encryption(self, event): # 按钮(加密)事件\\n try:\\n content_expressly = int(self.content_expressly.get())\\n content_N1= int(self.content_N1.get())\\n content_E = int(self.content_E.get())\\n except ValueError:\\n tkinter.messagebox.showinfo(title=\\\"消息提示(只能整数)\\\", message=\\\"请输入正确的 N1、E、明文\\\")\\n else:\\n B = pow(content_expressly,content_E) % content_N1 # 加密\\n self.content_ciphertext.set(\\\"%s\\\" % B) \\n \\n def button_handle_decrypt(self, event): # 按钮(解密)事件\\n try:\\n content_ciphertext = int(self.content_ciphertext.get())\\n content_N2= int(self.content_N2.get())\\n content_D = int(self.content_D.get())\\n except ValueError:\\n tkinter.messagebox.showinfo(title=\\\"消息提示(只能整数)\\\", message=\\\"请输入正确的 N2、D、密文\\\")\\n else:\\n C = pow(content_ciphertext,content_D) % content_N2 # 解密\\n self.content_expressly.set(\\\"%s\\\" % C)\\n\\n def close_handle(self):\\n if tkinter.messagebox.askyesnocancel(\\\"程序关闭确认！\\\", \\\"是否确认关闭程序？\\\"):\\n self.root.destroy() # 关闭程序\\n\\ndef main(): # 主函数 \\n MainForm() # 实例化窗体类\\n\\nif __name__ == \\\"__main__\\\":\\n main()\\n\"\n },\n {\n \"alpha_fraction\": 0.5285714268684387,\n \"alphanum_fraction\": 0.5532467365264893,\n \"avg_line_length\": 17.35714340209961,\n \"blob_id\": \"8b3f9ad50677be3d1fa89cd36c10bbe7466f48a7\",\n \"content_id\": \"2875efbfa46b52f41df49a981731cb9558ce81ab\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1134,\n \"license_type\": \"no_license\",\n \"max_line_length\": 41,\n \"num_lines\": 42,\n \"path\": \"/3.RSA_work/primes.py\",\n \"repo_name\": \"LJJ-CDD/Python_work\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"'''\\n埃氏筛法\\n（1）先把1删除（现今数学界1既不是质数也不是合数）\\n（2）读取队列中当前最小的数2，然后把2的倍数删去\\n（3）读取队列中当前最小的数3，然后把3的倍数删去\\n（4）读取队列中当前最小的数5，然后把5的倍数删去\\n（5）如上所述直到需求的范围内所有的数均删除或读取\\n'''\\n\\n# 生成一个奇数生成器。\\ndef odd_iter():\\n n = 1\\n while True:\\n n = n + 2\\n yield n\\n\\n# 过滤掉n的倍数的数。\\ndef not_divisible(n):\\n return lambda x: x % n > 0\\n\\n# 获取当前序列的第一个元素，然后删除后面序列该元素倍数的数，然后构造新序列。\\ndef count():\\n yield 2\\n it = odd_iter()\\n while True:\\n n = next(it)\\n yield n\\n it = filter(not_divisible(n), it)\\n\\n# 获取 start 到 stop 之间的 num 个素数\\ndef Primes(start , stop, num):\\n primes = []\\n k = 0\\n for n in count():\\n if n > start and n < stop:\\n primes.append(n)\\n k += 1\\n elif n > stop:\\n break\\n if k==num:\\n break\\n return primes\"\n },\n {\n \"alpha_fraction\": 0.5874528288841248,\n \"alphanum_fraction\": 0.6075044870376587,\n \"avg_line_length\": 48.382354736328125,\n \"blob_id\": \"e6847f32da8ff57452cecc37b4fadae5fd56f641\",\n \"content_id\": \"8af312705659d5bf673ca77c84e78993a7d62f4e\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 5727,\n \"license_type\": \"no_license\",\n \"max_line_length\": 119,\n \"num_lines\": 102,\n \"path\": \"/3.RSA_work/CalculatorText.py\",\n \"repo_name\": \"LJJ-CDD/Python_work\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from logging import root\\nimport tkinter # 窗体相关\\nimport tkinter.messagebox # 实现提示框的组件\\nimport tkinter.simpledialog # 对话框\\nimport os # 路径\\nimport sys # 操作系统交互\\nimport re\\nfrom typing import Pattern # 正则\\n\\nimport rsa_test\\n\\ndef get_resource_path(relative_path): # 利用此函数实现资源路径的定位\\n if getattr(sys, \\\"frozen\\\", False):\\n base_path = sys._MEIPASS # 获取临时资源\\n else:\\n base_path = os.path.abspath(\\\".\\\") # 获取当前路径\\n return os.path.join(base_path, relative_path) # 绝对路径\\n\\nLOGO_PATH = get_resource_path(os.path.join(\\\"Python_work\\\\\\\\3.RSA_work\\\\\\\\resources\\\", \\\"RSA.ico\\\")) # 图标文件路径\\nIMAGES_PATH = get_resource_path(os.path.join(\\\"Python_work\\\\\\\\3.RSA_work\\\\\\\\resources\\\", \\\"Rsa_Icon.png\\\")) # 图片路径\\nEMAIL_PATTERN = r\\\"[a-zA-Z0-9]\\\\w+@\\\\w+\\\\.(cn|com|com.cn|gov|net)\\\" # 正则表达式\\n#LOGO_PATH = get_resource_path(os.path.join(\\\"resources\\\", \\\"RSA.ico\\\")) # 图标文件路径\\n#IMAGES_PATH = get_resource_path(os.path.join(\\\"resources\\\", \\\"Rsa_Icon.png\\\")) # 图片路径\\n\\nimport tkinter # 导入相关的窗体模块\\nclass MainForm: # 定义窗体类\\n def __init__(self):\\n self.root = tkinter.Tk() # 创建一个窗体\\n self.root.title(\\\"CalculatorText\\\") # 设置标题\\n self.root.iconbitmap() # 设置logo的资源\\n self.root.geometry(\\\"231x280\\\") # 设置初始化尺寸\\n self.root[\\\"background\\\"] = \\\"LightSlateGray\\\" # 背景色\\n #self.photo = tkinter.PhotoImage(file=IMAGES_PATH) # 定义图片组件\\n #self.root.protocol(\\\"WM_DELETE_WINDOW\\\", self.close_handle) # 窗体关闭事件\\n\\n ''' 组件 '''\\n self.button_frame()\\n self.input_frame()\\n self.root.mainloop() # 显示窗体\\n\\n def input_frame(self): # 定义输入组\\n self.input_frame = tkinter.Frame(self.root, width=20) # 创建一个内部容器\\n self.content = tkinter.StringVar() # 修改标签文字\\n self.entry = tkinter.Entry(self.input_frame, \\n width=14, font=(\\\"微软雅黑\\\", 20), textvariable=self.content) # 用entry 控制单行输入\\n self.entry.pack(fill=\\\"x\\\", expand=1) # x轴全填充\\n self.clean = False # 清除标记，每一次计算完成之后清除\\n self.input_frame.pack(side=\\\"top\\\")\\n\\n def button_frame(self): # 定义按钮组\\n self.button_frame = tkinter.Frame(self.root, width=50) # 创建容器\\n self.button_list = [[], [], [], []] # 一共定义了4组组件\\n self.button_list[0].append(tkinter.Button(self.button_frame, text=\\\"1\\\", fg=\\\"black\\\", width=3, font=(\\\"微软雅黑\\\", 20)))\\n self.button_list[0].append(tkinter.Button(self.button_frame, text=\\\"2\\\", fg=\\\"black\\\", width=3, font=(\\\"微软雅黑\\\", 20)))\\n self.button_list[0].append(tkinter.Button(self.button_frame, text=\\\"3\\\", fg=\\\"black\\\", width=3, font=(\\\"微软雅黑\\\", 20)))\\n self.button_list[0].append(tkinter.Button(self.button_frame, text=\\\"+\\\", fg=\\\"black\\\", width=3, font=(\\\"微软雅黑\\\", 20)))\\n \\n self.button_list[1].append(tkinter.Button(self.button_frame, text=\\\"4\\\", fg=\\\"black\\\", width=3, font=(\\\"微软雅黑\\\", 20)))\\n self.button_list[1].append(tkinter.Button(self.button_frame, text=\\\"5\\\", fg=\\\"black\\\", width=3, font=(\\\"微软雅黑\\\", 20)))\\n self.button_list[1].append(tkinter.Button(self.button_frame, text=\\\"6\\\", fg=\\\"black\\\", width=3, font=(\\\"微软雅黑\\\", 20)))\\n self.button_list[1].append(tkinter.Button(self.button_frame, text=\\\"-\\\", fg=\\\"black\\\", width=3, font=(\\\"微软雅黑\\\", 20)))\\n \\n self.button_list[2].append(tkinter.Button(self.button_frame, text=\\\"7\\\", fg=\\\"black\\\", width=3, font=(\\\"微软雅黑\\\", 20)))\\n self.button_list[2].append(tkinter.Button(self.button_frame, text=\\\"8\\\", fg=\\\"black\\\", width=3, font=(\\\"微软雅黑\\\", 20)))\\n self.button_list[2].append(tkinter.Button(self.button_frame, text=\\\"9\\\", fg=\\\"black\\\", width=3, font=(\\\"微软雅黑\\\", 20)))\\n self.button_list[2].append(tkinter.Button(self.button_frame, text=\\\"*\\\", fg=\\\"black\\\", width=3, font=(\\\"微软雅黑\\\", 20)))\\n\\n self.button_list[3].append(tkinter.Button(self.button_frame, text=\\\".\\\", fg=\\\"black\\\", width=3, font=(\\\"微软雅黑\\\", 20)))\\n self.button_list[3].append(tkinter.Button(self.button_frame, text=\\\"0\\\", fg=\\\"black\\\", width=3, font=(\\\"微软雅黑\\\", 20)))\\n self.button_list[3].append(tkinter.Button(self.button_frame, text=\\\"=\\\", fg=\\\"black\\\", width=3, font=(\\\"微软雅黑\\\", 20)))\\n self.button_list[3].append(tkinter.Button(self.button_frame, text=\\\"/\\\", fg=\\\"black\\\", width=3, font=(\\\"微软雅黑\\\", 20)))\\n \\n self.row = 0 # 进行行数的控制\\n for group in self.button_list:\\n self.column = 0 # 进行列的控制\\n for button in group:\\n button.bind(\\\"\\\", lambda event: self.button_handle(event)) # 绑定事件\\n button.grid(row=self.row, column=self.column)\\n self.column += 1 # 每次列+1\\n self.row += 1\\n \\n self.button_frame.pack(side=\\\"bottom\\\")\\n\\n def button_handle(self, event):\\n oper = event.widget[\\\"text\\\"] # 获取组件中的文本\\n if self.clean: # 第二次计算\\n self.content.set(\\\"\\\") # 清除标记中的数据\\n self.clean = False # 留给下一次计算输入\\n if oper != \\\"=\\\": # 意味着计算\\n self.entry.insert(\\\"end\\\", oper)\\n elif oper == \\\"=\\\": # 执行运算\\n result = 0 # 保存程序的计算结果\\n exp = self.entry.get()\\n result = eval(exp)\\n self.entry.insert(\\\"end\\\", \\\"=%s\\\" % result) \\n self.clean = True\\n\\ndef main(): # 主函数 \\n MainForm() # 实例化窗体类\\n\\nif __name__ == \\\"__main__\\\":\\n main()\\n\"\n },\n {\n \"alpha_fraction\": 0.49096208810806274,\n \"alphanum_fraction\": 0.559183657169342,\n \"avg_line_length\": 34,\n \"blob_id\": \"59d7fd92afbcea116c691d2dcfef095dc2b9dad0\",\n \"content_id\": \"255e81daf5c242b1030a945bda8fc44887078ffc\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1847,\n \"license_type\": \"no_license\",\n \"max_line_length\": 194,\n \"num_lines\": 49,\n \"path\": \"/1.spider_maoyan/spider_board.py\",\n \"repo_name\": \"LJJ-CDD/Python_work\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from urllib import request,parse\\nimport random\\nimport time\\n\\nclass MaoYanSpider(object):\\n ''' 爬取网页 '''\\n def __init__(self, root):\\n self.url=\\\"https://maoyan.com/board/4?offset={}\\\"\\n self.ua_list = [\\n 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_11_6) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/77.0.3865.120 Safari/537.36',\\n 'Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/535.1 (KHTML, like Gecko) Chrome/14.0.835.163 Safari/535.1',\\n 'Mozilla/5.0 (Windows NT 6.1; WOW64; rv:6.0) Gecko/20100101 Firefox/6.0',\\n 'Mozilla/4.0 (compatible; MSIE 8.0; Windows NT 6.1; WOW64; Trident/4.0; SLCC2; .NET CLR 2.0.50727; .NET CLR 3.5.30729; .NET CLR 3.0.30729; Media Center PC 6.0; .NET4.0C; InfoPath.3)'\\n ]\\n #用于记录页数\\n self.page = 1\\n self.root = root\\n\\n '''发送请求函数'''\\n def get_page(self,url):\\n #定义一个headers\\n headers={\\n 'User-Agent':random.choice(self.ua_list),\\n }\\n #构造请求头\\n req=request.Request(url=url,headers=headers)\\n res=request.urlopen(req)\\n html=res.read().decode(\\\"utf-8\\\")\\n # 将获取的html写到本地\\n self.parse_page(html)\\n\\n '''定义一个函数写到本地'''\\n def parse_page(self,html):\\n filename = self.root + '/第{}页.html'.format(self.page)\\n print(filename)\\n with open(filename,'w+',encoding='utf-8') as f:\\n f.write(html)\\n\\n '''主函数'''\\n def main(self):\\n '''拼接url地址'''\\n for offset in range(0,60,10):\\n url=self.url.format(offset)\\n print(url)\\n #发送请求 获取响应\\n self.get_page(url)\\n time.sleep(random.randint(5,8))\\n print(\\\"第%d页爬取完成\\\"%self.page)\\n self.page+=1\\n\"\n },\n {\n \"alpha_fraction\": 0.5963488817214966,\n \"alphanum_fraction\": 0.5983772873878479,\n \"avg_line_length\": 21.454545974731445,\n \"blob_id\": \"da19e47dcb432ee7d78c28d8e2fac4485f70e7de\",\n \"content_id\": \"7420e5a49153bffb664e80d2feba0010149ccfa6\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 521,\n \"license_type\": \"no_license\",\n \"max_line_length\": 41,\n \"num_lines\": 22,\n \"path\": \"/2.JSON_analysis/main.py\",\n \"repo_name\": \"LJJ-CDD/Python_work\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import os\\nimport time\\nfrom analysis import JXSpider #解析\\nfrom spider_board import TXSpider # 爬取网页\\n\\ndef judge_os():\\n root = os.getcwd()\\n root = root + '/招聘信息'\\n root = root.replace(os.sep, '/')\\n if(not os.path.exists(root)):\\n os.mkdir(root) \\n return root\\n\\nif __name__ == '__main__':\\n root = judge_os()\\n start=time.time()\\n spider=TXSpider(root)\\n spider.main()\\n spider=JXSpider(root)\\n spider.main()\\n end=time.time()\\n print('执行时间%.2f'%(end-start))\"\n },\n {\n \"alpha_fraction\": 0.4467253088951111,\n \"alphanum_fraction\": 0.45698925852775574,\n \"avg_line_length\": 36.21818161010742,\n \"blob_id\": \"8e806fe5b3ea78c3fff3c581210d482969823755\",\n \"content_id\": \"1bfe2ea47882b00484c00b584b6063f437ddcfd4\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 2174,\n \"license_type\": \"no_license\",\n \"max_line_length\": 110,\n \"num_lines\": 55,\n \"path\": \"/1.spider_maoyan/analysis.py\",\n \"repo_name\": \"LJJ-CDD/Python_work\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from urllib import request\\nimport requests\\nimport re\\nimport csv\\nimport os\\n\\nclass JieXiBangDanSpider(object):\\n ''' 解析榜单 '''\\n def __init__(self, root):\\n self.root = root\\n\\n def parse_page(self, html):\\n ''' 正则匹配 '''\\n pattern = re.compile('.*?.*?' # 图片\\n '
.*?class=\\\"name\\\">.*?' # 电影名称\\n '(.*?).*?' #主演\\n 'class=\\\"releasetime\\\">(.*?).*?' # 上映时间\\n 'class=\\\"score\\\">.*?(.*?).*?(.*?)' # 评分\\n , re.S) \\n r_list = pattern.findall(html)\\n self.write_page(r_list)\\n\\n def write_page(self, r_list):\\n ''' 写入csv '''\\n filename = self.root + '/maoyan.csv'\\n film_list = []\\n with open(filename, 'a', encoding='utf-8') as f:\\n writer = csv.writer(f)\\n for rt in r_list:\\n one_film = [\\n rt[1].strip(), rt[2].strip()[5:15],rt[3].strip()[5:],rt[4].strip()+rt[5].strip(),rt[0]\\n ]\\n film_list.append(one_film)\\n self.download_image(rt[0], rt[1]) # 下载图片\\n writer.writerows(film_list)\\n \\n def save_image(self, content, name):\\n ''' 下载图片 '''\\n file_path = '{0}/{1}.{2}'.format(self.root, name, 'jpg')#注意斜杠是/\\n if not os.path.exists(file_path):#os.path.exists(file_path)判断文件是否存在，存在返回1，不存在返回0\\n with open(file_path, 'wb') as f:\\n f.write(content)\\n f.close()\\n\\n def download_image(self, url, name):#保存图片链接\\n r = requests.get(url)\\n r.raise_for_status()\\n self.save_image(r.content, name)\\n\\n def main(self):\\n for i in range(1,6):\\n filename = self.root + '/第{}页.html'.format(i)\\n f=open(filename,'r',encoding='utf-8')\\n html=f.read()\\n self.parse_page(html)\"\n },\n {\n \"alpha_fraction\": 0.5727580189704895,\n \"alphanum_fraction\": 0.5922166109085083,\n \"avg_line_length\": 32.79999923706055,\n \"blob_id\": \"5ca47b024bb52afcfba767b2148fd1e4bc009983\",\n \"content_id\": \"1d7427e815a9a6e7ac092575ac615d6950e18b48\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1224,\n \"license_type\": \"no_license\",\n \"max_line_length\": 168,\n \"num_lines\": 35,\n \"path\": \"/2.JSON_analysis/spider_board.py\",\n \"repo_name\": \"LJJ-CDD/Python_work\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from fake_useragent import UserAgent\\nimport requests\\nimport time\\nimport random\\nclass TXSpider(object):\\n '''爬取和写入到本地json'''\\n def __init__(self,root):\\n self.url='https://careers.tencent.com/tencentcareer/api/post/Query?timestamp=1619657326691&countryId=&cityId=&bgIds=&productId=&categoryId=&parentCategoryId=' \\\\\\n '&attrId=&keyword=&pageIndex={}&pageSize=10&language=zh-cn&area=cn'\\n self.headers={\\n 'user-agent':UserAgent().random\\n }\\n self.page=1\\n self.root = root\\n\\n def get_page(self,url):\\n res=requests.get(url=url,headers=self.headers)\\n html=res.content.decode('utf-8')\\n return html\\n\\n def write_page(self,html):\\n '''将json写到本地'''\\n filename = self.root + '/第{}页.json'.format(self.page)\\n print(filename)\\n with open(filename,'w+',encoding='utf-8') as f:\\n f.write(html)\\n\\n def main(self):\\n for page in range(1,6):\\n url=self.url.format(page)\\n html=self.get_page(url)\\n self.write_page(html)\\n time.sleep(random.randint(3,5))\\n print(\\\"第{}页爬取成功\\\".format(self.page))\\n self.page+=1\"\n },\n {\n \"alpha_fraction\": 0.6177605986595154,\n \"alphanum_fraction\": 0.6196911334991455,\n \"avg_line_length\": 22.545454025268555,\n \"blob_id\": \"7c84141679b1ce7d9b9ce8befdcdce8fe5d073b0\",\n \"content_id\": \"9f4e84dfccbf7f83a15af0b8a35d955d56fd0fdc\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 542,\n \"license_type\": \"no_license\",\n \"max_line_length\": 47,\n \"num_lines\": 22,\n \"path\": \"/1.spider_maoyan/main.py\",\n \"repo_name\": \"LJJ-CDD/Python_work\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import os\\nimport time\\nfrom analysis import JieXiBangDanSpider\\nfrom spider_board import MaoYanSpider # 爬取榜单网页\\n\\ndef judge_os():\\n root = os.getcwd()\\n root = root + '/榜单'\\n root = root.replace(os.sep, '/')\\n if(not os.path.exists(root)):\\n os.mkdir(root) \\n return root\\n\\nif __name__ == '__main__':\\n root = judge_os()\\n start=time.time()\\n #spider=MaoYanSpider(root)\\n #spider.main()\\n spider=JieXiBangDanSpider(root)\\n spider.main()\\n end=time.time()\\n print('执行时间%.2f'%(end-start))\\n\"\n },\n {\n \"alpha_fraction\": 0.5414551496505737,\n \"alphanum_fraction\": 0.5448392629623413,\n \"avg_line_length\": 32.79999923706055,\n \"blob_id\": \"d3567ce844c22a0dbcf2250ea1599043b95cc33e\",\n \"content_id\": \"306da3ca37c259090babd41b5b0e9983570be00b\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1226,\n \"license_type\": \"no_license\",\n \"max_line_length\": 104,\n \"num_lines\": 35,\n \"path\": \"/2.JSON_analysis/analysis.py\",\n \"repo_name\": \"LJJ-CDD/Python_work\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import json\\nimport csv\\n\\nclass JXSpider(object):\\n '''将本地json转换为CSV'''\\n def __init__(self, root):\\n self.root = root\\n\\n def parse_page(self,json_str):\\n '''将json字符串转成python字符串'''\\n python_dict=json.loads(json_str)\\n python_list=python_dict['Data']['Posts']\\n for car in python_list:\\n career_dict={}\\n career_dict['RecruitPostName']=car['RecruitPostName']\\n career_dict['LocationName']=car['LocationName']\\n career_dict['Responsibility']= car['Responsibility'].replace('\\\\n','').replace('\\\\r','') # 格式化\\n self.write_page(career_dict)\\n\\n def write_page(self, career_dict):\\n ''' 写入csv '''\\n filename = self.root + '/TX.csv'\\n film_list = []\\n with open(filename, 'a', encoding='utf-8') as f: \\n writer = csv.writer(f)\\n for K,V in career_dict.items():\\n film_list.append(V)\\n writer.writerow(film_list)\\n\\n def main(self):\\n for i in range(1,6):\\n filename = self.root + '/第{}页.json'.format(i)\\n f=open(filename,'r',encoding='utf-8')\\n json_str=f.read()\\n self.parse_page(json_str)\"\n },\n {\n \"alpha_fraction\": 0.5891246795654297,\n \"alphanum_fraction\": 0.6010609865188599,\n \"avg_line_length\": 35.25,\n \"blob_id\": \"8627baa98307d8bfb8a22ed0e028c0b373f01a71\",\n \"content_id\": \"40ba2b1cc945036da9e973561946eb9d8a77a9dd\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 4414,\n \"license_type\": \"no_license\",\n \"max_line_length\": 106,\n \"num_lines\": 104,\n \"path\": \"/3.RSA_work/main_test.py\",\n \"repo_name\": \"LJJ-CDD/Python_work\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from logging import root\\nimport tkinter # 窗体相关\\nimport tkinter.messagebox # 实现提示框的组件\\nimport tkinter.simpledialog # 对话框\\nimport os # 路径\\nimport sys # 操作系统交互\\nimport re # 正则\\n\\nimport rsa_test\\n\\ndef get_resource_path(relative_path): # 利用此函数实现资源路径的定位\\n if getattr(sys, \\\"frozen\\\", False):\\n base_path = sys._MEIPASS # 获取临时资源\\n else:\\n base_path = os.path.abspath(\\\".\\\") # 获取当前路径\\n return os.path.join(base_path, relative_path) # 绝对路径\\n\\nLOGO_PATH = get_resource_path(os.path.join(\\\"Python_work\\\\\\\\3.RSA_work\\\\\\\\resources\\\", \\\"RSA.ico\\\")) # 图标文件路径\\nIMAGES_PATH = get_resource_path(os.path.join(\\\"Python_work\\\\\\\\3.RSA_work\\\\\\\\resources\\\", \\\"Rsa_Icon.png\\\")) # 图片路径\\nEMAIL_PATTERN = r\\\"[a-zA-Z0-9]\\\\w+@\\\\w+\\\\.(cn|com|com.cn|gov|net)\\\" # 正则表达式\\n#LOGO_PATH = get_resource_path(os.path.join(\\\"resources\\\", \\\"RSA.ico\\\")) # 图标文件路径\\n#IMAGES_PATH = get_resource_path(os.path.join(\\\"resources\\\", \\\"Rsa_Icon.png\\\")) # 图片路径\\n\\nimport tkinter # 导入相关的窗体模块\\nclass MainForm: # 定义窗体类\\n def __init__(self):\\n self.root = tkinter.Tk() # 创建一个窗体\\n self.root.title(\\\"Liu_RsaText\\\") # 设置标题\\n self.root.iconbitmap() # 设置logo的资源\\n self.root.geometry(\\\"500x300\\\") # 设置初始化尺寸\\n self.root.maxsize(1000, 400) # 设置窗体的最大尺寸\\n self.root[\\\"background\\\"] = \\\"LightSlateGray\\\" # 背景色\\n\\n self.photo = tkinter.PhotoImage(file=IMAGES_PATH) # 定义图片组件\\n self.content = tkinter.StringVar() # 修改标签文字\\n self.root.protocol(\\\"WM_DELETE_WINDOW\\\", self.close_handle) # 窗体关闭事件\\n\\n ''' 组件 '''\\n #self.label_photo()\\n #self.TK_text()\\n #self.label_text()\\n self.TK_button()\\n\\n self.root.mainloop() # 显示窗体\\n\\n def label_text(self):\\n # 进行文本标签定义\\n Lambda_text = tkinter.Label(self.root, textvariable=self.content, width=200, height=200, \\n bg=\\\"#223011\\\", fg=\\\"#ffffff\\\",font=(\\\"微软雅黑\\\", 10), justify=\\\"right\\\")\\n Lambda_text.pack() # 组件显示\\n\\n def label_photo(self):\\n # 进行文本图片标签定义\\n Label_photo = tkinter.Label(self.root, image=self.photo) # 图片标签\\n Label_photo.pack() # 标签显示 \\n\\n def TK_text(self):\\n # 定义文本组件窗口\\n text = tkinter.Text(self.root, width=50, height=10, font=(\\\"微软雅黑\\\", 10))\\n #text.image_create(\\\"end\\\", image=self.photo)\\n text.insert(\\\"current\\\", \\\"请输入正确的Email信息....\\\") # 默认提示信息\\n text.bind(\\\"\\\", lambda event :\\n self.event_handle_text(event, text, \\\" \\\"))\\n text.bind(\\\"\\\",lambda even: \\n self.event_handle_keyboard(even, text))\\n text.bind(\\\"\\\",lambda even: \\n self.event_handle_keyboard(even, text))\\n text.pack() # 显示文本组件\\n\\n def TK_button(self):\\n # 定义按钮组件\\n button = tkinter.Button(self.root, text=\\\"Liu\\\" , image=self.photo,\\n compound=\\\"bottom\\\", fg=\\\"black\\\", font=(\\\"微软雅黑\\\", 10)) # 图片文本混合按钮\\n button.bind(\\\"\\\", lambda event :\\n self.event_handle(event, \\\"Hello World\\\")) # 事件\\n button.pack()\\n\\n def event_handle(self, event, info):\\n # 消息框事件\\n input_message = tkinter.simpledialog.askstring(\\\"提示信息\\\", \\\"请输入要显示的信息: \\\")\\n self.label_text()\\n tkinter.messagebox.showinfo(title=\\\"Liu消息提示\\\", message=input_message)\\n \\n def event_handle_text(self, event, text, info):\\n # 文本删除事件\\n text.delete(\\\"0.0\\\", \\\"end\\\")\\n\\n def event_handle_keyboard(self, event, text):\\n # 获得文本框信息输入事件\\n email = text.get(\\\"0.0\\\", \\\"end\\\")\\n if re.match(EMAIL_PATTERN, email, re.I | re.X):\\n self.content.set(\\\"Email邮箱输入正确，内容为: %s\\\" % email)\\n else:\\n self.content.set(\\\"Email数据输入错误!\\\")\\n\\n def close_handle(self):\\n if tkinter.messagebox.askyesnocancel(\\\"程序关闭确认！\\\", \\\"是否确认关闭程序？\\\"):\\n self.root.destroy() # 关闭程序\\n \\ndef main(): # 主函数 \\n MainForm() # 实例化窗体类\\n\\nif __name__ == \\\"__main__\\\":\\n main()\\n\"\n }\n]"},"num_files":{"kind":"number","value":10,"string":"10"}}},{"rowIdx":2027,"cells":{"repo_name":{"kind":"string","value":"rikenshah/Well-thy"},"repo_url":{"kind":"string","value":"https://github.com/rikenshah/Well-thy"},"snapshot_id":{"kind":"string","value":"80536111c41c69eff4730db00782912bcee930c8"},"revision_id":{"kind":"string","value":"20462a880313f839147795bb414da4927424e126"},"directory_id":{"kind":"string","value":"d8a2a85398ece4ed192deee4616fc9f500df59c5"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"string","value":"2022-12-10T09:13:26.372684"},"revision_date":{"kind":"string","value":"2019-10-21T20:28:27"},"committer_date":{"kind":"string","value":"2019-10-21T20:28:47"},"github_id":{"kind":"number","value":125094461,"string":"125,094,461"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"string","value":"MIT"},"gha_created_at":{"kind":"string","value":"2018-03-13T18:08:29"},"gha_updated_at":{"kind":"string","value":"2019-10-21T20:28:49"},"gha_pushed_at":{"kind":"string","value":"2022-12-07T23:50:28"},"gha_language":{"kind":"string","value":"Python"},"files":{"kind":"list like","value":[{"alpha_fraction":0.7058823704719543,"alphanum_fraction":0.7058823704719543,"avg_line_length":16,"blob_id":"1f0d7178c1302cd49ad3f7e2a3af3e1eecc42249","content_id":"9db719110b79436214e1918571b0f2833261b807","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":85,"license_type":"permissive","max_line_length":35,"num_lines":5,"path":"/pyScripts/analysis.py","repo_name":"rikenshah/Well-thy","src_encoding":"UTF-8","text":"import pandas as pd\n\ndatapath = \"../datasets/merged.csv\"\n\ndf = pd.read_csv(datapath)\n"},{"alpha_fraction":0.6770293712615967,"alphanum_fraction":0.7081174254417419,"avg_line_length":30.581817626953125,"blob_id":"5fb9bc817afb3dfd1081945de96c61e17e31689f","content_id":"30efff522f35abaaad20dcab3b84b5944f892ff4","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1737,"license_type":"permissive","max_line_length":131,"num_lines":55,"path":"/pyScripts/gov.py","repo_name":"rikenshah/Well-thy","src_encoding":"UTF-8","text":"# This is a magic script that transforms two datasets into one smartly by comparison of resonse parameters\n\nimport pandas as pd\n\ndatapath = \"../datasets/healthcaregov/data.csv\"\ndatapath2 = \"../datasets/prudentialLifeInsurance/train.csv\"\nsavepath1 = \"../datasets/merged1.csv\"\n\ndf = pd.read_csv(datapath)\n\ndf2 = df[df[\"Individual Tobacco Rate\"].notnull()]\n\nindividual_rate = df2[\"Individual Rate\"]\n# normalized_individual_rate = ((individual_rate-individual_rate.mean())/individual_rate.std())*4+4\n# normalized_individual_rate = (individual_rate-individual_rate.min())/(individual_rate.max()-individual_rate.min())\n\nindividual_tobacco_rate = df2[\"Individual Tobacco Rate\"]\n# normalized_individual_tobacco_rate = ((individual_tobacco_rate-individual_tobacco_rate.mean())/individual_tobacco_rate.std())*4+4\n\n# here multiplying by 8 does not give a good range\nrate_diff = (individual_tobacco_rate-individual_rate)*16/individual_rate\ndf2[\"rate_diff\"] = pd.Series(rate_diff)\n\nresponse = 1\n\nmapping_dict = {}\n\ndef init_map(df2,i):\n\tif i == 0:\n\t\tmapping_dict[0] = df2.loc[(df2.rate_diff < 0.5)].iterrows()\n\telif i == 1:\n\t\tmapping_dict[1] = df2.loc[(df2.rate_diff < 1) & (df2.rate_diff >0.5)].iterrows()\n\telif i in range(2,8):\n\t\tmapping_dict[i] = df2.loc[(df2.rate_diff < i) & (df2.rate_diff >(i-1))].iterrows()\n\telif i == 8:\n\t\tmapping_dict[8] = df2.loc[(df2.rate_diff >7)].iterrows()\n\telse:\n\t\treturn\n\nfor i in range(9):\n\tinit_map(df2,i)\n\n## Loading second dataset\ndf3 = pd.read_csv(datapath2)\ndf3 = df3[df3.Response.notnull()]\n\nfor i, row in df3.iterrows():\n\ttry:\n\t\tnew_tuple = next(mapping_dict[row.Response])\n\texcept:\n\t\tinit_map(df2,row.Response)\n\tfor key,value in new_tuple[1].iteritems():\n\t\tdf3.set_value(i,key,value)\n\ndf3.to_csv(savepath1)\n"},{"alpha_fraction":0.4479283392429352,"alphanum_fraction":0.4616461396217346,"avg_line_length":27.12598419189453,"blob_id":"717887825ed0b266b29b04471b581d799fc52da5","content_id":"2b374e42f0f6adc1a0dacc3b3d42a1db74bced54","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"HTML","length_bytes":3572,"license_type":"permissive","max_line_length":86,"num_lines":127,"path":"/templates/health/profile.html","repo_name":"rikenshah/Well-thy","src_encoding":"UTF-8","text":"\n{% extends 'base.html' %}\n\n{% block content %}\n\t', login_required(views.HealthProfileUpdate.as_view(template_name=\"health/form.html\")), name='health_update')\n]"}],"string":"[\n {\n \"alpha_fraction\": 0.7058823704719543,\n \"alphanum_fraction\": 0.7058823704719543,\n \"avg_line_length\": 16,\n \"blob_id\": \"1f0d7178c1302cd49ad3f7e2a3af3e1eecc42249\",\n \"content_id\": \"9db719110b79436214e1918571b0f2833261b807\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 85,\n \"license_type\": \"permissive\",\n \"max_line_length\": 35,\n \"num_lines\": 5,\n \"path\": \"/pyScripts/analysis.py\",\n \"repo_name\": \"rikenshah/Well-thy\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import pandas as pd\\n\\ndatapath = \\\"../datasets/merged.csv\\\"\\n\\ndf = pd.read_csv(datapath)\\n\"\n },\n {\n \"alpha_fraction\": 0.6770293712615967,\n \"alphanum_fraction\": 0.7081174254417419,\n \"avg_line_length\": 30.581817626953125,\n \"blob_id\": \"5fb9bc817afb3dfd1081945de96c61e17e31689f\",\n \"content_id\": \"30efff522f35abaaad20dcab3b84b5944f892ff4\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1737,\n \"license_type\": \"permissive\",\n \"max_line_length\": 131,\n \"num_lines\": 55,\n \"path\": \"/pyScripts/gov.py\",\n \"repo_name\": \"rikenshah/Well-thy\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# This is a magic script that transforms two datasets into one smartly by comparison of resonse parameters\\n\\nimport pandas as pd\\n\\ndatapath = \\\"../datasets/healthcaregov/data.csv\\\"\\ndatapath2 = \\\"../datasets/prudentialLifeInsurance/train.csv\\\"\\nsavepath1 = \\\"../datasets/merged1.csv\\\"\\n\\ndf = pd.read_csv(datapath)\\n\\ndf2 = df[df[\\\"Individual Tobacco Rate\\\"].notnull()]\\n\\nindividual_rate = df2[\\\"Individual Rate\\\"]\\n# normalized_individual_rate = ((individual_rate-individual_rate.mean())/individual_rate.std())*4+4\\n# normalized_individual_rate = (individual_rate-individual_rate.min())/(individual_rate.max()-individual_rate.min())\\n\\nindividual_tobacco_rate = df2[\\\"Individual Tobacco Rate\\\"]\\n# normalized_individual_tobacco_rate = ((individual_tobacco_rate-individual_tobacco_rate.mean())/individual_tobacco_rate.std())*4+4\\n\\n# here multiplying by 8 does not give a good range\\nrate_diff = (individual_tobacco_rate-individual_rate)*16/individual_rate\\ndf2[\\\"rate_diff\\\"] = pd.Series(rate_diff)\\n\\nresponse = 1\\n\\nmapping_dict = {}\\n\\ndef init_map(df2,i):\\n\\tif i == 0:\\n\\t\\tmapping_dict[0] = df2.loc[(df2.rate_diff < 0.5)].iterrows()\\n\\telif i == 1:\\n\\t\\tmapping_dict[1] = df2.loc[(df2.rate_diff < 1) & (df2.rate_diff >0.5)].iterrows()\\n\\telif i in range(2,8):\\n\\t\\tmapping_dict[i] = df2.loc[(df2.rate_diff < i) & (df2.rate_diff >(i-1))].iterrows()\\n\\telif i == 8:\\n\\t\\tmapping_dict[8] = df2.loc[(df2.rate_diff >7)].iterrows()\\n\\telse:\\n\\t\\treturn\\n\\nfor i in range(9):\\n\\tinit_map(df2,i)\\n\\n## Loading second dataset\\ndf3 = pd.read_csv(datapath2)\\ndf3 = df3[df3.Response.notnull()]\\n\\nfor i, row in df3.iterrows():\\n\\ttry:\\n\\t\\tnew_tuple = next(mapping_dict[row.Response])\\n\\texcept:\\n\\t\\tinit_map(df2,row.Response)\\n\\tfor key,value in new_tuple[1].iteritems():\\n\\t\\tdf3.set_value(i,key,value)\\n\\ndf3.to_csv(savepath1)\\n\"\n },\n {\n \"alpha_fraction\": 0.4479283392429352,\n \"alphanum_fraction\": 0.4616461396217346,\n \"avg_line_length\": 27.12598419189453,\n \"blob_id\": \"717887825ed0b266b29b04471b581d799fc52da5\",\n \"content_id\": \"2b374e42f0f6adc1a0dacc3b3d42a1db74bced54\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"HTML\",\n \"length_bytes\": 3572,\n \"license_type\": \"permissive\",\n \"max_line_length\": 86,\n \"num_lines\": 127,\n \"path\": \"/templates/health/profile.html\",\n \"repo_name\": \"rikenshah/Well-thy\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"\\n{% extends 'base.html' %}\\n\\n{% block content %}\\n\\t', login_required(views.HealthProfileUpdate.as_view(template_name=\\\"health/form.html\\\")), name='health_update')\\n]\"\n }\n]"},"num_files":{"kind":"number","value":18,"string":"18"}}},{"rowIdx":2028,"cells":{"repo_name":{"kind":"string","value":"haikaroseworx/dsworks"},"repo_url":{"kind":"string","value":"https://github.com/haikaroseworx/dsworks"},"snapshot_id":{"kind":"string","value":"7bc13a9b6acf0c8f9742ba96951afc558e483d42"},"revision_id":{"kind":"string","value":"f7c142c5222ca075a8e7080b6f3b39768fa3d02b"},"directory_id":{"kind":"string","value":"c6144a072f3f662f06ef36971df56511ac6243db"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"string","value":"2021-09-05T20:54:58.765384"},"revision_date":{"kind":"string","value":"2018-01-31T00:09:16"},"committer_date":{"kind":"string","value":"2018-01-31T00:09:16"},"github_id":{"kind":"number","value":119610786,"string":"119,610,786"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.5752895474433899,"alphanum_fraction":0.5830115675926208,"avg_line_length":24.899999618530273,"blob_id":"fb46d3d3b78564424c718431febf64bd03d97b2e","content_id":"1d702263a552c3e3bff66312118d85958bf2ffde","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":259,"license_type":"no_license","max_line_length":56,"num_lines":10,"path":"/camera_project.py","repo_name":"haikaroseworx/dsworks","src_encoding":"UTF-8","text":"import sys\n\n\n## GET THE INPUT CONCERN CAMERA AND IMAGES ##\ncamera_no = sys.argv[1]\nimage_shots = sys.argv[2]\n############################################\n\nprint(\"Camera to use is camera : \" +camera_no)\nprint(\"Total number of images to capture: \"+image_shots)\n"},{"alpha_fraction":0.6291390657424927,"alphanum_fraction":0.6490066051483154,"avg_line_length":20.571428298950195,"blob_id":"c2b762eebb9e62fad8201b3b29abf79975509e9d","content_id":"8612763c6ab94786b8555d96252cb8b9f54714a0","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":604,"license_type":"no_license","max_line_length":50,"num_lines":28,"path":"/sedoyeka project/campy2.py","repo_name":"haikaroseworx/dsworks","src_encoding":"UTF-8","text":"import numpy as np\nimport cv2\n\ncap = cv2.VideoCapture(0)\n\nwhile(True):\n # Capture frame-by-frame\n ret, frame = cap.read()\n\n # Our operations on the frame come here\n gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)\n\n # Display the resulting frame\n cv2.imshow('Camera desktop recorder',gray)\n\n ##this bullshit bellow is mine##\n camera = cap.read()\n cv2.imwrite('test.png', cap.read())\n del camera \n break\n ##end of my bullshit##\n\n if cv2.waitKey(1) & 0xFF == ord('q'):\n break\n\n# When everything done, release the capture\ncap.release()\ncv2.destroyAllWindows()\n"},{"alpha_fraction":0.6666666865348816,"alphanum_fraction":0.6691176295280457,"avg_line_length":20.473684310913086,"blob_id":"cc1671c459c62eb1b1019099218ca2dd833ba444","content_id":"b08a20adc010f3d7b4af886587f0663a709c7395","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":408,"license_type":"no_license","max_line_length":63,"num_lines":19,"path":"/flask_serve/camera_server.py","repo_name":"haikaroseworx/dsworks","src_encoding":"UTF-8","text":"from flask import Flask\nfrom flask import request\nimport sys\nimport os\n\n\napp = Flask(__name__)\n\n@app.route(\"/signal\")\ndef signal():\n camera = request.args.get(\"camera\")\n shots = request.args.get(\"shots\")\n\n sysparams = \"python3 camera_util.py \"+camera+\" \"+str(shots)\n os.system(sysparams)\n\n return \"proximity sensor signal received \"+sysparams\n\nif __name__ ==\"__main__\": app.run(debug = False)\n"},{"alpha_fraction":0.6491228342056274,"alphanum_fraction":0.7017543911933899,"avg_line_length":26,"blob_id":"efea71dc6313be753e76f8b243d2cc87a98ca5fb","content_id":"081474fbfd9de924546e13f4b727152d353e3290","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":57,"license_type":"no_license","max_line_length":42,"num_lines":2,"path":"/runner.py","repo_name":"haikaroseworx/dsworks","src_encoding":"UTF-8","text":"import os \nos.system('python camera_project.py 1 12')\n\n\n\n"},{"alpha_fraction":0.591549277305603,"alphanum_fraction":0.6291079521179199,"avg_line_length":20.299999237060547,"blob_id":"8fd5a31c69f7765c3f85c0e84147a9078c6993a3","content_id":"ba35303d7eb70fa78662fbcf633b66883caaf91f","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":213,"license_type":"no_license","max_line_length":46,"num_lines":10,"path":"/sedoyeka project/enter_capture.py","repo_name":"haikaroseworx/dsworks","src_encoding":"UTF-8","text":"import cv2\n\ncamera = cv2.VideoCapture(0)\ni = 0\nwhile i < 10:\n #raw_input('Press Enter to capture')\n return_value, image = camera.read()\n cv2.imwrite('opencv'+str(i)+'.png', image)\n i = i+1\ndel(camera)\n"}],"string":"[\n {\n \"alpha_fraction\": 0.5752895474433899,\n \"alphanum_fraction\": 0.5830115675926208,\n \"avg_line_length\": 24.899999618530273,\n \"blob_id\": \"fb46d3d3b78564424c718431febf64bd03d97b2e\",\n \"content_id\": \"1d702263a552c3e3bff66312118d85958bf2ffde\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 259,\n \"license_type\": \"no_license\",\n \"max_line_length\": 56,\n \"num_lines\": 10,\n \"path\": \"/camera_project.py\",\n \"repo_name\": \"haikaroseworx/dsworks\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\n\\n## GET THE INPUT CONCERN CAMERA AND IMAGES ##\\ncamera_no = sys.argv[1]\\nimage_shots = sys.argv[2]\\n############################################\\n\\nprint(\\\"Camera to use is camera : \\\" +camera_no)\\nprint(\\\"Total number of images to capture: \\\"+image_shots)\\n\"\n },\n {\n \"alpha_fraction\": 0.6291390657424927,\n \"alphanum_fraction\": 0.6490066051483154,\n \"avg_line_length\": 20.571428298950195,\n \"blob_id\": \"c2b762eebb9e62fad8201b3b29abf79975509e9d\",\n \"content_id\": \"8612763c6ab94786b8555d96252cb8b9f54714a0\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 604,\n \"license_type\": \"no_license\",\n \"max_line_length\": 50,\n \"num_lines\": 28,\n \"path\": \"/sedoyeka project/campy2.py\",\n \"repo_name\": \"haikaroseworx/dsworks\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import numpy as np\\nimport cv2\\n\\ncap = cv2.VideoCapture(0)\\n\\nwhile(True):\\n # Capture frame-by-frame\\n ret, frame = cap.read()\\n\\n # Our operations on the frame come here\\n gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)\\n\\n # Display the resulting frame\\n cv2.imshow('Camera desktop recorder',gray)\\n\\n ##this bullshit bellow is mine##\\n camera = cap.read()\\n cv2.imwrite('test.png', cap.read())\\n del camera \\n break\\n ##end of my bullshit##\\n\\n if cv2.waitKey(1) & 0xFF == ord('q'):\\n break\\n\\n# When everything done, release the capture\\ncap.release()\\ncv2.destroyAllWindows()\\n\"\n },\n {\n \"alpha_fraction\": 0.6666666865348816,\n \"alphanum_fraction\": 0.6691176295280457,\n \"avg_line_length\": 20.473684310913086,\n \"blob_id\": \"cc1671c459c62eb1b1019099218ca2dd833ba444\",\n \"content_id\": \"b08a20adc010f3d7b4af886587f0663a709c7395\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 408,\n \"license_type\": \"no_license\",\n \"max_line_length\": 63,\n \"num_lines\": 19,\n \"path\": \"/flask_serve/camera_server.py\",\n \"repo_name\": \"haikaroseworx/dsworks\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from flask import Flask\\nfrom flask import request\\nimport sys\\nimport os\\n\\n\\napp = Flask(__name__)\\n\\n@app.route(\\\"/signal\\\")\\ndef signal():\\n camera = request.args.get(\\\"camera\\\")\\n shots = request.args.get(\\\"shots\\\")\\n\\n sysparams = \\\"python3 camera_util.py \\\"+camera+\\\" \\\"+str(shots)\\n os.system(sysparams)\\n\\n return \\\"proximity sensor signal received \\\"+sysparams\\n\\nif __name__ ==\\\"__main__\\\": app.run(debug = False)\\n\"\n },\n {\n \"alpha_fraction\": 0.6491228342056274,\n \"alphanum_fraction\": 0.7017543911933899,\n \"avg_line_length\": 26,\n \"blob_id\": \"efea71dc6313be753e76f8b243d2cc87a98ca5fb\",\n \"content_id\": \"081474fbfd9de924546e13f4b727152d353e3290\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 57,\n \"license_type\": \"no_license\",\n \"max_line_length\": 42,\n \"num_lines\": 2,\n \"path\": \"/runner.py\",\n \"repo_name\": \"haikaroseworx/dsworks\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import os \\nos.system('python camera_project.py 1 12')\\n\\n\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.591549277305603,\n \"alphanum_fraction\": 0.6291079521179199,\n \"avg_line_length\": 20.299999237060547,\n \"blob_id\": \"8fd5a31c69f7765c3f85c0e84147a9078c6993a3\",\n \"content_id\": \"ba35303d7eb70fa78662fbcf633b66883caaf91f\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 213,\n \"license_type\": \"no_license\",\n \"max_line_length\": 46,\n \"num_lines\": 10,\n \"path\": \"/sedoyeka project/enter_capture.py\",\n \"repo_name\": \"haikaroseworx/dsworks\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import cv2\\n\\ncamera = cv2.VideoCapture(0)\\ni = 0\\nwhile i < 10:\\n #raw_input('Press Enter to capture')\\n return_value, image = camera.read()\\n cv2.imwrite('opencv'+str(i)+'.png', image)\\n i = i+1\\ndel(camera)\\n\"\n }\n]"},"num_files":{"kind":"number","value":5,"string":"5"}}},{"rowIdx":2029,"cells":{"repo_name":{"kind":"string","value":"yorkurt/pygame_controllers"},"repo_url":{"kind":"string","value":"https://github.com/yorkurt/pygame_controllers"},"snapshot_id":{"kind":"string","value":"8ad3e3a2fedd727377fa2ae9a3c90897da45a5dd"},"revision_id":{"kind":"string","value":"9cf9a67e15cf319efd504db20e8adeb7b41cb625"},"directory_id":{"kind":"string","value":"2563b823df882f8b9dd65c8d8c2814d6fb7ffb54"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"string","value":"2021-09-04T02:48:51.917479"},"revision_date":{"kind":"string","value":"2018-01-14T22:45:09"},"committer_date":{"kind":"string","value":"2018-01-14T22:45:09"},"github_id":{"kind":"number","value":110867165,"string":"110,867,165"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.8125,"alphanum_fraction":0.8125,"avg_line_length":35,"blob_id":"6425d8da6c05cb5631bd01fcdc8153d5965addae","content_id":"c046d11836767f0c163aabc6bff23c29be12ea43","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":144,"license_type":"no_license","max_line_length":80,"num_lines":4,"path":"/README.md","repo_name":"yorkurt/pygame_controllers","src_encoding":"UTF-8","text":"# pygame_controllers\nCrappy pygame code to run some joysticks\n\nIdeally this should work to control the rover. Full control schemes coming soon.\n"},{"alpha_fraction":0.48377305269241333,"alphanum_fraction":0.5155264735221863,"avg_line_length":29.382978439331055,"blob_id":"87ca61477d83fb56e738152464aff9b791582fe6","content_id":"6fb85b7728c8ff065a5eddd79f70bb1834c37042","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":4283,"license_type":"no_license","max_line_length":96,"num_lines":141,"path":"/joy.py","repo_name":"yorkurt/pygame_controllers","src_encoding":"UTF-8","text":"import math\nimport pygame\n\nimport helpers\n\nclass Joystick_L:\n\n def __init__(self):\n pygame.joystick.init()\n numJoys = pygame.joystick.get_count()\n self.joyInitL = False\n self.x = 0\n self.y = 0\n self.rad = 0\n self.throttle = 0\n if (numJoys > 0):\n self.joystick = pygame.joystick.Joystick(0)\n self.joystick.init()\n self.joyInitL = True\n else:\n print(\"No left joystick found\")\n self.joyInitL = False\n self.numButtons = 0\n return\n\n self.numButtons = self.joystick.get_numbuttons()\n self.buttons = [0]*self.numButtons\n \n \n pygame.font.init()\n self.font = pygame.font.Font(pygame.font.get_default_font(),32)\n\n def compute(self):\n self.x = self.joystick.get_axis(0)\n self.y = self.joystick.get_axis(1)\n self.throttle = ((-1 * self.joystick.get_axis(2)) + 1) / 2\n self.rad = math.hypot(self.x,self.y)\n self.rad = helpers.limitToRange(self.rad,0,1)\n self.ang = math.atan2(self.y,self.x)\n self.x = self.rad*math.cos(self.ang)\n self.y = self.rad*math.sin(self.ang)\n #'clicks' to middle\n tab = .12\n if -tab < self.x < tab:\n self.x = 0\n if -tab < self.y < tab:\n self.y = 0\n\n for i in xrange(self.numButtons):\n self.buttons[i] = self.joystick.get_button(i)\n\n \n\n \n ''' def draw(self,surface):\n r = 200\n w = surface.get_width()\n h = surface.get_height()\n\n for i in xrange(self.numButtons):\n if self.buttons[i]:\n col = (0,255,0)\n else:\n col = (64,0,64)\n text = self.font.render(str(i),1,col)\n surface.blit(text,text.get_rect(centerx=w*(i+1)/(self.numButtons+1),centery=h/2))\n \n x = int(round(w/2+self.x*r))\n y = int(round(h/2+self.y*r))\n pygame.draw.aaline(surface,(128,128,128),(w/2,h/2),(x,y),1)\n pygame.draw.circle(surface,(0,0,0),(x,y),8,4)\n pygame.draw.circle(surface,(0,255,255),(w/2,h/2),r,2) '''\n\nclass Joystick_R:\n\n def __init__(self):\n pygame.joystick.init()\n numJoys = pygame.joystick.get_count()\n self.joyInitR = False\n self.x = 0\n self.y = 0\n self.rad = 0\n self.throttle = 0\n if (numJoys > 1):\n self.joystick = pygame.joystick.Joystick(1)\n self.joystick.init()\n self.joyInitR = True\n else:\n print(\"No right joystick found\")\n self.joyInitR = False\n self.numButtons = 0\n return\n\n self.numButtons = self.joystick.get_numbuttons()\n self.buttons = [0]*self.numButtons\n \n \n pygame.font.init()\n self.font = pygame.font.Font(pygame.font.get_default_font(),32)\n\n def compute(self):\n self.x = self.joystick.get_axis(0)\n self.y = self.joystick.get_axis(1)\n self.throttle = ((-1 * self.joystick.get_axis(2)) + 1) / 2\n self.rad = math.hypot(self.x,self.y)\n self.rad = helpers.limitToRange(self.rad,0,1)\n self.ang = math.atan2(self.y,self.x)\n self.x = self.rad*math.cos(self.ang)\n self.y = self.rad*math.sin(self.ang)\n #'clicks' to middle\n tab = .12\n if -tab < self.x < tab:\n self.x = 0\n if -tab < self.y < tab:\n self.y = 0\n\n for i in xrange(self.numButtons):\n self.buttons[i] = self.joystick.get_button(i)\n\n \n\n \n ''' def draw(self,surface):\n r = 200\n w = surface.get_width()\n h = surface.get_height()\n\n for i in xrange(self.numButtons):\n if self.buttons[i]:\n col = (0,255,0)\n else:\n col = (64,0,64)\n \n text = self.font.render(str(i),1,col)\n surface.blit(text,text.get_rect(centerx=w*(i+1)/(self.numButtons+1),centery=h/2-60))\n \n x = int(round(w/2+self.x*r))\n y = int(round(h/2+self.y*r))\n pygame.draw.aaline(surface,(128,0,0),(w/2,h/2),(x,y),1)\n pygame.draw.circle(surface,(0,0,0),(x,y),8,4)\n pygame.draw.circle(surface,(0,255,255),(w/2,h/2),r,2) '''"},{"alpha_fraction":0.3854166567325592,"alphanum_fraction":0.3854166567325592,"avg_line_length":14.666666984558105,"blob_id":"0d8ee4068d1eae7ca84bb1fc90bc5d4d5926daaf","content_id":"52475857fc9b416159a5b17d4c0ab44a072410f1","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":96,"license_type":"no_license","max_line_length":24,"num_lines":6,"path":"/helpers.py","repo_name":"yorkurt/pygame_controllers","src_encoding":"UTF-8","text":"\n\ndef limitToRange(a,b,c):\n if a < b:\n a = b\n if a > c:\n a = c\n return a\n"},{"alpha_fraction":0.476492702960968,"alphanum_fraction":0.5159849524497986,"avg_line_length":29.826086044311523,"blob_id":"f6eaf19d1cc6a43597f61a0068a1af0bd060dc6e","content_id":"e2bd1618541a19ace6ae6d70fd527decda277afe","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":4254,"license_type":"no_license","max_line_length":139,"num_lines":138,"path":"/main.py","repo_name":"yorkurt/pygame_controllers","src_encoding":"UTF-8","text":"import math\nimport pygame\n\nimport joy\n\nclass Main:\n def __init__(self):\n self.SCREEN_WIDTH = 800\n self.SCREEN_HEIGHT = 450\n self.screen = pygame.display.set_mode((self.SCREEN_WIDTH,self.SCREEN_HEIGHT))\n\n self.objects = []\n self.mode = 1\n\n pygame.font.init()\n self.font = pygame.font.Font(pygame.font.get_default_font(),32)\n\n\t\n\t\n\n def setupGame(self):\n self.clock = pygame.time.Clock()\t\n self.FPS = 60\n self.joy = joy.Joystick_L()\n self.joy2 = joy.Joystick_R()\n\n self.objects.append(self.joy)\n self.objects.append(self.joy2)\n\n\tl = self.objects[0].get_numbuttons()\n\tself.buttonArr1 = [0 for i in range(l)]\n\n def runGame(self):\n self.gameRunning = 1\n\n\n while self.gameRunning:\n\t buttonArr1 = [0 for i in range(len(buttonArr1))]\n\n self.getInput()\n self.compute()\n self.draw(self.screen)\n self.clock.tick(self.FPS)\n \n #self.leftX = pygame.joystick.Joystick(0).get_axis(0)\n #self.leftY = -1 * pygame.joystick.Joystick(0).get_axis(1)\n #self.rightX = pygame.joystick.Joystick(1).get_axis(0)\n #self.rightY = -1 * pygame.joystick.Joystick(1).get_axis(1)\n\n self.leftX = self.objects[0].get_axis(0)\n\t self.leftY = self.objects[0].get_axis(1)\n\t #self.rightX = self.objects[1].get_axis(0)\n\t #self.rightY = self.objects[1].get_axis(1)\n\n #handle buttons \n for event in pygame.event.get(pygame.JOYBUTTONUP): #event handling loop\n #handle mode switching - buttons 8/9 on both sticks\n print(event)\n if (event.button == 7): #button 8 increases mode\n\t\t buttonArr1[7] = 1\n if (self.mode == 3):\n self.mode = 1\n else:\n self.mode = self.mode + 1\n print(\"Mode is now: \" + str(self.mode))\n if (event.button == 8): #button 9 decreases mode\n\t\t buttonArr1[8] = 1\n if (self.mode == 1):\n self.mode = 3\n else:\n self.mode = self.mode - 1\n print(\"Mode is now: \" + str(self.mode))\n\n\n def getInput(self):\n for event in pygame.event.get():\n if event.type == pygame.QUIT:\n self.gameRunning = 0\n\n #if(self.joy.joyInitL == True):\n pygame.display.set_caption(str(self.joy.x) + ', ' + str(self.joy.y) + ', ' + str(self.joy.rad) + ', ' + str(self.joy.throttle))\n\n def draw(self,surface):\n self.screen.fill((255,255,255))\n\n #for o in self.objects:\n # o.draw(self.screen)\n\n \n r = 200\n w = surface.get_width()\n h = surface.get_height()\n\n for i in xrange(self.joy.numButtons):\n if self.joy.buttons[i]:\n col = (0,255,0)\n else:\n col = (64,0,64)\n \n text = self.font.render(str(i),1,col)\n surface.blit(text,text.get_rect(centerx=w*(i+1)/(self.joy.numButtons+1),centery=h/2-30))\n\n x = int(round(w/2+self.joy.x*r))\n y = int(round(h/2+self.joy.y*r))\n pygame.draw.aaline(surface,(128,128,128),(w/2,h/2),(x,y),1)\n pygame.draw.circle(surface,(0,0,0),(x,y),8,4)\n #pygame.draw.circle(surface,(0,255,255),(w/2,h/2),r,2)\n\n for i in xrange(self.joy2.numButtons):\n if self.joy2.buttons[i]:\n col = (0,255,0)\n else:\n col = (64,0,64)\n \n text = self.font.render(str(i),1,col)\n surface.blit(text,text.get_rect(centerx=w*(i+1)/(self.joy2.numButtons+1),centery=h/2+30))\n \n x1 = int(round(w/2+self.joy2.x*r))\n y1 = int(round(h/2+self.joy2.y*r))\n pygame.draw.aaline(surface,(128,0,0),(w/2,h/2),(x1,y1),1)\n pygame.draw.circle(surface,(0,0,0),(x1,y1),8,4)\n pygame.draw.circle(surface,(0,255,255),(w/2,h/2),r,2)\n\n pygame.display.flip()\n\n def compute(self):\n i = 0\n while i < len(self.objects):\n self.objects[i].compute()\n i += 1\n\n\n\nm = Main()\nm.setupGame()\nm.runGame()\n\npygame.quit()\n"},{"alpha_fraction":0.6373276710510254,"alphanum_fraction":0.66171795129776,"avg_line_length":29.419355392456055,"blob_id":"6b74bc89f6bc7af5b1a183f189284355f71daa12","content_id":"fa7ac920e5ad41173676dc5b5350634761cca4d5","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":943,"license_type":"no_license","max_line_length":70,"num_lines":31,"path":"/talker.py","repo_name":"yorkurt/pygame_controllers","src_encoding":"UTF-8","text":"#!/usr/bin/env python\n\nimport rospy\nfrom std_msgs.msg import String#, Float64MultiArray\nfrom controller.msg import FloatList, IntList\n#import main\n\ndef talker():\n #float64[4] axes = [main.leftX,main.leftY,main.rightX,main.rightY]\n pub_axes = rospy.Publisher('controls', FloatList, queue_size=10)\n pub_buttons = rospy.Publisher('buttons', IntList, queue_size=10)\n rospy.init_node('controller_base', anonymous=True)\n rate = rospy.Rate(10) # 10hz\n axes = FloatList()\n buttons = IntList()\n while not rospy.is_shutdown():\n #axes.data = [main.leftX,main.leftY,main.rightX,main.rightY]\n\taxes.data = [1,-1,0,1]\n\t#buttons.data = main.buttonArr1\n\tbuttons.data = [1,0,1,0,1]\n rospy.loginfo(axes)\n pub_axes.publish(axes)\n\trospy.loginfo(buttons)\n pub_buttons.publish(buttons)\n rate.sleep()\n\nif __name__ == '__main__':\n try:\n talker()\n except rospy.ROSInterruptException:\n pass\n"}],"string":"[\n {\n \"alpha_fraction\": 0.8125,\n \"alphanum_fraction\": 0.8125,\n \"avg_line_length\": 35,\n \"blob_id\": \"6425d8da6c05cb5631bd01fcdc8153d5965addae\",\n \"content_id\": \"c046d11836767f0c163aabc6bff23c29be12ea43\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 144,\n \"license_type\": \"no_license\",\n \"max_line_length\": 80,\n \"num_lines\": 4,\n \"path\": \"/README.md\",\n \"repo_name\": \"yorkurt/pygame_controllers\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# pygame_controllers\\nCrappy pygame code to run some joysticks\\n\\nIdeally this should work to control the rover. Full control schemes coming soon.\\n\"\n },\n {\n \"alpha_fraction\": 0.48377305269241333,\n \"alphanum_fraction\": 0.5155264735221863,\n \"avg_line_length\": 29.382978439331055,\n \"blob_id\": \"87ca61477d83fb56e738152464aff9b791582fe6\",\n \"content_id\": \"6fb85b7728c8ff065a5eddd79f70bb1834c37042\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 4283,\n \"license_type\": \"no_license\",\n \"max_line_length\": 96,\n \"num_lines\": 141,\n \"path\": \"/joy.py\",\n \"repo_name\": \"yorkurt/pygame_controllers\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import math\\nimport pygame\\n\\nimport helpers\\n\\nclass Joystick_L:\\n\\n def __init__(self):\\n pygame.joystick.init()\\n numJoys = pygame.joystick.get_count()\\n self.joyInitL = False\\n self.x = 0\\n self.y = 0\\n self.rad = 0\\n self.throttle = 0\\n if (numJoys > 0):\\n self.joystick = pygame.joystick.Joystick(0)\\n self.joystick.init()\\n self.joyInitL = True\\n else:\\n print(\\\"No left joystick found\\\")\\n self.joyInitL = False\\n self.numButtons = 0\\n return\\n\\n self.numButtons = self.joystick.get_numbuttons()\\n self.buttons = [0]*self.numButtons\\n \\n \\n pygame.font.init()\\n self.font = pygame.font.Font(pygame.font.get_default_font(),32)\\n\\n def compute(self):\\n self.x = self.joystick.get_axis(0)\\n self.y = self.joystick.get_axis(1)\\n self.throttle = ((-1 * self.joystick.get_axis(2)) + 1) / 2\\n self.rad = math.hypot(self.x,self.y)\\n self.rad = helpers.limitToRange(self.rad,0,1)\\n self.ang = math.atan2(self.y,self.x)\\n self.x = self.rad*math.cos(self.ang)\\n self.y = self.rad*math.sin(self.ang)\\n #'clicks' to middle\\n tab = .12\\n if -tab < self.x < tab:\\n self.x = 0\\n if -tab < self.y < tab:\\n self.y = 0\\n\\n for i in xrange(self.numButtons):\\n self.buttons[i] = self.joystick.get_button(i)\\n\\n \\n\\n \\n ''' def draw(self,surface):\\n r = 200\\n w = surface.get_width()\\n h = surface.get_height()\\n\\n for i in xrange(self.numButtons):\\n if self.buttons[i]:\\n col = (0,255,0)\\n else:\\n col = (64,0,64)\\n text = self.font.render(str(i),1,col)\\n surface.blit(text,text.get_rect(centerx=w*(i+1)/(self.numButtons+1),centery=h/2))\\n \\n x = int(round(w/2+self.x*r))\\n y = int(round(h/2+self.y*r))\\n pygame.draw.aaline(surface,(128,128,128),(w/2,h/2),(x,y),1)\\n pygame.draw.circle(surface,(0,0,0),(x,y),8,4)\\n pygame.draw.circle(surface,(0,255,255),(w/2,h/2),r,2) '''\\n\\nclass Joystick_R:\\n\\n def __init__(self):\\n pygame.joystick.init()\\n numJoys = pygame.joystick.get_count()\\n self.joyInitR = False\\n self.x = 0\\n self.y = 0\\n self.rad = 0\\n self.throttle = 0\\n if (numJoys > 1):\\n self.joystick = pygame.joystick.Joystick(1)\\n self.joystick.init()\\n self.joyInitR = True\\n else:\\n print(\\\"No right joystick found\\\")\\n self.joyInitR = False\\n self.numButtons = 0\\n return\\n\\n self.numButtons = self.joystick.get_numbuttons()\\n self.buttons = [0]*self.numButtons\\n \\n \\n pygame.font.init()\\n self.font = pygame.font.Font(pygame.font.get_default_font(),32)\\n\\n def compute(self):\\n self.x = self.joystick.get_axis(0)\\n self.y = self.joystick.get_axis(1)\\n self.throttle = ((-1 * self.joystick.get_axis(2)) + 1) / 2\\n self.rad = math.hypot(self.x,self.y)\\n self.rad = helpers.limitToRange(self.rad,0,1)\\n self.ang = math.atan2(self.y,self.x)\\n self.x = self.rad*math.cos(self.ang)\\n self.y = self.rad*math.sin(self.ang)\\n #'clicks' to middle\\n tab = .12\\n if -tab < self.x < tab:\\n self.x = 0\\n if -tab < self.y < tab:\\n self.y = 0\\n\\n for i in xrange(self.numButtons):\\n self.buttons[i] = self.joystick.get_button(i)\\n\\n \\n\\n \\n ''' def draw(self,surface):\\n r = 200\\n w = surface.get_width()\\n h = surface.get_height()\\n\\n for i in xrange(self.numButtons):\\n if self.buttons[i]:\\n col = (0,255,0)\\n else:\\n col = (64,0,64)\\n \\n text = self.font.render(str(i),1,col)\\n surface.blit(text,text.get_rect(centerx=w*(i+1)/(self.numButtons+1),centery=h/2-60))\\n \\n x = int(round(w/2+self.x*r))\\n y = int(round(h/2+self.y*r))\\n pygame.draw.aaline(surface,(128,0,0),(w/2,h/2),(x,y),1)\\n pygame.draw.circle(surface,(0,0,0),(x,y),8,4)\\n pygame.draw.circle(surface,(0,255,255),(w/2,h/2),r,2) '''\"\n },\n {\n \"alpha_fraction\": 0.3854166567325592,\n \"alphanum_fraction\": 0.3854166567325592,\n \"avg_line_length\": 14.666666984558105,\n \"blob_id\": \"0d8ee4068d1eae7ca84bb1fc90bc5d4d5926daaf\",\n \"content_id\": \"52475857fc9b416159a5b17d4c0ab44a072410f1\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 96,\n \"license_type\": \"no_license\",\n \"max_line_length\": 24,\n \"num_lines\": 6,\n \"path\": \"/helpers.py\",\n \"repo_name\": \"yorkurt/pygame_controllers\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"\\n\\ndef limitToRange(a,b,c):\\n if a < b:\\n a = b\\n if a > c:\\n a = c\\n return a\\n\"\n },\n {\n \"alpha_fraction\": 0.476492702960968,\n \"alphanum_fraction\": 0.5159849524497986,\n \"avg_line_length\": 29.826086044311523,\n \"blob_id\": \"f6eaf19d1cc6a43597f61a0068a1af0bd060dc6e\",\n \"content_id\": \"e2bd1618541a19ace6ae6d70fd527decda277afe\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 4254,\n \"license_type\": \"no_license\",\n \"max_line_length\": 139,\n \"num_lines\": 138,\n \"path\": \"/main.py\",\n \"repo_name\": \"yorkurt/pygame_controllers\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import math\\nimport pygame\\n\\nimport joy\\n\\nclass Main:\\n def __init__(self):\\n self.SCREEN_WIDTH = 800\\n self.SCREEN_HEIGHT = 450\\n self.screen = pygame.display.set_mode((self.SCREEN_WIDTH,self.SCREEN_HEIGHT))\\n\\n self.objects = []\\n self.mode = 1\\n\\n pygame.font.init()\\n self.font = pygame.font.Font(pygame.font.get_default_font(),32)\\n\\n\\t\\n\\t\\n\\n def setupGame(self):\\n self.clock = pygame.time.Clock()\\t\\n self.FPS = 60\\n self.joy = joy.Joystick_L()\\n self.joy2 = joy.Joystick_R()\\n\\n self.objects.append(self.joy)\\n self.objects.append(self.joy2)\\n\\n\\tl = self.objects[0].get_numbuttons()\\n\\tself.buttonArr1 = [0 for i in range(l)]\\n\\n def runGame(self):\\n self.gameRunning = 1\\n\\n\\n while self.gameRunning:\\n\\t buttonArr1 = [0 for i in range(len(buttonArr1))]\\n\\n self.getInput()\\n self.compute()\\n self.draw(self.screen)\\n self.clock.tick(self.FPS)\\n \\n #self.leftX = pygame.joystick.Joystick(0).get_axis(0)\\n #self.leftY = -1 * pygame.joystick.Joystick(0).get_axis(1)\\n #self.rightX = pygame.joystick.Joystick(1).get_axis(0)\\n #self.rightY = -1 * pygame.joystick.Joystick(1).get_axis(1)\\n\\n self.leftX = self.objects[0].get_axis(0)\\n\\t self.leftY = self.objects[0].get_axis(1)\\n\\t #self.rightX = self.objects[1].get_axis(0)\\n\\t #self.rightY = self.objects[1].get_axis(1)\\n\\n #handle buttons \\n for event in pygame.event.get(pygame.JOYBUTTONUP): #event handling loop\\n #handle mode switching - buttons 8/9 on both sticks\\n print(event)\\n if (event.button == 7): #button 8 increases mode\\n\\t\\t buttonArr1[7] = 1\\n if (self.mode == 3):\\n self.mode = 1\\n else:\\n self.mode = self.mode + 1\\n print(\\\"Mode is now: \\\" + str(self.mode))\\n if (event.button == 8): #button 9 decreases mode\\n\\t\\t buttonArr1[8] = 1\\n if (self.mode == 1):\\n self.mode = 3\\n else:\\n self.mode = self.mode - 1\\n print(\\\"Mode is now: \\\" + str(self.mode))\\n\\n\\n def getInput(self):\\n for event in pygame.event.get():\\n if event.type == pygame.QUIT:\\n self.gameRunning = 0\\n\\n #if(self.joy.joyInitL == True):\\n pygame.display.set_caption(str(self.joy.x) + ', ' + str(self.joy.y) + ', ' + str(self.joy.rad) + ', ' + str(self.joy.throttle))\\n\\n def draw(self,surface):\\n self.screen.fill((255,255,255))\\n\\n #for o in self.objects:\\n # o.draw(self.screen)\\n\\n \\n r = 200\\n w = surface.get_width()\\n h = surface.get_height()\\n\\n for i in xrange(self.joy.numButtons):\\n if self.joy.buttons[i]:\\n col = (0,255,0)\\n else:\\n col = (64,0,64)\\n \\n text = self.font.render(str(i),1,col)\\n surface.blit(text,text.get_rect(centerx=w*(i+1)/(self.joy.numButtons+1),centery=h/2-30))\\n\\n x = int(round(w/2+self.joy.x*r))\\n y = int(round(h/2+self.joy.y*r))\\n pygame.draw.aaline(surface,(128,128,128),(w/2,h/2),(x,y),1)\\n pygame.draw.circle(surface,(0,0,0),(x,y),8,4)\\n #pygame.draw.circle(surface,(0,255,255),(w/2,h/2),r,2)\\n\\n for i in xrange(self.joy2.numButtons):\\n if self.joy2.buttons[i]:\\n col = (0,255,0)\\n else:\\n col = (64,0,64)\\n \\n text = self.font.render(str(i),1,col)\\n surface.blit(text,text.get_rect(centerx=w*(i+1)/(self.joy2.numButtons+1),centery=h/2+30))\\n \\n x1 = int(round(w/2+self.joy2.x*r))\\n y1 = int(round(h/2+self.joy2.y*r))\\n pygame.draw.aaline(surface,(128,0,0),(w/2,h/2),(x1,y1),1)\\n pygame.draw.circle(surface,(0,0,0),(x1,y1),8,4)\\n pygame.draw.circle(surface,(0,255,255),(w/2,h/2),r,2)\\n\\n pygame.display.flip()\\n\\n def compute(self):\\n i = 0\\n while i < len(self.objects):\\n self.objects[i].compute()\\n i += 1\\n\\n\\n\\nm = Main()\\nm.setupGame()\\nm.runGame()\\n\\npygame.quit()\\n\"\n },\n {\n \"alpha_fraction\": 0.6373276710510254,\n \"alphanum_fraction\": 0.66171795129776,\n \"avg_line_length\": 29.419355392456055,\n \"blob_id\": \"6b74bc89f6bc7af5b1a183f189284355f71daa12\",\n \"content_id\": \"fa7ac920e5ad41173676dc5b5350634761cca4d5\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 943,\n \"license_type\": \"no_license\",\n \"max_line_length\": 70,\n \"num_lines\": 31,\n \"path\": \"/talker.py\",\n \"repo_name\": \"yorkurt/pygame_controllers\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#!/usr/bin/env python\\n\\nimport rospy\\nfrom std_msgs.msg import String#, Float64MultiArray\\nfrom controller.msg import FloatList, IntList\\n#import main\\n\\ndef talker():\\n #float64[4] axes = [main.leftX,main.leftY,main.rightX,main.rightY]\\n pub_axes = rospy.Publisher('controls', FloatList, queue_size=10)\\n pub_buttons = rospy.Publisher('buttons', IntList, queue_size=10)\\n rospy.init_node('controller_base', anonymous=True)\\n rate = rospy.Rate(10) # 10hz\\n axes = FloatList()\\n buttons = IntList()\\n while not rospy.is_shutdown():\\n #axes.data = [main.leftX,main.leftY,main.rightX,main.rightY]\\n\\taxes.data = [1,-1,0,1]\\n\\t#buttons.data = main.buttonArr1\\n\\tbuttons.data = [1,0,1,0,1]\\n rospy.loginfo(axes)\\n pub_axes.publish(axes)\\n\\trospy.loginfo(buttons)\\n pub_buttons.publish(buttons)\\n rate.sleep()\\n\\nif __name__ == '__main__':\\n try:\\n talker()\\n except rospy.ROSInterruptException:\\n pass\\n\"\n }\n]"},"num_files":{"kind":"number","value":5,"string":"5"}}},{"rowIdx":2030,"cells":{"repo_name":{"kind":"string","value":"BramboraSK/osu-czsk-bot"},"repo_url":{"kind":"string","value":"https://github.com/BramboraSK/osu-czsk-bot"},"snapshot_id":{"kind":"string","value":"755caf48f790884eb6960e6bc6337a55b37e88c0"},"revision_id":{"kind":"string","value":"efa016f24eeab0e698ee53ff9fb7b3fd50035930"},"directory_id":{"kind":"string","value":"0669b18df848b2132c19b1d50cb6fc17d8cfb003"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"string","value":"2020-09-12T17:43:56.093019"},"revision_date":{"kind":"string","value":"2019-11-18T21:18:58"},"committer_date":{"kind":"string","value":"2019-11-18T21:18:58"},"github_id":{"kind":"number","value":222499234,"string":"222,499,234"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":1,"string":"1"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"string","value":"2019-11-18T16:55:58"},"gha_updated_at":{"kind":"string","value":"2019-11-18T17:07:56"},"gha_pushed_at":{"kind":"string","value":"2019-11-18T19:34:45"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.6193415522575378,"alphanum_fraction":0.6419752836227417,"avg_line_length":22.14285659790039,"blob_id":"07a752665e16019d9c1ad660eec8dd6b5bd7c598","content_id":"024592b3751cc5399ec6e568b69596aa60b38736","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":491,"license_type":"no_license","max_line_length":119,"num_lines":21,"path":"/index.py","repo_name":"BramboraSK/osu-czsk-bot","src_encoding":"UTF-8","text":"import tweepy\nimport random\nimport threading\n\n//API\nauth = tweepy.OAuthHandler(\"...\", \"...\")\nauth.set_access_token(\"...\", \"...\")\n\napi = tweepy.API(auth)\n\n//Súbory\nhraci = open(\"hraci.txt\").readlines()\npridavne_mena = open(\"pridavne_mena.txt\").readlines()\n\ndef send():\n //Tweet každých 1200 sekúnd (20 minút)\n threading.Timer(1200.0, send).start()\n \n api.update_status(random.choice(hraci).replace(\"\\n\", \"\") + \" je \" + random.choice(pridavne_mena).replace(\"\\n\", \"\"))\n\nsend()\n"},{"alpha_fraction":0.6319444179534912,"alphanum_fraction":0.6875,"avg_line_length":23,"blob_id":"50a1e443d40a715ad60bb8c9cb788dddd4b7df49","content_id":"36e5e9f65c088193cf2d78df1f8972f2b146c21f","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":153,"license_type":"no_license","max_line_length":54,"num_lines":6,"path":"/README.md","repo_name":"BramboraSK/osu-czsk-bot","src_encoding":"UTF-8","text":"# Súbory\n**pridavne_mena.txt** - 37,138 českých prídavných mien\n\n**cz.txt** - Takmer milión českých slov\n\n**hraci.txt** - Ľudia z Top 100 CZ/SK\n"}],"string":"[\n {\n \"alpha_fraction\": 0.6193415522575378,\n \"alphanum_fraction\": 0.6419752836227417,\n \"avg_line_length\": 22.14285659790039,\n \"blob_id\": \"07a752665e16019d9c1ad660eec8dd6b5bd7c598\",\n \"content_id\": \"024592b3751cc5399ec6e568b69596aa60b38736\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 491,\n \"license_type\": \"no_license\",\n \"max_line_length\": 119,\n \"num_lines\": 21,\n \"path\": \"/index.py\",\n \"repo_name\": \"BramboraSK/osu-czsk-bot\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import tweepy\\nimport random\\nimport threading\\n\\n//API\\nauth = tweepy.OAuthHandler(\\\"...\\\", \\\"...\\\")\\nauth.set_access_token(\\\"...\\\", \\\"...\\\")\\n\\napi = tweepy.API(auth)\\n\\n//Súbory\\nhraci = open(\\\"hraci.txt\\\").readlines()\\npridavne_mena = open(\\\"pridavne_mena.txt\\\").readlines()\\n\\ndef send():\\n //Tweet každých 1200 sekúnd (20 minút)\\n threading.Timer(1200.0, send).start()\\n \\n api.update_status(random.choice(hraci).replace(\\\"\\\\n\\\", \\\"\\\") + \\\" je \\\" + random.choice(pridavne_mena).replace(\\\"\\\\n\\\", \\\"\\\"))\\n\\nsend()\\n\"\n },\n {\n \"alpha_fraction\": 0.6319444179534912,\n \"alphanum_fraction\": 0.6875,\n \"avg_line_length\": 23,\n \"blob_id\": \"50a1e443d40a715ad60bb8c9cb788dddd4b7df49\",\n \"content_id\": \"36e5e9f65c088193cf2d78df1f8972f2b146c21f\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 153,\n \"license_type\": \"no_license\",\n \"max_line_length\": 54,\n \"num_lines\": 6,\n \"path\": \"/README.md\",\n \"repo_name\": \"BramboraSK/osu-czsk-bot\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# Súbory\\n**pridavne_mena.txt** - 37,138 českých prídavných mien\\n\\n**cz.txt** - Takmer milión českých slov\\n\\n**hraci.txt** - Ľudia z Top 100 CZ/SK\\n\"\n }\n]"},"num_files":{"kind":"number","value":2,"string":"2"}}},{"rowIdx":2031,"cells":{"repo_name":{"kind":"string","value":"Zheng392/Python-Repository"},"repo_url":{"kind":"string","value":"https://github.com/Zheng392/Python-Repository"},"snapshot_id":{"kind":"string","value":"fe04a8ac232d31926228f3beb81faa415f5622b8"},"revision_id":{"kind":"string","value":"34b809383a985ed0040b3ccf8247b10fdb6ba7bf"},"directory_id":{"kind":"string","value":"f8711392cf9cefe379277a8cb535afa2a39cc9dc"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"string","value":"2020-04-13T03:58:28.730211"},"revision_date":{"kind":"string","value":"2019-10-08T01:18:07"},"committer_date":{"kind":"string","value":"2019-10-08T01:18:07"},"github_id":{"kind":"number","value":162945854,"string":"162,945,854"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.68388432264328,"alphanum_fraction":0.6859503984451294,"avg_line_length":22.095237731933594,"blob_id":"896efde7319a1a45e01aff1cb3f3c72da82de728","content_id":"68a30f24115f801551ea676631b5aa7824f01aab","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":484,"license_type":"no_license","max_line_length":68,"num_lines":21,"path":"/Spider/XieCheng Hotel Data/xiecheng selenium/text/xiechengservices/hotelInfotext.py","repo_name":"Zheng392/Python-Repository","src_encoding":"UTF-8","text":"# -*- coding:utf-8 -*-\n__author__ = 'LiuYang'\n\nfrom services.xiechengservices.hotelInfo import XiechenghotelService\n\nclass DriverServiceTest(object):\n\n def __init__(self):\n self.xiechenghotelService = XiechenghotelService()\n\n def crawlxiechengTest(self):\n self.xiechenghotelService.getdata()\n self.xiechenghotelService.depose()\n\n\n\nif __name__ == \"__main__\":\n\n driverServiceTest = DriverServiceTest()\n\n driverServiceTest.crawlxiechengTest()"},{"alpha_fraction":0.5402272939682007,"alphanum_fraction":0.5747727155685425,"avg_line_length":43.45454406738281,"blob_id":"45f337add63611ab6ba9b60535cfca4c203a3f0a","content_id":"c62cdf683120b2298bd3ff418f42191f173c8e1d","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":4566,"license_type":"no_license","max_line_length":113,"num_lines":99,"path":"/Spider/Jindong review data by Scrapy/jd_spider-fundamental/jd_spider/spiders/jd_home.py","repo_name":"Zheng392/Python-Repository","src_encoding":"UTF-8","text":"# -*- coding: utf-8 -*-\nfrom scrapy.spiders import Spider\nfrom jd_spider.items import goodsItem\nfrom scrapy.selector import Selector\nimport scrapy\nimport re\nimport json\n\nurls={'phone': 'https://list.jd.com/list.html?cat=9987,653,655&sort=sort_commentcount_desc&page=',\n 'laptop':'https://list.jd.com/list.html?cat=670,671,672&sort=sort_commentcount_desc&page=',\n 'men_cloth':'https://list.jd.com/list.html?cat=1315,1342&sort=sort_commentcount_desc&page=',\n 'women_cloth':'https://list.jd.com/list.html?cat=1315,1343&sort=sort_commentcount_desc&page=',\n 'home_textiles':'https://list.jd.com/list.html?cat=1620,1621&sort=sort_commentcount_desc&page=',\n 'sporting_goods':'https://list.jd.com/list.html?cat=1318,1466&sort=sort_commentcount_desc&page=',\n 'food':'https://list.jd.com/list.html?cat=1320,1583&sort=sort_commentcount_desc&page='\n }\n\nclass jd_spider(Spider):\n name = \"jd\"\n\n start_urls = []\n for i in range(1, 121): # 这里请自己设置页数，目前只能抓取电子烟分类下前10页的商品\n url = 'https://list.jd.com/list.html?cat=1315,1342&sort=sort_commentcount_desc&page=' + str(i)#\n start_urls.append(url)\n\n # def start_requests(self):\n # urls = []\n # for i in range(1, 61): # 这里请自己设置页数，目前只能抓取电子烟分类下前10页的商品\n # url = 'https://list.jd.com/list.html?cat=1315,1342&page=' + str(i)\n # urls.append(url)\n # for url in urls:\n # yield scrapy.Request(url=url, callback=self.parse)\n # def parse_price(self, response):\n # item1 = response.meta['item']\n # temp1 = response.body.split(b'jQuery([')\n # s = temp1[1][:-4] # 获取到需要的json内容\n # js = json.loads(s.decode()) # js是一个list\n # if 'pcp' in js:\n # item1['price'] = js['pcp']\n # else:\n # item1['price'] = js['p']\n # return item1\n\n # def parse_getCommentnum(self, response):\n # item1 = response.meta['item']\n # # response.body是一个json格式的\n # js = json.loads(response.body.decode())\n # item1['score1count'] = js['CommentsCount'][0]['Score1Count']\n # item1['score2count'] = js['CommentsCount'][0]['Score2Count']\n # item1['score3count'] = js['CommentsCount'][0]['Score3Count']\n # item1['score4count'] = js['CommentsCount'][0]['Score4Count']\n # item1['score5count'] = js['CommentsCount'][0]['Score5Count']\n # item1['comment_num'] = js['CommentsCount'][0]['CommentCount']\n # num = item1['ID'] # 获得商品ID\n # s1 = str(num)\n # url = \"http://pm.3.cn/prices/pcpmgets?callback=jQuery&skuids=\" + s1[3:-2] + \"&origin=2\"\n # yield scrapy.Request(url, meta={'item': item1}, callback=self.parse_price)\n\n # def parse_detail(self, response):\n # item1 = response.meta['item']\n # sel = Selector(response)\n #\n # temp = response.body.split(b'commentVersion:')\n #\n # pattern = re.compile(b\"[\\'](\\d+)[\\']\")\n # if len(temp) < 2:\n # item1['commentVersion'] = -1\n # else:\n # match = pattern.match(temp[1][:10])\n # item1['commentVersion'] = match.group()\n #\n # url = \"http://club.jd.com/clubservice.aspx?method=GetCommentsCount&referenceIds=\" + str(item1['ID'][0])\n # yield scrapy.Request(url, meta={'item': item1}, callback=self.parse_getCommentnum)\n def __init__(self):\n self.allids=[]\n self.count=0\n def parse(self, response): # 解析搜索页\n sel = Selector(response) # Xpath选择器\n goods = sel.xpath('//li[@class=\"gl-item\"]')\n i=0\n for good in goods:\n i=i+1\n item1 = goodsItem()\n item1['ID'] = good.xpath('./div/@data-sku').extract()\n if item1['ID'] in self.allids:\n continue\n self.allids.append(item1['ID'])\n item1['name'] = good.xpath('./div/div[@class=\"p-name\"]/a/em/text()').extract()\n item1['shop_name'] = good.xpath('./div/div[@class=\"p-shop\"]/@data-shop_name').extract()\n try:\n item1['link'] = good.xpath('./div/div[@class=\"p-img\"]/a/@href').extract()\n url = \"http:\" + item1['link'][0] + \"#comments-list\"\n except:\n pass\n\n print(\"goodNum is\",i)\n yield item1#scrapy.Request(url, meta={'item': item1}, callback=self.parse_detail)\n self.count=self.count+1\n print('count is ',self.count,response)"},{"alpha_fraction":0.5977542996406555,"alphanum_fraction":0.7014530897140503,"avg_line_length":20.338027954101562,"blob_id":"f0b3c59edd792a595320c5f5e25fefbfebf20610","content_id":"0c78ec6a3c072423d0b886fb8421ed3ad07433c7","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1514,"license_type":"permissive","max_line_length":78,"num_lines":71,"path":"/Foursquare research/Projects/Get venues/Foursquare api.py","repo_name":"Zheng392/Python-Repository","src_encoding":"UTF-8","text":"'''\n#test the search function\nimport json, requests\nurl = 'https://api.foursquare.com/v2/venues/search'\n\nparams = dict(\n client_id='5MDTT4NQVXV3VQF3KEA50Z2T0DLQ5TJAF1C2UVERXOJD5V4E',\n client_secret='QK4AM22AD13GNIMNJLSHGEFX5VPBPH3JALD50L3P3CHBYHQF',\n v='20180323',\n ll='37.756803, -122.429917',\n radius=100000,\n intent='browse',\n limit=20\n)\nresp = requests.get(url=url, params=params)\ndata = json.loads(resp.text)\n\n'''\n\n#test explore\n'''\nimport json, requests\nurl = 'https://api.foursquare.com/v2/venues/explore'\n\nparams = dict(\n client_id='5MDTT4NQVXV3VQF3KEA50Z2T0DLQ5TJAF1C2UVERXOJD5V4E',\n client_secret='QK4AM22AD13GNIMNJLSHGEFX5VPBPH3JALD50L3P3CHBYHQF',\n near='San Francisco, CA',\n v='20180323',\n radius=100000,\noffset='100000',\n limit='50',\n time='any',\n day='any',\n)\nresp = requests.get(url=url, params=params)\ndata = json.loads(resp.text)\nprint(resp.text)\n'''\n\n# #test venue's photo\n# import json, requests\n# url = 'https://api.foursquare.com/v2/venues/445e36bff964a520fb321fe3/photos'\n#\n# params = dict(\n# client_id='5MDTT4NQVXV3VQF3KEA50Z2T0DLQ5TJAF1C2UVERXOJD5V4E',\n# client_secret='QK4AM22AD13GNIMNJLSHGEFX5VPBPH3JALD50L3P3CHBYHQF',\n# v='20180323',\n# limit='200',\n#\n# )\n# resp = requests.get(url=url, params=params)\n# data = json.loads(resp.text)\n# print(resp.text)\n\n\n#test venue's tips\nimport json, requests\nurl = 'https://api.foursquare.com/v2/venues/4c29567f9fb5d13aa2139b57/tips'\n\nparams = dict(\n client_id='5MDTT4NQVXV3VQF3KEA50Z2T0DLQ5TJAF1C2UVERXOJD5V4E',\n client_secret='QK4AM22AD13GNIMNJLSHGEFX5VPBPH3JALD50L3P3CHBYHQF',\n v='20180323',\n sort='popular',\n limit='500',\n\n)\nresp = requests.get(url=url, params=params)\ndata = json.loads(resp.text)\nprint(resp.text)"},{"alpha_fraction":0.6493775844573975,"alphanum_fraction":0.680497944355011,"avg_line_length":24.3157901763916,"blob_id":"e8d795942f91a3c6b3428a1de2cf849ba5584b4b","content_id":"fa7292bc20be8a690f8afa4e03fdb3e8a8a81e50","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":482,"license_type":"no_license","max_line_length":51,"num_lines":19,"path":"/Foursquare research/Projects/Small Dataset creating/Get part pictures.py","repo_name":"Zheng392/Python-Repository","src_encoding":"UTF-8","text":"pictures=[]\nwith open('all.tsv','r') as f:\n\tfor line in f.readlines():\n\t\tpictures.append(line.strip().split('\\t')[4])\nprint(pictures)\n\nphotos1=[]\nphotosfeature=[]\nallphotolines=[]\nwith open('name-fc8.txt','r') as f1:\n\tallphotolines=f1.readlines()\n\tfor line in allphotolines:\n\t\tphoto=eval(line.split(' ',1)[0])[0].split('.')[0]\n\t\tphotos1.append(photo)\n\nwith open('name-fc8_2.txt','w') as f2:\n\tfor picture in pictures:\n\t\tindex=photos1.index(picture)\n\t\tf2.write(allphotolines[index])\n\n"},{"alpha_fraction":0.5956472158432007,"alphanum_fraction":0.6040473580360413,"avg_line_length":30.14285659790039,"blob_id":"2e3c9efaae86c8c295bff9f9e585d17cbcd948f1","content_id":"66534950642ee9d4041e6daade4514d367b6ae97","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":2619,"license_type":"no_license","max_line_length":124,"num_lines":84,"path":"/Foursquare research/Projects/Data analysis/Create data.py","repo_name":"Zheng392/Python-Repository","src_encoding":"UTF-8","text":"import pandas as pd\nimport random\ndata=pd.read_csv('photo,user,venue,time.txt',names=(\"photo\",\"user\",\"venue\",\"time\"),encoding='utf-8')\ndata=data.sort_values('time')\n# data['venue']=pd.factorize(data['venue'])[0]\n# data['user']=pd.factorize(data['user'])[0]\nvenueNum=len(pd.factorize(data['venue'])[1])\ntrain=data.iloc[0:110000]\ntest=data.iloc[110000:]\n\n\n\nprint('start now')\n\ndropList=[]\nfor x in range(len(test)):\n if (test.iloc[x]['user'] not in list(train['user'].values) or test.iloc[x]['venue'] not in list(train['venue'].values)):\n dropList.append(x)\ntest = test.drop(test.index[dropList])\n\n\ntrain['venue'],venueIndex=pd.factorize(train['venue'])\ntrain['user'],userIndex=pd.factorize(train['user'])\n\ntemp=[]\nfor venue in test['venue']:\n temp.append(venueIndex.get_loc(venue))\ntest['venue']=temp\n\ntemp=[]\nfor user in test['user']:\n temp.append(userIndex.get_loc(user))\ntest['user']=temp\n\n\n\nwith open('train.tsv','w') as f:\n for x in range(len(train)):\n f.write(str(train.iloc[x]['user'])+'\\t'+str(train.iloc[x]['venue'])+'\\t'+'1'\n +'\\t'+str(train.iloc[x]['time'])+'\\t'+str(train.iloc[x]['photo'])+'\\n')\n\nprint('sucessfully save train.tsv')\nwith open('test.tsv','w') as f:\n for x in range(len(test)):\n f.write(str(test.iloc[x]['user']) + '\\t' + str(test.iloc[x]['venue']) + '\\t' + '1'\n + '\\t' + str(test.iloc[x]['time']) + '\\t' + str(test.iloc[x]['photo']) + '\\n')\n\nprint('sucessfully save test.tsv')\n\ntrainPlusTest=pd.concat([train,test])\n\nwith open('all.tsv','w') as f:\n for x in range(len(trainPlusTest)):\n f.write(str(trainPlusTest.iloc[x]['user'])+'\\t'+str(trainPlusTest.iloc[x]['venue'])+'\\t'+'1'\n +'\\t'+str(trainPlusTest.iloc[x]['time'])+ '\\t' + str(trainPlusTest.iloc[x]['photo'])+'\\n')\n\n\n\nuserVenueSet=set()\nuserVenueDict=dict()\nvenueSet=set([i for i in range(venueNum)])\nfor x in range(len(trainPlusTest)):\n if trainPlusTest.iloc[x]['user'] not in userVenueDict:\n userVenueDict[trainPlusTest.iloc[x]['user']]=set()\n userVenueDict[trainPlusTest.iloc[x]['user']].add(trainPlusTest.iloc[x]['venue'])\n\n\n\nwith open('test.negative.tsv','w') as f:\n for x in range(len(test)):\n if test.iloc[x]['user'] in userVenueDict:\n m=list(venueSet-userVenueDict[test.iloc[x]['user']])\n else:\n m=[]\n random.shuffle(m)\n r=50\n if len(m)', ' ')\n name = name.replace('|', ' ')\n print(os.path.join(path, file))\n os.rename(os.path.join(path, file), os.path.join(path,name+\".pdf\"))\n"},{"alpha_fraction":0.5977763533592224,"alphanum_fraction":0.6000654101371765,"avg_line_length":35.35714340209961,"blob_id":"50c483ac09faaec95f173745b384a53a3b319069","content_id":"2c414c614807af7c8d6a506e41e796244d4b4d75","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":3152,"license_type":"no_license","max_line_length":529,"num_lines":84,"path":"/Spider/XieCheng Hotel Data/xiecheng selenium/DAO/xiecheng.py","repo_name":"Zheng392/Python-Repository","src_encoding":"UTF-8","text":"# -*- coding: utf-8 -*-\n__author__ = 'LiuYang'\nimport pymysql\nimport uuid\nimport random\n\nclass xiechengDAO(object):\n def __init__(self,host= 'localhost',db='mysql',user='root',password='73628'):\n self.host = host\n self.db = db\n self.user=user\n self.password =password\n\n # 存储酒店基本信息\n def savehotelComment(self,items):\n db = pymysql.connect(self.host,self.user,self.password,self.db,charset='utf8')\n cursor = db.cursor()\n for item in items:\n try:\n cursor.execute(\"replace into hotelinfo(guid,city,title,price,score,recommend,area,havawifi,discussNum,common_facilities,activity_facilities,service_facilities,room_facilities,around_facilities)values(%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s)\" ,(item[\"guid\"],item[\"city\"],item[\"title\"],item[\"price\"],item[\"score\"],item[\"recommend\"],item[\"area\"],item[\"havawifi\"],item[\"discussNum\"],item[\"common_facilities\"],item[\"activity_facilities\"],item[\"service_facilities\"],item[\"room_facilities\"],item[\"around_facilities\"]))\n except Exception as e:\n print(e)\n db.commit()\n cursor.close()\n db.close()\n\n\n # 存储所有酒店的链接\n def savehotellink(self,listPageInfo):\n db = pymysql.connect(self.host,self.user,self.password,self.db,charset='utf8')\n cursor = db.cursor()\n for hotel in listPageInfo:\n try:\n id = uuid.uuid1()\n cursor.execute(\"replace into hotellianjie(guid,lianjie,city,comm_num)values(%s,%s,%s,%s)\" ,(id,hotel[\"url\"],hotel[\"city\"],hotel[\"comm_num\"]))\n except Exception as e:\n print(hotel[\"url\"])\n db.commit()\n cursor.close()\n db.close()\n\n\n # 从数据库中读取链接数据\n def _return(self):\n db = pymysql.connect(self.host,self.user,self.password,self.db,charset='utf8')\n cursor = db.cursor()\n\n cursor.execute(\"SELECT * FROM hotellianjie\")\n\n rows = cursor.fetchall()\n return rows\n\n db.commit()\n cursor.close()\n db.close()\n\n # 存储酒店评论信息\n def savehotelCommentinfo(self,items):\n db = pymysql.connect(self.host,self.user,self.password,self.db,charset='utf8')\n cursor = db.cursor()\n for item in items:\n\n try:\n cursor.execute(\"insert into hotelcommentinfo(hotelname,username,commentscore,intime,tourstyle,praisenum,commenttime,comment)values(%s,%s,%s,%s,%s,%s,%s,%s)\" ,(item[\"title\"],item[\"username\"],item[\"commentscore\"],item[\"intime\"],item[\"tourstyle\"],item[\"praisenum\"],item[\"commenttime\"],item[\"comment\"]))\n except :\n print(item)\n db.commit()\n cursor.close()\n db.close()\n\n\n # 从数据库中读取评论数据\n def _returncomment(self):\n db = pymysql.connect(self.host,self.user,self.password,self.db,charset='utf8')\n cursor = db.cursor()\n\n cursor.execute(\"SELECT * FROM hotelcommentinfo\")\n\n rows = cursor.fetchall()\n return rows\n\n db.commit()\n cursor.close()\n db.close()\n\n\n\n\n"},{"alpha_fraction":0.5355501770973206,"alphanum_fraction":0.5528520941734314,"avg_line_length":31.743362426757812,"blob_id":"f91616be7377d19912865f599c1a619eb8d2e6f6","content_id":"d95ac368eb7b1d99157f281d0ef185d06fb9d903","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":3699,"license_type":"no_license","max_line_length":109,"num_lines":113,"path":"/Foursquare research/Projects/Venues details/tutorial/spiders/scraper.py","repo_name":"Zheng392/Python-Repository","src_encoding":"UTF-8","text":"import scrapy\nimport json\nimport re\nfrom scrapy import Selector\nfrom tutorial.items import *\nfrom urllib.parse import urlencode\nimport yaml\nimport json\nimport pandas as pd\nimport numpy as np\nimport re\n\ndef get_delta(lower, upper, length):\n return (upper - lower) / length\n\nclass scraper(scrapy.Spider):\n name = \"scraper\"\n # base_url = \"http://www.tripadvisor.cn\"\n # start_urls = [\n # base_url + \"/Hotels-g297463-Chengdu_Sichuan-Hotels.html\"\n # ]\n with open(\"config.yaml\", \"r\") as f:\n cfg = yaml.load(f)\n search_params = {\n 'client_id': cfg['client_id'],\n 'client_secret': cfg['client_secret'],\n 'v': '20180218'\n }\n start_urls = []\n\n df=pd.read_csv('data.csv',encoding='utf-8')\n df=df.sort_values(by='checkinsCount',ascending=False)\n ids=list(df['id'][0:500].values)\n for id in ids:\n url = 'https://api.foursquare.com/v2/venues/{}'.format(id) + '?' + urlencode(search_params)\n start_urls.append(url)\n\n\n def __init__(self):\n\n self.venue_ids = set()\n self.allVenues = []\n self.search_count=0\n with open(\"config.yaml\", \"r\") as f:\n cfg = yaml.load(f)\n self.photosParams = {\n 'client_id': cfg['client_id'],\n 'client_secret': cfg['client_secret'],\n 'v': '20180218',\n \"limit\": 200\n\n }\n self.tipsParams = {\n 'client_id': cfg['client_id'],\n 'client_secret': cfg['client_secret'],\n 'v': '20180218',\n \"limit\":200\n }\n\n\n def parse(self, response):\n\n if 'venue' in json.loads(response.body)['response']:\n venue = json.loads(response.body)['response']['venue']\n photosNum=venue['photos']['count']\n tipsNum=venue['stats']['tipCount']\n venuesItemInsta=venuesItem()\n venuesItemInsta['venue']=venue\n yield venuesItemInsta\n\n self.search_count += 1\n print(\"search count: {}; \".format(self.search_count))\n\n for photosCount in range(int(photosNum/200)+1):\n self.photosParams.update({\"offset\":200*photosCount})\n yield scrapy.Request(url=response.url.split('?')[0]+'/photos?'+ urlencode(self.photosParams),\n callback=self.ParsePhotos)\n\n\n for tipsCount in range(int(tipsNum/200)+1):\n self.tipsParams.update({\"offset\":200*tipsCount})\n yield scrapy.Request(url=response.url.split('?')[0]+'/tips?'+ urlencode(self.tipsParams),\n callback=self.ParseTips)\n\n\n\n def ParsePhotos(self, response):\n if 'photos' in json.loads(response.body)['response']:\n photos=json.loads(response.body)['response']['photos']['items']\n id=re.search('(venues/)(.*?)(/photo)',response.url).group(2)\n for photo in photos:\n photosItemInst=photosItem()\n photosItemInst['photo']=photo\n photosItemInst['id']=id\n yield photosItemInst\n\n self.search_count += 1\n print(\"search count: {}; \".format(self.search_count))\n\n\n\n def ParseTips(self, response):\n if 'tips' in json.loads(response.body)['response']:\n tips=json.loads(response.body)['response']['tips']['items']\n id=re.search('(venues/)(.*?)(/tips)',response.url).group(2)\n for tip in tips:\n tipsItemInst=tipsItem()\n tipsItemInst['tip']=tip\n tipsItemInst['id']=id\n yield tipsItemInst\n\n self.search_count += 1\n print(\"search count: {}; \".format(self.search_count))"},{"alpha_fraction":0.6243761777877808,"alphanum_fraction":0.6401151418685913,"avg_line_length":29.296510696411133,"blob_id":"41825925840ffb892c9040704d77eb2563550e5f","content_id":"b710477c2ac06d1b0b48f8ae1e9d9669e57db93d","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":5472,"license_type":"no_license","max_line_length":191,"num_lines":172,"path":"/Foursquare research/Projects/Data analysis/main.py","repo_name":"Zheng392/Python-Repository","src_encoding":"UTF-8","text":"#!/usr/bin/env python3\n# -*- coding: utf-8 -*-\n\nimport json\nimport pandas as pd\nimport numpy\nimport pickle\n\n#一个用户可能在一个景点发很多图片，后缀ByPhotos表示按图片统计，ByVenues表示按景点统计，\nvenue_id=[] #景点ID\ncategories=[] #标签的景点数\ncategories_num=[] #景点的标签数\nuserVenueByPhotos=[] #照片的user,景点\ntip_user=[] #tip的user,景点\nusrByPhotos=[]\nplaByPhotos=[]\nuserid=[] #大于10的用户ID\nvenueid=[] #大于10的地点ID\nfolders=['1-500','500-2000','2000-5000','5000-10000','Supplements']\nphotos=[]\n'''\nfor m in folders:\n # with open('venues'+str(m)+'.json','r',encoding=\"utf8\") as file:\n # for line in file.readlines():\n # venue=json.loads(line)['venue']\n # for i in range(0, len(venue['categories'])):\n # categories.append(venue['categories'][i]['id'])\n # categories_num.append(len(venue['categories']))\n # venue_id.append(venue['id'])\n\n with open(m+'/photosData.json','r',encoding=\"utf8\") as file:\n for line in file.readlines():\n userVenueByPhotos.append([json.loads(line)['photo']['user']['id'],json.loads(line)['id']])\n usrByPhotos.append(json.loads(line)['photo']['user']['id'])\n plaByPhotos.append(json.loads(line)['id'])\n photos.append(json.loads(line)['photo']['id'])\n print(\"load %s successfully\"%{m})\n\n'''\n\n# with open('params.sav', 'wb') as f:\n# pickle.dump([userVenueByPhotos,usrByPhotos,plaByPhotos,photos], f, -1)\n\nprint('save params successfully')\nparams=[]\nwith open('params.sav', 'rb') as f:\n tmp = pickle.load(f)\n userVenueByPhotos, usrByPhotos, plaByPhotos,photos=tmp\nuserVenueByVenues=set() # 用户景点set\nfor pu in userVenueByPhotos:\n pu=tuple(pu)\n userVenueByVenues.add(pu)\n\nusersByVenues=[]\nfor m in userVenueByVenues:\n usersByVenues.append(m[0])\n\n\nuserNumByVenues=list(zip(*numpy.unique(usersByVenues, return_counts=True)))\nuserNumByPhotos=list(zip(*numpy.unique(usrByPhotos, return_counts=True)))\nplaNumByPhotos=list(zip(*numpy.unique(plaByPhotos, return_counts=True)))\n\n#筛选出去过景点数大于20（即图片数肯定更多）的用户\nfor p in range(1,len(userNumByVenues)):\n if userNumByVenues[p][1] >=20:\n userid.append(userNumByVenues[p][0])\n\n\n#再筛选出图片数大于x的景点\nfor p in range(1,len(plaNumByPhotos)):\n if plaNumByPhotos[p][1] >=50:\n venueid.append(plaNumByPhotos[p][0])\n\n\n\n\n# print(dict(zip(*numpy.unique(categories, return_counts=True)))) #标签的景点数\n# print(dict(zip(*numpy.unique(categories_num, return_counts=True))))#景点的标签数\n# lab=dict(zip(*numpy.unique(categories, return_counts=True))).values()\n# print(lab)\n\n\n\nuserVenueByPhotos=numpy.array(userVenueByPhotos)\nuser_label=numpy.unique(userVenueByPhotos[:,0])\nvenue_label=numpy.unique(userVenueByPhotos[:,1])\na=list(zip(*numpy.unique(userVenueByPhotos[:,0], return_counts=True)))\nb=list(zip(*numpy.unique(userVenueByPhotos[:,1], return_counts=True)))\na=numpy.array(a)[:,1]\nb=numpy.array(b)[:,1]\na=list(zip(*numpy.unique(a, return_counts=True)))\nb=list(zip(*numpy.unique(b, return_counts=True)))\na=numpy.array(a)\nb=numpy.array(b)\na1=list(a[:,0])\na2=list(a[:,1])\nb1=list(b[:,0])\nb2=list(b[:,1])\n\n\n\nfile_obj = open(\"distribution.txt\", 'w')\nfor num in a1:\n file_obj.writelines(num)\n file_obj.writelines(', ')\nfile_obj.write('\\n\\n')\nfor num in a2:\n file_obj.writelines(num)\n file_obj.writelines(', ')\nfile_obj.write('\\n')\nfile_obj.write('\\n')\nfor num in b1:\n file_obj.writelines(num)\n file_obj.writelines(', ')\nfile_obj.write('\\n\\n')\nfor num in b2:\n file_obj.writelines(num)\n file_obj.writelines(', ')\nfile_obj.write('\\n')\n\nfile_obj.close()\n\n\n# with open('tipsData.json','r',encoding=\"utf8\") as file:\n# for line in file.readlines():\n# tip_user.append([json.loads(line)['tip']['user']['id'], json.loads(line)['id']])\n#\n# tip_user=numpy.array(tip_user)\n# user_label=numpy.unique(tip_user[:,0])\n# venue_label=numpy.unique(tip_user[:,1])\n# print('tip')\n# print(len(user_label))\n# print(len(venue_label))\n\n'''\nmatrix=numpy.zeros((len(user_label),len(venue_label)))\nprint(numpy.sum(matrix))\n\n\nfor k in range(0,len(tip_user)):\n data=tip_user[k]\n i=user_label.tolist().index(data[0])\n j=venue_label.tolist().index(data[1])\n matrix[i,j]=matrix[i,j]+1\nprint(numpy.sum(matrix))\n'''\n\n\n# df=pd.DataFrame(matrix,columns=venue_label,index=user_label)\n# df.to_csv('Data analysis result.csv')\n\n\n\nn=0\nnn=0\nfile_write_obj = open(\"photo,user,venue,time.txt\", 'w')\nfor m in folders:\n with open(m+'/photosData.json','r',encoding=\"utf8\") as file:\n for line in file.readlines():\n nn = nn + 1\n if json.loads(line)['photo']['user']['id'] in userid:\n if json.loads(line)['id'] in venueid:\n puvt = json.loads(line)['photo']['id'] +', '+ json.loads(line)['photo']['user']['id'] + ', '+ json.loads(line)['id'] + ', ' + str(json.loads(line)['photo']['createdAt'])\n file_write_obj.writelines(puvt)\n file_write_obj.write('\\n')\n n=n+1\n print(\"secondly load %s successfully\" % {m})\nprint('地点剩余 ',len(venueid),'/',len(plaNumByPhotos))\nprint('用户剩余 ',len(userid),'/',len(userNumByPhotos))\nprint('photo剩余 ',n,'/',nn)\nfile_write_obj.close()\nprint('稀疏性=',1-(n/(len(userid)*len(venueid))))"},{"alpha_fraction":0.4955223798751831,"alphanum_fraction":0.5671641826629639,"avg_line_length":29.363636016845703,"blob_id":"453b55f905a9119fbc50d92dd6022119826e91c3","content_id":"cd3cf100b621f63d17179436b1433ebb3f7ef7f8","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":335,"license_type":"no_license","max_line_length":61,"num_lines":11,"path":"/Spider/Jindong review data by Scrapy/jdcomment/jd_spider/test.py","repo_name":"Zheng392/Python-Repository","src_encoding":"UTF-8","text":"from urllib.parse import urlencode\ndata = {\n 'callback': 'fetchJSON_comment98vv61',\n 'productId': '3555984',\n 'score': 0, # all 0 bad 1 mid 2 good 3 zhuiping 5\n 'sortType': 5, # time series rank 6 recommend rank 5\n 'pageSize': 10,\n 'isShadowSku': 0,\n 'page': 0\n }\nurlencode(data)\n\n"},{"alpha_fraction":0.8108108043670654,"alphanum_fraction":0.8108108043670654,"avg_line_length":36.5,"blob_id":"02795151a3dc1db3a058f14401ccffd488ab4fe6","content_id":"a3ace824bd6fd39a3d39e0c2044f6838054ca10d","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":74,"license_type":"permissive","max_line_length":47,"num_lines":2,"path":"/Foursquare research/Projects/Get venues/execute.py","repo_name":"Zheng392/Python-Repository","src_encoding":"UTF-8","text":"from scrapy import cmdline\ncmdline.execute('scrapy crawl scraper'.split())"},{"alpha_fraction":0.6770491600036621,"alphanum_fraction":0.6811475157737732,"avg_line_length":30.30769157409668,"blob_id":"856e20f356dd19bd8f3dacd503e2f9155984ecc6","content_id":"17ad6c538eb3e65bed741c25bcfee149589f2e08","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1220,"license_type":"no_license","max_line_length":120,"num_lines":39,"path":"/Foursquare research/Projects/Venues details/Data analysis.py","repo_name":"Zheng392/Python-Repository","src_encoding":"UTF-8","text":"#!/usr/bin/env python3\n# -*- coding: utf-8 -*-\nimport json\nimport pandas as pd\nimport numpy as np\nvenues=[]\nids=set()\nvenueLine=[]\nphotos=[]\ntips=[]\nwith open('venues.json','r',encoding=\"utf8\") as f:\n for line in f.readlines():\n venue=json.loads(line)['venue']\n venues.append([venue['id'],venue['stats']['tipCount'],venue['stats']['checkinsCount'],venue['photos']['count']])\n ids.add(venue['id'])\n\nwith open('photosData.json','r',encoding=\"utf8\") as f:\n for line in f.readlines():\n photo=json.loads(line)['id']\n photos.append(photo)\n\nwith open('tipsData.json','r',encoding=\"utf8\") as f:\n for line in f.readlines():\n tip=json.loads(line)['id']\n tips.append(tip)\n\nphotosSeries=pd.Series(photos)\nphotosScraperCount=photosSeries.value_counts()\n\ntipsSeries=pd.Series(tips)\ntipsScraperCount=tipsSeries.value_counts()\n\ndf=pd.DataFrame(np.array(venues),columns=['id','tipsCount','checkinsCount','photosCount'])\ndf=df.set_index('id')\ndf=pd.merge(df, pd.DataFrame(tipsScraperCount), left_index=True, right_index=True, how='outer')\ndf=pd.merge(df, pd.DataFrame(photosScraperCount), left_index=True, right_index=True, how='outer')\n\ndf.to_csv('Data analysis result.csv')\npass"},{"alpha_fraction":0.6166666746139526,"alphanum_fraction":0.6166666746139526,"avg_line_length":31.384614944458008,"blob_id":"d9d21fd5f44f61ae0a71eddbceda80537fbc265a","content_id":"ae2c680449c4ba9a1b54e6a0f1da24c613b4f574","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":420,"license_type":"no_license","max_line_length":115,"num_lines":13,"path":"/Foursquare research/Projects/Venues details/README.md","repo_name":"Zheng392/Python-Repository","src_encoding":"UTF-8","text":"# Venues details\n\nGet detailed data for venues, including tips and photos of venues.\n\n\n\n## Output\n\nphotosData.json: Every line stands for a photo and the format of a line is {\"photo\": {.........}, \"id\": \".......\"}\n\ntipsData.json: Every line stands for a tip and the format of a line is {\"tip\": {.........}, \"id\": \".......\"}\n\nvenues.json: Every line stands for a venue and the format of a line is {\"venue\": {.........}}"},{"alpha_fraction":0.593879222869873,"alphanum_fraction":0.6253101825714111,"avg_line_length":45.5,"blob_id":"a8ca9f2f118a5cf6b5c48581ff355b0497c5edc0","content_id":"01a6db8835815a634e1e88d88f4f672cab76e182","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1209,"license_type":"no_license","max_line_length":184,"num_lines":26,"path":"/Spider/XieCheng Hotel Data/hotel_index_data/hotel_index_data/spiders/hotel_index_data.py","repo_name":"Zheng392/Python-Repository","src_encoding":"UTF-8","text":"\nfrom scrapy.spiders import Spider\nfrom scrapy import *\nfrom scrapy.selector import Selector\nimport re\nimport json\nimport xlrd\nimport sys\nimport re\nfrom urllib.parse import urlencode\nclass hotel_index_data(Spider):\n name='hotel_index_data'\n def start_requests(self):\n url = \"https://hotels.ctrip.com/Domestic/Tool/AjaxHotelList.aspx\"\n data = {'page': '1', 'cityPY': 'shanghai', 'cityId': '2', 'cityCode': '021',\n\n }\n headers = {'Referer': 'http://hotels.ctrip.com/hotel/shanghai2',\n 'Accept': '* / *', 'Accept-Encoding': 'gzip, deflate', 'Accept-Language': 'en-US,en;q=0.9', 'Cache-Control': 'max-age=0',\n 'Content-Type': 'application/x-www-form-urlencoded; charset=UTF-8', 'Host': 'hotels.ctrip.com', 'Origin': 'http://hotels.ctrip.com',\n 'Proxy-Connection': 'keep-alive', 'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/62.0.3202.75 Safari/537.36',\n }\n yield Request(url, self.parse, method=\"POST\", headers=headers, body=json.dumps(data))\n\n def parse(self, response):\n data = json.loads(response.body)\n print(data)"},{"alpha_fraction":0.747474730014801,"alphanum_fraction":0.7575757503509521,"avg_line_length":15.5,"blob_id":"e10fd64787c467768c4bc097262d4007ed9a12c5","content_id":"a8431a2ced2cd5b4a1423bff74287b37b595b8bb","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":99,"license_type":"no_license","max_line_length":42,"num_lines":6,"path":"/Spider/Jindong review data by Scrapy/jd_spider-fundamental/jd_spider/exec.py","repo_name":"Zheng392/Python-Repository","src_encoding":"UTF-8","text":"# coding:utf-8\n\nfrom scrapy import cmdline\nimport json\n\ncmdline.execute(\"scrapy crawl jd\".split())\n"},{"alpha_fraction":0.5968858003616333,"alphanum_fraction":0.5968858003616333,"avg_line_length":35.1875,"blob_id":"26d3cc23ac27e9fe3359dd14d32fabfc5bc72af8","content_id":"58c89c816a7f7baa72f383a5c846a01331e03934","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":578,"license_type":"permissive","max_line_length":107,"num_lines":16,"path":"/Foursquare research/Projects/Get venues/Data analysis.py","repo_name":"Zheng392/Python-Repository","src_encoding":"UTF-8","text":"import json\nimport pandas as pd\nimport numpy as np\nvenues=[]\nids=set()\nwith open('venues.json','r') as f:\n for line in f.readlines():\n venue=json.loads(line)['venue']\n venues.append([venue['id'],venue['name'],venue['stats']['tipCount'],venue['stats']['usersCount'],\n venue['stats']['checkinsCount'],venue['location']['lat'],\n venue['location']['lng']])\n ids.add(venue['id'])\n\ndf=pd.DataFrame(np.array(venues),columns=['id','name','tipCount','usersCount','checkinsCount','lat','lng'])\ndf.to_csv('data.csv')\npass"},{"alpha_fraction":0.6331658363342285,"alphanum_fraction":0.6633166074752808,"avg_line_length":21.11111068725586,"blob_id":"a6e53ad428ec2ba53a5ae3926986896be3c7f846","content_id":"ecb5c521ffc1b5b8e16da91bff4d38fce896f0ac","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":199,"license_type":"no_license","max_line_length":49,"num_lines":9,"path":"/Foursquare research/Projects/Small Dataset creating/Get part lines.py","repo_name":"Zheng392/Python-Repository","src_encoding":"UTF-8","text":"lines=[]\nwith open('photo,user,venue,time.txt','r') as f:\n\tfor i in range(5000):\n\t\tlines.append(f.readline())\n\n\nwith open('photo,user,venue,time.txt','w') as f2:\n\tfor line in lines:\n\t\tf2.write(line)\n"},{"alpha_fraction":0.7524116039276123,"alphanum_fraction":0.7524116039276123,"avg_line_length":17.235294342041016,"blob_id":"430c2484df751b2c57df444f72b3af9399a2dbdf","content_id":"9a994ebe5d64a1cb60359b52804ab6d461ee433a","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":365,"license_type":"no_license","max_line_length":76,"num_lines":17,"path":"/README.md","repo_name":"Zheng392/Python-Repository","src_encoding":"UTF-8","text":"# Python Repository\n\nCollections of my code in python.\n\nNote：This repository is only used to backup my code，not for version control.\n\n## Contents\n\n*tutorial*: a Scrapy project for Build a spider project quickly\n\n*download pdf*: 自动批量下载文献\n\n*HTML-to-PDF*: 将HTML-to-PDF转成pdf\n\n*Spider*: 曾经用过的爬虫\n\n*Gamepad*: 游戏手柄控制器\n\n"},{"alpha_fraction":0.8072289228439331,"alphanum_fraction":0.8072289228439331,"avg_line_length":41,"blob_id":"00e3df1627d25380665c38bdc9f6163f2b9b877e","content_id":"1d1aa085b42a66a14cd9a8a6b5d64bb58bc328fb","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":83,"license_type":"no_license","max_line_length":56,"num_lines":2,"path":"/Spider/XieCheng Hotel Data/hotel_index_data/begin.py","repo_name":"Zheng392/Python-Repository","src_encoding":"UTF-8","text":"from scrapy import cmdline\ncmdline.execute('scrapy crawl hotel_index_data'.split())"},{"alpha_fraction":0.529335081577301,"alphanum_fraction":0.5874034762382507,"avg_line_length":41.78969955444336,"blob_id":"1d000445cfdba6dfb231072aff6f1d47eb7b7b08","content_id":"8e85ec38e9cf507e4413a8e3f5bc5edd82847ed9","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":10981,"license_type":"no_license","max_line_length":189,"num_lines":233,"path":"/Spider/XieCheng Hotel Data/Requests_threading/hotel_data_threading.py","repo_name":"Zheng392/Python-Repository","src_encoding":"UTF-8","text":"import requests,json,random\nimport re,threading\nimport json\nfrom lxml import etree\nimport time\nimport random\nlock=threading.Lock()\n\ncity='shanghai'\nunsucesspage=[]\nproxies=[]\n# user_agent_list = [\n# \"Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/537.1 (KHTML, like Gecko) Chrome/22.0.1207.1 Safari/537.1\" ,\\\n# \"Mozilla/5.0 (X11; CrOS i686 2268.111.0) AppleWebKit/536.11 (KHTML, like Gecko) Chrome/20.0.1132.57 Safari/536.11\", \\\n# \"Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/536.6 (KHTML, like Gecko) Chrome/20.0.1092.0 Safari/536.6\", \\\n# \"Mozilla/5.0 (Windows NT 6.2) AppleWebKit/536.6 (KHTML, like Gecko) Chrome/20.0.1090.0 Safari/536.6\", \\\n# \"Mozilla/5.0 (Windows NT 6.2; WOW64) AppleWebKit/537.1 (KHTML, like Gecko) Chrome/19.77.34.5 Safari/537.1\", \\\n# \"Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/536.5 (KHTML, like Gecko) Chrome/19.0.1084.9 Safari/536.5\", \\\n# \"Mozilla/5.0 (Windows NT 6.0) AppleWebKit/536.5 (KHTML, like Gecko) Chrome/19.0.1084.36 Safari/536.5\", \\\n# \"Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/536.3 (KHTML, like Gecko) Chrome/19.0.1063.0 Safari/536.3\", \\\n# \"Mozilla/5.0 (Windows NT 5.1) AppleWebKit/536.3 (KHTML, like Gecko) Chrome/19.0.1063.0 Safari/536.3\", \\\n# \"Mozilla/5.0 (Macintosh; Intel Mac OS X 10_8_0) AppleWebKit/536.3 (KHTML, like Gecko) Chrome/19.0.1063.0 Safari/536.3\", \\\n# \"Mozilla/5.0 (Windows NT 6.2) AppleWebKit/536.3 (KHTML, like Gecko) Chrome/19.0.1062.0 Safari/536.3\", \\\n# \"Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/536.3 (KHTML, like Gecko) Chrome/19.0.1062.0 Safari/536.3\", \\\n# \"Mozilla/5.0 (Windows NT 6.2) AppleWebKit/536.3 (KHTML, like Gecko) Chrome/19.0.1061.1 Safari/536.3\", \\\n# \"Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/536.3 (KHTML, like Gecko) Chrome/19.0.1061.1 Safari/536.3\", \\\n# \"Mozilla/5.0 (Windows NT 6.1) AppleWebKit/536.3 (KHTML, like Gecko) Chrome/19.0.1061.1 Safari/536.3\", \\\n# \"Mozilla/5.0 (Windows NT 6.2) AppleWebKit/536.3 (KHTML, like Gecko) Chrome/19.0.1061.0 Safari/536.3\", \\\n# \"Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/535.24 (KHTML, like Gecko) Chrome/19.0.1055.1 Safari/535.24\", \\\n# \"Mozilla/5.0 (Windows NT 6.2; WOW64) AppleWebKit/535.24 (KHTML, like Gecko) Chrome/19.0.1055.1 Safari/535.24\"\n# ]\nuser_agent_list = [\n'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/62.0.3202.89 Safari/537.36'\n\n ]\n\ncount=0\ndef header_body_update(page):\n data = {'cityPY': 'shanghai', 'cityId': 2, 'cityCode': '021','page':page}\n headers = {'Referer': 'https://hotels.ctrip.com/hotel/shanghai2/sl1274819', \"Host\": \"hotels.ctrip.com\",\n 'Origin':'http://hotels.ctrip.com',\n \"Accept-Language\": \"en-US,en;q=0.9\",\n \"Connection\": \"keep-alive\",\n 'Accept': '* / *',\n \"Accept-Encoding\": \"gzip, deflate\",\n 'Cache-Control':'max-age=0',}\n \n headers['User-Agent'] = random.choice(user_agent_list)\n return headers,data\ndef proxy_update():\n ip=random.sample(proxies,1)[0].replace('\\n','')\n http='http://'+ip\n proxy={'http' : http,\n 'https': http}\n\n return proxy\ndef get_page():\n headers, data = header_body_update(1)\n se=[]\n while 1:\n try:\n proxy = proxy_update()\n hotel_list_requests = requests.post('https://hotels.ctrip.com/Domestic/Tool/AjaxHotelList.aspx', data=data,\n headers=headers,proxies=proxy)#\n hotel_info = eval(hotel_list_requests.text)\n text = hotel_info['paging']\n se = etree.HTML(text)\n page_number=json.loads(se.xpath('//a[@rel=\"nofollow\"]/text()')[0])\n\n break\n except Exception as e:\n print(e)\n\n \n return page_number\n\ndef fang_com(page): ##列表页\n # print('page is ',page)\n headers,data=header_body_update(page)\n prices=[]\n hotel_lists=[]\n fail_try=10\n while(fail_try): ###这个主要是，fang.com会随机返回几个10054或者10053，如果连页面都没读取到，提取就是后话了，这网站没有封杀，即使使用单ip只会很少时候随机来几个10054 ，('Connection aborted.', error(10054, ''))\n hotel_info={}\n try:\n proxy = proxy_update()\n hotel_list_requests=requests.post('https://hotels.ctrip.com/Domestic/Tool/AjaxHotelList.aspx', data=data,\n headers=headers)#,timeout=2,proxies=proxy\n text=hotel_list_requests.text\n \n hotel_info=eval(text)\n prices = json.loads(hotel_info['HotelMaiDianData']['value']['htllist'])\n hotel_lists = hotel_info['hotelPositionJSON']\n for hotel, price in zip(hotel_lists, prices):\n hotel.update(price)\n\n line = json.dumps(hotel) + '\\n'\n file.write(line)\n print(hotel_lists)\n print('success',page)\n break\n #print text\n except Exception as e:\n print(e)\n fail_try=fail_try-1\n if fail_try==0:\n print('unsuccess page',page)\n\n\n\n\n time.sleep(1)\n\n # lock.acquire()\n # print(hotel_lists)\n # lock.release()\n\n'''\n text=''\n se = etree.HTML(text) ###########为了利于大家学习，这段演示xpath提取信息\n all_dl=se.xpath('//dl[@class=\"list rel\"]')\n print(len(all_dl))\n for dl in all_dl:\n title=dl.xpath('.//dd[@class=\"info rel floatr\"]/p[@class=\"title\"]/a/text()')[0]\n url=dl.xpath('.//dd[@class=\"info rel floatr\"]/p[@class=\"title\"]/a/@href')[0]\n url='http://esf.sz.fang.com'+url\n\n info_list=dl.xpath('.//dd[@class=\"info rel floatr\"]/p[@class=\"mt12\"]/text()')\n #print json.dumps(info,ensure_ascii=False) #py2显示汉字，py3可以直接print mt12\n info=''\n for l in info_list:\n l2= re.findall('\\S*',l)[0] ###消除空白和换行\n #print m_str\n info+=l2+'|'\n\n time.sleep(1)\n # total_price,price_squere,huxin,cankao_shoufu,shiyong_mianji,jianzhu_mianji,years,discription=get_detail(url)\n\n\n lock.acquire() ###这里叫锁，一是保证count计数准确，而是不会导致多个线程乱print，导致看不清楚。加锁的目的是别的线程不能运行这段代码了。但我之前看到有的人乱加锁，把消耗时间很长的代码加锁，那样导致多线程就基本个废物\n global count\n count+=1\n print(time.strftime('%H:%M:%S', time.localtime(time.time())), ' ', count)\n print('列表页：')\n print(' title: %s\\n url: %s\\n info: %s\\n' % (title, url, info))\n\n print('详情页:')\n # print(\n # ' total_price: %s\\n price_squere: %s\\n huxin: %s\\n cankao_shoufu: %s\\n shiyong_mianji: %s\\n jianzhu_mianji: %s\\n years: %s \\n' % (\n # total_price, price_squere, huxin, cankao_shoufu, shiyong_mianji, jianzhu_mianji, years))\n print('**************************************************************')\n lock.release()\n\n'''\n\ndef get_detail(url): ###详情页\n\n header={'User-Agent':random.choice(user_agent_list)}\n header.update({\"Host\":\"esf.sz.fang.com\"})\n\n while(1):\n content=''\n try:\n content=requests.get(url,headers=header,timeout=10).content\n except Exception as e:\n print(e)\n pass\n if content!='':\n break\n\n content=content.decode('gbk').encode('utf8') ##查看网页源代码可看到是gbk编码，直接print的话，如果你在pycharm设置控制台是utf8编码，那么控制台的中文则会乱码，cmd是gbk的恰好可以显示。如果你在pycharm设置控制台是utf8编码，需要这样做\n #print content\n\n inforTxt=getlist0(re.findall('(
- \n\t{% if health_profile %}\n\t\n\t
Following is your health profile
\n\t\n\t\t
\n\t\t\t
\n\t{% else %}\n\t\t\n\t\t\t\t\n\t\t\t\t \n\t\t\t\t
\n\t\t\t
\n\t\t\t| Attribute | \n\t\t\t\tValue | \n\t\t\t\t||
|---|---|---|---|
| Age | \n\t\t\t\t{{health_profile.age}} | \n\t\t\t\t||
| Height | \n\t\t\t\t{{health_profile.height}} | \n\t\t\t\t||
| Weight | \n\t\t\t\t{{health_profile.weight}} | \n\t\t\t\t||
| Ailments | \n\t\t\t\t{{health_profile.ailments}} | \n\t\t\t\t||
| Health Care Costs (per year) | \n\t\t\t\t{{health_profile.healthcare_costs}} | \n\t\t\t\t||
| Tobacco | \n\t\t\t\t{{health_profile.tobacco}} | \n\t\t\t\t||
| Smoke | \n\t\t\t\t{{health_profile.smoke}} | \n\t\t\t\t||
| Drink | \n\t\t\t\t{{health_profile.drink}} | \n\t\t\t\t||
| Exercise | \n\t\t\t\t {% if health_profile.exercise == 2 %}\n\t\t\t\t \t>15 hours/week | \n\t\t\t\t {% elif health_profile.exercise == 1 %}\n\t\t\t\t \t6-15 hours/week | \n\t\t\t\t {% elif health_profile.exercise == 0 %}\n\t\t\t\t \t<6 hours/week | \n\t\t\t\t\t {% endif %}\n\t\t\t\t
| Travel | \n\t\t\t\t {% if health_profile.travel_time == 2 %}\n\t\t\t\t \t>10 hours/week | \n\t\t\t\t {% elif health_profile.travel_time == 1 %}\n\t\t\t\t \t5-10 hours/week | \n\t\t\t\t {% elif health_profile.travel_time == 0 %}\n\t\t\t\t \t<5 hours/week | \n\t\t\t\t\t {% endif %}\n\t\t\t\t
| Sleep | \n\t\t\t\t {% if health_profile.sleep_time == 2 %}\n\t\t\t\t \t>8 hours/day | \n\t\t\t\t {% elif health_profile.sleep_time == 1 %}\n\t\t\t\t \t6-8 hours/day | \n\t\t\t\t {% elif health_profile.sleep_time == 0 %}\n\t\t\t\t \t<6 hours/day | \n\t\t\t\t\t {% endif %}\n\t\t\t\t
| Job Type | \n\t\t\t\t{{health_profile.job_type}} | \n\t\t\t\t
\n\t\t\t\t
\n\t\t\n\t\t\t\t\t
\n\t\t\t\t\n\t\t\t\t\t\t
\n\t\t\t\t\t\n\t\t\t\t\t\t\t
\n\t\t\t\t\t\n\t\t\t\t\t\t\t\tHealth Score
\n\t\t\t\t\t\t\t
\n\t\t\t\t\t\t\tHealth Score
(out of 1000)
\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t
\n\t\t\t\t\t\t{{health_score}}
\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t
\n\t\t\t\t\n\t\t\t\t\t\t\t
\n\t\t\t\t\t\n\t\t\t\t\t\t\t\tPossible Savings
\n\t\t\t\t\t\t\t
\n\t\t\t\t\t\t\tPossible Savings
(per year)
\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t
\n\t\t\t\t\t\t${{savings}}
\n\t\t\t\t\t\t\t\n\t\t\t\t\t
\n\t\t\tRecommendations
\n\t\t\t\t\t\t
\n\t\t\t\t\t{% endfor %}\n\t\t\t\t{{r}}
\n\t\t\t\t\tPlease create your profile
\n\t\tCreate Profile\n\t{% endif %}\n\t- \\n\\t{% if health_profile %}\\n\\t\\n\\t
Following is your health profile
\\n\\t\\n\\t\\t
\\n\\t\\t\\t
\\n\\t{% else %}\\n\\t\\t\\n\\t\\t\\t\\t\\n\\t\\t\\t\\t \\n\\t\\t\\t\\t
\\n\\t\\t\\t
\\n\\t\\t\\t| Attribute | \\n\\t\\t\\t\\tValue | \\n\\t\\t\\t\\t||
|---|---|---|---|
| Age | \\n\\t\\t\\t\\t{{health_profile.age}} | \\n\\t\\t\\t\\t||
| Height | \\n\\t\\t\\t\\t{{health_profile.height}} | \\n\\t\\t\\t\\t||
| Weight | \\n\\t\\t\\t\\t{{health_profile.weight}} | \\n\\t\\t\\t\\t||
| Ailments | \\n\\t\\t\\t\\t{{health_profile.ailments}} | \\n\\t\\t\\t\\t||
| Health Care Costs (per year) | \\n\\t\\t\\t\\t{{health_profile.healthcare_costs}} | \\n\\t\\t\\t\\t||
| Tobacco | \\n\\t\\t\\t\\t{{health_profile.tobacco}} | \\n\\t\\t\\t\\t||
| Smoke | \\n\\t\\t\\t\\t{{health_profile.smoke}} | \\n\\t\\t\\t\\t||
| Drink | \\n\\t\\t\\t\\t{{health_profile.drink}} | \\n\\t\\t\\t\\t||
| Exercise | \\n\\t\\t\\t\\t {% if health_profile.exercise == 2 %}\\n\\t\\t\\t\\t \\t>15 hours/week | \\n\\t\\t\\t\\t {% elif health_profile.exercise == 1 %}\\n\\t\\t\\t\\t \\t6-15 hours/week | \\n\\t\\t\\t\\t {% elif health_profile.exercise == 0 %}\\n\\t\\t\\t\\t \\t<6 hours/week | \\n\\t\\t\\t\\t\\t {% endif %}\\n\\t\\t\\t\\t
| Travel | \\n\\t\\t\\t\\t {% if health_profile.travel_time == 2 %}\\n\\t\\t\\t\\t \\t>10 hours/week | \\n\\t\\t\\t\\t {% elif health_profile.travel_time == 1 %}\\n\\t\\t\\t\\t \\t5-10 hours/week | \\n\\t\\t\\t\\t {% elif health_profile.travel_time == 0 %}\\n\\t\\t\\t\\t \\t<5 hours/week | \\n\\t\\t\\t\\t\\t {% endif %}\\n\\t\\t\\t\\t
| Sleep | \\n\\t\\t\\t\\t {% if health_profile.sleep_time == 2 %}\\n\\t\\t\\t\\t \\t>8 hours/day | \\n\\t\\t\\t\\t {% elif health_profile.sleep_time == 1 %}\\n\\t\\t\\t\\t \\t6-8 hours/day | \\n\\t\\t\\t\\t {% elif health_profile.sleep_time == 0 %}\\n\\t\\t\\t\\t \\t<6 hours/day | \\n\\t\\t\\t\\t\\t {% endif %}\\n\\t\\t\\t\\t
| Job Type | \\n\\t\\t\\t\\t{{health_profile.job_type}} | \\n\\t\\t\\t\\t
\\n\\t\\t\\t\\t
\\n\\t\\t\\n\\t\\t\\t\\t\\t
\\n\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t
\\n\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\t
\\n\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\t\\tHealth Score
\\n\\t\\t\\t\\t\\t\\t\\t
\\n\\t\\t\\t\\t\\t\\t\\tHealth Score
(out of 1000)
\\n\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\t\\t
\\n\\t\\t\\t\\t\\t\\t{{health_score}}
\\n\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t
\\n\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\t
\\n\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\t\\tPossible Savings
\\n\\t\\t\\t\\t\\t\\t\\t
\\n\\t\\t\\t\\t\\t\\t\\tPossible Savings
(per year)
\\n\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\t\\t
\\n\\t\\t\\t\\t\\t\\t${{savings}}
\\n\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t
\\n\\t\\t\\tRecommendations
\\n\\t\\t\\t\\t\\t\\t
\\n\\t\\t\\t\\t\\t{% endfor %}\\n\\t\\t\\t\\t{{r}}
\\n\\t\\t\\t\\t\\tPlease create your profile
\\n\\t\\tCreate Profile\\n\\t{% endif %}\\n\\t[\\s\\S]*?)
- ',content)) ###########为了利于大家学习，这段演示正则表达式提取信息，某些信息可能在有的房子界面没有，要做好判断\n #print inforTxt\n\n total_price=getlist0(re.findall('价：(.*?)',inforTxt))\n\n price_squere=getlist0(re.findall('class=\"black\">万\\((\\d+?)元[\\s\\S]*?户型：(.*?)',inforTxt))\n cankao_shoufu=getlist0(re.findall('参考首付：(.*?万) ',inforTxt))\n shiyong_mianji=getlist0(re.findall('>使用面积：(.*?)',inforTxt))\n shiyong_mianji=getlist0(re.findall('\\d+',shiyong_mianji))\n jianzhu_mianji=getlist0(re.findall('建筑面积：(.*?)',inforTxt))\n jianzhu_mianji=getlist0(re.findall('\\d+',jianzhu_mianji))\n years=getlist0(re.findall('年代：(.*?)',inforTxt))\n\n discription=getlist0(re.findall('style=\"-moz-user-select: none;\">([\\s\\S]*?)
0):\n matrix=np.array(Alldata)\n cov=np.cov(matrix)\n sigma=(1/(i+1))**2*np.sum(cov)\n allsigma.append(sigma)\n # rng = pd.date_range(start='7/19/2016', end='10/18/2016', freq='20min')\n # rng = pd.DataFrame(pd.Series(rng), columns=[\"time_window\"]).set_index(\"time_window\")\n pass\n # data.to_excel('stock of %s.xlsx' % stock)\nallsigma=pd.Series(allsigma)\nallsigma.to_csv('sigma4.csv')\npass"},{"alpha_fraction":0.6072629690170288,"alphanum_fraction":0.614660382270813,"avg_line_length":26.054546356201172,"blob_id":"1b191d19ec29a71e98b26779431e49c40408bfe2","content_id":"9a38bd94cf96483ebe2e0764099e3e0ab2040f2e","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1815,"license_type":"no_license","max_line_length":51,"num_lines":55,"path":"/Spider/Jindong review data by Scrapy/jdcomment/jd_spider/items.py","repo_name":"Zheng392/Python-Repository","src_encoding":"UTF-8","text":"# -*- coding: utf-8 -*-\n\n# Define here the models for your scraped items\n#\n# See documentation in:\n# http://doc.scrapy.org/en/latest/topics/items.html\n\nimport scrapy\nfrom scrapy import Item, Field\n\n\nclass JdSpiderItem(scrapy.Item):\n # define the fields for your item here like:\n # name = scrapy.Field()\n pass\n\n\nclass goodsItem(Item):\n link = Field() # 商品链接\n ID = Field() # 商品ID\n name = Field() # 商品名字\n comment_num = Field() # 评论人数\n shop_name = Field() # 店家名字\n price = Field() # 价钱\n commentVersion = Field() # 为了得到评论的地址需要该字段\n score1count = Field() # 评分为1星的人数\n score2count = Field() # 评分为2星的人数\n score3count = Field() # 评分为3星的人数\n score4count = Field() # 评分为4星的人数\n score5count = Field() # 评分为5星的人数\n\n\nclass commentItem(Item):\n user_name = Field() # 评论用户的名字\n user_ID = Field() # 评论用户的ID\n userProvince = Field() # 评论用户来自的地区\n content = Field() # 评论内容\n good_ID = Field() # 评论的商品ID\n good_name = Field() # 评论的商品名字\n date = Field() # 评论时间\n replyCount = Field() # 回复数\n score = Field() # 评分\n status = Field() # 状态\n title = Field()\n userLevelId = Field()\n userRegisterTime = Field() # 用户注册时间\n productColor = Field() # 商品颜色\n productSize = Field() # 商品大小\n userLevelName = Field() # 银牌会员，钻石会员等\n userClientShow = Field() # 来自什么 比如来自京东客户端\n isMobile = Field() # 是否来自手机\n days = Field() # 天数\n commentTags = Field() # 标签\n usefulVoteCount=Field()\n uselessVoteCount=Field()"},{"alpha_fraction":0.5719166398048401,"alphanum_fraction":0.6498121023178101,"avg_line_length":29.5,"blob_id":"059b82e001ecfb34e1ccba9ff37638b6210c5318","content_id":"726e6e2e9f8e3845c404e7a3ec5d6c5019b88059","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":2927,"license_type":"no_license","max_line_length":173,"num_lines":96,"path":"/download pdf/test.py","repo_name":"Zheng392/Python-Repository","src_encoding":"UTF-8","text":"import requests\nfrom lxml import etree\nimport os\nimport re\nfrom selenium import webdriver\n\nfrom selenium.webdriver.chrome.options import Options\nfrom selenium.webdriver.common.by import By\nfrom selenium.webdriver.common.keys import Keys\nfrom selenium.webdriver.support import expected_conditions as EC\nfrom selenium.webdriver.support.wait import WebDriverWait\nimport json\nimport time\n\ndef get_html(url):\n headers={\n 'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/71.0.3578.98 Safari/537.36'\n }\n\n r=requests.get(url,headers=headers)\n # print(r.text)\n html=etree.HTML(r.text)\n result=html.xpath('//*[@id=\"article-list\"]/form/div[3]/ol/li/dl/dd[4]/a/@href')\n if result==[]:\n result = html.xpath('//*[@id=\"article-list\"]/form/div[3]/ol//ol/li/dl/dd[4]/a/@href')\n return result\n\ndef save_pdf(url,folder,name):\n headers = {\n 'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/71.0.3578.98 Safari/537.36'\n }\n if os.path.exists(folder+'/'+name+'.pdf'):\n return\n\n chrome_options = Options()\n # chrome_options.add_argument('--headless')\n # chrome_options.add_argument('--disable-gpu')\n browser = webdriver.Chrome(chrome_options=chrome_options)\n browser.get(url)\n # time.sleep(1)\n url=browser.current_url\n browser.close()\n\n r = requests.get(url, headers=headers)\n if not os.path.exists(folder):\n os.makedirs(folder)\n\n\n with open(folder+'/'+name+'.pdf','wb') as f:\n f.write(r.content)\n\n'''test download pdf\nurl='https://ac.els-cdn.com/S0306457315000242/1-s2.0-S0306457315000242-main.pdf?_tid=44624573-386b-4ebf-921c-825259bf4488&acdnat=1545467755_f582eab50ca643aeeb8c4ecf4756a951'\nsave_pdf(url,'test','aaa')\n\n'''\n\n'''test selenium\n\n\n\nbrowser= webdriver.Chrome()\nurl='https://www.sciencedirect.com/science/article/pii/S0306457315000242/pdfft?md5=abece181b57cc15e01f82237124b92d9&pid=1-s2.0-S0306457315000242-main.pdf'\nbrowser.get(url)\nprint(browser.current_url)\nbrowser.close()\npass\n\n\n'''\n\n\n\nif __name__=='__main__':\n links={}\n # for i in range(4):\n # for j in range(6):\n # url = 'https://www.sciencedirect.com/journal/information-processing-and-management/vol/%d/issue/%d'%(51+i,j+1)\n # links['vol%dissue%d'%(51+i,j+1)]=get_html(url)\n # print('get links of vol%d issue%d '%(51+i,j+1))\n\n\n # with open('data2.json','w') as file:\n # file.write(json.dumps(links))\n with open('data2.json','r') as file:\n links=json.loads(file.read())\n\n\n\n for i in range(4):\n for j in range(6):\n part=links['vol%dissue%d'%(51+i,j+1)]\n for l,u in enumerate(part):\n url='https://www.sciencedirect.com'+u\n save_pdf(url, 'vol%d/issue%d'%(51+i,j+1),str(l))\n print('save pdf of vol%d issue%d %d'%(51+i,j+1,l))"},{"alpha_fraction":0.517257571220398,"alphanum_fraction":0.5372152924537659,"avg_line_length":37.36936950683594,"blob_id":"0e6973e42970ffc8522495a3390f8e7696b488dc","content_id":"0ae5c4e8321d4e46010a291fc5ccae277e945aef","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":4435,"license_type":"no_license","max_line_length":119,"num_lines":111,"path":"/Spider/Jindong review data by Scrapy/jdcomment/jd_spider/spiders/jd_comment.py","repo_name":"Zheng392/Python-Repository","src_encoding":"UTF-8","text":"# -*- coding: utf-8 -*-\nfrom scrapy.spiders import Spider\nfrom jd_spider.items import goodsItem, commentItem\nfrom scrapy.selector import Selector\nimport re\nimport json\nimport xlrd\nimport sys\nimport re\nfrom urllib.parse import urlencode\nclass comment_spider(Spider):\n name = \"comment2\"\n IDs = []\n file = open(\"./data/women_cloth_data.json\", 'r')\n for line in file:\n line = line.strip()\n try: # try parsing to dict\n a = json.loads(line)\n IDs.append(a[\"ID\"])\n except:\n print(repr(line))\n print(sys.exc_info())\n print(\"fail\")\n file.close()\n url = 'https://club.jd.com/comment/skuProductPageComments.action'\n data = {\n 'callback': 'fetchJSON_comment98vv61',\n 'productId': '3555984',\n 'score': 0, # all 0 bad 1 mid 2 good 3 zhuiping 5\n 'sortType': 5, # time series rank 6 recommend rank 5\n 'pageSize': 10,\n 'isShadowSku': 0,\n 'page': 0\n }\n start_urls = []\n for ID in IDs:\n try:\n data[\"productId\"] = ID[0]\n except:\n pass\n for page in range(1,6):\n data['page']=page\n data['score'] = 1\n comb_url=url+'?'+urlencode(data)\n start_urls.append(comb_url)\n data['score'] = 3\n comb_url = url + '?' + urlencode(data)\n start_urls.append(comb_url)\n\n # name = \"comment2\"\n # xlrd.Book.encoding = \"utf-8\"\n # data = xlrd.open_workbook(\"goods.xls\")\n # # goods为要抓取评论的商品信息，现提供一个goods.xls文件供参考,第1列：商品ID；第2列：商品评论数；第3列：商品的commentVersion\n # # test.xlsx也可以使用\n # table = data.sheets()[0]\n # nrows = table.nrows # 行数\n # ncols = table.ncols # 列数\n # good_id = table.col_values(0) # 商品ID\n # comment_n = table.col_values(1) # 商品评论数\n # comment_V = table.col_values(2) # 商品评论的commentVersion\n #\n # start_urls = []\n # for i in range(len(good_id)): # 一件商品一件商品的抽取\n # good_num = int(good_id[i])\n # comment_total = int(comment_n[i])\n # if comment_total % 10 == 0: # 算出评论的页数，一页10条评论\n # page = comment_total/10\n # else:\n # page = comment_total/10 + 1\n # for k in range(0, int(page)):\n # url = \"http://sclub.jd.com/productpage/p-\" + str(good_num) + \"-s-0-t-3-p-\" + str(k) \\\n # + \".html?callback=fetchJSON_comment98vv\" #+ str(comment_V[i])\n # start_urls.append(url)\n\n def parse(self, response):\n m = re.search(r'(?<=fetchJSON_comment98vv61\\().*(?=\\);)', response.body.decode('gbk',errors='ignore')).group(0)\n j = json.loads(m)\n commentSummary = j['comments']\n items = []\n for comment in commentSummary:\n item1 = commentItem()\n item1['user_name'] = comment['nickname']\n item1['user_ID'] = comment['id']\n item1['userProvince'] = comment['userProvince']\n item1['content'] = comment['content'].replace('\\n','')\n item1['good_ID'] = comment['referenceId']\n item1['userClientShow'] = comment['userClientShow']\n item1['good_name'] = comment['referenceName']\n item1['date'] = comment['referenceTime']\n item1['replyCount'] = comment['replyCount']\n item1['score'] = comment['score']\n item1['uselessVoteCount']=comment[\"uselessVoteCount\"]\n item1['usefulVoteCount']=comment['usefulVoteCount']\n # item1['status'] = comment['status']\n # title = \"\"\n # if 'title'in comment:\n # item1['title'] = comment['title']\n # item1['title'] = title\n # item1['userRegisterTime'] = comment['userRegisterTime']\n # item1['productColor'] = comment['productColor']\n # item1['productSize'] = comment['productSize']\n # item1['userLevelName'] = comment['userLevelName']\n # item1['isMobile'] = comment['isMobile']\n # item1['days'] = comment['days']\n # tags = \"\"\n # if 'commentTags' in comment:\n # for i in comment['commentTags']:\n # tags = tags + i['name'] + \" \"\n # item1['commentTags'] = tags\n #items.append(item1)\n yield item1\n"},{"alpha_fraction":0.6158690452575684,"alphanum_fraction":0.6750629544258118,"avg_line_length":36.85714340209961,"blob_id":"ec9616fbfd35c88556bfdec01702a20333d427e1","content_id":"2d04b7d49c4aef5eff001761849af2330bc592b1","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":794,"license_type":"no_license","max_line_length":143,"num_lines":21,"path":"/Spider/Shanghai Stock Exchange data by requests/Shanghai Stock Exchange data.py","repo_name":"Zheng392/Python-Repository","src_encoding":"UTF-8","text":"import requests\n\nheaders = {'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/62.0.3202.75 Safari/537.36',\\\n 'Referer': 'http: // www.sse.com.cn / disclosure / dealinstruc / suspension /'\n}\npayload = {'jsonCallBack': 'vajsonpCallback68485', 'isPagination': 'true', 'bgFlag': '1', \\\n 'pageHelp.pageNo': '1', 'pageHelp.beginPage': '1'}\nparams={\"isPagination\": 'true','searchDate': \"\",'bgFlag': 1,\n'searchDo': 1,\\\n\"pageHelp.pageSize\": 1500,\\\n\"pageHelp.pageNo\": 1,\\\n\"pageHelp.beginPage\": 1,\\\n\"pageHelp.cacheSize\": 1,\\\n\"pageHelp.endPage\": 3,\\\n'desc':\"\",\\\n'pageCache':1\n}\nr=requests.get(url='http://query.sse.com.cn/infodisplay/querySpecialTipsInfoByPage.do',params=params,headers=headers)\nprint(r.headers)\nprint(r.json())\npass"},{"alpha_fraction":0.7878788113594055,"alphanum_fraction":0.7878788113594055,"avg_line_length":32,"blob_id":"b8809293153bdefe1586f9af408c426cd4528adf","content_id":"ca3f9ae8160644f4f026486100edc20477b818e9","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":63,"license_type":"no_license","max_line_length":32,"num_lines":1,"path":"/download pdf/README.md","repo_name":"Zheng392/Python-Repository","src_encoding":"UTF-8","text":"*rename.pdf*: 读取pdf获得文章名然后重命名文件。\n"},{"alpha_fraction":0.49803921580314636,"alphanum_fraction":0.505591869354248,"avg_line_length":39.26315689086914,"blob_id":"c47671c66f750881afcf4826adcb4c62293c4a59","content_id":"95f59b9533bb9430b50c9369d22f14ef1346eb19","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":6885,"license_type":"no_license","max_line_length":246,"num_lines":171,"path":"/Spider/Jindong review data by Scrapy/jdcomment/jd_spider/pipelines.py","repo_name":"Zheng392/Python-Repository","src_encoding":"UTF-8","text":"# -*- coding: utf-8 -*-\n\n# Define your item pipelines here\n#\n# Don't forget to add your pipeline to the ITEM_PIPELINES setting\n# See: http://doc.scrapy.org/en/latest/topics/item-pipeline.html\nimport pymysql.cursors\nimport json\n\nfrom twisted.enterprise import adbapi\n\nfrom scrapy.xlib.pydispatch import dispatcher\nfrom scrapy import signals\nfrom scrapy.utils.project import get_project_settings\nfrom scrapy import log\n# import chardet\n\nSETTINGS = get_project_settings()\n\n#\n# class MySQLPipeline(object):\n# @classmethod\n# def from_crawler(cls, crawler):\n# return cls(crawler.stats)\n#\n# def __init__(self, stats):\n# # Instantiate DB\n# self.file=open('phone_data.json', 'w', encoding='utf-8')\n# # self.dbpool = adbapi.ConnectionPool('pymysql',\n# # host=SETTINGS['DB_HOST'],\n# # user=SETTINGS['DB_USER'],\n# # passwd=SETTINGS['DB_PASSWD'],\n# # port=SETTINGS['DB_PORT'],\n# # db=SETTINGS['DB_DB'],\n# # charset='utf8',\n# # use_unicode=True,\n# # cursorclass=pymysql.cursors.DictCursor\n# # )\n# # self.stats = stats\n# # dispatcher.connect(self.spider_closed, signals.spider_closed)\n#\n# def spider_closed(self, spider):\n# print(\"done!!!\")\n#\n# \"\"\" Cleanup function, called after crawing has finished to close open\n# objects.\n# Close ConnectionPool. \"\"\"\n# # self.dbpool.close()\n#\n# def process_item(self, item, spider):\n# line=json.dumps(dict(item,ensure_ascii=False))+'\\n'\n# self.file.write(line)\n#\n# # query = self.dbpool.runInteraction(self._insert_record, item)\n# # query.addErrback(self._handle_error)\n# return item\n#\n# def _insert_record(self, tx, item):\n# ID = item['ID'][0]\n# name = item['name'][0]\n# comment_num = str(item['comment_num'])\n# shop_name = item['shop_name'][0]\n# link = item['link'][0]\n# commentVersion = str(item['commentVersion'])\n# commentVersion = commentVersion[1:-1]\n#\n# score1count = str(item['score1count'])\n# score2count = str(item['score2count'])\n# score3count = str(item['score3count'])\n# score4count = str(item['score4count'])\n# score5count = str(item['score5count'])\n#\n# price = str(item['price'])\n#\n# ID = ID.encode('utf-8')\n# name = name.encode('utf-8')\n# comment_num = comment_num.encode('utf-8')\n# shop_name = shop_name.encode('utf-8')\n# link = link.encode('utf-8')\n# commentVersion = commentVersion.encode('utf-8')\n# score1count = score1count.encode('utf-8')\n# score2count = score2count.encode('utf-8')\n# score3count = score3count.encode('utf-8')\n# score4count = score4count.encode('utf-8')\n# score5count = score5count.encode('utf-8')\n# price = price.encode('utf-8')\n#\n# sql = \"INSERT INTO jd_goods VALUES ('%s', '%s', '%s', '%s', '%s', '%s', '%s', '%s', '%s', '%s', '%s', '%s')\" % \\\n# (ID, name, comment_num, shop_name, link, commentVersion, score1count, score2count, score3count,\n# score4count, score5count, price)\n# tx.execute(sql)\n# print(\"yes\")\n#\n# def _handle_error(self, e):\n# log.err(e)\n\n\nclass CommentPipeline(object):\n # @classmethod\n # def from_crawler(cls, crawler):\n # return cls(crawler.stats)\n\n def __init__(self):\n self.count=0\n self.allline=[]\n self.file = open('women_cloth_comment.csv', 'w', encoding='utf-8')\n # Instantiate DB\n # self.dbpool = adbapi.ConnectionPool('pymysql',\n # host=SETTINGS['DB_HOST'],\n # user=SETTINGS['DB_USER'],\n # passwd=SETTINGS['DB_PASSWD'],\n # port=SETTINGS['DB_PORT'],\n # db=SETTINGS['DB_DB'],\n # charset='utf8',\n # use_unicode=True,\n # cursorclass=pymysql.cursors.DictCursor\n # )\n # self.stats = stats\n # dispatcher.connect(self.spider_closed, signals.spider_closed)\n\n def spider_closed(self, spider):\n \"\"\" Cleanup function, called after crawing has finished to close open\n objects.\n Close ConnectionPool. \"\"\"\n # self.dbpool.close()\n print(\"done2!!!\")\n def process_item(self, item, spider):\n # query = self.dbpool.runInteraction(self._insert_record, item)\n # query.addErrback(self._handle_error)\n self.count=self.count+1\n line = '0'+','+ str(item['score'])+','+ str(item['user_ID'])+','+ item['content'] +','+ str(item['good_ID']) +','+item['userClientShow'] +','+ str(item['replyCount'])+','+str(item['uselessVoteCount'])+','+str(item['usefulVoteCount'])+'\\n'\n if line not in self.allline:\n self.file.write(line)\n self.allline.append(line)\n else:\n print('repetition!!')\n\n print(\"scrapy item num is\",self.count)\n return item\n\n # def _insert_record(self, tx, item):\n # user_name = item['user_name']\n # user_ID = item['user_ID']\n # userProvince = item['userProvince']\n # content = item['content']\n # good_ID = item['good_ID']\n # good_name = item['good_name']\n # date = item['date']\n # replyCount = item['replyCount']\n # score = item['score']\n # status = item['status']\n # title = item['title']\n # userRegisterTime = item['userRegisterTime']\n # productColor = item['productColor']\n # productSize = item['productSize']\n # userLevelName = item['userLevelName']\n # isMobile = item['isMobile']\n # days = item['days']\n # tags = item['commentTags']\n #\n # sql = \"INSERT INTO jd_comment VALUES ('%s', '%s', '%s', '%s', '%s', '%s', '%s', '%s', '%s', '%s',\" \\\n # \"'%s', '%s', '%s', '%s', '%s', '%s', '%s', '%s')\" % \\\n # (user_name, user_ID, userProvince, content, good_ID, good_name, date, replyCount, score,\n # status, title, userRegisterTime, productColor, productSize, userLevelName,\n # isMobile, days, tags)\n #\n # tx.execute(sql)\n # print(\"yes\")\n\n def _handle_error(self, e):\n log.err(e)\n"},{"alpha_fraction":0.6912065148353577,"alphanum_fraction":0.6932515501976013,"avg_line_length":24.789474487304688,"blob_id":"26aae946ac43fbb6332cd83cd9d7fe97eb7c8116","content_id":"e8c2df4c789bb58cf88cced36a894ea507a466a3","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":489,"license_type":"no_license","max_line_length":73,"num_lines":19,"path":"/Spider/XieCheng Hotel Data/xiecheng selenium/text/xiechengservices/DriveServices.py","repo_name":"Zheng392/Python-Repository","src_encoding":"UTF-8","text":"# -*- coding:utf-8 -*-\n__author__ = 'LiuYang'\nfrom services.xiechengservices.DriveServices import XiechengDriverService\n\nclass DriverServiceTest(object):\n\n def __init__(self):\n self.xiechengDriverService = XiechengDriverService()\n\n def crawlxiechengTest(self):\n self.xiechengDriverService.start()\n self.xiechengDriverService.depose()\n\n\nif __name__ == \"__main__\":\n\n driverServiceTest = DriverServiceTest()\n\n driverServiceTest.crawlxiechengTest()"},{"alpha_fraction":0.6729399561882019,"alphanum_fraction":0.7105798721313477,"avg_line_length":25.945205688476562,"blob_id":"1dbf999423708fabeedc917859a42432eddfa9f3","content_id":"6a08ccaa9cf3a6d9e38e091733d8e392078af975","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":2384,"license_type":"no_license","max_line_length":74,"num_lines":73,"path":"/Spider/XieCheng Hotel Data/xiecheng selenium/README.md","repo_name":"Zheng392/Python-Repository","src_encoding":"GB18030","text":"xiecheng\n=================================\n\n众源时空信息聚合平台\n--------------------------\n\n##基本信息：\n\n基于scrapy+selenium的爬去策略，以南京市为例，抽取南京市酒店的基本信息数据与酒店点评数据
\n\n##使用Python 库：\n1.scrapy，网上安装方法许多，可自行下载相关依赖
\n\n2.selenium
\n可以直接使用pip进行安装
\n\nSelenium也是一个用于Web应用程序测试的工具。Selenium测试直接运行在浏览器中，就像真正的用户在操作一样。
\n\n\n##使用驱动:\n1.Chrome驱动
\n下载地址：http://npm.taobao.org/mirrors/chromedriver
\n\nselenium调用需要，需下载系统对应版本，将其放置到系统能直接访问的文件夹，如放在{PYTHON_HOME}/Scripts文件夹中
\n\n\n##数据库：\n\n###数据库名:xiecheng\n1.hotellianjie（存储酒店url）
\n```sql\nDROP TABLE IF EXISTS `hotellianjie`;\nCREATE TABLE `hotellianjie` (\n `guid` varchar(255) DEFAULT NULL,\n `lianjie` varchar(255) DEFAULT NULL,\n `city` varchar(30) DEFAULT NULL,\n `comm_num` int(30) DEFAULT NULL\n) ENGINE=InnoDB DEFAULT CHARSET=utf8;\n```\n2.hotelinfo（酒店基本信息数据）
\n```sql\nDROP TABLE IF EXISTS `hotelinfo`;\nCREATE TABLE `hotelinfo` (\n `guid` varchar(255) DEFAULT NULL,\n `city` varchar(30) DEFAULT NULL,\n `title` varchar(60) DEFAULT NULL,\n `price` decimal(10,1) DEFAULT NULL,\n `score` int(20) DEFAULT NULL,\n `recommend` varchar(120) DEFAULT NULL,\n `area` varchar(120) DEFAULT NULL,\n `havawifi` varchar(20) DEFAULT NULL,\n `discussNum` int(11) DEFAULT NULL,\n `common_facilities` varchar(500) DEFAULT NULL,\n `activity_facilities` varchar(255) DEFAULT NULL,\n `service_facilities` varchar(255) DEFAULT NULL,\n `room_facilities` varchar(255) DEFAULT NULL,\n `around_facilities` varchar(255) DEFAULT NULL\n) ENGINE=InnoDB DEFAULT CHARSET=utf8;\n```\n3.hotelcommentinfo（存储酒店评论数据）
\n```sql\nDROP TABLE IF EXISTS `hotelcommentinfo`;\nCREATE TABLE `hotelcommentinfo` (\n `hotelname` varchar(50) DEFAULT NULL,\n `username` varchar(40) DEFAULT NULL,\n `commentscore` varchar(40) DEFAULT NULL,\n `intime` varchar(40) DEFAULT NULL,\n `tourstyle` varchar(40) DEFAULT NULL,\n `praisenum` int(11) DEFAULT NULL,\n `commenttime` varchar(60) DEFAULT NULL,\n `comment` varchar(1000) DEFAULT NULL\n) ENGINE=InnoDB DEFAULT CHARSET=utf8;\n```"},{"alpha_fraction":0.46783626079559326,"alphanum_fraction":0.4938271641731262,"avg_line_length":27.165138244628906,"blob_id":"40cbb623bd7a6e0658e92668be6d67c464eca3aa","content_id":"cc44b77ed77b623ecf41436d85bae434ce4fad66","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":3244,"license_type":"no_license","max_line_length":85,"num_lines":109,"path":"/Foursquare research/Projects/Small Dataset creating/Data_scraping.py","repo_name":"Zheng392/Python-Repository","src_encoding":"UTF-8","text":"import pandas as pd\n\n\ndef get_tuple(f,max = 10):#获得(user,time,id)的元组\n n = 1\n while n<= max:\n line = f.readline().split('\\t')\n user = line[0]\n venue = line[1]\n # 1 = line[2]\n time = line[3]\n photo_id = line[4].split('\\n')[0]\n TUPLE = (user,time,photo_id)\n yield TUPLE\n n += 1\n #print(TUPLE)\n\ndef divide_time(start,end,num=10):#均分时间段\n list = []\n gap = (end - start)/num\n for i in range(num+1):\n list.append(start+i*gap)\n return list\n\ndef find_time_index(time,list):#在均分的时间点list里找到时间的位置\n for i in range(len(list)):\n if i == len(list)-1 and time == list[i]:\n return len(list)-1\n break\n if list[i]<=time=1):\n # 循环次数加1\n loopNum = loopNum + 1\n # 到达页面90%处\n js=\"var q=document.documentElement.scrollTop=9000\"\n self.driver.execute_script(js)\n # 当页面中出现“返前价”字样时，爬取页面并跳转到下一页\n if u\"收藏\" in self.driver.page_source:\n # 对未解析过的页面进行解析\n if ifHandle==False:\n self.crawllianjie(self.driver.page_source)\n ifHandle = True\n # 跳转到下一页\n if u\"下一页\" in self.driver.page_source:\n # self.driver.find_element_by_partial_link_text(u\"下一页\").click()\n pageNum = pageNum - 1\n # self.driver.find_element_by_xpath(\"//a[@class='c_down']\").click()\n element = self.driver.find_element_by_xpath(\"//a[@class='c_down']\")\n self.driver.execute_script(\"arguments[0].click();\", element)\n # 处理标识重新置为未处理\n ifHandle = False\n # 单页循环次数置为零\n loopNum = 0\n time.sleep(random.uniform(3, 6))\n print(\"页数：\" + str(pageNum))\n # try:\n # if u\"下一页\" in self.driver.page_source:\n # # self.driver.find_element_by_partial_link_text(u\"下一页\").click()\n # pageNum = pageNum - 1\n # self.driver.find_element_by_xpath(\"//a[@class='c_down']\").click()\n # # 处理标识重新置为未处理\n # ifHandle = False\n # # 单页循环次数置为零\n # loopNum = 0\n # time.sleep(random.uniform(3, 6))\n # print(\"页数：\" + str(pageNum))\n # except :\n # pageNum = pageNum + 1\n # 将当前的错误页保存下来\n # self.driver.save_screenshot('%s.png'%pageNum)\n # 如果单页循环次数不为零，说明没有跳转到下一页\n if loopNum != 0:\n # 循环次数较大的情况下（此处预定为15次）说明页面可能加载失败，跳出循环，否则继续循环获取\n if loopNum < 15:\n time.sleep(3)\n continue\n else:\n break\n return False if pageNum > 1 else True\n # 爬取酒店基本信息\n def pagecollect(self,response):\n items = []\n commentData = response.xpath(\"//div[@id='hotel_list']/div[@class='searchresult_list ']/ul[@class='searchresult_info']\")\n\n for itemData in commentData:\n itemDict = dict()\n\n # 唯一标识\n itemDict['guid'] = uuid.uuid1()\n\n # 城市名\n itemDict[\"city\"] = \"南京\"\n\n # 名称\n itemDict[\"title\"] = itemData.xpath(\"li/h2/a[@title]/text()\").extract()[0]\n\n # 价格\n price = itemData.xpath(\"li[@class='hotel_price_icon']/div/span/text()\").extract()[0]\n if price:\n itemDict[\"price\"] = price\n # print(price)\n else:\n itemDict[\"price\"] = \"\"\n\n # 评分\n score = itemData.xpath(\"li[@class='searchresult_info_judge ']/div/a/span[@class='hotel_value']/text()\").extract()[0]\n if score:\n itemDict[\"score\"] = score\n else:\n itemDict[\"score\"] = \" \"\n\n # 位置\n location = itemData.xpath(\"li[@class='searchresult_info_name']/p[@class='searchresult_htladdress']/text()\").extract()[0]\n Location = location.split(\" \")\n if(Location):\n itemDict[\"location\"] = Location[0]\n else:\n itemDict[\"location\"] = \" \"\n\n # 评论\n discussnum = itemData.xpath(\"li[@class='searchresult_info_judge ']/div/a/span[@class='hotel_judgement']/text()\").extract()[0]\n Discuss = re.sub('\\D','',discussnum)\n if Discuss:\n itemDict[\"discussnum\"] = Discuss\n else:\n itemDict[\"discussnum\"] = \"\"\n\n # 有无wifi\n havewifi1 = itemData.xpath(\"li[@class='searchresult_info_name']/div[@class='icon_list']/i[@class='icons-facility32']\")\n havawifi2 = itemData.xpath(\"li[@class='searchresult_info_name']/div[@class='icon_list']/i[@class='icons-facility01']\")\n if (havewifi1 or havawifi2):\n itemDict[\"havawifi\"] = \"yes\"\n else:\n itemDict[\"havawifi\"] = \"no\"\n\n # 用户推荐百分比\n recommend = itemData.xpath(\"li[@class='searchresult_info_judge ']/div[@class='searchresult_judge_box']/a/span[@class='total_judgement_score']/text()\").extract()[1]\n Recommend = re.sub('\\D','',recommend)\n Recommend += \"%\"\n if Recommend:\n itemDict[\"recommend\"] = Recommend\n else:\n itemDict[\"recommend\"] = \" \"\n\n items.append(itemDict)\n return items\n\n\n # 爬取页面链接\n def crawllianjie(self,page_sourse):\n response = HtmlResponse(url=\"my HTML string\",body=page_sourse,encoding=\"utf-8\")\n\n A = response.xpath(\"//div[@class='searchresult_list ']/ul\")\n # 获取每个酒店的链接\n for B in A:\n url = B.xpath(\"li[@class='searchresult_info_name']/h2/a/@href\").extract()\n # 评论\n commnum = B.xpath(\"li[@class='searchresult_info_judge ']/div/a/span[@class='hotel_judgement']/text()\").extract()\n if len(commnum):\n Discuss = re.sub('\\D','',commnum[0])\n if len(Discuss):\n pass\n else:\n Discuss = 0\n else:\n Discuss = 0\n self.listPageInfo.append({\"url\":url[0], \"comm_num\":Discuss, \"city\":\"南京\"})\n self.saveListPageInfo()\n if len(self.listPageInfo) == 25:\n pass\n else:\n print(len(self.listPageInfo))\n self.listPageInfo = []\n\n\n def saveListPageInfo(self):\n self.xiechengDao.savehotellink(self.listPageInfo)\n\n def depose(self):\n self.driver.close()\n\nif __name__==\"__main__\":\n xiechengService = XiechengDriverService()\n xiechengService.start()\n\n xiechengService.depose()\n"},{"alpha_fraction":0.5232515335083008,"alphanum_fraction":0.538996696472168,"avg_line_length":38.550724029541016,"blob_id":"214d9967cb9306551434c1d707c8ee5372a09d01","content_id":"22b631b14f2aa4b254bdfa1643a6d329bbb1ff82","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":5462,"license_type":"no_license","max_line_length":167,"num_lines":138,"path":"/tutorial/tutorial/spiders/scraper.py","repo_name":"Zheng392/Python-Repository","src_encoding":"UTF-8","text":"import scrapy\nimport json\nimport re\nfrom scrapy import Selector\nfrom tutorial.items import *\nfrom urllib.parse import urlencode\n\nheaders = {'Accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,image/webp,image/apng,*/*;q=0.8',\n 'Accept - Encoding':'gzip, deflate, br',\n 'Accept-Language':'en-US,en;q=0.9',\n 'Connection':'Keep-Alive',\n\t 'Cache-Control': 'max-age=0',\n 'User-Agent':'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/65.0.3325.181 Safari/537.36'}\n\nclass scraper(scrapy.Spider):\n name = \"scraper\"\n base_url = \"http://www.tripadvisor.cn\"\n\n def __init__(self):\n\n self.hotel_photo_links=[]\n \n def start_requests(self):\n\t yield scrapy.Request(url=self.base_url+\"/Hotels-g297463-Chengdu_Sichuan-Hotels.html\", callback=self.parse)\n\n \n\n def parse(self, response):\n\n\n\n hotel_urls = response.xpath('//h2[@class=\"listing_title\"]//a[contains(@class, \"property_title\")]/@href').extract()\n\n if hotel_urls:\n for hotel_url in hotel_urls:\n hotel_completed_url = self.base_url + hotel_url\n yield scrapy.Request(url=hotel_completed_url,\n callback=self.parse_fetch_hotel)\n break\n\n\n\n def parse_fetch_hotel(self, response):\n hxs=Selector(response)\n\n hi = Hotel_Item_Detail()\n\n hi['item_type'] = 'hotel'\n hi['detail_id'] = re.search('d[0-9]+', response.url).group(0).strip('d')\n hi['geo_id']=re.search('g[0-9]+',response.url).group(0).strip('g')\n hi['name'] = hxs.xpath( '//h1[contains(@id, \"HEADING\")]/text()').extract()[0]\n hi['url'] = response.url\n hi['rank']=hxs.xpath('//*[@id=\"taplc_location_detail_header_hotels_0\"]//div/span/b/text()').extract()[0]\n hi['traveler_photo_nums']=int(re.search('[0-9]+',\n hxs.xpath('//*[@id=\"taplc_hr_atf_north_star_nostalgic_0\"]//div[@class=\"albumInfo\"]/text()').extract()[0]).group(0))\n hi['offical_photo_nums']=int(re.search('[0-9]+',\n hxs.xpath('//*[@id=\"taplc_hr_atf_north_star_nostalgic_0\"]//span[@class=\"see_all_count\"]/text()').extract()[0]).group(0))\\\n -hi['traveler_photo_nums']\n yield hi\n\n for count,j in enumerate(['offical_photo_nums','traveler_photo_nums']):\n for i in range(int(hi[j]/50)+1):\n headers={\n 'geo':hi['geo_id'],\n 'detail':hi['detail_id'],\n 'albumViewMode':'images',\n 'aggregationId':101,\n 'albumid':101,\n 'cnt':50,\n 'offset': 50*i,\n 'filter':count+1,\n 'albumPartialsToUpdate':'partial',\n }\n photo_url='https://www.tripadvisor.cn/LocationPhotoAlbum?'+urlencode(headers)\n yield scrapy.Request(photo_url,self.parse_fetch_photo,\n meta={'id':hi['detail_id'],'count':count})\n break\n\n\n\n\n #get review\n pages=hxs.xpath('//*[@id=\"taplc_location_reviews_list_hotels_0\"]//div[@class=\"pageNumbers\"]/span[@class=\"pageNum last taLnk \"]/@data-page-number').extract()[0]\n pages=int(pages)\n for i in range(pages):\n split = response.url.split('Reviews')\n review_page_url = ('Reviews-or' + str(i * 5)).join(split)\n yield scrapy.Request(review_page_url,self.parse_review,meta={'id':hi['detail_id']})\n if i > 2:\n break\n\n\n\n def parse_fetch_photo(self,response):\n photos=photo_links()\n\n sel=Selector(response)\n photo_link=sel.xpath('//img[@onload]/@src').extract()\n if response.meta['count']==0:\n photos['photo_from']='official'\n else:\n photos['photo_from'] = 'traveler'\n photos['hotel_id'] =response.meta['id']\n\n temp=[]\n for i in photo_link:\n temp.append(i)\n photos['photo_link']=temp\n\n\n\n yield photos\n\n\n def parse_review(self,response):\n pass\n\n sel=Selector(response)\n\n\n username=sel.xpath('//*[@id=\"taplc_location_reviews_list_hotels_0\"]//div[@class=\"review-conta'\n 'iner\"]//span[@class=\"expand_inline scrname\"]/text()').extract()\n location=sel.xpath('//*[@id=\"taplc_location_reviews_list_hotels_0\"]//div[@class=\"review-conta'\n 'iner\"]//span[@class=\"expand_inline userLocation\"]/text()').extract()\n title=sel.xpath('//*[@id=\"taplc_location_reviews_list_hotels_0\"]//div[@class=\"review-container\"]'\n '//span[@class=\"noQuotes\"]/text()').extract()\n review_content=sel.xpath('//*[@id=\"taplc_location_reviews_list_hotels_0\"]//div[@class=\"review-container\"]'\n '//div[@class=\"wrap\"]/div[@class=\"prw_rup prw_reviews_text_summary_hsx\"]'\n '/div/p[@class=\"partial_entry\"]/text()').extract()\n\n for i in range(len(review_content)):\n Reviews = Review_Detail()\n Reviews['location']=location[i]\n Reviews['username'] = username[i]\n Reviews['title'] = title[i]\n Reviews['review_content'] = review_content[i]\n Reviews['hotel_id']=response.meta['id']\n yield Reviews\n\n\n\n\n"},{"alpha_fraction":0.7445783019065857,"alphanum_fraction":0.7566264867782593,"avg_line_length":49.10344696044922,"blob_id":"d3615c8af8acf4e1355f55e37b3f981501589506","content_id":"d1295244e1d8c4e007cb7d03c571d705d8069cca","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":2929,"license_type":"permissive","max_line_length":337,"num_lines":58,"path":"/Foursquare research/Projects/Get venues/README.md","repo_name":"Zheng392/Python-Repository","src_encoding":"UTF-8","text":"# Get venues\n\nGet venues in a rectangle. I improve the method used in [foursquare-venue-scraper](https://github.com/minimaxir/foursquare-venue-scraper), which is more effecient and complete. \n\n\n\n\n\n# foursquare-venue-scraper\n\n\n\nA [Foursquare](https://foursquare.com) data scraper that gathers all venues within a specified geographic area. The data retrieved can then be used for statistical analysis and fun data visualizations.\n\n## Overview\n\nThe script queries the official [Foursquare API](https://developer.foursquare.com/docs) (with a user-provided `client_id` and `client_secret` from a Foursquare application) to search for venues, and then query additional metadata for each unique venue.\n\nThe specified area is defined by a geographic bounding box (by latitude and longitude). Since the API can only return up to 50 venues per search, the bounding box is broken into sub-bounding boxes as a form of grid search (by default, the `grid_size` is 100, so 100x100=10000 searches total).\n\nThe output file is a CSV with the following fields:\n\n* `id` — The Foursquare ID for the venue.\n* `name` — The name of the venue.\n* `categories` — The list of categories of the venue.\n* `lat` — Latitude\n* `long` — Longitude\n* `num_checkins` — Number of Foursquare Checkins\n* `num_likes` — Number of Foursquare Likes\n* `price` — Price Tier between 1-4 (i.e. $-$$$$)\n* `rating` — Rating for the venue.\n* `num_ratings` — Number of ratings for the venue.\n* `url_venue` — URL of the venue.\n* `url_foursquare` — URL for the Foursquare venue.\n\nA demo CSV of the Top 100 San Francisco venues (by number of checkins) is available in `foursquare_sf_sample.csv`.\n\n## Usage\n\nSet the parameters in `config.yaml` as appropriate, then run `foursquare_venues.py`.\n\nThe Foursquare API has a **daily [rate limit](https://developer.foursquare.com/docs/api/troubleshooting/rate-limits) of 1,000 requests/day** for free accounts, but with verification, the rate limit upgrades to **100,000/day**. You can test the script with a small bounding box/low grid size to see if it fits your needs before upgrading.\n\nBoth of the API endpoints used in this script have a **rate limit of 5,000 requests/hour**. Once the script hits that limit, it'll sleep for an hour. Plan scraping accordingly.\n\n## Foursquare Terms of Use\n\nThis script follows the specifications of the Foursquare API, and does not circumvent the API and its rate limits. If you're using the data for projects other than data analysis, make sure to follow the [Foursquare Terms of Use](https://developer.foursquare.com/docs/terms-of-use/overview).\n\n## Maintainer\n\nMax Woolf ([@minimaxir](http://minimaxir.com))\n\n*Max's open-source projects are supported by his [Patreon](https://www.patreon.com/minimaxir). If you found this project helpful, any monetary contributions to the Patreon are appreciated and will be put to good creative use.*\n\n## License\n\nMIT"},{"alpha_fraction":0.5251753330230713,"alphanum_fraction":0.6241232752799988,"avg_line_length":52.22666549682617,"blob_id":"000731c85fb40f442bb8e2bdcbde36ef13465b22","content_id":"e6b5f9c0455e8c829ef068f9cc383cd8a480d2f9","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":8994,"license_type":"no_license","max_line_length":692,"num_lines":150,"path":"/Spider/fangtianxia data with threading/fang_data_threading.py","repo_name":"Zheng392/Python-Repository","src_encoding":"UTF-8","text":"import requests,json,random\nimport re,threading\nfrom lxml import etree\nimport time\n\nlock=threading.Lock()\n\nuser_agent_list = [\n \"Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/537.1 (KHTML, like Gecko) Chrome/22.0.1207.1 Safari/537.1\" ,\\\n \"Mozilla/5.0 (X11; CrOS i686 2268.111.0) AppleWebKit/536.11 (KHTML, like Gecko) Chrome/20.0.1132.57 Safari/536.11\", \\\n \"Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/536.6 (KHTML, like Gecko) Chrome/20.0.1092.0 Safari/536.6\", \\\n \"Mozilla/5.0 (Windows NT 6.2) AppleWebKit/536.6 (KHTML, like Gecko) Chrome/20.0.1090.0 Safari/536.6\", \\\n \"Mozilla/5.0 (Windows NT 6.2; WOW64) AppleWebKit/537.1 (KHTML, like Gecko) Chrome/19.77.34.5 Safari/537.1\", \\\n \"Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/536.5 (KHTML, like Gecko) Chrome/19.0.1084.9 Safari/536.5\", \\\n \"Mozilla/5.0 (Windows NT 6.0) AppleWebKit/536.5 (KHTML, like Gecko) Chrome/19.0.1084.36 Safari/536.5\", \\\n \"Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/536.3 (KHTML, like Gecko) Chrome/19.0.1063.0 Safari/536.3\", \\\n \"Mozilla/5.0 (Windows NT 5.1) AppleWebKit/536.3 (KHTML, like Gecko) Chrome/19.0.1063.0 Safari/536.3\", \\\n \"Mozilla/5.0 (Macintosh; Intel Mac OS X 10_8_0) AppleWebKit/536.3 (KHTML, like Gecko) Chrome/19.0.1063.0 Safari/536.3\", \\\n \"Mozilla/5.0 (Windows NT 6.2) AppleWebKit/536.3 (KHTML, like Gecko) Chrome/19.0.1062.0 Safari/536.3\", \\\n \"Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/536.3 (KHTML, like Gecko) Chrome/19.0.1062.0 Safari/536.3\", \\\n \"Mozilla/5.0 (Windows NT 6.2) AppleWebKit/536.3 (KHTML, like Gecko) Chrome/19.0.1061.1 Safari/536.3\", \\\n \"Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/536.3 (KHTML, like Gecko) Chrome/19.0.1061.1 Safari/536.3\", \\\n \"Mozilla/5.0 (Windows NT 6.1) AppleWebKit/536.3 (KHTML, like Gecko) Chrome/19.0.1061.1 Safari/536.3\", \\\n \"Mozilla/5.0 (Windows NT 6.2) AppleWebKit/536.3 (KHTML, like Gecko) Chrome/19.0.1061.0 Safari/536.3\", \\\n \"Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/535.24 (KHTML, like Gecko) Chrome/19.0.1055.1 Safari/535.24\", \\\n \"Mozilla/5.0 (Windows NT 6.2; WOW64) AppleWebKit/535.24 (KHTML, like Gecko) Chrome/19.0.1055.1 Safari/535.24\"\n ]\ncount=0\n\ndef fang_com(page_url,page): ##列表页\n print('page is ',i)\n header={}\n\n header['User-Agent']=random.choice(user_agent_list)\n header.update({\n \"Host\":\"esf.sz.fang.com\",\n #\"Cookie\":\"global_cookie=fb1g6d0w64d2cmu86sv4g9n3va0j137sk48; vh_newhouse=3_1491312022_2816%5B%3A%7C%40%7C%3A%5D833300ee3177d88529c7aa418942ece9; newhouse_user_guid=2F163DE7-8201-7FA9-2FB6-E507FE6F03B1; SoufunSessionID_Esf=3_1495389730_232; sf_source=; s=; showAdsh=1; hlist_xfadhq_SZ=0%7c2017%2f5%2f25+1%3a21%3a47%7c; city=sz; __utmt_t0=1; __utmt_t1=1; __utmt_t2=1; logGuid=a768dd46-b85b-47f4-a7a0-0a6596cab4cd; __utma=147393320.1111837171.1491290389.1495646208.1495650134.9; __utmb=147393320.12.10.1495650134; __utmc=147393320; __utmz=147393320.1495650134.9.4.utmcsr=esf.sz.fang.com|utmccn=(referral)|utmcmd=referral|utmcct=/; unique_cookie=U_cqyov4ut5vv1al8e2858qhzgt17j2z06mph*14\"\n })\n while(1): ###这个主要是，fang.com会随机返回几个10054或者10053，如果连页面都没读取到，提取就是后话了，这网站没有封杀，即使使用单ip只会很少时候随机来几个10054 ，('Connection aborted.', error(10054, ''))\n text=''\n try:\n text=requests.get(page_url,headers=header,timeout=10).text\n #print text\n except Exception as e:\n print(e)\n if text!='':\n break\n\n se = etree.HTML(text) ###########为了利于大家学习，这段演示xpath提取信息\n all_dl=se.xpath('//dl[@class=\"list rel\"]')\n print(len(all_dl))\n for dl in all_dl:\n title=dl.xpath('.//dd[@class=\"info rel floatr\"]/p[@class=\"title\"]/a/text()')[0]\n url=dl.xpath('.//dd[@class=\"info rel floatr\"]/p[@class=\"title\"]/a/@href')[0]\n url='http://esf.sz.fang.com'+url\n\n info_list=dl.xpath('.//dd[@class=\"info rel floatr\"]/p[@class=\"mt12\"]/text()')\n #print json.dumps(info,ensure_ascii=False) #py2显示汉字，py3可以直接print mt12\n info=''\n for l in info_list:\n l2= re.findall('\\S*',l)[0] ###消除空白和换行\n #print m_str\n info+=l2+'|'\n\n time.sleep(1)\n # total_price,price_squere,huxin,cankao_shoufu,shiyong_mianji,jianzhu_mianji,years,discription=get_detail(url)\n\n\n lock.acquire() ###这里叫锁，一是保证count计数准确，而是不会导致多个线程乱print，导致看不清楚。加锁的目的是别的线程不能运行这段代码了。但我之前看到有的人乱加锁，把消耗时间很长的代码加锁，那样导致多线程就基本个废物\n global count\n count+=1\n print(time.strftime('%H:%M:%S', time.localtime(time.time())), ' ', count)\n print('列表页：')\n print(' title: %s\\n url: %s\\n info: %s\\n' % (title, url, info))\n\n print('详情页:')\n # print(\n # ' total_price: %s\\n price_squere: %s\\n huxin: %s\\n cankao_shoufu: %s\\n shiyong_mianji: %s\\n jianzhu_mianji: %s\\n years: %s \\n' % (\n # total_price, price_squere, huxin, cankao_shoufu, shiyong_mianji, jianzhu_mianji, years))\n print('**************************************************************')\n lock.release()\n\n\n\ndef get_detail(url): ###详情页\n\n header={'User-Agent':random.choice(user_agent_list)}\n header.update({\"Host\":\"esf.sz.fang.com\"})\n\n while(1):\n content=''\n try:\n content=requests.get(url,headers=header,timeout=10).content\n except Exception as e:\n print(e)\n pass\n if content!='':\n break\n\n content=content.decode('gbk').encode('utf8') ##查看网页源代码可看到是gbk编码，直接print的话，如果你在pycharm设置控制台是utf8编码，那么控制台的中文则会乱码，cmd是gbk的恰好可以显示。如果你在pycharm设置控制台是utf8编码，需要这样做\n #print content\n\n inforTxt=getlist0(re.findall('(
\n\n##使用Python 库：\n1.scrapy，网上安装方法许多，可自行下载相关依赖
\n\n2.selenium
\n可以直接使用pip进行安装
\n\nSelenium也是一个用于Web应用程序测试的工具。Selenium测试直接运行在浏览器中，就像真正的用户在操作一样。
\n\n\n##使用驱动:\n1.Chrome驱动
\n下载地址：http://npm.taobao.org/mirrors/chromedriver
\n\nselenium调用需要，需下载系统对应版本，将其放置到系统能直接访问的文件夹，如放在{PYTHON_HOME}/Scripts文件夹中
\n\n\n##数据库：\n\n###数据库名:xiecheng\n1.hotellianjie（存储酒店url）
\n```sql\nDROP TABLE IF EXISTS `hotellianjie`;\nCREATE TABLE `hotellianjie` (\n `guid` varchar(255) DEFAULT NULL,\n `lianjie` varchar(255) DEFAULT NULL,\n `city` varchar(30) DEFAULT NULL,\n `comm_num` int(30) DEFAULT NULL\n) ENGINE=InnoDB DEFAULT CHARSET=utf8;\n```\n2.hotelinfo（酒店基本信息数据）
\n```sql\nDROP TABLE IF EXISTS `hotelinfo`;\nCREATE TABLE `hotelinfo` (\n `guid` varchar(255) DEFAULT NULL,\n `city` varchar(30) DEFAULT NULL,\n `title` varchar(60) DEFAULT NULL,\n `price` decimal(10,1) DEFAULT NULL,\n `score` int(20) DEFAULT NULL,\n `recommend` varchar(120) DEFAULT NULL,\n `area` varchar(120) DEFAULT NULL,\n `havawifi` varchar(20) DEFAULT NULL,\n `discussNum` int(11) DEFAULT NULL,\n `common_facilities` varchar(500) DEFAULT NULL,\n `activity_facilities` varchar(255) DEFAULT NULL,\n `service_facilities` varchar(255) DEFAULT NULL,\n `room_facilities` varchar(255) DEFAULT NULL,\n `around_facilities` varchar(255) DEFAULT NULL\n) ENGINE=InnoDB DEFAULT CHARSET=utf8;\n```\n3.hotelcommentinfo（存储酒店评论数据）
\n```sql\nDROP TABLE IF EXISTS `hotelcommentinfo`;\nCREATE TABLE `hotelcommentinfo` (\n `hotelname` varchar(50) DEFAULT NULL,\n `username` varchar(40) DEFAULT NULL,\n `commentscore` varchar(40) DEFAULT NULL,\n `intime` varchar(40) DEFAULT NULL,\n `tourstyle` varchar(40) DEFAULT NULL,\n `praisenum` int(11) DEFAULT NULL,\n `commenttime` varchar(60) DEFAULT NULL,\n `comment` varchar(1000) DEFAULT NULL\n) ENGINE=InnoDB DEFAULT CHARSET=utf8;\n```"},{"alpha_fraction":0.46783626079559326,"alphanum_fraction":0.4938271641731262,"avg_line_length":27.165138244628906,"blob_id":"40cbb623bd7a6e0658e92668be6d67c464eca3aa","content_id":"cc44b77ed77b623ecf41436d85bae434ce4fad66","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":3244,"license_type":"no_license","max_line_length":85,"num_lines":109,"path":"/Foursquare research/Projects/Small Dataset creating/Data_scraping.py","repo_name":"Zheng392/Python-Repository","src_encoding":"UTF-8","text":"import pandas as pd\n\n\ndef get_tuple(f,max = 10):#获得(user,time,id)的元组\n n = 1\n while n<= max:\n line = f.readline().split('\\t')\n user = line[0]\n venue = line[1]\n # 1 = line[2]\n time = line[3]\n photo_id = line[4].split('\\n')[0]\n TUPLE = (user,time,photo_id)\n yield TUPLE\n n += 1\n #print(TUPLE)\n\ndef divide_time(start,end,num=10):#均分时间段\n list = []\n gap = (end - start)/num\n for i in range(num+1):\n list.append(start+i*gap)\n return list\n\ndef find_time_index(time,list):#在均分的时间点list里找到时间的位置\n for i in range(len(list)):\n if i == len(list)-1 and time == list[i]:\n return len(list)-1\n break\n if list[i]<=time
[\\s\\S]*?)
- ',content)) ###########为了利于大家学习，这段演示正则表达式提取信息，某些信息可能在有的房子界面没有，要做好判断\n #print inforTxt\n\n total_price=getlist0(re.findall('价：(.*?)',inforTxt))\n\n price_squere=getlist0(re.findall('class=\"black\">万\\((\\d+?)元[\\s\\S]*?户型：(.*?)',inforTxt))\n cankao_shoufu=getlist0(re.findall('参考首付：(.*?万) ',inforTxt))\n shiyong_mianji=getlist0(re.findall('>使用面积：(.*?)',inforTxt))\n shiyong_mianji=getlist0(re.findall('\\d+',shiyong_mianji))\n jianzhu_mianji=getlist0(re.findall('建筑面积：(.*?)',inforTxt))\n jianzhu_mianji=getlist0(re.findall('\\d+',jianzhu_mianji))\n years=getlist0(re.findall('年代：(.*?)',inforTxt))\n\n discription=getlist0(re.findall('style=\"-moz-user-select: none;\">([\\s\\S]*?)
', ' ')\\n name = name.replace('|', ' ')\\n print(os.path.join(path, file))\\n os.rename(os.path.join(path, file), os.path.join(path,name+\\\".pdf\\\"))\\n\"\n },\n {\n \"alpha_fraction\": 0.5977763533592224,\n \"alphanum_fraction\": 0.6000654101371765,\n \"avg_line_length\": 35.35714340209961,\n \"blob_id\": \"50c483ac09faaec95f173745b384a53a3b319069\",\n \"content_id\": \"2c414c614807af7c8d6a506e41e796244d4b4d75\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 3152,\n \"license_type\": \"no_license\",\n \"max_line_length\": 529,\n \"num_lines\": 84,\n \"path\": \"/Spider/XieCheng Hotel Data/xiecheng selenium/DAO/xiecheng.py\",\n \"repo_name\": \"Zheng392/Python-Repository\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: utf-8 -*-\\n__author__ = 'LiuYang'\\nimport pymysql\\nimport uuid\\nimport random\\n\\nclass xiechengDAO(object):\\n def __init__(self,host= 'localhost',db='mysql',user='root',password='73628'):\\n self.host = host\\n self.db = db\\n self.user=user\\n self.password =password\\n\\n # 存储酒店基本信息\\n def savehotelComment(self,items):\\n db = pymysql.connect(self.host,self.user,self.password,self.db,charset='utf8')\\n cursor = db.cursor()\\n for item in items:\\n try:\\n cursor.execute(\\\"replace into hotelinfo(guid,city,title,price,score,recommend,area,havawifi,discussNum,common_facilities,activity_facilities,service_facilities,room_facilities,around_facilities)values(%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s)\\\" ,(item[\\\"guid\\\"],item[\\\"city\\\"],item[\\\"title\\\"],item[\\\"price\\\"],item[\\\"score\\\"],item[\\\"recommend\\\"],item[\\\"area\\\"],item[\\\"havawifi\\\"],item[\\\"discussNum\\\"],item[\\\"common_facilities\\\"],item[\\\"activity_facilities\\\"],item[\\\"service_facilities\\\"],item[\\\"room_facilities\\\"],item[\\\"around_facilities\\\"]))\\n except Exception as e:\\n print(e)\\n db.commit()\\n cursor.close()\\n db.close()\\n\\n\\n # 存储所有酒店的链接\\n def savehotellink(self,listPageInfo):\\n db = pymysql.connect(self.host,self.user,self.password,self.db,charset='utf8')\\n cursor = db.cursor()\\n for hotel in listPageInfo:\\n try:\\n id = uuid.uuid1()\\n cursor.execute(\\\"replace into hotellianjie(guid,lianjie,city,comm_num)values(%s,%s,%s,%s)\\\" ,(id,hotel[\\\"url\\\"],hotel[\\\"city\\\"],hotel[\\\"comm_num\\\"]))\\n except Exception as e:\\n print(hotel[\\\"url\\\"])\\n db.commit()\\n cursor.close()\\n db.close()\\n\\n\\n # 从数据库中读取链接数据\\n def _return(self):\\n db = pymysql.connect(self.host,self.user,self.password,self.db,charset='utf8')\\n cursor = db.cursor()\\n\\n cursor.execute(\\\"SELECT * FROM hotellianjie\\\")\\n\\n rows = cursor.fetchall()\\n return rows\\n\\n db.commit()\\n cursor.close()\\n db.close()\\n\\n # 存储酒店评论信息\\n def savehotelCommentinfo(self,items):\\n db = pymysql.connect(self.host,self.user,self.password,self.db,charset='utf8')\\n cursor = db.cursor()\\n for item in items:\\n\\n try:\\n cursor.execute(\\\"insert into hotelcommentinfo(hotelname,username,commentscore,intime,tourstyle,praisenum,commenttime,comment)values(%s,%s,%s,%s,%s,%s,%s,%s)\\\" ,(item[\\\"title\\\"],item[\\\"username\\\"],item[\\\"commentscore\\\"],item[\\\"intime\\\"],item[\\\"tourstyle\\\"],item[\\\"praisenum\\\"],item[\\\"commenttime\\\"],item[\\\"comment\\\"]))\\n except :\\n print(item)\\n db.commit()\\n cursor.close()\\n db.close()\\n\\n\\n # 从数据库中读取评论数据\\n def _returncomment(self):\\n db = pymysql.connect(self.host,self.user,self.password,self.db,charset='utf8')\\n cursor = db.cursor()\\n\\n cursor.execute(\\\"SELECT * FROM hotelcommentinfo\\\")\\n\\n rows = cursor.fetchall()\\n return rows\\n\\n db.commit()\\n cursor.close()\\n db.close()\\n\\n\\n\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.5355501770973206,\n \"alphanum_fraction\": 0.5528520941734314,\n \"avg_line_length\": 31.743362426757812,\n \"blob_id\": \"f91616be7377d19912865f599c1a619eb8d2e6f6\",\n \"content_id\": \"d95ac368eb7b1d99157f281d0ef185d06fb9d903\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 3699,\n \"license_type\": \"no_license\",\n \"max_line_length\": 109,\n \"num_lines\": 113,\n \"path\": \"/Foursquare research/Projects/Venues details/tutorial/spiders/scraper.py\",\n \"repo_name\": \"Zheng392/Python-Repository\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import scrapy\\nimport json\\nimport re\\nfrom scrapy import Selector\\nfrom tutorial.items import *\\nfrom urllib.parse import urlencode\\nimport yaml\\nimport json\\nimport pandas as pd\\nimport numpy as np\\nimport re\\n\\ndef get_delta(lower, upper, length):\\n return (upper - lower) / length\\n\\nclass scraper(scrapy.Spider):\\n name = \\\"scraper\\\"\\n # base_url = \\\"http://www.tripadvisor.cn\\\"\\n # start_urls = [\\n # base_url + \\\"/Hotels-g297463-Chengdu_Sichuan-Hotels.html\\\"\\n # ]\\n with open(\\\"config.yaml\\\", \\\"r\\\") as f:\\n cfg = yaml.load(f)\\n search_params = {\\n 'client_id': cfg['client_id'],\\n 'client_secret': cfg['client_secret'],\\n 'v': '20180218'\\n }\\n start_urls = []\\n\\n df=pd.read_csv('data.csv',encoding='utf-8')\\n df=df.sort_values(by='checkinsCount',ascending=False)\\n ids=list(df['id'][0:500].values)\\n for id in ids:\\n url = 'https://api.foursquare.com/v2/venues/{}'.format(id) + '?' + urlencode(search_params)\\n start_urls.append(url)\\n\\n\\n def __init__(self):\\n\\n self.venue_ids = set()\\n self.allVenues = []\\n self.search_count=0\\n with open(\\\"config.yaml\\\", \\\"r\\\") as f:\\n cfg = yaml.load(f)\\n self.photosParams = {\\n 'client_id': cfg['client_id'],\\n 'client_secret': cfg['client_secret'],\\n 'v': '20180218',\\n \\\"limit\\\": 200\\n\\n }\\n self.tipsParams = {\\n 'client_id': cfg['client_id'],\\n 'client_secret': cfg['client_secret'],\\n 'v': '20180218',\\n \\\"limit\\\":200\\n }\\n\\n\\n def parse(self, response):\\n\\n if 'venue' in json.loads(response.body)['response']:\\n venue = json.loads(response.body)['response']['venue']\\n photosNum=venue['photos']['count']\\n tipsNum=venue['stats']['tipCount']\\n venuesItemInsta=venuesItem()\\n venuesItemInsta['venue']=venue\\n yield venuesItemInsta\\n\\n self.search_count += 1\\n print(\\\"search count: {}; \\\".format(self.search_count))\\n\\n for photosCount in range(int(photosNum/200)+1):\\n self.photosParams.update({\\\"offset\\\":200*photosCount})\\n yield scrapy.Request(url=response.url.split('?')[0]+'/photos?'+ urlencode(self.photosParams),\\n callback=self.ParsePhotos)\\n\\n\\n for tipsCount in range(int(tipsNum/200)+1):\\n self.tipsParams.update({\\\"offset\\\":200*tipsCount})\\n yield scrapy.Request(url=response.url.split('?')[0]+'/tips?'+ urlencode(self.tipsParams),\\n callback=self.ParseTips)\\n\\n\\n\\n def ParsePhotos(self, response):\\n if 'photos' in json.loads(response.body)['response']:\\n photos=json.loads(response.body)['response']['photos']['items']\\n id=re.search('(venues/)(.*?)(/photo)',response.url).group(2)\\n for photo in photos:\\n photosItemInst=photosItem()\\n photosItemInst['photo']=photo\\n photosItemInst['id']=id\\n yield photosItemInst\\n\\n self.search_count += 1\\n print(\\\"search count: {}; \\\".format(self.search_count))\\n\\n\\n\\n def ParseTips(self, response):\\n if 'tips' in json.loads(response.body)['response']:\\n tips=json.loads(response.body)['response']['tips']['items']\\n id=re.search('(venues/)(.*?)(/tips)',response.url).group(2)\\n for tip in tips:\\n tipsItemInst=tipsItem()\\n tipsItemInst['tip']=tip\\n tipsItemInst['id']=id\\n yield tipsItemInst\\n\\n self.search_count += 1\\n print(\\\"search count: {}; \\\".format(self.search_count))\"\n },\n {\n \"alpha_fraction\": 0.6243761777877808,\n \"alphanum_fraction\": 0.6401151418685913,\n \"avg_line_length\": 29.296510696411133,\n \"blob_id\": \"41825925840ffb892c9040704d77eb2563550e5f\",\n \"content_id\": \"b710477c2ac06d1b0b48f8ae1e9d9669e57db93d\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 5472,\n \"license_type\": \"no_license\",\n \"max_line_length\": 191,\n \"num_lines\": 172,\n \"path\": \"/Foursquare research/Projects/Data analysis/main.py\",\n \"repo_name\": \"Zheng392/Python-Repository\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#!/usr/bin/env python3\\n# -*- coding: utf-8 -*-\\n\\nimport json\\nimport pandas as pd\\nimport numpy\\nimport pickle\\n\\n#一个用户可能在一个景点发很多图片，后缀ByPhotos表示按图片统计，ByVenues表示按景点统计，\\nvenue_id=[] #景点ID\\ncategories=[] #标签的景点数\\ncategories_num=[] #景点的标签数\\nuserVenueByPhotos=[] #照片的user,景点\\ntip_user=[] #tip的user,景点\\nusrByPhotos=[]\\nplaByPhotos=[]\\nuserid=[] #大于10的用户ID\\nvenueid=[] #大于10的地点ID\\nfolders=['1-500','500-2000','2000-5000','5000-10000','Supplements']\\nphotos=[]\\n'''\\nfor m in folders:\\n # with open('venues'+str(m)+'.json','r',encoding=\\\"utf8\\\") as file:\\n # for line in file.readlines():\\n # venue=json.loads(line)['venue']\\n # for i in range(0, len(venue['categories'])):\\n # categories.append(venue['categories'][i]['id'])\\n # categories_num.append(len(venue['categories']))\\n # venue_id.append(venue['id'])\\n\\n with open(m+'/photosData.json','r',encoding=\\\"utf8\\\") as file:\\n for line in file.readlines():\\n userVenueByPhotos.append([json.loads(line)['photo']['user']['id'],json.loads(line)['id']])\\n usrByPhotos.append(json.loads(line)['photo']['user']['id'])\\n plaByPhotos.append(json.loads(line)['id'])\\n photos.append(json.loads(line)['photo']['id'])\\n print(\\\"load %s successfully\\\"%{m})\\n\\n'''\\n\\n# with open('params.sav', 'wb') as f:\\n# pickle.dump([userVenueByPhotos,usrByPhotos,plaByPhotos,photos], f, -1)\\n\\nprint('save params successfully')\\nparams=[]\\nwith open('params.sav', 'rb') as f:\\n tmp = pickle.load(f)\\n userVenueByPhotos, usrByPhotos, plaByPhotos,photos=tmp\\nuserVenueByVenues=set() # 用户景点set\\nfor pu in userVenueByPhotos:\\n pu=tuple(pu)\\n userVenueByVenues.add(pu)\\n\\nusersByVenues=[]\\nfor m in userVenueByVenues:\\n usersByVenues.append(m[0])\\n\\n\\nuserNumByVenues=list(zip(*numpy.unique(usersByVenues, return_counts=True)))\\nuserNumByPhotos=list(zip(*numpy.unique(usrByPhotos, return_counts=True)))\\nplaNumByPhotos=list(zip(*numpy.unique(plaByPhotos, return_counts=True)))\\n\\n#筛选出去过景点数大于20（即图片数肯定更多）的用户\\nfor p in range(1,len(userNumByVenues)):\\n if userNumByVenues[p][1] >=20:\\n userid.append(userNumByVenues[p][0])\\n\\n\\n#再筛选出图片数大于x的景点\\nfor p in range(1,len(plaNumByPhotos)):\\n if plaNumByPhotos[p][1] >=50:\\n venueid.append(plaNumByPhotos[p][0])\\n\\n\\n\\n\\n# print(dict(zip(*numpy.unique(categories, return_counts=True)))) #标签的景点数\\n# print(dict(zip(*numpy.unique(categories_num, return_counts=True))))#景点的标签数\\n# lab=dict(zip(*numpy.unique(categories, return_counts=True))).values()\\n# print(lab)\\n\\n\\n\\nuserVenueByPhotos=numpy.array(userVenueByPhotos)\\nuser_label=numpy.unique(userVenueByPhotos[:,0])\\nvenue_label=numpy.unique(userVenueByPhotos[:,1])\\na=list(zip(*numpy.unique(userVenueByPhotos[:,0], return_counts=True)))\\nb=list(zip(*numpy.unique(userVenueByPhotos[:,1], return_counts=True)))\\na=numpy.array(a)[:,1]\\nb=numpy.array(b)[:,1]\\na=list(zip(*numpy.unique(a, return_counts=True)))\\nb=list(zip(*numpy.unique(b, return_counts=True)))\\na=numpy.array(a)\\nb=numpy.array(b)\\na1=list(a[:,0])\\na2=list(a[:,1])\\nb1=list(b[:,0])\\nb2=list(b[:,1])\\n\\n\\n\\nfile_obj = open(\\\"distribution.txt\\\", 'w')\\nfor num in a1:\\n file_obj.writelines(num)\\n file_obj.writelines(', ')\\nfile_obj.write('\\\\n\\\\n')\\nfor num in a2:\\n file_obj.writelines(num)\\n file_obj.writelines(', ')\\nfile_obj.write('\\\\n')\\nfile_obj.write('\\\\n')\\nfor num in b1:\\n file_obj.writelines(num)\\n file_obj.writelines(', ')\\nfile_obj.write('\\\\n\\\\n')\\nfor num in b2:\\n file_obj.writelines(num)\\n file_obj.writelines(', ')\\nfile_obj.write('\\\\n')\\n\\nfile_obj.close()\\n\\n\\n# with open('tipsData.json','r',encoding=\\\"utf8\\\") as file:\\n# for line in file.readlines():\\n# tip_user.append([json.loads(line)['tip']['user']['id'], json.loads(line)['id']])\\n#\\n# tip_user=numpy.array(tip_user)\\n# user_label=numpy.unique(tip_user[:,0])\\n# venue_label=numpy.unique(tip_user[:,1])\\n# print('tip')\\n# print(len(user_label))\\n# print(len(venue_label))\\n\\n'''\\nmatrix=numpy.zeros((len(user_label),len(venue_label)))\\nprint(numpy.sum(matrix))\\n\\n\\nfor k in range(0,len(tip_user)):\\n data=tip_user[k]\\n i=user_label.tolist().index(data[0])\\n j=venue_label.tolist().index(data[1])\\n matrix[i,j]=matrix[i,j]+1\\nprint(numpy.sum(matrix))\\n'''\\n\\n\\n# df=pd.DataFrame(matrix,columns=venue_label,index=user_label)\\n# df.to_csv('Data analysis result.csv')\\n\\n\\n\\nn=0\\nnn=0\\nfile_write_obj = open(\\\"photo,user,venue,time.txt\\\", 'w')\\nfor m in folders:\\n with open(m+'/photosData.json','r',encoding=\\\"utf8\\\") as file:\\n for line in file.readlines():\\n nn = nn + 1\\n if json.loads(line)['photo']['user']['id'] in userid:\\n if json.loads(line)['id'] in venueid:\\n puvt = json.loads(line)['photo']['id'] +', '+ json.loads(line)['photo']['user']['id'] + ', '+ json.loads(line)['id'] + ', ' + str(json.loads(line)['photo']['createdAt'])\\n file_write_obj.writelines(puvt)\\n file_write_obj.write('\\\\n')\\n n=n+1\\n print(\\\"secondly load %s successfully\\\" % {m})\\nprint('地点剩余 ',len(venueid),'/',len(plaNumByPhotos))\\nprint('用户剩余 ',len(userid),'/',len(userNumByPhotos))\\nprint('photo剩余 ',n,'/',nn)\\nfile_write_obj.close()\\nprint('稀疏性=',1-(n/(len(userid)*len(venueid))))\"\n },\n {\n \"alpha_fraction\": 0.4955223798751831,\n \"alphanum_fraction\": 0.5671641826629639,\n \"avg_line_length\": 29.363636016845703,\n \"blob_id\": \"453b55f905a9119fbc50d92dd6022119826e91c3\",\n \"content_id\": \"cd3cf100b621f63d17179436b1433ebb3f7ef7f8\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 335,\n \"license_type\": \"no_license\",\n \"max_line_length\": 61,\n \"num_lines\": 11,\n \"path\": \"/Spider/Jindong review data by Scrapy/jdcomment/jd_spider/test.py\",\n \"repo_name\": \"Zheng392/Python-Repository\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from urllib.parse import urlencode\\ndata = {\\n 'callback': 'fetchJSON_comment98vv61',\\n 'productId': '3555984',\\n 'score': 0, # all 0 bad 1 mid 2 good 3 zhuiping 5\\n 'sortType': 5, # time series rank 6 recommend rank 5\\n 'pageSize': 10,\\n 'isShadowSku': 0,\\n 'page': 0\\n }\\nurlencode(data)\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.8108108043670654,\n \"alphanum_fraction\": 0.8108108043670654,\n \"avg_line_length\": 36.5,\n \"blob_id\": \"02795151a3dc1db3a058f14401ccffd488ab4fe6\",\n \"content_id\": \"a3ace824bd6fd39a3d39e0c2044f6838054ca10d\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 74,\n \"license_type\": \"permissive\",\n \"max_line_length\": 47,\n \"num_lines\": 2,\n \"path\": \"/Foursquare research/Projects/Get venues/execute.py\",\n \"repo_name\": \"Zheng392/Python-Repository\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from scrapy import cmdline\\ncmdline.execute('scrapy crawl scraper'.split())\"\n },\n {\n \"alpha_fraction\": 0.6770491600036621,\n \"alphanum_fraction\": 0.6811475157737732,\n \"avg_line_length\": 30.30769157409668,\n \"blob_id\": \"856e20f356dd19bd8f3dacd503e2f9155984ecc6\",\n \"content_id\": \"17ad6c538eb3e65bed741c25bcfee149589f2e08\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1220,\n \"license_type\": \"no_license\",\n \"max_line_length\": 120,\n \"num_lines\": 39,\n \"path\": \"/Foursquare research/Projects/Venues details/Data analysis.py\",\n \"repo_name\": \"Zheng392/Python-Repository\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#!/usr/bin/env python3\\n# -*- coding: utf-8 -*-\\nimport json\\nimport pandas as pd\\nimport numpy as np\\nvenues=[]\\nids=set()\\nvenueLine=[]\\nphotos=[]\\ntips=[]\\nwith open('venues.json','r',encoding=\\\"utf8\\\") as f:\\n for line in f.readlines():\\n venue=json.loads(line)['venue']\\n venues.append([venue['id'],venue['stats']['tipCount'],venue['stats']['checkinsCount'],venue['photos']['count']])\\n ids.add(venue['id'])\\n\\nwith open('photosData.json','r',encoding=\\\"utf8\\\") as f:\\n for line in f.readlines():\\n photo=json.loads(line)['id']\\n photos.append(photo)\\n\\nwith open('tipsData.json','r',encoding=\\\"utf8\\\") as f:\\n for line in f.readlines():\\n tip=json.loads(line)['id']\\n tips.append(tip)\\n\\nphotosSeries=pd.Series(photos)\\nphotosScraperCount=photosSeries.value_counts()\\n\\ntipsSeries=pd.Series(tips)\\ntipsScraperCount=tipsSeries.value_counts()\\n\\ndf=pd.DataFrame(np.array(venues),columns=['id','tipsCount','checkinsCount','photosCount'])\\ndf=df.set_index('id')\\ndf=pd.merge(df, pd.DataFrame(tipsScraperCount), left_index=True, right_index=True, how='outer')\\ndf=pd.merge(df, pd.DataFrame(photosScraperCount), left_index=True, right_index=True, how='outer')\\n\\ndf.to_csv('Data analysis result.csv')\\npass\"\n },\n {\n \"alpha_fraction\": 0.6166666746139526,\n \"alphanum_fraction\": 0.6166666746139526,\n \"avg_line_length\": 31.384614944458008,\n \"blob_id\": \"d9d21fd5f44f61ae0a71eddbceda80537fbc265a\",\n \"content_id\": \"ae2c680449c4ba9a1b54e6a0f1da24c613b4f574\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 420,\n \"license_type\": \"no_license\",\n \"max_line_length\": 115,\n \"num_lines\": 13,\n \"path\": \"/Foursquare research/Projects/Venues details/README.md\",\n \"repo_name\": \"Zheng392/Python-Repository\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# Venues details\\n\\nGet detailed data for venues, including tips and photos of venues.\\n\\n\\n\\n## Output\\n\\nphotosData.json: Every line stands for a photo and the format of a line is {\\\"photo\\\": {.........}, \\\"id\\\": \\\".......\\\"}\\n\\ntipsData.json: Every line stands for a tip and the format of a line is {\\\"tip\\\": {.........}, \\\"id\\\": \\\".......\\\"}\\n\\nvenues.json: Every line stands for a venue and the format of a line is {\\\"venue\\\": {.........}}\"\n },\n {\n \"alpha_fraction\": 0.593879222869873,\n \"alphanum_fraction\": 0.6253101825714111,\n \"avg_line_length\": 45.5,\n \"blob_id\": \"a8ca9f2f118a5cf6b5c48581ff355b0497c5edc0\",\n \"content_id\": \"01a6db8835815a634e1e88d88f4f672cab76e182\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1209,\n \"license_type\": \"no_license\",\n \"max_line_length\": 184,\n \"num_lines\": 26,\n \"path\": \"/Spider/XieCheng Hotel Data/hotel_index_data/hotel_index_data/spiders/hotel_index_data.py\",\n \"repo_name\": \"Zheng392/Python-Repository\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"\\nfrom scrapy.spiders import Spider\\nfrom scrapy import *\\nfrom scrapy.selector import Selector\\nimport re\\nimport json\\nimport xlrd\\nimport sys\\nimport re\\nfrom urllib.parse import urlencode\\nclass hotel_index_data(Spider):\\n name='hotel_index_data'\\n def start_requests(self):\\n url = \\\"https://hotels.ctrip.com/Domestic/Tool/AjaxHotelList.aspx\\\"\\n data = {'page': '1', 'cityPY': 'shanghai', 'cityId': '2', 'cityCode': '021',\\n\\n }\\n headers = {'Referer': 'http://hotels.ctrip.com/hotel/shanghai2',\\n 'Accept': '* / *', 'Accept-Encoding': 'gzip, deflate', 'Accept-Language': 'en-US,en;q=0.9', 'Cache-Control': 'max-age=0',\\n 'Content-Type': 'application/x-www-form-urlencoded; charset=UTF-8', 'Host': 'hotels.ctrip.com', 'Origin': 'http://hotels.ctrip.com',\\n 'Proxy-Connection': 'keep-alive', 'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/62.0.3202.75 Safari/537.36',\\n }\\n yield Request(url, self.parse, method=\\\"POST\\\", headers=headers, body=json.dumps(data))\\n\\n def parse(self, response):\\n data = json.loads(response.body)\\n print(data)\"\n },\n {\n \"alpha_fraction\": 0.747474730014801,\n \"alphanum_fraction\": 0.7575757503509521,\n \"avg_line_length\": 15.5,\n \"blob_id\": \"e10fd64787c467768c4bc097262d4007ed9a12c5\",\n \"content_id\": \"a8431a2ced2cd5b4a1423bff74287b37b595b8bb\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 99,\n \"license_type\": \"no_license\",\n \"max_line_length\": 42,\n \"num_lines\": 6,\n \"path\": \"/Spider/Jindong review data by Scrapy/jd_spider-fundamental/jd_spider/exec.py\",\n \"repo_name\": \"Zheng392/Python-Repository\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# coding:utf-8\\n\\nfrom scrapy import cmdline\\nimport json\\n\\ncmdline.execute(\\\"scrapy crawl jd\\\".split())\\n\"\n },\n {\n \"alpha_fraction\": 0.5968858003616333,\n \"alphanum_fraction\": 0.5968858003616333,\n \"avg_line_length\": 35.1875,\n \"blob_id\": \"26d3cc23ac27e9fe3359dd14d32fabfc5bc72af8\",\n \"content_id\": \"58c89c816a7f7baa72f383a5c846a01331e03934\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 578,\n \"license_type\": \"permissive\",\n \"max_line_length\": 107,\n \"num_lines\": 16,\n \"path\": \"/Foursquare research/Projects/Get venues/Data analysis.py\",\n \"repo_name\": \"Zheng392/Python-Repository\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import json\\nimport pandas as pd\\nimport numpy as np\\nvenues=[]\\nids=set()\\nwith open('venues.json','r') as f:\\n for line in f.readlines():\\n venue=json.loads(line)['venue']\\n venues.append([venue['id'],venue['name'],venue['stats']['tipCount'],venue['stats']['usersCount'],\\n venue['stats']['checkinsCount'],venue['location']['lat'],\\n venue['location']['lng']])\\n ids.add(venue['id'])\\n\\ndf=pd.DataFrame(np.array(venues),columns=['id','name','tipCount','usersCount','checkinsCount','lat','lng'])\\ndf.to_csv('data.csv')\\npass\"\n },\n {\n \"alpha_fraction\": 0.6331658363342285,\n \"alphanum_fraction\": 0.6633166074752808,\n \"avg_line_length\": 21.11111068725586,\n \"blob_id\": \"a6e53ad428ec2ba53a5ae3926986896be3c7f846\",\n \"content_id\": \"ecb5c521ffc1b5b8e16da91bff4d38fce896f0ac\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 199,\n \"license_type\": \"no_license\",\n \"max_line_length\": 49,\n \"num_lines\": 9,\n \"path\": \"/Foursquare research/Projects/Small Dataset creating/Get part lines.py\",\n \"repo_name\": \"Zheng392/Python-Repository\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"lines=[]\\nwith open('photo,user,venue,time.txt','r') as f:\\n\\tfor i in range(5000):\\n\\t\\tlines.append(f.readline())\\n\\n\\nwith open('photo,user,venue,time.txt','w') as f2:\\n\\tfor line in lines:\\n\\t\\tf2.write(line)\\n\"\n },\n {\n \"alpha_fraction\": 0.7524116039276123,\n \"alphanum_fraction\": 0.7524116039276123,\n \"avg_line_length\": 17.235294342041016,\n \"blob_id\": \"430c2484df751b2c57df444f72b3af9399a2dbdf\",\n \"content_id\": \"9a994ebe5d64a1cb60359b52804ab6d461ee433a\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 365,\n \"license_type\": \"no_license\",\n \"max_line_length\": 76,\n \"num_lines\": 17,\n \"path\": \"/README.md\",\n \"repo_name\": \"Zheng392/Python-Repository\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# Python Repository\\n\\nCollections of my code in python.\\n\\nNote：This repository is only used to backup my code，not for version control.\\n\\n## Contents\\n\\n*tutorial*: a Scrapy project for Build a spider project quickly\\n\\n*download pdf*: 自动批量下载文献\\n\\n*HTML-to-PDF*: 将HTML-to-PDF转成pdf\\n\\n*Spider*: 曾经用过的爬虫\\n\\n*Gamepad*: 游戏手柄控制器\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.8072289228439331,\n \"alphanum_fraction\": 0.8072289228439331,\n \"avg_line_length\": 41,\n \"blob_id\": \"00e3df1627d25380665c38bdc9f6163f2b9b877e\",\n \"content_id\": \"1d1aa085b42a66a14cd9a8a6b5d64bb58bc328fb\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 83,\n \"license_type\": \"no_license\",\n \"max_line_length\": 56,\n \"num_lines\": 2,\n \"path\": \"/Spider/XieCheng Hotel Data/hotel_index_data/begin.py\",\n \"repo_name\": \"Zheng392/Python-Repository\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from scrapy import cmdline\\ncmdline.execute('scrapy crawl hotel_index_data'.split())\"\n },\n {\n \"alpha_fraction\": 0.529335081577301,\n \"alphanum_fraction\": 0.5874034762382507,\n \"avg_line_length\": 41.78969955444336,\n \"blob_id\": \"1d000445cfdba6dfb231072aff6f1d47eb7b7b08\",\n \"content_id\": \"8e85ec38e9cf507e4413a8e3f5bc5edd82847ed9\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 10981,\n \"license_type\": \"no_license\",\n \"max_line_length\": 189,\n \"num_lines\": 233,\n \"path\": \"/Spider/XieCheng Hotel Data/Requests_threading/hotel_data_threading.py\",\n \"repo_name\": \"Zheng392/Python-Repository\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import requests,json,random\\nimport re,threading\\nimport json\\nfrom lxml import etree\\nimport time\\nimport random\\nlock=threading.Lock()\\n\\ncity='shanghai'\\nunsucesspage=[]\\nproxies=[]\\n# user_agent_list = [\\n# \\\"Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/537.1 (KHTML, like Gecko) Chrome/22.0.1207.1 Safari/537.1\\\" ,\\\\\\n# \\\"Mozilla/5.0 (X11; CrOS i686 2268.111.0) AppleWebKit/536.11 (KHTML, like Gecko) Chrome/20.0.1132.57 Safari/536.11\\\", \\\\\\n# \\\"Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/536.6 (KHTML, like Gecko) Chrome/20.0.1092.0 Safari/536.6\\\", \\\\\\n# \\\"Mozilla/5.0 (Windows NT 6.2) AppleWebKit/536.6 (KHTML, like Gecko) Chrome/20.0.1090.0 Safari/536.6\\\", \\\\\\n# \\\"Mozilla/5.0 (Windows NT 6.2; WOW64) AppleWebKit/537.1 (KHTML, like Gecko) Chrome/19.77.34.5 Safari/537.1\\\", \\\\\\n# \\\"Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/536.5 (KHTML, like Gecko) Chrome/19.0.1084.9 Safari/536.5\\\", \\\\\\n# \\\"Mozilla/5.0 (Windows NT 6.0) AppleWebKit/536.5 (KHTML, like Gecko) Chrome/19.0.1084.36 Safari/536.5\\\", \\\\\\n# \\\"Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/536.3 (KHTML, like Gecko) Chrome/19.0.1063.0 Safari/536.3\\\", \\\\\\n# \\\"Mozilla/5.0 (Windows NT 5.1) AppleWebKit/536.3 (KHTML, like Gecko) Chrome/19.0.1063.0 Safari/536.3\\\", \\\\\\n# \\\"Mozilla/5.0 (Macintosh; Intel Mac OS X 10_8_0) AppleWebKit/536.3 (KHTML, like Gecko) Chrome/19.0.1063.0 Safari/536.3\\\", \\\\\\n# \\\"Mozilla/5.0 (Windows NT 6.2) AppleWebKit/536.3 (KHTML, like Gecko) Chrome/19.0.1062.0 Safari/536.3\\\", \\\\\\n# \\\"Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/536.3 (KHTML, like Gecko) Chrome/19.0.1062.0 Safari/536.3\\\", \\\\\\n# \\\"Mozilla/5.0 (Windows NT 6.2) AppleWebKit/536.3 (KHTML, like Gecko) Chrome/19.0.1061.1 Safari/536.3\\\", \\\\\\n# \\\"Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/536.3 (KHTML, like Gecko) Chrome/19.0.1061.1 Safari/536.3\\\", \\\\\\n# \\\"Mozilla/5.0 (Windows NT 6.1) AppleWebKit/536.3 (KHTML, like Gecko) Chrome/19.0.1061.1 Safari/536.3\\\", \\\\\\n# \\\"Mozilla/5.0 (Windows NT 6.2) AppleWebKit/536.3 (KHTML, like Gecko) Chrome/19.0.1061.0 Safari/536.3\\\", \\\\\\n# \\\"Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/535.24 (KHTML, like Gecko) Chrome/19.0.1055.1 Safari/535.24\\\", \\\\\\n# \\\"Mozilla/5.0 (Windows NT 6.2; WOW64) AppleWebKit/535.24 (KHTML, like Gecko) Chrome/19.0.1055.1 Safari/535.24\\\"\\n# ]\\nuser_agent_list = [\\n'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/62.0.3202.89 Safari/537.36'\\n\\n ]\\n\\ncount=0\\ndef header_body_update(page):\\n data = {'cityPY': 'shanghai', 'cityId': 2, 'cityCode': '021','page':page}\\n headers = {'Referer': 'https://hotels.ctrip.com/hotel/shanghai2/sl1274819', \\\"Host\\\": \\\"hotels.ctrip.com\\\",\\n 'Origin':'http://hotels.ctrip.com',\\n \\\"Accept-Language\\\": \\\"en-US,en;q=0.9\\\",\\n \\\"Connection\\\": \\\"keep-alive\\\",\\n 'Accept': '* / *',\\n \\\"Accept-Encoding\\\": \\\"gzip, deflate\\\",\\n 'Cache-Control':'max-age=0',}\\n \\n headers['User-Agent'] = random.choice(user_agent_list)\\n return headers,data\\ndef proxy_update():\\n ip=random.sample(proxies,1)[0].replace('\\\\n','')\\n http='http://'+ip\\n proxy={'http' : http,\\n 'https': http}\\n\\n return proxy\\ndef get_page():\\n headers, data = header_body_update(1)\\n se=[]\\n while 1:\\n try:\\n proxy = proxy_update()\\n hotel_list_requests = requests.post('https://hotels.ctrip.com/Domestic/Tool/AjaxHotelList.aspx', data=data,\\n headers=headers,proxies=proxy)#\\n hotel_info = eval(hotel_list_requests.text)\\n text = hotel_info['paging']\\n se = etree.HTML(text)\\n page_number=json.loads(se.xpath('//a[@rel=\\\"nofollow\\\"]/text()')[0])\\n\\n break\\n except Exception as e:\\n print(e)\\n\\n \\n return page_number\\n\\ndef fang_com(page): ##列表页\\n # print('page is ',page)\\n headers,data=header_body_update(page)\\n prices=[]\\n hotel_lists=[]\\n fail_try=10\\n while(fail_try): ###这个主要是，fang.com会随机返回几个10054或者10053，如果连页面都没读取到，提取就是后话了，这网站没有封杀，即使使用单ip只会很少时候随机来几个10054 ，('Connection aborted.', error(10054, ''))\\n hotel_info={}\\n try:\\n proxy = proxy_update()\\n hotel_list_requests=requests.post('https://hotels.ctrip.com/Domestic/Tool/AjaxHotelList.aspx', data=data,\\n headers=headers)#,timeout=2,proxies=proxy\\n text=hotel_list_requests.text\\n \\n hotel_info=eval(text)\\n prices = json.loads(hotel_info['HotelMaiDianData']['value']['htllist'])\\n hotel_lists = hotel_info['hotelPositionJSON']\\n for hotel, price in zip(hotel_lists, prices):\\n hotel.update(price)\\n\\n line = json.dumps(hotel) + '\\\\n'\\n file.write(line)\\n print(hotel_lists)\\n print('success',page)\\n break\\n #print text\\n except Exception as e:\\n print(e)\\n fail_try=fail_try-1\\n if fail_try==0:\\n print('unsuccess page',page)\\n\\n\\n\\n\\n time.sleep(1)\\n\\n # lock.acquire()\\n # print(hotel_lists)\\n # lock.release()\\n\\n'''\\n text=''\\n se = etree.HTML(text) ###########为了利于大家学习，这段演示xpath提取信息\\n all_dl=se.xpath('//dl[@class=\\\"list rel\\\"]')\\n print(len(all_dl))\\n for dl in all_dl:\\n title=dl.xpath('.//dd[@class=\\\"info rel floatr\\\"]/p[@class=\\\"title\\\"]/a/text()')[0]\\n url=dl.xpath('.//dd[@class=\\\"info rel floatr\\\"]/p[@class=\\\"title\\\"]/a/@href')[0]\\n url='http://esf.sz.fang.com'+url\\n\\n info_list=dl.xpath('.//dd[@class=\\\"info rel floatr\\\"]/p[@class=\\\"mt12\\\"]/text()')\\n #print json.dumps(info,ensure_ascii=False) #py2显示汉字，py3可以直接print mt12\\n info=''\\n for l in info_list:\\n l2= re.findall('\\\\S*',l)[0] ###消除空白和换行\\n #print m_str\\n info+=l2+'|'\\n\\n time.sleep(1)\\n # total_price,price_squere,huxin,cankao_shoufu,shiyong_mianji,jianzhu_mianji,years,discription=get_detail(url)\\n\\n\\n lock.acquire() ###这里叫锁，一是保证count计数准确，而是不会导致多个线程乱print，导致看不清楚。加锁的目的是别的线程不能运行这段代码了。但我之前看到有的人乱加锁，把消耗时间很长的代码加锁，那样导致多线程就基本个废物\\n global count\\n count+=1\\n print(time.strftime('%H:%M:%S', time.localtime(time.time())), ' ', count)\\n print('列表页：')\\n print(' title: %s\\\\n url: %s\\\\n info: %s\\\\n' % (title, url, info))\\n\\n print('详情页:')\\n # print(\\n # ' total_price: %s\\\\n price_squere: %s\\\\n huxin: %s\\\\n cankao_shoufu: %s\\\\n shiyong_mianji: %s\\\\n jianzhu_mianji: %s\\\\n years: %s \\\\n' % (\\n # total_price, price_squere, huxin, cankao_shoufu, shiyong_mianji, jianzhu_mianji, years))\\n print('**************************************************************')\\n lock.release()\\n\\n'''\\n\\ndef get_detail(url): ###详情页\\n\\n header={'User-Agent':random.choice(user_agent_list)}\\n header.update({\\\"Host\\\":\\\"esf.sz.fang.com\\\"})\\n\\n while(1):\\n content=''\\n try:\\n content=requests.get(url,headers=header,timeout=10).content\\n except Exception as e:\\n print(e)\\n pass\\n if content!='':\\n break\\n\\n content=content.decode('gbk').encode('utf8') ##查看网页源代码可看到是gbk编码，直接print的话，如果你在pycharm设置控制台是utf8编码，那么控制台的中文则会乱码，cmd是gbk的恰好可以显示。如果你在pycharm设置控制台是utf8编码，需要这样做\\n #print content\\n\\n inforTxt=getlist0(re.findall('(
[\\\\s\\\\S]*?)
- ',content)) ###########为了利于大家学习，这段演示正则表达式提取信息，某些信息可能在有的房子界面没有，要做好判断\\n #print inforTxt\\n\\n total_price=getlist0(re.findall('价：(.*?)',inforTxt))\\n\\n price_squere=getlist0(re.findall('class=\\\"black\\\">万\\\\((\\\\d+?)元[\\\\s\\\\S]*?户型：(.*?)',inforTxt))\\n cankao_shoufu=getlist0(re.findall('参考首付：(.*?万) ',inforTxt))\\n shiyong_mianji=getlist0(re.findall('>使用面积：(.*?)',inforTxt))\\n shiyong_mianji=getlist0(re.findall('\\\\d+',shiyong_mianji))\\n jianzhu_mianji=getlist0(re.findall('建筑面积：(.*?)',inforTxt))\\n jianzhu_mianji=getlist0(re.findall('\\\\d+',jianzhu_mianji))\\n years=getlist0(re.findall('年代：(.*?)',inforTxt))\\n\\n discription=getlist0(re.findall('style=\\\"-moz-user-select: none;\\\">([\\\\s\\\\S]*?)
0):\\n matrix=np.array(Alldata)\\n cov=np.cov(matrix)\\n sigma=(1/(i+1))**2*np.sum(cov)\\n allsigma.append(sigma)\\n # rng = pd.date_range(start='7/19/2016', end='10/18/2016', freq='20min')\\n # rng = pd.DataFrame(pd.Series(rng), columns=[\\\"time_window\\\"]).set_index(\\\"time_window\\\")\\n pass\\n # data.to_excel('stock of %s.xlsx' % stock)\\nallsigma=pd.Series(allsigma)\\nallsigma.to_csv('sigma4.csv')\\npass\"\n },\n {\n \"alpha_fraction\": 0.6072629690170288,\n \"alphanum_fraction\": 0.614660382270813,\n \"avg_line_length\": 26.054546356201172,\n \"blob_id\": \"1b191d19ec29a71e98b26779431e49c40408bfe2\",\n \"content_id\": \"9a38bd94cf96483ebe2e0764099e3e0ab2040f2e\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1815,\n \"license_type\": \"no_license\",\n \"max_line_length\": 51,\n \"num_lines\": 55,\n \"path\": \"/Spider/Jindong review data by Scrapy/jdcomment/jd_spider/items.py\",\n \"repo_name\": \"Zheng392/Python-Repository\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: utf-8 -*-\\n\\n# Define here the models for your scraped items\\n#\\n# See documentation in:\\n# http://doc.scrapy.org/en/latest/topics/items.html\\n\\nimport scrapy\\nfrom scrapy import Item, Field\\n\\n\\nclass JdSpiderItem(scrapy.Item):\\n # define the fields for your item here like:\\n # name = scrapy.Field()\\n pass\\n\\n\\nclass goodsItem(Item):\\n link = Field() # 商品链接\\n ID = Field() # 商品ID\\n name = Field() # 商品名字\\n comment_num = Field() # 评论人数\\n shop_name = Field() # 店家名字\\n price = Field() # 价钱\\n commentVersion = Field() # 为了得到评论的地址需要该字段\\n score1count = Field() # 评分为1星的人数\\n score2count = Field() # 评分为2星的人数\\n score3count = Field() # 评分为3星的人数\\n score4count = Field() # 评分为4星的人数\\n score5count = Field() # 评分为5星的人数\\n\\n\\nclass commentItem(Item):\\n user_name = Field() # 评论用户的名字\\n user_ID = Field() # 评论用户的ID\\n userProvince = Field() # 评论用户来自的地区\\n content = Field() # 评论内容\\n good_ID = Field() # 评论的商品ID\\n good_name = Field() # 评论的商品名字\\n date = Field() # 评论时间\\n replyCount = Field() # 回复数\\n score = Field() # 评分\\n status = Field() # 状态\\n title = Field()\\n userLevelId = Field()\\n userRegisterTime = Field() # 用户注册时间\\n productColor = Field() # 商品颜色\\n productSize = Field() # 商品大小\\n userLevelName = Field() # 银牌会员，钻石会员等\\n userClientShow = Field() # 来自什么 比如来自京东客户端\\n isMobile = Field() # 是否来自手机\\n days = Field() # 天数\\n commentTags = Field() # 标签\\n usefulVoteCount=Field()\\n uselessVoteCount=Field()\"\n },\n {\n \"alpha_fraction\": 0.5719166398048401,\n \"alphanum_fraction\": 0.6498121023178101,\n \"avg_line_length\": 29.5,\n \"blob_id\": \"059b82e001ecfb34e1ccba9ff37638b6210c5318\",\n \"content_id\": \"726e6e2e9f8e3845c404e7a3ec5d6c5019b88059\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 2927,\n \"license_type\": \"no_license\",\n \"max_line_length\": 173,\n \"num_lines\": 96,\n \"path\": \"/download pdf/test.py\",\n \"repo_name\": \"Zheng392/Python-Repository\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import requests\\nfrom lxml import etree\\nimport os\\nimport re\\nfrom selenium import webdriver\\n\\nfrom selenium.webdriver.chrome.options import Options\\nfrom selenium.webdriver.common.by import By\\nfrom selenium.webdriver.common.keys import Keys\\nfrom selenium.webdriver.support import expected_conditions as EC\\nfrom selenium.webdriver.support.wait import WebDriverWait\\nimport json\\nimport time\\n\\ndef get_html(url):\\n headers={\\n 'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/71.0.3578.98 Safari/537.36'\\n }\\n\\n r=requests.get(url,headers=headers)\\n # print(r.text)\\n html=etree.HTML(r.text)\\n result=html.xpath('//*[@id=\\\"article-list\\\"]/form/div[3]/ol/li/dl/dd[4]/a/@href')\\n if result==[]:\\n result = html.xpath('//*[@id=\\\"article-list\\\"]/form/div[3]/ol//ol/li/dl/dd[4]/a/@href')\\n return result\\n\\ndef save_pdf(url,folder,name):\\n headers = {\\n 'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/71.0.3578.98 Safari/537.36'\\n }\\n if os.path.exists(folder+'/'+name+'.pdf'):\\n return\\n\\n chrome_options = Options()\\n # chrome_options.add_argument('--headless')\\n # chrome_options.add_argument('--disable-gpu')\\n browser = webdriver.Chrome(chrome_options=chrome_options)\\n browser.get(url)\\n # time.sleep(1)\\n url=browser.current_url\\n browser.close()\\n\\n r = requests.get(url, headers=headers)\\n if not os.path.exists(folder):\\n os.makedirs(folder)\\n\\n\\n with open(folder+'/'+name+'.pdf','wb') as f:\\n f.write(r.content)\\n\\n'''test download pdf\\nurl='https://ac.els-cdn.com/S0306457315000242/1-s2.0-S0306457315000242-main.pdf?_tid=44624573-386b-4ebf-921c-825259bf4488&acdnat=1545467755_f582eab50ca643aeeb8c4ecf4756a951'\\nsave_pdf(url,'test','aaa')\\n\\n'''\\n\\n'''test selenium\\n\\n\\n\\nbrowser= webdriver.Chrome()\\nurl='https://www.sciencedirect.com/science/article/pii/S0306457315000242/pdfft?md5=abece181b57cc15e01f82237124b92d9&pid=1-s2.0-S0306457315000242-main.pdf'\\nbrowser.get(url)\\nprint(browser.current_url)\\nbrowser.close()\\npass\\n\\n\\n'''\\n\\n\\n\\nif __name__=='__main__':\\n links={}\\n # for i in range(4):\\n # for j in range(6):\\n # url = 'https://www.sciencedirect.com/journal/information-processing-and-management/vol/%d/issue/%d'%(51+i,j+1)\\n # links['vol%dissue%d'%(51+i,j+1)]=get_html(url)\\n # print('get links of vol%d issue%d '%(51+i,j+1))\\n\\n\\n # with open('data2.json','w') as file:\\n # file.write(json.dumps(links))\\n with open('data2.json','r') as file:\\n links=json.loads(file.read())\\n\\n\\n\\n for i in range(4):\\n for j in range(6):\\n part=links['vol%dissue%d'%(51+i,j+1)]\\n for l,u in enumerate(part):\\n url='https://www.sciencedirect.com'+u\\n save_pdf(url, 'vol%d/issue%d'%(51+i,j+1),str(l))\\n print('save pdf of vol%d issue%d %d'%(51+i,j+1,l))\"\n },\n {\n \"alpha_fraction\": 0.517257571220398,\n \"alphanum_fraction\": 0.5372152924537659,\n \"avg_line_length\": 37.36936950683594,\n \"blob_id\": \"0e6973e42970ffc8522495a3390f8e7696b488dc\",\n \"content_id\": \"0ae5c4e8321d4e46010a291fc5ccae277e945aef\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 4435,\n \"license_type\": \"no_license\",\n \"max_line_length\": 119,\n \"num_lines\": 111,\n \"path\": \"/Spider/Jindong review data by Scrapy/jdcomment/jd_spider/spiders/jd_comment.py\",\n \"repo_name\": \"Zheng392/Python-Repository\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: utf-8 -*-\\nfrom scrapy.spiders import Spider\\nfrom jd_spider.items import goodsItem, commentItem\\nfrom scrapy.selector import Selector\\nimport re\\nimport json\\nimport xlrd\\nimport sys\\nimport re\\nfrom urllib.parse import urlencode\\nclass comment_spider(Spider):\\n name = \\\"comment2\\\"\\n IDs = []\\n file = open(\\\"./data/women_cloth_data.json\\\", 'r')\\n for line in file:\\n line = line.strip()\\n try: # try parsing to dict\\n a = json.loads(line)\\n IDs.append(a[\\\"ID\\\"])\\n except:\\n print(repr(line))\\n print(sys.exc_info())\\n print(\\\"fail\\\")\\n file.close()\\n url = 'https://club.jd.com/comment/skuProductPageComments.action'\\n data = {\\n 'callback': 'fetchJSON_comment98vv61',\\n 'productId': '3555984',\\n 'score': 0, # all 0 bad 1 mid 2 good 3 zhuiping 5\\n 'sortType': 5, # time series rank 6 recommend rank 5\\n 'pageSize': 10,\\n 'isShadowSku': 0,\\n 'page': 0\\n }\\n start_urls = []\\n for ID in IDs:\\n try:\\n data[\\\"productId\\\"] = ID[0]\\n except:\\n pass\\n for page in range(1,6):\\n data['page']=page\\n data['score'] = 1\\n comb_url=url+'?'+urlencode(data)\\n start_urls.append(comb_url)\\n data['score'] = 3\\n comb_url = url + '?' + urlencode(data)\\n start_urls.append(comb_url)\\n\\n # name = \\\"comment2\\\"\\n # xlrd.Book.encoding = \\\"utf-8\\\"\\n # data = xlrd.open_workbook(\\\"goods.xls\\\")\\n # # goods为要抓取评论的商品信息，现提供一个goods.xls文件供参考,第1列：商品ID；第2列：商品评论数；第3列：商品的commentVersion\\n # # test.xlsx也可以使用\\n # table = data.sheets()[0]\\n # nrows = table.nrows # 行数\\n # ncols = table.ncols # 列数\\n # good_id = table.col_values(0) # 商品ID\\n # comment_n = table.col_values(1) # 商品评论数\\n # comment_V = table.col_values(2) # 商品评论的commentVersion\\n #\\n # start_urls = []\\n # for i in range(len(good_id)): # 一件商品一件商品的抽取\\n # good_num = int(good_id[i])\\n # comment_total = int(comment_n[i])\\n # if comment_total % 10 == 0: # 算出评论的页数，一页10条评论\\n # page = comment_total/10\\n # else:\\n # page = comment_total/10 + 1\\n # for k in range(0, int(page)):\\n # url = \\\"http://sclub.jd.com/productpage/p-\\\" + str(good_num) + \\\"-s-0-t-3-p-\\\" + str(k) \\\\\\n # + \\\".html?callback=fetchJSON_comment98vv\\\" #+ str(comment_V[i])\\n # start_urls.append(url)\\n\\n def parse(self, response):\\n m = re.search(r'(?<=fetchJSON_comment98vv61\\\\().*(?=\\\\);)', response.body.decode('gbk',errors='ignore')).group(0)\\n j = json.loads(m)\\n commentSummary = j['comments']\\n items = []\\n for comment in commentSummary:\\n item1 = commentItem()\\n item1['user_name'] = comment['nickname']\\n item1['user_ID'] = comment['id']\\n item1['userProvince'] = comment['userProvince']\\n item1['content'] = comment['content'].replace('\\\\n','')\\n item1['good_ID'] = comment['referenceId']\\n item1['userClientShow'] = comment['userClientShow']\\n item1['good_name'] = comment['referenceName']\\n item1['date'] = comment['referenceTime']\\n item1['replyCount'] = comment['replyCount']\\n item1['score'] = comment['score']\\n item1['uselessVoteCount']=comment[\\\"uselessVoteCount\\\"]\\n item1['usefulVoteCount']=comment['usefulVoteCount']\\n # item1['status'] = comment['status']\\n # title = \\\"\\\"\\n # if 'title'in comment:\\n # item1['title'] = comment['title']\\n # item1['title'] = title\\n # item1['userRegisterTime'] = comment['userRegisterTime']\\n # item1['productColor'] = comment['productColor']\\n # item1['productSize'] = comment['productSize']\\n # item1['userLevelName'] = comment['userLevelName']\\n # item1['isMobile'] = comment['isMobile']\\n # item1['days'] = comment['days']\\n # tags = \\\"\\\"\\n # if 'commentTags' in comment:\\n # for i in comment['commentTags']:\\n # tags = tags + i['name'] + \\\" \\\"\\n # item1['commentTags'] = tags\\n #items.append(item1)\\n yield item1\\n\"\n },\n {\n \"alpha_fraction\": 0.6158690452575684,\n \"alphanum_fraction\": 0.6750629544258118,\n \"avg_line_length\": 36.85714340209961,\n \"blob_id\": \"ec9616fbfd35c88556bfdec01702a20333d427e1\",\n \"content_id\": \"2d04b7d49c4aef5eff001761849af2330bc592b1\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 794,\n \"license_type\": \"no_license\",\n \"max_line_length\": 143,\n \"num_lines\": 21,\n \"path\": \"/Spider/Shanghai Stock Exchange data by requests/Shanghai Stock Exchange data.py\",\n \"repo_name\": \"Zheng392/Python-Repository\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import requests\\n\\nheaders = {'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/62.0.3202.75 Safari/537.36',\\\\\\n 'Referer': 'http: // www.sse.com.cn / disclosure / dealinstruc / suspension /'\\n}\\npayload = {'jsonCallBack': 'vajsonpCallback68485', 'isPagination': 'true', 'bgFlag': '1', \\\\\\n 'pageHelp.pageNo': '1', 'pageHelp.beginPage': '1'}\\nparams={\\\"isPagination\\\": 'true','searchDate': \\\"\\\",'bgFlag': 1,\\n'searchDo': 1,\\\\\\n\\\"pageHelp.pageSize\\\": 1500,\\\\\\n\\\"pageHelp.pageNo\\\": 1,\\\\\\n\\\"pageHelp.beginPage\\\": 1,\\\\\\n\\\"pageHelp.cacheSize\\\": 1,\\\\\\n\\\"pageHelp.endPage\\\": 3,\\\\\\n'desc':\\\"\\\",\\\\\\n'pageCache':1\\n}\\nr=requests.get(url='http://query.sse.com.cn/infodisplay/querySpecialTipsInfoByPage.do',params=params,headers=headers)\\nprint(r.headers)\\nprint(r.json())\\npass\"\n },\n {\n \"alpha_fraction\": 0.7878788113594055,\n \"alphanum_fraction\": 0.7878788113594055,\n \"avg_line_length\": 32,\n \"blob_id\": \"b8809293153bdefe1586f9af408c426cd4528adf\",\n \"content_id\": \"ca3f9ae8160644f4f026486100edc20477b818e9\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 63,\n \"license_type\": \"no_license\",\n \"max_line_length\": 32,\n \"num_lines\": 1,\n \"path\": \"/download pdf/README.md\",\n \"repo_name\": \"Zheng392/Python-Repository\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"*rename.pdf*: 读取pdf获得文章名然后重命名文件。\\n\"\n },\n {\n \"alpha_fraction\": 0.49803921580314636,\n \"alphanum_fraction\": 0.505591869354248,\n \"avg_line_length\": 39.26315689086914,\n \"blob_id\": \"c47671c66f750881afcf4826adcb4c62293c4a59\",\n \"content_id\": \"95f59b9533bb9430b50c9369d22f14ef1346eb19\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 6885,\n \"license_type\": \"no_license\",\n \"max_line_length\": 246,\n \"num_lines\": 171,\n \"path\": \"/Spider/Jindong review data by Scrapy/jdcomment/jd_spider/pipelines.py\",\n \"repo_name\": \"Zheng392/Python-Repository\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: utf-8 -*-\\n\\n# Define your item pipelines here\\n#\\n# Don't forget to add your pipeline to the ITEM_PIPELINES setting\\n# See: http://doc.scrapy.org/en/latest/topics/item-pipeline.html\\nimport pymysql.cursors\\nimport json\\n\\nfrom twisted.enterprise import adbapi\\n\\nfrom scrapy.xlib.pydispatch import dispatcher\\nfrom scrapy import signals\\nfrom scrapy.utils.project import get_project_settings\\nfrom scrapy import log\\n# import chardet\\n\\nSETTINGS = get_project_settings()\\n\\n#\\n# class MySQLPipeline(object):\\n# @classmethod\\n# def from_crawler(cls, crawler):\\n# return cls(crawler.stats)\\n#\\n# def __init__(self, stats):\\n# # Instantiate DB\\n# self.file=open('phone_data.json', 'w', encoding='utf-8')\\n# # self.dbpool = adbapi.ConnectionPool('pymysql',\\n# # host=SETTINGS['DB_HOST'],\\n# # user=SETTINGS['DB_USER'],\\n# # passwd=SETTINGS['DB_PASSWD'],\\n# # port=SETTINGS['DB_PORT'],\\n# # db=SETTINGS['DB_DB'],\\n# # charset='utf8',\\n# # use_unicode=True,\\n# # cursorclass=pymysql.cursors.DictCursor\\n# # )\\n# # self.stats = stats\\n# # dispatcher.connect(self.spider_closed, signals.spider_closed)\\n#\\n# def spider_closed(self, spider):\\n# print(\\\"done!!!\\\")\\n#\\n# \\\"\\\"\\\" Cleanup function, called after crawing has finished to close open\\n# objects.\\n# Close ConnectionPool. \\\"\\\"\\\"\\n# # self.dbpool.close()\\n#\\n# def process_item(self, item, spider):\\n# line=json.dumps(dict(item,ensure_ascii=False))+'\\\\n'\\n# self.file.write(line)\\n#\\n# # query = self.dbpool.runInteraction(self._insert_record, item)\\n# # query.addErrback(self._handle_error)\\n# return item\\n#\\n# def _insert_record(self, tx, item):\\n# ID = item['ID'][0]\\n# name = item['name'][0]\\n# comment_num = str(item['comment_num'])\\n# shop_name = item['shop_name'][0]\\n# link = item['link'][0]\\n# commentVersion = str(item['commentVersion'])\\n# commentVersion = commentVersion[1:-1]\\n#\\n# score1count = str(item['score1count'])\\n# score2count = str(item['score2count'])\\n# score3count = str(item['score3count'])\\n# score4count = str(item['score4count'])\\n# score5count = str(item['score5count'])\\n#\\n# price = str(item['price'])\\n#\\n# ID = ID.encode('utf-8')\\n# name = name.encode('utf-8')\\n# comment_num = comment_num.encode('utf-8')\\n# shop_name = shop_name.encode('utf-8')\\n# link = link.encode('utf-8')\\n# commentVersion = commentVersion.encode('utf-8')\\n# score1count = score1count.encode('utf-8')\\n# score2count = score2count.encode('utf-8')\\n# score3count = score3count.encode('utf-8')\\n# score4count = score4count.encode('utf-8')\\n# score5count = score5count.encode('utf-8')\\n# price = price.encode('utf-8')\\n#\\n# sql = \\\"INSERT INTO jd_goods VALUES ('%s', '%s', '%s', '%s', '%s', '%s', '%s', '%s', '%s', '%s', '%s', '%s')\\\" % \\\\\\n# (ID, name, comment_num, shop_name, link, commentVersion, score1count, score2count, score3count,\\n# score4count, score5count, price)\\n# tx.execute(sql)\\n# print(\\\"yes\\\")\\n#\\n# def _handle_error(self, e):\\n# log.err(e)\\n\\n\\nclass CommentPipeline(object):\\n # @classmethod\\n # def from_crawler(cls, crawler):\\n # return cls(crawler.stats)\\n\\n def __init__(self):\\n self.count=0\\n self.allline=[]\\n self.file = open('women_cloth_comment.csv', 'w', encoding='utf-8')\\n # Instantiate DB\\n # self.dbpool = adbapi.ConnectionPool('pymysql',\\n # host=SETTINGS['DB_HOST'],\\n # user=SETTINGS['DB_USER'],\\n # passwd=SETTINGS['DB_PASSWD'],\\n # port=SETTINGS['DB_PORT'],\\n # db=SETTINGS['DB_DB'],\\n # charset='utf8',\\n # use_unicode=True,\\n # cursorclass=pymysql.cursors.DictCursor\\n # )\\n # self.stats = stats\\n # dispatcher.connect(self.spider_closed, signals.spider_closed)\\n\\n def spider_closed(self, spider):\\n \\\"\\\"\\\" Cleanup function, called after crawing has finished to close open\\n objects.\\n Close ConnectionPool. \\\"\\\"\\\"\\n # self.dbpool.close()\\n print(\\\"done2!!!\\\")\\n def process_item(self, item, spider):\\n # query = self.dbpool.runInteraction(self._insert_record, item)\\n # query.addErrback(self._handle_error)\\n self.count=self.count+1\\n line = '0'+','+ str(item['score'])+','+ str(item['user_ID'])+','+ item['content'] +','+ str(item['good_ID']) +','+item['userClientShow'] +','+ str(item['replyCount'])+','+str(item['uselessVoteCount'])+','+str(item['usefulVoteCount'])+'\\\\n'\\n if line not in self.allline:\\n self.file.write(line)\\n self.allline.append(line)\\n else:\\n print('repetition!!')\\n\\n print(\\\"scrapy item num is\\\",self.count)\\n return item\\n\\n # def _insert_record(self, tx, item):\\n # user_name = item['user_name']\\n # user_ID = item['user_ID']\\n # userProvince = item['userProvince']\\n # content = item['content']\\n # good_ID = item['good_ID']\\n # good_name = item['good_name']\\n # date = item['date']\\n # replyCount = item['replyCount']\\n # score = item['score']\\n # status = item['status']\\n # title = item['title']\\n # userRegisterTime = item['userRegisterTime']\\n # productColor = item['productColor']\\n # productSize = item['productSize']\\n # userLevelName = item['userLevelName']\\n # isMobile = item['isMobile']\\n # days = item['days']\\n # tags = item['commentTags']\\n #\\n # sql = \\\"INSERT INTO jd_comment VALUES ('%s', '%s', '%s', '%s', '%s', '%s', '%s', '%s', '%s', '%s',\\\" \\\\\\n # \\\"'%s', '%s', '%s', '%s', '%s', '%s', '%s', '%s')\\\" % \\\\\\n # (user_name, user_ID, userProvince, content, good_ID, good_name, date, replyCount, score,\\n # status, title, userRegisterTime, productColor, productSize, userLevelName,\\n # isMobile, days, tags)\\n #\\n # tx.execute(sql)\\n # print(\\\"yes\\\")\\n\\n def _handle_error(self, e):\\n log.err(e)\\n\"\n },\n {\n \"alpha_fraction\": 0.6912065148353577,\n \"alphanum_fraction\": 0.6932515501976013,\n \"avg_line_length\": 24.789474487304688,\n \"blob_id\": \"26aae946ac43fbb6332cd83cd9d7fe97eb7c8116\",\n \"content_id\": \"e8c2df4c789bb58cf88cced36a894ea507a466a3\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 489,\n \"license_type\": \"no_license\",\n \"max_line_length\": 73,\n \"num_lines\": 19,\n \"path\": \"/Spider/XieCheng Hotel Data/xiecheng selenium/text/xiechengservices/DriveServices.py\",\n \"repo_name\": \"Zheng392/Python-Repository\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding:utf-8 -*-\\n__author__ = 'LiuYang'\\nfrom services.xiechengservices.DriveServices import XiechengDriverService\\n\\nclass DriverServiceTest(object):\\n\\n def __init__(self):\\n self.xiechengDriverService = XiechengDriverService()\\n\\n def crawlxiechengTest(self):\\n self.xiechengDriverService.start()\\n self.xiechengDriverService.depose()\\n\\n\\nif __name__ == \\\"__main__\\\":\\n\\n driverServiceTest = DriverServiceTest()\\n\\n driverServiceTest.crawlxiechengTest()\"\n },\n {\n \"alpha_fraction\": 0.6729399561882019,\n \"alphanum_fraction\": 0.7105798721313477,\n \"avg_line_length\": 25.945205688476562,\n \"blob_id\": \"1dbf999423708fabeedc917859a42432eddfa9f3\",\n \"content_id\": \"6a08ccaa9cf3a6d9e38e091733d8e392078af975\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 2384,\n \"license_type\": \"no_license\",\n \"max_line_length\": 74,\n \"num_lines\": 73,\n \"path\": \"/Spider/XieCheng Hotel Data/xiecheng selenium/README.md\",\n \"repo_name\": \"Zheng392/Python-Repository\",\n \"src_encoding\": \"GB18030\",\n \"text\": \"xiecheng\\n=================================\\n\\n众源时空信息聚合平台\\n--------------------------\\n\\n##基本信息：\\n\\n基于scrapy+selenium的爬去策略，以南京市为例，抽取南京市酒店的基本信息数据与酒店点评数据
\\n\\n##使用Python 库：\\n1.scrapy，网上安装方法许多，可自行下载相关依赖
\\n\\n2.selenium
\\n可以直接使用pip进行安装
\\n\\nSelenium也是一个用于Web应用程序测试的工具。Selenium测试直接运行在浏览器中，就像真正的用户在操作一样。
\\n\\n\\n##使用驱动:\\n1.Chrome驱动
\\n下载地址：http://npm.taobao.org/mirrors/chromedriver
\\n\\nselenium调用需要，需下载系统对应版本，将其放置到系统能直接访问的文件夹，如放在{PYTHON_HOME}/Scripts文件夹中
\\n\\n\\n##数据库：\\n\\n###数据库名:xiecheng\\n1.hotellianjie（存储酒店url）
\\n```sql\\nDROP TABLE IF EXISTS `hotellianjie`;\\nCREATE TABLE `hotellianjie` (\\n `guid` varchar(255) DEFAULT NULL,\\n `lianjie` varchar(255) DEFAULT NULL,\\n `city` varchar(30) DEFAULT NULL,\\n `comm_num` int(30) DEFAULT NULL\\n) ENGINE=InnoDB DEFAULT CHARSET=utf8;\\n```\\n2.hotelinfo（酒店基本信息数据）
\\n```sql\\nDROP TABLE IF EXISTS `hotelinfo`;\\nCREATE TABLE `hotelinfo` (\\n `guid` varchar(255) DEFAULT NULL,\\n `city` varchar(30) DEFAULT NULL,\\n `title` varchar(60) DEFAULT NULL,\\n `price` decimal(10,1) DEFAULT NULL,\\n `score` int(20) DEFAULT NULL,\\n `recommend` varchar(120) DEFAULT NULL,\\n `area` varchar(120) DEFAULT NULL,\\n `havawifi` varchar(20) DEFAULT NULL,\\n `discussNum` int(11) DEFAULT NULL,\\n `common_facilities` varchar(500) DEFAULT NULL,\\n `activity_facilities` varchar(255) DEFAULT NULL,\\n `service_facilities` varchar(255) DEFAULT NULL,\\n `room_facilities` varchar(255) DEFAULT NULL,\\n `around_facilities` varchar(255) DEFAULT NULL\\n) ENGINE=InnoDB DEFAULT CHARSET=utf8;\\n```\\n3.hotelcommentinfo（存储酒店评论数据）
\\n```sql\\nDROP TABLE IF EXISTS `hotelcommentinfo`;\\nCREATE TABLE `hotelcommentinfo` (\\n `hotelname` varchar(50) DEFAULT NULL,\\n `username` varchar(40) DEFAULT NULL,\\n `commentscore` varchar(40) DEFAULT NULL,\\n `intime` varchar(40) DEFAULT NULL,\\n `tourstyle` varchar(40) DEFAULT NULL,\\n `praisenum` int(11) DEFAULT NULL,\\n `commenttime` varchar(60) DEFAULT NULL,\\n `comment` varchar(1000) DEFAULT NULL\\n) ENGINE=InnoDB DEFAULT CHARSET=utf8;\\n```\"\n },\n {\n \"alpha_fraction\": 0.46783626079559326,\n \"alphanum_fraction\": 0.4938271641731262,\n \"avg_line_length\": 27.165138244628906,\n \"blob_id\": \"40cbb623bd7a6e0658e92668be6d67c464eca3aa\",\n \"content_id\": \"cc44b77ed77b623ecf41436d85bae434ce4fad66\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 3244,\n \"license_type\": \"no_license\",\n \"max_line_length\": 85,\n \"num_lines\": 109,\n \"path\": \"/Foursquare research/Projects/Small Dataset creating/Data_scraping.py\",\n \"repo_name\": \"Zheng392/Python-Repository\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import pandas as pd\\n\\n\\ndef get_tuple(f,max = 10):#获得(user,time,id)的元组\\n n = 1\\n while n<= max:\\n line = f.readline().split('\\\\t')\\n user = line[0]\\n venue = line[1]\\n # 1 = line[2]\\n time = line[3]\\n photo_id = line[4].split('\\\\n')[0]\\n TUPLE = (user,time,photo_id)\\n yield TUPLE\\n n += 1\\n #print(TUPLE)\\n\\ndef divide_time(start,end,num=10):#均分时间段\\n list = []\\n gap = (end - start)/num\\n for i in range(num+1):\\n list.append(start+i*gap)\\n return list\\n\\ndef find_time_index(time,list):#在均分的时间点list里找到时间的位置\\n for i in range(len(list)):\\n if i == len(list)-1 and time == list[i]:\\n return len(list)-1\\n break\\n if list[i]<=time=1):\\n # 循环次数加1\\n loopNum = loopNum + 1\\n # 到达页面90%处\\n js=\\\"var q=document.documentElement.scrollTop=9000\\\"\\n self.driver.execute_script(js)\\n # 当页面中出现“返前价”字样时，爬取页面并跳转到下一页\\n if u\\\"收藏\\\" in self.driver.page_source:\\n # 对未解析过的页面进行解析\\n if ifHandle==False:\\n self.crawllianjie(self.driver.page_source)\\n ifHandle = True\\n # 跳转到下一页\\n if u\\\"下一页\\\" in self.driver.page_source:\\n # self.driver.find_element_by_partial_link_text(u\\\"下一页\\\").click()\\n pageNum = pageNum - 1\\n # self.driver.find_element_by_xpath(\\\"//a[@class='c_down']\\\").click()\\n element = self.driver.find_element_by_xpath(\\\"//a[@class='c_down']\\\")\\n self.driver.execute_script(\\\"arguments[0].click();\\\", element)\\n # 处理标识重新置为未处理\\n ifHandle = False\\n # 单页循环次数置为零\\n loopNum = 0\\n time.sleep(random.uniform(3, 6))\\n print(\\\"页数：\\\" + str(pageNum))\\n # try:\\n # if u\\\"下一页\\\" in self.driver.page_source:\\n # # self.driver.find_element_by_partial_link_text(u\\\"下一页\\\").click()\\n # pageNum = pageNum - 1\\n # self.driver.find_element_by_xpath(\\\"//a[@class='c_down']\\\").click()\\n # # 处理标识重新置为未处理\\n # ifHandle = False\\n # # 单页循环次数置为零\\n # loopNum = 0\\n # time.sleep(random.uniform(3, 6))\\n # print(\\\"页数：\\\" + str(pageNum))\\n # except :\\n # pageNum = pageNum + 1\\n # 将当前的错误页保存下来\\n # self.driver.save_screenshot('%s.png'%pageNum)\\n # 如果单页循环次数不为零，说明没有跳转到下一页\\n if loopNum != 0:\\n # 循环次数较大的情况下（此处预定为15次）说明页面可能加载失败，跳出循环，否则继续循环获取\\n if loopNum < 15:\\n time.sleep(3)\\n continue\\n else:\\n break\\n return False if pageNum > 1 else True\\n # 爬取酒店基本信息\\n def pagecollect(self,response):\\n items = []\\n commentData = response.xpath(\\\"//div[@id='hotel_list']/div[@class='searchresult_list ']/ul[@class='searchresult_info']\\\")\\n\\n for itemData in commentData:\\n itemDict = dict()\\n\\n # 唯一标识\\n itemDict['guid'] = uuid.uuid1()\\n\\n # 城市名\\n itemDict[\\\"city\\\"] = \\\"南京\\\"\\n\\n # 名称\\n itemDict[\\\"title\\\"] = itemData.xpath(\\\"li/h2/a[@title]/text()\\\").extract()[0]\\n\\n # 价格\\n price = itemData.xpath(\\\"li[@class='hotel_price_icon']/div/span/text()\\\").extract()[0]\\n if price:\\n itemDict[\\\"price\\\"] = price\\n # print(price)\\n else:\\n itemDict[\\\"price\\\"] = \\\"\\\"\\n\\n # 评分\\n score = itemData.xpath(\\\"li[@class='searchresult_info_judge ']/div/a/span[@class='hotel_value']/text()\\\").extract()[0]\\n if score:\\n itemDict[\\\"score\\\"] = score\\n else:\\n itemDict[\\\"score\\\"] = \\\" \\\"\\n\\n # 位置\\n location = itemData.xpath(\\\"li[@class='searchresult_info_name']/p[@class='searchresult_htladdress']/text()\\\").extract()[0]\\n Location = location.split(\\\" \\\")\\n if(Location):\\n itemDict[\\\"location\\\"] = Location[0]\\n else:\\n itemDict[\\\"location\\\"] = \\\" \\\"\\n\\n # 评论\\n discussnum = itemData.xpath(\\\"li[@class='searchresult_info_judge ']/div/a/span[@class='hotel_judgement']/text()\\\").extract()[0]\\n Discuss = re.sub('\\\\D','',discussnum)\\n if Discuss:\\n itemDict[\\\"discussnum\\\"] = Discuss\\n else:\\n itemDict[\\\"discussnum\\\"] = \\\"\\\"\\n\\n # 有无wifi\\n havewifi1 = itemData.xpath(\\\"li[@class='searchresult_info_name']/div[@class='icon_list']/i[@class='icons-facility32']\\\")\\n havawifi2 = itemData.xpath(\\\"li[@class='searchresult_info_name']/div[@class='icon_list']/i[@class='icons-facility01']\\\")\\n if (havewifi1 or havawifi2):\\n itemDict[\\\"havawifi\\\"] = \\\"yes\\\"\\n else:\\n itemDict[\\\"havawifi\\\"] = \\\"no\\\"\\n\\n # 用户推荐百分比\\n recommend = itemData.xpath(\\\"li[@class='searchresult_info_judge ']/div[@class='searchresult_judge_box']/a/span[@class='total_judgement_score']/text()\\\").extract()[1]\\n Recommend = re.sub('\\\\D','',recommend)\\n Recommend += \\\"%\\\"\\n if Recommend:\\n itemDict[\\\"recommend\\\"] = Recommend\\n else:\\n itemDict[\\\"recommend\\\"] = \\\" \\\"\\n\\n items.append(itemDict)\\n return items\\n\\n\\n # 爬取页面链接\\n def crawllianjie(self,page_sourse):\\n response = HtmlResponse(url=\\\"my HTML string\\\",body=page_sourse,encoding=\\\"utf-8\\\")\\n\\n A = response.xpath(\\\"//div[@class='searchresult_list ']/ul\\\")\\n # 获取每个酒店的链接\\n for B in A:\\n url = B.xpath(\\\"li[@class='searchresult_info_name']/h2/a/@href\\\").extract()\\n # 评论\\n commnum = B.xpath(\\\"li[@class='searchresult_info_judge ']/div/a/span[@class='hotel_judgement']/text()\\\").extract()\\n if len(commnum):\\n Discuss = re.sub('\\\\D','',commnum[0])\\n if len(Discuss):\\n pass\\n else:\\n Discuss = 0\\n else:\\n Discuss = 0\\n self.listPageInfo.append({\\\"url\\\":url[0], \\\"comm_num\\\":Discuss, \\\"city\\\":\\\"南京\\\"})\\n self.saveListPageInfo()\\n if len(self.listPageInfo) == 25:\\n pass\\n else:\\n print(len(self.listPageInfo))\\n self.listPageInfo = []\\n\\n\\n def saveListPageInfo(self):\\n self.xiechengDao.savehotellink(self.listPageInfo)\\n\\n def depose(self):\\n self.driver.close()\\n\\nif __name__==\\\"__main__\\\":\\n xiechengService = XiechengDriverService()\\n xiechengService.start()\\n\\n xiechengService.depose()\\n\"\n },\n {\n \"alpha_fraction\": 0.5232515335083008,\n \"alphanum_fraction\": 0.538996696472168,\n \"avg_line_length\": 38.550724029541016,\n \"blob_id\": \"214d9967cb9306551434c1d707c8ee5372a09d01\",\n \"content_id\": \"22b631b14f2aa4b254bdfa1643a6d329bbb1ff82\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 5462,\n \"license_type\": \"no_license\",\n \"max_line_length\": 167,\n \"num_lines\": 138,\n \"path\": \"/tutorial/tutorial/spiders/scraper.py\",\n \"repo_name\": \"Zheng392/Python-Repository\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import scrapy\\nimport json\\nimport re\\nfrom scrapy import Selector\\nfrom tutorial.items import *\\nfrom urllib.parse import urlencode\\n\\nheaders = {'Accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,image/webp,image/apng,*/*;q=0.8',\\n 'Accept - Encoding':'gzip, deflate, br',\\n 'Accept-Language':'en-US,en;q=0.9',\\n 'Connection':'Keep-Alive',\\n\\t 'Cache-Control': 'max-age=0',\\n 'User-Agent':'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/65.0.3325.181 Safari/537.36'}\\n\\nclass scraper(scrapy.Spider):\\n name = \\\"scraper\\\"\\n base_url = \\\"http://www.tripadvisor.cn\\\"\\n\\n def __init__(self):\\n\\n self.hotel_photo_links=[]\\n \\n def start_requests(self):\\n\\t yield scrapy.Request(url=self.base_url+\\\"/Hotels-g297463-Chengdu_Sichuan-Hotels.html\\\", callback=self.parse)\\n\\n \\n\\n def parse(self, response):\\n\\n\\n\\n hotel_urls = response.xpath('//h2[@class=\\\"listing_title\\\"]//a[contains(@class, \\\"property_title\\\")]/@href').extract()\\n\\n if hotel_urls:\\n for hotel_url in hotel_urls:\\n hotel_completed_url = self.base_url + hotel_url\\n yield scrapy.Request(url=hotel_completed_url,\\n callback=self.parse_fetch_hotel)\\n break\\n\\n\\n\\n def parse_fetch_hotel(self, response):\\n hxs=Selector(response)\\n\\n hi = Hotel_Item_Detail()\\n\\n hi['item_type'] = 'hotel'\\n hi['detail_id'] = re.search('d[0-9]+', response.url).group(0).strip('d')\\n hi['geo_id']=re.search('g[0-9]+',response.url).group(0).strip('g')\\n hi['name'] = hxs.xpath( '//h1[contains(@id, \\\"HEADING\\\")]/text()').extract()[0]\\n hi['url'] = response.url\\n hi['rank']=hxs.xpath('//*[@id=\\\"taplc_location_detail_header_hotels_0\\\"]//div/span/b/text()').extract()[0]\\n hi['traveler_photo_nums']=int(re.search('[0-9]+',\\n hxs.xpath('//*[@id=\\\"taplc_hr_atf_north_star_nostalgic_0\\\"]//div[@class=\\\"albumInfo\\\"]/text()').extract()[0]).group(0))\\n hi['offical_photo_nums']=int(re.search('[0-9]+',\\n hxs.xpath('//*[@id=\\\"taplc_hr_atf_north_star_nostalgic_0\\\"]//span[@class=\\\"see_all_count\\\"]/text()').extract()[0]).group(0))\\\\\\n -hi['traveler_photo_nums']\\n yield hi\\n\\n for count,j in enumerate(['offical_photo_nums','traveler_photo_nums']):\\n for i in range(int(hi[j]/50)+1):\\n headers={\\n 'geo':hi['geo_id'],\\n 'detail':hi['detail_id'],\\n 'albumViewMode':'images',\\n 'aggregationId':101,\\n 'albumid':101,\\n 'cnt':50,\\n 'offset': 50*i,\\n 'filter':count+1,\\n 'albumPartialsToUpdate':'partial',\\n }\\n photo_url='https://www.tripadvisor.cn/LocationPhotoAlbum?'+urlencode(headers)\\n yield scrapy.Request(photo_url,self.parse_fetch_photo,\\n meta={'id':hi['detail_id'],'count':count})\\n break\\n\\n\\n\\n\\n #get review\\n pages=hxs.xpath('//*[@id=\\\"taplc_location_reviews_list_hotels_0\\\"]//div[@class=\\\"pageNumbers\\\"]/span[@class=\\\"pageNum last taLnk \\\"]/@data-page-number').extract()[0]\\n pages=int(pages)\\n for i in range(pages):\\n split = response.url.split('Reviews')\\n review_page_url = ('Reviews-or' + str(i * 5)).join(split)\\n yield scrapy.Request(review_page_url,self.parse_review,meta={'id':hi['detail_id']})\\n if i > 2:\\n break\\n\\n\\n\\n def parse_fetch_photo(self,response):\\n photos=photo_links()\\n\\n sel=Selector(response)\\n photo_link=sel.xpath('//img[@onload]/@src').extract()\\n if response.meta['count']==0:\\n photos['photo_from']='official'\\n else:\\n photos['photo_from'] = 'traveler'\\n photos['hotel_id'] =response.meta['id']\\n\\n temp=[]\\n for i in photo_link:\\n temp.append(i)\\n photos['photo_link']=temp\\n\\n\\n\\n yield photos\\n\\n\\n def parse_review(self,response):\\n pass\\n\\n sel=Selector(response)\\n\\n\\n username=sel.xpath('//*[@id=\\\"taplc_location_reviews_list_hotels_0\\\"]//div[@class=\\\"review-conta'\\n 'iner\\\"]//span[@class=\\\"expand_inline scrname\\\"]/text()').extract()\\n location=sel.xpath('//*[@id=\\\"taplc_location_reviews_list_hotels_0\\\"]//div[@class=\\\"review-conta'\\n 'iner\\\"]//span[@class=\\\"expand_inline userLocation\\\"]/text()').extract()\\n title=sel.xpath('//*[@id=\\\"taplc_location_reviews_list_hotels_0\\\"]//div[@class=\\\"review-container\\\"]'\\n '//span[@class=\\\"noQuotes\\\"]/text()').extract()\\n review_content=sel.xpath('//*[@id=\\\"taplc_location_reviews_list_hotels_0\\\"]//div[@class=\\\"review-container\\\"]'\\n '//div[@class=\\\"wrap\\\"]/div[@class=\\\"prw_rup prw_reviews_text_summary_hsx\\\"]'\\n '/div/p[@class=\\\"partial_entry\\\"]/text()').extract()\\n\\n for i in range(len(review_content)):\\n Reviews = Review_Detail()\\n Reviews['location']=location[i]\\n Reviews['username'] = username[i]\\n Reviews['title'] = title[i]\\n Reviews['review_content'] = review_content[i]\\n Reviews['hotel_id']=response.meta['id']\\n yield Reviews\\n\\n\\n\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.7445783019065857,\n \"alphanum_fraction\": 0.7566264867782593,\n \"avg_line_length\": 49.10344696044922,\n \"blob_id\": \"d3615c8af8acf4e1355f55e37b3f981501589506\",\n \"content_id\": \"d1295244e1d8c4e007cb7d03c571d705d8069cca\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 2929,\n \"license_type\": \"permissive\",\n \"max_line_length\": 337,\n \"num_lines\": 58,\n \"path\": \"/Foursquare research/Projects/Get venues/README.md\",\n \"repo_name\": \"Zheng392/Python-Repository\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# Get venues\\n\\nGet venues in a rectangle. I improve the method used in [foursquare-venue-scraper](https://github.com/minimaxir/foursquare-venue-scraper), which is more effecient and complete. \\n\\n\\n\\n\\n\\n# foursquare-venue-scraper\\n\\n\\n\\nA [Foursquare](https://foursquare.com) data scraper that gathers all venues within a specified geographic area. The data retrieved can then be used for statistical analysis and fun data visualizations.\\n\\n## Overview\\n\\nThe script queries the official [Foursquare API](https://developer.foursquare.com/docs) (with a user-provided `client_id` and `client_secret` from a Foursquare application) to search for venues, and then query additional metadata for each unique venue.\\n\\nThe specified area is defined by a geographic bounding box (by latitude and longitude). Since the API can only return up to 50 venues per search, the bounding box is broken into sub-bounding boxes as a form of grid search (by default, the `grid_size` is 100, so 100x100=10000 searches total).\\n\\nThe output file is a CSV with the following fields:\\n\\n* `id` — The Foursquare ID for the venue.\\n* `name` — The name of the venue.\\n* `categories` — The list of categories of the venue.\\n* `lat` — Latitude\\n* `long` — Longitude\\n* `num_checkins` — Number of Foursquare Checkins\\n* `num_likes` — Number of Foursquare Likes\\n* `price` — Price Tier between 1-4 (i.e. $-$$$$)\\n* `rating` — Rating for the venue.\\n* `num_ratings` — Number of ratings for the venue.\\n* `url_venue` — URL of the venue.\\n* `url_foursquare` — URL for the Foursquare venue.\\n\\nA demo CSV of the Top 100 San Francisco venues (by number of checkins) is available in `foursquare_sf_sample.csv`.\\n\\n## Usage\\n\\nSet the parameters in `config.yaml` as appropriate, then run `foursquare_venues.py`.\\n\\nThe Foursquare API has a **daily [rate limit](https://developer.foursquare.com/docs/api/troubleshooting/rate-limits) of 1,000 requests/day** for free accounts, but with verification, the rate limit upgrades to **100,000/day**. You can test the script with a small bounding box/low grid size to see if it fits your needs before upgrading.\\n\\nBoth of the API endpoints used in this script have a **rate limit of 5,000 requests/hour**. Once the script hits that limit, it'll sleep for an hour. Plan scraping accordingly.\\n\\n## Foursquare Terms of Use\\n\\nThis script follows the specifications of the Foursquare API, and does not circumvent the API and its rate limits. If you're using the data for projects other than data analysis, make sure to follow the [Foursquare Terms of Use](https://developer.foursquare.com/docs/terms-of-use/overview).\\n\\n## Maintainer\\n\\nMax Woolf ([@minimaxir](http://minimaxir.com))\\n\\n*Max's open-source projects are supported by his [Patreon](https://www.patreon.com/minimaxir). If you found this project helpful, any monetary contributions to the Patreon are appreciated and will be put to good creative use.*\\n\\n## License\\n\\nMIT\"\n },\n {\n \"alpha_fraction\": 0.5251753330230713,\n \"alphanum_fraction\": 0.6241232752799988,\n \"avg_line_length\": 52.22666549682617,\n \"blob_id\": \"000731c85fb40f442bb8e2bdcbde36ef13465b22\",\n \"content_id\": \"e6b5f9c0455e8c829ef068f9cc383cd8a480d2f9\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 8994,\n \"license_type\": \"no_license\",\n \"max_line_length\": 692,\n \"num_lines\": 150,\n \"path\": \"/Spider/fangtianxia data with threading/fang_data_threading.py\",\n \"repo_name\": \"Zheng392/Python-Repository\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import requests,json,random\\nimport re,threading\\nfrom lxml import etree\\nimport time\\n\\nlock=threading.Lock()\\n\\nuser_agent_list = [\\n \\\"Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/537.1 (KHTML, like Gecko) Chrome/22.0.1207.1 Safari/537.1\\\" ,\\\\\\n \\\"Mozilla/5.0 (X11; CrOS i686 2268.111.0) AppleWebKit/536.11 (KHTML, like Gecko) Chrome/20.0.1132.57 Safari/536.11\\\", \\\\\\n \\\"Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/536.6 (KHTML, like Gecko) Chrome/20.0.1092.0 Safari/536.6\\\", \\\\\\n \\\"Mozilla/5.0 (Windows NT 6.2) AppleWebKit/536.6 (KHTML, like Gecko) Chrome/20.0.1090.0 Safari/536.6\\\", \\\\\\n \\\"Mozilla/5.0 (Windows NT 6.2; WOW64) AppleWebKit/537.1 (KHTML, like Gecko) Chrome/19.77.34.5 Safari/537.1\\\", \\\\\\n \\\"Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/536.5 (KHTML, like Gecko) Chrome/19.0.1084.9 Safari/536.5\\\", \\\\\\n \\\"Mozilla/5.0 (Windows NT 6.0) AppleWebKit/536.5 (KHTML, like Gecko) Chrome/19.0.1084.36 Safari/536.5\\\", \\\\\\n \\\"Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/536.3 (KHTML, like Gecko) Chrome/19.0.1063.0 Safari/536.3\\\", \\\\\\n \\\"Mozilla/5.0 (Windows NT 5.1) AppleWebKit/536.3 (KHTML, like Gecko) Chrome/19.0.1063.0 Safari/536.3\\\", \\\\\\n \\\"Mozilla/5.0 (Macintosh; Intel Mac OS X 10_8_0) AppleWebKit/536.3 (KHTML, like Gecko) Chrome/19.0.1063.0 Safari/536.3\\\", \\\\\\n \\\"Mozilla/5.0 (Windows NT 6.2) AppleWebKit/536.3 (KHTML, like Gecko) Chrome/19.0.1062.0 Safari/536.3\\\", \\\\\\n \\\"Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/536.3 (KHTML, like Gecko) Chrome/19.0.1062.0 Safari/536.3\\\", \\\\\\n \\\"Mozilla/5.0 (Windows NT 6.2) AppleWebKit/536.3 (KHTML, like Gecko) Chrome/19.0.1061.1 Safari/536.3\\\", \\\\\\n \\\"Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/536.3 (KHTML, like Gecko) Chrome/19.0.1061.1 Safari/536.3\\\", \\\\\\n \\\"Mozilla/5.0 (Windows NT 6.1) AppleWebKit/536.3 (KHTML, like Gecko) Chrome/19.0.1061.1 Safari/536.3\\\", \\\\\\n \\\"Mozilla/5.0 (Windows NT 6.2) AppleWebKit/536.3 (KHTML, like Gecko) Chrome/19.0.1061.0 Safari/536.3\\\", \\\\\\n \\\"Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/535.24 (KHTML, like Gecko) Chrome/19.0.1055.1 Safari/535.24\\\", \\\\\\n \\\"Mozilla/5.0 (Windows NT 6.2; WOW64) AppleWebKit/535.24 (KHTML, like Gecko) Chrome/19.0.1055.1 Safari/535.24\\\"\\n ]\\ncount=0\\n\\ndef fang_com(page_url,page): ##列表页\\n print('page is ',i)\\n header={}\\n\\n header['User-Agent']=random.choice(user_agent_list)\\n header.update({\\n \\\"Host\\\":\\\"esf.sz.fang.com\\\",\\n #\\\"Cookie\\\":\\\"global_cookie=fb1g6d0w64d2cmu86sv4g9n3va0j137sk48; vh_newhouse=3_1491312022_2816%5B%3A%7C%40%7C%3A%5D833300ee3177d88529c7aa418942ece9; newhouse_user_guid=2F163DE7-8201-7FA9-2FB6-E507FE6F03B1; SoufunSessionID_Esf=3_1495389730_232; sf_source=; s=; showAdsh=1; hlist_xfadhq_SZ=0%7c2017%2f5%2f25+1%3a21%3a47%7c; city=sz; __utmt_t0=1; __utmt_t1=1; __utmt_t2=1; logGuid=a768dd46-b85b-47f4-a7a0-0a6596cab4cd; __utma=147393320.1111837171.1491290389.1495646208.1495650134.9; __utmb=147393320.12.10.1495650134; __utmc=147393320; __utmz=147393320.1495650134.9.4.utmcsr=esf.sz.fang.com|utmccn=(referral)|utmcmd=referral|utmcct=/; unique_cookie=U_cqyov4ut5vv1al8e2858qhzgt17j2z06mph*14\\\"\\n })\\n while(1): ###这个主要是，fang.com会随机返回几个10054或者10053，如果连页面都没读取到，提取就是后话了，这网站没有封杀，即使使用单ip只会很少时候随机来几个10054 ，('Connection aborted.', error(10054, ''))\\n text=''\\n try:\\n text=requests.get(page_url,headers=header,timeout=10).text\\n #print text\\n except Exception as e:\\n print(e)\\n if text!='':\\n break\\n\\n se = etree.HTML(text) ###########为了利于大家学习，这段演示xpath提取信息\\n all_dl=se.xpath('//dl[@class=\\\"list rel\\\"]')\\n print(len(all_dl))\\n for dl in all_dl:\\n title=dl.xpath('.//dd[@class=\\\"info rel floatr\\\"]/p[@class=\\\"title\\\"]/a/text()')[0]\\n url=dl.xpath('.//dd[@class=\\\"info rel floatr\\\"]/p[@class=\\\"title\\\"]/a/@href')[0]\\n url='http://esf.sz.fang.com'+url\\n\\n info_list=dl.xpath('.//dd[@class=\\\"info rel floatr\\\"]/p[@class=\\\"mt12\\\"]/text()')\\n #print json.dumps(info,ensure_ascii=False) #py2显示汉字，py3可以直接print mt12\\n info=''\\n for l in info_list:\\n l2= re.findall('\\\\S*',l)[0] ###消除空白和换行\\n #print m_str\\n info+=l2+'|'\\n\\n time.sleep(1)\\n # total_price,price_squere,huxin,cankao_shoufu,shiyong_mianji,jianzhu_mianji,years,discription=get_detail(url)\\n\\n\\n lock.acquire() ###这里叫锁，一是保证count计数准确，而是不会导致多个线程乱print，导致看不清楚。加锁的目的是别的线程不能运行这段代码了。但我之前看到有的人乱加锁，把消耗时间很长的代码加锁，那样导致多线程就基本个废物\\n global count\\n count+=1\\n print(time.strftime('%H:%M:%S', time.localtime(time.time())), ' ', count)\\n print('列表页：')\\n print(' title: %s\\\\n url: %s\\\\n info: %s\\\\n' % (title, url, info))\\n\\n print('详情页:')\\n # print(\\n # ' total_price: %s\\\\n price_squere: %s\\\\n huxin: %s\\\\n cankao_shoufu: %s\\\\n shiyong_mianji: %s\\\\n jianzhu_mianji: %s\\\\n years: %s \\\\n' % (\\n # total_price, price_squere, huxin, cankao_shoufu, shiyong_mianji, jianzhu_mianji, years))\\n print('**************************************************************')\\n lock.release()\\n\\n\\n\\ndef get_detail(url): ###详情页\\n\\n header={'User-Agent':random.choice(user_agent_list)}\\n header.update({\\\"Host\\\":\\\"esf.sz.fang.com\\\"})\\n\\n while(1):\\n content=''\\n try:\\n content=requests.get(url,headers=header,timeout=10).content\\n except Exception as e:\\n print(e)\\n pass\\n if content!='':\\n break\\n\\n content=content.decode('gbk').encode('utf8') ##查看网页源代码可看到是gbk编码，直接print的话，如果你在pycharm设置控制台是utf8编码，那么控制台的中文则会乱码，cmd是gbk的恰好可以显示。如果你在pycharm设置控制台是utf8编码，需要这样做\\n #print content\\n\\n inforTxt=getlist0(re.findall('(
\\n\\n##使用Python 库：\\n1.scrapy，网上安装方法许多，可自行下载相关依赖
\\n\\n2.selenium
\\n可以直接使用pip进行安装
\\n\\nSelenium也是一个用于Web应用程序测试的工具。Selenium测试直接运行在浏览器中，就像真正的用户在操作一样。
\\n\\n\\n##使用驱动:\\n1.Chrome驱动
\\n下载地址：http://npm.taobao.org/mirrors/chromedriver
\\n\\nselenium调用需要，需下载系统对应版本，将其放置到系统能直接访问的文件夹，如放在{PYTHON_HOME}/Scripts文件夹中
\\n\\n\\n##数据库：\\n\\n###数据库名:xiecheng\\n1.hotellianjie（存储酒店url）
\\n```sql\\nDROP TABLE IF EXISTS `hotellianjie`;\\nCREATE TABLE `hotellianjie` (\\n `guid` varchar(255) DEFAULT NULL,\\n `lianjie` varchar(255) DEFAULT NULL,\\n `city` varchar(30) DEFAULT NULL,\\n `comm_num` int(30) DEFAULT NULL\\n) ENGINE=InnoDB DEFAULT CHARSET=utf8;\\n```\\n2.hotelinfo（酒店基本信息数据）
\\n```sql\\nDROP TABLE IF EXISTS `hotelinfo`;\\nCREATE TABLE `hotelinfo` (\\n `guid` varchar(255) DEFAULT NULL,\\n `city` varchar(30) DEFAULT NULL,\\n `title` varchar(60) DEFAULT NULL,\\n `price` decimal(10,1) DEFAULT NULL,\\n `score` int(20) DEFAULT NULL,\\n `recommend` varchar(120) DEFAULT NULL,\\n `area` varchar(120) DEFAULT NULL,\\n `havawifi` varchar(20) DEFAULT NULL,\\n `discussNum` int(11) DEFAULT NULL,\\n `common_facilities` varchar(500) DEFAULT NULL,\\n `activity_facilities` varchar(255) DEFAULT NULL,\\n `service_facilities` varchar(255) DEFAULT NULL,\\n `room_facilities` varchar(255) DEFAULT NULL,\\n `around_facilities` varchar(255) DEFAULT NULL\\n) ENGINE=InnoDB DEFAULT CHARSET=utf8;\\n```\\n3.hotelcommentinfo（存储酒店评论数据）
\\n```sql\\nDROP TABLE IF EXISTS `hotelcommentinfo`;\\nCREATE TABLE `hotelcommentinfo` (\\n `hotelname` varchar(50) DEFAULT NULL,\\n `username` varchar(40) DEFAULT NULL,\\n `commentscore` varchar(40) DEFAULT NULL,\\n `intime` varchar(40) DEFAULT NULL,\\n `tourstyle` varchar(40) DEFAULT NULL,\\n `praisenum` int(11) DEFAULT NULL,\\n `commenttime` varchar(60) DEFAULT NULL,\\n `comment` varchar(1000) DEFAULT NULL\\n) ENGINE=InnoDB DEFAULT CHARSET=utf8;\\n```\"\n },\n {\n \"alpha_fraction\": 0.46783626079559326,\n \"alphanum_fraction\": 0.4938271641731262,\n \"avg_line_length\": 27.165138244628906,\n \"blob_id\": \"40cbb623bd7a6e0658e92668be6d67c464eca3aa\",\n \"content_id\": \"cc44b77ed77b623ecf41436d85bae434ce4fad66\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 3244,\n \"license_type\": \"no_license\",\n \"max_line_length\": 85,\n \"num_lines\": 109,\n \"path\": \"/Foursquare research/Projects/Small Dataset creating/Data_scraping.py\",\n \"repo_name\": \"Zheng392/Python-Repository\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import pandas as pd\\n\\n\\ndef get_tuple(f,max = 10):#获得(user,time,id)的元组\\n n = 1\\n while n<= max:\\n line = f.readline().split('\\\\t')\\n user = line[0]\\n venue = line[1]\\n # 1 = line[2]\\n time = line[3]\\n photo_id = line[4].split('\\\\n')[0]\\n TUPLE = (user,time,photo_id)\\n yield TUPLE\\n n += 1\\n #print(TUPLE)\\n\\ndef divide_time(start,end,num=10):#均分时间段\\n list = []\\n gap = (end - start)/num\\n for i in range(num+1):\\n list.append(start+i*gap)\\n return list\\n\\ndef find_time_index(time,list):#在均分的时间点list里找到时间的位置\\n for i in range(len(list)):\\n if i == len(list)-1 and time == list[i]:\\n return len(list)-1\\n break\\n if list[i]<=time
[\\\\s\\\\S]*?)
- ',content)) ###########为了利于大家学习，这段演示正则表达式提取信息，某些信息可能在有的房子界面没有，要做好判断\\n #print inforTxt\\n\\n total_price=getlist0(re.findall('价：(.*?)',inforTxt))\\n\\n price_squere=getlist0(re.findall('class=\\\"black\\\">万\\\\((\\\\d+?)元[\\\\s\\\\S]*?户型：(.*?)',inforTxt))\\n cankao_shoufu=getlist0(re.findall('参考首付：(.*?万) ',inforTxt))\\n shiyong_mianji=getlist0(re.findall('>使用面积：(.*?)',inforTxt))\\n shiyong_mianji=getlist0(re.findall('\\\\d+',shiyong_mianji))\\n jianzhu_mianji=getlist0(re.findall('建筑面积：(.*?)',inforTxt))\\n jianzhu_mianji=getlist0(re.findall('\\\\d+',jianzhu_mianji))\\n years=getlist0(re.findall('年代：(.*?)',inforTxt))\\n\\n discription=getlist0(re.findall('style=\\\"-moz-user-select: none;\\\">([\\\\s\\\\S]*?)
= len(self.tokenized)\n def gen_code(self,instr,a,r):\n self.machine_code.append(instr+' '+str(a)+' '+str(r))\n def use_next_free_address(self):\n nfa = self.next_free_address\n self.next_free_address += 1\n return nfa\n\n def write_constants_table(self):\n l = len(self.machine_code)\n for l in self.machine_code:\n i, n, r = l.split(' ')\n if i=='loadconst':\n l[:] = 'load %s %s' % (int(self.number_addresses[n]) + l, r)\n for n in self.numbers:\n self.machine_code.append(n)\n def match_number(self):\n num=float(self.peek())\n if num not in self.number_addresses:\n self.number_addresses[num] = self.use_next_free_address()\n self.numbers.append(num)\n self.gen_code('loadconst',num,0)\n self.match(self.peek())\n def match_variable(self):\n var=self.peek()\n if var not in self.variable_addresses:\n self.variable_addresses[var] = self.use_next_free_address()\n self.next_free_address += 1\n self.gen_code('load',self.variable_addresses[var],0)\n self.match(self.peek())\n def match_factor(self):\n if is_number(self.peek()): self.match_number()\n elif is_identifier(self.peek()): self.match_identifier()\n else:\n temp1 = self.use_next_free_address()\n temp2 = self.use_next_free_address()\n self.gen_code('store',temp1,1)\n self.gen_code('store',temp2,2)\n self.match('(')\n self.match_expression()\n self.match(')')\n self.gen_code('load',temp1,1)\n self.gen_code('load',temp2,2)\n def match_term(self):\n self.match_factor()\n while not self.at_end() and self.peek() in ['*']:\n self.match('*')\n self.gen_code('swap',0,1)\n self.match_factor()\n self.gen_code('multiply',0,1)\n def match_expression(self):\n self.match_term()\n while not self.at_end() and self.peek() in ['+']:\n self.match('+')\n self.gen_code('swap',0,2)\n self.match_term()\n self.gen_code('add',0,2)\n def match_statement(self):\n pass\n def match_assignment(self):\n #self.match_variable() #generates unnecessary load statement\n var=self.peek(); assert(is_variable(var)); self.match(var)\n self.match('=')\n self.match_expression()\n self.gen_code('store',self.variable_addresses[var],0)\n #NOTE: notation easier to parse: expr->varname (assignment written backward)\n def match_if(self):\n self.match('if')\n self.match('(')\n self.match(')')\n self.match_statement()\n def match_while(self):\n pass\n"},{"alpha_fraction":0.5965909361839294,"alphanum_fraction":0.6363636255264282,"avg_line_length":21,"blob_id":"d58151f96a1480199b32f524b7b9cb84646423ff","content_id":"1fe93baac27ee0f3d64173ce37e02e42ceabf389","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":176,"license_type":"no_license","max_line_length":41,"num_lines":8,"path":"/ParserTest.py","repo_name":"samueltenka/LearnToHack-Compiler","src_encoding":"UTF-8","text":"from Parser import Parser\n\nprogram = '1 * ( 2 + 3 * 4 + 5 ) + 6 * 7'\nP = Parser(program)\nP.match_expression()\nP.write_constants_table()\nfor mc in P.machine_code:\n print(mc)\n"},{"alpha_fraction":0.5738466382026672,"alphanum_fraction":0.5974112153053284,"avg_line_length":39.716217041015625,"blob_id":"c761d43d31ed9ab2d008c16d2a898f62c46c3bf9","content_id":"07afd1e5c097c69d860a43c888db0c5ab6fb1b28","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":3013,"license_type":"no_license","max_line_length":91,"num_lines":74,"path":"/Machine.py","repo_name":"samueltenka/LearnToHack-Compiler","src_encoding":"UTF-8","text":"#Michigan Hackers Presentation on Compilers\nimport EnsureVersion3\n\n'''\ninstructions:\nload\t A B\t R[B] <-- M[R[A]]\nstore\t A B\t R[B] --> M[R[A]]\ncopy\t\tA B\t R[B] <-- R[A]\nset\t\t A B\t B --> R[A]\nbranchif0\tA B\t PC <-- R[A] if R[B]==0\nbranchifneg\tA B\t PC <-- R[A] if R[B] < 0\njump\t\tA B\t PC <-- R[A] (so B is dummy var.)\nadd\t\t A B\t R[B] <-- R[B] + R[A]\nsub\t\t A B\t R[B] <-- R[B] - R[A]\nmul\t\t A B\t R[B] <-- R[B] * R[A]\ndiv\t\t A B\t R[B] <-- R[B] / R[A]\nmod\t\t A B\t R[B] <-- R[B] % R[A]\nNote: program might also contain literal numbers in addition to instructions.\nMachine halts when program counter reaches -1.\n\nMachine Specifics:\nEach memory address contains a float or program instruction.\nFloats are rounded to integers when interpreted as addresses.\nThe program counter starts at 4.\nThe first 4 memory addresses are IO devices:\n0 [Input, e.g. temperature sensor]\n1 [Input, e.g. joystick]\n2 [Output, e.g. LED]\n3 [Output, e.g. motor]\n4&beyond [Program then data]\n'''\n\nclass Machine:\n PRECISION = 0.0001\n def __init__(self, num_addresses, num_registers):\n self.memory = [0.0 for i in range(num_addresses)]\n self.registers = [0.0 for i in range(num_registers)]\n self.program_counter = None\n def load_program(self, lines, inputs=(0.0,0.0)):\n self.memory[:2] = inputs\n for i in range(len(lines)):\n self.memory[4+i] = lines[i] if ' ' in lines[i] else eval(lines[i])\n self.program_counter = 4\n def print_mem(self, l=8):\n print('memory', ' '.join(str(s).replace(' ','_') for s in self.memory[:l])+'. . .')\n print('registers', self.registers)\n def step(self):\n instr = self.memory[self.program_counter]\n print(\"instr \", self.program_counter, instr)\n command, arg0, arg1 = instr.split(' ')\n getattr(self,command)(eval(arg0),eval(arg1))\n self.program_counter += 1\n def at_end(self):\n return self.program_counter == -1\n\n def load(self, r, r_): self.registers[r_] = self.memory[int(self.registers[r])]\n def store(self, r, r_): self.memory[int(self.registers[r])] = self.registers[r_]\n def copy(self, r, r_): self.registers[r_] = self.registers[r]\n def set(self, r, f): self.registers[r] = f\n\n def branchif0(self, r, r_):\n if self.registers[r_]==0.0: self.jump(r)\n def branchifneg(self, r, r_):\n if self.registers[r_] < 0.0: self.jump(r)\n def jump(self, r, dummy):\n #subtract 1 to counter end-of-cycle PC increment:\n self.program_counter = int(self.registers[r])-1\n\n def add (self, r, r_): self.registers[r_] += self.registers[r]\n def sub (self, r, r_): self.registers[r_] -= self.registers[r]\n def mul (self, r, r_): self.registers[r_] *= self.registers[r]\n def div (self, r, r_): self.registers[r_] /= self.registers[r]\n def mod (self, r, r_): self.registers[r_] = self.registers[r_] % self.registers[r]\n '''Beware of floating point modulo: 0.0 != 3.50 % 0.10 == 0.09999999999999992 != 0.10'''\n"},{"alpha_fraction":0.6748878955841064,"alphanum_fraction":0.6860986351966858,"avg_line_length":30.85714340209961,"blob_id":"6bef20996c03ef619c8c011d09c4573b93bbb201","content_id":"d3e8d38dac5e1705c621f6eb8d5101cd5261b635","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":446,"license_type":"no_license","max_line_length":87,"num_lines":14,"path":"/MachineTest.py","repo_name":"samueltenka/LearnToHack-Compiler","src_encoding":"UTF-8","text":"import Machine\n\ndef readfile(filename):\n with open(filename,'r') as f:\n return f.read()\n\nlines = readfile('MachineCode01.test').strip().split('\\n')\nlines = [l.split('#')[0].strip() for l in lines] #remove line-comments such as this one\nprint(lines)\nnum_registers, num_addresses = lines[0].split()\nM = Machine.Machine(eval(num_registers), eval(num_addresses), debug=False)\nM.print_mem()\nM.load_program(lines[2:], float(input()))\nM.run()\n"},{"alpha_fraction":0.5475285053253174,"alphanum_fraction":0.5779467821121216,"avg_line_length":42.83333206176758,"blob_id":"e3958a2552af2d5dee45b4e199ab4518935b0320","content_id":"1b532d87a13fb0a52ea2e116eaf15bbeaf452dd2","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":263,"license_type":"no_license","max_line_length":65,"num_lines":6,"path":"/PrettyPrint.py","repo_name":"samueltenka/LearnToHack-Compiler","src_encoding":"UTF-8","text":"def pretty_print(string, minlen=10):\n if type(string) in [type(0), type(0.0)] or ' ' not in string:\n string = str(round(float(string),4))\n else:\n string = string[:3] + ';'.join(string.split(' ')[1:])\n return string+' '*(minlen-len(string))\n"},{"alpha_fraction":0.6497461795806885,"alphanum_fraction":0.6565144062042236,"avg_line_length":24.69565200805664,"blob_id":"3a550a270c80f3d4773035fee84b7843d100cbb7","content_id":"ba500bc2cbaa3c1561e0ec7fa930ff62e297c3bb","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":591,"license_type":"no_license","max_line_length":72,"num_lines":23,"path":"/NumberedTextboxTest.py","repo_name":"samueltenka/LearnToHack-Compiler","src_encoding":"UTF-8","text":"'''\nThanks to Robert@pytrash (see link below)\nhttp://tk.unpythonic.net/wiki/A_Text_Widget_with_Line_Numbers\n'''\n\nimport tkinter as tk\nimport NumberedTextbox\n\nroot = tk.Tk()\n\ndef demo(noOfLines):\n pane = tk.PanedWindow(root, orient=tk.HORIZONTAL, opaqueresize=True)\n ed = NumberedTextbox.EditorClass(root)\n pane.add(ed.frame)\n s = 'line %s'\n s = '\\n'.join( s%i for i in range(3, noOfLines+3) )\n ed.text.insert(tk.END, s)\n pane.pack(fill='both', expand=1)\n root.title(\"Example - Line Numbers For Text Widgets\")\n\nif __name__ == '__main__':\n demo(9)\n tk.mainloop()\n"},{"alpha_fraction":0.8260869383811951,"alphanum_fraction":0.8260869383811951,"avg_line_length":22,"blob_id":"3a2f83fc51cf2649be0a8bdbf1bbe71b2e7cbedd","content_id":"3c3382a92ddbab51348cac4c32750d7e0d2665b5","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":23,"license_type":"no_license","max_line_length":22,"num_lines":1,"path":"/README.md","repo_name":"samueltenka/LearnToHack-Compiler","src_encoding":"UTF-8","text":"# LearnToHack-Compiler\n"}],"string":"[\n {\n \"alpha_fraction\": 0.5817132592201233,\n \"alphanum_fraction\": 0.5941676497459412,\n \"avg_line_length\": 34.021278381347656,\n \"blob_id\": \"5dc60cae03c2a86726100eb63d6a901849a23bbe\",\n \"content_id\": \"838929dc2ca106258c48645f7ebdedc6a035b789\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 3292,\n \"license_type\": \"no_license\",\n \"max_line_length\": 82,\n \"num_lines\": 94,\n \"path\": \"/Parser.py\",\n \"repo_name\": \"samueltenka/LearnToHack-Compiler\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import EnsureVersion3\\n\\ndef is_number(string):\\n return string and (string[0] in '0123456789.')\\ndef is_identifier(string):\\n return string and (string[0] in 'abcdefghijklmnopqrstuvwxyz')\\n\\nclass Parser:\\n def __init__(self, program_text):\\n self.tokenized = program_text.split()\\n self.index = 0\\n self.variable_addresses = {'input':0, 'output':1}\\n self.number_addresses = dict([]); self.numbers = []\\n self.next_free_address = 3\\n self.machine_code = []\\n def peek(self):\\n return self.tokenized[self.index]\\n def match(self, token):\\n assert(self.peek() == token)\\n self.index += 1\\n def at_end(self):\\n return self.index >= len(self.tokenized)\\n def gen_code(self,instr,a,r):\\n self.machine_code.append(instr+' '+str(a)+' '+str(r))\\n def use_next_free_address(self):\\n nfa = self.next_free_address\\n self.next_free_address += 1\\n return nfa\\n\\n def write_constants_table(self):\\n l = len(self.machine_code)\\n for l in self.machine_code:\\n i, n, r = l.split(' ')\\n if i=='loadconst':\\n l[:] = 'load %s %s' % (int(self.number_addresses[n]) + l, r)\\n for n in self.numbers:\\n self.machine_code.append(n)\\n def match_number(self):\\n num=float(self.peek())\\n if num not in self.number_addresses:\\n self.number_addresses[num] = self.use_next_free_address()\\n self.numbers.append(num)\\n self.gen_code('loadconst',num,0)\\n self.match(self.peek())\\n def match_variable(self):\\n var=self.peek()\\n if var not in self.variable_addresses:\\n self.variable_addresses[var] = self.use_next_free_address()\\n self.next_free_address += 1\\n self.gen_code('load',self.variable_addresses[var],0)\\n self.match(self.peek())\\n def match_factor(self):\\n if is_number(self.peek()): self.match_number()\\n elif is_identifier(self.peek()): self.match_identifier()\\n else:\\n temp1 = self.use_next_free_address()\\n temp2 = self.use_next_free_address()\\n self.gen_code('store',temp1,1)\\n self.gen_code('store',temp2,2)\\n self.match('(')\\n self.match_expression()\\n self.match(')')\\n self.gen_code('load',temp1,1)\\n self.gen_code('load',temp2,2)\\n def match_term(self):\\n self.match_factor()\\n while not self.at_end() and self.peek() in ['*']:\\n self.match('*')\\n self.gen_code('swap',0,1)\\n self.match_factor()\\n self.gen_code('multiply',0,1)\\n def match_expression(self):\\n self.match_term()\\n while not self.at_end() and self.peek() in ['+']:\\n self.match('+')\\n self.gen_code('swap',0,2)\\n self.match_term()\\n self.gen_code('add',0,2)\\n def match_statement(self):\\n pass\\n def match_assignment(self):\\n #self.match_variable() #generates unnecessary load statement\\n var=self.peek(); assert(is_variable(var)); self.match(var)\\n self.match('=')\\n self.match_expression()\\n self.gen_code('store',self.variable_addresses[var],0)\\n #NOTE: notation easier to parse: expr->varname (assignment written backward)\\n def match_if(self):\\n self.match('if')\\n self.match('(')\\n self.match(')')\\n self.match_statement()\\n def match_while(self):\\n pass\\n\"\n },\n {\n \"alpha_fraction\": 0.5965909361839294,\n \"alphanum_fraction\": 0.6363636255264282,\n \"avg_line_length\": 21,\n \"blob_id\": \"d58151f96a1480199b32f524b7b9cb84646423ff\",\n \"content_id\": \"1fe93baac27ee0f3d64173ce37e02e42ceabf389\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 176,\n \"license_type\": \"no_license\",\n \"max_line_length\": 41,\n \"num_lines\": 8,\n \"path\": \"/ParserTest.py\",\n \"repo_name\": \"samueltenka/LearnToHack-Compiler\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from Parser import Parser\\n\\nprogram = '1 * ( 2 + 3 * 4 + 5 ) + 6 * 7'\\nP = Parser(program)\\nP.match_expression()\\nP.write_constants_table()\\nfor mc in P.machine_code:\\n print(mc)\\n\"\n },\n {\n \"alpha_fraction\": 0.5738466382026672,\n \"alphanum_fraction\": 0.5974112153053284,\n \"avg_line_length\": 39.716217041015625,\n \"blob_id\": \"c761d43d31ed9ab2d008c16d2a898f62c46c3bf9\",\n \"content_id\": \"07afd1e5c097c69d860a43c888db0c5ab6fb1b28\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 3013,\n \"license_type\": \"no_license\",\n \"max_line_length\": 91,\n \"num_lines\": 74,\n \"path\": \"/Machine.py\",\n \"repo_name\": \"samueltenka/LearnToHack-Compiler\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#Michigan Hackers Presentation on Compilers\\nimport EnsureVersion3\\n\\n'''\\ninstructions:\\nload\\t A B\\t R[B] <-- M[R[A]]\\nstore\\t A B\\t R[B] --> M[R[A]]\\ncopy\\t\\tA B\\t R[B] <-- R[A]\\nset\\t\\t A B\\t B --> R[A]\\nbranchif0\\tA B\\t PC <-- R[A] if R[B]==0\\nbranchifneg\\tA B\\t PC <-- R[A] if R[B] < 0\\njump\\t\\tA B\\t PC <-- R[A] (so B is dummy var.)\\nadd\\t\\t A B\\t R[B] <-- R[B] + R[A]\\nsub\\t\\t A B\\t R[B] <-- R[B] - R[A]\\nmul\\t\\t A B\\t R[B] <-- R[B] * R[A]\\ndiv\\t\\t A B\\t R[B] <-- R[B] / R[A]\\nmod\\t\\t A B\\t R[B] <-- R[B] % R[A]\\nNote: program might also contain literal numbers in addition to instructions.\\nMachine halts when program counter reaches -1.\\n\\nMachine Specifics:\\nEach memory address contains a float or program instruction.\\nFloats are rounded to integers when interpreted as addresses.\\nThe program counter starts at 4.\\nThe first 4 memory addresses are IO devices:\\n0 [Input, e.g. temperature sensor]\\n1 [Input, e.g. joystick]\\n2 [Output, e.g. LED]\\n3 [Output, e.g. motor]\\n4&beyond [Program then data]\\n'''\\n\\nclass Machine:\\n PRECISION = 0.0001\\n def __init__(self, num_addresses, num_registers):\\n self.memory = [0.0 for i in range(num_addresses)]\\n self.registers = [0.0 for i in range(num_registers)]\\n self.program_counter = None\\n def load_program(self, lines, inputs=(0.0,0.0)):\\n self.memory[:2] = inputs\\n for i in range(len(lines)):\\n self.memory[4+i] = lines[i] if ' ' in lines[i] else eval(lines[i])\\n self.program_counter = 4\\n def print_mem(self, l=8):\\n print('memory', ' '.join(str(s).replace(' ','_') for s in self.memory[:l])+'. . .')\\n print('registers', self.registers)\\n def step(self):\\n instr = self.memory[self.program_counter]\\n print(\\\"instr \\\", self.program_counter, instr)\\n command, arg0, arg1 = instr.split(' ')\\n getattr(self,command)(eval(arg0),eval(arg1))\\n self.program_counter += 1\\n def at_end(self):\\n return self.program_counter == -1\\n\\n def load(self, r, r_): self.registers[r_] = self.memory[int(self.registers[r])]\\n def store(self, r, r_): self.memory[int(self.registers[r])] = self.registers[r_]\\n def copy(self, r, r_): self.registers[r_] = self.registers[r]\\n def set(self, r, f): self.registers[r] = f\\n\\n def branchif0(self, r, r_):\\n if self.registers[r_]==0.0: self.jump(r)\\n def branchifneg(self, r, r_):\\n if self.registers[r_] < 0.0: self.jump(r)\\n def jump(self, r, dummy):\\n #subtract 1 to counter end-of-cycle PC increment:\\n self.program_counter = int(self.registers[r])-1\\n\\n def add (self, r, r_): self.registers[r_] += self.registers[r]\\n def sub (self, r, r_): self.registers[r_] -= self.registers[r]\\n def mul (self, r, r_): self.registers[r_] *= self.registers[r]\\n def div (self, r, r_): self.registers[r_] /= self.registers[r]\\n def mod (self, r, r_): self.registers[r_] = self.registers[r_] % self.registers[r]\\n '''Beware of floating point modulo: 0.0 != 3.50 % 0.10 == 0.09999999999999992 != 0.10'''\\n\"\n },\n {\n \"alpha_fraction\": 0.6748878955841064,\n \"alphanum_fraction\": 0.6860986351966858,\n \"avg_line_length\": 30.85714340209961,\n \"blob_id\": \"6bef20996c03ef619c8c011d09c4573b93bbb201\",\n \"content_id\": \"d3e8d38dac5e1705c621f6eb8d5101cd5261b635\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 446,\n \"license_type\": \"no_license\",\n \"max_line_length\": 87,\n \"num_lines\": 14,\n \"path\": \"/MachineTest.py\",\n \"repo_name\": \"samueltenka/LearnToHack-Compiler\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import Machine\\n\\ndef readfile(filename):\\n with open(filename,'r') as f:\\n return f.read()\\n\\nlines = readfile('MachineCode01.test').strip().split('\\\\n')\\nlines = [l.split('#')[0].strip() for l in lines] #remove line-comments such as this one\\nprint(lines)\\nnum_registers, num_addresses = lines[0].split()\\nM = Machine.Machine(eval(num_registers), eval(num_addresses), debug=False)\\nM.print_mem()\\nM.load_program(lines[2:], float(input()))\\nM.run()\\n\"\n },\n {\n \"alpha_fraction\": 0.5475285053253174,\n \"alphanum_fraction\": 0.5779467821121216,\n \"avg_line_length\": 42.83333206176758,\n \"blob_id\": \"e3958a2552af2d5dee45b4e199ab4518935b0320\",\n \"content_id\": \"1b532d87a13fb0a52ea2e116eaf15bbeaf452dd2\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 263,\n \"license_type\": \"no_license\",\n \"max_line_length\": 65,\n \"num_lines\": 6,\n \"path\": \"/PrettyPrint.py\",\n \"repo_name\": \"samueltenka/LearnToHack-Compiler\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"def pretty_print(string, minlen=10):\\n if type(string) in [type(0), type(0.0)] or ' ' not in string:\\n string = str(round(float(string),4))\\n else:\\n string = string[:3] + ';'.join(string.split(' ')[1:])\\n return string+' '*(minlen-len(string))\\n\"\n },\n {\n \"alpha_fraction\": 0.6497461795806885,\n \"alphanum_fraction\": 0.6565144062042236,\n \"avg_line_length\": 24.69565200805664,\n \"blob_id\": \"3a550a270c80f3d4773035fee84b7843d100cbb7\",\n \"content_id\": \"ba500bc2cbaa3c1561e0ec7fa930ff62e297c3bb\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 591,\n \"license_type\": \"no_license\",\n \"max_line_length\": 72,\n \"num_lines\": 23,\n \"path\": \"/NumberedTextboxTest.py\",\n \"repo_name\": \"samueltenka/LearnToHack-Compiler\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"'''\\nThanks to Robert@pytrash (see link below)\\nhttp://tk.unpythonic.net/wiki/A_Text_Widget_with_Line_Numbers\\n'''\\n\\nimport tkinter as tk\\nimport NumberedTextbox\\n\\nroot = tk.Tk()\\n\\ndef demo(noOfLines):\\n pane = tk.PanedWindow(root, orient=tk.HORIZONTAL, opaqueresize=True)\\n ed = NumberedTextbox.EditorClass(root)\\n pane.add(ed.frame)\\n s = 'line %s'\\n s = '\\\\n'.join( s%i for i in range(3, noOfLines+3) )\\n ed.text.insert(tk.END, s)\\n pane.pack(fill='both', expand=1)\\n root.title(\\\"Example - Line Numbers For Text Widgets\\\")\\n\\nif __name__ == '__main__':\\n demo(9)\\n tk.mainloop()\\n\"\n },\n {\n \"alpha_fraction\": 0.8260869383811951,\n \"alphanum_fraction\": 0.8260869383811951,\n \"avg_line_length\": 22,\n \"blob_id\": \"3a2f83fc51cf2649be0a8bdbf1bbe71b2e7cbedd\",\n \"content_id\": \"3c3382a92ddbab51348cac4c32750d7e0d2665b5\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 23,\n \"license_type\": \"no_license\",\n \"max_line_length\": 22,\n \"num_lines\": 1,\n \"path\": \"/README.md\",\n \"repo_name\": \"samueltenka/LearnToHack-Compiler\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# LearnToHack-Compiler\\n\"\n }\n]"},"num_files":{"kind":"number","value":7,"string":"7"}}},{"rowIdx":2033,"cells":{"repo_name":{"kind":"string","value":"alexseitsinger/django-rest-framework-expandable"},"repo_url":{"kind":"string","value":"https://github.com/alexseitsinger/django-rest-framework-expandable"},"snapshot_id":{"kind":"string","value":"1cf7c4737f33a0d050e8944dc9f1cfe34586ad2e"},"revision_id":{"kind":"string","value":"aacff4781387c19d319a778c569d36d57ab4b079"},"directory_id":{"kind":"string","value":"488635ce385c5235c5df4224d20a8be0f35a25f1"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"string","value":"2022-05-04T04:45:48.314469"},"revision_date":{"kind":"string","value":"2019-12-15T00:05:32"},"committer_date":{"kind":"string","value":"2019-12-15T00:05:32"},"github_id":{"kind":"number","value":215830180,"string":"215,830,180"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":1,"string":"1"},"gha_license_id":{"kind":"string","value":"BSD-2-Clause"},"gha_created_at":{"kind":"string","value":"2019-10-17T15:49:41"},"gha_updated_at":{"kind":"string","value":"2019-12-15T04:01:18"},"gha_pushed_at":{"kind":"string","value":"2022-04-22T22:34:18"},"gha_language":{"kind":"string","value":"Python"},"files":{"kind":"list like","value":[{"alpha_fraction":0.8670212626457214,"alphanum_fraction":0.8670212626457214,"avg_line_length":30.33333396911621,"blob_id":"3bd0647f9aa87d6a787af50215cdae38cd5a740c","content_id":"1c1a3b981a7050b70b52f14396c54b13361e444a","detected_licenses":["BSD-2-Clause"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":376,"license_type":"permissive","max_line_length":82,"num_lines":12,"path":"/src/rest_framework_expandable/serializers.py","repo_name":"alexseitsinger/django-rest-framework-expandable","src_encoding":"UTF-8","text":"from rest_framework.serializers import ModelSerializer, HyperlinkedModelSerializer\nfrom .mixins.expandable_model_serializer import ExpandableModelSerializerMixin\n\n\nclass ExpandableHyperlinkedModelSerializer(\n ExpandableModelSerializerMixin, HyperlinkedModelSerializer\n):\n pass\n\n\nclass ExpandableModelSerializer(ExpandableModelSerializerMixin, ModelSerializer):\n pass\n"},{"alpha_fraction":0.556477963924408,"alphanum_fraction":0.5625157356262207,"avg_line_length":26.040817260742188,"blob_id":"a91062de4c9652cafeeceb6e9b08db8fa6c999fa","content_id":"638e5f9f22c621e78f0b0076af9eb3833b77356f","detected_licenses":["BSD-2-Clause"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":3975,"license_type":"permissive","max_line_length":88,"num_lines":147,"path":"/src/rest_framework_expandable/utils.py","repo_name":"alexseitsinger/django-rest-framework-expandable","src_encoding":"UTF-8","text":"import re\nfrom django.db.models import Manager\nfrom django.db.models.query import QuerySet\n\n\ndef get_class_name(obj=None):\n # Get name of parent object.\n if obj is None:\n return \"Unnamed\"\n else:\n return obj.__class__.__name__\n\n\nclass HashableList(list):\n def __hash__(self):\n return id(self)\n\n\nclass HashableDict(dict):\n \"\"\"\n Hashable Dictionary\n\n Hashables should be immutable -- not enforcing this but TRUSTING you not to mutate a\n dict after its first use as a key.\n\n https://stackoverflow.com/questions/1151658/python-hashable-dicts\n \"\"\"\n\n def __hash__(self):\n vals = ()\n for v in self.values():\n try:\n hash(v)\n vals += (str(v),)\n except TypeError:\n if isinstance(v, list):\n for x in v:\n vals += (str(x),)\n else:\n vals += (str(v),)\n return hash((frozenset(self), frozenset(vals)))\n\n\ndef normalize_path(path):\n if path.startswith(\".\"):\n path = path[1:]\n if path.endswith(\".\"):\n path = path[:-1]\n return path\n\n\ndef get_path_parts(obj, path, base_name=None):\n pattern = re.compile(r\"(\\w+\\.\\w+)\")\n parts = [normalize_path(x) for x in pattern.split(path, 1) if len(x)]\n parts_final = []\n for part in parts:\n try:\n part_field = part.split(\".\")[1]\n except IndexError:\n part_field = part\n parts_final.append([part_field, part])\n\n ret = (parts_final[0][0], parts_final[0][1])\n if len(parts_final) > 1:\n ret += (parts_final[1][0], parts_final[1][1])\n else:\n ret += (\"\", \"\")\n return ret\n\n\ndef get_object(obj):\n if isinstance(obj, Manager):\n obj = obj.all()\n if isinstance(obj, QuerySet):\n obj = obj.first()\n return obj\n\n\nclass DictDiffer(object):\n \"\"\"\n Calculate the difference between two dictionaries as:\n (1) items added\n (2) items removed\n (3) keys same in both but changed values\n (4) keys same in both and unchanged values\n \"\"\"\n\n def __init__(self, current_dict, past_dict):\n self.current_dict, self.past_dict = current_dict, past_dict\n self.current_keys, self.past_keys = (\n set(current_dict.keys()),\n set(past_dict.keys()),\n )\n self.intersect = self.current_keys.intersection(self.past_keys)\n\n def added(self):\n \"\"\" Find keys that have been added \"\"\"\n return self.current_keys - self.intersect\n\n def removed(self):\n \"\"\" Find keys that have been removed \"\"\"\n return self.past_keys - self.intersect\n\n def changed(self):\n \"\"\" Find keys that have been changed \"\"\"\n return set(\n o for o in self.intersect if self.past_dict[o] != self.current_dict[o]\n )\n\n def unchanged(self):\n \"\"\" Find keys that are unchanged \"\"\"\n return set(\n o for o in self.intersect if self.past_dict[o] == self.current_dict[o]\n )\n\n def new_or_changed(self):\n \"\"\" Find keys that are new or changed \"\"\"\n # return set(k for k, v in self.current_dict.items()\n # if k not in self.past_keys or v != self.past_dict[k])\n return self.added().union(self.changed())\n\n\ndef remove_redundant_paths(paths):\n \"\"\"\n Returns a list of unique paths.\n \"\"\"\n results = []\n for path in paths:\n redundant = False\n paths_copy = paths[:]\n paths_copy.pop(paths.index(path))\n for p in paths_copy:\n if p.startswith(path) and len(p) > len(path):\n redundant = True\n if redundant is False:\n results.append(path)\n return results\n\n\ndef sort_field_paths(field_paths):\n \"\"\"\n Clean up a list of field paths by removing duplicates, etc.\n \"\"\"\n result = list(set(field_paths))\n result = remove_redundant_paths(result)\n result = [x for x in result if len(x)]\n return result\n"},{"alpha_fraction":0.5601385831832886,"alphanum_fraction":0.5625120401382446,"avg_line_length":35.25348663330078,"blob_id":"d6fd0414adba0594e4e089861a1f8784206a5876","content_id":"edef52e16ee682d6afae91c8bda58d432dfe6acd","detected_licenses":["BSD-2-Clause"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":15589,"license_type":"permissive","max_line_length":90,"num_lines":430,"path":"/src/rest_framework_expandable/mixins/expandable_related_field.py","repo_name":"alexseitsinger/django-rest-framework-expandable","src_encoding":"UTF-8","text":"from rest_framework.relations import ManyRelatedField\nfrom django.db.models import Manager\nfrom django.db.models.query import QuerySet\nfrom django.utils.module_loading import import_string\n\nfrom .expandable import ExpandableMixin\nfrom ..utils import (\n get_object,\n get_class_name,\n get_path_parts,\n DictDiffer,\n HashableList,\n HashableDict,\n)\n\n\n# TODO: Add an assertion for field names existing on the model.\n# TODO: Detect and fallback to default representation for circular references instead of\n# just removing the field completely on the parent.\n\n\nclass ExpandableRelatedFieldMixin(ExpandableMixin):\n settings_attr = \"expand_settings\"\n initialized_attrs = [\"allowed\", \"ignored\"]\n comparison_field_name = \"uuid\"\n\n def __init__(self, *args, **kwargs):\n # When we set read_only on the related field instance, the queryset attribute\n # will raise an exception. So, to avoid this, reset the queryset attribute to\n # None to allow these instances to be read_only when specified.\n read_only = kwargs.get(\"read_only\", False)\n if read_only is True:\n setattr(self, \"queryset\", None)\n\n for name in self.initialized_attrs:\n kwarg = kwargs.pop(name, None)\n if kwarg is not None:\n setattr(self, name, kwarg)\n\n super().__init__(*args, **kwargs)\n\n @property\n def settings(self):\n \"\"\"\n Returns the settings used for this related field instance.\n \"\"\"\n return getattr(self, self.settings_attr, {})\n\n @property\n def ignored_paths(self):\n \"\"\"\n Returns a list of field paths to ignore when generating the representation of\n this field instance.\n \"\"\"\n ignored_paths = []\n ignored = getattr(self, \"ignored\", None)\n\n if ignored is not None:\n for path in ignored:\n ignored_paths.append(self.get_field_path(path))\n\n return ignored_paths\n\n def is_ignored(self, path):\n \"\"\"\n Returns True/False if the specified path is one of the ignored field paths. Used\n by to_representation_for_field to determine if the field is the one to expand.\n \"\"\"\n if path in self.ignored_paths:\n return True\n\n return False\n\n def to_non_circular_path(self, path):\n if self.is_circular(path):\n try:\n prefix, field_name = path.rsplit(\".\", 1)\n return prefix\n except ValueError:\n return path\n return path\n\n def is_circular(self, path):\n try:\n prefix, field_name = path.rsplit(\".\", 1)\n except ValueError:\n field_name = path\n\n if field_name in self.circular_field_names:\n return True\n return False\n\n @property\n def circular_field_names(self):\n circular_field_names = []\n\n # Remove circular references to the parent model.\n parent_model_name = self.model_serializer.get_model_name()\n parent_set_name = \"{}_set\".format(parent_model_name)\n parent_names = (parent_model_name, parent_set_name)\n for parent_name in parent_names:\n circular_field_names.append(parent_name)\n\n return circular_field_names\n\n def get_skipped_fields(self, skipped=None):\n \"\"\"\n Returns a list of field paths (ignored and skipped) to pass to the serializer\n class so it doensn't return them in the representation.\n \"\"\"\n skipped_fields = self.ignored_paths\n\n for field_name in self.circular_field_names:\n skipped_fields.append(field_name)\n\n if skipped is not None:\n skipped_fields.extend(skipped)\n\n return list(set(skipped_fields))\n\n @property\n def allowed_paths(self):\n \"\"\"\n Returns a list of field paths that are permitted to be expanded from this\n expandable class instance.\n \"\"\"\n allowed = getattr(self, \"allowed\", [])\n allowed_paths = [self.get_field_path(x) for x in allowed]\n return allowed_paths\n\n def is_allowed(self, path):\n \"\"\"\n Returns True/False if the specified path is one of the allowed field paths. Used\n by to_representation_for_field to determine if the field is to be expanded.\n \"\"\"\n if path.startswith(self.allowed_prefix):\n return True\n if path in self.allowed_paths:\n return True\n return False\n\n def assert_is_allowed(self, path):\n \"\"\"\n Raises an AssertionError if the field path specified is not in the list of\n allowed field paths.\n \"\"\"\n model_serializer_name = get_class_name(self.model_serializer)\n model_serializer_field_name = self.model_serializer_field_name\n related_field_class_name = get_class_name(self)\n if self.is_allowed(path) is False:\n\n path = \".\".join(path.split(\".\")[1:])\n\n raise AssertionError(\n \"The path '{}' is not listed as an allowed field path on {}'s {} \"\n \"field. Please add the path to 'allowed' kwarg on {}'s '{}' field \"\n \"to allow its expansion.\".format(\n path,\n model_serializer_name,\n model_serializer_field_name,\n model_serializer_name,\n model_serializer_field_name,\n )\n )\n\n def assert_is_specified(self, path):\n \"\"\"\n Raises an AssertionError if the field path specified is not in the list of\n entries in the 'expands' attribute on the related field class instance.\n \"\"\"\n if self.is_specified(path) is False:\n # if field_path.startswith(self.model_name):\n # field_path.replace(\"{}.\".format(self.model_name), \"\")\n msg = []\n indent = \"\\n\"\n for d in self.settings.get(\"serializers\", []):\n msg.append(\n \"{}{}{}\".format(d[\"serializer\"], indent, indent.join(d[\"paths\"]))\n )\n\n raise AssertionError(\n \"The field path '{field_path}' is not specified in '{attr_name}' on \"\n \"{related_field_class_name}.\\n\\nCurrently Specified:\\n{specified}\".format(\n field_path=path,\n attr_name=self.settings_attr,\n related_field_class_name=get_class_name(self),\n specified=\"\\n\".join(msg),\n )\n )\n\n def is_specified(self, path):\n \"\"\"\n Returns True/False if the specified path is in any of the listed paths on the\n class isntance's 'expands' attribute.\n \"\"\"\n for d in self.settings.get(\"serializers\", []):\n if path in d.get(\"paths\", []):\n return True\n return False\n\n def is_matching(self, requested_path):\n \"\"\"\n Returns True/False if the requested path starts with the current\n 'model_serializer_field_name'.\n \"\"\"\n base_path = self.get_field_path(self.model_serializer_field_name)\n if requested_path == base_path:\n return True\n\n prefix = \"{}.\".format(base_path)\n if requested_path.startswith(prefix):\n return True\n\n return False\n\n def to_default_representation(self, obj):\n \"\"\"\n Returns the default representation of the object.\n \"\"\"\n return super().to_representation(obj)\n\n def expand_object(self, obj, path):\n \"\"\"\n Method for expanding a model instance object. If a target field name is\n specified, the serializer will use that nested object to generate a\n representation.\n \"\"\"\n # If the field exists, but its an empty object (no entry saved), obj will be\n # None. So, if we get None as obj, return None instead of trying to serializer\n # its representation.\n if obj is None:\n return None\n\n serializer = self.get_serializer(obj, path)\n representation = serializer.to_representation(obj)\n\n return representation\n\n def get_alias(self, prefix_field, prefix_path, suffix_field, suffix_path):\n for d in self.settings.get(\"aliases\", []):\n if prefix_path in d.get(\"paths\", []):\n alias = d.get(\"alias\", {})\n prefix_field = alias.get(\"prefix_field\", prefix_field)\n prefix_path = alias.get(\"prefix_path\", prefix_path)\n suffix_field = alias.get(\"suffix_field\", suffix_field)\n suffix_path = alias.get(\"suffix_path\", suffix_path)\n return (prefix_field, prefix_path, suffix_field, suffix_path)\n\n def expand(self, obj, prefix_field, prefix_path, suffix_field, suffix_path):\n if isinstance(obj, Manager):\n obj = obj.all()\n\n target = obj\n target_name = get_class_name(get_object(target)).lower()\n names = (target_name, \"{}_set\".format(target_name))\n\n if len(prefix_field) and prefix_field not in names:\n target = getattr(target, prefix_field, target)\n\n expanded = self.expand_object(target, prefix_path)\n\n if len(suffix_field):\n # If our prefix path is a manytomanyfield, then use the first string in the\n # suffix path as the field name.\n if prefix_path.endswith(\"_set\"):\n try:\n suffix_field, _ = suffix_path.split(\".\", 1)\n except ValueError:\n suffix_field = suffix_path\n expanded[suffix_field] = self.get_expanded(target, suffix_path)\n\n return expanded\n\n def get_expanded(self, obj, path):\n \"\"\"\n Fascade method for expanding objects or querysets into expanded (nested)\n representations.\n \"\"\"\n prefix_field, prefix_path, suffix_field, suffix_path = get_path_parts(obj, path)\n prefix_field, prefix_path, suffix_field, suffix_path = self.get_alias(\n prefix_field, prefix_path, suffix_field, suffix_path\n )\n if isinstance(obj, QuerySet):\n return [self.get_expanded(o, path) for o in obj]\n\n return self.expand(obj, prefix_field, prefix_path, suffix_field, suffix_path)\n\n def has_comparison_field(self, d1, d2):\n \"\"\"\n Returns True/False if both 'd1' and 'd2' have the 'comparison_field' key,\n regardless of their respective values.\n \"\"\"\n result = False\n for name in self.settings.get(\"comparison_fields\", []):\n if result is True:\n break\n result = all([name in x for x in [d1, d2]])\n return result\n\n def compare_objects(self, d1, d2):\n for name in self.settings.get(\"comparison_fields\", []):\n if all([name in x for x in [d1, d2]]):\n return d1[name] == d2[name]\n return False\n\n def get_changed_field_names(self, d1, d2):\n return DictDiffer(d1, d2).changed()\n\n def get_target_field_names(self, paths):\n result = []\n for path in paths:\n bits = path.split(\".\")\n field_name = bits[-1]\n try:\n i = bits.index(field_name)\n if bits[i - 2].endswith(\"_set\"):\n field_name = bits[i - 1]\n except IndexError:\n pass\n result.append(field_name)\n return result\n\n def to_expanded_representation(self, obj, paths):\n \"\"\"\n Entry method for converting an model object instance into a representation by\n expanding the paths specified (if they are allowed and specified).\n \"\"\"\n if isinstance(obj, Manager):\n obj = obj.all()\n\n expanded = None\n target_fields = self.get_target_field_names(paths)\n\n if len(paths) > 1:\n # expand multiple fields\n for path in paths:\n current = self.get_expanded(obj, path)\n\n if expanded is None:\n expanded = current\n elif isinstance(expanded, list):\n for d1 in expanded:\n for d2 in current:\n if self.has_comparison_field(d1, d2):\n if self.compare_objects(d1, d2):\n changed_fields = self.get_changed_field_names(\n d1, d2\n )\n for field_name in changed_fields:\n # The dict with the updated (from a url) will\n # have a smaller length.\n if len(d2[field_name]) < len(d1[field_name]):\n d1[field_name] = d2[field_name]\n else:\n # expand single field\n expanded = self.get_expanded(obj, paths[0])\n\n if isinstance(expanded, list):\n return HashableList(expanded)\n return HashableDict(expanded)\n\n def get_serializer_context(self):\n return self.context\n\n def get_serializer(self, source, path=None, context=None):\n \"\"\"\n Finds and returns the serializer class instance to use. Either imports the class\n specified in the entry on the 'expands' attribute of the ExpandableRelatedField\n instance, or re-uses the serializer class that was already imported and saved to\n the settings previously.\n \"\"\"\n serializer_class = None\n\n if context is None:\n context = self.context\n\n ret = {\"skipped_fields\": [], \"many\": False, \"context\": context}\n\n if isinstance(source, Manager):\n source = source.all()\n\n if isinstance(source, (ManyRelatedField, QuerySet)):\n ret[\"many\"] = True\n\n for d in self.settings.get(\"serializers\", []):\n if path in d.get(\"paths\", []):\n serializer_class = self.get_serializer_class(d[\"serializer\"])\n ret[\"skipped_fields\"] = self.get_skipped_fields(d.get(\"skipped\", []))\n ret[\"many\"] = d.get(\"many\", ret[\"many\"])\n\n if not isinstance(source, QuerySet):\n ret[\"many\"] = False\n # if ret[\"many\"] is True:\n # if not isinstance(source, (QuerySet)):\n # source = QuerySet(source)\n\n if serializer_class is None:\n raise RuntimeError(\n \"There is no specification for '{path}' in {class_name}.\\n\\n\"\n \"Add a dictionary to the 'expandable' list with:\\n\"\n \" 'paths': ['{path}']\".format(\n path=path, class_name=get_class_name(self)\n )\n )\n\n # print(\"---------- get_serializer_class -----------\")\n # print(\"path: \", path)\n # print(\"serializer_class: \", serializer_class.__name__)\n return serializer_class(**ret)\n\n def get_serializer_class(self, serializer_path):\n \"\"\"\n Returns the serializer class to use for serializing the object instances.\n \"\"\"\n target = None\n\n for d in self.settings.get(\"serializers\", []):\n if serializer_path == d.get(\"serializer\", \"\"):\n target = d\n\n if target is None:\n raise AttributeError(\n \"Failed to find an entry for serializer '{}'.\".format(serializer_path)\n )\n\n klass = target.get(\"serializer_class\", None)\n if klass is None:\n klass = target[\"serializer_class\"] = import_string(serializer_path)\n\n return klass\n"},{"alpha_fraction":0.5984615087509155,"alphanum_fraction":0.5984615087509155,"avg_line_length":30.325302124023438,"blob_id":"d68e28e4237b4629d81195011b4f487aa20f08c0","content_id":"e0408a2b54ce4b284875222427f4cd9f1f3d3da5","detected_licenses":["BSD-2-Clause"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":2600,"license_type":"permissive","max_line_length":88,"num_lines":83,"path":"/src/rest_framework_expandable/mixins/expandable.py","repo_name":"alexseitsinger/django-rest-framework-expandable","src_encoding":"UTF-8","text":"from ..utils import sort_field_paths\n\n\nclass ExpandableMixin(object):\n model_name = None\n query_param = \"expand\"\n expanded_fields = None\n\n @property\n def request(self):\n \"\"\"\n Returns the current request context passed from DRF.\n \"\"\"\n context = getattr(self, \"context\", None)\n if context is None:\n raise AttributeError(\"Context not found.\")\n\n request = context.get(\"request\", None)\n if request is None:\n raise AttributeError(\"Request not found in context.\")\n\n return request\n\n @property\n def all_query_params(self):\n return getattr(self.request, \"query_params\", getattr(self.request, \"GET\", {}))\n\n @property\n def params(self):\n \"\"\"\n Returns a list of unique relative field paths that should be used for expanding.\n \"\"\"\n field_paths = []\n\n target_param = getattr(self, \"query_param\", None)\n if target_param is not None:\n values = self.all_query_params.get(target_param, \"\").split(\",\")\n for param in values:\n field_paths.append(param)\n\n return sort_field_paths(field_paths)\n\n def get_model_name(self):\n \"\"\"\n Returns the model name from the ModelSerializer Meta class model specified, or\n from the previously saved model name on the class.\n \"\"\"\n model_name = getattr(self, \"model_name\", None)\n\n if model_name is None:\n model = self.Meta.model\n model_name = model.__name__.lower()\n self.model_name = model_name\n\n return model_name\n\n def get_field_path(self, path):\n \"\"\"\n Returns a list of possible field paths that are prefixed with the current\n serializers model name, plus one suffixed with _set for django's default\n reverse relationship names.\n \"\"\"\n model_name = self.get_model_name()\n prefix = \"{}.\".format(model_name)\n if not path.startswith(prefix):\n return \"{}{}\".format(prefix, path)\n return path\n\n @property\n def requested_fields(self):\n \"\"\"\n Returns a list of field paths to expand.\n Can be specified via class instance or via query params.\n \"\"\"\n requested_fields = self.params\n\n # Add our target fields that we specified on the class.\n if isinstance(self.expanded_fields, list):\n for field_path in self.expanded_fields:\n requested_fields.append(field_path)\n\n requested_fields = sort_field_paths(requested_fields)\n return requested_fields\n"},{"alpha_fraction":0.6968048810958862,"alphanum_fraction":0.704282820224762,"avg_line_length":21.630769729614258,"blob_id":"c21107e4e49c11124f4b831d4975123c8eafd024","content_id":"ba85ce52cb5228247386bcb62fa159a715aa3357","detected_licenses":["BSD-2-Clause"],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":1471,"license_type":"permissive","max_line_length":76,"num_lines":65,"path":"/README.md","repo_name":"alexseitsinger/django-rest-framework-expandable","src_encoding":"UTF-8","text":"# Django Rest Framework Expandable\n\n## Description\n\nExpandable serializers for Django REST Framework. Allow for selective object\nexpansion through query parameters or serializer class kwargs.\n\n## Installation\n\n```\npip install django-rest-framework-expandable\n```\n\n## Usage\n\n```python\n# apps/users/api.serializers.py\n# (User serializer)\nclass UserSerializer(ExpandableHyperlinkedModelSerializer):\n class Meta:\n model = User\n fields = (\"username\", \"id\", ...)\n\n# apps/users/api/fields.py\n# (User expandable serializer field)\nclass UserRelatedField(ExpandableHyperlinkedRelatedField):\n queryset = User.objects.all()\n lookup_field = \"id\"\n view_name = \"api:user-detail\"\n expand_settings = {\n \"comparison_fields\": [\"id\"],\n \"serializers\": [\n {\n \"paths\": [\"example.user\"],\n \"serializer\": \"apps.users.api.serializers.UserSerializer\",\n \"skipped\": [],\n }\n ]\n }\n\n# apps/example/api/serializers.py\n# Example serializer (using nested expandable serializer fields)\nfrom apps.users.api.fields import UserRelatedField\nfrom apps.another.api.fields import AnotherRelatedField\n\nclass ExampleSerializer(ExpandableHyperlinkedModelSerializer):\n another_related_field = AnotherRelatedField()\n user = UserRelatedField()\n ...\n```\n\nReturns...\n\n```\nGET http://localhost:8000/api/examples/?expand=example.user\n{\n id: 1,\n another_related_field: \"http://localhost:8000/api/another/1\",\n user: {\n id: 1,\n username: \"Alex\",\n ...\n }\n}\n```\n"},{"alpha_fraction":0.8484848737716675,"alphanum_fraction":0.8484848737716675,"avg_line_length":26.923076629638672,"blob_id":"1d17affc78aeb22f17a1076b522c13fd7c4083b0","content_id":"abee381392056880b28cca41a369c15e7f91ca08","detected_licenses":["BSD-2-Clause"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":363,"license_type":"permissive","max_line_length":80,"num_lines":13,"path":"/src/rest_framework_expandable/fields.py","repo_name":"alexseitsinger/django-rest-framework-expandable","src_encoding":"UTF-8","text":"from rest_framework.serializers import SlugRelatedField, HyperlinkedRelatedField\nfrom .mixins.expandable_related_field import ExpandableRelatedFieldMixin\n\n\nclass ExpandableHyperlinkedRelatedField(\n ExpandableRelatedFieldMixin,\n HyperlinkedRelatedField,\n):\n pass\n\n\nclass ExpandableSlugRelatedField(ExpandableRelatedFieldMixin, SlugRelatedField):\n pass\n"},{"alpha_fraction":0.5850965976715088,"alphanum_fraction":0.7424103021621704,"avg_line_length":44.25,"blob_id":"c2c378c4fa93a1e85f2e165f1420c57c83cdf12f","content_id":"423e99d7d459be91cae435884fd87fc549d10e2c","detected_licenses":["BSD-2-Clause"],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":2174,"license_type":"permissive","max_line_length":158,"num_lines":48,"path":"/CHANGELOG.md","repo_name":"alexseitsinger/django-rest-framework-expandable","src_encoding":"UTF-8","text":"\n## [v0.5.0](https://github.com/alexseitsinger/django-rest-framework-expandable/compare/v0.4.1...v0.5.0) (2019-12-15)\n\n### Bug Fixes\n- Allows for read_only fields. ([e681d1e](https://github.com/alexseitsinger/django-rest-framework-expandable/commit/e681d1e1c6b126a6b979b509002606fda0a54e54))\n\n### Code Refactoring\n- Fixes query params. ([d086d4c](https://github.com/alexseitsinger/django-rest-framework-expandable/commit/d086d4c5bc60a69340a0ceb2aba2488728bfeef8))\n\n\n\n## [v0.4.1](https://github.com/alexseitsinger/django-rest-framework-expandable/compare/v0.4.0...v0.4.1) (2019-10-17)\n\n\n\n## [v0.4.0](https://github.com/alexseitsinger/django-rest-framework-expandable/compare/v0.3.0...v0.4.0) (2019-10-17)\n\n\n\n## [v0.3.0](https://github.com/alexseitsinger/django-rest-framework-expandable/compare/v0.2.0...v0.3.0) (2019-10-17)\n\n\n\n## [v0.2.0](https://github.com/alexseitsinger/django-rest-framework-expandable/compare/v0.1.2...v0.2.0) (2019-10-17)\n\n### Code Refactoring\n- Renamed class property. ([05cb5a1](https://github.com/alexseitsinger/django-rest-framework-expandable/commit/05cb5a16c09013a29c8097cfebaefd182a888626))\n\n\n\n## [v0.1.2](https://github.com/alexseitsinger/django-rest-framework-expandable/compare/v0.1.1...v0.1.2) (2019-10-17)\n\n### Bug Fixes\n- Fixes import. ([b92de0c](https://github.com/alexseitsinger/django-rest-framework-expandable/commit/b92de0c7dbe718acb084b7153a48365eca2f734f))\n\n\n\n## [v0.1.1](https://github.com/alexseitsinger/django-rest-framework-expandable/compare/v0.1.0...v0.1.1) (2019-10-17)\n\n### Features\n- Adds missing util. ([19f910a](https://github.com/alexseitsinger/django-rest-framework-expandable/commit/19f910a0ab91019e400d035e5fb7abe58ab967dc))\n\n\n\n## [v0.1.0](https://github.com/alexseitsinger/django-rest-framework-expandable/compare/cdaeffc293fd0bf333d7048e2cb587d977b90a05...v0.1.0) (2019-10-17)\n\n### Features\n- Initial commit, master. ([cdaeffc](https://github.com/alexseitsinger/django-rest-framework-expandable/commit/cdaeffc293fd0bf333d7048e2cb587d977b90a05))\n\n\n"},{"alpha_fraction":0.6382263898849487,"alphanum_fraction":0.6382263898849487,"avg_line_length":34.867469787597656,"blob_id":"980253617f3d915c1cbacfae9ecbf36a8adecb3f","content_id":"bfb265e86dd36fe59a57e07214facf7510ee3cf3","detected_licenses":["BSD-2-Clause"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":2977,"license_type":"permissive","max_line_length":87,"num_lines":83,"path":"/src/rest_framework_expandable/mixins/expandable_model_serializer.py","repo_name":"alexseitsinger/django-rest-framework-expandable","src_encoding":"UTF-8","text":"from django.db.models import Manager\nfrom rest_framework.relations import ManyRelatedField\n\nfrom .expandable import ExpandableMixin\nfrom .expandable_related_field import ExpandableRelatedFieldMixin\nfrom rest_framework_helpers.mixins import RepresentationMixin\n\n\nclass ExpandableModelSerializerMixin(RepresentationMixin, ExpandableMixin):\n def __init__(self, *args, **kwargs):\n self.expanded_fields = kwargs.pop(\"expanded_fields\", None)\n super().__init__(*args, **kwargs)\n self.initialize_expandable_fields()\n\n def initialize_expandable_fields(self):\n model_name = self.get_model_name()\n\n for field_name, field in self.expandable_fields:\n field.model_name = model_name\n field.model_serializer = self\n field.model_serializer_field_name = field_name\n field.allowed_prefix = \"{}.{}.\".format(model_name, field_name)\n field.allowed = list(set([field_name] + getattr(field, \"allowed\", [])))\n\n @property\n def expandable_fields(self):\n \"\"\"\n Returns a list of all the fields that subclass ExpandableRelatedFieldMixin\n \"\"\"\n fields = []\n\n for field_name, field in self.fields.items():\n target = (\n field.child_relation if isinstance(field, ManyRelatedField) else field\n )\n\n if isinstance(target, ExpandableRelatedFieldMixin):\n fields.append([field_name, target])\n\n return fields\n\n def is_expandable(self, field):\n \"\"\"\n Returns True if the field is a subclass of the ExpandableRelatedFieldMixin\n \"\"\"\n target = field.child_relation if isinstance(field, ManyRelatedField) else field\n\n for field_name, field in self.expandable_fields:\n if field == target:\n return True\n\n return False\n\n def get_matched_paths(self, expandable_field):\n matched = []\n\n for requested_path in self.requested_fields:\n if expandable_field.is_matching(requested_path):\n expandable_field.assert_is_allowed(requested_path)\n expandable_field.assert_is_specified(requested_path)\n matched.append(requested_path)\n\n return matched\n\n def to_representation_for_field(self, field, obj):\n \"\"\"\n A function to customize what each field representation produces. Can be\n overwritten in sublclasses to add custom behavoir on a per-field basis.\n\n By default, if the field is an expandable field, it will check if it should be\n expanded, and do so if checks pass.\n \"\"\"\n if isinstance(obj, Manager):\n obj = obj.all()\n\n if self.is_expandable(field):\n target = getattr(field, \"child_relation\", field)\n\n matched = self.get_matched_paths(target)\n if len(matched):\n return target.to_expanded_representation(obj, matched)\n\n return field.to_representation(obj)\n"}],"string":"[\n {\n \"alpha_fraction\": 0.8670212626457214,\n \"alphanum_fraction\": 0.8670212626457214,\n \"avg_line_length\": 30.33333396911621,\n \"blob_id\": \"3bd0647f9aa87d6a787af50215cdae38cd5a740c\",\n \"content_id\": \"1c1a3b981a7050b70b52f14396c54b13361e444a\",\n \"detected_licenses\": [\n \"BSD-2-Clause\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 376,\n \"license_type\": \"permissive\",\n \"max_line_length\": 82,\n \"num_lines\": 12,\n \"path\": \"/src/rest_framework_expandable/serializers.py\",\n \"repo_name\": \"alexseitsinger/django-rest-framework-expandable\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from rest_framework.serializers import ModelSerializer, HyperlinkedModelSerializer\\nfrom .mixins.expandable_model_serializer import ExpandableModelSerializerMixin\\n\\n\\nclass ExpandableHyperlinkedModelSerializer(\\n ExpandableModelSerializerMixin, HyperlinkedModelSerializer\\n):\\n pass\\n\\n\\nclass ExpandableModelSerializer(ExpandableModelSerializerMixin, ModelSerializer):\\n pass\\n\"\n },\n {\n \"alpha_fraction\": 0.556477963924408,\n \"alphanum_fraction\": 0.5625157356262207,\n \"avg_line_length\": 26.040817260742188,\n \"blob_id\": \"a91062de4c9652cafeeceb6e9b08db8fa6c999fa\",\n \"content_id\": \"638e5f9f22c621e78f0b0076af9eb3833b77356f\",\n \"detected_licenses\": [\n \"BSD-2-Clause\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 3975,\n \"license_type\": \"permissive\",\n \"max_line_length\": 88,\n \"num_lines\": 147,\n \"path\": \"/src/rest_framework_expandable/utils.py\",\n \"repo_name\": \"alexseitsinger/django-rest-framework-expandable\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import re\\nfrom django.db.models import Manager\\nfrom django.db.models.query import QuerySet\\n\\n\\ndef get_class_name(obj=None):\\n # Get name of parent object.\\n if obj is None:\\n return \\\"Unnamed\\\"\\n else:\\n return obj.__class__.__name__\\n\\n\\nclass HashableList(list):\\n def __hash__(self):\\n return id(self)\\n\\n\\nclass HashableDict(dict):\\n \\\"\\\"\\\"\\n Hashable Dictionary\\n\\n Hashables should be immutable -- not enforcing this but TRUSTING you not to mutate a\\n dict after its first use as a key.\\n\\n https://stackoverflow.com/questions/1151658/python-hashable-dicts\\n \\\"\\\"\\\"\\n\\n def __hash__(self):\\n vals = ()\\n for v in self.values():\\n try:\\n hash(v)\\n vals += (str(v),)\\n except TypeError:\\n if isinstance(v, list):\\n for x in v:\\n vals += (str(x),)\\n else:\\n vals += (str(v),)\\n return hash((frozenset(self), frozenset(vals)))\\n\\n\\ndef normalize_path(path):\\n if path.startswith(\\\".\\\"):\\n path = path[1:]\\n if path.endswith(\\\".\\\"):\\n path = path[:-1]\\n return path\\n\\n\\ndef get_path_parts(obj, path, base_name=None):\\n pattern = re.compile(r\\\"(\\\\w+\\\\.\\\\w+)\\\")\\n parts = [normalize_path(x) for x in pattern.split(path, 1) if len(x)]\\n parts_final = []\\n for part in parts:\\n try:\\n part_field = part.split(\\\".\\\")[1]\\n except IndexError:\\n part_field = part\\n parts_final.append([part_field, part])\\n\\n ret = (parts_final[0][0], parts_final[0][1])\\n if len(parts_final) > 1:\\n ret += (parts_final[1][0], parts_final[1][1])\\n else:\\n ret += (\\\"\\\", \\\"\\\")\\n return ret\\n\\n\\ndef get_object(obj):\\n if isinstance(obj, Manager):\\n obj = obj.all()\\n if isinstance(obj, QuerySet):\\n obj = obj.first()\\n return obj\\n\\n\\nclass DictDiffer(object):\\n \\\"\\\"\\\"\\n Calculate the difference between two dictionaries as:\\n (1) items added\\n (2) items removed\\n (3) keys same in both but changed values\\n (4) keys same in both and unchanged values\\n \\\"\\\"\\\"\\n\\n def __init__(self, current_dict, past_dict):\\n self.current_dict, self.past_dict = current_dict, past_dict\\n self.current_keys, self.past_keys = (\\n set(current_dict.keys()),\\n set(past_dict.keys()),\\n )\\n self.intersect = self.current_keys.intersection(self.past_keys)\\n\\n def added(self):\\n \\\"\\\"\\\" Find keys that have been added \\\"\\\"\\\"\\n return self.current_keys - self.intersect\\n\\n def removed(self):\\n \\\"\\\"\\\" Find keys that have been removed \\\"\\\"\\\"\\n return self.past_keys - self.intersect\\n\\n def changed(self):\\n \\\"\\\"\\\" Find keys that have been changed \\\"\\\"\\\"\\n return set(\\n o for o in self.intersect if self.past_dict[o] != self.current_dict[o]\\n )\\n\\n def unchanged(self):\\n \\\"\\\"\\\" Find keys that are unchanged \\\"\\\"\\\"\\n return set(\\n o for o in self.intersect if self.past_dict[o] == self.current_dict[o]\\n )\\n\\n def new_or_changed(self):\\n \\\"\\\"\\\" Find keys that are new or changed \\\"\\\"\\\"\\n # return set(k for k, v in self.current_dict.items()\\n # if k not in self.past_keys or v != self.past_dict[k])\\n return self.added().union(self.changed())\\n\\n\\ndef remove_redundant_paths(paths):\\n \\\"\\\"\\\"\\n Returns a list of unique paths.\\n \\\"\\\"\\\"\\n results = []\\n for path in paths:\\n redundant = False\\n paths_copy = paths[:]\\n paths_copy.pop(paths.index(path))\\n for p in paths_copy:\\n if p.startswith(path) and len(p) > len(path):\\n redundant = True\\n if redundant is False:\\n results.append(path)\\n return results\\n\\n\\ndef sort_field_paths(field_paths):\\n \\\"\\\"\\\"\\n Clean up a list of field paths by removing duplicates, etc.\\n \\\"\\\"\\\"\\n result = list(set(field_paths))\\n result = remove_redundant_paths(result)\\n result = [x for x in result if len(x)]\\n return result\\n\"\n },\n {\n \"alpha_fraction\": 0.5601385831832886,\n \"alphanum_fraction\": 0.5625120401382446,\n \"avg_line_length\": 35.25348663330078,\n \"blob_id\": \"d6fd0414adba0594e4e089861a1f8784206a5876\",\n \"content_id\": \"edef52e16ee682d6afae91c8bda58d432dfe6acd\",\n \"detected_licenses\": [\n \"BSD-2-Clause\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 15589,\n \"license_type\": \"permissive\",\n \"max_line_length\": 90,\n \"num_lines\": 430,\n \"path\": \"/src/rest_framework_expandable/mixins/expandable_related_field.py\",\n \"repo_name\": \"alexseitsinger/django-rest-framework-expandable\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from rest_framework.relations import ManyRelatedField\\nfrom django.db.models import Manager\\nfrom django.db.models.query import QuerySet\\nfrom django.utils.module_loading import import_string\\n\\nfrom .expandable import ExpandableMixin\\nfrom ..utils import (\\n get_object,\\n get_class_name,\\n get_path_parts,\\n DictDiffer,\\n HashableList,\\n HashableDict,\\n)\\n\\n\\n# TODO: Add an assertion for field names existing on the model.\\n# TODO: Detect and fallback to default representation for circular references instead of\\n# just removing the field completely on the parent.\\n\\n\\nclass ExpandableRelatedFieldMixin(ExpandableMixin):\\n settings_attr = \\\"expand_settings\\\"\\n initialized_attrs = [\\\"allowed\\\", \\\"ignored\\\"]\\n comparison_field_name = \\\"uuid\\\"\\n\\n def __init__(self, *args, **kwargs):\\n # When we set read_only on the related field instance, the queryset attribute\\n # will raise an exception. So, to avoid this, reset the queryset attribute to\\n # None to allow these instances to be read_only when specified.\\n read_only = kwargs.get(\\\"read_only\\\", False)\\n if read_only is True:\\n setattr(self, \\\"queryset\\\", None)\\n\\n for name in self.initialized_attrs:\\n kwarg = kwargs.pop(name, None)\\n if kwarg is not None:\\n setattr(self, name, kwarg)\\n\\n super().__init__(*args, **kwargs)\\n\\n @property\\n def settings(self):\\n \\\"\\\"\\\"\\n Returns the settings used for this related field instance.\\n \\\"\\\"\\\"\\n return getattr(self, self.settings_attr, {})\\n\\n @property\\n def ignored_paths(self):\\n \\\"\\\"\\\"\\n Returns a list of field paths to ignore when generating the representation of\\n this field instance.\\n \\\"\\\"\\\"\\n ignored_paths = []\\n ignored = getattr(self, \\\"ignored\\\", None)\\n\\n if ignored is not None:\\n for path in ignored:\\n ignored_paths.append(self.get_field_path(path))\\n\\n return ignored_paths\\n\\n def is_ignored(self, path):\\n \\\"\\\"\\\"\\n Returns True/False if the specified path is one of the ignored field paths. Used\\n by to_representation_for_field to determine if the field is the one to expand.\\n \\\"\\\"\\\"\\n if path in self.ignored_paths:\\n return True\\n\\n return False\\n\\n def to_non_circular_path(self, path):\\n if self.is_circular(path):\\n try:\\n prefix, field_name = path.rsplit(\\\".\\\", 1)\\n return prefix\\n except ValueError:\\n return path\\n return path\\n\\n def is_circular(self, path):\\n try:\\n prefix, field_name = path.rsplit(\\\".\\\", 1)\\n except ValueError:\\n field_name = path\\n\\n if field_name in self.circular_field_names:\\n return True\\n return False\\n\\n @property\\n def circular_field_names(self):\\n circular_field_names = []\\n\\n # Remove circular references to the parent model.\\n parent_model_name = self.model_serializer.get_model_name()\\n parent_set_name = \\\"{}_set\\\".format(parent_model_name)\\n parent_names = (parent_model_name, parent_set_name)\\n for parent_name in parent_names:\\n circular_field_names.append(parent_name)\\n\\n return circular_field_names\\n\\n def get_skipped_fields(self, skipped=None):\\n \\\"\\\"\\\"\\n Returns a list of field paths (ignored and skipped) to pass to the serializer\\n class so it doensn't return them in the representation.\\n \\\"\\\"\\\"\\n skipped_fields = self.ignored_paths\\n\\n for field_name in self.circular_field_names:\\n skipped_fields.append(field_name)\\n\\n if skipped is not None:\\n skipped_fields.extend(skipped)\\n\\n return list(set(skipped_fields))\\n\\n @property\\n def allowed_paths(self):\\n \\\"\\\"\\\"\\n Returns a list of field paths that are permitted to be expanded from this\\n expandable class instance.\\n \\\"\\\"\\\"\\n allowed = getattr(self, \\\"allowed\\\", [])\\n allowed_paths = [self.get_field_path(x) for x in allowed]\\n return allowed_paths\\n\\n def is_allowed(self, path):\\n \\\"\\\"\\\"\\n Returns True/False if the specified path is one of the allowed field paths. Used\\n by to_representation_for_field to determine if the field is to be expanded.\\n \\\"\\\"\\\"\\n if path.startswith(self.allowed_prefix):\\n return True\\n if path in self.allowed_paths:\\n return True\\n return False\\n\\n def assert_is_allowed(self, path):\\n \\\"\\\"\\\"\\n Raises an AssertionError if the field path specified is not in the list of\\n allowed field paths.\\n \\\"\\\"\\\"\\n model_serializer_name = get_class_name(self.model_serializer)\\n model_serializer_field_name = self.model_serializer_field_name\\n related_field_class_name = get_class_name(self)\\n if self.is_allowed(path) is False:\\n\\n path = \\\".\\\".join(path.split(\\\".\\\")[1:])\\n\\n raise AssertionError(\\n \\\"The path '{}' is not listed as an allowed field path on {}'s {} \\\"\\n \\\"field. Please add the path to 'allowed' kwarg on {}'s '{}' field \\\"\\n \\\"to allow its expansion.\\\".format(\\n path,\\n model_serializer_name,\\n model_serializer_field_name,\\n model_serializer_name,\\n model_serializer_field_name,\\n )\\n )\\n\\n def assert_is_specified(self, path):\\n \\\"\\\"\\\"\\n Raises an AssertionError if the field path specified is not in the list of\\n entries in the 'expands' attribute on the related field class instance.\\n \\\"\\\"\\\"\\n if self.is_specified(path) is False:\\n # if field_path.startswith(self.model_name):\\n # field_path.replace(\\\"{}.\\\".format(self.model_name), \\\"\\\")\\n msg = []\\n indent = \\\"\\\\n\\\"\\n for d in self.settings.get(\\\"serializers\\\", []):\\n msg.append(\\n \\\"{}{}{}\\\".format(d[\\\"serializer\\\"], indent, indent.join(d[\\\"paths\\\"]))\\n )\\n\\n raise AssertionError(\\n \\\"The field path '{field_path}' is not specified in '{attr_name}' on \\\"\\n \\\"{related_field_class_name}.\\\\n\\\\nCurrently Specified:\\\\n{specified}\\\".format(\\n field_path=path,\\n attr_name=self.settings_attr,\\n related_field_class_name=get_class_name(self),\\n specified=\\\"\\\\n\\\".join(msg),\\n )\\n )\\n\\n def is_specified(self, path):\\n \\\"\\\"\\\"\\n Returns True/False if the specified path is in any of the listed paths on the\\n class isntance's 'expands' attribute.\\n \\\"\\\"\\\"\\n for d in self.settings.get(\\\"serializers\\\", []):\\n if path in d.get(\\\"paths\\\", []):\\n return True\\n return False\\n\\n def is_matching(self, requested_path):\\n \\\"\\\"\\\"\\n Returns True/False if the requested path starts with the current\\n 'model_serializer_field_name'.\\n \\\"\\\"\\\"\\n base_path = self.get_field_path(self.model_serializer_field_name)\\n if requested_path == base_path:\\n return True\\n\\n prefix = \\\"{}.\\\".format(base_path)\\n if requested_path.startswith(prefix):\\n return True\\n\\n return False\\n\\n def to_default_representation(self, obj):\\n \\\"\\\"\\\"\\n Returns the default representation of the object.\\n \\\"\\\"\\\"\\n return super().to_representation(obj)\\n\\n def expand_object(self, obj, path):\\n \\\"\\\"\\\"\\n Method for expanding a model instance object. If a target field name is\\n specified, the serializer will use that nested object to generate a\\n representation.\\n \\\"\\\"\\\"\\n # If the field exists, but its an empty object (no entry saved), obj will be\\n # None. So, if we get None as obj, return None instead of trying to serializer\\n # its representation.\\n if obj is None:\\n return None\\n\\n serializer = self.get_serializer(obj, path)\\n representation = serializer.to_representation(obj)\\n\\n return representation\\n\\n def get_alias(self, prefix_field, prefix_path, suffix_field, suffix_path):\\n for d in self.settings.get(\\\"aliases\\\", []):\\n if prefix_path in d.get(\\\"paths\\\", []):\\n alias = d.get(\\\"alias\\\", {})\\n prefix_field = alias.get(\\\"prefix_field\\\", prefix_field)\\n prefix_path = alias.get(\\\"prefix_path\\\", prefix_path)\\n suffix_field = alias.get(\\\"suffix_field\\\", suffix_field)\\n suffix_path = alias.get(\\\"suffix_path\\\", suffix_path)\\n return (prefix_field, prefix_path, suffix_field, suffix_path)\\n\\n def expand(self, obj, prefix_field, prefix_path, suffix_field, suffix_path):\\n if isinstance(obj, Manager):\\n obj = obj.all()\\n\\n target = obj\\n target_name = get_class_name(get_object(target)).lower()\\n names = (target_name, \\\"{}_set\\\".format(target_name))\\n\\n if len(prefix_field) and prefix_field not in names:\\n target = getattr(target, prefix_field, target)\\n\\n expanded = self.expand_object(target, prefix_path)\\n\\n if len(suffix_field):\\n # If our prefix path is a manytomanyfield, then use the first string in the\\n # suffix path as the field name.\\n if prefix_path.endswith(\\\"_set\\\"):\\n try:\\n suffix_field, _ = suffix_path.split(\\\".\\\", 1)\\n except ValueError:\\n suffix_field = suffix_path\\n expanded[suffix_field] = self.get_expanded(target, suffix_path)\\n\\n return expanded\\n\\n def get_expanded(self, obj, path):\\n \\\"\\\"\\\"\\n Fascade method for expanding objects or querysets into expanded (nested)\\n representations.\\n \\\"\\\"\\\"\\n prefix_field, prefix_path, suffix_field, suffix_path = get_path_parts(obj, path)\\n prefix_field, prefix_path, suffix_field, suffix_path = self.get_alias(\\n prefix_field, prefix_path, suffix_field, suffix_path\\n )\\n if isinstance(obj, QuerySet):\\n return [self.get_expanded(o, path) for o in obj]\\n\\n return self.expand(obj, prefix_field, prefix_path, suffix_field, suffix_path)\\n\\n def has_comparison_field(self, d1, d2):\\n \\\"\\\"\\\"\\n Returns True/False if both 'd1' and 'd2' have the 'comparison_field' key,\\n regardless of their respective values.\\n \\\"\\\"\\\"\\n result = False\\n for name in self.settings.get(\\\"comparison_fields\\\", []):\\n if result is True:\\n break\\n result = all([name in x for x in [d1, d2]])\\n return result\\n\\n def compare_objects(self, d1, d2):\\n for name in self.settings.get(\\\"comparison_fields\\\", []):\\n if all([name in x for x in [d1, d2]]):\\n return d1[name] == d2[name]\\n return False\\n\\n def get_changed_field_names(self, d1, d2):\\n return DictDiffer(d1, d2).changed()\\n\\n def get_target_field_names(self, paths):\\n result = []\\n for path in paths:\\n bits = path.split(\\\".\\\")\\n field_name = bits[-1]\\n try:\\n i = bits.index(field_name)\\n if bits[i - 2].endswith(\\\"_set\\\"):\\n field_name = bits[i - 1]\\n except IndexError:\\n pass\\n result.append(field_name)\\n return result\\n\\n def to_expanded_representation(self, obj, paths):\\n \\\"\\\"\\\"\\n Entry method for converting an model object instance into a representation by\\n expanding the paths specified (if they are allowed and specified).\\n \\\"\\\"\\\"\\n if isinstance(obj, Manager):\\n obj = obj.all()\\n\\n expanded = None\\n target_fields = self.get_target_field_names(paths)\\n\\n if len(paths) > 1:\\n # expand multiple fields\\n for path in paths:\\n current = self.get_expanded(obj, path)\\n\\n if expanded is None:\\n expanded = current\\n elif isinstance(expanded, list):\\n for d1 in expanded:\\n for d2 in current:\\n if self.has_comparison_field(d1, d2):\\n if self.compare_objects(d1, d2):\\n changed_fields = self.get_changed_field_names(\\n d1, d2\\n )\\n for field_name in changed_fields:\\n # The dict with the updated (from a url) will\\n # have a smaller length.\\n if len(d2[field_name]) < len(d1[field_name]):\\n d1[field_name] = d2[field_name]\\n else:\\n # expand single field\\n expanded = self.get_expanded(obj, paths[0])\\n\\n if isinstance(expanded, list):\\n return HashableList(expanded)\\n return HashableDict(expanded)\\n\\n def get_serializer_context(self):\\n return self.context\\n\\n def get_serializer(self, source, path=None, context=None):\\n \\\"\\\"\\\"\\n Finds and returns the serializer class instance to use. Either imports the class\\n specified in the entry on the 'expands' attribute of the ExpandableRelatedField\\n instance, or re-uses the serializer class that was already imported and saved to\\n the settings previously.\\n \\\"\\\"\\\"\\n serializer_class = None\\n\\n if context is None:\\n context = self.context\\n\\n ret = {\\\"skipped_fields\\\": [], \\\"many\\\": False, \\\"context\\\": context}\\n\\n if isinstance(source, Manager):\\n source = source.all()\\n\\n if isinstance(source, (ManyRelatedField, QuerySet)):\\n ret[\\\"many\\\"] = True\\n\\n for d in self.settings.get(\\\"serializers\\\", []):\\n if path in d.get(\\\"paths\\\", []):\\n serializer_class = self.get_serializer_class(d[\\\"serializer\\\"])\\n ret[\\\"skipped_fields\\\"] = self.get_skipped_fields(d.get(\\\"skipped\\\", []))\\n ret[\\\"many\\\"] = d.get(\\\"many\\\", ret[\\\"many\\\"])\\n\\n if not isinstance(source, QuerySet):\\n ret[\\\"many\\\"] = False\\n # if ret[\\\"many\\\"] is True:\\n # if not isinstance(source, (QuerySet)):\\n # source = QuerySet(source)\\n\\n if serializer_class is None:\\n raise RuntimeError(\\n \\\"There is no specification for '{path}' in {class_name}.\\\\n\\\\n\\\"\\n \\\"Add a dictionary to the 'expandable' list with:\\\\n\\\"\\n \\\" 'paths': ['{path}']\\\".format(\\n path=path, class_name=get_class_name(self)\\n )\\n )\\n\\n # print(\\\"---------- get_serializer_class -----------\\\")\\n # print(\\\"path: \\\", path)\\n # print(\\\"serializer_class: \\\", serializer_class.__name__)\\n return serializer_class(**ret)\\n\\n def get_serializer_class(self, serializer_path):\\n \\\"\\\"\\\"\\n Returns the serializer class to use for serializing the object instances.\\n \\\"\\\"\\\"\\n target = None\\n\\n for d in self.settings.get(\\\"serializers\\\", []):\\n if serializer_path == d.get(\\\"serializer\\\", \\\"\\\"):\\n target = d\\n\\n if target is None:\\n raise AttributeError(\\n \\\"Failed to find an entry for serializer '{}'.\\\".format(serializer_path)\\n )\\n\\n klass = target.get(\\\"serializer_class\\\", None)\\n if klass is None:\\n klass = target[\\\"serializer_class\\\"] = import_string(serializer_path)\\n\\n return klass\\n\"\n },\n {\n \"alpha_fraction\": 0.5984615087509155,\n \"alphanum_fraction\": 0.5984615087509155,\n \"avg_line_length\": 30.325302124023438,\n \"blob_id\": \"d68e28e4237b4629d81195011b4f487aa20f08c0\",\n \"content_id\": \"e0408a2b54ce4b284875222427f4cd9f1f3d3da5\",\n \"detected_licenses\": [\n \"BSD-2-Clause\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 2600,\n \"license_type\": \"permissive\",\n \"max_line_length\": 88,\n \"num_lines\": 83,\n \"path\": \"/src/rest_framework_expandable/mixins/expandable.py\",\n \"repo_name\": \"alexseitsinger/django-rest-framework-expandable\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from ..utils import sort_field_paths\\n\\n\\nclass ExpandableMixin(object):\\n model_name = None\\n query_param = \\\"expand\\\"\\n expanded_fields = None\\n\\n @property\\n def request(self):\\n \\\"\\\"\\\"\\n Returns the current request context passed from DRF.\\n \\\"\\\"\\\"\\n context = getattr(self, \\\"context\\\", None)\\n if context is None:\\n raise AttributeError(\\\"Context not found.\\\")\\n\\n request = context.get(\\\"request\\\", None)\\n if request is None:\\n raise AttributeError(\\\"Request not found in context.\\\")\\n\\n return request\\n\\n @property\\n def all_query_params(self):\\n return getattr(self.request, \\\"query_params\\\", getattr(self.request, \\\"GET\\\", {}))\\n\\n @property\\n def params(self):\\n \\\"\\\"\\\"\\n Returns a list of unique relative field paths that should be used for expanding.\\n \\\"\\\"\\\"\\n field_paths = []\\n\\n target_param = getattr(self, \\\"query_param\\\", None)\\n if target_param is not None:\\n values = self.all_query_params.get(target_param, \\\"\\\").split(\\\",\\\")\\n for param in values:\\n field_paths.append(param)\\n\\n return sort_field_paths(field_paths)\\n\\n def get_model_name(self):\\n \\\"\\\"\\\"\\n Returns the model name from the ModelSerializer Meta class model specified, or\\n from the previously saved model name on the class.\\n \\\"\\\"\\\"\\n model_name = getattr(self, \\\"model_name\\\", None)\\n\\n if model_name is None:\\n model = self.Meta.model\\n model_name = model.__name__.lower()\\n self.model_name = model_name\\n\\n return model_name\\n\\n def get_field_path(self, path):\\n \\\"\\\"\\\"\\n Returns a list of possible field paths that are prefixed with the current\\n serializers model name, plus one suffixed with _set for django's default\\n reverse relationship names.\\n \\\"\\\"\\\"\\n model_name = self.get_model_name()\\n prefix = \\\"{}.\\\".format(model_name)\\n if not path.startswith(prefix):\\n return \\\"{}{}\\\".format(prefix, path)\\n return path\\n\\n @property\\n def requested_fields(self):\\n \\\"\\\"\\\"\\n Returns a list of field paths to expand.\\n Can be specified via class instance or via query params.\\n \\\"\\\"\\\"\\n requested_fields = self.params\\n\\n # Add our target fields that we specified on the class.\\n if isinstance(self.expanded_fields, list):\\n for field_path in self.expanded_fields:\\n requested_fields.append(field_path)\\n\\n requested_fields = sort_field_paths(requested_fields)\\n return requested_fields\\n\"\n },\n {\n \"alpha_fraction\": 0.6968048810958862,\n \"alphanum_fraction\": 0.704282820224762,\n \"avg_line_length\": 21.630769729614258,\n \"blob_id\": \"c21107e4e49c11124f4b831d4975123c8eafd024\",\n \"content_id\": \"ba85ce52cb5228247386bcb62fa159a715aa3357\",\n \"detected_licenses\": [\n \"BSD-2-Clause\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 1471,\n \"license_type\": \"permissive\",\n \"max_line_length\": 76,\n \"num_lines\": 65,\n \"path\": \"/README.md\",\n \"repo_name\": \"alexseitsinger/django-rest-framework-expandable\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# Django Rest Framework Expandable\\n\\n## Description\\n\\nExpandable serializers for Django REST Framework. Allow for selective object\\nexpansion through query parameters or serializer class kwargs.\\n\\n## Installation\\n\\n```\\npip install django-rest-framework-expandable\\n```\\n\\n## Usage\\n\\n```python\\n# apps/users/api.serializers.py\\n# (User serializer)\\nclass UserSerializer(ExpandableHyperlinkedModelSerializer):\\n class Meta:\\n model = User\\n fields = (\\\"username\\\", \\\"id\\\", ...)\\n\\n# apps/users/api/fields.py\\n# (User expandable serializer field)\\nclass UserRelatedField(ExpandableHyperlinkedRelatedField):\\n queryset = User.objects.all()\\n lookup_field = \\\"id\\\"\\n view_name = \\\"api:user-detail\\\"\\n expand_settings = {\\n \\\"comparison_fields\\\": [\\\"id\\\"],\\n \\\"serializers\\\": [\\n {\\n \\\"paths\\\": [\\\"example.user\\\"],\\n \\\"serializer\\\": \\\"apps.users.api.serializers.UserSerializer\\\",\\n \\\"skipped\\\": [],\\n }\\n ]\\n }\\n\\n# apps/example/api/serializers.py\\n# Example serializer (using nested expandable serializer fields)\\nfrom apps.users.api.fields import UserRelatedField\\nfrom apps.another.api.fields import AnotherRelatedField\\n\\nclass ExampleSerializer(ExpandableHyperlinkedModelSerializer):\\n another_related_field = AnotherRelatedField()\\n user = UserRelatedField()\\n ...\\n```\\n\\nReturns...\\n\\n```\\nGET http://localhost:8000/api/examples/?expand=example.user\\n{\\n id: 1,\\n another_related_field: \\\"http://localhost:8000/api/another/1\\\",\\n user: {\\n id: 1,\\n username: \\\"Alex\\\",\\n ...\\n }\\n}\\n```\\n\"\n },\n {\n \"alpha_fraction\": 0.8484848737716675,\n \"alphanum_fraction\": 0.8484848737716675,\n \"avg_line_length\": 26.923076629638672,\n \"blob_id\": \"1d17affc78aeb22f17a1076b522c13fd7c4083b0\",\n \"content_id\": \"abee381392056880b28cca41a369c15e7f91ca08\",\n \"detected_licenses\": [\n \"BSD-2-Clause\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 363,\n \"license_type\": \"permissive\",\n \"max_line_length\": 80,\n \"num_lines\": 13,\n \"path\": \"/src/rest_framework_expandable/fields.py\",\n \"repo_name\": \"alexseitsinger/django-rest-framework-expandable\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from rest_framework.serializers import SlugRelatedField, HyperlinkedRelatedField\\nfrom .mixins.expandable_related_field import ExpandableRelatedFieldMixin\\n\\n\\nclass ExpandableHyperlinkedRelatedField(\\n ExpandableRelatedFieldMixin,\\n HyperlinkedRelatedField,\\n):\\n pass\\n\\n\\nclass ExpandableSlugRelatedField(ExpandableRelatedFieldMixin, SlugRelatedField):\\n pass\\n\"\n },\n {\n \"alpha_fraction\": 0.5850965976715088,\n \"alphanum_fraction\": 0.7424103021621704,\n \"avg_line_length\": 44.25,\n \"blob_id\": \"c2c378c4fa93a1e85f2e165f1420c57c83cdf12f\",\n \"content_id\": \"423e99d7d459be91cae435884fd87fc549d10e2c\",\n \"detected_licenses\": [\n \"BSD-2-Clause\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 2174,\n \"license_type\": \"permissive\",\n \"max_line_length\": 158,\n \"num_lines\": 48,\n \"path\": \"/CHANGELOG.md\",\n \"repo_name\": \"alexseitsinger/django-rest-framework-expandable\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"\\n## [v0.5.0](https://github.com/alexseitsinger/django-rest-framework-expandable/compare/v0.4.1...v0.5.0) (2019-12-15)\\n\\n### Bug Fixes\\n- Allows for read_only fields. ([e681d1e](https://github.com/alexseitsinger/django-rest-framework-expandable/commit/e681d1e1c6b126a6b979b509002606fda0a54e54))\\n\\n### Code Refactoring\\n- Fixes query params. ([d086d4c](https://github.com/alexseitsinger/django-rest-framework-expandable/commit/d086d4c5bc60a69340a0ceb2aba2488728bfeef8))\\n\\n\\n\\n## [v0.4.1](https://github.com/alexseitsinger/django-rest-framework-expandable/compare/v0.4.0...v0.4.1) (2019-10-17)\\n\\n\\n\\n## [v0.4.0](https://github.com/alexseitsinger/django-rest-framework-expandable/compare/v0.3.0...v0.4.0) (2019-10-17)\\n\\n\\n\\n## [v0.3.0](https://github.com/alexseitsinger/django-rest-framework-expandable/compare/v0.2.0...v0.3.0) (2019-10-17)\\n\\n\\n\\n## [v0.2.0](https://github.com/alexseitsinger/django-rest-framework-expandable/compare/v0.1.2...v0.2.0) (2019-10-17)\\n\\n### Code Refactoring\\n- Renamed class property. ([05cb5a1](https://github.com/alexseitsinger/django-rest-framework-expandable/commit/05cb5a16c09013a29c8097cfebaefd182a888626))\\n\\n\\n\\n## [v0.1.2](https://github.com/alexseitsinger/django-rest-framework-expandable/compare/v0.1.1...v0.1.2) (2019-10-17)\\n\\n### Bug Fixes\\n- Fixes import. ([b92de0c](https://github.com/alexseitsinger/django-rest-framework-expandable/commit/b92de0c7dbe718acb084b7153a48365eca2f734f))\\n\\n\\n\\n## [v0.1.1](https://github.com/alexseitsinger/django-rest-framework-expandable/compare/v0.1.0...v0.1.1) (2019-10-17)\\n\\n### Features\\n- Adds missing util. ([19f910a](https://github.com/alexseitsinger/django-rest-framework-expandable/commit/19f910a0ab91019e400d035e5fb7abe58ab967dc))\\n\\n\\n\\n## [v0.1.0](https://github.com/alexseitsinger/django-rest-framework-expandable/compare/cdaeffc293fd0bf333d7048e2cb587d977b90a05...v0.1.0) (2019-10-17)\\n\\n### Features\\n- Initial commit, master. ([cdaeffc](https://github.com/alexseitsinger/django-rest-framework-expandable/commit/cdaeffc293fd0bf333d7048e2cb587d977b90a05))\\n\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.6382263898849487,\n \"alphanum_fraction\": 0.6382263898849487,\n \"avg_line_length\": 34.867469787597656,\n \"blob_id\": \"980253617f3d915c1cbacfae9ecbf36a8adecb3f\",\n \"content_id\": \"bfb265e86dd36fe59a57e07214facf7510ee3cf3\",\n \"detected_licenses\": [\n \"BSD-2-Clause\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 2977,\n \"license_type\": \"permissive\",\n \"max_line_length\": 87,\n \"num_lines\": 83,\n \"path\": \"/src/rest_framework_expandable/mixins/expandable_model_serializer.py\",\n \"repo_name\": \"alexseitsinger/django-rest-framework-expandable\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from django.db.models import Manager\\nfrom rest_framework.relations import ManyRelatedField\\n\\nfrom .expandable import ExpandableMixin\\nfrom .expandable_related_field import ExpandableRelatedFieldMixin\\nfrom rest_framework_helpers.mixins import RepresentationMixin\\n\\n\\nclass ExpandableModelSerializerMixin(RepresentationMixin, ExpandableMixin):\\n def __init__(self, *args, **kwargs):\\n self.expanded_fields = kwargs.pop(\\\"expanded_fields\\\", None)\\n super().__init__(*args, **kwargs)\\n self.initialize_expandable_fields()\\n\\n def initialize_expandable_fields(self):\\n model_name = self.get_model_name()\\n\\n for field_name, field in self.expandable_fields:\\n field.model_name = model_name\\n field.model_serializer = self\\n field.model_serializer_field_name = field_name\\n field.allowed_prefix = \\\"{}.{}.\\\".format(model_name, field_name)\\n field.allowed = list(set([field_name] + getattr(field, \\\"allowed\\\", [])))\\n\\n @property\\n def expandable_fields(self):\\n \\\"\\\"\\\"\\n Returns a list of all the fields that subclass ExpandableRelatedFieldMixin\\n \\\"\\\"\\\"\\n fields = []\\n\\n for field_name, field in self.fields.items():\\n target = (\\n field.child_relation if isinstance(field, ManyRelatedField) else field\\n )\\n\\n if isinstance(target, ExpandableRelatedFieldMixin):\\n fields.append([field_name, target])\\n\\n return fields\\n\\n def is_expandable(self, field):\\n \\\"\\\"\\\"\\n Returns True if the field is a subclass of the ExpandableRelatedFieldMixin\\n \\\"\\\"\\\"\\n target = field.child_relation if isinstance(field, ManyRelatedField) else field\\n\\n for field_name, field in self.expandable_fields:\\n if field == target:\\n return True\\n\\n return False\\n\\n def get_matched_paths(self, expandable_field):\\n matched = []\\n\\n for requested_path in self.requested_fields:\\n if expandable_field.is_matching(requested_path):\\n expandable_field.assert_is_allowed(requested_path)\\n expandable_field.assert_is_specified(requested_path)\\n matched.append(requested_path)\\n\\n return matched\\n\\n def to_representation_for_field(self, field, obj):\\n \\\"\\\"\\\"\\n A function to customize what each field representation produces. Can be\\n overwritten in sublclasses to add custom behavoir on a per-field basis.\\n\\n By default, if the field is an expandable field, it will check if it should be\\n expanded, and do so if checks pass.\\n \\\"\\\"\\\"\\n if isinstance(obj, Manager):\\n obj = obj.all()\\n\\n if self.is_expandable(field):\\n target = getattr(field, \\\"child_relation\\\", field)\\n\\n matched = self.get_matched_paths(target)\\n if len(matched):\\n return target.to_expanded_representation(obj, matched)\\n\\n return field.to_representation(obj)\\n\"\n }\n]"},"num_files":{"kind":"number","value":8,"string":"8"}}},{"rowIdx":2034,"cells":{"repo_name":{"kind":"string","value":"TruongKhang/topic_models"},"repo_url":{"kind":"string","value":"https://github.com/TruongKhang/topic_models"},"snapshot_id":{"kind":"string","value":"44505e89d3609c511aa2f29b349abf438c1796a2"},"revision_id":{"kind":"string","value":"ed912425532dad46792986b768aa8e37bd647b2a"},"directory_id":{"kind":"string","value":"d1bb25cf90a0499cfb351d787f304db537560840"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"string","value":"2019-08-23T11:25:50.637917"},"revision_date":{"kind":"string","value":"2017-03-22T19:13:53"},"committer_date":{"kind":"string","value":"2017-03-22T19:13:53"},"github_id":{"kind":"number","value":67353561,"string":"67,353,561"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.6532507538795471,"alphanum_fraction":0.6656346917152405,"avg_line_length":23.846153259277344,"blob_id":"99b5494de905cdebe776ee9a4a85048a31a1b015","content_id":"71d7a738ef132f37d0ec62b280565aaf4f355167","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":323,"license_type":"no_license","max_line_length":71,"num_lines":13,"path":"/ap/read_line_specific.py","repo_name":"TruongKhang/topic_models","src_encoding":"UTF-8","text":"from time import time\ndef readline_number_x(file,x):\n for index,line in enumerate(iter(file)):\n if index+1 == x: return line\n\n return None\n\nf = open('grolier_train.txt')\nx = 1\nt0 = time()\nline_number_x = readline_number_x(f,x) #This will return the third line\nprint \"Time: %f\" %(time()-t0)\nprint line_number_x\n"},{"alpha_fraction":0.5002655386924744,"alphanum_fraction":0.5087625980377197,"avg_line_length":36.90604019165039,"blob_id":"3fbc3be3b46f12507dae158c3db1b72b069a20e1","content_id":"b8dbc9dd62b23582084773c480f109b150558ef4","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":5649,"license_type":"no_license","max_line_length":184,"num_lines":149,"path":"/run_batch.py","repo_name":"TruongKhang/topic_models","src_encoding":"UTF-8","text":"# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Mon Oct 26 15:52:29 2015\n\n@author: dhbk\n\"\"\"\nimport sys, os, shutil\nimport numpy as np\nmypath = ['./lda/Batch_VB', './lda/OPE', './lda/Online-VB']\n\n# Name of current path directory which contains this file\ndir_path = os.path.dirname(os.path.realpath(__file__))\n\nfor temp in mypath:\n sys.path.insert(0, temp)\nfrom datasets import base\n#import run_Batch_VB\n#import run_OPE\n\ndef main():\n # Check input\n if len(sys.argv)!=10 and len(sys.argv)!=9:\n print(\"usage: python run_batch.py [method name] [data file] [setting file] [model folder] [test_folder] [method noise] [alpha] [only_doc] [[vocab:vocabulary file (optional)]]\")\n print(\"or: python run_batch.py [method name] [data file] [setting file] [model folder] [test_folder] [a] [method noise] [only_doc] [[beta:beta file (optional)]]\")\n exit()\n else:\n # Get environment variables\n method_name = sys.argv[1]\n data_file = sys.argv[2]\n setting_file = sys.argv[3]\n model_folder = sys.argv[4]\n test_folder = sys.argv[5]\n method_noise = sys.argv[6]\n alpha = sys.argv[7]\n only_doc = sys.argv[8]\n beta_file = ''\n vocab_file = ''\n if len(sys.argv) == 10:\n name = sys.argv[9].split('[')\n if name[0] == 'vocab':\n vocab_file = name[1]\n elif name[0] == 'beta':\n beta_file = name[1]\n\n tops = 10 # int(sys.argv[5])\n # Check format data: raw text or not\n data = base.Dataset(data_file)\n formatted_data = data.load_dataset()\n if len(sys.argv) == 9:\n if not data.is_raw_text:\n print(\"File %s is formatted file. Please add argument [vocabulary file] into command\" % data_file)\n exit()\n else:\n vocab_file = data.vocab_path\n elif len(sys.argv) == 10:\n if data.is_raw_text:\n if beta_file:\n print(\"Input is raw text. Library will preprocessing it.\\\n Vocaburaly can change. So, beta file can't be used in this case. Please remove this argument\")\n exit()\n vocab_file = data.vocab_path\n\n # Read settings\n print('reading setting ...')\n settings = base.read_setting(setting_file)\n num_docs = formatted_data.num_doc\n if beta_file:\n file = beta_file\n else:\n file = vocab_file\n if os.path.isfile(file):\n f = open(file, 'r')\n lines = f.readlines()\n if vocab_file:\n num_terms = len(lines)\n if beta_file:\n num_terms = len(lines[0].strip().split())\n shutil.copyfile(beta_file, dir_path+'/beta_copy.txt')\n beta_file = dir_path+'/beta_copy.txt'\n del lines\n f.close()\n settings['num_docs'] = num_docs\n settings['num_terms'] = num_terms\n else:\n print(\"Can't find vocabulary file!\")\n exit()\n\n # Create model folder if it doesn't exist\n if os.path.exists(model_folder):\n shutil.rmtree(model_folder)\n os.makedirs(model_folder)\n a = None\n if beta_file:\n namebeta = name[1]\n lname = namebeta.split('/')\n b = lname[len(lname)-2]\n if 'True' in b:\n value = b[4:]\n elif 'False' in b:\n value = b[5:]\n elif 'batchvb' in b:\n value = b[7:]\n settings['iter_train'] = int(value)\n if method_noise == 'add_ope' or method_noise == 'mult_ope':\n direct = namebeta[:-(len('beta_final.dat'))]\n filea = direct + '/a_' + value + '.txt'\n f = open(filea)\n\n print('Read a...')\n if only_doc == 'True':\n lines = f.readlines()\n a = np.zeros(len(lines), dtype=np.int32)\n for d in range(len(lines)):\n a[d] = int(lines[d].strip())\n else:\n lines = f.readlines()\n a = list()\n for d in range(len(lines)):\n words = lines[d].strip().split()\n w = np.zeros(len(words), dtype=np.int32)\n for n in range(len(words)):\n w[n] = int(words[n])\n a.append(w)\n f.close()\n # Read data for computing perplexities\n print('read data for computing perplexities ...')\n test_data = base.read_data_for_perpl(test_folder)\n # Check method and run algorithm\n alpha = float(alpha)\n if only_doc == 'True':\n only_doc = True\n else:\n only_doc = False\n\n if method_name == 'batch-vb':\n import run_Batch_VB\n runbatchvb = run_Batch_VB.runBatchVB(formatted_data, settings, model_folder, tops, test_data, beta_file)\n runbatchvb.run(method_noise,alpha,only_doc,a)\n elif method_name == 'batch-ope':\n import run_OPE\n runbatchope = run_OPE.runOPE(formatted_data, settings, model_folder, tops, test_data, beta_file)\n runbatchope.run(method_noise, alpha, only_doc, a)\n elif method_name == 'online-vb':\n import run_VB\n runbatchvb = run_VB.runOnlineVB(formatted_data, settings, model_folder, tops, test_data, beta_file)\n runbatchvb.run(method_noise,alpha,only_doc,a)\n\nif __name__ == '__main__':\n main()\n\n"},{"alpha_fraction":0.45909690856933594,"alphanum_fraction":0.4643869400024414,"avg_line_length":34.2933349609375,"blob_id":"7cf6a5f1cf23ce76398b34373a52de2f9aa67a99","content_id":"17d3281195ef03b4e4eb1f3604f7d48cd16140fb","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":5293,"license_type":"no_license","max_line_length":82,"num_lines":150,"path":"/preprocessing/preprocessing.py","repo_name":"TruongKhang/topic_models","src_encoding":"UTF-8","text":"import os, os.path\nfrom os.path import isfile, join, isdir\nimport numpy as np\nfrom nltk.tokenize import TreebankWordTokenizer\nfrom nltk.tokenize import RegexpTokenizer\nfrom nltk.stem.porter import PorterStemmer\n\ndir_path = os.path.dirname(os.path.realpath(__file__))\ntokenizer = RegexpTokenizer(r'\\w+')\np_stemmer = PorterStemmer()\n\nclass PreProcessing:\n def __init__(self, stemmed=False, remove_rare_word=True):\n self.list_doc = list()\n self.vocab = list()\n self.list_doc_freq = list()\n self.stemmed = stemmed\n self.remove_rare_word = remove_rare_word\n self.id_doc = 0\n self.df = list()\n\n def pro_per_doc(self, doc, stop_list):\n words = tokenizer.tokenize(doc.lower())\n list_word = list()\n for word in words:\n if word not in stop_list:\n if word.isalpha() and len(word) > 2:\n if self.stemmed:\n word = p_stemmer.stem(word)\n if word in self.vocab:\n index = self.vocab.index(word)\n if self.id_doc not in self.df[index]:\n self.df[index].append(self.id_doc)\n #list_word.append(word)\n else:\n self.vocab.append(word)\n self.df.append([self.id_doc])\n list_word.append(word)\n self.id_doc += 1\n return list_word\n\n def filter(self):\n if self.vocab:\n V = len(self.vocab)\n remove_list = []\n i = 0\n while i < V:\n #print(V)\n freq = len(self.df[i])\n #print(freq)\n if freq <= 5 or freq > int(0.5*self.id_doc):\n #remove_list.append(i)\n docs = self.df[i]\n word = self.vocab[i]\n for j in docs:\n while word in self.list_doc[j]:\n self.list_doc[j].remove(word)\n del self.vocab[i]\n del self.df[i]\n V = len(self.vocab)\n i = i - 1\n i += 1\n else:\n print(\"Vocabulary is empty! Please run process first!\")\n\n def process(self, path):\n name_file = path.split(\"\\\\\")\n name_file = name_file[-1].split(\"/\")\n name = name_file[-1].split(\".\")\n self.filename = name[0]\n #print(self.filename)\n fin = open(dir_path+\"/stop_word_list.txt\")\n stop_list = list()\n line = fin.readline()\n while line:\n line = line.strip()\n stop_list.append(line)\n line = fin.readline()\n fin.close()\n stop_list = stop_list + ['_',]\n print(\"Waiting...\")\n if isfile(path):\n fread = open(path)\n line = fread.readline()\n num = 1\n while line:\n line = line.strip()\n if line == \"\":\n doc = fread.readline().strip()\n #print(num)\n list_word = self.pro_per_doc(doc,stop_list)\n self.list_doc.append(list_word)\n num += 1\n line = fread.readline()\n if self.remove_rare_word:\n self.filter()\n\n numDocs = len(self.list_doc)\n for d in range(0,numDocs):\n list_word = []\n numWords = len(self.list_doc[d])\n for w in range(0,numWords):\n word = self.list_doc[d][w]\n self.list_doc[d][w] = self.vocab.index(word)\n inlist = False\n for elem in list_word:\n if self.list_doc[d][w] == elem[0]:\n elem[1] += 1\n inlist = True\n break\n if not inlist:\n list_word.append([self.list_doc[d][w],1])\n self.list_doc_freq.append(list_word)\n\n def extract_vocab(self):\n if self.vocab:\n self.dir_path_data = dir_path[:-13] + \"datasets/data/\" + self.filename\n if not os.path.exists(self.dir_path_data):\n os.makedirs(self.dir_path_data)\n fout = open(join(self.dir_path_data,\"vocab.txt\"),\"w\")\n for word in self.vocab:\n fout.write(\"%s\\n\" %word)\n fout.close()\n\n def format_seq(self):\n if self.list_doc:\n fout = open(join(self.dir_path_data,\"term_sequence.txt\"), \"w\")\n for doc in self.list_doc:\n fout.write(\"%d \" %len(doc))\n for word in doc:\n fout.write(\"%d \" %word)\n fout.write(\"\\n\")\n fout.close()\n\n def format_freq(self):\n if self.list_doc:\n fout = open(join(self.dir_path_data,\"term_frequency.txt\"), \"w\")\n for doc in self.list_doc_freq:\n fout.write(\"%d \" %len(doc))\n for elem in doc:\n fout.write(\"%d:%d \" %(elem[0],elem[1]))\n fout.write(\"\\n\")\n fout.close()\n\nif __name__ == '__main__':\n p = PreProcessing()\n p.process(\"D:\\\\UCR_TS_Archive_2015\\\\ap/ap.txt\")\n p.extract_vocab()\n p.format_freq()\n p.format_seq()"},{"alpha_fraction":0.5302867293357849,"alphanum_fraction":0.5345979928970337,"avg_line_length":38.99137878417969,"blob_id":"9e19973236fdadce9914de69d2ae441dd8e15ad4","content_id":"17d89ecc721c9af1a5647fc6d1a32b39ef7a8201","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":4639,"license_type":"no_license","max_line_length":116,"num_lines":116,"path":"/lda/Batch_VB/run_Batch_VB.py","repo_name":"TruongKhang/topic_models","src_encoding":"UTF-8","text":"#!/usr/bin/python\n# -*- coding: utf-8 -*-\n\nimport sys, os\nimport Batch_VB\nimport numpy as np\n\nfrom datasets import base, noise_data\nfrom evaluation import perplexity\n\nclass runBatchVB:\n\n def __init__(self, formatted_data, settings, model_folder, tops, test_data, beta_file=None):\n self.formatted_data = formatted_data\n self.settings = settings\n self.model_folder = model_folder\n self.beta_file = beta_file\n self.test_data = test_data\n self.tops = tops\n\n def run(self,method,alpha,only_doc=True, a=None):\n # Initialize the algorithm\n if self.beta_file:\n print('Load beta to continue learn...')\n beta = base.read_beta(self.beta_file)\n os.remove(self.beta_file)\n\t i = self.settings['iter_train']\n\t self.settings['iter_train'] += 50\n else:\n print('initialize the algorithm ...')\n beta = None\n\t i = 0\n batch_vb = Batch_VB.BatchVB(self.settings['num_terms'], self.settings['num_topics'], self.settings['alpha'],\n self.settings['eta'], self.settings['iter_infer'],\n self.settings['conv_infer'], beta)\n # Start\n print('start!!!')\n datafp = open(self.formatted_data.data_path, 'r')\n (wordids, wordcts) = self.formatted_data.load_batch(datafp)\n\tif a is None:\n if only_doc:\n a = np.zeros(len(wordids), dtype=np.int32)\n else:\n\t a = list()\n\t for d in range(0, len(wordids)):\n\t\t N = len(wordids[d])\n\t\t w = np.zeros(N, dtype=np.int32)\n\t\t a.append(w)\n del wordids\n del wordcts\n if method != 'none':\n if only_doc:\n print('Method: %s, alpha: %.1f, only_doc=true' %(method,alpha))\n else:\n print('Method: %s, alpha: %.1f, only_doc=false' % (method, alpha))\n else:\n print('Method: none noise data')\n while i < self.settings['iter_train']:\n i += 1\n print('***num_iter_train***: %d' %i)\n iter_train = i\n train_file = self.formatted_data.data_path\n datafp = open(train_file, 'r')\n (wordids, wordcts) = self.formatted_data.load_batch(datafp)\n data = noise_data.Noise_Data(wordids,wordcts,iter_train,alpha,a,self.settings['p'],only_doc)\n if method == 'add_uniform':\n (wordids,wordcts) = data.add_uniform()\n elif method == 'mult_uniform':\n (wordids,wordcts) = data.mult_uniform()\n elif method == 'add_ope':\n (wordids,wordcts,a) = data.add_ope()\n elif method == 'mult_ope':\n (wordids,wordcts,a) = data.mult_ope()\n (time_e, time_m, theta) = batch_vb.static_online(wordids, wordcts)\n # Compute sparsity\n #sparsity = base.compute_sparsity(theta, theta.shape[0], theta.shape[1], 't')\n # Compute perplexities\n LD2 = perplexity.average_predict(self.test_data, self.settings['alpha'], self.settings['eta'],\n batch_vb._lambda, self.settings['iter_infer'])\n # Search top words of each topics\n #list_tops = base.list_top(batch_vb._lambda, self.tops)\n # Write files\n base.write_file(i, 0, batch_vb._lambda, time_e, time_m, theta, [], LD2, [], self.tops,\n self.model_folder)\n datafp.close()\n # Write settings\n print('write setting ...')\n file_name = '%s/setting.txt'%(self.model_folder)\n base.write_setting(self.settings, file_name)\n # Write final model to file\n print('write final model ...')\n file_name = '%s/beta_final.dat'%(self.model_folder)\n base.write_topics(batch_vb._lambda, file_name)\n\t# Write a\n\tfile_name = '%s/a_%d.txt'%(self.model_folder, i)\n\tf = open(file_name, 'w')\n\tD = len(a)\n\tif only_doc:\n\t for d in range(0, D):\n\t\tf.write('%d\\n' %a[d])\n\telse:\n\t for d in range(0,D):\n\t\tN = len(a[d])\n\t\tfor n in range(0,N):\n\t\t f.write('%d '%a[d][n])\n\t\tf.write('\\n')\n\tf.close()\n # caculate avarage predict probability\n \"\"\"file_name = '%s/perplexity.txt'%(self.model_folder)\n value = perplexity.average_predict(self.test_folder, self.settings['alpha'], self.settings['eta'],\n batch_vb._lambda, self.settings['iter_infer'])\n base.write_perplexities(value,file_name)\"\"\"\n\n # Finish\n print('done!!!')\n print('-----------------------------------------\\n')\n"},{"alpha_fraction":0.5662844181060791,"alphanum_fraction":0.6080275177955627,"avg_line_length":33.60317611694336,"blob_id":"b642126ca3844bdadaefaff8b0354cd11fc47778","content_id":"125b06905636338ddf2ea3cb07144065635b2876","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":4360,"license_type":"no_license","max_line_length":117,"num_lines":126,"path":"/plot_graph.py","repo_name":"TruongKhang/topic_models","src_encoding":"UTF-8","text":"import csv\nimport numpy as np\nimport matplotlib.pyplot as plt\nimport matplotlib\ncopus = ['grolier']\n#method_learing = ['OPE_linear_function', 'OPE_linear_function']\nnoise = ['add_uniform', 'mult_uniform', 'add_ope', 'mult_ope']\nalpha = [0.3, 0.5, 0.7, 1.0]\nonly_doc = ['True', 'False']\nnum_train = [100] #[50, 100, 150, 200]\nlist_alpha1 = list()\nfor name in copus:\n for value in alpha:\n\tnew_value = int(value*10)\n\tlist_method = list()\n\tfor method in noise:\n\t list_only = list()\n\t for boolean in only_doc:\n\t\tlist_per = list()\n\t\tfor index in num_train:\n\t\t for i in range(1,index+1):\n\t\t\taverage = 0.\n\t\t\tfor j in range(4,5):\n\t\t\t file_name = '%s_model_ver2/VB%d/%s/alpha%d/%s200/perplexities_%d.csv'%(name, j, method, new_value, boolean, i)\n\t\t\t f = open(file_name, 'rb')\n\t\t\t reader = csv.reader(f)\n\t\t\t for row in reader:\n\t\t\t perplex = float(row[0])\n\t\t\t average += perplex\n\t\t\taverage = float(average/1)\n\t\t\tlist_per.append(average)\n\t\tlist_only.append(np.array(list_per))\n\t list_method.append(list_only)\n list_alpha1.append(list_method)\nprint(len(list_alpha1[0]))\n\nper_batch = list()\nnum_train1 = [100]\nfor index in num_train1:\n for i in range(1,index+1):\n\taverage = 0.\n\tfor j in range(4,5):\n\t filename = 'grolier_model_ver2/VB%d/batch_vb/batchvb200/perplexities_%d.csv'%(j,i)\n\t f = open(filename, 'rb')\n\t reader = csv.reader(f)\n\t for row in reader:\n\t perplex = float(row[0])\n\t average += perplex\n\taverage = float(average/1)\n\tper_batch.append(average)\n#print(len(list_alpha))\n\nt = np.arange(1,101,1)\ncolor = ['red', 'blue', 'green', 'orange', 'black']\nname_method = ['add1', 'mult1', 'add2', 'mult2']\nfont = {#'family' : 'normal',\n #'weight' : 'bold',\n 'size' : 8}\nmatplotlib.rc('font', **font)\nfor j in range(0,len(list_alpha1)):\n fig = plt.figure()\n plt.xlabel('number of iteration training')\n plt.ylabel('Log Predict Probability')\n plt.title('Method: VB. Grolier dataset, c=%.1f, function: 1/t^3' %alpha[j])\n ax = plt.subplot(111)\n for i in range(0,len(list_alpha1[j])):\n ax.plot(t, list_alpha1[j][i][1], color=color[i], linewidth=1.0, label=name_method[i])\n ax.plot(t, list_alpha1[j][i][0], color=color[i], linewidth=1.0, linestyle='--')\n ax.plot(t, per_batch, color=color[4], linewidth=1.0, label='Original VB')\n #plt.axis([0, 200, -8.30, -7.90])\n box = ax.get_position()\n ax.set_position([box.x0, box.y0, box.width * 0.9, box.height])\n ax.legend(loc='center left', bbox_to_anchor=(1, 0.5))\n #plt.axis([0,200,-10,0])\n plt.show()\n\n\"\"\"list_alpha2 = list()\nnoise = ['add_ope', 'mult_ope']\nalpha = [1.0]\nfor name in copus:\n for value in alpha:\n\tnew_value = int(value*10)\n\tlist_method = list()\n\tfor method in noise:\n\t list_only = list()\n\t for boolean in only_doc:\n\t\tlist_per = list()\n\t\tfor index in num_train:\n\t\t for i in range(index-199,index+1):\n\t\t\taverage = 0.\n\t\t\tfor j in range(1,11):\n\t\t\t file_name = '%s_model/OPE%d/%s/alpha%d/%s200/perplexities_%d.csv'%(name, j, method, new_value, boolean, i)\n\t\t\t f = open(file_name, 'rb')\n\t\t\t reader = csv.reader(f)\n\t\t\t for row in reader:\n\t\t\t perplex = float(row[0])\n\t\t\t average += perplex\n\t\t\taverage = float(average/10)\n\t\t\tlist_per.append(average)\n\t\tlist_only.append(np.array(list_per))\n\t list_method.append(list_only)\n list_alpha2.append(list_method)\n\nt = np.arange(1,201,1)\ncolor = ['green', 'orange', 'black']\nname_method = ['add2', 'mult2']\nfont = {#'family' : 'normal',\n #'weight' : 'bold',\n 'size' : 8}\nmatplotlib.rc('font', **font)\nfor j in range(0,len(list_alpha2)):\n fig = plt.figure()\n plt.xlabel('number of iteration training')\n plt.ylabel('Log Predict Probability')\n plt.title('Method: OPE. AP dataset, c=%.1f, function: 1/t' %alpha[j])\n ax = plt.subplot(111)\n for i in range(0,len(list_alpha2[j])):\n ax.plot(t, list_alpha2[j][i][1], color=color[i], linewidth=1.0, label=name_method[i])\n ax.plot(t, list_alpha2[j][i][0], color=color[i], linewidth=1.0, linestyle='--')\n ax.plot(t, per_batch, color=color[2], linewidth=1.0, label='Original OPE')\n plt.axis([0, 200, -8.30, -7.90])\n box = ax.get_position()\n ax.set_position([box.x0, box.y0, box.width * 0.9, box.height])\n ax.legend(loc='center left', bbox_to_anchor=(1, 0.5))\n #plt.axis([0,200,-10,0])\n plt.show()\"\"\"\n"},{"alpha_fraction":0.4723404347896576,"alphanum_fraction":0.4959810972213745,"avg_line_length":42.597938537597656,"blob_id":"7e1287757533b37b92f10e900a8fd3468548492e","content_id":"0faa277e3e2ea54591ed97833ca509ca09ac64e1","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":4230,"license_type":"no_license","max_line_length":142,"num_lines":97,"path":"/datasets/noise_data.py","repo_name":"TruongKhang/topic_models","src_encoding":"UTF-8","text":"import numpy as np\nimport math\nimport random\n\nclass Noise_Data:\n def __init__(self, wordids, wordcts, iter_train, alpha, a, p, only_doc=True):\n self.wordids = wordids\n self.wordcts = wordcts\n self.iter_train = iter_train\n self.alpha = alpha # hyperparameter\n self.only_doc = only_doc\n self.a = a #number of sample which received value -1 in set {-1, 1}\n self.p = p\n\n def add_uniform(self):\n D = len(self.wordids)\n new_wordcts = list()\n for d in range(0,D):\n if self.only_doc:\n c = random.choice([-1,0,1])#np.random.random_integers(-1,1)\n N = len(self.wordids[d])\n new_wordct = np.zeros(N, dtype=np.float64)\n for n in range(0,N):\n if not self.only_doc:\n c = random.choice([-1,0,1])#np.random.random_integers(-1,1)\n new_wordct[n] = self.wordcts[d][n] + c*self.alpha/math.pow(self.iter_train,self.p)\n new_wordcts.append(new_wordct)\n return (self.wordids, new_wordcts)\n\n def mult_uniform(self):\n D = len(self.wordids)\n new_wordcts = list()\n for d in range(0,D):\n if self.only_doc:\n c = random.choice([-1,0,1])#np.random.random_integers(-1,1)\n N = len(self.wordids[d])\n new_wordct = np.zeros(N, dtype=np.float64)\n for n in range(0,N):\n if not self.only_doc:\n c = random.choice([-1,0,1])#np.random.random_integers(-1,1)\n new_wordct[n] = self.wordcts[d][n] * (1 + float(c*self.alpha/math.pow(self.iter_train,self.p)))\n new_wordcts.append(new_wordct)\n return (self.wordids, new_wordcts)\n\n def add_ope(self):\n D = len(self.wordids)\n new_wordcts = list()\n for d in range(0,D):\n N = len(self.wordids[d])\n new_wordct = np.zeros(N, dtype=np.float64)\n if self.only_doc:\n rand = random.choice([0,1])#np.random.random_integers(0,1)\n if rand == 0:\n self.a[d] = self.a[d] + 1\n #if d == 0:\n # print(self.a[d])\n for n in range(0,N):\n new_wordct[n] = self.wordcts[d][n] + self.alpha*(self.iter_train - 2*self.a[d])/math.pow(self.iter_train, self.p)\n else:\n for n in range(0,N):\n rand = random.choice([0,1])#np.random.random_integers(0,1)\n if rand == 0:\n self.a[d][n] = self.a[d][n] + 1\n new_wordct[n] = self.wordcts[d][n] + self.alpha*(self.iter_train - 2*self.a[d][n])/math.pow(self.iter_train, self.p)\n new_wordcts.append(new_wordct)\n return (self.wordids, new_wordcts, self.a)\n\n def mult_ope(self):\n D = len(self.wordids)\n new_wordcts = list()\n for d in range(0,D):\n N = len(self.wordids[d])\n new_wordct = np.zeros(N, dtype=np.float64)\n if self.only_doc:\n rand = random.choice([0,1])#np.random.random_integers(0,1)\n if rand == 0:\n self.a[d] = self.a[d] + 1\n for n in range(0,N):\n new_wordct[n] = self.wordcts[d][n] * (1 - self.alpha*(self.iter_train - 2*self.a[d])/math.pow(self.iter_train, self.p))\n else:\n for n in range(0,N):\n rand = random.choice([0,1])#np.random.random_integers(0,1)\n if rand == 0:\n self.a[d][n] = self.a[d][n] + 1\n new_wordct[n] = self.wordcts[d][n] * (1 - self.alpha*(self.iter_train - 2*self.a[d][n])/math.pow(self.iter_train, self.p))\n new_wordcts.append(new_wordct)\n return (self.wordids, new_wordcts, self.a)\n\nif __name__ == '__main__':\n for i in range(0,1):\n print('setting %d: '%i)\n a = np.zeros(3, dtype=np.int32)\n for t in range(1,50):\n wordids = [[1, 2, 3], [4, 6, 7], [1, 4, 7]]\n wordcts = [[1., 1., 2.], [1., 5., 2.], [1., 4., 1.]]\n noise = Noise_Data(wordids,wordcts,t,1,a,only_doc=True)\n (wordids,wordcts,a) = noise.add_ope()\n\n"},{"alpha_fraction":0.4721164405345917,"alphanum_fraction":0.48028498888015747,"avg_line_length":35.022125244140625,"blob_id":"ca01e1a98457f47052eddd9c260db763ba16b922","content_id":"8e0408ba2653298d92b61c10405df1030db12681","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":16282,"license_type":"no_license","max_line_length":120,"num_lines":452,"path":"/datasets/base.py","repo_name":"TruongKhang/topic_models","src_encoding":"UTF-8","text":"import os, os.path\nimport sys\nimport shutil\nfrom os.path import isdir, isfile, join\nfrom preprocessing import preprocessing\nimport numpy as np\nfrom time import time\n\n# Name of current path directory which contains this file\ndir_path = os.path.dirname(os.path.realpath(__file__))\n\n# check format of input file(text formatted or raw text)\ndef check_format(line, c):\n result = True\n l = len(line)\n for i in range(0,l):\n if line[i].isalpha():\n result = False\n break\n elif not line[i].isalnum() and line[i] != ' ' and line[i] != c:\n result = False\n break\n return result\n\nclass Dataset:\n def __init__(self,path):\n self.vocab_path = None\n self.is_raw_text = False\n if isfile(path):\n print(\"Path %s is a file\" %path)\n self.path_isfile = path\n self.path_isdir = None\n name_file = self.path_isfile.split(\"\\\\\")\n name_file = name_file[-1].split(\"/\")\n main_name = name_file[-1]\n self.main_name_file = main_name[:-4]\n elif isdir(path):\n self.path_isdir = path\n self.path_isfile = None\n print(\"Path %s is a directory\" %path)\n else:\n self.path_isdir = None\n self.path_isfile = None\n print(\"Unknown path %s!\" %path)\n exit()\n\n \"\"\"\n read file input, check format is raw input or term frequency or term sequence\n \"\"\"\n def load_dataset(self, term_seq=False, term_freq=True):\n if self.path_isfile:\n f = open(self.path_isfile)\n line = f.readline().strip()\n while len(line) == 0:\n line = f.readline().strip()\n if line == \"\":\n self.is_raw_text = True\n print(\"Pre-processing:\")\n p = preprocessing.PreProcessing()\n p.process(self.path_isfile)\n p.extract_vocab()\n p.format_freq()\n p.format_seq()\n self.vocab_path = p.dir_path_data + \"/vocab.txt\"\n if term_freq:\n data_path = p.dir_path_data + \"/term_frequency.txt\"\n term_seq = False\n else:\n data_path = p.dir_path_data + \"/term_sequence.txt\"\n term_seq = True\n elif check_format(line, ' '):\n data_path = self.path_isfile\n \"\"\"if 'wikipedia' in self.path_isfile:\n data_path = self.path_isfile\n else:\n dir_folder = dir_path + \"/data/\" + self.main_name_file\n # Create model folder if it doesn't exist\n if os.path.exists(dir_folder):\n shutil.rmtree(dir_folder)\n os.makedirs(dir_folder)\n data_path = dir_folder + \"/term_sequence.txt\"\n print(\"Copy file %s => %s\" %(self.path_isfile,data_path))\n shutil.copyfile(self.path_isfile,data_path)\"\"\"\n term_freq = False\n term_seq = True\n elif check_format(line, ':'):\n data_path = self.path_isfile\n \"\"\"if 'wikipedia' in self.path_isfile:\n data_path = self.path_isfile\n else:\n dir_folder = dir_path + \"/data/\" + self.main_name_file\n # Create model folder if it doesn't exist\n if os.path.exists(dir_folder):\n shutil.rmtree(dir_folder)\n os.makedirs(dir_folder)\n data_path = dir_folder + \"/term_frequency.txt\"\n print(\"Copy file %s => %s\" % (self.path_isfile, data_path))\n shutil.copyfile(self.path_isfile, data_path)\"\"\"\n term_seq = False\n term_freq = True\n else:\n print(\"File %s is not true format!\" %self.path_isfile)\n sys.exit()\n f.close()\n bunch = self.Bunch(data_path,term_seq,term_freq)\n return bunch\n\n \"\"\"\n inner class with methods load data from formatted file\n \"\"\"\n class Bunch:\n def __init__(self, data_path, term_seq, term_freq):\n self.data_path = data_path\n self.term_seq = term_seq\n self.term_freq = term_freq\n self.copus = []\n # load number of documents\n f = open(data_path,'r')\n lines = f.readlines()\n self.num_doc = len(lines)\n del lines\n f.close()\n\n \"\"\"\n shuffle input and write into file file_shuffled.txt, return path of this file\n \"\"\"\n def shuffle(self):\n f = open(self.data_path)\n lines = f.readlines()\n self.num_doc = len(lines)\n np.random.shuffle(lines)\n f.close()\n if self.term_freq:\n d = self.data_path[:-19]\n elif self.term_seq:\n d = self.data_path[:-18]\n fout = open(join(d,\"file_shuffled.txt\"), \"w\")\n for line in lines:\n fout.write(\"%s\" %line)\n fout.close()\n del lines\n return join(d,\"file_shuffled.txt\")\n\n def load_batch(self, fp):\n docs = fp.readlines();\n D = len(docs)\n wordids = list()\n wordcts = list()\n for d in range(0,D):\n list_word = docs[d].strip().split()\n N = int(list_word[0])\n if N+1 != len(list_word):\n print(\"Line %d in file %s is error!\" % (d + 1, self.data_path))\n exit()\n wordid = np.zeros(N, dtype=np.int32)\n wordct = np.zeros(N, dtype=np.float64)\n for n in range(1, N+1):\n id_ct = list_word[n].split(':')\n wordid[n-1] = int(id_ct[0])\n wordct[n-1] = float(id_ct[1])\n wordids.append(wordid)\n wordcts.append(wordct)\n return (wordids,wordcts)\n\n \"\"\"\n read mini-batch data and store with format term sequence\n fp is file pointer after shuffled\n \"\"\"\n def load_minibatch_term_seq(self, fp, size_batch):\n doc_terms = []\n doc_lens = []\n for i in range(0, size_batch):\n doc = fp.readline()\n #check end file\n if len(doc) < 5:\n break\n list_word = doc.strip().split()\n N = int(list_word[0])\n if N + 1 != len(list_word):\n print(\"Line %d in file %s is error!\" % (i + 1, self.data_path))\n sys.exit()\n if self.term_freq:\n tokens = list()\n for j in range(1, N + 1):\n tf = list_word[j].split(\":\")\n for k in range(0,int(tf[1])):\n tokens.append(int(tf[0]))\n doc_terms.append(np.array(tokens))\n doc_lens.append(len(tokens))\n elif self.term_seq:\n doc_t = np.zeros(N, dtype=np.int32)\n for j in range(1, N + 1):\n doc_t[j - 1] = int(list_word[j])\n doc_l = N\n doc_terms.append(doc_t)\n doc_lens.append(doc_l)\n del list_word\n return (doc_terms,doc_lens)\n\n \"\"\"\n read mini-batch data and store with format term frequency\n fp is file pointer after shuffled\n \"\"\"\n def load_minibatch_term_freq(self,fp,size_batch):\n doc_terms = []\n doc_freqs = []\n for i in range(0,size_batch):\n doc = fp.readline()\n if len(doc) < 5:\n break\n list_word = doc.strip().split()\n N = int(list_word[0])\n if N + 1 != len(list_word):\n print(\"Line %d in file %s is error!\" % (i + 1, self.data_path))\n sys.exit()\n if self.term_freq:\n doc_t = np.zeros(N,dtype=np.int32)\n doc_f = np.zeros(N,dtype=np.int32)\n for j in range(1,N+1):\n tf = list_word[j].split(\":\")\n doc_t[j-1] = int(tf[0])\n doc_f[j-1] = int(tf[1])\n doc_terms.append(doc_t)\n doc_freqs.append(doc_f)\n elif self.term_seq:\n terms = []\n freqs = []\n k = 0\n for j in range(1,N+1):\n if int(list_word[j]) not in terms:\n terms.append(int(list_word[j]))\n freqs.append(1)\n else:\n index = terms.index(int(list_word[j]))\n freqs[index] += 1\n doc_terms.append(np.array(terms))\n doc_freqs.append(np.array(freqs))\n del list_word\n return (doc_terms,doc_freqs)\n\n\"\"\"------------------------------------------------------------------------------------------------------------------\"\"\"\n\ndef read_setting(file_name):\n if isfile(file_name):\n f = open(file_name, 'r')\n settings = f.readlines()\n f.close()\n sets = list()\n vals = list()\n for i in range(len(settings)):\n # print'%s\\n'%(settings[i])\n line = settings[i].strip()\n if len(line) != 0:\n if line[0] == '#':\n continue\n set_val = settings[i].strip().split(':')\n sets.append(set_val[0])\n vals.append(float(set_val[1]))\n ddict = dict(zip(sets, vals))\n #ddict['num_terms'] = int(ddict['num_terms'])\n ddict['num_topics'] = int(ddict['num_topics'])\n ddict['iter_train'] = int(ddict['iter_train'])\n ddict['iter_infer'] = int(ddict['iter_infer'])\n ddict['batch_size'] = int(ddict['batch_size'])\n ddict['num_crawling'] = int(ddict['num_crawling'])\n #ddict['p'] = int(ddict['p'])\n return (ddict)\n else:\n print(\"Can't find file!\")\n sys.exit()\n\n\"\"\"\n Read all documents in the file and stores terms and counts in lists.\n\"\"\"\ndef read_data(filename):\n wordids = list()\n wordcts = list()\n fp = open(filename, 'r')\n while True:\n line = fp.readline()\n # check end of file\n if len(line) < 1:\n break\n terms = line.split()\n doc_length = int(terms[0])\n ids = np.zeros(doc_length, dtype = np.int32)\n cts = np.zeros(doc_length, dtype = np.int32)\n for j in range(1, doc_length + 1):\n term_count = terms[j].split(':')\n ids[j - 1] = int(term_count[0])\n cts[j - 1] = int(term_count[1])\n wordids.append(ids)\n wordcts.append(cts)\n fp.close()\n return(wordids, wordcts)\n\n\"\"\"\n Read data for computing perplexities.\n\"\"\"\ndef read_data_for_perpl(test_data_folder):\n onlyfiles = [f for f in os.listdir(test_data_folder) if isfile(os.path.join(test_data_folder, f))]\n k_fold_cross = int(len(onlyfiles) / 2)\n list_data_test = list()\n for i in range(0,k_fold_cross):\n filename_part1 = '%s/data_test_%d_part_1.txt'%(test_data_folder, i+1)\n filename_part2 = '%s/data_test_%d_part_2.txt'%(test_data_folder, i+1)\n (wordids_1, wordcts_1) = read_data(filename_part1)\n (wordids_2, wordcts_2) = read_data(filename_part2)\n data_test = list()\n data_test.append(wordids_1)\n data_test.append(wordcts_1)\n data_test.append(wordids_2)\n data_test.append(wordcts_2)\n list_data_test.append(data_test)\n return(list_data_test)\n\ndef read_beta(filename):\n if isfile(filename):\n f = open(filename)\n lines = f.readlines()\n words = lines[0].strip().split()\n K = len(lines)\n W = len(words)\n beta = np.zeros((K,W))\n for i in range(0,K):\n words = lines[i].strip().split()\n if len(words) != W:\n print('File %s is error' %filename)\n exit()\n for j in range(0,W):\n beta[i][j] = float(words[j])\n return beta\n else:\n print('Unknown file %s' %filename)\n exit()\n\n\"\"\"\n Compute document sparsity.\n\"\"\"\ndef compute_sparsity(doc_tp, batch_size, num_topics, _type):\n sparsity = np.zeros(batch_size, dtype = np.float)\n if _type == 'z':\n for d in range(batch_size):\n N_z = np.zeros(num_topics, dtype = np.int)\n N = len(doc_tp[d])\n for i in range(N):\n N_z[doc_tp[d][i]] += 1.\n sparsity[d] = len(np.where(N_z != 0)[0])\n else:\n for d in range(batch_size):\n sparsity[d] = len(np.where(doc_tp[d] > 1e-10)[0])\n sparsity /= num_topics\n return(np.mean(sparsity))\n\n\"\"\"\n Create list of top words of topics.\n\"\"\"\ndef list_top(beta, tops):\n min_float = -sys.float_info.max\n num_tops = beta.shape[0]\n list_tops = list()\n for k in range(num_tops):\n top = list()\n arr = np.array(beta[k,:], copy = True)\n for t in range(tops):\n index = arr.argmax()\n top.append(index)\n arr[index] = min_float\n list_tops.append(top)\n return(list_tops)\n\n\n\"\"\"------------------------------------------------------------------------------------------------------------------\"\"\"\ndef write_setting(ddict,file_name):\n keys = list(ddict.keys())\n vals = list(ddict.values())\n f = open(file_name, 'w')\n for i in range(len(keys)):\n f.write('%s: %f\\n' % (keys[i], vals[i]))\n f.close()\n\ndef write_topics(beta, file_name):\n num_terms = beta.shape[1]\n num_topics = beta.shape[0]\n f = open(file_name, 'w')\n for k in range(num_topics):\n for i in range(num_terms - 1):\n f.write('%.10f ' % (beta[k][i]))\n f.write('%.10f\\n' % (beta[k][num_terms - 1]))\n f.close()\n\ndef write_topic_mixtures(theta, file_name):\n batch_size = theta.shape[0]\n num_topics = theta.shape[1]\n f = open(file_name, 'a')\n for d in range(batch_size):\n for k in range(num_topics - 1):\n f.write('%.5f ' % (theta[d][k]))\n f.write('%.5f\\n' % (theta[d][num_topics - 1]))\n f.close()\n\ndef write_perplexities(LD2, file_name):\n f = open(file_name, 'a')\n f.writelines('%f,'%(LD2))\n f.close()\n\ndef write_time(i, j, time_e, time_m, file_name):\n f = open(file_name, 'a')\n f.write('tloop_%d_iloop_%d, %f, %f, %f,\\n' % (i, j, time_e, time_m, time_e + time_m))\n f.close()\n\ndef write_loop(i, j, file_name):\n f = open(file_name, 'w')\n f.write('%d, %d' % (i, j))\n f.close()\n\ndef write_file(i, j, beta, time_e, time_m, theta, sparsity, LD2, list_tops, tops, model_folder):\n beta_file_name = '%s/beta_%d_%d.dat'%(model_folder, i, j)\n theta_file_name = '%s/theta_%d.dat'%(model_folder, i)\n per_file_name = '%s/perplexities_%d.csv'%(model_folder, i)\n #top_file_name = '%s/top%d_%d_%d.dat'%(model_folder, tops, i, j)\n #spar_file_name = '%s/sparsity_%d.csv'%(model_folder, i)\n time_file_name = '%s/time_%d.csv'%(model_folder, i)\n loop_file_name = '%s/loops.csv'%(model_folder)\n\n # write beta\n #if i % 10 == 1:\n # write_topics(beta, beta_file_name)\n # write theta\n #write_topic_mixtures(theta, theta_file_name)\n\n # write perplexities\n write_perplexities(LD2, per_file_name)\n # write list top\n ##write_topic_top(list_tops, top_file_name)\n # write sparsity\n ##write_sparsity(sparsity, spar_file_name)\n # write time\n write_time(i, j, time_e, time_m, time_file_name)\n # write loop\n write_loop(i, j, loop_file_name)\n\nif __name__ == '__main__':\n t0 = time()\n data = Dataset(\"D:\\\\UCR_TS_Archive_2015\\\\ap/ap.txt\").load_dataset()\n (docs,freqs) = data.load_batch()\n print(len(docs))\n print(docs[0])\n (docs,lengs) = data.load_minibatch(2)\n print(docs)\n print(lengs)\n print(\"Done in %.3f\" %(time() - t0))\n"},{"alpha_fraction":0.5423541069030762,"alphanum_fraction":0.5463746190071106,"avg_line_length":34.70792007446289,"blob_id":"97a9c32c646dab1ae89a9660a9ce34aa14826a53","content_id":"c98ccaa4e5737c6666e1f6aea27b6b113408cd0e","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":7213,"license_type":"no_license","max_line_length":119,"num_lines":202,"path":"/datasets/crawl_wiki_ariticles.py","repo_name":"TruongKhang/topic_models","src_encoding":"UTF-8","text":"\"\"\"Reference: M.Hoffman - onlineldavb\"\"\"\n\nimport sys, urllib2, re, string, time, threading\nimport os\n\n# Name of current path directory which contains this file\ndir_path = os.path.dirname(os.path.realpath(__file__))\n\ndef get_random_wikipedia_article():\n \"\"\"\n Downloads a randomly selected Wikipedia article (via\n http://en.wikipedia.org/wiki/Special:Random) and strips out (most\n of) the formatting, links, etc.\n\n This function is a bit simpler and less robust than the code that\n was used for the experiments in \"Online VB for LDA.\"\n \"\"\"\n failed = True\n while failed:\n articletitle = None\n failed = False\n try:\n req = urllib2.Request('http://en.wikipedia.org/wiki/Special:Random',\n None, { 'User-Agent' : 'x'})\n f = urllib2.urlopen(req)\n while not articletitle:\n line = f.readline()\n result = re.search(r'title=\"Edit this page\" href=\"/w/index.php\\?title=(.*)\\&action=edit\"\\/>', line)\n if (result):\n articletitle = result.group(1)\n break\n elif (len(line) < 1):\n sys.exit(1)\n\n req = urllib2.Request('http://en.wikipedia.org/w/index.php?title=Special:Export/%s&action=submit' \\\n % (articletitle),\n None, { 'User-Agent' : 'x'})\n f = urllib2.urlopen(req)\n all = f.read()\n except (urllib2.HTTPError, urllib2.URLError):\n print('oops. there was a failure downloading %s. retrying...' % articletitle)\n failed = True\n continue\n print('downloaded %s. parsing...' % articletitle)\n\n try:\n all = re.search(r'(.*)\\n\")\n fdata.write(\" %s <\\\\TITLE>\\n\" %articlenames[j])\n fdata.write(\"<TEXT>\\n\")\n fdata.write(\"%s\\n\" %docset[j])\n fdata.write(\"<\\DOC>\\n\")\n fdata.write(\"<\\TEXT>\\n\")\n parse_doc_list(fformat,docset,d_vocab)\n\tif i < num_crawling-1:\n\t fformat.write('\\n')\n fdata.close()\n fformat.close()\n\nif __name__ == '__main__':\n t0 = time.time()\n\n (articles, articlenames) = get_random_wikipedia_articles(4)\n for i in range(0, len(articles)):\n print(articlenames[i])\n\n t1 = time.time()\n print('took %f' % (t1 - t0))\n"},{"alpha_fraction":0.5380309224128723,"alphanum_fraction":0.5591043829917908,"avg_line_length":29.676767349243164,"blob_id":"b4150171ac2937919f7579a3e937a4c998502c45","content_id":"37e91a59a128b94ba707394d771ca3dc5d4383a8","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":3037,"license_type":"no_license","max_line_length":84,"num_lines":99,"path":"/lda/Batch_VB/Batch_VB.py","repo_name":"TruongKhang/topic_models","src_encoding":"UTF-8","text":"import re, time\nimport sys\nfrom datetime import datetime\n\nimport numpy as n\nfrom scipy.special import gammaln, psi\n\nt = datetime.now()\ntime_cur = t.hour*3600 + t.minute*60 + t.second\nn.random.seed(time_cur+100000000)\n\"\"\"\nCreated : 03 /08 /2016\n@author : Ha Nhat Cuong\n\"\"\"\n\ndef dirichlet_expectation(alpha):\n if len(alpha.shape) == 1:\n return psi(alpha) - psi(n.sum(alpha))\n return psi(alpha) - psi(n.sum(alpha, 1))[:, n.newaxis]\n\n\nclass BatchVB:\n\n def __init__(self, num_terms, num_topics, alpha, eta,\n iter_infer, meanchangethresh, beta=None):\n #self._D = num_docs\n\n self._K = num_topics\n self._W = num_terms\n\n self._iter_infer = iter_infer\n self._meanchangethresh = meanchangethresh\n\n self._alpha = alpha\n self._eta = eta\n\n if beta is not None:\n self._lambda = beta\n else:\n self._lambda = 1*n.random.gamma(100.0, 1.0/100.0, (self._K, self._W))\n self._Elogbeta = dirichlet_expectation(self._lambda)\n self._expElogbeta = n.exp(self._Elogbeta)\n\n def do_e_step(self, wordids, wordcts):\n batchD = len(wordids)\n\n gamma = n.random.gamma(100.0, 1.0/100.0, (batchD, self._K))\n Elogtheta = dirichlet_expectation(gamma)\n expElogtheta = n.exp(Elogtheta)\n\n sstats = n.zeros(self._lambda.shape)\n\n for d in range(0, batchD) :\n ids = wordids[d]\n cts = wordcts[d] # 1 * size(ids)\n\n gammad = gamma[d, :] # gammad [1* K]\n Elogthetad = Elogtheta[d, :]\n expElogthetad = expElogtheta[d, :] #1*K\n expElogbetad = self._expElogbeta[:, ids] # K * size(ids)\n\n phinorm = n.dot(expElogthetad, expElogbetad) + 1e-100 # 1 * size(ids)\n\n for it in range(0, self._iter_infer):\n lastgamma = gammad\n\n gammad = self._alpha + expElogthetad*\\\n n.dot(cts/phinorm, expElogbetad.T)\n\n Elogthetad = dirichlet_expectation(gammad)\n expElogthetad = n.exp(Elogthetad)\n phinorm = n.dot(expElogthetad, expElogbetad) + 1e-100\n\n meanchange = n.mean(abs(lastgamma - gammad))\n if meanchange < self._meanchangethresh :\n break\n\n gamma[d, :] = gammad\n sstats[:, ids] += n.outer(expElogthetad.T, cts/phinorm) # K * size(ids)\n\n sstats = sstats * self._expElogbeta # K * W\n return gamma, sstats # batchD * K , K * W\n\n def update_lambda(self, sstats):\n\n self._lambda = self._eta + sstats # num_topics * W\n self._Elogbeta = dirichlet_expectation(self._lambda)\n self._expElogbeta = n.exp(self._Elogbeta)\n\n\n def static_online(self, wordids, wordcts):\n # E step\n start = time.time()\n (gamma, sstats) = self.do_e_step(wordids, wordcts)\n end1 = time.time()\n # M step\n self.update_lambda(sstats)\n end2 = time.time()\n return (end1 - start, end2 - start, gamma)\n"}],"string":"[\n {\n \"alpha_fraction\": 0.6532507538795471,\n \"alphanum_fraction\": 0.6656346917152405,\n \"avg_line_length\": 23.846153259277344,\n \"blob_id\": \"99b5494de905cdebe776ee9a4a85048a31a1b015\",\n \"content_id\": \"71d7a738ef132f37d0ec62b280565aaf4f355167\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 323,\n \"license_type\": \"no_license\",\n \"max_line_length\": 71,\n \"num_lines\": 13,\n \"path\": \"/ap/read_line_specific.py\",\n \"repo_name\": \"TruongKhang/topic_models\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from time import time\\ndef readline_number_x(file,x):\\n for index,line in enumerate(iter(file)):\\n if index+1 == x: return line\\n\\n return None\\n\\nf = open('grolier_train.txt')\\nx = 1\\nt0 = time()\\nline_number_x = readline_number_x(f,x) #This will return the third line\\nprint \\\"Time: %f\\\" %(time()-t0)\\nprint line_number_x\\n\"\n },\n {\n \"alpha_fraction\": 0.5002655386924744,\n \"alphanum_fraction\": 0.5087625980377197,\n \"avg_line_length\": 36.90604019165039,\n \"blob_id\": \"3fbc3be3b46f12507dae158c3db1b72b069a20e1\",\n \"content_id\": \"b8dbc9dd62b23582084773c480f109b150558ef4\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 5649,\n \"license_type\": \"no_license\",\n \"max_line_length\": 184,\n \"num_lines\": 149,\n \"path\": \"/run_batch.py\",\n \"repo_name\": \"TruongKhang/topic_models\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: utf-8 -*-\\n\\\"\\\"\\\"\\nCreated on Mon Oct 26 15:52:29 2015\\n\\n@author: dhbk\\n\\\"\\\"\\\"\\nimport sys, os, shutil\\nimport numpy as np\\nmypath = ['./lda/Batch_VB', './lda/OPE', './lda/Online-VB']\\n\\n# Name of current path directory which contains this file\\ndir_path = os.path.dirname(os.path.realpath(__file__))\\n\\nfor temp in mypath:\\n sys.path.insert(0, temp)\\nfrom datasets import base\\n#import run_Batch_VB\\n#import run_OPE\\n\\ndef main():\\n # Check input\\n if len(sys.argv)!=10 and len(sys.argv)!=9:\\n print(\\\"usage: python run_batch.py [method name] [data file] [setting file] [model folder] [test_folder] [method noise] [alpha] [only_doc] [[vocab:vocabulary file (optional)]]\\\")\\n print(\\\"or: python run_batch.py [method name] [data file] [setting file] [model folder] [test_folder] [a] [method noise] [only_doc] [[beta:beta file (optional)]]\\\")\\n exit()\\n else:\\n # Get environment variables\\n method_name = sys.argv[1]\\n data_file = sys.argv[2]\\n setting_file = sys.argv[3]\\n model_folder = sys.argv[4]\\n test_folder = sys.argv[5]\\n method_noise = sys.argv[6]\\n alpha = sys.argv[7]\\n only_doc = sys.argv[8]\\n beta_file = ''\\n vocab_file = ''\\n if len(sys.argv) == 10:\\n name = sys.argv[9].split('[')\\n if name[0] == 'vocab':\\n vocab_file = name[1]\\n elif name[0] == 'beta':\\n beta_file = name[1]\\n\\n tops = 10 # int(sys.argv[5])\\n # Check format data: raw text or not\\n data = base.Dataset(data_file)\\n formatted_data = data.load_dataset()\\n if len(sys.argv) == 9:\\n if not data.is_raw_text:\\n print(\\\"File %s is formatted file. Please add argument [vocabulary file] into command\\\" % data_file)\\n exit()\\n else:\\n vocab_file = data.vocab_path\\n elif len(sys.argv) == 10:\\n if data.is_raw_text:\\n if beta_file:\\n print(\\\"Input is raw text. Library will preprocessing it.\\\\\\n Vocaburaly can change. So, beta file can't be used in this case. Please remove this argument\\\")\\n exit()\\n vocab_file = data.vocab_path\\n\\n # Read settings\\n print('reading setting ...')\\n settings = base.read_setting(setting_file)\\n num_docs = formatted_data.num_doc\\n if beta_file:\\n file = beta_file\\n else:\\n file = vocab_file\\n if os.path.isfile(file):\\n f = open(file, 'r')\\n lines = f.readlines()\\n if vocab_file:\\n num_terms = len(lines)\\n if beta_file:\\n num_terms = len(lines[0].strip().split())\\n shutil.copyfile(beta_file, dir_path+'/beta_copy.txt')\\n beta_file = dir_path+'/beta_copy.txt'\\n del lines\\n f.close()\\n settings['num_docs'] = num_docs\\n settings['num_terms'] = num_terms\\n else:\\n print(\\\"Can't find vocabulary file!\\\")\\n exit()\\n\\n # Create model folder if it doesn't exist\\n if os.path.exists(model_folder):\\n shutil.rmtree(model_folder)\\n os.makedirs(model_folder)\\n a = None\\n if beta_file:\\n namebeta = name[1]\\n lname = namebeta.split('/')\\n b = lname[len(lname)-2]\\n if 'True' in b:\\n value = b[4:]\\n elif 'False' in b:\\n value = b[5:]\\n elif 'batchvb' in b:\\n value = b[7:]\\n settings['iter_train'] = int(value)\\n if method_noise == 'add_ope' or method_noise == 'mult_ope':\\n direct = namebeta[:-(len('beta_final.dat'))]\\n filea = direct + '/a_' + value + '.txt'\\n f = open(filea)\\n\\n print('Read a...')\\n if only_doc == 'True':\\n lines = f.readlines()\\n a = np.zeros(len(lines), dtype=np.int32)\\n for d in range(len(lines)):\\n a[d] = int(lines[d].strip())\\n else:\\n lines = f.readlines()\\n a = list()\\n for d in range(len(lines)):\\n words = lines[d].strip().split()\\n w = np.zeros(len(words), dtype=np.int32)\\n for n in range(len(words)):\\n w[n] = int(words[n])\\n a.append(w)\\n f.close()\\n # Read data for computing perplexities\\n print('read data for computing perplexities ...')\\n test_data = base.read_data_for_perpl(test_folder)\\n # Check method and run algorithm\\n alpha = float(alpha)\\n if only_doc == 'True':\\n only_doc = True\\n else:\\n only_doc = False\\n\\n if method_name == 'batch-vb':\\n import run_Batch_VB\\n runbatchvb = run_Batch_VB.runBatchVB(formatted_data, settings, model_folder, tops, test_data, beta_file)\\n runbatchvb.run(method_noise,alpha,only_doc,a)\\n elif method_name == 'batch-ope':\\n import run_OPE\\n runbatchope = run_OPE.runOPE(formatted_data, settings, model_folder, tops, test_data, beta_file)\\n runbatchope.run(method_noise, alpha, only_doc, a)\\n elif method_name == 'online-vb':\\n import run_VB\\n runbatchvb = run_VB.runOnlineVB(formatted_data, settings, model_folder, tops, test_data, beta_file)\\n runbatchvb.run(method_noise,alpha,only_doc,a)\\n\\nif __name__ == '__main__':\\n main()\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.45909690856933594,\n \"alphanum_fraction\": 0.4643869400024414,\n \"avg_line_length\": 34.2933349609375,\n \"blob_id\": \"7cf6a5f1cf23ce76398b34373a52de2f9aa67a99\",\n \"content_id\": \"17d3281195ef03b4e4eb1f3604f7d48cd16140fb\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 5293,\n \"license_type\": \"no_license\",\n \"max_line_length\": 82,\n \"num_lines\": 150,\n \"path\": \"/preprocessing/preprocessing.py\",\n \"repo_name\": \"TruongKhang/topic_models\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import os, os.path\\nfrom os.path import isfile, join, isdir\\nimport numpy as np\\nfrom nltk.tokenize import TreebankWordTokenizer\\nfrom nltk.tokenize import RegexpTokenizer\\nfrom nltk.stem.porter import PorterStemmer\\n\\ndir_path = os.path.dirname(os.path.realpath(__file__))\\ntokenizer = RegexpTokenizer(r'\\\\w+')\\np_stemmer = PorterStemmer()\\n\\nclass PreProcessing:\\n def __init__(self, stemmed=False, remove_rare_word=True):\\n self.list_doc = list()\\n self.vocab = list()\\n self.list_doc_freq = list()\\n self.stemmed = stemmed\\n self.remove_rare_word = remove_rare_word\\n self.id_doc = 0\\n self.df = list()\\n\\n def pro_per_doc(self, doc, stop_list):\\n words = tokenizer.tokenize(doc.lower())\\n list_word = list()\\n for word in words:\\n if word not in stop_list:\\n if word.isalpha() and len(word) > 2:\\n if self.stemmed:\\n word = p_stemmer.stem(word)\\n if word in self.vocab:\\n index = self.vocab.index(word)\\n if self.id_doc not in self.df[index]:\\n self.df[index].append(self.id_doc)\\n #list_word.append(word)\\n else:\\n self.vocab.append(word)\\n self.df.append([self.id_doc])\\n list_word.append(word)\\n self.id_doc += 1\\n return list_word\\n\\n def filter(self):\\n if self.vocab:\\n V = len(self.vocab)\\n remove_list = []\\n i = 0\\n while i < V:\\n #print(V)\\n freq = len(self.df[i])\\n #print(freq)\\n if freq <= 5 or freq > int(0.5*self.id_doc):\\n #remove_list.append(i)\\n docs = self.df[i]\\n word = self.vocab[i]\\n for j in docs:\\n while word in self.list_doc[j]:\\n self.list_doc[j].remove(word)\\n del self.vocab[i]\\n del self.df[i]\\n V = len(self.vocab)\\n i = i - 1\\n i += 1\\n else:\\n print(\\\"Vocabulary is empty! Please run process first!\\\")\\n\\n def process(self, path):\\n name_file = path.split(\\\"\\\\\\\\\\\")\\n name_file = name_file[-1].split(\\\"/\\\")\\n name = name_file[-1].split(\\\".\\\")\\n self.filename = name[0]\\n #print(self.filename)\\n fin = open(dir_path+\\\"/stop_word_list.txt\\\")\\n stop_list = list()\\n line = fin.readline()\\n while line:\\n line = line.strip()\\n stop_list.append(line)\\n line = fin.readline()\\n fin.close()\\n stop_list = stop_list + ['_',]\\n print(\\\"Waiting...\\\")\\n if isfile(path):\\n fread = open(path)\\n line = fread.readline()\\n num = 1\\n while line:\\n line = line.strip()\\n if line == \\\"<TEXT>\\\":\\n doc = fread.readline().strip()\\n #print(num)\\n list_word = self.pro_per_doc(doc,stop_list)\\n self.list_doc.append(list_word)\\n num += 1\\n line = fread.readline()\\n if self.remove_rare_word:\\n self.filter()\\n\\n numDocs = len(self.list_doc)\\n for d in range(0,numDocs):\\n list_word = []\\n numWords = len(self.list_doc[d])\\n for w in range(0,numWords):\\n word = self.list_doc[d][w]\\n self.list_doc[d][w] = self.vocab.index(word)\\n inlist = False\\n for elem in list_word:\\n if self.list_doc[d][w] == elem[0]:\\n elem[1] += 1\\n inlist = True\\n break\\n if not inlist:\\n list_word.append([self.list_doc[d][w],1])\\n self.list_doc_freq.append(list_word)\\n\\n def extract_vocab(self):\\n if self.vocab:\\n self.dir_path_data = dir_path[:-13] + \\\"datasets/data/\\\" + self.filename\\n if not os.path.exists(self.dir_path_data):\\n os.makedirs(self.dir_path_data)\\n fout = open(join(self.dir_path_data,\\\"vocab.txt\\\"),\\\"w\\\")\\n for word in self.vocab:\\n fout.write(\\\"%s\\\\n\\\" %word)\\n fout.close()\\n\\n def format_seq(self):\\n if self.list_doc:\\n fout = open(join(self.dir_path_data,\\\"term_sequence.txt\\\"), \\\"w\\\")\\n for doc in self.list_doc:\\n fout.write(\\\"%d \\\" %len(doc))\\n for word in doc:\\n fout.write(\\\"%d \\\" %word)\\n fout.write(\\\"\\\\n\\\")\\n fout.close()\\n\\n def format_freq(self):\\n if self.list_doc:\\n fout = open(join(self.dir_path_data,\\\"term_frequency.txt\\\"), \\\"w\\\")\\n for doc in self.list_doc_freq:\\n fout.write(\\\"%d \\\" %len(doc))\\n for elem in doc:\\n fout.write(\\\"%d:%d \\\" %(elem[0],elem[1]))\\n fout.write(\\\"\\\\n\\\")\\n fout.close()\\n\\nif __name__ == '__main__':\\n p = PreProcessing()\\n p.process(\\\"D:\\\\\\\\UCR_TS_Archive_2015\\\\\\\\ap/ap.txt\\\")\\n p.extract_vocab()\\n p.format_freq()\\n p.format_seq()\"\n },\n {\n \"alpha_fraction\": 0.5302867293357849,\n \"alphanum_fraction\": 0.5345979928970337,\n \"avg_line_length\": 38.99137878417969,\n \"blob_id\": \"9e19973236fdadce9914de69d2ae441dd8e15ad4\",\n \"content_id\": \"17d89ecc721c9af1a5647fc6d1a32b39ef7a8201\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 4639,\n \"license_type\": \"no_license\",\n \"max_line_length\": 116,\n \"num_lines\": 116,\n \"path\": \"/lda/Batch_VB/run_Batch_VB.py\",\n \"repo_name\": \"TruongKhang/topic_models\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#!/usr/bin/python\\n# -*- coding: utf-8 -*-\\n\\nimport sys, os\\nimport Batch_VB\\nimport numpy as np\\n\\nfrom datasets import base, noise_data\\nfrom evaluation import perplexity\\n\\nclass runBatchVB:\\n\\n def __init__(self, formatted_data, settings, model_folder, tops, test_data, beta_file=None):\\n self.formatted_data = formatted_data\\n self.settings = settings\\n self.model_folder = model_folder\\n self.beta_file = beta_file\\n self.test_data = test_data\\n self.tops = tops\\n\\n def run(self,method,alpha,only_doc=True, a=None):\\n # Initialize the algorithm\\n if self.beta_file:\\n print('Load beta to continue learn...')\\n beta = base.read_beta(self.beta_file)\\n os.remove(self.beta_file)\\n\\t i = self.settings['iter_train']\\n\\t self.settings['iter_train'] += 50\\n else:\\n print('initialize the algorithm ...')\\n beta = None\\n\\t i = 0\\n batch_vb = Batch_VB.BatchVB(self.settings['num_terms'], self.settings['num_topics'], self.settings['alpha'],\\n self.settings['eta'], self.settings['iter_infer'],\\n self.settings['conv_infer'], beta)\\n # Start\\n print('start!!!')\\n datafp = open(self.formatted_data.data_path, 'r')\\n (wordids, wordcts) = self.formatted_data.load_batch(datafp)\\n\\tif a is None:\\n if only_doc:\\n a = np.zeros(len(wordids), dtype=np.int32)\\n else:\\n\\t a = list()\\n\\t for d in range(0, len(wordids)):\\n\\t\\t N = len(wordids[d])\\n\\t\\t w = np.zeros(N, dtype=np.int32)\\n\\t\\t a.append(w)\\n del wordids\\n del wordcts\\n if method != 'none':\\n if only_doc:\\n print('Method: %s, alpha: %.1f, only_doc=true' %(method,alpha))\\n else:\\n print('Method: %s, alpha: %.1f, only_doc=false' % (method, alpha))\\n else:\\n print('Method: none noise data')\\n while i < self.settings['iter_train']:\\n i += 1\\n print('***num_iter_train***: %d' %i)\\n iter_train = i\\n train_file = self.formatted_data.data_path\\n datafp = open(train_file, 'r')\\n (wordids, wordcts) = self.formatted_data.load_batch(datafp)\\n data = noise_data.Noise_Data(wordids,wordcts,iter_train,alpha,a,self.settings['p'],only_doc)\\n if method == 'add_uniform':\\n (wordids,wordcts) = data.add_uniform()\\n elif method == 'mult_uniform':\\n (wordids,wordcts) = data.mult_uniform()\\n elif method == 'add_ope':\\n (wordids,wordcts,a) = data.add_ope()\\n elif method == 'mult_ope':\\n (wordids,wordcts,a) = data.mult_ope()\\n (time_e, time_m, theta) = batch_vb.static_online(wordids, wordcts)\\n # Compute sparsity\\n #sparsity = base.compute_sparsity(theta, theta.shape[0], theta.shape[1], 't')\\n # Compute perplexities\\n LD2 = perplexity.average_predict(self.test_data, self.settings['alpha'], self.settings['eta'],\\n batch_vb._lambda, self.settings['iter_infer'])\\n # Search top words of each topics\\n #list_tops = base.list_top(batch_vb._lambda, self.tops)\\n # Write files\\n base.write_file(i, 0, batch_vb._lambda, time_e, time_m, theta, [], LD2, [], self.tops,\\n self.model_folder)\\n datafp.close()\\n # Write settings\\n print('write setting ...')\\n file_name = '%s/setting.txt'%(self.model_folder)\\n base.write_setting(self.settings, file_name)\\n # Write final model to file\\n print('write final model ...')\\n file_name = '%s/beta_final.dat'%(self.model_folder)\\n base.write_topics(batch_vb._lambda, file_name)\\n\\t# Write a\\n\\tfile_name = '%s/a_%d.txt'%(self.model_folder, i)\\n\\tf = open(file_name, 'w')\\n\\tD = len(a)\\n\\tif only_doc:\\n\\t for d in range(0, D):\\n\\t\\tf.write('%d\\\\n' %a[d])\\n\\telse:\\n\\t for d in range(0,D):\\n\\t\\tN = len(a[d])\\n\\t\\tfor n in range(0,N):\\n\\t\\t f.write('%d '%a[d][n])\\n\\t\\tf.write('\\\\n')\\n\\tf.close()\\n # caculate avarage predict probability\\n \\\"\\\"\\\"file_name = '%s/perplexity.txt'%(self.model_folder)\\n value = perplexity.average_predict(self.test_folder, self.settings['alpha'], self.settings['eta'],\\n batch_vb._lambda, self.settings['iter_infer'])\\n base.write_perplexities(value,file_name)\\\"\\\"\\\"\\n\\n # Finish\\n print('done!!!')\\n print('-----------------------------------------\\\\n')\\n\"\n },\n {\n \"alpha_fraction\": 0.5662844181060791,\n \"alphanum_fraction\": 0.6080275177955627,\n \"avg_line_length\": 33.60317611694336,\n \"blob_id\": \"b642126ca3844bdadaefaff8b0354cd11fc47778\",\n \"content_id\": \"125b06905636338ddf2ea3cb07144065635b2876\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 4360,\n \"license_type\": \"no_license\",\n \"max_line_length\": 117,\n \"num_lines\": 126,\n \"path\": \"/plot_graph.py\",\n \"repo_name\": \"TruongKhang/topic_models\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import csv\\nimport numpy as np\\nimport matplotlib.pyplot as plt\\nimport matplotlib\\ncopus = ['grolier']\\n#method_learing = ['OPE_linear_function', 'OPE_linear_function']\\nnoise = ['add_uniform', 'mult_uniform', 'add_ope', 'mult_ope']\\nalpha = [0.3, 0.5, 0.7, 1.0]\\nonly_doc = ['True', 'False']\\nnum_train = [100] #[50, 100, 150, 200]\\nlist_alpha1 = list()\\nfor name in copus:\\n for value in alpha:\\n\\tnew_value = int(value*10)\\n\\tlist_method = list()\\n\\tfor method in noise:\\n\\t list_only = list()\\n\\t for boolean in only_doc:\\n\\t\\tlist_per = list()\\n\\t\\tfor index in num_train:\\n\\t\\t for i in range(1,index+1):\\n\\t\\t\\taverage = 0.\\n\\t\\t\\tfor j in range(4,5):\\n\\t\\t\\t file_name = '%s_model_ver2/VB%d/%s/alpha%d/%s200/perplexities_%d.csv'%(name, j, method, new_value, boolean, i)\\n\\t\\t\\t f = open(file_name, 'rb')\\n\\t\\t\\t reader = csv.reader(f)\\n\\t\\t\\t for row in reader:\\n\\t\\t\\t perplex = float(row[0])\\n\\t\\t\\t average += perplex\\n\\t\\t\\taverage = float(average/1)\\n\\t\\t\\tlist_per.append(average)\\n\\t\\tlist_only.append(np.array(list_per))\\n\\t list_method.append(list_only)\\n list_alpha1.append(list_method)\\nprint(len(list_alpha1[0]))\\n\\nper_batch = list()\\nnum_train1 = [100]\\nfor index in num_train1:\\n for i in range(1,index+1):\\n\\taverage = 0.\\n\\tfor j in range(4,5):\\n\\t filename = 'grolier_model_ver2/VB%d/batch_vb/batchvb200/perplexities_%d.csv'%(j,i)\\n\\t f = open(filename, 'rb')\\n\\t reader = csv.reader(f)\\n\\t for row in reader:\\n\\t perplex = float(row[0])\\n\\t average += perplex\\n\\taverage = float(average/1)\\n\\tper_batch.append(average)\\n#print(len(list_alpha))\\n\\nt = np.arange(1,101,1)\\ncolor = ['red', 'blue', 'green', 'orange', 'black']\\nname_method = ['add1', 'mult1', 'add2', 'mult2']\\nfont = {#'family' : 'normal',\\n #'weight' : 'bold',\\n 'size' : 8}\\nmatplotlib.rc('font', **font)\\nfor j in range(0,len(list_alpha1)):\\n fig = plt.figure()\\n plt.xlabel('number of iteration training')\\n plt.ylabel('Log Predict Probability')\\n plt.title('Method: VB. Grolier dataset, c=%.1f, function: 1/t^3' %alpha[j])\\n ax = plt.subplot(111)\\n for i in range(0,len(list_alpha1[j])):\\n ax.plot(t, list_alpha1[j][i][1], color=color[i], linewidth=1.0, label=name_method[i])\\n ax.plot(t, list_alpha1[j][i][0], color=color[i], linewidth=1.0, linestyle='--')\\n ax.plot(t, per_batch, color=color[4], linewidth=1.0, label='Original VB')\\n #plt.axis([0, 200, -8.30, -7.90])\\n box = ax.get_position()\\n ax.set_position([box.x0, box.y0, box.width * 0.9, box.height])\\n ax.legend(loc='center left', bbox_to_anchor=(1, 0.5))\\n #plt.axis([0,200,-10,0])\\n plt.show()\\n\\n\\\"\\\"\\\"list_alpha2 = list()\\nnoise = ['add_ope', 'mult_ope']\\nalpha = [1.0]\\nfor name in copus:\\n for value in alpha:\\n\\tnew_value = int(value*10)\\n\\tlist_method = list()\\n\\tfor method in noise:\\n\\t list_only = list()\\n\\t for boolean in only_doc:\\n\\t\\tlist_per = list()\\n\\t\\tfor index in num_train:\\n\\t\\t for i in range(index-199,index+1):\\n\\t\\t\\taverage = 0.\\n\\t\\t\\tfor j in range(1,11):\\n\\t\\t\\t file_name = '%s_model/OPE%d/%s/alpha%d/%s200/perplexities_%d.csv'%(name, j, method, new_value, boolean, i)\\n\\t\\t\\t f = open(file_name, 'rb')\\n\\t\\t\\t reader = csv.reader(f)\\n\\t\\t\\t for row in reader:\\n\\t\\t\\t perplex = float(row[0])\\n\\t\\t\\t average += perplex\\n\\t\\t\\taverage = float(average/10)\\n\\t\\t\\tlist_per.append(average)\\n\\t\\tlist_only.append(np.array(list_per))\\n\\t list_method.append(list_only)\\n list_alpha2.append(list_method)\\n\\nt = np.arange(1,201,1)\\ncolor = ['green', 'orange', 'black']\\nname_method = ['add2', 'mult2']\\nfont = {#'family' : 'normal',\\n #'weight' : 'bold',\\n 'size' : 8}\\nmatplotlib.rc('font', **font)\\nfor j in range(0,len(list_alpha2)):\\n fig = plt.figure()\\n plt.xlabel('number of iteration training')\\n plt.ylabel('Log Predict Probability')\\n plt.title('Method: OPE. AP dataset, c=%.1f, function: 1/t' %alpha[j])\\n ax = plt.subplot(111)\\n for i in range(0,len(list_alpha2[j])):\\n ax.plot(t, list_alpha2[j][i][1], color=color[i], linewidth=1.0, label=name_method[i])\\n ax.plot(t, list_alpha2[j][i][0], color=color[i], linewidth=1.0, linestyle='--')\\n ax.plot(t, per_batch, color=color[2], linewidth=1.0, label='Original OPE')\\n plt.axis([0, 200, -8.30, -7.90])\\n box = ax.get_position()\\n ax.set_position([box.x0, box.y0, box.width * 0.9, box.height])\\n ax.legend(loc='center left', bbox_to_anchor=(1, 0.5))\\n #plt.axis([0,200,-10,0])\\n plt.show()\\\"\\\"\\\"\\n\"\n },\n {\n \"alpha_fraction\": 0.4723404347896576,\n \"alphanum_fraction\": 0.4959810972213745,\n \"avg_line_length\": 42.597938537597656,\n \"blob_id\": \"7e1287757533b37b92f10e900a8fd3468548492e\",\n \"content_id\": \"0faa277e3e2ea54591ed97833ca509ca09ac64e1\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 4230,\n \"license_type\": \"no_license\",\n \"max_line_length\": 142,\n \"num_lines\": 97,\n \"path\": \"/datasets/noise_data.py\",\n \"repo_name\": \"TruongKhang/topic_models\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import numpy as np\\nimport math\\nimport random\\n\\nclass Noise_Data:\\n def __init__(self, wordids, wordcts, iter_train, alpha, a, p, only_doc=True):\\n self.wordids = wordids\\n self.wordcts = wordcts\\n self.iter_train = iter_train\\n self.alpha = alpha # hyperparameter\\n self.only_doc = only_doc\\n self.a = a #number of sample which received value -1 in set {-1, 1}\\n self.p = p\\n\\n def add_uniform(self):\\n D = len(self.wordids)\\n new_wordcts = list()\\n for d in range(0,D):\\n if self.only_doc:\\n c = random.choice([-1,0,1])#np.random.random_integers(-1,1)\\n N = len(self.wordids[d])\\n new_wordct = np.zeros(N, dtype=np.float64)\\n for n in range(0,N):\\n if not self.only_doc:\\n c = random.choice([-1,0,1])#np.random.random_integers(-1,1)\\n new_wordct[n] = self.wordcts[d][n] + c*self.alpha/math.pow(self.iter_train,self.p)\\n new_wordcts.append(new_wordct)\\n return (self.wordids, new_wordcts)\\n\\n def mult_uniform(self):\\n D = len(self.wordids)\\n new_wordcts = list()\\n for d in range(0,D):\\n if self.only_doc:\\n c = random.choice([-1,0,1])#np.random.random_integers(-1,1)\\n N = len(self.wordids[d])\\n new_wordct = np.zeros(N, dtype=np.float64)\\n for n in range(0,N):\\n if not self.only_doc:\\n c = random.choice([-1,0,1])#np.random.random_integers(-1,1)\\n new_wordct[n] = self.wordcts[d][n] * (1 + float(c*self.alpha/math.pow(self.iter_train,self.p)))\\n new_wordcts.append(new_wordct)\\n return (self.wordids, new_wordcts)\\n\\n def add_ope(self):\\n D = len(self.wordids)\\n new_wordcts = list()\\n for d in range(0,D):\\n N = len(self.wordids[d])\\n new_wordct = np.zeros(N, dtype=np.float64)\\n if self.only_doc:\\n rand = random.choice([0,1])#np.random.random_integers(0,1)\\n if rand == 0:\\n self.a[d] = self.a[d] + 1\\n #if d == 0:\\n # print(self.a[d])\\n for n in range(0,N):\\n new_wordct[n] = self.wordcts[d][n] + self.alpha*(self.iter_train - 2*self.a[d])/math.pow(self.iter_train, self.p)\\n else:\\n for n in range(0,N):\\n rand = random.choice([0,1])#np.random.random_integers(0,1)\\n if rand == 0:\\n self.a[d][n] = self.a[d][n] + 1\\n new_wordct[n] = self.wordcts[d][n] + self.alpha*(self.iter_train - 2*self.a[d][n])/math.pow(self.iter_train, self.p)\\n new_wordcts.append(new_wordct)\\n return (self.wordids, new_wordcts, self.a)\\n\\n def mult_ope(self):\\n D = len(self.wordids)\\n new_wordcts = list()\\n for d in range(0,D):\\n N = len(self.wordids[d])\\n new_wordct = np.zeros(N, dtype=np.float64)\\n if self.only_doc:\\n rand = random.choice([0,1])#np.random.random_integers(0,1)\\n if rand == 0:\\n self.a[d] = self.a[d] + 1\\n for n in range(0,N):\\n new_wordct[n] = self.wordcts[d][n] * (1 - self.alpha*(self.iter_train - 2*self.a[d])/math.pow(self.iter_train, self.p))\\n else:\\n for n in range(0,N):\\n rand = random.choice([0,1])#np.random.random_integers(0,1)\\n if rand == 0:\\n self.a[d][n] = self.a[d][n] + 1\\n new_wordct[n] = self.wordcts[d][n] * (1 - self.alpha*(self.iter_train - 2*self.a[d][n])/math.pow(self.iter_train, self.p))\\n new_wordcts.append(new_wordct)\\n return (self.wordids, new_wordcts, self.a)\\n\\nif __name__ == '__main__':\\n for i in range(0,1):\\n print('setting %d: '%i)\\n a = np.zeros(3, dtype=np.int32)\\n for t in range(1,50):\\n wordids = [[1, 2, 3], [4, 6, 7], [1, 4, 7]]\\n wordcts = [[1., 1., 2.], [1., 5., 2.], [1., 4., 1.]]\\n noise = Noise_Data(wordids,wordcts,t,1,a,only_doc=True)\\n (wordids,wordcts,a) = noise.add_ope()\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.4721164405345917,\n \"alphanum_fraction\": 0.48028498888015747,\n \"avg_line_length\": 35.022125244140625,\n \"blob_id\": \"ca01e1a98457f47052eddd9c260db763ba16b922\",\n \"content_id\": \"8e0408ba2653298d92b61c10405df1030db12681\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 16282,\n \"license_type\": \"no_license\",\n \"max_line_length\": 120,\n \"num_lines\": 452,\n \"path\": \"/datasets/base.py\",\n \"repo_name\": \"TruongKhang/topic_models\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import os, os.path\\nimport sys\\nimport shutil\\nfrom os.path import isdir, isfile, join\\nfrom preprocessing import preprocessing\\nimport numpy as np\\nfrom time import time\\n\\n# Name of current path directory which contains this file\\ndir_path = os.path.dirname(os.path.realpath(__file__))\\n\\n# check format of input file(text formatted or raw text)\\ndef check_format(line, c):\\n result = True\\n l = len(line)\\n for i in range(0,l):\\n if line[i].isalpha():\\n result = False\\n break\\n elif not line[i].isalnum() and line[i] != ' ' and line[i] != c:\\n result = False\\n break\\n return result\\n\\nclass Dataset:\\n def __init__(self,path):\\n self.vocab_path = None\\n self.is_raw_text = False\\n if isfile(path):\\n print(\\\"Path %s is a file\\\" %path)\\n self.path_isfile = path\\n self.path_isdir = None\\n name_file = self.path_isfile.split(\\\"\\\\\\\\\\\")\\n name_file = name_file[-1].split(\\\"/\\\")\\n main_name = name_file[-1]\\n self.main_name_file = main_name[:-4]\\n elif isdir(path):\\n self.path_isdir = path\\n self.path_isfile = None\\n print(\\\"Path %s is a directory\\\" %path)\\n else:\\n self.path_isdir = None\\n self.path_isfile = None\\n print(\\\"Unknown path %s!\\\" %path)\\n exit()\\n\\n \\\"\\\"\\\"\\n read file input, check format is raw input or term frequency or term sequence\\n \\\"\\\"\\\"\\n def load_dataset(self, term_seq=False, term_freq=True):\\n if self.path_isfile:\\n f = open(self.path_isfile)\\n line = f.readline().strip()\\n while len(line) == 0:\\n line = f.readline().strip()\\n if line == \\\"<DOC>\\\":\\n self.is_raw_text = True\\n print(\\\"Pre-processing:\\\")\\n p = preprocessing.PreProcessing()\\n p.process(self.path_isfile)\\n p.extract_vocab()\\n p.format_freq()\\n p.format_seq()\\n self.vocab_path = p.dir_path_data + \\\"/vocab.txt\\\"\\n if term_freq:\\n data_path = p.dir_path_data + \\\"/term_frequency.txt\\\"\\n term_seq = False\\n else:\\n data_path = p.dir_path_data + \\\"/term_sequence.txt\\\"\\n term_seq = True\\n elif check_format(line, ' '):\\n data_path = self.path_isfile\\n \\\"\\\"\\\"if 'wikipedia' in self.path_isfile:\\n data_path = self.path_isfile\\n else:\\n dir_folder = dir_path + \\\"/data/\\\" + self.main_name_file\\n # Create model folder if it doesn't exist\\n if os.path.exists(dir_folder):\\n shutil.rmtree(dir_folder)\\n os.makedirs(dir_folder)\\n data_path = dir_folder + \\\"/term_sequence.txt\\\"\\n print(\\\"Copy file %s => %s\\\" %(self.path_isfile,data_path))\\n shutil.copyfile(self.path_isfile,data_path)\\\"\\\"\\\"\\n term_freq = False\\n term_seq = True\\n elif check_format(line, ':'):\\n data_path = self.path_isfile\\n \\\"\\\"\\\"if 'wikipedia' in self.path_isfile:\\n data_path = self.path_isfile\\n else:\\n dir_folder = dir_path + \\\"/data/\\\" + self.main_name_file\\n # Create model folder if it doesn't exist\\n if os.path.exists(dir_folder):\\n shutil.rmtree(dir_folder)\\n os.makedirs(dir_folder)\\n data_path = dir_folder + \\\"/term_frequency.txt\\\"\\n print(\\\"Copy file %s => %s\\\" % (self.path_isfile, data_path))\\n shutil.copyfile(self.path_isfile, data_path)\\\"\\\"\\\"\\n term_seq = False\\n term_freq = True\\n else:\\n print(\\\"File %s is not true format!\\\" %self.path_isfile)\\n sys.exit()\\n f.close()\\n bunch = self.Bunch(data_path,term_seq,term_freq)\\n return bunch\\n\\n \\\"\\\"\\\"\\n inner class with methods load data from formatted file\\n \\\"\\\"\\\"\\n class Bunch:\\n def __init__(self, data_path, term_seq, term_freq):\\n self.data_path = data_path\\n self.term_seq = term_seq\\n self.term_freq = term_freq\\n self.copus = []\\n # load number of documents\\n f = open(data_path,'r')\\n lines = f.readlines()\\n self.num_doc = len(lines)\\n del lines\\n f.close()\\n\\n \\\"\\\"\\\"\\n shuffle input and write into file file_shuffled.txt, return path of this file\\n \\\"\\\"\\\"\\n def shuffle(self):\\n f = open(self.data_path)\\n lines = f.readlines()\\n self.num_doc = len(lines)\\n np.random.shuffle(lines)\\n f.close()\\n if self.term_freq:\\n d = self.data_path[:-19]\\n elif self.term_seq:\\n d = self.data_path[:-18]\\n fout = open(join(d,\\\"file_shuffled.txt\\\"), \\\"w\\\")\\n for line in lines:\\n fout.write(\\\"%s\\\" %line)\\n fout.close()\\n del lines\\n return join(d,\\\"file_shuffled.txt\\\")\\n\\n def load_batch(self, fp):\\n docs = fp.readlines();\\n D = len(docs)\\n wordids = list()\\n wordcts = list()\\n for d in range(0,D):\\n list_word = docs[d].strip().split()\\n N = int(list_word[0])\\n if N+1 != len(list_word):\\n print(\\\"Line %d in file %s is error!\\\" % (d + 1, self.data_path))\\n exit()\\n wordid = np.zeros(N, dtype=np.int32)\\n wordct = np.zeros(N, dtype=np.float64)\\n for n in range(1, N+1):\\n id_ct = list_word[n].split(':')\\n wordid[n-1] = int(id_ct[0])\\n wordct[n-1] = float(id_ct[1])\\n wordids.append(wordid)\\n wordcts.append(wordct)\\n return (wordids,wordcts)\\n\\n \\\"\\\"\\\"\\n read mini-batch data and store with format term sequence\\n fp is file pointer after shuffled\\n \\\"\\\"\\\"\\n def load_minibatch_term_seq(self, fp, size_batch):\\n doc_terms = []\\n doc_lens = []\\n for i in range(0, size_batch):\\n doc = fp.readline()\\n #check end file\\n if len(doc) < 5:\\n break\\n list_word = doc.strip().split()\\n N = int(list_word[0])\\n if N + 1 != len(list_word):\\n print(\\\"Line %d in file %s is error!\\\" % (i + 1, self.data_path))\\n sys.exit()\\n if self.term_freq:\\n tokens = list()\\n for j in range(1, N + 1):\\n tf = list_word[j].split(\\\":\\\")\\n for k in range(0,int(tf[1])):\\n tokens.append(int(tf[0]))\\n doc_terms.append(np.array(tokens))\\n doc_lens.append(len(tokens))\\n elif self.term_seq:\\n doc_t = np.zeros(N, dtype=np.int32)\\n for j in range(1, N + 1):\\n doc_t[j - 1] = int(list_word[j])\\n doc_l = N\\n doc_terms.append(doc_t)\\n doc_lens.append(doc_l)\\n del list_word\\n return (doc_terms,doc_lens)\\n\\n \\\"\\\"\\\"\\n read mini-batch data and store with format term frequency\\n fp is file pointer after shuffled\\n \\\"\\\"\\\"\\n def load_minibatch_term_freq(self,fp,size_batch):\\n doc_terms = []\\n doc_freqs = []\\n for i in range(0,size_batch):\\n doc = fp.readline()\\n if len(doc) < 5:\\n break\\n list_word = doc.strip().split()\\n N = int(list_word[0])\\n if N + 1 != len(list_word):\\n print(\\\"Line %d in file %s is error!\\\" % (i + 1, self.data_path))\\n sys.exit()\\n if self.term_freq:\\n doc_t = np.zeros(N,dtype=np.int32)\\n doc_f = np.zeros(N,dtype=np.int32)\\n for j in range(1,N+1):\\n tf = list_word[j].split(\\\":\\\")\\n doc_t[j-1] = int(tf[0])\\n doc_f[j-1] = int(tf[1])\\n doc_terms.append(doc_t)\\n doc_freqs.append(doc_f)\\n elif self.term_seq:\\n terms = []\\n freqs = []\\n k = 0\\n for j in range(1,N+1):\\n if int(list_word[j]) not in terms:\\n terms.append(int(list_word[j]))\\n freqs.append(1)\\n else:\\n index = terms.index(int(list_word[j]))\\n freqs[index] += 1\\n doc_terms.append(np.array(terms))\\n doc_freqs.append(np.array(freqs))\\n del list_word\\n return (doc_terms,doc_freqs)\\n\\n\\\"\\\"\\\"------------------------------------------------------------------------------------------------------------------\\\"\\\"\\\"\\n\\ndef read_setting(file_name):\\n if isfile(file_name):\\n f = open(file_name, 'r')\\n settings = f.readlines()\\n f.close()\\n sets = list()\\n vals = list()\\n for i in range(len(settings)):\\n # print'%s\\\\n'%(settings[i])\\n line = settings[i].strip()\\n if len(line) != 0:\\n if line[0] == '#':\\n continue\\n set_val = settings[i].strip().split(':')\\n sets.append(set_val[0])\\n vals.append(float(set_val[1]))\\n ddict = dict(zip(sets, vals))\\n #ddict['num_terms'] = int(ddict['num_terms'])\\n ddict['num_topics'] = int(ddict['num_topics'])\\n ddict['iter_train'] = int(ddict['iter_train'])\\n ddict['iter_infer'] = int(ddict['iter_infer'])\\n ddict['batch_size'] = int(ddict['batch_size'])\\n ddict['num_crawling'] = int(ddict['num_crawling'])\\n #ddict['p'] = int(ddict['p'])\\n return (ddict)\\n else:\\n print(\\\"Can't find file!\\\")\\n sys.exit()\\n\\n\\\"\\\"\\\"\\n Read all documents in the file and stores terms and counts in lists.\\n\\\"\\\"\\\"\\ndef read_data(filename):\\n wordids = list()\\n wordcts = list()\\n fp = open(filename, 'r')\\n while True:\\n line = fp.readline()\\n # check end of file\\n if len(line) < 1:\\n break\\n terms = line.split()\\n doc_length = int(terms[0])\\n ids = np.zeros(doc_length, dtype = np.int32)\\n cts = np.zeros(doc_length, dtype = np.int32)\\n for j in range(1, doc_length + 1):\\n term_count = terms[j].split(':')\\n ids[j - 1] = int(term_count[0])\\n cts[j - 1] = int(term_count[1])\\n wordids.append(ids)\\n wordcts.append(cts)\\n fp.close()\\n return(wordids, wordcts)\\n\\n\\\"\\\"\\\"\\n Read data for computing perplexities.\\n\\\"\\\"\\\"\\ndef read_data_for_perpl(test_data_folder):\\n onlyfiles = [f for f in os.listdir(test_data_folder) if isfile(os.path.join(test_data_folder, f))]\\n k_fold_cross = int(len(onlyfiles) / 2)\\n list_data_test = list()\\n for i in range(0,k_fold_cross):\\n filename_part1 = '%s/data_test_%d_part_1.txt'%(test_data_folder, i+1)\\n filename_part2 = '%s/data_test_%d_part_2.txt'%(test_data_folder, i+1)\\n (wordids_1, wordcts_1) = read_data(filename_part1)\\n (wordids_2, wordcts_2) = read_data(filename_part2)\\n data_test = list()\\n data_test.append(wordids_1)\\n data_test.append(wordcts_1)\\n data_test.append(wordids_2)\\n data_test.append(wordcts_2)\\n list_data_test.append(data_test)\\n return(list_data_test)\\n\\ndef read_beta(filename):\\n if isfile(filename):\\n f = open(filename)\\n lines = f.readlines()\\n words = lines[0].strip().split()\\n K = len(lines)\\n W = len(words)\\n beta = np.zeros((K,W))\\n for i in range(0,K):\\n words = lines[i].strip().split()\\n if len(words) != W:\\n print('File %s is error' %filename)\\n exit()\\n for j in range(0,W):\\n beta[i][j] = float(words[j])\\n return beta\\n else:\\n print('Unknown file %s' %filename)\\n exit()\\n\\n\\\"\\\"\\\"\\n Compute document sparsity.\\n\\\"\\\"\\\"\\ndef compute_sparsity(doc_tp, batch_size, num_topics, _type):\\n sparsity = np.zeros(batch_size, dtype = np.float)\\n if _type == 'z':\\n for d in range(batch_size):\\n N_z = np.zeros(num_topics, dtype = np.int)\\n N = len(doc_tp[d])\\n for i in range(N):\\n N_z[doc_tp[d][i]] += 1.\\n sparsity[d] = len(np.where(N_z != 0)[0])\\n else:\\n for d in range(batch_size):\\n sparsity[d] = len(np.where(doc_tp[d] > 1e-10)[0])\\n sparsity /= num_topics\\n return(np.mean(sparsity))\\n\\n\\\"\\\"\\\"\\n Create list of top words of topics.\\n\\\"\\\"\\\"\\ndef list_top(beta, tops):\\n min_float = -sys.float_info.max\\n num_tops = beta.shape[0]\\n list_tops = list()\\n for k in range(num_tops):\\n top = list()\\n arr = np.array(beta[k,:], copy = True)\\n for t in range(tops):\\n index = arr.argmax()\\n top.append(index)\\n arr[index] = min_float\\n list_tops.append(top)\\n return(list_tops)\\n\\n\\n\\\"\\\"\\\"------------------------------------------------------------------------------------------------------------------\\\"\\\"\\\"\\ndef write_setting(ddict,file_name):\\n keys = list(ddict.keys())\\n vals = list(ddict.values())\\n f = open(file_name, 'w')\\n for i in range(len(keys)):\\n f.write('%s: %f\\\\n' % (keys[i], vals[i]))\\n f.close()\\n\\ndef write_topics(beta, file_name):\\n num_terms = beta.shape[1]\\n num_topics = beta.shape[0]\\n f = open(file_name, 'w')\\n for k in range(num_topics):\\n for i in range(num_terms - 1):\\n f.write('%.10f ' % (beta[k][i]))\\n f.write('%.10f\\\\n' % (beta[k][num_terms - 1]))\\n f.close()\\n\\ndef write_topic_mixtures(theta, file_name):\\n batch_size = theta.shape[0]\\n num_topics = theta.shape[1]\\n f = open(file_name, 'a')\\n for d in range(batch_size):\\n for k in range(num_topics - 1):\\n f.write('%.5f ' % (theta[d][k]))\\n f.write('%.5f\\\\n' % (theta[d][num_topics - 1]))\\n f.close()\\n\\ndef write_perplexities(LD2, file_name):\\n f = open(file_name, 'a')\\n f.writelines('%f,'%(LD2))\\n f.close()\\n\\ndef write_time(i, j, time_e, time_m, file_name):\\n f = open(file_name, 'a')\\n f.write('tloop_%d_iloop_%d, %f, %f, %f,\\\\n' % (i, j, time_e, time_m, time_e + time_m))\\n f.close()\\n\\ndef write_loop(i, j, file_name):\\n f = open(file_name, 'w')\\n f.write('%d, %d' % (i, j))\\n f.close()\\n\\ndef write_file(i, j, beta, time_e, time_m, theta, sparsity, LD2, list_tops, tops, model_folder):\\n beta_file_name = '%s/beta_%d_%d.dat'%(model_folder, i, j)\\n theta_file_name = '%s/theta_%d.dat'%(model_folder, i)\\n per_file_name = '%s/perplexities_%d.csv'%(model_folder, i)\\n #top_file_name = '%s/top%d_%d_%d.dat'%(model_folder, tops, i, j)\\n #spar_file_name = '%s/sparsity_%d.csv'%(model_folder, i)\\n time_file_name = '%s/time_%d.csv'%(model_folder, i)\\n loop_file_name = '%s/loops.csv'%(model_folder)\\n\\n # write beta\\n #if i % 10 == 1:\\n # write_topics(beta, beta_file_name)\\n # write theta\\n #write_topic_mixtures(theta, theta_file_name)\\n\\n # write perplexities\\n write_perplexities(LD2, per_file_name)\\n # write list top\\n ##write_topic_top(list_tops, top_file_name)\\n # write sparsity\\n ##write_sparsity(sparsity, spar_file_name)\\n # write time\\n write_time(i, j, time_e, time_m, time_file_name)\\n # write loop\\n write_loop(i, j, loop_file_name)\\n\\nif __name__ == '__main__':\\n t0 = time()\\n data = Dataset(\\\"D:\\\\\\\\UCR_TS_Archive_2015\\\\\\\\ap/ap.txt\\\").load_dataset()\\n (docs,freqs) = data.load_batch()\\n print(len(docs))\\n print(docs[0])\\n (docs,lengs) = data.load_minibatch(2)\\n print(docs)\\n print(lengs)\\n print(\\\"Done in %.3f\\\" %(time() - t0))\\n\"\n },\n {\n \"alpha_fraction\": 0.5423541069030762,\n \"alphanum_fraction\": 0.5463746190071106,\n \"avg_line_length\": 34.70792007446289,\n \"blob_id\": \"97a9c32c646dab1ae89a9660a9ce34aa14826a53\",\n \"content_id\": \"c98ccaa4e5737c6666e1f6aea27b6b113408cd0e\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 7213,\n \"license_type\": \"no_license\",\n \"max_line_length\": 119,\n \"num_lines\": 202,\n \"path\": \"/datasets/crawl_wiki_ariticles.py\",\n \"repo_name\": \"TruongKhang/topic_models\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"\\\"\\\"\\\"Reference: M.Hoffman - onlineldavb\\\"\\\"\\\"\\n\\nimport sys, urllib2, re, string, time, threading\\nimport os\\n\\n# Name of current path directory which contains this file\\ndir_path = os.path.dirname(os.path.realpath(__file__))\\n\\ndef get_random_wikipedia_article():\\n \\\"\\\"\\\"\\n Downloads a randomly selected Wikipedia article (via\\n http://en.wikipedia.org/wiki/Special:Random) and strips out (most\\n of) the formatting, links, etc.\\n\\n This function is a bit simpler and less robust than the code that\\n was used for the experiments in \\\"Online VB for LDA.\\\"\\n \\\"\\\"\\\"\\n failed = True\\n while failed:\\n articletitle = None\\n failed = False\\n try:\\n req = urllib2.Request('http://en.wikipedia.org/wiki/Special:Random',\\n None, { 'User-Agent' : 'x'})\\n f = urllib2.urlopen(req)\\n while not articletitle:\\n line = f.readline()\\n result = re.search(r'title=\\\"Edit this page\\\" href=\\\"/w/index.php\\\\?title=(.*)\\\\&action=edit\\\"\\\\/>', line)\\n if (result):\\n articletitle = result.group(1)\\n break\\n elif (len(line) < 1):\\n sys.exit(1)\\n\\n req = urllib2.Request('http://en.wikipedia.org/w/index.php?title=Special:Export/%s&action=submit' \\\\\\n % (articletitle),\\n None, { 'User-Agent' : 'x'})\\n f = urllib2.urlopen(req)\\n all = f.read()\\n except (urllib2.HTTPError, urllib2.URLError):\\n print('oops. there was a failure downloading %s. retrying...' % articletitle)\\n failed = True\\n continue\\n print('downloaded %s. parsing...' % articletitle)\\n\\n try:\\n all = re.search(r'<text.*?>(.*)</text', all, flags=re.DOTALL).group(1)\\n all = re.sub(r'\\\\n', ' ', all)\\n all = re.sub(r'\\\\{\\\\{.*?\\\\}\\\\}', r'', all)\\n all = re.sub(r'\\\\[\\\\[Category:.*', '', all)\\n all = re.sub(r'==\\\\s*[Ss]ource\\\\s*==.*', '', all)\\n all = re.sub(r'==\\\\s*[Rr]eferences\\\\s*==.*', '', all)\\n all = re.sub(r'==\\\\s*[Ee]xternal [Ll]inks\\\\s*==.*', '', all)\\n all = re.sub(r'==\\\\s*[Ee]xternal [Ll]inks and [Rr]eferences==\\\\s*', '', all)\\n all = re.sub(r'==\\\\s*[Ss]ee [Aa]lso\\\\s*==.*', '', all)\\n all = re.sub(r'http://[^\\\\s]*', '', all)\\n all = re.sub(r'\\\\[\\\\[Image:.*?\\\\]\\\\]', '', all)\\n all = re.sub(r'Image:.*?\\\\|', '', all)\\n all = re.sub(r'\\\\[\\\\[.*?\\\\|*([^\\\\|]*?)\\\\]\\\\]', r'\\\\1', all)\\n all = re.sub(r'\\\\<.*?>', '', all)\\n except:\\n # Something went wrong, try again. (This is bad coding practice.)\\n print('oops. there was a failure parsing %s. retrying...' % articletitle)\\n failed = True\\n continue\\n\\n return(all, articletitle)\\n\\nclass WikiThread(threading.Thread):\\n articles = list()\\n articlenames = list()\\n lock = threading.Lock()\\n def __init__(self):\\n\\tthreading.Thread.__init__(self)\\n\\n def run(self):\\n (article, articlename) = get_random_wikipedia_article()\\n WikiThread.lock.acquire()\\n WikiThread.articles.append(article)\\n WikiThread.articlenames.append(articlename)\\n WikiThread.lock.release()\\n\\ndef get_random_wikipedia_articles(n):\\n \\\"\\\"\\\"\\n Downloads n articles in parallel from Wikipedia and returns lists\\n of their names and contents. Much faster than calling\\n get_random_wikipedia_article() serially.\\n \\\"\\\"\\\"\\n maxthreads = 8\\n WikiThread.articles = list()\\n WikiThread.articlenames = list()\\n wtlist = list()\\n for i in range(0, n, maxthreads):\\n print('downloaded %d/%d articles...' % (i, n))\\n for j in range(i, min(i+maxthreads, n)):\\n wtlist.append(WikiThread())\\n wtlist[len(wtlist)-1].start()\\n for j in range(i, min(i+maxthreads, n)):\\n wtlist[j].join()\\n\\n return (WikiThread.articles, WikiThread.articlenames)\\n\\ndef parse_doc_list(fp, docs, vocab):\\n \\\"\\\"\\\"\\n Parse a document into a list of word ids and a list of counts,\\n or parse a set of documents into two lists of lists of word ids\\n and counts.\\n\\n Arguments:\\n docs: List of D documents. Each document must be represented as\\n a single string. (Word order is unimportant.) Any\\n words not in the vocabulary will be ignored.\\n vocab: Dictionary mapping from words to integer ids.\\n\\n Returns a pair of lists of lists.\\n\\n The first, wordids, says what vocabulary tokens are present in\\n each document. wordids[i][j] gives the jth unique token present in\\n document i. (Don't count on these tokens being in any particular\\n order.)\\n\\n The second, wordcts, says how many times each vocabulary token is\\n present. wordcts[i][j] is the number of times that the token given\\n by wordids[i][j] appears in document i.\\n \\\"\\\"\\\"\\n if (type(docs).__name__ == 'str'):\\n temp = list()\\n temp.append(docs)\\n docs = temp\\n\\n D = len(docs)\\n\\n wordids = list()\\n wordcts = list()\\n for d in range(0, D):\\n docs[d] = docs[d].lower()\\n docs[d] = re.sub(r'-', ' ', docs[d])\\n docs[d] = re.sub(r'[^a-z ]', '', docs[d])\\n docs[d] = re.sub(r' +', ' ', docs[d])\\n words = string.split(docs[d])\\n ddict = dict()\\n for word in words:\\n if (word in vocab):\\n wordtoken = vocab[word]\\n if (not wordtoken in ddict):\\n ddict[wordtoken] = 0\\n ddict[wordtoken] += 1\\n wordids = ddict.keys()\\n wordcts = ddict.values()\\n fp.write('%d ' %len(wordids))\\n for i in range(0,len(wordids)):\\n fp.write('%d:%d ' %(wordids[i],wordcts[i]))\\n\\tif d < D-1:\\n\\t fp.write('\\\\n')\\n\\n del wordids\\n del wordcts\\n\\ndef crawl(size_batch, num_crawling):\\n path_vocab = dir_path+\\\"/data/wikipedia/vocab.txt\\\"\\n if(os.path.isfile(path_vocab)):\\n f = open(path_vocab,'r')\\n l_vocab = f.readlines()\\n f.close()\\n else:\\n print('Unknown file %s' %path_vocab)\\n exit()\\n d_vocab = dict()\\n for word in l_vocab:\\n word = word.lower()\\n word = re.sub(r'[^a-z]', '', word)\\n d_vocab[word] = len(d_vocab)\\n del l_vocab\\n\\n fdata = open(os.path.join(dir_path+\\\"/data/wikipedia\\\",\\\"articles.txt\\\"),'w')\\n fformat = open(os.path.join(dir_path+\\\"/data/wikipedia\\\",\\\"input.txt\\\"),'w')\\n\\n for i in range(0,num_crawling):\\n (docset,articlenames) = get_random_wikipedia_articles(size_batch)\\n N = len(docset)\\n \\tfor j in range(0,N):\\n fdata.write(\\\"<DOC>\\\\n\\\")\\n fdata.write(\\\"<TITLE> %s <\\\\\\\\TITLE>\\\\n\\\" %articlenames[j])\\n fdata.write(\\\"<TEXT>\\\\n\\\")\\n fdata.write(\\\"%s\\\\n\\\" %docset[j])\\n fdata.write(\\\"<\\\\DOC>\\\\n\\\")\\n fdata.write(\\\"<\\\\TEXT>\\\\n\\\")\\n parse_doc_list(fformat,docset,d_vocab)\\n\\tif i < num_crawling-1:\\n\\t fformat.write('\\\\n')\\n fdata.close()\\n fformat.close()\\n\\nif __name__ == '__main__':\\n t0 = time.time()\\n\\n (articles, articlenames) = get_random_wikipedia_articles(4)\\n for i in range(0, len(articles)):\\n print(articlenames[i])\\n\\n t1 = time.time()\\n print('took %f' % (t1 - t0))\\n\"\n },\n {\n \"alpha_fraction\": 0.5380309224128723,\n \"alphanum_fraction\": 0.5591043829917908,\n \"avg_line_length\": 29.676767349243164,\n \"blob_id\": \"b4150171ac2937919f7579a3e937a4c998502c45\",\n \"content_id\": \"37e91a59a128b94ba707394d771ca3dc5d4383a8\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 3037,\n \"license_type\": \"no_license\",\n \"max_line_length\": 84,\n \"num_lines\": 99,\n \"path\": \"/lda/Batch_VB/Batch_VB.py\",\n \"repo_name\": \"TruongKhang/topic_models\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import re, time\\nimport sys\\nfrom datetime import datetime\\n\\nimport numpy as n\\nfrom scipy.special import gammaln, psi\\n\\nt = datetime.now()\\ntime_cur = t.hour*3600 + t.minute*60 + t.second\\nn.random.seed(time_cur+100000000)\\n\\\"\\\"\\\"\\nCreated : 03 /08 /2016\\n@author : Ha Nhat Cuong\\n\\\"\\\"\\\"\\n\\ndef dirichlet_expectation(alpha):\\n if len(alpha.shape) == 1:\\n return psi(alpha) - psi(n.sum(alpha))\\n return psi(alpha) - psi(n.sum(alpha, 1))[:, n.newaxis]\\n\\n\\nclass BatchVB:\\n\\n def __init__(self, num_terms, num_topics, alpha, eta,\\n iter_infer, meanchangethresh, beta=None):\\n #self._D = num_docs\\n\\n self._K = num_topics\\n self._W = num_terms\\n\\n self._iter_infer = iter_infer\\n self._meanchangethresh = meanchangethresh\\n\\n self._alpha = alpha\\n self._eta = eta\\n\\n if beta is not None:\\n self._lambda = beta\\n else:\\n self._lambda = 1*n.random.gamma(100.0, 1.0/100.0, (self._K, self._W))\\n self._Elogbeta = dirichlet_expectation(self._lambda)\\n self._expElogbeta = n.exp(self._Elogbeta)\\n\\n def do_e_step(self, wordids, wordcts):\\n batchD = len(wordids)\\n\\n gamma = n.random.gamma(100.0, 1.0/100.0, (batchD, self._K))\\n Elogtheta = dirichlet_expectation(gamma)\\n expElogtheta = n.exp(Elogtheta)\\n\\n sstats = n.zeros(self._lambda.shape)\\n\\n for d in range(0, batchD) :\\n ids = wordids[d]\\n cts = wordcts[d] # 1 * size(ids)\\n\\n gammad = gamma[d, :] # gammad [1* K]\\n Elogthetad = Elogtheta[d, :]\\n expElogthetad = expElogtheta[d, :] #1*K\\n expElogbetad = self._expElogbeta[:, ids] # K * size(ids)\\n\\n phinorm = n.dot(expElogthetad, expElogbetad) + 1e-100 # 1 * size(ids)\\n\\n for it in range(0, self._iter_infer):\\n lastgamma = gammad\\n\\n gammad = self._alpha + expElogthetad*\\\\\\n n.dot(cts/phinorm, expElogbetad.T)\\n\\n Elogthetad = dirichlet_expectation(gammad)\\n expElogthetad = n.exp(Elogthetad)\\n phinorm = n.dot(expElogthetad, expElogbetad) + 1e-100\\n\\n meanchange = n.mean(abs(lastgamma - gammad))\\n if meanchange < self._meanchangethresh :\\n break\\n\\n gamma[d, :] = gammad\\n sstats[:, ids] += n.outer(expElogthetad.T, cts/phinorm) # K * size(ids)\\n\\n sstats = sstats * self._expElogbeta # K * W\\n return gamma, sstats # batchD * K , K * W\\n\\n def update_lambda(self, sstats):\\n\\n self._lambda = self._eta + sstats # num_topics * W\\n self._Elogbeta = dirichlet_expectation(self._lambda)\\n self._expElogbeta = n.exp(self._Elogbeta)\\n\\n\\n def static_online(self, wordids, wordcts):\\n # E step\\n start = time.time()\\n (gamma, sstats) = self.do_e_step(wordids, wordcts)\\n end1 = time.time()\\n # M step\\n self.update_lambda(sstats)\\n end2 = time.time()\\n return (end1 - start, end2 - start, gamma)\\n\"\n }\n]"},"num_files":{"kind":"number","value":9,"string":"9"}}},{"rowIdx":2035,"cells":{"repo_name":{"kind":"string","value":"shannonserrao/Stack_Exchange"},"repo_url":{"kind":"string","value":"https://github.com/shannonserrao/Stack_Exchange"},"snapshot_id":{"kind":"string","value":"dfcc1ba8ad47296f8785d9c751cdcb85fd4567d2"},"revision_id":{"kind":"string","value":"502806325175c3c965cd5c571fb61c0338cb8d3b"},"directory_id":{"kind":"string","value":"c5767ab2af88e5eede79ae8495c003fe0b7026d0"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"string","value":"2020-12-19T19:13:38.849408"},"revision_date":{"kind":"string","value":"2020-02-11T04:26:44"},"committer_date":{"kind":"string","value":"2020-02-11T04:26:44"},"github_id":{"kind":"number","value":235825185,"string":"235,825,185"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.8042226433753967,"alphanum_fraction":0.8157389760017395,"avg_line_length":29.52941131591797,"blob_id":"b5690b391bf5a07d954ab373ac869a8d827b6320","content_id":"50c6bd73cde672281dadd5166eb3688fa698e4cd","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":521,"license_type":"no_license","max_line_length":125,"num_lines":17,"path":"/Project files final/README.md","repo_name":"shannonserrao/Stack_Exchange","src_encoding":"UTF-8","text":"# Read me \n\n1. Python Processing file\nThis file does some of the preprocessing like removing special charachters from the nominal fields and converting to numeric.\ndatapreprocessing.py\n\n2. Filter file description\nSO_Weka_Data_PreProc_filters\n\n3. Classification/Regression configuration files\nSO_Weka_Classification_regression_config\n\n4. Model files : Present in 'model'folder in Classification/Regression folder\n\n5. Results Dump Files: Present in Classification/Regression folder\n\n6. Data Files: Present in Data folder\n\n\n"},{"alpha_fraction":0.7084047794342041,"alphanum_fraction":0.7217838764190674,"avg_line_length":25.990739822387695,"blob_id":"f6624a32951029e8747f75f7cdc98eb6676b9b1c","content_id":"e1c66a06adb5a58f608a89da8c72f8190559991f","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":2915,"license_type":"no_license","max_line_length":114,"num_lines":108,"path":"/datapreprocessing.py","repo_name":"shannonserrao/Stack_Exchange","src_encoding":"UTF-8","text":"#!/usr/bin/env python3\n# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Sat Apr 28 18:49:47 2018\n\n@author: shannon\n\"\"\"\nimport pandas as pd\n#data = pd.read_csv('/home/shannon/Pictures/Data analysis 5525/Project stuff/survey_results_public.csv')\nimport warnings\ndata= pd.read_csv('/home/shannon/Pictures/Data analysis 5525/Project stuff/survey_results_stackoverflow_only.csv')\ndata.describe\ndata.shape\ndata['StackOverflowDescribes'].replace(\n to_replace=\"I have a login for Stack Overflow, but haven\\'t created a CV or Developer Story\",\n value=\"2\",\n inplace=True\n)\ndata['StackOverflowDescribes'].replace(\n to_replace=\"I\\'ve visited Stack Overflow, but haven\\'t logged in/created an account\",\n value='1',\n inplace=True\n)\ndata['StackOverflowDescribes'].replace(\n to_replace='I have created a CV or Developer Story on Stack Overflow',\n value='3',\n inplace=True\n)\ndata['StackOverflowDescribes'].replace(\n to_replace='I\\'d never heard of Stack Overflow before today',\n value='0',\n inplace=True\n)\ndata['StackOverflowDescribes'].replace(\n to_replace='I\\'ve heard of Stack Overflow, but have never visited',\n value='0',\n inplace=True\n)\ndata.StackOverflowDescribes.unique()\ndata.StackOverflowFoundAnswer.unique()\ndata['StackOverflowFoundAnswer'].replace(\n to_replace='Haven\\'t done at all',\n value='0',\n inplace=True\n)\ndata.StackOverflowCopiedCode.unique()\ndata['StackOverflowCopiedCode'].replace(\n to_replace='Haven\\'t done at all',\n value='0',\n inplace=True\n)\n\n\ndata.StackOverflowJobListing.unique()\ndata['StackOverflowJobListing'].replace(\n to_replace='Haven\\'t done at all',\n value='0',\n inplace=True\n)\n\ndata['StackOverflowJobListing'].replace(\n to_replace='Haven\\'t done at all',\n value='0',\n inplace=True\n)\ndata.StackOverflowJobListing.unique()\n#StackOverflowCompanyPage\ndata['StackOverflowCompanyPage'].replace(\n to_replace='Haven\\'t done at all',\n value='0',\n inplace=True\n)\ndata.StackOverflowCompanyPage.unique()\n\n#StackOverflowJobSearch\ndata['StackOverflowJobSearch'].replace(\n to_replace='Haven\\'t done at all',\n value='0',\n inplace=True\n)\ndata.StackOverflowJobSearch.unique()\n#StackOverflowNewQuestion\ndata['StackOverflowNewQuestion'].replace(\n to_replace='Haven\\'t done at all',\n value='0',\n inplace=True\n)\ndata.StackOverflowNewQuestion.unique()\n#StackOverflowAnswer\n#StackOverflowMetaChat\ndata['StackOverflowAnswer'].replace(\n to_replace='Haven\\'t done at all',\n value='0',\n inplace=True\n)\ndata.StackOverflowMetaChat.unique()\ndata['StackOverflowMetaChat'].replace(\n to_replace='Haven\\'t done at all',\n value='0',\n inplace=True\n)\ndata.StackOverflowAnswer.unique()\ndata.to_csv('SOformat.csv', sep=',', encoding='utf-8')\ndata.to_csv('SOformat1.csv', sep=',')\ndata.to_csv('SOformattab.csv', sep='\\t', encoding='utf-8')\n\ndata.StackOverflowAdsDistracting.unique()\ndata.StackOverflowMakeMoney.unique()\n"}],"string":"[\n {\n \"alpha_fraction\": 0.8042226433753967,\n \"alphanum_fraction\": 0.8157389760017395,\n \"avg_line_length\": 29.52941131591797,\n \"blob_id\": \"b5690b391bf5a07d954ab373ac869a8d827b6320\",\n \"content_id\": \"50c6bd73cde672281dadd5166eb3688fa698e4cd\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 521,\n \"license_type\": \"no_license\",\n \"max_line_length\": 125,\n \"num_lines\": 17,\n \"path\": \"/Project files final/README.md\",\n \"repo_name\": \"shannonserrao/Stack_Exchange\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# Read me \\n\\n1. Python Processing file\\nThis file does some of the preprocessing like removing special charachters from the nominal fields and converting to numeric.\\ndatapreprocessing.py\\n\\n2. Filter file description\\nSO_Weka_Data_PreProc_filters\\n\\n3. Classification/Regression configuration files\\nSO_Weka_Classification_regression_config\\n\\n4. Model files : Present in 'model'folder in Classification/Regression folder\\n\\n5. Results Dump Files: Present in Classification/Regression folder\\n\\n6. Data Files: Present in Data folder\\n\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.7084047794342041,\n \"alphanum_fraction\": 0.7217838764190674,\n \"avg_line_length\": 25.990739822387695,\n \"blob_id\": \"f6624a32951029e8747f75f7cdc98eb6676b9b1c\",\n \"content_id\": \"e1c66a06adb5a58f608a89da8c72f8190559991f\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 2915,\n \"license_type\": \"no_license\",\n \"max_line_length\": 114,\n \"num_lines\": 108,\n \"path\": \"/datapreprocessing.py\",\n \"repo_name\": \"shannonserrao/Stack_Exchange\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#!/usr/bin/env python3\\n# -*- coding: utf-8 -*-\\n\\\"\\\"\\\"\\nCreated on Sat Apr 28 18:49:47 2018\\n\\n@author: shannon\\n\\\"\\\"\\\"\\nimport pandas as pd\\n#data = pd.read_csv('/home/shannon/Pictures/Data analysis 5525/Project stuff/survey_results_public.csv')\\nimport warnings\\ndata= pd.read_csv('/home/shannon/Pictures/Data analysis 5525/Project stuff/survey_results_stackoverflow_only.csv')\\ndata.describe\\ndata.shape\\ndata['StackOverflowDescribes'].replace(\\n to_replace=\\\"I have a login for Stack Overflow, but haven\\\\'t created a CV or Developer Story\\\",\\n value=\\\"2\\\",\\n inplace=True\\n)\\ndata['StackOverflowDescribes'].replace(\\n to_replace=\\\"I\\\\'ve visited Stack Overflow, but haven\\\\'t logged in/created an account\\\",\\n value='1',\\n inplace=True\\n)\\ndata['StackOverflowDescribes'].replace(\\n to_replace='I have created a CV or Developer Story on Stack Overflow',\\n value='3',\\n inplace=True\\n)\\ndata['StackOverflowDescribes'].replace(\\n to_replace='I\\\\'d never heard of Stack Overflow before today',\\n value='0',\\n inplace=True\\n)\\ndata['StackOverflowDescribes'].replace(\\n to_replace='I\\\\'ve heard of Stack Overflow, but have never visited',\\n value='0',\\n inplace=True\\n)\\ndata.StackOverflowDescribes.unique()\\ndata.StackOverflowFoundAnswer.unique()\\ndata['StackOverflowFoundAnswer'].replace(\\n to_replace='Haven\\\\'t done at all',\\n value='0',\\n inplace=True\\n)\\ndata.StackOverflowCopiedCode.unique()\\ndata['StackOverflowCopiedCode'].replace(\\n to_replace='Haven\\\\'t done at all',\\n value='0',\\n inplace=True\\n)\\n\\n\\ndata.StackOverflowJobListing.unique()\\ndata['StackOverflowJobListing'].replace(\\n to_replace='Haven\\\\'t done at all',\\n value='0',\\n inplace=True\\n)\\n\\ndata['StackOverflowJobListing'].replace(\\n to_replace='Haven\\\\'t done at all',\\n value='0',\\n inplace=True\\n)\\ndata.StackOverflowJobListing.unique()\\n#StackOverflowCompanyPage\\ndata['StackOverflowCompanyPage'].replace(\\n to_replace='Haven\\\\'t done at all',\\n value='0',\\n inplace=True\\n)\\ndata.StackOverflowCompanyPage.unique()\\n\\n#StackOverflowJobSearch\\ndata['StackOverflowJobSearch'].replace(\\n to_replace='Haven\\\\'t done at all',\\n value='0',\\n inplace=True\\n)\\ndata.StackOverflowJobSearch.unique()\\n#StackOverflowNewQuestion\\ndata['StackOverflowNewQuestion'].replace(\\n to_replace='Haven\\\\'t done at all',\\n value='0',\\n inplace=True\\n)\\ndata.StackOverflowNewQuestion.unique()\\n#StackOverflowAnswer\\n#StackOverflowMetaChat\\ndata['StackOverflowAnswer'].replace(\\n to_replace='Haven\\\\'t done at all',\\n value='0',\\n inplace=True\\n)\\ndata.StackOverflowMetaChat.unique()\\ndata['StackOverflowMetaChat'].replace(\\n to_replace='Haven\\\\'t done at all',\\n value='0',\\n inplace=True\\n)\\ndata.StackOverflowAnswer.unique()\\ndata.to_csv('SOformat.csv', sep=',', encoding='utf-8')\\ndata.to_csv('SOformat1.csv', sep=',')\\ndata.to_csv('SOformattab.csv', sep='\\\\t', encoding='utf-8')\\n\\ndata.StackOverflowAdsDistracting.unique()\\ndata.StackOverflowMakeMoney.unique()\\n\"\n }\n]"},"num_files":{"kind":"number","value":2,"string":"2"}}},{"rowIdx":2036,"cells":{"repo_name":{"kind":"string","value":"AlbertoDelLop/NextEra-Energy---WSMS-project"},"repo_url":{"kind":"string","value":"https://github.com/AlbertoDelLop/NextEra-Energy---WSMS-project"},"snapshot_id":{"kind":"string","value":"fa8a54cd44d96fd19420ccce6ff2642bd2233a3b"},"revision_id":{"kind":"string","value":"24c29c7e2b32059335203a3711f3d452c7156d67"},"directory_id":{"kind":"string","value":"398cd3f9b97646c328a181044f4fe4fd37c5f52e"},"branch_name":{"kind":"string","value":"refs/heads/main"},"visit_date":{"kind":"string","value":"2023-04-19T01:20:18.400595"},"revision_date":{"kind":"string","value":"2021-05-09T15:10:53"},"committer_date":{"kind":"string","value":"2021-05-09T15:10:53"},"github_id":{"kind":"number","value":365616898,"string":"365,616,898"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.7901430726051331,"alphanum_fraction":0.7901430726051331,"avg_line_length":26.34782600402832,"blob_id":"e56c73cdde9b9702863e73b250b0d5a9c4084d2f","content_id":"6296a6d7a8d784198e1c87a67e26ce2094618610","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":629,"license_type":"no_license","max_line_length":245,"num_lines":23,"path":"/README.md","repo_name":"AlbertoDelLop/NextEra-Energy---WSMS-project","src_encoding":"UTF-8","text":"# NextEra-Energy---WSMS-project\nWeb Scraping and Social Media Scraping project for Data Science Master's Studies in WNE University of Warsaw. This scraping project intends to extract some basic stock information from the Investor Relations portal of the NextEra Energy website.\n\nhttp://www.investor.nexteraenergy.com/\n\n## How to run scrapers:\n\n- Beautiful Soup\n\n\n- Scrapy\n\nIn terminal run the following commands:\n\nscrapy crawl crawler -o overview.csv(or preferred name for saving the output)\n\nscrapy crawl stock -o stock.csv (or preferred name for saving the output)\n\n- Selenium\n\nIn terminal run the command:\n\npython Selenium.py\n"},{"alpha_fraction":0.6583476662635803,"alphanum_fraction":0.6781411170959473,"avg_line_length":43.11538314819336,"blob_id":"915172b4e3522d7c74384a380d64289437311049","content_id":"66d3f46995338bef4f0d823a9dd8b01f6028e779","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":4648,"license_type":"no_license","max_line_length":134,"num_lines":104,"path":"/soup/soup.py","repo_name":"AlbertoDelLop/NextEra-Energy---WSMS-project","src_encoding":"UTF-8","text":" #NextEra energy\n#Extracting Company Overview\n#First of all, upload necessary packages\nimport time\nfrom urllib import request as re\nfrom bs4 import BeautifulSoup as BS\nimport pandas as pd\nimport requests\n# Then, open the page below in a browser of your choice.\nurl = 'http://www.investor.nexteraenergy.com'\nhtml = re.urlopen(url)\nbs = BS(html.read(), 'html.parser')\n\n\n# Beautiful Soup 'find' method allows to create list of tags by class:\nintro = bs.find('div', {'class': 'home-intro'}).get_text()\nprint(intro)\n\nintro=intro.split(sep='\\n')\nprint(type(intro))\nprint(intro[3])\n\n# Instead of displaying it one by one we might use list comprehension to put them into new list and pandas data frame:\n# The data can be put into data frame, later into .csv file.\noverview = {'Title': [intro[1]], 'Text': [intro[3]]}\n\nd = pd.DataFrame(overview)\n\nprint(d)\n# ################################################################################\n# # This part saves data to csv.\n# ################################################################################\nd.to_csv('overview.csv')\n\n # Extraction of Stock Chart Table\n\n\n# We download the code as before:\n#Changing the link for getting stock chart information\nurl = 'http://ir.tools.investis.com/Clients/(S(i350sggxfguad3cfd2icvazs))/us/nextera_energy_inc/SM8/Default.aspx?culture=en-US'\nhtml = re.urlopen(url)\nbs = BS(html.read(), 'html.parser')\n# Variables created is a list to store quotes\nISIN = []\nSymbol = []\nNumber_of_shares_Tota=[]\nMarket_Cap_Mn=[]\nBest_Bid=[]\nBest_offer=[]\nDay_Volume=[]\nDividend=[]\nLast_Close=[]\nOpen=[]\nDay_High=[]\nDay_Low=[]\n_52_Week_High=[]\n_52_Week_Low=[]\nDividend_yield=[]\n\n\n# Agent is any software that retrieves and presents Web content for end users.\n# it can be web browsers, media players, and plug-ins that help in retrieving, rendering and interacting with web content.\nagent = {\"User-Agent\":'Mozilla/5.0 (Windows NT 6.3; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/59.0.3071.115 Safari/537.36'}\n\nrqst_html= requests.get(url, headers=agent)\nhtml=rqst_html.text\ndata=BS(html, 'html.parser')\n\n#Here with find_all method using span and its attributes via indexes [0] I am getting the information.\n#Span id's are unique for each information this is why it is the best way to extract information with those id's.\n#There are some classes that are the same and I can't use it for getting the information I needed.\n#And this information that I get is appending to the quotes that I created to store\nISIN.append(data.find_all('span', attrs={'id':'snapShotBox_Instrument4'})[0].text)\nSymbol.append(data.find_all('span', attrs={'id':'snapShotBox_inst1'})[0].text)\nNumber_of_shares_Tota.append(data.find_all('span', attrs={'id':'snapShotBox_Instrument9'})[0].text)\nMarket_Cap_Mn.append(data.find_all('span', attrs={'id':'snapShotBox_marketcap2'})[0].text)\nBest_Bid.append(data.find_all('span', attrs={'id':'snapShotBox_Snapshot1'})[0].text)\nBest_offer.append(data.find_all('span', attrs={'id':'snapShotBox_Snapshot16'})[0].text)\nDay_Volume.append(data.find_all('span', attrs={'id':'snapShotBox_Snapshot11'})[0].text)\nDividend.append(data.find_all('span', attrs={'id':'snapShotBox_Dividend1'})[0].text)\nLast_Close.append(data.find_all('span', attrs={'id':'snapShotBox_Snapshot10'})[0].text)\nOpen.append(data.find_all('span', attrs={'id':'snapShotBox_Snapshot9'})[0].text)\nDay_High.append(data.find_all('span', attrs={'id':'snapShotBox_Snapshot13'})[0].text)\nDay_Low.append(data.find_all('span', attrs={'id':'snapShotBox_Snapshot14'})[0].text)\n_52_Week_High.append(data.find_all('span', attrs={'id':'snapShotBox_Snapshot17'})[0].text)\n_52_Week_Low.append(data.find_all('span', attrs={'id':'snapShotBox_Snapshot18'})[0].text)\nDividend_yield.append(data.find_all('span', attrs={'id':'snapShotBox_Dividend2'})[0].text)\n\n\n\n# Dataframe\n# I am creating dataframe with the main names in the table and giving them titles to make it clearer.\n# These names can be found in\nDF = pd.DataFrame({\"ISIN\": ISIN, \"Symbol\": Symbol, \"Number of shares - Total\": Number_of_shares_Tota,\n\t\"Market Cap\": Market_Cap_Mn, \"Best Bid\": Best_Bid, \"Best Offer\": Best_offer, \"Day Volume\": Day_Volume,\n \t\t\t\"Dividend\": Dividend,\"Last Close\":Last_Close, \"Open\": Open,\n \t\t\t\"Day High\": Day_High, \"Day Low\": Day_Low,\n \t\t\t\"52 Week High\": _52_Week_High, \"52 Week Low\": _52_Week_Low, \"Dividend Yield\": Dividend_yield})\n\n# save to StockChart\nDF.to_csv('StockChart.csv', header = True)\n\nstart = time.perf_counter()\nprint('\\nExecution time:',str(round(time.perf_counter() - start , 4))+'s') #execution time is 0 second\n"},{"alpha_fraction":0.5442337989807129,"alphanum_fraction":0.5570695400238037,"avg_line_length":38.17460250854492,"blob_id":"2297d7a6a8ce12167a0db6d822c1dd89d0582d46","content_id":"63467c94929207abb6420f50bb3b35499c51edf7","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":5066,"license_type":"no_license","max_line_length":144,"num_lines":126,"path":"/scrapy/scrapy_group_2/scrapy_group_2/spiders/scrapy_pr.py","repo_name":"AlbertoDelLop/NextEra-Energy---WSMS-project","src_encoding":"UTF-8","text":"# -*- coding: utf-8 -*-\r\nimport scrapy\r\nimport time\r\n\r\n\r\nstart = time.perf_counter()\r\n\r\n\r\n\r\n\r\n\r\nclass Overview(scrapy.Item):\r\n CompanyOverview = scrapy.Field()\r\n\r\n#creating spider named crawler and telling it to go to the following webpage\r\nclass OverviewSpider(scrapy.Spider):\r\n name = 'crawler'\r\n start_urls = ['http://www.investor.nexteraenergy.com/']\r\n\r\n#scraping the text from the assigned xpath\r\n def parse(self, response):\r\n p = Overview()\r\n p['CompanyOverview'] = response.xpath('//*[@id=\"contentwrapperinner\"]/div/div[1]/p/span/text()').getall()\r\n\r\n yield p\r\n\r\n\r\nclass StockTable(scrapy.Item):\r\n Stock_parameter = scrapy.Field()\r\n Value = scrapy.Field()\r\n\r\n#creating spider named stock and telling it to go to the following url\r\nclass StockSpider(scrapy.Spider):\r\n name = 'stock'\r\n start_urls = ['http://ir.tools.investis.com/Clients/(S(1odes4dttvfhicymklu3tcp3))/us/nextera_energy_inc/SM8/Default.aspx?culture=en-US']\r\n \r\n def parse(self, response):\r\n \r\n#the spider will extract information from the following xpath\r\n col1_xpath = '//div[re:test(@class, \"box share-information\")]//div[re:test(@class, \"col-one\")]//text()'\r\n selection = response.xpath(col1_xpath)\r\n col1=[] #creating an empty vector\r\n \r\n for s in selection: #removing all empty spaces from the scraped text\r\n if ('\\n' or '\\r') in s.getall()[0]:\r\n continue\r\n col1.append(s.getall()[0]) #appends to the empty vector every extracted element from the given xpath\r\n\r\n #the vector contains every text element separately, however we need for some elements to be together such as money symbol and value\r\n #let's fix the first vector\r\n\r\n s=0\r\n stockp=[]\r\n while (s<len(col1)):\r\n \r\n if (col1[s+1]==' / '): #appending the elements if there's '/'\r\n stockp.append([col1[s]+col1[s+1]+col1[s+2]])\r\n s = s+3\r\n else:\r\n stockp.append([col1[s]]) #if no '/' keep iterating\r\n s = s+1\r\n \r\n if s+1 == len(col1): #stop the while loop once the correct length is reached\r\n stockp.append([col1[s]])\r\n break\r\n\r\n# the spider will extract information from the following xpath\r\n \r\n col2_xpath = '//div[re:test(@class, \"box share-information\")]//div[re:test(@class, \"col-two\")]//text()'\r\n selection = response.xpath(col2_xpath)\r\n col2=[] #creating an empty vector\r\n \r\n for s in selection: #appending the scraped text without empty spaces\r\n if ('\\n' or '\\r') in s.getall()[0]:\r\n continue\r\n col2.append(s.getall()[0])\r\n \r\n#fixing the second vector\r\n\r\n s=0\r\n value=[] #empty vector that will contain the fixed data\r\n while (s<len(col2)):\r\n \r\n if (col2[s+1]==' / '):\r\n value.append([col2[s]+col2[s+1]+col2[s+2]]) #appending the elements if there's '/' and then moving to the next index\r\n s = s+3\r\n elif (col2[s]=='$'): #appending the elements if there's '$' and then moving to the next index\r\n value.append([col2[s]+col2[s+1]])\r\n s = s+2\r\n else: #keep iterating if none of the symbols are found\r\n value.append([col2[s]])\r\n s = s+1\r\n \r\n if s+1 >= len(col2): #stop while loop at reached length\r\n value.append([col2[s]])\r\n break\r\n \r\n\r\n #creating a table with two columns from the data\r\n d = StockTable()\r\n \r\n for data in range(14):\r\n d['Stock_parameter']=stockp[data]\r\n d['Value']=value[data]\r\n yield d\r\n\r\n\r\nprint('\\nExecution time:',str(round(time.perf_counter() - start , 4))+'s')\r\n\r\n#after running the first spider, i saved the output with overview.csv\r\n\r\n#the code below serves to read the saved file in order to check the most common words\r\n#uncomment it if this needs to be checked and eneter the path to the saved output\r\n\r\n\r\n#text = open('C:/Users/Dell/Desktop/pythonProject/scrapy_group_2/scrapy_group_2/overview.csv').read()\r\n#words = text.split() #spliting every word as separate elements\r\n#word_count = {}\r\n#for word in words:\r\n# count = word_count.get(word, 0) #counting the number of times the word appears\r\n# # the number is either the number of times we encountered the word, or 0 if we haven’t seen it yet\r\n# count += 1\r\n# word_count[word] = count #store the updated count into the dictionary\r\n# word_count_list = sorted(word_count, key=word_count.get, reverse=True) #sort the input and return a list\r\n# for word in word_count_list[:20]:\r\n# print(word, word_count[word]0)\r\n\r\n"},{"alpha_fraction":0.6723589897155762,"alphanum_fraction":0.6795075535774231,"avg_line_length":28.611764907836914,"blob_id":"7a99844d35af15c17416cd451deca29c4210c684","content_id":"1293e515dc9edea2686841963f6466a9424088f7","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":2518,"license_type":"no_license","max_line_length":127,"num_lines":85,"path":"/selenium/Selenium.py","repo_name":"AlbertoDelLop/NextEra-Energy---WSMS-project","src_encoding":"UTF-8","text":"from selenium import webdriver\nimport time\nimport pandas as pd\n\nstart = time.perf_counter()\n\ngecko_path = '/usr/local/bin/geckodriver'\nurl = 'http://www.investor.nexteraenergy.com/'\n\noptions = webdriver.firefox.options.Options()\noptions.headless = False\n\ndriver = webdriver.Firefox(options = options, executable_path = gecko_path)\n\n# Actual program:\ndriver.get(url)\ntime.sleep(2)\n\n\n#Extract the information from overview site\nintro = driver.find_element_by_xpath('/html/body/form/div[3]/div[5]/div/div/div/div[1]').text\nintro = intro.split(sep='\\n') #divides the elements in a vector\n\nprint(\"************************************\")\n\nd = pd.DataFrame({'Title':[intro[0]],'Text':[intro[2]]}) #Adds the title and the main text in a dataframe from the vector intro\nprint(d)\nd.to_csv('overview.csv') #Saves it in a .csv file\n\nprint(\"************************************\")\ntime.sleep(2)\n\n\n#click and change to the Stock Information section\nstock = driver.find_element_by_xpath('//*[@id=\"secondnav-nav-stock-information-level1\"]')\nstock.click()\n\ntime.sleep(2)\n\n\n# It's necessary to switch to the iframe because the next information we want to extract is in there\ndriver.switch_to.frame(driver.find_element_by_id(\"ExternalWebContentExternalIFrame\"))\n\n#The information is hidden so it is necessary to click the button 'Show more' in order to extract it\nshowmore = driver.find_element_by_xpath('/html/body/form/div[3]/div[2]/div/a')\nshowmore.click()\n\ntime.sleep(2)\n\n\n#Etract the data from the two columns of the data\nstockp = driver.find_elements_by_xpath('//*[@id=\"upSnapshot\"]//*[@class=\"col-one\" or @class=\"col-one share_in_issue\"]')\nvalues = driver.find_elements_by_xpath('//*[@id=\"upSnapshot\"]//*[@class=\"col-two\"]')\n\nprint(\"************************************\")\n\nprint('Stock parameters\\n')\nprint(len(stockp))\n#print(stockp)\nStockp=[]\nfor data in stockp:\n print(data.text)\n Stockp.append(data.text) #Creates a vector with the names of the stock parameters from column 1\n\nprint('Values\\n')\nprint(len(values))\n#print(values)\nValues=[]\nfor data in values:\n print(data.text)\n Values.append(data.text) #Creates a vector with the values of the stock parameters from column 2\n\nd = pd.DataFrame({'Stock parameter':Stockp,'Value':Values}) #Creates a dataframe with the table\nprint('\\n',d)\nd.to_csv('Stock output.csv') #Saves it in a .csv file\n\nprint(\"************************************\")\n\n\ntime.sleep(5)\n\n# Close browser:\ndriver.quit()\n\nprint('\\nExecution time:',str(round(time.perf_counter() - start - 13, 4))+'s')\n\n"}],"string":"[\n {\n \"alpha_fraction\": 0.7901430726051331,\n \"alphanum_fraction\": 0.7901430726051331,\n \"avg_line_length\": 26.34782600402832,\n \"blob_id\": \"e56c73cdde9b9702863e73b250b0d5a9c4084d2f\",\n \"content_id\": \"6296a6d7a8d784198e1c87a67e26ce2094618610\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 629,\n \"license_type\": \"no_license\",\n \"max_line_length\": 245,\n \"num_lines\": 23,\n \"path\": \"/README.md\",\n \"repo_name\": \"AlbertoDelLop/NextEra-Energy---WSMS-project\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# NextEra-Energy---WSMS-project\\nWeb Scraping and Social Media Scraping project for Data Science Master's Studies in WNE University of Warsaw. This scraping project intends to extract some basic stock information from the Investor Relations portal of the NextEra Energy website.\\n\\nhttp://www.investor.nexteraenergy.com/\\n\\n## How to run scrapers:\\n\\n- Beautiful Soup\\n\\n\\n- Scrapy\\n\\nIn terminal run the following commands:\\n\\nscrapy crawl crawler -o overview.csv(or preferred name for saving the output)\\n\\nscrapy crawl stock -o stock.csv (or preferred name for saving the output)\\n\\n- Selenium\\n\\nIn terminal run the command:\\n\\npython Selenium.py\\n\"\n },\n {\n \"alpha_fraction\": 0.6583476662635803,\n \"alphanum_fraction\": 0.6781411170959473,\n \"avg_line_length\": 43.11538314819336,\n \"blob_id\": \"915172b4e3522d7c74384a380d64289437311049\",\n \"content_id\": \"66d3f46995338bef4f0d823a9dd8b01f6028e779\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 4648,\n \"license_type\": \"no_license\",\n \"max_line_length\": 134,\n \"num_lines\": 104,\n \"path\": \"/soup/soup.py\",\n \"repo_name\": \"AlbertoDelLop/NextEra-Energy---WSMS-project\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \" #NextEra energy\\n#Extracting Company Overview\\n#First of all, upload necessary packages\\nimport time\\nfrom urllib import request as re\\nfrom bs4 import BeautifulSoup as BS\\nimport pandas as pd\\nimport requests\\n# Then, open the page below in a browser of your choice.\\nurl = 'http://www.investor.nexteraenergy.com'\\nhtml = re.urlopen(url)\\nbs = BS(html.read(), 'html.parser')\\n\\n\\n# Beautiful Soup 'find' method allows to create list of tags by class:\\nintro = bs.find('div', {'class': 'home-intro'}).get_text()\\nprint(intro)\\n\\nintro=intro.split(sep='\\\\n')\\nprint(type(intro))\\nprint(intro[3])\\n\\n# Instead of displaying it one by one we might use list comprehension to put them into new list and pandas data frame:\\n# The data can be put into data frame, later into .csv file.\\noverview = {'Title': [intro[1]], 'Text': [intro[3]]}\\n\\nd = pd.DataFrame(overview)\\n\\nprint(d)\\n# ################################################################################\\n# # This part saves data to csv.\\n# ################################################################################\\nd.to_csv('overview.csv')\\n\\n # Extraction of Stock Chart Table\\n\\n\\n# We download the code as before:\\n#Changing the link for getting stock chart information\\nurl = 'http://ir.tools.investis.com/Clients/(S(i350sggxfguad3cfd2icvazs))/us/nextera_energy_inc/SM8/Default.aspx?culture=en-US'\\nhtml = re.urlopen(url)\\nbs = BS(html.read(), 'html.parser')\\n# Variables created is a list to store quotes\\nISIN = []\\nSymbol = []\\nNumber_of_shares_Tota=[]\\nMarket_Cap_Mn=[]\\nBest_Bid=[]\\nBest_offer=[]\\nDay_Volume=[]\\nDividend=[]\\nLast_Close=[]\\nOpen=[]\\nDay_High=[]\\nDay_Low=[]\\n_52_Week_High=[]\\n_52_Week_Low=[]\\nDividend_yield=[]\\n\\n\\n# Agent is any software that retrieves and presents Web content for end users.\\n# it can be web browsers, media players, and plug-ins that help in retrieving, rendering and interacting with web content.\\nagent = {\\\"User-Agent\\\":'Mozilla/5.0 (Windows NT 6.3; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/59.0.3071.115 Safari/537.36'}\\n\\nrqst_html= requests.get(url, headers=agent)\\nhtml=rqst_html.text\\ndata=BS(html, 'html.parser')\\n\\n#Here with find_all method using span and its attributes via indexes [0] I am getting the information.\\n#Span id's are unique for each information this is why it is the best way to extract information with those id's.\\n#There are some classes that are the same and I can't use it for getting the information I needed.\\n#And this information that I get is appending to the quotes that I created to store\\nISIN.append(data.find_all('span', attrs={'id':'snapShotBox_Instrument4'})[0].text)\\nSymbol.append(data.find_all('span', attrs={'id':'snapShotBox_inst1'})[0].text)\\nNumber_of_shares_Tota.append(data.find_all('span', attrs={'id':'snapShotBox_Instrument9'})[0].text)\\nMarket_Cap_Mn.append(data.find_all('span', attrs={'id':'snapShotBox_marketcap2'})[0].text)\\nBest_Bid.append(data.find_all('span', attrs={'id':'snapShotBox_Snapshot1'})[0].text)\\nBest_offer.append(data.find_all('span', attrs={'id':'snapShotBox_Snapshot16'})[0].text)\\nDay_Volume.append(data.find_all('span', attrs={'id':'snapShotBox_Snapshot11'})[0].text)\\nDividend.append(data.find_all('span', attrs={'id':'snapShotBox_Dividend1'})[0].text)\\nLast_Close.append(data.find_all('span', attrs={'id':'snapShotBox_Snapshot10'})[0].text)\\nOpen.append(data.find_all('span', attrs={'id':'snapShotBox_Snapshot9'})[0].text)\\nDay_High.append(data.find_all('span', attrs={'id':'snapShotBox_Snapshot13'})[0].text)\\nDay_Low.append(data.find_all('span', attrs={'id':'snapShotBox_Snapshot14'})[0].text)\\n_52_Week_High.append(data.find_all('span', attrs={'id':'snapShotBox_Snapshot17'})[0].text)\\n_52_Week_Low.append(data.find_all('span', attrs={'id':'snapShotBox_Snapshot18'})[0].text)\\nDividend_yield.append(data.find_all('span', attrs={'id':'snapShotBox_Dividend2'})[0].text)\\n\\n\\n\\n# Dataframe\\n# I am creating dataframe with the main names in the table and giving them titles to make it clearer.\\n# These names can be found in\\nDF = pd.DataFrame({\\\"ISIN\\\": ISIN, \\\"Symbol\\\": Symbol, \\\"Number of shares - Total\\\": Number_of_shares_Tota,\\n\\t\\\"Market Cap\\\": Market_Cap_Mn, \\\"Best Bid\\\": Best_Bid, \\\"Best Offer\\\": Best_offer, \\\"Day Volume\\\": Day_Volume,\\n \\t\\t\\t\\\"Dividend\\\": Dividend,\\\"Last Close\\\":Last_Close, \\\"Open\\\": Open,\\n \\t\\t\\t\\\"Day High\\\": Day_High, \\\"Day Low\\\": Day_Low,\\n \\t\\t\\t\\\"52 Week High\\\": _52_Week_High, \\\"52 Week Low\\\": _52_Week_Low, \\\"Dividend Yield\\\": Dividend_yield})\\n\\n# save to StockChart\\nDF.to_csv('StockChart.csv', header = True)\\n\\nstart = time.perf_counter()\\nprint('\\\\nExecution time:',str(round(time.perf_counter() - start , 4))+'s') #execution time is 0 second\\n\"\n },\n {\n \"alpha_fraction\": 0.5442337989807129,\n \"alphanum_fraction\": 0.5570695400238037,\n \"avg_line_length\": 38.17460250854492,\n \"blob_id\": \"2297d7a6a8ce12167a0db6d822c1dd89d0582d46\",\n \"content_id\": \"63467c94929207abb6420f50bb3b35499c51edf7\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 5066,\n \"license_type\": \"no_license\",\n \"max_line_length\": 144,\n \"num_lines\": 126,\n \"path\": \"/scrapy/scrapy_group_2/scrapy_group_2/spiders/scrapy_pr.py\",\n \"repo_name\": \"AlbertoDelLop/NextEra-Energy---WSMS-project\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: utf-8 -*-\\r\\nimport scrapy\\r\\nimport time\\r\\n\\r\\n\\r\\nstart = time.perf_counter()\\r\\n\\r\\n\\r\\n\\r\\n\\r\\n\\r\\nclass Overview(scrapy.Item):\\r\\n CompanyOverview = scrapy.Field()\\r\\n\\r\\n#creating spider named crawler and telling it to go to the following webpage\\r\\nclass OverviewSpider(scrapy.Spider):\\r\\n name = 'crawler'\\r\\n start_urls = ['http://www.investor.nexteraenergy.com/']\\r\\n\\r\\n#scraping the text from the assigned xpath\\r\\n def parse(self, response):\\r\\n p = Overview()\\r\\n p['CompanyOverview'] = response.xpath('//*[@id=\\\"contentwrapperinner\\\"]/div/div[1]/p/span/text()').getall()\\r\\n\\r\\n yield p\\r\\n\\r\\n\\r\\nclass StockTable(scrapy.Item):\\r\\n Stock_parameter = scrapy.Field()\\r\\n Value = scrapy.Field()\\r\\n\\r\\n#creating spider named stock and telling it to go to the following url\\r\\nclass StockSpider(scrapy.Spider):\\r\\n name = 'stock'\\r\\n start_urls = ['http://ir.tools.investis.com/Clients/(S(1odes4dttvfhicymklu3tcp3))/us/nextera_energy_inc/SM8/Default.aspx?culture=en-US']\\r\\n \\r\\n def parse(self, response):\\r\\n \\r\\n#the spider will extract information from the following xpath\\r\\n col1_xpath = '//div[re:test(@class, \\\"box share-information\\\")]//div[re:test(@class, \\\"col-one\\\")]//text()'\\r\\n selection = response.xpath(col1_xpath)\\r\\n col1=[] #creating an empty vector\\r\\n \\r\\n for s in selection: #removing all empty spaces from the scraped text\\r\\n if ('\\\\n' or '\\\\r') in s.getall()[0]:\\r\\n continue\\r\\n col1.append(s.getall()[0]) #appends to the empty vector every extracted element from the given xpath\\r\\n\\r\\n #the vector contains every text element separately, however we need for some elements to be together such as money symbol and value\\r\\n #let's fix the first vector\\r\\n\\r\\n s=0\\r\\n stockp=[]\\r\\n while (s<len(col1)):\\r\\n \\r\\n if (col1[s+1]==' / '): #appending the elements if there's '/'\\r\\n stockp.append([col1[s]+col1[s+1]+col1[s+2]])\\r\\n s = s+3\\r\\n else:\\r\\n stockp.append([col1[s]]) #if no '/' keep iterating\\r\\n s = s+1\\r\\n \\r\\n if s+1 == len(col1): #stop the while loop once the correct length is reached\\r\\n stockp.append([col1[s]])\\r\\n break\\r\\n\\r\\n# the spider will extract information from the following xpath\\r\\n \\r\\n col2_xpath = '//div[re:test(@class, \\\"box share-information\\\")]//div[re:test(@class, \\\"col-two\\\")]//text()'\\r\\n selection = response.xpath(col2_xpath)\\r\\n col2=[] #creating an empty vector\\r\\n \\r\\n for s in selection: #appending the scraped text without empty spaces\\r\\n if ('\\\\n' or '\\\\r') in s.getall()[0]:\\r\\n continue\\r\\n col2.append(s.getall()[0])\\r\\n \\r\\n#fixing the second vector\\r\\n\\r\\n s=0\\r\\n value=[] #empty vector that will contain the fixed data\\r\\n while (s<len(col2)):\\r\\n \\r\\n if (col2[s+1]==' / '):\\r\\n value.append([col2[s]+col2[s+1]+col2[s+2]]) #appending the elements if there's '/' and then moving to the next index\\r\\n s = s+3\\r\\n elif (col2[s]=='$'): #appending the elements if there's '$' and then moving to the next index\\r\\n value.append([col2[s]+col2[s+1]])\\r\\n s = s+2\\r\\n else: #keep iterating if none of the symbols are found\\r\\n value.append([col2[s]])\\r\\n s = s+1\\r\\n \\r\\n if s+1 >= len(col2): #stop while loop at reached length\\r\\n value.append([col2[s]])\\r\\n break\\r\\n \\r\\n\\r\\n #creating a table with two columns from the data\\r\\n d = StockTable()\\r\\n \\r\\n for data in range(14):\\r\\n d['Stock_parameter']=stockp[data]\\r\\n d['Value']=value[data]\\r\\n yield d\\r\\n\\r\\n\\r\\nprint('\\\\nExecution time:',str(round(time.perf_counter() - start , 4))+'s')\\r\\n\\r\\n#after running the first spider, i saved the output with overview.csv\\r\\n\\r\\n#the code below serves to read the saved file in order to check the most common words\\r\\n#uncomment it if this needs to be checked and eneter the path to the saved output\\r\\n\\r\\n\\r\\n#text = open('C:/Users/Dell/Desktop/pythonProject/scrapy_group_2/scrapy_group_2/overview.csv').read()\\r\\n#words = text.split() #spliting every word as separate elements\\r\\n#word_count = {}\\r\\n#for word in words:\\r\\n# count = word_count.get(word, 0) #counting the number of times the word appears\\r\\n# # the number is either the number of times we encountered the word, or 0 if we haven’t seen it yet\\r\\n# count += 1\\r\\n# word_count[word] = count #store the updated count into the dictionary\\r\\n# word_count_list = sorted(word_count, key=word_count.get, reverse=True) #sort the input and return a list\\r\\n# for word in word_count_list[:20]:\\r\\n# print(word, word_count[word]0)\\r\\n\\r\\n\"\n },\n {\n \"alpha_fraction\": 0.6723589897155762,\n \"alphanum_fraction\": 0.6795075535774231,\n \"avg_line_length\": 28.611764907836914,\n \"blob_id\": \"7a99844d35af15c17416cd451deca29c4210c684\",\n \"content_id\": \"1293e515dc9edea2686841963f6466a9424088f7\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 2518,\n \"license_type\": \"no_license\",\n \"max_line_length\": 127,\n \"num_lines\": 85,\n \"path\": \"/selenium/Selenium.py\",\n \"repo_name\": \"AlbertoDelLop/NextEra-Energy---WSMS-project\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from selenium import webdriver\\nimport time\\nimport pandas as pd\\n\\nstart = time.perf_counter()\\n\\ngecko_path = '/usr/local/bin/geckodriver'\\nurl = 'http://www.investor.nexteraenergy.com/'\\n\\noptions = webdriver.firefox.options.Options()\\noptions.headless = False\\n\\ndriver = webdriver.Firefox(options = options, executable_path = gecko_path)\\n\\n# Actual program:\\ndriver.get(url)\\ntime.sleep(2)\\n\\n\\n#Extract the information from overview site\\nintro = driver.find_element_by_xpath('/html/body/form/div[3]/div[5]/div/div/div/div[1]').text\\nintro = intro.split(sep='\\\\n') #divides the elements in a vector\\n\\nprint(\\\"************************************\\\")\\n\\nd = pd.DataFrame({'Title':[intro[0]],'Text':[intro[2]]}) #Adds the title and the main text in a dataframe from the vector intro\\nprint(d)\\nd.to_csv('overview.csv') #Saves it in a .csv file\\n\\nprint(\\\"************************************\\\")\\ntime.sleep(2)\\n\\n\\n#click and change to the Stock Information section\\nstock = driver.find_element_by_xpath('//*[@id=\\\"secondnav-nav-stock-information-level1\\\"]')\\nstock.click()\\n\\ntime.sleep(2)\\n\\n\\n# It's necessary to switch to the iframe because the next information we want to extract is in there\\ndriver.switch_to.frame(driver.find_element_by_id(\\\"ExternalWebContentExternalIFrame\\\"))\\n\\n#The information is hidden so it is necessary to click the button 'Show more' in order to extract it\\nshowmore = driver.find_element_by_xpath('/html/body/form/div[3]/div[2]/div/a')\\nshowmore.click()\\n\\ntime.sleep(2)\\n\\n\\n#Etract the data from the two columns of the data\\nstockp = driver.find_elements_by_xpath('//*[@id=\\\"upSnapshot\\\"]//*[@class=\\\"col-one\\\" or @class=\\\"col-one share_in_issue\\\"]')\\nvalues = driver.find_elements_by_xpath('//*[@id=\\\"upSnapshot\\\"]//*[@class=\\\"col-two\\\"]')\\n\\nprint(\\\"************************************\\\")\\n\\nprint('Stock parameters\\\\n')\\nprint(len(stockp))\\n#print(stockp)\\nStockp=[]\\nfor data in stockp:\\n print(data.text)\\n Stockp.append(data.text) #Creates a vector with the names of the stock parameters from column 1\\n\\nprint('Values\\\\n')\\nprint(len(values))\\n#print(values)\\nValues=[]\\nfor data in values:\\n print(data.text)\\n Values.append(data.text) #Creates a vector with the values of the stock parameters from column 2\\n\\nd = pd.DataFrame({'Stock parameter':Stockp,'Value':Values}) #Creates a dataframe with the table\\nprint('\\\\n',d)\\nd.to_csv('Stock output.csv') #Saves it in a .csv file\\n\\nprint(\\\"************************************\\\")\\n\\n\\ntime.sleep(5)\\n\\n# Close browser:\\ndriver.quit()\\n\\nprint('\\\\nExecution time:',str(round(time.perf_counter() - start - 13, 4))+'s')\\n\\n\"\n }\n]"},"num_files":{"kind":"number","value":4,"string":"4"}}},{"rowIdx":2037,"cells":{"repo_name":{"kind":"string","value":"KiboNaku/dice_simulator"},"repo_url":{"kind":"string","value":"https://github.com/KiboNaku/dice_simulator"},"snapshot_id":{"kind":"string","value":"23f9e74df051cb2bb2b018eb131156b97d9c23b9"},"revision_id":{"kind":"string","value":"6af753822816ad5d0f4e226f16a8c21a7c9b51d5"},"directory_id":{"kind":"string","value":"4611f362e5dfce18d662a27c47500085ac22fdfa"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"string","value":"2020-06-23T01:56:09.820875"},"revision_date":{"kind":"string","value":"2019-07-30T01:13:44"},"committer_date":{"kind":"string","value":"2019-07-30T01:13:44"},"github_id":{"kind":"number","value":198467367,"string":"198,467,367"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.5991674065589905,"alphanum_fraction":0.6037020683288574,"avg_line_length":29.09395980834961,"blob_id":"f0a66d8a18f1371b1336e8b51a8699c92e34cd6f","content_id":"22d2204fb61deda59080742453b3e183d6e2ef37","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":13452,"license_type":"no_license","max_line_length":120,"num_lines":447,"path":"/dice_roller.py","repo_name":"KiboNaku/dice_simulator","src_encoding":"UTF-8","text":"import pickle\nimport sys\nfrom os import path, makedirs\nfrom random import randrange as rand\n\nimport math\n\n\nclass Die:\n\n \"\"\"\"\n Class used to simulate rolling of a die.\n\n :param values: values on the die (each value represents a \"face\").\n :type values: sequence of any\n :param name: value used to identify the die. If no value is specified, name is defaulted to \"generic die\",\n meaning all unnamed dice will have the same name (NOT recommended).\n :type name: str\n \"\"\"\n\n def __init__(self, values, name=\"generic die\"):\n self._values = values\n self.name = name\n\n def roll(self):\n \"\"\"\n Simulates a single die roll.\n\n :returns: the value rolled.\n :rtype: type contained in self._values\n \"\"\"\n return self._values[rand(len(self._values))]\n\n def roll_multiple(self, times):\n \"\"\"\n Simulates a specified number of die rolls.\n\n :param times: number of times to roll the die.\n :type times: int\n\n :return: a list of the the roll results.\n :rtype: list of type contained in self._values\n \"\"\"\n rolls = []\n for _ in range(times):\n rolls.append(self.roll())\n return rolls\n\n def get_values(self):\n \"\"\"\n :return: a separate copy of the self._values.\n :rtype: list\n \"\"\"\n return list(self._values)\n\n\nclass NumericalDie (Die):\n\n \"\"\"\"\n Class used to simulate numerical die. Allows for mathematical operations.\n\n :param num_values: numerical values on the die.\n :type num_values: sequence of int\n :param name: defaults to \"numerical die\"\n :type name: str\n \"\"\"\n\n def __init__(self, num_values, name=\"numerical die\"):\n \"\"\"\n :raises: \"ValueError\": a value in the sequence passed is not of int type.\n \"\"\"\n for num in num_values:\n if type(num) is not int:\n raise ValueError(\"Each of the value passed to the NumericalDie must be an integer value.\")\n super().__init__(num_values, name)\n\n def roll_multiple(self, times):\n \"\"\"\n Simulates a specified number of die rolls. Overrides the super().roll_multiple(self, times) method by\n also returning additional values (mathematical calculations).\n Additional Values: sum, average, max, min.\n\n :param times: number of times to roll the die.\n :type times: int\n\n :return: a list of the the roll results, additional numerical calculations.\n :rtype: tuple of (list, tuple of (float, float, float, float))\n \"\"\"\n rolls = super().roll_multiple(times)\n return rolls, NumericalDie._additional_values(rolls)\n\n @staticmethod\n def _additional_values(rolls):\n \"\"\"\n Returns additional mathematical calculations for the rolls passed: sum, average, max, min.\n\n :param rolls: a list of the rolls.\n :type rolls: list\n\n :return: additional mathematical calculations: (sum, average, max, min).\n :rtype: tuple\n \"\"\"\n return NumericalDie._sum(rolls), NumericalDie._average(rolls), \\\n NumericalDie._max(rolls), NumericalDie._min(rolls)\n\n @staticmethod\n def _sum(rolls):\n \"\"\"\n :param rolls: list of the dice rolls.\n :type rolls: list\n\n :return: sum of the values.\n :rtype: int\n \"\"\"\n return sum(rolls)\n\n @staticmethod\n def _average(rolls):\n \"\"\"\n :param rolls: list of the dice rolls.\n :type rolls: list\n\n :return: average of the values.\n :rtype: double\n \"\"\"\n return NumericalDie._sum(rolls) / len(rolls)\n\n @staticmethod\n def _max(rolls):\n \"\"\"\n :param rolls: list of the dice rolls.\n :type rolls: list\n\n :return: max of the values.\n :rtype: int\n \"\"\"\n return max(rolls)\n\n @staticmethod\n def _min(rolls):\n \"\"\"\n :param rolls: list of the dice rolls.\n :type rolls: list\n\n :return: min of the values.\n :rtype: int\n \"\"\"\n return min(rolls)\n\n\nclass ClassicDie (NumericalDie):\n \"\"\"\"\n Simplified version of NumericalDie with values ranging from 1 to the specified max.\n\n :param max_val: the max values on the die. Example: enter 6 to create a die with values from 1 to 6.\n :type max_val: int\n :param name: defaults to \"classical die\"\n :type name: str\n \"\"\"\n\n def __init__(self, max_val, name=\"classical die\"):\n super().__init__(range(0, max_val + 1), name)\n\n\n# constants\n_back = \"back\"\n_user_dir = \"userdata\"\n_dice_file = \"custom_dice.pickle\"\n_file_path = path.join(_user_dir, _dice_file)\n\n# holds all of the dice\n_all_dice = [Die(ClassicDie(spots, \"D{}\".format(spots))) for spots in [4, 6, 8, 10, 12, 20]]\n\n\ndef _print_die_values(die_obj):\n \"\"\"Prints out all of the potential values of the die in a table format with \"Potential Value\" heading.\"\"\"\n print(\"Potential values:\")\n _print_table(die_obj.get_values())\n\n\ndef _print_die_summary(die_obj):\n \"\"\"\n Prints out simple summary of the die.\n Name: (name)\n Potential Values:\n (values in table format)\n \"\"\"\n print(\"Name:\\t{}\".format(die_obj.name))\n _print_die_values(die_obj)\n\n\ndef _print_table(values, columns=5, padding=4):\n \"\"\"\n Prints a list of values in table format.\n\n :param values: values to print.\n :type values: list\n :param columns: number of columns. Defaults to 5.\n :type columns: int\n :param padding: padding for each column (padded on the left)\n :type padding: int\n \"\"\"\n val_len = len(values)\n\n # width is padding + length of the longest value.\n i_width = padding + len(str(val_len))\n v_width = padding + max([len(str(val)) for val in values])\n\n # printing the values in rows\n for row in range(int(math.ceil(val_len/columns))):\n num_index = row + columns\n num_rolls = values[row:num_index]\n print(' '.join(\"{:{i_width}}. {:{v_width}}\\t\"\n .format(columns * row + roll_index + 1, num_rolls[roll_index], i_width=i_width, v_width=v_width)\n for roll_index in range(len(num_rolls))))\n\n\ndef _print_rolls(die_obj, rolls_list, other_info=None):\n \"\"\"\n Prints the dice rolls with additional information.\n\n :param die_obj: the die object that was rolled.\n :type die_obj: Die\n :param rolls_list: list of the rolls.\n :type rolls_list: list\n :param other_info: additional info to display (eg the mathematical calculations returned by NumericalDie).\n if not specified, nothing is printed for this.\n :type other_info: list or tuple\n \"\"\"\n\n # the main info\n print()\n _print_die_values(die_obj)\n _print_table(rolls_list)\n\n # the mathematical info\n other_labels = [\"sum\", \"avg\", \"max\", \"min\"]\n if other_info is not None:\n print(\"\\nsimple results:\\n\", \"\\n\".join(\"\\t{}:\\t{}\"\n .format(other_labels[i], other_info[i]) for i in range(len(other_info))))\n\n # the frequency at which each value was rolled\n print(\"\\nfrequency of each value:\")\n print(\"\\n\".join(\"\\t{}:\\t{}\".format(val, rolls_list.count(val)) for val in die_obj.get_values()))\n\n _print_menu_die()\n\n\n# below are the \"menu methods\" used to help users navigate and perform what they want.\n\ndef _menu_input(input_min, input_max):\n \"\"\"\n Simple method used to request a numerical input or the back command which takes them back to the previous menu.\n\n :param input_min: the minimum integer that can be accepted.\n :type input_min: int\n :param input_max: the maximum integer that can be accepted.\n :type input_max: int\n\n :return: the numerical input or \"back\"\n :rtype: int or str\n \"\"\"\n input_error = \"Integer Input Error:\"\n input_val = input()\n try:\n input_int = int(input_val)\n except ValueError:\n if input_val.lower() == _back:\n return _back\n else:\n if input_min <= input_int <= input_max:\n return input_int\n print(input_error, \"invalid input.\")\n return _menu_input(input_min, input_max)\n\n\ndef _print_menu(*options, back_string=\"previous menu\"):\n \"\"\"\n Simple function used to print a basic menu.\n\n :param options: tuple arguments that contain the menu options.\n :type options: tuple of (str, any) where str is what will be displayed to the user as the option and any is what\n will be returned if the option is chosen.\n :param back_string: option printed for the \"back command\". If nothing is specified, \"previous menu\" will be used.\n :type back_string: str\n\n :return: the option chosen.\n :rtype: any (what is contained in the option tuple)\n \"\"\"\n option_format = \"{:<8}{}\"\n options_size = len(options)\n\n # prints heading: \"INPUT OPTION\"\n print(option_format.format(\"INPUT\", \"OPTION\") + \"\\n\")\n\n # prints the options for the menu\n print(\"\\n\".join(option_format.format(i + 1, options[i][0]) for i in range(options_size)))\n print(option_format.format(_back, back_string))\n print(\"\\n\")\n\n menu_option = _menu_input(1, options_size)\n return None if menu_option == _back else options[menu_option - 1][1]\n\n\ndef _print_menu_main():\n \"\"\"\"\n The first menu: choose die or exit.\n \"\"\"\n print(\"\\nDice Roll Simulator\")\n main_menu_input = _print_menu((\"choose die\", _print_menu_die), back_string=\"exit app\")\n\n if main_menu_input is None:\n return\n\n return main_menu_input()\n\n\ndef _print_menu_die():\n \"\"\"\n Second menu: choose die or create custom die.\n \"\"\"\n print(\"\\n\")\n print(\"Please choose of the following dice:\")\n selected_die = _print_menu(*[(dice.name, dice) for dice in _all_dice], (\"create custom die\", create_custom_die))\n if selected_die is None:\n return _print_menu_main()\n elif isinstance(selected_die, Die):\n return _print_menu_roll(selected_die)\n else:\n create_custom_die()\n return _print_menu_die()\n\n\ndef create_custom_die():\n \"\"\"simple menu used to create a custom die and write to file.\"\"\"\n custom_die = custom_numerical_die()\n _print_die_summary(custom_die)\n while True:\n verify_die = input(\"\\n\\ncontinue with these values? y or n\\n\").lower()\n if verify_die == \"n\":\n return create_custom_die()\n elif verify_die == \"y\":\n break\n print(\"Please enter y or n\")\n with open(_file_path, \"ab\") as dice_file:\n pickle.dump(custom_die, dice_file)\n _all_dice.append(custom_die)\n\n\ndef custom_numerical_die():\n \"\"\"\n ask user to input values and create the custom die.\n\n :return: the custom die the user specified.\n :rtype: NumericalDie\n \"\"\"\n print(\"Please enter a list of numerical values separated by commas (spaces ok).\")\n print(\"Example 1: '1,2,3,4,5,6,7' --> [1,2,3,4,5,6,7]\")\n print(\"Example 2: '1, 2 , 3, 4, 5, 6, 7' --> [1,2,3,4,5,6,7]\\n\")\n values_input = input().replace(\" \", \"\").split(',')\n num_values = []\n invalid_values = []\n for val in values_input:\n try:\n num_values.append(int(val))\n except ValueError:\n invalid_values.append(val)\n if len(num_values) > 0:\n print(\"Values added to die: \")\n _print_table(num_values)\n else:\n print(\"No values was added to die.\\nTry again\")\n return custom_numerical_die()\n if len(invalid_values) > 0:\n print(\"Invalid values that failed to add: \")\n _print_table(invalid_values)\n else:\n print(\"All values was added properly\")\n name = input(\"Please enter a name for the die:\\n\")\n return NumericalDie(num_values, name)\n\n\ndef _print_menu_roll(current_die):\n \"\"\"\n User specifies the number of rolls to roll. If successful, the rolls are printed and they are brought back to\n the _print_menu_die().\n\n :param current_die: the die used to roll.\n :type current_die: Die\n \"\"\"\n _print_die_values(current_die)\n\n while True:\n print(\"how many times? ({} to {} times)\\n\"\n \"enter {} to go back\".format(1, sys.maxsize, _back))\n\n num_input = _menu_input(1, sys.maxsize)\n try:\n num_rolls = int(num_input)\n break\n except TypeError:\n if num_input == _back:\n return _print_menu_die()\n print(\"Invalid value.\")\n\n rolls = current_die.roll_multiple(num_rolls)\n if rolls is None:\n print(\"sorry something unexpected happened with the rolls.\\n\"\n \"please try again\\n\")\n return _print_menu_roll(current_die)\n return _print_rolls(current_die, rolls[0], rolls[1])\n\n\n# initialization methods\n\ndef run():\n \"\"\"used to run the program from start to finish\"\"\"\n _create_user_dir_file()\n _load_saved_dice()\n _print_menu_main()\n print(\"closing app...\")\n\n\ndef _create_user_dir_file():\n \"\"\"creates the directory for storing the custom dice if doesn't already exist.\"\"\"\n if not path.isfile(_file_path):\n try:\n open(_file_path, 'r')\n except IOError:\n open(_file_path, 'w')\n\n if not path.exists(_user_dir):\n makedirs(_user_dir)\n\n\ndef _load_saved_dice():\n \"\"\"loads the custom die that have been saved and appends them to all_dice\"\"\"\n with open(_file_path, \"rb\") as dice_file:\n while True:\n try:\n _all_dice.append(pickle.load(dice_file))\n except EOFError:\n break\n\n\nif __name__ == \"__main__\":\n run()\n"}],"string":"[\n {\n \"alpha_fraction\": 0.5991674065589905,\n \"alphanum_fraction\": 0.6037020683288574,\n \"avg_line_length\": 29.09395980834961,\n \"blob_id\": \"f0a66d8a18f1371b1336e8b51a8699c92e34cd6f\",\n \"content_id\": \"22d2204fb61deda59080742453b3e183d6e2ef37\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 13452,\n \"license_type\": \"no_license\",\n \"max_line_length\": 120,\n \"num_lines\": 447,\n \"path\": \"/dice_roller.py\",\n \"repo_name\": \"KiboNaku/dice_simulator\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import pickle\\nimport sys\\nfrom os import path, makedirs\\nfrom random import randrange as rand\\n\\nimport math\\n\\n\\nclass Die:\\n\\n \\\"\\\"\\\"\\\"\\n Class used to simulate rolling of a die.\\n\\n :param values: values on the die (each value represents a \\\"face\\\").\\n :type values: sequence of any\\n :param name: value used to identify the die. If no value is specified, name is defaulted to \\\"generic die\\\",\\n meaning all unnamed dice will have the same name (NOT recommended).\\n :type name: str\\n \\\"\\\"\\\"\\n\\n def __init__(self, values, name=\\\"generic die\\\"):\\n self._values = values\\n self.name = name\\n\\n def roll(self):\\n \\\"\\\"\\\"\\n Simulates a single die roll.\\n\\n :returns: the value rolled.\\n :rtype: type contained in self._values\\n \\\"\\\"\\\"\\n return self._values[rand(len(self._values))]\\n\\n def roll_multiple(self, times):\\n \\\"\\\"\\\"\\n Simulates a specified number of die rolls.\\n\\n :param times: number of times to roll the die.\\n :type times: int\\n\\n :return: a list of the the roll results.\\n :rtype: list of type contained in self._values\\n \\\"\\\"\\\"\\n rolls = []\\n for _ in range(times):\\n rolls.append(self.roll())\\n return rolls\\n\\n def get_values(self):\\n \\\"\\\"\\\"\\n :return: a separate copy of the self._values.\\n :rtype: list\\n \\\"\\\"\\\"\\n return list(self._values)\\n\\n\\nclass NumericalDie (Die):\\n\\n \\\"\\\"\\\"\\\"\\n Class used to simulate numerical die. Allows for mathematical operations.\\n\\n :param num_values: numerical values on the die.\\n :type num_values: sequence of int\\n :param name: defaults to \\\"numerical die\\\"\\n :type name: str\\n \\\"\\\"\\\"\\n\\n def __init__(self, num_values, name=\\\"numerical die\\\"):\\n \\\"\\\"\\\"\\n :raises: \\\"ValueError\\\": a value in the sequence passed is not of int type.\\n \\\"\\\"\\\"\\n for num in num_values:\\n if type(num) is not int:\\n raise ValueError(\\\"Each of the value passed to the NumericalDie must be an integer value.\\\")\\n super().__init__(num_values, name)\\n\\n def roll_multiple(self, times):\\n \\\"\\\"\\\"\\n Simulates a specified number of die rolls. Overrides the super().roll_multiple(self, times) method by\\n also returning additional values (mathematical calculations).\\n Additional Values: sum, average, max, min.\\n\\n :param times: number of times to roll the die.\\n :type times: int\\n\\n :return: a list of the the roll results, additional numerical calculations.\\n :rtype: tuple of (list, tuple of (float, float, float, float))\\n \\\"\\\"\\\"\\n rolls = super().roll_multiple(times)\\n return rolls, NumericalDie._additional_values(rolls)\\n\\n @staticmethod\\n def _additional_values(rolls):\\n \\\"\\\"\\\"\\n Returns additional mathematical calculations for the rolls passed: sum, average, max, min.\\n\\n :param rolls: a list of the rolls.\\n :type rolls: list\\n\\n :return: additional mathematical calculations: (sum, average, max, min).\\n :rtype: tuple\\n \\\"\\\"\\\"\\n return NumericalDie._sum(rolls), NumericalDie._average(rolls), \\\\\\n NumericalDie._max(rolls), NumericalDie._min(rolls)\\n\\n @staticmethod\\n def _sum(rolls):\\n \\\"\\\"\\\"\\n :param rolls: list of the dice rolls.\\n :type rolls: list\\n\\n :return: sum of the values.\\n :rtype: int\\n \\\"\\\"\\\"\\n return sum(rolls)\\n\\n @staticmethod\\n def _average(rolls):\\n \\\"\\\"\\\"\\n :param rolls: list of the dice rolls.\\n :type rolls: list\\n\\n :return: average of the values.\\n :rtype: double\\n \\\"\\\"\\\"\\n return NumericalDie._sum(rolls) / len(rolls)\\n\\n @staticmethod\\n def _max(rolls):\\n \\\"\\\"\\\"\\n :param rolls: list of the dice rolls.\\n :type rolls: list\\n\\n :return: max of the values.\\n :rtype: int\\n \\\"\\\"\\\"\\n return max(rolls)\\n\\n @staticmethod\\n def _min(rolls):\\n \\\"\\\"\\\"\\n :param rolls: list of the dice rolls.\\n :type rolls: list\\n\\n :return: min of the values.\\n :rtype: int\\n \\\"\\\"\\\"\\n return min(rolls)\\n\\n\\nclass ClassicDie (NumericalDie):\\n \\\"\\\"\\\"\\\"\\n Simplified version of NumericalDie with values ranging from 1 to the specified max.\\n\\n :param max_val: the max values on the die. Example: enter 6 to create a die with values from 1 to 6.\\n :type max_val: int\\n :param name: defaults to \\\"classical die\\\"\\n :type name: str\\n \\\"\\\"\\\"\\n\\n def __init__(self, max_val, name=\\\"classical die\\\"):\\n super().__init__(range(0, max_val + 1), name)\\n\\n\\n# constants\\n_back = \\\"back\\\"\\n_user_dir = \\\"userdata\\\"\\n_dice_file = \\\"custom_dice.pickle\\\"\\n_file_path = path.join(_user_dir, _dice_file)\\n\\n# holds all of the dice\\n_all_dice = [Die(ClassicDie(spots, \\\"D{}\\\".format(spots))) for spots in [4, 6, 8, 10, 12, 20]]\\n\\n\\ndef _print_die_values(die_obj):\\n \\\"\\\"\\\"Prints out all of the potential values of the die in a table format with \\\"Potential Value\\\" heading.\\\"\\\"\\\"\\n print(\\\"Potential values:\\\")\\n _print_table(die_obj.get_values())\\n\\n\\ndef _print_die_summary(die_obj):\\n \\\"\\\"\\\"\\n Prints out simple summary of the die.\\n Name: (name)\\n Potential Values:\\n (values in table format)\\n \\\"\\\"\\\"\\n print(\\\"Name:\\\\t{}\\\".format(die_obj.name))\\n _print_die_values(die_obj)\\n\\n\\ndef _print_table(values, columns=5, padding=4):\\n \\\"\\\"\\\"\\n Prints a list of values in table format.\\n\\n :param values: values to print.\\n :type values: list\\n :param columns: number of columns. Defaults to 5.\\n :type columns: int\\n :param padding: padding for each column (padded on the left)\\n :type padding: int\\n \\\"\\\"\\\"\\n val_len = len(values)\\n\\n # width is padding + length of the longest value.\\n i_width = padding + len(str(val_len))\\n v_width = padding + max([len(str(val)) for val in values])\\n\\n # printing the values in rows\\n for row in range(int(math.ceil(val_len/columns))):\\n num_index = row + columns\\n num_rolls = values[row:num_index]\\n print(' '.join(\\\"{:{i_width}}. {:{v_width}}\\\\t\\\"\\n .format(columns * row + roll_index + 1, num_rolls[roll_index], i_width=i_width, v_width=v_width)\\n for roll_index in range(len(num_rolls))))\\n\\n\\ndef _print_rolls(die_obj, rolls_list, other_info=None):\\n \\\"\\\"\\\"\\n Prints the dice rolls with additional information.\\n\\n :param die_obj: the die object that was rolled.\\n :type die_obj: Die\\n :param rolls_list: list of the rolls.\\n :type rolls_list: list\\n :param other_info: additional info to display (eg the mathematical calculations returned by NumericalDie).\\n if not specified, nothing is printed for this.\\n :type other_info: list or tuple\\n \\\"\\\"\\\"\\n\\n # the main info\\n print()\\n _print_die_values(die_obj)\\n _print_table(rolls_list)\\n\\n # the mathematical info\\n other_labels = [\\\"sum\\\", \\\"avg\\\", \\\"max\\\", \\\"min\\\"]\\n if other_info is not None:\\n print(\\\"\\\\nsimple results:\\\\n\\\", \\\"\\\\n\\\".join(\\\"\\\\t{}:\\\\t{}\\\"\\n .format(other_labels[i], other_info[i]) for i in range(len(other_info))))\\n\\n # the frequency at which each value was rolled\\n print(\\\"\\\\nfrequency of each value:\\\")\\n print(\\\"\\\\n\\\".join(\\\"\\\\t{}:\\\\t{}\\\".format(val, rolls_list.count(val)) for val in die_obj.get_values()))\\n\\n _print_menu_die()\\n\\n\\n# below are the \\\"menu methods\\\" used to help users navigate and perform what they want.\\n\\ndef _menu_input(input_min, input_max):\\n \\\"\\\"\\\"\\n Simple method used to request a numerical input or the back command which takes them back to the previous menu.\\n\\n :param input_min: the minimum integer that can be accepted.\\n :type input_min: int\\n :param input_max: the maximum integer that can be accepted.\\n :type input_max: int\\n\\n :return: the numerical input or \\\"back\\\"\\n :rtype: int or str\\n \\\"\\\"\\\"\\n input_error = \\\"Integer Input Error:\\\"\\n input_val = input()\\n try:\\n input_int = int(input_val)\\n except ValueError:\\n if input_val.lower() == _back:\\n return _back\\n else:\\n if input_min <= input_int <= input_max:\\n return input_int\\n print(input_error, \\\"invalid input.\\\")\\n return _menu_input(input_min, input_max)\\n\\n\\ndef _print_menu(*options, back_string=\\\"previous menu\\\"):\\n \\\"\\\"\\\"\\n Simple function used to print a basic menu.\\n\\n :param options: tuple arguments that contain the menu options.\\n :type options: tuple of (str, any) where str is what will be displayed to the user as the option and any is what\\n will be returned if the option is chosen.\\n :param back_string: option printed for the \\\"back command\\\". If nothing is specified, \\\"previous menu\\\" will be used.\\n :type back_string: str\\n\\n :return: the option chosen.\\n :rtype: any (what is contained in the option tuple)\\n \\\"\\\"\\\"\\n option_format = \\\"{:<8}{}\\\"\\n options_size = len(options)\\n\\n # prints heading: \\\"INPUT OPTION\\\"\\n print(option_format.format(\\\"INPUT\\\", \\\"OPTION\\\") + \\\"\\\\n\\\")\\n\\n # prints the options for the menu\\n print(\\\"\\\\n\\\".join(option_format.format(i + 1, options[i][0]) for i in range(options_size)))\\n print(option_format.format(_back, back_string))\\n print(\\\"\\\\n\\\")\\n\\n menu_option = _menu_input(1, options_size)\\n return None if menu_option == _back else options[menu_option - 1][1]\\n\\n\\ndef _print_menu_main():\\n \\\"\\\"\\\"\\\"\\n The first menu: choose die or exit.\\n \\\"\\\"\\\"\\n print(\\\"\\\\nDice Roll Simulator\\\")\\n main_menu_input = _print_menu((\\\"choose die\\\", _print_menu_die), back_string=\\\"exit app\\\")\\n\\n if main_menu_input is None:\\n return\\n\\n return main_menu_input()\\n\\n\\ndef _print_menu_die():\\n \\\"\\\"\\\"\\n Second menu: choose die or create custom die.\\n \\\"\\\"\\\"\\n print(\\\"\\\\n\\\")\\n print(\\\"Please choose of the following dice:\\\")\\n selected_die = _print_menu(*[(dice.name, dice) for dice in _all_dice], (\\\"create custom die\\\", create_custom_die))\\n if selected_die is None:\\n return _print_menu_main()\\n elif isinstance(selected_die, Die):\\n return _print_menu_roll(selected_die)\\n else:\\n create_custom_die()\\n return _print_menu_die()\\n\\n\\ndef create_custom_die():\\n \\\"\\\"\\\"simple menu used to create a custom die and write to file.\\\"\\\"\\\"\\n custom_die = custom_numerical_die()\\n _print_die_summary(custom_die)\\n while True:\\n verify_die = input(\\\"\\\\n\\\\ncontinue with these values? y or n\\\\n\\\").lower()\\n if verify_die == \\\"n\\\":\\n return create_custom_die()\\n elif verify_die == \\\"y\\\":\\n break\\n print(\\\"Please enter y or n\\\")\\n with open(_file_path, \\\"ab\\\") as dice_file:\\n pickle.dump(custom_die, dice_file)\\n _all_dice.append(custom_die)\\n\\n\\ndef custom_numerical_die():\\n \\\"\\\"\\\"\\n ask user to input values and create the custom die.\\n\\n :return: the custom die the user specified.\\n :rtype: NumericalDie\\n \\\"\\\"\\\"\\n print(\\\"Please enter a list of numerical values separated by commas (spaces ok).\\\")\\n print(\\\"Example 1: '1,2,3,4,5,6,7' --> [1,2,3,4,5,6,7]\\\")\\n print(\\\"Example 2: '1, 2 , 3, 4, 5, 6, 7' --> [1,2,3,4,5,6,7]\\\\n\\\")\\n values_input = input().replace(\\\" \\\", \\\"\\\").split(',')\\n num_values = []\\n invalid_values = []\\n for val in values_input:\\n try:\\n num_values.append(int(val))\\n except ValueError:\\n invalid_values.append(val)\\n if len(num_values) > 0:\\n print(\\\"Values added to die: \\\")\\n _print_table(num_values)\\n else:\\n print(\\\"No values was added to die.\\\\nTry again\\\")\\n return custom_numerical_die()\\n if len(invalid_values) > 0:\\n print(\\\"Invalid values that failed to add: \\\")\\n _print_table(invalid_values)\\n else:\\n print(\\\"All values was added properly\\\")\\n name = input(\\\"Please enter a name for the die:\\\\n\\\")\\n return NumericalDie(num_values, name)\\n\\n\\ndef _print_menu_roll(current_die):\\n \\\"\\\"\\\"\\n User specifies the number of rolls to roll. If successful, the rolls are printed and they are brought back to\\n the _print_menu_die().\\n\\n :param current_die: the die used to roll.\\n :type current_die: Die\\n \\\"\\\"\\\"\\n _print_die_values(current_die)\\n\\n while True:\\n print(\\\"how many times? ({} to {} times)\\\\n\\\"\\n \\\"enter {} to go back\\\".format(1, sys.maxsize, _back))\\n\\n num_input = _menu_input(1, sys.maxsize)\\n try:\\n num_rolls = int(num_input)\\n break\\n except TypeError:\\n if num_input == _back:\\n return _print_menu_die()\\n print(\\\"Invalid value.\\\")\\n\\n rolls = current_die.roll_multiple(num_rolls)\\n if rolls is None:\\n print(\\\"sorry something unexpected happened with the rolls.\\\\n\\\"\\n \\\"please try again\\\\n\\\")\\n return _print_menu_roll(current_die)\\n return _print_rolls(current_die, rolls[0], rolls[1])\\n\\n\\n# initialization methods\\n\\ndef run():\\n \\\"\\\"\\\"used to run the program from start to finish\\\"\\\"\\\"\\n _create_user_dir_file()\\n _load_saved_dice()\\n _print_menu_main()\\n print(\\\"closing app...\\\")\\n\\n\\ndef _create_user_dir_file():\\n \\\"\\\"\\\"creates the directory for storing the custom dice if doesn't already exist.\\\"\\\"\\\"\\n if not path.isfile(_file_path):\\n try:\\n open(_file_path, 'r')\\n except IOError:\\n open(_file_path, 'w')\\n\\n if not path.exists(_user_dir):\\n makedirs(_user_dir)\\n\\n\\ndef _load_saved_dice():\\n \\\"\\\"\\\"loads the custom die that have been saved and appends them to all_dice\\\"\\\"\\\"\\n with open(_file_path, \\\"rb\\\") as dice_file:\\n while True:\\n try:\\n _all_dice.append(pickle.load(dice_file))\\n except EOFError:\\n break\\n\\n\\nif __name__ == \\\"__main__\\\":\\n run()\\n\"\n }\n]"},"num_files":{"kind":"number","value":1,"string":"1"}}},{"rowIdx":2038,"cells":{"repo_name":{"kind":"string","value":"JohnWinkeler/LaxLinkProto"},"repo_url":{"kind":"string","value":"https://github.com/JohnWinkeler/LaxLinkProto"},"snapshot_id":{"kind":"string","value":"3fee40af08614cf7457ccd1bea9bc3088cef71db"},"revision_id":{"kind":"string","value":"3a34c0e6c907b6b6bfb9a253216640f0ac89b987"},"directory_id":{"kind":"string","value":"47568272f6d4c0d7420ddd8a5631484c01de7c21"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"string","value":"2020-03-31T06:06:20.853260"},"revision_date":{"kind":"string","value":"2018-10-07T17:39:53"},"committer_date":{"kind":"string","value":"2018-10-07T17:39:53"},"github_id":{"kind":"number","value":151968432,"string":"151,968,432"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.6470588445663452,"alphanum_fraction":0.6470588445663452,"avg_line_length":10.333333015441895,"blob_id":"55a2ce8db54fad8119b1391dc0e5486b0346bed9","content_id":"6d817b12d236a8cb06ee300f69855e6a78494e7f","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":34,"license_type":"no_license","max_line_length":25,"num_lines":3,"path":"/LaxLinkProto/LaxLinkProto/__init__.py","repo_name":"JohnWinkeler/LaxLinkProto","src_encoding":"UTF-8","text":"\"\"\"\nPackage for LaxLinkProto.\n\"\"\"\n"}],"string":"[\n {\n \"alpha_fraction\": 0.6470588445663452,\n \"alphanum_fraction\": 0.6470588445663452,\n \"avg_line_length\": 10.333333015441895,\n \"blob_id\": \"55a2ce8db54fad8119b1391dc0e5486b0346bed9\",\n \"content_id\": \"6d817b12d236a8cb06ee300f69855e6a78494e7f\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 34,\n \"license_type\": \"no_license\",\n \"max_line_length\": 25,\n \"num_lines\": 3,\n \"path\": \"/LaxLinkProto/LaxLinkProto/__init__.py\",\n \"repo_name\": \"JohnWinkeler/LaxLinkProto\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"\\\"\\\"\\\"\\nPackage for LaxLinkProto.\\n\\\"\\\"\\\"\\n\"\n }\n]"},"num_files":{"kind":"number","value":1,"string":"1"}}},{"rowIdx":2039,"cells":{"repo_name":{"kind":"string","value":"eekhait/1008_Project"},"repo_url":{"kind":"string","value":"https://github.com/eekhait/1008_Project"},"snapshot_id":{"kind":"string","value":"3a4cc3a3dcec866cbb088d493d7e71cb8a235ced"},"revision_id":{"kind":"string","value":"55b161d33e2ddd41889a31666dffcf427ac421f6"},"directory_id":{"kind":"string","value":"d336d75e3e4443ddce3d909c31dc0f40b2415bf6"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"string","value":"2022-04-18T01:39:53.902233"},"revision_date":{"kind":"string","value":"2020-04-03T12:45:31"},"committer_date":{"kind":"string","value":"2020-04-03T12:45:31"},"github_id":{"kind":"number","value":244609796,"string":"244,609,796"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.5688451528549194,"alphanum_fraction":0.5842322111129761,"avg_line_length":42.77777862548828,"blob_id":"6448e485c4fcdbbaf2d1225e1d358defac085294","content_id":"2621f67eeb107180d66ed8257df35c109589baf1","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":6304,"license_type":"no_license","max_line_length":137,"num_lines":144,"path":"/lrt_adj.py","repo_name":"eekhait/1008_Project","src_encoding":"UTF-8","text":"import pandas as pd\nimport csv\nimport math\n\nimport main_graph as m_graph\n\nlrtData = pd.read_csv('Punggol_LRT_Routing.csv', sep=',', header=None)\n\n\ndef round_up(n, decimals=0):\n # this is to round up even is 0.1 above\n multiplier = 10 ** decimals\n return math.ceil(n * multiplier) / multiplier\n\n\ndef bfs_route(graph, start, end):\n # maintain a queue of paths\n queue = []\n # push the first path into the queue\n queue.append([start])\n while queue:\n # get the first path from the queue\n path = queue.pop(0)\n # get the last node from the path\n node = path[-1]\n # path found\n if node == end:\n return path\n # enumerate all adjacent nodes, construct a new path and push it into the queue\n for adjacent in graph.get(node, []):\n new_path = list(path)\n new_path.append(adjacent)\n queue.append(new_path)\n\n\ndef cal_distance(adj_list_val, result):\n distance = 0\n # e.g. PE1, PE2, PE3\n for i in range(len(result) - 1): # number of time to run\n for y in range(len(adj_list_val[result[i]])): # e.g. adj_list_val['PE1'] return number of list value\n if result[i + 1] in adj_list_val[result[i]][\n y]: # e.g. check if PE2 is in adj_list_val['PE1'][0] or adj_list_val['PE1'][1] LISTING\n distance += int(adj_list_val[result[i]][y][result[\n i + 1]]) # e.g. adj_list_val['PE1'][0][['PE2'] will return the distance weightage\n return distance\n\n\ndef take_lrt(start_node, end_node):\n start_node = str(start_node) # Store the start name\n end_node = str(end_node) # Store the end name\n walk_start_node = [] # Store the array from the TAKE_WALK Function FROM START POINT TO LRT\n walk_end_node = [] # Store the array from the TAKE_WALK Function FROM LRT TO END POINT\n lrt_name = [] # Store the LRT NAME\n lrt_code = [] # Store the LRT CODE\n adj_list = {} # Store the Adj list\n adj_list_val = {} # Store the Adj list with value\n with open('Punggol_LRT_Routing.csv', 'r') as csv_file:\n reader = csv.reader(csv_file)\n first = True\n for row in reader:\n if (first == True):\n for i in range(len(row)):\n first = False\n else:\n # for i in range(0, len(row)):\n # # key_value = {row[0]: row[2].split()} # This is to create the Adj\n lrt_name.append(row[1]) # Append the LRT NAME into the lrt_name\n lrt_code.append(row[0]) # Append the LRT CODE into the lrt_code\n keys = row[2].split(\", \")\n values = row[3].split(\", \")\n add_value = []\n for i in range(len(keys)):\n add_value.append({keys[i]: values[i]}) # Create a list of dict e.g. 'PE1' : 1010\n adj_list_val[row[0]] = add_value # Append the linked code into the list\n adj_list[row[0]] = row[2].split(\", \") # Append the linked code into the list\n\n # Check if start node is mrt or blocks\n if start_node in lrt_name:\n # Convert the LRT NAME INTO LRT CODE\n for i in range(len(adj_list)):\n if lrt_name[i] == start_node:\n start_node = lrt_code[i] # Convert start_node Into LRT CODE\n break\n else:\n temp_string_start_node = start_node # Store the postal code\n start_node = m_graph.get_nearest_lrt(start_node) # To Store the nearest LRT station with the postal code\n walk_start_node = m_graph.take_walk(temp_string_start_node, start_node) # Store the walking node from Start of Postal Code to LRT\n\n if end_node in lrt_name:\n for i in range(len(adj_list)):\n if lrt_name[i] == end_node:\n end_node = lrt_code[i] # Convert end_noce Into LRT CODE\n break\n else:\n temp_string_end_node = end_node # Store the postal code\n end_node = m_graph.get_nearest_lrt(end_node) # To Store the nearest LRT station with the postal code\n walk_end_node = m_graph.take_walk(end_node, temp_string_end_node) # Store the walking node from LRT To the End of Postal code\n\n\n\n # if start and end are connected\n if m_graph.is_adjacent_lrt(adj_list, start_node, end_node):\n result = [start_node, end_node]\n\n # average SG MRT 45km/h == 12.5m/s\n # Calculate the timing Second in minutes,\n distance = cal_distance(adj_list_val, result)\n timing = round_up((distance / 12.5) / 60)\n\n # Check if there any array\n if len(walk_start_node) != 0:\n del result[0] # To delete the first array as is duplicated\n result = walk_start_node[1] + result # Combine the Walking array with result (LRT)\n timing = walk_start_node[0] + timing # Combine the Time required\n if len(walk_end_node) != 0:\n del result[-1] # To delete the last array as is duplicated\n result = result + walk_end_node[1] # Combine the result (LRT) with Walking array\n return [int(timing), result]\n else:\n result = (bfs_route(adj_list, start_node, end_node))\n\n # average SG MRT 45km/h == 12.5m/s\n # Calculate the timing Second in minutes,\n distance = cal_distance(adj_list_val, result)\n timing = round_up((distance / 12.5) / 60)\n # average timing stop at each mrt is 30second == 0.5\n mrt_stopping = 0.5 * int(len(result) - 1)\n # Calculate the timing Second in minutes,\n timing = round_up((distance / 12.5) / 60) + mrt_stopping\n # Add another 5 min flat waiting for the train to arrival\n timing = timing + 5\n\n if len(walk_start_node) != 0:\n del result[0] # To delete the first array as is duplicated\n result = walk_start_node[1] + result # Combine the Walking array with result (LRT)\n timing = walk_start_node[0] + timing # Combine the Time required\n if len(walk_end_node) != 0:\n del result[-1] # To delete the last array as is duplicated\n result = result + walk_end_node[1] # Combine the result (LRT) with Walking array\n\n # print([int(timing), result])\n return [int(timing), result]\n\n# print(\"LRT ROUTE: \", take_lrt(\"828858\",\"65009\"))\n"},{"alpha_fraction":0.535467803478241,"alphanum_fraction":0.5473470091819763,"avg_line_length":33.5234375,"blob_id":"734a621e48078d64bb4301cd28ecb71513e7e2ce","content_id":"d96a7c5f2e19546ca3844f59f17e0587283b975e","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":8839,"license_type":"no_license","max_line_length":107,"num_lines":256,"path":"/main_graph.py","repo_name":"eekhait/1008_Project","src_encoding":"UTF-8","text":"import pandas as pd\n\n\n# THIS PART CONCERNS WITH:\n# THE CSV FILES AND EXTRACTING DATA FROM THEM\n# --------------------------------- #\n# Indexes of the Complete_Punggol_Graph.csv file:\n# Columns: 0-Code, 1-Name, 2-Type, 3-Latitude, 4-Longitude, 5-Buses, 6-ConnectedWalks, 7-ConnectedDistances\n# Columns: 8-1197 to refer to nodes (+7 difference from corresponding node in rows)\n# Rows: 1-1190 to refer to nodes\n# --------------------------------- #\n# How to use pandas dataframe (treat it as a 2D array/excel file):\n# mainGraph.at[row,column]\n# --------------------------------- #\nmainGraph = pd.read_csv('Complete_Punggol_Graph.csv', sep=',', header=None)\nmainGraph[0] = mainGraph[0].apply(str) # converts column to be string-only (rather than int+str)\nstartIndex = 1\nendIndex = len(mainGraph.index)\n# --------------------------------- #\n\n\ndef get_distance_to_from(point_a, point_b):\n index_a = get_node_index(point_a)+7\n index_b = get_node_index(point_b)\n return int(mainGraph.at[index_b, index_a])\n\n\ndef get_long_lat(target):\n index = get_node_index(target)\n return [round(float(mainGraph.at[index, 3]), 4), round(float(mainGraph.at[index, 4]), 4)]\n\n\ndef get_lat_long(target):\n index = get_node_index(target)\n return [round(float(mainGraph.at[index, 4]), 4), round(float(mainGraph.at[index, 3]), 4)]\n\n\ndef get_node_index(target):\n # Start location codes are from index 1 to 1190\n # print(type(target),target)\n target=str(target)\n low = startIndex\n high = endIndex\n mid = (startIndex+endIndex)//2\n while target != str(mainGraph.at[mid, 0]):\n if target < str(mainGraph.at[mid, 0]): # if target is in smaller half\n high = mid\n if mid == (low+high)//2:\n return -1\n mid = (low+high)//2\n elif target > str(mainGraph.at[mid, 0]): # if target is in larger half\n low = mid\n if mid == (low+high)//2:\n return -1\n mid = (low+high)//2\n return mid\n\n\ndef get_nearest_bus_stops(target, distance):\n pass\n\n\ndef get_nearest_lrt(target):\n if len(target) == 3:\n return target\n else:\n index = get_node_index(target)\n node = \"\"\n distance = 3000\n for i in range(endIndex+7-14, endIndex+7): # start and end of LRT columns in csv\n if int(mainGraph.at[index, i]) < distance:\n node = mainGraph.at[0, i]\n distance = int(mainGraph.at[index, i])\n return str(node)\n\n\ndef get_adjacent_walks(start_node):\n start_index = get_node_index(start_node)\n connected_nodes = mainGraph.at[start_index, 6].split(', ')\n return connected_nodes\n\n\ndef is_adjacent_walk(start_node, end_node):\n start_index = get_node_index(start_node)\n connected_nodes = mainGraph.at[start_index, 6].split(', ')\n if end_node in connected_nodes:\n return True\n else:\n return False\n\n\ndef is_adjacent_bus(start_node, end_node):\n pass\n\n\ndef is_adjacent_lrt(adj_list, start_node, end_node):\n # Check If Are Both LRT are directly connected!\n for i in adj_list:\n if start_node == i: # To check if able to found the KEY\n if end_node in adj_list[i]: # To check if both Start_Node & End_Node are directly connected\n return 1 # If Yes, return 1\n else:\n return 0 # If No, return 0\n\n\n# ----------------------------------\n# THIS PART CONCERNS WITH ALGORITHMS:\n# ----------------------------------\nclass AStarStack:\n def __init__(self):\n self.top = -1\n self.data = []\n self.total_distance = 0\n self.distance_to_end = 0\n\n def show_stack(self):\n print(\"start\")\n for i in self.data:\n print(i)\n print(\"end\")\n\n def push(self, node, val):\n self.top += 1\n self.data.append(node)\n if self.top > 0: # if there is at least two elements...\n self.total_distance += get_distance_to_from(self.data[self.top], self.data[self.top-1])\n self.distance_to_end = val\n\n # def pop(self):\n # if self.top > -1:\n # node = self.data[self.top]\n # if self.top > 0:\n # self.total_distance -= get_distance_to_from(self.data[self.top], self.data[self.top-1])\n # del self.data[self.top]\n # self.top -= 1\n # return node\n\n def is_empty(self):\n if self.top < 0:\n return True\n else:\n return False\n\n def peek(self):\n if not self.is_empty():\n return self.data[self.top]\n\n def peek_distance(self):\n if not self.is_empty():\n return self.total_distance\n\n def copy_from(self, a_stack):\n for x in a_stack.data:\n self.push(x, a_stack.distance_to_end)\n\n\nclass AStarQueue:\n def __init__(self):\n self.top = -1\n self.data = []\n self.distances_to_target = []\n\n def enqueue(self, node):\n temp = node.distance_to_end\n front = 1\n back = self.top\n mid = (front+back)//2\n if self.top > -1:\n # print(str(temp) + \" \" + str(self.distances_to_target[0]))\n if temp < self.distances_to_target[0]: # add to the front\n self.data.insert(0, node)\n self.distances_to_target.insert(0, temp)\n elif temp > self.distances_to_target[self.top]: # add to the back\n self.data.append(node)\n self.distances_to_target.append(temp)\n else:\n while temp != self.distances_to_target[mid] and front != mid:\n if temp < self.distances_to_target[mid]:\n back = mid\n mid = (front + back) // 2\n elif temp > self.distances_to_target[mid]:\n front = mid\n mid = (front + back) // 2\n # if temp == self.distances_to_target[mid]\n self.data.insert(mid, node)\n self.distances_to_target.insert(mid, temp)\n elif self.top < 0:\n self.data.append(node)\n self.distances_to_target.append(temp)\n self.top += 1\n # print(\"[\", end='')\n # for i in self.data:\n # print(str(i.distance_to_end) + \", \", end='')\n # print(\"]\")\n # print(str(self.distances_to_target))\n\n def dequeue(self):\n if self.top > -1:\n temp = self.data[0]\n del self.data[0]\n del self.distances_to_target[0]\n self.top -= 1\n return temp\n\n def is_empty(self):\n if self.top < 0:\n return True\n else:\n return False\n\n def peek(self):\n if not self.is_empty():\n return self.data[0]\n\n\ndef take_walk(start_node, end_node):\n start_node = str(start_node)\n end_node = str(end_node)\n # if start and end are connected\n if is_adjacent_walk(start_node, end_node):\n return [1, [start_node, end_node]]\n else: # this part begins like the word ladder\n # initialization of queue and first stack (of just start node)\n # also initialization of visited nodes\n star_queue = AStarQueue()\n star_stack = AStarStack()\n star_stack.push(start_node, get_distance_to_from(start_node, end_node))\n star_queue.enqueue(star_stack)\n visited_nodes = {}\n counter = 0\n # while end node is not reached\n while star_queue.data[0].peek() != end_node:\n # dequeue the first stack\n temp_stack = star_queue.dequeue()\n mid_node = temp_stack.peek()\n # add all adjacent nodes to mid_node in separate stacks\n # move stacks to queue\n for i in get_adjacent_walks(mid_node):\n # create new stack with each adjacent node\n temper_stack = AStarStack()\n temper_stack.copy_from(temp_stack)\n temper_stack.push(str(i), get_distance_to_from(str(i), end_node))\n # temper_stack.show_stack()\n # if node is visited before\n if i in visited_nodes:\n # only enqueue if new path/stack is shorter than old path\n if temper_stack.total_distance < visited_nodes[i]:\n star_queue.enqueue(temper_stack)\n visited_nodes[i] = temper_stack.total_distance\n # if node is new, enqueue normally\n elif i not in visited_nodes:\n # enqueue the stack\n star_queue.enqueue(temper_stack)\n visited_nodes[i] = temper_stack.total_distance\n # return assumes a walking speed of 5km/h. first element is time taken in minutes\n return [round(star_queue.data[0].total_distance/5000*60), star_queue.data[0].data]\n\n"},{"alpha_fraction":0.7825203537940979,"alphanum_fraction":0.7876016497612,"avg_line_length":32.89655303955078,"blob_id":"a9279f2eab0fb5749fedddfab8ee9bbd465939c5","content_id":"465f2746e9c27b36e44542024b69717a2b977f55","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":984,"license_type":"no_license","max_line_length":170,"num_lines":29,"path":"/README.md","repo_name":"eekhait/1008_Project","src_encoding":"UTF-8","text":"# 1008_Project\nPunggol Pathfinder\n\n\n*Introduction*\nAn application that lets users find a path (from a start and end node input) within Punggol. They will be able to select the main method of travel (Bus, LRT, or Walking).\n\nThe output includes strings printed by the console as well as a graph that shows the path the user has to take. \n\n\n*Installation*\nThe application has been developed with the following:\nPyCharm - https://www.jetbrains.com/pycharm/download/#section=windows\nGit - https://git-scm.com/download \nAnaconda - https://www.anaconda.com/distribution/#download-section\n\nThe following line of pip install is also required:\npip install folium PyQt5 PyQtWebEngine\n\n\n*How to Use*\nRun map.py and follow the instructions displayed. \nIn order, the console will ask for:\nStart location\nEnd location\nLocation confirmation\nMethod of travel\n\nThereafter, an estimated time of travel is shown together with a list of nodes in the path, and the method of connection between the nodes. \n"},{"alpha_fraction":0.5936199426651001,"alphanum_fraction":0.6393897533416748,"avg_line_length":40.20000076293945,"blob_id":"5ed6b9f0026b640978f9f27e464ff7dee2149f2a","content_id":"000a43277cfd3b899256979bb65da46950dd452c","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1442,"license_type":"no_license","max_line_length":107,"num_lines":35,"path":"/oldfiles/DistanceTabulator.py","repo_name":"eekhait/1008_Project","src_encoding":"UTF-8","text":"import pandas as pd\nfrom geopy.distance import geodesic\n\n# Take note:\n# Latitude is vertical (How 'north-south' a place is)\n# Longitude is horizontal (How 'east-west' a place is)\ndistance_table = pd.read_csv(\"Punggol Coordinates.csv\", header=None)\n\n# to mimic cell selection in pandas dataframe, for iteration\n# iloc[horizontal, vertical]\n# iloc[1123, 1119] <--- most bottom right value\n# 0,0 0,1 0,2 0,3 0,4...\n# postal_code Street Latitude Longitude 820136...\n\n# FOR EVERY ROW... (Skips header row)\nfor i in range(1, 1191): # 1191\n # FOR EVERY COLUMN... (Skips first 4 already-populated columns)\n nearbyNodes = []\n nearbyDistances = []\n for j in range(7, 1197):\n # Assign distance between nodes in meters\n distance = 1000 * round(geodesic((distance_table.iloc[i, 2], distance_table.iloc[i, 3]),\n (distance_table.iloc[j-6, 2], distance_table.iloc[j-6, 3])).km, 3)\n distance_table.iloc[i, j] = distance\n if 0 < distance < 180:\n nearbyNodes.append(str(distance_table.iloc[j-6, 0]))\n nearbyDistances.append(int(distance))\n distance_table.iloc[i, 5] = str(nearbyNodes)\n distance_table.iloc[i, 6] = str(nearbyDistances)\n\n # Prints progress of population per row\n print(round(i / 1191 * 100, 2))\n\n# Create new csv\ndistance_table.to_csv('Complete_Punggol_Graph.csv', header=False, index=False)\n"},{"alpha_fraction":0.501806378364563,"alphanum_fraction":0.5308887362480164,"avg_line_length":36.4054069519043,"blob_id":"a93d902b55395015fdedbf4179e38abe46e389aa","content_id":"f4e62748caa9e7020e1db37b271a7b89aaa78b5a","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":5536,"license_type":"no_license","max_line_length":223,"num_lines":148,"path":"/oldfiles/LRT_Algorithm.py","repo_name":"eekhait/1008_Project","src_encoding":"UTF-8","text":"from collections import deque\nimport csv\n\n\nclass Graph:\n def __init__(self, lists):\n self.lists = lists\n\n def get_neighbours(self, i):\n return self.lists[i]\n\n import csv\n cove_lrt, meridian_lrt, coraledge_lrt, riviera_lrt, kadaloor_lrt, oasis_lrt, damai_lrt, punggol_lrt, samkee_lrt, tecklee_lrt, punggolpoint_lrt, samudera_lrt, nibong_lrt, sumang_lrt, sooteck_lrt = ([] for i in range(15))\n\n with open('LRT.csv') as file:\n lrt = list(csv.reader(file))\n cove_lrt.append(lrt[1])\n meridian_lrt.append(lrt[2])\n coraledge_lrt.append(lrt[3])\n riviera_lrt.append(lrt[4])\n kadaloor_lrt.append(lrt[5])\n oasis_lrt.append(lrt[6])\n damai_lrt.append(lrt[7])\n punggol_lrt.append(lrt[8])\n samkee_lrt.append(lrt[9])\n tecklee_lrt.append(lrt[10])\n punggolpoint_lrt.append(lrt[11])\n samudera_lrt.append(lrt[12])\n nibong_lrt.append(lrt[13])\n sumang_lrt.append(lrt[14])\n sooteck_lrt.append(lrt[15])\n\n #heuristic function for all nodes\n def heuristic(self, n):\n Heuristic = {\n 'Punggol_MRT': 1,\n 'SamKee_LRT': 1,\n 'SooTeck_LRT': 1,\n 'PunggolPoint_LRT': 1,\n 'Samudera_LRT': 1,\n 'Sumang_LRT': 1,\n 'Nibong_LRT': 1,\n 'Damai_LRT': 1,\n 'Kadaloor_LRT': 1,\n 'Riviera_LRT': 1,\n 'CoralEdge_LRT': 1,\n 'Meridian_LRT': 1,\n 'Oasis_LRT': 1,\n 'Cove_LRT': 1,\n }\n return Heuristic[n]\n\n def astar_algorithm(self, start_node, stop_node):\n # open_list is a list of nodes which have been visited, but who's neighbors\n # haven't all been inspected, starts off with the start node\n # closed_list is a list of nodes which have been visited\n # and who's neighbors have been inspected\n open_list = set([start_node])\n closed_list = set([])\n\n # cdist contains current distances from start_node to all other nodes\n # the default value (if it's not found in the map) is +infinity\n cdist = {}\n\n cdist[start_node] = 0\n\n # parents contains an adjacency map of all nodes\n parents = {}\n parents[start_node] = start_node\n\n while len(open_list) > 0:\n n = None\n\n # find a node with the lowest value of f() - evaluation function\n for i in open_list:\n if n == None or cdist[i] + self.heuristic(i) < cdist[n] + self.heuristic(n):\n n = i;\n\n if n == None:\n print('Path does not exist!')\n return None\n\n # if the current node is the stop_node\n # then we begin reconstructing the path from it to the start_node\n if n == stop_node:\n reconst_path = []\n\n while parents[n] != n:\n reconst_path.append(n)\n n = parents[n]\n\n reconst_path.append(start_node)\n\n reconst_path.reverse()\n print('Path found: {}'.format(reconst_path))\n return reconst_path\n\n # for all neighbors of the current node do\n for (m, weight) in self.get_neighbours(n):\n # if the current node isn't in both open_list and closed_list\n # add it to open_list and note n as it's parent\n if m not in open_list and m not in closed_list:\n open_list.add(m)\n parents[m] = n\n cdist[m] = cdist[n] + weight\n\n # otherwise, check if it's quicker to first visit n, then m\n # and if it is, update parent data and g data\n # and if the node was in the closed_list, move it to open_list\n else:\n if cdist[m] > cdist[n] + weight:\n cdist[m] = cdist[n] + weight\n parents[m] = n\n\n if m in closed_list:\n closed_list.remove(m)\n open_list.add(m)\n\n # remove n from the open_list, and add it to closed_list\n # because all of his neighbors were inspected\n open_list.remove(n)\n closed_list.add(n)\n\n print('Path does not exist!')\n return None\n\nlists = {\n # LRT on Punggol East\n 'Punggol_MRT': [('SamKee_LRT', 0.589), ('SooTeck_LRT', 0.605), ('Damai_LRT', 0.690), ('Cove_LRT', 0.763)],\n 'SamKee_LRT': [('Punggol_MRT', 0.589), ('PunggolPoint_LRT', 0.815)],\n 'PunggolPoint_LRT': [('SamKee_LRT', 0.815), ('Samudera_LRT', 0.513)],\n 'Samudera_LRT': [('PunggolPoint_LRT', 0.513), ('Nibong_LRT', 0.493)],\n 'Nibong_LRT': [('Samudera_LRT', 0.493), ('Sumang_LRT', 0.429)],\n 'Sumang_LRT': [('Nibong_LRT', 0.429), ('SooTeck_LRT', 0.478)],\n 'SooTeck_LRT': [('Sumang_LRT', 0.478), ('Punggol_MRT', 0.605)],\n\n # LRT on Punggol West\n 'Damai_LRT': [('Punggol_MRT', 0.690), ('Oasis_LRT', 0.563)],\n 'Oasis_LRT': [('Damai_LRT', 0.563), ('Kadaloor_LRT', 0.515)],\n 'Kadaloor_LRT': [('Oasis_LRT', 0.515), ('Riviera_LRT', 0.558)],\n 'Riviera_LRT': [('Kadaloor_LRT', 0.558), ('CoralEdge_LRT', 0.386)],\n 'CoralEdge_LRT': [('Riviera_LRT', 0.386), ('Meridian_LRT', 0.530)],\n 'Meridian_LRT': [('CoralEdge_LRT', 0.530), ('Cove_LRT', 0.443)],\n 'Cove_LRT': [('Meridian_LRT', 0.443), ('Punggol_MRT', 0.763)],\n}\n\ngraph1 = Graph(lists)\ngraph1.astar_algorithm('Samudera_LRT', 'Riviera_LRT')\n"},{"alpha_fraction":0.5070756077766418,"alphanum_fraction":0.5182813405990601,"avg_line_length":46.324241638183594,"blob_id":"7f79b81551c8f3b2dd70426d2d508f5d62150620","content_id":"e556747388939d07b81a3c4d3f4b171f78cf81d5","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":15617,"license_type":"no_license","max_line_length":227,"num_lines":330,"path":"/map.py","repo_name":"eekhait/1008_Project","src_encoding":"UTF-8","text":"import folium\nimport io\nimport sys\nimport main_graph as m_graph\nimport bus_adj as bus_graph\nimport lrt_adj as lrt_graph\nimport pandas as pd\nfrom PyQt5 import QtWidgets, QtWebEngineWidgets\nimport csv\n\n# ----------------------------------\n# THIS PART CONCERNS WITH UI\n# EVERYTHING COMES TOGETHER HERE\n# ----------------------------------\nif __name__ == \"__main__\":\n app = QtWidgets.QApplication(sys.argv)\n # Create map object, set default location, map theme & zoom\n m = folium.Map(location=[1.4046357, 103.9090000], zoom_start=14.5, prefer_canvas=True)\n # Global tooltip, hover info\n tooltip = 'Click For More Info'\n\n # ASKS FOR INPUT/OUTPUT HERE, EVERYTHING TAKEN IN AS STRING (Irvyn)\n def check(start):\n with open('Complete_Punggol_Graph.csv', 'rt') as f:\n reader = csv.reader(f, delimiter=',')\n for row in reader:\n if start == row[0] or start == row[1]:\n location.append(row[0])\n name.append(row[1])\n return location, name\n\n def confirmation(msg):\n while True:\n answer = input(msg).upper()\n if answer in ('Y', 'N'):\n return answer\n else:\n print('Not a valid input, please try again')\n\n def transportation(tp):\n while True:\n mode = input(tp).upper()\n if mode in ('L', 'B', 'W', 'M'):\n return mode\n else:\n print('Not a valid input, please try again')\n\n def show_walks():\n # Used to create a file to show graph of connectivity\n # This one is just nodes that are of walkable distance\n marked = []\n for i in range(1, len(m_graph.mainGraph[0])):\n for j in list(m_graph.mainGraph.at[i, 6].split(\", \")):\n # print(m_graph.mainGraph[0][i], j)\n if [m_graph.mainGraph[0][i], j] not in marked and [j, m_graph.mainGraph[0][i]] not in marked:\n coords_to_add = [m_graph.get_long_lat(m_graph.mainGraph[0][i]), m_graph.get_long_lat(j)]\n # print(coords_to_add)\n marked.append(coords_to_add)\n folium.PolyLine(coords_to_add, color=\"grey\", opacity=0.5, weight=0.5).add_to(m)\n m.save(\"walks.html\")\n\n def show_lrts():\n # Used to create a file to show graph of connectivity\n # This one is just the LRTs, and what blocks are 'connected' to them\n marked = []\n # Buildings and their closest LRTs\n for i in range(1, len(m_graph.mainGraph[0])-14):\n closest_lrt = m_graph.get_nearest_lrt(m_graph.mainGraph[0][i])\n if [m_graph.mainGraph[0][i], closest_lrt] not in marked and [closest_lrt, m_graph.mainGraph[0][i]] not in marked:\n coords_to_add = [m_graph.get_long_lat(m_graph.mainGraph[0][i]), m_graph.get_long_lat(closest_lrt)]\n marked.append(coords_to_add)\n folium.PolyLine(coords_to_add, color=\"grey\", opacity=1, weight=1).add_to(m)\n # Markers for LRTs\n marked = []\n marked2 = []\n with open('Punggol_LRT_Routing.csv', 'rt') as lrt:\n reader = csv.reader(lrt, delimiter=',')\n next(reader)\n for row in reader:\n for i in row[2].split(\", \"): # connected nodes\n if [row, i] not in marked and [i, row] not in marked:\n # print(row[0], i)\n coords_to_add = [m_graph.get_long_lat(row[0]), m_graph.get_long_lat(i)]\n marked.append(coords_to_add)\n folium.PolyLine(coords_to_add, color=\"purple\").add_to(m)\n if coords_to_add not in marked2:\n folium.Marker(coords_to_add[0],\n icon=folium.Icon(color=\"purple\", icon=\"train\", prefix='fa'),\n popup=i, tooltip=row[0]).add_to(m)\n marked2.append(coords_to_add[0])\n # Edges between LRTs\n marked = []\n m.save(\"lrts.html\")\n\n def show_buses():\n b_graph = pd.read_csv('Punggol_Bus_Routing_Type2.csv', sep=',')\n b_graph[\"ServiceNo\"] = b_graph[\"ServiceNo\"].apply(str) # converts column to be string-only (rather than int+str)\n b_graph[\"NextStop\"] = b_graph[\"NextStop\"].apply(str) # converts column to be string-only (rather than int+str)\n marked = []\n for i in range(0,len(b_graph[\"ServiceNo\"])):\n longlats = [m_graph.get_long_lat(b_graph.at[i, \"BusStopCode\"]), m_graph.get_long_lat(b_graph.at[i, \"NextStop\"])]\n # add marker (latlong)\n if b_graph.at[i, \"BusStopCode\"] not in marked:\n folium.Marker(m_graph.get_long_lat(b_graph.at[i, \"BusStopCode\"]),\n icon=folium.Icon(color=\"green\", icon=\"bus\", prefix='fa'),popup=\"\",tooltip=\"\").add_to(m)\n marked.append(i)\n # add edge (longlat)\n folium.PolyLine(longlats, color=\"green\", weight=2, opacity=0.75).add_to(m)\n m.save(\"buses.html\")\n\n\n # show_walks()\n # show_lrts()\n # show_buses()\n print(\"\\nWelcome to Punggol Pathfinder\")\n print(\"Valid inputs are: \\033[1m Postal codes, bus stop numbers, train station names, train station codes. \\033[0m\")\n\n while True:\n name = []\n # User start and end code will be stored in here\n location = []\n # User choosen mode will stored in here\n mode = []\n result_path = []\n # Prompt user for start and destination point\n start = input(\"\\nWhere are you coming from?\\n\")\n end = input(\"Where is your destination?\\n\")\n check(start)\n check(end)\n\n # Calls function to check if input is valid by comparing with CSV\n if len(location) != 2:\n print(\"Location not valid, please try again\\n\")\n continue\n else:\n sp = name[0]\n ep = name[1]\n\n if sp:\n print(\"Start location: \", sp)\n else:\n print(\"Start location: \", start)\n if ep:\n print(\"Destination: \", ep)\n else:\n print(\"Destination: \", end)\n\n answer = confirmation(\"\\nConfirm start location and destination? [Y/N] \\n\")\n if answer == 'N':\n print(\"Let\\'s try again\")\n elif answer == 'Y':\n mode = transportation(\"Select mode of transport: LRT (L), Bus (B), Walk (W), or Mixed (M)\\n\")\n if mode == 'L':\n # Call Lrt algorithm here\n result_path = lrt_graph.take_lrt(location[0], location[1])\n\n print(\"Time taken:\", result_path[0], \"mins\")\n print(\"Take LRT from\")\n for i in range(0, len(result_path[1])):\n print(result_path[1][i])\n if len(result_path[1]) - 1 != i:\n print(\"to\")\n elif mode == 'B':\n # Call Bus algorithm here\n result_path = bus_graph.route_finder(location[0], location[1])\n print(\"Time taken:\", result_path[0], \"mins\")\n print(\"From\")\n for i in range(0, len(result_path[1])):\n print(result_path[1][i])\n if (result_path[2][i]) == True:\n print(\"Take bus\", result_path[3], \"to \")\n else:\n if len(result_path[1]) - 1 != i:\n print(\"Walk to\")\n elif mode == 'W':\n # Call Walk algorithm here\n result_path = m_graph.take_walk(location[0], location[1])\n\n print(\"Time taken:\", result_path[0], \"mins\")\n print(\"Walk from\")\n for i in range(0, len(result_path[1])):\n print(result_path[1][i])\n if len(result_path[1]) - 1 != i:\n print(\"to\")\n elif mode == 'M':\n # Call Mixed algorithm here\n print(\"Option not implemented. Please try again with a different options\")\n sys.exit()\n break\n\n\n # (khai)\n # THIS PART IS WHERE THE MAP GETS POPULATED WITH NODES AND EDGES ---------------------------------------------\n\n # Adding of markers and edges for Single Transport Routes\n def singleTransportPlot(paths, markerColor, lineColor, markerIcon):\n marker_coords = []\n edge_coords = []\n for i in paths:\n # this loop creates a list of coordinates to add markers/nodes with\n marker_coords.append(m_graph.get_lat_long(i))\n edge_coords.append(m_graph.get_long_lat(i))\n\n for i in range(0, len(marker_coords)):\n folium.Marker([marker_coords[i][1], marker_coords[i][0]],\n icon=folium.Icon(color=markerColor, icon=markerIcon, prefix='fa'), popup=i,\n tooltip=result_path[1][i]).add_to(m)\n folium.PolyLine(edge_coords, color=lineColor).add_to(m)\n\n # Set icon for different transportation types\n def iconMaker(length):\n if length == 3:\n return \"train\"\n elif (length == 5):\n return \"bus\"\n elif length == 6:\n return \"building\"\n\n # Set color based on transportation type\n def setColor(length):\n if length == 3:\n return \"purple\"\n elif (length == 5):\n return \"green\"\n elif length == 6:\n return \"gray\" \n\n\n # Set route based on different transport\n def routePlotting(MOT, paths):\n changes_Indicator = 0\n if (MOT == \"L\"):\n marker_coords = []\n edge_coords = []\n\n for i in range(0, len(paths[1])):\n marker_coords.append(m_graph.get_lat_long(paths[1][i]))\n\n current_node = paths[1][i]\n if i+1 < len(paths[1]):\n next_node = paths[1][i+1]\n \n edge_coords.append(m_graph.get_long_lat(current_node))\n\n if len(current_node) == 3 and len(next_node) == 3:\n folium.Marker([marker_coords[i][1], marker_coords[i][0]], icon=folium.Icon(color=setColor(len(current_node)),icon=iconMaker(len(current_node)), prefix='fa'), popup=i, tooltip=result_path[1][i]).add_to(m)\n edge_coords.append(m_graph.get_long_lat(next_node))\n folium.PolyLine(edge_coords, color=\"purple\").add_to(m)\n edge_coords = []\n else:\n folium.Marker([marker_coords[i][1], marker_coords[i][0]], icon=folium.Icon(color=setColor(len(current_node)),icon=iconMaker(len(current_node)), prefix='fa'), popup=i, tooltip=result_path[1][i]).add_to(m)\n edge_coords.append(m_graph.get_long_lat(next_node))\n folium.PolyLine(edge_coords, color=\"grey\").add_to(m)\n edge_coords = [] \n elif (MOT == \"B\"):\n marker_coords = []\n edge_coords = []\n\n for i in range(0, len(paths[1])):\n marker_coords.append(m_graph.get_lat_long(paths[1][i]))\n\n current_node = paths[1][i]\n if i+1 < len(paths[1]):\n next_node = paths[1][i+1]\n \n edge_coords.append(m_graph.get_long_lat(current_node))\n\n if len(current_node) == 5 and len(next_node) == 5:\n if paths[2][i] == True:\n folium.Marker([marker_coords[i][1], marker_coords[i][0]], icon=folium.Icon(color=setColor(len(current_node)),icon=iconMaker(len(current_node)), prefix='fa'), popup=i, tooltip=result_path[1][i]).add_to(m)\n edge_coords.append(m_graph.get_long_lat(next_node))\n folium.PolyLine(edge_coords, color=\"green\").add_to(m)\n edge_coords = []\n else:\n folium.Marker([marker_coords[i][1], marker_coords[i][0]], icon=folium.Icon(color=setColor(len(current_node)),icon=iconMaker(len(current_node)), prefix='fa'), popup=i, tooltip=result_path[1][i]).add_to(m)\n edge_coords.append(m_graph.get_long_lat(next_node))\n folium.PolyLine(edge_coords, color=\"grey\").add_to(m)\n edge_coords = []\n else:\n folium.Marker([marker_coords[i][1], marker_coords[i][0]], icon=folium.Icon(color=setColor(len(current_node)),icon=iconMaker(len(current_node)), prefix='fa'), popup=i, tooltip=result_path[1][i]).add_to(m)\n edge_coords.append(m_graph.get_long_lat(next_node))\n folium.PolyLine(edge_coords, color=\"grey\").add_to(m)\n edge_coords = [] \n elif (MOT == \"W\"):\n singleTransportPlot(paths[1], \"gray\", \"grey\", \"building\")\n elif (MOT == \"M\"):\n marker_coords = []\n edge_coords = []\n changes_Indicator = 0\n\n for i in range(0, len(paths[1])):\n marker_coords.append(m_graph.get_lat_long(paths[1][i]))\n\n current_node = paths[1][i]\n if i+1 < len(paths[1]):\n next_node = paths[1][i+1]\n \n edge_coords.append(m_graph.get_long_lat(current_node))\n\n if len(current_node) == len(next_node):\n folium.Marker([marker_coords[i][1], marker_coords[i][0]], icon=folium.Icon(color=\"darkred\",icon=iconMaker(len(current_node)), prefix='fa'), popup=i, tooltip=result_path[1][i]).add_to(m)\n edge_coords.append(m_graph.get_long_lat(next_node))\n folium.PolyLine(edge_coords, color=setColor(len(current_node))).add_to(m)\n edge_coords = []\n elif len(current_node) != len(next_node):\n if changes_Indicator == 1:\n folium.Marker([marker_coords[i][1], marker_coords[i][0]], icon=folium.Icon(color=\"darkred\",icon=iconMaker(len(current_node)), prefix='fa'), popup=i, tooltip=result_path[1][i]).add_to(m)\n edge_coords.append(m_graph.get_long_lat(next_node))\n folium.PolyLine(edge_coords, color=setColor(len(next_node))).add_to(m)\n edge_coords = []\n changes_Indicator -= 1\n else:\n folium.Marker([marker_coords[i][1], marker_coords[i][0]], icon=folium.Icon(color=\"darkred\",icon=iconMaker(len(current_node)), prefix='fa'), popup=i, tooltip=result_path[1][i]).add_to(m)\n edge_coords.append(m_graph.get_long_lat(next_node))\n folium.PolyLine(edge_coords, color=setColor(len(current_node))).add_to(m)\n edge_coords = []\n changes_Indicator +=1\n\n # Call Set routes and pass in mode of transport and routes\n # Sample Input: [Coming From: PE1], [Coming From: ]\n routePlotting(mode, result_path)\n\n # Initialization of the map\n data = io.BytesIO() # creates a temporary 'container' for html code\n m.save(data, close_file=False) # folium html code is saved inside data variable\n w = QtWebEngineWidgets.QWebEngineView() # then the rest of the code is the map running\n w.setHtml(data.getvalue().decode())\n w.resize(840, 680)\n w.show()\n sys.exit(app.exec_())\n"},{"alpha_fraction":0.5475651025772095,"alphanum_fraction":0.5736126899719238,"avg_line_length":28.797468185424805,"blob_id":"1c9d9bbdec453ad02f5394d547e6cc2088b5334d","content_id":"993bb8dcfa5015924c599b63ce1dc89a5179756f","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":7064,"license_type":"no_license","max_line_length":96,"num_lines":237,"path":"/bus_adj.py","repo_name":"eekhait/1008_Project","src_encoding":"UTF-8","text":"import pandas as pd\nimport main_graph as m_graph\nimport csv\nimport sys\nimport math\nimport numpy as np\n\n\n# Columns: 0-Code, ....... pending\nbusData = pd.read_csv('Punggol_Bus_Routing.csv', sep=',', header=None)\n# Columns: 0-Code, ....... pending\nbusData2 = pd.read_csv('Punggol_Bus_Routing_Type2.csv', sep=',',header=None)\npunggol = pd.read_csv('Complete_Punggol_Graph.csv',sep=',',header=None)\npunggol1 = pd.read_csv('Punggol_complete_graph2.csv',sep=',',header=None)\n\nbus_speed = 50000/60\nbus_waiting_time = 5\n'''\nTest Cases\nstart = \"65141\"\nend = \"65339\"\nnew_start = \"828858\"\nnew_end = \"821266\"\n'''\ndef busStopCode1(data):\n start = (punggol[0] == data)\n return start\n\ndef busStopCode2(data):\n start = punggol1[0] == data\n return start\n\ndef connected(data):\n connected1 = punggol[busStopCode1(data)]\n if connected1.empty is True:\n connected1 = punggol1[busStopCode2(data)]\n hg = []\n test = pd.DataFrame(connected1[6].str.split(',').tolist())\n test1 = pd.DataFrame((connected1[7].str.split(',').tolist()))\n if test.empty == True:\n print(\"no such route For Buses\")\n sys.exit()\n if test1.empty == True:\n print (\"no such route For buses\")\n sys.exit()\n ht =[]\n if len(data) == 5:\n ht.append(int(data))\n # print(int(test1[0].values))\n try:\n niii = max(test1.columns.values)\n except ValueError:\n niii = (test1.columns.values)\n for i in test.iterrows():\n for k in range (0, niii):\n if int(test1[k].values) <=200:\n #for connected nodes and distance\n hg.append(((int(test[k].values)),(int(test1[k].values))))\n #just for connected nodes\n ht.append(int((test[k].values)))\n\n return ht\n\n# For finding starting bus Stop( See csv for column 1 and compare to check for bus stop code)\ndef busStopCode(data):\n startStop = busData2[1] == data\n return startStop\n\n# For finding starting bus Stop( See csv for column 2 and compare to check for bus stop code)\ndef endStopCode(data):\n endStop = busData2[2] == data\n return endStop\n\ndef busNoInserter(data):\n busNo = busData2[0] == data\n return busNo\n\n#For finding the starting point of the bus\ndef busStopCode_startfinder(data):\n length = len(data)\n new_array =[]\n isa =0\n for i in range(0,length):\n test_test = busStopCode(str(data[i]))\n test_test1 = busData2[test_test]\n if test_test1.empty == False:\n new_array.append(test_test1)\n return new_array\n\n#For findin the ending point of the bus\ndef busStopCode_endfinder(data):\n length = len(data)\n new_array =[]\n isa =0\n for i in range(0,length):\n test_test = endStopCode(str(data[i]))\n test_test1 = busData2[test_test]\n if test_test1.empty == False:\n new_array.append(test_test1)\n return new_array\n\n# Checking the routes taken by the buses to see if there is a route to the ending bus stop.\ndef take_bus(start_node, end_node,data):\n bus_route = (busNoInserter(data)) & ((busStopCode(start_node) | endStopCode(end_node)))\n asd =[]\n asd.append(start_node)\n bus_distance = 0\n lol = np.int64(0)\n lol1 = np.int64(0)\n #bus_route = (bus_route[0]) >= 1 & (bus_route[0] <=3)\n route = busData2[bus_route]\n if len(route) < 2:\n pass\n else:\n if route.empty == True:\n pass\n else:\n lol = route.index.values[0]\n try:\n lol1= route.index.values[1]\n except IndexError:\n lol1 = lol\n for i in range (lol,lol1+1):\n if busData2.at[lol,6] != busData2.at[lol1,6]:\n pass\n else:\n bus_distance += int(busData2.at[i,3])\n asd.append(busData2.at[i,2])\n\n if len(asd) < 2:\n asd = []\n return None\n\n\n return (data,asd, math.ceil(bus_distance/bus_speed + bus_waiting_time + (lol1-lol)))\n\n\n#For appending all the routes that could be taken and return the one with the least time\ndef route_finder(new_start, new_end):\n starting = busStopCode_startfinder(connected(new_start))\n ending = busStopCode_endfinder(connected(new_end))\n str1 = ' '\n str2 = ' '\n k = []\n n = []\n for i in range (0,len(starting)):\n bus_to_take = starting[i][0].values\n asd = (starting[i][1].values)\n #bus_to_take , indices = np.unique(asd,return_counts=True)\n for l in bus_to_take:\n try:\n a ,indices= np.unique((starting[i][1].values),return_counts=True)\n b, indices = np.unique((ending[i][2].values),return_counts= True)\n str1 = str1.join(a)\n str2 = str2.join(b)\n if take_bus(str1,str2,l) is None:\n pass\n else:\n p = list(take_bus(str1,str2,l))\n n.append((take_bus(str1,str2,l))[2])\n k.append(p)\n\n except IndexError:\n \"Do Nothing\"\n df = pd.DataFrame(k)\n\n if df.empty == True:\n print(\"No common bus nearby start and end points. Please restart with another option. \")\n sys.exit()\n\n route = df[2] == min(n)\n optimised_route = df[route]\n optimised_route[0], optimised_route[2] = optimised_route[2], optimised_route[0]\n pop = optimised_route.head(1)\n\n first_route = []\n lol = pd.DataFrame(pop[1].tolist())\n\n starting_walk = m_graph.take_walk(new_start,lol[0].values[0])\n lemon =[]\n if ((starting_walk[0]) == 0):\n pass\n else:\n first_route=starting_walk[1]\n first_route.pop(len(first_route)-1)\n\n for i in range(1,len(starting_walk)):\n lemon.append(False)\n\n\n for i in range (0,len(lol)):\n for l in lol:\n first_route.append((lol[l][i]))\n if l == 0:\n pass\n else:\n lemon.append(True)\n\n length = max(lol)\n Last_Point = lol[length].values[0]\n ending_walk = m_graph.take_walk(Last_Point, new_end)\n\n\n if len(ending_walk) <= 2:\n\n end_route = ending_walk[1]\n # print(end_route)\n first_route.append(end_route[0])\n end_route.pop(0)\n first_route.append(end_route[0])\n lemon.append(False)\n else:\n new = np.array(ending_walk[1])\n counter = 1\n for i in range(1, len(new)):\n first_route.append(new[counter])\n lemon.append(False)\n counter = counter + 1\n lemon.append(False)\n k = []\n # all route here\n for i, l in optimised_route.iterrows():\n k.append((l[0], l[1], l[2]))\n route = []\n test1 = pop\n m = test1.index.values[0]\n route.append(test1[0][m]) # time taken is fine\n route[0] += starting_walk[0]\n route[0] += ending_walk[0]\n # print(\"first_route:\", first_route)\n route.append(first_route)\n route.append(lemon) # lemon is fine\n # print(\"\")\n route.append(test1[2][m]) # bus number is fine\n return (route)\n\n# print(\"BUS ROUTE: \", route_finder(\"828858\",\"65009\"))\n\n\n"}],"string":"[\n {\n \"alpha_fraction\": 0.5688451528549194,\n \"alphanum_fraction\": 0.5842322111129761,\n \"avg_line_length\": 42.77777862548828,\n \"blob_id\": \"6448e485c4fcdbbaf2d1225e1d358defac085294\",\n \"content_id\": \"2621f67eeb107180d66ed8257df35c109589baf1\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 6304,\n \"license_type\": \"no_license\",\n \"max_line_length\": 137,\n \"num_lines\": 144,\n \"path\": \"/lrt_adj.py\",\n \"repo_name\": \"eekhait/1008_Project\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import pandas as pd\\nimport csv\\nimport math\\n\\nimport main_graph as m_graph\\n\\nlrtData = pd.read_csv('Punggol_LRT_Routing.csv', sep=',', header=None)\\n\\n\\ndef round_up(n, decimals=0):\\n # this is to round up even is 0.1 above\\n multiplier = 10 ** decimals\\n return math.ceil(n * multiplier) / multiplier\\n\\n\\ndef bfs_route(graph, start, end):\\n # maintain a queue of paths\\n queue = []\\n # push the first path into the queue\\n queue.append([start])\\n while queue:\\n # get the first path from the queue\\n path = queue.pop(0)\\n # get the last node from the path\\n node = path[-1]\\n # path found\\n if node == end:\\n return path\\n # enumerate all adjacent nodes, construct a new path and push it into the queue\\n for adjacent in graph.get(node, []):\\n new_path = list(path)\\n new_path.append(adjacent)\\n queue.append(new_path)\\n\\n\\ndef cal_distance(adj_list_val, result):\\n distance = 0\\n # e.g. PE1, PE2, PE3\\n for i in range(len(result) - 1): # number of time to run\\n for y in range(len(adj_list_val[result[i]])): # e.g. adj_list_val['PE1'] return number of list value\\n if result[i + 1] in adj_list_val[result[i]][\\n y]: # e.g. check if PE2 is in adj_list_val['PE1'][0] or adj_list_val['PE1'][1] LISTING\\n distance += int(adj_list_val[result[i]][y][result[\\n i + 1]]) # e.g. adj_list_val['PE1'][0][['PE2'] will return the distance weightage\\n return distance\\n\\n\\ndef take_lrt(start_node, end_node):\\n start_node = str(start_node) # Store the start name\\n end_node = str(end_node) # Store the end name\\n walk_start_node = [] # Store the array from the TAKE_WALK Function FROM START POINT TO LRT\\n walk_end_node = [] # Store the array from the TAKE_WALK Function FROM LRT TO END POINT\\n lrt_name = [] # Store the LRT NAME\\n lrt_code = [] # Store the LRT CODE\\n adj_list = {} # Store the Adj list\\n adj_list_val = {} # Store the Adj list with value\\n with open('Punggol_LRT_Routing.csv', 'r') as csv_file:\\n reader = csv.reader(csv_file)\\n first = True\\n for row in reader:\\n if (first == True):\\n for i in range(len(row)):\\n first = False\\n else:\\n # for i in range(0, len(row)):\\n # # key_value = {row[0]: row[2].split()} # This is to create the Adj\\n lrt_name.append(row[1]) # Append the LRT NAME into the lrt_name\\n lrt_code.append(row[0]) # Append the LRT CODE into the lrt_code\\n keys = row[2].split(\\\", \\\")\\n values = row[3].split(\\\", \\\")\\n add_value = []\\n for i in range(len(keys)):\\n add_value.append({keys[i]: values[i]}) # Create a list of dict e.g. 'PE1' : 1010\\n adj_list_val[row[0]] = add_value # Append the linked code into the list\\n adj_list[row[0]] = row[2].split(\\\", \\\") # Append the linked code into the list\\n\\n # Check if start node is mrt or blocks\\n if start_node in lrt_name:\\n # Convert the LRT NAME INTO LRT CODE\\n for i in range(len(adj_list)):\\n if lrt_name[i] == start_node:\\n start_node = lrt_code[i] # Convert start_node Into LRT CODE\\n break\\n else:\\n temp_string_start_node = start_node # Store the postal code\\n start_node = m_graph.get_nearest_lrt(start_node) # To Store the nearest LRT station with the postal code\\n walk_start_node = m_graph.take_walk(temp_string_start_node, start_node) # Store the walking node from Start of Postal Code to LRT\\n\\n if end_node in lrt_name:\\n for i in range(len(adj_list)):\\n if lrt_name[i] == end_node:\\n end_node = lrt_code[i] # Convert end_noce Into LRT CODE\\n break\\n else:\\n temp_string_end_node = end_node # Store the postal code\\n end_node = m_graph.get_nearest_lrt(end_node) # To Store the nearest LRT station with the postal code\\n walk_end_node = m_graph.take_walk(end_node, temp_string_end_node) # Store the walking node from LRT To the End of Postal code\\n\\n\\n\\n # if start and end are connected\\n if m_graph.is_adjacent_lrt(adj_list, start_node, end_node):\\n result = [start_node, end_node]\\n\\n # average SG MRT 45km/h == 12.5m/s\\n # Calculate the timing Second in minutes,\\n distance = cal_distance(adj_list_val, result)\\n timing = round_up((distance / 12.5) / 60)\\n\\n # Check if there any array\\n if len(walk_start_node) != 0:\\n del result[0] # To delete the first array as is duplicated\\n result = walk_start_node[1] + result # Combine the Walking array with result (LRT)\\n timing = walk_start_node[0] + timing # Combine the Time required\\n if len(walk_end_node) != 0:\\n del result[-1] # To delete the last array as is duplicated\\n result = result + walk_end_node[1] # Combine the result (LRT) with Walking array\\n return [int(timing), result]\\n else:\\n result = (bfs_route(adj_list, start_node, end_node))\\n\\n # average SG MRT 45km/h == 12.5m/s\\n # Calculate the timing Second in minutes,\\n distance = cal_distance(adj_list_val, result)\\n timing = round_up((distance / 12.5) / 60)\\n # average timing stop at each mrt is 30second == 0.5\\n mrt_stopping = 0.5 * int(len(result) - 1)\\n # Calculate the timing Second in minutes,\\n timing = round_up((distance / 12.5) / 60) + mrt_stopping\\n # Add another 5 min flat waiting for the train to arrival\\n timing = timing + 5\\n\\n if len(walk_start_node) != 0:\\n del result[0] # To delete the first array as is duplicated\\n result = walk_start_node[1] + result # Combine the Walking array with result (LRT)\\n timing = walk_start_node[0] + timing # Combine the Time required\\n if len(walk_end_node) != 0:\\n del result[-1] # To delete the last array as is duplicated\\n result = result + walk_end_node[1] # Combine the result (LRT) with Walking array\\n\\n # print([int(timing), result])\\n return [int(timing), result]\\n\\n# print(\\\"LRT ROUTE: \\\", take_lrt(\\\"828858\\\",\\\"65009\\\"))\\n\"\n },\n {\n \"alpha_fraction\": 0.535467803478241,\n \"alphanum_fraction\": 0.5473470091819763,\n \"avg_line_length\": 33.5234375,\n \"blob_id\": \"734a621e48078d64bb4301cd28ecb71513e7e2ce\",\n \"content_id\": \"d96a7c5f2e19546ca3844f59f17e0587283b975e\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 8839,\n \"license_type\": \"no_license\",\n \"max_line_length\": 107,\n \"num_lines\": 256,\n \"path\": \"/main_graph.py\",\n \"repo_name\": \"eekhait/1008_Project\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import pandas as pd\\n\\n\\n# THIS PART CONCERNS WITH:\\n# THE CSV FILES AND EXTRACTING DATA FROM THEM\\n# --------------------------------- #\\n# Indexes of the Complete_Punggol_Graph.csv file:\\n# Columns: 0-Code, 1-Name, 2-Type, 3-Latitude, 4-Longitude, 5-Buses, 6-ConnectedWalks, 7-ConnectedDistances\\n# Columns: 8-1197 to refer to nodes (+7 difference from corresponding node in rows)\\n# Rows: 1-1190 to refer to nodes\\n# --------------------------------- #\\n# How to use pandas dataframe (treat it as a 2D array/excel file):\\n# mainGraph.at[row,column]\\n# --------------------------------- #\\nmainGraph = pd.read_csv('Complete_Punggol_Graph.csv', sep=',', header=None)\\nmainGraph[0] = mainGraph[0].apply(str) # converts column to be string-only (rather than int+str)\\nstartIndex = 1\\nendIndex = len(mainGraph.index)\\n# --------------------------------- #\\n\\n\\ndef get_distance_to_from(point_a, point_b):\\n index_a = get_node_index(point_a)+7\\n index_b = get_node_index(point_b)\\n return int(mainGraph.at[index_b, index_a])\\n\\n\\ndef get_long_lat(target):\\n index = get_node_index(target)\\n return [round(float(mainGraph.at[index, 3]), 4), round(float(mainGraph.at[index, 4]), 4)]\\n\\n\\ndef get_lat_long(target):\\n index = get_node_index(target)\\n return [round(float(mainGraph.at[index, 4]), 4), round(float(mainGraph.at[index, 3]), 4)]\\n\\n\\ndef get_node_index(target):\\n # Start location codes are from index 1 to 1190\\n # print(type(target),target)\\n target=str(target)\\n low = startIndex\\n high = endIndex\\n mid = (startIndex+endIndex)//2\\n while target != str(mainGraph.at[mid, 0]):\\n if target < str(mainGraph.at[mid, 0]): # if target is in smaller half\\n high = mid\\n if mid == (low+high)//2:\\n return -1\\n mid = (low+high)//2\\n elif target > str(mainGraph.at[mid, 0]): # if target is in larger half\\n low = mid\\n if mid == (low+high)//2:\\n return -1\\n mid = (low+high)//2\\n return mid\\n\\n\\ndef get_nearest_bus_stops(target, distance):\\n pass\\n\\n\\ndef get_nearest_lrt(target):\\n if len(target) == 3:\\n return target\\n else:\\n index = get_node_index(target)\\n node = \\\"\\\"\\n distance = 3000\\n for i in range(endIndex+7-14, endIndex+7): # start and end of LRT columns in csv\\n if int(mainGraph.at[index, i]) < distance:\\n node = mainGraph.at[0, i]\\n distance = int(mainGraph.at[index, i])\\n return str(node)\\n\\n\\ndef get_adjacent_walks(start_node):\\n start_index = get_node_index(start_node)\\n connected_nodes = mainGraph.at[start_index, 6].split(', ')\\n return connected_nodes\\n\\n\\ndef is_adjacent_walk(start_node, end_node):\\n start_index = get_node_index(start_node)\\n connected_nodes = mainGraph.at[start_index, 6].split(', ')\\n if end_node in connected_nodes:\\n return True\\n else:\\n return False\\n\\n\\ndef is_adjacent_bus(start_node, end_node):\\n pass\\n\\n\\ndef is_adjacent_lrt(adj_list, start_node, end_node):\\n # Check If Are Both LRT are directly connected!\\n for i in adj_list:\\n if start_node == i: # To check if able to found the KEY\\n if end_node in adj_list[i]: # To check if both Start_Node & End_Node are directly connected\\n return 1 # If Yes, return 1\\n else:\\n return 0 # If No, return 0\\n\\n\\n# ----------------------------------\\n# THIS PART CONCERNS WITH ALGORITHMS:\\n# ----------------------------------\\nclass AStarStack:\\n def __init__(self):\\n self.top = -1\\n self.data = []\\n self.total_distance = 0\\n self.distance_to_end = 0\\n\\n def show_stack(self):\\n print(\\\"start\\\")\\n for i in self.data:\\n print(i)\\n print(\\\"end\\\")\\n\\n def push(self, node, val):\\n self.top += 1\\n self.data.append(node)\\n if self.top > 0: # if there is at least two elements...\\n self.total_distance += get_distance_to_from(self.data[self.top], self.data[self.top-1])\\n self.distance_to_end = val\\n\\n # def pop(self):\\n # if self.top > -1:\\n # node = self.data[self.top]\\n # if self.top > 0:\\n # self.total_distance -= get_distance_to_from(self.data[self.top], self.data[self.top-1])\\n # del self.data[self.top]\\n # self.top -= 1\\n # return node\\n\\n def is_empty(self):\\n if self.top < 0:\\n return True\\n else:\\n return False\\n\\n def peek(self):\\n if not self.is_empty():\\n return self.data[self.top]\\n\\n def peek_distance(self):\\n if not self.is_empty():\\n return self.total_distance\\n\\n def copy_from(self, a_stack):\\n for x in a_stack.data:\\n self.push(x, a_stack.distance_to_end)\\n\\n\\nclass AStarQueue:\\n def __init__(self):\\n self.top = -1\\n self.data = []\\n self.distances_to_target = []\\n\\n def enqueue(self, node):\\n temp = node.distance_to_end\\n front = 1\\n back = self.top\\n mid = (front+back)//2\\n if self.top > -1:\\n # print(str(temp) + \\\" \\\" + str(self.distances_to_target[0]))\\n if temp < self.distances_to_target[0]: # add to the front\\n self.data.insert(0, node)\\n self.distances_to_target.insert(0, temp)\\n elif temp > self.distances_to_target[self.top]: # add to the back\\n self.data.append(node)\\n self.distances_to_target.append(temp)\\n else:\\n while temp != self.distances_to_target[mid] and front != mid:\\n if temp < self.distances_to_target[mid]:\\n back = mid\\n mid = (front + back) // 2\\n elif temp > self.distances_to_target[mid]:\\n front = mid\\n mid = (front + back) // 2\\n # if temp == self.distances_to_target[mid]\\n self.data.insert(mid, node)\\n self.distances_to_target.insert(mid, temp)\\n elif self.top < 0:\\n self.data.append(node)\\n self.distances_to_target.append(temp)\\n self.top += 1\\n # print(\\\"[\\\", end='')\\n # for i in self.data:\\n # print(str(i.distance_to_end) + \\\", \\\", end='')\\n # print(\\\"]\\\")\\n # print(str(self.distances_to_target))\\n\\n def dequeue(self):\\n if self.top > -1:\\n temp = self.data[0]\\n del self.data[0]\\n del self.distances_to_target[0]\\n self.top -= 1\\n return temp\\n\\n def is_empty(self):\\n if self.top < 0:\\n return True\\n else:\\n return False\\n\\n def peek(self):\\n if not self.is_empty():\\n return self.data[0]\\n\\n\\ndef take_walk(start_node, end_node):\\n start_node = str(start_node)\\n end_node = str(end_node)\\n # if start and end are connected\\n if is_adjacent_walk(start_node, end_node):\\n return [1, [start_node, end_node]]\\n else: # this part begins like the word ladder\\n # initialization of queue and first stack (of just start node)\\n # also initialization of visited nodes\\n star_queue = AStarQueue()\\n star_stack = AStarStack()\\n star_stack.push(start_node, get_distance_to_from(start_node, end_node))\\n star_queue.enqueue(star_stack)\\n visited_nodes = {}\\n counter = 0\\n # while end node is not reached\\n while star_queue.data[0].peek() != end_node:\\n # dequeue the first stack\\n temp_stack = star_queue.dequeue()\\n mid_node = temp_stack.peek()\\n # add all adjacent nodes to mid_node in separate stacks\\n # move stacks to queue\\n for i in get_adjacent_walks(mid_node):\\n # create new stack with each adjacent node\\n temper_stack = AStarStack()\\n temper_stack.copy_from(temp_stack)\\n temper_stack.push(str(i), get_distance_to_from(str(i), end_node))\\n # temper_stack.show_stack()\\n # if node is visited before\\n if i in visited_nodes:\\n # only enqueue if new path/stack is shorter than old path\\n if temper_stack.total_distance < visited_nodes[i]:\\n star_queue.enqueue(temper_stack)\\n visited_nodes[i] = temper_stack.total_distance\\n # if node is new, enqueue normally\\n elif i not in visited_nodes:\\n # enqueue the stack\\n star_queue.enqueue(temper_stack)\\n visited_nodes[i] = temper_stack.total_distance\\n # return assumes a walking speed of 5km/h. first element is time taken in minutes\\n return [round(star_queue.data[0].total_distance/5000*60), star_queue.data[0].data]\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.7825203537940979,\n \"alphanum_fraction\": 0.7876016497612,\n \"avg_line_length\": 32.89655303955078,\n \"blob_id\": \"a9279f2eab0fb5749fedddfab8ee9bbd465939c5\",\n \"content_id\": \"465f2746e9c27b36e44542024b69717a2b977f55\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 984,\n \"license_type\": \"no_license\",\n \"max_line_length\": 170,\n \"num_lines\": 29,\n \"path\": \"/README.md\",\n \"repo_name\": \"eekhait/1008_Project\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# 1008_Project\\nPunggol Pathfinder\\n\\n\\n*Introduction*\\nAn application that lets users find a path (from a start and end node input) within Punggol. They will be able to select the main method of travel (Bus, LRT, or Walking).\\n\\nThe output includes strings printed by the console as well as a graph that shows the path the user has to take. \\n\\n\\n*Installation*\\nThe application has been developed with the following:\\nPyCharm - https://www.jetbrains.com/pycharm/download/#section=windows\\nGit - https://git-scm.com/download \\nAnaconda - https://www.anaconda.com/distribution/#download-section\\n\\nThe following line of pip install is also required:\\npip install folium PyQt5 PyQtWebEngine\\n\\n\\n*How to Use*\\nRun map.py and follow the instructions displayed. \\nIn order, the console will ask for:\\nStart location\\nEnd location\\nLocation confirmation\\nMethod of travel\\n\\nThereafter, an estimated time of travel is shown together with a list of nodes in the path, and the method of connection between the nodes. \\n\"\n },\n {\n \"alpha_fraction\": 0.5936199426651001,\n \"alphanum_fraction\": 0.6393897533416748,\n \"avg_line_length\": 40.20000076293945,\n \"blob_id\": \"5ed6b9f0026b640978f9f27e464ff7dee2149f2a\",\n \"content_id\": \"000a43277cfd3b899256979bb65da46950dd452c\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1442,\n \"license_type\": \"no_license\",\n \"max_line_length\": 107,\n \"num_lines\": 35,\n \"path\": \"/oldfiles/DistanceTabulator.py\",\n \"repo_name\": \"eekhait/1008_Project\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import pandas as pd\\nfrom geopy.distance import geodesic\\n\\n# Take note:\\n# Latitude is vertical (How 'north-south' a place is)\\n# Longitude is horizontal (How 'east-west' a place is)\\ndistance_table = pd.read_csv(\\\"Punggol Coordinates.csv\\\", header=None)\\n\\n# to mimic cell selection in pandas dataframe, for iteration\\n# iloc[horizontal, vertical]\\n# iloc[1123, 1119] <--- most bottom right value\\n# 0,0 0,1 0,2 0,3 0,4...\\n# postal_code Street Latitude Longitude 820136...\\n\\n# FOR EVERY ROW... (Skips header row)\\nfor i in range(1, 1191): # 1191\\n # FOR EVERY COLUMN... (Skips first 4 already-populated columns)\\n nearbyNodes = []\\n nearbyDistances = []\\n for j in range(7, 1197):\\n # Assign distance between nodes in meters\\n distance = 1000 * round(geodesic((distance_table.iloc[i, 2], distance_table.iloc[i, 3]),\\n (distance_table.iloc[j-6, 2], distance_table.iloc[j-6, 3])).km, 3)\\n distance_table.iloc[i, j] = distance\\n if 0 < distance < 180:\\n nearbyNodes.append(str(distance_table.iloc[j-6, 0]))\\n nearbyDistances.append(int(distance))\\n distance_table.iloc[i, 5] = str(nearbyNodes)\\n distance_table.iloc[i, 6] = str(nearbyDistances)\\n\\n # Prints progress of population per row\\n print(round(i / 1191 * 100, 2))\\n\\n# Create new csv\\ndistance_table.to_csv('Complete_Punggol_Graph.csv', header=False, index=False)\\n\"\n },\n {\n \"alpha_fraction\": 0.501806378364563,\n \"alphanum_fraction\": 0.5308887362480164,\n \"avg_line_length\": 36.4054069519043,\n \"blob_id\": \"a93d902b55395015fdedbf4179e38abe46e389aa\",\n \"content_id\": \"f4e62748caa9e7020e1db37b271a7b89aaa78b5a\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 5536,\n \"license_type\": \"no_license\",\n \"max_line_length\": 223,\n \"num_lines\": 148,\n \"path\": \"/oldfiles/LRT_Algorithm.py\",\n \"repo_name\": \"eekhait/1008_Project\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from collections import deque\\nimport csv\\n\\n\\nclass Graph:\\n def __init__(self, lists):\\n self.lists = lists\\n\\n def get_neighbours(self, i):\\n return self.lists[i]\\n\\n import csv\\n cove_lrt, meridian_lrt, coraledge_lrt, riviera_lrt, kadaloor_lrt, oasis_lrt, damai_lrt, punggol_lrt, samkee_lrt, tecklee_lrt, punggolpoint_lrt, samudera_lrt, nibong_lrt, sumang_lrt, sooteck_lrt = ([] for i in range(15))\\n\\n with open('LRT.csv') as file:\\n lrt = list(csv.reader(file))\\n cove_lrt.append(lrt[1])\\n meridian_lrt.append(lrt[2])\\n coraledge_lrt.append(lrt[3])\\n riviera_lrt.append(lrt[4])\\n kadaloor_lrt.append(lrt[5])\\n oasis_lrt.append(lrt[6])\\n damai_lrt.append(lrt[7])\\n punggol_lrt.append(lrt[8])\\n samkee_lrt.append(lrt[9])\\n tecklee_lrt.append(lrt[10])\\n punggolpoint_lrt.append(lrt[11])\\n samudera_lrt.append(lrt[12])\\n nibong_lrt.append(lrt[13])\\n sumang_lrt.append(lrt[14])\\n sooteck_lrt.append(lrt[15])\\n\\n #heuristic function for all nodes\\n def heuristic(self, n):\\n Heuristic = {\\n 'Punggol_MRT': 1,\\n 'SamKee_LRT': 1,\\n 'SooTeck_LRT': 1,\\n 'PunggolPoint_LRT': 1,\\n 'Samudera_LRT': 1,\\n 'Sumang_LRT': 1,\\n 'Nibong_LRT': 1,\\n 'Damai_LRT': 1,\\n 'Kadaloor_LRT': 1,\\n 'Riviera_LRT': 1,\\n 'CoralEdge_LRT': 1,\\n 'Meridian_LRT': 1,\\n 'Oasis_LRT': 1,\\n 'Cove_LRT': 1,\\n }\\n return Heuristic[n]\\n\\n def astar_algorithm(self, start_node, stop_node):\\n # open_list is a list of nodes which have been visited, but who's neighbors\\n # haven't all been inspected, starts off with the start node\\n # closed_list is a list of nodes which have been visited\\n # and who's neighbors have been inspected\\n open_list = set([start_node])\\n closed_list = set([])\\n\\n # cdist contains current distances from start_node to all other nodes\\n # the default value (if it's not found in the map) is +infinity\\n cdist = {}\\n\\n cdist[start_node] = 0\\n\\n # parents contains an adjacency map of all nodes\\n parents = {}\\n parents[start_node] = start_node\\n\\n while len(open_list) > 0:\\n n = None\\n\\n # find a node with the lowest value of f() - evaluation function\\n for i in open_list:\\n if n == None or cdist[i] + self.heuristic(i) < cdist[n] + self.heuristic(n):\\n n = i;\\n\\n if n == None:\\n print('Path does not exist!')\\n return None\\n\\n # if the current node is the stop_node\\n # then we begin reconstructing the path from it to the start_node\\n if n == stop_node:\\n reconst_path = []\\n\\n while parents[n] != n:\\n reconst_path.append(n)\\n n = parents[n]\\n\\n reconst_path.append(start_node)\\n\\n reconst_path.reverse()\\n print('Path found: {}'.format(reconst_path))\\n return reconst_path\\n\\n # for all neighbors of the current node do\\n for (m, weight) in self.get_neighbours(n):\\n # if the current node isn't in both open_list and closed_list\\n # add it to open_list and note n as it's parent\\n if m not in open_list and m not in closed_list:\\n open_list.add(m)\\n parents[m] = n\\n cdist[m] = cdist[n] + weight\\n\\n # otherwise, check if it's quicker to first visit n, then m\\n # and if it is, update parent data and g data\\n # and if the node was in the closed_list, move it to open_list\\n else:\\n if cdist[m] > cdist[n] + weight:\\n cdist[m] = cdist[n] + weight\\n parents[m] = n\\n\\n if m in closed_list:\\n closed_list.remove(m)\\n open_list.add(m)\\n\\n # remove n from the open_list, and add it to closed_list\\n # because all of his neighbors were inspected\\n open_list.remove(n)\\n closed_list.add(n)\\n\\n print('Path does not exist!')\\n return None\\n\\nlists = {\\n # LRT on Punggol East\\n 'Punggol_MRT': [('SamKee_LRT', 0.589), ('SooTeck_LRT', 0.605), ('Damai_LRT', 0.690), ('Cove_LRT', 0.763)],\\n 'SamKee_LRT': [('Punggol_MRT', 0.589), ('PunggolPoint_LRT', 0.815)],\\n 'PunggolPoint_LRT': [('SamKee_LRT', 0.815), ('Samudera_LRT', 0.513)],\\n 'Samudera_LRT': [('PunggolPoint_LRT', 0.513), ('Nibong_LRT', 0.493)],\\n 'Nibong_LRT': [('Samudera_LRT', 0.493), ('Sumang_LRT', 0.429)],\\n 'Sumang_LRT': [('Nibong_LRT', 0.429), ('SooTeck_LRT', 0.478)],\\n 'SooTeck_LRT': [('Sumang_LRT', 0.478), ('Punggol_MRT', 0.605)],\\n\\n # LRT on Punggol West\\n 'Damai_LRT': [('Punggol_MRT', 0.690), ('Oasis_LRT', 0.563)],\\n 'Oasis_LRT': [('Damai_LRT', 0.563), ('Kadaloor_LRT', 0.515)],\\n 'Kadaloor_LRT': [('Oasis_LRT', 0.515), ('Riviera_LRT', 0.558)],\\n 'Riviera_LRT': [('Kadaloor_LRT', 0.558), ('CoralEdge_LRT', 0.386)],\\n 'CoralEdge_LRT': [('Riviera_LRT', 0.386), ('Meridian_LRT', 0.530)],\\n 'Meridian_LRT': [('CoralEdge_LRT', 0.530), ('Cove_LRT', 0.443)],\\n 'Cove_LRT': [('Meridian_LRT', 0.443), ('Punggol_MRT', 0.763)],\\n}\\n\\ngraph1 = Graph(lists)\\ngraph1.astar_algorithm('Samudera_LRT', 'Riviera_LRT')\\n\"\n },\n {\n \"alpha_fraction\": 0.5070756077766418,\n \"alphanum_fraction\": 0.5182813405990601,\n \"avg_line_length\": 46.324241638183594,\n \"blob_id\": \"7f79b81551c8f3b2dd70426d2d508f5d62150620\",\n \"content_id\": \"e556747388939d07b81a3c4d3f4b171f78cf81d5\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 15617,\n \"license_type\": \"no_license\",\n \"max_line_length\": 227,\n \"num_lines\": 330,\n \"path\": \"/map.py\",\n \"repo_name\": \"eekhait/1008_Project\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import folium\\nimport io\\nimport sys\\nimport main_graph as m_graph\\nimport bus_adj as bus_graph\\nimport lrt_adj as lrt_graph\\nimport pandas as pd\\nfrom PyQt5 import QtWidgets, QtWebEngineWidgets\\nimport csv\\n\\n# ----------------------------------\\n# THIS PART CONCERNS WITH UI\\n# EVERYTHING COMES TOGETHER HERE\\n# ----------------------------------\\nif __name__ == \\\"__main__\\\":\\n app = QtWidgets.QApplication(sys.argv)\\n # Create map object, set default location, map theme & zoom\\n m = folium.Map(location=[1.4046357, 103.9090000], zoom_start=14.5, prefer_canvas=True)\\n # Global tooltip, hover info\\n tooltip = 'Click For More Info'\\n\\n # ASKS FOR INPUT/OUTPUT HERE, EVERYTHING TAKEN IN AS STRING (Irvyn)\\n def check(start):\\n with open('Complete_Punggol_Graph.csv', 'rt') as f:\\n reader = csv.reader(f, delimiter=',')\\n for row in reader:\\n if start == row[0] or start == row[1]:\\n location.append(row[0])\\n name.append(row[1])\\n return location, name\\n\\n def confirmation(msg):\\n while True:\\n answer = input(msg).upper()\\n if answer in ('Y', 'N'):\\n return answer\\n else:\\n print('Not a valid input, please try again')\\n\\n def transportation(tp):\\n while True:\\n mode = input(tp).upper()\\n if mode in ('L', 'B', 'W', 'M'):\\n return mode\\n else:\\n print('Not a valid input, please try again')\\n\\n def show_walks():\\n # Used to create a file to show graph of connectivity\\n # This one is just nodes that are of walkable distance\\n marked = []\\n for i in range(1, len(m_graph.mainGraph[0])):\\n for j in list(m_graph.mainGraph.at[i, 6].split(\\\", \\\")):\\n # print(m_graph.mainGraph[0][i], j)\\n if [m_graph.mainGraph[0][i], j] not in marked and [j, m_graph.mainGraph[0][i]] not in marked:\\n coords_to_add = [m_graph.get_long_lat(m_graph.mainGraph[0][i]), m_graph.get_long_lat(j)]\\n # print(coords_to_add)\\n marked.append(coords_to_add)\\n folium.PolyLine(coords_to_add, color=\\\"grey\\\", opacity=0.5, weight=0.5).add_to(m)\\n m.save(\\\"walks.html\\\")\\n\\n def show_lrts():\\n # Used to create a file to show graph of connectivity\\n # This one is just the LRTs, and what blocks are 'connected' to them\\n marked = []\\n # Buildings and their closest LRTs\\n for i in range(1, len(m_graph.mainGraph[0])-14):\\n closest_lrt = m_graph.get_nearest_lrt(m_graph.mainGraph[0][i])\\n if [m_graph.mainGraph[0][i], closest_lrt] not in marked and [closest_lrt, m_graph.mainGraph[0][i]] not in marked:\\n coords_to_add = [m_graph.get_long_lat(m_graph.mainGraph[0][i]), m_graph.get_long_lat(closest_lrt)]\\n marked.append(coords_to_add)\\n folium.PolyLine(coords_to_add, color=\\\"grey\\\", opacity=1, weight=1).add_to(m)\\n # Markers for LRTs\\n marked = []\\n marked2 = []\\n with open('Punggol_LRT_Routing.csv', 'rt') as lrt:\\n reader = csv.reader(lrt, delimiter=',')\\n next(reader)\\n for row in reader:\\n for i in row[2].split(\\\", \\\"): # connected nodes\\n if [row, i] not in marked and [i, row] not in marked:\\n # print(row[0], i)\\n coords_to_add = [m_graph.get_long_lat(row[0]), m_graph.get_long_lat(i)]\\n marked.append(coords_to_add)\\n folium.PolyLine(coords_to_add, color=\\\"purple\\\").add_to(m)\\n if coords_to_add not in marked2:\\n folium.Marker(coords_to_add[0],\\n icon=folium.Icon(color=\\\"purple\\\", icon=\\\"train\\\", prefix='fa'),\\n popup=i, tooltip=row[0]).add_to(m)\\n marked2.append(coords_to_add[0])\\n # Edges between LRTs\\n marked = []\\n m.save(\\\"lrts.html\\\")\\n\\n def show_buses():\\n b_graph = pd.read_csv('Punggol_Bus_Routing_Type2.csv', sep=',')\\n b_graph[\\\"ServiceNo\\\"] = b_graph[\\\"ServiceNo\\\"].apply(str) # converts column to be string-only (rather than int+str)\\n b_graph[\\\"NextStop\\\"] = b_graph[\\\"NextStop\\\"].apply(str) # converts column to be string-only (rather than int+str)\\n marked = []\\n for i in range(0,len(b_graph[\\\"ServiceNo\\\"])):\\n longlats = [m_graph.get_long_lat(b_graph.at[i, \\\"BusStopCode\\\"]), m_graph.get_long_lat(b_graph.at[i, \\\"NextStop\\\"])]\\n # add marker (latlong)\\n if b_graph.at[i, \\\"BusStopCode\\\"] not in marked:\\n folium.Marker(m_graph.get_long_lat(b_graph.at[i, \\\"BusStopCode\\\"]),\\n icon=folium.Icon(color=\\\"green\\\", icon=\\\"bus\\\", prefix='fa'),popup=\\\"\\\",tooltip=\\\"\\\").add_to(m)\\n marked.append(i)\\n # add edge (longlat)\\n folium.PolyLine(longlats, color=\\\"green\\\", weight=2, opacity=0.75).add_to(m)\\n m.save(\\\"buses.html\\\")\\n\\n\\n # show_walks()\\n # show_lrts()\\n # show_buses()\\n print(\\\"\\\\nWelcome to Punggol Pathfinder\\\")\\n print(\\\"Valid inputs are: \\\\033[1m Postal codes, bus stop numbers, train station names, train station codes. \\\\033[0m\\\")\\n\\n while True:\\n name = []\\n # User start and end code will be stored in here\\n location = []\\n # User choosen mode will stored in here\\n mode = []\\n result_path = []\\n # Prompt user for start and destination point\\n start = input(\\\"\\\\nWhere are you coming from?\\\\n\\\")\\n end = input(\\\"Where is your destination?\\\\n\\\")\\n check(start)\\n check(end)\\n\\n # Calls function to check if input is valid by comparing with CSV\\n if len(location) != 2:\\n print(\\\"Location not valid, please try again\\\\n\\\")\\n continue\\n else:\\n sp = name[0]\\n ep = name[1]\\n\\n if sp:\\n print(\\\"Start location: \\\", sp)\\n else:\\n print(\\\"Start location: \\\", start)\\n if ep:\\n print(\\\"Destination: \\\", ep)\\n else:\\n print(\\\"Destination: \\\", end)\\n\\n answer = confirmation(\\\"\\\\nConfirm start location and destination? [Y/N] \\\\n\\\")\\n if answer == 'N':\\n print(\\\"Let\\\\'s try again\\\")\\n elif answer == 'Y':\\n mode = transportation(\\\"Select mode of transport: LRT (L), Bus (B), Walk (W), or Mixed (M)\\\\n\\\")\\n if mode == 'L':\\n # Call Lrt algorithm here\\n result_path = lrt_graph.take_lrt(location[0], location[1])\\n\\n print(\\\"Time taken:\\\", result_path[0], \\\"mins\\\")\\n print(\\\"Take LRT from\\\")\\n for i in range(0, len(result_path[1])):\\n print(result_path[1][i])\\n if len(result_path[1]) - 1 != i:\\n print(\\\"to\\\")\\n elif mode == 'B':\\n # Call Bus algorithm here\\n result_path = bus_graph.route_finder(location[0], location[1])\\n print(\\\"Time taken:\\\", result_path[0], \\\"mins\\\")\\n print(\\\"From\\\")\\n for i in range(0, len(result_path[1])):\\n print(result_path[1][i])\\n if (result_path[2][i]) == True:\\n print(\\\"Take bus\\\", result_path[3], \\\"to \\\")\\n else:\\n if len(result_path[1]) - 1 != i:\\n print(\\\"Walk to\\\")\\n elif mode == 'W':\\n # Call Walk algorithm here\\n result_path = m_graph.take_walk(location[0], location[1])\\n\\n print(\\\"Time taken:\\\", result_path[0], \\\"mins\\\")\\n print(\\\"Walk from\\\")\\n for i in range(0, len(result_path[1])):\\n print(result_path[1][i])\\n if len(result_path[1]) - 1 != i:\\n print(\\\"to\\\")\\n elif mode == 'M':\\n # Call Mixed algorithm here\\n print(\\\"Option not implemented. Please try again with a different options\\\")\\n sys.exit()\\n break\\n\\n\\n # (khai)\\n # THIS PART IS WHERE THE MAP GETS POPULATED WITH NODES AND EDGES ---------------------------------------------\\n\\n # Adding of markers and edges for Single Transport Routes\\n def singleTransportPlot(paths, markerColor, lineColor, markerIcon):\\n marker_coords = []\\n edge_coords = []\\n for i in paths:\\n # this loop creates a list of coordinates to add markers/nodes with\\n marker_coords.append(m_graph.get_lat_long(i))\\n edge_coords.append(m_graph.get_long_lat(i))\\n\\n for i in range(0, len(marker_coords)):\\n folium.Marker([marker_coords[i][1], marker_coords[i][0]],\\n icon=folium.Icon(color=markerColor, icon=markerIcon, prefix='fa'), popup=i,\\n tooltip=result_path[1][i]).add_to(m)\\n folium.PolyLine(edge_coords, color=lineColor).add_to(m)\\n\\n # Set icon for different transportation types\\n def iconMaker(length):\\n if length == 3:\\n return \\\"train\\\"\\n elif (length == 5):\\n return \\\"bus\\\"\\n elif length == 6:\\n return \\\"building\\\"\\n\\n # Set color based on transportation type\\n def setColor(length):\\n if length == 3:\\n return \\\"purple\\\"\\n elif (length == 5):\\n return \\\"green\\\"\\n elif length == 6:\\n return \\\"gray\\\" \\n\\n\\n # Set route based on different transport\\n def routePlotting(MOT, paths):\\n changes_Indicator = 0\\n if (MOT == \\\"L\\\"):\\n marker_coords = []\\n edge_coords = []\\n\\n for i in range(0, len(paths[1])):\\n marker_coords.append(m_graph.get_lat_long(paths[1][i]))\\n\\n current_node = paths[1][i]\\n if i+1 < len(paths[1]):\\n next_node = paths[1][i+1]\\n \\n edge_coords.append(m_graph.get_long_lat(current_node))\\n\\n if len(current_node) == 3 and len(next_node) == 3:\\n folium.Marker([marker_coords[i][1], marker_coords[i][0]], icon=folium.Icon(color=setColor(len(current_node)),icon=iconMaker(len(current_node)), prefix='fa'), popup=i, tooltip=result_path[1][i]).add_to(m)\\n edge_coords.append(m_graph.get_long_lat(next_node))\\n folium.PolyLine(edge_coords, color=\\\"purple\\\").add_to(m)\\n edge_coords = []\\n else:\\n folium.Marker([marker_coords[i][1], marker_coords[i][0]], icon=folium.Icon(color=setColor(len(current_node)),icon=iconMaker(len(current_node)), prefix='fa'), popup=i, tooltip=result_path[1][i]).add_to(m)\\n edge_coords.append(m_graph.get_long_lat(next_node))\\n folium.PolyLine(edge_coords, color=\\\"grey\\\").add_to(m)\\n edge_coords = [] \\n elif (MOT == \\\"B\\\"):\\n marker_coords = []\\n edge_coords = []\\n\\n for i in range(0, len(paths[1])):\\n marker_coords.append(m_graph.get_lat_long(paths[1][i]))\\n\\n current_node = paths[1][i]\\n if i+1 < len(paths[1]):\\n next_node = paths[1][i+1]\\n \\n edge_coords.append(m_graph.get_long_lat(current_node))\\n\\n if len(current_node) == 5 and len(next_node) == 5:\\n if paths[2][i] == True:\\n folium.Marker([marker_coords[i][1], marker_coords[i][0]], icon=folium.Icon(color=setColor(len(current_node)),icon=iconMaker(len(current_node)), prefix='fa'), popup=i, tooltip=result_path[1][i]).add_to(m)\\n edge_coords.append(m_graph.get_long_lat(next_node))\\n folium.PolyLine(edge_coords, color=\\\"green\\\").add_to(m)\\n edge_coords = []\\n else:\\n folium.Marker([marker_coords[i][1], marker_coords[i][0]], icon=folium.Icon(color=setColor(len(current_node)),icon=iconMaker(len(current_node)), prefix='fa'), popup=i, tooltip=result_path[1][i]).add_to(m)\\n edge_coords.append(m_graph.get_long_lat(next_node))\\n folium.PolyLine(edge_coords, color=\\\"grey\\\").add_to(m)\\n edge_coords = []\\n else:\\n folium.Marker([marker_coords[i][1], marker_coords[i][0]], icon=folium.Icon(color=setColor(len(current_node)),icon=iconMaker(len(current_node)), prefix='fa'), popup=i, tooltip=result_path[1][i]).add_to(m)\\n edge_coords.append(m_graph.get_long_lat(next_node))\\n folium.PolyLine(edge_coords, color=\\\"grey\\\").add_to(m)\\n edge_coords = [] \\n elif (MOT == \\\"W\\\"):\\n singleTransportPlot(paths[1], \\\"gray\\\", \\\"grey\\\", \\\"building\\\")\\n elif (MOT == \\\"M\\\"):\\n marker_coords = []\\n edge_coords = []\\n changes_Indicator = 0\\n\\n for i in range(0, len(paths[1])):\\n marker_coords.append(m_graph.get_lat_long(paths[1][i]))\\n\\n current_node = paths[1][i]\\n if i+1 < len(paths[1]):\\n next_node = paths[1][i+1]\\n \\n edge_coords.append(m_graph.get_long_lat(current_node))\\n\\n if len(current_node) == len(next_node):\\n folium.Marker([marker_coords[i][1], marker_coords[i][0]], icon=folium.Icon(color=\\\"darkred\\\",icon=iconMaker(len(current_node)), prefix='fa'), popup=i, tooltip=result_path[1][i]).add_to(m)\\n edge_coords.append(m_graph.get_long_lat(next_node))\\n folium.PolyLine(edge_coords, color=setColor(len(current_node))).add_to(m)\\n edge_coords = []\\n elif len(current_node) != len(next_node):\\n if changes_Indicator == 1:\\n folium.Marker([marker_coords[i][1], marker_coords[i][0]], icon=folium.Icon(color=\\\"darkred\\\",icon=iconMaker(len(current_node)), prefix='fa'), popup=i, tooltip=result_path[1][i]).add_to(m)\\n edge_coords.append(m_graph.get_long_lat(next_node))\\n folium.PolyLine(edge_coords, color=setColor(len(next_node))).add_to(m)\\n edge_coords = []\\n changes_Indicator -= 1\\n else:\\n folium.Marker([marker_coords[i][1], marker_coords[i][0]], icon=folium.Icon(color=\\\"darkred\\\",icon=iconMaker(len(current_node)), prefix='fa'), popup=i, tooltip=result_path[1][i]).add_to(m)\\n edge_coords.append(m_graph.get_long_lat(next_node))\\n folium.PolyLine(edge_coords, color=setColor(len(current_node))).add_to(m)\\n edge_coords = []\\n changes_Indicator +=1\\n\\n # Call Set routes and pass in mode of transport and routes\\n # Sample Input: [Coming From: PE1], [Coming From: ]\\n routePlotting(mode, result_path)\\n\\n # Initialization of the map\\n data = io.BytesIO() # creates a temporary 'container' for html code\\n m.save(data, close_file=False) # folium html code is saved inside data variable\\n w = QtWebEngineWidgets.QWebEngineView() # then the rest of the code is the map running\\n w.setHtml(data.getvalue().decode())\\n w.resize(840, 680)\\n w.show()\\n sys.exit(app.exec_())\\n\"\n },\n {\n \"alpha_fraction\": 0.5475651025772095,\n \"alphanum_fraction\": 0.5736126899719238,\n \"avg_line_length\": 28.797468185424805,\n \"blob_id\": \"1c9d9bbdec453ad02f5394d547e6cc2088b5334d\",\n \"content_id\": \"993bb8dcfa5015924c599b63ce1dc89a5179756f\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 7064,\n \"license_type\": \"no_license\",\n \"max_line_length\": 96,\n \"num_lines\": 237,\n \"path\": \"/bus_adj.py\",\n \"repo_name\": \"eekhait/1008_Project\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import pandas as pd\\nimport main_graph as m_graph\\nimport csv\\nimport sys\\nimport math\\nimport numpy as np\\n\\n\\n# Columns: 0-Code, ....... pending\\nbusData = pd.read_csv('Punggol_Bus_Routing.csv', sep=',', header=None)\\n# Columns: 0-Code, ....... pending\\nbusData2 = pd.read_csv('Punggol_Bus_Routing_Type2.csv', sep=',',header=None)\\npunggol = pd.read_csv('Complete_Punggol_Graph.csv',sep=',',header=None)\\npunggol1 = pd.read_csv('Punggol_complete_graph2.csv',sep=',',header=None)\\n\\nbus_speed = 50000/60\\nbus_waiting_time = 5\\n'''\\nTest Cases\\nstart = \\\"65141\\\"\\nend = \\\"65339\\\"\\nnew_start = \\\"828858\\\"\\nnew_end = \\\"821266\\\"\\n'''\\ndef busStopCode1(data):\\n start = (punggol[0] == data)\\n return start\\n\\ndef busStopCode2(data):\\n start = punggol1[0] == data\\n return start\\n\\ndef connected(data):\\n connected1 = punggol[busStopCode1(data)]\\n if connected1.empty is True:\\n connected1 = punggol1[busStopCode2(data)]\\n hg = []\\n test = pd.DataFrame(connected1[6].str.split(',').tolist())\\n test1 = pd.DataFrame((connected1[7].str.split(',').tolist()))\\n if test.empty == True:\\n print(\\\"no such route For Buses\\\")\\n sys.exit()\\n if test1.empty == True:\\n print (\\\"no such route For buses\\\")\\n sys.exit()\\n ht =[]\\n if len(data) == 5:\\n ht.append(int(data))\\n # print(int(test1[0].values))\\n try:\\n niii = max(test1.columns.values)\\n except ValueError:\\n niii = (test1.columns.values)\\n for i in test.iterrows():\\n for k in range (0, niii):\\n if int(test1[k].values) <=200:\\n #for connected nodes and distance\\n hg.append(((int(test[k].values)),(int(test1[k].values))))\\n #just for connected nodes\\n ht.append(int((test[k].values)))\\n\\n return ht\\n\\n# For finding starting bus Stop( See csv for column 1 and compare to check for bus stop code)\\ndef busStopCode(data):\\n startStop = busData2[1] == data\\n return startStop\\n\\n# For finding starting bus Stop( See csv for column 2 and compare to check for bus stop code)\\ndef endStopCode(data):\\n endStop = busData2[2] == data\\n return endStop\\n\\ndef busNoInserter(data):\\n busNo = busData2[0] == data\\n return busNo\\n\\n#For finding the starting point of the bus\\ndef busStopCode_startfinder(data):\\n length = len(data)\\n new_array =[]\\n isa =0\\n for i in range(0,length):\\n test_test = busStopCode(str(data[i]))\\n test_test1 = busData2[test_test]\\n if test_test1.empty == False:\\n new_array.append(test_test1)\\n return new_array\\n\\n#For findin the ending point of the bus\\ndef busStopCode_endfinder(data):\\n length = len(data)\\n new_array =[]\\n isa =0\\n for i in range(0,length):\\n test_test = endStopCode(str(data[i]))\\n test_test1 = busData2[test_test]\\n if test_test1.empty == False:\\n new_array.append(test_test1)\\n return new_array\\n\\n# Checking the routes taken by the buses to see if there is a route to the ending bus stop.\\ndef take_bus(start_node, end_node,data):\\n bus_route = (busNoInserter(data)) & ((busStopCode(start_node) | endStopCode(end_node)))\\n asd =[]\\n asd.append(start_node)\\n bus_distance = 0\\n lol = np.int64(0)\\n lol1 = np.int64(0)\\n #bus_route = (bus_route[0]) >= 1 & (bus_route[0] <=3)\\n route = busData2[bus_route]\\n if len(route) < 2:\\n pass\\n else:\\n if route.empty == True:\\n pass\\n else:\\n lol = route.index.values[0]\\n try:\\n lol1= route.index.values[1]\\n except IndexError:\\n lol1 = lol\\n for i in range (lol,lol1+1):\\n if busData2.at[lol,6] != busData2.at[lol1,6]:\\n pass\\n else:\\n bus_distance += int(busData2.at[i,3])\\n asd.append(busData2.at[i,2])\\n\\n if len(asd) < 2:\\n asd = []\\n return None\\n\\n\\n return (data,asd, math.ceil(bus_distance/bus_speed + bus_waiting_time + (lol1-lol)))\\n\\n\\n#For appending all the routes that could be taken and return the one with the least time\\ndef route_finder(new_start, new_end):\\n starting = busStopCode_startfinder(connected(new_start))\\n ending = busStopCode_endfinder(connected(new_end))\\n str1 = ' '\\n str2 = ' '\\n k = []\\n n = []\\n for i in range (0,len(starting)):\\n bus_to_take = starting[i][0].values\\n asd = (starting[i][1].values)\\n #bus_to_take , indices = np.unique(asd,return_counts=True)\\n for l in bus_to_take:\\n try:\\n a ,indices= np.unique((starting[i][1].values),return_counts=True)\\n b, indices = np.unique((ending[i][2].values),return_counts= True)\\n str1 = str1.join(a)\\n str2 = str2.join(b)\\n if take_bus(str1,str2,l) is None:\\n pass\\n else:\\n p = list(take_bus(str1,str2,l))\\n n.append((take_bus(str1,str2,l))[2])\\n k.append(p)\\n\\n except IndexError:\\n \\\"Do Nothing\\\"\\n df = pd.DataFrame(k)\\n\\n if df.empty == True:\\n print(\\\"No common bus nearby start and end points. Please restart with another option. \\\")\\n sys.exit()\\n\\n route = df[2] == min(n)\\n optimised_route = df[route]\\n optimised_route[0], optimised_route[2] = optimised_route[2], optimised_route[0]\\n pop = optimised_route.head(1)\\n\\n first_route = []\\n lol = pd.DataFrame(pop[1].tolist())\\n\\n starting_walk = m_graph.take_walk(new_start,lol[0].values[0])\\n lemon =[]\\n if ((starting_walk[0]) == 0):\\n pass\\n else:\\n first_route=starting_walk[1]\\n first_route.pop(len(first_route)-1)\\n\\n for i in range(1,len(starting_walk)):\\n lemon.append(False)\\n\\n\\n for i in range (0,len(lol)):\\n for l in lol:\\n first_route.append((lol[l][i]))\\n if l == 0:\\n pass\\n else:\\n lemon.append(True)\\n\\n length = max(lol)\\n Last_Point = lol[length].values[0]\\n ending_walk = m_graph.take_walk(Last_Point, new_end)\\n\\n\\n if len(ending_walk) <= 2:\\n\\n end_route = ending_walk[1]\\n # print(end_route)\\n first_route.append(end_route[0])\\n end_route.pop(0)\\n first_route.append(end_route[0])\\n lemon.append(False)\\n else:\\n new = np.array(ending_walk[1])\\n counter = 1\\n for i in range(1, len(new)):\\n first_route.append(new[counter])\\n lemon.append(False)\\n counter = counter + 1\\n lemon.append(False)\\n k = []\\n # all route here\\n for i, l in optimised_route.iterrows():\\n k.append((l[0], l[1], l[2]))\\n route = []\\n test1 = pop\\n m = test1.index.values[0]\\n route.append(test1[0][m]) # time taken is fine\\n route[0] += starting_walk[0]\\n route[0] += ending_walk[0]\\n # print(\\\"first_route:\\\", first_route)\\n route.append(first_route)\\n route.append(lemon) # lemon is fine\\n # print(\\\"\\\")\\n route.append(test1[2][m]) # bus number is fine\\n return (route)\\n\\n# print(\\\"BUS ROUTE: \\\", route_finder(\\\"828858\\\",\\\"65009\\\"))\\n\\n\\n\"\n }\n]"},"num_files":{"kind":"number","value":7,"string":"7"}}},{"rowIdx":2040,"cells":{"repo_name":{"kind":"string","value":"vishvadesai9/Breast_Cancer_Classification"},"repo_url":{"kind":"string","value":"https://github.com/vishvadesai9/Breast_Cancer_Classification"},"snapshot_id":{"kind":"string","value":"5e40d95d30bb420060851bfb248024acc4d5bba6"},"revision_id":{"kind":"string","value":"c9e60fd852f1944a1b569534aaefeb432e49c3e5"},"directory_id":{"kind":"string","value":"3925cdd37c2ec0429b71e128f751aaf84b25860c"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"string","value":"2022-12-21T23:20:21.763345"},"revision_date":{"kind":"string","value":"2020-10-01T18:11:06"},"committer_date":{"kind":"string","value":"2020-10-01T18:11:06"},"github_id":{"kind":"number","value":298875594,"string":"298,875,594"},"star_events_count":{"kind":"number","value":4,"string":"4"},"fork_events_count":{"kind":"number","value":3,"string":"3"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.8223602771759033,"alphanum_fraction":0.8223602771759033,"avg_line_length":400.5,"blob_id":"0e5293f1e7c8438a9cdba53164441692a92c7bf8","content_id":"c3238fb4171f59141a6f945ff720e8e3c88219ed","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":806,"license_type":"no_license","max_line_length":771,"num_lines":2,"path":"/README.md","repo_name":"vishvadesai9/Breast_Cancer_Classification","src_encoding":"UTF-8","text":"# Breast_Cancer_Classification\nThe aim of this project is to classify breast cancer as either malignant or benign using the dataset from sckit-learn. It is a web application built using streamlit and deployed with heroku(link: https://breast-cancer-detection-heroku.herokuapp.com/). The app analyzes the given data and provides prediction accuracy for the various classification algorithms used i.e Support Vector Machine, Logistic Regression, K-Nearest Neighbor, Random Forest, Decision Trees and Naïve Bayes. The application allows for interactivity with the parameters of these classification algorithms. In addition, I have plot Confusion Matrix, Precision-Recall Curve and ROC curve for each of the classifications. For data visualization I have used Pandas, Matplotlib, Seaborn, Plotly and Numpy. \n"},{"alpha_fraction":0.5,"alphanum_fraction":0.6944444179534912,"avg_line_length":14.285714149475098,"blob_id":"6b79ff5dcd452a7374229ad437692ba17b604f1b","content_id":"fe40c97ced8b8896e797d3776537d3893ced14ae","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Text","length_bytes":108,"license_type":"no_license","max_line_length":20,"num_lines":7,"path":"/requirements.txt","repo_name":"vishvadesai9/Breast_Cancer_Classification","src_encoding":"UTF-8","text":"numpy>=1.16.4\npandas>=0.24.2\nseaborn>=0.9.0\nmatplotlib>=3.1.0\nplotly>=4.4.1\nscikit-learn==0.23.2\nstreamlit\n\n"},{"alpha_fraction":0.5270372629165649,"alphanum_fraction":0.5391121506690979,"avg_line_length":44.967124938964844,"blob_id":"2ae3abd3cdb82fb216ae8244a04cfe04e9802eb6","content_id":"a96efe48019e548deda2c7039cd7967c08ec74a9","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":17143,"license_type":"no_license","max_line_length":177,"num_lines":365,"path":"/app_bcd.py","repo_name":"vishvadesai9/Breast_Cancer_Classification","src_encoding":"UTF-8","text":"import streamlit as st\r\nimport pandas as pd\r\nimport numpy as np\r\nimport seaborn as sns\r\nimport matplotlib.pyplot as plt\r\nimport plotly.express as px\r\nimport time\r\nfrom sklearn.svm import SVC\r\nfrom sklearn.linear_model import LogisticRegression\r\nfrom sklearn.ensemble import RandomForestClassifier\r\nfrom sklearn.neighbors import KNeighborsClassifier\r\nfrom sklearn.tree import DecisionTreeClassifier\r\nfrom sklearn.naive_bayes import GaussianNB\r\nfrom sklearn.preprocessing import LabelEncoder\r\nfrom sklearn.model_selection import train_test_split\r\nfrom sklearn.metrics import precision_score, recall_score\r\nfrom sklearn.metrics import confusion_matrix, roc_curve, precision_recall_curve, auc\r\nfrom sklearn.datasets import load_breast_cancer\r\n\r\n\r\n\r\n\r\ndef main():\r\n st.beta_set_page_config(page_title='Breast Cancer Detection', page_icon='tumor_icon.png', layout='centered', initial_sidebar_state='auto')\r\n \r\n st.title('Breast Cancer Detection')\r\n st.image('tumor_icon.png',width=100)\r\n st.sidebar.title('Breast Cancer Detection')\r\n st.markdown('Cancer is Malignant or Benign? ')\r\n navigation=st.sidebar.radio('VIEW', ('Data Analysis','Prediction'))\r\n \r\n \r\n @st.cache(persist=True)\r\n def load_data():\r\n cancer = load_breast_cancer()\r\n df = pd.DataFrame(cancer.data,columns=cancer.feature_names)\r\n df['target'] = cancer.target \r\n labelencoder=LabelEncoder()\r\n for col in df.columns:\r\n df[col] = labelencoder.fit_transform(df[col])\r\n return df\r\n \r\n @st.cache(persist=True)\r\n def split(df):\r\n y = df['target']\r\n x = df.drop(columns=['target'])\r\n x_train, x_test, y_train, y_test = train_test_split(x, y, test_size=0.3, random_state=3)\r\n return x_train, x_test, y_train, y_test\r\n \r\n \r\n \r\n def plot_metrics(metrics_list):\r\n if 'Confusion Matrix' in metrics_list:\r\n st.subheader(\"Confusion Matrix\")\r\n cm = confusion_matrix(y_test, y_pred)\r\n fig,ax = plt.subplots()\r\n sns.heatmap(cm, annot = True)\r\n # plot_confusion_matrix(model, x_test, y_test, display_labels=class_names)\r\n ax.figure.savefig('file.png')\r\n st.pyplot(fig)\r\n if 'Precision-Recall Curve' in metrics_list:\r\n st.subheader('Precision-Recall Curve')\r\n \r\n precision, recall, thresholds = precision_recall_curve(y_test, y_pred)\r\n\r\n fig = px.area(\r\n x=recall, y=precision,\r\n title=f'Precision-Recall Curve (AUC={auc(precision, recall):.4f})',\r\n labels=dict(x='Recall', y='Precision'),\r\n width=700, height=500\r\n )\r\n fig.add_shape(\r\n type='line', line=dict(dash='dash'),\r\n x0=0, x1=1, y0=1, y1=0\r\n )\r\n fig.update_yaxes(scaleanchor=\"x\", scaleratio=1)\r\n fig.update_xaxes(constrain='domain')\r\n st.write(fig)\r\n \r\n \r\n if 'ROC Curve' in metrics_list:\r\n fpr, tpr, thresholds = roc_curve(y_test, y_pred)\r\n\r\n fig = px.area(\r\n x=fpr, y=tpr,\r\n title=f'ROC Curve (AUC={auc(fpr, tpr):.4f})',\r\n labels=dict(x='False Positive Rate', y='True Positive Rate'),\r\n width=700, height=500\r\n ) \r\n fig.add_shape(\r\n type='line', line=dict(dash='dash'),\r\n x0=0, x1=1, y0=0, y1=1\r\n )\r\n\r\n fig.update_yaxes(scaleanchor=\"x\", scaleratio=1)\r\n fig.update_xaxes(constrain='domain')\r\n st.write(fig)\r\n \r\n if 'Training and Test accuracies' in metrics_list:\r\n mal_train_X = x_train[y_train==0]\r\n mal_train_y = y_train[y_train==0]\r\n ben_train_X = x_train[y_train==1]\r\n ben_train_y = y_train[y_train==1]\r\n \r\n mal_test_X = x_test[y_test==0]\r\n mal_test_y = y_test[y_test==0]\r\n ben_test_X = x_test[y_test==1]\r\n ben_test_y = y_test[y_test==1]\r\n \r\n scores = [model.score(mal_train_X, mal_train_y), model.score(ben_train_X, ben_train_y), model.score(mal_test_X, mal_test_y), model.score(ben_test_X, ben_test_y)]\r\n\r\n fig,ax = plt.subplots()\r\n \r\n # Plot the scores as a bar chart\r\n bars = plt.bar(np.arange(4), scores, color=['#4c72b0','#4c72b0','#55a868','#55a868'])\r\n\r\n # directly label the score onto the bars\r\n for bar in bars:\r\n height = bar.get_height()\r\n plt.gca().text(bar.get_x() + bar.get_width()/2, height*.90, '{0:.{1}f}'.format(height, 2), ha='center', color='w', fontsize=11)\r\n\r\n # remove all the ticks (both axes), and tick labels on the Y axis\r\n plt.tick_params(top='off', bottom='off', left='off', right='off', labelleft='off', labelbottom='on')\r\n\r\n # remove the frame of the chart\r\n for spine in plt.gca().spines.values():\r\n spine.set_visible(False)\r\n\r\n plt.xticks([0,1,2,3], ['Malignant\\nTraining', 'Benign\\nTraining', 'Malignant\\nTest', 'Benign\\nTest'], alpha=0.8);\r\n plt.title('Training and Test Accuracies for Malignant and Benign Cells', alpha=0.8)\r\n ax.xaxis.set_tick_params(length=0)\r\n ax.yaxis.set_tick_params(length=0)\r\n ax.figure.savefig('file1.png')\r\n st.pyplot(fig)\r\n \r\n df = load_data()\r\n class_names = ['malignant', 'benign']\r\n \r\n \r\n###------------------DATA ANAlYSIS-------------------------- \r\n if navigation == 'Data Analysis':\r\n \r\n \r\n \r\n if st.sidebar.checkbox(\"Show Raw Data\", False):\r\n st.subheader('Breast Cancer Dataset')\r\n \r\n st.dataframe(df)\r\n \r\n if st.sidebar.checkbox(\"Show Features\", False):\r\n cancer = load_breast_cancer()\r\n st.subheader('Features')\r\n features = pd.DataFrame(cancer.feature_names)\r\n features.columns = ['Features']\r\n st.dataframe(features)\r\n \r\n \r\n plots = st.sidebar.multiselect(\"Plots\", ('Scatter Matrix', 'Number of Malignant and Benign','Heatmap','Mean radius vs Mean area','Mean smoothness vs Mean area'))\r\n \r\n \r\n if st.sidebar.button(\"Plot\", key='plotss'):\r\n with st.spinner('Wait for it...'):\r\n time.sleep(5)\r\n \r\n if 'Number of Malignant and Benign' in plots:\r\n st.subheader(\"Malignant and Benign Count\")\r\n fig,ax = plt.subplots()\r\n \r\n ma = len(df[df['target']==1])\r\n be = len(df[df['target']==0])\r\n count=[ma,be]\r\n bars = plt.bar(np.arange(2), count, color=['#000099','#ffff00'])\r\n ##show value in bars\r\n for bar in bars:\r\n height = bar.get_height()\r\n plt.gca().text(bar.get_x() + bar.get_width()/2, height*.90, '{0:.{1}f}'.format(height, 2), ha='center', color='black', fontsize=11)\r\n plt.tick_params(top='off', bottom='off', left='off', right='off', labelleft='on', labelbottom='on')\r\n for spine in plt.gca().spines.values():\r\n spine.set_visible(False)\r\n plt.xticks(ticks=[0,1])\r\n ax.set_ylabel('Count')\r\n ax.set_xlabel('Target')\r\n ##remove dashes from frame\r\n ax.xaxis.set_tick_params(length=0)\r\n ax.yaxis.set_tick_params(length=0)\r\n st.pyplot(fig)\r\n \r\n \r\n if 'Scatter Matrix' in plots:\r\n st.subheader(\"Scatter Matrix\")\r\n fig = px.scatter_matrix(df,dimensions=['mean radius','mean texture','mean perimeter','mean area','mean smoothness'],color=\"target\",width = 800,height = 700)\r\n st.write(fig)\r\n \r\n if 'Heatmap' in plots:\r\n st.subheader(\"Heatmap\")\r\n fig=plt.figure(figsize = (30,20))\r\n hmap=sns.heatmap(df.drop(columns=['target']).corr(), annot = True,cmap= 'Blues',annot_kws={\"size\": 18})\r\n hmap.set_xticklabels(hmap.get_xmajorticklabels(), fontsize = 25)\r\n hmap.set_yticklabels(hmap.get_ymajorticklabels(), fontsize = 25)\r\n st.pyplot(fig)\r\n if 'Mean radius vs Mean area' in plots:\r\n st.subheader('Cancer Radius and Area')\r\n fig = plt.figure()\r\n sns.scatterplot(x=df['mean radius'],y = df['mean area'],hue = df['target'],palette=['#000099','#ffff00'])\r\n st.pyplot(fig)\r\n if 'Mean smoothness vs Mean area' in plots:\r\n st.subheader('Cancer Smoothness and Area')\r\n fig = plt.figure()\r\n sns.scatterplot(x=df['mean smoothness'],y = df['mean area'],hue = df['target'],palette=['#000099','#ffff00'])\r\n st.pyplot(fig)\r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n###---------------classification----------------------\r\n if navigation == 'Prediction':\r\n \r\n x_train, x_test, y_train, y_test = split(df)\r\n if st.sidebar.checkbox(\"Show X_train/Y_train\", False):\r\n st.subheader('X_train')\r\n st.dataframe(x_train)\r\n st.subheader('Y_train')\r\n st.dataframe(y_train)\r\n \r\n st.sidebar.subheader(\"Choose Classifier\")\r\n classifier = st.sidebar.selectbox(\"Classifier\", (\"Support Vector Machine (SVM)\", \"Logistic Regression\", \"Random Forest\", 'KNN', 'Decision Tree', 'Gaussian Naive Bayes'))\r\n\r\n if classifier == 'Support Vector Machine (SVM)':\r\n st.sidebar.subheader(\"Model Hyperparameters\")\r\n #choose parameters\r\n C = st.sidebar.number_input(\"C (Regularization parameter)\", 0.01, 10.0, step=0.01, key='C_SVM')\r\n kernel = st.sidebar.radio(\"Kernel\", (\"rbf\", \"linear\"), key='kernel')\r\n gamma = st.sidebar.radio(\"Gamma (Kernel Coefficient)\", (\"scale\", \"auto\"), key='gamma')\r\n\r\n metrics = st.sidebar.multiselect(\"Metrics to Plot\", ('Confusion Matrix', 'ROC Curve', 'Precision-Recall Curve','Training and Test accuracies'))\r\n \r\n if st.sidebar.button(\"Classify\", key='classify'):\r\n st.subheader(\"Support Vector Machine (SVM) Results\")\r\n model = SVC(C=C, kernel=kernel, gamma=gamma)\r\n model.fit(x_train, y_train)\r\n accuracy = model.score(x_test, y_test)\r\n y_pred = model.predict(x_test)\r\n st.write(\"Accuracy: \", accuracy.round(2))\r\n st.write(\"Precision: \", precision_score(y_test, y_pred, labels=class_names).round(2))\r\n st.write(\"Recall: \", recall_score(y_test, y_pred, labels=class_names).round(2))\r\n plot_metrics(metrics)\r\n \r\n if classifier == 'Logistic Regression':\r\n st.sidebar.subheader(\"Model Hyperparameters\")\r\n C = st.sidebar.number_input(\"C (Regularization parameter)\", 0.01, 10.0, step=0.01, key='C_LR')\r\n max_iter = st.sidebar.slider(\"Maximum number of iterations\", 100, 500, key='max_iter')\r\n \r\n metrics = st.sidebar.multiselect(\"Metrics to Plot\", ('Confusion Matrix', 'ROC Curve', 'Precision-Recall Curve','Training and Test accuracies'))\r\n \r\n if st.sidebar.button(\"Classify\", key='classify'):\r\n st.subheader(\"Logistic Regression Results\")\r\n model = LogisticRegression(C=C, penalty='l2', max_iter=max_iter)\r\n model.fit(x_train, y_train)\r\n accuracy = model.score(x_test, y_test)\r\n y_pred = model.predict(x_test)\r\n st.write(\"Accuracy: \", accuracy.round(2))\r\n st.write(\"Precision: \", precision_score(y_test, y_pred, labels=class_names).round(2))\r\n st.write(\"Recall: \", recall_score(y_test, y_pred, labels=class_names).round(2))\r\n plot_metrics(metrics)\r\n \r\n if classifier == 'Random Forest':\r\n st.sidebar.subheader(\"Model Hyperparameters\")\r\n n_estimators = st.sidebar.number_input(\"The number of trees in the forest\", 100, 5000, step=10, key='n_estimators')\r\n max_depth = st.sidebar.number_input(\"The maximum depth of the tree\", 1, 20, step=1, key='max_depth')\r\n bootstrap = st.sidebar.radio(\"Bootstrap samples when building trees\", ('True', 'False'), key='bootstrap')\r\n metrics = st.sidebar.multiselect(\"Metrics to Plot\", ('Confusion Matrix', 'ROC Curve', 'Precision-Recall Curve','Training and Test accuracies'))\r\n \r\n if st.sidebar.button(\"Classify\", key='classify'):\r\n st.subheader(\"Random Forest Results\")\r\n model = RandomForestClassifier(n_estimators=n_estimators, max_depth=max_depth, bootstrap=bootstrap, n_jobs=-1)\r\n model.fit(x_train, y_train)\r\n accuracy = model.score(x_test, y_test)\r\n y_pred = model.predict(x_test)\r\n st.write(\"Accuracy: \", accuracy.round(2))\r\n st.write(\"Precision: \", precision_score(y_test, y_pred, labels=class_names).round(2))\r\n st.write(\"Recall: \", recall_score(y_test, y_pred, labels=class_names).round(2))\r\n plot_metrics(metrics)\r\n \r\n if classifier == 'KNN':\r\n st.sidebar.subheader(\"Model Hyperparameters\")\r\n n_neighbors = st.sidebar.number_input(\"Number of neighbors\", 1, 100, step=1, key='n_neighbors')\r\n \r\n metrics = st.sidebar.multiselect(\"Metrics to Plot\", ('Confusion Matrix', 'ROC Curve', 'Precision-Recall Curve','Training and Test accuracies'))\r\n\r\n if st.sidebar.button(\"Classify\", key='classify'):\r\n st.subheader(\"KNN Results\")\r\n model = KNeighborsClassifier(n_neighbors = n_neighbors )\r\n model.fit(x_train, y_train)\r\n accuracy = model.score(x_test, y_test)\r\n y_pred = model.predict(x_test)\r\n st.write(\"Accuracy: \", accuracy.round(2))\r\n st.write(\"Precision: \", precision_score(y_test, y_pred, labels=class_names).round(2))\r\n st.write(\"Recall: \", recall_score(y_test, y_pred, labels=class_names).round(2))\r\n plot_metrics(metrics)\r\n \r\n if classifier == 'Decision Tree':\r\n st.sidebar.subheader(\"Model Hyperparameters\")\r\n \r\n max_depth = st.sidebar.number_input(\"The maximum depth of the tree\", 1, 20, step=1, key='max_depth')\r\n criterion = st.sidebar.radio(\"Criterion\", (\"gini\", \"entropy\"), key='criterion')\r\n splitter = st.sidebar.radio(\"Splitter\", (\"best\", \"random\"), key='splitter')\r\n metrics = st.sidebar.multiselect(\"Metrics to Plot\", ('Confusion Matrix', 'ROC Curve', 'Precision-Recall Curve','Training and Test accuracies'))\r\n \r\n if st.sidebar.button(\"Classify\", key='classify'):\r\n st.subheader(\"Decision Tree Results\")\r\n model = DecisionTreeClassifier(max_depth= max_depth, criterion= criterion, splitter= splitter )\r\n model.fit(x_train, y_train)\r\n accuracy = model.score(x_test, y_test)\r\n y_pred = model.predict(x_test)\r\n st.write(\"Accuracy: \", accuracy.round(2))\r\n st.write(\"Precision: \", precision_score(y_test, y_pred, labels=class_names).round(2))\r\n st.write(\"Recall: \", recall_score(y_test, y_pred, labels=class_names).round(2))\r\n plot_metrics(metrics)\r\n \r\n if classifier == 'Gaussian Naive Bayes':\r\n st.sidebar.subheader(\"Model Hyperparameters\")\r\n \r\n \r\n metrics = st.sidebar.multiselect(\"Metrics to Plot\", ('Confusion Matrix', 'ROC Curve', 'Precision-Recall Curve','Training and Test accuracies'))\r\n\r\n if st.sidebar.button(\"Classify\", key='classify'):\r\n st.subheader(\"Gaussian Naive Bayes Results\")\r\n model = GaussianNB()\r\n model.fit(x_train, y_train)\r\n accuracy = model.score(x_test, y_test)\r\n y_pred = model.predict(x_test)\r\n st.write(\"Accuracy: \", accuracy.round(2))\r\n st.write(\"Precision: \", precision_score(y_test, y_pred, labels=class_names).round(2))\r\n st.write(\"Recall: \", recall_score(y_test, y_pred, labels=class_names).round(2))\r\n plot_metrics(metrics) \r\n \r\n st.sidebar.subheader(\"ABOUT\")\r\n st.sidebar.write('By: Vishva Desai')\r\n st.sidebar.write(\"Github: https://github.com/vishvadesai9\") \r\n \r\n \r\n \r\n\r\n\r\n\r\n\r\n\r\n\r\nif __name__ == '__main__':\r\n main()\r\n"}],"string":"[\n {\n \"alpha_fraction\": 0.8223602771759033,\n \"alphanum_fraction\": 0.8223602771759033,\n \"avg_line_length\": 400.5,\n \"blob_id\": \"0e5293f1e7c8438a9cdba53164441692a92c7bf8\",\n \"content_id\": \"c3238fb4171f59141a6f945ff720e8e3c88219ed\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 806,\n \"license_type\": \"no_license\",\n \"max_line_length\": 771,\n \"num_lines\": 2,\n \"path\": \"/README.md\",\n \"repo_name\": \"vishvadesai9/Breast_Cancer_Classification\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# Breast_Cancer_Classification\\nThe aim of this project is to classify breast cancer as either malignant or benign using the dataset from sckit-learn. It is a web application built using streamlit and deployed with heroku(link: https://breast-cancer-detection-heroku.herokuapp.com/). The app analyzes the given data and provides prediction accuracy for the various classification algorithms used i.e Support Vector Machine, Logistic Regression, K-Nearest Neighbor, Random Forest, Decision Trees and Naïve Bayes. The application allows for interactivity with the parameters of these classification algorithms. In addition, I have plot Confusion Matrix, Precision-Recall Curve and ROC curve for each of the classifications. For data visualization I have used Pandas, Matplotlib, Seaborn, Plotly and Numpy. \\n\"\n },\n {\n \"alpha_fraction\": 0.5,\n \"alphanum_fraction\": 0.6944444179534912,\n \"avg_line_length\": 14.285714149475098,\n \"blob_id\": \"6b79ff5dcd452a7374229ad437692ba17b604f1b\",\n \"content_id\": \"fe40c97ced8b8896e797d3776537d3893ced14ae\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Text\",\n \"length_bytes\": 108,\n \"license_type\": \"no_license\",\n \"max_line_length\": 20,\n \"num_lines\": 7,\n \"path\": \"/requirements.txt\",\n \"repo_name\": \"vishvadesai9/Breast_Cancer_Classification\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"numpy>=1.16.4\\npandas>=0.24.2\\nseaborn>=0.9.0\\nmatplotlib>=3.1.0\\nplotly>=4.4.1\\nscikit-learn==0.23.2\\nstreamlit\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.5270372629165649,\n \"alphanum_fraction\": 0.5391121506690979,\n \"avg_line_length\": 44.967124938964844,\n \"blob_id\": \"2ae3abd3cdb82fb216ae8244a04cfe04e9802eb6\",\n \"content_id\": \"a96efe48019e548deda2c7039cd7967c08ec74a9\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 17143,\n \"license_type\": \"no_license\",\n \"max_line_length\": 177,\n \"num_lines\": 365,\n \"path\": \"/app_bcd.py\",\n \"repo_name\": \"vishvadesai9/Breast_Cancer_Classification\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import streamlit as st\\r\\nimport pandas as pd\\r\\nimport numpy as np\\r\\nimport seaborn as sns\\r\\nimport matplotlib.pyplot as plt\\r\\nimport plotly.express as px\\r\\nimport time\\r\\nfrom sklearn.svm import SVC\\r\\nfrom sklearn.linear_model import LogisticRegression\\r\\nfrom sklearn.ensemble import RandomForestClassifier\\r\\nfrom sklearn.neighbors import KNeighborsClassifier\\r\\nfrom sklearn.tree import DecisionTreeClassifier\\r\\nfrom sklearn.naive_bayes import GaussianNB\\r\\nfrom sklearn.preprocessing import LabelEncoder\\r\\nfrom sklearn.model_selection import train_test_split\\r\\nfrom sklearn.metrics import precision_score, recall_score\\r\\nfrom sklearn.metrics import confusion_matrix, roc_curve, precision_recall_curve, auc\\r\\nfrom sklearn.datasets import load_breast_cancer\\r\\n\\r\\n\\r\\n\\r\\n\\r\\ndef main():\\r\\n st.beta_set_page_config(page_title='Breast Cancer Detection', page_icon='tumor_icon.png', layout='centered', initial_sidebar_state='auto')\\r\\n \\r\\n st.title('Breast Cancer Detection')\\r\\n st.image('tumor_icon.png',width=100)\\r\\n st.sidebar.title('Breast Cancer Detection')\\r\\n st.markdown('Cancer is Malignant or Benign? ')\\r\\n navigation=st.sidebar.radio('VIEW', ('Data Analysis','Prediction'))\\r\\n \\r\\n \\r\\n @st.cache(persist=True)\\r\\n def load_data():\\r\\n cancer = load_breast_cancer()\\r\\n df = pd.DataFrame(cancer.data,columns=cancer.feature_names)\\r\\n df['target'] = cancer.target \\r\\n labelencoder=LabelEncoder()\\r\\n for col in df.columns:\\r\\n df[col] = labelencoder.fit_transform(df[col])\\r\\n return df\\r\\n \\r\\n @st.cache(persist=True)\\r\\n def split(df):\\r\\n y = df['target']\\r\\n x = df.drop(columns=['target'])\\r\\n x_train, x_test, y_train, y_test = train_test_split(x, y, test_size=0.3, random_state=3)\\r\\n return x_train, x_test, y_train, y_test\\r\\n \\r\\n \\r\\n \\r\\n def plot_metrics(metrics_list):\\r\\n if 'Confusion Matrix' in metrics_list:\\r\\n st.subheader(\\\"Confusion Matrix\\\")\\r\\n cm = confusion_matrix(y_test, y_pred)\\r\\n fig,ax = plt.subplots()\\r\\n sns.heatmap(cm, annot = True)\\r\\n # plot_confusion_matrix(model, x_test, y_test, display_labels=class_names)\\r\\n ax.figure.savefig('file.png')\\r\\n st.pyplot(fig)\\r\\n if 'Precision-Recall Curve' in metrics_list:\\r\\n st.subheader('Precision-Recall Curve')\\r\\n \\r\\n precision, recall, thresholds = precision_recall_curve(y_test, y_pred)\\r\\n\\r\\n fig = px.area(\\r\\n x=recall, y=precision,\\r\\n title=f'Precision-Recall Curve (AUC={auc(precision, recall):.4f})',\\r\\n labels=dict(x='Recall', y='Precision'),\\r\\n width=700, height=500\\r\\n )\\r\\n fig.add_shape(\\r\\n type='line', line=dict(dash='dash'),\\r\\n x0=0, x1=1, y0=1, y1=0\\r\\n )\\r\\n fig.update_yaxes(scaleanchor=\\\"x\\\", scaleratio=1)\\r\\n fig.update_xaxes(constrain='domain')\\r\\n st.write(fig)\\r\\n \\r\\n \\r\\n if 'ROC Curve' in metrics_list:\\r\\n fpr, tpr, thresholds = roc_curve(y_test, y_pred)\\r\\n\\r\\n fig = px.area(\\r\\n x=fpr, y=tpr,\\r\\n title=f'ROC Curve (AUC={auc(fpr, tpr):.4f})',\\r\\n labels=dict(x='False Positive Rate', y='True Positive Rate'),\\r\\n width=700, height=500\\r\\n ) \\r\\n fig.add_shape(\\r\\n type='line', line=dict(dash='dash'),\\r\\n x0=0, x1=1, y0=0, y1=1\\r\\n )\\r\\n\\r\\n fig.update_yaxes(scaleanchor=\\\"x\\\", scaleratio=1)\\r\\n fig.update_xaxes(constrain='domain')\\r\\n st.write(fig)\\r\\n \\r\\n if 'Training and Test accuracies' in metrics_list:\\r\\n mal_train_X = x_train[y_train==0]\\r\\n mal_train_y = y_train[y_train==0]\\r\\n ben_train_X = x_train[y_train==1]\\r\\n ben_train_y = y_train[y_train==1]\\r\\n \\r\\n mal_test_X = x_test[y_test==0]\\r\\n mal_test_y = y_test[y_test==0]\\r\\n ben_test_X = x_test[y_test==1]\\r\\n ben_test_y = y_test[y_test==1]\\r\\n \\r\\n scores = [model.score(mal_train_X, mal_train_y), model.score(ben_train_X, ben_train_y), model.score(mal_test_X, mal_test_y), model.score(ben_test_X, ben_test_y)]\\r\\n\\r\\n fig,ax = plt.subplots()\\r\\n \\r\\n # Plot the scores as a bar chart\\r\\n bars = plt.bar(np.arange(4), scores, color=['#4c72b0','#4c72b0','#55a868','#55a868'])\\r\\n\\r\\n # directly label the score onto the bars\\r\\n for bar in bars:\\r\\n height = bar.get_height()\\r\\n plt.gca().text(bar.get_x() + bar.get_width()/2, height*.90, '{0:.{1}f}'.format(height, 2), ha='center', color='w', fontsize=11)\\r\\n\\r\\n # remove all the ticks (both axes), and tick labels on the Y axis\\r\\n plt.tick_params(top='off', bottom='off', left='off', right='off', labelleft='off', labelbottom='on')\\r\\n\\r\\n # remove the frame of the chart\\r\\n for spine in plt.gca().spines.values():\\r\\n spine.set_visible(False)\\r\\n\\r\\n plt.xticks([0,1,2,3], ['Malignant\\\\nTraining', 'Benign\\\\nTraining', 'Malignant\\\\nTest', 'Benign\\\\nTest'], alpha=0.8);\\r\\n plt.title('Training and Test Accuracies for Malignant and Benign Cells', alpha=0.8)\\r\\n ax.xaxis.set_tick_params(length=0)\\r\\n ax.yaxis.set_tick_params(length=0)\\r\\n ax.figure.savefig('file1.png')\\r\\n st.pyplot(fig)\\r\\n \\r\\n df = load_data()\\r\\n class_names = ['malignant', 'benign']\\r\\n \\r\\n \\r\\n###------------------DATA ANAlYSIS-------------------------- \\r\\n if navigation == 'Data Analysis':\\r\\n \\r\\n \\r\\n \\r\\n if st.sidebar.checkbox(\\\"Show Raw Data\\\", False):\\r\\n st.subheader('Breast Cancer Dataset')\\r\\n \\r\\n st.dataframe(df)\\r\\n \\r\\n if st.sidebar.checkbox(\\\"Show Features\\\", False):\\r\\n cancer = load_breast_cancer()\\r\\n st.subheader('Features')\\r\\n features = pd.DataFrame(cancer.feature_names)\\r\\n features.columns = ['Features']\\r\\n st.dataframe(features)\\r\\n \\r\\n \\r\\n plots = st.sidebar.multiselect(\\\"Plots\\\", ('Scatter Matrix', 'Number of Malignant and Benign','Heatmap','Mean radius vs Mean area','Mean smoothness vs Mean area'))\\r\\n \\r\\n \\r\\n if st.sidebar.button(\\\"Plot\\\", key='plotss'):\\r\\n with st.spinner('Wait for it...'):\\r\\n time.sleep(5)\\r\\n \\r\\n if 'Number of Malignant and Benign' in plots:\\r\\n st.subheader(\\\"Malignant and Benign Count\\\")\\r\\n fig,ax = plt.subplots()\\r\\n \\r\\n ma = len(df[df['target']==1])\\r\\n be = len(df[df['target']==0])\\r\\n count=[ma,be]\\r\\n bars = plt.bar(np.arange(2), count, color=['#000099','#ffff00'])\\r\\n ##show value in bars\\r\\n for bar in bars:\\r\\n height = bar.get_height()\\r\\n plt.gca().text(bar.get_x() + bar.get_width()/2, height*.90, '{0:.{1}f}'.format(height, 2), ha='center', color='black', fontsize=11)\\r\\n plt.tick_params(top='off', bottom='off', left='off', right='off', labelleft='on', labelbottom='on')\\r\\n for spine in plt.gca().spines.values():\\r\\n spine.set_visible(False)\\r\\n plt.xticks(ticks=[0,1])\\r\\n ax.set_ylabel('Count')\\r\\n ax.set_xlabel('Target')\\r\\n ##remove dashes from frame\\r\\n ax.xaxis.set_tick_params(length=0)\\r\\n ax.yaxis.set_tick_params(length=0)\\r\\n st.pyplot(fig)\\r\\n \\r\\n \\r\\n if 'Scatter Matrix' in plots:\\r\\n st.subheader(\\\"Scatter Matrix\\\")\\r\\n fig = px.scatter_matrix(df,dimensions=['mean radius','mean texture','mean perimeter','mean area','mean smoothness'],color=\\\"target\\\",width = 800,height = 700)\\r\\n st.write(fig)\\r\\n \\r\\n if 'Heatmap' in plots:\\r\\n st.subheader(\\\"Heatmap\\\")\\r\\n fig=plt.figure(figsize = (30,20))\\r\\n hmap=sns.heatmap(df.drop(columns=['target']).corr(), annot = True,cmap= 'Blues',annot_kws={\\\"size\\\": 18})\\r\\n hmap.set_xticklabels(hmap.get_xmajorticklabels(), fontsize = 25)\\r\\n hmap.set_yticklabels(hmap.get_ymajorticklabels(), fontsize = 25)\\r\\n st.pyplot(fig)\\r\\n if 'Mean radius vs Mean area' in plots:\\r\\n st.subheader('Cancer Radius and Area')\\r\\n fig = plt.figure()\\r\\n sns.scatterplot(x=df['mean radius'],y = df['mean area'],hue = df['target'],palette=['#000099','#ffff00'])\\r\\n st.pyplot(fig)\\r\\n if 'Mean smoothness vs Mean area' in plots:\\r\\n st.subheader('Cancer Smoothness and Area')\\r\\n fig = plt.figure()\\r\\n sns.scatterplot(x=df['mean smoothness'],y = df['mean area'],hue = df['target'],palette=['#000099','#ffff00'])\\r\\n st.pyplot(fig)\\r\\n \\r\\n \\r\\n \\r\\n \\r\\n \\r\\n \\r\\n \\r\\n \\r\\n \\r\\n \\r\\n \\r\\n \\r\\n \\r\\n \\r\\n \\r\\n \\r\\n \\r\\n \\r\\n \\r\\n###---------------classification----------------------\\r\\n if navigation == 'Prediction':\\r\\n \\r\\n x_train, x_test, y_train, y_test = split(df)\\r\\n if st.sidebar.checkbox(\\\"Show X_train/Y_train\\\", False):\\r\\n st.subheader('X_train')\\r\\n st.dataframe(x_train)\\r\\n st.subheader('Y_train')\\r\\n st.dataframe(y_train)\\r\\n \\r\\n st.sidebar.subheader(\\\"Choose Classifier\\\")\\r\\n classifier = st.sidebar.selectbox(\\\"Classifier\\\", (\\\"Support Vector Machine (SVM)\\\", \\\"Logistic Regression\\\", \\\"Random Forest\\\", 'KNN', 'Decision Tree', 'Gaussian Naive Bayes'))\\r\\n\\r\\n if classifier == 'Support Vector Machine (SVM)':\\r\\n st.sidebar.subheader(\\\"Model Hyperparameters\\\")\\r\\n #choose parameters\\r\\n C = st.sidebar.number_input(\\\"C (Regularization parameter)\\\", 0.01, 10.0, step=0.01, key='C_SVM')\\r\\n kernel = st.sidebar.radio(\\\"Kernel\\\", (\\\"rbf\\\", \\\"linear\\\"), key='kernel')\\r\\n gamma = st.sidebar.radio(\\\"Gamma (Kernel Coefficient)\\\", (\\\"scale\\\", \\\"auto\\\"), key='gamma')\\r\\n\\r\\n metrics = st.sidebar.multiselect(\\\"Metrics to Plot\\\", ('Confusion Matrix', 'ROC Curve', 'Precision-Recall Curve','Training and Test accuracies'))\\r\\n \\r\\n if st.sidebar.button(\\\"Classify\\\", key='classify'):\\r\\n st.subheader(\\\"Support Vector Machine (SVM) Results\\\")\\r\\n model = SVC(C=C, kernel=kernel, gamma=gamma)\\r\\n model.fit(x_train, y_train)\\r\\n accuracy = model.score(x_test, y_test)\\r\\n y_pred = model.predict(x_test)\\r\\n st.write(\\\"Accuracy: \\\", accuracy.round(2))\\r\\n st.write(\\\"Precision: \\\", precision_score(y_test, y_pred, labels=class_names).round(2))\\r\\n st.write(\\\"Recall: \\\", recall_score(y_test, y_pred, labels=class_names).round(2))\\r\\n plot_metrics(metrics)\\r\\n \\r\\n if classifier == 'Logistic Regression':\\r\\n st.sidebar.subheader(\\\"Model Hyperparameters\\\")\\r\\n C = st.sidebar.number_input(\\\"C (Regularization parameter)\\\", 0.01, 10.0, step=0.01, key='C_LR')\\r\\n max_iter = st.sidebar.slider(\\\"Maximum number of iterations\\\", 100, 500, key='max_iter')\\r\\n \\r\\n metrics = st.sidebar.multiselect(\\\"Metrics to Plot\\\", ('Confusion Matrix', 'ROC Curve', 'Precision-Recall Curve','Training and Test accuracies'))\\r\\n \\r\\n if st.sidebar.button(\\\"Classify\\\", key='classify'):\\r\\n st.subheader(\\\"Logistic Regression Results\\\")\\r\\n model = LogisticRegression(C=C, penalty='l2', max_iter=max_iter)\\r\\n model.fit(x_train, y_train)\\r\\n accuracy = model.score(x_test, y_test)\\r\\n y_pred = model.predict(x_test)\\r\\n st.write(\\\"Accuracy: \\\", accuracy.round(2))\\r\\n st.write(\\\"Precision: \\\", precision_score(y_test, y_pred, labels=class_names).round(2))\\r\\n st.write(\\\"Recall: \\\", recall_score(y_test, y_pred, labels=class_names).round(2))\\r\\n plot_metrics(metrics)\\r\\n \\r\\n if classifier == 'Random Forest':\\r\\n st.sidebar.subheader(\\\"Model Hyperparameters\\\")\\r\\n n_estimators = st.sidebar.number_input(\\\"The number of trees in the forest\\\", 100, 5000, step=10, key='n_estimators')\\r\\n max_depth = st.sidebar.number_input(\\\"The maximum depth of the tree\\\", 1, 20, step=1, key='max_depth')\\r\\n bootstrap = st.sidebar.radio(\\\"Bootstrap samples when building trees\\\", ('True', 'False'), key='bootstrap')\\r\\n metrics = st.sidebar.multiselect(\\\"Metrics to Plot\\\", ('Confusion Matrix', 'ROC Curve', 'Precision-Recall Curve','Training and Test accuracies'))\\r\\n \\r\\n if st.sidebar.button(\\\"Classify\\\", key='classify'):\\r\\n st.subheader(\\\"Random Forest Results\\\")\\r\\n model = RandomForestClassifier(n_estimators=n_estimators, max_depth=max_depth, bootstrap=bootstrap, n_jobs=-1)\\r\\n model.fit(x_train, y_train)\\r\\n accuracy = model.score(x_test, y_test)\\r\\n y_pred = model.predict(x_test)\\r\\n st.write(\\\"Accuracy: \\\", accuracy.round(2))\\r\\n st.write(\\\"Precision: \\\", precision_score(y_test, y_pred, labels=class_names).round(2))\\r\\n st.write(\\\"Recall: \\\", recall_score(y_test, y_pred, labels=class_names).round(2))\\r\\n plot_metrics(metrics)\\r\\n \\r\\n if classifier == 'KNN':\\r\\n st.sidebar.subheader(\\\"Model Hyperparameters\\\")\\r\\n n_neighbors = st.sidebar.number_input(\\\"Number of neighbors\\\", 1, 100, step=1, key='n_neighbors')\\r\\n \\r\\n metrics = st.sidebar.multiselect(\\\"Metrics to Plot\\\", ('Confusion Matrix', 'ROC Curve', 'Precision-Recall Curve','Training and Test accuracies'))\\r\\n\\r\\n if st.sidebar.button(\\\"Classify\\\", key='classify'):\\r\\n st.subheader(\\\"KNN Results\\\")\\r\\n model = KNeighborsClassifier(n_neighbors = n_neighbors )\\r\\n model.fit(x_train, y_train)\\r\\n accuracy = model.score(x_test, y_test)\\r\\n y_pred = model.predict(x_test)\\r\\n st.write(\\\"Accuracy: \\\", accuracy.round(2))\\r\\n st.write(\\\"Precision: \\\", precision_score(y_test, y_pred, labels=class_names).round(2))\\r\\n st.write(\\\"Recall: \\\", recall_score(y_test, y_pred, labels=class_names).round(2))\\r\\n plot_metrics(metrics)\\r\\n \\r\\n if classifier == 'Decision Tree':\\r\\n st.sidebar.subheader(\\\"Model Hyperparameters\\\")\\r\\n \\r\\n max_depth = st.sidebar.number_input(\\\"The maximum depth of the tree\\\", 1, 20, step=1, key='max_depth')\\r\\n criterion = st.sidebar.radio(\\\"Criterion\\\", (\\\"gini\\\", \\\"entropy\\\"), key='criterion')\\r\\n splitter = st.sidebar.radio(\\\"Splitter\\\", (\\\"best\\\", \\\"random\\\"), key='splitter')\\r\\n metrics = st.sidebar.multiselect(\\\"Metrics to Plot\\\", ('Confusion Matrix', 'ROC Curve', 'Precision-Recall Curve','Training and Test accuracies'))\\r\\n \\r\\n if st.sidebar.button(\\\"Classify\\\", key='classify'):\\r\\n st.subheader(\\\"Decision Tree Results\\\")\\r\\n model = DecisionTreeClassifier(max_depth= max_depth, criterion= criterion, splitter= splitter )\\r\\n model.fit(x_train, y_train)\\r\\n accuracy = model.score(x_test, y_test)\\r\\n y_pred = model.predict(x_test)\\r\\n st.write(\\\"Accuracy: \\\", accuracy.round(2))\\r\\n st.write(\\\"Precision: \\\", precision_score(y_test, y_pred, labels=class_names).round(2))\\r\\n st.write(\\\"Recall: \\\", recall_score(y_test, y_pred, labels=class_names).round(2))\\r\\n plot_metrics(metrics)\\r\\n \\r\\n if classifier == 'Gaussian Naive Bayes':\\r\\n st.sidebar.subheader(\\\"Model Hyperparameters\\\")\\r\\n \\r\\n \\r\\n metrics = st.sidebar.multiselect(\\\"Metrics to Plot\\\", ('Confusion Matrix', 'ROC Curve', 'Precision-Recall Curve','Training and Test accuracies'))\\r\\n\\r\\n if st.sidebar.button(\\\"Classify\\\", key='classify'):\\r\\n st.subheader(\\\"Gaussian Naive Bayes Results\\\")\\r\\n model = GaussianNB()\\r\\n model.fit(x_train, y_train)\\r\\n accuracy = model.score(x_test, y_test)\\r\\n y_pred = model.predict(x_test)\\r\\n st.write(\\\"Accuracy: \\\", accuracy.round(2))\\r\\n st.write(\\\"Precision: \\\", precision_score(y_test, y_pred, labels=class_names).round(2))\\r\\n st.write(\\\"Recall: \\\", recall_score(y_test, y_pred, labels=class_names).round(2))\\r\\n plot_metrics(metrics) \\r\\n \\r\\n st.sidebar.subheader(\\\"ABOUT\\\")\\r\\n st.sidebar.write('By: Vishva Desai')\\r\\n st.sidebar.write(\\\"Github: https://github.com/vishvadesai9\\\") \\r\\n \\r\\n \\r\\n \\r\\n\\r\\n\\r\\n\\r\\n\\r\\n\\r\\n\\r\\nif __name__ == '__main__':\\r\\n main()\\r\\n\"\n }\n]"},"num_files":{"kind":"number","value":3,"string":"3"}}},{"rowIdx":2041,"cells":{"repo_name":{"kind":"string","value":"Bolteren/avtoDoc"},"repo_url":{"kind":"string","value":"https://github.com/Bolteren/avtoDoc"},"snapshot_id":{"kind":"string","value":"38eec4deaabfada6c16ad54bb2e4d6e1f445dc43"},"revision_id":{"kind":"string","value":"d3c8ea91491186213cbd49ccb3a317533b3019be"},"directory_id":{"kind":"string","value":"65bd5cafb96948dbd82ce5489fc6bb1f375a64cb"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"string","value":"2023-06-19T11:46:25.123755"},"revision_date":{"kind":"string","value":"2021-07-13T11:47:08"},"committer_date":{"kind":"string","value":"2021-07-13T11:47:08"},"github_id":{"kind":"number","value":382865640,"string":"382,865,640"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.4722435474395752,"alphanum_fraction":0.4840112626552582,"avg_line_length":30.27199935913086,"blob_id":"aa83eaa344ea60444cc7da8cc7988ece286d7b1f","content_id":"de1197babe3e866f9d236f3c71d74b0458fbfa8c","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":4005,"license_type":"no_license","max_line_length":138,"num_lines":125,"path":"/parrss.py","repo_name":"Bolteren/avtoDoc","src_encoding":"UTF-8","text":"import copy\nimport codecs\nimport re\n\ndef clear_file(name):\n input_file = codecs.open(name, 'r')\n output_file = open('temp.htm', 'w')\n for i in range(1, 119):\n next(input_file)\n while True:\n try:\n words = input_file.readline()\n except Exception:\n next(input_file)\n words = input_file.readline()\n output_file.write(words)\n if not words:\n break\n input_file.close()\n output_file.close()\n\n\ndef parse_programm():\n f = open('temp.htm', 'r')\n html = f.read()\n lst = html.split('\\n')\n out_text = []\n checked_element = \"\"\"Установленные программы\"\"\"\n checked_end_element = \"\"\"</TABLE><BR><BR>\"\"\"\n checked_header = \"\"\"<TR><TD><TD><TD><B>Программа</B> <TD CLASS=cr><B>Версия</B> <TD \n CLASS=cr><B>Размер</B> <TD><B>GUID</B> <TD><B>Издатель</B> <TD \n CLASS=cr><B>Дата</B> \"\"\"\n t = -1\n for element in lst:\n if element.find(checked_header) != -1:\n continue\n if t == -1:\n t = element.find(checked_element)\n continue\n if t > 0 and element.find(checked_end_element) != -1:\n t = -1\n if t > 0:\n out = element.replace('<TR><TD><TD><TD>', '')\n out1 = out.replace(' <TD CLASS=cr>', '$$').split('$$')[0]\n out_text.append(out1)\n return out_text\n\n\ndef parse_licence():\n f = open('temp.htm', 'r')\n html = f.read()\n lst = html.split('\\n')\n out_text = {}\n checked_element = \"\"\"<A NAME=\"licenses\">Лицензии</A>\"\"\"\n checked_end_element = \"\"\"</TABLE><BR><BR>\"\"\"\n checked_header = \"\"\"<TR><TD><TD><TD><B>Программы</B> <TD><B>Ключ продукта</B>\"\"\"\n t = -1\n for element in lst:\n if element.find(checked_header) != -1:\n continue\n if t == -1:\n t = element.find(checked_element)\n continue\n if t > 0 and element.find(checked_end_element) != -1:\n t = -1\n if t > 0:\n out = element.replace('<TR><TD><TD><TD>', '')\n out1 = out.replace(' <TD>', '$$').split('$$')[0]\n out_l = out.replace(' <TD>', '$$').split('$$')[1]\n out_text[out1] = out_l\n return out_text\n\n\ndef parse_fix():\n f = open('Report_New_0.html', 'r')\n file_element = []\n file_params = []\n check = -1\n while True:\n str = f.readline()\n if not str:\n break\n if re.match(\n r\"\"\"<td class=\"ktlg\" COLSPAN=6 ALIGN=CENTER>Каталог C:\\\\Program\\sFiles(\\s\\(x86\\))?\\\\Secret\\sNet\\sStudio\\\\Client\\\\</td>\"\"\",\n str):\n check = 0\n continue\n if check == 0:\n if str.find('<td class=\"ks\" >') != -1:\n name_file = str.replace(\"<\", \">\").split(\">\")[2]\n file_params.append(name_file)\n check = 1\n continue\n if check == 1:\n data_file = str.replace(\"<\", \">\").split(\">\")[2]\n file_params.append(data_file)\n check = 2\n continue\n if check == 2:\n len_file = str.replace(\"<\", \">\").split(\">\")[2]\n file_params.append(len_file)\n check = 3\n continue\n if check == 3:\n if str.find('<td class=\"ks\" ALIGN=CENTER>') != -1:\n ks = str.replace(\"<\", \">\").split(\">\")[2]\n file_params.append(ks)\n check = 0\n else:\n continue\n if str.find(\"итого:\") != -1:\n break\n if not file_params:\n continue\n file_element.append(copy.deepcopy(file_params))\n file_params.clear()\n return file_element\n\n\nif __name__ == '__main__':\n clear_file('Report.htm')\n # print(parse_programm())\n # print(parse_licence())\n #parse_fix()\n print(len(parse_fix()))\n"}],"string":"[\n {\n \"alpha_fraction\": 0.4722435474395752,\n \"alphanum_fraction\": 0.4840112626552582,\n \"avg_line_length\": 30.27199935913086,\n \"blob_id\": \"aa83eaa344ea60444cc7da8cc7988ece286d7b1f\",\n \"content_id\": \"de1197babe3e866f9d236f3c71d74b0458fbfa8c\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 4005,\n \"license_type\": \"no_license\",\n \"max_line_length\": 138,\n \"num_lines\": 125,\n \"path\": \"/parrss.py\",\n \"repo_name\": \"Bolteren/avtoDoc\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import copy\\nimport codecs\\nimport re\\n\\ndef clear_file(name):\\n input_file = codecs.open(name, 'r')\\n output_file = open('temp.htm', 'w')\\n for i in range(1, 119):\\n next(input_file)\\n while True:\\n try:\\n words = input_file.readline()\\n except Exception:\\n next(input_file)\\n words = input_file.readline()\\n output_file.write(words)\\n if not words:\\n break\\n input_file.close()\\n output_file.close()\\n\\n\\ndef parse_programm():\\n f = open('temp.htm', 'r')\\n html = f.read()\\n lst = html.split('\\\\n')\\n out_text = []\\n checked_element = \\\"\\\"\\\"Установленные программы\\\"\\\"\\\"\\n checked_end_element = \\\"\\\"\\\"</TABLE><BR><BR>\\\"\\\"\\\"\\n checked_header = \\\"\\\"\\\"<TR><TD><TD><TD><B>Программа</B> <TD CLASS=cr><B>Версия</B> <TD \\n CLASS=cr><B>Размер</B> <TD><B>GUID</B> <TD><B>Издатель</B> <TD \\n CLASS=cr><B>Дата</B> \\\"\\\"\\\"\\n t = -1\\n for element in lst:\\n if element.find(checked_header) != -1:\\n continue\\n if t == -1:\\n t = element.find(checked_element)\\n continue\\n if t > 0 and element.find(checked_end_element) != -1:\\n t = -1\\n if t > 0:\\n out = element.replace('<TR><TD><TD><TD>', '')\\n out1 = out.replace(' <TD CLASS=cr>', '$$').split('$$')[0]\\n out_text.append(out1)\\n return out_text\\n\\n\\ndef parse_licence():\\n f = open('temp.htm', 'r')\\n html = f.read()\\n lst = html.split('\\\\n')\\n out_text = {}\\n checked_element = \\\"\\\"\\\"<A NAME=\\\"licenses\\\">Лицензии</A>\\\"\\\"\\\"\\n checked_end_element = \\\"\\\"\\\"</TABLE><BR><BR>\\\"\\\"\\\"\\n checked_header = \\\"\\\"\\\"<TR><TD><TD><TD><B>Программы</B> <TD><B>Ключ продукта</B>\\\"\\\"\\\"\\n t = -1\\n for element in lst:\\n if element.find(checked_header) != -1:\\n continue\\n if t == -1:\\n t = element.find(checked_element)\\n continue\\n if t > 0 and element.find(checked_end_element) != -1:\\n t = -1\\n if t > 0:\\n out = element.replace('<TR><TD><TD><TD>', '')\\n out1 = out.replace(' <TD>', '$$').split('$$')[0]\\n out_l = out.replace(' <TD>', '$$').split('$$')[1]\\n out_text[out1] = out_l\\n return out_text\\n\\n\\ndef parse_fix():\\n f = open('Report_New_0.html', 'r')\\n file_element = []\\n file_params = []\\n check = -1\\n while True:\\n str = f.readline()\\n if not str:\\n break\\n if re.match(\\n r\\\"\\\"\\\"<td class=\\\"ktlg\\\" COLSPAN=6 ALIGN=CENTER>Каталог C:\\\\\\\\Program\\\\sFiles(\\\\s\\\\(x86\\\\))?\\\\\\\\Secret\\\\sNet\\\\sStudio\\\\\\\\Client\\\\\\\\</td>\\\"\\\"\\\",\\n str):\\n check = 0\\n continue\\n if check == 0:\\n if str.find('<td class=\\\"ks\\\" >') != -1:\\n name_file = str.replace(\\\"<\\\", \\\">\\\").split(\\\">\\\")[2]\\n file_params.append(name_file)\\n check = 1\\n continue\\n if check == 1:\\n data_file = str.replace(\\\"<\\\", \\\">\\\").split(\\\">\\\")[2]\\n file_params.append(data_file)\\n check = 2\\n continue\\n if check == 2:\\n len_file = str.replace(\\\"<\\\", \\\">\\\").split(\\\">\\\")[2]\\n file_params.append(len_file)\\n check = 3\\n continue\\n if check == 3:\\n if str.find('<td class=\\\"ks\\\" ALIGN=CENTER>') != -1:\\n ks = str.replace(\\\"<\\\", \\\">\\\").split(\\\">\\\")[2]\\n file_params.append(ks)\\n check = 0\\n else:\\n continue\\n if str.find(\\\"итого:\\\") != -1:\\n break\\n if not file_params:\\n continue\\n file_element.append(copy.deepcopy(file_params))\\n file_params.clear()\\n return file_element\\n\\n\\nif __name__ == '__main__':\\n clear_file('Report.htm')\\n # print(parse_programm())\\n # print(parse_licence())\\n #parse_fix()\\n print(len(parse_fix()))\\n\"\n }\n]"},"num_files":{"kind":"number","value":1,"string":"1"}}},{"rowIdx":2042,"cells":{"repo_name":{"kind":"string","value":"aviator19941/DATA-301"},"repo_url":{"kind":"string","value":"https://github.com/aviator19941/DATA-301"},"snapshot_id":{"kind":"string","value":"ecb7627b792141e7cba800c0e6eb46a1deecfd82"},"revision_id":{"kind":"string","value":"c891fce5c230c1de11a93326d5fdc818232dad34"},"directory_id":{"kind":"string","value":"12810b7df2b0a34459423cce4913df9575ccaa38"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"string","value":"2021-01-19T13:56:11.181789"},"revision_date":{"kind":"string","value":"2017-02-19T05:46:41"},"committer_date":{"kind":"string","value":"2017-02-19T05:46:41"},"github_id":{"kind":"number","value":82435281,"string":"82,435,281"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.6182026267051697,"alphanum_fraction":0.633085310459137,"avg_line_length":29.05172348022461,"blob_id":"a9f9156dc9fab0432c78ce18511b7e9665df5a13","content_id":"514cb0fe922f0de82fe61e90c2148e5bc9fbf30d","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1747,"license_type":"no_license","max_line_length":90,"num_lines":58,"path":"/lab1q1.py","repo_name":"aviator19941/DATA-301","src_encoding":"UTF-8","text":"# James Ly\n# Avinash Sharma\n# Purpose : reports the amount of unique names over the years to a file\n# named \"question1.txt\"\n# input file is names1000.csv\n\n#object for baby names\nclass BabyName:\n def __init__(self, in_name, in_year, in_gender, in_count) :\n self.name = in_name\n self.year = in_year\n self.gender = in_gender\n self.count = in_count\n\n\n#blank list\nnamesList = []\n\n#read through whole file\ninputFile = open(\"names1000.csv\", 'r')\nwhile True:\n line = inputFile.readline()\n if len(line) == 0:\n break\n data = line.split(',')\n #add data to list\n namesList.append(BabyName(data[1],data[2],data[3],data[4]))\n\n#open file to be written to\noutputFile = open(\"question1.txt\", 'w')\noutputFile.write(\"Question 1: Which year has the most unique names?\\n\\n\")\noutputFile.write(\"Results for the amount of unique names over the years\\n\\n\")\n\nyearList = []\n#check for unique names\nfor i in range(0, len(namesList)):\n #separate by year\n if namesList[i].year not in yearList:\n yearNum = namesList[i].year\n yearList.append(yearNum)\n \n #create a list of unique names\n uniqueAmount = []\n\n #add all unique names that are in the same year\n for j in range(0, len(namesList)):\n if yearNum == namesList[j].year:\n uniqueAmount.append(namesList[j].name)\n outputFile.write(str(yearNum) + \": \" + str(len(uniqueAmount)) + \" unique names\\n\")\n \n#write total # of names and years in file\noutputFile.write(\"\\n\") \noutputFile.write(\"total names in names1000: \" + str(len(namesList)) + \"\\n\")\noutputFile.write(\"# of years in names1000: \" + str(len(yearList)) + \"\\n\")\n\n#close files\ninputFile.close()\noutputFile.close()\n\n\n\n\n"},{"alpha_fraction":0.5517393350601196,"alphanum_fraction":0.5623073577880859,"avg_line_length":28.88157844543457,"blob_id":"5ee607829022450c11131bb2a81707c82557ac95","content_id":"e562aa15ead9336de50b07556038307a4c3e6c2a","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":2271,"license_type":"no_license","max_line_length":109,"num_lines":76,"path":"/lab1q2.py","repo_name":"aviator19941/DATA-301","src_encoding":"UTF-8","text":"# James Ly\n# Avinash Sharma\n# Purpose : reports number of male and female births in each year\n# to a file named \"question2.txt\"\n# input file is names1000.csv\n\n#object for baby names\nclass BabyName:\n def __init__(self, in_name, in_year, in_gender, in_count) :\n self.name = in_name\n self.year = in_year\n self.gender = in_gender\n self.count = in_count\n\n#blank list\nnamesList = []\n\n#read through whole file\ninputFile = open(\"names1000.csv\", 'r')\nwhile True:\n line = inputFile.readline()\n if len(line) == 0:\n break\n data = line.split(',')\n #add data to list\n namesList.append(BabyName(data[1],data[2],data[3],data[4]))\n\n\n#open file to be written to\noutputFile = open(\"question2.txt\", 'w')\noutputFile.write(\"Question 2: How did the number of births change over the years for males and females?\\n\\n\")\noutputFile.write(\"Results for number of male and female births over the years\\n\\n\")\n\nyearList = []\n#sum up number of births in each year\nfor i in range(0, len(namesList)):\n\n #separate by year\n if namesList[i].year not in yearList:\n yearNum = namesList[i].year\n yearList.append(yearNum)\n maleList = []\n femaleList = []\n\n #separate by male or female\n #into male or female lists\n for j in range(0, len(namesList)):\n if yearNum == namesList[j].year:\n if namesList[j].gender == 'M':\n maleList.append(namesList[j])\n else:\n femaleList.append(namesList[j])\n\n #add up all the male counts \n if len(maleList) > 0:\n maleSum = 0\n for x in range(1, len(maleList)): \n item = maleList[x].count\n item.replace(\"\\n\", \"\")\n maleSum += int(item)\n\n outputFile.write(str(yearNum) + \" m: \" + str(maleSum))\n\n #add up all the female counts \n if len(femaleList) > 0:\n femaleSum = 0\n for x in range(1, len(femaleList)):\n item = femaleList[x].count\n item.replace(\"\\n\",\"\")\n femaleSum += int(item)\n \n outputFile.write(\" f: \" + str(femaleSum) + \"\\n\")\n \n#close files\ninputFile.close()\noutputFile.close()\n"},{"alpha_fraction":0.6206425428390503,"alphanum_fraction":0.6329460144042969,"avg_line_length":28.40816307067871,"blob_id":"e0ccefdf54850404f0319445d84d19cc50724776","content_id":"6709df8fa1267333e6a531e2b0dc85f15e53ab0d","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1463,"license_type":"no_license","max_line_length":90,"num_lines":49,"path":"/lab1q3.py","repo_name":"aviator19941/DATA-301","src_encoding":"UTF-8","text":"# James Ly\n# Avinash Sharma\n# Purpose : reports the count of baby names with \"Emma\" throughout the years\n# to a text file named \"question3.txt\"\n# input file is names1000.csv\n\n#object for baby names\nclass BabyName:\n def __init__(self, in_name, in_year, in_gender, in_count) :\n self.name = in_name\n self.year = in_year\n self.gender = in_gender\n self.count = in_count\n\n#blank list\nnamesList = []\n\n#read through whole file\ninputFile = open(\"names1000.csv\", 'r')\nwhile True:\n line = inputFile.readline()\n if len(line) == 0:\n break\n data = line.split(',')\n #add data to list\n namesList.append(BabyName(data[1],data[2],data[3],data[4]))\n\n\n#open file to be written to\noutputFile = open(\"question3.txt\", 'w')\noutputFile.write(\"Question 3: How does the popularity of Emma change over the years?\\n\\n\")\noutputFile.write(\"Results for popularity of Emma over the years\\n\\n\")\n\nyearList = []\n#check for instances of \"Emma\" in each year\nfor i in range(0, len(namesList)):\n #separate by year\n if namesList[i].year not in yearList:\n yearNum = namesList[i].year\n yearList.append(yearNum)\n\n #check if baby name is \"Emma\"\n for j in range(0, len(namesList)):\n if (namesList[j].name == 'Emma') and (namesList[j].year == yearNum):\n outputFile.write(str(yearNum) + \" count: \" + str(namesList[j].count))\n\n#close files\ninputFile.close()\noutputFile.close()\n\n \n"}],"string":"[\n {\n \"alpha_fraction\": 0.6182026267051697,\n \"alphanum_fraction\": 0.633085310459137,\n \"avg_line_length\": 29.05172348022461,\n \"blob_id\": \"a9f9156dc9fab0432c78ce18511b7e9665df5a13\",\n \"content_id\": \"514cb0fe922f0de82fe61e90c2148e5bc9fbf30d\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1747,\n \"license_type\": \"no_license\",\n \"max_line_length\": 90,\n \"num_lines\": 58,\n \"path\": \"/lab1q1.py\",\n \"repo_name\": \"aviator19941/DATA-301\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# James Ly\\n# Avinash Sharma\\n# Purpose : reports the amount of unique names over the years to a file\\n# named \\\"question1.txt\\\"\\n# input file is names1000.csv\\n\\n#object for baby names\\nclass BabyName:\\n def __init__(self, in_name, in_year, in_gender, in_count) :\\n self.name = in_name\\n self.year = in_year\\n self.gender = in_gender\\n self.count = in_count\\n\\n\\n#blank list\\nnamesList = []\\n\\n#read through whole file\\ninputFile = open(\\\"names1000.csv\\\", 'r')\\nwhile True:\\n line = inputFile.readline()\\n if len(line) == 0:\\n break\\n data = line.split(',')\\n #add data to list\\n namesList.append(BabyName(data[1],data[2],data[3],data[4]))\\n\\n#open file to be written to\\noutputFile = open(\\\"question1.txt\\\", 'w')\\noutputFile.write(\\\"Question 1: Which year has the most unique names?\\\\n\\\\n\\\")\\noutputFile.write(\\\"Results for the amount of unique names over the years\\\\n\\\\n\\\")\\n\\nyearList = []\\n#check for unique names\\nfor i in range(0, len(namesList)):\\n #separate by year\\n if namesList[i].year not in yearList:\\n yearNum = namesList[i].year\\n yearList.append(yearNum)\\n \\n #create a list of unique names\\n uniqueAmount = []\\n\\n #add all unique names that are in the same year\\n for j in range(0, len(namesList)):\\n if yearNum == namesList[j].year:\\n uniqueAmount.append(namesList[j].name)\\n outputFile.write(str(yearNum) + \\\": \\\" + str(len(uniqueAmount)) + \\\" unique names\\\\n\\\")\\n \\n#write total # of names and years in file\\noutputFile.write(\\\"\\\\n\\\") \\noutputFile.write(\\\"total names in names1000: \\\" + str(len(namesList)) + \\\"\\\\n\\\")\\noutputFile.write(\\\"# of years in names1000: \\\" + str(len(yearList)) + \\\"\\\\n\\\")\\n\\n#close files\\ninputFile.close()\\noutputFile.close()\\n\\n\\n\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.5517393350601196,\n \"alphanum_fraction\": 0.5623073577880859,\n \"avg_line_length\": 28.88157844543457,\n \"blob_id\": \"5ee607829022450c11131bb2a81707c82557ac95\",\n \"content_id\": \"e562aa15ead9336de50b07556038307a4c3e6c2a\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 2271,\n \"license_type\": \"no_license\",\n \"max_line_length\": 109,\n \"num_lines\": 76,\n \"path\": \"/lab1q2.py\",\n \"repo_name\": \"aviator19941/DATA-301\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# James Ly\\n# Avinash Sharma\\n# Purpose : reports number of male and female births in each year\\n# to a file named \\\"question2.txt\\\"\\n# input file is names1000.csv\\n\\n#object for baby names\\nclass BabyName:\\n def __init__(self, in_name, in_year, in_gender, in_count) :\\n self.name = in_name\\n self.year = in_year\\n self.gender = in_gender\\n self.count = in_count\\n\\n#blank list\\nnamesList = []\\n\\n#read through whole file\\ninputFile = open(\\\"names1000.csv\\\", 'r')\\nwhile True:\\n line = inputFile.readline()\\n if len(line) == 0:\\n break\\n data = line.split(',')\\n #add data to list\\n namesList.append(BabyName(data[1],data[2],data[3],data[4]))\\n\\n\\n#open file to be written to\\noutputFile = open(\\\"question2.txt\\\", 'w')\\noutputFile.write(\\\"Question 2: How did the number of births change over the years for males and females?\\\\n\\\\n\\\")\\noutputFile.write(\\\"Results for number of male and female births over the years\\\\n\\\\n\\\")\\n\\nyearList = []\\n#sum up number of births in each year\\nfor i in range(0, len(namesList)):\\n\\n #separate by year\\n if namesList[i].year not in yearList:\\n yearNum = namesList[i].year\\n yearList.append(yearNum)\\n maleList = []\\n femaleList = []\\n\\n #separate by male or female\\n #into male or female lists\\n for j in range(0, len(namesList)):\\n if yearNum == namesList[j].year:\\n if namesList[j].gender == 'M':\\n maleList.append(namesList[j])\\n else:\\n femaleList.append(namesList[j])\\n\\n #add up all the male counts \\n if len(maleList) > 0:\\n maleSum = 0\\n for x in range(1, len(maleList)): \\n item = maleList[x].count\\n item.replace(\\\"\\\\n\\\", \\\"\\\")\\n maleSum += int(item)\\n\\n outputFile.write(str(yearNum) + \\\" m: \\\" + str(maleSum))\\n\\n #add up all the female counts \\n if len(femaleList) > 0:\\n femaleSum = 0\\n for x in range(1, len(femaleList)):\\n item = femaleList[x].count\\n item.replace(\\\"\\\\n\\\",\\\"\\\")\\n femaleSum += int(item)\\n \\n outputFile.write(\\\" f: \\\" + str(femaleSum) + \\\"\\\\n\\\")\\n \\n#close files\\ninputFile.close()\\noutputFile.close()\\n\"\n },\n {\n \"alpha_fraction\": 0.6206425428390503,\n \"alphanum_fraction\": 0.6329460144042969,\n \"avg_line_length\": 28.40816307067871,\n \"blob_id\": \"e0ccefdf54850404f0319445d84d19cc50724776\",\n \"content_id\": \"6709df8fa1267333e6a531e2b0dc85f15e53ab0d\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1463,\n \"license_type\": \"no_license\",\n \"max_line_length\": 90,\n \"num_lines\": 49,\n \"path\": \"/lab1q3.py\",\n \"repo_name\": \"aviator19941/DATA-301\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# James Ly\\n# Avinash Sharma\\n# Purpose : reports the count of baby names with \\\"Emma\\\" throughout the years\\n# to a text file named \\\"question3.txt\\\"\\n# input file is names1000.csv\\n\\n#object for baby names\\nclass BabyName:\\n def __init__(self, in_name, in_year, in_gender, in_count) :\\n self.name = in_name\\n self.year = in_year\\n self.gender = in_gender\\n self.count = in_count\\n\\n#blank list\\nnamesList = []\\n\\n#read through whole file\\ninputFile = open(\\\"names1000.csv\\\", 'r')\\nwhile True:\\n line = inputFile.readline()\\n if len(line) == 0:\\n break\\n data = line.split(',')\\n #add data to list\\n namesList.append(BabyName(data[1],data[2],data[3],data[4]))\\n\\n\\n#open file to be written to\\noutputFile = open(\\\"question3.txt\\\", 'w')\\noutputFile.write(\\\"Question 3: How does the popularity of Emma change over the years?\\\\n\\\\n\\\")\\noutputFile.write(\\\"Results for popularity of Emma over the years\\\\n\\\\n\\\")\\n\\nyearList = []\\n#check for instances of \\\"Emma\\\" in each year\\nfor i in range(0, len(namesList)):\\n #separate by year\\n if namesList[i].year not in yearList:\\n yearNum = namesList[i].year\\n yearList.append(yearNum)\\n\\n #check if baby name is \\\"Emma\\\"\\n for j in range(0, len(namesList)):\\n if (namesList[j].name == 'Emma') and (namesList[j].year == yearNum):\\n outputFile.write(str(yearNum) + \\\" count: \\\" + str(namesList[j].count))\\n\\n#close files\\ninputFile.close()\\noutputFile.close()\\n\\n \\n\"\n }\n]"},"num_files":{"kind":"number","value":3,"string":"3"}}},{"rowIdx":2043,"cells":{"repo_name":{"kind":"string","value":"vaillant/SataRDM"},"repo_url":{"kind":"string","value":"https://github.com/vaillant/SataRDM"},"snapshot_id":{"kind":"string","value":"b2455569099ffe30e1cc95bba758cade394895bb"},"revision_id":{"kind":"string","value":"8adf587f1ccf5769dc6885e803c07acb0d1b36d6"},"directory_id":{"kind":"string","value":"ba4a78ae9d3e9e381e75128e78e11f0601ad6597"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"string","value":"2021-01-22T21:13:24.185566"},"revision_date":{"kind":"string","value":"2012-12-30T19:22:40"},"committer_date":{"kind":"string","value":"2012-12-30T19:22:40"},"github_id":{"kind":"number","value":2212496,"string":"2,212,496"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":2,"string":"2"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.5822513103485107,"alphanum_fraction":0.5899940729141235,"avg_line_length":42.19587707519531,"blob_id":"e80564d7d3761958fd24f61a865a3bfa7ea1e098","content_id":"26cfa755eec34b15c604ad9189687073c007a8f8","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":8395,"license_type":"no_license","max_line_length":146,"num_lines":194,"path":"/SataRdm/src/vmksatardm.py","repo_name":"vaillant/SataRDM","src_encoding":"UTF-8","text":"#!/usr/bin/python\n'''\nCreated on Jul 30, 2011\n\n@author: Stefan Vaillant\nCopyright Stefan Vaillant, 2011-2012\n\n'''\n\nfrom xml.etree.ElementTree import parse\nfrom optparse import OptionParser\nfrom subprocess import Popen, PIPE\nimport exceptions\nimport os\nimport StringIO\n\nRDM_DIR = \"RDMs\" # in which folder to create the RDMs\nFILE_EXT = \".vmdk\"\nTYPE_MAP = { \"physical\": \"-z\", \"virtual\": \"-r\"} # maps options to vmkfstools option\nGIBIBYTES = 1024 * 1024 * 1024\nVMLPATH = \"/vmfs/devices/disks/\"\n\ndef getValueFor(element, s):\n ''' return v, where <value name=x>v</value> and x==s'''\n result = [ v.text for v in element.getchildren() if v.tag == \"value\" and v.attrib['name'] == s]\n assert len(result) == 1, \"expecting element with <value name='%s'> under %s element\" % (s, element.tag)\n return result[0]\n\ndef stringToIntList(str,maximum):\n # return (error, [int])\n # i.e. (None, [1,2]) = stringToIntList(\"1,2\", 2)\n error = None\n result = []\n if str==\"all\":\n result = range(1,maximum+1)\n elif str==\"none\" or str==\"\":\n result = []\n else:\n try:\n result = [int(s) for s in str.split(\",\") ]\n for r in result:\n if not r in range(1,maximum+1):\n error = \"value '%d' out of range (1..%d)\" % (r,maximum)\n except exceptions.ValueError, e:\n error = \"%s\" % (e)\n return (error,result)\n\ndef executeCmd(strs, noprint, noexec):\n result = \"\"\n if not noprint:\n print \" \".join(strs)\n if not noexec:\n if strs[0] == \"cd\":\n os.chdir(strs[1])\n elif strs[0] == \"mkdir\":\n os.mkdir(strs[1])\n else:\n result = Popen(strs)\n return result \n\nclass DiskInfo(object):\n def __init__(self,root,dict):\n self.__dict__.update(dict)\n self.root = root\n def getpreferredpathuid(self):\n e = self.root.find(\"lun/nmp-device-configuration/fixed-path-selection-policy\")\n# result = [ v.text for v in e.iter(\"value\") if v.attrib['name'] == \"preferred-path-uid\" ]\n# assert len(result) == 1, \"expecting element with <value name='preferred-path-uid'> under <lun> element\"\n return getValueFor(e, \"preferred-path-uid\")\n def getpartitiontypes(self):\n parts = self.root.findall(\"partitions/disk-lun-partition\")\n result = [ getValueFor(p, \"partition-type\") for p in parts ]\n return result\n def getDeviceUID(self):\n uids = self.root.findall(\"lun/device-uids/device-uid\")\n result = [ getValueFor(p, \"uid\") for p in uids if getValueFor(p, \"uid\").startswith(\"vml.\")]\n assert len(result) > 0, \"The device must have one UID starting with 'vml.'\"\n return result[0]\n def getRDMFile(self):\n def convert(str):\n return str.replace(\" \", \"\")\n def convert2(str):\n return str.replace(\" \", \"-\",1).replace(\" \",\"\")\n def serialnumber():\n return self.devfspath.split(\"_\")[-1]\n basename = \"%s-%s-%dGB\" % (convert2(self.model), serialnumber(), long(self.size) / GIBIBYTES)\n if os.path.exists(basename + FILE_EXT):\n i = 0\n while os.path.exists(basename + \"-\" + str(i) + FILE_EXT): i=i+1\n basename = basename + \"-\" + str(i)\n return basename + FILE_EXT\n def getCmd(self, options):\n #return command to create RDM as string[]\n vmlfile = VMLPATH + self.getDeviceUID()\n # removed, fails always in MacOS test env: assert os.path.exists(vmlfile)\n return [\"vmkfstools\",TYPE_MAP[options.dtype], vmlfile, self.getRDMFile(), \"-a\", options.adapter]\n\ndef getDiskInfo(filename):\n tree = parse(filename)\n luns = tree.findall(\"all-luns/disk-lun\")\n disks = []\n for lun in luns:\n d = dict()\n for v in lun.find(\"lun\").getchildren():\n if v.tag == \"value\":\n d[v.attrib['name'].replace(\"-\",\"\")] = v.text\n disks.append(DiskInfo(lun,d))\n \n chdir = None\n allvmfs = tree.findall(\"vmfs-filesystems/vm-filesystem\")\n if len(allvmfs) > 0:\n chdir = getValueFor(allvmfs[0],\"console-path\")\n return (chdir,disks)\n\ndef main():\n usage = \"usage: %prog [options]\\n Create raw device mapping for (S)ATA disks. \\nExample:\\n cd /vmfs/volumes/datastore1/\\n vmksatardm.py\"\n parser = OptionParser(usage)\n parser.add_option(\"-f\", \"--file\", dest=\"filename\",\n help=\"read storage config from FILENAME instead of using 'esxcfg-info -s -F xml', used mainly for testing\")\n parser.add_option(\"-q\", \"--quiet\", action=\"store_true\", dest=\"quiet\", default=False,\n help=\"Run quiet, do not show information. Implies -all\")\n parser.add_option(\"-n\", \"--noexec\", dest=\"noexec\", action=\"store_true\",\n help=\"show only commands, do not execute\")\n parser.add_option(\"-l\", \"--all\", dest=\"all\", action=\"store_true\",\n help=\"create mapping for all disks without asking\")\n parser.add_option(\"-a\", \"--adapter\", dest=\"adapter\", default=\"lsilogic\",\n help=\"adapter type: buslogic|lsilogic|ide [default: %default]\")\n parser.add_option(\"-t\", \"--type\", dest=\"dtype\", default=\"physical\", choices=['physical', 'virtual'], type=\"choice\",\n help=\"type of RDM: virtual|physical [default: %default] \")\n parser.add_option(\"-c\", \"--nochdir\", dest=\"nochdir\", action=\"store_true\",\n help=\"do not change directory to <first vmfs>/RDMs. If you specify this, execute command in correct VMFS folder. \")\n (options, args) = parser.parse_args()\n if len(args) != 0:\n parser.error(\"no argument allowed\")\n assert options.dtype in TYPE_MAP\n if options.quiet:\n options.all = True\n\n ''' Reading configuration'''\n filename = \"\"\n if options.filename:\n if not options.quiet: print \"reading from file %s...\" % options.filename\n filename = options.filename\n else:\n if not options.quiet: print \"reading from file 'esxcfg-info -s'...\"\n if not os.path.exists(\"/sbin/esxcfg-info\"):\n parser.error(\"Cannot find executable '/sbin/esxcfg-info', do you run on ESXi?\")\n content = Popen([\"esxcfg-info\", \"-s\", \"-F\", \"xml\"], stdout=PIPE).communicate()[0]\n filename = StringIO.StringIO(content)\n (chdir,disks) = getDiskInfo(filename)\n if not options.nochdir and chdir == None:\n parser.error(\"Cannot find a VMFS file system for RDM files\")\n if not options.nochdir and not options.quiet:\n print \"RDM folder: \" + chdir + \"/\" + RDM_DIR\n\n ''' Show possible disks (ataDisks)'''\n allAtaDisks = [d for d in disks if d.getpreferredpathuid().startswith(\"ide\") or d.getpreferredpathuid().startswith(\"sata\")]\n ataDisks = [d for d in allAtaDisks if d.getpartitiontypes().count(\"251\") == 0]\n if not options.quiet:\n print \"Found %d relevant ATA disks, not relevant:\\n %d other disks,\\n %d ATA disks with VMFS partition\" % (\n len(ataDisks), len(disks)-len(allAtaDisks), len(allAtaDisks)-len(ataDisks))\n for i in range(0,len(ataDisks)):\n disk = ataDisks[i]\n print \"%d) %s -> \" % (i+1, disk.getRDMFile())\n print \" \" + disk.getDeviceUID()\n\n ''' Ask for to-be mapped disks (rdmDisks)''' \n rdmDisks = []\n if options.all:\n rdmDisks = ataDisks \n elif ataDisks != []:\n inputList = [] # list of int's\n error = \"dummy\"\n while error:\n input = raw_input(\"Create Raw Device Mapping for which disks? [1..%d,all,none]\" % len(ataDisks))\n (error,inputList) = stringToIntList(input, len(ataDisks))\n if error: print \"Wrong input, please repeat (%s)\" % error\n rdmDisks = [ataDisks[i-1] for i in inputList]\n \n '''execute commands for disks'''\n if rdmDisks != []:\n if not options.nochdir:\n # optionally create and cd to $chdir/RDMs\n assert os.path.exists(chdir) # the filesystem discovered must exists\n rdmpath = chdir + \"/\" + RDM_DIR\n if not os.path.exists(rdmpath):\n executeCmd([\"mkdir\", rdmpath], options.quiet, options.noexec)\n executeCmd([\"cd\", rdmpath], options.quiet, options.noexec)\n for d in rdmDisks:\n executeCmd( d.getCmd(options), options.quiet, options.noexec)\n exit(0)\n\nif __name__ == \"__main__\":\n main()\n \n\n \n"},{"alpha_fraction":0.545488715171814,"alphanum_fraction":0.6323308348655701,"avg_line_length":37.565216064453125,"blob_id":"4f17d163af8c8c4a8b3d16cdf6a6a0d44ba54d21","content_id":"4334bb729f958bf3fa2b74fdf47027ea6e510e1d","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":2660,"license_type":"no_license","max_line_length":151,"num_lines":69,"path":"/SataRdm/test/testvmksatardm.py","repo_name":"vaillant/SataRDM","src_encoding":"UTF-8","text":"'''\nCreated on Jul 30, 2011\n\n@author: vaillant\n'''\nimport unittest\nimport vmksatardm\n\nclass Test(unittest.TestCase):\n\n def testGetDiskInfo(self):\n (chdir, disks) = vmksatardm.getDiskInfo(\"storage-1ide.xml\")\n self.assertEquals(chdir, \"/vmfs/volumes/4e3144a9-545ea006-7f1c-000c292e315e\")\n self.assertEqual(len(disks), 5)\n self.assertEqual(disks[0].name,\"mpx.vmhba1:C0:T2:L0\")\n self.assertEqual(disks[0].vendor,\"VMware, \")\n self.assertEqual(disks[0].size,\"4294967296\")\n self.assertEqual(disks[0].getpreferredpathuid(), \"pscsi.vmhba1-pscsi.0:2-mpx.vmhba1:C0:T2:L0\")\n self.assertEqual(disks[0].getpartitiontypes(), [\"0\"])\n \n self.assertEqual(disks[2].getpartitiontypes(), [\"0\", \"5\", \"6\", \"251\", \"4\", \"6\", \"6\", \"252\", \"6\"])\n \n self.assertEqual(disks[3].name, \"t10.ATA_____VMware_Virtual_IDE_Hard_Drive___________00000000000000000001\")\n self.assertEqual(disks[3].size, \"6442450944\")\n self.assertEqual(disks[3].getpreferredpathuid(), \"ide.vmhba0-ide.0:0-t10.ATA_____VMware_Virtual_IDE_Hard_Drive___________00000000000000000001\")\n self.assertEqual(disks[3].getpartitiontypes(), [\"0\"])\n self.assertEqual(disks[3].getpartitiontypes().count(\"251\"), 0)\n self.assertEqual(disks[3].getDeviceUID(), \"vml.01000000003030303030303030303030303030303030303031564d77617265\")\n \n def testStringToIntList(self):\n\n\n (error, list) = vmksatardm.stringToIntList(\"a\",1)\n self.assertNotEqual(error, None)\n \n (error, list) = vmksatardm.stringToIntList(\"0\",1)\n self.assertNotEqual(error, None)\n\n (error, list) = vmksatardm.stringToIntList(\"1,2,3\",2)\n self.assertNotEqual(error, None)\n\n (error, list) = vmksatardm.stringToIntList(\"\",1)\n self.assertEqual(error, None)\n self.assertEqual(list, [])\n \n (error, list) = vmksatardm.stringToIntList(\"none\",1)\n self.assertEqual(error, None)\n self.assertEqual(list, [])\n \n (error, list) = vmksatardm.stringToIntList(\"all\",1)\n self.assertEqual(error, None)\n self.assertEqual(list, [1])\n\n (error, list) = vmksatardm.stringToIntList(\"all\",4)\n self.assertEqual(error, None)\n self.assertEqual(list, [1,2,3,4])\n\n (error, list) = vmksatardm.stringToIntList(\"1,2,3,4\",4)\n self.assertEqual(error, None)\n self.assertEqual(list, [1,2,3,4])\n\n (error, list) = vmksatardm.stringToIntList(\"1,4\",4)\n self.assertEqual(error, None)\n self.assertEqual(list, [1,4])\n\n\nif __name__ == \"__main__\":\n #import sys;sys.argv = ['', 'Test.testGetDiskInfo']\n unittest.main()"}],"string":"[\n {\n \"alpha_fraction\": 0.5822513103485107,\n \"alphanum_fraction\": 0.5899940729141235,\n \"avg_line_length\": 42.19587707519531,\n \"blob_id\": \"e80564d7d3761958fd24f61a865a3bfa7ea1e098\",\n \"content_id\": \"26cfa755eec34b15c604ad9189687073c007a8f8\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 8395,\n \"license_type\": \"no_license\",\n \"max_line_length\": 146,\n \"num_lines\": 194,\n \"path\": \"/SataRdm/src/vmksatardm.py\",\n \"repo_name\": \"vaillant/SataRDM\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#!/usr/bin/python\\n'''\\nCreated on Jul 30, 2011\\n\\n@author: Stefan Vaillant\\nCopyright Stefan Vaillant, 2011-2012\\n\\n'''\\n\\nfrom xml.etree.ElementTree import parse\\nfrom optparse import OptionParser\\nfrom subprocess import Popen, PIPE\\nimport exceptions\\nimport os\\nimport StringIO\\n\\nRDM_DIR = \\\"RDMs\\\" # in which folder to create the RDMs\\nFILE_EXT = \\\".vmdk\\\"\\nTYPE_MAP = { \\\"physical\\\": \\\"-z\\\", \\\"virtual\\\": \\\"-r\\\"} # maps options to vmkfstools option\\nGIBIBYTES = 1024 * 1024 * 1024\\nVMLPATH = \\\"/vmfs/devices/disks/\\\"\\n\\ndef getValueFor(element, s):\\n ''' return v, where <value name=x>v</value> and x==s'''\\n result = [ v.text for v in element.getchildren() if v.tag == \\\"value\\\" and v.attrib['name'] == s]\\n assert len(result) == 1, \\\"expecting element with <value name='%s'> under %s element\\\" % (s, element.tag)\\n return result[0]\\n\\ndef stringToIntList(str,maximum):\\n # return (error, [int])\\n # i.e. (None, [1,2]) = stringToIntList(\\\"1,2\\\", 2)\\n error = None\\n result = []\\n if str==\\\"all\\\":\\n result = range(1,maximum+1)\\n elif str==\\\"none\\\" or str==\\\"\\\":\\n result = []\\n else:\\n try:\\n result = [int(s) for s in str.split(\\\",\\\") ]\\n for r in result:\\n if not r in range(1,maximum+1):\\n error = \\\"value '%d' out of range (1..%d)\\\" % (r,maximum)\\n except exceptions.ValueError, e:\\n error = \\\"%s\\\" % (e)\\n return (error,result)\\n\\ndef executeCmd(strs, noprint, noexec):\\n result = \\\"\\\"\\n if not noprint:\\n print \\\" \\\".join(strs)\\n if not noexec:\\n if strs[0] == \\\"cd\\\":\\n os.chdir(strs[1])\\n elif strs[0] == \\\"mkdir\\\":\\n os.mkdir(strs[1])\\n else:\\n result = Popen(strs)\\n return result \\n\\nclass DiskInfo(object):\\n def __init__(self,root,dict):\\n self.__dict__.update(dict)\\n self.root = root\\n def getpreferredpathuid(self):\\n e = self.root.find(\\\"lun/nmp-device-configuration/fixed-path-selection-policy\\\")\\n# result = [ v.text for v in e.iter(\\\"value\\\") if v.attrib['name'] == \\\"preferred-path-uid\\\" ]\\n# assert len(result) == 1, \\\"expecting element with <value name='preferred-path-uid'> under <lun> element\\\"\\n return getValueFor(e, \\\"preferred-path-uid\\\")\\n def getpartitiontypes(self):\\n parts = self.root.findall(\\\"partitions/disk-lun-partition\\\")\\n result = [ getValueFor(p, \\\"partition-type\\\") for p in parts ]\\n return result\\n def getDeviceUID(self):\\n uids = self.root.findall(\\\"lun/device-uids/device-uid\\\")\\n result = [ getValueFor(p, \\\"uid\\\") for p in uids if getValueFor(p, \\\"uid\\\").startswith(\\\"vml.\\\")]\\n assert len(result) > 0, \\\"The device must have one UID starting with 'vml.'\\\"\\n return result[0]\\n def getRDMFile(self):\\n def convert(str):\\n return str.replace(\\\" \\\", \\\"\\\")\\n def convert2(str):\\n return str.replace(\\\" \\\", \\\"-\\\",1).replace(\\\" \\\",\\\"\\\")\\n def serialnumber():\\n return self.devfspath.split(\\\"_\\\")[-1]\\n basename = \\\"%s-%s-%dGB\\\" % (convert2(self.model), serialnumber(), long(self.size) / GIBIBYTES)\\n if os.path.exists(basename + FILE_EXT):\\n i = 0\\n while os.path.exists(basename + \\\"-\\\" + str(i) + FILE_EXT): i=i+1\\n basename = basename + \\\"-\\\" + str(i)\\n return basename + FILE_EXT\\n def getCmd(self, options):\\n #return command to create RDM as string[]\\n vmlfile = VMLPATH + self.getDeviceUID()\\n # removed, fails always in MacOS test env: assert os.path.exists(vmlfile)\\n return [\\\"vmkfstools\\\",TYPE_MAP[options.dtype], vmlfile, self.getRDMFile(), \\\"-a\\\", options.adapter]\\n\\ndef getDiskInfo(filename):\\n tree = parse(filename)\\n luns = tree.findall(\\\"all-luns/disk-lun\\\")\\n disks = []\\n for lun in luns:\\n d = dict()\\n for v in lun.find(\\\"lun\\\").getchildren():\\n if v.tag == \\\"value\\\":\\n d[v.attrib['name'].replace(\\\"-\\\",\\\"\\\")] = v.text\\n disks.append(DiskInfo(lun,d))\\n \\n chdir = None\\n allvmfs = tree.findall(\\\"vmfs-filesystems/vm-filesystem\\\")\\n if len(allvmfs) > 0:\\n chdir = getValueFor(allvmfs[0],\\\"console-path\\\")\\n return (chdir,disks)\\n\\ndef main():\\n usage = \\\"usage: %prog [options]\\\\n Create raw device mapping for (S)ATA disks. \\\\nExample:\\\\n cd /vmfs/volumes/datastore1/\\\\n vmksatardm.py\\\"\\n parser = OptionParser(usage)\\n parser.add_option(\\\"-f\\\", \\\"--file\\\", dest=\\\"filename\\\",\\n help=\\\"read storage config from FILENAME instead of using 'esxcfg-info -s -F xml', used mainly for testing\\\")\\n parser.add_option(\\\"-q\\\", \\\"--quiet\\\", action=\\\"store_true\\\", dest=\\\"quiet\\\", default=False,\\n help=\\\"Run quiet, do not show information. Implies -all\\\")\\n parser.add_option(\\\"-n\\\", \\\"--noexec\\\", dest=\\\"noexec\\\", action=\\\"store_true\\\",\\n help=\\\"show only commands, do not execute\\\")\\n parser.add_option(\\\"-l\\\", \\\"--all\\\", dest=\\\"all\\\", action=\\\"store_true\\\",\\n help=\\\"create mapping for all disks without asking\\\")\\n parser.add_option(\\\"-a\\\", \\\"--adapter\\\", dest=\\\"adapter\\\", default=\\\"lsilogic\\\",\\n help=\\\"adapter type: buslogic|lsilogic|ide [default: %default]\\\")\\n parser.add_option(\\\"-t\\\", \\\"--type\\\", dest=\\\"dtype\\\", default=\\\"physical\\\", choices=['physical', 'virtual'], type=\\\"choice\\\",\\n help=\\\"type of RDM: virtual|physical [default: %default] \\\")\\n parser.add_option(\\\"-c\\\", \\\"--nochdir\\\", dest=\\\"nochdir\\\", action=\\\"store_true\\\",\\n help=\\\"do not change directory to <first vmfs>/RDMs. If you specify this, execute command in correct VMFS folder. \\\")\\n (options, args) = parser.parse_args()\\n if len(args) != 0:\\n parser.error(\\\"no argument allowed\\\")\\n assert options.dtype in TYPE_MAP\\n if options.quiet:\\n options.all = True\\n\\n ''' Reading configuration'''\\n filename = \\\"\\\"\\n if options.filename:\\n if not options.quiet: print \\\"reading from file %s...\\\" % options.filename\\n filename = options.filename\\n else:\\n if not options.quiet: print \\\"reading from file 'esxcfg-info -s'...\\\"\\n if not os.path.exists(\\\"/sbin/esxcfg-info\\\"):\\n parser.error(\\\"Cannot find executable '/sbin/esxcfg-info', do you run on ESXi?\\\")\\n content = Popen([\\\"esxcfg-info\\\", \\\"-s\\\", \\\"-F\\\", \\\"xml\\\"], stdout=PIPE).communicate()[0]\\n filename = StringIO.StringIO(content)\\n (chdir,disks) = getDiskInfo(filename)\\n if not options.nochdir and chdir == None:\\n parser.error(\\\"Cannot find a VMFS file system for RDM files\\\")\\n if not options.nochdir and not options.quiet:\\n print \\\"RDM folder: \\\" + chdir + \\\"/\\\" + RDM_DIR\\n\\n ''' Show possible disks (ataDisks)'''\\n allAtaDisks = [d for d in disks if d.getpreferredpathuid().startswith(\\\"ide\\\") or d.getpreferredpathuid().startswith(\\\"sata\\\")]\\n ataDisks = [d for d in allAtaDisks if d.getpartitiontypes().count(\\\"251\\\") == 0]\\n if not options.quiet:\\n print \\\"Found %d relevant ATA disks, not relevant:\\\\n %d other disks,\\\\n %d ATA disks with VMFS partition\\\" % (\\n len(ataDisks), len(disks)-len(allAtaDisks), len(allAtaDisks)-len(ataDisks))\\n for i in range(0,len(ataDisks)):\\n disk = ataDisks[i]\\n print \\\"%d) %s -> \\\" % (i+1, disk.getRDMFile())\\n print \\\" \\\" + disk.getDeviceUID()\\n\\n ''' Ask for to-be mapped disks (rdmDisks)''' \\n rdmDisks = []\\n if options.all:\\n rdmDisks = ataDisks \\n elif ataDisks != []:\\n inputList = [] # list of int's\\n error = \\\"dummy\\\"\\n while error:\\n input = raw_input(\\\"Create Raw Device Mapping for which disks? [1..%d,all,none]\\\" % len(ataDisks))\\n (error,inputList) = stringToIntList(input, len(ataDisks))\\n if error: print \\\"Wrong input, please repeat (%s)\\\" % error\\n rdmDisks = [ataDisks[i-1] for i in inputList]\\n \\n '''execute commands for disks'''\\n if rdmDisks != []:\\n if not options.nochdir:\\n # optionally create and cd to $chdir/RDMs\\n assert os.path.exists(chdir) # the filesystem discovered must exists\\n rdmpath = chdir + \\\"/\\\" + RDM_DIR\\n if not os.path.exists(rdmpath):\\n executeCmd([\\\"mkdir\\\", rdmpath], options.quiet, options.noexec)\\n executeCmd([\\\"cd\\\", rdmpath], options.quiet, options.noexec)\\n for d in rdmDisks:\\n executeCmd( d.getCmd(options), options.quiet, options.noexec)\\n exit(0)\\n\\nif __name__ == \\\"__main__\\\":\\n main()\\n \\n\\n \\n\"\n },\n {\n \"alpha_fraction\": 0.545488715171814,\n \"alphanum_fraction\": 0.6323308348655701,\n \"avg_line_length\": 37.565216064453125,\n \"blob_id\": \"4f17d163af8c8c4a8b3d16cdf6a6a0d44ba54d21\",\n \"content_id\": \"4334bb729f958bf3fa2b74fdf47027ea6e510e1d\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 2660,\n \"license_type\": \"no_license\",\n \"max_line_length\": 151,\n \"num_lines\": 69,\n \"path\": \"/SataRdm/test/testvmksatardm.py\",\n \"repo_name\": \"vaillant/SataRDM\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"'''\\nCreated on Jul 30, 2011\\n\\n@author: vaillant\\n'''\\nimport unittest\\nimport vmksatardm\\n\\nclass Test(unittest.TestCase):\\n\\n def testGetDiskInfo(self):\\n (chdir, disks) = vmksatardm.getDiskInfo(\\\"storage-1ide.xml\\\")\\n self.assertEquals(chdir, \\\"/vmfs/volumes/4e3144a9-545ea006-7f1c-000c292e315e\\\")\\n self.assertEqual(len(disks), 5)\\n self.assertEqual(disks[0].name,\\\"mpx.vmhba1:C0:T2:L0\\\")\\n self.assertEqual(disks[0].vendor,\\\"VMware, \\\")\\n self.assertEqual(disks[0].size,\\\"4294967296\\\")\\n self.assertEqual(disks[0].getpreferredpathuid(), \\\"pscsi.vmhba1-pscsi.0:2-mpx.vmhba1:C0:T2:L0\\\")\\n self.assertEqual(disks[0].getpartitiontypes(), [\\\"0\\\"])\\n \\n self.assertEqual(disks[2].getpartitiontypes(), [\\\"0\\\", \\\"5\\\", \\\"6\\\", \\\"251\\\", \\\"4\\\", \\\"6\\\", \\\"6\\\", \\\"252\\\", \\\"6\\\"])\\n \\n self.assertEqual(disks[3].name, \\\"t10.ATA_____VMware_Virtual_IDE_Hard_Drive___________00000000000000000001\\\")\\n self.assertEqual(disks[3].size, \\\"6442450944\\\")\\n self.assertEqual(disks[3].getpreferredpathuid(), \\\"ide.vmhba0-ide.0:0-t10.ATA_____VMware_Virtual_IDE_Hard_Drive___________00000000000000000001\\\")\\n self.assertEqual(disks[3].getpartitiontypes(), [\\\"0\\\"])\\n self.assertEqual(disks[3].getpartitiontypes().count(\\\"251\\\"), 0)\\n self.assertEqual(disks[3].getDeviceUID(), \\\"vml.01000000003030303030303030303030303030303030303031564d77617265\\\")\\n \\n def testStringToIntList(self):\\n\\n\\n (error, list) = vmksatardm.stringToIntList(\\\"a\\\",1)\\n self.assertNotEqual(error, None)\\n \\n (error, list) = vmksatardm.stringToIntList(\\\"0\\\",1)\\n self.assertNotEqual(error, None)\\n\\n (error, list) = vmksatardm.stringToIntList(\\\"1,2,3\\\",2)\\n self.assertNotEqual(error, None)\\n\\n (error, list) = vmksatardm.stringToIntList(\\\"\\\",1)\\n self.assertEqual(error, None)\\n self.assertEqual(list, [])\\n \\n (error, list) = vmksatardm.stringToIntList(\\\"none\\\",1)\\n self.assertEqual(error, None)\\n self.assertEqual(list, [])\\n \\n (error, list) = vmksatardm.stringToIntList(\\\"all\\\",1)\\n self.assertEqual(error, None)\\n self.assertEqual(list, [1])\\n\\n (error, list) = vmksatardm.stringToIntList(\\\"all\\\",4)\\n self.assertEqual(error, None)\\n self.assertEqual(list, [1,2,3,4])\\n\\n (error, list) = vmksatardm.stringToIntList(\\\"1,2,3,4\\\",4)\\n self.assertEqual(error, None)\\n self.assertEqual(list, [1,2,3,4])\\n\\n (error, list) = vmksatardm.stringToIntList(\\\"1,4\\\",4)\\n self.assertEqual(error, None)\\n self.assertEqual(list, [1,4])\\n\\n\\nif __name__ == \\\"__main__\\\":\\n #import sys;sys.argv = ['', 'Test.testGetDiskInfo']\\n unittest.main()\"\n }\n]"},"num_files":{"kind":"number","value":2,"string":"2"}}},{"rowIdx":2044,"cells":{"repo_name":{"kind":"string","value":"djkemmet/Central-Inventory-Agent"},"repo_url":{"kind":"string","value":"https://github.com/djkemmet/Central-Inventory-Agent"},"snapshot_id":{"kind":"string","value":"58bc52cf47fa0b1eb0ecbbfacaf51993c40a53df"},"revision_id":{"kind":"string","value":"9a35fa31dd92ffd316bad79ea798346ecad59beb"},"directory_id":{"kind":"string","value":"b53b0550d980b3d852406d43b6c19d694e125294"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"string","value":"2022-07-31T12:56:23.617835"},"revision_date":{"kind":"string","value":"2020-05-23T20:01:16"},"committer_date":{"kind":"string","value":"2020-05-23T20:01:16"},"github_id":{"kind":"number","value":266409208,"string":"266,409,208"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.7461773753166199,"alphanum_fraction":0.7635066509246826,"avg_line_length":48.099998474121094,"blob_id":"61253f5cf0371e46b9f7bac4b7ab8947b4097002","content_id":"657a707a9d40839053292ab0bb8ca0d77dd293b4","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":981,"license_type":"no_license","max_line_length":119,"num_lines":20,"path":"/readme.md","repo_name":"djkemmet/Central-Inventory-Agent","src_encoding":"UTF-8","text":"# Custom Inventory Agent\nThis custom inventory agent was built to collect the necessary information to migrate a device from airwave and other \nmanagment tools into aruba central. Given the complexity of and lack of documentation for SNMP in aruba products, this \ntool was written to collect only the necessary information. However, future iterations of this tool will likely accept \na list of OIDs and process them into a CSV simliar to what this tool currently puts out.\n\n## What does this tool collect?\nThis tool collects the following information and stores them as a string to \na CSV file for further consumption\n1. Hostname\n * If a system did not have it's host name defined, This ool acknowledges the\n default hostname and makes the user aware of this issue in the inventory\n2. Controller Model\n3. Software Version\n * Supported Platforms include:\n * ArubaOS 7.4.0.1\n * ArubaOS 7.4.1.1\n * ArubaOS 8.1.0.1\n4. System Serial\n5. System MAC address"},{"alpha_fraction":0.5347582101821899,"alphanum_fraction":0.557498574256897,"avg_line_length":40.48358154296875,"blob_id":"515d886ea309411cee046a1cf1dd178d500e7ed3","content_id":"b77499751c406654c01dc3680cbcf29d1544a53d","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":13896,"license_type":"no_license","max_line_length":118,"num_lines":335,"path":"/main.py","repo_name":"djkemmet/Central-Inventory-Agent","src_encoding":"UTF-8","text":"#\n# AUTHOR: DJ Kemmet, dj@ziosk.com\n# DATE: 8/14/17\n# REQUIREMENTS: Python 3.4 or greater, Python Standard Library.\n# PURPOSE: The Purpose of this script is to collect the necessary data-points required to import a site into Central.\n# CURRENT VERSION: Milestone 0.5\n#\n\nimport csv\nimport logging\nimport os\n\n\n# Set up global variables\nlogging. basicConfig(filename='error.log', level=logging.WARNING)\nerrors_to_csv = ['Site Marked for retry', 'Site marked for retry', 'Site marked for retry']\n\n\n# Make sure the inventory file where the results go exists, if not, create it and verify it.\ndef verify_supporting_files():\n\n # Check for and create inventory.csv if necessary\n if os.path.lexists('inventory.csv'):\n print('Inventory Manifest Found. ')\n else:\n with open('inventory.csv', 'a+') as results_file:\n results_file.close()\n print('Inventory Manifest created.')\n\n # Check for and create error.log if necessary.\n if os.path.lexists('error.log'):\n print('Error Log Found.')\n else:\n with open('error.log', 'a+') as log_file:\n log_file.close()\n print('Error Log Created')\n\n # Check for and create retries.csv if necessary.\n if os.path.lexists('retries.csv'):\n print(\"Previous retry queue was discovered. Something should be done about that.\")\n else:\n with open('retries.csv', 'a+') as retry_file:\n retry_file.close()\n print('Retry log created.')\n\n # Check for and create Completed directory if necessary.\n if os.path.lexists('Completed/'):\n pass\n else:\n os.system('mkdir Completed')\n\n\n# Inventories the Controller at a given store.\ndef inventory_controller(site_ip):\n\n print(\"inventorying site: \" + site_ip)\n try:\n # Facilitates Gathering the Hostname, Software Version, and Controller Model.\n simfile_system = os.popen('snmpwalk -v 2c -c nhB7S@wX ' + site_ip + ' system')\n simfile_system_lines = simfile_system.readlines()\n\n # For each line of output from the host device, Check for the system string\n for line in simfile_system_lines:\n # Gather Model and Software Version.\n if \"sysDescr\" in line:\n system_string = line\n pass1 = str.split(system_string, '=')\n pass2 = str.split(pass1[1], ',')\n pass3 = str.split(pass2[0], ':')\n controller = ((pass3[2]).replace(\")\", \"\")).strip()\n software_root_version = (pass2[1]).strip()\n\n # Gather Hostname.\n if \"sysName\" in line:\n if 'Aruba' in line:\n print('This host was not named.')\n hostname = 'System Not Named: ' + site_ip\n break\n else:\n dirty_sys_line = line\n pass1 = str.split(dirty_sys_line, '=')\n pass2 = str.split(pass1[1], ':')\n hostname = ((pass2[1]).replace(\"\\n\", '')).strip()\n break\n\n # Facilitates Gathering the System Serial Number.\n software_root_version_split = str.split(software_root_version, \" \")\n software_string = software_root_version_split[1].strip()\n if \"7.4.0.1\" in software_string:\n serial_request = os.popen('snmpwalk -v 2c -c nhB7S@wX ' + site_ip + ' .1.3.6.1.2.1.47.1.1.1.1.11.1001')\n for line in serial_request.readlines():\n if \"STRING\" in line:\n dirty_serial_line = line\n pass1 = str.split(dirty_serial_line, ' ')\n pass2 = pass1[3]\n serial = str.replace(pass2, '\"', '').strip()\n\n if \"7.4.0.4\" in software_string:\n serial_request = os.popen('snmpwalk -v 2c -c nhB7S@wX ' + site_ip + ' .1.3.6.1.2.1.47.1.1.1.1.11.1001')\n for line in serial_request.readlines():\n if \"STRING\" in line:\n dirty_serial_line = line\n pass1 = str.split(dirty_serial_line, ' ')\n pass2 = pass1[3]\n serial = str.replace(pass2, '\"', '').strip()\n\n elif \"7.4.1.1\" in software_string:\n serial_request = os.popen('snmpwalk -v 2c -c nhB7S@wX ' + site_ip + ' .1.3.6.1.2.1.47.1.1.1.1.11.1001')\n for line in serial_request.readlines():\n if \"STRING\" in line:\n dirty_serial_line = line\n pass1 = str.split(dirty_serial_line, ' ')\n pass2 = pass1[3]\n serial = str.replace(pass2, '\"', '').strip()\n\n elif \"8.1.0.1\" in software_string:\n serial_request = os.popen('snmpwalk -v 2c -c nhB7S@wX ' + site_ip + ' .1.3.6.1.4.1.14823.2.2.1.1.1.12')\n for line in serial_request.readlines():\n if \"STRING\" in line:\n dirty_serial_line = line\n pass1 = str.split(dirty_serial_line, ' ')\n pass2 = pass1[3]\n pass3 = str.replace(pass2, '\"', '').strip()\n serial = pass3\n\n MAC_request = os.popen('snmpwalk -v 2c -c nhB7S@wX ' + site_ip + ' .1.3.6.1.4.1.14823.2.2.1.2.1.7')\n for line in MAC_request.readlines():\n if \"STRING\" in line:\n dirty_mac_line = line\n pass1 = str.split(dirty_mac_line, '=')\n pass2 = pass1[1]\n pass2 = str.split(pass2, ':')\n pass3 = str.strip(pass2[1], ' ')\n MAC = str.strip(str.strip(pass3, '\\n'), ' ')\n\n data_gathered = [hostname, controller, software_root_version, serial, MAC]\n with open('inventory.csv', \"a\", newline=\"\") as inventory_file:\n file_writer = csv.writer(inventory_file, quoting=csv.QUOTE_ALL)\n file_writer.writerow(data_gathered)\n inventory_file.close()\n\n print(hostname + \" has been inventoried.\")\n\n # Define Exceptions for the code above.\n except IndexError:\n logging.info(hostname + \" Could not collect requested SNMP Objects.\")\n with open('inventory.csv', \"a\", newline=\"\") as inventory_file:\n file_writer = csv.writer(inventory_file, quoting=csv.QUOTE_ALL)\n file_writer.write(errors_to_csv)\n inventory_file.close()\n logging.debug(site_ip + ' could not be reliably inventoried')\n inventory_file.close()\n exit()\n\n with open('retries.csv', \"a\", newline=\"\") as retries_file:\n retry_writer = csv.writer(retries_file, quoting=csv.QUOTE_ALL)\n retry_site = [site_ip]\n retry_writer.writerow(retry_site)\n retries_file.close()\n\n except TimeoutError:\n logging.info(hostname + \"is either unavailable or removed from service.\")\n with open('inventory.csv', \"a\", newline=\"\") as inventory_file:\n file_writer = csv.writer(inventory_file, quoting=csv.QUOTE_ALL)\n file_writer.write(errors_to_csv)\n inventory_file.close()\n logging.debug(site_ip + ' site did not respond to snmp query')\n with open('retries.csv', \"a\", newline=\"\") as retries_file:\n retry_writer = csv.writer(retries_file, quoting=csv.QUOTE_ALL)\n retry_site = [site_ip]\n retry_writer.writerow(retry_site)\n retries_file.close()\n\n except KeyboardInterrupt:\n logging.debug('Inventory interrupted by Keystroke. Removing Inventory file.')\n # os.system('rm -rf inventory.csv')\n exit()\n\n except UnboundLocalError:\n print(\"General Exception has occurred.\")\n with open('inventory.csv', \"a\", newline=\"\") as inventory_file:\n print(\"Inventory Stopped By User Key Stroke. Deleting Inventory Manifest.\")\n file_writer = csv.writer(inventory_file, quoting=csv.QUOTE_ALL)\n file_writer.writerow(errors_to_csv)\n inventory_file.close()\n logging.debug(site_ip + ' encountered a general exception occurred.')\n with open('retries.csv', \"a\", newline=\"\") as retries_file:\n retry_writer = csv.writer(retries_file, quoting=csv.QUOTE_ALL)\n retry_site =[site_ip]\n retry_writer.writerow(retry_site)\n retries_file.close()\n\n\n# Inventories the AP Cluster at a given store.\ndef inventory_APs(site_ip):\n #\n # CLUSTER SOFTWARE VERSION. Results in a single string\n #\n cluster_software_version = os.popen('snmpwalk -v 2c -c nhB7S@wX ' + site_ip + ' .1.3.6.1.4.1.14823.2.3.3.1.1.4.0')\n results = cluster_software_version.readlines()\n for line in results:\n pass1 = line.split(\"STRING:\")\n pass2 = pass1[1].strip()\n final_cluster_software_version = str.replace(pass2, '\"', \"\")\n\n\n #\n # CLUSTER NAME. Results in a single string\n #\n cluster_name = os.popen('snmpwalk -v 2c -c nhB7S@wX ' + site_ip + ' .1.3.6.1.4.1.14823.2.3.3.1.1.2.0')\n for line in cluster_name.readlines():\n pass1 = line.split(\"STRING:\")\n pass2 = pass1[1].strip()\n final_cluster_name = pass2.replace('\"', '')\n\n #\n # MEMBER AP MAC ADDRESSES. returns a list of mac addresses, one of each AP in the cluster.\n #\n membermac_list = []\n member_mac_addresses = os.popen('snmpwalk -v 2c -c nhB7S@wX ' + site_ip + ' .1.3.6.1.4.1.14823.2.3.3.1.2.1.1.1')\n for line in member_mac_addresses.readlines():\n pass1 = line.split(\"STRING:\")\n pass2 = pass1[1].strip()\n final_member_mac_address = pass2.replace(\" \", \"\")\n membermac_list.append(final_member_mac_address)\n\n #\n # MEMBER AP SERIAL NUMBERS. returns a list of serials, one of each AP in the cluster.\n #\n memberserial_list = []\n member_serial_numbers = os.popen('snmpwalk -v 2c -c nhB7S@wX ' + site_ip + ' .1.3.6.1.4.1.14823.2.3.3.1.2.1.1.4')\n for line in member_serial_numbers.readlines():\n pass1 = line.split(\"STRING: \")\n pass2 = pass1[1].replace('\"', '')\n final_member_serial_number = pass2.strip()\n memberserial_list.append(final_member_serial_number)\n\n #\n # MEMBER AP MODEL NUMBERS. returns a list of model numbers, one of each AP in the cluster.\n #\n membermodel_list = []\n member_model_numbers = os.popen('snmpwalk -v 2c -c nhB7S@wX ' + site_ip + ' .1.3.6.1.4.1.14823.2.3.3.1.2.1.1.6')\n for line in member_model_numbers.readlines():\n pass1 = line.split(\"STRING:\")\n pass2 = pass1[1].replace('\"', '')\n final_member_model_number = pass2.strip()\n membermodel_list.append(final_member_model_number)\n\n\n # Get the length of each list:\n if len(membermac_list) == len(memberserial_list):\n if len(membermac_list) == len(membermodel_list):\n for entry in range(0, len(membermac_list)):\n name = final_cluster_name\n software = final_cluster_software_version\n model = membermac_list[entry]\n mac = membermac_list[entry]\n serial = memberserial_list[entry]\n data_gathered = [name, software, model, mac, serial]\n with open('inventory.csv', \"a\", newline=\"\") as inventory_file:\n file_writer = csv.writer(inventory_file, quoting=csv.QUOTE_ALL)\n file_writer.writerow(data_gathered)\n inventory_file.close()\n print(\"wrote \"+ name + \" \" + software + \" \" + model + \" \" + mac + \" \" + serial + \" \" + serial)\n inventory_file.close()\n else:\n print(\"Cannot reliably inventory \" + cluster_name + \". It appears that one or more APs did not respond to \"\n \"an SNMP query \")\n\n\n# Converts a Site Address to a Controller address and returns it to the calling function\ndef check_ip(site_ip):\n site_ip = (str.replace(site_ip, '\"', ''))\n new_ip = ''\n if \"\\n\" in site_ip:\n site_ip = site_ip.replace('\\n', \"\")\n site_octets = str(site_ip).split(\".\")\n if site_octets[3] is not \"1\":\n site_octets[3] = \"1\"\n for octet in site_octets:\n if octet is not \"1\":\n new_ip += octet + \".\"\n else:\n new_ip += octet\n site_ip = new_ip\n else:\n site_ip = site_ip\n return site_ip\n\n\n# Converts a Site Address to a VC address and returns it to the calling function\ndef make_ap_ip(site_ip):\n site_ip = (str.replace(site_ip, '\"', ''))\n new_ip = ''\n if \"\\n\" in site_ip:\n site_ip = str.replace(site_ip, \"\\n\", '')\n octets = str(site_ip).split(\".\")\n if octets[3] is not \"2\":\n octets[3] = \"2\"\n for octet in octets:\n if octet is not \"2\":\n new_ip += octet + \".\"\n else:\n new_ip += octet\n else:\n new_ip = site_ip\n return new_ip\n\n\n# The Sauce of this tool.\ndef main():\n verify_supporting_files()\n for file in os.listdir('.'):\n if '.csv' in file:\n verify_supporting_files() with open(file, 'r') as list_file:\n reader = list_file.readlines()\n for site in reader:\n inventory_controller(check_ip(site))\n inventory_APs(make_ap_ip(site))\n\n if os.path.lexists('retries.csv') is True:\n with open('retries.csv', 'r') as retries:\n reader = retries.readlines()\n for site in reader:\n inventory_controller(check_ip(site))\n inventory_APs(make_ap_ip(site))\n\n job_name = str(file.split(\".\")[0])\n os.system('mkdir Completed/' + job_name)\n\n # Move inventory.csv, error.log, retries.csv the CSV itself to this directory\n os.system('mv inventory.csv error.log retries.csv ' + job_name + '.csv' + ' Completed/' + job_name)\n\n\nmain()"}],"string":"[\n {\n \"alpha_fraction\": 0.7461773753166199,\n \"alphanum_fraction\": 0.7635066509246826,\n \"avg_line_length\": 48.099998474121094,\n \"blob_id\": \"61253f5cf0371e46b9f7bac4b7ab8947b4097002\",\n \"content_id\": \"657a707a9d40839053292ab0bb8ca0d77dd293b4\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 981,\n \"license_type\": \"no_license\",\n \"max_line_length\": 119,\n \"num_lines\": 20,\n \"path\": \"/readme.md\",\n \"repo_name\": \"djkemmet/Central-Inventory-Agent\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# Custom Inventory Agent\\nThis custom inventory agent was built to collect the necessary information to migrate a device from airwave and other \\nmanagment tools into aruba central. Given the complexity of and lack of documentation for SNMP in aruba products, this \\ntool was written to collect only the necessary information. However, future iterations of this tool will likely accept \\na list of OIDs and process them into a CSV simliar to what this tool currently puts out.\\n\\n## What does this tool collect?\\nThis tool collects the following information and stores them as a string to \\na CSV file for further consumption\\n1. Hostname\\n * If a system did not have it's host name defined, This ool acknowledges the\\n default hostname and makes the user aware of this issue in the inventory\\n2. Controller Model\\n3. Software Version\\n * Supported Platforms include:\\n * ArubaOS 7.4.0.1\\n * ArubaOS 7.4.1.1\\n * ArubaOS 8.1.0.1\\n4. System Serial\\n5. System MAC address\"\n },\n {\n \"alpha_fraction\": 0.5347582101821899,\n \"alphanum_fraction\": 0.557498574256897,\n \"avg_line_length\": 40.48358154296875,\n \"blob_id\": \"515d886ea309411cee046a1cf1dd178d500e7ed3\",\n \"content_id\": \"b77499751c406654c01dc3680cbcf29d1544a53d\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 13896,\n \"license_type\": \"no_license\",\n \"max_line_length\": 118,\n \"num_lines\": 335,\n \"path\": \"/main.py\",\n \"repo_name\": \"djkemmet/Central-Inventory-Agent\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#\\n# AUTHOR: DJ Kemmet, dj@ziosk.com\\n# DATE: 8/14/17\\n# REQUIREMENTS: Python 3.4 or greater, Python Standard Library.\\n# PURPOSE: The Purpose of this script is to collect the necessary data-points required to import a site into Central.\\n# CURRENT VERSION: Milestone 0.5\\n#\\n\\nimport csv\\nimport logging\\nimport os\\n\\n\\n# Set up global variables\\nlogging. basicConfig(filename='error.log', level=logging.WARNING)\\nerrors_to_csv = ['Site Marked for retry', 'Site marked for retry', 'Site marked for retry']\\n\\n\\n# Make sure the inventory file where the results go exists, if not, create it and verify it.\\ndef verify_supporting_files():\\n\\n # Check for and create inventory.csv if necessary\\n if os.path.lexists('inventory.csv'):\\n print('Inventory Manifest Found. ')\\n else:\\n with open('inventory.csv', 'a+') as results_file:\\n results_file.close()\\n print('Inventory Manifest created.')\\n\\n # Check for and create error.log if necessary.\\n if os.path.lexists('error.log'):\\n print('Error Log Found.')\\n else:\\n with open('error.log', 'a+') as log_file:\\n log_file.close()\\n print('Error Log Created')\\n\\n # Check for and create retries.csv if necessary.\\n if os.path.lexists('retries.csv'):\\n print(\\\"Previous retry queue was discovered. Something should be done about that.\\\")\\n else:\\n with open('retries.csv', 'a+') as retry_file:\\n retry_file.close()\\n print('Retry log created.')\\n\\n # Check for and create Completed directory if necessary.\\n if os.path.lexists('Completed/'):\\n pass\\n else:\\n os.system('mkdir Completed')\\n\\n\\n# Inventories the Controller at a given store.\\ndef inventory_controller(site_ip):\\n\\n print(\\\"inventorying site: \\\" + site_ip)\\n try:\\n # Facilitates Gathering the Hostname, Software Version, and Controller Model.\\n simfile_system = os.popen('snmpwalk -v 2c -c nhB7S@wX ' + site_ip + ' system')\\n simfile_system_lines = simfile_system.readlines()\\n\\n # For each line of output from the host device, Check for the system string\\n for line in simfile_system_lines:\\n # Gather Model and Software Version.\\n if \\\"sysDescr\\\" in line:\\n system_string = line\\n pass1 = str.split(system_string, '=')\\n pass2 = str.split(pass1[1], ',')\\n pass3 = str.split(pass2[0], ':')\\n controller = ((pass3[2]).replace(\\\")\\\", \\\"\\\")).strip()\\n software_root_version = (pass2[1]).strip()\\n\\n # Gather Hostname.\\n if \\\"sysName\\\" in line:\\n if 'Aruba' in line:\\n print('This host was not named.')\\n hostname = 'System Not Named: ' + site_ip\\n break\\n else:\\n dirty_sys_line = line\\n pass1 = str.split(dirty_sys_line, '=')\\n pass2 = str.split(pass1[1], ':')\\n hostname = ((pass2[1]).replace(\\\"\\\\n\\\", '')).strip()\\n break\\n\\n # Facilitates Gathering the System Serial Number.\\n software_root_version_split = str.split(software_root_version, \\\" \\\")\\n software_string = software_root_version_split[1].strip()\\n if \\\"7.4.0.1\\\" in software_string:\\n serial_request = os.popen('snmpwalk -v 2c -c nhB7S@wX ' + site_ip + ' .1.3.6.1.2.1.47.1.1.1.1.11.1001')\\n for line in serial_request.readlines():\\n if \\\"STRING\\\" in line:\\n dirty_serial_line = line\\n pass1 = str.split(dirty_serial_line, ' ')\\n pass2 = pass1[3]\\n serial = str.replace(pass2, '\\\"', '').strip()\\n\\n if \\\"7.4.0.4\\\" in software_string:\\n serial_request = os.popen('snmpwalk -v 2c -c nhB7S@wX ' + site_ip + ' .1.3.6.1.2.1.47.1.1.1.1.11.1001')\\n for line in serial_request.readlines():\\n if \\\"STRING\\\" in line:\\n dirty_serial_line = line\\n pass1 = str.split(dirty_serial_line, ' ')\\n pass2 = pass1[3]\\n serial = str.replace(pass2, '\\\"', '').strip()\\n\\n elif \\\"7.4.1.1\\\" in software_string:\\n serial_request = os.popen('snmpwalk -v 2c -c nhB7S@wX ' + site_ip + ' .1.3.6.1.2.1.47.1.1.1.1.11.1001')\\n for line in serial_request.readlines():\\n if \\\"STRING\\\" in line:\\n dirty_serial_line = line\\n pass1 = str.split(dirty_serial_line, ' ')\\n pass2 = pass1[3]\\n serial = str.replace(pass2, '\\\"', '').strip()\\n\\n elif \\\"8.1.0.1\\\" in software_string:\\n serial_request = os.popen('snmpwalk -v 2c -c nhB7S@wX ' + site_ip + ' .1.3.6.1.4.1.14823.2.2.1.1.1.12')\\n for line in serial_request.readlines():\\n if \\\"STRING\\\" in line:\\n dirty_serial_line = line\\n pass1 = str.split(dirty_serial_line, ' ')\\n pass2 = pass1[3]\\n pass3 = str.replace(pass2, '\\\"', '').strip()\\n serial = pass3\\n\\n MAC_request = os.popen('snmpwalk -v 2c -c nhB7S@wX ' + site_ip + ' .1.3.6.1.4.1.14823.2.2.1.2.1.7')\\n for line in MAC_request.readlines():\\n if \\\"STRING\\\" in line:\\n dirty_mac_line = line\\n pass1 = str.split(dirty_mac_line, '=')\\n pass2 = pass1[1]\\n pass2 = str.split(pass2, ':')\\n pass3 = str.strip(pass2[1], ' ')\\n MAC = str.strip(str.strip(pass3, '\\\\n'), ' ')\\n\\n data_gathered = [hostname, controller, software_root_version, serial, MAC]\\n with open('inventory.csv', \\\"a\\\", newline=\\\"\\\") as inventory_file:\\n file_writer = csv.writer(inventory_file, quoting=csv.QUOTE_ALL)\\n file_writer.writerow(data_gathered)\\n inventory_file.close()\\n\\n print(hostname + \\\" has been inventoried.\\\")\\n\\n # Define Exceptions for the code above.\\n except IndexError:\\n logging.info(hostname + \\\" Could not collect requested SNMP Objects.\\\")\\n with open('inventory.csv', \\\"a\\\", newline=\\\"\\\") as inventory_file:\\n file_writer = csv.writer(inventory_file, quoting=csv.QUOTE_ALL)\\n file_writer.write(errors_to_csv)\\n inventory_file.close()\\n logging.debug(site_ip + ' could not be reliably inventoried')\\n inventory_file.close()\\n exit()\\n\\n with open('retries.csv', \\\"a\\\", newline=\\\"\\\") as retries_file:\\n retry_writer = csv.writer(retries_file, quoting=csv.QUOTE_ALL)\\n retry_site = [site_ip]\\n retry_writer.writerow(retry_site)\\n retries_file.close()\\n\\n except TimeoutError:\\n logging.info(hostname + \\\"is either unavailable or removed from service.\\\")\\n with open('inventory.csv', \\\"a\\\", newline=\\\"\\\") as inventory_file:\\n file_writer = csv.writer(inventory_file, quoting=csv.QUOTE_ALL)\\n file_writer.write(errors_to_csv)\\n inventory_file.close()\\n logging.debug(site_ip + ' site did not respond to snmp query')\\n with open('retries.csv', \\\"a\\\", newline=\\\"\\\") as retries_file:\\n retry_writer = csv.writer(retries_file, quoting=csv.QUOTE_ALL)\\n retry_site = [site_ip]\\n retry_writer.writerow(retry_site)\\n retries_file.close()\\n\\n except KeyboardInterrupt:\\n logging.debug('Inventory interrupted by Keystroke. Removing Inventory file.')\\n # os.system('rm -rf inventory.csv')\\n exit()\\n\\n except UnboundLocalError:\\n print(\\\"General Exception has occurred.\\\")\\n with open('inventory.csv', \\\"a\\\", newline=\\\"\\\") as inventory_file:\\n print(\\\"Inventory Stopped By User Key Stroke. Deleting Inventory Manifest.\\\")\\n file_writer = csv.writer(inventory_file, quoting=csv.QUOTE_ALL)\\n file_writer.writerow(errors_to_csv)\\n inventory_file.close()\\n logging.debug(site_ip + ' encountered a general exception occurred.')\\n with open('retries.csv', \\\"a\\\", newline=\\\"\\\") as retries_file:\\n retry_writer = csv.writer(retries_file, quoting=csv.QUOTE_ALL)\\n retry_site =[site_ip]\\n retry_writer.writerow(retry_site)\\n retries_file.close()\\n\\n\\n# Inventories the AP Cluster at a given store.\\ndef inventory_APs(site_ip):\\n #\\n # CLUSTER SOFTWARE VERSION. Results in a single string\\n #\\n cluster_software_version = os.popen('snmpwalk -v 2c -c nhB7S@wX ' + site_ip + ' .1.3.6.1.4.1.14823.2.3.3.1.1.4.0')\\n results = cluster_software_version.readlines()\\n for line in results:\\n pass1 = line.split(\\\"STRING:\\\")\\n pass2 = pass1[1].strip()\\n final_cluster_software_version = str.replace(pass2, '\\\"', \\\"\\\")\\n\\n\\n #\\n # CLUSTER NAME. Results in a single string\\n #\\n cluster_name = os.popen('snmpwalk -v 2c -c nhB7S@wX ' + site_ip + ' .1.3.6.1.4.1.14823.2.3.3.1.1.2.0')\\n for line in cluster_name.readlines():\\n pass1 = line.split(\\\"STRING:\\\")\\n pass2 = pass1[1].strip()\\n final_cluster_name = pass2.replace('\\\"', '')\\n\\n #\\n # MEMBER AP MAC ADDRESSES. returns a list of mac addresses, one of each AP in the cluster.\\n #\\n membermac_list = []\\n member_mac_addresses = os.popen('snmpwalk -v 2c -c nhB7S@wX ' + site_ip + ' .1.3.6.1.4.1.14823.2.3.3.1.2.1.1.1')\\n for line in member_mac_addresses.readlines():\\n pass1 = line.split(\\\"STRING:\\\")\\n pass2 = pass1[1].strip()\\n final_member_mac_address = pass2.replace(\\\" \\\", \\\"\\\")\\n membermac_list.append(final_member_mac_address)\\n\\n #\\n # MEMBER AP SERIAL NUMBERS. returns a list of serials, one of each AP in the cluster.\\n #\\n memberserial_list = []\\n member_serial_numbers = os.popen('snmpwalk -v 2c -c nhB7S@wX ' + site_ip + ' .1.3.6.1.4.1.14823.2.3.3.1.2.1.1.4')\\n for line in member_serial_numbers.readlines():\\n pass1 = line.split(\\\"STRING: \\\")\\n pass2 = pass1[1].replace('\\\"', '')\\n final_member_serial_number = pass2.strip()\\n memberserial_list.append(final_member_serial_number)\\n\\n #\\n # MEMBER AP MODEL NUMBERS. returns a list of model numbers, one of each AP in the cluster.\\n #\\n membermodel_list = []\\n member_model_numbers = os.popen('snmpwalk -v 2c -c nhB7S@wX ' + site_ip + ' .1.3.6.1.4.1.14823.2.3.3.1.2.1.1.6')\\n for line in member_model_numbers.readlines():\\n pass1 = line.split(\\\"STRING:\\\")\\n pass2 = pass1[1].replace('\\\"', '')\\n final_member_model_number = pass2.strip()\\n membermodel_list.append(final_member_model_number)\\n\\n\\n # Get the length of each list:\\n if len(membermac_list) == len(memberserial_list):\\n if len(membermac_list) == len(membermodel_list):\\n for entry in range(0, len(membermac_list)):\\n name = final_cluster_name\\n software = final_cluster_software_version\\n model = membermac_list[entry]\\n mac = membermac_list[entry]\\n serial = memberserial_list[entry]\\n data_gathered = [name, software, model, mac, serial]\\n with open('inventory.csv', \\\"a\\\", newline=\\\"\\\") as inventory_file:\\n file_writer = csv.writer(inventory_file, quoting=csv.QUOTE_ALL)\\n file_writer.writerow(data_gathered)\\n inventory_file.close()\\n print(\\\"wrote \\\"+ name + \\\" \\\" + software + \\\" \\\" + model + \\\" \\\" + mac + \\\" \\\" + serial + \\\" \\\" + serial)\\n inventory_file.close()\\n else:\\n print(\\\"Cannot reliably inventory \\\" + cluster_name + \\\". It appears that one or more APs did not respond to \\\"\\n \\\"an SNMP query \\\")\\n\\n\\n# Converts a Site Address to a Controller address and returns it to the calling function\\ndef check_ip(site_ip):\\n site_ip = (str.replace(site_ip, '\\\"', ''))\\n new_ip = ''\\n if \\\"\\\\n\\\" in site_ip:\\n site_ip = site_ip.replace('\\\\n', \\\"\\\")\\n site_octets = str(site_ip).split(\\\".\\\")\\n if site_octets[3] is not \\\"1\\\":\\n site_octets[3] = \\\"1\\\"\\n for octet in site_octets:\\n if octet is not \\\"1\\\":\\n new_ip += octet + \\\".\\\"\\n else:\\n new_ip += octet\\n site_ip = new_ip\\n else:\\n site_ip = site_ip\\n return site_ip\\n\\n\\n# Converts a Site Address to a VC address and returns it to the calling function\\ndef make_ap_ip(site_ip):\\n site_ip = (str.replace(site_ip, '\\\"', ''))\\n new_ip = ''\\n if \\\"\\\\n\\\" in site_ip:\\n site_ip = str.replace(site_ip, \\\"\\\\n\\\", '')\\n octets = str(site_ip).split(\\\".\\\")\\n if octets[3] is not \\\"2\\\":\\n octets[3] = \\\"2\\\"\\n for octet in octets:\\n if octet is not \\\"2\\\":\\n new_ip += octet + \\\".\\\"\\n else:\\n new_ip += octet\\n else:\\n new_ip = site_ip\\n return new_ip\\n\\n\\n# The Sauce of this tool.\\ndef main():\\n verify_supporting_files()\\n for file in os.listdir('.'):\\n if '.csv' in file:\\n verify_supporting_files() with open(file, 'r') as list_file:\\n reader = list_file.readlines()\\n for site in reader:\\n inventory_controller(check_ip(site))\\n inventory_APs(make_ap_ip(site))\\n\\n if os.path.lexists('retries.csv') is True:\\n with open('retries.csv', 'r') as retries:\\n reader = retries.readlines()\\n for site in reader:\\n inventory_controller(check_ip(site))\\n inventory_APs(make_ap_ip(site))\\n\\n job_name = str(file.split(\\\".\\\")[0])\\n os.system('mkdir Completed/' + job_name)\\n\\n # Move inventory.csv, error.log, retries.csv the CSV itself to this directory\\n os.system('mv inventory.csv error.log retries.csv ' + job_name + '.csv' + ' Completed/' + job_name)\\n\\n\\nmain()\"\n }\n]"},"num_files":{"kind":"number","value":2,"string":"2"}}},{"rowIdx":2045,"cells":{"repo_name":{"kind":"string","value":"fanout/headline"},"repo_url":{"kind":"string","value":"https://github.com/fanout/headline"},"snapshot_id":{"kind":"string","value":"db7562bc4e44c6d77e92080e3418af984c220420"},"revision_id":{"kind":"string","value":"c8d52ff36180d46a6e103fef219ae653c89e93d6"},"directory_id":{"kind":"string","value":"50018ca594d790d633e0d50c49e7bbc6613e504c"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"string","value":"2023-05-24T18:37:00.210681"},"revision_date":{"kind":"string","value":"2019-12-07T19:45:32"},"committer_date":{"kind":"string","value":"2019-12-07T19:45:32"},"github_id":{"kind":"number","value":25950623,"string":"25,950,623"},"star_events_count":{"kind":"number","value":6,"string":"6"},"fork_events_count":{"kind":"number","value":2,"string":"2"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"string","value":"2014-10-30T02:09:58"},"gha_updated_at":{"kind":"string","value":"2019-12-07T19:45:35"},"gha_pushed_at":{"kind":"string","value":"2023-05-22T22:27:53"},"gha_language":{"kind":"string","value":"Python"},"files":{"kind":"list like","value":[{"alpha_fraction":0.7731958627700806,"alphanum_fraction":0.7731958627700806,"avg_line_length":18.399999618530273,"blob_id":"43bf75b3368ca2f0e5a75a1bcf6c2c7d074f83f3","content_id":"d27ae38790e03d96ac53c199c43c540eb9206787","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":97,"license_type":"no_license","max_line_length":35,"num_lines":5,"path":"/headlineapp/apps.py","repo_name":"fanout/headline","src_encoding":"UTF-8","text":"from django.apps import AppConfig\n\n\nclass HeadlineappConfig(AppConfig):\n name = 'headlineapp'\n"},{"alpha_fraction":0.7035040259361267,"alphanum_fraction":0.7169811129570007,"avg_line_length":13.84000015258789,"blob_id":"1ee8c07155b22cb415e04171ecf6708f635e79f0","content_id":"d3e6f096722ae85542a702fd4287a5517c479bb3","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":371,"license_type":"no_license","max_line_length":71,"num_lines":25,"path":"/README.md","repo_name":"fanout/headline","src_encoding":"UTF-8","text":"# Headline\n\nHeadline API example for Python/Django.\n\n## Setup\n\nCreate virtualenv and install dependencies:\n\n```sh\nvirtualenv --python=python3 venv\n. venv/bin/activate\npip install -r requirements.txt\n```\n\nCreate a `.env` file in the base directory containing `GRIP_URL`, e.g.:\n\n```\nGRIP_URL=http://localhost:5561\n```\n\nRun the server:\n\n```sh\npython manage.py runserver\n```\n"},{"alpha_fraction":0.6402438879013062,"alphanum_fraction":0.6402438879013062,"avg_line_length":22.428571701049805,"blob_id":"048f445f77d1f6ebe92a5e424738c6f3cce54a11","content_id":"765cb6a2501fe6e38a989953ae47fce51d5fd81c","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":164,"license_type":"no_license","max_line_length":56,"num_lines":7,"path":"/headlineapp/urls.py","repo_name":"fanout/headline","src_encoding":"UTF-8","text":"from django.urls import path\nfrom . import views\n\nurlpatterns = [\n path('', views.base, name='base'),\n path('<int:headline_id>/', views.item, name='item'),\n]\n"},{"alpha_fraction":0.5530035495758057,"alphanum_fraction":0.5671378374099731,"avg_line_length":27.299999237060547,"blob_id":"d7c2c291c279bee27b2afe899eb81fdbe0db27bf","content_id":"124fbccf60f926572b7b18bb89dc614dbc3b6dca","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":566,"license_type":"no_license","max_line_length":54,"num_lines":20,"path":"/headlineapp/models.py","repo_name":"fanout/headline","src_encoding":"UTF-8","text":"from django.db import models\n\nclass Headline(models.Model):\n type = models.CharField(max_length=64)\n title = models.CharField(max_length=200)\n text = models.TextField()\n date = models.DateTimeField(auto_now=True)\n\n def to_data(self):\n out = {}\n out['id'] = str(self.id)\n out['type'] = self.type\n if self.title:\n out['title'] = self.title\n out['date'] = self.date.isoformat()\n out['text'] = self.text\n return out\n\n def __str__(self):\n return '%s: %s' % (self.type, self.text[:100])\n"},{"alpha_fraction":0.567531168460846,"alphanum_fraction":0.5725833773612976,"avg_line_length":33.12643814086914,"blob_id":"9493b15dc818e58f7d447437c93b75c796f5bf14","content_id":"63ee1f8e79a0d925cbba4f0901273cb2a9304fab","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":2969,"license_type":"no_license","max_line_length":79,"num_lines":87,"path":"/headlineapp/views.py","repo_name":"fanout/headline","src_encoding":"UTF-8","text":"import json\nimport calendar\nfrom django.http import HttpResponse, HttpResponseRedirect, \\\n HttpResponseNotModified, HttpResponseNotAllowed\nfrom django.shortcuts import get_object_or_404\nfrom gripcontrol import HttpResponseFormat, HttpStreamFormat, \\\n WebSocketMessageFormat\nfrom django_grip import set_hold_longpoll, set_hold_stream, publish\nfrom headlineapp.models import Headline\n\ndef _json_response(data):\n body = json.dumps(data, indent=4) + '\\n' # pretty print\n return HttpResponse(body, content_type='application/json')\n\ndef base(request):\n if request.method == 'POST':\n h = Headline(type='none', title='', text='')\n h.save()\n return _json_response(h.to_data())\n else:\n return HttpResponseNotAllowed(['POST'])\n\ndef item(request, headline_id):\n h = get_object_or_404(Headline, pk=headline_id)\n\n hchannel = str(headline_id)\n\n if request.wscontext:\n ws = request.wscontext\n if ws.is_opening():\n ws.accept()\n ws.subscribe(hchannel)\n while ws.can_recv():\n message = ws.recv()\n if message is None:\n ws.close()\n break\n return HttpResponse()\n elif request.method == 'GET':\n if request.META.get('HTTP_ACCEPT') == 'text/event-stream':\n resp = HttpResponse(content_type='text/event-stream')\n set_hold_stream(request, hchannel)\n return resp\n else:\n wait = request.META.get('HTTP_WAIT')\n if wait:\n wait = int(wait)\n if wait < 1:\n wait = None\n if wait > 300:\n wait = 300\n inm = request.META.get('HTTP_IF_NONE_MATCH')\n etag = '\"%s\"' % calendar.timegm(h.date.utctimetuple())\n if inm == etag:\n resp = HttpResponseNotModified()\n if wait:\n set_hold_longpoll(request, hchannel, timeout=wait)\n else:\n resp = _json_response(h.to_data())\n resp['ETag'] = etag\n return resp\n elif request.method == 'PUT':\n hdata = json.loads(request.read())\n\n h.type = hdata['type']\n h.title = hdata.get('title', '')\n h.text = hdata.get('text', '')\n h.save()\n hdata = h.to_data()\n\n hjson = json.dumps(hdata)\n etag = '\"%s\"' % calendar.timegm(h.date.utctimetuple())\n rheaders = {'Content-Type': 'application/json', 'ETag': etag}\n hpretty = json.dumps(hdata, indent=4) + '\\n'\n\n formats = []\n formats.append(HttpResponseFormat(body=hpretty, headers=rheaders))\n formats.append(HttpStreamFormat('event: update\\ndata: %s\\n\\n' % hjson))\n formats.append(WebSocketMessageFormat(hjson))\n\n publish(hchannel, formats)\n\n resp = _json_response(hdata)\n resp['ETag'] = etag\n return resp\n else:\n return HttpResponseNotAllowed(['GET', 'PUT'])\n"},{"alpha_fraction":0.4612903296947479,"alphanum_fraction":0.6838709712028503,"avg_line_length":15.315789222717285,"blob_id":"a0f0c55c63a6a9f63ccab81dc56f2fc68f60ba24","content_id":"a455ee41694683ddaf530e2c7b8490b817733746","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Text","length_bytes":310,"license_type":"no_license","max_line_length":22,"num_lines":19,"path":"/requirements.txt","repo_name":"fanout/headline","src_encoding":"UTF-8","text":"certifi==2018.4.16\nchardet==3.0.4\ndj-database-url==0.5.0\ndj-static==0.0.6\nDjango==2.2.8\ndjango-dotenv==1.4.2\ndjango-grip==1.8.0\ngripcontrol==3.2.1\ngunicorn==19.9.0\nidna==2.7\npsycopg2==2.8.2\npubcontrol==2.4.2\nPyJWT==1.6.4\npytz==2018.5\nrequests==2.22.0\nsix==1.11.0\nsqlparse==0.3.0\nstatic3==0.7.0\nurllib3==1.24.2\n"}],"string":"[\n {\n \"alpha_fraction\": 0.7731958627700806,\n \"alphanum_fraction\": 0.7731958627700806,\n \"avg_line_length\": 18.399999618530273,\n \"blob_id\": \"43bf75b3368ca2f0e5a75a1bcf6c2c7d074f83f3\",\n \"content_id\": \"d27ae38790e03d96ac53c199c43c540eb9206787\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 97,\n \"license_type\": \"no_license\",\n \"max_line_length\": 35,\n \"num_lines\": 5,\n \"path\": \"/headlineapp/apps.py\",\n \"repo_name\": \"fanout/headline\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from django.apps import AppConfig\\n\\n\\nclass HeadlineappConfig(AppConfig):\\n name = 'headlineapp'\\n\"\n },\n {\n \"alpha_fraction\": 0.7035040259361267,\n \"alphanum_fraction\": 0.7169811129570007,\n \"avg_line_length\": 13.84000015258789,\n \"blob_id\": \"1ee8c07155b22cb415e04171ecf6708f635e79f0\",\n \"content_id\": \"d3e6f096722ae85542a702fd4287a5517c479bb3\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 371,\n \"license_type\": \"no_license\",\n \"max_line_length\": 71,\n \"num_lines\": 25,\n \"path\": \"/README.md\",\n \"repo_name\": \"fanout/headline\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# Headline\\n\\nHeadline API example for Python/Django.\\n\\n## Setup\\n\\nCreate virtualenv and install dependencies:\\n\\n```sh\\nvirtualenv --python=python3 venv\\n. venv/bin/activate\\npip install -r requirements.txt\\n```\\n\\nCreate a `.env` file in the base directory containing `GRIP_URL`, e.g.:\\n\\n```\\nGRIP_URL=http://localhost:5561\\n```\\n\\nRun the server:\\n\\n```sh\\npython manage.py runserver\\n```\\n\"\n },\n {\n \"alpha_fraction\": 0.6402438879013062,\n \"alphanum_fraction\": 0.6402438879013062,\n \"avg_line_length\": 22.428571701049805,\n \"blob_id\": \"048f445f77d1f6ebe92a5e424738c6f3cce54a11\",\n \"content_id\": \"765cb6a2501fe6e38a989953ae47fce51d5fd81c\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 164,\n \"license_type\": \"no_license\",\n \"max_line_length\": 56,\n \"num_lines\": 7,\n \"path\": \"/headlineapp/urls.py\",\n \"repo_name\": \"fanout/headline\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from django.urls import path\\nfrom . import views\\n\\nurlpatterns = [\\n path('', views.base, name='base'),\\n path('<int:headline_id>/', views.item, name='item'),\\n]\\n\"\n },\n {\n \"alpha_fraction\": 0.5530035495758057,\n \"alphanum_fraction\": 0.5671378374099731,\n \"avg_line_length\": 27.299999237060547,\n \"blob_id\": \"d7c2c291c279bee27b2afe899eb81fdbe0db27bf\",\n \"content_id\": \"124fbccf60f926572b7b18bb89dc614dbc3b6dca\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 566,\n \"license_type\": \"no_license\",\n \"max_line_length\": 54,\n \"num_lines\": 20,\n \"path\": \"/headlineapp/models.py\",\n \"repo_name\": \"fanout/headline\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from django.db import models\\n\\nclass Headline(models.Model):\\n type = models.CharField(max_length=64)\\n title = models.CharField(max_length=200)\\n text = models.TextField()\\n date = models.DateTimeField(auto_now=True)\\n\\n def to_data(self):\\n out = {}\\n out['id'] = str(self.id)\\n out['type'] = self.type\\n if self.title:\\n out['title'] = self.title\\n out['date'] = self.date.isoformat()\\n out['text'] = self.text\\n return out\\n\\n def __str__(self):\\n return '%s: %s' % (self.type, self.text[:100])\\n\"\n },\n {\n \"alpha_fraction\": 0.567531168460846,\n \"alphanum_fraction\": 0.5725833773612976,\n \"avg_line_length\": 33.12643814086914,\n \"blob_id\": \"9493b15dc818e58f7d447437c93b75c796f5bf14\",\n \"content_id\": \"63ee1f8e79a0d925cbba4f0901273cb2a9304fab\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 2969,\n \"license_type\": \"no_license\",\n \"max_line_length\": 79,\n \"num_lines\": 87,\n \"path\": \"/headlineapp/views.py\",\n \"repo_name\": \"fanout/headline\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import json\\nimport calendar\\nfrom django.http import HttpResponse, HttpResponseRedirect, \\\\\\n HttpResponseNotModified, HttpResponseNotAllowed\\nfrom django.shortcuts import get_object_or_404\\nfrom gripcontrol import HttpResponseFormat, HttpStreamFormat, \\\\\\n WebSocketMessageFormat\\nfrom django_grip import set_hold_longpoll, set_hold_stream, publish\\nfrom headlineapp.models import Headline\\n\\ndef _json_response(data):\\n body = json.dumps(data, indent=4) + '\\\\n' # pretty print\\n return HttpResponse(body, content_type='application/json')\\n\\ndef base(request):\\n if request.method == 'POST':\\n h = Headline(type='none', title='', text='')\\n h.save()\\n return _json_response(h.to_data())\\n else:\\n return HttpResponseNotAllowed(['POST'])\\n\\ndef item(request, headline_id):\\n h = get_object_or_404(Headline, pk=headline_id)\\n\\n hchannel = str(headline_id)\\n\\n if request.wscontext:\\n ws = request.wscontext\\n if ws.is_opening():\\n ws.accept()\\n ws.subscribe(hchannel)\\n while ws.can_recv():\\n message = ws.recv()\\n if message is None:\\n ws.close()\\n break\\n return HttpResponse()\\n elif request.method == 'GET':\\n if request.META.get('HTTP_ACCEPT') == 'text/event-stream':\\n resp = HttpResponse(content_type='text/event-stream')\\n set_hold_stream(request, hchannel)\\n return resp\\n else:\\n wait = request.META.get('HTTP_WAIT')\\n if wait:\\n wait = int(wait)\\n if wait < 1:\\n wait = None\\n if wait > 300:\\n wait = 300\\n inm = request.META.get('HTTP_IF_NONE_MATCH')\\n etag = '\\\"%s\\\"' % calendar.timegm(h.date.utctimetuple())\\n if inm == etag:\\n resp = HttpResponseNotModified()\\n if wait:\\n set_hold_longpoll(request, hchannel, timeout=wait)\\n else:\\n resp = _json_response(h.to_data())\\n resp['ETag'] = etag\\n return resp\\n elif request.method == 'PUT':\\n hdata = json.loads(request.read())\\n\\n h.type = hdata['type']\\n h.title = hdata.get('title', '')\\n h.text = hdata.get('text', '')\\n h.save()\\n hdata = h.to_data()\\n\\n hjson = json.dumps(hdata)\\n etag = '\\\"%s\\\"' % calendar.timegm(h.date.utctimetuple())\\n rheaders = {'Content-Type': 'application/json', 'ETag': etag}\\n hpretty = json.dumps(hdata, indent=4) + '\\\\n'\\n\\n formats = []\\n formats.append(HttpResponseFormat(body=hpretty, headers=rheaders))\\n formats.append(HttpStreamFormat('event: update\\\\ndata: %s\\\\n\\\\n' % hjson))\\n formats.append(WebSocketMessageFormat(hjson))\\n\\n publish(hchannel, formats)\\n\\n resp = _json_response(hdata)\\n resp['ETag'] = etag\\n return resp\\n else:\\n return HttpResponseNotAllowed(['GET', 'PUT'])\\n\"\n },\n {\n \"alpha_fraction\": 0.4612903296947479,\n \"alphanum_fraction\": 0.6838709712028503,\n \"avg_line_length\": 15.315789222717285,\n \"blob_id\": \"a0f0c55c63a6a9f63ccab81dc56f2fc68f60ba24\",\n \"content_id\": \"a455ee41694683ddaf530e2c7b8490b817733746\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Text\",\n \"length_bytes\": 310,\n \"license_type\": \"no_license\",\n \"max_line_length\": 22,\n \"num_lines\": 19,\n \"path\": \"/requirements.txt\",\n \"repo_name\": \"fanout/headline\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"certifi==2018.4.16\\nchardet==3.0.4\\ndj-database-url==0.5.0\\ndj-static==0.0.6\\nDjango==2.2.8\\ndjango-dotenv==1.4.2\\ndjango-grip==1.8.0\\ngripcontrol==3.2.1\\ngunicorn==19.9.0\\nidna==2.7\\npsycopg2==2.8.2\\npubcontrol==2.4.2\\nPyJWT==1.6.4\\npytz==2018.5\\nrequests==2.22.0\\nsix==1.11.0\\nsqlparse==0.3.0\\nstatic3==0.7.0\\nurllib3==1.24.2\\n\"\n }\n]"},"num_files":{"kind":"number","value":6,"string":"6"}}},{"rowIdx":2046,"cells":{"repo_name":{"kind":"string","value":"ufeindt/simsurvey-paper-scripts"},"repo_url":{"kind":"string","value":"https://github.com/ufeindt/simsurvey-paper-scripts"},"snapshot_id":{"kind":"string","value":"1fa7e04c3d3d3731b73ed58457083c5150fe58e0"},"revision_id":{"kind":"string","value":"d1f09d60172d9f30b2659d3874e697320175fc6b"},"directory_id":{"kind":"string","value":"dc56c3afd5461f730a9b759ee7873f8dadf4b8ff"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"string","value":"2020-04-20T01:24:46.618008"},"revision_date":{"kind":"string","value":"2020-03-28T21:15:36"},"committer_date":{"kind":"string","value":"2020-03-28T21:15:36"},"github_id":{"kind":"number","value":168544721,"string":"168,544,721"},"star_events_count":{"kind":"number","value":3,"string":"3"},"fork_events_count":{"kind":"number","value":1,"string":"1"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.5059621334075928,"alphanum_fraction":0.5251344442367554,"avg_line_length":36.19130325317383,"blob_id":"da6d05579999b20eb426b3438d68234e7684e9ef","content_id":"ee6981ad3678a454bdb531dea30df57b86b1e8c0","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":4277,"license_type":"no_license","max_line_length":103,"num_lines":115,"path":"/run_sim.py","repo_name":"ufeindt/simsurvey-paper-scripts","src_encoding":"UTF-8","text":"import os\nimport sys\nfrom argparse import ArgumentParser\n\nimport numpy as np\n#from astropy.cosmology import Planck15\nfrom astropy.table import Table\nimport simsurvey\nimport sncosmo\n\n_RATES = {'Ia': 3e-5, 'Ibc': 2.25e-5, 'IIn': 7.5e-6, 'IIP': 1.2e-4}\n\ndef load_fields_ccd(fields_file='ztf_fields.txt', ccd_file='ztf_ccd_corners.txt'):\n fields_raw = np.genfromtxt(fields_file, comments='%')\n\n fields = {'field_id': np.array(fields_raw[:,0], dtype=int),\n 'ra': fields_raw[:,1],\n 'dec': fields_raw[:,2]}\n\n ccd_corners = np.genfromtxt(ccd_file, skip_header=1)\n ccds = [ccd_corners[np.array([0,1,3,2])+4*k, :2] for k in range(16)]\n\n return fields, ccds\n \ndef load_ztf_bands(bandpass_dir=''):\n bands = {\n 'ztfg' : 'ztfg_eff.txt',\n 'ztfr' : 'ztfr_eff.txt',\n 'ztfi' : 'ztfi_eff.txt',\n }\n\n for bandname in bands.keys() :\n fname = bands[bandname]\n b = np.loadtxt(os.path.join(bandpass_dir,fname))\n band = sncosmo.Bandpass(b[:,0], b[:,1], name=bandname)\n sncosmo.registry.register(band, force=True)\n\ndef main():\n if 'SFD_DIR' not in os.environ.keys():\n raise ValueError('Please set $SFD_DIR to where you downloaded the SFD dust maps.')\n \n parser = ArgumentParser(description='Run lightcurve simulations for ZTF')\n parser.add_argument('plan', type=str,\n help='CSV file containing survey plan')\n parser.add_argument('transient', type=str,\n help='Transient type (e.g. \"Ia\" for SNe Ia)')\n parser.add_argument('template', type=str,\n help='Transient template (e.g. \"salt2\" or \"nugent\")')\n parser.add_argument('-z', '--redshift', default=None, nargs=2,\n help='redshift boundaries', type=float)\n parser.add_argument('--no-weather', action='store_true',\n help='do not apply weather loss')\n \n \n args = parser.parse_args()\n\n if args.redshift is None:\n args.redshift = (0, 0.2)\n\n obs = Table.read(args.plan, format='ascii.csv')\n fields, ccds = load_fields_ccd()\n load_ztf_bands()\n \n plan = simsurvey.SurveyPlan(time=obs['time'], band=obs['band'], obs_field=obs['field'],\n skynoise=obs['skynoise'], comment=obs['comment'],\n fields={k: v for k, v in fields.items()\n if k in ['ra', 'dec', 'field_id',\n 'width', 'height']},\n ccds=ccds)\n\n mjd_range = (plan.pointings['time'].min(), plan.pointings['time'].max())\n ra_range = (0, 360)\n dec_range = (-40, 90)\n\n tr = simsurvey.get_transient_generator((args.redshift[0], args.redshift[1]),\n ratefunc=(lambda z: _RATES[args.transient]),\n transient=args.transient, \n template=args.template,\n ra_range=ra_range,\n dec_range=dec_range,\n mjd_range=(mjd_range[0],\n mjd_range[1]))\n\n survey = simsurvey.SimulSurvey(generator=tr, plan=plan)\n\n lcs = survey.get_lightcurves(progress_bar=True)\n\n if not os.path.exists('lcs'):\n os.makedirs('lcs')\n\n prev_files = [fn for fn in os.listdir('lcs')\n if fn.startswith('lcs_%s_%s'%(args.transient, args.template))]\n if len(prev_files) > 0:\n k = max([int(fn.split('.')[0].split('_')[-1]) for fn in prev_files]) + 1\n else:\n k = 0\n \n outfile = 'lcs/lcs_%s_%s_%06i.pkl'%(args.transient, args.template, k)\n\n if not args.no_weather:\n real_nights = np.genfromtxt('hours_per_obsnight.dat')\n idx = np.concatenate((range(31,365), range(31)))\n rn_2016 = np.where(real_nights[idx, -1] > 3.5)[0] + 2458151\n\n def filterfunc(lc):\n mask = np.array([(int(t_) in rn_2016) and (t_ < lc.meta['t0'] + 100) for t_ in lc['time']])\n \n return lc[mask]\n\n lcs = lcs.filter(filterfunc)\n \n lcs.save(outfile)\n \nif __name__ == '__main__':\n main()\n"},{"alpha_fraction":0.7394191026687622,"alphanum_fraction":0.7551867365837097,"avg_line_length":43.62963104248047,"blob_id":"d06c96f8b2772a974168a311fba0555d1d1c3bd9","content_id":"d137c98b7f9dc26bdc8ff7856c423dc25117515f","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":1205,"license_type":"no_license","max_line_length":265,"num_lines":27,"path":"/README.md","repo_name":"ufeindt/simsurvey-paper-scripts","src_encoding":"UTF-8","text":"# simsurvey-paper-scripts\nScripts and files required to reproduce the ZTF lightcurve simulations presented in [Feindt et al. (2019)](https://arxiv.org/pdf/1902.03923.pdf)\n\nRequirements\n------------\n\n- Install `simsurvey` and its required packages. The paper used `simsurvey v0.4.4`. Default settings in other versions may differ.\n- Download the data for `sfdmap` from https://github.com/kbarbary/sfddata\n- Set `$SFD_DIR` to the `sfddata` download path\n\nUsage Example\n-------------\n\n```\npython run_sim.py plan_sim_paper.csv Ia salt2\n```\n\nThe last two arguments can be replaced by the other supernova types simulated in the paper and further options are available, see `python run_sim_paper.py -h`.\n\nThe script will save the output in the directory `lcs` and give it a file name that contains SN type and template. New runs with the same type and template will be save with an incremented number at the end. (Note that each file will be several hundred MB in size.)\n\nTo load the output, use the following lines:\n```\nfrom simsurvey import LightcurveCollection\nlcs = LightcurveCollection(load='/path/to/file')\n```\nNote that output files generated using Python 3 cannot be loaded with Python 2 and vice versa.\n"}],"string":"[\n {\n \"alpha_fraction\": 0.5059621334075928,\n \"alphanum_fraction\": 0.5251344442367554,\n \"avg_line_length\": 36.19130325317383,\n \"blob_id\": \"da6d05579999b20eb426b3438d68234e7684e9ef\",\n \"content_id\": \"ee6981ad3678a454bdb531dea30df57b86b1e8c0\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 4277,\n \"license_type\": \"no_license\",\n \"max_line_length\": 103,\n \"num_lines\": 115,\n \"path\": \"/run_sim.py\",\n \"repo_name\": \"ufeindt/simsurvey-paper-scripts\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import os\\nimport sys\\nfrom argparse import ArgumentParser\\n\\nimport numpy as np\\n#from astropy.cosmology import Planck15\\nfrom astropy.table import Table\\nimport simsurvey\\nimport sncosmo\\n\\n_RATES = {'Ia': 3e-5, 'Ibc': 2.25e-5, 'IIn': 7.5e-6, 'IIP': 1.2e-4}\\n\\ndef load_fields_ccd(fields_file='ztf_fields.txt', ccd_file='ztf_ccd_corners.txt'):\\n fields_raw = np.genfromtxt(fields_file, comments='%')\\n\\n fields = {'field_id': np.array(fields_raw[:,0], dtype=int),\\n 'ra': fields_raw[:,1],\\n 'dec': fields_raw[:,2]}\\n\\n ccd_corners = np.genfromtxt(ccd_file, skip_header=1)\\n ccds = [ccd_corners[np.array([0,1,3,2])+4*k, :2] for k in range(16)]\\n\\n return fields, ccds\\n \\ndef load_ztf_bands(bandpass_dir=''):\\n bands = {\\n 'ztfg' : 'ztfg_eff.txt',\\n 'ztfr' : 'ztfr_eff.txt',\\n 'ztfi' : 'ztfi_eff.txt',\\n }\\n\\n for bandname in bands.keys() :\\n fname = bands[bandname]\\n b = np.loadtxt(os.path.join(bandpass_dir,fname))\\n band = sncosmo.Bandpass(b[:,0], b[:,1], name=bandname)\\n sncosmo.registry.register(band, force=True)\\n\\ndef main():\\n if 'SFD_DIR' not in os.environ.keys():\\n raise ValueError('Please set $SFD_DIR to where you downloaded the SFD dust maps.')\\n \\n parser = ArgumentParser(description='Run lightcurve simulations for ZTF')\\n parser.add_argument('plan', type=str,\\n help='CSV file containing survey plan')\\n parser.add_argument('transient', type=str,\\n help='Transient type (e.g. \\\"Ia\\\" for SNe Ia)')\\n parser.add_argument('template', type=str,\\n help='Transient template (e.g. \\\"salt2\\\" or \\\"nugent\\\")')\\n parser.add_argument('-z', '--redshift', default=None, nargs=2,\\n help='redshift boundaries', type=float)\\n parser.add_argument('--no-weather', action='store_true',\\n help='do not apply weather loss')\\n \\n \\n args = parser.parse_args()\\n\\n if args.redshift is None:\\n args.redshift = (0, 0.2)\\n\\n obs = Table.read(args.plan, format='ascii.csv')\\n fields, ccds = load_fields_ccd()\\n load_ztf_bands()\\n \\n plan = simsurvey.SurveyPlan(time=obs['time'], band=obs['band'], obs_field=obs['field'],\\n skynoise=obs['skynoise'], comment=obs['comment'],\\n fields={k: v for k, v in fields.items()\\n if k in ['ra', 'dec', 'field_id',\\n 'width', 'height']},\\n ccds=ccds)\\n\\n mjd_range = (plan.pointings['time'].min(), plan.pointings['time'].max())\\n ra_range = (0, 360)\\n dec_range = (-40, 90)\\n\\n tr = simsurvey.get_transient_generator((args.redshift[0], args.redshift[1]),\\n ratefunc=(lambda z: _RATES[args.transient]),\\n transient=args.transient, \\n template=args.template,\\n ra_range=ra_range,\\n dec_range=dec_range,\\n mjd_range=(mjd_range[0],\\n mjd_range[1]))\\n\\n survey = simsurvey.SimulSurvey(generator=tr, plan=plan)\\n\\n lcs = survey.get_lightcurves(progress_bar=True)\\n\\n if not os.path.exists('lcs'):\\n os.makedirs('lcs')\\n\\n prev_files = [fn for fn in os.listdir('lcs')\\n if fn.startswith('lcs_%s_%s'%(args.transient, args.template))]\\n if len(prev_files) > 0:\\n k = max([int(fn.split('.')[0].split('_')[-1]) for fn in prev_files]) + 1\\n else:\\n k = 0\\n \\n outfile = 'lcs/lcs_%s_%s_%06i.pkl'%(args.transient, args.template, k)\\n\\n if not args.no_weather:\\n real_nights = np.genfromtxt('hours_per_obsnight.dat')\\n idx = np.concatenate((range(31,365), range(31)))\\n rn_2016 = np.where(real_nights[idx, -1] > 3.5)[0] + 2458151\\n\\n def filterfunc(lc):\\n mask = np.array([(int(t_) in rn_2016) and (t_ < lc.meta['t0'] + 100) for t_ in lc['time']])\\n \\n return lc[mask]\\n\\n lcs = lcs.filter(filterfunc)\\n \\n lcs.save(outfile)\\n \\nif __name__ == '__main__':\\n main()\\n\"\n },\n {\n \"alpha_fraction\": 0.7394191026687622,\n \"alphanum_fraction\": 0.7551867365837097,\n \"avg_line_length\": 43.62963104248047,\n \"blob_id\": \"d06c96f8b2772a974168a311fba0555d1d1c3bd9\",\n \"content_id\": \"d137c98b7f9dc26bdc8ff7856c423dc25117515f\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 1205,\n \"license_type\": \"no_license\",\n \"max_line_length\": 265,\n \"num_lines\": 27,\n \"path\": \"/README.md\",\n \"repo_name\": \"ufeindt/simsurvey-paper-scripts\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# simsurvey-paper-scripts\\nScripts and files required to reproduce the ZTF lightcurve simulations presented in [Feindt et al. (2019)](https://arxiv.org/pdf/1902.03923.pdf)\\n\\nRequirements\\n------------\\n\\n- Install `simsurvey` and its required packages. The paper used `simsurvey v0.4.4`. Default settings in other versions may differ.\\n- Download the data for `sfdmap` from https://github.com/kbarbary/sfddata\\n- Set `$SFD_DIR` to the `sfddata` download path\\n\\nUsage Example\\n-------------\\n\\n```\\npython run_sim.py plan_sim_paper.csv Ia salt2\\n```\\n\\nThe last two arguments can be replaced by the other supernova types simulated in the paper and further options are available, see `python run_sim_paper.py -h`.\\n\\nThe script will save the output in the directory `lcs` and give it a file name that contains SN type and template. New runs with the same type and template will be save with an incremented number at the end. (Note that each file will be several hundred MB in size.)\\n\\nTo load the output, use the following lines:\\n```\\nfrom simsurvey import LightcurveCollection\\nlcs = LightcurveCollection(load='/path/to/file')\\n```\\nNote that output files generated using Python 3 cannot be loaded with Python 2 and vice versa.\\n\"\n }\n]"},"num_files":{"kind":"number","value":2,"string":"2"}}},{"rowIdx":2047,"cells":{"repo_name":{"kind":"string","value":"Carter4502/hangman.py"},"repo_url":{"kind":"string","value":"https://github.com/Carter4502/hangman.py"},"snapshot_id":{"kind":"string","value":"ab1d4c75ea0994951ac4072e8dbfe53cee07c8d1"},"revision_id":{"kind":"string","value":"ecab8fcfdfaacc9fe63a0e230f1aff9dd60c2191"},"directory_id":{"kind":"string","value":"820b12e04cc9a1b6b88b155d1a88ce987150f5d5"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"string","value":"2020-04-04T18:19:45.797804"},"revision_date":{"kind":"string","value":"2018-11-05T04:08:51"},"committer_date":{"kind":"string","value":"2018-11-05T04:08:51"},"github_id":{"kind":"number","value":156159212,"string":"156,159,212"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.7878788113594055,"alphanum_fraction":0.7878788113594055,"avg_line_length":32,"blob_id":"1dcdea5cd8decf32fd60fa6c2be6c9cdd1b5fc82","content_id":"43f4510a70e0a7c239bfee76473ed6466cf03baa","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":66,"license_type":"no_license","max_line_length":52,"num_lines":2,"path":"/README.md","repo_name":"Carter4502/hangman.py","src_encoding":"UTF-8","text":"# hangman.py\nThis is a very simple hangman game created in Python\n"},{"alpha_fraction":0.6274768710136414,"alphanum_fraction":0.649933934211731,"avg_line_length":31.223403930664062,"blob_id":"e5f77a5b0623d4d94340bc86846a917bc1a12de0","content_id":"60b774328381b8d00ed47f548a06f4271be8ba7a","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":3028,"license_type":"no_license","max_line_length":99,"num_lines":94,"path":"/hangman.py","repo_name":"Carter4502/hangman.py","src_encoding":"UTF-8","text":"import time\nimport math\nstart = time.time()\nprint(\"WELCOME TO HANGMAN!!\")\nprint(\"What would you like your word to be?\")\nogword = input(\"input your word here: \")\nword = ogword.lower()\nprint(\"Ok now give it to the player tryna guess ur word.\")\ntime.sleep(5)\nlength = str(len(word))\nprint(\"Before we get started... the word given is \" + length + \" letters long. (including spaces)\")\ntime.sleep(2)\nprint(\"You will get 12 guesses before you must guess the full word.\")\ntime.sleep(1)\nprint(\"Now.. take a guess and i will tell you if the letter is in the word.\")\ng1 = input(\"first guess: \")\nif g1 in word:\n\tposition = str(word.index(g1) + 1)\n\n\tprint(\"That is letter number \" + position + \" in the \" + length + \" letter long word.\")\nelse:\n\tprint(\"That is not part of the word...\")\ng2 = input(\"second guess: \")\nif g2 in word:\n\tposition2 = str(word.index(g2) + 1)\n\n\tprint(\"That is letter number \" + position2 + \" in the \" + length + \" letter long word.\")\nelse:\n\tprint(\"That is not part of the word...\")\ng3 = input(\"third guess: \")\nif g3 in word:\n\tposition3 = str(word.index(g3) + 1)\n\n\tprint(\"That is letter number \" + position3 + \" in the \" + length + \" letter long word.\")\nelse:\n\tprint(\"That is not part of the word...\")\ng4 = input(\"fourth guess: \")\nif g4 in word:\n\tposition4 = str(word.index(g4) + 1)\n\n\tprint(\"That is letter number \" + position4 + \" in the \" + length + \" letter long word.\")\nelse:\n\tprint(\"That is not part of the word...\")\ng5 = input(\"fifth guess: \")\nif g5 in word:\n\tposition5 = str(word.index(g5) + 1)\n\n\tprint(\"That is letter number \" + position5 + \" in the \" + length + \" letter long word.\")\nelse:\n\tprint(\"That is not part of the word...\")\ng6 = input(\"sixth guess: \")\nif g6 in word:\n\tposition6 = str(word.index(g6) + 1)\n\n\tprint(\"That is letter number \" + position6 + \" in the \" + length + \" letter long word.\")\nelse:\n\tprint(\"That is not part of the word...\")\ng7 = input(\"seventh guess: \")\nif g7 in word:\n\tposition7 = str(word.index(g7) + 1)\n\n\tprint(\"That is letter number \" + position7 + \" in the \" + length + \" letter long word.\")\nelse:\n\tprint(\"That is not part of the word...\")\ng8 = input(\"eighth guess: \")\nif g8 in word:\n\tposition8 = str(word.index(g8) + 1)\n\n\tprint(\"That is letter number \" + position8 + \" in the \" + length + \" letter long word.\")\nelse:\n\tprint(\"That is not part of the word...\")\ng9 = input(\"nineth guess: \")\nif g9 in word:\n\tposition9 = str(word.index(g9) + 1)\n\n\tprint(\"That is letter number \" + position9 + \" in the \" + length + \" letter long word.\")\nelse:\n\tprint(\"That is not part of the word...\")\ng10 = input(\"LAST guess: \")\nif g10 in word:\n\tposition10 = str(word.index(g10) + 1)\n\n\tprint(\"That is letter number \" + position10 + \" in the \" + length + \" letter long word.\")\nelse:\n\tprint(\"That is not part of the word...\")\nprint(\"Now, take your guess on what you think the word is.\")\nguess = input(\"Guess: \").lower()\nend = time.time()\nif guess == word:\n\ttime = end - start\n\tprint(\"YOU WIN!\")\n\tprint(\"It took \" + str(end - start) + \" seconds for you to guess the word.\")\nelse:\n\tprint(\"You lose :/\")"}],"string":"[\n {\n \"alpha_fraction\": 0.7878788113594055,\n \"alphanum_fraction\": 0.7878788113594055,\n \"avg_line_length\": 32,\n \"blob_id\": \"1dcdea5cd8decf32fd60fa6c2be6c9cdd1b5fc82\",\n \"content_id\": \"43f4510a70e0a7c239bfee76473ed6466cf03baa\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 66,\n \"license_type\": \"no_license\",\n \"max_line_length\": 52,\n \"num_lines\": 2,\n \"path\": \"/README.md\",\n \"repo_name\": \"Carter4502/hangman.py\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# hangman.py\\nThis is a very simple hangman game created in Python\\n\"\n },\n {\n \"alpha_fraction\": 0.6274768710136414,\n \"alphanum_fraction\": 0.649933934211731,\n \"avg_line_length\": 31.223403930664062,\n \"blob_id\": \"e5f77a5b0623d4d94340bc86846a917bc1a12de0\",\n \"content_id\": \"60b774328381b8d00ed47f548a06f4271be8ba7a\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 3028,\n \"license_type\": \"no_license\",\n \"max_line_length\": 99,\n \"num_lines\": 94,\n \"path\": \"/hangman.py\",\n \"repo_name\": \"Carter4502/hangman.py\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import time\\nimport math\\nstart = time.time()\\nprint(\\\"WELCOME TO HANGMAN!!\\\")\\nprint(\\\"What would you like your word to be?\\\")\\nogword = input(\\\"input your word here: \\\")\\nword = ogword.lower()\\nprint(\\\"Ok now give it to the player tryna guess ur word.\\\")\\ntime.sleep(5)\\nlength = str(len(word))\\nprint(\\\"Before we get started... the word given is \\\" + length + \\\" letters long. (including spaces)\\\")\\ntime.sleep(2)\\nprint(\\\"You will get 12 guesses before you must guess the full word.\\\")\\ntime.sleep(1)\\nprint(\\\"Now.. take a guess and i will tell you if the letter is in the word.\\\")\\ng1 = input(\\\"first guess: \\\")\\nif g1 in word:\\n\\tposition = str(word.index(g1) + 1)\\n\\n\\tprint(\\\"That is letter number \\\" + position + \\\" in the \\\" + length + \\\" letter long word.\\\")\\nelse:\\n\\tprint(\\\"That is not part of the word...\\\")\\ng2 = input(\\\"second guess: \\\")\\nif g2 in word:\\n\\tposition2 = str(word.index(g2) + 1)\\n\\n\\tprint(\\\"That is letter number \\\" + position2 + \\\" in the \\\" + length + \\\" letter long word.\\\")\\nelse:\\n\\tprint(\\\"That is not part of the word...\\\")\\ng3 = input(\\\"third guess: \\\")\\nif g3 in word:\\n\\tposition3 = str(word.index(g3) + 1)\\n\\n\\tprint(\\\"That is letter number \\\" + position3 + \\\" in the \\\" + length + \\\" letter long word.\\\")\\nelse:\\n\\tprint(\\\"That is not part of the word...\\\")\\ng4 = input(\\\"fourth guess: \\\")\\nif g4 in word:\\n\\tposition4 = str(word.index(g4) + 1)\\n\\n\\tprint(\\\"That is letter number \\\" + position4 + \\\" in the \\\" + length + \\\" letter long word.\\\")\\nelse:\\n\\tprint(\\\"That is not part of the word...\\\")\\ng5 = input(\\\"fifth guess: \\\")\\nif g5 in word:\\n\\tposition5 = str(word.index(g5) + 1)\\n\\n\\tprint(\\\"That is letter number \\\" + position5 + \\\" in the \\\" + length + \\\" letter long word.\\\")\\nelse:\\n\\tprint(\\\"That is not part of the word...\\\")\\ng6 = input(\\\"sixth guess: \\\")\\nif g6 in word:\\n\\tposition6 = str(word.index(g6) + 1)\\n\\n\\tprint(\\\"That is letter number \\\" + position6 + \\\" in the \\\" + length + \\\" letter long word.\\\")\\nelse:\\n\\tprint(\\\"That is not part of the word...\\\")\\ng7 = input(\\\"seventh guess: \\\")\\nif g7 in word:\\n\\tposition7 = str(word.index(g7) + 1)\\n\\n\\tprint(\\\"That is letter number \\\" + position7 + \\\" in the \\\" + length + \\\" letter long word.\\\")\\nelse:\\n\\tprint(\\\"That is not part of the word...\\\")\\ng8 = input(\\\"eighth guess: \\\")\\nif g8 in word:\\n\\tposition8 = str(word.index(g8) + 1)\\n\\n\\tprint(\\\"That is letter number \\\" + position8 + \\\" in the \\\" + length + \\\" letter long word.\\\")\\nelse:\\n\\tprint(\\\"That is not part of the word...\\\")\\ng9 = input(\\\"nineth guess: \\\")\\nif g9 in word:\\n\\tposition9 = str(word.index(g9) + 1)\\n\\n\\tprint(\\\"That is letter number \\\" + position9 + \\\" in the \\\" + length + \\\" letter long word.\\\")\\nelse:\\n\\tprint(\\\"That is not part of the word...\\\")\\ng10 = input(\\\"LAST guess: \\\")\\nif g10 in word:\\n\\tposition10 = str(word.index(g10) + 1)\\n\\n\\tprint(\\\"That is letter number \\\" + position10 + \\\" in the \\\" + length + \\\" letter long word.\\\")\\nelse:\\n\\tprint(\\\"That is not part of the word...\\\")\\nprint(\\\"Now, take your guess on what you think the word is.\\\")\\nguess = input(\\\"Guess: \\\").lower()\\nend = time.time()\\nif guess == word:\\n\\ttime = end - start\\n\\tprint(\\\"YOU WIN!\\\")\\n\\tprint(\\\"It took \\\" + str(end - start) + \\\" seconds for you to guess the word.\\\")\\nelse:\\n\\tprint(\\\"You lose :/\\\")\"\n }\n]"},"num_files":{"kind":"number","value":2,"string":"2"}}},{"rowIdx":2048,"cells":{"repo_name":{"kind":"string","value":"sorrow4468/BAEKJOON"},"repo_url":{"kind":"string","value":"https://github.com/sorrow4468/BAEKJOON"},"snapshot_id":{"kind":"string","value":"bebb4f0463ae5240b55f2a861c2e8723cd48ec8b"},"revision_id":{"kind":"string","value":"768f20bfc1490f87d601aedb5e4669a2d261fa08"},"directory_id":{"kind":"string","value":"2a6e92ad80730b517a98e1d96dbdbdee24593b7a"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"string","value":"2023-07-26T12:39:13.188551"},"revision_date":{"kind":"string","value":"2023-06-14T13:08:00"},"committer_date":{"kind":"string","value":"2023-06-14T13:08:00"},"github_id":{"kind":"number","value":386566995,"string":"386,566,995"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.49275362491607666,"alphanum_fraction":0.5024154782295227,"avg_line_length":19.799999237060547,"blob_id":"5637fe4795b9b5ff0544c8c4136315d28d5845ad","content_id":"512d235b655e9976f3a0c808f9cb82754fc3c46f","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":207,"license_type":"no_license","max_line_length":50,"num_lines":10,"path":"/알고리즘/SWEA/LEARN/Course/1. Programming Beginner/파이썬 프로그래밍 기초(2)/16차시 2. 자료구조 – 리스트, 튜플 - 연습문제 18.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N, M = map(int, input().split(', '))\n\nresult = [[0 for _ in range(M)] for i in range(N)]\n\nfor i in range(N):\n for j in range(M):\n if result[i][j] == 0:\n result[i][j] = i*j\n\nprint(result)"},{"alpha_fraction":0.5903614163398743,"alphanum_fraction":0.6204819083213806,"avg_line_length":17.55555534362793,"blob_id":"d6d4cc0411656f9906e9032569ffaa1d908a80f4","content_id":"f6b0b1f0a20ae62e74b919f2917df2b97c322db0","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":166,"license_type":"no_license","max_line_length":34,"num_lines":9,"path":"/알고리즘/온라인저지/2023/06/0605/노솔브 방지문제야!!.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\n\nQ = int(input())\ndouble = [2**i for i in range(32)]\nfor q in range(Q):\n A = int(input())\n print(1 if A in double else 0)"},{"alpha_fraction":0.446958988904953,"alphanum_fraction":0.4752475321292877,"avg_line_length":34.400001525878906,"blob_id":"9d7f54b287fb9549e3c68451a4b400b2815ebfb5","content_id":"28cafc0cfd6a2bf238ff3a302836ece6422db141","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1109,"license_type":"no_license","max_line_length":64,"num_lines":20,"path":"/알고리즘/온라인저지/2021/08/0813/설탕 배달.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"\"\"\"\n3kg봉지, 5kg봉지\n정확하게 Nkg, 못만들면 -1 출력\n3과 5를 이중for문 돌리면서 \n순회중인 무게를 3과 5로 만들어서 \n그 때 사용한 각각의 봉지 개수를 리스트에 저장\n봉지 리스트 길이가 0이면 만들 수 없는 무게이므로 -1\n봉지 리스트에서 최소값을 출력\n\"\"\"\n\nN = int(input()) # 설탕 무게\ncnt = [] # 사용한 봉지개수를 더한 값을 담을 리스트\nfor three in range(N//3 + 1): # 3kg, 시간 단축을 위해 범위 조절\n for five in range(N//5 + 1): # 5kg, 마찬가지로 범위 조절\n if three*3 + five*5 == N: # 해당 무게가 설탕무게이면\n cnt.append(three + five)# 그때 사용된 봉지의 개수를 더한 값을 저장\nif len(cnt) == 0: # 저장된 봉지개수 값이 없으면 만들 수 없는 무게\n print(-1) # -1 출력\nelse: # 저장된 봉지 개수값이 있다면\n print(min(cnt)) # 봉지 개수중 최소값을 출력"},{"alpha_fraction":0.5506493449211121,"alphanum_fraction":0.5558441281318665,"avg_line_length":26.571428298950195,"blob_id":"1678315064784a81b3d30ee661cca5f9d17832f7","content_id":"1af89b6d17d1b51d0da487cdd5d5dcb732779f53","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":385,"license_type":"no_license","max_line_length":66,"num_lines":14,"path":"/알고리즘/온라인저지/2022/11/1101/임시 반장 정하기.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\n\nN = int(input().rstrip())\narr = [list(map(int, input().rstrip().split())) for _ in range(N)]\ncheck = [set() for _ in range(N)]\nfor j in range(5):\n for i in range(N):\n for k in range(N):\n if arr[i][j] == arr[k][j] and i != k:\n check[i].add(k)\nresult = [len(c) for c in check]\nprint(result.index(max(result))+1)"},{"alpha_fraction":0.49193549156188965,"alphanum_fraction":0.5134408473968506,"avg_line_length":18.63157844543457,"blob_id":"cdbdc3cbd865d3832839cd0c08ec12aaf35980c4","content_id":"af3bab9f1312b632973504645a46d84b033d4835","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":372,"license_type":"no_license","max_line_length":45,"num_lines":19,"path":"/알고리즘/온라인저지/2022/10/1003/피보나치 수의 개수.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\n\ndef check(fib):\n if A<=fib<=B: return 1\n else: return 0\n\nwhile True:\n A, B = map(int, input().rstrip().split())\n if A == 0 and B == 0: break\n result = 0\n a, b = 1, 2\n result += check(a) + check(b)\n for _ in range(B-2): \n if b>B: break\n a, b = b, a+b\n result += check(b)\n print(result)"},{"alpha_fraction":0.4593908488750458,"alphanum_fraction":0.4763113260269165,"avg_line_length":22.65999984741211,"blob_id":"2cf714e1cb8d280ea6a53b35cb8d487fd820d645","content_id":"3668bec89d0eddd9d1952219e929a45449fd5572","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1696,"license_type":"no_license","max_line_length":56,"num_lines":50,"path":"/알고리즘/온라인저지/2022/01/0122/귀여운 라이언.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N, K = map(int, input().split())\n\n# 라이언 혹은 어피치\nryans = list(map(int, input().split()))\n\ns = e = cnt = 0 # 시작 끝 라이언개수\n\nif ryans[s] == 1: # 라이언으로 시작하면\n cnt += 1 # cnt 1로 초기화\n\nresult = N # 가상의 최대값\n\nis_answer = False # 조합을 찾았는가??\n\nwhile True: # 무지성 while True\n # while 종료 조건문\n # 1. 라이언이 K개 미만인데 더 뒤로 못 감\n # 2. 라이언이 K개 초과인데 더 앞에서 땡길 수 없음\n if (cnt < K and e == N-1) or (cnt > K and s == N-1):\n break\n\n if cnt == K: # K개 라이언인 구간 발견!\n if not is_answer: # 처음 발견한거면\n # K개인 라이언구간이 존재하니\n # 일단 답이 -1은 아님\n is_answer = True # 라이언구간 존재함 체크\n \n length = e-s+1 # 라이언구간의 길이\n if length < result: # 더 짧은 구간길이라면\n result = length # 최소 길이 갱신\n \n # 포인터를 옮길건데\n if ryans[s] == 1: # 구간 맨 앞이 라이언이면\n cnt -= 1 # 라이언 카운트 빼주고\n s += 1 # 한 칸 땡기기\n\n elif cnt < K: # K개 미만 라이언구간이면\n e += 1 # 한 칸 밀고\n if ryans[e] == 1: # 밀은 위치가 라이언이면\n cnt += 1 # 카운트\n\n elif cnt > K: # K개 초과 라이언구간이면\n if ryans[s] == 1: # 맨 앞이 라이언이면\n cnt -= 1 # 카운트 감소하고\n s += 1 # 한 칸 땡김\n\nif is_answer: # K개인 라이언구간을 찾았었으면\n print(result)\nelse: # 못찾았었으면\n print(-1)"},{"alpha_fraction":0.5270270109176636,"alphanum_fraction":0.5405405163764954,"avg_line_length":24,"blob_id":"d177e28e0d42b2ed6332431130b150e4aaf969d9","content_id":"6c90f64e19d77e448c91bf86a3eaade1d6a693c5","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":74,"license_type":"no_license","max_line_length":35,"num_lines":3,"path":"/알고리즘/온라인저지/2023/02/0228/Koszykarz.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"K, W, M = map(int, input().split())\nA = W-K\nprint(A//M+1 if A%M else A//M)"},{"alpha_fraction":0.5267857313156128,"alphanum_fraction":0.5803571343421936,"avg_line_length":27.125,"blob_id":"ea41653ec7245ab7e7c0fee0b12b72e5494a7aad","content_id":"e3526922e073cea4a99eccd99f9e19139d658a5c","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":224,"license_type":"no_license","max_line_length":44,"num_lines":8,"path":"/알고리즘/온라인저지/2023/04/0423/과자 사기.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"cospas = []\nfor snack in ['S', 'N', 'U']:\n cost, weight = map(int, input().split())\n cost *= 10\n if cost>=5000: cost -= 500\n cospas.append((snack, weight/cost))\ncospas.sort(key=lambda x:-x[1])\nprint(cospas[0][0])"},{"alpha_fraction":0.5014326572418213,"alphanum_fraction":0.5300859808921814,"avg_line_length":18.44444465637207,"blob_id":"4e7b1537a1f6948107090d906f042b5f7c99299e","content_id":"02afbda505628654af495f5726d4f4e3e5b39b58","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":441,"license_type":"no_license","max_line_length":50,"num_lines":18,"path":"/알고리즘/온라인저지/2022/08/0808/트럭 주차.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"P = [0] * 101 # parking\nC = [0] + list(map(int, input().split())) # charge\nfor _ in range(3):\n I, O = map(int, input().split()) # in out\n for i in range(I, O): P[i] += 1\nresult = 0\nfor p in P:\n tmp = C[p] * p\n result += tmp\nprint(result)\n\n\"\"\"\n시간 : 13분\n풀이\n 트럭의 출입을 기록한 일지(P)를 만들고\n 그 시간에 주차장에 있었던 트럭대수와\n 요금을 곱해서 result++ 하여 출력\n\"\"\""},{"alpha_fraction":0.5820895433425903,"alphanum_fraction":0.5970149040222168,"avg_line_length":33,"blob_id":"29a376fcc878ca6d3cf05074324c7fa9c4b5e86c","content_id":"2cef6a4f32bf4436e6b00442633dce242f5b1d85","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":67,"license_type":"no_license","max_line_length":54,"num_lines":2,"path":"/알고리즘/온라인저지/2022/08/0820/코딩은 체육과목 입니다.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"for i in range(int(input())//4):print('long', end=' ')\nprint('int')"},{"alpha_fraction":0.38566553592681885,"alphanum_fraction":0.4095562994480133,"avg_line_length":14.473684310913086,"blob_id":"5fc98f1ceae3529578c830b429a12d562d5175ee","content_id":"d8e37e2b8ecb37c20b031bb5149b82b2a28efe84","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":293,"license_type":"no_license","max_line_length":34,"num_lines":19,"path":"/알고리즘/온라인저지/2022/02/0205/만취한 상범.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"T = int(input())\n\nfor t in range(T):\n N = int(input())\n\n dp = [True] * (N+1)\n dp[0] = False\n\n for i in range(2, N+1):\n for j in range(i, N+1, i):\n dp[j] = not dp[j]\n \n result = 0\n\n for d in dp:\n if d:\n result += 1\n \n print(result)"},{"alpha_fraction":0.482051283121109,"alphanum_fraction":0.4871794879436493,"avg_line_length":27,"blob_id":"aa11fbdb91205e00783f7bbacb571f841557ee56","content_id":"342355176a4b4534b6d7d97cd5c97974ad7b44be","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":195,"license_type":"no_license","max_line_length":43,"num_lines":7,"path":"/알고리즘/온라인저지/2022/12/1206/꿍의 우주여행.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"for _ in range(int(input())):\n N, D = map(int, input().split())\n result = 0\n for n in range(N):\n v, f, s = map(int, input().split())\n result += v*f >= D*s\n print(result)"},{"alpha_fraction":0.44262295961380005,"alphanum_fraction":0.5,"avg_line_length":40,"blob_id":"b9e57499a44208b4f9a4ed29f7d63b4ebde09b9b","content_id":"66280451043b2a4fc910e44a3f48789d5a9f7124","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":166,"license_type":"no_license","max_line_length":41,"num_lines":3,"path":"/알고리즘/온라인저지/2021/08/0804/구구단.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = int(input()) # 1 < N <= 9 인 N을 입력받아서\nfor i in range(1, 10): # 1부터 9까지 순회하면서 \n print(f'{N} * {i} = {N*i}') # 구구단을 출력"},{"alpha_fraction":0.446153849363327,"alphanum_fraction":0.4615384638309479,"avg_line_length":21,"blob_id":"213f14103d47db93e410049e180fa68738389d43","content_id":"b6157dccbff71530d50da2c8e819e6b299881ce1","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":65,"license_type":"no_license","max_line_length":38,"num_lines":3,"path":"/알고리즘/온라인저지/2022/02/0210/스타후르츠.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N, T, C, P = map(int, input().split())\n\nprint(((N-1)//T) * C * P)"},{"alpha_fraction":0.5798319578170776,"alphanum_fraction":0.5882353186607361,"avg_line_length":12.333333015441895,"blob_id":"cf0e626c5cdf52e0edcb9758a39726da0543ee38","content_id":"2fc784abf4f1b3049878bd35657236cb7b2a6ba0","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":119,"license_type":"no_license","max_line_length":31,"num_lines":9,"path":"/알고리즘/온라인저지/2021/09/0906/돌 게임.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\ndef input():\n return sys.stdin.readline()\n\nN = int(input())\nif N%2:\n print('SK')\nelse:\n print('CY')"},{"alpha_fraction":0.5625,"alphanum_fraction":0.5972222089767456,"avg_line_length":47.33333206176758,"blob_id":"95ba1e5cf265fa9c1f74ec8759e42628ccaee2d2","content_id":"ae361a4a4a315d1ee0ed3b155942b138aab6eb0d","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":144,"license_type":"no_license","max_line_length":62,"num_lines":3,"path":"/알고리즘/온라인저지/2022/09/0910/점수 집계.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"for _ in range(int(input())):\n score = sorted(list(map(int, input().split())))\n print(sum(score[1:-1]) if score[-2]-score[1]<4 else 'KIN')"},{"alpha_fraction":0.47663551568984985,"alphanum_fraction":0.4953271150588989,"avg_line_length":12.5,"blob_id":"5305e99966fc00a221026d0ceb9381d622e1591e","content_id":"7703d041c79a25ab3fa5aabc0ce4d54d85d3f3a7","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":107,"license_type":"no_license","max_line_length":19,"num_lines":8,"path":"/알고리즘/온라인저지/2023/06/0604/Gum Gum for Jay Jay.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"result = 0\nwhile True:\n try:\n input()\n result += 1\n except:\n break\nprint(result)"},{"alpha_fraction":0.5188323855400085,"alphanum_fraction":0.5555555820465088,"avg_line_length":31.212121963500977,"blob_id":"0d47de68f1ac69ee6afb8d3b722b7e92a9b66850","content_id":"2de90d8202deeadfe44b8d7561a76d1d79837cd3","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1334,"license_type":"no_license","max_line_length":145,"num_lines":33,"path":"/알고리즘/[템플릿]/Floyd-Warshall/Small World Network.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"INF = int(1e9)\nN, K = map(int, input().split())\nworld = [[INF]*N for _ in range(N)] # 친구간 거리 배열 초기화\nfor k in range(K):\n A, B = map(int, input().split())\n A, B = A-1, B-1\n world[A][B], world[B][A] = 1, 1 # 친구인 관계는 서로 거리가 1\nfor k in range(N):\n for i in range(N):\n for j in range(N):\n if i != j: # 자기 자신과 친구는 카운트하지 않음\n world[i][j] = min(world[i][j], world[i][k]+world[k][j])\nresult = 'Small World!' # 초기값을 Small World로 놓고 거리가 6을 초과하는 관계를 찾을 것\nfor i in range(N):\n if result != 'Small World!': # Small World가 아닌 것이 증명되었다면 \n break\n for j in range(N):\n if i != j: # 자기 자신이 아니면서\n if world[i][j] > 6: # 친구 거리가 6을 초과한다?\n result = 'Big World!'\n break\nprint(result)\n\n\"\"\"\n플로이드 워셜(Floyd-Warshall) 알고리즘\nhttps://velog.io/@kimdukbae/%ED%94%8C%EB%A1%9C%EC%9D%B4%EB%93%9C-%EC%9B%8C%EC%85%9C-%EC%95%8C%EA%B3%A0%EB%A6%AC%EC%A6%98-Floyd-Warshall-Algorithm\ni에서 j로 가는 최소값은\n이미 구한 \"i에서 j로 가는 값\"과\n\"지점 k를 거쳐가는 i -> k -> j로 가는 값\"\n두 값중 최소값이다\n\"\"\"\n\n# https://www.acmicpc.net/problem/18243"},{"alpha_fraction":0.4516128897666931,"alphanum_fraction":0.49395161867141724,"avg_line_length":23.850000381469727,"blob_id":"512e820bfa19c7f67c9a7051ba9a524047ea89ff","content_id":"0da8cd1034f9f8bebb2ce44e049a6f3f2ddb9e2e","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":572,"license_type":"no_license","max_line_length":57,"num_lines":20,"path":"/알고리즘/온라인저지/2022/07/0727/5학년은 다니기 싫어요.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N, A, B = map(int, input().split())\nL = 8-N # left : 남은 학기\nLA = 66-A # 남은 전공학점\nLB = 130-B # 남은 총학점\nresult = 'Nae ga wae'\nC = [tuple(map(int, input().split())) for _ in range(10)]\nfor l in range(L):\n # 한 학기 최대 이수 6과목 18학점\n LC = 6 # left credits : 남은 이번학기 수강가능 학점\n tmp_a = C[l][0]\n LA -= tmp_a * 3\n LC -= tmp_a\n tmp_b = C[l][1]\n if LC >= tmp_b:\n LB -= tmp_a*3 + tmp_b*3\n else:\n LB -= tmp_a*3 + LC*3\n if LA<=0 and LB<=0:\n result = 'Nice'\nprint(result)"},{"alpha_fraction":0.3652482330799103,"alphanum_fraction":0.3758865296840668,"avg_line_length":20.769229888916016,"blob_id":"70d431864efcf07f47758276e93c4e2f4538aa05","content_id":"c5f07363f66a551115347f1386cfc212040d79fc","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":282,"license_type":"no_license","max_line_length":43,"num_lines":13,"path":"/알고리즘/온라인저지/2022/06/0629/캥거루 세마리2.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"while True:\n try:\n A, B, C = map(int, input().split())\n result = 0\n al = abs(A-B)\n cl = abs(B-C)\n if al <= cl:\n result += C - (B+1)\n elif al > cl:\n result += (B-1) - A\n print(result)\n except:\n break"},{"alpha_fraction":0.4270462691783905,"alphanum_fraction":0.47330960631370544,"avg_line_length":30.33333396911621,"blob_id":"caae94943f193cca55d0d8a81d89342c03f35a8a","content_id":"f7e7cafdf1284645bd7865ca50f432606ad60454","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":281,"license_type":"no_license","max_line_length":40,"num_lines":9,"path":"/알고리즘/온라인저지/2023/01/0117/신용카드 판별.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"for _ in range(int(input())):\n card = list(map(int, list(input())))\n result = 0\n for i in range(0, 16, 2):\n card[i] = card[i]*2\n if card[i] > 9:\n card[i] = (card[i]%10) + 1\n result += card[i] + card[i+1]\n print('F' if result%10 else 'T')"},{"alpha_fraction":0.4673366844654083,"alphanum_fraction":0.5376884341239929,"avg_line_length":15.666666984558105,"blob_id":"d75be4920374727333676c5224b901aff6dd4b4d","content_id":"c3bcf21ddebe55ef918454746aa839692a93d5b7","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":199,"license_type":"no_license","max_line_length":36,"num_lines":12,"path":"/알고리즘/온라인저지/2022/02/0220/카드 역배치.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"cards = list(range(21))\n\n# a, b = 5, 10\n# print(cards[a:b+1])\n# print(cards[b:a-1:-1])\n\nfor i in range(10):\n a, b = map(int, input().split())\n\n cards[a:b+1] = cards[b:a-1:-1]\n\nprint(*cards[1:])"},{"alpha_fraction":0.5909090638160706,"alphanum_fraction":0.6818181872367859,"avg_line_length":22,"blob_id":"8df19a54d0fcb1c74c7f5a3d58b7ad274babc966","content_id":"16266bf0be4d01829f08fe4eacc1eced2cf6690b","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":22,"license_type":"no_license","max_line_length":22,"num_lines":1,"path":"/알고리즘/온라인저지/2023/04/0410/時間 (Hour).py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"print(int(input())*24)"},{"alpha_fraction":0.516094446182251,"alphanum_fraction":0.5364806652069092,"avg_line_length":29.09677505493164,"blob_id":"76a5eab002625165c0f76b5f666d8389f73defd1","content_id":"d9491a9cf4a0ef349cd448793e2e2b49cf351b85","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1266,"license_type":"no_license","max_line_length":106,"num_lines":31,"path":"/알고리즘/온라인저지/2022/09/0927/백양로 브레이크.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\nINF = int(1e9) # 가상의, 변경해야 할 길의 수 최대값\n\nN, M = map(int, input().rstrip().split())\narr = [[INF]*N for _ in range(N)]\nfor m in range(M):\n u, v, b = map(int, input().rstrip().split())\n u, v = u-1, v-1 # 인덱스 맞추기\n if b == 0: # 일방통행이면\n arr[u][v] = 0 # 한 쪽은 괜찮지만\n arr[v][u] = 1 # 다른 한 쪽은 길을 바꿔줘야 함\n else: arr[u][v], arr[v][u] = 0, 0 # 양방향 통행이면 서로 오갈 수 있음\nfor k in range(N):\n for a in range(N):\n for b in range(N):\n arr[a][b] = min(arr[a][b], arr[a][k]+arr[k][b]) # 최소값(기존에 구한 변경해야 하는 길의 수, 새로 구한 변경해야 하는 길의 수)\nK = int(input().rstrip())\nfor k in range(K):\n s, e = map(int, input().rstrip().split())\n s, e = s-1, e-1 # 인덱스 맞추기\n if s == e: print(0) # 1->1 같은 경우는 갔다 돌아오는 것이 아닌, 출발 자체를 하지 않는 것으로 함\n else: print(arr[s][e])\n\n# https://www.acmicpc.net/problem/11562\n\"\"\" \n플로이드-워셜 알고리즘\na->b 로 가기 위해 바꿔야하는 일방통행 길의 수는\na->k->b 로 가기 위해 바꿔야 하는 길의 수와 같다\n\"\"\""},{"alpha_fraction":0.48927614092826843,"alphanum_fraction":0.5080428719520569,"avg_line_length":23.899999618530273,"blob_id":"1db74d81d6b785893a91c892e6bfee6eced7cf1b","content_id":"96579c68bc200f50ec733cfcbc2befe1f0f2d89a","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":816,"license_type":"no_license","max_line_length":48,"num_lines":30,"path":"/알고리즘/온라인저지/2021/09/0908/카드2.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\ndef input():\n return sys.stdin.readline()\n\ndef is_odd_or_even(N):\n if N%2:\n return True\n else:\n return False\n\nN = int(input())\ndeck = list(range(1, N+1))\npop_or_keep = True # 버리기, False=살리기, 처음엔 버리면서 시작\nwhile len(deck) > 1:\n odd_or_even = is_odd_or_even(len(deck))\n if odd_or_even:\n if pop_or_keep: # 홀수, 버리기\n deck = deck[1:len(deck)+1:2]\n pop_or_keep = False\n else: # 홀수, 살리기\n deck = deck[0:len(deck):2]\n pop_or_keep = True\n else:\n if pop_or_keep: # 짝수, 버리기\n deck = deck[1:len(deck)+1:2]\n pop_or_keep = True\n else: # 짝수, 살리기\n deck = deck[0:len(deck):2]\n pop_or_keep = False\nprint(*deck)"},{"alpha_fraction":0.429198682308197,"alphanum_fraction":0.4588364362716675,"avg_line_length":21.799999237060547,"blob_id":"d508adfa8a62345374d6b7f670788332367213d9","content_id":"7cf59cafb587050f9156da0fb6e9e7ef70049f99","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":961,"license_type":"no_license","max_line_length":35,"num_lines":40,"path":"/알고리즘/온라인저지/2022/07/0706/가위 바위 보.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"def RSP(player1, player2):\n result = 0\n if player1 == 'R':\n if player2 == 'R':\n result += 1 \n elif player2 == 'S':\n result += 2\n elif player1 == 'S':\n if player2 == 'S':\n result += 1\n elif player2 == 'P':\n result += 2\n elif player1 == 'P':\n if player2 == 'R':\n result += 2\n elif player2 == 'P':\n result += 1\n return result\n\n\nR = int(input())\nSG = list(input()) # 상근\nN = int(input())\nfriend = [] # 친구들\nfor n in range(N): \n friend.append(list(input()))\nresult1 = result2 = 0\nfor i in range(R):\n for f in friend: # 상근이의 점수\n result1 += RSP(SG[i], f[i])\n maxx = 0 # 최대점수 초기화\n for j in 'RSP': # 최대점수 구하기\n tmp = 0\n for f in friend:\n tmp += RSP(j, f[i])\n if tmp > maxx:\n maxx = tmp\n result2 += maxx\nprint(result1)\nprint(result2)"},{"alpha_fraction":0.4267912805080414,"alphanum_fraction":0.5327102541923523,"avg_line_length":20.46666717529297,"blob_id":"7bf847a3d0f98097b641cd3f908b7de47cd883b7","content_id":"a874c41343d9e4bad382e835e1cf3c3adf7844f6","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":321,"license_type":"no_license","max_line_length":52,"num_lines":15,"path":"/알고리즘/온라인저지/2023/03/0317/추첨을 통해 커피를 받자.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"scores = list(map(int, input().split()))\nmaxx = [100, 100, 200, 200, 300, 300, 400, 400, 500]\ncoffee, hacker = 0, 0\nfor i in range(9):\n S, M = scores[i], maxx[i]\n if S>M:\n hacker = 1\n coffee += S\nif hacker:\n print('hacker')\nelse:\n if coffee<100:\n print('none')\n else:\n print('draw')"},{"alpha_fraction":0.3705308735370636,"alphanum_fraction":0.3911159336566925,"avg_line_length":20.488372802734375,"blob_id":"8404d6428c10092faa10089a1819a6452d229fca","content_id":"8c35509f58ecdd42e704b478c2f519e76fbc417d","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":923,"license_type":"no_license","max_line_length":67,"num_lines":43,"path":"/알고리즘/온라인저지/2021/12/1216/단지번호붙이기.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"from collections import deque\n\ndx = (-1, 1, 0, 0)\ndy = (0, 0, -1, 1)\n\nN = int(input())\n\nmap = [list(map(int, input())) for _ in range(N)]\n\ncomplex_cnt = 0\n\ncomplex_counts = []\n\nbfs = deque()\n\nfor i in range(N):\n for j in range(N):\n if map[i][j]:\n bfs.append((i, j))\n complex_cnt += 1\n cnt = 0\n while bfs:\n tmp = bfs.popleft()\n y = tmp[0]\n x = tmp[1]\n\n if map[y][x] == 0:\n continue\n \n map[y][x] = 0\n cnt += 1\n\n for k in range(4):\n ny = y + dy[k]\n nx = x + dx[k]\n\n if 0 <= ny < N and 0 <= nx < N and map[ny][nx]:\n bfs.append((ny, nx))\n complex_counts.append(cnt)\nprint(complex_cnt)\ncomplex_counts.sort()\nfor c in complex_counts:\n print(c)"},{"alpha_fraction":0.47999998927116394,"alphanum_fraction":0.4950000047683716,"avg_line_length":21.33333396911621,"blob_id":"93d2c3b89ce62186b3e54f3351eb66cfc59223fa","content_id":"d65d3aed872b96f32cc29453b4a2b3a3a80f152a","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":200,"license_type":"no_license","max_line_length":31,"num_lines":9,"path":"/알고리즘/온라인저지/2022/07/0728/서로 다른 부분 문자열의 개수.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"S = input()\nresult = set()\nfor i in range(1, len(S)+1):\n # print(i)\n for j in range(len(S)+1-i):\n # print(j, j+i)\n # print(S[j:j+i])\n result.add(S[j:j+i])\nprint(len(result))"},{"alpha_fraction":0.5102040767669678,"alphanum_fraction":0.5306122303009033,"avg_line_length":11.375,"blob_id":"bb6cec09058d814a352f6b81809e5bf48de06c9b","content_id":"6588444cd13d3e54d4edbcde6867882caba78616","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":98,"license_type":"no_license","max_line_length":35,"num_lines":8,"path":"/알고리즘/온라인저지/2022/03/0309/帰省 (Homecoming).py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"A, B, C = map(int, input().split())\n\nresult = 1\n\nif C < A or C >= B:\n result = 0\n\nprint(result)"},{"alpha_fraction":0.5327731370925903,"alphanum_fraction":0.5596638917922974,"avg_line_length":21.074073791503906,"blob_id":"f6511fe9d1495b309a9c5f6e55c0982f23c8485d","content_id":"1072422906c9c0070b26901873e6452da4177d34","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":761,"license_type":"no_license","max_line_length":51,"num_lines":27,"path":"/알고리즘/온라인저지/2022/10/1012/골드바흐의 추측 실버1.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\n\nn = int(1e6)\na = [False,False] + [True]*(n-1)\nfor i in range(2, 1001):\n if a[i]:\n for j in range(2*i, n+1, i):\n a[j] = False\nwhile True:\n N = int(input().rstrip())\n if N == 0: break\n for i in range(3, n):\n if a[N-i] and a[i]:\n print('{} = {} + {}'.format(N, i, N-i))\n break\n else: print(\"Goldbach's conjecture is wrong.\")\n\n\"\"\"\n에라토스테네스의 체를 만드는 과정에서 \nprimes를 만들기 위해 append 하는 부분을 없앴다\n소수판정 테이블인 a만 활용하여 시간초과를 회피하였다\n결론적으로 골드바흐의 추측은 백만 이하 모든 짝수에 적용이 가능하다\n\"\"\"\n\n# https://www.acmicpc.net/problem/6588"},{"alpha_fraction":0.4693877696990967,"alphanum_fraction":0.4920634925365448,"avg_line_length":19.045454025268555,"blob_id":"8e45bcd77a990f25c7762fd852964fdc734a075e","content_id":"81e9075ee4027c9f0222cceb39ddd076dc5e77c2","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":471,"license_type":"no_license","max_line_length":43,"num_lines":22,"path":"/알고리즘/온라인저지/2021/08/0818/p3.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\nsys.stdin = open('input.txt')\n\nV, E = map(int, input().split()) # 정점수, 간선수\n# 인접 행렬\nG = [[0]*(V+1) for _ in range(V+1)]\nfor _ in range(E):\n u, v = map(int, input().split())\n G[u][v] = G[v][u] = 1\n\nfor lst in G[1:]:\n print(*lst[1:])\n\n# 인접 리스트\nG = [[]*(V+1) for _ in range(V+1)]\nfor _ in range(E):\n u, v = map(int, input().split())\n G[u].append(v)\n G[v].append(u)\n\nfor i in range(1, V+1):\n print(i, '-->', G[i])\n"},{"alpha_fraction":0.3415493071079254,"alphanum_fraction":0.35680750012397766,"avg_line_length":21.421052932739258,"blob_id":"004f9b2ae1f57ef4a903e171242bfab9f48556f7","content_id":"e2b52e6bad1ecd04aa04dc8b35f87542efc5c560","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":852,"license_type":"no_license","max_line_length":43,"num_lines":38,"path":"/알고리즘/SWEA/LEARN/Course/2. Programming Intermediate/4. 파이썬 SW문제해결 기본 Stack1/7차시 4일차 - 괄호검사.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"T = int(input())\n\nfor t in range(1, T+1):\n code = input()\n \n stack = []\n bracket = ['(', ')', '{', '}']\n\n for c in code:\n if c == bracket[0]:\n stack.append(c)\n elif c == bracket[1]:\n if stack:\n if stack[-1] == bracket[0]:\n stack.pop()\n else:\n stack.append(c)\n else:\n stack.append(c)\n elif c == bracket[2]:\n stack.append(c)\n elif c == bracket[3]:\n if stack:\n if stack[-1] == bracket[2]:\n stack.pop()\n else:\n stack.append(c)\n else:\n stack.append(c)\n \n result = 0\n if stack:\n result = 0\n else:\n result = 1\n \n \n print('#{} {}'.format(t, result))\n"},{"alpha_fraction":0.4421199560165405,"alphanum_fraction":0.5202231407165527,"avg_line_length":23.758621215820312,"blob_id":"71dda0cb0c14e8369a8c7e1ac732d1a49ae65951","content_id":"7b4577af0f6f1a4f77e75c801701626e41d20300","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":735,"license_type":"no_license","max_line_length":69,"num_lines":29,"path":"/알고리즘/[템플릿]/진법 변환/싱기한 네자리 숫자.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import string\n\ntmp = string.digits + string.ascii_uppercase # 자릿수를 담은 문자열\ndigits_dict = {\n '0': 0, '1': 1, '2': 2, '3': 3,\n '4': 4, '5': 5, '6': 6, '7': 7,\n '8': 8, '9': 9, 'A': 10, 'B': 11,\n 'C': 12, 'D': 13, 'E': 14, 'F': 15,\n}\n\ndef change(num, base):\n result = ''\n while num:\n result = tmp[num%base] + result\n num //= base\n return result\n\ndef digits_sum(num, base):\n result = 0\n for n in num:\n result += digits_dict[n]\n return result\n\nfor num in range(1000, 10000):\n A, B, C = str(num), change(num, 12), change(num, 16)\n A, B, C = digits_sum(A, 10), digits_sum(B, 12), digits_sum(C, 16)\n if A == B == C: print(num)\n\n# https://www.acmicpc.net/problem/6679"},{"alpha_fraction":0.47441861033439636,"alphanum_fraction":0.4883720874786377,"avg_line_length":22.88888931274414,"blob_id":"0d5d793f03074caac7d1ccd253b907ad8e5029a4","content_id":"4803deb43723a7786bb2d226799349067d071b19","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":430,"license_type":"no_license","max_line_length":45,"num_lines":18,"path":"/알고리즘/온라인저지/2022/09/0927/팰린드롬.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\nfrom itertools import combinations as comb\n\ninput = sys.stdin.readline\n\nfor _ in [0]*int(input().rstrip()):\n K = int(input().rstrip())\n words = [input().rstrip() for _ in [0]*K]\n word_comb = list(comb(words, 2))\n for a, b in word_comb:\n A, B = a+b, b+a\n if A == A[::-1]:\n print(A)\n break\n if B == B[::-1]:\n print(B)\n break\n else: print(0)\n"},{"alpha_fraction":0.49841269850730896,"alphanum_fraction":0.565079391002655,"avg_line_length":14.800000190734863,"blob_id":"6c32fefe76219981377494ecd95d51f729f28103","content_id":"16d8e9027e414e818cafca4d84b79e9a58b132fd","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":439,"license_type":"no_license","max_line_length":34,"num_lines":20,"path":"/알고리즘/온라인저지/2022/09/0904/애너그램 만들기.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"A, B = input(), input()\narr1, arr2 = [0]*26, [0]*26\nfor a in A:\n i = ord(a)-97\n arr1[i] += 1\nfor b in B:\n i = ord(b)-97\n arr2[i] += 1\nresult = 0\nfor i in range(26):\n result += abs(arr1[i]-arr2[i])\nprint(result)\n\n\"\"\"\n같은 알파벳이 같은 개수만큼 있어야 함\n문제에서는 알파벳을 새로 추가하지는 않고\n불필요할 경우 제거하면서\n애너그램을 만듬\n몇개를 제거해야 하는가\n\"\"\""},{"alpha_fraction":0.5340909361839294,"alphanum_fraction":0.5454545617103577,"avg_line_length":28.5,"blob_id":"a7cdbeb11674ae8d0d57c18a9057da971dd7f7f3","content_id":"5e6094fc851320c16ad1588ebb85d0c73b1911a9","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":176,"license_type":"no_license","max_line_length":39,"num_lines":6,"path":"/알고리즘/온라인저지/2022/09/0910/공 바꾸기.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N, M = map(int, input().split())\nball = [i for i in range(N+1)]\nfor m in range(M):\n i, j = map(int, input().split())\n ball[i], ball[j] = ball[j], ball[i]\nprint(*ball[1:])"},{"alpha_fraction":0.4644128084182739,"alphanum_fraction":0.4750889539718628,"avg_line_length":27.149999618530273,"blob_id":"40ebdb5d59e66505db4f48252e24b4b7fcc191ec","content_id":"1bc7491ce79e3fc1b445c413c85885089badae2c","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":562,"license_type":"no_license","max_line_length":61,"num_lines":20,"path":"/알고리즘/온라인저지/2023/02/0205/운동.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"INF = int(1e9)\nN, M = map(int, input().split())\narr = [[INF]*N for _ in range(N)]\nfor m in range(M):\n a, b, c = map(int, input().split())\n a, b = a-1, b-1\n if c < arr[a][b]:\n arr[a][b] = c\nfor k in range(N):\n for a in range(N):\n for b in range(N):\n arr[a][b] = min(arr[a][b], arr[a][k] + arr[k][b])\nfor i in range(N):\n for j in range(N):\n if arr[i][j] == INF:\n if i != j:\n arr[i][j] = 0\nresult = INF\nfor i in range(N): result = min(result, arr[i][i])\nprint(result if result != INF else -1)"},{"alpha_fraction":0.5643564462661743,"alphanum_fraction":0.594059407711029,"avg_line_length":19.399999618530273,"blob_id":"42777dea1921398b57e879dcf9cb87dc95cf1ea9","content_id":"d41d4a801154684d5fea2ddf2005e2e126d547de","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":101,"license_type":"no_license","max_line_length":34,"num_lines":5,"path":"/알고리즘/온라인저지/2023/01/0125/반지.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"S = input()\nresult = 0\nfor _ in range(int(input())):\n if S in input()*2: result += 1\nprint(result)"},{"alpha_fraction":0.4342857003211975,"alphanum_fraction":0.477142870426178,"avg_line_length":19.647058486938477,"blob_id":"016f357231ee172f2a6dcc7ee5a38830981a0975","content_id":"bac9c4768c4f4e81310bcaf4398bb68b7dedbf91","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":362,"license_type":"no_license","max_line_length":35,"num_lines":17,"path":"/알고리즘/온라인저지/2022/08/0822/분수찾기.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = int(input())\nprev, next, line, move = 0, 0, 0, 0\nD = 1 # 우상향: 1, 좌하향: 0\nfor cnt in range(1, int(1e9)):\n next += cnt\n if prev <= N <= next:\n line, move = cnt, N-prev-1\n D = line%2\n break\n prev += cnt\n# print(line, move, D)\nA, B = 1, line\nfor i in range(move):\n A += 1\n B -= 1\nif D: A, B = B, A\nprint(f'{A}/{B}')"},{"alpha_fraction":0.540229856967926,"alphanum_fraction":0.5747126340866089,"avg_line_length":13.666666984558105,"blob_id":"a294395c9bb265de35aac2207275ad0452881131","content_id":"724b46bc776a635c7e5fbf9d6e26af4328050078","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":87,"license_type":"no_license","max_line_length":22,"num_lines":6,"path":"/알고리즘/온라인저지/2022/05/0511/택시 기하학.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import math\n\npi = math.pi\nR = int(input())\nprint(f'{pi*R*R:.6f}')\nprint(f'{2*R*R:.6f}')"},{"alpha_fraction":0.5221238732337952,"alphanum_fraction":0.5398229956626892,"avg_line_length":21.799999237060547,"blob_id":"62e10a003fc3d3e44b13928626243ef68046055b","content_id":"1f1043882482b8847d269423898de6b17f14d4c7","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":113,"license_type":"no_license","max_line_length":41,"num_lines":5,"path":"/알고리즘/온라인저지/2023/05/0502/Intercepting Information.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"result = 'S'\nfor i in list(map(int, input().split())):\n if i not in (0, 1):\n result = 'F'\nprint(result)"},{"alpha_fraction":0.53125,"alphanum_fraction":0.53125,"avg_line_length":31.200000762939453,"blob_id":"eafb7e2e1d27ffa87fa5b4dd9a34abb0fce4b3d6","content_id":"115e532b9127217c6b23f6215be0d7048cd25e31","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":160,"license_type":"no_license","max_line_length":66,"num_lines":5,"path":"/알고리즘/온라인저지/2022/05/0527/할로윈의 사탕.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"T = int(input())\nfor t in range(T):\n C, V = map(int, input().split())\n A, B = C//V, C%V\n print(f'You get {A} piece(s) and your dad gets {B} piece(s).')"},{"alpha_fraction":0.5161290168762207,"alphanum_fraction":0.524193525314331,"avg_line_length":14.625,"blob_id":"d889ff6505f2e7edd42dc18ae8ca83319f090a50","content_id":"0452676e22d32d0d7b28be9a89c1c82b73d8dba0","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":124,"license_type":"no_license","max_line_length":38,"num_lines":8,"path":"/알고리즘/온라인저지/2022/02/0223/Darius님 한타 안 함.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"K, D, A = map(int, input().split('/'))\n\nis_Darius = 'gosu'\n\nif K + A < D or D == 0:\n is_Darius = 'hasu'\n\nprint(is_Darius)"},{"alpha_fraction":0.50310879945755,"alphanum_fraction":0.5207253694534302,"avg_line_length":30.129032135009766,"blob_id":"8b1def6b78499f45901cb2d021376703bdb59cfd","content_id":"417a7f974598cdd41dfaf4bdc852f6ab73c97ccd","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":2104,"license_type":"no_license","max_line_length":72,"num_lines":62,"path":"/알고리즘/온라인저지/2022/11/1113/연구소 3.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\nfrom itertools import combinations as comb\nfrom collections import deque\n\ninput = sys.stdin.readline\ndy, dx = [-1, 1, 0, 0], [0, 0, -1, 1]\n\ndef spread_virus(viruses):\n new_arr = [[-1]*N for _ in range(N)] # 문제의 예시처럼, 바이러스가 퍼진 시간을 기록할 배열\n # deactivate other viruses\n for i in range(N):\n for j in range(N):\n if new_arr[i][j] == 2 and (i, j) not in viruses:\n new_arr[i][j] = 3\n Q = deque()\n visited = [[0]*N for _ in range(N)]\n for y, x in viruses: \n Q.append((y, x))\n new_arr[y][x] = 0\n visited[y][x] = 1\n while Q:\n y, x = Q.popleft()\n for i in range(4):\n ny, nx = y+dy[i], x+dx[i]\n if 0<=ny<N and 0<=nx<N and not visited[ny][nx]:\n if arr[ny][nx] != 1:\n Q.append((ny, nx))\n new_arr[ny][nx] = new_arr[y][x]+1\n visited[ny][nx] = 1\n all_spreaded_check(new_arr, visited)\n\ndef all_spreaded_check(arr, visited):\n global result\n new_wall = 0\n max_time = 0\n for i in range(N):\n for j in range(N):\n if (i, j) not in virus_coordinates: # 바이러스의 시간은 카운트하지 않는다\n max_time = max(max_time, arr[i][j])\n if visited[i][j] == 0:\n new_wall += 1\n if wall == new_wall: # \n result = min(max_time, result)\n\nN, M = map(int, input().rstrip().split())\narr = [list(map(int, input().rstrip().split())) for _ in range(N)]\nvirus_coordinates = []\nwall = 0\nfor i in range(N):\n for j in range(N):\n if arr[i][j] == 2:\n virus_coordinates.append((i, j))\n if arr[i][j] == 1:\n wall += 1\nvirus_combinations = list(comb(virus_coordinates, M))\nresult = int(1e9) # 가상의 최소값\nfor viruses in virus_combinations: # 매 바이러스 조합에 대해\n spread_virus(viruses) # 바이러스 퍼뜨리기\nif result == int(1e9): result = -1 # 한 번도 바이러스가 다 퍼지지 못했다면 -1\nprint(result)\n\n# 문제가 좀 이상합니다....;;\n"},{"alpha_fraction":0.48785871267318726,"alphanum_fraction":0.50772625207901,"avg_line_length":16.461538314819336,"blob_id":"45636644c2553054f49a5fee7f48dadca7be41a8","content_id":"95a6912609e8c8008c85f750fb8636b4600baaf7","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":453,"license_type":"no_license","max_line_length":43,"num_lines":26,"path":"/알고리즘/SWEA/LEARN/Course/1. Programming Beginner/파이썬 프로그래밍 기초(2)/39차시 4. 문자열 - 연습문제 3.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"url = 'http://www.example.com/test?p=1&q=2'\n\nprotocol = ''\nhost = ''\nothers = ''\n\nhost_s = 0\nhost_e = 0\n\nfor i in range(len(url)):\n if url[i] == ':':\n protocol = url[:i]\n \n if url[i:i+3] == 'www':\n host_s = i\n \n if url[i-2:i+1] == 'com':\n host_e = i+1\n\n others = url[host_e+1:]\n\nhost = url[host_s:host_e]\n\nprint('protocol: {}'.format(protocol))\nprint('host: {}'.format(host))\nprint('others: {}'.format(others))"},{"alpha_fraction":0.5047393441200256,"alphanum_fraction":0.521327018737793,"avg_line_length":31.538461685180664,"blob_id":"9feaef80329af9a8f18552245f1c508b4f984506","content_id":"e1eaffeebcbf31c3da2b5eb2ca5b9d6fdbf24216","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":612,"license_type":"no_license","max_line_length":45,"num_lines":13,"path":"/알고리즘/온라인저지/2022/04/0410/짐 챙기는 숌.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N, M = map(int, input().split())\nif N > 0: # 담아야 할 책이 있으면\n books = list(map(int, input().split()))\n result = 1 # 상자를 하나 가져다 놓고\n box = M # 상자에 담을 수 있는 무게는 M\n for book in books: # 책들을 순회하면서\n box -= book # 상자에 책을 하나씩 담는다\n if box < 0: # 상자에 책을 담을 수 없으면\n box = M - book # 다음 상자를 가져와 책을 담고\n result += 1 # 상자 개수를 +1\nelse: # 담아야 할 책이 없으면\n result = 0 # 필요한 상자의 개수는 0\nprint(result)"},{"alpha_fraction":0.5694444179534912,"alphanum_fraction":0.5972222089767456,"avg_line_length":35.5,"blob_id":"5e2fe2a5437e66924459c3b5c46e2c545f46e2f7","content_id":"fb0fd3cfe6cc4fc499a9e1582326dfb327a5ddb3","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":72,"license_type":"no_license","max_line_length":37,"num_lines":2,"path":"/알고리즘/온라인저지/2022/02/0207/Hello Judge.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"for i in range(1, int(input())+1):\n print(f'Hello World, Judge {i}!')"},{"alpha_fraction":0.4193548262119293,"alphanum_fraction":0.43478259444236755,"avg_line_length":24.285715103149414,"blob_id":"631f204724be1a670b34bdbe17d146ee2ff5cafd","content_id":"c5477022311522dde65d7794260ce7e175e41b4b","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":713,"license_type":"no_license","max_line_length":45,"num_lines":28,"path":"/알고리즘/온라인저지/2021/12/1216/약수들의 합.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"while True:\n n = int(input())\n\n if n == -1:\n break\n\n measure_counts = [0 for _ in range(n+1)]\n measures = []\n\n for i in range(1, n+1):\n if not measure_counts[i]:\n if n % i == 0:\n measure_counts[i] = 1\n measure_counts[n//i] = 1\n measures.append(i)\n measures.append(n//i)\n\n measures.sort()\n\n if sum(measures[:len(measures)-1]) == n:\n print('{} = '.format(n), end='')\n for i in range(len(measures)-1):\n print(measures[i], end='')\n if i != len(measures)-2:\n print(' + ', end='')\n print() \n else:\n print('{} is NOT perfect.'.format(n))\n \n"},{"alpha_fraction":0.4487309753894806,"alphanum_fraction":0.46700507402420044,"avg_line_length":21.930233001708984,"blob_id":"e82d6603afa5da2de0463db4bbf39e0621a53c6c","content_id":"ee8b88e44c21ba4fabe914d3505608aa63897781","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":985,"license_type":"no_license","max_line_length":82,"num_lines":43,"path":"/알고리즘/온라인저지/2022/06/0629/적록색약.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"from collections import deque\nimport sys\n\n\ndef input():\n return sys.stdin.readline()\n\ndef bfs(i, j):\n q.append((i, j))\n now = arr[i][j]\n while q:\n y, x = q.popleft()\n visited[y][x] = 1\n for k in range(4):\n ny, nx = y+dy[k], x+dx[k]\n if 0<=ny<N and 0<=nx<N and not visited[ny][nx] and arr[ny][nx] == now:\n if (ny, nx) not in q:\n q.append((ny, nx))\n\n\ndx = [1, -1, 0, 0]\ndy = [0, 0, 1, -1]\nN = int(input())\narr = [list(input()) for _ in range(N)]\nNCB = 0 # Non Color Blindness\nCB = 0 # Color Blindness\nvisited = [[0]*N for _ in range(N)]\nq = deque()\nfor i in range(N):\n for j in range(N):\n if not visited[i][j]:\n bfs(i, j)\n NCB += 1\n if arr[i][j] in 'RG':\n arr[i][j] = 'Y'\nvisited = [[0]*N for _ in range(N)]\nq = deque()\nfor i in range(N):\n for j in range(N):\n if not visited[i][j]:\n bfs(i, j)\n CB += 1\nprint(NCB, CB)"},{"alpha_fraction":0.27398988604545593,"alphanum_fraction":0.3156565725803375,"avg_line_length":26.34482765197754,"blob_id":"13511a4d459a9c8cc73c79a5a9b4e690180c7dab","content_id":"dcd20864ad5c1b406836a139cab7c502c350d4a9","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":792,"license_type":"no_license","max_line_length":45,"num_lines":29,"path":"/알고리즘/SWEA/LEARN/Course/2. Programming Intermediate/2. 파이썬 SW문제해결 기본 List2/5차시 2일차 - 색칠하기.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"T = int(input())\n\nfor t in range(1, T+1):\n arr = [[0]*10 for _ in range(10)]\n N = int(input())\n for n in range(N):\n tmp = list(map(int, input().split()))\n r1 = tmp[0]\n c1 = tmp[1]\n r2 = tmp[2]\n c2 = tmp[3]\n \n for i in range(c1, c2+1):\n for j in range(r1, r2+1):\n if tmp[4] == 1:\n if arr[i][j] == 0:\n arr[i][j] = 1\n elif arr[i][j] == 2:\n arr[i][j] = 3\n else:\n if arr[i][j] == 0:\n arr[i][j] = 2\n elif arr[i][j] == 1:\n arr[i][j] = 3\n \n cnt = 0\n for a in arr:\n cnt += a.count(3)\n print('#{} {}'.format(t, cnt))"},{"alpha_fraction":0.3867403268814087,"alphanum_fraction":0.4806629717350006,"avg_line_length":19.22222137451172,"blob_id":"6b2ab27b4a2525c8359ebad206593023a920ccdb","content_id":"f434eccb490458f6dba43731400fe2eee5f7abed","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":181,"license_type":"no_license","max_line_length":41,"num_lines":9,"path":"/알고리즘/온라인저지/2023/06/0613/Vending Machine.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"result = 5000\nfor i in list(map(int, input().split())):\n if i == 1:\n result -= 500\n if i == 2:\n result -= 800\n if i == 3:\n result -= 1000\nprint(result)"},{"alpha_fraction":0.4347222149372101,"alphanum_fraction":0.4763889014720917,"avg_line_length":23.03333282470703,"blob_id":"7c84ee759fb606740b73fba316acad914bba8fe6","content_id":"7703df2598d60ad15636caea02e6a1900d898ae7","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":826,"license_type":"no_license","max_line_length":63,"num_lines":30,"path":"/알고리즘/온라인저지/2021/07/0731/바둑알 십자 뒤집기.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"num = 19\nboard = [[int(x) for x in input().split()] for y in range(num)]\n\nn = int(input())\n\npoints = []\nfor i in range(n): # 뒤집을 점들의 개수만큼\n a, b = map(int, input().split())\n points.append([a, b])\n # 입력 받아서 좌표들을 리스트로 저장\n \ndef cross(x, y): # 십자뒤집기 로직\n for i in range(19):\n if board[x-1][i] == 0: # 가로줄 0 -> 1, 1 -> 0\n board[x-1][i] = 1\n else:\n board[x-1][i] = 0\n if board[i][y-1] == 0: # 세로줄 0 -> 1, 1 -> 0\n board[i][y-1] = 1\n else:\n board[i][y-1] = 0\n return board\n\nfor point in points:\n cross(point[0], point[1]) # 좌표들 각각 십자뒤집기 실행\n\nfor i in range(19) :\n for j in range(19) : \n print(board[i][j], end=' ')\n print() # 출력문"},{"alpha_fraction":0.5121951103210449,"alphanum_fraction":0.5528455376625061,"avg_line_length":17.5,"blob_id":"e031ae14019c67b34994abd1c79038cac7fdf513","content_id":"d105034d93d06424410618a16d4d78cbc26cd513","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":369,"license_type":"no_license","max_line_length":40,"num_lines":20,"path":"/알고리즘/온라인저지/2021/12/1216/네 번째 점.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"xdots = [0 for _ in range(1001)]\nydots = [0 for _ in range(1001)]\n\nfor _ in range(3):\n x, y = map(int, input().split())\n xdots[x] += 1\n ydots[y] += 1\n\nresult = []\n\nfor xdot in xdots:\n if xdot == 1:\n result.append(xdots.index(xdot))\n\nfor ydot in ydots:\n if ydot == 1:\n result.append(ydots.index(ydot))\n\nfor r in result:\n print(r, end=' ')"},{"alpha_fraction":0.44262295961380005,"alphanum_fraction":0.5081967115402222,"avg_line_length":30,"blob_id":"010fbfd4bbf22c0e592821180288e6ac9992445c","content_id":"5e1aca49f575780f525c1526e381d54ab496a5e3","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":61,"license_type":"no_license","max_line_length":36,"num_lines":2,"path":"/알고리즘/온라인저지/2022/08/0824/РАВЕНСТВО.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = [int(input()) for _ in range(3)]\nprint((N[1]-N[2])//N[0])"},{"alpha_fraction":0.6334232091903687,"alphanum_fraction":0.6522911190986633,"avg_line_length":25.571428298950195,"blob_id":"ef7c60a74127183882dbef9b2df582a0b8811e42","content_id":"612047f27f063d514d94910c86fbad5c28ec2ac7","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":473,"license_type":"no_license","max_line_length":75,"num_lines":14,"path":"/알고리즘/[템플릿]/스택/옥상 정원 꾸미기.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\n\nstack = []\nresult = 0\nfor _ in [0]*int(input().rstrip()):\n height = int(input().rstrip())\n while stack and height>=stack[-1]: stack.pop() # 스택안의, 높이가 낮은 건물들 전부 삭제\n result += len(stack) # while문을 통과하고 스택에 남아있는 건물들은, 현재 건물의 옥상을 볼 수 있다\n stack.append(height) # 현재 건물 추가\nprint(result)\n\n# https://www.acmicpc.net/problem/6198"},{"alpha_fraction":0.4453781545162201,"alphanum_fraction":0.462184876203537,"avg_line_length":16,"blob_id":"d191d344d1772fa911791a9719ec5fbabd47ca89","content_id":"905e9f8858de030ab07f2fe3d9c069e3dc41c593","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":119,"license_type":"no_license","max_line_length":22,"num_lines":7,"path":"/알고리즘/온라인저지/2023/04/0417/골뱅이 찍기 - 뒤집힌 ㄱ.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = int(input())\nfor _ in range(N):\n print('@'*5*N)\n\nfor _ in range(4):\n for _ in range(N):\n print('@'*N)\n"},{"alpha_fraction":0.5378378629684448,"alphanum_fraction":0.5837838053703308,"avg_line_length":19.61111068725586,"blob_id":"cd4c0641d347168d0a81d56edce7c07bf640c3dd","content_id":"500281a035c64fff5186ade3d3c1da9e9296f8c9","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":370,"license_type":"no_license","max_line_length":45,"num_lines":18,"path":"/알고리즘/온라인저지/2022/09/0917/게임.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\n\nX, Y = map(int, input().rstrip().split())\nZ = int((Y*100/X))\nresult = -1\nstart, end = 1, int(1e9)\nwhile start<=end:\n mid = (start+end) // 2\n new_win_rate = int(((Y+mid)*100/(X+mid)))\n if new_win_rate>Z:\n result = mid\n end = mid-1\n else: start = mid+1\nprint(result)\n\n# https://www.acmicpc.net/problem/1072"},{"alpha_fraction":0.6126760840415955,"alphanum_fraction":0.6126760840415955,"avg_line_length":27.600000381469727,"blob_id":"7abf3a70da02db24fdd86d7ef1569e8f60001d0c","content_id":"a2a0f6c5447cd40d2fa344b31437a12512306dfa","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":142,"license_type":"no_license","max_line_length":39,"num_lines":5,"path":"/알고리즘/온라인저지/2022/06/0610/다리 놓기.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"from math import factorial as fact\n\nfor t in range(int(input())):\n N, M = map(int, input().split())\n print(fact(M)//(fact(N)*fact(M-N)))"},{"alpha_fraction":0.4444444477558136,"alphanum_fraction":0.4722222089767456,"avg_line_length":17.16666603088379,"blob_id":"a9b8a8100175d62d41cb14a60df0a31fff677889","content_id":"d7f600153bc46cc3837dd9c86a9242dd655c76dc","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":108,"license_type":"no_license","max_line_length":32,"num_lines":6,"path":"/알고리즘/온라인저지/2023/04/0405/AdivB - 3.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"A, B = map(int, input().split())\nC, D = A//B, A%B\nif A != 0 and D < 0:\n C, D = C+1, D-B\nprint(C)\nprint(D)"},{"alpha_fraction":0.5226939916610718,"alphanum_fraction":0.5710102319717407,"avg_line_length":25.30769157409668,"blob_id":"7ba113b810dcf22249633f575884d9ba159d2299","content_id":"c6942e3e6259beba02df84ebcc88092269eece56","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":963,"license_type":"no_license","max_line_length":79,"num_lines":26,"path":"/알고리즘/온라인저지/2022/09/0904/마라톤 1.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = int(input())\ncheck = [tuple(map(int, input().split())) for _ in range(N)]\nresult = 0\nfor i in range(N-1):\n A, B = check[i], check[i+1]\n result += abs(A[0]-B[0]) + abs(A[1]-B[1])\ndist = 0\nfor i in range(1, N-1):\n A, B, C = check[i-1], check[i], check[i+1]\n jump = abs(A[0]-C[0]) + abs(A[1]-C[1])\n no_jump = abs(A[0]-B[0]) + abs(A[1]-B[1]) + abs(B[0]-C[0]) + abs(B[1]-C[1])\n tmp = no_jump - jump\n dist = max(dist, tmp)\nprint(result - dist)\n\n\"\"\"\n구간을 점프할 때 얻을 수 있는 이익을 모아 테이블을 만든다\n예제에서 B를 점프했을 때 얻는 이익값이 6\nC를 점프했을 때 얻는 이익값이 4이다\n그러면 B를 점프하는게 동선을 가장 단축시킬 수 있고\n이 이익값 6을 전체 경로 20에서 빼주면 14가 나온다\n0번과 N-1번을 제외한 점들에서\n해당 점을 빼고 뛰었을 때 얻을 수 있는 이익값 테이블의\n최대값을\n전체 경로값에서 빼준다\n\"\"\""},{"alpha_fraction":0.4611872136592865,"alphanum_fraction":0.465753436088562,"avg_line_length":17.33333396911621,"blob_id":"967fd978ba580198d4f1630215bbcb42abf70020","content_id":"3cd1e346ece2d616aed71c4d71add1478699d8ad","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":219,"license_type":"no_license","max_line_length":32,"num_lines":12,"path":"/알고리즘/온라인저지/2022/02/0220/오타맨 고창영.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"T = int(input())\n\nfor t in range(T):\n typo, word = input().split()\n typo = int(typo)\n\n for i in range(len(word)):\n if i == typo-1:\n continue\n \n print(word[i], end='')\n print()"},{"alpha_fraction":0.6790123581886292,"alphanum_fraction":0.6790123581886292,"avg_line_length":26.33333396911621,"blob_id":"95d0e611b79f837cae23b6f73e2cb7c6dff29da7","content_id":"b7c51a149fbdc6c908443cc23a5cef1fef5a365f","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":81,"license_type":"no_license","max_line_length":52,"num_lines":3,"path":"/알고리즘/온라인저지/2022/02/0206/연세대학교.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"yonsei = ['YONSEI', 'Leading the Way to the Future']\n\nprint(yonsei[int(input())])"},{"alpha_fraction":0.4554140269756317,"alphanum_fraction":0.4792993664741516,"avg_line_length":22.296297073364258,"blob_id":"39b5423590f79a4e3321a43ab377de8dc30a8c26","content_id":"905d88d290dbbb081a227e2a05baf31392afb0fb","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":628,"license_type":"no_license","max_line_length":39,"num_lines":27,"path":"/알고리즘/온라인저지/2022/12/1221/별 찍기 - 19.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"def fill(arr):\n for k in range(0, size//2+1, 2):\n for i in range(k, size-k):\n arr[i][k] = 1\n\ndef rotate(arr):\n new_arr = []\n for j in range(size):\n tmp = []\n for i in range(size-1, -1, -1):\n tmp.append(arr[i][j])\n new_arr.append(tmp)\n return new_arr\n\nN = int(input())\nsize = 1\nfor _ in range((N-1)*2): size += 2\narr = [[0]*size for _ in range(size)]\nfor _ in range(4):\n fill(arr)\n arr = rotate(arr)\nfor i in range(size):\n for j in range(size):\n if arr[i][j]:\n print('*', end='')\n else: print(' ', end='')\n if i != size-1: print()"},{"alpha_fraction":0.5810526609420776,"alphanum_fraction":0.6084210276603699,"avg_line_length":19.69565200805664,"blob_id":"c39366f266d2dcc4360ea6ae5155c4c3c7309c63","content_id":"19dc3a718fec769ac295364e41313ae87ee6eeea","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":475,"license_type":"no_license","max_line_length":41,"num_lines":23,"path":"/알고리즘/온라인저지/2022/10/1002/정수 a를 k로 만들기.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\nfrom collections import deque\n\ninput = sys.stdin.readline\n\ndef move(next, new_cnt):\n if 0<=next<mxl and not visited[next]:\n Q.append((next, new_cnt))\n visited[next] = 1\n\nA, K = map(int, input().rstrip().split())\nmxl = int(1e6)+1 # max_length\nvisited = [0]*mxl\nQ = deque()\nQ.append((A, 0))\nvisited[A] = 1\nresult = 0\nwhile Q:\n now, cnt = Q.popleft()\n if now == K: result = cnt; break\n move(now+1, cnt+1)\n move(now*2, cnt+1)\nprint(result)"},{"alpha_fraction":0.3992537260055542,"alphanum_fraction":0.41791045665740967,"avg_line_length":16.933332443237305,"blob_id":"04235cfffc577a348d6e139b2c5008be68e466ee","content_id":"64c696378d5ea916b5f63b7120f057979f9e7301","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":268,"license_type":"no_license","max_line_length":25,"num_lines":15,"path":"/알고리즘/온라인저지/2021/08/0819/제로.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"K = int(input())\nstack = []\ntop = -1\nfor k in range(K):\n num = int(input())\n if num == 0:\n if top == -1:\n continue\n else:\n stack.pop()\n top -= 1\n else:\n stack.append(num)\n top += 1\nprint(sum(stack))"},{"alpha_fraction":0.4109589159488678,"alphanum_fraction":0.4931506812572479,"avg_line_length":36,"blob_id":"4f25ba821a074fd89a640514f11ce01121b63480","content_id":"fb89847feee8c83fcf67b87caae0f2c3539dd923","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":73,"license_type":"no_license","max_line_length":36,"num_lines":2,"path":"/알고리즘/온라인저지/2022/09/0904/移動 (Moving).py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"H = [int(input()) for _ in range(3)]\nprint(int(H[0] + H[1] < H[2] + 0.5))"},{"alpha_fraction":0.4285714328289032,"alphanum_fraction":0.5428571701049805,"avg_line_length":35,"blob_id":"313ed2e7b33735e25b1d17d812d33d06be4bedc5","content_id":"593b64b86972e231183efb09b400a508dd001149","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":35,"license_type":"no_license","max_line_length":35,"num_lines":1,"path":"/알고리즘/온라인저지/2023/02/0226/Atrium.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"print(f'{int(input())**0.5*4:.8f}')"},{"alpha_fraction":0.4540654718875885,"alphanum_fraction":0.47729673981666565,"avg_line_length":26.882352828979492,"blob_id":"8eaa5f70aadd78318ed44b147304f96b8418c845","content_id":"a7b5330e01fc9167e8980ca0e095d89e915b7ec6","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1207,"license_type":"no_license","max_line_length":58,"num_lines":34,"path":"/알고리즘/온라인저지/2022/07/0709/단지번호붙이기.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"from collections import deque\n\n\ndef bfs(y, x): # 단지 내 가구 수 탐색 BFS\n Q.append((y, x))\n cnt = 0\n while Q:\n y, x = Q.popleft()\n if arr[y][x] == 0: # Q에 넣어놓은 사이에 탐색을 마친 경우라면\n continue # 컨티뉴\n arr[y][x] = 0 # 해당 위치 탐색 완료\n cnt += 1 # 단지 내 가구 수 ++\n for i in range(4):\n ny = y+dy[i]\n nx = x+dx[i]\n if 0<=ny<N and 0<=nx<N and arr[ny][nx]: \n # 지도의 범위를 벗어나지 않으면서 이웃한 단지이면\n Q.append((ny, nx))\n return cnt # 단지 내 가구 수 반환\n\n\ndy = [-1, 1, 0, 0] # 상하좌우 4방향 델타이동\ndx = [0, 0, -1, 1]\nN = int(input())\narr = [list(map(int, list(input()))) for _ in range(N)]\nresult = [0] # 단지 수 0으로 초기화\nQ = deque()\nfor i in range(N):\n for j in range(N):\n if arr[i][j]: # 단지를 발견하면\n result.append(bfs(i, j)) # 탐색한 단지내 가구수 추가\n result[0] += 1 # 단지 수 ++\nprint(result[0]) # 단지 수 출력\nfor r in sorted(result[1:]): print(r) # 단지내 가구수를 오름차순으로 출력"},{"alpha_fraction":0.3693181872367859,"alphanum_fraction":0.38825756311416626,"avg_line_length":36.78571319580078,"blob_id":"8c9678063190b9f1e63ec12bdc97abfeb2263c11","content_id":"1142953ef6ff9b7a540eae3582247ce7e8b25916","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":676,"license_type":"no_license","max_line_length":71,"num_lines":14,"path":"/알고리즘/온라인저지/2021/12/1216/소인수분해.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"n = int(input()) # 소수를 찾을 범위\na = [False,False] + [True]*(n-1) # 0 ~ n 까지의 숫자 리스트\nprimes=[] # 소수 집합\nfor i in range(2,n+1): # 2 ~ n까지 반복\n if a[i]: # 2부터 시작, 해당 숫자가 지워지지 않고 남아있는 소수라면 \n primes.append(i) # 소수 리스트에 추가\n for j in range(2*i, n+1, i): # 해당 소수의 배수들을 \n a[j] = False # 리스트에서 전부 False로 만들기\n\nwhile n != 1:\n for p in primes:\n while n % p == 0:\n n //= p\n print(p)"},{"alpha_fraction":0.45864662528038025,"alphanum_fraction":0.4736842215061188,"avg_line_length":18.14285659790039,"blob_id":"10db02c0ab7a4822915bf76ca9f6399ab3b3ddfb","content_id":"f18b068108ff0f4ebdbd33d92b9b10e48e5d27bb","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":133,"license_type":"no_license","max_line_length":32,"num_lines":7,"path":"/알고리즘/온라인저지/2023/03/0312/좋은 암호.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"K, L = map(int, input().split())\nfor i in range(2, L):\n if K%i == 0:\n print('BAD', i)\n break\nelse:\n print('GOOD')"},{"alpha_fraction":0.420634925365448,"alphanum_fraction":0.43386244773864746,"avg_line_length":15.47826099395752,"blob_id":"4d0b96b49d19e5b5eb9a79f8971434bfac227d8a","content_id":"9e0c88b23a862a35ac6b310d1c68842b7e107d83","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":378,"license_type":"no_license","max_line_length":50,"num_lines":23,"path":"/알고리즘/온라인저지/2022/10/1029/운동.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\n\nN, m, M, T, R = map(int, input().rstrip().split())\nn = 0\nresult = 0\nnow = m\nwhile n < N:\n result += 1\n # print(result, now, T, R)\n if m+T > M:\n result = -1\n break\n if now+T <= M:\n n += 1\n now += T\n else:\n if now-R <= m:\n now = m\n else:\n now -= R\nprint(result)"},{"alpha_fraction":0.625,"alphanum_fraction":0.637499988079071,"avg_line_length":19.25,"blob_id":"6ab283b7dcc96735afa323d87ab2139368e0be4e","content_id":"2d5077a69bf35f042ca70744cf5847acb44fd2cf","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":80,"license_type":"no_license","max_line_length":23,"num_lines":4,"path":"/알고리즘/온라인저지/2022/04/0415/자동완성.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"result = 'Naver Whale'\nif input() in 'Nn':\n result = 'Naver D2'\nprint(result)"},{"alpha_fraction":0.5079872012138367,"alphanum_fraction":0.5143769979476929,"avg_line_length":17.47058868408203,"blob_id":"fee8332a08be4e0c364f804ca7b9dee182e1c746","content_id":"4823b245763595b360c87c906a4adb37884eda5a","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":331,"license_type":"no_license","max_line_length":32,"num_lines":17,"path":"/알고리즘/온라인저지/2022/07/0722/라디오.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"A, B = map(int, input().split())\nN = int(input())\nF = [] # favorite\nR = A # radio\nfor n in range(N):\n F.append(int(input()))\nminn = abs(B-R)\nfor f in F:\n tmp = abs(B-f)\n if tmp < minn: \n minn = tmp\n R = f\nresult = 0\nif R != A: # 즐겨찾기를 한 번 누름\n result += 1\nresult += abs(B-R)\nprint(result)"},{"alpha_fraction":0.443708598613739,"alphanum_fraction":0.4768211841583252,"avg_line_length":20.64285659790039,"blob_id":"f786c31298689b338d27f9a92c05a6b04f981980","content_id":"2456cab5309ea7429c0d841ea752d155bcc7204e","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":302,"license_type":"no_license","max_line_length":45,"num_lines":14,"path":"/알고리즘/온라인저지/2023/02/0216/수찬은 마린보이야!!.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = int(input())\ntry:\n records = list(map(int, input().split()))\n dp = [0]*101\n A = sum(records)/N\n for record in records:\n dp[record] += 1\n B = 0\n for i in range(101):\n if dp[i]:\n B += i * (dp[i]/N)\n print(f'{A/B:.2f}')\nexcept:\n print('divide by zero')"},{"alpha_fraction":0.41951218247413635,"alphanum_fraction":0.4390243887901306,"avg_line_length":24.75,"blob_id":"c0077997e9895fb7f22c3ef1413c0107aaa2753e","content_id":"b0e9dbda375290f7ce75dbf967bf1d3fafcefbf4","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":205,"license_type":"no_license","max_line_length":36,"num_lines":8,"path":"/알고리즘/온라인저지/2022/06/0612/0의 개수.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"for t in range(int(input())):\n N, M = map(int, input().split())\n result = 0\n for a in range(N, M+1):\n for b in str(a):\n if b == '0':\n result += 1\n print(result)"},{"alpha_fraction":0.42491209506988525,"alphanum_fraction":0.43897539377212524,"avg_line_length":30.619047164916992,"blob_id":"a1c33e2efa84eb561f7805fc7c22f7176a2226f5","content_id":"0d216d0f2d182c4901c28750870eab30848710d9","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":2481,"license_type":"no_license","max_line_length":60,"num_lines":63,"path":"/알고리즘/온라인저지/2022/03/0315/후보 추천하기.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = int(input())\nK = int(input())\npicks = list(map(int, input().split())) # 추천 후보\n\nresult = []\n\n# [후보번호, 추천수, 등록시간]\nfor i in range(K):\n # print(result)\n if len(result) < N: # 사진틀이 남았을 때\n # 이미 있는 후보를 추천하는지 확인\n in_result = False\n idx = 0\n for k in range(len(result)):\n if picks[i] == result[k][0]:\n in_result = True\n idx = k\n\n if not in_result: # 이미 있는 후보가 아닐 경우\n result.append([picks[i], 1, i]) # 후보 추가\n else: # 있는 후보일 경우\n result[idx][1] += 1 # 추천 +1\n \n else: # 사진틀이 남지 않았을 때\n # 이미 있는 후보를 추천하는지 확인\n in_result = False\n idx = 0\n for k in range(N):\n if picks[i] == result[k][0]:\n in_result = True\n idx = k\n\n if not in_result: # 이미 있는 후보가 아닐 경우\n # 후보 사진을 갈아끼워야 함\n recommended = 10**3 # 가상의 추천수 최대값\n recommend_idx = 0 # 가장 추천을 많이 받은 후보의 인덱스\n oldest_time = 10**3 # 가상의 등록순서 최대값\n oldest_idx = 0 # 가장 오래전에 등록된 후보의 인덱스\n for j in range(N): # 후보 사진들 중\n # 추천이 가장 적은 후보 찾기\n if result[j][1] < recommended:\n recommended = result[j][1]\n recommend_idx = j\n # 동시에 그 후보의 등록시간도 기록\n oldest_time = result[j][2]\n oldest_idx = j\n\n # 추천수가 가장 적은 후보가 여러명일 때\n elif result[j][1] == recommended:\n # 등록시간이 오래된 후보를 찾아서\n if oldest_time > result[j][2]:\n oldest_time = result[j][2]\n oldest_idx = j\n recommend_idx = oldest_idx # 인덱스 잡고\n # print(recommend_idx)\n result[recommend_idx] = [picks[i], 1, i] # 덮어씌우기\n else: # 있는 후보일 경우\n result[idx][1] += 1 # 추천 +1\n # print(result)\n\nresult.sort(key=lambda x:x[0]) # 후보번호순 정렬\nfor r in result:\n print(r[0], end=' ') # 출력"},{"alpha_fraction":0.504273533821106,"alphanum_fraction":0.504273533821106,"avg_line_length":13.75,"blob_id":"bc77b127a60d63d2c8fa532fe06e2044be22119b","content_id":"ed4d430c0d4f8210b3f129b87f46b5a7bdabd75e","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":117,"license_type":"no_license","max_line_length":35,"num_lines":8,"path":"/알고리즘/온라인저지/2022/02/0202/파티가 끝나고 난 뒤.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"L, P = map(int, input().split())\n\na = list(map(int, input().split()))\n\ns = L * P\n\nfor i in a:\n print(i-s, end=' ')"},{"alpha_fraction":0.4020356237888336,"alphanum_fraction":0.4452926218509674,"avg_line_length":16.909090042114258,"blob_id":"d549458b9e9d63a94f3b195afa84cadc1e4196f4","content_id":"df21e5d886025b7a16483e2444febe214707943c","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":393,"license_type":"no_license","max_line_length":62,"num_lines":22,"path":"/알고리즘/온라인저지/2021/08/0829/자리배정.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\nC, R = map(int, sys.stdin.readline().split())\nK = int(sys.stdin.readline())\n\ndx = [0, 1, 0, -1]\ndy = [1, 0, -1, 0]\n\nhall = [[0]*C for _ in range(R)]\ni = 1\nx = y = k = 0\n\nwhile i < K:\n hall[y][x] = i\n i += 1\n if x+dx[k] >= C or y+dy[k] >= R or hall[y+dy[k]][x+dx[k]]:\n k = (k+1)%4\n x = (x+dx[k])\n y = (y+dy[k])\nif C*R < K:\n print(0)\nelse:\n print(x+1, y+1)"},{"alpha_fraction":0.5452961921691895,"alphanum_fraction":0.5522648096084595,"avg_line_length":29.263158798217773,"blob_id":"928021474cba99457c8b2b04dbd173afa07b11c6","content_id":"7af088e857095e87d905978c083f85dad85a7720","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":744,"license_type":"no_license","max_line_length":60,"num_lines":19,"path":"/알고리즘/온라인저지/2022/11/1127/N과 M (6).py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\n\ndef dfs(start):\n if len(result) == M: # 수열이 완성됐다면\n print(*result) # 완성된 수열 출력\n # 이번 함수가 종료되고 나오면서 line14의 result.pop()에서 마지막 숫자 제거\n else: # 아직 수열이 완성되지 않았다면\n for i in range(start, N): # 수열에 더 들어올 남은 숫자 개수만큼 for\n if nums[i] not in result:\n result.append(nums[i]) # nums[i]를 집어넣고\n dfs(i+1) # 더 깊이 탐색\n result.pop() # 방금 넣었던 nums[i]를 빼주기\n\nN, M = map(int, input().rstrip().split())\nnums = sorted(list(map(int, input().rstrip().split())))\nresult = []\ndfs(0)"},{"alpha_fraction":0.5398229956626892,"alphanum_fraction":0.5575221180915833,"avg_line_length":27.33333396911621,"blob_id":"4e86b5df9ba8ea8532729f1fd18c3c26e12a8924","content_id":"32fe6f431a0b351431b794a7a2608bd391a40d1f","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":339,"license_type":"no_license","max_line_length":42,"num_lines":12,"path":"/알고리즘/온라인저지/2022/09/0910/카드게임.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"A_card = list(map(int, input().split()))\nB_card = list(map(int, input().split()))\nA_win = B_win = draw = 0\nfor i in range(10):\n if A_card[i] > B_card[i]: A_win += 1\n elif A_card[i] < B_card[i]: B_win += 1\n else: draw += 1\nresult = ''\nif A_win > B_win: result = 'A'\nelif A_win < B_win: result = 'B'\nelse: result = 'D'\nprint(result)"},{"alpha_fraction":0.37383177876472473,"alphanum_fraction":0.44859811663627625,"avg_line_length":20.600000381469727,"blob_id":"dc3a2207bd6485006fb527f212e2f695d46ee3d5","content_id":"86462cc82ad1dcfbdd0fa21605b722002876decd","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":107,"license_type":"no_license","max_line_length":33,"num_lines":5,"path":"/알고리즘/온라인저지/2023/01/0130/2018 연세대학교 프로그래밍 경진대회.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = int(input())\nfor k in range(1, 10101):\n if eval('k**2 + k + 1') == N:\n print(k)\n break"},{"alpha_fraction":0.47663551568984985,"alphanum_fraction":0.514018714427948,"avg_line_length":20.600000381469727,"blob_id":"8a4db5b859392937afc961ffa35a0e1d8a018746","content_id":"ae664d974a4a4ea3c56059c66c0bc4c8296ea733","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":107,"license_type":"no_license","max_line_length":31,"num_lines":5,"path":"/알고리즘/온라인저지/2022/05/0519/양수 개수 세기.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"result = 0\nfor i in list(input().split()):\n if i[0] not in ('-', '0'):\n result += 1\nprint(result)"},{"alpha_fraction":0.5199999809265137,"alphanum_fraction":0.5400000214576721,"avg_line_length":27.714284896850586,"blob_id":"b703a8efae28754d8127f136866de4f9b23a9c52","content_id":"22d045fcfe189f3c1596b8d78964656cbc652c91","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":200,"license_type":"no_license","max_line_length":56,"num_lines":7,"path":"/알고리즘/온라인저지/2023/02/0212/바구니 뒤집기.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N, M = map(int, input().split())\nresult = list(range(1, N+1))\nfor m in range(M):\n i, j = map(int, input().split())\n i -= 1\n result = result[:i] + result[i:j][::-1] + result[j:]\nprint(*result)"},{"alpha_fraction":0.5879828333854675,"alphanum_fraction":0.5879828333854675,"avg_line_length":22.399999618530273,"blob_id":"9934fd38e46d4c4fa6f3f55fefe0f20e43da3bf0","content_id":"706fd732dc605207a0d99700cdd9217075dd96f7","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":233,"license_type":"no_license","max_line_length":45,"num_lines":10,"path":"/알고리즘/온라인저지/2022/11/1106/대회 자리.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\n\nfor _ in range(int(input().rstrip())):\n P, M = map(int, input().rstrip().split())\n result = set()\n for p in range(P):\n result.add(int(input().rstrip()))\n print(P-len(result))"},{"alpha_fraction":0.4575645625591278,"alphanum_fraction":0.4944649338722229,"avg_line_length":14.11111068725586,"blob_id":"3b9fe55baa92335e61f7a37fb05ca6950d9a59ec","content_id":"e4ba9d5c888fb9e574cb45970da91608383f4de6","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":271,"license_type":"no_license","max_line_length":25,"num_lines":18,"path":"/알고리즘/온라인저지/2022/02/0209/특별한 날.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"M = int(input())\nD = int(input())\n\nresult = ''\n\nif M == 2 and D == 18:\n result = 'Special'\nelif M < 2:\n result = 'Before'\nelif M > 2:\n result = 'After'\nelif M == 2:\n if D < 18:\n result = 'Before'\n elif D > 18:\n result = 'After'\n\nprint(result)"},{"alpha_fraction":0.5528455376625061,"alphanum_fraction":0.5691056847572327,"avg_line_length":23.799999237060547,"blob_id":"b64a9e3afc161dd5947328d2ccd9b7b7e496658f","content_id":"2787e3ca5e3b14d2e7ece980ae690358a87bbfd3","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":123,"license_type":"no_license","max_line_length":33,"num_lines":5,"path":"/알고리즘/온라인저지/2022/08/0822/Julka.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"A = int(input()) # apple\nG = int(input()) # gap\nKlaudia = (A-G)//2 + G\nNatalia = (A-G)//2\nprint(Klaudia, Natalia, sep='\\n')"},{"alpha_fraction":0.40716612339019775,"alphanum_fraction":0.4527687430381775,"avg_line_length":17.117647171020508,"blob_id":"2eca37b61d7bafe52a8016d0fbf9e42d275383a8","content_id":"800e905d6d85f9b3fff1857dc0a2769ddae40095","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":307,"license_type":"no_license","max_line_length":46,"num_lines":17,"path":"/알고리즘/온라인저지/2022/12/1204/카드 구매하기.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = int(input())\ncards = list(map(int, input().split()))\ndp = [0]*(N+1)\nfor i in range(1, N+1):\n for j in range(i):\n dp[i] = max(dp[i], dp[j]+cards[i-j-1])\nprint(dp[-1])\n\n\"\"\"\ndp[i] = max(\n dp[1] + cards[i-1],\n dp[2] + cards[i-2],\n ...\n dp[i-2] + cards[2],\n dp[i-1] + cards[1],\n)\n\"\"\""},{"alpha_fraction":0.34794774651527405,"alphanum_fraction":0.4048507511615753,"avg_line_length":21.82978630065918,"blob_id":"633db1042372d0c4efcabbc0507c33465347af29","content_id":"84d26e16237db07662ec7f66a36bfced49b387b8","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1072,"license_type":"no_license","max_line_length":58,"num_lines":47,"path":"/알고리즘/프로그래머스/Level1/신규 아이디 추천.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"def solution(new_id):\n answer = ''\n # print(new_id)\n new_id = new_id.lower()\n tmp = ''\n \n for n in new_id: # step 2\n if n in 'abcdefghijklmnopqrstuvwxyz0123456789-_.':\n tmp = tmp + n\n switch = False\n tmp2 = ''\n \n for t in tmp: # step 3\n if t == '.':\n if not switch:\n switch = True\n tmp2 = tmp2 + t\n else:\n tmp2 = tmp2 + t\n if switch:\n switch = False\n # print('step3', tmp2)\n \n if len(tmp2) >= 2:\n if tmp2[0] == '.': # step 4\n tmp2 = tmp2[1:]\n if tmp2[-1] == '.':\n tmp2 = tmp2[:len(tmp2)-1]\n else:\n tmp2 = ''\n # print('step4', tmp2)\n \n if tmp2 == '': # step 5\n tmp2 = 'a'\n \n if len(tmp2) >= 16: # step 6\n tmp2 = tmp2[:15]\n if tmp2[-1] == '.':\n tmp2 = tmp2[:len(tmp2)-1]\n \n while len(tmp2) <= 2: # step 7\n tmp2 = tmp2 + tmp2[-1]\n \n answer = tmp2\n return answer\n\nprint(solution(input()))"},{"alpha_fraction":0.5703883767127991,"alphanum_fraction":0.5800970792770386,"avg_line_length":23.235294342041016,"blob_id":"f79e58b556b0778ac092216898033296daf91886","content_id":"620accbf8bdc7777fca0f32d1030651d97b3a867","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":412,"license_type":"no_license","max_line_length":36,"num_lines":17,"path":"/알고리즘/온라인저지/2022/03/0329/맞았는데 왜 틀리죠.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"S1, S2 = map(int, input().split())\nresult = 'Accepted'\nis_wrong_answer = False\nis_why_wrong = False\nfor s in range(S1):\n A, B = map(int, input().split())\n if A != B:\n is_wrong_answer = True\nfor s in range(S2):\n A, B = map(int, input().split())\n if A != B:\n is_why_wrong = True\nif is_wrong_answer:\n result = 'Wrong Answer'\nelif is_why_wrong:\n result = 'Why Wrong!!!'\nprint(result)\n"},{"alpha_fraction":0.529411792755127,"alphanum_fraction":0.5441176295280457,"avg_line_length":33.5,"blob_id":"254eb6e75ec447388270de7ba79dc8a522fdb0a1","content_id":"a1ea7e94ac60a7be519ef0ed1e5e0f0ee06a771f","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":68,"license_type":"no_license","max_line_length":35,"num_lines":2,"path":"/알고리즘/온라인저지/2023/04/0402/Piece of Cake.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N, H, V = map(int, input().split())\nprint(max(N-H, H)*max(N-V, V)*4)"},{"alpha_fraction":0.46859902143478394,"alphanum_fraction":0.49275362491607666,"avg_line_length":22.11111068725586,"blob_id":"4ef3b33cfe25d3270e15b91a347fcc812901b50e","content_id":"feff1f3d4a405339384f173ed943fe42ffdffc8f","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":207,"license_type":"no_license","max_line_length":35,"num_lines":9,"path":"/알고리즘/온라인저지/2022/05/0512/앵그리 창영.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N, W, H = map(int, input().split())\nmax_match = W**2 + H**2\nresult = ['DA', 'NE']\nfor n in range(N):\n M = int(input())\n if M**2 <= max_match:\n print(result[0])\n else:\n print(result[1])"},{"alpha_fraction":0.5070063471794128,"alphanum_fraction":0.522292971611023,"avg_line_length":36.39682388305664,"blob_id":"82af38fbd1673953956c2203c119d5583a6aadd0","content_id":"8622017e0465f39f96ac027c8e280cd75f66ef74","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":2997,"license_type":"no_license","max_line_length":85,"num_lines":63,"path":"/알고리즘/온라인저지/2022/11/1119/로봇 시뮬레이션.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\n\ndirection_to_index = { # NESW를 0123으로 바꿔서 델타이동을 아래와 같이 할 것\n 'N': 0,\n 'E': 1,\n 'S': 2,\n 'W': 3,\n}\ndy, dx = [-1, 0, 1, 0], [0, 1, 0, -1]\n\nA, B = map(int, input().rstrip().split())\narr = [[-1]*A for _ in range(B)]\nN, M = map(int, input().rstrip().split())\nrobot_location = [(0, 0) for _ in range(N+1)] # n번 로봇의 좌표를 (y,x)꼴로 담을 배열 공간 N+1개만큼 생성\nfor n in range(1, N+1):\n x, y, direction = input().rstrip().split()\n # 예제처럼 왼쪽아래를 1,1로 두기 위해 아래와 같이 y좌표를 바꿔서 집어넣는다\n x, y, direction = int(x)-1, B-(int(y)), direction_to_index[direction]\n robot = n # 로봇 번호\n arr[y][x] = direction # 원본 배열에는 로봇이 바라보는 방향을 집어넣는다\n robot_location[robot] = (y, x)\n# 디버깅\n# for a in arr: print(a) \n# print()\norders = [] # 입력은 일단 다 받기 위해 리스트 생성\nfor m in range(M):\n robot, command, loop = input().rstrip().split()\n robot, loop = int(robot), int(loop)\n orders.append((robot, command, loop))\nresult = 'OK' # 명령들을 이상없이 수행하면 출력할 OK\nfor order in orders:\n if result != 'OK': break # 뭔가 심상치 않은 일이 생긴거야~\n robot, command, loop = order # ex) 1 F 3\n y, x = robot_location[robot] # 명령으로 들어온 로봇이 현재 배열에 위치한 좌표 y, x\n direction = arr[y][x] # 로봇이 보고 있는 방향\n if command == 'R': # 오른쪽으로 돌리고~\n arr[y][x] += loop\n arr[y][x] %= 4\n elif command == 'L': # 왼쪽으로 돌리고~\n for i in range(loop):\n arr[y][x] = (arr[y][x]+3)%4 # 오른쪽으로 세 번 돌린 것과 같다\n else: # 앞으로 가자!\n for i in range(loop):\n if result != 'OK': break # 뭔가 심상치 않은 일이 생긴거야~\n ny, nx = y+dy[direction], x+dx[direction] # 로봇의 다음 이동할 좌표\n if not (0<=ny<B) or not (0<=nx<A): # 벽에 부딪혔다 == 범위를 벗어났다\n result = f'Robot {robot} crashes into the wall'\n elif arr[ny][nx] != -1: # 다른 로봇과 부딪혔다\n crashed_robot = 0 # 부딪힌 로봇의 번호 초기화\n for n in range(N+1): # 부딧힌 로봇의 번호를 찾자\n if robot_location[n] == (ny, nx): # 로봇들 중 ny,nx에 위치한 로봇의 인덱스\n crashed_robot = n\n result = f'Robot {robot} crashes into robot {crashed_robot}'\n else: # 이상없이 앞으로 갈 수 있다\n arr[y][x], arr[ny][nx] = arr[ny][nx], arr[y][x] # 한 칸 앞으로\n y, x = ny, nx # 로봇의 새 좌표로 갱신\n robot_location[robot] = (y, x) # 로봇 좌표모음 배열도 갱신\n # 디버깅\n # for a in arr: print(a)\n # print()\nprint(result)"},{"alpha_fraction":0.4356435537338257,"alphanum_fraction":0.4752475321292877,"avg_line_length":19.399999618530273,"blob_id":"15ff4d94e1891fe0b220191d9a09ad265789c018","content_id":"343b101c94ec5dd399e1084be5e347259dbf1479","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":101,"license_type":"no_license","max_line_length":32,"num_lines":5,"path":"/알고리즘/온라인저지/2022/08/0822/AFC 윔블던.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N, M = map(int, input().split())\nif (N+M)%2 or N<M:\n print(-1)\nelse:\n print((N+M)//2, (N-M)//2)"},{"alpha_fraction":0.4752941131591797,"alphanum_fraction":0.4964706003665924,"avg_line_length":21.421052932739258,"blob_id":"a7c209f5e5c48c2d014adf5c1c83a19f38559c80","content_id":"51d7f086064c595f90c3542c1a319a6b6c8a859f","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":425,"license_type":"no_license","max_line_length":55,"num_lines":19,"path":"/알고리즘/온라인저지/2022/10/1002/The Game of Death.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\n\nfor _ in [0]*int(input().rstrip()):\n result = 0\n N = int(input().rstrip())\n death = [int(input().rstrip())-1 for _ in range(N)]\n visited = [0]*N\n i = 0\n flag = True\n while i != N-1:\n if not visited[i]:\n visited[i] = 1\n i = death[i]\n result += 1\n else: flag = False; break\n if flag: print(result)\n else: print(0)"},{"alpha_fraction":0.5112782120704651,"alphanum_fraction":0.5413534045219421,"avg_line_length":25.600000381469727,"blob_id":"19c40a7828639ff75b327da66f9547ea3800d701","content_id":"e5fdab905d504f98992f4b6656d19555e911996e","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":133,"license_type":"no_license","max_line_length":37,"num_lines":5,"path":"/알고리즘/온라인저지/2022/09/0910/등장하지 않는 문자의 합.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"for _ in range(int(input())):\n result = sum(list(range(65, 91)))\n for i in input():\n result -= ord(i)\n print(result)\n"},{"alpha_fraction":0.43292683362960815,"alphanum_fraction":0.4491869807243347,"avg_line_length":19.54166603088379,"blob_id":"2c63a28fe7a01d76b65f641c60fd21c4d7f51f38","content_id":"f22c3b4d9b547bd987fb6371e0dd408d042efc08","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":492,"license_type":"no_license","max_line_length":39,"num_lines":24,"path":"/알고리즘/온라인저지/2022/09/0910/공약수.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"def gcd(a, b):\n while b > 0:\n a, b = b, a%b\n return a\n\nN = int(input())\nGCD = 0\nif N == 2:\n A, B = map(int, input().split())\n GCD = gcd(A, B)\nelse:\n A, B, C = map(int, input().split())\n GCD = gcd(gcd(A, B), gcd(B, C))\nresult = []\nfor i in range(1, int(GCD**0.5)+1):\n if GCD%i == 0:\n A, B = GCD//i, i\n if A != B:\n result.append(A)\n result.append(B)\n else:\n result.append(A)\nfor i in sorted(result):\n print(i)"},{"alpha_fraction":0.5858823657035828,"alphanum_fraction":0.5976470708847046,"avg_line_length":19.285715103149414,"blob_id":"dc7f0693262fb040c1a57c1bf4ed3d3c04a7956f","content_id":"a127e9330295a096304ebce14da7e7d9f0021771","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":677,"license_type":"no_license","max_line_length":59,"num_lines":21,"path":"/알고리즘/온라인저지/2022/08/0816/한조서열정리하고옴ㅋㅋ.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = int(input())\nlst = list(map(int, input().split()))\nA, result, cnt = 0, 0, 0 # archor\nfor l in lst:\n # 봉우리 높이 갱신, 임시값 초기화, 결과값 갱신\n if l > A: A, cnt, result = l, 0, max(result, cnt)\n else: cnt += 1\nprint(max(result, cnt)) # 봉우리를 갱신하지 않고 for문이 끝난 경우가 있을 수 있음\n\n\"\"\"\n그리디 문제\n출발한 높이보다 더 높은 봉우리에 부딪히기 전까지\n몇개의 봉우리를 만나는지\n가장 많이 만난 봉우리의 수는 몇인지를 구하는 문제\n\n최소최대값 갱신을 여태\nif a > b: a = b\n를 사용했었는데\na = max(a, b)\n로 바꾸는 것도 좋을 것 같다\n\"\"\""},{"alpha_fraction":0.4749034643173218,"alphanum_fraction":0.5057914853096008,"avg_line_length":18.961538314819336,"blob_id":"8592907d76f8a09548097e8a7e07eb5c86cc7c84","content_id":"d7f797841e08c56ee866d5b22de0da9bb67ad66c","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":518,"license_type":"no_license","max_line_length":59,"num_lines":26,"path":"/알고리즘/온라인저지/2022/03/0325/이게 분수.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import copy\n\n\ndef rotate():\n global arr\n new = []\n for j in range(2):\n tmp = []\n for i in range(1, -1, -1):\n tmp.append(arr[i][j])\n new.append(tmp)\n arr = copy.deepcopy(new)\n\narr = [list(map(int, input().split())) for _ in range(2)]\n# print(arr)\nmaxx = 0\nresult = 0\n# rotate()\nfor i in range(4):\n A, B, C, D = arr[0][0], arr[0][1], arr[1][0], arr[1][1]\n fraction = A/C + B/D\n if fraction > maxx:\n maxx = fraction\n result = i\n rotate()\nprint(result)"},{"alpha_fraction":0.47598254680633545,"alphanum_fraction":0.49344977736473083,"avg_line_length":24.5,"blob_id":"67a6e7d6c2e588e28270de8ddc61ca99652a8708","content_id":"6368c60cfea3a9e5c11ce12cf1e3d0d203d9c6ba","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":458,"license_type":"no_license","max_line_length":42,"num_lines":18,"path":"/알고리즘/온라인저지/2022/10/1012/골드바흐의 추측.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"n = int(1e4)\na = [False,False] + [True]*(n-1)\nprimes = []\nfor i in range(2, n+1):\n if a[i]:\n primes.append(i)\n for j in range(2*i, n+1, i):\n a[j] = False\nfor t in range(int(input())):\n N = int(input())\n result = []\n for prime in primes:\n if prime > N: break\n if N-prime in primes:\n tmp = sorted((N-prime, prime))\n if tmp not in result:\n result.append(tmp)\n print(*result[-1])"},{"alpha_fraction":0.5074999928474426,"alphanum_fraction":0.5450000166893005,"avg_line_length":21.27777862548828,"blob_id":"8c69bc58f58f32c8b4c9759198b0b727d2a8be7d","content_id":"8b32f1fa68ac452a55b66255d9c7a94a23d609c0","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":400,"license_type":"no_license","max_line_length":51,"num_lines":18,"path":"/알고리즘/온라인저지/2022/11/1113/사나운 개.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\n\ndef bark(start, stop):\n i = 1\n while i+start < 1000:\n for j in range(i, i+start):\n if j < 1000: \n dog[j] += 1\n i += start+stop\n\ndog = [0]*1000\nA, B, C, D = map(int, input().rstrip().split())\nvisitors = list(map(int, input().rstrip().split()))\nbark(A, B); bark(C, D)\nfor visitor in visitors:\n print(dog[visitor])"},{"alpha_fraction":0.44285714626312256,"alphanum_fraction":0.5857142806053162,"avg_line_length":34.5,"blob_id":"17aa27c1727ead5f890beeb81e8a693b2d756165","content_id":"42a01015bfdfaf4d788dd64c8152c97dcc4577a7","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":70,"license_type":"no_license","max_line_length":37,"num_lines":2,"path":"/알고리즘/온라인저지/2022/08/0822/가희와 방어율 무시.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"A, B = map(int, input().split())\nprint(0 if A*(100-B) >= 10000 else 1)"},{"alpha_fraction":0.4842519760131836,"alphanum_fraction":0.5,"avg_line_length":20.25,"blob_id":"ff76b56b06a4083826bb3be605866b7eb3bcac70","content_id":"2b1cc1f023a82ca889cede6b906e1f73938194d6","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":254,"license_type":"no_license","max_line_length":41,"num_lines":12,"path":"/알고리즘/SWEA/LEARN/Course/2. Programming Intermediate/6. 파이썬 SW문제해결 기본 Queue/5차시 6일차 - 회전.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"T = int(input())\n\nfor t in range(1, T+1):\n N, M = map(int, input().split())\n arr = list(map(int, input().split()))\n tmp = M%N\n for i in range(tmp):\n arr.append(arr.pop(0))\n \n result = arr[0]\n\n print('#{} {}'.format(t, result))"},{"alpha_fraction":0.5,"alphanum_fraction":0.5249999761581421,"avg_line_length":19.5,"blob_id":"d4d09322343760f3a5c8aeda4522941377be0c19","content_id":"da679b9fdffb389ffe147ca355fb3d95f2aaf169","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":40,"license_type":"no_license","max_line_length":28,"num_lines":2,"path":"/알고리즘/온라인저지/2021/12/1213/팰린드롬인지 확인하기.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"a = input()\nprint(int(bool(a==a[::-1])))"},{"alpha_fraction":0.49799197912216187,"alphanum_fraction":0.5582329034805298,"avg_line_length":15.666666984558105,"blob_id":"7203ec5f0c26c0c6d5310a0413777b202e5fb984","content_id":"2b71e0077b0034f210a3ccced374c5b54a648c2d","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":249,"license_type":"no_license","max_line_length":39,"num_lines":15,"path":"/알고리즘/[템플릿]/Dynamic Programming/점화식.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\n\nN = int(input().rstrip())\ndp = [0]*36\ndp[0] = 1\nfor i in range(35):\n tmp = 0 \n for j in range(i+1):\n tmp += dp[j]*dp[i-j]\n dp[i+1] = tmp\nprint(dp[N])\n\n# https://www.acmicpc.net/problem/13699"},{"alpha_fraction":0.5250896215438843,"alphanum_fraction":0.5286738276481628,"avg_line_length":31.882352828979492,"blob_id":"b66769161b9f94148c43d7c128385a69cec94997","content_id":"218fb84ce2e49a00a95dfa948f39e071472f6240","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":904,"license_type":"no_license","max_line_length":75,"num_lines":17,"path":"/알고리즘/온라인저지/2022/09/0903/재귀함수가 뭔가요.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"def dfs(level):\n tmp = '____'*level\n if level != N:\n print(tmp + '\"재귀함수가 뭔가요?\"')\n print(tmp + '\"잘 들어보게. 옛날옛날 한 산 꼭대기에 이세상 모든 지식을 통달한 선인이 있었어.')\n print(tmp + '마을 사람들은 모두 그 선인에게 수많은 질문을 했고, 모두 지혜롭게 대답해 주었지.')\n print(tmp + '그의 답은 대부분 옳았다고 하네. 그런데 어느 날, 그 선인에게 한 선비가 찾아와서 물었어.\"')\n dfs(level+1)\n print(tmp + '라고 답변하였지.')\n else:\n print(tmp + '\"재귀함수가 뭔가요?\"')\n print(tmp + '\"재귀함수는 자기 자신을 호출하는 함수라네\"')\n print(tmp + '라고 답변하였지.')\n\nN = int(input())\nprint('어느 한 컴퓨터공학과 학생이 유명한 교수님을 찾아가 물었다.')\ndfs(0)"},{"alpha_fraction":0.4591836631298065,"alphanum_fraction":0.4897959232330322,"avg_line_length":18.799999237060547,"blob_id":"cbd5868577a721804567cf9d43bef35da98dcf67","content_id":"bf88d1835cf4637319cbc2a8d5a20bc40488907f","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":98,"license_type":"no_license","max_line_length":40,"num_lines":5,"path":"/알고리즘/온라인저지/2023/02/0210/The Fastest Sorting Algorithm In The World.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"i = 1\nwhile True:\n if input() == '0': break\n print(f'Case {i}: Sorting... done!')\n i += 1"},{"alpha_fraction":0.47719594836235046,"alphanum_fraction":0.49070945382118225,"avg_line_length":29.384614944458008,"blob_id":"76cd710fe9eb359047051b92247709ffe44f8471","content_id":"87a312d802455a3a8008ed210fce9d89cca38f16","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1446,"license_type":"no_license","max_line_length":60,"num_lines":39,"path":"/알고리즘/온라인저지/2022/07/0710/적록색약.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"from collections import deque # BFS\nfrom copy import deepcopy # 원본 배열 복사하여 색약 배열로 변경하기 위함\n\n\ndef bfs(arr, y, x, color):\n Q = deque()\n Q.append((y, x))\n while Q:\n y, x = Q.popleft()\n if not arr[y][x]:\n continue\n arr[y][x] = 0\n for i in range(4):\n ny = y+dy[i]\n nx = x+dx[i]\n if 0<=ny<N and 0<=nx<N and arr[ny][nx] == color:\n # 탐색범위를 벗어나지 않으면서, 현재 탐색중인 색깔과 같으면\n Q.append((ny, nx))\n\n\ndy = [-1, 1, 0, 0] # 4방향 델타이동\ndx = [0, 0, -1, 1]\nN = int(input())\nnormal_arr = [list(input()) for _ in range(N)] # 원본배열\nCB_arr = deepcopy(normal_arr) # 원본 배열 복사하여 색약배열 초기화\nfor i in range(N): # 적록색약 배열\n for j in range(N):\n if CB_arr[i][j] in 'RG': # 빨강과 초록을 구분할 수 없으므로\n CB_arr[i][j] = 'A' # 임의의 문자 A로 통일\nnormal = CB = 0 # 일반인, 색약인(color blind) 결과값 초기화\nfor i in range(N):\n for j in range(N):\n if normal_arr[i][j]: # normal\n bfs(normal_arr, i, j, normal_arr[i][j])\n normal += 1 # 일반인이 볼 수 있는 구역 ++\n if CB_arr[i][j]: # color blind\n bfs(CB_arr, i, j, CB_arr[i][j])\n CB += 1 # 색약인이 볼 수 있는 구역 ++\nprint(normal, CB) # 출력"},{"alpha_fraction":0.5493230223655701,"alphanum_fraction":0.5802707672119141,"avg_line_length":27.72222137451172,"blob_id":"788c2f3361b962163e159ab6d2d1d800be952725","content_id":"4048cd0a3e10aba860606d19dd3a232b39dfef17","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":691,"license_type":"no_license","max_line_length":60,"num_lines":18,"path":"/알고리즘/온라인저지/2023/03/0326/평범한 배낭.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N, K = map(int, input().split())\nitems = [tuple(map(int, input().split())) for _ in range(N)]\ndp = [0]*(K+1)\nfor item in items:\n weight, value = item\n for i in range(K, weight-1, -1): # top-down\n dp[i] = max(dp[i], dp[i-weight]+value)\nprint(dp[-1])\n\n\"\"\"\ntop-down 방식의 문제이다\n현재 무게(dp[i])에서 얻을 수 있는 가장 큰 가치를\n아래 두 값 중 최대값으로 갱신한다\n1. 이미 구한 현재 무게의 가치 최대치(dp[i])\n2. 현재 물건의 무게만큼 더 담을 수 있던 시점의 가치 최대치에 현재 물건의 가치를 더한 값\nex) dp[7] = max(dp[7], dp[3]+items[4][value])\nex2) dp[6] = max(dp[6], dp[0]+items[6][value])\n\"\"\"\n"},{"alpha_fraction":0.5526315569877625,"alphanum_fraction":0.5789473652839661,"avg_line_length":18.5,"blob_id":"9e1cf1567f1350a0add7a20eb09d7065d65d73b8","content_id":"9f996e893be83d9d391e27560c8d8690ebcf97ff","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":38,"license_type":"no_license","max_line_length":21,"num_lines":2,"path":"/알고리즘/온라인저지/2023/01/0105/선린인터넷고등학교 교가.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = int(input())\nprint(input()[N-5:N])"},{"alpha_fraction":0.4736842215061188,"alphanum_fraction":0.5403508543968201,"avg_line_length":19.428571701049805,"blob_id":"16d12e624fbd5e2fc50cb63e4dd5f0d2eb5b5f08","content_id":"577b99230c0481c713fd41ade8d53bf54d193ad3","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":285,"license_type":"no_license","max_line_length":69,"num_lines":14,"path":"/알고리즘/온라인저지/2022/03/0315/나이 계산하기.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"birth = list(map(int, input().split()))\nnow = list(map(int, input().split()))\n\nolds = [0, 0, 0]\n\nolds[2] = now[0] - birth[0]\nolds[1] = olds[2] + 1\nolds[0] = olds[2]\n\nif (now[1] < birth[1]) or (now[1] == birth[1] and now[2] < birth[2]):\n olds[0] -= 1\n\nfor old in olds:\n print(old)"},{"alpha_fraction":0.597597599029541,"alphanum_fraction":0.6966966986656189,"avg_line_length":21.266666412353516,"blob_id":"73d6e45e3c5530b2d80c0bbdb95cfd4d1ae7b02b","content_id":"d9841906b6935555519fe1043e0f11a7d6cb210a","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":333,"license_type":"no_license","max_line_length":61,"num_lines":15,"path":"/알고리즘/[템플릿]/문자열 탐색/Brute Force.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import timeit\nstart = timeit.default_timer()\n\ntext = 'aawneifonoeiwmcl,xjfklsajdfklajewklfhaefnk1r7e8yiueniuencieh02cf12fh0v3ymn,cgjklo10f321hcqvyjkn9og4ml0f21hc3v9yjknqom0h1vcf2y93njkmof210hc3v9jkoymn0f21hcvko9jnym021hfok9cqv3jln,210hf9ocv3jklmny,qgf21h0kmn,jlocqv39cf30hkv9mn,ojlgfvc0hkx12mn,jol9210cf3hk9qvomn,jl10fh9cv3okjmn,g10cf3hv9knom0f9h3koncvm,02f1h9kcv3omn,j2f103vhc9knmjog0f2h19kncv3jmoyg0f21h9cv3njkgmoy0fh921ojkymncgv3,rlf21h0c3v9nyjkmgoh0n9f2yjkmcv13g4h0f21c3vn9kmjyg0hf219ncvjkm3og0f21hc3v9mnjky,o0f21hcvn9km3jy0h1vcf2nk9mj3021hnkf9m,cv3jhf210ncv3mjk9h0f219nycv3jkg0h9f21nycv3jk0h9f21nycv3kjg0fh219mnjkcv3,yogf20h1v3n9cg4kmf0h2913vcgf3210cvh9g4n20f31h9cvnkgf02h9c13vngtkr40fh921nkcvm30hn9kfmcv3h0nf1mk,j9cv3gf,mn12v0chkljox30cf21hkv3mn,9of0cmn,hkvjlo390hk9omnj,2f13vc0h9nk1mojfc3v0h9n12cfkmv3021h9cfnvyh0nf29kmcv13jh29fn1kmcv30f2h91ncvkm30h92nkf1mcv3o0h9f21nkmocv,30h9nk2fmcv130h9fknc12v30h9nk12fmcv320hc9f1nvk30f2h9c1vnkm30h9fnkc1vh9nkmjof12cv30h9fnkmcv12o,30h9f21nkcvmx30hf9n12ckv30h9nfkmc12v30hk9n,mfjloc1v0fh912vcnk3mh9f12vcn30h9nkcf12v30hf2n91mcv0hnf9c12v3h0n9mkj2cfv130h9nfc12v30h9fnkcv12m3gf219hcvn3kg0f21h9cvn3f219hcvk3nf021h9cnv39hf21cv30h9nf2c1vg3h09n1f2ycvg30h9fnc12vy8g3df09h2c1vg30h98y7nfcv213gh0987yfv2c13h0987yf2cv13ghy0987ncfv123h09872fyv134chyf7098cv2g09h87fv2cg13hy67098cv12gh09f21ycv3g4h09y87f12v3cg0h9821vc309h8f12cv309hfcv09hn12vcx309hn1f2cv30h9nf12cv30hn1cf2'\npattern = 'cx309hn1f2cv30h9'\nresult = 0\n\nfor i in range(len(text)-len(pattern)):\n if text[i:i+len(pattern)] == pattern:\n result = 1\n break\nprint(result)\n\nend = timeit.default_timer()\nprint(f'{end-start:.5f}')"},{"alpha_fraction":0.5829383730888367,"alphanum_fraction":0.6255924105644226,"avg_line_length":22.44444465637207,"blob_id":"0e6b036ec70f7710d9cfe71f67aa2269538db18a","content_id":"ddcb0bb13cd837b44f82b0c142d965f3c19c2a94","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":211,"license_type":"no_license","max_line_length":48,"num_lines":9,"path":"/알고리즘/온라인저지/2021/08/0822/단어 공부.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"word = input()\nword = word.upper()\nalphabet = [0] * 26\nfor wrd in word:\n alphabet[ord(wrd)-65] += 1\nif alphabet.count(max(alphabet)) > 1:\n print('?')\nelse:\n print(chr(alphabet.index(max(alphabet))+65))\n"},{"alpha_fraction":0.49484536051750183,"alphanum_fraction":0.5103092789649963,"avg_line_length":20.66666603088379,"blob_id":"83731e0c44d84a7ea51479ef3694e184b9c2e4c4","content_id":"70f245015a9844025ba5de6dc1989533c6362a30","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":194,"license_type":"no_license","max_line_length":48,"num_lines":9,"path":"/알고리즘/온라인저지/2022/07/0722/콘서트.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = int(input())\nA = list(map(int, input().split())) # first sold\nA.sort()\nC = list(range(1, len(A)+1))\nfor i in range(len(A)):\n if A[i] != C[i]:\n print(C[i])\n exit()\nprint(N+1)"},{"alpha_fraction":0.36477985978126526,"alphanum_fraction":0.4433962404727936,"avg_line_length":28,"blob_id":"290ee7d9c6415599be247470c4d66c7bf1072241","content_id":"365dd4d49ad36d75e82693d02b00d99834bc0738","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":318,"license_type":"no_license","max_line_length":45,"num_lines":11,"path":"/알고리즘/온라인저지/2022/07/0731/투자의 귀재 배주형.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"H, Y = map(int, input().split())\ndp = [0]*(Y+1)\ndp[0] = H\nfor i in range(1, Y+1):\n if i-1 >= 0 and dp[i-1]:\n dp[i] = max(int(dp[i-1]*1.05), dp[i])\n if i-3 >= 0 and dp[i-3]:\n dp[i] = max(int(dp[i-3]*1.2), dp[i])\n if i-5 >= 0 and dp[i-5]:\n dp[i] = max(int(dp[i-5]*1.35), dp[i])\nprint(dp[Y])"},{"alpha_fraction":0.5499181747436523,"alphanum_fraction":0.5908346772193909,"avg_line_length":24.5,"blob_id":"2cac20762e0868fa5e3a1325ce224952afafdbc6","content_id":"e3b1c02714410d9e8969d7b4e3f0449b223c77e8","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":999,"license_type":"no_license","max_line_length":52,"num_lines":24,"path":"/알고리즘/온라인저지/2021/08/0807/소수 찾기.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"\"\"\" 초기 풀이\nN개의 숫자 중 소수는 몇개인가\n소수인지 아는 법?\n약수가 1과 자기 자신\n주어질 수들은 1000이하 라는 조건\n1000까지, 주어진 수들을, 이중순회 하면서\n주어진 수를 1부터 주어진 수까지 나눌 때\n주어진 수까지 나머지가 안 생기면 소수\n중간에 나머지가 생기면(True) not소수\n\"\"\"\n\n# 최종 코드\nN = int(input()) # 숫자 개수 입력받고\nnumbers = list(map(int, input().split())) # 숫자들 입력받고\ncount = 0 # 소수 개수를 셀 count 초기화\nfor number in numbers: # 입력받은 숫자들을 순회하면서\n for i in range(2, 1001): # 2부터 1000까지 나누면서 검사\n if number % i == 0: # 나머지가 없고\n if number == i: # number본인이면\n count += 1 # 소수이므로 count에 1 저장\n else: # 나머지는 0이지만 number본인이 아니라면\n break # 약수임\n\nprint(count) # 소수 개수 출력"},{"alpha_fraction":0.31092438101768494,"alphanum_fraction":0.3613445460796356,"avg_line_length":14,"blob_id":"b2910816929c4b50f6fa19e77b8a7dd7e3f42fe4","content_id":"b30eff541e516d477a4b4828bd67f159edfb3e7a","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":119,"license_type":"no_license","max_line_length":35,"num_lines":8,"path":"/알고리즘/온라인저지/2022/01/0131/별 찍기 - 6.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = int(input())\n\ni = (N*2)-1\n\nfor n in range(N):\n a = ((N*2-1)-i)//2\n print(' ' * a, '*' * i, sep='')\n i -= 2"},{"alpha_fraction":0.515539288520813,"alphanum_fraction":0.5265082120895386,"avg_line_length":25.095237731933594,"blob_id":"40fb92975b17618fbc3938de80cfabf9d6427fbc","content_id":"bb2187291662d2f2cb5f5d8b3f41d3b835829936","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":547,"license_type":"no_license","max_line_length":57,"num_lines":21,"path":"/알고리즘/온라인저지/2022/06/0629/스타트와 링크.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"from itertools import combinations as comb\n\nN = int(input())\nscope = N\ncount = scope//2\ntmp = list(comb(list(range(scope)), count))\nresult = 1e9\narr = [list(map(int, input().split())) for _ in range(N)]\nfor i in range(len(tmp)//2):\n start = tmp[i]\n link = tmp[-i-1]\n S = L = 0\n for j in range(N):\n for k in range(N):\n if j in start and k in start:\n S += arr[j][k]\n elif j in link and k in link:\n L += arr[j][k]\n if abs(S-L) < result:\n result = abs(S-L)\nprint(result)"},{"alpha_fraction":0.5777778029441833,"alphanum_fraction":0.5777778029441833,"avg_line_length":22,"blob_id":"b6267902303e193af17f093aba9b58e04cde2c0a","content_id":"a97fd0489f708bdb650613bd101cfe2a1b8a09de","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":45,"license_type":"no_license","max_line_length":22,"num_lines":2,"path":"/알고리즘/온라인저지/2023/05/0501/2 桁の整数 (Two-digit Integer).py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"print(input(), end='')\nprint(input(), end='')"},{"alpha_fraction":0.41632652282714844,"alphanum_fraction":0.5020408034324646,"avg_line_length":21.363636016845703,"blob_id":"ab3773a5e5cc5e2a3b83f3cb4450bc2391b0ea89","content_id":"554f2f5d0a09a75a6434832d5062bdaa5d34154c","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":245,"license_type":"no_license","max_line_length":61,"num_lines":11,"path":"/알고리즘/온라인저지/2022/06/0619/핸드폰 번호 궁합.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"A = input()\nB = input()\ntmp1 = ''\ntmp2 = ''\nfor i in range(8):\n tmp1 = tmp1 + A[i] + B[i]\nfor j in range(16, 2, -1):\n for i in range(1, j):\n tmp2 = tmp2 + str((int(tmp1[i-1]) + int(tmp1[i]))%10)\n tmp1, tmp2 = tmp2, ''\nprint(tmp1)"},{"alpha_fraction":0.4017094075679779,"alphanum_fraction":0.42307692766189575,"avg_line_length":15.785714149475098,"blob_id":"f3faf142176edca1e070e889a5cb844b4563b897","content_id":"0510e5a6b193ea492f4c84a9907960eca107a65c","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":234,"license_type":"no_license","max_line_length":23,"num_lines":14,"path":"/알고리즘/온라인저지/2023/01/0107/A와 B.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"S = list(input())\nT = list(input())\nresult = 0\nwhile len(T) > 0:\n if S == T: \n result = 1\n break\n flag = False\n if T[-1] == 'B':\n flag = True\n T.pop()\n if flag:\n T = T[::-1] \nprint(result)"},{"alpha_fraction":0.557603657245636,"alphanum_fraction":0.5714285969734192,"avg_line_length":23.22222137451172,"blob_id":"4804ad55b076211b17bd44ce228a85fef7ad49a2","content_id":"e25a0d90b0350e1da12009848b64374f6ca76739","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":217,"license_type":"no_license","max_line_length":41,"num_lines":9,"path":"/알고리즘/온라인저지/2022/10/1013/폭죽쇼.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N, C = map(int, input().split())\nhanabi = [int(input()) for _ in range(N)]\nresult = 0\nfor i in range(1, C+1):\n fire = False\n for h in hanabi:\n if not i%h: fire = True\n result += int(fire)\nprint(result)"},{"alpha_fraction":0.4517958462238312,"alphanum_fraction":0.47826087474823,"avg_line_length":26.894737243652344,"blob_id":"ac615c5a0a07b933c2b7f57c756d577fed07411c","content_id":"380a248caed932d91fe75b6cb140dc686158fd9b","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":529,"license_type":"no_license","max_line_length":70,"num_lines":19,"path":"/알고리즘/온라인저지/2022/06/0629/하키.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"W, H, X, Y, P = map(int, input().split())\nLB = [X, Y] # left bottom\nRT = [X+W, Y+H] # right top\nR = H//2\nresult = 0\nfor p in range(P):\n tmp = list(map(int, input().split()))\n square = True\n for i in range(2):\n if tmp[i] < LB[i] or tmp[i] > RT[i]:\n square = False\n if square:\n result += 1\n x, y = tmp\n if (abs(x-X)**2 + abs(y-(Y+R))**2)**0.5 <= R and not square:\n result += 1\n elif (abs(x-(X+W))**2 + abs(y-(Y+R))**2)**0.5 <= R and not square:\n result += 1\nprint(result)"},{"alpha_fraction":0.5574468374252319,"alphanum_fraction":0.5936170220375061,"avg_line_length":17.84000015258789,"blob_id":"c961d8ba7bcbaa0fdaf899d553714d2837233899","content_id":"39a00d1bd7deeaf4ddd03513e2bd939d4fc31eb0","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":480,"license_type":"no_license","max_line_length":54,"num_lines":25,"path":"/알고리즘/온라인저지/2022/10/1006/N과 M (8).py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\n\ndef dfs(depth, start):\n if depth == M: \n print(*result) \n return\n for i in range(start, N):\n result.append(arr[i])\n dfs(depth+1, i)\n result.pop()\n\nN, M = map(int, input().rstrip().split())\narr = sorted(list(map(int, input().rstrip().split())))\nresult = []\ndfs(0, 0)\n\n\"\"\"\n<참고한 링크>\nhttps://tmdrl5779.tistory.com/27\nhttps://honggom.tistory.com/110\n\"\"\"\n\n# https://www.acmicpc.net/problem/15657"},{"alpha_fraction":0.5089285969734192,"alphanum_fraction":0.5178571343421936,"avg_line_length":11.55555534362793,"blob_id":"439c4b6618ae305a4189c95b7f9c7c0da9d5c7ab","content_id":"10bb0d84c03a13e5afe4002c152c99b8f4e4b776","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":112,"license_type":"no_license","max_line_length":33,"num_lines":9,"path":"/알고리즘/온라인저지/2022/02/0220/이상한 곱셈.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"A, B = input().split()\n\nresult = 0\n\nfor a in A:\n for b in B:\n result += int(a) * int(b)\n\nprint(result)"},{"alpha_fraction":0.4029850661754608,"alphanum_fraction":0.5074626803398132,"avg_line_length":21.66666603088379,"blob_id":"29dfb69b90dd1b65a0e90ddbc4c6b17968c17777","content_id":"c8ce52b0d69142867374148adfd0a72f3d332fb6","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":67,"license_type":"no_license","max_line_length":32,"num_lines":3,"path":"/알고리즘/온라인저지/2022/08/0831/욱 제.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"A, B = map(int, input().split())\nM = (B-A)/400\nprint(1/(10**M + 1))"},{"alpha_fraction":0.4801762104034424,"alphanum_fraction":0.5330396294593811,"avg_line_length":13.25,"blob_id":"e5ff3bd3d073f6cb8c8c2b977c57b6f5ea6df32b","content_id":"d3de0384006bb7c71be5da3c17a3151020d848e9","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":227,"license_type":"no_license","max_line_length":28,"num_lines":16,"path":"/알고리즘/온라인저지/2022/01/0131/상근날드.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"burger = 2000\ndrink = 2000\n\nfor i in range(3):\n b = int(input())\n if b < burger:\n burger = b\n\nfor i in range(2):\n d = int(input())\n if d < drink:\n drink = d\n\nresult = burger + drink - 50\n\nprint(result)"},{"alpha_fraction":0.5483193397521973,"alphanum_fraction":0.5651260614395142,"avg_line_length":19.7391300201416,"blob_id":"a1917bdd9a5d900a5822a8786e57cb6c37b09636","content_id":"a1b80d0a6f610c2938dba0c84aa3fea048f68cf1","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":646,"license_type":"no_license","max_line_length":61,"num_lines":23,"path":"/알고리즘/온라인저지/2022/09/0904/조깅.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N, T = map(int, input().split())\nrunner = [tuple(map(int, input().split())) for _ in range(N)]\nstack = []\ncnt = 1\nfor r in runner[::-1]:\n tmp = r[0] + (r[1]*T)\n if stack and tmp < stack[-1]:\n cnt += 1\n if stack and tmp >= stack[-1]:\n stack.append(stack[-1])\n else:\n stack.append(tmp)\n print(tmp, stack)\nprint(cnt)\n\n\"\"\"\n맨 선두에 있는 주자부터 이동한다\n당연히 맨 선두 주자는 하나의 그룹이 된다\n그 다음 주자를 이동한다\n그 다음 주자의 최고 이동거리가 선두주자보다\n같거나 클 경우 한 그룹으로 붙는다\n아닐 경우 다른 그룹이 된다\n\"\"\""},{"alpha_fraction":0.5477477312088013,"alphanum_fraction":0.5819819569587708,"avg_line_length":24.272727966308594,"blob_id":"017792240767bab4ae12d0a40b4590c7320b74bc","content_id":"37ed1e402f31098d85c28e29bb387e9e058e0f78","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":567,"license_type":"no_license","max_line_length":41,"num_lines":22,"path":"/알고리즘/온라인저지/2022/05/0508/경고.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"from datetime import datetime\n\na = input()\nb = input()\ntime_1 = datetime.strptime(a,\"%H:%M:%S\")\ntime_2 = datetime.strptime(b,\"%H:%M:%S\")\nday_over = False\ntime_interval = time_2 - time_1\nif str(time_interval)[0] == '-':\n day_over = True\nif a == b: # 문제를 잘 읽자\n print('24:00:00')\nelif day_over:\n if len(str(time_interval)) == 16:\n print(str(time_interval)[8:])\n else:\n print('0'+str(time_interval)[8:])\nelse: \n if len(str(time_interval)) == 16:\n print(str(time_interval))\n else:\n print('0'+str(time_interval))"},{"alpha_fraction":0.3164556920528412,"alphanum_fraction":0.5,"avg_line_length":13.454545021057129,"blob_id":"eb5a34f3f2de84201e13e021f1c737a16ebf134a","content_id":"e8e84516f0835ad9f5da5c6327e8dcbe400e3184","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":158,"license_type":"no_license","max_line_length":29,"num_lines":11,"path":"/알고리즘/SWEA/LEARN/Course/1. Programming Beginner/파이썬 프로그래밍 기초(2)/24차시 2. 자료구조 – 리스트, 튜플 - 연습문제 26.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"l1 = [1,3,6,78,35,55]\nl2 = [12,24,35,24,88,120,155]\n\nresult = []\n\nfor i in l1:\n for j in l2:\n if i == j:\n result.append(i)\n\nprint(result)"},{"alpha_fraction":0.49264705181121826,"alphanum_fraction":0.5073529481887817,"avg_line_length":21.83333396911621,"blob_id":"70c1cd7a2bb9310b15a978145f0c16fb472f3cbd","content_id":"d9ac805ef6aecb37307f98271f8949dae5827ef6","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":136,"license_type":"no_license","max_line_length":43,"num_lines":6,"path":"/알고리즘/온라인저지/2022/09/0903/최대공약수.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"def gcd(a, b):\n while b > 0: a, b = b, a%b\n return a\n\nA, B = map(int, input().split())\nfor _ in range(gcd(A, B)): print(1, end='')"},{"alpha_fraction":0.41432225704193115,"alphanum_fraction":0.4271099865436554,"avg_line_length":19.157894134521484,"blob_id":"0561318cd2ea1df41e34a61550740e705a751eba","content_id":"7147f7869569e7d603149fabfa9c3b6196721106","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":391,"license_type":"no_license","max_line_length":36,"num_lines":19,"path":"/알고리즘/온라인저지/2021/08/0828/그룹 단어 체커.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\nT = int(sys.stdin.readline())\ncnt = 0\nfor tc in range(T):\n word = sys.stdin.readline()\n i = 0\n char = []\n for i in range(len(word)):\n if word[i] not in char:\n char.append(word[i])\n else:\n if word[i] == word[i-1]:\n pass\n else:\n cnt -= 1\n break\n cnt += 1\nprint(cnt)\n "},{"alpha_fraction":0.316546767950058,"alphanum_fraction":0.3381294906139374,"avg_line_length":21.280000686645508,"blob_id":"a45d6082fea13752146098dc84b130239464b4b7","content_id":"6e8aef03e9d560715519221159be584d49cf0c69","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":556,"license_type":"no_license","max_line_length":37,"num_lines":25,"path":"/알고리즘/온라인저지/2022/08/0827/기술 연계마스터 임스.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"O = False # combo over\nN = int(input())\nresult = 0\nS = [[], []] # stack\nfor i in list(input()):\n if O: break\n try: # 1~9\n i = int(i)\n result += 1\n except: # LRSK\n if i == 'L': S[0].append(i)\n elif i == 'S': S[1].append(i)\n elif i == 'R':\n if S[0]:\n S[0].pop()\n result += 1\n else:\n O = True\n elif i == 'K':\n if S[1]:\n S[1].pop()\n result += 1\n else:\n O = True\nprint(result)"},{"alpha_fraction":0.5037146806716919,"alphanum_fraction":0.5304605960845947,"avg_line_length":27.08333396911621,"blob_id":"48bd548b5ab7f33d8d5218ca7c64abe0142a5026","content_id":"bdcfd737cde95d84d9a549d4d841842cc684a239","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":673,"license_type":"no_license","max_line_length":46,"num_lines":24,"path":"/알고리즘/온라인저지/2022/06/0629/덱.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"from collections import deque\nimport sys\ndef input():\n return sys.stdin.readline()\n\nD = deque()\nfor i in range(int(input())):\n tmp = input().split()\n if tmp[0] == 'push_front':\n D.appendleft(tmp[1])\n elif tmp[0] == 'push_back':\n D.append(tmp[1])\n elif tmp[0] == 'pop_front':\n print(D.popleft()) if D else print(-1)\n elif tmp[0] == 'pop_back':\n print(D.pop()) if D else print(-1)\n elif tmp[0] == 'size':\n print(len(D))\n elif tmp[0] == 'empty':\n print(0) if D else print(1)\n elif tmp[0] == 'front':\n print(D[0]) if D else print(-1)\n elif tmp[0] == 'back':\n print(D[-1]) if D else print(-1)"},{"alpha_fraction":0.4285714328289032,"alphanum_fraction":0.5408163070678711,"avg_line_length":32,"blob_id":"cc5fb66e151c00cf4e5c20f61aad802a99a8351f","content_id":"2b183588dd92a4764d19d055326bdd9a3ce59460","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":98,"license_type":"no_license","max_line_length":42,"num_lines":3,"path":"/알고리즘/온라인저지/2022/08/0822/Cupcake Party.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"B = [int(input()) for _ in range(2)] # box\nC = B[0]*8 + B[1]*3 # cake\nprint(C-28 if C-28>0 else 0)"},{"alpha_fraction":0.5188679099082947,"alphanum_fraction":0.5283018946647644,"avg_line_length":25.75,"blob_id":"ab1fb14bc1b9389596579769312148f6fd1fe4c9","content_id":"7669e22c1729ef7a5dab25856f24e70d0d91a234","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":106,"license_type":"no_license","max_line_length":36,"num_lines":4,"path":"/알고리즘/온라인저지/2023/06/0610/Schronisko.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"for _ in range(int(input())):\n W, H = map(int, input().split())\n result = (W*H)//2\n print(result)"},{"alpha_fraction":0.46543779969215393,"alphanum_fraction":0.4930875599384308,"avg_line_length":23.22222137451172,"blob_id":"ebf3291e911e0b358a1f3e934a91711c31eaceb0","content_id":"6afe7d28382ed1531f307f68a819ac33ec570cfe","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":217,"license_type":"no_license","max_line_length":34,"num_lines":9,"path":"/알고리즘/온라인저지/2023/06/0611/Basketball One-on-One.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"record = input()\nA, B = 0, 0\nfor i in range(0, len(record), 2):\n player = record[i]\n if player == 'A':\n A += int(record[i+1])\n if player == 'B':\n B += int(record[i+1])\nprint('A' if A>B else 'B')"},{"alpha_fraction":0.4163934290409088,"alphanum_fraction":0.4557377099990845,"avg_line_length":18.125,"blob_id":"5a40390bcbf1a6bc222c41fe67d1e623600ece70","content_id":"c45c6c5226a89096a61c131b6645ca87f7e67d7e","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":305,"license_type":"no_license","max_line_length":42,"num_lines":16,"path":"/알고리즘/SWEA/LEARN/Course/2. Programming Intermediate/1. 파이썬 SW문제해결 기본 List1/9차시 1일차 - 구간합.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"T = int(input())\n\nfor t in range(1, T+1):\n N, M = map(int, input().split())\n\n nums = list(map(int, input().split()))\n\n a = 99999999\n b = 0\n\n for i in range(len(nums)-M+1):\n tmp = sum(nums[i:i+M])\n a = min(a, tmp)\n b = max(b, tmp)\n \n print('#{} {}'.format(t, b-a))"},{"alpha_fraction":0.48852458596229553,"alphanum_fraction":0.4961748719215393,"avg_line_length":26.75757598876953,"blob_id":"9c7102b660fd0ed42f774be11c0c0e8b6dead4a9","content_id":"0fe0d3be48b674b56a567a25977eb59e448cd1ad","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1179,"license_type":"no_license","max_line_length":44,"num_lines":33,"path":"/알고리즘/온라인저지/2022/03/0322/택배 배송.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import heapq\nimport sys\nINF = sys.maxsize # 가상의 최대값\n\ndef dijkstra(start):\n q = [] # 방문가능한 지점\n heapq.heappush(q, (0, start)) # 출발점 입력\n dis[start] = 0 # 출발지점은 거리가 0\n while q: # 다익스트라\n d, now = heapq.heappop(q)\n # print(d, now) # 디버깅\n if dis[now] < d: # 최소거리가 될 수 없으면\n continue # 백트래킹\n # print(graph[now]) # 디버깅\n for v, w in graph[now]:\n # 들고 있는 최소거리 + 이동할 거리\n cost = d + w \n if cost < dis[v]: # 새로운 최소값이면\n dis[v] = cost # 갱신\n # 다음 이동지점에 갱신된 최소값 추가\n heapq.heappush(q, (cost, v))\n\nN, M = map(int, input().split())\n# 각 노드에서 이동 가능한 지점들 리스트\ngraph = [[] for _ in range(N+1)]\ndis = [INF]*(N+1) # 각 노드별 최소 이동거리 DP\nfor _ in range(M):\n a, b, c = map(int, input().split())\n # 양방향 방문가능 노드 추가\n graph[a].append((b, c))\n graph[b].append((a, c))\ndijkstra(1) # 1부터 출발\nprint(dis[N]) # 출력"},{"alpha_fraction":0.43065693974494934,"alphanum_fraction":0.45985400676727295,"avg_line_length":12.800000190734863,"blob_id":"350afad8dc5fad2c5884f3a9d81d26e146e40066","content_id":"1a347220dc61b354c911629c18916106a693b0a5","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":137,"license_type":"no_license","max_line_length":26,"num_lines":10,"path":"/알고리즘/SWEA/LEARN/Course/1. Programming Beginner/파이썬 프로그래밍 기초(2)/7차시 2. 자료구조 – 리스트, 튜플 - 연습문제 6.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"x = int(input())\n\ns = set()\n\nfor i in range(1, x//2+1):\n if x%i == 0:\n s.add(i)\n s.add(int(x/i))\n\nprint(sorted(list(s)))"},{"alpha_fraction":0.41600000858306885,"alphanum_fraction":0.42399999499320984,"avg_line_length":13.764705657958984,"blob_id":"bb27e22a09bc517898ad3450c9e511d09c976978","content_id":"d6dfe442099ccde164c0a3a5786b95c6309ff058","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":250,"license_type":"no_license","max_line_length":35,"num_lines":17,"path":"/알고리즘/온라인저지/2022/02/0214/나는 행복합니다~.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"i = 0\n\nN, M, K = map(int, input().split())\n\nseat_found = False\n\nfor n in range(N):\n for m in range(M):\n if i == K:\n print(n, m)\n seat_found = True\n break\n\n i += 1\n \n if seat_found:\n break"},{"alpha_fraction":0.43609023094177246,"alphanum_fraction":0.4661654233932495,"avg_line_length":8.571428298950195,"blob_id":"3c4ef75b41fde13a31379380d6636163b80a9adc","content_id":"7746808e50c3875e740ed4226dfdc8b18946cacf","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":133,"license_type":"no_license","max_line_length":18,"num_lines":14,"path":"/알고리즘/온라인저지/2022/02/0227/2의 제곱인가.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = int(input())\n\nresult = 0\n\ntmp = 1\n\nwhile tmp <= N:\n if tmp == N:\n result = 1\n break\n\n tmp *= 2\n\nprint(result)"},{"alpha_fraction":0.3854489028453827,"alphanum_fraction":0.39783281087875366,"avg_line_length":39.125,"blob_id":"0a2580fc047b86ba36227f1208ca1e4f511e9578","content_id":"ce13783f39bb810fceecd3de1903746ec1cfe9df","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":852,"license_type":"no_license","max_line_length":76,"num_lines":16,"path":"/알고리즘/온라인저지/2021/08/0816/소수 구하기.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"A, B = map(int, input().split())\n\nn = B # 소수를 찾을 범위\na = [False,False] + [True]*(n-1) # 0 ~ n 까지의 숫자 리스트\n # 일단 True로 만들고, 소수가 아닌 숫자를 찾아서 False로 지움\nprimes=[] # 소수 집합\nfor i in range(2,n+1): # 2 ~ n까지 반복\n if a[i]: # 2부터 시작, 해당 숫자가 지워지지 않고 남아있는 소수라면 \n primes.append(i) # 소수 리스트에 추가\n for j in range(2*i, n+1, i): # 해당 소수의 배수들을 \n a[j] = False # 리스트에서 전부 False로 만들기\n # bool타입이라 연산이 빠름\n\nfor prime in primes:\n if prime >= A:\n print(prime)\n "},{"alpha_fraction":0.45392492413520813,"alphanum_fraction":0.4778156876564026,"avg_line_length":21.615385055541992,"blob_id":"df05f1bf667cb0cda4f97786e746f79cf2b993c9","content_id":"b0af1f962490f09538cfb35add0f08b487f91a05","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":293,"license_type":"no_license","max_line_length":36,"num_lines":13,"path":"/알고리즘/온라인저지/2022/07/0710/백설 공주와 일곱 난쟁이.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"D = [int(input()) for _ in range(9)]\nresult = []\n# print(D)\nsumm = sum(D)\nfor i in range(9):\n for j in range(i+1, 9):\n tmp = summ - (D[i]+D[j])\n if tmp == 100:\n result.append(D[i])\n result.append(D[j])\nfor d in D:\n if d not in result:\n print(d)"},{"alpha_fraction":0.40758293867111206,"alphanum_fraction":0.44075828790664673,"avg_line_length":25.5,"blob_id":"363bb21c3f2e22172097fb633cb56d3799d46711","content_id":"2d600e0163c0b82fb9657c52ff96506a750e902a","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":211,"license_type":"no_license","max_line_length":42,"num_lines":8,"path":"/알고리즘/온라인저지/2023/01/0102/CTP공국으로 이민 가자.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"for tc in range(int(input())-1, -1, -1):\n input()\n for i in input().split():\n try:\n print(chr(int(i)+64), end=' ')\n except:\n print(ord(i)-64, end=' ')\n if tc: print()"},{"alpha_fraction":0.44133099913597107,"alphanum_fraction":0.457092821598053,"avg_line_length":39.85714340209961,"blob_id":"fa544fa0b76292b50da0baa81a91806d284d1e9a","content_id":"a61788dfffe20d13f84b0babbee0afe581c07f05","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":719,"license_type":"no_license","max_line_length":71,"num_lines":14,"path":"/알고리즘/온라인저지/2022/05/0521/텔레프라임.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"num, new = map(int, input().split())\nnew_num = int(str(new)+str(num))\nn = new_num+2 # 소수를 찾을 범위\na = [False,False] + [True]*(n-1) # 0 ~ n 까지의 숫자 리스트\nprimes=[] # 소수 집합\nfor i in range(2,n+1): # 2 ~ n까지 반복\n if a[i]: # 2부터 시작, 해당 숫자가 지워지지 않고 남아있는 소수라면 \n primes.append(i) # 소수 리스트에 추가\n for j in range(2*i, n+1, i): # 해당 소수의 배수들을 \n a[j] = False # 리스트에서 전부 False로 만들기\nif num in primes and new_num in primes:\n print('Yes')\nelse:\n print('No')"},{"alpha_fraction":0.2628205120563507,"alphanum_fraction":0.33012819290161133,"avg_line_length":18.5625,"blob_id":"335759fcf8cf506a8d419fb209bafe5040fcf324","content_id":"da6f98c844aaa8c240122d9f6f4a5bafc14a29ed","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":312,"license_type":"no_license","max_line_length":29,"num_lines":16,"path":"/알고리즘/온라인저지/2023/01/0118/미국 스타일.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"for _ in range(int(input())):\n A, B = input().split()\n A = float(A)\n if B == 'kg':\n A *= 2.2046\n B = 'lb'\n elif B == 'lb':\n A *= 0.4536\n B = 'kg'\n elif B == 'l':\n A *= 0.2642\n B = 'g'\n else:\n A *= 3.7854\n B = 'l'\n print(f'{A:.4f} {B}')"},{"alpha_fraction":0.4202898442745209,"alphanum_fraction":0.4202898442745209,"avg_line_length":16.375,"blob_id":"eb37dc7370a0ca2e71a4687fd0785ac680ce3dc2","content_id":"b08b12ad8fba64415c31f3bd6c1fd3d0f9079b96","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":138,"license_type":"no_license","max_line_length":22,"num_lines":8,"path":"/알고리즘/온라인저지/2023/05/0530/Triangles.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"while True:\n N = int(input())\n if not N:\n break\n line = '*'\n for i in range(N):\n print(line)\n line += '*'"},{"alpha_fraction":0.4774535894393921,"alphanum_fraction":0.5623342394828796,"avg_line_length":10.8125,"blob_id":"0982f4b5aaf63ff0f28cde1a6aab477a1674b0c0","content_id":"7f2296dab404e575a6064a70cfc0bd2875dc7298","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":533,"license_type":"no_license","max_line_length":39,"num_lines":32,"path":"/알고리즘/온라인저지/2021/10/1011/이장님 초대.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"\"\"\"\n1. 묘목 하나 심는데 1일\n2. 묘목 n개 구입 -> n일\n3. 이장님을 초대하기위해, 대신 묘목들이 완전히 자란 후에\n 이장님을 초대하기 위한 최소 시간\n\n1. 묘목의 수\n2. 각 묘목별 걸리는 시간\n\n1. 4 3 3 2 -> \n2. 39 39 38 35 20 9\n\n2 3 4 5 ....\n\n값을 정렬하고\nfor문 돌려서\nrange(2, N) 더해주고\nmax\n\"\"\"\n\nN = int(input())\ntrees = list(map(int, input().split()))\n\ntrees.sort(reverse=True)\n\nj = 0\n\nfor i in range(2, 2+N):\n trees[j] += i\n j += 1\n\nprint(max(trees))"},{"alpha_fraction":0.4636015295982361,"alphanum_fraction":0.49042144417762756,"avg_line_length":22.81818199157715,"blob_id":"5bd9de97cedd2b2d77f669fdbacd7e8ed53947eb","content_id":"362cac01835180fbc040a9f32de10e22c1b7c482","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":261,"license_type":"no_license","max_line_length":50,"num_lines":11,"path":"/알고리즘/온라인저지/2023/02/0217/동혁 피자.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"pizza = 0\nwhile True:\n tmp = input()\n if tmp == '0': break\n pizza += 1\n R, W, L = map(int, tmp.split())\n A = (R*2)**2\n B = W**2 + L**2\n result = 'fits'\n if A < B: result = 'does not fit'\n print(f'Pizza {pizza} {result} on the table.')"},{"alpha_fraction":0.4188311696052551,"alphanum_fraction":0.4350649416446686,"avg_line_length":21.071428298950195,"blob_id":"f7b1a290c7e4774b35dd4cfd4dab62b8cd0cea8c","content_id":"b2a8b0ba3775b22aba9eb7c882cc08e8e7c17d24","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":308,"license_type":"no_license","max_line_length":39,"num_lines":14,"path":"/알고리즘/온라인저지/2022/09/0903/GCD 합.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"def gcd(a, b):\n while b > 0:\n a, b = b, a % b\n return a\n\nfor _ in range(int(input())):\n N = list(map(int, input().split()))\n n = N.pop(0)\n result = 0\n for i in range(n-1):\n for j in range(i+1, n):\n A, B = N[i], N[j]\n result += gcd(A, B)\n print(result)"},{"alpha_fraction":0.5523809790611267,"alphanum_fraction":0.5523809790611267,"avg_line_length":20.200000762939453,"blob_id":"44afbf6170a27dd2156fe7384baf0a7fbc7a2d1e","content_id":"8858f1bd875530e71be45f8d76be62dbe69ce996","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":105,"license_type":"no_license","max_line_length":47,"num_lines":5,"path":"/알고리즘/온라인저지/2022/02/0205/더하기.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"T = int(input())\n\nfor t in range(T):\n N = int(input())\n print(sum(list(map(int, input().split()))))"},{"alpha_fraction":0.5377049446105957,"alphanum_fraction":0.5639344453811646,"avg_line_length":22.538461685180664,"blob_id":"18e38a05eb5c0363aa91182ddd6581008f43b212","content_id":"b2879343159e3055f8d2bd7e2a875e8a108a544a","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":305,"license_type":"no_license","max_line_length":40,"num_lines":13,"path":"/알고리즘/[템플릿]/이분탐색/숫자 카드 2.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = int(input())\nN_list = list(map(int, input().split()))\ndct = {}\nfor n in N_list:\n try: dct[n] += 1\n except: dct[n] = 1\nM = int(input())\nM_list = list(map(int, input().split()))\nfor m in M_list:\n try: print(dct[m], end=' ')\n except: print(0, end=' ')\n\n# https://www.acmicpc.net/problem/10816"},{"alpha_fraction":0.6299999952316284,"alphanum_fraction":0.6399999856948853,"avg_line_length":24.04166603088379,"blob_id":"ed8e3a359486ee79ee287374a0a3dcfced3892b0","content_id":"9b4607b5c2ad5116cfe9ee31e522da1875ead236","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1054,"license_type":"no_license","max_line_length":52,"num_lines":24,"path":"/알고리즘/온라인저지/2021/08/0814/로프.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"\"\"\"\n로프는 k개\nk개의 로프로 w만큼을 나눠서 들어올릴 때\n각 로프에 가해지는 하중은 w/k\n로프의 최대하중이 w/k를 넘기면 안됌\n모든 로프에 걸리는 하중은 w/k로 같고\n제일 하중이 낮은 로프가 이를 버텨내야 한다\n그 때의 w값\n큰거부터 내려가야 한다\n하중이 큰 로프부터 한개 두개 세개... 하다가 \n최대하중이 계속 증가하는데 꺾이는 순간이 온다\n\"\"\"\n\nN = int(input()) # 줄의 개수\nropes = [] # 로프들 초기화\nfor n in range(N): # 로프 개수만큼 반복하면서\n ropes.append(int(input())) # 로프들 입력받기\nropes.sort() # 정렬하고\nropes.reverse() # 뒤집어서 중량이 큰 로프가 앞으로 오도록\nmax_weight = ropes[0] # 제일 중량이 큰 로프 혼자 있을때가 최대중량 초기값\nfor n in range(1, N+1): # 로프 1개부터 N개까지\n if max_weight <= ropes[n-1]*n: # 최대하중이 기존보다 크면\n max_weight = ropes[n-1]*n # 새로 저장\nprint(max_weight) # 최대하중 출력"},{"alpha_fraction":0.5228426456451416,"alphanum_fraction":0.5279187560081482,"avg_line_length":23.625,"blob_id":"78c03d4ee5954b29091254c63a1bc4b01fb4a986","content_id":"2562e818da9f5bc9d3096591a92aeb0e6147331c","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":197,"license_type":"no_license","max_line_length":38,"num_lines":8,"path":"/알고리즘/온라인저지/2023/05/0515/Teleportation.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"A, B, X, Y = map(int, input().split())\nA, B = min((A, B)), max((A, B))\nX, Y = min((X, Y)), max((X, Y))\nresult = 0\nresult += abs(A-X)\nresult += abs(B-Y)\nresult = min(result, abs(A-B))\nprint(result)\n"},{"alpha_fraction":0.5198019742965698,"alphanum_fraction":0.5396039485931396,"avg_line_length":22.823530197143555,"blob_id":"28356683acc71a1d4cf2f62566db06e8e818ac8c","content_id":"433f200d53edac9eb713303f72be19b3a751fe46","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":404,"license_type":"no_license","max_line_length":50,"num_lines":17,"path":"/알고리즘/온라인저지/2021/08/0822/일곱 난쟁이.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"dwarf = []\nfor n in range(9):\n dwarf.append(int(input()))\ndwarf.sort()\nall_dwarf = sum(dwarf)\nfound = False\nfor i in range(8):\n for j in range(i+1, 9):\n if all_dwarf - dwarf[i] - dwarf[j] == 100:\n dwarf.pop(dwarf.index(dwarf[i]))\n dwarf.pop(dwarf.index(dwarf[j-1]))\n found = True\n break\n if found:\n break\nfor dwa in dwarf:\n print(dwa)"},{"alpha_fraction":0.6240601539611816,"alphanum_fraction":0.6315789222717285,"avg_line_length":21.33333396911621,"blob_id":"fe069c22940eb8350c9b348e5840ac763e43904e","content_id":"b671fe63d1017fc1f2fb97b0763fd18d400307b8","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":133,"license_type":"no_license","max_line_length":67,"num_lines":6,"path":"/알고리즘/온라인저지/2022/09/0927/수 정렬하기 5.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\n\nN = int(input().rstrip())\nfor i in sorted([int(input().rstrip()) for _ in [0]*(N)]): print(i)"},{"alpha_fraction":0.41981130838394165,"alphanum_fraction":0.4245283007621765,"avg_line_length":24,"blob_id":"406883a14d39be71fce2082477af3ea690f2226f","content_id":"7f7c7ebde5e46310c8521e68c8ce6ba9c320f581","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":478,"license_type":"no_license","max_line_length":33,"num_lines":17,"path":"/알고리즘/온라인저지/2022/07/0726/사과 담기 게임.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N, M = map(int, input().split())\nJ = int(input())\nresult, s, e = 0, 1, M\nfor j in range(J):\n A = int(input())\n if s<=A<=e: # 움직이지 않아도 될 때\n continue\n else: # 움직여야 할 때\n if A < s: # 좌로 움직일 때\n move = s-A\n result += move \n s, e = s-move, e-move\n elif e < A: # 우로 움직일 때\n move = A-e\n result += move\n s, e = s+move, e+move\nprint(result)"},{"alpha_fraction":0.5605095624923706,"alphanum_fraction":0.5796178579330444,"avg_line_length":18.75,"blob_id":"3cc4f0f3d54594d150c93db2f40675d4e4531984","content_id":"32f7d0c62b800c8ecdd547111f4506fd4f183b05","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":157,"license_type":"no_license","max_line_length":32,"num_lines":8,"path":"/알고리즘/온라인저지/2022/03/0331/치킨 두 마리 (...).py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"A, B = map(int, input().split())\nchicken = int(input())\nresult = 0\nif A+B >= chicken*2:\n result = A + B - chicken*2\nelse:\n result = A + B\nprint(result)"},{"alpha_fraction":0.4131578803062439,"alphanum_fraction":0.44999998807907104,"avg_line_length":20.11111068725586,"blob_id":"f430985660094bc7d47a683bb9725283234680e9","content_id":"b794a39b2a7880a7bf66339cf5dd7823f749af52","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":380,"license_type":"no_license","max_line_length":46,"num_lines":18,"path":"/알고리즘/온라인저지/2022/07/0708/APC는 왜 서브태스크 대회가 되었을까.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N, L, K = map(int, input().split())\nP = [] # problems\nfor n in range(N):\n P.append(tuple(map(int, input().split())))\nP.sort(key=lambda x:x[1])\n# print(P)\nsolved = [0] * N\nk = 0\nresult = 0\nfor i in range(N):\n if k < K:\n if P[i][1] <= L:\n k += 1\n result += 140\n elif P[i][0] <= L:\n k += 1\n result += 100\nprint(result)\n"},{"alpha_fraction":0.5524079203605652,"alphanum_fraction":0.5920680165290833,"avg_line_length":19.823530197143555,"blob_id":"bf1163c08244c46a46f3850c5903bf1b1a346313","content_id":"010af6cc6b1b79c32ba17ecb51454a88548f8267","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":353,"license_type":"no_license","max_line_length":38,"num_lines":17,"path":"/알고리즘/온라인저지/2022/07/0714/통계학.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"from collections import Counter\n\n\nN = int(input())\narr = [int(input()) for _ in range(N)]\narr.sort()\ncommon = Counter(arr).most_common()\nprint(round(sum(arr)/N))\nprint(arr[N//2])\nif len(common) > 1:\n if common[0][1] == common[1][1]:\n print(common[1][0])\n else:\n print(common[0][0])\nelse:\n print(common[0][0])\nprint(arr[-1]-arr[0])"},{"alpha_fraction":0.43497759103775024,"alphanum_fraction":0.5112107396125793,"avg_line_length":14.928571701049805,"blob_id":"e6afa6eb2a7d74036e05bb93544773c00958b112","content_id":"4dcf91f2192056d02af4a63d7a9ed7ce4385c60d","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":223,"license_type":"no_license","max_line_length":49,"num_lines":14,"path":"/알고리즘/SWEA/LEARN/Course/1. Programming Beginner/파이썬 프로그래밍 기초(2)/32차시 3. 자료구조 – 셋, 딕셔너리 - 연습문제 7.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"sen = input()\n\nLETTERS = 0\nDIGITS = 0\n\nfor s in sen:\n if 65 <= ord(s) <= 90 or 97 <= ord(s) <= 122:\n LETTERS += 1\n\n if 48 <= ord(s) <= 57:\n DIGITS += 1\n\nprint('LETTERS', LETTERS)\nprint('DIGITS', DIGITS)\n"},{"alpha_fraction":0.5794947743415833,"alphanum_fraction":0.6032689213752747,"avg_line_length":34.47368240356445,"blob_id":"a8bb59cbaa059a14642f588bf9a0edd2183f933b","content_id":"4eb850d20c76f3329b153f7175f89a2c10d9f70a","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":963,"license_type":"no_license","max_line_length":62,"num_lines":19,"path":"/알고리즘/온라인저지/2021/08/0801/숫자의 개수.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"numbers = [] # 입력받을 숫자의 리스트 초기화\nfor i in range(3): # A, B, C 세개의 숫자를 입력받음\n numbers += [int(input())] # 입력받아서 리스트에 추가\nmultipled = 1 # 다 곱한 값의 초기값 1:O, 0:X\nfor number in numbers: # multipled에 입력받은 숫자 곱해서 집어넣었고\n multipled *= number\nmultipled = str(multipled) # 곱한 값을 str로 변경\ncounts = [] # 숫자들을 셀 리스트 초기화\nfor i in range(10):\n counts.append([]) # 각 카운트들을 담을 빈 리스트 생성\nfor num in multipled:\n for i in range(10):\n if num == str(i): # 순회중인 숫자가 0~9중에 일치하는 수를\n counts[i] += [1] # 확인해서 count 한 번\nfor i in range(10):\n counts[i] = sum(counts[i]) # 카운트한 숫자는 [1, 1, 1] 이렇게 되 있으니까\n # 다 더한 값을 카운트에 재설정\nfor count in counts:\n print(count) # 카운트값들을 출력"},{"alpha_fraction":0.49572649598121643,"alphanum_fraction":0.5341880321502686,"avg_line_length":25.11111068725586,"blob_id":"e8e4392364571628917a3e8b86ca3b88fe5f9f8f","content_id":"efbd706ec6b1f59f020c6bf048f711077419379f","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":234,"license_type":"no_license","max_line_length":81,"num_lines":9,"path":"/알고리즘/온라인저지/2021/08/0815/다이얼.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"dial = {2:\"ABC\", 3:\"DEF\", 4:\"GHI\", 5:\"JKL\", 6:\"MNO\", 7:\"PQRS\", 8:\"TUV\", 9:\"WXYZ\"}\nword = input()\nresult = 0\nfor wor in word:\n for dil in dial:\n if wor in dial[dil]:\n result += dil\nresult += len(word)\nprint(result)"},{"alpha_fraction":0.468137264251709,"alphanum_fraction":0.48774510622024536,"avg_line_length":24.5625,"blob_id":"0eb013050782576e1f3e44ae5f04c6376de07098","content_id":"5bd2afb0741b3f7734ba81b9477db1b908f9fd68","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":408,"license_type":"no_license","max_line_length":61,"num_lines":16,"path":"/알고리즘/온라인저지/2022/08/0801/먹을 것인가 먹힐 것인가.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"T = int(input())\nfor t in range(T):\n N, M = map(int, input().split())\n A = sorted(list(map(int, input().split())), reverse=True)\n B = sorted(list(map(int, input().split())), reverse=True)\n i = j = 0\n result = 0\n while i<N and j<M:\n if A[i] > B[j]:\n result += M-j\n i += 1\n else:\n j += 1\n print(result)\n\n# https://www.acmicpc.net/problem/7795"},{"alpha_fraction":0.5077399611473083,"alphanum_fraction":0.5263158082962036,"avg_line_length":17,"blob_id":"5b5300c6298d92ab3a09c9dfa936d9fde03121f1","content_id":"0514a5505f54889b5c52f45d17e6f983f206dba8","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":323,"license_type":"no_license","max_line_length":49,"num_lines":18,"path":"/알고리즘/온라인저지/2022/10/1002/죽음의 게임.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\n\nN, K = map(int, input().rstrip().split())\ndeath = [int(input().rstrip()) for _ in range(N)]\nresult = 0\ni = 0\nvisited = [0]*N\nwhile i != K:\n if not visited[i]:\n visited[i] = 1\n i = death[i]\n result += 1\n else: \n print(-1)\n exit()\nprint(result)"},{"alpha_fraction":0.465568870306015,"alphanum_fraction":0.47604790329933167,"avg_line_length":30.85714340209961,"blob_id":"79d38458c02f609cfabab69330fb1079df89c8eb","content_id":"f02a7b28896863fc8213a4dcf0fcd48b0aa43beb","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":668,"license_type":"no_license","max_line_length":67,"num_lines":21,"path":"/알고리즘/온라인저지/2021/08/0815/블랙잭_영남이 덕분에 성공.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N, M = map(int, input().split())\ncards = list(map(int, input().split()))\nblackjack = cards[0]+cards[1]+cards[2]\ncards.sort()\nfor i in range(N-2):\n if cards[i] > M:\n break\n for j in range(i+1, N-1):\n if cards[i] + cards[j] > M:\n break\n for k in range(j+1, N):\n if cards[i] + cards[j] + cards[k] > M:\n break\n is_this_blackjack = cards[i]+cards[j]+cards[k]\n if is_this_blackjack == M:\n print(M)\n exit()\n else:\n if abs(M - is_this_blackjack) < abs(M - blackjack):\n blackjack = is_this_blackjack\nprint(blackjack)"},{"alpha_fraction":0.46859902143478394,"alphanum_fraction":0.48792269825935364,"avg_line_length":28.714284896850586,"blob_id":"e348f06afbca14ad86467dff0bdedcc723d81c71","content_id":"2af9d999be9272ef6be2366c639661bde4d74c62","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":207,"license_type":"no_license","max_line_length":47,"num_lines":7,"path":"/알고리즘/온라인저지/2022/06/0626/나무 조각.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"arr = list(map(int, input().split()))\ntmp = sorted(arr)\nwhile arr != tmp:\n for i in range(len(arr)-1):\n if arr[i] > arr[i+1]:\n arr[i], arr[i+1] = arr[i+1], arr[i]\n print(*arr)"},{"alpha_fraction":0.4787878692150116,"alphanum_fraction":0.5030303001403809,"avg_line_length":15.600000381469727,"blob_id":"34f9eb7ded60f0191d8fd16de5a0ae1f7e98551b","content_id":"1404cebde3f33f92f0402c17e3fe95af36b1dd90","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":165,"license_type":"no_license","max_line_length":44,"num_lines":10,"path":"/알고리즘/온라인저지/2022/02/0202/나는 요리사다.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"winner = 0\nmax_p = 0\n\nfor i in range(1, 6):\n p = sum(list(map(int, input().split())))\n if p > max_p:\n max_p = p\n winner = i\n\nprint(winner, max_p)"},{"alpha_fraction":0.4573054909706116,"alphanum_fraction":0.4775458574295044,"avg_line_length":25.81355857849121,"blob_id":"2c384c00de3e5dd1f84484a6d49227fc4fddaa2b","content_id":"bc436ae94342912704409000914fd95ad726f772","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1667,"license_type":"no_license","max_line_length":87,"num_lines":59,"path":"/알고리즘/온라인저지/2022/10/1006/빙산.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\nfrom collections import deque\n\ninput = sys.stdin.readline\ndy, dx = [-1, 1, 0, 0], [0, 0, -1, 1]\n\ndef count_iceberg():\n Q = deque()\n visited = [[0]*M for _ in range(N)]\n iceberg = 0\n for i in range(N):\n for j in range(M):\n if arr[i][j] and not visited[i][j]:\n iceberg += 1\n Q.append((i, j))\n visited[i][j] = 1\n while Q:\n y, x = Q.popleft()\n for k in range(4):\n ny, nx = y+dy[k], x+dx[k]\n if 0<=ny<N and 0<=nx<M and not visited[ny][nx] and arr[ny][nx]:\n Q.append((ny, nx))\n visited[ny][nx] = 1\n return iceberg\n\ndef check_seawater():\n tmp_Q = deque()\n for i in range(N):\n for j in range(M):\n if arr[i][j] == 0:\n tmp_Q.append((i, j))\n return tmp_Q\n\ndef melt_iceberg(seawater_Q):\n while seawater_Q:\n y, x = seawater_Q.popleft()\n for k in range(4):\n ny, nx = y+dy[k], x+dx[k]\n if 0<=ny<N and 0<=nx<M and arr[ny][nx]>0:\n arr[ny][nx] -= 1\n return\n\nN, M = map(int, input().rstrip().split())\narr = [list(map(int, input().rstrip().split())) for _ in range(N)]\nQ = deque()\nresult = 0\nwhile count_iceberg() == 1:\n result += 1\n seawater_Q = check_seawater()\n melt_iceberg(seawater_Q)\nif count_iceberg() == 0: print(0)\nelse: print(result)\n\n\"\"\"\n두 덩어리로 분리되는 최초의 시간을 구해야 한다\n끝까지 두덩이가 되지 않고 통째로 녹아버린다면 0을 출력\n\"\"\"\n\n# https://www.acmicpc.net/problem/2573"},{"alpha_fraction":0.40229883790016174,"alphanum_fraction":0.4195402264595032,"avg_line_length":13.583333015441895,"blob_id":"f76f08f07fa306f409656706f53ca18b8910d1ea","content_id":"3d7cbdc71f22f4b2a939ffcc55b02f72b4aa0f3b","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":174,"license_type":"no_license","max_line_length":41,"num_lines":12,"path":"/알고리즘/온라인저지/2022/04/0425/鉛筆 (Pencils).py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N, A, B, C, D = map(int, input().split())\nE = F = 0\nif N%A:\n E = N//A + 1\nelse:\n E = N//A\nif N%C:\n F = N//C + 1\nelse:\n F = N//C\n# print(E, F)\nprint(min(E*B, F*D))"},{"alpha_fraction":0.4746543765068054,"alphanum_fraction":0.5414746403694153,"avg_line_length":24.58823585510254,"blob_id":"8aea8a168501d007b53551db291f8b8489e335ee","content_id":"4b563852e71defe80557232cf3a7742768afebff","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":434,"license_type":"no_license","max_line_length":63,"num_lines":17,"path":"/알고리즘/[템플릿]/Dynamic Programming/다이나믹이 뭐예요.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\ndy, dx = [0, 1, 1], [1, 0, 1] # right, down, right-down\nmod = int(1e9)+7\n\nN, M = map(int, input().rstrip().split())\ndp = [[0]*M for _ in range(N)]\ny, x = 0, 0\nfor i in range(N): dp[i][0] = 1\nfor i in range(M): dp[0][i] = 1\nfor i in range(1, N):\n for j in range(1, M):\n dp[i][j] = (dp[i-1][j] + dp[i][j-1] + dp[i-1][j-1])%mod\nprint(dp[N-1][M-1])\n\n# https://www.acmicpc.net/problem/14494"},{"alpha_fraction":0.4393063485622406,"alphanum_fraction":0.4797687828540802,"avg_line_length":23.85714340209961,"blob_id":"dcce28229834651ee2cb5885a10cd5d127c02bca","content_id":"0142b136fa2f5a1d91410735d0b0e5621fbd3aca","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":173,"license_type":"no_license","max_line_length":36,"num_lines":7,"path":"/알고리즘/온라인저지/2023/04/0418/겨울왕국 티켓 예매.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"H, W = ord('L')-65+1, 4\nfor _ in range(int(input())):\n N, M = map(int, input().split())\n result = -1\n if N>=H and M>=W:\n result = (H-1)*M+4\n print(result)"},{"alpha_fraction":0.5508981943130493,"alphanum_fraction":0.5928143858909607,"avg_line_length":32.599998474121094,"blob_id":"9e42b3e0d516df438a5618438b30ec94cba49b34","content_id":"be538d3c8e476c6150e5f104359db4b5b0abf6d1","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":167,"license_type":"no_license","max_line_length":54,"num_lines":5,"path":"/알고리즘/온라인저지/2023/04/0422/2017 아주대학교 프로그래밍 경시대회 (Small).py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"scores = []\nfor i in range(1, int(input())+1):\n scores.append(list(map(int, input().split()))+[i])\nscores.sort(key=lambda x:(-x[0], x[1], x[2]))\nprint(scores[0][3])"},{"alpha_fraction":0.56886225938797,"alphanum_fraction":0.5888223648071289,"avg_line_length":19.91666603088379,"blob_id":"99ce2fba60e98428a56234311f4fe940be51a67d","content_id":"6da09cb928f19fe48d933f0138bf19213368fed5","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":739,"license_type":"no_license","max_line_length":58,"num_lines":24,"path":"/알고리즘/온라인저지/2022/08/0808/가희와 키워드.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\n\nN, M = map(int, input().split())\nK = set(input().rstrip() for _ in range(N)) # keyword\nfor _ in range(M): \n tmp = set(input().rstrip().split(',')) # 개행문자('\\n') 제거\n K -= tmp\n print(len(K))\n\n\"\"\"\n시간 : 21분\n풀이\n 시간은 1.5초지만 메모리가 넉넉한 문제이다\n 제출언어로 PyPy를 사용한다\n 빠른 입력을 위해 \n input = sys.stdin.readline도 사용한다\n N과 M은 둘 다 200,000으로 큰 편이다\n set 클래스인 A와 B에 대해서 A-B가 가능하다\n 키워드를 담은 set(K)에서\n 가희가 메모로 작성하여 없앤 키워드를 빼주고\n 매번 글을 쓰고 남은 키워드 개수를 출력한다\n\"\"\""},{"alpha_fraction":0.38064515590667725,"alphanum_fraction":0.4580645263195038,"avg_line_length":21.14285659790039,"blob_id":"4c6a6ea46ea8b3ba87b302e233d4dda96120f30d","content_id":"ea0813fdf249da916305677791e3f4216ee45468","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":155,"license_type":"no_license","max_line_length":43,"num_lines":7,"path":"/알고리즘/온라인저지/2022/06/0606/나누기.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = int(input())\nF = int(input())\ntmp = ((N//100)*100)\nif tmp%F:\n print((str((tmp//F)*F + F)+'0')[-3:-1])\nelse:\n print((str((tmp//F)*F)+'0')[-3:-1])\n"},{"alpha_fraction":0.47983869910240173,"alphanum_fraction":0.5080645084381104,"avg_line_length":23.899999618530273,"blob_id":"a9352abad8ba5a90237010f928c484c9e9ae5e13","content_id":"6d71cd04fc81339dea1d96560eacc403deb8a8a5","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":248,"license_type":"no_license","max_line_length":45,"num_lines":10,"path":"/알고리즘/온라인저지/2022/10/1003/피보나치.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\n\nfor t in range(1, int(input().rstrip())+1):\n P, Q = map(int, input().rstrip().split())\n a, b = 1, 1\n for _ in range(P-2): a, b = b, (a+b)%Q\n if Q == 1: b = 0\n print('Case #{}: {}'.format(t, b))"},{"alpha_fraction":0.5232323408126831,"alphanum_fraction":0.5535353422164917,"avg_line_length":19.66666603088379,"blob_id":"8c016928c58eebc240fdafd98c40c8b88ce75ba0","content_id":"1de2a8d0af9cafcce41caa85f8e9de5288d65ade","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":495,"license_type":"no_license","max_line_length":48,"num_lines":24,"path":"/알고리즘/온라인저지/2022/09/0912/별 찍기 - 10.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"from copy import deepcopy\n\nN = int(input())\nfor k in range(1, 8): \n if N == 3**k: break\nwidth = k\nsquare = ['*'*3] + ['* *'] + ['*'*3]\n\nlevel = 0\ntmp, result = deepcopy(square), deepcopy(square)\n\nwhile level < k-1:\n level += 1\n result = []\n for s in tmp:\n result.append(s*3)\n for s in tmp:\n result.append(s + ' '*(3**level) + s)\n for s in tmp:\n result.append(s*3)\n tmp = deepcopy(result)\nfor r in result: print(r)\n\n# https://www.acmicpc.net/problem/2447"},{"alpha_fraction":0.38513514399528503,"alphanum_fraction":0.46621620655059814,"avg_line_length":23.83333396911621,"blob_id":"a5a0909b799e9689e0f91e691f8f9ba86ad0570c","content_id":"cc4d6bab3d888eca1eab59ff3f69b05bfdf2f427","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":148,"license_type":"no_license","max_line_length":37,"num_lines":6,"path":"/알고리즘/온라인저지/2022/07/0731/피보나치 수 4.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = int(input())\ndp = [0, 1]\nif N > 1: dp += [0] * (N-1)\nfor i in range(2, N+1):\n dp[i] = dp[i-1] + dp[i-2]\nprint(dp[-1]) if N != 0 else print(0)"},{"alpha_fraction":0.4324324429035187,"alphanum_fraction":0.45945945382118225,"avg_line_length":14.904762268066406,"blob_id":"0607d3ad476e524f828a81dfafafe94373438a87","content_id":"d436c730334632964476d89869140b03e0deb0e7","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":333,"license_type":"no_license","max_line_length":44,"num_lines":21,"path":"/알고리즘/온라인저지/2022/09/0919/영식이와 친구들.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\n\nN, M, L = map(int, input().rstrip().split())\narr = [0]*N\narr[0] += 1\nresult = 0\nnow = 0\nwhile max(arr)<M:\n if arr[now]%2:\n now += L\n now %= N\n arr[now] += 1\n else:\n now -= L\n now += N\n now %= N\n arr[now] += 1\n result += 1\nprint(result)"},{"alpha_fraction":0.4039604067802429,"alphanum_fraction":0.4534653425216675,"avg_line_length":20.04166603088379,"blob_id":"646918ea1308c5f15f208b7b96d6660a3721416a","content_id":"f112be1d9387d246c604d6daeaec79e46cb0f63a","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":505,"license_type":"no_license","max_line_length":45,"num_lines":24,"path":"/알고리즘/온라인저지/2021/12/1216/사분면.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = int(input())\n\nquadrant = [0 for _ in range(5)]\n\nfor n in range(N):\n x, y = map(int, input().split())\n\n if x == 0 or y == 0:\n quadrant[4] += 1\n elif x > 0 and y > 0:\n quadrant[0] += 1\n elif x < 0 and y > 0:\n quadrant[1] += 1\n elif x < 0 and y < 0:\n quadrant[2] += 1\n elif x > 0 and y < 0:\n quadrant[3] += 1\n\nfor i in range(5):\n if i == 4:\n print('AXIS: {}'.format(quadrant[i]))\n break\n\n print('Q{}: {}'.format(i+1, quadrant[i]))\n"},{"alpha_fraction":0.43220338225364685,"alphanum_fraction":0.4406779706478119,"avg_line_length":18.83333396911621,"blob_id":"99d0d9955da0c0454dffdc8b47e34b235f92a036","content_id":"5dff70e872b27fb4fc862bd469c7b8302f780991","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":118,"license_type":"no_license","max_line_length":35,"num_lines":6,"path":"/알고리즘/온라인저지/2021/08/0822/달팽이는 올라가고 싶다.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"A, B, V = map(int, input().split())\nif (V-B)%(A-B):\n day = (V-B)//(A-B) + 1\nelse:\n day = (V-B)//(A-B)\nprint(day)"},{"alpha_fraction":0.4656488597393036,"alphanum_fraction":0.49618321657180786,"avg_line_length":17.85714340209961,"blob_id":"a4d8a7d0425bf41d1b4dab4e05b638f08a814997","content_id":"d31bee524d636eb83c4d45382d134d78cb59e384","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":131,"license_type":"no_license","max_line_length":32,"num_lines":7,"path":"/알고리즘/온라인저지/2023/05/0514/악마의 제안.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"K, N = map(int, input().split())\nresult = -1\nif N != 1:\n A, B = N*K, N-1\n result = A//B\n if A%B: result += 1\nprint(result)"},{"alpha_fraction":0.48695650696754456,"alphanum_fraction":0.4956521689891815,"avg_line_length":37.66666793823242,"blob_id":"f65717f7346d74f0d215de30f95fa609bf014c73","content_id":"0a0d7886d8cc34161109c11e0f6ddce4f11f7e69","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":115,"license_type":"no_license","max_line_length":47,"num_lines":3,"path":"/알고리즘/온라인저지/2023/01/0110/폰 노이만.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"for _ in range(int(input())):\n N, D, A, B, F = map(float, input().split())\n print(int(N), f'{D/(A+B)*F:.6f}')"},{"alpha_fraction":0.50971919298172,"alphanum_fraction":0.5356371402740479,"avg_line_length":32.07143020629883,"blob_id":"e48be24025c536ebdceb261d16ff635c3a969686","content_id":"6e922edcac4f86837ea7be48f87e3feff172e3e6","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":647,"license_type":"no_license","max_line_length":49,"num_lines":14,"path":"/알고리즘/온라인저지/2021/07/0731/3 6 9 게임의 왕이 되자.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"def three_six_nine(n):\n n = str(n) # 입력받은 숫자를 str로 변환\n tsn_list = \"369\" # 369를 확인하는 str값 설정\n result = \"\" # 초기 공백 결과값\n for num in n: # str로 바꿔준 n을 순회\n if num in tsn_list: # n의 각 숫자가 3,6,9일때\n result += \"X\" # 결과값에 박수 한 번\n if result == \"\": # 순회 다 해도 박수가 없으면\n result += n # 원본 숫자 출력\n return result # 결과값 반환\n\nn = int(input()) # 숫자를 입력받고\nfor i in range(1, n+1): # 1부터 입력값까지 반복\n print(three_six_nine(i), sep = \"\") # 공백단위로 출력\n"},{"alpha_fraction":0.4336734712123871,"alphanum_fraction":0.4591836631298065,"avg_line_length":23.625,"blob_id":"6f55fdc4fa3f64482286104e6f5c8e29a6518397","content_id":"6fca9a427475178a5820519b77c8d8817aa9f804","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":196,"license_type":"no_license","max_line_length":42,"num_lines":8,"path":"/알고리즘/온라인저지/2023/05/0516/Gauß.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"for i in range(int(input())):\n N, M = map(int, input().split())\n A = M-N+1\n B = A//2\n result = (N+M)*B\n if A%2:\n result += (N+M)//2\n print(f'Scenario #{i+1}:\\n{result}\\n')"},{"alpha_fraction":0.529629647731781,"alphanum_fraction":0.5666666626930237,"avg_line_length":19.846153259277344,"blob_id":"96c8e1747d340169bc1136820623445af8cba9a6","content_id":"68595d9aeb4d10e64a30f224de3ef1fc6865ab91","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":270,"license_type":"no_license","max_line_length":35,"num_lines":13,"path":"/알고리즘/온라인저지/2022/06/0609/농구 경기.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"table = [0]*26\nN = int(input())\nfor n in range(N):\n first = ord(input()[0]) - 97\n table[first] += 1\n# print(table)\nresult = ''\nfor i in range(len(table)):\n if table[i] >= 5:\n result = result + chr(i+97)\nif not result:\n result = 'PREDAJA'\nprint(result)"},{"alpha_fraction":0.5793871879577637,"alphanum_fraction":0.5905292630195618,"avg_line_length":17.947368621826172,"blob_id":"6e7f56da0c750d5af0b5bca0a6c98c34e02af949","content_id":"677b4a8a3a6eda7df600de055b12fa66c8aaf0b1","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":359,"license_type":"no_license","max_line_length":47,"num_lines":19,"path":"/알고리즘/온라인저지/2022/10/1009/트로피 진열.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"from audioop import reverse\nfrom re import A\nimport sys\n\ninput = sys.stdin.readline\n\ndef check(arr):\n result = 1\n biggest = arr[0]\n for a in arr:\n if a>biggest:\n biggest = a\n result += 1\n return result\n\nN = int(input().rstrip())\narr = [int(input().rstrip()) for _ in range(N)]\nprint(check(arr))\nprint(check(arr[::-1]))"},{"alpha_fraction":0.4727272689342499,"alphanum_fraction":0.5454545617103577,"avg_line_length":17.66666603088379,"blob_id":"3c76ccd668a06618fb744c0b812588f8680ba0ec","content_id":"ebc7e8efc6274496dce58dcbf1c56a471c28a293","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":55,"license_type":"no_license","max_line_length":40,"num_lines":3,"path":"/알고리즘/온라인저지/2022/09/0925/악수.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"a=b=1\nfor _ in [0]*int(input()):a,b=b,(a+b)%10\nprint(a)"},{"alpha_fraction":0.48275861144065857,"alphanum_fraction":0.5344827771186829,"avg_line_length":18.5,"blob_id":"ac158ef99ff55cce4aff99a3223a8eae61624491","content_id":"bf295b928eeb3bd4627d3c55c86de34dab745a28","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":116,"license_type":"no_license","max_line_length":33,"num_lines":6,"path":"/알고리즘/온라인저지/2022/09/0913/직사각형을 만드는 방법.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = int(input())\nresult = 0\nfor i in range(1, int(N**0.5)+1):\n tmp = N//i - (i-1)\n result += tmp\nprint(result)"},{"alpha_fraction":0.4781849980354309,"alphanum_fraction":0.5340313911437988,"avg_line_length":29.210525512695312,"blob_id":"a582a64625e08ef546c5a39c294549eadc67eec7","content_id":"4ee4c1599337cd4e7bff1692e1ac1632418d564a","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":573,"license_type":"no_license","max_line_length":51,"num_lines":19,"path":"/알고리즘/온라인저지/2022/12/1209/Hawk eyes.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"def mix(order):\n if order == 'A':\n result[0], result[1] = result[1], result[0]\n elif order == 'B':\n result[0], result[2] = result[2], result[0]\n elif order == 'C':\n result[0], result[3] = result[3], result[0]\n elif order == 'D':\n result[2], result[1] = result[1], result[2]\n elif order == 'E':\n result[3], result[1] = result[1], result[3]\n elif order == 'F':\n result[2], result[3] = result[3], result[2]\n\nresult = [1, 0, 0, 2]\nfor order in input():\n mix(order)\nprint(result.index(1)+1)\nprint(result.index(2)+1)"},{"alpha_fraction":0.4952380955219269,"alphanum_fraction":0.5047619342803955,"avg_line_length":34.33333206176758,"blob_id":"d13e07760ff14e0820d2b3e13f68136399c9f6d7","content_id":"6f85bace3f0ad7ceb858c0e6dd546bb6f85db37e","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":105,"license_type":"no_license","max_line_length":59,"num_lines":3,"path":"/알고리즘/온라인저지/2023/01/0123/자기복제수.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"for _ in range(int(input())):\n N = input()\n print('YES' if N == str(int(N)**2)[-len(N):] else 'NO')"},{"alpha_fraction":0.5040650367736816,"alphanum_fraction":0.5203251838684082,"avg_line_length":16.714284896850586,"blob_id":"d95b7e68328c000663165f74331bdbc84165d25d","content_id":"f4bedaf6d33277c377491ee45a430952c15dc240","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":123,"license_type":"no_license","max_line_length":24,"num_lines":7,"path":"/알고리즘/온라인저지/2022/08/0828/사장님 도박은 재미로 하셔야 합니다.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"result = 0\nwhile True:\n money = int(input())\n if money == -1:\n print(result)\n break\n result += money"},{"alpha_fraction":0.38461539149284363,"alphanum_fraction":0.39835163950920105,"avg_line_length":23.266666412353516,"blob_id":"59233dc2edb549cf11a3b9d7ff72d384abd73fbd","content_id":"42df7147547984d6c79ef895e8e339399ad1d12e","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":364,"license_type":"no_license","max_line_length":37,"num_lines":15,"path":"/알고리즘/온라인저지/2022/09/0903/쌍의 합.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"for _ in range(int(input())):\n N = int(input())\n result = []\n for n in range(1, (N//2)+1):\n A, B = n, N-n\n if A != B:\n result.append((A, B))\n print(f'Pairs for {N}: ', end='')\n cnt = 0\n for r in result:\n print(*r, end='')\n cnt += 1\n if cnt != len(result):\n print(', ', end='')\n print()\n"},{"alpha_fraction":0.37823835015296936,"alphanum_fraction":0.4715026021003723,"avg_line_length":16.18181800842285,"blob_id":"238202db72b4d41a4c4798e5e5990080d3fcea72","content_id":"e9271e35f72d9f4f9ef706e9c0eaed0201a0c034","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":225,"license_type":"no_license","max_line_length":60,"num_lines":11,"path":"/알고리즘/SWEA/LEARN/Course/1. Programming Beginner/파이썬 프로그래밍 기초(2)/3차시 2. 자료구조 – 리스트, 튜플 - 연습문제 1.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"scores = [(90, 80), (85, 75), (90, 100)]\n\ns = 0\navg = 0\ni = 0\n\nfor score in scores:\n i += 1\n s = sum(score)\n avg = s/2\n print('{}번 학생의 총점은 {}점이고, 평균은 {}입니다.'.format(i, s, avg))\n "},{"alpha_fraction":0.41265398263931274,"alphanum_fraction":0.4440089464187622,"avg_line_length":23.81944465637207,"blob_id":"d741dd72442868550a9ea209d9a53dc92f11e34e","content_id":"0ffdf49d206be3ec3d03d3a838fa02ee9223f007","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":2162,"license_type":"no_license","max_line_length":66,"num_lines":72,"path":"/알고리즘/온라인저지/2022/07/0709/섬의 개수.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"\"\"\"\n배열을 탐색하다가 섬을 발견하면\n 섬의 개수 ++\n 섬을 바다로 만든다 (1 -> 0) # BFS (DFS로 하는데 메모리초과가 계속 남 ㅜㅜ)\n 발견한 섬의 개수를 출력\n\"\"\"\nfrom collections import deque # BFS용 double ended queue\n\n\ndef bfs(y, x): # 섬을 바다로 만드는 BFS함수\n Q.append((y, x))\n while Q:\n y, x = Q.popleft()\n if arr[y][x] == 0:\n continue\n arr[y][x] = 0\n for i in range(8):\n ny = y+dy[i]\n nx = x+dx[i]\n if 0<=ny<H and 0<=nx<W and arr[ny][nx]:\n Q.append((ny, nx))\n\n\ndy = [-1, 1, 0, 0, 1, 1, -1, -1] # 대각선 포함한 8방향 델타이동\ndx = [0, 0, -1, 1, 1, -1, 1, -1]\nwhile True:\n W, H = map(int, input().split())\n if W == 0 and H == 0: # 테스트케이스 입력 종료조건\n break\n arr = [list(map(int, input().split())) for _ in range(H)] # 지도\n result = 0 # 섬의 개수\n Q = deque()\n for h in range(H):\n for w in range(W):\n if arr[h][w]: # 섬을 발견하면\n bfs(h, w) # 섬을 바다로 만들기\n result += 1 # 섬의 개수 ++\n print(result) # 섬의 개수 출력\n\n\n# 아래는 재귀함수를 활용한 DFS로 풀었는데\n# 메모리초과를 피하지 못했습니다ㅜㅜ\n# 재귀를 계속 돌면서 함수 내 메모리를 전부 사용한 것 같은데...\n# import sys\n# sys.setrecursionlimit(10**9)\n\n\n# def dfs(y, x): # 섬을 바다로 만들어 주면서 섬 개수 세기\n# if arr[y][x] == 0:\n# return\n# arr[y][x] = 0\n# for i in range(8):\n# ny = y+dy[i]\n# nx = x+dx[i]\n# if 0<=ny<H and 0<=nx<W and arr[ny][nx]:\n# dfs(ny, nx)\n\n\n# dy = [-1, 1, 0, 0, 1, 1, -1, -1]\n# dx = [0, 0, -1, 1, 1, -1, 1, -1]\n# while True:\n# W, H = map(int, input().split())\n# if W == 0 and H == 0:\n# break\n# arr = [list(map(int, input().split())) for _ in range(H)]\n# result = 0\n# for h in range(H):\n# for w in range(W):\n# if arr[h][w]:\n# dfs(h, w)\n# result += 1\n# print(result)"},{"alpha_fraction":0.6880733966827393,"alphanum_fraction":0.6926605701446533,"avg_line_length":23.22222137451172,"blob_id":"47bb257df616eea53fa1b0c255d8eb2e401a4624","content_id":"eef34007a192acd17c7e1d1fd6d1446f3336b7fd","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":218,"license_type":"no_license","max_line_length":54,"num_lines":9,"path":"/알고리즘/온라인저지/2021/08/0829/줄 세우기.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\nstudent_count = int(sys.stdin.readline())\nnumbers = list(map(int, sys.stdin.readline().split()))\nresult = []\nfor i in range(len(numbers)):\n result.insert(numbers[i], i+1)\nresult.reverse()\nprint(*result)\n"},{"alpha_fraction":0.610859751701355,"alphanum_fraction":0.6199095249176025,"avg_line_length":13.800000190734863,"blob_id":"a1b88c0bd5eb6f171e0f1a722e4580becb9a96df","content_id":"36e164cbf19f52bc2e011cd5c5bf8818164c3e4b","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":221,"license_type":"no_license","max_line_length":46,"num_lines":15,"path":"/알고리즘/온라인저지/2021/10/1011/등수 매기기.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = int(input())\n\nstudents = []\n\nfor n in range(N):\n students.append(int(input()))\n\nstudents.sort()\n\ngrades = list(range(1, N+1))\n\nfor i in range(N):\n students[i] = abs(students[i] - grades[i])\n\nprint(sum(students))"},{"alpha_fraction":0.42553192377090454,"alphanum_fraction":0.44964540004730225,"avg_line_length":22.53333282470703,"blob_id":"e673c66160ac51884acdad2ec216ce05c088c4fe","content_id":"888c4cccd1a6c17a27069030cc66f0e164909e9d","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":853,"license_type":"no_license","max_line_length":71,"num_lines":30,"path":"/알고리즘/온라인저지/2021/12/1230/소수.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = int(input())\nM = int(input())\n\nn = M # 소수를 찾을 범위\na = [False,False] + [True]*(n-1) # 0 ~ n 까지의 숫자 리스트\nprimes=[] # 소수 집합\nfor i in range(2,n+1): # 2 ~ n까지 반복\n if a[i]: # 2부터 시작, 해당 숫자가 지워지지 않고 남아있는 소수라면 \n primes.append(i) # 소수 리스트에 추가\n for j in range(2*i, n+1, i): # 해당 소수의 배수들을 \n a[j] = False # 리스트에서 전부 False로 만들기\n\nresult1 = 0\nresult2 = 0\n\nfind_min = False\n\nfor p in primes:\n if p >= N and not find_min:\n find_min = True\n result2 = p\n \n if find_min:\n result1 += p\n \nif find_min:\n print(result1)\n print(result2)\nelse:\n print(-1)"},{"alpha_fraction":0.5068492889404297,"alphanum_fraction":0.5479452013969421,"avg_line_length":23.44444465637207,"blob_id":"efa0b162be31747c5eb691fa0043689dd2f81ea9","content_id":"9c6111bbca13f81616f44bc003140ae2da84bd9a","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":219,"license_type":"no_license","max_line_length":47,"num_lines":9,"path":"/알고리즘/온라인저지/2022/04/0411/일우는 야바위.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N, X, K = map(int, input().split())\ncups = [0] * N\ncups[X-1] = 1\n# print(cups)\nfor k in range(K):\n A, B = map(int, input().split())\n cups[A-1], cups[B-1] = cups[B-1], cups[A-1]\n# print(cups)\nprint(cups.index(1)+1)"},{"alpha_fraction":0.36966824531555176,"alphanum_fraction":0.3909952640533447,"avg_line_length":14.666666984558105,"blob_id":"cbff5d09413cda50063a553d3e903c920f8c95a8","content_id":"f5d4f196e220852b6acac9e5b8f7eac537e95b46","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":422,"license_type":"no_license","max_line_length":31,"num_lines":27,"path":"/알고리즘/온라인저지/2021/09/0910/Router.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\ndef input():\n return sys.stdin.readline()\n\nN = int(input())\nq = [0] * N\np = 0\nwhile True:\n a = int(input())\n if a == -1:\n break\n elif a == 0:\n q.pop(0)\n q.append(0)\n p -= 1\n else:\n if q[-1]:\n continue\n else:\n q[p] = a\n p += 1\nif sum(q):\n for i in q:\n if i:\n print(i, end=' ')\nelse:\n print('empty')"},{"alpha_fraction":0.3734939694404602,"alphanum_fraction":0.46987950801849365,"avg_line_length":15.800000190734863,"blob_id":"abf22fbc7546b5dce3b3c7c12c1c33d646b445a7","content_id":"56fdd128b42e70b803ad84da59d56a0183d09851","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":83,"license_type":"no_license","max_line_length":20,"num_lines":5,"path":"/알고리즘/온라인저지/2021/08/0822/나머지.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"d = [0] * 42\nfor _ in range(10):\n n = int(input())\n d[n%42] = 1\nprint(sum(d))"},{"alpha_fraction":0.6906779408454895,"alphanum_fraction":0.6991525292396545,"avg_line_length":20.545454025268555,"blob_id":"1678dd85d89e4ab51acaca81b93f39ff5697ae19","content_id":"8a91f777956e088fe72d41e4e5867696bbdf25bd","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":236,"license_type":"no_license","max_line_length":67,"num_lines":11,"path":"/알고리즘/온라인저지/2022/11/1117/나는 친구가 적다 (Small).py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\n\nword = input().rstrip()\nkeyword = input().rstrip()\ntmp = ''\nfor w in word:\n if w in 'abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ':\n tmp = tmp+w\nprint(1 if keyword in tmp else 0)"},{"alpha_fraction":0.4435215890407562,"alphanum_fraction":0.5033222436904907,"avg_line_length":21.296297073364258,"blob_id":"f253cc01c49cec93efa65ca86cee73b567a4d9eb","content_id":"e827bfd15aa21396a3e6a19e9826297b9f03598f","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":834,"license_type":"no_license","max_line_length":55,"num_lines":27,"path":"/알고리즘/온라인저지/2021/10/1016/1로 만들기.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"from collections import deque\n\nN = int(input())\n\nif N == 1: # 입력값이 1이면 0을 곧바로 반환합니다\n print(0)\n exit()\n\n# 1에서부터 거꾸로 탐색합니다\nq = deque()\nq.append((1, 0)) # 시작하는 1, 연산횟수 0부터 시작\n\ncheck = set() # 중복연산 방지\n\nwhile q:\n a = q.popleft()\n\n for i in [a[0]*3, a[0]*2, a[0]+1]: # 1에서 출발하기 때문에\n # 연산들을 거꾸로 실행\n if i == N: # N을 찾으면\n print(a[1]+1) # 연산횟수 1회 더하여 출력\n exit() # 바로 코드를 종료\n\n if i not in check and 1 <= i <= 1000000: # 가지치기\n # N은 1000000을 넘지 않는 자연수입니다\n check.add(i) # 범위를 만족하면 check에 추가\n q.append((i, a[1]+1)) # BFS 대기열에 추가\n"},{"alpha_fraction":0.5248869061470032,"alphanum_fraction":0.5429864525794983,"avg_line_length":19.18181800842285,"blob_id":"2a1de6f8c097c6714747f8e0678e0d1c898d5695","content_id":"00fb7bbec6973bed5f12409192aa35717c360b42","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":221,"license_type":"no_license","max_line_length":41,"num_lines":11,"path":"/알고리즘/온라인저지/2022/07/0730/2+1 세일.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = int(input())\nP = [] # price\nfor n in range(N): P.append(int(input()))\nP.sort(reverse=True)\nresult = 0\nfor i in range(0, N, 3):\n try:\n result += sum(P[i:i+2])\n except:\n result += P[i:]\nprint(result)"},{"alpha_fraction":0.6243094205856323,"alphanum_fraction":0.6464088559150696,"avg_line_length":17.200000762939453,"blob_id":"6ffa92dcb21acea0b85b62c5f8d82324f598fe8e","content_id":"49a1f55543b7824778e1c831d4ecee780df33ecf","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":181,"license_type":"no_license","max_line_length":42,"num_lines":10,"path":"/알고리즘/온라인저지/2022/02/0222/과목선택.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"science = [int(input()) for _ in range(4)]\nsocial = [int(input()) for _ in range(2)]\n\nscience.sort(reverse=True)\n\nresult = 0\n\nresult += sum(science[:3]) + max(social)\n\nprint(result)"},{"alpha_fraction":0.44897958636283875,"alphanum_fraction":0.47755101323127747,"avg_line_length":16.5,"blob_id":"2320c53a56dae959300b621d051ecf26fc1b0564","content_id":"bfd1c879c6c46531fc4137f9119a5cd8f1e761d5","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":245,"license_type":"no_license","max_line_length":42,"num_lines":14,"path":"/알고리즘/온라인저지/2022/02/0207/최댓값.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"maxx = 0\nmaxi = 0\nmaxj = 0\n\nfor i in range(9):\n line = list(map(int, input().split()))\n \n for j in range(9):\n if line[j] > maxx:\n maxx = line[j] \n maxi, maxj = i, j\n\nprint(maxx)\nprint(maxi+1, maxj+1)\n"},{"alpha_fraction":0.5443925261497498,"alphanum_fraction":0.5630841255187988,"avg_line_length":18.5,"blob_id":"7251d55610e6ac81de3323a94b8e9e71609b7b9d","content_id":"23c599716e0e3a4cbef555028c2e8e7c810a33b6","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":428,"license_type":"no_license","max_line_length":41,"num_lines":22,"path":"/알고리즘/온라인저지/2022/11/1104/찍기.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\n\nstudent = [\n 'ABCABCABCABC',\n 'BABCBABCBABC',\n 'CCAABBCCAABB',\n]\nN = int(input().rstrip())\nanswer = input().rstrip()\nresult = [0, 0, 0]\nfor i in range(N):\n for j in range(3):\n if answer[i] == student[j][i%12]:\n result[j] += 1\nIDs = ['Adrian', 'Bruno', 'Goran']\nmaxx = max(result)\nprint(maxx)\nfor i in range(3):\n if result[i] == maxx:\n print(IDs[i])"},{"alpha_fraction":0.5270935893058777,"alphanum_fraction":0.5714285969734192,"avg_line_length":28.14285659790039,"blob_id":"30a25931616b2ef6937dfe891deaea72cdaa0fb8","content_id":"a4114167277cdbab29ad9692a1ccb0f1650882e9","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":203,"license_type":"no_license","max_line_length":41,"num_lines":7,"path":"/알고리즘/온라인저지/2022/11/1129/이교수님의 시험.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = int(input())\ncorrect = [1, 2, 3, 4, 5]\nfor answer in range(1, N+1):\n arr = list(map(int, input().split()))\n if arr[:5] != correct: continue\n if arr[5:] != correct: continue\n print(answer)"},{"alpha_fraction":0.4822694957256317,"alphanum_fraction":0.4893617033958435,"avg_line_length":19.285715103149414,"blob_id":"b52f1a55c23402cab543b69b2946c3f2ac303f27","content_id":"53291c653d7f2677189c43a7d0753c415b3cea22","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":141,"license_type":"no_license","max_line_length":32,"num_lines":7,"path":"/알고리즘/온라인저지/2022/09/0903/최소공배수.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"def gcd(a, b):\n while b > 0: a, b = b, a%b\n return a\n\nA, B = map(int, input().split())\nGCD = gcd(A, B)\nprint(GCD * (A//GCD) * (B//GCD))"},{"alpha_fraction":0.607594907283783,"alphanum_fraction":0.607594907283783,"avg_line_length":21.714284896850586,"blob_id":"ccd944d4e831fa17d2728e36fc20227465893322","content_id":"fff69a3e69e485f7b533b783c534d9f107c50694","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":270,"license_type":"no_license","max_line_length":43,"num_lines":7,"path":"/알고리즘/온라인저지/2021/07/0730/[기초-산술연산] 정수 2개 입력받아 거듭제곱 계산하기.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"# 두 변수를 입력받아서 각각 저장한다\n# .split()이 하는 일이, 결국 input()받은 건 하나의 str인데\n# 그걸 공백으로 쪼개서 각각 저장하는 기능을 한거다\na, b = input().split()\n# **는 거듭제곱\nc = int(a)**int(b) \nprint(c)"},{"alpha_fraction":0.3464052379131317,"alphanum_fraction":0.379084974527359,"avg_line_length":17.399999618530273,"blob_id":"28bc9eb73169acef4c8c9c1818213a68de320365","content_id":"280983134c50c67bcad0e8a608eafb2e11a3e8e6","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":459,"license_type":"no_license","max_line_length":36,"num_lines":25,"path":"/알고리즘/온라인저지/2022/02/0205/문자열 분석.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"upper = 'ABCDEFGHIJKLMNOPQRSTUVWXYZ'\nlower = 'abcdefghijklmnopqrstuvwxyz'\nnum = '0123456789'\n\n\nwhile True:\n try:\n a = b = c = d = 0\n \n sen = input()\n \n for s in sen:\n if s in upper:\n b += 1\n elif s in lower:\n a += 1\n elif s in num:\n c += 1\n elif s == ' ':\n d += 1\n\n print(a, b, c, d)\n\n except:\n break"},{"alpha_fraction":0.589353621006012,"alphanum_fraction":0.5969581604003906,"avg_line_length":21,"blob_id":"a99a7269d47c7ddda4b4fe485464bebd81571fd5","content_id":"d2f992a14ec8ec0cc55ed229b128dfa6bac8492e","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":263,"license_type":"no_license","max_line_length":38,"num_lines":12,"path":"/알고리즘/온라인저지/2022/09/0923/최대 힙.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\nfrom heapq import heappush, heappop\n\ninput = sys.stdin.readline\n\nHQ = []\nfor _ in range(int(input().rstrip())):\n num = int(input().rstrip())\n if num: heappush(HQ, (-num, num))\n else: \n if HQ: print(heappop(HQ)[1])\n else: print(0)"},{"alpha_fraction":0.5037453174591064,"alphanum_fraction":0.5599250793457031,"avg_line_length":27.891891479492188,"blob_id":"a5fa93ea7e5093b470e1054bbaed2db7d3a1dbe6","content_id":"8ac4b3475278057bf810ea88ea1b01a2dfe29a4b","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1720,"license_type":"no_license","max_line_length":72,"num_lines":37,"path":"/알고리즘/온라인저지/2021/08/0807/셀프 넘버.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"\"\"\"\n함수 d(75) = 75 + 7 + 5 = 75 + 12 + 87\n87의 생성자(이전항) = 75\n생성자(이전항)가 없는 숫자 = 셀프 넘버\n셀프넘버 = 자연수 - 셀프넘버가 아닌 수\n셀프넘버가 아닌 수 \n = 생성자가 있는 수\n = N까지 함수d 돌려서 나온 값들\n셀프넘버가 아닌 수 리스트를 만들고 \nN까지와, 셀프넘버아닌수 리스트를 이중순회 하면서\n리스트안에 없으면 출력\n\"\"\"\n\nN = 10000 # 순회 범위\n\ndef Kaprekar(n): # n본인과 각 자리수들을 더하는 함수\n # Kaprekar를 통해 만들어진 값은 생성자가 존재하는 \"셀프넘버가 아닌 숫자\"\n # 10의 자리 : n + n%10 + (n//10)%10\n # 100의 자리 : n + n%10 + (n//10)%10 + (n//100)%10\n def Kapre(n): # 각 자릿수를 더하는 재귀함수\n result = 0 # 결과값 초기화\n if n < 10: # 한 자리수 일때\n result += n # 결과값에 저장\n else: # 두 자리 이상일 때\n return n%10 + Kapre(n//10) # 1의 자리수 값과 재귀호출 반환\n return result # 각 자리수를 더한 값을 반환\n return n + Kapre(n) # 처음 input값 n과, 각자리 숫자들을 더한 값을 반환\n\nnot_self_numbers = [] # 셀프넘버가 아닌 수 리스트 초기화\nfor i in range(N + 1): # 10000보다 작거나 \"같은\" 셀프넘버가 아닌 수\n not_self_numbers.append(Kaprekar(i)) # 함수를 통과한 값은 셀프넘버가 아니므로 리스트에 추가\n\nfor i in range(1, N + 1): # 1부터 N까지 순회하면서 \n if i in not_self_numbers: # 순회중인 i가 셀프넘버가 아닌 값이면\n continue # 지나가고\n else: # 셀프넘버이면\n print(i) # 출력"},{"alpha_fraction":0.5553505420684814,"alphanum_fraction":0.5664206743240356,"avg_line_length":21.625,"blob_id":"6866b7ac06b560a1c19e07e04b50482992001c05","content_id":"b2f657285aea0b24f2f8816b1b2e43ca6829ca6e","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":542,"license_type":"no_license","max_line_length":38,"num_lines":24,"path":"/알고리즘/온라인저지/2022/04/0413/홀짝 칵테일.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"from itertools import combinations\n\nnums = list(map(int, input().split()))\nnums.sort(reverse=True)\nodd_drinks = []\neven_drinks = []\nfor i in range(1, len(nums)+1):\n tmp = list(combinations(nums, i))\n # print(tmp)\n for t in tmp:\n a = 1\n for j in t:\n # print(j)\n a *= j\n if a%2:\n odd_drinks.append(a)\n else:\n even_drinks.append(a)\nodd_drinks.sort(reverse=True)\neven_drinks.sort(reverse=True)\nif odd_drinks:\n print(odd_drinks[0])\nelse:\n print(even_drinks[0])"},{"alpha_fraction":0.4548022747039795,"alphanum_fraction":0.5310734510421753,"avg_line_length":19.882352828979492,"blob_id":"826f2e0b1f0d7be685d16d669370a2121c3fb13b","content_id":"17ddaa4e5886a233da9c6e5d04d7ca4c2d087e0e","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":388,"license_type":"no_license","max_line_length":54,"num_lines":17,"path":"/알고리즘/온라인저지/2022/08/0817/터렛.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import math\n\nfor t in range(int(input())):\n x1, y1, r1, x2, y2, r2 = map(int, input().split())\n D = math.sqrt((x1-x2)**2 + (y1-y2)**2) # distance\n result = 0\n if D == 0 and r1 == r2: result = -1\n elif D == abs(r1-r2) or D == r1+r2: result = 1\n elif abs(r1-r2) < D < r1+r2: result = 2\n print(result)\n\n\"\"\"\n일치\n내접or외접\n두 점에서 접함\n접점이 없음\n\"\"\""},{"alpha_fraction":0.4150943458080292,"alphanum_fraction":0.5408805012702942,"avg_line_length":15,"blob_id":"4db976a06b8552e9211984575f2439dd85eefb38","content_id":"339afa166635ef03f3067fe8809b8fffa294d297","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":159,"license_type":"no_license","max_line_length":36,"num_lines":10,"path":"/알고리즘/SWEA/LEARN/Course/1. Programming Beginner/파이썬 프로그래밍 기초(2)/23차시 2. 자료구조 – 리스트, 튜플 - 연습문제 25.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"arr = [12, 24, 35, 70, 88, 120, 155]\n\nresult = []\n\nfor i in range(len(arr)):\n if i+1 in (1, 5, 6):\n continue\n result.append(arr[i])\n\nprint(result)"},{"alpha_fraction":0.3530927896499634,"alphanum_fraction":0.3814432919025421,"avg_line_length":17.5238094329834,"blob_id":"e2db528c1480c4016cc9246fe3ea7f95a803c4f9","content_id":"9ff41b953fd1ab9019498f67abbb1722e07fe3aa","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":388,"license_type":"no_license","max_line_length":59,"num_lines":21,"path":"/알고리즘/온라인저지/2021/08/0828/크로아티아 알파벳.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ncroatia = ['c=', 'c-', 'dz=', 'd-', 'lj', 'nj', 's=', 'z=']\n\nword = sys.stdin.readline()\ni = 0\ncnt = 0\nwhile i < len(word)-1:\n try:\n if word[i:i+2] in croatia:\n cnt += 1\n i += 2\n elif word[i:i+3] in croatia:\n cnt += 1\n i += 3\n else:\n cnt += 1\n i += 1\n except:\n pass\nprint(cnt)"},{"alpha_fraction":0.43718594312667847,"alphanum_fraction":0.46063652634620667,"avg_line_length":21.148147583007812,"blob_id":"54edaa97c63bca5054a0217098d040de1eab138d","content_id":"713cf37b692aa3b7f8e51735aa999e7a49bf450a","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":791,"license_type":"no_license","max_line_length":45,"num_lines":27,"path":"/알고리즘/온라인저지/2021/10/1016/로또.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"def dfs(x, cnt):\n if cnt == 6: # 고른 숫자가 6개면\n for i in range(k): # 고른 숫자들을 전체 조회할 것\n if visited[i]: # 고른 숫자가 있으면\n print(tmp[i], end=' ') # 출력\n print() # 줄바꿈\n return # 해당 재귀 종료\n \n for i in range(x, k): # 숫자를 하나씩 선택할건데\n visited[i] = 1 # 해당 숫자 선택\n dfs(i+1, cnt+1) # 다음 숫자 선택하러\n visited[i] = 0 # DFS\n # 갔다가 찍고 되돌아오는 부분\n\nwhile True:\n tmp = list(map(int, input().split()))\n \n if tmp[0] == 0:\n break\n\n k = tmp.pop(0)\n\n visited = [0] * k\n\n dfs(0, 0) # 0번째숫자부터, 고른숫자 0개부터\n\n print() # 매 케이스마다 줄바꿈"},{"alpha_fraction":0.6242774724960327,"alphanum_fraction":0.647398829460144,"avg_line_length":25,"blob_id":"5d02de840e1810bee1bc8859696aef301538ca82","content_id":"8153b9946e9f4cc9719b256788318b07a3c23787","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":519,"license_type":"no_license","max_line_length":68,"num_lines":20,"path":"/알고리즘/온라인저지/2022/09/0923/주유소.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\n\nN = int(input().rstrip())\ndistances = list(map(int, input().rstrip().split()))\nfuels = list(map(int, input().rstrip().split()))\nrefuel = []\nfuel_min = int(1e9)\nfor i in range(len(fuels)-1):\n if fuels[i] < fuel_min:\n refuel.append(i)\n fuel_min = min(fuel_min, fuels[i])\nrefuel.append(len(fuels)-1)\nresult = 0\nfor i in range(len(refuel)-1):\n result += sum(distances[refuel[i]:refuel[i+1]])*fuels[refuel[i]]\nprint(result)\n\n# https://www.acmicpc.net/problem/13305"},{"alpha_fraction":0.5873016119003296,"alphanum_fraction":0.60317462682724,"avg_line_length":31,"blob_id":"6c9f1ec9b1179afb2db22d83dee28f8b321b9179","content_id":"669aa37d9cdac846ad1d6eb75a09f87d863db0ae","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":63,"license_type":"no_license","max_line_length":48,"num_lines":2,"path":"/알고리즘/온라인저지/2022/12/1216/팰린드롬.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"word = input()\nprint('true' if word == word[::-1] else 'false')"},{"alpha_fraction":0.375342458486557,"alphanum_fraction":0.40547946095466614,"avg_line_length":11.620689392089844,"blob_id":"f490660458e0370fec87bcbf961d418b46b51017","content_id":"e15b2614de980a1cc5eceb4912d06050d4cf1742","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":365,"license_type":"no_license","max_line_length":29,"num_lines":29,"path":"/알고리즘/온라인저지/2022/02/0202/완전제곱수.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"M = 0\nN = 0\n\nfor i in range(2):\n if i == 0:\n M = int(input())\n elif i == 1:\n N = int(input())\n\ni = 0\nminn = 0\nsumm = 0\n\nwhile True:\n i += 1\n pow = i ** 2\n if pow > N:\n break\n\n if pow >= M and pow <= N:\n if not minn:\n minn = pow\n \n summ += pow\n\nif minn:\n print(summ, minn)\nelse:\n print(-1)"},{"alpha_fraction":0.5176470875740051,"alphanum_fraction":0.6000000238418579,"avg_line_length":27.44444465637207,"blob_id":"aa0168d82441c37bb6f8fabef8dc0b5fb7d9b688","content_id":"7382192a602227f3eecf0e2f673d6ea44beb7f7c","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":255,"license_type":"no_license","max_line_length":45,"num_lines":9,"path":"/알고리즘/온라인저지/2023/03/0320/출석 이벤트.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = int(input())\nP = int(input())\nresult = P\nif N >= 5: result = min(result, P-500)\nif N >= 10: result = min(result, int(P*0.9))\nif N >= 15: result = min(result, P-2000)\nif N >= 20: result = min(result, int(P*0.75))\nif result < 0: result = 0\nprint(result)"},{"alpha_fraction":0.3758741319179535,"alphanum_fraction":0.3916083872318268,"avg_line_length":25,"blob_id":"7e78d2d3721326c4b6eeb84f3c425d2935b33d06","content_id":"7a1bcbed171434aca047eb05209df4a41a0aeefd","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":696,"license_type":"no_license","max_line_length":43,"num_lines":22,"path":"/알고리즘/온라인저지/2022/01/0122/베르트랑 공준.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"while True:\n N = int(input())\n if N == 0: # 종료 조건\n break\n \n n = 2 * N # 2n까지 소수를 구할 것\n\n # 에라토스테네스의 체\n a = [False,False] + [True]*(n-1)\n primes = [] \n for i in range(2,n+1): \n if a[i]: \n primes.append(i) \n for j in range(2*i, n+1, i): \n a[j] = False \n\n # 2n까지 구한 소수들을 순회하다가\n for i in range(len(primes)):\n if primes[i] > N: # n보다 커지는 구간이 나오면\n # 소수 전체 길이에서 구간시작 인덱스 빼기\n print(len(primes)-i)\n break\n"},{"alpha_fraction":0.5144927501678467,"alphanum_fraction":0.5362318754196167,"avg_line_length":22.16666603088379,"blob_id":"ce3b70fb30164523498f445735fbf9deef507826","content_id":"c217edc639b1569b71d6be5692bdbd88a76ee996","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":246,"license_type":"no_license","max_line_length":34,"num_lines":6,"path":"/알고리즘/온라인저지/2021/07/0730/[기초-비트시프트연산] 정수 1개 입력받아 2배 곱해 출력하기.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"n = int(input())\n# 숫자를 비트단위로 밀어버리는 << >>\n# << : 숫자는 2진수이고 왼쪽으로 한 칸 밀면 값이 두배\n# >> : 오른쪽으로 한 칸 밀면 값이 반\n# <<로 n만큼 밀어주면 값이 2**n배\nprint(n << 1)"},{"alpha_fraction":0.5432432293891907,"alphanum_fraction":0.5540540814399719,"avg_line_length":29.91666603088379,"blob_id":"c7ce8376699516bddee8c368aa83a4d086b35aac","content_id":"b97bbfe3f8ab86b75ec6203d36274f4e5c574882","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":536,"license_type":"no_license","max_line_length":49,"num_lines":12,"path":"/알고리즘/온라인저지/2022/07/0729/추월.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = int(input())\ndct = {input(): i for i in range(N)} # 터널에 들어간 순서\nresult = 0\ncheck = [0] * N # 나간 차 기록 list\nfor n in range(N): # 나가는 차 입력\n tmp = input() # 나간 차 번호판\n IN = dct[tmp] # 나간 차의 터널에 들어간 순서\n OUT = sum(check[:IN]) # 먼저 나간 차량 수\n # 내 앞 차량들의 수가 터널을 들어갈 때 보다 나올 때 더 적으면\n if OUT < IN: result += 1 # 추월차량\n check[IN] = 1 # 해당 차는 터널을 빠져나옴\nprint(result)"},{"alpha_fraction":0.4465116262435913,"alphanum_fraction":0.47441861033439636,"avg_line_length":21.275861740112305,"blob_id":"d4fc4dabb61772057e2a0bad918233a8765f6dba","content_id":"2ce9a90dbb0b8aa8fabece610bf1379001e5d0d7","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":645,"license_type":"no_license","max_line_length":52,"num_lines":29,"path":"/알고리즘/온라인저지/2023/01/0130/언더프라임.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"def prime_list(size):\n sieve = [True]*(size+1)\n for i in range(2, int(size**0.5)+1):\n if sieve[i]:\n for j in range(i+i, size+1, i):\n sieve[j] = False\n return [i for i in range(2, size+1) if sieve[i]]\n \ndef factorization(x):\n i = 0\n d = primes[i]\n answer = 0\n while d <= x:\n if x % d == 0:\n answer += 1\n x = x // d\n else:\n i += 1\n d = primes[i]\n return answer\n\n\nprimes = prime_list(int(1e6))\nA, B = map(int, input().split())\nresult = 0\nfor i in range(A, B+1):\n if factorization(i) in primes:\n result += 1\nprint(result)"},{"alpha_fraction":0.5034482479095459,"alphanum_fraction":0.5241379141807556,"avg_line_length":30.071428298950195,"blob_id":"06289fbfbae63f6e9b36ad9db0c8e7e31ad7e8d4","content_id":"272a8dc4c42092081f93f2e9b133b763c4e46720","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":571,"license_type":"no_license","max_line_length":74,"num_lines":14,"path":"/알고리즘/온라인저지/2022/04/0417/덩치.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = int(input())\nwnhs = [] # 덩치 리스트\nresult = [] # 덩치 순위 리스트\nfor n in range(N): # N명의\n wnhs.append(tuple(map(int, input().split()))) # 덩치 입력\n# N * N \nfor i in range(N): # 5명의 덩치를 비교\n cnt = 1 # 덩치를 비교하기 전까지는 모두가 덩치 1등\n for j in range(N):\n # 본인보다 덩치가 큰 사람이 있다면\n if i != j and wnhs[i][0] < wnhs[j][0] and wnhs[i][1] < wnhs[j][1]:\n cnt += 1 # 덩치 순위 +1\n result.append(cnt) # 덩치 순위 추가\nprint(*result) # 출력\n"},{"alpha_fraction":0.4611872136592865,"alphanum_fraction":0.465753436088562,"avg_line_length":15.923076629638672,"blob_id":"0360dc695cbb6f3df34b3f8bbd4f3d819d225da5","content_id":"45ee1628f5cd5b2014cd257ca784bb976959e9e5","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":219,"license_type":"no_license","max_line_length":36,"num_lines":13,"path":"/알고리즘/온라인저지/2022/07/0713/초6 수학.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"def gcd(a, b):\n while b > 0:\n a, b = b, a%b\n return a\n\ndef lcm(a, b):\n return a * b // gcd(a, b)\n\n\nT = int(input())\nfor t in range(T):\n a, b = map(int, input().split())\n print(lcm(a, b), gcd(a, b))"},{"alpha_fraction":0.6290322542190552,"alphanum_fraction":0.6344085931777954,"avg_line_length":22.375,"blob_id":"b09966a700262a2e7d52e1556dce7e7280ef0c46","content_id":"ffe128c874e93f0744925cc3c78a03e8db3e5aa5","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":186,"license_type":"no_license","max_line_length":54,"num_lines":8,"path":"/알고리즘/온라인저지/2022/09/0926/주차의 신.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\n\nfor _ in range(int(input().rstrip())):\n input()\n parking = list(map(int, input().rstrip().split()))\n print((max(parking)-min(parking))*2)"},{"alpha_fraction":0.5405405163764954,"alphanum_fraction":0.5540540814399719,"avg_line_length":36.5,"blob_id":"d068498d57067002d6b4a9d7abd0b7c50f8a764a","content_id":"45369a96aab0c046dff54ae2e956e53a2d8c5bcb","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":74,"license_type":"no_license","max_line_length":43,"num_lines":2,"path":"/알고리즘/온라인저지/2023/02/0201/태보태보 총난타.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"taebo = input().split('(^0^)')\nfor t in taebo:print(t.count('@'), end=' ')"},{"alpha_fraction":0.44485294818878174,"alphanum_fraction":0.4595588147640228,"avg_line_length":17.133333206176758,"blob_id":"2bff4bba422a29e81afd0c499d371eb13617907d","content_id":"1d2ed8a1dbd88d007d2b53d1ae54b0e7b915c031","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":272,"license_type":"no_license","max_line_length":37,"num_lines":15,"path":"/알고리즘/온라인저지/2021/12/1213/Yangjojang of The Year.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"T = int(input())\n\nfor tc in range(T):\n N = int(input())\n\n YOTY = ''\n YOTY_drink = 0\n\n for n in range(N):\n univ = input().split()\n if int(univ[1]) > YOTY_drink:\n YOTY_drink = int(univ[1])\n YOTY = univ[0]\n \n print(YOTY)\n"},{"alpha_fraction":0.5190274715423584,"alphanum_fraction":0.5528541207313538,"avg_line_length":27.696969985961914,"blob_id":"337f3d6032a84f3f6f256e26fa64e9529febc53d","content_id":"0af2cfe37964ac2ca47cea61c259c80e7d0811fe","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1444,"license_type":"no_license","max_line_length":63,"num_lines":33,"path":"/알고리즘/온라인저지/2022/03/0321/지름길.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"\"\"\"\n세준이는 지름길을 타고 이동하지 않는다\n그저 일자로 직진하면서\n지름길이 있는지, 있다면 그 지름길을 지나갈 때\n운전거리가 얼마나 줄어드는지\"만\" 확인한다\n세준이는 일자로 간다\n\"\"\"\nfrom collections import deque\nN, D = map(int, input().split())\ntmp = [list(map(int, input().split())) for _ in range(N)]\ntmp.sort(key=lambda x:x[0]) # 출발점 기준 정렬\nroad = deque(tmp) # 지름길들을 담아놓음\n# 문제의 조건 : D < 10000\ndp = [int(1e4) for _ in range(D+1)] # 1e4 = 10000.0, 인덱스 위한 D+1\ndp[0] = 0 # 시작은 0\nfor i in range(D): # i = 세준이 위치\n # 현재 위치에서 갈 수 있는 지름길이 있을 때\n while road and road[0][0] == i:\n x = road.popleft() # 지름길을 꺼내와서\n if x[1] > D: # 목적지를 넘어가면\n continue # 패스\n # 지름길의 끝에 거리 갱신\n dp[x[1]] = min(dp[i] + x[2], dp[x[1]])\n # print(i, x[1], x[2]) # 디버깅\n # print(dp) # 디버깅\n # 다음 칸의 거리는, \n # min(이전 칸에서 한 칸 이동한 거리, 지름길 타고 넘어온 거리)\n dp[i+1] = min(dp[i] + 1, dp[i+1])\n# print(dp) # 디버깅\n# 세준이는 지름길을 타고 이동하지는 않았지만\n# 일자로 이동하면서 파악한 지름길들을\n# 적절히 활용하여 목적지에 도착할 수 있는 최소거리를\nprint(dp[D]) # 출력"},{"alpha_fraction":0.45771142840385437,"alphanum_fraction":0.4776119291782379,"avg_line_length":11.5625,"blob_id":"6b44f1c26bc1694260a900740cec958cc533fbb0","content_id":"d2294410e46b0bfc5e3ebff1936a7a471da62a61","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":227,"license_type":"no_license","max_line_length":33,"num_lines":16,"path":"/알고리즘/온라인저지/2021/08/0818/factorial.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"\ndef factorial(n):\n if n == 1:\n return n\n else:\n return n * factorial(n-1)\n\nprint(factorial(10))\n\n\"\"\"\n재귀함수\ndef 재귀():\n if 기저:\n return \n else: 기저 아닐 때\n return \n\"\"\""},{"alpha_fraction":0.5607843399047852,"alphanum_fraction":0.5686274766921997,"avg_line_length":18.69230842590332,"blob_id":"ea47adba7c599fa078efed07cc42df5d61a30cfd","content_id":"3780edbfff855187e8c2ea17809f8031268ea7d0","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":255,"license_type":"no_license","max_line_length":36,"num_lines":13,"path":"/알고리즘/온라인저지/2023/03/0310/터널의 입구와 출구.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = int(input())\nM = int(input())\nresult = M\ntunnel = M\nzero = False\nfor n in range(N):\n A, B = map(int, input().split())\n tunnel += A\n tunnel -= B\n result = max(result, tunnel)\n if tunnel<0:\n zero = True\nprint(0 if zero else result)"},{"alpha_fraction":0.3801652789115906,"alphanum_fraction":0.4545454680919647,"avg_line_length":16.428571701049805,"blob_id":"93a89efe6cf24f975835fc33fbe557ddf3ac1963","content_id":"80ebc00fe5083bddb4ad90b44e732aa68cc3d698","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":121,"license_type":"no_license","max_line_length":28,"num_lines":7,"path":"/알고리즘/온라인저지/2021/08/0817/n자리m진수.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"n = 3\nm = 5\nlist1 = [0] * n\nfor i in range(n-1, -1, -1):\n for j in range(m):\n list1[i] = j\n print(list1)"},{"alpha_fraction":0.4235033392906189,"alphanum_fraction":0.47671839594841003,"avg_line_length":18.65217399597168,"blob_id":"57de5c6c3ad49f19a73bd2362dc4941abfb2e509","content_id":"37d2d331e7763b95045dcc0855bc3648e3777501","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":451,"license_type":"no_license","max_line_length":50,"num_lines":23,"path":"/알고리즘/온라인저지/2023/04/0430/사격 내기.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"targets = [2**i for i in range(10)]\nscores = [[0]*10 for _ in range(2)] # A, B\nA, B = map(int, input().split())\n\nfor i in range(9, -1, -1):\n target = targets[i]\n\n if A>=target:\n scores[0][i] = 1\n A -= target\n\n if B>=target:\n scores[1][i] = 1\n B -= target\n\nresult = 0\n\nfor i in range(10):\n C, D = scores[0][i], scores[1][i]\n if (C == 0 and D == 1) or (C == 1 and D == 0):\n result += 2**i\n\nprint(result)"},{"alpha_fraction":0.5214285850524902,"alphanum_fraction":0.5357142686843872,"avg_line_length":22.5,"blob_id":"2c343fed58989b578dd151f5ffb06ffd9f26faa9","content_id":"76c0e12ba87461bd5a2e8ebd3c608b00364a4f74","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":140,"license_type":"no_license","max_line_length":50,"num_lines":6,"path":"/알고리즘/온라인저지/2023/04/0421/등차수열에서 항 번호 찾기.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"a, d, k = map(int, input().split())\nresult = 1\nif not (not (k-a)%d and (k-a)//d>=0): result = 'X'\nelse:\n result += (k-a)//d\nprint(result)"},{"alpha_fraction":0.4129793643951416,"alphanum_fraction":0.4410029351711273,"avg_line_length":20.90322494506836,"blob_id":"6063291ea43f7d10fe605f7e76e63e8b23cbea94","content_id":"da1c175bd9ba8bc0cfd99e8f2e72439d5ce592c9","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":678,"license_type":"no_license","max_line_length":69,"num_lines":31,"path":"/알고리즘/온라인저지/2023/01/0114/소수의 연속합.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"def prime_list(size):\n sieve = [True]*(size+1)\n for i in range(2, int(size**0.5)+1):\n if sieve[i]:\n for j in range(i+i, size+1, i):\n sieve[j] = False\n return [i for i in range(2, size+1) if sieve[i]]\n\nN = int(input())\nif N == 1: \n print(0)\nelse:\n primes = prime_list(N)\n s, e, now = 0, 0, primes[0]\n max_len = len(primes)-1\n result = 0\n\n while 1:\n if (now < N and e == max_len) or (now > N and s == max_len): \n break\n\n if now == N: result += 1\n\n if now < N:\n e += 1\n now += primes[e]\n else:\n now -= primes[s]\n s += 1\n\n print(result)"},{"alpha_fraction":0.45562130212783813,"alphanum_fraction":0.48520711064338684,"avg_line_length":20.25,"blob_id":"d01f224b12ab11fe1bb6b01e606aa0c0a313fed9","content_id":"faa4cb73ff00fe6efb934eb4118157c22a3558e9","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":169,"license_type":"no_license","max_line_length":51,"num_lines":8,"path":"/알고리즘/[템플릿]/[SAMPLE]/요세푸스 점화식.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"def josephus(N, K):\n if N == 1:\n return 1\n else:\n return ((josephus(N-1, K) + K - 1) % N) + 1\n\nN, K = map(int, input().split())\nprint(josephus(N, K))"},{"alpha_fraction":0.44131454825401306,"alphanum_fraction":0.5164319276809692,"avg_line_length":16.83333396911621,"blob_id":"77162f597988f1cd5c68f752ba3f351b923a1d35","content_id":"3eb225596b2edab4c87d42f51e7fdb48a3b526c1","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":213,"license_type":"no_license","max_line_length":43,"num_lines":12,"path":"/알고리즘/온라인저지/2022/09/0925/피보나치는 지겨웡~.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\n\nN = int(input().rstrip())\nmod = int(1e9)+7\ndp = [0] * (N+30)\ndp[0], dp[1] = 1, 1\nif N>1:\n for i in range(2, N+1):\n dp[i] = (dp[i-1] + dp[i-2] + 1)%mod\nprint(dp[N])"},{"alpha_fraction":0.5226730108261108,"alphanum_fraction":0.5680190920829773,"avg_line_length":23.705883026123047,"blob_id":"c39f32e1a111a6514d83f81d806d3b3e6657b395","content_id":"c40715d5e7a78b6aac50bd161fbbc600c031fa6d","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":419,"license_type":"no_license","max_line_length":69,"num_lines":17,"path":"/알고리즘/온라인저지/2022/10/1014/숫자 맞추기 게임.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\n\ni = 0\nwhile True:\n i += 1\n N = int(input())\n if N == 0: break\n result = [N]\n result.append(3*result[0])\n if not result[1]%2: result.append(result[1]//2)\n else: result.append((result[1]+1)//2)\n result.append(3*result[2])\n result.append(result[3]//9)\n odd_or_even = ['even', 'odd']\n print('{}. {} {}'.format(i, odd_or_even[result[1]%2], result[4]))"},{"alpha_fraction":0.5649546980857849,"alphanum_fraction":0.5709969997406006,"avg_line_length":22.714284896850586,"blob_id":"5a6d2af43eb0b99afe6aee4ba1acea1c10e42a76","content_id":"311d1ed22c5fa7099f0ca8756e5984c4508bde93","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":331,"license_type":"no_license","max_line_length":53,"num_lines":14,"path":"/알고리즘/온라인저지/2022/07/0729/회사에 있는 사람.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = int(input())\ncompany = dict()\nresult = []\nfor n in range(N):\n name, el = input().split() # name, enter or leave\n if el == 'enter':\n company[name] = 1\n else: # el == 'leave\n company[name] = 0\nfor c in company:\n if company[c]:\n result.append(c)\nresult.sort(reverse=True)\nfor r in result: print(r)"},{"alpha_fraction":0.4114285707473755,"alphanum_fraction":0.4342857003211975,"avg_line_length":16.600000381469727,"blob_id":"7e784ab2b441b4d2715de9d992295f0d9c209fe7","content_id":"d265a542ec94b42237a4858ae33bfd461f72b59d","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":175,"license_type":"no_license","max_line_length":38,"num_lines":10,"path":"/알고리즘/온라인저지/2023/04/0416/골뱅이 찍기 - ㅁ.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = int(input())\nfor _ in range(N):\n print('@'*5*N)\n\nfor _ in range(3):\n for _ in range(N):\n print('@'*N + ' '*N*3 + '@'*N)\n\nfor _ in range(N):\n print('@'*5*N)"},{"alpha_fraction":0.5,"alphanum_fraction":0.5067567825317383,"avg_line_length":11.416666984558105,"blob_id":"95e8fdb6d0c7e348dd586bf8641d859b05b01d99","content_id":"26d4f7d2ab2731c99c92fbe6e9749ae0409e9744","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":148,"license_type":"no_license","max_line_length":35,"num_lines":12,"path":"/알고리즘/온라인저지/2022/03/0304/X に最も近い値 (The Nearest Value).py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"X, L, R = map(int, input().split())\n\nresult = 0\n\nif X < L:\n result = L\nelif L <= X < R:\n result = X\nelif X >= R:\n result = R\n\nprint(result)"},{"alpha_fraction":0.5120290517807007,"alphanum_fraction":0.5265547037124634,"avg_line_length":30.042253494262695,"blob_id":"e8ca497a22fb1acf8a146a8d32c6b0d1c9532e69","content_id":"2614ee9a9dc9c1182908090ab43282e5d07b38a4","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":3597,"license_type":"no_license","max_line_length":72,"num_lines":71,"path":"/알고리즘/온라인저지/2021/10/1003/연구소.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"# 모든 0에 벽을 세 개 세워보고 가장 안전영역을 많이 확보가능한게 정답\nimport copy # 2차원 배열 복사를 위한 import copy, deepcopy를 사용함\nfrom collections import deque # bfs로 바이러스를 퍼뜨릴 때 사용할 deque\n\ndx = [1, -1, 0, 0]\ndy = [0, 0, 1, -1]\n\nres = 0 # 결과값 초기화\n\ndef virus(): # 바이러스가 퍼진다!\n global res # 함수 밖에 있는 전역변수 res를 사용\n\n tmp = copy.deepcopy(arr) # 입력받은 배열 arr을 완전히 복제할 것\n # 벽을 세우고 허물고 할건데\n # 매번 세우는 벽의 위치가 바뀌는데 원본 배열을 들고 수정하기보다\n # 배열을 복사해서 백업을 따놓고 \n # \"여기여기 벽을 세운거로는 바이러스를 못막는구나\"는 결과가 확인이 되면\n # 해당 복사는 지우고 다시 원본 배열을 복사해서 또 벽을 세우고\n # 그 벽에 바이러스 퍼뜨려보고를 반복\n # 그런데 2차원 배열을 복사해야 하기 때문에 deepcopy를 사용함\n\n for i in range(N): # 바이러스 시작점을\n for j in range(M): # 찾자\n if tmp[i][j] == 2: # 해당 칸이 바이러스면\n q.append([i, j]) # 이동할 칸에 추가\n # 배열의 처음 바이러스 위치를 q에 담음\n # 이후 아래 while문을 반복하면서 바이러스를 퍼뜨림\n \n while q: # 바이러스가 퍼질 곳이 남아있다면\n x, y = q.popleft() # 맨 앞에 좌표부터 꺼내서\n for i in range(4): # 상하좌우 전부 확인\n nx = x + dx[i]\n ny = y + dy[i]\n if 0 <= nx < N and 0 <= ny < M: # 연구소를 벗어나지 않는 범위에서\n if tmp[nx][ny] == 0: # 바이러스를 퍼뜨릴 수 있으면\n tmp[nx][ny] = 2 # 받아라 바이러스!\n q.append([nx,ny]) # 해당 좌표의 상하좌우에 또 바이러스가 퍼지도록 q에 담기\n\n cnt = 0 # 지금 세워진 벽에 대하여 바이러스가 얼마나 퍼졌는지 확인하는 변수 초기화\n \n for t in tmp:\n cnt += t.count(0) # 연구소 해당 줄에서 확인된 안전구역의 수\n \n res = max(res, cnt) # 전역변수 res와 비교하여 지금 세워진 벽에서의 안전구역이 더 많은지 비교하고 저장\n # if cnt > res: 와 같은 문장을 max()를 사용하였음\n\ndef wall(x):\n if x == 3: # 벽을 세 개 세웠다면\n virus() # 바이러스를 퍼뜨려보자!\n return # 바이러스를 다 퍼뜨리고 해당 재귀함수 종료, 다시 다른 벽을 세워보자\n \n for i in range(N):\n for j in range(M):\n if arr[i][j] == 0: # 벽을 세울 수 있으면\n arr[i][j] = 1 # 벽을 세우고\n wall(x+1) # 다음 벽을 세우자\n arr[i][j] = 0 # 다른 위치에 벽을 세울 수 있도록 위에서 세웠던 벽을 허물자\n\n\nN, M = map(int, input().split()) # 연구소의 가로와 세로 크기\n\narr = [list(map(int, input().split())) for _ in range(N)] # 연구소 상황\n\nq = deque() # 바이러스를 퍼뜨릴 q\n\nwall(0) # 벽 0개, 벽 1개, 벽 2개, 벽 3개, 그 시작은 0개\n\nprint(res) # 3개의 벽을 세운 각각의 경우에 대하여 얻은 안전구역의 수가 \n# 기존에 얻은 안전구역의 수 보다 클 때마다 갱신해주어서\n# 결국 벽을 세우는 모든 경우의 수에서 퍼뜨려 본 바이러스에 대해 확인된 안전구역의 최대 수가 담겨있는\n# res를 출력"},{"alpha_fraction":0.3029460906982422,"alphanum_fraction":0.40744858980178833,"avg_line_length":28.508195877075195,"blob_id":"d23b424b695ddca33848acb446292289d6eceafa","content_id":"77dc69334f426303535d90ba79f99570fa121ac1","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1871,"license_type":"no_license","max_line_length":72,"num_lines":61,"path":"/알고리즘/SW역량테스트/2021.10.19 A형.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"T = int(input())\n\nfor t in range(1, T+1):\n N = int(input())\n arr = list(map(int, input().split()))\n \n result = []\n\t# 제곱까지 갈 필요없다 \n # A + B + C + D 가 가장 크면 결과값이 가장 클거다\n # 결과값만 (A+B)**2 + (C+D)**2 를 출력해주면 된다\n \n stack = []\n tmp = 0\n \n visited = [0] * N\n for i in range(N-6):\n stack.append(arr[i])\n visited[i-1], visited[i], visited[i+1] = 1, 1, 1\n for j in range(i, N-4):\n if visited[j] == 0:\n stack.append(arr[j])\n visited[j-1], visited[j], visited[j+1] = 1, 1, 1\n for k in range(j, N-2):\n if visited[k] == 0:\n stack.append(arr[k])\n visited[k-1], visited[k], visited[k+1] = 1, 1, 1\n for l in range(k, N):\n if visited[l] == 0:\n stack.append(arr[l])\n if sum(stack) > tmp:\n tmp = sum(stack)\n result = [s for s in stack]\n stack.pop()\n visited[k-1], visited[k], visited[k+1] = 0, 0, 0\n stack.pop()\n visited[j-1], visited[j], visited[j+1] = 0, 0, 0\n stack.pop()\n visited[i-1], visited[i], visited[i+1] = 0, 0, 0\n stack.pop()\n A = result[0]\n B = result[1]\n C = result[2]\n D = result[3]\n ans1 = (A+B)**2 + (C+D)**2\n ans2 = (A+D)**2 + (B+C)**2\n print('#{} {}'.format(t, (max(ans1, ans2))))\n\n\"\"\"\ninput↓\n5\n10\n80 90 65 55 90 60 40 35 30 25\n8\n30 25 70 55 95 75 90 20\n10\n60 85 45 25 15 70 55 70 85 35\n15\n80 30 35 95 45 85 30 25 100 85 10 60 80 30 5\n20\n45 30 5 85 55 85 10 5 75 60 15 65 45 50 75 80 15 10 50 90\n\"\"\""},{"alpha_fraction":0.5087719559669495,"alphanum_fraction":0.5131579041481018,"avg_line_length":18.08333396911621,"blob_id":"428207c8cf1ee70c7ee238b38e71097991566a36","content_id":"3495bb730745928ad09ef6a3a88ee66ca990c0d4","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":228,"license_type":"no_license","max_line_length":45,"num_lines":12,"path":"/알고리즘/온라인저지/2022/09/0927/LCM.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\n\ndef gcd(a, b):\n while a%b: a, b = b, a%b\n return b\n\nfor _ in [0]*int(input().rstrip()):\n a, b = map(int, input().rstrip().split())\n G = gcd(a, b)\n print(G * (a//G) * (b//G))"},{"alpha_fraction":0.35199999809265137,"alphanum_fraction":0.3733333349227905,"avg_line_length":28.431371688842773,"blob_id":"b466e0cfb7ad746b112160b5d36d5d0e19ee6ea8","content_id":"6aa886b707e82f1b1194d8f5819883bcec187dad","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":2000,"license_type":"no_license","max_line_length":71,"num_lines":51,"path":"/알고리즘/온라인저지/2021/10/1016/섬의 개수.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"from collections import deque\n\ndx = [-1, 1, 0, 0, -1, 1, -1, 1] # 8방향\ndy = [0, 0, -1, 1, -1, -1, 1, 1]\n\nwhile True: # 0 0 을 받을때까지\n w, h = map(int, input().split())\n if w+h == 0: # 종료조건\n break\n\n arr = [] # 섬과 육지\n\n for i in range(h):\n arr.append(list(map(int, input().split())))\n \n q = deque()\n cnt = 0 # 섬의 개수 초기화\n\n # 배열 전체를 확인하면서\n # 육지가 나오면, 그 육지를 바다로 바꿔버리고\n # 주변 8칸에 또 육지가 있는지 즉, 이어져 있는 섬인지 확인할 것\n for i in range(h):\n for j in range(w): # 배열을 돌면서\n if arr[i][j]: # 육지를 찾았다?\n q.append((j, i)) # 탐색할 육지에 추가\n \n while q: # 탐색할 육지가 있을 때\n tmp = q.popleft() # 육지 좌표\n a = tmp[0]\n b = tmp[1]\n\n if arr[b][a] == 0: # 가지치기 조건\n # 탐색하려던 육지좌표였지만\n # 다른 육지를 탐색하던 중 바다로 만들었다면\n continue\n\n arr[b][a] = 0 # 해당 육지를 바다로 만들어버리자\n\n for k in range(8): # 8방향 BFS\n nx = a+dx[k]\n ny = b+dy[k]\n\n if 0 <= nx < w and 0 <= ny < h and arr[ny][nx]:\n # 범위를 벗어나지 않고, 8방향중 하나로 이동할 수 있는 육지면\n # 즉 이어져 있는 섬이면\n q.append((nx, ny)) # 탐색할 육지에 추가\n \n cnt += 1 # while문을 통해 섬을 전부 바다로 만들었다\n # 해당 섬은 사라졌고, 우리는 섬이 하나 존재하였음을 확인할 수 있음\n\n print(cnt) # 확인된 섬의 개수"},{"alpha_fraction":0.4591836631298065,"alphanum_fraction":0.5102040767669678,"avg_line_length":16.909090042114258,"blob_id":"cd5f995fb6ac426c5ddf43031f89092e2d7a6112","content_id":"2db238478f8b0dcd8f134b8fca176992f7a2013d","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":196,"license_type":"no_license","max_line_length":42,"num_lines":11,"path":"/알고리즘/온라인저지/2021/08/0818/피보나치 DP.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"def fibo(n):\n table[0] = 0\n table[1] = 1\n for i in range(2, n+1):\n table[i] = table[i-1] + table[i-2]\n return table[n]\n\nn = int(input())\ntable = [0] * (n+1)\nfibo(n)\nprint(table)"},{"alpha_fraction":0.48480844497680664,"alphanum_fraction":0.5178335309028625,"avg_line_length":38.894737243652344,"blob_id":"5a0c286545912e91c0322d1a679639448076947d","content_id":"b791b4f7e42266ff0e62b35b55e2ade764f34e44","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1061,"license_type":"no_license","max_line_length":82,"num_lines":19,"path":"/알고리즘/온라인저지/2023/02/0218/동전 바꿔주기.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"T = int(input())\nk = int(input())\n\ncoin = [(0, 0)] + [tuple(map(int, input().split())) for _ in range(k)]\n\ndp = [[0 for _ in range(T+1)] for _ in range(k+1)] # 가로 세로 첫 줄은 0원\ndp[0][0] = 1 # 0원을 만들 수 있는 경우는 1\n\nfor i in range(1, k+1): # 1번 동전, 2번 동전, i번 동전, ..., k번 동전\n val, cnt = coin[i] # 동전 가치, 동전 개수\n for cost in range(T+1): # 0원부터 T원까지, i번 동전을 사용하여 만들 수 있는 지 확인\n dp[i][cost] = dp[i-1][cost] # 앞서 i-1번 동전을 사용한 경우를 미리 불러오기\n for c in range(1, cnt+1): # val원의 동전 1개, 2개, c개, ..., cnt개\n if cost-c*val >= 0: # dp갱신 최소 조건\n dp[i][cost] += dp[i-1][cost-c*val] # i번 동전을 c개 사용하여 갱신할 수 있는 지점 확인\n else: # cost원을 i번 동전을 사용하여 갱신할 수 없을 경우에\n break\n\nprint(dp[k][T]) # k개 종류의 동전을 사용하여 T원을 만들 수 있는 경우 출력"},{"alpha_fraction":0.4470588266849518,"alphanum_fraction":0.5235294103622437,"avg_line_length":21.217391967773438,"blob_id":"9c60d8546374beebadf583a3b641b66324185435","content_id":"8ed6bb7e1450dc849d5a2e1c201cbd62754ab930","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":510,"license_type":"no_license","max_line_length":55,"num_lines":23,"path":"/알고리즘/온라인저지/2022/09/0930/투명.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\n\ndef cover(x1, y1, x2, y2):\n for i in range(y1, y2):\n for j in range(x1, x2):\n arr[i][j] += 1\n\ndef check():\n result = 0\n for i in range(100):\n for j in range(100):\n if arr[i][j]>M: result += 1\n return result\n\nN, M = map(int, input().rstrip().split())\narr = [[0]*100 for _ in [0]*100]\nfor n in range(N):\n x1, y1, x2, y2 = map(int, input().rstrip().split())\n x1, y1 = x1-1, y1-1\n cover(x1, y1, x2, y2)\nprint(check())"},{"alpha_fraction":0.4022066295146942,"alphanum_fraction":0.4403209686279297,"avg_line_length":16.821428298950195,"blob_id":"56de27a6c50eb6ff30fda4a2d7e790024a6ead59","content_id":"7745686dc6aacf67012a4de2fe9e9ef67a12b7f1","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":997,"license_type":"no_license","max_line_length":59,"num_lines":56,"path":"/알고리즘/온라인저지/2023/03/0326/소문난 칠공주.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"from collections import deque\n\n\ndef check(arr):\n visited = [[1]*5 for _ in range(5)]\n\n for a in arr:\n y, x = a\n visited[y][x] = 0\n \n Q = deque([(arr[0])])\n y, x = arr[0]\n visited[y][x] = 1\n cnt = 1\n\n while Q:\n y, x = Q.popleft()\n\n for k in range(4):\n ny, nx = y+dy[k], x+dx[k]\n\n if 0<=ny<5 and 0<=nx<5 and not visited[ny][nx]:\n visited[ny][nx] = 1\n cnt += 1\n Q.append((ny, nx))\n\n return True if cnt == 7 else False\n\n\ndef DFS(depth, idx, YDY_cnt):\n global result\n\n if YDY_cnt>=4:\n return\n \n if depth == 7:\n if check(arr):\n result += 1\n return\n \n for i in range(idx, 25):\n y, x = i//5, i%5\n arr.append((y, x))\n DFS(depth+1, i+1, YDY_cnt+(students[y][x]=='Y'))\n arr.pop()\n\n\ndy, dx = [-1, 1, 0, 0], [0, 0, -1, 1]\n\nstudents = [input() for _ in range(5)]\nresult = 0\narr = []\n\nDFS(0, 0, 0)\n\nprint(result)"},{"alpha_fraction":0.3855421543121338,"alphanum_fraction":0.42168673872947693,"avg_line_length":12.833333015441895,"blob_id":"a0287260e483bfcfd22abc5f83b6f18ec381a343","content_id":"a4c4f1302cda1fe46e86647f3171462bca1edc1e","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":166,"license_type":"no_license","max_line_length":47,"num_lines":12,"path":"/알고리즘/온라인저지/2022/01/0131/윷놀이.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"status = {\n 3: 'A',\n 2: 'B',\n 1: 'C',\n 0: 'D',\n 4: 'E',\n}\n\nfor t in range(3):\n yoot = sum(list(map(int, input().split())))\n\n print(status[yoot])\n"},{"alpha_fraction":0.5993788838386536,"alphanum_fraction":0.6304348111152649,"avg_line_length":23.846153259277344,"blob_id":"b4dd59ad31b139590cd5fe8a186685fc05fd712d","content_id":"339424802e35ba25baad225d69b201bb73ac3c61","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":322,"license_type":"no_license","max_line_length":46,"num_lines":13,"path":"/알고리즘/온라인저지/2022/09/0927/생일.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\n\nstudents = []\nfor _ in [0]*int(input().rstrip()):\n student = input().rstrip().split()\n name = [student[0]]\n birthday = list(map(int, student[1:]))\n students.append(name+birthday)\nstudents.sort(key=lambda x:(x[3], x[2], x[1]))\nprint(students[-1][0])\nprint(students[0][0])"},{"alpha_fraction":0.5993788838386536,"alphanum_fraction":0.6055900454521179,"avg_line_length":22,"blob_id":"f7f9719db4d0990842179ad982a603f13b5e2fbb","content_id":"4edfda9f41d66242116e5d1dc7f971f1865d86c5","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":500,"license_type":"no_license","max_line_length":53,"num_lines":14,"path":"/알고리즘/온라인저지/2021/08/0806/최댓값.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"\"\"\"\n숫자를 다 받아서\n리스트에 넣고\n최댓값 찾아서\n리스트 순회하면서\n최댓값과 일치하는 요소의 인덱스(길이)\n\"\"\"\nnumbers = [] # 입력받을 리스트 초기화\nfor i in range(9):\n numbers.append(int(input())) # Enter단위로 값들 입력받기\nfor i in range(len(numbers)): # 리스트를 순회\n if numbers[i] == max(numbers): # 최댓값과 순회중인 값이 같으면\n print(numbers[i]) # 값 출력\n print(i + 1) # 인덱스 출력\n"},{"alpha_fraction":0.5245901346206665,"alphanum_fraction":0.5450819730758667,"avg_line_length":21.272727966308594,"blob_id":"013500daa75a28d9df9280f425be067085431846","content_id":"3aa32378aa3f76ba13012d6bd642be2c152c4c3f","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":244,"license_type":"no_license","max_line_length":49,"num_lines":11,"path":"/알고리즘/온라인저지/2022/09/0927/UCPC는 무엇의 약자일까.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\n\nUCPC = ('U', 'C', 'P', 'C')\nsen = input().rstrip()\ni, j = 0, 0 # sen, UCPC\nfor i in range(len(sen)):\n if j == 4: break\n if sen[i] == UCPC[j]: j += 1\nprint('I love UCPC' if j == 4 else 'I hate UCPC')"},{"alpha_fraction":0.5296167135238647,"alphanum_fraction":0.5644599199295044,"avg_line_length":18.16666603088379,"blob_id":"630ea95461ddb7917c077c3276b5a3275079e936","content_id":"1308689d224d9e0af4c833909361ba79370d6145","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":842,"license_type":"no_license","max_line_length":39,"num_lines":30,"path":"/알고리즘/온라인저지/2022/08/0809/IOIOI.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\n\nN = int(input())\nM = int(input())\nS = input().rstrip()\nresult = 0\nlst = []\nfor i in range(len(S)):\n if S[i] == 'I': lst.append(i)\ncnt = 0\nfor i in range(len(lst)-1):\n if lst[i+1] - lst[i] == 2: cnt += 1\n else: cnt = 0\n if cnt >= N: result += 1\nprint(result)\n\n\"\"\"\n시간 : 1시간 초과, 정답 풀이 확인\n풀이\n 제한 시간 1초, 3<=M<=1,000,000 이므로\n O(n) 이하로 코드 동작을 마쳐야 한다\n 전체 문자열을 한 번만 탐색한다\n I의 인덱스만 모은 리스트를 생성하여\n 리스트에서 두개씩 원소를 비교할 때\n 앞 원소와 뒷 원소의 차가 2이면 'IOI'이다\n 해당 패턴이 N번 이상일 경우 문제에서 원하는 정답이며\n 패턴의 연속됨이 끊어질 시, 카운트를 0으로 돌린다\n\"\"\""},{"alpha_fraction":0.416879802942276,"alphanum_fraction":0.4578005075454712,"avg_line_length":36.28571319580078,"blob_id":"b3fc416b28ab2adb3f6bf3f2277d199c06b7ef21","content_id":"ee44b5ac630e1c264d7efc125e6f2af612d45326","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1112,"license_type":"no_license","max_line_length":62,"num_lines":21,"path":"/알고리즘/온라인저지/2022/07/0705/어린 왕자.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"for t in range(int(input())):\n x1, y1, x2, y2 = map(int, input().split())\n result = 0\n for n in range(int(input())): # 각 행성을 입력\n cx, cy, cr = map(int, input().split())\n d1 = (x1-cx)**2 + (y1-cy)**2 # 출발점과 행성 중심간의 거리\n d2 = (x2-cx)**2 + (y2-cy)**2 # 도착점과 행성 중심간의 거리\n d3 = cr**2 # 행성 반지름의 제곱\n if d3 > d1 and d3 > d2: # 같은 행성 안에 있으면\n pass # 행성 진입/이탈할 필요 없음\n \"\"\"\n 위의 if문을 거치면서 아래 세가지 경우만 남게됨\n 1. 출발점 도착점 다 행성 밖에 있는 경우, 진입/이탈 없이 행성 사이를 움직일 수 있음\n 2. 출발점은 행성 안에, 도착점은 행성 밖에 있는 경우, 진입/이탈이 필요함\n 3. 출발점은 행성 밖에, 도착점은 행성 안에 있는 경우, 진입/이탈이 필요함\n \"\"\"\n elif d3 > d1: # Case 2\n result += 1\n elif d3 > d2: # Case 3\n result += 1\n print(result)"},{"alpha_fraction":0.5817825794219971,"alphanum_fraction":0.5905974507331848,"avg_line_length":35.5,"blob_id":"eea6199cacd1f5b860638b05aa8f49d4d3ecd82e","content_id":"216f7156a462c7bf4272d7c619f483ba8141feb7","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1413,"license_type":"no_license","max_line_length":82,"num_lines":28,"path":"/알고리즘/온라인저지/2022/08/0828/최단경로.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\nimport heapq # 탐색 시 가장 작은 값을 탐색하기 위함\n\ninput = sys.stdin.readline\nINF = int(1e9) # 가상의 최대값\n\ndef dijkstra(start):\n distance[start] = 0 # 시작점에서 시작점으로 가는 최단 경로값은 0\n heapq.heappush(Q, (0, start))\n while Q:\n dist, now = heapq.heappop(Q) # 가장 작은 값을 heappop으로 꺼내기\n for next, weight in data[now]: # 현재 노드에서 갈 수 있는 노드와 가중치들을 순회하면서\n cost = dist + weight # 경로값은 들고 있는 경로값 + 가중치\n if cost < distance[next]: # 더 작은 경로값이 발견되면\n distance[next] = cost # 최소 경로값 갱신\n heapq.heappush(Q, (cost, next)) # 해당 경로와 다음 노드를 heappush로 가장 앞에 추가\n\nV,E = map(int, input().split())\nstart = int(input())\ndata = [[] for _ in range(V+1)]\nfor _ in range(E):\n u, v, w = map(int, input().split())\n data[u].append((v, w)) # 노드 u에서 갈 수 있는 노드v와 그 때의 가중치 w\ndistance = [INF]*(V+1) # 가상의 최대 경로값 배열\nQ = [] # heapq의 메소드만 사용함, deque와 다르게, 일반적인 리스트 선언\ndijkstra(start) # start부터 출발\nfor d in distance[1:]: # 0번은 인덱스 맞추기용\n print(d if d != INF else 'INF') # 값이 있으면 해당 경로값, 없으면 'INF'"},{"alpha_fraction":0.27731093764305115,"alphanum_fraction":0.45798319578170776,"avg_line_length":6.645161151885986,"blob_id":"76f37429951da3fc3b96b574ff6f9dec15b24f6a","content_id":"0515a00605c5d4b36b1eddd4cc8c18c103990e6e","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":238,"license_type":"no_license","max_line_length":36,"num_lines":31,"path":"/알고리즘/온라인저지/2022/02/0220/BABBA.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"\"\"\"\n0\n1\n10\n101\n10110\n\n1 1\n1 2\n2 3\n3 4\n5 5\n8 6\n13 7\n21 8\n34 9\n\n\"\"\"\n\ndp = [0, 1, 1]\n\nK = int(input())\n\n\nif K <= 2:\n print(dp[K-1], dp[K])\nelse:\n for i in range(3, K+1):\n dp.append(dp[i-1] + dp[i-2])\n\n print(dp[K-1], dp[K])\n\n"},{"alpha_fraction":0.6800000071525574,"alphanum_fraction":0.6800000071525574,"avg_line_length":20.571428298950195,"blob_id":"a445ac1655a5ab010de8db283caa34f5ef8845ca","content_id":"bd9fdd21d4147459afb08a274b3d3c39fe8fdd96","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":150,"license_type":"no_license","max_line_length":42,"num_lines":7,"path":"/알고리즘/온라인저지/2021/09/0906/약수.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\ndef input():\n return sys.stdin.readline()\n\ncnt = input()\nmeasures = list(map(int, input().split()))\nprint(max(measures) * min(measures))"},{"alpha_fraction":0.44408944249153137,"alphanum_fraction":0.4792332351207733,"avg_line_length":21.39285659790039,"blob_id":"da3f588cc31ef7876c18d65114326d7ece2bf304","content_id":"c8c2855bd3d46d54488879aaecdf4e7f51fcfa1b","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":634,"license_type":"no_license","max_line_length":52,"num_lines":28,"path":"/알고리즘/온라인저지/2022/09/0923/달팽이2.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\ndy, dx = [0, 1, 0, -1], [1, 0, -1, 0] # 우 하 좌 상\n\ndef check_goal(y, x):\n flag = True\n for i in range(4):\n ny, nx = y+dy[i], x+dx[i]\n if 0<=ny<N and 0<=nx<M and not arr[ny][nx]: \n flag = False\n return flag\n\nN, M = map(int, input().rstrip().split())\nresult = 0\narr = [[0]*M for _ in range(N)]\ny, x = 0, 0\ni = 0\nwhile True:\n if check_goal(y, x): break\n arr[y][x] = 1\n ny, nx = y+dy[i], x+dx[i]\n if not (0<=ny<N and 0<=nx<M) or arr[ny][nx]:\n i = (i+1)%4\n ny, nx = y+dy[i], x+dx[i]\n result += 1\n y, x = ny, nx\nprint(result)"},{"alpha_fraction":0.487458199262619,"alphanum_fraction":0.5367892980575562,"avg_line_length":25.600000381469727,"blob_id":"d93a2c9ef1eae9a91d35a61c425c3d58469dd79f","content_id":"cb2abe94c08ea03fad894c28e015757c199ea403","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1764,"license_type":"no_license","max_line_length":60,"num_lines":45,"path":"/알고리즘/온라인저지/2022/08/0816/외계인의 기타 연주.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\n\nN, P = map(int, input().split()) # 놀랍게도 프렛은 영어도 Fret이다\nstack, result = [[] for _ in range(7)], 0 # 기타줄은 여섯줄 인덱스 맞추기\nfor n in range(N):\n S, F = map(int, input().split()) # string, fret\n if not stack[S]:\n stack[S].append(F)\n result += 1\n else: # stack[S]\n if F > stack[S][-1]:\n stack[S].append(F)\n result += 1\n elif F < stack[S][-1]:\n # 같거나 더 낮은 프렛을 만날 때 까지 pop\n while stack[S] and F < stack[S][-1]:\n stack[S].pop()\n result += 1\n # 누른 손을 모두 떼거나, 더 낮은 프렛을 만났을 경우\n if not stack[S] or stack[S][-1] < F:\n stack[S].append(F)\n result += 1\n else: # F == stack[-1]\n pass\nprint(result)\n\n\"\"\"\n예제 1번처럼 8 10 12 10 5 를 연주할 때\n실제로 외계인처럼 누른다면\n현실에선 5 8 10 12 -12 -10 -8 순으로 눌렀다 떼며 답이 7이 된다\n하지만 입력 순서상 5는 맨 뒤에 있으므로\n8을 입력받는 시점에서 5를 동시에 눌러도 되는지 알 방법이 없다\n때문에 컴퓨터적으로 사고하여, 마지막에 5를 추가하여도\n앞에서 눌렀던 셈 치는 코드가 필요하다\n위 코드는 아래 순서로 스택에 들어간다\n<8 10 12 -12 -10 -8 5>\n\n그리고 P의 범위가 300,000 이면서, 시간이 1초이므로\n50만줄의 입력을 받으면서 30만줄의 for문을 돌며\n다음 프렛을 찾아 인덱스를 1씩 다르게 하면서 탐색하면\n아마 시간초과가 날 것이다\n어떻게든, 스택에 넣은 값 자체를 특정할 방법이 필요하다\n\"\"\""},{"alpha_fraction":0.5530864000320435,"alphanum_fraction":0.5679012537002563,"avg_line_length":27.928571701049805,"blob_id":"e6a730bc96ba79ef86cdf08137bed6de339a839e","content_id":"56f0f9ed81e97092fc3e4de814dd163fef478223","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":599,"license_type":"no_license","max_line_length":49,"num_lines":14,"path":"/알고리즘/온라인저지/2022/07/0701/국영수.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"arr = [] # 성적표 배열\nfor n in range(int(input())):\n tmp = input().split() # 성적을 입력받아서\n for i in range(4): # 성적을 int형으로 변환\n try: tmp[i] = int(tmp[i])\n except: pass\n arr.append(tmp) # 성적표에 추가\n\"\"\"\nlambda에서 정렬 자체를 역순서로 할 수는 없지만\n숫자의 경우 값을 음수(-)로 만들어주어 역정렬을 할 수 있음\n\"\"\"\narr.sort(key=lambda x:(-x[1], x[2], -x[3], x[0]))\n# 국어는 내림차순, 영어는 오름차순, 수학은 내림차순, 이름은 오름차순\nfor a in arr: print(a[0]) # 출력\n"},{"alpha_fraction":0.4117647111415863,"alphanum_fraction":0.4313725531101227,"avg_line_length":11.875,"blob_id":"27953f7bacf33bfd49c55f8cd077f9bc44426fbe","content_id":"2d7b633b75247fd53bbc973b58aba81054a78612","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":102,"license_type":"no_license","max_line_length":35,"num_lines":8,"path":"/알고리즘/온라인저지/2022/04/0420/Do Not Touch Anything.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"R, C, N = map(int, input().split())\nA = R//N\nB = C//N\nif R%N:\n A += 1\nif C%N:\n B += 1\nprint(A*B)"},{"alpha_fraction":0.4895104765892029,"alphanum_fraction":0.503496527671814,"avg_line_length":10.076923370361328,"blob_id":"ff6702f9bd9c541e47518944a4afe8f5d30baa52","content_id":"56e7f3aaedc20022e5747e268b7c4a49c5eb81f1","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":143,"license_type":"no_license","max_line_length":38,"num_lines":13,"path":"/알고리즘/온라인저지/2022/02/0205/개수 세기.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = int(input())\n\nnums = list(map(int, input().split()))\n\nv = int(input())\n\ncnt = 0\n\nfor n in nums:\n if n == v:\n cnt += 1\n\nprint(cnt)"},{"alpha_fraction":0.4139534831047058,"alphanum_fraction":0.43255814909935,"avg_line_length":10.368420600891113,"blob_id":"203df9bd5c722c2a01dcf2c1ba965b08869761df","content_id":"8306c95e2519b1c9d869cd48f2b8c2440baebc3a","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":215,"license_type":"no_license","max_line_length":23,"num_lines":19,"path":"/알고리즘/온라인저지/2023/04/0429/골뱅이 찍기 - ㅂ.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"A, B = '', ''\nN = int(input())\nB = '@'*N*5\nA = '@'*N+' '*N*3+'@'*N\nfor _ in range(N*2):\n print(A)\nfor _ in range(N):\n print(B)\nfor _ in range(N):\n print(A)\nfor _ in range(N):\n print(B)\n\n\"\"\"\nN*2\nN\nN\nN\n\"\"\""},{"alpha_fraction":0.5045045018196106,"alphanum_fraction":0.5180180072784424,"avg_line_length":19.272727966308594,"blob_id":"7259ab5a0266e03c755b7ba4e385b478d1ea84ae","content_id":"658cfca99f77129d49ca9c5aefbd719ecf0bad2a","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":268,"license_type":"no_license","max_line_length":41,"num_lines":11,"path":"/알고리즘/온라인저지/2022/05/0515/9진수.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"def solution(n, q):\n rev_base = ''\n\n while n > 0:\n n, mod = divmod(n, q)\n rev_base += str(mod)\n\n return rev_base[::-1] \n # 역순인 진수를 뒤집어 줘야 원래 변환 하고자하는 base가 출력\n \nprint(solution(int(input()), 9))"},{"alpha_fraction":0.5092024803161621,"alphanum_fraction":0.5153374075889587,"avg_line_length":19.5,"blob_id":"f507a01a3e564b4ecadfa739fe964a692341cf00","content_id":"e250fb777eb523ecd0fbdda35b2fd2a87aca0a4b","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":163,"license_type":"no_license","max_line_length":44,"num_lines":8,"path":"/알고리즘/온라인저지/2022/07/0718/스네이크버드.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N, L = map(int, input().split())\nF = list(map(int, input().split())) # fruits\nF.sort()\n# print(F)\nfor i in range(len(F)):\n if L >= F[i]:\n L += 1\nprint(L)"},{"alpha_fraction":0.3952000141143799,"alphanum_fraction":0.4607999920845032,"avg_line_length":23.076923370361328,"blob_id":"e64a9cf0bad1968308abb2d0c09ae1669ed3578a","content_id":"35432e00413a7350e379792f62638331312a493a","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":839,"license_type":"no_license","max_line_length":44,"num_lines":26,"path":"/알고리즘/온라인저지/2022/07/0701/다음 순열.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = int(input())\nM = list(map(int, input().split()))\nfind = False\n\"\"\"\nex) 1 2 3 5 4\n1. 뒤에서부터 숫자 두개씩 비교하다가\n2. 뒤에 숫자(5)가 앞에 숫자(3)보다 클 때\n3. 다시 맨 뒤에서부터 시작하여\n4. 2에서 비교하여 더 작았던 앞에 숫자(3)보다 큰 수(4)를 찾으면\n5. 둘(3, 4)의 자리를 바꿔줌 (1 2 3 5 4 -> 1 2 4 5 3)\n6. 찾았던 앞의 숫자보다 큰 수(4)의 뒤쪽을 오름차순 정렬\n7. 앞부분과 정렬된 뒷부분을 붙여서 출력\n\"\"\"\nfor i in range(N-1, 0, -1):\n if M[i-1] < M[i]:\n for j in range(N-1, 0, -1):\n if M[i-1] < M[j]:\n M[i-1], M[j] = M[j], M[i-1]\n M = M[:i] + sorted(M[i:])\n find = True\n break\n if find:\n print(*M)\n break\nif not find:\n print(-1)"},{"alpha_fraction":0.4789915978908539,"alphanum_fraction":0.4789915978908539,"avg_line_length":17.384614944458008,"blob_id":"8074689f4ae5b2edcb3a8d64bf2847a50000c767","content_id":"eea30838651b793d58bd3eeddf644a2fe5c1d848","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":238,"license_type":"no_license","max_line_length":29,"num_lines":13,"path":"/알고리즘/온라인저지/2022/07/0722/問題 ２.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = int(input())\nC = dict() # change\nfor n in range(N):\n a, b = input().split()\n C[a] = b\n# print(C)\nM = int(input())\nfor m in range(M):\n tmp = input()\n try:\n print(C[tmp], end='')\n except:\n print(tmp, end='')"},{"alpha_fraction":0.5716292262077332,"alphanum_fraction":0.608146071434021,"avg_line_length":34.650001525878906,"blob_id":"bb0629795a0b51670cc09952b4bdf91ce479881f","content_id":"5ce30a4eea87a21da6c806f5af0ccf381931c804","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":946,"license_type":"no_license","max_line_length":107,"num_lines":20,"path":"/알고리즘/[템플릿]/BFS/돌다리.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"from collections import deque\n\nA, B, N, M = map(int, input().split())\nQ = deque() # BFS\nQ.append((N, 0)) # 시작점, 초기 이동횟수\nresult = 0\nvisited = [0] * 100001 # 돌다리 방문배열\nwhile Q: # 항상 도달할 수 있는 경우만 주어짐\n now, move = Q.popleft() # 현재 위치, 현재까지 이동한 횟수\n if visited[now]: continue # 방문한 적이 있는 돌다리면 continue\n visited[now] = 1 # 현재 돌다리를 방문함\n if now == M: # 목적지에 도착했을 때\n result = move # result = 가지고 있는 이동횟수\n break # while문 종료\n nexts = [now-1, now+1, now-A, now+A, now-B, now+B, now*A, now*B] # 6가지 경우의 다음 이동 돌다리\n for next in nexts:\n if 0<=next<=100000 and not visited[next]: Q.append((next, move+1)) # 돌다리 범위를 만족하며, 방문한 적 없는 돌다리 일 때\nprint(result)\n\n# https://www.acmicpc.net/problem/12761"},{"alpha_fraction":0.27020201086997986,"alphanum_fraction":0.30050504207611084,"avg_line_length":13.107142448425293,"blob_id":"8a2b493d0d8f18f56bcced407938e46ec7a2cba7","content_id":"166b67762360623e07b0c1664dce0d533c46d062","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":396,"license_type":"no_license","max_line_length":28,"num_lines":28,"path":"/알고리즘/온라인저지/2022/01/0131/분해합.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = int(input())\n\nif N == 1:\n print(0)\nelse:\n t = 0\n if N >= 100:\n t = len(str(N)) * 10\n M = N - t\n else:\n M = 1\n\n while True:\n M += 1\n\n a = 0\n\n for i in str(M):\n a += int(i)\n \n temp = M + a\n\n if temp == N:\n print(M)\n break\n elif M == N:\n print(0)\n break\n\n"},{"alpha_fraction":0.5116279125213623,"alphanum_fraction":0.5193798542022705,"avg_line_length":25,"blob_id":"92f1ea5be288fb165f1d2a6d7dc4bca694bf866d","content_id":"63ed72d7ba78b8d3e8a54ca0904235bc0eff6e66","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":129,"license_type":"no_license","max_line_length":36,"num_lines":5,"path":"/알고리즘/온라인저지/2022/08/0811/영수증.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"X = int(input())\nfor n in range(int(input())):\n A, B = map(int, input().split())\n X -= A*B\nprint('Yes' if X == 0 else 'No')"},{"alpha_fraction":0.5787500143051147,"alphanum_fraction":0.5912500023841858,"avg_line_length":21.25,"blob_id":"f6d7040d8c7b10f5f2be29e13d4a4fb8b2ee7688","content_id":"ba1afa8c9b5126ad93a7418a7417249cc777098b","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1318,"license_type":"no_license","max_line_length":49,"num_lines":36,"path":"/알고리즘/온라인저지/2022/10/1021/퇴사.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\n\nN = int(input().rstrip())\nT, P = [], []\nfor _ in range(N):\n a, b = map(int, input().rstrip().split())\n T.append(a)\n P.append(b)\ndp = P[:] + [0] # 최대 수익을 동적으로 기록할 DP테이블\nfor i in range(N-1, -1, -1): # Top-Down\n if T[i]+i > N: dp[i] = dp[i+1]\n else: dp[i] = max(dp[i+1], P[i] + dp[i+T[i]])\nprint(dp[0])\n\n\"\"\"\ni일에 시작한 일이 근무일을 넘길 경우\n해당 일은 처리할 수 없고\n그 다음날의 일 처리량과 동일하다\n반대로 근무일 안에 끝낼 수 있을 경우\n그 일을 할 수도 있고 안 할 수도 있는데\n안 할 경우는 dp[i+1]\n할 경우는 P[i] + dp[i+T[i]]\n\n안 할 경우에 dp[i+1]인 이유는\n그 일을 하지 않았기 때문에 dp[i]의 일 처리량과 \n하지 않고 넘어간 다음날인 dp[i+1]의 일 처리량이 동일하다\n일을 할 경우 P[i]는 일 처리량이고\ndp[i+T[i]]는 \n일 처리에 필요한 시간이 경과한 날의 일 처리량이 된다\n이 경우 시간 안에 일 처리가 가능하므로 \nP[i]의 일 처리량을 dp[i+T[i]]에 얹은 값을 계산한다\n그리고 이 둘의 크기를 비교하여 큰 값을 최대 일처리량으로 기록하면서\n위에서부터 내려오는 Top Down 방식으로 값들을 계산하는 DP문제이다\n\"\"\""},{"alpha_fraction":0.5945945978164673,"alphanum_fraction":0.5995085835456848,"avg_line_length":17.454545974731445,"blob_id":"b7a16541ff899b6ba9782f9071ba9a307bf80b6a","content_id":"0037be3b9b28282c33058dc545935b136f2d1fe4","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":407,"license_type":"no_license","max_line_length":56,"num_lines":22,"path":"/알고리즘/온라인저지/2021/12/1219/나는야 포켓몬 마스터 이다솜 딕셔너리.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\nprint(dir(list))\n\ndef input():\n return sys.stdin.readline().rstrip()\n\nN, M = map(int, input().split())\n\npokemon_by_key = {}\n\nfor i in range(1, N+1):\n pokemon_by_key.update({i:input()})\n\nkey_by_pokemon = {v:k for k,v in pokemon_by_key.items()}\n\nfor i in range(M):\n quiz = input()\n try:\n print(pokemon_by_key.get(int(quiz)))\n except:\n print(key_by_pokemon.get(quiz))\n\n"},{"alpha_fraction":0.34756097197532654,"alphanum_fraction":0.46341463923454285,"avg_line_length":14,"blob_id":"ba97a7dd945e24785657bf6ff0e70fc181c0e252","content_id":"b40bfc6e287e9a1cc07fb86a4778801d0484fb89","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":164,"license_type":"no_license","max_line_length":32,"num_lines":11,"path":"/알고리즘/온라인저지/2023/04/0424/푸앙이와 종윤이.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N, M = map(int, input().split())\na = 100-N\nb = 100-M\nc = 100-(a+b)\nd = a*b\nq, r = 0, d\nif d>=100:\n q = d//100\n r = d%100\nprint(a, b, c, d, q, r)\nprint(c+q, r)"},{"alpha_fraction":0.5315315127372742,"alphanum_fraction":0.5585585832595825,"avg_line_length":21.200000762939453,"blob_id":"8e194c58ae5422e5c68b9561f10156419d31472c","content_id":"00b147ee084f780920ce525d3b8b756d2ce2a702","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":111,"license_type":"no_license","max_line_length":35,"num_lines":5,"path":"/알고리즘/온라인저지/2022/04/0429/고려대학교에는 공식 와인이 있다.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"C, K, P = map(int, input().split())\nresult = 0\nfor c in range(1, C+1):\n result += K*c + P*c*c\nprint(result)\n"},{"alpha_fraction":0.35353535413742065,"alphanum_fraction":0.3717171847820282,"avg_line_length":34.21428680419922,"blob_id":"061029b4a371f1f9012baeb7cdbc008c84452e12","content_id":"22f4649966cefbd36d3574ac94c518f9bf6a162d","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":619,"license_type":"no_license","max_line_length":73,"num_lines":14,"path":"/알고리즘/온라인저지/2022/01/0122/에라토스테네스의 체.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"n, K = map(int, input().split()) # 소수를 찾을 범위\na = [False,False] + [True]*(n-1) # 0 ~ n 까지의 숫자 리스트\n\ncnt = 0\n\nfor i in range(2,n+1): # 2 ~ n까지 반복\n if a[i]: # 2부터 시작, 해당 숫자가 지워지지 않고 남아있는 소수라면 \n for j in range(i, n+1, i): # 해당 소수의 배수들을 \n if a[j] == False:\n continue\n a[j] = False # 리스트에서 전부 False로 만들기\n cnt += 1\n if cnt == K:\n print(j)\n \n"},{"alpha_fraction":0.4202898442745209,"alphanum_fraction":0.4492753744125366,"avg_line_length":22.33333396911621,"blob_id":"17cdb11de8ad3783d9e84e8805c3aefba77aab0d","content_id":"2dc507afdfedcf9457e5eb6c536ead88e1d3f3c7","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":69,"license_type":"no_license","max_line_length":28,"num_lines":3,"path":"/알고리즘/온라인저지/2021/08/0822/별 찍기-2.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = int(input())\nfor n in range(1, N+1):\n print(' '*(N-n) + '*'*n)"},{"alpha_fraction":0.5575757622718811,"alphanum_fraction":0.5575757622718811,"avg_line_length":19.75,"blob_id":"f4294d5d6b4de59098ca89d3aba34ddd94a26c94","content_id":"6a5d45da9a80ba69f44f2ee97726b54a7ed96104","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":165,"license_type":"no_license","max_line_length":34,"num_lines":8,"path":"/알고리즘/온라인저지/2022/06/0629/단어 정렬.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"arr = []\nfor i in range(int(input())):\n tmp = input()\n if tmp not in arr:\n arr.append(tmp)\narr.sort(key=lambda x:(len(x), x))\nfor a in arr:\n print(a)"},{"alpha_fraction":0.5632184147834778,"alphanum_fraction":0.5747126340866089,"avg_line_length":28.33333396911621,"blob_id":"1a06f0853f5266ee5c5b0c9319013d9fd2e53e9b","content_id":"e60abd7b79ccd82cf48acfb67f5f2ddffdff3bd6","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":87,"license_type":"no_license","max_line_length":56,"num_lines":3,"path":"/알고리즘/온라인저지/2023/03/0321/chino_shock.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"emoji = input()\nA, B, C = len(emoji), emoji.count(':'), emoji.count('_')\nprint(A+B+C*5)"},{"alpha_fraction":0.4745098054409027,"alphanum_fraction":0.4901960790157318,"avg_line_length":20.33333396911621,"blob_id":"7ea15ac34ef9ca7d47a55a57ff4598a20a00b35c","content_id":"0b286336f46876208a70ea17495ed87e9909fd46","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":255,"license_type":"no_license","max_line_length":32,"num_lines":12,"path":"/알고리즘/온라인저지/2022/06/0629/N과 M (3).py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"def comb(scope, depth):\n for i in range(1, scope+1):\n result.append(i)\n if depth == M:\n print(*result)\n else:\n comb(scope, depth+1)\n result.pop()\n\nN, M = map(int, input().split())\nresult = []\ncomb(N, 1)"},{"alpha_fraction":0.542553186416626,"alphanum_fraction":0.5957446694374084,"avg_line_length":18,"blob_id":"c358a177c15233102b38e07c6a3b064a3210b7ae","content_id":"5c3cc3130797f09fac40523b37ab5a51801c2571","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":94,"license_type":"no_license","max_line_length":28,"num_lines":5,"path":"/알고리즘/온라인저지/2023/05/0529/Silnia.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = int(input())\nresult = 1\nfor i in range(1, N+1):\n result = (result * i)%10\nprint(result)"},{"alpha_fraction":0.5284237861633301,"alphanum_fraction":0.5684754252433777,"avg_line_length":21.14285659790039,"blob_id":"2108fd8730ec7aabce617c2bd650b3624d7a761b","content_id":"d8c841403a56129bc00fc191a1699d6b7aad9d55","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":942,"license_type":"no_license","max_line_length":65,"num_lines":35,"path":"/알고리즘/온라인저지/2022/10/1006/알파벳.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\ndy, dx = [-1, 1, 0, 0], [0, 0, -1, 1]\n\ndef idx(char):\n return ord(char)-65\n\ndef dfs(y, x, move):\n global result\n result = max(result, move)\n for i in range(4):\n ny, nx = y+dy[i], x+dx[i]\n if 0<=ny<R and 0<=nx<C and not visited[idx(arr[ny][nx])]:\n visited[idx(arr[ny][nx])] = 1\n dfs(ny, nx, move+1)\n visited[idx(arr[ny][nx])] = 0\n\nR, C = map(int, input().rstrip().split())\narr = [list(input().rstrip()) for _ in ' '*R]\nvisited = [0]*26\nresult = 0\nvisited[idx(arr[0][0])] = 1\ndfs(0, 0, 0)\nprint(result+1)\n\n\"\"\"\n처음으로 스스로 풀은 DFS문제인 것 같다\n채점속도가 좀 느려서, 이게 정답이 될 까 걱정이 되었는데\n신기하게도 정답이었다\nBFS에서 다음 탐색점을 Q에 넣듯이\nDFS에서 다음 탐색점을 재귀로 함수를 실행해주는 코드를 짰다\n\"\"\"\n\n# https://www.acmicpc.net/problem/1987"},{"alpha_fraction":0.5095541477203369,"alphanum_fraction":0.5286624431610107,"avg_line_length":12.166666984558105,"blob_id":"06216a2f0b31a3d73f481036f1f3689354744ac5","content_id":"c8e691b25d02a00a9ad4e9c6ff0f6eacc64323f7","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":157,"license_type":"no_license","max_line_length":39,"num_lines":12,"path":"/알고리즘/온라인저지/2022/02/0201/지능형 기차.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"now = 0\nresult = 0\n\nfor t in range(4):\n off, on = map(int, input().split())\n\n now += (on-off)\n\n if now > result:\n result = now\n\nprint(result)"},{"alpha_fraction":0.5405405163764954,"alphanum_fraction":0.5540540814399719,"avg_line_length":24,"blob_id":"ad398029b41d2da3a29c2af8888bf4db5aba3c32","content_id":"545a900c46a7c019e3624689f29bbf34b2e061cf","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":74,"license_type":"no_license","max_line_length":43,"num_lines":3,"path":"/알고리즘/온라인저지/2023/04/0425/세 막대.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"a, b, c = sorted(map(int, input().split()))\nc = min(a+b-1, c)\nprint(a+b+c)"},{"alpha_fraction":0.5180055499076843,"alphanum_fraction":0.5401661992073059,"avg_line_length":20.294116973876953,"blob_id":"39f0691870a91e042aa0eb719eb0081409ed4987","content_id":"f19df6d5b76809d291dfdd7c9ce74b8a66a2f290","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":361,"license_type":"no_license","max_line_length":56,"num_lines":17,"path":"/알고리즘/온라인저지/2022/10/1002/주몽.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\n\nN = int(input().rstrip())\nM = int(input().rstrip())\nparts = sorted(list(map(int, input().rstrip().split())))\ni, j = 0, N-1 # j = len(parts)-1\nresult = 0\nwhile i < j:\n armor = parts[i] + parts[j]\n if armor > M: j -= 1\n elif armor < M: i += 1\n else: # armor == M\n result += 1\n i += 1\nprint(result)"},{"alpha_fraction":0.3636363744735718,"alphanum_fraction":0.3903743326663971,"avg_line_length":18.736841201782227,"blob_id":"fb91cec79cb413fbfb77819d88139a8a8c92ffd2","content_id":"b772bc963ec2c86a938600626ac70de2ab349537","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":374,"license_type":"no_license","max_line_length":43,"num_lines":19,"path":"/알고리즘/SWEA/LEARN/Course/2. Programming Intermediate/2. 파이썬 SW문제해결 기본 List2/6차시 2일차 - 부분집합의 합.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"A = list(range(1, 12+1))\n\nT = int(input())\n\nfor t in range(1, T+1):\n N, K = map(int, input().split())\n\n n = len(A)\n cnt = 0\n\n for i in range(1<<n):\n tmp = set()\n for j in range(n):\n if i&(1<<j):\n tmp.add(A[j])\n if sum(tmp) == K and len(tmp) == N:\n cnt += 1\n \n print('#{} {}'.format(t, cnt))"},{"alpha_fraction":0.5641025900840759,"alphanum_fraction":0.5641025900840759,"avg_line_length":38.33333206176758,"blob_id":"4cce9e73830accd3be9ffda20d56baf5b4d74d53","content_id":"bd80c64d884a281d6f4f3e3780b6cd0261d8c05d","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":117,"license_type":"no_license","max_line_length":50,"num_lines":3,"path":"/알고리즘/온라인저지/2022/12/1212/No Brainer.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"for _ in range(int(input())):\n X, Y = map(int, input().split())\n print('MMM BRAINS' if X >= Y else 'NO BRAINS')"},{"alpha_fraction":0.5709969997406006,"alphanum_fraction":0.5951661467552185,"avg_line_length":19.75,"blob_id":"1b8501c01b316fa7164780968061f4d469977a32","content_id":"00c35731198f426cc622a34edef0f905a0504ddd","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":331,"license_type":"no_license","max_line_length":48,"num_lines":16,"path":"/알고리즘/온라인저지/2022/07/0729/생태학.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\n\ndct = dict() # tree dict\nlst = [] # tree list\ncnt = 0\nwhile True:\n tree = input().rstrip() # EOFerror\n if not tree: break\n if tree not in lst: lst.append(tree)\n try: dct[tree] += 1\n except: dct[tree] = 1\n cnt += 1\nlst.sort()\nfor l in lst: print(f'{l} {dct[l]/cnt*100:.4f}')"},{"alpha_fraction":0.2801932394504547,"alphanum_fraction":0.4202898442745209,"avg_line_length":7.666666507720947,"blob_id":"63323988debfddaee78c316b13cb184e01a9213c","content_id":"5a4c742db5d7bf1ea2a261497de4bc949c7c55e6","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":207,"license_type":"no_license","max_line_length":36,"num_lines":24,"path":"/알고리즘/온라인저지/2022/02/0227/중앙 이동 알고리즘.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"\"\"\"\n0: 4\n1: 4+5 = 9\n2: 9+ \n\n4\n4*4-4-3\n9*4-8-3\n\n\ndp[i] = dp[i-1] * 4 - (4*i+3)\n\"\"\"\n\nN = int(input())\n\ndp = [4]\n\ntmp = 4\n\nfor i in range(1, N+1):\n dp.append(dp[i-1] * 4 - (tmp+3))\n tmp *= 2\n\nprint(dp[N])"},{"alpha_fraction":0.390625,"alphanum_fraction":0.41796875,"avg_line_length":20.41666603088379,"blob_id":"9ce4ab6184a811f534692c36c4041a29c47f4d23","content_id":"82f6b3471e5948c4e54bfe2cde3b3255a58e1601","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":256,"license_type":"no_license","max_line_length":43,"num_lines":12,"path":"/알고리즘/[템플릿]/[SAMPLE]/순열.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"def perm(arr, i):\n if i == len(arr)-1:\n print(arr)\n else:\n for j in range(i, len(arr)):\n arr[i], arr[j] = arr[j], arr[i]\n perm(arr, i+1)\n arr[i], arr[j] = arr[j], arr[i]\n\narr = [1, 2, 3, 4]\n\nperm(arr, 0)"},{"alpha_fraction":0.4354838728904724,"alphanum_fraction":0.4838709533214569,"avg_line_length":27.69230842590332,"blob_id":"4384994712fc5fa0bb80eba91bb5822135369efe","content_id":"360d428d6fbd6914cfee579287d0909925f85eef","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":372,"license_type":"no_license","max_line_length":50,"num_lines":13,"path":"/알고리즘/온라인저지/2022/12/1220/알파벳 전부 쓰기.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"for _ in range(int(input())):\n arr = [0]*26\n for s in input():\n char = s.lower()\n if 97 <= ord(char) < 97+26:\n arr[ord(char)-97] = 1\n result = 'missing '\n for i in range(26):\n if not arr[i]:\n result = result + chr(i+97)\n if i == 25 and result != 'missing ': break\n else: result = 'pangram'\n print(result)"},{"alpha_fraction":0.31512194871902466,"alphanum_fraction":0.49073171615600586,"avg_line_length":17.654544830322266,"blob_id":"b81a12e175829dd03bfea8ec38d16255fc844ade","content_id":"a09448283dafa4c99af9c9eeb112e1bd39535488","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1395,"license_type":"no_license","max_line_length":45,"num_lines":55,"path":"/알고리즘/온라인저지/2021/10/1003/이진 딸기.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"strawberry = {\n 0: '0010',\n 1: '0001',\n 2: '0010',\n 3: '0011',\n 4: '0100',\n 5: '0101',\n 6: '0110',\n 7: '0111',\n 8: '1000',\n 9: '1001',\n 10: '1010',\n 11: '1011',\n 12: '1100',\n 13: '1101',\n 14: '1110',\n 15: '1111',\n 16: '1110',\n 17: '1101',\n 18: '1100',\n 19: '1011',\n 20: '1010',\n 21: '1001',\n 22: '1000',\n 23: '0111',\n 24: '0110',\n 25: '0101',\n 26: '0100',\n 27: '0011',\n}\n# 이진딸기의 1번째는 VVV딸기 이다\n# 그리고 쭉 올라갔다가 16부터 내려오는데\n# 14번 올라가고 14번 내려오는 구조이다\n# 때문에 28로 나눠준 나머지를 딕셔너리에서 호출하면 문제가 없을 줄 알았는데\n# 계속 KeyError가 발생했다\n# 핵심은 딕셔너리의 0번째 VV딸기V\n# 0번째의 의미는 14번째 내려온 마지막 딸기이고\n# 그래야 0번째의 다음인 1번째가 VVV딸기 로 다시 순환하는 구조가 된다\n\nT = int(input())\n\nfor t in range(T):\n N = int(input()) # N번째 이진딸기는?\n\n tmp = strawberry[N%28] # 이진딸기는 28번마다 돌아온다\n\n result = '' # 이진수를 V와 딸기로 바꿔줄 result 초기화\n\n for m in tmp: # 구한 이진수를 0을 V로, 1을 딸기로\n if m == '0':\n result = result + 'V'\n else:\n result = result + '딸기'\n \n print(result) # 출력"},{"alpha_fraction":0.4923076927661896,"alphanum_fraction":0.5384615659713745,"avg_line_length":15.5,"blob_id":"3eb675aca58724d68fb67f8e338fbf0763204839","content_id":"2351068e420af35d7c600af0053eb7969d08dbea","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":65,"license_type":"no_license","max_line_length":32,"num_lines":4,"path":"/알고리즘/온라인저지/2023/04/0420/Correct.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"H, M = map(int, input().split())\nH -= 9\nend = H*60 + M\nprint(end)"},{"alpha_fraction":0.4695121943950653,"alphanum_fraction":0.4878048896789551,"avg_line_length":15.5,"blob_id":"93dde88295a4bb46d520d68ff064c2a1feecef08","content_id":"38980f5ee2a48ab4c2065f60d39cb7740edeef37","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":164,"license_type":"no_license","max_line_length":29,"num_lines":10,"path":"/알고리즘/온라인저지/2022/06/0621/창영이의 일기장.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"text = input()\nresult = ''\ni = 0\nwhile i < len(text):\n result = result + text[i]\n if text[i] in 'aeiou':\n i += 3\n else:\n i += 1\nprint(result)"},{"alpha_fraction":0.4457831382751465,"alphanum_fraction":0.45783132314682007,"avg_line_length":19.8125,"blob_id":"84068a22a874430eae2c5c944d6cdfd30619c888","content_id":"3505f0d0476c096669a5d6ad11b182972bd6b191","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":332,"license_type":"no_license","max_line_length":33,"num_lines":16,"path":"/알고리즘/온라인저지/2022/07/0712/FBI.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"FBI = False\nresult = []\nfor i in range(1, 6):\n agent = input()\n for j in range(len(agent)-2):\n tmp = agent[j:j+3]\n # print(tmp, i)\n if tmp == 'FBI':\n result.append(i)\n if not FBI:\n FBI = True\n break\nif FBI:\n print(*result)\nelse:\n print('HE GOT AWAY!')"},{"alpha_fraction":0.4423791766166687,"alphanum_fraction":0.4535315930843353,"avg_line_length":15.625,"blob_id":"6f7c16d4028512598eabab7441e33063d8601006","content_id":"5b60554b8961f2fd293049d2922dcd246163c52e","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":269,"license_type":"no_license","max_line_length":36,"num_lines":16,"path":"/알고리즘/온라인저지/2022/02/0203/세로읽기.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"arr = []\n\nmax_len = 0\n\nfor _ in range(5):\n tmp = input()\n arr.append(tmp)\n if len(tmp) > max_len:\n max_len = len(tmp)\n\nfor j in range(max_len):\n for i in range(5):\n try:\n print(arr[i][j], end='')\n except:\n pass\n\n\n\n"},{"alpha_fraction":0.4575471580028534,"alphanum_fraction":0.49528300762176514,"avg_line_length":33.16666793823242,"blob_id":"dcadb0a567a6595d5ee1452cc2a0189a1d8de76e","content_id":"c751dc85954af198a31d4341b52ffd2c80c2d2bb","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":212,"license_type":"no_license","max_line_length":58,"num_lines":6,"path":"/알고리즘/온라인저지/2022/08/0805/고급 수학.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = int(input())\nfor n in range(1, N+1):\n T = sorted(list(map(int, input().split()))) # triangle\n print(f'Scenario #{n}:')\n if T[0]**2 + T[1]**2 == T[2]**2: print('yes\\n')\n else: print('no\\n') "},{"alpha_fraction":0.41310539841651917,"alphanum_fraction":0.45868945121765137,"avg_line_length":21,"blob_id":"02eef63d382e36b2a9fe2a1b068fdf29cd2628e4","content_id":"f3c6b58474c784056a47322e63510f06f93c0c42","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":351,"license_type":"no_license","max_line_length":38,"num_lines":16,"path":"/알고리즘/온라인저지/2022/05/0504/문문문.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = int(input())\nM = int(input())\nif N < 6:\n result = []\n door = [0, 1, 0, 1, 0, 1]\n door__reverse = [1, 0, 1, 0, 1, 0]\n if M == 0:\n for i in door[1:N]:\n result.append(i)\n else:\n for i in door__reverse[1:N]:\n result.append(i)\n for r in result:\n print(r)\nelse:\n print('Love is open door')"},{"alpha_fraction":0.5007451772689819,"alphanum_fraction":0.5089418888092041,"avg_line_length":28.844444274902344,"blob_id":"786d645a26c67e6c19fb89e89208741593fbd1fb","content_id":"3f7baa6cac484d8096ae7ee5f12f5d56bd4df98d","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":2010,"license_type":"no_license","max_line_length":56,"num_lines":45,"path":"/알고리즘/온라인저지/2022/01/0116/단어 뒤집기 2.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"sen = input() # 입력\n\nword = '' # 단어 혹은 태그\n\nresult = [] # 단어 혹은 태그 단위로 짤라서 담을 리스트\n\nin_tag = False # 입력값을 돌면서, 현재 스캔중인 단어가 태그인지 확인\n\nfor s in sen: # 입력값을 하나씩 순회\n if s == '<': # 태그의 시작\n if word: # 단어가 추가되던 중이었으면\n result.append(word) # 추가중이던 단어를 끊어주고 리스트에 추가\n word = s # 태그를 담으면서 다시 시작\n else: # 시작 혹은 바로 앞에서 단어를 끊어줘서 단어가 없는 경우\n word = word + s # 태그를 담으면서 시작\n in_tag = True # 태그를 스캔중이므로 True\n elif s == '>': # 태그의 끝\n word = word + s # '>'를 담고\n result.append(word) # 리스트에 태그를 추가\n word = '' # 단어 초기화\n in_tag = False # 태그에 담는 것이 종료되었음\n elif s == ' ' and not in_tag: # 공백이면서 태그에 담는 중이 아닐 때\n result.append(word) # 태그가 아닌 그냥 단어를 리스트에 담고\n word = '' # 단어 초기화\n else: # 단어 혹은 태그를 스캔중\n word = word + s # 단어에 담아줌\n\nif word: # 스캔이 끝난 마지막 단어\n result.append(word) # 리스트에 추가\n\n# 첫번째 단어 출력\nif result[0][0] == '<': # 태그이면\n print(result[0], end='') # 그대로 출력\nelse: # 단어이면\n print(result[0][::-1], end='') # 뒤집어서 출력\n \nfor i in range(1, len(result)): # 두번째 단어부터 끝까지 출력\n # 이전 단어가 태그가 아니고 지금 단어도 태그가 아니면\n if result[i-1][0] != '<' and result[i][0] != '<':\n print(end=' ') # 단어 사이 공백\n \n if result[i][0] == '<': # 지금 단어가 태그이면\n print(result[i], end='') # 그대로 출력\n else: # 단어이면\n print(result[i][::-1], end='') # 뒤집어서 출력"},{"alpha_fraction":0.4285714328289032,"alphanum_fraction":0.45864662528038025,"avg_line_length":21.16666603088379,"blob_id":"1658dd10e7fb802435fb29c7e0d063e06eb5422c","content_id":"ea17ebb1f085499a5a56a9da762b78d88a2f1d37","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":266,"license_type":"no_license","max_line_length":39,"num_lines":12,"path":"/알고리즘/온라인저지/2021/08/0804/직각삼각형.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"a, b, c = 1, 1, 1\nresult = []\nwhile a + b + c != 0:\n a, b, c = map(int, input().split())\n if a + b + c == 0:\n continue\n if a**2 + b**2 == c**2:\n result.append('right')\n else:\n result.append('wrong')\nfor res in result:\n print(res)\n"},{"alpha_fraction":0.4943181872367859,"alphanum_fraction":0.5,"avg_line_length":34.400001525878906,"blob_id":"eb334300f8a8a8cc088ff330ddea0e83074d7b45","content_id":"65db4c10510e82dac7f462f520ebf386f6c69b51","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":176,"license_type":"no_license","max_line_length":49,"num_lines":5,"path":"/알고리즘/온라인저지/2023/02/0220/페르시아의 왕들.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"while True:\n a, b, c, d = map(int, input().split())\n if a == b == c == d == 0: break\n result = list(map(abs, [a-c, a-d, b-c, b-d]))\n print(min(result), max(result))"},{"alpha_fraction":0.40454545617103577,"alphanum_fraction":0.5068181753158569,"avg_line_length":26.5625,"blob_id":"ff4979ad8153e978225ba7a802e2ddd0b4e0d396","content_id":"85d9292fdababfd5ce85ccaba5f092e4c1194f9f","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":440,"license_type":"no_license","max_line_length":82,"num_lines":16,"path":"/알고리즘/온라인저지/2022/07/0731/이름 궁합.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"# stroke\nS = [3, 2, 1, 2, 3, 3, 2, 3, 3, 2, 2, 1, 2, 2, 1, 2, 2, 2, 1, 2, 1, 1, 1, 2, 2, 1]\nname1 = input()\nname2 = input()\nfor n in name1:\n tmp = ord(n)-65\narr = []\nfor i in range(len(name1)):\n arr.append(S[ord(name1[i])-65])\n arr.append(S[ord(name2[i])-65])\nfor i in range(len(arr)-2):\n tmp = [0] * (len(arr)-1)\n for j in range(len(arr)-1):\n tmp[j] = (arr[j]+arr[j+1])%10\n arr = tmp\nfor a in arr: print(a, end='')"},{"alpha_fraction":0.4482758641242981,"alphanum_fraction":0.4482758641242981,"avg_line_length":29,"blob_id":"65755037053fe2641595e2b65032c463e4f2a3ea","content_id":"51ae396b233e359eecdeb7ed9e3e6015e9de53b2","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":29,"license_type":"no_license","max_line_length":29,"num_lines":1,"path":"/알고리즘/온라인저지/2022/02/0202/10926.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"print(input(), '??!', sep='')"},{"alpha_fraction":0.47012731432914734,"alphanum_fraction":0.48481881618499756,"avg_line_length":30.9375,"blob_id":"ae7b01266b37342a33029e99aa49457af6cc73f7","content_id":"04b86364e9567f0cdab6949218ed5fe73a24f614","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1247,"license_type":"no_license","max_line_length":55,"num_lines":32,"path":"/알고리즘/온라인저지/2022/04/0426/맥주 마시면서 걸어가기.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\nfrom collections import deque\ninput = sys.stdin.readline\n\ndef bfs():\n q = deque()\n q.append([home[0], home[1]]) # 집에서부터\n while q: # 갈 수 있는 편의점이 있는 동안\n x, y = q.popleft() # 출발\n # 목적지에 도착할 수 있으면\n if abs(x - goal[0]) + abs(y - goal[1]) <= 1000:\n print(\"happy\") # 축제에 갈 수 있다\n return # 축제에 갈 수 있으므로 코드 종료\n for i in range(N): # N개의 편의점 중\n if not visited[i]: # 간 적 없는 편의점\n nx, ny = store[i] # 편의점의 좌표\n # 갈 수 있는 편의점이면\n if abs(x - nx) + abs(y - ny) <= 1000:\n q.append((nx, ny)) # 편의점 좌표 추가\n visited[i] = 1 # 편의점 방문처리\n print(\"sad\") # 다 돌아도 못갔네 ㅠㅠ\n return\n\nfor t in range(int(input())):\n N = int(input())\n home = list(map(int, input().split()))\n store = []\n for i in range(N): # N개의 편의점\n store.append(tuple(map(int, input().split())))\n goal = list(map(int, input().split()))\n visited = [0 for _ in range(N+1)] #home 제외\n bfs() # 집부터 출발"},{"alpha_fraction":0.49082568287849426,"alphanum_fraction":0.5229358077049255,"avg_line_length":14.642857551574707,"blob_id":"d1793eb3a256c98d0d4d964c94bbeb59984bc905","content_id":"7cbf1e0b5698b0a1ff5625602bcd0f834822bc08","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":218,"license_type":"no_license","max_line_length":38,"num_lines":14,"path":"/알고리즘/온라인저지/2022/03/0303/3 つの整数 (Three Integers).py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"nums = list(map(int, input().split()))\n\nmaxx = 0\nresult = 0\n\ndp = [0] * 101\n\nfor i in range(len(nums)):\n dp[nums[i]] += 1\n if dp[nums[i]] > maxx:\n maxx = dp[nums[i]]\n result = nums[i]\n\nprint(result)"},{"alpha_fraction":0.36567163467407227,"alphanum_fraction":0.4029850661754608,"avg_line_length":9.307692527770996,"blob_id":"9f5addd664048bdc94fb450d53bdc1456d1b5623","content_id":"539d8f05fe3151e4f1237dba61b42aead6f2ede6","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":134,"license_type":"no_license","max_line_length":20,"num_lines":13,"path":"/알고리즘/온라인저지/2022/01/0131/별 찍기 - 13.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = int(input())\n\ni = 1\n\nfor n in range(N):\n print('*' * i)\n i += 1\n\ni -= 1\n\nfor n in range(N-1):\n i -= 1\n print('*' * i)\n"},{"alpha_fraction":0.5736196041107178,"alphanum_fraction":0.5858895778656006,"avg_line_length":22.35714340209961,"blob_id":"50ffdc2329f799fb580123515896053517243ee1","content_id":"b59fc2983b85993026aa08a64effb612946b710b","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":326,"license_type":"no_license","max_line_length":52,"num_lines":14,"path":"/알고리즘/온라인저지/2022/10/1021/Base Conversion.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\n\nA, B = map(int, input().rstrip().split())\nM = int(input().rstrip())\narr = list(map(int, input().rstrip().split()))[::-1]\nnum = 0\nfor i in range(M): num += A**i*arr[i]\nbase = 1\nwhile base*B < num: base *= B\nwhile base >= 1:\n print(num//base, end=' ')\n num, base = num%base, base//B"},{"alpha_fraction":0.5883134007453918,"alphanum_fraction":0.6095617413520813,"avg_line_length":25,"blob_id":"dfbe9f83925dfca4a2bc17c77991267c91d9b191","content_id":"5df77e2a65b40d704d7b42ab10918c1692c79ad5","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1125,"license_type":"no_license","max_line_length":66,"num_lines":29,"path":"/알고리즘/온라인저지/2022/08/0805/입국심사.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\n\nN, M = map(int, input().split())\ntime = sorted(list(int(input()) for _ in range(N)))\nstart = 0\n# time의 최소값 * 사람 수 => 최대 시간 \nend = min(time) * M # Worst Case : 모든 입국 심사자가 1번 심사대를 통과하려고 떼쓰는 경우\nresult = 0\nwhile start <= end :\n mid = (start + end) // 2\n I = 0 # immigration : 입국심사\n for t in time: I += mid // t # mid초 동안 심사대를 통과할 수 있는 사람 수\n if I >= M: # mid초 동안 M명 이상 심사대를 통과할 수 있음\n end = mid-1 # 더 작은 시간 탐색\n result = mid # 매개 변수 탐색 : 최소값 저장\n else: start = mid+1 # mid초 동안 M명 이상 심사대를 통과할 수 없음\nprint(result)\n\n\"\"\"\n시간을 기준으로 이분탐색한다\n예제1같이 28초의 경우, 1번 심사대가 4명을 심사한다\n\"이번 mid초 동안 몇명이 심사대를 통과할 수 있는가\"를 확인하여\nstart<=end 인 동안 M명을 심사할 수 있는 시간초를\n이분탐색으로 줄여나간다\n\"\"\"\n\n# https://www.acmicpc.net/problem/3079"},{"alpha_fraction":0.4375,"alphanum_fraction":0.5071428418159485,"avg_line_length":24.5,"blob_id":"3b7ac71da6cfe9bb043ce6ab0649f76aefa6e35c","content_id":"233bbf1b7d284f843c7da65fb83ebe712e31d0a6","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":560,"license_type":"no_license","max_line_length":61,"num_lines":22,"path":"/알고리즘/[템플릿]/문자열 탐색/Boyer Moore.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import timeit\nstart = timeit.default_timer()\n\ntext = 'aawneifonoeiwmcl,xjfklsajdfklajewklfhaefnk1r7e8yiueniuencieh02cf12fh0v3ymn,cgjklo10f321hcqvyjkn9og4ml0f21hc3v9yjknqom0h1vcf2y93njkmof210hc3v9jkoymn0f21hcvko9jnym021hfok9cqv3jln,210hf9ocv3jklmny,qgf21h0kmn,jlocqv39cf30hkv9mn,ojlgfvc0hkx12mn,jol9210cf3hk9qvomn,jl10fh9cv3okjmn,g10cf3hv9knom0f9h3koncvm,02f1h9kcv3omn,j2f103vhc9knmjog0f2h19kncv3jmoyg0f21h9cv3njkgmoy0fh921ojkymncgv3,rlf21h0c3v9nyjkmgoh0n9f2yjkmcv13g4h0f21c3vn9kmjyg0hf219ncvjkm3og0f21hc3v9mnjky,o0f21hcvn9km3jy0h1vcf2nk9mj3021hnkf9m,cv3jhf210ncv3mjk9h0f219nycv3jkg0h9f21nycv3jk0h9f21nycv3kjg0fh219mnjkcv3,yogf20h1v3n9cg4kmf0h2913vcgf3210cvh9g4n20f31h9cvnkgf02h9c13vngtkr40fh921nkcvm30hn9kfmcv3h0nf1mk,j9cv3gf,mn12v0chkljox30cf21hkv3mn,9of0cmn,hkvjlo390hk9omnj,2f13vc0h9nk1mojfc3v0h9n12cfkmv3021h9cfnvyh0nf29kmcv13jh29fn1kmcv30f2h91ncvkm30h92nkf1mcv3o0h9f21nkmocv,30h9nk2fmcv130h9fknc12v30h9nk12fmcv320hc9f1nvk30f2h9c1vnkm30h9fnkc1vh9nkmjof12cv30h9fnkmcv12o,30h9f21nkcvmx30hf9n12ckv30h9nfkmc12v30hk9n,mfjloc1v0fh912vcnk3mh9f12vcn30h9nkcf12v30hf2n91mcv0hnf9c12v3h0n9mkj2cfv130h9nfc12v30h9fnkcv12m3gf219hcvn3kg0f21h9cvn3f219hcvk3nf021h9cnv39hf21cv30h9nf2c1vg3h09n1f2ycvg30h9fnc12vy8g3df09h2c1vg30h98y7nfcv213gh0987yfv2c13h0987yf2cv13ghy0987ncfv123h09872fyv134chyf7098cv2g09h87fv2cg13hy67098cv12gh09f21ycv3g4h09y87f12v3cg0h9821vc309h8f12cv309hfcv09hn12vcx309hn1f2cv30h9nf12cv30hn1cf2'\npattern = 'cx309hn1f2cv30h9'\nresult = 0\nfor i in range(len(pattern)-1, len(text)):\n if text[i] == pattern[-1]:\n j = 2\n while True:\n if pattern[-j] == text[i-j+1]:\n if pattern[-j] == pattern[0]:\n result = 1\n break\n else:\n j += 1\n else:\n break\nprint(result)\n\nend = timeit.default_timer()\nprint(f'{end-start:.5f}')"},{"alpha_fraction":0.41304346919059753,"alphanum_fraction":0.43478259444236755,"avg_line_length":12.214285850524902,"blob_id":"ffcae2b2ea2bd33339f2b2c3bddbd8f677e1b196","content_id":"cd9fcff1e7d6f32499dac4c28a97511849274d99","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":184,"license_type":"no_license","max_line_length":17,"num_lines":14,"path":"/알고리즘/온라인저지/2023/03/0301/Serious Problem.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"result = 'yee'\ninput()\nA = B = 0\nfor i in input():\n try:\n int(i)\n A += 1\n except:\n B += 1\nif A > B:\n result = 2\nelif A < B:\n result = 'e'\nprint(result)"},{"alpha_fraction":0.4534534513950348,"alphanum_fraction":0.462462455034256,"avg_line_length":21.200000762939453,"blob_id":"40e375e89993ca1942025715ea253267fc8551b8","content_id":"5409bf21be262397c0d4c974e508471a782fb264","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":333,"license_type":"no_license","max_line_length":40,"num_lines":15,"path":"/알고리즘/온라인저지/2022/07/0720/사탕.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"T = int(input())\nfor t in range(T):\n J, N = map(int, input().split())\n boxes = []\n for n in range(N):\n R, C = map(int, input().split())\n boxes.append(R*C)\n boxes.sort(reverse=True)\n result = 0\n for b in boxes:\n result += 1\n J -= b\n if J <= 0: \n break\n print(result)\n"},{"alpha_fraction":0.5605095624923706,"alphanum_fraction":0.5700637102127075,"avg_line_length":16.5,"blob_id":"0bcf0d9dff5fe7298f0c4c2ec8fc06926f08a53f","content_id":"884814b5d254ce909297348cecb5fdbe91365a38","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":314,"license_type":"no_license","max_line_length":40,"num_lines":18,"path":"/알고리즘/온라인저지/2021/12/1219/나는야 포켓몬 마스터 이다솜.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ndef input():\n return sys.stdin.readline().rstrip()\n\nN, M = map(int, input().split())\n\npokemon = ['' for _ in range(N+1)]\n\nfor i in range(1, N+1):\n pokemon[i] = input()\n\nfor i in range(M):\n quiz = input()\n try:\n print(pokemon[int(quiz)])\n except:\n print(pokemon.index(quiz))"},{"alpha_fraction":0.5,"alphanum_fraction":0.5666666626930237,"avg_line_length":30,"blob_id":"ae6ce872f24bc84ec03d94cba203a17771d16183","content_id":"3a01f41c7c43067ff8cb734d3515164593d6617f","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":30,"license_type":"no_license","max_line_length":30,"num_lines":1,"path":"/알고리즘/온라인저지/2023/05/0518/Metronome.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"print(f'{int(input())/4:.2f}')"},{"alpha_fraction":0.5620437860488892,"alphanum_fraction":0.5620437860488892,"avg_line_length":9.538461685180664,"blob_id":"4cf8c09ae7960615c4e93b074666fc75788e6757","content_id":"af0b0129450d154c35f65fb94a8c3412f0f6110f","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":137,"license_type":"no_license","max_line_length":23,"num_lines":13,"path":"/알고리즘/온라인저지/2022/02/0220/유학 금지.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"\"\"\"\nCAMBRIDGE\n\"\"\"\n\nCAMBRIDGE = \"CAMBRIDGE\"\n\ntext = input()\n\nfor t in text:\n if t in CAMBRIDGE:\n continue\n\n print(t, end='')\n"},{"alpha_fraction":0.6423357725143433,"alphanum_fraction":0.6496350169181824,"avg_line_length":21.83333396911621,"blob_id":"25dec903ad9b237344443376aeb8357521268347","content_id":"ee3b5143d6677a78558dee9a5c3e266882fc0a2f","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":137,"license_type":"no_license","max_line_length":70,"num_lines":6,"path":"/알고리즘/온라인저지/2022/09/0927/수 정렬하기 4.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\n\nN = int(input().rstrip())\nfor i in sorted([int(input()) for _ in [0]*N], reverse=True): print(i)\n"},{"alpha_fraction":0.356890469789505,"alphanum_fraction":0.5088339447975159,"avg_line_length":14.666666984558105,"blob_id":"aeecd25ecb028a7c2365763e459744c7a103d160","content_id":"8b66caccc86483bbaac78a69a634cd3700783891","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":315,"license_type":"no_license","max_line_length":42,"num_lines":18,"path":"/알고리즘/SWEA/LEARN/Course/1. Programming Beginner/파이썬 프로그래밍 기초(2)/28차시 3. 자료구조 – 셋, 딕셔너리 - 연습문제 3.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"data = {\n \"TV\": 2000000,\n \"냉장고\": 1500000,\n \"책상\": 350000,\n \"노트북\": 1200000,\n \"가스레인지\": 200000,\n \"세탁기\": 1000000,\n}\n\ntmp = []\n\nfor d in data:\n tmp.append((d, data[d]))\n\ntmp.sort(key=lambda x: x[1], reverse=True)\n\nfor t in tmp:\n print('{}: {}'.format(t[0], t[1]))\n\n"},{"alpha_fraction":0.43852460384368896,"alphanum_fraction":0.5204917788505554,"avg_line_length":23.5,"blob_id":"d8c02b23a1fca34cd56c7fa838e04c0cfd921aea","content_id":"2f33f623c8d764324547bfb1400d9a5dcc0f06f0","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":328,"license_type":"no_license","max_line_length":34,"num_lines":10,"path":"/알고리즘/온라인저지/2022/04/0417/영화감독 숌.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = int(input())\ncnt = 0 # 몇번째 666인가\nsix3 = 666 # 666부터 출발\nwhile True:\n if '666' in str(six3): # 종말숫자면\n cnt += 1 # 카운트 +1\n if cnt == N: # N번째 종말숫자면\n print(six3) # 값을 출력\n break # while문 종료\n six3 += 1 # 다음 숫자는 종말숫자인가"},{"alpha_fraction":0.5828220844268799,"alphanum_fraction":0.5828220844268799,"avg_line_length":19.5,"blob_id":"57349ba4ebc810e5a39c9ebba1996660e8bcc571","content_id":"0a230881870fde291ae6ce511324df1e28564e1e","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":163,"license_type":"no_license","max_line_length":74,"num_lines":8,"path":"/알고리즘/온라인저지/2021/12/1216/배열 합치기.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N, M = map(int, input().split())\n\nresult = list(map(int, input().split())) + list(map(int, input().split()))\n\nresult.sort()\n\nfor r in result:\n print(r, end=' ')"},{"alpha_fraction":0.65625,"alphanum_fraction":0.65625,"avg_line_length":20.27777862548828,"blob_id":"615b8cd9e0d514fbb85db3d79476159cb87492d4","content_id":"6c6d32a70084ea885405874a6ce436bec54d6565","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":808,"license_type":"no_license","max_line_length":52,"num_lines":18,"path":"/README.md","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"# Just Do It \n\n# 목표\n\n- 배운 내용들을 매일 기록\n- 覚えた内容を毎日記録する\n- Note that I studied today for everyday\n\n# 쉴 때 보기 좋은 명언들\n\n- 건강한 몸에 건강한 정신이 깃든다\n- 하루를 쉬면 메꾸는 데에 삼일이 걸린다\n- 해결할 수 있는 일은 고민하지 말고 하면 되고, 해결할 수 없는 일은 고민해도 소용이 없다\n- 우생마사 : 장마비에 떠내려가는, 소는 가만히 있다가 살고, 말은 발버둥치다가 죽는다\n- 노력이란, 보이지 않는 곳에서 나만 알게 아무도 모르게 하는 것을 말한다\n- 뭘 해야할지, 뭐가 하고 싶은지 모르겠을 땐, 내일 죽는 상상을 해라\n- 완벽하고자 하는 생각이, 모든 일을 시작조차 할 수 없게 만든다\n- \n"},{"alpha_fraction":0.529411792755127,"alphanum_fraction":0.5459558963775635,"avg_line_length":20.799999237060547,"blob_id":"f56e43d383e12710c160419ba79b493029795abb","content_id":"dd6eb87d5b53d1d6980d15e3b29eddd388acf63f","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":588,"license_type":"no_license","max_line_length":58,"num_lines":25,"path":"/알고리즘/온라인저지/2023/01/0107/공유기 설치.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"def install_wifi(distance):\n prev = houses[0]\n cnt = 1\n for house in houses[1:]:\n if house>=prev+distance:\n cnt += 1\n prev = house\n return cnt\n\nN, C = map(int, input().rstrip().split())\nhouses = sorted([int(input().rstrip()) for _ in range(N)])\nresult = 0\nstart, end = result, houses[-1]\nwhile start<=end:\n mid = (start + end)//2\n if install_wifi(mid)>=C:\n result = max(result, mid)\n start = mid+1\n else: \n end = mid-1\nprint(result)\n\n\"\"\"\n다음 집을 탐색할 때, 다음 집이 위치한 인덱스만 확인함\n\"\"\""},{"alpha_fraction":0.4517241418361664,"alphanum_fraction":0.5103448033332825,"avg_line_length":27.700000762939453,"blob_id":"ec91fe98ce55b86a0b053d18b3a65926ba84023f","content_id":"edcfae794bfa825bceda9713217885b3c7d6aff3","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":290,"license_type":"no_license","max_line_length":47,"num_lines":10,"path":"/알고리즘/온라인저지/2023/02/0211/창영마을.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"orders = input()\nballs = [1, 0, 0]\nfor order in orders:\n if order == 'A':\n balls[0], balls[1] = balls[1], balls[0]\n if order == 'B':\n balls[2], balls[1] = balls[1], balls[2]\n if order == 'C':\n balls[0], balls[2] = balls[2], balls[0]\nprint(balls.index(1)+1) "},{"alpha_fraction":0.3638676702976227,"alphanum_fraction":0.44783714413642883,"avg_line_length":18.649999618530273,"blob_id":"a192af52606681438f5eb3e7625baa58b3c14c68","content_id":"3141aa1157817671aba41ef539528d58d47b0d1d","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":393,"license_type":"no_license","max_line_length":40,"num_lines":20,"path":"/알고리즘/온라인저지/2022/03/0317/전자레인지.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"n = [int(input()) for _ in range(5)]\n# print(n)\n\"\"\"\n- to -\n- to +\n0 to +\n+ to +\n\"\"\"\nresult = 0\nif n[0] < 0 and n[1] < 0:\n result += abs(n[0]-n[1]) * n[2]\nelif n[0] < 0 and n[1] > 0:\n result += abs(n[0])*n[2] + n[1]*n[4]\n result += n[3]\nelif n[0] == 0 and n[1] > 0:\n result += n[3]\n result += n[1]*n[4]\nelif n[0] > 0 and n[1] > 0:\n result += abs(n[0]-n[1])*n[4]\nprint(result)\n"},{"alpha_fraction":0.5310077667236328,"alphanum_fraction":0.5426356792449951,"avg_line_length":23.619047164916992,"blob_id":"6a52531cd8767e066e66f9dbf13716785c3bb0b6","content_id":"76abbdf341eba27ccc5492f413d44e96d9524ba8","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":818,"license_type":"no_license","max_line_length":52,"num_lines":21,"path":"/알고리즘/온라인저지/2021/08/0807/OX퀴즈.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"\"\"\"\nO가 연속되는지 알 수 있는 법?\n순회할 때\n이번 값이 O인지 확인하고\n몇번째 O인지 확인해서\n인덱스만큼 더해주기\n\"\"\"\n\nT = int(input()) # 테스트 케이스 개수\n\nfor i in range(T): # 테스트 케이스 개수만큼 반복하면서\n O_and_X = input() # OX를 입력받고\n count = 0 # 연속된 O의 개수를 세는 count를 초기화 하고\n result = 0 # 결과값을 0으로 초기화하고\n for O_or_X in O_and_X: # OX를 순회하면서\n if O_or_X == \"O\": # 순회중인 값이 O면\n count += 1 # 연속된 O의 개수 +1\n result += count # O가 연속된 횟수값을 result에 저장\n else: # 순회중인 값이 X일때\n count = 0 # 연속된 O의 카운트를 초기화\n print(result) # 결과값 출력"},{"alpha_fraction":0.5285714268684387,"alphanum_fraction":0.5690476298332214,"avg_line_length":29.071428298950195,"blob_id":"6a8184efd36129f8ece5ac409441526270aa4a09","content_id":"749bc57666400fa979e42739a2e2e4e77503cf0d","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":592,"license_type":"no_license","max_line_length":70,"num_lines":14,"path":"/알고리즘/온라인저지/2021/08/0805/더하기 사이클.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"a = int(input())\n\ndef calc(a): # 제시된 계산 규칙을 함수로 정의하고\n result = ((a % 10) + (a // 10)) % 10 + (a % 10) * 10\n return result\n\ncalc_list = [a] # 계산된 수들을 저장할 리스트의 0번째를 a로 초기화\ni = 0 # while문 돌리기 위한 i\nwhile True:\n calc_list.append(calc(calc_list[i])) # 함수를 적용하여 리스트에 추가\n i += 1\n if calc_list[0] == calc_list[::-1][0]: # 첫항(입력값)과 계산해서 추가한 값이 같을 때\n break # while문 종료하고\nprint(len(calc_list)-1) # 사이클 수 구해서 출력"},{"alpha_fraction":0.5888158082962036,"alphanum_fraction":0.5986841917037964,"avg_line_length":16.941177368164062,"blob_id":"5248cb7ed3065ee3510e209caf6327ce40009b88","content_id":"39021b7056c88b8116066430bf30cd2b6dafa090","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":304,"license_type":"no_license","max_line_length":36,"num_lines":17,"path":"/알고리즘/온라인저지/2023/02/0226/잃어버린 괄호.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"def new_sum(exp):\n plus_split = exp.split('+')\n answer = 0\n\n for i in range(len(plus_split)):\n answer += int(plus_split[i])\n\n return answer\n\nexps = input()\nminus_split = exps.split('-')\nresult = new_sum(minus_split[0])\n\nfor a in minus_split[1:]:\n result -= new_sum(a)\n\nprint(result)"},{"alpha_fraction":0.42236700654029846,"alphanum_fraction":0.43431052565574646,"avg_line_length":26.117647171020508,"blob_id":"6a01dd2355498daeb346647a4782aca2f8c0ae0d","content_id":"9d5ddc206c6ab609a5daf0e5aef0059790911c3f","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1313,"license_type":"no_license","max_line_length":59,"num_lines":34,"path":"/알고리즘/SWEA/LEARN/Course/2. Programming Intermediate/1. 파이썬 SW문제해결 기본 List1/7차시 1일차 - 전기버스.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"T = int(input())\n\nfor t in range(1, T+1):\n K, N, M = map(int, input().split())\n charge = list(map(int, input().split())) # 충전소 위치\n\n stop = [0] * (N+1) # 정류장 초기값\n\n for c in charge: # 충전소가 있는 정류장 정보를 갱신\n stop[c] = 1\n \n now = 0 # 현재 위치(초기 출발위치)\n cnt = 0 # 충전 횟수\n\n while now+K < N: # 목적지에 도달하기 전까지\n tmp = now # now값을 조작할 것이므로\n # 조작 전 now값을 tmp에 저장\n\n for i in range(now+K, now-1, -1): # 갈 수 있는 가장 멀리부터 \n # 현재 위치까지 거꾸로 확인하기\n if stop[i]: # 충전소가 발견되면\n # 뒤에서 탐색하였기 때문에\n # 가장 먼저 발견되는 충전소는 \n # 갈 수 있는 충전소 중 가장 멀리있는 충전소\n now = i # 해당 충전소의 위치로 이동\n cnt += 1 # 충전 한번 하였음\n break # 해당 for문 종료\n \n if i == tmp: # 충전소를 못찾고 결국 제자리로 돌아오면\n # 목적지에 도달할 수 없으므로\n cnt = 0 # 갈 수 없음\n break # while 종료\n\n print('#{} {}'.format(t, cnt))"},{"alpha_fraction":0.5458333492279053,"alphanum_fraction":0.5708333253860474,"avg_line_length":15.066666603088379,"blob_id":"e364e49c186d6d6d978eb12641affaa6327193f4","content_id":"0114afa6ea0afd667649979e2a698807808ad673","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":240,"license_type":"no_license","max_line_length":30,"num_lines":15,"path":"/알고리즘/온라인저지/2022/09/0930/문서 검색.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\n\nword = input().rstrip()\npattern = input().rstrip()\nL = len(pattern)\ni = 0\nresult = 0\nwhile i<len(word)-L+1:\n if pattern == word[i:i+L]:\n result += 1\n i += L-1\n i += 1\nprint(result)"},{"alpha_fraction":0.43933823704719543,"alphanum_fraction":0.4595588147640228,"avg_line_length":23.772727966308594,"blob_id":"0e4a9dadd61ed42e09b2c17899fe22e42b0bbe31","content_id":"3d3e5eaccd4d1095fd249c561a3dce8edda33415","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":544,"license_type":"no_license","max_line_length":61,"num_lines":22,"path":"/알고리즘/[템플릿]/Floyd-Warshall/플로이드.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"INF = int(1e9)\nN = int(input())\nM = int(input())\narr = [[INF]*N for _ in range(N)]\nfor m in range(M):\n a, b, c = map(int, input().split())\n a, b = a-1, b-1\n if c < arr[a][b]:\n arr[a][b] = c\nfor k in range(N):\n for a in range(N):\n for b in range(N):\n arr[a][b] = min(arr[a][b], arr[a][k] + arr[k][b])\nfor i in range(N):\n for j in range(N):\n if i == j:\n arr[i][j] = 0 \n if arr[i][j] == INF:\n arr[i][j] = 0\nfor a in arr: print(*a)\n\n# https://www.acmicpc.net/problem/11404"},{"alpha_fraction":0.3787878751754761,"alphanum_fraction":0.469696968793869,"avg_line_length":10.166666984558105,"blob_id":"27dfa310cf5c134b8c673ce3891b7e38f7b724e9","content_id":"f6936d15b61d136d2965137e2654e1a9d222f551","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":66,"license_type":"no_license","max_line_length":25,"num_lines":6,"path":"/알고리즘/SWEA/LEARN/Course/1. Programming Beginner/파이썬 프로그래밍 기초(2)/10차시 2. 자료구조 – 리스트, 튜플 - 연습문제 11.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"l = [1, 1]\n\nwhile len(l) < 10:\n l.append(l[-1]+l[-2])\n\nprint(l)"},{"alpha_fraction":0.6000000238418579,"alphanum_fraction":0.6380952596664429,"avg_line_length":16.66666603088379,"blob_id":"d86568666bb62b27a98706524533232e230ae619","content_id":"ee35419877ac6335611130b249c0443dee68370e","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":105,"license_type":"no_license","max_line_length":44,"num_lines":6,"path":"/알고리즘/온라인저지/2022/09/0927/소수.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\n\nA, B, N = map(int, input().rstrip().split())\nprint(A*10**N//B%10)"},{"alpha_fraction":0.48179271817207336,"alphanum_fraction":0.5070028305053711,"avg_line_length":28.83333396911621,"blob_id":"72948bf732ad1b06a77f373173cc6c7a71b896c5","content_id":"074cc9b03882bb36fc868b03a201bf39170fb280","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":357,"license_type":"no_license","max_line_length":47,"num_lines":12,"path":"/알고리즘/온라인저지/2022/04/0427/성적 통계.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"K = int(input())\nfor k in range(1, K+1):\n score = list(map(int, input().split()))\n score = score[1:]\n # print(score)\n score.sort()\n A, B, C = score[-1], score[0], 0\n for i in range(len(score)-1):\n if score[i+1]-score[i] > C:\n C = score[i+1]-score[i]\n print(f'Class {k}')\n print(f'Max {A}, Min {B}, Largest gap {C}')"},{"alpha_fraction":0.4864864945411682,"alphanum_fraction":0.5027027130126953,"avg_line_length":12.214285850524902,"blob_id":"50db3dc051ffeb499789bdebe9c6972ce0196442","content_id":"c742b893d0132977f18561320ed2fb467d5c9b56","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":185,"license_type":"no_license","max_line_length":35,"num_lines":14,"path":"/알고리즘/온라인저지/2022/02/0217/와글와글 숭고한.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"S, K, H = map(int, input().split())\n\nOK_check = True\n\ndictt = {\n S:'Soongsil',\n K:'Korea',\n H:'Hanyang',\n}\n\nif S+K+H >= 100:\n print('OK')\nelse:\n print(dictt[min(S,K,H)])\n"},{"alpha_fraction":0.29646018147468567,"alphanum_fraction":0.36283186078071594,"avg_line_length":9.318181991577148,"blob_id":"ab0030daa1105a84aa65971ad823cfb253656a81","content_id":"f030c5c666abf3cefc5b4e7675cd1a05e2f77628","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":226,"license_type":"no_license","max_line_length":30,"num_lines":22,"path":"/알고리즘/온라인저지/2021/12/1216/학점계산.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"grade = input()\n\nalpha = {\n 'A': 4,\n 'B': 3,\n 'C': 2,\n 'D': 1,\n 'F': 0,\n '+': 0.3,\n '0': 0.0,\n '-': -0.3,\n},\n\nresult = 0\n\n\n\nfor g in grade:\n result += alpha[0][g]\n \n\nprint('{:.1f}'.format(result))"},{"alpha_fraction":0.5574324131011963,"alphanum_fraction":0.5810810923576355,"avg_line_length":21.846153259277344,"blob_id":"99c9c1246ff25e1c097054b33b3f12118b46ab2c","content_id":"01593ab99ddf4a86b60918067f2df032eb7496c3","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":296,"license_type":"no_license","max_line_length":40,"num_lines":13,"path":"/알고리즘/온라인저지/2022/07/0724/박 터뜨리기.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N, K = map(int, input().split())\nbuckets = list(range(1, K+1))\nbuckets.sort(reverse=True)\nresult = 0\nif N < sum(buckets):\n result = -1\nelse:\n idx = 0\n for i in range(N-sum(buckets)):\n buckets[idx] += 1\n idx = (idx+1)%K\n result = max(buckets) - min(buckets)\nprint(result)"},{"alpha_fraction":0.47999998927116394,"alphanum_fraction":0.5600000023841858,"avg_line_length":12,"blob_id":"e1c9a5a5f55a6a89d996f6c031e82a407e76b61b","content_id":"896b5a18df2d6a376fc438ed4705848bee82883f","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":25,"license_type":"no_license","max_line_length":13,"num_lines":2,"path":"/알고리즘/온라인저지/2022/03/0303/알고리즘 수업 - 알고리즘의 수행 시간 1.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"n = input()\nprint('1\\n0')"},{"alpha_fraction":0.4524714946746826,"alphanum_fraction":0.47148290276527405,"avg_line_length":19.30769157409668,"blob_id":"07e478c87a1bf9ae98e19879597e23fcd35a33a3","content_id":"c393e820a6830fd2cd06c7bd863ace94c7bae03b","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":263,"license_type":"no_license","max_line_length":37,"num_lines":13,"path":"/알고리즘/온라인저지/2022/06/0613/한조서열정리하고옴ㅋㅋ.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = int(input())\narr = list(map(int, input().split()))\nresult = 0\nfor i in range(N-1):\n tmp = 0\n for j in range(i+1, N):\n if arr[i] > arr[j]:\n tmp += 1\n else:\n break\n if tmp > result:\n result = tmp\nprint(result)"},{"alpha_fraction":0.48148149251937866,"alphanum_fraction":0.5259259343147278,"avg_line_length":21.66666603088379,"blob_id":"9eed69c5e4aa7e34a28382e842de976a2869d204","content_id":"4a26191c9a63789601a44c9aabc5453a1261c66d","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":135,"license_type":"no_license","max_line_length":32,"num_lines":6,"path":"/알고리즘/온라인저지/2023/01/0126/숫자 빈도수.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N, D = map(int, input().split())\ncount = [0]*10\nfor i in range(1, N+1):\n for j in str(i):\n count[int(j)] += 1\nprint(count[D])"},{"alpha_fraction":0.4688427448272705,"alphanum_fraction":0.48367953300476074,"avg_line_length":23.14285659790039,"blob_id":"026a47c7470f95d4eafa3003bf65d72e93e1160e","content_id":"a55d6cc7bf2f99d3f6171ebffa2a0c568d5257d9","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":337,"license_type":"no_license","max_line_length":43,"num_lines":14,"path":"/알고리즘/온라인저지/2022/10/1012/모든 순열.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"def perm(arr, i):\n if i == len(arr)-1:\n result.append(arr[:])\n else:\n for j in range(i, len(arr)):\n arr[i], arr[j] = arr[j], arr[i]\n perm(arr, i+1)\n arr[i], arr[j] = arr[j], arr[i]\n\narr = list(range(1, int(input())+1))\nresult = []\nperm(arr, 0)\nresult.sort()\nfor r in result: print(*r)"},{"alpha_fraction":0.4663677215576172,"alphanum_fraction":0.4708520174026489,"avg_line_length":19.18181800842285,"blob_id":"7c212d2d82f9343ea7fefebf8833825a7779c863","content_id":"d32d308af643480b5a6601c5c1689ce512db4f39","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":223,"license_type":"no_license","max_line_length":35,"num_lines":11,"path":"/알고리즘/온라인저지/2021/09/0906/최소공배수.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\ndef input():\n return sys.stdin.readline()\n\nT = int(input())\nfor t in range(T):\n A, B = map(int,input().split())\n C, D = A, B\n while A % B != 0:\n A, B = B, A % B\n print(B * (C//B) * (D//B))\n\n"},{"alpha_fraction":0.5,"alphanum_fraction":0.5,"avg_line_length":24.5,"blob_id":"5ff55148ee570657acc29af2a02533fef31505ed","content_id":"2bee23986f9ac5b03e49f9e95b10df7be3ad9d58","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":254,"license_type":"no_license","max_line_length":42,"num_lines":10,"path":"/알고리즘/온라인저지/2022/06/0615/성 지키기.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N, M = map(int, input().split())\ncastle = [list(input()) for _ in range(N)]\nrow = set()\ncol = set()\nfor i in range(N):\n for j in range(M):\n if castle[i][j] == 'X':\n row.add(i)\n col.add(j)\nprint(max(N-len(row), M-len(col)))"},{"alpha_fraction":0.40956342220306396,"alphanum_fraction":0.4615384638309479,"avg_line_length":16.851852416992188,"blob_id":"304a204e877399af57ba8e5710d35031fd4b2386","content_id":"a58b9822e891db72acab15cd6af7f7906a7371b7","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":481,"license_type":"no_license","max_line_length":33,"num_lines":27,"path":"/알고리즘/SWEA/LEARN/Course/1. Programming Beginner/파이썬 프로그래밍 기초(2)/5차시 2. 자료구조 – 리스트, 튜플 - 연습문제 3.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"all = set()\n\nfor i in range(1, 10):\n for j in range(1, 10):\n all.add(i * j)\n\nall.discard(1)\n\nfor i in range(3, 82, 3):\n for j in range(7, 82, 7):\n if i in all:\n all.discard(i)\n elif j in all:\n all.discard(j)\n\nresult = [[] for _ in range(8)]\n\nfor i in range(2, 10):\n tmp = 0\n for j in range(i, 82, i):\n tmp += 1\n if j in all:\n result[i-2].append(j)\n if tmp == 9:\n break\n\nprint(result)"},{"alpha_fraction":0.4434782564640045,"alphanum_fraction":0.5652173757553101,"avg_line_length":37.66666793823242,"blob_id":"d46f46b724b9a3f336f8acf2bcf04ad0269117bb","content_id":"6cef050bb8a8e946af7af24c7058a9da02a45040","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":115,"license_type":"no_license","max_line_length":42,"num_lines":3,"path":"/알고리즘/온라인저지/2022/08/0822/Contest Timing.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"D, H, M = map(int, input().split())\nresult = (D-11)*24*60 + (H-11)*60 + (M-11)\nprint(result if result >= 0 else -1)"},{"alpha_fraction":0.5293244123458862,"alphanum_fraction":0.5567928552627563,"avg_line_length":29.636363983154297,"blob_id":"afdd97f08677ba672abe91eff28bba9755249878","content_id":"9047eb822e4dbf74caacb7a59760aee5f82e5f8f","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1845,"license_type":"no_license","max_line_length":69,"num_lines":44,"path":"/알고리즘/[템플릿]/Dijkstra/미로만들기.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\nfrom heapq import heappush, heappop\n\ninput = sys.stdin.readline # 일종의 루틴 같은 것\ndy, dx = [1, 0, -1, 0], [0, 1, 0, -1] # 델타이동\n\ndef dijkstra():\n heappush(Q, (0, 0, 0)) # change, y, x\n visited[0][0] = 1 # 0, 0 출발\n while Q:\n change, y, x = heappop(Q) # heapq 특성상, 튜플등에선 맨 앞 값을 기준으로 정렬한다\n if y == x == N-1: break # 방을 바꿔가며 어찌저찌 목표지점에 도착\n delta_move(change, y, x) # 4방향 델타이동\n return change # line 11의 change를 의미함, while문을 break했을 때의 change\n\ndef delta_move(change, y, x):\n for i in range(4):\n ny, nx = y+dy[i], x+dx[i]\n if 0<=ny<N and 0<=nx<N and not visited[ny][nx]:\n visited[ny][nx] = 1\n if room[ny][nx] == 0: # 검은 방 : 통과 불가능, 흰 방으로 바꿈\n heappush(Q, (change+1, ny, nx)) # 방 바꾸면서 가자\n else: # 흰 방 : 통과 가능\n heappush(Q, (change, ny, nx))\n\nN = int(input().rstrip())\nroom = [list(map(int, input().rstrip())) for _ in range(N)]\nvisited = [[0]*N for _ in range(N)]\nQ = []\nprint(dijkstra())\n\n\"\"\"\n핵심\n1. visited[i][j]에 대해서, 한 차원 더 방문배열을 만들면서\n \"방을 몇 번 바꾸면서 지나왔는가\"는 기록할 필요가 없다\n 어차피 i,j번 방이, 검은 방을 흰색 방으로 바꿔야 갈 수 있다면\n 방을 바꾸지 않고는, change+1 하지 않고는 해당 지점에 닿을 수 없다\n2. room[N-1][N-1]에 도달하던 말던 상관없이\n 방을 바꾸는 횟수를 최소로 하여 목표까지 도달해야 하기 때문에\n Q[0]에 집어 넣은 change의 값이 작은 것 부터 탐색한다\n 그래서 이 문제는 다익스트라다\n\"\"\"\n\n# https://www.acmicpc.net/problem/2665"},{"alpha_fraction":0.26778241991996765,"alphanum_fraction":0.3012552261352539,"avg_line_length":18.58333396911621,"blob_id":"8f863018ae81c5a8c18c4a55312dcc8ab2345523","content_id":"f9333004ce1914d8555f56fb19f2d2d027e093b8","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":239,"license_type":"no_license","max_line_length":51,"num_lines":12,"path":"/알고리즘/온라인저지/2022/06/0605/별 찍기 - 21.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = int(input())\n# N = 3\nif N == 1:\n tmp = ['*']\nelse:\n if N%2:\n tmp = [['*']*((N//2)+1), ['']+['*']*(N//2)]\n else:\n tmp = [['*']*(N//2), ['']+['*']*(N//2)]\nfor i in range(N):\n for t in tmp:\n print(*t)\n "},{"alpha_fraction":0.42578125,"alphanum_fraction":0.4375,"avg_line_length":29.760000228881836,"blob_id":"bd11aa1d53509053977f0630b933b88bc3f823b4","content_id":"42e49d8d3627b2b5a02e76c9d14c53049d683ceb","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":884,"license_type":"no_license","max_line_length":102,"num_lines":25,"path":"/알고리즘/온라인저지/2021/08/0823/암호 만들기.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"L, C = map(int, input().split())\narr = list(input().split())\n\nn = len(arr)\nresult = []\nfor i in range(1<<n): # 모든 암호(부분집합)들 중에서\n tmp = []\n for j in range(n):\n if i&(1<<j):\n tmp.append(arr[j])\n if len(tmp) == L: # 길이가 L이고\n if ('a' in tmp) or ('e' in tmp) or ('i' in tmp) or ('o' in tmp) or ('u' in tmp): # 모음이 하나이상 있고\n count = 0\n for tm in tmp:\n if tm in 'bcdfghjklmnpqrstvwxyz': # 자음이\n count += 1\n if count >= 2: # 두개 이상일 때\n tmp.sort() # 정렬해서\n tmp2 = ''\n for t in tmp:\n tmp2 = tmp2 + t # 단어로 만들어서\n result.append(tmp2) # 추가\nresult.sort() # 추가한 값들을 정렬\nfor res in result:\n print(res) # 출력"},{"alpha_fraction":0.5122873187065125,"alphanum_fraction":0.5406427383422852,"avg_line_length":23.090909957885742,"blob_id":"14a7acb5a0e885f230591d75bbe486596f1a885f","content_id":"63c65bd4e38b399ee5c9286ff7aefd13d709135a","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":629,"license_type":"no_license","max_line_length":47,"num_lines":22,"path":"/알고리즘/온라인저지/2022/09/0925/퇴사.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\n\nN = int(input().rstrip())\nT, P, dp = [], [], []\nfor i in range(N):\n a, b = map(int, input().rstrip().split())\n T.append(a)\n P.append(b)\n dp.append(b)\ndp.append(0)\nfor i in range(N-1, -1, -1):\n if T[i]+i > N: # 이 날 시작한 일이 퇴사일을 넘길 경우\n dp[i] = dp[i+1]\n else: # 퇴사일 전에 일을 마칠 수 있는 경우\n # 그 일을 마친 날 기준, 해당 일에 얻을 수 있는 최대 이익\n dp[i] = max(dp[i+1], P[i] + dp[i+T[i]])\nprint(dp[0])\n\n# https://www.acmicpc.net/problem/14501\n# https://pacific-ocean.tistory.com/199"},{"alpha_fraction":0.4275362193584442,"alphanum_fraction":0.4492753744125366,"avg_line_length":22.16666603088379,"blob_id":"c978fe442dfc40753c7577772655ca0dc7717d4f","content_id":"b0ab13b81175361078d58bc389b049bec3b78fca","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":138,"license_type":"no_license","max_line_length":32,"num_lines":6,"path":"/알고리즘/온라인저지/2022/06/0607/시그마.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"a, b = map(int, input().split())\nn_max = max(a, b)\nn_min = min(a, b)\nn = n_max - n_min\ns = (n * (n + 1)) // 2\nprint(s + (n_min * (n + 1)))"},{"alpha_fraction":0.46060606837272644,"alphanum_fraction":0.539393961429596,"avg_line_length":19.75,"blob_id":"d598e479161cc6c290b07b9acb6e4cf8c628bfba","content_id":"0505780c3b58618328f0c2a780b57edaea1bb717","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":165,"license_type":"no_license","max_line_length":39,"num_lines":8,"path":"/알고리즘/온라인저지/2023/04/0409/Bicycle.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"nums = [int(input()) for _ in range(5)]\na, x, b, y, T = nums\nresult = [a, b]\nA = max(0, T-30)\nB = max(0, T-45)\nresult[0] += A*x*21\nresult[1] += B*y*21\nprint(*result)"},{"alpha_fraction":0.4301075339317322,"alphanum_fraction":0.44301074743270874,"avg_line_length":21.190475463867188,"blob_id":"5794ecc16106255d36e5ffb0e94f809ecea77980","content_id":"62cea035ba915366f744c7cec0135fdc2a67dee9","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":639,"license_type":"no_license","max_line_length":38,"num_lines":21,"path":"/알고리즘/온라인저지/2021/08/0823/A와 B.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"S = list(input())\nT = list(input())\nresult = 0\n# A를 추가하거나, 뒤집고 B를 추가하는 두가지만 가능\n# 뒤집어서 생각하면\n# T에서 A를 빼거나, B를 빼고 뒤집어가면서 S와 일치하는지 확인\nwhile True:\n if S == T: # 만들 수 있으면 \n result = 1 # 1\n break\n if T[-1] == 'A': # 맨 뒷글자가 A면\n T.pop() # 빼고\n if not T: # 다 빼서 T가 []가 되면\n break # 종료\n elif T[-1] == 'B': # 맨 뒷글자가 B면\n T.pop() # 빼고\n if not T: # T == []\n break # 종료\n T = T[::-1] # 뒤집고\n\nprint(result)"},{"alpha_fraction":0.4858299493789673,"alphanum_fraction":0.4898785352706909,"avg_line_length":19.66666603088379,"blob_id":"ff138b5dec70e26398ec97f58cbfb4c00e03dbb3","content_id":"bc0518ef6ce8ac139bff759b42cf85a1e81ae49f","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":247,"license_type":"no_license","max_line_length":32,"num_lines":12,"path":"/알고리즘/온라인저지/2022/09/0903/분수 합.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"def gcd(a, b):\n while b > 0: a, b = b, a%b\n return a\n\nA, B = map(int, input().split())\nC, D = map(int, input().split())\nGCD = gcd(B, D)\nLCM = GCD * (B//GCD) * (D//GCD)\nE = A*(LCM//B) + C*(LCM//D)\nF = LCM\nGCD = gcd(E, F)\nprint(E//GCD, F//GCD)"},{"alpha_fraction":0.47058823704719543,"alphanum_fraction":0.48235294222831726,"avg_line_length":20.375,"blob_id":"41ad2a1b99efda3ebf55d6138dd53de5a467e2fc","content_id":"4b674e4f0b78191770d60272502900b1d2a06045","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":170,"license_type":"no_license","max_line_length":39,"num_lines":8,"path":"/알고리즘/온라인저지/2023/06/0608/Triathlon.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"result = 0\nfor _ in range(int(input())):\n A, D, G = map(int, input().split())\n C = A*(D+G)\n if A == D+G:\n C *= 2\n result = max(result, C)\nprint(result)"},{"alpha_fraction":0.5520833134651184,"alphanum_fraction":0.5729166865348816,"avg_line_length":11.125,"blob_id":"b0ce847b856a2d50c8685c18365bea0960a930e6","content_id":"7555147602ad2e5b10807573ffd8473cb148b393","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":96,"license_type":"no_license","max_line_length":26,"num_lines":8,"path":"/알고리즘/SWEA/LEARN/Course/1. Programming Beginner/파이썬 프로그래밍 기초(2)/31차시 3. 자료구조 – 셋, 딕셔너리 - 연습문제 6.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = int(input())\n\nresult = {}\n\nfor i in range(1, N+1):\n result.update({i:i*i})\n\nprint(result)"},{"alpha_fraction":0.5396419167518616,"alphanum_fraction":0.5652173757553101,"avg_line_length":29.153846740722656,"blob_id":"6d55bc0f1c426a8b9e25e7dc0b2705df8df0c1ea","content_id":"a504f7b1a131bc599c52f2d28d771db8ce7ef5f8","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":391,"license_type":"no_license","max_line_length":57,"num_lines":13,"path":"/알고리즘/온라인저지/2023/01/0114/텔레프라임.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"def prime_list(size):\n sieve = [True]*(size+1)\n for i in range(2, int(size**0.5)+1):\n if sieve[i]:\n for j in range(i+i, size+1, i):\n sieve[j] = False\n return [i for i in range(2, size+1) if sieve[i]]\n\nold, new = input().split()\nnew = int(new+old)\nold = int(old)\nprimes = prime_list(int(1e7))\nprint('Yes' if old in primes and new in primes else 'No')"},{"alpha_fraction":0.45781466364860535,"alphanum_fraction":0.46473029255867004,"avg_line_length":33.47618865966797,"blob_id":"b66fa1c79978d5f3526c6d26667576eaa4f5a9cb","content_id":"70ea43d18493bdb22ee55fdea47dad285faf1747","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":947,"license_type":"no_license","max_line_length":71,"num_lines":21,"path":"/알고리즘/온라인저지/2022/09/0908/마니또.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"case = 1 # 테스트 케이스\nwhile True:\n N = int(input()) # 사람 수\n if N == 0: break # while 종료\n result = [] # 결과를 담을 배열\n for n in range(N):\n A, B = input().split() # 사람 A, 사람 B\n flag = False # 이미 있는 그룹인지 확인할 것\n for i in range(len(result)): # 마니또 그룹들 중에서\n if A in result[i] or B in result[i]: # 둘 중 하나라도 속하는 그룹이 있다면\n flag = True # 둘 다 결국 같은 그룹\n # set()로 중복처리하면서 사람들을 다 추가할 것\n result[i].add(A)\n result[i].add(B)\n if not flag: # 둘 다 속한 마니또그룹이 없으면\n result.append(set()) # 그룹 추가\n # 사람들 추가\n result[-1].add(A)\n result[-1].add(B)\n print(case, len(result)) # 출력\n case += 1 # 다음 케이스"},{"alpha_fraction":0.6487804651260376,"alphanum_fraction":0.6487804651260376,"avg_line_length":21.88888931274414,"blob_id":"4e298261d501b46768387138f205e6f9478322d3","content_id":"35838888439273c23c5bcea09c070a224a3e2e18","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":205,"license_type":"no_license","max_line_length":46,"num_lines":9,"path":"/알고리즘/온라인저지/2023/05/0513/빅데이터 정보보호.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"input()\nS = input()\nbigdata, security = S.count('b'), S.count('s')\nresult = 'bigdata? security!'\nif bigdata > security:\n result = 'bigdata?'\nif bigdata < security:\n result = 'security!'\nprint(result)"},{"alpha_fraction":0.5222222208976746,"alphanum_fraction":0.5444444417953491,"avg_line_length":10.375,"blob_id":"c5ca30f1159baf3e0f52aa88315cc76c79e7cdce","content_id":"10cd16d61291bfde9bf077d8920231e5a3be715b","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":90,"license_type":"no_license","max_line_length":23,"num_lines":8,"path":"/알고리즘/온라인저지/2022/02/0209/나머지와 몫이 같은 수.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = int(input())\n\nresult = 0\n\nfor n in range(1, N):\n result += N * n + n\n\nprint(result)"},{"alpha_fraction":0.48404255509376526,"alphanum_fraction":0.5106382966041565,"avg_line_length":17.899999618530273,"blob_id":"6284f1d16b5fdb96c570593733abc628c28c1b2c","content_id":"6a15fcaa6c84350c0702f6e59de77f95da8b1c48","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":188,"license_type":"no_license","max_line_length":41,"num_lines":10,"path":"/알고리즘/SWEA/LEARN/Course/1. Programming Beginner/파이썬 프로그래밍 기초(2)/15차시 2. 자료구조 – 리스트, 튜플 - 연습문제 17.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import math\nfrom math import pi\n\nx = list(map(int, input().split(', ')))\n\nfor i in x:\n if i == x[-1]:\n print(round(2*pi*i, 2))\n else:\n print(round(2*pi*i, 2), end=', ')"},{"alpha_fraction":0.5833333134651184,"alphanum_fraction":0.5952380895614624,"avg_line_length":41.5,"blob_id":"b87ce35f7bcca3781963da20eb25a75eae60cc8c","content_id":"fb992ead3d912680f659de9b016e792100b27bcc","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":84,"license_type":"no_license","max_line_length":54,"num_lines":2,"path":"/알고리즘/온라인저지/2022/08/0803/N번째 큰 수.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"for _ in range(int(input())):\n print(sorted(list(map(int, input().split())))[-3])"},{"alpha_fraction":0.6113074421882629,"alphanum_fraction":0.6466431021690369,"avg_line_length":20.846153259277344,"blob_id":"e078c5b357834ad5ddec44806f3f7258212c18dd","content_id":"d45d7b03417b1e995045c02b6b663957f23a8816","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":283,"license_type":"no_license","max_line_length":63,"num_lines":13,"path":"/알고리즘/온라인저지/2022/09/0927/점수 계산.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\n\nscores = []\nfor i in range(1, 9): scores.append([int(input().rstrip()), i])\nscores.sort(key=lambda x:-x[0])\nresult = [0]\nfor score in scores[:5]:\n result[0] += score[0]\n result.append(score[1])\nprint(result[0])\nprint(*sorted(result[1:]))"},{"alpha_fraction":0.6132264733314514,"alphanum_fraction":0.6432865858078003,"avg_line_length":30.25,"blob_id":"06560b7b8febe621f12edc8b9953ec9beeb50a9a","content_id":"a643fca562ba1f7faff32c4078ff86e8701c9cf5","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":499,"license_type":"no_license","max_line_length":49,"num_lines":16,"path":"/알고리즘/온라인저지/2022/07/0721/카우버거.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"B, C, D = map(int, input().split())\nburger = list(map(int, input().split()))\nside = list(map(int, input().split()))\ndrink = list(map(int, input().split()))\nburger.sort(reverse=True)\nside.sort(reverse=True)\ndrink.sort(reverse=True)\nmin_set = min(len(burger), len(side), len(drink))\nresult1 = sum(burger) + sum(side) + sum(drink)\nprint(result1)\nresult2 = result1\nfor i in range(min_set):\n result2 -= burger[i] * 0.1\n result2 -= side[i] * 0.1\n result2 -= drink[i] * 0.1\nprint(f'{result2:.0f}')"},{"alpha_fraction":0.4595959484577179,"alphanum_fraction":0.502525269985199,"avg_line_length":19.894737243652344,"blob_id":"923a6ece9e13afe4039da11aca1ae3d0d5c3a066","content_id":"f068a3cc2301a75db56adc5d254709600f7b352f","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":396,"license_type":"no_license","max_line_length":38,"num_lines":19,"path":"/알고리즘/온라인저지/2023/01/0112/부재중 전화.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N, L, D = map(int, input().split())\nsong_len_max = N*L + (N-1)*5\nring_len_max = (song_len_max//D + 2)*D\narr1 = [0]*ring_len_max\narr2 = [0]*ring_len_max\ni = 0\nfor n in range(N):\n for l in range(L):\n arr1[i] = 1\n i += 1\n i += 5\ni = 0\nwhile i < ring_len_max:\n arr2[i] += 1\n i += D\nfor i in range(ring_len_max):\n if not arr1[i] and arr2[i]:\n print(i)\n break"},{"alpha_fraction":0.5312855243682861,"alphanum_fraction":0.5711035132408142,"avg_line_length":22.157894134521484,"blob_id":"a1d70113e03cad99468197ae840eb4a3bf77bd7d","content_id":"820462ac5123397507d7eb36808454f54fd40c6b","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1185,"license_type":"no_license","max_line_length":66,"num_lines":38,"path":"/알고리즘/온라인저지/2022/10/1006/내리막 길.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\ndy, dx = [-1, 1, 0, 0], [0, 0, -1, 1]\n\ndef dfs(y, x):\n if y == N-1 and x == M-1: return 1\n if visited[y][x] != -1: return visited[y][x]\n visited[y][x] = 0\n for i in range(4):\n ny, nx = y+dy[i], x+dx[i]\n if 0<=ny<N and 0<=nx<M:\n if arr[ny][nx] < arr[y][x]:\n visited[y][x] += dfs(ny, nx)\n return visited[y][x]\n\nN, M = map(int, input().rstrip().split())\narr = [list(map(int, input().rstrip().split())) for _ in range(N)]\nvisited = [[-1]*M for _ in range(N)]\nprint(dfs(0, 0))\n\n\"\"\"\n탐색하면서 처리하는 방문 배열이 그냥 배열이 아닌 DP배열이다\n1.방문배열 초기화는 -1\n2.방문처리는 0\n3.해당 지점을 경유하여 목적지에 도달 가능한 경로 경우의 수\n등으로 방문배열을 채워나간다\n3번이 채워지는 원리가 신박하다\n목적지에 도달할 경우 line 7을 통해서\n지나온 모든 경로에 1을 더해준다\n결과적으로 시작점에서 봤을 때\n목적지까지 갈 수 있는 경로의 수가 visited[0][0]에 들어오게 된다\n\n<참고한 링크>\nhttps://ca.ramel.be/70\n\"\"\"\n\n# https://www.acmicpc.net/problem/1520"},{"alpha_fraction":0.4149560034275055,"alphanum_fraction":0.4545454680919647,"avg_line_length":19.696969985961914,"blob_id":"03a49c42fbbf838e945fa3e9afba076faae20fdf","content_id":"a10d8d54523e780736fbbf23ca8e8c896ba10d83","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":682,"license_type":"no_license","max_line_length":56,"num_lines":33,"path":"/알고리즘/SWEA/LEARN/Course/3. Programming Advanced/2. 파이썬 SW문제해결 응용 구현 02 완전 검색/3차시 2일차 - 최소합.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"dx = [1, 0]\ndy = [0, 1]\n\ndef dfs(x, y, tmp):\n global result\n if x == N-1 and y == N-1:\n if tmp < result:\n result = tmp\n\n if tmp > result:\n return\n\n for i in range(2):\n visited[y][x] = 1\n nx = x+dx[i]\n ny = y+dy[i]\n if 0<=nx<N and 0<=ny<N and visited[ny][nx] == 0:\n dfs(nx, ny, tmp+arr[ny][nx])\n visited[y][x] = 0\n\nTC = int(input())\n\nfor tc in range(1, TC+1):\n N = int(input())\n arr = []\n for n in range(N):\n arr.append(list(map(int, input().split())))\n \n visited = [[0]*N for _ in range(N)]\n\n result = 99999999\n dfs(0, 0, arr[0][0])\n print('#{} {}'.format(tc, result))"},{"alpha_fraction":0.631147563457489,"alphanum_fraction":0.6434426307678223,"avg_line_length":23.5,"blob_id":"d5afc7a1eff0d28be6d0ecc2d95fcc5fece9ba38","content_id":"f36655b0d474b9897db3e1ac6ca2a93cd3c61cb9","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":244,"license_type":"no_license","max_line_length":53,"num_lines":10,"path":"/알고리즘/온라인저지/2022/11/1115/멀티탭 충분하니.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\n\nN, K = map(int, input().rstrip().split())\nmulti_taps = list(map(int, input().rstrip().split()))\nresult = 0\nfor multi_tap in multi_taps:\n result += (multi_tap+1)//2\nprint('YES' if result >= N else 'NO')"},{"alpha_fraction":0.5072463750839233,"alphanum_fraction":0.52173912525177,"avg_line_length":24.875,"blob_id":"db041a3de5ca13a121bf7e3874c9b158945e489a","content_id":"c8aefa21b27dd2bd48461e3c4ed514df90a6ca31","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":207,"license_type":"no_license","max_line_length":36,"num_lines":8,"path":"/알고리즘/온라인저지/2021/08/0816/단어순서 뒤집기.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"T = int(input())\nfor t in range(1, T+1):\n sentence = list(input().split())\n sentence = sentence[::-1]\n print(f'Case #{t}: ', end='')\n for sen in sentence:\n print(sen, end=' ')\n print()\n"},{"alpha_fraction":0.4270557165145874,"alphanum_fraction":0.4482758641242981,"avg_line_length":24.200000762939453,"blob_id":"0950086e4df027a87da9f72a88612c0b44f783c9","content_id":"0c19491eebbb31027b188c1e05a90b4700ce7b8e","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":377,"license_type":"no_license","max_line_length":35,"num_lines":15,"path":"/알고리즘/온라인저지/2022/07/0726/카약.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"R, C = map(int, input().split())\nresult = [0] * 9\narr = [input() for _ in range(R)]\nrank = 1\nfor c in range(C-2, 0, -1):\n goal = False\n for r in range(R):\n if arr[r][c] != '.':\n tmp = int(arr[r][c])-1\n if not result[tmp]:\n result[tmp] += rank\n goal = True\n if goal:\n rank += 1\nfor r in result: print(r)"},{"alpha_fraction":0.4096728265285492,"alphanum_fraction":0.4267425239086151,"avg_line_length":31.720930099487305,"blob_id":"eff56f39e6216551a91040ec11b88dbc94b7e175","content_id":"99b9cf72495fae81c4f766c8c247b5a1ab52497a","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1782,"license_type":"no_license","max_line_length":62,"num_lines":43,"path":"/알고리즘/온라인저지/2022/05/0501/사탕 게임.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\nN = int(sys.stdin.readline())\narr = [list(map(str, input())) for _ in range(N)]\nresult = 0 # 결과 최대값\n\ndef check(arr): # 현재 배열에서 최대값을 확인함\n cnt = 0 # 배열에서 확인할 최대값 초기화\n for i in range(N):\n row = 1 # 행, 가로\n col = 1 # 열, 세로\n # 최대길이를 파악하는 방향은 한 쪽 방향이다\n # 하지만 배열의 모든 좌표에 대해서 진행하므로 문제없음!\n for j in range(N-1): \n if arr[i][j] == arr[i][j+1]: # 연속할 경우\n row += 1 # 길이++\n else: # 연속하지 않을 경우 다시 1부터\n cnt = max(cnt, row) # 갱신 한 번 해주고\n row = 1\n \n if arr[j][i] == arr[j+1][i]: # 연속할 경우\n col += 1 # 길이++\n else: # 연속하지 않을 경우 다시 1부터\n cnt = max(cnt, col) # 갱신 한 번 해주고\n col = 1\n cnt = max(cnt, row, col) # 기존cnt, 행, 열의 각각 값들 중 최대값 갱신\n return cnt\n\nfor i in range(N):\n for j in range(N-1):\n # 위치를 바꿔서 같으면 옮길 필요가 없음\n # 가로 옮겨보고\n if arr[i][j] != arr[i][j+1]:\n arr[i][j], arr[i][j+1] = arr[i][j+1], arr[i][j]\n result = max(result, check(arr)) # 최대값 갱신\n arr[i][j], arr[i][j+1] = arr[i][j+1], arr[i][j]\n # 세로 옮겨보고\n if arr[j][i] != arr[j+1][i]:\n arr[j][i], arr[j+1][i] = arr[j+1][i], arr[j][i]\n result = max(result, check(arr)) # 최대값 갱신\n arr[j][i], arr[j+1][i] = arr[j+1][i], arr[j][i]\n \nprint(result) # 최대값 출력"},{"alpha_fraction":0.41886791586875916,"alphanum_fraction":0.4226415157318115,"avg_line_length":16.733333587646484,"blob_id":"13d4e056522da7a1ab73c6acbb5bb962584bb156","content_id":"a24058580efd4ebe8cfa97031cf4552245cf5044","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":265,"license_type":"no_license","max_line_length":33,"num_lines":15,"path":"/알고리즘/온라인저지/2022/10/1024/1.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\n\nwhile True:\n try:\n N = int(input().rstrip())\n num = ''\n while True:\n num += '1'\n if not int(num)%N:\n print(len(num))\n break\n except:\n break"},{"alpha_fraction":0.6846153736114502,"alphanum_fraction":0.6846153736114502,"avg_line_length":20.83333396911621,"blob_id":"61fdbf44f745f827825cec12a425775c956e1fb1","content_id":"1692136e8c7d63df93d433c17a60cf8696c13433","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":130,"license_type":"no_license","max_line_length":31,"num_lines":6,"path":"/알고리즘/온라인저지/2021/08/0814/숫자의 합.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = int(input())\nstr_numbers = input()\nnumbers = []\nfor number in str_numbers:\n numbers.append(int(number))\nprint(sum(numbers))"},{"alpha_fraction":0.4690265357494354,"alphanum_fraction":0.5132743120193481,"avg_line_length":17.91666603088379,"blob_id":"a7774dbeb12de0cfd5f0d62c89b9e8f1af0caaea","content_id":"1fc940e0e8e0a452e53152b2f0d569dc9cb3de6a","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":226,"license_type":"no_license","max_line_length":47,"num_lines":12,"path":"/알고리즘/온라인저지/2022/06/0627/가장 많은 글자.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\ninput = sys.stdin.read\n\nS = input().replace('\\n', '').replace(' ', '')\nA = [0] * 26\nfor s in S:\n A[ord(s)-97] += 1\nresult = ''\nfor i in range(26):\n if A[i] == max(A):\n result += chr(i+97)\nprint(result)"},{"alpha_fraction":0.44999998807907104,"alphanum_fraction":0.5,"avg_line_length":19.14285659790039,"blob_id":"2b46e39cc66ae1e35dcac213f6bd4b7fd67fc808","content_id":"83160b63ed88087627e24e4076fe7dcb2c6ba1fc","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":140,"license_type":"no_license","max_line_length":33,"num_lines":7,"path":"/알고리즘/온라인저지/2022/11/1128/Fan Death.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = int(input())\narr = set()\nfor n in range(1, int(N**0.5)+1):\n if not N%n:\n arr.add(n)\n arr.add(N//n)\nprint(sum(arr)*5-24)"},{"alpha_fraction":0.35854342579841614,"alphanum_fraction":0.39355742931365967,"avg_line_length":27.600000381469727,"blob_id":"3b1968678fe2e4a856e62524966e1638eb5f8d4a","content_id":"3dabdc7f6d8b5db1bae7cc5f2170f0863cb442cc","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":722,"license_type":"no_license","max_line_length":57,"num_lines":25,"path":"/알고리즘/온라인저지/2022/09/0913/겉넓이 구하기.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"dy, dx = [-1, 1, 0, 0], [0, 0, -1, 1]\nN, M = map(int, input().split())\narr = [list(map(int, input().split())) for _ in range(N)]\nzero = 0\nresult = 0\nfor i in range(N):\n for j in range(M):\n if arr[i][j] == 0: \n zero += 1\n continue\n now = arr[i][j]\n while now > 0:\n face = 4 # 도형의 면\n if now == arr[i][j]: face += 1\n y, x = i, j\n for k in range(4):\n ny, nx = y+dy[k], x+dx[k]\n if 0<=ny<N and 0<=nx<M:\n if arr[ny][nx] >= now:\n face -= 1\n result += face\n now -= 1 \nprint(result + N*M - zero)\n\n# https://www.acmicpc.net/problem/16931"},{"alpha_fraction":0.3983488082885742,"alphanum_fraction":0.4241486191749573,"avg_line_length":23.871795654296875,"blob_id":"0f7533770f36470f311fd00597c8e4f0d14b5d4e","content_id":"f1bb2b8be5d7b200bf8e1e5c53cc1bf2d7d1b042","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1085,"license_type":"no_license","max_line_length":63,"num_lines":39,"path":"/알고리즘/온라인저지/2023/03/0326/부등호.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"K = int(input())\nsign = input().split()\nvisited = [0]*10 # 0~9\nmaxx, minn = \"\", \"\"\n\ndef check(a, b, K):\n # 1<2 : True\n # '1'<'2' : True\n if K == '<':\n return a<b # T or F\n if K == '>':\n return a>b # T or F\n\ndef recur(idx, num):\n global maxx, minn\n\n if idx == K+1:\n if not minn: # 가장 먼저 부등호를 완성한 숫자가 최소값\n minn = num\n else: # 최소값을 찾았을 경우, 이후 나오는 숫자들로 최대값 갱신\n maxx = num\n return # 아래 for문 스킵\n \n for i in range(10):# 0부터 9까지 \n if not visited[i]:\n # 디버깅\n # if idx != 0:\n # print(*list(num))\n # print('', *sign[:len(num)-1])\n # print(num[-1], sign[idx-1], i)\n # print()\n if idx == 0 or check(num[-1], str(i), sign[idx-1]):\n visited[i] = 1 # visited 찍고\n recur(idx+1, num+str(i)) # 재귀\n visited[i] = 0 # visited 풀고\n\nrecur(0, \"\")\nprint(maxx)\nprint(minn)"},{"alpha_fraction":0.5955334901809692,"alphanum_fraction":0.6054590344429016,"avg_line_length":24.25,"blob_id":"68a6e018e663eb982d1eabf625c83c6169e6c248","content_id":"e0cb7ed285af67c14e5d46d3fdec392e1251b184","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":403,"license_type":"no_license","max_line_length":51,"num_lines":16,"path":"/알고리즘/온라인저지/2022/10/1012/결혼식.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\n\nN, M = int(input().rstrip()), int(input().rstrip())\nresult = set()\nfriends = [[] for _ in range(N+1)]\nfor m in range(M):\n a, b = map(int, input().rstrip().split())\n friends[a].append(b)\n friends[b].append(a)\nfor friend in friends[1]:\n if friend != 1: result.add(friend)\n for f in friends[friend]:\n if f != 1: result.add(f)\nprint(len(result))"},{"alpha_fraction":0.5416666865348816,"alphanum_fraction":0.5476190447807312,"avg_line_length":23.14285659790039,"blob_id":"6efab427f96bb5b28fc2b3725472540debacbc24","content_id":"68db41f4fd197a5828bbaa97b184754efc3b0e81","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":168,"license_type":"no_license","max_line_length":35,"num_lines":7,"path":"/알고리즘/온라인저지/2023/02/0213/Hard choice.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"A, B, C = map(int, input().split())\nD, E, F = map(int, input().split())\nresult = 0\nif A < D: result += D-A\nif B < E: result += E-B\nif C < F: result += F-C\nprint(result)"},{"alpha_fraction":0.44144144654273987,"alphanum_fraction":0.477477490901947,"avg_line_length":21.299999237060547,"blob_id":"f5aab2e47674738ce8a2b4f19b23a49541cb49fe","content_id":"527f9082c4d4ae09ca5bad082fde6232ae9f2356","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":222,"license_type":"no_license","max_line_length":43,"num_lines":10,"path":"/알고리즘/온라인저지/2022/07/0727/공 포장하기.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"B = list(map(int, input().split())) # balls\nresult = tmp = min(B)\nfor i in range(3):\n B[i] -= tmp\n if B[i]:\n result += B[i]//3\n B[i] = B[i]%3\nL = [0, 1, 1, 2, 2] # left\nresult += L[sum(B)]\nprint(result)"},{"alpha_fraction":0.4736842215061188,"alphanum_fraction":0.4912280738353729,"avg_line_length":11.052631378173828,"blob_id":"e931bd5324ad62edf679af734eee4071fd8f5a63","content_id":"a93b9af30875fe75e014aa075a63b4894967bca0","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":228,"license_type":"no_license","max_line_length":19,"num_lines":19,"path":"/알고리즘/온라인저지/2021/12/1216/개표.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"V = int(input())\n\nvotes = input()\n\navote = 0\nbvote = 0\n\nfor v in votes:\n if v == 'A':\n avote += 1\n else:\n bvote += 1\n\nif avote > bvote:\n print('A')\nelif bvote > avote:\n print('B')\nelse:\n print('Tie')"},{"alpha_fraction":0.4975288212299347,"alphanum_fraction":0.51729816198349,"avg_line_length":19.965517044067383,"blob_id":"2f8509ba839ca9c2bee8defb38e9a574aaa5e282","content_id":"b3299775651bb70fc39fbb1ff50ae1470aa3d6e6","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":607,"license_type":"no_license","max_line_length":42,"num_lines":29,"path":"/알고리즘/온라인저지/2022/09/0918/누울 자리를 찾아라.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\n\ndef lay_check(arr):\n cnt = 0\n for i in range(N):\n size = 0\n for j in range(N):\n if arr[i][j] == '.': size += 1\n else:\n if size>=2: cnt += 1 \n size = 0\n if size>=2: cnt += 1\n result.append(cnt)\n\nN = int(input().rstrip())\narr = [input().rstrip() for _ in range(N)]\nrotated_arr = []\nresult = []\nlay_check(arr)\nfor j in range(N):\n tmp = ''\n for i in range(N):tmp += arr[i][j]\n rotated_arr.append(tmp)\nlay_check(rotated_arr)\nprint(*result)\n\n# https://www.acmicpc.net/problem/1652"},{"alpha_fraction":0.3913043439388275,"alphanum_fraction":0.43478259444236755,"avg_line_length":22.5,"blob_id":"c918e74bf5070db4fa9b5749a001e13aea856f58","content_id":"b37021c44aa5d293946be4bf1ac24cb1d9edc18e","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":46,"license_type":"no_license","max_line_length":29,"num_lines":2,"path":"/알고리즘/온라인저지/2023/06/0601/Робинзон Крузо.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = int(input())\nprint('V'*(N//5) + 'I'*(N%5))"},{"alpha_fraction":0.45483359694480896,"alphanum_fraction":0.49286845326423645,"avg_line_length":14.023809432983398,"blob_id":"de6e50f47d4beb06b171f8efb430021b74c431a9","content_id":"16102c2cb104c07a67a5e02beb8f56200af909c0","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":755,"license_type":"no_license","max_line_length":34,"num_lines":42,"path":"/알고리즘/온라인저지/2022/01/0116/달팽이.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"# 상우하좌\n\ndy = (-1, 0, 1, 0)\ndx = (0, 1, 0, -1)\n\n\"\"\"\nN이 홀수일때 짝수일때 각각 스타트포인트 잡아서\n델타 이동으로 배열을 채우면서\nK의 좌표를 찾아서 저장 후\n배열 다 채우고 배열 출력\nK의 좌표 출력\n\"\"\"\n\nN = int(input())\nK = int(input())\n\nstart_x = start_y = N//2\n\narr = [[0] * N for _ in range(N)]\n\narr[start_y][start_x] = 1\n\ndir = 0\na = b = 0\n\nfor i in range(2, N**2 + 1):\n start_x = start_x + dx[dir]\n start_y = start_y + dy[dir]\n\n arr[start_y][start_x] = i\n if i == K:\n a = start_y\n b = start_x\n\n tp_x = start_x + dx[(dir+1)%4]\n tp_y = start_y + dy[(dir+1)%4]\n if not arr[tp_y][tp_x]:\n dir = (dir+1)%4\n\nfor ar in arr:\n print(*ar)\nprint(a+1, b+1) "},{"alpha_fraction":0.5961538553237915,"alphanum_fraction":0.6346153616905212,"avg_line_length":38.25,"blob_id":"63ecef5e152618b9d7235593cf70011bb53e205e","content_id":"8a3110d3ba02a71c216274ca12c34588e9630ed3","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":156,"license_type":"no_license","max_line_length":42,"num_lines":4,"path":"/알고리즘/온라인저지/2022/08/0822/Which Alien.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N, M = int(input()), int(input())\nif N>=3 and M<=4: print('TroyMartian')\nif N<=6 and M>=2: print('VladSaturnian')\nif N<=2 and M<=3: print('GraemeMercurian')"},{"alpha_fraction":0.37226277589797974,"alphanum_fraction":0.43795621395111084,"avg_line_length":9.615385055541992,"blob_id":"3aa8fc59e05056b739e44176f099e12bea154b3b","content_id":"f57e1d95598c7fe21e78206aabeffbc5636e0f30","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":137,"license_type":"no_license","max_line_length":32,"num_lines":13,"path":"/알고리즘/온라인저지/2021/12/1213/오븐 시계.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"A, B = map(int, input().split())\nC = int(input())\n\nB += C\n\nwhile B >= 60:\n A += 1\n B -= 60\n\nwhile A >= 24:\n A -= 24\n\nprint(A, B)"},{"alpha_fraction":0.43923240900039673,"alphanum_fraction":0.4648187756538391,"avg_line_length":25.11111068725586,"blob_id":"0444435160a7b188ae9f1669ae6ea59875494cde","content_id":"d97f7129a9f8d908c353630127d807ec40727d31","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":469,"license_type":"no_license","max_line_length":39,"num_lines":18,"path":"/알고리즘/온라인저지/2022/06/0629/역사.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N, M = map(int, input().split())\narr = [[0]*N for _ in range(N)]\nfor m in range(M):\n a, b = map(int, input().split())\n arr[a-1][b-1] = 1\nfor k in range(N):\n for a in range(N):\n for b in range(N):\n if arr[a][k] and arr[k][b]:\n arr[a][b] = 1\nfor s in range(int(input())):\n a, b = map(int, input().split()) \n result = 0\n if arr[a-1][b-1]:\n result = -1\n elif arr[b-1][a-1]:\n result = 1\n print(result)"},{"alpha_fraction":0.48275861144065857,"alphanum_fraction":0.517241358757019,"avg_line_length":29,"blob_id":"9a5efa2adf415e3529731e08057e9b907438940e","content_id":"58b612214433657cd93f0c755b081f6b72e4c8d1","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":29,"license_type":"no_license","max_line_length":29,"num_lines":1,"path":"/알고리즘/온라인저지/2022/03/0303/알고리즘 수업 - 알고리즘의 수행 시간 2.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"print(input(), '\\n1', sep='')"},{"alpha_fraction":0.3238866329193115,"alphanum_fraction":0.4048582911491394,"avg_line_length":19.66666603088379,"blob_id":"49fb93bcdf813804e9c7e3a59962d99f53b3352e","content_id":"49d52541f15d698e1b1747ad7e0a21556e901b8a","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":247,"license_type":"no_license","max_line_length":45,"num_lines":12,"path":"/알고리즘/온라인저지/2022/06/0608/날짜 계산.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"E, S, M = map(int, input().split())\ne, s, m = 1, 1, 1\nresult = 1\nwhile (E, S, M) != (e, s, m):\n e, s, m, result = e+1, s+1, m+1, result+1\n if e > 15:\n e -= 15\n if s > 28:\n s -= 28\n if m > 19:\n m -= 19\nprint(result)"},{"alpha_fraction":0.4895833432674408,"alphanum_fraction":0.5104166865348816,"avg_line_length":18.399999618530273,"blob_id":"b8c6cf6f4868450d5e6fc7163152b793bcb29ab5","content_id":"10ada1d6d7f292fade523ca3f2e22409ba86ecce","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":96,"license_type":"no_license","max_line_length":29,"num_lines":5,"path":"/알고리즘/온라인저지/2023/04/0404/골뱅이 찍기 - ㄴ.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = int(input())\nA = '@'*N\nB = '@'*N*5\nfor _ in range(N*4): print(A)\nfor _ in range(N): print(B)"},{"alpha_fraction":0.4689265489578247,"alphanum_fraction":0.5819209218025208,"avg_line_length":18.77777862548828,"blob_id":"90b991c4aaec2c8237d80882a5e922cc5b7ad393","content_id":"0d79f3edf4f4b0339ebc88136a43287911e2ec3b","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":177,"license_type":"no_license","max_line_length":42,"num_lines":9,"path":"/알고리즘/온라인저지/2022/09/0924/피보나치 수 7.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\n\nN = int(input().rstrip())\ndp = [0, 1] + [0]*int(1e7)\nfor i in range(2, int(1e7)):\n dp[i] = (dp[i-1] + dp[i-2])%1000000007\nprint(dp[N])"},{"alpha_fraction":0.5,"alphanum_fraction":0.550000011920929,"avg_line_length":40,"blob_id":"25320a376f968d5665ab580f85c95e7cb634f43f","content_id":"fdf095285bc58fe316824fe78fc545d918c3d9ed","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":40,"license_type":"no_license","max_line_length":40,"num_lines":1,"path":"/알고리즘/온라인저지/2023/05/0525/연세여 사랑한다.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"print(abs(ord('I') - ord(input())) + 84)"},{"alpha_fraction":0.45145630836486816,"alphanum_fraction":0.4805825352668762,"avg_line_length":19.700000762939453,"blob_id":"3e8b8ac326a8e9b9496253ea6028961509c3f71f","content_id":"ae48678ee8951689ee285d6d3b1893bc1f686660","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":206,"license_type":"no_license","max_line_length":39,"num_lines":10,"path":"/알고리즘/온라인저지/2023/03/0307/Telemarketer or not.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"A = int(input())\nB = int(input())\nC = int(input())\nD = int(input())\nresult = 0\nif A == 8 or A == 9:\n if D == 8 or D == 9:\n if C == B:\n result = 1\nprint('ignore' if result else 'answer')"},{"alpha_fraction":0.5178267955780029,"alphanum_fraction":0.5432937145233154,"avg_line_length":25.81818199157715,"blob_id":"9a925dfadfcceee1232c6bd95c91e977cb6debb5","content_id":"431dab2af24902a5bb5522932a290f45a46e11fd","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":589,"license_type":"no_license","max_line_length":66,"num_lines":22,"path":"/알고리즘/온라인저지/2022/10/1002/점프왕 쩰리 (Small).py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\nfrom collections import deque\n\ninput = sys.stdin.readline\ndy, dx = [1, 0], [0, 1] # down, right\n\nN = int(input().rstrip())\narr = [list(map(int, input().rstrip().split())) for _ in range(N)]\nvisited = [[0]*N for _ in range(N)]\nQ = deque()\nQ.append((0, 0))\nvisited[0][0] = 1\nwhile Q:\n y, x = Q.popleft()\n if y == x == N-1: print('HaruHaru'); break\n jump = arr[y][x]\n for i in range(2):\n ny, nx = y+dy[i]*jump, x+dx[i]*jump\n if 0<=ny<N and 0<=nx<N and not visited[ny][nx]:\n Q.append((ny, nx))\n visited[ny][nx] = 1\nelse: print('Hing')"},{"alpha_fraction":0.5714285969734192,"alphanum_fraction":0.5844155550003052,"avg_line_length":18.375,"blob_id":"59f2a147b4f30cd611c1aed4b4f5bd3c2b19dc26","content_id":"075e3d74778d18a082f4728e126641b58522499c","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":154,"license_type":"no_license","max_line_length":46,"num_lines":8,"path":"/알고리즘/온라인저지/2023/06/0614/Terms of Office.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"X = int(input())\nY = int(input())\nresult = []\nwhile X<=Y:\n result.append(X)\n X += 60\nfor r in result:\n print(f'All positions change in year {r}')"},{"alpha_fraction":0.39401495456695557,"alphanum_fraction":0.39650872349739075,"avg_line_length":21.33333396911621,"blob_id":"b8342aac27029be3feb201ce23223cdb1f5b2497","content_id":"49da4f87e2b5b62de30dfe68753a8e419bdb7aa5","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":401,"license_type":"no_license","max_line_length":27,"num_lines":18,"path":"/알고리즘/온라인저지/2022/06/0603/계산기 프로그램.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"result = 0\nwhile True:\n order = input()\n if order == '=':\n print(result)\n break\n elif order in '+-*/':\n num = int(input())\n if order == '+':\n result += num\n elif order == '-':\n result -= num\n elif order == '*':\n result *= num\n elif order == '/':\n result //= num\n else:\n result = int(order)"},{"alpha_fraction":0.4428044259548187,"alphanum_fraction":0.468634694814682,"avg_line_length":13.315789222717285,"blob_id":"f1c7939216383a759564141cee45f9acd79ec359","content_id":"324bc01165c18301cd23e57547b71e1ef02deeb6","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":271,"license_type":"no_license","max_line_length":25,"num_lines":19,"path":"/알고리즘/온라인저지/2022/02/0202/홀수.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"summ = 0\nminn = 100\nis_odd = False\n\nfor _ in range(7):\n num = int(input())\n\n if num%2:\n if num < minn:\n minn = num\n summ += num\n if not is_odd:\n is_odd = True\n\nif is_odd:\n print(summ)\n print(minn)\nelse:\n print(-1)"},{"alpha_fraction":0.4083601236343384,"alphanum_fraction":0.5112540125846863,"avg_line_length":14.600000381469727,"blob_id":"922aab98faeb3f187637a572273b34bfb2c699c5","content_id":"4233d6e3a376f1e84c11e9a7ba29844a1ac9c91a","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":351,"license_type":"no_license","max_line_length":60,"num_lines":20,"path":"/알고리즘/온라인저지/2022/01/0131/2007년.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"\"\"\"\n1월 1일은 월요일\nx월y일이 1년중 몇번째 날인지 구해서\nmod 7\n\"\"\"\n\nx, y = map(int, input().split())\n\nday = y-1\n\nif x > 1:\n month = [31, 28, 31, 30, 31, 30, 31, 31, 30, 31, 30, 31]\n for i in range(x-1):\n day += month[i]\n\nweek = ['MON', 'TUE', 'WED', 'THU', 'FRI', 'SAT', 'SUN']\n\nweekday = day % 7\n\nprint(week[weekday])"},{"alpha_fraction":0.3866666555404663,"alphanum_fraction":0.41777777671813965,"avg_line_length":21.600000381469727,"blob_id":"1e4e93491a0ad54e41f6bef17b123ec3824b2adf","content_id":"19fb859599c4ff8adb51f9abfaa7902a8f5cbf71","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":225,"license_type":"no_license","max_line_length":59,"num_lines":10,"path":"/알고리즘/온라인저지/2022/12/1214/전북대학교.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = int(input())\nif not N%2:\n print('I LOVE CBNU')\nelse:\n print('*'*N)\n space = N//2\n print(' '*space + '*')\n for _ in range(N//2):\n space -= 1\n print(' '*space + '*'+' '*(((N//2)-space)*2-1)+'*')"},{"alpha_fraction":0.4701492488384247,"alphanum_fraction":0.503731369972229,"avg_line_length":25.899999618530273,"blob_id":"253cdc08615cd0b512edb5495c66af2d3dea533d","content_id":"77e65dfe341c120ae8b96a7b4532a60b542bb290","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":268,"license_type":"no_license","max_line_length":53,"num_lines":10,"path":"/알고리즘/온라인저지/2022/06/0629/정수 삼각형.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = int(input())\narr = []\nfor n in range(N):\n tmp = [0] + list(map(int, input().split())) + [0]\n arr.append(tmp)\nfor i in range(1, len(arr)):\n for j in range(1, len(arr[i])-1):\n tmp = arr[i-1][j-1:j+1]\n arr[i][j] += max(tmp)\nprint(max(arr[N-1]))"},{"alpha_fraction":0.5648535490036011,"alphanum_fraction":0.5648535490036011,"avg_line_length":29,"blob_id":"f62db0002cfb38af8f6b306601e4e0571bf435e8","content_id":"1624de62176ce8987f705c340191854b2512eda3","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":239,"license_type":"no_license","max_line_length":49,"num_lines":8,"path":"/알고리즘/온라인저지/2023/05/0511/Gnome Sequencing.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"print('Gnomes:')\nfor i in range(int(input())):\n tmp = list(map(int, input().split()))\n A, B = sorted(tmp), sorted(tmp, reverse=True)\n result = 'Unordered'\n if (tmp == A or tmp == B):\n result = 'Ordered'\n print(result)"},{"alpha_fraction":0.42489269375801086,"alphanum_fraction":0.4849785268306732,"avg_line_length":13.5625,"blob_id":"79fb8f5445a103d423c659d163b5c05ea05a5ed4","content_id":"65a7d37d19f3761289a19ddea3f19d2b678e45b7","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":233,"license_type":"no_license","max_line_length":22,"num_lines":16,"path":"/알고리즘/온라인저지/2022/02/0212/대표값.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"dp = [0] * (101)\nsumm = 0\nmode = 0\nmaxx = 0\n\nfor i in range(10):\n num = int(input())\n summ += num\n tmp = num//10\n dp[tmp] += 1\n if dp[tmp] > maxx:\n maxx = dp[tmp]\n mode = num\n\nprint(summ//10)\nprint(mode)\n"},{"alpha_fraction":0.47252747416496277,"alphanum_fraction":0.593406617641449,"avg_line_length":17.266666412353516,"blob_id":"6794d53ef724942b96a757a3175d018697dbc51c","content_id":"ed6acb1c3707dbc92a48a87e54463165b8256a7b","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":395,"license_type":"no_license","max_line_length":49,"num_lines":15,"path":"/알고리즘/SWEA/LEARN/Course/1. Programming Beginner/파이썬 프로그래밍 기초(2)/27차시 3. 자료구조 – 셋, 딕셔너리 - 연습문제 2.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"phone = {\n '홍길동': '010-1111-1111',\n '이순신': '010-1111-2222',\n '강감찬': '010-1111-3333',\n}\n\nprint('아래 학생들의 전화번호를 조회할 수 있습니다.')\nfor name in phone:\n print(name)\n\nprint('전화번호를 조회하고자 하는 학생의 이름을 입력하십시오.')\n\ntmp = input()\n\nprint('{}의 전화번호는 {}입니다.'.format(tmp, phone[tmp]))"},{"alpha_fraction":0.4720279574394226,"alphanum_fraction":0.5262237787246704,"avg_line_length":18.724138259887695,"blob_id":"0354f11f81581962fb45da14e33130478adaf459","content_id":"27d3003d4bdbe29d2f8fb37d261bd9d0e1e2e7d9","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":572,"license_type":"no_license","max_line_length":49,"num_lines":29,"path":"/알고리즘/온라인저지/2021/12/1216/주사위 게임.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = int(input())\n\nb = []\n\nfor n in range(N):\n\n a = list(map(int, input().split()))\n\n dice_num_count = [0 for _ in range(6)]\n\n for i in a:\n dice_num_count[i-1] += 1\n\n same_or_max = 0\n result = 0\n\n if 3 in dice_num_count:\n same_or_max = dice_num_count.index(3) + 1\n result = 10000 + same_or_max * 1000\n elif 2 in dice_num_count:\n same_or_max = dice_num_count.index(2) + 1\n result = 1000 + same_or_max * 100\n else:\n same_or_max = max(a)\n result = same_or_max * 100\n\n b.append(result)\n\nprint(max(b))\n"},{"alpha_fraction":0.5839999914169312,"alphanum_fraction":0.5839999914169312,"avg_line_length":30.5,"blob_id":"16acc665d09f482b029015338164b1b4238dcdf9","content_id":"0200e9845c3719ce8ca2a36a90dac62e9991f9ae","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":125,"license_type":"no_license","max_line_length":40,"num_lines":4,"path":"/알고리즘/온라인저지/2022/05/0513/헬멧과 조끼.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N, M = map(int, input().split())\nA = max(list(map(int, input().split())))\nB = max(list(map(int, input().split())))\nprint(A+B)"},{"alpha_fraction":0.48040884733200073,"alphanum_fraction":0.5332197546958923,"avg_line_length":24.565217971801758,"blob_id":"a7b1ad3bd5f6f3aace344e928f3a49bc1f52287c","content_id":"4b542233ffd8b4d91ce9879265dba67ece455330","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":587,"license_type":"no_license","max_line_length":55,"num_lines":23,"path":"/알고리즘/온라인저지/2022/10/1006/데스 나이트.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\nfrom collections import deque\n\ninput = sys.stdin.readline\ndy = [-2, -2, 0, 0, 2, 2]\ndx = [-1, 1, -2, 2, -1, 1]\n\nN = int(input().rstrip())\nr1, c1, r2, c2 = map(int, input().rstrip().split())\nvisited = [[0]*N for _ in range(N)]\nQ = deque()\nQ.append((r1, c1, 0))\nvisited[r1][c1] = 1\nresult = -1\nwhile Q:\n y, x, move = Q.popleft()\n if y == r2 and x == c2: result = move; break\n for i in range(6):\n ny, nx = y+dy[i], x+dx[i]\n if 0<=ny<N and 0<=nx<N and not visited[ny][nx]:\n Q.append((ny, nx, move+1))\n visited[ny][nx] = 1\nprint(result)"},{"alpha_fraction":0.4341636896133423,"alphanum_fraction":0.4590747356414795,"avg_line_length":11.260869979858398,"blob_id":"d4906c3d32a50e78c72d07b6d4757dbb4504e31c","content_id":"ebfb47b421a99388f94e3edbc9dfe08b03977fe9","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":281,"license_type":"no_license","max_line_length":26,"num_lines":23,"path":"/알고리즘/온라인저지/2022/02/0205/방학 숙제.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"L = int(input())\nA = int(input())\nB = int(input())\nC = int(input())\nD = int(input())\n\nmaxx = 0\n\nA_by_C = 0\nif A%C == 0:\n A_by_C = A//C\nelse:\n A_by_C = A//C + 1\n\nB_by_D = 0\nif B%D == 0:\n B_by_D = B//D\nelse:\n B_by_D = B//D + 1\n\nmaxx = max(A_by_C, B_by_D)\n\nprint(L - maxx)"},{"alpha_fraction":0.5180723071098328,"alphanum_fraction":0.5397590398788452,"avg_line_length":19.799999237060547,"blob_id":"3a6f1801bf11ea0f85e7d4176457e043d2a30130","content_id":"5f35053c1cb3fd11e653a6f94f48fff514f29dcf","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":415,"license_type":"no_license","max_line_length":42,"num_lines":20,"path":"/알고리즘/온라인저지/2022/11/1124/비밀 이메일.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\n\nmessage = input().rstrip()\nlength = len(message)\ndivs = []\nfor i in range(1, int((length+1)**0.5)+1):\n if not length%i:\n divs.append((i, length//i))\nR, C = divs[-1]\narr = [[0]*C for _ in range(R)]\nk = 0\nfor j in range(C):\n for i in range(R):\n arr[i][j] = message[k]\n k += 1\nfor i in range(R):\n for j in range(C):\n print(arr[i][j], end='')"},{"alpha_fraction":0.40611353516578674,"alphanum_fraction":0.4192139804363251,"avg_line_length":27.75,"blob_id":"46b0ea7e5dea5af9c462951e28037163c08e78b2","content_id":"b64acdfb4d99a1a4ab99823f4a72e7027b2dbb45","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":229,"license_type":"no_license","max_line_length":51,"num_lines":8,"path":"/알고리즘/온라인저지/2023/03/0319/Viva la Diferencia.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"while True:\n A, B, C, D = map(int, input().split())\n if A == B == C == D == 0: break\n result = 0\n while not (A == B == C == D):\n A, B, C, D = map(abs, (A-B, B-C, C-D, D-A))\n result += 1\n print(result)"},{"alpha_fraction":0.38591548800468445,"alphanum_fraction":0.42323943972587585,"avg_line_length":40.79411697387695,"blob_id":"52abcdd05eb4a43523da52633f7ed4d691a9f081","content_id":"c9174e807f57df57b0599eb474c53b3c9c9a902a","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1832,"license_type":"no_license","max_line_length":89,"num_lines":34,"path":"/알고리즘/온라인저지/2022/09/0908/십자뒤집기.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"from itertools import combinations as comb\n\ncoordinate = [None, \n (0, 0), (0, 1), (0, 2),\n (1, 0), (1, 1), (1, 2),\n (2, 0), (2, 1), (2, 2),\n] # 3x3 사각형의 좌표들\ndy, dx = [0, -1, 1, 0, 0], [0, 0, 0, -1, 1] # 자기 자신 + 상하좌우\n\nP = int(input())\nfor p in range(P):\n answer = [list(input()) for _ in range(3)] # 정답 배열\n result = 0 # 최소 클릭 횟수\n for i in range(1, 10): # 누르는 횟수 1부터 9까지 브루트포스\n tmp = list(comb(range(1, 10), i)) # i번 누를 때 나올 수 있는 조합\n for t in tmp: # 클릭할 수 있는 조합들 중에서\n if result: break # 정답을 찾았다면 종료\n arr = [list('.'*3) for _ in range(3)] # 답안지\n for j in t: # 클릭할 수 있는 조합들에서\n coor = coordinate[j] # 클릭할 좌표\n y, x = coor[0], coor[1] # 좌표의 y, x\n for k in range(5): # 자기 자신과 상하좌우, 총 5지점의 색을 뒤집는다\n ny, nx = y+dy[k], x+dx[k] # 색을 뒤집을 좌표들\n if 0<=ny<3 and 0<=nx<3: # 새로 얻은 좌표들은 사각형 안에 있어야 한다 (3x3 사각형이니 망정이지;;)\n if arr[ny][nx] == '*': # * -> .\n arr[ny][nx] = '.'\n elif arr[ny][nx] == '.': # . -> *\n arr[ny][nx] = '*'\n flag = True # 구한 답안과 정답을 비교할 것\n for l in range(3):\n if arr[l] != answer[l]: # 답안과 정답이 다른 줄이 나오면 그 답안은 정답이 아님\n flag = False\n if flag: result = i # 답안의 모든 줄이 정답과 일치하면 해당 클릭 수를 결과로 저장\n print(result)"},{"alpha_fraction":0.4691357910633087,"alphanum_fraction":0.5020576119422913,"avg_line_length":33.57143020629883,"blob_id":"e44458d7fa8a4c1738fd8abaa98b90feb23228ce","content_id":"7fd03f61d54ca516e7a787c0e9b200a813552eee","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":243,"license_type":"no_license","max_line_length":52,"num_lines":7,"path":"/알고리즘/[템플릿]/에라토스테네스의 체/에라토스테네스의 체.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"def prime_list(size):\n sieve = [True]*(size+1)\n for i in range(2, int(size**0.5)+1):\n if sieve[i]:\n for j in range(i+i, size+1, i):\n sieve[j] = False\n return [i for i in range(2, size+1) if sieve[i]]\n\n"},{"alpha_fraction":0.6521739363670349,"alphanum_fraction":0.6645962595939636,"avg_line_length":21,"blob_id":"0c031accf3d3c6e39bc91b862adc603140989c13","content_id":"9f604bea7c74a63f660f966f7279e1d92f993c98","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":809,"license_type":"no_license","max_line_length":54,"num_lines":22,"path":"/알고리즘/온라인저지/2022/09/0911/연속합.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = int(input())\nnums = list(map(int, input().split()))\nresult = [nums[0]]\nfor i in range(len(nums)-1):\n result.append(max(result[i]+nums[i+1], nums[i+1]))\nprint(max(result))\n\n\"\"\"\n한 시간을 머리를 박았는데\n접근도 못하고\n답지를 봤더니 이렇게 허무할 줄은 몰랐다\n실패요인은\nDP라는 태그를 보고 그 계산값들을 저장하면서\n들고 간다는 것 까지는 이해하였지만\n어떻게 들고 가는지, 그 과정을 이해하지 못하였다\nresult[i] : min(여기까지 끌고온 연속합, i번째 값)\nresult[i]+nums[i+1] : 구해온 연속합에 다음 수를 더한 값\nnums[i+1] : 현재 값\nresult에는, 최대값이 될 수 있는\n구한 연속값들이 모두 들어있고\n그 중에 최대값을 max(result)를 통해 출력하는 문제였다\n\"\"\""},{"alpha_fraction":0.43529412150382996,"alphanum_fraction":0.4588235318660736,"avg_line_length":24.600000381469727,"blob_id":"6836023895af0b8ed822741f6e47bfcd2fbba9a5","content_id":"06d6f4eab9a644c2e2c7960d4188da1e1f821089","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":255,"license_type":"no_license","max_line_length":46,"num_lines":10,"path":"/알고리즘/온라인저지/2022/11/1130/팬그램.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"while True:\n S = input()\n if S == '*': break\n alphabet = [0]*26\n for s in S:\n if s == ' ': continue\n tmp = ord(s)-ord('a')\n if not alphabet[tmp]:\n alphabet[tmp] = 1\n print('Y' if sum(alphabet) == 26 else 'N')"},{"alpha_fraction":0.45945945382118225,"alphanum_fraction":0.5135135054588318,"avg_line_length":37,"blob_id":"bdeb59730db9e56be932d7b2172b19cf633ab808","content_id":"bc6f838a66be475816fcf39be4354abbbfc2027f","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":37,"license_type":"no_license","max_line_length":37,"num_lines":1,"path":"/알고리즘/온라인저지/2022/03/0303/알고리즘 수업 - 알고리즘의 수행 시간 3.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"print(int(input())**2, '\\n2', sep='')"},{"alpha_fraction":0.47445255517959595,"alphanum_fraction":0.5328466892242432,"avg_line_length":16.25,"blob_id":"6e7252763012fbec27dabf8250f9295df022dbea","content_id":"0e14d78425ec89f745a3548b14287661365b5102","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":137,"license_type":"no_license","max_line_length":34,"num_lines":8,"path":"/알고리즘/온라인저지/2022/02/0205/과제 안 내신 분.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"table = [False] * 30\n\nfor _ in range(28):\n table[int(input()) - 1] = True\n\nfor i in range(30):\n if not table[i]:\n print(i+1)"},{"alpha_fraction":0.5622775554656982,"alphanum_fraction":0.5836299061775208,"avg_line_length":30.33333396911621,"blob_id":"745c75bad8df0de66f3cbda545a86f8bc47ca668","content_id":"6e8a3ab642459928f90c7f561d8e4587166a75d1","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":427,"license_type":"no_license","max_line_length":45,"num_lines":9,"path":"/알고리즘/온라인저지/2021/07/0731/언제까지 더해야 할까.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"a = int(input())\nlast_num = 1 # 출력값, 초기값은 1\nsum_all = 0 # 1부터 전부 더한 값\nwhile sum_all < a: # 전부 더한 값이 입력값보다 작을 때\n sum_all += last_num # 1부터 하나씩 더한다\n if sum_all >= a: # 전부 더한 값이 입력값보다 크거나 같으면\n break # while문 종료\n last_num += 1 # 그렇지 않으면 출력값을 계속 더하고\nprint(last_num) # 출력"},{"alpha_fraction":0.5659340620040894,"alphanum_fraction":0.5879120826721191,"avg_line_length":17.299999237060547,"blob_id":"2efc53685c3ed08b1f3678f1d782519287602ee0","content_id":"9a8f13950ad3c6e88096fcb24d97ce383d45657b","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":182,"license_type":"no_license","max_line_length":33,"num_lines":10,"path":"/알고리즘/온라인저지/2022/10/1025/일반 화학 실험.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\n\nnow = float(input().rstrip())\nwhile True:\n D = float(input().rstrip())\n if D >= 999: break\n print('{:.2f}'.format(D-now))\n now = D"},{"alpha_fraction":0.5165125727653503,"alphanum_fraction":0.5640686750411987,"avg_line_length":26.071428298950195,"blob_id":"9cada81095d39a18099e37bc206f644d9c3ef7bb","content_id":"ed8d61ebda3f947fa9a950051f2d7f595ea6b84c","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1263,"license_type":"no_license","max_line_length":57,"num_lines":28,"path":"/알고리즘/온라인저지/2021/08/0808/A→B.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"\"\"\"\nA, B = 시작값, 결과값\n2를 곱하거나, 맨 뒤에 1을 넣거나\nA -> B로 가는 연산의 최솟값\nB의 1의자리가 1이면 직전 연산에서 1추가를 실행한것\n 1을 빼주고\nB의 1의자리가 1이 아니고 2의배수면 직전 연산에서 2 곱하기를 실행한것\n 2를 나눠주고\nB를 시작으로 A까지 가는 코드를 구성\n만들 수 없는 경우를 찾는법?\n\n\"\"\"\n\nimport sys # sys.stdin.readline()\nA, B = map(int, sys.stdin.readline().split()) # A, B 입력받고\ncount = 0 # 결과값 초기화\nwhile B != A: # A와 B가 같아질때까지 while문 반복\n if B%10 == 1: # B의 1의자리수가 1이면 직전 연산에서 맨 뒤에 1을 추가한 것\n B //= 10 # 10으로 나눈 몫을 반환하여 1을 제거\n count += 1 # 연산 카운트 +1\n else: # B의 1의자리수가 1이 아니면 직전연산에서 *2를 한 것\n B /= 2 # 2로 나눠주고\n count += 1 # 연산 카운트 +1\n if B < A: # 연산을 계속했는데 B가 A로 가지 못하고 A보다 작아지면\n # B에서 A를 만들 수 없으니\n count = -2 # 결과값에 1 더해질 경우를 포함해 카운트를 -2로 저장\n break # while문 종료\nprint(count + 1) # 출력"},{"alpha_fraction":0.6086956262588501,"alphanum_fraction":0.6304348111152649,"avg_line_length":46,"blob_id":"3f8f4d576c681084211daf1c804bbab36bf1e043","content_id":"ff1166a7601f1cf1961ee8c7985298a8072a6e72","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":46,"license_type":"no_license","max_line_length":46,"num_lines":1,"path":"/알고리즘/온라인저지/2022/10/1012/SciComLove.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"for _ in [0]*int(input()): print('SciComLove')"},{"alpha_fraction":0.5454545617103577,"alphanum_fraction":0.5757575631141663,"avg_line_length":21.33333396911621,"blob_id":"7b4e660a242fe7500a5022d395f2072085ebc240","content_id":"26972a19119955f21f60d8d6574d6da40bbd0a52","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":66,"license_type":"no_license","max_line_length":33,"num_lines":3,"path":"/알고리즘/온라인저지/2022/03/0303/알고리즘 수업 - 알고리즘의 수행 시간 5.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"result = int(input())**3\ndim = 3\nprint(result, f'\\n{dim}', sep='')"},{"alpha_fraction":0.54347825050354,"alphanum_fraction":0.5688405632972717,"avg_line_length":22.08333396911621,"blob_id":"092361e9ca22699e381dc79b5d1e6e0f9c75edb5","content_id":"19b84f2bbd1db18f132bd722f4b1b07111cd86b4","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":276,"license_type":"no_license","max_line_length":65,"num_lines":12,"path":"/알고리즘/온라인저지/2022/09/0927/단어 나누기.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\n\nword = input().rstrip()\nlength = len(word)\nchange = []\nfor i in range(1, length-1):\n for j in range(i+1, length):\n A, B, C = word[:i][::-1], word[i:j][::-1], word[j:][::-1]\n change.append(A+B+C)\nprint(sorted(change)[0])"},{"alpha_fraction":0.49787235260009766,"alphanum_fraction":0.5063830018043518,"avg_line_length":22.600000381469727,"blob_id":"a36d18925e9cecc6e41416d90b92752384c6d6aa","content_id":"526b93b1d765c134fd51d4fd1ad71ac122c62394","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":235,"license_type":"no_license","max_line_length":43,"num_lines":10,"path":"/알고리즘/온라인저지/2023/03/0305/스트릿 코딩 파이터.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"A, B, C = map(int, input().split())\nN = int(input())\nresult = []\nfor n in range(N):\n tmp = 0\n for i in range(3):\n a, b, c = map(int, input().split())\n tmp += a*A + b*B + c*C\n result.append(tmp)\nprint(max(result))"},{"alpha_fraction":0.6053169965744019,"alphanum_fraction":0.6237218976020813,"avg_line_length":29.625,"blob_id":"032a1c34126b5743e55adfa7604edb8ad2ad1155","content_id":"7663cd4bd0993df2e22bfe55b2d19dfb8125bca6","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":525,"license_type":"no_license","max_line_length":60,"num_lines":16,"path":"/알고리즘/[템플릿]/스택/에디터.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\n\nleft = list(input().rstrip())\nright = []\n# 커서의 이동을 좌우 스택간에 이동으로 구현\nfor _ in range(int(input().rstrip())):\n order = input().rstrip().split()\n if order[0] == 'L' and left: right.append(left.pop())\n elif order[0] == 'D' and right: left.append(right.pop())\n elif order[0] == 'B' and left: left.pop()\n elif order[0] == 'P': left.append(order[1])\nfor a in left+list(reversed(right)): print(a, end='')\n\n# https://www.acmicpc.net/problem/1406"},{"alpha_fraction":0.2628205120563507,"alphanum_fraction":0.5064102411270142,"avg_line_length":7.722222328186035,"blob_id":"c66221e74c9419d93995a27c3eb93187e07d4bc5","content_id":"2f1a3f40041c583117339146cf66f6b74172c645","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":156,"license_type":"no_license","max_line_length":62,"num_lines":18,"path":"/알고리즘/온라인저지/2022/04/0430/거북이.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"\"\"\"\n1 2 3 4\n4 1 3 2\n4 3\n1 2\n\n4 4 3 4\n3 4 4 4\n4 4\n3 4\n\n4 7 3 9\n3 4 7 9\n9 3 7 4\n\n\"\"\"\nA, B = map(int, sorted(list(map(int, input().split())))[:3:2])\nprint(A*B)"},{"alpha_fraction":0.4771573543548584,"alphanum_fraction":0.4771573543548584,"avg_line_length":18.600000381469727,"blob_id":"5dc97a961aa501a4c2fd9cd64dd1401654b29ee8","content_id":"c945c5520f1cfd88e75f5e850a7ccf1556224d68","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":197,"license_type":"no_license","max_line_length":44,"num_lines":10,"path":"/알고리즘/온라인저지/2022/02/0207/아.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"jh = input()\nhospital = input()\n\nfor i in range(max(len(jh), len(hospital))):\n if hospital[i] == 'h':\n print('go')\n break\n elif jh[i] == 'h':\n print('no')\n break\n\n"},{"alpha_fraction":0.48695650696754456,"alphanum_fraction":0.48695650696754456,"avg_line_length":15.571428298950195,"blob_id":"7658a99d40944ffbe34d9ec696607b7f17ce61f3","content_id":"c1dede77301ccf831ff37e2daa79b4bdd4128c70","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":115,"license_type":"no_license","max_line_length":36,"num_lines":7,"path":"/알고리즘/온라인저지/2022/06/0624/더하기 2.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"num = ''\nwhile True:\n try:\n num += input()\n except:\n break\nprint(sum(map(int, num.split(','))))"},{"alpha_fraction":0.41743120551109314,"alphanum_fraction":0.5458715558052063,"avg_line_length":30.285715103149414,"blob_id":"6d76577f86b6a99b82b744e98fa6538275668345","content_id":"1da8bb83990a2d96a684dccc896225612a0b5e87","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":218,"license_type":"no_license","max_line_length":47,"num_lines":7,"path":"/알고리즘/온라인저지/2022/05/0501/전투 드로이드 가격.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"menu = [350.34, 230.90, 190.55, 125.30, 180.90]\nfor t in range(int(input())):\n tmp = list(map(int, input().split()))\n result = 0\n for i in range(5):\n result += menu[i]*tmp[i]\n print(f'${result:.2f}')"},{"alpha_fraction":0.4779411852359772,"alphanum_fraction":0.5073529481887817,"avg_line_length":18.571428298950195,"blob_id":"366b0e24c897ee6333a087120c087d9f128a9706","content_id":"f9c8c725f26e6a75f0d111b67dba6205c20e32b3","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":136,"license_type":"no_license","max_line_length":27,"num_lines":7,"path":"/알고리즘/온라인저지/2022/12/1201/파인만.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"while True:\n N = int(input())\n if not N: break\n result = 0\n for i in range(1, N+1):\n result += i**2\n print(result)"},{"alpha_fraction":0.4680851101875305,"alphanum_fraction":0.4893617033958435,"avg_line_length":26,"blob_id":"88aae1c374b2a8299c3aedaa7a9dd15c35bdfd79","content_id":"cd3d9011527f102b81fe88ed16434b7aa5ddb8a6","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":188,"license_type":"no_license","max_line_length":43,"num_lines":7,"path":"/알고리즘/온라인저지/2022/09/0902/부호.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"for _ in range(3):\n N = int(input())\n tmp = [int(input()) for __ in range(N)]\n result = '0'\n if sum(tmp) > 0: result = '+'\n elif sum(tmp) < 0: result = '-'\n print(result)"},{"alpha_fraction":0.5044247508049011,"alphanum_fraction":0.5132743120193481,"avg_line_length":13.125,"blob_id":"8ec2dcf6eaf614389371b39640dbc70948822c1a","content_id":"79474395687b273dcf75c1b32592b13871a5c735","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":113,"license_type":"no_license","max_line_length":35,"num_lines":8,"path":"/알고리즘/온라인저지/2022/02/0207/캥거루 세마리.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"A, B, C = map(int, input().split())\n\nfurther = A\n\nif (B-A) < (C-B):\n further = C\n\nprint(abs(further - B) - 1)\n"},{"alpha_fraction":0.5304877758026123,"alphanum_fraction":0.5609756112098694,"avg_line_length":22.571428298950195,"blob_id":"c4bd9fa3164844d7772f84a2dcc3c5494cfc8726","content_id":"369f44dc5b3ede4670c2661be681fdb01edb78ea","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":164,"license_type":"no_license","max_line_length":34,"num_lines":7,"path":"/알고리즘/온라인저지/2023/02/0203/치킨댄스를 추는 곰곰이를 본 임스 2.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"result = 0\nfor _ in range(int(input())):\n gifticon = input().split('D-')\n left_day = int(gifticon[1])\n if left_day <= 90:\n result += 1\nprint(result)"},{"alpha_fraction":0.46489858627319336,"alphanum_fraction":0.4836193323135376,"avg_line_length":20.399999618530273,"blob_id":"0ef99bed4963ca1319ec162dd9300c8de7196203","content_id":"b0659c51ed07469826a2d5148dce5d7280db2c0f","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":665,"license_type":"no_license","max_line_length":36,"num_lines":30,"path":"/알고리즘/온라인저지/2022/12/1204/효율적인 해킹.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"from collections import deque\n\ndef bfs(i):\n Q = deque([i])\n cnt = 1 # i번 컴퓨터를 해킹하면서 bfs 시작\n visited = [0]*(N+1)\n visited[i] = 1\n while Q:\n i = Q.popleft()\n for nxt in arr[i]:\n if not visited[nxt]:\n visited[nxt] = 1\n Q.append(nxt)\n cnt += 1\n return cnt\n\nN, M = map(int, input().split())\narr = [[] for _ in range(N+1)]\nfor _ in range(M):\n a, b = map(int, input().split())\n arr[b].append(a)\n\nresult = [0]*(N+1)\nfor i in range(1, N+1):\n result[i] = bfs(i)\n\nmaxx = max(result)\nfor i in range(N+1):\n if result[i] == maxx:\n print(i, end=' ')"},{"alpha_fraction":0.40740740299224854,"alphanum_fraction":0.4273504316806793,"avg_line_length":18.55555534362793,"blob_id":"51d9052bffacada0481557ceb3c8a2f90d044d80","content_id":"e1bb38ba2468cd75cdaa8b7308bb5bb1ff62de76","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":351,"license_type":"no_license","max_line_length":43,"num_lines":18,"path":"/알고리즘/온라인저지/2023/03/0326/선물할인.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N, B, A = map(int, input().split())\nP = sorted(list(map(int, input().split())))\nresult = 0\nsumm = 0\n\nfor i in range(N):\n if summ+P[i]<=B:\n summ += P[i]\n result += 1\n else:\n if summ+(P[i]//2)<=B and A:\n summ += P[i]//2\n result += 1\n A -= 1\n else:\n break\n\nprint(summ, result)"},{"alpha_fraction":0.44961240887641907,"alphanum_fraction":0.4961240291595459,"avg_line_length":15.25,"blob_id":"7d02f29c339aa84625434da74d4a5a46e08955e4","content_id":"602f705c14dd98823c307d8c14242d70a038077a","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":129,"license_type":"no_license","max_line_length":22,"num_lines":8,"path":"/알고리즘/온라인저지/2022/07/0702/문어.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = int(input())\nresult = [1] * N\nfor i in range(N):\n if i%2:\n result[i] += 1\nif N%2:\n result[-1] = 3\nprint(*result)"},{"alpha_fraction":0.38655462861061096,"alphanum_fraction":0.3949579894542694,"avg_line_length":12.333333015441895,"blob_id":"e8189246c35cb2453ab369ba784bce1a8a14d4f6","content_id":"5472326aee6ffe8dba35289e2ecb30b6d257de7b","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":119,"license_type":"no_license","max_line_length":26,"num_lines":9,"path":"/알고리즘/SWEA/LEARN/Course/1. Programming Beginner/파이썬 프로그래밍 기초(2)/17차시 2. 자료구조 – 리스트, 튜플 - 연습문제 19.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"x = input().split(', ')\n\nx.sort()\n\nfor i in x:\n if i == x[-1]:\n print(i)\n else:\n print(i, end=', ')"},{"alpha_fraction":0.4084506928920746,"alphanum_fraction":0.46948355436325073,"avg_line_length":29.428571701049805,"blob_id":"8fb0d65015489351f59c3fa13562c67141cd6053","content_id":"a2904dc8e4465a471571900533211eb92e066499","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":213,"license_type":"no_license","max_line_length":63,"num_lines":7,"path":"/알고리즘/온라인저지/2023/01/0115/회의실 배정 2.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = int(input())\narr = [0] + [list(map(int, input().split())) for _ in range(N)]\ndp = [0, arr[1][2]] + [0]*(N-1)\nif N > 1:\n for i in range(2, N+1):\n dp[i] = max(dp[i-1], dp[i-2]+arr[i][2])\nprint(dp[-1])\n"},{"alpha_fraction":0.5537189841270447,"alphanum_fraction":0.5743801593780518,"avg_line_length":19.25,"blob_id":"7402bb6b7ce4765d45a3ebf1e00e51558e2c8ea1","content_id":"7ecc86937e4ab8ad6502a366fc9cabd98fe3ca7f","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":242,"license_type":"no_license","max_line_length":35,"num_lines":12,"path":"/알고리즘/온라인저지/2022/09/0930/문자열.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\n\nA, B = input().rstrip().split()\nresult = int(1e9)\nfor i in range(len(B)-len(A)+1):\n tmp = 0\n for j in range(len(A)):\n if A[j] != B[i+j]: tmp += 1\n result = min(result, tmp)\nprint(result)"},{"alpha_fraction":0.41860464215278625,"alphanum_fraction":0.43410852551460266,"avg_line_length":13.44444465637207,"blob_id":"18570ce7e55d191b03d44c85373b28eae8d8b29a","content_id":"32d7a72d6582b61cadc90c420bdd210a3af3c09c","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":129,"license_type":"no_license","max_line_length":24,"num_lines":9,"path":"/알고리즘/온라인저지/2022/02/0213/홀수일까 짝수일까.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = int(input())\n\nfor n in range(N):\n K = int(input()[-1])\n\n if K % 2:\n print('odd')\n else:\n print('even')"},{"alpha_fraction":0.388127863407135,"alphanum_fraction":0.4337899684906006,"avg_line_length":43,"blob_id":"15c76e18da7ef3d0e60d69e6b4682a0e7e8c23b5","content_id":"7822fba43ad12751db9f8901b2c2d8210c0a6292","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":219,"license_type":"no_license","max_line_length":101,"num_lines":5,"path":"/알고리즘/온라인저지/2023/03/0324/Report Card Time.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"grades = ['F']*60 + ['D']*7 + ['D+']*3 + ['C']*7 + ['C+']*3 + ['B']*7 + ['B+']*3 + ['A']*7 + ['A+']*4\nfor _ in range(int(input())):\n name, score = input().split()\n score = int(score)\n print(name, grades[score])"},{"alpha_fraction":0.5822784900665283,"alphanum_fraction":0.6202531456947327,"avg_line_length":25.66666603088379,"blob_id":"20e363df146cc65785f831c994f973ddd722ff5f","content_id":"782451d0c3693f09f8413c7344bec98deee2da18","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":79,"license_type":"no_license","max_line_length":45,"num_lines":3,"path":"/알고리즘/온라인저지/2022/09/0913/이진수 덧셈.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"result = 0\nfor i in input().split(): result += int(i, 2)\nprint(bin(result)[2:])"},{"alpha_fraction":0.5087719559669495,"alphanum_fraction":0.5263158082962036,"avg_line_length":31.125,"blob_id":"cea27185dc5e65a0b92ae2d4c144d7bea7dc4880","content_id":"c2e1fd4b63d6c5ddbcd33fc3188fb9ff8d222ab7","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":521,"license_type":"no_license","max_line_length":58,"num_lines":16,"path":"/알고리즘/온라인저지/2022/10/1012/행렬 곱셈.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"def multiply(matrix1, matrix2): # 행렬 곱셈\n output = []\n for i in range(N):\n output.append([])\n for j in range(K):\n tmp = 0\n for k in range(M):\n tmp += matrix1[i][k] * matrix2[k][j]\n output[i].append(tmp)\n return output\n\nN, M = map(int, input().split())\nmat1 = [list(map(int, input().split())) for _ in range(N)]\nM, K = map(int, input().split())\nmat2 = [list(map(int, input().split())) for _ in range(M)]\nfor i in multiply(mat1, mat2): print(*i)"},{"alpha_fraction":0.49560633301734924,"alphanum_fraction":0.5184534192085266,"avg_line_length":16.272727966308594,"blob_id":"705dc9059b8facdf9f2ca190ae9ed19f9fe0af08","content_id":"f7c8d52ad5f3357072414c6ccd31377de8913750","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":761,"license_type":"no_license","max_line_length":42,"num_lines":33,"path":"/알고리즘/온라인저지/2022/01/0122/게으른 백곰.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N, K = map(int, input().split())\n\npen = [0] * 1000001 # 우리(pen)의 범위\n\nnow = K # K에서 시작해야, 앞으로 K만큼, 뒤로 K만큼\n\nx_max = 0 # 양동이좌표 최대까지만 탐색\n\nfor n in range(N):\n g, x = map(int, input().split())\n\n pen[x] = g # 우리 채우기\n\n if x > x_max:\n x_max = x # 최대 양동이좌표 저장\n\nresult = window = sum(pen[:now+K+1]) # 초기값\n\nnow += 1 # 한 칸 앞으로\n\n# 백만 다 안돌고, 최대양동이까지만 탐색\nwhile now+K <= x_max: \n # 윈도우 한 칸 앞으로 슬라이딩~\n window -= pen[now-K-1]\n window += pen[now+K]\n \n # 최대값 갱신 가능한가?\n if window > result:\n result = window\n \n now += 1 # 한 칸 앞으로~\n\nprint(result)"},{"alpha_fraction":0.5423728823661804,"alphanum_fraction":0.5706214904785156,"avg_line_length":21.25,"blob_id":"020a634e0b21f6fe0cf69b69c0e67889a0e8e9b0","content_id":"56786f068f246702eb3be17790ff967a6c41afe7","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":177,"license_type":"no_license","max_line_length":57,"num_lines":8,"path":"/알고리즘/온라인저지/2022/08/0827/장신구 명장 임스.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"P, N = map(int, input().split())\nA = sorted(list(map(int, input().split()))) # accessories\nresult = 0\nfor a in A:\n if P >= 200: break\n P += a\n result += 1\nprint(result)"},{"alpha_fraction":0.375,"alphanum_fraction":0.42500001192092896,"avg_line_length":11.100000381469727,"blob_id":"6363fc300a50ebea8f976c000b06391c3de8ee32","content_id":"e957ef52f3ee14b8d75c07c3cd75aae13d744c3e","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":120,"license_type":"no_license","max_line_length":20,"num_lines":10,"path":"/알고리즘/온라인저지/2021/12/1213/평균 점수.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"a = []\n\nfor i in range(5):\n b = int(input())\n if b < 40:\n b = 40\n \n a.append(b)\n\nprint(int(sum(a)/5))"},{"alpha_fraction":0.4337811768054962,"alphanum_fraction":0.44913628697395325,"avg_line_length":18.33333396911621,"blob_id":"e899caf1c32df269b93f99c6533f014e2c85617f","content_id":"ed8f87c6378c38c02c65ab7eddc4871475b280e0","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":521,"license_type":"no_license","max_line_length":35,"num_lines":27,"path":"/알고리즘/온라인저지/2021/09/0905/스택 수열.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\nn = int(sys.stdin.readline())\nori = list(range(2, n+1))\ntmp = [1]\nope = ['+']\n\nfor _ in range(n):\n if not tmp:\n tmp.append(ori.pop(0))\n ope.append('+')\n num = int(sys.stdin.readline())\n if num == tmp[-1]:\n tmp.pop()\n ope.append('-') \n elif num < tmp[-1]:\n print('NO')\n exit()\n else:\n while num != tmp[-1]:\n tmp.append(ori.pop(0))\n ope.append('+')\n tmp.pop()\n ope.append('-') \n\nfor o in ope:\n print(o)"},{"alpha_fraction":0.4351145029067993,"alphanum_fraction":0.442748099565506,"avg_line_length":13.55555534362793,"blob_id":"6c8c3bee863f15d8aa7cf4c603b586df546a6a76","content_id":"2a876075d87ff865b35961e8b2b1628e73fcf8e3","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":131,"license_type":"no_license","max_line_length":31,"num_lines":9,"path":"/알고리즘/온라인저지/2022/02/0205/단어 뒤집기.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"T = int(input())\n\nfor t in range(T):\n sen = input().split()\n\n for s in sen:\n print(s[::-1], end=' ')\n \n print()\n"},{"alpha_fraction":0.38461539149284363,"alphanum_fraction":0.4472934603691101,"avg_line_length":22.399999618530273,"blob_id":"074b00d44aaa41ee9fa6fa69becbc4f19affbe02","content_id":"24b1a2cc7dea4199b1a971857a3f600c43c8f8a1","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":351,"license_type":"no_license","max_line_length":43,"num_lines":15,"path":"/알고리즘/온라인저지/2022/06/0628/애너그램.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"T = int(input())\nfor t in range(T):\n result = 'NOT '\n arr = input().split()\n word1 = [0] * 26\n word2 = [0] * 26\n for w in arr[0]:\n word1[ord(w)-97] += 1\n for w in arr[1]:\n word2[ord(w)-97] += 1\n if word1 == word2:\n result = ''\n print('{} & {} are {}anagrams.'.format(\n arr[0], arr[1], result\n ))\n"},{"alpha_fraction":0.5296523571014404,"alphanum_fraction":0.5521472096443176,"avg_line_length":21.272727966308594,"blob_id":"e693232d62d1b0adc245c7f3439a55e5de1f8b7d","content_id":"6b94620fc13ed7dfe3dacfa0c0569e76587c675c","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":489,"license_type":"no_license","max_line_length":52,"num_lines":22,"path":"/알고리즘/온라인저지/2022/08/0801/예산.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"def binary(start, end):\n global result, M\n if start > end: return\n budget = (start + end) // 2\n tmp = 0\n for b in B: tmp += min(b, budget)\n if tmp <= M:\n if budget > result: \n result = budget\n binary(budget+1, end)\n else:\n binary(start, budget-1)\n\nN = int(input())\nB = sorted(list(map(int, input().split()))) # budget\nM = int(input())\nS, E = 0, M\nresult = 0\nbinary(S, E)\nprint(min(B[-1], result))\n\n# https://www.acmicpc.net/problem/2512"},{"alpha_fraction":0.5460993051528931,"alphanum_fraction":0.588652491569519,"avg_line_length":14.777777671813965,"blob_id":"7be936052a2461d09b971f70700ebb30381d2125","content_id":"88747d0e3bee45dc09230b727dc8a5fbe3b4a0ad","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":141,"license_type":"no_license","max_line_length":32,"num_lines":9,"path":"/알고리즘/온라인저지/2022/10/1012/체스판 조각.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\n\nN = int(input())\nodd = False\nif N%2: N += 1; odd = True\nA = N//2 + 1\nprint(A**2 - A if odd else A**2)"},{"alpha_fraction":0.5694444179534912,"alphanum_fraction":0.5972222089767456,"avg_line_length":11.166666984558105,"blob_id":"7f04d15c1601c41bf900bb7b08e8278fd7c62552","content_id":"c7d4b3cde04bbfe8da7d8ab56daf64a953f66e95","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":72,"license_type":"no_license","max_line_length":26,"num_lines":6,"path":"/알고리즘/온라인저지/2022/02/0205/카드 게임.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"result = 0\n\nfor _ in range(5):\n result += int(input())\n\nprint(result)"},{"alpha_fraction":0.5797545909881592,"alphanum_fraction":0.6012269854545593,"avg_line_length":19.4375,"blob_id":"e66de8337469520acf8e46cfc036e9f48f5a38e7","content_id":"35fc1f6570233cbba1272e696ca1aba9a3e07330","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":390,"license_type":"no_license","max_line_length":43,"num_lines":16,"path":"/알고리즘/온라인저지/2022/07/0717/뒤집기.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"\"\"\"\n블록(구간)의 개수가 적은 숫자를 뒤집기\n그냥 숫자의 개수가 적은 숫자를 뒤집기\n\"\"\"\narr = list(map(int, list(input())))\n# print(arr)\nswitch = True\nresult = [0, 0, arr.count(0), arr.count(1)]\nswitch = bool(arr[0])\nresult[switch] += 1\nfor a in arr:\n if a != switch:\n switch = not switch\n result[switch] += 1\n# print(result)\nprint(min(result))"},{"alpha_fraction":0.5202797055244446,"alphanum_fraction":0.5398601293563843,"avg_line_length":20.058822631835938,"blob_id":"d74e66e5cb5770d001c038d4a47cc1abeaf57cbf","content_id":"90e11bea0639306b4ba7291ff619e95e2d698dc1","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":715,"license_type":"no_license","max_line_length":45,"num_lines":34,"path":"/알고리즘/온라인저지/2022/09/0917/연결 요소의 개수.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\nfrom collections import deque\n\ninput = sys.stdin.readline\n\ndef BFS(node):\n global result\n Q.append(node)\n visited[node] = 1\n cnt = 0\n while Q:\n now = Q.popleft()\n for next in arr[now]:\n if not visited[next]:\n Q.append(next)\n visited[next] = 1\n cnt += 1\n result -= cnt\n\nN, M = map(int, input().rstrip().split())\narr = [[] for _ in range(N+1)]\nvisited = [0] * (N+1)\nQ = deque()\nfor m in range(M):\n u, v = map(int, input().rstrip().split())\n arr[u].append(v)\n arr[v].append(u)\nresult = N\nfor i in range(1, N+1): \n BFS(i)\n if sum(visited) == N: break\nprint(result)\n\n# https://www.acmicpc.net/problem/11724"},{"alpha_fraction":0.6091370582580566,"alphanum_fraction":0.624365508556366,"avg_line_length":28.22222137451172,"blob_id":"a19d6079ab23c3e6fc7b464eb993672af5cb3c55","content_id":"3dc3828d3ba8f786213e3d2b4717d683c66a2b59","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1530,"license_type":"no_license","max_line_length":58,"num_lines":27,"path":"/알고리즘/온라인저지/2021/08/0807/손익분기점.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"\"\"\"\nA, B, C = 고정비용, 생산비용, 노트북 가격\n손익분기점 : 판매수입>총 생산비용(고정비용+생산비용)이 되는 시점\n생산대수를 1대부터 점점 증가시켜서(while)\n손익분기점을 만족하는 N값을 찾아서 출력\n할려고 했는데 예시 2만원에 생산해서 1만원에 파는 사람이 어딨냐고ㅋㅋㅋ\n문제 끝에 \"손익분기점이 발생하지 않으면 -1을 출력한다\"고 있네요\n문제 잘 읽겠습니다...\nwhile문으로 21억까지 +1 하면서 가려니까 시간이 너무 오래 걸려서\n직접 손익분기점을 구해서 올림을 통해 값을 주기로 했는데\n아무래도 math모듈을 불러올 수 없는 것 같다\n올림을 못쓰니, 생산대수를 근사한 값으로 구해서 하나씩 더하기로 했다\nZeroDivisionError가 나왔다, 테스트케이스중에 생산비용과 판매비용이 같은 케이스가 있다는건데\n이 상황을 추가하였다\n\"\"\"\n\nA, B, C = map(int, input().split()) # 고정비용, 가변비용, 판매가 입력\nif B >= C: # 손익분기점이 발생하지 않을 경우\n N = -1 # -1을\nelse: # 손익분기점이 발생할 경우\n N = round(A / (C-B)) - 1 # N일수도 있고 아닐수도 있는 근사값을 설정한다\n while True: # 반복문을 돌리면서\n if N > A / (C-B): # 손익분기점이라면\n break # while문을 마치고\n else: # 손익분기점이 아니라면\n N += 1 # +1 해서 다시 돌려보고\nprint(N) # 출력한다"},{"alpha_fraction":0.5302491188049316,"alphanum_fraction":0.5480427145957947,"avg_line_length":22.41666603088379,"blob_id":"d4b86e3647e17ab8a260fed4960e28cbe82c0817","content_id":"42365851c22a6223934a063930f0543652bec03a","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":413,"license_type":"no_license","max_line_length":40,"num_lines":12,"path":"/알고리즘/온라인저지/2021/08/0809/수들의 합.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\nS = int(sys.stdin.readline()) # S값 입력받고\nN = 0 # 더해줄 N값 초기화\ncount = 0 # 최대 개수 초기화\nwhile True: # while문 반복하면서\n N += 1 # 1부터 S값에서 빼기 시작\n if N > S: # 종료조건\n break\n S -= N # S에서 N을 빼주면서 S를 N보다 작게 만들때까지\n # 수의 개수를 \n count += 1 # 세어주고\nprint(count) # 출력\n"},{"alpha_fraction":0.38879457116127014,"alphanum_fraction":0.5670627951622009,"avg_line_length":13.75,"blob_id":"c60111bafab358f2f649917d396da8975699de37","content_id":"bc3b74f247a613e52d434b182870b8577f540432","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":815,"license_type":"no_license","max_line_length":46,"num_lines":40,"path":"/알고리즘/온라인저지/2022/03/0323/저울.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"\"\"\"\nex) 무게추 = [1 2 4 7 8 30]\n1 1 \n2 2\n3 2 1\n4 4\n5 4 1\n6 4 2\n7 4 2 1\n8 7 1\n9 7 2\n10 7 2 1\n11 7 4\n12 7 4 1\n13 7 4 2\n14 7 4 2 1\n15 8 7\n16 8 7 1\n17 8 7 2\n18 8 7 2 1\n19 8 7 4\n20 8 7 4 1\n21 8 7 4 2\n22 8 7 4 2 1\n23 X\n추들을 순회할 때\n진행중인 모든 추를 다 더한 것 + 1\n보다 큰 추가 있거나, 다 더하고 for문이 끝나면\n그 더한 값이 답이 된다\n\"\"\"\nN = int(input())\nweights = list(map(int, input().split())) # 추들\nweights.sort() # 작은 추부터 차례대로 더할 것\ntarget = 1 # 시작점, 혹은 목표 무게\nfor w in weights: # 추들을 순회하면서\n # print(target, w) # 디버깅\n if target < w: # 더 큰 추가 나왔으면\n break # 지금 보는 무게가 답이 된다\n target += w # 다음 추 더하기\nprint(target) # 목표 무게 출력"},{"alpha_fraction":0.42934781312942505,"alphanum_fraction":0.489130437374115,"avg_line_length":25.428571701049805,"blob_id":"2e05a75fe920cd1bd593fe893505df4c6787fbbe","content_id":"ebe99b2037c4da7e92bfd309a96fa86a4ebd19e4","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":184,"license_type":"no_license","max_line_length":35,"num_lines":7,"path":"/알고리즘/온라인저지/2023/02/0207/주사위.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"A, B, C = map(int, input().split())\ndp = [0]*100\nfor a in range(1, A+1):\n for b in range(1, B+1):\n for c in range(1, C+1):\n dp[a+b+c] += 1\nprint(dp.index(max(dp)))"},{"alpha_fraction":0.5071770548820496,"alphanum_fraction":0.540669858455658,"avg_line_length":26.933332443237305,"blob_id":"73d179e435cf6bdc2766ef7e1a1bcdcf49afe479","content_id":"edb801b7562c9f481e7a70e2e1707e0cddc4967c","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":418,"license_type":"no_license","max_line_length":52,"num_lines":15,"path":"/알고리즘/온라인저지/2023/01/0127/2021은 무엇이 특별할까.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"def prime_list(size):\n sieve = [True]*(size+1)\n for i in range(2, int(size**0.5)+1):\n if sieve[i]:\n for j in range(i+i, size+1, i):\n sieve[j] = False\n return [i for i in range(2, size+1) if sieve[i]]\n\nN = int(input())\nprimes = prime_list(5500)\nfor i in range(len(primes)-1):\n is_special = primes[i]*primes[i+1]\n if is_special > N:\n print(is_special)\n break"},{"alpha_fraction":0.4900990128517151,"alphanum_fraction":0.5118811726570129,"avg_line_length":23.658536911010742,"blob_id":"4ad5c46b849f6e36cb7a616fba3b64aa9d3b52d9","content_id":"8c3fcf68a0b5d8dedb9d86e236ba8b6545b80940","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1228,"license_type":"no_license","max_line_length":61,"num_lines":41,"path":"/알고리즘/온라인저지/2022/08/0828/녹색 옷 입은 애가 젤다지.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\nimport heapq # 탐색 시 가장 작은 값을 탐색하기 위함\n\ninput = sys.stdin.readline\nINF = int(1e9) # 가상의 최대값\ndy, dx = [-1, 1, 0, 0], [0, 0, -1, 1]\n\ndef dijkstra(y, x):\n global result\n heapq.heappush(Q, (y, x, arr[y][x]))\n visited[y][x] = arr[y][x]\n while Q:\n y, x, dist = heapq.heappop(Q)\n for i in range(4):\n ny, nx = y+dy[i], x+dx[i]\n if 0<=ny<N and 0<=nx<N:\n cost = dist + arr[ny][nx]\n if cost < visited[ny][nx]:\n visited[ny][nx] = cost\n heapq.heappush(Q, (ny, nx, cost))\n\ncase = 0\nwhile True:\n case += 1\n N = int(input())\n if N == 0: break\n arr = [list(map(int, input().split())) for _ in range(N)]\n visited = [[INF]*N for _ in range(N)]\n result = INF\n Q = []\n dijkstra(0, 0)\n print(f'Problem {case}: {visited[N-1][N-1]}')\n\n\"\"\"\n최소 경로값을 저장하는 배열 생성\n모든 지점에 대해 최소 경로값을 구하며 진행\n도착점 arr[N-1][N-1]의 최소 경로값을 출력\nheapq 자체의 빠른 속도만을 이용하였고\n별도의 백트래킹문은 넣지 않음\nDP처럼 모든 지점의 최소 경로값을 구하였음\n\"\"\""},{"alpha_fraction":0.37060701847076416,"alphanum_fraction":0.3993610143661499,"avg_line_length":19.866666793823242,"blob_id":"0e67eea0bdc031f21e8a4f4afcabe7266281ef3b","content_id":"d6f65d5ea36ffbaf01c7be72ffdfa6f63fdf04a6","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":313,"license_type":"no_license","max_line_length":43,"num_lines":15,"path":"/알고리즘/온라인저지/2022/05/0523/별 찍기 - 17.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = int(input())\nstart = N-1\nlast = N*2-1\nmiddle = 1\nfor n in range(N):\n if n == 0:\n print(' '*start, '*', sep='')\n start -= 1\n elif n == N-1:\n print('*'*last)\n else:\n print(' '*start, end='')\n print('*', ' '*middle, '*', sep='')\n middle += 2\n start -= 1\n"},{"alpha_fraction":0.553398072719574,"alphanum_fraction":0.6019417643547058,"avg_line_length":25,"blob_id":"82057bf2426ad090e54bfe566b443942d24d3865","content_id":"44c94bdfc19d8e24d6f0813c2838c91b36121bf2","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":103,"license_type":"no_license","max_line_length":41,"num_lines":4,"path":"/알고리즘/온라인저지/2022/12/1207/Dog Treats.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"result = 0\nfor i in range(1, 4):\n result += int(input())*i\nprint('happy' if result >= 10 else 'sad')"},{"alpha_fraction":0.4206642210483551,"alphanum_fraction":0.4206642210483551,"avg_line_length":21.66666603088379,"blob_id":"b3ab30184962cd9a4b5fe008a15c925c0208187a","content_id":"a5969ed2dae7213d8fc37a3fd74dd4467ec04da0","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":271,"license_type":"no_license","max_line_length":31,"num_lines":12,"path":"/알고리즘/온라인저지/2023/05/0520/좋은놈 나쁜놈.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"for _ in range(int(input())):\n S = input()\n G = S.count('G')\n G += S.count('g')\n B = S.count('B')\n B += S.count('b')\n result = 'NEUTRAL'\n if G > B:\n result = 'GOOD' \n if G < B:\n result = 'A BADDY'\n print(f'{S} is {result}')"},{"alpha_fraction":0.46357616782188416,"alphanum_fraction":0.5430463552474976,"avg_line_length":15.88888931274414,"blob_id":"6bc66001c1f38c2876f76e0eb0910f11c8b75875","content_id":"f80c9a225ea758ba8a491161bd7637abe8b5f464","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":151,"license_type":"no_license","max_line_length":29,"num_lines":9,"path":"/알고리즘/온라인저지/2022/09/0924/피보나치 비스무리한 수열.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\n\nN = int(input())\ndp = [0, 1, 1, 1] + [0]*114\nfor i in range(4, N+1):\n dp[i] = dp[i-1] + dp[i-3]\nprint(dp[N])"},{"alpha_fraction":0.6756756901741028,"alphanum_fraction":0.6756756901741028,"avg_line_length":17.66666603088379,"blob_id":"e8068822513fa36a39f272bf33a7889d2ccbd218","content_id":"3f30abd89d5cb6537429a0271139c5b6d6f350e3","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":111,"license_type":"no_license","max_line_length":63,"num_lines":6,"path":"/알고리즘/온라인저지/2022/09/0927/중복 빼고 정렬하기.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\n\ninput()\nprint(*(sorted(list(set(map(int, input().rstrip().split()))))))"},{"alpha_fraction":0.5025996565818787,"alphanum_fraction":0.5242634415626526,"avg_line_length":24.66666603088379,"blob_id":"8090ca597ba66828e7c113c9c876ffcb9056804c","content_id":"bc28444de5390de6bbf3d1e93422f6e6cfc24ee1","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1742,"license_type":"no_license","max_line_length":58,"num_lines":45,"path":"/알고리즘/온라인저지/2021/10/1016/미로 탐색.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"from collections import deque # popleft() 사용할 것\n\ndx = (-1, 1, 0, 0) # 델타이동 속도를 조금이라도 높이기 위해\ndy = (0, 0, -1, 1) # tuple() 사용\n\nN, M = map(int, input().split())\n\narr = []\n\nfor n in range(N):\n arr.append(list(map(int,input()))) # 공백 없으니, split()없이\n\nq = deque()\n\nq.append((0, 0, 1)) # 출발지점, 출발점부터 거리 카운트함\n\nresult = 0 # 결과값 초기화\n\nwhile q: # == BFS\n tmp = q.popleft() # == pop(0)\n x = tmp[0] # 탐색할 x좌표\n y = tmp[1] # 탐색할 y좌표\n cnt = tmp[2] # 여기까지 오는데 걸린 거리\n if arr[y][x] == 0: # 이전 탐색에서 q에 담았었지만 꺼내보니 방문한 적이 있다면\n # 방문할 곳에 해당하여 q에 담았지만, 막상 차례가 되서 꺼내보니 탐색할 필요가 없다면\n # 아래 과정들을 또 진행하여 중복방문이 일어나지 않도록\n continue\n arr[y][x] = 0 # 방문처리\n # 처음에는 arr과 동일한 크기의 visited 배열을 만들어서 방문처리를 하였으나\n # 메모리가 넉넉하지 않은 문제임을 확인하였고\n # 원본 배열 자체에서 방문처리 하였음\n\n if x == M-1 and y == N-1: # 도착좌표\n result = cnt # 거리를 결과값에 저장\n break # 종료\n\n for i in range(4): # 탐색중인 좌표가 목적지가 아니라면 \n # 범위를 벗어나지 않고 방문한 적이 없는 주변 4칸 담을 것\n nx = x+dx[i] # 좌우\n ny = y+dy[i] # 상하\n if 0 <= nx < M and 0 <= ny < N and arr[ny][nx]:\n # 배열 안에서, 방문한 적이 없다면\n q.append((nx, ny, cnt+1)) # 방문할 곳에 추가\n\nprint(result)"},{"alpha_fraction":0.44117647409439087,"alphanum_fraction":0.4632352888584137,"avg_line_length":16.0625,"blob_id":"49a816c129f781ec7b37860f285b5f47cc57ef1b","content_id":"fe5cb498bad4dbd73623cb0c32c22295e7a06efa","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":272,"license_type":"no_license","max_line_length":31,"num_lines":16,"path":"/알고리즘/온라인저지/2021/09/0906/수들의 합 5.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\ndef input():\n return sys.stdin.readline()\n\nN = int(input())\ncnt = 0\nfor n in range(1, N+1):\n tmp = N\n for i in range(n, N+1):\n tmp -= i\n if tmp < 0:\n break\n elif not tmp:\n cnt += 1\n break\nprint(cnt)"},{"alpha_fraction":0.37567567825317383,"alphanum_fraction":0.4162162244319916,"avg_line_length":25.5,"blob_id":"7d5253ea21502a7961567ea0b2277be8effc5554","content_id":"8a0999cf925fcc4601bbb879bfca13ee051f9f36","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":370,"license_type":"no_license","max_line_length":98,"num_lines":14,"path":"/알고리즘/온라인저지/2022/12/1218/e 계산.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"print('n e')\nprint('- -----------')\nfor n in range(10):\n e = 0\n for i in range(n+1):\n factorial = 1\n s = 1\n for f in range(1, i+1):\n factorial *= f\n s /= factorial\n e += s\n print(n, end=' ')\n e = str(e).split('.')\n print(f'{float(\".\".join(e)):0.9f}' if len(e[1]) > 9 else \".\".join(e) if e[1] != '0' else e[0])"},{"alpha_fraction":0.5170068144798279,"alphanum_fraction":0.5510203838348389,"avg_line_length":20.14285659790039,"blob_id":"edf7d7c4f4e8471999694b198aa9de88c2d1ce95","content_id":"6d5d6e2e360ff0a049fac299157028d5e03a24b0","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":147,"license_type":"no_license","max_line_length":38,"num_lines":7,"path":"/알고리즘/온라인저지/2022/03/0328/조교는 새디스트야!!.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = int(input())\ncrew = list(map(int, input().split()))\nresult = 0\nfor i in range(1, N+1):\n if crew[i-1] != i:\n result += 1\nprint(result)"},{"alpha_fraction":0.4440000057220459,"alphanum_fraction":0.47200000286102295,"avg_line_length":26.88888931274414,"blob_id":"f9e34ae56861de691ac7e1326cba1073f51dd4e1","content_id":"6b1c695f156f92bb4901fe11bdd9a7d5add97e99","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":250,"license_type":"no_license","max_line_length":41,"num_lines":9,"path":"/알고리즘/온라인저지/2022/09/0912/알파벳 거리.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"for _ in range(int(input())):\n X, Y = input().split()\n result = []\n for i in range(len(X)):\n y, x = ord(Y[i])-64, ord(X[i])-64\n tmp = y-x\n if tmp < 0: tmp += 26\n result.append(tmp)\n print('Distances:', *result)"},{"alpha_fraction":0.40692123770713806,"alphanum_fraction":0.42243435978889465,"avg_line_length":22.30555534362793,"blob_id":"f32533e75252f83d7c425f40079e5ea48479500e","content_id":"7aa081ea63ae1b970f2fb5521172e8d8fbd9e856","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":906,"license_type":"no_license","max_line_length":63,"num_lines":36,"path":"/알고리즘/SWEA/LEARN/Course/2. Programming Intermediate/3. 파이썬 SW문제해결 기본 String/4차시 3일차 - 회문.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"def palindrome(arr): # 팰린드롬을 찾아서 result에 추가하는 함수\n for i in range(N):\n for j in range(N-M+1):\n if not M%2:\n if arr[i][j:j+M//2] == arr[i][j+M:j+M//2-1:-1]:\n result.append(arr[i][j:j+M])\n break\n else:\n if arr[i][j:j+M//2] == arr[i][j+M:j+M//2:-1]:\n result.append(arr[i][j:j+M])\n break \n\n\nT = int(input())\n\nfor t in range(1, T+1):\n N, M = map(int, input().split())\n\n arr = tuple(input() for _ in range(N))\n\n result = []\n # 가로\n palindrome(arr)\n \n # 세로 : 배열을 90도 뒤집어서 똑같은 코드 실행\n arr = list(arr)\n\n tmp = ['' for _ in range(N)]\n \n for a in arr:\n for i in range(N):\n tmp[i] = tmp[i] + a[i]\n \n palindrome(tmp)\n\n print('#{} {}'.format(t, *result))"},{"alpha_fraction":0.5236220359802246,"alphanum_fraction":0.539370059967041,"avg_line_length":14.9375,"blob_id":"d80325e272700c470082b17f4ca8b3e9aed87e3a","content_id":"19344b6ccbe56c6e9a9d3620ab6f9737f617d8a5","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":254,"license_type":"no_license","max_line_length":26,"num_lines":16,"path":"/알고리즘/온라인저지/2022/09/0903/30.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = input()\ntmp = 0\nzero = False\nresult = []\nfor n in N:\n n = int(n)\n tmp += n\n result.append(n)\n if n == 0: zero = True\ntmp %= 3\nresult.sort(reverse=True)\nif not tmp and zero:\n for r in result:\n print(r, end='')\nelse:\n print(-1)"},{"alpha_fraction":0.5714285969734192,"alphanum_fraction":0.6285714507102966,"avg_line_length":35,"blob_id":"2e0fc741a6f78fa8c60aa966b5dae4d6e733a5af","content_id":"ad8efce2b6b676c0a67cf96ff1138971b7875b8c","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":35,"license_type":"no_license","max_line_length":35,"num_lines":1,"path":"/알고리즘/온라인저지/2023/04/0427/ゾロ目 (Same Numbers).py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"a,b=input();print(1 if a==b else 0)"},{"alpha_fraction":0.5246636867523193,"alphanum_fraction":0.5650224089622498,"avg_line_length":21.399999618530273,"blob_id":"783df0b75a5bf00a31f2c537249a898380d449fb","content_id":"3defba8010f0187f79044cf1bb7e0fab8df521ac","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":223,"license_type":"no_license","max_line_length":42,"num_lines":10,"path":"/알고리즘/온라인저지/2022/11/1127/JOI와 IOI.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\n\nresult = [0, 0] # JOI, IOI\nS = input().rstrip()\nfor i in range(len(S)-2):\n if S[i:i+3] == 'JOI': result[0] += 1\n elif S[i:i+3] == 'IOI': result[1] += 1\nfor r in result: print(r)"},{"alpha_fraction":0.4480408728122711,"alphanum_fraction":0.475298136472702,"avg_line_length":23.95652198791504,"blob_id":"ff2d095d9f15609aed06ca59aaadc5476b20dc01","content_id":"1d324a72c061935a6e75debf0b2f886da0f4f503","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":807,"license_type":"no_license","max_line_length":57,"num_lines":23,"path":"/알고리즘/온라인저지/2021/10/1003/부분수열의 합.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N, S = map(int, input().split())\n\narr = list(map(int, input().split()))\n\nn = len(arr)\n\ncnt = 0 # 부분집합의 합이 S가 될 때마다 +1\n\n# 비트연산 \"<<\"를 통해 부분집합을 구해줄 것\nfor i in range(1<<n): # 2의 len(arr)승 -> arr의 부분집합의 개수\n tmp = [] # 부분집합 초기화\n for j in range(n): \n if i&(1<<j): # 1<<j == arr에서 j번째 원소를 의미\n # 만약 i의 비트가 11100이면\n # tmp == 리스트의 0번째, 1번째, 2번째 원소를 가지는 arr의 부분집합\n tmp.append(arr[j]) # 해당 부분집합의 원소를 부분집합에 추가\n if sum(tmp) == S:\n if len(tmp) == 0: # 공집합은 예외처리\n pass\n else: # \n cnt += 1\n\nprint(cnt) # 출력\n \n"},{"alpha_fraction":0.4107142984867096,"alphanum_fraction":0.5059523582458496,"avg_line_length":20.125,"blob_id":"164d01b972c587fd9e803973aa97cc7360405223","content_id":"95b727a63e6144247fdd53c127f0d95cb3b38906","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":168,"license_type":"no_license","max_line_length":43,"num_lines":8,"path":"/알고리즘/온라인저지/2022/02/0206/5와 6의 차이.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"A, B = input().split()\n\nA5 = A.replace('6', '5')\nA6 = A.replace('5', '6')\nB5 = B.replace('6', '5')\nB6 = B.replace('5', '6')\n\nprint(int(A5) + int(B5), int(A6) + int(B6))"},{"alpha_fraction":0.5761589407920837,"alphanum_fraction":0.6158940196037292,"avg_line_length":15.88888931274414,"blob_id":"4771af0518336e6f867b278cf383ed248c21a2d1","content_id":"21e87d2ea81b6865b0cdc77fc842dbd7d6cdfed6","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":151,"license_type":"no_license","max_line_length":56,"num_lines":9,"path":"/알고리즘/온라인저지/2022/03/0301/팀 나누기.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"players = list(map(int, input().split()))\n\nplayers.sort()\n\ntmp = [players[0] + players[3], players[1] + players[2]]\n\ntmp.sort()\n\nprint(tmp[1] - tmp[0])"},{"alpha_fraction":0.3425000011920929,"alphanum_fraction":0.38749998807907104,"avg_line_length":13.851851463317871,"blob_id":"5ea179f9fd0a5408d228219a09a8f79ec0caa652","content_id":"d65adb19549de5b44d6cfcc3b5a01a7f8e25f272","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":400,"license_type":"no_license","max_line_length":34,"num_lines":27,"path":"/알고리즘/온라인저지/2022/01/0108/1, 2, 3 더하기.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"T = int(input())\n\nfor tc in range(T):\n N = int(input())\n\n dp = [0 for _ in range(N+1)]\n\n dp[1] = 1\n if N == 1:\n print(dp[1])\n continue\n dp[2] = 2\n\n if N == 2:\n print(dp[2])\n continue\n\n dp[3] = 4\n if N == 3:\n print(dp[3])\n continue\n\n if N > 3:\n for i in range(4, N+1):\n dp[i] = sum(dp[i-3:i])\n\n print(dp[N])"},{"alpha_fraction":0.4372294247150421,"alphanum_fraction":0.5064935088157654,"avg_line_length":20.090909957885742,"blob_id":"166cfacd163b1397eeb72618e1d3b86aeed98d7e","content_id":"ebb3675ac542628b3c0ea2815d6a111822966531","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":231,"license_type":"no_license","max_line_length":32,"num_lines":11,"path":"/알고리즘/온라인저지/2022/09/0901/진법 변환.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"number = input().split()\nN, B = number[0], int(number[1])\nresult = 0\nN = N[::-1]\nfor i in range(len(N)):\n O = ord(N[i]) # ord\n if 48<=O<=57: O -= 48\n elif 65<=O<=90: O -= 55\n tmp = B**i*O\n result += tmp\nprint(result)"},{"alpha_fraction":0.34688347578048706,"alphanum_fraction":0.38482385873794556,"avg_line_length":13.800000190734863,"blob_id":"702a8cfb42d9fba87b161cd0a659026b016b94e6","content_id":"693ad1168fca5d1f5b1057bc0ce5a70242996049","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":369,"license_type":"no_license","max_line_length":38,"num_lines":25,"path":"/알고리즘/온라인저지/2022/11/1116/문어 숫자.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\n\noctopus = {\n '-': 0,\n '\\\\': 1,\n '(': 2,\n '@': 3,\n '?': 4,\n '>': 5,\n '&': 6,\n '%': 7,\n '/': -1,\n}\n\nwhile True:\n tmp = list(input().rstrip())[::-1]\n if tmp == ['#']: break\n j = 0\n result = 0\n for i in range(len(tmp)):\n result += 8**j*octopus[tmp[i]]\n j += 1\n print(result)"},{"alpha_fraction":0.4805825352668762,"alphanum_fraction":0.553398072719574,"avg_line_length":22,"blob_id":"7408283afe8e5563b6c779cdfcfd571b64bf4151","content_id":"2ec7e41b36ba889233dbc8a4deb8e2ad10b4d5f5","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":206,"license_type":"no_license","max_line_length":43,"num_lines":9,"path":"/알고리즘/온라인저지/2022/10/1003/Generations of Tribbles.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\n\ndp = [1, 1, 2, 4] + [0]*66\nfor i in range(4, 70):\n dp[i] = dp[i-1]+dp[i-2]+dp[i-3]+dp[i-4]\nfor i in [0]*int(input().rstrip()):\n print(dp[int(input().rstrip())])"},{"alpha_fraction":0.6302083134651184,"alphanum_fraction":0.6302083134651184,"avg_line_length":26.571428298950195,"blob_id":"ef4864106946dbfe9ed1c1c4817f1a7280b6878c","content_id":"348ce8e0edba8c5f35c4d7ae37f146713f0befaf","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":192,"license_type":"no_license","max_line_length":45,"num_lines":7,"path":"/알고리즘/온라인저지/2023/04/0419/특별한 학교 이름.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"school = {\n 'NLCS': 'North London Collegiate School',\n 'BHA': 'Branksome Hall Asia',\n 'KIS': 'Korea International School',\n 'SJA': 'St. Johnsbury Academy',\n}\nprint(school[input()])"},{"alpha_fraction":0.49814125895500183,"alphanum_fraction":0.5018587112426758,"avg_line_length":19.769229888916016,"blob_id":"8f8de9852e62d66ca0618f9ebab6440392a2673a","content_id":"b2cc8304696776c735f7d87dd6327ea8be675e2c","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":269,"license_type":"no_license","max_line_length":50,"num_lines":13,"path":"/알고리즘/온라인저지/2022/03/0320/공.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"M = int(input())\nmoves = []\nfor m in range(M):\n moves.append(tuple(map(int, input().split())))\n# print(moves)\nball = 1\nfor move in moves:\n if ball in move:\n for m in move:\n if ball != m:\n ball = m\n break\nprint(ball)"},{"alpha_fraction":0.5317460298538208,"alphanum_fraction":0.60317462682724,"avg_line_length":24.399999618530273,"blob_id":"883d94378d5c373039dac2304b525982ef02e3be","content_id":"ca2571aada4b8cc2472f5c372c587c947c754c3b","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":126,"license_type":"no_license","max_line_length":38,"num_lines":5,"path":"/알고리즘/온라인저지/2023/04/0414/덧셈과 곱셈.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"a, b = map(int, input().split())\nresult = 1\nfor i in range(a, b+1):\n result *= sum(list(range(1, i+1)))\nprint(result%14579)"},{"alpha_fraction":0.42352941632270813,"alphanum_fraction":0.4470588266849518,"avg_line_length":16,"blob_id":"49d41ac31357400bfdd1a8775289b8902afb7299","content_id":"c7f3e81358032745e47a5d3d97330d8d638a5c62","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":255,"license_type":"no_license","max_line_length":36,"num_lines":15,"path":"/알고리즘/온라인저지/2022/05/0514/팩토리얼 진법.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"table = []\na = 1\nfor i in range(1, 6):\n table.append(a*i)\n a *= i\nwhile True:\n N = input()\n if N == '0':\n break\n M = len(N)\n N = N[::-1]\n result = 0\n for i in range(M):\n result += int(N[i])*table[i]\n print(result)\n"},{"alpha_fraction":0.450236976146698,"alphanum_fraction":0.450236976146698,"avg_line_length":14.142857551574707,"blob_id":"d52006b5c96a1762fe3eba34428b2789b71833b9","content_id":"159853587b92910b72bf3805fe2299a14e2ac109","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":211,"license_type":"no_license","max_line_length":40,"num_lines":14,"path":"/알고리즘/온라인저지/2022/02/0213/얼마.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"T = int(input())\n\nfor t in range(T):\n S = int(input())\n N = int(input())\n \n result = S\n\n for n in range(N):\n q, p = map(int, input().split())\n\n result += q * p\n \n print(result)"},{"alpha_fraction":0.565517246723175,"alphanum_fraction":0.5793103575706482,"avg_line_length":35.5,"blob_id":"dcaf2cede807a7219785e05b4fcb672afea1098e","content_id":"ac5f0fc9ac7cfb1c506886ef2f193d01ed64c6dc","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":145,"license_type":"no_license","max_line_length":76,"num_lines":4,"path":"/알고리즘/온라인저지/2022/08/0806/숫자 카드.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = int(input())\nC = set(map(int, input().split()))\nM = int(input())\nfor i in list(map(int, input().split())): print(1 if i in C else 0, end=' ')"},{"alpha_fraction":0.446393758058548,"alphanum_fraction":0.4684860408306122,"avg_line_length":32.4782600402832,"blob_id":"381502c937816e48575f7d696e5c8b885e71f4ff","content_id":"12b2b6279a1808f853f9153bba8751e12fdff6db","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1983,"license_type":"no_license","max_line_length":85,"num_lines":46,"path":"/알고리즘/온라인저지/2022/09/0913/치즈.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"from collections import deque\n\ndy, dx = [-1, 1, 0, 0], [0, 0, -1, 1]\nN, M = map(int, input().split())\narr = [list(map(int, input().split())) for _ in range(N)]\nresult = [0, int(1e9)] # [녹는데 걸리는 시간, 다 녹기 한 시간 전 남은 치즈 수]\nwhile True:\n melt = True # 다 녹았는지 확인할 것\n cheese = 0 # 지금 남아있는 치즈 수\n for i in range(N):\n for j in range(M):\n if arr[i][j]: # 하나라도 안 녹은 치즈가 있다면\n melt = False # 다 녹은 것은 아니지\n cheese += 1 # 치즈 개수 증가\n if melt: # 다 녹았다면\n for r in result: print(r) # 출력\n break\n else: # 다 안녹았다면 녹이러 가자!\n Q, cheese_Q = deque(), deque() # 배열탐색 deque, 녹일 치즈만 담을 deque\n visited = [[0]*M for _ in range(N)]\n Q.append((0, 0)) # 배열의 가장자리는 무조건 공기이다\n visited[0][0] = 1 \n while Q:\n y, x = Q.popleft()\n for k in range(4):\n ny, nx = y+dy[k], x+dx[k] # 상하좌우\n if 0<=ny<N and 0<=nx<M and not visited[ny][nx]:\n visited[ny][nx] = 1 # 치즈든 공기든, 탐색할 것\n if arr[ny][nx]: # 치즈\n cheese_Q.append((ny, nx)) # 녹일 치즈\n else: # 공기\n Q.append((ny, nx)) # 다음 탐색할 공기\n while cheese_Q: # 치즈를 녹이자\n y, x = cheese_Q.popleft()\n arr[y][x] = 0 # 치즈가 녹는다\n result[0] += 1 # 한 시간 경과\n result[1] = min(result[1], cheese) # 배열의 치즈들은 녹았지만, cheese는 녹기 전 치즈 수를 가지고 있다\n\n\"\"\"\n핵심\n1. 공기를 기준으로 주변 치즈를 녹인다\n2. 녹이면서 진행하지 말고\n 녹일 치즈들을 한 데 모아, 한 번에 녹인다\n\"\"\"\n\n# https://www.acmicpc.net/problem/2636"},{"alpha_fraction":0.5240174531936646,"alphanum_fraction":0.5327510833740234,"avg_line_length":27.75,"blob_id":"568692f7dc0910a82bb61ea04e4b91c952fc2f5b","content_id":"a0925f50f0880181d80ee561fe6e3c7ad38ba08d","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":229,"license_type":"no_license","max_line_length":56,"num_lines":8,"path":"/알고리즘/온라인저지/2022/12/1210/대충 더해.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"A, B = map(str, sorted(list(map(int, input().split()))))\nresult = ''\nfor i in range(1, len(B)+1):\n try:\n result = str(int(A[-i]) + int(B[-i])) + result\n except:\n result = str(int(B[-i])) + result\nprint(result)"},{"alpha_fraction":0.4330601096153259,"alphanum_fraction":0.4439890682697296,"avg_line_length":21.90625,"blob_id":"dbdfccaf4c158bd8a1a414f13136687066f71142","content_id":"c05feedc47e5fc56044244c8be8aaf5cbe0658de","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":732,"license_type":"no_license","max_line_length":47,"num_lines":32,"path":"/알고리즘/온라인저지/2022/04/0403/세 수.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import copy\nnums = list(map(int, input().split()))\noriginal = copy.deepcopy(nums)\nnums.sort()\nA, B, C = nums[0], nums[1], nums[2]\n# print(A, B, C)\nope = 1 # * or /\nif A+B == C:\n ope = 0 # + or -\n# print(ope)\n# print(nums, original)\nD, E, F = original[0], original[1], original[2]\nresult = ''\nif not ope:\n if D+E == F:\n result = f'{D}+{E}={F}'\n elif E+F == D:\n result = f'{D}={E}+{F}'\n elif D-E == F:\n result = f'{D}-{E}={F}'\n elif E-F == D:\n result = f'{D}={E}-{F}'\nelse:\n if D*E == F:\n result = f'{D}*{E}={F}'\n elif E*F == D:\n result = f'{D}={E}*{F}'\n elif D//E == F:\n result = f'{D}/{E}={F}'\n elif E//F == D:\n result = f'{D}={E}/{F}'\nprint(result)"},{"alpha_fraction":0.5584415793418884,"alphanum_fraction":0.5714285969734192,"avg_line_length":12,"blob_id":"6480c6993f063ac21f93d51bed3aef955264d14b","content_id":"e7dbee1d222b155f47cd53e5ad0a5f170309e999","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":77,"license_type":"no_license","max_line_length":24,"num_lines":6,"path":"/알고리즘/온라인저지/2022/02/0202/영수증.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"bill = int(input())\n\nfor _ in range(9):\n bill -= int(input())\n\nprint(bill)"},{"alpha_fraction":0.4455958604812622,"alphanum_fraction":0.46113988757133484,"avg_line_length":18.399999618530273,"blob_id":"79ca20c7a273aad5dcbfaf7770e9f644cf683ce0","content_id":"d4e88f61dc1833c454a77d3907e808cf7d29430b","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":193,"license_type":"no_license","max_line_length":38,"num_lines":10,"path":"/알고리즘/온라인저지/2022/02/0220/ABC.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"nums = list(map(int, input().split()))\nnums.sort()\n\nfor i in input():\n if i == 'A':\n print(nums[0])\n elif i == 'B':\n print(nums[1])\n elif i == 'C':\n print(nums[2])"},{"alpha_fraction":0.4766763746738434,"alphanum_fraction":0.5199222564697266,"avg_line_length":22.397727966308594,"blob_id":"ac9780e815a2647a0816600313fad516f4576630","content_id":"df70e96931cd8eb4b9b272fb63a1421e27eff755","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":2602,"license_type":"no_license","max_line_length":68,"num_lines":88,"path":"/알고리즘/온라인저지/2022/03/0314/톱니바퀴.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"\"\"\"\n반시계\n11001110\n-1\n10011101\n\n시계\n11001110\n1\n01100111\n\"\"\"\n\nfrom pprint import pprint\n\n\ndef clockwise(i): # 시계방향\n global gears, visited\n if i not in range(4): # 톱니 인덱스가 범위를 벗어나면\n return # 함수 종료\n # print(\"clockwise!\", i+1) # 디버깅\n try:\n if gears[i][2] != gears[i+1][6]: # 현재 톱니바퀴의 오른쪽 톱니바퀴와 극이 다르면\n visited[i] = 1 # 방문처리\n if not visited[i+1]: # 확인하지 않은 톱니바퀴에 대해\n counter_clockwise(i+1) # 오른쪽 톱니 반시계방향\n except:\n pass\n try:\n if gears[i][6] != gears[i-1][2]: # 현재 톱니바퀴의 왼쪽 톱니바퀴와 극이 다르면\n visited[i] = 1\n if not visited[i-1]:\n counter_clockwise(i-1) # 왼쪽 톱니 반시계방향\n except:\n pass\n tmp = [gears[i][-1]] + gears[i][:7] # 시계방향으로 돌려주기\n gears[i] = tmp\n\ndef counter_clockwise(i): # 반시계방향\n global gears, visited\n if i not in range(4): # 톱니 인덱스가 범위를 벗어나면\n return # 함수 종료\n # print('counter!!', i+1) # 디버깅\n try:\n if gears[i][2] != gears[i+1][6]: # 오른쪽 톱니와 극이 다르면\n visited[i] = 1\n if not visited[i+1]:\n clockwise(i+1) # 오른쪽 톱니 시계방향\n except:\n pass\n try:\n if gears[i][6] != gears[i-1][2]: # 왼쪽 톱니와 극이 다르면\n visited[i] = 1\n if not visited[i-1]:\n clockwise(i-1) # 왼쪽 톱니 시계방향\n except:\n pass\n tmp = gears[i][1:] + [gears[i][0]] # 반시계방향으로 돌려주기\n gears[i] = tmp\n\n\n# 값들 입력받기\ngears = [] # 톱니들\nfor _ in range(4):\n gears.append(list(map(int, input())))\nK = int(input())\norders = [] # 돌리는 톱니번호와 방향들\nfor k in range(K):\n orders.append(tuple(map(int, input().split())))\n\n# pprint(gears) # 디버깅\n\nfor order in orders: \n # print(order) # 디버깅\n visited = [0] * 4 # 매 톱니마다 방문배열 초기화\n if order[1] == 1:\n clockwise(order[0]-1) # 시계방향\n elif order[1] == -1:\n counter_clockwise(order[0]-1) # 반시계방향\n # pprint(gears) # 디버깅\n\nresult = 0 # 결과값 초기화\nnum = 1 # 결과값에 더할 변수값 초기화\nfor i in range(4):\n if gears[i][0]: # 12시 톱니가 1이면\n result += num # 결과값 갱신\n num *= 2 # 1 2 4 8 \n\nprint(result) # 결과값 출력"},{"alpha_fraction":0.4950000047683716,"alphanum_fraction":0.5149999856948853,"avg_line_length":21.33333396911621,"blob_id":"58c73bbd31ce80e07433c7117e77e02416d75334","content_id":"0c95248971f536e888baadc3cac34581bae48eb6","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":200,"license_type":"no_license","max_line_length":38,"num_lines":9,"path":"/알고리즘/온라인저지/2022/05/0519/나이순 정렬.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"age = [[] for _ in range(201)]\nT = int(input())\nfor t in range(T):\n member = input().split()\n age[int(member[0])].append(member)\nfor a in age:\n if a:\n for i in a:\n print(*i)"},{"alpha_fraction":0.27710843086242676,"alphanum_fraction":0.4518072307109833,"avg_line_length":12.916666984558105,"blob_id":"6e33e24ff9174afac506797062913afb4a99e02e","content_id":"6a33f7a4b542b779d8d4624dbc2d15fbf4c39976","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":166,"license_type":"no_license","max_line_length":40,"num_lines":12,"path":"/알고리즘/온라인저지/2022/05/0531/도미노.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"a = 0\nresult = 0\nfor i in range(int(input()), -1, -1):\n a += 3\n result += i*a\nprint(result)\n\n\"\"\"\n2 = 0+1+2 = 0+3+9\n3=0+1+2+3 = 0+3+9+18 = 0+3+(3+6)+(3+6+9)\n\n\"\"\""},{"alpha_fraction":0.4956521689891815,"alphanum_fraction":0.4956521689891815,"avg_line_length":16.769229888916016,"blob_id":"600a78a3dd5d9d751b8e1e3dab0ff4dbeef146f8","content_id":"a2a76d0ad887dc2fa74cbee100a56ff7ccd0ec58","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":230,"license_type":"no_license","max_line_length":39,"num_lines":13,"path":"/알고리즘/온라인저지/2021/12/1216/TGN.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = int(input())\n\nfor n in range(N):\n r, e, c = map(int, input().split())\n\n fee = e-c\n\n if fee > r:\n print('advertise')\n elif fee < r:\n print('do not advertise')\n else:\n print('does not matter')"},{"alpha_fraction":0.5249999761581421,"alphanum_fraction":0.550000011920929,"avg_line_length":12.666666984558105,"blob_id":"ff196def3d709304e1b727e33236d0290332be74","content_id":"dba783ef9e53faedbc43ed33d75b3c9466b98f24","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":40,"license_type":"no_license","max_line_length":21,"num_lines":3,"path":"/알고리즘/SWEA/LEARN/Course/1. Programming Beginner/파이썬 프로그래밍 기초(2)/38차시 4. 문자열 - 연습문제 2.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"tmp = input().split()\n\nprint(*tmp[::-1])"},{"alpha_fraction":0.4427710771560669,"alphanum_fraction":0.45783132314682007,"avg_line_length":21.200000762939453,"blob_id":"b45e1f3596602fda0343822d9f279cc6df6e2b55","content_id":"1016c790054ead630c171542ec4a7acfaa766c1a","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":332,"license_type":"no_license","max_line_length":41,"num_lines":15,"path":"/알고리즘/온라인저지/2022/07/0723/폴리오미노.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"board = input().split('.')\n# print(board)\nresult = ''\nfor i in range(len(board)):\n if len(board[i])%2:\n result = -1\n break\n result += 'AAAA' * (len(board[i])//4)\n if len(board[i])%4:\n result += 'BB'\n if i != len(board)-1:\n result += '.'\n # if b == '':\n # result += '.'\nprint(result)"},{"alpha_fraction":0.5798816680908203,"alphanum_fraction":0.5964497327804565,"avg_line_length":24.636363983154297,"blob_id":"f700b080ff8632ffebd63c839c4583cca59f1a6e","content_id":"0289e2c412d52bd79e3328ed9df2764663cba35e","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1475,"license_type":"no_license","max_line_length":69,"num_lines":33,"path":"/알고리즘/온라인저지/2022/08/0816/쇠막대기.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"B, result, S, j = input(), 0, [], 0 # bar, result, stack, laser index\nL = [i for i in range(1, len(B)) if B[i-1]+B[i] == '()'] # laser\nfor i in range(len(B)):\n if B[i] == '(': S.append(B[i])\n elif B[i] == ')':\n if i == L[j]: \n S.pop()\n result += len(S)\n if j < len(L)-1: j += 1\n else: S.pop(); result += 1\nprint(result)\n\n\"\"\"\n쇠막대기의 시작('(')을 스택에 넣는다\n레이저가 등장하면 등장한 모든 쇠막대기는 잘려나가고\nlen(stack) 만큼의 잘린 부분이 생겨난다\n쇠막대기가 끝나면 바로 직전 레이저에서 잘려나갔기 때문에\n잘린 마지막 파편을 result++ 하고, 스택에서 꺼낸다\n위 과정을 반복하되\n레이저는 시작과 끝에 존재할 수 있으니 조심\n\n<코드 리팩토링>\n레이저인지 확인하는 방법으로\n쇠막대기 입력에서 레이저의 인덱스를 추출하고 저장하였다\n')'가 등장할 때의 인덱스가, 레이저인덱스(L)에 있으면 레이저고\n레이저인덱스에 없으면 레이저가 아닌 닫는 쇠막대기다\n이 레이저인덱스를 확인하는 과정에서 in 연산자를 사용했던\n처음 제출한 코드는 608ms의 시간이 걸렸고\n인덱스를 직접 잡아주는 방식으로 코드를 바꿔주니\n156ms가 걸리면서, 약 4배의 시간단축을 보여주었다\nin이 진짜 느리긴 느리구나.. 실버 상위 문제부터는\n사용하기가 망설여진다\n\"\"\""},{"alpha_fraction":0.4560000002384186,"alphanum_fraction":0.4959999918937683,"avg_line_length":11.5,"blob_id":"5727dc3f42de44389f632e1e85f90cff7d95ce78","content_id":"d1514f23d48eef9574fb83d3d0754f06bfc4be86","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":125,"license_type":"no_license","max_line_length":27,"num_lines":10,"path":"/알고리즘/온라인저지/2022/01/0131/팩토리얼.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = int(input())\n\nresult = 1\n\nif N > 1:\n for i in range(2, N+1):\n result *= i\n print(result)\nelse:\n print(1)\n"},{"alpha_fraction":0.4845132827758789,"alphanum_fraction":0.508849561214447,"avg_line_length":20.571428298950195,"blob_id":"423923f14024b5c7867f1043b30e0623642c4379","content_id":"9ae4bb6f259de670d6fa943e2326c4758f369745","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":630,"license_type":"no_license","max_line_length":44,"num_lines":21,"path":"/알고리즘/온라인저지/2022/03/0307/N과 M (4).py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"def dfs(s, depth):\n global N, M\n\n if depth == M: # M개의 수를 담았을 때\n print(*result[1:]) # *로 언패킹해서 출력\n return # 재귀 탈출\n\n # 아직 M개의 수를 담지 않았을 때\n depth += 1 # 하나 더 고르자\n\n for i in range(s, N+1): # 시작하는 수 s부터 N까지\n result[depth] = i # depth번째 수는 i\n dfs(s, depth) # 한 depth더 들어가기\n s += 1 # 들어갔다 나왔으면 s를 하나 올리기\n\n\nN, M = map(int, input().split())\n\nresult = [0] * (M+1) # 인덱스 맞추기 위한 M+1\n\ndfs(1, 0) # 시작은 1, 깊이는 0부터 시작"},{"alpha_fraction":0.38823530077934265,"alphanum_fraction":0.4117647111415863,"avg_line_length":11.285714149475098,"blob_id":"d8ddeac45dae25d116f633d63f94ec68a0720735","content_id":"c1cfc5e192f87fb931205176dfa20a7a91d87dbd","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":85,"license_type":"no_license","max_line_length":20,"num_lines":7,"path":"/알고리즘/온라인저지/2023/05/0522/末尾の文字 (Last Letter).py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"input()\nS = input()\nif S[-1] == 'G':\n S = S[:len(S)-1]\nelse:\n S += 'G'\nprint(S)"},{"alpha_fraction":0.51171875,"alphanum_fraction":0.53515625,"avg_line_length":22.363636016845703,"blob_id":"ff83b866bf74ee84e2c12dbbeb977a5f8cf0ead1","content_id":"ba8b014e5726aa1edcef68da71ea28d342e1faa7","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":256,"license_type":"no_license","max_line_length":39,"num_lines":11,"path":"/알고리즘/온라인저지/2022/07/0728/베스트셀러.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = int(input())\narr = dict()\nfor n in range(N):\n book = input()\n if book not in arr:\n arr[book] = 1\n else: # book in arr\n arr[book] += 1\nresult = [(a, arr[a]) for a in arr]\nresult.sort(key=lambda x:(-x[1], x[0]))\nprint(result[0][0])"},{"alpha_fraction":0.4858871102333069,"alphanum_fraction":0.49193549156188965,"avg_line_length":26.61111068725586,"blob_id":"ed588628c101b2a57f2d2053901bf053bf7f6355","content_id":"09cda782898f459038bcc6bc11b09f57ffe21602","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":496,"license_type":"no_license","max_line_length":59,"num_lines":18,"path":"/알고리즘/온라인저지/2022/11/1126/기상캐스터.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\nINF = int(1e9)\nH, W = map(int, input().rstrip().split())\nresult = [[INF]*W for _ in range(H)]\narr = [input().rstrip() for _ in range(H)]\nfor i in range(H):\n for j in range(W):\n if arr[i][j] == 'c':\n for k in range(W):\n if j+k < W:\n result[i][j+k] = min(result[i][j+k], k)\nfor i in range(H):\n for j in range(W):\n if result[i][j] == INF:\n result[i][j] = -1\nfor r in result: print(*r)"},{"alpha_fraction":0.4585798680782318,"alphanum_fraction":0.4822485148906708,"avg_line_length":24.461538314819336,"blob_id":"b5d675023456534f33549813ddd29a11444266ef","content_id":"bfc05ec1b2095455a00c26cfe0941665c0646ec7","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":338,"license_type":"no_license","max_line_length":39,"num_lines":13,"path":"/알고리즘/온라인저지/2022/12/1227/3대 측정.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N, K, L = map(int, input().split())\nresult = [0, []]\nfor n in range(N):\n A, B, C = map(int, input().split())\n summ = A + B + C\n minn = min(A, B, C)\n if summ >= K and minn >= L:\n result[0] += 1\n result[1].append(A)\n result[1].append(B)\n result[1].append(C)\nprint(result[0])\nprint(*result[1]) "},{"alpha_fraction":0.6518518328666687,"alphanum_fraction":0.6666666865348816,"avg_line_length":26.200000762939453,"blob_id":"66c20f34d98d555707ddc2725996014ffcd2b13b","content_id":"650c521bbded45a6afd9bbd5a19ccae9f84ea023","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":135,"license_type":"no_license","max_line_length":52,"num_lines":5,"path":"/알고리즘/온라인저지/2022/05/0519/N과 M (2).py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"from itertools import combinations\n\nN, M = map(int, input().split())\nfor i in list(combinations(list(range(1, N+1)), M)):\n print(*i)"},{"alpha_fraction":0.47044631838798523,"alphanum_fraction":0.5054282546043396,"avg_line_length":23.41176414489746,"blob_id":"8b523ddc1783b78c958286e79de0230c4b6510d4","content_id":"bbd064548cffe53384b53bfeb53d311ab709a496","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":899,"license_type":"no_license","max_line_length":63,"num_lines":34,"path":"/알고리즘/온라인저지/2022/10/1002/아기 상어 2.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\nfrom collections import deque\n\ninput = sys.stdin.readline\ndy = [-1, -1, 0, 1, 1, 1, 0, -1] # 12시부터 시계방향\ndx = [0, 1, 1, 1, 0, -1, -1, -1]\n\ndef BFS(i, j):\n visited = [[0]*M for _ in [0]*N]\n Q = deque()\n Q.append((i, j, 0))\n visited[i][j] = 1\n while Q:\n y, x, dist = Q.popleft()\n if arr[y][x]: break\n for k in range(8):\n ny, nx = y+dy[k], x+dx[k]\n if 0<=ny<N and 0<=nx<M and not visited[ny][nx]:\n Q.append((ny, nx, dist+1))\n visited[ny][nx] = 1\n return dist\n\nN, M = map(int, input().rstrip().split())\narr = [list(map(int, input().rstrip().split())) for _ in [0]*N]\nresult = 0\nfor i in range(N):\n for j in range(M):\n result = max(result,BFS(i, j))\nprint(result)\n\n\"\"\"\n매 좌표마다 상어안전거리를 구한다 : brute force\n새 최소값을 매 회마다 갱신한다\n\"\"\""},{"alpha_fraction":0.5189873576164246,"alphanum_fraction":0.5189873576164246,"avg_line_length":14.699999809265137,"blob_id":"b45794a29d8491747869683fe07a39901b7df620","content_id":"5f16ec828277d86c002c39a058a0fe9777be760d","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":158,"license_type":"no_license","max_line_length":43,"num_lines":10,"path":"/알고리즘/SWEA/LEARN/Course/1. Programming Beginner/파이썬 프로그래밍 기초(2)/30차시 3. 자료구조 – 셋, 딕셔너리 - 연습문제 5.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"fruit = [' apple ','banana',' melon']\n\nresult = {}\n\nfor f in fruit:\n f = f.lstrip()\n f = f.rstrip()\n result.update({f:len(f)})\n\nprint(result)\n\n"},{"alpha_fraction":0.45185184478759766,"alphanum_fraction":0.5333333611488342,"avg_line_length":18.428571701049805,"blob_id":"cf5456cd9601d3bbe7ef8c4de2188bb85be45dbb","content_id":"cf1126879f42b55b445e9acb94e00230a7ba17e9","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":135,"license_type":"no_license","max_line_length":35,"num_lines":7,"path":"/알고리즘/온라인저지/2022/08/0810/Site Score.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"S = list(map(int, input().split()))\nC = [56, 24, 14, 6]\nresult = 0\nfor i in range(4):\n result += S[i]*C[i]\n S *= 10\nprint(result)"},{"alpha_fraction":0.6004140973091125,"alphanum_fraction":0.6169772148132324,"avg_line_length":24.473684310913086,"blob_id":"5656ccc00fce2f2d2bff3e570a2e7087b77e4290","content_id":"d6f844d98a7725b20bf052bfb1cba640cd15a191","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":483,"license_type":"no_license","max_line_length":69,"num_lines":19,"path":"/알고리즘/온라인저지/2022/10/1022/종이자르기.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\n\nW, H = map(int, input().rstrip().split())\nrows, cols = [0, H], [0, W]\nN = int(input().rstrip())\nfor n in range(N):\n D, C = map(int, input().rstrip().split()) # direction, coordinate\n if D: cols.append(C)\n else: rows.append(C)\nrows.sort()\ncols.sort()\nwidth, height = 0, 0\nfor i in range(len(rows)-1):\n width = max(width, rows[i+1]-rows[i])\nfor i in range(len(cols)-1):\n height = max(height, cols[i+1]-cols[i])\nprint(width*height)"},{"alpha_fraction":0.5625,"alphanum_fraction":0.581250011920929,"avg_line_length":19.125,"blob_id":"05fe42c5321e844645939c10c3d87bbc0b1dd8a6","content_id":"d13cf8ae43341a7312cf700471c38dfb598f5a6f","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":160,"license_type":"no_license","max_line_length":55,"num_lines":8,"path":"/알고리즘/온라인저지/2022/07/0715/탄산 음료.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"E, F, C = map(int, input().split()) # empty find change\nresult = 0\nbottle = E+F\nwhile bottle >= C:\n result += 1\n bottle -= C\n bottle += 1\nprint(result)"},{"alpha_fraction":0.26377952098846436,"alphanum_fraction":0.29527559876441956,"avg_line_length":14,"blob_id":"b9fbb6d961f9a2d9566498a3a58185aa1aa149dc","content_id":"bcb9f4f102d2c3429c11f5b93084a331d9e7bbee","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":254,"license_type":"no_license","max_line_length":35,"num_lines":17,"path":"/알고리즘/온라인저지/2023/02/0225/명장 남정훈.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"L, R, A = map(int, input().split())\n\nwhile A:\n if L > R:\n R += 1\n A -= 1\n elif L < R:\n L += 1\n A -= 1\n else:\n if A == 1:\n break\n else:\n L += 1\n A -= 1\n\nprint(min(L, R)*2)"},{"alpha_fraction":0.43617022037506104,"alphanum_fraction":0.46072012186050415,"avg_line_length":21.236364364624023,"blob_id":"135b4507d32569caa05fc9bb53520c10d28bf6ef","content_id":"f28a68652aab3e2f182025ee2b961333d9c9e5ee","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1232,"license_type":"no_license","max_line_length":61,"num_lines":55,"path":"/알고리즘/SWEA/LEARN/Course/2. Programming Intermediate/5. 파이썬 SW문제해결 기본 Stack2/7차시 5일차 - 배열 최소 합.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"def dfs(N, depth, tmp):\n global result\n if N == depth :\n if tmp < result:\n result = tmp\n \n if tmp > result:\n return\n else:\n for i in range(N):\n if visited[i] == 0:\n visited[i] = 1\n dfs(N, depth+1, tmp+arr[depth][i])\n visited[i] = 0\n \nT = int(input())\nfor t in range(1, T+1):\n N = int(input())\n arr = [list(map(int, input().split())) for _ in range(N)]\n visited = [0]*N\n \n depth = 0\n result = 10*N\n \n dfs(N, 0, 0)\n print('#{} {}'.format(t, result))\n\n\n\"\"\"\n2022-09-01에 다시 풀음\ndef dfs(level):\n global result, tmp\n if level == N:\n result = min(result, tmp)\n return\n if tmp > result: return\n for i in range(N): \n # print(level, i, arr[level][i])\n if not visited[i]:\n tmp += arr[level][i]\n visited[i] = 1\n dfs(level+1)\n tmp -= arr[level][i]\n visited[i] = 0\n\nfor t in range(1, int(input())+1):\n N = int(input())\n arr = [list(map(int, input().split())) for _ in range(N)]\n # for a in arr: print(a)\n visited = [0] * N\n result = int(1e9)\n tmp = 0\n dfs(0)\n print('#{} {}'.format(t, result))\n\"\"\""},{"alpha_fraction":0.5841270089149475,"alphanum_fraction":0.5841270089149475,"avg_line_length":23.30769157409668,"blob_id":"d2e751895220c69fd8d09932b02e41aa6a698747","content_id":"3bc76cdbe11369b994895155ce9069d4bf493cf6","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":315,"license_type":"no_license","max_line_length":40,"num_lines":13,"path":"/알고리즘/온라인저지/2022/07/0729/대칭 차집합.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"A, B = map(int, input().split())\nA_list = list(map(int, input().split()))\nA_set = set(A_list)\nB_list = list(map(int, input().split()))\nB_set = set(B_list)\nresult = []\nfor a in A_list:\n if a not in B_set:\n result.append(a)\nfor b in B_list:\n if b not in A_set:\n result.append(b)\nprint(len(result))"},{"alpha_fraction":0.351005494594574,"alphanum_fraction":0.35283362865448,"avg_line_length":19.884614944458008,"blob_id":"5389ecc35c91ed4ac9ec61061dd4c17202329c9e","content_id":"771d947536fe3653be95cb1c2e671bd9ffe471d4","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":579,"license_type":"no_license","max_line_length":60,"num_lines":26,"path":"/알고리즘/온라인저지/2021/09/0905/균형잡힌 세상.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"bracket = {\n ')': '(',\n '}': '{',\n ']': '[',\n}\n\nwhile True:\n sen = input() # sys.stdin.readline() 쓰니까 종료조건을 회피하지 못하더라\n if sen == '.':\n break\n stack = []\n for s in sen:\n if s in '[{(':\n stack.append(s)\n elif s in ')}]':\n if stack:\n if bracket[s] == stack[-1]:\n stack.pop()\n else:\n stack.append(s)\n else:\n stack.append(s)\n if stack:\n print('no')\n else:\n print('yes')\n "},{"alpha_fraction":0.5792349576950073,"alphanum_fraction":0.5846994519233704,"avg_line_length":15.727272987365723,"blob_id":"9efababed0f87f34dd080672c7febe1e107d3a36","content_id":"13e8c2b663b2a740a5e7cb509832fb6c73f58bea","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":183,"license_type":"no_license","max_line_length":43,"num_lines":11,"path":"/알고리즘/온라인저지/2022/07/0726/귀찮음.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\n\nN = int(input())\nP = sorted(list(map(int, input().split())))\nresult, S = 0, sum(P)\nfor p in P:\n result += p * (S-p)\n S -= p\nprint(result)"},{"alpha_fraction":0.2741433084011078,"alphanum_fraction":0.30841121077537537,"avg_line_length":12.391304016113281,"blob_id":"d718d4c5ed37facaaf6461d05c82f8a03b6cf98c","content_id":"2be348ccedfd89cfd99a5809b796d43203f42a81","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":321,"license_type":"no_license","max_line_length":36,"num_lines":23,"path":"/알고리즘/온라인저지/2022/02/0201/하얀 칸.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"i = 1\n\nresult = 0\n\nfor _ in range(8):\n line = input()\n\n j = 1\n\n for l in line:\n if i%2:\n if j%2 and l == 'F':\n result += 1\n \n else:\n if not j%2 and l == 'F':\n result += 1\n \n j += 1\n \n i += 1\n\nprint(result)\n \n "},{"alpha_fraction":0.2732732594013214,"alphanum_fraction":0.39039039611816406,"avg_line_length":10.066666603088379,"blob_id":"28b268a28a1f446198d2c7d004f2585000a6f4b4","content_id":"a09525f598db7b1c4733143cafd2b84781204e9e","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":333,"license_type":"no_license","max_line_length":33,"num_lines":30,"path":"/알고리즘/온라인저지/2022/01/0104/2×n 타일링 2.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = int(input())\n\ndp = [0 for _ in range(N+1)]\n\ndp[1] = 1\nif N >= 2:\n dp[2] = 3\n if N == 2:\n print(dp[2])\n exit()\nif N >= 3:\n dp[3] = 5\n if N == 3:\n print(dp[3])\n exit()\n\nfor i in range(4, N+1):\n dp[i] = dp[i-1] + dp[i-2] * 2\n\nprint(dp[N]%10007)\n\n# 0\n# 1\n# 3\n# 5\n# 11\n# 21\n# 43\n# 85\n# 171\n\n"},{"alpha_fraction":0.4626334607601166,"alphanum_fraction":0.4839857518672943,"avg_line_length":12.428571701049805,"blob_id":"f3b5808de2af6f929c3bb35a87784d8e27b38b35","content_id":"ac388b59e6cb072b16fa3274a9263c384a9ca452","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":281,"license_type":"no_license","max_line_length":26,"num_lines":21,"path":"/알고리즘/온라인저지/2022/10/1012/수 이어 쓰기 1.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\n\nN = int(input().rstrip())\nD = 9\nsep = []\nwhile True:\n if N >= D:\n sep.append(D)\n N -= D\n D *= 10\n else:\n sep.append(N)\n break\nresult = 0\ni = 1\nfor s in sep: \n result += i*s\n i += 1\nprint(result)"},{"alpha_fraction":0.3025210201740265,"alphanum_fraction":0.3235294222831726,"avg_line_length":25.44444465637207,"blob_id":"e6277b30e4fc7e8a35d8a080d1cf51687447a491","content_id":"99da6e60f7674adbd4da1fb615eb23342721dc6d","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":952,"license_type":"no_license","max_line_length":42,"num_lines":36,"path":"/알고리즘/온라인저지/2021/09/0908/프린터 큐.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\ndef input():\n return sys.stdin.readline()\n\nT = int(input())\nfor t in range(T):\n N, M = map(int, input().split())\n docs = list(map(int, input().split()))\n cnt = 0\n end = True\n while end:\n if docs[M] != max(docs):\n if docs[0] != max(docs):\n docs.append(docs.pop(0))\n M -= 1\n if M < 0:\n M += N\n else: # docs[0] == max(docs)\n docs.pop(0)\n cnt += 1\n N -= 1\n M -= 1 \n else: # docs[M] == max(docs)\n if M != 0:\n if docs[0] == docs[M]:\n docs.pop(0)\n cnt += 1\n M -= 1\n else: # docs[0] != docs[M]\n docs.pop(0)\n M -= 1\n else: # M == 0\n cnt += 1\n end = False\n break\n print(cnt)\n"},{"alpha_fraction":0.5416666865348816,"alphanum_fraction":0.5572916865348816,"avg_line_length":18.299999237060547,"blob_id":"8c8bb12f2f8e8519e155f6d3d494ca0c2d372173","content_id":"2c31c9c5b85a016342bb921fd52c8ac9a54f0878","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":192,"license_type":"no_license","max_line_length":32,"num_lines":10,"path":"/알고리즘/온라인저지/2021/08/0802/쉽게 푸는 문제.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"A, B = map(int, input().split())\nnumbers = []\nfor i in range(1, B+2):\n for j in range(i):\n numbers.append(i)\nls = []\nfor i in range(A-1, B):\n ls.append(numbers[i])\n\nprint(sum(ls))"},{"alpha_fraction":0.4839743673801422,"alphanum_fraction":0.5256410241127014,"avg_line_length":21.35714340209961,"blob_id":"5de89e8473a4126b47d44360cbf370b1e4cb0d5d","content_id":"1b00554f47b389f94b22363138a3d9f46d17b8da","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":312,"license_type":"no_license","max_line_length":62,"num_lines":14,"path":"/알고리즘/온라인저지/2022/11/1118/좋은 자동차 번호판.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\n\nfor _ in range(int(input().rstrip())):\n number = input().rstrip()\n front = number[:3]\n rear = number[4:]\n tmp = 0\n j = 0\n for f in front[::-1]:\n tmp += 26**j*(ord(f)-65)\n j += 1\n print('nice' if abs(tmp-int(rear)) <= 100 else 'not nice')"},{"alpha_fraction":0.5081967115402222,"alphanum_fraction":0.5245901346206665,"avg_line_length":30,"blob_id":"4d41bf1041cea1f4c1830ea1eaed491db541b828","content_id":"21b62b699e0561e07bc396aa1ee332473d61fea4","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":61,"license_type":"no_license","max_line_length":35,"num_lines":2,"path":"/알고리즘/온라인저지/2023/02/0209/WARBOY.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"A, B, C = map(int, input().split())\nprint(eval('C*3*(B//A)'))"},{"alpha_fraction":0.4615384638309479,"alphanum_fraction":0.4615384638309479,"avg_line_length":18.5625,"blob_id":"804c5a2af7ddb14784ae35df2162fbde344d4f2a","content_id":"b85ad088ea9778ee02ebfa8a8bd7c9a540aaa38e","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":312,"license_type":"no_license","max_line_length":49,"num_lines":16,"path":"/알고리즘/온라인저지/2022/10/1027/치킨 쿠폰.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\n\nwhile True:\n try:\n N, K = map(int, input().rstrip().split())\n result = N\n stamp = N\n while stamp>=K:\n tmp = stamp//K\n stamp %= K\n result += tmp\n stamp += tmp\n print(result)\n except: break"},{"alpha_fraction":0.4871794879436493,"alphanum_fraction":0.5192307829856873,"avg_line_length":25.16666603088379,"blob_id":"b37c146e11723be6e0547c43baacd05f7da73177","content_id":"a160a2216c7f4b8e5ed99aa6aba4bdb89d40a49f","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":156,"license_type":"no_license","max_line_length":44,"num_lines":6,"path":"/알고리즘/온라인저지/2023/01/0120/삼각수의 합.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"for _ in range(int(input())):\n N = int(input())\n result = 0\n for k in range(1, N+1):\n result += k*sum(list(range(1, k+2)))\n print(result)"},{"alpha_fraction":0.46612149477005005,"alphanum_fraction":0.4754672944545746,"avg_line_length":21.526315689086914,"blob_id":"8b484550b4bfef6ee0be15cd610492e0fd364835","content_id":"e05db2367aa6e0630341b096c10e0841c870863f","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":856,"license_type":"no_license","max_line_length":54,"num_lines":38,"path":"/알고리즘/온라인저지/2022/07/0703/test.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"def dfs(start):\n global is_dfs, result, visited\n print(start)\n if start == 1:\n for j in arr[1]:\n result = []\n visited = [True] + [False] * N \n visited[start] = True\n result.append(start)\n dfs(j)\n tmp.append(result)\n if result == answer:\n is_dfs = True\n else:\n visited[start] = True\n result.append(start)\n for i in arr[start]:\n if not visited[i]:\n dfs(i)\n\nN = int(input())\narr = [[] for _ in range(N+1)]\nfor n in range(N-1):\n s, e = map(int, input().split())\n arr[s].append(e)\n arr[e].append(s)\nanswer = list(map(int, input().split()))[::-1]\nis_dfs = False\nresult = []\ntmp = []\nvisited = [True] + [False] * N\ntmp = []\ndfs(1)\nprint(tmp)\nif is_dfs:\n print(1)\nelse:\n print(0)\n"},{"alpha_fraction":0.42702701687812805,"alphanum_fraction":0.5027027130126953,"avg_line_length":25.5,"blob_id":"e78d2f4475de576407e092e2eb17a8937ace5594","content_id":"ba43116ef0143428dc9417eb823c109973c2c845","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":398,"license_type":"no_license","max_line_length":55,"num_lines":14,"path":"/알고리즘/[템플릿]/Dynamic Programming/계단 오르기.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = int(input())\nS = [0 for _ in range(301)] # stairs \ndp = [0 for _ in range(301)] # 미리 선언하여 N<=3 일 때 에러를 방지함\nfor i in range(N): S[i] = int(input())\ndp[0] = S[0]\ndp[1] = S[0] + S[1]\ndp[2] = max(S[1]+S[2], S[0]+S[2])\nfor i in range(3, N):\n A = dp[i-3] + S[i-1] + S[i]\n B = dp[i-2] + S[i]\n dp[i] = max(A, B)\nprint(dp[N-1])\n\n# https://www.acmicpc.net/problem/2579"},{"alpha_fraction":0.5869565010070801,"alphanum_fraction":0.602173924446106,"avg_line_length":34.46154022216797,"blob_id":"4c972b8f9953bfd2311707560877b896010ea685","content_id":"a2f31c245bdf2da6cdcd9e44b2fd5050b884b2ac","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":644,"license_type":"no_license","max_line_length":81,"num_lines":13,"path":"/알고리즘/온라인저지/2022/09/0927/부분수열의 합.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\n\nN, S = map(int, input().rstrip().split())\narr = list(map(int, input().rstrip().split()))\nresult = 0\nfor i in range(1<<N): # N개의 원소를 포함한다, 안한다의 경우가 있으므로 총 경우의 수는 1<<N == 2**N\n seq = [] # 부분수열 초기화\n for j in range(N): # N개 원소들에 대하여 부분수열인지 확인\n if i&(1<<j): seq.append(arr[j]) # &연산을 거친 값이 True라면, j번째 원소는 부분수열에 존재한다\n if sum(seq) == S and len(seq) != 0: result += 1 # 공집합이 아니면서, 부분수열의 합이 S이면 카운트\nprint(result)"},{"alpha_fraction":0.5051020383834839,"alphanum_fraction":0.5204081535339355,"avg_line_length":18.700000762939453,"blob_id":"f76fbaf731e5ac896de99dda409f31b888404c9d","content_id":"6f9133bc61c9b364a942f2cee06ce58e9b7f7316","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":196,"license_type":"no_license","max_line_length":37,"num_lines":10,"path":"/알고리즘/온라인저지/2022/05/0529/수빈이와 수열.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = int(input())\narr = list(map(int, input().split()))\n# print(arr)\nfor i in range(N):\n arr[i] *= i+1\n# print(arr)\nif N > 0:\n for i in range(1, N):\n arr[i] -= sum(arr[:i])\nprint(*arr)"},{"alpha_fraction":0.40740740299224854,"alphanum_fraction":0.4444444477558136,"avg_line_length":15.399999618530273,"blob_id":"5a94c070f0c057635141a9fe7471796e9f0cfc09","content_id":"78ad9fb612b4e9fbc22373d6439d9cbb5a1b918c","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":81,"license_type":"no_license","max_line_length":23,"num_lines":5,"path":"/알고리즘/온라인저지/2023/05/0524/Gömda ord.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"S = input()\ni = 0\nwhile i < len(S):\n print(S[i], end='')\n i += ord(S[i])-64"},{"alpha_fraction":0.5045045018196106,"alphanum_fraction":0.522522509098053,"avg_line_length":22.421052932739258,"blob_id":"9c7da66eaba53648b2d64ff39456a63d652c048d","content_id":"6a50bcfce6adc29477389f9d66068a14f5f01a10","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":772,"license_type":"no_license","max_line_length":38,"num_lines":19,"path":"/알고리즘/온라인저지/2021/10/1003/무한이진트리.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"a, b = map(int, input().split()) # 끝노드\n\n# 시작노드에서 왼쪽으로 내려가면 a가 커지고\n# 오른쪽으로 내려가면 b가 커진다\n# 주어진 (a, b)노드에서 a가 크면 왼쪽으로 내려온 노드\n# b가 크면 오른쪽으로 내려온 노드임을 알 수 있다\n# 이를 이용해 (a, b)에서 (1, 1)까지 거꾸로 올라간다\n\nl = r = 0 # 올라가면서 체크할 왼쪽 오른쪽 이동 횟수\n\nwhile a+b != 2: # 루트노드에 도달할 때 까지\n if a > b: # 왼쪽으로 내려왔던 노드이면\n a -= b # 부모노드의 a\n l += 1 # 왼쪽 카운트 +1\n elif a < b: # 오른쪽으로 내려왔던 노드이면\n b -= a # 부모노드의 b\n r += 1 # 오른쪽 카운트 +1\n\nprint(l, r) # 출력"},{"alpha_fraction":0.4974271059036255,"alphanum_fraction":0.5403087735176086,"avg_line_length":21.461538314819336,"blob_id":"bedab36d73699ed8a4f33bfa5a3f553ee83f9267","content_id":"7926594e4824120282c82228fc2019c639ea6429","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":583,"license_type":"no_license","max_line_length":64,"num_lines":26,"path":"/알고리즘/온라인저지/2023/01/0114/숨바꼭질 3.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"from heapq import heappush, heappop\n\nN, K = map(int, input().split())\nQ = [(0, N)]\nvisited = [int(1e9)]*(int(1e6)+1)\nvisited[N] = 0\nwhile Q:\n time, now = heappop(Q)\n go, back, jump = max(0, now+1), max(0, now-1), max(0, now*2)\n\n if now == K:\n break\n\n if visited[go] > time+1:\n visited[go] = time+1\n heappush(Q, (time+1, go))\n\n if visited[back] > time+1:\n visited[back] = time+1\n heappush(Q, (time+1, back))\n \n if visited[jump] > time and jump<=100000:\n visited[jump] = time\n heappush(Q, (time, jump))\n\nprint(time)"},{"alpha_fraction":0.5367646813392639,"alphanum_fraction":0.5808823704719543,"avg_line_length":16.125,"blob_id":"ede47a184c3cbccd5c80ea47ac04168bf8199a75","content_id":"858755e24bc6dd0c7f896c18205492fdced4985b","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":136,"license_type":"no_license","max_line_length":20,"num_lines":8,"path":"/알고리즘/온라인저지/2023/04/0426/Covid-19.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"result = 'Yellow'\np = int(input())\nq = int(input())\nif p<=50 and q<=10:\n result = 'White'\nelif q>30:\n result = 'Red'\nprint(result)"},{"alpha_fraction":0.5107526779174805,"alphanum_fraction":0.5215053558349609,"avg_line_length":14.583333015441895,"blob_id":"9749ff6e6df404d7c8b48fafdccb0472ec503475","content_id":"b35f547d9ff358abe44a928562996fae89c27d8c","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":186,"license_type":"no_license","max_line_length":27,"num_lines":12,"path":"/알고리즘/온라인저지/2023/05/0507/골뱅이 찍기 - 돌아간 ㅍ.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"def new_print(line):\n for _ in range(N):\n print(line)\n\nN = int(input())\nA = '@'*N + ' '*3*N + '@'*N\nB = '@'*N*5\nnew_print(A)\nnew_print(B)\nnew_print(A)\nnew_print(B)\nnew_print(A)"},{"alpha_fraction":0.5596330165863037,"alphanum_fraction":0.5688073635101318,"avg_line_length":21,"blob_id":"765e3806800e17b0909bb65c1b6eca9444ce7c29","content_id":"1035a17b589c42898a8c2cbf2a59d52cb92ba224","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":109,"license_type":"no_license","max_line_length":36,"num_lines":5,"path":"/알고리즘/온라인저지/2023/01/0119/謎紛芥索紀 (Small).py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"result = 0\nfor _ in range(int(input())):\n A, B = map(int, input().split())\n result += A*B\nprint(result)"},{"alpha_fraction":0.5743243098258972,"alphanum_fraction":0.587837815284729,"avg_line_length":20.285715103149414,"blob_id":"a99af847b7922f62c9249d6d80edcb7394500c44","content_id":"a0abe24cfcd058f9b0b5871ea2d6423e9b665239","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":148,"license_type":"no_license","max_line_length":45,"num_lines":7,"path":"/알고리즘/온라인저지/2022/11/1122/쿠키애호가.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\n\nfor _ in range(int(input().rstrip())):\n N, C = map(int, input().rstrip().split())\n print((N-1)//C + 1)"},{"alpha_fraction":0.48322147130966187,"alphanum_fraction":0.4899328947067261,"avg_line_length":15.666666984558105,"blob_id":"394b3f5a09da0c587816dbd81dc3ce587daa1042","content_id":"7a596ad3b0f8be6f14db10cf3ea4c19c139a95e0","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":149,"license_type":"no_license","max_line_length":31,"num_lines":9,"path":"/알고리즘/온라인저지/2023/03/0325/골뱅이 찍기 - 정사각형.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = int(input())\narr = []\nA, B = '@'*(N+2), '@'+' '*N+'@'\narr.append(A)\nfor _ in range(N):\n arr.append(B)\narr.append(A)\nfor a in arr:\n print(a)"},{"alpha_fraction":0.40514469146728516,"alphanum_fraction":0.4244372844696045,"avg_line_length":25,"blob_id":"6bcab918b29c0cc0e41a1d49dadc74d74a0dd5e6","content_id":"65a60d7271a1e37d14e7e5db89002243889bb697","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":311,"license_type":"no_license","max_line_length":38,"num_lines":12,"path":"/알고리즘/온라인저지/2022/03/0329/J박스.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"T = int(input())\nfor t in range(T):\n N = int(input())\n jbox = [['J']*N for _ in range(N)]\n jbox[0] = jbox[-1] = ['#']*N\n for i in range(1, N-1):\n jbox[i][0] = jbox[i][-1] = '#'\n for i in range(N):\n for j in range(N):\n print(jbox[i][j], end='')\n print()\n print()"},{"alpha_fraction":0.5210526585578918,"alphanum_fraction":0.5368421077728271,"avg_line_length":26.285715103149414,"blob_id":"975d2257e76aac02f51262c9e04c0fd238284d5a","content_id":"bbb0abd27461e4642ac3edaf54a0ba37c8b6b992","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":190,"license_type":"no_license","max_line_length":45,"num_lines":7,"path":"/알고리즘/온라인저지/2022/08/0804/럭키 스트레이트.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = input()\nM = len(N)//2 # middle\nF, B = N[:M], N[M:] # front, back\nF_int, B_int = 0, 0\nfor f in F: F_int += int(f)\nfor b in B: B_int += int(b)\nprint('LUCKY' if F_int == B_int else 'READY')"},{"alpha_fraction":0.4161849617958069,"alphanum_fraction":0.4393063485622406,"avg_line_length":18.22222137451172,"blob_id":"3c6f10a8c922f09d4c945d730531b48d43bbcff0","content_id":"7329872dddc97da0a947eb7b74a0102a478f0c36","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":173,"license_type":"no_license","max_line_length":39,"num_lines":9,"path":"/알고리즘/온라인저지/2021/12/1230/트리 만들기.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"n, m = map(int, input().split())\n\nfor i in range(n-1):\n if i >= n-m+1:\n print('{} {}'.format(n-m, i+1))\n continue\n \n print(i, end=' ')\n print(i+1)\n"},{"alpha_fraction":0.5315126180648804,"alphanum_fraction":0.5441176295280457,"avg_line_length":20.68181800842285,"blob_id":"cb2b0db2bcba2a91c20932ce159717a4ca3f8fd2","content_id":"552a0da153073f5a618b9bffd161f5cf864f87c2","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":740,"license_type":"no_license","max_line_length":57,"num_lines":22,"path":"/알고리즘/온라인저지/2021/08/0807/링.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"\"\"\"\n8 4 2의 지름이 각각 같아야한다\n파이를 생략하고\n반지름 각각 A, B, C, ...\n각각의 바퀴수는 A / B\n이 바퀴수를 기약분수형태로 출력\nA/B A/C ... \n테스트케이스 개수 T\n\"\"\"\n\nT = int(input()) # 테스트케이스 개수, 쓰지는 않았다\nrs = list(map(int, input().split())) # 반지름 들 입력받아서 list()\n\ndef gcd(x, y): # 최대공약수 구하는 함수, 유클리드 호제법\n while y:\n x, y = y, x % y\n return x\n\nfor i in range(1, len(rs)): # 첫 링 제외하고 링의 반지름들 순회\n gcd_rs = gcd(rs[0], rs[i]) # 반지름들의 최대공약수 구해서\n print(f'{rs[0] // gcd_rs}/{rs[i] // gcd_rs}')\n # 각 링들을 기약분수 형태로 출력"},{"alpha_fraction":0.5203620195388794,"alphanum_fraction":0.5429864525794983,"avg_line_length":21.200000762939453,"blob_id":"fc1819857a0d41e83a146329b48f7cf1fc8bab9c","content_id":"31e3a71f061e51cb5d8d5704cbfb31775dc2a5c8","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":221,"license_type":"no_license","max_line_length":36,"num_lines":10,"path":"/알고리즘/온라인저지/2021/08/0816/카드1.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = int(input())\ndeck = list(range(1, N+1))\nnew_deck = []\nfor n in range(N):\n if len(deck) == 1:\n new_deck += deck\n else:\n new_deck.append(deck.pop(0))\n deck.append(deck.pop(0))\nprint(*new_deck)"},{"alpha_fraction":0.5535714030265808,"alphanum_fraction":0.5714285969734192,"avg_line_length":15.142857551574707,"blob_id":"c730d281ddd10286cc81c5aa565e29fc1656cbda","content_id":"91dcb474f695881ba0a3aae1cfba440e2a6430d6","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":112,"license_type":"no_license","max_line_length":22,"num_lines":7,"path":"/알고리즘/온라인저지/2022/03/0319/팬들에게 둘러싸인 홍준.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"name = ':'+input()+':'\nfan = ':fan:'\nprint(fan*3)\nprint(fan, end='')\nprint(name, end='')\nprint(fan)\nprint(fan*3)"},{"alpha_fraction":0.4375655949115753,"alphanum_fraction":0.45802727341651917,"avg_line_length":25.48611068725586,"blob_id":"3f84f5f0c5f621805d16cb3efff7205baacf45d8","content_id":"00f01995da28c777ccd05aedbbcf18d578b49c7d","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":2014,"license_type":"no_license","max_line_length":67,"num_lines":72,"path":"/알고리즘/SW역량테스트/2022.03.15 A형.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"\"\"\"\n어딜 갈 수 있는가\n잡기 전\n1 2 3\n1을 잡은 후\n2 3 -1\n3을 잡은 후\n2 -1 -3\n\ndfs돌 필요도 없다 좌표찾고 더하기빼기로도 가능\n\n가지고 있는 최소값보다 커지면 가지치기\n\"\"\"\nimport tabnanny\n\n\ndef dfs(c, y, x, h, can_go):\n global monster_visited, customer_visited, minn\n # print(c)\n for mnc in monsters_and_customers:\n if mnc[0] == c:\n h += abs(y-mnc[1]) + abs(x-mnc[2])\n if h > minn:\n continue\n y = mnc[1]\n x = mnc[2]\n if c > 0:\n can_go.append((can_go.pop(can_go.index(c)) * (-1)))\n elif c < 0:\n can_go.pop(can_go.index(c))\n if not can_go:\n if h < minn:\n minn = h\n # print('renew minn!!', minn)\n\n # print(can_go)\n for g in can_go:\n if g > 0:\n if not monster_visited[g-1]:\n dfs(g, y, x, h, can_go)\n elif g < 0:\n if not customer_visited[g*(-1)-1]:\n dfs(g, y, x, h, can_go)\n\n\nT = int(input())\nfor t in range(1, T+1):\n N = int(input())\n arr = []\n how_many_customer = 0\n for n in range(N):\n tmp = list(map(int, input().split()))\n if max(tmp) > how_many_customer:\n how_many_customer = max(tmp)\n arr.append(tmp)\n # print(how_many_customer)\n monsters_and_customers = []\n for i in range(N):\n for j in range(N):\n if arr[i][j] != 0:\n monsters_and_customers.append([arr[i][j], i, j])\n # print(monsters_and_customers)\n monsters = list(range(1, how_many_customer+1))\n # print(monsters)\n minn = 10**6\n for m in monsters:\n monster_visited = [0] * how_many_customer\n customer_visited = [0] * how_many_customer\n h = 0\n x = y = 0 \n dfs(m, y, x, h, list(range(1, how_many_customer+1)))\n print('#{} {}'.format(t, minn))"},{"alpha_fraction":0.38434162735939026,"alphanum_fraction":0.41281139850616455,"avg_line_length":20.69230842590332,"blob_id":"2d011cc0192baa79d0d1de7095a3565f76391c28","content_id":"b39abe6774776d1188633ec7f584be2364f7a02e","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":281,"license_type":"no_license","max_line_length":37,"num_lines":13,"path":"/알고리즘/온라인저지/2022/09/0910/연속구간.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"for _ in range(3):\n num = input()\n prev = num[0]\n tmp = 1\n result = 1\n for i in range(1, 8):\n if prev == num[i]:\n tmp += 1\n else:\n result = max(result, tmp)\n tmp = 1\n prev = num[i]\n print(max(result, tmp))"},{"alpha_fraction":0.4141414165496826,"alphanum_fraction":0.4343434274196625,"avg_line_length":18.799999237060547,"blob_id":"b8545d1dafbaa50490cdd27c8cfbba171dd5ca5f","content_id":"389eca97a08bda5a29435854df943b3f5228aa71","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":99,"license_type":"no_license","max_line_length":37,"num_lines":5,"path":"/알고리즘/온라인저지/2022/02/0208/TV 크기.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"D, H, W = map(int, input().split())\n\nC = ((H*H)+(W*W))**0.5\n\nprint(int(D * H / C), int(D * W / C))\n"},{"alpha_fraction":0.5050504803657532,"alphanum_fraction":0.6363636255264282,"avg_line_length":15.666666984558105,"blob_id":"2851c4a56704245b21de115b2258d11a0c3aae10","content_id":"95b18739a64a4fe55be542240351a8b1818eefc0","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":99,"license_type":"no_license","max_line_length":22,"num_lines":6,"path":"/알고리즘/온라인저지/2023/03/0316/Boiling Water.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"P = 5*int(input())-400\nresult = 0\nif P>100: result = -1\nif P<100: result = 1\nprint(P)\nprint(result)"},{"alpha_fraction":0.4259776473045349,"alphanum_fraction":0.4427374303340912,"avg_line_length":24.60714340209961,"blob_id":"e4692880145dc3b5862b6b57c8397c286f77334c","content_id":"fce679379195ee2938ec0367d9b12dd3facd697f","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":716,"license_type":"no_license","max_line_length":44,"num_lines":28,"path":"/알고리즘/온라인저지/2022/07/0714/체스판 다시 칠하기.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"def check_tile(y, x):\n cnt = 0\n switch = False # Black:True, White:False\n for i in range(8):\n for j in range(8):\n tmp = arr[y+i][x+j]\n switch = not switch\n if j == 0:\n switch = not switch\n if switch: # Black\n if tmp == 'W':\n cnt += 1\n elif not switch: # White\n if tmp == 'B':\n cnt += 1\n result = min(cnt, 64-cnt)\n return result\n\n\nN, M = map(int, input().split())\narr = [list(input()) for _ in range(N)]\nresult = 1e9\nfor i in range(N-7):\n for j in range(M-7):\n tmp = check_tile(i, j)\n if tmp < result:\n result = tmp\nprint(result)"},{"alpha_fraction":0.5263158082962036,"alphanum_fraction":0.5263158082962036,"avg_line_length":24.66666603088379,"blob_id":"f6cf29c3b02ff99496ea4be6ca648a5e60fab672","content_id":"9e3e11cf907e9a3b818f82fca56d840e13501d0a","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":76,"license_type":"no_license","max_line_length":29,"num_lines":3,"path":"/알고리즘/온라인저지/2023/02/0223/Time to Decompress.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"for _ in range(int(input())):\n A, B = input().split()\n print(B*int(A))"},{"alpha_fraction":0.4464285671710968,"alphanum_fraction":0.4553571343421936,"avg_line_length":21.600000381469727,"blob_id":"ffa0acd52e59018c8b7f83ff0ee8f4a217055890","content_id":"920b24f3f9d4839e52cbe0d5248fc9e6624145a4","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":112,"license_type":"no_license","max_line_length":36,"num_lines":5,"path":"/알고리즘/온라인저지/2022/04/0428/남욱이의 닭장.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"for t in range(int(input())):\n N, M = map(int, input().split())\n U = M*2 - N\n T = M - U\n print(U, T)"},{"alpha_fraction":0.477761834859848,"alphanum_fraction":0.4964132010936737,"avg_line_length":23.928571701049805,"blob_id":"f564f852e9593ada3ab3f75a7400dd748b443f8a","content_id":"c51cc1c877d3ed2d4d9431d71a1d545dfeb484f0","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":743,"license_type":"no_license","max_line_length":45,"num_lines":28,"path":"/알고리즘/[템플릿]/이분탐색/기타 레슨.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"def binary(start, end):\n global result\n if start > end: return\n Blu_ray = (start + end) // 2\n tmp = [0] * M\n i = 0\n for l in L:\n if tmp[i] + l <= Blu_ray:\n tmp[i] += l\n else:\n i += 1\n try: tmp[i] += l\n except: binary(Blu_ray+1, end)\n if i>=M: break\n if i >= M: # 블루레이 개수가 모자람\n binary(Blu_ray+1, end)\n else: # i < M : 블루레이 크기를 더 줄일 수 있음\n if Blu_ray < result: result = Blu_ray\n binary(start, Blu_ray-1)\n\nN, M = map(int, input().split())\nL = list(map(int, input().split())) # lecture\nS, E = max(L), sum(L)\nresult = int(1e9)\nbinary(S, E)\nprint(result)\n\n# https://www.acmicpc.net/problem/2343"},{"alpha_fraction":0.4312500059604645,"alphanum_fraction":0.46875,"avg_line_length":16.88888931274414,"blob_id":"944784d3c1b7b5138d19afaebcae7a603aa2782a","content_id":"120308a0e85148adb60ba2243cf0f46229004dc7","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":160,"license_type":"no_license","max_line_length":35,"num_lines":9,"path":"/알고리즘/온라인저지/2022/05/0524/대회 or 인턴.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N, M, K = map(int, input().split())\nresult = 0\nwhile True:\n N -= 2\n M -= 1\n if N < 0 or M < 0 or (N+M) < K:\n break\n result += 1\nprint(result)"},{"alpha_fraction":0.4752066135406494,"alphanum_fraction":0.5206611752510071,"avg_line_length":26,"blob_id":"89d8952aace376e4b1a63ed3abe0b192a960279b","content_id":"c4f26dcab171151fcb9a027412c52bc5baf26002","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":242,"license_type":"no_license","max_line_length":34,"num_lines":9,"path":"/알고리즘/온라인저지/2023/05/0526/Hurra!.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"for i in range(1, int(input())+1):\n result = ''\n if not i%7 and i%11:\n result = 'Hurra!'\n if i%7 and not i%11:\n result = 'Super!'\n if not i%7 and not i%11:\n result = 'Wiwat!'\n print(result if result else i)"},{"alpha_fraction":0.5777778029441833,"alphanum_fraction":0.5925925970077515,"avg_line_length":33,"blob_id":"d91695adf060f4055ff573195301c8541df6470a","content_id":"739c486f9b1aaa99037fe57b6afc4679efa485fb","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":135,"license_type":"no_license","max_line_length":58,"num_lines":4,"path":"/알고리즘/온라인저지/2022/07/0714/좌표 정렬하기 2.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = int(input())\narr = [tuple(map(int, input().split())) for _ in range(N)]\narr.sort(key=lambda x:(x[1], x[0]))\nfor a in arr: print(*a)"},{"alpha_fraction":0.5462962985038757,"alphanum_fraction":0.5648148059844971,"avg_line_length":53.5,"blob_id":"b4f3ccef19ef6965e1caef22b97258033b1bb863","content_id":"b229e2d18c02cab0880877c1e09ba771b09788ce","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":108,"license_type":"no_license","max_line_length":73,"num_lines":2,"path":"/알고리즘/온라인저지/2022/03/0323/주사위.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"for t in range(1, int(input())+1):\n print('Case {}: {}'.format(t, sum(tuple(map(int, input().split())))))"},{"alpha_fraction":0.4819277226924896,"alphanum_fraction":0.4819277226924896,"avg_line_length":19.83333396911621,"blob_id":"65b4d3967ee67845517d14fa1fff3523fac7fa3e","content_id":"3c6d7c104b55581c40f14a89e3c006ce0e8d93e0","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":249,"license_type":"no_license","max_line_length":40,"num_lines":12,"path":"/알고리즘/온라인저지/2022/06/0622/스캐너.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"R, C, ZR, ZC = map(int, input().split())\nresult = []\nfor r in range(R):\n tmp = input()\n a = ''\n for t in tmp:\n for zc in range(ZC):\n a = a + t\n for zr in range(ZR):\n result.append(a)\nfor r in result:\n print(r)"},{"alpha_fraction":0.6186440587043762,"alphanum_fraction":0.6186440587043762,"avg_line_length":22.799999237060547,"blob_id":"9e78bae6d849710cdd29da26e51a1d63771b3421","content_id":"19df9d8f4d961f7b47d0d7ba5282e6280109b39a","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":118,"license_type":"no_license","max_line_length":35,"num_lines":5,"path":"/알고리즘/온라인저지/2023/06/0609/정보섬의 대중교통.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N, A, B = map(int, input().split())\nresult = 'Anything'\nif A>B: result = 'Subway'\nif A<B: result = 'Bus'\nprint(result)"},{"alpha_fraction":0.359281450510025,"alphanum_fraction":0.359281450510025,"avg_line_length":17.66666603088379,"blob_id":"fe79171095303e80d80e4fe9e9bd04c3549621d5","content_id":"df71cbef3af4590c9fadfefaa7fbe69d1e9b3b39","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":167,"license_type":"no_license","max_line_length":27,"num_lines":9,"path":"/알고리즘/온라인저지/2022/12/1225/연길이의 이상형.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"yeongil = input()\ndictt = {\n 'E': 'I', 'I':'E',\n 'S': 'N', 'N':'S',\n 'T': 'F', 'F':'T',\n 'J': 'P', 'P':'J',\n}\nfor y in yeongil:\n print(dictt[y], end='')"},{"alpha_fraction":0.4533762037754059,"alphanum_fraction":0.4887459874153137,"avg_line_length":16.33333396911621,"blob_id":"5ffacf7db43de070240c1390ae0e402be69fe67c","content_id":"962039166d8c4452747d5c610a12e161cf33eb3d","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":311,"license_type":"no_license","max_line_length":33,"num_lines":18,"path":"/알고리즘/온라인저지/2023/05/0512/Don’t pass me the ball!.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"def dfs(size, idx):\n global result\n\n if arr[2] != 0:\n result += 1\n return\n\n for player in range(size, N):\n if player not in arr:\n arr[idx] = player\n dfs(player+1, idx+1)\n arr[idx] = 0\n\nN = int(input())\narr = [0]*3\nresult = 0\ndfs(1, 0)\nprint(result)"},{"alpha_fraction":0.443452388048172,"alphanum_fraction":0.449404776096344,"avg_line_length":15.800000190734863,"blob_id":"45aab3a7faca59934bd86f2c08252c6b76e3e390","content_id":"e4e2f308e21d3e4a2daeec2c912e648b58f13eae","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":336,"license_type":"no_license","max_line_length":32,"num_lines":20,"path":"/알고리즘/온라인저지/2022/02/0201/명령 프롬프트.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = int(input())\n\ninputs = [''] * N\n\nfor i in range(N):\n inputs[i] = input()\n\nfor i in range(len(inputs[0])):\n flag = True\n word = inputs[0][i]\n\n for j in range(N):\n if word != inputs[j][i]:\n flag = False\n break\n \n if flag:\n print(word, end='')\n else:\n print('?', end='')\n"},{"alpha_fraction":0.5428571701049805,"alphanum_fraction":0.5857142806053162,"avg_line_length":14.666666984558105,"blob_id":"3f550a2448527c5f254d1d25aeb3a8cb3e15660e","content_id":"77b3679fbd4542793cfc3a846989b1ce587d2d27","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":140,"license_type":"no_license","max_line_length":36,"num_lines":9,"path":"/알고리즘/온라인저지/2022/12/1205/피보나치 수.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\n\nN = int(input().rstrip())\nmod = int(1e9)+7\na, b = 1, 1\nfor _ in range(N-2): a, b = b, (a+b)\nprint(b)"},{"alpha_fraction":0.3098958432674408,"alphanum_fraction":0.3151041567325592,"avg_line_length":20.38888931274414,"blob_id":"f4d6dc40eb26aa7b795a83c9414bfa1e789524bf","content_id":"b3a663e427f355581771035efa44be48aac45d77","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":384,"license_type":"no_license","max_line_length":31,"num_lines":18,"path":"/알고리즘/온라인저지/2022/07/0725/부분 문자열.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"while True:\n try:\n S, T = input().split()\n j = 0\n tmp = ''\n result = 'No'\n for i in range(len(T)):\n if T[i] == S[j]:\n tmp += T[i]\n j += 1\n if j >= len(S):\n break\n # print(tmp)\n if tmp == S:\n result = 'Yes'\n print(result)\n except:\n exit()"},{"alpha_fraction":0.43877550959587097,"alphanum_fraction":0.4413265287876129,"avg_line_length":22.117647171020508,"blob_id":"0e47b41cbdc1747fa9ca97a1c3bc23693338d6ee","content_id":"501ebbfc931611c33abbf0cd85ff017b9a782d5b","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":512,"license_type":"no_license","max_line_length":56,"num_lines":17,"path":"/알고리즘/온라인저지/2022/08/0816/괄호.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"for _ in range(int(input())):\n P = input() # parenthesis string : 괄호\n S = [] # stack\n for p in P:\n if p == '(': S.append(p)\n elif p == ')':\n if S: \n if S[-1] == '(': S.pop() \n else: S.append(p)\n print('NO' if S else 'YES')\n\n\"\"\"\n괄호를 하나씩 스택에 집어넣어서\n짝이 맞으면 pop해주고\n스택이 딱 맞아 떨어지면 괄호의 짝이 맞는 것\n스택이 남아있다면 괄호가 짝이 맞지 않는 것\n\"\"\""},{"alpha_fraction":0.578125,"alphanum_fraction":0.5833333134651184,"avg_line_length":20.44444465637207,"blob_id":"bedaf56a7a0d2fd341410431bf91cf8ccf568187","content_id":"ce325de2f38eb1e736e85d258a686b9f7c368156","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":192,"license_type":"no_license","max_line_length":50,"num_lines":9,"path":"/알고리즘/온라인저지/2022/09/0927/아름다운 수.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"# import sys\n\n# input = sys.stdin.readline\n\n# for _ in range(int(input().rstrip())):\n# num = set(input().rstrip())\n# print(len(num))\n\nfor _ in [0]*int(input()):print(len(set(input())))"},{"alpha_fraction":0.5954545736312866,"alphanum_fraction":0.5977272987365723,"avg_line_length":18.173913955688477,"blob_id":"520b5c7ce84a76b34eeef9ffd638cd9da367f39e","content_id":"bd434113fff4777d2d2bc6472fb51a29521817b1","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":648,"license_type":"no_license","max_line_length":45,"num_lines":23,"path":"/알고리즘/온라인저지/2022/01/0122/N번째 큰 수.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import heapq # 우선순위 큐\n\nN = int(input())\n\nhq = heapq # 힙큐 메서드 사용하기 위함\n\nresult = [] # 힙큐로 담을 리스트\n\n# 일단 첫 줄을 힙큐로 넣는다\nfor i in list(map(int, input().split())):\n hq.heappush(result, i)\n\n# 두번째줄부터\nfor n in range(1, N):\n # 매 줄 마다 힙큐에 넣는 동시에 pop 해주면서\n # N개로 개수를 맞춘다\n for i in list(map(int, input().split())):\n # 개사기메서드 힙푸시팝\n hq.heappushpop(result, i)\n\n# 입력받는 동시에 힙푸시팝을 진행하고 남은 리스트의\n# 첫번째 값이 정답 \nprint(hq.heappop(result))"},{"alpha_fraction":0.5592592358589172,"alphanum_fraction":0.5777778029441833,"avg_line_length":17.066667556762695,"blob_id":"76d0f07dedb2c51c15255e7a0b096af1a302fbe2","content_id":"1d3767c7902c82671add213838bb6778c0a242bb","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":332,"license_type":"no_license","max_line_length":63,"num_lines":15,"path":"/알고리즘/온라인저지/2023/02/0214/8진수.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"tmp = 0\ni = 1\nfor j in input()[::-1]:\n tmp += i * int(j)\n i *= 2\n\nimport string\n\nN, B = tmp, 8\ntmp = string.digits + string.ascii_uppercase # 자릿수를 담은 문자열\nresult = ''\nwhile N:\n result = tmp[N%B] + result # B진법이므로 B로 나눈 나머지번째 문자를 계속 추가한다\n N //= B\nprint(result)"},{"alpha_fraction":0.4029850661754608,"alphanum_fraction":0.46268656849861145,"avg_line_length":33,"blob_id":"0978cdb1082167250694ae15542de18b31331681","content_id":"05de05185a11935b1df8d9612b27753a6fa4df52","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":67,"license_type":"no_license","max_line_length":35,"num_lines":2,"path":"/알고리즘/온라인저지/2022/08/0812/Rats.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"A, B, C = map(int, input().split())\nprint(((A+1)*(B+1))//(C+1) - 1)"},{"alpha_fraction":0.4000000059604645,"alphanum_fraction":0.5,"avg_line_length":19.5,"blob_id":"76e3bb9c246fc4948eb62815b8c00168ad0286af","content_id":"0d88ca4d9094393e76f4df431b71fafc24b2c876","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":40,"license_type":"no_license","max_line_length":23,"num_lines":2,"path":"/알고리즘/온라인저지/2022/08/0822/Zadanie próbne 2.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = int(input())\nprint((N+1)*2, (N+1)*3)"},{"alpha_fraction":0.6363636255264282,"alphanum_fraction":0.6363636255264282,"avg_line_length":18,"blob_id":"0728081c0a9a931d93b23b639d1c601b0fd25cb2","content_id":"ba6d012a8b669a9ca3b490f99ae2cabb06b0c415","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":226,"license_type":"no_license","max_line_length":27,"num_lines":7,"path":"/알고리즘/온라인저지/2021/07/0730/[기초-산술연산] 정수 2개 입력받아 나눈 몫 계산하기.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"# 각각 입력받아서 split으로 각각 저장해주고\na, b = input().split()\n# 무조건 각각 int 적용해줘야 한다\n# 입력받는 과정에서 하려니까 에러가 나버리네\na = int(a)\nb = int(b)\nprint(a//b)"},{"alpha_fraction":0.6106870174407959,"alphanum_fraction":0.6106870174407959,"avg_line_length":65,"blob_id":"3ed0733bd904b124988b83d907ea8155bf5cf48f","content_id":"6d0972d98752d3642a5b7d6184783e224b980bec","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":131,"license_type":"no_license","max_line_length":114,"num_lines":2,"path":"/알고리즘/온라인저지/2022/07/0705/욱제는 도박쟁이야!!.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = int(input())\nprint(sum(list(map(abs, list(map(int, input().split()))))) + sum(list(map(abs, list(map(int, input().split()))))))"},{"alpha_fraction":0.5736842155456543,"alphanum_fraction":0.5789473652839661,"avg_line_length":30.83333396911621,"blob_id":"0a4f30936bc46cc946d78e1ebbc8091a21f60fd4","content_id":"22b292a087022bf6418d527bdbe56f2fc7c5e02e","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":190,"license_type":"no_license","max_line_length":45,"num_lines":6,"path":"/알고리즘/온라인저지/2022/09/0910/아이들은 사탕을 좋아해.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"for _ in range(int(input())):\n N, K = map(int, input().split())\n candies = list(map(int, input().split()))\n result = 0\n for candy in candies: result += candy//K\n print(result)"},{"alpha_fraction":0.542553186416626,"alphanum_fraction":0.542553186416626,"avg_line_length":14.833333015441895,"blob_id":"0f49f6a61721ff3f5d25a7c8093c9adebee50b72","content_id":"a2a9b4b5f7564f73c450317a82ca1a690aed2241","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":94,"license_type":"no_license","max_line_length":32,"num_lines":6,"path":"/알고리즘/온라인저지/2023/03/0323/전체 계산 횟수.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N, M = map(int, input().split())\nresult = N\nwhile N:\n N //= M\n result += N\nprint(result)"},{"alpha_fraction":0.5791505575180054,"alphanum_fraction":0.5965250730514526,"avg_line_length":19.760000228881836,"blob_id":"93bf35b0eaa61fb2300a3519f385ddc1a1c04474","content_id":"e845e5e0059e195aba781fb250a217dedac75fe1","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":518,"license_type":"no_license","max_line_length":50,"num_lines":25,"path":"/알고리즘/[템플릿]/이분탐색/랜선 자르기.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\n\ndef cut(length):\n cutted = 0\n for cable in cables:\n cutted += cable//length\n if cutted>=N: return True\n return False\n\nK, N = map(int, input().rstrip().split())\ncables = [int(input().rstrip()) for _ in range(K)]\nresult = 1\nstart, end = result, sum(cables)//N\nwhile start<=end:\n mid = (start+end) // 2\n if cut(mid):\n start = mid+1\n result = max(result, mid)\n else:\n end = mid-1\nprint(result)\n\n# https://www.acmicpc.net/problem/1654"},{"alpha_fraction":0.5112359523773193,"alphanum_fraction":0.5280898809432983,"avg_line_length":18.88888931274414,"blob_id":"7da2d26ccaf16740989662214d791e34004d3e1a","content_id":"d392be358a76cb8392372237bf1d99fb4f96d200","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":266,"license_type":"no_license","max_line_length":35,"num_lines":9,"path":"/알고리즘/온라인저지/2021/07/0730/[기초-산술연산] 정수 3개 입력받아 합과 평균 출력하기.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"# 변수 세 개 받아서\n# 공백으로 쪼개서\n# int로 바꿔주고\n# map으로 각각 저장해준다\na, b, c = map(int, input().split())\nd = a + b + c\ne = round(d / 3, 3)\n# f\"{:.?f}\"로 소수점 아래 자리수 고정시킬 수 있다\nprint(f\"{d} {e:.2f}\")"},{"alpha_fraction":0.46666666865348816,"alphanum_fraction":0.49047619104385376,"avg_line_length":14.071428298950195,"blob_id":"1e91eb399b26a92be8b5e65bcc8b04170ed0849f","content_id":"b6d9e4da16bbe3648aa424a54c91934c68867d7b","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":210,"license_type":"no_license","max_line_length":36,"num_lines":14,"path":"/알고리즘/온라인저지/2022/02/0201/분산처리.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"T = int(input())\n\nfor t in range(T):\n a, b = map(int, input().split())\n\n result = 1\n\n for i in range(b):\n result = (result*a)%10\n\n if result:\n print(result)\n else:\n print(10)"},{"alpha_fraction":0.38268792629241943,"alphanum_fraction":0.4441913366317749,"avg_line_length":26.5,"blob_id":"6e6e0f3727b34932bc5930d70e5496956105fe79","content_id":"128ea8b4c3305b1de233d41a8cf46b7e47994ddc","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":439,"license_type":"no_license","max_line_length":104,"num_lines":16,"path":"/알고리즘/온라인저지/2021/08/0828/한수.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ndef arithmetic_sequence(N):\n if N < 100:\n return N\n else:\n cnt = 0\n for n in range(100, N+1):\n a, b, c = n//100, (n-(n//100)*100)//10, n%10\n for k in range(6):\n if (a+k == b and b+k == c and a+(k*2) == c) or (c+k == b and b+k == a and c+(k*2) == a):\n cnt += 1\n return 99 + cnt\n\nN = int(sys.stdin.readline())\nprint(arithmetic_sequence(N))"},{"alpha_fraction":0.4635658860206604,"alphanum_fraction":0.48217055201530457,"avg_line_length":21.275861740112305,"blob_id":"475808a6e4e5e7d9f058286f2f577adb08a61ee8","content_id":"ddc47017f7e459dee1c03d151fa4057d87c2096b","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":885,"license_type":"no_license","max_line_length":56,"num_lines":29,"path":"/알고리즘/온라인저지/2022/01/0122/수들의 합 2.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N, M = map(int, input().split())\n\nseq = list(map(int, input().split())) # 수열 입력\n\ns = e = 0 # 두포인터\n\nnow = sum(seq[s:e+1]) # 초기값(seq[0])\n\nresult = 0 # 크기가 M과 같은 수열 부분합의 개수 초기화\n\nwhile True: # 무지성 while True\n # 종료조건\n # 1. e를 뒤로 밀어봤자 M보다 크거나 같아질 수 없음\n # 2. s를 뒤로 땡겨봤자 M보다 작거나 같아질 수 없음\n if (now < M and e == N-1) or (now > M and s == N-1):\n break\n\n if now == M: # 수열 부분합이 M과 같으면\n result += 1\n now -= seq[s]\n s += 1 # 앞에서 한 칸 땡기기\n elif now < M: # 부분합이 M보다 작으면\n e += 1 # 뒤로 한 칸 밀기\n now += seq[e]\n elif now > M: # 부분합이 M보다 크면\n now -= seq[s]\n s += 1 # 앞에서 한 칸 땡기기\n\nprint(result)"},{"alpha_fraction":0.3333333432674408,"alphanum_fraction":0.4047619104385376,"avg_line_length":14.363636016845703,"blob_id":"966ab38e930649b80051442398272ea1b1fd3b45","content_id":"3abe518c1ea369b0b33a6f86ccc476eb9d779781","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":168,"license_type":"no_license","max_line_length":22,"num_lines":11,"path":"/알고리즘/온라인저지/2022/09/0901/방 번호.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = input()\ndp = [0]*9\nfor n in N:\n tmp = int(n)\n if tmp == 9:\n dp[6] += 1\n else:\n dp[tmp] += 1\nif dp[6]%2: dp[6] += 1\ndp[6] //= 2\nprint(max(dp))"},{"alpha_fraction":0.3842794895172119,"alphanum_fraction":0.4410480260848999,"avg_line_length":17.360000610351562,"blob_id":"1af1e8c971600bc02e3e69a246fe238cd3e8144b","content_id":"5f26a1cec754f42ecee4e420bd21882d6e1046bb","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":458,"license_type":"no_license","max_line_length":46,"num_lines":25,"path":"/알고리즘/온라인저지/2023/05/0507/너의 평점은.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"grade_to_score = {\n 'A+': 4.5,\n 'A0': 4.0,\n 'B+': 3.5,\n 'B0': 3.0,\n 'C+': 2.5,\n 'C0': 2.0,\n 'D+': 1.5,\n 'D0': 1.0,\n 'F': 0.0,\n}\n\ntime_sum = 0\nresult = 0\nwhile True:\n try:\n subject, time, grade = input().split()\n if grade == 'P':\n continue\n time = int(time[0])\n time_sum += time\n result += time*grade_to_score[grade]\n except EOFError:\n break\nprint(f'{result/time_sum:.6f}')"},{"alpha_fraction":0.39915966987609863,"alphanum_fraction":0.4453781545162201,"avg_line_length":13.9375,"blob_id":"ab1d6c66c529b88445baf50d6c1913acf2711d9f","content_id":"5089422109a20652efc07b473d030c2acaab43e5","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":238,"license_type":"no_license","max_line_length":39,"num_lines":16,"path":"/알고리즘/온라인저지/2022/02/0212/핸드폰 요금.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = int(input())\n\ncalls = list(map(int, input().split()))\n\nY = M = 0\n\nfor c in calls:\n Y += (c//30 + 1) * 10\n M += (c//60 + 1) * 15\n\nif Y > M:\n print('M', min(Y, M))\nelif M > Y:\n print('Y', min(Y, M))\nelse:\n print('Y M', Y)"},{"alpha_fraction":0.5779816508293152,"alphanum_fraction":0.5871559381484985,"avg_line_length":21,"blob_id":"4590535f7c9a97d407080e7be4377e35fb9d4c44","content_id":"9c3447ab8a02b8806cc54970d03476d4ec4937d7","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":109,"license_type":"no_license","max_line_length":41,"num_lines":5,"path":"/알고리즘/온라인저지/2023/03/0303/특식 배부.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = int(input())\nresult = 0\nfor i in list(map(int, input().split())):\n result += min((N, i))\nprint(result)"},{"alpha_fraction":0.4789719581604004,"alphanum_fraction":0.5046728849411011,"avg_line_length":22.83333396911621,"blob_id":"af55433231398a15d8c08433aaec5da0dc7a49f9","content_id":"16727945fa36123f9fd1407a35457faea6f81e8b","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":428,"license_type":"no_license","max_line_length":49,"num_lines":18,"path":"/알고리즘/온라인저지/2022/09/0929/피카츄.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\n\nword = list(input().rstrip())\ni = 0\nwhile i<len(word)-1:\n pikachu = word[i] + word[i+1]\n if pikachu in ['pi', 'ka']:\n for _ in [0]*2: word.pop(i); \n continue\n if i<len(word)-2:\n pikachu = word[i] + word[i+1] + word[i+2]\n if pikachu == 'chu':\n for _ in [0]*3: word.pop(i); \n continue\n i += 1\nprint('NO' if len(word) else 'YES')"},{"alpha_fraction":0.6047903895378113,"alphanum_fraction":0.6407185792922974,"avg_line_length":23,"blob_id":"445b84c5a07a7d4ef531c59388eac39d1805d75c","content_id":"997e80b0c499d720a5864f86a1c51767697b2b09","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":167,"license_type":"no_license","max_line_length":44,"num_lines":7,"path":"/알고리즘/온라인저지/2022/09/0914/숫자.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"A, B = map(int, input().split())\nresult = list(range(min(A, B)+1, max(A, B)))\nprint(len(result))\nif result:\n print(*result)\n\n# https://www.acmicpc.net/problem/10093"},{"alpha_fraction":0.3644859790802002,"alphanum_fraction":0.40186914801597595,"avg_line_length":20.5,"blob_id":"441fe2552aa24f9c481c2fe2b1d8417bd32da5be","content_id":"6fb1ac81ae6dd40877fd437ecaaddd80b2efd354","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":214,"license_type":"no_license","max_line_length":37,"num_lines":10,"path":"/알고리즘/온라인저지/2023/01/0106/암호.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"S = input()\nP = input()\ni = 0\nfor s in S:\n if s != ' ':\n tmp = ord(s) - (ord(P[i])-96)\n if not tmp >= 97: tmp += 26\n print(chr(tmp), end='')\n else: print(' ', end='')\n i = (i+1)%len(P)"},{"alpha_fraction":0.47783932089805603,"alphanum_fraction":0.4819944500923157,"avg_line_length":21.59375,"blob_id":"11f8a919ccf624eaf5a259ec464cf724d04eae05","content_id":"12638af50a068f8a190e0fff9ee7277b5ce90301","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":722,"license_type":"no_license","max_line_length":51,"num_lines":32,"path":"/알고리즘/온라인저지/2022/10/1002/바닥 장식.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\n\ndef check(N, M, arr):\n board = 0\n for i in range(N):\n flag = False\n for j in range(M):\n if arr[i][j] == '-' and not flag:\n flag = True\n board += 1\n elif not arr[i][j] == '-': flag = False\n return board\n\ndef rotate(arr):\n rotated = []\n for j in range(M):\n tmp = ''\n for i in range(N): \n if arr[i][j] == '-': tmp += '|'\n else: tmp += '-'\n rotated.append(tmp)\n return rotated\n\nN, M = map(int, input().rstrip().split())\narr = [input().rstrip() for _ in range(N)]\nresult = 0\nresult += check(N, M, arr)\narr = rotate(arr)\nresult += check(M, N, arr)\nprint(result)"},{"alpha_fraction":0.5561797618865967,"alphanum_fraction":0.5561797618865967,"avg_line_length":21.375,"blob_id":"72d814e14f21f67d5eb95adeb5d1f0d15368d6e1","content_id":"5bb88dc6844058bdbc92eaaa3b37163bf5a2c7ed","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":178,"license_type":"no_license","max_line_length":94,"num_lines":8,"path":"/알고리즘/온라인저지/2022/02/0220/배수 찾기.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = int(input())\n\nwhile True:\n num = int(input())\n if not num:\n break\n\n print(f'{num} is a multiple of {N}.' if not num%N else f'{num} is NOT a multiple of {N}.')"},{"alpha_fraction":0.5537037253379822,"alphanum_fraction":0.5657407641410828,"avg_line_length":26,"blob_id":"8898086a59a10313fbf356996787082e72c03ecf","content_id":"896be0e6a16031a34fd02c2468cdeb3aeaf49f18","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1504,"license_type":"no_license","max_line_length":67,"num_lines":40,"path":"/알고리즘/온라인저지/2021/10/1003/집합.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\nM = int(input())\n\nS = set() # set자료형으로 생성\n# add과정에서 x가 이미 있는 경우 무시할 것이기 때문에 데이터들은 절대 중복될 수 없다\n# 따라서 순서를 지니지 않는 set자료형으로 만들어서 시간초과를 회피\n# 추가하고 제거하는 과정에서 list자료형의 append와 remove혹은 pop을 쓰는 것 보다\n# set자료형의 add와 discard를 쓰는 것이 빠르다\n\nfor m in range(M):\n orders = sys.stdin.readline().split()\n\n if len(orders) == 1: # all이 명령어로 들어왔을 때\n order = orders[0] # add remove check toggle all empty등, 명령어\n else: # all을 제외한 명령어들일 때\n order = orders[0] # 명령어\n num = int(orders[1]) # 목적 숫자 x\n\n if order == 'add':\n S.add(num) # list자료형의 append와 같음\n elif order == 'remove':\n S.discard(num) # list자료형의 remove혹은 pop와 같음\n elif order == 'check':\n if num in S:\n print(1)\n else:\n print(0)\n elif order == 'toggle':\n if num in S:\n S.discard(num)\n else:\n S.add(num)\n elif order == 'all':\n S = set([i for i in range(1, 21)]) # 1~20까지 전부 채워진 set로 리셋\n else:\n S = set() # set를 초기화\n\n# 추가적으로 해당 문제는 메모리도 많이 적은 편이라\n# python의 경우 평소처럼 pypy3로 제출하면 메모리부족으로 오답처리 된다\n"},{"alpha_fraction":0.5719298124313354,"alphanum_fraction":0.582456111907959,"avg_line_length":25,"blob_id":"a70c780f0cb8be9918390b30635239b1deb84d00","content_id":"ab32a4a159be360f1f947ba42d7f6b7224b59e0b","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":285,"license_type":"no_license","max_line_length":42,"num_lines":11,"path":"/알고리즘/온라인저지/2022/09/0911/민균이의 비밀번호.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = int(input())\ntext_list = [input() for _ in range(N)]\ntext_set = set(text_list)\nresult = ''\nfor text in text_list:\n if result: break\n if text == text[::-1]:\n result = text\n elif text[::-1] in text_set:\n result = text\nprint(len(result), result[len(result)//2])"},{"alpha_fraction":0.42607003450393677,"alphanum_fraction":0.48249027132987976,"avg_line_length":21.39130401611328,"blob_id":"9db1e9255814c1ab7d5a44a6d8fa63fac88aa300","content_id":"98b4fa02f1ea9f9efe638ab2ee7d6047a322e5db","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":514,"license_type":"no_license","max_line_length":45,"num_lines":23,"path":"/알고리즘/온라인저지/2022/10/1012/롤 케이크.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\n\nresult = [[0, 0], [0, 0]]\nL = int(input().rstrip())\nN = int(input().rstrip())\ncakes = [1]*L\nfor i in range(1, N+1):\n P, K = map(int, input().rstrip().split())\n if K-P+1 > result[1][1]:\n result[1][1] = K-P+1\n result[1][0] = i\n cake = 0\n for j in range(P-1, K):\n if cakes[j]:\n cakes[j] = 0\n cake += 1\n if cake > result[0][1]:\n result[0][1] = cake\n result[0][0] = i\nprint(result[1][0])\nprint(result[0][0])"},{"alpha_fraction":0.4491978585720062,"alphanum_fraction":0.4946524202823639,"avg_line_length":14.625,"blob_id":"3aeb4e6ae390550ca410e54c3e7c7f0c79daa230","content_id":"f56101f22ded30ce19544a0112e7cc4400ff0da2","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":374,"license_type":"no_license","max_line_length":40,"num_lines":24,"path":"/알고리즘/온라인저지/2022/02/0213/슈퍼 마리오.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"now = int(input())\nans_found = False\nresult = 0\n\nfor _ in range(9):\n num = int(input())\n tmp = now + num\n\n if ans_found:\n continue\n\n if tmp >= 100 and num < 100:\n if abs(tmp-100) <= abs(100-now):\n result = tmp\n else:\n result = now\n ans_found = True\n\n now += num\n\nif now <= 100:\n result = now\n\nprint(result)"},{"alpha_fraction":0.4876847267150879,"alphanum_fraction":0.5024630427360535,"avg_line_length":16,"blob_id":"70cef0592aaea48e2e110017dc8a174d5bedd16d","content_id":"8322b1a564f368e87e2f3832202da0018beaa77e","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":203,"license_type":"no_license","max_line_length":32,"num_lines":12,"path":"/알고리즘/온라인저지/2022/06/0601/암호제작.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"P, K = map(int, input().split())\nresult = 'GOOD'\nnum = 0\nfor k in range(2, K):\n if P%k == 0:\n result = 'BAD'\n num = k\n break\nif num:\n print(result, num)\nelse:\n print(result)"},{"alpha_fraction":0.5446808338165283,"alphanum_fraction":0.5446808338165283,"avg_line_length":12.11111068725586,"blob_id":"d4f51ef4aa3e0d6b2b42f6a52778dba03743a947","content_id":"34edccf3d114e5aaa0ed4b4510ec9c32a91c6876","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":235,"license_type":"no_license","max_line_length":32,"num_lines":18,"path":"/알고리즘/온라인저지/2021/10/1016/듣보잡.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N, M = map(int, input().split())\n\na = set()\n\nfor n in range(N):\n a.add(input())\n\nresult = []\n\nfor m in range(M):\n b = input()\n if b in a:\n result.append(b)\n\nprint(len(result))\nresult.sort()\nfor r in result:\n print(r)"},{"alpha_fraction":0.45039165019989014,"alphanum_fraction":0.48433420062065125,"avg_line_length":24.566667556762695,"blob_id":"172d8d7567868b150c20efa532dc9a7e1df897ab","content_id":"ed33f66f910809f83be208e20f6ea2ba83f80c6f","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":766,"license_type":"no_license","max_line_length":57,"num_lines":30,"path":"/알고리즘/[템플릿]/BFS/토마토.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"from collections import deque\n\ndy, dx = [-1, 1, 0, 0], [0, 0, -1, 1]\nM, N = map(int, input().split())\narr = [list(map(int, input().split())) for _ in range(N)]\nQ = deque()\nfor i in range(N):\n for j in range(M):\n if arr[i][j] == 1:\n Q.append((i, j, 0))\n arr[i][j] = 0\nresult = 0\nwhile Q:\n y, x, day = Q.popleft()\n if arr[y][x] == 1: continue\n arr[y][x] = 1\n result = max(result, day)\n for i in range(4):\n ny, nx = y+dy[i], x+dx[i]\n if 0<=ny<N and 0<=nx<M and arr[ny][nx] == 0:\n Q.append((ny, nx, day+1))\nfor i in range(N):\n if result == -1: break\n for j in range(M):\n if arr[i][j] == 0:\n result = -1\n break\nprint(result)\n\n# https://www.acmicpc.net/problem/7576"},{"alpha_fraction":0.5901639461517334,"alphanum_fraction":0.5901639461517334,"avg_line_length":30,"blob_id":"6bc47d3c2df3673c502e5828f8558fa4e69d0306","content_id":"884bc73ed3fcbf78f04cae5bd9694cca0efa2264","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":61,"license_type":"no_license","max_line_length":44,"num_lines":2,"path":"/알고리즘/온라인저지/2023/04/0413/Mathematics.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = int(input())\nprint(sum([int(input()) for _ in range(N)]))"},{"alpha_fraction":0.5882353186607361,"alphanum_fraction":0.5882353186607361,"avg_line_length":22,"blob_id":"fe8d31df2c1e6b746fc7b2035ac4bb3406610995","content_id":"8c4c75b645f53fcf629faf9cce60bfbb4cb82073","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":68,"license_type":"no_license","max_line_length":32,"num_lines":3,"path":"/알고리즘/온라인저지/2023/04/0412/샤틀버스.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"x, y = map(int, input().split())\nif x>y: print(x+y)\nelse: print(y-x)"},{"alpha_fraction":0.525073766708374,"alphanum_fraction":0.5545722842216492,"avg_line_length":27.33333396911621,"blob_id":"2abbf5356b1b5fa36834bad8b97fce086551c9d9","content_id":"abcc75e52ceed980ec180a4945731b9c561622a0","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":389,"license_type":"no_license","max_line_length":47,"num_lines":12,"path":"/알고리즘/프로그래머스/Level1/로또의 최고 순위와 최저 순위.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"def solution(lottos, win_nums):\n answer = []\n # print(lottos, win_nums)\n # 일치하는 번호의 개수만이, 오직 등수에 영향을 줌\n minn = 0\n for l in lottos:\n if l in win_nums:\n minn += 1\n result = [6, 6, 5, 4, 3, 2, 1] # 등수 테이블\n answer.append(result[lottos.count(0)+minn])\n answer.append(result[minn]) \n return answer"},{"alpha_fraction":0.38860103487968445,"alphanum_fraction":0.41450777649879456,"avg_line_length":18.399999618530273,"blob_id":"c2bafa392890ad09ee73a9bd0f3718818556e535","content_id":"84961694ffb6f3e1989b7aef238a63bbe6ae5f68","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":193,"license_type":"no_license","max_line_length":29,"num_lines":10,"path":"/알고리즘/온라인저지/2023/05/0508/탁구 경기.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"D, P = 0, 0\nfor i in range(int(input())):\n winner = input()\n if abs(D-P) == 2:\n continue\n if winner == 'D':\n D += 1\n if winner == 'P':\n P += 1\nprint(f'{D}:{P}')"},{"alpha_fraction":0.3870967626571655,"alphanum_fraction":0.4516128897666931,"avg_line_length":20.375,"blob_id":"c9bdb0a33128ceb90ede7a41c189981ae3e75802","content_id":"ab0aab0acc44229549a72e9e0d9b861cd995c308","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":341,"license_type":"no_license","max_line_length":35,"num_lines":16,"path":"/알고리즘/온라인저지/2022/07/0731/파스칼 삼각형.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"R, C, W = map(int, input().split())\nN = R+W-1\nP = [[1], [1, 1], [1, 2, 1]]\nfor n in range(N-3):\n tmp = [0] * (2+n)\n for i in range(len(P[-1])-1):\n tmp[i] = sum(P[-1][i:i+2])\n tmp = [1]+tmp+[1]\n P.append(tmp)\nresult = 0\nj = 0\nfor i in range(R-1, N):\n j += 1\n tmp = P[i][C-1:C+j-1]\n result += sum(tmp)\nprint(result)"},{"alpha_fraction":0.43581080436706543,"alphanum_fraction":0.5033783912658691,"avg_line_length":20.214284896850586,"blob_id":"d34ad401d79957409e2f9384ac3a6c2b50601d45","content_id":"23ca1b22d73d24a849b947d78375cc4a95902b19","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":296,"license_type":"no_license","max_line_length":44,"num_lines":14,"path":"/알고리즘/온라인저지/2022/09/0925/돌 게임 3.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\n\nN = int(input().rstrip())\ndp = [0, 1, 0, 1, 1] + [0]*(N-4)\nif N>4:\n for i in range(5, N+1):\n if 0 in [dp[i-1], dp[i-3], dp[i-4]]:\n dp[i] = 1\n else: dp[i] = 0\nprint('SK' if dp[N] else 'CY')\n\n# https://www.acmicpc.net/problem/9657"},{"alpha_fraction":0.39919355511665344,"alphanum_fraction":0.4193548262119293,"avg_line_length":14.5625,"blob_id":"efbd15895c22a7437250e6a8eafe2b23e548af02","content_id":"dd07afe1f4b9026444310f745d0b58ae8c0d13cc","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":248,"license_type":"no_license","max_line_length":42,"num_lines":16,"path":"/알고리즘/온라인저지/2022/02/0220/짝수를 찾아라.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"T = int(input())\n\nfor t in range(T):\n nums = list(map(int, input().split()))\n\n minn = 100\n summ = 0\n\n for n in nums:\n if not n%2:\n summ += n\n\n if n < minn:\n minn = n\n \n print(summ, minn)"},{"alpha_fraction":0.5467422008514404,"alphanum_fraction":0.5524079203605652,"avg_line_length":22.600000381469727,"blob_id":"c4ac5f8d81323f084109d8e0e2ac0a7dc8e905ab","content_id":"a54067bdd6c3a28c7e50cef89bb8648b0ba6c1fb","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":397,"license_type":"no_license","max_line_length":58,"num_lines":15,"path":"/알고리즘/온라인저지/2022/08/0802/자료구조는 정말 최고야.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\n\nN, M = map(int, input().split())\nresult = True\nfor _ in range(M):\n K = int(input())\n B = list(map(int, input().split()))\n for k in range(K-1):\n if B[k] < B[k+1]: # 한 권의 책이라도 오름차순이 아니면 정답이 될 수 없다\n result = False\n break\n if not result: break\nprint('Yes' if result else 'No')"},{"alpha_fraction":0.418552041053772,"alphanum_fraction":0.4570135772228241,"avg_line_length":16.038461685180664,"blob_id":"0b3dfddd6de5acc67b7869a1dafdd86d247f16d2","content_id":"310402c0c2607f5acf7688e4af97e67a39fa1429","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":442,"license_type":"no_license","max_line_length":38,"num_lines":26,"path":"/알고리즘/온라인저지/2022/02/0203/소수 찾기.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"dp = [False, False] + [True] * (999)\nprimes = []\n\nfor i in range(2, 1001):\n if dp[i]:\n primes.append(i)\n for j in range(i*2, 1001, i):\n dp[j] = False\n\nN = int(input())\nnums = list(map(int, input().split()))\n\nmaxx = nums[-1]\nresult = 0\n\nfor p in primes:\n for n in nums:\n if n == p:\n if n == 1:\n continue\n result += 1\n \n if p == maxx:\n break\n\nprint(result)"},{"alpha_fraction":0.41428571939468384,"alphanum_fraction":0.4285714328289032,"avg_line_length":13.199999809265137,"blob_id":"993788a65893448161bc850bcac60ff23afac79d","content_id":"4b574b750852b72afc2588711880588e64e9379a","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":70,"license_type":"no_license","max_line_length":20,"num_lines":5,"path":"/알고리즘/온라인저지/2022/01/0131/별 찍기 - 3.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = M = int(input())\n\nfor i in range(N):\n print('*' * M)\n M -= 1"},{"alpha_fraction":0.6212121248245239,"alphanum_fraction":0.6287878751754761,"avg_line_length":25.600000381469727,"blob_id":"cf77ef42934391e16653138c272e94e4b245edea","content_id":"66b8ce8a746125ab664c56802df919e6f6bc0b3d","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":132,"license_type":"no_license","max_line_length":40,"num_lines":5,"path":"/알고리즘/온라인저지/2022/06/0625/이항 계수 1.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"from math import factorial as fact\n\nN, K = map(int, input().split())\nresult = fact(N) / (fact(K) * fact(N-K))\nprint(f'{result:.0f}')"},{"alpha_fraction":0.40361446142196655,"alphanum_fraction":0.42168673872947693,"avg_line_length":10.928571701049805,"blob_id":"f002b8fc3503a1d4e74d0c0f5b29250e384a1869","content_id":"f4d09a223421acb7db97d10c7ae83dd010353439","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":166,"license_type":"no_license","max_line_length":36,"num_lines":14,"path":"/알고리즘/온라인저지/2021/12/1216/주사위 게임 2.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = int(input())\n\nA = B = 100\n\nfor n in range(N):\n a, b = map(int, input().split())\n\n if a > b:\n B -= a\n elif b > a:\n A -= b\n\nprint(A)\nprint(B)"},{"alpha_fraction":0.4909090995788574,"alphanum_fraction":0.5272727012634277,"avg_line_length":17.66666603088379,"blob_id":"17143390e1734347d223ecd4b828b1b0d21b3177","content_id":"3ec6307de83f70a53933e5bd90ae5250f0e33040","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":55,"license_type":"no_license","max_line_length":25,"num_lines":3,"path":"/알고리즘/온라인저지/2021/08/0822/기찍 N.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = int(input())\nfor n in range(N, 0, -1):\n print(n)"},{"alpha_fraction":0.5445544719696045,"alphanum_fraction":0.5742574334144592,"avg_line_length":16,"blob_id":"c6a6bdba710f5fd9a949e0adb74d3505714ec50e","content_id":"d4d356d755423560fb45b3bcdba82517e472e134","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":101,"license_type":"no_license","max_line_length":21,"num_lines":6,"path":"/알고리즘/온라인저지/2023/05/0509/三方比較 (Three-Way Comparison).py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"result = 0\nA = int(input())\nB = int(input())\nif A < B: result = -1\nif A > B: result = 1\nprint(result)"},{"alpha_fraction":0.4621676802635193,"alphanum_fraction":0.5296523571014404,"avg_line_length":26.22222137451172,"blob_id":"5ac9a8334f81fa4079428604e8bb436a4127eca3","content_id":"7416bc3d3b07ee580bc527a30a664b7d45568178","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":489,"license_type":"no_license","max_line_length":54,"num_lines":18,"path":"/알고리즘/온라인저지/2022/10/1016/나는 학급회장이다.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\n\nresult = [[0]*5 for _ in range(3)]\nfor i in range(3): result[i][4] = i+1\nfor _ in range(int(input().rstrip())):\n A, B, C = map(int, input().rstrip().split())\n result[0][0] += A\n result[1][0] += B\n result[2][0] += C\n result[0][A] += 1\n result[1][B] += 1\n result[2][C] += 1\nresult.sort(key=lambda x:(-x[0], -x[3], -x[2], -x[1]))\nif result[0][:4] == result[1][:4]:\n print(0, result[0][0])\nelse: print(result[0][4], result[0][0])"},{"alpha_fraction":0.5081080794334412,"alphanum_fraction":0.545945942401886,"avg_line_length":22.25,"blob_id":"8e3f1ae768f3bf09c28efd483b8ac96d76d964d7","content_id":"58ee747b1b6bae1d668fcc49b468f6802f49b1e7","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":185,"license_type":"no_license","max_line_length":37,"num_lines":8,"path":"/알고리즘/온라인저지/2023/06/0607/모비스.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"S = input()\nresult = 0\nif 'M' in S: result += 1\nif 'O' in S: result += 1\nif 'B' in S: result += 1\nif 'I' in S: result += 1\nif 'S' in S: result += 1\nprint('YES' if result == 5 else 'NO')"},{"alpha_fraction":0.277688592672348,"alphanum_fraction":0.29293739795684814,"avg_line_length":24.97916603088379,"blob_id":"bafc2ddff1439b35f011ee518a59a217e03cc984","content_id":"6e7e31b0968b078ae81d32a5d3ac8a00c6ff175d","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1256,"license_type":"no_license","max_line_length":54,"num_lines":48,"path":"/알고리즘/온라인저지/2022/06/0611/양.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"from collections import deque\nimport sys\n\ninput = sys.stdin.readline\n\nR, C = map(int, input().split())\narr = []\nfor _ in range(R):\n tmp = list(input())\n arr.append(tmp)\n\ndx = [-1, 1, 0, 0]\ndy = [0, 0, -1, 1]\nq = deque()\nV = O = 0\n\nfor r in range(R): # 행\n for c in range(C): # 열\n if arr[r][c] in '.vo': # BFS\n q.append((r, c))\n v = o = 0\n while q:\n tmp = q.popleft()\n y, x = tmp[0], tmp[1]\n if arr[y][x] != '1':\n if arr[y][x] == 'o':\n o += 1\n elif arr[y][x] == 'v':\n v += 1\n arr[y][x] = '1'\n for i in range(4):\n ny = y+dy[i]\n nx = x+dx[i]\n try:\n if arr[ny][nx] in '.vo':\n if arr[ny][nx] != '1':\n if (ny, nx) not in q:\n q.append((ny, nx))\n except:\n q = deque()\n v = o = 0\n # print(o, v) # 디버깅\n if o > v:\n O += o\n else:\n V += v\n\nprint(O, V)"},{"alpha_fraction":0.4951830506324768,"alphanum_fraction":0.5202311873435974,"avg_line_length":33.63333511352539,"blob_id":"f17e6b03692ec2f3ad72fed33bf42c063daa9128","content_id":"0be5c3cda7c4887a139e317b7e36412d0ee6abc1","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1330,"license_type":"no_license","max_line_length":61,"num_lines":30,"path":"/알고리즘/온라인저지/2022/09/0912/토마토.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"from collections import deque # BFS\n\ndy, dx = [-1, 1, 0, 0], [0, 0, -1, 1] # delta 이동\nM, N = map(int, input().split()) # M부터 받는 거, 낚시 주의\narr = [list(map(int, input().split())) for _ in range(N)]\nQ = deque()\nfor i in range(N):\n for j in range(M):\n if arr[i][j] == 1: # 첫 날 토마토인 좌표들 추가\n Q.append((i, j, 0)) # y, x, day\n arr[i][j] = 0\nresult = 0\nwhile Q: # BFS\n y, x, day = Q.popleft() # day를 추가하면서 가장 마지막에 나온 day를 잡을 것\n if arr[y][x] == 1: continue # 다른 토마토를 통해서 이미 익은 토마토\n arr[y][x] = 1 # 잘 익은 토마토\n result = max(result, day) # 더 오랜시간이 걸려서 익은 토마토가 있으면 갱신\n for i in range(4):\n ny, nx = y+dy[i], x+dx[i] # 전후좌우 토마토\n if 0<=ny<N and 0<=nx<M and arr[ny][nx] == 0:\n Q.append((ny, nx, day+1)) # 다음 날에 이 토마토는 익는다\nfor i in range(N):\n if result == -1: break # 모든 토마토가 익을 수 없었다? -> 종료\n for j in range(M):\n if arr[i][j] == 0: # 충분한 시간이 흘렀는데 안익은 토마토가 있다?\n result = -1 # 모든 토마토가 익을 수 없었다\n break\nprint(result)\n\n# https://www.acmicpc.net/problem/7576"},{"alpha_fraction":0.3545454442501068,"alphanum_fraction":0.40303030610084534,"avg_line_length":18.352941513061523,"blob_id":"9c63da119c55bc957be00ccfc650158f112da147","content_id":"617f9913e5a8ae33d082b78caa663dd45d70d51f","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":330,"license_type":"no_license","max_line_length":24,"num_lines":17,"path":"/알고리즘/온라인저지/2022/04/0417/공백 없는 A+B.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"num = input()\nA = B = 0\nif len(num) == 2:\n A = int(num[0])\n B = int(num[1])\nelif len(num) == 3:\n if num[1] == '0':\n A = int(num[:2])\n B = int(num[-1])\n elif num[-1] == '0':\n A = int(num[0])\n B = int(num[1:])\nelse: # len 4\n A = int(num[:2])\n B = int(num[2:])\n# print(A, B)\nprint(A+B)\n\n"},{"alpha_fraction":0.5306122303009033,"alphanum_fraction":0.5510203838348389,"avg_line_length":10,"blob_id":"97baab3aa42d5e126377dcf6a3ce81e63ce6bcf5","content_id":"b43d26137f3c389b8232c4f3486e8ed2e2628841","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":98,"license_type":"no_license","max_line_length":20,"num_lines":9,"path":"/알고리즘/온라인저지/2022/02/0205/모음의 개수.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"result = 0\n\ntext = input()\n\nfor t in text:\n if t in 'aeiou':\n result += 1\n\nprint(result)"},{"alpha_fraction":0.43478259444236755,"alphanum_fraction":0.4434782564640045,"avg_line_length":15.571428298950195,"blob_id":"85e388e17493395c68fa2abaa35a5bf9f0f9bc77","content_id":"8b63a298555ad7ee477415ec8b5ee13953082307","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":115,"license_type":"no_license","max_line_length":32,"num_lines":7,"path":"/알고리즘/온라인저지/2021/08/0825/최대공약수와 최소공배수.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"a, b = map(int, input().split())\nc, d = a, b\nwhile a % b != 0:\n a, b = b, a % b\n\nprint(b)\nprint(b*(c//b)*(d//b))"},{"alpha_fraction":0.5570470094680786,"alphanum_fraction":0.5973154306411743,"avg_line_length":20.428571701049805,"blob_id":"b76e6691b5004590fe6901e5ca007a58669ba7fe","content_id":"362251c1e4598117dae8c927a5a94400a43d6b4e","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":149,"license_type":"no_license","max_line_length":37,"num_lines":7,"path":"/알고리즘/온라인저지/2022/02/0220/콘테스트.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"W = [int(input()) for _ in range(10)]\nK = [int(input()) for _ in range(10)]\n\nW.sort(reverse=True)\nK.sort(reverse=True)\n\nprint(sum(W[:3]), sum(K[:3]))"},{"alpha_fraction":0.42105263471603394,"alphanum_fraction":0.6736842393875122,"avg_line_length":15,"blob_id":"77117f5b7f31de18c79563c19a8512036e56c7a4","content_id":"36788e9fa08a24afc2ea3f0c0afdc92e8899f6d9","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":95,"license_type":"no_license","max_line_length":41,"num_lines":6,"path":"/알고리즘/SWEA/LEARN/Course/1. Programming Beginner/파이썬 프로그래밍 기초(2)/25차시 2. 자료구조 – 리스트, 튜플 - 연습문제 27.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"arr = [12,24,35,24,88,120,155,88,120,155]\n\nresult = list(set(arr))\n\nresult.sort()\nprint(result)"},{"alpha_fraction":0.53125,"alphanum_fraction":0.5580357313156128,"avg_line_length":19.409090042114258,"blob_id":"2f89ffa455e3e09160886712c6bc1a06f7a74238","content_id":"a8cdbfac89b0e0f1cdd09ea909a539c73312911e","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":510,"license_type":"no_license","max_line_length":38,"num_lines":22,"path":"/알고리즘/온라인저지/2022/04/0402/네 번째 수.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"\"\"\"\n까먹은 수의 위치\n1. 맨 앞 or 맨 뒤\n2. 중간\n\n맨 앞 or 맨 뒤 일 경우 둘 중 아무거나 편한 거 출력\n\"\"\"\nnums = list(map(int, input().split()))\nnums.sort()\ndiff = 1e9\nfor i in range(1, len(nums)):\n if nums[i] - nums[i-1] < diff:\n diff = nums[i] - nums[i-1]\nin_middle = False\nresult = 0\nfor i in range(1, len(nums)):\n if nums[i] != nums[i-1] + diff:\n in_middle = True\n result = nums[i-1] + diff\nif not in_middle:\n result = nums[-1] + diff\nprint(result)"},{"alpha_fraction":0.5075757503509521,"alphanum_fraction":0.5227272510528564,"avg_line_length":13.777777671813965,"blob_id":"df8187d3494e734176500ffe8819edcf2e410a68","content_id":"d41dfe637a71b9781e89b03a921cbeac322cc91f","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":132,"license_type":"no_license","max_line_length":20,"num_lines":9,"path":"/알고리즘/온라인저지/2023/03/0326/골뱅이 찍기 - ㄷ.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = int(input())\nA = '@'*N\nB = A*5\nfor i in range(N):\n print(B)\nfor i in range(N*3):\n print(A)\nfor i in range(N):\n print(B)"},{"alpha_fraction":0.5315315127372742,"alphanum_fraction":0.5525525808334351,"avg_line_length":18.58823585510254,"blob_id":"91e0c9b32f9686c8e6ec90e4d5ddf8199d4516d9","content_id":"a27039bf792ebba55ced1dc68a1d746a01421861","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":333,"license_type":"no_license","max_line_length":51,"num_lines":17,"path":"/알고리즘/온라인저지/2021/10/1016/구간 합 구하기 4 .py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\nN, M = map(int, sys.stdin.readline().split())\n\narr = tuple(map(int, sys.stdin.readline().split()))\n\ntmp = [arr[0]]\n\nfor n in range(1, N):\n tmp.append(arr[n]+tmp[-1])\n\nfor m in range(M):\n a, b = map(int, sys.stdin.readline().split())\n if a == 1:\n print(tmp[b-1])\n else:\n print(tmp[b-1]-tmp[a-2])\n"},{"alpha_fraction":0.451977401971817,"alphanum_fraction":0.4858756959438324,"avg_line_length":21.25,"blob_id":"5a47f42c6a214b56e4dfd5a53dbb0e220366c8a2","content_id":"ad119848ff2abb1695c4767a5289384768ab1a65","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":177,"license_type":"no_license","max_line_length":28,"num_lines":8,"path":"/알고리즘/온라인저지/2023/01/0114/문자가 몇갤까.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"while True:\n tmp = input()\n if tmp == '#': break\n result = set()\n for t in tmp.lower():\n if 97<=ord(t)<97+26:\n result.add(t)\n print(len(result))"},{"alpha_fraction":0.4675324559211731,"alphanum_fraction":0.523809552192688,"avg_line_length":13.5,"blob_id":"4fa98cf5e46475e07f2165b76369d734d547e0b2","content_id":"0052547a85b53c9637149484ce73d605bfeecbd0","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":231,"license_type":"no_license","max_line_length":31,"num_lines":16,"path":"/알고리즘/온라인저지/2022/02/0201/수 정렬하기 3.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ndef input():\n return sys.stdin.readline()\n\ndp = [0] * 10001\n\nN = int(input())\n\nfor n in range(N):\n dp[int(input())] += 1\n\nfor i in range(1, 10001):\n if dp[i]:\n for j in range(dp[i]):\n print(i)"},{"alpha_fraction":0.5,"alphanum_fraction":0.5169082283973694,"avg_line_length":16.25,"blob_id":"03ddc92c1d87c4246b6110b11a30b348ecb5251d","content_id":"65d5f04548de5f5a21507359d266348f51303281","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":414,"license_type":"no_license","max_line_length":35,"num_lines":24,"path":"/알고리즘/온라인저지/2022/02/0205/백설 공주와 일곱 난쟁이.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"dwarfs = []\n\nfor _ in range(9):\n dwarfs.append(int(input()))\n\nsum_dwarfs = sum(dwarfs)\n\nfakes_idx = []\n\nfor i in range(8):\n temp = sum_dwarfs - dwarfs[i]\n\n for j in range(i, 9):\n if temp - dwarfs[j] == 100:\n fakes_idx.append(i)\n fakes_idx.append(j)\n break\n \n if fakes_idx:\n break\n\nfor i in range(9):\n if i not in fakes_idx:\n print(dwarfs[i])\n"},{"alpha_fraction":0.3867403268814087,"alphanum_fraction":0.4254143536090851,"avg_line_length":19.22222137451172,"blob_id":"b3d962521170bc06ff4b3468ce4d95aa3a4f022c","content_id":"4c9ceacd5d829ddc5664eaba5028ac2603d9a683","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":181,"license_type":"no_license","max_line_length":32,"num_lines":9,"path":"/알고리즘/온라인저지/2023/01/0101/희주의 수학시험.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"A, B = map(int, input().split())\narr = [0]*(B+1)\nk = 0\nfor i in range(1, B+1):\n for j in range(i):\n k += 1\n if k <= B:\n arr[k] = i\nprint(sum(arr[A:B+1]))"},{"alpha_fraction":0.43455496430397034,"alphanum_fraction":0.46422338485717773,"avg_line_length":30.236364364624023,"blob_id":"160117f4df71d0d513cd36b37dda433797558530","content_id":"8ff24c71fadcbec1ff404e45dda08170959dcd0d","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1727,"license_type":"no_license","max_line_length":86,"num_lines":55,"path":"/알고리즘/온라인저지/2021/08/0829/경비원.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\nW, H = map(int, sys.stdin.readline().split())\nmarket_count = int(sys.stdin.readline())\nmarkets = []\nfor _ in range(market_count):\n markets.append(list(map(int, sys.stdin.readline().split())))\ndgnswe, dgdist = map(int, sys.stdin.readline().split())\n\nresult = 0\n\nfor i in range(market_count):\n if (markets[i][0] == 1 and dgnswe == 2) or (markets[i][0] == 2 and dgnswe == 1):\n result += H\n tmp1 = markets[i][1] + dgdist\n tmp2 = W - markets[i][1] + W - dgdist\n if tmp1 < tmp2:\n result += tmp1\n else:\n result += tmp2\n\n elif (markets[i][0] == 3 and dgnswe == 4) or (markets[i][0] == 4 and dgnswe == 3):\n result += W\n tmp1 = markets[i][1] + dgdist\n tmp2 = H - markets[i][1] + H - dgdist\n if tmp1 < tmp2:\n result += tmp1\n else:\n result += tmp2\n\n elif markets[i][0] == dgnswe:\n result += abs(markets[i][1] - dgdist)\n else: # 좌 우 일때\n if markets[i][0] == 1:\n if dgnswe == 3:\n result += markets[i][1] + dgdist\n else:\n result += W - markets[i][1] + dgdist\n if markets[i][0] == 2:\n if dgnswe == 3:\n result += markets[i][1] + H - dgdist\n else:\n result += W - markets[i][1] + H - dgdist\n if markets[i][0] == 3:\n if dgnswe == 1:\n result += markets[i][1] + dgdist\n else:\n result += H - markets[i][1] + dgdist\n if markets[i][0] == 4:\n if dgnswe == 1:\n result += markets[i][1] + W - dgdist\n else:\n result += H - markets[i][1] + W - dgdist\n\nprint(result)\n\n"},{"alpha_fraction":0.45012786984443665,"alphanum_fraction":0.46547314524650574,"avg_line_length":28.769229888916016,"blob_id":"446e7697ac7ac2096f66107f7341ef94dbccb03d","content_id":"7c5a0d0fe753e9ed4d9219a7f75eb7b00fec577b","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":525,"license_type":"no_license","max_line_length":64,"num_lines":13,"path":"/알고리즘/온라인저지/2021/08/0810/캠핑.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"\"\"\"\nL P V\nresult = (V//P) * L\"\"\"\ncount = 0\nwhile True:\n L, P, V = map(int, input().split()) # 각각 변수를 입력받고\n count += 1 # Case count: ? 출력해줄 count변수\n if L + P + V == 0: # 마지막항으로 0 0 0 들어오면\n break # 종료\n C = V - ((V//P) * P) # 다 나눠주고 나머지 더할 상수 C\n if C > L: # C가 L보다 크면\n C = L # L보다 클 때 모두 다 C로 치환\n print(f'Case {count}: {((V//P) * L) + C}') # 테스트케이스마다 결과값 출력\n "},{"alpha_fraction":0.5040983557701111,"alphanum_fraction":0.5778688788414001,"avg_line_length":29.625,"blob_id":"f002a95df185def78ebdffd781308f50f2a3ee37","content_id":"52394af2094eb192267b99647699d67250dc441d","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":244,"license_type":"no_license","max_line_length":117,"num_lines":8,"path":"/알고리즘/온라인저지/2022/08/0830/Speed fines are not fine!.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"F = [100, 270, 500] # fine\nA = int(input())\nB = int(input())\ni = 0\nif B > A:\n if 21<=B-A<=30: i = 1\n elif 31<=B-A: i = 2\nprint(f'You are speeding and your fine is ${F[i]}.' if B > A else 'Congratulations, you are within the speed limit!')"},{"alpha_fraction":0.39175257086753845,"alphanum_fraction":0.4192439913749695,"avg_line_length":16.176469802856445,"blob_id":"ed2874f1dcf496dcc51c17fa419800b27e7c0b6d","content_id":"446a9e3bef8d5b453b6d9520d4ba5c4d0bcf24c4","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":291,"license_type":"no_license","max_line_length":36,"num_lines":17,"path":"/알고리즘/온라인저지/2023/04/0401/루트.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"while True:\n B, N = map(int, input().split())\n \n if B == 0 and N == 0: break\n\n minn = int(1e9)\n result = 0\n\n for A in range(1, int(1e9)):\n D = abs(B - A**N)\n\n if D < minn: \n minn = D\n result = A\n else: break\n \n print(result)"},{"alpha_fraction":0.6292682886123657,"alphanum_fraction":0.6536585092544556,"avg_line_length":16.16666603088379,"blob_id":"0622a76f978d8e7406aa818fb617ba1f12793709","content_id":"2da5655f4a4edcb70340d2633538e1fe8a53b360","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":205,"license_type":"no_license","max_line_length":47,"num_lines":12,"path":"/알고리즘/온라인저지/2022/11/1125/거리의 합.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\n\ninput()\nnums = list(map(int, input().rstrip().split()))\nnums.sort()\nresult = 0\nfor num1 in nums:\n for num2 in nums:\n result += abs(num1-num2)\nprint(result)"},{"alpha_fraction":0.5130434632301331,"alphanum_fraction":0.5565217137336731,"avg_line_length":11.88888931274414,"blob_id":"095f712f4bdab121946e0ccf6b7f8f3758d1452f","content_id":"666082decbae1fa6b676961515c6a8fa3a738e34","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":115,"license_type":"no_license","max_line_length":29,"num_lines":9,"path":"/알고리즘/온라인저지/2021/08/0828/벌집.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\nN = int(sys.stdin.readline())\n\nlayer = 1\ni = 1\nwhile layer < N:\n i += 1\n layer += (i-1)*6\nprint(i)"},{"alpha_fraction":0.43478259444236755,"alphanum_fraction":0.54347825050354,"avg_line_length":46,"blob_id":"57a13229b5ab104a9c7e8a75bd8498aea806ec71","content_id":"387239b75a8a35bab4d8dbe592b107a40f5c5773","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":46,"license_type":"no_license","max_line_length":46,"num_lines":1,"path":"/알고리즘/온라인저지/2022/03/0312/17배.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"print(str(bin(int('0b'+input(), 2) * 17))[2:])"},{"alpha_fraction":0.3802816867828369,"alphanum_fraction":0.44014084339141846,"avg_line_length":34.5,"blob_id":"2dd58aa7f1183cf3655b36e1fdeb81b82d1abecb","content_id":"15227be07a035cf18de054f870a233abb5ad9b26","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":310,"license_type":"no_license","max_line_length":78,"num_lines":8,"path":"/알고리즘/[템플릿]/정렬/버블 정렬.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"arr = [55, 7, 42, 78, 12]\nfor i in range(len(arr)-1, 0, -1):\n for j in range(i):\n print(i, j)\n if arr[j] > arr[j+1]:\n print(f'{arr[j]}가 {arr[j+1]}보다 크므로, {arr[j]}와 {arr[j+1]}의 자리를 변경')\n arr[j], arr[j+1] = arr[j+1], arr[j]\n print(arr)\n"},{"alpha_fraction":0.4858657121658325,"alphanum_fraction":0.5141342878341675,"avg_line_length":19.25,"blob_id":"2bf6936e97abd2cf4806a845e9944f0e55fa0e92","content_id":"be871ee39f58ec47c01000e610e51c7aa65c2ec1","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":566,"license_type":"no_license","max_line_length":73,"num_lines":28,"path":"/알고리즘/온라인저지/2022/09/0917/못생긴 수.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\nfrom heapq import heappush, heappop\n\ninput = sys.stdin.readline\n\ndef ugly(num):\n result = 0\n HQ = []\n heappush(HQ, 1)\n cnt = 0\n while HQ:\n num = heappop(HQ)\n cnt += 1\n if cnt == N: \n result = num\n break\n for i in (2, 3, 5):\n next = num*i\n if next not in HQ:\n heappush(HQ, next)\n return result\n\nwhile True:\n N = int(input().rstrip())\n if N == 0: break\n print(ugly(N))\n\n# http://www.jungol.co.kr/bbs/board.php?bo_table=pbank&code=1318&sca=4030"},{"alpha_fraction":0.44291090965270996,"alphanum_fraction":0.4667503237724304,"avg_line_length":22.47058868408203,"blob_id":"39f1d9e4f85fb5217bce6039082cf1f6dac70d74","content_id":"5a55d484521baf7231fbf186721e319274676f52","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":819,"license_type":"no_license","max_line_length":49,"num_lines":34,"path":"/알고리즘/[템플릿]/문자열 탐색/KMP 알고리즘/찾기.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\n\ndef get_pi(pattern):\n j = 0\n for i in range(1, len(pattern)):\n while j > 0 and pattern[i] != pattern[j]:\n j = pi[j-1]\n if pattern[i] == pattern[j]:\n j += 1\n pi[i] = j\n\ndef KMP(string, pattern):\n get_pi(pattern)\n j = 0\n for i in range(len(string)):\n while j > 0 and string[i] != pattern[j]:\n j = pi[j-1]\n if string[i] == pattern[j]:\n if j == len(pattern)-1:\n result.append(i-j+1)\n result[0] += 1\n j = pi[j] # 다음 패턴 찾는 인덱싱 주의\n else:\n j += 1\n\nS, P = input().rstrip(), input().rstrip()\npi = [0] * len(P)\nresult = [0]\nKMP(S, P)\nfor r in result: print(r)\n\n# https://www.acmicpc.net/problem/1786"},{"alpha_fraction":0.4868420958518982,"alphanum_fraction":0.5065789222717285,"avg_line_length":14.947368621826172,"blob_id":"8ff6c20589f8934c9be0b7aadaf60440e9c38872","content_id":"dc6371fd5843b3f992ba1f6c0ffb912bd97e3c2d","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":304,"license_type":"no_license","max_line_length":74,"num_lines":19,"path":"/알고리즘/온라인저지/2022/02/0201/덩치.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = int(input())\n\nwnhs = []\n\nresult = []\n\nfor n in range(N):\n wnhs.append(tuple(map(int, input().split())))\n\nfor i in range(N):\n cnt = 1\n\n for j in range(N):\n if i != j and wnhs[i][0] < wnhs[j][0] and wnhs[i][1] < wnhs[j][1]:\n cnt += 1\n\n result.append(cnt)\n\nprint(*result)\n\n"},{"alpha_fraction":0.47752809524536133,"alphanum_fraction":0.5,"avg_line_length":18.83333396911621,"blob_id":"7b250ef340653b42f12db4340c6720cd27c8e1a5","content_id":"31fd26b84973f5933fabb7aca107357696aab2ae","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":356,"license_type":"no_license","max_line_length":41,"num_lines":18,"path":"/알고리즘/온라인저지/2022/10/1028/기숙사 바닥.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\n\nR, B = map(int, input().rstrip().split())\ndivisors = []\nfor i in range(1, int((R+B)**0.5+1)):\n if not (R+B)%i:\n divisors.append((i, (R+B)//i))\nfor divisor in divisors:\n W, L = divisor\n red = 0\n if W > 1:\n red += (W+L-2)*2\n else: red = L\n if red == R:\n print(L, W)\n break"},{"alpha_fraction":0.5775076150894165,"alphanum_fraction":0.6003039479255676,"avg_line_length":22.535715103149414,"blob_id":"84cea56092292d36844c6845260b465ec6f6bf50","content_id":"a4ffcf7764b8d5b1c3f6a76659bb0d5702aefdcf","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1008,"license_type":"no_license","max_line_length":53,"num_lines":28,"path":"/알고리즘/온라인저지/2022/10/1023/태상이의 훈련소 생활.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\n\nN, M = map(int, input().rstrip().split())\narr = list(map(int, input().rstrip().split()))\nacc = [0]*(N+1)\nfor m in range(M):\n a, b, k = map(int, input().rstrip().split())\n acc[a-1] += k\n acc[b] -= k\ndp = [0]*(N+1)\ndp[0] = acc[0]\nfor i in range(1, N+1):\n dp[i] = dp[i-1] + acc[i]\n print(arr[i-1] + dp[i-1], end=' ')\n\n\"\"\"\n누적합 배열인 acc를 생성한다\nacc에는 누적합의 시작과 끝만 들어있으며\n누적합이 시작될 때 k만큼 더했다가 끝나면서 k만큼 빼준다\n현재 누적합은 변수로 가지고 있지는 않고\n전에 계산한 누적합(dp[i-1])을 불러와서 acc[i]와 더한다\nacc[i]가 0일 경우, 이전 누적합을 그대로 사용하며 그 값은 dp[i-1]에 같이 들어있다\n해당 누적합이 종료되는 경우 k만큼 빼주어 해당 누적합을 종료한다\ndp에 들어있는 값은 m줄 만큼 들어온 입력들의 누적합이며\n이를 원 배열과 합한 결과를 출력한다\n\"\"\""},{"alpha_fraction":0.4058355391025543,"alphanum_fraction":0.48275861144065857,"avg_line_length":22.625,"blob_id":"abf13c9c74924b326531475eb19cb10d728c874d","content_id":"aaddab8f944d7d10ef549937cf24166b4b49f8ce","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":377,"license_type":"no_license","max_line_length":49,"num_lines":16,"path":"/알고리즘/온라인저지/2022/10/1003/달나라 토끼를 위한 구매대금 지불 도우미.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\nINF = int(1e9)\n\nN = int(input().rstrip())\ndp = [INF]*(int(1e5)+10)\ndp[0], dp[1], dp[2], dp[5], dp[7] = 0, 1, 1, 1, 1\nfor i in range(1, int(1e5)+1):\n tmp = dp[i]+1\n if dp[i]:\n dp[i+1] = min(dp[i+1], tmp)\n dp[i+2] = min(dp[i+2], tmp) \n dp[i+5] = min(dp[i+5], tmp) \n dp[i+7] = min(dp[i+7], tmp)\nprint(dp[N])"},{"alpha_fraction":0.46932005882263184,"alphanum_fraction":0.5107794404029846,"avg_line_length":34.52941131591797,"blob_id":"610a8a13dd70da3a712496e2a80da51279831284","content_id":"65180dab07673799bfc7fcca60b0c9f2e58a7576","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":775,"license_type":"no_license","max_line_length":80,"num_lines":17,"path":"/알고리즘/온라인저지/2022/10/1020/개미.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N, M = map(int, input().split())\nants1, ants2 = list(input()), list(input())\nT = int(input())\narr = []\nfor i in range(N): arr.append((ants1[::-1][i], 1)) # 오른쪽으로 가려고 함, 배열이 뒤집히는 점에 주의\nfor i in range(M): arr.append((ants2[i], -1)) # 왼쪽으로 가려고 함\ntime = 0\nwhile time < T: # T초동안 움직일 것\n time += 1\n i = 0\n while i < N+M-1:\n ant1, ant2 = arr[i], arr[i+1]\n if ant1[1] == 1 and ant2[1] == -1: # 진행하려는 방향이 교차하는 경우\n arr[i], arr[i+1] = arr[i+1], arr[i] # 서로 자리를 바꿔준다 == 두 개미중 하나가 점프\n i += 1 # 인덱스 추가로 하나 더 늘려주기\n i += 1 # 다음 개미 탐색\nfor a in arr: print(a[0], end='')"},{"alpha_fraction":0.5675675868988037,"alphanum_fraction":0.5945945978164673,"avg_line_length":74,"blob_id":"40d124aa2870a85ba5367356709e60c92989de1f","content_id":"86918264e4c5bda9ca7d40c6bdf7dc64a47d3187","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":74,"license_type":"no_license","max_line_length":74,"num_lines":1,"path":"/알고리즘/온라인저지/2022/08/0825/성택이의 은밀한 비밀번호.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"for _ in range(int(input())): print('yes' if 6<=len(input())<=9 else 'no')"},{"alpha_fraction":0.4747474789619446,"alphanum_fraction":0.49494948983192444,"avg_line_length":18.899999618530273,"blob_id":"1c0a2e49b87e3d5c3f0785a2ce2a4c93e9fa697e","content_id":"32578c8e1c7aa32ef2419038fb4d8ffe2ff6452c","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":198,"license_type":"no_license","max_line_length":33,"num_lines":10,"path":"/알고리즘/온라인저지/2022/09/0909/지영 공주님의 마법 거울.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = int(input())\narr = [input() for _ in range(N)]\nK = int(input())\nif K == 1:\n for a in arr: print(a)\nelif K == 2:\n for a in arr: print(a[::-1])\nelse:\n for a in arr[::-1]:\n print(a)"},{"alpha_fraction":0.5416666865348816,"alphanum_fraction":0.5625,"avg_line_length":25.272727966308594,"blob_id":"2b053e33c44bc7540abf65a19ec323e070c2f6a4","content_id":"7718290e102e87952bb763a9dbd9108e39859964","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":288,"license_type":"no_license","max_line_length":51,"num_lines":11,"path":"/알고리즘/온라인저지/2022/11/1105/해밍 거리.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\n\nfor _ in range(int(input().rstrip())):\n nums = [input().rstrip() for i in range(2)]\n result = 0\n for i in range(len(nums[0])):\n if nums[0][i] != nums[1][i]:\n result += 1\n print('Hamming distance is {}.'.format(result))"},{"alpha_fraction":0.5492957830429077,"alphanum_fraction":0.577464759349823,"avg_line_length":13.300000190734863,"blob_id":"3b10d57aa2c43d315707e48a469db74632d0d66f","content_id":"3d37083c698ecfb2c734b2d116847979d0008758","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":142,"license_type":"no_license","max_line_length":29,"num_lines":10,"path":"/알고리즘/온라인저지/2023/02/0218/회문은 회문아니야!!.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\n\nS = input().strip()\nl = len(S)\n\nif S == S[0]*l: print(-1)\nelif S == S[::-1]: print(l-1)\nelse: print(l)"},{"alpha_fraction":0.47413793206214905,"alphanum_fraction":0.47413793206214905,"avg_line_length":28.08333396911621,"blob_id":"5e68bcf6566601e625145a08f22f84697f7cd385","content_id":"d4d32e30008f31dbad65eea6317ea51f505c6075","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":348,"license_type":"no_license","max_line_length":60,"num_lines":12,"path":"/알고리즘/온라인저지/2022/12/1224/사칙연산.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"for _ in range(int(input())):\n A, ope, B, equal, answer = input().split()\n A, B, answer = map(int, [A, B, answer])\n if ope == '+':\n result = A+B\n elif ope == '-':\n result = A-B\n elif ope == '*':\n result = A*B\n elif ope == '/':\n result = A//B\n print('correct' if result == answer else 'wrong answer')"},{"alpha_fraction":0.5234899520874023,"alphanum_fraction":0.5335570573806763,"avg_line_length":18.933332443237305,"blob_id":"521c7e12f97e690cafe762e9124f0230edd96e98","content_id":"12a5ef32ee62cacd54ea0a33308d0f845a02c54f","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":298,"license_type":"no_license","max_line_length":40,"num_lines":15,"path":"/알고리즘/온라인저지/2022/10/1026/유진수.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\n\nN = input().rstrip()\nflag = False\nfor i in range(1, len(N)):\n A, B = N[:i], N[i:]\n front, rear = 1, 1\n for a in A:\n front *= int(a)\n for b in B:\n rear *= int(b)\n if front == rear: flag = True; break\nprint('YES' if flag else 'NO')"},{"alpha_fraction":0.44718310236930847,"alphanum_fraction":0.5211267471313477,"avg_line_length":12.571428298950195,"blob_id":"de3c948ae43b86f88aa5127864984822b76bf77b","content_id":"207f6e5660aa28ae440eaf3eb99103b066314f44","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":284,"license_type":"no_license","max_line_length":35,"num_lines":21,"path":"/알고리즘/[템플릿]/유클리드 호제법/유클리드 호제법.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import timeit\nstart = timeit.default_timer()\n\n\na, b = 12368711, 2678178\n\nwhile a % b != 0:\n a, b = b, a % b\n\nprint(b)\n\n\n\n\n# for i in range(max(a,b),0,-1):\n# if a % i == 0 and b % i == 0:\n# print(i)\n# break\n\nend = timeit.default_timer()\nprint(f'{end-start:.5f}')"},{"alpha_fraction":0.5405405163764954,"alphanum_fraction":0.5608108043670654,"avg_line_length":20.214284896850586,"blob_id":"8ce7e43e5fa89d92e94d907b524eac0e9941a384","content_id":"7534a2259b78d0bdad9cf5a2e000d46e6d5b4b10","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":296,"license_type":"no_license","max_line_length":38,"num_lines":14,"path":"/알고리즘/온라인저지/2022/11/1109/지우개.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\n\nN = int(input().rstrip())\narr = list(range(1, N+1))\nwhile len(arr) > 1:\n pop_idx_list = []\n for i in range(len(arr)):\n if not i%2:\n pop_idx_list.append(i)\n for pop_idx in pop_idx_list[::-1]:\n arr.pop(pop_idx)\nprint(arr[0])"},{"alpha_fraction":0.49528300762176514,"alphanum_fraction":0.5141509175300598,"avg_line_length":24,"blob_id":"f07290d36abc2eb61d77e8c4da725cd0903bc131","content_id":"7199c117e430453677f2e7cc6f3ed5a9a19dae83","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":424,"license_type":"no_license","max_line_length":41,"num_lines":17,"path":"/알고리즘/온라인저지/2022/10/1008/첼시를 도와줘!.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\n\nfor _ in range(int(input().rstrip())):\n P = int(input().rstrip())\n cost, name = [], []\n for p in range(P):\n player = input().rstrip().split()\n cost.append(int(player[0]))\n name.append(player[1])\n result = [0, 0]\n for i in range(P):\n if cost[i] > result[0]:\n result[0] = cost[i]\n result[1] = i\n print(name[result[1]])"},{"alpha_fraction":0.5017921328544617,"alphanum_fraction":0.5232974886894226,"avg_line_length":22.33333396911621,"blob_id":"fd9b98cfcbb969b138d0826b553da5f2147db3ac","content_id":"1571e63c2fb1ad23453a4aff1c8e7761ded850f5","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":279,"license_type":"no_license","max_line_length":50,"num_lines":12,"path":"/알고리즘/온라인저지/2022/10/1003/Maximum Subarray.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\n\nfor _ in [0]*int(input().rstrip()):\n N = int(input().rstrip())\n arr = list(map(int, input().rstrip().split()))\n dp = [0]*N\n dp[0] = arr[0]\n for i in range(1, N):\n dp[i] = max(dp[i-1]+arr[i], arr[i])\n print(max(dp))"},{"alpha_fraction":0.4647887349128723,"alphanum_fraction":0.49295774102211,"avg_line_length":34.75,"blob_id":"9dd2f49874fe37c9153133107a8207728691bfcb","content_id":"54ebf63835bcf8c14bac6d6d71d7dca75bfeb429","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":142,"license_type":"no_license","max_line_length":35,"num_lines":4,"path":"/알고리즘/온라인저지/2023/03/0306/백발백준하는 명사수.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"A, B, C = map(int, input().split())\nD, E, F = map(int, input().split())\ntmp = ((A-D)**2 + (B-E)**2) ** 0.5\nprint('YES' if tmp < C+F else 'NO')"},{"alpha_fraction":0.5824742317199707,"alphanum_fraction":0.5979381203651428,"avg_line_length":23.375,"blob_id":"27fa5ee763e6ee8c32dc89cc1202d911b4dbe01b","content_id":"a8d2ab868644aebcf2962bf18f6b33b95e0cadee","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":194,"license_type":"no_license","max_line_length":55,"num_lines":8,"path":"/알고리즘/온라인저지/2022/09/0924/연속부분최대곱.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\n\nN = int(input().rstrip())\ndp = [float(input().rstrip()) for _ in range(N)]\nfor i in range(1, N): dp[i] = max(dp[i], dp[i]*dp[i-1])\nprint(f'{max(dp):.3f}')"},{"alpha_fraction":0.5766870975494385,"alphanum_fraction":0.5981594920158386,"avg_line_length":20.799999237060547,"blob_id":"2e9ea56b06fab675e78195b0bc6c94e3d5701dde","content_id":"2dbee2c71ac3d2500e195daaa0b5946279196ba4","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":326,"license_type":"no_license","max_line_length":54,"num_lines":15,"path":"/알고리즘/온라인저지/2022/10/1003/두 수의 합.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\n\nN = int(input().rstrip())\narr = sorted(list(map(int, input().rstrip().split())))\nK = int(input().rstrip())\nresult = 0\nstart, end = 0, N-1\nwhile start<end:\n tmp = arr[start]+arr[end]\n if tmp > K: end -= 1\n elif tmp < K: start += 1\n else: result += 1; start += 1\nprint(result)"},{"alpha_fraction":0.5569105744361877,"alphanum_fraction":0.577235758304596,"avg_line_length":26.44444465637207,"blob_id":"99d07dccd5f757a19e860473aa22ab761bf74e70","content_id":"0c933460f10d0fa7e079da08281aa7c545b5a807","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":246,"license_type":"no_license","max_line_length":59,"num_lines":9,"path":"/알고리즘/온라인저지/2022/11/1107/한다 안한다.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\n\nfor _ in range(int(input().rstrip())):\n word = input().rstrip()\n prev, rear = word[:len(word)//2], word[len(word)//2:]\n rear = rear[::-1]\n print('Do-it' if prev[-1] == rear[-1] else 'Do-it-Not')"},{"alpha_fraction":0.4350649416446686,"alphanum_fraction":0.46320345997810364,"avg_line_length":26.235294342041016,"blob_id":"21c3f39199275cf4a031a5d15098d3ea68032a4b","content_id":"8fd0d968d99f14f94ca0ce73edcc0a15f41a15ac","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":558,"license_type":"no_license","max_line_length":62,"num_lines":17,"path":"/알고리즘/온라인저지/2022/08/0817/순열 사이클.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"for _ in range(int(input())):\n N = int(input())\n P = [list(range(1, N+1)), list(map(int, input().split()))]\n used, result = [0] * N, 0\n for i in range(N):\n if not used[i]:\n used[i], start, now = 1, P[0][i], P[1][i]\n while now != start:\n used[now-1] = 1\n now = P[1][now-1]\n result += 1\n print(result)\n\n\"\"\"\n문제 조건이, 1부터 N까지의 자연수로 이루어졌다고 \n주어졌기 때문에, 한 사이클을 돌 때 인덱스를 고민하지 않아도 되었다\n\"\"\""},{"alpha_fraction":0.5480769276618958,"alphanum_fraction":0.6282051205635071,"avg_line_length":27.454545974731445,"blob_id":"1485f432d58b7213f6c81b97ae80a75cc00a2940","content_id":"e61498fcab4ef789082b8b431aa62d3148cad1aa","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":312,"license_type":"no_license","max_line_length":40,"num_lines":11,"path":"/알고리즘/온라인저지/2023/01/0115/나의 학점은.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"scores = list(map(int, input().split()))\nhongik = int(input())\nrank = scores.index(hongik)+1\nif 1<=rank<6: result = 'A+'\nelif 6<=rank<16: result = 'A0'\nelif 16<=rank<31: result = 'B+'\nelif 31<=rank<36: result = 'B0'\nelif 36<=rank<46: result = 'C+'\nelif 46<=rank<49: result = 'C0'\nelse: result = 'F'\nprint(result)"},{"alpha_fraction":0.43801653385162354,"alphanum_fraction":0.43801653385162354,"avg_line_length":15.199999809265137,"blob_id":"f387025a3fb539b5d8507eaecea275d7639558ce","content_id":"b95b7b427073e1c2c3e2eab53c452ea200e72e55","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":242,"license_type":"no_license","max_line_length":35,"num_lines":15,"path":"/알고리즘/온라인저지/2023/05/0517/Andando no tempo.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"A, B, C = map(int, input().split())\nresult = 'N'\nif A == B: \n result = 'S'\nif C == B: \n result = 'S'\nif A == C: \n result = 'S'\nif A+C == B: \n result = 'S'\nif A == B+C: \n result = 'S'\nif A+B == C: \n result = 'S'\nprint(result)"},{"alpha_fraction":0.40856030583381653,"alphanum_fraction":0.4591439664363861,"avg_line_length":18.846153259277344,"blob_id":"c150362ddca8e9e21887bcafcd44cc48859de273","content_id":"862003390eb7a0ba29bb02a1899ba17182f64689","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":257,"license_type":"no_license","max_line_length":32,"num_lines":13,"path":"/알고리즘/온라인저지/2023/05/0527/Electric Bill.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"A, B = map(int, input().split())\nN = int(input())\nfor i in range(N):\n C = int(input())\n print(C, end=' ')\n result = 0\n if C > 1000:\n result += A*1000\n C -= 1000\n result += B*C\n else:\n result = A*C\n print(result)"},{"alpha_fraction":0.5373134613037109,"alphanum_fraction":0.6268656849861145,"avg_line_length":16,"blob_id":"be411eec98f587d7ef761fd8f415f9214e018343","content_id":"aaf9ba812bca29e30ed71f9ae0b42a3574b51789","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":67,"license_type":"no_license","max_line_length":20,"num_lines":4,"path":"/알고리즘/온라인저지/2022/12/1231/Even or Odd.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = int(input())\nif N%2:print(0)\nelif N//2%2:print(1)\nelse:print(2)"},{"alpha_fraction":0.6019417643547058,"alphanum_fraction":0.6019417643547058,"avg_line_length":25,"blob_id":"b57ba08f0ccecd4c0ac5f00568d2ac72b5074b73","content_id":"480eabf627f685057794bfcf64e27afdc70b9a4f","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":103,"license_type":"no_license","max_line_length":36,"num_lines":4,"path":"/알고리즘/온라인저지/2022/02/0205/시험 점수.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"mk = list(map(int, input().split()))\nms = list(map(int, input().split()))\n\nprint(max(sum(mk), sum(ms)))"},{"alpha_fraction":0.4843304753303528,"alphanum_fraction":0.5327635407447815,"avg_line_length":22.46666717529297,"blob_id":"edbb4049033f0319e1c814f230bbaf55f40e9499","content_id":"cd595490d148a0e79a92d95f3dec6a881bd8d2d6","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":477,"license_type":"no_license","max_line_length":56,"num_lines":15,"path":"/알고리즘/온라인저지/2022/09/0911/RGB거리.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = int(input())\ndp = [list(map(int, input().split())) for _ in range(N)]\nfor i in range(1, len(dp)):\n dp[i][0] += min(dp[i-1][1], dp[i-1][2])\n dp[i][1] += min(dp[i-1][0], dp[i-1][2])\n dp[i][2] += min(dp[i-1][0], dp[i-1][1])\nprint(min(dp[N-1]))\n\n\"\"\"\nDP문제 진짜 현타오네\n코드가 이렇게 간단할 수가 있나\n배열 그대로 들고 이동하면서\n해당 집이 해당 색으로 집을 칠할 때의 \n최소값들을 전부 구하면서 이동한다\n\"\"\""},{"alpha_fraction":0.5537634491920471,"alphanum_fraction":0.5645161271095276,"avg_line_length":30.16666603088379,"blob_id":"d08dd5cdd8fad69d413bd7e570bdccc10d6af51b","content_id":"382be1ec83a5e76a1f39a4d004a9b3659035c269","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":186,"license_type":"no_license","max_line_length":48,"num_lines":6,"path":"/알고리즘/온라인저지/2023/01/0107/암기왕.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"for _ in range(int(input())):\n input()\n notes = set(map(int, input().split()))\n input()\n for note in list(map(int, input().split())):\n print(1 if note in notes else 0)"},{"alpha_fraction":0.4583333432674408,"alphanum_fraction":0.46296295523643494,"avg_line_length":18.727272033691406,"blob_id":"a1cc1aea855633f1eb7b7e3449bb76e36a83f038","content_id":"4f2faf58669f42eac5d3f516615e416b3c99ca4a","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":216,"license_type":"no_license","max_line_length":40,"num_lines":11,"path":"/알고리즘/SWEA/LEARN/Course/1. Programming Beginner/파이썬 프로그래밍 기초(2)/40차시 4. 문자열 - 연습문제 4.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"# while True:\n# tmp = input()\n# print('>> {}'.format(tmp.upper()))\n# if not tmp:\n# exit()\n\nfor i in range(3):\n tmp = input()\n print('>> {}'.format(tmp.upper()))\n if not tmp:\n break"},{"alpha_fraction":0.4615384638309479,"alphanum_fraction":0.5054945349693298,"avg_line_length":29.5,"blob_id":"3fe44d4a3ac3ceae0e69bb902d1f05e070d49e92","content_id":"79374eea1e74a122f91bfa38ec1d89197f842164","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":182,"license_type":"no_license","max_line_length":47,"num_lines":6,"path":"/알고리즘/온라인저지/2022/08/0826/Football Scoring.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"C = [6, 3, 2, 1, 2] # change\nfor _ in range(2):\n S = list(map(int, input().split())) # score\n result = 0\n for i in range(5): result += C[i] * S[i]\n print(result, end=' ')"},{"alpha_fraction":0.5773195624351501,"alphanum_fraction":0.5979381203651428,"avg_line_length":16.727272033691406,"blob_id":"cb7e8599953499fb8eb60355540fd6a5cef010fc","content_id":"dcc19782001d138bb7a80bb3640f34d79669c01c","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":194,"license_type":"no_license","max_line_length":31,"num_lines":11,"path":"/알고리즘/온라인저지/2022/10/1002/내 선물을 받아줘 2.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\n\nN = int(input().rstrip())\narr = input().rstrip()\nresult = 0\nfor i in range(N-1):\n tmp = arr[i] + arr[i+1]\n if tmp == 'EW': result += 1\nprint(result)"},{"alpha_fraction":0.5378151535987854,"alphanum_fraction":0.5462185144424438,"avg_line_length":11,"blob_id":"e0c9b7601595cc1aa76f73f594f1d174db3a652b","content_id":"edfe5a70b9e7e7fb5db21302baca0b88a9487c5a","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":119,"license_type":"no_license","max_line_length":36,"num_lines":10,"path":"/알고리즘/온라인저지/2022/02/0205/사과.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = int(input())\n\nresult = 0\n\nfor n in range(N):\n s, a = map(int, input().split())\n\n result += a%s\n\nprint(result)"},{"alpha_fraction":0.6412213444709778,"alphanum_fraction":0.6412213444709778,"avg_line_length":25.399999618530273,"blob_id":"3f54bb447531d5ba55947d9f493ff8f696ffd578","content_id":"c195c344aeb47dc5bca5908bbeff9d083593ebc1","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":131,"license_type":"no_license","max_line_length":38,"num_lines":5,"path":"/알고리즘/온라인저지/2021/08/0822/직사각형에서 탈출.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"x, y, w, h = map(int, input().split())\ndistance = []\ndistance.append(min(x, w-x))\ndistance.append(min(y, h-y))\nprint(min(distance))"},{"alpha_fraction":0.6243094205856323,"alphanum_fraction":0.6243094205856323,"avg_line_length":35,"blob_id":"63a0c7356245db393cdcaaeca142cf66c8291356","content_id":"08256a863a5058f128b1548992acf9a7f342aec6","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":181,"license_type":"no_license","max_line_length":116,"num_lines":5,"path":"/알고리즘/SWEA/LEARN/Course/1. Programming Beginner/파이썬 프로그래밍 기초(2)/4차시 2. 자료구조 – 리스트, 튜플 - 연습문제 2.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"s = 'Python is powerful... and fast; plays well with others; runs everywhere; is friendly & easy to learn; is Open.'\n\nfor i in s:\n if i not in 'aeiou':\n print(i, end='')\n\n"},{"alpha_fraction":0.3636363744735718,"alphanum_fraction":0.38181817531585693,"avg_line_length":17.5,"blob_id":"32b1b3caec9718e0d9b91be7dabb8f7d1617c653","content_id":"c464d215f6d79ec64626296ac2d079b1ca4f224a","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":110,"license_type":"no_license","max_line_length":23,"num_lines":6,"path":"/알고리즘/온라인저지/2022/05/0526/별 찍기 - 20.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = int(input())\nfor n in range(N):\n if n%2 == 0:\n print('* ' * N)\n else:\n print(' *' * N)"},{"alpha_fraction":0.5142624378204346,"alphanum_fraction":0.5509372353553772,"avg_line_length":34.08571243286133,"blob_id":"042dbbb25cd79bd3eba22a38f8da120c83eaff27","content_id":"30078684c569aae908149f1c6bf23d09d27c5f86","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1567,"license_type":"no_license","max_line_length":100,"num_lines":35,"path":"/알고리즘/온라인저지/2022/09/0916/공주님을 구해라!.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\nfrom collections import deque\n\ninput = sys.stdin.readline\ndy, dx = [-1, 1, 0, 0], [0, 0, -1, 1]\n\nN, M, T = map(int, input().rstrip().split())\narr = [list(map(int, input().rstrip().split())) for _ in range(N)]\nvisited = [[0]*M for _ in range(N)]\ndistance = int(1e9) # 임의의 거리 최대값\nQ = deque()\nif arr[0][0] == 2: distance = N+M-2 # 시작부터 그람인 경우, 무지성 택시거리 이동\nelse: # 시작이 그람은 아닌 경우\n Q.append((0, 0, 0)) # move, y, x\n visited[0][0] = 1\nwhile Q:\n move, y, x = Q.popleft()\n if y == N-1 and x == M-1: distance = min(distance, move) # 공주님한테 도착했을 때 걸린 시간 갱신\n for i in range(4): # 델타 이동\n ny, nx = y+dy[i], x+dx[i]\n if 0<=ny<N and 0<=nx<M and not visited[ny][nx] and arr[ny][nx] != 1: # 방문한 적이 없으며, 마법벽이 아닐 때\n Q.append((move+1, ny, nx)) # 빈 방이든 그람이든 일단 탐색\n visited[ny][nx] = 1\n if arr[ny][nx] == 2: # 그람인 경우\n gram = move+1 + (N+M-2-ny-nx) # 무지성 택시이동, 왔던 길 무시 가능\n distance = min(distance, gram) # 돌고 돌아 그람을 줍는 경우는 배제된다, BFS이니까!\nprint(distance if distance<=T else 'Fail') # T시간 이내에 공주님을 구할 수 있습니까?\n\n\"\"\"\n그람을 주운 자리에서 무지성 택시거리로 이동 가능\n택시거리 : 두 좌표 (x1, y1), (x2, y2)의 가로+세로\n abs(x1-x2) + abs(y1-y2)\n\"\"\"\n\n# https://www.acmicpc.net/problem/17836"},{"alpha_fraction":0.4115842580795288,"alphanum_fraction":0.47708407044410706,"avg_line_length":24.781394958496094,"blob_id":"9956cd3b26e271a99c53ef00bdb8a36dc307571d","content_id":"cd2949dd5072ba3030dc351fe49eaf42388d2afb","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":6852,"license_type":"no_license","max_line_length":101,"num_lines":215,"path":"/알고리즘/온라인저지/2022/08/0812/말이 되고픈 원숭이.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\nfrom collections import deque\n\ninput = sys.stdin.readline\n\ndy = [-1, 1, 0, 0] # delta y\ndx = [0, 0, -1, 1] # delta x\nky = [-2, -1, 1, 2, 2, 1, -1, -2] # knight y\nkx = [1, 2, 2, 1, -1, -2, -2, -1] # knight x\n\ndef bfs():\n Q = deque()\n Q.append((0, 0, K, 0)) # y, x, k, move\n # 3차원 방문배열\n # 만약 K가 2일 때, 해당 좌표까지 나이트 이동을 0번 혹은 1번 혹은 2번 사용하여\n # 해당 좌표에 도착할 수 있는지 체크하기 위함\n visited = [[[False]*(K+1) for _ in range(W)] for _ in range(H)] \n # 아래 코드에서 방문 좌표를 추가하면서 방문처리 할 것이므로\n # 시작 점 방문 처리\n visited[0][0][K] = True \n while Q: # 탐색할 좌표가 있을 때\n y, x, k, move = Q.popleft() # 세로, 가로, 남은 나이트 이동 횟수, 이동한 횟수\n if y == H-1 and x == W-1: # 도착했다면\n return move # 그 때의 이동 횟수\n if k > 0: # 나이트 이동 횟수가 남아있을 때\n for i in range(8):\n ny = y+ky[i] # 나이트 이동 y\n nx = x+kx[i] # 나이트 이동 x\n # 범위 안에 있고, 장애물이 아니면서, 나이트이동으로 탐색할 수 있다면\n if 0<=ny<H and 0<=nx<W and not arr[ny][nx] and not visited[ny][nx][k-1]:\n # 해당 좌표를 탐색할 것이며\n # 아직 나이트 이동을 k-1번 할 수 있습니다\n visited[ny][nx][k-1] = True \n Q.append((ny, nx, k-1, move+1))\n for i in range(4):\n ny = y+dy[i] # 델타 이동 y\n nx = x+dx[i] # 델타 이동 x\n # 범위 안에 있고, 장애물이 아니면서\n # 현재 사용가능한 나이트이동의 횟수로 해당 좌표를 방문한 적이 없을 때\n if 0<=ny<H and 0<=nx<W and not arr[ny][nx] and not visited[ny][nx][k]:\n # 해당 좌표를 탐색할 것이며\n # 나이트 이동을 사용하지 않고 탐색합니다\n # 여전히 k번의 나이트 이동을 사용할 수 있습니다\n visited[ny][nx][k] = True\n Q.append((ny, nx, k, move+1))\n return -1 # 도착할 수 없음\n\nK = int(input())\nW, H = map(int, input().split())\narr = tuple(tuple(map(int, input().split())) for _ in range(H)) # 시간 단축을 위한 tuple (list보다 빠름, 아마도..?)\nprint(bfs())\n\n\n\"\"\"\n시간 : 120분, 미해결, 정답 풀이 확인 \n\n풀이\n 나이트이동이 가능하다고 해서 아무때나 그리디하게 적용하게 되면 오답이다\n 세로 가로 에서 하나 더 추가한 3차원 방문배열이 필요하다\n 방문 배열의 해당 좌표에 몇번의 나이트 이동으로 도달하였는지 기록하며 진행한다\n 나이트이동과 그냥 이동을 통한 탐색을 동시에 진행한다\n\n반례 모음\n\n1\n6 6\n0 0 1 1 0 0\n1 1 1 0 0 0\n0 0 1 1 0 0\n1 0 1 1 1 1\n1 0 0 1 1 1\n0 0 0 0 0 0\nanswer : 8\n\n2\n6 6\n0 0 1 1 0 0\n1 1 1 0 0 0\n0 0 1 1 0 0\n1 0 1 1 1 1\n1 0 0 1 1 1\n0 0 0 0 0 0\nanswer : 6\n\n1\n2 3\n0 1\n1 1\n1 0\nanswer : 1\n\n4\n6 6\n0 0 1 1 0 0\n1 1 1 0 0 0\n0 0 1 1 0 0\n1 0 1 1 1 1\n1 0 0 1 1 1\n0 0 0 0 0 0\nanswer : 4\n\n3\n4 5\n0 1 1 1\n1 1 0 1\n1 1 1 1\n1 1 1 0\n1 1 1 0\nanswer : 3\n\n1\n5 5\n0 0 0 0 0\n0 0 0 0 0\n0 0 0 0 0\n0 0 0 1 1\n0 0 0 1 0\nanswer : 6\n\n1\n4 4\n0 0 1 1\n0 0 1 1\n0 0 1 1\n1 1 1 0\nanswer : 4\n\"\"\"\n\n\n# 쾅\n# from collections import deque\n\n# K = int(input())\n# W, H = map(int, input().split())\n# arr = [list(map(int, input().split())) for _ in range(H)]\n# result = -1\n# K_dy = [-2, -1, 1, 2, 2, 1, -1, -2] # Knight dy\n# K_dx = [1, 2, 2, 1, -1, -2, -2, -1] # Knight dx\n# dy = [-1, 1, 0, 0] # 나이트 이동 이후 델타 dy\n# dx = [0, 0, -1, 1] # 나이트 이동 이후 델타 dx\n# Q = deque()\n# Q.append((H-1, W-1, 0, 0)) # (y, x, K_cnt, move)\n# visited = [[0]*W for _ in range(H)] # 방문배열\n# K_visited = [[0]*W for _ in range(H)] # 나이트 이동 방문배열\n# visited[H-1][W-1] = 1\n# K_visited[H-1][W-1] = 1\n# tmp = int(1e9) # 가상의 최소값\n# while Q:\n# y, x, K_cnt, move = Q.popleft()\n# if y == 0 and x == 0: # 도착했을 경우\n# if move < tmp: tmp = move\n# continue\n# if visited[y][x]: continue\n# if K_cnt < K: # 나이트 이동을 할 기회가 남아있을 때\n# for i in range(8):\n# ny = y + K_dy[i]\n# nx = x + K_dx[i]\n# # 이동하려는 좌표가 범위안에 있고, 방문한 적이 없고, 장애물이 아닐 때\n# if 0<=ny<H and 0<=nx<W and not K_visited[ny][nx] and not arr[ny][nx]:\n# Q.append((ny, nx, K_cnt+1, move+1))\n# K_visited[ny][nx] = 1\n# for i in range(4):\n# ny = y + dy[i]\n# nx = x + dx[i]\n# # 이동하려는 좌표가 범위안에 있고, 방문한 적이 없고, 장애물이 아닐 때\n# if 0<=ny<H and 0<=nx<W and not visited[ny][nx] and not arr[ny][nx]:\n# Q.append((ny, nx, K_cnt, move+1))\n# visited[ny][nx] = 1\n# for v in visited: print(v)\n# print(tmp if tmp != int(1e9) else result)\n\n\n# 쾅쾅\n# from collections import deque\n\n# K = int(input())\n# W, H = map(int, input().split())\n# arr = [list(map(int, input().split())) for _ in range(H)]\n# result = -1\n# K_dy = [-2, -1, 1, 2, 2, 1, -1, -2] # Knight dy\n# K_dx = [1, 2, 2, 1, -1, -2, -2, -1] # Knight dx\n# dy = [-1, 1, 0, 0] # 나이트 이동 이후 델타 dy\n# dx = [0, 0, -1, 1] # 나이트 이동 이후 델타 dx\n# Q = deque()\n# Q.append((H-1, W-1, 0, 0)) # (y, x, K_cnt, move)\n# visited = [[0]*W for _ in range(H)] # 방문배열\n# tmp = int(1e9) # 가상의 최소값\n# while Q:\n# y, x, K_cnt, move = Q.popleft()\n# if y == 0 and x == 0: # 도착했을 경우\n# tmp = move\n# # print(K_cnt, K)\n# if K_cnt < K: tmp -= (K-K_cnt)*2\n# break\n# if visited[y][x]: continue\n# visited[y][x] = 1\n# blocked = True\n# for i in range(4):\n# ny = y + dy[i]\n# nx = x + dx[i]\n# # 이동하려는 좌표가 범위안에 있고, 방문한 적이 없고, 장애물이 아닐 때\n# if 0<=ny<H and 0<=nx<W and not visited[ny][nx] and not arr[ny][nx]:\n# Q.append((ny, nx, K_cnt, move+1))\n# blocked = False\n# for i in range(8):\n# ny = y + K_dy[i]\n# nx = x + K_dx[i]\n# if ny == 0 and nx == 0:\n# Q.append((ny, nx, K_cnt+1, move+1))\n# elif blocked and K_cnt < K:\n# # 이동하려는 좌표가 범위안에 있고, 방문한 적이 없고, 장애물이 아닐 때\n# if 0<=ny<H and 0<=nx<W and not visited[ny][nx] and not arr[ny][nx]:\n# Q.append((ny, nx, K_cnt+1, move+1))\n# # for v in visited: print(v)\n# print(tmp if tmp != int(1e9) else result)"},{"alpha_fraction":0.5086206793785095,"alphanum_fraction":0.5258620977401733,"avg_line_length":13.625,"blob_id":"11a29653a73b79585508e44040e8bc92445b4942","content_id":"41e535c930a05a2dfc83558fb403bdc7e59ce00d","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":116,"license_type":"no_license","max_line_length":20,"num_lines":8,"path":"/알고리즘/온라인저지/2023/05/0503/줄 세기.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"result = 0\nwhile True:\n try:\n input()\n result += 1\n except EOFError:\n break\nprint(result)"},{"alpha_fraction":0.34090909361839294,"alphanum_fraction":0.3636363744735718,"avg_line_length":19.384614944458008,"blob_id":"3120419b70924cf2f36cba3f4c93dce807e0f0cc","content_id":"02577ddb77a5f6470844d4600fc62d90abbea5ac","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":270,"license_type":"no_license","max_line_length":38,"num_lines":13,"path":"/알고리즘/온라인저지/2022/07/0701/피로도.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"A, B, C, M = map(int, input().split())\nresult = 0\nF = 0 # fatigue : 피로도\nif not A > M:\n for i in range(24):\n if F+A <= M:\n F += A\n result += B\n else:\n F -= C\n if F < 0:\n F = 0\nprint(result)"},{"alpha_fraction":0.5199999809265137,"alphanum_fraction":0.5299999713897705,"avg_line_length":19.066667556762695,"blob_id":"6bab7dfd68e31ce14c5677d36a208b81fcfc71af","content_id":"fff09b0ec6d02517d3145f3888e1b27445f444c9","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":300,"license_type":"no_license","max_line_length":40,"num_lines":15,"path":"/알고리즘/온라인저지/2022/07/0729/나는야 포켓몬 마스터 이다솜.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ndef input():\n return sys.stdin.readline().rstrip()\n\nN, M = map(int, input().split())\nP = ['' for _ in range(N+1)] # pokemon\nfor n in range(1, N+1):\n P[n] = input()\nfor m in range(M):\n Q = input()\n try: # int\n print(P[int(Q)])\n except: # str\n print(P.index(Q))"},{"alpha_fraction":0.41903170943260193,"alphanum_fraction":0.4407345652580261,"avg_line_length":30.552631378173828,"blob_id":"13df03152c058a237f88e9d4b61c3b486a64c0f3","content_id":"9eee1eaef83d9566c9767fb33e674cbd048e6991","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1486,"license_type":"no_license","max_line_length":95,"num_lines":38,"path":"/알고리즘/온라인저지/2022/04/0420/영역 구하기.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"from collections import deque\n\nN, M, K = map(int, input().split())\n# 모눈종이를 전부 1로 채우고, 직사각형으로 채워지는 곳을 0으로 바꿈\narr = [[1]*M for _ in range(N)]\nfor k in range(K):\n area = list(map(int, input().split()))\n for i in range(area[1], area[3]):\n for j in range(area[0], area[2]):\n arr[i][j] = 0\nresult = [] # 넓이를 담을 리스트\n# 델타이동\ndx = [0, 1, 0, -1]\ndy = [1, 0, -1, 0]\nq = deque() # BFS\ncnt = 0 # 넓이(영역)의 개수\n# 모눈종이를 돌다가\nfor n in range(N):\n for m in range(M):\n if arr[n][m]: # 분리된 영역이 있으면\n q.append((m, n)) # 출발\n square = 0 # 넓이값 초기화\n while q: # BFS\n tmp = q.popleft()\n x, y = tmp[0], tmp[1]\n if arr[y][x]:\n arr[y][x] = 0 # 방문 처리\n square += 1 # 넓이 계산\n for i in range(4): # 델타이동 하였을 때\n # 모눈종이를 벗어나지 않으며, 이웃한 분리된영역일 경우\n if (0 <= x+dx[i] < M) and (0 <= y+dy[i] < N) and arr[y+dy[i]][x+dx[i]]:\n q.append((x+dx[i], y+dy[i])) # 탐색점 추가\n result.append(square) # 영역의 넓이 리스트에 저장\n cnt += 1 # 영역 한 개 확인\nresult.sort() # 넓이 오름차순으로 정렬\n# 출력\nprint(cnt)\nprint(*result)"},{"alpha_fraction":0.4285714328289032,"alphanum_fraction":0.4523809552192688,"avg_line_length":16.58333396911621,"blob_id":"b747a114050e1890192fd0efb31e1f9ea47d826d","content_id":"ba5b2da593487a4176cb8ad4db8dfa6e1cdb2639","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":210,"license_type":"no_license","max_line_length":43,"num_lines":12,"path":"/알고리즘/온라인저지/2022/03/0320/감정이입.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"def dec_to_bin(X):\n m = 1\n output = 0\n for x in X[::-1]:\n if int(x):\n output += m\n m *= 2\n return output\n\nA = input()\nB = input()\nprint(bin(dec_to_bin(A)*dec_to_bin(B))[2:])"},{"alpha_fraction":0.4429530203342438,"alphanum_fraction":0.45413869619369507,"avg_line_length":39.727272033691406,"blob_id":"88d0c0c0dd85a0dca3322528dbdb06d962333cd1","content_id":"4381b38cefd92c98c9d99a4c28a9598f27eb5484","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":589,"license_type":"no_license","max_line_length":72,"num_lines":11,"path":"/알고리즘/온라인저지/2022/04/0429/숫자 정사각형.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N, M = map(int, input().split())\narr = [list(map(int, input())) for _ in range(N)] # 숫자 배열 입력 받기\nfor i in range(N, -1, -1): # 가장 큰 정사각형부터 확인\n # 정사각형의 길이가 i+1 일 때\n for j in range(N-i):\n for k in range(M-i):\n # arr[j][k] 는 정사각형 가장 왼쪽 위\n # 보고있는 정사각형의 꼭지점 숫자들이 전부 같을 때\n if arr[j][k] == arr[j][k+i] == arr[j+i][k+i] == arr[j+i][k]:\n print((i+1)**2) # 넓이 구해서 출력\n exit() # 코드 종료"},{"alpha_fraction":0.5344827771186829,"alphanum_fraction":0.5517241358757019,"avg_line_length":18.44444465637207,"blob_id":"007fe795296c04c0818c0c1f67fef61f077cc86e","content_id":"761140506af3dc4a9ad355329530938ea5c2522c","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":174,"license_type":"no_license","max_line_length":39,"num_lines":9,"path":"/알고리즘/온라인저지/2022/03/0327/서버.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N, T = map(int, input().split())\nworks = list(map(int, input().split()))\nresult = 0\nfor work in works:\n T -= work\n if T < 0:\n break\n result += 1\nprint(result)"},{"alpha_fraction":0.5281456708908081,"alphanum_fraction":0.5645695328712463,"avg_line_length":22.269229888916016,"blob_id":"8d1828b06acc1f1d40a55e352bf246d574600fb8","content_id":"67a7c1323419224dfcf75fad4feda8f4d97ac467","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":604,"license_type":"no_license","max_line_length":49,"num_lines":26,"path":"/알고리즘/온라인저지/2022/09/0913/참외밭.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"K = int(input())\nbig = small = 1\nlines = []\nsmall_idx = []\nfor _ in range(6):\n lines.append(list(map(int, input().split())))\nresult = [[] for _ in range(4)]\nwhile lines[2][0] != lines[4][0]:\n lines.append(lines.pop(0))\n lines.append(lines.pop(0))\nfor i in range(6):\n ewsn, length = lines[i][0], lines[i][1]\n ewsn -= 1\n if result[ewsn]:\n small_idx.append(ewsn)\n result[ewsn].append(length)\nfor r in result: \n if len(r) == 1:\n big *= r[0]\ni = 0\nfor s in small_idx[::-1]:\n small *= result[s][i]\n i += 1\nprint((big-small)*K)\n\n# https://www.acmicpc.net/problem/2477"},{"alpha_fraction":0.5952380895614624,"alphanum_fraction":0.6190476417541504,"avg_line_length":20.25,"blob_id":"1035d45dae73e20ded71863a6a431362589341ea","content_id":"1462fcfa17324a03b5cffd4a1a39a4dda820c539","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":84,"license_type":"no_license","max_line_length":41,"num_lines":4,"path":"/알고리즘/온라인저지/2022/08/0805/Bottle Return.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"result = 0\nfor i in list(map(int, input().split())):\n result += i*5\nprint(result)"},{"alpha_fraction":0.47806355357170105,"alphanum_fraction":0.5128592848777771,"avg_line_length":29.090909957885742,"blob_id":"1548df1aeed4c9fa748cf6948a3e6b47fdf84f2e","content_id":"9cf1ca9977314a2ba9d115b0336e9376da7f4d9e","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":997,"license_type":"no_license","max_line_length":58,"num_lines":22,"path":"/알고리즘/온라인저지/2021/08/0821/직사각형 네개의 합집합의 면적 구하기.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"\"\"\"\n좌표평면배열을 만들어서\n직사각형들을 1로 저장하고\n저장하는 과정에서 겹치면 continue\n저장된 1들을 전부 출력\"\"\"\n\narr = [[0]*101 for _ in range(101)] # 0번째칸 추가해서 인덱스와 숫자 일치\nfor tc in range(4): # 모든 케이스는 4개의 직사각형\n x1, y1, x2, y2 = map(int, input().split()) # 좌표들\n for i in range(y1, y2): # y좌표 for문 먼저\n for j in range(x1, x2): # x좌표\n if arr[i][j]: # 값이 들어있으면\n continue # 컨티뉴\n else: # 아직 저장된 값이 없으면\n arr[i][j] = 1 # 1을 저장\n # 합집합은 or연산\n # True or로 넘어가기 때문에 값이 있으면 저장이 되지 않고\n # 합해지는 부분을 연산할 필요가 없어짐\narea = 0 # 면적\nfor ar in arr: # 저장된 배열을 돌면서\n area += sum(ar) # 각 줄을 더해서 면적에 저장\nprint(area) # 출력"},{"alpha_fraction":0.5,"alphanum_fraction":0.5348837375640869,"avg_line_length":20.75,"blob_id":"cd49df5bd2dcd5318ea22a7aa9bb6230a1c5178b","content_id":"8cf4d7f7af75810ca162549a862456b6e976058c","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":86,"license_type":"no_license","max_line_length":49,"num_lines":4,"path":"/알고리즘/온라인저지/2022/02/0209/쿠폰.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = int(input())\n\nfor n in range(N):\n print('${:.2f}'.format(float(input()) * 0.8))"},{"alpha_fraction":0.46979865431785583,"alphanum_fraction":0.48322147130966187,"avg_line_length":29,"blob_id":"655f226db7d4262ee5eefca28cd0d686b8f8d0bc","content_id":"827de99c8d418dae8d758cd36ba071dd69398581","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":149,"license_type":"no_license","max_line_length":46,"num_lines":5,"path":"/알고리즘/온라인저지/2022/09/0904/수 뒤집기.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"for _ in range(int(input())):\n num = input()\n A, B = int(num), int(num[::-1])\n tmp = str(A+B)\n print('YES' if tmp == tmp[::-1] else 'NO')"},{"alpha_fraction":0.4054054021835327,"alphanum_fraction":0.4864864945411682,"avg_line_length":11.666666984558105,"blob_id":"df02734a1decd16cb4f930582d8b87974d1a12d5","content_id":"c81fc81d02fea6cefb76dc897d999e948ac7dc83","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":37,"license_type":"no_license","max_line_length":20,"num_lines":3,"path":"/알고리즘/온라인저지/2022/02/0213/조별과제를 하려는데 조장이 사라졌다.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"L = int(input()) - 1\n\nprint(L//5 + 1)"},{"alpha_fraction":0.47093021869659424,"alphanum_fraction":0.4883720874786377,"avg_line_length":13.416666984558105,"blob_id":"96f20e699840e5de2aff0ada4036ab18fb3cdd95","content_id":"873e782408626c7225957daca916c4bc4876d0cd","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":172,"license_type":"no_license","max_line_length":20,"num_lines":12,"path":"/알고리즘/온라인저지/2023/05/0519/골뱅이 찍기 - 돌아간 ㄹ.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = int(input())\nA = '@'*N\nB = ' '*N\nS = A*3+B+A\nM = A+B+A+B+A\nE = A+B+A*3\nfor i in range(N):\n print(S)\nfor i in range(N*3):\n print(M)\nfor i in range(N):\n print(E)"},{"alpha_fraction":0.5115875005722046,"alphanum_fraction":0.5428736805915833,"avg_line_length":27.31147575378418,"blob_id":"3315b5923cc493c203477967692db618954b7837","content_id":"5a8ce88572db0a31507e8223037fc782a7d7aba4","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":2338,"license_type":"no_license","max_line_length":84,"num_lines":61,"path":"/알고리즘/[템플릿]/BFS/채굴.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\nfrom collections import deque\nfrom copy import deepcopy\n\ninput = sys.stdin.readline\n\ndef delta_move(y, x, D, mine, Q, visited):\n for i in range(4):\n ny, nx = y+dy[i], x+dx[i]\n if 0<=ny<N and 0<=nx<M and not visited[ny][nx]:\n if mine[ny][nx]<=D: # 공기or캘 수 있는 광물\n visited[ny][nx] = 1\n Q.append((ny, nx))\n else: # 캘 수 없는 광물\n visited[ny][nx] = 1 # 방문하였으나 캘 수 없었다\n\ndef BFS(D): # 채굴기의 성능 D\n mine = deepcopy(arr) # 광__산\n mineral = 0 # 채굴기 성능이 D일때 캘 수 있는 광물의 수 초기화\n visited = [[0]*M for _ in range(N)] # 광산 방문배열\n Q = deque()\n Q.append((0, 0)) # 공기층을 추가하였으니, 0,0부터 시작\n visited[0][0] = 1\n while Q: # 캘 수 있는 광물 체크\n y, x = Q.popleft()\n if mine[y][x]: # 광물이면\n mine[y][x] = 0 # 캐고\n mineral += 1 # 저장\n delta_move(y, x, D, mine, Q, visited)\n return mineral # 채굴기 성능이 D일때 캘 수 있는 광물 수\n\ndy, dx = [-1, 1, 0, 0], [0, 0, -1, 1] # 4방향 델타이동\nN, M, K = map(int, input().rstrip().split())\nM += 2\n# 배열 테두리에 공기층 생성\narr = [[0]*M] + [[0]+list(map(int, input().rstrip().split()))+[0] for _ in range(N)]\nN += 1\n# 1<=N,M<=1000, 1<=K<=1e6\n# 채굴기의 성능을 1부터 +1하면서 전수조사 할 수 없다\n# 채굴기의 성능 이분탐색 필요\nresult = int(1e7)\nstart, end = 1, int(1e7)\nwhile start<=end:\n mid = (start+end) // 2\n mineral = BFS(mid) # 현재 채굴기의 성능으로 광물을 채굴해보자\n if mineral>=K: # K개의 광물을 충분히 채굴할 수 있음, 성능 D를 좀 더 높여도 됌\n end = mid-1\n result = min(result, mid)\n else: # 현재 성능으로는 K개의 광물을 채굴할 수 없음\n start = mid+1\nprint(result)\n\n\"\"\"\n이분탐색과 BFS의 혼합문제다\nBFS를 함수화시켜서 이분탐색안에 넣는 편이 좋다\n고난이도 문제로 오면서 \"코드 구조화\"가 중요해지는 것 같다\n탭 3번정도 단위로 끊어서 함수화 시키자\n브론즈 실버등, 간단한 문제도 함수화(구조화)연습을 많이 하자\n\"\"\"\n\n# https://www.acmicpc.net/problem/15573"},{"alpha_fraction":0.4810126721858978,"alphanum_fraction":0.5316455960273743,"avg_line_length":39,"blob_id":"722940d6e14ac6e3f2a13f9ffcd6fccede3691f9","content_id":"47abeb54b1a36dfc85b8c3e4e2948cb9c4f189b5","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":79,"license_type":"no_license","max_line_length":40,"num_lines":2,"path":"/알고리즘/온라인저지/2023/03/0302/Laptop Sticker.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"A, B, C, D = map(int, input().split())\nprint(1 if ((A>C+1) and (B>D+1)) else 0)"},{"alpha_fraction":0.4702194333076477,"alphanum_fraction":0.5023511052131653,"avg_line_length":23.09433937072754,"blob_id":"e78c9ad5ad6bb1a454aa717ee5e9caa52bf7d28e","content_id":"26e07503338452c10745e817f95823ba2cffce06","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1276,"license_type":"no_license","max_line_length":52,"num_lines":53,"path":"/알고리즘/온라인저지/2022/09/0930/빙고.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\ncross = [\n (0, 0), (1, 1), (3, 3), (4, 4),\n (2, 2), \n (4, 0), (3, 1), (1, 3), (0, 4),\n ]\n\ndef check(call):\n bingo = 0\n y, x = arr_dict[call]\n arr[y][x] = 1\n for i in range(5): # ga-ro\n is_bingo = True\n for j in range(5):\n if not arr[i][j]: is_bingo = False\n if is_bingo: bingo += 1\n\n for j in range(5): # se-ro\n is_bingo = True\n for i in range(5):\n if not arr[i][j]: is_bingo = False\n if is_bingo: bingo += 1\n\n is_bingo = True # dae-gak-seon 1\n for c in cross[:5]:\n i, j = c\n if not arr[i][j]: is_bingo = False\n if is_bingo: bingo += 1\n\n is_bingo = True # dae-gak-seon 2\n for c in cross[4:]:\n i, j = c\n if not arr[i][j]: is_bingo = False\n if is_bingo: bingo += 1\n if bingo>=3: return True\n\narr_dict = dict()\nfor i in range(5):\n nums = list(map(int, input().rstrip().split()))\n for j in range(5): arr_dict[nums[j]] = (i, j)\nresult = 0\narr = [[0]*5 for _ in range(5)]\nflag = False\nfor i in range(5):\n calls = list(map(int, input().rstrip().split()))\n if flag: continue\n for call in calls:\n if flag: continue\n result += 1\n if check(call): flag = True\nprint(result)"},{"alpha_fraction":0.5492957830429077,"alphanum_fraction":0.6056337952613831,"avg_line_length":22.33333396911621,"blob_id":"b00e7a89b9c487a1b4dc5afdc2571214cfec6529","content_id":"6d0ceb89c12bd97606505acc02c6881821e78187","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":71,"license_type":"no_license","max_line_length":54,"num_lines":3,"path":"/알고리즘/SWEA/LEARN/Course/1. Programming Beginner/파이썬 프로그래밍 기초(2)/22차시 2. 자료구조 – 리스트, 튜플 - 연습문제 24.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"result = [[[0]*4 for i in range(3)] for j in range(2)]\n\nprint(result)\n\n"},{"alpha_fraction":0.37569060921669006,"alphanum_fraction":0.469613254070282,"avg_line_length":17.149999618530273,"blob_id":"1a8a1ed3c30406a2fd164b29d1a178010bb59862","content_id":"fb74fce9ed63ced4256141431fca86fbabbe1d7c","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":362,"license_type":"no_license","max_line_length":37,"num_lines":20,"path":"/알고리즘/온라인저지/2022/09/0911/수학은 비대면강의입니다.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"from copy import deepcopy\n\nnum = list(map(int, input().split()))\nX, Y = deepcopy(num), deepcopy(num)\nx, y = 0, 0\nX[0] *= num[4]\nX[1] *= num[4]\nX[2] *= num[4]\nX[3] *= num[1]\nX[4] *= num[1]\nX[5] *= num[1]\nx = (X[2]-X[5])//(X[0]-X[3])\nY[0] *= num[3]\nY[1] *= num[3]\nY[2] *= num[3]\nY[3] *= num[0]\nY[4] *= num[0]\nY[5] *= num[0]\ny = (Y[2]-Y[5])//(Y[1]-Y[4])\nprint(x, y)"},{"alpha_fraction":0.41355931758880615,"alphanum_fraction":0.4440678060054779,"avg_line_length":21.769229888916016,"blob_id":"eb0488ba01812142344f4cb0b1eae7d4534a51c6","content_id":"b19ebe4bb903a740103e7a0c1b05d9e0cea54ed3","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":321,"license_type":"no_license","max_line_length":44,"num_lines":13,"path":"/알고리즘/온라인저지/2022/06/0623/소가 길을 건너간 이유 1.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = int(input())\ncow = ['Zero'] + [0]*10 # 0:미발견, 1:왼쪽, 2:오른쪽\nresult = 0\nfor n in range(N):\n c, lr = map(int, input().split())\n lr += 1\n if cow[c]:\n if cow[c] != lr: # 길을 건넜음\n result += 1\n cow[c] = lr\n else: # not cow[c]\n cow[c] = lr\nprint(result)"},{"alpha_fraction":0.45856353640556335,"alphanum_fraction":0.4806629717350006,"avg_line_length":10.375,"blob_id":"0f0ed25d7e6977676013aaee9f0d3fd9a00b1623","content_id":"ff83e0eecfad42e6a18167e546a6fea6be381b55","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":181,"license_type":"no_license","max_line_length":41,"num_lines":16,"path":"/알고리즘/온라인저지/2022/02/0205/점수계산.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = int(input())\n\nanswers = list(map(int, input().split()))\n\np = 0\nresult = 0\n\nfor a in answers:\n if a:\n p += 1\n else:\n p = 0\n \n result += p\n\nprint(result)"},{"alpha_fraction":0.35537189245224,"alphanum_fraction":0.39669421315193176,"avg_line_length":19.33333396911621,"blob_id":"b1e8c6103b243ac63f4f78d07b777fc44302399c","content_id":"5d348fe264c832816e5bea29e3a2e52dd8f1e42f","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":121,"license_type":"no_license","max_line_length":32,"num_lines":6,"path":"/알고리즘/온라인저지/2022/11/1110/지각.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"for _ in range(int(input())):\n n = int(input())\n t = 0\n while (t+1) + (t+1)**2 <= n:\n t += 1\n print(t)"},{"alpha_fraction":0.4692671298980713,"alphanum_fraction":0.49527186155319214,"avg_line_length":29.25,"blob_id":"a4bbcac589b85097d62bce8f5a324f69e4e69670","content_id":"d7a70242157d9e159a42d317d23a7373c1bdedbc","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1090,"license_type":"no_license","max_line_length":72,"num_lines":28,"path":"/알고리즘/온라인저지/2021/07/0731/설탕과자 뽑기.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"h, w = map(int, input().split()) # 뽑기 상자의 가로 세로\nn = int(input()) # 막대 개수\npoints = [] # 막대길이, 방향, 좌표 리스트\nfor i in range(n):\n l, d, x, y = map(int, input().split()) \n # 막대 개수만큼 for문 돌리면서 정보 입력\n points.append([l, d, x, y])\n # 막대 길이, 막대 놓는 방향(0:가로, 1:세로), 막대 좌표x, 막대 좌표y(x, y = 1, 1 에서 시작)\nboard = [] # 빈 보드\nfor i in range(h):# 세로줄 만들면서\n board.append([])\n for j in range(w): # 가로에 전부 0 채우기\n board[i].append(0)\n\nfor point in points:\n if point[1] == 0: # 가로일 때\n for i in range(point[0]): # 막대 길이만큼\n board[point[2]-1][point[3]-1 + i] = 1\n # 오른쪽으로 1 넣어주기\n else: # 세로일 때\n for j in range(point[0]): # 막대 길이만큼\n board[point[2]-1 + j][point[3]-1] = 1\n # 아래로 1 넣어주기\n\nfor i in range(h):\n for j in range(w): \n print(board[i][j], end=' ')\n print() # 출력문"},{"alpha_fraction":0.4333333373069763,"alphanum_fraction":0.699999988079071,"avg_line_length":30,"blob_id":"1b191339e0a6ab6307ef0fd7de6ede1897f98750","content_id":"89911ee092dc7fbac2a5cf579b486f8357de9fee","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":30,"license_type":"no_license","max_line_length":30,"num_lines":1,"path":"/알고리즘/온라인저지/2022/02/0216/큰 수(BIG).py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"print((int(input()))%20000303)"},{"alpha_fraction":0.5206185579299927,"alphanum_fraction":0.5979381203651428,"avg_line_length":26.85714340209961,"blob_id":"08c5b151b2da07dea2b0219a1c55534d7b779543","content_id":"8c2ed12f30a4044d2582e8d23fc5380ea938cd0e","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":242,"license_type":"no_license","max_line_length":52,"num_lines":7,"path":"/알고리즘/온라인저지/2021/08/0816/remove pop.py.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"my_list = [1, 5, 4, 2, 5, 2, 3, 8, 9, 4, 2, 3, 2, 1]\nprint(len(my_list))\nprint(my_list)\n# my_list.pop() # 해당 인덱스의 요소를 제거\nmy_list.remove(5) # 가장 앞에 있는 해당 요소를 제거\nprint(len(my_list))\nprint(my_list)"},{"alpha_fraction":0.5315487384796143,"alphanum_fraction":0.5353728532791138,"avg_line_length":23.952381134033203,"blob_id":"562caf35ede0d15c1aea12a59ba5bdcb2ad10a3d","content_id":"10b4c0ed5edd5e7bff322316a9354b8c329443bf","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":539,"license_type":"no_license","max_line_length":52,"num_lines":21,"path":"/알고리즘/온라인저지/2021/07/0731/정수 1개 입력받아 분류하기.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"a = int(input())\ndef odd_even(n): # True: 홀수, False: 짝수\n if n % 2 == True:\n return True\n else:\n return False\n\ndef plus_minus(n): # True: 양수, False: 짝수\n if n >= 0:\n return True\n else:\n return False\n\nif odd_even(a) == False and plus_minus(a) == False:\n print(\"A\") # A: - and even\nelif plus_minus(a) == False and odd_even(a) == True:\n print(\"B\") # B: - and odd\nelif plus_minus(a) == True and odd_even(a) == False:\n print(\"C\") # C: + and even\nelse:\n print(\"D\") # D: + and odd"},{"alpha_fraction":0.4942166209220886,"alphanum_fraction":0.5373291373252869,"avg_line_length":23.41025733947754,"blob_id":"a644123420792555f4471a34305c9b9e83aaf94b","content_id":"a352b4e9c6d742bfc81c6dbe1defc867c9e76ccd","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1293,"license_type":"no_license","max_line_length":63,"num_lines":39,"path":"/알고리즘/온라인저지/2021/10/1015/숨바꼭질.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"from collections import deque # deque의 메서드인 popleft()를 사용하기 위함\n\nN, M = map(int, input().split())\n\nresult = 0\n\nq = deque()\nq.append((N, result)) # N부터 출발합니다\n\ncheck = set() # +1 -1 *2 를 진행하면서 중복되는 숫자가 발견될 경우 \n# q에 추가하는 것을 막기 위해 중복검사를 해주기 위한 set()\n\nwhile q:\n if not N and not M or N == M: # 수빈이가 동생과 같은 위치에 있을 때\n break\n \n tmp = q.popleft() # BFS\n \n a = tmp[0] + 1\n b = tmp[0] - 1\n c = tmp[0] * 2\n cnt = tmp[1] + 1 # 수빈이가 이동하였고 1초가 지났습니다\n \n if M in (a, b, c): # 이동중 수빈이가 동생을 발견하였을 때\n result = cnt # 그 때의 시간을 저장\n break\n\n # 동생은 0부터 100000 사이에 있습니다, 범위를 벗어나면 동생을 찾을 수 없습니다\n if a not in check and 0<=a<=100000: # 간 적이 없고, 범위를 벗어나지 않으면\n q.append((a, cnt)) # 다음 가볼 곳에 추가\n check.add(a) # 가본 곳에 추가\n if b not in check and 0<=b<=100000:\n q.append((b, cnt))\n check.add(b) \n if c not in check and 0<=c<=100000:\n q.append((c, cnt))\n check.add(c)\n\nprint(result)"},{"alpha_fraction":0.4542483687400818,"alphanum_fraction":0.5065359473228455,"avg_line_length":26.909090042114258,"blob_id":"3ba45e575dfb3f2645c083b4403e3d654bcbacd8","content_id":"3fcb400911d47399b69c278136fa492d8f33bf5d","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":306,"license_type":"no_license","max_line_length":42,"num_lines":11,"path":"/알고리즘/온라인저지/2022/11/1102/Doubles.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"while True:\n nums = list(map(int, input().split()))\n if nums[0] == -1: break\n result = 0\n arr = [0]*101\n for num in nums[:len(nums)-1]:\n if not arr[num]: arr[num] = 1\n for num in nums[:len(nums)-1]:\n if num*2 <= 100 and arr[num*2]: \n result += 1\n print(result)"},{"alpha_fraction":0.5,"alphanum_fraction":0.5246913433074951,"avg_line_length":15.100000381469727,"blob_id":"2b538b140f825cf32719241484a43d30e31a3e90","content_id":"5be8026accd9a43e3098fe627e359643ba3096f8","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":162,"license_type":"no_license","max_line_length":36,"num_lines":10,"path":"/알고리즘/온라인저지/2022/02/0205/지능형 기차 2.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"maxx = 0\nin_train = 0\n\nfor _ in range(10):\n l, b = map(int, input().split())\n in_train += b-l\n if in_train > maxx:\n maxx = in_train\n\nprint(maxx)\n\n"},{"alpha_fraction":0.4041095972061157,"alphanum_fraction":0.48630136251449585,"avg_line_length":20,"blob_id":"50d4ac02cc332704c25d1aa06a073b20f27b5c2b","content_id":"bdb820d257d11dac78828ee1181d101da13561e0","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":146,"license_type":"no_license","max_line_length":28,"num_lines":7,"path":"/알고리즘/온라인저지/2022/05/0518/완전 제곱수.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = int(input())\nresult = 0\nfor b in range(1, 501):\n for a in range(1, 501):\n if a**2 == b**2 + N:\n result += 1\nprint(result)"},{"alpha_fraction":0.5081967115402222,"alphanum_fraction":0.5081967115402222,"avg_line_length":19.66666603088379,"blob_id":"f34121bf32314ea2c691d946ab37b107acece598","content_id":"6e7a0bec8a3e8d6e26254a0e33eae04501c1a408","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":61,"license_type":"no_license","max_line_length":29,"num_lines":3,"path":"/알고리즘/온라인저지/2023/04/0406/Copier.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"for _ in range(int(input())):\n N = input()\n print(N, N)"},{"alpha_fraction":0.33282673358917236,"alphanum_fraction":0.36018237471580505,"avg_line_length":18.969696044921875,"blob_id":"b0dc75955d7bd099e235e7653fa42fb53eaec471","content_id":"1ec072252516183f2eb0ed0e7eb076c1ee057952","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":658,"license_type":"no_license","max_line_length":59,"num_lines":33,"path":"/알고리즘/SWEA/LEARN/Course/2. Programming Intermediate/8. 파이썬 SW문제해결 기본 Tree/8차시 8일차 - 이진 힙.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"TC = int(input())\n\nfor tc in range(1, TC+1):\n N = int(input())\n nodes = list(map(int, input().split()))\n arr = [0]\n\n for n in nodes:\n arr.append(n)\n\n for i in range(1, N//2+1):\n try:\n if arr[i] > arr[i*2]:\n arr[i], arr[i*2] = arr[i*2], arr[i] \n\n if arr[i] > arr[i*2+1]:\n arr[i], arr[i*2+1] = arr[i*2+1], arr[i]\n \n except:\n pass\n\n n = len(arr)\n result = 0\n \n while True:\n N //= 2\n\n result += arr[N]\n\n if N == 1:\n break\n \n print('#{} {}'.format(tc, result))"},{"alpha_fraction":0.5388127565383911,"alphanum_fraction":0.5616438388824463,"avg_line_length":14.714285850524902,"blob_id":"5f27c780f1c7e72917adadedae4b0b3206130e92","content_id":"f0ad61fb19f7b422e0b3af84c118fc1257e092e5","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":219,"license_type":"no_license","max_line_length":34,"num_lines":14,"path":"/알고리즘/온라인저지/2022/09/0927/3의 배수.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\n\nX = input().rstrip()\nresult = 0\nwhile len(X)>1:\n tmp = 0\n for x in X:\n tmp += int(x)\n X = str(tmp)\n result += 1\nprint(result)\nprint('NO' if int(X)%3 else 'YES')"},{"alpha_fraction":0.42032331228256226,"alphanum_fraction":0.46766743063926697,"avg_line_length":31.11111068725586,"blob_id":"58e661d2ab7df3998a889c99923c8ea46357e35b","content_id":"7c7c9f56b5c9486426b97dacf694bfed51c26506","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":866,"license_type":"no_license","max_line_length":64,"num_lines":27,"path":"/알고리즘/온라인저지/2022/09/0913/정사각형.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"for _ in range(int(input())):\n dots = [tuple(map(int, input().split())) for __ in range(4)]\n x1, y1 = dots[0][0], dots[0][1]\n distance_pows = []\n for dot in dots[1:]:\n x2, y2 = dot[0], dot[1]\n distance_pow = abs(x1-x2)**2 + abs(y1-y2)**2\n distance_pows.append(distance_pow)\n flag = 1\n distance_pows.sort()\n if distance_pows[0] != distance_pows[1]:\n print(0)\n else:\n for self in dots:\n if not flag: break\n x1, y1 = self[0], self[1]\n tmp = []\n for other in dots:\n if self != other:\n x2, y2 = other[0], other[1]\n pow = abs(x1-x2)**2 + abs(y1-y2)**2\n tmp.append(pow)\n tmp.sort()\n if tmp != distance_pows: flag = 0\n print(flag)\n\n# https://www.acmicpc.net/problem/1485"},{"alpha_fraction":0.4154929518699646,"alphanum_fraction":0.44366195797920227,"avg_line_length":19.314285278320312,"blob_id":"27390bc83979c9a27536a33599189f70a718ad67","content_id":"d99a00e3f01bb74f4ea12d47da0b78786d1929a4","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":710,"license_type":"no_license","max_line_length":49,"num_lines":35,"path":"/알고리즘/온라인저지/2021/08/0830/DFS와 BFS.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ndef dfs(v):\n visited[v] = 1\n print(v, end=' ')\n for w in range(1, N+1):\n if G[v][w] == 1 and not visited[w]:\n dfs(w)\n\ndef bfs(v, n):\n q = []\n visited = [0] * (N+1)\n q.append(v)\n visited[v] = 1\n while q:\n t = q.pop(0)\n print(t, end=' ')\n for i in range(1, N+1):\n if G[t][i] == 1 and not visited[i]:\n q.append(i)\n visited[i] = visited[t] + 1\n\nN, M, V = map(int, sys.stdin.readline().split())\n\nG = [[0] * (N+1) for _ in range(N+1)]\nfor _ in range(M):\n u, v = map(int, sys.stdin.readline().split())\n G[u][v] = G[v][u] = 1\n\nvisited = [0] * (N+1)\ndfs(V)\nprint()\n\nvisited = [0] * (N+1)\nbfs(V, N)"},{"alpha_fraction":0.4791666567325592,"alphanum_fraction":0.4962121248245239,"avg_line_length":20.571428298950195,"blob_id":"95990ebe98345f6d0b1f318b722434e733197b1b","content_id":"22c16e1d9a3285f162073566de95c0e7ede0a7b5","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1410,"license_type":"no_license","max_line_length":46,"num_lines":49,"path":"/알고리즘/온라인저지/2022/08/0817/탑.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\n\nN = int(input())\nT = list(map(int, input().split())) # tower\nS, result = [], [0] * N # stack\nfor i in range(N):\n t = T[i]\n while S and T[S[-1]] < t: S.pop()\n if S: result[i] = S[-1] + 1\n S.append(i)\nprint(*result)\n\n\"\"\"\n스택에 들어있는, 현재 탑보다 낮은 탑의 인덱스를 전부 제거한다\n스택이 남아있을 때, stack[-1]의 인덱스는\n앞에서 등장했던 탑들 중 현재 탑 다음으로 높은 탑이 되고\n레이저 신호는 여기서 수신될 것이다\n현재 탑의 신호 수신탑에, stack[-1]+1번째 탑을 저장한다\n그리고 해당 탑의 인덱스를 스택에 추가한다\n\n늘 코드의 시작부터 적는 습관이 있었는데\n위의 코드는 진행 중간만 깔끔하게 적혀있다\n위 코드처럼 짤 수 있도록 더 열심히 해야겠다... ㅜㅜ\n\"\"\"\n\n# 쾅\n# import sys\n\n# input = sys.stdin.readline\n\n# N = int(input())\n# T = list(map(int, input().split())) # tower\n# S = [] # stack\n# result = [0] * N\n# for i in range(N-1, -1, -1): # 진행은 우->좌 가 맞다\n# t = T[i]\n# if not S: \n# S.append((t, i))\n# else:\n# S.append((t, i))\n# for j in range(len(S)-1, -1, -1):\n# if j < len(S)-1:\n# if t > S[j][0]:\n# result[S[j][1]] = i+1\n# S.pop()\n# else: pass\n# print(*result)"},{"alpha_fraction":0.4103773534297943,"alphanum_fraction":0.4245283007621765,"avg_line_length":20.299999237060547,"blob_id":"0f62e005527198dc37b8127eecec4f274dc7e27d","content_id":"4b8951832eba7d583131baab381e4dea27cf8452","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":212,"license_type":"no_license","max_line_length":32,"num_lines":10,"path":"/알고리즘/온라인저지/2022/04/0407/Can you add this.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"T = int(input())\nfor t in range(T):\n result = 0\n tmp = input().split()\n for i in tmp:\n if i[0] == '-':\n result -= int(i[1:])\n else:\n result += int(i)\n print(result)"},{"alpha_fraction":0.5512048006057739,"alphanum_fraction":0.5783132314682007,"avg_line_length":22.785715103149414,"blob_id":"ba05fb838517cf92c1090ebe4ae7d0fc287cf2fd","content_id":"208ca4cf273e67676fdc3da4ec23dd114b2c95f9","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":332,"license_type":"no_license","max_line_length":63,"num_lines":14,"path":"/알고리즘/온라인저지/2022/10/1002/경로 찾기.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\nINF = int(1e9)\n\nN = int(input().rstrip())\narr = [list(map(int, input().rstrip().split())) for _ in [0]*N]\nfor k in range(N):\n for a in range(N):\n for b in range(N):\n if arr[a][k] and arr[k][b]: arr[a][b] = 1\nfor a in arr: print(*a)\n\n# https://www.acmicpc.net/problem/11403"},{"alpha_fraction":0.5639810562133789,"alphanum_fraction":0.6113743782043457,"avg_line_length":22.55555534362793,"blob_id":"7482ad47eb32b41d957f396f56b49f4830765523","content_id":"d290b15b864464a7011c6c26727e06ad3a5a249c","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":211,"license_type":"no_license","max_line_length":38,"num_lines":9,"path":"/알고리즘/온라인저지/2022/07/0731/수 찾기.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = int(input())\narr1 = set(map(int, input().split()))\nM = int(input())\narr2 = list(map(int, input().split()))\nfor a in arr2:\n if a in arr1: print(1)\n else: print(0)\n\n# https://www.acmicpc.net/problem/1920"},{"alpha_fraction":0.4373672902584076,"alphanum_fraction":0.46284499764442444,"avg_line_length":22.600000381469727,"blob_id":"66f54d43505513792fb478482d5f158c42064dd5","content_id":"022ba88eddb71522afe5587380cc80cd3f33a9de","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":471,"license_type":"no_license","max_line_length":54,"num_lines":20,"path":"/알고리즘/온라인저지/2022/09/0927/별 찍기 - 23.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\n\nN = int(input().rstrip())\nmid = 1+2*(N-2)\nresult = ['*'*N+' '*mid+'*'*N]\nstart = 0\nsize = N-2\nfor i in range(2, N+1):\n start, mid = start+1, mid-2\n tmp = ' '*start\n if mid>0: \n tmp += '*' + ' '*size + '*'\n tmp += ' '*mid\n tmp += '*' + ' '*size + '*'\n else: tmp += '*' + ' '*size + '*' + ' '*size + '*'\n result.append(tmp)\nfor r in result[:len(result)-1]: print(r)\nfor r in result[::-1]: print(r)"},{"alpha_fraction":0.6571428775787354,"alphanum_fraction":0.6571428775787354,"avg_line_length":35,"blob_id":"47ddbcbb3a1f19f158da307ddb8a569cb7c7bc73","content_id":"a52722a4efcfeacd29591cee33b7287245153837","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":35,"license_type":"no_license","max_line_length":35,"num_lines":1,"path":"/알고리즘/SWEA/LEARN/Course/1. Programming Beginner/파이썬 프로그래밍 기초(2)/12차시 2. 자료구조 – 리스트, 튜플 - 연습문제 13.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"print(sum(list(map(int, input()))))"},{"alpha_fraction":0.5011037588119507,"alphanum_fraction":0.5253863334655762,"avg_line_length":18.7391300201416,"blob_id":"dfe84252545d30e4be97bce1a5b4594236eae14e","content_id":"959135c92441edf416979513b33a792bae6656d7","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":493,"license_type":"no_license","max_line_length":51,"num_lines":23,"path":"/알고리즘/온라인저지/2021/08/0829/수열.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\nN = int(sys.stdin.readline())\nnums = list(map(int, sys.stdin.readline().split()))\ncnt = 1\nresult = 1\n# 증가할 때 따로, 감소할 때 따로, 두번 돌려주는 코드\nfor i in range(len(nums)-1):\n if nums[i] >= nums[i+1]:\n cnt += 1\n else:\n cnt = 1\n if result < cnt:\n result = cnt\n\ncnt = 1\nfor i in range(len(nums)-1):\n if nums[i] <= nums[i+1]:\n cnt += 1\n else:\n cnt = 1\n if result < cnt:\n result = cnt\nprint(result)"},{"alpha_fraction":0.6521739363670349,"alphanum_fraction":0.6521739363670349,"avg_line_length":18.85714340209961,"blob_id":"8fa4bce5a1f44e31615864402136bcbf041db539","content_id":"76bd35bc2e590b97b4b1a7bcbc24b135358f0e6b","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":138,"license_type":"no_license","max_line_length":32,"num_lines":7,"path":"/알고리즘/온라인저지/2021/08/0822/수 정렬하기 2.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"T = int(input())\nnumbers = []\nfor tc in range(T):\n numbers.append(int(input()))\nnumbers.sort()\nfor number in numbers:\n print(number)"},{"alpha_fraction":0.5740740895271301,"alphanum_fraction":0.5820105671882629,"avg_line_length":18.947368621826172,"blob_id":"7191e446c4a4164453e9763a9835c01492b68a66","content_id":"77be887efdafc5c47dee91640b63b85da83f70ce","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":378,"license_type":"no_license","max_line_length":35,"num_lines":19,"path":"/알고리즘/온라인저지/2022/03/0316/카드 뽑기.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"from pprint import pprint\n\nN, M, K = map(int, input().split())\narr = [[] for _ in range(N)]\nfor m in range(M):\n arr[m].append(True)\nfor m in range(M, N):\n arr[m].append(False)\n# print(arr)\nfor k in range(K):\n arr[k].append(True)\nfor k in range(K, N):\n arr[k].append(False)\n# pprint(arr)\nresult = N\nfor a in arr:\n if a[0] != a[1]:\n result -= 1\nprint(result)"},{"alpha_fraction":0.4307228922843933,"alphanum_fraction":0.46084338426589966,"avg_line_length":14.7619047164917,"blob_id":"a7c24bdfe850d476027dc9598a0466c568c88f8d","content_id":"2da38b0e8e2e448feb24250b87110f15a12810e9","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":332,"license_type":"no_license","max_line_length":54,"num_lines":21,"path":"/알고리즘/SWEA/LEARN/Course/2. Programming Intermediate/8. 파이썬 SW문제해결 기본 Tree/7차시 8일차 - 이진탐색.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"def makeTree(n):\n global count\n\n if n <= N:\n makeTree(n*2)\n\n tree[n] = count\n count += 1\n\n makeTree(n*2 + 1)\n\nTC = int(input())\nfor tc in range(TC):\n N = int(input())\n \n tree = [0 for _ in range(N+1)]\n count = 1\n\n makeTree(1)\n\n print('#{} {} {}'.format(tc, tree[1], tree[N//2]))\n "},{"alpha_fraction":0.4254473149776459,"alphanum_fraction":0.46222662925720215,"avg_line_length":29.515151977539062,"blob_id":"e6e8f2e5753be2a2861388f3bd3c0cb86e68a24c","content_id":"a4305429cc023cd0371e249bf46a018c2a09e98b","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1038,"license_type":"no_license","max_line_length":77,"num_lines":33,"path":"/알고리즘/[템플릿]/BFS/토마토 3차원.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"from collections import deque\n\n# 상 하 전 후 좌 우 델타이동\ndz, dy, dx = [-1, 1, 0, 0, 0, 0], [0, 0, -1, 1, 0, 0], [0, 0, 0, 0, -1, 1]\nM, N, H = map(int, input().split())\narr = [[list(map(int, input().split())) for _ in range(N)] for _ in range(H)]\nQ = deque()\nfor k in range(H):\n for i in range(N):\n for j in range(M):\n if arr[k][i][j] == 1:\n Q.append((k, i, j, 0)) # z, y, x, day\n arr[k][i][j] = 0\nresult = 0\nwhile Q:\n z, y, x, day = Q.popleft()\n if arr[z][y][x] == 1: continue\n arr[z][y][x] = 1\n result = max(result, day)\n for i in range(6): # 상 하 전 후 좌 우\n nz, ny, nx = z+dz[i], y+dy[i], x+dx[i]\n if 0<=nz<H and 0<=ny<N and 0<=nx<M and arr[nz][ny][nx] == 0:\n Q.append((nz, ny, nx, day+1))\nfor k in range(H):\n if result == -1: break\n for i in range(N):\n for j in range(M):\n if arr[k][i][j] == 0:\n result = -1\n break\nprint(result)\n\n# https://www.acmicpc.net/problem/7569"},{"alpha_fraction":0.48466256260871887,"alphanum_fraction":0.5030674934387207,"avg_line_length":16.210525512695312,"blob_id":"3df82339556a451a01526cddb98ceb5fdd713aeb","content_id":"7fad2c804bae41a95c125f75fe082417fd5d2fac","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":404,"license_type":"no_license","max_line_length":36,"num_lines":19,"path":"/알고리즘/온라인저지/2023/02/0226/팰린드롬 만들기.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"S = input()\nL, S_rev = len(S), S[::-1]\nresult = 0\n\nfor i in range(L, 0, -1):\n if S_rev[:i] == S_rev[:i][::-1]:\n result = i+(L-i)*2\n break\n\nprint(result)\n\n\"\"\"\nex) abczzzz -> abc + zzzz + cba\n\nL = 문자열 전체의 길이(abczzzz)\ni = 뒤에서 가장 긴 팰린드롬의 길이(zzzz)\nL-i = 문자열 전체에서 가장 긴 팰린드롬을 뺀 길이(abc)\nresult = (L-i) + i + (L-i)\n\"\"\""},{"alpha_fraction":0.4526315927505493,"alphanum_fraction":0.5052631497383118,"avg_line_length":12.714285850524902,"blob_id":"a42f0f25848b5ffe281fd4d60629c87b6bf44486","content_id":"097e778b6c597ca330ab185f22eda60b7b0dfcc1","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":95,"license_type":"no_license","max_line_length":22,"num_lines":7,"path":"/알고리즘/SWEA/LEARN/Course/1. Programming Beginner/파이썬 프로그래밍 기초(2)/11차시 2. 자료구조 – 리스트, 튜플 - 연습문제 12.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"s = set()\n\nfor i in range(1, 21):\n if i%3 or i%5:\n s.add(i*i)\n\nprint(sorted(list(s)))"},{"alpha_fraction":0.420634925365448,"alphanum_fraction":0.43386244773864746,"avg_line_length":26.071428298950195,"blob_id":"3907629e6c8256a07e4480e33b85f861816a1b7a","content_id":"760aa93cbb579555c38c9f7a66dff07f11c161ef","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":378,"license_type":"no_license","max_line_length":52,"num_lines":14,"path":"/알고리즘/온라인저지/2022/07/0727/김인천씨의 식료품가게 (Large).py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"T = int(input())\nfor t in range(1, T+1):\n N = int(input())\n A = list(map(int, input().split())) # all prices\n result = []\n for i in range(N):\n tmp = A.pop(0)\n O = (tmp//3) * 4 # original\n for j in range(len(A)):\n if A[j] == O:\n A.pop(j)\n break\n result.append(tmp)\n print(f'Case #{t}:', *result)"},{"alpha_fraction":0.3589743673801422,"alphanum_fraction":0.43589743971824646,"avg_line_length":8.375,"blob_id":"b3a1762d1b90c8f9c9ca34a680dc6bbf5720f75c","content_id":"ceaa32df0a36eeac6f6e5900f31e993ba8df0f7a","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":78,"license_type":"no_license","max_line_length":22,"num_lines":8,"path":"/알고리즘/온라인저지/2022/01/0131/알파벳 개수.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"dp = [0] * 26\n\nS = input()\n\nfor s in S:\n dp[ord(s)-97] += 1\n\nprint(*dp) "},{"alpha_fraction":0.550939679145813,"alphanum_fraction":0.5934718251228333,"avg_line_length":21,"blob_id":"e50bc5527d0bf28dce2f3a59022703f7ffc05d94","content_id":"b1b60999feb3aae2a58c5d0586569a69918233ee","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1311,"license_type":"no_license","max_line_length":52,"num_lines":46,"path":"/알고리즘/[템플릿]/분할정복/피보나치 수 6.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\nmod = int(1e9)+7\n\ndef multiply(matrix1, matrix2): # 행렬 곱셈\n output = []\n for i in range(2):\n output.append([])\n for j in range(2):\n tmp = 0\n for k in range(2):\n tmp += matrix1[i][k] * matrix2[k][j]\n output[i].append(tmp%mod)\n return output\n\ndef power(matrix, n): # 거듭제곱 분할정복\n if n == 1: return matrix\n tmp = power(matrix, n//2)\n if n%2 == 0:\n return multiply(tmp, tmp)\n else:\n return multiply(multiply(tmp, tmp), matrix)\n\nN = int(input().rstrip())\nmatrix = [[1, 1], [1, 0]] # 피보나치 행렬 거듭제곱 일반항\nprint(power(matrix, N)[0][1])\n\n\"\"\"\n피보나치 일반항을, 행렬의 거듭제곱으로 변환할 줄 알아야 하고\n행렬의 거듭제곱을 할 줄 알아야 하고\n거듭제곱을 분할정복으로 할 줄 알아야 풀 수 있는 문제이다\n2022-10-08기준, 가장 빠른 속도로 피보나치를 구할 수 있는 코드이다\n\n<참고한 링크>\n참고한 코드 원문\nhttps://ca.ramel.be/50\n\n백준 피보나치 블로그글\nhttps://www.acmicpc.net/blog/view/28\n\n피보나치가 [1, 1],[1, 0]의 거듭제곱이 되는 과정\nhttps://www.youtube.com/watch?v=uX2IsIykLJc\n\"\"\"\n\n# https://www.acmicpc.net/problem/11444"},{"alpha_fraction":0.5959885120391846,"alphanum_fraction":0.6060171723365784,"avg_line_length":18.97142791748047,"blob_id":"c37d208ed72e37ae26204315abe9bf4d1a3f3c32","content_id":"0b8c44931d1a0bc860f62cdefb003c2d6af29a2c","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":950,"license_type":"no_license","max_line_length":54,"num_lines":35,"path":"/알고리즘/온라인저지/2022/10/1004/N과 M (5).py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\n\ndef solve(depth, N, M):\n if depth == M:\n print(*result); return\n for i in range(N):\n if not visited[i]:\n visited[i] = True; result.append(arr[i])\n solve(depth+1, N, M)\n result.pop(); visited[i] = False\n\nN, M = map(int, input().rstrip().split())\narr = sorted(list(map(int, input().rstrip().split())))\nvisited = [False] * N\nresult = []\nsolve(0, N, M)\n\n\"\"\"\nBFS 돌 때 \n방문하지 않았으면\n방문처리, Q에 추가 해주듯이\nDFS도 똑같이\n함수 자체 메모리를 Q처럼 활용하면서\n방문하지 않았으면\n방문처리, 다음 탐색\n나오면서 방문 풀어주고, 탐색점 취소해주고\n그러니까\nBFS DFS 차이는\n다른건 다 같고, 방문지점을 당장갈거냐(DFS), 나중에 갈거냐(BFS) 인 것 같다\n진짜 근데 DFS는 구현이 왤케 감이 안잡히냐 어렵네\n\"\"\"\n\n# https://www.acmicpc.net/problem/15654"},{"alpha_fraction":0.5014662742614746,"alphanum_fraction":0.5190615653991699,"avg_line_length":19.117647171020508,"blob_id":"180fbbcc7e64da3a44ba8f43929d24b31d2eaf5c","content_id":"9f6247bd5668bb3612ae42497f942fd7ef6fa622","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":341,"license_type":"no_license","max_line_length":33,"num_lines":17,"path":"/알고리즘/온라인저지/2021/08/0825/요세푸스 문제.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N, K = map(int, input().split())\nq = list(range(1, N+1))\npointer = K-1\nresult = []\nwhile q:\n result.append(q.pop(pointer))\n pointer += K - 1\n if not len(q):\n break\n else:\n pointer %= len(q)\n \nprint('<', end='')\nprint(result[0], end='')\nfor i in range(1, len(result)):\n print(',', result[i], end='')\nprint('>')"},{"alpha_fraction":0.4923076927661896,"alphanum_fraction":0.5153846144676208,"avg_line_length":20.83333396911621,"blob_id":"55407429dd335b586d619e417195bd491252b097","content_id":"1c1f91116f638f71cfc0e068b5c1df45ef3d5675","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":130,"license_type":"no_license","max_line_length":40,"num_lines":6,"path":"/알고리즘/온라인저지/2023/05/0510/POT.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"result = 0\nfor i in range(int(input())):\n N = input()\n N, P = int(N[:len(N)-1]), int(N[-1])\n result += N**P\nprint(result)"},{"alpha_fraction":0.5361445546150208,"alphanum_fraction":0.5481927990913391,"avg_line_length":18.58823585510254,"blob_id":"fae8757ca2261ac20a2ef53e8af0bbab84ee530a","content_id":"cd4fb7b3c4b22ecfb736d011742825a2fd22e444","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":332,"license_type":"no_license","max_line_length":32,"num_lines":17,"path":"/알고리즘/온라인저지/2022/06/0618/뚊.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N, M = map(int, input().split())\nchar = []\nis_same = []\nfor n in range(N):\n char.append(input())\nfor n in range(N):\n is_same.append(input())\nresult = 'Not Eyfa'\ntmp = []\nfor i in range(N):\n tmp2 = ''\n for c in char[i]:\n tmp2 = tmp2 + c + c\n tmp.append(tmp2)\nif tmp == is_same:\n result = 'Eyfa'\nprint(result)"},{"alpha_fraction":0.5392376780509949,"alphanum_fraction":0.5526905655860901,"avg_line_length":27.80645179748535,"blob_id":"28921cb3d9f496e8d7c132824af343c27f7efffe","content_id":"638d288a2be34894e7117f60705d9eee0a6fd805","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1094,"license_type":"no_license","max_line_length":62,"num_lines":31,"path":"/알고리즘/온라인저지/2022/08/0828/특정 거리의 도시 찾기.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys, heapq\n\ninput = sys.stdin.readline\nINF = int(1e9) # 가상의 최대 거리\n\ndef dijkstra(start):\n distance[start] = 0\n heapq.heappush(Q, (0, start))\n while Q:\n dist, now = heapq.heappop(Q)\n for next, weight in data[now]: # weight = 1, 출력용으로만 사용\n cost = dist + 1\n if cost < distance[next]:\n distance[next] = cost\n heapq.heappush(Q, (cost, next))\n\nV, E, K, X = map(int, input().split())\ndata = [[] for _ in range(V+1)]\nfor _ in range(E):\n A, B = map(int, input().split())\n data[A].append((B, 1)) # 가중치 = 1\ndistance = [INF] * (V+1) # 가상의 최대 거리 배열\nQ = []\ndijkstra(X) # X부터 시작하여 다른 도시까지 이동하는 최소 거리 배열 값 구하기\nflag = False # K거리인 도시가 있는지 체크하는 플래그\nfor i in range(1, len(distance)):\n if distance[i] == K:\n print(i) # 도시 번호 출력\n flag = True # 최소 거리가 K에 해당하는 도시가 있음\nif not flag: # 해당하는 도시가 없을 경우\n print(-1)"},{"alpha_fraction":0.394812673330307,"alphanum_fraction":0.5100864768028259,"avg_line_length":17.3157901763916,"blob_id":"a62951e5e3dd69903716d6251c5e0b6b9e2d30bc","content_id":"8a549b34b13a94dd4da11f29403edec5d02b3cee","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":347,"license_type":"no_license","max_line_length":39,"num_lines":19,"path":"/알고리즘/온라인저지/2022/07/0716/트럭 주차.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"fees = list(map(int, input().split()))\nresult = 0\nparking = [0] * 101\nfor i in range(3):\n IN, OUT = map(int, input().split())\n for j in range(IN, OUT):\n parking[j] += 1\nfor p in parking:\n result += p*fees[p-1]\nprint(result)\n\n\"\"\"\n1 2 3 4 5 \n 3 4 \n 2 3 4 5 6 7 \n5 6 3 3 6 5 5\n17 20 36\n\"\"\"\n# print(sum([5, 6, 6, 6, 5, 5]))"},{"alpha_fraction":0.5721153616905212,"alphanum_fraction":0.5849359035491943,"avg_line_length":33.66666793823242,"blob_id":"11d64cb999ecb91b9b6eff90bb52d0a2ded8be87","content_id":"631c8b41ef131f289cc8f9a6fed02af85dd14ef9","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1066,"license_type":"no_license","max_line_length":68,"num_lines":18,"path":"/알고리즘/온라인저지/2021/09/0928/소트인사이드.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = input()\na = [] # N을 쪼개어 담을 리스트\nfor n in N: # 입력받은 숫자는 아직 str문자형\n a.append(int(n)) # int로 형변환 하여 담기\n\na_sorted = [] # a에 담긴 숫자들을 정렬하여 담을 리스트\na_count = [0] * (max(a)+1) # N을 쪼개어 담은 a라는 리스트에 각 숫자들이 몇개씩 들어있는지 셀 것\n# max(a)은, N의 각 자리수중 가장 큰 수를 의미하며\n# +1은 각 숫자들의 개수를 세어 담을 때 리스트 맨 앞에 0을 의미함 -> 숫자와 인덱스가 일치함\n\nfor i in range(len(a)):\n a_count[a[i]] += 1 # 숫자와 인덱스가 일치, 해당 숫자의 개수를 세어줌\n\nfor i in range(len(a_count)-1, -1, -1): # 담겨있는 숫자의 개수들을 반복하면서\n # 문제에서는 역정렬을 요구하였음\n if a_count[i]: # 숫자의 개수가 하나라도 있으면\n for j in range(a_count[i]): # 카운트 한 개수만큼의 횟수를 반복하며\n print(i, end='') # 공백없이 출력하면 문제에서 요구하는 정답이 됨\n"},{"alpha_fraction":0.5655737519264221,"alphanum_fraction":0.5860655903816223,"avg_line_length":19.41666603088379,"blob_id":"d194b07ecd3007f63704b90354fe5b4817ba40f5","content_id":"03d6f2af0853cf00cd3ba61c3dc8363f965deb34","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":244,"license_type":"no_license","max_line_length":45,"num_lines":12,"path":"/알고리즘/온라인저지/2022/09/0924/크림 파스타.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\n\nN = int(input().rstrip())\ndp = list(map(int, input().rstrip().split()))\nmin_num = dp[0]\ndp[0] = 0\nfor i in range(1, N):\n min_num = min(min_num, dp[i])\n dp[i] = max(dp[i]-min_num, dp[i-1])\nprint(*dp)"},{"alpha_fraction":0.6578947305679321,"alphanum_fraction":0.6578947305679321,"avg_line_length":18.16666603088379,"blob_id":"237a21e1d5137e1928d5aebcffd15e20ec2c727b","content_id":"ee50502bb8e14c386819acdf91c10bf7e1b2bbff","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":114,"license_type":"no_license","max_line_length":38,"num_lines":6,"path":"/알고리즘/온라인저지/2022/10/1015/입실 관리.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\n\nfor _ in range(int(input().rstrip())):\n print(input().rstrip().lower())"},{"alpha_fraction":0.3955555558204651,"alphanum_fraction":0.4399999976158142,"avg_line_length":21.600000381469727,"blob_id":"ae3fb0f11489d52fad9a3d383b41f3c6471bb70d","content_id":"2324375107a3179f164e90bbbccfc131d23b76be","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":225,"license_type":"no_license","max_line_length":31,"num_lines":10,"path":"/알고리즘/온라인저지/2022/09/0901/2진수 8진수.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = input()\ntmp = 3-len(N)%3\nif tmp != 3: N = '0'*tmp + N\nfor i in range(0, len(N), 3):\n S = N[i:i+3] # section\n S = S[::-1]\n tmp = 0\n for j in range(len(S)):\n tmp += int(S[j])*(2**j)\n print(tmp, end='')"},{"alpha_fraction":0.5894736647605896,"alphanum_fraction":0.6105263233184814,"avg_line_length":18.100000381469727,"blob_id":"e85dd190d21a23b6516846f82c645c23c58accbd","content_id":"c27ca6140ba0893cae4a8d7e3d10dbd4b27593af","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":190,"license_type":"no_license","max_line_length":41,"num_lines":10,"path":"/알고리즘/온라인저지/2022/10/1030/거꾸로 구구단.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\n\nN, K = map(int, input().rstrip().split())\nresult = 0\nfor k in range(1, K+1):\n tmp = int(str(N*k)[::-1])\n result = max(result, tmp)\nprint(result)"},{"alpha_fraction":0.4361445903778076,"alphanum_fraction":0.4746987819671631,"avg_line_length":26.66666603088379,"blob_id":"2e593644f9e296affd7d6f9b5cb6ba36cd372e70","content_id":"88eb88d1795c2abf46d5640a9c58f0d17b422ff9","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":597,"license_type":"no_license","max_line_length":63,"num_lines":15,"path":"/알고리즘/온라인저지/2021/08/0807/직각삼각형.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"\"\"\"\n입력받는 변 3개 A, B, C\n0 0 0 입력받으면 실행 종료\n피타고라스 정리 <if a**2 + b**2 == c**2: 직각삼각형>\n\"\"\"\n\nwhile True: # 계속 반복하는 while True\n A, B, C = map(int, input().split()) # 각 변을 입력받고\n if A + B + C == 0: # 마지막 줄인 0 0 0 이면\n break # 종료\n if A**2 + B**2 + C**2 == ((max(A, B, C))**2) * 2: # 직각삼각형이면\n # 가장 큰 수만 찾아서 구하는 공식을 위와같이 구성하였음\n print('right') # 출력\n else: # 직각삼각형 아니면 \n print('wrong') # 출력\n"},{"alpha_fraction":0.38725489377975464,"alphanum_fraction":0.41911765933036804,"avg_line_length":17.590909957885742,"blob_id":"2ac4bce7eab5f5974fe7d05030b5bece16877703","content_id":"26453d6a6ea5a31d3244c696065c89deb8dfffff","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":408,"license_type":"no_license","max_line_length":52,"num_lines":22,"path":"/알고리즘/온라인저지/2022/02/0201/GCD 곱.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"mod = 1000000007\n\nN, M = map(int, input().split())\n\nmaxn = max(N, M)\n\ndp = [False, False] + [True] * maxn\n\nresult = 1\n\nfor i in range(2, maxn):\n if dp[i]:\n j = i\n while j <= maxn:\n cnt = 0\n for k in range(i, maxn, i):\n dp[k] = False\n cnt += (N//j) * (M//j)\n result = (result * ((i**cnt)%mod)) % mod\n j *= i\n\nprint(result)"},{"alpha_fraction":0.4910941421985626,"alphanum_fraction":0.49618321657180786,"avg_line_length":25.266666412353516,"blob_id":"ca62971baa6beb144b93dbd2dd644cc2495aa3d2","content_id":"3487a1cc24854cace4cafe41f9959ecef86f1563","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":407,"license_type":"no_license","max_line_length":55,"num_lines":15,"path":"/알고리즘/온라인저지/2022/06/0616/유니크.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = int(input())\nplayer = []\nfor n in range(N):\n player.append(list(map(int, input().split())))\nresult = [0] * N\nfor i in range(N): # 플레이어\n for j in range(3): # 점수들\n switch = True\n for k in range(N):\n if player[i][j] == player[k][j] and i != k:\n switch = False\n if switch:\n result[i] += player[i][j]\nfor r in result:\n print(r)"},{"alpha_fraction":0.3924914598464966,"alphanum_fraction":0.4778156876564026,"avg_line_length":12.363636016845703,"blob_id":"c2de15d44eb840b9dc1e11f8f6cad62397785eab","content_id":"acc6b02a53248985f49a1535e8108ba04f53b78a","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":339,"license_type":"no_license","max_line_length":35,"num_lines":22,"path":"/알고리즘/SWEA/LEARN/Course/1. Programming Beginner/파이썬 프로그래밍 기초(2)/34차시 3. 자료구조 – 셋, 딕셔너리 - 연습문제 9.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"beer = {\n '하이트': 2000, \n '카스': 2100, \n '칭따오': 2500, \n '하이네켄': 4000, \n '버드와이저': 500,\n}\n\n# print(beer, ' # 인상 전')\n\n# for b in beer:\n# beer.update({b:beer[b]*1.05})\n\n# print(beer, ' # 인상 후')\n\n\nprint(beer)\n\nfor b in beer:\n beer.update({b:beer[b]*1.05})\n\nprint(beer)"},{"alpha_fraction":0.4861878454685211,"alphanum_fraction":0.4917127192020416,"avg_line_length":13,"blob_id":"458cbdac97a6ad5f39f4b38aebb6914c0cc09a2f","content_id":"7490b58fcc96d2460ff20489f4eec117df444889","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":181,"license_type":"no_license","max_line_length":24,"num_lines":13,"path":"/알고리즘/SWEA/LEARN/Course/1. Programming Beginner/파이썬 프로그래밍 기초(2)/41차시 4. 문자열 - 연습문제 5.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"tmp = input().split()\n\nresult = list(set(tmp))\n\nresult.sort()\n\nfor r in result:\n if r == result[-1]:\n print(r, end='')\n print()\n break\n\n print(r, end=',')"},{"alpha_fraction":0.30078125,"alphanum_fraction":0.36328125,"avg_line_length":15.0625,"blob_id":"7a89e92357f8f48d383e5ede10e609a92300f04f","content_id":"4ded52f8a97d41af12fe614e3d8e95d30a31cfa9","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":256,"license_type":"no_license","max_line_length":54,"num_lines":16,"path":"/알고리즘/온라인저지/2022/02/0228/타임 카드.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"for _ in range(3):\n AH, AM, AS, BH, BM, BS = map(int, input().split())\n\n BH -= 1 + AH\n BM += 59 - AM\n BS += 60 - AS\n \n if BS >= 60:\n BM += 1\n BS -= 60\n\n if BM >= 60:\n BH += 1\n BM -= 60\n\n print(BH, BM, BS)"},{"alpha_fraction":0.5,"alphanum_fraction":0.5357142686843872,"avg_line_length":9.600000381469727,"blob_id":"2d6fbc8d986da801f6f61e2d98c253fa1437d5aa","content_id":"aa5ae0fa3c33c619639c67881ef60d75f6cdba7d","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":56,"license_type":"no_license","max_line_length":19,"num_lines":5,"path":"/알고리즘/온라인저지/2022/01/0116/오리.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"sen = list(input())\n\nresult = 0\n\nquack = [False] * 5\n\n\n\n"},{"alpha_fraction":0.4591194987297058,"alphanum_fraction":0.4800838530063629,"avg_line_length":21.761905670166016,"blob_id":"c5200dab7515077680b19a97db77c2bd2ef635d3","content_id":"297960e17c5f05408c0bc1ef8b9910b943ef2694","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":747,"license_type":"no_license","max_line_length":46,"num_lines":21,"path":"/알고리즘/온라인저지/2021/08/0807/ACM 호텔.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"\"\"\"\nH = 호텔 높이\nW = 호텔 길이\n그림은 정면에서 봤을 때 호텔 모습\nYYXX = Y층 X호\n들어오는 순서대로 각 층 1호실부터 방 배정\nT = 테스트케이스 개수\nN = 입장 순서\nYY = N % H\nXX = N // H + 1\"\"\"\n\nT = int(input()) # 테스트케이스 개수\nfor i in range(T): # 테스트케이스 개수만큼 반복\n H, W, N = map(int, input().split()) # 입력받고\n if N % H == 0: # 손님들을 차례로 방 배정할 때 나머지가 0이면\n Y = H # 호실의 층수는 높이\n X = N // H # 호수는 몫\n else: # 나머지가 0이 아니면\n Y = N % H # 층수는 나누고 난 나머지\n X = (N // H) + 1 # 호수는 몫에 +1\n print(100 * Y + X) # 방 번호 출력"},{"alpha_fraction":0.26037734746932983,"alphanum_fraction":0.5169811248779297,"avg_line_length":6,"blob_id":"f9b9db6f4489b7bc50661bd064c8690231e1a656","content_id":"f1888e4047f443052cf4d5e26c2e822c72492f4c","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":265,"license_type":"no_license","max_line_length":29,"num_lines":38,"path":"/알고리즘/온라인저지/2022/01/0108/이친수.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"\"\"\"\n1 1\n1\n\n2 1\n10\n\n3 2\n100\n101\n\n4 3\n1000\n1001\n1010\n\n5 5\n10000\n10001\n10010\n10100\n10101\n\"\"\"\n\nN = int(input())\n\ndp = [0 for _ in range(91)]\n\ndp[1], dp[2] = 1, 1\n\nif N < 3:\n print(dp[N])\n exit()\n\nfor i in range(3, N+1):\n dp[i] = dp[i-1] + dp[i-2]\n\nprint(dp[N])"},{"alpha_fraction":0.5094066858291626,"alphanum_fraction":0.5267727971076965,"avg_line_length":21.322580337524414,"blob_id":"11ca0eb7103cde73d0cf3732c668a4889ddf9b59","content_id":"9109d65d6b49c7339689aa25e539d3eac85433bb","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":903,"license_type":"no_license","max_line_length":67,"num_lines":31,"path":"/알고리즘/온라인저지/2021/10/1016/N과 M (1).py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"# 외부모됼\n# from itertools import permutations\n# N, M = map(int, input().split())\n# arr = list(range(1, N+1))\n# print(list(permutations(arr, M)))\n\n# dfs 재귀로 구현\ndef dfs(x): # x는 숫자 고른 개수\n if x == M: # M개만큼 골랐으면\n print(*result) # 들어있는 순열 언패킹\n return # 해당 재귀 종료\n \n for i in range(N): # 재귀를 통해, N개중 하나 -> N-1개중 하나 -> N-2개중 하나 ...\n if visited[i]: # 이미 고른 수이면\n continue\n\n result.append(arr[i]) # 하나 고르고\n visited[i] = 1 # 방문처리 하고\n dfs(x+1) # 다음 숫자 고르기\n result.pop() # 돌아와서 골랐던 숫자 빼고\n visited[i] = 0 # 방문 취소하고\n\nN, M = map(int, input().split())\n\narr = list(range(1, N+1))\n\nvisited = [0] * N\n\nresult = []\n\ndfs(0) # 고른 숫자 0개부터 시작"},{"alpha_fraction":0.5365853905677795,"alphanum_fraction":0.5365853905677795,"avg_line_length":12.833333015441895,"blob_id":"8ea0e51cd9745090ac21149d1646cca14c08e807","content_id":"5f305afd10484b2fed5e51706e453f5549abade3","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":88,"license_type":"no_license","max_line_length":32,"num_lines":6,"path":"/알고리즘/온라인저지/2022/02/0205/와이버스 부릉부릉.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N, K = map(int, input().split())\n\nfor n in range(N):\n a = input()\n\nprint('비와이')"},{"alpha_fraction":0.5511363744735718,"alphanum_fraction":0.5625,"avg_line_length":26.842105865478516,"blob_id":"75dd18fbe39a44723b70ec0b4217c24414a508c0","content_id":"ab8ebcf02b2bb3b9a72a4d9b257c6a0cf1cf0f49","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":590,"license_type":"no_license","max_line_length":98,"num_lines":19,"path":"/알고리즘/온라인저지/2023/01/0124/회문인 수.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import string\n\ndef base_change(number, base):\n tmp = string.digits + string.ascii_uppercase + string.ascii_lowercase + '!@#$%^' # 자릿수를 담은 문자열\n result = ''\n while number:\n result = tmp[number%base] + result # B진법이므로 B로 나눈 나머지번째 문자를 계속 추가한다\n number //= base\n return result\n\nfor _ in range(int(input())):\n T = int(input())\n result = 0\n for base in range(2, 65):\n new_num = base_change(T, base)\n if new_num == new_num[::-1]:\n result = 1\n break\n print(result)"},{"alpha_fraction":0.5670102834701538,"alphanum_fraction":0.6020618677139282,"avg_line_length":24.578947067260742,"blob_id":"814e772dfd4e80fc123fa3a945c7ff0d4203d233","content_id":"0188397c69b30b192fb67a270a6297bd71d9998f","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":485,"license_type":"no_license","max_line_length":53,"num_lines":19,"path":"/알고리즘/온라인저지/2022/10/1007/유레카 이론.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\n\ntriangle = [1]\nfor i in range(2, 1000):\n tmp = triangle[-1]+i\n if tmp<=1000: triangle.append(tmp)\n else: break\nresult = set()\nlen_tri = len(triangle)\nfor i in range(len_tri):\n for j in range(len_tri):\n for k in range(len_tri):\n tmp = triangle[i]+triangle[j]+triangle[k]\n if tmp<=1000: result.add(tmp)\nfor _ in range(int(input().rstrip())):\n K = int(input().rstrip())\n print(1 if K in result else 0)"},{"alpha_fraction":0.5032680034637451,"alphanum_fraction":0.529411792755127,"avg_line_length":17.058822631835938,"blob_id":"aa005383fe7cb3256b5a9e520220845ee40df8f1","content_id":"bcc9931577852a294d7d3f9230e9f2f9b51668c3","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":306,"license_type":"no_license","max_line_length":39,"num_lines":17,"path":"/알고리즘/온라인저지/2022/03/0310/베시와 데이지.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"B = tuple(map(int, input().split()))\nD = tuple(map(int, input().split()))\nJ = tuple(map(int, input().split()))\n\nd = abs(D[0]-J[0]) + abs(D[1]-J[1])\nb = max(abs(B[0]-J[0]), abs(B[1]-J[1]))\n\nresult = ''\n\nif d < b:\n result = 'daisy'\nelif b < d:\n result = 'bessie'\nelse:\n result = 'tie'\n\nprint(result)"},{"alpha_fraction":0.4935064911842346,"alphanum_fraction":0.5324675440788269,"avg_line_length":38,"blob_id":"31a834b1d9bf930dab2cf1ef92f73ec7e5ef35ab","content_id":"7ca41aefa9a586938f816f1a3b5ef69294f8aef1","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":77,"license_type":"no_license","max_line_length":58,"num_lines":2,"path":"/알고리즘/온라인저지/2022/08/0822/Equality.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"Q = input() # quiz\nprint('YES' if int(Q[0])+int(Q[4]) == int(Q[8]) else 'NO')"},{"alpha_fraction":0.4591549336910248,"alphanum_fraction":0.5042253732681274,"avg_line_length":24.428571701049805,"blob_id":"436baf1a9b9ec92217f541ae9b7f3fc74af6db63","content_id":"a651318562020a1400757a931ba3400c15e1bd01","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":355,"license_type":"no_license","max_line_length":69,"num_lines":14,"path":"/알고리즘/온라인저지/2022/10/1017/소수 단어.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"word = input()\nnum = 0\nfor w in word:\n if w.isupper(): # upper\n num += ord(w)-65+26+1\n else: # lower\n num += ord(w)-97+1\nn = int(1e4)\na = [False, True] + [True]*(n-1)\nfor i in range(2, n+1):\n if a[i]:\n for j in range(2*i, n+1, i):\n a[j] = False\nprint('It is a prime word.' if a[num] else 'It is not a prime word.')"},{"alpha_fraction":0.6142857074737549,"alphanum_fraction":0.6571428775787354,"avg_line_length":16.75,"blob_id":"099a02d05501c8f3025396ffd09719bb666b941f","content_id":"db16edb0bbea6e1e1dfaee1edf38582cafb283b9","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":70,"license_type":"no_license","max_line_length":37,"num_lines":4,"path":"/알고리즘/온라인저지/2022/12/1226/너의 이름은 몇 점이니.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"input()\nresult = 0\nfor i in input(): result += ord(i)-64\nprint(result)"},{"alpha_fraction":0.47680413722991943,"alphanum_fraction":0.5051546096801758,"avg_line_length":28.923076629638672,"blob_id":"60010eb3bdd8af01bd5b6eddac6fb3c5d5fdfc52","content_id":"24a0d7a3a9ef67e3441a626fd58d937f69a140d8","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":388,"license_type":"no_license","max_line_length":42,"num_lines":13,"path":"/알고리즘/온라인저지/2022/10/1012/가위 바위 보.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"player_1_win = ['P R', 'R S', 'S P']\nplayer_2_win = ['R P', 'S R', 'P S']\nfor t in range(int(input())):\n RSP = 0\n result = ''\n for n in range(int(input())):\n tmp = input()\n if tmp in player_1_win: RSP += 1\n elif tmp in player_2_win: RSP -= 1\n if RSP > 0: result = 'Player 1'\n elif RSP < 0: result = 'Player 2'\n else: result = 'TIE'\n print(result)"},{"alpha_fraction":0.5976095795631409,"alphanum_fraction":0.6215139627456665,"avg_line_length":20,"blob_id":"f0cb06faad63eee39a5850e3454f8954aa2898f2","content_id":"87e37cb007829ba62932568ddce7fd57030cbb3e","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":251,"license_type":"no_license","max_line_length":54,"num_lines":12,"path":"/알고리즘/온라인저지/2022/10/1003/수리공 항승.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\n\nN, L = map(int, input().rstrip().split())\narr = sorted(list(map(int, input().rstrip().split())))\nresult = 0\nwhile arr:\n tmp = arr[0]+L-1\n while arr and arr[0]<=tmp: arr.pop(0)\n result += 1\nprint(result)"},{"alpha_fraction":0.3227176368236542,"alphanum_fraction":0.40976646542549133,"avg_line_length":21.4761905670166,"blob_id":"e37272de4483ee87142df3d774a1b52786ce1f20","content_id":"3f68a06eaea56d3944f1bbb152ee210a4fcb7e71","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":471,"license_type":"no_license","max_line_length":37,"num_lines":21,"path":"/알고리즘/온라인저지/2023/03/0318/받아올림.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"while True:\n A, B = input().split()\n if A == '0' and B == '0': break\n A = '00000000000000'+A\n B = '00000000000000'+B\n arr = []\n A = list(A)[::-1]\n B = list(B)[::-1]\n for i in range(10):\n a, b = map(int, (A[i], B[i]))\n C = a+b\n if C:\n arr.append(C)\n arr.append(0)\n result = 0\n for i in range(len(arr)):\n a = arr[i]\n if a>=10:\n result += 1\n arr[i+1] += 1\n print(result)"},{"alpha_fraction":0.41603052616119385,"alphanum_fraction":0.4312977194786072,"avg_line_length":12.8421049118042,"blob_id":"aa4ef13da2107a93024e8d35cdb95cc00296fc60","content_id":"865b24e0d546f2dcf3225b2e1633974aef63733f","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":262,"license_type":"no_license","max_line_length":35,"num_lines":19,"path":"/알고리즘/온라인저지/2022/01/0131/시험 감독.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = int(input())\n\nresult = 0\n\nA = list(map(int, input().split()))\n\nB, C = map(int, input().split())\n\nfor a in A:\n a -= B\n result += 1\n\n if a > 0:\n result += a//C\n tmp = C * (a//C)\n if a != tmp:\n result += 1\n\nprint(result)"},{"alpha_fraction":0.4332129955291748,"alphanum_fraction":0.5577617287635803,"avg_line_length":19.55555534362793,"blob_id":"b54183e331a3cfdebb865971c8f7ed3655d2bed0","content_id":"69bce0481659e57f376eb4e78bf3deea794234f5","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":896,"license_type":"no_license","max_line_length":52,"num_lines":27,"path":"/알고리즘/[템플릿]/[SAMPLE]/비트연산 부분집합.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"arr = [3, 6, 8]\nn = len(arr)\n\nfor i in range(1<<n):\n for j in range(n):\n if i&(1<<j):\n print(arr[j], end=' ')\n print()\n \n\"\"\"\n0 0 0 : 0\n0 0 1 : 3\n0 1 0 : 6\n0 1 1 : 3 6\n1 0 0 : 8\n1 0 1 : 3 8\n1 1 0 : 6 8\n1 1 1 : 3 6 8\n각각의 숫자는, 각각의 원소들이 있고, 없고를 의미함\ni는 십진수이지만 연산상에서는 2진수로 작용하고\n1<<j는 range에서 0 1 2 ... 일 때, 1 10 100 1000... 으로 증가함\ni&(1<<j)라는건 결국 이진수로 표현된 i가 해당 자리수가 1인지\n즉, 리스트에서 그 원소를 포함하는 부분집합인지를 의미함\nj는 원소 자체를 의미하는게 아니라 원소의 위치, 순서를 의미하고\n3번째 원소(인덱스 상으로 2번째)인 8을 확인하는건 1<<3, 즉 100(이진수)\n이는 돌고있는 i가 1 X X면 8을 포함하는 부분집합이라는 것을 알 수 있다\n\"\"\""},{"alpha_fraction":0.5684455037117004,"alphanum_fraction":0.5870069861412048,"avg_line_length":24.41176414489746,"blob_id":"de41654ecfce008da98074dbf597bd3a86d20ed3","content_id":"478a429ad8173502949c471a1c25761448ece7fb","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":607,"license_type":"no_license","max_line_length":68,"num_lines":17,"path":"/알고리즘/온라인저지/2021/10/1016/회의실 배정.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = int(input())\n\narr = []\n\nfor n in range(N):\n arr.append(tuple(map(int, input().split()))) # 속도 향상을 위한 tuple()\n\narr.sort() # arr[x][0]을 기준으로 정렬\narr.sort(key=lambda x: x[1]) # 다시 한번 x[1]을 기준으로 정렬\n\nresult = [arr[0]] # 첫번째 회의\n\nfor i in range(1, len(arr)): # 두번째 회의부터 회의실 사용 가능한지 확인\n if result[-1][1] <= arr[i][0]: # 이전 회의의 종료시간보다 다음 회의의 시작시간이 늦으면\n result.append(arr[i]) # 회의실 사용가능\n \nprint(len(result)) # 회의실 사용팀 수 출력"},{"alpha_fraction":0.5836910009384155,"alphanum_fraction":0.5836910009384155,"avg_line_length":20.272727966308594,"blob_id":"a1fc9f43a73ede6d07661c29781e76dea9da6d1f","content_id":"da72491349c5377040c2ae28a04b56a074bb9471","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":233,"license_type":"no_license","max_line_length":33,"num_lines":11,"path":"/알고리즘/온라인저지/2022/07/0729/듣보잡.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N, M = map(int, input().split())\nL = set() # listened\nfor n in range(N): L.add(input())\nresult = []\nfor m in range(M):\n s = input()\n if s in L:\n result.append(s)\nresult.sort()\nprint(len(result))\nfor r in result: print(r)"},{"alpha_fraction":0.5286624431610107,"alphanum_fraction":0.5414012670516968,"avg_line_length":30.600000381469727,"blob_id":"6571a36dc3d87ff9d1ead769cb364ada30fae46d","content_id":"a2efb9f05a12de3fbd40902fc460fc7dd48188e1","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":157,"license_type":"no_license","max_line_length":60,"num_lines":5,"path":"/알고리즘/온라인저지/2022/12/1219/주식 투자.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"for _ in range(int(input())):\n result = 0\n for n in range(int(input())):\n result += max(list(map(int, input().split())) + [0])\n print(result)"},{"alpha_fraction":0.46686747670173645,"alphanum_fraction":0.4909638464450836,"avg_line_length":19.8125,"blob_id":"fed60ae259d0a0e3cff519d3c42a19c1705e116c","content_id":"c7a8c12cdce9597a69b4492ae133f20c7910dfb3","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":332,"license_type":"no_license","max_line_length":47,"num_lines":16,"path":"/알고리즘/온라인저지/2022/08/0807/꿀벌.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\n\nT = ['Re', 'Pt', 'Cc', 'Ea', 'Tb', 'Cm', 'Ex']\nB = {t:0 for t in T}\ncnt = 0\nwhile True:\n I = input().rstrip().split()\n if not I: break\n for i in I:\n cnt += 1\n try: B[i] += 1\n except: pass\nfor t in T: print(f'{t} {B[t]} {B[t]/cnt:.2f}')\nprint(f'Total {cnt} 1.00')"},{"alpha_fraction":0.46268656849861145,"alphanum_fraction":0.49253731966018677,"avg_line_length":18.285715103149414,"blob_id":"9cb3f799ef7336e04f77f239324c46215ce8ab0a","content_id":"5877e1f38deb1c4c2da7c625fc8346ad2c4bb8c0","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":134,"license_type":"no_license","max_line_length":27,"num_lines":7,"path":"/알고리즘/온라인저지/2023/03/0313/Pyramids.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"while True:\n N = int(input())\n if N == 0: break\n result = 0\n for i in range(1, N+1):\n result += i\n print(result)"},{"alpha_fraction":0.36206895112991333,"alphanum_fraction":0.4367816150188446,"avg_line_length":12.384614944458008,"blob_id":"aa498041dbb0c132d5a3fa0edcfea6c707359a2d","content_id":"8d262ca2dd8a4e52e6ddafab4a2a2a007f579f9e","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":174,"license_type":"no_license","max_line_length":27,"num_lines":13,"path":"/알고리즘/SWEA/LEARN/Course/1. Programming Beginner/파이썬 프로그래밍 기초(2)/33차시 3. 자료구조 – 셋, 딕셔너리 - 연습문제 8.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"sen = input()\n\nu = 0\nl = 0\n\nfor s in sen:\n if 65 <= ord(s) <= 90:\n u += 1\n if 97 <= ord(s) <= 122:\n l += 1\n\nprint('UPPER CASE', u)\nprint('LOWER CASE', l)\n"},{"alpha_fraction":0.5600000023841858,"alphanum_fraction":0.568648636341095,"avg_line_length":23.36842155456543,"blob_id":"f01ed89b93d4b0d78574e6899e1e4f21d68041d7","content_id":"62b8aaf986f8bc0ff02bbc329bafd63dbbfd5b1a","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1213,"license_type":"no_license","max_line_length":47,"num_lines":38,"path":"/알고리즘/[템플릿]/정렬/퀵정렬.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"\"\"\"\n첫 피봇은 arr[0]\narr의 앞에서 시작하는 left, 뒤에서 시작하는 right\n피봇을 기준으로 이 두 값이 각각 작고 큰 값을 찾다가\n찾으면 두 값을 서로 바꿔주고\n못찾고 left와 right가 교차해버리면\nright와 피봇값을 바꿔주어, 정렬중인 배열의 left와 right 중간에\n그러니까, 피봇이 있어야 할 자리에 피봇을 넣어준다\npartition 함수를 통해 피봇값을 얻고\nquick_sort 함수를 통해 계속해서 분할하여 정복하는 식으로 배열을 정렬해나간다\n\"\"\"\n\ndef partition(arr, left, right):\n pivot = arr[left]\n i = left + 1\n j = right\n\n while i <= j:\n while i <= j and arr[i] <= pivot:\n i += 1\n while i <= j and arr[j] >= pivot:\n j -= 1\n\n if i <= j:\n arr[i], arr[j] = arr[j], arr[i]\n arr[left], arr[j] = arr[j], arr[left]\n return j\n\ndef quick_sort(arr, left, right):\n if left < right:\n center = partition(arr, left, right)\n quick_sort(arr, left, center-1)\n quick_sort(arr, center+1, right)\n\nfor t in range(int(input())):\n arr = list(map(int, input().split()))\n quick_sort(arr, 0, len(arr)-1)\n print(*arr)"},{"alpha_fraction":0.42506811022758484,"alphanum_fraction":0.4386920928955078,"avg_line_length":20.647058486938477,"blob_id":"e8f8953833c7f4342343f6f45896b80e75a535a3","content_id":"1ccc19dfff3751d3059560aafd02dda1d03cc661","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":367,"license_type":"no_license","max_line_length":38,"num_lines":17,"path":"/알고리즘/온라인저지/2022/02/0220/방 배정하기.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"A, B, C, N = map(int, input().split())\n\nfound_ans = False\n\nfor a in range(N//A + 1):\n if found_ans:\n break\n for b in range(N//B + 1):\n if found_ans:\n break\n for c in range(N//C + 1):\n tmp = N-(a*A + b*B + c*C)\n if not tmp:\n found_ans = True\n break\n\nprint(1 if found_ans else 0)"},{"alpha_fraction":0.49462366104125977,"alphanum_fraction":0.5161290168762207,"avg_line_length":14.666666984558105,"blob_id":"7589e79fe8586a60479f7d2d86f2aa3faf329c0d","content_id":"6d15475a2227f91236745081681271bd6866a5c8","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":93,"license_type":"no_license","max_line_length":36,"num_lines":6,"path":"/알고리즘/온라인저지/2022/02/0220/문자열.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"T = int(input())\n\nfor t in range(T):\n text = input()\n\n print(text[0], text[-1], sep='')"},{"alpha_fraction":0.3807106614112854,"alphanum_fraction":0.4568527936935425,"avg_line_length":18.799999237060547,"blob_id":"5cf765420a2089ae3db51cc7b155764851ec5842","content_id":"65a37239321e96f0ee39e9c6927c9a2636107ce0","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":197,"license_type":"no_license","max_line_length":38,"num_lines":10,"path":"/알고리즘/온라인저지/2022/06/0611/적어도 대부분의 배수.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"nums = list(map(int, input().split()))\nmaxx = 10000000000\nfor i in range(1, maxx):\n a = 0\n for n in nums:\n if not i%n:\n a += 1\n if a >= 3:\n print(i)\n exit()"},{"alpha_fraction":0.29611650109291077,"alphanum_fraction":0.46116504073143005,"avg_line_length":16.95652198791504,"blob_id":"a8a210f337347b4f5ec49da930f4370731b1795d","content_id":"cac4bea1247b5d3a7cdc550c60fb7859782f4817","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":412,"license_type":"no_license","max_line_length":35,"num_lines":23,"path":"/알고리즘/온라인저지/2022/02/0203/저항.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"r = {\n 'black': ('0', 1),\n 'brown': ('1', 10),\n 'red': ('2', 100),\n 'orange': ('3', 1000),\n 'yellow': ('4', 10000),\n 'green': ('5', 100000),\n 'blue': ('6', 1000000),\n 'violet': ('7', 10000000),\n 'grey': ('8', 100000000),\n 'white': ('9', 1000000000),\n}\n\nresult = ''\n\nfor _ in range(2):\n result = result + r[input()][0]\n\nresult = int(result)\n\nresult *= r[input()][1]\n\nprint(result)"},{"alpha_fraction":0.42105263471603394,"alphanum_fraction":0.4417862892150879,"avg_line_length":23.153846740722656,"blob_id":"0ec4ae41156f014d01d047f5794e2ddc62e8c1e7","content_id":"00306e1cbf921fafc5d5009246bc079eab8e7a2f","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":627,"license_type":"no_license","max_line_length":49,"num_lines":26,"path":"/알고리즘/온라인저지/2022/09/0904/부분 문자열.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"def get_pi(pattern):\n j = 0\n for i in range(1, len(pattern)):\n while j > 0 and pattern[i] != pattern[j]:\n j = pi[j - 1]\n if pattern[i] == pattern[j]:\n j += 1\n pi[i] = j\n\ndef KMP(string, pattern):\n get_pi(pattern)\n j = 0\n for i in range(len(string)):\n while j > 0 and string[i] != pattern[j]:\n j = pi[j-1]\n if string[i] == pattern[j]:\n if j == len(pattern)-1:\n return True\n else:\n j += 1\n return False\n\nS, P = input(), input()\npi = [0] * len(P)\nif KMP(S, P): print('1')\nelse: print('0')"},{"alpha_fraction":0.4172042906284332,"alphanum_fraction":0.43225806951522827,"avg_line_length":19.217391967773438,"blob_id":"82ce95e3602fa122847521808a5f55034dd96eca","content_id":"a38de496a80c399a6d27ac7bc9b262d0515f0f1c","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":465,"license_type":"no_license","max_line_length":40,"num_lines":23,"path":"/알고리즘/온라인저지/2022/02/0225/삼각형과 세 변.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"while True:\n A, B, C = map(int, input().split())\n if A+B+C == 0:\n break\n\n result = 'Scalene'\n\n if A+B+C == max(A, B, C) * 2:\n result = 'Invalid'\n \n nums = set([A, B, C])\n\n if len(nums) == 2:\n temp = [A, B, C]\n temp.sort()\n if temp[2] - temp[0] >= temp[1]:\n result = 'Invalid'\n else:\n result = 'Isosceles'\n elif len(nums) == 1:\n result = 'Equilateral'\n\n print(result)\n"},{"alpha_fraction":0.4945652186870575,"alphanum_fraction":0.5,"avg_line_length":9.277777671813965,"blob_id":"e0ad5d7f011785cd33f0daabb68e77bb5454756b","content_id":"e275252de5a46cae786cb9211050acdb03add30a","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":184,"license_type":"no_license","max_line_length":20,"num_lines":18,"path":"/알고리즘/온라인저지/2022/02/0207/수도요금.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"A = int(input())\nB = int(input())\nC = int(input())\nD = int(input())\nP = int(input())\n\nresult = 0\n\nXP = A * P\n\nYP = B\n\nif P > C:\n YP += (P-C) * D\n\nresult = min(XP, YP)\n\nprint(result)"},{"alpha_fraction":0.6086956262588501,"alphanum_fraction":0.695652186870575,"avg_line_length":11,"blob_id":"4b1ba1bcb7dcbad9b5b13406806d7558ea7867a1","content_id":"dde44ec7ab3a33bb89892b9f89fb2c4fcfc46992","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":23,"license_type":"no_license","max_line_length":15,"num_lines":2,"path":"/알고리즘/온라인저지/2023/05/0506/소수가 아닌 수.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"input()\nprint(int(1e9))"},{"alpha_fraction":0.5422885417938232,"alphanum_fraction":0.572139322757721,"avg_line_length":21.44444465637207,"blob_id":"9d2cb6716f3411ee8e6be871208fa84f81772626","content_id":"52aa7eab5c6b43578290d89e5f4cda7866ff3a75","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":201,"license_type":"no_license","max_line_length":39,"num_lines":9,"path":"/알고리즘/온라인저지/2023/02/0218/알바생 강호.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"result = 0\nN = int(input())\ntips = [int(input()) for _ in range(N)]\ntips.sort(reverse=True)\nfor i in range(1, N+1):\n tip = tips[i-1]\n tip = tip - (i-1)\n if tip > 0: result += tip\nprint(result)"},{"alpha_fraction":0.46783626079559326,"alphanum_fraction":0.5087719559669495,"avg_line_length":13.333333015441895,"blob_id":"c9830558f3082d842a11bbbfeca0c84dd0e60e2c","content_id":"133a8ef2ba010a04d4000ac72132ed93198f21b0","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":171,"license_type":"no_license","max_line_length":31,"num_lines":12,"path":"/알고리즘/온라인저지/2021/08/0818/팩토리얼 DP.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"def fact(n):\n table [0] = 1\n for i in range(1, n+1):\n table[i] = i*table[i-1]\n\n\n return table[n]\n\nn = int(input())\ntable = [0] * (n+1)\nfact(n)\nprint(table)"},{"alpha_fraction":0.369047611951828,"alphanum_fraction":0.3928571343421936,"avg_line_length":17.77777862548828,"blob_id":"8542ce2a7eaaa4603a26dc2b1a2d1b587d497de4","content_id":"b1b08cbbd0f92efa0e666e1849fef9510e9aafe9","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":168,"license_type":"no_license","max_line_length":25,"num_lines":9,"path":"/알고리즘/온라인저지/2022/12/1211/숫자 놀이.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"while True:\n N = int(input())\n if N == 0: break\n while N >= 10:\n tmp = 0\n for n in str(N):\n tmp += int(n)\n N = tmp\n print(N)"},{"alpha_fraction":0.4337349534034729,"alphanum_fraction":0.4518072307109833,"avg_line_length":21.200000762939453,"blob_id":"ec25611fa3973661b012eb2a81b12babc4eec058","content_id":"f3eed1e5829a57d697f32fa9390b14ddd599a4fb","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":332,"license_type":"no_license","max_line_length":39,"num_lines":15,"path":"/알고리즘/온라인저지/2022/07/0703/Pen Pineapple Apple Pen.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = int(input())\nword = input()\nresult = 0\nidxs = []\nfor i in range(N-3):\n tmp = word[i:i+4]\n if tmp == 'pPAp':\n is_used = False\n for j in range(i, i+4):\n if j in idxs:\n is_used = True\n if not is_used:\n result += 1\n idxs += list(range(i, i+4))\nprint(result)"},{"alpha_fraction":0.43089431524276733,"alphanum_fraction":0.577235758304596,"avg_line_length":14.5,"blob_id":"ddaf8fe5774594d1aa02eefc5ff2d8def1205d9e","content_id":"3141a245ea92760f14de34b50cd81d3a070d06fd","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":123,"license_type":"no_license","max_line_length":36,"num_lines":8,"path":"/알고리즘/SWEA/LEARN/Course/1. Programming Beginner/파이썬 프로그래밍 기초(2)/21차시 2. 자료구조 – 리스트, 튜플 - 연습문제 23.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"arr = [12, 24, 35, 70, 88, 120, 155]\n\nresult = []\n\nfor i in range(1, len(arr), 2):\n result.append(arr[i])\n\nprint(result)"},{"alpha_fraction":0.3997906744480133,"alphanum_fraction":0.42804813385009766,"avg_line_length":28.8125,"blob_id":"bc9912e2cffd75f68dcb3793040f03495d5dfce2","content_id":"b90dcba4d539c1e31c3b3813d3fc1db7a69046e8","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1965,"license_type":"no_license","max_line_length":87,"num_lines":64,"path":"/알고리즘/SW역량테스트/2022.04.12 A형.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"def dfs(w, h, depth, tmp):\n global visited, maxx\n print(h, w, depth, tmp)\n # print(visited)\n if depth == 4:\n # print('depth 4 here', w, h, depth, tmp)\n if tmp > maxx:\n maxx = tmp\n print('THIS IS MAXX😊😉😊😊', maxx)\n return\n for i in range(6):\n if (0 <= w+dx[i] < W) and (0 <= h+dy[i] < H) and not visited[h+dy[i]][w+dx[i]]:\n visited[h+dy[i]][w+dx[i]] = 1\n dfs(w+dx[i], h+dy[i], depth+1, tmp+arr[h+dy[i]][w+dx[i]])\n visited[h+dy[i]][w+dx[i]] = 0\n\n# 12시 방향부터 시계방향으로 델타이동\ndx = [0, 1, 1, 0, -1, -1]\ndy = [-1, -1, 0, 1, 0, -1]\nT = int(input())\nfor t in range(1, T+1):\n W, H = map(int, input().split())\n arr = [list(map(int, input().split())) for _ in range(H)]\n # print(arr)\n maxx = 0\n for h in range(H):\n for w in range(W):\n visited = [[0]*W for _ in range(H)]\n visited[h][w] = 1\n dfs(w, h, 1, arr[h][w])\n print('------------------')\n print(maxx ** 2)\n\n\n# def dfs(i, depth, tmp):\n# global visited, maxx\n# print(i, depth, tmp)\n# if depth == 4:\n# # print('depth 4 here', w, h, depth, tmp)\n# if tmp > maxx:\n# maxx = tmp\n# print('THIS IS MAXX😊😉😊😊', maxx)\n# return\n# for j in range(6):\n# if (1 <= i+dx[j] < W*H+1) and not visited[i+dx[j]]:\n# visited[i+dx[j]] = 1\n# dfs(i+dx[j], depth+1, tmp+arr[i+dx[j]])\n# visited[i+dx[j]] = 0\n\n# dx = [-5, -4, 1, 5, -1, -6]\n# T = int(input())\n# for t in range(1, T+1):\n# W, H = map(int, input().split())\n# arr = [0]\n# for h in range(H):\n# arr += list(map(int, input().split()))\n# maxx = 0\n# for i in range(1, W*H+1):\n# visited = [0] * len(arr)\n# visited[i] = 1\n# dfs(i, 1, arr[i])\n# print('------------------')\n# print(maxx ** 2)\n# print(arr[9]) "},{"alpha_fraction":0.5130434632301331,"alphanum_fraction":0.530434787273407,"avg_line_length":13.5,"blob_id":"60468c1a785829c9871f68fedb7d353e2000f96d","content_id":"d537011f60bfaeef70220c148a5e4451d5014b9e","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":115,"license_type":"no_license","max_line_length":35,"num_lines":8,"path":"/알고리즘/온라인저지/2021/12/1213/과자.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"a, b, c = map(int, input().split())\n\nresult = c - (a * b)\n\nif result < 0:\n print(abs(result))\nelse:\n print(0)"},{"alpha_fraction":0.4268292784690857,"alphanum_fraction":0.48373982310295105,"avg_line_length":19.58333396911621,"blob_id":"f0f7757e20e223a16eb06261ba79b3f014f0b45c","content_id":"edc903b12a421f78ab76e136bb42586ef6e78837","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":246,"license_type":"no_license","max_line_length":36,"num_lines":12,"path":"/알고리즘/온라인저지/2022/05/0530/삼각 김밥.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"a, b = map(int, input().split())\ncheap = b/a\ne, f = a, b\nN = int(input())\nfor n in range(N):\n c, d = map(int, input().split())\n if d/c > cheap:\n cheap = d/c\n e, f = c, d\n# print(e, f)\nprint(f'{e*1000/f:.2f}')\n# 37:532 = x:1000"},{"alpha_fraction":0.54076087474823,"alphanum_fraction":0.5625,"avg_line_length":20.705883026123047,"blob_id":"85500c74c0eb0b48691208e94cc131b6e9cd46d9","content_id":"3d5ebd8ea76c6abf1bd83ba2fa737f39b902d185","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":368,"license_type":"no_license","max_line_length":49,"num_lines":17,"path":"/알고리즘/온라인저지/2022/10/1012/동전 2.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\nINF = int(1e9)\n\nN, K = map(int, input().rstrip().split())\ncoins = set()\nfor i in range(N):\n coins.add(int(input().rstrip()))\ncoins = list(coins)\ndp = [INF]*(K+1)\ndp[0] = 0\nfor i in range(K+1):\n for coin in coins:\n if i+coin <= K:\n dp[i+coin] = min(dp[i]+1, dp[i+coin])\nprint(dp[K] if dp[K] != INF else -1)"},{"alpha_fraction":0.4523809552192688,"alphanum_fraction":0.5,"avg_line_length":27.16666603088379,"blob_id":"c0ea716f3da6c5e8ec063f292e0837e7f1a48d94","content_id":"28952e7638e1785803668385e3e8decbcc73547b","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":168,"license_type":"no_license","max_line_length":47,"num_lines":6,"path":"/알고리즘/온라인저지/2022/08/0821/Winning Score.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"A, B = 0, 0\nfor i in range(3, 0, -1): A += int(input()) * i\nfor i in range(3, 0, -1): B += int(input()) * i\nif A > B: print('A')\nelif B > A: print('B')\nelse: print('T')"},{"alpha_fraction":0.4456404745578766,"alphanum_fraction":0.46824541687965393,"avg_line_length":29,"blob_id":"9b025bc0228d3634c729c1295ca26f6b515527f6","content_id":"b2f67723ee223e95235030e3d67dad23470e9afa","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1451,"license_type":"no_license","max_line_length":72,"num_lines":31,"path":"/알고리즘/온라인저지/2021/08/0814/전자레인지.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"\"\"\"\n버튼 A, B, C 각각 300초, 60초, 10초\n버튼을 누른 총 횟수가 최소횟수 일 때\n각 버튼을 누른 횟수를 버튼별로 출력\nT만큼 정확히 전자레인지를 동작시킬 수 없으면 -1\n\"\"\"\n\"\"\"\n해결법 탐색\n초기 접근법 독스트링 작성\n코드 작성\n백준 제출\n코드주석 작성\n백준에는 주석은 달지말고\n백준 통과하면 그 다음에 코드파일에만 주석 달자\n\"\"\"\n\nT = int(input()) # 시간초 입력\nbuttons = [300, 60, 10] # 버튼 A, B, C를 초로 환산\ncounts = [0] * 3 # 버튼 누른 횟수 리스트 초기화\nfor i in range(len(buttons)): # 버튼의 개수만큼 순회\n if buttons[i] <= T: # 순회중인 버튼(A->B->C)으로 작동 시켜도 시간을 초과하지 않으면\n while True: # 버튼 누르기를 반복\n counts[i] += 1 # 버튼을 누르고\n T -= buttons[i] # 버튼이 동작하는 시간만큼 빼주고\n if buttons[i] > T: # 버튼시간이 더 크면\n break # while문 종료\nif T == 0: # 깔끔하게 T초만큼 동작했으면\n for count in counts: # 버튼 카운트들 순회하면서\n print(count, end=' ') # 카운트 출력\nelse: # 버튼들로 T초를 완벽하게 동작시키지 못했으면\n print(-1) # -1 출력"},{"alpha_fraction":0.35930734872817993,"alphanum_fraction":0.43290042877197266,"avg_line_length":24.77777862548828,"blob_id":"4b45b62b32bdeeb19efb96b10e0d9379142626b6","content_id":"51fc876d0e9f05470950e728b22dec226965264b","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":231,"license_type":"no_license","max_line_length":34,"num_lines":9,"path":"/알고리즘/온라인저지/2022/07/0731/파스칼의 삼각형.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N, K = map(int, input().split())\nP = [[1], [1, 1], [1, 2, 1]]\nfor n in range(N-3):\n tmp = [0] * (2+n)\n for i in range(len(P[-1])-1):\n tmp[i] = sum(P[-1][i:i+2])\n tmp = [1]+tmp+[1]\n P.append(tmp)\nprint(P[-1][K-1])"},{"alpha_fraction":0.5058823823928833,"alphanum_fraction":0.5215686559677124,"avg_line_length":17.285715103149414,"blob_id":"b9f28aa32082e882ad7b6c3fb4edf1e4fa2f5723","content_id":"8425547ce50a744fc851bfddf9ef23b1b8553d40","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":255,"license_type":"no_license","max_line_length":30,"num_lines":14,"path":"/알고리즘/온라인저지/2022/11/1108/도비의 영어 공부.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\n\nwhile True:\n tmp = input().rstrip()\n check = tmp[0]\n if check == '#': break\n sen = tmp[2:]\n result = 0\n for s in sen:\n if s.lower() == check:\n result += 1\n print(check, result)"},{"alpha_fraction":0.5030674934387207,"alphanum_fraction":0.5153374075889587,"avg_line_length":19.375,"blob_id":"33ef02e8d4ea7cadcbd78e044c894c8d1fc73c3e","content_id":"90abd7c62fb0ec98970dc898d24b3b778961ace8","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":163,"license_type":"no_license","max_line_length":34,"num_lines":8,"path":"/알고리즘/온라인저지/2023/06/0603/Judging Moose.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"L, R = map(int, input().split())\nresult = 'Not a moose'\nif L == R:\n if L:\n result = f'Even {L*2}'\nelse:\n result = f'Odd {max((L,R))*2}'\nprint(result)\n"},{"alpha_fraction":0.6071428656578064,"alphanum_fraction":0.6071428656578064,"avg_line_length":16.625,"blob_id":"2c46261a38fcbd67da442e7156a7413c23fed7ea","content_id":"14f6a0a667db5396199c32e6861b6d0f22ef5fc8","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":164,"license_type":"no_license","max_line_length":56,"num_lines":8,"path":"/알고리즘/온라인저지/2022/07/0701/접미사 배열.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"\"\"\"\n접미사를 모아서, 정렬 후 출력\n\"\"\"\nword = input()\narr = []\nfor i in range(len(word)): arr.append(word[i:len(word)])\narr.sort()\nfor a in arr: print(a)"},{"alpha_fraction":0.4838709533214569,"alphanum_fraction":0.5307917594909668,"avg_line_length":27.5,"blob_id":"9bdfc1f225ca2816c47656e83377f71e7567a063","content_id":"e5edb6361d2d60e30b09ceb4e645a79bd5a867fe","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":341,"license_type":"no_license","max_line_length":72,"num_lines":12,"path":"/알고리즘/온라인저지/2021/08/0818/삼각형 외우기.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"data = []\nfor _ in range(3):\n data.append(int(input()))\nif sum(data) == 180:\n if data[0] == data[1] and data[1] == data[2] and data[2] == data[0]:\n print('Equilateral')\n elif data[0] == data[1] or data[1] == data[2] or data[2] == data[0]:\n print('Isosceles')\n else:\n print('Scalene')\nelse:\n print('Error')"},{"alpha_fraction":0.4481408894062042,"alphanum_fraction":0.4618395268917084,"avg_line_length":22.272727966308594,"blob_id":"ff2573218e2beb5fca0986a005aa3a2c15285f44","content_id":"86415d71d7ad228b4a6789d1b4fd92a91a145c77","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":741,"license_type":"no_license","max_line_length":35,"num_lines":22,"path":"/알고리즘/온라인저지/2022/03/0323/A와 B.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"S = list(input())\nT = list(input())\nresult = 0\n# S를 T로 만들지 않고, T를 S로 만든다\n# 이유는 두 가지\n# 1.pop()에서 인덱스 없이 사용하여 속도 향상\n# 2.추가, 뒤집고 추가 -> 제거, 제거 후 뒤집기\n# 후자는 둘 다 일단 제거하고 시작하므로 더 직관적임\nwhile True:\n if S == T:\n result = 1 # S를 T로 만들 수 있다!\n break # 종료\n if T[-1] == 'A':\n T.pop() # A를 빼주고\n if not T: # 마지막 문자를 뺐다면\n break # 종료\n elif T[-1] == 'B':\n T.pop() # B를 빼주고\n if not T: # 마지막 문자를 뺐다면\n break # 종료\n T = T[::-1] # 뒤집고\nprint(result) # 결과 출력"},{"alpha_fraction":0.5269230604171753,"alphanum_fraction":0.5423076748847961,"avg_line_length":20.75,"blob_id":"341c3fce55c73ffef13d5ee4255424e07a75e5d4","content_id":"0ada239f67af0a17f60f8d852360f69bdc2ea2e6","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":260,"license_type":"no_license","max_line_length":39,"num_lines":12,"path":"/알고리즘/온라인저지/2023/01/0108/고급 여관.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"A_atk, A_hp = map(int, input().split())\nB_atk, B_hp = map(int, input().split())\nwhile A_hp > 0 and B_hp > 0:\n A_hp -= B_atk\n B_hp -= A_atk\nif A_hp > 0:\n result = 'PLAYER A'\nelif B_hp > 0:\n result = 'PLAYER B'\nelse:\n result = 'DRAW'\nprint(result)"},{"alpha_fraction":0.4957983195781708,"alphanum_fraction":0.5462185144424438,"avg_line_length":19,"blob_id":"c530d9f3fb9b641fe47aa9bae4e3c4e5c8c024bb","content_id":"e0c2834302ec44a4eee72ac31b67fbaf5d8d4c98","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":119,"license_type":"no_license","max_line_length":50,"num_lines":6,"path":"/알고리즘/온라인저지/2022/09/0906/アイスクリーム (Ice Cream).py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"S, A, B = int(input()), int(input()), int(input())\nresult = 250\nwhile A < S:\n A += B\n result += 100\nprint(result)"},{"alpha_fraction":0.5072463750839233,"alphanum_fraction":0.5507246255874634,"avg_line_length":26.799999237060547,"blob_id":"e2a6170203004231145789d3e95112b4be71927d","content_id":"1bf9366add35ecc10481f340e203b4ad66f7db7a","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":138,"license_type":"no_license","max_line_length":49,"num_lines":5,"path":"/알고리즘/온라인저지/2023/02/0208/Patyki.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"A, B, C = sorted(list(map(int, input().split())))\nresult = 0\nif A == B == C: result = 2\nelif C**2 == A**2 + B**2: result = 1\nprint(result)"},{"alpha_fraction":0.4878048896789551,"alphanum_fraction":0.5365853905677795,"avg_line_length":20,"blob_id":"ae4121ca33a00e7cafae6093fdfdf7feb3bdd090","content_id":"6b9f8f60309f5ea937420a5bb44fcea757514f3d","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":41,"license_type":"no_license","max_line_length":24,"num_lines":2,"path":"/알고리즘/온라인저지/2022/05/0520/접시 안의 원.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"T = int(input())\nprint(round((T/2) ** 2))"},{"alpha_fraction":0.5882353186607361,"alphanum_fraction":0.6274510025978088,"avg_line_length":19.600000381469727,"blob_id":"21f5688b03600b1fdc3aab959b3e34a6a9c77c82","content_id":"273b9247cf8931846ff651d5559045ea1792d180","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":102,"license_type":"no_license","max_line_length":38,"num_lines":5,"path":"/알고리즘/온라인저지/2021/08/0822/검증수.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"data = list(map(int, input().split()))\nresult = 0\nfor dt in data:\n result += dt**2\nprint(result%10)"},{"alpha_fraction":0.5511810779571533,"alphanum_fraction":0.5669291615486145,"avg_line_length":13.222222328186035,"blob_id":"ccd862d4c533f21d56ba0b2f1b3d649c3c68ae81","content_id":"4c92aa24095aee2573d391ea2e56ac78c2f018a9","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":127,"license_type":"no_license","max_line_length":35,"num_lines":9,"path":"/알고리즘/온라인저지/2021/12/1230/트리 순회.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = int(input())\n\ntree = dict()\n\nfor n in range(N):\n temp = input().split()\n tree.update({temp[0]:temp[1:]})\n\nprint(tree)"},{"alpha_fraction":0.30434781312942505,"alphanum_fraction":0.49275362491607666,"avg_line_length":16.5,"blob_id":"975333771309e83239097a6fd6a08bd9ea6a3fe2","content_id":"5084e59fb323d465c857878932c1d49c820bb523","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":69,"license_type":"no_license","max_line_length":26,"num_lines":4,"path":"/알고리즘/SWEA/LEARN/Course/1. Programming Beginner/파이썬 프로그래밍 기초(2)/19차시 2. 자료구조 – 리스트, 튜플 - 연습문제 21.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"x = (1,2,3,4,5,6,7,8,9,10)\n\nprint(x[:len(x)//2])\nprint(x[len(x)//2:])"},{"alpha_fraction":0.5405405163764954,"alphanum_fraction":0.5675675868988037,"avg_line_length":14,"blob_id":"f110fcbdbd347580a7c3199890c084393ee1e233","content_id":"05fb42ba8025166ead673f64d4e8694069039497","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":74,"license_type":"no_license","max_line_length":25,"num_lines":5,"path":"/알고리즘/온라인저지/2022/07/0714/5의 수난.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = input()\nresult = 0\nfor n in N:\n result += int(n) ** 5\nprint(result)"},{"alpha_fraction":0.47422680258750916,"alphanum_fraction":0.49484536051750183,"avg_line_length":10.470588684082031,"blob_id":"cf6645afaf8fe6f76032956bd127eb5fd94001dc","content_id":"a768d4a2c00fed585d0b18ad1cbf3d2c9a40e32a","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":194,"license_type":"no_license","max_line_length":31,"num_lines":17,"path":"/알고리즘/온라인저지/2022/03/0302/막대기.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = int(input())\n\nsticks = []\n\nfor n in range(N):\n sticks.append(int(input()))\n\nTH = 0 # Top Height\n\ncnt = 0\n\nfor s in sticks[::-1]:\n if s > TH:\n TH = s\n cnt += 1\n\nprint(cnt)"},{"alpha_fraction":0.38085541129112244,"alphanum_fraction":0.395112007856369,"avg_line_length":14.870967864990234,"blob_id":"aea18e9578905e352a590d0a8601c8114c92d2ab","content_id":"f1667807a7c6af88cf7aed4c583d487c4115b44b","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":491,"license_type":"no_license","max_line_length":36,"num_lines":31,"path":"/알고리즘/온라인저지/2021/09/0909/Fly me to the Alpha Centauri.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\ndef input():\n return sys.stdin.readline()\n\ndef how_many_times(x):\n a = 1\n i = 1\n if a == x:\n return i\n b = 1\n a = a+b\n i += 1\n if a == x:\n return i\n while True:\n b += 1\n a = a+b\n i += 1\n if a >= x:\n break\n a = a+b\n i += 1\n if a >= x:\n break\n return i\n\nT = int(input())\nfor t in range(T):\n x, y = map(int, input().split())\n d = y-x\n print(how_many_times(d))"},{"alpha_fraction":0.4335154891014099,"alphanum_fraction":0.47358834743499756,"avg_line_length":31.352941513061523,"blob_id":"397751710974cc1a035a75880fd41afa22b71776","content_id":"3d34bf0f4ecb1fc3ad860cab2be87c63be96e74f","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":739,"license_type":"no_license","max_line_length":52,"num_lines":17,"path":"/알고리즘/온라인저지/2021/08/0822/색종이.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"T = int(input())\narr = [[0]*101 for _ in range(101)]\nfor tc in range(T):\n x1, y1 = map(int, input().split())\n for i in range(y1, y1+10): # 색종이 크기는 10\n for j in range(x1, x1+10): \n if arr[i][j]: # 값이 들어있으면\n continue # 컨티뉴\n else: # 아직 저장된 값이 없으면\n arr[i][j] = 1 # 1을 저장\n # 합집합은 or연산\n # True or로 넘어가기 때문에 값이 있으면 저장이 되지 않고\n # 합해지는 부분을 연산할 필요가 없어짐\narea = 0 # 면적\nfor ar in arr: # 저장된 배열을 돌면서\n area += sum(ar) # 각 줄을 더해서 면적에 저장\nprint(area) # 출력"},{"alpha_fraction":0.5136986374855042,"alphanum_fraction":0.5410959124565125,"avg_line_length":12.363636016845703,"blob_id":"ef1d321b927c51ee0dc7b30995ae4f71b7325630","content_id":"1c11a7e0bd4e2383ecfe5390cbe6dcbdfad0cc48","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":146,"license_type":"no_license","max_line_length":32,"num_lines":11,"path":"/알고리즘/온라인저지/2022/03/0314/조합.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N, M = map(int, input().split())\n\nresult = 1\n\nfor n in range(N, N-M, -1):\n result *= n\n\nfor m in range(1, M+1):\n result //= m\n\nprint(result)"},{"alpha_fraction":0.5,"alphanum_fraction":0.5148147940635681,"avg_line_length":17.066667556762695,"blob_id":"2f145f5581c9b7a1b73059cab2f2b3412db626f3","content_id":"59ed8cb888a97a936ce7dc7a1fe0a28ab9a2d904","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":270,"license_type":"no_license","max_line_length":29,"num_lines":15,"path":"/알고리즘/온라인저지/2022/05/0519/카드.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"card = dict()\nfor n in range(int(input())):\n tmp = int(input())\n try:\n card[tmp] += 1\n except:\n card[tmp] = 1\nnum = sorted(list(card))\nmaxx = 0\nresult = 0\nfor n in num:\n if card[n] > maxx:\n maxx = card[n]\n result = n\nprint(result)"},{"alpha_fraction":0.569553792476654,"alphanum_fraction":0.5774278044700623,"avg_line_length":18.100000381469727,"blob_id":"248ba5581730d62acece3d2deb71420699e1603f","content_id":"0e191f45b800d3949d0db6250dacb4f22f90af51","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":381,"license_type":"no_license","max_line_length":51,"num_lines":20,"path":"/알고리즘/온라인저지/2022/11/1127/블로그.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\n\nN, X = map(int, input().rstrip().split())\nvisitors = list(map(int, input().rstrip().split()))\n\ntmp = sum(visitors[:X])\nmaxx = tmp\ncnt = 1\n\nfor i in range(X, N):\n tmp -= visitors[i-X]\n tmp += visitors[i]\n if maxx < tmp:\n maxx, cnt = tmp, 1\n elif maxx == tmp:\n cnt += 1\n\nprint('SAD') if not maxx else print(maxx, cnt)"},{"alpha_fraction":0.4729064106941223,"alphanum_fraction":0.5049260854721069,"avg_line_length":17.5,"blob_id":"a5d77773fcfb2a0df9be510881a2b7bd3896b6bd","content_id":"038020313039b0ebaa3c9af6ff069b19a31dab3b","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":406,"license_type":"no_license","max_line_length":49,"num_lines":22,"path":"/알고리즘/온라인저지/2021/08/0830/바이러스.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ndef dfs(v):\n visited[v] = 1\n global cnt\n cnt += 1\n for w in range(1, V+1):\n if G[v][w] == 1 and not visited[w]:\n dfs(w)\n\nV = int(sys.stdin.readline())\nE = int(sys.stdin.readline())\n\nG = [[0] * (V+1) for _ in range(V+1)]\nfor _ in range(E):\n u, v = map(int, sys.stdin.readline().split())\n G[u][v] = G[v][u] = 1\n\nvisited = [0] * (V+1)\ncnt = -1\ndfs(1)\nprint(cnt)"},{"alpha_fraction":0.4962962865829468,"alphanum_fraction":0.5135802626609802,"avg_line_length":21.55555534362793,"blob_id":"aa184790deb9b4bca496bbb1a2ac7c1a84f64a46","content_id":"5d02e94eabab7b19a291b06c03caa754d4fa16ed","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":405,"license_type":"no_license","max_line_length":39,"num_lines":18,"path":"/알고리즘/온라인저지/2022/07/0726/카약과 강풍.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N, S, R = map(int, input().split())\ncrack = list(map(int, input().split()))\nspare = list(map(int, input().split()))\nK = [True] * N # kayak\nfor c in crack:\n K[c-1] = False\nfor s in spare:\n try:\n if not K[s-1]: K[s-1] = True\n elif not K[s-2]: K[s-2] = True\n elif not K[s]: K[s] = True\n except:\n pass\nresult = 0\nfor k in K:\n if not k:\n result += 1\nprint(result)"},{"alpha_fraction":0.5233160853385925,"alphanum_fraction":0.5492228269577026,"avg_line_length":23.25,"blob_id":"0405622770cca534e75e4565e5793810a645ecb2","content_id":"cacdc4d478ed2d82da0bd4ac5e409418f06a6399","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":193,"license_type":"no_license","max_line_length":36,"num_lines":8,"path":"/알고리즘/온라인저지/2023/04/0407/친구 친구.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N, M = map(int, input().split())\nfriends = [0]*(N+1)\nfor m in range(M):\n A, B = map(int, input().split())\n friends[A] += 1\n friends[B] += 1\nfor friend in friends[1:]:\n print(friend)"},{"alpha_fraction":0.6222222447395325,"alphanum_fraction":0.6222222447395325,"avg_line_length":21.75,"blob_id":"95bc9a368540f8dbfdf69f4d0cd780927787deed","content_id":"059d3176a16002d48e839d17cbb2254ecd850f2b","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":90,"license_type":"no_license","max_line_length":32,"num_lines":4,"path":"/알고리즘/온라인저지/2022/03/0308/計算 (Calculation).py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"A, B = map(int, input().split())\nresult = [A+B, A-B]\nprint(max(result))\nprint(min(result))"},{"alpha_fraction":0.4357541799545288,"alphanum_fraction":0.46927374601364136,"avg_line_length":19,"blob_id":"da118e15c58a35e688249db65f79b7503af501c0","content_id":"dfe52a50185ea1dd87e3cb19d65da228420e1272","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":179,"license_type":"no_license","max_line_length":36,"num_lines":9,"path":"/알고리즘/온라인저지/2022/03/0326/경기 결과.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = int(input())\nresult = [0, 0]\nfor n in range(N):\n A, B = map(int, input().split())\n if A > B:\n result[0] += 1\n elif B > A:\n result[1] += 1\nprint(*result)"},{"alpha_fraction":0.3196721374988556,"alphanum_fraction":0.33811476826667786,"avg_line_length":24.05128288269043,"blob_id":"df2adfc59d6279c57db076d78cbb8c134a8d52b5","content_id":"7e085a366050e2dbd6ab58e3c61a8a0440f8c2a8","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":976,"license_type":"no_license","max_line_length":73,"num_lines":39,"path":"/알고리즘/온라인저지/2021/12/1216/유기농 배추.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"from collections import deque\n\nT = int(input())\n\ndx = [-1, 1, 0, 0]\ndy = [0, 0, -1, 1]\n\nfor tc in range(T):\n M, N, K = map(int, input().split())\n\n field = [[0] * M for _ in range(N)]\n\n for k in range(K):\n x, y = map(int, input().split())\n field[y][x] = 1\n \n worm = deque()\n cnt = 0\n\n for i in range(N):\n for j in range(M):\n if field[i][j]:\n worm.append((i, j))\n cnt += 1\n while worm:\n tmp = worm.popleft()\n y = tmp[0]\n x = tmp[1]\n if field[y][x]:\n field[y][x] = 0\n else:\n continue\n for k in range(4):\n nx = x + dx[k]\n ny = y + dy[k]\n if 0 <= nx < M and 0 <= ny < N and field[ny][nx]:\n worm.append((ny, nx))\n\n print(cnt)"},{"alpha_fraction":0.3085106313228607,"alphanum_fraction":0.3297872245311737,"avg_line_length":17.799999237060547,"blob_id":"4ff5d3dba6c60429d2c2323ec5be6b705a2432d2","content_id":"ab1b6f613269ad0d268a17de920e8ef6520cd742","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":282,"license_type":"no_license","max_line_length":30,"num_lines":15,"path":"/알고리즘/온라인저지/2021/12/1213/화성 수학.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"T = int(input())\n\nfor tc in range(T):\n a = input().split()\n b = float(a[0])\n\n for i in range(1, len(a)):\n if a[i] == '@':\n b *= 3\n elif a[i] == '%':\n b += 5\n elif a[i] == '#':\n b -= 7\n \n print('{:.2f}'.format(b))\n"},{"alpha_fraction":0.41516244411468506,"alphanum_fraction":0.4332129955291748,"avg_line_length":22.16666603088379,"blob_id":"251080aecbb4122b51c51c8418e11f1e887b0fb0","content_id":"fdab24c692535f786919a4c7cc4f53816dfdef9f","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":277,"license_type":"no_license","max_line_length":37,"num_lines":12,"path":"/알고리즘/온라인저지/2023/01/0113/중복을 없애자.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"while True:\n tmp = input()\n if tmp == '0': break\n tmp = list(map(int, tmp.split()))\n N, arr = tmp[0], tmp[1:]\n last = arr[0]\n print(last, end=' ')\n for a in arr[1:]:\n if a != last:\n last = a\n print(last, end=' ')\n print('$')"},{"alpha_fraction":0.5337837934494019,"alphanum_fraction":0.6036036014556885,"avg_line_length":20.14285659790039,"blob_id":"2b6965ac4e179e9e9303f4034351e1d2b6da808c","content_id":"3e693c441e72d8b894f1d01f7fa1b4c18a476895","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":444,"license_type":"no_license","max_line_length":45,"num_lines":21,"path":"/알고리즘/온라인저지/2021/12/1213/주사위 세개.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"a = list(map(int, input().split()))\n\ndice_num_count = [0 for _ in range(6)]\n\nfor i in a:\n dice_num_count[i-1] += 1\n\nsame_or_max = 0\nresult = 0\n\nif 3 in dice_num_count:\n same_or_max = dice_num_count.index(3) + 1\n result = 10000 + same_or_max * 1000\nelif 2 in dice_num_count:\n same_or_max = dice_num_count.index(2) + 1\n result = 1000 + same_or_max * 100\nelse:\n same_or_max = max(a)\n result = same_or_max * 100\n\nprint(result)\n"},{"alpha_fraction":0.5522388219833374,"alphanum_fraction":0.5671641826629639,"avg_line_length":18.285715103149414,"blob_id":"4fbf180120aed0adb4f422f6ca1e9b774cb487dc","content_id":"bab83934a4ed66fcd62cc3a56a40e16067f43293","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":134,"license_type":"no_license","max_line_length":38,"num_lines":7,"path":"/알고리즘/온라인저지/2022/03/0320/Identifying tea.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"T = int(input())\nteas = list(map(int, input().split()))\nresult = 0\nfor tea in teas:\n if T == tea:\n result += 1\nprint(result)"},{"alpha_fraction":0.3494318127632141,"alphanum_fraction":0.3920454680919647,"avg_line_length":31.090909957885742,"blob_id":"ccd8ef9cedfae2ac5436e5805ca534d1e973415c","content_id":"7ca0f0131c32920e94ef35766056dc67218b9726","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":352,"license_type":"no_license","max_line_length":44,"num_lines":11,"path":"/알고리즘/온라인저지/2022/05/0509/수학적 호기심.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"for t in range(int(input())):\n N, M = map(int, input().split())\n result = 0\n for i in range(1, N-1):\n for j in range(i+1, N):\n # print((i**2 + j**2 + M)/(i*j))\n case1 = (i**2 + j**2 + M)/(i*j)\n case2 = (i**2 + j**2 + M)//(i*j)\n if case1 == case2:\n result += 1\n print(result)"},{"alpha_fraction":0.6030769348144531,"alphanum_fraction":0.6123076677322388,"avg_line_length":22.285715103149414,"blob_id":"759fb04e5626169f42c59e41c20fb3dd7661eb3c","content_id":"2275b27bf4143e1a2eb6fa797b6e4800f365c77a","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":325,"license_type":"no_license","max_line_length":50,"num_lines":14,"path":"/알고리즘/온라인저지/2022/09/0927/숫자 카드 2.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\n\ninput().rstrip()\ncards = list(map(int, input().rstrip().split()))\ncount = dict()\nfor card in cards:\n try: count[card] += 1\n except: count[card] = 1\ninput().rstrip()\nfor i in list(map(int, input().rstrip().split())):\n try: print(count[i], end=' ')\n except: print(0, end=' ')"},{"alpha_fraction":0.4481012523174286,"alphanum_fraction":0.4911392331123352,"avg_line_length":22.294116973876953,"blob_id":"91b0453cf990e3e3f2b1fe56ebfbb62484cd6929","content_id":"e94f931a39991219afe02f4e5837dfb7472d77ea","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":403,"license_type":"no_license","max_line_length":45,"num_lines":17,"path":"/알고리즘/온라인저지/2022/12/1223/추론.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"def plus_or_multiply(A, B):\n if A == B: # 등차\n Q = nums[1]-nums[0]\n result = nums[-1]+Q\n else: # 등비\n Q = nums[1]//nums[0]\n result = nums[-1]*Q\n return result\n\nN = int(input())\nnums = [int(input()) for _ in range(N)]\nA, B = 0, 0\nif N == 3:\n A, B = nums[0]+nums[-1], nums[1]*2\nelse:\n A, B = nums[0]+nums[-1], nums[1]+nums[-2]\nprint(plus_or_multiply(A, B))"},{"alpha_fraction":0.4821428656578064,"alphanum_fraction":0.5,"avg_line_length":27.5,"blob_id":"5c8bd0d07688a36f8ecb58abe8e6a776e95cd13f","content_id":"ac82ca538c24ebbf6292e8741ff37b0402f35508","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":56,"license_type":"no_license","max_line_length":35,"num_lines":2,"path":"/알고리즘/온라인저지/2022/04/0424/폰 노이만과 파리.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"S, T, D = map(int, input().split())\nprint((D//S//2) * T)"},{"alpha_fraction":0.4094955623149872,"alphanum_fraction":0.4540059268474579,"avg_line_length":16.789474487304688,"blob_id":"9c5d06eb0c1943cd39e4e18b4f70b58959cb597a","content_id":"f2ec5b66bf341f4649c2d791ebbfbcd484fd84ff","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":337,"license_type":"no_license","max_line_length":40,"num_lines":19,"path":"/알고리즘/온라인저지/2022/03/0303/알고리즘 수업 - 알고리즘의 수행 시간 6.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"n = int(input())\n\n# result = 0\n# dim = 3\n\n# for i in range(1, n-1):\n# for j in range(i+1, n):\n# for k in range(j+1, n+1): \n# result += 1\n# print(i, j, k)\n\nresult = 0\ndim = 3\n\nfor i in range(1, n-1):\n # result += sum(list(range(1, i+1)))\n result += i * (n-i-1)\n\nprint(result, f'\\n{dim}', sep='')"},{"alpha_fraction":0.4348958432674408,"alphanum_fraction":0.4479166567325592,"avg_line_length":13.259259223937988,"blob_id":"8b7b4b18f4032998f59adf6c1e580f452fc3f498","content_id":"f658042b74e1a8f255b8ed6e533455fbc945b3c2","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":384,"license_type":"no_license","max_line_length":37,"num_lines":27,"path":"/알고리즘/온라인저지/2022/02/0207/오르막길.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = int(input())\n\narr = list(map(int, input().split()))\n\nstart = arr[0]\n\nup = True\n\nmaxx = 0\n\nfor i in range(1, N):\n if arr[i] <= arr[i-1]:\n up = False\n tmp = arr[i-1] - start\n start = arr[i]\n \n if tmp > maxx:\n maxx = tmp\n\n else:\n up = True\n\nif up:\n if arr[i]-start > maxx:\n maxx = arr[i]-start\n \nprint(maxx)"},{"alpha_fraction":0.49643704295158386,"alphanum_fraction":0.5344418287277222,"avg_line_length":24.545454025268555,"blob_id":"134846b54d424bd59d3f64a5536af70262f2ebc3","content_id":"b149304ffa5aef723d5f145c149da59900d4f02a","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1178,"license_type":"no_license","max_line_length":70,"num_lines":33,"path":"/알고리즘/온라인저지/2022/02/0225/마인크래프트.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys # 주어진 시간이 적은 문제\n# sys.stdin.readline()과 PyPy3을 사용\n\nN, M, B = map(int, sys.stdin.readline().split())\n\narr = [list(map(int, sys.stdin.readline().split())) for _ in range(N)]\n\ntime, height = 9223372036854775807, 0 # 가상의 최대시간, 높이\n\nfor h in range(257): # 브루트포스, 모든 높이에 대한 소요시간과 높이 계산\n # 동일 시간인 경우 더 높은 높이를 출력할 것이므로 \n # 높이는 0에서 256으로 진행\n\n bot = top = 0 # 변수 초기화\n\n # 매 높이 h에 대하여, 모든 배열 순회\n for i in range(N):\n for j in range(M):\n if arr[i][j] < h: # 블럭을 채워야하면\n bot += h-arr[i][j] # bot에 추가\n else: # 블럭을 깎아야하면\n top += arr[i][j]-h # top에 추가\n\n if bot > top + B: # 가진블럭 + 깎은블럭으로도 다 채우지 못하면\n continue # 지나가고\n\n t = bot + top*2 # 걸리는 시간은 채우기1초 깎기2초를 총 더한 시간\n\n if t <= time:\n time = t # 최소시간 갱신\n height = h # 최대높이 갱신\n\nprint(time, height) # 출력"},{"alpha_fraction":0.5333333611488342,"alphanum_fraction":0.5696969628334045,"avg_line_length":26.66666603088379,"blob_id":"e8ee647a1a00164d47558a516edd1dec4e7ea06d","content_id":"1d775d2d67e335ffa60c0be74027590b1fa9ac68","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":165,"license_type":"no_license","max_line_length":33,"num_lines":6,"path":"/알고리즘/온라인저지/2023/06/0606/Fence Painting.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"A, B = map(int, input().split())\nC, D = map(int, input().split())\nwall = [0]*101\nfor i in range(A, B): wall[i] = 1\nfor i in range(C, D): wall[i] = 1\nprint(sum(wall))"},{"alpha_fraction":0.29209622740745544,"alphanum_fraction":0.3161512017250061,"avg_line_length":19.85714340209961,"blob_id":"475d7aff513dc9ddfd9772683a4febd0d1ce7427","content_id":"e3eab673f3146b5ac2746c855c2c24f281e7201f","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":291,"license_type":"no_license","max_line_length":27,"num_lines":14,"path":"/알고리즘/온라인저지/2022/03/0329/집 주소.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"while True:\n N = list(input())\n if N == ['0']:\n break\n else:\n result = 1\n for n in N:\n if n == '1':\n result += 3\n elif n == '0':\n result += 5\n else:\n result += 4\n print(result)"},{"alpha_fraction":0.5138888955116272,"alphanum_fraction":0.5416666865348816,"avg_line_length":17.25,"blob_id":"8792bac9a564e78f090d21bac5de4cc6e676d3d6","content_id":"822eb4358aa1c85c2a915318706ee3b67efb5ef9","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":72,"license_type":"no_license","max_line_length":31,"num_lines":4,"path":"/알고리즘/SWEA/LEARN/Course/1. Programming Beginner/파이썬 프로그래밍 기초(2)/42차시 4. 문자열 - 연습문제 7.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"tmp = input()\n\nfor i in range(0, len(tmp), 2):\n print(tmp[i], end='')"},{"alpha_fraction":0.4774305522441864,"alphanum_fraction":0.49884259700775146,"avg_line_length":25.196969985961914,"blob_id":"3f5af3f94d5139142baf97e9d01655e9d2294b60","content_id":"c4df36605e424a20b4ca08134b93bef5a9ed3abd","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":2024,"license_type":"no_license","max_line_length":66,"num_lines":66,"path":"/알고리즘/[템플릿]/BFS/치즈 업그레이드.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\nfrom collections import deque\n\ninput = sys.stdin.readline\ndy, dx = [-1, 1, 0, 0], [0, 0, -1, 1]\n\ndef melt_check():\n global time\n melt = True\n for i in range(N):\n for j in range(M):\n if arr[i][j]:\n melt = False\n if not melt: time += 1\n return melt\n\ndef delta_move(y, x):\n for i in range(4):\n ny, nx = y+dy[i], x+dx[i]\n if 0<=ny<N and 0<=nx<M and not visited[ny][nx]:\n if arr[ny][nx]:\n cheese_Q.append((ny, nx))\n visited[ny][nx] = 2 # 방문 배열에 2는 치즈\n # 치즈를 녹일 때 주위에 1(공기)이 2개 이상 있으면 녹일 것\n else: \n Q.append((ny, nx))\n visited[ny][nx] = 1 # 방문 배열에 1은 공기\n\ndef melt_cheese(y, x):\n tmp = 0\n for i in range(4):\n ny, nx = y+dy[i], x+dx[i]\n if visited[ny][nx] == 1: tmp += 1\n if tmp >= 2:\n melt_Q.append((y, x))\n else: visited[y][x] = 0\n # 치즈 배열의 특성상 반드시 두 면 이상 공기와 접촉하는 치즈가 있고\n # 녹은 치즈, 즉 새로운 탐색점은, 매 while문마다 반드시 나온다\n\nN, M = map(int, input().rstrip().split())\narr = [list(map(int, input().rstrip().split())) for _ in range(N)]\nQ, cheese_Q, melt_Q = deque(), deque(), deque()\nvisited = [[0]*M for _ in range(N)]\nQ.append((0, 0))\nvisited[0][0] = 1\ntime = 0\nwhile True:\n if melt_check(): print(time); break\n while Q: # 공기를 탐색하면서\n y, x = Q.popleft()\n delta_move(y, x) # 치즈를 찾자\n while cheese_Q: # 치즈들 중에서\n y, x = cheese_Q.popleft()\n melt_cheese(y, x) # 녹일 수 있는 치즈를 찾자\n while melt_Q: # 녹일 수 있는 치즈들을\n y, x = melt_Q.popleft()\n arr[y][x] = 0 # 녹이자\n visited[y][x] = 1\n Q.append((y, x))\n \n\"\"\"\n치즈가 녹은 자리는 공기가 된다\n녹이고 Q에 추가하기\n\"\"\"\n\n# https://www.acmicpc.net/problem/2638"},{"alpha_fraction":0.6451612710952759,"alphanum_fraction":0.6451612710952759,"avg_line_length":23.22222137451172,"blob_id":"dff9cf1226079b0c6fd26d73b7450656c02d5192","content_id":"4c134be02501a7be8383fc9dd8b36565998b3b1f","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":279,"license_type":"no_license","max_line_length":63,"num_lines":9,"path":"/알고리즘/[템플릿]/진법 변환/진법 변환 2.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import string\n\nN, B = map(int, input().split())\ntmp = string.digits + string.ascii_uppercase # 자릿수를 담은 문자열\nresult = ''\nwhile N:\n result = tmp[N%B] + result # B진법이므로 B로 나눈 나머지번째 문자를 계속 추가한다\n N //= B\nprint(result)"},{"alpha_fraction":0.41310539841651917,"alphanum_fraction":0.5384615659713745,"avg_line_length":17.421052932739258,"blob_id":"b4b42aa6602a741971957249b50e815fb0eaaf93","content_id":"8f8d39dc6115fdcbed96e262bb7447d74cbb1f97","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":561,"license_type":"no_license","max_line_length":41,"num_lines":19,"path":"/알고리즘/온라인저지/2021/08/0806/알람 시계.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"\"\"\"\n구하고자 하는 건 45분 전\n분에 15분을 더하고\n시간에 한시간을 빼고\n60분을 넘기면 60을 빼주고\n24시간을 넘기면 24를 빼주고\n\"\"\"\n\nH, M = map(int, input().split()) # 입력 받아서\nM += 15 # 15분 더하고\nH -= 1 # 1시간 빼고\nif M >= 60: # 60분을 넘기면\n M -= 60 # 60빼주고 0분부터\n H += 1 # 1시간 더하고\nif H >= 24: # 24시간 넘기면 0시부터\n H -= 24\nif H == -1: # 계산을 마친 시간이 23시면\n H = 23 # 계산값인 -1을 23으로 덮어 씌우기\nprint(H, M) # 출력\n\n"},{"alpha_fraction":0.4157303273677826,"alphanum_fraction":0.483146071434021,"avg_line_length":29,"blob_id":"b9e666a91d43b43f0a5bd75f65704f7fb84ea42f","content_id":"9e0cecd9cad8f0eb13dfa12b175911b4f9acff8f","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":89,"license_type":"no_license","max_line_length":40,"num_lines":3,"path":"/알고리즘/온라인저지/2022/05/0502/꼬리를 무는 숫자 나열.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"A, B = map(int, input().split())\nC, D = A-1, B-1\nprint(abs(C%4 - D%4) + abs(C//4 - D//4))"},{"alpha_fraction":0.5511363744735718,"alphanum_fraction":0.5994318127632141,"avg_line_length":28.375,"blob_id":"2627af9b9bc41cb439e32069057b8b8f9c2ccb95","content_id":"32c9ba503606df4f8788e4e309c64e522640511c","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1074,"license_type":"no_license","max_line_length":67,"num_lines":24,"path":"/알고리즘/온라인저지/2022/10/1004/동전 1.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\n\nN, K = map(int, input().rstrip().split())\ncoins = [int(input().rstrip()) for _ in range(N)]\ndp = [0]*(K+1)\ndp[0] = 1 # 0원을 지불하는 방법은, 아무것도 내지 않는 경우 딱 하나\nfor coin in coins: # 각각 동전 종류에 대해\n for i in range(1, K+1): # 1원을 내는 경우부터 출발\n if i-coin>=0: # 음수의 금액을 낸 경우는 존재하지 않으므로, 0원을 낸 경우 이상부터 확인\n dp[i] += dp[i-coin] # 해당 금액의 동전을 내기 전의 경우의 수 만큼을 더해준다\nprint(dp[K])\n\n\"\"\"\n예제는 동전의 종류가 1 2 5 이므로 1원동전 일 때, dp가 1, 1, 1, ... 이 되기 때문에 헷갈릴 수 있으나\n만약 2 5 7과 같은 종류였다면\nfor coin in coins 1회차에 dp는 \n1, 0, 1, 0, 1, 0, 1 ... 과 같이 저장되었을 것이다\n계산된 값(dp[i])를 실시간으로 반영하면서 line 10의 for문을 돌기 때문에\ndp[i] += dp[i-coin] 만으로도 정답코드가 될 수 있다\n\"\"\"\n\n# https://www.acmicpc.net/problem/2293"},{"alpha_fraction":0.5011600852012634,"alphanum_fraction":0.5127609968185425,"avg_line_length":29.821428298950195,"blob_id":"cbf3a204b5a3f9bf35bc1a275a5ec9e947d3e22b","content_id":"8aa1af75b83181076c166cafdc62fb666c1cbb10","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1122,"license_type":"no_license","max_line_length":57,"num_lines":28,"path":"/알고리즘/온라인저지/2022/04/0430/프린터 큐.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\nfrom collections import deque\n\ndef input():\n return sys.stdin.readline()\n\nfor t in range(int(input())):\n result = 1 # 인쇄 순서 초기화\n N, M = map(int, input().split())\n tmp = list(map(int, input().split())) # 문서 중요도 입력\n docs = deque() # popleft() 사용할 것\n i = 0 # 문서의 순서\n for tm in tmp:\n docs.append((tm, i)) # 현재 문서의 (중요도, 순서) 를 담은 리스트\n i += 1\n # print(docs) # 디버깅\n while docs: # \n tmp = [] # 문서의 중요도들만을 담을 리스트\n for i in range(len(docs)):\n tmp.append(docs[i][0])\n if docs[0][0] != max(tmp): # 가장 중요도가 높은 문서가 아니라면\n docs.append(docs.popleft()) # 해당 문서를 가장 뒤로 이동\n else: # 가장 중요도가 높은 문서라면\n if M == docs[0][1]: # 구하고자 하는 인쇄순서의 문서라면\n break # 종료하고\n docs.popleft() # 인쇄\n result += 1 # 인쇄순서 +1\n print(result) # 현재 인쇄순서 번호를 출력"},{"alpha_fraction":0.41818180680274963,"alphanum_fraction":0.4561983346939087,"avg_line_length":16.257143020629883,"blob_id":"508d18ffc92b103f069b90ad4d80b2c31603390c","content_id":"a78d07f40fc64425b5c0d96e38579f3739e8a212","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":605,"license_type":"no_license","max_line_length":56,"num_lines":35,"path":"/알고리즘/온라인저지/2021/12/1216/미로 탐색.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"from collections import deque\n\nN, M = map(int, input().split())\nmaze = [list(map(int, input())) for _ in range(N)]\n\ndx = [-1, 1, 0, 0]\ndy = [0, 0, -1, 1]\n\nroutes = deque()\n\nroutes.append((0, 0, 0))\n\nwhile routes:\n tmp = routes.popleft()\n y = tmp[0]\n x = tmp[1]\n cnt = tmp[2]\n \n if y == N-1 and x == M-1:\n print(cnt + 1)\n break\n\n if maze[y][x] == 0:\n continue\n\n maze[y][x] = 0\n\n cnt += 1\n\n for i in range(4):\n ny = y + dy[i]\n nx = x + dx[i]\n\n if 0 <= ny < N and 0 <= nx < M and maze[ny][nx]:\n routes.append((ny, nx, cnt))\n\n"},{"alpha_fraction":0.45255473256111145,"alphanum_fraction":0.48175182938575745,"avg_line_length":14.333333015441895,"blob_id":"f007621dd739effddcf425885143f52566fd86ab","content_id":"c8e8246694df9a3e8bbf4bd3ffa08b73d536bafb","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":137,"license_type":"no_license","max_line_length":21,"num_lines":9,"path":"/알고리즘/온라인저지/2022/05/0517/지속.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = input()\nresult = 0\nwhile len(N) > 1:\n tmp = 1\n for n in N:\n tmp *= int(n)\n N = str(tmp)\n result += 1\nprint(result)"},{"alpha_fraction":0.417391300201416,"alphanum_fraction":0.426086962223053,"avg_line_length":18.33333396911621,"blob_id":"76820257f4dfa2cbf3850f3e8c84abaf0884dfd7","content_id":"ab80de87cf6144c80ea7de0a93e23f42b78e5afd","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":115,"license_type":"no_license","max_line_length":40,"num_lines":6,"path":"/알고리즘/온라인저지/2022/08/0827/Shares.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"while True:\n try:\n N, S = map(int, input().split())\n N += 1\n print(S//N)\n except: exit()"},{"alpha_fraction":0.36915886402130127,"alphanum_fraction":0.4579439163208008,"avg_line_length":27.566667556762695,"blob_id":"cba2c47b9b09ca8fb1dc5e5d78700695801ee29c","content_id":"01cd0a77d818568e1f0410012619e3f1abe738ac","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1242,"license_type":"no_license","max_line_length":59,"num_lines":30,"path":"/알고리즘/온라인저지/2021/08/0813/ATM.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = int(input()) # 사람 수\nusers = list(map(int, input().split())) # 각자 ATM 이용에 걸리는 시간\n\"\"\"\n1 2 3 4 5 번째 사람이\n3 1 4 3 2 분이 걸린다 하면\n\n1 2 3 4 5 순으로 가면\n1번은 3분 걸리고\n2번은 3분걸린 1번에 얹어서 1분걸려서 총 4분\n3번은 앞에서 걸린 4분 + 본인 4분 = 8분\n4번은 앞사람 8분 + 본인 3분\n결국 앞에서 걸린 시간들이 길수록 뒤에도 늦어진다는거\n용무가 빨리 끝나는 사람 먼저 하는게 핵심\n걸리는 시간이 짧은순으로 정렬하고 볼일 보게 하는 것\n1 = 1\n1+2 = 3\n1+2+3 = 6\n1+2+3+3 = 9\n1+2+3+3+4 = 13\n1+3+6+9+13 = 32\n1 (1+2) (1+2+3) (1+2+3+3) (1+2+3+3+4)\n\"\"\"\nusers.sort() # 걸리는 시간들을 정렬\nresult = 0 # 결과값을 초기화\nfor n in range(N): # 사람수만큼 반복\n wait_time = 0 # 본인의 대기시간\n for j in range(n+1): # 앞사람들+본인 시간만큼 반복\n wait_time += users[j] # 대기+사용시간 구해서\n result += wait_time # 다 집어넣고\nprint(result) # 출력"},{"alpha_fraction":0.42975205183029175,"alphanum_fraction":0.4793388545513153,"avg_line_length":23.399999618530273,"blob_id":"065c00350c9b4cb1db77bd209e2f9beb09307995","content_id":"9c465cc04a6ff091fdc5bfd38bbb5001a7dd8c9e","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":121,"license_type":"no_license","max_line_length":32,"num_lines":5,"path":"/알고리즘/온라인저지/2022/12/1208/A나누기B - 2.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"A, B = map(int, input().split())\nprint(f'{A//B}.', end='')\nfor _ in range(1001):\n A = (A%B)*10\n print(A//B, end='')"},{"alpha_fraction":0.5166666507720947,"alphanum_fraction":0.5366666913032532,"avg_line_length":29.100000381469727,"blob_id":"c8430d9db43435a971d86ffb2b18d07773e6c57e","content_id":"e39b10aeae30802284a37019b6b26d233003c667","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":300,"license_type":"no_license","max_line_length":49,"num_lines":10,"path":"/알고리즘/온라인저지/2022/07/0731/기타줄.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N, M = map(int, input().split())\nS_min = P_min = 1e9 # set min, piece min\nfor m in range(M):\n S, P = map(int, input().split()) # set, piece\n if S < S_min: S_min = S\n if P < P_min: P_min = P\n if P*6 < S_min: S_min = P*6\nresult = N//6 * S_min\nresult += min(N%6 * P_min, S_min)\nprint(result)"},{"alpha_fraction":0.4893617033958435,"alphanum_fraction":0.5319148898124695,"avg_line_length":22.66666603088379,"blob_id":"3b50934dea7449c34c89b0d094d260ab1a462aef","content_id":"541df3e0a30eed520471d3529c261ed2df129a56","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":141,"license_type":"no_license","max_line_length":38,"num_lines":6,"path":"/알고리즘/온라인저지/2023/04/0411/ZOAC 4.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"H, W, N, M = map(int, input().split())\nresult = 0\nfor i in range(0, H, 1+N):\n for j in range(0, W, 1+M):\n result += 1\nprint(result)"},{"alpha_fraction":0.5049999952316284,"alphanum_fraction":0.5400000214576721,"avg_line_length":25.733333587646484,"blob_id":"c79d50d3e6ac5c7eaa7352f748699c1069cc093a","content_id":"39c6e3e10549a9dc8e1fad269e4aea21109a0a94","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":400,"license_type":"no_license","max_line_length":46,"num_lines":15,"path":"/알고리즘/온라인저지/2022/07/0731/수 찾기(재귀함수).py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"def binary(t, s, e): # target, start, end\n if s > e: return 0\n i = (s+e) // 2 # index\n if t == arr1[i]: return 1\n elif t < arr1[i]: return binary(t, s, i-1)\n elif t > arr1[i]: return binary(t, i+1, e)\n\nN = int(input())\narr1 = list(map(int, input().split()))\narr1.sort()\nM = int(input())\narr2 = list(map(int, input().split()))\nfor a in arr2:\n s, e = 0, N-1\n print(binary(a, s, e))"},{"alpha_fraction":0.40532544255256653,"alphanum_fraction":0.4289940893650055,"avg_line_length":20.1875,"blob_id":"0e17b301b3d8c3a2d0cdeb9b878ccfa20d33216f","content_id":"2aead024c4e8a4eab8f908f2cd3fff1180f09680","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":338,"license_type":"no_license","max_line_length":41,"num_lines":16,"path":"/알고리즘/온라인저지/2022/07/0704/반복.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"S = input()\nalphabet = [chr(i+97) for i in range(26)]\n# print(alphabet)\nresult = 0\nword = ''\ns = 0 # S index\nwhile True:\n result += 1\n for a in alphabet:\n if a == S[s]:\n word += a\n if word == S:\n print(result)\n exit()\n s += 1\n # print(result, word, s)"},{"alpha_fraction":0.3913043439388275,"alphanum_fraction":0.52173912525177,"avg_line_length":22.33333396911621,"blob_id":"e4e29cb33bbfdd75c644b62ff6fc30f8b551ee6b","content_id":"431dfd8828cc7c33898ef962f514d28a5a79e3f8","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":69,"license_type":"no_license","max_line_length":33,"num_lines":3,"path":"/알고리즘/온라인저지/2022/04/0418/수학은 체육과목 입니다 2.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = int(input())\nfinger = [2, 1, 2, 3, 4, 5, 4, 3]\nprint(finger[N%8])"},{"alpha_fraction":0.5177664756774902,"alphanum_fraction":0.6142131686210632,"avg_line_length":16.954545974731445,"blob_id":"fcd61c19e56c5cfef43e1661a35d062b4416afb9","content_id":"7cb84463704f7d999efb4317c887bda85caae2ad","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":506,"license_type":"no_license","max_line_length":45,"num_lines":22,"path":"/알고리즘/온라인저지/2022/10/1003/피보나치 수의 확장.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\nmod = int(1e9)\n\nN = int(input().rstrip())\na, b = 1, 1\nfor _ in range(abs(N)-2): a, b = b, (a+b)%mod\nif abs(N)%2 == 0 and N < 0: print(-1)\nelif N == 0: print(0)\nelse: print(1)\nprint(b if N != 0 else 0)\n\n\"\"\"\n문제를 잘 보자\n1,000,000,007로 나누는 문제가 많았다고 해서\n모든 문제들이 그런 것은 아니다\n1,000,000,000으로 나누면 되는걸로 \n문제 제대로 안읽고 몇분을 날린거냐..\n\"\"\"\n\n# https://www.acmicpc.net/problem/1788"},{"alpha_fraction":0.37172773480415344,"alphanum_fraction":0.39921465516090393,"avg_line_length":17.658536911010742,"blob_id":"e340b6f4c49aeea2871780825f7af9074cef35c7","content_id":"fed5d49d327fe124e15ad8be28c4c1643b408be6","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":764,"license_type":"no_license","max_line_length":31,"num_lines":41,"path":"/알고리즘/온라인저지/2021/09/0908/큐 2.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\ndef input():\n return sys.stdin.readline()\n\n\n\nN = int(input())\nq = [0] * N\npnt = 0\ncnt = 0\nback = 0\nfor n in range(N):\n order = input().split()\n if order[0] == 'push':\n q[back] = order[1]\n cnt += 1\n back += 1\n elif order[0] == 'pop':\n if cnt:\n print(q[pnt])\n pnt += 1\n cnt -= 1\n else:\n print(-1)\n elif order[0] == 'size':\n print(cnt)\n elif order[0] == 'empty':\n if cnt:\n print(0)\n else:\n print(1)\n elif order[0] == 'front':\n if cnt:\n print(q[pnt])\n else:\n print(-1)\n elif order[0] == 'back':\n if cnt:\n print(q[back-1])\n else:\n print(-1)"},{"alpha_fraction":0.4285714328289032,"alphanum_fraction":0.4444444477558136,"avg_line_length":18,"blob_id":"cafc1e157af92c1dfa09543d90da7dd236ab9fe4","content_id":"cd06dd07209eb7039f52d94eb25d08722ea5524d","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":189,"license_type":"no_license","max_line_length":37,"num_lines":10,"path":"/알고리즘/온라인저지/2022/02/0207/이진수.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"T = int(input())\n\nfor t in range(T):\n N = int(input())\n\n binary = (str(bin(N))[::-1])[:-2]\n\n for i in range(len(binary)):\n if binary[i] == '1':\n print(i, end=' ')"},{"alpha_fraction":0.5568862557411194,"alphanum_fraction":0.5868263244628906,"avg_line_length":32.599998474121094,"blob_id":"ea688bd50e5b123fa479f656e198dbb9129ef58f","content_id":"c49fc1d3f2971dc6dad6541ce95840b93d96734b","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":167,"license_type":"no_license","max_line_length":43,"num_lines":5,"path":"/알고리즘/온라인저지/2022/09/0905/빵.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"result = int(1e9)\nfor _ in range(int(input())):\n A, B = map(int, input().split())\n if A <= B: result = min(result, B)\nprint(-1 if result == int(1e9) else result)"},{"alpha_fraction":0.46084338426589966,"alphanum_fraction":0.5391566157341003,"avg_line_length":25.600000381469727,"blob_id":"ce1ce4897f4ab2d1f79e8a958dda10859bdbc402","content_id":"f62084d06d58623937723983c29c98cbc9a6d6ee","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":664,"license_type":"no_license","max_line_length":52,"num_lines":25,"path":"/알고리즘/온라인저지/2022/09/0922/주사위 네개.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\n\nresult = 0\nfor _ in range(int(input().rstrip())):\n dices = list(map(int, input().rstrip().split()))\n count_arr = [0]*11\n for dice in dices: count_arr[dice] += 1\n tmp = 0\n if 4 in count_arr:\n tmp += 50000 + count_arr.index(4)*5000\n elif 3 in count_arr:\n tmp += 10000 + count_arr.index(3)*1000\n elif count_arr.count(2) == 2:\n tmp += 2000\n for i in range(11):\n if count_arr[i] == 2: \n tmp += i*500\n elif 2 in count_arr:\n tmp += 1000 + count_arr.index(2)*100\n else: \n tmp += max(dices)*100\n result = max(result, tmp)\nprint(result)"},{"alpha_fraction":0.4392419159412384,"alphanum_fraction":0.47380155324935913,"avg_line_length":27.90322494506836,"blob_id":"911187260355f4ee89b7ee384980b118d7fc96eb","content_id":"46add3df2b8269ea76ee904ac864095dec6072ec","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1257,"license_type":"no_license","max_line_length":70,"num_lines":31,"path":"/알고리즘/온라인저지/2021/08/0816/소수&팰린드롬.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"\"\"\"\nN보다 큰 수를 하나씩 올려가면서\n소수들로 나눠서 나머지가 있으면서 소수본인과 같아지면 소수\n2~N까지의 소수들을 먼저 리스트에 추가\nN+1이 소수인지 보고 소수이면 리스트에 추가\n소수일 때 팰린드롬인지 보고\n팰린드롬이면 출력\n\"\"\"\nimport sys\nN = int(sys.stdin.readline())\n\n # 1003001까지 에라토스테네스의 체로 소수 전부 골라내기\nn = 1003003 # 조금 편법이긴 한데\n # 최대값이 1003001이라는 걸 계산해서 먼저 알아냄\na = [False,False] + [True]*(n-1)\nprimes=[]\nfor i in range(2,n+1):\n if a[i]:\n primes.append(i)\n for j in range(2*i, n+1, i):\n a[j] = False\n\nprime_palindrome = 0 # 소수팰린드롬 초기값\nwhile True:\n if str(N) == str(N)[::-1]: # 팰린드롬이고\n if N in primes: # 소수이면\n prime_palindrome = N # 소수팰린드롬\n if prime_palindrome: # 값을 찾았다면\n print(prime_palindrome) # 출력하고\n break # while문 종료\n N += 1 # 다음 숫자 탐색\n\n"},{"alpha_fraction":0.6336206793785095,"alphanum_fraction":0.6336206793785095,"avg_line_length":22.299999237060547,"blob_id":"edd95ff0cbaec0c87f19f1db698602338d2d9085","content_id":"e58b68684eb8a8014addfd54d13b2a4f2291b5ad","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":232,"license_type":"no_license","max_line_length":47,"num_lines":10,"path":"/알고리즘/온라인저지/2022/10/1001/비밀번호 찾기.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\n\nN, M = map(int, input().rstrip().split())\ndct = dict()\nfor n in range(N):\n site, password = input().rstrip().split()\n dct[site] = password\nfor m in range(M): print(dct[input().rstrip()])"},{"alpha_fraction":0.4627249240875244,"alphanum_fraction":0.519280195236206,"avg_line_length":15.956521987915039,"blob_id":"ead0b7748c82b654bfd944226466a9213ff92c62","content_id":"d9d50c1624f805552b25f2227184c45e102a9327","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":389,"license_type":"no_license","max_line_length":41,"num_lines":23,"path":"/알고리즘/온라인저지/2023/02/0219/8진수, 10진수, 16진수.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"def base_change(num, base):\n base_str = '0123456789abcdef'\n answer = 0\n power = 1\n\n for n in num[::-1]:\n answer += power*base_str.index(n)\n power *= base\n\n return answer\n\nX = input()\nresult = 0\n\nif X[0] == '0':\n if X[1] == 'x':\n result = base_change(X[2:], 16)\n else:\n result = base_change(X[1:], 8)\nelse:\n result = int(X)\n\nprint(result)"},{"alpha_fraction":0.5263158082962036,"alphanum_fraction":0.5413534045219421,"avg_line_length":12.399999618530273,"blob_id":"ef58bb5673ede891532858bcfb1d6a7c7ad68168","content_id":"1fc003976a6a36c30f10d9988ef4ab27d8e8b564","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":133,"license_type":"no_license","max_line_length":38,"num_lines":10,"path":"/알고리즘/온라인저지/2022/02/0201/10부제.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"D = int(input())\ncars = list(map(int, input().split()))\n\nresult = 0\n\nfor c in cars:\n if c == D:\n result += 1\n\nprint(result)"},{"alpha_fraction":0.34730538725852966,"alphanum_fraction":0.371257483959198,"avg_line_length":14.272727012634277,"blob_id":"fa1f12abc76025fb3a0ed5bf32cedfa84201022e","content_id":"74bf51922582febe29cb9bcbe4d7cf6f3c45bb02","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":167,"license_type":"no_license","max_line_length":39,"num_lines":11,"path":"/알고리즘/온라인저지/2022/02/0201/별 찍기 - 12.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = int(input())\n\ni = 0\n\nfor n in range(N):\n i += 1\n print(' ' * (N-i), '*' * i, sep='')\n\nfor n in range(N-1):\n i -= 1\n print(' ' * (N-i), '*' * i, sep='')"},{"alpha_fraction":0.3888888955116272,"alphanum_fraction":0.41777777671813965,"avg_line_length":12.636363983154297,"blob_id":"97790eb978067567390ed0b644fce974bda74e98","content_id":"b10183d82a7868d41708f850016ec836892b272f","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":450,"license_type":"no_license","max_line_length":49,"num_lines":33,"path":"/알고리즘/온라인저지/2022/02/0221/DNA.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N, M = map(int, input().split())\n\nDNAs = [input() for _ in range(N)]\n\ndictt = {\n 'A': 0,\n 'C': 1,\n 'G': 2,\n 'T': 3,\n 0: 'A',\n 1: 'C',\n 2: 'G',\n 3: 'T',\n}\n\nHD = 0\n\nfor i in range(M):\n\n table = [0] * 4\n\n for d in DNAs:\n table[dictt[d[i]]] += 1\n \n for j in range(4):\n if j != table.index(max(table)):\n HD += table[j]\n\n print(dictt[table.index(max(table))], end='')\n\nprint()\n\nprint(HD)\n"},{"alpha_fraction":0.4709418714046478,"alphanum_fraction":0.4809619188308716,"avg_line_length":30.25,"blob_id":"78f02a057dbe3aa4527c60b65603a00c70e262ea","content_id":"b748efd8c15369276385a8033a42915cb3265835","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":703,"license_type":"no_license","max_line_length":48,"num_lines":16,"path":"/알고리즘/온라인저지/2022/04/0417/그룹 단어 체커.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = int(input())\nresult = 0 # 그룹단어개수 초기화\nfor n in range(N):\n word = input()\n char = [] # 사용한 글자\n for i in range(len(word)): # 단어를 순회하면서\n if word[i] not in char: # 사용한 적 없는 글자라면\n char.append(word[i]) # 사용한 글자에 추가\n else: # 사용한 적 있는 글자라면\n if word[i] != word[i-1]: # 앞글자와 다르다면\n result -= 1 # 그룹단어가 아닙니다\n # 매 케이스 그룹단어라고 가정하고\n # 그룹단어가 아닐 경우 -1 하였음\n break\n result += 1 # 그룹단어입니다!\nprint(result) # 출력"},{"alpha_fraction":0.5698529481887817,"alphanum_fraction":0.5698529481887817,"avg_line_length":23.81818199157715,"blob_id":"876d6bf33832bd19f360b42f30f25c95e290c899","content_id":"b189945214f5559c580b9a37361816a49aa12c80","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":310,"license_type":"no_license","max_line_length":89,"num_lines":11,"path":"/알고리즘/온라인저지/2022/12/1211/한국이 그리울 땐 서버에 접속하지.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = int(input())\nstart, end = input().split('*')\nfor n in range(N):\n file = input()\n if len(start) + len(end) > len(file): print('NE')\n else: print('DA' if start == file[:len(start)] and end == file[-len(end):] else 'NE')\n\n\"\"\"\nabc*def\n와 같은 경우가 테스트케이스에 포함되어 있음\n\"\"\""},{"alpha_fraction":0.5026881694793701,"alphanum_fraction":0.5188171863555908,"avg_line_length":15,"blob_id":"a58fe6e007d81533895bf19a6e6781413c0fcce6","content_id":"f0ffff53cae92d33fede0762006c960a38867b88","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":478,"license_type":"no_license","max_line_length":38,"num_lines":23,"path":"/알고리즘/온라인저지/2022/01/0122/꿀 아르바이트.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N, M = map(int, input().split())\n\n# 급여 정보 입력\npays = list(map(int, input().split()))\n\ns = 0 # 창문의 시작과\ne = M-1 # 끝\n\n# 결과값과 윈도우값 초기화\nresult = window = sum(pays[s:e+1])\n\nwhile e < N-1: # 윈도우 이동을 종료하는 조건\n # 윈도우 한 칸 이동~~\n window -= pays[s]\n s += 1\n e += 1\n window += pays[e]\n\n # 결과값을 갱신할 지 여부\n if window > result:\n result = window\n\nprint(result)\n "},{"alpha_fraction":0.4035087823867798,"alphanum_fraction":0.46929824352264404,"avg_line_length":14.266666412353516,"blob_id":"731e667936da3095cd52640ed7179775635e5944","content_id":"7d06fc54a223537fc4fad4b9b2f1f203f5cd14bd","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":228,"license_type":"no_license","max_line_length":31,"num_lines":15,"path":"/알고리즘/온라인저지/2021/09/0906/막대기.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\ndef input():\n return sys.stdin.readline()\n\nX = int(input())\nbars = [64, 32, 16, 8, 4, 2, 1]\ni = 0\ncnt = 0\nwhile X != 0:\n if X >= bars[i]:\n X -= bars[i]\n cnt += 1\n else:\n i += 1\nprint(cnt)"},{"alpha_fraction":0.4975247383117676,"alphanum_fraction":0.5272276997566223,"avg_line_length":14.576923370361328,"blob_id":"dfc24364b20040990949308aa5852bae807e5b3f","content_id":"6c52305f42e3332124184c50bb3f70abbe46c86e","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":404,"license_type":"no_license","max_line_length":36,"num_lines":26,"path":"/알고리즘/온라인저지/2021/12/1230/트리의 부모 찾기.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\nsys.setrecursionlimit(99999)\n\ndef dfs(i):\n for n in nodes[i]:\n if not parent[n]:\n parent[n] = i\n dfs(n)\n\nN = int(input())\n\nnodes = [[] for _ in range(N+1)]\n\nparent = [0 for _ in range(N+1)]\nparent[1] = 'root'\n\nfor n in range(N-1):\n a, b = map(int, input().split())\n \n nodes[a].append(b)\n nodes[b].append(a)\n\ndfs(1)\n\nfor p in parent[2:]:\n print(p)"},{"alpha_fraction":0.5570470094680786,"alphanum_fraction":0.5682326555252075,"avg_line_length":23.88888931274414,"blob_id":"a276d39976f25f1f7cb350cfb30af811b9325068","content_id":"f7d805244a527024269a754658618f2f8ea33651","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":447,"license_type":"no_license","max_line_length":47,"num_lines":18,"path":"/알고리즘/온라인저지/2022/10/1019/풍선 터뜨리기.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\nfrom collections import deque\n\ninput = sys.stdin.readline\nN = int(input().rstrip())\narr = list(map(int, input().rstrip().split()))\nQ = deque()\nfor i in range(1, N+1): Q.append((i, arr[i-1]))\nwhile True:\n idx, move = Q.popleft()\n print(idx, end=' ')\n if not Q: break\n if move > 0:\n for i in range(move-1):\n Q.append(Q.popleft())\n else:\n for i in range(abs(move)):\n Q.appendleft(Q.pop())"},{"alpha_fraction":0.31734317541122437,"alphanum_fraction":0.361623615026474,"avg_line_length":37.85714340209961,"blob_id":"f5495119abf703f7eeee40c46ac4ad3355f0cd7f","content_id":"752ef90d9e2a0c5b37c24f7ab61da0c6f0e552f0","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":271,"license_type":"no_license","max_line_length":78,"num_lines":7,"path":"/알고리즘/온라인저지/2022/12/1217/완전 세제곱.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"for a in range(1, 101):\n for b in range(2, a+1):\n for c in range(b, a+1):\n for d in range(c, a+1):\n tmp = b**3 + c**3 + d**3\n if a**3 == tmp:\n print('Cube = {}, Triple = ({},{},{})'.format(a, b, c, d))"},{"alpha_fraction":0.443113774061203,"alphanum_fraction":0.455089807510376,"avg_line_length":17.66666603088379,"blob_id":"8df5848801d4997d502a09fcfbe63e978e101da0","content_id":"e5133575edc97696fb8e657da5e632335f7e3f2c","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":167,"license_type":"no_license","max_line_length":29,"num_lines":9,"path":"/알고리즘/온라인저지/2022/07/0711/모음의 개수.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"while True:\n sen = input()\n if sen == '#':\n break\n result = 0\n for s in sen:\n if s in 'aeiouAEIOU':\n result += 1\n print(result)"},{"alpha_fraction":0.5526315569877625,"alphanum_fraction":0.5614035129547119,"avg_line_length":37.33333206176758,"blob_id":"cf0097bc7b5b4c37e402f2f46887d6aaa5d959d7","content_id":"a20b7ae9ad16b39980cec2fcbcb4594378be7714","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":114,"license_type":"no_license","max_line_length":48,"num_lines":3,"path":"/알고리즘/온라인저지/2022/10/1012/팰린드롬.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"for i in range(int(input().rstrip())):\n word = input().lower()\n print('Yes' if word == word[::-1] else 'No')"},{"alpha_fraction":0.38063910603523254,"alphanum_fraction":0.4530075192451477,"avg_line_length":18.72222137451172,"blob_id":"0e25e4efe8363e8e2295cce1c75e8b2dfc442a42","content_id":"e32a895d2dd5d59808111c94f030a3faf7b8c1a4","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1064,"license_type":"no_license","max_line_length":48,"num_lines":54,"path":"/알고리즘/온라인저지/2022/03/0314/구간 합 구하기 5.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\ndef input():\n return sys.stdin.readline()\n\nN, M = map(int, input().split())\n\narr = []\n\ntmp = list(map(int, input().split()))\nnum = 0\nline = []\nfor t in tmp:\n num += t\n line.append(num)\narr.append(line)\n\nfor n in range(1, N):\n tmp = list(map(int, input().split()))\n num = 0\n line = []\n for t in tmp:\n num += t\n line.append(num)\n for i in range(len(line)):\n line[i] += arr[-1][i]\n arr.append(line)\n \n\nfor m in range(M):\n y1, x1, y2, x2 = (map(int, input().split()))\n e = v = h = s = 0\n if x1 > 1 and y1 > 1 and x2 > 1 and y2 > 1:\n e = arr[y2-1][x2-1]\n v = arr[y2-1][x1-2]\n h = arr[y1-2][x2-1]\n s = arr[y1-2][x1-2]\n elif x1 == 1 and y1 > 1:\n e = arr[y2-1][x2-1]\n h = arr[y1-2][x2-1]\n elif y1 == 1 and x1 > 1:\n e = arr[y2-1][x2-1]\n v = arr[y2-1][x1-2]\n elif x1 == 1 and y1 == 1:\n e = arr[y2-1][x2-1]\n\n result = e - v - h + s\n print(result)\n\n# for a in arr:\n# print(*a)\n\n\"\"\"\n2 2 3 4 = [3][4]-[3][1]-[1][4]+[1][1]\n\"\"\""},{"alpha_fraction":0.5176848769187927,"alphanum_fraction":0.5562701225280762,"avg_line_length":25,"blob_id":"e65f38fbd9690cfda2b93a5c0291c17f365b97e4","content_id":"6787ada15675778039e888a163929f50f3488770","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":311,"license_type":"no_license","max_line_length":44,"num_lines":12,"path":"/알고리즘/온라인저지/2022/09/0921/Strfry.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\n\nfor _ in range(int(input().rstrip())):\n A, B = input().rstrip().split()\n A_arr, B_arr = [0]*26, [0]*26\n for a in A: A_arr[ord(a)-97] += 1\n for b in B: B_arr[ord(b)-97] += 1\n result = 'Possible'\n if A_arr != B_arr: result = 'Impossible'\n print(result)"},{"alpha_fraction":0.53665691614151,"alphanum_fraction":0.5601173043251038,"avg_line_length":37,"blob_id":"77d11479a7e502a243fdf9787b7cbb5e533f8ad6","content_id":"cc266ae202472bc8d2cbe517a808d6ff8752833b","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":491,"license_type":"no_license","max_line_length":55,"num_lines":9,"path":"/알고리즘/온라인저지/2021/08/0803/알파벳 찾기.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"S = input() # 단어를 입력받아서\nresult = [-1] * 26 # 결과값을 -1 26개로 초기화해주고 \nfor s in S: # 알파벳을 순회하면서 \n for i in range(len(result)): # 그리고 result를 순회하면서\n if s == chr(97+i): # 단어의 해당 알파벳을 확인해서\n result[i] = S.index(s) # 알파벳의 index값의 등장위치를\n # result에 추가하고\nfor res in result: # result를 순회하면서\n print(res, end=' ') # 출력"},{"alpha_fraction":0.5102040767669678,"alphanum_fraction":0.5357142686843872,"avg_line_length":11.25,"blob_id":"ee5bed4c5eb165e57971ec392f5a481eb3a411d6","content_id":"04750b58f2dbd4988bedfd1475b1146ad8047f90","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":196,"license_type":"no_license","max_line_length":40,"num_lines":16,"path":"/알고리즘/온라인저지/2022/02/0220/피시방 알바.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = int(input())\n\nguests = list(map(int, input().split()))\n\npcs = [False] * 101\n\nreject = 0\n\nfor g in guests:\n if pcs[g]:\n reject += 1\n continue\n\n pcs[g] = True\n\nprint(reject)\n"},{"alpha_fraction":0.5555555820465088,"alphanum_fraction":0.5737977027893066,"avg_line_length":21.370370864868164,"blob_id":"3aa0b157feba509d13593ec442a3f0a1120708b7","content_id":"14dcec6eb299a8565b7ffedbb04050c1a52aec5b","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":603,"license_type":"no_license","max_line_length":47,"num_lines":27,"path":"/알고리즘/온라인저지/2022/09/0917/용돈 관리.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\n\ndef enough(money):\n money_in_hand, draw = money, 1\n for a in arr:\n if money_in_hand>=a: money_in_hand -= a\n else:\n draw += 1\n money_in_hand = money-a\n if draw<=M: return True\n return False\n\nN, M = map(int, input().rstrip().split())\narr = [int(input()) for _ in range(N)]\nresult = int(1e9)\nstart, end = max(arr), result\nwhile start<=end:\n mid = (start+end) // 2\n if enough(mid):\n result = min(result, mid)\n end = mid-1\n else: start = mid+1\nprint(result)\n\n# https://www.acmicpc.net/problem/6236"},{"alpha_fraction":0.6372548937797546,"alphanum_fraction":0.656862735748291,"avg_line_length":16.16666603088379,"blob_id":"ad9d2e348d26e99c2964776d3a330317e07fa066","content_id":"60fcdfff9c999eeac678da7683d124d08494e230","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":102,"license_type":"no_license","max_line_length":42,"num_lines":6,"path":"/알고리즘/온라인저지/2022/02/0211/오늘의 날짜는.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"from datetime import datetime\n\ndate = str(datetime.now())[:10].split('-')\n\nfor d in date:\n print(d)"},{"alpha_fraction":0.3861386179924011,"alphanum_fraction":0.4297029674053192,"avg_line_length":17.740739822387695,"blob_id":"237cd94ecbfcdb7acba5e8c22074618f024f8c98","content_id":"8b9b6782af1a759626ac40a8d4784bc4dab41ec3","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":505,"license_type":"no_license","max_line_length":28,"num_lines":27,"path":"/알고리즘/온라인저지/2022/04/0404/아이 러브 크로아티아.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"K = int(input()) - 1\nN = int(input())\nquizs = []\nfor n in range(N):\n tmp = input().split()\n tmp[0] = int(tmp[0])\n quizs.append(tmp)\n# print(quizs)\ntime = 60*3 + 30\n# print(time)\ni = 0\nwhile True:\n now = quizs[i]\n # print(now, time, K, i)\n if time < now[0]:\n break\n if now[1] == 'T':\n time -= now[0]\n K = (K+1)%8\n i += 1\n elif now[1] == 'N':\n time -= now[0]\n i += 1 \n elif now[1] == 'P':\n time -= now[0]\n i += 1\nprint(K+1)"},{"alpha_fraction":0.5545454621315002,"alphanum_fraction":0.5545454621315002,"avg_line_length":30.571428298950195,"blob_id":"211d86e78f4e1f1bc92a5868b29adb3dcb583806","content_id":"51f6c1aa78f30a672a5be3798c8b5c4ef5609e18","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":220,"license_type":"no_license","max_line_length":42,"num_lines":7,"path":"/알고리즘/온라인저지/2023/03/0327/괴짜 교수.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"for _ in range(int(input())):\n D, N, S, P = map(int, input().split())\n A, B = D+N*P, N*S\n result = 'does not matter'\n if A<B: result = 'parallelize'\n if A>B: result = 'do not parallelize'\n print(result)"},{"alpha_fraction":0.5151515007019043,"alphanum_fraction":0.5151515007019043,"avg_line_length":15.75,"blob_id":"8a8da07e571193661d5dcea8ed38ba04400cbdf8","content_id":"02035e789f62d80421f18ce75f29b2edb1af61aa","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":66,"license_type":"no_license","max_line_length":29,"num_lines":4,"path":"/알고리즘/온라인저지/2022/02/0209/히스토그램.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = int(input())\n\nfor n in range(N):\n print('=' * int(input()))"},{"alpha_fraction":0.36320754885673523,"alphanum_fraction":0.4292452931404114,"avg_line_length":13.199999809265137,"blob_id":"ef278bff20b1a99e35c9abbaa5765fb6fe82c181","content_id":"192675d650ffbeae1bb90c1f6229e64b7f5d76f7","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":212,"license_type":"no_license","max_line_length":29,"num_lines":15,"path":"/알고리즘/온라인저지/2022/02/0201/피보나치 함수.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"T = int(input())\n\ndp = [0] * 42\ndp[1] = 1\n\nfor i in range(2, 42):\n dp[i] = dp[i-1] + dp[i-2]\n\nfor t in range(T):\n N = int(input())\n\n if N == 0:\n print(1, 0)\n else:\n print(dp[N-1], dp[N])"},{"alpha_fraction":0.5956678986549377,"alphanum_fraction":0.6028881072998047,"avg_line_length":20.384614944458008,"blob_id":"c6d4e0b4a532ade93e734ebee0e2a197a5e5135c","content_id":"a72d35502117d19686fc67c5b94014ccbd763244","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":277,"license_type":"no_license","max_line_length":47,"num_lines":13,"path":"/알고리즘/온라인저지/2022/11/1111/배수들의 합.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\n\nN, M = map(int, input().rstrip().split())\nnums = list(map(int, input().rstrip().split()))\nsett = set()\nresult = 0\nfor num in nums:\n for i in range(num, N+1, num):\n if i not in sett: result += i\n sett.add(i)\nprint(result)"},{"alpha_fraction":0.313296914100647,"alphanum_fraction":0.32058286666870117,"avg_line_length":21.91666603088379,"blob_id":"6e1be4c8813a001daadec17f8355817ee49423f6","content_id":"05a617a39923b2a4d6310a7b273db2a71a63217d","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":549,"license_type":"no_license","max_line_length":37,"num_lines":24,"path":"/알고리즘/온라인저지/2021/08/0822/괄호.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"T = int(input())\nfor tc in range(T):\n data = input()\n stack = []\n top = -1\n for dt in data:\n if dt == '(':\n stack.append(dt)\n top += 1\n else: # dt == ')'\n if top == -1:\n stack.append(dt)\n break\n else:\n if stack[top] == '(':\n stack.pop()\n top -= 1\n else:\n stack.append(dt)\n break\n if stack:\n print('NO')\n else:\n print('YES')"},{"alpha_fraction":0.5096153616905212,"alphanum_fraction":0.5480769276618958,"avg_line_length":16.38888931274414,"blob_id":"d42a9915354997ce3c8d9c648b3ddb8ca79d2b7b","content_id":"8f59ecb6a68b6a8c02160211d2f3420ed86a7576","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":354,"license_type":"no_license","max_line_length":42,"num_lines":18,"path":"/알고리즘/온라인저지/2023/03/0326/금민수의 개수.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"from collections import deque\n\nA,B = map(int,input().split())\nQ = deque()\n\nQ.append(4); Q.append(7)\nresult = 0\n\nwhile Q:\n GMS = Q.popleft()\n\n if GMS<=B:\n if A<=GMS: \n result += 1 # A이상 B이하 만족하는 금민수\n Q.append(GMS*10+4) # 다음 금민수 1\n Q.append(GMS*10+7) # 다음 금민수 2\n\nprint(result)"},{"alpha_fraction":0.39759036898612976,"alphanum_fraction":0.4337349534034729,"avg_line_length":14.625,"blob_id":"b1ac4fb8c1c3e635a1615fcd77a3d6d72d7466e7","content_id":"230aabb1b98e1773972cbf8d079bca7dd31cc490","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":249,"license_type":"no_license","max_line_length":31,"num_lines":16,"path":"/알고리즘/온라인저지/2021/09/0906/거스름돈.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\ndef input():\n return sys.stdin.readline()\n\nN = int(input())\ncnt = 0\nif N == 1 or N == 3:\n print(-1)\nelse:\n while N != 0:\n if not N%5:\n cnt += N//5\n break\n N -= 2\n cnt += 1\n print(cnt)"},{"alpha_fraction":0.4655172526836395,"alphanum_fraction":0.49425286054611206,"avg_line_length":16.5,"blob_id":"ef44730a6e825965bf6a70a994445d638a33d973","content_id":"c7c22e7e17a745e975864adf2b6f7e480abcf027","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":174,"license_type":"no_license","max_line_length":38,"num_lines":10,"path":"/알고리즘/온라인저지/2022/04/0401/우유 축제.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = int(input())\nmilk = list(map(int, input().split()))\nnow = 0\nresult = 0\nfor m in milk:\n if now == m:\n result += 1\n now += 1\n now %= 3\nprint(result)"},{"alpha_fraction":0.4915824830532074,"alphanum_fraction":0.5101010203361511,"avg_line_length":19.517240524291992,"blob_id":"49b59ca4b16429f84722a1f535455d94df3095ef","content_id":"00389b8c30972f0811c7a7aa92344f451d6db60a","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":594,"license_type":"no_license","max_line_length":39,"num_lines":29,"path":"/알고리즘/온라인저지/2023/01/0122/2진수 뒤집기.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"def dec_to_bin(number):\n # number : str\n dividor = 1\n number = int(number)\n while dividor*2 <= number:\n dividor *= 2\n answer = ''\n while dividor >= 1:\n if number >= dividor:\n answer += '1'\n number -= dividor\n else:\n answer += '0'\n dividor //= 2\n return answer\n\ndef bin_to_dec(number):\n # number : str\n multiplier = 1\n answer = 0\n for num in number:\n answer += int(num) * multiplier\n multiplier *= 2\n return answer\n\nN = input()\nN = dec_to_bin(N).rstrip('0')\nN = bin_to_dec(N)\nprint(N)"},{"alpha_fraction":0.5082873106002808,"alphanum_fraction":0.5368323922157288,"avg_line_length":26.174999237060547,"blob_id":"06e3eaa0a8dc6d945419d2236d82add3a6697d12","content_id":"c636a37faf7d85eb9c896a7ed762a393d8cab5de","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1456,"license_type":"no_license","max_line_length":73,"num_lines":40,"path":"/알고리즘/온라인저지/2022/04/0410/수강변경.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"# N = int(input())\n# student = []\n# for i in list(map(int, input().split())):\n# student.append([i])\n# j = 0\n# for i in list(map(int, input().split())):\n# student[j].append(i)\n# j += 1\n# for i in range(N):\n# for j in range(i, N):\n# if student[i][1] == student[j][0]:\n# student[i][0], student[j][0] = student[j][0], student[i][0]\n# elif student[j][1] == student[i][0]:\n# student[i][0], student[j][0] = student[j][0], student[i][0]\n# result = 0\n# for s in student:\n# if s[0] != s[1]:\n# result += 1\n# print(result)\n\n\"\"\"\n원하는 학생들끼리 일대일로 교환시켜주는 코드를 짰는데\n시간초과가 나왔다\n문제는 \"그래서 원하는 수업을 못 듣는 학생수는 몇명인가\" 였고\n아래 코드를 통하여 해결하였다\n\"\"\"\n\n# 핵심은 수업 교환횟수는 제한이 없고\n# 학생들끼리 어떻게든 돌리고 돌리다 남는 학생의 수만 구하면 됨\nN = int(input())\ndp = [0] * 1000001 # 수업들 목록\nfor i in list(map(int, input().split())):\n dp[i] += 1 # 해당 수업을 신청하였음\nresult = 0 # 원하는 수업을 듣지 못하는 학생 수\nfor i in list(map(int, input().split())):\n if dp[i] >= 1: # 그 수업을 들고 있는 사람이 있으면\n dp[i] -= 1 # 교환\n else: # 그 수업을 들고 있는 사람 자체가 없으면\n result += 1 # 원하는 수업을 듣지 못하는 사람\nprint(result)"},{"alpha_fraction":0.4796747863292694,"alphanum_fraction":0.4918699264526367,"avg_line_length":16.64285659790039,"blob_id":"aca21764521c939603241a122fe599f33e756abf","content_id":"8772a3df5e1782533b44e07273bb323c585f0d44","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":246,"license_type":"no_license","max_line_length":31,"num_lines":14,"path":"/알고리즘/온라인저지/2022/04/0405/디지털 루트.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"def main(n):\n tmp = 0\n for i in str(n):\n tmp += int(i)\n return tmp\n\nwhile True:\n N = int(input())\n if N == 0:\n break\n result = main(N)\n while len(str(result)) > 1:\n result = main(result)\n print(result)"},{"alpha_fraction":0.4733542203903198,"alphanum_fraction":0.48275861144065857,"avg_line_length":15.736842155456543,"blob_id":"87fd7b5a35973a3fe7b6ae42598abd85cf4949fc","content_id":"e3e915871481a660fbd27b3c6c716d08433936e7","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":319,"license_type":"no_license","max_line_length":47,"num_lines":19,"path":"/알고리즘/온라인저지/2022/02/0202/2차원 배열의 합.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N, M = map(int, input().split())\n\narr = []\n\nfor n in range(N):\n arr.append(list(map(int, input().split())))\n\nK = int(input())\n\nfor k in range(K):\n i, j, x, y = map(int, input().split())\n\n summ = 0\n\n for a in range(i-1, x):\n for b in range(j-1, y):\n summ += arr[a][b]\n \n print(summ)\n\n"},{"alpha_fraction":0.4453125,"alphanum_fraction":0.4453125,"avg_line_length":17.428571701049805,"blob_id":"159e1caf305a6e1e7ac1d804207a2159c9dbb0a6","content_id":"8c0356e0f7129ee6d905cd4de47e22ea626faf80","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":132,"license_type":"no_license","max_line_length":29,"num_lines":7,"path":"/알고리즘/온라인저지/2023/03/0314/2루수 이름이 뭐야.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"print('뭐야', end='')\nfor _ in range(int(input())):\n if input() == 'anj':\n print(';')\n break\nelse:\n print('?')"},{"alpha_fraction":0.5604395866394043,"alphanum_fraction":0.5769230723381042,"avg_line_length":25.14285659790039,"blob_id":"a41ccafb304aab9b23d0f28f1cb7ad82b6025807","content_id":"9fb9fc4f8c9cc60618a6779fb14a664ee5e311dc","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":182,"license_type":"no_license","max_line_length":54,"num_lines":7,"path":"/알고리즘/온라인저지/2022/08/0827/Counting Antibodies.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"result = 0\nfor _ in range(2):\n tmp = 1\n for i in list(map(int, input().split())): tmp *= i\n result += tmp\nfor i in list(map(int, input().split())): result *= i\nprint(result)"},{"alpha_fraction":0.5730336904525757,"alphanum_fraction":0.584269642829895,"avg_line_length":13.833333015441895,"blob_id":"6eeac743e95bedb043d25a81531cc03fe37d9357","content_id":"1fb43e2f270405a535fc7bd47548eff6e9397c95","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":113,"license_type":"no_license","max_line_length":40,"num_lines":6,"path":"/알고리즘/SWEA/LEARN/Course/1. Programming Beginner/파이썬 프로그래밍 기초(2)/37차시 4. 문자열 - 연습문제 1.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"tmp = input()\n\nprint(tmp)\n\nif tmp == tmp[::-1]:\n print('입력하신 단어는 회문(Palindrome)입니다.')\n"},{"alpha_fraction":0.4285714328289032,"alphanum_fraction":0.4458874464035034,"avg_line_length":15.571428298950195,"blob_id":"5f08d2ce6443cdc7ec8ed0548c94cdf42a93c946","content_id":"72080190fac9469bb52dd39aab646f9314f20edd","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":231,"license_type":"no_license","max_line_length":36,"num_lines":14,"path":"/알고리즘/온라인저지/2021/12/1216/배수와 약수.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"while True:\n a, b = map(int, input().split())\n\n if a == 0 and b == 0:\n break\n\n result = 'neither'\n\n if a % b == 0:\n result = 'multiple'\n elif b % a == 0:\n result = 'factor'\n \n print(result)"},{"alpha_fraction":0.5227272510528564,"alphanum_fraction":0.5378788113594055,"avg_line_length":32.125,"blob_id":"8d636b333b4561ab3c71d11e6fa2cd76af4c1a8b","content_id":"3638ac3b7af46514765d80362da5e0ce95bb6e16","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":344,"license_type":"no_license","max_line_length":62,"num_lines":8,"path":"/알고리즘/온라인저지/2021/08/0803/상수.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"a, b = input().split() # a와 b를 공백을 기준으로 input 받아서\ndef aigosangsuya(a, b): \n if int(a[::-1]) >= int(b[::-1]): # 각각 뒤에서 읽은 값의 int값을 비교해서\n result = a[::-1]\n else:\n result = b[::-1]\n return result # 큰 쪽을 저장해서 반환\nprint(aigosangsuya(a, b)) # 값을 출력"},{"alpha_fraction":0.5515695214271545,"alphanum_fraction":0.5784753561019897,"avg_line_length":22.526315689086914,"blob_id":"f868f553d9e4dbc74475d6d8f46116cdf0bfd8bc","content_id":"1e8dc5411b002f4a7b15898d06cd90b8903559f2","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":446,"license_type":"no_license","max_line_length":48,"num_lines":19,"path":"/알고리즘/온라인저지/2022/10/1006/점프 점프.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\nfrom collections import deque\n\ninput = sys.stdin.readline\n\nN = int(input().rstrip())\narr = list(map(int, input().rstrip().split()))\nQ = deque()\nvisited = [0]*N\nQ.append((0, 0))\nvisited[0] = 1\nwhile Q:\n now, move = Q.popleft()\n if now == N-1: print(move); break\n for i in range(now+1, now+1+arr[now]):\n if 0<=i<N and arr[i] and not visited[i]:\n Q.append((i, move+1))\n visited[i] = 1\nelse: print(-1)"},{"alpha_fraction":0.44186046719551086,"alphanum_fraction":0.45348837971687317,"avg_line_length":13.5,"blob_id":"851a561528e5023b3d15b2b95fbeed1ae0625306","content_id":"cc957f801b7f5eb7f1b4cf0d14f147a7ff37b22b","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":86,"license_type":"no_license","max_line_length":20,"num_lines":6,"path":"/알고리즘/온라인저지/2022/02/0206/!밀비 급일.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"while True:\n sen = input()\n if sen == 'END':\n break\n\n print(sen[::-1])"},{"alpha_fraction":0.3992537260055542,"alphanum_fraction":0.41044774651527405,"avg_line_length":13.833333015441895,"blob_id":"fb66f3bff28f3fb5bf51c470d8a09be53a53426d","content_id":"34f70adc1681ec856a282fad2fe4e56405e71064","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":268,"license_type":"no_license","max_line_length":45,"num_lines":18,"path":"/알고리즘/온라인저지/2022/02/0213/내 학점을 구해줘.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"T = int(input())\n\nfor t in range(T):\n N = int(input())\n\n sumC = 0\n\n tmp = 0\n\n for n in range(N):\n C, G = map(float, input().split())\n C = int(C)\n\n sumC += C\n \n tmp += C * G\n\n print('{} {:.1f}'.format(sumC, tmp/sumC))\n\n"},{"alpha_fraction":0.5714285969734192,"alphanum_fraction":0.5952380895614624,"avg_line_length":27.33333396911621,"blob_id":"febc505e53e99d642622fb932b829af8edadf636","content_id":"50412a65d30006796a35d0f30b57792ffbc33861","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":84,"license_type":"no_license","max_line_length":42,"num_lines":3,"path":"/알고리즘/온라인저지/2022/03/0303/알고리즘 수업 - 알고리즘의 수행 시간 4.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"result = sum(list(range(1, int(input()))))\ndim = 2\nprint(result, f'\\n{dim}', sep='')"},{"alpha_fraction":0.5887850522994995,"alphanum_fraction":0.5981308221817017,"avg_line_length":22.88888931274414,"blob_id":"3d948194e389fa119ba80efdaf019adab6e193e0","content_id":"25c950c060d96543eca997e1f06242586fc3e008","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":214,"license_type":"no_license","max_line_length":47,"num_lines":9,"path":"/알고리즘/온라인저지/2022/11/1120/요다.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\n\nfor _ in range(int(input().rstrip())):\n words = input().split()\n for word in words[2:]: print(word, end=' ')\n for word in words[:2]: print(word, end=' ')\n print()"},{"alpha_fraction":0.3683373034000397,"alphanum_fraction":0.38663485646247864,"avg_line_length":20.32203483581543,"blob_id":"3c81233a9a5c0b649374fe37901c65948c28fe1b","content_id":"a7d4267f8c14b187acb3872df97e1f80f4b182b3","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1281,"license_type":"no_license","max_line_length":75,"num_lines":59,"path":"/알고리즘/온라인저지/2021/12/1216/안전 영역.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import copy\nfrom collections import deque\n\nN = int(input())\n\ndx = (-1, 1, 0, 0)\ndy = (0, 0, -1, 1)\n\nheight_map = [list(map(int, input().split())) for _ in range(N)]\n\nrain = 0\n\nbfs = deque()\n\nresult = 0\n\nwhile True:\n tmp_map = copy.deepcopy(height_map)\n\n flooded_check = 0\n for i in range(N):\n for j in range(N):\n if tmp_map[i][j] <= rain:\n tmp_map[i][j] = 0\n flooded_check += sum(tmp_map[i])\n \n if flooded_check == 0:\n break\n \n safe = 0 # 현재 rain에서 나온 안전영역의 수\n\n for i in range(N):\n for j in range(N):\n if tmp_map[i][j]:\n bfs.append((i, j))\n safe += 1\n\n while bfs:\n tmp = bfs.popleft()\n y = tmp[0]\n x = tmp[1]\n\n if tmp_map[y][x] == 0:\n continue\n \n tmp_map[y][x] = 0\n for k in range(4):\n ny = y + dy[k]\n nx = x + dx[k]\n\n if 0 <= ny < N and 0 <= nx < N and tmp_map[ny][nx]:\n bfs.append((ny, nx))\n\n rain += 1\n \n if safe > result:\n result = safe\n\nprint(result)"},{"alpha_fraction":0.596187174320221,"alphanum_fraction":0.6048526763916016,"avg_line_length":29.421052932739258,"blob_id":"ba008688e5385eb03b480e864b59dc2fa7dbc2d6","content_id":"463c28ea2e3c51280e04c821260db708adce0ace","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":725,"license_type":"no_license","max_line_length":53,"num_lines":19,"path":"/알고리즘/온라인저지/2022/09/0908/점프 점프.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"from collections import deque\n\nN = int(input())\narr = list(map(int, input().split()))\nstart = int(input()) - 1 # 인덱스 맞추기\nvisited = [0] * N # 점들의 방문 배열\nQ = deque()\nQ.append(start) # 시작점 넣고 출발\nwhile Q:\n now = Q.popleft()\n if visited[now]: continue # 방문한 적 있는 점이면 continue\n visited[now] = 1 # 방문 처리\n tmp = arr[now] # 현재 지점에서 점프할 수 있는 거리\n front, back = now+tmp, now-tmp # 점프 시 인덱스\n if 0<=front<N and not visited[front]:\n Q.append(front) # 앞으로 점프\n if 0<=back<N and not visited[back]:\n Q.append(back) # 뒤로 점프\nprint(sum(visited)) # 방문한 적 있는 점들의 수 출력"},{"alpha_fraction":0.5549132823944092,"alphanum_fraction":0.589595377445221,"avg_line_length":14.818181991577148,"blob_id":"9c8d3f58ea68835399b5a852b4ac3de85bce390f","content_id":"dba8bc49f077dacdf3670d5e0ca0378f096f157a","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":173,"license_type":"no_license","max_line_length":34,"num_lines":11,"path":"/알고리즘/온라인저지/2022/06/0614/다각형의 대각선.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"from math import factorial as fact\n\nN = int(input())\nresult = 0\nif N == 3:\n result = 0\nelse:\n result = fact(N)\n result //= 24\n result //= fact(N-4)\nprint(result)"},{"alpha_fraction":0.567685604095459,"alphanum_fraction":0.5764192342758179,"avg_line_length":19.909090042114258,"blob_id":"ae37922eaacb52619edc0d2db806ac51871bb36e","content_id":"8f73c95da4bef5a47add7cdb889fbe3e4641c058","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":229,"license_type":"no_license","max_line_length":48,"num_lines":11,"path":"/알고리즘/온라인저지/2022/10/1031/공 넣기.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\n\nN, M = map(int, input().rstrip().split())\nresult = [0]*N\nfor m in range(M):\n a, b, c = map(int, input().rstrip().split())\n for i in range(a-1, b):\n result[i] = c\nprint(*result)"},{"alpha_fraction":0.49754902720451355,"alphanum_fraction":0.5098039507865906,"avg_line_length":23.727272033691406,"blob_id":"7b2675f169228b1065bf6f56ac606c0cc8a59446","content_id":"f9cba670894799d5cb642fe1729824389668ac1f","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":816,"license_type":"no_license","max_line_length":60,"num_lines":33,"path":"/알고리즘/온라인저지/2021/08/0828/스위치 켜고 끄기.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ndef change(num):\n if switch[num]:\n switch[num] = 0\n else:\n switch[num] = 1\n return\n\nswitch_count = int(sys.stdin.readline())\nswitch = [-1] + list(map(int, sys.stdin.readline().split()))\nstudents = int(sys.stdin.readline())\n\nfor i in range(students):\n sex, num = map(int, sys.stdin.readline().split())\n if sex == 1:\n for j in range(num, switch_count+1, num):\n change(j)\n else:\n change(num)\n for k in range(switch_count//2):\n if num+k > switch_count or num - k < 1:\n break\n if switch[num+k] == switch[num-k]:\n change(num+k)\n change(num-k)\n else:\n break\n\nfor i in range(1, len(switch)):\n print(switch[i], end=' ')\n if not i%20:\n print()\n"},{"alpha_fraction":0.5022830963134766,"alphanum_fraction":0.534246563911438,"avg_line_length":14.642857551574707,"blob_id":"07c3a2236f2a434a728847aea658822aa65ca3f1","content_id":"f5339ff4db8c02424f9f43b167785a46c0e6ae33","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":219,"license_type":"no_license","max_line_length":33,"num_lines":14,"path":"/알고리즘/온라인저지/2021/12/1216/그릇.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"dishes = input()\n\nheight = 10\n\nprev_dish = dishes[0]\n\nfor i in range(1, len(dishes)): \n if dishes[i] == prev_dish:\n height += 5\n else:\n height += 10\n prev_dish = dishes[i]\n \nprint(height)\n"},{"alpha_fraction":0.5562701225280762,"alphanum_fraction":0.5691318511962891,"avg_line_length":23,"blob_id":"b572e244d087762a67cafcb0f8396a1d1eb148a5","content_id":"151f3e69787f1328249e071dc55eeb9eb4fb82cd","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":311,"license_type":"no_license","max_line_length":39,"num_lines":13,"path":"/알고리즘/온라인저지/2022/09/0911/진짜 공간.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = int(input())\nfiles = list(map(int, input().split()))\ncluster = int(input())\nresult = 0\nfor file in files:\n if not file: continue\n if file > cluster:\n tmp = file//cluster + 1\n if file%cluster == 0: tmp -= 1\n result += cluster * tmp\n else:\n result += cluster\nprint(result)"},{"alpha_fraction":0.5961538553237915,"alphanum_fraction":0.6153846383094788,"avg_line_length":52,"blob_id":"40f58b147df1210de1beed3089ca32470f1af037","content_id":"2edaf399c8852c60b17f623ab92321b6e85c57fc","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":52,"license_type":"no_license","max_line_length":52,"num_lines":1,"path":"/알고리즘/온라인저지/2022/07/0731/돌 게임 2.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"print('SK') if not int(input()) % 2 else print('CY')"},{"alpha_fraction":0.582524299621582,"alphanum_fraction":0.6155340075492859,"avg_line_length":23.571428298950195,"blob_id":"980725440c2bc5ec04a8e1dc6be5d4aa50ceb2c2","content_id":"9e441cc14038f1cb1a57dbf8c7de5c284a6f6f0f","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":719,"license_type":"no_license","max_line_length":59,"num_lines":21,"path":"/알고리즘/온라인저지/2022/02/0225/로마 숫자 만들기.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"from itertools import combinations_with_replacement as comb\n# itertools를 코테에서도 쓸 수 있다고 하니\n# 실력향상을 위한 빡구현 vs 일단 라이브러리 사용\n# 고민해볼 가치가 있을 듯 (아래는 참고 블로그 링크)\n# https://uni2237.tistory.com/56\n\n\nN = int(input())\nresult = [] # 경우의 수 들이 담길 리스트\nrome = [1, 5, 10, 50] # 로마숫자 IVXL\n\nfor temp in comb(range(4), N):\n summ = 0 # 매 경우의 수\n # N==2 일 때, temp = (0, 0) ...\n for i in temp:\n summ += rome[i] # i는 rome의 인덱스값으로 사용\n\n result.append(summ) # 경우의 수를 완성해서 \n # result에 추가\n\nprint(len(set(result))) # set으로 중복제거"},{"alpha_fraction":0.40869563817977905,"alphanum_fraction":0.417391300201416,"avg_line_length":22.200000762939453,"blob_id":"075ea83a22110fa3beb79f66689ea6107acc2f7e","content_id":"d2c31ef14b1eb09a75de57cee4c5a348f23b79c5","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":115,"license_type":"no_license","max_line_length":36,"num_lines":5,"path":"/알고리즘/온라인저지/2022/05/0506/분수좋아해.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"while True:\n N, M = map(int, input().split())\n if N == M == 0:\n break\n print(f'{N//M} {N%M} / {M}')"},{"alpha_fraction":0.5279187560081482,"alphanum_fraction":0.5380710363388062,"avg_line_length":15.5,"blob_id":"76a01b7d6343833b00b89700b04735a2e6fdb3f2","content_id":"f1a5604b8c1591a4934f2e6e1421802b981114e7","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":197,"license_type":"no_license","max_line_length":41,"num_lines":12,"path":"/알고리즘/SWEA/LEARN/Course/1. Programming Beginner/파이썬 프로그래밍 기초(2)/35차시 3. 자료구조 – 셋, 딕셔너리 - 연습문제 10.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"alphabet = {}\n\ntmp = input()\n\nfor t in tmp:\n if t not in alphabet:\n alphabet.update({t:1})\n else:\n alphabet[t] += 1\n\nfor a in alphabet:\n print('{},{}'.format(a, alphabet[a]))"},{"alpha_fraction":0.4621409773826599,"alphanum_fraction":0.5483028888702393,"avg_line_length":26.428571701049805,"blob_id":"01a0c599142bad682bb3b56c9ff8e505f3f9bb0e","content_id":"7333b1f8de368e8fe007c05d83deb7a52cddcfce","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":383,"license_type":"no_license","max_line_length":56,"num_lines":14,"path":"/알고리즘/[템플릿]/Dynamic Programming/포도주 시식.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = int(input())\nwines = [0] * 10002\ndp = [0] * 10002\nfor n in range(N): wines[n] = int(input())\ndp[0] = wines[0]\ndp[1] = max(dp[0], wines[0]+wines[1])\ndp[2] = max(dp[1], wines[1]+wines[2], wines[0]+wines[2])\nfor i in range(3, N):\n A = dp[i-3] + wines[i-1] + wines[i]\n B = dp[i-2] + wines[i]\n dp[i] = max(A, B, dp[i-1])\nprint(max(dp))\n\n# https://www.acmicpc.net/problem/2156"},{"alpha_fraction":0.5573248267173767,"alphanum_fraction":0.5668789744377136,"avg_line_length":23.230770111083984,"blob_id":"6db09059b3288cb0f63a8e5b00ed48bba01fd718","content_id":"2e03a071287aaf2f1d09a948047e4c3fdf9099af","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":368,"license_type":"no_license","max_line_length":57,"num_lines":13,"path":"/알고리즘/온라인저지/2022/08/0815/좋은 단어.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\n\nN = int(input())\nresult = 0\nfor n in range(N):\n W, S = input().rstrip(), [] # word, stack\n for w in W:\n if S and w == S[-1]: S.pop() # 스택 마지막과 같으면 pop\n else: S.append(w) # 다르면 append\n if not S: result += 1 # 다 짝이 맞아서 스택에 남은게 없으면 result++\nprint(result)"},{"alpha_fraction":0.44936707615852356,"alphanum_fraction":0.4810126721858978,"avg_line_length":12.782608985900879,"blob_id":"5acaba1aa831ac0fec08ba84ce5fa391de7f6c81","content_id":"d9d2bdd8e426123dde9b9b04d1e6f03b8bf79fd8","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":316,"license_type":"no_license","max_line_length":34,"num_lines":23,"path":"/알고리즘/온라인저지/2022/01/0108/계단 오르기.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = int(input())\n\nstairs = []\n\nfor n in range(N):\n stairs.append(int(input()))\n\nN -= 1\n\nresult = stairs[N]\n\nwhile N >= 2:\n if stairs[N-1] >= stairs[N-2]:\n result += stairs[N-1]\n N -= 1\n else:\n result += stairs[N-2]\n N -= 2\n \nif N == 1:\n result += stairs[N-1]\n\nprint(result)"},{"alpha_fraction":0.4912280738353729,"alphanum_fraction":0.5087719559669495,"avg_line_length":12.470588684082031,"blob_id":"ba2cedd7cf98ebab0bcfb199a494517640322491","content_id":"8067ae73fb5a0b9861600819a7249a5e824e8483","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":228,"license_type":"no_license","max_line_length":32,"num_lines":17,"path":"/알고리즘/온라인저지/2021/12/1213/0 = not cute, 1 = cute.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"T = int(input())\n\ncute = 0\ncut = 0\n\nfor tc in range(T):\n is_cute = int(input())\n\n if is_cute:\n cute += 1\n else:\n cut += 1\n\nif cute < cut:\n print('Junhee is not cute!')\nelse:\n print('Junhee is cute!')"},{"alpha_fraction":0.468822181224823,"alphanum_fraction":0.494226336479187,"avg_line_length":27.933332443237305,"blob_id":"1502ee4aa8f6b1d68c6ffbbe9e25c2da1f02e631","content_id":"00d56cfe7dc1ddb43f3051a66200185f32a6e1e8","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":433,"license_type":"no_license","max_line_length":66,"num_lines":15,"path":"/알고리즘/온라인저지/2022/11/1103/이동하기.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\ndy, dx = [1, 0, 1], [0, 1, 1]\n\nN, M = map(int, input().rstrip().split())\narr = [list(map(int, input().rstrip().split())) for _ in range(N)]\ndp = [a[:] for a in arr]\nfor i in range(N):\n for j in range(M):\n for k in range(3):\n ny, nx = i+dy[k], j+dx[k]\n if 0<=ny<N and 0<=nx<M:\n dp[ny][nx] = max(dp[ny][nx], arr[ny][nx]+dp[i][j])\nprint(dp[N-1][M-1])"},{"alpha_fraction":0.6231883764266968,"alphanum_fraction":0.6376811861991882,"avg_line_length":34,"blob_id":"4e2516de7d98e9177e93bca847a6c69b3ce778c8","content_id":"e385c0c5d72340e3061ef37a2b801c7031ef84a5","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":69,"license_type":"no_license","max_line_length":38,"num_lines":2,"path":"/알고리즘/온라인저지/2022/03/0306/金平糖 (Konpeito).py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"nums = list(map(int, input().split()))\nprint(max(nums)*3 - sum(nums))"},{"alpha_fraction":0.4350649416446686,"alphanum_fraction":0.5064935088157654,"avg_line_length":21.14285659790039,"blob_id":"cbebbd888bd8ef9fd9e6d7b0125038527fe6f39c","content_id":"b38a7606ceb1498e597534c2d30d1b8aba5ae6f7","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":154,"license_type":"no_license","max_line_length":44,"num_lines":7,"path":"/알고리즘/온라인저지/2023/04/0415/Every Second Counts.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"times = []\nfor _ in range(2):\n h, m, s = map(int, input().split(' : '))\n times.append((h*60+m)*60+s)\na, b = times\nif b < a: b += 24*60*60\nprint(b-a)"},{"alpha_fraction":0.33421751856803894,"alphanum_fraction":0.4615384638309479,"avg_line_length":12.034482955932617,"blob_id":"ea9c02f39632b51b2c601199ec4742a87875c242","content_id":"d80df80b8ac4421b56dbe7818ffad3a6bff34e4d","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":481,"license_type":"no_license","max_line_length":31,"num_lines":29,"path":"/알고리즘/SWEA/LEARN/Course/1. Programming Beginner/파이썬 프로그래밍 기초(2)/29차시 3. 자료구조 – 셋, 딕셔너리 - 연습문제 4.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"a = {\n '아메리카노': 1900, \n '카페모카': 3300, \n '에스프레소': 1900, \n '카페라떼': 2500, \n '카푸치노': 2500, \n '바닐라라떼': 2900\n }\n\nb = {\n '헤이즐럿라떼': 2900, \n '카페모카': 3300, \n '밀크커피': 3300, \n '아메리카노': 1900, \n '샷크린티라떼': 3300\n }\n\ntmp = {}\n\ntmp.update(b)\ntmp.update(a)\n\nresult = set()\n\nfor t in tmp:\n if tmp[t] >= 3000:\n result.add((t, tmp[t]))\n\nprint(result)"},{"alpha_fraction":0.4507211446762085,"alphanum_fraction":0.4951923191547394,"avg_line_length":26.600000381469727,"blob_id":"b590b330131224abbce25f6b6e9f0168a66b97a4","content_id":"e439f456ac51e28234df65662f962528b5f2e944","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1196,"license_type":"no_license","max_line_length":53,"num_lines":30,"path":"/알고리즘/온라인저지/2021/08/0812/세탁소 사장 동혁.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"\"\"\"\n미국동전\n1: 페니 = 10원\n5: 니켈 = 50원\n10: 다임 = 100원\n25: 쿼터 = 250\n\n아래 두개는 문제에서 안 씀\n# 50: 하프달러 = 500원\n# 100: 달러 = 1000원\n\"\"\"\nT = int(input()) # 테스트케이스\ncoins = [25, 10, 5, 1] # 동전들\nfor t in range(T): # 테스트케이스 개수만큼\n change = int(input()) # 거스름돈\n changed_coins = [] # 사용된 모든 동전들\n for coin in coins: # 동전들을 순회하면서\n if coin <= change: # 거슬러줄 수 있으면\n while True: # while문 반복하면서 거슬러준다\n change -= coin # 해당 동전을 하나 거슬러주고\n changed_coins.append(coin) # 그 동전을\n # 거슬러준 동전 리스트에 추가\n if coin > change: # 순회중인 동전이 금액보다 커져서\n # 그 동전으로 거슬러 줄 수 없게되면\n break # while문 종료\n for i in range(4): # 동전은 총 4개\n # 사용된 동전의 개수의 종류는 4개\n print(changed_coins.count(coins[i]), end=' ')\n # 동전개수를 세서 출력\n print() # 줄바꿈\n "},{"alpha_fraction":0.550632894039154,"alphanum_fraction":0.6392405033111572,"avg_line_length":21.428571701049805,"blob_id":"0a76605c86a62d9a9362bcfe0fbed0d7d1c6e112","content_id":"873ebf7b7061fa227582099a328f18af894628f5","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":158,"license_type":"no_license","max_line_length":35,"num_lines":7,"path":"/알고리즘/온라인저지/2023/02/0206/정육각형과 삼각형.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import math\n\nL = int(input())\ncos_30 = math.cos(math.radians(30))\ncos_60 = math.cos(math.radians(60))\nresult = L**2 * cos_30 * cos_60\nprint(f'{result:.9f}') "},{"alpha_fraction":0.40336135029792786,"alphanum_fraction":0.4075630307197571,"avg_line_length":22.899999618530273,"blob_id":"330d164ec17d33adedb03ddf1c9c1b9a187eae19","content_id":"7007dee796672c42f1573b2961bf9650e268f563","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":238,"license_type":"no_license","max_line_length":39,"num_lines":10,"path":"/알고리즘/온라인저지/2022/05/0503/다음수.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"while True:\n A, B, C = map(int, input().split())\n if A == B == C == 0:\n break\n result = 'AP'\n if B-A == C-B: # AP\n print(result, C + (C-B))\n else: # GP\n result = 'GP'\n print(result, (C * (B//A)))"},{"alpha_fraction":0.5176470875740051,"alphanum_fraction":0.529411792755127,"avg_line_length":20.5,"blob_id":"762842be446e110e892cf3e53f6f797ab098d11a","content_id":"2a7d054610a7e8608bc0f70d0794dd2e30001aee","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":85,"license_type":"no_license","max_line_length":30,"num_lines":4,"path":"/알고리즘/온라인저지/2023/04/0428/스키테일 암호.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"K = int(input())\nPW = input()\nfor i in range(0, len(PW), K):\n print(PW[i], end='')"},{"alpha_fraction":0.5176211595535278,"alphanum_fraction":0.5616739988327026,"avg_line_length":33.92307662963867,"blob_id":"5fe865008bdce35e2d0fc712eec44e63e10ec214","content_id":"023118db16e631716bda5901abea1b8f9298d388","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":582,"license_type":"no_license","max_line_length":96,"num_lines":13,"path":"/알고리즘/온라인저지/2021/08/0816/주사위.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = int(input())\nnumbers = list(map(int, input().split()))\nnumber = [min(numbers[0], numbers[5]), min(numbers[1], numbers[4]), min(numbers[2], numbers[3])]\n # 최소값을 도출해낼 수 있는 면 찾기\nnumber.sort() # 사용할 숫자들 크기순으로 정리\nA = number[0]\nB = number[1]\nC = number[2]\nif N == 1: # 1*1일때는 그 주사위 자체이니까\n print(sum(numbers)-max(numbers)) # 가장 큰 수를 아랫면으로 놓은 값을 출력\nelse: # 1이 아니면\n print((((((N-1)*A)+B)*N)*4) + C*4 + (((N-2)*B)*4) + A*(N-2)*(N-2))\n # 최소값 출력\n"},{"alpha_fraction":0.4436090290546417,"alphanum_fraction":0.49624061584472656,"avg_line_length":18.14285659790039,"blob_id":"a6d9f4568fd6b212f19bbdc71957f15914f5a6f5","content_id":"7c81fadb186cdf8a9c1a8c7295b6b27524e5cf95","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":133,"license_type":"no_license","max_line_length":23,"num_lines":7,"path":"/알고리즘/온라인저지/2022/05/0507/369.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = int(input())\nresult = 0\nfor n in range(1, N+1):\n for i in str(n):\n if i in '369':\n result += 1\nprint(result)"},{"alpha_fraction":0.45026177167892456,"alphanum_fraction":0.4921466112136841,"avg_line_length":15,"blob_id":"a50cf074b95cfe4a18128166bc9d0ebe1d0c4158","content_id":"511230e575c4c90f98bec7a40bd6e6c086b11f06","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":191,"license_type":"no_license","max_line_length":34,"num_lines":12,"path":"/알고리즘/온라인저지/2022/07/0731/알고리즘 수업 - 피보나치 수 1.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"def fib(n):\n global result\n if n == 1 or n == 2:\n result += 1\n return 1\n else:\n return fib(n-1) + fib(n-2)\n\nN = int(input())\nresult = 0\nfib(N)\nprint(result, N-2)"},{"alpha_fraction":0.3333333432674408,"alphanum_fraction":0.46236559748649597,"avg_line_length":9.44444465637207,"blob_id":"9d377968726ff4d0c1c9c9955351ed8f56c1769f","content_id":"a840027d6880af73de75bc156004a8c9c6bf3788","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":93,"license_type":"no_license","max_line_length":29,"num_lines":9,"path":"/알고리즘/온라인저지/2022/02/0225/운동장 한 바퀴.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"pi = 3.141592\n\nA = 13\nB = 8\n\nA = int(input())\nB = int(input())\n\nprint((A * 2) + (2 * pi * B))"},{"alpha_fraction":0.4301075339317322,"alphanum_fraction":0.5376344323158264,"avg_line_length":25.714284896850586,"blob_id":"6c3486bea5bf6a493f568a0e025153c97c5508cc","content_id":"1b761553461679d90ff8b963d16d66c93c9cbf03","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":186,"license_type":"no_license","max_line_length":38,"num_lines":7,"path":"/알고리즘/[템플릿]/Dynamic Programming/파도반 수열.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"dp = [1, 1, 1, 2, 2, 3] + [0]*97\nfor i in range(5, 103): \n dp[i] = dp[i-5]+dp[i-1]\nfor _ in range(int(input())): \n print(dp[int(input())-1])\n\n# https://www.acmicpc.net/problem/9461"},{"alpha_fraction":0.4232558012008667,"alphanum_fraction":0.4558139443397522,"avg_line_length":14.428571701049805,"blob_id":"7dd864055711d3cf66b55d930ff3a27ea8c75b53","content_id":"04c7366cfd69a02e293943a592321560a7a8491a","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":215,"license_type":"no_license","max_line_length":35,"num_lines":14,"path":"/알고리즘/온라인저지/2022/05/0505/ソーシャルゲーム (Social Game).py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"A, B, C = map(int, input().split())\nresult = 0\nday = 0\ncoin = 0\nwhile True:\n coin += A\n day += 1\n result += 1\n if day == 7:\n day = 0\n coin += B\n if coin >= C:\n break\nprint(result)"},{"alpha_fraction":0.5569620132446289,"alphanum_fraction":0.594936728477478,"avg_line_length":39,"blob_id":"d2bb54d1843c0f8867805aed2047ed6ab52ca0dd","content_id":"d6a2bd278cf69aeb17450e24f24810724a3599af","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":79,"license_type":"no_license","max_line_length":49,"num_lines":2,"path":"/알고리즘/온라인저지/2022/05/0516/Sum of Odd Sequence.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"for t in range(int(input())):\n print(sum(list(range(1, int(input())+1, 2))))"},{"alpha_fraction":0.5161290168762207,"alphanum_fraction":0.6129032373428345,"avg_line_length":17.799999237060547,"blob_id":"62799550449c404c8fc14b0f3601928ecb618c96","content_id":"5df930954e9eb2ee46d6e8c78c6f2a1884227cdc","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":93,"license_type":"no_license","max_line_length":36,"num_lines":5,"path":"/알고리즘/온라인저지/2021/08/0822/윤년.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = int(input())\nresult = 0\nif (not N%4 and N%100) or not N%400:\n result = 1\nprint(result)"},{"alpha_fraction":0.5375722646713257,"alphanum_fraction":0.5664739608764648,"avg_line_length":12.384614944458008,"blob_id":"a85e80b0a57b0c2d33cc08bacdf0cc66aa0e32fe","content_id":"6eb7062b6fb412a70b93cd085808f6aaca531392","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":173,"license_type":"no_license","max_line_length":26,"num_lines":13,"path":"/알고리즘/온라인저지/2022/10/1011/새.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\n\nN = int(input().rstrip())\nresult = 0\nnum = 1\nwhile N:\n result += 1\n if num > N: num = 1\n N -= num\n num += 1\nprint(result)"},{"alpha_fraction":0.5277777910232544,"alphanum_fraction":0.5347222089767456,"avg_line_length":13.5,"blob_id":"d967f38e0cb9e77b7f17d6953750b953e797ff51","content_id":"db667f7a8b2d4f9990e0be99bf0a3fcf2b04d556","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":144,"license_type":"no_license","max_line_length":32,"num_lines":10,"path":"/알고리즘/온라인저지/2022/02/0224/뉴비의 기준은 뭘까.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N, M = map(int, input().split())\n\nresult = 'NEWBIE!'\n\nif M <= N and M > 2:\n result = 'OLDBIE!'\nelif M > N:\n result = 'TLE!'\n\nprint(result)"},{"alpha_fraction":0.3737373650074005,"alphanum_fraction":0.4040403962135315,"avg_line_length":18.799999237060547,"blob_id":"cc3112aeee5edf1984a4ecb4adcbd4d546f161a7","content_id":"c1d83e9ce0a682adb477e5925dedeaf22c4c7899","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":99,"license_type":"no_license","max_line_length":22,"num_lines":5,"path":"/알고리즘/온라인저지/2021/08/0816/for break.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"for i in range(5):\n for j in range(5):\n if j == 3:\n break\n print(i, j)\n"},{"alpha_fraction":0.4229764938354492,"alphanum_fraction":0.44778066873550415,"avg_line_length":20.30555534362793,"blob_id":"5e22b2dddb8ef33504dddb31d388a2b2e3a16134","content_id":"53ed0e39933546bf42b2b7fe8940954f4e687533","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":870,"license_type":"no_license","max_line_length":65,"num_lines":36,"path":"/알고리즘/온라인저지/2022/12/1204/갤러리.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"def find(height, width):\n global result\n for i in range(height-1):\n j = 0\n while j < width-1:\n j += 1\n if arr[i][j:j+2] == 'XX' and arr[i+1][j:j+2] == '..':\n result += 1\n j += 1\n if arr[i][j:j+2] == '..' and arr[i+1][j:j+2] == 'XX':\n result += 1\n j += 1\n\ndef rotate(arr):\n new_arr = []\n for j in range(M):\n tmp = ''\n for i in range(N):\n tmp += arr[i][j]\n new_arr.append(tmp)\n return new_arr\n\nN, M = map(int, input().split())\narr = [input() for _ in range(N)]\nresult = 0\nfind(N, M)\narr = rotate(arr)\nfind(M, N)\nprint(result)\n\n\"\"\"\n그림을 걸 수 있는지 가로로만 스캔할 것\n그리고 배열을 90도 돌려주고 다시 스캔\n주의할 점은\n90도만 배열을 돌리기 때문에 N과 M이 반전됨\n\"\"\""},{"alpha_fraction":0.43579766154289246,"alphanum_fraction":0.4630350172519684,"avg_line_length":18.846153259277344,"blob_id":"795fd9194e395140893fe86ef609053cc5a797bf","content_id":"8eda7c5ff287e47ad46132b86150be19276b45e0","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":257,"license_type":"no_license","max_line_length":42,"num_lines":13,"path":"/알고리즘/온라인저지/2022/07/0726/국회의원 선거.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = int(input())\nresult = 0\nif N == 1:\n print(result)\nelse:\n D = int(input()) # dasom\n C = [int(input()) for _ in range(N-1)]\n while D <= max(C):\n C.sort(reverse=True)\n D += 1\n result += 1\n C[0] -= 1\n print(result)"},{"alpha_fraction":0.508083164691925,"alphanum_fraction":0.5265588760375977,"avg_line_length":26.0625,"blob_id":"94482ad6e55605edb11211878983d0c4220704fd","content_id":"50b762f7cff82b266ce4da7354bedffe1d3b3a31","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":433,"license_type":"no_license","max_line_length":92,"num_lines":16,"path":"/알고리즘/온라인저지/2023/01/0129/숫자놀이.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"M, N = map(int, input().split())\narr = []\nnum_to_en = ['zero', 'one', 'two', 'three', 'four', 'five', 'six', 'seven', 'eight', 'nine']\nnum_list = list(range(M, N+1))\nfor num in num_list:\n tmp = ''\n for i in str(num):\n tmp += num_to_en[int(i)]\n translated = [tmp, num]\n arr.append(translated)\narr.sort(key=lambda x:x[0])\ncnt = 0\nfor a in arr: \n print(a[1], end=' ')\n cnt = (cnt+1)%10\n if cnt == 0: print()\n"},{"alpha_fraction":0.5,"alphanum_fraction":0.5074626803398132,"avg_line_length":26,"blob_id":"161baa71a0a801971651800bc412c6a0e49d68fd","content_id":"b267dfd38f82b808ee6de791fa6f320f6a2002a4","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":134,"license_type":"no_license","max_line_length":36,"num_lines":5,"path":"/알고리즘/온라인저지/2022/09/0910/닉네임에 갓 붙이기.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"for _ in range(int(input())):\n nickname = input().split()\n for i in ['god'] + nickname[1:]:\n print(i, end='')\n print()"},{"alpha_fraction":0.391259104013443,"alphanum_fraction":0.40894901752471924,"avg_line_length":21.372093200683594,"blob_id":"2477fa5ef1f248ee0f95e42baeb9a93dd6897809","content_id":"f49e1a82df9f206abc06f2446b12c12b16630553","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1233,"license_type":"no_license","max_line_length":80,"num_lines":43,"path":"/알고리즘/온라인저지/2022/01/0122/소수의 연속합.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = int(input())\n\nif N == 1:\n # 놀랍게도 1은 소수가 아니었다!!\n cnt = 0\nelse:\n # 에라토스테네스의 체로 N까지의 소수 구하기\n a = [False,False] + [True]*(N-1)\n primes = []\n for i in range(2,N+1):\n if a[i]:\n primes.append(i)\n for j in range(2*i, N+1, i):\n if a[j]:\n a[j] = False\n\n # 투포인터에 사용할 변수 s, e와\n # 연속합이 N일때 카운트할 cnt\n s = e = cnt = 0\n\n # 가장 작은 소수부터 시작\n now = 2\n\n while True:\n # 투포인터 탐색 종료조건\n if (now < N and e == len(primes)-1) or (now > N and s == len(primes)-1):\n break\n\n if now == N: # 구간합이 N과 같으면\n cnt += 1 # 카운트 증가\n now -= primes[s] # 포인터 이동\n s += 1\n elif now < N: # 구간합이 N보다 작을 때\n e += 1 # 한 칸 밀어주기\n now += primes[e]\n elif now > N: # 구간합이 N보다 클 때\n now -= primes[s]\n s += 1 # 한 칸 땡겨주기\n\n if now == N: # 다 돌고 마지막 본인이 소수일 때\n cnt += 1 # 카운트 증가\n\nprint(cnt)"},{"alpha_fraction":0.5679012537002563,"alphanum_fraction":0.6296296119689941,"avg_line_length":26.33333396911621,"blob_id":"058d9bb0d27ca5d0a006c1f504a5bb4e23a05061","content_id":"b245c4e797708f56f4ec280f8a5aefe95a4bd3a0","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":81,"license_type":"no_license","max_line_length":40,"num_lines":3,"path":"/알고리즘/온라인저지/2023/02/0215/간지(干支).py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"year = int(input())\ntmp = 'IJKLABCDEFGH'\nprint(tmp[year%12], (year+6)%10, sep='')"},{"alpha_fraction":0.45254236459732056,"alphanum_fraction":0.5169491767883301,"avg_line_length":16.909090042114258,"blob_id":"d20212a1fb806d5cf77900901143d92fdefc25f3","content_id":"1d02dfc8b84d2c56f391006144684a22cc1865a0","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":590,"license_type":"no_license","max_line_length":49,"num_lines":33,"path":"/알고리즘/온라인저지/2021/12/1216/숨바꼭질.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"from collections import deque\n\nN, K = map(int, input().split())\n\nbfs = deque()\nbfs.append((N, 0))\n\nvisited = [0 for _ in range(100001)]\n\nwhile bfs:\n tmp = bfs.popleft()\n n = tmp[0]\n t = tmp[1]\n\n if visited[n]:\n continue\n\n if n == K:\n print(t)\n break\n\n visited[n] = 1\n\n go = n+1\n back = n-1\n jump = n*2\n\n if 0 <= go <= 100000 and not visited[go]:\n bfs.append((go, t+1))\n if 0 <= back <= 100000 and not visited[back]:\n bfs.append((back, t+1))\n if 0 <= jump <= 100000 and not visited[jump]:\n bfs.append((jump, t+1))"},{"alpha_fraction":0.5080440044403076,"alphanum_fraction":0.5309060215950012,"avg_line_length":29.947368621826172,"blob_id":"21dccf9f15012be838282d0e163e354ebd066f7d","content_id":"4030e62ba11cca3746c0689d54a60333aab74119","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1735,"license_type":"no_license","max_line_length":59,"num_lines":38,"path":"/알고리즘/온라인저지/2022/01/0116/달력.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = int(input()) # 일정의 개수\n\ndp = [0] * 365 # 일년치 달력\n\nfor n in range(N):\n S, E = map(int, input().split()) # 일정 입력\n\n for i in range(S-1, E): # 리스트를 365로 하였기 때문에 1일은 dp[0]\n # 시작도 S-1부터\n dp[i] += 1 # 일정이 있는 날 달력의 높이 하나 추가\n\n# 연속된 일정단위로 만들어지는 직사각형의 넓이들의 합을 구해야 함\nstart = end = width = height = result = 0 # result는 출력값\ncounting = False # 연속된 일정인지 확인하기 위함\n\nfor i in range(365): # 일년동안\n if dp[i]: # 일정이 있는 날이면\n if not counting: # 연속된지 체크중이지 않으면\n counting = True # 체크중으로 변경\n start = i # 이 날 부터 연속된 일정이 시작\n height = dp[i] # 일정들의 높이의 최대값 초기화\n elif counting: # 연속된지 체크중이면\n if dp[i] > height: # 지금 보고 있는 일정의 높이가 더 높으면\n height = dp[i] # 높이 갱신\n else: # 일정이 없는 날이면\n if counting: # 체크중이면\n counting = False # 체크를 종료하고\n end = i # 전날까지가 연속된 일정\n width = end - start # 연속된 일정들의 직사각형의 가로는 (끝-시작)\n result += width * height # 결과값에 직사각형의 높이 저장\n width = height = 0 # 가로 세로 초기화\n\nif dp[364] and counting: # 달력 마지막날이고, 체크중이라면\n end = 365 # 끝은 12월31일\n width = end - start # 가로\n result += width * height # 넓이를 결과값에 더해서\n\nprint(result) # 출력\n \n"},{"alpha_fraction":0.448587566614151,"alphanum_fraction":0.4689265489578247,"avg_line_length":24.285715103149414,"blob_id":"038151a60487cee5ccd57f7a79b0367c24f29d07","content_id":"2acd08aa238e48ada0d7b85a71af8178acb56d50","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1073,"license_type":"no_license","max_line_length":57,"num_lines":35,"path":"/알고리즘/온라인저지/2022/07/0709/그림.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"from collections import deque\n\n\ndef bfs(y, x):\n Q.append((y, x))\n global maxx # 가장 넓이가 넓은 그림의 넓이 전역변수 선언\n tmp = 0\n while Q:\n y, x = Q.popleft()\n if arr[y][x] == 0: # 이전에 이미 탐색한 지점이면\n continue # 컨티뉴\n arr[y][x] = 0\n tmp += 1 # 해당 그림의 넓이 ++\n for i in range(4):\n ny = y+dy[i]\n nx = x+dx[i]\n if 0<=ny<N and 0<=nx<M and arr[ny][nx]:\n Q.append((ny, nx))\n if tmp > maxx: # 가장 넓이가 넓은 그림을 새로 발견하였으면\n maxx = tmp # 갱신\n\n\ndy = [-1, 1, 0, 0] # 상하좌우 4방향 델타이동\ndx = [0, 0, -1, 1]\nN, M = map(int, input().split())\narr = [list(map(int, input().split())) for _ in range(N)]\nresult = maxx = 0 # 그림의 수, 최대 넓이 초기화\nQ = deque()\nfor n in range(N):\n for m in range(M):\n if arr[n][m]: # 그림을 발견하면\n bfs(n, m) # BFS 탐색\n result += 1 # 그림의 수 ++\nprint(result)\nprint(maxx) "},{"alpha_fraction":0.5760456323623657,"alphanum_fraction":0.5969581604003906,"avg_line_length":20.079999923706055,"blob_id":"3a3e93abeffc14bc2c7f3986239389b37d8b4e99","content_id":"960abd72c5c368955be19857e9f84cc37fcacd60","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":526,"license_type":"no_license","max_line_length":48,"num_lines":25,"path":"/알고리즘/온라인저지/2022/09/0916/나무 자르기.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\n\ndef cut(height):\n cutted = 0\n for tree in trees:\n if tree>height:\n cutted += tree-height\n if cutted>=M: return True\n return False\n\nN, M = map(int, input().rstrip().split())\ntrees = list(map(int, input().rstrip().split()))\nresult = 0\nstart, end = result, int(1e9)\nwhile start<=end:\n mid = (start+end) // 2\n if cut(mid):\n start = mid+1\n result = max(result, mid)\n else: end = mid-1\nprint(result)\n\n# https://www.acmicpc.net/problem/2805"},{"alpha_fraction":0.44978782534599304,"alphanum_fraction":0.4653465449810028,"avg_line_length":29.782608032226562,"blob_id":"4b02b72da6efad7d2bc6b8d62884c29a3a2c7901","content_id":"becd0d4e30c0757154d0b539745fe6048f091518","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":707,"license_type":"no_license","max_line_length":57,"num_lines":23,"path":"/알고리즘/온라인저지/2022/10/1002/친구.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\n\nN = int(input().rstrip())\narr = [input().rstrip() for _ in range(N)]\nfriend_2 = [[] for _ in range(N)]\nfor i in range(N):\n for j in range(N):\n if arr[i][j] == 'Y':\n if j not in friend_2[i]:\n friend_2[i].append(j)\n if i not in friend_2[j]:\n friend_2[j].append(i)\n for k in range(N):\n if arr[j][k] == 'Y' and i != k:\n if k not in friend_2[i]:\n friend_2[i].append(k)\n if i not in friend_2[k]:\n friend_2[k].append(i)\nresult = 0\nfor friend in friend_2: result = max(result, len(friend))\nprint(result)"},{"alpha_fraction":0.6010362505912781,"alphanum_fraction":0.6424870491027832,"avg_line_length":13.923076629638672,"blob_id":"4918a77527c10f744a07eecfae124b838a7700de","content_id":"72f850a6e5c5840b26e15f5e6916ac09a139152e","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":203,"license_type":"no_license","max_line_length":41,"num_lines":13,"path":"/알고리즘/온라인저지/2022/10/1010/NN.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\n\nN, M = map(int, input().rstrip().split())\nprint((str(N)*N)[:M])\n\n\"\"\"\n<참고한 링크>\nhttps://hongku.tistory.com/268\n\"\"\"\n\n# https://www.acmicpc.net/problem/11944"},{"alpha_fraction":0.5444234609603882,"alphanum_fraction":0.5652173757553101,"avg_line_length":21.08333396911621,"blob_id":"a18ac7384da7f8d3b74122d1d4362ce032fb49e6","content_id":"c5cb3185974f5c2aa02e6b853484a47e2793e7ed","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":529,"license_type":"no_license","max_line_length":58,"num_lines":24,"path":"/알고리즘/온라인저지/2022/10/1012/공유기 설치.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\n\ndef install(distance):\n prev = houses[0]\n cnt = 1\n for house in houses[1:]:\n if house>=prev+distance:\n cnt += 1\n prev = house\n return cnt\n\nN, C = map(int, input().rstrip().split())\nhouses = sorted([int(input().rstrip()) for _ in range(N)])\nstart, end = 0, houses[-1]-houses[0]\nresult = 1\nwhile start<=end:\n mid = (start+end) // 2\n if install(mid)>=C:\n result = max(result, mid)\n start = mid+1\n else: end = mid-1\nprint(result)"},{"alpha_fraction":0.4357798099517822,"alphanum_fraction":0.4403669834136963,"avg_line_length":17.25,"blob_id":"8d38edaec428d40691cc989cf6ed61cbb5fadacd","content_id":"4db2cbdd01f2c17507037cf7e87ef7663103a317","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":218,"license_type":"no_license","max_line_length":42,"num_lines":12,"path":"/알고리즘/온라인저지/2022/02/0220/첫 글자를 대문자로.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = int(input())\n\nfor n in range(N):\n text = input()\n\n for i in range(len(text)):\n if i == 0:\n print(text[i].upper(), end='')\n continue\n print(text[i], end='')\n \n print()"},{"alpha_fraction":0.6515151262283325,"alphanum_fraction":0.6666666865348816,"avg_line_length":21.33333396911621,"blob_id":"00877637a2e3b4506b90076de048e4d982e6495c","content_id":"617f1d91833b575e542f8def22b9f2b830802766","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":66,"license_type":"no_license","max_line_length":41,"num_lines":3,"path":"/알고리즘/온라인저지/2022/07/0731/피자 (Small).py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"result = 0\nfor i in range(int(input())): result += i\nprint(result)"},{"alpha_fraction":0.5478261113166809,"alphanum_fraction":0.573913037776947,"avg_line_length":16.769229888916016,"blob_id":"76bb87a5912a81999381510246cd5eba9e955c7f","content_id":"cf8b5c777bb7c12a6fb5fb885c7d7d6957d9eaf0","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":230,"license_type":"no_license","max_line_length":41,"num_lines":13,"path":"/알고리즘/온라인저지/2022/10/1018/싸이클.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\n\nN, P = map(int, input().rstrip().split())\narr = [0]*(P+1)\nflag = False\nnow = N\nwhile not flag:\n now = (now*N)%P\n arr[now] += 1\n if arr[now] == 3: flag = True\nprint(arr.count(2) + 1)"},{"alpha_fraction":0.5064935088157654,"alphanum_fraction":0.5227272510528564,"avg_line_length":16.882352828979492,"blob_id":"9449e0396e6c8fc2d8684b559bb20c1803264dc2","content_id":"5cbc4ec1c7c56f150dee0c11a944afbe3b236727","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":308,"license_type":"no_license","max_line_length":26,"num_lines":17,"path":"/알고리즘/온라인저지/2022/11/1112/보너스 점수.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\n\nN = int(input().rstrip())\nanswer = input().rstrip()\nresult = 0\nbonus = 0\nfor i in range(N):\n if answer[i] == 'X':\n bonus = 0\n elif answer[i] == 'O':\n result += i+1\n result += bonus\n bonus += 1\n # print(bonus)\nprint(result)\n "},{"alpha_fraction":0.4422110617160797,"alphanum_fraction":0.4673366844654083,"avg_line_length":17.18181800842285,"blob_id":"7b63d79d91bb155ffa1defbcad958aaf6bd23220","content_id":"120a4cd802598ef4876facdee0d7fb59f637a969","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":199,"license_type":"no_license","max_line_length":26,"num_lines":11,"path":"/알고리즘/온라인저지/2022/06/0620/가장 큰 금민수.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = int(input())\nresult = 0\nfor n in range(N, -1, -1):\n gms = True\n for s in str(n):\n if s not in '47':\n gms = False\n if gms:\n result = n\n break\nprint(result)"},{"alpha_fraction":0.3533916771411896,"alphanum_fraction":0.37527352571487427,"avg_line_length":49.83333206176758,"blob_id":"911a03edbeb1e0b018f1b5c171f100da51c97895","content_id":"6574bab9eff9851dec609b6a858b8937090b50fe","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1236,"license_type":"no_license","max_line_length":70,"num_lines":18,"path":"/알고리즘/온라인저지/2021/08/0814/ZOAC 2.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"\"\"\"\n시계모양에서 알파벳간에 거리는 ASCII 코드로 |A-B|\n13을 초과하면 26-|A-B|\n\"\"\"\nword = input() # 입력받을 단어\nword = 'A' + word # 단어의 맨 앞에 시작점인 A 추가\ndef zoac(A, B): # 글자간 거리를 구하는 함수 zoac()\n if abs(ord(A)-ord(B)) > 13: # 두 글자의 거리가 13을 초과하면\n result = 26 - abs(ord(A)-ord(B)) # 26에서 거리만큼을 빼줌\n # 한바퀴(26)에서 거리만큼 뒤로 오겠다는 뜻\n else: # 거리가 13아래면\n result = abs(ord(A)-ord(B)) # 거리 = 절대값\n return result # 결과 반환\nsum_word = 0 # 글자간 거리를 더할 변수\nfor i in range(1, len(word)): # 2번째 글자부터 마지막 글자까지\n # 두 글자씩 비교할 것이기 때문\n sum_word += zoac(word[i-1], word[i]) # 글자간 거리들을 변수에 더하고\nprint(sum_word) # 거리들을 더한 값을 출력"},{"alpha_fraction":0.4845360815525055,"alphanum_fraction":0.5154638886451721,"avg_line_length":15.222222328186035,"blob_id":"db968c031f912cd613aba4006f551dca03e93d18","content_id":"253d1d645cb39911c0345829cf5c83d6e3d9f97e","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":291,"license_type":"no_license","max_line_length":33,"num_lines":18,"path":"/알고리즘/온라인저지/2022/02/0203/약수 구하기.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N, K = map(int, input().split())\n\nmeasures = []\n\nfor i in range(1, int(N**0.5)+1):\n if not N%i:\n measures.append(i)\n \ntmp = measures[::-1]\n\nfor t in tmp:\n if N//t != N**0.5:\n measures.append(N//t)\n\nif len(measures) >= K:\n print(measures[K-1])\nelse:\n print(0)"},{"alpha_fraction":0.5076923370361328,"alphanum_fraction":0.5230769515037537,"avg_line_length":11.600000381469727,"blob_id":"ab606376ffdc7d2e4e383e89e98710c91c49647c","content_id":"387bb3870e44cf4ea5cf7bf3f976b158c7a1c08d","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":130,"license_type":"no_license","max_line_length":26,"num_lines":10,"path":"/알고리즘/온라인저지/2022/02/0205/플러그.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = int(input())\n\nresult = 0\n\nfor n in range(N):\n if result:\n result -= 1\n result += int(input())\n\nprint(result)\n "},{"alpha_fraction":0.49295774102211,"alphanum_fraction":0.49295774102211,"avg_line_length":19.428571701049805,"blob_id":"9eaebedf8599d6348bab3f7c540db90d8f2a41df","content_id":"4b5bb8aee58a6cdbc58e45bc82172d3200af3c02","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":142,"license_type":"no_license","max_line_length":29,"num_lines":7,"path":"/알고리즘/온라인저지/2021/08/0814/문자열반복.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"T = int(input())\nfor t in range(T):\n R, word = input().split()\n R = int(R)\n for wor in word:\n print(wor*R, end='')\n print()"},{"alpha_fraction":0.5189003348350525,"alphanum_fraction":0.5257731676101685,"avg_line_length":23.33333396911621,"blob_id":"1703bdb343ec8af2476b537a8ec9b6d55fd2b84d","content_id":"8f7a4b05798177ca5a4b5840c6e46d1f2934479f","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":291,"license_type":"no_license","max_line_length":57,"num_lines":12,"path":"/알고리즘/온라인저지/2022/04/0412/질투진서.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N, A, B = map(int, input().split())\narr = [list(map(int, input().split())) for _ in range(N)]\n# print(arr)\nA, B = A-1, B-1\nresult = 'HAPPY'\nfor a in arr[A]:\n if a > arr[A][B]:\n result = 'ANGRY'\nfor i in range(N):\n if arr[i][B] > arr[A][B]:\n result = 'ANGRY'\nprint(result)"},{"alpha_fraction":0.5368421077728271,"alphanum_fraction":0.5368421077728271,"avg_line_length":16.363636016845703,"blob_id":"41105922ce4a87432bc94c8f3ace7e710b55b4c6","content_id":"ade66cae6231cac0d60201001c70cdf12b8131f8","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":190,"license_type":"no_license","max_line_length":44,"num_lines":11,"path":"/알고리즘/온라인저지/2022/09/0927/백대열.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\n\ndef gcd(a, b):\n while a%b: a, b = b, a%b\n return b\n\nN, M = map(int, input().rstrip().split(':'))\nG = gcd(N, M)\nprint('{}:{}'.format(N//G, M//G))"},{"alpha_fraction":0.37987011671066284,"alphanum_fraction":0.3874458968639374,"avg_line_length":21.0238094329834,"blob_id":"769f02edc8b38b2c4980a4a772f32c0348e5aef6","content_id":"4ce566aa035a8155f29f31c58286a392c2561a5c","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":924,"license_type":"no_license","max_line_length":56,"num_lines":42,"path":"/알고리즘/온라인저지/2021/10/1016/AC.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"from collections import deque\nimport sys\n\nT = int(sys.stdin.readline())\n\nfor t in range(T):\n order = sys.stdin.readline().rstrip()\n order.replace('RR', '')\n N = int(sys.stdin.readline())\n arr = sys.stdin.readline().rstrip()[1:-1].split(',')\n q = deque(arr)\n\n rev, left, right = False, 0, len(q)-1\n flag = False\n\n if N == 0:\n q = []\n right = 0\n\n for o in order:\n if o == 'R':\n if rev:\n rev = False\n else:\n rev = True\n elif o == 'D':\n if len(q) < 1:\n flag = True\n print('error')\n break\n else:\n if rev:\n q.pop()\n else:\n q.popleft()\n \n if not flag:\n if rev:\n q.reverse()\n print('['+','.join(q)+']')\n else:\n print('['+','.join(q)+']')"},{"alpha_fraction":0.4639175236225128,"alphanum_fraction":0.5103092789649963,"avg_line_length":16.727272033691406,"blob_id":"ec9d3bad09e8647d5b5847c420b6243e65fe7e18","content_id":"e3c28ba3d6a2218b345e48b486549e6990ff52ba","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":194,"license_type":"no_license","max_line_length":26,"num_lines":11,"path":"/알고리즘/온라인저지/2022/06/0604/신기한 수.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"# print(list(str(392)))\nN = int(input())\ni = 1\nresult = 0\nfor n in range(1, N+1):\n tmp = 0\n for j in list(str(n)):\n tmp += int(j)\n if not n%tmp:\n result += 1\nprint(result)"},{"alpha_fraction":0.4649122953414917,"alphanum_fraction":0.5175438523292542,"avg_line_length":15.428571701049805,"blob_id":"78006e23c92c804515c288f022cf001bb238f1d5","content_id":"b5142fe3d6f95811beeeda813722d1a7776dce6c","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":114,"license_type":"no_license","max_line_length":42,"num_lines":7,"path":"/알고리즘/온라인저지/2023/03/0331/Máquina de café.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"A = int(input())\nB = int(input())\nC = int(input())\n\nresult = [A*4 + B*2, A*2 + C*2, B*2 + C*4]\n\nprint(min(result))"},{"alpha_fraction":0.6237623691558838,"alphanum_fraction":0.6237623691558838,"avg_line_length":13.571428298950195,"blob_id":"99742ea043268f0a915fb625b4ac8ab22db8fab2","content_id":"d94d37bbbc84c5dea789b5b5ae551ae6490c876d","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":101,"license_type":"no_license","max_line_length":28,"num_lines":7,"path":"/알고리즘/온라인저지/2022/11/1121/CAPS.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\n\nS = input().rstrip()\nfor s in S:\n print(s.upper(), end='')"},{"alpha_fraction":0.42718446254730225,"alphanum_fraction":0.45436891913414,"avg_line_length":21.434782028198242,"blob_id":"08fb6100f1a847f5129a0eabe4427e3861143123","content_id":"44c22493c8bde902c54c7164af3a042d46361f43","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":515,"license_type":"no_license","max_line_length":35,"num_lines":23,"path":"/알고리즘/온라인저지/2022/03/0330/카드놀이.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"A = list(map(int, input().split()))\nB = list(map(int, input().split()))\npoint = [0, 0]\nwinner = ''\nall_draw = True\nfor i in range(len(A)):\n if A[i] > B[i]:\n point[0] += 3\n all_draw = False\n if point[0] >= point[1]:\n winner = 'A'\n elif A[i] < B[i]:\n point[1] += 3\n all_draw = False\n if point[0] <= point[1]:\n winner = 'B'\n elif A[i] == B[i]:\n point[0] += 1\n point[1] += 1\nif all_draw:\n winner = 'D'\nprint(*point)\nprint(winner)"},{"alpha_fraction":0.5875576138496399,"alphanum_fraction":0.6059907674789429,"avg_line_length":38.54545593261719,"blob_id":"3038b28ece597c614a7e819b1ffd65a1fccbe94f","content_id":"d007ea2b5b54003d84ffdfc84443fe7abb96ab19","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":698,"license_type":"no_license","max_line_length":65,"num_lines":11,"path":"/알고리즘/온라인저지/2021/08/0803/곱셈.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"a = int(input()) # a를 정수로 입력받고\nb = input() # b를 str 그대로 입력받아서\nc = 1 * int(b) # c에 b를 백업해두고\nb = list(b) # b는 리스트로 ['3', '8', '5']로 만들어 준 다음\ncalc_list = [] # 각각의 계산값들을 더해서 리스트에 [0], [1], [2]에 저장할 리스트를 만들어주고\nfor i in range(3): # 리스트를 순회하면서 \n calc_list.append(a * int(b[i])) # 각각 자릿수를 곱한 값들을 구해서 저장\ncalc_list.reverse() # 결과값들을 뒤집어서\nfor calc in calc_list: # 결과값 리스트를 순회하면서\n print(calc) # 출력\nprint(a * c) # 마지막에 백업해놓은 원래b값과 a값을 곱해서 출력"},{"alpha_fraction":0.4900990128517151,"alphanum_fraction":0.5198019742965698,"avg_line_length":21.55555534362793,"blob_id":"126441bc363e14c180360d481e423f84dfadeb94","content_id":"5e225fc797a5de15c56d34b167a9c4221030e3fa","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":202,"license_type":"no_license","max_line_length":43,"num_lines":9,"path":"/알고리즘/온라인저지/2022/08/0827/Square Pasture.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"X = []\nY = []\nfor _ in range(2):\n tmp = list(map(int, input().split()))\n X.append(tmp[0])\n Y.append(tmp[1])\n X.append(tmp[2])\n Y.append(tmp[3])\nprint(max(max(X)-min(X), max(Y)-min(Y))**2)"},{"alpha_fraction":0.40077072381973267,"alphanum_fraction":0.42581889033317566,"avg_line_length":19,"blob_id":"64aae3888b6474eb53faa4abcb924191ac01c86a","content_id":"aef03e4b65529dc5bcd80381cb248fab3113bb73","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":519,"license_type":"no_license","max_line_length":45,"num_lines":26,"path":"/알고리즘/SWEA/LEARN/Course/2. Programming Intermediate/1. 파이썬 SW문제해결 기본 List1/8차시 1일차 - 숫자 카드.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"T = int(input())\n\nfor t in range(1, T+1):\n N = int(input())\n\n counts = [0] * (10)\n\n num = input()\n \n for n in num:\n counts[int(n)] += 1\n \n cnt = 0\n result = 0\n\n if counts.count(max(counts)) == 1:\n result = counts.index(max(counts))\n cnt = max(counts)\n else: # != 1\n for i in range(9, -1, -1):\n if counts[i] == max(counts):\n result = i\n cnt = counts[i]\n break\n\n print('#{} {} {}'.format(t, result, cnt))"},{"alpha_fraction":0.47037702798843384,"alphanum_fraction":0.4955116808414459,"avg_line_length":20.461538314819336,"blob_id":"aed8a86468c1912102969352622e717e97f5836e","content_id":"ee94a2b99e64f93f42fbcbf44a6b9f5a091bb32d","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":557,"license_type":"no_license","max_line_length":51,"num_lines":26,"path":"/알고리즘/온라인저지/2023/02/0226/인간-컴퓨터 상호작용.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\n\nS = input().strip()\nprefix_sum = [[0]*26 for _ in range(len(S))]\n\nfor i in range(len(S)):\n for j in range(26):\n idx = ord(S[i])-97\n \n if idx == j:\n prefix_sum[i][j] = prefix_sum[i-1][j]+1\n else:\n prefix_sum[i][j] = prefix_sum[i-1][j]\n\nfor _ in range(int(input().strip())):\n A, L, R = input().strip().split()\n L, R = map(int, (L, R))\n\n idx = ord(A)-97\n result = prefix_sum[R][idx]\n if L != 0:\n result -= prefix_sum[L-1][idx]\n\n print(result)"},{"alpha_fraction":0.41981130838394165,"alphanum_fraction":0.4811320900917053,"avg_line_length":16.75,"blob_id":"a371b57874b1fcd826e79f939671ab8fc7d7fe80","content_id":"b8d8d5245f6269533ccf2d2c0693a915f98b5cfd","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":212,"license_type":"no_license","max_line_length":24,"num_lines":12,"path":"/알고리즘/온라인저지/2023/03/0315/Tournament Selection.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"result = -1\ncnt = 0\nfor _ in range(6):\n if input() == 'W':\n cnt += 1\nif cnt == 1 or cnt == 2:\n result = 3\nif cnt == 3 or cnt == 4:\n result = 2\nif cnt == 5 or cnt == 6:\n result = 1\nprint(result)"},{"alpha_fraction":0.6127819418907166,"alphanum_fraction":0.6278195381164551,"avg_line_length":25.700000762939453,"blob_id":"b20d00cba5299247d7a20f8389e0a10e06db7355","content_id":"6be19f47a64a3858d760879f0f1baa0aee2c1731","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":266,"license_type":"no_license","max_line_length":89,"num_lines":10,"path":"/알고리즘/온라인저지/2022/12/1228/2009년.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"from datetime import datetime, date\n\n\ndef what_day_is_it(date):\n days = ['Monday', 'Tuesday', 'Wednesday', 'Thursday', 'Friday', 'Saturday', 'Sunday']\n day = date.weekday()\n print(days[day])\n\nD, M = map(int, input().split())\nwhat_day_is_it(date(2009, M, D))"},{"alpha_fraction":0.5090909004211426,"alphanum_fraction":0.5181818008422852,"avg_line_length":26.75,"blob_id":"61dc20bc2f7d6512cac558dfa6a5ded2202e5eca","content_id":"2f76d270a6241e27e07102e6e888feda31ed6b39","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":110,"license_type":"no_license","max_line_length":34,"num_lines":4,"path":"/알고리즘/온라인저지/2023/06/0602/Oddities.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"result = ['even', 'odd']\nfor _ in range(int(input())):\n X = int(input())\n print(f'{X} is {result[X%2]}')"},{"alpha_fraction":0.5087336301803589,"alphanum_fraction":0.539301335811615,"avg_line_length":20.85714340209961,"blob_id":"a0275f9e30570eaf2de1467cba760dcd56060944","content_id":"bc18ac8001dd741704bb93da1e6ee733e2b550a3","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":458,"license_type":"no_license","max_line_length":71,"num_lines":21,"path":"/알고리즘/온라인저지/2022/10/1003/올림픽.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\n\nN, K = map(int, input().rstrip().split())\narr = []\nfor n in range(N): arr.append(list(map(int, input().rstrip().split())))\narr.sort(key=lambda x:(-x[1], -x[2], -x[3]))\nprev = arr[0][1:]\nrank = 1\nstep = 0\nresult = 1\nfor i in range(1, N):\n now = arr[i][1:]\n if now != prev: \n rank += 1+step\n prev = now[:]\n step = 0\n else: step += 1\n if arr[i][0] == K: result = rank; break\nprint(result)"},{"alpha_fraction":0.523809552192688,"alphanum_fraction":0.5555555820465088,"avg_line_length":24.399999618530273,"blob_id":"dfc0f7c73b3897bb39c82c577e8f9fd9c8ae4736","content_id":"9286afeb85c69592efd21df79bd29c676415dd74","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":126,"license_type":"no_license","max_line_length":35,"num_lines":5,"path":"/알고리즘/온라인저지/2022/12/1202/3000번 버스.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"for _ in range(int(input())):\n result = 1\n for i in range(int(input())-1):\n result = result*2+1\n print(result)"},{"alpha_fraction":0.4647887349128723,"alphanum_fraction":0.48826292157173157,"avg_line_length":25.75,"blob_id":"f4e1ba7a9ee0342d8c2a53877caec5f68ab65536","content_id":"5fcf237c8d826108c5611ea0abc552ef1b800b00","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":213,"license_type":"no_license","max_line_length":53,"num_lines":8,"path":"/알고리즘/온라인저지/2022/12/1215/IBM 빼기 1.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = int(input())\nfor tc in range(1, N+1):\n print('String #{}'.format(tc))\n for i in input():\n tmp = ord(i)+1\n print(chr(tmp) if tmp <= 90 else 'A', end='')\n if tc == N: break\n print('\\n')"},{"alpha_fraction":0.5736842155456543,"alphanum_fraction":0.6052631735801697,"avg_line_length":20.22222137451172,"blob_id":"48fa14d179b07878114af8fa688e7f07997243aa","content_id":"ff1400aa71db5a8f38a30eb0ca9760660ac8eac9","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":190,"license_type":"no_license","max_line_length":56,"num_lines":9,"path":"/알고리즘/온라인저지/2023/02/0204/끝말잇기.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"input()\nresult = 1\nwords = input().split()\npalindrome = words[0][0]\nfor word in words:\n if word[0] != palindrome or word[-1] != palindrome: \n result = 0\n break\nprint(result)"},{"alpha_fraction":0.5263158082962036,"alphanum_fraction":0.5263158082962036,"avg_line_length":24.5,"blob_id":"06c1e29cc75609b090847c86d43b1bdeacd0ae34","content_id":"5590086b8620ad2f2f2a3e53b8625e85685d8907","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":152,"license_type":"no_license","max_line_length":42,"num_lines":6,"path":"/알고리즘/온라인저지/2023/01/0107/사탕 선생 고창영.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"T = int(input())\nfor t in range(T):\n input()\n N = int(input())\n arr = [int(input()) for _ in range(N)]\n print('NO' if sum(arr)%N else 'YES')"},{"alpha_fraction":0.6027088165283203,"alphanum_fraction":0.6139954924583435,"avg_line_length":25.117647171020508,"blob_id":"cb15499481384f67ce6d7be19b79140827ecedfc","content_id":"35293e16c7169ad9befdd6333433fdada4b8cdb4","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":589,"license_type":"no_license","max_line_length":66,"num_lines":17,"path":"/알고리즘/온라인저지/2022/11/1113/최소 회의실 개수.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\nimport heapq\n\ninput = sys.stdin.readline\n\nN = int(input())\narr = [list(map(int, input().rstrip().split())) for _ in range(N)]\narr.sort(key=lambda x:x[0]) # 회의 시작 시간 기준 오름차순 정렬\nrooms = [0] # 비어있는 회의실 하나로 시작\nresult = 1 # 회의실은 한 개 이상 반드시 필요하다\nfor s, e in arr:\n if s >= rooms[0]: # 빈 회의실이 있다면\n heapq.heappop(rooms)\n else: # 빈 회의실이 없다면\n result += 1 # 최소 회의실 개수 추가\n heapq.heappush(rooms, e) # 회의를 시작하지\nprint(result)"},{"alpha_fraction":0.4049079716205597,"alphanum_fraction":0.4171779155731201,"avg_line_length":18.235294342041016,"blob_id":"2a6ea32fdd66642bbe0e9562aaa155878592a4c0","content_id":"c73a338b7051d98a9530f1da4753e01175510364","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":326,"license_type":"no_license","max_line_length":41,"num_lines":17,"path":"/알고리즘/온라인저지/2022/06/0602/양념 반 후라이드 반.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"A, B, C, X, Y = map(int, input().split())\nx = min(X, Y)\ny = max(X, Y)\nresult = 0\nif C > (A+B)//2:\n result += A*X + B*Y\nelse:\n result += C*x*2\n if X != Y:\n if X > Y:\n result += A*(y-x)\n else:\n result += B*(y-x)\n tmp = C*y*2\n if result > tmp:\n result = tmp\nprint(result)"},{"alpha_fraction":0.35305342078208923,"alphanum_fraction":0.4236641228199005,"avg_line_length":17.75,"blob_id":"fe906653bdfe93056c1e7e1c26a7f7eed12401e1","content_id":"0637b9a16ce27162b9fd105ad5699ac80f84f5c9","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":524,"license_type":"no_license","max_line_length":36,"num_lines":28,"path":"/알고리즘/온라인저지/2022/03/0321/8진수 2진수.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"def oct_to_bin(x):\n global result\n dictt = {\n '0': '000',\n '1': '001',\n '2': '010',\n '3': '011',\n '4': '100',\n '5': '101',\n '6': '110',\n '7': '111',\n }\n # print(dictt[x])\n return dictt[x]\n\nN = input()\nif N == '0':\n print(0)\n exit()\n# print(N, len(N))\nresult = [''] * (len(N))\n# print(result)\nfor i in range(len(N)):\n result[i] = oct_to_bin(N[i])\n # print(result)\nprint(result[0].lstrip('0'), end='')\nfor r in result[1:]:\n print(r, end='')"},{"alpha_fraction":0.52173912525177,"alphanum_fraction":0.539130449295044,"avg_line_length":13.5,"blob_id":"0ffca1c2cba7af7d38899a033652919e9ca9935e","content_id":"32a8cec44ca606761a704c94dda891ee177719c8","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":137,"license_type":"no_license","max_line_length":44,"num_lines":8,"path":"/알고리즘/SWEA/LEARN/Course/1. Programming Beginner/파이썬 프로그래밍 기초(2)/6차시 2. 자료구조 – 리스트, 튜플 - 연습문제 4.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"l = []\n\nfor i in range(5):\n l.append(int(input()))\n\navg = sum(l)/5\n\nprint('입력된 값 {}의 평균은 {}입니다.'.format(l, avg))"},{"alpha_fraction":0.4297872483730316,"alphanum_fraction":0.47659575939178467,"avg_line_length":22.600000381469727,"blob_id":"02d63904efaa4e50d16b1f03247fe37a6cd547ce","content_id":"ea0ce9d749ad30b4e9f4bd1836cd76ccdc14e8fa","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":235,"license_type":"no_license","max_line_length":41,"num_lines":10,"path":"/알고리즘/온라인저지/2022/08/0827/럭비 클럽.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"result = ['Senior', 'Junior']\nwhile True:\n tmp = input()\n if tmp == '# 0 0': break\n M = tmp.split()\n print(M[0], end=' ')\n if int(M[1]) > 17 or int(M[2]) >= 80:\n print(result[0])\n else:\n print(result[1])"},{"alpha_fraction":0.48630136251449585,"alphanum_fraction":0.4931506812572479,"avg_line_length":11.166666984558105,"blob_id":"c4f7639e34470782d29768e0016833d1f3852b8e","content_id":"9a980c670a15c519fdd03c50afc98d7a17f3432c","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":146,"license_type":"no_license","max_line_length":18,"num_lines":12,"path":"/알고리즘/온라인저지/2021/12/1213/소음.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"A = int(input())\nope = input()\nB = int(input())\n\nresult = 0\n\nif ope == '+':\n result = A + B\nelif ope == '*':\n result = A * B\n\nprint(result)\n"},{"alpha_fraction":0.4037036895751953,"alphanum_fraction":0.4185185134410858,"avg_line_length":21.58333396911621,"blob_id":"609539741264b02181e82177bc6ca33fdfde4e18","content_id":"55e7826b75a2500ccbc42998a034884566e65dad","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":270,"license_type":"no_license","max_line_length":33,"num_lines":12,"path":"/알고리즘/온라인저지/2023/04/0403/헤라클레스와 히드라.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"K = int(input())\nfor tc in range(1, K+1):\n H = int(input())\n action = input()\n for a in action:\n if H:\n if a == 'c': H += 1\n elif a == 'b': H -= 1\n else: break\n print(f'Data Set {tc}:')\n print(H)\n if tc != K: print()"},{"alpha_fraction":0.3520749807357788,"alphanum_fraction":0.3627844750881195,"avg_line_length":43,"blob_id":"8cc834de00fedce201770fc9a60d29d84a773398","content_id":"eff96d7ea2361b9e9efdb761caad8fbae22a3604","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1013,"license_type":"no_license","max_line_length":64,"num_lines":17,"path":"/알고리즘/온라인저지/2021/08/0813/컵홀더.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"\"\"\"\n컵홀더 개수 = 좌석수 - 커플석 개수 + 1\n리스트 받아서 while문으로 리스트 탐색\n\"\"\"\nN = int(input()) # 좌석 수\nseats = list(input()) # 좌석 리스트\ni = 0 # 좌석 리스트 탐색 인덱스\ncouple_go_to_hell = 0 # 커플석 개수 카운트\nwhile i != len(seats): # 좌석 탐색 반복\n if seats[i] == 'L': # 자리가 커플석이면\n couple_go_to_hell += 1 # 커플석 카운트\n i += 1 # 옆칸도 커플석이니까 한 칸 패스\n i += 1 # 다음 좌석으로 ㄱㄱ\nif N <= N - couple_go_to_hell + 1: # 커플석이 없으면\n print(N) # 그냥 좌석수 출력\nelse: # 커플석이 많아서 컵홀더가 좌석보다 적으면\n print(N - couple_go_to_hell + 1) # 컵홀더개수 출력"},{"alpha_fraction":0.48120301961898804,"alphanum_fraction":0.5037593841552734,"avg_line_length":25.799999237060547,"blob_id":"cc2f98d981d8cd0f0f0fc4bf6cc8b3426c92eeb4","content_id":"066b1a686c24fd6e83ccaec74b26f921a3194690","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":133,"license_type":"no_license","max_line_length":36,"num_lines":5,"path":"/알고리즘/온라인저지/2022/08/0814/Abdelrahman.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"T = int(input())\nfor t in range(1, T+1):\n N, M = map(int, input().split())\n result = M - (N-1)\n print(f'Case {t}: {result}')"},{"alpha_fraction":0.4912280738353729,"alphanum_fraction":0.5065789222717285,"avg_line_length":23.052631378173828,"blob_id":"73f4238470095f5afc28767fa20ba1413d39b1e7","content_id":"7d34eb6cdb689eb8e038ba1b097bed082d77c682","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":456,"license_type":"no_license","max_line_length":38,"num_lines":19,"path":"/알고리즘/온라인저지/2023/01/0104/친구.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N, M = map(int, input().split())\ndictt = {}\nfor n in range(1, N+1):\n dictt[n] = set()\nfor _ in range(M):\n A, B = map(int, input().split())\n dictt[A].add(B)\n dictt[B].add(A)\nfor n in range(1, N+1):\n print(len(dictt[n]))\n\n# N, M = map(int, input().split())\n# arr = [set() for _ in range(N+1)]\n# for m in range(M):\n# A, B = map(int, input().split())\n# arr[A].add(B)\n# arr[B].add(A)\n# for n in range(1, N+1):\n# print(len(arr[n]))"},{"alpha_fraction":0.44999998807907104,"alphanum_fraction":0.5,"avg_line_length":17.81818199157715,"blob_id":"27df47c51cb1b1cba93d06622823b436fa082b35","content_id":"d54622dff050a05e0c029a49c176223e9022cc9a","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":840,"license_type":"no_license","max_line_length":63,"num_lines":33,"path":"/알고리즘/온라인저지/2021/07/0731/성실한 개미.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"num = 10\nboard = [[int(x) for x in input().split()] for y in range(num)]\n # 10 * 10 배열 받기\n\"\"\"\n스타트는 고정\n개미가 있는 자리가 0이면 \n 있는 자리를 9로 바꾸고\n 그 오른쪽칸이 1이면 다음 경로를 한칸 아래로\n 그 외에는 오른쪽으로\n 2가 있는 자리에 도착할건데 만약 아닐수 있으니\n 2인지 확인하고 9로 바꿔주고 코드 종료\n\"\"\"\n# 개미의 x, y좌표\n# 인덱스에서는 [y][x]로 호출해야함\ny = 1\nx = 1\nant = board[y][x]\n\nwhile board[y][x] == 0:\n board[y][x] = 9\n if board[y][x+1] == 1:\n y += 1\n elif board[y][x+1] == 0:\n x += 1\n elif board[y][x+1] == 2:\n x += 1\nif board[y][x] == 2:\n board[y][x] = 9\n\nfor i in range(10):\n for j in range(10): \n print(board[i][j], end=' ')\n print() # 출력문"},{"alpha_fraction":0.4735516309738159,"alphanum_fraction":0.508816123008728,"avg_line_length":14.920000076293945,"blob_id":"f8164e7aae03792885c6b87ce456f7ad275e5d15","content_id":"16502a4146021495b31a0e993b8701743b9f709d","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":397,"license_type":"no_license","max_line_length":39,"num_lines":25,"path":"/알고리즘/온라인저지/2022/01/0131/부녀회장이 될테야.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"T = int(input())\n\nks = []\nns = []\n\nfor t in range(T):\n ks.append(int(input()))\n ns.append(int(input()))\n\nmaxk = max(ks)\nmaxn = max(ns)\n\na = [[0]*maxn for _ in range(maxk+1)]\n\na[0] = list(range(1, maxn+1))\n\nfor i in range(maxk+1):\n a[i][0] = 1\n\nfor i in range(1, maxk+1):\n for j in range(1, maxn):\n a[i][j] = a[i][j-1] + a[i-1][j]\n\nfor t in range(T):\n print(a[ks[t]][ns[t]-1])"},{"alpha_fraction":0.5095447897911072,"alphanum_fraction":0.5433186292648315,"avg_line_length":28.65217399597168,"blob_id":"1d7a8d8f9315853df1c2fa934226c96939dacf54","content_id":"144e58f823f09ccd8f27229db96577726501c8a9","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":681,"license_type":"no_license","max_line_length":59,"num_lines":23,"path":"/알고리즘/온라인저지/2022/11/1114/중간계 전쟁.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\n\ngandalf = [1, 2, 3, 3, 4, 10]\nsauron = [1, 2, 2, 2, 3, 5, 10]\nfor tc in range(1, int(input().rstrip())+1):\n G = S = 0\n gandalf_army = list(map(int, input().rstrip().split()))\n for i in range(6):\n G += gandalf[i]*gandalf_army[i]\n sauron_army = list(map(int, input().rstrip().split()))\n for i in range(7):\n S += sauron[i]*sauron_army[i]\n result = [\n 'No victor on this battle field', # draw\n 'Good triumphs over Evil', # gandalf win\n 'Evil eradicates all trace of Good', # sauron win\n ]\n i = 0\n if G > S: i = 1\n elif G < S: i = 2\n print('Battle {}: {}'.format(tc, result[i]))"},{"alpha_fraction":0.5714285969734192,"alphanum_fraction":0.5789473652839661,"avg_line_length":21.33333396911621,"blob_id":"44ef0dabf4d89191120e9322ea20c69895822e9e","content_id":"fb929a41de7ed1d07bc3ac86b303731aaf2ee064","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":133,"license_type":"no_license","max_line_length":41,"num_lines":6,"path":"/알고리즘/온라인저지/2023/05/0531/오버플로우와 모듈러.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N, M = map(int, input().split())\nresult = 1\nfor i in list(map(int, input().split())):\n result *= i%M\n result %= M\nprint(result)"},{"alpha_fraction":0.5465465188026428,"alphanum_fraction":0.5705705881118774,"avg_line_length":21.266666412353516,"blob_id":"0a99b8bed350199c86e028108367a35c9ad79215","content_id":"69d19f44fe94bb0697854c8a370c0b885952f3fd","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":333,"license_type":"no_license","max_line_length":39,"num_lines":15,"path":"/알고리즘/온라인저지/2021/08/0814/음계.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"notes = list(map(int, input().split()))\nascending = 0\ndescending = 0\nfor i in range(1, len(notes)):\n if notes[i-1] < notes[i]:\n ascending += 1\n else:\n descending += 1\nif ascending != 0 and descending != 0:\n print('mixed')\nelse:\n if ascending:\n print('ascending')\n else:\n print('descending')"},{"alpha_fraction":0.43448275327682495,"alphanum_fraction":0.4689655303955078,"avg_line_length":19.85714340209961,"blob_id":"b04fba16166df29c221b5d00184e9acb22be15f2","content_id":"ce8c0ed6cec8ac6912d86ef650be66549c3e2e5e","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":145,"license_type":"no_license","max_line_length":39,"num_lines":7,"path":"/알고리즘/온라인저지/2022/02/0207/카이사르 암호.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"word = input()\n\nfor w in word:\n if ord(w)-3 < ord('A'):\n print(chr(ord(w)-3+26), end='')\n else:\n print(chr(ord(w)-3), end='')"},{"alpha_fraction":0.3789346218109131,"alphanum_fraction":0.39830508828163147,"avg_line_length":18.690475463867188,"blob_id":"87b794f2384746ab712e13c8cb075e2fa93092a3","content_id":"265e74ebcb1b3d3677c2f87d75289616b159e6f6","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":826,"license_type":"no_license","max_line_length":45,"num_lines":42,"path":"/알고리즘/SWEA/LEARN/Course/2. Programming Intermediate/6. 파이썬 SW문제해결 기본 Queue/8차시 6일차 - 노드의 거리.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"T = int(input())\n\nfor t in range(1, T+1):\n V, E = map(int, input().split())\n \n arr = [[] for _ in range(V+1)]\n\n for e in range(E):\n a, b = map(int, input().split())\n arr[a].append(b)\n arr[b].append(a)\n \n S, G = map(int, input().split())\n\n visited = [0] * (V+1)\n cnt = 0\n\n q = [arr[S]+[cnt]]\n visited[S] = 1\n result = 0\n found = False\n\n while q:\n tmp = q.pop(0)\n cnt = tmp[-1]\n if found:\n break\n\n for i in range(len(tmp)-1):\n if tmp[i] == G:\n result = cnt+1\n found = True\n break\n\n if visited[tmp[i]] == 0:\n q.append(arr[tmp[i]]+[cnt+1])\n visited[tmp[i]] = 1\n\n if S == G:\n result = 0\n\n print('#{} {}'.format(t, result))"},{"alpha_fraction":0.3980582654476166,"alphanum_fraction":0.4417475759983063,"avg_line_length":33.5,"blob_id":"074d601470bd3339232040a939dd18dd09d237b9","content_id":"6f6693ce788e50fbbeab0717c4e0ca5be097803d","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":306,"license_type":"no_license","max_line_length":53,"num_lines":6,"path":"/알고리즘/온라인저지/2021/07/0730/[기초-산술연산] 정수 2개 입력받아 차 계산하기.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"a = input() # -> 123\nb = input() # -> -123\nc = int(a) - int(b) # 입력받은 문자열 a와 b를 int로 바꿔주고 뻴셈\nprint(c) # -> 246\n# 깃, 커밋은 양보다 질\n# 한 문제를 올려도, 정말 고민하고 의미있게 풀은 문제들을 올리자"},{"alpha_fraction":0.5729166865348816,"alphanum_fraction":0.5763888955116272,"avg_line_length":21.230770111083984,"blob_id":"6d3d751f018fb0ce3334b74fd1beaa0ac3a42ba9","content_id":"6610edd5b21e7fac78a568fa6c20e12dfb9d90f6","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":288,"license_type":"no_license","max_line_length":40,"num_lines":13,"path":"/알고리즘/온라인저지/2022/12/1204/파일 완전 삭제.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = int(input())\nfiles = list(map(int, list(input())))\nresult = ''\nfor i in range(len(files)):\n if N%2:\n result += str(int(not files[i]))\n else:\n result += str(files[i])\ntmp = input()\nif result == tmp:\n print('Deletion succeeded')\nelse:\n print('Deletion failed')"},{"alpha_fraction":0.5380434989929199,"alphanum_fraction":0.570652186870575,"avg_line_length":19.55555534362793,"blob_id":"97a8785a82727cefada1319277f22dfe712284fc","content_id":"41e60587370956a8762eeb785b45ee431a3d4215","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":184,"license_type":"no_license","max_line_length":45,"num_lines":9,"path":"/알고리즘/온라인저지/2023/03/0308/노 땡스!.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = int(input())\narr = sorted(list(map(int, input().split())))\nlast_plus_1 = 0\nresult = 0\nfor a in arr:\n if a != last_plus_1:\n result += a\n last_plus_1 = a+1\nprint(result)"},{"alpha_fraction":0.5068492889404297,"alphanum_fraction":0.5369862914085388,"avg_line_length":17.299999237060547,"blob_id":"5674f65e6c276720abef73f6eef229b84963d3dc","content_id":"4c6f05b2b4a6e283efde43654841a258c98a3f74","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":365,"license_type":"no_license","max_line_length":36,"num_lines":20,"path":"/알고리즘/온라인저지/2022/07/0712/트리의 부모 찾기.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\nsys.setrecursionlimit(99999)\n\n\ndef dfs(i):\n for n in nodes[i]:\n if not parents[n]:\n parents[n] = i\n dfs(n)\n\n\nN = int(input())\nnodes = [[] for _ in range(N+1)]\nparents = [0] * (N+1)\nfor n in range(N-1):\n s, e = map(int, input().split())\n nodes[s].append(e)\n nodes[e].append(s)\ndfs(1)\nfor p in parents[2:]: print(p)"},{"alpha_fraction":0.38985738158226013,"alphanum_fraction":0.4088748097419739,"avg_line_length":22.370370864868164,"blob_id":"d5e77ae4f623572b1ace0c7e6fbc619cb623356f","content_id":"cedb0cc1c95bb36174d8034faea9734680b72c64","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":631,"license_type":"no_license","max_line_length":45,"num_lines":27,"path":"/알고리즘/온라인저지/2021/08/0822/딱지놀이.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = int(input())\nfor tc in range(N):\n A_cards = list(map(int, input().split()))\n A_count = A_cards.pop(0)\n B_cards = list(map(int, input().split()))\n B_count = B_cards.pop(0)\n A_cards.sort()\n B_cards.sort()\n A = [0] * 5 \n B = [0] * 5\n for a in A_cards:\n A[a] += 1\n for b in B_cards:\n B[b] += 1\n winner = ''\n for i in range(4, -1, -1):\n if i == 0:\n winner = 'D'\n if A[i] > B[i]:\n winner = 'A'\n break\n elif A[i] == B[i]:\n continue\n elif A[i] < B[i]:\n winner = 'B'\n break\n print(winner)\n"},{"alpha_fraction":0.5591397881507874,"alphanum_fraction":0.5806451439857483,"avg_line_length":17.799999237060547,"blob_id":"654d1ed2b9eb1322656e01ae0932c1719a69a8c9","content_id":"c850664c96342e3368085908d7532bbae9f40ab7","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":93,"license_type":"no_license","max_line_length":32,"num_lines":5,"path":"/알고리즘/온라인저지/2022/09/0907/母音を数える (Counting Vowels).py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N, S = input(), input()\nresult = 0\nfor s in S:\n if s in 'aeiou': result += 1\nprint(result)"},{"alpha_fraction":0.540123462677002,"alphanum_fraction":0.595678985118866,"avg_line_length":39.625,"blob_id":"59376e7d942beffa1ca176e04b9526eed994e2e8","content_id":"b3b651ee76c6ab01914d2e04379e2fa0a01b255e","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":324,"license_type":"no_license","max_line_length":58,"num_lines":8,"path":"/알고리즘/온라인저지/2022/10/1012/Mini Fantasy War.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"for _ in range(int(input())):\n inputs = list(map(int, input().split()))\n stats = []\n stats.append(max(1, inputs[0]+inputs[4]))\n stats.append(max(1, inputs[1]+inputs[5]))\n stats.append(max(0, inputs[2]+inputs[6]))\n stats.append(inputs[3]+inputs[7])\n print(stats[0] + stats[1]*5 + stats[2]*2 + stats[3]*2)"},{"alpha_fraction":0.4203979969024658,"alphanum_fraction":0.44029849767684937,"avg_line_length":24.0625,"blob_id":"6f4ba5881baad944af19c1cd9963f67c97e2cd9c","content_id":"0f3f6651ada2655d733f04174a785f0530d42ff1","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":402,"license_type":"no_license","max_line_length":43,"num_lines":16,"path":"/알고리즘/온라인저지/2022/02/0204/ROT13.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"sen = input()\n\nfor s in sen:\n o = ord(s)\n if s in 'ABCDEFGHIJKLMNOPQRSTUVWXYZ':\n if o <= ord('M'):\n print(chr(o + 13), end='')\n else:\n print(chr(o - 13), end='')\n elif s in 'abcdefghijklmnopqrstuvwxyz':\n if o >= ord('n'):\n print(chr(o - 13), end='')\n else:\n print(chr(o + 13), end='')\n else:\n print(s, end='')\n\n"},{"alpha_fraction":0.4649122953414917,"alphanum_fraction":0.5350877046585083,"avg_line_length":9.363636016845703,"blob_id":"da6070e8c56bce5c816f37104b49fa4025897b1e","content_id":"ceabc03666e6cc547f5c2554490a295f304672e9","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":114,"license_type":"no_license","max_line_length":22,"num_lines":11,"path":"/알고리즘/온라인저지/2022/01/0131/열 개씩 끊어 출력하기.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"sen = input()\n\ni = 10\n\nlenn = len(sen)\n\nwhile i < lenn:\n print(sen[i-10:i])\n i += 10\n\nprint(sen[i-10:lenn])\n"},{"alpha_fraction":0.3687500059604645,"alphanum_fraction":0.41874998807907104,"avg_line_length":13.636363983154297,"blob_id":"f2aec11634e7af6ae5ddc2f96284c75470aaf718","content_id":"25f52b889ebe1d052db7a921757a4a9cc5f2c5aa","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":160,"license_type":"no_license","max_line_length":19,"num_lines":11,"path":"/알고리즘/온라인저지/2022/04/0406/3n+1 수열.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = int(input())\nresult = 0\nwhile True:\n if N == 1:\n break\n if N % 2:\n N = N*3 + 1\n else:\n N //= 2\n result += 1\nprint(result+1)"},{"alpha_fraction":0.4918699264526367,"alphanum_fraction":0.5081300735473633,"avg_line_length":18,"blob_id":"376dae1f54760f0650d74cd5e194527938eadd47","content_id":"3ee57821aee9c98b2894dba70c6ed44574f2df8a","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":246,"license_type":"no_license","max_line_length":35,"num_lines":13,"path":"/알고리즘/온라인저지/2022/09/0901/회전하는 큐.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N, _ = map(int, input().split())\nM = list(map(int, input().split()))\nN = list(range(1, N+1))\nprev = 0\nresult = 0\nfor m in M:\n i = N.index(m)\n D = abs(prev - i)\n D = min(D, len(N)-D)\n result += D\n N.pop(i)\n prev = i\nprint(result)"},{"alpha_fraction":0.32826748490333557,"alphanum_fraction":0.4559270441532135,"avg_line_length":11.692307472229004,"blob_id":"c93b2bf7fe73a6474a83a5d80f7b5cf25f818aa9","content_id":"20ca2229d9415f35cf5ecf6a7db53f47cac3094c","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":329,"license_type":"no_license","max_line_length":44,"num_lines":26,"path":"/알고리즘/온라인저지/2022/02/0220/타일 장식물.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"\"\"\"\n1 : 1+1+1+1\n2 : 4-1+1+1+1\n3 : 6-2+2+2+2\n4 : 10-3+3+3+3\n5 : \n1 : \n\"\"\"\n\nN = int(input())\n\nresult = [0, 4]\n\ndp = [0, 1]\n\nif N >= 2:\n for i in range(2, N+1):\n dp.append(dp[i-1] + dp[i-2])\n\n for i in range(2, N+1):\n result.append(result[i-1] + dp[i]*2)\n\nif result == 1:\n print(4)\nelse:\n print(result[-1])"},{"alpha_fraction":0.4178321659564972,"alphanum_fraction":0.45279720425605774,"avg_line_length":23.913043975830078,"blob_id":"1465176bef6fd75580d4ba2386ca304d98343832","content_id":"1f8f4d4ee7386d933c855d923f70308802e0e710","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":572,"license_type":"no_license","max_line_length":55,"num_lines":23,"path":"/알고리즘/온라인저지/2021/08/0829/색종이.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\nN = int(sys.stdin.readline())\nboard = [[0]*1002 for _ in range(1002)]\nmax_y = 0\nmax_x = 0\nfor n in range(1, N+1):\n Y, X, H, W = map(int, sys.stdin.readline().split())\n for y in range(Y, Y+H):\n for x in range(X, X+W):\n board[y][x] = n\n if max_y < y:\n max_y = y\n if max_x < x:\n max_x = x\nresult = [0] * N\nfor n in range(1, N+1):\n for i in range(max_y+1):\n for j in range(max_x+1):\n if board[i][j] == n:\n result[n-1] += 1\nfor r in result:\n print(r)"},{"alpha_fraction":0.5398229956626892,"alphanum_fraction":0.5575221180915833,"avg_line_length":18,"blob_id":"83f17923ca52fd7982129ddbfa25632c9ced2d20","content_id":"b439f5c8d8838c387fba45109029975454307d38","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":113,"license_type":"no_license","max_line_length":29,"num_lines":6,"path":"/알고리즘/온라인저지/2022/12/1229/MBTI.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"MBTI = input()\nresult = 0\nfor _ in range(int(input())):\n if MBTI == input():\n result += 1\nprint(result)"},{"alpha_fraction":0.5419161915779114,"alphanum_fraction":0.5958083868026733,"avg_line_length":16.63157844543457,"blob_id":"805c02f08f828ee25383f6d3a365d3e7c7719cac","content_id":"ce2d015034a6b8fe30fb183d2ad5b82120459c1b","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":344,"license_type":"no_license","max_line_length":41,"num_lines":19,"path":"/알고리즘/온라인저지/2022/10/1006/병든 나이트.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\n\nN, M = map(int, input().rstrip().split())\nresult = 0\nif N == 1: result = 1\nelif N == 2: result = min(4, (M+1)//2)\nelse: # N >= 3\n if M < 7: result = min(4, M)\n else: result = M-2\nprint(result)\n\n\"\"\"\n<참고한 링크>\nhttps://pacific-ocean.tistory.com/354\n\"\"\"\n\n# https://www.acmicpc.net/problem/1783"},{"alpha_fraction":0.3558441698551178,"alphanum_fraction":0.3636363744735718,"avg_line_length":15.782608985900879,"blob_id":"8e504ff8c1ed1e7bc665e89545a008c1fd766144","content_id":"44f8935b3eef84ba35e6716e1b9657c4c438c336","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":385,"license_type":"no_license","max_line_length":42,"num_lines":23,"path":"/알고리즘/온라인저지/2022/11/1123/우유가 넘어지면.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\n\nrotate = {\n \".\": \".\",\n \"O\": \"O\",\n \"-\": \"|\",\n \"|\": \"-\",\n \"/\": \"\\\\\",\n \"\\\\\": \"/\",\n \"^\": \"<\",\n \"<\": \"v\",\n \"v\": \">\",\n \">\": \"^\",\n}\n\nN, M = map(int, input().rstrip().split())\narr = [input().rstrip() for _ in range(N)]\nfor j in range(M-1, -1, -1):\n for i in range(N):\n print(rotate[arr[i][j]], end='')\n print()"},{"alpha_fraction":0.42657342553138733,"alphanum_fraction":0.4545454680919647,"avg_line_length":19.5,"blob_id":"05b68bb8397d837db3c96a0bd201e80d5af0b9ce","content_id":"cee7965588ac63f029fdf4c57d8d1a40bf33ed2f","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":336,"license_type":"no_license","max_line_length":32,"num_lines":14,"path":"/알고리즘/온라인저지/2021/08/0803/사분면 고르기.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"x = int(input()) # x와\ny = int(input()) # y값을 int로 받아서 \nquadrant = 0 # 사분면 값을 초기화해주고\nif x >= 0:\n if y >= 0:\n quadrant = 1 # + +\n else:\n quadrant = 4 # + -\nelse:\n if y >= 0:\n quadrant = 2 # - +\n else:\n quadrant = 3 # - -\nprint(quadrant) # 사분면 값을 출력"},{"alpha_fraction":0.43379446864128113,"alphanum_fraction":0.45059287548065186,"avg_line_length":27.13888931274414,"blob_id":"c85ba4be0659933352281f162df7e30785b7ba3d","content_id":"9905f6c3c6635a07cbcc2f56eaa345dd6159fca7","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1012,"license_type":"no_license","max_line_length":62,"num_lines":36,"path":"/알고리즘/온라인저지/2021/08/0829/주사위 쌓기.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ndice_count = int(sys.stdin.readline())\ndices = []\nfor d in range(dice_count):\n dices.append(list(map(int, sys.stdin.readline().split())))\nresult = 0\nfor j in range(6):\n max_sum = 0\n up = 0\n for i in range(dice_count):\n dice_opposite = {\n dices[i][0]:dices[i][5], \n dices[i][1]:dices[i][3],\n dices[i][2]:dices[i][4],\n dices[i][3]:dices[i][1],\n dices[i][4]:dices[i][2],\n dices[i][5]:dices[i][0]\n }\n tmp = [*dices[i]]\n try:\n if up == 0:\n tmp.remove(dices[i][j])\n tmp.remove(dice_opposite[dices[i][j]])\n up = dice_opposite[dices[i][j]]\n max_sum += max(tmp)\n else:\n tmp.remove(up)\n tmp.remove(dice_opposite[up])\n up = dice_opposite[up]\n max_sum += max(tmp)\n except:\n pass\n if result < max_sum:\n result = max_sum\nprint(result)"},{"alpha_fraction":0.5882353186607361,"alphanum_fraction":0.5882353186607361,"avg_line_length":35.25,"blob_id":"4f39cc3ffa1fc9b8a155db24042ee4117aa8bdc5","content_id":"13461c3ae9d201b056b0928d875654620ae879ea","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":437,"license_type":"no_license","max_line_length":56,"num_lines":8,"path":"/알고리즘/온라인저지/2021/08/0803/X보다 작은 수.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N, X = map(int, input().split()) # N은 왜준거지? 모르겠다\nA = list(map(int, input().split())) # 수열을 입력받아서 리스트로 만들고\nresult = [] # 결과값을 초기화하고\nfor a in A: # 수열을 순회하면서\n if a < X: # X보다 작은 수는\n result.append(a) # 결과값에 추가\nfor res in result: # 결과값 수열을 순회하면서\n print(res, end=' ') # 띄어쓰기 간격으로 출력"},{"alpha_fraction":0.481675386428833,"alphanum_fraction":0.5078533887863159,"avg_line_length":11.800000190734863,"blob_id":"9c0d56d6542133b0885779e26c784f764479c824","content_id":"82fe8cc20233b606ef7e4909072f36528ea78363","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":191,"license_type":"no_license","max_line_length":40,"num_lines":15,"path":"/알고리즘/온라인저지/2022/02/0220/행복.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = int(input())\n\nscores = list(map(int, input().split()))\n\nmaxx = 0\nminn = 1000\n\nfor s in scores:\n if s >= maxx:\n maxx = s\n \n if s <= minn:\n minn = s\n\nprint(maxx-minn)"},{"alpha_fraction":0.5213675498962402,"alphanum_fraction":0.5897436141967773,"avg_line_length":13.75,"blob_id":"cd28b5f866cd7215eb883ba25475f7a44b895132","content_id":"d1c5fca7afb793b1a4e387892a171233dbe51ce6","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":117,"license_type":"no_license","max_line_length":40,"num_lines":8,"path":"/알고리즘/온라인저지/2022/02/0203/네 수.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"nums1 = input().split()\n\nresult = 0\n\nfor i in range(0, 4, 2):\n result += int(nums1[i] + nums1[i+1])\n\nprint(result)"},{"alpha_fraction":0.29192546010017395,"alphanum_fraction":0.3913043439388275,"avg_line_length":12.5,"blob_id":"b45db5ce4065a63ba1be19a16a1bc3d0c81c70ad","content_id":"aa8f2197092b708dad2b9d21c94d67141fadb7a3","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":161,"license_type":"no_license","max_line_length":30,"num_lines":12,"path":"/알고리즘/SWEA/LEARN/Course/1. Programming Beginner/파이썬 프로그래밍 기초(2)/20차시 2. 자료구조 – 리스트, 튜플 - 연습문제 22.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"x = [5, 6, 77, 45, 22, 12, 24]\n\ni = 0\nwhile True:\n if x[i]%2 == 0:\n x.remove(x[i])\n else:\n i += 1\n if i == len(x):\n break\n\nprint(x)"},{"alpha_fraction":0.46783626079559326,"alphanum_fraction":0.46783626079559326,"avg_line_length":18.11111068725586,"blob_id":"2cdc85add6b18fe4b5ee54d4b3db7b1a6221571c","content_id":"619458b2400cbd2bece94328f59b1b25feaa621a","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":171,"license_type":"no_license","max_line_length":32,"num_lines":9,"path":"/알고리즘/온라인저지/2022/02/0206/대소문자 바꾸기.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"sen = input()\n\nfor s in sen:\n if s.isupper():\n print(s.lower(), end='')\n elif s.islower():\n print(s.upper(), end='')\n else:\n print(s, end='')"},{"alpha_fraction":0.4260089695453644,"alphanum_fraction":0.4506726562976837,"avg_line_length":26.9375,"blob_id":"451c7d5e60aef773ade8e8613c3480b8acfc55b6","content_id":"86b634d8298052d43c40d5407b0e9bd593658394","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":446,"license_type":"no_license","max_line_length":63,"num_lines":16,"path":"/알고리즘/온라인저지/2022/06/0617/박스.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"def down():\n global result\n for i in range(N-2, -1, -1):\n for j in range(M):\n if arr[i][j] == 1 and arr[i+1][j] == 0:\n arr[i][j], arr[i+1][j] = arr[i+1][j], arr[i][j]\n result += 1\n\nT = int(input())\nfor t in range(T):\n N, M = map(int, input().split())\n arr = [list(map(int, input().split())) for _ in range(N)]\n result = 0\n for n in range(N-1):\n down() \n print(result)"},{"alpha_fraction":0.5649717450141907,"alphanum_fraction":0.5762711763381958,"avg_line_length":26.30769157409668,"blob_id":"559e249b4f56abfae6ee86d48ffd17124162e203","content_id":"7c1d976cbfeda2d7704267f3149434c1c5af0e28","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":468,"license_type":"no_license","max_line_length":54,"num_lines":13,"path":"/알고리즘/온라인저지/2022/04/0417/차이를 최대로.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"from itertools import permutations\n\nN = int(input())\ntmp = list(map(int, input().split()))\nperm = list(permutations(tmp, N)) # 배열에서 나올 수 있는 모든 경우\nmaxx = 0 # \"차이를 최대로\"\nfor p in perm:\n a = 0 # 해당 배열의 최대값 초기화\n for i in range(N-1):\n a += abs(p[i]-p[i+1]) # 앞뒤 값의 절대값 더하기\n if a > maxx: # 최대값 갱신이 가능하면\n maxx = a # 최대값 갱신\nprint(maxx) # 출력"},{"alpha_fraction":0.5613811016082764,"alphanum_fraction":0.5664961934089661,"avg_line_length":47.9375,"blob_id":"b8b1e39f9adcd95e6d957f99cbdd5aca7328ecf2","content_id":"833231e7898ce1f63534f3e1297c46a67cebdf10","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":968,"license_type":"no_license","max_line_length":90,"num_lines":16,"path":"/알고리즘/프로그래머스/Level1/신고 결과 받기.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"def solution(id_list, report, k):\n answer = [0] * len(id_list) # 정답 배열\n report_list = [[] for _ in range(len(id_list))] # 신고받은 목록\n black_list = [0] * len(id_list) # 신고받은 횟수\n for r in report:\n user, reported = r.split() # 공백을 간격으로, 유저, 피신고자\n if reported not in report_list[id_list.index(user)]: # 중복 신고 방지, 아직 신고 받은 적 없는지 확인\n report_list[id_list.index(user)].append(reported) # 신고 받은 목록 추가\n black_list[id_list.index(reported)] += 1 # 신고 받은 횟수 추가\n # print(id_list, report, k) # 디버깅\n # print(report_list, black_list) # 디버깅\n for i in range(len(id_list)): # 해당 유저가\n for a in report_list[i]: # 신고한 사람이\n if black_list[id_list.index(a)] >= k: # k번 이상 신고 되었을 때\n answer[i] += 1 # 제재완료\n return answer"},{"alpha_fraction":0.5055928230285645,"alphanum_fraction":0.5548098683357239,"avg_line_length":27,"blob_id":"5cf550c23cade46acc6a48779641bd04b1539374","content_id":"e54f7018f7b512051f5e6aeb599b5451abf422b3","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":677,"license_type":"no_license","max_line_length":44,"num_lines":16,"path":"/알고리즘/온라인저지/2021/08/0811/거스름돈.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"\"\"\"\n1000엔에서 물건값 빼고\n거스름돈을 거슬러주면 된다\n동전의 최소개수\"\"\"\nprice = int(input()) # 물건의 가격\nchange = 1000-price # 거스름돈\ncoins = [500, 100, 50, 10, 5, 1] # 동전들\ncount = 0 # 동전의 개수 초기화\nfor coin in coins: # 동전들을 금액이 큰 순서로 순회하면서\n if coin <= change: # 거슬러줄 수 있으면\n while True:\n change -= coin # 해당 동전을 하나 거슬러주고\n count += 1 # 동전 개수 증가\n if coin > change: # 거슬러주지 못하면\n break # 종료하고 다음 작은 동전으로\nprint(count) # 동전 개수 출력"},{"alpha_fraction":0.4670184552669525,"alphanum_fraction":0.4854881167411804,"avg_line_length":19,"blob_id":"a77b5d42f948a58e61778e036c0a0fc78d26e14e","content_id":"fbcf9f955be9e09b86c9c9776267e6f533315481","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":379,"license_type":"no_license","max_line_length":36,"num_lines":19,"path":"/알고리즘/온라인저지/2021/08/0822/방 배정.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N, K = map(int, input().split())\narr = [[0]*2 for _ in range(6)]\nfor n in range(N):\n S, Y = map(int, input().split())\n arr[Y-1][S] += 1\nnew_arr = []\nfor ar in arr:\n for a in ar:\n new_arr.append(a)\nresult = 0\nfor ar in new_arr:\n if ar > K: \n result += ar//K\n ar = ar%K\n if not ar:\n continue\n else:\n result += 1\nprint(result)"},{"alpha_fraction":0.6321070194244385,"alphanum_fraction":0.654403567314148,"avg_line_length":21.450000762939453,"blob_id":"b0efe938fe583d8c6f34c96e41c0a659aff0b767","content_id":"53a7e22be4a1902e58c9e16ff5ad37c8973e0c78","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1527,"license_type":"no_license","max_line_length":41,"num_lines":40,"path":"/알고리즘/온라인저지/2022/10/1002/1로 만들기 2.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\nfrom collections import deque\n\ninput = sys.stdin.readline\n\nN = int(input().rstrip())\nQ = deque()\nQ.append([N])\nresult = []\nwhile Q:\n now = Q.popleft()\n X = now[-1]\n if X == 1: result = now; break\n if X % 3 == 0: Q.append(now + [X//3])\n if X % 2 == 0: Q.append(now + [X//2])\n Q.append(now + [X-1])\nprint(len(result)-1)\nprint(*result)\n\n\"\"\"\n3으로 나누고, 2로 나누고, 1을 빼는\n탐색기록 그 자체를 큐에 담으며 진행함\n1에 도착했을 때의 탐색기록이 결과가 됨\n스페셜저지 이므로 답은 아무거나 상관이 없음\n해당 코드는 top-down DP코드이지만\n1에서 출발하여 N까지 가는 bottom-up 코드를 짤 수도 있음\n하지만 *연산보다 //연산이 시간이 조금 더 빠를지도..?\nDP의 개념은 매우 단순함\n\"계산한 값을 기억했다가 다시 사용한다\"\n본디 다이나믹 프로그래밍이라는 이름 자체가\n별 뜻이 없고, 만든 사람이 그냥 어그로성으로 붙인 이름이라고 함\n한 번 계산된 값을 기록하여 재활용하는 알고리즘을 전부 DP로 봄\n특징으로는, 계산된 값을 날리지 않고 들고 있는만큼\n메모리가 많이 필요함\n해당 코드는 수많은 리스트들이 Q에 들어가는 것처럼 보이지만\n시간이 logN으로 빠른 이(二)분탐색보다 훨씬 빠른\n코드상 삼(三)분탐색을 사용하므로 \n저렇게 넘치게 Q에 append 하는 것처럼 보여도 메모리는 괜찮다\n\"\"\"\n# https://www.acmicpc.net/problem/12852"},{"alpha_fraction":0.6751269102096558,"alphanum_fraction":0.6751269102096558,"avg_line_length":32,"blob_id":"50bece0232b422491a7a6d8808a441a22cd0ba13","content_id":"44e30ccea0f8e6da6aa462490d436e9cbacc8783","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":197,"license_type":"no_license","max_line_length":48,"num_lines":6,"path":"/알고리즘/온라인저지/2023/01/0128/줄 세우기.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"players = [input() for _ in range(int(input()))]\nif players == sorted(players):\n print('INCREASING')\nelif players == sorted(players, reverse=True):\n print('DECREASING')\nelse: print('NEITHER')"},{"alpha_fraction":0.5317515730857849,"alphanum_fraction":0.5415213108062744,"avg_line_length":30.866666793823242,"blob_id":"66c5d2db3902be5a3155bf5fce3ae62a30239505","content_id":"720a9223315b3822c2c2c1a8050f5549b954148b","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":2215,"license_type":"no_license","max_line_length":62,"num_lines":45,"path":"/알고리즘/온라인저지/2022/08/0812/외판원 순회 2.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"def dfs(start, now):\n global result, tmp\n if tmp > result: return # 백트래킹\n for next in range(N): # 다음 방문 지점\n # 다음 방문할 지점이 지금 지점과 다르고\n # 방문한 적이 없으며\n # 방문을 할 수 있을 때(W배열에 값이 존재할 때)\n if now != next and not visited[next] and W[now][next]:\n visited[next] = 1 # 다음 지점 방문 찍고\n tmp += W[now][next] # 그 지점의 코스트를 더하고\n dfs(start, next) # 해당 지점 탐색\n visited[next] = 0 # 방문 지워주고\n tmp -= W[now][next] # 코스트 지워주고\n elif sum(visited) == N and W[now][start]:\n tmp += W[now][start] # 코스트 더하고\n if tmp < result: result = tmp # 최소값 갱신\n tmp -= W[now][start] # 코스트 지워주고\n\nN = int(input())\nW = [list(map(int, input().split())) for _ in range(N)]\nresult = int(1e9) # 가상의 최소값\nvisited = [0] * N # 방문 배열\nfor n in range(N): # 모든 점에서 다 출발해본다\n tmp = 0 # 해당 출발의 임시 결과값\n visited[n] = 1 # 들어가면서 찍고\n dfs(n, n) # 출발 시, 시작점과 탐색점은 같다\n visited[n] = 0 # 나오면서 지운다\nprint(result) # 얻은 최소값 출력\n\n\"\"\"\n시간 : 80분(혼자 고민) + 10분(\"질문검색\"탭에서 반례 및 힌트 참고)\n풀이\n 갈 수 있는 동선을 모두 체크하여(브루트포스)\n dfs로 탐색하면서\n 방문배열을 만들어서, 들어갈 때 찍고, 나올 때 지워준다\n 모든 점을 탐색했을 때 시작점으로 돌아가서\n 해당 순회의 결과값이 최소값인지 비교하여 갱신한다\n (from itertools import permutation을 사용하여 풀 수도 있을 것이다)\n\n 문제의 함정\n 1. 다음 지점으로 갈 수 없는 경우가 있다\n 순회 도중에 갈 수 없는 경우만 구현하였더니 오답이었고\n 마지막 지점에서 다시 시작점으로 갈 수 없는 경우를 구현해주니 맞았음\n 2. 순회 도중, 이미 구한 최소값보다 값이 커지면 return한다 (백트래킹)\n\"\"\""},{"alpha_fraction":0.5054945349693298,"alphanum_fraction":0.5164835453033447,"avg_line_length":14.333333015441895,"blob_id":"9c3430f7d7500c3724f96fc0f3a43a96de3a3dab","content_id":"84e89fd50779e6550cacb1238064f0e79f6354fc","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":91,"license_type":"no_license","max_line_length":36,"num_lines":6,"path":"/알고리즘/온라인저지/2022/02/0211/다면체.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"T = int(input())\n\nfor t in range(T):\n V, E = map(int, input().split())\n\n print(E-V+2)"},{"alpha_fraction":0.35384616255760193,"alphanum_fraction":0.5076923370361328,"avg_line_length":21,"blob_id":"72075ee002a3440075dd7f938d88d65aecacb2d2","content_id":"0ed46d4655bb4cd672272fa115981f7d35f22ead","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":65,"license_type":"no_license","max_line_length":47,"num_lines":3,"path":"/알고리즘/온라인저지/2022/02/0221/세금.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"N = int(input())\n\nprint(int(N*0.78), int((N*0.8) + (N*0.2)*0.78))"},{"alpha_fraction":0.4741035997867584,"alphanum_fraction":0.5119521617889404,"avg_line_length":24.149999618530273,"blob_id":"1cde46789ad61409c9ca3cb5420cff414cd9f00a","content_id":"0689a6120b1ea835ed59575fd1112c578e164777","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":502,"license_type":"no_license","max_line_length":66,"num_lines":20,"path":"/알고리즘/온라인저지/2022/10/1006/숫자판 점프.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\ndy, dx = [-1, 1, 0, 0], [0, 0, -1, 1]\n\ndef dfs(y, x, move, str_num):\n if move == 5: \n result.add(int(str_num))\n return\n for i in range(4):\n ny, nx = y+dy[i], x+dx[i]\n if 0<=ny<5 and 0<=nx<5:\n dfs(ny, nx, move+1, str_num+str(arr[ny][nx]))\n\narr = [list(map(int, input().rstrip().split())) for _ in range(5)]\nresult = set()\nfor i in range(5):\n for j in range(5):\n dfs(i, j, 0, str(arr[i][j]))\nprint(len(result))"},{"alpha_fraction":0.4848484992980957,"alphanum_fraction":0.5353535413742065,"avg_line_length":11.5,"blob_id":"31e9830d34873c93249dfee32a85a81c1281f10b","content_id":"48f90ff8c3b42ca6b65dc1f614d2aea9c28b05d0","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":99,"license_type":"no_license","max_line_length":16,"num_lines":8,"path":"/알고리즘/온라인저지/2023/05/0521/11 月 (November).py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"A = int(input())\nB = int(input())\nB *= 7\nC = A+B\nresult = 1\nif C > 30:\n result = 0\nprint(result)"},{"alpha_fraction":0.48106446862220764,"alphanum_fraction":0.5076765418052673,"avg_line_length":22.08661460876465,"blob_id":"69f2bdf44f86c9c5cd90c21dfd1a2468d5eb7bea","content_id":"1f0c4b40d6bb0aa58b6ee4bce76020495addd8cb","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":3589,"license_type":"no_license","max_line_length":61,"num_lines":127,"path":"/알고리즘/온라인저지/2022/03/0313/배열 돌리기 3.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"\"\"\"\narr = 원본 배열\nresult = 연산을 실행한 배열\n매 연산마다 배열을 돌리고\nresult를 다시 arr에 deepcopy하면서 진행\n\"\"\"\n\nimport copy # deepcopy 사용\n\ndef one():\n global arr, result\n result = []\n for a in arr[::-1]: # 세로로 뒤집어서\n result.append(a) # 한 줄 씩 추가\n arr = copy.deepcopy(result) # arr에 result 덮어쓰기\n\ndef two():\n global arr, result\n result = []\n for a in arr:\n result.append(a[::-1]) # 가로로 뒤집어서 한 줄 씩 추가\n arr = copy.deepcopy(result) # arr에 result 덮어쓰기\n \ndef three():\n global arr, result\n result = []\n for j in range(M): # 왼쪽 줄을\n tmp = []\n for i in range(N-1, -1, -1): # 거꾸로 읽어와서\n tmp.append(arr[i][j])\n result.append(tmp) # 한 줄 씩 추가\n arr = copy.deepcopy(result) # arr에 result 덮어쓰기\n\ndef four():\n global arr, result\n result = []\n for j in range(M-1, -1, -1): # 오른쪽 줄을\n tmp = []\n for i in range(N): # 읽어와서\n tmp.append(arr[i][j])\n result.append(tmp) # 한 줄 씩 추가\n arr = copy.deepcopy(result) # arr에 result 덮어쓰기\n\n\"\"\"\n5번연산, 6번연산은\n배열의 모양을 \n1 2\n4 3\n으로 나누어 생각하기로 함\n5번연산을 실행한 결과값의 맨 윗줄은\n4번의 첫 줄 + 1번의 첫 줄이 되고\n그렇게 결과값의 반을 채우고 나면 나머지 반은\n3번의 첫 줄 + 2번의 첫 줄\n을 더한 값으로 순서대로 나머지 반을 채우게 됨\n\"\"\"\ndef five():\n global arr, result\n result = []\n for i in range(N//2, N):\n tmp1 = [] # 4\n tmp2 = [] # 1\n for j in range(M//2):\n tmp1.append(arr[i][j])\n tmp2.append(arr[i-(N//2)][j])\n result.append(tmp1+tmp2) # 4와 1을 한 줄 씩 더해서 result에 추가\n for i in range(N//2, N):\n tmp1 = [] # 3\n tmp2 = [] # 2\n for j in range(M//2, M):\n tmp1.append(arr[i][j])\n tmp2.append(arr[i-(N//2)][j])\n result.append(tmp1+tmp2) # 3과 2를 한 줄 씩 더해서 result에 추가\n arr = copy.deepcopy(result) # arr에 result 덮어쓰기\n\n\"\"\"\n6번연산은\n2번의 첫 줄 + 3번의 첫 줄\n을 구해서 결과값의 절반을 채우고\n나머지 절반은\n1번의 첫 줄 + 4번의 첫 줄\n을 더한 값으로 채움\n\"\"\"\ndef six():\n global arr, result\n result = []\n for i in range(N//2):\n tmp1 = [] # 2\n tmp2 = [] # 3\n for j in range(M//2, M):\n tmp1.append(arr[i][j])\n tmp2.append(arr[i+(N//2)][j])\n result.append(tmp1+tmp2) \n for i in range(N//2):\n tmp1 = [] # 1\n tmp2 = [] # 4\n for j in range(M//2):\n tmp1.append(arr[i][j])\n tmp2.append(arr[i+(N//2)][j])\n result.append(tmp1+tmp2)\n arr = copy.deepcopy(result) # arr에 result 덮어쓰기\n\n\nN, M, R = map(int, input().split())\narr = [] # 원본 배열\nfor n in range(N):\n arr.append(list(map(int, input().split())))\norders = list(map(int, input().split())) # 연산들\nresult = [] # 연산을 진행할 배열\n\nfor order in orders:\n if order == 1:\n one()\n elif order == 2:\n two()\n elif order == 3:\n three()\n N, M = M, N # 직사각형 배열인 경우 에러 방지\n elif order == 4:\n four() \n N, M = M, N # 직사각형 배열인 경우 에러 방지\n elif order == 5:\n five()\n elif order == 6:\n six()\n\nfor r in result:\n print(*r) # 각 줄 출력"},{"alpha_fraction":0.5787781476974487,"alphanum_fraction":0.5932475924491882,"avg_line_length":27.272727966308594,"blob_id":"ea3799b49cf2ba67c0b01b1566b1a8060d689f18","content_id":"ad93b25c07599cc59743bc6368c11a24a5ed2484","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1028,"license_type":"no_license","max_line_length":70,"num_lines":22,"path":"/알고리즘/온라인저지/2021/08/0806/평균은 넘겠지.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"\"\"\"\n테스트케이스 개수 C개\n학생의 수 N명, 점수 N개\n점수 N개의 평균\n을 넘는 점수의 개수\n를 전체 점수의 개수로 나눈 퍼센트\n을 3자리까지 출력\n을 테스트케이스 개수만큼\"\"\"\n\nC = int(input()) # 테스트케이스 개수\nfor i in range(C): # 테스트케이스 개수만큼 순회하면서\n N_and_scores = list(map(int, input().split())) # 점수개수 N과 점수들을 입력받고\n N = N_and_scores[0] # N값을 잡아주고\n average = (sum(N_and_scores) - N) / N # 평균 구해주고\n count = 0 # 평균이상인 점수 개수 초기화\n for j in range(1, len(N_and_scores)): # 점수 리스트 순회하면서\n if N_and_scores[j] > average: # 평균이상인 점수 있으면\n count += 1 # 카운트 증가\n print(f'{(count / N) * 100:.3f}%') # 출력\n\n# 입력받고 출력하고를 테스트케이스 개수만큼 반복하는 것이 가능하다\n# 모든 값을 입력받고 저장해서 거기서 값을 꺼낼 필요가 없다\n"},{"alpha_fraction":0.5025728940963745,"alphanum_fraction":0.5454545617103577,"avg_line_length":26.809524536132812,"blob_id":"96a48ac352d10a06be0088c8f4fabf0e9f3805be","content_id":"a9dc1ea1f3180f1ea0110d252e0f995d56d51fcb","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":889,"license_type":"no_license","max_line_length":49,"num_lines":21,"path":"/알고리즘/온라인저지/2021/08/0807/동전O.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"\"\"\"\nN = 동전의 종류 가짓수\nK = 목표 금액\n필요한 동전 개수의 최솟값을 구하는 문제\n\"\"\"\n\nN, K = map(int, input().split()) # 동전개수, 목표금액 입력\ncoins = [] # 입력받을 동전 리스트 초기화\nfor i in range(N): # 동전개수만큼 순회하면서\n coins.append(int(input())) # 동전들 입력받아서 추가\ncoins.reverse() # 입력받은 리스트 뒤집고\ncount = 0 # 필요한 동전개수 count 초기화\nfor coin in coins: # 동전들 순회하면서\n if coin <= K: # 이 동전이 목표금액보다 작으면\n while True: # 반복해서\n K -= coin # 목표금액에서 빼고\n count += 1 # 동전 개수 추가하고\n if coin > K: # 동전값이 목표금액보다 크면\n break # 정지\n# 4200 -> 3200 -> 2200 -> 1200 -> 200 -> 100 -> 0\nprint(count) # 동전갯수 출력"},{"alpha_fraction":0.44768211245536804,"alphanum_fraction":0.4834437072277069,"avg_line_length":28.076923370361328,"blob_id":"989fad5fac506e5fad6162f0ade46949e5be9ec3","content_id":"09716823664e4da785982603d2473a6e09aea197","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":755,"license_type":"no_license","max_line_length":59,"num_lines":26,"path":"/알고리즘/온라인저지/2022/10/1002/나이트의 이동.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\nfrom collections import deque\n\ninput = sys.stdin.readline\ndy = [-1, -2, -2, -1, 1, 2, 2, 1]\ndx = [-2, -1, 1, 2, 2, 1, -1, -2]\n\nfor _ in [0]*int(input().rstrip()):\n L = int(input().rstrip())\n start = tuple(map(int, input().rstrip().split()))\n goal = tuple(map(int, input().rstrip().split()))\n result = 0\n visited = [[0]*L for l in [0]*L]\n Q = deque()\n y, x = start\n Q.append((y, x, 0))\n visited[y][x] = 1\n while Q:\n y, x, move = Q.popleft()\n if (y, x) == goal: result = move; break\n for i in range(8):\n ny, nx = y+dy[i], x+dx[i]\n if 0<=ny<L and 0<=nx<L and not visited[ny][nx]:\n Q.append((ny, nx, move+1))\n visited[ny][nx] = 1\n print(move)"},{"alpha_fraction":0.560606062412262,"alphanum_fraction":0.6212121248245239,"avg_line_length":14.7619047164917,"blob_id":"1b7c30bee4210564164513959d010e9e807f31b2","content_id":"ec8bbbd3dd91dde827dea45570e928e76748adcf","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":438,"license_type":"no_license","max_line_length":39,"num_lines":21,"path":"/알고리즘/온라인저지/2022/10/1006/오르막 수.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"import sys\n\ninput = sys.stdin.readline\n\nN = int(input().rstrip())\ndp = [1]*10\nfor i in range(1,N) :\n for j in range(1,10) :\n dp[j] += dp[j-1]\nprint(sum(dp)%10007)\n\n\"\"\"\n규칙은 찾았는데 구현하는게 막혔다\n구현된 코드를 보고 이해는 가는데\n어떻게 하면 이런 걸 코드로 쓸 수 있는지.. 신기하다\n\n<참고한 링크>\nhttps://jainn.tistory.com/91\n\"\"\"\n\n# https://www.acmicpc.net/problem/11057"},{"alpha_fraction":0.5062656402587891,"alphanum_fraction":0.5137844681739807,"avg_line_length":25.66666603088379,"blob_id":"0d24da98f36f421c766736b3556c607ed85ce61d","content_id":"eb9076b1d5eee14f4872856434d15627749ac493","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":399,"license_type":"no_license","max_line_length":46,"num_lines":15,"path":"/알고리즘/온라인저지/2022/09/0904/크로스워드 만들기.py","repo_name":"sorrow4468/BAEKJOON","src_encoding":"UTF-8","text":"A, B = input().split()\nresult = [['.']*len(A) for _ in range(len(B))]\ny = 0\nchar = ''\nfor a in A[::-1]:\n if a in B:\n y = B.index(a)\n char = a\nx = A.index(char)\nfor j in range(len(A)): result[y][j] = A[j]\nfor i in range(len(B)): result[i][x] = B[i]\nfor i in range(len(result)):\n for j in range(len(result[i])):\n print(result[i][j], end='')\n if i < len(result)-1: print()"}],"string":"[\n {\n \"alpha_fraction\": 0.49275362491607666,\n \"alphanum_fraction\": 0.5024154782295227,\n \"avg_line_length\": 19.799999237060547,\n \"blob_id\": \"5637fe4795b9b5ff0544c8c4136315d28d5845ad\",\n \"content_id\": \"512d235b655e9976f3a0c808f9cb82754fc3c46f\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 207,\n \"license_type\": \"no_license\",\n \"max_line_length\": 50,\n \"num_lines\": 10,\n \"path\": \"/알고리즘/SWEA/LEARN/Course/1. Programming Beginner/파이썬 프로그래밍 기초(2)/16차시 2. 자료구조 – 리스트, 튜플 - 연습문제 18.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N, M = map(int, input().split(', '))\\n\\nresult = [[0 for _ in range(M)] for i in range(N)]\\n\\nfor i in range(N):\\n for j in range(M):\\n if result[i][j] == 0:\\n result[i][j] = i*j\\n\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.5903614163398743,\n \"alphanum_fraction\": 0.6204819083213806,\n \"avg_line_length\": 17.55555534362793,\n \"blob_id\": \"d6d4cc0411656f9906e9032569ffaa1d908a80f4\",\n \"content_id\": \"f6b0b1f0a20ae62e74b919f2917df2b97c322db0\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 166,\n \"license_type\": \"no_license\",\n \"max_line_length\": 34,\n \"num_lines\": 9,\n \"path\": \"/알고리즘/온라인저지/2023/06/0605/노솔브 방지문제야!!.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\n\\nQ = int(input())\\ndouble = [2**i for i in range(32)]\\nfor q in range(Q):\\n A = int(input())\\n print(1 if A in double else 0)\"\n },\n {\n \"alpha_fraction\": 0.446958988904953,\n \"alphanum_fraction\": 0.4752475321292877,\n \"avg_line_length\": 34.400001525878906,\n \"blob_id\": \"9d7f54b287fb9549e3c68451a4b400b2815ebfb5\",\n \"content_id\": \"28cafc0cfd6a2bf238ff3a302836ece6422db141\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1109,\n \"license_type\": \"no_license\",\n \"max_line_length\": 64,\n \"num_lines\": 20,\n \"path\": \"/알고리즘/온라인저지/2021/08/0813/설탕 배달.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"\\\"\\\"\\\"\\n3kg봉지, 5kg봉지\\n정확하게 Nkg, 못만들면 -1 출력\\n3과 5를 이중for문 돌리면서 \\n순회중인 무게를 3과 5로 만들어서 \\n그 때 사용한 각각의 봉지 개수를 리스트에 저장\\n봉지 리스트 길이가 0이면 만들 수 없는 무게이므로 -1\\n봉지 리스트에서 최소값을 출력\\n\\\"\\\"\\\"\\n\\nN = int(input()) # 설탕 무게\\ncnt = [] # 사용한 봉지개수를 더한 값을 담을 리스트\\nfor three in range(N//3 + 1): # 3kg, 시간 단축을 위해 범위 조절\\n for five in range(N//5 + 1): # 5kg, 마찬가지로 범위 조절\\n if three*3 + five*5 == N: # 해당 무게가 설탕무게이면\\n cnt.append(three + five)# 그때 사용된 봉지의 개수를 더한 값을 저장\\nif len(cnt) == 0: # 저장된 봉지개수 값이 없으면 만들 수 없는 무게\\n print(-1) # -1 출력\\nelse: # 저장된 봉지 개수값이 있다면\\n print(min(cnt)) # 봉지 개수중 최소값을 출력\"\n },\n {\n \"alpha_fraction\": 0.5506493449211121,\n \"alphanum_fraction\": 0.5558441281318665,\n \"avg_line_length\": 26.571428298950195,\n \"blob_id\": \"1678315064784a81b3d30ee661cca5f9d17832f7\",\n \"content_id\": \"1af89b6d17d1b51d0da487cdd5d5dcb732779f53\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 385,\n \"license_type\": \"no_license\",\n \"max_line_length\": 66,\n \"num_lines\": 14,\n \"path\": \"/알고리즘/온라인저지/2022/11/1101/임시 반장 정하기.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\n\\nN = int(input().rstrip())\\narr = [list(map(int, input().rstrip().split())) for _ in range(N)]\\ncheck = [set() for _ in range(N)]\\nfor j in range(5):\\n for i in range(N):\\n for k in range(N):\\n if arr[i][j] == arr[k][j] and i != k:\\n check[i].add(k)\\nresult = [len(c) for c in check]\\nprint(result.index(max(result))+1)\"\n },\n {\n \"alpha_fraction\": 0.49193549156188965,\n \"alphanum_fraction\": 0.5134408473968506,\n \"avg_line_length\": 18.63157844543457,\n \"blob_id\": \"cdbdc3cbd865d3832839cd0c08ec12aaf35980c4\",\n \"content_id\": \"af3bab9f1312b632973504645a46d84b033d4835\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 372,\n \"license_type\": \"no_license\",\n \"max_line_length\": 45,\n \"num_lines\": 19,\n \"path\": \"/알고리즘/온라인저지/2022/10/1003/피보나치 수의 개수.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\n\\ndef check(fib):\\n if A<=fib<=B: return 1\\n else: return 0\\n\\nwhile True:\\n A, B = map(int, input().rstrip().split())\\n if A == 0 and B == 0: break\\n result = 0\\n a, b = 1, 2\\n result += check(a) + check(b)\\n for _ in range(B-2): \\n if b>B: break\\n a, b = b, a+b\\n result += check(b)\\n print(result)\"\n },\n {\n \"alpha_fraction\": 0.4593908488750458,\n \"alphanum_fraction\": 0.4763113260269165,\n \"avg_line_length\": 22.65999984741211,\n \"blob_id\": \"2cf714e1cb8d280ea6a53b35cb8d487fd820d645\",\n \"content_id\": \"3668bec89d0eddd9d1952219e929a45449fd5572\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1696,\n \"license_type\": \"no_license\",\n \"max_line_length\": 56,\n \"num_lines\": 50,\n \"path\": \"/알고리즘/온라인저지/2022/01/0122/귀여운 라이언.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N, K = map(int, input().split())\\n\\n# 라이언 혹은 어피치\\nryans = list(map(int, input().split()))\\n\\ns = e = cnt = 0 # 시작 끝 라이언개수\\n\\nif ryans[s] == 1: # 라이언으로 시작하면\\n cnt += 1 # cnt 1로 초기화\\n\\nresult = N # 가상의 최대값\\n\\nis_answer = False # 조합을 찾았는가??\\n\\nwhile True: # 무지성 while True\\n # while 종료 조건문\\n # 1. 라이언이 K개 미만인데 더 뒤로 못 감\\n # 2. 라이언이 K개 초과인데 더 앞에서 땡길 수 없음\\n if (cnt < K and e == N-1) or (cnt > K and s == N-1):\\n break\\n\\n if cnt == K: # K개 라이언인 구간 발견!\\n if not is_answer: # 처음 발견한거면\\n # K개인 라이언구간이 존재하니\\n # 일단 답이 -1은 아님\\n is_answer = True # 라이언구간 존재함 체크\\n \\n length = e-s+1 # 라이언구간의 길이\\n if length < result: # 더 짧은 구간길이라면\\n result = length # 최소 길이 갱신\\n \\n # 포인터를 옮길건데\\n if ryans[s] == 1: # 구간 맨 앞이 라이언이면\\n cnt -= 1 # 라이언 카운트 빼주고\\n s += 1 # 한 칸 땡기기\\n\\n elif cnt < K: # K개 미만 라이언구간이면\\n e += 1 # 한 칸 밀고\\n if ryans[e] == 1: # 밀은 위치가 라이언이면\\n cnt += 1 # 카운트\\n\\n elif cnt > K: # K개 초과 라이언구간이면\\n if ryans[s] == 1: # 맨 앞이 라이언이면\\n cnt -= 1 # 카운트 감소하고\\n s += 1 # 한 칸 땡김\\n\\nif is_answer: # K개인 라이언구간을 찾았었으면\\n print(result)\\nelse: # 못찾았었으면\\n print(-1)\"\n },\n {\n \"alpha_fraction\": 0.5270270109176636,\n \"alphanum_fraction\": 0.5405405163764954,\n \"avg_line_length\": 24,\n \"blob_id\": \"d177e28e0d42b2ed6332431130b150e4aaf969d9\",\n \"content_id\": \"6c90f64e19d77e448c91bf86a3eaade1d6a693c5\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 74,\n \"license_type\": \"no_license\",\n \"max_line_length\": 35,\n \"num_lines\": 3,\n \"path\": \"/알고리즘/온라인저지/2023/02/0228/Koszykarz.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"K, W, M = map(int, input().split())\\nA = W-K\\nprint(A//M+1 if A%M else A//M)\"\n },\n {\n \"alpha_fraction\": 0.5267857313156128,\n \"alphanum_fraction\": 0.5803571343421936,\n \"avg_line_length\": 27.125,\n \"blob_id\": \"ea41653ec7245ab7e7c0fee0b12b72e5494a7aad\",\n \"content_id\": \"e3526922e073cea4a99eccd99f9e19139d658a5c\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 224,\n \"license_type\": \"no_license\",\n \"max_line_length\": 44,\n \"num_lines\": 8,\n \"path\": \"/알고리즘/온라인저지/2023/04/0423/과자 사기.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"cospas = []\\nfor snack in ['S', 'N', 'U']:\\n cost, weight = map(int, input().split())\\n cost *= 10\\n if cost>=5000: cost -= 500\\n cospas.append((snack, weight/cost))\\ncospas.sort(key=lambda x:-x[1])\\nprint(cospas[0][0])\"\n },\n {\n \"alpha_fraction\": 0.5014326572418213,\n \"alphanum_fraction\": 0.5300859808921814,\n \"avg_line_length\": 18.44444465637207,\n \"blob_id\": \"4e7b1537a1f6948107090d906f042b5f7c99299e\",\n \"content_id\": \"02afbda505628654af495f5726d4f4e3e5b39b58\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 441,\n \"license_type\": \"no_license\",\n \"max_line_length\": 50,\n \"num_lines\": 18,\n \"path\": \"/알고리즘/온라인저지/2022/08/0808/트럭 주차.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"P = [0] * 101 # parking\\nC = [0] + list(map(int, input().split())) # charge\\nfor _ in range(3):\\n I, O = map(int, input().split()) # in out\\n for i in range(I, O): P[i] += 1\\nresult = 0\\nfor p in P:\\n tmp = C[p] * p\\n result += tmp\\nprint(result)\\n\\n\\\"\\\"\\\"\\n시간 : 13분\\n풀이\\n 트럭의 출입을 기록한 일지(P)를 만들고\\n 그 시간에 주차장에 있었던 트럭대수와\\n 요금을 곱해서 result++ 하여 출력\\n\\\"\\\"\\\"\"\n },\n {\n \"alpha_fraction\": 0.5820895433425903,\n \"alphanum_fraction\": 0.5970149040222168,\n \"avg_line_length\": 33,\n \"blob_id\": \"29a376fcc878ca6d3cf05074324c7fa9c4b5e86c\",\n \"content_id\": \"2cef6a4f32bf4436e6b00442633dce242f5b1d85\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 67,\n \"license_type\": \"no_license\",\n \"max_line_length\": 54,\n \"num_lines\": 2,\n \"path\": \"/알고리즘/온라인저지/2022/08/0820/코딩은 체육과목 입니다.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"for i in range(int(input())//4):print('long', end=' ')\\nprint('int')\"\n },\n {\n \"alpha_fraction\": 0.38566553592681885,\n \"alphanum_fraction\": 0.4095562994480133,\n \"avg_line_length\": 14.473684310913086,\n \"blob_id\": \"5fc98f1ceae3529578c830b429a12d562d5175ee\",\n \"content_id\": \"d8e37e2b8ecb37c20b031bb5149b82b2a28efe84\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 293,\n \"license_type\": \"no_license\",\n \"max_line_length\": 34,\n \"num_lines\": 19,\n \"path\": \"/알고리즘/온라인저지/2022/02/0205/만취한 상범.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"T = int(input())\\n\\nfor t in range(T):\\n N = int(input())\\n\\n dp = [True] * (N+1)\\n dp[0] = False\\n\\n for i in range(2, N+1):\\n for j in range(i, N+1, i):\\n dp[j] = not dp[j]\\n \\n result = 0\\n\\n for d in dp:\\n if d:\\n result += 1\\n \\n print(result)\"\n },\n {\n \"alpha_fraction\": 0.482051283121109,\n \"alphanum_fraction\": 0.4871794879436493,\n \"avg_line_length\": 27,\n \"blob_id\": \"aa11fbdb91205e00783f7bbacb571f841557ee56\",\n \"content_id\": \"342355176a4b4534b6d7d97cd5c97974ad7b44be\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 195,\n \"license_type\": \"no_license\",\n \"max_line_length\": 43,\n \"num_lines\": 7,\n \"path\": \"/알고리즘/온라인저지/2022/12/1206/꿍의 우주여행.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"for _ in range(int(input())):\\n N, D = map(int, input().split())\\n result = 0\\n for n in range(N):\\n v, f, s = map(int, input().split())\\n result += v*f >= D*s\\n print(result)\"\n },\n {\n \"alpha_fraction\": 0.44262295961380005,\n \"alphanum_fraction\": 0.5,\n \"avg_line_length\": 40,\n \"blob_id\": \"b9e57499a44208b4f9a4ed29f7d63b4ebde09b9b\",\n \"content_id\": \"66280451043b2a4fc910e44a3f48789d5a9f7124\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 166,\n \"license_type\": \"no_license\",\n \"max_line_length\": 41,\n \"num_lines\": 3,\n \"path\": \"/알고리즘/온라인저지/2021/08/0804/구구단.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = int(input()) # 1 < N <= 9 인 N을 입력받아서\\nfor i in range(1, 10): # 1부터 9까지 순회하면서 \\n print(f'{N} * {i} = {N*i}') # 구구단을 출력\"\n },\n {\n \"alpha_fraction\": 0.446153849363327,\n \"alphanum_fraction\": 0.4615384638309479,\n \"avg_line_length\": 21,\n \"blob_id\": \"213f14103d47db93e410049e180fa68738389d43\",\n \"content_id\": \"b6157dccbff71530d50da2c8e819e6b299881ce1\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 65,\n \"license_type\": \"no_license\",\n \"max_line_length\": 38,\n \"num_lines\": 3,\n \"path\": \"/알고리즘/온라인저지/2022/02/0210/스타후르츠.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N, T, C, P = map(int, input().split())\\n\\nprint(((N-1)//T) * C * P)\"\n },\n {\n \"alpha_fraction\": 0.5798319578170776,\n \"alphanum_fraction\": 0.5882353186607361,\n \"avg_line_length\": 12.333333015441895,\n \"blob_id\": \"cf0e626c5cdf52e0edcb9758a39726da0543ee38\",\n \"content_id\": \"2fc784abf4f1b3049878bd35657236cb7b2a6ba0\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 119,\n \"license_type\": \"no_license\",\n \"max_line_length\": 31,\n \"num_lines\": 9,\n \"path\": \"/알고리즘/온라인저지/2021/09/0906/돌 게임.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\ndef input():\\n return sys.stdin.readline()\\n\\nN = int(input())\\nif N%2:\\n print('SK')\\nelse:\\n print('CY')\"\n },\n {\n \"alpha_fraction\": 0.5625,\n \"alphanum_fraction\": 0.5972222089767456,\n \"avg_line_length\": 47.33333206176758,\n \"blob_id\": \"95ba1e5cf265fa9c1f74ec8759e42628ccaee2d2\",\n \"content_id\": \"ae361a4a4a315d1ee0ed3b155942b138aab6eb0d\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 144,\n \"license_type\": \"no_license\",\n \"max_line_length\": 62,\n \"num_lines\": 3,\n \"path\": \"/알고리즘/온라인저지/2022/09/0910/점수 집계.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"for _ in range(int(input())):\\n score = sorted(list(map(int, input().split())))\\n print(sum(score[1:-1]) if score[-2]-score[1]<4 else 'KIN')\"\n },\n {\n \"alpha_fraction\": 0.47663551568984985,\n \"alphanum_fraction\": 0.4953271150588989,\n \"avg_line_length\": 12.5,\n \"blob_id\": \"5305e99966fc00a221026d0ceb9381d622e1591e\",\n \"content_id\": \"7703d041c79a25ab3fa5aabc0ce4d54d85d3f3a7\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 107,\n \"license_type\": \"no_license\",\n \"max_line_length\": 19,\n \"num_lines\": 8,\n \"path\": \"/알고리즘/온라인저지/2023/06/0604/Gum Gum for Jay Jay.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"result = 0\\nwhile True:\\n try:\\n input()\\n result += 1\\n except:\\n break\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.5188323855400085,\n \"alphanum_fraction\": 0.5555555820465088,\n \"avg_line_length\": 31.212121963500977,\n \"blob_id\": \"0d47de68f1ac69ee6afb8d3b722b7e92a9b66850\",\n \"content_id\": \"2de90d8202deeadfe44b8d7561a76d1d79837cd3\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1334,\n \"license_type\": \"no_license\",\n \"max_line_length\": 145,\n \"num_lines\": 33,\n \"path\": \"/알고리즘/[템플릿]/Floyd-Warshall/Small World Network.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"INF = int(1e9)\\nN, K = map(int, input().split())\\nworld = [[INF]*N for _ in range(N)] # 친구간 거리 배열 초기화\\nfor k in range(K):\\n A, B = map(int, input().split())\\n A, B = A-1, B-1\\n world[A][B], world[B][A] = 1, 1 # 친구인 관계는 서로 거리가 1\\nfor k in range(N):\\n for i in range(N):\\n for j in range(N):\\n if i != j: # 자기 자신과 친구는 카운트하지 않음\\n world[i][j] = min(world[i][j], world[i][k]+world[k][j])\\nresult = 'Small World!' # 초기값을 Small World로 놓고 거리가 6을 초과하는 관계를 찾을 것\\nfor i in range(N):\\n if result != 'Small World!': # Small World가 아닌 것이 증명되었다면 \\n break\\n for j in range(N):\\n if i != j: # 자기 자신이 아니면서\\n if world[i][j] > 6: # 친구 거리가 6을 초과한다?\\n result = 'Big World!'\\n break\\nprint(result)\\n\\n\\\"\\\"\\\"\\n플로이드 워셜(Floyd-Warshall) 알고리즘\\nhttps://velog.io/@kimdukbae/%ED%94%8C%EB%A1%9C%EC%9D%B4%EB%93%9C-%EC%9B%8C%EC%85%9C-%EC%95%8C%EA%B3%A0%EB%A6%AC%EC%A6%98-Floyd-Warshall-Algorithm\\ni에서 j로 가는 최소값은\\n이미 구한 \\\"i에서 j로 가는 값\\\"과\\n\\\"지점 k를 거쳐가는 i -> k -> j로 가는 값\\\"\\n두 값중 최소값이다\\n\\\"\\\"\\\"\\n\\n# https://www.acmicpc.net/problem/18243\"\n },\n {\n \"alpha_fraction\": 0.4516128897666931,\n \"alphanum_fraction\": 0.49395161867141724,\n \"avg_line_length\": 23.850000381469727,\n \"blob_id\": \"512e820bfa19c7f67c9a7051ba9a524047ea89ff\",\n \"content_id\": \"0da8cd1034f9f8bebb2ce44e049a6f3f2ddb9e2e\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 572,\n \"license_type\": \"no_license\",\n \"max_line_length\": 57,\n \"num_lines\": 20,\n \"path\": \"/알고리즘/온라인저지/2022/07/0727/5학년은 다니기 싫어요.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N, A, B = map(int, input().split())\\nL = 8-N # left : 남은 학기\\nLA = 66-A # 남은 전공학점\\nLB = 130-B # 남은 총학점\\nresult = 'Nae ga wae'\\nC = [tuple(map(int, input().split())) for _ in range(10)]\\nfor l in range(L):\\n # 한 학기 최대 이수 6과목 18학점\\n LC = 6 # left credits : 남은 이번학기 수강가능 학점\\n tmp_a = C[l][0]\\n LA -= tmp_a * 3\\n LC -= tmp_a\\n tmp_b = C[l][1]\\n if LC >= tmp_b:\\n LB -= tmp_a*3 + tmp_b*3\\n else:\\n LB -= tmp_a*3 + LC*3\\n if LA<=0 and LB<=0:\\n result = 'Nice'\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.3652482330799103,\n \"alphanum_fraction\": 0.3758865296840668,\n \"avg_line_length\": 20.769229888916016,\n \"blob_id\": \"70d431864efcf07f47758276e93c4e2f4538aa05\",\n \"content_id\": \"c5f07363f66a551115347f1386cfc212040d79fc\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 282,\n \"license_type\": \"no_license\",\n \"max_line_length\": 43,\n \"num_lines\": 13,\n \"path\": \"/알고리즘/온라인저지/2022/06/0629/캥거루 세마리2.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"while True:\\n try:\\n A, B, C = map(int, input().split())\\n result = 0\\n al = abs(A-B)\\n cl = abs(B-C)\\n if al <= cl:\\n result += C - (B+1)\\n elif al > cl:\\n result += (B-1) - A\\n print(result)\\n except:\\n break\"\n },\n {\n \"alpha_fraction\": 0.4270462691783905,\n \"alphanum_fraction\": 0.47330960631370544,\n \"avg_line_length\": 30.33333396911621,\n \"blob_id\": \"caae94943f193cca55d0d8a81d89342c03f35a8a\",\n \"content_id\": \"f7e7cafdf1284645bd7865ca50f432606ad60454\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 281,\n \"license_type\": \"no_license\",\n \"max_line_length\": 40,\n \"num_lines\": 9,\n \"path\": \"/알고리즘/온라인저지/2023/01/0117/신용카드 판별.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"for _ in range(int(input())):\\n card = list(map(int, list(input())))\\n result = 0\\n for i in range(0, 16, 2):\\n card[i] = card[i]*2\\n if card[i] > 9:\\n card[i] = (card[i]%10) + 1\\n result += card[i] + card[i+1]\\n print('F' if result%10 else 'T')\"\n },\n {\n \"alpha_fraction\": 0.4673366844654083,\n \"alphanum_fraction\": 0.5376884341239929,\n \"avg_line_length\": 15.666666984558105,\n \"blob_id\": \"d75be4920374727333676c5224b901aff6dd4b4d\",\n \"content_id\": \"c3bcf21ddebe55ef918454746aa839692a93d5b7\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 199,\n \"license_type\": \"no_license\",\n \"max_line_length\": 36,\n \"num_lines\": 12,\n \"path\": \"/알고리즘/온라인저지/2022/02/0220/카드 역배치.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"cards = list(range(21))\\n\\n# a, b = 5, 10\\n# print(cards[a:b+1])\\n# print(cards[b:a-1:-1])\\n\\nfor i in range(10):\\n a, b = map(int, input().split())\\n\\n cards[a:b+1] = cards[b:a-1:-1]\\n\\nprint(*cards[1:])\"\n },\n {\n \"alpha_fraction\": 0.5909090638160706,\n \"alphanum_fraction\": 0.6818181872367859,\n \"avg_line_length\": 22,\n \"blob_id\": \"8df19a54d0fcb1c74c7f5a3d58b7ad274babc966\",\n \"content_id\": \"16266bf0be4d01829f08fe4eacc1eced2cf6690b\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 22,\n \"license_type\": \"no_license\",\n \"max_line_length\": 22,\n \"num_lines\": 1,\n \"path\": \"/알고리즘/온라인저지/2023/04/0410/時間 (Hour).py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"print(int(input())*24)\"\n },\n {\n \"alpha_fraction\": 0.516094446182251,\n \"alphanum_fraction\": 0.5364806652069092,\n \"avg_line_length\": 29.09677505493164,\n \"blob_id\": \"76a5eab002625165c0f76b5f666d8389f73defd1\",\n \"content_id\": \"d9491a9cf4a0ef349cd448793e2e2b49cf351b85\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1266,\n \"license_type\": \"no_license\",\n \"max_line_length\": 106,\n \"num_lines\": 31,\n \"path\": \"/알고리즘/온라인저지/2022/09/0927/백양로 브레이크.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\nINF = int(1e9) # 가상의, 변경해야 할 길의 수 최대값\\n\\nN, M = map(int, input().rstrip().split())\\narr = [[INF]*N for _ in range(N)]\\nfor m in range(M):\\n u, v, b = map(int, input().rstrip().split())\\n u, v = u-1, v-1 # 인덱스 맞추기\\n if b == 0: # 일방통행이면\\n arr[u][v] = 0 # 한 쪽은 괜찮지만\\n arr[v][u] = 1 # 다른 한 쪽은 길을 바꿔줘야 함\\n else: arr[u][v], arr[v][u] = 0, 0 # 양방향 통행이면 서로 오갈 수 있음\\nfor k in range(N):\\n for a in range(N):\\n for b in range(N):\\n arr[a][b] = min(arr[a][b], arr[a][k]+arr[k][b]) # 최소값(기존에 구한 변경해야 하는 길의 수, 새로 구한 변경해야 하는 길의 수)\\nK = int(input().rstrip())\\nfor k in range(K):\\n s, e = map(int, input().rstrip().split())\\n s, e = s-1, e-1 # 인덱스 맞추기\\n if s == e: print(0) # 1->1 같은 경우는 갔다 돌아오는 것이 아닌, 출발 자체를 하지 않는 것으로 함\\n else: print(arr[s][e])\\n\\n# https://www.acmicpc.net/problem/11562\\n\\\"\\\"\\\" \\n플로이드-워셜 알고리즘\\na->b 로 가기 위해 바꿔야하는 일방통행 길의 수는\\na->k->b 로 가기 위해 바꿔야 하는 길의 수와 같다\\n\\\"\\\"\\\"\"\n },\n {\n \"alpha_fraction\": 0.48927614092826843,\n \"alphanum_fraction\": 0.5080428719520569,\n \"avg_line_length\": 23.899999618530273,\n \"blob_id\": \"1db74d81d6b785893a91c892e6bfee6eced7cf1b\",\n \"content_id\": \"96579c68bc200f50ec733cfcbc2befe1f0f2d89a\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 816,\n \"license_type\": \"no_license\",\n \"max_line_length\": 48,\n \"num_lines\": 30,\n \"path\": \"/알고리즘/온라인저지/2021/09/0908/카드2.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\ndef input():\\n return sys.stdin.readline()\\n\\ndef is_odd_or_even(N):\\n if N%2:\\n return True\\n else:\\n return False\\n\\nN = int(input())\\ndeck = list(range(1, N+1))\\npop_or_keep = True # 버리기, False=살리기, 처음엔 버리면서 시작\\nwhile len(deck) > 1:\\n odd_or_even = is_odd_or_even(len(deck))\\n if odd_or_even:\\n if pop_or_keep: # 홀수, 버리기\\n deck = deck[1:len(deck)+1:2]\\n pop_or_keep = False\\n else: # 홀수, 살리기\\n deck = deck[0:len(deck):2]\\n pop_or_keep = True\\n else:\\n if pop_or_keep: # 짝수, 버리기\\n deck = deck[1:len(deck)+1:2]\\n pop_or_keep = True\\n else: # 짝수, 살리기\\n deck = deck[0:len(deck):2]\\n pop_or_keep = False\\nprint(*deck)\"\n },\n {\n \"alpha_fraction\": 0.429198682308197,\n \"alphanum_fraction\": 0.4588364362716675,\n \"avg_line_length\": 21.799999237060547,\n \"blob_id\": \"d508adfa8a62345374d6b7f670788332367213d9\",\n \"content_id\": \"7cf59cafb587050f9156da0fb6e9e7ef70049f99\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 961,\n \"license_type\": \"no_license\",\n \"max_line_length\": 35,\n \"num_lines\": 40,\n \"path\": \"/알고리즘/온라인저지/2022/07/0706/가위 바위 보.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"def RSP(player1, player2):\\n result = 0\\n if player1 == 'R':\\n if player2 == 'R':\\n result += 1 \\n elif player2 == 'S':\\n result += 2\\n elif player1 == 'S':\\n if player2 == 'S':\\n result += 1\\n elif player2 == 'P':\\n result += 2\\n elif player1 == 'P':\\n if player2 == 'R':\\n result += 2\\n elif player2 == 'P':\\n result += 1\\n return result\\n\\n\\nR = int(input())\\nSG = list(input()) # 상근\\nN = int(input())\\nfriend = [] # 친구들\\nfor n in range(N): \\n friend.append(list(input()))\\nresult1 = result2 = 0\\nfor i in range(R):\\n for f in friend: # 상근이의 점수\\n result1 += RSP(SG[i], f[i])\\n maxx = 0 # 최대점수 초기화\\n for j in 'RSP': # 최대점수 구하기\\n tmp = 0\\n for f in friend:\\n tmp += RSP(j, f[i])\\n if tmp > maxx:\\n maxx = tmp\\n result2 += maxx\\nprint(result1)\\nprint(result2)\"\n },\n {\n \"alpha_fraction\": 0.4267912805080414,\n \"alphanum_fraction\": 0.5327102541923523,\n \"avg_line_length\": 20.46666717529297,\n \"blob_id\": \"7bf847a3d0f98097b641cd3f908b7de47cd883b7\",\n \"content_id\": \"a874c41343d9e4bad382e835e1cf3c3adf7844f6\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 321,\n \"license_type\": \"no_license\",\n \"max_line_length\": 52,\n \"num_lines\": 15,\n \"path\": \"/알고리즘/온라인저지/2023/03/0317/추첨을 통해 커피를 받자.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"scores = list(map(int, input().split()))\\nmaxx = [100, 100, 200, 200, 300, 300, 400, 400, 500]\\ncoffee, hacker = 0, 0\\nfor i in range(9):\\n S, M = scores[i], maxx[i]\\n if S>M:\\n hacker = 1\\n coffee += S\\nif hacker:\\n print('hacker')\\nelse:\\n if coffee<100:\\n print('none')\\n else:\\n print('draw')\"\n },\n {\n \"alpha_fraction\": 0.3705308735370636,\n \"alphanum_fraction\": 0.3911159336566925,\n \"avg_line_length\": 20.488372802734375,\n \"blob_id\": \"8404d6428c10092faa10089a1819a6452d229fca\",\n \"content_id\": \"8c35509f58ecdd42e704b478c2f519e76fbc417d\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 923,\n \"license_type\": \"no_license\",\n \"max_line_length\": 67,\n \"num_lines\": 43,\n \"path\": \"/알고리즘/온라인저지/2021/12/1216/단지번호붙이기.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from collections import deque\\n\\ndx = (-1, 1, 0, 0)\\ndy = (0, 0, -1, 1)\\n\\nN = int(input())\\n\\nmap = [list(map(int, input())) for _ in range(N)]\\n\\ncomplex_cnt = 0\\n\\ncomplex_counts = []\\n\\nbfs = deque()\\n\\nfor i in range(N):\\n for j in range(N):\\n if map[i][j]:\\n bfs.append((i, j))\\n complex_cnt += 1\\n cnt = 0\\n while bfs:\\n tmp = bfs.popleft()\\n y = tmp[0]\\n x = tmp[1]\\n\\n if map[y][x] == 0:\\n continue\\n \\n map[y][x] = 0\\n cnt += 1\\n\\n for k in range(4):\\n ny = y + dy[k]\\n nx = x + dx[k]\\n\\n if 0 <= ny < N and 0 <= nx < N and map[ny][nx]:\\n bfs.append((ny, nx))\\n complex_counts.append(cnt)\\nprint(complex_cnt)\\ncomplex_counts.sort()\\nfor c in complex_counts:\\n print(c)\"\n },\n {\n \"alpha_fraction\": 0.47999998927116394,\n \"alphanum_fraction\": 0.4950000047683716,\n \"avg_line_length\": 21.33333396911621,\n \"blob_id\": \"93d2c3b89ce62186b3e54f3351eb66cfc59223fa\",\n \"content_id\": \"d65d3aed872b96f32cc29453b4a2b3a3a80f152a\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 200,\n \"license_type\": \"no_license\",\n \"max_line_length\": 31,\n \"num_lines\": 9,\n \"path\": \"/알고리즘/온라인저지/2022/07/0728/서로 다른 부분 문자열의 개수.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"S = input()\\nresult = set()\\nfor i in range(1, len(S)+1):\\n # print(i)\\n for j in range(len(S)+1-i):\\n # print(j, j+i)\\n # print(S[j:j+i])\\n result.add(S[j:j+i])\\nprint(len(result))\"\n },\n {\n \"alpha_fraction\": 0.5102040767669678,\n \"alphanum_fraction\": 0.5306122303009033,\n \"avg_line_length\": 11.375,\n \"blob_id\": \"bb6cec09058d814a352f6b81809e5bf48de06c9b\",\n \"content_id\": \"6588444cd13d3e54d4edbcde6867882caba78616\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 98,\n \"license_type\": \"no_license\",\n \"max_line_length\": 35,\n \"num_lines\": 8,\n \"path\": \"/알고리즘/온라인저지/2022/03/0309/帰省 (Homecoming).py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"A, B, C = map(int, input().split())\\n\\nresult = 1\\n\\nif C < A or C >= B:\\n result = 0\\n\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.5327731370925903,\n \"alphanum_fraction\": 0.5596638917922974,\n \"avg_line_length\": 21.074073791503906,\n \"blob_id\": \"f6511fe9d1495b309a9c5f6e55c0982f23c8485d\",\n \"content_id\": \"1072422906c9c0070b26901873e6452da4177d34\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 761,\n \"license_type\": \"no_license\",\n \"max_line_length\": 51,\n \"num_lines\": 27,\n \"path\": \"/알고리즘/온라인저지/2022/10/1012/골드바흐의 추측 실버1.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\n\\nn = int(1e6)\\na = [False,False] + [True]*(n-1)\\nfor i in range(2, 1001):\\n if a[i]:\\n for j in range(2*i, n+1, i):\\n a[j] = False\\nwhile True:\\n N = int(input().rstrip())\\n if N == 0: break\\n for i in range(3, n):\\n if a[N-i] and a[i]:\\n print('{} = {} + {}'.format(N, i, N-i))\\n break\\n else: print(\\\"Goldbach's conjecture is wrong.\\\")\\n\\n\\\"\\\"\\\"\\n에라토스테네스의 체를 만드는 과정에서 \\nprimes를 만들기 위해 append 하는 부분을 없앴다\\n소수판정 테이블인 a만 활용하여 시간초과를 회피하였다\\n결론적으로 골드바흐의 추측은 백만 이하 모든 짝수에 적용이 가능하다\\n\\\"\\\"\\\"\\n\\n# https://www.acmicpc.net/problem/6588\"\n },\n {\n \"alpha_fraction\": 0.4693877696990967,\n \"alphanum_fraction\": 0.4920634925365448,\n \"avg_line_length\": 19.045454025268555,\n \"blob_id\": \"8e45bcd77a990f25c7762fd852964fdc734a075e\",\n \"content_id\": \"81e9075ee4027c9f0222cceb39ddd076dc5e77c2\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 471,\n \"license_type\": \"no_license\",\n \"max_line_length\": 43,\n \"num_lines\": 22,\n \"path\": \"/알고리즘/온라인저지/2021/08/0818/p3.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\nsys.stdin = open('input.txt')\\n\\nV, E = map(int, input().split()) # 정점수, 간선수\\n# 인접 행렬\\nG = [[0]*(V+1) for _ in range(V+1)]\\nfor _ in range(E):\\n u, v = map(int, input().split())\\n G[u][v] = G[v][u] = 1\\n\\nfor lst in G[1:]:\\n print(*lst[1:])\\n\\n# 인접 리스트\\nG = [[]*(V+1) for _ in range(V+1)]\\nfor _ in range(E):\\n u, v = map(int, input().split())\\n G[u].append(v)\\n G[v].append(u)\\n\\nfor i in range(1, V+1):\\n print(i, '-->', G[i])\\n\"\n },\n {\n \"alpha_fraction\": 0.3415493071079254,\n \"alphanum_fraction\": 0.35680750012397766,\n \"avg_line_length\": 21.421052932739258,\n \"blob_id\": \"004f9b2ae1f57ef4a903e171242bfab9f48556f7\",\n \"content_id\": \"e2b52e6bad1ecd04aa04dc8b35f87542efc5c560\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 852,\n \"license_type\": \"no_license\",\n \"max_line_length\": 43,\n \"num_lines\": 38,\n \"path\": \"/알고리즘/SWEA/LEARN/Course/2. Programming Intermediate/4. 파이썬 SW문제해결 기본 Stack1/7차시 4일차 - 괄호검사.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"T = int(input())\\n\\nfor t in range(1, T+1):\\n code = input()\\n \\n stack = []\\n bracket = ['(', ')', '{', '}']\\n\\n for c in code:\\n if c == bracket[0]:\\n stack.append(c)\\n elif c == bracket[1]:\\n if stack:\\n if stack[-1] == bracket[0]:\\n stack.pop()\\n else:\\n stack.append(c)\\n else:\\n stack.append(c)\\n elif c == bracket[2]:\\n stack.append(c)\\n elif c == bracket[3]:\\n if stack:\\n if stack[-1] == bracket[2]:\\n stack.pop()\\n else:\\n stack.append(c)\\n else:\\n stack.append(c)\\n \\n result = 0\\n if stack:\\n result = 0\\n else:\\n result = 1\\n \\n \\n print('#{} {}'.format(t, result))\\n\"\n },\n {\n \"alpha_fraction\": 0.4421199560165405,\n \"alphanum_fraction\": 0.5202231407165527,\n \"avg_line_length\": 23.758621215820312,\n \"blob_id\": \"71dda0cb0c14e8369a8c7e1ac732d1a49ae65951\",\n \"content_id\": \"7b4577af0f6f1a4f77e75c801701626e41d20300\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 735,\n \"license_type\": \"no_license\",\n \"max_line_length\": 69,\n \"num_lines\": 29,\n \"path\": \"/알고리즘/[템플릿]/진법 변환/싱기한 네자리 숫자.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import string\\n\\ntmp = string.digits + string.ascii_uppercase # 자릿수를 담은 문자열\\ndigits_dict = {\\n '0': 0, '1': 1, '2': 2, '3': 3,\\n '4': 4, '5': 5, '6': 6, '7': 7,\\n '8': 8, '9': 9, 'A': 10, 'B': 11,\\n 'C': 12, 'D': 13, 'E': 14, 'F': 15,\\n}\\n\\ndef change(num, base):\\n result = ''\\n while num:\\n result = tmp[num%base] + result\\n num //= base\\n return result\\n\\ndef digits_sum(num, base):\\n result = 0\\n for n in num:\\n result += digits_dict[n]\\n return result\\n\\nfor num in range(1000, 10000):\\n A, B, C = str(num), change(num, 12), change(num, 16)\\n A, B, C = digits_sum(A, 10), digits_sum(B, 12), digits_sum(C, 16)\\n if A == B == C: print(num)\\n\\n# https://www.acmicpc.net/problem/6679\"\n },\n {\n \"alpha_fraction\": 0.47441861033439636,\n \"alphanum_fraction\": 0.4883720874786377,\n \"avg_line_length\": 22.88888931274414,\n \"blob_id\": \"0d5d793f03074caac7d1ccd253b907ad8e5029a4\",\n \"content_id\": \"4803deb43723a7786bb2d226799349067d071b19\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 430,\n \"license_type\": \"no_license\",\n \"max_line_length\": 45,\n \"num_lines\": 18,\n \"path\": \"/알고리즘/온라인저지/2022/09/0927/팰린드롬.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\nfrom itertools import combinations as comb\\n\\ninput = sys.stdin.readline\\n\\nfor _ in [0]*int(input().rstrip()):\\n K = int(input().rstrip())\\n words = [input().rstrip() for _ in [0]*K]\\n word_comb = list(comb(words, 2))\\n for a, b in word_comb:\\n A, B = a+b, b+a\\n if A == A[::-1]:\\n print(A)\\n break\\n if B == B[::-1]:\\n print(B)\\n break\\n else: print(0)\\n\"\n },\n {\n \"alpha_fraction\": 0.49841269850730896,\n \"alphanum_fraction\": 0.565079391002655,\n \"avg_line_length\": 14.800000190734863,\n \"blob_id\": \"6c32fefe76219981377494ecd95d51f729f28103\",\n \"content_id\": \"16d8e9027e414e818cafca4d84b79e9a58b132fd\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 439,\n \"license_type\": \"no_license\",\n \"max_line_length\": 34,\n \"num_lines\": 20,\n \"path\": \"/알고리즘/온라인저지/2022/09/0904/애너그램 만들기.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"A, B = input(), input()\\narr1, arr2 = [0]*26, [0]*26\\nfor a in A:\\n i = ord(a)-97\\n arr1[i] += 1\\nfor b in B:\\n i = ord(b)-97\\n arr2[i] += 1\\nresult = 0\\nfor i in range(26):\\n result += abs(arr1[i]-arr2[i])\\nprint(result)\\n\\n\\\"\\\"\\\"\\n같은 알파벳이 같은 개수만큼 있어야 함\\n문제에서는 알파벳을 새로 추가하지는 않고\\n불필요할 경우 제거하면서\\n애너그램을 만듬\\n몇개를 제거해야 하는가\\n\\\"\\\"\\\"\"\n },\n {\n \"alpha_fraction\": 0.5340909361839294,\n \"alphanum_fraction\": 0.5454545617103577,\n \"avg_line_length\": 28.5,\n \"blob_id\": \"a7cdbeb11674ae8d0d57c18a9057da971dd7f7f3\",\n \"content_id\": \"5e6094fc851320c16ad1588ebb85d0c73b1911a9\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 176,\n \"license_type\": \"no_license\",\n \"max_line_length\": 39,\n \"num_lines\": 6,\n \"path\": \"/알고리즘/온라인저지/2022/09/0910/공 바꾸기.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N, M = map(int, input().split())\\nball = [i for i in range(N+1)]\\nfor m in range(M):\\n i, j = map(int, input().split())\\n ball[i], ball[j] = ball[j], ball[i]\\nprint(*ball[1:])\"\n },\n {\n \"alpha_fraction\": 0.4644128084182739,\n \"alphanum_fraction\": 0.4750889539718628,\n \"avg_line_length\": 27.149999618530273,\n \"blob_id\": \"40ebdb5d59e66505db4f48252e24b4b7fcc191ec\",\n \"content_id\": \"1bc7491ce79e3fc1b445c413c85885089badae2c\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 562,\n \"license_type\": \"no_license\",\n \"max_line_length\": 61,\n \"num_lines\": 20,\n \"path\": \"/알고리즘/온라인저지/2023/02/0205/운동.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"INF = int(1e9)\\nN, M = map(int, input().split())\\narr = [[INF]*N for _ in range(N)]\\nfor m in range(M):\\n a, b, c = map(int, input().split())\\n a, b = a-1, b-1\\n if c < arr[a][b]:\\n arr[a][b] = c\\nfor k in range(N):\\n for a in range(N):\\n for b in range(N):\\n arr[a][b] = min(arr[a][b], arr[a][k] + arr[k][b])\\nfor i in range(N):\\n for j in range(N):\\n if arr[i][j] == INF:\\n if i != j:\\n arr[i][j] = 0\\nresult = INF\\nfor i in range(N): result = min(result, arr[i][i])\\nprint(result if result != INF else -1)\"\n },\n {\n \"alpha_fraction\": 0.5643564462661743,\n \"alphanum_fraction\": 0.594059407711029,\n \"avg_line_length\": 19.399999618530273,\n \"blob_id\": \"42777dea1921398b57e879dcf9cb87dc95cf1ea9\",\n \"content_id\": \"d41d4a801154684d5fea2ddf2005e2e126d547de\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 101,\n \"license_type\": \"no_license\",\n \"max_line_length\": 34,\n \"num_lines\": 5,\n \"path\": \"/알고리즘/온라인저지/2023/01/0125/반지.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"S = input()\\nresult = 0\\nfor _ in range(int(input())):\\n if S in input()*2: result += 1\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.4342857003211975,\n \"alphanum_fraction\": 0.477142870426178,\n \"avg_line_length\": 19.647058486938477,\n \"blob_id\": \"016f357231ee172f2a6dcc7ee5a38830981a0975\",\n \"content_id\": \"bac9c4768c4f4e81310bcaf4398bb68b7dedbf91\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 362,\n \"license_type\": \"no_license\",\n \"max_line_length\": 35,\n \"num_lines\": 17,\n \"path\": \"/알고리즘/온라인저지/2022/08/0822/분수찾기.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = int(input())\\nprev, next, line, move = 0, 0, 0, 0\\nD = 1 # 우상향: 1, 좌하향: 0\\nfor cnt in range(1, int(1e9)):\\n next += cnt\\n if prev <= N <= next:\\n line, move = cnt, N-prev-1\\n D = line%2\\n break\\n prev += cnt\\n# print(line, move, D)\\nA, B = 1, line\\nfor i in range(move):\\n A += 1\\n B -= 1\\nif D: A, B = B, A\\nprint(f'{A}/{B}')\"\n },\n {\n \"alpha_fraction\": 0.540229856967926,\n \"alphanum_fraction\": 0.5747126340866089,\n \"avg_line_length\": 13.666666984558105,\n \"blob_id\": \"a294395c9bb265de35aac2207275ad0452881131\",\n \"content_id\": \"724b46bc776a635c7e5fbf9d6e26af4328050078\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 87,\n \"license_type\": \"no_license\",\n \"max_line_length\": 22,\n \"num_lines\": 6,\n \"path\": \"/알고리즘/온라인저지/2022/05/0511/택시 기하학.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import math\\n\\npi = math.pi\\nR = int(input())\\nprint(f'{pi*R*R:.6f}')\\nprint(f'{2*R*R:.6f}')\"\n },\n {\n \"alpha_fraction\": 0.5221238732337952,\n \"alphanum_fraction\": 0.5398229956626892,\n \"avg_line_length\": 21.799999237060547,\n \"blob_id\": \"62e10a003fc3d3e44b13928626243ef68046055b\",\n \"content_id\": \"1f1043882482b8847d269423898de6b17f14d4c7\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 113,\n \"license_type\": \"no_license\",\n \"max_line_length\": 41,\n \"num_lines\": 5,\n \"path\": \"/알고리즘/온라인저지/2023/05/0502/Intercepting Information.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"result = 'S'\\nfor i in list(map(int, input().split())):\\n if i not in (0, 1):\\n result = 'F'\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.53125,\n \"alphanum_fraction\": 0.53125,\n \"avg_line_length\": 31.200000762939453,\n \"blob_id\": \"eafb7e2e1d27ffa87fa5b4dd9a34abb0fce4b3d6\",\n \"content_id\": \"115e532b9127217c6b23f6215be0d7048cd25e31\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 160,\n \"license_type\": \"no_license\",\n \"max_line_length\": 66,\n \"num_lines\": 5,\n \"path\": \"/알고리즘/온라인저지/2022/05/0527/할로윈의 사탕.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"T = int(input())\\nfor t in range(T):\\n C, V = map(int, input().split())\\n A, B = C//V, C%V\\n print(f'You get {A} piece(s) and your dad gets {B} piece(s).')\"\n },\n {\n \"alpha_fraction\": 0.5161290168762207,\n \"alphanum_fraction\": 0.524193525314331,\n \"avg_line_length\": 14.625,\n \"blob_id\": \"d889ff6505f2e7edd42dc18ae8ca83319f090a50\",\n \"content_id\": \"0452676e22d32d0d7b28be9a89c1c82b73d8dba0\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 124,\n \"license_type\": \"no_license\",\n \"max_line_length\": 38,\n \"num_lines\": 8,\n \"path\": \"/알고리즘/온라인저지/2022/02/0223/Darius님 한타 안 함.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"K, D, A = map(int, input().split('/'))\\n\\nis_Darius = 'gosu'\\n\\nif K + A < D or D == 0:\\n is_Darius = 'hasu'\\n\\nprint(is_Darius)\"\n },\n {\n \"alpha_fraction\": 0.50310879945755,\n \"alphanum_fraction\": 0.5207253694534302,\n \"avg_line_length\": 30.129032135009766,\n \"blob_id\": \"8b1def6b78499f45901cb2d021376703bdb59cfd\",\n \"content_id\": \"417a7f974598cdd41dfaf4bdc852f6ab73c97ccd\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 2104,\n \"license_type\": \"no_license\",\n \"max_line_length\": 72,\n \"num_lines\": 62,\n \"path\": \"/알고리즘/온라인저지/2022/11/1113/연구소 3.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\nfrom itertools import combinations as comb\\nfrom collections import deque\\n\\ninput = sys.stdin.readline\\ndy, dx = [-1, 1, 0, 0], [0, 0, -1, 1]\\n\\ndef spread_virus(viruses):\\n new_arr = [[-1]*N for _ in range(N)] # 문제의 예시처럼, 바이러스가 퍼진 시간을 기록할 배열\\n # deactivate other viruses\\n for i in range(N):\\n for j in range(N):\\n if new_arr[i][j] == 2 and (i, j) not in viruses:\\n new_arr[i][j] = 3\\n Q = deque()\\n visited = [[0]*N for _ in range(N)]\\n for y, x in viruses: \\n Q.append((y, x))\\n new_arr[y][x] = 0\\n visited[y][x] = 1\\n while Q:\\n y, x = Q.popleft()\\n for i in range(4):\\n ny, nx = y+dy[i], x+dx[i]\\n if 0<=ny<N and 0<=nx<N and not visited[ny][nx]:\\n if arr[ny][nx] != 1:\\n Q.append((ny, nx))\\n new_arr[ny][nx] = new_arr[y][x]+1\\n visited[ny][nx] = 1\\n all_spreaded_check(new_arr, visited)\\n\\ndef all_spreaded_check(arr, visited):\\n global result\\n new_wall = 0\\n max_time = 0\\n for i in range(N):\\n for j in range(N):\\n if (i, j) not in virus_coordinates: # 바이러스의 시간은 카운트하지 않는다\\n max_time = max(max_time, arr[i][j])\\n if visited[i][j] == 0:\\n new_wall += 1\\n if wall == new_wall: # \\n result = min(max_time, result)\\n\\nN, M = map(int, input().rstrip().split())\\narr = [list(map(int, input().rstrip().split())) for _ in range(N)]\\nvirus_coordinates = []\\nwall = 0\\nfor i in range(N):\\n for j in range(N):\\n if arr[i][j] == 2:\\n virus_coordinates.append((i, j))\\n if arr[i][j] == 1:\\n wall += 1\\nvirus_combinations = list(comb(virus_coordinates, M))\\nresult = int(1e9) # 가상의 최소값\\nfor viruses in virus_combinations: # 매 바이러스 조합에 대해\\n spread_virus(viruses) # 바이러스 퍼뜨리기\\nif result == int(1e9): result = -1 # 한 번도 바이러스가 다 퍼지지 못했다면 -1\\nprint(result)\\n\\n# 문제가 좀 이상합니다....;;\\n\"\n },\n {\n \"alpha_fraction\": 0.48785871267318726,\n \"alphanum_fraction\": 0.50772625207901,\n \"avg_line_length\": 16.461538314819336,\n \"blob_id\": \"45636644c2553054f49a5fee7f48dadca7be41a8\",\n \"content_id\": \"95a6912609e8c8008c85f750fb8636b4600baaf7\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 453,\n \"license_type\": \"no_license\",\n \"max_line_length\": 43,\n \"num_lines\": 26,\n \"path\": \"/알고리즘/SWEA/LEARN/Course/1. Programming Beginner/파이썬 프로그래밍 기초(2)/39차시 4. 문자열 - 연습문제 3.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"url = 'http://www.example.com/test?p=1&q=2'\\n\\nprotocol = ''\\nhost = ''\\nothers = ''\\n\\nhost_s = 0\\nhost_e = 0\\n\\nfor i in range(len(url)):\\n if url[i] == ':':\\n protocol = url[:i]\\n \\n if url[i:i+3] == 'www':\\n host_s = i\\n \\n if url[i-2:i+1] == 'com':\\n host_e = i+1\\n\\n others = url[host_e+1:]\\n\\nhost = url[host_s:host_e]\\n\\nprint('protocol: {}'.format(protocol))\\nprint('host: {}'.format(host))\\nprint('others: {}'.format(others))\"\n },\n {\n \"alpha_fraction\": 0.5047393441200256,\n \"alphanum_fraction\": 0.521327018737793,\n \"avg_line_length\": 31.538461685180664,\n \"blob_id\": \"9feaef80329af9a8f18552245f1c508b4f984506\",\n \"content_id\": \"e1eaffeebcbf31c3da2b5eb2ca5b9d6fdbf24216\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 612,\n \"license_type\": \"no_license\",\n \"max_line_length\": 45,\n \"num_lines\": 13,\n \"path\": \"/알고리즘/온라인저지/2022/04/0410/짐 챙기는 숌.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N, M = map(int, input().split())\\nif N > 0: # 담아야 할 책이 있으면\\n books = list(map(int, input().split()))\\n result = 1 # 상자를 하나 가져다 놓고\\n box = M # 상자에 담을 수 있는 무게는 M\\n for book in books: # 책들을 순회하면서\\n box -= book # 상자에 책을 하나씩 담는다\\n if box < 0: # 상자에 책을 담을 수 없으면\\n box = M - book # 다음 상자를 가져와 책을 담고\\n result += 1 # 상자 개수를 +1\\nelse: # 담아야 할 책이 없으면\\n result = 0 # 필요한 상자의 개수는 0\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.5694444179534912,\n \"alphanum_fraction\": 0.5972222089767456,\n \"avg_line_length\": 35.5,\n \"blob_id\": \"5e2fe2a5437e66924459c3b5c46e2c545f46e2f7\",\n \"content_id\": \"fb0fd3cfe6cc4fc499a9e1582326dfb327a5ddb3\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 72,\n \"license_type\": \"no_license\",\n \"max_line_length\": 37,\n \"num_lines\": 2,\n \"path\": \"/알고리즘/온라인저지/2022/02/0207/Hello Judge.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"for i in range(1, int(input())+1):\\n print(f'Hello World, Judge {i}!')\"\n },\n {\n \"alpha_fraction\": 0.4193548262119293,\n \"alphanum_fraction\": 0.43478259444236755,\n \"avg_line_length\": 24.285715103149414,\n \"blob_id\": \"631f204724be1a670b34bdbe17d146ee2ff5cafd\",\n \"content_id\": \"c5477022311522dde65d7794260ce7e175e41b4b\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 713,\n \"license_type\": \"no_license\",\n \"max_line_length\": 45,\n \"num_lines\": 28,\n \"path\": \"/알고리즘/온라인저지/2021/12/1216/약수들의 합.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"while True:\\n n = int(input())\\n\\n if n == -1:\\n break\\n\\n measure_counts = [0 for _ in range(n+1)]\\n measures = []\\n\\n for i in range(1, n+1):\\n if not measure_counts[i]:\\n if n % i == 0:\\n measure_counts[i] = 1\\n measure_counts[n//i] = 1\\n measures.append(i)\\n measures.append(n//i)\\n\\n measures.sort()\\n\\n if sum(measures[:len(measures)-1]) == n:\\n print('{} = '.format(n), end='')\\n for i in range(len(measures)-1):\\n print(measures[i], end='')\\n if i != len(measures)-2:\\n print(' + ', end='')\\n print() \\n else:\\n print('{} is NOT perfect.'.format(n))\\n \\n\"\n },\n {\n \"alpha_fraction\": 0.4487309753894806,\n \"alphanum_fraction\": 0.46700507402420044,\n \"avg_line_length\": 21.930233001708984,\n \"blob_id\": \"e82d6603afa5da2de0463db4bbf39e0621a53c6c\",\n \"content_id\": \"ee8b88e44c21ba4fabe914d3505608aa63897781\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 985,\n \"license_type\": \"no_license\",\n \"max_line_length\": 82,\n \"num_lines\": 43,\n \"path\": \"/알고리즘/온라인저지/2022/06/0629/적록색약.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from collections import deque\\nimport sys\\n\\n\\ndef input():\\n return sys.stdin.readline()\\n\\ndef bfs(i, j):\\n q.append((i, j))\\n now = arr[i][j]\\n while q:\\n y, x = q.popleft()\\n visited[y][x] = 1\\n for k in range(4):\\n ny, nx = y+dy[k], x+dx[k]\\n if 0<=ny<N and 0<=nx<N and not visited[ny][nx] and arr[ny][nx] == now:\\n if (ny, nx) not in q:\\n q.append((ny, nx))\\n\\n\\ndx = [1, -1, 0, 0]\\ndy = [0, 0, 1, -1]\\nN = int(input())\\narr = [list(input()) for _ in range(N)]\\nNCB = 0 # Non Color Blindness\\nCB = 0 # Color Blindness\\nvisited = [[0]*N for _ in range(N)]\\nq = deque()\\nfor i in range(N):\\n for j in range(N):\\n if not visited[i][j]:\\n bfs(i, j)\\n NCB += 1\\n if arr[i][j] in 'RG':\\n arr[i][j] = 'Y'\\nvisited = [[0]*N for _ in range(N)]\\nq = deque()\\nfor i in range(N):\\n for j in range(N):\\n if not visited[i][j]:\\n bfs(i, j)\\n CB += 1\\nprint(NCB, CB)\"\n },\n {\n \"alpha_fraction\": 0.27398988604545593,\n \"alphanum_fraction\": 0.3156565725803375,\n \"avg_line_length\": 26.34482765197754,\n \"blob_id\": \"13511a4d459a9c8cc73c79a5a9b4e690180c7dab\",\n \"content_id\": \"dcd20864ad5c1b406836a139cab7c502c350d4a9\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 792,\n \"license_type\": \"no_license\",\n \"max_line_length\": 45,\n \"num_lines\": 29,\n \"path\": \"/알고리즘/SWEA/LEARN/Course/2. Programming Intermediate/2. 파이썬 SW문제해결 기본 List2/5차시 2일차 - 색칠하기.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"T = int(input())\\n\\nfor t in range(1, T+1):\\n arr = [[0]*10 for _ in range(10)]\\n N = int(input())\\n for n in range(N):\\n tmp = list(map(int, input().split()))\\n r1 = tmp[0]\\n c1 = tmp[1]\\n r2 = tmp[2]\\n c2 = tmp[3]\\n \\n for i in range(c1, c2+1):\\n for j in range(r1, r2+1):\\n if tmp[4] == 1:\\n if arr[i][j] == 0:\\n arr[i][j] = 1\\n elif arr[i][j] == 2:\\n arr[i][j] = 3\\n else:\\n if arr[i][j] == 0:\\n arr[i][j] = 2\\n elif arr[i][j] == 1:\\n arr[i][j] = 3\\n \\n cnt = 0\\n for a in arr:\\n cnt += a.count(3)\\n print('#{} {}'.format(t, cnt))\"\n },\n {\n \"alpha_fraction\": 0.3867403268814087,\n \"alphanum_fraction\": 0.4806629717350006,\n \"avg_line_length\": 19.22222137451172,\n \"blob_id\": \"6b2ab27b4a2525c8359ebad206593023a920ccdb\",\n \"content_id\": \"f434eccb490458f6dba43731400fe2eee5f7abed\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 181,\n \"license_type\": \"no_license\",\n \"max_line_length\": 41,\n \"num_lines\": 9,\n \"path\": \"/알고리즘/온라인저지/2023/06/0613/Vending Machine.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"result = 5000\\nfor i in list(map(int, input().split())):\\n if i == 1:\\n result -= 500\\n if i == 2:\\n result -= 800\\n if i == 3:\\n result -= 1000\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.4347222149372101,\n \"alphanum_fraction\": 0.4763889014720917,\n \"avg_line_length\": 23.03333282470703,\n \"blob_id\": \"7c84ee759fb606740b73fba316acad914bba8fe6\",\n \"content_id\": \"7703df2598d60ad15636caea02e6a1900d898ae7\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 826,\n \"license_type\": \"no_license\",\n \"max_line_length\": 63,\n \"num_lines\": 30,\n \"path\": \"/알고리즘/온라인저지/2021/07/0731/바둑알 십자 뒤집기.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"num = 19\\nboard = [[int(x) for x in input().split()] for y in range(num)]\\n\\nn = int(input())\\n\\npoints = []\\nfor i in range(n): # 뒤집을 점들의 개수만큼\\n a, b = map(int, input().split())\\n points.append([a, b])\\n # 입력 받아서 좌표들을 리스트로 저장\\n \\ndef cross(x, y): # 십자뒤집기 로직\\n for i in range(19):\\n if board[x-1][i] == 0: # 가로줄 0 -> 1, 1 -> 0\\n board[x-1][i] = 1\\n else:\\n board[x-1][i] = 0\\n if board[i][y-1] == 0: # 세로줄 0 -> 1, 1 -> 0\\n board[i][y-1] = 1\\n else:\\n board[i][y-1] = 0\\n return board\\n\\nfor point in points:\\n cross(point[0], point[1]) # 좌표들 각각 십자뒤집기 실행\\n\\nfor i in range(19) :\\n for j in range(19) : \\n print(board[i][j], end=' ')\\n print() # 출력문\"\n },\n {\n \"alpha_fraction\": 0.5121951103210449,\n \"alphanum_fraction\": 0.5528455376625061,\n \"avg_line_length\": 17.5,\n \"blob_id\": \"e031ae14019c67b34994abd1c79038cac7fdf513\",\n \"content_id\": \"d105034d93d06424410618a16d4d78cbc26cd513\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 369,\n \"license_type\": \"no_license\",\n \"max_line_length\": 40,\n \"num_lines\": 20,\n \"path\": \"/알고리즘/온라인저지/2021/12/1216/네 번째 점.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"xdots = [0 for _ in range(1001)]\\nydots = [0 for _ in range(1001)]\\n\\nfor _ in range(3):\\n x, y = map(int, input().split())\\n xdots[x] += 1\\n ydots[y] += 1\\n\\nresult = []\\n\\nfor xdot in xdots:\\n if xdot == 1:\\n result.append(xdots.index(xdot))\\n\\nfor ydot in ydots:\\n if ydot == 1:\\n result.append(ydots.index(ydot))\\n\\nfor r in result:\\n print(r, end=' ')\"\n },\n {\n \"alpha_fraction\": 0.44262295961380005,\n \"alphanum_fraction\": 0.5081967115402222,\n \"avg_line_length\": 30,\n \"blob_id\": \"010fbfd4bbf22c0e592821180288e6ac9992445c\",\n \"content_id\": \"5e1aca49f575780f525c1526e381d54ab496a5e3\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 61,\n \"license_type\": \"no_license\",\n \"max_line_length\": 36,\n \"num_lines\": 2,\n \"path\": \"/알고리즘/온라인저지/2022/08/0824/РАВЕНСТВО.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = [int(input()) for _ in range(3)]\\nprint((N[1]-N[2])//N[0])\"\n },\n {\n \"alpha_fraction\": 0.6334232091903687,\n \"alphanum_fraction\": 0.6522911190986633,\n \"avg_line_length\": 25.571428298950195,\n \"blob_id\": \"ef7c60a74127183882dbef9b2df582a0b8811e42\",\n \"content_id\": \"612047f27f063d514d94910c86fbad5c28ec2ac7\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 473,\n \"license_type\": \"no_license\",\n \"max_line_length\": 75,\n \"num_lines\": 14,\n \"path\": \"/알고리즘/[템플릿]/스택/옥상 정원 꾸미기.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\n\\nstack = []\\nresult = 0\\nfor _ in [0]*int(input().rstrip()):\\n height = int(input().rstrip())\\n while stack and height>=stack[-1]: stack.pop() # 스택안의, 높이가 낮은 건물들 전부 삭제\\n result += len(stack) # while문을 통과하고 스택에 남아있는 건물들은, 현재 건물의 옥상을 볼 수 있다\\n stack.append(height) # 현재 건물 추가\\nprint(result)\\n\\n# https://www.acmicpc.net/problem/6198\"\n },\n {\n \"alpha_fraction\": 0.4453781545162201,\n \"alphanum_fraction\": 0.462184876203537,\n \"avg_line_length\": 16,\n \"blob_id\": \"d191d344d1772fa911791a9719ec5fbabd47ca89\",\n \"content_id\": \"905e9f8858de030ab07f2fe3d9c069e3dc41c593\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 119,\n \"license_type\": \"no_license\",\n \"max_line_length\": 22,\n \"num_lines\": 7,\n \"path\": \"/알고리즘/온라인저지/2023/04/0417/골뱅이 찍기 - 뒤집힌 ㄱ.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = int(input())\\nfor _ in range(N):\\n print('@'*5*N)\\n\\nfor _ in range(4):\\n for _ in range(N):\\n print('@'*N)\\n\"\n },\n {\n \"alpha_fraction\": 0.5378378629684448,\n \"alphanum_fraction\": 0.5837838053703308,\n \"avg_line_length\": 19.61111068725586,\n \"blob_id\": \"cd4c0641d347168d0a81d56edce7c07bf640c3dd\",\n \"content_id\": \"500281a035c64fff5186ade3d3c1da9e9296f8c9\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 370,\n \"license_type\": \"no_license\",\n \"max_line_length\": 45,\n \"num_lines\": 18,\n \"path\": \"/알고리즘/온라인저지/2022/09/0917/게임.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\n\\nX, Y = map(int, input().rstrip().split())\\nZ = int((Y*100/X))\\nresult = -1\\nstart, end = 1, int(1e9)\\nwhile start<=end:\\n mid = (start+end) // 2\\n new_win_rate = int(((Y+mid)*100/(X+mid)))\\n if new_win_rate>Z:\\n result = mid\\n end = mid-1\\n else: start = mid+1\\nprint(result)\\n\\n# https://www.acmicpc.net/problem/1072\"\n },\n {\n \"alpha_fraction\": 0.6126760840415955,\n \"alphanum_fraction\": 0.6126760840415955,\n \"avg_line_length\": 27.600000381469727,\n \"blob_id\": \"7abf3a70da02db24fdd86d7ef1569e8f60001d0c\",\n \"content_id\": \"a2a0f6c5447cd40d2fa344b31437a12512306dfa\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 142,\n \"license_type\": \"no_license\",\n \"max_line_length\": 39,\n \"num_lines\": 5,\n \"path\": \"/알고리즘/온라인저지/2022/06/0610/다리 놓기.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from math import factorial as fact\\n\\nfor t in range(int(input())):\\n N, M = map(int, input().split())\\n print(fact(M)//(fact(N)*fact(M-N)))\"\n },\n {\n \"alpha_fraction\": 0.4444444477558136,\n \"alphanum_fraction\": 0.4722222089767456,\n \"avg_line_length\": 17.16666603088379,\n \"blob_id\": \"a9b8a8100175d62d41cb14a60df0a31fff677889\",\n \"content_id\": \"d7f600153bc46cc3837dd9c86a9242dd655c76dc\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 108,\n \"license_type\": \"no_license\",\n \"max_line_length\": 32,\n \"num_lines\": 6,\n \"path\": \"/알고리즘/온라인저지/2023/04/0405/AdivB - 3.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"A, B = map(int, input().split())\\nC, D = A//B, A%B\\nif A != 0 and D < 0:\\n C, D = C+1, D-B\\nprint(C)\\nprint(D)\"\n },\n {\n \"alpha_fraction\": 0.5226939916610718,\n \"alphanum_fraction\": 0.5710102319717407,\n \"avg_line_length\": 25.30769157409668,\n \"blob_id\": \"7ba113b810dcf22249633f575884d9ba159d2299\",\n \"content_id\": \"c6942e3e6259beba02df84ebcc88092269eece56\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 963,\n \"license_type\": \"no_license\",\n \"max_line_length\": 79,\n \"num_lines\": 26,\n \"path\": \"/알고리즘/온라인저지/2022/09/0904/마라톤 1.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = int(input())\\ncheck = [tuple(map(int, input().split())) for _ in range(N)]\\nresult = 0\\nfor i in range(N-1):\\n A, B = check[i], check[i+1]\\n result += abs(A[0]-B[0]) + abs(A[1]-B[1])\\ndist = 0\\nfor i in range(1, N-1):\\n A, B, C = check[i-1], check[i], check[i+1]\\n jump = abs(A[0]-C[0]) + abs(A[1]-C[1])\\n no_jump = abs(A[0]-B[0]) + abs(A[1]-B[1]) + abs(B[0]-C[0]) + abs(B[1]-C[1])\\n tmp = no_jump - jump\\n dist = max(dist, tmp)\\nprint(result - dist)\\n\\n\\\"\\\"\\\"\\n구간을 점프할 때 얻을 수 있는 이익을 모아 테이블을 만든다\\n예제에서 B를 점프했을 때 얻는 이익값이 6\\nC를 점프했을 때 얻는 이익값이 4이다\\n그러면 B를 점프하는게 동선을 가장 단축시킬 수 있고\\n이 이익값 6을 전체 경로 20에서 빼주면 14가 나온다\\n0번과 N-1번을 제외한 점들에서\\n해당 점을 빼고 뛰었을 때 얻을 수 있는 이익값 테이블의\\n최대값을\\n전체 경로값에서 빼준다\\n\\\"\\\"\\\"\"\n },\n {\n \"alpha_fraction\": 0.4611872136592865,\n \"alphanum_fraction\": 0.465753436088562,\n \"avg_line_length\": 17.33333396911621,\n \"blob_id\": \"967fd978ba580198d4f1630215bbcb42abf70020\",\n \"content_id\": \"3cd1e346ece2d616aed71c4d71add1478699d8ad\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 219,\n \"license_type\": \"no_license\",\n \"max_line_length\": 32,\n \"num_lines\": 12,\n \"path\": \"/알고리즘/온라인저지/2022/02/0220/오타맨 고창영.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"T = int(input())\\n\\nfor t in range(T):\\n typo, word = input().split()\\n typo = int(typo)\\n\\n for i in range(len(word)):\\n if i == typo-1:\\n continue\\n \\n print(word[i], end='')\\n print()\"\n },\n {\n \"alpha_fraction\": 0.6790123581886292,\n \"alphanum_fraction\": 0.6790123581886292,\n \"avg_line_length\": 26.33333396911621,\n \"blob_id\": \"95d0e611b79f837cae23b6f73e2cb7c6dff29da7\",\n \"content_id\": \"b7c51a149fbdc6c908443cc23a5cef1fef5a365f\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 81,\n \"license_type\": \"no_license\",\n \"max_line_length\": 52,\n \"num_lines\": 3,\n \"path\": \"/알고리즘/온라인저지/2022/02/0206/연세대학교.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"yonsei = ['YONSEI', 'Leading the Way to the Future']\\n\\nprint(yonsei[int(input())])\"\n },\n {\n \"alpha_fraction\": 0.4554140269756317,\n \"alphanum_fraction\": 0.4792993664741516,\n \"avg_line_length\": 22.296297073364258,\n \"blob_id\": \"39b5423590f79a4e3321a43ab377de8dc30a8c26\",\n \"content_id\": \"905d88d290dbbb081a227e2a05baf31392afb0fb\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 628,\n \"license_type\": \"no_license\",\n \"max_line_length\": 39,\n \"num_lines\": 27,\n \"path\": \"/알고리즘/온라인저지/2022/12/1221/별 찍기 - 19.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"def fill(arr):\\n for k in range(0, size//2+1, 2):\\n for i in range(k, size-k):\\n arr[i][k] = 1\\n\\ndef rotate(arr):\\n new_arr = []\\n for j in range(size):\\n tmp = []\\n for i in range(size-1, -1, -1):\\n tmp.append(arr[i][j])\\n new_arr.append(tmp)\\n return new_arr\\n\\nN = int(input())\\nsize = 1\\nfor _ in range((N-1)*2): size += 2\\narr = [[0]*size for _ in range(size)]\\nfor _ in range(4):\\n fill(arr)\\n arr = rotate(arr)\\nfor i in range(size):\\n for j in range(size):\\n if arr[i][j]:\\n print('*', end='')\\n else: print(' ', end='')\\n if i != size-1: print()\"\n },\n {\n \"alpha_fraction\": 0.5810526609420776,\n \"alphanum_fraction\": 0.6084210276603699,\n \"avg_line_length\": 19.69565200805664,\n \"blob_id\": \"c39366f266d2dcc4360ea6ae5155c4c3c7309c63\",\n \"content_id\": \"19dc3a718fec769ac295364e41313ae87ee6eeea\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 475,\n \"license_type\": \"no_license\",\n \"max_line_length\": 41,\n \"num_lines\": 23,\n \"path\": \"/알고리즘/온라인저지/2022/10/1002/정수 a를 k로 만들기.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\nfrom collections import deque\\n\\ninput = sys.stdin.readline\\n\\ndef move(next, new_cnt):\\n if 0<=next<mxl and not visited[next]:\\n Q.append((next, new_cnt))\\n visited[next] = 1\\n\\nA, K = map(int, input().rstrip().split())\\nmxl = int(1e6)+1 # max_length\\nvisited = [0]*mxl\\nQ = deque()\\nQ.append((A, 0))\\nvisited[A] = 1\\nresult = 0\\nwhile Q:\\n now, cnt = Q.popleft()\\n if now == K: result = cnt; break\\n move(now+1, cnt+1)\\n move(now*2, cnt+1)\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.3992537260055542,\n \"alphanum_fraction\": 0.41791045665740967,\n \"avg_line_length\": 16.933332443237305,\n \"blob_id\": \"04235cfffc577a348d6e139b2c5008be68e466ee\",\n \"content_id\": \"64c696378d5ea916b5f63b7120f057979f9e7301\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 268,\n \"license_type\": \"no_license\",\n \"max_line_length\": 25,\n \"num_lines\": 15,\n \"path\": \"/알고리즘/온라인저지/2021/08/0819/제로.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"K = int(input())\\nstack = []\\ntop = -1\\nfor k in range(K):\\n num = int(input())\\n if num == 0:\\n if top == -1:\\n continue\\n else:\\n stack.pop()\\n top -= 1\\n else:\\n stack.append(num)\\n top += 1\\nprint(sum(stack))\"\n },\n {\n \"alpha_fraction\": 0.4109589159488678,\n \"alphanum_fraction\": 0.4931506812572479,\n \"avg_line_length\": 36,\n \"blob_id\": \"4f25ba821a074fd89a640514f11ce01121b63480\",\n \"content_id\": \"fb89847feee8c83fcf67b87caae0f2c3539dd923\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 73,\n \"license_type\": \"no_license\",\n \"max_line_length\": 36,\n \"num_lines\": 2,\n \"path\": \"/알고리즘/온라인저지/2022/09/0904/移動 (Moving).py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"H = [int(input()) for _ in range(3)]\\nprint(int(H[0] + H[1] < H[2] + 0.5))\"\n },\n {\n \"alpha_fraction\": 0.4285714328289032,\n \"alphanum_fraction\": 0.5428571701049805,\n \"avg_line_length\": 35,\n \"blob_id\": \"313ed2e7b33735e25b1d17d812d33d06be4bedc5\",\n \"content_id\": \"593b64b86972e231183efb09b400a508dd001149\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 35,\n \"license_type\": \"no_license\",\n \"max_line_length\": 35,\n \"num_lines\": 1,\n \"path\": \"/알고리즘/온라인저지/2023/02/0226/Atrium.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"print(f'{int(input())**0.5*4:.8f}')\"\n },\n {\n \"alpha_fraction\": 0.4540654718875885,\n \"alphanum_fraction\": 0.47729673981666565,\n \"avg_line_length\": 26.882352828979492,\n \"blob_id\": \"8eaa5f70aadd78318ed44b147304f96b8418c845\",\n \"content_id\": \"a7b5330e01fc9167e8980ca0e095d89e915b7ec6\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1207,\n \"license_type\": \"no_license\",\n \"max_line_length\": 58,\n \"num_lines\": 34,\n \"path\": \"/알고리즘/온라인저지/2022/07/0709/단지번호붙이기.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from collections import deque\\n\\n\\ndef bfs(y, x): # 단지 내 가구 수 탐색 BFS\\n Q.append((y, x))\\n cnt = 0\\n while Q:\\n y, x = Q.popleft()\\n if arr[y][x] == 0: # Q에 넣어놓은 사이에 탐색을 마친 경우라면\\n continue # 컨티뉴\\n arr[y][x] = 0 # 해당 위치 탐색 완료\\n cnt += 1 # 단지 내 가구 수 ++\\n for i in range(4):\\n ny = y+dy[i]\\n nx = x+dx[i]\\n if 0<=ny<N and 0<=nx<N and arr[ny][nx]: \\n # 지도의 범위를 벗어나지 않으면서 이웃한 단지이면\\n Q.append((ny, nx))\\n return cnt # 단지 내 가구 수 반환\\n\\n\\ndy = [-1, 1, 0, 0] # 상하좌우 4방향 델타이동\\ndx = [0, 0, -1, 1]\\nN = int(input())\\narr = [list(map(int, list(input()))) for _ in range(N)]\\nresult = [0] # 단지 수 0으로 초기화\\nQ = deque()\\nfor i in range(N):\\n for j in range(N):\\n if arr[i][j]: # 단지를 발견하면\\n result.append(bfs(i, j)) # 탐색한 단지내 가구수 추가\\n result[0] += 1 # 단지 수 ++\\nprint(result[0]) # 단지 수 출력\\nfor r in sorted(result[1:]): print(r) # 단지내 가구수를 오름차순으로 출력\"\n },\n {\n \"alpha_fraction\": 0.3693181872367859,\n \"alphanum_fraction\": 0.38825756311416626,\n \"avg_line_length\": 36.78571319580078,\n \"blob_id\": \"8c9678063190b9f1e63ec12bdc97abfeb2263c11\",\n \"content_id\": \"1142953ef6ff9b7a540eae3582247ce7e8b25916\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 676,\n \"license_type\": \"no_license\",\n \"max_line_length\": 71,\n \"num_lines\": 14,\n \"path\": \"/알고리즘/온라인저지/2021/12/1216/소인수분해.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"n = int(input()) # 소수를 찾을 범위\\na = [False,False] + [True]*(n-1) # 0 ~ n 까지의 숫자 리스트\\nprimes=[] # 소수 집합\\nfor i in range(2,n+1): # 2 ~ n까지 반복\\n if a[i]: # 2부터 시작, 해당 숫자가 지워지지 않고 남아있는 소수라면 \\n primes.append(i) # 소수 리스트에 추가\\n for j in range(2*i, n+1, i): # 해당 소수의 배수들을 \\n a[j] = False # 리스트에서 전부 False로 만들기\\n\\nwhile n != 1:\\n for p in primes:\\n while n % p == 0:\\n n //= p\\n print(p)\"\n },\n {\n \"alpha_fraction\": 0.45864662528038025,\n \"alphanum_fraction\": 0.4736842215061188,\n \"avg_line_length\": 18.14285659790039,\n \"blob_id\": \"10db02c0ab7a4822915bf76ca9f6399ab3b3ddfb\",\n \"content_id\": \"f18b068108ff0f4ebdbd33d92b9b10e48e5d27bb\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 133,\n \"license_type\": \"no_license\",\n \"max_line_length\": 32,\n \"num_lines\": 7,\n \"path\": \"/알고리즘/온라인저지/2023/03/0312/좋은 암호.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"K, L = map(int, input().split())\\nfor i in range(2, L):\\n if K%i == 0:\\n print('BAD', i)\\n break\\nelse:\\n print('GOOD')\"\n },\n {\n \"alpha_fraction\": 0.420634925365448,\n \"alphanum_fraction\": 0.43386244773864746,\n \"avg_line_length\": 15.47826099395752,\n \"blob_id\": \"4d0b96b49d19e5b5eb9a79f8971434bfac227d8a\",\n \"content_id\": \"9e0c88b23a862a35ac6b310d1c68842b7e107d83\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 378,\n \"license_type\": \"no_license\",\n \"max_line_length\": 50,\n \"num_lines\": 23,\n \"path\": \"/알고리즘/온라인저지/2022/10/1029/운동.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\n\\nN, m, M, T, R = map(int, input().rstrip().split())\\nn = 0\\nresult = 0\\nnow = m\\nwhile n < N:\\n result += 1\\n # print(result, now, T, R)\\n if m+T > M:\\n result = -1\\n break\\n if now+T <= M:\\n n += 1\\n now += T\\n else:\\n if now-R <= m:\\n now = m\\n else:\\n now -= R\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.625,\n \"alphanum_fraction\": 0.637499988079071,\n \"avg_line_length\": 19.25,\n \"blob_id\": \"6ab283b7dcc96735afa323d87ab2139368e0be4e\",\n \"content_id\": \"2d5077a69bf35f042ca70744cf5847acb44fd2cf\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 80,\n \"license_type\": \"no_license\",\n \"max_line_length\": 23,\n \"num_lines\": 4,\n \"path\": \"/알고리즘/온라인저지/2022/04/0415/자동완성.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"result = 'Naver Whale'\\nif input() in 'Nn':\\n result = 'Naver D2'\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.5079872012138367,\n \"alphanum_fraction\": 0.5143769979476929,\n \"avg_line_length\": 17.47058868408203,\n \"blob_id\": \"fee8332a08be4e0c364f804ca7b9dee182e1c746\",\n \"content_id\": \"4823b245763595b360c87c906a4adb37884eda5a\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 331,\n \"license_type\": \"no_license\",\n \"max_line_length\": 32,\n \"num_lines\": 17,\n \"path\": \"/알고리즘/온라인저지/2022/07/0722/라디오.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"A, B = map(int, input().split())\\nN = int(input())\\nF = [] # favorite\\nR = A # radio\\nfor n in range(N):\\n F.append(int(input()))\\nminn = abs(B-R)\\nfor f in F:\\n tmp = abs(B-f)\\n if tmp < minn: \\n minn = tmp\\n R = f\\nresult = 0\\nif R != A: # 즐겨찾기를 한 번 누름\\n result += 1\\nresult += abs(B-R)\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.443708598613739,\n \"alphanum_fraction\": 0.4768211841583252,\n \"avg_line_length\": 20.64285659790039,\n \"blob_id\": \"f786c31298689b338d27f9a92c05a6b04f981980\",\n \"content_id\": \"2456cab5309ea7429c0d841ea752d155bcc7204e\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 302,\n \"license_type\": \"no_license\",\n \"max_line_length\": 45,\n \"num_lines\": 14,\n \"path\": \"/알고리즘/온라인저지/2023/02/0216/수찬은 마린보이야!!.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = int(input())\\ntry:\\n records = list(map(int, input().split()))\\n dp = [0]*101\\n A = sum(records)/N\\n for record in records:\\n dp[record] += 1\\n B = 0\\n for i in range(101):\\n if dp[i]:\\n B += i * (dp[i]/N)\\n print(f'{A/B:.2f}')\\nexcept:\\n print('divide by zero')\"\n },\n {\n \"alpha_fraction\": 0.41951218247413635,\n \"alphanum_fraction\": 0.4390243887901306,\n \"avg_line_length\": 24.75,\n \"blob_id\": \"c0077997e9895fb7f22c3ef1413c0107aaa2753e\",\n \"content_id\": \"b0e9dbda375290f7ce75dbf967bf1d3fafcefbf4\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 205,\n \"license_type\": \"no_license\",\n \"max_line_length\": 36,\n \"num_lines\": 8,\n \"path\": \"/알고리즘/온라인저지/2022/06/0612/0의 개수.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"for t in range(int(input())):\\n N, M = map(int, input().split())\\n result = 0\\n for a in range(N, M+1):\\n for b in str(a):\\n if b == '0':\\n result += 1\\n print(result)\"\n },\n {\n \"alpha_fraction\": 0.42491209506988525,\n \"alphanum_fraction\": 0.43897539377212524,\n \"avg_line_length\": 30.619047164916992,\n \"blob_id\": \"a1c33e2efa84eb561f7805fc7c22f7176a2226f5\",\n \"content_id\": \"0d216d0f2d182c4901c28750870eab30848710d9\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 2481,\n \"license_type\": \"no_license\",\n \"max_line_length\": 60,\n \"num_lines\": 63,\n \"path\": \"/알고리즘/온라인저지/2022/03/0315/후보 추천하기.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = int(input())\\nK = int(input())\\npicks = list(map(int, input().split())) # 추천 후보\\n\\nresult = []\\n\\n# [후보번호, 추천수, 등록시간]\\nfor i in range(K):\\n # print(result)\\n if len(result) < N: # 사진틀이 남았을 때\\n # 이미 있는 후보를 추천하는지 확인\\n in_result = False\\n idx = 0\\n for k in range(len(result)):\\n if picks[i] == result[k][0]:\\n in_result = True\\n idx = k\\n\\n if not in_result: # 이미 있는 후보가 아닐 경우\\n result.append([picks[i], 1, i]) # 후보 추가\\n else: # 있는 후보일 경우\\n result[idx][1] += 1 # 추천 +1\\n \\n else: # 사진틀이 남지 않았을 때\\n # 이미 있는 후보를 추천하는지 확인\\n in_result = False\\n idx = 0\\n for k in range(N):\\n if picks[i] == result[k][0]:\\n in_result = True\\n idx = k\\n\\n if not in_result: # 이미 있는 후보가 아닐 경우\\n # 후보 사진을 갈아끼워야 함\\n recommended = 10**3 # 가상의 추천수 최대값\\n recommend_idx = 0 # 가장 추천을 많이 받은 후보의 인덱스\\n oldest_time = 10**3 # 가상의 등록순서 최대값\\n oldest_idx = 0 # 가장 오래전에 등록된 후보의 인덱스\\n for j in range(N): # 후보 사진들 중\\n # 추천이 가장 적은 후보 찾기\\n if result[j][1] < recommended:\\n recommended = result[j][1]\\n recommend_idx = j\\n # 동시에 그 후보의 등록시간도 기록\\n oldest_time = result[j][2]\\n oldest_idx = j\\n\\n # 추천수가 가장 적은 후보가 여러명일 때\\n elif result[j][1] == recommended:\\n # 등록시간이 오래된 후보를 찾아서\\n if oldest_time > result[j][2]:\\n oldest_time = result[j][2]\\n oldest_idx = j\\n recommend_idx = oldest_idx # 인덱스 잡고\\n # print(recommend_idx)\\n result[recommend_idx] = [picks[i], 1, i] # 덮어씌우기\\n else: # 있는 후보일 경우\\n result[idx][1] += 1 # 추천 +1\\n # print(result)\\n\\nresult.sort(key=lambda x:x[0]) # 후보번호순 정렬\\nfor r in result:\\n print(r[0], end=' ') # 출력\"\n },\n {\n \"alpha_fraction\": 0.504273533821106,\n \"alphanum_fraction\": 0.504273533821106,\n \"avg_line_length\": 13.75,\n \"blob_id\": \"bc77b127a60d63d2c8fa532fe06e2044be22119b\",\n \"content_id\": \"ed4d430c0d4f8210b3f129b87f46b5a7bdabd75e\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 117,\n \"license_type\": \"no_license\",\n \"max_line_length\": 35,\n \"num_lines\": 8,\n \"path\": \"/알고리즘/온라인저지/2022/02/0202/파티가 끝나고 난 뒤.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"L, P = map(int, input().split())\\n\\na = list(map(int, input().split()))\\n\\ns = L * P\\n\\nfor i in a:\\n print(i-s, end=' ')\"\n },\n {\n \"alpha_fraction\": 0.4020356237888336,\n \"alphanum_fraction\": 0.4452926218509674,\n \"avg_line_length\": 16.909090042114258,\n \"blob_id\": \"d549458b9e9d63a94f3b195afa84cadc1e4196f4\",\n \"content_id\": \"df21e5d886025b7a16483e2444febe214707943c\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 393,\n \"license_type\": \"no_license\",\n \"max_line_length\": 62,\n \"num_lines\": 22,\n \"path\": \"/알고리즘/온라인저지/2021/08/0829/자리배정.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\nC, R = map(int, sys.stdin.readline().split())\\nK = int(sys.stdin.readline())\\n\\ndx = [0, 1, 0, -1]\\ndy = [1, 0, -1, 0]\\n\\nhall = [[0]*C for _ in range(R)]\\ni = 1\\nx = y = k = 0\\n\\nwhile i < K:\\n hall[y][x] = i\\n i += 1\\n if x+dx[k] >= C or y+dy[k] >= R or hall[y+dy[k]][x+dx[k]]:\\n k = (k+1)%4\\n x = (x+dx[k])\\n y = (y+dy[k])\\nif C*R < K:\\n print(0)\\nelse:\\n print(x+1, y+1)\"\n },\n {\n \"alpha_fraction\": 0.5452961921691895,\n \"alphanum_fraction\": 0.5522648096084595,\n \"avg_line_length\": 29.263158798217773,\n \"blob_id\": \"928021474cba99457c8b2b04dbd173afa07b11c6\",\n \"content_id\": \"7af088e857095e87d905978c083f85dad85a7720\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 744,\n \"license_type\": \"no_license\",\n \"max_line_length\": 60,\n \"num_lines\": 19,\n \"path\": \"/알고리즘/온라인저지/2022/11/1127/N과 M (6).py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\n\\ndef dfs(start):\\n if len(result) == M: # 수열이 완성됐다면\\n print(*result) # 완성된 수열 출력\\n # 이번 함수가 종료되고 나오면서 line14의 result.pop()에서 마지막 숫자 제거\\n else: # 아직 수열이 완성되지 않았다면\\n for i in range(start, N): # 수열에 더 들어올 남은 숫자 개수만큼 for\\n if nums[i] not in result:\\n result.append(nums[i]) # nums[i]를 집어넣고\\n dfs(i+1) # 더 깊이 탐색\\n result.pop() # 방금 넣었던 nums[i]를 빼주기\\n\\nN, M = map(int, input().rstrip().split())\\nnums = sorted(list(map(int, input().rstrip().split())))\\nresult = []\\ndfs(0)\"\n },\n {\n \"alpha_fraction\": 0.5398229956626892,\n \"alphanum_fraction\": 0.5575221180915833,\n \"avg_line_length\": 27.33333396911621,\n \"blob_id\": \"4e86b5df9ba8ea8532729f1fd18c3c26e12a8924\",\n \"content_id\": \"32fe6f431a0b351431b794a7a2608bd391a40d1f\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 339,\n \"license_type\": \"no_license\",\n \"max_line_length\": 42,\n \"num_lines\": 12,\n \"path\": \"/알고리즘/온라인저지/2022/09/0910/카드게임.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"A_card = list(map(int, input().split()))\\nB_card = list(map(int, input().split()))\\nA_win = B_win = draw = 0\\nfor i in range(10):\\n if A_card[i] > B_card[i]: A_win += 1\\n elif A_card[i] < B_card[i]: B_win += 1\\n else: draw += 1\\nresult = ''\\nif A_win > B_win: result = 'A'\\nelif A_win < B_win: result = 'B'\\nelse: result = 'D'\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.37383177876472473,\n \"alphanum_fraction\": 0.44859811663627625,\n \"avg_line_length\": 20.600000381469727,\n \"blob_id\": \"dc3a2207bd6485006fb527f212e2f695d46ee3d5\",\n \"content_id\": \"86462cc82ad1dcfbdd0fa21605b722002876decd\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 107,\n \"license_type\": \"no_license\",\n \"max_line_length\": 33,\n \"num_lines\": 5,\n \"path\": \"/알고리즘/온라인저지/2023/01/0130/2018 연세대학교 프로그래밍 경진대회.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = int(input())\\nfor k in range(1, 10101):\\n if eval('k**2 + k + 1') == N:\\n print(k)\\n break\"\n },\n {\n \"alpha_fraction\": 0.47663551568984985,\n \"alphanum_fraction\": 0.514018714427948,\n \"avg_line_length\": 20.600000381469727,\n \"blob_id\": \"8a4db5b859392937afc961ffa35a0e1d8a018746\",\n \"content_id\": \"ae664d974a4a4ea3c56059c66c0bc4c8296ea733\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 107,\n \"license_type\": \"no_license\",\n \"max_line_length\": 31,\n \"num_lines\": 5,\n \"path\": \"/알고리즘/온라인저지/2022/05/0519/양수 개수 세기.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"result = 0\\nfor i in list(input().split()):\\n if i[0] not in ('-', '0'):\\n result += 1\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.5199999809265137,\n \"alphanum_fraction\": 0.5400000214576721,\n \"avg_line_length\": 27.714284896850586,\n \"blob_id\": \"b703a8efae28754d8127f136866de4f9b23a9c52\",\n \"content_id\": \"22d045fcfe189f3c1596b8d78964656cbc652c91\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 200,\n \"license_type\": \"no_license\",\n \"max_line_length\": 56,\n \"num_lines\": 7,\n \"path\": \"/알고리즘/온라인저지/2023/02/0212/바구니 뒤집기.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N, M = map(int, input().split())\\nresult = list(range(1, N+1))\\nfor m in range(M):\\n i, j = map(int, input().split())\\n i -= 1\\n result = result[:i] + result[i:j][::-1] + result[j:]\\nprint(*result)\"\n },\n {\n \"alpha_fraction\": 0.5879828333854675,\n \"alphanum_fraction\": 0.5879828333854675,\n \"avg_line_length\": 22.399999618530273,\n \"blob_id\": \"9934fd38e46d4c4fa6f3f55fefe0f20e43da3bf0\",\n \"content_id\": \"706fd732dc605207a0d99700cdd9217075dd96f7\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 233,\n \"license_type\": \"no_license\",\n \"max_line_length\": 45,\n \"num_lines\": 10,\n \"path\": \"/알고리즘/온라인저지/2022/11/1106/대회 자리.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\n\\nfor _ in range(int(input().rstrip())):\\n P, M = map(int, input().rstrip().split())\\n result = set()\\n for p in range(P):\\n result.add(int(input().rstrip()))\\n print(P-len(result))\"\n },\n {\n \"alpha_fraction\": 0.4575645625591278,\n \"alphanum_fraction\": 0.4944649338722229,\n \"avg_line_length\": 14.11111068725586,\n \"blob_id\": \"3b9fe55baa92335e61f7a37fb05ca6950d9a59ec\",\n \"content_id\": \"e4ba9d5c888fb9e574cb45970da91608383f4de6\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 271,\n \"license_type\": \"no_license\",\n \"max_line_length\": 25,\n \"num_lines\": 18,\n \"path\": \"/알고리즘/온라인저지/2022/02/0209/특별한 날.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"M = int(input())\\nD = int(input())\\n\\nresult = ''\\n\\nif M == 2 and D == 18:\\n result = 'Special'\\nelif M < 2:\\n result = 'Before'\\nelif M > 2:\\n result = 'After'\\nelif M == 2:\\n if D < 18:\\n result = 'Before'\\n elif D > 18:\\n result = 'After'\\n\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.5528455376625061,\n \"alphanum_fraction\": 0.5691056847572327,\n \"avg_line_length\": 23.799999237060547,\n \"blob_id\": \"b64a9e3afc161dd5947328d2ccd9b7b7e496658f\",\n \"content_id\": \"2787e3ca5e3b14d2e7ece980ae690358a87bbfd3\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 123,\n \"license_type\": \"no_license\",\n \"max_line_length\": 33,\n \"num_lines\": 5,\n \"path\": \"/알고리즘/온라인저지/2022/08/0822/Julka.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"A = int(input()) # apple\\nG = int(input()) # gap\\nKlaudia = (A-G)//2 + G\\nNatalia = (A-G)//2\\nprint(Klaudia, Natalia, sep='\\\\n')\"\n },\n {\n \"alpha_fraction\": 0.40716612339019775,\n \"alphanum_fraction\": 0.4527687430381775,\n \"avg_line_length\": 17.117647171020508,\n \"blob_id\": \"2eca37b61d7bafe52a8016d0fbf9e42d275383a8\",\n \"content_id\": \"800e905d6d85f9b3fff1857dc0a2769ddae40095\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 307,\n \"license_type\": \"no_license\",\n \"max_line_length\": 46,\n \"num_lines\": 17,\n \"path\": \"/알고리즘/온라인저지/2022/12/1204/카드 구매하기.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = int(input())\\ncards = list(map(int, input().split()))\\ndp = [0]*(N+1)\\nfor i in range(1, N+1):\\n for j in range(i):\\n dp[i] = max(dp[i], dp[j]+cards[i-j-1])\\nprint(dp[-1])\\n\\n\\\"\\\"\\\"\\ndp[i] = max(\\n dp[1] + cards[i-1],\\n dp[2] + cards[i-2],\\n ...\\n dp[i-2] + cards[2],\\n dp[i-1] + cards[1],\\n)\\n\\\"\\\"\\\"\"\n },\n {\n \"alpha_fraction\": 0.34794774651527405,\n \"alphanum_fraction\": 0.4048507511615753,\n \"avg_line_length\": 21.82978630065918,\n \"blob_id\": \"633db1042372d0c4efcabbc0507c33465347af29\",\n \"content_id\": \"84d26e16237db07662ec7f66a36bfced49b387b8\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1072,\n \"license_type\": \"no_license\",\n \"max_line_length\": 58,\n \"num_lines\": 47,\n \"path\": \"/알고리즘/프로그래머스/Level1/신규 아이디 추천.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"def solution(new_id):\\n answer = ''\\n # print(new_id)\\n new_id = new_id.lower()\\n tmp = ''\\n \\n for n in new_id: # step 2\\n if n in 'abcdefghijklmnopqrstuvwxyz0123456789-_.':\\n tmp = tmp + n\\n switch = False\\n tmp2 = ''\\n \\n for t in tmp: # step 3\\n if t == '.':\\n if not switch:\\n switch = True\\n tmp2 = tmp2 + t\\n else:\\n tmp2 = tmp2 + t\\n if switch:\\n switch = False\\n # print('step3', tmp2)\\n \\n if len(tmp2) >= 2:\\n if tmp2[0] == '.': # step 4\\n tmp2 = tmp2[1:]\\n if tmp2[-1] == '.':\\n tmp2 = tmp2[:len(tmp2)-1]\\n else:\\n tmp2 = ''\\n # print('step4', tmp2)\\n \\n if tmp2 == '': # step 5\\n tmp2 = 'a'\\n \\n if len(tmp2) >= 16: # step 6\\n tmp2 = tmp2[:15]\\n if tmp2[-1] == '.':\\n tmp2 = tmp2[:len(tmp2)-1]\\n \\n while len(tmp2) <= 2: # step 7\\n tmp2 = tmp2 + tmp2[-1]\\n \\n answer = tmp2\\n return answer\\n\\nprint(solution(input()))\"\n },\n {\n \"alpha_fraction\": 0.5703883767127991,\n \"alphanum_fraction\": 0.5800970792770386,\n \"avg_line_length\": 23.235294342041016,\n \"blob_id\": \"f79e58b556b0778ac092216898033296daf91886\",\n \"content_id\": \"620accbf8bdc7777fca0f32d1030651d97b3a867\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 412,\n \"license_type\": \"no_license\",\n \"max_line_length\": 36,\n \"num_lines\": 17,\n \"path\": \"/알고리즘/온라인저지/2022/03/0329/맞았는데 왜 틀리죠.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"S1, S2 = map(int, input().split())\\nresult = 'Accepted'\\nis_wrong_answer = False\\nis_why_wrong = False\\nfor s in range(S1):\\n A, B = map(int, input().split())\\n if A != B:\\n is_wrong_answer = True\\nfor s in range(S2):\\n A, B = map(int, input().split())\\n if A != B:\\n is_why_wrong = True\\nif is_wrong_answer:\\n result = 'Wrong Answer'\\nelif is_why_wrong:\\n result = 'Why Wrong!!!'\\nprint(result)\\n\"\n },\n {\n \"alpha_fraction\": 0.529411792755127,\n \"alphanum_fraction\": 0.5441176295280457,\n \"avg_line_length\": 33.5,\n \"blob_id\": \"254eb6e75ec447388270de7ba79dc8a522fdb0a1\",\n \"content_id\": \"a1ea7e94ac60a7be519ef0ed1e5e0f0ee06a771f\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 68,\n \"license_type\": \"no_license\",\n \"max_line_length\": 35,\n \"num_lines\": 2,\n \"path\": \"/알고리즘/온라인저지/2023/04/0402/Piece of Cake.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N, H, V = map(int, input().split())\\nprint(max(N-H, H)*max(N-V, V)*4)\"\n },\n {\n \"alpha_fraction\": 0.46859902143478394,\n \"alphanum_fraction\": 0.49275362491607666,\n \"avg_line_length\": 22.11111068725586,\n \"blob_id\": \"4ef3b33cfe25d3270e15b91a347fcc812901b50e\",\n \"content_id\": \"feff1f3d4a405339384f173ed943fe42ffdffc8f\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 207,\n \"license_type\": \"no_license\",\n \"max_line_length\": 35,\n \"num_lines\": 9,\n \"path\": \"/알고리즘/온라인저지/2022/05/0512/앵그리 창영.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N, W, H = map(int, input().split())\\nmax_match = W**2 + H**2\\nresult = ['DA', 'NE']\\nfor n in range(N):\\n M = int(input())\\n if M**2 <= max_match:\\n print(result[0])\\n else:\\n print(result[1])\"\n },\n {\n \"alpha_fraction\": 0.5070063471794128,\n \"alphanum_fraction\": 0.522292971611023,\n \"avg_line_length\": 36.39682388305664,\n \"blob_id\": \"82af38fbd1673953956c2203c119d5583a6aadd0\",\n \"content_id\": \"8622017e0465f39f96ac027c8e280cd75f66ef74\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 2997,\n \"license_type\": \"no_license\",\n \"max_line_length\": 85,\n \"num_lines\": 63,\n \"path\": \"/알고리즘/온라인저지/2022/11/1119/로봇 시뮬레이션.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\n\\ndirection_to_index = { # NESW를 0123으로 바꿔서 델타이동을 아래와 같이 할 것\\n 'N': 0,\\n 'E': 1,\\n 'S': 2,\\n 'W': 3,\\n}\\ndy, dx = [-1, 0, 1, 0], [0, 1, 0, -1]\\n\\nA, B = map(int, input().rstrip().split())\\narr = [[-1]*A for _ in range(B)]\\nN, M = map(int, input().rstrip().split())\\nrobot_location = [(0, 0) for _ in range(N+1)] # n번 로봇의 좌표를 (y,x)꼴로 담을 배열 공간 N+1개만큼 생성\\nfor n in range(1, N+1):\\n x, y, direction = input().rstrip().split()\\n # 예제처럼 왼쪽아래를 1,1로 두기 위해 아래와 같이 y좌표를 바꿔서 집어넣는다\\n x, y, direction = int(x)-1, B-(int(y)), direction_to_index[direction]\\n robot = n # 로봇 번호\\n arr[y][x] = direction # 원본 배열에는 로봇이 바라보는 방향을 집어넣는다\\n robot_location[robot] = (y, x)\\n# 디버깅\\n# for a in arr: print(a) \\n# print()\\norders = [] # 입력은 일단 다 받기 위해 리스트 생성\\nfor m in range(M):\\n robot, command, loop = input().rstrip().split()\\n robot, loop = int(robot), int(loop)\\n orders.append((robot, command, loop))\\nresult = 'OK' # 명령들을 이상없이 수행하면 출력할 OK\\nfor order in orders:\\n if result != 'OK': break # 뭔가 심상치 않은 일이 생긴거야~\\n robot, command, loop = order # ex) 1 F 3\\n y, x = robot_location[robot] # 명령으로 들어온 로봇이 현재 배열에 위치한 좌표 y, x\\n direction = arr[y][x] # 로봇이 보고 있는 방향\\n if command == 'R': # 오른쪽으로 돌리고~\\n arr[y][x] += loop\\n arr[y][x] %= 4\\n elif command == 'L': # 왼쪽으로 돌리고~\\n for i in range(loop):\\n arr[y][x] = (arr[y][x]+3)%4 # 오른쪽으로 세 번 돌린 것과 같다\\n else: # 앞으로 가자!\\n for i in range(loop):\\n if result != 'OK': break # 뭔가 심상치 않은 일이 생긴거야~\\n ny, nx = y+dy[direction], x+dx[direction] # 로봇의 다음 이동할 좌표\\n if not (0<=ny<B) or not (0<=nx<A): # 벽에 부딪혔다 == 범위를 벗어났다\\n result = f'Robot {robot} crashes into the wall'\\n elif arr[ny][nx] != -1: # 다른 로봇과 부딪혔다\\n crashed_robot = 0 # 부딪힌 로봇의 번호 초기화\\n for n in range(N+1): # 부딧힌 로봇의 번호를 찾자\\n if robot_location[n] == (ny, nx): # 로봇들 중 ny,nx에 위치한 로봇의 인덱스\\n crashed_robot = n\\n result = f'Robot {robot} crashes into robot {crashed_robot}'\\n else: # 이상없이 앞으로 갈 수 있다\\n arr[y][x], arr[ny][nx] = arr[ny][nx], arr[y][x] # 한 칸 앞으로\\n y, x = ny, nx # 로봇의 새 좌표로 갱신\\n robot_location[robot] = (y, x) # 로봇 좌표모음 배열도 갱신\\n # 디버깅\\n # for a in arr: print(a)\\n # print()\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.4356435537338257,\n \"alphanum_fraction\": 0.4752475321292877,\n \"avg_line_length\": 19.399999618530273,\n \"blob_id\": \"15ff4d94e1891fe0b220191d9a09ad265789c018\",\n \"content_id\": \"343b101c94ec5dd399e1084be5e347259dbf1479\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 101,\n \"license_type\": \"no_license\",\n \"max_line_length\": 32,\n \"num_lines\": 5,\n \"path\": \"/알고리즘/온라인저지/2022/08/0822/AFC 윔블던.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N, M = map(int, input().split())\\nif (N+M)%2 or N<M:\\n print(-1)\\nelse:\\n print((N+M)//2, (N-M)//2)\"\n },\n {\n \"alpha_fraction\": 0.4752941131591797,\n \"alphanum_fraction\": 0.4964706003665924,\n \"avg_line_length\": 21.421052932739258,\n \"blob_id\": \"a7c209f5e5c48c2d014adf5c1c83a19f38559c80\",\n \"content_id\": \"51d7f086064c595f90c3542c1a319a6b6c8a859f\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 425,\n \"license_type\": \"no_license\",\n \"max_line_length\": 55,\n \"num_lines\": 19,\n \"path\": \"/알고리즘/온라인저지/2022/10/1002/The Game of Death.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\n\\nfor _ in [0]*int(input().rstrip()):\\n result = 0\\n N = int(input().rstrip())\\n death = [int(input().rstrip())-1 for _ in range(N)]\\n visited = [0]*N\\n i = 0\\n flag = True\\n while i != N-1:\\n if not visited[i]:\\n visited[i] = 1\\n i = death[i]\\n result += 1\\n else: flag = False; break\\n if flag: print(result)\\n else: print(0)\"\n },\n {\n \"alpha_fraction\": 0.5112782120704651,\n \"alphanum_fraction\": 0.5413534045219421,\n \"avg_line_length\": 25.600000381469727,\n \"blob_id\": \"19c40a7828639ff75b327da66f9547ea3800d701\",\n \"content_id\": \"e5fdab905d504f98992f4b6656d19555e911996e\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 133,\n \"license_type\": \"no_license\",\n \"max_line_length\": 37,\n \"num_lines\": 5,\n \"path\": \"/알고리즘/온라인저지/2022/09/0910/등장하지 않는 문자의 합.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"for _ in range(int(input())):\\n result = sum(list(range(65, 91)))\\n for i in input():\\n result -= ord(i)\\n print(result)\\n\"\n },\n {\n \"alpha_fraction\": 0.43292683362960815,\n \"alphanum_fraction\": 0.4491869807243347,\n \"avg_line_length\": 19.54166603088379,\n \"blob_id\": \"2c63a28fe7a01d76b65f641c60fd21c4d7f51f38\",\n \"content_id\": \"f22c3b4d9b547bd987fb6371e0dd408d042efc08\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 492,\n \"license_type\": \"no_license\",\n \"max_line_length\": 39,\n \"num_lines\": 24,\n \"path\": \"/알고리즘/온라인저지/2022/09/0910/공약수.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"def gcd(a, b):\\n while b > 0:\\n a, b = b, a%b\\n return a\\n\\nN = int(input())\\nGCD = 0\\nif N == 2:\\n A, B = map(int, input().split())\\n GCD = gcd(A, B)\\nelse:\\n A, B, C = map(int, input().split())\\n GCD = gcd(gcd(A, B), gcd(B, C))\\nresult = []\\nfor i in range(1, int(GCD**0.5)+1):\\n if GCD%i == 0:\\n A, B = GCD//i, i\\n if A != B:\\n result.append(A)\\n result.append(B)\\n else:\\n result.append(A)\\nfor i in sorted(result):\\n print(i)\"\n },\n {\n \"alpha_fraction\": 0.5858823657035828,\n \"alphanum_fraction\": 0.5976470708847046,\n \"avg_line_length\": 19.285715103149414,\n \"blob_id\": \"dc7f0693262fb040c1a57c1bf4ed3d3c04a7956f\",\n \"content_id\": \"a127e9330295a096304ebce14da7e7d9f0021771\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 677,\n \"license_type\": \"no_license\",\n \"max_line_length\": 59,\n \"num_lines\": 21,\n \"path\": \"/알고리즘/온라인저지/2022/08/0816/한조서열정리하고옴ㅋㅋ.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = int(input())\\nlst = list(map(int, input().split()))\\nA, result, cnt = 0, 0, 0 # archor\\nfor l in lst:\\n # 봉우리 높이 갱신, 임시값 초기화, 결과값 갱신\\n if l > A: A, cnt, result = l, 0, max(result, cnt)\\n else: cnt += 1\\nprint(max(result, cnt)) # 봉우리를 갱신하지 않고 for문이 끝난 경우가 있을 수 있음\\n\\n\\\"\\\"\\\"\\n그리디 문제\\n출발한 높이보다 더 높은 봉우리에 부딪히기 전까지\\n몇개의 봉우리를 만나는지\\n가장 많이 만난 봉우리의 수는 몇인지를 구하는 문제\\n\\n최소최대값 갱신을 여태\\nif a > b: a = b\\n를 사용했었는데\\na = max(a, b)\\n로 바꾸는 것도 좋을 것 같다\\n\\\"\\\"\\\"\"\n },\n {\n \"alpha_fraction\": 0.4749034643173218,\n \"alphanum_fraction\": 0.5057914853096008,\n \"avg_line_length\": 18.961538314819336,\n \"blob_id\": \"8592907d76f8a09548097e8a7e07eb5c86cc7c84\",\n \"content_id\": \"d7f797841e08c56ee866d5b22de0da9bb67ad66c\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 518,\n \"license_type\": \"no_license\",\n \"max_line_length\": 59,\n \"num_lines\": 26,\n \"path\": \"/알고리즘/온라인저지/2022/03/0325/이게 분수.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import copy\\n\\n\\ndef rotate():\\n global arr\\n new = []\\n for j in range(2):\\n tmp = []\\n for i in range(1, -1, -1):\\n tmp.append(arr[i][j])\\n new.append(tmp)\\n arr = copy.deepcopy(new)\\n\\narr = [list(map(int, input().split())) for _ in range(2)]\\n# print(arr)\\nmaxx = 0\\nresult = 0\\n# rotate()\\nfor i in range(4):\\n A, B, C, D = arr[0][0], arr[0][1], arr[1][0], arr[1][1]\\n fraction = A/C + B/D\\n if fraction > maxx:\\n maxx = fraction\\n result = i\\n rotate()\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.47598254680633545,\n \"alphanum_fraction\": 0.49344977736473083,\n \"avg_line_length\": 24.5,\n \"blob_id\": \"67a6e7d6c2e588e28270de8ddc61ca99652a8708\",\n \"content_id\": \"6368c60cfea3a9e5c11ce12cf1e3d0d203d9c6ba\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 458,\n \"license_type\": \"no_license\",\n \"max_line_length\": 42,\n \"num_lines\": 18,\n \"path\": \"/알고리즘/온라인저지/2022/10/1012/골드바흐의 추측.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"n = int(1e4)\\na = [False,False] + [True]*(n-1)\\nprimes = []\\nfor i in range(2, n+1):\\n if a[i]:\\n primes.append(i)\\n for j in range(2*i, n+1, i):\\n a[j] = False\\nfor t in range(int(input())):\\n N = int(input())\\n result = []\\n for prime in primes:\\n if prime > N: break\\n if N-prime in primes:\\n tmp = sorted((N-prime, prime))\\n if tmp not in result:\\n result.append(tmp)\\n print(*result[-1])\"\n },\n {\n \"alpha_fraction\": 0.5074999928474426,\n \"alphanum_fraction\": 0.5450000166893005,\n \"avg_line_length\": 21.27777862548828,\n \"blob_id\": \"8c69bc58f58f32c8b4c9759198b0b727d2a8be7d\",\n \"content_id\": \"8b32f1fa68ac452a55b66255d9c7a94a23d609c0\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 400,\n \"license_type\": \"no_license\",\n \"max_line_length\": 51,\n \"num_lines\": 18,\n \"path\": \"/알고리즘/온라인저지/2022/11/1113/사나운 개.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\n\\ndef bark(start, stop):\\n i = 1\\n while i+start < 1000:\\n for j in range(i, i+start):\\n if j < 1000: \\n dog[j] += 1\\n i += start+stop\\n\\ndog = [0]*1000\\nA, B, C, D = map(int, input().rstrip().split())\\nvisitors = list(map(int, input().rstrip().split()))\\nbark(A, B); bark(C, D)\\nfor visitor in visitors:\\n print(dog[visitor])\"\n },\n {\n \"alpha_fraction\": 0.44285714626312256,\n \"alphanum_fraction\": 0.5857142806053162,\n \"avg_line_length\": 34.5,\n \"blob_id\": \"17aa27c1727ead5f890beeb81e8a693b2d756165\",\n \"content_id\": \"42a01015bfdfaf4d788dd64c8152c97dcc4577a7\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 70,\n \"license_type\": \"no_license\",\n \"max_line_length\": 37,\n \"num_lines\": 2,\n \"path\": \"/알고리즘/온라인저지/2022/08/0822/가희와 방어율 무시.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"A, B = map(int, input().split())\\nprint(0 if A*(100-B) >= 10000 else 1)\"\n },\n {\n \"alpha_fraction\": 0.4842519760131836,\n \"alphanum_fraction\": 0.5,\n \"avg_line_length\": 20.25,\n \"blob_id\": \"ff76b56b06a4083826bb3be605866b7eb3bcac70\",\n \"content_id\": \"2b1cc1f023a82ca889cede6b906e1f73938194d6\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 254,\n \"license_type\": \"no_license\",\n \"max_line_length\": 41,\n \"num_lines\": 12,\n \"path\": \"/알고리즘/SWEA/LEARN/Course/2. Programming Intermediate/6. 파이썬 SW문제해결 기본 Queue/5차시 6일차 - 회전.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"T = int(input())\\n\\nfor t in range(1, T+1):\\n N, M = map(int, input().split())\\n arr = list(map(int, input().split()))\\n tmp = M%N\\n for i in range(tmp):\\n arr.append(arr.pop(0))\\n \\n result = arr[0]\\n\\n print('#{} {}'.format(t, result))\"\n },\n {\n \"alpha_fraction\": 0.5,\n \"alphanum_fraction\": 0.5249999761581421,\n \"avg_line_length\": 19.5,\n \"blob_id\": \"d4d09322343760f3a5c8aeda4522941377be0c19\",\n \"content_id\": \"da679b9fdffb389ffe147ca355fb3d95f2aaf169\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 40,\n \"license_type\": \"no_license\",\n \"max_line_length\": 28,\n \"num_lines\": 2,\n \"path\": \"/알고리즘/온라인저지/2021/12/1213/팰린드롬인지 확인하기.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"a = input()\\nprint(int(bool(a==a[::-1])))\"\n },\n {\n \"alpha_fraction\": 0.49799197912216187,\n \"alphanum_fraction\": 0.5582329034805298,\n \"avg_line_length\": 15.666666984558105,\n \"blob_id\": \"7203ec5f0c26c0c6d5310a0413777b202e5fb984\",\n \"content_id\": \"2b71e0077b0034f210a3ccced374c5b54a648c2d\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 249,\n \"license_type\": \"no_license\",\n \"max_line_length\": 39,\n \"num_lines\": 15,\n \"path\": \"/알고리즘/[템플릿]/Dynamic Programming/점화식.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\n\\nN = int(input().rstrip())\\ndp = [0]*36\\ndp[0] = 1\\nfor i in range(35):\\n tmp = 0 \\n for j in range(i+1):\\n tmp += dp[j]*dp[i-j]\\n dp[i+1] = tmp\\nprint(dp[N])\\n\\n# https://www.acmicpc.net/problem/13699\"\n },\n {\n \"alpha_fraction\": 0.5250896215438843,\n \"alphanum_fraction\": 0.5286738276481628,\n \"avg_line_length\": 31.882352828979492,\n \"blob_id\": \"b66769161b9f94148c43d7c128385a69cec94997\",\n \"content_id\": \"218fb84ce2e49a00a95dfa948f39e071472f6240\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 904,\n \"license_type\": \"no_license\",\n \"max_line_length\": 75,\n \"num_lines\": 17,\n \"path\": \"/알고리즘/온라인저지/2022/09/0903/재귀함수가 뭔가요.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"def dfs(level):\\n tmp = '____'*level\\n if level != N:\\n print(tmp + '\\\"재귀함수가 뭔가요?\\\"')\\n print(tmp + '\\\"잘 들어보게. 옛날옛날 한 산 꼭대기에 이세상 모든 지식을 통달한 선인이 있었어.')\\n print(tmp + '마을 사람들은 모두 그 선인에게 수많은 질문을 했고, 모두 지혜롭게 대답해 주었지.')\\n print(tmp + '그의 답은 대부분 옳았다고 하네. 그런데 어느 날, 그 선인에게 한 선비가 찾아와서 물었어.\\\"')\\n dfs(level+1)\\n print(tmp + '라고 답변하였지.')\\n else:\\n print(tmp + '\\\"재귀함수가 뭔가요?\\\"')\\n print(tmp + '\\\"재귀함수는 자기 자신을 호출하는 함수라네\\\"')\\n print(tmp + '라고 답변하였지.')\\n\\nN = int(input())\\nprint('어느 한 컴퓨터공학과 학생이 유명한 교수님을 찾아가 물었다.')\\ndfs(0)\"\n },\n {\n \"alpha_fraction\": 0.4591836631298065,\n \"alphanum_fraction\": 0.4897959232330322,\n \"avg_line_length\": 18.799999237060547,\n \"blob_id\": \"cbd5868577a721804567cf9d43bef35da98dcf67\",\n \"content_id\": \"bf88d1835cf4637319cbc2a8d5a20bc40488907f\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 98,\n \"license_type\": \"no_license\",\n \"max_line_length\": 40,\n \"num_lines\": 5,\n \"path\": \"/알고리즘/온라인저지/2023/02/0210/The Fastest Sorting Algorithm In The World.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"i = 1\\nwhile True:\\n if input() == '0': break\\n print(f'Case {i}: Sorting... done!')\\n i += 1\"\n },\n {\n \"alpha_fraction\": 0.47719594836235046,\n \"alphanum_fraction\": 0.49070945382118225,\n \"avg_line_length\": 29.384614944458008,\n \"blob_id\": \"76cd710fe9eb359047051b92247709ffe44f8471\",\n \"content_id\": \"87a312d802455a3a8008ed210fce9d89cca38f16\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1446,\n \"license_type\": \"no_license\",\n \"max_line_length\": 60,\n \"num_lines\": 39,\n \"path\": \"/알고리즘/온라인저지/2022/07/0710/적록색약.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from collections import deque # BFS\\nfrom copy import deepcopy # 원본 배열 복사하여 색약 배열로 변경하기 위함\\n\\n\\ndef bfs(arr, y, x, color):\\n Q = deque()\\n Q.append((y, x))\\n while Q:\\n y, x = Q.popleft()\\n if not arr[y][x]:\\n continue\\n arr[y][x] = 0\\n for i in range(4):\\n ny = y+dy[i]\\n nx = x+dx[i]\\n if 0<=ny<N and 0<=nx<N and arr[ny][nx] == color:\\n # 탐색범위를 벗어나지 않으면서, 현재 탐색중인 색깔과 같으면\\n Q.append((ny, nx))\\n\\n\\ndy = [-1, 1, 0, 0] # 4방향 델타이동\\ndx = [0, 0, -1, 1]\\nN = int(input())\\nnormal_arr = [list(input()) for _ in range(N)] # 원본배열\\nCB_arr = deepcopy(normal_arr) # 원본 배열 복사하여 색약배열 초기화\\nfor i in range(N): # 적록색약 배열\\n for j in range(N):\\n if CB_arr[i][j] in 'RG': # 빨강과 초록을 구분할 수 없으므로\\n CB_arr[i][j] = 'A' # 임의의 문자 A로 통일\\nnormal = CB = 0 # 일반인, 색약인(color blind) 결과값 초기화\\nfor i in range(N):\\n for j in range(N):\\n if normal_arr[i][j]: # normal\\n bfs(normal_arr, i, j, normal_arr[i][j])\\n normal += 1 # 일반인이 볼 수 있는 구역 ++\\n if CB_arr[i][j]: # color blind\\n bfs(CB_arr, i, j, CB_arr[i][j])\\n CB += 1 # 색약인이 볼 수 있는 구역 ++\\nprint(normal, CB) # 출력\"\n },\n {\n \"alpha_fraction\": 0.5493230223655701,\n \"alphanum_fraction\": 0.5802707672119141,\n \"avg_line_length\": 27.72222137451172,\n \"blob_id\": \"788c2f3361b962163e159ab6d2d1d800be952725\",\n \"content_id\": \"4048cd0a3e10aba860606d19dd3a232b39dfef17\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 691,\n \"license_type\": \"no_license\",\n \"max_line_length\": 60,\n \"num_lines\": 18,\n \"path\": \"/알고리즘/온라인저지/2023/03/0326/평범한 배낭.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N, K = map(int, input().split())\\nitems = [tuple(map(int, input().split())) for _ in range(N)]\\ndp = [0]*(K+1)\\nfor item in items:\\n weight, value = item\\n for i in range(K, weight-1, -1): # top-down\\n dp[i] = max(dp[i], dp[i-weight]+value)\\nprint(dp[-1])\\n\\n\\\"\\\"\\\"\\ntop-down 방식의 문제이다\\n현재 무게(dp[i])에서 얻을 수 있는 가장 큰 가치를\\n아래 두 값 중 최대값으로 갱신한다\\n1. 이미 구한 현재 무게의 가치 최대치(dp[i])\\n2. 현재 물건의 무게만큼 더 담을 수 있던 시점의 가치 최대치에 현재 물건의 가치를 더한 값\\nex) dp[7] = max(dp[7], dp[3]+items[4][value])\\nex2) dp[6] = max(dp[6], dp[0]+items[6][value])\\n\\\"\\\"\\\"\\n\"\n },\n {\n \"alpha_fraction\": 0.5526315569877625,\n \"alphanum_fraction\": 0.5789473652839661,\n \"avg_line_length\": 18.5,\n \"blob_id\": \"9e1cf1567f1350a0add7a20eb09d7065d65d73b8\",\n \"content_id\": \"9f996e893be83d9d391e27560c8d8690ebcf97ff\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 38,\n \"license_type\": \"no_license\",\n \"max_line_length\": 21,\n \"num_lines\": 2,\n \"path\": \"/알고리즘/온라인저지/2023/01/0105/선린인터넷고등학교 교가.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = int(input())\\nprint(input()[N-5:N])\"\n },\n {\n \"alpha_fraction\": 0.4736842215061188,\n \"alphanum_fraction\": 0.5403508543968201,\n \"avg_line_length\": 19.428571701049805,\n \"blob_id\": \"16d12e624fbd5e2fc50cb63e4dd5f0d2eb5b5f08\",\n \"content_id\": \"577b99230c0481c713fd41ade8d53bf54d193ad3\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 285,\n \"license_type\": \"no_license\",\n \"max_line_length\": 69,\n \"num_lines\": 14,\n \"path\": \"/알고리즘/온라인저지/2022/03/0315/나이 계산하기.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"birth = list(map(int, input().split()))\\nnow = list(map(int, input().split()))\\n\\nolds = [0, 0, 0]\\n\\nolds[2] = now[0] - birth[0]\\nolds[1] = olds[2] + 1\\nolds[0] = olds[2]\\n\\nif (now[1] < birth[1]) or (now[1] == birth[1] and now[2] < birth[2]):\\n olds[0] -= 1\\n\\nfor old in olds:\\n print(old)\"\n },\n {\n \"alpha_fraction\": 0.597597599029541,\n \"alphanum_fraction\": 0.6966966986656189,\n \"avg_line_length\": 21.266666412353516,\n \"blob_id\": \"73d6e45e3c5530b2d80c0bbdb95cfd4d1ae7b02b\",\n \"content_id\": \"d9841906b6935555519fe1043e0f11a7d6cb210a\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 333,\n \"license_type\": \"no_license\",\n \"max_line_length\": 61,\n \"num_lines\": 15,\n \"path\": \"/알고리즘/[템플릿]/문자열 탐색/Brute Force.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import timeit\\nstart = timeit.default_timer()\\n\\ntext = 'aawneifonoeiwmcl,xjfklsajdfklajewklfhaefnk1r7e8yiueniuencieh02cf12fh0v3ymn,cgjklo10f321hcqvyjkn9og4ml0f21hc3v9yjknqom0h1vcf2y93njkmof210hc3v9jkoymn0f21hcvko9jnym021hfok9cqv3jln,210hf9ocv3jklmny,qgf21h0kmn,jlocqv39cf30hkv9mn,ojlgfvc0hkx12mn,jol9210cf3hk9qvomn,jl10fh9cv3okjmn,g10cf3hv9knom0f9h3koncvm,02f1h9kcv3omn,j2f103vhc9knmjog0f2h19kncv3jmoyg0f21h9cv3njkgmoy0fh921ojkymncgv3,rlf21h0c3v9nyjkmgoh0n9f2yjkmcv13g4h0f21c3vn9kmjyg0hf219ncvjkm3og0f21hc3v9mnjky,o0f21hcvn9km3jy0h1vcf2nk9mj3021hnkf9m,cv3jhf210ncv3mjk9h0f219nycv3jkg0h9f21nycv3jk0h9f21nycv3kjg0fh219mnjkcv3,yogf20h1v3n9cg4kmf0h2913vcgf3210cvh9g4n20f31h9cvnkgf02h9c13vngtkr40fh921nkcvm30hn9kfmcv3h0nf1mk,j9cv3gf,mn12v0chkljox30cf21hkv3mn,9of0cmn,hkvjlo390hk9omnj,2f13vc0h9nk1mojfc3v0h9n12cfkmv3021h9cfnvyh0nf29kmcv13jh29fn1kmcv30f2h91ncvkm30h92nkf1mcv3o0h9f21nkmocv,30h9nk2fmcv130h9fknc12v30h9nk12fmcv320hc9f1nvk30f2h9c1vnkm30h9fnkc1vh9nkmjof12cv30h9fnkmcv12o,30h9f21nkcvmx30hf9n12ckv30h9nfkmc12v30hk9n,mfjloc1v0fh912vcnk3mh9f12vcn30h9nkcf12v30hf2n91mcv0hnf9c12v3h0n9mkj2cfv130h9nfc12v30h9fnkcv12m3gf219hcvn3kg0f21h9cvn3f219hcvk3nf021h9cnv39hf21cv30h9nf2c1vg3h09n1f2ycvg30h9fnc12vy8g3df09h2c1vg30h98y7nfcv213gh0987yfv2c13h0987yf2cv13ghy0987ncfv123h09872fyv134chyf7098cv2g09h87fv2cg13hy67098cv12gh09f21ycv3g4h09y87f12v3cg0h9821vc309h8f12cv309hfcv09hn12vcx309hn1f2cv30h9nf12cv30hn1cf2'\\npattern = 'cx309hn1f2cv30h9'\\nresult = 0\\n\\nfor i in range(len(text)-len(pattern)):\\n if text[i:i+len(pattern)] == pattern:\\n result = 1\\n break\\nprint(result)\\n\\nend = timeit.default_timer()\\nprint(f'{end-start:.5f}')\"\n },\n {\n \"alpha_fraction\": 0.5829383730888367,\n \"alphanum_fraction\": 0.6255924105644226,\n \"avg_line_length\": 22.44444465637207,\n \"blob_id\": \"0e6b036ec70f7710d9cfe71f67aa2269538db18a\",\n \"content_id\": \"ddcb0bb13cd837b44f82b0c142d965f3c19c2a94\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 211,\n \"license_type\": \"no_license\",\n \"max_line_length\": 48,\n \"num_lines\": 9,\n \"path\": \"/알고리즘/온라인저지/2021/08/0822/단어 공부.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"word = input()\\nword = word.upper()\\nalphabet = [0] * 26\\nfor wrd in word:\\n alphabet[ord(wrd)-65] += 1\\nif alphabet.count(max(alphabet)) > 1:\\n print('?')\\nelse:\\n print(chr(alphabet.index(max(alphabet))+65))\\n\"\n },\n {\n \"alpha_fraction\": 0.49484536051750183,\n \"alphanum_fraction\": 0.5103092789649963,\n \"avg_line_length\": 20.66666603088379,\n \"blob_id\": \"83731e0c44d84a7ea51479ef3694e184b9c2e4c4\",\n \"content_id\": \"70f245015a9844025ba5de6dc1989533c6362a30\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 194,\n \"license_type\": \"no_license\",\n \"max_line_length\": 48,\n \"num_lines\": 9,\n \"path\": \"/알고리즘/온라인저지/2022/07/0722/콘서트.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = int(input())\\nA = list(map(int, input().split())) # first sold\\nA.sort()\\nC = list(range(1, len(A)+1))\\nfor i in range(len(A)):\\n if A[i] != C[i]:\\n print(C[i])\\n exit()\\nprint(N+1)\"\n },\n {\n \"alpha_fraction\": 0.36477985978126526,\n \"alphanum_fraction\": 0.4433962404727936,\n \"avg_line_length\": 28,\n \"blob_id\": \"290ee7d9c6415599be247470c4d66c7bf1072241\",\n \"content_id\": \"365dd4d49ad36d75e82693d02b00d99834bc0738\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 318,\n \"license_type\": \"no_license\",\n \"max_line_length\": 45,\n \"num_lines\": 11,\n \"path\": \"/알고리즘/온라인저지/2022/07/0731/투자의 귀재 배주형.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"H, Y = map(int, input().split())\\ndp = [0]*(Y+1)\\ndp[0] = H\\nfor i in range(1, Y+1):\\n if i-1 >= 0 and dp[i-1]:\\n dp[i] = max(int(dp[i-1]*1.05), dp[i])\\n if i-3 >= 0 and dp[i-3]:\\n dp[i] = max(int(dp[i-3]*1.2), dp[i])\\n if i-5 >= 0 and dp[i-5]:\\n dp[i] = max(int(dp[i-5]*1.35), dp[i])\\nprint(dp[Y])\"\n },\n {\n \"alpha_fraction\": 0.5499181747436523,\n \"alphanum_fraction\": 0.5908346772193909,\n \"avg_line_length\": 24.5,\n \"blob_id\": \"2cac20762e0868fa5e3a1325ce224952afafdbc6\",\n \"content_id\": \"e3b1c02714410d9e8969d7b4e3f0449b223c77e8\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 999,\n \"license_type\": \"no_license\",\n \"max_line_length\": 52,\n \"num_lines\": 24,\n \"path\": \"/알고리즘/온라인저지/2021/08/0807/소수 찾기.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"\\\"\\\"\\\" 초기 풀이\\nN개의 숫자 중 소수는 몇개인가\\n소수인지 아는 법?\\n약수가 1과 자기 자신\\n주어질 수들은 1000이하 라는 조건\\n1000까지, 주어진 수들을, 이중순회 하면서\\n주어진 수를 1부터 주어진 수까지 나눌 때\\n주어진 수까지 나머지가 안 생기면 소수\\n중간에 나머지가 생기면(True) not소수\\n\\\"\\\"\\\"\\n\\n# 최종 코드\\nN = int(input()) # 숫자 개수 입력받고\\nnumbers = list(map(int, input().split())) # 숫자들 입력받고\\ncount = 0 # 소수 개수를 셀 count 초기화\\nfor number in numbers: # 입력받은 숫자들을 순회하면서\\n for i in range(2, 1001): # 2부터 1000까지 나누면서 검사\\n if number % i == 0: # 나머지가 없고\\n if number == i: # number본인이면\\n count += 1 # 소수이므로 count에 1 저장\\n else: # 나머지는 0이지만 number본인이 아니라면\\n break # 약수임\\n\\nprint(count) # 소수 개수 출력\"\n },\n {\n \"alpha_fraction\": 0.31092438101768494,\n \"alphanum_fraction\": 0.3613445460796356,\n \"avg_line_length\": 14,\n \"blob_id\": \"b2910816929c4b50f6fa19e77b8a7dd7e3f42fe4\",\n \"content_id\": \"b30eff541e516d477a4b4828bd67f159edfb3e7a\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 119,\n \"license_type\": \"no_license\",\n \"max_line_length\": 35,\n \"num_lines\": 8,\n \"path\": \"/알고리즘/온라인저지/2022/01/0131/별 찍기 - 6.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = int(input())\\n\\ni = (N*2)-1\\n\\nfor n in range(N):\\n a = ((N*2-1)-i)//2\\n print(' ' * a, '*' * i, sep='')\\n i -= 2\"\n },\n {\n \"alpha_fraction\": 0.515539288520813,\n \"alphanum_fraction\": 0.5265082120895386,\n \"avg_line_length\": 25.095237731933594,\n \"blob_id\": \"40fb92975b17618fbc3938de80cfabf9d6427fbc\",\n \"content_id\": \"bb2187291662d2f2cb5f5d8b3f41d3b835829936\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 547,\n \"license_type\": \"no_license\",\n \"max_line_length\": 57,\n \"num_lines\": 21,\n \"path\": \"/알고리즘/온라인저지/2022/06/0629/스타트와 링크.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from itertools import combinations as comb\\n\\nN = int(input())\\nscope = N\\ncount = scope//2\\ntmp = list(comb(list(range(scope)), count))\\nresult = 1e9\\narr = [list(map(int, input().split())) for _ in range(N)]\\nfor i in range(len(tmp)//2):\\n start = tmp[i]\\n link = tmp[-i-1]\\n S = L = 0\\n for j in range(N):\\n for k in range(N):\\n if j in start and k in start:\\n S += arr[j][k]\\n elif j in link and k in link:\\n L += arr[j][k]\\n if abs(S-L) < result:\\n result = abs(S-L)\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.5777778029441833,\n \"alphanum_fraction\": 0.5777778029441833,\n \"avg_line_length\": 22,\n \"blob_id\": \"b6267902303e193af17f093aba9b58e04cde2c0a\",\n \"content_id\": \"a97fd0489f708bdb650613bd101cfe2a1b8a09de\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 45,\n \"license_type\": \"no_license\",\n \"max_line_length\": 22,\n \"num_lines\": 2,\n \"path\": \"/알고리즘/온라인저지/2023/05/0501/2 桁の整数 (Two-digit Integer).py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"print(input(), end='')\\nprint(input(), end='')\"\n },\n {\n \"alpha_fraction\": 0.41632652282714844,\n \"alphanum_fraction\": 0.5020408034324646,\n \"avg_line_length\": 21.363636016845703,\n \"blob_id\": \"ab3773a5e5cc5e2a3b83f3cb4450bc2391b0ea89\",\n \"content_id\": \"554f2f5d0a09a75a6434832d5062bdaa5d34154c\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 245,\n \"license_type\": \"no_license\",\n \"max_line_length\": 61,\n \"num_lines\": 11,\n \"path\": \"/알고리즘/온라인저지/2022/06/0619/핸드폰 번호 궁합.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"A = input()\\nB = input()\\ntmp1 = ''\\ntmp2 = ''\\nfor i in range(8):\\n tmp1 = tmp1 + A[i] + B[i]\\nfor j in range(16, 2, -1):\\n for i in range(1, j):\\n tmp2 = tmp2 + str((int(tmp1[i-1]) + int(tmp1[i]))%10)\\n tmp1, tmp2 = tmp2, ''\\nprint(tmp1)\"\n },\n {\n \"alpha_fraction\": 0.4017094075679779,\n \"alphanum_fraction\": 0.42307692766189575,\n \"avg_line_length\": 15.785714149475098,\n \"blob_id\": \"f3faf142176edca1e070e889a5cb844b4563b897\",\n \"content_id\": \"0510e5a6b193ea492f4c84a9907960eca107a65c\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 234,\n \"license_type\": \"no_license\",\n \"max_line_length\": 23,\n \"num_lines\": 14,\n \"path\": \"/알고리즘/온라인저지/2023/01/0107/A와 B.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"S = list(input())\\nT = list(input())\\nresult = 0\\nwhile len(T) > 0:\\n if S == T: \\n result = 1\\n break\\n flag = False\\n if T[-1] == 'B':\\n flag = True\\n T.pop()\\n if flag:\\n T = T[::-1] \\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.557603657245636,\n \"alphanum_fraction\": 0.5714285969734192,\n \"avg_line_length\": 23.22222137451172,\n \"blob_id\": \"4804ad55b076211b17bd44ce228a85fef7ad49a2\",\n \"content_id\": \"e25a0d90b0350e1da12009848b64374f6ca76739\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 217,\n \"license_type\": \"no_license\",\n \"max_line_length\": 41,\n \"num_lines\": 9,\n \"path\": \"/알고리즘/온라인저지/2022/10/1013/폭죽쇼.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N, C = map(int, input().split())\\nhanabi = [int(input()) for _ in range(N)]\\nresult = 0\\nfor i in range(1, C+1):\\n fire = False\\n for h in hanabi:\\n if not i%h: fire = True\\n result += int(fire)\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.4517958462238312,\n \"alphanum_fraction\": 0.47826087474823,\n \"avg_line_length\": 26.894737243652344,\n \"blob_id\": \"ac615c5a0a07b933c2b7f57c756d577fed07411c\",\n \"content_id\": \"380a248caed932d91fe75b6cb140dc686158fd9b\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 529,\n \"license_type\": \"no_license\",\n \"max_line_length\": 70,\n \"num_lines\": 19,\n \"path\": \"/알고리즘/온라인저지/2022/06/0629/하키.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"W, H, X, Y, P = map(int, input().split())\\nLB = [X, Y] # left bottom\\nRT = [X+W, Y+H] # right top\\nR = H//2\\nresult = 0\\nfor p in range(P):\\n tmp = list(map(int, input().split()))\\n square = True\\n for i in range(2):\\n if tmp[i] < LB[i] or tmp[i] > RT[i]:\\n square = False\\n if square:\\n result += 1\\n x, y = tmp\\n if (abs(x-X)**2 + abs(y-(Y+R))**2)**0.5 <= R and not square:\\n result += 1\\n elif (abs(x-(X+W))**2 + abs(y-(Y+R))**2)**0.5 <= R and not square:\\n result += 1\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.5574468374252319,\n \"alphanum_fraction\": 0.5936170220375061,\n \"avg_line_length\": 17.84000015258789,\n \"blob_id\": \"c961d8ba7bcbaa0fdaf899d553714d2837233899\",\n \"content_id\": \"39a00d1bd7deeaf4ddd03513e2bd939d4fc31eb0\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 480,\n \"license_type\": \"no_license\",\n \"max_line_length\": 54,\n \"num_lines\": 25,\n \"path\": \"/알고리즘/온라인저지/2022/10/1006/N과 M (8).py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\n\\ndef dfs(depth, start):\\n if depth == M: \\n print(*result) \\n return\\n for i in range(start, N):\\n result.append(arr[i])\\n dfs(depth+1, i)\\n result.pop()\\n\\nN, M = map(int, input().rstrip().split())\\narr = sorted(list(map(int, input().rstrip().split())))\\nresult = []\\ndfs(0, 0)\\n\\n\\\"\\\"\\\"\\n<참고한 링크>\\nhttps://tmdrl5779.tistory.com/27\\nhttps://honggom.tistory.com/110\\n\\\"\\\"\\\"\\n\\n# https://www.acmicpc.net/problem/15657\"\n },\n {\n \"alpha_fraction\": 0.5089285969734192,\n \"alphanum_fraction\": 0.5178571343421936,\n \"avg_line_length\": 11.55555534362793,\n \"blob_id\": \"439c4b6618ae305a4189c95b7f9c7c0da9d5c7ab\",\n \"content_id\": \"10bb0d84c03a13e5afe4002c152c99b8f4e4b776\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 112,\n \"license_type\": \"no_license\",\n \"max_line_length\": 33,\n \"num_lines\": 9,\n \"path\": \"/알고리즘/온라인저지/2022/02/0220/이상한 곱셈.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"A, B = input().split()\\n\\nresult = 0\\n\\nfor a in A:\\n for b in B:\\n result += int(a) * int(b)\\n\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.4029850661754608,\n \"alphanum_fraction\": 0.5074626803398132,\n \"avg_line_length\": 21.66666603088379,\n \"blob_id\": \"29dfb69b90dd1b65a0e90ddbc4c6b17968c17777\",\n \"content_id\": \"c8ce52b0d69142867374148adfd0a72f3d332fb6\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 67,\n \"license_type\": \"no_license\",\n \"max_line_length\": 32,\n \"num_lines\": 3,\n \"path\": \"/알고리즘/온라인저지/2022/08/0831/욱 제.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"A, B = map(int, input().split())\\nM = (B-A)/400\\nprint(1/(10**M + 1))\"\n },\n {\n \"alpha_fraction\": 0.4801762104034424,\n \"alphanum_fraction\": 0.5330396294593811,\n \"avg_line_length\": 13.25,\n \"blob_id\": \"e5ff3bd3d073f6cb8c8c2b977c57b6f5ea6df32b\",\n \"content_id\": \"d3de0384006bb7c71be5da3c17a3151020d848e9\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 227,\n \"license_type\": \"no_license\",\n \"max_line_length\": 28,\n \"num_lines\": 16,\n \"path\": \"/알고리즘/온라인저지/2022/01/0131/상근날드.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"burger = 2000\\ndrink = 2000\\n\\nfor i in range(3):\\n b = int(input())\\n if b < burger:\\n burger = b\\n\\nfor i in range(2):\\n d = int(input())\\n if d < drink:\\n drink = d\\n\\nresult = burger + drink - 50\\n\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.5483193397521973,\n \"alphanum_fraction\": 0.5651260614395142,\n \"avg_line_length\": 19.7391300201416,\n \"blob_id\": \"a1917bdd9a5d900a5822a8786e57cb6c37b09636\",\n \"content_id\": \"a1b80d0a6f610c2938dba0c84aa3fea048f68cf1\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 646,\n \"license_type\": \"no_license\",\n \"max_line_length\": 61,\n \"num_lines\": 23,\n \"path\": \"/알고리즘/온라인저지/2022/09/0904/조깅.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N, T = map(int, input().split())\\nrunner = [tuple(map(int, input().split())) for _ in range(N)]\\nstack = []\\ncnt = 1\\nfor r in runner[::-1]:\\n tmp = r[0] + (r[1]*T)\\n if stack and tmp < stack[-1]:\\n cnt += 1\\n if stack and tmp >= stack[-1]:\\n stack.append(stack[-1])\\n else:\\n stack.append(tmp)\\n print(tmp, stack)\\nprint(cnt)\\n\\n\\\"\\\"\\\"\\n맨 선두에 있는 주자부터 이동한다\\n당연히 맨 선두 주자는 하나의 그룹이 된다\\n그 다음 주자를 이동한다\\n그 다음 주자의 최고 이동거리가 선두주자보다\\n같거나 클 경우 한 그룹으로 붙는다\\n아닐 경우 다른 그룹이 된다\\n\\\"\\\"\\\"\"\n },\n {\n \"alpha_fraction\": 0.5477477312088013,\n \"alphanum_fraction\": 0.5819819569587708,\n \"avg_line_length\": 24.272727966308594,\n \"blob_id\": \"017792240767bab4ae12d0a40b4590c7320b74bc\",\n \"content_id\": \"37ed1e402f31098d85c28e29bb387e9e058e0f78\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 567,\n \"license_type\": \"no_license\",\n \"max_line_length\": 41,\n \"num_lines\": 22,\n \"path\": \"/알고리즘/온라인저지/2022/05/0508/경고.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from datetime import datetime\\n\\na = input()\\nb = input()\\ntime_1 = datetime.strptime(a,\\\"%H:%M:%S\\\")\\ntime_2 = datetime.strptime(b,\\\"%H:%M:%S\\\")\\nday_over = False\\ntime_interval = time_2 - time_1\\nif str(time_interval)[0] == '-':\\n day_over = True\\nif a == b: # 문제를 잘 읽자\\n print('24:00:00')\\nelif day_over:\\n if len(str(time_interval)) == 16:\\n print(str(time_interval)[8:])\\n else:\\n print('0'+str(time_interval)[8:])\\nelse: \\n if len(str(time_interval)) == 16:\\n print(str(time_interval))\\n else:\\n print('0'+str(time_interval))\"\n },\n {\n \"alpha_fraction\": 0.3164556920528412,\n \"alphanum_fraction\": 0.5,\n \"avg_line_length\": 13.454545021057129,\n \"blob_id\": \"eb5a34f3f2de84201e13e021f1c737a16ebf134a\",\n \"content_id\": \"e8e84516f0835ad9f5da5c6327e8dcbe400e3184\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 158,\n \"license_type\": \"no_license\",\n \"max_line_length\": 29,\n \"num_lines\": 11,\n \"path\": \"/알고리즘/SWEA/LEARN/Course/1. Programming Beginner/파이썬 프로그래밍 기초(2)/24차시 2. 자료구조 – 리스트, 튜플 - 연습문제 26.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"l1 = [1,3,6,78,35,55]\\nl2 = [12,24,35,24,88,120,155]\\n\\nresult = []\\n\\nfor i in l1:\\n for j in l2:\\n if i == j:\\n result.append(i)\\n\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.49264705181121826,\n \"alphanum_fraction\": 0.5073529481887817,\n \"avg_line_length\": 21.83333396911621,\n \"blob_id\": \"70c1cd7a2bb9310b15a978145f0c16fb472f3cbd\",\n \"content_id\": \"d9ac805ef6aecb37307f98271f8949dae5827ef6\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 136,\n \"license_type\": \"no_license\",\n \"max_line_length\": 43,\n \"num_lines\": 6,\n \"path\": \"/알고리즘/온라인저지/2022/09/0903/최대공약수.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"def gcd(a, b):\\n while b > 0: a, b = b, a%b\\n return a\\n\\nA, B = map(int, input().split())\\nfor _ in range(gcd(A, B)): print(1, end='')\"\n },\n {\n \"alpha_fraction\": 0.41432225704193115,\n \"alphanum_fraction\": 0.4271099865436554,\n \"avg_line_length\": 19.157894134521484,\n \"blob_id\": \"0561318cd2ea1df41e34a61550740e705a751eba\",\n \"content_id\": \"7147f7869569e7d603149fabfa9c3b6196721106\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 391,\n \"license_type\": \"no_license\",\n \"max_line_length\": 36,\n \"num_lines\": 19,\n \"path\": \"/알고리즘/온라인저지/2021/08/0828/그룹 단어 체커.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\nT = int(sys.stdin.readline())\\ncnt = 0\\nfor tc in range(T):\\n word = sys.stdin.readline()\\n i = 0\\n char = []\\n for i in range(len(word)):\\n if word[i] not in char:\\n char.append(word[i])\\n else:\\n if word[i] == word[i-1]:\\n pass\\n else:\\n cnt -= 1\\n break\\n cnt += 1\\nprint(cnt)\\n \"\n },\n {\n \"alpha_fraction\": 0.316546767950058,\n \"alphanum_fraction\": 0.3381294906139374,\n \"avg_line_length\": 21.280000686645508,\n \"blob_id\": \"a45d6082fea13752146098dc84b130239464b4b7\",\n \"content_id\": \"6e8aef03e9d560715519221159be584d49cf0c69\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 556,\n \"license_type\": \"no_license\",\n \"max_line_length\": 37,\n \"num_lines\": 25,\n \"path\": \"/알고리즘/온라인저지/2022/08/0827/기술 연계마스터 임스.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"O = False # combo over\\nN = int(input())\\nresult = 0\\nS = [[], []] # stack\\nfor i in list(input()):\\n if O: break\\n try: # 1~9\\n i = int(i)\\n result += 1\\n except: # LRSK\\n if i == 'L': S[0].append(i)\\n elif i == 'S': S[1].append(i)\\n elif i == 'R':\\n if S[0]:\\n S[0].pop()\\n result += 1\\n else:\\n O = True\\n elif i == 'K':\\n if S[1]:\\n S[1].pop()\\n result += 1\\n else:\\n O = True\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.5037146806716919,\n \"alphanum_fraction\": 0.5304605960845947,\n \"avg_line_length\": 27.08333396911621,\n \"blob_id\": \"48bd548b5ab7f33d8d5218ca7c64abe0142a5026\",\n \"content_id\": \"bdcfd737cde95d84d9a549d4d841842cc684a239\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 673,\n \"license_type\": \"no_license\",\n \"max_line_length\": 46,\n \"num_lines\": 24,\n \"path\": \"/알고리즘/온라인저지/2022/06/0629/덱.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from collections import deque\\nimport sys\\ndef input():\\n return sys.stdin.readline()\\n\\nD = deque()\\nfor i in range(int(input())):\\n tmp = input().split()\\n if tmp[0] == 'push_front':\\n D.appendleft(tmp[1])\\n elif tmp[0] == 'push_back':\\n D.append(tmp[1])\\n elif tmp[0] == 'pop_front':\\n print(D.popleft()) if D else print(-1)\\n elif tmp[0] == 'pop_back':\\n print(D.pop()) if D else print(-1)\\n elif tmp[0] == 'size':\\n print(len(D))\\n elif tmp[0] == 'empty':\\n print(0) if D else print(1)\\n elif tmp[0] == 'front':\\n print(D[0]) if D else print(-1)\\n elif tmp[0] == 'back':\\n print(D[-1]) if D else print(-1)\"\n },\n {\n \"alpha_fraction\": 0.4285714328289032,\n \"alphanum_fraction\": 0.5408163070678711,\n \"avg_line_length\": 32,\n \"blob_id\": \"cc5fb66e151c00cf4e5c20f61aad802a99a8351f\",\n \"content_id\": \"2b183588dd92a4764d19d055326bdd9a3ce59460\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 98,\n \"license_type\": \"no_license\",\n \"max_line_length\": 42,\n \"num_lines\": 3,\n \"path\": \"/알고리즘/온라인저지/2022/08/0822/Cupcake Party.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"B = [int(input()) for _ in range(2)] # box\\nC = B[0]*8 + B[1]*3 # cake\\nprint(C-28 if C-28>0 else 0)\"\n },\n {\n \"alpha_fraction\": 0.5188679099082947,\n \"alphanum_fraction\": 0.5283018946647644,\n \"avg_line_length\": 25.75,\n \"blob_id\": \"ab1fb14bc1b9389596579769312148f6fd1fe4c9\",\n \"content_id\": \"7669e22c1729ef7a5dab25856f24e70d0d91a234\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 106,\n \"license_type\": \"no_license\",\n \"max_line_length\": 36,\n \"num_lines\": 4,\n \"path\": \"/알고리즘/온라인저지/2023/06/0610/Schronisko.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"for _ in range(int(input())):\\n W, H = map(int, input().split())\\n result = (W*H)//2\\n print(result)\"\n },\n {\n \"alpha_fraction\": 0.46543779969215393,\n \"alphanum_fraction\": 0.4930875599384308,\n \"avg_line_length\": 23.22222137451172,\n \"blob_id\": \"ebf3291e911e0b358a1f3e934a91711c31eaceb0\",\n \"content_id\": \"6afe7d28382ed1531f307f68a819ac33ec570cfe\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 217,\n \"license_type\": \"no_license\",\n \"max_line_length\": 34,\n \"num_lines\": 9,\n \"path\": \"/알고리즘/온라인저지/2023/06/0611/Basketball One-on-One.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"record = input()\\nA, B = 0, 0\\nfor i in range(0, len(record), 2):\\n player = record[i]\\n if player == 'A':\\n A += int(record[i+1])\\n if player == 'B':\\n B += int(record[i+1])\\nprint('A' if A>B else 'B')\"\n },\n {\n \"alpha_fraction\": 0.4163934290409088,\n \"alphanum_fraction\": 0.4557377099990845,\n \"avg_line_length\": 18.125,\n \"blob_id\": \"5a40390bcbf1a6bc222c41fe67d1e623600ece70\",\n \"content_id\": \"c45c6c5226a89096a61c131b6645ca87f7e67d7e\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 305,\n \"license_type\": \"no_license\",\n \"max_line_length\": 42,\n \"num_lines\": 16,\n \"path\": \"/알고리즘/SWEA/LEARN/Course/2. Programming Intermediate/1. 파이썬 SW문제해결 기본 List1/9차시 1일차 - 구간합.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"T = int(input())\\n\\nfor t in range(1, T+1):\\n N, M = map(int, input().split())\\n\\n nums = list(map(int, input().split()))\\n\\n a = 99999999\\n b = 0\\n\\n for i in range(len(nums)-M+1):\\n tmp = sum(nums[i:i+M])\\n a = min(a, tmp)\\n b = max(b, tmp)\\n \\n print('#{} {}'.format(t, b-a))\"\n },\n {\n \"alpha_fraction\": 0.48852458596229553,\n \"alphanum_fraction\": 0.4961748719215393,\n \"avg_line_length\": 26.75757598876953,\n \"blob_id\": \"9c7102b660fd0ed42f774be11c0c0e8b6dead4a9\",\n \"content_id\": \"0fe0d3be48b674b56a567a25977eb59e448cd1ad\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1179,\n \"license_type\": \"no_license\",\n \"max_line_length\": 44,\n \"num_lines\": 33,\n \"path\": \"/알고리즘/온라인저지/2022/03/0322/택배 배송.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import heapq\\nimport sys\\nINF = sys.maxsize # 가상의 최대값\\n\\ndef dijkstra(start):\\n q = [] # 방문가능한 지점\\n heapq.heappush(q, (0, start)) # 출발점 입력\\n dis[start] = 0 # 출발지점은 거리가 0\\n while q: # 다익스트라\\n d, now = heapq.heappop(q)\\n # print(d, now) # 디버깅\\n if dis[now] < d: # 최소거리가 될 수 없으면\\n continue # 백트래킹\\n # print(graph[now]) # 디버깅\\n for v, w in graph[now]:\\n # 들고 있는 최소거리 + 이동할 거리\\n cost = d + w \\n if cost < dis[v]: # 새로운 최소값이면\\n dis[v] = cost # 갱신\\n # 다음 이동지점에 갱신된 최소값 추가\\n heapq.heappush(q, (cost, v))\\n\\nN, M = map(int, input().split())\\n# 각 노드에서 이동 가능한 지점들 리스트\\ngraph = [[] for _ in range(N+1)]\\ndis = [INF]*(N+1) # 각 노드별 최소 이동거리 DP\\nfor _ in range(M):\\n a, b, c = map(int, input().split())\\n # 양방향 방문가능 노드 추가\\n graph[a].append((b, c))\\n graph[b].append((a, c))\\ndijkstra(1) # 1부터 출발\\nprint(dis[N]) # 출력\"\n },\n {\n \"alpha_fraction\": 0.43065693974494934,\n \"alphanum_fraction\": 0.45985400676727295,\n \"avg_line_length\": 12.800000190734863,\n \"blob_id\": \"350afad8dc5fad2c5884f3a9d81d26e146e40066\",\n \"content_id\": \"1a347220dc61b354c911629c18916106a693b0a5\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 137,\n \"license_type\": \"no_license\",\n \"max_line_length\": 26,\n \"num_lines\": 10,\n \"path\": \"/알고리즘/SWEA/LEARN/Course/1. Programming Beginner/파이썬 프로그래밍 기초(2)/7차시 2. 자료구조 – 리스트, 튜플 - 연습문제 6.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"x = int(input())\\n\\ns = set()\\n\\nfor i in range(1, x//2+1):\\n if x%i == 0:\\n s.add(i)\\n s.add(int(x/i))\\n\\nprint(sorted(list(s)))\"\n },\n {\n \"alpha_fraction\": 0.41600000858306885,\n \"alphanum_fraction\": 0.42399999499320984,\n \"avg_line_length\": 13.764705657958984,\n \"blob_id\": \"bb27e22a09bc517898ad3450c9e511d09c976978\",\n \"content_id\": \"d6dfe442099ccde164c0a3a5786b95c6309ff058\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 250,\n \"license_type\": \"no_license\",\n \"max_line_length\": 35,\n \"num_lines\": 17,\n \"path\": \"/알고리즘/온라인저지/2022/02/0214/나는 행복합니다~.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"i = 0\\n\\nN, M, K = map(int, input().split())\\n\\nseat_found = False\\n\\nfor n in range(N):\\n for m in range(M):\\n if i == K:\\n print(n, m)\\n seat_found = True\\n break\\n\\n i += 1\\n \\n if seat_found:\\n break\"\n },\n {\n \"alpha_fraction\": 0.43609023094177246,\n \"alphanum_fraction\": 0.4661654233932495,\n \"avg_line_length\": 8.571428298950195,\n \"blob_id\": \"3c4ef75b41fde13a31379380d6636163b80a9adc\",\n \"content_id\": \"7746808e50c3875e740ed4226dfdc8b18946cacf\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 133,\n \"license_type\": \"no_license\",\n \"max_line_length\": 18,\n \"num_lines\": 14,\n \"path\": \"/알고리즘/온라인저지/2022/02/0227/2의 제곱인가.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = int(input())\\n\\nresult = 0\\n\\ntmp = 1\\n\\nwhile tmp <= N:\\n if tmp == N:\\n result = 1\\n break\\n\\n tmp *= 2\\n\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.3854489028453827,\n \"alphanum_fraction\": 0.39783281087875366,\n \"avg_line_length\": 39.125,\n \"blob_id\": \"0a2580fc047b86ba36227f1208ca1e4f511e9578\",\n \"content_id\": \"ce13783f39bb810fceecd3de1903746ec1cfe9df\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 852,\n \"license_type\": \"no_license\",\n \"max_line_length\": 76,\n \"num_lines\": 16,\n \"path\": \"/알고리즘/온라인저지/2021/08/0816/소수 구하기.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"A, B = map(int, input().split())\\n\\nn = B # 소수를 찾을 범위\\na = [False,False] + [True]*(n-1) # 0 ~ n 까지의 숫자 리스트\\n # 일단 True로 만들고, 소수가 아닌 숫자를 찾아서 False로 지움\\nprimes=[] # 소수 집합\\nfor i in range(2,n+1): # 2 ~ n까지 반복\\n if a[i]: # 2부터 시작, 해당 숫자가 지워지지 않고 남아있는 소수라면 \\n primes.append(i) # 소수 리스트에 추가\\n for j in range(2*i, n+1, i): # 해당 소수의 배수들을 \\n a[j] = False # 리스트에서 전부 False로 만들기\\n # bool타입이라 연산이 빠름\\n\\nfor prime in primes:\\n if prime >= A:\\n print(prime)\\n \"\n },\n {\n \"alpha_fraction\": 0.45392492413520813,\n \"alphanum_fraction\": 0.4778156876564026,\n \"avg_line_length\": 21.615385055541992,\n \"blob_id\": \"df05f1bf667cb0cda4f97786e746f79cf2b993c9\",\n \"content_id\": \"b0af1f962490f09538cfb35add0f08b487f91a05\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 293,\n \"license_type\": \"no_license\",\n \"max_line_length\": 36,\n \"num_lines\": 13,\n \"path\": \"/알고리즘/온라인저지/2022/07/0710/백설 공주와 일곱 난쟁이.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"D = [int(input()) for _ in range(9)]\\nresult = []\\n# print(D)\\nsumm = sum(D)\\nfor i in range(9):\\n for j in range(i+1, 9):\\n tmp = summ - (D[i]+D[j])\\n if tmp == 100:\\n result.append(D[i])\\n result.append(D[j])\\nfor d in D:\\n if d not in result:\\n print(d)\"\n },\n {\n \"alpha_fraction\": 0.40758293867111206,\n \"alphanum_fraction\": 0.44075828790664673,\n \"avg_line_length\": 25.5,\n \"blob_id\": \"363bb21c3f2e22172097fb633cb56d3799d46711\",\n \"content_id\": \"2d600e0163c0b82fb9657c52ff96506a750e902a\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 211,\n \"license_type\": \"no_license\",\n \"max_line_length\": 42,\n \"num_lines\": 8,\n \"path\": \"/알고리즘/온라인저지/2023/01/0102/CTP공국으로 이민 가자.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"for tc in range(int(input())-1, -1, -1):\\n input()\\n for i in input().split():\\n try:\\n print(chr(int(i)+64), end=' ')\\n except:\\n print(ord(i)-64, end=' ')\\n if tc: print()\"\n },\n {\n \"alpha_fraction\": 0.44133099913597107,\n \"alphanum_fraction\": 0.457092821598053,\n \"avg_line_length\": 39.85714340209961,\n \"blob_id\": \"fa544fa0b76292b50da0baa81a91806d284d1e9a\",\n \"content_id\": \"a61788dfffe20d13f84b0babbee0afe581c07f05\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 719,\n \"license_type\": \"no_license\",\n \"max_line_length\": 71,\n \"num_lines\": 14,\n \"path\": \"/알고리즘/온라인저지/2022/05/0521/텔레프라임.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"num, new = map(int, input().split())\\nnew_num = int(str(new)+str(num))\\nn = new_num+2 # 소수를 찾을 범위\\na = [False,False] + [True]*(n-1) # 0 ~ n 까지의 숫자 리스트\\nprimes=[] # 소수 집합\\nfor i in range(2,n+1): # 2 ~ n까지 반복\\n if a[i]: # 2부터 시작, 해당 숫자가 지워지지 않고 남아있는 소수라면 \\n primes.append(i) # 소수 리스트에 추가\\n for j in range(2*i, n+1, i): # 해당 소수의 배수들을 \\n a[j] = False # 리스트에서 전부 False로 만들기\\nif num in primes and new_num in primes:\\n print('Yes')\\nelse:\\n print('No')\"\n },\n {\n \"alpha_fraction\": 0.2628205120563507,\n \"alphanum_fraction\": 0.33012819290161133,\n \"avg_line_length\": 18.5625,\n \"blob_id\": \"335759fcf8cf506a8d419fb209bafe5040fcf324\",\n \"content_id\": \"da6f98c844aaa8c240122d9f6f4a5bafc14a29ed\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 312,\n \"license_type\": \"no_license\",\n \"max_line_length\": 29,\n \"num_lines\": 16,\n \"path\": \"/알고리즘/온라인저지/2023/01/0118/미국 스타일.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"for _ in range(int(input())):\\n A, B = input().split()\\n A = float(A)\\n if B == 'kg':\\n A *= 2.2046\\n B = 'lb'\\n elif B == 'lb':\\n A *= 0.4536\\n B = 'kg'\\n elif B == 'l':\\n A *= 0.2642\\n B = 'g'\\n else:\\n A *= 3.7854\\n B = 'l'\\n print(f'{A:.4f} {B}')\"\n },\n {\n \"alpha_fraction\": 0.4202898442745209,\n \"alphanum_fraction\": 0.4202898442745209,\n \"avg_line_length\": 16.375,\n \"blob_id\": \"eb37dc7370a0ca2e71a4687fd0785ac680ce3dc2\",\n \"content_id\": \"b08b12ad8fba64415c31f3bd6c1fd3d0f9079b96\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 138,\n \"license_type\": \"no_license\",\n \"max_line_length\": 22,\n \"num_lines\": 8,\n \"path\": \"/알고리즘/온라인저지/2023/05/0530/Triangles.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"while True:\\n N = int(input())\\n if not N:\\n break\\n line = '*'\\n for i in range(N):\\n print(line)\\n line += '*'\"\n },\n {\n \"alpha_fraction\": 0.4774535894393921,\n \"alphanum_fraction\": 0.5623342394828796,\n \"avg_line_length\": 10.8125,\n \"blob_id\": \"0982f4b5aaf63ff0f28cde1a6aab477a1674b0c0\",\n \"content_id\": \"7f2296dab404e575a6064a70cfc0bd2875dc7298\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 533,\n \"license_type\": \"no_license\",\n \"max_line_length\": 39,\n \"num_lines\": 32,\n \"path\": \"/알고리즘/온라인저지/2021/10/1011/이장님 초대.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"\\\"\\\"\\\"\\n1. 묘목 하나 심는데 1일\\n2. 묘목 n개 구입 -> n일\\n3. 이장님을 초대하기위해, 대신 묘목들이 완전히 자란 후에\\n 이장님을 초대하기 위한 최소 시간\\n\\n1. 묘목의 수\\n2. 각 묘목별 걸리는 시간\\n\\n1. 4 3 3 2 -> \\n2. 39 39 38 35 20 9\\n\\n2 3 4 5 ....\\n\\n값을 정렬하고\\nfor문 돌려서\\nrange(2, N) 더해주고\\nmax\\n\\\"\\\"\\\"\\n\\nN = int(input())\\ntrees = list(map(int, input().split()))\\n\\ntrees.sort(reverse=True)\\n\\nj = 0\\n\\nfor i in range(2, 2+N):\\n trees[j] += i\\n j += 1\\n\\nprint(max(trees))\"\n },\n {\n \"alpha_fraction\": 0.4636015295982361,\n \"alphanum_fraction\": 0.49042144417762756,\n \"avg_line_length\": 22.81818199157715,\n \"blob_id\": \"5bd9de97cedd2b2d77f669fdbacd7e8ed53947eb\",\n \"content_id\": \"362cac01835180fbc040a9f32de10e22c1b7c482\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 261,\n \"license_type\": \"no_license\",\n \"max_line_length\": 50,\n \"num_lines\": 11,\n \"path\": \"/알고리즘/온라인저지/2023/02/0217/동혁 피자.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"pizza = 0\\nwhile True:\\n tmp = input()\\n if tmp == '0': break\\n pizza += 1\\n R, W, L = map(int, tmp.split())\\n A = (R*2)**2\\n B = W**2 + L**2\\n result = 'fits'\\n if A < B: result = 'does not fit'\\n print(f'Pizza {pizza} {result} on the table.')\"\n },\n {\n \"alpha_fraction\": 0.4188311696052551,\n \"alphanum_fraction\": 0.4350649416446686,\n \"avg_line_length\": 21.071428298950195,\n \"blob_id\": \"f7b1a290c7e4774b35dd4cfd4dab62b8cd0cea8c\",\n \"content_id\": \"b2a8b0ba3775b22aba9eb7c882cc08e8e7c17d24\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 308,\n \"license_type\": \"no_license\",\n \"max_line_length\": 39,\n \"num_lines\": 14,\n \"path\": \"/알고리즘/온라인저지/2022/09/0903/GCD 합.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"def gcd(a, b):\\n while b > 0:\\n a, b = b, a % b\\n return a\\n\\nfor _ in range(int(input())):\\n N = list(map(int, input().split()))\\n n = N.pop(0)\\n result = 0\\n for i in range(n-1):\\n for j in range(i+1, n):\\n A, B = N[i], N[j]\\n result += gcd(A, B)\\n print(result)\"\n },\n {\n \"alpha_fraction\": 0.5523809790611267,\n \"alphanum_fraction\": 0.5523809790611267,\n \"avg_line_length\": 20.200000762939453,\n \"blob_id\": \"44afbf6170a27dd2156fe7384baf0a7fbc7a2d1e\",\n \"content_id\": \"8858f1bd875530e71be45f8d76be62dbe69ce996\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 105,\n \"license_type\": \"no_license\",\n \"max_line_length\": 47,\n \"num_lines\": 5,\n \"path\": \"/알고리즘/온라인저지/2022/02/0205/더하기.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"T = int(input())\\n\\nfor t in range(T):\\n N = int(input())\\n print(sum(list(map(int, input().split()))))\"\n },\n {\n \"alpha_fraction\": 0.5377049446105957,\n \"alphanum_fraction\": 0.5639344453811646,\n \"avg_line_length\": 22.538461685180664,\n \"blob_id\": \"18e38a05eb5c0363aa91182ddd6581008f43b212\",\n \"content_id\": \"b2879343159e3055f8d2bd7e2a875e8a108a544a\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 305,\n \"license_type\": \"no_license\",\n \"max_line_length\": 40,\n \"num_lines\": 13,\n \"path\": \"/알고리즘/[템플릿]/이분탐색/숫자 카드 2.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = int(input())\\nN_list = list(map(int, input().split()))\\ndct = {}\\nfor n in N_list:\\n try: dct[n] += 1\\n except: dct[n] = 1\\nM = int(input())\\nM_list = list(map(int, input().split()))\\nfor m in M_list:\\n try: print(dct[m], end=' ')\\n except: print(0, end=' ')\\n\\n# https://www.acmicpc.net/problem/10816\"\n },\n {\n \"alpha_fraction\": 0.6299999952316284,\n \"alphanum_fraction\": 0.6399999856948853,\n \"avg_line_length\": 24.04166603088379,\n \"blob_id\": \"ed8e3a359486ee79ee287374a0a3dcfced3892b0\",\n \"content_id\": \"9b4607b5c2ad5116cfe9ee31e522da1875ead236\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1054,\n \"license_type\": \"no_license\",\n \"max_line_length\": 52,\n \"num_lines\": 24,\n \"path\": \"/알고리즘/온라인저지/2021/08/0814/로프.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"\\\"\\\"\\\"\\n로프는 k개\\nk개의 로프로 w만큼을 나눠서 들어올릴 때\\n각 로프에 가해지는 하중은 w/k\\n로프의 최대하중이 w/k를 넘기면 안됌\\n모든 로프에 걸리는 하중은 w/k로 같고\\n제일 하중이 낮은 로프가 이를 버텨내야 한다\\n그 때의 w값\\n큰거부터 내려가야 한다\\n하중이 큰 로프부터 한개 두개 세개... 하다가 \\n최대하중이 계속 증가하는데 꺾이는 순간이 온다\\n\\\"\\\"\\\"\\n\\nN = int(input()) # 줄의 개수\\nropes = [] # 로프들 초기화\\nfor n in range(N): # 로프 개수만큼 반복하면서\\n ropes.append(int(input())) # 로프들 입력받기\\nropes.sort() # 정렬하고\\nropes.reverse() # 뒤집어서 중량이 큰 로프가 앞으로 오도록\\nmax_weight = ropes[0] # 제일 중량이 큰 로프 혼자 있을때가 최대중량 초기값\\nfor n in range(1, N+1): # 로프 1개부터 N개까지\\n if max_weight <= ropes[n-1]*n: # 최대하중이 기존보다 크면\\n max_weight = ropes[n-1]*n # 새로 저장\\nprint(max_weight) # 최대하중 출력\"\n },\n {\n \"alpha_fraction\": 0.5228426456451416,\n \"alphanum_fraction\": 0.5279187560081482,\n \"avg_line_length\": 23.625,\n \"blob_id\": \"78c03d4ee5954b29091254c63a1bc4b01fb4a986\",\n \"content_id\": \"2562e818da9f5bc9d3096591a92aeb0e6147331c\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 197,\n \"license_type\": \"no_license\",\n \"max_line_length\": 38,\n \"num_lines\": 8,\n \"path\": \"/알고리즘/온라인저지/2023/05/0515/Teleportation.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"A, B, X, Y = map(int, input().split())\\nA, B = min((A, B)), max((A, B))\\nX, Y = min((X, Y)), max((X, Y))\\nresult = 0\\nresult += abs(A-X)\\nresult += abs(B-Y)\\nresult = min(result, abs(A-B))\\nprint(result)\\n\"\n },\n {\n \"alpha_fraction\": 0.5198019742965698,\n \"alphanum_fraction\": 0.5396039485931396,\n \"avg_line_length\": 22.823530197143555,\n \"blob_id\": \"28356683acc71a1d4cf2f62566db06e8e818ac8c\",\n \"content_id\": \"433f200d53edac9eb713303f72be19b3a751fe46\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 404,\n \"license_type\": \"no_license\",\n \"max_line_length\": 50,\n \"num_lines\": 17,\n \"path\": \"/알고리즘/온라인저지/2021/08/0822/일곱 난쟁이.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"dwarf = []\\nfor n in range(9):\\n dwarf.append(int(input()))\\ndwarf.sort()\\nall_dwarf = sum(dwarf)\\nfound = False\\nfor i in range(8):\\n for j in range(i+1, 9):\\n if all_dwarf - dwarf[i] - dwarf[j] == 100:\\n dwarf.pop(dwarf.index(dwarf[i]))\\n dwarf.pop(dwarf.index(dwarf[j-1]))\\n found = True\\n break\\n if found:\\n break\\nfor dwa in dwarf:\\n print(dwa)\"\n },\n {\n \"alpha_fraction\": 0.6240601539611816,\n \"alphanum_fraction\": 0.6315789222717285,\n \"avg_line_length\": 21.33333396911621,\n \"blob_id\": \"fe069c22940eb8350c9b348e5840ac763e43904e\",\n \"content_id\": \"b671fe63d1017fc1f2fb97b0763fd18d400307b8\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 133,\n \"license_type\": \"no_license\",\n \"max_line_length\": 67,\n \"num_lines\": 6,\n \"path\": \"/알고리즘/온라인저지/2022/09/0927/수 정렬하기 5.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\n\\nN = int(input().rstrip())\\nfor i in sorted([int(input().rstrip()) for _ in [0]*(N)]): print(i)\"\n },\n {\n \"alpha_fraction\": 0.41981130838394165,\n \"alphanum_fraction\": 0.4245283007621765,\n \"avg_line_length\": 24,\n \"blob_id\": \"406883a14d39be71fce2082477af3ea690f2226f\",\n \"content_id\": \"7f7c7ebde5e46310c8521e68c8ce6ba9c320f581\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 478,\n \"license_type\": \"no_license\",\n \"max_line_length\": 33,\n \"num_lines\": 17,\n \"path\": \"/알고리즘/온라인저지/2022/07/0726/사과 담기 게임.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N, M = map(int, input().split())\\nJ = int(input())\\nresult, s, e = 0, 1, M\\nfor j in range(J):\\n A = int(input())\\n if s<=A<=e: # 움직이지 않아도 될 때\\n continue\\n else: # 움직여야 할 때\\n if A < s: # 좌로 움직일 때\\n move = s-A\\n result += move \\n s, e = s-move, e-move\\n elif e < A: # 우로 움직일 때\\n move = A-e\\n result += move\\n s, e = s+move, e+move\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.5605095624923706,\n \"alphanum_fraction\": 0.5796178579330444,\n \"avg_line_length\": 18.75,\n \"blob_id\": \"3cc4f0f3d54594d150c93db2f40675d4e4531984\",\n \"content_id\": \"32f7d0c62b800c8ecdd547111f4506fd4f183b05\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 157,\n \"license_type\": \"no_license\",\n \"max_line_length\": 32,\n \"num_lines\": 8,\n \"path\": \"/알고리즘/온라인저지/2022/03/0331/치킨 두 마리 (...).py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"A, B = map(int, input().split())\\nchicken = int(input())\\nresult = 0\\nif A+B >= chicken*2:\\n result = A + B - chicken*2\\nelse:\\n result = A + B\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.4131578803062439,\n \"alphanum_fraction\": 0.44999998807907104,\n \"avg_line_length\": 20.11111068725586,\n \"blob_id\": \"f430985660094bc7d47a683bb9725283234680e9\",\n \"content_id\": \"b794a39b2a7880a7bf66339cf5dd7823f749af52\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 380,\n \"license_type\": \"no_license\",\n \"max_line_length\": 46,\n \"num_lines\": 18,\n \"path\": \"/알고리즘/온라인저지/2022/07/0708/APC는 왜 서브태스크 대회가 되었을까.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N, L, K = map(int, input().split())\\nP = [] # problems\\nfor n in range(N):\\n P.append(tuple(map(int, input().split())))\\nP.sort(key=lambda x:x[1])\\n# print(P)\\nsolved = [0] * N\\nk = 0\\nresult = 0\\nfor i in range(N):\\n if k < K:\\n if P[i][1] <= L:\\n k += 1\\n result += 140\\n elif P[i][0] <= L:\\n k += 1\\n result += 100\\nprint(result)\\n\"\n },\n {\n \"alpha_fraction\": 0.5524079203605652,\n \"alphanum_fraction\": 0.5920680165290833,\n \"avg_line_length\": 19.823530197143555,\n \"blob_id\": \"bf1163c08244c46a46f3850c5903bf1b1a346313\",\n \"content_id\": \"010af6cc6b1b79c32ba17ecb51454a88548f8267\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 353,\n \"license_type\": \"no_license\",\n \"max_line_length\": 38,\n \"num_lines\": 17,\n \"path\": \"/알고리즘/온라인저지/2022/07/0714/통계학.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from collections import Counter\\n\\n\\nN = int(input())\\narr = [int(input()) for _ in range(N)]\\narr.sort()\\ncommon = Counter(arr).most_common()\\nprint(round(sum(arr)/N))\\nprint(arr[N//2])\\nif len(common) > 1:\\n if common[0][1] == common[1][1]:\\n print(common[1][0])\\n else:\\n print(common[0][0])\\nelse:\\n print(common[0][0])\\nprint(arr[-1]-arr[0])\"\n },\n {\n \"alpha_fraction\": 0.43497759103775024,\n \"alphanum_fraction\": 0.5112107396125793,\n \"avg_line_length\": 14.928571701049805,\n \"blob_id\": \"e6afa6eb2a7d74036e05bb93544773c00958b112\",\n \"content_id\": \"4dcf91f2192056d02af4a63d7a9ed7ce4385c60d\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 223,\n \"license_type\": \"no_license\",\n \"max_line_length\": 49,\n \"num_lines\": 14,\n \"path\": \"/알고리즘/SWEA/LEARN/Course/1. Programming Beginner/파이썬 프로그래밍 기초(2)/32차시 3. 자료구조 – 셋, 딕셔너리 - 연습문제 7.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"sen = input()\\n\\nLETTERS = 0\\nDIGITS = 0\\n\\nfor s in sen:\\n if 65 <= ord(s) <= 90 or 97 <= ord(s) <= 122:\\n LETTERS += 1\\n\\n if 48 <= ord(s) <= 57:\\n DIGITS += 1\\n\\nprint('LETTERS', LETTERS)\\nprint('DIGITS', DIGITS)\\n\"\n },\n {\n \"alpha_fraction\": 0.5794947743415833,\n \"alphanum_fraction\": 0.6032689213752747,\n \"avg_line_length\": 34.47368240356445,\n \"blob_id\": \"a8bb59cbaa059a14642f588bf9a0edd2183f933b\",\n \"content_id\": \"4eb850d20c76f3329b153f7175f89a2c10d9f70a\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 963,\n \"license_type\": \"no_license\",\n \"max_line_length\": 62,\n \"num_lines\": 19,\n \"path\": \"/알고리즘/온라인저지/2021/08/0801/숫자의 개수.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"numbers = [] # 입력받을 숫자의 리스트 초기화\\nfor i in range(3): # A, B, C 세개의 숫자를 입력받음\\n numbers += [int(input())] # 입력받아서 리스트에 추가\\nmultipled = 1 # 다 곱한 값의 초기값 1:O, 0:X\\nfor number in numbers: # multipled에 입력받은 숫자 곱해서 집어넣었고\\n multipled *= number\\nmultipled = str(multipled) # 곱한 값을 str로 변경\\ncounts = [] # 숫자들을 셀 리스트 초기화\\nfor i in range(10):\\n counts.append([]) # 각 카운트들을 담을 빈 리스트 생성\\nfor num in multipled:\\n for i in range(10):\\n if num == str(i): # 순회중인 숫자가 0~9중에 일치하는 수를\\n counts[i] += [1] # 확인해서 count 한 번\\nfor i in range(10):\\n counts[i] = sum(counts[i]) # 카운트한 숫자는 [1, 1, 1] 이렇게 되 있으니까\\n # 다 더한 값을 카운트에 재설정\\nfor count in counts:\\n print(count) # 카운트값들을 출력\"\n },\n {\n \"alpha_fraction\": 0.49572649598121643,\n \"alphanum_fraction\": 0.5341880321502686,\n \"avg_line_length\": 25.11111068725586,\n \"blob_id\": \"e8e4392364571628917a3e8b86ca3b88fe5f9f8f\",\n \"content_id\": \"efbd706ec6b1f59f020c6bf048f711077419379f\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 234,\n \"license_type\": \"no_license\",\n \"max_line_length\": 81,\n \"num_lines\": 9,\n \"path\": \"/알고리즘/온라인저지/2021/08/0815/다이얼.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"dial = {2:\\\"ABC\\\", 3:\\\"DEF\\\", 4:\\\"GHI\\\", 5:\\\"JKL\\\", 6:\\\"MNO\\\", 7:\\\"PQRS\\\", 8:\\\"TUV\\\", 9:\\\"WXYZ\\\"}\\nword = input()\\nresult = 0\\nfor wor in word:\\n for dil in dial:\\n if wor in dial[dil]:\\n result += dil\\nresult += len(word)\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.468137264251709,\n \"alphanum_fraction\": 0.48774510622024536,\n \"avg_line_length\": 24.5625,\n \"blob_id\": \"0eb013050782576e1f3e44ae5f04c6376de07098\",\n \"content_id\": \"5bd2afb0741b3f7734ba81b9477db1b908f9fd68\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 408,\n \"license_type\": \"no_license\",\n \"max_line_length\": 61,\n \"num_lines\": 16,\n \"path\": \"/알고리즘/온라인저지/2022/08/0801/먹을 것인가 먹힐 것인가.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"T = int(input())\\nfor t in range(T):\\n N, M = map(int, input().split())\\n A = sorted(list(map(int, input().split())), reverse=True)\\n B = sorted(list(map(int, input().split())), reverse=True)\\n i = j = 0\\n result = 0\\n while i<N and j<M:\\n if A[i] > B[j]:\\n result += M-j\\n i += 1\\n else:\\n j += 1\\n print(result)\\n\\n# https://www.acmicpc.net/problem/7795\"\n },\n {\n \"alpha_fraction\": 0.5077399611473083,\n \"alphanum_fraction\": 0.5263158082962036,\n \"avg_line_length\": 17,\n \"blob_id\": \"5b5300c6298d92ab3a09c9dfa936d9fde03121f1\",\n \"content_id\": \"0514a5505f54889b5c52f45d17e6f983f206dba8\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 323,\n \"license_type\": \"no_license\",\n \"max_line_length\": 49,\n \"num_lines\": 18,\n \"path\": \"/알고리즘/온라인저지/2022/10/1002/죽음의 게임.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\n\\nN, K = map(int, input().rstrip().split())\\ndeath = [int(input().rstrip()) for _ in range(N)]\\nresult = 0\\ni = 0\\nvisited = [0]*N\\nwhile i != K:\\n if not visited[i]:\\n visited[i] = 1\\n i = death[i]\\n result += 1\\n else: \\n print(-1)\\n exit()\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.465568870306015,\n \"alphanum_fraction\": 0.47604790329933167,\n \"avg_line_length\": 30.85714340209961,\n \"blob_id\": \"79d38458c02f609cfabab69330fb1079df89c8eb\",\n \"content_id\": \"f02a7b28896863fc8213a4dcf0fcd48b0aa43beb\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 668,\n \"license_type\": \"no_license\",\n \"max_line_length\": 67,\n \"num_lines\": 21,\n \"path\": \"/알고리즘/온라인저지/2021/08/0815/블랙잭_영남이 덕분에 성공.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N, M = map(int, input().split())\\ncards = list(map(int, input().split()))\\nblackjack = cards[0]+cards[1]+cards[2]\\ncards.sort()\\nfor i in range(N-2):\\n if cards[i] > M:\\n break\\n for j in range(i+1, N-1):\\n if cards[i] + cards[j] > M:\\n break\\n for k in range(j+1, N):\\n if cards[i] + cards[j] + cards[k] > M:\\n break\\n is_this_blackjack = cards[i]+cards[j]+cards[k]\\n if is_this_blackjack == M:\\n print(M)\\n exit()\\n else:\\n if abs(M - is_this_blackjack) < abs(M - blackjack):\\n blackjack = is_this_blackjack\\nprint(blackjack)\"\n },\n {\n \"alpha_fraction\": 0.46859902143478394,\n \"alphanum_fraction\": 0.48792269825935364,\n \"avg_line_length\": 28.714284896850586,\n \"blob_id\": \"e348f06afbca14ad86467dff0bdedcc723d81c71\",\n \"content_id\": \"2af9d999be9272ef6be2366c639661bde4d74c62\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 207,\n \"license_type\": \"no_license\",\n \"max_line_length\": 47,\n \"num_lines\": 7,\n \"path\": \"/알고리즘/온라인저지/2022/06/0626/나무 조각.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"arr = list(map(int, input().split()))\\ntmp = sorted(arr)\\nwhile arr != tmp:\\n for i in range(len(arr)-1):\\n if arr[i] > arr[i+1]:\\n arr[i], arr[i+1] = arr[i+1], arr[i]\\n print(*arr)\"\n },\n {\n \"alpha_fraction\": 0.4787878692150116,\n \"alphanum_fraction\": 0.5030303001403809,\n \"avg_line_length\": 15.600000381469727,\n \"blob_id\": \"34f9eb7ded60f0191d8fd16de5a0ae1f7e98551b\",\n \"content_id\": \"1404cebde3f33f92f0402c17e3fe95af36b1dd90\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 165,\n \"license_type\": \"no_license\",\n \"max_line_length\": 44,\n \"num_lines\": 10,\n \"path\": \"/알고리즘/온라인저지/2022/02/0202/나는 요리사다.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"winner = 0\\nmax_p = 0\\n\\nfor i in range(1, 6):\\n p = sum(list(map(int, input().split())))\\n if p > max_p:\\n max_p = p\\n winner = i\\n\\nprint(winner, max_p)\"\n },\n {\n \"alpha_fraction\": 0.4573054909706116,\n \"alphanum_fraction\": 0.4775458574295044,\n \"avg_line_length\": 25.81355857849121,\n \"blob_id\": \"2c384c00de3e5dd1f84484a6d49227fc4fddaa2b\",\n \"content_id\": \"bc436ae94342912704409000914fd95ad726f772\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1667,\n \"license_type\": \"no_license\",\n \"max_line_length\": 87,\n \"num_lines\": 59,\n \"path\": \"/알고리즘/온라인저지/2022/10/1006/빙산.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\nfrom collections import deque\\n\\ninput = sys.stdin.readline\\ndy, dx = [-1, 1, 0, 0], [0, 0, -1, 1]\\n\\ndef count_iceberg():\\n Q = deque()\\n visited = [[0]*M for _ in range(N)]\\n iceberg = 0\\n for i in range(N):\\n for j in range(M):\\n if arr[i][j] and not visited[i][j]:\\n iceberg += 1\\n Q.append((i, j))\\n visited[i][j] = 1\\n while Q:\\n y, x = Q.popleft()\\n for k in range(4):\\n ny, nx = y+dy[k], x+dx[k]\\n if 0<=ny<N and 0<=nx<M and not visited[ny][nx] and arr[ny][nx]:\\n Q.append((ny, nx))\\n visited[ny][nx] = 1\\n return iceberg\\n\\ndef check_seawater():\\n tmp_Q = deque()\\n for i in range(N):\\n for j in range(M):\\n if arr[i][j] == 0:\\n tmp_Q.append((i, j))\\n return tmp_Q\\n\\ndef melt_iceberg(seawater_Q):\\n while seawater_Q:\\n y, x = seawater_Q.popleft()\\n for k in range(4):\\n ny, nx = y+dy[k], x+dx[k]\\n if 0<=ny<N and 0<=nx<M and arr[ny][nx]>0:\\n arr[ny][nx] -= 1\\n return\\n\\nN, M = map(int, input().rstrip().split())\\narr = [list(map(int, input().rstrip().split())) for _ in range(N)]\\nQ = deque()\\nresult = 0\\nwhile count_iceberg() == 1:\\n result += 1\\n seawater_Q = check_seawater()\\n melt_iceberg(seawater_Q)\\nif count_iceberg() == 0: print(0)\\nelse: print(result)\\n\\n\\\"\\\"\\\"\\n두 덩어리로 분리되는 최초의 시간을 구해야 한다\\n끝까지 두덩이가 되지 않고 통째로 녹아버린다면 0을 출력\\n\\\"\\\"\\\"\\n\\n# https://www.acmicpc.net/problem/2573\"\n },\n {\n \"alpha_fraction\": 0.40229883790016174,\n \"alphanum_fraction\": 0.4195402264595032,\n \"avg_line_length\": 13.583333015441895,\n \"blob_id\": \"f76f08f07fa306f409656706f53ca18b8910d1ea\",\n \"content_id\": \"3d7cbdc71f22f4b2a939ffcc55b02f72b4aa0f3b\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 174,\n \"license_type\": \"no_license\",\n \"max_line_length\": 41,\n \"num_lines\": 12,\n \"path\": \"/알고리즘/온라인저지/2022/04/0425/鉛筆 (Pencils).py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N, A, B, C, D = map(int, input().split())\\nE = F = 0\\nif N%A:\\n E = N//A + 1\\nelse:\\n E = N//A\\nif N%C:\\n F = N//C + 1\\nelse:\\n F = N//C\\n# print(E, F)\\nprint(min(E*B, F*D))\"\n },\n {\n \"alpha_fraction\": 0.4746543765068054,\n \"alphanum_fraction\": 0.5414746403694153,\n \"avg_line_length\": 24.58823585510254,\n \"blob_id\": \"8aea8a168501d007b53551db291f8b8489e335ee\",\n \"content_id\": \"4b563852e71defe80557232cf3a7742768afebff\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 434,\n \"license_type\": \"no_license\",\n \"max_line_length\": 63,\n \"num_lines\": 17,\n \"path\": \"/알고리즘/[템플릿]/Dynamic Programming/다이나믹이 뭐예요.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\ndy, dx = [0, 1, 1], [1, 0, 1] # right, down, right-down\\nmod = int(1e9)+7\\n\\nN, M = map(int, input().rstrip().split())\\ndp = [[0]*M for _ in range(N)]\\ny, x = 0, 0\\nfor i in range(N): dp[i][0] = 1\\nfor i in range(M): dp[0][i] = 1\\nfor i in range(1, N):\\n for j in range(1, M):\\n dp[i][j] = (dp[i-1][j] + dp[i][j-1] + dp[i-1][j-1])%mod\\nprint(dp[N-1][M-1])\\n\\n# https://www.acmicpc.net/problem/14494\"\n },\n {\n \"alpha_fraction\": 0.4393063485622406,\n \"alphanum_fraction\": 0.4797687828540802,\n \"avg_line_length\": 23.85714340209961,\n \"blob_id\": \"dcce28229834651ee2cb5885a10cd5d127c02bca\",\n \"content_id\": \"0142b136fa2f5a1d91410735d0b0e5621fbd3aca\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 173,\n \"license_type\": \"no_license\",\n \"max_line_length\": 36,\n \"num_lines\": 7,\n \"path\": \"/알고리즘/온라인저지/2023/04/0418/겨울왕국 티켓 예매.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"H, W = ord('L')-65+1, 4\\nfor _ in range(int(input())):\\n N, M = map(int, input().split())\\n result = -1\\n if N>=H and M>=W:\\n result = (H-1)*M+4\\n print(result)\"\n },\n {\n \"alpha_fraction\": 0.5508981943130493,\n \"alphanum_fraction\": 0.5928143858909607,\n \"avg_line_length\": 32.599998474121094,\n \"blob_id\": \"9e42b3e0d516df438a5618438b30ec94cba49b34\",\n \"content_id\": \"be538d3c8e476c6150e5f104359db4b5b0abf6d1\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 167,\n \"license_type\": \"no_license\",\n \"max_line_length\": 54,\n \"num_lines\": 5,\n \"path\": \"/알고리즘/온라인저지/2023/04/0422/2017 아주대학교 프로그래밍 경시대회 (Small).py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"scores = []\\nfor i in range(1, int(input())+1):\\n scores.append(list(map(int, input().split()))+[i])\\nscores.sort(key=lambda x:(-x[0], x[1], x[2]))\\nprint(scores[0][3])\"\n },\n {\n \"alpha_fraction\": 0.56886225938797,\n \"alphanum_fraction\": 0.5888223648071289,\n \"avg_line_length\": 19.91666603088379,\n \"blob_id\": \"99ce2fba60e98428a56234311f4fe940be51a67d\",\n \"content_id\": \"6da09cb928f19fe48d933f0138bf19213368fed5\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 739,\n \"license_type\": \"no_license\",\n \"max_line_length\": 58,\n \"num_lines\": 24,\n \"path\": \"/알고리즘/온라인저지/2022/08/0808/가희와 키워드.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\n\\nN, M = map(int, input().split())\\nK = set(input().rstrip() for _ in range(N)) # keyword\\nfor _ in range(M): \\n tmp = set(input().rstrip().split(',')) # 개행문자('\\\\n') 제거\\n K -= tmp\\n print(len(K))\\n\\n\\\"\\\"\\\"\\n시간 : 21분\\n풀이\\n 시간은 1.5초지만 메모리가 넉넉한 문제이다\\n 제출언어로 PyPy를 사용한다\\n 빠른 입력을 위해 \\n input = sys.stdin.readline도 사용한다\\n N과 M은 둘 다 200,000으로 큰 편이다\\n set 클래스인 A와 B에 대해서 A-B가 가능하다\\n 키워드를 담은 set(K)에서\\n 가희가 메모로 작성하여 없앤 키워드를 빼주고\\n 매번 글을 쓰고 남은 키워드 개수를 출력한다\\n\\\"\\\"\\\"\"\n },\n {\n \"alpha_fraction\": 0.38064515590667725,\n \"alphanum_fraction\": 0.4580645263195038,\n \"avg_line_length\": 21.14285659790039,\n \"blob_id\": \"4c6a6ea46ea8b3ba87b302e233d4dda96120f30d\",\n \"content_id\": \"ea0813fdf249da916305677791e3f4216ee45468\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 155,\n \"license_type\": \"no_license\",\n \"max_line_length\": 43,\n \"num_lines\": 7,\n \"path\": \"/알고리즘/온라인저지/2022/06/0606/나누기.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = int(input())\\nF = int(input())\\ntmp = ((N//100)*100)\\nif tmp%F:\\n print((str((tmp//F)*F + F)+'0')[-3:-1])\\nelse:\\n print((str((tmp//F)*F)+'0')[-3:-1])\\n\"\n },\n {\n \"alpha_fraction\": 0.47983869910240173,\n \"alphanum_fraction\": 0.5080645084381104,\n \"avg_line_length\": 23.899999618530273,\n \"blob_id\": \"a9352abad8ba5a90237010f928c484c9e9ae5e13\",\n \"content_id\": \"6d71cd04fc81339dea1d96560eacc403deb8a8a5\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 248,\n \"license_type\": \"no_license\",\n \"max_line_length\": 45,\n \"num_lines\": 10,\n \"path\": \"/알고리즘/온라인저지/2022/10/1003/피보나치.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\n\\nfor t in range(1, int(input().rstrip())+1):\\n P, Q = map(int, input().rstrip().split())\\n a, b = 1, 1\\n for _ in range(P-2): a, b = b, (a+b)%Q\\n if Q == 1: b = 0\\n print('Case #{}: {}'.format(t, b))\"\n },\n {\n \"alpha_fraction\": 0.5232323408126831,\n \"alphanum_fraction\": 0.5535353422164917,\n \"avg_line_length\": 19.66666603088379,\n \"blob_id\": \"8c016928c58eebc240fdafd98c40c8b88ce75ba0\",\n \"content_id\": \"1de2a8d0af9cafcce41caa85f8e9de5288d65ade\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 495,\n \"license_type\": \"no_license\",\n \"max_line_length\": 48,\n \"num_lines\": 24,\n \"path\": \"/알고리즘/온라인저지/2022/09/0912/별 찍기 - 10.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from copy import deepcopy\\n\\nN = int(input())\\nfor k in range(1, 8): \\n if N == 3**k: break\\nwidth = k\\nsquare = ['*'*3] + ['* *'] + ['*'*3]\\n\\nlevel = 0\\ntmp, result = deepcopy(square), deepcopy(square)\\n\\nwhile level < k-1:\\n level += 1\\n result = []\\n for s in tmp:\\n result.append(s*3)\\n for s in tmp:\\n result.append(s + ' '*(3**level) + s)\\n for s in tmp:\\n result.append(s*3)\\n tmp = deepcopy(result)\\nfor r in result: print(r)\\n\\n# https://www.acmicpc.net/problem/2447\"\n },\n {\n \"alpha_fraction\": 0.38513514399528503,\n \"alphanum_fraction\": 0.46621620655059814,\n \"avg_line_length\": 23.83333396911621,\n \"blob_id\": \"a5a0909b799e9689e0f91e691f8f9ba86ad0570c\",\n \"content_id\": \"cc4d6bab3d888eca1eab59ff3f69b05bfdf2f427\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 148,\n \"license_type\": \"no_license\",\n \"max_line_length\": 37,\n \"num_lines\": 6,\n \"path\": \"/알고리즘/온라인저지/2022/07/0731/피보나치 수 4.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = int(input())\\ndp = [0, 1]\\nif N > 1: dp += [0] * (N-1)\\nfor i in range(2, N+1):\\n dp[i] = dp[i-1] + dp[i-2]\\nprint(dp[-1]) if N != 0 else print(0)\"\n },\n {\n \"alpha_fraction\": 0.4324324429035187,\n \"alphanum_fraction\": 0.45945945382118225,\n \"avg_line_length\": 14.904762268066406,\n \"blob_id\": \"0607d3ad476e524f828a81dfafafe94373438a87\",\n \"content_id\": \"d436c730334632964476d89869140b03e0deb0e7\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 333,\n \"license_type\": \"no_license\",\n \"max_line_length\": 44,\n \"num_lines\": 21,\n \"path\": \"/알고리즘/온라인저지/2022/09/0919/영식이와 친구들.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\n\\nN, M, L = map(int, input().rstrip().split())\\narr = [0]*N\\narr[0] += 1\\nresult = 0\\nnow = 0\\nwhile max(arr)<M:\\n if arr[now]%2:\\n now += L\\n now %= N\\n arr[now] += 1\\n else:\\n now -= L\\n now += N\\n now %= N\\n arr[now] += 1\\n result += 1\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.4039604067802429,\n \"alphanum_fraction\": 0.4534653425216675,\n \"avg_line_length\": 20.04166603088379,\n \"blob_id\": \"646918ea1308c5f15f208b7b96d6660a3721416a\",\n \"content_id\": \"f112be1d9387d246c604d6daeaec79e46cb0f63a\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 505,\n \"license_type\": \"no_license\",\n \"max_line_length\": 45,\n \"num_lines\": 24,\n \"path\": \"/알고리즘/온라인저지/2021/12/1216/사분면.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = int(input())\\n\\nquadrant = [0 for _ in range(5)]\\n\\nfor n in range(N):\\n x, y = map(int, input().split())\\n\\n if x == 0 or y == 0:\\n quadrant[4] += 1\\n elif x > 0 and y > 0:\\n quadrant[0] += 1\\n elif x < 0 and y > 0:\\n quadrant[1] += 1\\n elif x < 0 and y < 0:\\n quadrant[2] += 1\\n elif x > 0 and y < 0:\\n quadrant[3] += 1\\n\\nfor i in range(5):\\n if i == 4:\\n print('AXIS: {}'.format(quadrant[i]))\\n break\\n\\n print('Q{}: {}'.format(i+1, quadrant[i]))\\n\"\n },\n {\n \"alpha_fraction\": 0.43220338225364685,\n \"alphanum_fraction\": 0.4406779706478119,\n \"avg_line_length\": 18.83333396911621,\n \"blob_id\": \"99d0d9955da0c0454dffdc8b47e34b235f92a036\",\n \"content_id\": \"5dff70e872b27fb4fc862bd469c7b8302f780991\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 118,\n \"license_type\": \"no_license\",\n \"max_line_length\": 35,\n \"num_lines\": 6,\n \"path\": \"/알고리즘/온라인저지/2021/08/0822/달팽이는 올라가고 싶다.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"A, B, V = map(int, input().split())\\nif (V-B)%(A-B):\\n day = (V-B)//(A-B) + 1\\nelse:\\n day = (V-B)//(A-B)\\nprint(day)\"\n },\n {\n \"alpha_fraction\": 0.4656488597393036,\n \"alphanum_fraction\": 0.49618321657180786,\n \"avg_line_length\": 17.85714340209961,\n \"blob_id\": \"a4d8a7d0425bf41d1b4dab4e05b638f08a814997\",\n \"content_id\": \"d31bee524d636eb83c4d45382d134d78cb59e384\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 131,\n \"license_type\": \"no_license\",\n \"max_line_length\": 32,\n \"num_lines\": 7,\n \"path\": \"/알고리즘/온라인저지/2023/05/0514/악마의 제안.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"K, N = map(int, input().split())\\nresult = -1\\nif N != 1:\\n A, B = N*K, N-1\\n result = A//B\\n if A%B: result += 1\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.48695650696754456,\n \"alphanum_fraction\": 0.4956521689891815,\n \"avg_line_length\": 37.66666793823242,\n \"blob_id\": \"f65717f7346d74f0d215de30f95fa609bf014c73\",\n \"content_id\": \"0a0d7886d8cc34161109c11e0f6ddce4f11f7e69\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 115,\n \"license_type\": \"no_license\",\n \"max_line_length\": 47,\n \"num_lines\": 3,\n \"path\": \"/알고리즘/온라인저지/2023/01/0110/폰 노이만.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"for _ in range(int(input())):\\n N, D, A, B, F = map(float, input().split())\\n print(int(N), f'{D/(A+B)*F:.6f}')\"\n },\n {\n \"alpha_fraction\": 0.50971919298172,\n \"alphanum_fraction\": 0.5356371402740479,\n \"avg_line_length\": 32.07143020629883,\n \"blob_id\": \"e48be24025c536ebdceb261d16ff635c3a969686\",\n \"content_id\": \"6e922edcac4f86837ea7be48f87e3feff172e3e6\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 647,\n \"license_type\": \"no_license\",\n \"max_line_length\": 49,\n \"num_lines\": 14,\n \"path\": \"/알고리즘/온라인저지/2021/07/0731/3 6 9 게임의 왕이 되자.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"def three_six_nine(n):\\n n = str(n) # 입력받은 숫자를 str로 변환\\n tsn_list = \\\"369\\\" # 369를 확인하는 str값 설정\\n result = \\\"\\\" # 초기 공백 결과값\\n for num in n: # str로 바꿔준 n을 순회\\n if num in tsn_list: # n의 각 숫자가 3,6,9일때\\n result += \\\"X\\\" # 결과값에 박수 한 번\\n if result == \\\"\\\": # 순회 다 해도 박수가 없으면\\n result += n # 원본 숫자 출력\\n return result # 결과값 반환\\n\\nn = int(input()) # 숫자를 입력받고\\nfor i in range(1, n+1): # 1부터 입력값까지 반복\\n print(three_six_nine(i), sep = \\\"\\\") # 공백단위로 출력\\n\"\n },\n {\n \"alpha_fraction\": 0.4336734712123871,\n \"alphanum_fraction\": 0.4591836631298065,\n \"avg_line_length\": 23.625,\n \"blob_id\": \"6f55fdc4fa3f64482286104e6f5c8e29a6518397\",\n \"content_id\": \"6fca9a427475178a5820519b77c8d8817aa9f804\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 196,\n \"license_type\": \"no_license\",\n \"max_line_length\": 42,\n \"num_lines\": 8,\n \"path\": \"/알고리즘/온라인저지/2023/05/0516/Gauß.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"for i in range(int(input())):\\n N, M = map(int, input().split())\\n A = M-N+1\\n B = A//2\\n result = (N+M)*B\\n if A%2:\\n result += (N+M)//2\\n print(f'Scenario #{i+1}:\\\\n{result}\\\\n')\"\n },\n {\n \"alpha_fraction\": 0.529629647731781,\n \"alphanum_fraction\": 0.5666666626930237,\n \"avg_line_length\": 19.846153259277344,\n \"blob_id\": \"96c8e1747d340169bc1136820623445af8cba9a6\",\n \"content_id\": \"68595d9aeb4d10e64a30f224de3ef1fc6865ab91\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 270,\n \"license_type\": \"no_license\",\n \"max_line_length\": 35,\n \"num_lines\": 13,\n \"path\": \"/알고리즘/온라인저지/2022/06/0609/농구 경기.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"table = [0]*26\\nN = int(input())\\nfor n in range(N):\\n first = ord(input()[0]) - 97\\n table[first] += 1\\n# print(table)\\nresult = ''\\nfor i in range(len(table)):\\n if table[i] >= 5:\\n result = result + chr(i+97)\\nif not result:\\n result = 'PREDAJA'\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.5793871879577637,\n \"alphanum_fraction\": 0.5905292630195618,\n \"avg_line_length\": 17.947368621826172,\n \"blob_id\": \"6e7f56da0c750d5af0b5bca0a6c98c34e02af949\",\n \"content_id\": \"677b4a8a3a6eda7df600de055b12fa66c8aaf0b1\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 359,\n \"license_type\": \"no_license\",\n \"max_line_length\": 47,\n \"num_lines\": 19,\n \"path\": \"/알고리즘/온라인저지/2022/10/1009/트로피 진열.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from audioop import reverse\\nfrom re import A\\nimport sys\\n\\ninput = sys.stdin.readline\\n\\ndef check(arr):\\n result = 1\\n biggest = arr[0]\\n for a in arr:\\n if a>biggest:\\n biggest = a\\n result += 1\\n return result\\n\\nN = int(input().rstrip())\\narr = [int(input().rstrip()) for _ in range(N)]\\nprint(check(arr))\\nprint(check(arr[::-1]))\"\n },\n {\n \"alpha_fraction\": 0.4727272689342499,\n \"alphanum_fraction\": 0.5454545617103577,\n \"avg_line_length\": 17.66666603088379,\n \"blob_id\": \"3c76ccd668a06618fb744c0b812588f8680ba0ec\",\n \"content_id\": \"ebc7e8efc6274496dce58dcbf1c56a471c28a293\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 55,\n \"license_type\": \"no_license\",\n \"max_line_length\": 40,\n \"num_lines\": 3,\n \"path\": \"/알고리즘/온라인저지/2022/09/0925/악수.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"a=b=1\\nfor _ in [0]*int(input()):a,b=b,(a+b)%10\\nprint(a)\"\n },\n {\n \"alpha_fraction\": 0.48275861144065857,\n \"alphanum_fraction\": 0.5344827771186829,\n \"avg_line_length\": 18.5,\n \"blob_id\": \"ac158ef99ff55cce4aff99a3223a8eae61624491\",\n \"content_id\": \"bf295b928eeb3bd4627d3c55c86de34dab745a28\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 116,\n \"license_type\": \"no_license\",\n \"max_line_length\": 33,\n \"num_lines\": 6,\n \"path\": \"/알고리즘/온라인저지/2022/09/0913/직사각형을 만드는 방법.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = int(input())\\nresult = 0\\nfor i in range(1, int(N**0.5)+1):\\n tmp = N//i - (i-1)\\n result += tmp\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.4781849980354309,\n \"alphanum_fraction\": 0.5340313911437988,\n \"avg_line_length\": 29.210525512695312,\n \"blob_id\": \"a582a64625e08ef546c5a39c294549eadc67eec7\",\n \"content_id\": \"4ee4c1599337cd4e7bff1692e1ac1632418d564a\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 573,\n \"license_type\": \"no_license\",\n \"max_line_length\": 51,\n \"num_lines\": 19,\n \"path\": \"/알고리즘/온라인저지/2022/12/1209/Hawk eyes.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"def mix(order):\\n if order == 'A':\\n result[0], result[1] = result[1], result[0]\\n elif order == 'B':\\n result[0], result[2] = result[2], result[0]\\n elif order == 'C':\\n result[0], result[3] = result[3], result[0]\\n elif order == 'D':\\n result[2], result[1] = result[1], result[2]\\n elif order == 'E':\\n result[3], result[1] = result[1], result[3]\\n elif order == 'F':\\n result[2], result[3] = result[3], result[2]\\n\\nresult = [1, 0, 0, 2]\\nfor order in input():\\n mix(order)\\nprint(result.index(1)+1)\\nprint(result.index(2)+1)\"\n },\n {\n \"alpha_fraction\": 0.4952380955219269,\n \"alphanum_fraction\": 0.5047619342803955,\n \"avg_line_length\": 34.33333206176758,\n \"blob_id\": \"d13e07760ff14e0820d2b3e13f68136399c9f6d7\",\n \"content_id\": \"6f85bace3f0ad7ceb858c0e6dd546bb6f85db37e\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 105,\n \"license_type\": \"no_license\",\n \"max_line_length\": 59,\n \"num_lines\": 3,\n \"path\": \"/알고리즘/온라인저지/2023/01/0123/자기복제수.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"for _ in range(int(input())):\\n N = input()\\n print('YES' if N == str(int(N)**2)[-len(N):] else 'NO')\"\n },\n {\n \"alpha_fraction\": 0.5040650367736816,\n \"alphanum_fraction\": 0.5203251838684082,\n \"avg_line_length\": 16.714284896850586,\n \"blob_id\": \"d95b7e68328c000663165f74331bdbc84165d25d\",\n \"content_id\": \"f4bedaf6d33277c377491ee45a430952c15dc240\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 123,\n \"license_type\": \"no_license\",\n \"max_line_length\": 24,\n \"num_lines\": 7,\n \"path\": \"/알고리즘/온라인저지/2022/08/0828/사장님 도박은 재미로 하셔야 합니다.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"result = 0\\nwhile True:\\n money = int(input())\\n if money == -1:\\n print(result)\\n break\\n result += money\"\n },\n {\n \"alpha_fraction\": 0.38461539149284363,\n \"alphanum_fraction\": 0.39835163950920105,\n \"avg_line_length\": 23.266666412353516,\n \"blob_id\": \"59233dc2edb549cf11a3b9d7ff72d384abd73fbd\",\n \"content_id\": \"42df7147547984d6c79ef895e8e339399ad1d12e\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 364,\n \"license_type\": \"no_license\",\n \"max_line_length\": 37,\n \"num_lines\": 15,\n \"path\": \"/알고리즘/온라인저지/2022/09/0903/쌍의 합.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"for _ in range(int(input())):\\n N = int(input())\\n result = []\\n for n in range(1, (N//2)+1):\\n A, B = n, N-n\\n if A != B:\\n result.append((A, B))\\n print(f'Pairs for {N}: ', end='')\\n cnt = 0\\n for r in result:\\n print(*r, end='')\\n cnt += 1\\n if cnt != len(result):\\n print(', ', end='')\\n print()\\n\"\n },\n {\n \"alpha_fraction\": 0.37823835015296936,\n \"alphanum_fraction\": 0.4715026021003723,\n \"avg_line_length\": 16.18181800842285,\n \"blob_id\": \"238202db72b4d41a4c4798e5e5990080d3fcea72\",\n \"content_id\": \"e9271e35f72d9f4f9ef706e9c0eaed0201a0c034\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 225,\n \"license_type\": \"no_license\",\n \"max_line_length\": 60,\n \"num_lines\": 11,\n \"path\": \"/알고리즘/SWEA/LEARN/Course/1. Programming Beginner/파이썬 프로그래밍 기초(2)/3차시 2. 자료구조 – 리스트, 튜플 - 연습문제 1.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"scores = [(90, 80), (85, 75), (90, 100)]\\n\\ns = 0\\navg = 0\\ni = 0\\n\\nfor score in scores:\\n i += 1\\n s = sum(score)\\n avg = s/2\\n print('{}번 학생의 총점은 {}점이고, 평균은 {}입니다.'.format(i, s, avg))\\n \"\n },\n {\n \"alpha_fraction\": 0.41265398263931274,\n \"alphanum_fraction\": 0.4440089464187622,\n \"avg_line_length\": 23.81944465637207,\n \"blob_id\": \"d741dd72442868550a9ea209d9a53dc92f11e34e\",\n \"content_id\": \"0ffdf49d206be3ec3d03d3a838fa02ee9223f007\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 2162,\n \"license_type\": \"no_license\",\n \"max_line_length\": 66,\n \"num_lines\": 72,\n \"path\": \"/알고리즘/온라인저지/2022/07/0709/섬의 개수.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"\\\"\\\"\\\"\\n배열을 탐색하다가 섬을 발견하면\\n 섬의 개수 ++\\n 섬을 바다로 만든다 (1 -> 0) # BFS (DFS로 하는데 메모리초과가 계속 남 ㅜㅜ)\\n 발견한 섬의 개수를 출력\\n\\\"\\\"\\\"\\nfrom collections import deque # BFS용 double ended queue\\n\\n\\ndef bfs(y, x): # 섬을 바다로 만드는 BFS함수\\n Q.append((y, x))\\n while Q:\\n y, x = Q.popleft()\\n if arr[y][x] == 0:\\n continue\\n arr[y][x] = 0\\n for i in range(8):\\n ny = y+dy[i]\\n nx = x+dx[i]\\n if 0<=ny<H and 0<=nx<W and arr[ny][nx]:\\n Q.append((ny, nx))\\n\\n\\ndy = [-1, 1, 0, 0, 1, 1, -1, -1] # 대각선 포함한 8방향 델타이동\\ndx = [0, 0, -1, 1, 1, -1, 1, -1]\\nwhile True:\\n W, H = map(int, input().split())\\n if W == 0 and H == 0: # 테스트케이스 입력 종료조건\\n break\\n arr = [list(map(int, input().split())) for _ in range(H)] # 지도\\n result = 0 # 섬의 개수\\n Q = deque()\\n for h in range(H):\\n for w in range(W):\\n if arr[h][w]: # 섬을 발견하면\\n bfs(h, w) # 섬을 바다로 만들기\\n result += 1 # 섬의 개수 ++\\n print(result) # 섬의 개수 출력\\n\\n\\n# 아래는 재귀함수를 활용한 DFS로 풀었는데\\n# 메모리초과를 피하지 못했습니다ㅜㅜ\\n# 재귀를 계속 돌면서 함수 내 메모리를 전부 사용한 것 같은데...\\n# import sys\\n# sys.setrecursionlimit(10**9)\\n\\n\\n# def dfs(y, x): # 섬을 바다로 만들어 주면서 섬 개수 세기\\n# if arr[y][x] == 0:\\n# return\\n# arr[y][x] = 0\\n# for i in range(8):\\n# ny = y+dy[i]\\n# nx = x+dx[i]\\n# if 0<=ny<H and 0<=nx<W and arr[ny][nx]:\\n# dfs(ny, nx)\\n\\n\\n# dy = [-1, 1, 0, 0, 1, 1, -1, -1]\\n# dx = [0, 0, -1, 1, 1, -1, 1, -1]\\n# while True:\\n# W, H = map(int, input().split())\\n# if W == 0 and H == 0:\\n# break\\n# arr = [list(map(int, input().split())) for _ in range(H)]\\n# result = 0\\n# for h in range(H):\\n# for w in range(W):\\n# if arr[h][w]:\\n# dfs(h, w)\\n# result += 1\\n# print(result)\"\n },\n {\n \"alpha_fraction\": 0.6880733966827393,\n \"alphanum_fraction\": 0.6926605701446533,\n \"avg_line_length\": 23.22222137451172,\n \"blob_id\": \"47bb257df616eea53fa1b0c255d8eb2e401a4624\",\n \"content_id\": \"eef34007a192acd17c7e1d1fd6d1446f3336b7fd\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 218,\n \"license_type\": \"no_license\",\n \"max_line_length\": 54,\n \"num_lines\": 9,\n \"path\": \"/알고리즘/온라인저지/2021/08/0829/줄 세우기.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\nstudent_count = int(sys.stdin.readline())\\nnumbers = list(map(int, sys.stdin.readline().split()))\\nresult = []\\nfor i in range(len(numbers)):\\n result.insert(numbers[i], i+1)\\nresult.reverse()\\nprint(*result)\\n\"\n },\n {\n \"alpha_fraction\": 0.610859751701355,\n \"alphanum_fraction\": 0.6199095249176025,\n \"avg_line_length\": 13.800000190734863,\n \"blob_id\": \"a1b88c0bd5eb6f171e0f1a722e4580becb9a96df\",\n \"content_id\": \"36e164cbf19f52bc2e011cd5c5bf8818164c3e4b\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 221,\n \"license_type\": \"no_license\",\n \"max_line_length\": 46,\n \"num_lines\": 15,\n \"path\": \"/알고리즘/온라인저지/2021/10/1011/등수 매기기.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = int(input())\\n\\nstudents = []\\n\\nfor n in range(N):\\n students.append(int(input()))\\n\\nstudents.sort()\\n\\ngrades = list(range(1, N+1))\\n\\nfor i in range(N):\\n students[i] = abs(students[i] - grades[i])\\n\\nprint(sum(students))\"\n },\n {\n \"alpha_fraction\": 0.42553192377090454,\n \"alphanum_fraction\": 0.44964540004730225,\n \"avg_line_length\": 22.53333282470703,\n \"blob_id\": \"e673c66160ac51884acdad2ec216ce05c088c4fe\",\n \"content_id\": \"888c4cccd1a6c17a27069030cc66f0e164909e9d\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 853,\n \"license_type\": \"no_license\",\n \"max_line_length\": 71,\n \"num_lines\": 30,\n \"path\": \"/알고리즘/온라인저지/2021/12/1230/소수.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = int(input())\\nM = int(input())\\n\\nn = M # 소수를 찾을 범위\\na = [False,False] + [True]*(n-1) # 0 ~ n 까지의 숫자 리스트\\nprimes=[] # 소수 집합\\nfor i in range(2,n+1): # 2 ~ n까지 반복\\n if a[i]: # 2부터 시작, 해당 숫자가 지워지지 않고 남아있는 소수라면 \\n primes.append(i) # 소수 리스트에 추가\\n for j in range(2*i, n+1, i): # 해당 소수의 배수들을 \\n a[j] = False # 리스트에서 전부 False로 만들기\\n\\nresult1 = 0\\nresult2 = 0\\n\\nfind_min = False\\n\\nfor p in primes:\\n if p >= N and not find_min:\\n find_min = True\\n result2 = p\\n \\n if find_min:\\n result1 += p\\n \\nif find_min:\\n print(result1)\\n print(result2)\\nelse:\\n print(-1)\"\n },\n {\n \"alpha_fraction\": 0.5068492889404297,\n \"alphanum_fraction\": 0.5479452013969421,\n \"avg_line_length\": 23.44444465637207,\n \"blob_id\": \"efa0b162be31747c5eb691fa0043689dd2f81ea9\",\n \"content_id\": \"9c6111bbca13f81616f44bc003140ae2da84bd9a\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 219,\n \"license_type\": \"no_license\",\n \"max_line_length\": 47,\n \"num_lines\": 9,\n \"path\": \"/알고리즘/온라인저지/2022/04/0411/일우는 야바위.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N, X, K = map(int, input().split())\\ncups = [0] * N\\ncups[X-1] = 1\\n# print(cups)\\nfor k in range(K):\\n A, B = map(int, input().split())\\n cups[A-1], cups[B-1] = cups[B-1], cups[A-1]\\n# print(cups)\\nprint(cups.index(1)+1)\"\n },\n {\n \"alpha_fraction\": 0.36966824531555176,\n \"alphanum_fraction\": 0.3909952640533447,\n \"avg_line_length\": 14.666666984558105,\n \"blob_id\": \"cbff5d09413cda50063a553d3e903c920f8c95a8\",\n \"content_id\": \"f5d4f196e220852b6acac9e5b8f7eac537e95b46\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 422,\n \"license_type\": \"no_license\",\n \"max_line_length\": 31,\n \"num_lines\": 27,\n \"path\": \"/알고리즘/온라인저지/2021/09/0910/Router.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\ndef input():\\n return sys.stdin.readline()\\n\\nN = int(input())\\nq = [0] * N\\np = 0\\nwhile True:\\n a = int(input())\\n if a == -1:\\n break\\n elif a == 0:\\n q.pop(0)\\n q.append(0)\\n p -= 1\\n else:\\n if q[-1]:\\n continue\\n else:\\n q[p] = a\\n p += 1\\nif sum(q):\\n for i in q:\\n if i:\\n print(i, end=' ')\\nelse:\\n print('empty')\"\n },\n {\n \"alpha_fraction\": 0.3734939694404602,\n \"alphanum_fraction\": 0.46987950801849365,\n \"avg_line_length\": 15.800000190734863,\n \"blob_id\": \"abf22fbc7546b5dce3b3c7c12c1c33d646b445a7\",\n \"content_id\": \"56fdd128b42e70b803ad84da59d56a0183d09851\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 83,\n \"license_type\": \"no_license\",\n \"max_line_length\": 20,\n \"num_lines\": 5,\n \"path\": \"/알고리즘/온라인저지/2021/08/0822/나머지.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"d = [0] * 42\\nfor _ in range(10):\\n n = int(input())\\n d[n%42] = 1\\nprint(sum(d))\"\n },\n {\n \"alpha_fraction\": 0.6906779408454895,\n \"alphanum_fraction\": 0.6991525292396545,\n \"avg_line_length\": 20.545454025268555,\n \"blob_id\": \"1678dd85d89e4ab51acaca81b93f39ff5697ae19\",\n \"content_id\": \"8a91f777956e088fe72d41e4e5867696bbdf25bd\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 236,\n \"license_type\": \"no_license\",\n \"max_line_length\": 67,\n \"num_lines\": 11,\n \"path\": \"/알고리즘/온라인저지/2022/11/1117/나는 친구가 적다 (Small).py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\n\\nword = input().rstrip()\\nkeyword = input().rstrip()\\ntmp = ''\\nfor w in word:\\n if w in 'abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ':\\n tmp = tmp+w\\nprint(1 if keyword in tmp else 0)\"\n },\n {\n \"alpha_fraction\": 0.4435215890407562,\n \"alphanum_fraction\": 0.5033222436904907,\n \"avg_line_length\": 21.296297073364258,\n \"blob_id\": \"f253cc01c49cec93efa65ca86cee73b567a4d9eb\",\n \"content_id\": \"e827bfd15aa21396a3e6a19e9826297b9f03598f\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 834,\n \"license_type\": \"no_license\",\n \"max_line_length\": 55,\n \"num_lines\": 27,\n \"path\": \"/알고리즘/온라인저지/2021/10/1016/1로 만들기.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from collections import deque\\n\\nN = int(input())\\n\\nif N == 1: # 입력값이 1이면 0을 곧바로 반환합니다\\n print(0)\\n exit()\\n\\n# 1에서부터 거꾸로 탐색합니다\\nq = deque()\\nq.append((1, 0)) # 시작하는 1, 연산횟수 0부터 시작\\n\\ncheck = set() # 중복연산 방지\\n\\nwhile q:\\n a = q.popleft()\\n\\n for i in [a[0]*3, a[0]*2, a[0]+1]: # 1에서 출발하기 때문에\\n # 연산들을 거꾸로 실행\\n if i == N: # N을 찾으면\\n print(a[1]+1) # 연산횟수 1회 더하여 출력\\n exit() # 바로 코드를 종료\\n\\n if i not in check and 1 <= i <= 1000000: # 가지치기\\n # N은 1000000을 넘지 않는 자연수입니다\\n check.add(i) # 범위를 만족하면 check에 추가\\n q.append((i, a[1]+1)) # BFS 대기열에 추가\\n\"\n },\n {\n \"alpha_fraction\": 0.5248869061470032,\n \"alphanum_fraction\": 0.5429864525794983,\n \"avg_line_length\": 19.18181800842285,\n \"blob_id\": \"2a1de6f8c097c6714747f8e0678e0d1c898d5695\",\n \"content_id\": \"00fb7bbec6973bed5f12409192aa35717c360b42\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 221,\n \"license_type\": \"no_license\",\n \"max_line_length\": 41,\n \"num_lines\": 11,\n \"path\": \"/알고리즘/온라인저지/2022/07/0730/2+1 세일.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = int(input())\\nP = [] # price\\nfor n in range(N): P.append(int(input()))\\nP.sort(reverse=True)\\nresult = 0\\nfor i in range(0, N, 3):\\n try:\\n result += sum(P[i:i+2])\\n except:\\n result += P[i:]\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.6243094205856323,\n \"alphanum_fraction\": 0.6464088559150696,\n \"avg_line_length\": 17.200000762939453,\n \"blob_id\": \"6ffa92dcb21acea0b85b62c5f8d82324f598fe8e\",\n \"content_id\": \"49a1f55543b7824778e1c831d4ecee780df33ecf\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 181,\n \"license_type\": \"no_license\",\n \"max_line_length\": 42,\n \"num_lines\": 10,\n \"path\": \"/알고리즘/온라인저지/2022/02/0222/과목선택.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"science = [int(input()) for _ in range(4)]\\nsocial = [int(input()) for _ in range(2)]\\n\\nscience.sort(reverse=True)\\n\\nresult = 0\\n\\nresult += sum(science[:3]) + max(social)\\n\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.44897958636283875,\n \"alphanum_fraction\": 0.47755101323127747,\n \"avg_line_length\": 16.5,\n \"blob_id\": \"2320c53a56dae959300b621d051ecf26fc1b0564\",\n \"content_id\": \"bfd1c879c6c46531fc4137f9119a5cd8f1e761d5\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 245,\n \"license_type\": \"no_license\",\n \"max_line_length\": 42,\n \"num_lines\": 14,\n \"path\": \"/알고리즘/온라인저지/2022/02/0207/최댓값.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"maxx = 0\\nmaxi = 0\\nmaxj = 0\\n\\nfor i in range(9):\\n line = list(map(int, input().split()))\\n \\n for j in range(9):\\n if line[j] > maxx:\\n maxx = line[j] \\n maxi, maxj = i, j\\n\\nprint(maxx)\\nprint(maxi+1, maxj+1)\\n\"\n },\n {\n \"alpha_fraction\": 0.5443925261497498,\n \"alphanum_fraction\": 0.5630841255187988,\n \"avg_line_length\": 18.5,\n \"blob_id\": \"7251d55610e6ac81de3323a94b8e9e71609b7b9d\",\n \"content_id\": \"23c599716e0e3a4cbef555028c2e8e7c810a33b6\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 428,\n \"license_type\": \"no_license\",\n \"max_line_length\": 41,\n \"num_lines\": 22,\n \"path\": \"/알고리즘/온라인저지/2022/11/1104/찍기.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\n\\nstudent = [\\n 'ABCABCABCABC',\\n 'BABCBABCBABC',\\n 'CCAABBCCAABB',\\n]\\nN = int(input().rstrip())\\nanswer = input().rstrip()\\nresult = [0, 0, 0]\\nfor i in range(N):\\n for j in range(3):\\n if answer[i] == student[j][i%12]:\\n result[j] += 1\\nIDs = ['Adrian', 'Bruno', 'Goran']\\nmaxx = max(result)\\nprint(maxx)\\nfor i in range(3):\\n if result[i] == maxx:\\n print(IDs[i])\"\n },\n {\n \"alpha_fraction\": 0.5270935893058777,\n \"alphanum_fraction\": 0.5714285969734192,\n \"avg_line_length\": 28.14285659790039,\n \"blob_id\": \"30a25931616b2ef6937dfe891deaea72cdaa0fb8\",\n \"content_id\": \"a4114167277cdbab29ad9692a1ccb0f1650882e9\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 203,\n \"license_type\": \"no_license\",\n \"max_line_length\": 41,\n \"num_lines\": 7,\n \"path\": \"/알고리즘/온라인저지/2022/11/1129/이교수님의 시험.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = int(input())\\ncorrect = [1, 2, 3, 4, 5]\\nfor answer in range(1, N+1):\\n arr = list(map(int, input().split()))\\n if arr[:5] != correct: continue\\n if arr[5:] != correct: continue\\n print(answer)\"\n },\n {\n \"alpha_fraction\": 0.4822694957256317,\n \"alphanum_fraction\": 0.4893617033958435,\n \"avg_line_length\": 19.285715103149414,\n \"blob_id\": \"b52f1a55c23402cab543b69b2946c3f2ac303f27\",\n \"content_id\": \"53291c653d7f2677189c43a7d0753c415b3cea22\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 141,\n \"license_type\": \"no_license\",\n \"max_line_length\": 32,\n \"num_lines\": 7,\n \"path\": \"/알고리즘/온라인저지/2022/09/0903/최소공배수.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"def gcd(a, b):\\n while b > 0: a, b = b, a%b\\n return a\\n\\nA, B = map(int, input().split())\\nGCD = gcd(A, B)\\nprint(GCD * (A//GCD) * (B//GCD))\"\n },\n {\n \"alpha_fraction\": 0.607594907283783,\n \"alphanum_fraction\": 0.607594907283783,\n \"avg_line_length\": 21.714284896850586,\n \"blob_id\": \"ccd944d4e831fa17d2728e36fc20227465893322\",\n \"content_id\": \"fff69a3e69e485f7b533b783c534d9f107c50694\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 270,\n \"license_type\": \"no_license\",\n \"max_line_length\": 43,\n \"num_lines\": 7,\n \"path\": \"/알고리즘/온라인저지/2021/07/0730/[기초-산술연산] 정수 2개 입력받아 거듭제곱 계산하기.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# 두 변수를 입력받아서 각각 저장한다\\n# .split()이 하는 일이, 결국 input()받은 건 하나의 str인데\\n# 그걸 공백으로 쪼개서 각각 저장하는 기능을 한거다\\na, b = input().split()\\n# **는 거듭제곱\\nc = int(a)**int(b) \\nprint(c)\"\n },\n {\n \"alpha_fraction\": 0.3464052379131317,\n \"alphanum_fraction\": 0.379084974527359,\n \"avg_line_length\": 17.399999618530273,\n \"blob_id\": \"28bc9eb73169acef4c8c9c1818213a68de320365\",\n \"content_id\": \"280983134c50c67bcad0e8a608eafb2e11a3e8e6\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 459,\n \"license_type\": \"no_license\",\n \"max_line_length\": 36,\n \"num_lines\": 25,\n \"path\": \"/알고리즘/온라인저지/2022/02/0205/문자열 분석.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"upper = 'ABCDEFGHIJKLMNOPQRSTUVWXYZ'\\nlower = 'abcdefghijklmnopqrstuvwxyz'\\nnum = '0123456789'\\n\\n\\nwhile True:\\n try:\\n a = b = c = d = 0\\n \\n sen = input()\\n \\n for s in sen:\\n if s in upper:\\n b += 1\\n elif s in lower:\\n a += 1\\n elif s in num:\\n c += 1\\n elif s == ' ':\\n d += 1\\n\\n print(a, b, c, d)\\n\\n except:\\n break\"\n },\n {\n \"alpha_fraction\": 0.589353621006012,\n \"alphanum_fraction\": 0.5969581604003906,\n \"avg_line_length\": 21,\n \"blob_id\": \"a99a7269d47c7ddda4b4fe485464bebd81571fd5\",\n \"content_id\": \"d2f992a14ec8ec0cc55ed229b128dfa6bac8492e\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 263,\n \"license_type\": \"no_license\",\n \"max_line_length\": 38,\n \"num_lines\": 12,\n \"path\": \"/알고리즘/온라인저지/2022/09/0923/최대 힙.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\nfrom heapq import heappush, heappop\\n\\ninput = sys.stdin.readline\\n\\nHQ = []\\nfor _ in range(int(input().rstrip())):\\n num = int(input().rstrip())\\n if num: heappush(HQ, (-num, num))\\n else: \\n if HQ: print(heappop(HQ)[1])\\n else: print(0)\"\n },\n {\n \"alpha_fraction\": 0.5037453174591064,\n \"alphanum_fraction\": 0.5599250793457031,\n \"avg_line_length\": 27.891891479492188,\n \"blob_id\": \"a5fa93ea7e5093b470e1054bbaed2db7d3a1dbe6\",\n \"content_id\": \"8ac4b3475278057bf810ea88ea1b01a2dfe29a4b\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1720,\n \"license_type\": \"no_license\",\n \"max_line_length\": 72,\n \"num_lines\": 37,\n \"path\": \"/알고리즘/온라인저지/2021/08/0807/셀프 넘버.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"\\\"\\\"\\\"\\n함수 d(75) = 75 + 7 + 5 = 75 + 12 + 87\\n87의 생성자(이전항) = 75\\n생성자(이전항)가 없는 숫자 = 셀프 넘버\\n셀프넘버 = 자연수 - 셀프넘버가 아닌 수\\n셀프넘버가 아닌 수 \\n = 생성자가 있는 수\\n = N까지 함수d 돌려서 나온 값들\\n셀프넘버가 아닌 수 리스트를 만들고 \\nN까지와, 셀프넘버아닌수 리스트를 이중순회 하면서\\n리스트안에 없으면 출력\\n\\\"\\\"\\\"\\n\\nN = 10000 # 순회 범위\\n\\ndef Kaprekar(n): # n본인과 각 자리수들을 더하는 함수\\n # Kaprekar를 통해 만들어진 값은 생성자가 존재하는 \\\"셀프넘버가 아닌 숫자\\\"\\n # 10의 자리 : n + n%10 + (n//10)%10\\n # 100의 자리 : n + n%10 + (n//10)%10 + (n//100)%10\\n def Kapre(n): # 각 자릿수를 더하는 재귀함수\\n result = 0 # 결과값 초기화\\n if n < 10: # 한 자리수 일때\\n result += n # 결과값에 저장\\n else: # 두 자리 이상일 때\\n return n%10 + Kapre(n//10) # 1의 자리수 값과 재귀호출 반환\\n return result # 각 자리수를 더한 값을 반환\\n return n + Kapre(n) # 처음 input값 n과, 각자리 숫자들을 더한 값을 반환\\n\\nnot_self_numbers = [] # 셀프넘버가 아닌 수 리스트 초기화\\nfor i in range(N + 1): # 10000보다 작거나 \\\"같은\\\" 셀프넘버가 아닌 수\\n not_self_numbers.append(Kaprekar(i)) # 함수를 통과한 값은 셀프넘버가 아니므로 리스트에 추가\\n\\nfor i in range(1, N + 1): # 1부터 N까지 순회하면서 \\n if i in not_self_numbers: # 순회중인 i가 셀프넘버가 아닌 값이면\\n continue # 지나가고\\n else: # 셀프넘버이면\\n print(i) # 출력\"\n },\n {\n \"alpha_fraction\": 0.5553505420684814,\n \"alphanum_fraction\": 0.5664206743240356,\n \"avg_line_length\": 21.625,\n \"blob_id\": \"6866b7ac06b560a1c19e07e04b50482992001c05\",\n \"content_id\": \"b2f657285aea0b24f2f8816b1b2e43ca6829ca6e\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 542,\n \"license_type\": \"no_license\",\n \"max_line_length\": 38,\n \"num_lines\": 24,\n \"path\": \"/알고리즘/온라인저지/2022/04/0413/홀짝 칵테일.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from itertools import combinations\\n\\nnums = list(map(int, input().split()))\\nnums.sort(reverse=True)\\nodd_drinks = []\\neven_drinks = []\\nfor i in range(1, len(nums)+1):\\n tmp = list(combinations(nums, i))\\n # print(tmp)\\n for t in tmp:\\n a = 1\\n for j in t:\\n # print(j)\\n a *= j\\n if a%2:\\n odd_drinks.append(a)\\n else:\\n even_drinks.append(a)\\nodd_drinks.sort(reverse=True)\\neven_drinks.sort(reverse=True)\\nif odd_drinks:\\n print(odd_drinks[0])\\nelse:\\n print(even_drinks[0])\"\n },\n {\n \"alpha_fraction\": 0.4548022747039795,\n \"alphanum_fraction\": 0.5310734510421753,\n \"avg_line_length\": 19.882352828979492,\n \"blob_id\": \"826f2e0b1f0d7be685d16d669370a2121c3fb13b\",\n \"content_id\": \"17ddaa4e5886a233da9c6e5d04d7ca4c2d087e0e\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 388,\n \"license_type\": \"no_license\",\n \"max_line_length\": 54,\n \"num_lines\": 17,\n \"path\": \"/알고리즘/온라인저지/2022/08/0817/터렛.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import math\\n\\nfor t in range(int(input())):\\n x1, y1, r1, x2, y2, r2 = map(int, input().split())\\n D = math.sqrt((x1-x2)**2 + (y1-y2)**2) # distance\\n result = 0\\n if D == 0 and r1 == r2: result = -1\\n elif D == abs(r1-r2) or D == r1+r2: result = 1\\n elif abs(r1-r2) < D < r1+r2: result = 2\\n print(result)\\n\\n\\\"\\\"\\\"\\n일치\\n내접or외접\\n두 점에서 접함\\n접점이 없음\\n\\\"\\\"\\\"\"\n },\n {\n \"alpha_fraction\": 0.4150943458080292,\n \"alphanum_fraction\": 0.5408805012702942,\n \"avg_line_length\": 15,\n \"blob_id\": \"4db976a06b8552e9211984575f2439dd85eefb38\",\n \"content_id\": \"339afa166635ef03f3067fe8809b8fffa294d297\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 159,\n \"license_type\": \"no_license\",\n \"max_line_length\": 36,\n \"num_lines\": 10,\n \"path\": \"/알고리즘/SWEA/LEARN/Course/1. Programming Beginner/파이썬 프로그래밍 기초(2)/23차시 2. 자료구조 – 리스트, 튜플 - 연습문제 25.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"arr = [12, 24, 35, 70, 88, 120, 155]\\n\\nresult = []\\n\\nfor i in range(len(arr)):\\n if i+1 in (1, 5, 6):\\n continue\\n result.append(arr[i])\\n\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.3530927896499634,\n \"alphanum_fraction\": 0.3814432919025421,\n \"avg_line_length\": 17.5238094329834,\n \"blob_id\": \"e2db528c1480c4016cc9246fe3ea7f95a803c4f9\",\n \"content_id\": \"9ff41b953fd1ab9019498f67abbb1722e07fe3aa\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 388,\n \"license_type\": \"no_license\",\n \"max_line_length\": 59,\n \"num_lines\": 21,\n \"path\": \"/알고리즘/온라인저지/2021/08/0828/크로아티아 알파벳.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ncroatia = ['c=', 'c-', 'dz=', 'd-', 'lj', 'nj', 's=', 'z=']\\n\\nword = sys.stdin.readline()\\ni = 0\\ncnt = 0\\nwhile i < len(word)-1:\\n try:\\n if word[i:i+2] in croatia:\\n cnt += 1\\n i += 2\\n elif word[i:i+3] in croatia:\\n cnt += 1\\n i += 3\\n else:\\n cnt += 1\\n i += 1\\n except:\\n pass\\nprint(cnt)\"\n },\n {\n \"alpha_fraction\": 0.43718594312667847,\n \"alphanum_fraction\": 0.46063652634620667,\n \"avg_line_length\": 21.148147583007812,\n \"blob_id\": \"54edaa97c63bca5054a0217098d040de1eab138d\",\n \"content_id\": \"713cf37b692aa3b7f8e51735aa999e7a49bf450a\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 791,\n \"license_type\": \"no_license\",\n \"max_line_length\": 45,\n \"num_lines\": 27,\n \"path\": \"/알고리즘/온라인저지/2021/10/1016/로또.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"def dfs(x, cnt):\\n if cnt == 6: # 고른 숫자가 6개면\\n for i in range(k): # 고른 숫자들을 전체 조회할 것\\n if visited[i]: # 고른 숫자가 있으면\\n print(tmp[i], end=' ') # 출력\\n print() # 줄바꿈\\n return # 해당 재귀 종료\\n \\n for i in range(x, k): # 숫자를 하나씩 선택할건데\\n visited[i] = 1 # 해당 숫자 선택\\n dfs(i+1, cnt+1) # 다음 숫자 선택하러\\n visited[i] = 0 # DFS\\n # 갔다가 찍고 되돌아오는 부분\\n\\nwhile True:\\n tmp = list(map(int, input().split()))\\n \\n if tmp[0] == 0:\\n break\\n\\n k = tmp.pop(0)\\n\\n visited = [0] * k\\n\\n dfs(0, 0) # 0번째숫자부터, 고른숫자 0개부터\\n\\n print() # 매 케이스마다 줄바꿈\"\n },\n {\n \"alpha_fraction\": 0.6242774724960327,\n \"alphanum_fraction\": 0.647398829460144,\n \"avg_line_length\": 25,\n \"blob_id\": \"5d02de840e1810bee1bc8859696aef301538ca82\",\n \"content_id\": \"8153b9946e9f4cc9719b256788318b07a3c23787\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 519,\n \"license_type\": \"no_license\",\n \"max_line_length\": 68,\n \"num_lines\": 20,\n \"path\": \"/알고리즘/온라인저지/2022/09/0923/주유소.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\n\\nN = int(input().rstrip())\\ndistances = list(map(int, input().rstrip().split()))\\nfuels = list(map(int, input().rstrip().split()))\\nrefuel = []\\nfuel_min = int(1e9)\\nfor i in range(len(fuels)-1):\\n if fuels[i] < fuel_min:\\n refuel.append(i)\\n fuel_min = min(fuel_min, fuels[i])\\nrefuel.append(len(fuels)-1)\\nresult = 0\\nfor i in range(len(refuel)-1):\\n result += sum(distances[refuel[i]:refuel[i+1]])*fuels[refuel[i]]\\nprint(result)\\n\\n# https://www.acmicpc.net/problem/13305\"\n },\n {\n \"alpha_fraction\": 0.5873016119003296,\n \"alphanum_fraction\": 0.60317462682724,\n \"avg_line_length\": 31,\n \"blob_id\": \"6c9f1ec9b1179afb2db22d83dee28f8b321b9179\",\n \"content_id\": \"669aa37d9cdac846ad1d6eb75a09f87d863db0ae\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 63,\n \"license_type\": \"no_license\",\n \"max_line_length\": 48,\n \"num_lines\": 2,\n \"path\": \"/알고리즘/온라인저지/2022/12/1216/팰린드롬.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"word = input()\\nprint('true' if word == word[::-1] else 'false')\"\n },\n {\n \"alpha_fraction\": 0.375342458486557,\n \"alphanum_fraction\": 0.40547946095466614,\n \"avg_line_length\": 11.620689392089844,\n \"blob_id\": \"f490660458e0370fec87bcbf961d418b46b51017\",\n \"content_id\": \"e15b2614de980a1cc5eceb4912d06050d4cf1742\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 365,\n \"license_type\": \"no_license\",\n \"max_line_length\": 29,\n \"num_lines\": 29,\n \"path\": \"/알고리즘/온라인저지/2022/02/0202/완전제곱수.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"M = 0\\nN = 0\\n\\nfor i in range(2):\\n if i == 0:\\n M = int(input())\\n elif i == 1:\\n N = int(input())\\n\\ni = 0\\nminn = 0\\nsumm = 0\\n\\nwhile True:\\n i += 1\\n pow = i ** 2\\n if pow > N:\\n break\\n\\n if pow >= M and pow <= N:\\n if not minn:\\n minn = pow\\n \\n summ += pow\\n\\nif minn:\\n print(summ, minn)\\nelse:\\n print(-1)\"\n },\n {\n \"alpha_fraction\": 0.5176470875740051,\n \"alphanum_fraction\": 0.6000000238418579,\n \"avg_line_length\": 27.44444465637207,\n \"blob_id\": \"aa0168d82441c37bb6f8fabef8dc0b5fb7d9b688\",\n \"content_id\": \"7382192a602227f3eecf0e2f673d6ea44beb7f7c\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 255,\n \"license_type\": \"no_license\",\n \"max_line_length\": 45,\n \"num_lines\": 9,\n \"path\": \"/알고리즘/온라인저지/2023/03/0320/출석 이벤트.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = int(input())\\nP = int(input())\\nresult = P\\nif N >= 5: result = min(result, P-500)\\nif N >= 10: result = min(result, int(P*0.9))\\nif N >= 15: result = min(result, P-2000)\\nif N >= 20: result = min(result, int(P*0.75))\\nif result < 0: result = 0\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.3758741319179535,\n \"alphanum_fraction\": 0.3916083872318268,\n \"avg_line_length\": 25,\n \"blob_id\": \"7e78d2d3721326c4b6eeb84f3c425d2935b33d06\",\n \"content_id\": \"7a1bcbed171434aca047eb05209df4a41a0aeefd\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 696,\n \"license_type\": \"no_license\",\n \"max_line_length\": 43,\n \"num_lines\": 22,\n \"path\": \"/알고리즘/온라인저지/2022/01/0122/베르트랑 공준.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"while True:\\n N = int(input())\\n if N == 0: # 종료 조건\\n break\\n \\n n = 2 * N # 2n까지 소수를 구할 것\\n\\n # 에라토스테네스의 체\\n a = [False,False] + [True]*(n-1)\\n primes = [] \\n for i in range(2,n+1): \\n if a[i]: \\n primes.append(i) \\n for j in range(2*i, n+1, i): \\n a[j] = False \\n\\n # 2n까지 구한 소수들을 순회하다가\\n for i in range(len(primes)):\\n if primes[i] > N: # n보다 커지는 구간이 나오면\\n # 소수 전체 길이에서 구간시작 인덱스 빼기\\n print(len(primes)-i)\\n break\\n\"\n },\n {\n \"alpha_fraction\": 0.5144927501678467,\n \"alphanum_fraction\": 0.5362318754196167,\n \"avg_line_length\": 22.16666603088379,\n \"blob_id\": \"ce3b70fb30164523498f445735fbf9deef507826\",\n \"content_id\": \"c217edc639b1569b71d6be5692bdbd88a76ee996\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 246,\n \"license_type\": \"no_license\",\n \"max_line_length\": 34,\n \"num_lines\": 6,\n \"path\": \"/알고리즘/온라인저지/2021/07/0730/[기초-비트시프트연산] 정수 1개 입력받아 2배 곱해 출력하기.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"n = int(input())\\n# 숫자를 비트단위로 밀어버리는 << >>\\n# << : 숫자는 2진수이고 왼쪽으로 한 칸 밀면 값이 두배\\n# >> : 오른쪽으로 한 칸 밀면 값이 반\\n# <<로 n만큼 밀어주면 값이 2**n배\\nprint(n << 1)\"\n },\n {\n \"alpha_fraction\": 0.5432432293891907,\n \"alphanum_fraction\": 0.5540540814399719,\n \"avg_line_length\": 29.91666603088379,\n \"blob_id\": \"c7ce8376699516bddee8c368aa83a4d086b35aac\",\n \"content_id\": \"b97bbfe3f8ab86b75ec6203d36274f4e5c574882\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 536,\n \"license_type\": \"no_license\",\n \"max_line_length\": 49,\n \"num_lines\": 12,\n \"path\": \"/알고리즘/온라인저지/2022/07/0729/추월.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = int(input())\\ndct = {input(): i for i in range(N)} # 터널에 들어간 순서\\nresult = 0\\ncheck = [0] * N # 나간 차 기록 list\\nfor n in range(N): # 나가는 차 입력\\n tmp = input() # 나간 차 번호판\\n IN = dct[tmp] # 나간 차의 터널에 들어간 순서\\n OUT = sum(check[:IN]) # 먼저 나간 차량 수\\n # 내 앞 차량들의 수가 터널을 들어갈 때 보다 나올 때 더 적으면\\n if OUT < IN: result += 1 # 추월차량\\n check[IN] = 1 # 해당 차는 터널을 빠져나옴\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.4465116262435913,\n \"alphanum_fraction\": 0.47441861033439636,\n \"avg_line_length\": 21.275861740112305,\n \"blob_id\": \"d4fc4dabb61772057e2a0bad918233a8765f6dba\",\n \"content_id\": \"2ce9a90dbb0b8aa8fabece610bf1379001e5d0d7\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 645,\n \"license_type\": \"no_license\",\n \"max_line_length\": 52,\n \"num_lines\": 29,\n \"path\": \"/알고리즘/온라인저지/2023/01/0130/언더프라임.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"def prime_list(size):\\n sieve = [True]*(size+1)\\n for i in range(2, int(size**0.5)+1):\\n if sieve[i]:\\n for j in range(i+i, size+1, i):\\n sieve[j] = False\\n return [i for i in range(2, size+1) if sieve[i]]\\n \\ndef factorization(x):\\n i = 0\\n d = primes[i]\\n answer = 0\\n while d <= x:\\n if x % d == 0:\\n answer += 1\\n x = x // d\\n else:\\n i += 1\\n d = primes[i]\\n return answer\\n\\n\\nprimes = prime_list(int(1e6))\\nA, B = map(int, input().split())\\nresult = 0\\nfor i in range(A, B+1):\\n if factorization(i) in primes:\\n result += 1\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.5034482479095459,\n \"alphanum_fraction\": 0.5241379141807556,\n \"avg_line_length\": 30.071428298950195,\n \"blob_id\": \"06289fbfbae63f6e9b36ad9db0c8e7e31ad7e8d4\",\n \"content_id\": \"272a8dc4c42092081f93f2e9b133b763c4e46720\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 571,\n \"license_type\": \"no_license\",\n \"max_line_length\": 74,\n \"num_lines\": 14,\n \"path\": \"/알고리즘/온라인저지/2022/04/0417/덩치.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = int(input())\\nwnhs = [] # 덩치 리스트\\nresult = [] # 덩치 순위 리스트\\nfor n in range(N): # N명의\\n wnhs.append(tuple(map(int, input().split()))) # 덩치 입력\\n# N * N \\nfor i in range(N): # 5명의 덩치를 비교\\n cnt = 1 # 덩치를 비교하기 전까지는 모두가 덩치 1등\\n for j in range(N):\\n # 본인보다 덩치가 큰 사람이 있다면\\n if i != j and wnhs[i][0] < wnhs[j][0] and wnhs[i][1] < wnhs[j][1]:\\n cnt += 1 # 덩치 순위 +1\\n result.append(cnt) # 덩치 순위 추가\\nprint(*result) # 출력\\n\"\n },\n {\n \"alpha_fraction\": 0.4611872136592865,\n \"alphanum_fraction\": 0.465753436088562,\n \"avg_line_length\": 15.923076629638672,\n \"blob_id\": \"0360dc695cbb6f3df34b3f8bbd4f3d819d225da5\",\n \"content_id\": \"45ee1628f5cd5b2014cd257ca784bb976959e9e5\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 219,\n \"license_type\": \"no_license\",\n \"max_line_length\": 36,\n \"num_lines\": 13,\n \"path\": \"/알고리즘/온라인저지/2022/07/0713/초6 수학.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"def gcd(a, b):\\n while b > 0:\\n a, b = b, a%b\\n return a\\n\\ndef lcm(a, b):\\n return a * b // gcd(a, b)\\n\\n\\nT = int(input())\\nfor t in range(T):\\n a, b = map(int, input().split())\\n print(lcm(a, b), gcd(a, b))\"\n },\n {\n \"alpha_fraction\": 0.6290322542190552,\n \"alphanum_fraction\": 0.6344085931777954,\n \"avg_line_length\": 22.375,\n \"blob_id\": \"b09966a700262a2e7d52e1556dce7e7280ef0c46\",\n \"content_id\": \"ffe128c874e93f0744925cc3c78a03e8db3e5aa5\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 186,\n \"license_type\": \"no_license\",\n \"max_line_length\": 54,\n \"num_lines\": 8,\n \"path\": \"/알고리즘/온라인저지/2022/09/0926/주차의 신.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\n\\nfor _ in range(int(input().rstrip())):\\n input()\\n parking = list(map(int, input().rstrip().split()))\\n print((max(parking)-min(parking))*2)\"\n },\n {\n \"alpha_fraction\": 0.5405405163764954,\n \"alphanum_fraction\": 0.5540540814399719,\n \"avg_line_length\": 36.5,\n \"blob_id\": \"d068498d57067002d6b4a9d7abd0b7c50f8a764a\",\n \"content_id\": \"45369a96aab0c046dff54ae2e956e53a2d8c5bcb\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 74,\n \"license_type\": \"no_license\",\n \"max_line_length\": 43,\n \"num_lines\": 2,\n \"path\": \"/알고리즘/온라인저지/2023/02/0201/태보태보 총난타.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"taebo = input().split('(^0^)')\\nfor t in taebo:print(t.count('@'), end=' ')\"\n },\n {\n \"alpha_fraction\": 0.44485294818878174,\n \"alphanum_fraction\": 0.4595588147640228,\n \"avg_line_length\": 17.133333206176758,\n \"blob_id\": \"2bff4bba422a29e81afd0c499d371eb13617907d\",\n \"content_id\": \"1d2ed8a1dbd88d007d2b53d1ae54b0e7b915c031\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 272,\n \"license_type\": \"no_license\",\n \"max_line_length\": 37,\n \"num_lines\": 15,\n \"path\": \"/알고리즘/온라인저지/2021/12/1213/Yangjojang of The Year.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"T = int(input())\\n\\nfor tc in range(T):\\n N = int(input())\\n\\n YOTY = ''\\n YOTY_drink = 0\\n\\n for n in range(N):\\n univ = input().split()\\n if int(univ[1]) > YOTY_drink:\\n YOTY_drink = int(univ[1])\\n YOTY = univ[0]\\n \\n print(YOTY)\\n\"\n },\n {\n \"alpha_fraction\": 0.5190274715423584,\n \"alphanum_fraction\": 0.5528541207313538,\n \"avg_line_length\": 27.696969985961914,\n \"blob_id\": \"337f3d6032a84f3f6f256e26fa64e9529febc53d\",\n \"content_id\": \"0af2cfe37964ac2ca47cea61c259c80e7d0811fe\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1444,\n \"license_type\": \"no_license\",\n \"max_line_length\": 63,\n \"num_lines\": 33,\n \"path\": \"/알고리즘/온라인저지/2022/03/0321/지름길.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"\\\"\\\"\\\"\\n세준이는 지름길을 타고 이동하지 않는다\\n그저 일자로 직진하면서\\n지름길이 있는지, 있다면 그 지름길을 지나갈 때\\n운전거리가 얼마나 줄어드는지\\\"만\\\" 확인한다\\n세준이는 일자로 간다\\n\\\"\\\"\\\"\\nfrom collections import deque\\nN, D = map(int, input().split())\\ntmp = [list(map(int, input().split())) for _ in range(N)]\\ntmp.sort(key=lambda x:x[0]) # 출발점 기준 정렬\\nroad = deque(tmp) # 지름길들을 담아놓음\\n# 문제의 조건 : D < 10000\\ndp = [int(1e4) for _ in range(D+1)] # 1e4 = 10000.0, 인덱스 위한 D+1\\ndp[0] = 0 # 시작은 0\\nfor i in range(D): # i = 세준이 위치\\n # 현재 위치에서 갈 수 있는 지름길이 있을 때\\n while road and road[0][0] == i:\\n x = road.popleft() # 지름길을 꺼내와서\\n if x[1] > D: # 목적지를 넘어가면\\n continue # 패스\\n # 지름길의 끝에 거리 갱신\\n dp[x[1]] = min(dp[i] + x[2], dp[x[1]])\\n # print(i, x[1], x[2]) # 디버깅\\n # print(dp) # 디버깅\\n # 다음 칸의 거리는, \\n # min(이전 칸에서 한 칸 이동한 거리, 지름길 타고 넘어온 거리)\\n dp[i+1] = min(dp[i] + 1, dp[i+1])\\n# print(dp) # 디버깅\\n# 세준이는 지름길을 타고 이동하지는 않았지만\\n# 일자로 이동하면서 파악한 지름길들을\\n# 적절히 활용하여 목적지에 도착할 수 있는 최소거리를\\nprint(dp[D]) # 출력\"\n },\n {\n \"alpha_fraction\": 0.45771142840385437,\n \"alphanum_fraction\": 0.4776119291782379,\n \"avg_line_length\": 11.5625,\n \"blob_id\": \"6b44f1c26bc1694260a900740cec958cc533fbb0\",\n \"content_id\": \"d2294410e46b0bfc5e3ebff1936a7a471da62a61\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 227,\n \"license_type\": \"no_license\",\n \"max_line_length\": 33,\n \"num_lines\": 16,\n \"path\": \"/알고리즘/온라인저지/2021/08/0818/factorial.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"\\ndef factorial(n):\\n if n == 1:\\n return n\\n else:\\n return n * factorial(n-1)\\n\\nprint(factorial(10))\\n\\n\\\"\\\"\\\"\\n재귀함수\\ndef 재귀():\\n if 기저:\\n return \\n else: 기저 아닐 때\\n return \\n\\\"\\\"\\\"\"\n },\n {\n \"alpha_fraction\": 0.5607843399047852,\n \"alphanum_fraction\": 0.5686274766921997,\n \"avg_line_length\": 18.69230842590332,\n \"blob_id\": \"ea47adba7c599fa078efed07cc42df5d61a30cfd\",\n \"content_id\": \"3780edbfff855187e8c2ea17809f8031268ea7d0\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 255,\n \"license_type\": \"no_license\",\n \"max_line_length\": 36,\n \"num_lines\": 13,\n \"path\": \"/알고리즘/온라인저지/2023/03/0310/터널의 입구와 출구.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = int(input())\\nM = int(input())\\nresult = M\\ntunnel = M\\nzero = False\\nfor n in range(N):\\n A, B = map(int, input().split())\\n tunnel += A\\n tunnel -= B\\n result = max(result, tunnel)\\n if tunnel<0:\\n zero = True\\nprint(0 if zero else result)\"\n },\n {\n \"alpha_fraction\": 0.3801652789115906,\n \"alphanum_fraction\": 0.4545454680919647,\n \"avg_line_length\": 16.428571701049805,\n \"blob_id\": \"93a89efe6cf24f975835fc33fbe557ddf3ac1963\",\n \"content_id\": \"80ebc00fe5083bddb4ad90b44e732aa68cc3d698\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 121,\n \"license_type\": \"no_license\",\n \"max_line_length\": 28,\n \"num_lines\": 7,\n \"path\": \"/알고리즘/온라인저지/2021/08/0817/n자리m진수.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"n = 3\\nm = 5\\nlist1 = [0] * n\\nfor i in range(n-1, -1, -1):\\n for j in range(m):\\n list1[i] = j\\n print(list1)\"\n },\n {\n \"alpha_fraction\": 0.4235033392906189,\n \"alphanum_fraction\": 0.47671839594841003,\n \"avg_line_length\": 18.65217399597168,\n \"blob_id\": \"57de5c6c3ad49f19a73bd2362dc4941abfb2e509\",\n \"content_id\": \"37d2d331e7763b95045dcc0855bc3648e3777501\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 451,\n \"license_type\": \"no_license\",\n \"max_line_length\": 50,\n \"num_lines\": 23,\n \"path\": \"/알고리즘/온라인저지/2023/04/0430/사격 내기.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"targets = [2**i for i in range(10)]\\nscores = [[0]*10 for _ in range(2)] # A, B\\nA, B = map(int, input().split())\\n\\nfor i in range(9, -1, -1):\\n target = targets[i]\\n\\n if A>=target:\\n scores[0][i] = 1\\n A -= target\\n\\n if B>=target:\\n scores[1][i] = 1\\n B -= target\\n\\nresult = 0\\n\\nfor i in range(10):\\n C, D = scores[0][i], scores[1][i]\\n if (C == 0 and D == 1) or (C == 1 and D == 0):\\n result += 2**i\\n\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.5214285850524902,\n \"alphanum_fraction\": 0.5357142686843872,\n \"avg_line_length\": 22.5,\n \"blob_id\": \"2c343fed58989b578dd151f5ffb06ffd9f26faa9\",\n \"content_id\": \"76c0e12ba87461bd5a2e8ebd3c608b00364a4f74\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 140,\n \"license_type\": \"no_license\",\n \"max_line_length\": 50,\n \"num_lines\": 6,\n \"path\": \"/알고리즘/온라인저지/2023/04/0421/등차수열에서 항 번호 찾기.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"a, d, k = map(int, input().split())\\nresult = 1\\nif not (not (k-a)%d and (k-a)//d>=0): result = 'X'\\nelse:\\n result += (k-a)//d\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.4129793643951416,\n \"alphanum_fraction\": 0.4410029351711273,\n \"avg_line_length\": 20.90322494506836,\n \"blob_id\": \"6063291ea43f7d10fe605f7e76e63e8b23cbea94\",\n \"content_id\": \"da1c175bd9ba8bc0cfd99e8f2e72439d5ce592c9\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 678,\n \"license_type\": \"no_license\",\n \"max_line_length\": 69,\n \"num_lines\": 31,\n \"path\": \"/알고리즘/온라인저지/2023/01/0114/소수의 연속합.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"def prime_list(size):\\n sieve = [True]*(size+1)\\n for i in range(2, int(size**0.5)+1):\\n if sieve[i]:\\n for j in range(i+i, size+1, i):\\n sieve[j] = False\\n return [i for i in range(2, size+1) if sieve[i]]\\n\\nN = int(input())\\nif N == 1: \\n print(0)\\nelse:\\n primes = prime_list(N)\\n s, e, now = 0, 0, primes[0]\\n max_len = len(primes)-1\\n result = 0\\n\\n while 1:\\n if (now < N and e == max_len) or (now > N and s == max_len): \\n break\\n\\n if now == N: result += 1\\n\\n if now < N:\\n e += 1\\n now += primes[e]\\n else:\\n now -= primes[s]\\n s += 1\\n\\n print(result)\"\n },\n {\n \"alpha_fraction\": 0.45562130212783813,\n \"alphanum_fraction\": 0.48520711064338684,\n \"avg_line_length\": 20.25,\n \"blob_id\": \"d01f224b12ab11fe1bb6b01e606aa0c0a313fed9\",\n \"content_id\": \"faa4cb73ff00fe6efb934eb4118157c22a3558e9\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 169,\n \"license_type\": \"no_license\",\n \"max_line_length\": 51,\n \"num_lines\": 8,\n \"path\": \"/알고리즘/[템플릿]/[SAMPLE]/요세푸스 점화식.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"def josephus(N, K):\\n if N == 1:\\n return 1\\n else:\\n return ((josephus(N-1, K) + K - 1) % N) + 1\\n\\nN, K = map(int, input().split())\\nprint(josephus(N, K))\"\n },\n {\n \"alpha_fraction\": 0.44131454825401306,\n \"alphanum_fraction\": 0.5164319276809692,\n \"avg_line_length\": 16.83333396911621,\n \"blob_id\": \"77162f597988f1cd5c68f752ba3f351b923a1d35\",\n \"content_id\": \"3eb225596b2edab4c87d42f51e7fdb48a3b526c1\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 213,\n \"license_type\": \"no_license\",\n \"max_line_length\": 43,\n \"num_lines\": 12,\n \"path\": \"/알고리즘/온라인저지/2022/09/0925/피보나치는 지겨웡~.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\n\\nN = int(input().rstrip())\\nmod = int(1e9)+7\\ndp = [0] * (N+30)\\ndp[0], dp[1] = 1, 1\\nif N>1:\\n for i in range(2, N+1):\\n dp[i] = (dp[i-1] + dp[i-2] + 1)%mod\\nprint(dp[N])\"\n },\n {\n \"alpha_fraction\": 0.5226730108261108,\n \"alphanum_fraction\": 0.5680190920829773,\n \"avg_line_length\": 23.705883026123047,\n \"blob_id\": \"c39f32e1a111a6514d83f81d806d3b3e6657b395\",\n \"content_id\": \"c40715d5e7a78b6aac50bd161fbbc600c031fa6d\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 419,\n \"license_type\": \"no_license\",\n \"max_line_length\": 69,\n \"num_lines\": 17,\n \"path\": \"/알고리즘/온라인저지/2022/10/1014/숫자 맞추기 게임.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\n\\ni = 0\\nwhile True:\\n i += 1\\n N = int(input())\\n if N == 0: break\\n result = [N]\\n result.append(3*result[0])\\n if not result[1]%2: result.append(result[1]//2)\\n else: result.append((result[1]+1)//2)\\n result.append(3*result[2])\\n result.append(result[3]//9)\\n odd_or_even = ['even', 'odd']\\n print('{}. {} {}'.format(i, odd_or_even[result[1]%2], result[4]))\"\n },\n {\n \"alpha_fraction\": 0.5649546980857849,\n \"alphanum_fraction\": 0.5709969997406006,\n \"avg_line_length\": 22.714284896850586,\n \"blob_id\": \"5a6d2af43eb0b99afe6aee4ba1acea1c10e42a76\",\n \"content_id\": \"311d1ed22c5fa7099f0ca8756e5984c4508bde93\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 331,\n \"license_type\": \"no_license\",\n \"max_line_length\": 53,\n \"num_lines\": 14,\n \"path\": \"/알고리즘/온라인저지/2022/07/0729/회사에 있는 사람.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = int(input())\\ncompany = dict()\\nresult = []\\nfor n in range(N):\\n name, el = input().split() # name, enter or leave\\n if el == 'enter':\\n company[name] = 1\\n else: # el == 'leave\\n company[name] = 0\\nfor c in company:\\n if company[c]:\\n result.append(c)\\nresult.sort(reverse=True)\\nfor r in result: print(r)\"\n },\n {\n \"alpha_fraction\": 0.4114285707473755,\n \"alphanum_fraction\": 0.4342857003211975,\n \"avg_line_length\": 16.600000381469727,\n \"blob_id\": \"7e784ab2b441b4d2715de9d992295f0d9c209fe7\",\n \"content_id\": \"d265a542ec94b42237a4858ae33bfd461f72b59d\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 175,\n \"license_type\": \"no_license\",\n \"max_line_length\": 38,\n \"num_lines\": 10,\n \"path\": \"/알고리즘/온라인저지/2023/04/0416/골뱅이 찍기 - ㅁ.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = int(input())\\nfor _ in range(N):\\n print('@'*5*N)\\n\\nfor _ in range(3):\\n for _ in range(N):\\n print('@'*N + ' '*N*3 + '@'*N)\\n\\nfor _ in range(N):\\n print('@'*5*N)\"\n },\n {\n \"alpha_fraction\": 0.5,\n \"alphanum_fraction\": 0.5067567825317383,\n \"avg_line_length\": 11.416666984558105,\n \"blob_id\": \"95e8fdb6d0c7e348dd586bf8641d859b05b01d99\",\n \"content_id\": \"26d4f7d2ab2731c99c92fbe6e9749ae0409e9744\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 148,\n \"license_type\": \"no_license\",\n \"max_line_length\": 35,\n \"num_lines\": 12,\n \"path\": \"/알고리즘/온라인저지/2022/03/0304/X に最も近い値 (The Nearest Value).py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"X, L, R = map(int, input().split())\\n\\nresult = 0\\n\\nif X < L:\\n result = L\\nelif L <= X < R:\\n result = X\\nelif X >= R:\\n result = R\\n\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.5120290517807007,\n \"alphanum_fraction\": 0.5265547037124634,\n \"avg_line_length\": 30.042253494262695,\n \"blob_id\": \"e8ca497a22fb1acf8a146a8d32c6b0d1c9532e69\",\n \"content_id\": \"2614ee9a9dc9c1182908090ab43282e5d07b38a4\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 3597,\n \"license_type\": \"no_license\",\n \"max_line_length\": 72,\n \"num_lines\": 71,\n \"path\": \"/알고리즘/온라인저지/2021/10/1003/연구소.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# 모든 0에 벽을 세 개 세워보고 가장 안전영역을 많이 확보가능한게 정답\\nimport copy # 2차원 배열 복사를 위한 import copy, deepcopy를 사용함\\nfrom collections import deque # bfs로 바이러스를 퍼뜨릴 때 사용할 deque\\n\\ndx = [1, -1, 0, 0]\\ndy = [0, 0, 1, -1]\\n\\nres = 0 # 결과값 초기화\\n\\ndef virus(): # 바이러스가 퍼진다!\\n global res # 함수 밖에 있는 전역변수 res를 사용\\n\\n tmp = copy.deepcopy(arr) # 입력받은 배열 arr을 완전히 복제할 것\\n # 벽을 세우고 허물고 할건데\\n # 매번 세우는 벽의 위치가 바뀌는데 원본 배열을 들고 수정하기보다\\n # 배열을 복사해서 백업을 따놓고 \\n # \\\"여기여기 벽을 세운거로는 바이러스를 못막는구나\\\"는 결과가 확인이 되면\\n # 해당 복사는 지우고 다시 원본 배열을 복사해서 또 벽을 세우고\\n # 그 벽에 바이러스 퍼뜨려보고를 반복\\n # 그런데 2차원 배열을 복사해야 하기 때문에 deepcopy를 사용함\\n\\n for i in range(N): # 바이러스 시작점을\\n for j in range(M): # 찾자\\n if tmp[i][j] == 2: # 해당 칸이 바이러스면\\n q.append([i, j]) # 이동할 칸에 추가\\n # 배열의 처음 바이러스 위치를 q에 담음\\n # 이후 아래 while문을 반복하면서 바이러스를 퍼뜨림\\n \\n while q: # 바이러스가 퍼질 곳이 남아있다면\\n x, y = q.popleft() # 맨 앞에 좌표부터 꺼내서\\n for i in range(4): # 상하좌우 전부 확인\\n nx = x + dx[i]\\n ny = y + dy[i]\\n if 0 <= nx < N and 0 <= ny < M: # 연구소를 벗어나지 않는 범위에서\\n if tmp[nx][ny] == 0: # 바이러스를 퍼뜨릴 수 있으면\\n tmp[nx][ny] = 2 # 받아라 바이러스!\\n q.append([nx,ny]) # 해당 좌표의 상하좌우에 또 바이러스가 퍼지도록 q에 담기\\n\\n cnt = 0 # 지금 세워진 벽에 대하여 바이러스가 얼마나 퍼졌는지 확인하는 변수 초기화\\n \\n for t in tmp:\\n cnt += t.count(0) # 연구소 해당 줄에서 확인된 안전구역의 수\\n \\n res = max(res, cnt) # 전역변수 res와 비교하여 지금 세워진 벽에서의 안전구역이 더 많은지 비교하고 저장\\n # if cnt > res: 와 같은 문장을 max()를 사용하였음\\n\\ndef wall(x):\\n if x == 3: # 벽을 세 개 세웠다면\\n virus() # 바이러스를 퍼뜨려보자!\\n return # 바이러스를 다 퍼뜨리고 해당 재귀함수 종료, 다시 다른 벽을 세워보자\\n \\n for i in range(N):\\n for j in range(M):\\n if arr[i][j] == 0: # 벽을 세울 수 있으면\\n arr[i][j] = 1 # 벽을 세우고\\n wall(x+1) # 다음 벽을 세우자\\n arr[i][j] = 0 # 다른 위치에 벽을 세울 수 있도록 위에서 세웠던 벽을 허물자\\n\\n\\nN, M = map(int, input().split()) # 연구소의 가로와 세로 크기\\n\\narr = [list(map(int, input().split())) for _ in range(N)] # 연구소 상황\\n\\nq = deque() # 바이러스를 퍼뜨릴 q\\n\\nwall(0) # 벽 0개, 벽 1개, 벽 2개, 벽 3개, 그 시작은 0개\\n\\nprint(res) # 3개의 벽을 세운 각각의 경우에 대하여 얻은 안전구역의 수가 \\n# 기존에 얻은 안전구역의 수 보다 클 때마다 갱신해주어서\\n# 결국 벽을 세우는 모든 경우의 수에서 퍼뜨려 본 바이러스에 대해 확인된 안전구역의 최대 수가 담겨있는\\n# res를 출력\"\n },\n {\n \"alpha_fraction\": 0.3029460906982422,\n \"alphanum_fraction\": 0.40744858980178833,\n \"avg_line_length\": 28.508195877075195,\n \"blob_id\": \"d23b424b695ddca33848acb446292289d6eceafa\",\n \"content_id\": \"77dc69334f426303535d90ba79f99570fa121ac1\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1871,\n \"license_type\": \"no_license\",\n \"max_line_length\": 72,\n \"num_lines\": 61,\n \"path\": \"/알고리즘/SW역량테스트/2021.10.19 A형.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"T = int(input())\\n\\nfor t in range(1, T+1):\\n N = int(input())\\n arr = list(map(int, input().split()))\\n \\n result = []\\n\\t# 제곱까지 갈 필요없다 \\n # A + B + C + D 가 가장 크면 결과값이 가장 클거다\\n # 결과값만 (A+B)**2 + (C+D)**2 를 출력해주면 된다\\n \\n stack = []\\n tmp = 0\\n \\n visited = [0] * N\\n for i in range(N-6):\\n stack.append(arr[i])\\n visited[i-1], visited[i], visited[i+1] = 1, 1, 1\\n for j in range(i, N-4):\\n if visited[j] == 0:\\n stack.append(arr[j])\\n visited[j-1], visited[j], visited[j+1] = 1, 1, 1\\n for k in range(j, N-2):\\n if visited[k] == 0:\\n stack.append(arr[k])\\n visited[k-1], visited[k], visited[k+1] = 1, 1, 1\\n for l in range(k, N):\\n if visited[l] == 0:\\n stack.append(arr[l])\\n if sum(stack) > tmp:\\n tmp = sum(stack)\\n result = [s for s in stack]\\n stack.pop()\\n visited[k-1], visited[k], visited[k+1] = 0, 0, 0\\n stack.pop()\\n visited[j-1], visited[j], visited[j+1] = 0, 0, 0\\n stack.pop()\\n visited[i-1], visited[i], visited[i+1] = 0, 0, 0\\n stack.pop()\\n A = result[0]\\n B = result[1]\\n C = result[2]\\n D = result[3]\\n ans1 = (A+B)**2 + (C+D)**2\\n ans2 = (A+D)**2 + (B+C)**2\\n print('#{} {}'.format(t, (max(ans1, ans2))))\\n\\n\\\"\\\"\\\"\\ninput↓\\n5\\n10\\n80 90 65 55 90 60 40 35 30 25\\n8\\n30 25 70 55 95 75 90 20\\n10\\n60 85 45 25 15 70 55 70 85 35\\n15\\n80 30 35 95 45 85 30 25 100 85 10 60 80 30 5\\n20\\n45 30 5 85 55 85 10 5 75 60 15 65 45 50 75 80 15 10 50 90\\n\\\"\\\"\\\"\"\n },\n {\n \"alpha_fraction\": 0.5087719559669495,\n \"alphanum_fraction\": 0.5131579041481018,\n \"avg_line_length\": 18.08333396911621,\n \"blob_id\": \"428207c8cf1ee70c7ee238b38e71097991566a36\",\n \"content_id\": \"3495bb730745928ad09ef6a3a88ee66ca990c0d4\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 228,\n \"license_type\": \"no_license\",\n \"max_line_length\": 45,\n \"num_lines\": 12,\n \"path\": \"/알고리즘/온라인저지/2022/09/0927/LCM.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\n\\ndef gcd(a, b):\\n while a%b: a, b = b, a%b\\n return b\\n\\nfor _ in [0]*int(input().rstrip()):\\n a, b = map(int, input().rstrip().split())\\n G = gcd(a, b)\\n print(G * (a//G) * (b//G))\"\n },\n {\n \"alpha_fraction\": 0.35199999809265137,\n \"alphanum_fraction\": 0.3733333349227905,\n \"avg_line_length\": 28.431371688842773,\n \"blob_id\": \"b466e0cfb7ad746b112160b5d36d5d0e19ee6ea8\",\n \"content_id\": \"6aa886b707e82f1b1194d8f5819883bcec187dad\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 2000,\n \"license_type\": \"no_license\",\n \"max_line_length\": 71,\n \"num_lines\": 51,\n \"path\": \"/알고리즘/온라인저지/2021/10/1016/섬의 개수.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from collections import deque\\n\\ndx = [-1, 1, 0, 0, -1, 1, -1, 1] # 8방향\\ndy = [0, 0, -1, 1, -1, -1, 1, 1]\\n\\nwhile True: # 0 0 을 받을때까지\\n w, h = map(int, input().split())\\n if w+h == 0: # 종료조건\\n break\\n\\n arr = [] # 섬과 육지\\n\\n for i in range(h):\\n arr.append(list(map(int, input().split())))\\n \\n q = deque()\\n cnt = 0 # 섬의 개수 초기화\\n\\n # 배열 전체를 확인하면서\\n # 육지가 나오면, 그 육지를 바다로 바꿔버리고\\n # 주변 8칸에 또 육지가 있는지 즉, 이어져 있는 섬인지 확인할 것\\n for i in range(h):\\n for j in range(w): # 배열을 돌면서\\n if arr[i][j]: # 육지를 찾았다?\\n q.append((j, i)) # 탐색할 육지에 추가\\n \\n while q: # 탐색할 육지가 있을 때\\n tmp = q.popleft() # 육지 좌표\\n a = tmp[0]\\n b = tmp[1]\\n\\n if arr[b][a] == 0: # 가지치기 조건\\n # 탐색하려던 육지좌표였지만\\n # 다른 육지를 탐색하던 중 바다로 만들었다면\\n continue\\n\\n arr[b][a] = 0 # 해당 육지를 바다로 만들어버리자\\n\\n for k in range(8): # 8방향 BFS\\n nx = a+dx[k]\\n ny = b+dy[k]\\n\\n if 0 <= nx < w and 0 <= ny < h and arr[ny][nx]:\\n # 범위를 벗어나지 않고, 8방향중 하나로 이동할 수 있는 육지면\\n # 즉 이어져 있는 섬이면\\n q.append((nx, ny)) # 탐색할 육지에 추가\\n \\n cnt += 1 # while문을 통해 섬을 전부 바다로 만들었다\\n # 해당 섬은 사라졌고, 우리는 섬이 하나 존재하였음을 확인할 수 있음\\n\\n print(cnt) # 확인된 섬의 개수\"\n },\n {\n \"alpha_fraction\": 0.4591836631298065,\n \"alphanum_fraction\": 0.5102040767669678,\n \"avg_line_length\": 16.909090042114258,\n \"blob_id\": \"cd5f995fb6ac426c5ddf43031f89092e2d7a6112\",\n \"content_id\": \"2db238478f8b0dcd8f134b8fca176992f7a2013d\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 196,\n \"license_type\": \"no_license\",\n \"max_line_length\": 42,\n \"num_lines\": 11,\n \"path\": \"/알고리즘/온라인저지/2021/08/0818/피보나치 DP.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"def fibo(n):\\n table[0] = 0\\n table[1] = 1\\n for i in range(2, n+1):\\n table[i] = table[i-1] + table[i-2]\\n return table[n]\\n\\nn = int(input())\\ntable = [0] * (n+1)\\nfibo(n)\\nprint(table)\"\n },\n {\n \"alpha_fraction\": 0.48480844497680664,\n \"alphanum_fraction\": 0.5178335309028625,\n \"avg_line_length\": 38.894737243652344,\n \"blob_id\": \"5a0c286545912e91c0322d1a679639448076947d\",\n \"content_id\": \"b791b4f7e42266ff0e62b35b55e2ade764f34e44\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1061,\n \"license_type\": \"no_license\",\n \"max_line_length\": 82,\n \"num_lines\": 19,\n \"path\": \"/알고리즘/온라인저지/2023/02/0218/동전 바꿔주기.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"T = int(input())\\nk = int(input())\\n\\ncoin = [(0, 0)] + [tuple(map(int, input().split())) for _ in range(k)]\\n\\ndp = [[0 for _ in range(T+1)] for _ in range(k+1)] # 가로 세로 첫 줄은 0원\\ndp[0][0] = 1 # 0원을 만들 수 있는 경우는 1\\n\\nfor i in range(1, k+1): # 1번 동전, 2번 동전, i번 동전, ..., k번 동전\\n val, cnt = coin[i] # 동전 가치, 동전 개수\\n for cost in range(T+1): # 0원부터 T원까지, i번 동전을 사용하여 만들 수 있는 지 확인\\n dp[i][cost] = dp[i-1][cost] # 앞서 i-1번 동전을 사용한 경우를 미리 불러오기\\n for c in range(1, cnt+1): # val원의 동전 1개, 2개, c개, ..., cnt개\\n if cost-c*val >= 0: # dp갱신 최소 조건\\n dp[i][cost] += dp[i-1][cost-c*val] # i번 동전을 c개 사용하여 갱신할 수 있는 지점 확인\\n else: # cost원을 i번 동전을 사용하여 갱신할 수 없을 경우에\\n break\\n\\nprint(dp[k][T]) # k개 종류의 동전을 사용하여 T원을 만들 수 있는 경우 출력\"\n },\n {\n \"alpha_fraction\": 0.4470588266849518,\n \"alphanum_fraction\": 0.5235294103622437,\n \"avg_line_length\": 21.217391967773438,\n \"blob_id\": \"9c60d8546374beebadf583a3b641b66324185435\",\n \"content_id\": \"8ed6bb7e1450dc849d5a2e1c201cbd62754ab930\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 510,\n \"license_type\": \"no_license\",\n \"max_line_length\": 55,\n \"num_lines\": 23,\n \"path\": \"/알고리즘/온라인저지/2022/09/0930/투명.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\n\\ndef cover(x1, y1, x2, y2):\\n for i in range(y1, y2):\\n for j in range(x1, x2):\\n arr[i][j] += 1\\n\\ndef check():\\n result = 0\\n for i in range(100):\\n for j in range(100):\\n if arr[i][j]>M: result += 1\\n return result\\n\\nN, M = map(int, input().rstrip().split())\\narr = [[0]*100 for _ in [0]*100]\\nfor n in range(N):\\n x1, y1, x2, y2 = map(int, input().rstrip().split())\\n x1, y1 = x1-1, y1-1\\n cover(x1, y1, x2, y2)\\nprint(check())\"\n },\n {\n \"alpha_fraction\": 0.4022066295146942,\n \"alphanum_fraction\": 0.4403209686279297,\n \"avg_line_length\": 16.821428298950195,\n \"blob_id\": \"56de27a6c50eb6ff30fda4a2d7e790024a6ead59\",\n \"content_id\": \"7745686dc6aacf67012a4de2fe9e9ef67a12b7f1\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 997,\n \"license_type\": \"no_license\",\n \"max_line_length\": 59,\n \"num_lines\": 56,\n \"path\": \"/알고리즘/온라인저지/2023/03/0326/소문난 칠공주.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from collections import deque\\n\\n\\ndef check(arr):\\n visited = [[1]*5 for _ in range(5)]\\n\\n for a in arr:\\n y, x = a\\n visited[y][x] = 0\\n \\n Q = deque([(arr[0])])\\n y, x = arr[0]\\n visited[y][x] = 1\\n cnt = 1\\n\\n while Q:\\n y, x = Q.popleft()\\n\\n for k in range(4):\\n ny, nx = y+dy[k], x+dx[k]\\n\\n if 0<=ny<5 and 0<=nx<5 and not visited[ny][nx]:\\n visited[ny][nx] = 1\\n cnt += 1\\n Q.append((ny, nx))\\n\\n return True if cnt == 7 else False\\n\\n\\ndef DFS(depth, idx, YDY_cnt):\\n global result\\n\\n if YDY_cnt>=4:\\n return\\n \\n if depth == 7:\\n if check(arr):\\n result += 1\\n return\\n \\n for i in range(idx, 25):\\n y, x = i//5, i%5\\n arr.append((y, x))\\n DFS(depth+1, i+1, YDY_cnt+(students[y][x]=='Y'))\\n arr.pop()\\n\\n\\ndy, dx = [-1, 1, 0, 0], [0, 0, -1, 1]\\n\\nstudents = [input() for _ in range(5)]\\nresult = 0\\narr = []\\n\\nDFS(0, 0, 0)\\n\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.3855421543121338,\n \"alphanum_fraction\": 0.42168673872947693,\n \"avg_line_length\": 12.833333015441895,\n \"blob_id\": \"a0287260e483bfcfd22abc5f83b6f18ec381a343\",\n \"content_id\": \"a4c4f1302cda1fe46e86647f3171462bca1edc1e\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 166,\n \"license_type\": \"no_license\",\n \"max_line_length\": 47,\n \"num_lines\": 12,\n \"path\": \"/알고리즘/온라인저지/2022/01/0131/윷놀이.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"status = {\\n 3: 'A',\\n 2: 'B',\\n 1: 'C',\\n 0: 'D',\\n 4: 'E',\\n}\\n\\nfor t in range(3):\\n yoot = sum(list(map(int, input().split())))\\n\\n print(status[yoot])\\n\"\n },\n {\n \"alpha_fraction\": 0.5993788838386536,\n \"alphanum_fraction\": 0.6304348111152649,\n \"avg_line_length\": 23.846153259277344,\n \"blob_id\": \"b4dd59ad31b139590cd5fe8a186685fc05fd712d\",\n \"content_id\": \"339424802e35ba25baad225d69b201bb73ac3c61\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 322,\n \"license_type\": \"no_license\",\n \"max_line_length\": 46,\n \"num_lines\": 13,\n \"path\": \"/알고리즘/온라인저지/2022/09/0927/생일.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\n\\nstudents = []\\nfor _ in [0]*int(input().rstrip()):\\n student = input().rstrip().split()\\n name = [student[0]]\\n birthday = list(map(int, student[1:]))\\n students.append(name+birthday)\\nstudents.sort(key=lambda x:(x[3], x[2], x[1]))\\nprint(students[-1][0])\\nprint(students[0][0])\"\n },\n {\n \"alpha_fraction\": 0.5993788838386536,\n \"alphanum_fraction\": 0.6055900454521179,\n \"avg_line_length\": 22,\n \"blob_id\": \"f7f9719db4d0990842179ad982a603f13b5e2fbb\",\n \"content_id\": \"4edfda9f41d66242116e5d1dc7f971f1865d86c5\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 500,\n \"license_type\": \"no_license\",\n \"max_line_length\": 53,\n \"num_lines\": 14,\n \"path\": \"/알고리즘/온라인저지/2021/08/0806/최댓값.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"\\\"\\\"\\\"\\n숫자를 다 받아서\\n리스트에 넣고\\n최댓값 찾아서\\n리스트 순회하면서\\n최댓값과 일치하는 요소의 인덱스(길이)\\n\\\"\\\"\\\"\\nnumbers = [] # 입력받을 리스트 초기화\\nfor i in range(9):\\n numbers.append(int(input())) # Enter단위로 값들 입력받기\\nfor i in range(len(numbers)): # 리스트를 순회\\n if numbers[i] == max(numbers): # 최댓값과 순회중인 값이 같으면\\n print(numbers[i]) # 값 출력\\n print(i + 1) # 인덱스 출력\\n\"\n },\n {\n \"alpha_fraction\": 0.5245901346206665,\n \"alphanum_fraction\": 0.5450819730758667,\n \"avg_line_length\": 21.272727966308594,\n \"blob_id\": \"013500daa75a28d9df9280f425be067085431846\",\n \"content_id\": \"3aa32378aa3f76ba13012d6bd642be2c152c4c3f\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 244,\n \"license_type\": \"no_license\",\n \"max_line_length\": 49,\n \"num_lines\": 11,\n \"path\": \"/알고리즘/온라인저지/2022/09/0927/UCPC는 무엇의 약자일까.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\n\\nUCPC = ('U', 'C', 'P', 'C')\\nsen = input().rstrip()\\ni, j = 0, 0 # sen, UCPC\\nfor i in range(len(sen)):\\n if j == 4: break\\n if sen[i] == UCPC[j]: j += 1\\nprint('I love UCPC' if j == 4 else 'I hate UCPC')\"\n },\n {\n \"alpha_fraction\": 0.5296167135238647,\n \"alphanum_fraction\": 0.5644599199295044,\n \"avg_line_length\": 18.16666603088379,\n \"blob_id\": \"630ea95461ddb7917c077c3276b5a3275079e936\",\n \"content_id\": \"1308689d224d9e0af4c833909361ba79370d6145\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 842,\n \"license_type\": \"no_license\",\n \"max_line_length\": 39,\n \"num_lines\": 30,\n \"path\": \"/알고리즘/온라인저지/2022/08/0809/IOIOI.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\n\\nN = int(input())\\nM = int(input())\\nS = input().rstrip()\\nresult = 0\\nlst = []\\nfor i in range(len(S)):\\n if S[i] == 'I': lst.append(i)\\ncnt = 0\\nfor i in range(len(lst)-1):\\n if lst[i+1] - lst[i] == 2: cnt += 1\\n else: cnt = 0\\n if cnt >= N: result += 1\\nprint(result)\\n\\n\\\"\\\"\\\"\\n시간 : 1시간 초과, 정답 풀이 확인\\n풀이\\n 제한 시간 1초, 3<=M<=1,000,000 이므로\\n O(n) 이하로 코드 동작을 마쳐야 한다\\n 전체 문자열을 한 번만 탐색한다\\n I의 인덱스만 모은 리스트를 생성하여\\n 리스트에서 두개씩 원소를 비교할 때\\n 앞 원소와 뒷 원소의 차가 2이면 'IOI'이다\\n 해당 패턴이 N번 이상일 경우 문제에서 원하는 정답이며\\n 패턴의 연속됨이 끊어질 시, 카운트를 0으로 돌린다\\n\\\"\\\"\\\"\"\n },\n {\n \"alpha_fraction\": 0.416879802942276,\n \"alphanum_fraction\": 0.4578005075454712,\n \"avg_line_length\": 36.28571319580078,\n \"blob_id\": \"b3fc416b28ab2adb3f6bf3f2277d199c06b7ef21\",\n \"content_id\": \"ee44b5ac630e1c264d7efc125e6f2af612d45326\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1112,\n \"license_type\": \"no_license\",\n \"max_line_length\": 62,\n \"num_lines\": 21,\n \"path\": \"/알고리즘/온라인저지/2022/07/0705/어린 왕자.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"for t in range(int(input())):\\n x1, y1, x2, y2 = map(int, input().split())\\n result = 0\\n for n in range(int(input())): # 각 행성을 입력\\n cx, cy, cr = map(int, input().split())\\n d1 = (x1-cx)**2 + (y1-cy)**2 # 출발점과 행성 중심간의 거리\\n d2 = (x2-cx)**2 + (y2-cy)**2 # 도착점과 행성 중심간의 거리\\n d3 = cr**2 # 행성 반지름의 제곱\\n if d3 > d1 and d3 > d2: # 같은 행성 안에 있으면\\n pass # 행성 진입/이탈할 필요 없음\\n \\\"\\\"\\\"\\n 위의 if문을 거치면서 아래 세가지 경우만 남게됨\\n 1. 출발점 도착점 다 행성 밖에 있는 경우, 진입/이탈 없이 행성 사이를 움직일 수 있음\\n 2. 출발점은 행성 안에, 도착점은 행성 밖에 있는 경우, 진입/이탈이 필요함\\n 3. 출발점은 행성 밖에, 도착점은 행성 안에 있는 경우, 진입/이탈이 필요함\\n \\\"\\\"\\\"\\n elif d3 > d1: # Case 2\\n result += 1\\n elif d3 > d2: # Case 3\\n result += 1\\n print(result)\"\n },\n {\n \"alpha_fraction\": 0.5817825794219971,\n \"alphanum_fraction\": 0.5905974507331848,\n \"avg_line_length\": 35.5,\n \"blob_id\": \"eea6199cacd1f5b860638b05aa8f49d4d3ecd82e\",\n \"content_id\": \"216f7156a462c7bf4272d7c619f483ba8141feb7\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1413,\n \"license_type\": \"no_license\",\n \"max_line_length\": 82,\n \"num_lines\": 28,\n \"path\": \"/알고리즘/온라인저지/2022/08/0828/최단경로.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\nimport heapq # 탐색 시 가장 작은 값을 탐색하기 위함\\n\\ninput = sys.stdin.readline\\nINF = int(1e9) # 가상의 최대값\\n\\ndef dijkstra(start):\\n distance[start] = 0 # 시작점에서 시작점으로 가는 최단 경로값은 0\\n heapq.heappush(Q, (0, start))\\n while Q:\\n dist, now = heapq.heappop(Q) # 가장 작은 값을 heappop으로 꺼내기\\n for next, weight in data[now]: # 현재 노드에서 갈 수 있는 노드와 가중치들을 순회하면서\\n cost = dist + weight # 경로값은 들고 있는 경로값 + 가중치\\n if cost < distance[next]: # 더 작은 경로값이 발견되면\\n distance[next] = cost # 최소 경로값 갱신\\n heapq.heappush(Q, (cost, next)) # 해당 경로와 다음 노드를 heappush로 가장 앞에 추가\\n\\nV,E = map(int, input().split())\\nstart = int(input())\\ndata = [[] for _ in range(V+1)]\\nfor _ in range(E):\\n u, v, w = map(int, input().split())\\n data[u].append((v, w)) # 노드 u에서 갈 수 있는 노드v와 그 때의 가중치 w\\ndistance = [INF]*(V+1) # 가상의 최대 경로값 배열\\nQ = [] # heapq의 메소드만 사용함, deque와 다르게, 일반적인 리스트 선언\\ndijkstra(start) # start부터 출발\\nfor d in distance[1:]: # 0번은 인덱스 맞추기용\\n print(d if d != INF else 'INF') # 값이 있으면 해당 경로값, 없으면 'INF'\"\n },\n {\n \"alpha_fraction\": 0.27731093764305115,\n \"alphanum_fraction\": 0.45798319578170776,\n \"avg_line_length\": 6.645161151885986,\n \"blob_id\": \"76f37429951da3fc3b96b574ff6f9dec15b24f6a\",\n \"content_id\": \"0515a00605c5d4b36b1eddd4cc8c18c103990e6e\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 238,\n \"license_type\": \"no_license\",\n \"max_line_length\": 36,\n \"num_lines\": 31,\n \"path\": \"/알고리즘/온라인저지/2022/02/0220/BABBA.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"\\\"\\\"\\\"\\n0\\n1\\n10\\n101\\n10110\\n\\n1 1\\n1 2\\n2 3\\n3 4\\n5 5\\n8 6\\n13 7\\n21 8\\n34 9\\n\\n\\\"\\\"\\\"\\n\\ndp = [0, 1, 1]\\n\\nK = int(input())\\n\\n\\nif K <= 2:\\n print(dp[K-1], dp[K])\\nelse:\\n for i in range(3, K+1):\\n dp.append(dp[i-1] + dp[i-2])\\n\\n print(dp[K-1], dp[K])\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.6800000071525574,\n \"alphanum_fraction\": 0.6800000071525574,\n \"avg_line_length\": 20.571428298950195,\n \"blob_id\": \"a445ac1655a5ab010de8db283caa34f5ef8845ca\",\n \"content_id\": \"bd9fdd21d4147459afb08a274b3d3c39fe8fdd96\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 150,\n \"license_type\": \"no_license\",\n \"max_line_length\": 42,\n \"num_lines\": 7,\n \"path\": \"/알고리즘/온라인저지/2021/09/0906/약수.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\ndef input():\\n return sys.stdin.readline()\\n\\ncnt = input()\\nmeasures = list(map(int, input().split()))\\nprint(max(measures) * min(measures))\"\n },\n {\n \"alpha_fraction\": 0.44408944249153137,\n \"alphanum_fraction\": 0.4792332351207733,\n \"avg_line_length\": 21.39285659790039,\n \"blob_id\": \"da3f588cc31ef7876c18d65114326d7ece2bf304\",\n \"content_id\": \"c8c2855bd3d46d54488879aaecdf4e7f51fcfa1b\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 634,\n \"license_type\": \"no_license\",\n \"max_line_length\": 52,\n \"num_lines\": 28,\n \"path\": \"/알고리즘/온라인저지/2022/09/0923/달팽이2.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\ndy, dx = [0, 1, 0, -1], [1, 0, -1, 0] # 우 하 좌 상\\n\\ndef check_goal(y, x):\\n flag = True\\n for i in range(4):\\n ny, nx = y+dy[i], x+dx[i]\\n if 0<=ny<N and 0<=nx<M and not arr[ny][nx]: \\n flag = False\\n return flag\\n\\nN, M = map(int, input().rstrip().split())\\nresult = 0\\narr = [[0]*M for _ in range(N)]\\ny, x = 0, 0\\ni = 0\\nwhile True:\\n if check_goal(y, x): break\\n arr[y][x] = 1\\n ny, nx = y+dy[i], x+dx[i]\\n if not (0<=ny<N and 0<=nx<M) or arr[ny][nx]:\\n i = (i+1)%4\\n ny, nx = y+dy[i], x+dx[i]\\n result += 1\\n y, x = ny, nx\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.487458199262619,\n \"alphanum_fraction\": 0.5367892980575562,\n \"avg_line_length\": 25.600000381469727,\n \"blob_id\": \"d93a2c9ef1eae9a91d35a61c425c3d58469dd79f\",\n \"content_id\": \"cb2abe94c08ea03fad894c28e015757c199ea403\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1764,\n \"license_type\": \"no_license\",\n \"max_line_length\": 60,\n \"num_lines\": 45,\n \"path\": \"/알고리즘/온라인저지/2022/08/0816/외계인의 기타 연주.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\n\\nN, P = map(int, input().split()) # 놀랍게도 프렛은 영어도 Fret이다\\nstack, result = [[] for _ in range(7)], 0 # 기타줄은 여섯줄 인덱스 맞추기\\nfor n in range(N):\\n S, F = map(int, input().split()) # string, fret\\n if not stack[S]:\\n stack[S].append(F)\\n result += 1\\n else: # stack[S]\\n if F > stack[S][-1]:\\n stack[S].append(F)\\n result += 1\\n elif F < stack[S][-1]:\\n # 같거나 더 낮은 프렛을 만날 때 까지 pop\\n while stack[S] and F < stack[S][-1]:\\n stack[S].pop()\\n result += 1\\n # 누른 손을 모두 떼거나, 더 낮은 프렛을 만났을 경우\\n if not stack[S] or stack[S][-1] < F:\\n stack[S].append(F)\\n result += 1\\n else: # F == stack[-1]\\n pass\\nprint(result)\\n\\n\\\"\\\"\\\"\\n예제 1번처럼 8 10 12 10 5 를 연주할 때\\n실제로 외계인처럼 누른다면\\n현실에선 5 8 10 12 -12 -10 -8 순으로 눌렀다 떼며 답이 7이 된다\\n하지만 입력 순서상 5는 맨 뒤에 있으므로\\n8을 입력받는 시점에서 5를 동시에 눌러도 되는지 알 방법이 없다\\n때문에 컴퓨터적으로 사고하여, 마지막에 5를 추가하여도\\n앞에서 눌렀던 셈 치는 코드가 필요하다\\n위 코드는 아래 순서로 스택에 들어간다\\n<8 10 12 -12 -10 -8 5>\\n\\n그리고 P의 범위가 300,000 이면서, 시간이 1초이므로\\n50만줄의 입력을 받으면서 30만줄의 for문을 돌며\\n다음 프렛을 찾아 인덱스를 1씩 다르게 하면서 탐색하면\\n아마 시간초과가 날 것이다\\n어떻게든, 스택에 넣은 값 자체를 특정할 방법이 필요하다\\n\\\"\\\"\\\"\"\n },\n {\n \"alpha_fraction\": 0.5530864000320435,\n \"alphanum_fraction\": 0.5679012537002563,\n \"avg_line_length\": 27.928571701049805,\n \"blob_id\": \"e6a730bc96ba79ef86cdf08137bed6de339a839e\",\n \"content_id\": \"56f0f9ed81e97092fc3e4de814dd163fef478223\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 599,\n \"license_type\": \"no_license\",\n \"max_line_length\": 49,\n \"num_lines\": 14,\n \"path\": \"/알고리즘/온라인저지/2022/07/0701/국영수.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"arr = [] # 성적표 배열\\nfor n in range(int(input())):\\n tmp = input().split() # 성적을 입력받아서\\n for i in range(4): # 성적을 int형으로 변환\\n try: tmp[i] = int(tmp[i])\\n except: pass\\n arr.append(tmp) # 성적표에 추가\\n\\\"\\\"\\\"\\nlambda에서 정렬 자체를 역순서로 할 수는 없지만\\n숫자의 경우 값을 음수(-)로 만들어주어 역정렬을 할 수 있음\\n\\\"\\\"\\\"\\narr.sort(key=lambda x:(-x[1], x[2], -x[3], x[0]))\\n# 국어는 내림차순, 영어는 오름차순, 수학은 내림차순, 이름은 오름차순\\nfor a in arr: print(a[0]) # 출력\\n\"\n },\n {\n \"alpha_fraction\": 0.4117647111415863,\n \"alphanum_fraction\": 0.4313725531101227,\n \"avg_line_length\": 11.875,\n \"blob_id\": \"27953f7bacf33bfd49c55f8cd077f9bc44426fbe\",\n \"content_id\": \"2d7b633b75247fd53bbc973b58aba81054a78612\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 102,\n \"license_type\": \"no_license\",\n \"max_line_length\": 35,\n \"num_lines\": 8,\n \"path\": \"/알고리즘/온라인저지/2022/04/0420/Do Not Touch Anything.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"R, C, N = map(int, input().split())\\nA = R//N\\nB = C//N\\nif R%N:\\n A += 1\\nif C%N:\\n B += 1\\nprint(A*B)\"\n },\n {\n \"alpha_fraction\": 0.4895104765892029,\n \"alphanum_fraction\": 0.503496527671814,\n \"avg_line_length\": 10.076923370361328,\n \"blob_id\": \"ff6702f9bd9c541e47518944a4afe8f5d30baa52\",\n \"content_id\": \"56e7f3aaedc20022e5747e268b7c4a49c5eb81f1\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 143,\n \"license_type\": \"no_license\",\n \"max_line_length\": 38,\n \"num_lines\": 13,\n \"path\": \"/알고리즘/온라인저지/2022/02/0205/개수 세기.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = int(input())\\n\\nnums = list(map(int, input().split()))\\n\\nv = int(input())\\n\\ncnt = 0\\n\\nfor n in nums:\\n if n == v:\\n cnt += 1\\n\\nprint(cnt)\"\n },\n {\n \"alpha_fraction\": 0.4139534831047058,\n \"alphanum_fraction\": 0.43255814909935,\n \"avg_line_length\": 10.368420600891113,\n \"blob_id\": \"203df9bd5c722c2a01dcf2c1ba965b08869761df\",\n \"content_id\": \"8306c95e2519b1c9d869cd48f2b8c2440baebc3a\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 215,\n \"license_type\": \"no_license\",\n \"max_line_length\": 23,\n \"num_lines\": 19,\n \"path\": \"/알고리즘/온라인저지/2023/04/0429/골뱅이 찍기 - ㅂ.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"A, B = '', ''\\nN = int(input())\\nB = '@'*N*5\\nA = '@'*N+' '*N*3+'@'*N\\nfor _ in range(N*2):\\n print(A)\\nfor _ in range(N):\\n print(B)\\nfor _ in range(N):\\n print(A)\\nfor _ in range(N):\\n print(B)\\n\\n\\\"\\\"\\\"\\nN*2\\nN\\nN\\nN\\n\\\"\\\"\\\"\"\n },\n {\n \"alpha_fraction\": 0.5045045018196106,\n \"alphanum_fraction\": 0.5180180072784424,\n \"avg_line_length\": 19.272727966308594,\n \"blob_id\": \"7259ab5a0266e03c755b7ba4e385b478d1ea84ae\",\n \"content_id\": \"658cfca99f77129d49ca9c5aefbd719ecf0bad2a\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 268,\n \"license_type\": \"no_license\",\n \"max_line_length\": 41,\n \"num_lines\": 11,\n \"path\": \"/알고리즘/온라인저지/2022/05/0515/9진수.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"def solution(n, q):\\n rev_base = ''\\n\\n while n > 0:\\n n, mod = divmod(n, q)\\n rev_base += str(mod)\\n\\n return rev_base[::-1] \\n # 역순인 진수를 뒤집어 줘야 원래 변환 하고자하는 base가 출력\\n \\nprint(solution(int(input()), 9))\"\n },\n {\n \"alpha_fraction\": 0.5092024803161621,\n \"alphanum_fraction\": 0.5153374075889587,\n \"avg_line_length\": 19.5,\n \"blob_id\": \"f507a01a3e564b4ecadfa739fe964a692341cf00\",\n \"content_id\": \"e250fb777eb523ecd0fbdda35b2fd2a87aca0a4b\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 163,\n \"license_type\": \"no_license\",\n \"max_line_length\": 44,\n \"num_lines\": 8,\n \"path\": \"/알고리즘/온라인저지/2022/07/0718/스네이크버드.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N, L = map(int, input().split())\\nF = list(map(int, input().split())) # fruits\\nF.sort()\\n# print(F)\\nfor i in range(len(F)):\\n if L >= F[i]:\\n L += 1\\nprint(L)\"\n },\n {\n \"alpha_fraction\": 0.3952000141143799,\n \"alphanum_fraction\": 0.4607999920845032,\n \"avg_line_length\": 23.076923370361328,\n \"blob_id\": \"e64a9cf0bad1968308abb2d0c09ae1669ed3578a\",\n \"content_id\": \"35432e00413a7350e379792f62638331312a493a\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 839,\n \"license_type\": \"no_license\",\n \"max_line_length\": 44,\n \"num_lines\": 26,\n \"path\": \"/알고리즘/온라인저지/2022/07/0701/다음 순열.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = int(input())\\nM = list(map(int, input().split()))\\nfind = False\\n\\\"\\\"\\\"\\nex) 1 2 3 5 4\\n1. 뒤에서부터 숫자 두개씩 비교하다가\\n2. 뒤에 숫자(5)가 앞에 숫자(3)보다 클 때\\n3. 다시 맨 뒤에서부터 시작하여\\n4. 2에서 비교하여 더 작았던 앞에 숫자(3)보다 큰 수(4)를 찾으면\\n5. 둘(3, 4)의 자리를 바꿔줌 (1 2 3 5 4 -> 1 2 4 5 3)\\n6. 찾았던 앞의 숫자보다 큰 수(4)의 뒤쪽을 오름차순 정렬\\n7. 앞부분과 정렬된 뒷부분을 붙여서 출력\\n\\\"\\\"\\\"\\nfor i in range(N-1, 0, -1):\\n if M[i-1] < M[i]:\\n for j in range(N-1, 0, -1):\\n if M[i-1] < M[j]:\\n M[i-1], M[j] = M[j], M[i-1]\\n M = M[:i] + sorted(M[i:])\\n find = True\\n break\\n if find:\\n print(*M)\\n break\\nif not find:\\n print(-1)\"\n },\n {\n \"alpha_fraction\": 0.4789915978908539,\n \"alphanum_fraction\": 0.4789915978908539,\n \"avg_line_length\": 17.384614944458008,\n \"blob_id\": \"8074689f4ae5b2edcb3a8d64bf2847a50000c767\",\n \"content_id\": \"eea30838651b793d58bd3eeddf644a2fe5c1d848\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 238,\n \"license_type\": \"no_license\",\n \"max_line_length\": 29,\n \"num_lines\": 13,\n \"path\": \"/알고리즘/온라인저지/2022/07/0722/問題 ２.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = int(input())\\nC = dict() # change\\nfor n in range(N):\\n a, b = input().split()\\n C[a] = b\\n# print(C)\\nM = int(input())\\nfor m in range(M):\\n tmp = input()\\n try:\\n print(C[tmp], end='')\\n except:\\n print(tmp, end='')\"\n },\n {\n \"alpha_fraction\": 0.5716292262077332,\n \"alphanum_fraction\": 0.608146071434021,\n \"avg_line_length\": 34.650001525878906,\n \"blob_id\": \"bb0629795a0b51670cc09952b4bdf91ce479881f\",\n \"content_id\": \"5ce30a4eea87a21da6c806f5af0ccf381931c804\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 946,\n \"license_type\": \"no_license\",\n \"max_line_length\": 107,\n \"num_lines\": 20,\n \"path\": \"/알고리즘/[템플릿]/BFS/돌다리.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from collections import deque\\n\\nA, B, N, M = map(int, input().split())\\nQ = deque() # BFS\\nQ.append((N, 0)) # 시작점, 초기 이동횟수\\nresult = 0\\nvisited = [0] * 100001 # 돌다리 방문배열\\nwhile Q: # 항상 도달할 수 있는 경우만 주어짐\\n now, move = Q.popleft() # 현재 위치, 현재까지 이동한 횟수\\n if visited[now]: continue # 방문한 적이 있는 돌다리면 continue\\n visited[now] = 1 # 현재 돌다리를 방문함\\n if now == M: # 목적지에 도착했을 때\\n result = move # result = 가지고 있는 이동횟수\\n break # while문 종료\\n nexts = [now-1, now+1, now-A, now+A, now-B, now+B, now*A, now*B] # 6가지 경우의 다음 이동 돌다리\\n for next in nexts:\\n if 0<=next<=100000 and not visited[next]: Q.append((next, move+1)) # 돌다리 범위를 만족하며, 방문한 적 없는 돌다리 일 때\\nprint(result)\\n\\n# https://www.acmicpc.net/problem/12761\"\n },\n {\n \"alpha_fraction\": 0.27020201086997986,\n \"alphanum_fraction\": 0.30050504207611084,\n \"avg_line_length\": 13.107142448425293,\n \"blob_id\": \"8a2b493d0d8f18f56bcced407938e46ec7a2cba7\",\n \"content_id\": \"166b67762360623e07b0c1664dce0d533c46d062\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 396,\n \"license_type\": \"no_license\",\n \"max_line_length\": 28,\n \"num_lines\": 28,\n \"path\": \"/알고리즘/온라인저지/2022/01/0131/분해합.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = int(input())\\n\\nif N == 1:\\n print(0)\\nelse:\\n t = 0\\n if N >= 100:\\n t = len(str(N)) * 10\\n M = N - t\\n else:\\n M = 1\\n\\n while True:\\n M += 1\\n\\n a = 0\\n\\n for i in str(M):\\n a += int(i)\\n \\n temp = M + a\\n\\n if temp == N:\\n print(M)\\n break\\n elif M == N:\\n print(0)\\n break\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.5116279125213623,\n \"alphanum_fraction\": 0.5193798542022705,\n \"avg_line_length\": 25,\n \"blob_id\": \"92f1ea5be288fb165f1d2a6d7dc4bca694bf866d\",\n \"content_id\": \"63ed72d7ba78b8d3e8a54ca0904235bc0eff6e66\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 129,\n \"license_type\": \"no_license\",\n \"max_line_length\": 36,\n \"num_lines\": 5,\n \"path\": \"/알고리즘/온라인저지/2022/08/0811/영수증.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"X = int(input())\\nfor n in range(int(input())):\\n A, B = map(int, input().split())\\n X -= A*B\\nprint('Yes' if X == 0 else 'No')\"\n },\n {\n \"alpha_fraction\": 0.5787500143051147,\n \"alphanum_fraction\": 0.5912500023841858,\n \"avg_line_length\": 21.25,\n \"blob_id\": \"f6d7040d8c7b10f5f2be29e13d4a4fb8b2ee7688\",\n \"content_id\": \"ba1afa8c9b5126ad93a7418a7417249cc777098b\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1318,\n \"license_type\": \"no_license\",\n \"max_line_length\": 49,\n \"num_lines\": 36,\n \"path\": \"/알고리즘/온라인저지/2022/10/1021/퇴사.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\n\\nN = int(input().rstrip())\\nT, P = [], []\\nfor _ in range(N):\\n a, b = map(int, input().rstrip().split())\\n T.append(a)\\n P.append(b)\\ndp = P[:] + [0] # 최대 수익을 동적으로 기록할 DP테이블\\nfor i in range(N-1, -1, -1): # Top-Down\\n if T[i]+i > N: dp[i] = dp[i+1]\\n else: dp[i] = max(dp[i+1], P[i] + dp[i+T[i]])\\nprint(dp[0])\\n\\n\\\"\\\"\\\"\\ni일에 시작한 일이 근무일을 넘길 경우\\n해당 일은 처리할 수 없고\\n그 다음날의 일 처리량과 동일하다\\n반대로 근무일 안에 끝낼 수 있을 경우\\n그 일을 할 수도 있고 안 할 수도 있는데\\n안 할 경우는 dp[i+1]\\n할 경우는 P[i] + dp[i+T[i]]\\n\\n안 할 경우에 dp[i+1]인 이유는\\n그 일을 하지 않았기 때문에 dp[i]의 일 처리량과 \\n하지 않고 넘어간 다음날인 dp[i+1]의 일 처리량이 동일하다\\n일을 할 경우 P[i]는 일 처리량이고\\ndp[i+T[i]]는 \\n일 처리에 필요한 시간이 경과한 날의 일 처리량이 된다\\n이 경우 시간 안에 일 처리가 가능하므로 \\nP[i]의 일 처리량을 dp[i+T[i]]에 얹은 값을 계산한다\\n그리고 이 둘의 크기를 비교하여 큰 값을 최대 일처리량으로 기록하면서\\n위에서부터 내려오는 Top Down 방식으로 값들을 계산하는 DP문제이다\\n\\\"\\\"\\\"\"\n },\n {\n \"alpha_fraction\": 0.5945945978164673,\n \"alphanum_fraction\": 0.5995085835456848,\n \"avg_line_length\": 17.454545974731445,\n \"blob_id\": \"b7a16541ff899b6ba9782f9071ba9a307bf80b6a\",\n \"content_id\": \"0037be3b9b28282c33058dc545935b136f2d1fe4\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 407,\n \"license_type\": \"no_license\",\n \"max_line_length\": 56,\n \"num_lines\": 22,\n \"path\": \"/알고리즘/온라인저지/2021/12/1219/나는야 포켓몬 마스터 이다솜 딕셔너리.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\nprint(dir(list))\\n\\ndef input():\\n return sys.stdin.readline().rstrip()\\n\\nN, M = map(int, input().split())\\n\\npokemon_by_key = {}\\n\\nfor i in range(1, N+1):\\n pokemon_by_key.update({i:input()})\\n\\nkey_by_pokemon = {v:k for k,v in pokemon_by_key.items()}\\n\\nfor i in range(M):\\n quiz = input()\\n try:\\n print(pokemon_by_key.get(int(quiz)))\\n except:\\n print(key_by_pokemon.get(quiz))\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.34756097197532654,\n \"alphanum_fraction\": 0.46341463923454285,\n \"avg_line_length\": 14,\n \"blob_id\": \"ba97a7dd945e24785657bf6ff0e70fc181c0e252\",\n \"content_id\": \"b40bfc6e287e9a1cc07fb86a4778801d0484fb89\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 164,\n \"license_type\": \"no_license\",\n \"max_line_length\": 32,\n \"num_lines\": 11,\n \"path\": \"/알고리즘/온라인저지/2023/04/0424/푸앙이와 종윤이.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N, M = map(int, input().split())\\na = 100-N\\nb = 100-M\\nc = 100-(a+b)\\nd = a*b\\nq, r = 0, d\\nif d>=100:\\n q = d//100\\n r = d%100\\nprint(a, b, c, d, q, r)\\nprint(c+q, r)\"\n },\n {\n \"alpha_fraction\": 0.5315315127372742,\n \"alphanum_fraction\": 0.5585585832595825,\n \"avg_line_length\": 21.200000762939453,\n \"blob_id\": \"8e194c58ae5422e5c68b9561f10156419d31472c\",\n \"content_id\": \"00b147ee084f780920ce525d3b8b756d2ce2a702\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 111,\n \"license_type\": \"no_license\",\n \"max_line_length\": 35,\n \"num_lines\": 5,\n \"path\": \"/알고리즘/온라인저지/2022/04/0429/고려대학교에는 공식 와인이 있다.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"C, K, P = map(int, input().split())\\nresult = 0\\nfor c in range(1, C+1):\\n result += K*c + P*c*c\\nprint(result)\\n\"\n },\n {\n \"alpha_fraction\": 0.35353535413742065,\n \"alphanum_fraction\": 0.3717171847820282,\n \"avg_line_length\": 34.21428680419922,\n \"blob_id\": \"061029b4a371f1f9012baeb7cdbc008c84452e12\",\n \"content_id\": \"22f4649966cefbd36d3574ac94c518f9bf6a162d\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 619,\n \"license_type\": \"no_license\",\n \"max_line_length\": 73,\n \"num_lines\": 14,\n \"path\": \"/알고리즘/온라인저지/2022/01/0122/에라토스테네스의 체.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"n, K = map(int, input().split()) # 소수를 찾을 범위\\na = [False,False] + [True]*(n-1) # 0 ~ n 까지의 숫자 리스트\\n\\ncnt = 0\\n\\nfor i in range(2,n+1): # 2 ~ n까지 반복\\n if a[i]: # 2부터 시작, 해당 숫자가 지워지지 않고 남아있는 소수라면 \\n for j in range(i, n+1, i): # 해당 소수의 배수들을 \\n if a[j] == False:\\n continue\\n a[j] = False # 리스트에서 전부 False로 만들기\\n cnt += 1\\n if cnt == K:\\n print(j)\\n \\n\"\n },\n {\n \"alpha_fraction\": 0.4202898442745209,\n \"alphanum_fraction\": 0.4492753744125366,\n \"avg_line_length\": 22.33333396911621,\n \"blob_id\": \"17cdb11de8ad3783d9e84e8805c3aefba77aab0d\",\n \"content_id\": \"2dc507afdfedcf9457e5eb6c536ead88e1d3f3c7\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 69,\n \"license_type\": \"no_license\",\n \"max_line_length\": 28,\n \"num_lines\": 3,\n \"path\": \"/알고리즘/온라인저지/2021/08/0822/별 찍기-2.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = int(input())\\nfor n in range(1, N+1):\\n print(' '*(N-n) + '*'*n)\"\n },\n {\n \"alpha_fraction\": 0.5575757622718811,\n \"alphanum_fraction\": 0.5575757622718811,\n \"avg_line_length\": 19.75,\n \"blob_id\": \"f4294d5d6b4de59098ca89d3aba34ddd94a26c94\",\n \"content_id\": \"6a5d45da9a80ba69f44f2ee97726b54a7ed96104\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 165,\n \"license_type\": \"no_license\",\n \"max_line_length\": 34,\n \"num_lines\": 8,\n \"path\": \"/알고리즘/온라인저지/2022/06/0629/단어 정렬.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"arr = []\\nfor i in range(int(input())):\\n tmp = input()\\n if tmp not in arr:\\n arr.append(tmp)\\narr.sort(key=lambda x:(len(x), x))\\nfor a in arr:\\n print(a)\"\n },\n {\n \"alpha_fraction\": 0.5632184147834778,\n \"alphanum_fraction\": 0.5747126340866089,\n \"avg_line_length\": 28.33333396911621,\n \"blob_id\": \"1a06f0853f5266ee5c5b0c9319013d9fd2e53e9b\",\n \"content_id\": \"e60abd7b79ccd82cf48acfb67f5f2ddffdff3bd6\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 87,\n \"license_type\": \"no_license\",\n \"max_line_length\": 56,\n \"num_lines\": 3,\n \"path\": \"/알고리즘/온라인저지/2023/03/0321/chino_shock.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"emoji = input()\\nA, B, C = len(emoji), emoji.count(':'), emoji.count('_')\\nprint(A+B+C*5)\"\n },\n {\n \"alpha_fraction\": 0.4745098054409027,\n \"alphanum_fraction\": 0.4901960790157318,\n \"avg_line_length\": 20.33333396911621,\n \"blob_id\": \"7ea15ac34ef9ca7d47a55a57ff4598a20a00b35c\",\n \"content_id\": \"0b286336f46876208a70ea17495ed87e9909fd46\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 255,\n \"license_type\": \"no_license\",\n \"max_line_length\": 32,\n \"num_lines\": 12,\n \"path\": \"/알고리즘/온라인저지/2022/06/0629/N과 M (3).py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"def comb(scope, depth):\\n for i in range(1, scope+1):\\n result.append(i)\\n if depth == M:\\n print(*result)\\n else:\\n comb(scope, depth+1)\\n result.pop()\\n\\nN, M = map(int, input().split())\\nresult = []\\ncomb(N, 1)\"\n },\n {\n \"alpha_fraction\": 0.542553186416626,\n \"alphanum_fraction\": 0.5957446694374084,\n \"avg_line_length\": 18,\n \"blob_id\": \"c358a177c15233102b38e07c6a3b064a3210b7ae\",\n \"content_id\": \"5c3cc3130797f09fac40523b37ab5a51801c2571\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 94,\n \"license_type\": \"no_license\",\n \"max_line_length\": 28,\n \"num_lines\": 5,\n \"path\": \"/알고리즘/온라인저지/2023/05/0529/Silnia.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = int(input())\\nresult = 1\\nfor i in range(1, N+1):\\n result = (result * i)%10\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.5284237861633301,\n \"alphanum_fraction\": 0.5684754252433777,\n \"avg_line_length\": 21.14285659790039,\n \"blob_id\": \"2108fd8730ec7aabce617c2bd650b3624d7a761b\",\n \"content_id\": \"d8c841403a56129bc00fc191a1699d6b7aad9d55\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 942,\n \"license_type\": \"no_license\",\n \"max_line_length\": 65,\n \"num_lines\": 35,\n \"path\": \"/알고리즘/온라인저지/2022/10/1006/알파벳.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\ndy, dx = [-1, 1, 0, 0], [0, 0, -1, 1]\\n\\ndef idx(char):\\n return ord(char)-65\\n\\ndef dfs(y, x, move):\\n global result\\n result = max(result, move)\\n for i in range(4):\\n ny, nx = y+dy[i], x+dx[i]\\n if 0<=ny<R and 0<=nx<C and not visited[idx(arr[ny][nx])]:\\n visited[idx(arr[ny][nx])] = 1\\n dfs(ny, nx, move+1)\\n visited[idx(arr[ny][nx])] = 0\\n\\nR, C = map(int, input().rstrip().split())\\narr = [list(input().rstrip()) for _ in ' '*R]\\nvisited = [0]*26\\nresult = 0\\nvisited[idx(arr[0][0])] = 1\\ndfs(0, 0, 0)\\nprint(result+1)\\n\\n\\\"\\\"\\\"\\n처음으로 스스로 풀은 DFS문제인 것 같다\\n채점속도가 좀 느려서, 이게 정답이 될 까 걱정이 되었는데\\n신기하게도 정답이었다\\nBFS에서 다음 탐색점을 Q에 넣듯이\\nDFS에서 다음 탐색점을 재귀로 함수를 실행해주는 코드를 짰다\\n\\\"\\\"\\\"\\n\\n# https://www.acmicpc.net/problem/1987\"\n },\n {\n \"alpha_fraction\": 0.5095541477203369,\n \"alphanum_fraction\": 0.5286624431610107,\n \"avg_line_length\": 12.166666984558105,\n \"blob_id\": \"06216a2f0b31a3d73f481036f1f3689354744ac5\",\n \"content_id\": \"c8e691b25d02a00a9ad4e9c6ff0f6eacc64323f7\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 157,\n \"license_type\": \"no_license\",\n \"max_line_length\": 39,\n \"num_lines\": 12,\n \"path\": \"/알고리즘/온라인저지/2022/02/0201/지능형 기차.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"now = 0\\nresult = 0\\n\\nfor t in range(4):\\n off, on = map(int, input().split())\\n\\n now += (on-off)\\n\\n if now > result:\\n result = now\\n\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.5405405163764954,\n \"alphanum_fraction\": 0.5540540814399719,\n \"avg_line_length\": 24,\n \"blob_id\": \"ad398029b41d2da3a29c2af8888bf4db5aba3c32\",\n \"content_id\": \"545a900c46a7c019e3624689f29bbf34b2e061cf\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 74,\n \"license_type\": \"no_license\",\n \"max_line_length\": 43,\n \"num_lines\": 3,\n \"path\": \"/알고리즘/온라인저지/2023/04/0425/세 막대.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"a, b, c = sorted(map(int, input().split()))\\nc = min(a+b-1, c)\\nprint(a+b+c)\"\n },\n {\n \"alpha_fraction\": 0.5180055499076843,\n \"alphanum_fraction\": 0.5401661992073059,\n \"avg_line_length\": 20.294116973876953,\n \"blob_id\": \"39f0691870a91e042aa0eb719eb0081409ed4987\",\n \"content_id\": \"f19df6d5b76809d291dfdd7c9ce74b8a66a2f290\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 361,\n \"license_type\": \"no_license\",\n \"max_line_length\": 56,\n \"num_lines\": 17,\n \"path\": \"/알고리즘/온라인저지/2022/10/1002/주몽.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\n\\nN = int(input().rstrip())\\nM = int(input().rstrip())\\nparts = sorted(list(map(int, input().rstrip().split())))\\ni, j = 0, N-1 # j = len(parts)-1\\nresult = 0\\nwhile i < j:\\n armor = parts[i] + parts[j]\\n if armor > M: j -= 1\\n elif armor < M: i += 1\\n else: # armor == M\\n result += 1\\n i += 1\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.3636363744735718,\n \"alphanum_fraction\": 0.3903743326663971,\n \"avg_line_length\": 18.736841201782227,\n \"blob_id\": \"fb91cec79cb413fbfb77819d88139a8a8c92ffd2\",\n \"content_id\": \"b772bc963ec2c86a938600626ac70de2ab349537\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 374,\n \"license_type\": \"no_license\",\n \"max_line_length\": 43,\n \"num_lines\": 19,\n \"path\": \"/알고리즘/SWEA/LEARN/Course/2. Programming Intermediate/2. 파이썬 SW문제해결 기본 List2/6차시 2일차 - 부분집합의 합.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"A = list(range(1, 12+1))\\n\\nT = int(input())\\n\\nfor t in range(1, T+1):\\n N, K = map(int, input().split())\\n\\n n = len(A)\\n cnt = 0\\n\\n for i in range(1<<n):\\n tmp = set()\\n for j in range(n):\\n if i&(1<<j):\\n tmp.add(A[j])\\n if sum(tmp) == K and len(tmp) == N:\\n cnt += 1\\n \\n print('#{} {}'.format(t, cnt))\"\n },\n {\n \"alpha_fraction\": 0.5641025900840759,\n \"alphanum_fraction\": 0.5641025900840759,\n \"avg_line_length\": 38.33333206176758,\n \"blob_id\": \"4cce9e73830accd3be9ffda20d56baf5b4d74d53\",\n \"content_id\": \"bd80c64d884a281d6f4f3e3780b6cd0261d8c05d\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 117,\n \"license_type\": \"no_license\",\n \"max_line_length\": 50,\n \"num_lines\": 3,\n \"path\": \"/알고리즘/온라인저지/2022/12/1212/No Brainer.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"for _ in range(int(input())):\\n X, Y = map(int, input().split())\\n print('MMM BRAINS' if X >= Y else 'NO BRAINS')\"\n },\n {\n \"alpha_fraction\": 0.5709969997406006,\n \"alphanum_fraction\": 0.5951661467552185,\n \"avg_line_length\": 19.75,\n \"blob_id\": \"1b8501c01b316fa7164780968061f4d469977a32\",\n \"content_id\": \"00c35731198f426cc622a34edef0f905a0504ddd\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 331,\n \"license_type\": \"no_license\",\n \"max_line_length\": 48,\n \"num_lines\": 16,\n \"path\": \"/알고리즘/온라인저지/2022/07/0729/생태학.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\n\\ndct = dict() # tree dict\\nlst = [] # tree list\\ncnt = 0\\nwhile True:\\n tree = input().rstrip() # EOFerror\\n if not tree: break\\n if tree not in lst: lst.append(tree)\\n try: dct[tree] += 1\\n except: dct[tree] = 1\\n cnt += 1\\nlst.sort()\\nfor l in lst: print(f'{l} {dct[l]/cnt*100:.4f}')\"\n },\n {\n \"alpha_fraction\": 0.2801932394504547,\n \"alphanum_fraction\": 0.4202898442745209,\n \"avg_line_length\": 7.666666507720947,\n \"blob_id\": \"63323988debfddaee78c316b13cb184e01a9213c\",\n \"content_id\": \"5a4c742db5d7bf1ea2a261497de4bc949c7c55e6\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 207,\n \"license_type\": \"no_license\",\n \"max_line_length\": 36,\n \"num_lines\": 24,\n \"path\": \"/알고리즘/온라인저지/2022/02/0227/중앙 이동 알고리즘.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"\\\"\\\"\\\"\\n0: 4\\n1: 4+5 = 9\\n2: 9+ \\n\\n4\\n4*4-4-3\\n9*4-8-3\\n\\n\\ndp[i] = dp[i-1] * 4 - (4*i+3)\\n\\\"\\\"\\\"\\n\\nN = int(input())\\n\\ndp = [4]\\n\\ntmp = 4\\n\\nfor i in range(1, N+1):\\n dp.append(dp[i-1] * 4 - (tmp+3))\\n tmp *= 2\\n\\nprint(dp[N])\"\n },\n {\n \"alpha_fraction\": 0.390625,\n \"alphanum_fraction\": 0.41796875,\n \"avg_line_length\": 20.41666603088379,\n \"blob_id\": \"9ce4ab6184a811f534692c36c4041a29c47f4d23\",\n \"content_id\": \"82f6b3471e5948c4e54bfe2cde3b3255a58e1601\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 256,\n \"license_type\": \"no_license\",\n \"max_line_length\": 43,\n \"num_lines\": 12,\n \"path\": \"/알고리즘/[템플릿]/[SAMPLE]/순열.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"def perm(arr, i):\\n if i == len(arr)-1:\\n print(arr)\\n else:\\n for j in range(i, len(arr)):\\n arr[i], arr[j] = arr[j], arr[i]\\n perm(arr, i+1)\\n arr[i], arr[j] = arr[j], arr[i]\\n\\narr = [1, 2, 3, 4]\\n\\nperm(arr, 0)\"\n },\n {\n \"alpha_fraction\": 0.4354838728904724,\n \"alphanum_fraction\": 0.4838709533214569,\n \"avg_line_length\": 27.69230842590332,\n \"blob_id\": \"4384994712fc5fa0bb80eba91bb5822135369efe\",\n \"content_id\": \"360d428d6fbd6914cfee579287d0909925f85eef\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 372,\n \"license_type\": \"no_license\",\n \"max_line_length\": 50,\n \"num_lines\": 13,\n \"path\": \"/알고리즘/온라인저지/2022/12/1220/알파벳 전부 쓰기.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"for _ in range(int(input())):\\n arr = [0]*26\\n for s in input():\\n char = s.lower()\\n if 97 <= ord(char) < 97+26:\\n arr[ord(char)-97] = 1\\n result = 'missing '\\n for i in range(26):\\n if not arr[i]:\\n result = result + chr(i+97)\\n if i == 25 and result != 'missing ': break\\n else: result = 'pangram'\\n print(result)\"\n },\n {\n \"alpha_fraction\": 0.31512194871902466,\n \"alphanum_fraction\": 0.49073171615600586,\n \"avg_line_length\": 17.654544830322266,\n \"blob_id\": \"b81a12e175829dd03bfea8ec38d16255fc844ade\",\n \"content_id\": \"a09448283dafa4c99af9c9eeb112e1bd39535488\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1395,\n \"license_type\": \"no_license\",\n \"max_line_length\": 45,\n \"num_lines\": 55,\n \"path\": \"/알고리즘/온라인저지/2021/10/1003/이진 딸기.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"strawberry = {\\n 0: '0010',\\n 1: '0001',\\n 2: '0010',\\n 3: '0011',\\n 4: '0100',\\n 5: '0101',\\n 6: '0110',\\n 7: '0111',\\n 8: '1000',\\n 9: '1001',\\n 10: '1010',\\n 11: '1011',\\n 12: '1100',\\n 13: '1101',\\n 14: '1110',\\n 15: '1111',\\n 16: '1110',\\n 17: '1101',\\n 18: '1100',\\n 19: '1011',\\n 20: '1010',\\n 21: '1001',\\n 22: '1000',\\n 23: '0111',\\n 24: '0110',\\n 25: '0101',\\n 26: '0100',\\n 27: '0011',\\n}\\n# 이진딸기의 1번째는 VVV딸기 이다\\n# 그리고 쭉 올라갔다가 16부터 내려오는데\\n# 14번 올라가고 14번 내려오는 구조이다\\n# 때문에 28로 나눠준 나머지를 딕셔너리에서 호출하면 문제가 없을 줄 알았는데\\n# 계속 KeyError가 발생했다\\n# 핵심은 딕셔너리의 0번째 VV딸기V\\n# 0번째의 의미는 14번째 내려온 마지막 딸기이고\\n# 그래야 0번째의 다음인 1번째가 VVV딸기 로 다시 순환하는 구조가 된다\\n\\nT = int(input())\\n\\nfor t in range(T):\\n N = int(input()) # N번째 이진딸기는?\\n\\n tmp = strawberry[N%28] # 이진딸기는 28번마다 돌아온다\\n\\n result = '' # 이진수를 V와 딸기로 바꿔줄 result 초기화\\n\\n for m in tmp: # 구한 이진수를 0을 V로, 1을 딸기로\\n if m == '0':\\n result = result + 'V'\\n else:\\n result = result + '딸기'\\n \\n print(result) # 출력\"\n },\n {\n \"alpha_fraction\": 0.4923076927661896,\n \"alphanum_fraction\": 0.5384615659713745,\n \"avg_line_length\": 15.5,\n \"blob_id\": \"3eb675aca58724d68fb67f8e338fbf0763204839\",\n \"content_id\": \"2351068e420af35d7c600af0053eb7969d08dbea\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 65,\n \"license_type\": \"no_license\",\n \"max_line_length\": 32,\n \"num_lines\": 4,\n \"path\": \"/알고리즘/온라인저지/2023/04/0420/Correct.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"H, M = map(int, input().split())\\nH -= 9\\nend = H*60 + M\\nprint(end)\"\n },\n {\n \"alpha_fraction\": 0.4695121943950653,\n \"alphanum_fraction\": 0.4878048896789551,\n \"avg_line_length\": 15.5,\n \"blob_id\": \"93dde88295a4bb46d520d68ff064c2a1feecef08\",\n \"content_id\": \"38980f5ee2a48ab4c2065f60d39cb7740edeef37\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 164,\n \"license_type\": \"no_license\",\n \"max_line_length\": 29,\n \"num_lines\": 10,\n \"path\": \"/알고리즘/온라인저지/2022/06/0621/창영이의 일기장.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"text = input()\\nresult = ''\\ni = 0\\nwhile i < len(text):\\n result = result + text[i]\\n if text[i] in 'aeiou':\\n i += 3\\n else:\\n i += 1\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.4457831382751465,\n \"alphanum_fraction\": 0.45783132314682007,\n \"avg_line_length\": 19.8125,\n \"blob_id\": \"84068a22a874430eae2c5c944d6cdfd30619c888\",\n \"content_id\": \"3505f0d0476c096669a5d6ad11b182972bd6b191\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 332,\n \"license_type\": \"no_license\",\n \"max_line_length\": 33,\n \"num_lines\": 16,\n \"path\": \"/알고리즘/온라인저지/2022/07/0712/FBI.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"FBI = False\\nresult = []\\nfor i in range(1, 6):\\n agent = input()\\n for j in range(len(agent)-2):\\n tmp = agent[j:j+3]\\n # print(tmp, i)\\n if tmp == 'FBI':\\n result.append(i)\\n if not FBI:\\n FBI = True\\n break\\nif FBI:\\n print(*result)\\nelse:\\n print('HE GOT AWAY!')\"\n },\n {\n \"alpha_fraction\": 0.4423791766166687,\n \"alphanum_fraction\": 0.4535315930843353,\n \"avg_line_length\": 15.625,\n \"blob_id\": \"6f7c16d4028512598eabab7441e33063d8601006\",\n \"content_id\": \"5b60554b8961f2fd293049d2922dcd246163c52e\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 269,\n \"license_type\": \"no_license\",\n \"max_line_length\": 36,\n \"num_lines\": 16,\n \"path\": \"/알고리즘/온라인저지/2022/02/0203/세로읽기.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"arr = []\\n\\nmax_len = 0\\n\\nfor _ in range(5):\\n tmp = input()\\n arr.append(tmp)\\n if len(tmp) > max_len:\\n max_len = len(tmp)\\n\\nfor j in range(max_len):\\n for i in range(5):\\n try:\\n print(arr[i][j], end='')\\n except:\\n pass\\n\\n\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.4575471580028534,\n \"alphanum_fraction\": 0.49528300762176514,\n \"avg_line_length\": 33.16666793823242,\n \"blob_id\": \"dcadb0a567a6595d5ee1452cc2a0189a1d8de76e\",\n \"content_id\": \"c751dc85954af198a31d4341b52ffd2c80c2d2bb\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 212,\n \"license_type\": \"no_license\",\n \"max_line_length\": 58,\n \"num_lines\": 6,\n \"path\": \"/알고리즘/온라인저지/2022/08/0805/고급 수학.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = int(input())\\nfor n in range(1, N+1):\\n T = sorted(list(map(int, input().split()))) # triangle\\n print(f'Scenario #{n}:')\\n if T[0]**2 + T[1]**2 == T[2]**2: print('yes\\\\n')\\n else: print('no\\\\n') \"\n },\n {\n \"alpha_fraction\": 0.41310539841651917,\n \"alphanum_fraction\": 0.45868945121765137,\n \"avg_line_length\": 21,\n \"blob_id\": \"02eef63d382e36b2a9fe2a1b068fdf29cd2628e4\",\n \"content_id\": \"f3c6b58474c784056a47322e63510f06f93c0c42\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 351,\n \"license_type\": \"no_license\",\n \"max_line_length\": 38,\n \"num_lines\": 16,\n \"path\": \"/알고리즘/온라인저지/2022/05/0504/문문문.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = int(input())\\nM = int(input())\\nif N < 6:\\n result = []\\n door = [0, 1, 0, 1, 0, 1]\\n door__reverse = [1, 0, 1, 0, 1, 0]\\n if M == 0:\\n for i in door[1:N]:\\n result.append(i)\\n else:\\n for i in door__reverse[1:N]:\\n result.append(i)\\n for r in result:\\n print(r)\\nelse:\\n print('Love is open door')\"\n },\n {\n \"alpha_fraction\": 0.5007451772689819,\n \"alphanum_fraction\": 0.5089418888092041,\n \"avg_line_length\": 28.844444274902344,\n \"blob_id\": \"786d645a26c67e6c19fb89e89208741593fbd1fb\",\n \"content_id\": \"3f7baa6cac484d8096ae7ee5f12f5d56bd4df98d\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 2010,\n \"license_type\": \"no_license\",\n \"max_line_length\": 56,\n \"num_lines\": 45,\n \"path\": \"/알고리즘/온라인저지/2022/01/0116/단어 뒤집기 2.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"sen = input() # 입력\\n\\nword = '' # 단어 혹은 태그\\n\\nresult = [] # 단어 혹은 태그 단위로 짤라서 담을 리스트\\n\\nin_tag = False # 입력값을 돌면서, 현재 스캔중인 단어가 태그인지 확인\\n\\nfor s in sen: # 입력값을 하나씩 순회\\n if s == '<': # 태그의 시작\\n if word: # 단어가 추가되던 중이었으면\\n result.append(word) # 추가중이던 단어를 끊어주고 리스트에 추가\\n word = s # 태그를 담으면서 다시 시작\\n else: # 시작 혹은 바로 앞에서 단어를 끊어줘서 단어가 없는 경우\\n word = word + s # 태그를 담으면서 시작\\n in_tag = True # 태그를 스캔중이므로 True\\n elif s == '>': # 태그의 끝\\n word = word + s # '>'를 담고\\n result.append(word) # 리스트에 태그를 추가\\n word = '' # 단어 초기화\\n in_tag = False # 태그에 담는 것이 종료되었음\\n elif s == ' ' and not in_tag: # 공백이면서 태그에 담는 중이 아닐 때\\n result.append(word) # 태그가 아닌 그냥 단어를 리스트에 담고\\n word = '' # 단어 초기화\\n else: # 단어 혹은 태그를 스캔중\\n word = word + s # 단어에 담아줌\\n\\nif word: # 스캔이 끝난 마지막 단어\\n result.append(word) # 리스트에 추가\\n\\n# 첫번째 단어 출력\\nif result[0][0] == '<': # 태그이면\\n print(result[0], end='') # 그대로 출력\\nelse: # 단어이면\\n print(result[0][::-1], end='') # 뒤집어서 출력\\n \\nfor i in range(1, len(result)): # 두번째 단어부터 끝까지 출력\\n # 이전 단어가 태그가 아니고 지금 단어도 태그가 아니면\\n if result[i-1][0] != '<' and result[i][0] != '<':\\n print(end=' ') # 단어 사이 공백\\n \\n if result[i][0] == '<': # 지금 단어가 태그이면\\n print(result[i], end='') # 그대로 출력\\n else: # 단어이면\\n print(result[i][::-1], end='') # 뒤집어서 출력\"\n },\n {\n \"alpha_fraction\": 0.4285714328289032,\n \"alphanum_fraction\": 0.45864662528038025,\n \"avg_line_length\": 21.16666603088379,\n \"blob_id\": \"1658dd10e7fb802435fb29c7e0d063e06eb5422c\",\n \"content_id\": \"ea17ebb1f085499a5a56a9da762b78d88a2f1d37\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 266,\n \"license_type\": \"no_license\",\n \"max_line_length\": 39,\n \"num_lines\": 12,\n \"path\": \"/알고리즘/온라인저지/2021/08/0804/직각삼각형.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"a, b, c = 1, 1, 1\\nresult = []\\nwhile a + b + c != 0:\\n a, b, c = map(int, input().split())\\n if a + b + c == 0:\\n continue\\n if a**2 + b**2 == c**2:\\n result.append('right')\\n else:\\n result.append('wrong')\\nfor res in result:\\n print(res)\\n\"\n },\n {\n \"alpha_fraction\": 0.4943181872367859,\n \"alphanum_fraction\": 0.5,\n \"avg_line_length\": 34.400001525878906,\n \"blob_id\": \"eb334300f8a8a8cc088ff330ddea0e83074d7b45\",\n \"content_id\": \"65db4c10510e82dac7f462f520ebf386f6c69b51\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 176,\n \"license_type\": \"no_license\",\n \"max_line_length\": 49,\n \"num_lines\": 5,\n \"path\": \"/알고리즘/온라인저지/2023/02/0220/페르시아의 왕들.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"while True:\\n a, b, c, d = map(int, input().split())\\n if a == b == c == d == 0: break\\n result = list(map(abs, [a-c, a-d, b-c, b-d]))\\n print(min(result), max(result))\"\n },\n {\n \"alpha_fraction\": 0.40454545617103577,\n \"alphanum_fraction\": 0.5068181753158569,\n \"avg_line_length\": 26.5625,\n \"blob_id\": \"ff4979ad8153e978225ba7a802e2ddd0b4e0d396\",\n \"content_id\": \"85d9292fdababfd5ce85ccaba5f092e4c1194f9f\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 440,\n \"license_type\": \"no_license\",\n \"max_line_length\": 82,\n \"num_lines\": 16,\n \"path\": \"/알고리즘/온라인저지/2022/07/0731/이름 궁합.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# stroke\\nS = [3, 2, 1, 2, 3, 3, 2, 3, 3, 2, 2, 1, 2, 2, 1, 2, 2, 2, 1, 2, 1, 1, 1, 2, 2, 1]\\nname1 = input()\\nname2 = input()\\nfor n in name1:\\n tmp = ord(n)-65\\narr = []\\nfor i in range(len(name1)):\\n arr.append(S[ord(name1[i])-65])\\n arr.append(S[ord(name2[i])-65])\\nfor i in range(len(arr)-2):\\n tmp = [0] * (len(arr)-1)\\n for j in range(len(arr)-1):\\n tmp[j] = (arr[j]+arr[j+1])%10\\n arr = tmp\\nfor a in arr: print(a, end='')\"\n },\n {\n \"alpha_fraction\": 0.4482758641242981,\n \"alphanum_fraction\": 0.4482758641242981,\n \"avg_line_length\": 29,\n \"blob_id\": \"65755037053fe2641595e2b65032c463e4f2a3ea\",\n \"content_id\": \"51ae396b233e359eecdeb7ed9e3e6015e9de53b2\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 29,\n \"license_type\": \"no_license\",\n \"max_line_length\": 29,\n \"num_lines\": 1,\n \"path\": \"/알고리즘/온라인저지/2022/02/0202/10926.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"print(input(), '??!', sep='')\"\n },\n {\n \"alpha_fraction\": 0.47012731432914734,\n \"alphanum_fraction\": 0.48481881618499756,\n \"avg_line_length\": 30.9375,\n \"blob_id\": \"ae7b01266b37342a33029e99aa49457af6cc73f7\",\n \"content_id\": \"04b86364e9567f0cdab6949218ed5fe73a24f614\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1247,\n \"license_type\": \"no_license\",\n \"max_line_length\": 55,\n \"num_lines\": 32,\n \"path\": \"/알고리즘/온라인저지/2022/04/0426/맥주 마시면서 걸어가기.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\nfrom collections import deque\\ninput = sys.stdin.readline\\n\\ndef bfs():\\n q = deque()\\n q.append([home[0], home[1]]) # 집에서부터\\n while q: # 갈 수 있는 편의점이 있는 동안\\n x, y = q.popleft() # 출발\\n # 목적지에 도착할 수 있으면\\n if abs(x - goal[0]) + abs(y - goal[1]) <= 1000:\\n print(\\\"happy\\\") # 축제에 갈 수 있다\\n return # 축제에 갈 수 있으므로 코드 종료\\n for i in range(N): # N개의 편의점 중\\n if not visited[i]: # 간 적 없는 편의점\\n nx, ny = store[i] # 편의점의 좌표\\n # 갈 수 있는 편의점이면\\n if abs(x - nx) + abs(y - ny) <= 1000:\\n q.append((nx, ny)) # 편의점 좌표 추가\\n visited[i] = 1 # 편의점 방문처리\\n print(\\\"sad\\\") # 다 돌아도 못갔네 ㅠㅠ\\n return\\n\\nfor t in range(int(input())):\\n N = int(input())\\n home = list(map(int, input().split()))\\n store = []\\n for i in range(N): # N개의 편의점\\n store.append(tuple(map(int, input().split())))\\n goal = list(map(int, input().split()))\\n visited = [0 for _ in range(N+1)] #home 제외\\n bfs() # 집부터 출발\"\n },\n {\n \"alpha_fraction\": 0.49082568287849426,\n \"alphanum_fraction\": 0.5229358077049255,\n \"avg_line_length\": 14.642857551574707,\n \"blob_id\": \"d1793eb3a256c98d0d4d964c94bbeb59984bc905\",\n \"content_id\": \"7cbf1e0b5698b0a1ff5625602bcd0f834822bc08\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 218,\n \"license_type\": \"no_license\",\n \"max_line_length\": 38,\n \"num_lines\": 14,\n \"path\": \"/알고리즘/온라인저지/2022/03/0303/3 つの整数 (Three Integers).py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"nums = list(map(int, input().split()))\\n\\nmaxx = 0\\nresult = 0\\n\\ndp = [0] * 101\\n\\nfor i in range(len(nums)):\\n dp[nums[i]] += 1\\n if dp[nums[i]] > maxx:\\n maxx = dp[nums[i]]\\n result = nums[i]\\n\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.36567163467407227,\n \"alphanum_fraction\": 0.4029850661754608,\n \"avg_line_length\": 9.307692527770996,\n \"blob_id\": \"9f5addd664048bdc94fb450d53bdc1456d1b5623\",\n \"content_id\": \"539d8f05fe3151e4f1237dba61b42aead6f2ede6\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 134,\n \"license_type\": \"no_license\",\n \"max_line_length\": 20,\n \"num_lines\": 13,\n \"path\": \"/알고리즘/온라인저지/2022/01/0131/별 찍기 - 13.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = int(input())\\n\\ni = 1\\n\\nfor n in range(N):\\n print('*' * i)\\n i += 1\\n\\ni -= 1\\n\\nfor n in range(N-1):\\n i -= 1\\n print('*' * i)\\n\"\n },\n {\n \"alpha_fraction\": 0.5736196041107178,\n \"alphanum_fraction\": 0.5858895778656006,\n \"avg_line_length\": 22.35714340209961,\n \"blob_id\": \"50ffdc2329f799fb580123515896053517243ee1\",\n \"content_id\": \"b59fc2983b85993026aa08a64effb612946b710b\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 326,\n \"license_type\": \"no_license\",\n \"max_line_length\": 52,\n \"num_lines\": 14,\n \"path\": \"/알고리즘/온라인저지/2022/10/1021/Base Conversion.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\n\\nA, B = map(int, input().rstrip().split())\\nM = int(input().rstrip())\\narr = list(map(int, input().rstrip().split()))[::-1]\\nnum = 0\\nfor i in range(M): num += A**i*arr[i]\\nbase = 1\\nwhile base*B < num: base *= B\\nwhile base >= 1:\\n print(num//base, end=' ')\\n num, base = num%base, base//B\"\n },\n {\n \"alpha_fraction\": 0.5883134007453918,\n \"alphanum_fraction\": 0.6095617413520813,\n \"avg_line_length\": 25,\n \"blob_id\": \"dfbe9f83925dfca4a2bc17c77991267c91d9b191\",\n \"content_id\": \"5df77e2a65b40d704d7b42ab10918c1692c79ad5\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1125,\n \"license_type\": \"no_license\",\n \"max_line_length\": 66,\n \"num_lines\": 29,\n \"path\": \"/알고리즘/온라인저지/2022/08/0805/입국심사.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\n\\nN, M = map(int, input().split())\\ntime = sorted(list(int(input()) for _ in range(N)))\\nstart = 0\\n# time의 최소값 * 사람 수 => 최대 시간 \\nend = min(time) * M # Worst Case : 모든 입국 심사자가 1번 심사대를 통과하려고 떼쓰는 경우\\nresult = 0\\nwhile start <= end :\\n mid = (start + end) // 2\\n I = 0 # immigration : 입국심사\\n for t in time: I += mid // t # mid초 동안 심사대를 통과할 수 있는 사람 수\\n if I >= M: # mid초 동안 M명 이상 심사대를 통과할 수 있음\\n end = mid-1 # 더 작은 시간 탐색\\n result = mid # 매개 변수 탐색 : 최소값 저장\\n else: start = mid+1 # mid초 동안 M명 이상 심사대를 통과할 수 없음\\nprint(result)\\n\\n\\\"\\\"\\\"\\n시간을 기준으로 이분탐색한다\\n예제1같이 28초의 경우, 1번 심사대가 4명을 심사한다\\n\\\"이번 mid초 동안 몇명이 심사대를 통과할 수 있는가\\\"를 확인하여\\nstart<=end 인 동안 M명을 심사할 수 있는 시간초를\\n이분탐색으로 줄여나간다\\n\\\"\\\"\\\"\\n\\n# https://www.acmicpc.net/problem/3079\"\n },\n {\n \"alpha_fraction\": 0.4375,\n \"alphanum_fraction\": 0.5071428418159485,\n \"avg_line_length\": 24.5,\n \"blob_id\": \"3b7ac71da6cfe9bb043ce6ab0649f76aefa6e35c\",\n \"content_id\": \"233bbf1b7d284f843c7da65fb83ebe712e31d0a6\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 560,\n \"license_type\": \"no_license\",\n \"max_line_length\": 61,\n \"num_lines\": 22,\n \"path\": \"/알고리즘/[템플릿]/문자열 탐색/Boyer Moore.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import timeit\\nstart = timeit.default_timer()\\n\\ntext = 'aawneifonoeiwmcl,xjfklsajdfklajewklfhaefnk1r7e8yiueniuencieh02cf12fh0v3ymn,cgjklo10f321hcqvyjkn9og4ml0f21hc3v9yjknqom0h1vcf2y93njkmof210hc3v9jkoymn0f21hcvko9jnym021hfok9cqv3jln,210hf9ocv3jklmny,qgf21h0kmn,jlocqv39cf30hkv9mn,ojlgfvc0hkx12mn,jol9210cf3hk9qvomn,jl10fh9cv3okjmn,g10cf3hv9knom0f9h3koncvm,02f1h9kcv3omn,j2f103vhc9knmjog0f2h19kncv3jmoyg0f21h9cv3njkgmoy0fh921ojkymncgv3,rlf21h0c3v9nyjkmgoh0n9f2yjkmcv13g4h0f21c3vn9kmjyg0hf219ncvjkm3og0f21hc3v9mnjky,o0f21hcvn9km3jy0h1vcf2nk9mj3021hnkf9m,cv3jhf210ncv3mjk9h0f219nycv3jkg0h9f21nycv3jk0h9f21nycv3kjg0fh219mnjkcv3,yogf20h1v3n9cg4kmf0h2913vcgf3210cvh9g4n20f31h9cvnkgf02h9c13vngtkr40fh921nkcvm30hn9kfmcv3h0nf1mk,j9cv3gf,mn12v0chkljox30cf21hkv3mn,9of0cmn,hkvjlo390hk9omnj,2f13vc0h9nk1mojfc3v0h9n12cfkmv3021h9cfnvyh0nf29kmcv13jh29fn1kmcv30f2h91ncvkm30h92nkf1mcv3o0h9f21nkmocv,30h9nk2fmcv130h9fknc12v30h9nk12fmcv320hc9f1nvk30f2h9c1vnkm30h9fnkc1vh9nkmjof12cv30h9fnkmcv12o,30h9f21nkcvmx30hf9n12ckv30h9nfkmc12v30hk9n,mfjloc1v0fh912vcnk3mh9f12vcn30h9nkcf12v30hf2n91mcv0hnf9c12v3h0n9mkj2cfv130h9nfc12v30h9fnkcv12m3gf219hcvn3kg0f21h9cvn3f219hcvk3nf021h9cnv39hf21cv30h9nf2c1vg3h09n1f2ycvg30h9fnc12vy8g3df09h2c1vg30h98y7nfcv213gh0987yfv2c13h0987yf2cv13ghy0987ncfv123h09872fyv134chyf7098cv2g09h87fv2cg13hy67098cv12gh09f21ycv3g4h09y87f12v3cg0h9821vc309h8f12cv309hfcv09hn12vcx309hn1f2cv30h9nf12cv30hn1cf2'\\npattern = 'cx309hn1f2cv30h9'\\nresult = 0\\nfor i in range(len(pattern)-1, len(text)):\\n if text[i] == pattern[-1]:\\n j = 2\\n while True:\\n if pattern[-j] == text[i-j+1]:\\n if pattern[-j] == pattern[0]:\\n result = 1\\n break\\n else:\\n j += 1\\n else:\\n break\\nprint(result)\\n\\nend = timeit.default_timer()\\nprint(f'{end-start:.5f}')\"\n },\n {\n \"alpha_fraction\": 0.41304346919059753,\n \"alphanum_fraction\": 0.43478259444236755,\n \"avg_line_length\": 12.214285850524902,\n \"blob_id\": \"ffcae2b2ea2bd33339f2b2c3bddbd8f677e1b196\",\n \"content_id\": \"cd9fcff1e7d6f32499dac4c28a97511849274d99\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 184,\n \"license_type\": \"no_license\",\n \"max_line_length\": 17,\n \"num_lines\": 14,\n \"path\": \"/알고리즘/온라인저지/2023/03/0301/Serious Problem.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"result = 'yee'\\ninput()\\nA = B = 0\\nfor i in input():\\n try:\\n int(i)\\n A += 1\\n except:\\n B += 1\\nif A > B:\\n result = 2\\nelif A < B:\\n result = 'e'\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.4534534513950348,\n \"alphanum_fraction\": 0.462462455034256,\n \"avg_line_length\": 21.200000762939453,\n \"blob_id\": \"40e375e89993ca1942025715ea253267fc8551b8\",\n \"content_id\": \"5409bf21be262397c0d4c974e508471a782fb264\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 333,\n \"license_type\": \"no_license\",\n \"max_line_length\": 40,\n \"num_lines\": 15,\n \"path\": \"/알고리즘/온라인저지/2022/07/0720/사탕.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"T = int(input())\\nfor t in range(T):\\n J, N = map(int, input().split())\\n boxes = []\\n for n in range(N):\\n R, C = map(int, input().split())\\n boxes.append(R*C)\\n boxes.sort(reverse=True)\\n result = 0\\n for b in boxes:\\n result += 1\\n J -= b\\n if J <= 0: \\n break\\n print(result)\\n\"\n },\n {\n \"alpha_fraction\": 0.5605095624923706,\n \"alphanum_fraction\": 0.5700637102127075,\n \"avg_line_length\": 16.5,\n \"blob_id\": \"0bcf0d9dff5fe7298f0c4c2ec8fc06926f08a53f\",\n \"content_id\": \"884814b5d254ce909297348cecb5fdbe91365a38\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 314,\n \"license_type\": \"no_license\",\n \"max_line_length\": 40,\n \"num_lines\": 18,\n \"path\": \"/알고리즘/온라인저지/2021/12/1219/나는야 포켓몬 마스터 이다솜.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ndef input():\\n return sys.stdin.readline().rstrip()\\n\\nN, M = map(int, input().split())\\n\\npokemon = ['' for _ in range(N+1)]\\n\\nfor i in range(1, N+1):\\n pokemon[i] = input()\\n\\nfor i in range(M):\\n quiz = input()\\n try:\\n print(pokemon[int(quiz)])\\n except:\\n print(pokemon.index(quiz))\"\n },\n {\n \"alpha_fraction\": 0.5,\n \"alphanum_fraction\": 0.5666666626930237,\n \"avg_line_length\": 30,\n \"blob_id\": \"ae6ce872f24bc84ec03d94cba203a17771d16183\",\n \"content_id\": \"3a01f41c7c43067ff8cb734d3515164593d6617f\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 30,\n \"license_type\": \"no_license\",\n \"max_line_length\": 30,\n \"num_lines\": 1,\n \"path\": \"/알고리즘/온라인저지/2023/05/0518/Metronome.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"print(f'{int(input())/4:.2f}')\"\n },\n {\n \"alpha_fraction\": 0.5620437860488892,\n \"alphanum_fraction\": 0.5620437860488892,\n \"avg_line_length\": 9.538461685180664,\n \"blob_id\": \"4cf8c09ae7960615c4e93b074666fc75788e6757\",\n \"content_id\": \"af0b0129450d154c35f65fb94a8c3412f0f6110f\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 137,\n \"license_type\": \"no_license\",\n \"max_line_length\": 23,\n \"num_lines\": 13,\n \"path\": \"/알고리즘/온라인저지/2022/02/0220/유학 금지.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"\\\"\\\"\\\"\\nCAMBRIDGE\\n\\\"\\\"\\\"\\n\\nCAMBRIDGE = \\\"CAMBRIDGE\\\"\\n\\ntext = input()\\n\\nfor t in text:\\n if t in CAMBRIDGE:\\n continue\\n\\n print(t, end='')\\n\"\n },\n {\n \"alpha_fraction\": 0.6423357725143433,\n \"alphanum_fraction\": 0.6496350169181824,\n \"avg_line_length\": 21.83333396911621,\n \"blob_id\": \"25dec903ad9b237344443376aeb8357521268347\",\n \"content_id\": \"ee3b5143d6677a78558dee9a5c3e266882fc0a2f\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 137,\n \"license_type\": \"no_license\",\n \"max_line_length\": 70,\n \"num_lines\": 6,\n \"path\": \"/알고리즘/온라인저지/2022/09/0927/수 정렬하기 4.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\n\\nN = int(input().rstrip())\\nfor i in sorted([int(input()) for _ in [0]*N], reverse=True): print(i)\\n\"\n },\n {\n \"alpha_fraction\": 0.356890469789505,\n \"alphanum_fraction\": 0.5088339447975159,\n \"avg_line_length\": 14.666666984558105,\n \"blob_id\": \"aeecd25ecb028a7c2365763e459744c7a103d160\",\n \"content_id\": \"8b66caccc86483bbaac78a69a634cd3700783891\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 315,\n \"license_type\": \"no_license\",\n \"max_line_length\": 42,\n \"num_lines\": 18,\n \"path\": \"/알고리즘/SWEA/LEARN/Course/1. Programming Beginner/파이썬 프로그래밍 기초(2)/28차시 3. 자료구조 – 셋, 딕셔너리 - 연습문제 3.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"data = {\\n \\\"TV\\\": 2000000,\\n \\\"냉장고\\\": 1500000,\\n \\\"책상\\\": 350000,\\n \\\"노트북\\\": 1200000,\\n \\\"가스레인지\\\": 200000,\\n \\\"세탁기\\\": 1000000,\\n}\\n\\ntmp = []\\n\\nfor d in data:\\n tmp.append((d, data[d]))\\n\\ntmp.sort(key=lambda x: x[1], reverse=True)\\n\\nfor t in tmp:\\n print('{}: {}'.format(t[0], t[1]))\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.43852460384368896,\n \"alphanum_fraction\": 0.5204917788505554,\n \"avg_line_length\": 23.5,\n \"blob_id\": \"d8c02b23a1fca34cd56c7fa838e04c0cfd921aea\",\n \"content_id\": \"2f33f623c8d764324547bfb1400d9a5dcc0f06f0\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 328,\n \"license_type\": \"no_license\",\n \"max_line_length\": 34,\n \"num_lines\": 10,\n \"path\": \"/알고리즘/온라인저지/2022/04/0417/영화감독 숌.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = int(input())\\ncnt = 0 # 몇번째 666인가\\nsix3 = 666 # 666부터 출발\\nwhile True:\\n if '666' in str(six3): # 종말숫자면\\n cnt += 1 # 카운트 +1\\n if cnt == N: # N번째 종말숫자면\\n print(six3) # 값을 출력\\n break # while문 종료\\n six3 += 1 # 다음 숫자는 종말숫자인가\"\n },\n {\n \"alpha_fraction\": 0.5828220844268799,\n \"alphanum_fraction\": 0.5828220844268799,\n \"avg_line_length\": 19.5,\n \"blob_id\": \"57349ba4ebc810e5a39c9ebba1996660e8bcc571\",\n \"content_id\": \"0a230881870fde291ae6ce511324df1e28564e1e\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 163,\n \"license_type\": \"no_license\",\n \"max_line_length\": 74,\n \"num_lines\": 8,\n \"path\": \"/알고리즘/온라인저지/2021/12/1216/배열 합치기.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N, M = map(int, input().split())\\n\\nresult = list(map(int, input().split())) + list(map(int, input().split()))\\n\\nresult.sort()\\n\\nfor r in result:\\n print(r, end=' ')\"\n },\n {\n \"alpha_fraction\": 0.65625,\n \"alphanum_fraction\": 0.65625,\n \"avg_line_length\": 20.27777862548828,\n \"blob_id\": \"615b8cd9e0d514fbb85db3d79476159cb87492d4\",\n \"content_id\": \"6c6d32a70084ea885405874a6ce436bec54d6565\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 808,\n \"license_type\": \"no_license\",\n \"max_line_length\": 52,\n \"num_lines\": 18,\n \"path\": \"/README.md\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# Just Do It \\n\\n# 목표\\n\\n- 배운 내용들을 매일 기록\\n- 覚えた内容を毎日記録する\\n- Note that I studied today for everyday\\n\\n# 쉴 때 보기 좋은 명언들\\n\\n- 건강한 몸에 건강한 정신이 깃든다\\n- 하루를 쉬면 메꾸는 데에 삼일이 걸린다\\n- 해결할 수 있는 일은 고민하지 말고 하면 되고, 해결할 수 없는 일은 고민해도 소용이 없다\\n- 우생마사 : 장마비에 떠내려가는, 소는 가만히 있다가 살고, 말은 발버둥치다가 죽는다\\n- 노력이란, 보이지 않는 곳에서 나만 알게 아무도 모르게 하는 것을 말한다\\n- 뭘 해야할지, 뭐가 하고 싶은지 모르겠을 땐, 내일 죽는 상상을 해라\\n- 완벽하고자 하는 생각이, 모든 일을 시작조차 할 수 없게 만든다\\n- \\n\"\n },\n {\n \"alpha_fraction\": 0.529411792755127,\n \"alphanum_fraction\": 0.5459558963775635,\n \"avg_line_length\": 20.799999237060547,\n \"blob_id\": \"f56e43d383e12710c160419ba79b493029795abb\",\n \"content_id\": \"dd6eb87d5b53d1d6980d15e3b29eddd388acf63f\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 588,\n \"license_type\": \"no_license\",\n \"max_line_length\": 58,\n \"num_lines\": 25,\n \"path\": \"/알고리즘/온라인저지/2023/01/0107/공유기 설치.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"def install_wifi(distance):\\n prev = houses[0]\\n cnt = 1\\n for house in houses[1:]:\\n if house>=prev+distance:\\n cnt += 1\\n prev = house\\n return cnt\\n\\nN, C = map(int, input().rstrip().split())\\nhouses = sorted([int(input().rstrip()) for _ in range(N)])\\nresult = 0\\nstart, end = result, houses[-1]\\nwhile start<=end:\\n mid = (start + end)//2\\n if install_wifi(mid)>=C:\\n result = max(result, mid)\\n start = mid+1\\n else: \\n end = mid-1\\nprint(result)\\n\\n\\\"\\\"\\\"\\n다음 집을 탐색할 때, 다음 집이 위치한 인덱스만 확인함\\n\\\"\\\"\\\"\"\n },\n {\n \"alpha_fraction\": 0.4517241418361664,\n \"alphanum_fraction\": 0.5103448033332825,\n \"avg_line_length\": 27.700000762939453,\n \"blob_id\": \"ec91fe98ce55b86a0b053d18b3a65926ba84023f\",\n \"content_id\": \"edcfae794bfa825bceda9713217885b3c7d6aff3\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 290,\n \"license_type\": \"no_license\",\n \"max_line_length\": 47,\n \"num_lines\": 10,\n \"path\": \"/알고리즘/온라인저지/2023/02/0211/창영마을.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"orders = input()\\nballs = [1, 0, 0]\\nfor order in orders:\\n if order == 'A':\\n balls[0], balls[1] = balls[1], balls[0]\\n if order == 'B':\\n balls[2], balls[1] = balls[1], balls[2]\\n if order == 'C':\\n balls[0], balls[2] = balls[2], balls[0]\\nprint(balls.index(1)+1) \"\n },\n {\n \"alpha_fraction\": 0.3638676702976227,\n \"alphanum_fraction\": 0.44783714413642883,\n \"avg_line_length\": 18.649999618530273,\n \"blob_id\": \"a192af52606681438f5eb3e7625baa58b3c14c68\",\n \"content_id\": \"3141aa1157817671aba41ef539528d58d47b0d1d\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 393,\n \"license_type\": \"no_license\",\n \"max_line_length\": 40,\n \"num_lines\": 20,\n \"path\": \"/알고리즘/온라인저지/2022/03/0317/전자레인지.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"n = [int(input()) for _ in range(5)]\\n# print(n)\\n\\\"\\\"\\\"\\n- to -\\n- to +\\n0 to +\\n+ to +\\n\\\"\\\"\\\"\\nresult = 0\\nif n[0] < 0 and n[1] < 0:\\n result += abs(n[0]-n[1]) * n[2]\\nelif n[0] < 0 and n[1] > 0:\\n result += abs(n[0])*n[2] + n[1]*n[4]\\n result += n[3]\\nelif n[0] == 0 and n[1] > 0:\\n result += n[3]\\n result += n[1]*n[4]\\nelif n[0] > 0 and n[1] > 0:\\n result += abs(n[0]-n[1])*n[4]\\nprint(result)\\n\"\n },\n {\n \"alpha_fraction\": 0.5310077667236328,\n \"alphanum_fraction\": 0.5426356792449951,\n \"avg_line_length\": 23.619047164916992,\n \"blob_id\": \"6a52531cd8767e066e66f9dbf13716785c3bb0b6\",\n \"content_id\": \"76abbdf341eba27ccc5492f413d44e96d9524ba8\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 818,\n \"license_type\": \"no_license\",\n \"max_line_length\": 52,\n \"num_lines\": 21,\n \"path\": \"/알고리즘/온라인저지/2021/08/0807/OX퀴즈.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"\\\"\\\"\\\"\\nO가 연속되는지 알 수 있는 법?\\n순회할 때\\n이번 값이 O인지 확인하고\\n몇번째 O인지 확인해서\\n인덱스만큼 더해주기\\n\\\"\\\"\\\"\\n\\nT = int(input()) # 테스트 케이스 개수\\n\\nfor i in range(T): # 테스트 케이스 개수만큼 반복하면서\\n O_and_X = input() # OX를 입력받고\\n count = 0 # 연속된 O의 개수를 세는 count를 초기화 하고\\n result = 0 # 결과값을 0으로 초기화하고\\n for O_or_X in O_and_X: # OX를 순회하면서\\n if O_or_X == \\\"O\\\": # 순회중인 값이 O면\\n count += 1 # 연속된 O의 개수 +1\\n result += count # O가 연속된 횟수값을 result에 저장\\n else: # 순회중인 값이 X일때\\n count = 0 # 연속된 O의 카운트를 초기화\\n print(result) # 결과값 출력\"\n },\n {\n \"alpha_fraction\": 0.5285714268684387,\n \"alphanum_fraction\": 0.5690476298332214,\n \"avg_line_length\": 29.071428298950195,\n \"blob_id\": \"6a8184efd36129f8ece5ac409441526270aa4a09\",\n \"content_id\": \"749bc57666400fa979e42739a2e2e4e77503cf0d\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 592,\n \"license_type\": \"no_license\",\n \"max_line_length\": 70,\n \"num_lines\": 14,\n \"path\": \"/알고리즘/온라인저지/2021/08/0805/더하기 사이클.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"a = int(input())\\n\\ndef calc(a): # 제시된 계산 규칙을 함수로 정의하고\\n result = ((a % 10) + (a // 10)) % 10 + (a % 10) * 10\\n return result\\n\\ncalc_list = [a] # 계산된 수들을 저장할 리스트의 0번째를 a로 초기화\\ni = 0 # while문 돌리기 위한 i\\nwhile True:\\n calc_list.append(calc(calc_list[i])) # 함수를 적용하여 리스트에 추가\\n i += 1\\n if calc_list[0] == calc_list[::-1][0]: # 첫항(입력값)과 계산해서 추가한 값이 같을 때\\n break # while문 종료하고\\nprint(len(calc_list)-1) # 사이클 수 구해서 출력\"\n },\n {\n \"alpha_fraction\": 0.5888158082962036,\n \"alphanum_fraction\": 0.5986841917037964,\n \"avg_line_length\": 16.941177368164062,\n \"blob_id\": \"5248cb7ed3065ee3510e209caf6327ce40009b88\",\n \"content_id\": \"39021b7056c88b8116066430bf30cd2b6dafa090\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 304,\n \"license_type\": \"no_license\",\n \"max_line_length\": 36,\n \"num_lines\": 17,\n \"path\": \"/알고리즘/온라인저지/2023/02/0226/잃어버린 괄호.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"def new_sum(exp):\\n plus_split = exp.split('+')\\n answer = 0\\n\\n for i in range(len(plus_split)):\\n answer += int(plus_split[i])\\n\\n return answer\\n\\nexps = input()\\nminus_split = exps.split('-')\\nresult = new_sum(minus_split[0])\\n\\nfor a in minus_split[1:]:\\n result -= new_sum(a)\\n\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.42236700654029846,\n \"alphanum_fraction\": 0.43431052565574646,\n \"avg_line_length\": 26.117647171020508,\n \"blob_id\": \"6a01dd2355498daeb346647a4782aca2f8c0ae0d\",\n \"content_id\": \"9d5ddc206c6ab609a5daf0e5aef0059790911c3f\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1313,\n \"license_type\": \"no_license\",\n \"max_line_length\": 59,\n \"num_lines\": 34,\n \"path\": \"/알고리즘/SWEA/LEARN/Course/2. Programming Intermediate/1. 파이썬 SW문제해결 기본 List1/7차시 1일차 - 전기버스.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"T = int(input())\\n\\nfor t in range(1, T+1):\\n K, N, M = map(int, input().split())\\n charge = list(map(int, input().split())) # 충전소 위치\\n\\n stop = [0] * (N+1) # 정류장 초기값\\n\\n for c in charge: # 충전소가 있는 정류장 정보를 갱신\\n stop[c] = 1\\n \\n now = 0 # 현재 위치(초기 출발위치)\\n cnt = 0 # 충전 횟수\\n\\n while now+K < N: # 목적지에 도달하기 전까지\\n tmp = now # now값을 조작할 것이므로\\n # 조작 전 now값을 tmp에 저장\\n\\n for i in range(now+K, now-1, -1): # 갈 수 있는 가장 멀리부터 \\n # 현재 위치까지 거꾸로 확인하기\\n if stop[i]: # 충전소가 발견되면\\n # 뒤에서 탐색하였기 때문에\\n # 가장 먼저 발견되는 충전소는 \\n # 갈 수 있는 충전소 중 가장 멀리있는 충전소\\n now = i # 해당 충전소의 위치로 이동\\n cnt += 1 # 충전 한번 하였음\\n break # 해당 for문 종료\\n \\n if i == tmp: # 충전소를 못찾고 결국 제자리로 돌아오면\\n # 목적지에 도달할 수 없으므로\\n cnt = 0 # 갈 수 없음\\n break # while 종료\\n\\n print('#{} {}'.format(t, cnt))\"\n },\n {\n \"alpha_fraction\": 0.5458333492279053,\n \"alphanum_fraction\": 0.5708333253860474,\n \"avg_line_length\": 15.066666603088379,\n \"blob_id\": \"e364e49c186d6d6d978eb12641affaa6327193f4\",\n \"content_id\": \"0114afa6ea0afd667649979e2a698807808ad673\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 240,\n \"license_type\": \"no_license\",\n \"max_line_length\": 30,\n \"num_lines\": 15,\n \"path\": \"/알고리즘/온라인저지/2022/09/0930/문서 검색.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\n\\nword = input().rstrip()\\npattern = input().rstrip()\\nL = len(pattern)\\ni = 0\\nresult = 0\\nwhile i<len(word)-L+1:\\n if pattern == word[i:i+L]:\\n result += 1\\n i += L-1\\n i += 1\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.43933823704719543,\n \"alphanum_fraction\": 0.4595588147640228,\n \"avg_line_length\": 23.772727966308594,\n \"blob_id\": \"0e4a9dadd61ed42e09b2c17899fe22e42b0bbe31\",\n \"content_id\": \"3d3e5eaccd4d1095fd249c561a3dce8edda33415\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 544,\n \"license_type\": \"no_license\",\n \"max_line_length\": 61,\n \"num_lines\": 22,\n \"path\": \"/알고리즘/[템플릿]/Floyd-Warshall/플로이드.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"INF = int(1e9)\\nN = int(input())\\nM = int(input())\\narr = [[INF]*N for _ in range(N)]\\nfor m in range(M):\\n a, b, c = map(int, input().split())\\n a, b = a-1, b-1\\n if c < arr[a][b]:\\n arr[a][b] = c\\nfor k in range(N):\\n for a in range(N):\\n for b in range(N):\\n arr[a][b] = min(arr[a][b], arr[a][k] + arr[k][b])\\nfor i in range(N):\\n for j in range(N):\\n if i == j:\\n arr[i][j] = 0 \\n if arr[i][j] == INF:\\n arr[i][j] = 0\\nfor a in arr: print(*a)\\n\\n# https://www.acmicpc.net/problem/11404\"\n },\n {\n \"alpha_fraction\": 0.3787878751754761,\n \"alphanum_fraction\": 0.469696968793869,\n \"avg_line_length\": 10.166666984558105,\n \"blob_id\": \"27dfa310cf5c134b8c673ce3891b7e38f7b724e9\",\n \"content_id\": \"f6936d15b61d136d2965137e2654e1a9d222f551\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 66,\n \"license_type\": \"no_license\",\n \"max_line_length\": 25,\n \"num_lines\": 6,\n \"path\": \"/알고리즘/SWEA/LEARN/Course/1. Programming Beginner/파이썬 프로그래밍 기초(2)/10차시 2. 자료구조 – 리스트, 튜플 - 연습문제 11.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"l = [1, 1]\\n\\nwhile len(l) < 10:\\n l.append(l[-1]+l[-2])\\n\\nprint(l)\"\n },\n {\n \"alpha_fraction\": 0.6000000238418579,\n \"alphanum_fraction\": 0.6380952596664429,\n \"avg_line_length\": 16.66666603088379,\n \"blob_id\": \"d86568666bb62b27a98706524533232e230ae619\",\n \"content_id\": \"ee35419877ac6335611130b249c0443dee68370e\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 105,\n \"license_type\": \"no_license\",\n \"max_line_length\": 44,\n \"num_lines\": 6,\n \"path\": \"/알고리즘/온라인저지/2022/09/0927/소수.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\n\\nA, B, N = map(int, input().rstrip().split())\\nprint(A*10**N//B%10)\"\n },\n {\n \"alpha_fraction\": 0.48179271817207336,\n \"alphanum_fraction\": 0.5070028305053711,\n \"avg_line_length\": 28.83333396911621,\n \"blob_id\": \"72948bf732ad1b06a77f373173cc6c7a71b896c5\",\n \"content_id\": \"074cc9b03882bb36fc868b03a201bf39170fb280\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 357,\n \"license_type\": \"no_license\",\n \"max_line_length\": 47,\n \"num_lines\": 12,\n \"path\": \"/알고리즘/온라인저지/2022/04/0427/성적 통계.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"K = int(input())\\nfor k in range(1, K+1):\\n score = list(map(int, input().split()))\\n score = score[1:]\\n # print(score)\\n score.sort()\\n A, B, C = score[-1], score[0], 0\\n for i in range(len(score)-1):\\n if score[i+1]-score[i] > C:\\n C = score[i+1]-score[i]\\n print(f'Class {k}')\\n print(f'Max {A}, Min {B}, Largest gap {C}')\"\n },\n {\n \"alpha_fraction\": 0.4864864945411682,\n \"alphanum_fraction\": 0.5027027130126953,\n \"avg_line_length\": 12.214285850524902,\n \"blob_id\": \"50db3dc051ffeb499789bdebe9c6972ce0196442\",\n \"content_id\": \"c742b893d0132977f18561320ed2fb467d5c9b56\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 185,\n \"license_type\": \"no_license\",\n \"max_line_length\": 35,\n \"num_lines\": 14,\n \"path\": \"/알고리즘/온라인저지/2022/02/0217/와글와글 숭고한.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"S, K, H = map(int, input().split())\\n\\nOK_check = True\\n\\ndictt = {\\n S:'Soongsil',\\n K:'Korea',\\n H:'Hanyang',\\n}\\n\\nif S+K+H >= 100:\\n print('OK')\\nelse:\\n print(dictt[min(S,K,H)])\\n\"\n },\n {\n \"alpha_fraction\": 0.29646018147468567,\n \"alphanum_fraction\": 0.36283186078071594,\n \"avg_line_length\": 9.318181991577148,\n \"blob_id\": \"ab0030daa1105a84aa65971ad823cfb253656a81\",\n \"content_id\": \"f030c5c666abf3cefc5b4e7675cd1a05e2f77628\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 226,\n \"license_type\": \"no_license\",\n \"max_line_length\": 30,\n \"num_lines\": 22,\n \"path\": \"/알고리즘/온라인저지/2021/12/1216/학점계산.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"grade = input()\\n\\nalpha = {\\n 'A': 4,\\n 'B': 3,\\n 'C': 2,\\n 'D': 1,\\n 'F': 0,\\n '+': 0.3,\\n '0': 0.0,\\n '-': -0.3,\\n},\\n\\nresult = 0\\n\\n\\n\\nfor g in grade:\\n result += alpha[0][g]\\n \\n\\nprint('{:.1f}'.format(result))\"\n },\n {\n \"alpha_fraction\": 0.5574324131011963,\n \"alphanum_fraction\": 0.5810810923576355,\n \"avg_line_length\": 21.846153259277344,\n \"blob_id\": \"99c9c1246ff25e1c097054b33b3f12118b46ab2c\",\n \"content_id\": \"01593ab99ddf4a86b60918067f2df032eb7496c3\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 296,\n \"license_type\": \"no_license\",\n \"max_line_length\": 40,\n \"num_lines\": 13,\n \"path\": \"/알고리즘/온라인저지/2022/07/0724/박 터뜨리기.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N, K = map(int, input().split())\\nbuckets = list(range(1, K+1))\\nbuckets.sort(reverse=True)\\nresult = 0\\nif N < sum(buckets):\\n result = -1\\nelse:\\n idx = 0\\n for i in range(N-sum(buckets)):\\n buckets[idx] += 1\\n idx = (idx+1)%K\\n result = max(buckets) - min(buckets)\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.47999998927116394,\n \"alphanum_fraction\": 0.5600000023841858,\n \"avg_line_length\": 12,\n \"blob_id\": \"e1c9a5a5f55a6a89d996f6c031e82a407e76b61b\",\n \"content_id\": \"896b5a18df2d6a376fc438ed4705848bee82883f\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 25,\n \"license_type\": \"no_license\",\n \"max_line_length\": 13,\n \"num_lines\": 2,\n \"path\": \"/알고리즘/온라인저지/2022/03/0303/알고리즘 수업 - 알고리즘의 수행 시간 1.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"n = input()\\nprint('1\\\\n0')\"\n },\n {\n \"alpha_fraction\": 0.4524714946746826,\n \"alphanum_fraction\": 0.47148290276527405,\n \"avg_line_length\": 19.30769157409668,\n \"blob_id\": \"07e478c87a1bf9ae98e19879597e23fcd35a33a3\",\n \"content_id\": \"c393e820a6830fd2cd06c7bd863ace94c7bae03b\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 263,\n \"license_type\": \"no_license\",\n \"max_line_length\": 37,\n \"num_lines\": 13,\n \"path\": \"/알고리즘/온라인저지/2022/06/0613/한조서열정리하고옴ㅋㅋ.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = int(input())\\narr = list(map(int, input().split()))\\nresult = 0\\nfor i in range(N-1):\\n tmp = 0\\n for j in range(i+1, N):\\n if arr[i] > arr[j]:\\n tmp += 1\\n else:\\n break\\n if tmp > result:\\n result = tmp\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.48148149251937866,\n \"alphanum_fraction\": 0.5259259343147278,\n \"avg_line_length\": 21.66666603088379,\n \"blob_id\": \"9eed69c5e4aa7e34a28382e842de976a2869d204\",\n \"content_id\": \"4a26191c9a63789601a44c9aabc5453a1261c66d\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 135,\n \"license_type\": \"no_license\",\n \"max_line_length\": 32,\n \"num_lines\": 6,\n \"path\": \"/알고리즘/온라인저지/2023/01/0126/숫자 빈도수.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N, D = map(int, input().split())\\ncount = [0]*10\\nfor i in range(1, N+1):\\n for j in str(i):\\n count[int(j)] += 1\\nprint(count[D])\"\n },\n {\n \"alpha_fraction\": 0.4688427448272705,\n \"alphanum_fraction\": 0.48367953300476074,\n \"avg_line_length\": 23.14285659790039,\n \"blob_id\": \"026a47c7470f95d4eafa3003bf65d72e93e1160e\",\n \"content_id\": \"a55d6cc7bf2f99d3f6171ebffa2a0c568d5257d9\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 337,\n \"license_type\": \"no_license\",\n \"max_line_length\": 43,\n \"num_lines\": 14,\n \"path\": \"/알고리즘/온라인저지/2022/10/1012/모든 순열.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"def perm(arr, i):\\n if i == len(arr)-1:\\n result.append(arr[:])\\n else:\\n for j in range(i, len(arr)):\\n arr[i], arr[j] = arr[j], arr[i]\\n perm(arr, i+1)\\n arr[i], arr[j] = arr[j], arr[i]\\n\\narr = list(range(1, int(input())+1))\\nresult = []\\nperm(arr, 0)\\nresult.sort()\\nfor r in result: print(*r)\"\n },\n {\n \"alpha_fraction\": 0.4663677215576172,\n \"alphanum_fraction\": 0.4708520174026489,\n \"avg_line_length\": 19.18181800842285,\n \"blob_id\": \"7c212d2d82f9343ea7fefebf8833825a7779c863\",\n \"content_id\": \"d32d308af643480b5a6601c5c1689ce512db4f39\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 223,\n \"license_type\": \"no_license\",\n \"max_line_length\": 35,\n \"num_lines\": 11,\n \"path\": \"/알고리즘/온라인저지/2021/09/0906/최소공배수.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\ndef input():\\n return sys.stdin.readline()\\n\\nT = int(input())\\nfor t in range(T):\\n A, B = map(int,input().split())\\n C, D = A, B\\n while A % B != 0:\\n A, B = B, A % B\\n print(B * (C//B) * (D//B))\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.5,\n \"alphanum_fraction\": 0.5,\n \"avg_line_length\": 24.5,\n \"blob_id\": \"5ff55148ee570657acc29af2a02533fef31505ed\",\n \"content_id\": \"2bee23986f9ac5b03e49f9e95b10df7be3ad9d58\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 254,\n \"license_type\": \"no_license\",\n \"max_line_length\": 42,\n \"num_lines\": 10,\n \"path\": \"/알고리즘/온라인저지/2022/06/0615/성 지키기.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N, M = map(int, input().split())\\ncastle = [list(input()) for _ in range(N)]\\nrow = set()\\ncol = set()\\nfor i in range(N):\\n for j in range(M):\\n if castle[i][j] == 'X':\\n row.add(i)\\n col.add(j)\\nprint(max(N-len(row), M-len(col)))\"\n },\n {\n \"alpha_fraction\": 0.40956342220306396,\n \"alphanum_fraction\": 0.4615384638309479,\n \"avg_line_length\": 16.851852416992188,\n \"blob_id\": \"304a204e877399af57ba8e5710d35031fd4b2386\",\n \"content_id\": \"a58b9822e891db72acab15cd6af7f7906a7371b7\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 481,\n \"license_type\": \"no_license\",\n \"max_line_length\": 33,\n \"num_lines\": 27,\n \"path\": \"/알고리즘/SWEA/LEARN/Course/1. Programming Beginner/파이썬 프로그래밍 기초(2)/5차시 2. 자료구조 – 리스트, 튜플 - 연습문제 3.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"all = set()\\n\\nfor i in range(1, 10):\\n for j in range(1, 10):\\n all.add(i * j)\\n\\nall.discard(1)\\n\\nfor i in range(3, 82, 3):\\n for j in range(7, 82, 7):\\n if i in all:\\n all.discard(i)\\n elif j in all:\\n all.discard(j)\\n\\nresult = [[] for _ in range(8)]\\n\\nfor i in range(2, 10):\\n tmp = 0\\n for j in range(i, 82, i):\\n tmp += 1\\n if j in all:\\n result[i-2].append(j)\\n if tmp == 9:\\n break\\n\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.4434782564640045,\n \"alphanum_fraction\": 0.5652173757553101,\n \"avg_line_length\": 37.66666793823242,\n \"blob_id\": \"d46f46b724b9a3f336f8acf2bcf04ad0269117bb\",\n \"content_id\": \"6cef050bb8a8e946af7af24c7058a9da02a45040\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 115,\n \"license_type\": \"no_license\",\n \"max_line_length\": 42,\n \"num_lines\": 3,\n \"path\": \"/알고리즘/온라인저지/2022/08/0822/Contest Timing.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"D, H, M = map(int, input().split())\\nresult = (D-11)*24*60 + (H-11)*60 + (M-11)\\nprint(result if result >= 0 else -1)\"\n },\n {\n \"alpha_fraction\": 0.5293244123458862,\n \"alphanum_fraction\": 0.5567928552627563,\n \"avg_line_length\": 29.636363983154297,\n \"blob_id\": \"afdd97f08677ba672abe91eff28bba9755249878\",\n \"content_id\": \"9047eb822e4dbf74caacb7a59760aee5f82e5f8f\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1845,\n \"license_type\": \"no_license\",\n \"max_line_length\": 69,\n \"num_lines\": 44,\n \"path\": \"/알고리즘/[템플릿]/Dijkstra/미로만들기.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\nfrom heapq import heappush, heappop\\n\\ninput = sys.stdin.readline # 일종의 루틴 같은 것\\ndy, dx = [1, 0, -1, 0], [0, 1, 0, -1] # 델타이동\\n\\ndef dijkstra():\\n heappush(Q, (0, 0, 0)) # change, y, x\\n visited[0][0] = 1 # 0, 0 출발\\n while Q:\\n change, y, x = heappop(Q) # heapq 특성상, 튜플등에선 맨 앞 값을 기준으로 정렬한다\\n if y == x == N-1: break # 방을 바꿔가며 어찌저찌 목표지점에 도착\\n delta_move(change, y, x) # 4방향 델타이동\\n return change # line 11의 change를 의미함, while문을 break했을 때의 change\\n\\ndef delta_move(change, y, x):\\n for i in range(4):\\n ny, nx = y+dy[i], x+dx[i]\\n if 0<=ny<N and 0<=nx<N and not visited[ny][nx]:\\n visited[ny][nx] = 1\\n if room[ny][nx] == 0: # 검은 방 : 통과 불가능, 흰 방으로 바꿈\\n heappush(Q, (change+1, ny, nx)) # 방 바꾸면서 가자\\n else: # 흰 방 : 통과 가능\\n heappush(Q, (change, ny, nx))\\n\\nN = int(input().rstrip())\\nroom = [list(map(int, input().rstrip())) for _ in range(N)]\\nvisited = [[0]*N for _ in range(N)]\\nQ = []\\nprint(dijkstra())\\n\\n\\\"\\\"\\\"\\n핵심\\n1. visited[i][j]에 대해서, 한 차원 더 방문배열을 만들면서\\n \\\"방을 몇 번 바꾸면서 지나왔는가\\\"는 기록할 필요가 없다\\n 어차피 i,j번 방이, 검은 방을 흰색 방으로 바꿔야 갈 수 있다면\\n 방을 바꾸지 않고는, change+1 하지 않고는 해당 지점에 닿을 수 없다\\n2. room[N-1][N-1]에 도달하던 말던 상관없이\\n 방을 바꾸는 횟수를 최소로 하여 목표까지 도달해야 하기 때문에\\n Q[0]에 집어 넣은 change의 값이 작은 것 부터 탐색한다\\n 그래서 이 문제는 다익스트라다\\n\\\"\\\"\\\"\\n\\n# https://www.acmicpc.net/problem/2665\"\n },\n {\n \"alpha_fraction\": 0.26778241991996765,\n \"alphanum_fraction\": 0.3012552261352539,\n \"avg_line_length\": 18.58333396911621,\n \"blob_id\": \"8f863018ae81c5a8c18c4a55312dcc8ab2345523\",\n \"content_id\": \"f9333004ce1914d8555f56fb19f2d2d027e093b8\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 239,\n \"license_type\": \"no_license\",\n \"max_line_length\": 51,\n \"num_lines\": 12,\n \"path\": \"/알고리즘/온라인저지/2022/06/0605/별 찍기 - 21.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = int(input())\\n# N = 3\\nif N == 1:\\n tmp = ['*']\\nelse:\\n if N%2:\\n tmp = [['*']*((N//2)+1), ['']+['*']*(N//2)]\\n else:\\n tmp = [['*']*(N//2), ['']+['*']*(N//2)]\\nfor i in range(N):\\n for t in tmp:\\n print(*t)\\n \"\n },\n {\n \"alpha_fraction\": 0.42578125,\n \"alphanum_fraction\": 0.4375,\n \"avg_line_length\": 29.760000228881836,\n \"blob_id\": \"bd11aa1d53509053977f0630b933b88bc3f823b4\",\n \"content_id\": \"42e49d8d3627b2b5a02e76c9d14c53049d683ceb\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 884,\n \"license_type\": \"no_license\",\n \"max_line_length\": 102,\n \"num_lines\": 25,\n \"path\": \"/알고리즘/온라인저지/2021/08/0823/암호 만들기.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"L, C = map(int, input().split())\\narr = list(input().split())\\n\\nn = len(arr)\\nresult = []\\nfor i in range(1<<n): # 모든 암호(부분집합)들 중에서\\n tmp = []\\n for j in range(n):\\n if i&(1<<j):\\n tmp.append(arr[j])\\n if len(tmp) == L: # 길이가 L이고\\n if ('a' in tmp) or ('e' in tmp) or ('i' in tmp) or ('o' in tmp) or ('u' in tmp): # 모음이 하나이상 있고\\n count = 0\\n for tm in tmp:\\n if tm in 'bcdfghjklmnpqrstvwxyz': # 자음이\\n count += 1\\n if count >= 2: # 두개 이상일 때\\n tmp.sort() # 정렬해서\\n tmp2 = ''\\n for t in tmp:\\n tmp2 = tmp2 + t # 단어로 만들어서\\n result.append(tmp2) # 추가\\nresult.sort() # 추가한 값들을 정렬\\nfor res in result:\\n print(res) # 출력\"\n },\n {\n \"alpha_fraction\": 0.5122873187065125,\n \"alphanum_fraction\": 0.5406427383422852,\n \"avg_line_length\": 23.090909957885742,\n \"blob_id\": \"14a7acb5a0e885f230591d75bbe486596f1a885f\",\n \"content_id\": \"63c65bd4e38b399ee5c9286ff7aefd13d709135a\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 629,\n \"license_type\": \"no_license\",\n \"max_line_length\": 47,\n \"num_lines\": 22,\n \"path\": \"/알고리즘/온라인저지/2022/09/0925/퇴사.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\n\\nN = int(input().rstrip())\\nT, P, dp = [], [], []\\nfor i in range(N):\\n a, b = map(int, input().rstrip().split())\\n T.append(a)\\n P.append(b)\\n dp.append(b)\\ndp.append(0)\\nfor i in range(N-1, -1, -1):\\n if T[i]+i > N: # 이 날 시작한 일이 퇴사일을 넘길 경우\\n dp[i] = dp[i+1]\\n else: # 퇴사일 전에 일을 마칠 수 있는 경우\\n # 그 일을 마친 날 기준, 해당 일에 얻을 수 있는 최대 이익\\n dp[i] = max(dp[i+1], P[i] + dp[i+T[i]])\\nprint(dp[0])\\n\\n# https://www.acmicpc.net/problem/14501\\n# https://pacific-ocean.tistory.com/199\"\n },\n {\n \"alpha_fraction\": 0.4275362193584442,\n \"alphanum_fraction\": 0.4492753744125366,\n \"avg_line_length\": 22.16666603088379,\n \"blob_id\": \"c978fe442dfc40753c7577772655ca0dc7717d4f\",\n \"content_id\": \"b0ab13b81175361078d58bc389b049bec3b78fca\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 138,\n \"license_type\": \"no_license\",\n \"max_line_length\": 32,\n \"num_lines\": 6,\n \"path\": \"/알고리즘/온라인저지/2022/06/0607/시그마.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"a, b = map(int, input().split())\\nn_max = max(a, b)\\nn_min = min(a, b)\\nn = n_max - n_min\\ns = (n * (n + 1)) // 2\\nprint(s + (n_min * (n + 1)))\"\n },\n {\n \"alpha_fraction\": 0.46060606837272644,\n \"alphanum_fraction\": 0.539393961429596,\n \"avg_line_length\": 19.75,\n \"blob_id\": \"d598e479161cc6c290b07b9acb6e4cf8c628bfba\",\n \"content_id\": \"0505780c3b58618328f0c2a780b57edaea1bb717\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 165,\n \"license_type\": \"no_license\",\n \"max_line_length\": 39,\n \"num_lines\": 8,\n \"path\": \"/알고리즘/온라인저지/2023/04/0409/Bicycle.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"nums = [int(input()) for _ in range(5)]\\na, x, b, y, T = nums\\nresult = [a, b]\\nA = max(0, T-30)\\nB = max(0, T-45)\\nresult[0] += A*x*21\\nresult[1] += B*y*21\\nprint(*result)\"\n },\n {\n \"alpha_fraction\": 0.4301075339317322,\n \"alphanum_fraction\": 0.44301074743270874,\n \"avg_line_length\": 21.190475463867188,\n \"blob_id\": \"5794ecc16106255d36e5ffb0e94f809ecea77980\",\n \"content_id\": \"62cea035ba915366f744c7cec0135fdc2a67dee9\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 639,\n \"license_type\": \"no_license\",\n \"max_line_length\": 38,\n \"num_lines\": 21,\n \"path\": \"/알고리즘/온라인저지/2021/08/0823/A와 B.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"S = list(input())\\nT = list(input())\\nresult = 0\\n# A를 추가하거나, 뒤집고 B를 추가하는 두가지만 가능\\n# 뒤집어서 생각하면\\n# T에서 A를 빼거나, B를 빼고 뒤집어가면서 S와 일치하는지 확인\\nwhile True:\\n if S == T: # 만들 수 있으면 \\n result = 1 # 1\\n break\\n if T[-1] == 'A': # 맨 뒷글자가 A면\\n T.pop() # 빼고\\n if not T: # 다 빼서 T가 []가 되면\\n break # 종료\\n elif T[-1] == 'B': # 맨 뒷글자가 B면\\n T.pop() # 빼고\\n if not T: # T == []\\n break # 종료\\n T = T[::-1] # 뒤집고\\n\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.4858299493789673,\n \"alphanum_fraction\": 0.4898785352706909,\n \"avg_line_length\": 19.66666603088379,\n \"blob_id\": \"ff138b5dec70e26398ec97f58cbfb4c00e03dbb3\",\n \"content_id\": \"bc0518ef6ce8ac139bff759b42cf85a1e81ae49f\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 247,\n \"license_type\": \"no_license\",\n \"max_line_length\": 32,\n \"num_lines\": 12,\n \"path\": \"/알고리즘/온라인저지/2022/09/0903/분수 합.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"def gcd(a, b):\\n while b > 0: a, b = b, a%b\\n return a\\n\\nA, B = map(int, input().split())\\nC, D = map(int, input().split())\\nGCD = gcd(B, D)\\nLCM = GCD * (B//GCD) * (D//GCD)\\nE = A*(LCM//B) + C*(LCM//D)\\nF = LCM\\nGCD = gcd(E, F)\\nprint(E//GCD, F//GCD)\"\n },\n {\n \"alpha_fraction\": 0.47058823704719543,\n \"alphanum_fraction\": 0.48235294222831726,\n \"avg_line_length\": 20.375,\n \"blob_id\": \"41ad2a1b99efda3ebf55d6138dd53de5a467e2fc\",\n \"content_id\": \"4b674e4f0b78191770d60272502900b1d2a06045\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 170,\n \"license_type\": \"no_license\",\n \"max_line_length\": 39,\n \"num_lines\": 8,\n \"path\": \"/알고리즘/온라인저지/2023/06/0608/Triathlon.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"result = 0\\nfor _ in range(int(input())):\\n A, D, G = map(int, input().split())\\n C = A*(D+G)\\n if A == D+G:\\n C *= 2\\n result = max(result, C)\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.5520833134651184,\n \"alphanum_fraction\": 0.5729166865348816,\n \"avg_line_length\": 11.125,\n \"blob_id\": \"b0ce847b856a2d50c8685c18365bea0960a930e6\",\n \"content_id\": \"7555147602ad2e5b10807573ffd8473cb148b393\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 96,\n \"license_type\": \"no_license\",\n \"max_line_length\": 26,\n \"num_lines\": 8,\n \"path\": \"/알고리즘/SWEA/LEARN/Course/1. Programming Beginner/파이썬 프로그래밍 기초(2)/31차시 3. 자료구조 – 셋, 딕셔너리 - 연습문제 6.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = int(input())\\n\\nresult = {}\\n\\nfor i in range(1, N+1):\\n result.update({i:i*i})\\n\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.5396419167518616,\n \"alphanum_fraction\": 0.5652173757553101,\n \"avg_line_length\": 29.153846740722656,\n \"blob_id\": \"6d55bc0f1c426a8b9e25e7dc0b2705df8df0c1ea\",\n \"content_id\": \"a504f7b1a131bc599c52f2d28d771db8ce7ef5f8\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 391,\n \"license_type\": \"no_license\",\n \"max_line_length\": 57,\n \"num_lines\": 13,\n \"path\": \"/알고리즘/온라인저지/2023/01/0114/텔레프라임.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"def prime_list(size):\\n sieve = [True]*(size+1)\\n for i in range(2, int(size**0.5)+1):\\n if sieve[i]:\\n for j in range(i+i, size+1, i):\\n sieve[j] = False\\n return [i for i in range(2, size+1) if sieve[i]]\\n\\nold, new = input().split()\\nnew = int(new+old)\\nold = int(old)\\nprimes = prime_list(int(1e7))\\nprint('Yes' if old in primes and new in primes else 'No')\"\n },\n {\n \"alpha_fraction\": 0.45781466364860535,\n \"alphanum_fraction\": 0.46473029255867004,\n \"avg_line_length\": 33.47618865966797,\n \"blob_id\": \"b66fa1c79978d5f3526c6d26667576eaa4f5a9cb\",\n \"content_id\": \"70ea43d18493bdb22ee55fdea47dad285faf1747\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 947,\n \"license_type\": \"no_license\",\n \"max_line_length\": 71,\n \"num_lines\": 21,\n \"path\": \"/알고리즘/온라인저지/2022/09/0908/마니또.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"case = 1 # 테스트 케이스\\nwhile True:\\n N = int(input()) # 사람 수\\n if N == 0: break # while 종료\\n result = [] # 결과를 담을 배열\\n for n in range(N):\\n A, B = input().split() # 사람 A, 사람 B\\n flag = False # 이미 있는 그룹인지 확인할 것\\n for i in range(len(result)): # 마니또 그룹들 중에서\\n if A in result[i] or B in result[i]: # 둘 중 하나라도 속하는 그룹이 있다면\\n flag = True # 둘 다 결국 같은 그룹\\n # set()로 중복처리하면서 사람들을 다 추가할 것\\n result[i].add(A)\\n result[i].add(B)\\n if not flag: # 둘 다 속한 마니또그룹이 없으면\\n result.append(set()) # 그룹 추가\\n # 사람들 추가\\n result[-1].add(A)\\n result[-1].add(B)\\n print(case, len(result)) # 출력\\n case += 1 # 다음 케이스\"\n },\n {\n \"alpha_fraction\": 0.6487804651260376,\n \"alphanum_fraction\": 0.6487804651260376,\n \"avg_line_length\": 21.88888931274414,\n \"blob_id\": \"4e298261d501b46768387138f205e6f9478322d3\",\n \"content_id\": \"35838888439273c23c5bcea09c070a224a3e2e18\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 205,\n \"license_type\": \"no_license\",\n \"max_line_length\": 46,\n \"num_lines\": 9,\n \"path\": \"/알고리즘/온라인저지/2023/05/0513/빅데이터 정보보호.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"input()\\nS = input()\\nbigdata, security = S.count('b'), S.count('s')\\nresult = 'bigdata? security!'\\nif bigdata > security:\\n result = 'bigdata?'\\nif bigdata < security:\\n result = 'security!'\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.5222222208976746,\n \"alphanum_fraction\": 0.5444444417953491,\n \"avg_line_length\": 10.375,\n \"blob_id\": \"c5ca30f1159baf3e0f52aa88315cc76c79e7cdce\",\n \"content_id\": \"10cd16d61291bfde9bf077d8920231e5a3be715b\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 90,\n \"license_type\": \"no_license\",\n \"max_line_length\": 23,\n \"num_lines\": 8,\n \"path\": \"/알고리즘/온라인저지/2022/02/0209/나머지와 몫이 같은 수.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = int(input())\\n\\nresult = 0\\n\\nfor n in range(1, N):\\n result += N * n + n\\n\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.48404255509376526,\n \"alphanum_fraction\": 0.5106382966041565,\n \"avg_line_length\": 17.899999618530273,\n \"blob_id\": \"6284f1d16b5fdb96c570593733abc628c28c1b2c\",\n \"content_id\": \"6a15fcaa6c84350c0702f6e59de77f95da8b1c48\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 188,\n \"license_type\": \"no_license\",\n \"max_line_length\": 41,\n \"num_lines\": 10,\n \"path\": \"/알고리즘/SWEA/LEARN/Course/1. Programming Beginner/파이썬 프로그래밍 기초(2)/15차시 2. 자료구조 – 리스트, 튜플 - 연습문제 17.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import math\\nfrom math import pi\\n\\nx = list(map(int, input().split(', ')))\\n\\nfor i in x:\\n if i == x[-1]:\\n print(round(2*pi*i, 2))\\n else:\\n print(round(2*pi*i, 2), end=', ')\"\n },\n {\n \"alpha_fraction\": 0.5833333134651184,\n \"alphanum_fraction\": 0.5952380895614624,\n \"avg_line_length\": 41.5,\n \"blob_id\": \"b87ce35f7bcca3781963da20eb25a75eae60cc8c\",\n \"content_id\": \"fb992ead3d912680f659de9b016e792100b27bcc\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 84,\n \"license_type\": \"no_license\",\n \"max_line_length\": 54,\n \"num_lines\": 2,\n \"path\": \"/알고리즘/온라인저지/2022/08/0803/N번째 큰 수.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"for _ in range(int(input())):\\n print(sorted(list(map(int, input().split())))[-3])\"\n },\n {\n \"alpha_fraction\": 0.6113074421882629,\n \"alphanum_fraction\": 0.6466431021690369,\n \"avg_line_length\": 20.846153259277344,\n \"blob_id\": \"e078c5b357834ad5ddec44806f3f7258212c18dd\",\n \"content_id\": \"d45d7b03417b1e995045c02b6b663957f23a8816\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 283,\n \"license_type\": \"no_license\",\n \"max_line_length\": 63,\n \"num_lines\": 13,\n \"path\": \"/알고리즘/온라인저지/2022/09/0927/점수 계산.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\n\\nscores = []\\nfor i in range(1, 9): scores.append([int(input().rstrip()), i])\\nscores.sort(key=lambda x:-x[0])\\nresult = [0]\\nfor score in scores[:5]:\\n result[0] += score[0]\\n result.append(score[1])\\nprint(result[0])\\nprint(*sorted(result[1:]))\"\n },\n {\n \"alpha_fraction\": 0.6132264733314514,\n \"alphanum_fraction\": 0.6432865858078003,\n \"avg_line_length\": 30.25,\n \"blob_id\": \"06560b7b8febe621f12edc8b9953ec9beeb50a9a\",\n \"content_id\": \"a643fca562ba1f7faff32c4078ff86e8701c9cf5\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 499,\n \"license_type\": \"no_license\",\n \"max_line_length\": 49,\n \"num_lines\": 16,\n \"path\": \"/알고리즘/온라인저지/2022/07/0721/카우버거.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"B, C, D = map(int, input().split())\\nburger = list(map(int, input().split()))\\nside = list(map(int, input().split()))\\ndrink = list(map(int, input().split()))\\nburger.sort(reverse=True)\\nside.sort(reverse=True)\\ndrink.sort(reverse=True)\\nmin_set = min(len(burger), len(side), len(drink))\\nresult1 = sum(burger) + sum(side) + sum(drink)\\nprint(result1)\\nresult2 = result1\\nfor i in range(min_set):\\n result2 -= burger[i] * 0.1\\n result2 -= side[i] * 0.1\\n result2 -= drink[i] * 0.1\\nprint(f'{result2:.0f}')\"\n },\n {\n \"alpha_fraction\": 0.4595959484577179,\n \"alphanum_fraction\": 0.502525269985199,\n \"avg_line_length\": 19.894737243652344,\n \"blob_id\": \"923a6ece9e13afe4039da11aca1ae3d0d5c3a066\",\n \"content_id\": \"f068a3cc2301a75db56adc5d254709600f7b352f\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 396,\n \"license_type\": \"no_license\",\n \"max_line_length\": 38,\n \"num_lines\": 19,\n \"path\": \"/알고리즘/온라인저지/2023/01/0112/부재중 전화.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N, L, D = map(int, input().split())\\nsong_len_max = N*L + (N-1)*5\\nring_len_max = (song_len_max//D + 2)*D\\narr1 = [0]*ring_len_max\\narr2 = [0]*ring_len_max\\ni = 0\\nfor n in range(N):\\n for l in range(L):\\n arr1[i] = 1\\n i += 1\\n i += 5\\ni = 0\\nwhile i < ring_len_max:\\n arr2[i] += 1\\n i += D\\nfor i in range(ring_len_max):\\n if not arr1[i] and arr2[i]:\\n print(i)\\n break\"\n },\n {\n \"alpha_fraction\": 0.5312855243682861,\n \"alphanum_fraction\": 0.5711035132408142,\n \"avg_line_length\": 22.157894134521484,\n \"blob_id\": \"a1d70113e03cad99468197ae840eb4a3bf77bd7d\",\n \"content_id\": \"820462ac5123397507d7eb36808454f54fd40c6b\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1185,\n \"license_type\": \"no_license\",\n \"max_line_length\": 66,\n \"num_lines\": 38,\n \"path\": \"/알고리즘/온라인저지/2022/10/1006/내리막 길.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\ndy, dx = [-1, 1, 0, 0], [0, 0, -1, 1]\\n\\ndef dfs(y, x):\\n if y == N-1 and x == M-1: return 1\\n if visited[y][x] != -1: return visited[y][x]\\n visited[y][x] = 0\\n for i in range(4):\\n ny, nx = y+dy[i], x+dx[i]\\n if 0<=ny<N and 0<=nx<M:\\n if arr[ny][nx] < arr[y][x]:\\n visited[y][x] += dfs(ny, nx)\\n return visited[y][x]\\n\\nN, M = map(int, input().rstrip().split())\\narr = [list(map(int, input().rstrip().split())) for _ in range(N)]\\nvisited = [[-1]*M for _ in range(N)]\\nprint(dfs(0, 0))\\n\\n\\\"\\\"\\\"\\n탐색하면서 처리하는 방문 배열이 그냥 배열이 아닌 DP배열이다\\n1.방문배열 초기화는 -1\\n2.방문처리는 0\\n3.해당 지점을 경유하여 목적지에 도달 가능한 경로 경우의 수\\n등으로 방문배열을 채워나간다\\n3번이 채워지는 원리가 신박하다\\n목적지에 도달할 경우 line 7을 통해서\\n지나온 모든 경로에 1을 더해준다\\n결과적으로 시작점에서 봤을 때\\n목적지까지 갈 수 있는 경로의 수가 visited[0][0]에 들어오게 된다\\n\\n<참고한 링크>\\nhttps://ca.ramel.be/70\\n\\\"\\\"\\\"\\n\\n# https://www.acmicpc.net/problem/1520\"\n },\n {\n \"alpha_fraction\": 0.4149560034275055,\n \"alphanum_fraction\": 0.4545454680919647,\n \"avg_line_length\": 19.696969985961914,\n \"blob_id\": \"03a49c42fbbf838e945fa3e9afba076faae20fdf\",\n \"content_id\": \"a10d8d54523e780736fbbf23ca8e8c896ba10d83\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 682,\n \"license_type\": \"no_license\",\n \"max_line_length\": 56,\n \"num_lines\": 33,\n \"path\": \"/알고리즘/SWEA/LEARN/Course/3. Programming Advanced/2. 파이썬 SW문제해결 응용 구현 02 완전 검색/3차시 2일차 - 최소합.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"dx = [1, 0]\\ndy = [0, 1]\\n\\ndef dfs(x, y, tmp):\\n global result\\n if x == N-1 and y == N-1:\\n if tmp < result:\\n result = tmp\\n\\n if tmp > result:\\n return\\n\\n for i in range(2):\\n visited[y][x] = 1\\n nx = x+dx[i]\\n ny = y+dy[i]\\n if 0<=nx<N and 0<=ny<N and visited[ny][nx] == 0:\\n dfs(nx, ny, tmp+arr[ny][nx])\\n visited[y][x] = 0\\n\\nTC = int(input())\\n\\nfor tc in range(1, TC+1):\\n N = int(input())\\n arr = []\\n for n in range(N):\\n arr.append(list(map(int, input().split())))\\n \\n visited = [[0]*N for _ in range(N)]\\n\\n result = 99999999\\n dfs(0, 0, arr[0][0])\\n print('#{} {}'.format(tc, result))\"\n },\n {\n \"alpha_fraction\": 0.631147563457489,\n \"alphanum_fraction\": 0.6434426307678223,\n \"avg_line_length\": 23.5,\n \"blob_id\": \"d5afc7a1eff0d28be6d0ecc2d95fcc5fece9ba38\",\n \"content_id\": \"f36655b0d474b9897db3e1ac6ca2a93cd3c61cb9\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 244,\n \"license_type\": \"no_license\",\n \"max_line_length\": 53,\n \"num_lines\": 10,\n \"path\": \"/알고리즘/온라인저지/2022/11/1115/멀티탭 충분하니.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\n\\nN, K = map(int, input().rstrip().split())\\nmulti_taps = list(map(int, input().rstrip().split()))\\nresult = 0\\nfor multi_tap in multi_taps:\\n result += (multi_tap+1)//2\\nprint('YES' if result >= N else 'NO')\"\n },\n {\n \"alpha_fraction\": 0.5072463750839233,\n \"alphanum_fraction\": 0.52173912525177,\n \"avg_line_length\": 24.875,\n \"blob_id\": \"db041a3de5ca13a121bf7e3874c9b158945e489a\",\n \"content_id\": \"c8aefa21b27dd2bd48461e3c4ed514df90a6ca31\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 207,\n \"license_type\": \"no_license\",\n \"max_line_length\": 36,\n \"num_lines\": 8,\n \"path\": \"/알고리즘/온라인저지/2021/08/0816/단어순서 뒤집기.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"T = int(input())\\nfor t in range(1, T+1):\\n sentence = list(input().split())\\n sentence = sentence[::-1]\\n print(f'Case #{t}: ', end='')\\n for sen in sentence:\\n print(sen, end=' ')\\n print()\\n\"\n },\n {\n \"alpha_fraction\": 0.4270557165145874,\n \"alphanum_fraction\": 0.4482758641242981,\n \"avg_line_length\": 24.200000762939453,\n \"blob_id\": \"0950086e4df027a87da9f72a88612c0b44f783c9\",\n \"content_id\": \"0c19491eebbb31027b188c1e05a90b4700ce7b8e\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 377,\n \"license_type\": \"no_license\",\n \"max_line_length\": 35,\n \"num_lines\": 15,\n \"path\": \"/알고리즘/온라인저지/2022/07/0726/카약.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"R, C = map(int, input().split())\\nresult = [0] * 9\\narr = [input() for _ in range(R)]\\nrank = 1\\nfor c in range(C-2, 0, -1):\\n goal = False\\n for r in range(R):\\n if arr[r][c] != '.':\\n tmp = int(arr[r][c])-1\\n if not result[tmp]:\\n result[tmp] += rank\\n goal = True\\n if goal:\\n rank += 1\\nfor r in result: print(r)\"\n },\n {\n \"alpha_fraction\": 0.4096728265285492,\n \"alphanum_fraction\": 0.4267425239086151,\n \"avg_line_length\": 31.720930099487305,\n \"blob_id\": \"eff56f39e6216551a91040ec11b88dbc94b7e175\",\n \"content_id\": \"99b9cf72495fae81c4f766c8c247b5a1ab52497a\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1782,\n \"license_type\": \"no_license\",\n \"max_line_length\": 62,\n \"num_lines\": 43,\n \"path\": \"/알고리즘/온라인저지/2022/05/0501/사탕 게임.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\nN = int(sys.stdin.readline())\\narr = [list(map(str, input())) for _ in range(N)]\\nresult = 0 # 결과 최대값\\n\\ndef check(arr): # 현재 배열에서 최대값을 확인함\\n cnt = 0 # 배열에서 확인할 최대값 초기화\\n for i in range(N):\\n row = 1 # 행, 가로\\n col = 1 # 열, 세로\\n # 최대길이를 파악하는 방향은 한 쪽 방향이다\\n # 하지만 배열의 모든 좌표에 대해서 진행하므로 문제없음!\\n for j in range(N-1): \\n if arr[i][j] == arr[i][j+1]: # 연속할 경우\\n row += 1 # 길이++\\n else: # 연속하지 않을 경우 다시 1부터\\n cnt = max(cnt, row) # 갱신 한 번 해주고\\n row = 1\\n \\n if arr[j][i] == arr[j+1][i]: # 연속할 경우\\n col += 1 # 길이++\\n else: # 연속하지 않을 경우 다시 1부터\\n cnt = max(cnt, col) # 갱신 한 번 해주고\\n col = 1\\n cnt = max(cnt, row, col) # 기존cnt, 행, 열의 각각 값들 중 최대값 갱신\\n return cnt\\n\\nfor i in range(N):\\n for j in range(N-1):\\n # 위치를 바꿔서 같으면 옮길 필요가 없음\\n # 가로 옮겨보고\\n if arr[i][j] != arr[i][j+1]:\\n arr[i][j], arr[i][j+1] = arr[i][j+1], arr[i][j]\\n result = max(result, check(arr)) # 최대값 갱신\\n arr[i][j], arr[i][j+1] = arr[i][j+1], arr[i][j]\\n # 세로 옮겨보고\\n if arr[j][i] != arr[j+1][i]:\\n arr[j][i], arr[j+1][i] = arr[j+1][i], arr[j][i]\\n result = max(result, check(arr)) # 최대값 갱신\\n arr[j][i], arr[j+1][i] = arr[j+1][i], arr[j][i]\\n \\nprint(result) # 최대값 출력\"\n },\n {\n \"alpha_fraction\": 0.41886791586875916,\n \"alphanum_fraction\": 0.4226415157318115,\n \"avg_line_length\": 16.733333587646484,\n \"blob_id\": \"13d4e056522da7a1ab73c6acbb5bb962584bb156\",\n \"content_id\": \"a24058580efd4ebe8cfa97031cf4552245cf5044\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 265,\n \"license_type\": \"no_license\",\n \"max_line_length\": 33,\n \"num_lines\": 15,\n \"path\": \"/알고리즘/온라인저지/2022/10/1024/1.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\n\\nwhile True:\\n try:\\n N = int(input().rstrip())\\n num = ''\\n while True:\\n num += '1'\\n if not int(num)%N:\\n print(len(num))\\n break\\n except:\\n break\"\n },\n {\n \"alpha_fraction\": 0.6846153736114502,\n \"alphanum_fraction\": 0.6846153736114502,\n \"avg_line_length\": 20.83333396911621,\n \"blob_id\": \"61fdbf44f745f827825cec12a425775c956e1fb1\",\n \"content_id\": \"1692136e8c7d63df93d433c17a60cf8696c13433\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 130,\n \"license_type\": \"no_license\",\n \"max_line_length\": 31,\n \"num_lines\": 6,\n \"path\": \"/알고리즘/온라인저지/2021/08/0814/숫자의 합.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = int(input())\\nstr_numbers = input()\\nnumbers = []\\nfor number in str_numbers:\\n numbers.append(int(number))\\nprint(sum(numbers))\"\n },\n {\n \"alpha_fraction\": 0.4690265357494354,\n \"alphanum_fraction\": 0.5132743120193481,\n \"avg_line_length\": 17.91666603088379,\n \"blob_id\": \"a7774dbeb12de0cfd5f0d62c89b9e8f1af0caaea\",\n \"content_id\": \"1fc940e0e8e0a452e53152b2f0d569dc9cb3de6a\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 226,\n \"license_type\": \"no_license\",\n \"max_line_length\": 47,\n \"num_lines\": 12,\n \"path\": \"/알고리즘/온라인저지/2022/06/0627/가장 많은 글자.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\ninput = sys.stdin.read\\n\\nS = input().replace('\\\\n', '').replace(' ', '')\\nA = [0] * 26\\nfor s in S:\\n A[ord(s)-97] += 1\\nresult = ''\\nfor i in range(26):\\n if A[i] == max(A):\\n result += chr(i+97)\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.44999998807907104,\n \"alphanum_fraction\": 0.5,\n \"avg_line_length\": 19.14285659790039,\n \"blob_id\": \"2b46e39cc66ae1e35dcac213f6bd4b7fd67fc808\",\n \"content_id\": \"83160b63ed88087627e24e4076fe7dcb2c6ba1fc\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 140,\n \"license_type\": \"no_license\",\n \"max_line_length\": 33,\n \"num_lines\": 7,\n \"path\": \"/알고리즘/온라인저지/2022/11/1128/Fan Death.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = int(input())\\narr = set()\\nfor n in range(1, int(N**0.5)+1):\\n if not N%n:\\n arr.add(n)\\n arr.add(N//n)\\nprint(sum(arr)*5-24)\"\n },\n {\n \"alpha_fraction\": 0.35854342579841614,\n \"alphanum_fraction\": 0.39355742931365967,\n \"avg_line_length\": 27.600000381469727,\n \"blob_id\": \"3b1968678fe2e4a856e62524966e1638eb5f8d4a\",\n \"content_id\": \"3dabdc7f6d8b5db1bae7cc5f2170f0863cb442cc\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 722,\n \"license_type\": \"no_license\",\n \"max_line_length\": 57,\n \"num_lines\": 25,\n \"path\": \"/알고리즘/온라인저지/2022/09/0913/겉넓이 구하기.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"dy, dx = [-1, 1, 0, 0], [0, 0, -1, 1]\\nN, M = map(int, input().split())\\narr = [list(map(int, input().split())) for _ in range(N)]\\nzero = 0\\nresult = 0\\nfor i in range(N):\\n for j in range(M):\\n if arr[i][j] == 0: \\n zero += 1\\n continue\\n now = arr[i][j]\\n while now > 0:\\n face = 4 # 도형의 면\\n if now == arr[i][j]: face += 1\\n y, x = i, j\\n for k in range(4):\\n ny, nx = y+dy[k], x+dx[k]\\n if 0<=ny<N and 0<=nx<M:\\n if arr[ny][nx] >= now:\\n face -= 1\\n result += face\\n now -= 1 \\nprint(result + N*M - zero)\\n\\n# https://www.acmicpc.net/problem/16931\"\n },\n {\n \"alpha_fraction\": 0.3983488082885742,\n \"alphanum_fraction\": 0.4241486191749573,\n \"avg_line_length\": 23.871795654296875,\n \"blob_id\": \"0f7533770f36470f311fd00597c8e4f0d14b5d4e\",\n \"content_id\": \"f1bb2b8be5d7b200bf8e1e5c53cc1bf2d7d1b042\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1085,\n \"license_type\": \"no_license\",\n \"max_line_length\": 63,\n \"num_lines\": 39,\n \"path\": \"/알고리즘/온라인저지/2023/03/0326/부등호.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"K = int(input())\\nsign = input().split()\\nvisited = [0]*10 # 0~9\\nmaxx, minn = \\\"\\\", \\\"\\\"\\n\\ndef check(a, b, K):\\n # 1<2 : True\\n # '1'<'2' : True\\n if K == '<':\\n return a<b # T or F\\n if K == '>':\\n return a>b # T or F\\n\\ndef recur(idx, num):\\n global maxx, minn\\n\\n if idx == K+1:\\n if not minn: # 가장 먼저 부등호를 완성한 숫자가 최소값\\n minn = num\\n else: # 최소값을 찾았을 경우, 이후 나오는 숫자들로 최대값 갱신\\n maxx = num\\n return # 아래 for문 스킵\\n \\n for i in range(10):# 0부터 9까지 \\n if not visited[i]:\\n # 디버깅\\n # if idx != 0:\\n # print(*list(num))\\n # print('', *sign[:len(num)-1])\\n # print(num[-1], sign[idx-1], i)\\n # print()\\n if idx == 0 or check(num[-1], str(i), sign[idx-1]):\\n visited[i] = 1 # visited 찍고\\n recur(idx+1, num+str(i)) # 재귀\\n visited[i] = 0 # visited 풀고\\n\\nrecur(0, \\\"\\\")\\nprint(maxx)\\nprint(minn)\"\n },\n {\n \"alpha_fraction\": 0.5955334901809692,\n \"alphanum_fraction\": 0.6054590344429016,\n \"avg_line_length\": 24.25,\n \"blob_id\": \"68a6e018e663eb982d1eabf625c83c6169e6c248\",\n \"content_id\": \"e0cb7ed285af67c14e5d46d3fdec392e1251b184\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 403,\n \"license_type\": \"no_license\",\n \"max_line_length\": 51,\n \"num_lines\": 16,\n \"path\": \"/알고리즘/온라인저지/2022/10/1012/결혼식.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\n\\nN, M = int(input().rstrip()), int(input().rstrip())\\nresult = set()\\nfriends = [[] for _ in range(N+1)]\\nfor m in range(M):\\n a, b = map(int, input().rstrip().split())\\n friends[a].append(b)\\n friends[b].append(a)\\nfor friend in friends[1]:\\n if friend != 1: result.add(friend)\\n for f in friends[friend]:\\n if f != 1: result.add(f)\\nprint(len(result))\"\n },\n {\n \"alpha_fraction\": 0.5416666865348816,\n \"alphanum_fraction\": 0.5476190447807312,\n \"avg_line_length\": 23.14285659790039,\n \"blob_id\": \"6efab427f96bb5b28fc2b3725472540debacbc24\",\n \"content_id\": \"68db41f4fd197a5828bbaa97b184754efc3b0e81\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 168,\n \"license_type\": \"no_license\",\n \"max_line_length\": 35,\n \"num_lines\": 7,\n \"path\": \"/알고리즘/온라인저지/2023/02/0213/Hard choice.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"A, B, C = map(int, input().split())\\nD, E, F = map(int, input().split())\\nresult = 0\\nif A < D: result += D-A\\nif B < E: result += E-B\\nif C < F: result += F-C\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.44144144654273987,\n \"alphanum_fraction\": 0.477477490901947,\n \"avg_line_length\": 21.299999237060547,\n \"blob_id\": \"f5aab2e47674738ce8a2b4f19b23a49541cb49fe\",\n \"content_id\": \"527f9082c4d4ae09ca5bad082fde6232ae9f2356\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 222,\n \"license_type\": \"no_license\",\n \"max_line_length\": 43,\n \"num_lines\": 10,\n \"path\": \"/알고리즘/온라인저지/2022/07/0727/공 포장하기.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"B = list(map(int, input().split())) # balls\\nresult = tmp = min(B)\\nfor i in range(3):\\n B[i] -= tmp\\n if B[i]:\\n result += B[i]//3\\n B[i] = B[i]%3\\nL = [0, 1, 1, 2, 2] # left\\nresult += L[sum(B)]\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.4736842215061188,\n \"alphanum_fraction\": 0.4912280738353729,\n \"avg_line_length\": 11.052631378173828,\n \"blob_id\": \"e931bd5324ad62edf679af734eee4071fd8f5a63\",\n \"content_id\": \"a93b9af30875fe75e014aa075a63b4894967bca0\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 228,\n \"license_type\": \"no_license\",\n \"max_line_length\": 19,\n \"num_lines\": 19,\n \"path\": \"/알고리즘/온라인저지/2021/12/1216/개표.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"V = int(input())\\n\\nvotes = input()\\n\\navote = 0\\nbvote = 0\\n\\nfor v in votes:\\n if v == 'A':\\n avote += 1\\n else:\\n bvote += 1\\n\\nif avote > bvote:\\n print('A')\\nelif bvote > avote:\\n print('B')\\nelse:\\n print('Tie')\"\n },\n {\n \"alpha_fraction\": 0.4975288212299347,\n \"alphanum_fraction\": 0.51729816198349,\n \"avg_line_length\": 19.965517044067383,\n \"blob_id\": \"2f8509ba839ca9c2bee8defb38e9a574aaa5e282\",\n \"content_id\": \"b3299775651bb70fc39fbb1ff50ae1470aa3d6e6\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 607,\n \"license_type\": \"no_license\",\n \"max_line_length\": 42,\n \"num_lines\": 29,\n \"path\": \"/알고리즘/온라인저지/2022/09/0918/누울 자리를 찾아라.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\n\\ndef lay_check(arr):\\n cnt = 0\\n for i in range(N):\\n size = 0\\n for j in range(N):\\n if arr[i][j] == '.': size += 1\\n else:\\n if size>=2: cnt += 1 \\n size = 0\\n if size>=2: cnt += 1\\n result.append(cnt)\\n\\nN = int(input().rstrip())\\narr = [input().rstrip() for _ in range(N)]\\nrotated_arr = []\\nresult = []\\nlay_check(arr)\\nfor j in range(N):\\n tmp = ''\\n for i in range(N):tmp += arr[i][j]\\n rotated_arr.append(tmp)\\nlay_check(rotated_arr)\\nprint(*result)\\n\\n# https://www.acmicpc.net/problem/1652\"\n },\n {\n \"alpha_fraction\": 0.3913043439388275,\n \"alphanum_fraction\": 0.43478259444236755,\n \"avg_line_length\": 22.5,\n \"blob_id\": \"c918e74bf5070db4fa9b5749a001e13aea856f58\",\n \"content_id\": \"b37021c44aa5d293946be4bf1ac24cb1d9edc18e\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 46,\n \"license_type\": \"no_license\",\n \"max_line_length\": 29,\n \"num_lines\": 2,\n \"path\": \"/알고리즘/온라인저지/2023/06/0601/Робинзон Крузо.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = int(input())\\nprint('V'*(N//5) + 'I'*(N%5))\"\n },\n {\n \"alpha_fraction\": 0.45483359694480896,\n \"alphanum_fraction\": 0.49286845326423645,\n \"avg_line_length\": 14.023809432983398,\n \"blob_id\": \"de6e50f47d4beb06b171f8efb430021b74c431a9\",\n \"content_id\": \"16102c2cb104c07a67a5e02beb8f56200af909c0\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 755,\n \"license_type\": \"no_license\",\n \"max_line_length\": 34,\n \"num_lines\": 42,\n \"path\": \"/알고리즘/온라인저지/2022/01/0116/달팽이.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# 상우하좌\\n\\ndy = (-1, 0, 1, 0)\\ndx = (0, 1, 0, -1)\\n\\n\\\"\\\"\\\"\\nN이 홀수일때 짝수일때 각각 스타트포인트 잡아서\\n델타 이동으로 배열을 채우면서\\nK의 좌표를 찾아서 저장 후\\n배열 다 채우고 배열 출력\\nK의 좌표 출력\\n\\\"\\\"\\\"\\n\\nN = int(input())\\nK = int(input())\\n\\nstart_x = start_y = N//2\\n\\narr = [[0] * N for _ in range(N)]\\n\\narr[start_y][start_x] = 1\\n\\ndir = 0\\na = b = 0\\n\\nfor i in range(2, N**2 + 1):\\n start_x = start_x + dx[dir]\\n start_y = start_y + dy[dir]\\n\\n arr[start_y][start_x] = i\\n if i == K:\\n a = start_y\\n b = start_x\\n\\n tp_x = start_x + dx[(dir+1)%4]\\n tp_y = start_y + dy[(dir+1)%4]\\n if not arr[tp_y][tp_x]:\\n dir = (dir+1)%4\\n\\nfor ar in arr:\\n print(*ar)\\nprint(a+1, b+1) \"\n },\n {\n \"alpha_fraction\": 0.5961538553237915,\n \"alphanum_fraction\": 0.6346153616905212,\n \"avg_line_length\": 38.25,\n \"blob_id\": \"63ecef5e152618b9d7235593cf70011bb53e205e\",\n \"content_id\": \"8a3110d3ba02a71c216274ca12c34588e9630ed3\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 156,\n \"license_type\": \"no_license\",\n \"max_line_length\": 42,\n \"num_lines\": 4,\n \"path\": \"/알고리즘/온라인저지/2022/08/0822/Which Alien.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N, M = int(input()), int(input())\\nif N>=3 and M<=4: print('TroyMartian')\\nif N<=6 and M>=2: print('VladSaturnian')\\nif N<=2 and M<=3: print('GraemeMercurian')\"\n },\n {\n \"alpha_fraction\": 0.37226277589797974,\n \"alphanum_fraction\": 0.43795621395111084,\n \"avg_line_length\": 9.615385055541992,\n \"blob_id\": \"3aa8fc59e05056b739e44176f099e12bea154b3b\",\n \"content_id\": \"f57e1d95598c7fe21e78206aabeffbc5636e0f30\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 137,\n \"license_type\": \"no_license\",\n \"max_line_length\": 32,\n \"num_lines\": 13,\n \"path\": \"/알고리즘/온라인저지/2021/12/1213/오븐 시계.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"A, B = map(int, input().split())\\nC = int(input())\\n\\nB += C\\n\\nwhile B >= 60:\\n A += 1\\n B -= 60\\n\\nwhile A >= 24:\\n A -= 24\\n\\nprint(A, B)\"\n },\n {\n \"alpha_fraction\": 0.43923240900039673,\n \"alphanum_fraction\": 0.4648187756538391,\n \"avg_line_length\": 25.11111068725586,\n \"blob_id\": \"0444435160a7b188ae9f1669ae6ea59875494cde\",\n \"content_id\": \"d97f7129a9f8d908c353630127d807ec40727d31\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 469,\n \"license_type\": \"no_license\",\n \"max_line_length\": 39,\n \"num_lines\": 18,\n \"path\": \"/알고리즘/온라인저지/2022/06/0629/역사.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N, M = map(int, input().split())\\narr = [[0]*N for _ in range(N)]\\nfor m in range(M):\\n a, b = map(int, input().split())\\n arr[a-1][b-1] = 1\\nfor k in range(N):\\n for a in range(N):\\n for b in range(N):\\n if arr[a][k] and arr[k][b]:\\n arr[a][b] = 1\\nfor s in range(int(input())):\\n a, b = map(int, input().split()) \\n result = 0\\n if arr[a-1][b-1]:\\n result = -1\\n elif arr[b-1][a-1]:\\n result = 1\\n print(result)\"\n },\n {\n \"alpha_fraction\": 0.48275861144065857,\n \"alphanum_fraction\": 0.517241358757019,\n \"avg_line_length\": 29,\n \"blob_id\": \"9a5efa2adf415e3529731e08057e9b907438940e\",\n \"content_id\": \"58b612214433657cd93f0c755b081f6b72e4c8d1\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 29,\n \"license_type\": \"no_license\",\n \"max_line_length\": 29,\n \"num_lines\": 1,\n \"path\": \"/알고리즘/온라인저지/2022/03/0303/알고리즘 수업 - 알고리즘의 수행 시간 2.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"print(input(), '\\\\n1', sep='')\"\n },\n {\n \"alpha_fraction\": 0.3238866329193115,\n \"alphanum_fraction\": 0.4048582911491394,\n \"avg_line_length\": 19.66666603088379,\n \"blob_id\": \"49fb93bcdf813804e9c7e3a59962d99f53b3352e\",\n \"content_id\": \"49d52541f15d698e1b1747ad7e0a21556e901b8a\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 247,\n \"license_type\": \"no_license\",\n \"max_line_length\": 45,\n \"num_lines\": 12,\n \"path\": \"/알고리즘/온라인저지/2022/06/0608/날짜 계산.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"E, S, M = map(int, input().split())\\ne, s, m = 1, 1, 1\\nresult = 1\\nwhile (E, S, M) != (e, s, m):\\n e, s, m, result = e+1, s+1, m+1, result+1\\n if e > 15:\\n e -= 15\\n if s > 28:\\n s -= 28\\n if m > 19:\\n m -= 19\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.4895833432674408,\n \"alphanum_fraction\": 0.5104166865348816,\n \"avg_line_length\": 18.399999618530273,\n \"blob_id\": \"b8c6cf6f4868450d5e6fc7163152b793bcb29ab5\",\n \"content_id\": \"10ada1d6d7f292fade523ca3f2e22409ba86ecce\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 96,\n \"license_type\": \"no_license\",\n \"max_line_length\": 29,\n \"num_lines\": 5,\n \"path\": \"/알고리즘/온라인저지/2023/04/0404/골뱅이 찍기 - ㄴ.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = int(input())\\nA = '@'*N\\nB = '@'*N*5\\nfor _ in range(N*4): print(A)\\nfor _ in range(N): print(B)\"\n },\n {\n \"alpha_fraction\": 0.4689265489578247,\n \"alphanum_fraction\": 0.5819209218025208,\n \"avg_line_length\": 18.77777862548828,\n \"blob_id\": \"90b991c4aaec2c8237d80882a5e922cc5b7ad393\",\n \"content_id\": \"0d79f3edf4f4b0339ebc88136a43287911e2ec3b\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 177,\n \"license_type\": \"no_license\",\n \"max_line_length\": 42,\n \"num_lines\": 9,\n \"path\": \"/알고리즘/온라인저지/2022/09/0924/피보나치 수 7.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\n\\nN = int(input().rstrip())\\ndp = [0, 1] + [0]*int(1e7)\\nfor i in range(2, int(1e7)):\\n dp[i] = (dp[i-1] + dp[i-2])%1000000007\\nprint(dp[N])\"\n },\n {\n \"alpha_fraction\": 0.5,\n \"alphanum_fraction\": 0.550000011920929,\n \"avg_line_length\": 40,\n \"blob_id\": \"25320a376f968d5665ab580f85c95e7cb634f43f\",\n \"content_id\": \"fdf095285bc58fe316824fe78fc545d918c3d9ed\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 40,\n \"license_type\": \"no_license\",\n \"max_line_length\": 40,\n \"num_lines\": 1,\n \"path\": \"/알고리즘/온라인저지/2023/05/0525/연세여 사랑한다.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"print(abs(ord('I') - ord(input())) + 84)\"\n },\n {\n \"alpha_fraction\": 0.45145630836486816,\n \"alphanum_fraction\": 0.4805825352668762,\n \"avg_line_length\": 19.700000762939453,\n \"blob_id\": \"3e8b8ac326a8e9b9496253ea6028961509c3f71f\",\n \"content_id\": \"ae48678ee8951689ee285d6d3b1893bc1f686660\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 206,\n \"license_type\": \"no_license\",\n \"max_line_length\": 39,\n \"num_lines\": 10,\n \"path\": \"/알고리즘/온라인저지/2023/03/0307/Telemarketer or not.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"A = int(input())\\nB = int(input())\\nC = int(input())\\nD = int(input())\\nresult = 0\\nif A == 8 or A == 9:\\n if D == 8 or D == 9:\\n if C == B:\\n result = 1\\nprint('ignore' if result else 'answer')\"\n },\n {\n \"alpha_fraction\": 0.5178267955780029,\n \"alphanum_fraction\": 0.5432937145233154,\n \"avg_line_length\": 25.81818199157715,\n \"blob_id\": \"9a925dfadfcceee1232c6bd95c91e977cb6debb5\",\n \"content_id\": \"431dab2af24902a5bb5522932a290f45a46e11fd\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 589,\n \"license_type\": \"no_license\",\n \"max_line_length\": 66,\n \"num_lines\": 22,\n \"path\": \"/알고리즘/온라인저지/2022/10/1002/점프왕 쩰리 (Small).py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\nfrom collections import deque\\n\\ninput = sys.stdin.readline\\ndy, dx = [1, 0], [0, 1] # down, right\\n\\nN = int(input().rstrip())\\narr = [list(map(int, input().rstrip().split())) for _ in range(N)]\\nvisited = [[0]*N for _ in range(N)]\\nQ = deque()\\nQ.append((0, 0))\\nvisited[0][0] = 1\\nwhile Q:\\n y, x = Q.popleft()\\n if y == x == N-1: print('HaruHaru'); break\\n jump = arr[y][x]\\n for i in range(2):\\n ny, nx = y+dy[i]*jump, x+dx[i]*jump\\n if 0<=ny<N and 0<=nx<N and not visited[ny][nx]:\\n Q.append((ny, nx))\\n visited[ny][nx] = 1\\nelse: print('Hing')\"\n },\n {\n \"alpha_fraction\": 0.5714285969734192,\n \"alphanum_fraction\": 0.5844155550003052,\n \"avg_line_length\": 18.375,\n \"blob_id\": \"59f2a147b4f30cd611c1aed4b4f5bd3c2b19dc26\",\n \"content_id\": \"075e3d74778d18a082f4728e126641b58522499c\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 154,\n \"license_type\": \"no_license\",\n \"max_line_length\": 46,\n \"num_lines\": 8,\n \"path\": \"/알고리즘/온라인저지/2023/06/0614/Terms of Office.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"X = int(input())\\nY = int(input())\\nresult = []\\nwhile X<=Y:\\n result.append(X)\\n X += 60\\nfor r in result:\\n print(f'All positions change in year {r}')\"\n },\n {\n \"alpha_fraction\": 0.39401495456695557,\n \"alphanum_fraction\": 0.39650872349739075,\n \"avg_line_length\": 21.33333396911621,\n \"blob_id\": \"b8342aac27029be3feb201ce23223cdb1f5b2497\",\n \"content_id\": \"49da4f87e2b5b62de30dfe68753a8e419bdb7aa5\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 401,\n \"license_type\": \"no_license\",\n \"max_line_length\": 27,\n \"num_lines\": 18,\n \"path\": \"/알고리즘/온라인저지/2022/06/0603/계산기 프로그램.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"result = 0\\nwhile True:\\n order = input()\\n if order == '=':\\n print(result)\\n break\\n elif order in '+-*/':\\n num = int(input())\\n if order == '+':\\n result += num\\n elif order == '-':\\n result -= num\\n elif order == '*':\\n result *= num\\n elif order == '/':\\n result //= num\\n else:\\n result = int(order)\"\n },\n {\n \"alpha_fraction\": 0.4428044259548187,\n \"alphanum_fraction\": 0.468634694814682,\n \"avg_line_length\": 13.315789222717285,\n \"blob_id\": \"f1c7939216383a759564141cee45f9acd79ec359\",\n \"content_id\": \"324bc01165c18301cd23e57547b71e1ef02deeb6\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 271,\n \"license_type\": \"no_license\",\n \"max_line_length\": 25,\n \"num_lines\": 19,\n \"path\": \"/알고리즘/온라인저지/2022/02/0202/홀수.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"summ = 0\\nminn = 100\\nis_odd = False\\n\\nfor _ in range(7):\\n num = int(input())\\n\\n if num%2:\\n if num < minn:\\n minn = num\\n summ += num\\n if not is_odd:\\n is_odd = True\\n\\nif is_odd:\\n print(summ)\\n print(minn)\\nelse:\\n print(-1)\"\n },\n {\n \"alpha_fraction\": 0.4083601236343384,\n \"alphanum_fraction\": 0.5112540125846863,\n \"avg_line_length\": 14.600000381469727,\n \"blob_id\": \"922aab98faeb3f187637a572273b34bfb2c699c5\",\n \"content_id\": \"4233d6e3a376f1e84c11e9a7ba29844a1ac9c91a\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 351,\n \"license_type\": \"no_license\",\n \"max_line_length\": 60,\n \"num_lines\": 20,\n \"path\": \"/알고리즘/온라인저지/2022/01/0131/2007년.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"\\\"\\\"\\\"\\n1월 1일은 월요일\\nx월y일이 1년중 몇번째 날인지 구해서\\nmod 7\\n\\\"\\\"\\\"\\n\\nx, y = map(int, input().split())\\n\\nday = y-1\\n\\nif x > 1:\\n month = [31, 28, 31, 30, 31, 30, 31, 31, 30, 31, 30, 31]\\n for i in range(x-1):\\n day += month[i]\\n\\nweek = ['MON', 'TUE', 'WED', 'THU', 'FRI', 'SAT', 'SUN']\\n\\nweekday = day % 7\\n\\nprint(week[weekday])\"\n },\n {\n \"alpha_fraction\": 0.3866666555404663,\n \"alphanum_fraction\": 0.41777777671813965,\n \"avg_line_length\": 21.600000381469727,\n \"blob_id\": \"1e4e93491a0ad54e41f6bef17b123ec3824b2adf\",\n \"content_id\": \"19fb859599c4ff8adb51f9abfaa7902a8f5cbf71\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 225,\n \"license_type\": \"no_license\",\n \"max_line_length\": 59,\n \"num_lines\": 10,\n \"path\": \"/알고리즘/온라인저지/2022/12/1214/전북대학교.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = int(input())\\nif not N%2:\\n print('I LOVE CBNU')\\nelse:\\n print('*'*N)\\n space = N//2\\n print(' '*space + '*')\\n for _ in range(N//2):\\n space -= 1\\n print(' '*space + '*'+' '*(((N//2)-space)*2-1)+'*')\"\n },\n {\n \"alpha_fraction\": 0.4701492488384247,\n \"alphanum_fraction\": 0.503731369972229,\n \"avg_line_length\": 25.899999618530273,\n \"blob_id\": \"253cdc08615cd0b512edb5495c66af2d3dea533d\",\n \"content_id\": \"77e65dfe341c120ae8b96a7b4532a60b542bb290\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 268,\n \"license_type\": \"no_license\",\n \"max_line_length\": 53,\n \"num_lines\": 10,\n \"path\": \"/알고리즘/온라인저지/2022/06/0629/정수 삼각형.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = int(input())\\narr = []\\nfor n in range(N):\\n tmp = [0] + list(map(int, input().split())) + [0]\\n arr.append(tmp)\\nfor i in range(1, len(arr)):\\n for j in range(1, len(arr[i])-1):\\n tmp = arr[i-1][j-1:j+1]\\n arr[i][j] += max(tmp)\\nprint(max(arr[N-1]))\"\n },\n {\n \"alpha_fraction\": 0.5648535490036011,\n \"alphanum_fraction\": 0.5648535490036011,\n \"avg_line_length\": 29,\n \"blob_id\": \"f62db0002cfb38af8f6b306601e4e0571bf435e8\",\n \"content_id\": \"1624de62176ce8987f705c340191854b2512eda3\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 239,\n \"license_type\": \"no_license\",\n \"max_line_length\": 49,\n \"num_lines\": 8,\n \"path\": \"/알고리즘/온라인저지/2023/05/0511/Gnome Sequencing.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"print('Gnomes:')\\nfor i in range(int(input())):\\n tmp = list(map(int, input().split()))\\n A, B = sorted(tmp), sorted(tmp, reverse=True)\\n result = 'Unordered'\\n if (tmp == A or tmp == B):\\n result = 'Ordered'\\n print(result)\"\n },\n {\n \"alpha_fraction\": 0.42489269375801086,\n \"alphanum_fraction\": 0.4849785268306732,\n \"avg_line_length\": 13.5625,\n \"blob_id\": \"79fb8f5445a103d423c659d163b5c05ea05a5ed4\",\n \"content_id\": \"65a7d37d19f3761289a19ddea3f19d2b678e45b7\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 233,\n \"license_type\": \"no_license\",\n \"max_line_length\": 22,\n \"num_lines\": 16,\n \"path\": \"/알고리즘/온라인저지/2022/02/0212/대표값.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"dp = [0] * (101)\\nsumm = 0\\nmode = 0\\nmaxx = 0\\n\\nfor i in range(10):\\n num = int(input())\\n summ += num\\n tmp = num//10\\n dp[tmp] += 1\\n if dp[tmp] > maxx:\\n maxx = dp[tmp]\\n mode = num\\n\\nprint(summ//10)\\nprint(mode)\\n\"\n },\n {\n \"alpha_fraction\": 0.47252747416496277,\n \"alphanum_fraction\": 0.593406617641449,\n \"avg_line_length\": 17.266666412353516,\n \"blob_id\": \"6794d53ef724942b96a757a3175d018697dbc51c\",\n \"content_id\": \"ed6acb1c3707dbc92a48a87e54463165b8256a7b\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 395,\n \"license_type\": \"no_license\",\n \"max_line_length\": 49,\n \"num_lines\": 15,\n \"path\": \"/알고리즘/SWEA/LEARN/Course/1. Programming Beginner/파이썬 프로그래밍 기초(2)/27차시 3. 자료구조 – 셋, 딕셔너리 - 연습문제 2.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"phone = {\\n '홍길동': '010-1111-1111',\\n '이순신': '010-1111-2222',\\n '강감찬': '010-1111-3333',\\n}\\n\\nprint('아래 학생들의 전화번호를 조회할 수 있습니다.')\\nfor name in phone:\\n print(name)\\n\\nprint('전화번호를 조회하고자 하는 학생의 이름을 입력하십시오.')\\n\\ntmp = input()\\n\\nprint('{}의 전화번호는 {}입니다.'.format(tmp, phone[tmp]))\"\n },\n {\n \"alpha_fraction\": 0.4720279574394226,\n \"alphanum_fraction\": 0.5262237787246704,\n \"avg_line_length\": 18.724138259887695,\n \"blob_id\": \"0354f11f81581962fb45da14e33130478adaf459\",\n \"content_id\": \"27d3003d4bdbe29d2f8fb37d261bd9d0e1e2e7d9\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 572,\n \"license_type\": \"no_license\",\n \"max_line_length\": 49,\n \"num_lines\": 29,\n \"path\": \"/알고리즘/온라인저지/2021/12/1216/주사위 게임.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = int(input())\\n\\nb = []\\n\\nfor n in range(N):\\n\\n a = list(map(int, input().split()))\\n\\n dice_num_count = [0 for _ in range(6)]\\n\\n for i in a:\\n dice_num_count[i-1] += 1\\n\\n same_or_max = 0\\n result = 0\\n\\n if 3 in dice_num_count:\\n same_or_max = dice_num_count.index(3) + 1\\n result = 10000 + same_or_max * 1000\\n elif 2 in dice_num_count:\\n same_or_max = dice_num_count.index(2) + 1\\n result = 1000 + same_or_max * 100\\n else:\\n same_or_max = max(a)\\n result = same_or_max * 100\\n\\n b.append(result)\\n\\nprint(max(b))\\n\"\n },\n {\n \"alpha_fraction\": 0.5839999914169312,\n \"alphanum_fraction\": 0.5839999914169312,\n \"avg_line_length\": 30.5,\n \"blob_id\": \"16acc665d09f482b029015338164b1b4238dcdf9\",\n \"content_id\": \"0200e9845c3719ce8ca2a36a90dac62e9991f9ae\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 125,\n \"license_type\": \"no_license\",\n \"max_line_length\": 40,\n \"num_lines\": 4,\n \"path\": \"/알고리즘/온라인저지/2022/05/0513/헬멧과 조끼.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N, M = map(int, input().split())\\nA = max(list(map(int, input().split())))\\nB = max(list(map(int, input().split())))\\nprint(A+B)\"\n },\n {\n \"alpha_fraction\": 0.48040884733200073,\n \"alphanum_fraction\": 0.5332197546958923,\n \"avg_line_length\": 24.565217971801758,\n \"blob_id\": \"a7b1ad3bd5f6f3aace344e928f3a49bc1f52287c\",\n \"content_id\": \"4b542233ffd8b4d91ce9879265dba67ece455330\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 587,\n \"license_type\": \"no_license\",\n \"max_line_length\": 55,\n \"num_lines\": 23,\n \"path\": \"/알고리즘/온라인저지/2022/10/1006/데스 나이트.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\nfrom collections import deque\\n\\ninput = sys.stdin.readline\\ndy = [-2, -2, 0, 0, 2, 2]\\ndx = [-1, 1, -2, 2, -1, 1]\\n\\nN = int(input().rstrip())\\nr1, c1, r2, c2 = map(int, input().rstrip().split())\\nvisited = [[0]*N for _ in range(N)]\\nQ = deque()\\nQ.append((r1, c1, 0))\\nvisited[r1][c1] = 1\\nresult = -1\\nwhile Q:\\n y, x, move = Q.popleft()\\n if y == r2 and x == c2: result = move; break\\n for i in range(6):\\n ny, nx = y+dy[i], x+dx[i]\\n if 0<=ny<N and 0<=nx<N and not visited[ny][nx]:\\n Q.append((ny, nx, move+1))\\n visited[ny][nx] = 1\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.4341636896133423,\n \"alphanum_fraction\": 0.4590747356414795,\n \"avg_line_length\": 11.260869979858398,\n \"blob_id\": \"d4906c3d32a50e78c72d07b6d4757dbb4504e31c\",\n \"content_id\": \"ebfb47b421a99388f94e3edbc9dfe08b03977fe9\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 281,\n \"license_type\": \"no_license\",\n \"max_line_length\": 26,\n \"num_lines\": 23,\n \"path\": \"/알고리즘/온라인저지/2022/02/0205/방학 숙제.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"L = int(input())\\nA = int(input())\\nB = int(input())\\nC = int(input())\\nD = int(input())\\n\\nmaxx = 0\\n\\nA_by_C = 0\\nif A%C == 0:\\n A_by_C = A//C\\nelse:\\n A_by_C = A//C + 1\\n\\nB_by_D = 0\\nif B%D == 0:\\n B_by_D = B//D\\nelse:\\n B_by_D = B//D + 1\\n\\nmaxx = max(A_by_C, B_by_D)\\n\\nprint(L - maxx)\"\n },\n {\n \"alpha_fraction\": 0.5180723071098328,\n \"alphanum_fraction\": 0.5397590398788452,\n \"avg_line_length\": 19.799999237060547,\n \"blob_id\": \"3a6f1801bf11ea0f85e7d4176457e043d2a30130\",\n \"content_id\": \"5f35053c1cb3fd11e653a6f94f48fff514f29dcf\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 415,\n \"license_type\": \"no_license\",\n \"max_line_length\": 42,\n \"num_lines\": 20,\n \"path\": \"/알고리즘/온라인저지/2022/11/1124/비밀 이메일.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\n\\nmessage = input().rstrip()\\nlength = len(message)\\ndivs = []\\nfor i in range(1, int((length+1)**0.5)+1):\\n if not length%i:\\n divs.append((i, length//i))\\nR, C = divs[-1]\\narr = [[0]*C for _ in range(R)]\\nk = 0\\nfor j in range(C):\\n for i in range(R):\\n arr[i][j] = message[k]\\n k += 1\\nfor i in range(R):\\n for j in range(C):\\n print(arr[i][j], end='')\"\n },\n {\n \"alpha_fraction\": 0.40611353516578674,\n \"alphanum_fraction\": 0.4192139804363251,\n \"avg_line_length\": 27.75,\n \"blob_id\": \"46b0ea7e5dea5af9c462951e28037163c08e78b2\",\n \"content_id\": \"b64acdfb4d99a1a4ab99823f4a72e7027b2dbb45\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 229,\n \"license_type\": \"no_license\",\n \"max_line_length\": 51,\n \"num_lines\": 8,\n \"path\": \"/알고리즘/온라인저지/2023/03/0319/Viva la Diferencia.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"while True:\\n A, B, C, D = map(int, input().split())\\n if A == B == C == D == 0: break\\n result = 0\\n while not (A == B == C == D):\\n A, B, C, D = map(abs, (A-B, B-C, C-D, D-A))\\n result += 1\\n print(result)\"\n },\n {\n \"alpha_fraction\": 0.38591548800468445,\n \"alphanum_fraction\": 0.42323943972587585,\n \"avg_line_length\": 40.79411697387695,\n \"blob_id\": \"52abcdd05eb4a43523da52633f7ed4d691a9f081\",\n \"content_id\": \"c9174e807f57df57b0599eb474c53b3c9c9a902a\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1832,\n \"license_type\": \"no_license\",\n \"max_line_length\": 89,\n \"num_lines\": 34,\n \"path\": \"/알고리즘/온라인저지/2022/09/0908/십자뒤집기.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from itertools import combinations as comb\\n\\ncoordinate = [None, \\n (0, 0), (0, 1), (0, 2),\\n (1, 0), (1, 1), (1, 2),\\n (2, 0), (2, 1), (2, 2),\\n] # 3x3 사각형의 좌표들\\ndy, dx = [0, -1, 1, 0, 0], [0, 0, 0, -1, 1] # 자기 자신 + 상하좌우\\n\\nP = int(input())\\nfor p in range(P):\\n answer = [list(input()) for _ in range(3)] # 정답 배열\\n result = 0 # 최소 클릭 횟수\\n for i in range(1, 10): # 누르는 횟수 1부터 9까지 브루트포스\\n tmp = list(comb(range(1, 10), i)) # i번 누를 때 나올 수 있는 조합\\n for t in tmp: # 클릭할 수 있는 조합들 중에서\\n if result: break # 정답을 찾았다면 종료\\n arr = [list('.'*3) for _ in range(3)] # 답안지\\n for j in t: # 클릭할 수 있는 조합들에서\\n coor = coordinate[j] # 클릭할 좌표\\n y, x = coor[0], coor[1] # 좌표의 y, x\\n for k in range(5): # 자기 자신과 상하좌우, 총 5지점의 색을 뒤집는다\\n ny, nx = y+dy[k], x+dx[k] # 색을 뒤집을 좌표들\\n if 0<=ny<3 and 0<=nx<3: # 새로 얻은 좌표들은 사각형 안에 있어야 한다 (3x3 사각형이니 망정이지;;)\\n if arr[ny][nx] == '*': # * -> .\\n arr[ny][nx] = '.'\\n elif arr[ny][nx] == '.': # . -> *\\n arr[ny][nx] = '*'\\n flag = True # 구한 답안과 정답을 비교할 것\\n for l in range(3):\\n if arr[l] != answer[l]: # 답안과 정답이 다른 줄이 나오면 그 답안은 정답이 아님\\n flag = False\\n if flag: result = i # 답안의 모든 줄이 정답과 일치하면 해당 클릭 수를 결과로 저장\\n print(result)\"\n },\n {\n \"alpha_fraction\": 0.4691357910633087,\n \"alphanum_fraction\": 0.5020576119422913,\n \"avg_line_length\": 33.57143020629883,\n \"blob_id\": \"e44458d7fa8a4c1738fd8abaa98b90feb23228ce\",\n \"content_id\": \"7fd03f61d54ca516e7a787c0e9b200a813552eee\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 243,\n \"license_type\": \"no_license\",\n \"max_line_length\": 52,\n \"num_lines\": 7,\n \"path\": \"/알고리즘/[템플릿]/에라토스테네스의 체/에라토스테네스의 체.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"def prime_list(size):\\n sieve = [True]*(size+1)\\n for i in range(2, int(size**0.5)+1):\\n if sieve[i]:\\n for j in range(i+i, size+1, i):\\n sieve[j] = False\\n return [i for i in range(2, size+1) if sieve[i]]\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.6521739363670349,\n \"alphanum_fraction\": 0.6645962595939636,\n \"avg_line_length\": 21,\n \"blob_id\": \"0c031accf3d3c6e39bc91b862adc603140989c13\",\n \"content_id\": \"9f604bea7c74a63f660f966f7279e1d92f993c98\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 809,\n \"license_type\": \"no_license\",\n \"max_line_length\": 54,\n \"num_lines\": 22,\n \"path\": \"/알고리즘/온라인저지/2022/09/0911/연속합.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = int(input())\\nnums = list(map(int, input().split()))\\nresult = [nums[0]]\\nfor i in range(len(nums)-1):\\n result.append(max(result[i]+nums[i+1], nums[i+1]))\\nprint(max(result))\\n\\n\\\"\\\"\\\"\\n한 시간을 머리를 박았는데\\n접근도 못하고\\n답지를 봤더니 이렇게 허무할 줄은 몰랐다\\n실패요인은\\nDP라는 태그를 보고 그 계산값들을 저장하면서\\n들고 간다는 것 까지는 이해하였지만\\n어떻게 들고 가는지, 그 과정을 이해하지 못하였다\\nresult[i] : min(여기까지 끌고온 연속합, i번째 값)\\nresult[i]+nums[i+1] : 구해온 연속합에 다음 수를 더한 값\\nnums[i+1] : 현재 값\\nresult에는, 최대값이 될 수 있는\\n구한 연속값들이 모두 들어있고\\n그 중에 최대값을 max(result)를 통해 출력하는 문제였다\\n\\\"\\\"\\\"\"\n },\n {\n \"alpha_fraction\": 0.43529412150382996,\n \"alphanum_fraction\": 0.4588235318660736,\n \"avg_line_length\": 24.600000381469727,\n \"blob_id\": \"6836023895af0b8ed822741f6e47bfcd2fbba9a5\",\n \"content_id\": \"06d6f4eab9a644c2e2c7960d4188da1e1f821089\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 255,\n \"license_type\": \"no_license\",\n \"max_line_length\": 46,\n \"num_lines\": 10,\n \"path\": \"/알고리즘/온라인저지/2022/11/1130/팬그램.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"while True:\\n S = input()\\n if S == '*': break\\n alphabet = [0]*26\\n for s in S:\\n if s == ' ': continue\\n tmp = ord(s)-ord('a')\\n if not alphabet[tmp]:\\n alphabet[tmp] = 1\\n print('Y' if sum(alphabet) == 26 else 'N')\"\n },\n {\n \"alpha_fraction\": 0.45945945382118225,\n \"alphanum_fraction\": 0.5135135054588318,\n \"avg_line_length\": 37,\n \"blob_id\": \"bdeb59730db9e56be932d7b2172b19cf633ab808\",\n \"content_id\": \"bc6f838a66be475816fcf39be4354abbbfc2027f\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 37,\n \"license_type\": \"no_license\",\n \"max_line_length\": 37,\n \"num_lines\": 1,\n \"path\": \"/알고리즘/온라인저지/2022/03/0303/알고리즘 수업 - 알고리즘의 수행 시간 3.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"print(int(input())**2, '\\\\n2', sep='')\"\n },\n {\n \"alpha_fraction\": 0.47445255517959595,\n \"alphanum_fraction\": 0.5328466892242432,\n \"avg_line_length\": 16.25,\n \"blob_id\": \"6e7252763012fbec27dabf8250f9295df022dbea\",\n \"content_id\": \"0e14d78425ec89f745a3548b14287661365b5102\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 137,\n \"license_type\": \"no_license\",\n \"max_line_length\": 34,\n \"num_lines\": 8,\n \"path\": \"/알고리즘/온라인저지/2022/02/0205/과제 안 내신 분.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"table = [False] * 30\\n\\nfor _ in range(28):\\n table[int(input()) - 1] = True\\n\\nfor i in range(30):\\n if not table[i]:\\n print(i+1)\"\n },\n {\n \"alpha_fraction\": 0.5622775554656982,\n \"alphanum_fraction\": 0.5836299061775208,\n \"avg_line_length\": 30.33333396911621,\n \"blob_id\": \"745c75bad8df0de66f3cbda545a86f8bc47ca668\",\n \"content_id\": \"6e8a3ab642459928f90c7f561d8e4587166a75d1\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 427,\n \"license_type\": \"no_license\",\n \"max_line_length\": 45,\n \"num_lines\": 9,\n \"path\": \"/알고리즘/온라인저지/2021/07/0731/언제까지 더해야 할까.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"a = int(input())\\nlast_num = 1 # 출력값, 초기값은 1\\nsum_all = 0 # 1부터 전부 더한 값\\nwhile sum_all < a: # 전부 더한 값이 입력값보다 작을 때\\n sum_all += last_num # 1부터 하나씩 더한다\\n if sum_all >= a: # 전부 더한 값이 입력값보다 크거나 같으면\\n break # while문 종료\\n last_num += 1 # 그렇지 않으면 출력값을 계속 더하고\\nprint(last_num) # 출력\"\n },\n {\n \"alpha_fraction\": 0.5659340620040894,\n \"alphanum_fraction\": 0.5879120826721191,\n \"avg_line_length\": 17.299999237060547,\n \"blob_id\": \"2efc53685c3ed08b1f3678f1d782519287602ee0\",\n \"content_id\": \"9a8f13950ad3c6e88096fcb24d97ce383d45657b\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 182,\n \"license_type\": \"no_license\",\n \"max_line_length\": 33,\n \"num_lines\": 10,\n \"path\": \"/알고리즘/온라인저지/2022/10/1025/일반 화학 실험.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\n\\nnow = float(input().rstrip())\\nwhile True:\\n D = float(input().rstrip())\\n if D >= 999: break\\n print('{:.2f}'.format(D-now))\\n now = D\"\n },\n {\n \"alpha_fraction\": 0.5165125727653503,\n \"alphanum_fraction\": 0.5640686750411987,\n \"avg_line_length\": 26.071428298950195,\n \"blob_id\": \"9cada81095d39a18099e37bc206f644d9c3ef7bb\",\n \"content_id\": \"ed8d61ebda3f947fa9a950051f2d7f595ea6b84c\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1263,\n \"license_type\": \"no_license\",\n \"max_line_length\": 57,\n \"num_lines\": 28,\n \"path\": \"/알고리즘/온라인저지/2021/08/0808/A→B.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"\\\"\\\"\\\"\\nA, B = 시작값, 결과값\\n2를 곱하거나, 맨 뒤에 1을 넣거나\\nA -> B로 가는 연산의 최솟값\\nB의 1의자리가 1이면 직전 연산에서 1추가를 실행한것\\n 1을 빼주고\\nB의 1의자리가 1이 아니고 2의배수면 직전 연산에서 2 곱하기를 실행한것\\n 2를 나눠주고\\nB를 시작으로 A까지 가는 코드를 구성\\n만들 수 없는 경우를 찾는법?\\n\\n\\\"\\\"\\\"\\n\\nimport sys # sys.stdin.readline()\\nA, B = map(int, sys.stdin.readline().split()) # A, B 입력받고\\ncount = 0 # 결과값 초기화\\nwhile B != A: # A와 B가 같아질때까지 while문 반복\\n if B%10 == 1: # B의 1의자리수가 1이면 직전 연산에서 맨 뒤에 1을 추가한 것\\n B //= 10 # 10으로 나눈 몫을 반환하여 1을 제거\\n count += 1 # 연산 카운트 +1\\n else: # B의 1의자리수가 1이 아니면 직전연산에서 *2를 한 것\\n B /= 2 # 2로 나눠주고\\n count += 1 # 연산 카운트 +1\\n if B < A: # 연산을 계속했는데 B가 A로 가지 못하고 A보다 작아지면\\n # B에서 A를 만들 수 없으니\\n count = -2 # 결과값에 1 더해질 경우를 포함해 카운트를 -2로 저장\\n break # while문 종료\\nprint(count + 1) # 출력\"\n },\n {\n \"alpha_fraction\": 0.6086956262588501,\n \"alphanum_fraction\": 0.6304348111152649,\n \"avg_line_length\": 46,\n \"blob_id\": \"3f8f4d576c681084211daf1c804bbab36bf1e043\",\n \"content_id\": \"ff1166a7601f1cf1961ee8c7985298a8072a6e72\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 46,\n \"license_type\": \"no_license\",\n \"max_line_length\": 46,\n \"num_lines\": 1,\n \"path\": \"/알고리즘/온라인저지/2022/10/1012/SciComLove.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"for _ in [0]*int(input()): print('SciComLove')\"\n },\n {\n \"alpha_fraction\": 0.5454545617103577,\n \"alphanum_fraction\": 0.5757575631141663,\n \"avg_line_length\": 21.33333396911621,\n \"blob_id\": \"7b4e660a242fe7500a5022d395f2072085ebc240\",\n \"content_id\": \"26972a19119955f21f60d8d6574d6da40bbd0a52\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 66,\n \"license_type\": \"no_license\",\n \"max_line_length\": 33,\n \"num_lines\": 3,\n \"path\": \"/알고리즘/온라인저지/2022/03/0303/알고리즘 수업 - 알고리즘의 수행 시간 5.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"result = int(input())**3\\ndim = 3\\nprint(result, f'\\\\n{dim}', sep='')\"\n },\n {\n \"alpha_fraction\": 0.54347825050354,\n \"alphanum_fraction\": 0.5688405632972717,\n \"avg_line_length\": 22.08333396911621,\n \"blob_id\": \"092361e9ca22699e381dc79b5d1e6e0f9c75edb5\",\n \"content_id\": \"19b84f2bbd1db18f132bd722f4b1b07111cd86b4\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 276,\n \"license_type\": \"no_license\",\n \"max_line_length\": 65,\n \"num_lines\": 12,\n \"path\": \"/알고리즘/온라인저지/2022/09/0927/단어 나누기.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\n\\nword = input().rstrip()\\nlength = len(word)\\nchange = []\\nfor i in range(1, length-1):\\n for j in range(i+1, length):\\n A, B, C = word[:i][::-1], word[i:j][::-1], word[j:][::-1]\\n change.append(A+B+C)\\nprint(sorted(change)[0])\"\n },\n {\n \"alpha_fraction\": 0.49787235260009766,\n \"alphanum_fraction\": 0.5063830018043518,\n \"avg_line_length\": 22.600000381469727,\n \"blob_id\": \"a36d18925e9cecc6e41416d90b92752384c6d6aa\",\n \"content_id\": \"526b93b1d765c134fd51d4fd1ad71ac122c62394\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 235,\n \"license_type\": \"no_license\",\n \"max_line_length\": 43,\n \"num_lines\": 10,\n \"path\": \"/알고리즘/온라인저지/2023/03/0305/스트릿 코딩 파이터.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"A, B, C = map(int, input().split())\\nN = int(input())\\nresult = []\\nfor n in range(N):\\n tmp = 0\\n for i in range(3):\\n a, b, c = map(int, input().split())\\n tmp += a*A + b*B + c*C\\n result.append(tmp)\\nprint(max(result))\"\n },\n {\n \"alpha_fraction\": 0.6053169965744019,\n \"alphanum_fraction\": 0.6237218976020813,\n \"avg_line_length\": 29.625,\n \"blob_id\": \"032a1c34126b5743e55adfa7604edb8ad2ad1155\",\n \"content_id\": \"7663cd4bd0993df2e22bfe55b2d19dfb8125bca6\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 525,\n \"license_type\": \"no_license\",\n \"max_line_length\": 60,\n \"num_lines\": 16,\n \"path\": \"/알고리즘/[템플릿]/스택/에디터.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\n\\nleft = list(input().rstrip())\\nright = []\\n# 커서의 이동을 좌우 스택간에 이동으로 구현\\nfor _ in range(int(input().rstrip())):\\n order = input().rstrip().split()\\n if order[0] == 'L' and left: right.append(left.pop())\\n elif order[0] == 'D' and right: left.append(right.pop())\\n elif order[0] == 'B' and left: left.pop()\\n elif order[0] == 'P': left.append(order[1])\\nfor a in left+list(reversed(right)): print(a, end='')\\n\\n# https://www.acmicpc.net/problem/1406\"\n },\n {\n \"alpha_fraction\": 0.2628205120563507,\n \"alphanum_fraction\": 0.5064102411270142,\n \"avg_line_length\": 7.722222328186035,\n \"blob_id\": \"c66221e74c9419d93995a27c3eb93187e07d4bc5\",\n \"content_id\": \"2f1a3f40041c583117339146cf66f6b74172c645\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 156,\n \"license_type\": \"no_license\",\n \"max_line_length\": 62,\n \"num_lines\": 18,\n \"path\": \"/알고리즘/온라인저지/2022/04/0430/거북이.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"\\\"\\\"\\\"\\n1 2 3 4\\n4 1 3 2\\n4 3\\n1 2\\n\\n4 4 3 4\\n3 4 4 4\\n4 4\\n3 4\\n\\n4 7 3 9\\n3 4 7 9\\n9 3 7 4\\n\\n\\\"\\\"\\\"\\nA, B = map(int, sorted(list(map(int, input().split())))[:3:2])\\nprint(A*B)\"\n },\n {\n \"alpha_fraction\": 0.4771573543548584,\n \"alphanum_fraction\": 0.4771573543548584,\n \"avg_line_length\": 18.600000381469727,\n \"blob_id\": \"5dc97a961aa501a4c2fd9cd64dd1401654b29ee8\",\n \"content_id\": \"c945c5520f1cfd88e75f5e850a7ccf1556224d68\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 197,\n \"license_type\": \"no_license\",\n \"max_line_length\": 44,\n \"num_lines\": 10,\n \"path\": \"/알고리즘/온라인저지/2022/02/0207/아.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"jh = input()\\nhospital = input()\\n\\nfor i in range(max(len(jh), len(hospital))):\\n if hospital[i] == 'h':\\n print('go')\\n break\\n elif jh[i] == 'h':\\n print('no')\\n break\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.48695650696754456,\n \"alphanum_fraction\": 0.48695650696754456,\n \"avg_line_length\": 15.571428298950195,\n \"blob_id\": \"7658a99d40944ffbe34d9ec696607b7f17ce61f3\",\n \"content_id\": \"c1dede77301ccf831ff37e2daa79b4bdd4128c70\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 115,\n \"license_type\": \"no_license\",\n \"max_line_length\": 36,\n \"num_lines\": 7,\n \"path\": \"/알고리즘/온라인저지/2022/06/0624/더하기 2.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"num = ''\\nwhile True:\\n try:\\n num += input()\\n except:\\n break\\nprint(sum(map(int, num.split(','))))\"\n },\n {\n \"alpha_fraction\": 0.41743120551109314,\n \"alphanum_fraction\": 0.5458715558052063,\n \"avg_line_length\": 30.285715103149414,\n \"blob_id\": \"6d76577f86b6a99b82b744e98fa6538275668345\",\n \"content_id\": \"1da8bb83990a2d96a684dccc896225612a0b5e87\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 218,\n \"license_type\": \"no_license\",\n \"max_line_length\": 47,\n \"num_lines\": 7,\n \"path\": \"/알고리즘/온라인저지/2022/05/0501/전투 드로이드 가격.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"menu = [350.34, 230.90, 190.55, 125.30, 180.90]\\nfor t in range(int(input())):\\n tmp = list(map(int, input().split()))\\n result = 0\\n for i in range(5):\\n result += menu[i]*tmp[i]\\n print(f'${result:.2f}')\"\n },\n {\n \"alpha_fraction\": 0.4779411852359772,\n \"alphanum_fraction\": 0.5073529481887817,\n \"avg_line_length\": 18.571428298950195,\n \"blob_id\": \"366b0e24c897ee6333a087120c087d9f128a9706\",\n \"content_id\": \"f9c8c725f26e6a75f0d111b67dba6205c20e32b3\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 136,\n \"license_type\": \"no_license\",\n \"max_line_length\": 27,\n \"num_lines\": 7,\n \"path\": \"/알고리즘/온라인저지/2022/12/1201/파인만.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"while True:\\n N = int(input())\\n if not N: break\\n result = 0\\n for i in range(1, N+1):\\n result += i**2\\n print(result)\"\n },\n {\n \"alpha_fraction\": 0.4680851101875305,\n \"alphanum_fraction\": 0.4893617033958435,\n \"avg_line_length\": 26,\n \"blob_id\": \"88aae1c374b2a8299c3aedaa7a9dd15c35bdfd79\",\n \"content_id\": \"cd3d9011527f102b81fe88ed16434b7aa5ddb8a6\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 188,\n \"license_type\": \"no_license\",\n \"max_line_length\": 43,\n \"num_lines\": 7,\n \"path\": \"/알고리즘/온라인저지/2022/09/0902/부호.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"for _ in range(3):\\n N = int(input())\\n tmp = [int(input()) for __ in range(N)]\\n result = '0'\\n if sum(tmp) > 0: result = '+'\\n elif sum(tmp) < 0: result = '-'\\n print(result)\"\n },\n {\n \"alpha_fraction\": 0.5044247508049011,\n \"alphanum_fraction\": 0.5132743120193481,\n \"avg_line_length\": 13.125,\n \"blob_id\": \"8ec2dcf6eaf614389371b39640dbc70948822c1a\",\n \"content_id\": \"79474395687b273dcf75c1b32592b13871a5c735\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 113,\n \"license_type\": \"no_license\",\n \"max_line_length\": 35,\n \"num_lines\": 8,\n \"path\": \"/알고리즘/온라인저지/2022/02/0207/캥거루 세마리.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"A, B, C = map(int, input().split())\\n\\nfurther = A\\n\\nif (B-A) < (C-B):\\n further = C\\n\\nprint(abs(further - B) - 1)\\n\"\n },\n {\n \"alpha_fraction\": 0.5304877758026123,\n \"alphanum_fraction\": 0.5609756112098694,\n \"avg_line_length\": 22.571428298950195,\n \"blob_id\": \"c4bd9fa3164844d7772f84a2dcc3c5494cfc8726\",\n \"content_id\": \"369f44dc5b3ede4670c2661be681fdb01edb78ea\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 164,\n \"license_type\": \"no_license\",\n \"max_line_length\": 34,\n \"num_lines\": 7,\n \"path\": \"/알고리즘/온라인저지/2023/02/0203/치킨댄스를 추는 곰곰이를 본 임스 2.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"result = 0\\nfor _ in range(int(input())):\\n gifticon = input().split('D-')\\n left_day = int(gifticon[1])\\n if left_day <= 90:\\n result += 1\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.46489858627319336,\n \"alphanum_fraction\": 0.4836193323135376,\n \"avg_line_length\": 20.399999618530273,\n \"blob_id\": \"0ef99bed4963ca1319ec162dd9300c8de7196203\",\n \"content_id\": \"b0659c51ed07469826a2d5148dce5d7280db2c0f\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 665,\n \"license_type\": \"no_license\",\n \"max_line_length\": 36,\n \"num_lines\": 30,\n \"path\": \"/알고리즘/온라인저지/2022/12/1204/효율적인 해킹.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from collections import deque\\n\\ndef bfs(i):\\n Q = deque([i])\\n cnt = 1 # i번 컴퓨터를 해킹하면서 bfs 시작\\n visited = [0]*(N+1)\\n visited[i] = 1\\n while Q:\\n i = Q.popleft()\\n for nxt in arr[i]:\\n if not visited[nxt]:\\n visited[nxt] = 1\\n Q.append(nxt)\\n cnt += 1\\n return cnt\\n\\nN, M = map(int, input().split())\\narr = [[] for _ in range(N+1)]\\nfor _ in range(M):\\n a, b = map(int, input().split())\\n arr[b].append(a)\\n\\nresult = [0]*(N+1)\\nfor i in range(1, N+1):\\n result[i] = bfs(i)\\n\\nmaxx = max(result)\\nfor i in range(N+1):\\n if result[i] == maxx:\\n print(i, end=' ')\"\n },\n {\n \"alpha_fraction\": 0.40740740299224854,\n \"alphanum_fraction\": 0.4273504316806793,\n \"avg_line_length\": 18.55555534362793,\n \"blob_id\": \"51d9052bffacada0481557ceb3c8a2f90d044d80\",\n \"content_id\": \"e1bb38ba2468cd75cdaa8b7308bb5bb1ff62de76\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 351,\n \"license_type\": \"no_license\",\n \"max_line_length\": 43,\n \"num_lines\": 18,\n \"path\": \"/알고리즘/온라인저지/2023/03/0326/선물할인.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N, B, A = map(int, input().split())\\nP = sorted(list(map(int, input().split())))\\nresult = 0\\nsumm = 0\\n\\nfor i in range(N):\\n if summ+P[i]<=B:\\n summ += P[i]\\n result += 1\\n else:\\n if summ+(P[i]//2)<=B and A:\\n summ += P[i]//2\\n result += 1\\n A -= 1\\n else:\\n break\\n\\nprint(summ, result)\"\n },\n {\n \"alpha_fraction\": 0.44961240887641907,\n \"alphanum_fraction\": 0.4961240291595459,\n \"avg_line_length\": 15.25,\n \"blob_id\": \"7d02f29c339aa84625434da74d4a5a46e08955e4\",\n \"content_id\": \"602f705c14dd98823c307d8c14242d70a038077a\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 129,\n \"license_type\": \"no_license\",\n \"max_line_length\": 22,\n \"num_lines\": 8,\n \"path\": \"/알고리즘/온라인저지/2022/07/0702/문어.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = int(input())\\nresult = [1] * N\\nfor i in range(N):\\n if i%2:\\n result[i] += 1\\nif N%2:\\n result[-1] = 3\\nprint(*result)\"\n },\n {\n \"alpha_fraction\": 0.38655462861061096,\n \"alphanum_fraction\": 0.3949579894542694,\n \"avg_line_length\": 12.333333015441895,\n \"blob_id\": \"e8189246c35cb2453ab369ba784bce1a8a14d4f6\",\n \"content_id\": \"5472326aee6ffe8dba35289e2ecb30b6d257de7b\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 119,\n \"license_type\": \"no_license\",\n \"max_line_length\": 26,\n \"num_lines\": 9,\n \"path\": \"/알고리즘/SWEA/LEARN/Course/1. Programming Beginner/파이썬 프로그래밍 기초(2)/17차시 2. 자료구조 – 리스트, 튜플 - 연습문제 19.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"x = input().split(', ')\\n\\nx.sort()\\n\\nfor i in x:\\n if i == x[-1]:\\n print(i)\\n else:\\n print(i, end=', ')\"\n },\n {\n \"alpha_fraction\": 0.4084506928920746,\n \"alphanum_fraction\": 0.46948355436325073,\n \"avg_line_length\": 29.428571701049805,\n \"blob_id\": \"8fb0d65015489351f59c3fa13562c67141cd6053\",\n \"content_id\": \"a2904dc8e4465a471571900533211eb92e066499\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 213,\n \"license_type\": \"no_license\",\n \"max_line_length\": 63,\n \"num_lines\": 7,\n \"path\": \"/알고리즘/온라인저지/2023/01/0115/회의실 배정 2.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = int(input())\\narr = [0] + [list(map(int, input().split())) for _ in range(N)]\\ndp = [0, arr[1][2]] + [0]*(N-1)\\nif N > 1:\\n for i in range(2, N+1):\\n dp[i] = max(dp[i-1], dp[i-2]+arr[i][2])\\nprint(dp[-1])\\n\"\n },\n {\n \"alpha_fraction\": 0.5537189841270447,\n \"alphanum_fraction\": 0.5743801593780518,\n \"avg_line_length\": 19.25,\n \"blob_id\": \"7402bb6b7ce4765d45a3ebf1e00e51558e2c8ea1\",\n \"content_id\": \"7ecc86937e4ab8ad6502a366fc9cabd98fe3ca7f\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 242,\n \"license_type\": \"no_license\",\n \"max_line_length\": 35,\n \"num_lines\": 12,\n \"path\": \"/알고리즘/온라인저지/2022/09/0930/문자열.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\n\\nA, B = input().rstrip().split()\\nresult = int(1e9)\\nfor i in range(len(B)-len(A)+1):\\n tmp = 0\\n for j in range(len(A)):\\n if A[j] != B[i+j]: tmp += 1\\n result = min(result, tmp)\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.41860464215278625,\n \"alphanum_fraction\": 0.43410852551460266,\n \"avg_line_length\": 13.44444465637207,\n \"blob_id\": \"18570ce7e55d191b03d44c85373b28eae8d8b29a\",\n \"content_id\": \"32d7a72d6582b61cadc90c420bdd210a3af3c09c\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 129,\n \"license_type\": \"no_license\",\n \"max_line_length\": 24,\n \"num_lines\": 9,\n \"path\": \"/알고리즘/온라인저지/2022/02/0213/홀수일까 짝수일까.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = int(input())\\n\\nfor n in range(N):\\n K = int(input()[-1])\\n\\n if K % 2:\\n print('odd')\\n else:\\n print('even')\"\n },\n {\n \"alpha_fraction\": 0.388127863407135,\n \"alphanum_fraction\": 0.4337899684906006,\n \"avg_line_length\": 43,\n \"blob_id\": \"15c76e18da7ef3d0e60d69e6b4682a0e7e8c23b5\",\n \"content_id\": \"7822fba43ad12751db9f8901b2c2d8210c0a6292\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 219,\n \"license_type\": \"no_license\",\n \"max_line_length\": 101,\n \"num_lines\": 5,\n \"path\": \"/알고리즘/온라인저지/2023/03/0324/Report Card Time.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"grades = ['F']*60 + ['D']*7 + ['D+']*3 + ['C']*7 + ['C+']*3 + ['B']*7 + ['B+']*3 + ['A']*7 + ['A+']*4\\nfor _ in range(int(input())):\\n name, score = input().split()\\n score = int(score)\\n print(name, grades[score])\"\n },\n {\n \"alpha_fraction\": 0.5822784900665283,\n \"alphanum_fraction\": 0.6202531456947327,\n \"avg_line_length\": 25.66666603088379,\n \"blob_id\": \"20e363df146cc65785f831c994f973ddd722ff5f\",\n \"content_id\": \"782451d0c3693f09f8413c7344bec98deee2da18\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 79,\n \"license_type\": \"no_license\",\n \"max_line_length\": 45,\n \"num_lines\": 3,\n \"path\": \"/알고리즘/온라인저지/2022/09/0913/이진수 덧셈.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"result = 0\\nfor i in input().split(): result += int(i, 2)\\nprint(bin(result)[2:])\"\n },\n {\n \"alpha_fraction\": 0.5087719559669495,\n \"alphanum_fraction\": 0.5263158082962036,\n \"avg_line_length\": 31.125,\n \"blob_id\": \"cea27185dc5e65a0b92ae2d4c144d7bea7dc4880\",\n \"content_id\": \"c2e1fd4b63d6c5ddbcd33fc3188fb9ff8d222ab7\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 521,\n \"license_type\": \"no_license\",\n \"max_line_length\": 58,\n \"num_lines\": 16,\n \"path\": \"/알고리즘/온라인저지/2022/10/1012/행렬 곱셈.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"def multiply(matrix1, matrix2): # 행렬 곱셈\\n output = []\\n for i in range(N):\\n output.append([])\\n for j in range(K):\\n tmp = 0\\n for k in range(M):\\n tmp += matrix1[i][k] * matrix2[k][j]\\n output[i].append(tmp)\\n return output\\n\\nN, M = map(int, input().split())\\nmat1 = [list(map(int, input().split())) for _ in range(N)]\\nM, K = map(int, input().split())\\nmat2 = [list(map(int, input().split())) for _ in range(M)]\\nfor i in multiply(mat1, mat2): print(*i)\"\n },\n {\n \"alpha_fraction\": 0.49560633301734924,\n \"alphanum_fraction\": 0.5184534192085266,\n \"avg_line_length\": 16.272727966308594,\n \"blob_id\": \"705dc9059b8facdf9f2ca190ae9ed19f9fe0af08\",\n \"content_id\": \"f7c8d52ad5f3357072414c6ccd31377de8913750\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 761,\n \"license_type\": \"no_license\",\n \"max_line_length\": 42,\n \"num_lines\": 33,\n \"path\": \"/알고리즘/온라인저지/2022/01/0122/게으른 백곰.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N, K = map(int, input().split())\\n\\npen = [0] * 1000001 # 우리(pen)의 범위\\n\\nnow = K # K에서 시작해야, 앞으로 K만큼, 뒤로 K만큼\\n\\nx_max = 0 # 양동이좌표 최대까지만 탐색\\n\\nfor n in range(N):\\n g, x = map(int, input().split())\\n\\n pen[x] = g # 우리 채우기\\n\\n if x > x_max:\\n x_max = x # 최대 양동이좌표 저장\\n\\nresult = window = sum(pen[:now+K+1]) # 초기값\\n\\nnow += 1 # 한 칸 앞으로\\n\\n# 백만 다 안돌고, 최대양동이까지만 탐색\\nwhile now+K <= x_max: \\n # 윈도우 한 칸 앞으로 슬라이딩~\\n window -= pen[now-K-1]\\n window += pen[now+K]\\n \\n # 최대값 갱신 가능한가?\\n if window > result:\\n result = window\\n \\n now += 1 # 한 칸 앞으로~\\n\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.5423728823661804,\n \"alphanum_fraction\": 0.5706214904785156,\n \"avg_line_length\": 21.25,\n \"blob_id\": \"020a634e0b21f6fe0cf69b69c0e67889a0e8e9b0\",\n \"content_id\": \"56786f068f246702eb3be17790ff967a6c41afe7\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 177,\n \"license_type\": \"no_license\",\n \"max_line_length\": 57,\n \"num_lines\": 8,\n \"path\": \"/알고리즘/온라인저지/2022/08/0827/장신구 명장 임스.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"P, N = map(int, input().split())\\nA = sorted(list(map(int, input().split()))) # accessories\\nresult = 0\\nfor a in A:\\n if P >= 200: break\\n P += a\\n result += 1\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.375,\n \"alphanum_fraction\": 0.42500001192092896,\n \"avg_line_length\": 11.100000381469727,\n \"blob_id\": \"6363fc300a50ebea8f976c000b06391c3de8ee32\",\n \"content_id\": \"e957ef52f3ee14b8d75c07c3cd75aae13d744c3e\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 120,\n \"license_type\": \"no_license\",\n \"max_line_length\": 20,\n \"num_lines\": 10,\n \"path\": \"/알고리즘/온라인저지/2021/12/1213/평균 점수.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"a = []\\n\\nfor i in range(5):\\n b = int(input())\\n if b < 40:\\n b = 40\\n \\n a.append(b)\\n\\nprint(int(sum(a)/5))\"\n },\n {\n \"alpha_fraction\": 0.4337811768054962,\n \"alphanum_fraction\": 0.44913628697395325,\n \"avg_line_length\": 18.33333396911621,\n \"blob_id\": \"e899caf1c32df269b93f99c6533f014e2c85617f\",\n \"content_id\": \"ed8f87c6378c38c02c65ab7eddc4871475b280e0\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 521,\n \"license_type\": \"no_license\",\n \"max_line_length\": 35,\n \"num_lines\": 27,\n \"path\": \"/알고리즘/온라인저지/2021/09/0905/스택 수열.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\nn = int(sys.stdin.readline())\\nori = list(range(2, n+1))\\ntmp = [1]\\nope = ['+']\\n\\nfor _ in range(n):\\n if not tmp:\\n tmp.append(ori.pop(0))\\n ope.append('+')\\n num = int(sys.stdin.readline())\\n if num == tmp[-1]:\\n tmp.pop()\\n ope.append('-') \\n elif num < tmp[-1]:\\n print('NO')\\n exit()\\n else:\\n while num != tmp[-1]:\\n tmp.append(ori.pop(0))\\n ope.append('+')\\n tmp.pop()\\n ope.append('-') \\n\\nfor o in ope:\\n print(o)\"\n },\n {\n \"alpha_fraction\": 0.4351145029067993,\n \"alphanum_fraction\": 0.442748099565506,\n \"avg_line_length\": 13.55555534362793,\n \"blob_id\": \"6c8c3bee863f15d8aa7cf4c603b586df546a6a76\",\n \"content_id\": \"2a876075d87ff865b35961e8b2b1628e73fcf8e3\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 131,\n \"license_type\": \"no_license\",\n \"max_line_length\": 31,\n \"num_lines\": 9,\n \"path\": \"/알고리즘/온라인저지/2022/02/0205/단어 뒤집기.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"T = int(input())\\n\\nfor t in range(T):\\n sen = input().split()\\n\\n for s in sen:\\n print(s[::-1], end=' ')\\n \\n print()\\n\"\n },\n {\n \"alpha_fraction\": 0.38461539149284363,\n \"alphanum_fraction\": 0.4472934603691101,\n \"avg_line_length\": 22.399999618530273,\n \"blob_id\": \"074b00d44aaa41ee9fa6fa69becbc4f19affbe02\",\n \"content_id\": \"24b1a2cc7dea4199b1a971857a3f600c43c8f8a1\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 351,\n \"license_type\": \"no_license\",\n \"max_line_length\": 43,\n \"num_lines\": 15,\n \"path\": \"/알고리즘/온라인저지/2022/06/0628/애너그램.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"T = int(input())\\nfor t in range(T):\\n result = 'NOT '\\n arr = input().split()\\n word1 = [0] * 26\\n word2 = [0] * 26\\n for w in arr[0]:\\n word1[ord(w)-97] += 1\\n for w in arr[1]:\\n word2[ord(w)-97] += 1\\n if word1 == word2:\\n result = ''\\n print('{} & {} are {}anagrams.'.format(\\n arr[0], arr[1], result\\n ))\\n\"\n },\n {\n \"alpha_fraction\": 0.5296523571014404,\n \"alphanum_fraction\": 0.5521472096443176,\n \"avg_line_length\": 21.272727966308594,\n \"blob_id\": \"e693232d62d1b0adc245c7f3439a55e5de1f8b7d\",\n \"content_id\": \"6b94620fc13ed7dfe3dacfa0c0569e76587c675c\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 489,\n \"license_type\": \"no_license\",\n \"max_line_length\": 52,\n \"num_lines\": 22,\n \"path\": \"/알고리즘/온라인저지/2022/08/0801/예산.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"def binary(start, end):\\n global result, M\\n if start > end: return\\n budget = (start + end) // 2\\n tmp = 0\\n for b in B: tmp += min(b, budget)\\n if tmp <= M:\\n if budget > result: \\n result = budget\\n binary(budget+1, end)\\n else:\\n binary(start, budget-1)\\n\\nN = int(input())\\nB = sorted(list(map(int, input().split()))) # budget\\nM = int(input())\\nS, E = 0, M\\nresult = 0\\nbinary(S, E)\\nprint(min(B[-1], result))\\n\\n# https://www.acmicpc.net/problem/2512\"\n },\n {\n \"alpha_fraction\": 0.5460993051528931,\n \"alphanum_fraction\": 0.588652491569519,\n \"avg_line_length\": 14.777777671813965,\n \"blob_id\": \"7be936052a2461d09b971f70700ebb30381d2125\",\n \"content_id\": \"88747d0e3bee45dc09230b727dc8a5fbe3b4a0ad\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 141,\n \"license_type\": \"no_license\",\n \"max_line_length\": 32,\n \"num_lines\": 9,\n \"path\": \"/알고리즘/온라인저지/2022/10/1012/체스판 조각.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\n\\nN = int(input())\\nodd = False\\nif N%2: N += 1; odd = True\\nA = N//2 + 1\\nprint(A**2 - A if odd else A**2)\"\n },\n {\n \"alpha_fraction\": 0.5694444179534912,\n \"alphanum_fraction\": 0.5972222089767456,\n \"avg_line_length\": 11.166666984558105,\n \"blob_id\": \"7f04d15c1601c41bf900bb7b08e8278fd7c62552\",\n \"content_id\": \"c7d4b3cde04bbfe8da7d8ab56daf64a953f66e95\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 72,\n \"license_type\": \"no_license\",\n \"max_line_length\": 26,\n \"num_lines\": 6,\n \"path\": \"/알고리즘/온라인저지/2022/02/0205/카드 게임.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"result = 0\\n\\nfor _ in range(5):\\n result += int(input())\\n\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.5797545909881592,\n \"alphanum_fraction\": 0.6012269854545593,\n \"avg_line_length\": 19.4375,\n \"blob_id\": \"e66de8337469520acf8e46cfc036e9f48f5a38e7\",\n \"content_id\": \"35fc1f6570233cbba1272e696ca1aba9a3e07330\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 390,\n \"license_type\": \"no_license\",\n \"max_line_length\": 43,\n \"num_lines\": 16,\n \"path\": \"/알고리즘/온라인저지/2022/07/0717/뒤집기.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"\\\"\\\"\\\"\\n블록(구간)의 개수가 적은 숫자를 뒤집기\\n그냥 숫자의 개수가 적은 숫자를 뒤집기\\n\\\"\\\"\\\"\\narr = list(map(int, list(input())))\\n# print(arr)\\nswitch = True\\nresult = [0, 0, arr.count(0), arr.count(1)]\\nswitch = bool(arr[0])\\nresult[switch] += 1\\nfor a in arr:\\n if a != switch:\\n switch = not switch\\n result[switch] += 1\\n# print(result)\\nprint(min(result))\"\n },\n {\n \"alpha_fraction\": 0.5202797055244446,\n \"alphanum_fraction\": 0.5398601293563843,\n \"avg_line_length\": 20.058822631835938,\n \"blob_id\": \"d74e66e5cb5770d001c038d4a47cc1abeaf57cbf\",\n \"content_id\": \"90e11bea0639306b4ba7291ff619e95e2d698dc1\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 715,\n \"license_type\": \"no_license\",\n \"max_line_length\": 45,\n \"num_lines\": 34,\n \"path\": \"/알고리즘/온라인저지/2022/09/0917/연결 요소의 개수.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\nfrom collections import deque\\n\\ninput = sys.stdin.readline\\n\\ndef BFS(node):\\n global result\\n Q.append(node)\\n visited[node] = 1\\n cnt = 0\\n while Q:\\n now = Q.popleft()\\n for next in arr[now]:\\n if not visited[next]:\\n Q.append(next)\\n visited[next] = 1\\n cnt += 1\\n result -= cnt\\n\\nN, M = map(int, input().rstrip().split())\\narr = [[] for _ in range(N+1)]\\nvisited = [0] * (N+1)\\nQ = deque()\\nfor m in range(M):\\n u, v = map(int, input().rstrip().split())\\n arr[u].append(v)\\n arr[v].append(u)\\nresult = N\\nfor i in range(1, N+1): \\n BFS(i)\\n if sum(visited) == N: break\\nprint(result)\\n\\n# https://www.acmicpc.net/problem/11724\"\n },\n {\n \"alpha_fraction\": 0.6091370582580566,\n \"alphanum_fraction\": 0.624365508556366,\n \"avg_line_length\": 28.22222137451172,\n \"blob_id\": \"a19d6079ab23c3e6fc7b464eb993672af5cb3c55\",\n \"content_id\": \"3dc3828d3ba8f786213e3d2b4717d683c66a2b59\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1530,\n \"license_type\": \"no_license\",\n \"max_line_length\": 58,\n \"num_lines\": 27,\n \"path\": \"/알고리즘/온라인저지/2021/08/0807/손익분기점.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"\\\"\\\"\\\"\\nA, B, C = 고정비용, 생산비용, 노트북 가격\\n손익분기점 : 판매수입>총 생산비용(고정비용+생산비용)이 되는 시점\\n생산대수를 1대부터 점점 증가시켜서(while)\\n손익분기점을 만족하는 N값을 찾아서 출력\\n할려고 했는데 예시 2만원에 생산해서 1만원에 파는 사람이 어딨냐고ㅋㅋㅋ\\n문제 끝에 \\\"손익분기점이 발생하지 않으면 -1을 출력한다\\\"고 있네요\\n문제 잘 읽겠습니다...\\nwhile문으로 21억까지 +1 하면서 가려니까 시간이 너무 오래 걸려서\\n직접 손익분기점을 구해서 올림을 통해 값을 주기로 했는데\\n아무래도 math모듈을 불러올 수 없는 것 같다\\n올림을 못쓰니, 생산대수를 근사한 값으로 구해서 하나씩 더하기로 했다\\nZeroDivisionError가 나왔다, 테스트케이스중에 생산비용과 판매비용이 같은 케이스가 있다는건데\\n이 상황을 추가하였다\\n\\\"\\\"\\\"\\n\\nA, B, C = map(int, input().split()) # 고정비용, 가변비용, 판매가 입력\\nif B >= C: # 손익분기점이 발생하지 않을 경우\\n N = -1 # -1을\\nelse: # 손익분기점이 발생할 경우\\n N = round(A / (C-B)) - 1 # N일수도 있고 아닐수도 있는 근사값을 설정한다\\n while True: # 반복문을 돌리면서\\n if N > A / (C-B): # 손익분기점이라면\\n break # while문을 마치고\\n else: # 손익분기점이 아니라면\\n N += 1 # +1 해서 다시 돌려보고\\nprint(N) # 출력한다\"\n },\n {\n \"alpha_fraction\": 0.5302491188049316,\n \"alphanum_fraction\": 0.5480427145957947,\n \"avg_line_length\": 22.41666603088379,\n \"blob_id\": \"d4b86e3647e17ab8a260fed4960e28cbe82c0817\",\n \"content_id\": \"42365851c22a6223934a063930f0543652bec03a\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 413,\n \"license_type\": \"no_license\",\n \"max_line_length\": 40,\n \"num_lines\": 12,\n \"path\": \"/알고리즘/온라인저지/2021/08/0809/수들의 합.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\nS = int(sys.stdin.readline()) # S값 입력받고\\nN = 0 # 더해줄 N값 초기화\\ncount = 0 # 최대 개수 초기화\\nwhile True: # while문 반복하면서\\n N += 1 # 1부터 S값에서 빼기 시작\\n if N > S: # 종료조건\\n break\\n S -= N # S에서 N을 빼주면서 S를 N보다 작게 만들때까지\\n # 수의 개수를 \\n count += 1 # 세어주고\\nprint(count) # 출력\\n\"\n },\n {\n \"alpha_fraction\": 0.38879457116127014,\n \"alphanum_fraction\": 0.5670627951622009,\n \"avg_line_length\": 13.75,\n \"blob_id\": \"c60111bafab358f2f649917d396da8975699de37\",\n \"content_id\": \"bc3b74f247a613e52d434b182870b8577f540432\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 815,\n \"license_type\": \"no_license\",\n \"max_line_length\": 46,\n \"num_lines\": 40,\n \"path\": \"/알고리즘/온라인저지/2022/03/0323/저울.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"\\\"\\\"\\\"\\nex) 무게추 = [1 2 4 7 8 30]\\n1 1 \\n2 2\\n3 2 1\\n4 4\\n5 4 1\\n6 4 2\\n7 4 2 1\\n8 7 1\\n9 7 2\\n10 7 2 1\\n11 7 4\\n12 7 4 1\\n13 7 4 2\\n14 7 4 2 1\\n15 8 7\\n16 8 7 1\\n17 8 7 2\\n18 8 7 2 1\\n19 8 7 4\\n20 8 7 4 1\\n21 8 7 4 2\\n22 8 7 4 2 1\\n23 X\\n추들을 순회할 때\\n진행중인 모든 추를 다 더한 것 + 1\\n보다 큰 추가 있거나, 다 더하고 for문이 끝나면\\n그 더한 값이 답이 된다\\n\\\"\\\"\\\"\\nN = int(input())\\nweights = list(map(int, input().split())) # 추들\\nweights.sort() # 작은 추부터 차례대로 더할 것\\ntarget = 1 # 시작점, 혹은 목표 무게\\nfor w in weights: # 추들을 순회하면서\\n # print(target, w) # 디버깅\\n if target < w: # 더 큰 추가 나왔으면\\n break # 지금 보는 무게가 답이 된다\\n target += w # 다음 추 더하기\\nprint(target) # 목표 무게 출력\"\n },\n {\n \"alpha_fraction\": 0.42934781312942505,\n \"alphanum_fraction\": 0.489130437374115,\n \"avg_line_length\": 25.428571701049805,\n \"blob_id\": \"2e05a75fe920cd1bd593fe893505df4c6787fbbe\",\n \"content_id\": \"ebe99b2037c4da7e92bfd309a96fa86a4ebd19e4\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 184,\n \"license_type\": \"no_license\",\n \"max_line_length\": 35,\n \"num_lines\": 7,\n \"path\": \"/알고리즘/온라인저지/2023/02/0207/주사위.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"A, B, C = map(int, input().split())\\ndp = [0]*100\\nfor a in range(1, A+1):\\n for b in range(1, B+1):\\n for c in range(1, C+1):\\n dp[a+b+c] += 1\\nprint(dp.index(max(dp)))\"\n },\n {\n \"alpha_fraction\": 0.5071770548820496,\n \"alphanum_fraction\": 0.540669858455658,\n \"avg_line_length\": 26.933332443237305,\n \"blob_id\": \"73d179e435cf6bdc2766ef7e1a1bcdcf49afe479\",\n \"content_id\": \"edb801b7562c9f481e7a70e2e1707e0cddc4967c\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 418,\n \"license_type\": \"no_license\",\n \"max_line_length\": 52,\n \"num_lines\": 15,\n \"path\": \"/알고리즘/온라인저지/2023/01/0127/2021은 무엇이 특별할까.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"def prime_list(size):\\n sieve = [True]*(size+1)\\n for i in range(2, int(size**0.5)+1):\\n if sieve[i]:\\n for j in range(i+i, size+1, i):\\n sieve[j] = False\\n return [i for i in range(2, size+1) if sieve[i]]\\n\\nN = int(input())\\nprimes = prime_list(5500)\\nfor i in range(len(primes)-1):\\n is_special = primes[i]*primes[i+1]\\n if is_special > N:\\n print(is_special)\\n break\"\n },\n {\n \"alpha_fraction\": 0.4900990128517151,\n \"alphanum_fraction\": 0.5118811726570129,\n \"avg_line_length\": 23.658536911010742,\n \"blob_id\": \"4ad5c46b849f6e36cb7a616fba3b64aa9d3b52d9\",\n \"content_id\": \"8c3fcf68a0b5d8dedb9d86e236ba8b6545b80940\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1228,\n \"license_type\": \"no_license\",\n \"max_line_length\": 61,\n \"num_lines\": 41,\n \"path\": \"/알고리즘/온라인저지/2022/08/0828/녹색 옷 입은 애가 젤다지.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\nimport heapq # 탐색 시 가장 작은 값을 탐색하기 위함\\n\\ninput = sys.stdin.readline\\nINF = int(1e9) # 가상의 최대값\\ndy, dx = [-1, 1, 0, 0], [0, 0, -1, 1]\\n\\ndef dijkstra(y, x):\\n global result\\n heapq.heappush(Q, (y, x, arr[y][x]))\\n visited[y][x] = arr[y][x]\\n while Q:\\n y, x, dist = heapq.heappop(Q)\\n for i in range(4):\\n ny, nx = y+dy[i], x+dx[i]\\n if 0<=ny<N and 0<=nx<N:\\n cost = dist + arr[ny][nx]\\n if cost < visited[ny][nx]:\\n visited[ny][nx] = cost\\n heapq.heappush(Q, (ny, nx, cost))\\n\\ncase = 0\\nwhile True:\\n case += 1\\n N = int(input())\\n if N == 0: break\\n arr = [list(map(int, input().split())) for _ in range(N)]\\n visited = [[INF]*N for _ in range(N)]\\n result = INF\\n Q = []\\n dijkstra(0, 0)\\n print(f'Problem {case}: {visited[N-1][N-1]}')\\n\\n\\\"\\\"\\\"\\n최소 경로값을 저장하는 배열 생성\\n모든 지점에 대해 최소 경로값을 구하며 진행\\n도착점 arr[N-1][N-1]의 최소 경로값을 출력\\nheapq 자체의 빠른 속도만을 이용하였고\\n별도의 백트래킹문은 넣지 않음\\nDP처럼 모든 지점의 최소 경로값을 구하였음\\n\\\"\\\"\\\"\"\n },\n {\n \"alpha_fraction\": 0.37060701847076416,\n \"alphanum_fraction\": 0.3993610143661499,\n \"avg_line_length\": 19.866666793823242,\n \"blob_id\": \"0e67eea0bdc031f21e8a4f4afcabe7266281ef3b\",\n \"content_id\": \"d6f65d5ea36ffbaf01c7be72ffdfa6f63fdf04a6\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 313,\n \"license_type\": \"no_license\",\n \"max_line_length\": 43,\n \"num_lines\": 15,\n \"path\": \"/알고리즘/온라인저지/2022/05/0523/별 찍기 - 17.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = int(input())\\nstart = N-1\\nlast = N*2-1\\nmiddle = 1\\nfor n in range(N):\\n if n == 0:\\n print(' '*start, '*', sep='')\\n start -= 1\\n elif n == N-1:\\n print('*'*last)\\n else:\\n print(' '*start, end='')\\n print('*', ' '*middle, '*', sep='')\\n middle += 2\\n start -= 1\\n\"\n },\n {\n \"alpha_fraction\": 0.553398072719574,\n \"alphanum_fraction\": 0.6019417643547058,\n \"avg_line_length\": 25,\n \"blob_id\": \"82057bf2426ad090e54bfe566b443942d24d3865\",\n \"content_id\": \"44c94bdfc19d8e24d6f0813c2838c91b36121bf2\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 103,\n \"license_type\": \"no_license\",\n \"max_line_length\": 41,\n \"num_lines\": 4,\n \"path\": \"/알고리즘/온라인저지/2022/12/1207/Dog Treats.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"result = 0\\nfor i in range(1, 4):\\n result += int(input())*i\\nprint('happy' if result >= 10 else 'sad')\"\n },\n {\n \"alpha_fraction\": 0.4206642210483551,\n \"alphanum_fraction\": 0.4206642210483551,\n \"avg_line_length\": 21.66666603088379,\n \"blob_id\": \"b3ab30184962cd9a4b5fe008a15c925c0208187a\",\n \"content_id\": \"a5969ed2dae7213d8fc37a3fd74dd4467ec04da0\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 271,\n \"license_type\": \"no_license\",\n \"max_line_length\": 31,\n \"num_lines\": 12,\n \"path\": \"/알고리즘/온라인저지/2023/05/0520/좋은놈 나쁜놈.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"for _ in range(int(input())):\\n S = input()\\n G = S.count('G')\\n G += S.count('g')\\n B = S.count('B')\\n B += S.count('b')\\n result = 'NEUTRAL'\\n if G > B:\\n result = 'GOOD' \\n if G < B:\\n result = 'A BADDY'\\n print(f'{S} is {result}')\"\n },\n {\n \"alpha_fraction\": 0.46357616782188416,\n \"alphanum_fraction\": 0.5430463552474976,\n \"avg_line_length\": 15.88888931274414,\n \"blob_id\": \"6bc66001c1f38c2876f76e0eb0910f11c8b75875\",\n \"content_id\": \"f80c9a225ea758ba8a491161bd7637abe8b5f464\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 151,\n \"license_type\": \"no_license\",\n \"max_line_length\": 29,\n \"num_lines\": 9,\n \"path\": \"/알고리즘/온라인저지/2022/09/0924/피보나치 비스무리한 수열.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\n\\nN = int(input())\\ndp = [0, 1, 1, 1] + [0]*114\\nfor i in range(4, N+1):\\n dp[i] = dp[i-1] + dp[i-3]\\nprint(dp[N])\"\n },\n {\n \"alpha_fraction\": 0.6756756901741028,\n \"alphanum_fraction\": 0.6756756901741028,\n \"avg_line_length\": 17.66666603088379,\n \"blob_id\": \"e8068822513fa36a39f272bf33a7889d2ccbd218\",\n \"content_id\": \"3f30abd89d5cb6537429a0271139c5b6d6f350e3\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 111,\n \"license_type\": \"no_license\",\n \"max_line_length\": 63,\n \"num_lines\": 6,\n \"path\": \"/알고리즘/온라인저지/2022/09/0927/중복 빼고 정렬하기.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\n\\ninput()\\nprint(*(sorted(list(set(map(int, input().rstrip().split()))))))\"\n },\n {\n \"alpha_fraction\": 0.5025996565818787,\n \"alphanum_fraction\": 0.5242634415626526,\n \"avg_line_length\": 24.66666603088379,\n \"blob_id\": \"8090ca597ba66828e7c113c9c876ffcb9056804c\",\n \"content_id\": \"bc28444de5390de6bbf3d1e93422f6e6cfc24ee1\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1742,\n \"license_type\": \"no_license\",\n \"max_line_length\": 58,\n \"num_lines\": 45,\n \"path\": \"/알고리즘/온라인저지/2021/10/1016/미로 탐색.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from collections import deque # popleft() 사용할 것\\n\\ndx = (-1, 1, 0, 0) # 델타이동 속도를 조금이라도 높이기 위해\\ndy = (0, 0, -1, 1) # tuple() 사용\\n\\nN, M = map(int, input().split())\\n\\narr = []\\n\\nfor n in range(N):\\n arr.append(list(map(int,input()))) # 공백 없으니, split()없이\\n\\nq = deque()\\n\\nq.append((0, 0, 1)) # 출발지점, 출발점부터 거리 카운트함\\n\\nresult = 0 # 결과값 초기화\\n\\nwhile q: # == BFS\\n tmp = q.popleft() # == pop(0)\\n x = tmp[0] # 탐색할 x좌표\\n y = tmp[1] # 탐색할 y좌표\\n cnt = tmp[2] # 여기까지 오는데 걸린 거리\\n if arr[y][x] == 0: # 이전 탐색에서 q에 담았었지만 꺼내보니 방문한 적이 있다면\\n # 방문할 곳에 해당하여 q에 담았지만, 막상 차례가 되서 꺼내보니 탐색할 필요가 없다면\\n # 아래 과정들을 또 진행하여 중복방문이 일어나지 않도록\\n continue\\n arr[y][x] = 0 # 방문처리\\n # 처음에는 arr과 동일한 크기의 visited 배열을 만들어서 방문처리를 하였으나\\n # 메모리가 넉넉하지 않은 문제임을 확인하였고\\n # 원본 배열 자체에서 방문처리 하였음\\n\\n if x == M-1 and y == N-1: # 도착좌표\\n result = cnt # 거리를 결과값에 저장\\n break # 종료\\n\\n for i in range(4): # 탐색중인 좌표가 목적지가 아니라면 \\n # 범위를 벗어나지 않고 방문한 적이 없는 주변 4칸 담을 것\\n nx = x+dx[i] # 좌우\\n ny = y+dy[i] # 상하\\n if 0 <= nx < M and 0 <= ny < N and arr[ny][nx]:\\n # 배열 안에서, 방문한 적이 없다면\\n q.append((nx, ny, cnt+1)) # 방문할 곳에 추가\\n\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.44117647409439087,\n \"alphanum_fraction\": 0.4632352888584137,\n \"avg_line_length\": 16.0625,\n \"blob_id\": \"49a816c129f781ec7b37860f285b5f47cc57ef1b\",\n \"content_id\": \"fe5cb498bad4dbd73623cb0c32c22295e7a06efa\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 272,\n \"license_type\": \"no_license\",\n \"max_line_length\": 31,\n \"num_lines\": 16,\n \"path\": \"/알고리즘/온라인저지/2021/09/0906/수들의 합 5.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\ndef input():\\n return sys.stdin.readline()\\n\\nN = int(input())\\ncnt = 0\\nfor n in range(1, N+1):\\n tmp = N\\n for i in range(n, N+1):\\n tmp -= i\\n if tmp < 0:\\n break\\n elif not tmp:\\n cnt += 1\\n break\\nprint(cnt)\"\n },\n {\n \"alpha_fraction\": 0.37567567825317383,\n \"alphanum_fraction\": 0.4162162244319916,\n \"avg_line_length\": 25.5,\n \"blob_id\": \"7d5253ea21502a7961567ea0b2277be8effc5554\",\n \"content_id\": \"8a0999cf925fcc4601bbb879bfca13ee051f9f36\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 370,\n \"license_type\": \"no_license\",\n \"max_line_length\": 98,\n \"num_lines\": 14,\n \"path\": \"/알고리즘/온라인저지/2022/12/1218/e 계산.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"print('n e')\\nprint('- -----------')\\nfor n in range(10):\\n e = 0\\n for i in range(n+1):\\n factorial = 1\\n s = 1\\n for f in range(1, i+1):\\n factorial *= f\\n s /= factorial\\n e += s\\n print(n, end=' ')\\n e = str(e).split('.')\\n print(f'{float(\\\".\\\".join(e)):0.9f}' if len(e[1]) > 9 else \\\".\\\".join(e) if e[1] != '0' else e[0])\"\n },\n {\n \"alpha_fraction\": 0.5170068144798279,\n \"alphanum_fraction\": 0.5510203838348389,\n \"avg_line_length\": 20.14285659790039,\n \"blob_id\": \"edf7d7c4f4e8471999694b198aa9de88c2d1ce95\",\n \"content_id\": \"6d5d6e2e360ff0a049fac299157028d5e03a24b0\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 147,\n \"license_type\": \"no_license\",\n \"max_line_length\": 38,\n \"num_lines\": 7,\n \"path\": \"/알고리즘/온라인저지/2022/03/0328/조교는 새디스트야!!.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = int(input())\\ncrew = list(map(int, input().split()))\\nresult = 0\\nfor i in range(1, N+1):\\n if crew[i-1] != i:\\n result += 1\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.4440000057220459,\n \"alphanum_fraction\": 0.47200000286102295,\n \"avg_line_length\": 26.88888931274414,\n \"blob_id\": \"f9e34ae56861de691ac7e1326cba1073f51dd4e1\",\n \"content_id\": \"6b1c695f156f92bb4901fe11bdd9a7d5add97e99\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 250,\n \"license_type\": \"no_license\",\n \"max_line_length\": 41,\n \"num_lines\": 9,\n \"path\": \"/알고리즘/온라인저지/2022/09/0912/알파벳 거리.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"for _ in range(int(input())):\\n X, Y = input().split()\\n result = []\\n for i in range(len(X)):\\n y, x = ord(Y[i])-64, ord(X[i])-64\\n tmp = y-x\\n if tmp < 0: tmp += 26\\n result.append(tmp)\\n print('Distances:', *result)\"\n },\n {\n \"alpha_fraction\": 0.40692123770713806,\n \"alphanum_fraction\": 0.42243435978889465,\n \"avg_line_length\": 22.30555534362793,\n \"blob_id\": \"f32533e75252f83d7c425f40079e5ea48479500e\",\n \"content_id\": \"7aa081ea63ae1b970f2fb5521172e8d8fbd9e856\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 906,\n \"license_type\": \"no_license\",\n \"max_line_length\": 63,\n \"num_lines\": 36,\n \"path\": \"/알고리즘/SWEA/LEARN/Course/2. Programming Intermediate/3. 파이썬 SW문제해결 기본 String/4차시 3일차 - 회문.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"def palindrome(arr): # 팰린드롬을 찾아서 result에 추가하는 함수\\n for i in range(N):\\n for j in range(N-M+1):\\n if not M%2:\\n if arr[i][j:j+M//2] == arr[i][j+M:j+M//2-1:-1]:\\n result.append(arr[i][j:j+M])\\n break\\n else:\\n if arr[i][j:j+M//2] == arr[i][j+M:j+M//2:-1]:\\n result.append(arr[i][j:j+M])\\n break \\n\\n\\nT = int(input())\\n\\nfor t in range(1, T+1):\\n N, M = map(int, input().split())\\n\\n arr = tuple(input() for _ in range(N))\\n\\n result = []\\n # 가로\\n palindrome(arr)\\n \\n # 세로 : 배열을 90도 뒤집어서 똑같은 코드 실행\\n arr = list(arr)\\n\\n tmp = ['' for _ in range(N)]\\n \\n for a in arr:\\n for i in range(N):\\n tmp[i] = tmp[i] + a[i]\\n \\n palindrome(tmp)\\n\\n print('#{} {}'.format(t, *result))\"\n },\n {\n \"alpha_fraction\": 0.5236220359802246,\n \"alphanum_fraction\": 0.539370059967041,\n \"avg_line_length\": 14.9375,\n \"blob_id\": \"d80325e272700c470082b17f4ca8b3e9aed87e3a\",\n \"content_id\": \"19344b6ccbe56c6e9a9d3620ab6f9737f617d8a5\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 254,\n \"license_type\": \"no_license\",\n \"max_line_length\": 26,\n \"num_lines\": 16,\n \"path\": \"/알고리즘/온라인저지/2022/09/0903/30.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = input()\\ntmp = 0\\nzero = False\\nresult = []\\nfor n in N:\\n n = int(n)\\n tmp += n\\n result.append(n)\\n if n == 0: zero = True\\ntmp %= 3\\nresult.sort(reverse=True)\\nif not tmp and zero:\\n for r in result:\\n print(r, end='')\\nelse:\\n print(-1)\"\n },\n {\n \"alpha_fraction\": 0.5714285969734192,\n \"alphanum_fraction\": 0.6285714507102966,\n \"avg_line_length\": 35,\n \"blob_id\": \"2e0fc741a6f78fa8c60aa966b5dae4d6e733a5af\",\n \"content_id\": \"ad8efce2b6b676c0a67cf96ff1138971b7875b8c\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 35,\n \"license_type\": \"no_license\",\n \"max_line_length\": 35,\n \"num_lines\": 1,\n \"path\": \"/알고리즘/온라인저지/2023/04/0427/ゾロ目 (Same Numbers).py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"a,b=input();print(1 if a==b else 0)\"\n },\n {\n \"alpha_fraction\": 0.5246636867523193,\n \"alphanum_fraction\": 0.5650224089622498,\n \"avg_line_length\": 21.399999618530273,\n \"blob_id\": \"783df0b75a5bf00a31f2c537249a898380d449fb\",\n \"content_id\": \"3defba8010f0187f79044cf1bb7e0fab8df521ac\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 223,\n \"license_type\": \"no_license\",\n \"max_line_length\": 42,\n \"num_lines\": 10,\n \"path\": \"/알고리즘/온라인저지/2022/11/1127/JOI와 IOI.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\n\\nresult = [0, 0] # JOI, IOI\\nS = input().rstrip()\\nfor i in range(len(S)-2):\\n if S[i:i+3] == 'JOI': result[0] += 1\\n elif S[i:i+3] == 'IOI': result[1] += 1\\nfor r in result: print(r)\"\n },\n {\n \"alpha_fraction\": 0.4480408728122711,\n \"alphanum_fraction\": 0.475298136472702,\n \"avg_line_length\": 23.95652198791504,\n \"blob_id\": \"ff2d095d9f15609aed06ca59aaadc5476b20dc01\",\n \"content_id\": \"1d324a72c061935a6e75debf0b2f886da0f4f503\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 807,\n \"license_type\": \"no_license\",\n \"max_line_length\": 57,\n \"num_lines\": 23,\n \"path\": \"/알고리즘/온라인저지/2021/10/1003/부분수열의 합.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N, S = map(int, input().split())\\n\\narr = list(map(int, input().split()))\\n\\nn = len(arr)\\n\\ncnt = 0 # 부분집합의 합이 S가 될 때마다 +1\\n\\n# 비트연산 \\\"<<\\\"를 통해 부분집합을 구해줄 것\\nfor i in range(1<<n): # 2의 len(arr)승 -> arr의 부분집합의 개수\\n tmp = [] # 부분집합 초기화\\n for j in range(n): \\n if i&(1<<j): # 1<<j == arr에서 j번째 원소를 의미\\n # 만약 i의 비트가 11100이면\\n # tmp == 리스트의 0번째, 1번째, 2번째 원소를 가지는 arr의 부분집합\\n tmp.append(arr[j]) # 해당 부분집합의 원소를 부분집합에 추가\\n if sum(tmp) == S:\\n if len(tmp) == 0: # 공집합은 예외처리\\n pass\\n else: # \\n cnt += 1\\n\\nprint(cnt) # 출력\\n \\n\"\n },\n {\n \"alpha_fraction\": 0.4107142984867096,\n \"alphanum_fraction\": 0.5059523582458496,\n \"avg_line_length\": 20.125,\n \"blob_id\": \"164d01b972c587fd9e803973aa97cc7360405223\",\n \"content_id\": \"95b727a63e6144247fdd53c127f0d95cb3b38906\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 168,\n \"license_type\": \"no_license\",\n \"max_line_length\": 43,\n \"num_lines\": 8,\n \"path\": \"/알고리즘/온라인저지/2022/02/0206/5와 6의 차이.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"A, B = input().split()\\n\\nA5 = A.replace('6', '5')\\nA6 = A.replace('5', '6')\\nB5 = B.replace('6', '5')\\nB6 = B.replace('5', '6')\\n\\nprint(int(A5) + int(B5), int(A6) + int(B6))\"\n },\n {\n \"alpha_fraction\": 0.5761589407920837,\n \"alphanum_fraction\": 0.6158940196037292,\n \"avg_line_length\": 15.88888931274414,\n \"blob_id\": \"4771af0518336e6f867b278cf383ed248c21a2d1\",\n \"content_id\": \"21e87d2ea81b6865b0cdc77fc842dbd7d6cdfed6\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 151,\n \"license_type\": \"no_license\",\n \"max_line_length\": 56,\n \"num_lines\": 9,\n \"path\": \"/알고리즘/온라인저지/2022/03/0301/팀 나누기.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"players = list(map(int, input().split()))\\n\\nplayers.sort()\\n\\ntmp = [players[0] + players[3], players[1] + players[2]]\\n\\ntmp.sort()\\n\\nprint(tmp[1] - tmp[0])\"\n },\n {\n \"alpha_fraction\": 0.3425000011920929,\n \"alphanum_fraction\": 0.38749998807907104,\n \"avg_line_length\": 13.851851463317871,\n \"blob_id\": \"5ea179f9fd0a5408d228219a09a8f79ec0caa652\",\n \"content_id\": \"d65adb19549de5b44d6cfcc3b5a01a7f8e25f272\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 400,\n \"license_type\": \"no_license\",\n \"max_line_length\": 34,\n \"num_lines\": 27,\n \"path\": \"/알고리즘/온라인저지/2022/01/0108/1, 2, 3 더하기.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"T = int(input())\\n\\nfor tc in range(T):\\n N = int(input())\\n\\n dp = [0 for _ in range(N+1)]\\n\\n dp[1] = 1\\n if N == 1:\\n print(dp[1])\\n continue\\n dp[2] = 2\\n\\n if N == 2:\\n print(dp[2])\\n continue\\n\\n dp[3] = 4\\n if N == 3:\\n print(dp[3])\\n continue\\n\\n if N > 3:\\n for i in range(4, N+1):\\n dp[i] = sum(dp[i-3:i])\\n\\n print(dp[N])\"\n },\n {\n \"alpha_fraction\": 0.4372294247150421,\n \"alphanum_fraction\": 0.5064935088157654,\n \"avg_line_length\": 20.090909957885742,\n \"blob_id\": \"166cfacd163b1397eeb72618e1d3b86aeed98d7e\",\n \"content_id\": \"ebb3675ac542628b3c0ea2815d6a111822966531\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 231,\n \"license_type\": \"no_license\",\n \"max_line_length\": 32,\n \"num_lines\": 11,\n \"path\": \"/알고리즘/온라인저지/2022/09/0901/진법 변환.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"number = input().split()\\nN, B = number[0], int(number[1])\\nresult = 0\\nN = N[::-1]\\nfor i in range(len(N)):\\n O = ord(N[i]) # ord\\n if 48<=O<=57: O -= 48\\n elif 65<=O<=90: O -= 55\\n tmp = B**i*O\\n result += tmp\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.34688347578048706,\n \"alphanum_fraction\": 0.38482385873794556,\n \"avg_line_length\": 13.800000190734863,\n \"blob_id\": \"702a8cfb42d9fba87b161cd0a659026b016b94e6\",\n \"content_id\": \"693ad1168fca5d1f5b1057bc0ce5a70242996049\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 369,\n \"license_type\": \"no_license\",\n \"max_line_length\": 38,\n \"num_lines\": 25,\n \"path\": \"/알고리즘/온라인저지/2022/11/1116/문어 숫자.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\n\\noctopus = {\\n '-': 0,\\n '\\\\\\\\': 1,\\n '(': 2,\\n '@': 3,\\n '?': 4,\\n '>': 5,\\n '&': 6,\\n '%': 7,\\n '/': -1,\\n}\\n\\nwhile True:\\n tmp = list(input().rstrip())[::-1]\\n if tmp == ['#']: break\\n j = 0\\n result = 0\\n for i in range(len(tmp)):\\n result += 8**j*octopus[tmp[i]]\\n j += 1\\n print(result)\"\n },\n {\n \"alpha_fraction\": 0.4805825352668762,\n \"alphanum_fraction\": 0.553398072719574,\n \"avg_line_length\": 22,\n \"blob_id\": \"7408283afe8e5563b6c779cdfcfd571b64bf4151\",\n \"content_id\": \"2ec7e41b36ba889233dbc8a4deb8e2ad10b4d5f5\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 206,\n \"license_type\": \"no_license\",\n \"max_line_length\": 43,\n \"num_lines\": 9,\n \"path\": \"/알고리즘/온라인저지/2022/10/1003/Generations of Tribbles.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\n\\ndp = [1, 1, 2, 4] + [0]*66\\nfor i in range(4, 70):\\n dp[i] = dp[i-1]+dp[i-2]+dp[i-3]+dp[i-4]\\nfor i in [0]*int(input().rstrip()):\\n print(dp[int(input().rstrip())])\"\n },\n {\n \"alpha_fraction\": 0.6302083134651184,\n \"alphanum_fraction\": 0.6302083134651184,\n \"avg_line_length\": 26.571428298950195,\n \"blob_id\": \"ef4864106946dbfe9ed1c1c4817f1a7280b6878c\",\n \"content_id\": \"348ce8e0edba8c5f35c4d7ae37f146713f0befaf\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 192,\n \"license_type\": \"no_license\",\n \"max_line_length\": 45,\n \"num_lines\": 7,\n \"path\": \"/알고리즘/온라인저지/2023/04/0419/특별한 학교 이름.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"school = {\\n 'NLCS': 'North London Collegiate School',\\n 'BHA': 'Branksome Hall Asia',\\n 'KIS': 'Korea International School',\\n 'SJA': 'St. Johnsbury Academy',\\n}\\nprint(school[input()])\"\n },\n {\n \"alpha_fraction\": 0.49814125895500183,\n \"alphanum_fraction\": 0.5018587112426758,\n \"avg_line_length\": 19.769229888916016,\n \"blob_id\": \"8f8de9852e62d66ca0618f9ebab6440392a2673a\",\n \"content_id\": \"b2cc8304696776c735f7d87dd6327ea8be675e2c\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 269,\n \"license_type\": \"no_license\",\n \"max_line_length\": 50,\n \"num_lines\": 13,\n \"path\": \"/알고리즘/온라인저지/2022/03/0320/공.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"M = int(input())\\nmoves = []\\nfor m in range(M):\\n moves.append(tuple(map(int, input().split())))\\n# print(moves)\\nball = 1\\nfor move in moves:\\n if ball in move:\\n for m in move:\\n if ball != m:\\n ball = m\\n break\\nprint(ball)\"\n },\n {\n \"alpha_fraction\": 0.5317460298538208,\n \"alphanum_fraction\": 0.60317462682724,\n \"avg_line_length\": 24.399999618530273,\n \"blob_id\": \"883d94378d5c373039dac2304b525982ef02e3be\",\n \"content_id\": \"ca2571aada4b8cc2472f5c372c587c947c754c3b\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 126,\n \"license_type\": \"no_license\",\n \"max_line_length\": 38,\n \"num_lines\": 5,\n \"path\": \"/알고리즘/온라인저지/2023/04/0414/덧셈과 곱셈.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"a, b = map(int, input().split())\\nresult = 1\\nfor i in range(a, b+1):\\n result *= sum(list(range(1, i+1)))\\nprint(result%14579)\"\n },\n {\n \"alpha_fraction\": 0.42352941632270813,\n \"alphanum_fraction\": 0.4470588266849518,\n \"avg_line_length\": 16,\n \"blob_id\": \"49d41ac31357400bfdd1a8775289b8902afb7299\",\n \"content_id\": \"c7f3e81358032745e47a5d3d97330d8d638a5c62\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 255,\n \"license_type\": \"no_license\",\n \"max_line_length\": 36,\n \"num_lines\": 15,\n \"path\": \"/알고리즘/온라인저지/2022/05/0514/팩토리얼 진법.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"table = []\\na = 1\\nfor i in range(1, 6):\\n table.append(a*i)\\n a *= i\\nwhile True:\\n N = input()\\n if N == '0':\\n break\\n M = len(N)\\n N = N[::-1]\\n result = 0\\n for i in range(M):\\n result += int(N[i])*table[i]\\n print(result)\\n\"\n },\n {\n \"alpha_fraction\": 0.450236976146698,\n \"alphanum_fraction\": 0.450236976146698,\n \"avg_line_length\": 14.142857551574707,\n \"blob_id\": \"d52006b5c96a1762fe3eba34428b2789b71833b9\",\n \"content_id\": \"159853587b92910b72bf3805fe2299a14e2ac109\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 211,\n \"license_type\": \"no_license\",\n \"max_line_length\": 40,\n \"num_lines\": 14,\n \"path\": \"/알고리즘/온라인저지/2022/02/0213/얼마.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"T = int(input())\\n\\nfor t in range(T):\\n S = int(input())\\n N = int(input())\\n \\n result = S\\n\\n for n in range(N):\\n q, p = map(int, input().split())\\n\\n result += q * p\\n \\n print(result)\"\n },\n {\n \"alpha_fraction\": 0.565517246723175,\n \"alphanum_fraction\": 0.5793103575706482,\n \"avg_line_length\": 35.5,\n \"blob_id\": \"dcaf2cede807a7219785e05b4fcb672afea1098e\",\n \"content_id\": \"ac5f0fc9ac7cfb1c506886ef2f193d01ed64c6dc\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 145,\n \"license_type\": \"no_license\",\n \"max_line_length\": 76,\n \"num_lines\": 4,\n \"path\": \"/알고리즘/온라인저지/2022/08/0806/숫자 카드.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = int(input())\\nC = set(map(int, input().split()))\\nM = int(input())\\nfor i in list(map(int, input().split())): print(1 if i in C else 0, end=' ')\"\n },\n {\n \"alpha_fraction\": 0.446393758058548,\n \"alphanum_fraction\": 0.4684860408306122,\n \"avg_line_length\": 32.4782600402832,\n \"blob_id\": \"381502c937816e48575f7d696e5c8b885e71f4ff\",\n \"content_id\": \"12b2b6279a1808f853f9153bba8751e12fdff6db\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1983,\n \"license_type\": \"no_license\",\n \"max_line_length\": 85,\n \"num_lines\": 46,\n \"path\": \"/알고리즘/온라인저지/2022/09/0913/치즈.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from collections import deque\\n\\ndy, dx = [-1, 1, 0, 0], [0, 0, -1, 1]\\nN, M = map(int, input().split())\\narr = [list(map(int, input().split())) for _ in range(N)]\\nresult = [0, int(1e9)] # [녹는데 걸리는 시간, 다 녹기 한 시간 전 남은 치즈 수]\\nwhile True:\\n melt = True # 다 녹았는지 확인할 것\\n cheese = 0 # 지금 남아있는 치즈 수\\n for i in range(N):\\n for j in range(M):\\n if arr[i][j]: # 하나라도 안 녹은 치즈가 있다면\\n melt = False # 다 녹은 것은 아니지\\n cheese += 1 # 치즈 개수 증가\\n if melt: # 다 녹았다면\\n for r in result: print(r) # 출력\\n break\\n else: # 다 안녹았다면 녹이러 가자!\\n Q, cheese_Q = deque(), deque() # 배열탐색 deque, 녹일 치즈만 담을 deque\\n visited = [[0]*M for _ in range(N)]\\n Q.append((0, 0)) # 배열의 가장자리는 무조건 공기이다\\n visited[0][0] = 1 \\n while Q:\\n y, x = Q.popleft()\\n for k in range(4):\\n ny, nx = y+dy[k], x+dx[k] # 상하좌우\\n if 0<=ny<N and 0<=nx<M and not visited[ny][nx]:\\n visited[ny][nx] = 1 # 치즈든 공기든, 탐색할 것\\n if arr[ny][nx]: # 치즈\\n cheese_Q.append((ny, nx)) # 녹일 치즈\\n else: # 공기\\n Q.append((ny, nx)) # 다음 탐색할 공기\\n while cheese_Q: # 치즈를 녹이자\\n y, x = cheese_Q.popleft()\\n arr[y][x] = 0 # 치즈가 녹는다\\n result[0] += 1 # 한 시간 경과\\n result[1] = min(result[1], cheese) # 배열의 치즈들은 녹았지만, cheese는 녹기 전 치즈 수를 가지고 있다\\n\\n\\\"\\\"\\\"\\n핵심\\n1. 공기를 기준으로 주변 치즈를 녹인다\\n2. 녹이면서 진행하지 말고\\n 녹일 치즈들을 한 데 모아, 한 번에 녹인다\\n\\\"\\\"\\\"\\n\\n# https://www.acmicpc.net/problem/2636\"\n },\n {\n \"alpha_fraction\": 0.5240174531936646,\n \"alphanum_fraction\": 0.5327510833740234,\n \"avg_line_length\": 27.75,\n \"blob_id\": \"568692f7dc0910a82bb61ea04e4b91c952fc2f5b\",\n \"content_id\": \"a0925f50f0880181d80ee561fe6e3c7ad38ba08d\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 229,\n \"license_type\": \"no_license\",\n \"max_line_length\": 56,\n \"num_lines\": 8,\n \"path\": \"/알고리즘/온라인저지/2022/12/1210/대충 더해.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"A, B = map(str, sorted(list(map(int, input().split()))))\\nresult = ''\\nfor i in range(1, len(B)+1):\\n try:\\n result = str(int(A[-i]) + int(B[-i])) + result\\n except:\\n result = str(int(B[-i])) + result\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.4330601096153259,\n \"alphanum_fraction\": 0.4439890682697296,\n \"avg_line_length\": 21.90625,\n \"blob_id\": \"dbdfccaf4c158bd8a1a414f13136687066f71142\",\n \"content_id\": \"c05feedc47e5fc56044244c8be8aaf5cbe0658de\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 732,\n \"license_type\": \"no_license\",\n \"max_line_length\": 47,\n \"num_lines\": 32,\n \"path\": \"/알고리즘/온라인저지/2022/04/0403/세 수.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import copy\\nnums = list(map(int, input().split()))\\noriginal = copy.deepcopy(nums)\\nnums.sort()\\nA, B, C = nums[0], nums[1], nums[2]\\n# print(A, B, C)\\nope = 1 # * or /\\nif A+B == C:\\n ope = 0 # + or -\\n# print(ope)\\n# print(nums, original)\\nD, E, F = original[0], original[1], original[2]\\nresult = ''\\nif not ope:\\n if D+E == F:\\n result = f'{D}+{E}={F}'\\n elif E+F == D:\\n result = f'{D}={E}+{F}'\\n elif D-E == F:\\n result = f'{D}-{E}={F}'\\n elif E-F == D:\\n result = f'{D}={E}-{F}'\\nelse:\\n if D*E == F:\\n result = f'{D}*{E}={F}'\\n elif E*F == D:\\n result = f'{D}={E}*{F}'\\n elif D//E == F:\\n result = f'{D}/{E}={F}'\\n elif E//F == D:\\n result = f'{D}={E}/{F}'\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.5584415793418884,\n \"alphanum_fraction\": 0.5714285969734192,\n \"avg_line_length\": 12,\n \"blob_id\": \"6480c6993f063ac21f93d51bed3aef955264d14b\",\n \"content_id\": \"e7dbee1d222b155f47cd53e5ad0a5f170309e999\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 77,\n \"license_type\": \"no_license\",\n \"max_line_length\": 24,\n \"num_lines\": 6,\n \"path\": \"/알고리즘/온라인저지/2022/02/0202/영수증.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"bill = int(input())\\n\\nfor _ in range(9):\\n bill -= int(input())\\n\\nprint(bill)\"\n },\n {\n \"alpha_fraction\": 0.4455958604812622,\n \"alphanum_fraction\": 0.46113988757133484,\n \"avg_line_length\": 18.399999618530273,\n \"blob_id\": \"79ca20c7a273aad5dcbfaf7770e9f644cf683ce0\",\n \"content_id\": \"d4e88f61dc1833c454a77d3907e808cf7d29430b\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 193,\n \"license_type\": \"no_license\",\n \"max_line_length\": 38,\n \"num_lines\": 10,\n \"path\": \"/알고리즘/온라인저지/2022/02/0220/ABC.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"nums = list(map(int, input().split()))\\nnums.sort()\\n\\nfor i in input():\\n if i == 'A':\\n print(nums[0])\\n elif i == 'B':\\n print(nums[1])\\n elif i == 'C':\\n print(nums[2])\"\n },\n {\n \"alpha_fraction\": 0.4766763746738434,\n \"alphanum_fraction\": 0.5199222564697266,\n \"avg_line_length\": 22.397727966308594,\n \"blob_id\": \"ac9780e815a2647a0816600313fad516f4576630\",\n \"content_id\": \"df70e96931cd8eb4b9b272fb63a1421e27eff755\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 2602,\n \"license_type\": \"no_license\",\n \"max_line_length\": 68,\n \"num_lines\": 88,\n \"path\": \"/알고리즘/온라인저지/2022/03/0314/톱니바퀴.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"\\\"\\\"\\\"\\n반시계\\n11001110\\n-1\\n10011101\\n\\n시계\\n11001110\\n1\\n01100111\\n\\\"\\\"\\\"\\n\\nfrom pprint import pprint\\n\\n\\ndef clockwise(i): # 시계방향\\n global gears, visited\\n if i not in range(4): # 톱니 인덱스가 범위를 벗어나면\\n return # 함수 종료\\n # print(\\\"clockwise!\\\", i+1) # 디버깅\\n try:\\n if gears[i][2] != gears[i+1][6]: # 현재 톱니바퀴의 오른쪽 톱니바퀴와 극이 다르면\\n visited[i] = 1 # 방문처리\\n if not visited[i+1]: # 확인하지 않은 톱니바퀴에 대해\\n counter_clockwise(i+1) # 오른쪽 톱니 반시계방향\\n except:\\n pass\\n try:\\n if gears[i][6] != gears[i-1][2]: # 현재 톱니바퀴의 왼쪽 톱니바퀴와 극이 다르면\\n visited[i] = 1\\n if not visited[i-1]:\\n counter_clockwise(i-1) # 왼쪽 톱니 반시계방향\\n except:\\n pass\\n tmp = [gears[i][-1]] + gears[i][:7] # 시계방향으로 돌려주기\\n gears[i] = tmp\\n\\ndef counter_clockwise(i): # 반시계방향\\n global gears, visited\\n if i not in range(4): # 톱니 인덱스가 범위를 벗어나면\\n return # 함수 종료\\n # print('counter!!', i+1) # 디버깅\\n try:\\n if gears[i][2] != gears[i+1][6]: # 오른쪽 톱니와 극이 다르면\\n visited[i] = 1\\n if not visited[i+1]:\\n clockwise(i+1) # 오른쪽 톱니 시계방향\\n except:\\n pass\\n try:\\n if gears[i][6] != gears[i-1][2]: # 왼쪽 톱니와 극이 다르면\\n visited[i] = 1\\n if not visited[i-1]:\\n clockwise(i-1) # 왼쪽 톱니 시계방향\\n except:\\n pass\\n tmp = gears[i][1:] + [gears[i][0]] # 반시계방향으로 돌려주기\\n gears[i] = tmp\\n\\n\\n# 값들 입력받기\\ngears = [] # 톱니들\\nfor _ in range(4):\\n gears.append(list(map(int, input())))\\nK = int(input())\\norders = [] # 돌리는 톱니번호와 방향들\\nfor k in range(K):\\n orders.append(tuple(map(int, input().split())))\\n\\n# pprint(gears) # 디버깅\\n\\nfor order in orders: \\n # print(order) # 디버깅\\n visited = [0] * 4 # 매 톱니마다 방문배열 초기화\\n if order[1] == 1:\\n clockwise(order[0]-1) # 시계방향\\n elif order[1] == -1:\\n counter_clockwise(order[0]-1) # 반시계방향\\n # pprint(gears) # 디버깅\\n\\nresult = 0 # 결과값 초기화\\nnum = 1 # 결과값에 더할 변수값 초기화\\nfor i in range(4):\\n if gears[i][0]: # 12시 톱니가 1이면\\n result += num # 결과값 갱신\\n num *= 2 # 1 2 4 8 \\n\\nprint(result) # 결과값 출력\"\n },\n {\n \"alpha_fraction\": 0.4950000047683716,\n \"alphanum_fraction\": 0.5149999856948853,\n \"avg_line_length\": 21.33333396911621,\n \"blob_id\": \"58c73bbd31ce80e07433c7117e77e02416d75334\",\n \"content_id\": \"0c95248971f536e888baadc3cac34581bae48eb6\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 200,\n \"license_type\": \"no_license\",\n \"max_line_length\": 38,\n \"num_lines\": 9,\n \"path\": \"/알고리즘/온라인저지/2022/05/0519/나이순 정렬.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"age = [[] for _ in range(201)]\\nT = int(input())\\nfor t in range(T):\\n member = input().split()\\n age[int(member[0])].append(member)\\nfor a in age:\\n if a:\\n for i in a:\\n print(*i)\"\n },\n {\n \"alpha_fraction\": 0.27710843086242676,\n \"alphanum_fraction\": 0.4518072307109833,\n \"avg_line_length\": 12.916666984558105,\n \"blob_id\": \"6e33e24ff9174afac506797062913afb4a99e02e\",\n \"content_id\": \"6a33f7a4b542b779d8d4624dbc2d15fbf4c39976\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 166,\n \"license_type\": \"no_license\",\n \"max_line_length\": 40,\n \"num_lines\": 12,\n \"path\": \"/알고리즘/온라인저지/2022/05/0531/도미노.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"a = 0\\nresult = 0\\nfor i in range(int(input()), -1, -1):\\n a += 3\\n result += i*a\\nprint(result)\\n\\n\\\"\\\"\\\"\\n2 = 0+1+2 = 0+3+9\\n3=0+1+2+3 = 0+3+9+18 = 0+3+(3+6)+(3+6+9)\\n\\n\\\"\\\"\\\"\"\n },\n {\n \"alpha_fraction\": 0.4956521689891815,\n \"alphanum_fraction\": 0.4956521689891815,\n \"avg_line_length\": 16.769229888916016,\n \"blob_id\": \"600a78a3dd5d9d751b8e1e3dab0ff4dbeef146f8\",\n \"content_id\": \"a2a76d0ad887dc2fa74cbee100a56ff7ccd0ec58\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 230,\n \"license_type\": \"no_license\",\n \"max_line_length\": 39,\n \"num_lines\": 13,\n \"path\": \"/알고리즘/온라인저지/2021/12/1216/TGN.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = int(input())\\n\\nfor n in range(N):\\n r, e, c = map(int, input().split())\\n\\n fee = e-c\\n\\n if fee > r:\\n print('advertise')\\n elif fee < r:\\n print('do not advertise')\\n else:\\n print('does not matter')\"\n },\n {\n \"alpha_fraction\": 0.5249999761581421,\n \"alphanum_fraction\": 0.550000011920929,\n \"avg_line_length\": 12.666666984558105,\n \"blob_id\": \"ff196def3d709304e1b727e33236d0290332be74\",\n \"content_id\": \"dba783ef9e53faedbc43ed33d75b3c9466b98f24\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 40,\n \"license_type\": \"no_license\",\n \"max_line_length\": 21,\n \"num_lines\": 3,\n \"path\": \"/알고리즘/SWEA/LEARN/Course/1. Programming Beginner/파이썬 프로그래밍 기초(2)/38차시 4. 문자열 - 연습문제 2.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"tmp = input().split()\\n\\nprint(*tmp[::-1])\"\n },\n {\n \"alpha_fraction\": 0.4427710771560669,\n \"alphanum_fraction\": 0.45783132314682007,\n \"avg_line_length\": 21.200000762939453,\n \"blob_id\": \"b45e1f3596602fda0343822d9f279cc6df6e2b55\",\n \"content_id\": \"1016c790054ead630c171542ec4a7acfaa766c1a\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 332,\n \"license_type\": \"no_license\",\n \"max_line_length\": 41,\n \"num_lines\": 15,\n \"path\": \"/알고리즘/온라인저지/2022/07/0723/폴리오미노.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"board = input().split('.')\\n# print(board)\\nresult = ''\\nfor i in range(len(board)):\\n if len(board[i])%2:\\n result = -1\\n break\\n result += 'AAAA' * (len(board[i])//4)\\n if len(board[i])%4:\\n result += 'BB'\\n if i != len(board)-1:\\n result += '.'\\n # if b == '':\\n # result += '.'\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.5798816680908203,\n \"alphanum_fraction\": 0.5964497327804565,\n \"avg_line_length\": 24.636363983154297,\n \"blob_id\": \"f700b080ff8632ffebd63c839c4583cca59f1a6e\",\n \"content_id\": \"0289e2c412d52bd79e3328ed9df2764663cba35e\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1475,\n \"license_type\": \"no_license\",\n \"max_line_length\": 69,\n \"num_lines\": 33,\n \"path\": \"/알고리즘/온라인저지/2022/08/0816/쇠막대기.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"B, result, S, j = input(), 0, [], 0 # bar, result, stack, laser index\\nL = [i for i in range(1, len(B)) if B[i-1]+B[i] == '()'] # laser\\nfor i in range(len(B)):\\n if B[i] == '(': S.append(B[i])\\n elif B[i] == ')':\\n if i == L[j]: \\n S.pop()\\n result += len(S)\\n if j < len(L)-1: j += 1\\n else: S.pop(); result += 1\\nprint(result)\\n\\n\\\"\\\"\\\"\\n쇠막대기의 시작('(')을 스택에 넣는다\\n레이저가 등장하면 등장한 모든 쇠막대기는 잘려나가고\\nlen(stack) 만큼의 잘린 부분이 생겨난다\\n쇠막대기가 끝나면 바로 직전 레이저에서 잘려나갔기 때문에\\n잘린 마지막 파편을 result++ 하고, 스택에서 꺼낸다\\n위 과정을 반복하되\\n레이저는 시작과 끝에 존재할 수 있으니 조심\\n\\n<코드 리팩토링>\\n레이저인지 확인하는 방법으로\\n쇠막대기 입력에서 레이저의 인덱스를 추출하고 저장하였다\\n')'가 등장할 때의 인덱스가, 레이저인덱스(L)에 있으면 레이저고\\n레이저인덱스에 없으면 레이저가 아닌 닫는 쇠막대기다\\n이 레이저인덱스를 확인하는 과정에서 in 연산자를 사용했던\\n처음 제출한 코드는 608ms의 시간이 걸렸고\\n인덱스를 직접 잡아주는 방식으로 코드를 바꿔주니\\n156ms가 걸리면서, 약 4배의 시간단축을 보여주었다\\nin이 진짜 느리긴 느리구나.. 실버 상위 문제부터는\\n사용하기가 망설여진다\\n\\\"\\\"\\\"\"\n },\n {\n \"alpha_fraction\": 0.4560000002384186,\n \"alphanum_fraction\": 0.4959999918937683,\n \"avg_line_length\": 11.5,\n \"blob_id\": \"5727dc3f42de44389f632e1e85f90cff7d95ce78\",\n \"content_id\": \"d1514f23d48eef9574fb83d3d0754f06bfc4be86\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 125,\n \"license_type\": \"no_license\",\n \"max_line_length\": 27,\n \"num_lines\": 10,\n \"path\": \"/알고리즘/온라인저지/2022/01/0131/팩토리얼.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = int(input())\\n\\nresult = 1\\n\\nif N > 1:\\n for i in range(2, N+1):\\n result *= i\\n print(result)\\nelse:\\n print(1)\\n\"\n },\n {\n \"alpha_fraction\": 0.4845132827758789,\n \"alphanum_fraction\": 0.508849561214447,\n \"avg_line_length\": 20.571428298950195,\n \"blob_id\": \"423923f14024b5c7867f1043b30e0623642c4379\",\n \"content_id\": \"9ae4bb6f259de670d6fa943e2326c4758f369745\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 630,\n \"license_type\": \"no_license\",\n \"max_line_length\": 44,\n \"num_lines\": 21,\n \"path\": \"/알고리즘/온라인저지/2022/03/0307/N과 M (4).py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"def dfs(s, depth):\\n global N, M\\n\\n if depth == M: # M개의 수를 담았을 때\\n print(*result[1:]) # *로 언패킹해서 출력\\n return # 재귀 탈출\\n\\n # 아직 M개의 수를 담지 않았을 때\\n depth += 1 # 하나 더 고르자\\n\\n for i in range(s, N+1): # 시작하는 수 s부터 N까지\\n result[depth] = i # depth번째 수는 i\\n dfs(s, depth) # 한 depth더 들어가기\\n s += 1 # 들어갔다 나왔으면 s를 하나 올리기\\n\\n\\nN, M = map(int, input().split())\\n\\nresult = [0] * (M+1) # 인덱스 맞추기 위한 M+1\\n\\ndfs(1, 0) # 시작은 1, 깊이는 0부터 시작\"\n },\n {\n \"alpha_fraction\": 0.38823530077934265,\n \"alphanum_fraction\": 0.4117647111415863,\n \"avg_line_length\": 11.285714149475098,\n \"blob_id\": \"d8ddeac45dae25d116f633d63f94ec68a0720735\",\n \"content_id\": \"c1cfc5e192f87fb931205176dfa20a7a91d87dbd\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 85,\n \"license_type\": \"no_license\",\n \"max_line_length\": 20,\n \"num_lines\": 7,\n \"path\": \"/알고리즘/온라인저지/2023/05/0522/末尾の文字 (Last Letter).py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"input()\\nS = input()\\nif S[-1] == 'G':\\n S = S[:len(S)-1]\\nelse:\\n S += 'G'\\nprint(S)\"\n },\n {\n \"alpha_fraction\": 0.51171875,\n \"alphanum_fraction\": 0.53515625,\n \"avg_line_length\": 22.363636016845703,\n \"blob_id\": \"ff83b866bf74ee84e2c12dbbeb977a5f8cf0ead1\",\n \"content_id\": \"ba8b014e5726aa1edcef68da71ea28d342e1faa7\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 256,\n \"license_type\": \"no_license\",\n \"max_line_length\": 39,\n \"num_lines\": 11,\n \"path\": \"/알고리즘/온라인저지/2022/07/0728/베스트셀러.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = int(input())\\narr = dict()\\nfor n in range(N):\\n book = input()\\n if book not in arr:\\n arr[book] = 1\\n else: # book in arr\\n arr[book] += 1\\nresult = [(a, arr[a]) for a in arr]\\nresult.sort(key=lambda x:(-x[1], x[0]))\\nprint(result[0][0])\"\n },\n {\n \"alpha_fraction\": 0.4858871102333069,\n \"alphanum_fraction\": 0.49193549156188965,\n \"avg_line_length\": 26.61111068725586,\n \"blob_id\": \"ed588628c101b2a57f2d2053901bf053bf7f6355\",\n \"content_id\": \"09cda782898f459038bcc6bc11b09f57ffe21602\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 496,\n \"license_type\": \"no_license\",\n \"max_line_length\": 59,\n \"num_lines\": 18,\n \"path\": \"/알고리즘/온라인저지/2022/11/1126/기상캐스터.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\nINF = int(1e9)\\nH, W = map(int, input().rstrip().split())\\nresult = [[INF]*W for _ in range(H)]\\narr = [input().rstrip() for _ in range(H)]\\nfor i in range(H):\\n for j in range(W):\\n if arr[i][j] == 'c':\\n for k in range(W):\\n if j+k < W:\\n result[i][j+k] = min(result[i][j+k], k)\\nfor i in range(H):\\n for j in range(W):\\n if result[i][j] == INF:\\n result[i][j] = -1\\nfor r in result: print(*r)\"\n },\n {\n \"alpha_fraction\": 0.4585798680782318,\n \"alphanum_fraction\": 0.4822485148906708,\n \"avg_line_length\": 24.461538314819336,\n \"blob_id\": \"b5d675023456534f33549813ddd29a11444266ef\",\n \"content_id\": \"bfc05ec1b2095455a00c26cfe0941665c0646ec7\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 338,\n \"license_type\": \"no_license\",\n \"max_line_length\": 39,\n \"num_lines\": 13,\n \"path\": \"/알고리즘/온라인저지/2022/12/1227/3대 측정.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N, K, L = map(int, input().split())\\nresult = [0, []]\\nfor n in range(N):\\n A, B, C = map(int, input().split())\\n summ = A + B + C\\n minn = min(A, B, C)\\n if summ >= K and minn >= L:\\n result[0] += 1\\n result[1].append(A)\\n result[1].append(B)\\n result[1].append(C)\\nprint(result[0])\\nprint(*result[1]) \"\n },\n {\n \"alpha_fraction\": 0.6518518328666687,\n \"alphanum_fraction\": 0.6666666865348816,\n \"avg_line_length\": 26.200000762939453,\n \"blob_id\": \"66c20f34d98d555707ddc2725996014ffcd2b13b\",\n \"content_id\": \"650c521bbded45a6afd9bbd5a19ccae9f84ea023\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 135,\n \"license_type\": \"no_license\",\n \"max_line_length\": 52,\n \"num_lines\": 5,\n \"path\": \"/알고리즘/온라인저지/2022/05/0519/N과 M (2).py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from itertools import combinations\\n\\nN, M = map(int, input().split())\\nfor i in list(combinations(list(range(1, N+1)), M)):\\n print(*i)\"\n },\n {\n \"alpha_fraction\": 0.47044631838798523,\n \"alphanum_fraction\": 0.5054282546043396,\n \"avg_line_length\": 23.41176414489746,\n \"blob_id\": \"8b523ddc1783b78c958286e79de0230c4b6510d4\",\n \"content_id\": \"bbd064548cffe53384b53bfeb53d311ab709a496\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 899,\n \"license_type\": \"no_license\",\n \"max_line_length\": 63,\n \"num_lines\": 34,\n \"path\": \"/알고리즘/온라인저지/2022/10/1002/아기 상어 2.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\nfrom collections import deque\\n\\ninput = sys.stdin.readline\\ndy = [-1, -1, 0, 1, 1, 1, 0, -1] # 12시부터 시계방향\\ndx = [0, 1, 1, 1, 0, -1, -1, -1]\\n\\ndef BFS(i, j):\\n visited = [[0]*M for _ in [0]*N]\\n Q = deque()\\n Q.append((i, j, 0))\\n visited[i][j] = 1\\n while Q:\\n y, x, dist = Q.popleft()\\n if arr[y][x]: break\\n for k in range(8):\\n ny, nx = y+dy[k], x+dx[k]\\n if 0<=ny<N and 0<=nx<M and not visited[ny][nx]:\\n Q.append((ny, nx, dist+1))\\n visited[ny][nx] = 1\\n return dist\\n\\nN, M = map(int, input().rstrip().split())\\narr = [list(map(int, input().rstrip().split())) for _ in [0]*N]\\nresult = 0\\nfor i in range(N):\\n for j in range(M):\\n result = max(result,BFS(i, j))\\nprint(result)\\n\\n\\\"\\\"\\\"\\n매 좌표마다 상어안전거리를 구한다 : brute force\\n새 최소값을 매 회마다 갱신한다\\n\\\"\\\"\\\"\"\n },\n {\n \"alpha_fraction\": 0.5189873576164246,\n \"alphanum_fraction\": 0.5189873576164246,\n \"avg_line_length\": 14.699999809265137,\n \"blob_id\": \"b45794a29d8491747869683fe07a39901b7df620\",\n \"content_id\": \"5f16ec828277d86c002c39a058a0fe9777be760d\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 158,\n \"license_type\": \"no_license\",\n \"max_line_length\": 43,\n \"num_lines\": 10,\n \"path\": \"/알고리즘/SWEA/LEARN/Course/1. Programming Beginner/파이썬 프로그래밍 기초(2)/30차시 3. 자료구조 – 셋, 딕셔너리 - 연습문제 5.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"fruit = [' apple ','banana',' melon']\\n\\nresult = {}\\n\\nfor f in fruit:\\n f = f.lstrip()\\n f = f.rstrip()\\n result.update({f:len(f)})\\n\\nprint(result)\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.45185184478759766,\n \"alphanum_fraction\": 0.5333333611488342,\n \"avg_line_length\": 18.428571701049805,\n \"blob_id\": \"cf5456cd9601d3bbe7ef8c4de2188bb85be45dbb\",\n \"content_id\": \"cf1126879f42b55b445e9acb94e00230a7ba17e9\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 135,\n \"license_type\": \"no_license\",\n \"max_line_length\": 35,\n \"num_lines\": 7,\n \"path\": \"/알고리즘/온라인저지/2022/08/0810/Site Score.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"S = list(map(int, input().split()))\\nC = [56, 24, 14, 6]\\nresult = 0\\nfor i in range(4):\\n result += S[i]*C[i]\\n S *= 10\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.6004140973091125,\n \"alphanum_fraction\": 0.6169772148132324,\n \"avg_line_length\": 24.473684310913086,\n \"blob_id\": \"5656ccc00fce2f2d2bff3e570a2e7087b77e4290\",\n \"content_id\": \"d6f844d98a7725b20bf052bfb1cba640cd15a191\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 483,\n \"license_type\": \"no_license\",\n \"max_line_length\": 69,\n \"num_lines\": 19,\n \"path\": \"/알고리즘/온라인저지/2022/10/1022/종이자르기.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\n\\nW, H = map(int, input().rstrip().split())\\nrows, cols = [0, H], [0, W]\\nN = int(input().rstrip())\\nfor n in range(N):\\n D, C = map(int, input().rstrip().split()) # direction, coordinate\\n if D: cols.append(C)\\n else: rows.append(C)\\nrows.sort()\\ncols.sort()\\nwidth, height = 0, 0\\nfor i in range(len(rows)-1):\\n width = max(width, rows[i+1]-rows[i])\\nfor i in range(len(cols)-1):\\n height = max(height, cols[i+1]-cols[i])\\nprint(width*height)\"\n },\n {\n \"alpha_fraction\": 0.5625,\n \"alphanum_fraction\": 0.581250011920929,\n \"avg_line_length\": 19.125,\n \"blob_id\": \"05fe42c5321e844645939c10c3d87bbc0b1dd8a6\",\n \"content_id\": \"d13cf8ae43341a7312cf700471c38dfb598f5a6f\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 160,\n \"license_type\": \"no_license\",\n \"max_line_length\": 55,\n \"num_lines\": 8,\n \"path\": \"/알고리즘/온라인저지/2022/07/0715/탄산 음료.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"E, F, C = map(int, input().split()) # empty find change\\nresult = 0\\nbottle = E+F\\nwhile bottle >= C:\\n result += 1\\n bottle -= C\\n bottle += 1\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.26377952098846436,\n \"alphanum_fraction\": 0.29527559876441956,\n \"avg_line_length\": 14,\n \"blob_id\": \"b9fbb6d961f9a2d9566498a3a58185aa1aa149dc\",\n \"content_id\": \"bcb9f4f102d2c3429c11f5b93084a331d9e7bbee\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 254,\n \"license_type\": \"no_license\",\n \"max_line_length\": 35,\n \"num_lines\": 17,\n \"path\": \"/알고리즘/온라인저지/2023/02/0225/명장 남정훈.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"L, R, A = map(int, input().split())\\n\\nwhile A:\\n if L > R:\\n R += 1\\n A -= 1\\n elif L < R:\\n L += 1\\n A -= 1\\n else:\\n if A == 1:\\n break\\n else:\\n L += 1\\n A -= 1\\n\\nprint(min(L, R)*2)\"\n },\n {\n \"alpha_fraction\": 0.43617022037506104,\n \"alphanum_fraction\": 0.46072012186050415,\n \"avg_line_length\": 21.236364364624023,\n \"blob_id\": \"135b4507d32569caa05fc9bb53520c10d28bf6ef\",\n \"content_id\": \"f28a68652aab3e2f182025ee2b961333d9c9e5ee\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1232,\n \"license_type\": \"no_license\",\n \"max_line_length\": 61,\n \"num_lines\": 55,\n \"path\": \"/알고리즘/SWEA/LEARN/Course/2. Programming Intermediate/5. 파이썬 SW문제해결 기본 Stack2/7차시 5일차 - 배열 최소 합.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"def dfs(N, depth, tmp):\\n global result\\n if N == depth :\\n if tmp < result:\\n result = tmp\\n \\n if tmp > result:\\n return\\n else:\\n for i in range(N):\\n if visited[i] == 0:\\n visited[i] = 1\\n dfs(N, depth+1, tmp+arr[depth][i])\\n visited[i] = 0\\n \\nT = int(input())\\nfor t in range(1, T+1):\\n N = int(input())\\n arr = [list(map(int, input().split())) for _ in range(N)]\\n visited = [0]*N\\n \\n depth = 0\\n result = 10*N\\n \\n dfs(N, 0, 0)\\n print('#{} {}'.format(t, result))\\n\\n\\n\\\"\\\"\\\"\\n2022-09-01에 다시 풀음\\ndef dfs(level):\\n global result, tmp\\n if level == N:\\n result = min(result, tmp)\\n return\\n if tmp > result: return\\n for i in range(N): \\n # print(level, i, arr[level][i])\\n if not visited[i]:\\n tmp += arr[level][i]\\n visited[i] = 1\\n dfs(level+1)\\n tmp -= arr[level][i]\\n visited[i] = 0\\n\\nfor t in range(1, int(input())+1):\\n N = int(input())\\n arr = [list(map(int, input().split())) for _ in range(N)]\\n # for a in arr: print(a)\\n visited = [0] * N\\n result = int(1e9)\\n tmp = 0\\n dfs(0)\\n print('#{} {}'.format(t, result))\\n\\\"\\\"\\\"\"\n },\n {\n \"alpha_fraction\": 0.5841270089149475,\n \"alphanum_fraction\": 0.5841270089149475,\n \"avg_line_length\": 23.30769157409668,\n \"blob_id\": \"d2e751895220c69fd8d09932b02e41aa6a698747\",\n \"content_id\": \"3bc76cdbe11369b994895155ce9069d4bf493cf6\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 315,\n \"license_type\": \"no_license\",\n \"max_line_length\": 40,\n \"num_lines\": 13,\n \"path\": \"/알고리즘/온라인저지/2022/07/0729/대칭 차집합.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"A, B = map(int, input().split())\\nA_list = list(map(int, input().split()))\\nA_set = set(A_list)\\nB_list = list(map(int, input().split()))\\nB_set = set(B_list)\\nresult = []\\nfor a in A_list:\\n if a not in B_set:\\n result.append(a)\\nfor b in B_list:\\n if b not in A_set:\\n result.append(b)\\nprint(len(result))\"\n },\n {\n \"alpha_fraction\": 0.351005494594574,\n \"alphanum_fraction\": 0.35283362865448,\n \"avg_line_length\": 19.884614944458008,\n \"blob_id\": \"5389ecc35c91ed4ac9ec61061dd4c17202329c9e\",\n \"content_id\": \"771d947536fe3653be95cb1c2e671bd9ffe471d4\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 579,\n \"license_type\": \"no_license\",\n \"max_line_length\": 60,\n \"num_lines\": 26,\n \"path\": \"/알고리즘/온라인저지/2021/09/0905/균형잡힌 세상.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"bracket = {\\n ')': '(',\\n '}': '{',\\n ']': '[',\\n}\\n\\nwhile True:\\n sen = input() # sys.stdin.readline() 쓰니까 종료조건을 회피하지 못하더라\\n if sen == '.':\\n break\\n stack = []\\n for s in sen:\\n if s in '[{(':\\n stack.append(s)\\n elif s in ')}]':\\n if stack:\\n if bracket[s] == stack[-1]:\\n stack.pop()\\n else:\\n stack.append(s)\\n else:\\n stack.append(s)\\n if stack:\\n print('no')\\n else:\\n print('yes')\\n \"\n },\n {\n \"alpha_fraction\": 0.5792349576950073,\n \"alphanum_fraction\": 0.5846994519233704,\n \"avg_line_length\": 15.727272987365723,\n \"blob_id\": \"9efababed0f87f34dd080672c7febe1e107d3a36\",\n \"content_id\": \"13e8c2b663b2a740a5e7cb509832fb6c73f58bea\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 183,\n \"license_type\": \"no_license\",\n \"max_line_length\": 43,\n \"num_lines\": 11,\n \"path\": \"/알고리즘/온라인저지/2022/07/0726/귀찮음.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\n\\nN = int(input())\\nP = sorted(list(map(int, input().split())))\\nresult, S = 0, sum(P)\\nfor p in P:\\n result += p * (S-p)\\n S -= p\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.2741433084011078,\n \"alphanum_fraction\": 0.30841121077537537,\n \"avg_line_length\": 12.391304016113281,\n \"blob_id\": \"d718d4c5ed37facaaf6461d05c82f8a03b6cf98c\",\n \"content_id\": \"2be348ccedfd89cfd99a5809b796d43203f42a81\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 321,\n \"license_type\": \"no_license\",\n \"max_line_length\": 36,\n \"num_lines\": 23,\n \"path\": \"/알고리즘/온라인저지/2022/02/0201/하얀 칸.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"i = 1\\n\\nresult = 0\\n\\nfor _ in range(8):\\n line = input()\\n\\n j = 1\\n\\n for l in line:\\n if i%2:\\n if j%2 and l == 'F':\\n result += 1\\n \\n else:\\n if not j%2 and l == 'F':\\n result += 1\\n \\n j += 1\\n \\n i += 1\\n\\nprint(result)\\n \\n \"\n },\n {\n \"alpha_fraction\": 0.2732732594013214,\n \"alphanum_fraction\": 0.39039039611816406,\n \"avg_line_length\": 10.066666603088379,\n \"blob_id\": \"28b268a28a1f446198d2c7d004f2585000a6f4b4\",\n \"content_id\": \"a09525f598db7b1c4733143cafd2b84781204e9e\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 333,\n \"license_type\": \"no_license\",\n \"max_line_length\": 33,\n \"num_lines\": 30,\n \"path\": \"/알고리즘/온라인저지/2022/01/0104/2×n 타일링 2.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = int(input())\\n\\ndp = [0 for _ in range(N+1)]\\n\\ndp[1] = 1\\nif N >= 2:\\n dp[2] = 3\\n if N == 2:\\n print(dp[2])\\n exit()\\nif N >= 3:\\n dp[3] = 5\\n if N == 3:\\n print(dp[3])\\n exit()\\n\\nfor i in range(4, N+1):\\n dp[i] = dp[i-1] + dp[i-2] * 2\\n\\nprint(dp[N]%10007)\\n\\n# 0\\n# 1\\n# 3\\n# 5\\n# 11\\n# 21\\n# 43\\n# 85\\n# 171\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.4626334607601166,\n \"alphanum_fraction\": 0.4839857518672943,\n \"avg_line_length\": 12.428571701049805,\n \"blob_id\": \"f3b5808de2af6f929c3bb35a87784d8e27b38b35\",\n \"content_id\": \"ac388b59e6cb072b16fa3274a9263c384a9ca452\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 281,\n \"license_type\": \"no_license\",\n \"max_line_length\": 26,\n \"num_lines\": 21,\n \"path\": \"/알고리즘/온라인저지/2022/10/1012/수 이어 쓰기 1.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\n\\nN = int(input().rstrip())\\nD = 9\\nsep = []\\nwhile True:\\n if N >= D:\\n sep.append(D)\\n N -= D\\n D *= 10\\n else:\\n sep.append(N)\\n break\\nresult = 0\\ni = 1\\nfor s in sep: \\n result += i*s\\n i += 1\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.3025210201740265,\n \"alphanum_fraction\": 0.3235294222831726,\n \"avg_line_length\": 25.44444465637207,\n \"blob_id\": \"e6277b30e4fc7e8a35d8a080d1cf51687447a491\",\n \"content_id\": \"99da6e60f7674adbd4da1fb615eb23342721dc6d\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 952,\n \"license_type\": \"no_license\",\n \"max_line_length\": 42,\n \"num_lines\": 36,\n \"path\": \"/알고리즘/온라인저지/2021/09/0908/프린터 큐.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\ndef input():\\n return sys.stdin.readline()\\n\\nT = int(input())\\nfor t in range(T):\\n N, M = map(int, input().split())\\n docs = list(map(int, input().split()))\\n cnt = 0\\n end = True\\n while end:\\n if docs[M] != max(docs):\\n if docs[0] != max(docs):\\n docs.append(docs.pop(0))\\n M -= 1\\n if M < 0:\\n M += N\\n else: # docs[0] == max(docs)\\n docs.pop(0)\\n cnt += 1\\n N -= 1\\n M -= 1 \\n else: # docs[M] == max(docs)\\n if M != 0:\\n if docs[0] == docs[M]:\\n docs.pop(0)\\n cnt += 1\\n M -= 1\\n else: # docs[0] != docs[M]\\n docs.pop(0)\\n M -= 1\\n else: # M == 0\\n cnt += 1\\n end = False\\n break\\n print(cnt)\\n\"\n },\n {\n \"alpha_fraction\": 0.5416666865348816,\n \"alphanum_fraction\": 0.5572916865348816,\n \"avg_line_length\": 18.299999237060547,\n \"blob_id\": \"8c8bb12f2f8e8519e155f6d3d494ca0c2d372173\",\n \"content_id\": \"2c31c9c5b85a016342bb921fd52c8ac9a54f0878\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 192,\n \"license_type\": \"no_license\",\n \"max_line_length\": 32,\n \"num_lines\": 10,\n \"path\": \"/알고리즘/온라인저지/2021/08/0802/쉽게 푸는 문제.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"A, B = map(int, input().split())\\nnumbers = []\\nfor i in range(1, B+2):\\n for j in range(i):\\n numbers.append(i)\\nls = []\\nfor i in range(A-1, B):\\n ls.append(numbers[i])\\n\\nprint(sum(ls))\"\n },\n {\n \"alpha_fraction\": 0.4839743673801422,\n \"alphanum_fraction\": 0.5256410241127014,\n \"avg_line_length\": 21.35714340209961,\n \"blob_id\": \"5de89e8473a4126b47d44360cbf370b1e4cb0d5d\",\n \"content_id\": \"1b00554f47b389f94b22363138a3d9f46d17b8da\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 312,\n \"license_type\": \"no_license\",\n \"max_line_length\": 62,\n \"num_lines\": 14,\n \"path\": \"/알고리즘/온라인저지/2022/11/1118/좋은 자동차 번호판.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\n\\nfor _ in range(int(input().rstrip())):\\n number = input().rstrip()\\n front = number[:3]\\n rear = number[4:]\\n tmp = 0\\n j = 0\\n for f in front[::-1]:\\n tmp += 26**j*(ord(f)-65)\\n j += 1\\n print('nice' if abs(tmp-int(rear)) <= 100 else 'not nice')\"\n },\n {\n \"alpha_fraction\": 0.5081967115402222,\n \"alphanum_fraction\": 0.5245901346206665,\n \"avg_line_length\": 30,\n \"blob_id\": \"4d41bf1041cea1f4c1830ea1eaed491db541b828\",\n \"content_id\": \"21b62b699e0561e07bc396aa1ee332473d61fea4\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 61,\n \"license_type\": \"no_license\",\n \"max_line_length\": 35,\n \"num_lines\": 2,\n \"path\": \"/알고리즘/온라인저지/2023/02/0209/WARBOY.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"A, B, C = map(int, input().split())\\nprint(eval('C*3*(B//A)'))\"\n },\n {\n \"alpha_fraction\": 0.4615384638309479,\n \"alphanum_fraction\": 0.4615384638309479,\n \"avg_line_length\": 18.5625,\n \"blob_id\": \"804c5a2af7ddb14784ae35df2162fbde344d4f2a\",\n \"content_id\": \"b85ad088ea9778ee02ebfa8a8bd7c9a540aaa38e\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 312,\n \"license_type\": \"no_license\",\n \"max_line_length\": 49,\n \"num_lines\": 16,\n \"path\": \"/알고리즘/온라인저지/2022/10/1027/치킨 쿠폰.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\n\\nwhile True:\\n try:\\n N, K = map(int, input().rstrip().split())\\n result = N\\n stamp = N\\n while stamp>=K:\\n tmp = stamp//K\\n stamp %= K\\n result += tmp\\n stamp += tmp\\n print(result)\\n except: break\"\n },\n {\n \"alpha_fraction\": 0.4871794879436493,\n \"alphanum_fraction\": 0.5192307829856873,\n \"avg_line_length\": 25.16666603088379,\n \"blob_id\": \"b37c146e11723be6e0547c43baacd05f7da73177\",\n \"content_id\": \"a160a2216c7f4b8e5ed99aa6aba4bdb89d40a49f\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 156,\n \"license_type\": \"no_license\",\n \"max_line_length\": 44,\n \"num_lines\": 6,\n \"path\": \"/알고리즘/온라인저지/2023/01/0120/삼각수의 합.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"for _ in range(int(input())):\\n N = int(input())\\n result = 0\\n for k in range(1, N+1):\\n result += k*sum(list(range(1, k+2)))\\n print(result)\"\n },\n {\n \"alpha_fraction\": 0.46612149477005005,\n \"alphanum_fraction\": 0.4754672944545746,\n \"avg_line_length\": 21.526315689086914,\n \"blob_id\": \"8b484550b4bfef6ee0be15cd610492e0fd364835\",\n \"content_id\": \"e05db2367aa6e0630341b096c10e0841c870863f\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 856,\n \"license_type\": \"no_license\",\n \"max_line_length\": 54,\n \"num_lines\": 38,\n \"path\": \"/알고리즘/온라인저지/2022/07/0703/test.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"def dfs(start):\\n global is_dfs, result, visited\\n print(start)\\n if start == 1:\\n for j in arr[1]:\\n result = []\\n visited = [True] + [False] * N \\n visited[start] = True\\n result.append(start)\\n dfs(j)\\n tmp.append(result)\\n if result == answer:\\n is_dfs = True\\n else:\\n visited[start] = True\\n result.append(start)\\n for i in arr[start]:\\n if not visited[i]:\\n dfs(i)\\n\\nN = int(input())\\narr = [[] for _ in range(N+1)]\\nfor n in range(N-1):\\n s, e = map(int, input().split())\\n arr[s].append(e)\\n arr[e].append(s)\\nanswer = list(map(int, input().split()))[::-1]\\nis_dfs = False\\nresult = []\\ntmp = []\\nvisited = [True] + [False] * N\\ntmp = []\\ndfs(1)\\nprint(tmp)\\nif is_dfs:\\n print(1)\\nelse:\\n print(0)\\n\"\n },\n {\n \"alpha_fraction\": 0.42702701687812805,\n \"alphanum_fraction\": 0.5027027130126953,\n \"avg_line_length\": 25.5,\n \"blob_id\": \"e78d2f4475de576407e092e2eb17a8937ace5594\",\n \"content_id\": \"ba43116ef0143428dc9417eb823c109973c2c845\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 398,\n \"license_type\": \"no_license\",\n \"max_line_length\": 55,\n \"num_lines\": 14,\n \"path\": \"/알고리즘/[템플릿]/Dynamic Programming/계단 오르기.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = int(input())\\nS = [0 for _ in range(301)] # stairs \\ndp = [0 for _ in range(301)] # 미리 선언하여 N<=3 일 때 에러를 방지함\\nfor i in range(N): S[i] = int(input())\\ndp[0] = S[0]\\ndp[1] = S[0] + S[1]\\ndp[2] = max(S[1]+S[2], S[0]+S[2])\\nfor i in range(3, N):\\n A = dp[i-3] + S[i-1] + S[i]\\n B = dp[i-2] + S[i]\\n dp[i] = max(A, B)\\nprint(dp[N-1])\\n\\n# https://www.acmicpc.net/problem/2579\"\n },\n {\n \"alpha_fraction\": 0.5869565010070801,\n \"alphanum_fraction\": 0.602173924446106,\n \"avg_line_length\": 34.46154022216797,\n \"blob_id\": \"4c972b8f9953bfd2311707560877b896010ea685\",\n \"content_id\": \"a2f31c245bdf2da6cdcd9e44b2fd5050b884b2ac\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 644,\n \"license_type\": \"no_license\",\n \"max_line_length\": 81,\n \"num_lines\": 13,\n \"path\": \"/알고리즘/온라인저지/2022/09/0927/부분수열의 합.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\n\\nN, S = map(int, input().rstrip().split())\\narr = list(map(int, input().rstrip().split()))\\nresult = 0\\nfor i in range(1<<N): # N개의 원소를 포함한다, 안한다의 경우가 있으므로 총 경우의 수는 1<<N == 2**N\\n seq = [] # 부분수열 초기화\\n for j in range(N): # N개 원소들에 대하여 부분수열인지 확인\\n if i&(1<<j): seq.append(arr[j]) # &연산을 거친 값이 True라면, j번째 원소는 부분수열에 존재한다\\n if sum(seq) == S and len(seq) != 0: result += 1 # 공집합이 아니면서, 부분수열의 합이 S이면 카운트\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.5051020383834839,\n \"alphanum_fraction\": 0.5204081535339355,\n \"avg_line_length\": 18.700000762939453,\n \"blob_id\": \"f76fbaf731e5ac896de99dda409f31b888404c9d\",\n \"content_id\": \"6f9133bc61c9b364a942f2cee06ce58e9b7f7316\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 196,\n \"license_type\": \"no_license\",\n \"max_line_length\": 37,\n \"num_lines\": 10,\n \"path\": \"/알고리즘/온라인저지/2022/05/0529/수빈이와 수열.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = int(input())\\narr = list(map(int, input().split()))\\n# print(arr)\\nfor i in range(N):\\n arr[i] *= i+1\\n# print(arr)\\nif N > 0:\\n for i in range(1, N):\\n arr[i] -= sum(arr[:i])\\nprint(*arr)\"\n },\n {\n \"alpha_fraction\": 0.40740740299224854,\n \"alphanum_fraction\": 0.4444444477558136,\n \"avg_line_length\": 15.399999618530273,\n \"blob_id\": \"5a94c070f0c057635141a9fe7471796e9f0cfc09\",\n \"content_id\": \"78ad9fb612b4e9fbc22373d6439d9cbb5a1b918c\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 81,\n \"license_type\": \"no_license\",\n \"max_line_length\": 23,\n \"num_lines\": 5,\n \"path\": \"/알고리즘/온라인저지/2023/05/0524/Gömda ord.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"S = input()\\ni = 0\\nwhile i < len(S):\\n print(S[i], end='')\\n i += ord(S[i])-64\"\n },\n {\n \"alpha_fraction\": 0.5045045018196106,\n \"alphanum_fraction\": 0.522522509098053,\n \"avg_line_length\": 22.421052932739258,\n \"blob_id\": \"9c7da66eaba53648b2d64ff39456a63d652c048d\",\n \"content_id\": \"6a50bcfce6adc29477389f9d66068a14f5f01a10\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 772,\n \"license_type\": \"no_license\",\n \"max_line_length\": 38,\n \"num_lines\": 19,\n \"path\": \"/알고리즘/온라인저지/2021/10/1003/무한이진트리.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"a, b = map(int, input().split()) # 끝노드\\n\\n# 시작노드에서 왼쪽으로 내려가면 a가 커지고\\n# 오른쪽으로 내려가면 b가 커진다\\n# 주어진 (a, b)노드에서 a가 크면 왼쪽으로 내려온 노드\\n# b가 크면 오른쪽으로 내려온 노드임을 알 수 있다\\n# 이를 이용해 (a, b)에서 (1, 1)까지 거꾸로 올라간다\\n\\nl = r = 0 # 올라가면서 체크할 왼쪽 오른쪽 이동 횟수\\n\\nwhile a+b != 2: # 루트노드에 도달할 때 까지\\n if a > b: # 왼쪽으로 내려왔던 노드이면\\n a -= b # 부모노드의 a\\n l += 1 # 왼쪽 카운트 +1\\n elif a < b: # 오른쪽으로 내려왔던 노드이면\\n b -= a # 부모노드의 b\\n r += 1 # 오른쪽 카운트 +1\\n\\nprint(l, r) # 출력\"\n },\n {\n \"alpha_fraction\": 0.4974271059036255,\n \"alphanum_fraction\": 0.5403087735176086,\n \"avg_line_length\": 21.461538314819336,\n \"blob_id\": \"bedab36d73699ed8a4f33bfa5a3f553ee83f9267\",\n \"content_id\": \"7926594e4824120282c82228fc2019c639ea6429\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 583,\n \"license_type\": \"no_license\",\n \"max_line_length\": 64,\n \"num_lines\": 26,\n \"path\": \"/알고리즘/온라인저지/2023/01/0114/숨바꼭질 3.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from heapq import heappush, heappop\\n\\nN, K = map(int, input().split())\\nQ = [(0, N)]\\nvisited = [int(1e9)]*(int(1e6)+1)\\nvisited[N] = 0\\nwhile Q:\\n time, now = heappop(Q)\\n go, back, jump = max(0, now+1), max(0, now-1), max(0, now*2)\\n\\n if now == K:\\n break\\n\\n if visited[go] > time+1:\\n visited[go] = time+1\\n heappush(Q, (time+1, go))\\n\\n if visited[back] > time+1:\\n visited[back] = time+1\\n heappush(Q, (time+1, back))\\n \\n if visited[jump] > time and jump<=100000:\\n visited[jump] = time\\n heappush(Q, (time, jump))\\n\\nprint(time)\"\n },\n {\n \"alpha_fraction\": 0.5367646813392639,\n \"alphanum_fraction\": 0.5808823704719543,\n \"avg_line_length\": 16.125,\n \"blob_id\": \"ede47a184c3cbccd5c80ea47ac04168bf8199a75\",\n \"content_id\": \"858755e24bc6dd0c7f896c18205492fdced4985b\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 136,\n \"license_type\": \"no_license\",\n \"max_line_length\": 20,\n \"num_lines\": 8,\n \"path\": \"/알고리즘/온라인저지/2023/04/0426/Covid-19.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"result = 'Yellow'\\np = int(input())\\nq = int(input())\\nif p<=50 and q<=10:\\n result = 'White'\\nelif q>30:\\n result = 'Red'\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.5107526779174805,\n \"alphanum_fraction\": 0.5215053558349609,\n \"avg_line_length\": 14.583333015441895,\n \"blob_id\": \"9749ff6e6df404d7c8b48fafdccb0472ec503475\",\n \"content_id\": \"b35f547d9ff358abe44a928562996fae89c27d8c\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 186,\n \"license_type\": \"no_license\",\n \"max_line_length\": 27,\n \"num_lines\": 12,\n \"path\": \"/알고리즘/온라인저지/2023/05/0507/골뱅이 찍기 - 돌아간 ㅍ.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"def new_print(line):\\n for _ in range(N):\\n print(line)\\n\\nN = int(input())\\nA = '@'*N + ' '*3*N + '@'*N\\nB = '@'*N*5\\nnew_print(A)\\nnew_print(B)\\nnew_print(A)\\nnew_print(B)\\nnew_print(A)\"\n },\n {\n \"alpha_fraction\": 0.5596330165863037,\n \"alphanum_fraction\": 0.5688073635101318,\n \"avg_line_length\": 21,\n \"blob_id\": \"765e3806800e17b0909bb65c1b6eca9444ce7c29\",\n \"content_id\": \"1035a17b589c42898a8c2cbf2a59d52cb92ba224\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 109,\n \"license_type\": \"no_license\",\n \"max_line_length\": 36,\n \"num_lines\": 5,\n \"path\": \"/알고리즘/온라인저지/2023/01/0119/謎紛芥索紀 (Small).py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"result = 0\\nfor _ in range(int(input())):\\n A, B = map(int, input().split())\\n result += A*B\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.5743243098258972,\n \"alphanum_fraction\": 0.587837815284729,\n \"avg_line_length\": 20.285715103149414,\n \"blob_id\": \"a99af847b7922f62c9249d6d80edcb7394500c44\",\n \"content_id\": \"a0abe24cfcd058f9b0b5871ea2d6423e9b665239\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 148,\n \"license_type\": \"no_license\",\n \"max_line_length\": 45,\n \"num_lines\": 7,\n \"path\": \"/알고리즘/온라인저지/2022/11/1122/쿠키애호가.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\n\\nfor _ in range(int(input().rstrip())):\\n N, C = map(int, input().rstrip().split())\\n print((N-1)//C + 1)\"\n },\n {\n \"alpha_fraction\": 0.48322147130966187,\n \"alphanum_fraction\": 0.4899328947067261,\n \"avg_line_length\": 15.666666984558105,\n \"blob_id\": \"394b3f5a09da0c587816dbd81dc3ce587daa1042\",\n \"content_id\": \"7a596ad3b0f8be6f14db10cf3ea4c19c139a95e0\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 149,\n \"license_type\": \"no_license\",\n \"max_line_length\": 31,\n \"num_lines\": 9,\n \"path\": \"/알고리즘/온라인저지/2023/03/0325/골뱅이 찍기 - 정사각형.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = int(input())\\narr = []\\nA, B = '@'*(N+2), '@'+' '*N+'@'\\narr.append(A)\\nfor _ in range(N):\\n arr.append(B)\\narr.append(A)\\nfor a in arr:\\n print(a)\"\n },\n {\n \"alpha_fraction\": 0.40514469146728516,\n \"alphanum_fraction\": 0.4244372844696045,\n \"avg_line_length\": 25,\n \"blob_id\": \"6bcab918b29c0cc0e41a1d49dadc74d74a0dd5e6\",\n \"content_id\": \"65a60d7271a1e37d14e7e5db89002243889bb697\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 311,\n \"license_type\": \"no_license\",\n \"max_line_length\": 38,\n \"num_lines\": 12,\n \"path\": \"/알고리즘/온라인저지/2022/03/0329/J박스.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"T = int(input())\\nfor t in range(T):\\n N = int(input())\\n jbox = [['J']*N for _ in range(N)]\\n jbox[0] = jbox[-1] = ['#']*N\\n for i in range(1, N-1):\\n jbox[i][0] = jbox[i][-1] = '#'\\n for i in range(N):\\n for j in range(N):\\n print(jbox[i][j], end='')\\n print()\\n print()\"\n },\n {\n \"alpha_fraction\": 0.5210526585578918,\n \"alphanum_fraction\": 0.5368421077728271,\n \"avg_line_length\": 26.285715103149414,\n \"blob_id\": \"975d2257e76aac02f51262c9e04c0fd238284d5a\",\n \"content_id\": \"bbb0abd27461e4642ac3edaf54a0ba37c8b6b992\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 190,\n \"license_type\": \"no_license\",\n \"max_line_length\": 45,\n \"num_lines\": 7,\n \"path\": \"/알고리즘/온라인저지/2022/08/0804/럭키 스트레이트.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = input()\\nM = len(N)//2 # middle\\nF, B = N[:M], N[M:] # front, back\\nF_int, B_int = 0, 0\\nfor f in F: F_int += int(f)\\nfor b in B: B_int += int(b)\\nprint('LUCKY' if F_int == B_int else 'READY')\"\n },\n {\n \"alpha_fraction\": 0.4161849617958069,\n \"alphanum_fraction\": 0.4393063485622406,\n \"avg_line_length\": 18.22222137451172,\n \"blob_id\": \"3c6f10a8c922f09d4c945d730531b48d43bbcff0\",\n \"content_id\": \"7329872dddc97da0a947eb7b74a0102a478f0c36\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 173,\n \"license_type\": \"no_license\",\n \"max_line_length\": 39,\n \"num_lines\": 9,\n \"path\": \"/알고리즘/온라인저지/2021/12/1230/트리 만들기.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"n, m = map(int, input().split())\\n\\nfor i in range(n-1):\\n if i >= n-m+1:\\n print('{} {}'.format(n-m, i+1))\\n continue\\n \\n print(i, end=' ')\\n print(i+1)\\n\"\n },\n {\n \"alpha_fraction\": 0.5315126180648804,\n \"alphanum_fraction\": 0.5441176295280457,\n \"avg_line_length\": 20.68181800842285,\n \"blob_id\": \"cb2b0db2bcba2a91c20932ce159717a4ca3f8fd2\",\n \"content_id\": \"552a0da153073f5a618b9bffd161f5cf864f87c2\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 740,\n \"license_type\": \"no_license\",\n \"max_line_length\": 57,\n \"num_lines\": 22,\n \"path\": \"/알고리즘/온라인저지/2021/08/0807/링.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"\\\"\\\"\\\"\\n8 4 2의 지름이 각각 같아야한다\\n파이를 생략하고\\n반지름 각각 A, B, C, ...\\n각각의 바퀴수는 A / B\\n이 바퀴수를 기약분수형태로 출력\\nA/B A/C ... \\n테스트케이스 개수 T\\n\\\"\\\"\\\"\\n\\nT = int(input()) # 테스트케이스 개수, 쓰지는 않았다\\nrs = list(map(int, input().split())) # 반지름 들 입력받아서 list()\\n\\ndef gcd(x, y): # 최대공약수 구하는 함수, 유클리드 호제법\\n while y:\\n x, y = y, x % y\\n return x\\n\\nfor i in range(1, len(rs)): # 첫 링 제외하고 링의 반지름들 순회\\n gcd_rs = gcd(rs[0], rs[i]) # 반지름들의 최대공약수 구해서\\n print(f'{rs[0] // gcd_rs}/{rs[i] // gcd_rs}')\\n # 각 링들을 기약분수 형태로 출력\"\n },\n {\n \"alpha_fraction\": 0.5203620195388794,\n \"alphanum_fraction\": 0.5429864525794983,\n \"avg_line_length\": 21.200000762939453,\n \"blob_id\": \"fc1819857a0d41e83a146329b48f7cf1fc8bab9c\",\n \"content_id\": \"31e3a71f061e51cb5d8d5704cbfb31775dc2a5c8\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 221,\n \"license_type\": \"no_license\",\n \"max_line_length\": 36,\n \"num_lines\": 10,\n \"path\": \"/알고리즘/온라인저지/2021/08/0816/카드1.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = int(input())\\ndeck = list(range(1, N+1))\\nnew_deck = []\\nfor n in range(N):\\n if len(deck) == 1:\\n new_deck += deck\\n else:\\n new_deck.append(deck.pop(0))\\n deck.append(deck.pop(0))\\nprint(*new_deck)\"\n },\n {\n \"alpha_fraction\": 0.5535714030265808,\n \"alphanum_fraction\": 0.5714285969734192,\n \"avg_line_length\": 15.142857551574707,\n \"blob_id\": \"c730d281ddd10286cc81c5aa565e29fc1656cbda\",\n \"content_id\": \"91dcb474f695881ba0a3aae1cfba440e2a6430d6\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 112,\n \"license_type\": \"no_license\",\n \"max_line_length\": 22,\n \"num_lines\": 7,\n \"path\": \"/알고리즘/온라인저지/2022/03/0319/팬들에게 둘러싸인 홍준.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"name = ':'+input()+':'\\nfan = ':fan:'\\nprint(fan*3)\\nprint(fan, end='')\\nprint(name, end='')\\nprint(fan)\\nprint(fan*3)\"\n },\n {\n \"alpha_fraction\": 0.4375655949115753,\n \"alphanum_fraction\": 0.45802727341651917,\n \"avg_line_length\": 25.48611068725586,\n \"blob_id\": \"3f84f5f0c5f621805d16cb3efff7205baacf45d8\",\n \"content_id\": \"00f01995da28c777ccd05aedbbcf18d578b49c7d\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 2014,\n \"license_type\": \"no_license\",\n \"max_line_length\": 67,\n \"num_lines\": 72,\n \"path\": \"/알고리즘/SW역량테스트/2022.03.15 A형.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"\\\"\\\"\\\"\\n어딜 갈 수 있는가\\n잡기 전\\n1 2 3\\n1을 잡은 후\\n2 3 -1\\n3을 잡은 후\\n2 -1 -3\\n\\ndfs돌 필요도 없다 좌표찾고 더하기빼기로도 가능\\n\\n가지고 있는 최소값보다 커지면 가지치기\\n\\\"\\\"\\\"\\nimport tabnanny\\n\\n\\ndef dfs(c, y, x, h, can_go):\\n global monster_visited, customer_visited, minn\\n # print(c)\\n for mnc in monsters_and_customers:\\n if mnc[0] == c:\\n h += abs(y-mnc[1]) + abs(x-mnc[2])\\n if h > minn:\\n continue\\n y = mnc[1]\\n x = mnc[2]\\n if c > 0:\\n can_go.append((can_go.pop(can_go.index(c)) * (-1)))\\n elif c < 0:\\n can_go.pop(can_go.index(c))\\n if not can_go:\\n if h < minn:\\n minn = h\\n # print('renew minn!!', minn)\\n\\n # print(can_go)\\n for g in can_go:\\n if g > 0:\\n if not monster_visited[g-1]:\\n dfs(g, y, x, h, can_go)\\n elif g < 0:\\n if not customer_visited[g*(-1)-1]:\\n dfs(g, y, x, h, can_go)\\n\\n\\nT = int(input())\\nfor t in range(1, T+1):\\n N = int(input())\\n arr = []\\n how_many_customer = 0\\n for n in range(N):\\n tmp = list(map(int, input().split()))\\n if max(tmp) > how_many_customer:\\n how_many_customer = max(tmp)\\n arr.append(tmp)\\n # print(how_many_customer)\\n monsters_and_customers = []\\n for i in range(N):\\n for j in range(N):\\n if arr[i][j] != 0:\\n monsters_and_customers.append([arr[i][j], i, j])\\n # print(monsters_and_customers)\\n monsters = list(range(1, how_many_customer+1))\\n # print(monsters)\\n minn = 10**6\\n for m in monsters:\\n monster_visited = [0] * how_many_customer\\n customer_visited = [0] * how_many_customer\\n h = 0\\n x = y = 0 \\n dfs(m, y, x, h, list(range(1, how_many_customer+1)))\\n print('#{} {}'.format(t, minn))\"\n },\n {\n \"alpha_fraction\": 0.38434162735939026,\n \"alphanum_fraction\": 0.41281139850616455,\n \"avg_line_length\": 20.69230842590332,\n \"blob_id\": \"2d011cc0192baa79d0d1de7095a3565f76391c28\",\n \"content_id\": \"b39abe6774776d1188633ec7f584be2364f7a02e\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 281,\n \"license_type\": \"no_license\",\n \"max_line_length\": 37,\n \"num_lines\": 13,\n \"path\": \"/알고리즘/온라인저지/2022/09/0910/연속구간.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"for _ in range(3):\\n num = input()\\n prev = num[0]\\n tmp = 1\\n result = 1\\n for i in range(1, 8):\\n if prev == num[i]:\\n tmp += 1\\n else:\\n result = max(result, tmp)\\n tmp = 1\\n prev = num[i]\\n print(max(result, tmp))\"\n },\n {\n \"alpha_fraction\": 0.4141414165496826,\n \"alphanum_fraction\": 0.4343434274196625,\n \"avg_line_length\": 18.799999237060547,\n \"blob_id\": \"b8545d1dafbaa50490cdd27c8cfbba171dd5ca5f\",\n \"content_id\": \"389eca97a08bda5a29435854df943b3f5228aa71\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 99,\n \"license_type\": \"no_license\",\n \"max_line_length\": 37,\n \"num_lines\": 5,\n \"path\": \"/알고리즘/온라인저지/2022/02/0208/TV 크기.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"D, H, W = map(int, input().split())\\n\\nC = ((H*H)+(W*W))**0.5\\n\\nprint(int(D * H / C), int(D * W / C))\\n\"\n },\n {\n \"alpha_fraction\": 0.5050504803657532,\n \"alphanum_fraction\": 0.6363636255264282,\n \"avg_line_length\": 15.666666984558105,\n \"blob_id\": \"2851c4a56704245b21de115b2258d11a0c3aae10\",\n \"content_id\": \"95b18739a64a4fe55be542240351a8b1818eefc0\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 99,\n \"license_type\": \"no_license\",\n \"max_line_length\": 22,\n \"num_lines\": 6,\n \"path\": \"/알고리즘/온라인저지/2023/03/0316/Boiling Water.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"P = 5*int(input())-400\\nresult = 0\\nif P>100: result = -1\\nif P<100: result = 1\\nprint(P)\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.4259776473045349,\n \"alphanum_fraction\": 0.4427374303340912,\n \"avg_line_length\": 24.60714340209961,\n \"blob_id\": \"e4692880145dc3b5862b6b57c8397c286f77334c\",\n \"content_id\": \"fce679379195ee2938ec0367d9b12dd3facd697f\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 716,\n \"license_type\": \"no_license\",\n \"max_line_length\": 44,\n \"num_lines\": 28,\n \"path\": \"/알고리즘/온라인저지/2022/07/0714/체스판 다시 칠하기.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"def check_tile(y, x):\\n cnt = 0\\n switch = False # Black:True, White:False\\n for i in range(8):\\n for j in range(8):\\n tmp = arr[y+i][x+j]\\n switch = not switch\\n if j == 0:\\n switch = not switch\\n if switch: # Black\\n if tmp == 'W':\\n cnt += 1\\n elif not switch: # White\\n if tmp == 'B':\\n cnt += 1\\n result = min(cnt, 64-cnt)\\n return result\\n\\n\\nN, M = map(int, input().split())\\narr = [list(input()) for _ in range(N)]\\nresult = 1e9\\nfor i in range(N-7):\\n for j in range(M-7):\\n tmp = check_tile(i, j)\\n if tmp < result:\\n result = tmp\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.5263158082962036,\n \"alphanum_fraction\": 0.5263158082962036,\n \"avg_line_length\": 24.66666603088379,\n \"blob_id\": \"f6cf29c3b02ff99496ea4be6ca648a5e60fab672\",\n \"content_id\": \"9e3e11cf907e9a3b818f82fca56d840e13501d0a\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 76,\n \"license_type\": \"no_license\",\n \"max_line_length\": 29,\n \"num_lines\": 3,\n \"path\": \"/알고리즘/온라인저지/2023/02/0223/Time to Decompress.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"for _ in range(int(input())):\\n A, B = input().split()\\n print(B*int(A))\"\n },\n {\n \"alpha_fraction\": 0.4464285671710968,\n \"alphanum_fraction\": 0.4553571343421936,\n \"avg_line_length\": 21.600000381469727,\n \"blob_id\": \"ffa0acd52e59018c8b7f83ff0ee8f4a217055890\",\n \"content_id\": \"920b24f3f9d4839e52cbe0d5248fc9e6624145a4\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 112,\n \"license_type\": \"no_license\",\n \"max_line_length\": 36,\n \"num_lines\": 5,\n \"path\": \"/알고리즘/온라인저지/2022/04/0428/남욱이의 닭장.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"for t in range(int(input())):\\n N, M = map(int, input().split())\\n U = M*2 - N\\n T = M - U\\n print(U, T)\"\n },\n {\n \"alpha_fraction\": 0.477761834859848,\n \"alphanum_fraction\": 0.4964132010936737,\n \"avg_line_length\": 23.928571701049805,\n \"blob_id\": \"f564f852e9593ada3ab3f75a7400dd748b443f8a\",\n \"content_id\": \"c51cc1c877d3ed2d4d9431d71a1d545dfeb484f0\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 743,\n \"license_type\": \"no_license\",\n \"max_line_length\": 45,\n \"num_lines\": 28,\n \"path\": \"/알고리즘/[템플릿]/이분탐색/기타 레슨.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"def binary(start, end):\\n global result\\n if start > end: return\\n Blu_ray = (start + end) // 2\\n tmp = [0] * M\\n i = 0\\n for l in L:\\n if tmp[i] + l <= Blu_ray:\\n tmp[i] += l\\n else:\\n i += 1\\n try: tmp[i] += l\\n except: binary(Blu_ray+1, end)\\n if i>=M: break\\n if i >= M: # 블루레이 개수가 모자람\\n binary(Blu_ray+1, end)\\n else: # i < M : 블루레이 크기를 더 줄일 수 있음\\n if Blu_ray < result: result = Blu_ray\\n binary(start, Blu_ray-1)\\n\\nN, M = map(int, input().split())\\nL = list(map(int, input().split())) # lecture\\nS, E = max(L), sum(L)\\nresult = int(1e9)\\nbinary(S, E)\\nprint(result)\\n\\n# https://www.acmicpc.net/problem/2343\"\n },\n {\n \"alpha_fraction\": 0.4312500059604645,\n \"alphanum_fraction\": 0.46875,\n \"avg_line_length\": 16.88888931274414,\n \"blob_id\": \"944784d3c1b7b5138d19afaebcae7a603aa2782a\",\n \"content_id\": \"120308a0e85148adb60ba2243cf0f46229004dc7\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 160,\n \"license_type\": \"no_license\",\n \"max_line_length\": 35,\n \"num_lines\": 9,\n \"path\": \"/알고리즘/온라인저지/2022/05/0524/대회 or 인턴.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N, M, K = map(int, input().split())\\nresult = 0\\nwhile True:\\n N -= 2\\n M -= 1\\n if N < 0 or M < 0 or (N+M) < K:\\n break\\n result += 1\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.4752066135406494,\n \"alphanum_fraction\": 0.5206611752510071,\n \"avg_line_length\": 26,\n \"blob_id\": \"89d8952aace376e4b1a63ed3abe0b192a960279b\",\n \"content_id\": \"c4f26dcab171151fcb9a027412c52bc5baf26002\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 242,\n \"license_type\": \"no_license\",\n \"max_line_length\": 34,\n \"num_lines\": 9,\n \"path\": \"/알고리즘/온라인저지/2023/05/0526/Hurra!.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"for i in range(1, int(input())+1):\\n result = ''\\n if not i%7 and i%11:\\n result = 'Hurra!'\\n if i%7 and not i%11:\\n result = 'Super!'\\n if not i%7 and not i%11:\\n result = 'Wiwat!'\\n print(result if result else i)\"\n },\n {\n \"alpha_fraction\": 0.5777778029441833,\n \"alphanum_fraction\": 0.5925925970077515,\n \"avg_line_length\": 33,\n \"blob_id\": \"d91695adf060f4055ff573195301c8541df6470a\",\n \"content_id\": \"739c486f9b1aaa99037fe57b6afc4679efa485fb\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 135,\n \"license_type\": \"no_license\",\n \"max_line_length\": 58,\n \"num_lines\": 4,\n \"path\": \"/알고리즘/온라인저지/2022/07/0714/좌표 정렬하기 2.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = int(input())\\narr = [tuple(map(int, input().split())) for _ in range(N)]\\narr.sort(key=lambda x:(x[1], x[0]))\\nfor a in arr: print(*a)\"\n },\n {\n \"alpha_fraction\": 0.5462962985038757,\n \"alphanum_fraction\": 0.5648148059844971,\n \"avg_line_length\": 53.5,\n \"blob_id\": \"b4f3ccef19ef6965e1caef22b97258033b1bb863\",\n \"content_id\": \"b229e2d18c02cab0880877c1e09ba771b09788ce\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 108,\n \"license_type\": \"no_license\",\n \"max_line_length\": 73,\n \"num_lines\": 2,\n \"path\": \"/알고리즘/온라인저지/2022/03/0323/주사위.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"for t in range(1, int(input())+1):\\n print('Case {}: {}'.format(t, sum(tuple(map(int, input().split())))))\"\n },\n {\n \"alpha_fraction\": 0.4819277226924896,\n \"alphanum_fraction\": 0.4819277226924896,\n \"avg_line_length\": 19.83333396911621,\n \"blob_id\": \"65b4d3967ee67845517d14fa1fff3523fac7fa3e\",\n \"content_id\": \"3c6d7c104b55581c40f14a89e3c006ce0e8d93e0\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 249,\n \"license_type\": \"no_license\",\n \"max_line_length\": 40,\n \"num_lines\": 12,\n \"path\": \"/알고리즘/온라인저지/2022/06/0622/스캐너.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"R, C, ZR, ZC = map(int, input().split())\\nresult = []\\nfor r in range(R):\\n tmp = input()\\n a = ''\\n for t in tmp:\\n for zc in range(ZC):\\n a = a + t\\n for zr in range(ZR):\\n result.append(a)\\nfor r in result:\\n print(r)\"\n },\n {\n \"alpha_fraction\": 0.6186440587043762,\n \"alphanum_fraction\": 0.6186440587043762,\n \"avg_line_length\": 22.799999237060547,\n \"blob_id\": \"9e78bae6d849710cdd29da26e51a1d63771b3421\",\n \"content_id\": \"19df9d8f4d961f7b47d0d7ba5282e6280109b39a\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 118,\n \"license_type\": \"no_license\",\n \"max_line_length\": 35,\n \"num_lines\": 5,\n \"path\": \"/알고리즘/온라인저지/2023/06/0609/정보섬의 대중교통.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N, A, B = map(int, input().split())\\nresult = 'Anything'\\nif A>B: result = 'Subway'\\nif A<B: result = 'Bus'\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.359281450510025,\n \"alphanum_fraction\": 0.359281450510025,\n \"avg_line_length\": 17.66666603088379,\n \"blob_id\": \"fe79171095303e80d80e4fe9e9bd04c3549621d5\",\n \"content_id\": \"df71cbef3af4590c9fadfefaa7fbe69d1e9b3b39\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 167,\n \"license_type\": \"no_license\",\n \"max_line_length\": 27,\n \"num_lines\": 9,\n \"path\": \"/알고리즘/온라인저지/2022/12/1225/연길이의 이상형.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"yeongil = input()\\ndictt = {\\n 'E': 'I', 'I':'E',\\n 'S': 'N', 'N':'S',\\n 'T': 'F', 'F':'T',\\n 'J': 'P', 'P':'J',\\n}\\nfor y in yeongil:\\n print(dictt[y], end='')\"\n },\n {\n \"alpha_fraction\": 0.4533762037754059,\n \"alphanum_fraction\": 0.4887459874153137,\n \"avg_line_length\": 16.33333396911621,\n \"blob_id\": \"5ffacf7db43de070240c1390ae0e402be69fe67c\",\n \"content_id\": \"962039166d8c4452747d5c610a12e161cf33eb3d\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 311,\n \"license_type\": \"no_license\",\n \"max_line_length\": 33,\n \"num_lines\": 18,\n \"path\": \"/알고리즘/온라인저지/2023/05/0512/Don’t pass me the ball!.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"def dfs(size, idx):\\n global result\\n\\n if arr[2] != 0:\\n result += 1\\n return\\n\\n for player in range(size, N):\\n if player not in arr:\\n arr[idx] = player\\n dfs(player+1, idx+1)\\n arr[idx] = 0\\n\\nN = int(input())\\narr = [0]*3\\nresult = 0\\ndfs(1, 0)\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.443452388048172,\n \"alphanum_fraction\": 0.449404776096344,\n \"avg_line_length\": 15.800000190734863,\n \"blob_id\": \"45aab3a7faca59934bd86f2c08252c6b76e3e390\",\n \"content_id\": \"e4e2f308e21d3e4a2daeec2c912e648b58f13eae\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 336,\n \"license_type\": \"no_license\",\n \"max_line_length\": 32,\n \"num_lines\": 20,\n \"path\": \"/알고리즘/온라인저지/2022/02/0201/명령 프롬프트.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = int(input())\\n\\ninputs = [''] * N\\n\\nfor i in range(N):\\n inputs[i] = input()\\n\\nfor i in range(len(inputs[0])):\\n flag = True\\n word = inputs[0][i]\\n\\n for j in range(N):\\n if word != inputs[j][i]:\\n flag = False\\n break\\n \\n if flag:\\n print(word, end='')\\n else:\\n print('?', end='')\\n\"\n },\n {\n \"alpha_fraction\": 0.5428571701049805,\n \"alphanum_fraction\": 0.5857142806053162,\n \"avg_line_length\": 14.666666984558105,\n \"blob_id\": \"3f550a2448527c5f254d1d25aeb3a8cb3e15660e\",\n \"content_id\": \"77b3679fbd4542793cfc3a846989b1ce587d2d27\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 140,\n \"license_type\": \"no_license\",\n \"max_line_length\": 36,\n \"num_lines\": 9,\n \"path\": \"/알고리즘/온라인저지/2022/12/1205/피보나치 수.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\n\\nN = int(input().rstrip())\\nmod = int(1e9)+7\\na, b = 1, 1\\nfor _ in range(N-2): a, b = b, (a+b)\\nprint(b)\"\n },\n {\n \"alpha_fraction\": 0.3098958432674408,\n \"alphanum_fraction\": 0.3151041567325592,\n \"avg_line_length\": 20.38888931274414,\n \"blob_id\": \"f4d6dc40eb26aa7b795a83c9414bfa1e789524bf\",\n \"content_id\": \"b3a663e427f355581771035efa44be48aac45d77\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 384,\n \"license_type\": \"no_license\",\n \"max_line_length\": 31,\n \"num_lines\": 18,\n \"path\": \"/알고리즘/온라인저지/2022/07/0725/부분 문자열.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"while True:\\n try:\\n S, T = input().split()\\n j = 0\\n tmp = ''\\n result = 'No'\\n for i in range(len(T)):\\n if T[i] == S[j]:\\n tmp += T[i]\\n j += 1\\n if j >= len(S):\\n break\\n # print(tmp)\\n if tmp == S:\\n result = 'Yes'\\n print(result)\\n except:\\n exit()\"\n },\n {\n \"alpha_fraction\": 0.43877550959587097,\n \"alphanum_fraction\": 0.4413265287876129,\n \"avg_line_length\": 22.117647171020508,\n \"blob_id\": \"0e47b41cbdc1747fa9ca97a1c3bc23693338d6ee\",\n \"content_id\": \"501ebbfc931611c33abbf0cd85ff017b9a782d5b\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 512,\n \"license_type\": \"no_license\",\n \"max_line_length\": 56,\n \"num_lines\": 17,\n \"path\": \"/알고리즘/온라인저지/2022/08/0816/괄호.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"for _ in range(int(input())):\\n P = input() # parenthesis string : 괄호\\n S = [] # stack\\n for p in P:\\n if p == '(': S.append(p)\\n elif p == ')':\\n if S: \\n if S[-1] == '(': S.pop() \\n else: S.append(p)\\n print('NO' if S else 'YES')\\n\\n\\\"\\\"\\\"\\n괄호를 하나씩 스택에 집어넣어서\\n짝이 맞으면 pop해주고\\n스택이 딱 맞아 떨어지면 괄호의 짝이 맞는 것\\n스택이 남아있다면 괄호가 짝이 맞지 않는 것\\n\\\"\\\"\\\"\"\n },\n {\n \"alpha_fraction\": 0.578125,\n \"alphanum_fraction\": 0.5833333134651184,\n \"avg_line_length\": 20.44444465637207,\n \"blob_id\": \"bedaf56a7a0d2fd341410431bf91cf8ccf568187\",\n \"content_id\": \"ce325de2f38eb1e736e85d258a686b9f7c368156\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 192,\n \"license_type\": \"no_license\",\n \"max_line_length\": 50,\n \"num_lines\": 9,\n \"path\": \"/알고리즘/온라인저지/2022/09/0927/아름다운 수.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# import sys\\n\\n# input = sys.stdin.readline\\n\\n# for _ in range(int(input().rstrip())):\\n# num = set(input().rstrip())\\n# print(len(num))\\n\\nfor _ in [0]*int(input()):print(len(set(input())))\"\n },\n {\n \"alpha_fraction\": 0.5954545736312866,\n \"alphanum_fraction\": 0.5977272987365723,\n \"avg_line_length\": 18.173913955688477,\n \"blob_id\": \"520b5c7ce84a76b34eeef9ffd638cd9da367f39e\",\n \"content_id\": \"bd434113fff4777d2d2bc6472fb51a29521817b1\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 648,\n \"license_type\": \"no_license\",\n \"max_line_length\": 45,\n \"num_lines\": 23,\n \"path\": \"/알고리즘/온라인저지/2022/01/0122/N번째 큰 수.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import heapq # 우선순위 큐\\n\\nN = int(input())\\n\\nhq = heapq # 힙큐 메서드 사용하기 위함\\n\\nresult = [] # 힙큐로 담을 리스트\\n\\n# 일단 첫 줄을 힙큐로 넣는다\\nfor i in list(map(int, input().split())):\\n hq.heappush(result, i)\\n\\n# 두번째줄부터\\nfor n in range(1, N):\\n # 매 줄 마다 힙큐에 넣는 동시에 pop 해주면서\\n # N개로 개수를 맞춘다\\n for i in list(map(int, input().split())):\\n # 개사기메서드 힙푸시팝\\n hq.heappushpop(result, i)\\n\\n# 입력받는 동시에 힙푸시팝을 진행하고 남은 리스트의\\n# 첫번째 값이 정답 \\nprint(hq.heappop(result))\"\n },\n {\n \"alpha_fraction\": 0.5592592358589172,\n \"alphanum_fraction\": 0.5777778029441833,\n \"avg_line_length\": 17.066667556762695,\n \"blob_id\": \"76d0f07dedb2c51c15255e7a0b096af1a302fbe2\",\n \"content_id\": \"1d3767c7902c82671add213838bb6778c0a242bb\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 332,\n \"license_type\": \"no_license\",\n \"max_line_length\": 63,\n \"num_lines\": 15,\n \"path\": \"/알고리즘/온라인저지/2023/02/0214/8진수.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"tmp = 0\\ni = 1\\nfor j in input()[::-1]:\\n tmp += i * int(j)\\n i *= 2\\n\\nimport string\\n\\nN, B = tmp, 8\\ntmp = string.digits + string.ascii_uppercase # 자릿수를 담은 문자열\\nresult = ''\\nwhile N:\\n result = tmp[N%B] + result # B진법이므로 B로 나눈 나머지번째 문자를 계속 추가한다\\n N //= B\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.4029850661754608,\n \"alphanum_fraction\": 0.46268656849861145,\n \"avg_line_length\": 33,\n \"blob_id\": \"0978cdb1082167250694ae15542de18b31331681\",\n \"content_id\": \"05de05185a11935b1df8d9612b27753a6fa4df52\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 67,\n \"license_type\": \"no_license\",\n \"max_line_length\": 35,\n \"num_lines\": 2,\n \"path\": \"/알고리즘/온라인저지/2022/08/0812/Rats.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"A, B, C = map(int, input().split())\\nprint(((A+1)*(B+1))//(C+1) - 1)\"\n },\n {\n \"alpha_fraction\": 0.4000000059604645,\n \"alphanum_fraction\": 0.5,\n \"avg_line_length\": 19.5,\n \"blob_id\": \"76e3bb9c246fc4948eb62815b8c00168ad0286af\",\n \"content_id\": \"0d88ca4d9094393e76f4df431b71fafc24b2c876\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 40,\n \"license_type\": \"no_license\",\n \"max_line_length\": 23,\n \"num_lines\": 2,\n \"path\": \"/알고리즘/온라인저지/2022/08/0822/Zadanie próbne 2.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = int(input())\\nprint((N+1)*2, (N+1)*3)\"\n },\n {\n \"alpha_fraction\": 0.6363636255264282,\n \"alphanum_fraction\": 0.6363636255264282,\n \"avg_line_length\": 18,\n \"blob_id\": \"0728081c0a9a931d93b23b639d1c601b0fd25cb2\",\n \"content_id\": \"ba6d012a8b669a9ca3b490f99ae2cabb06b0c415\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 226,\n \"license_type\": \"no_license\",\n \"max_line_length\": 27,\n \"num_lines\": 7,\n \"path\": \"/알고리즘/온라인저지/2021/07/0730/[기초-산술연산] 정수 2개 입력받아 나눈 몫 계산하기.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# 각각 입력받아서 split으로 각각 저장해주고\\na, b = input().split()\\n# 무조건 각각 int 적용해줘야 한다\\n# 입력받는 과정에서 하려니까 에러가 나버리네\\na = int(a)\\nb = int(b)\\nprint(a//b)\"\n },\n {\n \"alpha_fraction\": 0.6106870174407959,\n \"alphanum_fraction\": 0.6106870174407959,\n \"avg_line_length\": 65,\n \"blob_id\": \"3ed0733bd904b124988b83d907ea8155bf5cf48f\",\n \"content_id\": \"6d0972d98752d3642a5b7d6184783e224b980bec\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 131,\n \"license_type\": \"no_license\",\n \"max_line_length\": 114,\n \"num_lines\": 2,\n \"path\": \"/알고리즘/온라인저지/2022/07/0705/욱제는 도박쟁이야!!.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = int(input())\\nprint(sum(list(map(abs, list(map(int, input().split()))))) + sum(list(map(abs, list(map(int, input().split()))))))\"\n },\n {\n \"alpha_fraction\": 0.5736842155456543,\n \"alphanum_fraction\": 0.5789473652839661,\n \"avg_line_length\": 30.83333396911621,\n \"blob_id\": \"0a4f30936bc46cc946d78e1ebbc8091a21f60fd4\",\n \"content_id\": \"22b292a087022bf6418d527bdbe56f2fc7c5e02e\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 190,\n \"license_type\": \"no_license\",\n \"max_line_length\": 45,\n \"num_lines\": 6,\n \"path\": \"/알고리즘/온라인저지/2022/09/0910/아이들은 사탕을 좋아해.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"for _ in range(int(input())):\\n N, K = map(int, input().split())\\n candies = list(map(int, input().split()))\\n result = 0\\n for candy in candies: result += candy//K\\n print(result)\"\n },\n {\n \"alpha_fraction\": 0.542553186416626,\n \"alphanum_fraction\": 0.542553186416626,\n \"avg_line_length\": 14.833333015441895,\n \"blob_id\": \"0f49f6a61721ff3f5d25a7c8093c9adebee50b72\",\n \"content_id\": \"a2a9b4b5f7564f73c450317a82ca1a690aed2241\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 94,\n \"license_type\": \"no_license\",\n \"max_line_length\": 32,\n \"num_lines\": 6,\n \"path\": \"/알고리즘/온라인저지/2023/03/0323/전체 계산 횟수.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N, M = map(int, input().split())\\nresult = N\\nwhile N:\\n N //= M\\n result += N\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.5791505575180054,\n \"alphanum_fraction\": 0.5965250730514526,\n \"avg_line_length\": 19.760000228881836,\n \"blob_id\": \"93bf35b0eaa61fb2300a3519f385ddc1a1c04474\",\n \"content_id\": \"e845e5e0059e195aba781fb250a217dedac75fe1\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 518,\n \"license_type\": \"no_license\",\n \"max_line_length\": 50,\n \"num_lines\": 25,\n \"path\": \"/알고리즘/[템플릿]/이분탐색/랜선 자르기.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\n\\ndef cut(length):\\n cutted = 0\\n for cable in cables:\\n cutted += cable//length\\n if cutted>=N: return True\\n return False\\n\\nK, N = map(int, input().rstrip().split())\\ncables = [int(input().rstrip()) for _ in range(K)]\\nresult = 1\\nstart, end = result, sum(cables)//N\\nwhile start<=end:\\n mid = (start+end) // 2\\n if cut(mid):\\n start = mid+1\\n result = max(result, mid)\\n else:\\n end = mid-1\\nprint(result)\\n\\n# https://www.acmicpc.net/problem/1654\"\n },\n {\n \"alpha_fraction\": 0.5112359523773193,\n \"alphanum_fraction\": 0.5280898809432983,\n \"avg_line_length\": 18.88888931274414,\n \"blob_id\": \"7da2d26ccaf16740989662214d791e34004d3e1a\",\n \"content_id\": \"d392be358a76cb8392372237bf1d99fb4f96d200\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 266,\n \"license_type\": \"no_license\",\n \"max_line_length\": 35,\n \"num_lines\": 9,\n \"path\": \"/알고리즘/온라인저지/2021/07/0730/[기초-산술연산] 정수 3개 입력받아 합과 평균 출력하기.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# 변수 세 개 받아서\\n# 공백으로 쪼개서\\n# int로 바꿔주고\\n# map으로 각각 저장해준다\\na, b, c = map(int, input().split())\\nd = a + b + c\\ne = round(d / 3, 3)\\n# f\\\"{:.?f}\\\"로 소수점 아래 자리수 고정시킬 수 있다\\nprint(f\\\"{d} {e:.2f}\\\")\"\n },\n {\n \"alpha_fraction\": 0.46666666865348816,\n \"alphanum_fraction\": 0.49047619104385376,\n \"avg_line_length\": 14.071428298950195,\n \"blob_id\": \"1e91eb399b26a92be8b5e65bcc8b04170ed0849f\",\n \"content_id\": \"b6d9e4da16bbe3648aa424a54c91934c68867d7b\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 210,\n \"license_type\": \"no_license\",\n \"max_line_length\": 36,\n \"num_lines\": 14,\n \"path\": \"/알고리즘/온라인저지/2022/02/0201/분산처리.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"T = int(input())\\n\\nfor t in range(T):\\n a, b = map(int, input().split())\\n\\n result = 1\\n\\n for i in range(b):\\n result = (result*a)%10\\n\\n if result:\\n print(result)\\n else:\\n print(10)\"\n },\n {\n \"alpha_fraction\": 0.38268792629241943,\n \"alphanum_fraction\": 0.4441913366317749,\n \"avg_line_length\": 26.5,\n \"blob_id\": \"6e6e0f3727b34932bc5930d70e5496956105fe79\",\n \"content_id\": \"128ea8b4c3305b1de233d41a8cf46b7e47994ddc\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 439,\n \"license_type\": \"no_license\",\n \"max_line_length\": 104,\n \"num_lines\": 16,\n \"path\": \"/알고리즘/온라인저지/2021/08/0828/한수.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ndef arithmetic_sequence(N):\\n if N < 100:\\n return N\\n else:\\n cnt = 0\\n for n in range(100, N+1):\\n a, b, c = n//100, (n-(n//100)*100)//10, n%10\\n for k in range(6):\\n if (a+k == b and b+k == c and a+(k*2) == c) or (c+k == b and b+k == a and c+(k*2) == a):\\n cnt += 1\\n return 99 + cnt\\n\\nN = int(sys.stdin.readline())\\nprint(arithmetic_sequence(N))\"\n },\n {\n \"alpha_fraction\": 0.4635658860206604,\n \"alphanum_fraction\": 0.48217055201530457,\n \"avg_line_length\": 21.275861740112305,\n \"blob_id\": \"475808a6e4e5e7d9f058286f2f577adb08a61ee8\",\n \"content_id\": \"ddc47017f7e459dee1c03d151fa4057d87c2096b\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 885,\n \"license_type\": \"no_license\",\n \"max_line_length\": 56,\n \"num_lines\": 29,\n \"path\": \"/알고리즘/온라인저지/2022/01/0122/수들의 합 2.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N, M = map(int, input().split())\\n\\nseq = list(map(int, input().split())) # 수열 입력\\n\\ns = e = 0 # 두포인터\\n\\nnow = sum(seq[s:e+1]) # 초기값(seq[0])\\n\\nresult = 0 # 크기가 M과 같은 수열 부분합의 개수 초기화\\n\\nwhile True: # 무지성 while True\\n # 종료조건\\n # 1. e를 뒤로 밀어봤자 M보다 크거나 같아질 수 없음\\n # 2. s를 뒤로 땡겨봤자 M보다 작거나 같아질 수 없음\\n if (now < M and e == N-1) or (now > M and s == N-1):\\n break\\n\\n if now == M: # 수열 부분합이 M과 같으면\\n result += 1\\n now -= seq[s]\\n s += 1 # 앞에서 한 칸 땡기기\\n elif now < M: # 부분합이 M보다 작으면\\n e += 1 # 뒤로 한 칸 밀기\\n now += seq[e]\\n elif now > M: # 부분합이 M보다 크면\\n now -= seq[s]\\n s += 1 # 앞에서 한 칸 땡기기\\n\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.3333333432674408,\n \"alphanum_fraction\": 0.4047619104385376,\n \"avg_line_length\": 14.363636016845703,\n \"blob_id\": \"966ab38e930649b80051442398272ea1b1fd3b45\",\n \"content_id\": \"3abe518c1ea369b0b33a6f86ccc476eb9d779781\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 168,\n \"license_type\": \"no_license\",\n \"max_line_length\": 22,\n \"num_lines\": 11,\n \"path\": \"/알고리즘/온라인저지/2022/09/0901/방 번호.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = input()\\ndp = [0]*9\\nfor n in N:\\n tmp = int(n)\\n if tmp == 9:\\n dp[6] += 1\\n else:\\n dp[tmp] += 1\\nif dp[6]%2: dp[6] += 1\\ndp[6] //= 2\\nprint(max(dp))\"\n },\n {\n \"alpha_fraction\": 0.3842794895172119,\n \"alphanum_fraction\": 0.4410480260848999,\n \"avg_line_length\": 17.360000610351562,\n \"blob_id\": \"1af1e8c971600bc02e3e69a246fe238cd3e8144b\",\n \"content_id\": \"5f26a1cec754f42ecee4e420bd21882d6e1046bb\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 458,\n \"license_type\": \"no_license\",\n \"max_line_length\": 46,\n \"num_lines\": 25,\n \"path\": \"/알고리즘/온라인저지/2023/05/0507/너의 평점은.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"grade_to_score = {\\n 'A+': 4.5,\\n 'A0': 4.0,\\n 'B+': 3.5,\\n 'B0': 3.0,\\n 'C+': 2.5,\\n 'C0': 2.0,\\n 'D+': 1.5,\\n 'D0': 1.0,\\n 'F': 0.0,\\n}\\n\\ntime_sum = 0\\nresult = 0\\nwhile True:\\n try:\\n subject, time, grade = input().split()\\n if grade == 'P':\\n continue\\n time = int(time[0])\\n time_sum += time\\n result += time*grade_to_score[grade]\\n except EOFError:\\n break\\nprint(f'{result/time_sum:.6f}')\"\n },\n {\n \"alpha_fraction\": 0.39915966987609863,\n \"alphanum_fraction\": 0.4453781545162201,\n \"avg_line_length\": 13.9375,\n \"blob_id\": \"ab1d6c66c529b88445baf50d6c1913acf2711d9f\",\n \"content_id\": \"5089422109a20652efc07b473d030c2acaab43e5\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 238,\n \"license_type\": \"no_license\",\n \"max_line_length\": 39,\n \"num_lines\": 16,\n \"path\": \"/알고리즘/온라인저지/2022/02/0212/핸드폰 요금.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = int(input())\\n\\ncalls = list(map(int, input().split()))\\n\\nY = M = 0\\n\\nfor c in calls:\\n Y += (c//30 + 1) * 10\\n M += (c//60 + 1) * 15\\n\\nif Y > M:\\n print('M', min(Y, M))\\nelif M > Y:\\n print('Y', min(Y, M))\\nelse:\\n print('Y M', Y)\"\n },\n {\n \"alpha_fraction\": 0.5779816508293152,\n \"alphanum_fraction\": 0.5871559381484985,\n \"avg_line_length\": 21,\n \"blob_id\": \"4590535f7c9a97d407080e7be4377e35fb9d4c44\",\n \"content_id\": \"9c3447ab8a02b8806cc54970d03476d4ec4937d7\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 109,\n \"license_type\": \"no_license\",\n \"max_line_length\": 41,\n \"num_lines\": 5,\n \"path\": \"/알고리즘/온라인저지/2023/03/0303/특식 배부.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = int(input())\\nresult = 0\\nfor i in list(map(int, input().split())):\\n result += min((N, i))\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.4789719581604004,\n \"alphanum_fraction\": 0.5046728849411011,\n \"avg_line_length\": 22.83333396911621,\n \"blob_id\": \"af55433231398a15d8c08433aaec5da0dc7a49f9\",\n \"content_id\": \"16727945fa36123f9fd1407a35457faea6f81e8b\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 428,\n \"license_type\": \"no_license\",\n \"max_line_length\": 49,\n \"num_lines\": 18,\n \"path\": \"/알고리즘/온라인저지/2022/09/0929/피카츄.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\n\\nword = list(input().rstrip())\\ni = 0\\nwhile i<len(word)-1:\\n pikachu = word[i] + word[i+1]\\n if pikachu in ['pi', 'ka']:\\n for _ in [0]*2: word.pop(i); \\n continue\\n if i<len(word)-2:\\n pikachu = word[i] + word[i+1] + word[i+2]\\n if pikachu == 'chu':\\n for _ in [0]*3: word.pop(i); \\n continue\\n i += 1\\nprint('NO' if len(word) else 'YES')\"\n },\n {\n \"alpha_fraction\": 0.6047903895378113,\n \"alphanum_fraction\": 0.6407185792922974,\n \"avg_line_length\": 23,\n \"blob_id\": \"445b84c5a07a7d4ef531c59388eac39d1805d75c\",\n \"content_id\": \"997e80b0c499d720a5864f86a1c51767697b2b09\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 167,\n \"license_type\": \"no_license\",\n \"max_line_length\": 44,\n \"num_lines\": 7,\n \"path\": \"/알고리즘/온라인저지/2022/09/0914/숫자.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"A, B = map(int, input().split())\\nresult = list(range(min(A, B)+1, max(A, B)))\\nprint(len(result))\\nif result:\\n print(*result)\\n\\n# https://www.acmicpc.net/problem/10093\"\n },\n {\n \"alpha_fraction\": 0.3644859790802002,\n \"alphanum_fraction\": 0.40186914801597595,\n \"avg_line_length\": 20.5,\n \"blob_id\": \"441fe2552aa24f9c481c2fe2b1d8417bd32da5be\",\n \"content_id\": \"6fb1ac81ae6dd40877fd437ecaaddd80b2efd354\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 214,\n \"license_type\": \"no_license\",\n \"max_line_length\": 37,\n \"num_lines\": 10,\n \"path\": \"/알고리즘/온라인저지/2023/01/0106/암호.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"S = input()\\nP = input()\\ni = 0\\nfor s in S:\\n if s != ' ':\\n tmp = ord(s) - (ord(P[i])-96)\\n if not tmp >= 97: tmp += 26\\n print(chr(tmp), end='')\\n else: print(' ', end='')\\n i = (i+1)%len(P)\"\n },\n {\n \"alpha_fraction\": 0.47783932089805603,\n \"alphanum_fraction\": 0.4819944500923157,\n \"avg_line_length\": 21.59375,\n \"blob_id\": \"11f8a919ccf624eaf5a259ec464cf724d04eae05\",\n \"content_id\": \"12638af50a068f8a190e0fff9ee7277b5ce90301\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 722,\n \"license_type\": \"no_license\",\n \"max_line_length\": 51,\n \"num_lines\": 32,\n \"path\": \"/알고리즘/온라인저지/2022/10/1002/바닥 장식.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\n\\ndef check(N, M, arr):\\n board = 0\\n for i in range(N):\\n flag = False\\n for j in range(M):\\n if arr[i][j] == '-' and not flag:\\n flag = True\\n board += 1\\n elif not arr[i][j] == '-': flag = False\\n return board\\n\\ndef rotate(arr):\\n rotated = []\\n for j in range(M):\\n tmp = ''\\n for i in range(N): \\n if arr[i][j] == '-': tmp += '|'\\n else: tmp += '-'\\n rotated.append(tmp)\\n return rotated\\n\\nN, M = map(int, input().rstrip().split())\\narr = [input().rstrip() for _ in range(N)]\\nresult = 0\\nresult += check(N, M, arr)\\narr = rotate(arr)\\nresult += check(M, N, arr)\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.5561797618865967,\n \"alphanum_fraction\": 0.5561797618865967,\n \"avg_line_length\": 21.375,\n \"blob_id\": \"72d814e14f21f67d5eb95adeb5d1f0d15368d6e1\",\n \"content_id\": \"5bb88dc6844058bdbc92eaaa3b37163bf5a2c7ed\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 178,\n \"license_type\": \"no_license\",\n \"max_line_length\": 94,\n \"num_lines\": 8,\n \"path\": \"/알고리즘/온라인저지/2022/02/0220/배수 찾기.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = int(input())\\n\\nwhile True:\\n num = int(input())\\n if not num:\\n break\\n\\n print(f'{num} is a multiple of {N}.' if not num%N else f'{num} is NOT a multiple of {N}.')\"\n },\n {\n \"alpha_fraction\": 0.5537037253379822,\n \"alphanum_fraction\": 0.5657407641410828,\n \"avg_line_length\": 26,\n \"blob_id\": \"8898086a59a10313fbf356996787082e72c03ecf\",\n \"content_id\": \"896be0e6a16031a34fd02c2468cdeb3aeaf49f18\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1504,\n \"license_type\": \"no_license\",\n \"max_line_length\": 67,\n \"num_lines\": 40,\n \"path\": \"/알고리즘/온라인저지/2021/10/1003/집합.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\nM = int(input())\\n\\nS = set() # set자료형으로 생성\\n# add과정에서 x가 이미 있는 경우 무시할 것이기 때문에 데이터들은 절대 중복될 수 없다\\n# 따라서 순서를 지니지 않는 set자료형으로 만들어서 시간초과를 회피\\n# 추가하고 제거하는 과정에서 list자료형의 append와 remove혹은 pop을 쓰는 것 보다\\n# set자료형의 add와 discard를 쓰는 것이 빠르다\\n\\nfor m in range(M):\\n orders = sys.stdin.readline().split()\\n\\n if len(orders) == 1: # all이 명령어로 들어왔을 때\\n order = orders[0] # add remove check toggle all empty등, 명령어\\n else: # all을 제외한 명령어들일 때\\n order = orders[0] # 명령어\\n num = int(orders[1]) # 목적 숫자 x\\n\\n if order == 'add':\\n S.add(num) # list자료형의 append와 같음\\n elif order == 'remove':\\n S.discard(num) # list자료형의 remove혹은 pop와 같음\\n elif order == 'check':\\n if num in S:\\n print(1)\\n else:\\n print(0)\\n elif order == 'toggle':\\n if num in S:\\n S.discard(num)\\n else:\\n S.add(num)\\n elif order == 'all':\\n S = set([i for i in range(1, 21)]) # 1~20까지 전부 채워진 set로 리셋\\n else:\\n S = set() # set를 초기화\\n\\n# 추가적으로 해당 문제는 메모리도 많이 적은 편이라\\n# python의 경우 평소처럼 pypy3로 제출하면 메모리부족으로 오답처리 된다\\n\"\n },\n {\n \"alpha_fraction\": 0.5719298124313354,\n \"alphanum_fraction\": 0.582456111907959,\n \"avg_line_length\": 25,\n \"blob_id\": \"a70c780f0cb8be9918390b30635239b1deb84d00\",\n \"content_id\": \"ab32a4a159be360f1f947ba42d7f6b7224b59e0b\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 285,\n \"license_type\": \"no_license\",\n \"max_line_length\": 42,\n \"num_lines\": 11,\n \"path\": \"/알고리즘/온라인저지/2022/09/0911/민균이의 비밀번호.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = int(input())\\ntext_list = [input() for _ in range(N)]\\ntext_set = set(text_list)\\nresult = ''\\nfor text in text_list:\\n if result: break\\n if text == text[::-1]:\\n result = text\\n elif text[::-1] in text_set:\\n result = text\\nprint(len(result), result[len(result)//2])\"\n },\n {\n \"alpha_fraction\": 0.42607003450393677,\n \"alphanum_fraction\": 0.48249027132987976,\n \"avg_line_length\": 21.39130401611328,\n \"blob_id\": \"9db1e9255814c1ab7d5a44a6d8fa63fac88aa300\",\n \"content_id\": \"98b4fa02f1ea9f9efe638ab2ee7d6047a322e5db\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 514,\n \"license_type\": \"no_license\",\n \"max_line_length\": 45,\n \"num_lines\": 23,\n \"path\": \"/알고리즘/온라인저지/2022/10/1012/롤 케이크.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\n\\nresult = [[0, 0], [0, 0]]\\nL = int(input().rstrip())\\nN = int(input().rstrip())\\ncakes = [1]*L\\nfor i in range(1, N+1):\\n P, K = map(int, input().rstrip().split())\\n if K-P+1 > result[1][1]:\\n result[1][1] = K-P+1\\n result[1][0] = i\\n cake = 0\\n for j in range(P-1, K):\\n if cakes[j]:\\n cakes[j] = 0\\n cake += 1\\n if cake > result[0][1]:\\n result[0][1] = cake\\n result[0][0] = i\\nprint(result[1][0])\\nprint(result[0][0])\"\n },\n {\n \"alpha_fraction\": 0.4491978585720062,\n \"alphanum_fraction\": 0.4946524202823639,\n \"avg_line_length\": 14.625,\n \"blob_id\": \"3aeb4e6ae390550ca410e54c3e7c7f0c79daa230\",\n \"content_id\": \"f56101f22ded30ce19544a0112e7cc4400ff0da2\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 374,\n \"license_type\": \"no_license\",\n \"max_line_length\": 40,\n \"num_lines\": 24,\n \"path\": \"/알고리즘/온라인저지/2022/02/0213/슈퍼 마리오.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"now = int(input())\\nans_found = False\\nresult = 0\\n\\nfor _ in range(9):\\n num = int(input())\\n tmp = now + num\\n\\n if ans_found:\\n continue\\n\\n if tmp >= 100 and num < 100:\\n if abs(tmp-100) <= abs(100-now):\\n result = tmp\\n else:\\n result = now\\n ans_found = True\\n\\n now += num\\n\\nif now <= 100:\\n result = now\\n\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.4876847267150879,\n \"alphanum_fraction\": 0.5024630427360535,\n \"avg_line_length\": 16,\n \"blob_id\": \"70cef0592aaea48e2e110017dc8a174d5bedd16d\",\n \"content_id\": \"8322b1a564f368e87e2f3832202da0018beaa77e\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 203,\n \"license_type\": \"no_license\",\n \"max_line_length\": 32,\n \"num_lines\": 12,\n \"path\": \"/알고리즘/온라인저지/2022/06/0601/암호제작.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"P, K = map(int, input().split())\\nresult = 'GOOD'\\nnum = 0\\nfor k in range(2, K):\\n if P%k == 0:\\n result = 'BAD'\\n num = k\\n break\\nif num:\\n print(result, num)\\nelse:\\n print(result)\"\n },\n {\n \"alpha_fraction\": 0.5446808338165283,\n \"alphanum_fraction\": 0.5446808338165283,\n \"avg_line_length\": 12.11111068725586,\n \"blob_id\": \"d4f51ef4aa3e0d6b2b42f6a52778dba03743a947\",\n \"content_id\": \"34edccf3d114e5aaa0ed4b4510ec9c32a91c6876\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 235,\n \"license_type\": \"no_license\",\n \"max_line_length\": 32,\n \"num_lines\": 18,\n \"path\": \"/알고리즘/온라인저지/2021/10/1016/듣보잡.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N, M = map(int, input().split())\\n\\na = set()\\n\\nfor n in range(N):\\n a.add(input())\\n\\nresult = []\\n\\nfor m in range(M):\\n b = input()\\n if b in a:\\n result.append(b)\\n\\nprint(len(result))\\nresult.sort()\\nfor r in result:\\n print(r)\"\n },\n {\n \"alpha_fraction\": 0.45039165019989014,\n \"alphanum_fraction\": 0.48433420062065125,\n \"avg_line_length\": 24.566667556762695,\n \"blob_id\": \"172d8d7567868b150c20efa532dc9a7e1df897ab\",\n \"content_id\": \"ed33f66f910809f83be208e20f6ea2ba83f80c6f\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 766,\n \"license_type\": \"no_license\",\n \"max_line_length\": 57,\n \"num_lines\": 30,\n \"path\": \"/알고리즘/[템플릿]/BFS/토마토.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from collections import deque\\n\\ndy, dx = [-1, 1, 0, 0], [0, 0, -1, 1]\\nM, N = map(int, input().split())\\narr = [list(map(int, input().split())) for _ in range(N)]\\nQ = deque()\\nfor i in range(N):\\n for j in range(M):\\n if arr[i][j] == 1:\\n Q.append((i, j, 0))\\n arr[i][j] = 0\\nresult = 0\\nwhile Q:\\n y, x, day = Q.popleft()\\n if arr[y][x] == 1: continue\\n arr[y][x] = 1\\n result = max(result, day)\\n for i in range(4):\\n ny, nx = y+dy[i], x+dx[i]\\n if 0<=ny<N and 0<=nx<M and arr[ny][nx] == 0:\\n Q.append((ny, nx, day+1))\\nfor i in range(N):\\n if result == -1: break\\n for j in range(M):\\n if arr[i][j] == 0:\\n result = -1\\n break\\nprint(result)\\n\\n# https://www.acmicpc.net/problem/7576\"\n },\n {\n \"alpha_fraction\": 0.5901639461517334,\n \"alphanum_fraction\": 0.5901639461517334,\n \"avg_line_length\": 30,\n \"blob_id\": \"6bc47d3c2df3673c502e5828f8558fa4e69d0306\",\n \"content_id\": \"884bc73ed3fcbf78f04cae5bd9694cca0efa2264\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 61,\n \"license_type\": \"no_license\",\n \"max_line_length\": 44,\n \"num_lines\": 2,\n \"path\": \"/알고리즘/온라인저지/2023/04/0413/Mathematics.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = int(input())\\nprint(sum([int(input()) for _ in range(N)]))\"\n },\n {\n \"alpha_fraction\": 0.5882353186607361,\n \"alphanum_fraction\": 0.5882353186607361,\n \"avg_line_length\": 22,\n \"blob_id\": \"fe8d31df2c1e6b746fc7b2035ac4bb3406610995\",\n \"content_id\": \"8c4c75b645f53fcf629faf9cce60bfbb4cb82073\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 68,\n \"license_type\": \"no_license\",\n \"max_line_length\": 32,\n \"num_lines\": 3,\n \"path\": \"/알고리즘/온라인저지/2023/04/0412/샤틀버스.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"x, y = map(int, input().split())\\nif x>y: print(x+y)\\nelse: print(y-x)\"\n },\n {\n \"alpha_fraction\": 0.525073766708374,\n \"alphanum_fraction\": 0.5545722842216492,\n \"avg_line_length\": 27.33333396911621,\n \"blob_id\": \"2abbf5356b1b5fa36834bad8b97fce086551c9d9\",\n \"content_id\": \"abcc75e52ceed980ec180a4945731b9c561622a0\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 389,\n \"license_type\": \"no_license\",\n \"max_line_length\": 47,\n \"num_lines\": 12,\n \"path\": \"/알고리즘/프로그래머스/Level1/로또의 최고 순위와 최저 순위.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"def solution(lottos, win_nums):\\n answer = []\\n # print(lottos, win_nums)\\n # 일치하는 번호의 개수만이, 오직 등수에 영향을 줌\\n minn = 0\\n for l in lottos:\\n if l in win_nums:\\n minn += 1\\n result = [6, 6, 5, 4, 3, 2, 1] # 등수 테이블\\n answer.append(result[lottos.count(0)+minn])\\n answer.append(result[minn]) \\n return answer\"\n },\n {\n \"alpha_fraction\": 0.38860103487968445,\n \"alphanum_fraction\": 0.41450777649879456,\n \"avg_line_length\": 18.399999618530273,\n \"blob_id\": \"c2bafa392890ad09ee73a9bd0f3718818556e535\",\n \"content_id\": \"84961694ffb6f3e1989b7aef238a63bbe6ae5f68\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 193,\n \"license_type\": \"no_license\",\n \"max_line_length\": 29,\n \"num_lines\": 10,\n \"path\": \"/알고리즘/온라인저지/2023/05/0508/탁구 경기.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"D, P = 0, 0\\nfor i in range(int(input())):\\n winner = input()\\n if abs(D-P) == 2:\\n continue\\n if winner == 'D':\\n D += 1\\n if winner == 'P':\\n P += 1\\nprint(f'{D}:{P}')\"\n },\n {\n \"alpha_fraction\": 0.3870967626571655,\n \"alphanum_fraction\": 0.4516128897666931,\n \"avg_line_length\": 20.375,\n \"blob_id\": \"c9bdb0a33128ceb90ede7a41c189981ae3e75802\",\n \"content_id\": \"ab0aab0acc44229549a72e9e0d9b861cd995c308\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 341,\n \"license_type\": \"no_license\",\n \"max_line_length\": 35,\n \"num_lines\": 16,\n \"path\": \"/알고리즘/온라인저지/2022/07/0731/파스칼 삼각형.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"R, C, W = map(int, input().split())\\nN = R+W-1\\nP = [[1], [1, 1], [1, 2, 1]]\\nfor n in range(N-3):\\n tmp = [0] * (2+n)\\n for i in range(len(P[-1])-1):\\n tmp[i] = sum(P[-1][i:i+2])\\n tmp = [1]+tmp+[1]\\n P.append(tmp)\\nresult = 0\\nj = 0\\nfor i in range(R-1, N):\\n j += 1\\n tmp = P[i][C-1:C+j-1]\\n result += sum(tmp)\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.43581080436706543,\n \"alphanum_fraction\": 0.5033783912658691,\n \"avg_line_length\": 20.214284896850586,\n \"blob_id\": \"d34ad401d79957409e2f9384ac3a6c2b50601d45\",\n \"content_id\": \"23ca1b22d73d24a849b947d78375cc4a95902b19\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 296,\n \"license_type\": \"no_license\",\n \"max_line_length\": 44,\n \"num_lines\": 14,\n \"path\": \"/알고리즘/온라인저지/2022/09/0925/돌 게임 3.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\n\\nN = int(input().rstrip())\\ndp = [0, 1, 0, 1, 1] + [0]*(N-4)\\nif N>4:\\n for i in range(5, N+1):\\n if 0 in [dp[i-1], dp[i-3], dp[i-4]]:\\n dp[i] = 1\\n else: dp[i] = 0\\nprint('SK' if dp[N] else 'CY')\\n\\n# https://www.acmicpc.net/problem/9657\"\n },\n {\n \"alpha_fraction\": 0.39919355511665344,\n \"alphanum_fraction\": 0.4193548262119293,\n \"avg_line_length\": 14.5625,\n \"blob_id\": \"efbd15895c22a7437250e6a8eafe2b23e548af02\",\n \"content_id\": \"dd07afe1f4b9026444310f745d0b58ae8c0d13cc\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 248,\n \"license_type\": \"no_license\",\n \"max_line_length\": 42,\n \"num_lines\": 16,\n \"path\": \"/알고리즘/온라인저지/2022/02/0220/짝수를 찾아라.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"T = int(input())\\n\\nfor t in range(T):\\n nums = list(map(int, input().split()))\\n\\n minn = 100\\n summ = 0\\n\\n for n in nums:\\n if not n%2:\\n summ += n\\n\\n if n < minn:\\n minn = n\\n \\n print(summ, minn)\"\n },\n {\n \"alpha_fraction\": 0.5467422008514404,\n \"alphanum_fraction\": 0.5524079203605652,\n \"avg_line_length\": 22.600000381469727,\n \"blob_id\": \"c4ac5f8d81323f084109d8e0e2ac0a7dc8e905ab\",\n \"content_id\": \"a54067bdd6c3a28c7e50cef89bb8648b0ba6c1fb\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 397,\n \"license_type\": \"no_license\",\n \"max_line_length\": 58,\n \"num_lines\": 15,\n \"path\": \"/알고리즘/온라인저지/2022/08/0802/자료구조는 정말 최고야.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\n\\nN, M = map(int, input().split())\\nresult = True\\nfor _ in range(M):\\n K = int(input())\\n B = list(map(int, input().split()))\\n for k in range(K-1):\\n if B[k] < B[k+1]: # 한 권의 책이라도 오름차순이 아니면 정답이 될 수 없다\\n result = False\\n break\\n if not result: break\\nprint('Yes' if result else 'No')\"\n },\n {\n \"alpha_fraction\": 0.418552041053772,\n \"alphanum_fraction\": 0.4570135772228241,\n \"avg_line_length\": 16.038461685180664,\n \"blob_id\": \"0b3dfddd6de5acc67b7869a1dafdd86d247f16d2\",\n \"content_id\": \"310402c0c2607f5acf7688e4af97e67a39fa1429\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 442,\n \"license_type\": \"no_license\",\n \"max_line_length\": 38,\n \"num_lines\": 26,\n \"path\": \"/알고리즘/온라인저지/2022/02/0203/소수 찾기.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"dp = [False, False] + [True] * (999)\\nprimes = []\\n\\nfor i in range(2, 1001):\\n if dp[i]:\\n primes.append(i)\\n for j in range(i*2, 1001, i):\\n dp[j] = False\\n\\nN = int(input())\\nnums = list(map(int, input().split()))\\n\\nmaxx = nums[-1]\\nresult = 0\\n\\nfor p in primes:\\n for n in nums:\\n if n == p:\\n if n == 1:\\n continue\\n result += 1\\n \\n if p == maxx:\\n break\\n\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.41428571939468384,\n \"alphanum_fraction\": 0.4285714328289032,\n \"avg_line_length\": 13.199999809265137,\n \"blob_id\": \"993788a65893448161bc850bcac60ff23afac79d\",\n \"content_id\": \"4b574b750852b72afc2588711880588e64e9379a\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 70,\n \"license_type\": \"no_license\",\n \"max_line_length\": 20,\n \"num_lines\": 5,\n \"path\": \"/알고리즘/온라인저지/2022/01/0131/별 찍기 - 3.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = M = int(input())\\n\\nfor i in range(N):\\n print('*' * M)\\n M -= 1\"\n },\n {\n \"alpha_fraction\": 0.6212121248245239,\n \"alphanum_fraction\": 0.6287878751754761,\n \"avg_line_length\": 25.600000381469727,\n \"blob_id\": \"cf77ef42934391e16653138c272e94e4b245edea\",\n \"content_id\": \"66b8ce8a746125ab664c56802df919e6f6bc0b3d\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 132,\n \"license_type\": \"no_license\",\n \"max_line_length\": 40,\n \"num_lines\": 5,\n \"path\": \"/알고리즘/온라인저지/2022/06/0625/이항 계수 1.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from math import factorial as fact\\n\\nN, K = map(int, input().split())\\nresult = fact(N) / (fact(K) * fact(N-K))\\nprint(f'{result:.0f}')\"\n },\n {\n \"alpha_fraction\": 0.40361446142196655,\n \"alphanum_fraction\": 0.42168673872947693,\n \"avg_line_length\": 10.928571701049805,\n \"blob_id\": \"f002b8fc3503a1d4e74d0c0f5b29250e384a1869\",\n \"content_id\": \"f4d09a223421acb7db97d10c7ae83dd010353439\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 166,\n \"license_type\": \"no_license\",\n \"max_line_length\": 36,\n \"num_lines\": 14,\n \"path\": \"/알고리즘/온라인저지/2021/12/1216/주사위 게임 2.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = int(input())\\n\\nA = B = 100\\n\\nfor n in range(N):\\n a, b = map(int, input().split())\\n\\n if a > b:\\n B -= a\\n elif b > a:\\n A -= b\\n\\nprint(A)\\nprint(B)\"\n },\n {\n \"alpha_fraction\": 0.4909090995788574,\n \"alphanum_fraction\": 0.5272727012634277,\n \"avg_line_length\": 17.66666603088379,\n \"blob_id\": \"17143390e1734347d223ecd4b828b1b0d21b3177\",\n \"content_id\": \"3ec6307de83f70a53933e5bd90ae5250f0e33040\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 55,\n \"license_type\": \"no_license\",\n \"max_line_length\": 25,\n \"num_lines\": 3,\n \"path\": \"/알고리즘/온라인저지/2021/08/0822/기찍 N.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = int(input())\\nfor n in range(N, 0, -1):\\n print(n)\"\n },\n {\n \"alpha_fraction\": 0.5445544719696045,\n \"alphanum_fraction\": 0.5742574334144592,\n \"avg_line_length\": 16,\n \"blob_id\": \"c6a6bdba710f5fd9a949e0adb74d3505714ec50e\",\n \"content_id\": \"d4d356d755423560fb45b3bcdba82517e472e134\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 101,\n \"license_type\": \"no_license\",\n \"max_line_length\": 21,\n \"num_lines\": 6,\n \"path\": \"/알고리즘/온라인저지/2023/05/0509/三方比較 (Three-Way Comparison).py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"result = 0\\nA = int(input())\\nB = int(input())\\nif A < B: result = -1\\nif A > B: result = 1\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.4621676802635193,\n \"alphanum_fraction\": 0.5296523571014404,\n \"avg_line_length\": 26.22222137451172,\n \"blob_id\": \"5ac9a8334f81fa4079428604e8bb436a4127eca3\",\n \"content_id\": \"7416bc3d3b07ee580bc527a30a664b7d45568178\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 489,\n \"license_type\": \"no_license\",\n \"max_line_length\": 54,\n \"num_lines\": 18,\n \"path\": \"/알고리즘/온라인저지/2022/10/1016/나는 학급회장이다.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\n\\nresult = [[0]*5 for _ in range(3)]\\nfor i in range(3): result[i][4] = i+1\\nfor _ in range(int(input().rstrip())):\\n A, B, C = map(int, input().rstrip().split())\\n result[0][0] += A\\n result[1][0] += B\\n result[2][0] += C\\n result[0][A] += 1\\n result[1][B] += 1\\n result[2][C] += 1\\nresult.sort(key=lambda x:(-x[0], -x[3], -x[2], -x[1]))\\nif result[0][:4] == result[1][:4]:\\n print(0, result[0][0])\\nelse: print(result[0][4], result[0][0])\"\n },\n {\n \"alpha_fraction\": 0.5081080794334412,\n \"alphanum_fraction\": 0.545945942401886,\n \"avg_line_length\": 22.25,\n \"blob_id\": \"8e3f1ae768f3bf09c28efd483b8ac96d76d964d7\",\n \"content_id\": \"58ee747b1b6bae1d668fcc49b468f6802f49b1e7\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 185,\n \"license_type\": \"no_license\",\n \"max_line_length\": 37,\n \"num_lines\": 8,\n \"path\": \"/알고리즘/온라인저지/2023/06/0607/모비스.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"S = input()\\nresult = 0\\nif 'M' in S: result += 1\\nif 'O' in S: result += 1\\nif 'B' in S: result += 1\\nif 'I' in S: result += 1\\nif 'S' in S: result += 1\\nprint('YES' if result == 5 else 'NO')\"\n },\n {\n \"alpha_fraction\": 0.277688592672348,\n \"alphanum_fraction\": 0.29293739795684814,\n \"avg_line_length\": 24.97916603088379,\n \"blob_id\": \"bafc2ddff1439b35f011ee518a59a217e03cc984\",\n \"content_id\": \"6e7e31b0968b078ae81d32a5d3ac8a00c6ff175d\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1256,\n \"license_type\": \"no_license\",\n \"max_line_length\": 54,\n \"num_lines\": 48,\n \"path\": \"/알고리즘/온라인저지/2022/06/0611/양.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from collections import deque\\nimport sys\\n\\ninput = sys.stdin.readline\\n\\nR, C = map(int, input().split())\\narr = []\\nfor _ in range(R):\\n tmp = list(input())\\n arr.append(tmp)\\n\\ndx = [-1, 1, 0, 0]\\ndy = [0, 0, -1, 1]\\nq = deque()\\nV = O = 0\\n\\nfor r in range(R): # 행\\n for c in range(C): # 열\\n if arr[r][c] in '.vo': # BFS\\n q.append((r, c))\\n v = o = 0\\n while q:\\n tmp = q.popleft()\\n y, x = tmp[0], tmp[1]\\n if arr[y][x] != '1':\\n if arr[y][x] == 'o':\\n o += 1\\n elif arr[y][x] == 'v':\\n v += 1\\n arr[y][x] = '1'\\n for i in range(4):\\n ny = y+dy[i]\\n nx = x+dx[i]\\n try:\\n if arr[ny][nx] in '.vo':\\n if arr[ny][nx] != '1':\\n if (ny, nx) not in q:\\n q.append((ny, nx))\\n except:\\n q = deque()\\n v = o = 0\\n # print(o, v) # 디버깅\\n if o > v:\\n O += o\\n else:\\n V += v\\n\\nprint(O, V)\"\n },\n {\n \"alpha_fraction\": 0.4951830506324768,\n \"alphanum_fraction\": 0.5202311873435974,\n \"avg_line_length\": 33.63333511352539,\n \"blob_id\": \"f17e6b03692ec2f3ad72fed33bf42c063daa9128\",\n \"content_id\": \"0be5c3cda7c4887a139e317b7e36412d0ee6abc1\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1330,\n \"license_type\": \"no_license\",\n \"max_line_length\": 61,\n \"num_lines\": 30,\n \"path\": \"/알고리즘/온라인저지/2022/09/0912/토마토.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from collections import deque # BFS\\n\\ndy, dx = [-1, 1, 0, 0], [0, 0, -1, 1] # delta 이동\\nM, N = map(int, input().split()) # M부터 받는 거, 낚시 주의\\narr = [list(map(int, input().split())) for _ in range(N)]\\nQ = deque()\\nfor i in range(N):\\n for j in range(M):\\n if arr[i][j] == 1: # 첫 날 토마토인 좌표들 추가\\n Q.append((i, j, 0)) # y, x, day\\n arr[i][j] = 0\\nresult = 0\\nwhile Q: # BFS\\n y, x, day = Q.popleft() # day를 추가하면서 가장 마지막에 나온 day를 잡을 것\\n if arr[y][x] == 1: continue # 다른 토마토를 통해서 이미 익은 토마토\\n arr[y][x] = 1 # 잘 익은 토마토\\n result = max(result, day) # 더 오랜시간이 걸려서 익은 토마토가 있으면 갱신\\n for i in range(4):\\n ny, nx = y+dy[i], x+dx[i] # 전후좌우 토마토\\n if 0<=ny<N and 0<=nx<M and arr[ny][nx] == 0:\\n Q.append((ny, nx, day+1)) # 다음 날에 이 토마토는 익는다\\nfor i in range(N):\\n if result == -1: break # 모든 토마토가 익을 수 없었다? -> 종료\\n for j in range(M):\\n if arr[i][j] == 0: # 충분한 시간이 흘렀는데 안익은 토마토가 있다?\\n result = -1 # 모든 토마토가 익을 수 없었다\\n break\\nprint(result)\\n\\n# https://www.acmicpc.net/problem/7576\"\n },\n {\n \"alpha_fraction\": 0.3545454442501068,\n \"alphanum_fraction\": 0.40303030610084534,\n \"avg_line_length\": 18.352941513061523,\n \"blob_id\": \"9c63da119c55bc957be00ccfc650158f112da147\",\n \"content_id\": \"617f9913e5a8ae33d082b78caa663dd45d70d51f\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 330,\n \"license_type\": \"no_license\",\n \"max_line_length\": 24,\n \"num_lines\": 17,\n \"path\": \"/알고리즘/온라인저지/2022/04/0417/공백 없는 A+B.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"num = input()\\nA = B = 0\\nif len(num) == 2:\\n A = int(num[0])\\n B = int(num[1])\\nelif len(num) == 3:\\n if num[1] == '0':\\n A = int(num[:2])\\n B = int(num[-1])\\n elif num[-1] == '0':\\n A = int(num[0])\\n B = int(num[1:])\\nelse: # len 4\\n A = int(num[:2])\\n B = int(num[2:])\\n# print(A, B)\\nprint(A+B)\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.5306122303009033,\n \"alphanum_fraction\": 0.5510203838348389,\n \"avg_line_length\": 10,\n \"blob_id\": \"97baab3aa42d5e126377dcf6a3ce81e63ce6bcf5\",\n \"content_id\": \"b43d26137f3c389b8232c4f3486e8ed2e2628841\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 98,\n \"license_type\": \"no_license\",\n \"max_line_length\": 20,\n \"num_lines\": 9,\n \"path\": \"/알고리즘/온라인저지/2022/02/0205/모음의 개수.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"result = 0\\n\\ntext = input()\\n\\nfor t in text:\\n if t in 'aeiou':\\n result += 1\\n\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.43478259444236755,\n \"alphanum_fraction\": 0.4434782564640045,\n \"avg_line_length\": 15.571428298950195,\n \"blob_id\": \"85e388e17493395c68fa2abaa35a5bf9f0f9bc77\",\n \"content_id\": \"8b63a298555ad7ee477415ec8b5ee13953082307\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 115,\n \"license_type\": \"no_license\",\n \"max_line_length\": 32,\n \"num_lines\": 7,\n \"path\": \"/알고리즘/온라인저지/2021/08/0825/최대공약수와 최소공배수.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"a, b = map(int, input().split())\\nc, d = a, b\\nwhile a % b != 0:\\n a, b = b, a % b\\n\\nprint(b)\\nprint(b*(c//b)*(d//b))\"\n },\n {\n \"alpha_fraction\": 0.5570470094680786,\n \"alphanum_fraction\": 0.5973154306411743,\n \"avg_line_length\": 20.428571701049805,\n \"blob_id\": \"b76e6691b5004590fe6901e5ca007a58669ba7fe\",\n \"content_id\": \"362251c1e4598117dae8c927a5a94400a43d6b4e\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 149,\n \"license_type\": \"no_license\",\n \"max_line_length\": 37,\n \"num_lines\": 7,\n \"path\": \"/알고리즘/온라인저지/2022/02/0220/콘테스트.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"W = [int(input()) for _ in range(10)]\\nK = [int(input()) for _ in range(10)]\\n\\nW.sort(reverse=True)\\nK.sort(reverse=True)\\n\\nprint(sum(W[:3]), sum(K[:3]))\"\n },\n {\n \"alpha_fraction\": 0.42105263471603394,\n \"alphanum_fraction\": 0.6736842393875122,\n \"avg_line_length\": 15,\n \"blob_id\": \"77117f5b7f31de18c79563c19a8512036e56c7a4\",\n \"content_id\": \"36788e9fa08a24afc2ea3f0c0afdc92e8899f6d9\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 95,\n \"license_type\": \"no_license\",\n \"max_line_length\": 41,\n \"num_lines\": 6,\n \"path\": \"/알고리즘/SWEA/LEARN/Course/1. Programming Beginner/파이썬 프로그래밍 기초(2)/25차시 2. 자료구조 – 리스트, 튜플 - 연습문제 27.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"arr = [12,24,35,24,88,120,155,88,120,155]\\n\\nresult = list(set(arr))\\n\\nresult.sort()\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.53125,\n \"alphanum_fraction\": 0.5580357313156128,\n \"avg_line_length\": 19.409090042114258,\n \"blob_id\": \"2f89ffa455e3e09160886712c6bc1a06f7a74238\",\n \"content_id\": \"a8cdbfac89b0e0f1cdd09ea909a539c73312911e\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 510,\n \"license_type\": \"no_license\",\n \"max_line_length\": 38,\n \"num_lines\": 22,\n \"path\": \"/알고리즘/온라인저지/2022/04/0402/네 번째 수.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"\\\"\\\"\\\"\\n까먹은 수의 위치\\n1. 맨 앞 or 맨 뒤\\n2. 중간\\n\\n맨 앞 or 맨 뒤 일 경우 둘 중 아무거나 편한 거 출력\\n\\\"\\\"\\\"\\nnums = list(map(int, input().split()))\\nnums.sort()\\ndiff = 1e9\\nfor i in range(1, len(nums)):\\n if nums[i] - nums[i-1] < diff:\\n diff = nums[i] - nums[i-1]\\nin_middle = False\\nresult = 0\\nfor i in range(1, len(nums)):\\n if nums[i] != nums[i-1] + diff:\\n in_middle = True\\n result = nums[i-1] + diff\\nif not in_middle:\\n result = nums[-1] + diff\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.5075757503509521,\n \"alphanum_fraction\": 0.5227272510528564,\n \"avg_line_length\": 13.777777671813965,\n \"blob_id\": \"df8187d3494e734176500ffe8819edcf2e410a68\",\n \"content_id\": \"d41dfe637a71b9781e89b03a921cbeac322cc91f\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 132,\n \"license_type\": \"no_license\",\n \"max_line_length\": 20,\n \"num_lines\": 9,\n \"path\": \"/알고리즘/온라인저지/2023/03/0326/골뱅이 찍기 - ㄷ.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = int(input())\\nA = '@'*N\\nB = A*5\\nfor i in range(N):\\n print(B)\\nfor i in range(N*3):\\n print(A)\\nfor i in range(N):\\n print(B)\"\n },\n {\n \"alpha_fraction\": 0.5315315127372742,\n \"alphanum_fraction\": 0.5525525808334351,\n \"avg_line_length\": 18.58823585510254,\n \"blob_id\": \"91e0c9b32f9686c8e6ec90e4d5ddf8199d4516d9\",\n \"content_id\": \"a27039bf792ebba55ced1dc68a1d746a01421861\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 333,\n \"license_type\": \"no_license\",\n \"max_line_length\": 51,\n \"num_lines\": 17,\n \"path\": \"/알고리즘/온라인저지/2021/10/1016/구간 합 구하기 4 .py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\nN, M = map(int, sys.stdin.readline().split())\\n\\narr = tuple(map(int, sys.stdin.readline().split()))\\n\\ntmp = [arr[0]]\\n\\nfor n in range(1, N):\\n tmp.append(arr[n]+tmp[-1])\\n\\nfor m in range(M):\\n a, b = map(int, sys.stdin.readline().split())\\n if a == 1:\\n print(tmp[b-1])\\n else:\\n print(tmp[b-1]-tmp[a-2])\\n\"\n },\n {\n \"alpha_fraction\": 0.451977401971817,\n \"alphanum_fraction\": 0.4858756959438324,\n \"avg_line_length\": 21.25,\n \"blob_id\": \"5a47f42c6a214b56e4dfd5a53dbb0e220366c8a2\",\n \"content_id\": \"ad119848ff2abb1695c4767a5289384768ab1a65\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 177,\n \"license_type\": \"no_license\",\n \"max_line_length\": 28,\n \"num_lines\": 8,\n \"path\": \"/알고리즘/온라인저지/2023/01/0114/문자가 몇갤까.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"while True:\\n tmp = input()\\n if tmp == '#': break\\n result = set()\\n for t in tmp.lower():\\n if 97<=ord(t)<97+26:\\n result.add(t)\\n print(len(result))\"\n },\n {\n \"alpha_fraction\": 0.4675324559211731,\n \"alphanum_fraction\": 0.523809552192688,\n \"avg_line_length\": 13.5,\n \"blob_id\": \"4fa98cf5e46475e07f2165b76369d734d547e0b2\",\n \"content_id\": \"0052547a85b53c9637149484ce73d605bfeecbd0\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 231,\n \"license_type\": \"no_license\",\n \"max_line_length\": 31,\n \"num_lines\": 16,\n \"path\": \"/알고리즘/온라인저지/2022/02/0201/수 정렬하기 3.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ndef input():\\n return sys.stdin.readline()\\n\\ndp = [0] * 10001\\n\\nN = int(input())\\n\\nfor n in range(N):\\n dp[int(input())] += 1\\n\\nfor i in range(1, 10001):\\n if dp[i]:\\n for j in range(dp[i]):\\n print(i)\"\n },\n {\n \"alpha_fraction\": 0.5,\n \"alphanum_fraction\": 0.5169082283973694,\n \"avg_line_length\": 16.25,\n \"blob_id\": \"03ddc92c1d87c4246b6110b11a30b348ecb5251d\",\n \"content_id\": \"65d5f04548de5f5a21507359d266348f51303281\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 414,\n \"license_type\": \"no_license\",\n \"max_line_length\": 35,\n \"num_lines\": 24,\n \"path\": \"/알고리즘/온라인저지/2022/02/0205/백설 공주와 일곱 난쟁이.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"dwarfs = []\\n\\nfor _ in range(9):\\n dwarfs.append(int(input()))\\n\\nsum_dwarfs = sum(dwarfs)\\n\\nfakes_idx = []\\n\\nfor i in range(8):\\n temp = sum_dwarfs - dwarfs[i]\\n\\n for j in range(i, 9):\\n if temp - dwarfs[j] == 100:\\n fakes_idx.append(i)\\n fakes_idx.append(j)\\n break\\n \\n if fakes_idx:\\n break\\n\\nfor i in range(9):\\n if i not in fakes_idx:\\n print(dwarfs[i])\\n\"\n },\n {\n \"alpha_fraction\": 0.3867403268814087,\n \"alphanum_fraction\": 0.4254143536090851,\n \"avg_line_length\": 19.22222137451172,\n \"blob_id\": \"b3d962521170bc06ff4b3468ce4d95aa3a4f022c\",\n \"content_id\": \"4c9ceacd5d829ddc5664eaba5028ac2603d9a683\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 181,\n \"license_type\": \"no_license\",\n \"max_line_length\": 32,\n \"num_lines\": 9,\n \"path\": \"/알고리즘/온라인저지/2023/01/0101/희주의 수학시험.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"A, B = map(int, input().split())\\narr = [0]*(B+1)\\nk = 0\\nfor i in range(1, B+1):\\n for j in range(i):\\n k += 1\\n if k <= B:\\n arr[k] = i\\nprint(sum(arr[A:B+1]))\"\n },\n {\n \"alpha_fraction\": 0.43455496430397034,\n \"alphanum_fraction\": 0.46422338485717773,\n \"avg_line_length\": 30.236364364624023,\n \"blob_id\": \"160117f4df71d0d513cd36b37dda433797558530\",\n \"content_id\": \"8ff24c71fadcbec1ff404e45dda08170959dcd0d\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1727,\n \"license_type\": \"no_license\",\n \"max_line_length\": 86,\n \"num_lines\": 55,\n \"path\": \"/알고리즘/온라인저지/2021/08/0829/경비원.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\nW, H = map(int, sys.stdin.readline().split())\\nmarket_count = int(sys.stdin.readline())\\nmarkets = []\\nfor _ in range(market_count):\\n markets.append(list(map(int, sys.stdin.readline().split())))\\ndgnswe, dgdist = map(int, sys.stdin.readline().split())\\n\\nresult = 0\\n\\nfor i in range(market_count):\\n if (markets[i][0] == 1 and dgnswe == 2) or (markets[i][0] == 2 and dgnswe == 1):\\n result += H\\n tmp1 = markets[i][1] + dgdist\\n tmp2 = W - markets[i][1] + W - dgdist\\n if tmp1 < tmp2:\\n result += tmp1\\n else:\\n result += tmp2\\n\\n elif (markets[i][0] == 3 and dgnswe == 4) or (markets[i][0] == 4 and dgnswe == 3):\\n result += W\\n tmp1 = markets[i][1] + dgdist\\n tmp2 = H - markets[i][1] + H - dgdist\\n if tmp1 < tmp2:\\n result += tmp1\\n else:\\n result += tmp2\\n\\n elif markets[i][0] == dgnswe:\\n result += abs(markets[i][1] - dgdist)\\n else: # 좌 우 일때\\n if markets[i][0] == 1:\\n if dgnswe == 3:\\n result += markets[i][1] + dgdist\\n else:\\n result += W - markets[i][1] + dgdist\\n if markets[i][0] == 2:\\n if dgnswe == 3:\\n result += markets[i][1] + H - dgdist\\n else:\\n result += W - markets[i][1] + H - dgdist\\n if markets[i][0] == 3:\\n if dgnswe == 1:\\n result += markets[i][1] + dgdist\\n else:\\n result += H - markets[i][1] + dgdist\\n if markets[i][0] == 4:\\n if dgnswe == 1:\\n result += markets[i][1] + W - dgdist\\n else:\\n result += H - markets[i][1] + W - dgdist\\n\\nprint(result)\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.45012786984443665,\n \"alphanum_fraction\": 0.46547314524650574,\n \"avg_line_length\": 28.769229888916016,\n \"blob_id\": \"446e7697ac7ac2096f66107f7341ef94dbccb03d\",\n \"content_id\": \"7c5a0d0fe753e9ed4d9219a7f75eb7b00fec577b\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 525,\n \"license_type\": \"no_license\",\n \"max_line_length\": 64,\n \"num_lines\": 13,\n \"path\": \"/알고리즘/온라인저지/2021/08/0810/캠핑.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"\\\"\\\"\\\"\\nL P V\\nresult = (V//P) * L\\\"\\\"\\\"\\ncount = 0\\nwhile True:\\n L, P, V = map(int, input().split()) # 각각 변수를 입력받고\\n count += 1 # Case count: ? 출력해줄 count변수\\n if L + P + V == 0: # 마지막항으로 0 0 0 들어오면\\n break # 종료\\n C = V - ((V//P) * P) # 다 나눠주고 나머지 더할 상수 C\\n if C > L: # C가 L보다 크면\\n C = L # L보다 클 때 모두 다 C로 치환\\n print(f'Case {count}: {((V//P) * L) + C}') # 테스트케이스마다 결과값 출력\\n \"\n },\n {\n \"alpha_fraction\": 0.5040983557701111,\n \"alphanum_fraction\": 0.5778688788414001,\n \"avg_line_length\": 29.625,\n \"blob_id\": \"f002a95df185def78ebdffd781308f50f2a3ee37\",\n \"content_id\": \"52394af2094eb192267b99647699d67250dc441d\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 244,\n \"license_type\": \"no_license\",\n \"max_line_length\": 117,\n \"num_lines\": 8,\n \"path\": \"/알고리즘/온라인저지/2022/08/0830/Speed fines are not fine!.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"F = [100, 270, 500] # fine\\nA = int(input())\\nB = int(input())\\ni = 0\\nif B > A:\\n if 21<=B-A<=30: i = 1\\n elif 31<=B-A: i = 2\\nprint(f'You are speeding and your fine is ${F[i]}.' if B > A else 'Congratulations, you are within the speed limit!')\"\n },\n {\n \"alpha_fraction\": 0.39175257086753845,\n \"alphanum_fraction\": 0.4192439913749695,\n \"avg_line_length\": 16.176469802856445,\n \"blob_id\": \"ed2874f1dcf496dcc51c17fa419800b27e7c0b6d\",\n \"content_id\": \"446a9e3bef8d5b453b6d9520d4ba5c4d0bcf24c4\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 291,\n \"license_type\": \"no_license\",\n \"max_line_length\": 36,\n \"num_lines\": 17,\n \"path\": \"/알고리즘/온라인저지/2023/04/0401/루트.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"while True:\\n B, N = map(int, input().split())\\n \\n if B == 0 and N == 0: break\\n\\n minn = int(1e9)\\n result = 0\\n\\n for A in range(1, int(1e9)):\\n D = abs(B - A**N)\\n\\n if D < minn: \\n minn = D\\n result = A\\n else: break\\n \\n print(result)\"\n },\n {\n \"alpha_fraction\": 0.6292682886123657,\n \"alphanum_fraction\": 0.6536585092544556,\n \"avg_line_length\": 16.16666603088379,\n \"blob_id\": \"0622a76f978d8e7406aa818fb617ba1f12793709\",\n \"content_id\": \"2da5655f4a4edcb70340d2633538e1fe8a53b360\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 205,\n \"license_type\": \"no_license\",\n \"max_line_length\": 47,\n \"num_lines\": 12,\n \"path\": \"/알고리즘/온라인저지/2022/11/1125/거리의 합.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\n\\ninput()\\nnums = list(map(int, input().rstrip().split()))\\nnums.sort()\\nresult = 0\\nfor num1 in nums:\\n for num2 in nums:\\n result += abs(num1-num2)\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.5130434632301331,\n \"alphanum_fraction\": 0.5565217137336731,\n \"avg_line_length\": 11.88888931274414,\n \"blob_id\": \"095f712f4bdab121946e0ccf6b7f8f3758d1452f\",\n \"content_id\": \"666082decbae1fa6b676961515c6a8fa3a738e34\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 115,\n \"license_type\": \"no_license\",\n \"max_line_length\": 29,\n \"num_lines\": 9,\n \"path\": \"/알고리즘/온라인저지/2021/08/0828/벌집.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\nN = int(sys.stdin.readline())\\n\\nlayer = 1\\ni = 1\\nwhile layer < N:\\n i += 1\\n layer += (i-1)*6\\nprint(i)\"\n },\n {\n \"alpha_fraction\": 0.43478259444236755,\n \"alphanum_fraction\": 0.54347825050354,\n \"avg_line_length\": 46,\n \"blob_id\": \"57a13229b5ab104a9c7e8a75bd8498aea806ec71\",\n \"content_id\": \"387239b75a8a35bab4d8dbe592b107a40f5c5773\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 46,\n \"license_type\": \"no_license\",\n \"max_line_length\": 46,\n \"num_lines\": 1,\n \"path\": \"/알고리즘/온라인저지/2022/03/0312/17배.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"print(str(bin(int('0b'+input(), 2) * 17))[2:])\"\n },\n {\n \"alpha_fraction\": 0.3802816867828369,\n \"alphanum_fraction\": 0.44014084339141846,\n \"avg_line_length\": 34.5,\n \"blob_id\": \"2dd58aa7f1183cf3655b36e1fdeb81b82d1abecb\",\n \"content_id\": \"15227be07a035cf18de054f870a233abb5ad9b26\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 310,\n \"license_type\": \"no_license\",\n \"max_line_length\": 78,\n \"num_lines\": 8,\n \"path\": \"/알고리즘/[템플릿]/정렬/버블 정렬.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"arr = [55, 7, 42, 78, 12]\\nfor i in range(len(arr)-1, 0, -1):\\n for j in range(i):\\n print(i, j)\\n if arr[j] > arr[j+1]:\\n print(f'{arr[j]}가 {arr[j+1]}보다 크므로, {arr[j]}와 {arr[j+1]}의 자리를 변경')\\n arr[j], arr[j+1] = arr[j+1], arr[j]\\n print(arr)\\n\"\n },\n {\n \"alpha_fraction\": 0.4858657121658325,\n \"alphanum_fraction\": 0.5141342878341675,\n \"avg_line_length\": 19.25,\n \"blob_id\": \"2bf6936e97abd2cf4806a845e9944f0e55fa0e92\",\n \"content_id\": \"be871ee39f58ec47c01000e610e51c7aa65c2ec1\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 566,\n \"license_type\": \"no_license\",\n \"max_line_length\": 73,\n \"num_lines\": 28,\n \"path\": \"/알고리즘/온라인저지/2022/09/0917/못생긴 수.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\nfrom heapq import heappush, heappop\\n\\ninput = sys.stdin.readline\\n\\ndef ugly(num):\\n result = 0\\n HQ = []\\n heappush(HQ, 1)\\n cnt = 0\\n while HQ:\\n num = heappop(HQ)\\n cnt += 1\\n if cnt == N: \\n result = num\\n break\\n for i in (2, 3, 5):\\n next = num*i\\n if next not in HQ:\\n heappush(HQ, next)\\n return result\\n\\nwhile True:\\n N = int(input().rstrip())\\n if N == 0: break\\n print(ugly(N))\\n\\n# http://www.jungol.co.kr/bbs/board.php?bo_table=pbank&code=1318&sca=4030\"\n },\n {\n \"alpha_fraction\": 0.44291090965270996,\n \"alphanum_fraction\": 0.4667503237724304,\n \"avg_line_length\": 22.47058868408203,\n \"blob_id\": \"39f1d9e4f85fb5217bce6039082cf1f6dac70d74\",\n \"content_id\": \"5a55d484521baf7231fbf186721e319274676f52\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 819,\n \"license_type\": \"no_license\",\n \"max_line_length\": 49,\n \"num_lines\": 34,\n \"path\": \"/알고리즘/[템플릿]/문자열 탐색/KMP 알고리즘/찾기.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\n\\ndef get_pi(pattern):\\n j = 0\\n for i in range(1, len(pattern)):\\n while j > 0 and pattern[i] != pattern[j]:\\n j = pi[j-1]\\n if pattern[i] == pattern[j]:\\n j += 1\\n pi[i] = j\\n\\ndef KMP(string, pattern):\\n get_pi(pattern)\\n j = 0\\n for i in range(len(string)):\\n while j > 0 and string[i] != pattern[j]:\\n j = pi[j-1]\\n if string[i] == pattern[j]:\\n if j == len(pattern)-1:\\n result.append(i-j+1)\\n result[0] += 1\\n j = pi[j] # 다음 패턴 찾는 인덱싱 주의\\n else:\\n j += 1\\n\\nS, P = input().rstrip(), input().rstrip()\\npi = [0] * len(P)\\nresult = [0]\\nKMP(S, P)\\nfor r in result: print(r)\\n\\n# https://www.acmicpc.net/problem/1786\"\n },\n {\n \"alpha_fraction\": 0.4868420958518982,\n \"alphanum_fraction\": 0.5065789222717285,\n \"avg_line_length\": 14.947368621826172,\n \"blob_id\": \"8ff6c20589f8934c9be0b7aadaf60440e9c38872\",\n \"content_id\": \"dc6371fd5843b3f992ba1f6c0ffb912bd97e3c2d\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 304,\n \"license_type\": \"no_license\",\n \"max_line_length\": 74,\n \"num_lines\": 19,\n \"path\": \"/알고리즘/온라인저지/2022/02/0201/덩치.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = int(input())\\n\\nwnhs = []\\n\\nresult = []\\n\\nfor n in range(N):\\n wnhs.append(tuple(map(int, input().split())))\\n\\nfor i in range(N):\\n cnt = 1\\n\\n for j in range(N):\\n if i != j and wnhs[i][0] < wnhs[j][0] and wnhs[i][1] < wnhs[j][1]:\\n cnt += 1\\n\\n result.append(cnt)\\n\\nprint(*result)\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.47752809524536133,\n \"alphanum_fraction\": 0.5,\n \"avg_line_length\": 18.83333396911621,\n \"blob_id\": \"7b250ef340653b42f12db4340c6720cd27c8e1a5\",\n \"content_id\": \"31fd26b84973f5933fabb7aca107357696aab2ae\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 356,\n \"license_type\": \"no_license\",\n \"max_line_length\": 41,\n \"num_lines\": 18,\n \"path\": \"/알고리즘/온라인저지/2022/10/1028/기숙사 바닥.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\n\\nR, B = map(int, input().rstrip().split())\\ndivisors = []\\nfor i in range(1, int((R+B)**0.5+1)):\\n if not (R+B)%i:\\n divisors.append((i, (R+B)//i))\\nfor divisor in divisors:\\n W, L = divisor\\n red = 0\\n if W > 1:\\n red += (W+L-2)*2\\n else: red = L\\n if red == R:\\n print(L, W)\\n break\"\n },\n {\n \"alpha_fraction\": 0.5775076150894165,\n \"alphanum_fraction\": 0.6003039479255676,\n \"avg_line_length\": 22.535715103149414,\n \"blob_id\": \"84cea56092292d36844c6845260b465ec6f6bf50\",\n \"content_id\": \"a4ffcf7764b8d5b1c3f6a76659bb0d5702aefdcf\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1008,\n \"license_type\": \"no_license\",\n \"max_line_length\": 53,\n \"num_lines\": 28,\n \"path\": \"/알고리즘/온라인저지/2022/10/1023/태상이의 훈련소 생활.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\n\\nN, M = map(int, input().rstrip().split())\\narr = list(map(int, input().rstrip().split()))\\nacc = [0]*(N+1)\\nfor m in range(M):\\n a, b, k = map(int, input().rstrip().split())\\n acc[a-1] += k\\n acc[b] -= k\\ndp = [0]*(N+1)\\ndp[0] = acc[0]\\nfor i in range(1, N+1):\\n dp[i] = dp[i-1] + acc[i]\\n print(arr[i-1] + dp[i-1], end=' ')\\n\\n\\\"\\\"\\\"\\n누적합 배열인 acc를 생성한다\\nacc에는 누적합의 시작과 끝만 들어있으며\\n누적합이 시작될 때 k만큼 더했다가 끝나면서 k만큼 빼준다\\n현재 누적합은 변수로 가지고 있지는 않고\\n전에 계산한 누적합(dp[i-1])을 불러와서 acc[i]와 더한다\\nacc[i]가 0일 경우, 이전 누적합을 그대로 사용하며 그 값은 dp[i-1]에 같이 들어있다\\n해당 누적합이 종료되는 경우 k만큼 빼주어 해당 누적합을 종료한다\\ndp에 들어있는 값은 m줄 만큼 들어온 입력들의 누적합이며\\n이를 원 배열과 합한 결과를 출력한다\\n\\\"\\\"\\\"\"\n },\n {\n \"alpha_fraction\": 0.4058355391025543,\n \"alphanum_fraction\": 0.48275861144065857,\n \"avg_line_length\": 22.625,\n \"blob_id\": \"abf13c9c74924b326531475eb19cb10d728c874d\",\n \"content_id\": \"aaddab8f944d7d10ef549937cf24166b4b49f8ce\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 377,\n \"license_type\": \"no_license\",\n \"max_line_length\": 49,\n \"num_lines\": 16,\n \"path\": \"/알고리즘/온라인저지/2022/10/1003/달나라 토끼를 위한 구매대금 지불 도우미.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\nINF = int(1e9)\\n\\nN = int(input().rstrip())\\ndp = [INF]*(int(1e5)+10)\\ndp[0], dp[1], dp[2], dp[5], dp[7] = 0, 1, 1, 1, 1\\nfor i in range(1, int(1e5)+1):\\n tmp = dp[i]+1\\n if dp[i]:\\n dp[i+1] = min(dp[i+1], tmp)\\n dp[i+2] = min(dp[i+2], tmp) \\n dp[i+5] = min(dp[i+5], tmp) \\n dp[i+7] = min(dp[i+7], tmp)\\nprint(dp[N])\"\n },\n {\n \"alpha_fraction\": 0.46932005882263184,\n \"alphanum_fraction\": 0.5107794404029846,\n \"avg_line_length\": 34.52941131591797,\n \"blob_id\": \"610a8a13dd70da3a712496e2a80da51279831284\",\n \"content_id\": \"65180dab07673799bfc7fcca60b0c9f2e58a7576\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 775,\n \"license_type\": \"no_license\",\n \"max_line_length\": 80,\n \"num_lines\": 17,\n \"path\": \"/알고리즘/온라인저지/2022/10/1020/개미.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N, M = map(int, input().split())\\nants1, ants2 = list(input()), list(input())\\nT = int(input())\\narr = []\\nfor i in range(N): arr.append((ants1[::-1][i], 1)) # 오른쪽으로 가려고 함, 배열이 뒤집히는 점에 주의\\nfor i in range(M): arr.append((ants2[i], -1)) # 왼쪽으로 가려고 함\\ntime = 0\\nwhile time < T: # T초동안 움직일 것\\n time += 1\\n i = 0\\n while i < N+M-1:\\n ant1, ant2 = arr[i], arr[i+1]\\n if ant1[1] == 1 and ant2[1] == -1: # 진행하려는 방향이 교차하는 경우\\n arr[i], arr[i+1] = arr[i+1], arr[i] # 서로 자리를 바꿔준다 == 두 개미중 하나가 점프\\n i += 1 # 인덱스 추가로 하나 더 늘려주기\\n i += 1 # 다음 개미 탐색\\nfor a in arr: print(a[0], end='')\"\n },\n {\n \"alpha_fraction\": 0.5675675868988037,\n \"alphanum_fraction\": 0.5945945978164673,\n \"avg_line_length\": 74,\n \"blob_id\": \"40d124aa2870a85ba5367356709e60c92989de1f\",\n \"content_id\": \"86918264e4c5bda9ca7d40c6bdf7dc64a47d3187\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 74,\n \"license_type\": \"no_license\",\n \"max_line_length\": 74,\n \"num_lines\": 1,\n \"path\": \"/알고리즘/온라인저지/2022/08/0825/성택이의 은밀한 비밀번호.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"for _ in range(int(input())): print('yes' if 6<=len(input())<=9 else 'no')\"\n },\n {\n \"alpha_fraction\": 0.4747474789619446,\n \"alphanum_fraction\": 0.49494948983192444,\n \"avg_line_length\": 18.899999618530273,\n \"blob_id\": \"1c0a2e49b87e3d5c3f0785a2ce2a4c93e9fa697e\",\n \"content_id\": \"32578c8e1c7aa32ef2419038fb4d8ffe2ff6452c\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 198,\n \"license_type\": \"no_license\",\n \"max_line_length\": 33,\n \"num_lines\": 10,\n \"path\": \"/알고리즘/온라인저지/2022/09/0909/지영 공주님의 마법 거울.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = int(input())\\narr = [input() for _ in range(N)]\\nK = int(input())\\nif K == 1:\\n for a in arr: print(a)\\nelif K == 2:\\n for a in arr: print(a[::-1])\\nelse:\\n for a in arr[::-1]:\\n print(a)\"\n },\n {\n \"alpha_fraction\": 0.5416666865348816,\n \"alphanum_fraction\": 0.5625,\n \"avg_line_length\": 25.272727966308594,\n \"blob_id\": \"2b053e33c44bc7540abf65a19ec323e070c2f6a4\",\n \"content_id\": \"7718290e102e87952bb763a9dbd9108e39859964\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 288,\n \"license_type\": \"no_license\",\n \"max_line_length\": 51,\n \"num_lines\": 11,\n \"path\": \"/알고리즘/온라인저지/2022/11/1105/해밍 거리.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\n\\nfor _ in range(int(input().rstrip())):\\n nums = [input().rstrip() for i in range(2)]\\n result = 0\\n for i in range(len(nums[0])):\\n if nums[0][i] != nums[1][i]:\\n result += 1\\n print('Hamming distance is {}.'.format(result))\"\n },\n {\n \"alpha_fraction\": 0.5492957830429077,\n \"alphanum_fraction\": 0.577464759349823,\n \"avg_line_length\": 13.300000190734863,\n \"blob_id\": \"3b10d57aa2c43d315707e48a469db74632d0d66f\",\n \"content_id\": \"3d37083c698ecfb2c734b2d116847979d0008758\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 142,\n \"license_type\": \"no_license\",\n \"max_line_length\": 29,\n \"num_lines\": 10,\n \"path\": \"/알고리즘/온라인저지/2023/02/0218/회문은 회문아니야!!.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\n\\nS = input().strip()\\nl = len(S)\\n\\nif S == S[0]*l: print(-1)\\nelif S == S[::-1]: print(l-1)\\nelse: print(l)\"\n },\n {\n \"alpha_fraction\": 0.47413793206214905,\n \"alphanum_fraction\": 0.47413793206214905,\n \"avg_line_length\": 28.08333396911621,\n \"blob_id\": \"5e68bcf6566601e625145a08f22f84697f7cd385\",\n \"content_id\": \"d4d32e30008f31dbad65eea6317ea51f505c6075\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 348,\n \"license_type\": \"no_license\",\n \"max_line_length\": 60,\n \"num_lines\": 12,\n \"path\": \"/알고리즘/온라인저지/2022/12/1224/사칙연산.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"for _ in range(int(input())):\\n A, ope, B, equal, answer = input().split()\\n A, B, answer = map(int, [A, B, answer])\\n if ope == '+':\\n result = A+B\\n elif ope == '-':\\n result = A-B\\n elif ope == '*':\\n result = A*B\\n elif ope == '/':\\n result = A//B\\n print('correct' if result == answer else 'wrong answer')\"\n },\n {\n \"alpha_fraction\": 0.5234899520874023,\n \"alphanum_fraction\": 0.5335570573806763,\n \"avg_line_length\": 18.933332443237305,\n \"blob_id\": \"521c7e12f97e690cafe762e9124f0230edd96e98\",\n \"content_id\": \"12a5ef32ee62cacd54ea0a33308d0f845a02c54f\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 298,\n \"license_type\": \"no_license\",\n \"max_line_length\": 40,\n \"num_lines\": 15,\n \"path\": \"/알고리즘/온라인저지/2022/10/1026/유진수.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\n\\nN = input().rstrip()\\nflag = False\\nfor i in range(1, len(N)):\\n A, B = N[:i], N[i:]\\n front, rear = 1, 1\\n for a in A:\\n front *= int(a)\\n for b in B:\\n rear *= int(b)\\n if front == rear: flag = True; break\\nprint('YES' if flag else 'NO')\"\n },\n {\n \"alpha_fraction\": 0.44718310236930847,\n \"alphanum_fraction\": 0.5211267471313477,\n \"avg_line_length\": 12.571428298950195,\n \"blob_id\": \"de3c948ae43b86f88aa5127864984822b76bf77b\",\n \"content_id\": \"207f6e5660aa28ae440eaf3eb99103b066314f44\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 284,\n \"license_type\": \"no_license\",\n \"max_line_length\": 35,\n \"num_lines\": 21,\n \"path\": \"/알고리즘/[템플릿]/유클리드 호제법/유클리드 호제법.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import timeit\\nstart = timeit.default_timer()\\n\\n\\na, b = 12368711, 2678178\\n\\nwhile a % b != 0:\\n a, b = b, a % b\\n\\nprint(b)\\n\\n\\n\\n\\n# for i in range(max(a,b),0,-1):\\n# if a % i == 0 and b % i == 0:\\n# print(i)\\n# break\\n\\nend = timeit.default_timer()\\nprint(f'{end-start:.5f}')\"\n },\n {\n \"alpha_fraction\": 0.5405405163764954,\n \"alphanum_fraction\": 0.5608108043670654,\n \"avg_line_length\": 20.214284896850586,\n \"blob_id\": \"8ce7e43e5fa89d92e94d907b524eac0e9941a384\",\n \"content_id\": \"7534a2259b78d0bdad9cf5a2e000d46e6d5b4b10\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 296,\n \"license_type\": \"no_license\",\n \"max_line_length\": 38,\n \"num_lines\": 14,\n \"path\": \"/알고리즘/온라인저지/2022/11/1109/지우개.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\n\\nN = int(input().rstrip())\\narr = list(range(1, N+1))\\nwhile len(arr) > 1:\\n pop_idx_list = []\\n for i in range(len(arr)):\\n if not i%2:\\n pop_idx_list.append(i)\\n for pop_idx in pop_idx_list[::-1]:\\n arr.pop(pop_idx)\\nprint(arr[0])\"\n },\n {\n \"alpha_fraction\": 0.49528300762176514,\n \"alphanum_fraction\": 0.5141509175300598,\n \"avg_line_length\": 24,\n \"blob_id\": \"f07290d36abc2eb61d77e8c4da725cd0903bc131\",\n \"content_id\": \"7199c117e430453677f2e7cc6f3ed5a9a19dae83\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 424,\n \"license_type\": \"no_license\",\n \"max_line_length\": 41,\n \"num_lines\": 17,\n \"path\": \"/알고리즘/온라인저지/2022/10/1008/첼시를 도와줘!.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\n\\nfor _ in range(int(input().rstrip())):\\n P = int(input().rstrip())\\n cost, name = [], []\\n for p in range(P):\\n player = input().rstrip().split()\\n cost.append(int(player[0]))\\n name.append(player[1])\\n result = [0, 0]\\n for i in range(P):\\n if cost[i] > result[0]:\\n result[0] = cost[i]\\n result[1] = i\\n print(name[result[1]])\"\n },\n {\n \"alpha_fraction\": 0.5017921328544617,\n \"alphanum_fraction\": 0.5232974886894226,\n \"avg_line_length\": 22.33333396911621,\n \"blob_id\": \"fd9b98cfcbb969b138d0826b553da5f2147db3ac\",\n \"content_id\": \"1571e63c2fb1ad23453a4aff1c8e7761ded850f5\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 279,\n \"license_type\": \"no_license\",\n \"max_line_length\": 50,\n \"num_lines\": 12,\n \"path\": \"/알고리즘/온라인저지/2022/10/1003/Maximum Subarray.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\n\\nfor _ in [0]*int(input().rstrip()):\\n N = int(input().rstrip())\\n arr = list(map(int, input().rstrip().split()))\\n dp = [0]*N\\n dp[0] = arr[0]\\n for i in range(1, N):\\n dp[i] = max(dp[i-1]+arr[i], arr[i])\\n print(max(dp))\"\n },\n {\n \"alpha_fraction\": 0.4647887349128723,\n \"alphanum_fraction\": 0.49295774102211,\n \"avg_line_length\": 34.75,\n \"blob_id\": \"9dd2f49874fe37c9153133107a8207728691bfcb\",\n \"content_id\": \"54ebf63835bcf8c14bac6d6d71d7dca75bfeb429\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 142,\n \"license_type\": \"no_license\",\n \"max_line_length\": 35,\n \"num_lines\": 4,\n \"path\": \"/알고리즘/온라인저지/2023/03/0306/백발백준하는 명사수.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"A, B, C = map(int, input().split())\\nD, E, F = map(int, input().split())\\ntmp = ((A-D)**2 + (B-E)**2) ** 0.5\\nprint('YES' if tmp < C+F else 'NO')\"\n },\n {\n \"alpha_fraction\": 0.5824742317199707,\n \"alphanum_fraction\": 0.5979381203651428,\n \"avg_line_length\": 23.375,\n \"blob_id\": \"27fa5ee763e6ee8c32dc89cc1202d911b4dbe01b\",\n \"content_id\": \"a8d2ab868644aebcf2962bf18f6b33b95e0cadee\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 194,\n \"license_type\": \"no_license\",\n \"max_line_length\": 55,\n \"num_lines\": 8,\n \"path\": \"/알고리즘/온라인저지/2022/09/0924/연속부분최대곱.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\n\\nN = int(input().rstrip())\\ndp = [float(input().rstrip()) for _ in range(N)]\\nfor i in range(1, N): dp[i] = max(dp[i], dp[i]*dp[i-1])\\nprint(f'{max(dp):.3f}')\"\n },\n {\n \"alpha_fraction\": 0.5766870975494385,\n \"alphanum_fraction\": 0.5981594920158386,\n \"avg_line_length\": 20.799999237060547,\n \"blob_id\": \"2e9ea56b06fab675e78195b0bc6c94e3d5701dde\",\n \"content_id\": \"2dbee2c71ac3d2500e195daaa0b5946279196ba4\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 326,\n \"license_type\": \"no_license\",\n \"max_line_length\": 54,\n \"num_lines\": 15,\n \"path\": \"/알고리즘/온라인저지/2022/10/1003/두 수의 합.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\n\\nN = int(input().rstrip())\\narr = sorted(list(map(int, input().rstrip().split())))\\nK = int(input().rstrip())\\nresult = 0\\nstart, end = 0, N-1\\nwhile start<end:\\n tmp = arr[start]+arr[end]\\n if tmp > K: end -= 1\\n elif tmp < K: start += 1\\n else: result += 1; start += 1\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.5569105744361877,\n \"alphanum_fraction\": 0.577235758304596,\n \"avg_line_length\": 26.44444465637207,\n \"blob_id\": \"99d07dccd5f757a19e860473aa22ab761bf74e70\",\n \"content_id\": \"0c933460f10d0fa7e079da08281aa7c545b5a807\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 246,\n \"license_type\": \"no_license\",\n \"max_line_length\": 59,\n \"num_lines\": 9,\n \"path\": \"/알고리즘/온라인저지/2022/11/1107/한다 안한다.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\n\\nfor _ in range(int(input().rstrip())):\\n word = input().rstrip()\\n prev, rear = word[:len(word)//2], word[len(word)//2:]\\n rear = rear[::-1]\\n print('Do-it' if prev[-1] == rear[-1] else 'Do-it-Not')\"\n },\n {\n \"alpha_fraction\": 0.4350649416446686,\n \"alphanum_fraction\": 0.46320345997810364,\n \"avg_line_length\": 26.235294342041016,\n \"blob_id\": \"21c3f39199275cf4a031a5d15098d3ea68032a4b\",\n \"content_id\": \"8fd0d968d99f14f94ca0ce73edcc0a15f41a15ac\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 558,\n \"license_type\": \"no_license\",\n \"max_line_length\": 62,\n \"num_lines\": 17,\n \"path\": \"/알고리즘/온라인저지/2022/08/0817/순열 사이클.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"for _ in range(int(input())):\\n N = int(input())\\n P = [list(range(1, N+1)), list(map(int, input().split()))]\\n used, result = [0] * N, 0\\n for i in range(N):\\n if not used[i]:\\n used[i], start, now = 1, P[0][i], P[1][i]\\n while now != start:\\n used[now-1] = 1\\n now = P[1][now-1]\\n result += 1\\n print(result)\\n\\n\\\"\\\"\\\"\\n문제 조건이, 1부터 N까지의 자연수로 이루어졌다고 \\n주어졌기 때문에, 한 사이클을 돌 때 인덱스를 고민하지 않아도 되었다\\n\\\"\\\"\\\"\"\n },\n {\n \"alpha_fraction\": 0.5480769276618958,\n \"alphanum_fraction\": 0.6282051205635071,\n \"avg_line_length\": 27.454545974731445,\n \"blob_id\": \"1485f432d58b7213f6c81b97ae80a75cc00a2940\",\n \"content_id\": \"e61498fcab4ef789082b8b431aa62d3148cad1aa\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 312,\n \"license_type\": \"no_license\",\n \"max_line_length\": 40,\n \"num_lines\": 11,\n \"path\": \"/알고리즘/온라인저지/2023/01/0115/나의 학점은.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"scores = list(map(int, input().split()))\\nhongik = int(input())\\nrank = scores.index(hongik)+1\\nif 1<=rank<6: result = 'A+'\\nelif 6<=rank<16: result = 'A0'\\nelif 16<=rank<31: result = 'B+'\\nelif 31<=rank<36: result = 'B0'\\nelif 36<=rank<46: result = 'C+'\\nelif 46<=rank<49: result = 'C0'\\nelse: result = 'F'\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.43801653385162354,\n \"alphanum_fraction\": 0.43801653385162354,\n \"avg_line_length\": 15.199999809265137,\n \"blob_id\": \"f387025a3fb539b5d8507eaecea275d7639558ce\",\n \"content_id\": \"b95b7b427073e1c2c3e2eab53c452ea200e72e55\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 242,\n \"license_type\": \"no_license\",\n \"max_line_length\": 35,\n \"num_lines\": 15,\n \"path\": \"/알고리즘/온라인저지/2023/05/0517/Andando no tempo.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"A, B, C = map(int, input().split())\\nresult = 'N'\\nif A == B: \\n result = 'S'\\nif C == B: \\n result = 'S'\\nif A == C: \\n result = 'S'\\nif A+C == B: \\n result = 'S'\\nif A == B+C: \\n result = 'S'\\nif A+B == C: \\n result = 'S'\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.40856030583381653,\n \"alphanum_fraction\": 0.4591439664363861,\n \"avg_line_length\": 18.846153259277344,\n \"blob_id\": \"c150362ddca8e9e21887bcafcd44cc48859de273\",\n \"content_id\": \"862003390eb7a0ba29bb02a1899ba17182f64689\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 257,\n \"license_type\": \"no_license\",\n \"max_line_length\": 32,\n \"num_lines\": 13,\n \"path\": \"/알고리즘/온라인저지/2023/05/0527/Electric Bill.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"A, B = map(int, input().split())\\nN = int(input())\\nfor i in range(N):\\n C = int(input())\\n print(C, end=' ')\\n result = 0\\n if C > 1000:\\n result += A*1000\\n C -= 1000\\n result += B*C\\n else:\\n result = A*C\\n print(result)\"\n },\n {\n \"alpha_fraction\": 0.5373134613037109,\n \"alphanum_fraction\": 0.6268656849861145,\n \"avg_line_length\": 16,\n \"blob_id\": \"be411eec98f587d7ef761fd8f415f9214e018343\",\n \"content_id\": \"aaf9ba812bca29e30ed71f9ae0b42a3574b51789\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 67,\n \"license_type\": \"no_license\",\n \"max_line_length\": 20,\n \"num_lines\": 4,\n \"path\": \"/알고리즘/온라인저지/2022/12/1231/Even or Odd.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = int(input())\\nif N%2:print(0)\\nelif N//2%2:print(1)\\nelse:print(2)\"\n },\n {\n \"alpha_fraction\": 0.6019417643547058,\n \"alphanum_fraction\": 0.6019417643547058,\n \"avg_line_length\": 25,\n \"blob_id\": \"b57ba08f0ccecd4c0ac5f00568d2ac72b5074b73\",\n \"content_id\": \"480eabf627f685057794bfcf64e27afdc70b9a4f\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 103,\n \"license_type\": \"no_license\",\n \"max_line_length\": 36,\n \"num_lines\": 4,\n \"path\": \"/알고리즘/온라인저지/2022/02/0205/시험 점수.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"mk = list(map(int, input().split()))\\nms = list(map(int, input().split()))\\n\\nprint(max(sum(mk), sum(ms)))\"\n },\n {\n \"alpha_fraction\": 0.4843304753303528,\n \"alphanum_fraction\": 0.5327635407447815,\n \"avg_line_length\": 22.46666717529297,\n \"blob_id\": \"edbb4049033f0319e1c814f230bbaf55f40e9499\",\n \"content_id\": \"cd595490d148a0e79a92d95f3dec6a881bd8d2d6\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 477,\n \"license_type\": \"no_license\",\n \"max_line_length\": 56,\n \"num_lines\": 15,\n \"path\": \"/알고리즘/온라인저지/2022/09/0911/RGB거리.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = int(input())\\ndp = [list(map(int, input().split())) for _ in range(N)]\\nfor i in range(1, len(dp)):\\n dp[i][0] += min(dp[i-1][1], dp[i-1][2])\\n dp[i][1] += min(dp[i-1][0], dp[i-1][2])\\n dp[i][2] += min(dp[i-1][0], dp[i-1][1])\\nprint(min(dp[N-1]))\\n\\n\\\"\\\"\\\"\\nDP문제 진짜 현타오네\\n코드가 이렇게 간단할 수가 있나\\n배열 그대로 들고 이동하면서\\n해당 집이 해당 색으로 집을 칠할 때의 \\n최소값들을 전부 구하면서 이동한다\\n\\\"\\\"\\\"\"\n },\n {\n \"alpha_fraction\": 0.5537634491920471,\n \"alphanum_fraction\": 0.5645161271095276,\n \"avg_line_length\": 30.16666603088379,\n \"blob_id\": \"d08dd5cdd8fad69d413bd7e570bdccc10d6af51b\",\n \"content_id\": \"382be1ec83a5e76a1f39a4d004a9b3659035c269\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 186,\n \"license_type\": \"no_license\",\n \"max_line_length\": 48,\n \"num_lines\": 6,\n \"path\": \"/알고리즘/온라인저지/2023/01/0107/암기왕.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"for _ in range(int(input())):\\n input()\\n notes = set(map(int, input().split()))\\n input()\\n for note in list(map(int, input().split())):\\n print(1 if note in notes else 0)\"\n },\n {\n \"alpha_fraction\": 0.4583333432674408,\n \"alphanum_fraction\": 0.46296295523643494,\n \"avg_line_length\": 18.727272033691406,\n \"blob_id\": \"a1cc1aea855633f1eb7b7e3449bb76e36a83f038\",\n \"content_id\": \"4f2faf58669f42eac5d3f516615e416b3c99ca4a\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 216,\n \"license_type\": \"no_license\",\n \"max_line_length\": 40,\n \"num_lines\": 11,\n \"path\": \"/알고리즘/SWEA/LEARN/Course/1. Programming Beginner/파이썬 프로그래밍 기초(2)/40차시 4. 문자열 - 연습문제 4.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# while True:\\n# tmp = input()\\n# print('>> {}'.format(tmp.upper()))\\n# if not tmp:\\n# exit()\\n\\nfor i in range(3):\\n tmp = input()\\n print('>> {}'.format(tmp.upper()))\\n if not tmp:\\n break\"\n },\n {\n \"alpha_fraction\": 0.4615384638309479,\n \"alphanum_fraction\": 0.5054945349693298,\n \"avg_line_length\": 29.5,\n \"blob_id\": \"3fe44d4a3ac3ceae0e69bb902d1f05e070d49e92\",\n \"content_id\": \"79374eea1e74a122f91bfa38ec1d89197f842164\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 182,\n \"license_type\": \"no_license\",\n \"max_line_length\": 47,\n \"num_lines\": 6,\n \"path\": \"/알고리즘/온라인저지/2022/08/0826/Football Scoring.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"C = [6, 3, 2, 1, 2] # change\\nfor _ in range(2):\\n S = list(map(int, input().split())) # score\\n result = 0\\n for i in range(5): result += C[i] * S[i]\\n print(result, end=' ')\"\n },\n {\n \"alpha_fraction\": 0.5773195624351501,\n \"alphanum_fraction\": 0.5979381203651428,\n \"avg_line_length\": 16.727272033691406,\n \"blob_id\": \"cb7e8599953499fb8eb60355540fd6a5cef010fc\",\n \"content_id\": \"dcc19782001d138bb7a80bb3640f34d79669c01c\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 194,\n \"license_type\": \"no_license\",\n \"max_line_length\": 31,\n \"num_lines\": 11,\n \"path\": \"/알고리즘/온라인저지/2022/10/1002/내 선물을 받아줘 2.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\n\\nN = int(input().rstrip())\\narr = input().rstrip()\\nresult = 0\\nfor i in range(N-1):\\n tmp = arr[i] + arr[i+1]\\n if tmp == 'EW': result += 1\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.5378151535987854,\n \"alphanum_fraction\": 0.5462185144424438,\n \"avg_line_length\": 11,\n \"blob_id\": \"e0c9b7601595cc1aa76f73f594f1d174db3a652b\",\n \"content_id\": \"edfe5a70b9e7e7fb5db21302baca0b88a9487c5a\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 119,\n \"license_type\": \"no_license\",\n \"max_line_length\": 36,\n \"num_lines\": 10,\n \"path\": \"/알고리즘/온라인저지/2022/02/0205/사과.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = int(input())\\n\\nresult = 0\\n\\nfor n in range(N):\\n s, a = map(int, input().split())\\n\\n result += a%s\\n\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.6412213444709778,\n \"alphanum_fraction\": 0.6412213444709778,\n \"avg_line_length\": 25.399999618530273,\n \"blob_id\": \"3f54bb447531d5ba55947d9f493ff8f696ffd578\",\n \"content_id\": \"c195c344aeb47dc5bca5908bbeff9d083593ebc1\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 131,\n \"license_type\": \"no_license\",\n \"max_line_length\": 38,\n \"num_lines\": 5,\n \"path\": \"/알고리즘/온라인저지/2021/08/0822/직사각형에서 탈출.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"x, y, w, h = map(int, input().split())\\ndistance = []\\ndistance.append(min(x, w-x))\\ndistance.append(min(y, h-y))\\nprint(min(distance))\"\n },\n {\n \"alpha_fraction\": 0.6243094205856323,\n \"alphanum_fraction\": 0.6243094205856323,\n \"avg_line_length\": 35,\n \"blob_id\": \"63a0c7356245db393cdcaaeca142cf66c8291356\",\n \"content_id\": \"08256a863a5058f128b1548992acf9a7f342aec6\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 181,\n \"license_type\": \"no_license\",\n \"max_line_length\": 116,\n \"num_lines\": 5,\n \"path\": \"/알고리즘/SWEA/LEARN/Course/1. Programming Beginner/파이썬 프로그래밍 기초(2)/4차시 2. 자료구조 – 리스트, 튜플 - 연습문제 2.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"s = 'Python is powerful... and fast; plays well with others; runs everywhere; is friendly & easy to learn; is Open.'\\n\\nfor i in s:\\n if i not in 'aeiou':\\n print(i, end='')\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.3636363744735718,\n \"alphanum_fraction\": 0.38181817531585693,\n \"avg_line_length\": 17.5,\n \"blob_id\": \"32b1b3caec9718e0d9b91be7dabb8f7d1617c653\",\n \"content_id\": \"c464d215f6d79ec64626296ac2d079b1ca4f224a\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 110,\n \"license_type\": \"no_license\",\n \"max_line_length\": 23,\n \"num_lines\": 6,\n \"path\": \"/알고리즘/온라인저지/2022/05/0526/별 찍기 - 20.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = int(input())\\nfor n in range(N):\\n if n%2 == 0:\\n print('* ' * N)\\n else:\\n print(' *' * N)\"\n },\n {\n \"alpha_fraction\": 0.5142624378204346,\n \"alphanum_fraction\": 0.5509372353553772,\n \"avg_line_length\": 34.08571243286133,\n \"blob_id\": \"042dbbb25cd79bd3eba22a38f8da120c83eaff27\",\n \"content_id\": \"30078684c569aae908149f1c6bf23d09d27c5f86\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1567,\n \"license_type\": \"no_license\",\n \"max_line_length\": 100,\n \"num_lines\": 35,\n \"path\": \"/알고리즘/온라인저지/2022/09/0916/공주님을 구해라!.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\nfrom collections import deque\\n\\ninput = sys.stdin.readline\\ndy, dx = [-1, 1, 0, 0], [0, 0, -1, 1]\\n\\nN, M, T = map(int, input().rstrip().split())\\narr = [list(map(int, input().rstrip().split())) for _ in range(N)]\\nvisited = [[0]*M for _ in range(N)]\\ndistance = int(1e9) # 임의의 거리 최대값\\nQ = deque()\\nif arr[0][0] == 2: distance = N+M-2 # 시작부터 그람인 경우, 무지성 택시거리 이동\\nelse: # 시작이 그람은 아닌 경우\\n Q.append((0, 0, 0)) # move, y, x\\n visited[0][0] = 1\\nwhile Q:\\n move, y, x = Q.popleft()\\n if y == N-1 and x == M-1: distance = min(distance, move) # 공주님한테 도착했을 때 걸린 시간 갱신\\n for i in range(4): # 델타 이동\\n ny, nx = y+dy[i], x+dx[i]\\n if 0<=ny<N and 0<=nx<M and not visited[ny][nx] and arr[ny][nx] != 1: # 방문한 적이 없으며, 마법벽이 아닐 때\\n Q.append((move+1, ny, nx)) # 빈 방이든 그람이든 일단 탐색\\n visited[ny][nx] = 1\\n if arr[ny][nx] == 2: # 그람인 경우\\n gram = move+1 + (N+M-2-ny-nx) # 무지성 택시이동, 왔던 길 무시 가능\\n distance = min(distance, gram) # 돌고 돌아 그람을 줍는 경우는 배제된다, BFS이니까!\\nprint(distance if distance<=T else 'Fail') # T시간 이내에 공주님을 구할 수 있습니까?\\n\\n\\\"\\\"\\\"\\n그람을 주운 자리에서 무지성 택시거리로 이동 가능\\n택시거리 : 두 좌표 (x1, y1), (x2, y2)의 가로+세로\\n abs(x1-x2) + abs(y1-y2)\\n\\\"\\\"\\\"\\n\\n# https://www.acmicpc.net/problem/17836\"\n },\n {\n \"alpha_fraction\": 0.4115842580795288,\n \"alphanum_fraction\": 0.47708407044410706,\n \"avg_line_length\": 24.781394958496094,\n \"blob_id\": \"9956cd3b26e271a99c53ef00bdb8a36dc307571d\",\n \"content_id\": \"cd2949dd5072ba3030dc351fe49eaf42388d2afb\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 6852,\n \"license_type\": \"no_license\",\n \"max_line_length\": 101,\n \"num_lines\": 215,\n \"path\": \"/알고리즘/온라인저지/2022/08/0812/말이 되고픈 원숭이.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\nfrom collections import deque\\n\\ninput = sys.stdin.readline\\n\\ndy = [-1, 1, 0, 0] # delta y\\ndx = [0, 0, -1, 1] # delta x\\nky = [-2, -1, 1, 2, 2, 1, -1, -2] # knight y\\nkx = [1, 2, 2, 1, -1, -2, -2, -1] # knight x\\n\\ndef bfs():\\n Q = deque()\\n Q.append((0, 0, K, 0)) # y, x, k, move\\n # 3차원 방문배열\\n # 만약 K가 2일 때, 해당 좌표까지 나이트 이동을 0번 혹은 1번 혹은 2번 사용하여\\n # 해당 좌표에 도착할 수 있는지 체크하기 위함\\n visited = [[[False]*(K+1) for _ in range(W)] for _ in range(H)] \\n # 아래 코드에서 방문 좌표를 추가하면서 방문처리 할 것이므로\\n # 시작 점 방문 처리\\n visited[0][0][K] = True \\n while Q: # 탐색할 좌표가 있을 때\\n y, x, k, move = Q.popleft() # 세로, 가로, 남은 나이트 이동 횟수, 이동한 횟수\\n if y == H-1 and x == W-1: # 도착했다면\\n return move # 그 때의 이동 횟수\\n if k > 0: # 나이트 이동 횟수가 남아있을 때\\n for i in range(8):\\n ny = y+ky[i] # 나이트 이동 y\\n nx = x+kx[i] # 나이트 이동 x\\n # 범위 안에 있고, 장애물이 아니면서, 나이트이동으로 탐색할 수 있다면\\n if 0<=ny<H and 0<=nx<W and not arr[ny][nx] and not visited[ny][nx][k-1]:\\n # 해당 좌표를 탐색할 것이며\\n # 아직 나이트 이동을 k-1번 할 수 있습니다\\n visited[ny][nx][k-1] = True \\n Q.append((ny, nx, k-1, move+1))\\n for i in range(4):\\n ny = y+dy[i] # 델타 이동 y\\n nx = x+dx[i] # 델타 이동 x\\n # 범위 안에 있고, 장애물이 아니면서\\n # 현재 사용가능한 나이트이동의 횟수로 해당 좌표를 방문한 적이 없을 때\\n if 0<=ny<H and 0<=nx<W and not arr[ny][nx] and not visited[ny][nx][k]:\\n # 해당 좌표를 탐색할 것이며\\n # 나이트 이동을 사용하지 않고 탐색합니다\\n # 여전히 k번의 나이트 이동을 사용할 수 있습니다\\n visited[ny][nx][k] = True\\n Q.append((ny, nx, k, move+1))\\n return -1 # 도착할 수 없음\\n\\nK = int(input())\\nW, H = map(int, input().split())\\narr = tuple(tuple(map(int, input().split())) for _ in range(H)) # 시간 단축을 위한 tuple (list보다 빠름, 아마도..?)\\nprint(bfs())\\n\\n\\n\\\"\\\"\\\"\\n시간 : 120분, 미해결, 정답 풀이 확인 \\n\\n풀이\\n 나이트이동이 가능하다고 해서 아무때나 그리디하게 적용하게 되면 오답이다\\n 세로 가로 에서 하나 더 추가한 3차원 방문배열이 필요하다\\n 방문 배열의 해당 좌표에 몇번의 나이트 이동으로 도달하였는지 기록하며 진행한다\\n 나이트이동과 그냥 이동을 통한 탐색을 동시에 진행한다\\n\\n반례 모음\\n\\n1\\n6 6\\n0 0 1 1 0 0\\n1 1 1 0 0 0\\n0 0 1 1 0 0\\n1 0 1 1 1 1\\n1 0 0 1 1 1\\n0 0 0 0 0 0\\nanswer : 8\\n\\n2\\n6 6\\n0 0 1 1 0 0\\n1 1 1 0 0 0\\n0 0 1 1 0 0\\n1 0 1 1 1 1\\n1 0 0 1 1 1\\n0 0 0 0 0 0\\nanswer : 6\\n\\n1\\n2 3\\n0 1\\n1 1\\n1 0\\nanswer : 1\\n\\n4\\n6 6\\n0 0 1 1 0 0\\n1 1 1 0 0 0\\n0 0 1 1 0 0\\n1 0 1 1 1 1\\n1 0 0 1 1 1\\n0 0 0 0 0 0\\nanswer : 4\\n\\n3\\n4 5\\n0 1 1 1\\n1 1 0 1\\n1 1 1 1\\n1 1 1 0\\n1 1 1 0\\nanswer : 3\\n\\n1\\n5 5\\n0 0 0 0 0\\n0 0 0 0 0\\n0 0 0 0 0\\n0 0 0 1 1\\n0 0 0 1 0\\nanswer : 6\\n\\n1\\n4 4\\n0 0 1 1\\n0 0 1 1\\n0 0 1 1\\n1 1 1 0\\nanswer : 4\\n\\\"\\\"\\\"\\n\\n\\n# 쾅\\n# from collections import deque\\n\\n# K = int(input())\\n# W, H = map(int, input().split())\\n# arr = [list(map(int, input().split())) for _ in range(H)]\\n# result = -1\\n# K_dy = [-2, -1, 1, 2, 2, 1, -1, -2] # Knight dy\\n# K_dx = [1, 2, 2, 1, -1, -2, -2, -1] # Knight dx\\n# dy = [-1, 1, 0, 0] # 나이트 이동 이후 델타 dy\\n# dx = [0, 0, -1, 1] # 나이트 이동 이후 델타 dx\\n# Q = deque()\\n# Q.append((H-1, W-1, 0, 0)) # (y, x, K_cnt, move)\\n# visited = [[0]*W for _ in range(H)] # 방문배열\\n# K_visited = [[0]*W for _ in range(H)] # 나이트 이동 방문배열\\n# visited[H-1][W-1] = 1\\n# K_visited[H-1][W-1] = 1\\n# tmp = int(1e9) # 가상의 최소값\\n# while Q:\\n# y, x, K_cnt, move = Q.popleft()\\n# if y == 0 and x == 0: # 도착했을 경우\\n# if move < tmp: tmp = move\\n# continue\\n# if visited[y][x]: continue\\n# if K_cnt < K: # 나이트 이동을 할 기회가 남아있을 때\\n# for i in range(8):\\n# ny = y + K_dy[i]\\n# nx = x + K_dx[i]\\n# # 이동하려는 좌표가 범위안에 있고, 방문한 적이 없고, 장애물이 아닐 때\\n# if 0<=ny<H and 0<=nx<W and not K_visited[ny][nx] and not arr[ny][nx]:\\n# Q.append((ny, nx, K_cnt+1, move+1))\\n# K_visited[ny][nx] = 1\\n# for i in range(4):\\n# ny = y + dy[i]\\n# nx = x + dx[i]\\n# # 이동하려는 좌표가 범위안에 있고, 방문한 적이 없고, 장애물이 아닐 때\\n# if 0<=ny<H and 0<=nx<W and not visited[ny][nx] and not arr[ny][nx]:\\n# Q.append((ny, nx, K_cnt, move+1))\\n# visited[ny][nx] = 1\\n# for v in visited: print(v)\\n# print(tmp if tmp != int(1e9) else result)\\n\\n\\n# 쾅쾅\\n# from collections import deque\\n\\n# K = int(input())\\n# W, H = map(int, input().split())\\n# arr = [list(map(int, input().split())) for _ in range(H)]\\n# result = -1\\n# K_dy = [-2, -1, 1, 2, 2, 1, -1, -2] # Knight dy\\n# K_dx = [1, 2, 2, 1, -1, -2, -2, -1] # Knight dx\\n# dy = [-1, 1, 0, 0] # 나이트 이동 이후 델타 dy\\n# dx = [0, 0, -1, 1] # 나이트 이동 이후 델타 dx\\n# Q = deque()\\n# Q.append((H-1, W-1, 0, 0)) # (y, x, K_cnt, move)\\n# visited = [[0]*W for _ in range(H)] # 방문배열\\n# tmp = int(1e9) # 가상의 최소값\\n# while Q:\\n# y, x, K_cnt, move = Q.popleft()\\n# if y == 0 and x == 0: # 도착했을 경우\\n# tmp = move\\n# # print(K_cnt, K)\\n# if K_cnt < K: tmp -= (K-K_cnt)*2\\n# break\\n# if visited[y][x]: continue\\n# visited[y][x] = 1\\n# blocked = True\\n# for i in range(4):\\n# ny = y + dy[i]\\n# nx = x + dx[i]\\n# # 이동하려는 좌표가 범위안에 있고, 방문한 적이 없고, 장애물이 아닐 때\\n# if 0<=ny<H and 0<=nx<W and not visited[ny][nx] and not arr[ny][nx]:\\n# Q.append((ny, nx, K_cnt, move+1))\\n# blocked = False\\n# for i in range(8):\\n# ny = y + K_dy[i]\\n# nx = x + K_dx[i]\\n# if ny == 0 and nx == 0:\\n# Q.append((ny, nx, K_cnt+1, move+1))\\n# elif blocked and K_cnt < K:\\n# # 이동하려는 좌표가 범위안에 있고, 방문한 적이 없고, 장애물이 아닐 때\\n# if 0<=ny<H and 0<=nx<W and not visited[ny][nx] and not arr[ny][nx]:\\n# Q.append((ny, nx, K_cnt+1, move+1))\\n# # for v in visited: print(v)\\n# print(tmp if tmp != int(1e9) else result)\"\n },\n {\n \"alpha_fraction\": 0.5086206793785095,\n \"alphanum_fraction\": 0.5258620977401733,\n \"avg_line_length\": 13.625,\n \"blob_id\": \"11a29653a73b79585508e44040e8bc92445b4942\",\n \"content_id\": \"41e535c930a05a2dfc83558fb403bdc7e59ce00d\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 116,\n \"license_type\": \"no_license\",\n \"max_line_length\": 20,\n \"num_lines\": 8,\n \"path\": \"/알고리즘/온라인저지/2023/05/0503/줄 세기.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"result = 0\\nwhile True:\\n try:\\n input()\\n result += 1\\n except EOFError:\\n break\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.34090909361839294,\n \"alphanum_fraction\": 0.3636363744735718,\n \"avg_line_length\": 19.384614944458008,\n \"blob_id\": \"3120419b70924cf2f36cba3f4c93dce807e0f0cc\",\n \"content_id\": \"02577ddb77a5f6470844d4600fc62d90abbea5ac\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 270,\n \"license_type\": \"no_license\",\n \"max_line_length\": 38,\n \"num_lines\": 13,\n \"path\": \"/알고리즘/온라인저지/2022/07/0701/피로도.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"A, B, C, M = map(int, input().split())\\nresult = 0\\nF = 0 # fatigue : 피로도\\nif not A > M:\\n for i in range(24):\\n if F+A <= M:\\n F += A\\n result += B\\n else:\\n F -= C\\n if F < 0:\\n F = 0\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.5199999809265137,\n \"alphanum_fraction\": 0.5299999713897705,\n \"avg_line_length\": 19.066667556762695,\n \"blob_id\": \"6bab7dfd68e31ce14c5677d36a208b81fcfc71af\",\n \"content_id\": \"fff09b0ec6d02517d3145f3888e1b27445f444c9\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 300,\n \"license_type\": \"no_license\",\n \"max_line_length\": 40,\n \"num_lines\": 15,\n \"path\": \"/알고리즘/온라인저지/2022/07/0729/나는야 포켓몬 마스터 이다솜.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ndef input():\\n return sys.stdin.readline().rstrip()\\n\\nN, M = map(int, input().split())\\nP = ['' for _ in range(N+1)] # pokemon\\nfor n in range(1, N+1):\\n P[n] = input()\\nfor m in range(M):\\n Q = input()\\n try: # int\\n print(P[int(Q)])\\n except: # str\\n print(P.index(Q))\"\n },\n {\n \"alpha_fraction\": 0.41903170943260193,\n \"alphanum_fraction\": 0.4407345652580261,\n \"avg_line_length\": 30.552631378173828,\n \"blob_id\": \"13df03152c058a237f88e9d4b61c3b486a64c0f3\",\n \"content_id\": \"9eee1eaef83d9566c9767fb33e674cbd048e6991\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1486,\n \"license_type\": \"no_license\",\n \"max_line_length\": 95,\n \"num_lines\": 38,\n \"path\": \"/알고리즘/온라인저지/2022/04/0420/영역 구하기.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from collections import deque\\n\\nN, M, K = map(int, input().split())\\n# 모눈종이를 전부 1로 채우고, 직사각형으로 채워지는 곳을 0으로 바꿈\\narr = [[1]*M for _ in range(N)]\\nfor k in range(K):\\n area = list(map(int, input().split()))\\n for i in range(area[1], area[3]):\\n for j in range(area[0], area[2]):\\n arr[i][j] = 0\\nresult = [] # 넓이를 담을 리스트\\n# 델타이동\\ndx = [0, 1, 0, -1]\\ndy = [1, 0, -1, 0]\\nq = deque() # BFS\\ncnt = 0 # 넓이(영역)의 개수\\n# 모눈종이를 돌다가\\nfor n in range(N):\\n for m in range(M):\\n if arr[n][m]: # 분리된 영역이 있으면\\n q.append((m, n)) # 출발\\n square = 0 # 넓이값 초기화\\n while q: # BFS\\n tmp = q.popleft()\\n x, y = tmp[0], tmp[1]\\n if arr[y][x]:\\n arr[y][x] = 0 # 방문 처리\\n square += 1 # 넓이 계산\\n for i in range(4): # 델타이동 하였을 때\\n # 모눈종이를 벗어나지 않으며, 이웃한 분리된영역일 경우\\n if (0 <= x+dx[i] < M) and (0 <= y+dy[i] < N) and arr[y+dy[i]][x+dx[i]]:\\n q.append((x+dx[i], y+dy[i])) # 탐색점 추가\\n result.append(square) # 영역의 넓이 리스트에 저장\\n cnt += 1 # 영역 한 개 확인\\nresult.sort() # 넓이 오름차순으로 정렬\\n# 출력\\nprint(cnt)\\nprint(*result)\"\n },\n {\n \"alpha_fraction\": 0.4285714328289032,\n \"alphanum_fraction\": 0.4523809552192688,\n \"avg_line_length\": 16.58333396911621,\n \"blob_id\": \"b747a114050e1890192fd0efb31e1f9ea47d826d\",\n \"content_id\": \"ba5b2da593487a4176cb8ad4db8dfa6e1cdb2639\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 210,\n \"license_type\": \"no_license\",\n \"max_line_length\": 43,\n \"num_lines\": 12,\n \"path\": \"/알고리즘/온라인저지/2022/03/0320/감정이입.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"def dec_to_bin(X):\\n m = 1\\n output = 0\\n for x in X[::-1]:\\n if int(x):\\n output += m\\n m *= 2\\n return output\\n\\nA = input()\\nB = input()\\nprint(bin(dec_to_bin(A)*dec_to_bin(B))[2:])\"\n },\n {\n \"alpha_fraction\": 0.4429530203342438,\n \"alphanum_fraction\": 0.45413869619369507,\n \"avg_line_length\": 39.727272033691406,\n \"blob_id\": \"88d0c0c0dd85a0dca3322528dbdb06d962333cd1\",\n \"content_id\": \"4381b38cefd92c98c9d99a4c28a9598f27eb5484\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 589,\n \"license_type\": \"no_license\",\n \"max_line_length\": 72,\n \"num_lines\": 11,\n \"path\": \"/알고리즘/온라인저지/2022/04/0429/숫자 정사각형.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N, M = map(int, input().split())\\narr = [list(map(int, input())) for _ in range(N)] # 숫자 배열 입력 받기\\nfor i in range(N, -1, -1): # 가장 큰 정사각형부터 확인\\n # 정사각형의 길이가 i+1 일 때\\n for j in range(N-i):\\n for k in range(M-i):\\n # arr[j][k] 는 정사각형 가장 왼쪽 위\\n # 보고있는 정사각형의 꼭지점 숫자들이 전부 같을 때\\n if arr[j][k] == arr[j][k+i] == arr[j+i][k+i] == arr[j+i][k]:\\n print((i+1)**2) # 넓이 구해서 출력\\n exit() # 코드 종료\"\n },\n {\n \"alpha_fraction\": 0.5344827771186829,\n \"alphanum_fraction\": 0.5517241358757019,\n \"avg_line_length\": 18.44444465637207,\n \"blob_id\": \"007fe795296c04c0818c0c1f67fef61f077cc86e\",\n \"content_id\": \"761140506af3dc4a9ad355329530938ea5c2522c\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 174,\n \"license_type\": \"no_license\",\n \"max_line_length\": 39,\n \"num_lines\": 9,\n \"path\": \"/알고리즘/온라인저지/2022/03/0327/서버.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N, T = map(int, input().split())\\nworks = list(map(int, input().split()))\\nresult = 0\\nfor work in works:\\n T -= work\\n if T < 0:\\n break\\n result += 1\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.5281456708908081,\n \"alphanum_fraction\": 0.5645695328712463,\n \"avg_line_length\": 22.269229888916016,\n \"blob_id\": \"8d1828b06acc1f1d40a55e352bf246d574600fb8\",\n \"content_id\": \"67a7c1323419224dfcf75fad4feda8f4d97ac467\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 604,\n \"license_type\": \"no_license\",\n \"max_line_length\": 49,\n \"num_lines\": 26,\n \"path\": \"/알고리즘/온라인저지/2022/09/0913/참외밭.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"K = int(input())\\nbig = small = 1\\nlines = []\\nsmall_idx = []\\nfor _ in range(6):\\n lines.append(list(map(int, input().split())))\\nresult = [[] for _ in range(4)]\\nwhile lines[2][0] != lines[4][0]:\\n lines.append(lines.pop(0))\\n lines.append(lines.pop(0))\\nfor i in range(6):\\n ewsn, length = lines[i][0], lines[i][1]\\n ewsn -= 1\\n if result[ewsn]:\\n small_idx.append(ewsn)\\n result[ewsn].append(length)\\nfor r in result: \\n if len(r) == 1:\\n big *= r[0]\\ni = 0\\nfor s in small_idx[::-1]:\\n small *= result[s][i]\\n i += 1\\nprint((big-small)*K)\\n\\n# https://www.acmicpc.net/problem/2477\"\n },\n {\n \"alpha_fraction\": 0.5952380895614624,\n \"alphanum_fraction\": 0.6190476417541504,\n \"avg_line_length\": 20.25,\n \"blob_id\": \"1035d45dae73e20ded71863a6a431362589341ea\",\n \"content_id\": \"1462fcfa17324a03b5cffd4a1a39a4dda820c539\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 84,\n \"license_type\": \"no_license\",\n \"max_line_length\": 41,\n \"num_lines\": 4,\n \"path\": \"/알고리즘/온라인저지/2022/08/0805/Bottle Return.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"result = 0\\nfor i in list(map(int, input().split())):\\n result += i*5\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.47806355357170105,\n \"alphanum_fraction\": 0.5128592848777771,\n \"avg_line_length\": 29.090909957885742,\n \"blob_id\": \"1548df1aeed4c9fa748cf6948a3e6b47fdf84f2e\",\n \"content_id\": \"9cf1ca9977314a2ba9d115b0336e9376da7f4d9e\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 997,\n \"license_type\": \"no_license\",\n \"max_line_length\": 58,\n \"num_lines\": 22,\n \"path\": \"/알고리즘/온라인저지/2021/08/0821/직사각형 네개의 합집합의 면적 구하기.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"\\\"\\\"\\\"\\n좌표평면배열을 만들어서\\n직사각형들을 1로 저장하고\\n저장하는 과정에서 겹치면 continue\\n저장된 1들을 전부 출력\\\"\\\"\\\"\\n\\narr = [[0]*101 for _ in range(101)] # 0번째칸 추가해서 인덱스와 숫자 일치\\nfor tc in range(4): # 모든 케이스는 4개의 직사각형\\n x1, y1, x2, y2 = map(int, input().split()) # 좌표들\\n for i in range(y1, y2): # y좌표 for문 먼저\\n for j in range(x1, x2): # x좌표\\n if arr[i][j]: # 값이 들어있으면\\n continue # 컨티뉴\\n else: # 아직 저장된 값이 없으면\\n arr[i][j] = 1 # 1을 저장\\n # 합집합은 or연산\\n # True or로 넘어가기 때문에 값이 있으면 저장이 되지 않고\\n # 합해지는 부분을 연산할 필요가 없어짐\\narea = 0 # 면적\\nfor ar in arr: # 저장된 배열을 돌면서\\n area += sum(ar) # 각 줄을 더해서 면적에 저장\\nprint(area) # 출력\"\n },\n {\n \"alpha_fraction\": 0.5,\n \"alphanum_fraction\": 0.5348837375640869,\n \"avg_line_length\": 20.75,\n \"blob_id\": \"cd49df5bd2dcd5318ea22a7aa9bb6230a1c5178b\",\n \"content_id\": \"8cf4d7f7af75810ca162549a862456b6e976058c\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 86,\n \"license_type\": \"no_license\",\n \"max_line_length\": 49,\n \"num_lines\": 4,\n \"path\": \"/알고리즘/온라인저지/2022/02/0209/쿠폰.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = int(input())\\n\\nfor n in range(N):\\n print('${:.2f}'.format(float(input()) * 0.8))\"\n },\n {\n \"alpha_fraction\": 0.46979865431785583,\n \"alphanum_fraction\": 0.48322147130966187,\n \"avg_line_length\": 29,\n \"blob_id\": \"655f226db7d4262ee5eefca28cd0d686b8f8d0bc\",\n \"content_id\": \"827de99c8d418dae8d758cd36ba071dd69398581\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 149,\n \"license_type\": \"no_license\",\n \"max_line_length\": 46,\n \"num_lines\": 5,\n \"path\": \"/알고리즘/온라인저지/2022/09/0904/수 뒤집기.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"for _ in range(int(input())):\\n num = input()\\n A, B = int(num), int(num[::-1])\\n tmp = str(A+B)\\n print('YES' if tmp == tmp[::-1] else 'NO')\"\n },\n {\n \"alpha_fraction\": 0.4054054021835327,\n \"alphanum_fraction\": 0.4864864945411682,\n \"avg_line_length\": 11.666666984558105,\n \"blob_id\": \"df02734a1decd16cb4f930582d8b87974d1a12d5\",\n \"content_id\": \"c81fc81d02fea6cefb76dc897d999e948ac7dc83\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 37,\n \"license_type\": \"no_license\",\n \"max_line_length\": 20,\n \"num_lines\": 3,\n \"path\": \"/알고리즘/온라인저지/2022/02/0213/조별과제를 하려는데 조장이 사라졌다.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"L = int(input()) - 1\\n\\nprint(L//5 + 1)\"\n },\n {\n \"alpha_fraction\": 0.47093021869659424,\n \"alphanum_fraction\": 0.4883720874786377,\n \"avg_line_length\": 13.416666984558105,\n \"blob_id\": \"96f20e699840e5de2aff0ada4036ab18fb3cdd95\",\n \"content_id\": \"873e782408626c7225957daca916c4bc4876d0cd\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 172,\n \"license_type\": \"no_license\",\n \"max_line_length\": 20,\n \"num_lines\": 12,\n \"path\": \"/알고리즘/온라인저지/2023/05/0519/골뱅이 찍기 - 돌아간 ㄹ.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = int(input())\\nA = '@'*N\\nB = ' '*N\\nS = A*3+B+A\\nM = A+B+A+B+A\\nE = A+B+A*3\\nfor i in range(N):\\n print(S)\\nfor i in range(N*3):\\n print(M)\\nfor i in range(N):\\n print(E)\"\n },\n {\n \"alpha_fraction\": 0.5115875005722046,\n \"alphanum_fraction\": 0.5428736805915833,\n \"avg_line_length\": 27.31147575378418,\n \"blob_id\": \"3315b5923cc493c203477967692db618954b7837\",\n \"content_id\": \"5a8ce88572db0a31507e8223037fc782a7d7aba4\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 2338,\n \"license_type\": \"no_license\",\n \"max_line_length\": 84,\n \"num_lines\": 61,\n \"path\": \"/알고리즘/[템플릿]/BFS/채굴.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\nfrom collections import deque\\nfrom copy import deepcopy\\n\\ninput = sys.stdin.readline\\n\\ndef delta_move(y, x, D, mine, Q, visited):\\n for i in range(4):\\n ny, nx = y+dy[i], x+dx[i]\\n if 0<=ny<N and 0<=nx<M and not visited[ny][nx]:\\n if mine[ny][nx]<=D: # 공기or캘 수 있는 광물\\n visited[ny][nx] = 1\\n Q.append((ny, nx))\\n else: # 캘 수 없는 광물\\n visited[ny][nx] = 1 # 방문하였으나 캘 수 없었다\\n\\ndef BFS(D): # 채굴기의 성능 D\\n mine = deepcopy(arr) # 광__산\\n mineral = 0 # 채굴기 성능이 D일때 캘 수 있는 광물의 수 초기화\\n visited = [[0]*M for _ in range(N)] # 광산 방문배열\\n Q = deque()\\n Q.append((0, 0)) # 공기층을 추가하였으니, 0,0부터 시작\\n visited[0][0] = 1\\n while Q: # 캘 수 있는 광물 체크\\n y, x = Q.popleft()\\n if mine[y][x]: # 광물이면\\n mine[y][x] = 0 # 캐고\\n mineral += 1 # 저장\\n delta_move(y, x, D, mine, Q, visited)\\n return mineral # 채굴기 성능이 D일때 캘 수 있는 광물 수\\n\\ndy, dx = [-1, 1, 0, 0], [0, 0, -1, 1] # 4방향 델타이동\\nN, M, K = map(int, input().rstrip().split())\\nM += 2\\n# 배열 테두리에 공기층 생성\\narr = [[0]*M] + [[0]+list(map(int, input().rstrip().split()))+[0] for _ in range(N)]\\nN += 1\\n# 1<=N,M<=1000, 1<=K<=1e6\\n# 채굴기의 성능을 1부터 +1하면서 전수조사 할 수 없다\\n# 채굴기의 성능 이분탐색 필요\\nresult = int(1e7)\\nstart, end = 1, int(1e7)\\nwhile start<=end:\\n mid = (start+end) // 2\\n mineral = BFS(mid) # 현재 채굴기의 성능으로 광물을 채굴해보자\\n if mineral>=K: # K개의 광물을 충분히 채굴할 수 있음, 성능 D를 좀 더 높여도 됌\\n end = mid-1\\n result = min(result, mid)\\n else: # 현재 성능으로는 K개의 광물을 채굴할 수 없음\\n start = mid+1\\nprint(result)\\n\\n\\\"\\\"\\\"\\n이분탐색과 BFS의 혼합문제다\\nBFS를 함수화시켜서 이분탐색안에 넣는 편이 좋다\\n고난이도 문제로 오면서 \\\"코드 구조화\\\"가 중요해지는 것 같다\\n탭 3번정도 단위로 끊어서 함수화 시키자\\n브론즈 실버등, 간단한 문제도 함수화(구조화)연습을 많이 하자\\n\\\"\\\"\\\"\\n\\n# https://www.acmicpc.net/problem/15573\"\n },\n {\n \"alpha_fraction\": 0.4810126721858978,\n \"alphanum_fraction\": 0.5316455960273743,\n \"avg_line_length\": 39,\n \"blob_id\": \"722940d6e14ac6e3f2a13f9ffcd6fccede3691f9\",\n \"content_id\": \"47abeb54b1a36dfc85b8c3e4e2948cb9c4f189b5\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 79,\n \"license_type\": \"no_license\",\n \"max_line_length\": 40,\n \"num_lines\": 2,\n \"path\": \"/알고리즘/온라인저지/2023/03/0302/Laptop Sticker.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"A, B, C, D = map(int, input().split())\\nprint(1 if ((A>C+1) and (B>D+1)) else 0)\"\n },\n {\n \"alpha_fraction\": 0.4702194333076477,\n \"alphanum_fraction\": 0.5023511052131653,\n \"avg_line_length\": 23.09433937072754,\n \"blob_id\": \"e78c9ad5ad6bb1a454aa717ee5e9caa52bf7d28e\",\n \"content_id\": \"26e07503338452c10745e817f95823ba2cffce06\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1276,\n \"license_type\": \"no_license\",\n \"max_line_length\": 52,\n \"num_lines\": 53,\n \"path\": \"/알고리즘/온라인저지/2022/09/0930/빙고.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\ncross = [\\n (0, 0), (1, 1), (3, 3), (4, 4),\\n (2, 2), \\n (4, 0), (3, 1), (1, 3), (0, 4),\\n ]\\n\\ndef check(call):\\n bingo = 0\\n y, x = arr_dict[call]\\n arr[y][x] = 1\\n for i in range(5): # ga-ro\\n is_bingo = True\\n for j in range(5):\\n if not arr[i][j]: is_bingo = False\\n if is_bingo: bingo += 1\\n\\n for j in range(5): # se-ro\\n is_bingo = True\\n for i in range(5):\\n if not arr[i][j]: is_bingo = False\\n if is_bingo: bingo += 1\\n\\n is_bingo = True # dae-gak-seon 1\\n for c in cross[:5]:\\n i, j = c\\n if not arr[i][j]: is_bingo = False\\n if is_bingo: bingo += 1\\n\\n is_bingo = True # dae-gak-seon 2\\n for c in cross[4:]:\\n i, j = c\\n if not arr[i][j]: is_bingo = False\\n if is_bingo: bingo += 1\\n if bingo>=3: return True\\n\\narr_dict = dict()\\nfor i in range(5):\\n nums = list(map(int, input().rstrip().split()))\\n for j in range(5): arr_dict[nums[j]] = (i, j)\\nresult = 0\\narr = [[0]*5 for _ in range(5)]\\nflag = False\\nfor i in range(5):\\n calls = list(map(int, input().rstrip().split()))\\n if flag: continue\\n for call in calls:\\n if flag: continue\\n result += 1\\n if check(call): flag = True\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.5492957830429077,\n \"alphanum_fraction\": 0.6056337952613831,\n \"avg_line_length\": 22.33333396911621,\n \"blob_id\": \"b00e7a89b9c487a1b4dc5afdc2571214cfec6529\",\n \"content_id\": \"6d0ceb89c12bd97606505acc02c6881821e78187\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 71,\n \"license_type\": \"no_license\",\n \"max_line_length\": 54,\n \"num_lines\": 3,\n \"path\": \"/알고리즘/SWEA/LEARN/Course/1. Programming Beginner/파이썬 프로그래밍 기초(2)/22차시 2. 자료구조 – 리스트, 튜플 - 연습문제 24.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"result = [[[0]*4 for i in range(3)] for j in range(2)]\\n\\nprint(result)\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.37569060921669006,\n \"alphanum_fraction\": 0.469613254070282,\n \"avg_line_length\": 17.149999618530273,\n \"blob_id\": \"1a8a1ed3c30406a2fd164b29d1a178010bb59862\",\n \"content_id\": \"fb74fce9ed63ced4256141431fca86fbabbe1d7c\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 362,\n \"license_type\": \"no_license\",\n \"max_line_length\": 37,\n \"num_lines\": 20,\n \"path\": \"/알고리즘/온라인저지/2022/09/0911/수학은 비대면강의입니다.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from copy import deepcopy\\n\\nnum = list(map(int, input().split()))\\nX, Y = deepcopy(num), deepcopy(num)\\nx, y = 0, 0\\nX[0] *= num[4]\\nX[1] *= num[4]\\nX[2] *= num[4]\\nX[3] *= num[1]\\nX[4] *= num[1]\\nX[5] *= num[1]\\nx = (X[2]-X[5])//(X[0]-X[3])\\nY[0] *= num[3]\\nY[1] *= num[3]\\nY[2] *= num[3]\\nY[3] *= num[0]\\nY[4] *= num[0]\\nY[5] *= num[0]\\ny = (Y[2]-Y[5])//(Y[1]-Y[4])\\nprint(x, y)\"\n },\n {\n \"alpha_fraction\": 0.41355931758880615,\n \"alphanum_fraction\": 0.4440678060054779,\n \"avg_line_length\": 21.769229888916016,\n \"blob_id\": \"eb0488ba01812142344f4cb0b1eae7d4534a51c6\",\n \"content_id\": \"b19ebe4bb903a740103e7a0c1b05d9e0cea54ed3\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 321,\n \"license_type\": \"no_license\",\n \"max_line_length\": 44,\n \"num_lines\": 13,\n \"path\": \"/알고리즘/온라인저지/2022/06/0623/소가 길을 건너간 이유 1.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = int(input())\\ncow = ['Zero'] + [0]*10 # 0:미발견, 1:왼쪽, 2:오른쪽\\nresult = 0\\nfor n in range(N):\\n c, lr = map(int, input().split())\\n lr += 1\\n if cow[c]:\\n if cow[c] != lr: # 길을 건넜음\\n result += 1\\n cow[c] = lr\\n else: # not cow[c]\\n cow[c] = lr\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.45856353640556335,\n \"alphanum_fraction\": 0.4806629717350006,\n \"avg_line_length\": 10.375,\n \"blob_id\": \"0f0ed25d7e6977676013aaee9f0d3fd9a00b1623\",\n \"content_id\": \"ff83e0eecfad42e6a18167e546a6fea6be381b55\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 181,\n \"license_type\": \"no_license\",\n \"max_line_length\": 41,\n \"num_lines\": 16,\n \"path\": \"/알고리즘/온라인저지/2022/02/0205/점수계산.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = int(input())\\n\\nanswers = list(map(int, input().split()))\\n\\np = 0\\nresult = 0\\n\\nfor a in answers:\\n if a:\\n p += 1\\n else:\\n p = 0\\n \\n result += p\\n\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.35537189245224,\n \"alphanum_fraction\": 0.39669421315193176,\n \"avg_line_length\": 19.33333396911621,\n \"blob_id\": \"b1e8c6103b243ac63f4f78d07b777fc44302399c\",\n \"content_id\": \"5d348fe264c832816e5bea29e3a2e52dd8f1e42f\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 121,\n \"license_type\": \"no_license\",\n \"max_line_length\": 32,\n \"num_lines\": 6,\n \"path\": \"/알고리즘/온라인저지/2022/11/1110/지각.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"for _ in range(int(input())):\\n n = int(input())\\n t = 0\\n while (t+1) + (t+1)**2 <= n:\\n t += 1\\n print(t)\"\n },\n {\n \"alpha_fraction\": 0.4692671298980713,\n \"alphanum_fraction\": 0.49527186155319214,\n \"avg_line_length\": 29.25,\n \"blob_id\": \"a4bbcac589b85097d62bce8f5a324f69e4e69670\",\n \"content_id\": \"d7a70242157d9e159a42d317d23a7373c1bdedbc\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1090,\n \"license_type\": \"no_license\",\n \"max_line_length\": 72,\n \"num_lines\": 28,\n \"path\": \"/알고리즘/온라인저지/2021/07/0731/설탕과자 뽑기.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"h, w = map(int, input().split()) # 뽑기 상자의 가로 세로\\nn = int(input()) # 막대 개수\\npoints = [] # 막대길이, 방향, 좌표 리스트\\nfor i in range(n):\\n l, d, x, y = map(int, input().split()) \\n # 막대 개수만큼 for문 돌리면서 정보 입력\\n points.append([l, d, x, y])\\n # 막대 길이, 막대 놓는 방향(0:가로, 1:세로), 막대 좌표x, 막대 좌표y(x, y = 1, 1 에서 시작)\\nboard = [] # 빈 보드\\nfor i in range(h):# 세로줄 만들면서\\n board.append([])\\n for j in range(w): # 가로에 전부 0 채우기\\n board[i].append(0)\\n\\nfor point in points:\\n if point[1] == 0: # 가로일 때\\n for i in range(point[0]): # 막대 길이만큼\\n board[point[2]-1][point[3]-1 + i] = 1\\n # 오른쪽으로 1 넣어주기\\n else: # 세로일 때\\n for j in range(point[0]): # 막대 길이만큼\\n board[point[2]-1 + j][point[3]-1] = 1\\n # 아래로 1 넣어주기\\n\\nfor i in range(h):\\n for j in range(w): \\n print(board[i][j], end=' ')\\n print() # 출력문\"\n },\n {\n \"alpha_fraction\": 0.4333333373069763,\n \"alphanum_fraction\": 0.699999988079071,\n \"avg_line_length\": 30,\n \"blob_id\": \"1b191339e0a6ab6307ef0fd7de6ede1897f98750\",\n \"content_id\": \"89911ee092dc7fbac2a5cf579b486f8357de9fee\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 30,\n \"license_type\": \"no_license\",\n \"max_line_length\": 30,\n \"num_lines\": 1,\n \"path\": \"/알고리즘/온라인저지/2022/02/0216/큰 수(BIG).py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"print((int(input()))%20000303)\"\n },\n {\n \"alpha_fraction\": 0.5206185579299927,\n \"alphanum_fraction\": 0.5979381203651428,\n \"avg_line_length\": 26.85714340209961,\n \"blob_id\": \"08c5b151b2da07dea2b0219a1c55534d7b779543\",\n \"content_id\": \"8c2ed12f30a4044d2582e8d23fc5380ea938cd0e\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 242,\n \"license_type\": \"no_license\",\n \"max_line_length\": 52,\n \"num_lines\": 7,\n \"path\": \"/알고리즘/온라인저지/2021/08/0816/remove pop.py.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"my_list = [1, 5, 4, 2, 5, 2, 3, 8, 9, 4, 2, 3, 2, 1]\\nprint(len(my_list))\\nprint(my_list)\\n# my_list.pop() # 해당 인덱스의 요소를 제거\\nmy_list.remove(5) # 가장 앞에 있는 해당 요소를 제거\\nprint(len(my_list))\\nprint(my_list)\"\n },\n {\n \"alpha_fraction\": 0.5315487384796143,\n \"alphanum_fraction\": 0.5353728532791138,\n \"avg_line_length\": 23.952381134033203,\n \"blob_id\": \"562caf35ede0d15c1aea12a59ba5bdcb2ad10a3d\",\n \"content_id\": \"10b4c0ed5edd5e7bff322316a9354b8c329443bf\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 539,\n \"license_type\": \"no_license\",\n \"max_line_length\": 52,\n \"num_lines\": 21,\n \"path\": \"/알고리즘/온라인저지/2021/07/0731/정수 1개 입력받아 분류하기.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"a = int(input())\\ndef odd_even(n): # True: 홀수, False: 짝수\\n if n % 2 == True:\\n return True\\n else:\\n return False\\n\\ndef plus_minus(n): # True: 양수, False: 짝수\\n if n >= 0:\\n return True\\n else:\\n return False\\n\\nif odd_even(a) == False and plus_minus(a) == False:\\n print(\\\"A\\\") # A: - and even\\nelif plus_minus(a) == False and odd_even(a) == True:\\n print(\\\"B\\\") # B: - and odd\\nelif plus_minus(a) == True and odd_even(a) == False:\\n print(\\\"C\\\") # C: + and even\\nelse:\\n print(\\\"D\\\") # D: + and odd\"\n },\n {\n \"alpha_fraction\": 0.4942166209220886,\n \"alphanum_fraction\": 0.5373291373252869,\n \"avg_line_length\": 23.41025733947754,\n \"blob_id\": \"a644123420792555f4471a34305c9b9e83aaf94b\",\n \"content_id\": \"a352b4e9c6d742bfc81c6dbe1defc867c9e76ccd\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1293,\n \"license_type\": \"no_license\",\n \"max_line_length\": 63,\n \"num_lines\": 39,\n \"path\": \"/알고리즘/온라인저지/2021/10/1015/숨바꼭질.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from collections import deque # deque의 메서드인 popleft()를 사용하기 위함\\n\\nN, M = map(int, input().split())\\n\\nresult = 0\\n\\nq = deque()\\nq.append((N, result)) # N부터 출발합니다\\n\\ncheck = set() # +1 -1 *2 를 진행하면서 중복되는 숫자가 발견될 경우 \\n# q에 추가하는 것을 막기 위해 중복검사를 해주기 위한 set()\\n\\nwhile q:\\n if not N and not M or N == M: # 수빈이가 동생과 같은 위치에 있을 때\\n break\\n \\n tmp = q.popleft() # BFS\\n \\n a = tmp[0] + 1\\n b = tmp[0] - 1\\n c = tmp[0] * 2\\n cnt = tmp[1] + 1 # 수빈이가 이동하였고 1초가 지났습니다\\n \\n if M in (a, b, c): # 이동중 수빈이가 동생을 발견하였을 때\\n result = cnt # 그 때의 시간을 저장\\n break\\n\\n # 동생은 0부터 100000 사이에 있습니다, 범위를 벗어나면 동생을 찾을 수 없습니다\\n if a not in check and 0<=a<=100000: # 간 적이 없고, 범위를 벗어나지 않으면\\n q.append((a, cnt)) # 다음 가볼 곳에 추가\\n check.add(a) # 가본 곳에 추가\\n if b not in check and 0<=b<=100000:\\n q.append((b, cnt))\\n check.add(b) \\n if c not in check and 0<=c<=100000:\\n q.append((c, cnt))\\n check.add(c)\\n\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.4542483687400818,\n \"alphanum_fraction\": 0.5065359473228455,\n \"avg_line_length\": 26.909090042114258,\n \"blob_id\": \"3ba45e575dfb3f2645c083b4403e3d654bcbacd8\",\n \"content_id\": \"3fcb400911d47399b69c278136fa492d8f33bf5d\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 306,\n \"license_type\": \"no_license\",\n \"max_line_length\": 42,\n \"num_lines\": 11,\n \"path\": \"/알고리즘/온라인저지/2022/11/1102/Doubles.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"while True:\\n nums = list(map(int, input().split()))\\n if nums[0] == -1: break\\n result = 0\\n arr = [0]*101\\n for num in nums[:len(nums)-1]:\\n if not arr[num]: arr[num] = 1\\n for num in nums[:len(nums)-1]:\\n if num*2 <= 100 and arr[num*2]: \\n result += 1\\n print(result)\"\n },\n {\n \"alpha_fraction\": 0.5,\n \"alphanum_fraction\": 0.5246913433074951,\n \"avg_line_length\": 15.100000381469727,\n \"blob_id\": \"2b538b140f825cf32719241484a43d30e31a3e90\",\n \"content_id\": \"5be8026accd9a43e3098fe627e359643ba3096f8\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 162,\n \"license_type\": \"no_license\",\n \"max_line_length\": 36,\n \"num_lines\": 10,\n \"path\": \"/알고리즘/온라인저지/2022/02/0205/지능형 기차 2.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"maxx = 0\\nin_train = 0\\n\\nfor _ in range(10):\\n l, b = map(int, input().split())\\n in_train += b-l\\n if in_train > maxx:\\n maxx = in_train\\n\\nprint(maxx)\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.4041095972061157,\n \"alphanum_fraction\": 0.48630136251449585,\n \"avg_line_length\": 20,\n \"blob_id\": \"50d4ac02cc332704c25d1aa06a073b20f27b5c2b\",\n \"content_id\": \"bdb820d257d11dac78828ee1181d101da13561e0\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 146,\n \"license_type\": \"no_license\",\n \"max_line_length\": 28,\n \"num_lines\": 7,\n \"path\": \"/알고리즘/온라인저지/2022/05/0518/완전 제곱수.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = int(input())\\nresult = 0\\nfor b in range(1, 501):\\n for a in range(1, 501):\\n if a**2 == b**2 + N:\\n result += 1\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.5081967115402222,\n \"alphanum_fraction\": 0.5081967115402222,\n \"avg_line_length\": 19.66666603088379,\n \"blob_id\": \"f34121bf32314ea2c691d946ab37b107acece598\",\n \"content_id\": \"6e7a0bec8a3e8d6e26254a0e33eae04501c1a408\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 61,\n \"license_type\": \"no_license\",\n \"max_line_length\": 29,\n \"num_lines\": 3,\n \"path\": \"/알고리즘/온라인저지/2023/04/0406/Copier.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"for _ in range(int(input())):\\n N = input()\\n print(N, N)\"\n },\n {\n \"alpha_fraction\": 0.33282673358917236,\n \"alphanum_fraction\": 0.36018237471580505,\n \"avg_line_length\": 18.969696044921875,\n \"blob_id\": \"b0dc75955d7bd099e235e7653fa42fb53eaec471\",\n \"content_id\": \"1ec072252516183f2eb0ed0e7eb076c1ee057952\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 658,\n \"license_type\": \"no_license\",\n \"max_line_length\": 59,\n \"num_lines\": 33,\n \"path\": \"/알고리즘/SWEA/LEARN/Course/2. Programming Intermediate/8. 파이썬 SW문제해결 기본 Tree/8차시 8일차 - 이진 힙.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"TC = int(input())\\n\\nfor tc in range(1, TC+1):\\n N = int(input())\\n nodes = list(map(int, input().split()))\\n arr = [0]\\n\\n for n in nodes:\\n arr.append(n)\\n\\n for i in range(1, N//2+1):\\n try:\\n if arr[i] > arr[i*2]:\\n arr[i], arr[i*2] = arr[i*2], arr[i] \\n\\n if arr[i] > arr[i*2+1]:\\n arr[i], arr[i*2+1] = arr[i*2+1], arr[i]\\n \\n except:\\n pass\\n\\n n = len(arr)\\n result = 0\\n \\n while True:\\n N //= 2\\n\\n result += arr[N]\\n\\n if N == 1:\\n break\\n \\n print('#{} {}'.format(tc, result))\"\n },\n {\n \"alpha_fraction\": 0.5388127565383911,\n \"alphanum_fraction\": 0.5616438388824463,\n \"avg_line_length\": 14.714285850524902,\n \"blob_id\": \"5f27c780f1c7e72917adadedae4b0b3206130e92\",\n \"content_id\": \"f0ad61fb19f7b422e0b3af84c118fc1257e092e5\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 219,\n \"license_type\": \"no_license\",\n \"max_line_length\": 34,\n \"num_lines\": 14,\n \"path\": \"/알고리즘/온라인저지/2022/09/0927/3의 배수.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\n\\nX = input().rstrip()\\nresult = 0\\nwhile len(X)>1:\\n tmp = 0\\n for x in X:\\n tmp += int(x)\\n X = str(tmp)\\n result += 1\\nprint(result)\\nprint('NO' if int(X)%3 else 'YES')\"\n },\n {\n \"alpha_fraction\": 0.42032331228256226,\n \"alphanum_fraction\": 0.46766743063926697,\n \"avg_line_length\": 31.11111068725586,\n \"blob_id\": \"58e661d2ab7df3998a889c99923c8ea46357e35b\",\n \"content_id\": \"7c7c9f56b5c9486426b97dacf694bfed51c26506\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 866,\n \"license_type\": \"no_license\",\n \"max_line_length\": 64,\n \"num_lines\": 27,\n \"path\": \"/알고리즘/온라인저지/2022/09/0913/정사각형.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"for _ in range(int(input())):\\n dots = [tuple(map(int, input().split())) for __ in range(4)]\\n x1, y1 = dots[0][0], dots[0][1]\\n distance_pows = []\\n for dot in dots[1:]:\\n x2, y2 = dot[0], dot[1]\\n distance_pow = abs(x1-x2)**2 + abs(y1-y2)**2\\n distance_pows.append(distance_pow)\\n flag = 1\\n distance_pows.sort()\\n if distance_pows[0] != distance_pows[1]:\\n print(0)\\n else:\\n for self in dots:\\n if not flag: break\\n x1, y1 = self[0], self[1]\\n tmp = []\\n for other in dots:\\n if self != other:\\n x2, y2 = other[0], other[1]\\n pow = abs(x1-x2)**2 + abs(y1-y2)**2\\n tmp.append(pow)\\n tmp.sort()\\n if tmp != distance_pows: flag = 0\\n print(flag)\\n\\n# https://www.acmicpc.net/problem/1485\"\n },\n {\n \"alpha_fraction\": 0.4154929518699646,\n \"alphanum_fraction\": 0.44366195797920227,\n \"avg_line_length\": 19.314285278320312,\n \"blob_id\": \"27390bc83979c9a27536a33599189f70a718ad67\",\n \"content_id\": \"d99a00e3f01bb74f4ea12d47da0b78786d1929a4\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 710,\n \"license_type\": \"no_license\",\n \"max_line_length\": 49,\n \"num_lines\": 35,\n \"path\": \"/알고리즘/온라인저지/2021/08/0830/DFS와 BFS.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ndef dfs(v):\\n visited[v] = 1\\n print(v, end=' ')\\n for w in range(1, N+1):\\n if G[v][w] == 1 and not visited[w]:\\n dfs(w)\\n\\ndef bfs(v, n):\\n q = []\\n visited = [0] * (N+1)\\n q.append(v)\\n visited[v] = 1\\n while q:\\n t = q.pop(0)\\n print(t, end=' ')\\n for i in range(1, N+1):\\n if G[t][i] == 1 and not visited[i]:\\n q.append(i)\\n visited[i] = visited[t] + 1\\n\\nN, M, V = map(int, sys.stdin.readline().split())\\n\\nG = [[0] * (N+1) for _ in range(N+1)]\\nfor _ in range(M):\\n u, v = map(int, sys.stdin.readline().split())\\n G[u][v] = G[v][u] = 1\\n\\nvisited = [0] * (N+1)\\ndfs(V)\\nprint()\\n\\nvisited = [0] * (N+1)\\nbfs(V, N)\"\n },\n {\n \"alpha_fraction\": 0.4791666567325592,\n \"alphanum_fraction\": 0.4962121248245239,\n \"avg_line_length\": 20.571428298950195,\n \"blob_id\": \"95990ebe98345f6d0b1f318b722434e733197b1b\",\n \"content_id\": \"22c16e1d9a3285f162073566de95c0e7ede0a7b5\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1410,\n \"license_type\": \"no_license\",\n \"max_line_length\": 46,\n \"num_lines\": 49,\n \"path\": \"/알고리즘/온라인저지/2022/08/0817/탑.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\n\\nN = int(input())\\nT = list(map(int, input().split())) # tower\\nS, result = [], [0] * N # stack\\nfor i in range(N):\\n t = T[i]\\n while S and T[S[-1]] < t: S.pop()\\n if S: result[i] = S[-1] + 1\\n S.append(i)\\nprint(*result)\\n\\n\\\"\\\"\\\"\\n스택에 들어있는, 현재 탑보다 낮은 탑의 인덱스를 전부 제거한다\\n스택이 남아있을 때, stack[-1]의 인덱스는\\n앞에서 등장했던 탑들 중 현재 탑 다음으로 높은 탑이 되고\\n레이저 신호는 여기서 수신될 것이다\\n현재 탑의 신호 수신탑에, stack[-1]+1번째 탑을 저장한다\\n그리고 해당 탑의 인덱스를 스택에 추가한다\\n\\n늘 코드의 시작부터 적는 습관이 있었는데\\n위의 코드는 진행 중간만 깔끔하게 적혀있다\\n위 코드처럼 짤 수 있도록 더 열심히 해야겠다... ㅜㅜ\\n\\\"\\\"\\\"\\n\\n# 쾅\\n# import sys\\n\\n# input = sys.stdin.readline\\n\\n# N = int(input())\\n# T = list(map(int, input().split())) # tower\\n# S = [] # stack\\n# result = [0] * N\\n# for i in range(N-1, -1, -1): # 진행은 우->좌 가 맞다\\n# t = T[i]\\n# if not S: \\n# S.append((t, i))\\n# else:\\n# S.append((t, i))\\n# for j in range(len(S)-1, -1, -1):\\n# if j < len(S)-1:\\n# if t > S[j][0]:\\n# result[S[j][1]] = i+1\\n# S.pop()\\n# else: pass\\n# print(*result)\"\n },\n {\n \"alpha_fraction\": 0.4103773534297943,\n \"alphanum_fraction\": 0.4245283007621765,\n \"avg_line_length\": 20.299999237060547,\n \"blob_id\": \"0f62e005527198dc37b8127eecec4f274dc7e27d\",\n \"content_id\": \"4b8951832eba7d583131baab381e4dea27cf8452\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 212,\n \"license_type\": \"no_license\",\n \"max_line_length\": 32,\n \"num_lines\": 10,\n \"path\": \"/알고리즘/온라인저지/2022/04/0407/Can you add this.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"T = int(input())\\nfor t in range(T):\\n result = 0\\n tmp = input().split()\\n for i in tmp:\\n if i[0] == '-':\\n result -= int(i[1:])\\n else:\\n result += int(i)\\n print(result)\"\n },\n {\n \"alpha_fraction\": 0.5512048006057739,\n \"alphanum_fraction\": 0.5783132314682007,\n \"avg_line_length\": 22.785715103149414,\n \"blob_id\": \"ba05fb838517cf92c1090ebe4ae7d0fc287cf2fd\",\n \"content_id\": \"208ca4cf273e67676fdc3da4ec23dd114b2c95f9\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 332,\n \"license_type\": \"no_license\",\n \"max_line_length\": 63,\n \"num_lines\": 14,\n \"path\": \"/알고리즘/온라인저지/2022/10/1002/경로 찾기.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\nINF = int(1e9)\\n\\nN = int(input().rstrip())\\narr = [list(map(int, input().rstrip().split())) for _ in [0]*N]\\nfor k in range(N):\\n for a in range(N):\\n for b in range(N):\\n if arr[a][k] and arr[k][b]: arr[a][b] = 1\\nfor a in arr: print(*a)\\n\\n# https://www.acmicpc.net/problem/11403\"\n },\n {\n \"alpha_fraction\": 0.5639810562133789,\n \"alphanum_fraction\": 0.6113743782043457,\n \"avg_line_length\": 22.55555534362793,\n \"blob_id\": \"7482ad47eb32b41d957f396f56b49f4830765523\",\n \"content_id\": \"d290b15b864464a7011c6c26727e06ad3a5a249c\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 211,\n \"license_type\": \"no_license\",\n \"max_line_length\": 38,\n \"num_lines\": 9,\n \"path\": \"/알고리즘/온라인저지/2022/07/0731/수 찾기.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = int(input())\\narr1 = set(map(int, input().split()))\\nM = int(input())\\narr2 = list(map(int, input().split()))\\nfor a in arr2:\\n if a in arr1: print(1)\\n else: print(0)\\n\\n# https://www.acmicpc.net/problem/1920\"\n },\n {\n \"alpha_fraction\": 0.4373672902584076,\n \"alphanum_fraction\": 0.46284499764442444,\n \"avg_line_length\": 22.600000381469727,\n \"blob_id\": \"66f54d43505513792fb478482d5f158c42064dd5\",\n \"content_id\": \"022ba88eddb71522afe5587380cc80cd3f33a9de\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 471,\n \"license_type\": \"no_license\",\n \"max_line_length\": 54,\n \"num_lines\": 20,\n \"path\": \"/알고리즘/온라인저지/2022/09/0927/별 찍기 - 23.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\n\\nN = int(input().rstrip())\\nmid = 1+2*(N-2)\\nresult = ['*'*N+' '*mid+'*'*N]\\nstart = 0\\nsize = N-2\\nfor i in range(2, N+1):\\n start, mid = start+1, mid-2\\n tmp = ' '*start\\n if mid>0: \\n tmp += '*' + ' '*size + '*'\\n tmp += ' '*mid\\n tmp += '*' + ' '*size + '*'\\n else: tmp += '*' + ' '*size + '*' + ' '*size + '*'\\n result.append(tmp)\\nfor r in result[:len(result)-1]: print(r)\\nfor r in result[::-1]: print(r)\"\n },\n {\n \"alpha_fraction\": 0.6571428775787354,\n \"alphanum_fraction\": 0.6571428775787354,\n \"avg_line_length\": 35,\n \"blob_id\": \"47ddbcbb3a1f19f158da307ddb8a569cb7c7bc73\",\n \"content_id\": \"a52722a4efcfeacd29591cee33b7287245153837\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 35,\n \"license_type\": \"no_license\",\n \"max_line_length\": 35,\n \"num_lines\": 1,\n \"path\": \"/알고리즘/SWEA/LEARN/Course/1. Programming Beginner/파이썬 프로그래밍 기초(2)/12차시 2. 자료구조 – 리스트, 튜플 - 연습문제 13.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"print(sum(list(map(int, input()))))\"\n },\n {\n \"alpha_fraction\": 0.5011037588119507,\n \"alphanum_fraction\": 0.5253863334655762,\n \"avg_line_length\": 18.7391300201416,\n \"blob_id\": \"dfe84252545d30e4be97bce1a5b4594236eae14e\",\n \"content_id\": \"959135c92441edf416979513b33a792bae6656d7\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 493,\n \"license_type\": \"no_license\",\n \"max_line_length\": 51,\n \"num_lines\": 23,\n \"path\": \"/알고리즘/온라인저지/2021/08/0829/수열.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\nN = int(sys.stdin.readline())\\nnums = list(map(int, sys.stdin.readline().split()))\\ncnt = 1\\nresult = 1\\n# 증가할 때 따로, 감소할 때 따로, 두번 돌려주는 코드\\nfor i in range(len(nums)-1):\\n if nums[i] >= nums[i+1]:\\n cnt += 1\\n else:\\n cnt = 1\\n if result < cnt:\\n result = cnt\\n\\ncnt = 1\\nfor i in range(len(nums)-1):\\n if nums[i] <= nums[i+1]:\\n cnt += 1\\n else:\\n cnt = 1\\n if result < cnt:\\n result = cnt\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.6521739363670349,\n \"alphanum_fraction\": 0.6521739363670349,\n \"avg_line_length\": 18.85714340209961,\n \"blob_id\": \"8fa4bce5a1f44e31615864402136bcbf041db539\",\n \"content_id\": \"76bd35bc2e590b97b4b1a7bcbc24b135358f0e6b\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 138,\n \"license_type\": \"no_license\",\n \"max_line_length\": 32,\n \"num_lines\": 7,\n \"path\": \"/알고리즘/온라인저지/2021/08/0822/수 정렬하기 2.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"T = int(input())\\nnumbers = []\\nfor tc in range(T):\\n numbers.append(int(input()))\\nnumbers.sort()\\nfor number in numbers:\\n print(number)\"\n },\n {\n \"alpha_fraction\": 0.5740740895271301,\n \"alphanum_fraction\": 0.5820105671882629,\n \"avg_line_length\": 18.947368621826172,\n \"blob_id\": \"7191e446c4a4164453e9763a9835c01492b68a66\",\n \"content_id\": \"77be887efdafc5c47dee91640b63b85da83f70ce\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 378,\n \"license_type\": \"no_license\",\n \"max_line_length\": 35,\n \"num_lines\": 19,\n \"path\": \"/알고리즘/온라인저지/2022/03/0316/카드 뽑기.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from pprint import pprint\\n\\nN, M, K = map(int, input().split())\\narr = [[] for _ in range(N)]\\nfor m in range(M):\\n arr[m].append(True)\\nfor m in range(M, N):\\n arr[m].append(False)\\n# print(arr)\\nfor k in range(K):\\n arr[k].append(True)\\nfor k in range(K, N):\\n arr[k].append(False)\\n# pprint(arr)\\nresult = N\\nfor a in arr:\\n if a[0] != a[1]:\\n result -= 1\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.4307228922843933,\n \"alphanum_fraction\": 0.46084338426589966,\n \"avg_line_length\": 14.7619047164917,\n \"blob_id\": \"a7c24bdfe850d476027dc9598a0466c568c88f8d\",\n \"content_id\": \"2da38b0e8e2e448feb24250b87110f15a12810e9\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 332,\n \"license_type\": \"no_license\",\n \"max_line_length\": 54,\n \"num_lines\": 21,\n \"path\": \"/알고리즘/SWEA/LEARN/Course/2. Programming Intermediate/8. 파이썬 SW문제해결 기본 Tree/7차시 8일차 - 이진탐색.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"def makeTree(n):\\n global count\\n\\n if n <= N:\\n makeTree(n*2)\\n\\n tree[n] = count\\n count += 1\\n\\n makeTree(n*2 + 1)\\n\\nTC = int(input())\\nfor tc in range(TC):\\n N = int(input())\\n \\n tree = [0 for _ in range(N+1)]\\n count = 1\\n\\n makeTree(1)\\n\\n print('#{} {} {}'.format(tc, tree[1], tree[N//2]))\\n \"\n },\n {\n \"alpha_fraction\": 0.4254473149776459,\n \"alphanum_fraction\": 0.46222662925720215,\n \"avg_line_length\": 29.515151977539062,\n \"blob_id\": \"e6e8f2e5753be2a2861388f3bd3c0cb86e68a24c\",\n \"content_id\": \"a4305429cc023cd0371e249bf46a018c2a09e98b\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1038,\n \"license_type\": \"no_license\",\n \"max_line_length\": 77,\n \"num_lines\": 33,\n \"path\": \"/알고리즘/[템플릿]/BFS/토마토 3차원.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from collections import deque\\n\\n# 상 하 전 후 좌 우 델타이동\\ndz, dy, dx = [-1, 1, 0, 0, 0, 0], [0, 0, -1, 1, 0, 0], [0, 0, 0, 0, -1, 1]\\nM, N, H = map(int, input().split())\\narr = [[list(map(int, input().split())) for _ in range(N)] for _ in range(H)]\\nQ = deque()\\nfor k in range(H):\\n for i in range(N):\\n for j in range(M):\\n if arr[k][i][j] == 1:\\n Q.append((k, i, j, 0)) # z, y, x, day\\n arr[k][i][j] = 0\\nresult = 0\\nwhile Q:\\n z, y, x, day = Q.popleft()\\n if arr[z][y][x] == 1: continue\\n arr[z][y][x] = 1\\n result = max(result, day)\\n for i in range(6): # 상 하 전 후 좌 우\\n nz, ny, nx = z+dz[i], y+dy[i], x+dx[i]\\n if 0<=nz<H and 0<=ny<N and 0<=nx<M and arr[nz][ny][nx] == 0:\\n Q.append((nz, ny, nx, day+1))\\nfor k in range(H):\\n if result == -1: break\\n for i in range(N):\\n for j in range(M):\\n if arr[k][i][j] == 0:\\n result = -1\\n break\\nprint(result)\\n\\n# https://www.acmicpc.net/problem/7569\"\n },\n {\n \"alpha_fraction\": 0.48466256260871887,\n \"alphanum_fraction\": 0.5030674934387207,\n \"avg_line_length\": 16.210525512695312,\n \"blob_id\": \"3df82339556a451a01526cddb98ceb5fdd713aeb\",\n \"content_id\": \"7fad2c804bae41a95c125f75fe082417fd5d2fac\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 404,\n \"license_type\": \"no_license\",\n \"max_line_length\": 36,\n \"num_lines\": 19,\n \"path\": \"/알고리즘/온라인저지/2023/02/0226/팰린드롬 만들기.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"S = input()\\nL, S_rev = len(S), S[::-1]\\nresult = 0\\n\\nfor i in range(L, 0, -1):\\n if S_rev[:i] == S_rev[:i][::-1]:\\n result = i+(L-i)*2\\n break\\n\\nprint(result)\\n\\n\\\"\\\"\\\"\\nex) abczzzz -> abc + zzzz + cba\\n\\nL = 문자열 전체의 길이(abczzzz)\\ni = 뒤에서 가장 긴 팰린드롬의 길이(zzzz)\\nL-i = 문자열 전체에서 가장 긴 팰린드롬을 뺀 길이(abc)\\nresult = (L-i) + i + (L-i)\\n\\\"\\\"\\\"\"\n },\n {\n \"alpha_fraction\": 0.4526315927505493,\n \"alphanum_fraction\": 0.5052631497383118,\n \"avg_line_length\": 12.714285850524902,\n \"blob_id\": \"a42f0f25848b5ffe281fd4d60629c87b6bf44486\",\n \"content_id\": \"097e778b6c597ca330ab185f22eda60b7b0dfcc1\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 95,\n \"license_type\": \"no_license\",\n \"max_line_length\": 22,\n \"num_lines\": 7,\n \"path\": \"/알고리즘/SWEA/LEARN/Course/1. Programming Beginner/파이썬 프로그래밍 기초(2)/11차시 2. 자료구조 – 리스트, 튜플 - 연습문제 12.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"s = set()\\n\\nfor i in range(1, 21):\\n if i%3 or i%5:\\n s.add(i*i)\\n\\nprint(sorted(list(s)))\"\n },\n {\n \"alpha_fraction\": 0.420634925365448,\n \"alphanum_fraction\": 0.43386244773864746,\n \"avg_line_length\": 26.071428298950195,\n \"blob_id\": \"3907629e6c8256a07e4480e33b85f861816a1b7a\",\n \"content_id\": \"760aa93cbb579555c38c9f7a66dff07f11c161ef\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 378,\n \"license_type\": \"no_license\",\n \"max_line_length\": 52,\n \"num_lines\": 14,\n \"path\": \"/알고리즘/온라인저지/2022/07/0727/김인천씨의 식료품가게 (Large).py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"T = int(input())\\nfor t in range(1, T+1):\\n N = int(input())\\n A = list(map(int, input().split())) # all prices\\n result = []\\n for i in range(N):\\n tmp = A.pop(0)\\n O = (tmp//3) * 4 # original\\n for j in range(len(A)):\\n if A[j] == O:\\n A.pop(j)\\n break\\n result.append(tmp)\\n print(f'Case #{t}:', *result)\"\n },\n {\n \"alpha_fraction\": 0.3589743673801422,\n \"alphanum_fraction\": 0.43589743971824646,\n \"avg_line_length\": 8.375,\n \"blob_id\": \"b3a1762d1b90c8f9c9ca34a680dc6bbf5720f75c\",\n \"content_id\": \"ceaa32df0a36eeac6f6e5900f31e993ba8df0f7a\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 78,\n \"license_type\": \"no_license\",\n \"max_line_length\": 22,\n \"num_lines\": 8,\n \"path\": \"/알고리즘/온라인저지/2022/01/0131/알파벳 개수.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"dp = [0] * 26\\n\\nS = input()\\n\\nfor s in S:\\n dp[ord(s)-97] += 1\\n\\nprint(*dp) \"\n },\n {\n \"alpha_fraction\": 0.550939679145813,\n \"alphanum_fraction\": 0.5934718251228333,\n \"avg_line_length\": 21,\n \"blob_id\": \"e50bc5527d0bf28dce2f3a59022703f7ffc05d94\",\n \"content_id\": \"b1b60999feb3aae2a58c5d0586569a69918233ee\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1311,\n \"license_type\": \"no_license\",\n \"max_line_length\": 52,\n \"num_lines\": 46,\n \"path\": \"/알고리즘/[템플릿]/분할정복/피보나치 수 6.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\nmod = int(1e9)+7\\n\\ndef multiply(matrix1, matrix2): # 행렬 곱셈\\n output = []\\n for i in range(2):\\n output.append([])\\n for j in range(2):\\n tmp = 0\\n for k in range(2):\\n tmp += matrix1[i][k] * matrix2[k][j]\\n output[i].append(tmp%mod)\\n return output\\n\\ndef power(matrix, n): # 거듭제곱 분할정복\\n if n == 1: return matrix\\n tmp = power(matrix, n//2)\\n if n%2 == 0:\\n return multiply(tmp, tmp)\\n else:\\n return multiply(multiply(tmp, tmp), matrix)\\n\\nN = int(input().rstrip())\\nmatrix = [[1, 1], [1, 0]] # 피보나치 행렬 거듭제곱 일반항\\nprint(power(matrix, N)[0][1])\\n\\n\\\"\\\"\\\"\\n피보나치 일반항을, 행렬의 거듭제곱으로 변환할 줄 알아야 하고\\n행렬의 거듭제곱을 할 줄 알아야 하고\\n거듭제곱을 분할정복으로 할 줄 알아야 풀 수 있는 문제이다\\n2022-10-08기준, 가장 빠른 속도로 피보나치를 구할 수 있는 코드이다\\n\\n<참고한 링크>\\n참고한 코드 원문\\nhttps://ca.ramel.be/50\\n\\n백준 피보나치 블로그글\\nhttps://www.acmicpc.net/blog/view/28\\n\\n피보나치가 [1, 1],[1, 0]의 거듭제곱이 되는 과정\\nhttps://www.youtube.com/watch?v=uX2IsIykLJc\\n\\\"\\\"\\\"\\n\\n# https://www.acmicpc.net/problem/11444\"\n },\n {\n \"alpha_fraction\": 0.5959885120391846,\n \"alphanum_fraction\": 0.6060171723365784,\n \"avg_line_length\": 18.97142791748047,\n \"blob_id\": \"c37d208ed72e37ae26204315abe9bf4d1a3f3c32\",\n \"content_id\": \"0b8c44931d1a0bc860f62cdefb003c2d6af29a2c\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 950,\n \"license_type\": \"no_license\",\n \"max_line_length\": 54,\n \"num_lines\": 35,\n \"path\": \"/알고리즘/온라인저지/2022/10/1004/N과 M (5).py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\n\\ndef solve(depth, N, M):\\n if depth == M:\\n print(*result); return\\n for i in range(N):\\n if not visited[i]:\\n visited[i] = True; result.append(arr[i])\\n solve(depth+1, N, M)\\n result.pop(); visited[i] = False\\n\\nN, M = map(int, input().rstrip().split())\\narr = sorted(list(map(int, input().rstrip().split())))\\nvisited = [False] * N\\nresult = []\\nsolve(0, N, M)\\n\\n\\\"\\\"\\\"\\nBFS 돌 때 \\n방문하지 않았으면\\n방문처리, Q에 추가 해주듯이\\nDFS도 똑같이\\n함수 자체 메모리를 Q처럼 활용하면서\\n방문하지 않았으면\\n방문처리, 다음 탐색\\n나오면서 방문 풀어주고, 탐색점 취소해주고\\n그러니까\\nBFS DFS 차이는\\n다른건 다 같고, 방문지점을 당장갈거냐(DFS), 나중에 갈거냐(BFS) 인 것 같다\\n진짜 근데 DFS는 구현이 왤케 감이 안잡히냐 어렵네\\n\\\"\\\"\\\"\\n\\n# https://www.acmicpc.net/problem/15654\"\n },\n {\n \"alpha_fraction\": 0.5014662742614746,\n \"alphanum_fraction\": 0.5190615653991699,\n \"avg_line_length\": 19.117647171020508,\n \"blob_id\": \"180fbbcc7e64da3a44ba8f43929d24b31d2eaf5c\",\n \"content_id\": \"9f6247bd5668bb3612ae42497f942fd7ef6fa622\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 341,\n \"license_type\": \"no_license\",\n \"max_line_length\": 33,\n \"num_lines\": 17,\n \"path\": \"/알고리즘/온라인저지/2021/08/0825/요세푸스 문제.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N, K = map(int, input().split())\\nq = list(range(1, N+1))\\npointer = K-1\\nresult = []\\nwhile q:\\n result.append(q.pop(pointer))\\n pointer += K - 1\\n if not len(q):\\n break\\n else:\\n pointer %= len(q)\\n \\nprint('<', end='')\\nprint(result[0], end='')\\nfor i in range(1, len(result)):\\n print(',', result[i], end='')\\nprint('>')\"\n },\n {\n \"alpha_fraction\": 0.4923076927661896,\n \"alphanum_fraction\": 0.5153846144676208,\n \"avg_line_length\": 20.83333396911621,\n \"blob_id\": \"55407429dd335b586d619e417195bd491252b097\",\n \"content_id\": \"1c1f91116f638f71cfc0e068b5c1df45ef3d5675\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 130,\n \"license_type\": \"no_license\",\n \"max_line_length\": 40,\n \"num_lines\": 6,\n \"path\": \"/알고리즘/온라인저지/2023/05/0510/POT.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"result = 0\\nfor i in range(int(input())):\\n N = input()\\n N, P = int(N[:len(N)-1]), int(N[-1])\\n result += N**P\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.5361445546150208,\n \"alphanum_fraction\": 0.5481927990913391,\n \"avg_line_length\": 18.58823585510254,\n \"blob_id\": \"fae8757ca2261ac20a2ef53e8af0bbab84ee530a\",\n \"content_id\": \"cd4fb7b3c4b22ecfb736d011742825a2fd22e444\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 332,\n \"license_type\": \"no_license\",\n \"max_line_length\": 32,\n \"num_lines\": 17,\n \"path\": \"/알고리즘/온라인저지/2022/06/0618/뚊.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N, M = map(int, input().split())\\nchar = []\\nis_same = []\\nfor n in range(N):\\n char.append(input())\\nfor n in range(N):\\n is_same.append(input())\\nresult = 'Not Eyfa'\\ntmp = []\\nfor i in range(N):\\n tmp2 = ''\\n for c in char[i]:\\n tmp2 = tmp2 + c + c\\n tmp.append(tmp2)\\nif tmp == is_same:\\n result = 'Eyfa'\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.5392376780509949,\n \"alphanum_fraction\": 0.5526905655860901,\n \"avg_line_length\": 27.80645179748535,\n \"blob_id\": \"28921cb3d9f496e8d7c132824af343c27f7efffe\",\n \"content_id\": \"638d288a2be34894e7117f60705d9eee0a6fd805\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1094,\n \"license_type\": \"no_license\",\n \"max_line_length\": 62,\n \"num_lines\": 31,\n \"path\": \"/알고리즘/온라인저지/2022/08/0828/특정 거리의 도시 찾기.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys, heapq\\n\\ninput = sys.stdin.readline\\nINF = int(1e9) # 가상의 최대 거리\\n\\ndef dijkstra(start):\\n distance[start] = 0\\n heapq.heappush(Q, (0, start))\\n while Q:\\n dist, now = heapq.heappop(Q)\\n for next, weight in data[now]: # weight = 1, 출력용으로만 사용\\n cost = dist + 1\\n if cost < distance[next]:\\n distance[next] = cost\\n heapq.heappush(Q, (cost, next))\\n\\nV, E, K, X = map(int, input().split())\\ndata = [[] for _ in range(V+1)]\\nfor _ in range(E):\\n A, B = map(int, input().split())\\n data[A].append((B, 1)) # 가중치 = 1\\ndistance = [INF] * (V+1) # 가상의 최대 거리 배열\\nQ = []\\ndijkstra(X) # X부터 시작하여 다른 도시까지 이동하는 최소 거리 배열 값 구하기\\nflag = False # K거리인 도시가 있는지 체크하는 플래그\\nfor i in range(1, len(distance)):\\n if distance[i] == K:\\n print(i) # 도시 번호 출력\\n flag = True # 최소 거리가 K에 해당하는 도시가 있음\\nif not flag: # 해당하는 도시가 없을 경우\\n print(-1)\"\n },\n {\n \"alpha_fraction\": 0.394812673330307,\n \"alphanum_fraction\": 0.5100864768028259,\n \"avg_line_length\": 17.3157901763916,\n \"blob_id\": \"a62951e5e3dd69903716d6251c5e0b6b9e2d30bc\",\n \"content_id\": \"8a549b34b13a94dd4da11f29403edec5d02b3cee\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 347,\n \"license_type\": \"no_license\",\n \"max_line_length\": 39,\n \"num_lines\": 19,\n \"path\": \"/알고리즘/온라인저지/2022/07/0716/트럭 주차.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"fees = list(map(int, input().split()))\\nresult = 0\\nparking = [0] * 101\\nfor i in range(3):\\n IN, OUT = map(int, input().split())\\n for j in range(IN, OUT):\\n parking[j] += 1\\nfor p in parking:\\n result += p*fees[p-1]\\nprint(result)\\n\\n\\\"\\\"\\\"\\n1 2 3 4 5 \\n 3 4 \\n 2 3 4 5 6 7 \\n5 6 3 3 6 5 5\\n17 20 36\\n\\\"\\\"\\\"\\n# print(sum([5, 6, 6, 6, 5, 5]))\"\n },\n {\n \"alpha_fraction\": 0.5721153616905212,\n \"alphanum_fraction\": 0.5849359035491943,\n \"avg_line_length\": 33.66666793823242,\n \"blob_id\": \"11d64cb999ecb91b9b6eff90bb52d0a2ded8be87\",\n \"content_id\": \"631c8b41ef131f289cc8f9a6fed02af85dd14ef9\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1066,\n \"license_type\": \"no_license\",\n \"max_line_length\": 68,\n \"num_lines\": 18,\n \"path\": \"/알고리즘/온라인저지/2021/09/0928/소트인사이드.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = input()\\na = [] # N을 쪼개어 담을 리스트\\nfor n in N: # 입력받은 숫자는 아직 str문자형\\n a.append(int(n)) # int로 형변환 하여 담기\\n\\na_sorted = [] # a에 담긴 숫자들을 정렬하여 담을 리스트\\na_count = [0] * (max(a)+1) # N을 쪼개어 담은 a라는 리스트에 각 숫자들이 몇개씩 들어있는지 셀 것\\n# max(a)은, N의 각 자리수중 가장 큰 수를 의미하며\\n# +1은 각 숫자들의 개수를 세어 담을 때 리스트 맨 앞에 0을 의미함 -> 숫자와 인덱스가 일치함\\n\\nfor i in range(len(a)):\\n a_count[a[i]] += 1 # 숫자와 인덱스가 일치, 해당 숫자의 개수를 세어줌\\n\\nfor i in range(len(a_count)-1, -1, -1): # 담겨있는 숫자의 개수들을 반복하면서\\n # 문제에서는 역정렬을 요구하였음\\n if a_count[i]: # 숫자의 개수가 하나라도 있으면\\n for j in range(a_count[i]): # 카운트 한 개수만큼의 횟수를 반복하며\\n print(i, end='') # 공백없이 출력하면 문제에서 요구하는 정답이 됨\\n\"\n },\n {\n \"alpha_fraction\": 0.5655737519264221,\n \"alphanum_fraction\": 0.5860655903816223,\n \"avg_line_length\": 19.41666603088379,\n \"blob_id\": \"d194b07ecd3007f63704b90354fe5b4817ba40f5\",\n \"content_id\": \"03d6f2af0853cf00cd3ba61c3dc8363f965deb34\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 244,\n \"license_type\": \"no_license\",\n \"max_line_length\": 45,\n \"num_lines\": 12,\n \"path\": \"/알고리즘/온라인저지/2022/09/0924/크림 파스타.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\n\\nN = int(input().rstrip())\\ndp = list(map(int, input().rstrip().split()))\\nmin_num = dp[0]\\ndp[0] = 0\\nfor i in range(1, N):\\n min_num = min(min_num, dp[i])\\n dp[i] = max(dp[i]-min_num, dp[i-1])\\nprint(*dp)\"\n },\n {\n \"alpha_fraction\": 0.6578947305679321,\n \"alphanum_fraction\": 0.6578947305679321,\n \"avg_line_length\": 18.16666603088379,\n \"blob_id\": \"237a21e1d5137e1928d5aebcffd15e20ec2c727b\",\n \"content_id\": \"ee50502bb8e14c386819acdf91c10bf7e1b2bbff\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 114,\n \"license_type\": \"no_license\",\n \"max_line_length\": 38,\n \"num_lines\": 6,\n \"path\": \"/알고리즘/온라인저지/2022/10/1015/입실 관리.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\n\\nfor _ in range(int(input().rstrip())):\\n print(input().rstrip().lower())\"\n },\n {\n \"alpha_fraction\": 0.3955555558204651,\n \"alphanum_fraction\": 0.4399999976158142,\n \"avg_line_length\": 21.600000381469727,\n \"blob_id\": \"ae3fb0f11489d52fad9a3d383b41f3c6471bb70d\",\n \"content_id\": \"2324375107a3179f164e90bbbccfc131d23b76be\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 225,\n \"license_type\": \"no_license\",\n \"max_line_length\": 31,\n \"num_lines\": 10,\n \"path\": \"/알고리즘/온라인저지/2022/09/0901/2진수 8진수.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = input()\\ntmp = 3-len(N)%3\\nif tmp != 3: N = '0'*tmp + N\\nfor i in range(0, len(N), 3):\\n S = N[i:i+3] # section\\n S = S[::-1]\\n tmp = 0\\n for j in range(len(S)):\\n tmp += int(S[j])*(2**j)\\n print(tmp, end='')\"\n },\n {\n \"alpha_fraction\": 0.5894736647605896,\n \"alphanum_fraction\": 0.6105263233184814,\n \"avg_line_length\": 18.100000381469727,\n \"blob_id\": \"e85dd190d21a23b6516846f82c645c23c58accbd\",\n \"content_id\": \"c27ca6140ba0893cae4a8d7e3d10dbd4b27593af\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 190,\n \"license_type\": \"no_license\",\n \"max_line_length\": 41,\n \"num_lines\": 10,\n \"path\": \"/알고리즘/온라인저지/2022/10/1030/거꾸로 구구단.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\n\\nN, K = map(int, input().rstrip().split())\\nresult = 0\\nfor k in range(1, K+1):\\n tmp = int(str(N*k)[::-1])\\n result = max(result, tmp)\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.4361445903778076,\n \"alphanum_fraction\": 0.4746987819671631,\n \"avg_line_length\": 26.66666603088379,\n \"blob_id\": \"2e593644f9e296affd7d6f9b5cb6ba36cd372e70\",\n \"content_id\": \"88eb88d1795c2abf46d5640a9c58f0d17b422ff9\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 597,\n \"license_type\": \"no_license\",\n \"max_line_length\": 63,\n \"num_lines\": 15,\n \"path\": \"/알고리즘/온라인저지/2021/08/0807/직각삼각형.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"\\\"\\\"\\\"\\n입력받는 변 3개 A, B, C\\n0 0 0 입력받으면 실행 종료\\n피타고라스 정리 <if a**2 + b**2 == c**2: 직각삼각형>\\n\\\"\\\"\\\"\\n\\nwhile True: # 계속 반복하는 while True\\n A, B, C = map(int, input().split()) # 각 변을 입력받고\\n if A + B + C == 0: # 마지막 줄인 0 0 0 이면\\n break # 종료\\n if A**2 + B**2 + C**2 == ((max(A, B, C))**2) * 2: # 직각삼각형이면\\n # 가장 큰 수만 찾아서 구하는 공식을 위와같이 구성하였음\\n print('right') # 출력\\n else: # 직각삼각형 아니면 \\n print('wrong') # 출력\\n\"\n },\n {\n \"alpha_fraction\": 0.38725489377975464,\n \"alphanum_fraction\": 0.41911765933036804,\n \"avg_line_length\": 17.590909957885742,\n \"blob_id\": \"2ac4bce7eab5f5974fe7d05030b5bece16877703\",\n \"content_id\": \"26453d6a6ea5a31d3244c696065c89deb8dfffff\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 408,\n \"license_type\": \"no_license\",\n \"max_line_length\": 52,\n \"num_lines\": 22,\n \"path\": \"/알고리즘/온라인저지/2022/02/0201/GCD 곱.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"mod = 1000000007\\n\\nN, M = map(int, input().split())\\n\\nmaxn = max(N, M)\\n\\ndp = [False, False] + [True] * maxn\\n\\nresult = 1\\n\\nfor i in range(2, maxn):\\n if dp[i]:\\n j = i\\n while j <= maxn:\\n cnt = 0\\n for k in range(i, maxn, i):\\n dp[k] = False\\n cnt += (N//j) * (M//j)\\n result = (result * ((i**cnt)%mod)) % mod\\n j *= i\\n\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.4910941421985626,\n \"alphanum_fraction\": 0.49618321657180786,\n \"avg_line_length\": 25.266666412353516,\n \"blob_id\": \"ca62971baa6beb144b93dbd2dd644cc2495aa3d2\",\n \"content_id\": \"3487a1cc24854cace4cafe41f9959ecef86f1563\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 407,\n \"license_type\": \"no_license\",\n \"max_line_length\": 55,\n \"num_lines\": 15,\n \"path\": \"/알고리즘/온라인저지/2022/06/0616/유니크.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = int(input())\\nplayer = []\\nfor n in range(N):\\n player.append(list(map(int, input().split())))\\nresult = [0] * N\\nfor i in range(N): # 플레이어\\n for j in range(3): # 점수들\\n switch = True\\n for k in range(N):\\n if player[i][j] == player[k][j] and i != k:\\n switch = False\\n if switch:\\n result[i] += player[i][j]\\nfor r in result:\\n print(r)\"\n },\n {\n \"alpha_fraction\": 0.3924914598464966,\n \"alphanum_fraction\": 0.4778156876564026,\n \"avg_line_length\": 12.363636016845703,\n \"blob_id\": \"c2de15d44eb840b9dc1e11f8f6cad62397785eab\",\n \"content_id\": \"acc6b02a53248985f49a1535e8108ba04f53b78a\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 339,\n \"license_type\": \"no_license\",\n \"max_line_length\": 35,\n \"num_lines\": 22,\n \"path\": \"/알고리즘/SWEA/LEARN/Course/1. Programming Beginner/파이썬 프로그래밍 기초(2)/34차시 3. 자료구조 – 셋, 딕셔너리 - 연습문제 9.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"beer = {\\n '하이트': 2000, \\n '카스': 2100, \\n '칭따오': 2500, \\n '하이네켄': 4000, \\n '버드와이저': 500,\\n}\\n\\n# print(beer, ' # 인상 전')\\n\\n# for b in beer:\\n# beer.update({b:beer[b]*1.05})\\n\\n# print(beer, ' # 인상 후')\\n\\n\\nprint(beer)\\n\\nfor b in beer:\\n beer.update({b:beer[b]*1.05})\\n\\nprint(beer)\"\n },\n {\n \"alpha_fraction\": 0.4861878454685211,\n \"alphanum_fraction\": 0.4917127192020416,\n \"avg_line_length\": 13,\n \"blob_id\": \"458cbdac97a6ad5f39f4b38aebb6914c0cc09a2f\",\n \"content_id\": \"7490b58fcc96d2460ff20489f4eec117df444889\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 181,\n \"license_type\": \"no_license\",\n \"max_line_length\": 24,\n \"num_lines\": 13,\n \"path\": \"/알고리즘/SWEA/LEARN/Course/1. Programming Beginner/파이썬 프로그래밍 기초(2)/41차시 4. 문자열 - 연습문제 5.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"tmp = input().split()\\n\\nresult = list(set(tmp))\\n\\nresult.sort()\\n\\nfor r in result:\\n if r == result[-1]:\\n print(r, end='')\\n print()\\n break\\n\\n print(r, end=',')\"\n },\n {\n \"alpha_fraction\": 0.30078125,\n \"alphanum_fraction\": 0.36328125,\n \"avg_line_length\": 15.0625,\n \"blob_id\": \"7a89e92357f8f48d383e5ede10e609a92300f04f\",\n \"content_id\": \"4ded52f8a97d41af12fe614e3d8e95d30a31cfa9\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 256,\n \"license_type\": \"no_license\",\n \"max_line_length\": 54,\n \"num_lines\": 16,\n \"path\": \"/알고리즘/온라인저지/2022/02/0228/타임 카드.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"for _ in range(3):\\n AH, AM, AS, BH, BM, BS = map(int, input().split())\\n\\n BH -= 1 + AH\\n BM += 59 - AM\\n BS += 60 - AS\\n \\n if BS >= 60:\\n BM += 1\\n BS -= 60\\n\\n if BM >= 60:\\n BH += 1\\n BM -= 60\\n\\n print(BH, BM, BS)\"\n },\n {\n \"alpha_fraction\": 0.5,\n \"alphanum_fraction\": 0.5357142686843872,\n \"avg_line_length\": 9.600000381469727,\n \"blob_id\": \"2d6fbc8d986da801f6f61e2d98c253fa1437d5aa\",\n \"content_id\": \"aa5ae0fa3c33c619639c67881ef60d75f6cdba7d\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 56,\n \"license_type\": \"no_license\",\n \"max_line_length\": 19,\n \"num_lines\": 5,\n \"path\": \"/알고리즘/온라인저지/2022/01/0116/오리.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"sen = list(input())\\n\\nresult = 0\\n\\nquack = [False] * 5\\n\\n\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.4591194987297058,\n \"alphanum_fraction\": 0.4800838530063629,\n \"avg_line_length\": 21.761905670166016,\n \"blob_id\": \"c5200dab7515077680b19a97db77c2bd2ef635d3\",\n \"content_id\": \"297960e17c5f05408c0bc1ef8b9910b943ef2694\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 747,\n \"license_type\": \"no_license\",\n \"max_line_length\": 46,\n \"num_lines\": 21,\n \"path\": \"/알고리즘/온라인저지/2021/08/0807/ACM 호텔.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"\\\"\\\"\\\"\\nH = 호텔 높이\\nW = 호텔 길이\\n그림은 정면에서 봤을 때 호텔 모습\\nYYXX = Y층 X호\\n들어오는 순서대로 각 층 1호실부터 방 배정\\nT = 테스트케이스 개수\\nN = 입장 순서\\nYY = N % H\\nXX = N // H + 1\\\"\\\"\\\"\\n\\nT = int(input()) # 테스트케이스 개수\\nfor i in range(T): # 테스트케이스 개수만큼 반복\\n H, W, N = map(int, input().split()) # 입력받고\\n if N % H == 0: # 손님들을 차례로 방 배정할 때 나머지가 0이면\\n Y = H # 호실의 층수는 높이\\n X = N // H # 호수는 몫\\n else: # 나머지가 0이 아니면\\n Y = N % H # 층수는 나누고 난 나머지\\n X = (N // H) + 1 # 호수는 몫에 +1\\n print(100 * Y + X) # 방 번호 출력\"\n },\n {\n \"alpha_fraction\": 0.26037734746932983,\n \"alphanum_fraction\": 0.5169811248779297,\n \"avg_line_length\": 6,\n \"blob_id\": \"f9b9db6f4489b7bc50661bd064c8690231e1a656\",\n \"content_id\": \"f1888e4047f443052cf4d5e26c2e822c72492f4c\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 265,\n \"license_type\": \"no_license\",\n \"max_line_length\": 29,\n \"num_lines\": 38,\n \"path\": \"/알고리즘/온라인저지/2022/01/0108/이친수.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"\\\"\\\"\\\"\\n1 1\\n1\\n\\n2 1\\n10\\n\\n3 2\\n100\\n101\\n\\n4 3\\n1000\\n1001\\n1010\\n\\n5 5\\n10000\\n10001\\n10010\\n10100\\n10101\\n\\\"\\\"\\\"\\n\\nN = int(input())\\n\\ndp = [0 for _ in range(91)]\\n\\ndp[1], dp[2] = 1, 1\\n\\nif N < 3:\\n print(dp[N])\\n exit()\\n\\nfor i in range(3, N+1):\\n dp[i] = dp[i-1] + dp[i-2]\\n\\nprint(dp[N])\"\n },\n {\n \"alpha_fraction\": 0.5094066858291626,\n \"alphanum_fraction\": 0.5267727971076965,\n \"avg_line_length\": 21.322580337524414,\n \"blob_id\": \"11ca0eb7103cde73d0cf3732c668a4889ddf9b59\",\n \"content_id\": \"9109d65d6b49c7339689aa25e539d3eac85433bb\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 903,\n \"license_type\": \"no_license\",\n \"max_line_length\": 67,\n \"num_lines\": 31,\n \"path\": \"/알고리즘/온라인저지/2021/10/1016/N과 M (1).py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# 외부모됼\\n# from itertools import permutations\\n# N, M = map(int, input().split())\\n# arr = list(range(1, N+1))\\n# print(list(permutations(arr, M)))\\n\\n# dfs 재귀로 구현\\ndef dfs(x): # x는 숫자 고른 개수\\n if x == M: # M개만큼 골랐으면\\n print(*result) # 들어있는 순열 언패킹\\n return # 해당 재귀 종료\\n \\n for i in range(N): # 재귀를 통해, N개중 하나 -> N-1개중 하나 -> N-2개중 하나 ...\\n if visited[i]: # 이미 고른 수이면\\n continue\\n\\n result.append(arr[i]) # 하나 고르고\\n visited[i] = 1 # 방문처리 하고\\n dfs(x+1) # 다음 숫자 고르기\\n result.pop() # 돌아와서 골랐던 숫자 빼고\\n visited[i] = 0 # 방문 취소하고\\n\\nN, M = map(int, input().split())\\n\\narr = list(range(1, N+1))\\n\\nvisited = [0] * N\\n\\nresult = []\\n\\ndfs(0) # 고른 숫자 0개부터 시작\"\n },\n {\n \"alpha_fraction\": 0.5365853905677795,\n \"alphanum_fraction\": 0.5365853905677795,\n \"avg_line_length\": 12.833333015441895,\n \"blob_id\": \"8ea0e51cd9745090ac21149d1646cca14c08e807\",\n \"content_id\": \"5f305afd10484b2fed5e51706e453f5549abade3\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 88,\n \"license_type\": \"no_license\",\n \"max_line_length\": 32,\n \"num_lines\": 6,\n \"path\": \"/알고리즘/온라인저지/2022/02/0205/와이버스 부릉부릉.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N, K = map(int, input().split())\\n\\nfor n in range(N):\\n a = input()\\n\\nprint('비와이')\"\n },\n {\n \"alpha_fraction\": 0.5511363744735718,\n \"alphanum_fraction\": 0.5625,\n \"avg_line_length\": 26.842105865478516,\n \"blob_id\": \"75dd18fbe39a44723b70ec0b4217c24414a508c0\",\n \"content_id\": \"ab8ebcf02b2bb3b9a72a4d9b257c6a0cf1cf0f49\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 590,\n \"license_type\": \"no_license\",\n \"max_line_length\": 98,\n \"num_lines\": 19,\n \"path\": \"/알고리즘/온라인저지/2023/01/0124/회문인 수.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import string\\n\\ndef base_change(number, base):\\n tmp = string.digits + string.ascii_uppercase + string.ascii_lowercase + '!@#$%^' # 자릿수를 담은 문자열\\n result = ''\\n while number:\\n result = tmp[number%base] + result # B진법이므로 B로 나눈 나머지번째 문자를 계속 추가한다\\n number //= base\\n return result\\n\\nfor _ in range(int(input())):\\n T = int(input())\\n result = 0\\n for base in range(2, 65):\\n new_num = base_change(T, base)\\n if new_num == new_num[::-1]:\\n result = 1\\n break\\n print(result)\"\n },\n {\n \"alpha_fraction\": 0.5670102834701538,\n \"alphanum_fraction\": 0.6020618677139282,\n \"avg_line_length\": 24.578947067260742,\n \"blob_id\": \"814e772dfd4e80fc123fa3a945c7ff0d4203d233\",\n \"content_id\": \"0188397c69b30b192fb67a270a6297bd71d9998f\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 485,\n \"license_type\": \"no_license\",\n \"max_line_length\": 53,\n \"num_lines\": 19,\n \"path\": \"/알고리즘/온라인저지/2022/10/1007/유레카 이론.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\n\\ntriangle = [1]\\nfor i in range(2, 1000):\\n tmp = triangle[-1]+i\\n if tmp<=1000: triangle.append(tmp)\\n else: break\\nresult = set()\\nlen_tri = len(triangle)\\nfor i in range(len_tri):\\n for j in range(len_tri):\\n for k in range(len_tri):\\n tmp = triangle[i]+triangle[j]+triangle[k]\\n if tmp<=1000: result.add(tmp)\\nfor _ in range(int(input().rstrip())):\\n K = int(input().rstrip())\\n print(1 if K in result else 0)\"\n },\n {\n \"alpha_fraction\": 0.5032680034637451,\n \"alphanum_fraction\": 0.529411792755127,\n \"avg_line_length\": 17.058822631835938,\n \"blob_id\": \"aa005383fe7cb3256b5a9e520220845ee40df8f1\",\n \"content_id\": \"bcc9931577852a294d7d3f9230e9f2f9b51668c3\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 306,\n \"license_type\": \"no_license\",\n \"max_line_length\": 39,\n \"num_lines\": 17,\n \"path\": \"/알고리즘/온라인저지/2022/03/0310/베시와 데이지.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"B = tuple(map(int, input().split()))\\nD = tuple(map(int, input().split()))\\nJ = tuple(map(int, input().split()))\\n\\nd = abs(D[0]-J[0]) + abs(D[1]-J[1])\\nb = max(abs(B[0]-J[0]), abs(B[1]-J[1]))\\n\\nresult = ''\\n\\nif d < b:\\n result = 'daisy'\\nelif b < d:\\n result = 'bessie'\\nelse:\\n result = 'tie'\\n\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.4935064911842346,\n \"alphanum_fraction\": 0.5324675440788269,\n \"avg_line_length\": 38,\n \"blob_id\": \"31a834b1d9bf930dab2cf1ef92f73ec7e5ef35ab\",\n \"content_id\": \"7ca41aefa9a586938f816f1a3b5ef69294f8aef1\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 77,\n \"license_type\": \"no_license\",\n \"max_line_length\": 58,\n \"num_lines\": 2,\n \"path\": \"/알고리즘/온라인저지/2022/08/0822/Equality.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"Q = input() # quiz\\nprint('YES' if int(Q[0])+int(Q[4]) == int(Q[8]) else 'NO')\"\n },\n {\n \"alpha_fraction\": 0.4591549336910248,\n \"alphanum_fraction\": 0.5042253732681274,\n \"avg_line_length\": 24.428571701049805,\n \"blob_id\": \"436baf1a9b9ec92217f541ae9b7f3fc74af6db63\",\n \"content_id\": \"a651318562020a1400757a931ba3400c15e1bd01\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 355,\n \"license_type\": \"no_license\",\n \"max_line_length\": 69,\n \"num_lines\": 14,\n \"path\": \"/알고리즘/온라인저지/2022/10/1017/소수 단어.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"word = input()\\nnum = 0\\nfor w in word:\\n if w.isupper(): # upper\\n num += ord(w)-65+26+1\\n else: # lower\\n num += ord(w)-97+1\\nn = int(1e4)\\na = [False, True] + [True]*(n-1)\\nfor i in range(2, n+1):\\n if a[i]:\\n for j in range(2*i, n+1, i):\\n a[j] = False\\nprint('It is a prime word.' if a[num] else 'It is not a prime word.')\"\n },\n {\n \"alpha_fraction\": 0.6142857074737549,\n \"alphanum_fraction\": 0.6571428775787354,\n \"avg_line_length\": 16.75,\n \"blob_id\": \"099a02d05501c8f3025396ffd09719bb666b941f\",\n \"content_id\": \"db16edb0bbea6e1e1dfaee1edf38582cafb283b9\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 70,\n \"license_type\": \"no_license\",\n \"max_line_length\": 37,\n \"num_lines\": 4,\n \"path\": \"/알고리즘/온라인저지/2022/12/1226/너의 이름은 몇 점이니.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"input()\\nresult = 0\\nfor i in input(): result += ord(i)-64\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.47680413722991943,\n \"alphanum_fraction\": 0.5051546096801758,\n \"avg_line_length\": 28.923076629638672,\n \"blob_id\": \"60010eb3bdd8af01bd5b6eddac6fb3c5d5fdfc52\",\n \"content_id\": \"24a0d7a3a9ef67e3441a626fd58d937f69a140d8\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 388,\n \"license_type\": \"no_license\",\n \"max_line_length\": 42,\n \"num_lines\": 13,\n \"path\": \"/알고리즘/온라인저지/2022/10/1012/가위 바위 보.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"player_1_win = ['P R', 'R S', 'S P']\\nplayer_2_win = ['R P', 'S R', 'P S']\\nfor t in range(int(input())):\\n RSP = 0\\n result = ''\\n for n in range(int(input())):\\n tmp = input()\\n if tmp in player_1_win: RSP += 1\\n elif tmp in player_2_win: RSP -= 1\\n if RSP > 0: result = 'Player 1'\\n elif RSP < 0: result = 'Player 2'\\n else: result = 'TIE'\\n print(result)\"\n },\n {\n \"alpha_fraction\": 0.5976095795631409,\n \"alphanum_fraction\": 0.6215139627456665,\n \"avg_line_length\": 20,\n \"blob_id\": \"f0cb06faad63eee39a5850e3454f8954aa2898f2\",\n \"content_id\": \"87e37cb007829ba62932568ddce7fd57030cbb3e\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 251,\n \"license_type\": \"no_license\",\n \"max_line_length\": 54,\n \"num_lines\": 12,\n \"path\": \"/알고리즘/온라인저지/2022/10/1003/수리공 항승.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\n\\nN, L = map(int, input().rstrip().split())\\narr = sorted(list(map(int, input().rstrip().split())))\\nresult = 0\\nwhile arr:\\n tmp = arr[0]+L-1\\n while arr and arr[0]<=tmp: arr.pop(0)\\n result += 1\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.3227176368236542,\n \"alphanum_fraction\": 0.40976646542549133,\n \"avg_line_length\": 21.4761905670166,\n \"blob_id\": \"e37272de4483ee87142df3d774a1b52786ce1f20\",\n \"content_id\": \"3f68a06eaea56d3944f1bbb152ee210a4fcb7e71\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 471,\n \"license_type\": \"no_license\",\n \"max_line_length\": 37,\n \"num_lines\": 21,\n \"path\": \"/알고리즘/온라인저지/2023/03/0318/받아올림.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"while True:\\n A, B = input().split()\\n if A == '0' and B == '0': break\\n A = '00000000000000'+A\\n B = '00000000000000'+B\\n arr = []\\n A = list(A)[::-1]\\n B = list(B)[::-1]\\n for i in range(10):\\n a, b = map(int, (A[i], B[i]))\\n C = a+b\\n if C:\\n arr.append(C)\\n arr.append(0)\\n result = 0\\n for i in range(len(arr)):\\n a = arr[i]\\n if a>=10:\\n result += 1\\n arr[i+1] += 1\\n print(result)\"\n },\n {\n \"alpha_fraction\": 0.41603052616119385,\n \"alphanum_fraction\": 0.4312977194786072,\n \"avg_line_length\": 12.8421049118042,\n \"blob_id\": \"aa4ef13da2107a93024e8d35cdb95cc00296fc60\",\n \"content_id\": \"865b24e0d546f2dcf3225b2e1633974aef63733f\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 262,\n \"license_type\": \"no_license\",\n \"max_line_length\": 35,\n \"num_lines\": 19,\n \"path\": \"/알고리즘/온라인저지/2022/01/0131/시험 감독.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = int(input())\\n\\nresult = 0\\n\\nA = list(map(int, input().split()))\\n\\nB, C = map(int, input().split())\\n\\nfor a in A:\\n a -= B\\n result += 1\\n\\n if a > 0:\\n result += a//C\\n tmp = C * (a//C)\\n if a != tmp:\\n result += 1\\n\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.4332129955291748,\n \"alphanum_fraction\": 0.5577617287635803,\n \"avg_line_length\": 19.55555534362793,\n \"blob_id\": \"b54183e331a3cfdebb865971c8f7ed3655d2bed0\",\n \"content_id\": \"69bce0481659e57f376eb4e78bf3deea794234f5\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 896,\n \"license_type\": \"no_license\",\n \"max_line_length\": 52,\n \"num_lines\": 27,\n \"path\": \"/알고리즘/[템플릿]/[SAMPLE]/비트연산 부분집합.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"arr = [3, 6, 8]\\nn = len(arr)\\n\\nfor i in range(1<<n):\\n for j in range(n):\\n if i&(1<<j):\\n print(arr[j], end=' ')\\n print()\\n \\n\\\"\\\"\\\"\\n0 0 0 : 0\\n0 0 1 : 3\\n0 1 0 : 6\\n0 1 1 : 3 6\\n1 0 0 : 8\\n1 0 1 : 3 8\\n1 1 0 : 6 8\\n1 1 1 : 3 6 8\\n각각의 숫자는, 각각의 원소들이 있고, 없고를 의미함\\ni는 십진수이지만 연산상에서는 2진수로 작용하고\\n1<<j는 range에서 0 1 2 ... 일 때, 1 10 100 1000... 으로 증가함\\ni&(1<<j)라는건 결국 이진수로 표현된 i가 해당 자리수가 1인지\\n즉, 리스트에서 그 원소를 포함하는 부분집합인지를 의미함\\nj는 원소 자체를 의미하는게 아니라 원소의 위치, 순서를 의미하고\\n3번째 원소(인덱스 상으로 2번째)인 8을 확인하는건 1<<3, 즉 100(이진수)\\n이는 돌고있는 i가 1 X X면 8을 포함하는 부분집합이라는 것을 알 수 있다\\n\\\"\\\"\\\"\"\n },\n {\n \"alpha_fraction\": 0.5684455037117004,\n \"alphanum_fraction\": 0.5870069861412048,\n \"avg_line_length\": 24.41176414489746,\n \"blob_id\": \"de41654ecfce008da98074dbf597bd3a86d20ed3\",\n \"content_id\": \"478a429ad8173502949c471a1c25761448ece7fb\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 607,\n \"license_type\": \"no_license\",\n \"max_line_length\": 68,\n \"num_lines\": 17,\n \"path\": \"/알고리즘/온라인저지/2021/10/1016/회의실 배정.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = int(input())\\n\\narr = []\\n\\nfor n in range(N):\\n arr.append(tuple(map(int, input().split()))) # 속도 향상을 위한 tuple()\\n\\narr.sort() # arr[x][0]을 기준으로 정렬\\narr.sort(key=lambda x: x[1]) # 다시 한번 x[1]을 기준으로 정렬\\n\\nresult = [arr[0]] # 첫번째 회의\\n\\nfor i in range(1, len(arr)): # 두번째 회의부터 회의실 사용 가능한지 확인\\n if result[-1][1] <= arr[i][0]: # 이전 회의의 종료시간보다 다음 회의의 시작시간이 늦으면\\n result.append(arr[i]) # 회의실 사용가능\\n \\nprint(len(result)) # 회의실 사용팀 수 출력\"\n },\n {\n \"alpha_fraction\": 0.5836910009384155,\n \"alphanum_fraction\": 0.5836910009384155,\n \"avg_line_length\": 20.272727966308594,\n \"blob_id\": \"a1fc9f43a73ede6d07661c29781e76dea9da6d1f\",\n \"content_id\": \"da72491349c5377040c2ae28a04b56a074bb9471\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 233,\n \"license_type\": \"no_license\",\n \"max_line_length\": 33,\n \"num_lines\": 11,\n \"path\": \"/알고리즘/온라인저지/2022/07/0729/듣보잡.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N, M = map(int, input().split())\\nL = set() # listened\\nfor n in range(N): L.add(input())\\nresult = []\\nfor m in range(M):\\n s = input()\\n if s in L:\\n result.append(s)\\nresult.sort()\\nprint(len(result))\\nfor r in result: print(r)\"\n },\n {\n \"alpha_fraction\": 0.5286624431610107,\n \"alphanum_fraction\": 0.5414012670516968,\n \"avg_line_length\": 30.600000381469727,\n \"blob_id\": \"6571a36dc3d87ff9d1ead769cb364ada30fae46d\",\n \"content_id\": \"a2efb9f05a12de3fbd40902fc460fc7dd48188e1\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 157,\n \"license_type\": \"no_license\",\n \"max_line_length\": 60,\n \"num_lines\": 5,\n \"path\": \"/알고리즘/온라인저지/2022/12/1219/주식 투자.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"for _ in range(int(input())):\\n result = 0\\n for n in range(int(input())):\\n result += max(list(map(int, input().split())) + [0])\\n print(result)\"\n },\n {\n \"alpha_fraction\": 0.46686747670173645,\n \"alphanum_fraction\": 0.4909638464450836,\n \"avg_line_length\": 19.8125,\n \"blob_id\": \"fed60ae259d0a0e3cff519d3c42a19c1705e116c\",\n \"content_id\": \"c7a8c12cdce9597a69b4492ae133f20c7910dfb3\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 332,\n \"license_type\": \"no_license\",\n \"max_line_length\": 47,\n \"num_lines\": 16,\n \"path\": \"/알고리즘/온라인저지/2022/08/0807/꿀벌.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\n\\nT = ['Re', 'Pt', 'Cc', 'Ea', 'Tb', 'Cm', 'Ex']\\nB = {t:0 for t in T}\\ncnt = 0\\nwhile True:\\n I = input().rstrip().split()\\n if not I: break\\n for i in I:\\n cnt += 1\\n try: B[i] += 1\\n except: pass\\nfor t in T: print(f'{t} {B[t]} {B[t]/cnt:.2f}')\\nprint(f'Total {cnt} 1.00')\"\n },\n {\n \"alpha_fraction\": 0.46268656849861145,\n \"alphanum_fraction\": 0.49253731966018677,\n \"avg_line_length\": 18.285715103149414,\n \"blob_id\": \"9cb3f799ef7336e04f77f239324c46215ce8ab0a\",\n \"content_id\": \"5877e1f38deb1c4c2da7c625fc8346ad2c4bb8c0\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 134,\n \"license_type\": \"no_license\",\n \"max_line_length\": 27,\n \"num_lines\": 7,\n \"path\": \"/알고리즘/온라인저지/2023/03/0313/Pyramids.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"while True:\\n N = int(input())\\n if N == 0: break\\n result = 0\\n for i in range(1, N+1):\\n result += i\\n print(result)\"\n },\n {\n \"alpha_fraction\": 0.36206895112991333,\n \"alphanum_fraction\": 0.4367816150188446,\n \"avg_line_length\": 12.384614944458008,\n \"blob_id\": \"aa498041dbb0c132d5a3fa0edcfea6c707359a2d\",\n \"content_id\": \"8d262ca2dd8a4e52e6ddafab4a2a2a007f579f9e\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 174,\n \"license_type\": \"no_license\",\n \"max_line_length\": 27,\n \"num_lines\": 13,\n \"path\": \"/알고리즘/SWEA/LEARN/Course/1. Programming Beginner/파이썬 프로그래밍 기초(2)/33차시 3. 자료구조 – 셋, 딕셔너리 - 연습문제 8.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"sen = input()\\n\\nu = 0\\nl = 0\\n\\nfor s in sen:\\n if 65 <= ord(s) <= 90:\\n u += 1\\n if 97 <= ord(s) <= 122:\\n l += 1\\n\\nprint('UPPER CASE', u)\\nprint('LOWER CASE', l)\\n\"\n },\n {\n \"alpha_fraction\": 0.5600000023841858,\n \"alphanum_fraction\": 0.568648636341095,\n \"avg_line_length\": 23.36842155456543,\n \"blob_id\": \"f01ed89b93d4b0d78574e6899e1e4f21d68041d7\",\n \"content_id\": \"62b8aaf986f8bc0ff02bbc329bafd63dbbfd5b1a\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1213,\n \"license_type\": \"no_license\",\n \"max_line_length\": 47,\n \"num_lines\": 38,\n \"path\": \"/알고리즘/[템플릿]/정렬/퀵정렬.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"\\\"\\\"\\\"\\n첫 피봇은 arr[0]\\narr의 앞에서 시작하는 left, 뒤에서 시작하는 right\\n피봇을 기준으로 이 두 값이 각각 작고 큰 값을 찾다가\\n찾으면 두 값을 서로 바꿔주고\\n못찾고 left와 right가 교차해버리면\\nright와 피봇값을 바꿔주어, 정렬중인 배열의 left와 right 중간에\\n그러니까, 피봇이 있어야 할 자리에 피봇을 넣어준다\\npartition 함수를 통해 피봇값을 얻고\\nquick_sort 함수를 통해 계속해서 분할하여 정복하는 식으로 배열을 정렬해나간다\\n\\\"\\\"\\\"\\n\\ndef partition(arr, left, right):\\n pivot = arr[left]\\n i = left + 1\\n j = right\\n\\n while i <= j:\\n while i <= j and arr[i] <= pivot:\\n i += 1\\n while i <= j and arr[j] >= pivot:\\n j -= 1\\n\\n if i <= j:\\n arr[i], arr[j] = arr[j], arr[i]\\n arr[left], arr[j] = arr[j], arr[left]\\n return j\\n\\ndef quick_sort(arr, left, right):\\n if left < right:\\n center = partition(arr, left, right)\\n quick_sort(arr, left, center-1)\\n quick_sort(arr, center+1, right)\\n\\nfor t in range(int(input())):\\n arr = list(map(int, input().split()))\\n quick_sort(arr, 0, len(arr)-1)\\n print(*arr)\"\n },\n {\n \"alpha_fraction\": 0.42506811022758484,\n \"alphanum_fraction\": 0.4386920928955078,\n \"avg_line_length\": 20.647058486938477,\n \"blob_id\": \"e8f8953833c7f4342343f6f45896b80e75a535a3\",\n \"content_id\": \"1ccc19dfff3751d3059560aafd02dda1d03cc661\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 367,\n \"license_type\": \"no_license\",\n \"max_line_length\": 38,\n \"num_lines\": 17,\n \"path\": \"/알고리즘/온라인저지/2022/02/0220/방 배정하기.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"A, B, C, N = map(int, input().split())\\n\\nfound_ans = False\\n\\nfor a in range(N//A + 1):\\n if found_ans:\\n break\\n for b in range(N//B + 1):\\n if found_ans:\\n break\\n for c in range(N//C + 1):\\n tmp = N-(a*A + b*B + c*C)\\n if not tmp:\\n found_ans = True\\n break\\n\\nprint(1 if found_ans else 0)\"\n },\n {\n \"alpha_fraction\": 0.49462366104125977,\n \"alphanum_fraction\": 0.5161290168762207,\n \"avg_line_length\": 14.666666984558105,\n \"blob_id\": \"7589e79fe8586a60479f7d2d86f2aa3faf329c0d\",\n \"content_id\": \"6d15475a2227f91236745081681271bd6866a5c8\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 93,\n \"license_type\": \"no_license\",\n \"max_line_length\": 36,\n \"num_lines\": 6,\n \"path\": \"/알고리즘/온라인저지/2022/02/0220/문자열.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"T = int(input())\\n\\nfor t in range(T):\\n text = input()\\n\\n print(text[0], text[-1], sep='')\"\n },\n {\n \"alpha_fraction\": 0.3807106614112854,\n \"alphanum_fraction\": 0.4568527936935425,\n \"avg_line_length\": 18.799999237060547,\n \"blob_id\": \"5cf765420a2089ae3db51cc7b155764851ec5842\",\n \"content_id\": \"65a37239321e96f0ee39e9c6927c9a2636107ce0\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 197,\n \"license_type\": \"no_license\",\n \"max_line_length\": 38,\n \"num_lines\": 10,\n \"path\": \"/알고리즘/온라인저지/2022/06/0611/적어도 대부분의 배수.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"nums = list(map(int, input().split()))\\nmaxx = 10000000000\\nfor i in range(1, maxx):\\n a = 0\\n for n in nums:\\n if not i%n:\\n a += 1\\n if a >= 3:\\n print(i)\\n exit()\"\n },\n {\n \"alpha_fraction\": 0.29611650109291077,\n \"alphanum_fraction\": 0.46116504073143005,\n \"avg_line_length\": 16.95652198791504,\n \"blob_id\": \"a8a210f337347b4f5ec49da930f4370731b1795d\",\n \"content_id\": \"cac4bea1247b5d3a7cdc550c60fb7859782f4817\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 412,\n \"license_type\": \"no_license\",\n \"max_line_length\": 35,\n \"num_lines\": 23,\n \"path\": \"/알고리즘/온라인저지/2022/02/0203/저항.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"r = {\\n 'black': ('0', 1),\\n 'brown': ('1', 10),\\n 'red': ('2', 100),\\n 'orange': ('3', 1000),\\n 'yellow': ('4', 10000),\\n 'green': ('5', 100000),\\n 'blue': ('6', 1000000),\\n 'violet': ('7', 10000000),\\n 'grey': ('8', 100000000),\\n 'white': ('9', 1000000000),\\n}\\n\\nresult = ''\\n\\nfor _ in range(2):\\n result = result + r[input()][0]\\n\\nresult = int(result)\\n\\nresult *= r[input()][1]\\n\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.42105263471603394,\n \"alphanum_fraction\": 0.4417862892150879,\n \"avg_line_length\": 23.153846740722656,\n \"blob_id\": \"0ec4ae41156f014d01d047f5794e2ddc62e8c1e7\",\n \"content_id\": \"00306e1cbf921fafc5d5009246bc079eab8e7a2f\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 627,\n \"license_type\": \"no_license\",\n \"max_line_length\": 49,\n \"num_lines\": 26,\n \"path\": \"/알고리즘/온라인저지/2022/09/0904/부분 문자열.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"def get_pi(pattern):\\n j = 0\\n for i in range(1, len(pattern)):\\n while j > 0 and pattern[i] != pattern[j]:\\n j = pi[j - 1]\\n if pattern[i] == pattern[j]:\\n j += 1\\n pi[i] = j\\n\\ndef KMP(string, pattern):\\n get_pi(pattern)\\n j = 0\\n for i in range(len(string)):\\n while j > 0 and string[i] != pattern[j]:\\n j = pi[j-1]\\n if string[i] == pattern[j]:\\n if j == len(pattern)-1:\\n return True\\n else:\\n j += 1\\n return False\\n\\nS, P = input(), input()\\npi = [0] * len(P)\\nif KMP(S, P): print('1')\\nelse: print('0')\"\n },\n {\n \"alpha_fraction\": 0.4172042906284332,\n \"alphanum_fraction\": 0.43225806951522827,\n \"avg_line_length\": 19.217391967773438,\n \"blob_id\": \"82ce95e3602fa122847521808a5f55034dd96eca\",\n \"content_id\": \"a38de496a80c399a6d27ac7bc9b262d0515f0f1c\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 465,\n \"license_type\": \"no_license\",\n \"max_line_length\": 40,\n \"num_lines\": 23,\n \"path\": \"/알고리즘/온라인저지/2022/02/0225/삼각형과 세 변.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"while True:\\n A, B, C = map(int, input().split())\\n if A+B+C == 0:\\n break\\n\\n result = 'Scalene'\\n\\n if A+B+C == max(A, B, C) * 2:\\n result = 'Invalid'\\n \\n nums = set([A, B, C])\\n\\n if len(nums) == 2:\\n temp = [A, B, C]\\n temp.sort()\\n if temp[2] - temp[0] >= temp[1]:\\n result = 'Invalid'\\n else:\\n result = 'Isosceles'\\n elif len(nums) == 1:\\n result = 'Equilateral'\\n\\n print(result)\\n\"\n },\n {\n \"alpha_fraction\": 0.4945652186870575,\n \"alphanum_fraction\": 0.5,\n \"avg_line_length\": 9.277777671813965,\n \"blob_id\": \"e0ad5d7f011785cd33f0daabb68e77bb5454756b\",\n \"content_id\": \"e275252de5a46cae786cb9211050acdb03add30a\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 184,\n \"license_type\": \"no_license\",\n \"max_line_length\": 20,\n \"num_lines\": 18,\n \"path\": \"/알고리즘/온라인저지/2022/02/0207/수도요금.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"A = int(input())\\nB = int(input())\\nC = int(input())\\nD = int(input())\\nP = int(input())\\n\\nresult = 0\\n\\nXP = A * P\\n\\nYP = B\\n\\nif P > C:\\n YP += (P-C) * D\\n\\nresult = min(XP, YP)\\n\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.6086956262588501,\n \"alphanum_fraction\": 0.695652186870575,\n \"avg_line_length\": 11,\n \"blob_id\": \"4b1ba1bcb7dcbad9b5b13406806d7558ea7867a1\",\n \"content_id\": \"dde44ec7ab3a33bb89892b9f89fb2c4fcfc46992\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 23,\n \"license_type\": \"no_license\",\n \"max_line_length\": 15,\n \"num_lines\": 2,\n \"path\": \"/알고리즘/온라인저지/2023/05/0506/소수가 아닌 수.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"input()\\nprint(int(1e9))\"\n },\n {\n \"alpha_fraction\": 0.5422885417938232,\n \"alphanum_fraction\": 0.572139322757721,\n \"avg_line_length\": 21.44444465637207,\n \"blob_id\": \"9d2cb6716f3411ee8e6be871208fa84f81772626\",\n \"content_id\": \"52aa7eab5c6b43578290d89e5f4cda7866ff3a75\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 201,\n \"license_type\": \"no_license\",\n \"max_line_length\": 39,\n \"num_lines\": 9,\n \"path\": \"/알고리즘/온라인저지/2023/02/0218/알바생 강호.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"result = 0\\nN = int(input())\\ntips = [int(input()) for _ in range(N)]\\ntips.sort(reverse=True)\\nfor i in range(1, N+1):\\n tip = tips[i-1]\\n tip = tip - (i-1)\\n if tip > 0: result += tip\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.46783626079559326,\n \"alphanum_fraction\": 0.5087719559669495,\n \"avg_line_length\": 13.333333015441895,\n \"blob_id\": \"c9830558f3082d842a11bbbfeca0c84dd0e60e2c\",\n \"content_id\": \"133a8ef2ba010a04d4000ac72132ed93198f21b0\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 171,\n \"license_type\": \"no_license\",\n \"max_line_length\": 31,\n \"num_lines\": 12,\n \"path\": \"/알고리즘/온라인저지/2021/08/0818/팩토리얼 DP.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"def fact(n):\\n table [0] = 1\\n for i in range(1, n+1):\\n table[i] = i*table[i-1]\\n\\n\\n return table[n]\\n\\nn = int(input())\\ntable = [0] * (n+1)\\nfact(n)\\nprint(table)\"\n },\n {\n \"alpha_fraction\": 0.369047611951828,\n \"alphanum_fraction\": 0.3928571343421936,\n \"avg_line_length\": 17.77777862548828,\n \"blob_id\": \"8542ce2a7eaaa4603a26dc2b1a2d1b587d497de4\",\n \"content_id\": \"b1b08cbbd0f92efa0e666e1849fef9510e9aafe9\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 168,\n \"license_type\": \"no_license\",\n \"max_line_length\": 25,\n \"num_lines\": 9,\n \"path\": \"/알고리즘/온라인저지/2022/12/1211/숫자 놀이.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"while True:\\n N = int(input())\\n if N == 0: break\\n while N >= 10:\\n tmp = 0\\n for n in str(N):\\n tmp += int(n)\\n N = tmp\\n print(N)\"\n },\n {\n \"alpha_fraction\": 0.4337349534034729,\n \"alphanum_fraction\": 0.4518072307109833,\n \"avg_line_length\": 21.200000762939453,\n \"blob_id\": \"ec25611fa3973661b012eb2a81b12babc4eec058\",\n \"content_id\": \"f3eed1e5829a57d697f32fa9390b14ddd599a4fb\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 332,\n \"license_type\": \"no_license\",\n \"max_line_length\": 39,\n \"num_lines\": 15,\n \"path\": \"/알고리즘/온라인저지/2022/07/0703/Pen Pineapple Apple Pen.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = int(input())\\nword = input()\\nresult = 0\\nidxs = []\\nfor i in range(N-3):\\n tmp = word[i:i+4]\\n if tmp == 'pPAp':\\n is_used = False\\n for j in range(i, i+4):\\n if j in idxs:\\n is_used = True\\n if not is_used:\\n result += 1\\n idxs += list(range(i, i+4))\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.43089431524276733,\n \"alphanum_fraction\": 0.577235758304596,\n \"avg_line_length\": 14.5,\n \"blob_id\": \"ddaf8fe5774594d1aa02eefc5ff2d8def1205d9e\",\n \"content_id\": \"3141a245ea92760f14de34b50cd81d3a070d06fd\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 123,\n \"license_type\": \"no_license\",\n \"max_line_length\": 36,\n \"num_lines\": 8,\n \"path\": \"/알고리즘/SWEA/LEARN/Course/1. Programming Beginner/파이썬 프로그래밍 기초(2)/21차시 2. 자료구조 – 리스트, 튜플 - 연습문제 23.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"arr = [12, 24, 35, 70, 88, 120, 155]\\n\\nresult = []\\n\\nfor i in range(1, len(arr), 2):\\n result.append(arr[i])\\n\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.3997906744480133,\n \"alphanum_fraction\": 0.42804813385009766,\n \"avg_line_length\": 28.8125,\n \"blob_id\": \"bc9912e2cffd75f68dcb3793040f03495d5dfce2\",\n \"content_id\": \"b90dcba4d539c1e31c3b3813d3fc1db7a69046e8\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1965,\n \"license_type\": \"no_license\",\n \"max_line_length\": 87,\n \"num_lines\": 64,\n \"path\": \"/알고리즘/SW역량테스트/2022.04.12 A형.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"def dfs(w, h, depth, tmp):\\n global visited, maxx\\n print(h, w, depth, tmp)\\n # print(visited)\\n if depth == 4:\\n # print('depth 4 here', w, h, depth, tmp)\\n if tmp > maxx:\\n maxx = tmp\\n print('THIS IS MAXX😊😉😊😊', maxx)\\n return\\n for i in range(6):\\n if (0 <= w+dx[i] < W) and (0 <= h+dy[i] < H) and not visited[h+dy[i]][w+dx[i]]:\\n visited[h+dy[i]][w+dx[i]] = 1\\n dfs(w+dx[i], h+dy[i], depth+1, tmp+arr[h+dy[i]][w+dx[i]])\\n visited[h+dy[i]][w+dx[i]] = 0\\n\\n# 12시 방향부터 시계방향으로 델타이동\\ndx = [0, 1, 1, 0, -1, -1]\\ndy = [-1, -1, 0, 1, 0, -1]\\nT = int(input())\\nfor t in range(1, T+1):\\n W, H = map(int, input().split())\\n arr = [list(map(int, input().split())) for _ in range(H)]\\n # print(arr)\\n maxx = 0\\n for h in range(H):\\n for w in range(W):\\n visited = [[0]*W for _ in range(H)]\\n visited[h][w] = 1\\n dfs(w, h, 1, arr[h][w])\\n print('------------------')\\n print(maxx ** 2)\\n\\n\\n# def dfs(i, depth, tmp):\\n# global visited, maxx\\n# print(i, depth, tmp)\\n# if depth == 4:\\n# # print('depth 4 here', w, h, depth, tmp)\\n# if tmp > maxx:\\n# maxx = tmp\\n# print('THIS IS MAXX😊😉😊😊', maxx)\\n# return\\n# for j in range(6):\\n# if (1 <= i+dx[j] < W*H+1) and not visited[i+dx[j]]:\\n# visited[i+dx[j]] = 1\\n# dfs(i+dx[j], depth+1, tmp+arr[i+dx[j]])\\n# visited[i+dx[j]] = 0\\n\\n# dx = [-5, -4, 1, 5, -1, -6]\\n# T = int(input())\\n# for t in range(1, T+1):\\n# W, H = map(int, input().split())\\n# arr = [0]\\n# for h in range(H):\\n# arr += list(map(int, input().split()))\\n# maxx = 0\\n# for i in range(1, W*H+1):\\n# visited = [0] * len(arr)\\n# visited[i] = 1\\n# dfs(i, 1, arr[i])\\n# print('------------------')\\n# print(maxx ** 2)\\n# print(arr[9]) \"\n },\n {\n \"alpha_fraction\": 0.5130434632301331,\n \"alphanum_fraction\": 0.530434787273407,\n \"avg_line_length\": 13.5,\n \"blob_id\": \"60468c1a785829c9871f68fedb7d353e2000f96d\",\n \"content_id\": \"d537011f60bfaeef70220c148a5e4451d5014b9e\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 115,\n \"license_type\": \"no_license\",\n \"max_line_length\": 35,\n \"num_lines\": 8,\n \"path\": \"/알고리즘/온라인저지/2021/12/1213/과자.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"a, b, c = map(int, input().split())\\n\\nresult = c - (a * b)\\n\\nif result < 0:\\n print(abs(result))\\nelse:\\n print(0)\"\n },\n {\n \"alpha_fraction\": 0.4268292784690857,\n \"alphanum_fraction\": 0.48373982310295105,\n \"avg_line_length\": 19.58333396911621,\n \"blob_id\": \"f0f7757e20e223a16eb06261ba79b3f014f0b45c\",\n \"content_id\": \"edc903b12a421f78ab76e136bb42586ef6e78837\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 246,\n \"license_type\": \"no_license\",\n \"max_line_length\": 36,\n \"num_lines\": 12,\n \"path\": \"/알고리즘/온라인저지/2022/05/0530/삼각 김밥.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"a, b = map(int, input().split())\\ncheap = b/a\\ne, f = a, b\\nN = int(input())\\nfor n in range(N):\\n c, d = map(int, input().split())\\n if d/c > cheap:\\n cheap = d/c\\n e, f = c, d\\n# print(e, f)\\nprint(f'{e*1000/f:.2f}')\\n# 37:532 = x:1000\"\n },\n {\n \"alpha_fraction\": 0.54076087474823,\n \"alphanum_fraction\": 0.5625,\n \"avg_line_length\": 20.705883026123047,\n \"blob_id\": \"85500c74c0eb0b48691208e94cc131b6e9cd46d9\",\n \"content_id\": \"3d5ebd8ea76c6abf1bd83ba2fa737f39b902d185\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 368,\n \"license_type\": \"no_license\",\n \"max_line_length\": 49,\n \"num_lines\": 17,\n \"path\": \"/알고리즘/온라인저지/2022/10/1012/동전 2.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\nINF = int(1e9)\\n\\nN, K = map(int, input().rstrip().split())\\ncoins = set()\\nfor i in range(N):\\n coins.add(int(input().rstrip()))\\ncoins = list(coins)\\ndp = [INF]*(K+1)\\ndp[0] = 0\\nfor i in range(K+1):\\n for coin in coins:\\n if i+coin <= K:\\n dp[i+coin] = min(dp[i]+1, dp[i+coin])\\nprint(dp[K] if dp[K] != INF else -1)\"\n },\n {\n \"alpha_fraction\": 0.4523809552192688,\n \"alphanum_fraction\": 0.5,\n \"avg_line_length\": 27.16666603088379,\n \"blob_id\": \"c0ea716f3da6c5e8ec063f292e0837e7f1a48d94\",\n \"content_id\": \"28952e7638e1785803668385e3e8decbcc73547b\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 168,\n \"license_type\": \"no_license\",\n \"max_line_length\": 47,\n \"num_lines\": 6,\n \"path\": \"/알고리즘/온라인저지/2022/08/0821/Winning Score.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"A, B = 0, 0\\nfor i in range(3, 0, -1): A += int(input()) * i\\nfor i in range(3, 0, -1): B += int(input()) * i\\nif A > B: print('A')\\nelif B > A: print('B')\\nelse: print('T')\"\n },\n {\n \"alpha_fraction\": 0.4456404745578766,\n \"alphanum_fraction\": 0.46824541687965393,\n \"avg_line_length\": 29,\n \"blob_id\": \"9b025bc0228d3634c729c1295ca26f6b515527f6\",\n \"content_id\": \"b2f67723ee223e95235030e3d67dad23470e9afa\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1451,\n \"license_type\": \"no_license\",\n \"max_line_length\": 72,\n \"num_lines\": 31,\n \"path\": \"/알고리즘/온라인저지/2021/08/0814/전자레인지.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"\\\"\\\"\\\"\\n버튼 A, B, C 각각 300초, 60초, 10초\\n버튼을 누른 총 횟수가 최소횟수 일 때\\n각 버튼을 누른 횟수를 버튼별로 출력\\nT만큼 정확히 전자레인지를 동작시킬 수 없으면 -1\\n\\\"\\\"\\\"\\n\\\"\\\"\\\"\\n해결법 탐색\\n초기 접근법 독스트링 작성\\n코드 작성\\n백준 제출\\n코드주석 작성\\n백준에는 주석은 달지말고\\n백준 통과하면 그 다음에 코드파일에만 주석 달자\\n\\\"\\\"\\\"\\n\\nT = int(input()) # 시간초 입력\\nbuttons = [300, 60, 10] # 버튼 A, B, C를 초로 환산\\ncounts = [0] * 3 # 버튼 누른 횟수 리스트 초기화\\nfor i in range(len(buttons)): # 버튼의 개수만큼 순회\\n if buttons[i] <= T: # 순회중인 버튼(A->B->C)으로 작동 시켜도 시간을 초과하지 않으면\\n while True: # 버튼 누르기를 반복\\n counts[i] += 1 # 버튼을 누르고\\n T -= buttons[i] # 버튼이 동작하는 시간만큼 빼주고\\n if buttons[i] > T: # 버튼시간이 더 크면\\n break # while문 종료\\nif T == 0: # 깔끔하게 T초만큼 동작했으면\\n for count in counts: # 버튼 카운트들 순회하면서\\n print(count, end=' ') # 카운트 출력\\nelse: # 버튼들로 T초를 완벽하게 동작시키지 못했으면\\n print(-1) # -1 출력\"\n },\n {\n \"alpha_fraction\": 0.35930734872817993,\n \"alphanum_fraction\": 0.43290042877197266,\n \"avg_line_length\": 24.77777862548828,\n \"blob_id\": \"4b45b62b32bdeeb19efb96b10e0d9379142626b6\",\n \"content_id\": \"51fc876d0e9f05470950e728b22dec226965264b\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 231,\n \"license_type\": \"no_license\",\n \"max_line_length\": 34,\n \"num_lines\": 9,\n \"path\": \"/알고리즘/온라인저지/2022/07/0731/파스칼의 삼각형.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N, K = map(int, input().split())\\nP = [[1], [1, 1], [1, 2, 1]]\\nfor n in range(N-3):\\n tmp = [0] * (2+n)\\n for i in range(len(P[-1])-1):\\n tmp[i] = sum(P[-1][i:i+2])\\n tmp = [1]+tmp+[1]\\n P.append(tmp)\\nprint(P[-1][K-1])\"\n },\n {\n \"alpha_fraction\": 0.5058823823928833,\n \"alphanum_fraction\": 0.5215686559677124,\n \"avg_line_length\": 17.285715103149414,\n \"blob_id\": \"b9f28aa32082e882ad7b6c3fb4edf1e4fa2f5723\",\n \"content_id\": \"8425547ce50a744fc851bfddf9ef23b1b8553d40\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 255,\n \"license_type\": \"no_license\",\n \"max_line_length\": 30,\n \"num_lines\": 14,\n \"path\": \"/알고리즘/온라인저지/2022/11/1108/도비의 영어 공부.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\n\\nwhile True:\\n tmp = input().rstrip()\\n check = tmp[0]\\n if check == '#': break\\n sen = tmp[2:]\\n result = 0\\n for s in sen:\\n if s.lower() == check:\\n result += 1\\n print(check, result)\"\n },\n {\n \"alpha_fraction\": 0.5030674934387207,\n \"alphanum_fraction\": 0.5153374075889587,\n \"avg_line_length\": 19.375,\n \"blob_id\": \"33ef02e8d4ea7cadcbd78e044c894c8d1fc73c3e\",\n \"content_id\": \"90abd7c62fb0ec98970dc898d24b3b778961ace8\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 163,\n \"license_type\": \"no_license\",\n \"max_line_length\": 34,\n \"num_lines\": 8,\n \"path\": \"/알고리즘/온라인저지/2023/06/0603/Judging Moose.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"L, R = map(int, input().split())\\nresult = 'Not a moose'\\nif L == R:\\n if L:\\n result = f'Even {L*2}'\\nelse:\\n result = f'Odd {max((L,R))*2}'\\nprint(result)\\n\"\n },\n {\n \"alpha_fraction\": 0.6071428656578064,\n \"alphanum_fraction\": 0.6071428656578064,\n \"avg_line_length\": 16.625,\n \"blob_id\": \"2c46261a38fcbd67da442e7156a7413c23fed7ea\",\n \"content_id\": \"14f6a0a667db5396199c32e6861b6d0f22ef5fc8\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 164,\n \"license_type\": \"no_license\",\n \"max_line_length\": 56,\n \"num_lines\": 8,\n \"path\": \"/알고리즘/온라인저지/2022/07/0701/접미사 배열.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"\\\"\\\"\\\"\\n접미사를 모아서, 정렬 후 출력\\n\\\"\\\"\\\"\\nword = input()\\narr = []\\nfor i in range(len(word)): arr.append(word[i:len(word)])\\narr.sort()\\nfor a in arr: print(a)\"\n },\n {\n \"alpha_fraction\": 0.4838709533214569,\n \"alphanum_fraction\": 0.5307917594909668,\n \"avg_line_length\": 27.5,\n \"blob_id\": \"9bdfc1f225ca2816c47656e83377f71e7567a063\",\n \"content_id\": \"e5edb6361d2d60e30b09ceb4e645a79bd5a867fe\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 341,\n \"license_type\": \"no_license\",\n \"max_line_length\": 72,\n \"num_lines\": 12,\n \"path\": \"/알고리즘/온라인저지/2021/08/0818/삼각형 외우기.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"data = []\\nfor _ in range(3):\\n data.append(int(input()))\\nif sum(data) == 180:\\n if data[0] == data[1] and data[1] == data[2] and data[2] == data[0]:\\n print('Equilateral')\\n elif data[0] == data[1] or data[1] == data[2] or data[2] == data[0]:\\n print('Isosceles')\\n else:\\n print('Scalene')\\nelse:\\n print('Error')\"\n },\n {\n \"alpha_fraction\": 0.4481408894062042,\n \"alphanum_fraction\": 0.4618395268917084,\n \"avg_line_length\": 22.272727966308594,\n \"blob_id\": \"ff2573218e2beb5fca0986a005aa3a2c15285f44\",\n \"content_id\": \"86415d71d7ad228b4a6789d1b4fd92a91a145c77\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 741,\n \"license_type\": \"no_license\",\n \"max_line_length\": 35,\n \"num_lines\": 22,\n \"path\": \"/알고리즘/온라인저지/2022/03/0323/A와 B.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"S = list(input())\\nT = list(input())\\nresult = 0\\n# S를 T로 만들지 않고, T를 S로 만든다\\n# 이유는 두 가지\\n# 1.pop()에서 인덱스 없이 사용하여 속도 향상\\n# 2.추가, 뒤집고 추가 -> 제거, 제거 후 뒤집기\\n# 후자는 둘 다 일단 제거하고 시작하므로 더 직관적임\\nwhile True:\\n if S == T:\\n result = 1 # S를 T로 만들 수 있다!\\n break # 종료\\n if T[-1] == 'A':\\n T.pop() # A를 빼주고\\n if not T: # 마지막 문자를 뺐다면\\n break # 종료\\n elif T[-1] == 'B':\\n T.pop() # B를 빼주고\\n if not T: # 마지막 문자를 뺐다면\\n break # 종료\\n T = T[::-1] # 뒤집고\\nprint(result) # 결과 출력\"\n },\n {\n \"alpha_fraction\": 0.5269230604171753,\n \"alphanum_fraction\": 0.5423076748847961,\n \"avg_line_length\": 20.75,\n \"blob_id\": \"341c3fce55c73ffef13d5ee4255424e07a75e5d4\",\n \"content_id\": \"0ada239f67af0a17f60f8d852360f69bdc2ea2e6\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 260,\n \"license_type\": \"no_license\",\n \"max_line_length\": 39,\n \"num_lines\": 12,\n \"path\": \"/알고리즘/온라인저지/2023/01/0108/고급 여관.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"A_atk, A_hp = map(int, input().split())\\nB_atk, B_hp = map(int, input().split())\\nwhile A_hp > 0 and B_hp > 0:\\n A_hp -= B_atk\\n B_hp -= A_atk\\nif A_hp > 0:\\n result = 'PLAYER A'\\nelif B_hp > 0:\\n result = 'PLAYER B'\\nelse:\\n result = 'DRAW'\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.4957983195781708,\n \"alphanum_fraction\": 0.5462185144424438,\n \"avg_line_length\": 19,\n \"blob_id\": \"c530d9f3fb9b641fe47aa9bae4e3c4e5c8c024bb\",\n \"content_id\": \"e0c2834302ec44a4eee72ac31b67fbaf5d8d4c98\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 119,\n \"license_type\": \"no_license\",\n \"max_line_length\": 50,\n \"num_lines\": 6,\n \"path\": \"/알고리즘/온라인저지/2022/09/0906/アイスクリーム (Ice Cream).py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"S, A, B = int(input()), int(input()), int(input())\\nresult = 250\\nwhile A < S:\\n A += B\\n result += 100\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.5072463750839233,\n \"alphanum_fraction\": 0.5507246255874634,\n \"avg_line_length\": 26.799999237060547,\n \"blob_id\": \"e2a6170203004231145789d3e95112b4be71927d\",\n \"content_id\": \"1bf9366add35ecc10481f340e203b4ad66f7db7a\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 138,\n \"license_type\": \"no_license\",\n \"max_line_length\": 49,\n \"num_lines\": 5,\n \"path\": \"/알고리즘/온라인저지/2023/02/0208/Patyki.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"A, B, C = sorted(list(map(int, input().split())))\\nresult = 0\\nif A == B == C: result = 2\\nelif C**2 == A**2 + B**2: result = 1\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.4878048896789551,\n \"alphanum_fraction\": 0.5365853905677795,\n \"avg_line_length\": 20,\n \"blob_id\": \"ae4121ca33a00e7cafae6093fdfdf7feb3bdd090\",\n \"content_id\": \"6b9f8f60309f5ea937420a5bb44fcea757514f3d\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 41,\n \"license_type\": \"no_license\",\n \"max_line_length\": 24,\n \"num_lines\": 2,\n \"path\": \"/알고리즘/온라인저지/2022/05/0520/접시 안의 원.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"T = int(input())\\nprint(round((T/2) ** 2))\"\n },\n {\n \"alpha_fraction\": 0.5882353186607361,\n \"alphanum_fraction\": 0.6274510025978088,\n \"avg_line_length\": 19.600000381469727,\n \"blob_id\": \"21f5688b03600b1fdc3aab959b3e34a6a9c77c82\",\n \"content_id\": \"273b9247cf8931846ff651d5559045ea1792d180\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 102,\n \"license_type\": \"no_license\",\n \"max_line_length\": 38,\n \"num_lines\": 5,\n \"path\": \"/알고리즘/온라인저지/2021/08/0822/검증수.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"data = list(map(int, input().split()))\\nresult = 0\\nfor dt in data:\\n result += dt**2\\nprint(result%10)\"\n },\n {\n \"alpha_fraction\": 0.5511810779571533,\n \"alphanum_fraction\": 0.5669291615486145,\n \"avg_line_length\": 13.222222328186035,\n \"blob_id\": \"ccd862d4c533f21d56ba0b2f1b3d649c3c68ae81\",\n \"content_id\": \"4c92aa24095aee2573d391ea2e56ac78c2f018a9\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 127,\n \"license_type\": \"no_license\",\n \"max_line_length\": 35,\n \"num_lines\": 9,\n \"path\": \"/알고리즘/온라인저지/2021/12/1230/트리 순회.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = int(input())\\n\\ntree = dict()\\n\\nfor n in range(N):\\n temp = input().split()\\n tree.update({temp[0]:temp[1:]})\\n\\nprint(tree)\"\n },\n {\n \"alpha_fraction\": 0.30434781312942505,\n \"alphanum_fraction\": 0.49275362491607666,\n \"avg_line_length\": 16.5,\n \"blob_id\": \"975333771309e83239097a6fd6a08bd9ea6a3fe2\",\n \"content_id\": \"5084e59fb323d465c857878932c1d49c820bb523\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 69,\n \"license_type\": \"no_license\",\n \"max_line_length\": 26,\n \"num_lines\": 4,\n \"path\": \"/알고리즘/SWEA/LEARN/Course/1. Programming Beginner/파이썬 프로그래밍 기초(2)/19차시 2. 자료구조 – 리스트, 튜플 - 연습문제 21.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"x = (1,2,3,4,5,6,7,8,9,10)\\n\\nprint(x[:len(x)//2])\\nprint(x[len(x)//2:])\"\n },\n {\n \"alpha_fraction\": 0.5405405163764954,\n \"alphanum_fraction\": 0.5675675868988037,\n \"avg_line_length\": 14,\n \"blob_id\": \"f110fcbdbd347580a7c3199890c084393ee1e233\",\n \"content_id\": \"05fb42ba8025166ead673f64d4e8694069039497\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 74,\n \"license_type\": \"no_license\",\n \"max_line_length\": 25,\n \"num_lines\": 5,\n \"path\": \"/알고리즘/온라인저지/2022/07/0714/5의 수난.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = input()\\nresult = 0\\nfor n in N:\\n result += int(n) ** 5\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.47422680258750916,\n \"alphanum_fraction\": 0.49484536051750183,\n \"avg_line_length\": 10.470588684082031,\n \"blob_id\": \"cf6645afaf8fe6f76032956bd127eb5fd94001dc\",\n \"content_id\": \"a768d4a2c00fed585d0b18ad1cbf3d2c9a40e32a\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 194,\n \"license_type\": \"no_license\",\n \"max_line_length\": 31,\n \"num_lines\": 17,\n \"path\": \"/알고리즘/온라인저지/2022/03/0302/막대기.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = int(input())\\n\\nsticks = []\\n\\nfor n in range(N):\\n sticks.append(int(input()))\\n\\nTH = 0 # Top Height\\n\\ncnt = 0\\n\\nfor s in sticks[::-1]:\\n if s > TH:\\n TH = s\\n cnt += 1\\n\\nprint(cnt)\"\n },\n {\n \"alpha_fraction\": 0.38085541129112244,\n \"alphanum_fraction\": 0.395112007856369,\n \"avg_line_length\": 14.870967864990234,\n \"blob_id\": \"aea18e9578905e352a590d0a8601c8114c92d2ab\",\n \"content_id\": \"f1667807a7c6af88cf7aed4c583d487c4115b44b\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 491,\n \"license_type\": \"no_license\",\n \"max_line_length\": 36,\n \"num_lines\": 31,\n \"path\": \"/알고리즘/온라인저지/2021/09/0909/Fly me to the Alpha Centauri.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\ndef input():\\n return sys.stdin.readline()\\n\\ndef how_many_times(x):\\n a = 1\\n i = 1\\n if a == x:\\n return i\\n b = 1\\n a = a+b\\n i += 1\\n if a == x:\\n return i\\n while True:\\n b += 1\\n a = a+b\\n i += 1\\n if a >= x:\\n break\\n a = a+b\\n i += 1\\n if a >= x:\\n break\\n return i\\n\\nT = int(input())\\nfor t in range(T):\\n x, y = map(int, input().split())\\n d = y-x\\n print(how_many_times(d))\"\n },\n {\n \"alpha_fraction\": 0.4335154891014099,\n \"alphanum_fraction\": 0.47358834743499756,\n \"avg_line_length\": 31.352941513061523,\n \"blob_id\": \"397751710974cc1a035a75880fd41afa22b71776\",\n \"content_id\": \"3d34bf0f4ecb1fc3ad860cab2be87c63be96e74f\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 739,\n \"license_type\": \"no_license\",\n \"max_line_length\": 52,\n \"num_lines\": 17,\n \"path\": \"/알고리즘/온라인저지/2021/08/0822/색종이.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"T = int(input())\\narr = [[0]*101 for _ in range(101)]\\nfor tc in range(T):\\n x1, y1 = map(int, input().split())\\n for i in range(y1, y1+10): # 색종이 크기는 10\\n for j in range(x1, x1+10): \\n if arr[i][j]: # 값이 들어있으면\\n continue # 컨티뉴\\n else: # 아직 저장된 값이 없으면\\n arr[i][j] = 1 # 1을 저장\\n # 합집합은 or연산\\n # True or로 넘어가기 때문에 값이 있으면 저장이 되지 않고\\n # 합해지는 부분을 연산할 필요가 없어짐\\narea = 0 # 면적\\nfor ar in arr: # 저장된 배열을 돌면서\\n area += sum(ar) # 각 줄을 더해서 면적에 저장\\nprint(area) # 출력\"\n },\n {\n \"alpha_fraction\": 0.5136986374855042,\n \"alphanum_fraction\": 0.5410959124565125,\n \"avg_line_length\": 12.363636016845703,\n \"blob_id\": \"ef1d321b927c51ee0dc7b30995ae4f71b7325630\",\n \"content_id\": \"1c11a7e0bd4e2383ecfe5390cbe6dcbdfad0cc48\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 146,\n \"license_type\": \"no_license\",\n \"max_line_length\": 32,\n \"num_lines\": 11,\n \"path\": \"/알고리즘/온라인저지/2022/03/0314/조합.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N, M = map(int, input().split())\\n\\nresult = 1\\n\\nfor n in range(N, N-M, -1):\\n result *= n\\n\\nfor m in range(1, M+1):\\n result //= m\\n\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.5,\n \"alphanum_fraction\": 0.5148147940635681,\n \"avg_line_length\": 17.066667556762695,\n \"blob_id\": \"2f145f5581c9b7a1b73059cab2f2b3412db626f3\",\n \"content_id\": \"59ed8cb888a97a936ce7dc7a1fe0a28ab9a2d904\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 270,\n \"license_type\": \"no_license\",\n \"max_line_length\": 29,\n \"num_lines\": 15,\n \"path\": \"/알고리즘/온라인저지/2022/05/0519/카드.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"card = dict()\\nfor n in range(int(input())):\\n tmp = int(input())\\n try:\\n card[tmp] += 1\\n except:\\n card[tmp] = 1\\nnum = sorted(list(card))\\nmaxx = 0\\nresult = 0\\nfor n in num:\\n if card[n] > maxx:\\n maxx = card[n]\\n result = n\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.569553792476654,\n \"alphanum_fraction\": 0.5774278044700623,\n \"avg_line_length\": 18.100000381469727,\n \"blob_id\": \"248ba5581730d62acece3d2deb71420699e1603f\",\n \"content_id\": \"0e191f45b800d3949d0db6250dacb4f22f90af51\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 381,\n \"license_type\": \"no_license\",\n \"max_line_length\": 51,\n \"num_lines\": 20,\n \"path\": \"/알고리즘/온라인저지/2022/11/1127/블로그.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\n\\nN, X = map(int, input().rstrip().split())\\nvisitors = list(map(int, input().rstrip().split()))\\n\\ntmp = sum(visitors[:X])\\nmaxx = tmp\\ncnt = 1\\n\\nfor i in range(X, N):\\n tmp -= visitors[i-X]\\n tmp += visitors[i]\\n if maxx < tmp:\\n maxx, cnt = tmp, 1\\n elif maxx == tmp:\\n cnt += 1\\n\\nprint('SAD') if not maxx else print(maxx, cnt)\"\n },\n {\n \"alpha_fraction\": 0.4729064106941223,\n \"alphanum_fraction\": 0.5049260854721069,\n \"avg_line_length\": 17.5,\n \"blob_id\": \"a5d77773fcfb2a0df9be510881a2b7bd3896b6bd\",\n \"content_id\": \"038020313039b0ebaa3c9af6ff069b19a31dab3b\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 406,\n \"license_type\": \"no_license\",\n \"max_line_length\": 49,\n \"num_lines\": 22,\n \"path\": \"/알고리즘/온라인저지/2021/08/0830/바이러스.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ndef dfs(v):\\n visited[v] = 1\\n global cnt\\n cnt += 1\\n for w in range(1, V+1):\\n if G[v][w] == 1 and not visited[w]:\\n dfs(w)\\n\\nV = int(sys.stdin.readline())\\nE = int(sys.stdin.readline())\\n\\nG = [[0] * (V+1) for _ in range(V+1)]\\nfor _ in range(E):\\n u, v = map(int, sys.stdin.readline().split())\\n G[u][v] = G[v][u] = 1\\n\\nvisited = [0] * (V+1)\\ncnt = -1\\ndfs(1)\\nprint(cnt)\"\n },\n {\n \"alpha_fraction\": 0.4962962865829468,\n \"alphanum_fraction\": 0.5135802626609802,\n \"avg_line_length\": 21.55555534362793,\n \"blob_id\": \"aa184790deb9b4bca496bbb1a2ac7c1a84f64a46\",\n \"content_id\": \"5d02e94eabab7b19a291b06c03caa754d4fa16ed\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 405,\n \"license_type\": \"no_license\",\n \"max_line_length\": 39,\n \"num_lines\": 18,\n \"path\": \"/알고리즘/온라인저지/2022/07/0726/카약과 강풍.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N, S, R = map(int, input().split())\\ncrack = list(map(int, input().split()))\\nspare = list(map(int, input().split()))\\nK = [True] * N # kayak\\nfor c in crack:\\n K[c-1] = False\\nfor s in spare:\\n try:\\n if not K[s-1]: K[s-1] = True\\n elif not K[s-2]: K[s-2] = True\\n elif not K[s]: K[s] = True\\n except:\\n pass\\nresult = 0\\nfor k in K:\\n if not k:\\n result += 1\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.5233160853385925,\n \"alphanum_fraction\": 0.5492228269577026,\n \"avg_line_length\": 23.25,\n \"blob_id\": \"0405622770cca534e75e4565e5793810a645ecb2\",\n \"content_id\": \"cacdc4d478ed2d82da0bd4ac5e409418f06a6399\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 193,\n \"license_type\": \"no_license\",\n \"max_line_length\": 36,\n \"num_lines\": 8,\n \"path\": \"/알고리즘/온라인저지/2023/04/0407/친구 친구.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N, M = map(int, input().split())\\nfriends = [0]*(N+1)\\nfor m in range(M):\\n A, B = map(int, input().split())\\n friends[A] += 1\\n friends[B] += 1\\nfor friend in friends[1:]:\\n print(friend)\"\n },\n {\n \"alpha_fraction\": 0.6222222447395325,\n \"alphanum_fraction\": 0.6222222447395325,\n \"avg_line_length\": 21.75,\n \"blob_id\": \"95bc9a368540f8dbfdf69f4d0cd780927787deed\",\n \"content_id\": \"059d3176a16002d48e839d17cbb2254ecd850f2b\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 90,\n \"license_type\": \"no_license\",\n \"max_line_length\": 32,\n \"num_lines\": 4,\n \"path\": \"/알고리즘/온라인저지/2022/03/0308/計算 (Calculation).py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"A, B = map(int, input().split())\\nresult = [A+B, A-B]\\nprint(max(result))\\nprint(min(result))\"\n },\n {\n \"alpha_fraction\": 0.4357541799545288,\n \"alphanum_fraction\": 0.46927374601364136,\n \"avg_line_length\": 19,\n \"blob_id\": \"da118e15c58a35e688249db65f79b7503af501c0\",\n \"content_id\": \"dfe52a50185ea1dd87e3cb19d65da228420e1272\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 179,\n \"license_type\": \"no_license\",\n \"max_line_length\": 36,\n \"num_lines\": 9,\n \"path\": \"/알고리즘/온라인저지/2022/03/0326/경기 결과.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = int(input())\\nresult = [0, 0]\\nfor n in range(N):\\n A, B = map(int, input().split())\\n if A > B:\\n result[0] += 1\\n elif B > A:\\n result[1] += 1\\nprint(*result)\"\n },\n {\n \"alpha_fraction\": 0.3196721374988556,\n \"alphanum_fraction\": 0.33811476826667786,\n \"avg_line_length\": 24.05128288269043,\n \"blob_id\": \"df2adfc59d6279c57db076d78cbb8c134a8d52b5\",\n \"content_id\": \"7e085a366050e2dbd6ab58e3c61a8a0440f8c2a8\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 976,\n \"license_type\": \"no_license\",\n \"max_line_length\": 73,\n \"num_lines\": 39,\n \"path\": \"/알고리즘/온라인저지/2021/12/1216/유기농 배추.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from collections import deque\\n\\nT = int(input())\\n\\ndx = [-1, 1, 0, 0]\\ndy = [0, 0, -1, 1]\\n\\nfor tc in range(T):\\n M, N, K = map(int, input().split())\\n\\n field = [[0] * M for _ in range(N)]\\n\\n for k in range(K):\\n x, y = map(int, input().split())\\n field[y][x] = 1\\n \\n worm = deque()\\n cnt = 0\\n\\n for i in range(N):\\n for j in range(M):\\n if field[i][j]:\\n worm.append((i, j))\\n cnt += 1\\n while worm:\\n tmp = worm.popleft()\\n y = tmp[0]\\n x = tmp[1]\\n if field[y][x]:\\n field[y][x] = 0\\n else:\\n continue\\n for k in range(4):\\n nx = x + dx[k]\\n ny = y + dy[k]\\n if 0 <= nx < M and 0 <= ny < N and field[ny][nx]:\\n worm.append((ny, nx))\\n\\n print(cnt)\"\n },\n {\n \"alpha_fraction\": 0.3085106313228607,\n \"alphanum_fraction\": 0.3297872245311737,\n \"avg_line_length\": 17.799999237060547,\n \"blob_id\": \"4ff5d3dba6c60429d2c2323ec5be6b705a2432d2\",\n \"content_id\": \"ab1b6f613269ad0d268a17de920e8ef6520cd742\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 282,\n \"license_type\": \"no_license\",\n \"max_line_length\": 30,\n \"num_lines\": 15,\n \"path\": \"/알고리즘/온라인저지/2021/12/1213/화성 수학.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"T = int(input())\\n\\nfor tc in range(T):\\n a = input().split()\\n b = float(a[0])\\n\\n for i in range(1, len(a)):\\n if a[i] == '@':\\n b *= 3\\n elif a[i] == '%':\\n b += 5\\n elif a[i] == '#':\\n b -= 7\\n \\n print('{:.2f}'.format(b))\\n\"\n },\n {\n \"alpha_fraction\": 0.41516244411468506,\n \"alphanum_fraction\": 0.4332129955291748,\n \"avg_line_length\": 22.16666603088379,\n \"blob_id\": \"251080aecbb4122b51c51c8418e11f1e887b0fb0\",\n \"content_id\": \"fdab24c692535f786919a4c7cc4f53816dfdef9f\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 277,\n \"license_type\": \"no_license\",\n \"max_line_length\": 37,\n \"num_lines\": 12,\n \"path\": \"/알고리즘/온라인저지/2023/01/0113/중복을 없애자.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"while True:\\n tmp = input()\\n if tmp == '0': break\\n tmp = list(map(int, tmp.split()))\\n N, arr = tmp[0], tmp[1:]\\n last = arr[0]\\n print(last, end=' ')\\n for a in arr[1:]:\\n if a != last:\\n last = a\\n print(last, end=' ')\\n print('$')\"\n },\n {\n \"alpha_fraction\": 0.5337837934494019,\n \"alphanum_fraction\": 0.6036036014556885,\n \"avg_line_length\": 20.14285659790039,\n \"blob_id\": \"2b6965ac4e179e9e9303f4034351e1d2b6da808c\",\n \"content_id\": \"3e693c441e72d8b894f1d01f7fa1b4c18a476895\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 444,\n \"license_type\": \"no_license\",\n \"max_line_length\": 45,\n \"num_lines\": 21,\n \"path\": \"/알고리즘/온라인저지/2021/12/1213/주사위 세개.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"a = list(map(int, input().split()))\\n\\ndice_num_count = [0 for _ in range(6)]\\n\\nfor i in a:\\n dice_num_count[i-1] += 1\\n\\nsame_or_max = 0\\nresult = 0\\n\\nif 3 in dice_num_count:\\n same_or_max = dice_num_count.index(3) + 1\\n result = 10000 + same_or_max * 1000\\nelif 2 in dice_num_count:\\n same_or_max = dice_num_count.index(2) + 1\\n result = 1000 + same_or_max * 100\\nelse:\\n same_or_max = max(a)\\n result = same_or_max * 100\\n\\nprint(result)\\n\"\n },\n {\n \"alpha_fraction\": 0.5522388219833374,\n \"alphanum_fraction\": 0.5671641826629639,\n \"avg_line_length\": 18.285715103149414,\n \"blob_id\": \"4fbf180120aed0adb4f422f6ca1e9b774cb487dc\",\n \"content_id\": \"bab83934a4ed66fcd62cc3a56a40e16067f43293\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 134,\n \"license_type\": \"no_license\",\n \"max_line_length\": 38,\n \"num_lines\": 7,\n \"path\": \"/알고리즘/온라인저지/2022/03/0320/Identifying tea.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"T = int(input())\\nteas = list(map(int, input().split()))\\nresult = 0\\nfor tea in teas:\\n if T == tea:\\n result += 1\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.3494318127632141,\n \"alphanum_fraction\": 0.3920454680919647,\n \"avg_line_length\": 31.090909957885742,\n \"blob_id\": \"ccd8ef9cedfae2ac5436e5805ca534d1e973415c\",\n \"content_id\": \"7ca0f0131c32920e94ef35766056dc67218b9726\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 352,\n \"license_type\": \"no_license\",\n \"max_line_length\": 44,\n \"num_lines\": 11,\n \"path\": \"/알고리즘/온라인저지/2022/05/0509/수학적 호기심.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"for t in range(int(input())):\\n N, M = map(int, input().split())\\n result = 0\\n for i in range(1, N-1):\\n for j in range(i+1, N):\\n # print((i**2 + j**2 + M)/(i*j))\\n case1 = (i**2 + j**2 + M)/(i*j)\\n case2 = (i**2 + j**2 + M)//(i*j)\\n if case1 == case2:\\n result += 1\\n print(result)\"\n },\n {\n \"alpha_fraction\": 0.6030769348144531,\n \"alphanum_fraction\": 0.6123076677322388,\n \"avg_line_length\": 22.285715103149414,\n \"blob_id\": \"759fb04e5626169f42c59e41c20fb3dd7661eb3c\",\n \"content_id\": \"2275b27bf4143e1a2eb6fa797b6e4800f365c77a\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 325,\n \"license_type\": \"no_license\",\n \"max_line_length\": 50,\n \"num_lines\": 14,\n \"path\": \"/알고리즘/온라인저지/2022/09/0927/숫자 카드 2.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\n\\ninput().rstrip()\\ncards = list(map(int, input().rstrip().split()))\\ncount = dict()\\nfor card in cards:\\n try: count[card] += 1\\n except: count[card] = 1\\ninput().rstrip()\\nfor i in list(map(int, input().rstrip().split())):\\n try: print(count[i], end=' ')\\n except: print(0, end=' ')\"\n },\n {\n \"alpha_fraction\": 0.4481012523174286,\n \"alphanum_fraction\": 0.4911392331123352,\n \"avg_line_length\": 22.294116973876953,\n \"blob_id\": \"91b0453cf990e3e3f2b1fe56ebfbb62484cd6929\",\n \"content_id\": \"e94f931a39991219afe02f4e5837dfb7472d77ea\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 403,\n \"license_type\": \"no_license\",\n \"max_line_length\": 45,\n \"num_lines\": 17,\n \"path\": \"/알고리즘/온라인저지/2022/12/1223/추론.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"def plus_or_multiply(A, B):\\n if A == B: # 등차\\n Q = nums[1]-nums[0]\\n result = nums[-1]+Q\\n else: # 등비\\n Q = nums[1]//nums[0]\\n result = nums[-1]*Q\\n return result\\n\\nN = int(input())\\nnums = [int(input()) for _ in range(N)]\\nA, B = 0, 0\\nif N == 3:\\n A, B = nums[0]+nums[-1], nums[1]*2\\nelse:\\n A, B = nums[0]+nums[-1], nums[1]+nums[-2]\\nprint(plus_or_multiply(A, B))\"\n },\n {\n \"alpha_fraction\": 0.4821428656578064,\n \"alphanum_fraction\": 0.5,\n \"avg_line_length\": 27.5,\n \"blob_id\": \"5c8bd0d07688a36f8ecb58abe8e6a776e95cd13f\",\n \"content_id\": \"ac82ca538c24ebbf6292e8741ff37b0402f35508\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 56,\n \"license_type\": \"no_license\",\n \"max_line_length\": 35,\n \"num_lines\": 2,\n \"path\": \"/알고리즘/온라인저지/2022/04/0424/폰 노이만과 파리.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"S, T, D = map(int, input().split())\\nprint((D//S//2) * T)\"\n },\n {\n \"alpha_fraction\": 0.4094955623149872,\n \"alphanum_fraction\": 0.4540059268474579,\n \"avg_line_length\": 16.789474487304688,\n \"blob_id\": \"9c5d06eb0c1943cd39e4e18b4f70b58959cb597a\",\n \"content_id\": \"f2ec5b66bf341f4649c2d791ebbfbcd484fd84ff\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 337,\n \"license_type\": \"no_license\",\n \"max_line_length\": 40,\n \"num_lines\": 19,\n \"path\": \"/알고리즘/온라인저지/2022/03/0303/알고리즘 수업 - 알고리즘의 수행 시간 6.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"n = int(input())\\n\\n# result = 0\\n# dim = 3\\n\\n# for i in range(1, n-1):\\n# for j in range(i+1, n):\\n# for k in range(j+1, n+1): \\n# result += 1\\n# print(i, j, k)\\n\\nresult = 0\\ndim = 3\\n\\nfor i in range(1, n-1):\\n # result += sum(list(range(1, i+1)))\\n result += i * (n-i-1)\\n\\nprint(result, f'\\\\n{dim}', sep='')\"\n },\n {\n \"alpha_fraction\": 0.4348958432674408,\n \"alphanum_fraction\": 0.4479166567325592,\n \"avg_line_length\": 13.259259223937988,\n \"blob_id\": \"8b7b4b18f4032998f59adf6c1e580f452fc3f498\",\n \"content_id\": \"f658042b74e1a8f255b8ed6e533455fbc945b3c2\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 384,\n \"license_type\": \"no_license\",\n \"max_line_length\": 37,\n \"num_lines\": 27,\n \"path\": \"/알고리즘/온라인저지/2022/02/0207/오르막길.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = int(input())\\n\\narr = list(map(int, input().split()))\\n\\nstart = arr[0]\\n\\nup = True\\n\\nmaxx = 0\\n\\nfor i in range(1, N):\\n if arr[i] <= arr[i-1]:\\n up = False\\n tmp = arr[i-1] - start\\n start = arr[i]\\n \\n if tmp > maxx:\\n maxx = tmp\\n\\n else:\\n up = True\\n\\nif up:\\n if arr[i]-start > maxx:\\n maxx = arr[i]-start\\n \\nprint(maxx)\"\n },\n {\n \"alpha_fraction\": 0.49643704295158386,\n \"alphanum_fraction\": 0.5344418287277222,\n \"avg_line_length\": 24.545454025268555,\n \"blob_id\": \"134846b54d424bd59d3f64a5536af70262f2ebc3\",\n \"content_id\": \"b149304ffa5aef723d5f145c149da59900d4f02a\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1178,\n \"license_type\": \"no_license\",\n \"max_line_length\": 70,\n \"num_lines\": 33,\n \"path\": \"/알고리즘/온라인저지/2022/02/0225/마인크래프트.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys # 주어진 시간이 적은 문제\\n# sys.stdin.readline()과 PyPy3을 사용\\n\\nN, M, B = map(int, sys.stdin.readline().split())\\n\\narr = [list(map(int, sys.stdin.readline().split())) for _ in range(N)]\\n\\ntime, height = 9223372036854775807, 0 # 가상의 최대시간, 높이\\n\\nfor h in range(257): # 브루트포스, 모든 높이에 대한 소요시간과 높이 계산\\n # 동일 시간인 경우 더 높은 높이를 출력할 것이므로 \\n # 높이는 0에서 256으로 진행\\n\\n bot = top = 0 # 변수 초기화\\n\\n # 매 높이 h에 대하여, 모든 배열 순회\\n for i in range(N):\\n for j in range(M):\\n if arr[i][j] < h: # 블럭을 채워야하면\\n bot += h-arr[i][j] # bot에 추가\\n else: # 블럭을 깎아야하면\\n top += arr[i][j]-h # top에 추가\\n\\n if bot > top + B: # 가진블럭 + 깎은블럭으로도 다 채우지 못하면\\n continue # 지나가고\\n\\n t = bot + top*2 # 걸리는 시간은 채우기1초 깎기2초를 총 더한 시간\\n\\n if t <= time:\\n time = t # 최소시간 갱신\\n height = h # 최대높이 갱신\\n\\nprint(time, height) # 출력\"\n },\n {\n \"alpha_fraction\": 0.5333333611488342,\n \"alphanum_fraction\": 0.5696969628334045,\n \"avg_line_length\": 26.66666603088379,\n \"blob_id\": \"e8ee647a1a00164d47558a516edd1dec4e7ea06d\",\n \"content_id\": \"1d775d2d67e335ffa60c0be74027590b1fa9ac68\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 165,\n \"license_type\": \"no_license\",\n \"max_line_length\": 33,\n \"num_lines\": 6,\n \"path\": \"/알고리즘/온라인저지/2023/06/0606/Fence Painting.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"A, B = map(int, input().split())\\nC, D = map(int, input().split())\\nwall = [0]*101\\nfor i in range(A, B): wall[i] = 1\\nfor i in range(C, D): wall[i] = 1\\nprint(sum(wall))\"\n },\n {\n \"alpha_fraction\": 0.29209622740745544,\n \"alphanum_fraction\": 0.3161512017250061,\n \"avg_line_length\": 19.85714340209961,\n \"blob_id\": \"475d7aff513dc9ddfd9772683a4febd0d1ce7427\",\n \"content_id\": \"e3eab673f3146b5ac2746c855c2c24f281e7201f\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 291,\n \"license_type\": \"no_license\",\n \"max_line_length\": 27,\n \"num_lines\": 14,\n \"path\": \"/알고리즘/온라인저지/2022/03/0329/집 주소.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"while True:\\n N = list(input())\\n if N == ['0']:\\n break\\n else:\\n result = 1\\n for n in N:\\n if n == '1':\\n result += 3\\n elif n == '0':\\n result += 5\\n else:\\n result += 4\\n print(result)\"\n },\n {\n \"alpha_fraction\": 0.5138888955116272,\n \"alphanum_fraction\": 0.5416666865348816,\n \"avg_line_length\": 17.25,\n \"blob_id\": \"8792bac9a564e78f090d21bac5de4cc6e676d3d6\",\n \"content_id\": \"822eb4358aa1c85c2a915318706ee3b67efb5ef9\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 72,\n \"license_type\": \"no_license\",\n \"max_line_length\": 31,\n \"num_lines\": 4,\n \"path\": \"/알고리즘/SWEA/LEARN/Course/1. Programming Beginner/파이썬 프로그래밍 기초(2)/42차시 4. 문자열 - 연습문제 7.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"tmp = input()\\n\\nfor i in range(0, len(tmp), 2):\\n print(tmp[i], end='')\"\n },\n {\n \"alpha_fraction\": 0.4774305522441864,\n \"alphanum_fraction\": 0.49884259700775146,\n \"avg_line_length\": 25.196969985961914,\n \"blob_id\": \"3f5af3f94d5139142baf97e9d01655e9d2294b60\",\n \"content_id\": \"c4df36605e424a20b4ca08134b93bef5a9ed3abd\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 2024,\n \"license_type\": \"no_license\",\n \"max_line_length\": 66,\n \"num_lines\": 66,\n \"path\": \"/알고리즘/[템플릿]/BFS/치즈 업그레이드.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\nfrom collections import deque\\n\\ninput = sys.stdin.readline\\ndy, dx = [-1, 1, 0, 0], [0, 0, -1, 1]\\n\\ndef melt_check():\\n global time\\n melt = True\\n for i in range(N):\\n for j in range(M):\\n if arr[i][j]:\\n melt = False\\n if not melt: time += 1\\n return melt\\n\\ndef delta_move(y, x):\\n for i in range(4):\\n ny, nx = y+dy[i], x+dx[i]\\n if 0<=ny<N and 0<=nx<M and not visited[ny][nx]:\\n if arr[ny][nx]:\\n cheese_Q.append((ny, nx))\\n visited[ny][nx] = 2 # 방문 배열에 2는 치즈\\n # 치즈를 녹일 때 주위에 1(공기)이 2개 이상 있으면 녹일 것\\n else: \\n Q.append((ny, nx))\\n visited[ny][nx] = 1 # 방문 배열에 1은 공기\\n\\ndef melt_cheese(y, x):\\n tmp = 0\\n for i in range(4):\\n ny, nx = y+dy[i], x+dx[i]\\n if visited[ny][nx] == 1: tmp += 1\\n if tmp >= 2:\\n melt_Q.append((y, x))\\n else: visited[y][x] = 0\\n # 치즈 배열의 특성상 반드시 두 면 이상 공기와 접촉하는 치즈가 있고\\n # 녹은 치즈, 즉 새로운 탐색점은, 매 while문마다 반드시 나온다\\n\\nN, M = map(int, input().rstrip().split())\\narr = [list(map(int, input().rstrip().split())) for _ in range(N)]\\nQ, cheese_Q, melt_Q = deque(), deque(), deque()\\nvisited = [[0]*M for _ in range(N)]\\nQ.append((0, 0))\\nvisited[0][0] = 1\\ntime = 0\\nwhile True:\\n if melt_check(): print(time); break\\n while Q: # 공기를 탐색하면서\\n y, x = Q.popleft()\\n delta_move(y, x) # 치즈를 찾자\\n while cheese_Q: # 치즈들 중에서\\n y, x = cheese_Q.popleft()\\n melt_cheese(y, x) # 녹일 수 있는 치즈를 찾자\\n while melt_Q: # 녹일 수 있는 치즈들을\\n y, x = melt_Q.popleft()\\n arr[y][x] = 0 # 녹이자\\n visited[y][x] = 1\\n Q.append((y, x))\\n \\n\\\"\\\"\\\"\\n치즈가 녹은 자리는 공기가 된다\\n녹이고 Q에 추가하기\\n\\\"\\\"\\\"\\n\\n# https://www.acmicpc.net/problem/2638\"\n },\n {\n \"alpha_fraction\": 0.6451612710952759,\n \"alphanum_fraction\": 0.6451612710952759,\n \"avg_line_length\": 23.22222137451172,\n \"blob_id\": \"dff9cf1226079b0c6fd26d73b7450656c02d5192\",\n \"content_id\": \"4c134be02501a7be8383fc9dd8b36565998b3b1f\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 279,\n \"license_type\": \"no_license\",\n \"max_line_length\": 63,\n \"num_lines\": 9,\n \"path\": \"/알고리즘/[템플릿]/진법 변환/진법 변환 2.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import string\\n\\nN, B = map(int, input().split())\\ntmp = string.digits + string.ascii_uppercase # 자릿수를 담은 문자열\\nresult = ''\\nwhile N:\\n result = tmp[N%B] + result # B진법이므로 B로 나눈 나머지번째 문자를 계속 추가한다\\n N //= B\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.41310539841651917,\n \"alphanum_fraction\": 0.5384615659713745,\n \"avg_line_length\": 17.421052932739258,\n \"blob_id\": \"b4b42aa6602a741971957249b50e815fb0eaaf93\",\n \"content_id\": \"8f8d39dc6115fdcbed96e262bb7447d74cbb1f97\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 561,\n \"license_type\": \"no_license\",\n \"max_line_length\": 41,\n \"num_lines\": 19,\n \"path\": \"/알고리즘/온라인저지/2021/08/0806/알람 시계.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"\\\"\\\"\\\"\\n구하고자 하는 건 45분 전\\n분에 15분을 더하고\\n시간에 한시간을 빼고\\n60분을 넘기면 60을 빼주고\\n24시간을 넘기면 24를 빼주고\\n\\\"\\\"\\\"\\n\\nH, M = map(int, input().split()) # 입력 받아서\\nM += 15 # 15분 더하고\\nH -= 1 # 1시간 빼고\\nif M >= 60: # 60분을 넘기면\\n M -= 60 # 60빼주고 0분부터\\n H += 1 # 1시간 더하고\\nif H >= 24: # 24시간 넘기면 0시부터\\n H -= 24\\nif H == -1: # 계산을 마친 시간이 23시면\\n H = 23 # 계산값인 -1을 23으로 덮어 씌우기\\nprint(H, M) # 출력\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.4157303273677826,\n \"alphanum_fraction\": 0.483146071434021,\n \"avg_line_length\": 29,\n \"blob_id\": \"b9e666a91d43b43f0a5bd75f65704f7fb84ea42f\",\n \"content_id\": \"9e0cecd9cad8f0eb13dfa12b175911b4f9acff8f\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 89,\n \"license_type\": \"no_license\",\n \"max_line_length\": 40,\n \"num_lines\": 3,\n \"path\": \"/알고리즘/온라인저지/2022/05/0502/꼬리를 무는 숫자 나열.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"A, B = map(int, input().split())\\nC, D = A-1, B-1\\nprint(abs(C%4 - D%4) + abs(C//4 - D//4))\"\n },\n {\n \"alpha_fraction\": 0.5511363744735718,\n \"alphanum_fraction\": 0.5994318127632141,\n \"avg_line_length\": 28.375,\n \"blob_id\": \"2627af9b9bc41cb439e32069057b8b8f9c2ccb95\",\n \"content_id\": \"32c9ba503606df4f8788e4e309c64e522640511c\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1074,\n \"license_type\": \"no_license\",\n \"max_line_length\": 67,\n \"num_lines\": 24,\n \"path\": \"/알고리즘/온라인저지/2022/10/1004/동전 1.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\n\\nN, K = map(int, input().rstrip().split())\\ncoins = [int(input().rstrip()) for _ in range(N)]\\ndp = [0]*(K+1)\\ndp[0] = 1 # 0원을 지불하는 방법은, 아무것도 내지 않는 경우 딱 하나\\nfor coin in coins: # 각각 동전 종류에 대해\\n for i in range(1, K+1): # 1원을 내는 경우부터 출발\\n if i-coin>=0: # 음수의 금액을 낸 경우는 존재하지 않으므로, 0원을 낸 경우 이상부터 확인\\n dp[i] += dp[i-coin] # 해당 금액의 동전을 내기 전의 경우의 수 만큼을 더해준다\\nprint(dp[K])\\n\\n\\\"\\\"\\\"\\n예제는 동전의 종류가 1 2 5 이므로 1원동전 일 때, dp가 1, 1, 1, ... 이 되기 때문에 헷갈릴 수 있으나\\n만약 2 5 7과 같은 종류였다면\\nfor coin in coins 1회차에 dp는 \\n1, 0, 1, 0, 1, 0, 1 ... 과 같이 저장되었을 것이다\\n계산된 값(dp[i])를 실시간으로 반영하면서 line 10의 for문을 돌기 때문에\\ndp[i] += dp[i-coin] 만으로도 정답코드가 될 수 있다\\n\\\"\\\"\\\"\\n\\n# https://www.acmicpc.net/problem/2293\"\n },\n {\n \"alpha_fraction\": 0.5011600852012634,\n \"alphanum_fraction\": 0.5127609968185425,\n \"avg_line_length\": 29.821428298950195,\n \"blob_id\": \"cbf3a204b5a3f9bf35bc1a275a5ec9e947d3e22b\",\n \"content_id\": \"8aa1af75b83181076c166cafdc62fb666c1cbb10\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1122,\n \"license_type\": \"no_license\",\n \"max_line_length\": 57,\n \"num_lines\": 28,\n \"path\": \"/알고리즘/온라인저지/2022/04/0430/프린터 큐.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\nfrom collections import deque\\n\\ndef input():\\n return sys.stdin.readline()\\n\\nfor t in range(int(input())):\\n result = 1 # 인쇄 순서 초기화\\n N, M = map(int, input().split())\\n tmp = list(map(int, input().split())) # 문서 중요도 입력\\n docs = deque() # popleft() 사용할 것\\n i = 0 # 문서의 순서\\n for tm in tmp:\\n docs.append((tm, i)) # 현재 문서의 (중요도, 순서) 를 담은 리스트\\n i += 1\\n # print(docs) # 디버깅\\n while docs: # \\n tmp = [] # 문서의 중요도들만을 담을 리스트\\n for i in range(len(docs)):\\n tmp.append(docs[i][0])\\n if docs[0][0] != max(tmp): # 가장 중요도가 높은 문서가 아니라면\\n docs.append(docs.popleft()) # 해당 문서를 가장 뒤로 이동\\n else: # 가장 중요도가 높은 문서라면\\n if M == docs[0][1]: # 구하고자 하는 인쇄순서의 문서라면\\n break # 종료하고\\n docs.popleft() # 인쇄\\n result += 1 # 인쇄순서 +1\\n print(result) # 현재 인쇄순서 번호를 출력\"\n },\n {\n \"alpha_fraction\": 0.41818180680274963,\n \"alphanum_fraction\": 0.4561983346939087,\n \"avg_line_length\": 16.257143020629883,\n \"blob_id\": \"508d18ffc92b103f069b90ad4d80b2c31603390c\",\n \"content_id\": \"a78d07f40fc64425b5c0d96e38579f3739e8a212\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 605,\n \"license_type\": \"no_license\",\n \"max_line_length\": 56,\n \"num_lines\": 35,\n \"path\": \"/알고리즘/온라인저지/2021/12/1216/미로 탐색.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from collections import deque\\n\\nN, M = map(int, input().split())\\nmaze = [list(map(int, input())) for _ in range(N)]\\n\\ndx = [-1, 1, 0, 0]\\ndy = [0, 0, -1, 1]\\n\\nroutes = deque()\\n\\nroutes.append((0, 0, 0))\\n\\nwhile routes:\\n tmp = routes.popleft()\\n y = tmp[0]\\n x = tmp[1]\\n cnt = tmp[2]\\n \\n if y == N-1 and x == M-1:\\n print(cnt + 1)\\n break\\n\\n if maze[y][x] == 0:\\n continue\\n\\n maze[y][x] = 0\\n\\n cnt += 1\\n\\n for i in range(4):\\n ny = y + dy[i]\\n nx = x + dx[i]\\n\\n if 0 <= ny < N and 0 <= nx < M and maze[ny][nx]:\\n routes.append((ny, nx, cnt))\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.45255473256111145,\n \"alphanum_fraction\": 0.48175182938575745,\n \"avg_line_length\": 14.333333015441895,\n \"blob_id\": \"f007621dd739effddcf425885143f52566fd86ab\",\n \"content_id\": \"c8e8246694df9a3e8bbf4bd3ffa08b73d536bafb\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 137,\n \"license_type\": \"no_license\",\n \"max_line_length\": 21,\n \"num_lines\": 9,\n \"path\": \"/알고리즘/온라인저지/2022/05/0517/지속.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = input()\\nresult = 0\\nwhile len(N) > 1:\\n tmp = 1\\n for n in N:\\n tmp *= int(n)\\n N = str(tmp)\\n result += 1\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.417391300201416,\n \"alphanum_fraction\": 0.426086962223053,\n \"avg_line_length\": 18.33333396911621,\n \"blob_id\": \"76820257f4dfa2cbf3850f3e8c84abaf0884dfd7\",\n \"content_id\": \"ab80de87cf6144c80ea7de0a93e23f42b78e5afd\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 115,\n \"license_type\": \"no_license\",\n \"max_line_length\": 40,\n \"num_lines\": 6,\n \"path\": \"/알고리즘/온라인저지/2022/08/0827/Shares.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"while True:\\n try:\\n N, S = map(int, input().split())\\n N += 1\\n print(S//N)\\n except: exit()\"\n },\n {\n \"alpha_fraction\": 0.36915886402130127,\n \"alphanum_fraction\": 0.4579439163208008,\n \"avg_line_length\": 27.566667556762695,\n \"blob_id\": \"cba2c47b9b09ca8fb1dc5e5d78700695801ee29c\",\n \"content_id\": \"01cd0a77d818568e1f0410012619e3f1abe738ac\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1242,\n \"license_type\": \"no_license\",\n \"max_line_length\": 59,\n \"num_lines\": 30,\n \"path\": \"/알고리즘/온라인저지/2021/08/0813/ATM.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = int(input()) # 사람 수\\nusers = list(map(int, input().split())) # 각자 ATM 이용에 걸리는 시간\\n\\\"\\\"\\\"\\n1 2 3 4 5 번째 사람이\\n3 1 4 3 2 분이 걸린다 하면\\n\\n1 2 3 4 5 순으로 가면\\n1번은 3분 걸리고\\n2번은 3분걸린 1번에 얹어서 1분걸려서 총 4분\\n3번은 앞에서 걸린 4분 + 본인 4분 = 8분\\n4번은 앞사람 8분 + 본인 3분\\n결국 앞에서 걸린 시간들이 길수록 뒤에도 늦어진다는거\\n용무가 빨리 끝나는 사람 먼저 하는게 핵심\\n걸리는 시간이 짧은순으로 정렬하고 볼일 보게 하는 것\\n1 = 1\\n1+2 = 3\\n1+2+3 = 6\\n1+2+3+3 = 9\\n1+2+3+3+4 = 13\\n1+3+6+9+13 = 32\\n1 (1+2) (1+2+3) (1+2+3+3) (1+2+3+3+4)\\n\\\"\\\"\\\"\\nusers.sort() # 걸리는 시간들을 정렬\\nresult = 0 # 결과값을 초기화\\nfor n in range(N): # 사람수만큼 반복\\n wait_time = 0 # 본인의 대기시간\\n for j in range(n+1): # 앞사람들+본인 시간만큼 반복\\n wait_time += users[j] # 대기+사용시간 구해서\\n result += wait_time # 다 집어넣고\\nprint(result) # 출력\"\n },\n {\n \"alpha_fraction\": 0.42975205183029175,\n \"alphanum_fraction\": 0.4793388545513153,\n \"avg_line_length\": 23.399999618530273,\n \"blob_id\": \"065c00350c9b4cb1db77bd209e2f9beb09307995\",\n \"content_id\": \"9c465cc04a6ff091fdc5bfd38bbb5001a7dd8c9e\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 121,\n \"license_type\": \"no_license\",\n \"max_line_length\": 32,\n \"num_lines\": 5,\n \"path\": \"/알고리즘/온라인저지/2022/12/1208/A나누기B - 2.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"A, B = map(int, input().split())\\nprint(f'{A//B}.', end='')\\nfor _ in range(1001):\\n A = (A%B)*10\\n print(A//B, end='')\"\n },\n {\n \"alpha_fraction\": 0.5166666507720947,\n \"alphanum_fraction\": 0.5366666913032532,\n \"avg_line_length\": 29.100000381469727,\n \"blob_id\": \"c8430d9db43435a971d86ffb2b18d07773e6c57e\",\n \"content_id\": \"e39b10aeae30802284a37019b6b26d233003c667\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 300,\n \"license_type\": \"no_license\",\n \"max_line_length\": 49,\n \"num_lines\": 10,\n \"path\": \"/알고리즘/온라인저지/2022/07/0731/기타줄.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N, M = map(int, input().split())\\nS_min = P_min = 1e9 # set min, piece min\\nfor m in range(M):\\n S, P = map(int, input().split()) # set, piece\\n if S < S_min: S_min = S\\n if P < P_min: P_min = P\\n if P*6 < S_min: S_min = P*6\\nresult = N//6 * S_min\\nresult += min(N%6 * P_min, S_min)\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.4893617033958435,\n \"alphanum_fraction\": 0.5319148898124695,\n \"avg_line_length\": 22.66666603088379,\n \"blob_id\": \"3b50934dea7449c34c89b0d094d260ab1a462aef\",\n \"content_id\": \"541df3e0a30eed520471d3529c261ed2df129a56\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 141,\n \"license_type\": \"no_license\",\n \"max_line_length\": 38,\n \"num_lines\": 6,\n \"path\": \"/알고리즘/온라인저지/2023/04/0411/ZOAC 4.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"H, W, N, M = map(int, input().split())\\nresult = 0\\nfor i in range(0, H, 1+N):\\n for j in range(0, W, 1+M):\\n result += 1\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.5049999952316284,\n \"alphanum_fraction\": 0.5400000214576721,\n \"avg_line_length\": 25.733333587646484,\n \"blob_id\": \"c79d50d3e6ac5c7eaa7352f748699c1069cc093a\",\n \"content_id\": \"39c6e3e10549a9dc8e1fad269e4aea21109a0a94\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 400,\n \"license_type\": \"no_license\",\n \"max_line_length\": 46,\n \"num_lines\": 15,\n \"path\": \"/알고리즘/온라인저지/2022/07/0731/수 찾기(재귀함수).py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"def binary(t, s, e): # target, start, end\\n if s > e: return 0\\n i = (s+e) // 2 # index\\n if t == arr1[i]: return 1\\n elif t < arr1[i]: return binary(t, s, i-1)\\n elif t > arr1[i]: return binary(t, i+1, e)\\n\\nN = int(input())\\narr1 = list(map(int, input().split()))\\narr1.sort()\\nM = int(input())\\narr2 = list(map(int, input().split()))\\nfor a in arr2:\\n s, e = 0, N-1\\n print(binary(a, s, e))\"\n },\n {\n \"alpha_fraction\": 0.40532544255256653,\n \"alphanum_fraction\": 0.4289940893650055,\n \"avg_line_length\": 20.1875,\n \"blob_id\": \"0e17b301b3d8c3a2d0cdeb9b878ccfa20d33216f\",\n \"content_id\": \"2aead024c4e8a4eab8f908f2cd3fff1180f09680\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 338,\n \"license_type\": \"no_license\",\n \"max_line_length\": 41,\n \"num_lines\": 16,\n \"path\": \"/알고리즘/온라인저지/2022/07/0704/반복.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"S = input()\\nalphabet = [chr(i+97) for i in range(26)]\\n# print(alphabet)\\nresult = 0\\nword = ''\\ns = 0 # S index\\nwhile True:\\n result += 1\\n for a in alphabet:\\n if a == S[s]:\\n word += a\\n if word == S:\\n print(result)\\n exit()\\n s += 1\\n # print(result, word, s)\"\n },\n {\n \"alpha_fraction\": 0.3913043439388275,\n \"alphanum_fraction\": 0.52173912525177,\n \"avg_line_length\": 22.33333396911621,\n \"blob_id\": \"e4e29cb33bbfdd75c644b62ff6fc30f8b551ee6b\",\n \"content_id\": \"431dfd8828cc7c33898ef962f514d28a5a79e3f8\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 69,\n \"license_type\": \"no_license\",\n \"max_line_length\": 33,\n \"num_lines\": 3,\n \"path\": \"/알고리즘/온라인저지/2022/04/0418/수학은 체육과목 입니다 2.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = int(input())\\nfinger = [2, 1, 2, 3, 4, 5, 4, 3]\\nprint(finger[N%8])\"\n },\n {\n \"alpha_fraction\": 0.5177664756774902,\n \"alphanum_fraction\": 0.6142131686210632,\n \"avg_line_length\": 16.954545974731445,\n \"blob_id\": \"fcd61c19e56c5cfef43e1661a35d062b4416afb9\",\n \"content_id\": \"7cb84463704f7d999efb4317c887bda85caae2ad\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 506,\n \"license_type\": \"no_license\",\n \"max_line_length\": 45,\n \"num_lines\": 22,\n \"path\": \"/알고리즘/온라인저지/2022/10/1003/피보나치 수의 확장.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\nmod = int(1e9)\\n\\nN = int(input().rstrip())\\na, b = 1, 1\\nfor _ in range(abs(N)-2): a, b = b, (a+b)%mod\\nif abs(N)%2 == 0 and N < 0: print(-1)\\nelif N == 0: print(0)\\nelse: print(1)\\nprint(b if N != 0 else 0)\\n\\n\\\"\\\"\\\"\\n문제를 잘 보자\\n1,000,000,007로 나누는 문제가 많았다고 해서\\n모든 문제들이 그런 것은 아니다\\n1,000,000,000으로 나누면 되는걸로 \\n문제 제대로 안읽고 몇분을 날린거냐..\\n\\\"\\\"\\\"\\n\\n# https://www.acmicpc.net/problem/1788\"\n },\n {\n \"alpha_fraction\": 0.37172773480415344,\n \"alphanum_fraction\": 0.39921465516090393,\n \"avg_line_length\": 17.658536911010742,\n \"blob_id\": \"e340b6f4c49aeea2871780825f7af9074cef35c7\",\n \"content_id\": \"fed5d49d327fe124e15ad8be28c4c1643b408be6\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 764,\n \"license_type\": \"no_license\",\n \"max_line_length\": 31,\n \"num_lines\": 41,\n \"path\": \"/알고리즘/온라인저지/2021/09/0908/큐 2.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\ndef input():\\n return sys.stdin.readline()\\n\\n\\n\\nN = int(input())\\nq = [0] * N\\npnt = 0\\ncnt = 0\\nback = 0\\nfor n in range(N):\\n order = input().split()\\n if order[0] == 'push':\\n q[back] = order[1]\\n cnt += 1\\n back += 1\\n elif order[0] == 'pop':\\n if cnt:\\n print(q[pnt])\\n pnt += 1\\n cnt -= 1\\n else:\\n print(-1)\\n elif order[0] == 'size':\\n print(cnt)\\n elif order[0] == 'empty':\\n if cnt:\\n print(0)\\n else:\\n print(1)\\n elif order[0] == 'front':\\n if cnt:\\n print(q[pnt])\\n else:\\n print(-1)\\n elif order[0] == 'back':\\n if cnt:\\n print(q[back-1])\\n else:\\n print(-1)\"\n },\n {\n \"alpha_fraction\": 0.4285714328289032,\n \"alphanum_fraction\": 0.4444444477558136,\n \"avg_line_length\": 18,\n \"blob_id\": \"cafc1e157af92c1dfa09543d90da7dd236ab9fe4\",\n \"content_id\": \"cd06dd07209eb7039f52d94eb25d08722ea5524d\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 189,\n \"license_type\": \"no_license\",\n \"max_line_length\": 37,\n \"num_lines\": 10,\n \"path\": \"/알고리즘/온라인저지/2022/02/0207/이진수.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"T = int(input())\\n\\nfor t in range(T):\\n N = int(input())\\n\\n binary = (str(bin(N))[::-1])[:-2]\\n\\n for i in range(len(binary)):\\n if binary[i] == '1':\\n print(i, end=' ')\"\n },\n {\n \"alpha_fraction\": 0.5568862557411194,\n \"alphanum_fraction\": 0.5868263244628906,\n \"avg_line_length\": 32.599998474121094,\n \"blob_id\": \"ea688bd50e5b123fa479f656e198dbb9129ef58f\",\n \"content_id\": \"c49fc1d3f2971dc6dad6541ce95840b93d96734b\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 167,\n \"license_type\": \"no_license\",\n \"max_line_length\": 43,\n \"num_lines\": 5,\n \"path\": \"/알고리즘/온라인저지/2022/09/0905/빵.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"result = int(1e9)\\nfor _ in range(int(input())):\\n A, B = map(int, input().split())\\n if A <= B: result = min(result, B)\\nprint(-1 if result == int(1e9) else result)\"\n },\n {\n \"alpha_fraction\": 0.46084338426589966,\n \"alphanum_fraction\": 0.5391566157341003,\n \"avg_line_length\": 25.600000381469727,\n \"blob_id\": \"ce1ce4897f4ab2d1f79e8a958dda10859bdbc402\",\n \"content_id\": \"f62084d06d58623937723983c29c98cbc9a6d6ee\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 664,\n \"license_type\": \"no_license\",\n \"max_line_length\": 52,\n \"num_lines\": 25,\n \"path\": \"/알고리즘/온라인저지/2022/09/0922/주사위 네개.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\n\\nresult = 0\\nfor _ in range(int(input().rstrip())):\\n dices = list(map(int, input().rstrip().split()))\\n count_arr = [0]*11\\n for dice in dices: count_arr[dice] += 1\\n tmp = 0\\n if 4 in count_arr:\\n tmp += 50000 + count_arr.index(4)*5000\\n elif 3 in count_arr:\\n tmp += 10000 + count_arr.index(3)*1000\\n elif count_arr.count(2) == 2:\\n tmp += 2000\\n for i in range(11):\\n if count_arr[i] == 2: \\n tmp += i*500\\n elif 2 in count_arr:\\n tmp += 1000 + count_arr.index(2)*100\\n else: \\n tmp += max(dices)*100\\n result = max(result, tmp)\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.4392419159412384,\n \"alphanum_fraction\": 0.47380155324935913,\n \"avg_line_length\": 27.90322494506836,\n \"blob_id\": \"911187260355f4ee89b7ee384980b118d7fc96eb\",\n \"content_id\": \"46add3df2b8269ea76ee904ac864095dec6072ec\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1257,\n \"license_type\": \"no_license\",\n \"max_line_length\": 70,\n \"num_lines\": 31,\n \"path\": \"/알고리즘/온라인저지/2021/08/0816/소수&팰린드롬.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"\\\"\\\"\\\"\\nN보다 큰 수를 하나씩 올려가면서\\n소수들로 나눠서 나머지가 있으면서 소수본인과 같아지면 소수\\n2~N까지의 소수들을 먼저 리스트에 추가\\nN+1이 소수인지 보고 소수이면 리스트에 추가\\n소수일 때 팰린드롬인지 보고\\n팰린드롬이면 출력\\n\\\"\\\"\\\"\\nimport sys\\nN = int(sys.stdin.readline())\\n\\n # 1003001까지 에라토스테네스의 체로 소수 전부 골라내기\\nn = 1003003 # 조금 편법이긴 한데\\n # 최대값이 1003001이라는 걸 계산해서 먼저 알아냄\\na = [False,False] + [True]*(n-1)\\nprimes=[]\\nfor i in range(2,n+1):\\n if a[i]:\\n primes.append(i)\\n for j in range(2*i, n+1, i):\\n a[j] = False\\n\\nprime_palindrome = 0 # 소수팰린드롬 초기값\\nwhile True:\\n if str(N) == str(N)[::-1]: # 팰린드롬이고\\n if N in primes: # 소수이면\\n prime_palindrome = N # 소수팰린드롬\\n if prime_palindrome: # 값을 찾았다면\\n print(prime_palindrome) # 출력하고\\n break # while문 종료\\n N += 1 # 다음 숫자 탐색\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.6336206793785095,\n \"alphanum_fraction\": 0.6336206793785095,\n \"avg_line_length\": 22.299999237060547,\n \"blob_id\": \"edd95ff0cbaec0c87f19f1db698602338d2d9085\",\n \"content_id\": \"e58b68684eb8a8014addfd54d13b2a4f2291b5ad\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 232,\n \"license_type\": \"no_license\",\n \"max_line_length\": 47,\n \"num_lines\": 10,\n \"path\": \"/알고리즘/온라인저지/2022/10/1001/비밀번호 찾기.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\n\\nN, M = map(int, input().rstrip().split())\\ndct = dict()\\nfor n in range(N):\\n site, password = input().rstrip().split()\\n dct[site] = password\\nfor m in range(M): print(dct[input().rstrip()])\"\n },\n {\n \"alpha_fraction\": 0.4627249240875244,\n \"alphanum_fraction\": 0.519280195236206,\n \"avg_line_length\": 15.956521987915039,\n \"blob_id\": \"ead0b7748c82b654bfd944226466a9213ff92c62\",\n \"content_id\": \"d9d50c1624f805552b25f2227184c45e102a9327\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 389,\n \"license_type\": \"no_license\",\n \"max_line_length\": 41,\n \"num_lines\": 23,\n \"path\": \"/알고리즘/온라인저지/2023/02/0219/8진수, 10진수, 16진수.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"def base_change(num, base):\\n base_str = '0123456789abcdef'\\n answer = 0\\n power = 1\\n\\n for n in num[::-1]:\\n answer += power*base_str.index(n)\\n power *= base\\n\\n return answer\\n\\nX = input()\\nresult = 0\\n\\nif X[0] == '0':\\n if X[1] == 'x':\\n result = base_change(X[2:], 16)\\n else:\\n result = base_change(X[1:], 8)\\nelse:\\n result = int(X)\\n\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.5263158082962036,\n \"alphanum_fraction\": 0.5413534045219421,\n \"avg_line_length\": 12.399999618530273,\n \"blob_id\": \"ef58bb5673ede891532858bcfb1d6a7c7ad68168\",\n \"content_id\": \"1fc003976a6a36c30f10d9988ef4ab27d8e8b564\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 133,\n \"license_type\": \"no_license\",\n \"max_line_length\": 38,\n \"num_lines\": 10,\n \"path\": \"/알고리즘/온라인저지/2022/02/0201/10부제.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"D = int(input())\\ncars = list(map(int, input().split()))\\n\\nresult = 0\\n\\nfor c in cars:\\n if c == D:\\n result += 1\\n\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.34730538725852966,\n \"alphanum_fraction\": 0.371257483959198,\n \"avg_line_length\": 14.272727012634277,\n \"blob_id\": \"fa1f12abc76025fb3a0ed5bf32cedfa84201022e\",\n \"content_id\": \"74bf51922582febe29cb9bcbe4d7cf6f3c45bb02\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 167,\n \"license_type\": \"no_license\",\n \"max_line_length\": 39,\n \"num_lines\": 11,\n \"path\": \"/알고리즘/온라인저지/2022/02/0201/별 찍기 - 12.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = int(input())\\n\\ni = 0\\n\\nfor n in range(N):\\n i += 1\\n print(' ' * (N-i), '*' * i, sep='')\\n\\nfor n in range(N-1):\\n i -= 1\\n print(' ' * (N-i), '*' * i, sep='')\"\n },\n {\n \"alpha_fraction\": 0.3888888955116272,\n \"alphanum_fraction\": 0.41777777671813965,\n \"avg_line_length\": 12.636363983154297,\n \"blob_id\": \"97790eb978067567390ed0b644fce974bda74e98\",\n \"content_id\": \"b10183d82a7868d41708f850016ec836892b272f\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 450,\n \"license_type\": \"no_license\",\n \"max_line_length\": 49,\n \"num_lines\": 33,\n \"path\": \"/알고리즘/온라인저지/2022/02/0221/DNA.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N, M = map(int, input().split())\\n\\nDNAs = [input() for _ in range(N)]\\n\\ndictt = {\\n 'A': 0,\\n 'C': 1,\\n 'G': 2,\\n 'T': 3,\\n 0: 'A',\\n 1: 'C',\\n 2: 'G',\\n 3: 'T',\\n}\\n\\nHD = 0\\n\\nfor i in range(M):\\n\\n table = [0] * 4\\n\\n for d in DNAs:\\n table[dictt[d[i]]] += 1\\n \\n for j in range(4):\\n if j != table.index(max(table)):\\n HD += table[j]\\n\\n print(dictt[table.index(max(table))], end='')\\n\\nprint()\\n\\nprint(HD)\\n\"\n },\n {\n \"alpha_fraction\": 0.4709418714046478,\n \"alphanum_fraction\": 0.4809619188308716,\n \"avg_line_length\": 30.25,\n \"blob_id\": \"78f02a057dbe3aa4527c60b65603a00c70e262ea\",\n \"content_id\": \"b748efd8c15369276385a8033a42915cb3265835\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 703,\n \"license_type\": \"no_license\",\n \"max_line_length\": 48,\n \"num_lines\": 16,\n \"path\": \"/알고리즘/온라인저지/2022/04/0417/그룹 단어 체커.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = int(input())\\nresult = 0 # 그룹단어개수 초기화\\nfor n in range(N):\\n word = input()\\n char = [] # 사용한 글자\\n for i in range(len(word)): # 단어를 순회하면서\\n if word[i] not in char: # 사용한 적 없는 글자라면\\n char.append(word[i]) # 사용한 글자에 추가\\n else: # 사용한 적 있는 글자라면\\n if word[i] != word[i-1]: # 앞글자와 다르다면\\n result -= 1 # 그룹단어가 아닙니다\\n # 매 케이스 그룹단어라고 가정하고\\n # 그룹단어가 아닐 경우 -1 하였음\\n break\\n result += 1 # 그룹단어입니다!\\nprint(result) # 출력\"\n },\n {\n \"alpha_fraction\": 0.5698529481887817,\n \"alphanum_fraction\": 0.5698529481887817,\n \"avg_line_length\": 23.81818199157715,\n \"blob_id\": \"876d6bf33832bd19f360b42f30f25c95e290c899\",\n \"content_id\": \"b189945214f5559c580b9a37361816a49aa12c80\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 310,\n \"license_type\": \"no_license\",\n \"max_line_length\": 89,\n \"num_lines\": 11,\n \"path\": \"/알고리즘/온라인저지/2022/12/1211/한국이 그리울 땐 서버에 접속하지.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = int(input())\\nstart, end = input().split('*')\\nfor n in range(N):\\n file = input()\\n if len(start) + len(end) > len(file): print('NE')\\n else: print('DA' if start == file[:len(start)] and end == file[-len(end):] else 'NE')\\n\\n\\\"\\\"\\\"\\nabc*def\\n와 같은 경우가 테스트케이스에 포함되어 있음\\n\\\"\\\"\\\"\"\n },\n {\n \"alpha_fraction\": 0.5026881694793701,\n \"alphanum_fraction\": 0.5188171863555908,\n \"avg_line_length\": 15,\n \"blob_id\": \"a58fe6e007d81533895bf19a6e6781413c0fcce6\",\n \"content_id\": \"f0ffff53cae92d33fede0762006c960a38867b88\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 478,\n \"license_type\": \"no_license\",\n \"max_line_length\": 38,\n \"num_lines\": 23,\n \"path\": \"/알고리즘/온라인저지/2022/01/0122/꿀 아르바이트.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N, M = map(int, input().split())\\n\\n# 급여 정보 입력\\npays = list(map(int, input().split()))\\n\\ns = 0 # 창문의 시작과\\ne = M-1 # 끝\\n\\n# 결과값과 윈도우값 초기화\\nresult = window = sum(pays[s:e+1])\\n\\nwhile e < N-1: # 윈도우 이동을 종료하는 조건\\n # 윈도우 한 칸 이동~~\\n window -= pays[s]\\n s += 1\\n e += 1\\n window += pays[e]\\n\\n # 결과값을 갱신할 지 여부\\n if window > result:\\n result = window\\n\\nprint(result)\\n \"\n },\n {\n \"alpha_fraction\": 0.4035087823867798,\n \"alphanum_fraction\": 0.46929824352264404,\n \"avg_line_length\": 14.266666412353516,\n \"blob_id\": \"731e667936da3095cd52640ed7179775635e5944\",\n \"content_id\": \"7d06fc54a223537fc4fad4b9b2f1f203f5cd14bd\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 228,\n \"license_type\": \"no_license\",\n \"max_line_length\": 31,\n \"num_lines\": 15,\n \"path\": \"/알고리즘/온라인저지/2021/09/0906/막대기.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\ndef input():\\n return sys.stdin.readline()\\n\\nX = int(input())\\nbars = [64, 32, 16, 8, 4, 2, 1]\\ni = 0\\ncnt = 0\\nwhile X != 0:\\n if X >= bars[i]:\\n X -= bars[i]\\n cnt += 1\\n else:\\n i += 1\\nprint(cnt)\"\n },\n {\n \"alpha_fraction\": 0.4975247383117676,\n \"alphanum_fraction\": 0.5272276997566223,\n \"avg_line_length\": 14.576923370361328,\n \"blob_id\": \"dfc24364b20040990949308aa5852bae807e5b3f\",\n \"content_id\": \"6c52305f42e3332124184c50bb3f70abbe46c86e\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 404,\n \"license_type\": \"no_license\",\n \"max_line_length\": 36,\n \"num_lines\": 26,\n \"path\": \"/알고리즘/온라인저지/2021/12/1230/트리의 부모 찾기.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\nsys.setrecursionlimit(99999)\\n\\ndef dfs(i):\\n for n in nodes[i]:\\n if not parent[n]:\\n parent[n] = i\\n dfs(n)\\n\\nN = int(input())\\n\\nnodes = [[] for _ in range(N+1)]\\n\\nparent = [0 for _ in range(N+1)]\\nparent[1] = 'root'\\n\\nfor n in range(N-1):\\n a, b = map(int, input().split())\\n \\n nodes[a].append(b)\\n nodes[b].append(a)\\n\\ndfs(1)\\n\\nfor p in parent[2:]:\\n print(p)\"\n },\n {\n \"alpha_fraction\": 0.5570470094680786,\n \"alphanum_fraction\": 0.5682326555252075,\n \"avg_line_length\": 23.88888931274414,\n \"blob_id\": \"a276d39976f25f1f7cb350cfb30af811b9325068\",\n \"content_id\": \"f7d805244a527024269a754658618f2f8ea33651\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 447,\n \"license_type\": \"no_license\",\n \"max_line_length\": 47,\n \"num_lines\": 18,\n \"path\": \"/알고리즘/온라인저지/2022/10/1019/풍선 터뜨리기.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\nfrom collections import deque\\n\\ninput = sys.stdin.readline\\nN = int(input().rstrip())\\narr = list(map(int, input().rstrip().split()))\\nQ = deque()\\nfor i in range(1, N+1): Q.append((i, arr[i-1]))\\nwhile True:\\n idx, move = Q.popleft()\\n print(idx, end=' ')\\n if not Q: break\\n if move > 0:\\n for i in range(move-1):\\n Q.append(Q.popleft())\\n else:\\n for i in range(abs(move)):\\n Q.appendleft(Q.pop())\"\n },\n {\n \"alpha_fraction\": 0.31734317541122437,\n \"alphanum_fraction\": 0.361623615026474,\n \"avg_line_length\": 37.85714340209961,\n \"blob_id\": \"f5495119abf703f7eeee40c46ac4ad3355f0cd7f\",\n \"content_id\": \"752ef90d9e2a0c5b37c24f7ab61da0c6f0e552f0\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 271,\n \"license_type\": \"no_license\",\n \"max_line_length\": 78,\n \"num_lines\": 7,\n \"path\": \"/알고리즘/온라인저지/2022/12/1217/완전 세제곱.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"for a in range(1, 101):\\n for b in range(2, a+1):\\n for c in range(b, a+1):\\n for d in range(c, a+1):\\n tmp = b**3 + c**3 + d**3\\n if a**3 == tmp:\\n print('Cube = {}, Triple = ({},{},{})'.format(a, b, c, d))\"\n },\n {\n \"alpha_fraction\": 0.443113774061203,\n \"alphanum_fraction\": 0.455089807510376,\n \"avg_line_length\": 17.66666603088379,\n \"blob_id\": \"8df5848801d4997d502a09fcfbe63e978e101da0\",\n \"content_id\": \"e5133575edc97696fb8e657da5e632335f7e3f2c\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 167,\n \"license_type\": \"no_license\",\n \"max_line_length\": 29,\n \"num_lines\": 9,\n \"path\": \"/알고리즘/온라인저지/2022/07/0711/모음의 개수.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"while True:\\n sen = input()\\n if sen == '#':\\n break\\n result = 0\\n for s in sen:\\n if s in 'aeiouAEIOU':\\n result += 1\\n print(result)\"\n },\n {\n \"alpha_fraction\": 0.5526315569877625,\n \"alphanum_fraction\": 0.5614035129547119,\n \"avg_line_length\": 37.33333206176758,\n \"blob_id\": \"cf0097bc7b5b4c37e402f2f46887d6aaa5d959d7\",\n \"content_id\": \"a20b7ae9ad16b39980cec2fcbcb4594378be7714\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 114,\n \"license_type\": \"no_license\",\n \"max_line_length\": 48,\n \"num_lines\": 3,\n \"path\": \"/알고리즘/온라인저지/2022/10/1012/팰린드롬.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"for i in range(int(input().rstrip())):\\n word = input().lower()\\n print('Yes' if word == word[::-1] else 'No')\"\n },\n {\n \"alpha_fraction\": 0.38063910603523254,\n \"alphanum_fraction\": 0.4530075192451477,\n \"avg_line_length\": 18.72222137451172,\n \"blob_id\": \"0e25e4efe8363e8e2295cce1c75e8b2dfc442a42\",\n \"content_id\": \"e32a895d2dd5d59808111c94f030a3faf7b8c1a4\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1064,\n \"license_type\": \"no_license\",\n \"max_line_length\": 48,\n \"num_lines\": 54,\n \"path\": \"/알고리즘/온라인저지/2022/03/0314/구간 합 구하기 5.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\ndef input():\\n return sys.stdin.readline()\\n\\nN, M = map(int, input().split())\\n\\narr = []\\n\\ntmp = list(map(int, input().split()))\\nnum = 0\\nline = []\\nfor t in tmp:\\n num += t\\n line.append(num)\\narr.append(line)\\n\\nfor n in range(1, N):\\n tmp = list(map(int, input().split()))\\n num = 0\\n line = []\\n for t in tmp:\\n num += t\\n line.append(num)\\n for i in range(len(line)):\\n line[i] += arr[-1][i]\\n arr.append(line)\\n \\n\\nfor m in range(M):\\n y1, x1, y2, x2 = (map(int, input().split()))\\n e = v = h = s = 0\\n if x1 > 1 and y1 > 1 and x2 > 1 and y2 > 1:\\n e = arr[y2-1][x2-1]\\n v = arr[y2-1][x1-2]\\n h = arr[y1-2][x2-1]\\n s = arr[y1-2][x1-2]\\n elif x1 == 1 and y1 > 1:\\n e = arr[y2-1][x2-1]\\n h = arr[y1-2][x2-1]\\n elif y1 == 1 and x1 > 1:\\n e = arr[y2-1][x2-1]\\n v = arr[y2-1][x1-2]\\n elif x1 == 1 and y1 == 1:\\n e = arr[y2-1][x2-1]\\n\\n result = e - v - h + s\\n print(result)\\n\\n# for a in arr:\\n# print(*a)\\n\\n\\\"\\\"\\\"\\n2 2 3 4 = [3][4]-[3][1]-[1][4]+[1][1]\\n\\\"\\\"\\\"\"\n },\n {\n \"alpha_fraction\": 0.5176848769187927,\n \"alphanum_fraction\": 0.5562701225280762,\n \"avg_line_length\": 25,\n \"blob_id\": \"e65f38fbd9690cfda2b93a5c0291c17f365b97e4\",\n \"content_id\": \"6787ada15675778039e888a163929f50f3488770\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 311,\n \"license_type\": \"no_license\",\n \"max_line_length\": 44,\n \"num_lines\": 12,\n \"path\": \"/알고리즘/온라인저지/2022/09/0921/Strfry.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\n\\nfor _ in range(int(input().rstrip())):\\n A, B = input().rstrip().split()\\n A_arr, B_arr = [0]*26, [0]*26\\n for a in A: A_arr[ord(a)-97] += 1\\n for b in B: B_arr[ord(b)-97] += 1\\n result = 'Possible'\\n if A_arr != B_arr: result = 'Impossible'\\n print(result)\"\n },\n {\n \"alpha_fraction\": 0.53665691614151,\n \"alphanum_fraction\": 0.5601173043251038,\n \"avg_line_length\": 37,\n \"blob_id\": \"77d11479a7e502a243fdf9787b7cbb5e533f8ad6\",\n \"content_id\": \"cc266ae202472bc8d2cbe517a808d6ff8752833b\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 491,\n \"license_type\": \"no_license\",\n \"max_line_length\": 55,\n \"num_lines\": 9,\n \"path\": \"/알고리즘/온라인저지/2021/08/0803/알파벳 찾기.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"S = input() # 단어를 입력받아서\\nresult = [-1] * 26 # 결과값을 -1 26개로 초기화해주고 \\nfor s in S: # 알파벳을 순회하면서 \\n for i in range(len(result)): # 그리고 result를 순회하면서\\n if s == chr(97+i): # 단어의 해당 알파벳을 확인해서\\n result[i] = S.index(s) # 알파벳의 index값의 등장위치를\\n # result에 추가하고\\nfor res in result: # result를 순회하면서\\n print(res, end=' ') # 출력\"\n },\n {\n \"alpha_fraction\": 0.5102040767669678,\n \"alphanum_fraction\": 0.5357142686843872,\n \"avg_line_length\": 11.25,\n \"blob_id\": \"ee5bed4c5eb165e57971ec392f5a481eb3a411d6\",\n \"content_id\": \"04750b58f2dbd4988bedfd1475b1146ad8047f90\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 196,\n \"license_type\": \"no_license\",\n \"max_line_length\": 40,\n \"num_lines\": 16,\n \"path\": \"/알고리즘/온라인저지/2022/02/0220/피시방 알바.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = int(input())\\n\\nguests = list(map(int, input().split()))\\n\\npcs = [False] * 101\\n\\nreject = 0\\n\\nfor g in guests:\\n if pcs[g]:\\n reject += 1\\n continue\\n\\n pcs[g] = True\\n\\nprint(reject)\\n\"\n },\n {\n \"alpha_fraction\": 0.5555555820465088,\n \"alphanum_fraction\": 0.5737977027893066,\n \"avg_line_length\": 21.370370864868164,\n \"blob_id\": \"3aa0b157feba509d13593ec442a3f0a1120708b7\",\n \"content_id\": \"14dcec6eb299a8565b7ffedbb04050c1a52aec5b\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 603,\n \"license_type\": \"no_license\",\n \"max_line_length\": 47,\n \"num_lines\": 27,\n \"path\": \"/알고리즘/온라인저지/2022/09/0917/용돈 관리.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\n\\ndef enough(money):\\n money_in_hand, draw = money, 1\\n for a in arr:\\n if money_in_hand>=a: money_in_hand -= a\\n else:\\n draw += 1\\n money_in_hand = money-a\\n if draw<=M: return True\\n return False\\n\\nN, M = map(int, input().rstrip().split())\\narr = [int(input()) for _ in range(N)]\\nresult = int(1e9)\\nstart, end = max(arr), result\\nwhile start<=end:\\n mid = (start+end) // 2\\n if enough(mid):\\n result = min(result, mid)\\n end = mid-1\\n else: start = mid+1\\nprint(result)\\n\\n# https://www.acmicpc.net/problem/6236\"\n },\n {\n \"alpha_fraction\": 0.6372548937797546,\n \"alphanum_fraction\": 0.656862735748291,\n \"avg_line_length\": 16.16666603088379,\n \"blob_id\": \"ad9d2e348d26e99c2964776d3a330317e07fa066\",\n \"content_id\": \"60fcdfff9c999eeac678da7683d124d08494e230\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 102,\n \"license_type\": \"no_license\",\n \"max_line_length\": 42,\n \"num_lines\": 6,\n \"path\": \"/알고리즘/온라인저지/2022/02/0211/오늘의 날짜는.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from datetime import datetime\\n\\ndate = str(datetime.now())[:10].split('-')\\n\\nfor d in date:\\n print(d)\"\n },\n {\n \"alpha_fraction\": 0.3861386179924011,\n \"alphanum_fraction\": 0.4297029674053192,\n \"avg_line_length\": 17.740739822387695,\n \"blob_id\": \"237cd94ecbfcdb7acba5e8c22074618f024f8c98\",\n \"content_id\": \"8b9b6782af1a759626ac40a8d4784bc4dab41ec3\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 505,\n \"license_type\": \"no_license\",\n \"max_line_length\": 28,\n \"num_lines\": 27,\n \"path\": \"/알고리즘/온라인저지/2022/04/0404/아이 러브 크로아티아.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"K = int(input()) - 1\\nN = int(input())\\nquizs = []\\nfor n in range(N):\\n tmp = input().split()\\n tmp[0] = int(tmp[0])\\n quizs.append(tmp)\\n# print(quizs)\\ntime = 60*3 + 30\\n# print(time)\\ni = 0\\nwhile True:\\n now = quizs[i]\\n # print(now, time, K, i)\\n if time < now[0]:\\n break\\n if now[1] == 'T':\\n time -= now[0]\\n K = (K+1)%8\\n i += 1\\n elif now[1] == 'N':\\n time -= now[0]\\n i += 1 \\n elif now[1] == 'P':\\n time -= now[0]\\n i += 1\\nprint(K+1)\"\n },\n {\n \"alpha_fraction\": 0.5545454621315002,\n \"alphanum_fraction\": 0.5545454621315002,\n \"avg_line_length\": 30.571428298950195,\n \"blob_id\": \"211d86e78f4e1f1bc92a5868b29adb3dcb583806\",\n \"content_id\": \"51f6c1aa78f30a672a5be3798c8b5c4ef5609e18\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 220,\n \"license_type\": \"no_license\",\n \"max_line_length\": 42,\n \"num_lines\": 7,\n \"path\": \"/알고리즘/온라인저지/2023/03/0327/괴짜 교수.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"for _ in range(int(input())):\\n D, N, S, P = map(int, input().split())\\n A, B = D+N*P, N*S\\n result = 'does not matter'\\n if A<B: result = 'parallelize'\\n if A>B: result = 'do not parallelize'\\n print(result)\"\n },\n {\n \"alpha_fraction\": 0.5151515007019043,\n \"alphanum_fraction\": 0.5151515007019043,\n \"avg_line_length\": 15.75,\n \"blob_id\": \"8a8da07e571193661d5dcea8ed38ba04400cbdf8\",\n \"content_id\": \"02035e789f62d80421f18ce75f29b2edb1af61aa\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 66,\n \"license_type\": \"no_license\",\n \"max_line_length\": 29,\n \"num_lines\": 4,\n \"path\": \"/알고리즘/온라인저지/2022/02/0209/히스토그램.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = int(input())\\n\\nfor n in range(N):\\n print('=' * int(input()))\"\n },\n {\n \"alpha_fraction\": 0.36320754885673523,\n \"alphanum_fraction\": 0.4292452931404114,\n \"avg_line_length\": 13.199999809265137,\n \"blob_id\": \"ef278bff20b1a99e35c9abbaa5765fb6fe82c181\",\n \"content_id\": \"192675d650ffbeae1bb90c1f6229e64b7f5d76f7\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 212,\n \"license_type\": \"no_license\",\n \"max_line_length\": 29,\n \"num_lines\": 15,\n \"path\": \"/알고리즘/온라인저지/2022/02/0201/피보나치 함수.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"T = int(input())\\n\\ndp = [0] * 42\\ndp[1] = 1\\n\\nfor i in range(2, 42):\\n dp[i] = dp[i-1] + dp[i-2]\\n\\nfor t in range(T):\\n N = int(input())\\n\\n if N == 0:\\n print(1, 0)\\n else:\\n print(dp[N-1], dp[N])\"\n },\n {\n \"alpha_fraction\": 0.5956678986549377,\n \"alphanum_fraction\": 0.6028881072998047,\n \"avg_line_length\": 20.384614944458008,\n \"blob_id\": \"c6d4e0b4a532ade93e734ebee0e2a197a5e5135c\",\n \"content_id\": \"a72d35502117d19686fc67c5b94014ccbd763244\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 277,\n \"license_type\": \"no_license\",\n \"max_line_length\": 47,\n \"num_lines\": 13,\n \"path\": \"/알고리즘/온라인저지/2022/11/1111/배수들의 합.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\n\\nN, M = map(int, input().rstrip().split())\\nnums = list(map(int, input().rstrip().split()))\\nsett = set()\\nresult = 0\\nfor num in nums:\\n for i in range(num, N+1, num):\\n if i not in sett: result += i\\n sett.add(i)\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.313296914100647,\n \"alphanum_fraction\": 0.32058286666870117,\n \"avg_line_length\": 21.91666603088379,\n \"blob_id\": \"6e1be4c8813a001daadec17f8355817ee49423f6\",\n \"content_id\": \"05a617a39923b2a4d6310a7b273db2a71a63217d\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 549,\n \"license_type\": \"no_license\",\n \"max_line_length\": 37,\n \"num_lines\": 24,\n \"path\": \"/알고리즘/온라인저지/2021/08/0822/괄호.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"T = int(input())\\nfor tc in range(T):\\n data = input()\\n stack = []\\n top = -1\\n for dt in data:\\n if dt == '(':\\n stack.append(dt)\\n top += 1\\n else: # dt == ')'\\n if top == -1:\\n stack.append(dt)\\n break\\n else:\\n if stack[top] == '(':\\n stack.pop()\\n top -= 1\\n else:\\n stack.append(dt)\\n break\\n if stack:\\n print('NO')\\n else:\\n print('YES')\"\n },\n {\n \"alpha_fraction\": 0.5096153616905212,\n \"alphanum_fraction\": 0.5480769276618958,\n \"avg_line_length\": 16.38888931274414,\n \"blob_id\": \"d42a9915354997ce3c8d9c648b3ddb8ca79d2b7b\",\n \"content_id\": \"8f59ecb6a68b6a8c02160211d2f3420ed86a7576\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 354,\n \"license_type\": \"no_license\",\n \"max_line_length\": 42,\n \"num_lines\": 18,\n \"path\": \"/알고리즘/온라인저지/2023/03/0326/금민수의 개수.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from collections import deque\\n\\nA,B = map(int,input().split())\\nQ = deque()\\n\\nQ.append(4); Q.append(7)\\nresult = 0\\n\\nwhile Q:\\n GMS = Q.popleft()\\n\\n if GMS<=B:\\n if A<=GMS: \\n result += 1 # A이상 B이하 만족하는 금민수\\n Q.append(GMS*10+4) # 다음 금민수 1\\n Q.append(GMS*10+7) # 다음 금민수 2\\n\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.39759036898612976,\n \"alphanum_fraction\": 0.4337349534034729,\n \"avg_line_length\": 14.625,\n \"blob_id\": \"b1ac4fb8c1c3e635a1615fcd77a3d6d72d7466e7\",\n \"content_id\": \"230aabb1b98e1773972cbf8d079bca7dd31cc490\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 249,\n \"license_type\": \"no_license\",\n \"max_line_length\": 31,\n \"num_lines\": 16,\n \"path\": \"/알고리즘/온라인저지/2021/09/0906/거스름돈.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\ndef input():\\n return sys.stdin.readline()\\n\\nN = int(input())\\ncnt = 0\\nif N == 1 or N == 3:\\n print(-1)\\nelse:\\n while N != 0:\\n if not N%5:\\n cnt += N//5\\n break\\n N -= 2\\n cnt += 1\\n print(cnt)\"\n },\n {\n \"alpha_fraction\": 0.4655172526836395,\n \"alphanum_fraction\": 0.49425286054611206,\n \"avg_line_length\": 16.5,\n \"blob_id\": \"ef44730a6e825965bf6a70a994445d638a33d973\",\n \"content_id\": \"c7c22e7e17a745e975864adf2b6f7e480abcf027\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 174,\n \"license_type\": \"no_license\",\n \"max_line_length\": 38,\n \"num_lines\": 10,\n \"path\": \"/알고리즘/온라인저지/2022/04/0401/우유 축제.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = int(input())\\nmilk = list(map(int, input().split()))\\nnow = 0\\nresult = 0\\nfor m in milk:\\n if now == m:\\n result += 1\\n now += 1\\n now %= 3\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.4915824830532074,\n \"alphanum_fraction\": 0.5101010203361511,\n \"avg_line_length\": 19.517240524291992,\n \"blob_id\": \"49b59ca4b16429f84722a1f535455d94df3095ef\",\n \"content_id\": \"00389b8c30972f0811c7a7aa92344f451d6db60a\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 594,\n \"license_type\": \"no_license\",\n \"max_line_length\": 39,\n \"num_lines\": 29,\n \"path\": \"/알고리즘/온라인저지/2023/01/0122/2진수 뒤집기.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"def dec_to_bin(number):\\n # number : str\\n dividor = 1\\n number = int(number)\\n while dividor*2 <= number:\\n dividor *= 2\\n answer = ''\\n while dividor >= 1:\\n if number >= dividor:\\n answer += '1'\\n number -= dividor\\n else:\\n answer += '0'\\n dividor //= 2\\n return answer\\n\\ndef bin_to_dec(number):\\n # number : str\\n multiplier = 1\\n answer = 0\\n for num in number:\\n answer += int(num) * multiplier\\n multiplier *= 2\\n return answer\\n\\nN = input()\\nN = dec_to_bin(N).rstrip('0')\\nN = bin_to_dec(N)\\nprint(N)\"\n },\n {\n \"alpha_fraction\": 0.5082873106002808,\n \"alphanum_fraction\": 0.5368323922157288,\n \"avg_line_length\": 26.174999237060547,\n \"blob_id\": \"06e3eaa0a8dc6d945419d2236d82add3a6697d12\",\n \"content_id\": \"c636a37faf7d85eb9c896a7ed762a393d8cab5de\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1456,\n \"license_type\": \"no_license\",\n \"max_line_length\": 73,\n \"num_lines\": 40,\n \"path\": \"/알고리즘/온라인저지/2022/04/0410/수강변경.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# N = int(input())\\n# student = []\\n# for i in list(map(int, input().split())):\\n# student.append([i])\\n# j = 0\\n# for i in list(map(int, input().split())):\\n# student[j].append(i)\\n# j += 1\\n# for i in range(N):\\n# for j in range(i, N):\\n# if student[i][1] == student[j][0]:\\n# student[i][0], student[j][0] = student[j][0], student[i][0]\\n# elif student[j][1] == student[i][0]:\\n# student[i][0], student[j][0] = student[j][0], student[i][0]\\n# result = 0\\n# for s in student:\\n# if s[0] != s[1]:\\n# result += 1\\n# print(result)\\n\\n\\\"\\\"\\\"\\n원하는 학생들끼리 일대일로 교환시켜주는 코드를 짰는데\\n시간초과가 나왔다\\n문제는 \\\"그래서 원하는 수업을 못 듣는 학생수는 몇명인가\\\" 였고\\n아래 코드를 통하여 해결하였다\\n\\\"\\\"\\\"\\n\\n# 핵심은 수업 교환횟수는 제한이 없고\\n# 학생들끼리 어떻게든 돌리고 돌리다 남는 학생의 수만 구하면 됨\\nN = int(input())\\ndp = [0] * 1000001 # 수업들 목록\\nfor i in list(map(int, input().split())):\\n dp[i] += 1 # 해당 수업을 신청하였음\\nresult = 0 # 원하는 수업을 듣지 못하는 학생 수\\nfor i in list(map(int, input().split())):\\n if dp[i] >= 1: # 그 수업을 들고 있는 사람이 있으면\\n dp[i] -= 1 # 교환\\n else: # 그 수업을 들고 있는 사람 자체가 없으면\\n result += 1 # 원하는 수업을 듣지 못하는 사람\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.4796747863292694,\n \"alphanum_fraction\": 0.4918699264526367,\n \"avg_line_length\": 16.64285659790039,\n \"blob_id\": \"aca21764521c939603241a122fe599f33e756abf\",\n \"content_id\": \"8772a3df5e1782533b44e07273bb323c585f0d44\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 246,\n \"license_type\": \"no_license\",\n \"max_line_length\": 31,\n \"num_lines\": 14,\n \"path\": \"/알고리즘/온라인저지/2022/04/0405/디지털 루트.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"def main(n):\\n tmp = 0\\n for i in str(n):\\n tmp += int(i)\\n return tmp\\n\\nwhile True:\\n N = int(input())\\n if N == 0:\\n break\\n result = main(N)\\n while len(str(result)) > 1:\\n result = main(result)\\n print(result)\"\n },\n {\n \"alpha_fraction\": 0.4733542203903198,\n \"alphanum_fraction\": 0.48275861144065857,\n \"avg_line_length\": 15.736842155456543,\n \"blob_id\": \"87fd7b5a35973a3fe7b6ae42598abd85cf4949fc\",\n \"content_id\": \"e3e915871481a660fbd27b3c6c716d08433936e7\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 319,\n \"license_type\": \"no_license\",\n \"max_line_length\": 47,\n \"num_lines\": 19,\n \"path\": \"/알고리즘/온라인저지/2022/02/0202/2차원 배열의 합.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N, M = map(int, input().split())\\n\\narr = []\\n\\nfor n in range(N):\\n arr.append(list(map(int, input().split())))\\n\\nK = int(input())\\n\\nfor k in range(K):\\n i, j, x, y = map(int, input().split())\\n\\n summ = 0\\n\\n for a in range(i-1, x):\\n for b in range(j-1, y):\\n summ += arr[a][b]\\n \\n print(summ)\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.4453125,\n \"alphanum_fraction\": 0.4453125,\n \"avg_line_length\": 17.428571701049805,\n \"blob_id\": \"159e1caf305a6e1e7ac1d804207a2159c9dbb0a6\",\n \"content_id\": \"8c0356e0f7129ee6d905cd4de47e22ea626faf80\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 132,\n \"license_type\": \"no_license\",\n \"max_line_length\": 29,\n \"num_lines\": 7,\n \"path\": \"/알고리즘/온라인저지/2023/03/0314/2루수 이름이 뭐야.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"print('뭐야', end='')\\nfor _ in range(int(input())):\\n if input() == 'anj':\\n print(';')\\n break\\nelse:\\n print('?')\"\n },\n {\n \"alpha_fraction\": 0.5604395866394043,\n \"alphanum_fraction\": 0.5769230723381042,\n \"avg_line_length\": 25.14285659790039,\n \"blob_id\": \"a41ccafb304aab9b23d0f28f1cb7ad82b6025807\",\n \"content_id\": \"9fb9fc4f8c9cc60618a6779fb14a664ee5e311dc\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 182,\n \"license_type\": \"no_license\",\n \"max_line_length\": 54,\n \"num_lines\": 7,\n \"path\": \"/알고리즘/온라인저지/2022/08/0827/Counting Antibodies.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"result = 0\\nfor _ in range(2):\\n tmp = 1\\n for i in list(map(int, input().split())): tmp *= i\\n result += tmp\\nfor i in list(map(int, input().split())): result *= i\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.5730336904525757,\n \"alphanum_fraction\": 0.584269642829895,\n \"avg_line_length\": 13.833333015441895,\n \"blob_id\": \"6eeac743e95bedb043d25a81531cc03fe37d9357\",\n \"content_id\": \"1fb43e2f270405a535fc7bd47548eff6e9397c95\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 113,\n \"license_type\": \"no_license\",\n \"max_line_length\": 40,\n \"num_lines\": 6,\n \"path\": \"/알고리즘/SWEA/LEARN/Course/1. Programming Beginner/파이썬 프로그래밍 기초(2)/37차시 4. 문자열 - 연습문제 1.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"tmp = input()\\n\\nprint(tmp)\\n\\nif tmp == tmp[::-1]:\\n print('입력하신 단어는 회문(Palindrome)입니다.')\\n\"\n },\n {\n \"alpha_fraction\": 0.4285714328289032,\n \"alphanum_fraction\": 0.4458874464035034,\n \"avg_line_length\": 15.571428298950195,\n \"blob_id\": \"5f08d2ce6443cdc7ec8ed0548c94cdf42a93c946\",\n \"content_id\": \"72080190fac9469bb52dd39aab646f9314f20edd\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 231,\n \"license_type\": \"no_license\",\n \"max_line_length\": 36,\n \"num_lines\": 14,\n \"path\": \"/알고리즘/온라인저지/2021/12/1216/배수와 약수.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"while True:\\n a, b = map(int, input().split())\\n\\n if a == 0 and b == 0:\\n break\\n\\n result = 'neither'\\n\\n if a % b == 0:\\n result = 'multiple'\\n elif b % a == 0:\\n result = 'factor'\\n \\n print(result)\"\n },\n {\n \"alpha_fraction\": 0.5227272510528564,\n \"alphanum_fraction\": 0.5378788113594055,\n \"avg_line_length\": 32.125,\n \"blob_id\": \"8d636b333b4561ab3c71d11e6fa2cd76af4c1a8b\",\n \"content_id\": \"3638ac3b7af46514765d80362da5e0ce95bb6e16\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 344,\n \"license_type\": \"no_license\",\n \"max_line_length\": 62,\n \"num_lines\": 8,\n \"path\": \"/알고리즘/온라인저지/2021/08/0803/상수.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"a, b = input().split() # a와 b를 공백을 기준으로 input 받아서\\ndef aigosangsuya(a, b): \\n if int(a[::-1]) >= int(b[::-1]): # 각각 뒤에서 읽은 값의 int값을 비교해서\\n result = a[::-1]\\n else:\\n result = b[::-1]\\n return result # 큰 쪽을 저장해서 반환\\nprint(aigosangsuya(a, b)) # 값을 출력\"\n },\n {\n \"alpha_fraction\": 0.5515695214271545,\n \"alphanum_fraction\": 0.5784753561019897,\n \"avg_line_length\": 22.526315689086914,\n \"blob_id\": \"f868f553d9e4dbc74475d6d8f46116cdf0bfd8bc\",\n \"content_id\": \"1e8dc5411b002f4a7b15898d06cd90b8903559f2\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 446,\n \"license_type\": \"no_license\",\n \"max_line_length\": 48,\n \"num_lines\": 19,\n \"path\": \"/알고리즘/온라인저지/2022/10/1006/점프 점프.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\nfrom collections import deque\\n\\ninput = sys.stdin.readline\\n\\nN = int(input().rstrip())\\narr = list(map(int, input().rstrip().split()))\\nQ = deque()\\nvisited = [0]*N\\nQ.append((0, 0))\\nvisited[0] = 1\\nwhile Q:\\n now, move = Q.popleft()\\n if now == N-1: print(move); break\\n for i in range(now+1, now+1+arr[now]):\\n if 0<=i<N and arr[i] and not visited[i]:\\n Q.append((i, move+1))\\n visited[i] = 1\\nelse: print(-1)\"\n },\n {\n \"alpha_fraction\": 0.44186046719551086,\n \"alphanum_fraction\": 0.45348837971687317,\n \"avg_line_length\": 13.5,\n \"blob_id\": \"851a561528e5023b3d15b2b95fbeed1ae0625306\",\n \"content_id\": \"cc957f801b7f5eb7f1b4cf0d14f147a7ff37b22b\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 86,\n \"license_type\": \"no_license\",\n \"max_line_length\": 20,\n \"num_lines\": 6,\n \"path\": \"/알고리즘/온라인저지/2022/02/0206/!밀비 급일.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"while True:\\n sen = input()\\n if sen == 'END':\\n break\\n\\n print(sen[::-1])\"\n },\n {\n \"alpha_fraction\": 0.3992537260055542,\n \"alphanum_fraction\": 0.41044774651527405,\n \"avg_line_length\": 13.833333015441895,\n \"blob_id\": \"fb66f3bff28f3fb5bf51c470d8a09be53a53426d\",\n \"content_id\": \"34f70adc1681ec856a282fad2fe4e56405e71064\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 268,\n \"license_type\": \"no_license\",\n \"max_line_length\": 45,\n \"num_lines\": 18,\n \"path\": \"/알고리즘/온라인저지/2022/02/0213/내 학점을 구해줘.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"T = int(input())\\n\\nfor t in range(T):\\n N = int(input())\\n\\n sumC = 0\\n\\n tmp = 0\\n\\n for n in range(N):\\n C, G = map(float, input().split())\\n C = int(C)\\n\\n sumC += C\\n \\n tmp += C * G\\n\\n print('{} {:.1f}'.format(sumC, tmp/sumC))\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.5714285969734192,\n \"alphanum_fraction\": 0.5952380895614624,\n \"avg_line_length\": 27.33333396911621,\n \"blob_id\": \"febc505e53e99d642622fb932b829af8edadf636\",\n \"content_id\": \"50412a65d30006796a35d0f30b57792ffbc33861\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 84,\n \"license_type\": \"no_license\",\n \"max_line_length\": 42,\n \"num_lines\": 3,\n \"path\": \"/알고리즘/온라인저지/2022/03/0303/알고리즘 수업 - 알고리즘의 수행 시간 4.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"result = sum(list(range(1, int(input()))))\\ndim = 2\\nprint(result, f'\\\\n{dim}', sep='')\"\n },\n {\n \"alpha_fraction\": 0.5887850522994995,\n \"alphanum_fraction\": 0.5981308221817017,\n \"avg_line_length\": 22.88888931274414,\n \"blob_id\": \"3d948194e389fa119ba80efdaf019adab6e193e0\",\n \"content_id\": \"25c950c060d96543eca997e1f06242586fc3e008\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 214,\n \"license_type\": \"no_license\",\n \"max_line_length\": 47,\n \"num_lines\": 9,\n \"path\": \"/알고리즘/온라인저지/2022/11/1120/요다.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\n\\nfor _ in range(int(input().rstrip())):\\n words = input().split()\\n for word in words[2:]: print(word, end=' ')\\n for word in words[:2]: print(word, end=' ')\\n print()\"\n },\n {\n \"alpha_fraction\": 0.3683373034000397,\n \"alphanum_fraction\": 0.38663485646247864,\n \"avg_line_length\": 20.32203483581543,\n \"blob_id\": \"3c81233a9a5c0b649374fe37901c65948c28fe1b\",\n \"content_id\": \"a7d4267f8c14b187acb3872df97e1f80f4b182b3\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1281,\n \"license_type\": \"no_license\",\n \"max_line_length\": 75,\n \"num_lines\": 59,\n \"path\": \"/알고리즘/온라인저지/2021/12/1216/안전 영역.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import copy\\nfrom collections import deque\\n\\nN = int(input())\\n\\ndx = (-1, 1, 0, 0)\\ndy = (0, 0, -1, 1)\\n\\nheight_map = [list(map(int, input().split())) for _ in range(N)]\\n\\nrain = 0\\n\\nbfs = deque()\\n\\nresult = 0\\n\\nwhile True:\\n tmp_map = copy.deepcopy(height_map)\\n\\n flooded_check = 0\\n for i in range(N):\\n for j in range(N):\\n if tmp_map[i][j] <= rain:\\n tmp_map[i][j] = 0\\n flooded_check += sum(tmp_map[i])\\n \\n if flooded_check == 0:\\n break\\n \\n safe = 0 # 현재 rain에서 나온 안전영역의 수\\n\\n for i in range(N):\\n for j in range(N):\\n if tmp_map[i][j]:\\n bfs.append((i, j))\\n safe += 1\\n\\n while bfs:\\n tmp = bfs.popleft()\\n y = tmp[0]\\n x = tmp[1]\\n\\n if tmp_map[y][x] == 0:\\n continue\\n \\n tmp_map[y][x] = 0\\n for k in range(4):\\n ny = y + dy[k]\\n nx = x + dx[k]\\n\\n if 0 <= ny < N and 0 <= nx < N and tmp_map[ny][nx]:\\n bfs.append((ny, nx))\\n\\n rain += 1\\n \\n if safe > result:\\n result = safe\\n\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.596187174320221,\n \"alphanum_fraction\": 0.6048526763916016,\n \"avg_line_length\": 29.421052932739258,\n \"blob_id\": \"ba008688e5385eb03b480e864b59dc2fa7dbc2d6\",\n \"content_id\": \"463c28ea2e3c51280e04c821260db708adce0ace\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 725,\n \"license_type\": \"no_license\",\n \"max_line_length\": 53,\n \"num_lines\": 19,\n \"path\": \"/알고리즘/온라인저지/2022/09/0908/점프 점프.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from collections import deque\\n\\nN = int(input())\\narr = list(map(int, input().split()))\\nstart = int(input()) - 1 # 인덱스 맞추기\\nvisited = [0] * N # 점들의 방문 배열\\nQ = deque()\\nQ.append(start) # 시작점 넣고 출발\\nwhile Q:\\n now = Q.popleft()\\n if visited[now]: continue # 방문한 적 있는 점이면 continue\\n visited[now] = 1 # 방문 처리\\n tmp = arr[now] # 현재 지점에서 점프할 수 있는 거리\\n front, back = now+tmp, now-tmp # 점프 시 인덱스\\n if 0<=front<N and not visited[front]:\\n Q.append(front) # 앞으로 점프\\n if 0<=back<N and not visited[back]:\\n Q.append(back) # 뒤로 점프\\nprint(sum(visited)) # 방문한 적 있는 점들의 수 출력\"\n },\n {\n \"alpha_fraction\": 0.5549132823944092,\n \"alphanum_fraction\": 0.589595377445221,\n \"avg_line_length\": 14.818181991577148,\n \"blob_id\": \"9c8d3f58ea68835399b5a852b4ac3de85bce390f\",\n \"content_id\": \"dba8bc49f077dacdf3670d5e0ca0378f096f157a\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 173,\n \"license_type\": \"no_license\",\n \"max_line_length\": 34,\n \"num_lines\": 11,\n \"path\": \"/알고리즘/온라인저지/2022/06/0614/다각형의 대각선.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from math import factorial as fact\\n\\nN = int(input())\\nresult = 0\\nif N == 3:\\n result = 0\\nelse:\\n result = fact(N)\\n result //= 24\\n result //= fact(N-4)\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.567685604095459,\n \"alphanum_fraction\": 0.5764192342758179,\n \"avg_line_length\": 19.909090042114258,\n \"blob_id\": \"ae37922eaacb52619edc0d2db806ac51871bb36e\",\n \"content_id\": \"8f73c95da4bef5a47add7cdb889fbe3e4641c058\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 229,\n \"license_type\": \"no_license\",\n \"max_line_length\": 48,\n \"num_lines\": 11,\n \"path\": \"/알고리즘/온라인저지/2022/10/1031/공 넣기.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\n\\nN, M = map(int, input().rstrip().split())\\nresult = [0]*N\\nfor m in range(M):\\n a, b, c = map(int, input().rstrip().split())\\n for i in range(a-1, b):\\n result[i] = c\\nprint(*result)\"\n },\n {\n \"alpha_fraction\": 0.49754902720451355,\n \"alphanum_fraction\": 0.5098039507865906,\n \"avg_line_length\": 23.727272033691406,\n \"blob_id\": \"7b2675f169228b1065bf6f56ac606c0cc8a59446\",\n \"content_id\": \"f9cba670894799d5cb642fe1729824389668ac1f\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 816,\n \"license_type\": \"no_license\",\n \"max_line_length\": 60,\n \"num_lines\": 33,\n \"path\": \"/알고리즘/온라인저지/2021/08/0828/스위치 켜고 끄기.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ndef change(num):\\n if switch[num]:\\n switch[num] = 0\\n else:\\n switch[num] = 1\\n return\\n\\nswitch_count = int(sys.stdin.readline())\\nswitch = [-1] + list(map(int, sys.stdin.readline().split()))\\nstudents = int(sys.stdin.readline())\\n\\nfor i in range(students):\\n sex, num = map(int, sys.stdin.readline().split())\\n if sex == 1:\\n for j in range(num, switch_count+1, num):\\n change(j)\\n else:\\n change(num)\\n for k in range(switch_count//2):\\n if num+k > switch_count or num - k < 1:\\n break\\n if switch[num+k] == switch[num-k]:\\n change(num+k)\\n change(num-k)\\n else:\\n break\\n\\nfor i in range(1, len(switch)):\\n print(switch[i], end=' ')\\n if not i%20:\\n print()\\n\"\n },\n {\n \"alpha_fraction\": 0.5022830963134766,\n \"alphanum_fraction\": 0.534246563911438,\n \"avg_line_length\": 14.642857551574707,\n \"blob_id\": \"07c3a2236f2a434a728847aea658822aa65ca3f1\",\n \"content_id\": \"f5339ff4db8c02424f9f43b167785a46c0e6ae33\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 219,\n \"license_type\": \"no_license\",\n \"max_line_length\": 33,\n \"num_lines\": 14,\n \"path\": \"/알고리즘/온라인저지/2021/12/1216/그릇.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"dishes = input()\\n\\nheight = 10\\n\\nprev_dish = dishes[0]\\n\\nfor i in range(1, len(dishes)): \\n if dishes[i] == prev_dish:\\n height += 5\\n else:\\n height += 10\\n prev_dish = dishes[i]\\n \\nprint(height)\\n\"\n },\n {\n \"alpha_fraction\": 0.5562701225280762,\n \"alphanum_fraction\": 0.5691318511962891,\n \"avg_line_length\": 23,\n \"blob_id\": \"b572e244d087762a67cafcb0f8396a1d1eb148a5\",\n \"content_id\": \"151f3e69787f1328249e071dc55eeb9eb4fb82cd\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 311,\n \"license_type\": \"no_license\",\n \"max_line_length\": 39,\n \"num_lines\": 13,\n \"path\": \"/알고리즘/온라인저지/2022/09/0911/진짜 공간.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = int(input())\\nfiles = list(map(int, input().split()))\\ncluster = int(input())\\nresult = 0\\nfor file in files:\\n if not file: continue\\n if file > cluster:\\n tmp = file//cluster + 1\\n if file%cluster == 0: tmp -= 1\\n result += cluster * tmp\\n else:\\n result += cluster\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.5961538553237915,\n \"alphanum_fraction\": 0.6153846383094788,\n \"avg_line_length\": 52,\n \"blob_id\": \"40f58b147df1210de1beed3089ca32470f1af037\",\n \"content_id\": \"2edaf399c8852c60b17f623ab92321b6e85c57fc\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 52,\n \"license_type\": \"no_license\",\n \"max_line_length\": 52,\n \"num_lines\": 1,\n \"path\": \"/알고리즘/온라인저지/2022/07/0731/돌 게임 2.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"print('SK') if not int(input()) % 2 else print('CY')\"\n },\n {\n \"alpha_fraction\": 0.582524299621582,\n \"alphanum_fraction\": 0.6155340075492859,\n \"avg_line_length\": 23.571428298950195,\n \"blob_id\": \"980725440c2bc5ec04a8e1dc6be5d4aa50ceb2c2\",\n \"content_id\": \"9e441cc14038f1cb1a57dbf8c7de5c284a6f6f0f\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 719,\n \"license_type\": \"no_license\",\n \"max_line_length\": 59,\n \"num_lines\": 21,\n \"path\": \"/알고리즘/온라인저지/2022/02/0225/로마 숫자 만들기.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from itertools import combinations_with_replacement as comb\\n# itertools를 코테에서도 쓸 수 있다고 하니\\n# 실력향상을 위한 빡구현 vs 일단 라이브러리 사용\\n# 고민해볼 가치가 있을 듯 (아래는 참고 블로그 링크)\\n# https://uni2237.tistory.com/56\\n\\n\\nN = int(input())\\nresult = [] # 경우의 수 들이 담길 리스트\\nrome = [1, 5, 10, 50] # 로마숫자 IVXL\\n\\nfor temp in comb(range(4), N):\\n summ = 0 # 매 경우의 수\\n # N==2 일 때, temp = (0, 0) ...\\n for i in temp:\\n summ += rome[i] # i는 rome의 인덱스값으로 사용\\n\\n result.append(summ) # 경우의 수를 완성해서 \\n # result에 추가\\n\\nprint(len(set(result))) # set으로 중복제거\"\n },\n {\n \"alpha_fraction\": 0.40869563817977905,\n \"alphanum_fraction\": 0.417391300201416,\n \"avg_line_length\": 22.200000762939453,\n \"blob_id\": \"075ea83a22110fa3beb79f66689ea6107acc2f7e\",\n \"content_id\": \"d2c31ef14b1eb09a75de57cee4c5a348f23b79c5\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 115,\n \"license_type\": \"no_license\",\n \"max_line_length\": 36,\n \"num_lines\": 5,\n \"path\": \"/알고리즘/온라인저지/2022/05/0506/분수좋아해.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"while True:\\n N, M = map(int, input().split())\\n if N == M == 0:\\n break\\n print(f'{N//M} {N%M} / {M}')\"\n },\n {\n \"alpha_fraction\": 0.5279187560081482,\n \"alphanum_fraction\": 0.5380710363388062,\n \"avg_line_length\": 15.5,\n \"blob_id\": \"76a01b7d6343833b00b89700b04735a2e6fdb3f2\",\n \"content_id\": \"f1a5604b8c1591a4934f2e6e1421802b981114e7\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 197,\n \"license_type\": \"no_license\",\n \"max_line_length\": 41,\n \"num_lines\": 12,\n \"path\": \"/알고리즘/SWEA/LEARN/Course/1. Programming Beginner/파이썬 프로그래밍 기초(2)/35차시 3. 자료구조 – 셋, 딕셔너리 - 연습문제 10.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"alphabet = {}\\n\\ntmp = input()\\n\\nfor t in tmp:\\n if t not in alphabet:\\n alphabet.update({t:1})\\n else:\\n alphabet[t] += 1\\n\\nfor a in alphabet:\\n print('{},{}'.format(a, alphabet[a]))\"\n },\n {\n \"alpha_fraction\": 0.4621409773826599,\n \"alphanum_fraction\": 0.5483028888702393,\n \"avg_line_length\": 26.428571701049805,\n \"blob_id\": \"01a0c599142bad682bb3b56c9ff8e505f3f9bb0e\",\n \"content_id\": \"7333b1f8de368e8fe007c05d83deb7a52cddcfce\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 383,\n \"license_type\": \"no_license\",\n \"max_line_length\": 56,\n \"num_lines\": 14,\n \"path\": \"/알고리즘/[템플릿]/Dynamic Programming/포도주 시식.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = int(input())\\nwines = [0] * 10002\\ndp = [0] * 10002\\nfor n in range(N): wines[n] = int(input())\\ndp[0] = wines[0]\\ndp[1] = max(dp[0], wines[0]+wines[1])\\ndp[2] = max(dp[1], wines[1]+wines[2], wines[0]+wines[2])\\nfor i in range(3, N):\\n A = dp[i-3] + wines[i-1] + wines[i]\\n B = dp[i-2] + wines[i]\\n dp[i] = max(A, B, dp[i-1])\\nprint(max(dp))\\n\\n# https://www.acmicpc.net/problem/2156\"\n },\n {\n \"alpha_fraction\": 0.5573248267173767,\n \"alphanum_fraction\": 0.5668789744377136,\n \"avg_line_length\": 23.230770111083984,\n \"blob_id\": \"6db09059b3288cb0f63a8e5b00ed48bba01fd718\",\n \"content_id\": \"2e03a071287aaf2f1d09a948047e4c3fdf9099af\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 368,\n \"license_type\": \"no_license\",\n \"max_line_length\": 57,\n \"num_lines\": 13,\n \"path\": \"/알고리즘/온라인저지/2022/08/0815/좋은 단어.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\n\\nN = int(input())\\nresult = 0\\nfor n in range(N):\\n W, S = input().rstrip(), [] # word, stack\\n for w in W:\\n if S and w == S[-1]: S.pop() # 스택 마지막과 같으면 pop\\n else: S.append(w) # 다르면 append\\n if not S: result += 1 # 다 짝이 맞아서 스택에 남은게 없으면 result++\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.44936707615852356,\n \"alphanum_fraction\": 0.4810126721858978,\n \"avg_line_length\": 12.782608985900879,\n \"blob_id\": \"5acaba1aa831ac0fec08ba84ce5fa391de7f6c81\",\n \"content_id\": \"d9d2bdd8e426123dde9b9b04d1e6f03b8bf79fd8\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 316,\n \"license_type\": \"no_license\",\n \"max_line_length\": 34,\n \"num_lines\": 23,\n \"path\": \"/알고리즘/온라인저지/2022/01/0108/계단 오르기.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = int(input())\\n\\nstairs = []\\n\\nfor n in range(N):\\n stairs.append(int(input()))\\n\\nN -= 1\\n\\nresult = stairs[N]\\n\\nwhile N >= 2:\\n if stairs[N-1] >= stairs[N-2]:\\n result += stairs[N-1]\\n N -= 1\\n else:\\n result += stairs[N-2]\\n N -= 2\\n \\nif N == 1:\\n result += stairs[N-1]\\n\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.4912280738353729,\n \"alphanum_fraction\": 0.5087719559669495,\n \"avg_line_length\": 12.470588684082031,\n \"blob_id\": \"ba2cedd7cf98ebab0bcfb199a494517640322491\",\n \"content_id\": \"8067ae73fb5a0b9861600819a7249a5e824e8483\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 228,\n \"license_type\": \"no_license\",\n \"max_line_length\": 32,\n \"num_lines\": 17,\n \"path\": \"/알고리즘/온라인저지/2021/12/1213/0 = not cute, 1 = cute.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"T = int(input())\\n\\ncute = 0\\ncut = 0\\n\\nfor tc in range(T):\\n is_cute = int(input())\\n\\n if is_cute:\\n cute += 1\\n else:\\n cut += 1\\n\\nif cute < cut:\\n print('Junhee is not cute!')\\nelse:\\n print('Junhee is cute!')\"\n },\n {\n \"alpha_fraction\": 0.468822181224823,\n \"alphanum_fraction\": 0.494226336479187,\n \"avg_line_length\": 27.933332443237305,\n \"blob_id\": \"1502ee4aa8f6b1d68c6ffbbe9e25c2da1f02e631\",\n \"content_id\": \"00d56cfe7dc1ddb43f3051a66200185f32a6e1e8\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 433,\n \"license_type\": \"no_license\",\n \"max_line_length\": 66,\n \"num_lines\": 15,\n \"path\": \"/알고리즘/온라인저지/2022/11/1103/이동하기.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\ndy, dx = [1, 0, 1], [0, 1, 1]\\n\\nN, M = map(int, input().rstrip().split())\\narr = [list(map(int, input().rstrip().split())) for _ in range(N)]\\ndp = [a[:] for a in arr]\\nfor i in range(N):\\n for j in range(M):\\n for k in range(3):\\n ny, nx = i+dy[k], j+dx[k]\\n if 0<=ny<N and 0<=nx<M:\\n dp[ny][nx] = max(dp[ny][nx], arr[ny][nx]+dp[i][j])\\nprint(dp[N-1][M-1])\"\n },\n {\n \"alpha_fraction\": 0.6231883764266968,\n \"alphanum_fraction\": 0.6376811861991882,\n \"avg_line_length\": 34,\n \"blob_id\": \"4e2516de7d98e9177e93bca847a6c69b3ce778c8\",\n \"content_id\": \"e385c0c5d72340e3061ef37a2b801c7031ef84a5\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 69,\n \"license_type\": \"no_license\",\n \"max_line_length\": 38,\n \"num_lines\": 2,\n \"path\": \"/알고리즘/온라인저지/2022/03/0306/金平糖 (Konpeito).py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"nums = list(map(int, input().split()))\\nprint(max(nums)*3 - sum(nums))\"\n },\n {\n \"alpha_fraction\": 0.4350649416446686,\n \"alphanum_fraction\": 0.5064935088157654,\n \"avg_line_length\": 21.14285659790039,\n \"blob_id\": \"cbebbd888bd8ef9fd9e6d7b0125038527fe6f39c\",\n \"content_id\": \"b38a7606ceb1498e597534c2d30d1b8aba5ae6f7\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 154,\n \"license_type\": \"no_license\",\n \"max_line_length\": 44,\n \"num_lines\": 7,\n \"path\": \"/알고리즘/온라인저지/2023/04/0415/Every Second Counts.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"times = []\\nfor _ in range(2):\\n h, m, s = map(int, input().split(' : '))\\n times.append((h*60+m)*60+s)\\na, b = times\\nif b < a: b += 24*60*60\\nprint(b-a)\"\n },\n {\n \"alpha_fraction\": 0.33421751856803894,\n \"alphanum_fraction\": 0.4615384638309479,\n \"avg_line_length\": 12.034482955932617,\n \"blob_id\": \"ea9c02f39632b51b2c601199ec4742a87875c242\",\n \"content_id\": \"d80df80b8ac4421b56dbe7818ffad3a6bff34e4d\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 481,\n \"license_type\": \"no_license\",\n \"max_line_length\": 31,\n \"num_lines\": 29,\n \"path\": \"/알고리즘/SWEA/LEARN/Course/1. Programming Beginner/파이썬 프로그래밍 기초(2)/29차시 3. 자료구조 – 셋, 딕셔너리 - 연습문제 4.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"a = {\\n '아메리카노': 1900, \\n '카페모카': 3300, \\n '에스프레소': 1900, \\n '카페라떼': 2500, \\n '카푸치노': 2500, \\n '바닐라라떼': 2900\\n }\\n\\nb = {\\n '헤이즐럿라떼': 2900, \\n '카페모카': 3300, \\n '밀크커피': 3300, \\n '아메리카노': 1900, \\n '샷크린티라떼': 3300\\n }\\n\\ntmp = {}\\n\\ntmp.update(b)\\ntmp.update(a)\\n\\nresult = set()\\n\\nfor t in tmp:\\n if tmp[t] >= 3000:\\n result.add((t, tmp[t]))\\n\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.4507211446762085,\n \"alphanum_fraction\": 0.4951923191547394,\n \"avg_line_length\": 26.600000381469727,\n \"blob_id\": \"b590b330131224abbce25f6b6e9f0168a66b97a4\",\n \"content_id\": \"e439f456ac51e28234df65662f962528b5f2e944\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1196,\n \"license_type\": \"no_license\",\n \"max_line_length\": 53,\n \"num_lines\": 30,\n \"path\": \"/알고리즘/온라인저지/2021/08/0812/세탁소 사장 동혁.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"\\\"\\\"\\\"\\n미국동전\\n1: 페니 = 10원\\n5: 니켈 = 50원\\n10: 다임 = 100원\\n25: 쿼터 = 250\\n\\n아래 두개는 문제에서 안 씀\\n# 50: 하프달러 = 500원\\n# 100: 달러 = 1000원\\n\\\"\\\"\\\"\\nT = int(input()) # 테스트케이스\\ncoins = [25, 10, 5, 1] # 동전들\\nfor t in range(T): # 테스트케이스 개수만큼\\n change = int(input()) # 거스름돈\\n changed_coins = [] # 사용된 모든 동전들\\n for coin in coins: # 동전들을 순회하면서\\n if coin <= change: # 거슬러줄 수 있으면\\n while True: # while문 반복하면서 거슬러준다\\n change -= coin # 해당 동전을 하나 거슬러주고\\n changed_coins.append(coin) # 그 동전을\\n # 거슬러준 동전 리스트에 추가\\n if coin > change: # 순회중인 동전이 금액보다 커져서\\n # 그 동전으로 거슬러 줄 수 없게되면\\n break # while문 종료\\n for i in range(4): # 동전은 총 4개\\n # 사용된 동전의 개수의 종류는 4개\\n print(changed_coins.count(coins[i]), end=' ')\\n # 동전개수를 세서 출력\\n print() # 줄바꿈\\n \"\n },\n {\n \"alpha_fraction\": 0.550632894039154,\n \"alphanum_fraction\": 0.6392405033111572,\n \"avg_line_length\": 21.428571701049805,\n \"blob_id\": \"0a76605c86a62d9a9362bcfe0fbed0d7d1c6e112\",\n \"content_id\": \"873ebf7b7061fa227582099a328f18af894628f5\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 158,\n \"license_type\": \"no_license\",\n \"max_line_length\": 35,\n \"num_lines\": 7,\n \"path\": \"/알고리즘/온라인저지/2023/02/0206/정육각형과 삼각형.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import math\\n\\nL = int(input())\\ncos_30 = math.cos(math.radians(30))\\ncos_60 = math.cos(math.radians(60))\\nresult = L**2 * cos_30 * cos_60\\nprint(f'{result:.9f}') \"\n },\n {\n \"alpha_fraction\": 0.40336135029792786,\n \"alphanum_fraction\": 0.4075630307197571,\n \"avg_line_length\": 22.899999618530273,\n \"blob_id\": \"330d164ec17d33adedb03ddf1c9c1b9a187eae19\",\n \"content_id\": \"7007dee796672c42f1573b2961bf9650e268f563\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 238,\n \"license_type\": \"no_license\",\n \"max_line_length\": 39,\n \"num_lines\": 10,\n \"path\": \"/알고리즘/온라인저지/2022/05/0503/다음수.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"while True:\\n A, B, C = map(int, input().split())\\n if A == B == C == 0:\\n break\\n result = 'AP'\\n if B-A == C-B: # AP\\n print(result, C + (C-B))\\n else: # GP\\n result = 'GP'\\n print(result, (C * (B//A)))\"\n },\n {\n \"alpha_fraction\": 0.5176470875740051,\n \"alphanum_fraction\": 0.529411792755127,\n \"avg_line_length\": 20.5,\n \"blob_id\": \"762842be446e110e892cf3e53f6f797ab098d11a\",\n \"content_id\": \"2a7d054610a7e8608bc0f70d0794dd2e30001aee\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 85,\n \"license_type\": \"no_license\",\n \"max_line_length\": 30,\n \"num_lines\": 4,\n \"path\": \"/알고리즘/온라인저지/2023/04/0428/스키테일 암호.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"K = int(input())\\nPW = input()\\nfor i in range(0, len(PW), K):\\n print(PW[i], end='')\"\n },\n {\n \"alpha_fraction\": 0.5176211595535278,\n \"alphanum_fraction\": 0.5616739988327026,\n \"avg_line_length\": 33.92307662963867,\n \"blob_id\": \"5fe865008bdce35e2d0fc712eec44e63e10ec214\",\n \"content_id\": \"023118db16e631716bda5901abea1b8f9298d388\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 582,\n \"license_type\": \"no_license\",\n \"max_line_length\": 96,\n \"num_lines\": 13,\n \"path\": \"/알고리즘/온라인저지/2021/08/0816/주사위.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = int(input())\\nnumbers = list(map(int, input().split()))\\nnumber = [min(numbers[0], numbers[5]), min(numbers[1], numbers[4]), min(numbers[2], numbers[3])]\\n # 최소값을 도출해낼 수 있는 면 찾기\\nnumber.sort() # 사용할 숫자들 크기순으로 정리\\nA = number[0]\\nB = number[1]\\nC = number[2]\\nif N == 1: # 1*1일때는 그 주사위 자체이니까\\n print(sum(numbers)-max(numbers)) # 가장 큰 수를 아랫면으로 놓은 값을 출력\\nelse: # 1이 아니면\\n print((((((N-1)*A)+B)*N)*4) + C*4 + (((N-2)*B)*4) + A*(N-2)*(N-2))\\n # 최소값 출력\\n\"\n },\n {\n \"alpha_fraction\": 0.4436090290546417,\n \"alphanum_fraction\": 0.49624061584472656,\n \"avg_line_length\": 18.14285659790039,\n \"blob_id\": \"a6d9f4568fd6b212f19bbdc71957f15914f5a6f5\",\n \"content_id\": \"7c81fadb186cdf8a9c1a8c7295b6b27524e5cf95\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 133,\n \"license_type\": \"no_license\",\n \"max_line_length\": 23,\n \"num_lines\": 7,\n \"path\": \"/알고리즘/온라인저지/2022/05/0507/369.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = int(input())\\nresult = 0\\nfor n in range(1, N+1):\\n for i in str(n):\\n if i in '369':\\n result += 1\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.45026177167892456,\n \"alphanum_fraction\": 0.4921466112136841,\n \"avg_line_length\": 15,\n \"blob_id\": \"a50cf074b95cfe4a18128166bc9d0ebe1d0c4158\",\n \"content_id\": \"511230e575c4c90f98bec7a40bd6e6c086b11f06\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 191,\n \"license_type\": \"no_license\",\n \"max_line_length\": 34,\n \"num_lines\": 12,\n \"path\": \"/알고리즘/온라인저지/2022/07/0731/알고리즘 수업 - 피보나치 수 1.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"def fib(n):\\n global result\\n if n == 1 or n == 2:\\n result += 1\\n return 1\\n else:\\n return fib(n-1) + fib(n-2)\\n\\nN = int(input())\\nresult = 0\\nfib(N)\\nprint(result, N-2)\"\n },\n {\n \"alpha_fraction\": 0.3333333432674408,\n \"alphanum_fraction\": 0.46236559748649597,\n \"avg_line_length\": 9.44444465637207,\n \"blob_id\": \"9d377968726ff4d0c1c9c9955351ed8f56c1769f\",\n \"content_id\": \"a840027d6880af73de75bc156004a8c9c6bf3788\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 93,\n \"license_type\": \"no_license\",\n \"max_line_length\": 29,\n \"num_lines\": 9,\n \"path\": \"/알고리즘/온라인저지/2022/02/0225/운동장 한 바퀴.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"pi = 3.141592\\n\\nA = 13\\nB = 8\\n\\nA = int(input())\\nB = int(input())\\n\\nprint((A * 2) + (2 * pi * B))\"\n },\n {\n \"alpha_fraction\": 0.4301075339317322,\n \"alphanum_fraction\": 0.5376344323158264,\n \"avg_line_length\": 25.714284896850586,\n \"blob_id\": \"6c3486bea5bf6a493f568a0e025153c97c5508cc\",\n \"content_id\": \"1b761553461679d90ff8b963d16d66c93c9cbf03\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 186,\n \"license_type\": \"no_license\",\n \"max_line_length\": 38,\n \"num_lines\": 7,\n \"path\": \"/알고리즘/[템플릿]/Dynamic Programming/파도반 수열.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"dp = [1, 1, 1, 2, 2, 3] + [0]*97\\nfor i in range(5, 103): \\n dp[i] = dp[i-5]+dp[i-1]\\nfor _ in range(int(input())): \\n print(dp[int(input())-1])\\n\\n# https://www.acmicpc.net/problem/9461\"\n },\n {\n \"alpha_fraction\": 0.4232558012008667,\n \"alphanum_fraction\": 0.4558139443397522,\n \"avg_line_length\": 14.428571701049805,\n \"blob_id\": \"7dd864055711d3cf66b55d930ff3a27ea8c75b53\",\n \"content_id\": \"04c7366cfd69a02e293943a592321560a7a8491a\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 215,\n \"license_type\": \"no_license\",\n \"max_line_length\": 35,\n \"num_lines\": 14,\n \"path\": \"/알고리즘/온라인저지/2022/05/0505/ソーシャルゲーム (Social Game).py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"A, B, C = map(int, input().split())\\nresult = 0\\nday = 0\\ncoin = 0\\nwhile True:\\n coin += A\\n day += 1\\n result += 1\\n if day == 7:\\n day = 0\\n coin += B\\n if coin >= C:\\n break\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.5569620132446289,\n \"alphanum_fraction\": 0.594936728477478,\n \"avg_line_length\": 39,\n \"blob_id\": \"d2bb54d1843c0f8867805aed2047ed6ab52ca0dd\",\n \"content_id\": \"d6a2bd278cf69aeb17450e24f24810724a3599af\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 79,\n \"license_type\": \"no_license\",\n \"max_line_length\": 49,\n \"num_lines\": 2,\n \"path\": \"/알고리즘/온라인저지/2022/05/0516/Sum of Odd Sequence.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"for t in range(int(input())):\\n print(sum(list(range(1, int(input())+1, 2))))\"\n },\n {\n \"alpha_fraction\": 0.5161290168762207,\n \"alphanum_fraction\": 0.6129032373428345,\n \"avg_line_length\": 17.799999237060547,\n \"blob_id\": \"62799550449c404c8fc14b0f3601928ecb618c96\",\n \"content_id\": \"5df930954e9eb2ee46d6e8c78c6f2a1884227cdc\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 93,\n \"license_type\": \"no_license\",\n \"max_line_length\": 36,\n \"num_lines\": 5,\n \"path\": \"/알고리즘/온라인저지/2021/08/0822/윤년.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = int(input())\\nresult = 0\\nif (not N%4 and N%100) or not N%400:\\n result = 1\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.5375722646713257,\n \"alphanum_fraction\": 0.5664739608764648,\n \"avg_line_length\": 12.384614944458008,\n \"blob_id\": \"a85e80b0a57b0c2d33cc08bacdf0cc66aa0e32fe\",\n \"content_id\": \"6eb7062b6fb412a70b93cd085808f6aaca531392\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 173,\n \"license_type\": \"no_license\",\n \"max_line_length\": 26,\n \"num_lines\": 13,\n \"path\": \"/알고리즘/온라인저지/2022/10/1011/새.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\n\\nN = int(input().rstrip())\\nresult = 0\\nnum = 1\\nwhile N:\\n result += 1\\n if num > N: num = 1\\n N -= num\\n num += 1\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.5277777910232544,\n \"alphanum_fraction\": 0.5347222089767456,\n \"avg_line_length\": 13.5,\n \"blob_id\": \"d967f38e0cb9e77b7f17d6953750b953e797ff51\",\n \"content_id\": \"db667f7a8b2d4f9990e0be99bf0a3fcf2b04d556\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 144,\n \"license_type\": \"no_license\",\n \"max_line_length\": 32,\n \"num_lines\": 10,\n \"path\": \"/알고리즘/온라인저지/2022/02/0224/뉴비의 기준은 뭘까.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N, M = map(int, input().split())\\n\\nresult = 'NEWBIE!'\\n\\nif M <= N and M > 2:\\n result = 'OLDBIE!'\\nelif M > N:\\n result = 'TLE!'\\n\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.3737373650074005,\n \"alphanum_fraction\": 0.4040403962135315,\n \"avg_line_length\": 18.799999237060547,\n \"blob_id\": \"cc3112aeee5edf1984a4ecb4adcbd4d546f161a7\",\n \"content_id\": \"c1d83e9ce0a682adb477e5925dedeaf22c4c7899\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 99,\n \"license_type\": \"no_license\",\n \"max_line_length\": 22,\n \"num_lines\": 5,\n \"path\": \"/알고리즘/온라인저지/2021/08/0816/for break.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"for i in range(5):\\n for j in range(5):\\n if j == 3:\\n break\\n print(i, j)\\n\"\n },\n {\n \"alpha_fraction\": 0.4229764938354492,\n \"alphanum_fraction\": 0.44778066873550415,\n \"avg_line_length\": 20.30555534362793,\n \"blob_id\": \"5e22b2dddb8ef33504dddb31d388a2b2e3a16134\",\n \"content_id\": \"53ed0e39933546bf42b2b7fe8940954f4e687533\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 870,\n \"license_type\": \"no_license\",\n \"max_line_length\": 65,\n \"num_lines\": 36,\n \"path\": \"/알고리즘/온라인저지/2022/12/1204/갤러리.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"def find(height, width):\\n global result\\n for i in range(height-1):\\n j = 0\\n while j < width-1:\\n j += 1\\n if arr[i][j:j+2] == 'XX' and arr[i+1][j:j+2] == '..':\\n result += 1\\n j += 1\\n if arr[i][j:j+2] == '..' and arr[i+1][j:j+2] == 'XX':\\n result += 1\\n j += 1\\n\\ndef rotate(arr):\\n new_arr = []\\n for j in range(M):\\n tmp = ''\\n for i in range(N):\\n tmp += arr[i][j]\\n new_arr.append(tmp)\\n return new_arr\\n\\nN, M = map(int, input().split())\\narr = [input() for _ in range(N)]\\nresult = 0\\nfind(N, M)\\narr = rotate(arr)\\nfind(M, N)\\nprint(result)\\n\\n\\\"\\\"\\\"\\n그림을 걸 수 있는지 가로로만 스캔할 것\\n그리고 배열을 90도 돌려주고 다시 스캔\\n주의할 점은\\n90도만 배열을 돌리기 때문에 N과 M이 반전됨\\n\\\"\\\"\\\"\"\n },\n {\n \"alpha_fraction\": 0.43579766154289246,\n \"alphanum_fraction\": 0.4630350172519684,\n \"avg_line_length\": 18.846153259277344,\n \"blob_id\": \"795fd9194e395140893fe86ef609053cc5a797bf\",\n \"content_id\": \"8eda7c5ff287e47ad46132b86150be19276b45e0\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 257,\n \"license_type\": \"no_license\",\n \"max_line_length\": 42,\n \"num_lines\": 13,\n \"path\": \"/알고리즘/온라인저지/2022/07/0726/국회의원 선거.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = int(input())\\nresult = 0\\nif N == 1:\\n print(result)\\nelse:\\n D = int(input()) # dasom\\n C = [int(input()) for _ in range(N-1)]\\n while D <= max(C):\\n C.sort(reverse=True)\\n D += 1\\n result += 1\\n C[0] -= 1\\n print(result)\"\n },\n {\n \"alpha_fraction\": 0.508083164691925,\n \"alphanum_fraction\": 0.5265588760375977,\n \"avg_line_length\": 26.0625,\n \"blob_id\": \"94482ad6e55605edb11211878983d0c4220704fd\",\n \"content_id\": \"50b762f7cff82b266ce4da7354bedffe1d3b3a31\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 433,\n \"license_type\": \"no_license\",\n \"max_line_length\": 92,\n \"num_lines\": 16,\n \"path\": \"/알고리즘/온라인저지/2023/01/0129/숫자놀이.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"M, N = map(int, input().split())\\narr = []\\nnum_to_en = ['zero', 'one', 'two', 'three', 'four', 'five', 'six', 'seven', 'eight', 'nine']\\nnum_list = list(range(M, N+1))\\nfor num in num_list:\\n tmp = ''\\n for i in str(num):\\n tmp += num_to_en[int(i)]\\n translated = [tmp, num]\\n arr.append(translated)\\narr.sort(key=lambda x:x[0])\\ncnt = 0\\nfor a in arr: \\n print(a[1], end=' ')\\n cnt = (cnt+1)%10\\n if cnt == 0: print()\\n\"\n },\n {\n \"alpha_fraction\": 0.5,\n \"alphanum_fraction\": 0.5074626803398132,\n \"avg_line_length\": 26,\n \"blob_id\": \"161baa71a0a801971651800bc412c6a0e49d68fd\",\n \"content_id\": \"b267dfd38f82b808ee6de791fa6f320f6a2002a4\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 134,\n \"license_type\": \"no_license\",\n \"max_line_length\": 36,\n \"num_lines\": 5,\n \"path\": \"/알고리즘/온라인저지/2022/09/0910/닉네임에 갓 붙이기.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"for _ in range(int(input())):\\n nickname = input().split()\\n for i in ['god'] + nickname[1:]:\\n print(i, end='')\\n print()\"\n },\n {\n \"alpha_fraction\": 0.391259104013443,\n \"alphanum_fraction\": 0.40894901752471924,\n \"avg_line_length\": 21.372093200683594,\n \"blob_id\": \"2477fa5ef1f248ee0f95e42baeb9a93dd6897809\",\n \"content_id\": \"f49e1a82df9f206abc06f2446b12c12b16630553\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1233,\n \"license_type\": \"no_license\",\n \"max_line_length\": 80,\n \"num_lines\": 43,\n \"path\": \"/알고리즘/온라인저지/2022/01/0122/소수의 연속합.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = int(input())\\n\\nif N == 1:\\n # 놀랍게도 1은 소수가 아니었다!!\\n cnt = 0\\nelse:\\n # 에라토스테네스의 체로 N까지의 소수 구하기\\n a = [False,False] + [True]*(N-1)\\n primes = []\\n for i in range(2,N+1):\\n if a[i]:\\n primes.append(i)\\n for j in range(2*i, N+1, i):\\n if a[j]:\\n a[j] = False\\n\\n # 투포인터에 사용할 변수 s, e와\\n # 연속합이 N일때 카운트할 cnt\\n s = e = cnt = 0\\n\\n # 가장 작은 소수부터 시작\\n now = 2\\n\\n while True:\\n # 투포인터 탐색 종료조건\\n if (now < N and e == len(primes)-1) or (now > N and s == len(primes)-1):\\n break\\n\\n if now == N: # 구간합이 N과 같으면\\n cnt += 1 # 카운트 증가\\n now -= primes[s] # 포인터 이동\\n s += 1\\n elif now < N: # 구간합이 N보다 작을 때\\n e += 1 # 한 칸 밀어주기\\n now += primes[e]\\n elif now > N: # 구간합이 N보다 클 때\\n now -= primes[s]\\n s += 1 # 한 칸 땡겨주기\\n\\n if now == N: # 다 돌고 마지막 본인이 소수일 때\\n cnt += 1 # 카운트 증가\\n\\nprint(cnt)\"\n },\n {\n \"alpha_fraction\": 0.5679012537002563,\n \"alphanum_fraction\": 0.6296296119689941,\n \"avg_line_length\": 26.33333396911621,\n \"blob_id\": \"058d9bb0d27ca5d0a006c1f504a5bb4e23a05061\",\n \"content_id\": \"b245c4e797708f56f4ec280f8a5aefe95a4bd3a0\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 81,\n \"license_type\": \"no_license\",\n \"max_line_length\": 40,\n \"num_lines\": 3,\n \"path\": \"/알고리즘/온라인저지/2023/02/0215/간지(干支).py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"year = int(input())\\ntmp = 'IJKLABCDEFGH'\\nprint(tmp[year%12], (year+6)%10, sep='')\"\n },\n {\n \"alpha_fraction\": 0.45254236459732056,\n \"alphanum_fraction\": 0.5169491767883301,\n \"avg_line_length\": 16.909090042114258,\n \"blob_id\": \"d20212a1fb806d5cf77900901143d92fdefc25f3\",\n \"content_id\": \"1d02dfc8b84d2c56f391006144684a22cc1865a0\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 590,\n \"license_type\": \"no_license\",\n \"max_line_length\": 49,\n \"num_lines\": 33,\n \"path\": \"/알고리즘/온라인저지/2021/12/1216/숨바꼭질.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from collections import deque\\n\\nN, K = map(int, input().split())\\n\\nbfs = deque()\\nbfs.append((N, 0))\\n\\nvisited = [0 for _ in range(100001)]\\n\\nwhile bfs:\\n tmp = bfs.popleft()\\n n = tmp[0]\\n t = tmp[1]\\n\\n if visited[n]:\\n continue\\n\\n if n == K:\\n print(t)\\n break\\n\\n visited[n] = 1\\n\\n go = n+1\\n back = n-1\\n jump = n*2\\n\\n if 0 <= go <= 100000 and not visited[go]:\\n bfs.append((go, t+1))\\n if 0 <= back <= 100000 and not visited[back]:\\n bfs.append((back, t+1))\\n if 0 <= jump <= 100000 and not visited[jump]:\\n bfs.append((jump, t+1))\"\n },\n {\n \"alpha_fraction\": 0.5080440044403076,\n \"alphanum_fraction\": 0.5309060215950012,\n \"avg_line_length\": 29.947368621826172,\n \"blob_id\": \"21dccf9f15012be838282d0e163e354ebd066f7d\",\n \"content_id\": \"4030e62ba11cca3746c0689d54a60333aab74119\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1735,\n \"license_type\": \"no_license\",\n \"max_line_length\": 59,\n \"num_lines\": 38,\n \"path\": \"/알고리즘/온라인저지/2022/01/0116/달력.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = int(input()) # 일정의 개수\\n\\ndp = [0] * 365 # 일년치 달력\\n\\nfor n in range(N):\\n S, E = map(int, input().split()) # 일정 입력\\n\\n for i in range(S-1, E): # 리스트를 365로 하였기 때문에 1일은 dp[0]\\n # 시작도 S-1부터\\n dp[i] += 1 # 일정이 있는 날 달력의 높이 하나 추가\\n\\n# 연속된 일정단위로 만들어지는 직사각형의 넓이들의 합을 구해야 함\\nstart = end = width = height = result = 0 # result는 출력값\\ncounting = False # 연속된 일정인지 확인하기 위함\\n\\nfor i in range(365): # 일년동안\\n if dp[i]: # 일정이 있는 날이면\\n if not counting: # 연속된지 체크중이지 않으면\\n counting = True # 체크중으로 변경\\n start = i # 이 날 부터 연속된 일정이 시작\\n height = dp[i] # 일정들의 높이의 최대값 초기화\\n elif counting: # 연속된지 체크중이면\\n if dp[i] > height: # 지금 보고 있는 일정의 높이가 더 높으면\\n height = dp[i] # 높이 갱신\\n else: # 일정이 없는 날이면\\n if counting: # 체크중이면\\n counting = False # 체크를 종료하고\\n end = i # 전날까지가 연속된 일정\\n width = end - start # 연속된 일정들의 직사각형의 가로는 (끝-시작)\\n result += width * height # 결과값에 직사각형의 높이 저장\\n width = height = 0 # 가로 세로 초기화\\n\\nif dp[364] and counting: # 달력 마지막날이고, 체크중이라면\\n end = 365 # 끝은 12월31일\\n width = end - start # 가로\\n result += width * height # 넓이를 결과값에 더해서\\n\\nprint(result) # 출력\\n \\n\"\n },\n {\n \"alpha_fraction\": 0.448587566614151,\n \"alphanum_fraction\": 0.4689265489578247,\n \"avg_line_length\": 24.285715103149414,\n \"blob_id\": \"038151a60487cee5ccd57f7a79b0367c24f29d07\",\n \"content_id\": \"2acd08aa238e48ada0d7b85a71af8178acb56d50\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1073,\n \"license_type\": \"no_license\",\n \"max_line_length\": 57,\n \"num_lines\": 35,\n \"path\": \"/알고리즘/온라인저지/2022/07/0709/그림.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from collections import deque\\n\\n\\ndef bfs(y, x):\\n Q.append((y, x))\\n global maxx # 가장 넓이가 넓은 그림의 넓이 전역변수 선언\\n tmp = 0\\n while Q:\\n y, x = Q.popleft()\\n if arr[y][x] == 0: # 이전에 이미 탐색한 지점이면\\n continue # 컨티뉴\\n arr[y][x] = 0\\n tmp += 1 # 해당 그림의 넓이 ++\\n for i in range(4):\\n ny = y+dy[i]\\n nx = x+dx[i]\\n if 0<=ny<N and 0<=nx<M and arr[ny][nx]:\\n Q.append((ny, nx))\\n if tmp > maxx: # 가장 넓이가 넓은 그림을 새로 발견하였으면\\n maxx = tmp # 갱신\\n\\n\\ndy = [-1, 1, 0, 0] # 상하좌우 4방향 델타이동\\ndx = [0, 0, -1, 1]\\nN, M = map(int, input().split())\\narr = [list(map(int, input().split())) for _ in range(N)]\\nresult = maxx = 0 # 그림의 수, 최대 넓이 초기화\\nQ = deque()\\nfor n in range(N):\\n for m in range(M):\\n if arr[n][m]: # 그림을 발견하면\\n bfs(n, m) # BFS 탐색\\n result += 1 # 그림의 수 ++\\nprint(result)\\nprint(maxx) \"\n },\n {\n \"alpha_fraction\": 0.5760456323623657,\n \"alphanum_fraction\": 0.5969581604003906,\n \"avg_line_length\": 20.079999923706055,\n \"blob_id\": \"3a3e93abeffc14bc2c7f3986239389b37d8b4e99\",\n \"content_id\": \"960abd72c5c368955be19857e9f84cc37fcacd60\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 526,\n \"license_type\": \"no_license\",\n \"max_line_length\": 48,\n \"num_lines\": 25,\n \"path\": \"/알고리즘/온라인저지/2022/09/0916/나무 자르기.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\n\\ndef cut(height):\\n cutted = 0\\n for tree in trees:\\n if tree>height:\\n cutted += tree-height\\n if cutted>=M: return True\\n return False\\n\\nN, M = map(int, input().rstrip().split())\\ntrees = list(map(int, input().rstrip().split()))\\nresult = 0\\nstart, end = result, int(1e9)\\nwhile start<=end:\\n mid = (start+end) // 2\\n if cut(mid):\\n start = mid+1\\n result = max(result, mid)\\n else: end = mid-1\\nprint(result)\\n\\n# https://www.acmicpc.net/problem/2805\"\n },\n {\n \"alpha_fraction\": 0.44978782534599304,\n \"alphanum_fraction\": 0.4653465449810028,\n \"avg_line_length\": 29.782608032226562,\n \"blob_id\": \"4b02b72da6efad7d2bc6b8d62884c29a3a2c7901\",\n \"content_id\": \"becd0d4e30c0757154d0b539745fe6048f091518\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 707,\n \"license_type\": \"no_license\",\n \"max_line_length\": 57,\n \"num_lines\": 23,\n \"path\": \"/알고리즘/온라인저지/2022/10/1002/친구.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\n\\nN = int(input().rstrip())\\narr = [input().rstrip() for _ in range(N)]\\nfriend_2 = [[] for _ in range(N)]\\nfor i in range(N):\\n for j in range(N):\\n if arr[i][j] == 'Y':\\n if j not in friend_2[i]:\\n friend_2[i].append(j)\\n if i not in friend_2[j]:\\n friend_2[j].append(i)\\n for k in range(N):\\n if arr[j][k] == 'Y' and i != k:\\n if k not in friend_2[i]:\\n friend_2[i].append(k)\\n if i not in friend_2[k]:\\n friend_2[k].append(i)\\nresult = 0\\nfor friend in friend_2: result = max(result, len(friend))\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.6010362505912781,\n \"alphanum_fraction\": 0.6424870491027832,\n \"avg_line_length\": 13.923076629638672,\n \"blob_id\": \"4918a77527c10f744a07eecfae124b838a7700de\",\n \"content_id\": \"72f850a6e5c5840b26e15f5e6916ac09a139152e\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 203,\n \"license_type\": \"no_license\",\n \"max_line_length\": 41,\n \"num_lines\": 13,\n \"path\": \"/알고리즘/온라인저지/2022/10/1010/NN.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\n\\nN, M = map(int, input().rstrip().split())\\nprint((str(N)*N)[:M])\\n\\n\\\"\\\"\\\"\\n<참고한 링크>\\nhttps://hongku.tistory.com/268\\n\\\"\\\"\\\"\\n\\n# https://www.acmicpc.net/problem/11944\"\n },\n {\n \"alpha_fraction\": 0.5444234609603882,\n \"alphanum_fraction\": 0.5652173757553101,\n \"avg_line_length\": 21.08333396911621,\n \"blob_id\": \"a18ac7384da7f8d3b74122d1d4362ce032fb49e6\",\n \"content_id\": \"c5cb3185974f5c2aa02e6b853484a47e2793e7ed\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 529,\n \"license_type\": \"no_license\",\n \"max_line_length\": 58,\n \"num_lines\": 24,\n \"path\": \"/알고리즘/온라인저지/2022/10/1012/공유기 설치.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\n\\ndef install(distance):\\n prev = houses[0]\\n cnt = 1\\n for house in houses[1:]:\\n if house>=prev+distance:\\n cnt += 1\\n prev = house\\n return cnt\\n\\nN, C = map(int, input().rstrip().split())\\nhouses = sorted([int(input().rstrip()) for _ in range(N)])\\nstart, end = 0, houses[-1]-houses[0]\\nresult = 1\\nwhile start<=end:\\n mid = (start+end) // 2\\n if install(mid)>=C:\\n result = max(result, mid)\\n start = mid+1\\n else: end = mid-1\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.4357798099517822,\n \"alphanum_fraction\": 0.4403669834136963,\n \"avg_line_length\": 17.25,\n \"blob_id\": \"8d38edaec428d40691cc989cf6ed61cbb5fadacd\",\n \"content_id\": \"4db2cbdd01f2c17507037cf7e87ef7663103a317\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 218,\n \"license_type\": \"no_license\",\n \"max_line_length\": 42,\n \"num_lines\": 12,\n \"path\": \"/알고리즘/온라인저지/2022/02/0220/첫 글자를 대문자로.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = int(input())\\n\\nfor n in range(N):\\n text = input()\\n\\n for i in range(len(text)):\\n if i == 0:\\n print(text[i].upper(), end='')\\n continue\\n print(text[i], end='')\\n \\n print()\"\n },\n {\n \"alpha_fraction\": 0.6515151262283325,\n \"alphanum_fraction\": 0.6666666865348816,\n \"avg_line_length\": 21.33333396911621,\n \"blob_id\": \"00877637a2e3b4506b90076de048e4d982e6495c\",\n \"content_id\": \"617f1d91833b575e542f8def22b9f2b830802766\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 66,\n \"license_type\": \"no_license\",\n \"max_line_length\": 41,\n \"num_lines\": 3,\n \"path\": \"/알고리즘/온라인저지/2022/07/0731/피자 (Small).py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"result = 0\\nfor i in range(int(input())): result += i\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.5478261113166809,\n \"alphanum_fraction\": 0.573913037776947,\n \"avg_line_length\": 16.769229888916016,\n \"blob_id\": \"76bb87a5912a81999381510246cd5eba9e955c7f\",\n \"content_id\": \"cf8b5c777bb7c12a6fb5fb885c7d7d6957d9eaf0\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 230,\n \"license_type\": \"no_license\",\n \"max_line_length\": 41,\n \"num_lines\": 13,\n \"path\": \"/알고리즘/온라인저지/2022/10/1018/싸이클.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\n\\nN, P = map(int, input().rstrip().split())\\narr = [0]*(P+1)\\nflag = False\\nnow = N\\nwhile not flag:\\n now = (now*N)%P\\n arr[now] += 1\\n if arr[now] == 3: flag = True\\nprint(arr.count(2) + 1)\"\n },\n {\n \"alpha_fraction\": 0.5064935088157654,\n \"alphanum_fraction\": 0.5227272510528564,\n \"avg_line_length\": 16.882352828979492,\n \"blob_id\": \"9449e0396e6c8fc2d8684b559bb20c1803264dc2\",\n \"content_id\": \"5cbc4ec1c7c56f150dee0c11a944afbe3b236727\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 308,\n \"license_type\": \"no_license\",\n \"max_line_length\": 26,\n \"num_lines\": 17,\n \"path\": \"/알고리즘/온라인저지/2022/11/1112/보너스 점수.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\n\\nN = int(input().rstrip())\\nanswer = input().rstrip()\\nresult = 0\\nbonus = 0\\nfor i in range(N):\\n if answer[i] == 'X':\\n bonus = 0\\n elif answer[i] == 'O':\\n result += i+1\\n result += bonus\\n bonus += 1\\n # print(bonus)\\nprint(result)\\n \"\n },\n {\n \"alpha_fraction\": 0.4422110617160797,\n \"alphanum_fraction\": 0.4673366844654083,\n \"avg_line_length\": 17.18181800842285,\n \"blob_id\": \"7b63d79d91bb155ffa1defbcad958aaf6bd23220\",\n \"content_id\": \"120a4cd802598ef4876facdee0d7fb59f637a969\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 199,\n \"license_type\": \"no_license\",\n \"max_line_length\": 26,\n \"num_lines\": 11,\n \"path\": \"/알고리즘/온라인저지/2022/06/0620/가장 큰 금민수.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = int(input())\\nresult = 0\\nfor n in range(N, -1, -1):\\n gms = True\\n for s in str(n):\\n if s not in '47':\\n gms = False\\n if gms:\\n result = n\\n break\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.3533916771411896,\n \"alphanum_fraction\": 0.37527352571487427,\n \"avg_line_length\": 49.83333206176758,\n \"blob_id\": \"911a03edbeb1e0b018f1b5c171f100da51c97895\",\n \"content_id\": \"6574bab9eff9851dec609b6a858b8937090b50fe\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1236,\n \"license_type\": \"no_license\",\n \"max_line_length\": 70,\n \"num_lines\": 18,\n \"path\": \"/알고리즘/온라인저지/2021/08/0814/ZOAC 2.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"\\\"\\\"\\\"\\n시계모양에서 알파벳간에 거리는 ASCII 코드로 |A-B|\\n13을 초과하면 26-|A-B|\\n\\\"\\\"\\\"\\nword = input() # 입력받을 단어\\nword = 'A' + word # 단어의 맨 앞에 시작점인 A 추가\\ndef zoac(A, B): # 글자간 거리를 구하는 함수 zoac()\\n if abs(ord(A)-ord(B)) > 13: # 두 글자의 거리가 13을 초과하면\\n result = 26 - abs(ord(A)-ord(B)) # 26에서 거리만큼을 빼줌\\n # 한바퀴(26)에서 거리만큼 뒤로 오겠다는 뜻\\n else: # 거리가 13아래면\\n result = abs(ord(A)-ord(B)) # 거리 = 절대값\\n return result # 결과 반환\\nsum_word = 0 # 글자간 거리를 더할 변수\\nfor i in range(1, len(word)): # 2번째 글자부터 마지막 글자까지\\n # 두 글자씩 비교할 것이기 때문\\n sum_word += zoac(word[i-1], word[i]) # 글자간 거리들을 변수에 더하고\\nprint(sum_word) # 거리들을 더한 값을 출력\"\n },\n {\n \"alpha_fraction\": 0.4845360815525055,\n \"alphanum_fraction\": 0.5154638886451721,\n \"avg_line_length\": 15.222222328186035,\n \"blob_id\": \"db968c031f912cd613aba4006f551dca03e93d18\",\n \"content_id\": \"253d1d645cb39911c0345829cf5c83d6e3d9f97e\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 291,\n \"license_type\": \"no_license\",\n \"max_line_length\": 33,\n \"num_lines\": 18,\n \"path\": \"/알고리즘/온라인저지/2022/02/0203/약수 구하기.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N, K = map(int, input().split())\\n\\nmeasures = []\\n\\nfor i in range(1, int(N**0.5)+1):\\n if not N%i:\\n measures.append(i)\\n \\ntmp = measures[::-1]\\n\\nfor t in tmp:\\n if N//t != N**0.5:\\n measures.append(N//t)\\n\\nif len(measures) >= K:\\n print(measures[K-1])\\nelse:\\n print(0)\"\n },\n {\n \"alpha_fraction\": 0.5076923370361328,\n \"alphanum_fraction\": 0.5230769515037537,\n \"avg_line_length\": 11.600000381469727,\n \"blob_id\": \"ab606376ffdc7d2e4e383e89e98710c91c49647c\",\n \"content_id\": \"387bb3870e44cf4ea5cf7bf3f976b158c7a1c08d\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 130,\n \"license_type\": \"no_license\",\n \"max_line_length\": 26,\n \"num_lines\": 10,\n \"path\": \"/알고리즘/온라인저지/2022/02/0205/플러그.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = int(input())\\n\\nresult = 0\\n\\nfor n in range(N):\\n if result:\\n result -= 1\\n result += int(input())\\n\\nprint(result)\\n \"\n },\n {\n \"alpha_fraction\": 0.49295774102211,\n \"alphanum_fraction\": 0.49295774102211,\n \"avg_line_length\": 19.428571701049805,\n \"blob_id\": \"9eaebedf8599d6348bab3f7c540db90d8f2a41df\",\n \"content_id\": \"4b5bb8aee58a6cdbc58e45bc82172d3200af3c02\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 142,\n \"license_type\": \"no_license\",\n \"max_line_length\": 29,\n \"num_lines\": 7,\n \"path\": \"/알고리즘/온라인저지/2021/08/0814/문자열반복.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"T = int(input())\\nfor t in range(T):\\n R, word = input().split()\\n R = int(R)\\n for wor in word:\\n print(wor*R, end='')\\n print()\"\n },\n {\n \"alpha_fraction\": 0.5189003348350525,\n \"alphanum_fraction\": 0.5257731676101685,\n \"avg_line_length\": 23.33333396911621,\n \"blob_id\": \"1703bdb343ec8af2476b537a8ec9b6d55fd2b84d\",\n \"content_id\": \"8f7a4b05798177ca5a4b5840c6e46d1f2934479f\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 291,\n \"license_type\": \"no_license\",\n \"max_line_length\": 57,\n \"num_lines\": 12,\n \"path\": \"/알고리즘/온라인저지/2022/04/0412/질투진서.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N, A, B = map(int, input().split())\\narr = [list(map(int, input().split())) for _ in range(N)]\\n# print(arr)\\nA, B = A-1, B-1\\nresult = 'HAPPY'\\nfor a in arr[A]:\\n if a > arr[A][B]:\\n result = 'ANGRY'\\nfor i in range(N):\\n if arr[i][B] > arr[A][B]:\\n result = 'ANGRY'\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.5368421077728271,\n \"alphanum_fraction\": 0.5368421077728271,\n \"avg_line_length\": 16.363636016845703,\n \"blob_id\": \"41105922ce4a87432bc94c8f3ace7e710b55b4c6\",\n \"content_id\": \"ade66cae6231cac0d60201001c70cdf12b8131f8\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 190,\n \"license_type\": \"no_license\",\n \"max_line_length\": 44,\n \"num_lines\": 11,\n \"path\": \"/알고리즘/온라인저지/2022/09/0927/백대열.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\n\\ndef gcd(a, b):\\n while a%b: a, b = b, a%b\\n return b\\n\\nN, M = map(int, input().rstrip().split(':'))\\nG = gcd(N, M)\\nprint('{}:{}'.format(N//G, M//G))\"\n },\n {\n \"alpha_fraction\": 0.37987011671066284,\n \"alphanum_fraction\": 0.3874458968639374,\n \"avg_line_length\": 21.0238094329834,\n \"blob_id\": \"769f02edc8b38b2c4980a4a772f32c0348e5aef6\",\n \"content_id\": \"4ce566aa035a8155f29f31c58286a392c2561a5c\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 924,\n \"license_type\": \"no_license\",\n \"max_line_length\": 56,\n \"num_lines\": 42,\n \"path\": \"/알고리즘/온라인저지/2021/10/1016/AC.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from collections import deque\\nimport sys\\n\\nT = int(sys.stdin.readline())\\n\\nfor t in range(T):\\n order = sys.stdin.readline().rstrip()\\n order.replace('RR', '')\\n N = int(sys.stdin.readline())\\n arr = sys.stdin.readline().rstrip()[1:-1].split(',')\\n q = deque(arr)\\n\\n rev, left, right = False, 0, len(q)-1\\n flag = False\\n\\n if N == 0:\\n q = []\\n right = 0\\n\\n for o in order:\\n if o == 'R':\\n if rev:\\n rev = False\\n else:\\n rev = True\\n elif o == 'D':\\n if len(q) < 1:\\n flag = True\\n print('error')\\n break\\n else:\\n if rev:\\n q.pop()\\n else:\\n q.popleft()\\n \\n if not flag:\\n if rev:\\n q.reverse()\\n print('['+','.join(q)+']')\\n else:\\n print('['+','.join(q)+']')\"\n },\n {\n \"alpha_fraction\": 0.4639175236225128,\n \"alphanum_fraction\": 0.5103092789649963,\n \"avg_line_length\": 16.727272033691406,\n \"blob_id\": \"ec9d3bad09e8647d5b5847c420b6243e65fe7e18\",\n \"content_id\": \"e3c28ba3d6a2218b345e48b486549e6990ff52ba\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 194,\n \"license_type\": \"no_license\",\n \"max_line_length\": 26,\n \"num_lines\": 11,\n \"path\": \"/알고리즘/온라인저지/2022/06/0604/신기한 수.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# print(list(str(392)))\\nN = int(input())\\ni = 1\\nresult = 0\\nfor n in range(1, N+1):\\n tmp = 0\\n for j in list(str(n)):\\n tmp += int(j)\\n if not n%tmp:\\n result += 1\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.4649122953414917,\n \"alphanum_fraction\": 0.5175438523292542,\n \"avg_line_length\": 15.428571701049805,\n \"blob_id\": \"78006e23c92c804515c288f022cf001bb238f1d5\",\n \"content_id\": \"b5142fe3d6f95811beeeda813722d1a7776dce6c\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 114,\n \"license_type\": \"no_license\",\n \"max_line_length\": 42,\n \"num_lines\": 7,\n \"path\": \"/알고리즘/온라인저지/2023/03/0331/Máquina de café.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"A = int(input())\\nB = int(input())\\nC = int(input())\\n\\nresult = [A*4 + B*2, A*2 + C*2, B*2 + C*4]\\n\\nprint(min(result))\"\n },\n {\n \"alpha_fraction\": 0.6237623691558838,\n \"alphanum_fraction\": 0.6237623691558838,\n \"avg_line_length\": 13.571428298950195,\n \"blob_id\": \"99742ea043268f0a915fb625b4ac8ab22db8fab2\",\n \"content_id\": \"d94d37bbbc84c5dea789b5b5ae551ae6490c876d\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 101,\n \"license_type\": \"no_license\",\n \"max_line_length\": 28,\n \"num_lines\": 7,\n \"path\": \"/알고리즘/온라인저지/2022/11/1121/CAPS.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\n\\nS = input().rstrip()\\nfor s in S:\\n print(s.upper(), end='')\"\n },\n {\n \"alpha_fraction\": 0.42718446254730225,\n \"alphanum_fraction\": 0.45436891913414,\n \"avg_line_length\": 21.434782028198242,\n \"blob_id\": \"08fb6100f1a847f5129a0eabe4427e3861143123\",\n \"content_id\": \"44c22493c8bde902c54c7164af3a042d46361f43\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 515,\n \"license_type\": \"no_license\",\n \"max_line_length\": 35,\n \"num_lines\": 23,\n \"path\": \"/알고리즘/온라인저지/2022/03/0330/카드놀이.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"A = list(map(int, input().split()))\\nB = list(map(int, input().split()))\\npoint = [0, 0]\\nwinner = ''\\nall_draw = True\\nfor i in range(len(A)):\\n if A[i] > B[i]:\\n point[0] += 3\\n all_draw = False\\n if point[0] >= point[1]:\\n winner = 'A'\\n elif A[i] < B[i]:\\n point[1] += 3\\n all_draw = False\\n if point[0] <= point[1]:\\n winner = 'B'\\n elif A[i] == B[i]:\\n point[0] += 1\\n point[1] += 1\\nif all_draw:\\n winner = 'D'\\nprint(*point)\\nprint(winner)\"\n },\n {\n \"alpha_fraction\": 0.5875576138496399,\n \"alphanum_fraction\": 0.6059907674789429,\n \"avg_line_length\": 38.54545593261719,\n \"blob_id\": \"3038b28ece597c614a7e819b1ffd65a1fccbe94f\",\n \"content_id\": \"d007ea2b5b54003d84ffdfc84443fe7abb96ab19\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 698,\n \"license_type\": \"no_license\",\n \"max_line_length\": 65,\n \"num_lines\": 11,\n \"path\": \"/알고리즘/온라인저지/2021/08/0803/곱셈.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"a = int(input()) # a를 정수로 입력받고\\nb = input() # b를 str 그대로 입력받아서\\nc = 1 * int(b) # c에 b를 백업해두고\\nb = list(b) # b는 리스트로 ['3', '8', '5']로 만들어 준 다음\\ncalc_list = [] # 각각의 계산값들을 더해서 리스트에 [0], [1], [2]에 저장할 리스트를 만들어주고\\nfor i in range(3): # 리스트를 순회하면서 \\n calc_list.append(a * int(b[i])) # 각각 자릿수를 곱한 값들을 구해서 저장\\ncalc_list.reverse() # 결과값들을 뒤집어서\\nfor calc in calc_list: # 결과값 리스트를 순회하면서\\n print(calc) # 출력\\nprint(a * c) # 마지막에 백업해놓은 원래b값과 a값을 곱해서 출력\"\n },\n {\n \"alpha_fraction\": 0.4900990128517151,\n \"alphanum_fraction\": 0.5198019742965698,\n \"avg_line_length\": 21.55555534362793,\n \"blob_id\": \"126441bc363e14c180360d481e423f84dfadeb94\",\n \"content_id\": \"5e225fc797a5de15c56d34b167a9c4221030e3fa\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 202,\n \"license_type\": \"no_license\",\n \"max_line_length\": 43,\n \"num_lines\": 9,\n \"path\": \"/알고리즘/온라인저지/2022/08/0827/Square Pasture.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"X = []\\nY = []\\nfor _ in range(2):\\n tmp = list(map(int, input().split()))\\n X.append(tmp[0])\\n Y.append(tmp[1])\\n X.append(tmp[2])\\n Y.append(tmp[3])\\nprint(max(max(X)-min(X), max(Y)-min(Y))**2)\"\n },\n {\n \"alpha_fraction\": 0.40077072381973267,\n \"alphanum_fraction\": 0.42581889033317566,\n \"avg_line_length\": 19,\n \"blob_id\": \"64aae3888b6474eb53faa4abcb924191ac01c86a\",\n \"content_id\": \"aef03e4b65529dc5bcd80381cb248fab3113bb73\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 519,\n \"license_type\": \"no_license\",\n \"max_line_length\": 45,\n \"num_lines\": 26,\n \"path\": \"/알고리즘/SWEA/LEARN/Course/2. Programming Intermediate/1. 파이썬 SW문제해결 기본 List1/8차시 1일차 - 숫자 카드.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"T = int(input())\\n\\nfor t in range(1, T+1):\\n N = int(input())\\n\\n counts = [0] * (10)\\n\\n num = input()\\n \\n for n in num:\\n counts[int(n)] += 1\\n \\n cnt = 0\\n result = 0\\n\\n if counts.count(max(counts)) == 1:\\n result = counts.index(max(counts))\\n cnt = max(counts)\\n else: # != 1\\n for i in range(9, -1, -1):\\n if counts[i] == max(counts):\\n result = i\\n cnt = counts[i]\\n break\\n\\n print('#{} {} {}'.format(t, result, cnt))\"\n },\n {\n \"alpha_fraction\": 0.47037702798843384,\n \"alphanum_fraction\": 0.4955116808414459,\n \"avg_line_length\": 20.461538314819336,\n \"blob_id\": \"aed8a86468c1912102969352622e717e97f5836e\",\n \"content_id\": \"ee94a2b99e64f93f42fbcbf44a6b9f5a091bb32d\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 557,\n \"license_type\": \"no_license\",\n \"max_line_length\": 51,\n \"num_lines\": 26,\n \"path\": \"/알고리즘/온라인저지/2023/02/0226/인간-컴퓨터 상호작용.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\n\\nS = input().strip()\\nprefix_sum = [[0]*26 for _ in range(len(S))]\\n\\nfor i in range(len(S)):\\n for j in range(26):\\n idx = ord(S[i])-97\\n \\n if idx == j:\\n prefix_sum[i][j] = prefix_sum[i-1][j]+1\\n else:\\n prefix_sum[i][j] = prefix_sum[i-1][j]\\n\\nfor _ in range(int(input().strip())):\\n A, L, R = input().strip().split()\\n L, R = map(int, (L, R))\\n\\n idx = ord(A)-97\\n result = prefix_sum[R][idx]\\n if L != 0:\\n result -= prefix_sum[L-1][idx]\\n\\n print(result)\"\n },\n {\n \"alpha_fraction\": 0.41981130838394165,\n \"alphanum_fraction\": 0.4811320900917053,\n \"avg_line_length\": 16.75,\n \"blob_id\": \"a371b57874b1fcd826e79f939671ab8fc7d7fe80\",\n \"content_id\": \"b8d8d5245f6269533ccf2d2c0693a915f98b5cfd\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 212,\n \"license_type\": \"no_license\",\n \"max_line_length\": 24,\n \"num_lines\": 12,\n \"path\": \"/알고리즘/온라인저지/2023/03/0315/Tournament Selection.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"result = -1\\ncnt = 0\\nfor _ in range(6):\\n if input() == 'W':\\n cnt += 1\\nif cnt == 1 or cnt == 2:\\n result = 3\\nif cnt == 3 or cnt == 4:\\n result = 2\\nif cnt == 5 or cnt == 6:\\n result = 1\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.6127819418907166,\n \"alphanum_fraction\": 0.6278195381164551,\n \"avg_line_length\": 25.700000762939453,\n \"blob_id\": \"b20d00cba5299247d7a20f8389e0a10e06db7355\",\n \"content_id\": \"6be19f47a64a3858d760879f0f1baa0aee2c1731\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 266,\n \"license_type\": \"no_license\",\n \"max_line_length\": 89,\n \"num_lines\": 10,\n \"path\": \"/알고리즘/온라인저지/2022/12/1228/2009년.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from datetime import datetime, date\\n\\n\\ndef what_day_is_it(date):\\n days = ['Monday', 'Tuesday', 'Wednesday', 'Thursday', 'Friday', 'Saturday', 'Sunday']\\n day = date.weekday()\\n print(days[day])\\n\\nD, M = map(int, input().split())\\nwhat_day_is_it(date(2009, M, D))\"\n },\n {\n \"alpha_fraction\": 0.5090909004211426,\n \"alphanum_fraction\": 0.5181818008422852,\n \"avg_line_length\": 26.75,\n \"blob_id\": \"61dc20bc2f7d6512cac558dfa6a5ded2202e5eca\",\n \"content_id\": \"2f76d270a6241e27e07102e6e888feda31ed6b39\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 110,\n \"license_type\": \"no_license\",\n \"max_line_length\": 34,\n \"num_lines\": 4,\n \"path\": \"/알고리즘/온라인저지/2023/06/0602/Oddities.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"result = ['even', 'odd']\\nfor _ in range(int(input())):\\n X = int(input())\\n print(f'{X} is {result[X%2]}')\"\n },\n {\n \"alpha_fraction\": 0.5087336301803589,\n \"alphanum_fraction\": 0.539301335811615,\n \"avg_line_length\": 20.85714340209961,\n \"blob_id\": \"a0275f9e30570eaf2de1467cba760dcd56060944\",\n \"content_id\": \"bc18ac8001dd741704bb93da1e6ee733e2b550a3\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 458,\n \"license_type\": \"no_license\",\n \"max_line_length\": 71,\n \"num_lines\": 21,\n \"path\": \"/알고리즘/온라인저지/2022/10/1003/올림픽.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\n\\nN, K = map(int, input().rstrip().split())\\narr = []\\nfor n in range(N): arr.append(list(map(int, input().rstrip().split())))\\narr.sort(key=lambda x:(-x[1], -x[2], -x[3]))\\nprev = arr[0][1:]\\nrank = 1\\nstep = 0\\nresult = 1\\nfor i in range(1, N):\\n now = arr[i][1:]\\n if now != prev: \\n rank += 1+step\\n prev = now[:]\\n step = 0\\n else: step += 1\\n if arr[i][0] == K: result = rank; break\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.523809552192688,\n \"alphanum_fraction\": 0.5555555820465088,\n \"avg_line_length\": 24.399999618530273,\n \"blob_id\": \"dfc0f7c73b3897bb39c82c577e8f9fd9c8ae4736\",\n \"content_id\": \"9286afeb85c69592efd21df79bd29c676415dd74\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 126,\n \"license_type\": \"no_license\",\n \"max_line_length\": 35,\n \"num_lines\": 5,\n \"path\": \"/알고리즘/온라인저지/2022/12/1202/3000번 버스.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"for _ in range(int(input())):\\n result = 1\\n for i in range(int(input())-1):\\n result = result*2+1\\n print(result)\"\n },\n {\n \"alpha_fraction\": 0.4647887349128723,\n \"alphanum_fraction\": 0.48826292157173157,\n \"avg_line_length\": 25.75,\n \"blob_id\": \"f4e1ba7a9ee0342d8c2a53877caec5f68ab65536\",\n \"content_id\": \"5fcf237c8d826108c5611ea0abc552ef1b800b00\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 213,\n \"license_type\": \"no_license\",\n \"max_line_length\": 53,\n \"num_lines\": 8,\n \"path\": \"/알고리즘/온라인저지/2022/12/1215/IBM 빼기 1.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = int(input())\\nfor tc in range(1, N+1):\\n print('String #{}'.format(tc))\\n for i in input():\\n tmp = ord(i)+1\\n print(chr(tmp) if tmp <= 90 else 'A', end='')\\n if tc == N: break\\n print('\\\\n')\"\n },\n {\n \"alpha_fraction\": 0.5736842155456543,\n \"alphanum_fraction\": 0.6052631735801697,\n \"avg_line_length\": 20.22222137451172,\n \"blob_id\": \"48fa14d179b07878114af8fa688e7f07997243aa\",\n \"content_id\": \"ff1400aa71db5a8f38a30eb0ca9760660ac8eac9\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 190,\n \"license_type\": \"no_license\",\n \"max_line_length\": 56,\n \"num_lines\": 9,\n \"path\": \"/알고리즘/온라인저지/2023/02/0204/끝말잇기.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"input()\\nresult = 1\\nwords = input().split()\\npalindrome = words[0][0]\\nfor word in words:\\n if word[0] != palindrome or word[-1] != palindrome: \\n result = 0\\n break\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.5263158082962036,\n \"alphanum_fraction\": 0.5263158082962036,\n \"avg_line_length\": 24.5,\n \"blob_id\": \"06c1e29cc75609b090847c86d43b1bdeacd0ae34\",\n \"content_id\": \"5590086b8620ad2f2f2a3e53b8625e85685d8907\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 152,\n \"license_type\": \"no_license\",\n \"max_line_length\": 42,\n \"num_lines\": 6,\n \"path\": \"/알고리즘/온라인저지/2023/01/0107/사탕 선생 고창영.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"T = int(input())\\nfor t in range(T):\\n input()\\n N = int(input())\\n arr = [int(input()) for _ in range(N)]\\n print('NO' if sum(arr)%N else 'YES')\"\n },\n {\n \"alpha_fraction\": 0.6027088165283203,\n \"alphanum_fraction\": 0.6139954924583435,\n \"avg_line_length\": 25.117647171020508,\n \"blob_id\": \"cb15499481384f67ce6d7be19b79140827ecedfc\",\n \"content_id\": \"35293e16c7169ad9befdd6333433fdada4b8cdb4\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 589,\n \"license_type\": \"no_license\",\n \"max_line_length\": 66,\n \"num_lines\": 17,\n \"path\": \"/알고리즘/온라인저지/2022/11/1113/최소 회의실 개수.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\nimport heapq\\n\\ninput = sys.stdin.readline\\n\\nN = int(input())\\narr = [list(map(int, input().rstrip().split())) for _ in range(N)]\\narr.sort(key=lambda x:x[0]) # 회의 시작 시간 기준 오름차순 정렬\\nrooms = [0] # 비어있는 회의실 하나로 시작\\nresult = 1 # 회의실은 한 개 이상 반드시 필요하다\\nfor s, e in arr:\\n if s >= rooms[0]: # 빈 회의실이 있다면\\n heapq.heappop(rooms)\\n else: # 빈 회의실이 없다면\\n result += 1 # 최소 회의실 개수 추가\\n heapq.heappush(rooms, e) # 회의를 시작하지\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.4049079716205597,\n \"alphanum_fraction\": 0.4171779155731201,\n \"avg_line_length\": 18.235294342041016,\n \"blob_id\": \"2a6ea32fdd66642bbe0e9562aaa155878592a4c0\",\n \"content_id\": \"c73a338b7051d98a9530f1da4753e01175510364\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 326,\n \"license_type\": \"no_license\",\n \"max_line_length\": 41,\n \"num_lines\": 17,\n \"path\": \"/알고리즘/온라인저지/2022/06/0602/양념 반 후라이드 반.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"A, B, C, X, Y = map(int, input().split())\\nx = min(X, Y)\\ny = max(X, Y)\\nresult = 0\\nif C > (A+B)//2:\\n result += A*X + B*Y\\nelse:\\n result += C*x*2\\n if X != Y:\\n if X > Y:\\n result += A*(y-x)\\n else:\\n result += B*(y-x)\\n tmp = C*y*2\\n if result > tmp:\\n result = tmp\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.35305342078208923,\n \"alphanum_fraction\": 0.4236641228199005,\n \"avg_line_length\": 17.75,\n \"blob_id\": \"fe906653bdfe93056c1e7e1c26a7f7eed12401e1\",\n \"content_id\": \"0637b9a16ce27162b9fd105ad5699ac80f84f5c9\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 524,\n \"license_type\": \"no_license\",\n \"max_line_length\": 36,\n \"num_lines\": 28,\n \"path\": \"/알고리즘/온라인저지/2022/03/0321/8진수 2진수.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"def oct_to_bin(x):\\n global result\\n dictt = {\\n '0': '000',\\n '1': '001',\\n '2': '010',\\n '3': '011',\\n '4': '100',\\n '5': '101',\\n '6': '110',\\n '7': '111',\\n }\\n # print(dictt[x])\\n return dictt[x]\\n\\nN = input()\\nif N == '0':\\n print(0)\\n exit()\\n# print(N, len(N))\\nresult = [''] * (len(N))\\n# print(result)\\nfor i in range(len(N)):\\n result[i] = oct_to_bin(N[i])\\n # print(result)\\nprint(result[0].lstrip('0'), end='')\\nfor r in result[1:]:\\n print(r, end='')\"\n },\n {\n \"alpha_fraction\": 0.52173912525177,\n \"alphanum_fraction\": 0.539130449295044,\n \"avg_line_length\": 13.5,\n \"blob_id\": \"0ffca1c2cba7af7d38899a033652919e9ca9935e\",\n \"content_id\": \"32a8cec44ca606761a704c94dda891ee177719c8\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 137,\n \"license_type\": \"no_license\",\n \"max_line_length\": 44,\n \"num_lines\": 8,\n \"path\": \"/알고리즘/SWEA/LEARN/Course/1. Programming Beginner/파이썬 프로그래밍 기초(2)/6차시 2. 자료구조 – 리스트, 튜플 - 연습문제 4.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"l = []\\n\\nfor i in range(5):\\n l.append(int(input()))\\n\\navg = sum(l)/5\\n\\nprint('입력된 값 {}의 평균은 {}입니다.'.format(l, avg))\"\n },\n {\n \"alpha_fraction\": 0.4297872483730316,\n \"alphanum_fraction\": 0.47659575939178467,\n \"avg_line_length\": 22.600000381469727,\n \"blob_id\": \"02d63904efaa4e50d16b1f03247fe37a6cd547ce\",\n \"content_id\": \"ea0ce9d749ad30b4e9f4bd1836cd76ccdc14e8fa\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 235,\n \"license_type\": \"no_license\",\n \"max_line_length\": 41,\n \"num_lines\": 10,\n \"path\": \"/알고리즘/온라인저지/2022/08/0827/럭비 클럽.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"result = ['Senior', 'Junior']\\nwhile True:\\n tmp = input()\\n if tmp == '# 0 0': break\\n M = tmp.split()\\n print(M[0], end=' ')\\n if int(M[1]) > 17 or int(M[2]) >= 80:\\n print(result[0])\\n else:\\n print(result[1])\"\n },\n {\n \"alpha_fraction\": 0.48630136251449585,\n \"alphanum_fraction\": 0.4931506812572479,\n \"avg_line_length\": 11.166666984558105,\n \"blob_id\": \"c4f7639e34470782d29768e0016833d1f3852b8e\",\n \"content_id\": \"9a980c670a15c519fdd03c50afc98d7a17f3432c\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 146,\n \"license_type\": \"no_license\",\n \"max_line_length\": 18,\n \"num_lines\": 12,\n \"path\": \"/알고리즘/온라인저지/2021/12/1213/소음.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"A = int(input())\\nope = input()\\nB = int(input())\\n\\nresult = 0\\n\\nif ope == '+':\\n result = A + B\\nelif ope == '*':\\n result = A * B\\n\\nprint(result)\\n\"\n },\n {\n \"alpha_fraction\": 0.4037036895751953,\n \"alphanum_fraction\": 0.4185185134410858,\n \"avg_line_length\": 21.58333396911621,\n \"blob_id\": \"609539741264b02181e82177bc6ca33fdfde4e18\",\n \"content_id\": \"55e7826b75a2500ccbc42998a034884566e65dad\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 270,\n \"license_type\": \"no_license\",\n \"max_line_length\": 33,\n \"num_lines\": 12,\n \"path\": \"/알고리즘/온라인저지/2023/04/0403/헤라클레스와 히드라.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"K = int(input())\\nfor tc in range(1, K+1):\\n H = int(input())\\n action = input()\\n for a in action:\\n if H:\\n if a == 'c': H += 1\\n elif a == 'b': H -= 1\\n else: break\\n print(f'Data Set {tc}:')\\n print(H)\\n if tc != K: print()\"\n },\n {\n \"alpha_fraction\": 0.3520749807357788,\n \"alphanum_fraction\": 0.3627844750881195,\n \"avg_line_length\": 43,\n \"blob_id\": \"8cc834de00fedce201770fc9a60d29d84a773398\",\n \"content_id\": \"eff96d7ea2361b9e9efdb761caad8fbae22a3604\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1013,\n \"license_type\": \"no_license\",\n \"max_line_length\": 64,\n \"num_lines\": 17,\n \"path\": \"/알고리즘/온라인저지/2021/08/0813/컵홀더.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"\\\"\\\"\\\"\\n컵홀더 개수 = 좌석수 - 커플석 개수 + 1\\n리스트 받아서 while문으로 리스트 탐색\\n\\\"\\\"\\\"\\nN = int(input()) # 좌석 수\\nseats = list(input()) # 좌석 리스트\\ni = 0 # 좌석 리스트 탐색 인덱스\\ncouple_go_to_hell = 0 # 커플석 개수 카운트\\nwhile i != len(seats): # 좌석 탐색 반복\\n if seats[i] == 'L': # 자리가 커플석이면\\n couple_go_to_hell += 1 # 커플석 카운트\\n i += 1 # 옆칸도 커플석이니까 한 칸 패스\\n i += 1 # 다음 좌석으로 ㄱㄱ\\nif N <= N - couple_go_to_hell + 1: # 커플석이 없으면\\n print(N) # 그냥 좌석수 출력\\nelse: # 커플석이 많아서 컵홀더가 좌석보다 적으면\\n print(N - couple_go_to_hell + 1) # 컵홀더개수 출력\"\n },\n {\n \"alpha_fraction\": 0.48120301961898804,\n \"alphanum_fraction\": 0.5037593841552734,\n \"avg_line_length\": 25.799999237060547,\n \"blob_id\": \"cc2f98d981d8cd0f0f0fc4bf6cc8b3426c92eeb4\",\n \"content_id\": \"066b1a686c24fd6e83ccaec74b26f921a3194690\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 133,\n \"license_type\": \"no_license\",\n \"max_line_length\": 36,\n \"num_lines\": 5,\n \"path\": \"/알고리즘/온라인저지/2022/08/0814/Abdelrahman.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"T = int(input())\\nfor t in range(1, T+1):\\n N, M = map(int, input().split())\\n result = M - (N-1)\\n print(f'Case {t}: {result}')\"\n },\n {\n \"alpha_fraction\": 0.4912280738353729,\n \"alphanum_fraction\": 0.5065789222717285,\n \"avg_line_length\": 23.052631378173828,\n \"blob_id\": \"73f4238470095f5afc28767fa20ba1413d39b1e7\",\n \"content_id\": \"7d34eb6cdb689eb8e038ba1b097bed082d77c682\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 456,\n \"license_type\": \"no_license\",\n \"max_line_length\": 38,\n \"num_lines\": 19,\n \"path\": \"/알고리즘/온라인저지/2023/01/0104/친구.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N, M = map(int, input().split())\\ndictt = {}\\nfor n in range(1, N+1):\\n dictt[n] = set()\\nfor _ in range(M):\\n A, B = map(int, input().split())\\n dictt[A].add(B)\\n dictt[B].add(A)\\nfor n in range(1, N+1):\\n print(len(dictt[n]))\\n\\n# N, M = map(int, input().split())\\n# arr = [set() for _ in range(N+1)]\\n# for m in range(M):\\n# A, B = map(int, input().split())\\n# arr[A].add(B)\\n# arr[B].add(A)\\n# for n in range(1, N+1):\\n# print(len(arr[n]))\"\n },\n {\n \"alpha_fraction\": 0.44999998807907104,\n \"alphanum_fraction\": 0.5,\n \"avg_line_length\": 17.81818199157715,\n \"blob_id\": \"27df47c51cb1b1cba93d06622823b436fa082b35\",\n \"content_id\": \"d54622dff050a05e0c029a49c176223e9022cc9a\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 840,\n \"license_type\": \"no_license\",\n \"max_line_length\": 63,\n \"num_lines\": 33,\n \"path\": \"/알고리즘/온라인저지/2021/07/0731/성실한 개미.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"num = 10\\nboard = [[int(x) for x in input().split()] for y in range(num)]\\n # 10 * 10 배열 받기\\n\\\"\\\"\\\"\\n스타트는 고정\\n개미가 있는 자리가 0이면 \\n 있는 자리를 9로 바꾸고\\n 그 오른쪽칸이 1이면 다음 경로를 한칸 아래로\\n 그 외에는 오른쪽으로\\n 2가 있는 자리에 도착할건데 만약 아닐수 있으니\\n 2인지 확인하고 9로 바꿔주고 코드 종료\\n\\\"\\\"\\\"\\n# 개미의 x, y좌표\\n# 인덱스에서는 [y][x]로 호출해야함\\ny = 1\\nx = 1\\nant = board[y][x]\\n\\nwhile board[y][x] == 0:\\n board[y][x] = 9\\n if board[y][x+1] == 1:\\n y += 1\\n elif board[y][x+1] == 0:\\n x += 1\\n elif board[y][x+1] == 2:\\n x += 1\\nif board[y][x] == 2:\\n board[y][x] = 9\\n\\nfor i in range(10):\\n for j in range(10): \\n print(board[i][j], end=' ')\\n print() # 출력문\"\n },\n {\n \"alpha_fraction\": 0.4735516309738159,\n \"alphanum_fraction\": 0.508816123008728,\n \"avg_line_length\": 14.920000076293945,\n \"blob_id\": \"f8164e7aae03792885c6b87ce456f7ad275e5d15\",\n \"content_id\": \"16502a4146021495b31a0e993b8701743b9f709d\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 397,\n \"license_type\": \"no_license\",\n \"max_line_length\": 39,\n \"num_lines\": 25,\n \"path\": \"/알고리즘/온라인저지/2022/01/0131/부녀회장이 될테야.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"T = int(input())\\n\\nks = []\\nns = []\\n\\nfor t in range(T):\\n ks.append(int(input()))\\n ns.append(int(input()))\\n\\nmaxk = max(ks)\\nmaxn = max(ns)\\n\\na = [[0]*maxn for _ in range(maxk+1)]\\n\\na[0] = list(range(1, maxn+1))\\n\\nfor i in range(maxk+1):\\n a[i][0] = 1\\n\\nfor i in range(1, maxk+1):\\n for j in range(1, maxn):\\n a[i][j] = a[i][j-1] + a[i-1][j]\\n\\nfor t in range(T):\\n print(a[ks[t]][ns[t]-1])\"\n },\n {\n \"alpha_fraction\": 0.5095447897911072,\n \"alphanum_fraction\": 0.5433186292648315,\n \"avg_line_length\": 28.65217399597168,\n \"blob_id\": \"1d7a8d8f9315853df1c2fa934226c96939dacf54\",\n \"content_id\": \"144e58f823f09ccd8f27229db96577726501c8a9\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 681,\n \"license_type\": \"no_license\",\n \"max_line_length\": 59,\n \"num_lines\": 23,\n \"path\": \"/알고리즘/온라인저지/2022/11/1114/중간계 전쟁.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\n\\ngandalf = [1, 2, 3, 3, 4, 10]\\nsauron = [1, 2, 2, 2, 3, 5, 10]\\nfor tc in range(1, int(input().rstrip())+1):\\n G = S = 0\\n gandalf_army = list(map(int, input().rstrip().split()))\\n for i in range(6):\\n G += gandalf[i]*gandalf_army[i]\\n sauron_army = list(map(int, input().rstrip().split()))\\n for i in range(7):\\n S += sauron[i]*sauron_army[i]\\n result = [\\n 'No victor on this battle field', # draw\\n 'Good triumphs over Evil', # gandalf win\\n 'Evil eradicates all trace of Good', # sauron win\\n ]\\n i = 0\\n if G > S: i = 1\\n elif G < S: i = 2\\n print('Battle {}: {}'.format(tc, result[i]))\"\n },\n {\n \"alpha_fraction\": 0.5714285969734192,\n \"alphanum_fraction\": 0.5789473652839661,\n \"avg_line_length\": 21.33333396911621,\n \"blob_id\": \"44ef0dabf4d89191120e9322ea20c69895822e9e\",\n \"content_id\": \"fb929a41de7ed1d07bc3ac86b303731aaf2ee064\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 133,\n \"license_type\": \"no_license\",\n \"max_line_length\": 41,\n \"num_lines\": 6,\n \"path\": \"/알고리즘/온라인저지/2023/05/0531/오버플로우와 모듈러.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N, M = map(int, input().split())\\nresult = 1\\nfor i in list(map(int, input().split())):\\n result *= i%M\\n result %= M\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.5465465188026428,\n \"alphanum_fraction\": 0.5705705881118774,\n \"avg_line_length\": 21.266666412353516,\n \"blob_id\": \"0a99b8bed350199c86e028108367a35c9ad79215\",\n \"content_id\": \"69d19f44fe94bb0697854c8a370c0b885952f3fd\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 333,\n \"license_type\": \"no_license\",\n \"max_line_length\": 39,\n \"num_lines\": 15,\n \"path\": \"/알고리즘/온라인저지/2021/08/0814/음계.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"notes = list(map(int, input().split()))\\nascending = 0\\ndescending = 0\\nfor i in range(1, len(notes)):\\n if notes[i-1] < notes[i]:\\n ascending += 1\\n else:\\n descending += 1\\nif ascending != 0 and descending != 0:\\n print('mixed')\\nelse:\\n if ascending:\\n print('ascending')\\n else:\\n print('descending')\"\n },\n {\n \"alpha_fraction\": 0.43448275327682495,\n \"alphanum_fraction\": 0.4689655303955078,\n \"avg_line_length\": 19.85714340209961,\n \"blob_id\": \"b04fba16166df29c221b5d00184e9acb22be15f2\",\n \"content_id\": \"ce8c0ed6cec8ac6912d86ef650be66549c3e2e5e\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 145,\n \"license_type\": \"no_license\",\n \"max_line_length\": 39,\n \"num_lines\": 7,\n \"path\": \"/알고리즘/온라인저지/2022/02/0207/카이사르 암호.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"word = input()\\n\\nfor w in word:\\n if ord(w)-3 < ord('A'):\\n print(chr(ord(w)-3+26), end='')\\n else:\\n print(chr(ord(w)-3), end='')\"\n },\n {\n \"alpha_fraction\": 0.3789346218109131,\n \"alphanum_fraction\": 0.39830508828163147,\n \"avg_line_length\": 18.690475463867188,\n \"blob_id\": \"87b794f2384746ab712e13c8cb075e2fa93092a3\",\n \"content_id\": \"265e74ebcb1b3d3677c2f87d75289616b159e6f6\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 826,\n \"license_type\": \"no_license\",\n \"max_line_length\": 45,\n \"num_lines\": 42,\n \"path\": \"/알고리즘/SWEA/LEARN/Course/2. Programming Intermediate/6. 파이썬 SW문제해결 기본 Queue/8차시 6일차 - 노드의 거리.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"T = int(input())\\n\\nfor t in range(1, T+1):\\n V, E = map(int, input().split())\\n \\n arr = [[] for _ in range(V+1)]\\n\\n for e in range(E):\\n a, b = map(int, input().split())\\n arr[a].append(b)\\n arr[b].append(a)\\n \\n S, G = map(int, input().split())\\n\\n visited = [0] * (V+1)\\n cnt = 0\\n\\n q = [arr[S]+[cnt]]\\n visited[S] = 1\\n result = 0\\n found = False\\n\\n while q:\\n tmp = q.pop(0)\\n cnt = tmp[-1]\\n if found:\\n break\\n\\n for i in range(len(tmp)-1):\\n if tmp[i] == G:\\n result = cnt+1\\n found = True\\n break\\n\\n if visited[tmp[i]] == 0:\\n q.append(arr[tmp[i]]+[cnt+1])\\n visited[tmp[i]] = 1\\n\\n if S == G:\\n result = 0\\n\\n print('#{} {}'.format(t, result))\"\n },\n {\n \"alpha_fraction\": 0.3980582654476166,\n \"alphanum_fraction\": 0.4417475759983063,\n \"avg_line_length\": 33.5,\n \"blob_id\": \"074d601470bd3339232040a939dd18dd09d237b9\",\n \"content_id\": \"6f6693ce788e50fbbeab0717c4e0ca5be097803d\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 306,\n \"license_type\": \"no_license\",\n \"max_line_length\": 53,\n \"num_lines\": 6,\n \"path\": \"/알고리즘/온라인저지/2021/07/0730/[기초-산술연산] 정수 2개 입력받아 차 계산하기.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"a = input() # -> 123\\nb = input() # -> -123\\nc = int(a) - int(b) # 입력받은 문자열 a와 b를 int로 바꿔주고 뻴셈\\nprint(c) # -> 246\\n# 깃, 커밋은 양보다 질\\n# 한 문제를 올려도, 정말 고민하고 의미있게 풀은 문제들을 올리자\"\n },\n {\n \"alpha_fraction\": 0.5729166865348816,\n \"alphanum_fraction\": 0.5763888955116272,\n \"avg_line_length\": 21.230770111083984,\n \"blob_id\": \"6d3d751f018fb0ce3334b74fd1beaa0ac3a42ba9\",\n \"content_id\": \"6610edd5b21e7fac78a568fa6c20e12dfb9d90f6\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 288,\n \"license_type\": \"no_license\",\n \"max_line_length\": 40,\n \"num_lines\": 13,\n \"path\": \"/알고리즘/온라인저지/2022/12/1204/파일 완전 삭제.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = int(input())\\nfiles = list(map(int, list(input())))\\nresult = ''\\nfor i in range(len(files)):\\n if N%2:\\n result += str(int(not files[i]))\\n else:\\n result += str(files[i])\\ntmp = input()\\nif result == tmp:\\n print('Deletion succeeded')\\nelse:\\n print('Deletion failed')\"\n },\n {\n \"alpha_fraction\": 0.5380434989929199,\n \"alphanum_fraction\": 0.570652186870575,\n \"avg_line_length\": 19.55555534362793,\n \"blob_id\": \"97a8785a82727cefada1319277f22dfe712284fc\",\n \"content_id\": \"41e60587370956a8762eeb785b45ee431a3d4215\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 184,\n \"license_type\": \"no_license\",\n \"max_line_length\": 45,\n \"num_lines\": 9,\n \"path\": \"/알고리즘/온라인저지/2023/03/0308/노 땡스!.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = int(input())\\narr = sorted(list(map(int, input().split())))\\nlast_plus_1 = 0\\nresult = 0\\nfor a in arr:\\n if a != last_plus_1:\\n result += a\\n last_plus_1 = a+1\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.5068492889404297,\n \"alphanum_fraction\": 0.5369862914085388,\n \"avg_line_length\": 17.299999237060547,\n \"blob_id\": \"5674f65e6c276720abef73f6eef229b84963d3dc\",\n \"content_id\": \"4c6f05b2b4a6e283efde43654841a258c98a3f74\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 365,\n \"license_type\": \"no_license\",\n \"max_line_length\": 36,\n \"num_lines\": 20,\n \"path\": \"/알고리즘/온라인저지/2022/07/0712/트리의 부모 찾기.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\nsys.setrecursionlimit(99999)\\n\\n\\ndef dfs(i):\\n for n in nodes[i]:\\n if not parents[n]:\\n parents[n] = i\\n dfs(n)\\n\\n\\nN = int(input())\\nnodes = [[] for _ in range(N+1)]\\nparents = [0] * (N+1)\\nfor n in range(N-1):\\n s, e = map(int, input().split())\\n nodes[s].append(e)\\n nodes[e].append(s)\\ndfs(1)\\nfor p in parents[2:]: print(p)\"\n },\n {\n \"alpha_fraction\": 0.38985738158226013,\n \"alphanum_fraction\": 0.4088748097419739,\n \"avg_line_length\": 22.370370864868164,\n \"blob_id\": \"d5e77ae4f623572b1ace0c7e6fbc619cb623356f\",\n \"content_id\": \"cedb0cc1c95bb36174d8034faea9734680b72c64\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 631,\n \"license_type\": \"no_license\",\n \"max_line_length\": 45,\n \"num_lines\": 27,\n \"path\": \"/알고리즘/온라인저지/2021/08/0822/딱지놀이.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = int(input())\\nfor tc in range(N):\\n A_cards = list(map(int, input().split()))\\n A_count = A_cards.pop(0)\\n B_cards = list(map(int, input().split()))\\n B_count = B_cards.pop(0)\\n A_cards.sort()\\n B_cards.sort()\\n A = [0] * 5 \\n B = [0] * 5\\n for a in A_cards:\\n A[a] += 1\\n for b in B_cards:\\n B[b] += 1\\n winner = ''\\n for i in range(4, -1, -1):\\n if i == 0:\\n winner = 'D'\\n if A[i] > B[i]:\\n winner = 'A'\\n break\\n elif A[i] == B[i]:\\n continue\\n elif A[i] < B[i]:\\n winner = 'B'\\n break\\n print(winner)\\n\"\n },\n {\n \"alpha_fraction\": 0.5591397881507874,\n \"alphanum_fraction\": 0.5806451439857483,\n \"avg_line_length\": 17.799999237060547,\n \"blob_id\": \"654d1ed2b9eb1322656e01ae0932c1719a69a8c9\",\n \"content_id\": \"c850664c96342e3368085908d7532bbae9f40ab7\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 93,\n \"license_type\": \"no_license\",\n \"max_line_length\": 32,\n \"num_lines\": 5,\n \"path\": \"/알고리즘/온라인저지/2022/09/0907/母音を数える (Counting Vowels).py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N, S = input(), input()\\nresult = 0\\nfor s in S:\\n if s in 'aeiou': result += 1\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.540123462677002,\n \"alphanum_fraction\": 0.595678985118866,\n \"avg_line_length\": 39.625,\n \"blob_id\": \"59376e7d942beffa1ca176e04b9526eed994e2e8\",\n \"content_id\": \"b3b651ee76c6ab01914d2e04379e2fa0a01b255e\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 324,\n \"license_type\": \"no_license\",\n \"max_line_length\": 58,\n \"num_lines\": 8,\n \"path\": \"/알고리즘/온라인저지/2022/10/1012/Mini Fantasy War.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"for _ in range(int(input())):\\n inputs = list(map(int, input().split()))\\n stats = []\\n stats.append(max(1, inputs[0]+inputs[4]))\\n stats.append(max(1, inputs[1]+inputs[5]))\\n stats.append(max(0, inputs[2]+inputs[6]))\\n stats.append(inputs[3]+inputs[7])\\n print(stats[0] + stats[1]*5 + stats[2]*2 + stats[3]*2)\"\n },\n {\n \"alpha_fraction\": 0.4203979969024658,\n \"alphanum_fraction\": 0.44029849767684937,\n \"avg_line_length\": 24.0625,\n \"blob_id\": \"6f4ba5881baad944af19c1cd9963f67c97e2cd9c\",\n \"content_id\": \"0f3f6651ada2655d733f04174a785f0530d42ff1\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 402,\n \"license_type\": \"no_license\",\n \"max_line_length\": 43,\n \"num_lines\": 16,\n \"path\": \"/알고리즘/온라인저지/2022/02/0204/ROT13.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"sen = input()\\n\\nfor s in sen:\\n o = ord(s)\\n if s in 'ABCDEFGHIJKLMNOPQRSTUVWXYZ':\\n if o <= ord('M'):\\n print(chr(o + 13), end='')\\n else:\\n print(chr(o - 13), end='')\\n elif s in 'abcdefghijklmnopqrstuvwxyz':\\n if o >= ord('n'):\\n print(chr(o - 13), end='')\\n else:\\n print(chr(o + 13), end='')\\n else:\\n print(s, end='')\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.4649122953414917,\n \"alphanum_fraction\": 0.5350877046585083,\n \"avg_line_length\": 9.363636016845703,\n \"blob_id\": \"da6070e8c56bce5c816f37104b49fa4025897b1e\",\n \"content_id\": \"ceabc03666e6cc547f5c2554490a295f304672e9\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 114,\n \"license_type\": \"no_license\",\n \"max_line_length\": 22,\n \"num_lines\": 11,\n \"path\": \"/알고리즘/온라인저지/2022/01/0131/열 개씩 끊어 출력하기.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"sen = input()\\n\\ni = 10\\n\\nlenn = len(sen)\\n\\nwhile i < lenn:\\n print(sen[i-10:i])\\n i += 10\\n\\nprint(sen[i-10:lenn])\\n\"\n },\n {\n \"alpha_fraction\": 0.3687500059604645,\n \"alphanum_fraction\": 0.41874998807907104,\n \"avg_line_length\": 13.636363983154297,\n \"blob_id\": \"f2aec11634e7af6ae5ddc2f96284c75470aaf718\",\n \"content_id\": \"25f52b889ebe1d052db7a921757a4a9cc5f2c5aa\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 160,\n \"license_type\": \"no_license\",\n \"max_line_length\": 19,\n \"num_lines\": 11,\n \"path\": \"/알고리즘/온라인저지/2022/04/0406/3n+1 수열.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = int(input())\\nresult = 0\\nwhile True:\\n if N == 1:\\n break\\n if N % 2:\\n N = N*3 + 1\\n else:\\n N //= 2\\n result += 1\\nprint(result+1)\"\n },\n {\n \"alpha_fraction\": 0.4918699264526367,\n \"alphanum_fraction\": 0.5081300735473633,\n \"avg_line_length\": 18,\n \"blob_id\": \"376dae1f54760f0650d74cd5e194527938eadd47\",\n \"content_id\": \"3ee57821aee9c98b2894dba70c6ed44574f2df8a\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 246,\n \"license_type\": \"no_license\",\n \"max_line_length\": 35,\n \"num_lines\": 13,\n \"path\": \"/알고리즘/온라인저지/2022/09/0901/회전하는 큐.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N, _ = map(int, input().split())\\nM = list(map(int, input().split()))\\nN = list(range(1, N+1))\\nprev = 0\\nresult = 0\\nfor m in M:\\n i = N.index(m)\\n D = abs(prev - i)\\n D = min(D, len(N)-D)\\n result += D\\n N.pop(i)\\n prev = i\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.32826748490333557,\n \"alphanum_fraction\": 0.4559270441532135,\n \"avg_line_length\": 11.692307472229004,\n \"blob_id\": \"c93b2bf7fe73a6474a83a5d80f7b5cf25f818aa9\",\n \"content_id\": \"20ca2229d9415f35cf5ecf6a7db53f47cac3094c\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 329,\n \"license_type\": \"no_license\",\n \"max_line_length\": 44,\n \"num_lines\": 26,\n \"path\": \"/알고리즘/온라인저지/2022/02/0220/타일 장식물.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"\\\"\\\"\\\"\\n1 : 1+1+1+1\\n2 : 4-1+1+1+1\\n3 : 6-2+2+2+2\\n4 : 10-3+3+3+3\\n5 : \\n1 : \\n\\\"\\\"\\\"\\n\\nN = int(input())\\n\\nresult = [0, 4]\\n\\ndp = [0, 1]\\n\\nif N >= 2:\\n for i in range(2, N+1):\\n dp.append(dp[i-1] + dp[i-2])\\n\\n for i in range(2, N+1):\\n result.append(result[i-1] + dp[i]*2)\\n\\nif result == 1:\\n print(4)\\nelse:\\n print(result[-1])\"\n },\n {\n \"alpha_fraction\": 0.4178321659564972,\n \"alphanum_fraction\": 0.45279720425605774,\n \"avg_line_length\": 23.913043975830078,\n \"blob_id\": \"1465176bef6fd75580d4ba2386ca304d98343832\",\n \"content_id\": \"1f8f4d4ee7386d933c855d923f70308802e0e710\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 572,\n \"license_type\": \"no_license\",\n \"max_line_length\": 55,\n \"num_lines\": 23,\n \"path\": \"/알고리즘/온라인저지/2021/08/0829/색종이.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\nN = int(sys.stdin.readline())\\nboard = [[0]*1002 for _ in range(1002)]\\nmax_y = 0\\nmax_x = 0\\nfor n in range(1, N+1):\\n Y, X, H, W = map(int, sys.stdin.readline().split())\\n for y in range(Y, Y+H):\\n for x in range(X, X+W):\\n board[y][x] = n\\n if max_y < y:\\n max_y = y\\n if max_x < x:\\n max_x = x\\nresult = [0] * N\\nfor n in range(1, N+1):\\n for i in range(max_y+1):\\n for j in range(max_x+1):\\n if board[i][j] == n:\\n result[n-1] += 1\\nfor r in result:\\n print(r)\"\n },\n {\n \"alpha_fraction\": 0.5398229956626892,\n \"alphanum_fraction\": 0.5575221180915833,\n \"avg_line_length\": 18,\n \"blob_id\": \"83f17923ca52fd7982129ddbfa25632c9ced2d20\",\n \"content_id\": \"b439f5c8d8838c387fba45109029975454307d38\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 113,\n \"license_type\": \"no_license\",\n \"max_line_length\": 29,\n \"num_lines\": 6,\n \"path\": \"/알고리즘/온라인저지/2022/12/1229/MBTI.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"MBTI = input()\\nresult = 0\\nfor _ in range(int(input())):\\n if MBTI == input():\\n result += 1\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.5419161915779114,\n \"alphanum_fraction\": 0.5958083868026733,\n \"avg_line_length\": 16.63157844543457,\n \"blob_id\": \"805c02f08f828ee25383f6d3a365d3e7c7719cac\",\n \"content_id\": \"ce2d015034a6b8fe30fb183d2ad5b82120459c1b\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 344,\n \"license_type\": \"no_license\",\n \"max_line_length\": 41,\n \"num_lines\": 19,\n \"path\": \"/알고리즘/온라인저지/2022/10/1006/병든 나이트.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\n\\nN, M = map(int, input().rstrip().split())\\nresult = 0\\nif N == 1: result = 1\\nelif N == 2: result = min(4, (M+1)//2)\\nelse: # N >= 3\\n if M < 7: result = min(4, M)\\n else: result = M-2\\nprint(result)\\n\\n\\\"\\\"\\\"\\n<참고한 링크>\\nhttps://pacific-ocean.tistory.com/354\\n\\\"\\\"\\\"\\n\\n# https://www.acmicpc.net/problem/1783\"\n },\n {\n \"alpha_fraction\": 0.3558441698551178,\n \"alphanum_fraction\": 0.3636363744735718,\n \"avg_line_length\": 15.782608985900879,\n \"blob_id\": \"8e504ff8c1ed1e7bc665e89545a008c1fd766144\",\n \"content_id\": \"44f8935b3eef84ba35e6716e1b9657c4c438c336\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 385,\n \"license_type\": \"no_license\",\n \"max_line_length\": 42,\n \"num_lines\": 23,\n \"path\": \"/알고리즘/온라인저지/2022/11/1123/우유가 넘어지면.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\n\\nrotate = {\\n \\\".\\\": \\\".\\\",\\n \\\"O\\\": \\\"O\\\",\\n \\\"-\\\": \\\"|\\\",\\n \\\"|\\\": \\\"-\\\",\\n \\\"/\\\": \\\"\\\\\\\\\\\",\\n \\\"\\\\\\\\\\\": \\\"/\\\",\\n \\\"^\\\": \\\"<\\\",\\n \\\"<\\\": \\\"v\\\",\\n \\\"v\\\": \\\">\\\",\\n \\\">\\\": \\\"^\\\",\\n}\\n\\nN, M = map(int, input().rstrip().split())\\narr = [input().rstrip() for _ in range(N)]\\nfor j in range(M-1, -1, -1):\\n for i in range(N):\\n print(rotate[arr[i][j]], end='')\\n print()\"\n },\n {\n \"alpha_fraction\": 0.42657342553138733,\n \"alphanum_fraction\": 0.4545454680919647,\n \"avg_line_length\": 19.5,\n \"blob_id\": \"05b68bb8397d837db3c96a0bd201e80d5af0b9ce\",\n \"content_id\": \"cee7965588ac63f029fdf4c57d8d1a40bf33ed2f\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 336,\n \"license_type\": \"no_license\",\n \"max_line_length\": 32,\n \"num_lines\": 14,\n \"path\": \"/알고리즘/온라인저지/2021/08/0803/사분면 고르기.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"x = int(input()) # x와\\ny = int(input()) # y값을 int로 받아서 \\nquadrant = 0 # 사분면 값을 초기화해주고\\nif x >= 0:\\n if y >= 0:\\n quadrant = 1 # + +\\n else:\\n quadrant = 4 # + -\\nelse:\\n if y >= 0:\\n quadrant = 2 # - +\\n else:\\n quadrant = 3 # - -\\nprint(quadrant) # 사분면 값을 출력\"\n },\n {\n \"alpha_fraction\": 0.43379446864128113,\n \"alphanum_fraction\": 0.45059287548065186,\n \"avg_line_length\": 27.13888931274414,\n \"blob_id\": \"c85ba4be0659933352281f162df7e30785b7ba3d\",\n \"content_id\": \"9905f6c3c6635a07cbcc2f56eaa345dd6159fca7\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1012,\n \"license_type\": \"no_license\",\n \"max_line_length\": 62,\n \"num_lines\": 36,\n \"path\": \"/알고리즘/온라인저지/2021/08/0829/주사위 쌓기.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ndice_count = int(sys.stdin.readline())\\ndices = []\\nfor d in range(dice_count):\\n dices.append(list(map(int, sys.stdin.readline().split())))\\nresult = 0\\nfor j in range(6):\\n max_sum = 0\\n up = 0\\n for i in range(dice_count):\\n dice_opposite = {\\n dices[i][0]:dices[i][5], \\n dices[i][1]:dices[i][3],\\n dices[i][2]:dices[i][4],\\n dices[i][3]:dices[i][1],\\n dices[i][4]:dices[i][2],\\n dices[i][5]:dices[i][0]\\n }\\n tmp = [*dices[i]]\\n try:\\n if up == 0:\\n tmp.remove(dices[i][j])\\n tmp.remove(dice_opposite[dices[i][j]])\\n up = dice_opposite[dices[i][j]]\\n max_sum += max(tmp)\\n else:\\n tmp.remove(up)\\n tmp.remove(dice_opposite[up])\\n up = dice_opposite[up]\\n max_sum += max(tmp)\\n except:\\n pass\\n if result < max_sum:\\n result = max_sum\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.5882353186607361,\n \"alphanum_fraction\": 0.5882353186607361,\n \"avg_line_length\": 35.25,\n \"blob_id\": \"4f39cc3ffa1fc9b8a155db24042ee4117aa8bdc5\",\n \"content_id\": \"13461c3ae9d201b056b0928d875654620ae879ea\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 437,\n \"license_type\": \"no_license\",\n \"max_line_length\": 56,\n \"num_lines\": 8,\n \"path\": \"/알고리즘/온라인저지/2021/08/0803/X보다 작은 수.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N, X = map(int, input().split()) # N은 왜준거지? 모르겠다\\nA = list(map(int, input().split())) # 수열을 입력받아서 리스트로 만들고\\nresult = [] # 결과값을 초기화하고\\nfor a in A: # 수열을 순회하면서\\n if a < X: # X보다 작은 수는\\n result.append(a) # 결과값에 추가\\nfor res in result: # 결과값 수열을 순회하면서\\n print(res, end=' ') # 띄어쓰기 간격으로 출력\"\n },\n {\n \"alpha_fraction\": 0.481675386428833,\n \"alphanum_fraction\": 0.5078533887863159,\n \"avg_line_length\": 11.800000190734863,\n \"blob_id\": \"9c0d56d6542133b0885779e26c784f764479c824\",\n \"content_id\": \"82fe8cc20233b606ef7e4909072f36528ea78363\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 191,\n \"license_type\": \"no_license\",\n \"max_line_length\": 40,\n \"num_lines\": 15,\n \"path\": \"/알고리즘/온라인저지/2022/02/0220/행복.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = int(input())\\n\\nscores = list(map(int, input().split()))\\n\\nmaxx = 0\\nminn = 1000\\n\\nfor s in scores:\\n if s >= maxx:\\n maxx = s\\n \\n if s <= minn:\\n minn = s\\n\\nprint(maxx-minn)\"\n },\n {\n \"alpha_fraction\": 0.5213675498962402,\n \"alphanum_fraction\": 0.5897436141967773,\n \"avg_line_length\": 13.75,\n \"blob_id\": \"cd28b5f866cd7215eb883ba25475f7a44b895132\",\n \"content_id\": \"d1c5fca7afb793b1a4e387892a171233dbe51ce6\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 117,\n \"license_type\": \"no_license\",\n \"max_line_length\": 40,\n \"num_lines\": 8,\n \"path\": \"/알고리즘/온라인저지/2022/02/0203/네 수.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"nums1 = input().split()\\n\\nresult = 0\\n\\nfor i in range(0, 4, 2):\\n result += int(nums1[i] + nums1[i+1])\\n\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.29192546010017395,\n \"alphanum_fraction\": 0.3913043439388275,\n \"avg_line_length\": 12.5,\n \"blob_id\": \"b45db5ce4065a63ba1be19a16a1bc3d0c81c70ad\",\n \"content_id\": \"aa8f2197092b708dad2b9d21c94d67141fadb7a3\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 161,\n \"license_type\": \"no_license\",\n \"max_line_length\": 30,\n \"num_lines\": 12,\n \"path\": \"/알고리즘/SWEA/LEARN/Course/1. Programming Beginner/파이썬 프로그래밍 기초(2)/20차시 2. 자료구조 – 리스트, 튜플 - 연습문제 22.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"x = [5, 6, 77, 45, 22, 12, 24]\\n\\ni = 0\\nwhile True:\\n if x[i]%2 == 0:\\n x.remove(x[i])\\n else:\\n i += 1\\n if i == len(x):\\n break\\n\\nprint(x)\"\n },\n {\n \"alpha_fraction\": 0.46783626079559326,\n \"alphanum_fraction\": 0.46783626079559326,\n \"avg_line_length\": 18.11111068725586,\n \"blob_id\": \"2cdc85add6b18fe4b5ee54d4b3db7b1a6221571c\",\n \"content_id\": \"619458b2400cbd2bece94328f59b1b25feaa621a\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 171,\n \"license_type\": \"no_license\",\n \"max_line_length\": 32,\n \"num_lines\": 9,\n \"path\": \"/알고리즘/온라인저지/2022/02/0206/대소문자 바꾸기.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"sen = input()\\n\\nfor s in sen:\\n if s.isupper():\\n print(s.lower(), end='')\\n elif s.islower():\\n print(s.upper(), end='')\\n else:\\n print(s, end='')\"\n },\n {\n \"alpha_fraction\": 0.4260089695453644,\n \"alphanum_fraction\": 0.4506726562976837,\n \"avg_line_length\": 26.9375,\n \"blob_id\": \"451c7d5e60aef773ade8e8613c3480b8acfc55b6\",\n \"content_id\": \"86b634d8298052d43c40d5407b0e9bd593658394\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 446,\n \"license_type\": \"no_license\",\n \"max_line_length\": 63,\n \"num_lines\": 16,\n \"path\": \"/알고리즘/온라인저지/2022/06/0617/박스.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"def down():\\n global result\\n for i in range(N-2, -1, -1):\\n for j in range(M):\\n if arr[i][j] == 1 and arr[i+1][j] == 0:\\n arr[i][j], arr[i+1][j] = arr[i+1][j], arr[i][j]\\n result += 1\\n\\nT = int(input())\\nfor t in range(T):\\n N, M = map(int, input().split())\\n arr = [list(map(int, input().split())) for _ in range(N)]\\n result = 0\\n for n in range(N-1):\\n down() \\n print(result)\"\n },\n {\n \"alpha_fraction\": 0.5649717450141907,\n \"alphanum_fraction\": 0.5762711763381958,\n \"avg_line_length\": 26.30769157409668,\n \"blob_id\": \"559e249b4f56abfae6ee86d48ffd17124162e203\",\n \"content_id\": \"7c1d976cbfeda2d7704267f3149434c1c5af0e28\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 468,\n \"license_type\": \"no_license\",\n \"max_line_length\": 54,\n \"num_lines\": 13,\n \"path\": \"/알고리즘/온라인저지/2022/04/0417/차이를 최대로.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from itertools import permutations\\n\\nN = int(input())\\ntmp = list(map(int, input().split()))\\nperm = list(permutations(tmp, N)) # 배열에서 나올 수 있는 모든 경우\\nmaxx = 0 # \\\"차이를 최대로\\\"\\nfor p in perm:\\n a = 0 # 해당 배열의 최대값 초기화\\n for i in range(N-1):\\n a += abs(p[i]-p[i+1]) # 앞뒤 값의 절대값 더하기\\n if a > maxx: # 최대값 갱신이 가능하면\\n maxx = a # 최대값 갱신\\nprint(maxx) # 출력\"\n },\n {\n \"alpha_fraction\": 0.5613811016082764,\n \"alphanum_fraction\": 0.5664961934089661,\n \"avg_line_length\": 47.9375,\n \"blob_id\": \"b8b1e39f9adcd95e6d957f99cbdd5aca7328ecf2\",\n \"content_id\": \"833231e7898ce1f63534f3e1297c46a67cebdf10\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 968,\n \"license_type\": \"no_license\",\n \"max_line_length\": 90,\n \"num_lines\": 16,\n \"path\": \"/알고리즘/프로그래머스/Level1/신고 결과 받기.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"def solution(id_list, report, k):\\n answer = [0] * len(id_list) # 정답 배열\\n report_list = [[] for _ in range(len(id_list))] # 신고받은 목록\\n black_list = [0] * len(id_list) # 신고받은 횟수\\n for r in report:\\n user, reported = r.split() # 공백을 간격으로, 유저, 피신고자\\n if reported not in report_list[id_list.index(user)]: # 중복 신고 방지, 아직 신고 받은 적 없는지 확인\\n report_list[id_list.index(user)].append(reported) # 신고 받은 목록 추가\\n black_list[id_list.index(reported)] += 1 # 신고 받은 횟수 추가\\n # print(id_list, report, k) # 디버깅\\n # print(report_list, black_list) # 디버깅\\n for i in range(len(id_list)): # 해당 유저가\\n for a in report_list[i]: # 신고한 사람이\\n if black_list[id_list.index(a)] >= k: # k번 이상 신고 되었을 때\\n answer[i] += 1 # 제재완료\\n return answer\"\n },\n {\n \"alpha_fraction\": 0.5055928230285645,\n \"alphanum_fraction\": 0.5548098683357239,\n \"avg_line_length\": 27,\n \"blob_id\": \"5cf550c23cade46acc6a48779641bd04b1539374\",\n \"content_id\": \"e54f7018f7b512051f5e6aeb599b5451abf422b3\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 677,\n \"license_type\": \"no_license\",\n \"max_line_length\": 44,\n \"num_lines\": 16,\n \"path\": \"/알고리즘/온라인저지/2021/08/0811/거스름돈.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"\\\"\\\"\\\"\\n1000엔에서 물건값 빼고\\n거스름돈을 거슬러주면 된다\\n동전의 최소개수\\\"\\\"\\\"\\nprice = int(input()) # 물건의 가격\\nchange = 1000-price # 거스름돈\\ncoins = [500, 100, 50, 10, 5, 1] # 동전들\\ncount = 0 # 동전의 개수 초기화\\nfor coin in coins: # 동전들을 금액이 큰 순서로 순회하면서\\n if coin <= change: # 거슬러줄 수 있으면\\n while True:\\n change -= coin # 해당 동전을 하나 거슬러주고\\n count += 1 # 동전 개수 증가\\n if coin > change: # 거슬러주지 못하면\\n break # 종료하고 다음 작은 동전으로\\nprint(count) # 동전 개수 출력\"\n },\n {\n \"alpha_fraction\": 0.4670184552669525,\n \"alphanum_fraction\": 0.4854881167411804,\n \"avg_line_length\": 19,\n \"blob_id\": \"a77b5d42f948a58e61778e036c0a0fc78d26e14e\",\n \"content_id\": \"fbcf9f955be9e09b86c9c9776267e6f533315481\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 379,\n \"license_type\": \"no_license\",\n \"max_line_length\": 36,\n \"num_lines\": 19,\n \"path\": \"/알고리즘/온라인저지/2021/08/0822/방 배정.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N, K = map(int, input().split())\\narr = [[0]*2 for _ in range(6)]\\nfor n in range(N):\\n S, Y = map(int, input().split())\\n arr[Y-1][S] += 1\\nnew_arr = []\\nfor ar in arr:\\n for a in ar:\\n new_arr.append(a)\\nresult = 0\\nfor ar in new_arr:\\n if ar > K: \\n result += ar//K\\n ar = ar%K\\n if not ar:\\n continue\\n else:\\n result += 1\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.6321070194244385,\n \"alphanum_fraction\": 0.654403567314148,\n \"avg_line_length\": 21.450000762939453,\n \"blob_id\": \"b0efe938fe583d8c6f34c96e41c0a659aff0b767\",\n \"content_id\": \"53a7e22be4a1902e58c9e16ff5ad37c8973e0c78\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1527,\n \"license_type\": \"no_license\",\n \"max_line_length\": 41,\n \"num_lines\": 40,\n \"path\": \"/알고리즘/온라인저지/2022/10/1002/1로 만들기 2.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\nfrom collections import deque\\n\\ninput = sys.stdin.readline\\n\\nN = int(input().rstrip())\\nQ = deque()\\nQ.append([N])\\nresult = []\\nwhile Q:\\n now = Q.popleft()\\n X = now[-1]\\n if X == 1: result = now; break\\n if X % 3 == 0: Q.append(now + [X//3])\\n if X % 2 == 0: Q.append(now + [X//2])\\n Q.append(now + [X-1])\\nprint(len(result)-1)\\nprint(*result)\\n\\n\\\"\\\"\\\"\\n3으로 나누고, 2로 나누고, 1을 빼는\\n탐색기록 그 자체를 큐에 담으며 진행함\\n1에 도착했을 때의 탐색기록이 결과가 됨\\n스페셜저지 이므로 답은 아무거나 상관이 없음\\n해당 코드는 top-down DP코드이지만\\n1에서 출발하여 N까지 가는 bottom-up 코드를 짤 수도 있음\\n하지만 *연산보다 //연산이 시간이 조금 더 빠를지도..?\\nDP의 개념은 매우 단순함\\n\\\"계산한 값을 기억했다가 다시 사용한다\\\"\\n본디 다이나믹 프로그래밍이라는 이름 자체가\\n별 뜻이 없고, 만든 사람이 그냥 어그로성으로 붙인 이름이라고 함\\n한 번 계산된 값을 기록하여 재활용하는 알고리즘을 전부 DP로 봄\\n특징으로는, 계산된 값을 날리지 않고 들고 있는만큼\\n메모리가 많이 필요함\\n해당 코드는 수많은 리스트들이 Q에 들어가는 것처럼 보이지만\\n시간이 logN으로 빠른 이(二)분탐색보다 훨씬 빠른\\n코드상 삼(三)분탐색을 사용하므로 \\n저렇게 넘치게 Q에 append 하는 것처럼 보여도 메모리는 괜찮다\\n\\\"\\\"\\\"\\n# https://www.acmicpc.net/problem/12852\"\n },\n {\n \"alpha_fraction\": 0.6751269102096558,\n \"alphanum_fraction\": 0.6751269102096558,\n \"avg_line_length\": 32,\n \"blob_id\": \"50bece0232b422491a7a6d8808a441a22cd0ba13\",\n \"content_id\": \"44e30ccea0f8e6da6aa462490d436e9cbacc8783\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 197,\n \"license_type\": \"no_license\",\n \"max_line_length\": 48,\n \"num_lines\": 6,\n \"path\": \"/알고리즘/온라인저지/2023/01/0128/줄 세우기.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"players = [input() for _ in range(int(input()))]\\nif players == sorted(players):\\n print('INCREASING')\\nelif players == sorted(players, reverse=True):\\n print('DECREASING')\\nelse: print('NEITHER')\"\n },\n {\n \"alpha_fraction\": 0.5317515730857849,\n \"alphanum_fraction\": 0.5415213108062744,\n \"avg_line_length\": 30.866666793823242,\n \"blob_id\": \"66c5d2db3902be5a3155bf5fce3ae62a30239505\",\n \"content_id\": \"720a9223315b3822c2c2c1a8050f5549b954148b\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 2215,\n \"license_type\": \"no_license\",\n \"max_line_length\": 62,\n \"num_lines\": 45,\n \"path\": \"/알고리즘/온라인저지/2022/08/0812/외판원 순회 2.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"def dfs(start, now):\\n global result, tmp\\n if tmp > result: return # 백트래킹\\n for next in range(N): # 다음 방문 지점\\n # 다음 방문할 지점이 지금 지점과 다르고\\n # 방문한 적이 없으며\\n # 방문을 할 수 있을 때(W배열에 값이 존재할 때)\\n if now != next and not visited[next] and W[now][next]:\\n visited[next] = 1 # 다음 지점 방문 찍고\\n tmp += W[now][next] # 그 지점의 코스트를 더하고\\n dfs(start, next) # 해당 지점 탐색\\n visited[next] = 0 # 방문 지워주고\\n tmp -= W[now][next] # 코스트 지워주고\\n elif sum(visited) == N and W[now][start]:\\n tmp += W[now][start] # 코스트 더하고\\n if tmp < result: result = tmp # 최소값 갱신\\n tmp -= W[now][start] # 코스트 지워주고\\n\\nN = int(input())\\nW = [list(map(int, input().split())) for _ in range(N)]\\nresult = int(1e9) # 가상의 최소값\\nvisited = [0] * N # 방문 배열\\nfor n in range(N): # 모든 점에서 다 출발해본다\\n tmp = 0 # 해당 출발의 임시 결과값\\n visited[n] = 1 # 들어가면서 찍고\\n dfs(n, n) # 출발 시, 시작점과 탐색점은 같다\\n visited[n] = 0 # 나오면서 지운다\\nprint(result) # 얻은 최소값 출력\\n\\n\\\"\\\"\\\"\\n시간 : 80분(혼자 고민) + 10분(\\\"질문검색\\\"탭에서 반례 및 힌트 참고)\\n풀이\\n 갈 수 있는 동선을 모두 체크하여(브루트포스)\\n dfs로 탐색하면서\\n 방문배열을 만들어서, 들어갈 때 찍고, 나올 때 지워준다\\n 모든 점을 탐색했을 때 시작점으로 돌아가서\\n 해당 순회의 결과값이 최소값인지 비교하여 갱신한다\\n (from itertools import permutation을 사용하여 풀 수도 있을 것이다)\\n\\n 문제의 함정\\n 1. 다음 지점으로 갈 수 없는 경우가 있다\\n 순회 도중에 갈 수 없는 경우만 구현하였더니 오답이었고\\n 마지막 지점에서 다시 시작점으로 갈 수 없는 경우를 구현해주니 맞았음\\n 2. 순회 도중, 이미 구한 최소값보다 값이 커지면 return한다 (백트래킹)\\n\\\"\\\"\\\"\"\n },\n {\n \"alpha_fraction\": 0.5054945349693298,\n \"alphanum_fraction\": 0.5164835453033447,\n \"avg_line_length\": 14.333333015441895,\n \"blob_id\": \"9c3430f7d7500c3724f96fc0f3a43a96de3a3dab\",\n \"content_id\": \"84e89fd50779e6550cacb1238064f0e79f6354fc\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 91,\n \"license_type\": \"no_license\",\n \"max_line_length\": 36,\n \"num_lines\": 6,\n \"path\": \"/알고리즘/온라인저지/2022/02/0211/다면체.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"T = int(input())\\n\\nfor t in range(T):\\n V, E = map(int, input().split())\\n\\n print(E-V+2)\"\n },\n {\n \"alpha_fraction\": 0.35384616255760193,\n \"alphanum_fraction\": 0.5076923370361328,\n \"avg_line_length\": 21,\n \"blob_id\": \"72075ee002a3440075dd7f938d88d65aecacb2d2\",\n \"content_id\": \"0ed46d4655bb4cd672272fa115981f7d35f22ead\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 65,\n \"license_type\": \"no_license\",\n \"max_line_length\": 47,\n \"num_lines\": 3,\n \"path\": \"/알고리즘/온라인저지/2022/02/0221/세금.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"N = int(input())\\n\\nprint(int(N*0.78), int((N*0.8) + (N*0.2)*0.78))\"\n },\n {\n \"alpha_fraction\": 0.4741035997867584,\n \"alphanum_fraction\": 0.5119521617889404,\n \"avg_line_length\": 24.149999618530273,\n \"blob_id\": \"1cde46789ad61409c9ca3cb5420cff414cd9f00a\",\n \"content_id\": \"0689a6120b1ea835ed59575fd1112c578e164777\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 502,\n \"license_type\": \"no_license\",\n \"max_line_length\": 66,\n \"num_lines\": 20,\n \"path\": \"/알고리즘/온라인저지/2022/10/1006/숫자판 점프.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\ndy, dx = [-1, 1, 0, 0], [0, 0, -1, 1]\\n\\ndef dfs(y, x, move, str_num):\\n if move == 5: \\n result.add(int(str_num))\\n return\\n for i in range(4):\\n ny, nx = y+dy[i], x+dx[i]\\n if 0<=ny<5 and 0<=nx<5:\\n dfs(ny, nx, move+1, str_num+str(arr[ny][nx]))\\n\\narr = [list(map(int, input().rstrip().split())) for _ in range(5)]\\nresult = set()\\nfor i in range(5):\\n for j in range(5):\\n dfs(i, j, 0, str(arr[i][j]))\\nprint(len(result))\"\n },\n {\n \"alpha_fraction\": 0.4848484992980957,\n \"alphanum_fraction\": 0.5353535413742065,\n \"avg_line_length\": 11.5,\n \"blob_id\": \"31e9830d34873c93249dfee32a85a81c1281f10b\",\n \"content_id\": \"48f90ff8c3b42ca6b65dc1f614d2aea9c28b05d0\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 99,\n \"license_type\": \"no_license\",\n \"max_line_length\": 16,\n \"num_lines\": 8,\n \"path\": \"/알고리즘/온라인저지/2023/05/0521/11 月 (November).py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"A = int(input())\\nB = int(input())\\nB *= 7\\nC = A+B\\nresult = 1\\nif C > 30:\\n result = 0\\nprint(result)\"\n },\n {\n \"alpha_fraction\": 0.48106446862220764,\n \"alphanum_fraction\": 0.5076765418052673,\n \"avg_line_length\": 22.08661460876465,\n \"blob_id\": \"69f2bdf44f86c9c5cd90c21dfd1a2468d5eb7bea\",\n \"content_id\": \"1f0c4b40d6bb0aa58b6ee4bce76020495addd8cb\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 3589,\n \"license_type\": \"no_license\",\n \"max_line_length\": 61,\n \"num_lines\": 127,\n \"path\": \"/알고리즘/온라인저지/2022/03/0313/배열 돌리기 3.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"\\\"\\\"\\\"\\narr = 원본 배열\\nresult = 연산을 실행한 배열\\n매 연산마다 배열을 돌리고\\nresult를 다시 arr에 deepcopy하면서 진행\\n\\\"\\\"\\\"\\n\\nimport copy # deepcopy 사용\\n\\ndef one():\\n global arr, result\\n result = []\\n for a in arr[::-1]: # 세로로 뒤집어서\\n result.append(a) # 한 줄 씩 추가\\n arr = copy.deepcopy(result) # arr에 result 덮어쓰기\\n\\ndef two():\\n global arr, result\\n result = []\\n for a in arr:\\n result.append(a[::-1]) # 가로로 뒤집어서 한 줄 씩 추가\\n arr = copy.deepcopy(result) # arr에 result 덮어쓰기\\n \\ndef three():\\n global arr, result\\n result = []\\n for j in range(M): # 왼쪽 줄을\\n tmp = []\\n for i in range(N-1, -1, -1): # 거꾸로 읽어와서\\n tmp.append(arr[i][j])\\n result.append(tmp) # 한 줄 씩 추가\\n arr = copy.deepcopy(result) # arr에 result 덮어쓰기\\n\\ndef four():\\n global arr, result\\n result = []\\n for j in range(M-1, -1, -1): # 오른쪽 줄을\\n tmp = []\\n for i in range(N): # 읽어와서\\n tmp.append(arr[i][j])\\n result.append(tmp) # 한 줄 씩 추가\\n arr = copy.deepcopy(result) # arr에 result 덮어쓰기\\n\\n\\\"\\\"\\\"\\n5번연산, 6번연산은\\n배열의 모양을 \\n1 2\\n4 3\\n으로 나누어 생각하기로 함\\n5번연산을 실행한 결과값의 맨 윗줄은\\n4번의 첫 줄 + 1번의 첫 줄이 되고\\n그렇게 결과값의 반을 채우고 나면 나머지 반은\\n3번의 첫 줄 + 2번의 첫 줄\\n을 더한 값으로 순서대로 나머지 반을 채우게 됨\\n\\\"\\\"\\\"\\ndef five():\\n global arr, result\\n result = []\\n for i in range(N//2, N):\\n tmp1 = [] # 4\\n tmp2 = [] # 1\\n for j in range(M//2):\\n tmp1.append(arr[i][j])\\n tmp2.append(arr[i-(N//2)][j])\\n result.append(tmp1+tmp2) # 4와 1을 한 줄 씩 더해서 result에 추가\\n for i in range(N//2, N):\\n tmp1 = [] # 3\\n tmp2 = [] # 2\\n for j in range(M//2, M):\\n tmp1.append(arr[i][j])\\n tmp2.append(arr[i-(N//2)][j])\\n result.append(tmp1+tmp2) # 3과 2를 한 줄 씩 더해서 result에 추가\\n arr = copy.deepcopy(result) # arr에 result 덮어쓰기\\n\\n\\\"\\\"\\\"\\n6번연산은\\n2번의 첫 줄 + 3번의 첫 줄\\n을 구해서 결과값의 절반을 채우고\\n나머지 절반은\\n1번의 첫 줄 + 4번의 첫 줄\\n을 더한 값으로 채움\\n\\\"\\\"\\\"\\ndef six():\\n global arr, result\\n result = []\\n for i in range(N//2):\\n tmp1 = [] # 2\\n tmp2 = [] # 3\\n for j in range(M//2, M):\\n tmp1.append(arr[i][j])\\n tmp2.append(arr[i+(N//2)][j])\\n result.append(tmp1+tmp2) \\n for i in range(N//2):\\n tmp1 = [] # 1\\n tmp2 = [] # 4\\n for j in range(M//2):\\n tmp1.append(arr[i][j])\\n tmp2.append(arr[i+(N//2)][j])\\n result.append(tmp1+tmp2)\\n arr = copy.deepcopy(result) # arr에 result 덮어쓰기\\n\\n\\nN, M, R = map(int, input().split())\\narr = [] # 원본 배열\\nfor n in range(N):\\n arr.append(list(map(int, input().split())))\\norders = list(map(int, input().split())) # 연산들\\nresult = [] # 연산을 진행할 배열\\n\\nfor order in orders:\\n if order == 1:\\n one()\\n elif order == 2:\\n two()\\n elif order == 3:\\n three()\\n N, M = M, N # 직사각형 배열인 경우 에러 방지\\n elif order == 4:\\n four() \\n N, M = M, N # 직사각형 배열인 경우 에러 방지\\n elif order == 5:\\n five()\\n elif order == 6:\\n six()\\n\\nfor r in result:\\n print(*r) # 각 줄 출력\"\n },\n {\n \"alpha_fraction\": 0.5787781476974487,\n \"alphanum_fraction\": 0.5932475924491882,\n \"avg_line_length\": 27.272727966308594,\n \"blob_id\": \"ea3799b49cf2ba67c0b01b1566b1a8060d689f18\",\n \"content_id\": \"ad93b25c07599cc59743bc6368c11a24a5ed2484\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1028,\n \"license_type\": \"no_license\",\n \"max_line_length\": 70,\n \"num_lines\": 22,\n \"path\": \"/알고리즘/온라인저지/2021/08/0806/평균은 넘겠지.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"\\\"\\\"\\\"\\n테스트케이스 개수 C개\\n학생의 수 N명, 점수 N개\\n점수 N개의 평균\\n을 넘는 점수의 개수\\n를 전체 점수의 개수로 나눈 퍼센트\\n을 3자리까지 출력\\n을 테스트케이스 개수만큼\\\"\\\"\\\"\\n\\nC = int(input()) # 테스트케이스 개수\\nfor i in range(C): # 테스트케이스 개수만큼 순회하면서\\n N_and_scores = list(map(int, input().split())) # 점수개수 N과 점수들을 입력받고\\n N = N_and_scores[0] # N값을 잡아주고\\n average = (sum(N_and_scores) - N) / N # 평균 구해주고\\n count = 0 # 평균이상인 점수 개수 초기화\\n for j in range(1, len(N_and_scores)): # 점수 리스트 순회하면서\\n if N_and_scores[j] > average: # 평균이상인 점수 있으면\\n count += 1 # 카운트 증가\\n print(f'{(count / N) * 100:.3f}%') # 출력\\n\\n# 입력받고 출력하고를 테스트케이스 개수만큼 반복하는 것이 가능하다\\n# 모든 값을 입력받고 저장해서 거기서 값을 꺼낼 필요가 없다\\n\"\n },\n {\n \"alpha_fraction\": 0.5025728940963745,\n \"alphanum_fraction\": 0.5454545617103577,\n \"avg_line_length\": 26.809524536132812,\n \"blob_id\": \"96a48ac352d10a06be0088c8f4fabf0e9f3805be\",\n \"content_id\": \"a9dc1ea1f3180f1ea0110d252e0f995d56d51fcb\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 889,\n \"license_type\": \"no_license\",\n \"max_line_length\": 49,\n \"num_lines\": 21,\n \"path\": \"/알고리즘/온라인저지/2021/08/0807/동전O.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"\\\"\\\"\\\"\\nN = 동전의 종류 가짓수\\nK = 목표 금액\\n필요한 동전 개수의 최솟값을 구하는 문제\\n\\\"\\\"\\\"\\n\\nN, K = map(int, input().split()) # 동전개수, 목표금액 입력\\ncoins = [] # 입력받을 동전 리스트 초기화\\nfor i in range(N): # 동전개수만큼 순회하면서\\n coins.append(int(input())) # 동전들 입력받아서 추가\\ncoins.reverse() # 입력받은 리스트 뒤집고\\ncount = 0 # 필요한 동전개수 count 초기화\\nfor coin in coins: # 동전들 순회하면서\\n if coin <= K: # 이 동전이 목표금액보다 작으면\\n while True: # 반복해서\\n K -= coin # 목표금액에서 빼고\\n count += 1 # 동전 개수 추가하고\\n if coin > K: # 동전값이 목표금액보다 크면\\n break # 정지\\n# 4200 -> 3200 -> 2200 -> 1200 -> 200 -> 100 -> 0\\nprint(count) # 동전갯수 출력\"\n },\n {\n \"alpha_fraction\": 0.44768211245536804,\n \"alphanum_fraction\": 0.4834437072277069,\n \"avg_line_length\": 28.076923370361328,\n \"blob_id\": \"989fad5fac506e5fad6162f0ade46949e5be9ec3\",\n \"content_id\": \"09716823664e4da785982603d2473a6e09aea197\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 755,\n \"license_type\": \"no_license\",\n \"max_line_length\": 59,\n \"num_lines\": 26,\n \"path\": \"/알고리즘/온라인저지/2022/10/1002/나이트의 이동.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\nfrom collections import deque\\n\\ninput = sys.stdin.readline\\ndy = [-1, -2, -2, -1, 1, 2, 2, 1]\\ndx = [-2, -1, 1, 2, 2, 1, -1, -2]\\n\\nfor _ in [0]*int(input().rstrip()):\\n L = int(input().rstrip())\\n start = tuple(map(int, input().rstrip().split()))\\n goal = tuple(map(int, input().rstrip().split()))\\n result = 0\\n visited = [[0]*L for l in [0]*L]\\n Q = deque()\\n y, x = start\\n Q.append((y, x, 0))\\n visited[y][x] = 1\\n while Q:\\n y, x, move = Q.popleft()\\n if (y, x) == goal: result = move; break\\n for i in range(8):\\n ny, nx = y+dy[i], x+dx[i]\\n if 0<=ny<L and 0<=nx<L and not visited[ny][nx]:\\n Q.append((ny, nx, move+1))\\n visited[ny][nx] = 1\\n print(move)\"\n },\n {\n \"alpha_fraction\": 0.560606062412262,\n \"alphanum_fraction\": 0.6212121248245239,\n \"avg_line_length\": 14.7619047164917,\n \"blob_id\": \"1b7c30bee4210564164513959d010e9e807f31b2\",\n \"content_id\": \"ec8bbbd3dd91dde827dea45570e928e76748adcf\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 438,\n \"license_type\": \"no_license\",\n \"max_line_length\": 39,\n \"num_lines\": 21,\n \"path\": \"/알고리즘/온라인저지/2022/10/1006/오르막 수.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\ninput = sys.stdin.readline\\n\\nN = int(input().rstrip())\\ndp = [1]*10\\nfor i in range(1,N) :\\n for j in range(1,10) :\\n dp[j] += dp[j-1]\\nprint(sum(dp)%10007)\\n\\n\\\"\\\"\\\"\\n규칙은 찾았는데 구현하는게 막혔다\\n구현된 코드를 보고 이해는 가는데\\n어떻게 하면 이런 걸 코드로 쓸 수 있는지.. 신기하다\\n\\n<참고한 링크>\\nhttps://jainn.tistory.com/91\\n\\\"\\\"\\\"\\n\\n# https://www.acmicpc.net/problem/11057\"\n },\n {\n \"alpha_fraction\": 0.5062656402587891,\n \"alphanum_fraction\": 0.5137844681739807,\n \"avg_line_length\": 25.66666603088379,\n \"blob_id\": \"0d24da98f36f421c766736b3556c607ed85ce61d\",\n \"content_id\": \"eb9076b1d5eee14f4872856434d15627749ac493\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 399,\n \"license_type\": \"no_license\",\n \"max_line_length\": 46,\n \"num_lines\": 15,\n \"path\": \"/알고리즘/온라인저지/2022/09/0904/크로스워드 만들기.py\",\n \"repo_name\": \"sorrow4468/BAEKJOON\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"A, B = input().split()\\nresult = [['.']*len(A) for _ in range(len(B))]\\ny = 0\\nchar = ''\\nfor a in A[::-1]:\\n if a in B:\\n y = B.index(a)\\n char = a\\nx = A.index(char)\\nfor j in range(len(A)): result[y][j] = A[j]\\nfor i in range(len(B)): result[i][x] = B[i]\\nfor i in range(len(result)):\\n for j in range(len(result[i])):\\n print(result[i][j], end='')\\n if i < len(result)-1: print()\"\n }\n]"},"num_files":{"kind":"number","value":1015,"string":"1,015"}}},{"rowIdx":2049,"cells":{"repo_name":{"kind":"string","value":"kristinemaeg/SentimentAnalysis"},"repo_url":{"kind":"string","value":"https://github.com/kristinemaeg/SentimentAnalysis"},"snapshot_id":{"kind":"string","value":"f775d48ad32eae5e043717d5baa259c8b37bcbf3"},"revision_id":{"kind":"string","value":"55438beb63fce195b77ae051978d5d1d55d89ccf"},"directory_id":{"kind":"string","value":"2513225f9c03fa33f19f6fedb455a91029bc8b3c"},"branch_name":{"kind":"string","value":"refs/heads/main"},"visit_date":{"kind":"string","value":"2023-03-09T21:11:47.928069"},"revision_date":{"kind":"string","value":"2021-02-24T04:21:45"},"committer_date":{"kind":"string","value":"2021-02-24T04:21:45"},"github_id":{"kind":"number","value":341380331,"string":"341,380,331"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.4535974860191345,"alphanum_fraction":0.6538060307502747,"avg_line_length":15.759259223937988,"blob_id":"06c1e83b60765e67de3d70e5d911b9cead5505c1","content_id":"88fbb37c9111faf52d89fb80c982b9f7e8d6a2c4","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Text","length_bytes":959,"license_type":"no_license","max_line_length":28,"num_lines":54,"path":"/requirements.txt","repo_name":"kristinemaeg/SentimentAnalysis","src_encoding":"UTF-8","text":"backcall==0.2.0\r\nBrotli==1.0.9\r\ncertifi==2020.12.5\r\nchardet==4.0.0\r\nclick==7.1.2\r\ncolorama==0.4.4\r\ncycler==0.10.0\r\ndash==1.19.0\r\ndash-core-components==1.15.0\r\ndash-html-components==1.1.2\r\ndash-renderer==1.9.0\r\ndash-table==4.11.2\r\ndecorator==4.4.2\r\nFlask==1.1.2\r\nFlask-Compress==1.9.0\r\nfuture==0.18.2\r\ngunicorn==20.0.4\r\nidna==2.10\r\nipython==7.20.0\r\nipython-genutils==0.2.0\r\nitsdangerous==1.1.0\r\njedi==0.18.0\r\nJinja2==2.11.3\r\njoblib==1.0.1\r\nkiwisolver==1.3.1\r\nMarkupSafe==1.1.1\r\nmatplotlib==3.3.4\r\nnltk==3.5\r\nnumpy==1.20.1\r\noauthlib==3.1.0\r\npandas==1.2.2\r\nparso==0.8.1\r\npickleshare==0.7.5\r\nPillow==8.1.0\r\nplotly==4.14.3\r\nprompt-toolkit==3.0.16\r\nPygments==2.8.0\r\npyparsing==2.4.7\r\nPySocks==1.7.1\r\npython-dateutil==2.8.1\r\npytz==2021.1\r\nregex==2020.11.13\r\nrequests==2.25.1\r\nrequests-oauthlib==1.3.0\r\nretrying==1.3.3\r\nsix==1.15.0\r\ntextblob==0.15.3\r\ntqdm==4.57.0\r\ntraitlets==5.0.5\r\ntweepy==3.10.0\r\nurllib3==1.26.3\r\nwcwidth==0.2.5\r\nWerkzeug==1.0.1\r\nwordcloud==1.8.1\r\n"},{"alpha_fraction":0.5692776441574097,"alphanum_fraction":0.5773134827613831,"avg_line_length":32.103641510009766,"blob_id":"486a3891e09abb2872ecdde689a7a900a6f108d2","content_id":"a4701be62312e8dd1b940b8cd703c9a8284788dc","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":11826,"license_type":"no_license","max_line_length":250,"num_lines":357,"path":"/SentimentAnalysis.py","repo_name":"kristinemaeg/SentimentAnalysis","src_encoding":"UTF-8","text":"#!/usr/bin/env python\n# coding: utf-8\n\n# In[1]:\n\n\n#Import the libraries\nimport dash\nimport dash_core_components as dcc\nimport dash_html_components as html\nfrom dash.dependencies import Input, Output, State\n\nimport tweepy\nfrom textblob import TextBlob\nfrom wordcloud import WordCloud\nimport pandas as pd\nimport numpy as np\nimport re\nimport matplotlib.pyplot as plt\nplt.style.use('fivethirtyeight')\n\nimport plotly.graph_objects as go \n\nimport nltk\nfrom nltk.corpus import stopwords\nfrom nltk.tokenize import word_tokenize \nimport string\n\nimport base64\nfrom io import BytesIO\n\nimport urllib.request\nimport json \nimport datetime\n\nfrom wordcloud import WordCloud, STOPWORDS\nfrom nltk.sentiment.vader import SentimentIntensityAnalyzer\nfrom pprint import pprint\nfrom IPython import display\n\nnltk.download('vader_lexicon')\nnltk.download('stopwords')\nnltk.download('punkt')\n\n#Authentication\nconsumerKey=\"U4y7XJ0ejIy9ThRje9UtZXl8N\"\nconsumerSecret=\"M2QyH0E4VpxBwPnXWmV9Bnwy0ZTWobrWuuoFv02PsMECyLq1oJ\"\naccessToken=\"1268986499728580610-57f201gaeuOB0yHS4LdHcqm0ekNT6P\"\naccessTokenSecret=\"oIWLBcPVBEf5XZ8lQGlBWjC9ARV8PMrgL26mPkspZtYip\"\n\nauth = tweepy.OAuthHandler(consumerKey, consumerSecret)\nauth.set_access_token(accessToken, accessTokenSecret)\napi = tweepy.API(auth, wait_on_rate_limit= True)\n\n#Initiate the app\nexternal_stylesheets = ['https://codepen.io/chriddyp/pen/bWLwgP.css']\napp = dash.Dash(__name__, suppress_callback_exceptions=True, external_stylesheets=external_stylesheets)\nserver = app.server\n\ncolors = {\n 'background': '#111111',\n 'text': 'firebrick'\n}\n\napp.layout = html.Div([\n html.H6(\"Sentiment Analysis\",style={\n 'textAlign': 'left-center',\n 'color': colors['text'],\n 'fontWeight': 'bold',\n }),\n dcc.Location(id='url', refresh=False),\n html.Div(id='home_page')\n])\n\n\nindex_page = html.Div([\n dcc.Link('Analyze a Twitter Account', href='/twitter'),\n html.Br(),\n dcc.Link('Analyze a Subreddit Forum', href='/reddit'),\n])\n\n\n#Twitter Page\ntwitter_layout = html.Div([\n html.H6('Twitter'),\n dcc.Input(\n id='twitterhandle',\n placeholder='Enter a Twitter Handle',\n type='text',\n value='',\n style={'width': 300}\n ),\n html.Button('Submit', id='button', n_clicks=0),\n html.Div(id='twitter_output', style={'whiteSpace': 'pre-line'}),\n html.Br(),\n dcc.Link('Analyze using Reddit', href='/reddit'),\n html.Br(),\n dcc.Link('Go back to home', href='/'),\n])\n\n@app.callback(dash.dependencies.Output('twitter_output', 'children'),\n [dash.dependencies.Input('button', 'n_clicks')],\n [dash.dependencies.State('twitterhandle', 'value')])\ndef twitter_page(n_clicks, twitterhandle):\n if n_clicks > 0:\n # Extract 1000 tweets from twitter user\n posts = api.user_timeline(screen_name = twitterhandle, count=10000, lang = \"en\", tweet_mode=\"extended\")\n \n # Create dataframe \n df = pd.DataFrame( [tweet.full_text for tweet in posts] , columns=['Tweets'])\n \n # Clean text\n # Create function to clean tweets\n def cleanTxt(text):\n text = re.sub(r'@[A-Za-z0-9]+', '', text) #removes @mentions\n text = re.sub(r'#', '', text) #removes '#'\n text = re.sub(r'RT[\\s]+', '', text) # removes RT\n text = re.sub(r'https?:\\/\\/\\S+' , '', text) #removes links\n return text\n \n df['Text']= df['Tweets'].apply(cleanTxt)\n \n # Create function to get the subjectivity\n def getSubjectivity(text):\n return TextBlob(text).sentiment.subjectivity\n \n # Create function to get the polarity\n def getPolarity(text):\n return TextBlob(text).sentiment.polarity\n \n # Create two new columns\n df['Subjectivity'] = df['Text'].apply(getSubjectivity)\n df['Polarity'] = df['Text'].apply(getPolarity)\n \n # Calculate the negative, neutral and positive analysis\n def getAnalysis(score):\n if score < 0:\n return 'Negative'\n elif score == 0:\n return 'Neutral'\n else:\n return 'Positive'\n \n df['Sentiment'] = df['Polarity'].apply(getAnalysis)\n \n #Create Pie Chart\n labels = df['Sentiment'].value_counts().index\n values = df['Sentiment'].value_counts()\n fig = go.Figure(data=[go.Pie(labels=labels, values=values)])\n \n \n # Clean the text\n allWords = ' '.join( [twts for twts in df['Text']] )\n allWords_lower = allWords.lower()\n stop = set(stopwords.words('english') + list(string.punctuation))\n new_stopwords = ['...', '``', \"''\", '’', \"'s\", \"n't\" ]\n new_stopwords_list = stop.union(new_stopwords)\n\n text_tokens = nltk.word_tokenize(allWords_lower)\n text_no_stop_words_punct = [t for t in text_tokens if t not in new_stopwords_list and t not in string.punctuation]\n\n filtered_string = (\" \").join(text_no_stop_words_punct)\n \n # Convert the long string to a dictionary with frequency counts.\n def word_count(str):\n counts = dict()\n words = str.split()\n\n for word in words:\n if word in counts:\n counts[word] += 1\n else:\n counts[word] = 1\n\n return counts\n\n twitter_wordcloud = ( word_count(filtered_string))\n \n # Create Word Cloud\n wc = WordCloud().generate_from_frequencies(frequencies=twitter_wordcloud)\n wc_img = wc.to_image()\n with BytesIO() as buffer:\n wc_img.save(buffer, 'png')\n img2 = base64.b64encode(buffer.getvalue()).decode()\n\n\n #Display Pie Chart and Word Cloud\n twitter_results = html.Div([ \n html.Div(\n dcc.Graph(id='graph1', figure=fig)\n ,style={'width': '49%', 'display': 'inline-block'}), \n html.Div( \n children=[html.Img(src=\"data:image/png;base64,\" + img2,\n style={'height':'50%', 'width': '50%'})]\n ,style={'width': '49%', 'display': 'block', 'textAlign':'center'}), \n ])\n \n return twitter_results\n\n\n#Reddit Page\nreddit_layout = html.Div([\n html.H6('Reddit'),\n dcc.Input(\n id='subreddit',\n placeholder='Enter a Subreddit Forum',\n type='text',\n value='',\n style={'width': 300}\n ),\n html.Button('Submit', id='button', n_clicks=0),\n html.Div(id='reddit_output', style={'whiteSpace': 'pre-line'}),\n html.Br(),\n dcc.Link('Analyze using Twitter', href='/twitter'),\n html.Br(),\n dcc.Link('Go back to home', href='/')\n])\n\n@app.callback(dash.dependencies.Output('reddit_output', 'children'),\n [dash.dependencies.Input('button', 'n_clicks')],\n [dash.dependencies.State('subreddit', 'value')])\ndef reddit_radios(n_clicks, subreddit):\n if n_clicks > 0:\n #return 'You have selected \"{}\"'.format(subreddit)\n \n #Define function to pull up historical Reddit post information\n def load_results(lower_bound_timestamp, upper_bound_timestamp, target_result_size, target_subreddit, score_threshold):\n headline_collection = set()\n \n reddit_data_url = f\"https://api.pushshift.io/reddit/submission/search/?after={lower_bound_timestamp}&before={upper_bound_timestamp}&sort_type=score&sort=desc&subreddit={target_subreddit}&limit={target_result_size}&score={score_threshold}\"\n \n try:\n with urllib.request.urlopen(reddit_data_url) as url:\n data = json.loads(url.read().decode())\n \n for submission in data['data']:\n headline_collection.add(submission['title'])\n\n return headline_collection\n except urllib.error.HTTPError as e:\n print(e.__dict__)\n return set()\n except urllib.error.URLError as e:\n print(e.__dict__)\n return set()\n \n # Get Reddit posts\n headlines = set()\n\n time_now = datetime.datetime.now()\n\n limit_delta = 7\n limit_lower_delta = 6\n\n result_size = 1000\n score_limit = \">0\"\n\n for i in range(0, 8):\n previous_timestamp = int((time_now - datetime.timedelta(days=limit_delta)).timestamp())\n current_timestamp = int((time_now - datetime.timedelta(days=limit_lower_delta)).timestamp())\n\n full_collection = load_results(previous_timestamp, current_timestamp, result_size, subreddit, score_limit)\n headlines = headlines.union(full_collection)\n \n limit_delta = limit_delta - 1\n limit_lower_delta = limit_lower_delta - 1\n \n display.clear_output()\n \n # Calculate polarity to get the sentiment\n sia = SentimentIntensityAnalyzer()\n results = []\n\n for line in headlines:\n pol_score = sia.polarity_scores(line)\n pol_score['headline'] = line\n results.append(pol_score)\n \n #Convert the results to a dataframe\n df = pd.DataFrame.from_records(results)\n \n #Label the results accordingly\n df['label'] = 'Neutral'\n df.loc[df['compound'] > 0.1, 'label'] = 'Positive'\n df.loc[df['compound'] < -0.1, 'label'] = 'Negative'\n \n #Create Pie Chart\n labels = df['label'].value_counts().index\n values = df['label'].value_counts()\n fig = go.Figure(data=[go.Pie(labels=labels, values=values)])\n reddit_pie = html.Div([\n dcc.Graph(figure=fig)])\n \n # Clean the text\n allWords = ' '.join( [rdf for rdf in df['headline']] )\n allWords_lower = allWords.lower()\n stop = set(stopwords.words('english') + list(string.punctuation))\n new_stopwords = ['...', '``', \"''\", '’', \"'s\", \"n't\" ]\n new_stopwords_list = stop.union(new_stopwords)\n\n text_tokens = nltk.word_tokenize(allWords_lower)\n text_no_stop_words_punct = [t for t in text_tokens if t not in new_stopwords_list and t not in string.punctuation]\n\n filtered_string = (\" \").join(text_no_stop_words_punct)\n \n # Convert the long string to a dictionary with frequency counts.\n def word_count(str):\n counts = dict()\n words = str.split()\n\n for word in words:\n if word in counts:\n counts[word] += 1\n else:\n counts[word] = 1\n\n return counts\n\n reddit_wordcloud = ( word_count(filtered_string))\n \n # Create Word Cloud\n wc = WordCloud().generate_from_frequencies(frequencies=reddit_wordcloud)\n wc_img = wc.to_image()\n with BytesIO() as buffer:\n wc_img.save(buffer, 'png')\n img2 = base64.b64encode(buffer.getvalue()).decode()\n \n #Display Pie Chart and Word Cloud\n reddit_results = html.Div([ \n html.Div(\n dcc.Graph(id='graph1', figure=fig)\n ,style={'width': '49%', 'display': 'inline-block'}), \n html.Div( \n children=[html.Img(src=\"data:image/png;base64,\" + img2,\n style={'height':'50%', 'width': '50%'})]\n ,style={'width': '49%', 'display': 'block', 'textAlign':'center'}), \n ])\n \n return reddit_results\n \n\n# Update the index\n@app.callback(dash.dependencies.Output('home_page', 'children'),\n [dash.dependencies.Input('url', 'pathname')])\ndef display_page(pathname):\n if pathname == '/twitter':\n return twitter_layout\n elif pathname == '/reddit':\n return reddit_layout\n else:\n return index_page\n\nif __name__ == '__main__':\n app.run_server(debug=False)\n\n\n# In[ ]:\n\n\n\n\n"}],"string":"[\n {\n \"alpha_fraction\": 0.4535974860191345,\n \"alphanum_fraction\": 0.6538060307502747,\n \"avg_line_length\": 15.759259223937988,\n \"blob_id\": \"06c1e83b60765e67de3d70e5d911b9cead5505c1\",\n \"content_id\": \"88fbb37c9111faf52d89fb80c982b9f7e8d6a2c4\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Text\",\n \"length_bytes\": 959,\n \"license_type\": \"no_license\",\n \"max_line_length\": 28,\n \"num_lines\": 54,\n \"path\": \"/requirements.txt\",\n \"repo_name\": \"kristinemaeg/SentimentAnalysis\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"backcall==0.2.0\\r\\nBrotli==1.0.9\\r\\ncertifi==2020.12.5\\r\\nchardet==4.0.0\\r\\nclick==7.1.2\\r\\ncolorama==0.4.4\\r\\ncycler==0.10.0\\r\\ndash==1.19.0\\r\\ndash-core-components==1.15.0\\r\\ndash-html-components==1.1.2\\r\\ndash-renderer==1.9.0\\r\\ndash-table==4.11.2\\r\\ndecorator==4.4.2\\r\\nFlask==1.1.2\\r\\nFlask-Compress==1.9.0\\r\\nfuture==0.18.2\\r\\ngunicorn==20.0.4\\r\\nidna==2.10\\r\\nipython==7.20.0\\r\\nipython-genutils==0.2.0\\r\\nitsdangerous==1.1.0\\r\\njedi==0.18.0\\r\\nJinja2==2.11.3\\r\\njoblib==1.0.1\\r\\nkiwisolver==1.3.1\\r\\nMarkupSafe==1.1.1\\r\\nmatplotlib==3.3.4\\r\\nnltk==3.5\\r\\nnumpy==1.20.1\\r\\noauthlib==3.1.0\\r\\npandas==1.2.2\\r\\nparso==0.8.1\\r\\npickleshare==0.7.5\\r\\nPillow==8.1.0\\r\\nplotly==4.14.3\\r\\nprompt-toolkit==3.0.16\\r\\nPygments==2.8.0\\r\\npyparsing==2.4.7\\r\\nPySocks==1.7.1\\r\\npython-dateutil==2.8.1\\r\\npytz==2021.1\\r\\nregex==2020.11.13\\r\\nrequests==2.25.1\\r\\nrequests-oauthlib==1.3.0\\r\\nretrying==1.3.3\\r\\nsix==1.15.0\\r\\ntextblob==0.15.3\\r\\ntqdm==4.57.0\\r\\ntraitlets==5.0.5\\r\\ntweepy==3.10.0\\r\\nurllib3==1.26.3\\r\\nwcwidth==0.2.5\\r\\nWerkzeug==1.0.1\\r\\nwordcloud==1.8.1\\r\\n\"\n },\n {\n \"alpha_fraction\": 0.5692776441574097,\n \"alphanum_fraction\": 0.5773134827613831,\n \"avg_line_length\": 32.103641510009766,\n \"blob_id\": \"486a3891e09abb2872ecdde689a7a900a6f108d2\",\n \"content_id\": \"a4701be62312e8dd1b940b8cd703c9a8284788dc\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 11826,\n \"license_type\": \"no_license\",\n \"max_line_length\": 250,\n \"num_lines\": 357,\n \"path\": \"/SentimentAnalysis.py\",\n \"repo_name\": \"kristinemaeg/SentimentAnalysis\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#!/usr/bin/env python\\n# coding: utf-8\\n\\n# In[1]:\\n\\n\\n#Import the libraries\\nimport dash\\nimport dash_core_components as dcc\\nimport dash_html_components as html\\nfrom dash.dependencies import Input, Output, State\\n\\nimport tweepy\\nfrom textblob import TextBlob\\nfrom wordcloud import WordCloud\\nimport pandas as pd\\nimport numpy as np\\nimport re\\nimport matplotlib.pyplot as plt\\nplt.style.use('fivethirtyeight')\\n\\nimport plotly.graph_objects as go \\n\\nimport nltk\\nfrom nltk.corpus import stopwords\\nfrom nltk.tokenize import word_tokenize \\nimport string\\n\\nimport base64\\nfrom io import BytesIO\\n\\nimport urllib.request\\nimport json \\nimport datetime\\n\\nfrom wordcloud import WordCloud, STOPWORDS\\nfrom nltk.sentiment.vader import SentimentIntensityAnalyzer\\nfrom pprint import pprint\\nfrom IPython import display\\n\\nnltk.download('vader_lexicon')\\nnltk.download('stopwords')\\nnltk.download('punkt')\\n\\n#Authentication\\nconsumerKey=\\\"U4y7XJ0ejIy9ThRje9UtZXl8N\\\"\\nconsumerSecret=\\\"M2QyH0E4VpxBwPnXWmV9Bnwy0ZTWobrWuuoFv02PsMECyLq1oJ\\\"\\naccessToken=\\\"1268986499728580610-57f201gaeuOB0yHS4LdHcqm0ekNT6P\\\"\\naccessTokenSecret=\\\"oIWLBcPVBEf5XZ8lQGlBWjC9ARV8PMrgL26mPkspZtYip\\\"\\n\\nauth = tweepy.OAuthHandler(consumerKey, consumerSecret)\\nauth.set_access_token(accessToken, accessTokenSecret)\\napi = tweepy.API(auth, wait_on_rate_limit= True)\\n\\n#Initiate the app\\nexternal_stylesheets = ['https://codepen.io/chriddyp/pen/bWLwgP.css']\\napp = dash.Dash(__name__, suppress_callback_exceptions=True, external_stylesheets=external_stylesheets)\\nserver = app.server\\n\\ncolors = {\\n 'background': '#111111',\\n 'text': 'firebrick'\\n}\\n\\napp.layout = html.Div([\\n html.H6(\\\"Sentiment Analysis\\\",style={\\n 'textAlign': 'left-center',\\n 'color': colors['text'],\\n 'fontWeight': 'bold',\\n }),\\n dcc.Location(id='url', refresh=False),\\n html.Div(id='home_page')\\n])\\n\\n\\nindex_page = html.Div([\\n dcc.Link('Analyze a Twitter Account', href='/twitter'),\\n html.Br(),\\n dcc.Link('Analyze a Subreddit Forum', href='/reddit'),\\n])\\n\\n\\n#Twitter Page\\ntwitter_layout = html.Div([\\n html.H6('Twitter'),\\n dcc.Input(\\n id='twitterhandle',\\n placeholder='Enter a Twitter Handle',\\n type='text',\\n value='',\\n style={'width': 300}\\n ),\\n html.Button('Submit', id='button', n_clicks=0),\\n html.Div(id='twitter_output', style={'whiteSpace': 'pre-line'}),\\n html.Br(),\\n dcc.Link('Analyze using Reddit', href='/reddit'),\\n html.Br(),\\n dcc.Link('Go back to home', href='/'),\\n])\\n\\n@app.callback(dash.dependencies.Output('twitter_output', 'children'),\\n [dash.dependencies.Input('button', 'n_clicks')],\\n [dash.dependencies.State('twitterhandle', 'value')])\\ndef twitter_page(n_clicks, twitterhandle):\\n if n_clicks > 0:\\n # Extract 1000 tweets from twitter user\\n posts = api.user_timeline(screen_name = twitterhandle, count=10000, lang = \\\"en\\\", tweet_mode=\\\"extended\\\")\\n \\n # Create dataframe \\n df = pd.DataFrame( [tweet.full_text for tweet in posts] , columns=['Tweets'])\\n \\n # Clean text\\n # Create function to clean tweets\\n def cleanTxt(text):\\n text = re.sub(r'@[A-Za-z0-9]+', '', text) #removes @mentions\\n text = re.sub(r'#', '', text) #removes '#'\\n text = re.sub(r'RT[\\\\s]+', '', text) # removes RT\\n text = re.sub(r'https?:\\\\/\\\\/\\\\S+' , '', text) #removes links\\n return text\\n \\n df['Text']= df['Tweets'].apply(cleanTxt)\\n \\n # Create function to get the subjectivity\\n def getSubjectivity(text):\\n return TextBlob(text).sentiment.subjectivity\\n \\n # Create function to get the polarity\\n def getPolarity(text):\\n return TextBlob(text).sentiment.polarity\\n \\n # Create two new columns\\n df['Subjectivity'] = df['Text'].apply(getSubjectivity)\\n df['Polarity'] = df['Text'].apply(getPolarity)\\n \\n # Calculate the negative, neutral and positive analysis\\n def getAnalysis(score):\\n if score < 0:\\n return 'Negative'\\n elif score == 0:\\n return 'Neutral'\\n else:\\n return 'Positive'\\n \\n df['Sentiment'] = df['Polarity'].apply(getAnalysis)\\n \\n #Create Pie Chart\\n labels = df['Sentiment'].value_counts().index\\n values = df['Sentiment'].value_counts()\\n fig = go.Figure(data=[go.Pie(labels=labels, values=values)])\\n \\n \\n # Clean the text\\n allWords = ' '.join( [twts for twts in df['Text']] )\\n allWords_lower = allWords.lower()\\n stop = set(stopwords.words('english') + list(string.punctuation))\\n new_stopwords = ['...', '``', \\\"''\\\", '’', \\\"'s\\\", \\\"n't\\\" ]\\n new_stopwords_list = stop.union(new_stopwords)\\n\\n text_tokens = nltk.word_tokenize(allWords_lower)\\n text_no_stop_words_punct = [t for t in text_tokens if t not in new_stopwords_list and t not in string.punctuation]\\n\\n filtered_string = (\\\" \\\").join(text_no_stop_words_punct)\\n \\n # Convert the long string to a dictionary with frequency counts.\\n def word_count(str):\\n counts = dict()\\n words = str.split()\\n\\n for word in words:\\n if word in counts:\\n counts[word] += 1\\n else:\\n counts[word] = 1\\n\\n return counts\\n\\n twitter_wordcloud = ( word_count(filtered_string))\\n \\n # Create Word Cloud\\n wc = WordCloud().generate_from_frequencies(frequencies=twitter_wordcloud)\\n wc_img = wc.to_image()\\n with BytesIO() as buffer:\\n wc_img.save(buffer, 'png')\\n img2 = base64.b64encode(buffer.getvalue()).decode()\\n\\n\\n #Display Pie Chart and Word Cloud\\n twitter_results = html.Div([ \\n html.Div(\\n dcc.Graph(id='graph1', figure=fig)\\n ,style={'width': '49%', 'display': 'inline-block'}), \\n html.Div( \\n children=[html.Img(src=\\\"data:image/png;base64,\\\" + img2,\\n style={'height':'50%', 'width': '50%'})]\\n ,style={'width': '49%', 'display': 'block', 'textAlign':'center'}), \\n ])\\n \\n return twitter_results\\n\\n\\n#Reddit Page\\nreddit_layout = html.Div([\\n html.H6('Reddit'),\\n dcc.Input(\\n id='subreddit',\\n placeholder='Enter a Subreddit Forum',\\n type='text',\\n value='',\\n style={'width': 300}\\n ),\\n html.Button('Submit', id='button', n_clicks=0),\\n html.Div(id='reddit_output', style={'whiteSpace': 'pre-line'}),\\n html.Br(),\\n dcc.Link('Analyze using Twitter', href='/twitter'),\\n html.Br(),\\n dcc.Link('Go back to home', href='/')\\n])\\n\\n@app.callback(dash.dependencies.Output('reddit_output', 'children'),\\n [dash.dependencies.Input('button', 'n_clicks')],\\n [dash.dependencies.State('subreddit', 'value')])\\ndef reddit_radios(n_clicks, subreddit):\\n if n_clicks > 0:\\n #return 'You have selected \\\"{}\\\"'.format(subreddit)\\n \\n #Define function to pull up historical Reddit post information\\n def load_results(lower_bound_timestamp, upper_bound_timestamp, target_result_size, target_subreddit, score_threshold):\\n headline_collection = set()\\n \\n reddit_data_url = f\\\"https://api.pushshift.io/reddit/submission/search/?after={lower_bound_timestamp}&before={upper_bound_timestamp}&sort_type=score&sort=desc&subreddit={target_subreddit}&limit={target_result_size}&score={score_threshold}\\\"\\n \\n try:\\n with urllib.request.urlopen(reddit_data_url) as url:\\n data = json.loads(url.read().decode())\\n \\n for submission in data['data']:\\n headline_collection.add(submission['title'])\\n\\n return headline_collection\\n except urllib.error.HTTPError as e:\\n print(e.__dict__)\\n return set()\\n except urllib.error.URLError as e:\\n print(e.__dict__)\\n return set()\\n \\n # Get Reddit posts\\n headlines = set()\\n\\n time_now = datetime.datetime.now()\\n\\n limit_delta = 7\\n limit_lower_delta = 6\\n\\n result_size = 1000\\n score_limit = \\\">0\\\"\\n\\n for i in range(0, 8):\\n previous_timestamp = int((time_now - datetime.timedelta(days=limit_delta)).timestamp())\\n current_timestamp = int((time_now - datetime.timedelta(days=limit_lower_delta)).timestamp())\\n\\n full_collection = load_results(previous_timestamp, current_timestamp, result_size, subreddit, score_limit)\\n headlines = headlines.union(full_collection)\\n \\n limit_delta = limit_delta - 1\\n limit_lower_delta = limit_lower_delta - 1\\n \\n display.clear_output()\\n \\n # Calculate polarity to get the sentiment\\n sia = SentimentIntensityAnalyzer()\\n results = []\\n\\n for line in headlines:\\n pol_score = sia.polarity_scores(line)\\n pol_score['headline'] = line\\n results.append(pol_score)\\n \\n #Convert the results to a dataframe\\n df = pd.DataFrame.from_records(results)\\n \\n #Label the results accordingly\\n df['label'] = 'Neutral'\\n df.loc[df['compound'] > 0.1, 'label'] = 'Positive'\\n df.loc[df['compound'] < -0.1, 'label'] = 'Negative'\\n \\n #Create Pie Chart\\n labels = df['label'].value_counts().index\\n values = df['label'].value_counts()\\n fig = go.Figure(data=[go.Pie(labels=labels, values=values)])\\n reddit_pie = html.Div([\\n dcc.Graph(figure=fig)])\\n \\n # Clean the text\\n allWords = ' '.join( [rdf for rdf in df['headline']] )\\n allWords_lower = allWords.lower()\\n stop = set(stopwords.words('english') + list(string.punctuation))\\n new_stopwords = ['...', '``', \\\"''\\\", '’', \\\"'s\\\", \\\"n't\\\" ]\\n new_stopwords_list = stop.union(new_stopwords)\\n\\n text_tokens = nltk.word_tokenize(allWords_lower)\\n text_no_stop_words_punct = [t for t in text_tokens if t not in new_stopwords_list and t not in string.punctuation]\\n\\n filtered_string = (\\\" \\\").join(text_no_stop_words_punct)\\n \\n # Convert the long string to a dictionary with frequency counts.\\n def word_count(str):\\n counts = dict()\\n words = str.split()\\n\\n for word in words:\\n if word in counts:\\n counts[word] += 1\\n else:\\n counts[word] = 1\\n\\n return counts\\n\\n reddit_wordcloud = ( word_count(filtered_string))\\n \\n # Create Word Cloud\\n wc = WordCloud().generate_from_frequencies(frequencies=reddit_wordcloud)\\n wc_img = wc.to_image()\\n with BytesIO() as buffer:\\n wc_img.save(buffer, 'png')\\n img2 = base64.b64encode(buffer.getvalue()).decode()\\n \\n #Display Pie Chart and Word Cloud\\n reddit_results = html.Div([ \\n html.Div(\\n dcc.Graph(id='graph1', figure=fig)\\n ,style={'width': '49%', 'display': 'inline-block'}), \\n html.Div( \\n children=[html.Img(src=\\\"data:image/png;base64,\\\" + img2,\\n style={'height':'50%', 'width': '50%'})]\\n ,style={'width': '49%', 'display': 'block', 'textAlign':'center'}), \\n ])\\n \\n return reddit_results\\n \\n\\n# Update the index\\n@app.callback(dash.dependencies.Output('home_page', 'children'),\\n [dash.dependencies.Input('url', 'pathname')])\\ndef display_page(pathname):\\n if pathname == '/twitter':\\n return twitter_layout\\n elif pathname == '/reddit':\\n return reddit_layout\\n else:\\n return index_page\\n\\nif __name__ == '__main__':\\n app.run_server(debug=False)\\n\\n\\n# In[ ]:\\n\\n\\n\\n\\n\"\n }\n]"},"num_files":{"kind":"number","value":2,"string":"2"}}},{"rowIdx":2050,"cells":{"repo_name":{"kind":"string","value":"indapa/pgmPy"},"repo_url":{"kind":"string","value":"https://github.com/indapa/pgmPy"},"snapshot_id":{"kind":"string","value":"128c08ad9c201fa7eae0142f7e0f31f3138db028"},"revision_id":{"kind":"string","value":"0378d380e7fb33c941d3daa28a41d33cca2f4bcf"},"directory_id":{"kind":"string","value":"9354f46f726a3750081ea40e703ed3db55fd0a8d"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"string","value":"2020-12-24T17:45:04.068015"},"revision_date":{"kind":"string","value":"2013-08-30T17:28:42"},"committer_date":{"kind":"string","value":"2013-08-30T17:28:42"},"github_id":{"kind":"number","value":6001237,"string":"6,001,237"},"star_events_count":{"kind":"number","value":15,"string":"15"},"fork_events_count":{"kind":"number","value":4,"string":"4"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.7966291904449463,"alphanum_fraction":0.7988764047622681,"avg_line_length":41.380950927734375,"blob_id":"2f2cb0f9cbc7ca9c6e341920e6f3837f8eff677a","content_id":"b8e2946911b5163d8d9e528d6c28cb5557092251","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":890,"license_type":"no_license","max_line_length":152,"num_lines":21,"path":"/README.md","repo_name":"indapa/pgmPy","src_encoding":"UTF-8","text":"pgmPy\n=====\n\nBackground:\n\nProbablistic Graphical Models representation in Python\n\nProbablistic Graphical Models (PGMs) use a graph-based representation\nto compactly encode the joint distribution. PGMs use elements of \ngraph theory and probability theory. There are two classes of PGMs. \ndirected acyclic graphical models are called Bayesian Networks (BNs)\nand undirected graphical models are Markov networks.\n\nThe code in this repository is based off the Matlab code\nfrom Daphne Koller's Coursera class on PGMs <https://www.coursera.org/course/pgm> For the assignments in the class students were given starter Matlab code\nand had to implement various algorithms, etc.\n\nWhile I grew to like Matlab, I needed to implement the inference and represenation of PGMs in Python for a personal project of mine. So I went down the \nrabbit hole. The code here depends on NumPy and uses Python v2.7.\n\nAmit Indap\n"},{"alpha_fraction":0.7048406004905701,"alphanum_fraction":0.7201889157295227,"avg_line_length":27.233333587646484,"blob_id":"06fcb001f011f9b775eaa3dce60cef2e4e27bf09","content_id":"0e3a67446e7f339e59d777938ea0a92eb39acf0d","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":847,"license_type":"no_license","max_line_length":80,"num_lines":30,"path":"/PythonNotebooks/testCliqueTreeMaxSumCalibrate.py","repo_name":"indapa/pgmPy","src_encoding":"UTF-8","text":"from Factor import *\nfrom PGMcommon import *\nfrom CliqueTree import *\nfrom CliqueTreeOperations import *\nfrom FactorOperations import *\nimport scipy.io as sio\nimport numpy as np\nimport pprint\nimport pdb\nmatfile='/Users/amit/BC_Classes/PGM/Prog4/PA4Sample.mat'\nmat_contents=sio.loadmat(matfile)\nmat_struct=mat_contents['MaxSumCalibrate']\nval=mat_struct[0,0]\ninput_edges = val['INPUT']['edges'][0][0]\n#print input_edges\ninput_cliqueList= val['INPUT']['cliqueList'][0][0][0]\nclique_list_factorObj=[]\nfor tpl in input_cliqueList:\n (var, card, values)=tpl\n f= Factor( var[0].tolist(), card[0].tolist(), values[0].tolist(), 'factor' )\n #print f \n clique_list_factorObj.append(f)\n\nP=CliqueTree( clique_list_factorObj , input_edges, clique_list_factorObj, [])\n\nP=CliqueTreeCalibrate(P,1)\n\nfor f in P.getNodeList():\n print f\n print \"==\"\n"},{"alpha_fraction":0.6499402523040771,"alphanum_fraction":0.6606929302215576,"avg_line_length":25.15625,"blob_id":"8c6f9a8ec28ce746f319beaed03ca361e895f07e","content_id":"a5d7adfd01c27cd7128f476c30ee4a018c5346d1","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":837,"license_type":"no_license","max_line_length":114,"num_lines":32,"path":"/PythonNotebooks/testMaxDecoding.py","repo_name":"indapa/pgmPy","src_encoding":"UTF-8","text":"from Factor import *\nfrom PGMcommon import *\nfrom CliqueTree import *\nfrom CliqueTreeOperations import *\nfrom FactorOperations import *\nimport scipy.io as sio\nimport numpy as np\nimport pprint\nimport pdb\nmatfile='/Users/amit/BC_Classes/PGM/Prog4/PA4Sample.mat'\nmat_contents=sio.loadmat(matfile)\nmat_struct=mat_contents['MaxDecoded']\nval=mat_struct[0,0]\ninput_factors = val['INPUT']\nfactorList=[]\n\n\n\nfor elm in input_factors:\n #print ary[0]\n #print\n (var, card, values)=elm[0]\n #print var, card, values\n f= Factor( var[0].tolist(), card[0].tolist(), values[0].tolist(), 'factor' )\n print f\n factorList.append( f )\n\nDECODE= MaxDecoding( factorList )\nALPHABET=['a','b','c','d','e','f','g','h','i','j','k','l','m','n','o','p','q','r','s','t','u','v','w','x','y','z']\n\nprint DECODE\nprint [ALPHABET[idx] for idx in DECODE]\n"},{"alpha_fraction":0.6134676337242126,"alphanum_fraction":0.6289501786231995,"avg_line_length":37.806583404541016,"blob_id":"6722fc523b10085c87b5dd4e4738154978fbc2d2","content_id":"0305ab96f4d940ef4fd0f12b0a712221eba3f0cf","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":9430,"license_type":"no_license","max_line_length":127,"num_lines":243,"path":"/PGMcommon.py","repo_name":"indapa/pgmPy","src_encoding":"UTF-8","text":"#!/usr/bin/env python\nfrom Factor import *\nimport numpy as np\nfrom itertools import product\nimport sys\nimport itertools\n\n\ndef getUniqueVar( factorList):\n \"\"\" given factorList which is a list of Factor objects\n return a list of unique variables appearing in the\n Factor objects. See http://stackoverflow.com/a/2151553/1735942 \"\"\"\n\n return list(set().union(*[ list(f.getVar()) for f in factorList ] ))\n\n\ndef isMemberBoolean (A, B):\n \"\"\" returns an list of the same length as A containing True where the elements of A are in B and False otherwise \"\"\"\n \n return [ x in B for x in A ]\n\ndef isMember( A, B):\n \"\"\" return a python list containing indices in B where the elements of A are located\n A and B are numpy 1-d arrays\n mapA[i]=j if and only if B[i] == A[j]\"\"\"\n mapA=[]\n for i in range(len(A)):\n mapA.append( np.where(B==A[i])[0].tolist()[0] )\n\n return mapA\n\n\n\n\ndef accum(accmap, a, func=None, size=None, fill_value=0, dtype=None):\n \"\"\" based on the recipie here to implement a numpy equivalent to matlab accumarray:\n http://www.scipy.org/Cookbook/AccumarrayLike\n An accumulation function similar to Matlab's `accumarray` function.\n\n Parameters\n ----------\n accmap : ndarray\n This is the \"accumulation map\". It maps input (i.e. indices into\n `a`) to their destination in the output array. The first `a.ndim`\n dimensions of `accmap` must be the same as `a.shape`. That is,\n `accmap.shape[:a.ndim]` must equal `a.shape`. For example, if `a`\n has shape (15,4), then `accmap.shape[:2]` must equal (15,4). In this\n case `accmap[i,j]` gives the index into the output array where\n element (i,j) of `a` is to be accumulated. If the output is, say,\n a 2D, then `accmap` must have shape (15,4,2). The value in the\n last dimension give indices into the output array. If the output is\n 1D, then the shape of `accmap` can be either (15,4) or (15,4,1)\n a : ndarray\n The input data to be accumulated.\n func : callable or None\n The accumulation function. The function will be passed a list\n of values from `a` to be accumulated.\n If None, numpy.sum is assumed.\n size : ndarray or None\n The size of the output array. If None, the size will be determined\n from `accmap`.\n fill_value : scalar\n The default value for elements of the output array.\n dtype : numpy data type, or None\n The data type of the output array. If None, the data type of\n `a` is used.\n\n Returns\n -------\n out : ndarray\n The accumulated results.\n\n The shape of `out` is `size` if `size` is given. Otherwise the\n shape is determined by the (lexicographically) largest indices of\n the output found in `accmap`.\n\n\n Examples\n --------\n from numpy import array, prod\n a = array([[1,2,3],[4,-1,6],[-1,8,9]])\n a\n array([[ 1, 2, 3],\n [ 4, -1, 6],\n [-1, 8, 9]])\n # Sum the diagonals.\n accmap = array([[0,1,2],[2,0,1],[1,2,0]])\n s = accum(accmap, a)\n array([9, 7, 15])\n # A 2D output, from sub-arrays with shapes and positions like this:\n # [ (2,2) (2,1)]\n # [ (1,2) (1,1)]\n accmap = array([\n [[0,0],[0,0],[0,1]],\n [[0,0],[0,0],[0,1]],\n [[1,0],[1,0],[1,1]],\n ])\n # Accumulate using a product.\n accum(accmap, a, func=prod, dtype=float)\n array([[ -8., 18.],\n [ -8., 9.]])\n # Same accmap, but create an array of lists of values.\n accum(accmap, a, func=lambda x: x, dtype='O')\n array([[[1, 2, 4, -1], [3, 6]],\n [[-1, 8], [9]]], dtype=object)\n \"\"\"\n\n if accmap.shape[:a.ndim] != a.shape:\n raise ValueError(\"The initial dimensions of accmap must be the same as a.shape\")\n if func is None:\n func = np.sum\n if dtype is None:\n dtype = a.dtype\n if accmap.shape == a.shape:\n accmap = np.expand_dims(accmap, -1)\n adims = tuple(range(a.ndim))\n if size is None:\n size = 1 + np.squeeze(np.apply_over_axes(np.max, accmap, axes=adims))\n size = np.atleast_1d(size)\n size=np.array(size, dtype=int)\n # Create an array of python lists of values.\n vals = np.empty(size, dtype='O')\n for s in product(*[range(k) for k in size]):\n vals[s] = []\n for s in product(*[range(k) for k in a.shape]):\n indx = tuple(accmap[s])\n val = a[s]\n vals[indx].append(val)\n\n # Create the output array.\n out = np.empty(size, dtype=dtype)\n for s in product(*[range(k) for k in size]):\n if vals[s] == []:\n out[s] = fill_value\n else:\n out[s] = func(vals[s])\n\n return out\n\n\n\ndef getIndex ( V, I):\n \"\"\" this method finds for every element of 1d- NumPy array, the index in another 1d-NumPy array\n based off of this StackOverflow answer http://stackoverflow.com/a/8251757/1735942\n V is a numpy 1d array listing the variables of a factor in a PGM\n I is the numpy list reprsenting the intersection of variables between two factors\n\n This method returns the index of the intersection variables in the list V \n \"\"\"\n index=np.argsort(V) #np.argsort gives the index ordering of an array that would result in sorted order\n #http://docs.scipy.org/doc/numpy/reference/generated/numpy.argsort.html\n sorted_v=V[index] #sorted version of V array\n sorted_index=np.searchsorted( sorted_v, I) #i ndices where elements of I would be inserted into sorted_v to maintain order\n #http://docs.scipy.org/doc/numpy/reference/generated/numpy.searchsorted.html\n vindex=np.take(index, sorted_index, mode='clip') #Take elements from an array along an axis.\\\n #http://docs.scipy.org/doc/numpy/reference/generated/numpy.take.html\n #print vindex\n return vindex.tolist()\n\ndef generateAlleleGenotypeMappers( numAlleles):\n \"\"\" analogous to AssignmentToIndex and IndexToAssignment\n this function maps alleles to genotypes and genotypes to alleles\n each allele's id is its index in the list of alleles/list of allele freqs\n Similar for genotypes, its id is its index in list of genotypes\n\n This function returns to numpy 2-d arrays. if n is the number of alleles\n and m is the number of genotypes, then the following NumPy data structures\n are returned\n\n allelesToGenotypes: n x n matrix that maps pairs of allele IDs to\n genotype IDs -- if allelesToGenotypes[i, j] = k, then the genotype with\n ID k comprises of the alleles with IDs i and j\n\n genotypesToAlleles: m x 2 matrix of allele IDs, where m is the number of\n genotypes -- if genotypesToAlleles(k, :) = i, j, then the genotype with ID k\n is comprised of the allele with ID i and the allele with ID j\n\n \"\"\"\n allelesToGenotypes=np.zeros([numAlleles,numAlleles], dtype=np.int)\n index=0\n for i in range(numAlleles):\n for j in range (i,numAlleles):\n allelesToGenotypes[i, j] = index;\n index+=1\n\n for i in range(numAlleles):\n for j in range(0,i):\n allelesToGenotypes[i,j] = allelesToGenotypes[j,i]\n\n\n numGenotypes= (numAlleles * (numAlleles - 1))/2 + numAlleles\n genotypesToAlleles=np.zeros([numGenotypes,2], dtype=np.int)\n\n index=0\n for i in range(numGenotypes):\n for j in range(i,numAlleles):\n #print i, j\n genotypesToAlleles[index, :] = [i, j];\n index+=1\n return ( allelesToGenotypes, genotypesToAlleles)\n\n\ndef genotypeToIndex( geno, alleles='ACGT',ploidy=2):\n \"\"\" given a string enumerating possible alleles\n return the index of geno in enumerated list of genotypes\n by default, the enumerated list is all 10 possibel genotypes\"\"\"\n\n genotypes= [ \"\".join(list(genotype)) for genotype in itertools.combinations_with_replacement(alleles, ploidy) ]\n print genotypes\n \n try:\n return genotypes.index(geno)\n except ValueError:\n print \"genotype not in list of genotypes.\"\n \n\ndef indexToGenotype( index, alleles='ACGT', ploidy=2):\n \"\"\" return genotype at a given index position after\n enumerating all possible genotypes given string of alleles and\n assigning to a list. By default the list contains all possible 10 genotypes\"\"\"\n\n \n genotypes= [ \"\".join(list(genotype)) for genotype in itertools.combinations_with_replacement(alleles, ploidy) ]\n \n try:\n return genotypes[index]\n except IndexError:\n print \"Index out of bounds, not a valid index for list of genotypes\"\n\n\n\ndef lognormalize(x):\n \"\"\"http://atpassos.posterous.com/normalizing-log-probabilities-with-numpy\n 'when working with probabilities it's very easy to get floating point underflows,\n so most people use log probabilities. Probability multiplication is very easy in\n log-space (it's just addition), but probability addition (or normalization) is harder,\n and the linked post gives an equation to compute that. I used to implement it myself,\n but today I learned that numpy does almost everything you need.'\n\n x is (natural) log list/array of numbers\n this normalizes it in probabliity space\"\"\"\n a=np.logaddexp.reduce(x)\n return np.exp(x-a)\n"},{"alpha_fraction":0.6626373529434204,"alphanum_fraction":0.6725274920463562,"avg_line_length":25.764705657958984,"blob_id":"b8ba422539d63a40e51a28785a1acec6f66f6232","content_id":"699408ae88a86444bb8d779c9baf87a651d0865d","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":910,"license_type":"no_license","max_line_length":114,"num_lines":34,"path":"/PythonNotebooks/testComputeExactMaxMarginalsBP.py","repo_name":"indapa/pgmPy","src_encoding":"UTF-8","text":"from Factor import *\nfrom PGMcommon import *\nfrom CliqueTree import *\nfrom CliqueTreeOperations import *\nfrom FactorOperations import *\nimport scipy.io as sio\nimport numpy as np\nimport pprint\nimport pdb\nmatfile='/Users/amit/BC_Classes/PGM/Prog4/PA4Sample.mat'\nmat_contents=sio.loadmat(matfile)\nmat_struct=mat_contents['MaxMarginals']\nval=mat_struct[0,0]\ninput_factors = val['INPUT'][0]\nfactorList=[]\n\nALPHABET=['a','b','c','d','e','f','g','h','i','j','k','l','m','n','o','p','q','r','s','t','u','v','w','x','y','z']\n\nfor tpl in input_factors:\n (var, card, values)=tpl\n #print var, card, values\n f= Factor( var[0].tolist(), card[0].tolist(), values[0].tolist(), 'factor' )\n #print f\n factorList.append( f )\n\nMARGINALS= ComputeExactMarginalsBP( factorList, [], 1 )\n\nfor m in MARGINALS:\n print m\n print \n\nMAPAssignment=MaxDecoding( MARGINALS )\n\nprint [ALPHABET[idx] for idx in MAPAssignment]\n"},{"alpha_fraction":0.6729958057403564,"alphanum_fraction":0.6870604753494263,"avg_line_length":29.80434799194336,"blob_id":"f841b9c048f226eb153184190888b776b9c16e91","content_id":"4050115e93c84fe585b4751c0c64b0e71efca4a8","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1422,"license_type":"no_license","max_line_length":83,"num_lines":46,"path":"/PythonNotebooks/testGetNextC.py","repo_name":"indapa/pgmPy","src_encoding":"UTF-8","text":"import scipy.io as sio\nimport numpy as np\nimport pprint\nfrom Factor import *\nfrom PGMcommon import *\nfrom CliqueTree import *\nfrom CliqueTreeOperations import *\nfrom FactorOperations import *\nimport pickle\n\n\"\"\" load the test data from the matlab file \"\"\"\n\nmatfile='/Users/amit/BC_Classes/PGM/Prog4/PA4Sample.mat'\nmat_contents=sio.loadmat(matfile)\nmat_struct=mat_contents['GetNextC']\nnp.shape(mat_struct)\nval=mat_struct[0,0] \n\ninput_edges = val['INPUT1']['edges'][0][0]\ninput_cliqueList= val['INPUT1']['cliqueList'][0][0][0]\nclique_list_factorObj=[]\nfor tpl in input_cliqueList:\n (var, card, values)=tpl\n f= Factor( var[0].tolist(), card[0].tolist(), values[0].tolist(), 'factor' )\n clique_list_factorObj.append(f)\n\nmessages=val['INPUT2']\nmessageFactors=[]\n(nrow,ncol)=np.shape(messages)\nfor i in range( nrow ):\n for j in range ( ncol ):\n (var, card, values)=messages[i][j]\n f=Factor( var[0].tolist(), card[0].tolist(), values[0].tolist(), 'factor' )\n messageFactors.append(f)\nMESSAGES= np.reshape( np.array ( messageFactors ), (nrow,ncol) )\n\n\n\"\"\" dump it to Python pickle file \"\"\"\nwith open('GetNextC.INPUT1.pickle', 'wb') as f:\n pickle.dump(clique_list_factorObj,f)\nwith open('GetNextC.INPUT2.pickle', 'wb') as f:\n pickle.dump(MESSAGES, f)\n\nP=CliqueTree( clique_list_factorObj , input_edges, clique_list_factorObj, [])\n(a,b)=getNextClique(P,MESSAGES)\nprint 'a: ', a, ' b:', b\n\n\n\n\n\n"},{"alpha_fraction":0.7124645709991455,"alphanum_fraction":0.723796010017395,"avg_line_length":25.148147583007812,"blob_id":"3da136b5d711f3610dcdd7012ff1b9369c21a21b","content_id":"2be847120a8d1e3734495ecd1244c22c27111867","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":706,"license_type":"no_license","max_line_length":80,"num_lines":27,"path":"/PythonNotebooks/testComputeExactMarginalsBP.py","repo_name":"indapa/pgmPy","src_encoding":"UTF-8","text":"from Factor import *\nfrom PGMcommon import *\nfrom CliqueTree import *\nfrom CliqueTreeOperations import *\nfrom FactorOperations import *\nimport scipy.io as sio\nimport numpy as np\nimport pprint\nimport pdb\nmatfile='/Users/amit/BC_Classes/PGM/Prog4/PA4Sample.mat'\nmat_contents=sio.loadmat(matfile)\nmat_struct=mat_contents['ExactMarginal']\nval=mat_struct[0,0]\ninput_factors = val['INPUT'][0]\nfactorList=[]\nfor tpl in input_factors:\n (var, card, values)=tpl\n #print var, card, values\n f= Factor( var[0].tolist(), card[0].tolist(), values[0].tolist(), 'factor' )\n print f\n factorList.append( f )\n print\nM=ComputeExactMarginalsBP( factorList )\n\n#for marginal in M:\n# print marginal\n# print\n"},{"alpha_fraction":0.7310230731964111,"alphanum_fraction":0.7384488582611084,"avg_line_length":21.830188751220703,"blob_id":"0732913f71d3a0e37ce1578a80734298d803125d","content_id":"30737560acaabb2078c7491194efc40255b2bc76","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1212,"license_type":"no_license","max_line_length":82,"num_lines":53,"path":"/PythonNotebooks/testComputeExactMarginalsBP_SixPersonPedigree.py","repo_name":"indapa/pgmPy","src_encoding":"UTF-8","text":"from Factor import *\nfrom PGMcommon import *\nfrom CliqueTree import *\nfrom CliqueTreeOperations import *\nfrom FactorOperations import *\nimport scipy.io as sio\nimport numpy as np\nimport pprint\nimport pdb\n\nmatfile='/Users/indapa/software/PGM/Prog4/PA4Sample.mat'\nmat_contents=sio.loadmat(matfile)\n\nmat_struct=mat_contents['SixPersonPedigree']\nval=mat_struct[0]\n\nfactorList=[]\nfor elem in val:\n \n (var, card, val) =elem\n f= Factor( var[0].tolist(), card[0].tolist(), val[0].tolist(), 'factor' )\n #print f\n factorList.append(f)\n#print\n\njointFactor = ComputeJointDistribution(factorList)\n#print jointFactor\n\nMARGINALS= ComputeExactMarginalsBP( factorList, [], 1)\nP=CreatePrunedInitCtree(factorList, [] )\n(P, MESSAGES) = CliqueTreeCalibrate(P, isMax=1)\njointDistribution=ComputeJointDistributionFromCalibratedCliqueTree(P, MESSAGES, 1)\n\nprint jointDistribution\n\n\n #for marginal in MARGINALS:\n #print marginal\n#print\n\nMAPAssignment=MaxDecoding( MARGINALS )\nprint MAPAssignment\n\n\n #for m in MARGINALS:\n #m.setVal( np.log( lognormalize(m.getVal() ) ) )\n#print np.sum( lognormalize(m.getVal() ) )\n\n#print MAPAssignment\n\n #for marginal in MARGINALS:\n #print marginal.getVal()\n#print\n\n\n"},{"alpha_fraction":0.5498276948928833,"alphanum_fraction":0.5565862655639648,"avg_line_length":34.619049072265625,"blob_id":"28b1213670945b618ae76007849239564e60561a","content_id":"bc4b62dd851aee8a9a7b141e5692c63d02d25d65","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":7546,"license_type":"no_license","max_line_length":129,"num_lines":210,"path":"/CliqueTree.py","repo_name":"indapa/pgmPy","src_encoding":"UTF-8","text":"from Factor import *\nfrom FactorOperations import *\nimport numpy as np\nimport networkx as nx\nimport pdb\n\nclass CliqueTree(object):\n 'represent a Clique tree'\n\n def __init__(self, nodeList=[], edges=[], factorList=[],evidence=[]):\n self.nodeList=nodeList\n self.edges=edges\n self.factorList=factorList\n self.evidence=evidence\n self.card= []\n self.factorInds= []\n\n\n def toString(self):\n \n print 'nodes: ', self.nodeList\n print 'card: ', self.card\n print 'factorList: ', len( self.factorList)\n print 'factorInds:', self.factorInds\n print 'edges:\\n',self.edges\n \n \n def setNodeList(self,nodeList):\n self.nodeList=nodeList\n\n def setEdges(self,edges):\n self.edges=edges\n\n def setFactorList(self,factorList):\n self.factorList=factorList\n #self.factorInds= len( factorList ) * [None]\n\n def setEvidence(self,evidence):\n self.evidence=evidence\n\n\n def setCard(self, cardinality):\n self.card = cardinality\n\n def getNodeList(self):\n return self.nodeList\n\n def getNodeCount(self):\n return len(self.nodeList)\n\n\n def getEdges(self):\n return self.edges\n\n def getFactorList(self):\n return self.factorList\n\n def getFactorCount(self):\n return len(self.factorList)\n \n\n def getEvidence(self):\n return self.evidence\n\n def incorporateEvidence(self):\n for j in range ( len(self.evidence)):\n k=j+1\n if self.evidence[j] > 0:\n self.factorList=ObserveEvidence(self.factorList, np.matrix([[k, self.evidence[j] ]] ) )\n \n\n def eliminateVar(self,Z,E,factorList):\n \"\"\" a variable elimination function\n based on https://github.com/indapa/PGM/blob/master/Prog4/EliminateVar.m\n\n Z is the variable to be eliminated. We base this code on the matlab file\n linked to above as well as the Sum-product VE pseudo code in Koller and Friedman\n page 298\n\n E is a numpy 2d matrix representing adjacency matrix of variables\n It represents the induced VE graph\n Once a variable is eliminated, its edges are removed from E\n\n \"\"\"\n\n useFactors = []#the index of the factor that contains the variable Z\n scope = []\n\n #print 'Z: ', Z\n\n \n #get a list containining the index in self.factorLlist of factors\n #that contain the variable Z to be eliminated\n # get the scope of variables from the factors that contain variable Z\n for i in range (len(factorList)):\n \n if Z in factorList[i].getVar().tolist():\n useFactors.append(i)#the ith factor is being currently involved in elimination\n scope=list(set.union(set(scope), factorList[i].getVar().tolist() ))\n\n \n # update edge map\n \"\"\" These represent the induced edges for the VE graph.\n once the variable Z is eliminated, its edges are removed from the graph\n but in the process of elimination, we create a new factor. This\n introduces fill edges (see pg. 307 Koller and Friedman)\n Z is one based, but the indices in E are zero based, hence Z-1\n also the variable names in scope are 1 based, so we subtract 1 when\n updating the induced VE graph \"\"\"\n\n for i in range ( len(scope)):\n for j in range ( len(scope)):\n if i != j:\n E[ scope[i]-1, scope[j]-1 ]=1\n E[ scope[j]-1, scope[i]-1 ]=1\n E[Z-1,:]=0\n E[:,Z-1]=0\n\n #G=nx.from_numpy_matrix(E)\n #print 'induced graph edges:\\n', (G.edges())\n #nx.draw_shell(G)\n #plt.show()\n\n \n #these are the indices of factorList which are not involved in VE\n unusedFactors= list( set.difference ( set(range(len(factorList))), set(useFactors) ) )\n \n newF=None\n #check first if there are any unused factors left!\n if len(unusedFactors) > 0:\n newF=len(unusedFactors)*[None]\n newmap=np.zeros(max(unusedFactors)+1,dtype=int).tolist()\n \n #newF is a new factor list, we populate it first\n #with the unused factors\n #newmap is maps the new location of ith unusedFactor\n for i in range( len(unusedFactors)):\n newF[i]=factorList[ unusedFactors[i] ]\n newmap[ unusedFactors[i] ]= i\n \n #print 'newmap ', newmap,\"\\n\"\n #print 'length of newmap: ', len(newmap), \"\\n\"\n\n newFactor = Factor( [], [], [], 'newFactor')\n\n #we multiple in all the factors that contain the variable Z\n for i in range( len (useFactors)):\n newFactor = FactorProduct(newFactor,factorList[ useFactors[i] ])\n \n\n #then we marginalize Z out and obtain a new factor\n #then append it the end of newF, the new factor list\n newFactor = FactorMarginalization( newFactor,[Z] )\n #print 'newFactor: ',newFactor\n #newF(length(nonUseFactors)+1) = newFactor;\n if newFactor != None:\n newF.append ( newFactor )\n\n \n\n if newF != None:\n factorList=newF\n #return E\n\n ########################################################################\n \"\"\" the remaining code builds the edges of the clique tree \"\"\"\n\n \"\"\" add new node with the factors that contain the variable Z\n adding a new node represents new clique.\n The scope of every factor generated during the variable elimination process is a clique pg. 309 Koller & Friedman \"\"\"\n\n self.nodeList.append ( scope )\n \n #newC is the total number of nodes in the clique tree\n newC=len( self.nodeList )\n #print 'newC: ', newC\n\n #factorInds are individual factors with one variable ... I think\n self.factorInds.append ( len(unusedFactors) + 1 )\n \n\n #print 'range( newC -1) ', range( newC-1 )\n #print 'factorInds: ', self.factorInds\n #print 'useFactors: ', useFactors\n #pdb.set_trace()\n \"\"\" we update the edges of the clique tree \"\"\"\n for i in range( newC -1 ):\n \n #if self.factorInds [ i ] -1 in useFactors:\n #there was the off by onoe erorr - the values in factorInds\n #were one-based, need to subtract 1\n if self.factorInds [ i ] -1 in useFactors:\n \n self.edges[ i, newC-1 ] = 1\n self.edges [ newC-1, i ] = 1\n self.factorInds[ i ] = 0\n else:\n if self.factorInds [i] != 0:\n #print 'i: ', i\n #print 'factorInds: ', self.factorInds\n #print 'newmap: ', newmap\n #print 'newmap [ self.factorInds[i] -1: ', newmap [ self.factorInds[i] -1 ]\n #print 'self.factorInds[ i ] = newmap [ self.factorInds[i] - 1 ] + 1 '\n if len(unusedFactors) > 0:\n #self.factorInds[ i ] = newmap [ self.factorInds[i] -1 ] +1\n self.factorInds[ i ] = newmap [ self.factorInds[i] -1 ] +1\n #self.factorInds[ i ] = newmap [ self.factorInds[i] ]\n \n #print 'factorInds right before returning: ', self.factorInds\n return E, factorList\n\n \n \n \n \n \n \n\n\n \n"},{"alpha_fraction":0.6040363311767578,"alphanum_fraction":0.6095243692398071,"avg_line_length":32.891998291015625,"blob_id":"5c1ec832317f91ec124a82ea127d3d09b357f2f2","content_id":"7f8e61964fb1ca92ec0a9bb7bc030ecd890dca57","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":16946,"license_type":"no_license","max_line_length":125,"num_lines":500,"path":"/PedigreeFactors.py","repo_name":"indapa/pgmPy","src_encoding":"UTF-8","text":"import sys\nimport numpy as np\nfrom Factor import *\nfrom PGMcommon import *\nfrom FactorOperations import *\nimport itertools\n\nclass PhenotypeFactor (object):\n \"\"\" represents a factor that encodes Pr(phenotype|genotype)\n for purposes here the variable to the left of the conditioning\n bar is the first variable in the PhenotypeFactor var list. \"\"\"\n\n def __init__(self, isDominant, genotypeVar, phenotypeVar, name):\n\n #instantiate a Factor object\n phenotype = Factor( [phenotypeVar, genotypeVar], [2, 3], [], name )\n \n phenotype.setVal( np.zeros ( np.prod(phenotype.getCard())).tolist() )\n #this enumerates the values the factor can take\n # since there are 2x3 cardinality, 6 possible assignments\n assignments=IndexToAssignment( np.arange(np.prod(phenotype.getCard())), phenotype.getCard() )\n val=val = np.zeros(np.prod(phenotype.getCard() ))\n (nrows,ncols)=np.shape(assignments)\n\n for i in range(np.prod([2,3])):\n #if its dominant, if you have at least one copy, you have the phenotype\n (pheno,geno)=assignments[i]\n if isDominant==1:\n if pheno ==1: #affected\n if geno ==1 or geno ==2:\n val[i]=1\n else:\n val[i]=0\n else:#uneffected\n if geno == 3:\n val[i]=1\n\n\n if isDominant == 0:\n if pheno == 1:\n if geno==3:\n val[i]=1\n else:\n if geno ==1 or geno == 2:\n val[i]=1\n\n\n phenotype.setVal( val.tolist() )\n\n self.phenotype=phenotype\n\n\n\n def getVar(self):\n return self.phenotype.getVar()\n def getCard(self):\n return self.phenotype.getCard()\n def getVal(self):\n return self.phenotype.getVal()\n\n def getFactor(self):\n return self.phenotype\n\n def __str__(self):\n return self.phenotype.__str__()\n\n\n\nclass PhenotypeGivenGenotypeFactor(object):\n \"\"\" construct factor of phenotype|genotype\n #prob of being effected, given the ith genotype\n #alphaList[i] is the prob of being effected given the ith genotype \"\"\"\n def __init__(self,alphaList, phenotypeVar, genotypeVar , name):\n self.phenotypeFactor=Factor( [ phenotypeVar, genotypeVar], [], [], name)\n self.alpha=np.array ( alphaList)\n\n ngenotypes=len(alphaList)\n self.phenotypeFactor.setCard( [2, ngenotypes])\n\n values=[x for x in range( np.prod(self.phenotypeFactor.getCard()))]\n\n for i in range( len(alphaList )):\n\n values[i]=alphaList[i]\n values[i+1]=1-alphaList[i]\n ctr=0\n alphas=2*len(alphaList)*[None]\n for i in range(len(alphaList)):\n alphas[ctr]=alphaList[i];\n ctr=ctr+1\n alphas[ctr]=1-alphaList[i];\n ctr=ctr+1\n\n values=alphas\n self.phenotypeFactor.setVal( values)\n\n def getVar(self):\n return self.phenotypeFactor.getVar()\n def getCard(self):\n return self.phenotypeFactor.getCard()\n def getVal(self):\n return self.phenotypeFactor.getVal()\n def setVal(self,val):\n self.phenotypeFactor.setVal(val)\n def getFactor(self):\n return self.phenotypeFactor\n\n\n def __str__(self):\n return self.phenotypeFactor.__str__()\n\n\nclass GenotypeAlleleFreqFactor (object):\n \"\"\" construct a factor that has the probability of each genotype\n given allele frequencies Pr(genotype|allele_freq)\"\"\"\n\n def __init__(self, allelefreqs, genotypeVar, name):\n self.allelefreq=allelefreqs\n #number of alleles == number of allele frequencies passed in\n numAlleles=len(allelefreqs)\n self.allelesToGenotypes=None\n self.genotypesToAlleles=None\n self.genotypeFactor=None\n\n #map alleles to genotypes and genotyeps to alleles\n (self.allelesToGenotypes, self.genotypesToAlleles)=generateAlleleGenotypeMappers(numAlleles)\n (ngenos,ploidy)=np.shape(self.genotypesToAlleles)\n\n\n self.genotypeFactor = Factor( [genotypeVar], [], [], name)\n #the cardinality of the factor is the number of genotypes\n self.genotypeFactor.setCard( [ngenos] )\n\n #set the values to zero initially\n values=np.zeros( (np.prod(self.genotypeFactor.getCard()))).tolist()\n \n for i in range (ngenos):\n alleles=self.genotypesToAlleles[i,:].tolist()\n \n\n if alleles[0] == alleles[1]:\n values[i]= np.prod( [ allelefreqs[j] for j in alleles ])\n \n else:\n values[i]= np.prod( [ allelefreqs[j] for j in alleles ]) * 2\n \n self.genotypeFactor.setVal( values )\n\n\n def getVar(self):\n return self.genotypeFactor.getVar()\n def getCard(self):\n return self.genotypeFactor.getCard()\n def getVal(self):\n return self.genotypeFactor.getVal()\n def setVal(self,val):\n self.genotypeFactor.setVal(val)\n def getFactor(self):\n return self.genotypeFactor\n\n\n def __str__(self):\n return self.genotypeFactor.__str__()\n\nclass GenotypeGivenParentsFactor (object):\n \"\"\" construct factor that has prob of genotype of child given both parents\n Pr(g_child| g_mother, g_father \"\"\"\n\n def __init__(self,numAlleles, genotypeVarChild, genotypeVarParentOne, genotypeVarParentTwo, name):\n self.genotypeFactor = Factor( [genotypeVarChild, genotypeVarParentOne, genotypeVarParentTwo ], [ ], [ ], name)\n\n #map alleles to genotypes and genotyeps to alleles\n (self.allelesToGenotypes, self.genotypesToAlleles)=generateAlleleGenotypeMappers(numAlleles)\n\n (ngenos,ploidy)=np.shape(self.genotypesToAlleles)\n \n\n \n self.genotypeFactor.setCard([ ngenos,ngenos,ngenos ] )\n #set the values to zero initially\n values=np.zeros( (np.prod(self.genotypeFactor.getCard()))).tolist()\n\n #iterate thru variable assignments to random variables\n #assign probablities based on Punnet square crosses\n assignments=IndexToAssignment( np.arange(np.prod(self.genotypeFactor.getCard())), self.genotypeFactor.getCard() )-1\n for z in range( np.prod(self.genotypeFactor.getCard() ) ):\n curr_assign= assignments[z]\n childAssignment=int(curr_assign[0])\n\n parent1gametes= self.genotypesToAlleles[curr_assign[1],:]\n parent2gametes= self.genotypesToAlleles[curr_assign[2],:]\n #print 'parental gametes: ', parent1gametes, parent2gametes\n #print 'child assignment: ', childAssignment\n #list of tuples containing list of zygote(genotype) tuples\n zygote_list=list(itertools.product(parent1gametes,parent2gametes))\n punnet_freq=[ self.allelesToGenotypes[zygote[0],zygote[1]] for zygote in zygote_list ]\n histc={}\n hist=[]\n for g in range( ngenos):\n histc[g]=0.\n for x in punnet_freq:\n histc[x]+=1.\n #print histc.values()\n for g in range (ngenos):\n hist.append ( histc[g] )\n #print punnet_freq\n hist=(np.array ( hist)) /4\n #print 'hist:', hist\n #print zygote_list\n values[z]=hist[childAssignment]\n\n self.genotypeFactor.setVal( values )\n\n def getVar(self):\n return self.genotypeFactor.getVar()\n def getCard(self):\n return self.genotypeFactor.getCard()\n def getVal(self):\n return self.genotypeFactor.getVal()\n def setVal(self, val):\n self.genotypeFactor.setVal(val)\n\n def getFactor(self):\n return self.genotypeFactor\n def genotypeSlice(self):\n pass\n #see this http://stackoverflow.com/q/4257394/1735942\n\n def __str__(self):\n return self.genotypeFactor.__str__()\n\n\nclass ChildCopyGivenParentalsFactor(object):\n \"\"\" this represents a de-coupled factor\n given a parents two haplotypes, returns\n factor whose values are the probablity\n of inheriting (grand)paternal or (grand)maternal\n haplotype. This allows for some more flexibility\n in modeling inheritance, rather than clumping\n a single parent's haplotype into a genotype\n i.e. GenotypeGivenParentsFactor \"\"\"\n\n def __init__(self, numAlleles, geneCopyVarChild, geneCopyHapOne, geneCopyHapTwo):\n self.numalleles=numAlleles\n self.hapone=geneCopyVarChild\n self.haptwo=geneCopyHapTwo\n\n #geneCopyFactor = struct('var', [], 'card', [], 'val', []);\n self.geneCopyFactor=Factor( [geneCopyVarChild, geneCopyHapOne, geneCopyHapTwo ], [], [], 'child|hap1,hap2')\n self.geneCopyFactor.setCard( [self.numalleles,self.numalleles,self.numalleles ])\n values=np.zeros( np.prod([ self.numalleles,self.numalleles,self.numalleles])).tolist()\n #this keeps track of what posiiton you are in the values list\n index=0\n #the number of iterations thru the nested for loops should be equal to numallels^3\n\n for i in range(numAlleles):\n #iterate through alleles from\n #grand(paternal) haplotype\n for j in range(numAlleles):\n #iterate through alleles from\n #grand(maternal) haplotype\n for k in range(numAlleles):\n #iterate thru child alleles\n print i, j, k\n if j==k:#child has grandmotherhap\n if i==k:#grandfatherhap is the same\n values[index]=1\n else:\n values[index]=.5\n elif i==k:#child has grandfather hap\n values[index]=.5\n else:\n pass\n index+=1\n #print values\n self.geneCopyFactor.setVal( values )\n\n def getVar(self):\n return self.geneCopyFactor.getVar()\n def getCard(self):\n return self.geneCopyFactor.getCard()\n def getVal(self):\n return self.geneCopyFactor.getVal()\n def getFactor(self):\n return self.geneCopyFactor\n def __str__(self):\n return self.geneCopyFactor.__str__()\n \nclass ChildCopyGivenFreqFactor(object):\n \"\"\" for a founder, its particular haplotype is proprortional to the\n given allelel freq of the locus. This factor is part of the decoupled\n Bayesian Genetic network , along with ChildCopyGivenParentalsFactor\"\"\"\n \n def __init__(self, alleleFreqs, geneCopyVar):\n numAlleles = len(alleleFreqs)\n self.geneCopyFactor=Factor( [geneCopyVar], [], [], 'founderHap')\n self.geneCopyFactor.setCard ( [numAlleles])\n self.geneCopyFactor.setVal( alleleFreqs )\n #geneCopyFactor = struct('var', [], 'card', [], 'val', [])\n #geneCopyFactor.var(1) = geneCopyVar;\n #geneCopyFactor.card(1) = numAlleles;\n #geneCopyFactor.val = alleleFreqs';\n\n\n def getVar(self):\n return self.geneCopyFactor.getVar()\n def getCard(self):\n return self.geneCopyFactor.getCard()\n def getVal(self):\n return self.geneCopyFactor.getVal()\n def getFactor(self):\n return self.genCopyFactor\n def __str__(self):\n return self.geneCopyFactor.__str__()\n\nclass phenotypeGivenHaplotypesFactor(object):\n \"\"\" factor represents Pr(phenotype| paternal haplotype, maternal haplotype)\n very similiar to PhenotypeGivenGenotypeFactor, but we are de-coupling into\n paternal and maternal alleles rather than genotype\"\"\"\n\n def __init__(self, alphaList, numAlleles, geneCopyVarOne, geneCopyVarTwo, phenotypeVar):\n \n self.numalleles=numAlleles\n self.alphaList=alphaList\n self.phenotypeFactor=Factor([phenotypeVar,geneCopyVarOne, geneCopyVarTwo], [], [], 'phenotype| geneCopy1, geneCopy2')\n\n ngenos=len(alphaList)\n self.phenotypeFactor.setCard( [ 2, numAlleles, numAlleles])\n #phenotypeFactor.val = zeros(1, prod(phenotypeFactor.card));\n values=np.zeros( (1, np.prod(self.phenotypeFactor.getCard()))).flatten().tolist()\n\n affectedAlphas=alphaList\n unaffectedAlphas=[ 1- alpha for alpha in alphaList]\n\n\n (allelesToGenotypes, genotypesToAlleles) = generateAlleleGenotypeMappers(numAlleles)\n assignments=IndexToAssignment( np.arange(np.prod(self.phenotypeFactor.getCard())), self.phenotypeFactor.getCard() )-1\n for z in range( np.prod(self.phenotypeFactor.getCard() ) ):\n curr_assign= assignments[z]\n curr_assign=assignments[z]\n genotype_num=allelesToGenotypes[curr_assign[1], curr_assign[2]]\n if curr_assign[0] == 0:\n values[z] = affectedAlphas[genotype_num]\n else:\n values[z] = unaffectedAlphas[genotype_num]\n self.phenotypeFactor.setVal( values )\n\n\n #genotype_num=allelesToGenotypes(assignment(2), assignment(3));\n\n\n def getVar(self):\n return self.phenotypeFactor.getVar()\n def getCard(self):\n return self.phenotypeFactor.getCard()\n def getVal(self):\n return self.phenotypeFactor.getVal()\n def getFactor(self):\n return self.phenotypeFactor\n def __str__(self):\n return self.phenotypeFactor.__str__()\n\n def __str__(self):\n return self.phenotypeFactor.__str__()\n\n\n##########################\n\nclass Ped(object):\n \"\"\" represents a pedigree record in a Ped file http://pngu.mgh.harvard.edu/~purcell/plink/data.shtml#ped \"\"\"\n\n def __init__(self,famid='.', indv='.', paternal='.', maternal='.', sex='.', phenotype='.'):\n \"\"\" attributes of a Ped object \"\"\"\n self.famid=famid\n self.individ=indv\n self.pid=paternal\n self.mid=maternal\n self.sex=sex\n self.pheno=phenotype\n\n\n def setfamid(self,famid):\n self.famid=famid\n\n def setindvid(self,indv):\n self.individ=indv\n\n def setmid(self,mid):\n self.mid=mid\n\n def setpid(self,pid):\n self.pid=pid\n\n def setsex(self,sex):\n self.sex=sex\n\n def setpheno(self,pheno):\n self.pheno=pheno\n\n\n\n def getfamid(self):\n return self.famid\n\n def getid(self):\n return self.individ\n\n def getmid(self):\n return self.mid\n\n def getpid(self):\n return self.pid\n\n def getsex(self):\n return self.sex\n\n def getpheno(self):\n return self.pheno\n\n\n def isFounder(self):\n return self.pid == '0' and self.mid == '0'\n\n def getParents(self):\n\n return ( self.pid, self.mid)\n\n\n def __str__(self):\n return \"\\t\".join( [ self.famid, self.individ, self.pid, self.mid, self.sex, self.pheno] )\n\n\nclass Pedfile(object):\n \"\"\" a Pedfile object has a list of Ped objects \"\"\"\n\n def __init__(self,filename):\n self.filename=filename\n self.fh=open(self.filename, 'r')\n self.pedlist=[]\n\n def parsePedfile(self):\n \"\"\" given a filehandle to a *.ped file read its contents and populate the list pedlist with Ped objects \"\"\"\n for line in self.fh:\n fields=line.strip().split('\\t')\n (famid, indv, pid, mid, sex, pheno)=fields[0:6]\n self.pedlist.append( Ped(famid, indv, pid, mid, sex, pheno) )\n\n \n def returnFounders(self):\n \"\"\" return the founders in a ped file (those with unknown paternal and maternids \"\"\"\n founders=[]\n\n for pedobj in self.pedlist:\n if pedobj.getpid() == \"0\":\n founders.append(pedobj)\n\n return founders\n\n def returnFounderIds(self):\n \"\"\" return the indiv ids of the founders in the ped file\"\"\"\n founderids=[]\n for pedobj in self.pedlist:\n if pedobj.getpid() == \"0\":\n founderids.append( pedobj.getid() )\n return founderids\n\n def returnNonFounderIds(self):\n \"\"\" return the indiv ids of the founders in the ped file\"\"\"\n nonfounderids=[]\n for pedobj in self.pedlist:\n if pedobj.getpid() != \"0\":\n nonfounderids.append( pedobj.getid() )\n return nonfounderids\n\n def returnNonFounders(self):\n \"\"\" return the founders in a ped file (those with unknown paternal and maternids \"\"\"\n nonfounders=[]\n\n for pedobj in self.pedlist:\n if pedobj.getpid() != \"0\":\n nonfounders.append(pedobj)\n\n return nonfounders\n\n def returnIndivids(self):\n \"\"\" return a list of indvi ids from the ped file \"\"\"\n #samplelist=[]\n return [ ped.getid() for ped in self.pedlist]\n\n def getPedList(self):\n return self.pedlist\n def getTotalSize(self):\n return len(self.pedlist)\n\n def yieldMembers(self):\n for pedobj in self.pedlist:\n yield pedobj\n\n def __str__(self):\n return \"\\n\".join( [ x.__str__() for x in self.pedlist ] )\n"},{"alpha_fraction":0.6863157749176025,"alphanum_fraction":0.7442105412483215,"avg_line_length":29.645160675048828,"blob_id":"0a1a76b17b4d700f9be7186e8dd219773d8cc43a","content_id":"e8c8f724f79ebda14e822822476b89c63b38eef7","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":950,"license_type":"no_license","max_line_length":77,"num_lines":31,"path":"/PythonNotebooks/testFactorMaxMarginal.py","repo_name":"indapa/pgmPy","src_encoding":"UTF-8","text":"from Factor import *\nfrom PGMcommon import *\nfrom CliqueTree import *\nfrom CliqueTreeOperations import *\nfrom FactorOperations import *\nimport scipy.io as sio\nimport numpy as np\nimport pprint\nimport pdb\nmatfile='/Users/amit/BC_Classes/PGM/Prog4/PA4Sample.mat'\nmat_contents=sio.loadmat(matfile)\nmat_struct=mat_contents['FactorMax']\nval=mat_struct[0,0]\ninput_factors = val['INPUT1'][0][0]\nvar = input_factors[0].flatten().tolist()\ncard=input_factors[1].flatten().tolist()\nvalue=input_factors[2].flatten().tolist()\nprint var\nprint card\nprint value\nINPUT1= Factor( var, card, value, 'test')\nINPUT2= val['INPUT2'].flatten()\nprint INPUT1\nprint INPUT2\nprint FactorMaxMarginalization(INPUT1, INPUT2)\n#example used in section 13.2 pg 555 of Friedman and Koller\nprint \"=====\"\npsi=Factor( [ 1,2,3], [3,2,2], [.25,.05,.15,.08,0,.09,.35,.07,.21,.16,0,.18])\nmaxfactor= FactorMaxMarginalization(psi, [2])\nprint maxfactor\nprint IndexToAssignment(np.arange(6),[3,2])\n"},{"alpha_fraction":0.7376237511634827,"alphanum_fraction":0.7514851689338684,"avg_line_length":19.612245559692383,"blob_id":"86ff9b6732bcf620cf67d00014f02397c8fa240d","content_id":"54f67628fbc30361e5623bc83d6eed66e3c68a05","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1010,"license_type":"no_license","max_line_length":78,"num_lines":49,"path":"/PythonNotebooks/testCliqueTreeOperations.py","repo_name":"indapa/pgmPy","src_encoding":"UTF-8","text":"import sys\nimport numpy as np\nfrom Factor import *\nfrom PGMcommon import *\nfrom PedigreeFactors import *\nfrom FactorOperations import *\nfrom GeneticNetworkFactory import *\nfrom CliqueTree import *\nimport networkx as nx\nimport matplotlib.pyplot as plt\nfrom CliqueTreeOperations import *\n#to create a clique tree, we start with a list of factors\n#and potentially some observed evidence\nalphaList=[.8,.6,.1]\nallelefreq=[.1,.9]\nchrom='12'\nposition=1000\ng1=GeneticNetworkFactory('sixperson.ped',alphaList,allelefreq, chrom,position)\ng1.constructNetwork()\nfactorList=g1.getFactorList()\n\n#for f in factorList:\n# print f\n# print \n#print \"+++++++++\"\n\ncTree = createCliqueTree(factorList)\nG=nx.from_numpy_matrix( cTree.getEdges() )\n\nnx.draw_shell(G)\nplt.show()\n#print cTree.getEdges()\n\n#cTree.toString()\n\n\nprunedCTree=PruneTree( cTree )\nP=CliqueTreeInitialPotential( prunedCTree )\n\n#for f in P.getNodeList():\n# print f\n# print\n\n\n\n\nG=nx.from_numpy_matrix( prunedCTree.getEdges() )\nnx.draw_shell(G)\nplt.show()\n"},{"alpha_fraction":0.5923784971237183,"alphanum_fraction":0.5969107151031494,"avg_line_length":39.27850341796875,"blob_id":"b5132ff6c2652a9dccd8fb63ae78206208620c59","content_id":"371be786bccdbdfa6ed14e3f39ed6e62084ca22a","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":21623,"license_type":"no_license","max_line_length":172,"num_lines":535,"path":"/CliqueTreeOperations.py","repo_name":"indapa/pgmPy","src_encoding":"UTF-8","text":"import numpy as np\nfrom CliqueTree import *\nfrom FactorOperations import *\n#import matplotlib.pyplot as plt\nimport networkx as nx\nimport pdb\n\ndef createCliqueTree( factorList,E=[]):\n \"\"\" return a Clique Tree object given a list of factors\n it peforms VE and returns the clique tree the VE\n ordering defines. See Chapter 9 of Friedman and Koller\n Probabilistic Graphical Models\"\"\"\n\n V=getUniqueVar(factorList)\n \n totalVars=len(V)\n cardinality=np.zeros(len(V)).tolist()\n for i in range(len(V)):\n for j in range(len(factorList)):\n try:\n indx= factorList[j].getVar().tolist().index( V[i] )\n cardinality[i]=factorList[j].getCard().tolist()[indx]\n break\n except:\n continue\n\n edges=np.zeros( (totalVars, totalVars))\n\n\n \"\"\" Set up adjacency matrix: for each factor, get the list of variables in its scope and create an edge between each variable in the factor \"\"\"\n for f in factorList:\n variableList=f.getVar()\n for j in range(len(variableList) ):\n for k in range (len(variableList) ):\n edges[ variableList[j]-1, variableList[k]-1 ]=1\n\n (nrows,nedges)=np.shape(edges) \n\n C=CliqueTree()\n C.setCard( cardinality )\n C.setEdges(np.zeros( (totalVars, totalVars)))\n C.setFactorList(factorList)\n C.setEvidence(E)\n C.setNodeList([])\n #print 'length of factorList: ', len(factorList)\n #print C.toString()\n cliquesConsidered = 0\n #pdb.set_trace()\n while cliquesConsidered < len(V):\n bestClique = 0\n bestScore = sys.maxint\n for i in range(nrows):\n score=np.sum( edges[i,:] )\n if score > 0 and score < bestScore:\n bestScore = score\n bestClique = i+1\n cliquesConsidered+=1\n \n (edges, factorList)=C.eliminateVar(bestClique, edges, factorList)\n\n return C\n\n\ndef PruneTree ( C ):\n \"\"\" prune a clique tree by determing if neighboring cliques are \n supersets of each other. E.g.: [A,B,E] -- [A,B] -- [A,D] \n pruned: [A,B,E] -- [A,D] \"\"\"\n\n ctree_edges=C.getEdges()\n (nrows,ncols)=np.shape( ctree_edges )\n totalNodes=nrows\n Cnodes=C.getNodeList()\n \n toRemove=[]\n #print range( totalNodes )\n\n for i in range ( totalNodes ):\n if i in toRemove: continue\n #np.nonzero returns tuple, hence the [0]\n #we collect the neighbors of the ith clique\n neighborsI = np.nonzero ( ctree_edges[i,:] )[0].tolist()\n for c in range ( len(neighborsI) ):\n j= neighborsI[c]\n assert ( i != j), 'i cannot equal j: PruneTree'\n if j in toRemove: continue\n #here is where we look for superset neighboring nodes in the CTree\n if sum ( [ x in Cnodes[j] for x in Cnodes[i] ] ) == len( Cnodes[i] ):\n for nk in neighborsI:\n cnodes_i = set ( Cnodes[i] )\n cnodes_nk= set ( Cnodes[nk] )\n if len( list ( set.intersection( cnodes_i, cnodes_nk) ) ) == len (Cnodes[i]):\n neighborsI_set=set( neighborsI )\n nk_set=set( [nk] )\n ctree_edges [ list( neighborsI_set - nk_set ), nk ] = 1\n ctree_edges [ nk, list( neighborsI_set - nk_set )] = 1\n break\n ctree_edges[i,:]=0\n ctree_edges[:,i]=0\n toRemove.append(i)\n toKeep = list ( set ( range( totalNodes ) ) - set ( toRemove ) )\n for indx in toRemove:\n Cnodes[indx]=[]\n Cnodes=[ item for item in Cnodes if len(item) > 0 ]\n ctree_edges= ctree_edges[np.ix_(toKeep, toKeep)]\n\n C.setNodeList( Cnodes )\n C.setEdges( ctree_edges )\n #pdb.set_trace()\n #return the pruned tree with the updated nodes and edges\n return C\n\ndef CliqueTreeObserveEvidence ( C, E ):\n \"\"\" given a CliqueTree object C and list of values E, which represent evidence, update\n the factors of the cliqueTree C to reflect the observed evidence.\n Note that ObserveEvidence in FactorOperations assumes E is a Nx2 matrix,\n here we build the Nx2 matrix by assuing the jth index of E is the evidence\n for the variable j\"\"\"\n factorList= C.getFactorList()\n for j in range ( len (E)):\n if E[j] > 0:\n factorList=ObserveEvidence( factorList, np.array(np.matrix( [ j+1, E[j]] ) ) )\n C.setFactorList(factorList)\n #return the new CliqueTree object with the updated evidence\n return C\n\n\ndef CliqueTreeInitialPotential( C ):\n \"\"\" given a clique tree object C, calculate the initial potentials for each of the cliques\n the factors in the updated clique list are FActor objects\"\"\"\n\n \n N= C.getNodeCount()\n totalFactorCount=C.getFactorCount()\n\n nodeList=C.getNodeList()\n factorList=C.getFactorList()\n\n cliqueList=[ Factor( [], [], [], str(i) ) for i in range(N) ]\n #edges=np.zeros( (N,N) )\n\n \"\"\" First assign the factors to appropriate cliques\n based on the skeleton cliqueTree cTree\"\"\"\n\n factorsUsed=np.zeros( totalFactorCount, dtype=int).tolist()\n #pdb.set_trace()\n for i in range(N):\n cliqueList[i].setVar( nodeList[i] )\n F=[]\n \"\"\" we add factors to the clique if they are in the variable scope of the clique \"\"\"\n for j in range( len(factorList) ):\n if len( factorList[j].getVar().tolist() ) == len ( list( set.intersection ( set(cliqueList[i].getVar().tolist() ), set( factorList[j].getVar().tolist() ) ) ) ):\n \n if factorsUsed[j] == 0:\n F.append( factorList[j] )\n factorsUsed[j] = 1\n #print F\n #pdb.set_trace()\n #F= [ f.getFactor() for f in F ]\n cliqueList[i]=ComputeJointDistribution ( F )\n #pdb.set_trace()\n C.setNodeList(cliqueList)\n #pdb.set_trace()\n return C\n\ndef getNextClique(P, messages):\n\n \"\"\" we need to come up wih a proper message passing order. A clique is ready to pass\n messages upward once its recieved all downstream messages from its neighbor (and vice versa)\n its ready to transmit downstream once it recieves all its upstream messages\n\n the ith clique C_i is ready to transmit to its neighbor C_j when C_i recieves all its\n messages from neigbors except C_j. In cTree message passing, each message is passed\n once. To get the process started we start with our initial potential cTree, P\n and an empty matrix of factors, representing messages passed between the nodes on the clique\n tree \"\"\"\n i=j=-1\n edges=P.getEdges()\n #print edges\n (nrow, ncol) = np.shape(edges)\n\n for r in range(nrow):\n \n #we want to ignore nodes with only one neighbor\n #becuae they are ready to pass messages\n if np.sum(edges[r,:] ) == 1:\n continue \n\n foundmatch=0\n\n for c in range(ncol):\n if edges[r,c] == 1 and messages[r,c].getVarCount() == 0:\n #list of indices indicating neighbors or r\n #print 'r,c: ', r, ' ', c\n #print 'edges[r,c]: ', edges[r,c]\n Nbs=np.nonzero(edges[:,r])[0]\n #print 'Nbs before:', Nbs\n Nbs=Nbs[np.nonzero(Nbs!= c)[0]]\n #print 'Nbs after: ', Nbs\n allnbmp=1 #neighbors messages passed?\n \n #find all of r's neighbors have sent messages *to* r\n for z in range( len(Nbs) ):\n #print messages[Nbs[z],r].getVarCount()\n if messages[ Nbs[z],r].getVarCount() == 0:\n allnbmp=0\n\n if allnbmp == 1:\n foundmatch=1\n break\n \n if foundmatch==1:\n #sys.stderr.write(\"found match!\\n\")\n i=r\n j=c\n break\n \n return (i,j)\n\n\ndef CliqueTreeCalibrate( P, isMax=False):\n \"\"\" this function performs sum-product or max-product algorithm for clique tree calibration.\n P is the CliqueTree object. isMax is a boolean flag that when set to True performs Max-Product\n instead of the default Sum-Product. The function returns a calibrated clique tree in which the\n values of the factors is set to final calibrated potentials.\n\n Once a tree is calibrated, in each clique (node) contains the marginal probability over the variables in\n its scope. We can compute the marginal probability of a variable X by choosing a clique that contains the\n variable of interest, and summing out non-query variables in the clique. See page 357 in Koller and Friedman\n\n B_i(C_i)= sum_{X-C_i} P_phi(X)\n\n The main advantage of clique tree calibration is that it facilitates the computation of posterior\n probabliity of all variables in the graphical model with an efficient number of steps. See pg 358\n of Koller and Friedman\n\n After calibration, each clique will contain the marginal (or max-mariginal, if isMax is set to True)\n\n \"\"\"\n \n np.set_printoptions(suppress=True)\n ctree_edges=P.getEdges()\n\n ctree_cliqueList=P.getNodeList()\n\n \"\"\" if max-sum, we work in log space \"\"\"\n if isMax == True:\n ctree_cliqueList= [ LogFactor (factor) for factor in ctree_cliqueList ]\n\n \n \n N=P.getNodeCount() #Ni is the total number of nodes (cliques) in cTree\n\n #dummyFactor=Factor( [], [], [], 'factor')\n #set up messsages to be passed\n #MESSAGES[i,j] represents the message going from clique i to clique j\n #MESSAGES will be a matrix of Factor objects\n MESSAGES=np.tile( Factor( [], [], [], 'factor'), (N,N))\n DUMMY=np.reshape( np.arange(N*N)+1, (N,N) )\n \n\n \"\"\"While there are ready cliques to pass messages between, keep passing\n messages. Use GetNextCliques to find cliques to pass messages between.\n Once you have clique i that is ready to send message to clique\n j, compute the message and put it in MESSAGES(i,j).\n Remember that you only need an upward pass and a downward pass.\"\"\"\n\n \"\"\" leaf nodes are ready to pass messages right away\n so we initialize MESSAGES with leaf message factors\n recall, a node is a leave if row sum is equal to 1\"\"\"\n for row in range(N):\n rowsum= np.sum( ctree_edges[row,:] )\n if rowsum ==1 :\n #Returns a tuple of arrays, one for each dimension, we want the first, hence the [0]\n leafnode=np.nonzero( ctree_edges[row,:] )[0].tolist()[0]\n #I discovered NumPy set operations http://docs.scipy.org/doc/numpy/reference/routines.set.html\n marginalize=np.setdiff1d( ctree_cliqueList[row].getVar(), ctree_cliqueList[leafnode].getVar() ).tolist()\n sepset=np.intersect1d( ctree_cliqueList[row].getVar(), ctree_cliqueList[leafnode].getVar() ).tolist()\n\n \"\"\" if isMax is false, this is sumproduct, so we do factor marginalization \"\"\"\n if isMax == 0:\n #MESSAGES(row,leafnode)=FactorMarginalization(P.cliqueList(row),marginalize);\n MESSAGES[row,leafnode]=FactorMarginalization(ctree_cliqueList[row], marginalize )\n if np.sum( MESSAGES[row,leafnode].getVal() ) != 1:\n newVal=MESSAGES[row,leafnode].getVal() / np.sum( MESSAGES[row,leafnode].getVal() )\n MESSAGES[row,leafnode].setVal(newVal)\n else:\n \"\"\" if isMax is true, this is max-marginalization\n don't normalize the value just yet\"\"\"\n MESSAGES[row,leafnode]=FactorMaxMarginalization( ctree_cliqueList[row], marginalize )\n\n\n \n \"\"\" now that the leaf messages are initialized, we begin with the rest of the clique tree\n now we do a single pass to arrive at the calibrated clique tree. We depend on\n GetNextCliques to figure out which nodes i,j pass messages to each other\"\"\"\n \n while True:\n (i,j)=getNextClique(P,MESSAGES)\n if sum ( [ i, j] ) == -2:\n break\n #print 'i: ', i, 'j: ', j\n \"\"\" similiar to above, we figure out the sepset and what variables to marginalize out\n between the two cliques\"\"\"\n marginalize=np.setdiff1d( ctree_cliqueList[i].getVar(), ctree_cliqueList[j].getVar() ).tolist()\n sepset=np.intersect1d( ctree_cliqueList[i].getVar(), ctree_cliqueList[j].getVar() ).tolist()\n\n \"\"\" find all the incoming neighbors, except j \"\"\"\n Nbs=np.nonzero( ctree_edges[:,i])[0] #returns a tuple ...\n Nbs_minusj=[ elem for elem in Nbs if elem != j ]\n #print 'Nbs_minusj: ', Nbs_minusj, ' [i]: ', [i]\n #see numpy for matlab users http://www.scipy.org/NumPy_for_Matlab_Users\n # these are incoming messages to the ith clique\n Nbsfactors=MESSAGES[np.ix_(Nbs_minusj, [i] )].flatten().tolist()\n #print DUMMY[np.ix_(Nbs_minusj, [i] )].flatten()\n #for f in Nbsfactors:\n #print f\n \"\"\" this is sum/product \"\"\"\n if isMax == 0:\n #print 'total number of Nbs factors: ', len(Nbsfactors)\n if len(Nbsfactors) == 1:\n Nbsproduct=FactorProduct( Nbsfactors[0], IdentityFactor(Nbsfactors[0]) )\n else:\n Nbsproduct=ComputeJointDistribution( Nbsfactors )\n #pdb.set_trace()\n #val=Nbsproduct.getVal()\n #rowcount=len(val)/3\n #print Nbsproduct.getVar()\n #print Nbsproduct.getCard()\n #print np.reshape( val, (rowcount,3))\n #now mulitply wiht the clique factor\n \n CliqueNbsproduct=FactorProduct( Nbsproduct, ctree_cliqueList[i] )\n \n CliqueMarginal= FactorMarginalization ( CliqueNbsproduct, marginalize )\n \n #normalize the marginal\n newVal=CliqueMarginal.getVal() / np.sum( CliqueMarginal.getVal() )\n\n CliqueMarginal.setVal( newVal )\n \n MESSAGES[i,j] = CliqueMarginal\n else:\n if len(Nbsfactors) == 1:\n Nbssum=Nbsfactors[0]\n else:\n Nbssum=reduce ( lambda x,y: FactorSum(x,y), Nbsfactors )\n CliqueNbsSum=FactorSum( Nbssum, ctree_cliqueList[i] )\n CliqueMarginal=FactorMaxMarginalization( CliqueNbsSum, marginalize )\n MESSAGES[i,j] = CliqueMarginal\n #print\n\n\n\n #######################################################################\n \"\"\" once out the while True loop, the clique tree has been calibrated\n here is where we compute final belifs (potentials) for the cliques and place them in \"\"\"\n\n for i in range ( len(ctree_cliqueList)):\n Nbs=np.nonzero( ctree_edges[:,i])[0]#returns a tuple\n Nbsfactors=MESSAGES[np.ix_(Nbs, [i])].flatten().tolist()\n\n if isMax == 0:\n if len(Nbsfactors) == 1:\n Nbsproduct=FactorProduct( Nbsfactors[0], IdentityFactor(Nbsfactors[0]) )\n else:\n Nbsproduct=ComputeJointDistribution ( Nbsfactors)\n \n CliqueNbsProduct=FactorProduct(Nbsproduct, ctree_cliqueList[i])\n #pdb.set_trace()\n ctree_cliqueList[i]=CliqueNbsProduct\n else:\n if len(Nbsfactors) == 1:\n Nbssum=Nbsfactors[0]\n else:\n Nbssum=reduce ( lambda x,y: FactorSum(x,y), Nbsfactors )\n CliqueNbsSum=FactorSum(Nbssum, ctree_cliqueList[i])\n ctree_cliqueList[i]=CliqueNbsSum\n \n P.setNodeList( ctree_cliqueList )\n #np.savetxt( 'numpy.cTree.edges.calibrated.txt',ctree_edges,fmt='%d', delimiter='\\t')\n \n #pdb.set_trace()\n #return P\n return (P, MESSAGES)\n #for k in range(len(ctree_cliqueList)):\n # print 'k: ', k\n # print ctree_cliqueList[k]\n #IndexToAssignment(1:prod(P.cliqueList(1).card), P.cliqueList(1).card)\n # I=np.arange(np.prod( ctree_cliqueList[k].getCard() ))\n # print IndexToAssignment( I, ctree_cliqueList[k].getCard() )\n # print \"==\"\n\n #return P\n\n\ndef CreatePrunedInitCtree(F,E=[]):\n \"\"\" 1. create cTree from list of factors F and evidence E\n 2. prune it\n 3. compute initial potential of the tree\n 4. return it\"\"\"\n\n cTree = createCliqueTree(F,E)\n prunedCTree=PruneTree( cTree )\n prunedCTree.incorporateEvidence()\n return CliqueTreeInitialPotential( prunedCTree )\n\n \n\ndef ComputeExactMarginalsBP( F, E=[], isMax=False, computeJoint=0):\n \"\"\" We take a list of Factor objects, observed Evidence E\n and returns marignal proabilities for the variables in the\n Bayesian network. If isMax is 1 it runs MAP inference ( *still need to\n do this *) otherwise it runs exact inference using Sum/Product algorithm.\n The ith element of the returned list represents the ith variable in the\n network and its marginal prob of the variable\n\n Note, we implicitly create, prune, initialize, and calibrate a clique tree\n constructed from the factor list F \"\"\"\n\n MARGINALS=[]\n #pdb.set_trace()\n P = CreatePrunedInitCtree(F,E)\n #G=nx.from_numpy_matrix( P.getEdges() )\n #nx.draw_shell(G)\n #plt.show()\n \n #plt.savefig('cliqueTree.png', bbox_inches=0)\n (P,MESSAGES) = CliqueTreeCalibrate(P,isMax)\n #pdb.set_trace()\n if computeJoint==1:\n jointDistribution=ComputeJointDistributionFromCalibratedCliqueTree(P, MESSAGES, isMax)\n else:\n jointDistribution=None\n #pdb.set_trace()\n #P = CliqueTreeCalibrate(P,isMax)\n cliqueList=P.getNodeList()\n \n fh=open('ExactMarginals.CliqueTree.log','a')\n for i in range(len(cliqueList)):\n out = \",\".join( map(str, cliqueList[i].getVar().tolist() )) \n outstring= \"node \" + str(i) + \":\\t\" + out +'\\n'\n fh.write(outstring)\n fh.write(\"\\n\")\n #np.savetxt( 'numpy.cTree.edges.calibrated.txt',P.getEdges(),fmt='%d', delimiter='\\t')\n np.savetxt('ExactMarginals.CliqueTree.log',P.getEdges(),fmt='%d', delimiter='\\t')\n \n \n \n \n \"\"\" get the list of unique variables \"\"\"\n V=getUniqueVar(F)\n \n\n for i in range ( len(V ) ):\n for j in range ( len(cliqueList ) ):\n if V[i] in cliqueList[j].getVar():\n marginalize=np.setdiff1d ( cliqueList[j].getVar(), V[i] ).tolist()\n if not marginalize:\n MARGINALS.append( cliqueList[j] )\n else:\n if isMax == 0:\n #mfactor=FactorMarginalization(P.cliqueList(j), marginalize);\n mfactor=FactorMarginalization( cliqueList[j], marginalize )\n newVal=mfactor.getVal() / np.sum( mfactor.getVal() )\n mfactor.setVal( newVal )\n MARGINALS.append ( mfactor )\n else:\n mfactor=FactorMaxMarginalization( cliqueList[j], marginalize )\n MARGINALS.append( mfactor )\n break\n\n \n return (MARGINALS,jointDistribution)\n\ndef ComputeJointDistributionFromCalibratedCliqueTree( P, MESSAGES, isMax=0):\n \n \"\"\" this is a function to attempt to compute the joint distribution from\n a calibrated clique tree (cTree). The arguments are: \n 1. The calibrated cTree, P, which is a CliqueTree object\n 2. The sepset beliefs are is the matrix MESSAGES\n The MESSAGES matrix is a matrix of Factor objects\n We can get the indices of the sepset messages\n from the edges of the clique tree. \n \n This function attempts to implement equation 10.10 in Koller and Friedman\n in section 10.2.3: A Calibrated Clique Tree as a Distribution\n \n P_\\Phi(X) = \\frac{ \\prod_{i \\in V_T} \\Beta_i(C_i) } { \\prod_{i-j} \\in E_T \\mu_i,j(S_i,j) }\n \n Basically A) multiply the clique beliefs \n B) multiply the sepset beliefs\n C) divide A/B \n \n \n \"\"\"\n cliqueFactors=P.getNodeList()\n \n \"\"\" if this is a max-marginal calibrated clique tree the values are in log space\n Just re-exponentiate them \"\"\"\n if isMax==1:\n cliqueFactors = [ ExpFactorNormalize(c) for c in cliqueFactors ]\n \n \"\"\" this is the numerator \"\"\"\n cliqueBeliefProducts=reduce(lambda x, y: FactorProduct(x,y), cliqueFactors)\n \n \"\"\" get the adjacency matrix of the clique tree \"\"\"\n adj_matrix=P.getEdges()\n \n \"\"\" get the nonzero indices, then compute the product of the sepset beliefs \"\"\"\n nonzero_rows=adj_matrix.nonzero()[0].tolist()\n nonzero_cols=adj_matrix.nonzero()[1].tolist()\n \n \n\n \n \n sepsetBeliefsFactors= [ MESSAGES[x,y] for (x,y) in zip(nonzero_rows, nonzero_cols) ] \n \n \"\"\" if this is a max-marginal calibrated clique tree the values are in log space\n Just re-exponentiate them \"\"\"\n if isMax == 1:\n sepsetBeliefsFactors = [ ExpFactorNormalize(c) for c in sepsetBeliefsFactors ]\n \n \n \n sepsetBeliefProducts= reduce( lambda x,y: FactorProduct(x,y), sepsetBeliefsFactors)\n \n \"\"\" the re-parameterization of the joint (clique tree invariant) \n divide the clique beliefs by the sepset messages \"\"\"\n jointDistrbution=FactorDiv(cliqueBeliefProducts, sepsetBeliefProducts)\n \n val=jointDistrbution.getVal()/np.sum( jointDistrbution.getVal() )\n jointDistrbution.setVal( val )\n \n return jointDistrbution\n \n \n \n \n \n \n \n \n"},{"alpha_fraction":0.6553258895874023,"alphanum_fraction":0.6626390814781189,"avg_line_length":47.35384750366211,"blob_id":"052a0afcbd86e4459fa3a6420618a716e35992f8","content_id":"ed61124800b8bd503bbb5d69a2e2582775581716","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":3145,"license_type":"no_license","max_line_length":194,"num_lines":65,"path":"/GeneticNetworkFactory.py","repo_name":"indapa/pgmPy","src_encoding":"UTF-8","text":"from Factor import *\nfrom FactorOperations import *\nfrom PedigreeFactors import *\nimport itertools\nimport numpy as np\n\"\"\"\" Still not sure how this is going to work\n This class is a factory for generating a genetic network\n If we consider each location in the genome independent\n we generate a new network for each position along an interval.\n A network is a collection of factors, so we return a python\n list of Pedigree factors (either GenotypeAlleleFreqFactor for founders\n or GenotypeGivenParentsFactor for non-founders. Each phenotype is conditionally\n independent given its genotoype, so each member of the pedigree has a\n PhenotypeGivenGenotypeFactor\"\"\"\n\nclass GeneticNetworkFactory(object):\n \n\n def __init__(self, pedfile, alphaList, allelefreq, chrom, position):\n #parse pedfile\n self.alphaList=alphaList\n self.allelefreq=allelefreq\n self.totalAlleles=len(allelefreq)\n self.chrom=chrom\n self.pos=position\n\n self.pedigree=Pedfile(pedfile)\n self.pedigree.parsePedfile()\n self.pedlist=self.pedigree.getPedList()\n self.pedids=self.pedigree.returnIndivids()\n #print self.pedids\n\n #list of factors that will comprise the Genetic network\n self.totalFactors=self.pedigree.getTotalSize() * 2\n self.factorList=self.totalFactors*[None]\n\n \n def constructNetwork(self):\n totalPeople=self.pedigree.getTotalSize()\n for i in range( totalPeople ):\n \n \n if self.pedlist[i].isFounder():\n #print self.pedlist[i].getid()\n self.factorList[i]=GenotypeAlleleFreqFactor(self.allelefreq,i+1,self.pedlist[i].getid() + \" genotype \")\n #self.factorList[i]=GenotypeAlleleFreqFactor(self.allelefreq,self.pedlist[i].getid(),self.pedlist[i].getid())\n #factorList(i)=genotypeGivenAlleleFreqsFactor(alleleFreqs,i);\n else:\n #3print self.pedlist[i].getParents(), self.pedlist[i].getid()\n #GenotypeGivenParentsFactor(2,\"bart\",\"homer\",\"marge\",\"\"\"Bart | Homer, Marge \"\"\")\n #self.factorList[i]=GenotypeGivenParentsFactor(self.totalAlleles, self.pedlist[i].getid(), self.pedlist[i].getParents()[0], self.pedlist[i].getParents()[1], \"child|Father,Child\")\n parent1Index=self.pedids.index( self.pedlist[i].getParents()[0] )\n parent2Index=self.pedids.index( self.pedlist[i].getParents()[1] )\n child=self.pedlist[i].getid()\n parent1name=self.pedlist[parent1Index].getid()\n parent2name=self.pedlist[parent2Index].getid()\n name=child+\" genotype |\"+parent1name+\",\"+parent2name\n self.factorList[i]=GenotypeGivenParentsFactor(self.totalAlleles, i+1, parent1Index+1 , parent2Index+1 , name)\n \n name=self.pedlist[i].getid()+\" phenotype | \" + self.pedlist[i].getid() + \" genotype\"\n\n self.factorList[i+totalPeople]=PhenotypeGivenGenotypeFactor(self.alphaList,i+totalPeople+1,i+1, name )\n\n def getFactorList(self):\n return self.factorList\n\n\n"},{"alpha_fraction":0.69027179479599,"alphanum_fraction":0.6959942579269409,"avg_line_length":26.41176414489746,"blob_id":"9c2992617817dbf6c1fbdb56f4e689d9ea99368e","content_id":"10d1a9842a0bf1c1fdead15c69d0ccf7db82f50d","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1398,"license_type":"no_license","max_line_length":114,"num_lines":51,"path":"/PythonNotebooks/ocr_MAP.py","repo_name":"indapa/pgmPy","src_encoding":"UTF-8","text":"from Factor import *\nfrom PGMcommon import *\nfrom CliqueTree import *\nfrom CliqueTreeOperations import *\nfrom FactorOperations import *\nimport scipy.io as sio\nimport numpy as np\nimport pprint\nimport pdb\nimport matplotlib.pyplot as plt\nimport networkx as nx\nmatfile='/Users/amit/BC_Classes/PGM/Prog4/PA4Sample.mat'\nmat_contents=sio.loadmat(matfile)\nmat_struct=mat_contents['OCRNetworkToRun']\nval=mat_struct\nfactorList=[]\n\nALPHABET=['a','b','c','d','e','f','g','h','i','j','k','l','m','n','o','p','q','r','s','t','u','v','w','x','y','z']\n\nfor data in val:\n \n (var, card, values)=data[0]\n f= Factor( var[0].tolist(), card[0].tolist(), values[0].tolist(), 'factor' )\n factorList.append( f )\n\n#MARGINALS= ComputeExactMarginalsBP( factorList, [], 1 )\n#MAPAssignment=MaxDecoding( MARGINALS )\n#print \"\".join( [ALPHABET[idx] for idx in MAPAssignment] )\n\nMARGINALS= ComputeExactMarginalsBP( factorList, [], 1 )\nfor m in MARGINALS:\n log_val= m.getVal()\n prob_val_normalized=np.log( lognormalize( log_val ) )\n m.setVal(prob_val_normalized)\n\n\nMAPAssignment=MaxDecoding( MARGINALS )\nprint \"\".join( [ALPHABET[idx] for idx in MAPAssignment] )\n\nfor m in MARGINALS:\n print np.sum( lognormalize(m.getVal() ) )\n\n\n#V=getUniqueVar(factorList)\n#print 'unique variables:'\n#print V\n\n#cTree=CreatePrunedInitCtree(factorList)\n#G=nx.from_numpy_matrix( cTree.getEdges() )\n#nx.draw_shell(G)\n#plt.show()\n"},{"alpha_fraction":0.5952702760696411,"alphanum_fraction":0.5993243455886841,"avg_line_length":27.941177368164062,"blob_id":"e6d8e78b6e65a7eea8f3f483a8ce9e82cf7a1392","content_id":"3217b3e442a436bf70fc4fe7ed9919eb6a80733a","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1480,"license_type":"no_license","max_line_length":121,"num_lines":51,"path":"/Factor.py","repo_name":"indapa/pgmPy","src_encoding":"UTF-8","text":"import sys\nimport numpy as np\nclass Factor(object):\n\n \"\"\" Represents a factor in a PGM. A factor has variable scope, cardinality, value, and potentially a name.\n A factor's values (which can potentially be multi-dimensional table, are represented as NumPy 1d-arrays.\n See Chapter10 Friedman pg. 358 and Koller for more info. \"\"\"\n\n\n\n def __init__(self, var=[], card=[], val=[], name= 'None'):\n \"\"\" a factor has list of variables, each with a cardinality, and for each possible assignment to its variable(s),\n a position in the val array.\"\"\"\n self.var= np.array(var)\n self.card=np.array(card)\n self.val=np.array(val)\n self.name=name\n\n def __str__(self):\n varstring= \" \".join ( map(str, self.var) )\n cardstring=\" \".join ( map(str, self.card) )\n valstring= \" \".join( map(str, self.val))\n return \"\\n\".join( [ 'name: ' + self.name,'var: '+ varstring, 'card: '+ cardstring, 'val: ' + valstring])\n\n\n def setVar(self, var):\n self.var=np.array(var)\n\n def getVar(self):\n return self.var\n\n def getVarCount(self):\n return len( self.var.tolist() )\n\n def setVal(self, val):\n self.val=np.array(val)\n\n def getVal(self):\n return self.val\n\n def setCard(self,card):\n self.card=np.array(card)\n\n def getCard(self):\n return self.card\n\n def getName(self):\n return self.name\n\n def setName(self, name):\n self.name=name\n\n\n\n\n"},{"alpha_fraction":0.6409705877304077,"alphanum_fraction":0.6484430432319641,"avg_line_length":39.885555267333984,"blob_id":"80f59e493196baae8ffed0576e2078272e0110c1","content_id":"cdf59801c73aa21c25d1fb91b720b1549a6e36a7","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":36802,"license_type":"no_license","max_line_length":174,"num_lines":900,"path":"/FactorOperations.py","repo_name":"indapa/pgmPy","src_encoding":"UTF-8","text":"#!/usr/bin/env python\nfrom Factor import *\nimport numpy as np\nfrom PGMcommon import *\nimport sys\nimport itertools\nimport common\nimport pdb\n\ndef IndexToAssignment( I, D):\n\n \"\"\" given and index I (a row vector representing the indices of values a factor object's val field\n and D, an array representing the cadinality of variables in a factor object, this function produces\n a matrix of assignments, one assignment per row. See https://github.com/indapa/PGM/blob/master/Prog1/IndexToAssignment.m \"\"\"\n\n a=np.reshape ( np.arange(np.prod(D)).repeat(len(D)), (np.prod(D),len(D)))\n \n\n b=tmp=list( D[:-1] )\n tmp.insert(0,1)\n tmp =np.cumprod ( np.array (tmp) )\n b=np.tile( np.cumprod(b), (len(I), 1))\n #print b\n\n #print np.floor ( a /b )\n c=np.tile ( D, ( len(I), 1) )\n\n assignment = np.mod ( np.floor( a/b), c) +1\n return assignment\n\n\ndef AssignmentToIndex ( A, D):\n \"\"\" I = AssignmentToIndex(A, D) converts an assignment, A, over variables\n with cardinality D to an index into the .val vector for a factor.\n If A is a matrix then the function converts each row of A to an index.\n See https://github.com/indapa/PGM/blob/master/Prog1/AssignmentToIndex.m \"\"\"\n \n D=D.flatten(0) #turn array into vector (note that this forces a copy), see http://www.scipy.org/NumPy_for_Matlab_Users#head-fd74115e6798fbf3a628094a55d1cb2b2b5cdd3c\n I=np.array( [] )\n (nrowA,ncolA)=np.shape(A)\n\n if nrowA== 1 or ncolA ==1: #if assginments are 1 row or 1 col\n #sys.stderr.write(\"if block ...\\n\")\n b=tmp=list( D[:-1] )\n tmp.insert(0,1)\n \n tmp =np.cumprod ( np.array (tmp) )\n tmp=(np.array(np.matrix(tmp)))\n #print \"tmp: \", tmp\n \n a_flat=np.array ( np.matrix( A.flatten(0) ).transpose() )\n #print \"a flat: \", a_flat\n I= ( tmp * (a_flat-1) ) + 1\n return I\n \n\n else:\n #sys.stderr.write(\"else block ...\\n\")\n b=tmp=list( D[:-1] )\n tmp.insert(0,1)\n tmp =np.cumprod ( np.array (tmp) )\n tmp = np.tile( tmp, (nrowA,1) )\n #print tmp\n #print (A-1)\n I= np.sum( np.multiply(tmp, (A-1)), 1) + 1\n\n \n return np.array( np.matrix( I ).transpose() )\n\n\ndef SetValueOfAssignment( F, A, v, Vorder=None):\n \"\"\" % SetValueOfAssignment Sets the value of a variable assignment in a factor.\n%\n% F = SetValueOfAssignment(F, A, v) sets the value of a variable assignment,\n% A, in factor F to v. The order of the variables in A are assumed to be the\n% same as the order in F.var.\n%\n% F = SetValueOfAssignment(F, A, v, VO) sets the value of a variable\n% assignment, A, in factor F to v. The order of the variables in A are given\n% by the vector VO. See https://github.com/indapa/PGM/blob/master/Prog1/SetValueOfAssignment.m \"\"\"\n\n \n\n if Vorder == None:\n indx=AssignmentToIndex( A, F.getCard() )\n else:\n sys.stderr.write(\"assumes the order of variables in A are the sayme as in F.var ...\\n\")\n pass\n\n #http://stackoverflow.com/a/5183720, How to make List from Numpy Matrix in Python\n #http://stackoverflow.com/a/8373103, numpy function to set elements of array to a value given a list of indices\n indices=np.array(indx-1).flatten().tolist()\n zeros=np.zeros(len(A))\n zeros[indices]=v\n F.setVal( zeros.tolist() )\n\ndef GetValueOfAssignment( F, A, Vorder = None ):\n \"\"\" % GetValueOfAssignment Gets the value of a variable assignment in a factor.\n%\n% v = GetValueOfAssignment(F, A) returns the value of a variable assignment,\n% A, in factor F. The order of the variables in A are assumed to be the\n% same as the order in F.var.\n%\n% v = GetValueOfAssignment(F, A, VO) gets the value of a variable assignment,\n% A, in factor F. The order of the variables in A are given by the vector VO. See https://github.com/indapa/PGM/blob/master/Prog1/GetValueOfAssignment.m \"\"\"\n\n if Vorder == None:\n indx= AssignmentToIndex ( A, F.getCard() )\n else:\n sys.stderr.write(\"The order of the variables in A are assumed to be the same as the order in F var\\n\")\n pass\n #pdb.set_trace()\n indices=np.array(indx-1).flatten().tolist()\n return np.array ( np.matrix ( F.getVal()[indices] ))\n\ndef FactorProduct ( A, B):\n \"\"\" FactorProduct Computes the product of two factors.\n% C = FactorProduct(A,B) computes the product between two factors, A and B,\n% where each factor is defined over a set of variables with given dimension.\n% The factor data structure has the following fields:\n% .var Vector of variables in the factor, e.g. [1 2 3]\n% .card Vector of cardinalities corresponding to .var, e.g. [2 2 2]\n% .val Value table of size prod(.card)\n%\n% See also FactorMarginalization IndexToAssignment,\n% AssignmentToIndex, and https://github.com/indapa/PGM/blob/master/Prog1/FactorProduct.m \"\"\"\n\n #print \"A: \", A\n #print \"====\"\n #print \"B: \", B\n C=Factor()\n\n #check for empty factors\n if len( A.getVar() ) == 0 :\n sys.stderr.write(\"A factor is empty!\\n\")\n return B\n if len( B.getVar() ) == 0:\n sys.stderr.write(\"B factor is empty!\\n\")\n return A\n\n\n #check of variables that in both A and B have the same cardinality\n #print 'A.getVar(): ', A.getVar()\n #print 'B.getVar(): ',B.getVar()\n #setA= set( A.getVar() )\n #setB= set( B.getVar() )\n #intersect=np.array( list( setA.intersection(setB)))\n intersect=np.intersect1d( A.getVar(), B.getVar() ).tolist()\n #print \"Intersection of variables in FactorProduct \", intersect\n #print \"A var: \", A.getVar()\n #print \"B var: \", B.getVar()\n\n #if the intersection of variables in the two factors\n #is non-zero, then make sure they have the same cardinality\n if len(intersect) > 0:\n #iA=np.nonzero(intersect - A.getVar()==0)[0].tolist() # see this http://stackoverflow.com/a/432146, return the index of something in an array?\n iA=getIndex( A.getVar(), intersect )\n #print \"iA: \", iA\n #iB=np.nonzero(intersect - B.getVar()==0)[0].tolist()\n iB = getIndex ( B.getVar(), intersect )\n #print \"iB: \", iB\n\n # check to see if any of the comparisons in the array resulting from of a.getCard()[iA] == b.getCard()[iB] \n # are all False. If so print an error and exit\n if len( np.where( A.getCard()[iA].all() == B.getCard()[iB].all() ==False)[0].tolist() ) > 0:\n sys.stderr.write(\"dimensionality mismatch in factors!\\n\")\n sys.exit(1)\n\n #now set the variables of C to the union of variables in factors A and B\n #print 'setA ' ,setA\n #print 'setB ', setB\n #print list( setA.union(setB) )\n C.setVar( np.union1d ( A.getVar(), B.getVar() ).tolist() )\n #C.setVar ( list( setA.union(setB) ) )\n mapA=isMember(A.getVar(), C.getVar() )\n mapB=isMember(B.getVar(), C.getVar() )\n\n \n\n #Set the cardinality of variables in C\n C.setCard( np.zeros( len(C.getVar())).tolist() )\n C.getCard()[mapA]=A.getCard()\n C.getCard()[mapB]=B.getCard()\n\n #intitialize the values of the factor C to be zero\n C.setVal( np.zeros(np.prod(C.getCard())).tolist() )\n\n #some helper indices to tell what indices of A and B values to multiply\n assignments=IndexToAssignment( np.arange(np.prod(C.getCard())), C.getCard() ) #get the assignment of values of C\n indxA=AssignmentToIndex( assignments[:,mapA], A.getCard())-1 # re-arrange the assignment of C, to what it would be in factor A\n indxB=AssignmentToIndex( assignments[:,mapB], B.getCard())-1 # re-arange the assignment of C to what it would be in factorB\n\n \n\n c_val=A.getVal()[indxA.flatten().tolist()] * B.getVal()[indxB.flatten().tolist()] #now that we have the index into A.val and B.val vector, multiply them to factor product\n C.setVal ( c_val.tolist() )\n\n return C\n\ndef FactorMarginalization(A,V):\n \"\"\" FactorMarginalization Sums given variables out of a factor.\n B = FactorMarginalization(A,V) computes the factor with the variables\n in V summed out. The factor data structure has the following fields:\n .var Vector of variables in the factor, e.g. [1 2 3]\n .card Vector of cardinalities corresponding to .var, e.g. [2 2 2]\n .val Value table of size prod(.card)\n\n The resultant factor should have at least one variable remaining or this\n function will throw an error. See also FactorProduct, IndexToAssignment , and AssignmentToIndex\n Based on matlab code found here: https://github.com/indapa/PGM/blob/master/Prog1/FactorMarginalization.m \"\"\"\n\n #the resulting factor after marginalizing out variables in python list V that are in \n #the factor A\n B=Factor()\n\n #check for empy factor or variable list\n if len( A.getVar() ) == 0 or len(V) == 0:\n return A\n\n #construct the variables of the marginalized factor by \n #computing the set difference between A.var and V\n #These variables in the difference set will be the scope of the new factor\n setA=set( A.getVar() )\n setV=set(V)\n Bvar=np.array( list( setA.difference(setV)))\n mapB=isMember(Bvar, A.getVar()) #indices of the variables of the new factor in the original factor A\n #print mapB, Bvar\n\n #check to see if the new factor has empty scope\n if len(Bvar) == 0:\n sys.stderr.write(\"FactorMarginalization:Error, resultant factor has empty scope...\\n\")\n return None\n #set the marginalized factor's variable scope and cardinality\n B.setVar( Bvar.tolist() )\n B.setCard( A.getCard()[mapB] )\n B.setVal( np.zeros(np.prod(B.getCard())).tolist() )\n\n #compute some helper indices\n assignments=IndexToAssignment ( np.arange(np.prod(A.getCard()) ), A.getCard() )\n #indxB tells which values in A to sum together when marginalizing out the variable(s) in B\n indxB=AssignmentToIndex( assignments[:,mapB], B.getCard())-1\n\n #accum is a numpy implementation of matlab accumarray\n #accumarray sums data in each group\n #here the group(s) are defined in indxB\n #indxB is a map to tell which value in A.val to map the sum to\n #see http://blogs.mathworks.com/loren/2008/02/20/under-appreciated-accumarray/\n marginal_vals=accum(indxB, A.getVal() )\n \n #set the marginal values to the new factor with teh variable(s) in V summed(marginalized) out\n B.setVal( marginal_vals.tolist() )\n return B\n\n\n\ndef ObserveEvidence (INPUTS, EVIDENCE):\n\n \"\"\" ObserveEvidence Modify a vector of factors given some evidence.\n F = ObserveEvidence(INPUTS, EVIDENCE) sets all entries in the vector of factors,INPUTS,\n that are not consistent with the evidence, E, to zero. F is a vector of\n factors, each a data structure with the following fields:\n .var Vector of variables in the factor, e.g. [1 2 3]\n .card Vector of cardinalities corresponding to .var, e.g. [2 2 2]\n .val Value table of size prod(.card)\n EVIDENCE is an N-by-2 matrix, where each row consists of a variable/value pair.\n Variables are in the first column and values are in the second column. \"\"\"\n (nrows, ncols)=np.shape(EVIDENCE)\n #total_factors=len(INPUTS)\n #iterate through evidence\n for i in range(nrows):\n variable=EVIDENCE[i,0]\n value=EVIDENCE[i,1]\n #print 'var: ', variable, 'value: ', value\n if int(value) == 0:\n print \"Evidence is not set for variable: ', variable, ' in evidence matrix.\\n\"\n continue\n\n for factor in INPUTS:\n #the following returns a list\n indx=np.where( factor.getVar() == variable )[0].tolist()\n if indx: #if the indx is not empty, it contains the index value of the evidence variable in factor.val array\n indx=indx[0]\n \n if value > factor.getCard()[indx] or value < 0:\n sys.stderr.write(\"invalid evidene for variable X_'\" + str(variable) + \" = \" + str(value) + \"\\n\")\n sys.exit(1)\n\n #get the assignments of variables for the factor\n assignments=IndexToAssignment( np.arange(np.prod( factor.getCard() )), factor.getCard() )\n # now get the indices in the assignments that don't agree with the observed value (evidence)\n mask=np.where( assignments[:,indx] != value )[0].tolist()\n #we are going to update the val array for the current factor\n newvals=factor.getVal()\n #set the mask indices to zero and reset the val array of the factor\n newvals[mask]=0\n factor.setVal( newvals.tolist() )\n\n #now check to see the validity of the updated values of the factor\n #given the observed evidence. We cannot have all zero values for the factor!\n zeroIndices=np.where ( factor.getVal() == 0)[0].tolist()\n if len(zeroIndices) == len (factor.getVal() ):\n sys.stderr.write(\"All variable values are zero, which is not possible.\\n\")\n return INPUTS\n\ndef ComputeJointDistribution(INPUTS):\n \"\"\" ComputeJointDistribution Computes the joint distribution defined by a set of given factors\n\n Joint = ComputeJointDistribution(INPUTS) computes the joint distribution\n defined by a set of given factors\n\n Joint is a factor that encapsulates the joint distribution given by INPUTS\n INPUTS is a vector of Factor objects containing the factors defining the distribution\n\n \"\"\"\n\n totalFactors = len(INPUTS)\n #check for empty list of INPUTS\n\n if totalFactors== 0:\n sys.stderr.write(\"Empty factor list given as input\\n\")\n return Factor( [], [], [] )\n \n else:\n # see http://docs.python.org/library/functions.html#reduce for description of Python reduce function\n return reduce(lambda x, y: FactorProduct(x,y), INPUTS)\n\n\ndef ComputeMarginal(V, F, E):\n \"\"\"\n ComputeMarginal Computes the marginal over a set of given variables\n M = ComputeMarginal(V, F, E) computes the marginal over variables V\n in the distribution induced by the set of factors F, given evidence E\n\n M is a factor containing the marginal over variables V\n\n V is a vector containing the variables in the marginal e.g. [1 2 3] for X_1, X_2 and X_3.\n i.e. a result of FactorMarginalization\n\n F is a vector of factors (struct array) containing the factors\n defining the distribution\n\n E is an N-by-2 matrix, each row being a variable/value pair.\n Variables are in the first column and values are in the second column.\n If there is no evidence, pass in the empty matrix [] for E.\n\n \"\"\"\n totalFactors=len(F)\n #reshape a 1d array to 1 x ncol array\n #since ObserveEvidence requires Nx2 array, we reshape to a 2 column array\n #see http://stackoverflow.com/a/12576163 for reshaping 1d array to 2d array\n EVIDENCE= np.reshape( np.array ( E ), (-1,2) )\n #print np.shape(EVIDENCE)\n \n if totalFactors == 0:\n sys.stderr.write(\"empty factor list given as input.\\n\")\n return Factor( [], [], [])\n # union of all variables in list of factors F\n variableList=[] # a list of of lists, where each element is a list containing the variables of the factor in F\n for factor in F:\n var=factor.getVar().tolist()\n variableList.append( var )\n\n #get the union of variables across all the factor in F\n #see this http://stackoverflow.com/a/2151553, Pythonic Way to Create Union of All Values Contained in Multiple Lists\n union_variables = set().union(*variableList)\n #print union_variables\n #v contains the variables not in the list of variables in the marginal\n v=list( union_variables.difference(V) )\n \n # compute the joint distribution, but then reduce it, given the evidence\n # ComputeJointDistribution returns a factor, but ObserveEvidence expects a list\n # of factors as the first argument, so hence the need for brackets [ ]\n # ObserveEvidence returns a list, but we want the first element so thats why the [0]\n jointE= ObserveEvidence ( [ComputeJointDistribution ( F )], EVIDENCE )[0]\n\n #now we need to re-normaize the joint, since observe evidence doesn't do it for us\n jointE_normalizedVal = jointE.getVal()/np.sum( jointE.getVal() )\n jointE.setVal( jointE_normalizedVal.tolist() )\n\n return FactorMarginalization ( jointE, v)\n \n\ndef IdentityFactor( F ):\n return Factor ( F.getVar().tolist(), F.getCard().tolist(), np.ones( np.prod( F.getCard() ) ), F.getName()+ '_identity' )\n\n\n\ndef SumProductEliminateVar(z, factorList):\n\n \"\"\" this is a non-graph based sum-product variable elimination function\n z is a variable to eliminate\n pass in a list of factors\n\n 1. figure out which factor contain z in their variable scope\n 2. figure out which factors don't contain z in their scope\n 3. mulitply in all factors that have z\n 4. sum out z (marginalize) and return new factor with variable z eliminated\"\"\"\n\n useFactors = []# list of factors that contains the variable Z\n unusedFactors=[] #list of factors that don't contain variable Z\n scope = []\n\n \"\"\"get a list containining the index in self.factorLlist of factors\n that contain the variable Z to be eliminated\n get the scope of variables from the factors that contain variable Z \"\"\"\n for fi in factorList:\n if z in fi.getVar().tolist():\n useFactors.append(fi)#the ith factor is being currently involved in elimination\n scope=list(set.union(set(scope), fi.getVar().tolist() ))\n else:\n unusedFactors.append( fi )\n\n #for f in useFactors:\n # print 'useFactor: ', f\n #print '==='\n #for f in unusedFactors:\n # print 'unusedFactor: ', f\n\n psiFactor= ComputeJointDistribution ( useFactors )\n tauFactor=FactorMarginalization( psiFactor,[z] )\n\n #print 'psiFactor: ', psiFactor\n #print 'tauFactor: ', tauFactor\n return unusedFactors + [ tauFactor ]\n\ndef SumProductVE ( Z, F ):\n\n \"\"\" A wrapper function for SumProductEliminateVar\n sum-product variable elimination based on pseudocode algorithm 9.1 in Koller and Friedman\n We are giving a list of variables to eliminate in Z (in the order we want to\n elimiinate them) and a list of factors F\n eliminate each one getting getting the marginal distribution of the last variable in the list\n Z. \"\"\"\n\n for z in Z:\n F=SumProductEliminateVar(z, F)\n return reduce(lambda x, y: FactorProduct(x,y), F)\n\n\ndef FactorMaxMarginalization( A, V ):\n \"\"\" computes the factor with the variables in V *maxed* out.\n The resulting factor will have all the variables in A minus\n those variables in V. This is quite similiar to FactorMarginalization, but rather then summing out variables in V\n we take the max. In the code, this translates passing np.max as the function to accum\n See section 13.2 in Koller and Friedman for more information\"\"\"\n\n B=Factor()\n #check for empy factor or variable list\n if len( A.getVar() ) == 0 or len(V) == 0:\n return A\n Bvar=np.setdiff1d( A.getVar(), V)\n mapB=isMember(Bvar, A.getVar())\n\n if len(Bvar) == 0:\n sys.stderr.write(\"FactorMaxMarginalization: Error, resultant factor has empty scope...\\n\")\n return np.max (A.getVal() )\n #set the marginalized factor's variable scope and cardinality\n B.setVar( Bvar.tolist() )\n B.setCard( A.getCard()[mapB] )\n B.setVal( np.zeros(np.prod(B.getCard())).tolist() )\n\n #compute some helper indices\n assignments=IndexToAssignment ( np.arange(np.prod(A.getCard()) ), A.getCard() )\n #indxB tells which values in A to sum together when marginalizing out the variable(s) in B\n indxB=AssignmentToIndex( assignments[:,mapB], B.getCard())-1\n\n #here we pass in the function np.max\n #NumPy and Python are awesome\n max_vals=accum(indxB, A.getVal(), np.max )\n B.setVal( max_vals.tolist() )\n\n return B\n\n\ndef MaxProductEliminateVar(z, factorList):\n\n \"\"\" this is a non-graph based MAX-product variable elimination function\n z is a variable to eliminate\n pass in a list of factors\n\n 1. figure out which factor contain z in their variable scope\n 2. figure out which factors don't contain z in their scope\n 3. mulitply in all factors that have z\n 4. max marginalize out z and return new factor with variable z eliminated\"\"\"\n\n useFactors = []# list of factors that contains the variable Z\n unusedFactors=[] #list of factors that don't contain variable Z\n scope = []\n\n \"\"\"get a list containining the index in self.factorLlist of factors\n that contain the variable Z to be eliminated\n get the scope of variables from the factors that contain variable Z \"\"\"\n for fi in factorList:\n if z in fi.getVar().tolist():\n useFactors.append(fi)#the ith factor is being currently involved in elimination\n scope=list(set.union(set(scope), fi.getVar().tolist() ))\n else:\n unusedFactors.append( fi )\n\n \n \"\"\" psiFactor is an intermediate factor, prior to max-marginalization \"\"\"\n psiFactor= ComputeJointDistribution ( useFactors )\n tauFactor=FactorMaxMarginalization( psiFactor,[z] )\n\n \n \"\"\" we return tuple consisting of\n 1. a list factors that are unused, plus the result of max-marginal\n such that the variable z is not eliminated from the list of factors remaining.\n 2. For traceback, we return the intermediate factor generated in the process of eliminating\n variable z. \"\"\"\n return unusedFactors + [ tauFactor ], psiFactor\n\ndef TracebackMAP(FI, Z):\n \"\"\"We are back-tracing to the most probable assingments here ...\n See psuedo-code in Koller and Friedman page 557\n\n In order to return the most probable assignment from MaxProductVE\n we take in a list of intermediate factors, FI, that were generated in the process\n of MaxProductVE. Z is the same elimination ordering used as MaxProductVE.\n We traceback our steps by iterating in reverse order the elimination ordering Z.\n\n Following arguments section 13.2.2 page 558 in Koller and Friedman, as one eliminates\n variables you cannot determine their maximizing value. But you can compute their 'conditional'\n maximizing value - their max value given the other variables not eliminate yet. Once\n the last variable is eliminated, we can traceback to get the maximzing value of the remaining\n variables. Hence the reason for iterating thru the elimination ordering Z in reverse order\n \n Returns a python dictionary with key: variable value: variable assignment in the MAP\"\"\"\n\n z_i=Z[-1]\n f_i=FI[-1]\n Z=Z[:-1]\n FI=FI[:-1]\n\n #print 'z_i:', z_i\n #print 'f_i:', f_i\n\n values=f_i.getVal().tolist()\n fidx= IndexToAssignment( np.arange( np.prod( f_i.getCard() ) ), f_i.getCard() )\n maxidx=values.index(max(values))\n \n\n maxed_vars={} #key variable, value: max assignment value\n\n #print 'variable: ', z_i\n #print 'max value: ', fidx.flatten()[maxidx]\n maxed_vars[z_i]=int(fidx.flatten()[maxidx])\n #print maxed_vars\n #print\n for (z, f) in itertools.izip( reversed(Z), reversed(FI) ):\n #print z\n #print f\n #print 'setdiff: ', np.setdiff1d( f_i.getVar(), [z]).tolist()\n \n variables=np.setdiff1d( f_i.getVar(), [z]).tolist()\n evidence=[ [v, maxed_vars[v] ] for v in variables]\n #print 'Evidence: ',evidence\n f=ObserveEvidence( [f], np.matrix(evidence) )[0]\n #print f\n values=f.getVal().tolist()\n fidx= IndexToAssignment( np.arange( np.prod( f.getCard() ) ), f.getCard() )\n #print fidx\n #print max(values)\n maxidx=values.index(max(values))\n\n maxed_vars[z]=int(fidx.flatten()[maxidx])\n #print 'variable: ', z\n #print 'max value: ', fidx.flatten()[maxidx]\n \n #print\n #print maxed_vars\n return maxed_vars\n\n\n\ndef MaxDecoding ( F ):\n \"\"\" F is a list of max marginal factors passed in. The factors have a variable scope over a single variable only\n So no backtracing is inovlved, we just get the index of the highest number in the value array.\n The code here is based on https://github.com/indapa/PGM/blob/master/Prog4/MaxDecoding.m \"\"\"\n ASSIGNMENTS=[]\n for f in F:\n values=f.getVal().tolist()\n ASSIGNMENTS.append ( values.index( max(values) ) )\n return ASSIGNMENTS\n \ndef MaxDecodingNonUniq ( F ):\n \"\"\" F is a list of max marginal factors passed in. We don't assume that there is a unique\n max value. So we get the indices of the non-uniq max value as a tuple and add it to \"\"\"\n ASSIGNMENTS=[]\n for f in F:\n values=f.getVal().tolist()\n maxvalue=max(values)\n \"\"\" if the maxvalue is duplicated, we get the indices of where it resides in the value array \"\"\"\n if common.isMaxDuplicated(values):\n dup_indices_list=[dup for dup in sorted(common.list_duplicates(values)) ]\n dup_values= [ x for (x, y) in dup_indices_list ]\n dup_indices= [ y for (x, y) in dup_indices_list ]\n non_uniq_max_indices=tuple(dup_indices [ dup_values.index(maxvalue) ])\n ASSIGNMENTS.append ( non_uniq_max_indices )\n else:\n ASSIGNMENTS.append( values.index(maxvalue))\n return ASSIGNMENTS\n\n\ndef posterior_genotypes_values(factorList, ALPHABET,samplenames,bedstring,fh):\n \"\"\" given the factorlist of posterior marginals, the genotype alphabet, samplenames,bedstring position,\n and prettybase file handle, print to file the posterior marginals for all 10 possibel genotypes\n for each sample. \"\"\"\n genotype_factors=factorList[0:len(samplenames)]\n sample_factorObj_zip=zip(samplenames, genotype_factors)\n #print bedstring\n for sample, f in sample_factorObj_zip:\n #print sample, \": \"\n #values=f.getVal().tolist()\n \n #prob_val_normalized=( lognormalize( f.getVal() ) )\n prob_val_normalized=f.getVal()/np.sum(f.getVal())\n #print sample\n #val=f.getVal()\n #print np.sum(val)\n #print val/np.sum(val)\n #pdb.set_trace()\n #print prob_val_normalized.tolist()\n #genotype_probZip=zip(ALPHABET,values)\n posteriors=[]\n #print prob_val_normalized.tolist()\n for posterior_val in prob_val_normalized.tolist():\n #for posterior_val in values:\n posteriors.append(str(posterior_val))\n #posteriors.append(str(round(posterior_val,5) ))\n #print posteriors\n gstring=\"\\t\".join(posteriors)\n #print gstring\n outstring=\"\\t\".join([bedstring, sample,gstring])\n \n fh.write(outstring + \"\\n\")\n \n\n \ndef MaxProductVE ( Z, F ):\n\n \"\"\" A wrapper function for MaxProductEliminateVar\n sum-product variable elimination based on pseudocode algorithm 9.1 in Koller and Friedman\n We are giving a list of variables to eliminate in Z (in the order we want to\n elimiinate them) and a list of factors F\n eliminate each one getting getting the marginal distribution of the last variable in the list\n Z.\n\n Returns the probabliity of the MAP configuration as well as the variable assignments of the MAP configuration\"\"\"\n intermediateMaxFactors=[]\n for z in Z:\n (F, intermediateFactor)=MaxProductEliminateVar(z, F)\n intermediateMaxFactors.append ( intermediateFactor )\n \n #intermediateMaxFactors.append ( intermediateFactor )\n \n #MaxDecodingBT( intermediateMaxFactors, Z )\n bt_results=TracebackMAP( intermediateMaxFactors, Z )\n return (reduce(lambda x, y: FactorProduct(x,y), F), bt_results)\n\n\ndef FactorSum ( A, B):\n \"\"\" FactorSum Computes the sum of two factors.\n% Similiar to FactorProduct\n We would use this in log space where multiplication becomes addition\n% Based on the code here https://github.com/indapa/PGM/blob/master/Prog4/FactorSum.m \"\"\"\n\n\n C=Factor()\n\n #check for empty factors\n if len( A.getVar() ) == 0 :\n sys.stderr.write(\"A factor is empty!\\n\")\n return B\n if len( B.getVar() ) == 0:\n sys.stderr.write(\"B factor is empty!\\n\")\n return A\n\n\n #check of variables that in both A and B have the same cardinality\n #print 'A.getVar(): ', A.getVar()\n #print 'B.getVar(): ',B.getVar()\n #setA= set( A.getVar() )\n #setB= set( B.getVar() )\n #intersect=np.array( list( setA.intersection(setB)))\n intersect=np.intersect1d( A.getVar(), B.getVar() ).tolist()\n #print \"Intersection of variables in FactorProduct \", intersect\n #print \"A var: \", A.getVar()\n #print \"B var: \", B.getVar()\n\n #if the intersection of variables in the two factors\n #is non-zero, then make sure they have the same cardinality\n if len(intersect) > 0:\n #iA=np.nonzero(intersect - A.getVar()==0)[0].tolist() # see this http://stackoverflow.com/a/432146, return the index of something in an array?\n iA=getIndex( A.getVar(), intersect )\n #print \"iA: \", iA\n #iB=np.nonzero(intersect - B.getVar()==0)[0].tolist()\n iB = getIndex ( B.getVar(), intersect )\n #print \"iB: \", iB\n\n # check to see if any of the comparisons in the array resulting from of a.getCard()[iA] == b.getCard()[iB]\n # are all False. If so print an error and exit\n if len( np.where( A.getCard()[iA].all() == B.getCard()[iB].all() ==False)[0].tolist() ) > 0:\n sys.stderr.write(\"dimensionality mismatch in factors!\\n\")\n sys.exit(1)\n\n #now set the variables of C to the union of variables in factors A and B\n #print 'setA ' ,setA\n #print 'setB ', setB\n #print list( setA.union(setB) )\n C.setVar( np.union1d ( A.getVar(), B.getVar() ).tolist() )\n #C.setVar ( list( setA.union(setB) ) )\n mapA=isMember(A.getVar(), C.getVar() )\n mapB=isMember(B.getVar(), C.getVar() )\n\n\n\n #Set the cardinality of variables in C\n C.setCard( np.zeros( len(C.getVar())).tolist() )\n C.getCard()[mapA]=A.getCard()\n C.getCard()[mapB]=B.getCard()\n\n #intitialize the values of the factor C to be zero\n C.setVal( np.zeros(np.prod(C.getCard())).tolist() )\n\n #some helper indices to tell what indices of A and B values to multiply\n assignments=IndexToAssignment( np.arange(np.prod(C.getCard())), C.getCard() ) #get the assignment of values of C\n indxA=AssignmentToIndex( assignments[:,mapA], A.getCard())-1 # re-arrange the assignment of C, to what it would be in factor A\n indxB=AssignmentToIndex( assignments[:,mapB], B.getCard())-1 # re-arange the assignment of C to what it would be in factorB\n #print 'indxA ', indxA\n #print 'indxB ', indxB\n\n\n c_val=A.getVal()[indxA.flatten().tolist()] + B.getVal()[indxB.flatten().tolist()] #now that we have the index into A.val and B.val vector, multiply them to factor product\n C.setVal ( c_val.tolist() )\n\n return C\n\n\ndef LogFactor( F ):\n \"\"\" return a factor whose values are the natural log of the orginal factor F \"\"\"\n \n return Factor ( F.getVar().tolist(), F.getCard().tolist(), np.log ( F.getVal() ).tolist(), F.getName() )\n\n\ndef ExpFactorNormalize ( logF ):\n \"\"\" exponentiate a factor to probablity space from log space\n Since moving from log space to probablity space incures a decrease in dynamic range,\n factors should be normalized before applying the transform. One trick we use here is\n to shift every entry by the maximum entry. For example: phi[i] = exp{logPhi[i] -c}\n The value of c is max(logPhi). This type of transformation ensures the resulting factor\n has a maximum entry of 1 and prevents overflow. See page 360 of Koller and Friedman text\"\"\"\n logPhi=logF.getVal()\n #phi=lognormalize( logPhi )\n phi=np.exp(logPhi-np.max(logPhi) )\n logF.setVal( phi )\n return logF\n\ndef ExpFactor( logF ):\n \"\"\" similiar to above, but don't normalize \"\"\"\n logPhi=logF.getVal()\n phi=np.exp( logPhi )\n logF.setVal( phi )\n return logF\n\n\n\n\n\n\ndef FactorDiv ( A, B):\n \"\"\" FactorProduct Computes the dividend of two factors.\n% Similiar to Factor Product, but if we divide 0/0, return 0\n see page 365 in Koller and Friedman for definition of FactorDivision \"\"\"\n\n #print \"A: \", A\n #print \"====\"\n #print \"B: \", B\n C=Factor()\n\n #check for empty factors\n if len( A.getVar() ) == 0 :\n sys.stderr.write(\"A factor is empty!\\n\")\n return B\n if len( B.getVar() ) == 0:\n sys.stderr.write(\"B factor is empty!\\n\")\n return A\n\n\n #check of variables that in both A and B have the same cardinality\n #print 'A.getVar(): ', A.getVar()\n #print 'B.getVar(): ',B.getVar()\n #setA= set( A.getVar() )\n #setB= set( B.getVar() )\n #intersect=np.array( list( setA.intersection(setB)))\n intersect=np.intersect1d( A.getVar(), B.getVar() ).tolist()\n #print \"Intersection of variables in FactorProduct \", intersect\n #print \"A var: \", A.getVar()\n #print \"B var: \", B.getVar()\n\n #if the intersection of variables in the two factors\n #is non-zero, then make sure they have the same cardinality\n if len(intersect) > 0:\n #iA=np.nonzero(intersect - A.getVar()==0)[0].tolist() # see this http://stackoverflow.com/a/432146, return the index of something in an array?\n iA=getIndex( A.getVar(), intersect )\n #print \"iA: \", iA\n #iB=np.nonzero(intersect - B.getVar()==0)[0].tolist()\n iB = getIndex ( B.getVar(), intersect )\n #print \"iB: \", iB\n\n # check to see if any of the comparisons in the array resulting from of a.getCard()[iA] == b.getCard()[iB] \n # are all False. If so print an error and exit\n if len( np.where( A.getCard()[iA].all() == B.getCard()[iB].all() ==False)[0].tolist() ) > 0:\n sys.stderr.write(\"dimensionality mismatch in factors!\\n\")\n sys.exit(1)\n\n #now set the variables of C to the union of variables in factors A and B\n #print 'setA ' ,setA\n #print 'setB ', setB\n #print list( setA.union(setB) )\n C.setVar( np.union1d ( A.getVar(), B.getVar() ).tolist() )\n #C.setVar ( list( setA.union(setB) ) )\n mapA=isMember(A.getVar(), C.getVar() )\n mapB=isMember(B.getVar(), C.getVar() )\n\n \n\n #Set the cardinality of variables in C\n C.setCard( np.zeros( len(C.getVar())).tolist() )\n C.getCard()[mapA]=A.getCard()\n C.getCard()[mapB]=B.getCard()\n\n #intitialize the values of the factor C to be zero\n C.setVal( np.zeros(np.prod(C.getCard())).tolist() )\n\n #some helper indices to tell what indices of A and B values to multiply\n assignments=IndexToAssignment( np.arange(np.prod(C.getCard())), C.getCard() ) #get the assignment of values of C\n indxA=AssignmentToIndex( assignments[:,mapA], A.getCard())-1 # re-arrange the assignment of C, to what it would be in factor A\n indxB=AssignmentToIndex( assignments[:,mapB], B.getCard())-1 # re-arange the assignment of C to what it would be in factorB\n \n numerator=A.getVal()[indxA.flatten().tolist()]\n denominator=B.getVal()[indxB.flatten().tolist()]\n \n #print numerator\n #print denominator\n #print zip(numerator, denominator)\n val= map( lambda x: common.zerodiv_tuple(x), zip(numerator,denominator) )\n #print val\n C.setVal ( val )\n \n return C\n\n\n\n\n\n\ndef variableStride( f ):\n \"\"\" given a Factor object f, calculate its variable stride in value array of the factor \"\"\"\n strides=[]\n iF=IndexToAssignment ( np.arange(np.prod(f.getCard()) ), f.getCard() )\n variables=f.getVar()\n cardinalties=f.getCard()\n \n \n for i in range(0, len(variables) ):\n #assignment_slice=iF[:,i]\n #var_card=cardinalties[i]\n #print variables[i], cardinalties[i]\n curr_stride=iF[:,i]\n if cardinalties[i] > 1:\n stride=np.where(curr_stride==2)\n else:\n stride=0\n strides.append(stride)\n continue\n #print variables[i], cardinalties[i], stride[0][0]\n strides.append( stride[0][0] )\n #print \n \n return strides\n\n\n\n\ndef IndexOfAssignment( f, strides, assignment):\n \"\"\" given a Factor object f and the strides of each of the variables of f and \n a list of assignments of those variables, return the position in the value array of that assignment\n see page 358 box 10.a in Friedman and Koller text on how efficiently map a particular variable\n assignment to the and index in the value array of a factor\n \"\"\"\n \n idx=0\n \n #cardinalities=f.getCard()\n for (ass, stride) in zip( assignment, strides):\n #print ass, stride\n idx +=(ass *stride)\n\n return idx\n\n\n\n\n\n"}],"string":"[\n {\n \"alpha_fraction\": 0.7966291904449463,\n \"alphanum_fraction\": 0.7988764047622681,\n \"avg_line_length\": 41.380950927734375,\n \"blob_id\": \"2f2cb0f9cbc7ca9c6e341920e6f3837f8eff677a\",\n \"content_id\": \"b8e2946911b5163d8d9e528d6c28cb5557092251\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 890,\n \"license_type\": \"no_license\",\n \"max_line_length\": 152,\n \"num_lines\": 21,\n \"path\": \"/README.md\",\n \"repo_name\": \"indapa/pgmPy\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"pgmPy\\n=====\\n\\nBackground:\\n\\nProbablistic Graphical Models representation in Python\\n\\nProbablistic Graphical Models (PGMs) use a graph-based representation\\nto compactly encode the joint distribution. PGMs use elements of \\ngraph theory and probability theory. There are two classes of PGMs. \\ndirected acyclic graphical models are called Bayesian Networks (BNs)\\nand undirected graphical models are Markov networks.\\n\\nThe code in this repository is based off the Matlab code\\nfrom Daphne Koller's Coursera class on PGMs <https://www.coursera.org/course/pgm> For the assignments in the class students were given starter Matlab code\\nand had to implement various algorithms, etc.\\n\\nWhile I grew to like Matlab, I needed to implement the inference and represenation of PGMs in Python for a personal project of mine. So I went down the \\nrabbit hole. The code here depends on NumPy and uses Python v2.7.\\n\\nAmit Indap\\n\"\n },\n {\n \"alpha_fraction\": 0.7048406004905701,\n \"alphanum_fraction\": 0.7201889157295227,\n \"avg_line_length\": 27.233333587646484,\n \"blob_id\": \"06fcb001f011f9b775eaa3dce60cef2e4e27bf09\",\n \"content_id\": \"0e3a67446e7f339e59d777938ea0a92eb39acf0d\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 847,\n \"license_type\": \"no_license\",\n \"max_line_length\": 80,\n \"num_lines\": 30,\n \"path\": \"/PythonNotebooks/testCliqueTreeMaxSumCalibrate.py\",\n \"repo_name\": \"indapa/pgmPy\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from Factor import *\\nfrom PGMcommon import *\\nfrom CliqueTree import *\\nfrom CliqueTreeOperations import *\\nfrom FactorOperations import *\\nimport scipy.io as sio\\nimport numpy as np\\nimport pprint\\nimport pdb\\nmatfile='/Users/amit/BC_Classes/PGM/Prog4/PA4Sample.mat'\\nmat_contents=sio.loadmat(matfile)\\nmat_struct=mat_contents['MaxSumCalibrate']\\nval=mat_struct[0,0]\\ninput_edges = val['INPUT']['edges'][0][0]\\n#print input_edges\\ninput_cliqueList= val['INPUT']['cliqueList'][0][0][0]\\nclique_list_factorObj=[]\\nfor tpl in input_cliqueList:\\n (var, card, values)=tpl\\n f= Factor( var[0].tolist(), card[0].tolist(), values[0].tolist(), 'factor' )\\n #print f \\n clique_list_factorObj.append(f)\\n\\nP=CliqueTree( clique_list_factorObj , input_edges, clique_list_factorObj, [])\\n\\nP=CliqueTreeCalibrate(P,1)\\n\\nfor f in P.getNodeList():\\n print f\\n print \\\"==\\\"\\n\"\n },\n {\n \"alpha_fraction\": 0.6499402523040771,\n \"alphanum_fraction\": 0.6606929302215576,\n \"avg_line_length\": 25.15625,\n \"blob_id\": \"8c6f9a8ec28ce746f319beaed03ca361e895f07e\",\n \"content_id\": \"a5d7adfd01c27cd7128f476c30ee4a018c5346d1\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 837,\n \"license_type\": \"no_license\",\n \"max_line_length\": 114,\n \"num_lines\": 32,\n \"path\": \"/PythonNotebooks/testMaxDecoding.py\",\n \"repo_name\": \"indapa/pgmPy\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from Factor import *\\nfrom PGMcommon import *\\nfrom CliqueTree import *\\nfrom CliqueTreeOperations import *\\nfrom FactorOperations import *\\nimport scipy.io as sio\\nimport numpy as np\\nimport pprint\\nimport pdb\\nmatfile='/Users/amit/BC_Classes/PGM/Prog4/PA4Sample.mat'\\nmat_contents=sio.loadmat(matfile)\\nmat_struct=mat_contents['MaxDecoded']\\nval=mat_struct[0,0]\\ninput_factors = val['INPUT']\\nfactorList=[]\\n\\n\\n\\nfor elm in input_factors:\\n #print ary[0]\\n #print\\n (var, card, values)=elm[0]\\n #print var, card, values\\n f= Factor( var[0].tolist(), card[0].tolist(), values[0].tolist(), 'factor' )\\n print f\\n factorList.append( f )\\n\\nDECODE= MaxDecoding( factorList )\\nALPHABET=['a','b','c','d','e','f','g','h','i','j','k','l','m','n','o','p','q','r','s','t','u','v','w','x','y','z']\\n\\nprint DECODE\\nprint [ALPHABET[idx] for idx in DECODE]\\n\"\n },\n {\n \"alpha_fraction\": 0.6134676337242126,\n \"alphanum_fraction\": 0.6289501786231995,\n \"avg_line_length\": 37.806583404541016,\n \"blob_id\": \"6722fc523b10085c87b5dd4e4738154978fbc2d2\",\n \"content_id\": \"0305ab96f4d940ef4fd0f12b0a712221eba3f0cf\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 9430,\n \"license_type\": \"no_license\",\n \"max_line_length\": 127,\n \"num_lines\": 243,\n \"path\": \"/PGMcommon.py\",\n \"repo_name\": \"indapa/pgmPy\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#!/usr/bin/env python\\nfrom Factor import *\\nimport numpy as np\\nfrom itertools import product\\nimport sys\\nimport itertools\\n\\n\\ndef getUniqueVar( factorList):\\n \\\"\\\"\\\" given factorList which is a list of Factor objects\\n return a list of unique variables appearing in the\\n Factor objects. See http://stackoverflow.com/a/2151553/1735942 \\\"\\\"\\\"\\n\\n return list(set().union(*[ list(f.getVar()) for f in factorList ] ))\\n\\n\\ndef isMemberBoolean (A, B):\\n \\\"\\\"\\\" returns an list of the same length as A containing True where the elements of A are in B and False otherwise \\\"\\\"\\\"\\n \\n return [ x in B for x in A ]\\n\\ndef isMember( A, B):\\n \\\"\\\"\\\" return a python list containing indices in B where the elements of A are located\\n A and B are numpy 1-d arrays\\n mapA[i]=j if and only if B[i] == A[j]\\\"\\\"\\\"\\n mapA=[]\\n for i in range(len(A)):\\n mapA.append( np.where(B==A[i])[0].tolist()[0] )\\n\\n return mapA\\n\\n\\n\\n\\ndef accum(accmap, a, func=None, size=None, fill_value=0, dtype=None):\\n \\\"\\\"\\\" based on the recipie here to implement a numpy equivalent to matlab accumarray:\\n http://www.scipy.org/Cookbook/AccumarrayLike\\n An accumulation function similar to Matlab's `accumarray` function.\\n\\n Parameters\\n ----------\\n accmap : ndarray\\n This is the \\\"accumulation map\\\". It maps input (i.e. indices into\\n `a`) to their destination in the output array. The first `a.ndim`\\n dimensions of `accmap` must be the same as `a.shape`. That is,\\n `accmap.shape[:a.ndim]` must equal `a.shape`. For example, if `a`\\n has shape (15,4), then `accmap.shape[:2]` must equal (15,4). In this\\n case `accmap[i,j]` gives the index into the output array where\\n element (i,j) of `a` is to be accumulated. If the output is, say,\\n a 2D, then `accmap` must have shape (15,4,2). The value in the\\n last dimension give indices into the output array. If the output is\\n 1D, then the shape of `accmap` can be either (15,4) or (15,4,1)\\n a : ndarray\\n The input data to be accumulated.\\n func : callable or None\\n The accumulation function. The function will be passed a list\\n of values from `a` to be accumulated.\\n If None, numpy.sum is assumed.\\n size : ndarray or None\\n The size of the output array. If None, the size will be determined\\n from `accmap`.\\n fill_value : scalar\\n The default value for elements of the output array.\\n dtype : numpy data type, or None\\n The data type of the output array. If None, the data type of\\n `a` is used.\\n\\n Returns\\n -------\\n out : ndarray\\n The accumulated results.\\n\\n The shape of `out` is `size` if `size` is given. Otherwise the\\n shape is determined by the (lexicographically) largest indices of\\n the output found in `accmap`.\\n\\n\\n Examples\\n --------\\n from numpy import array, prod\\n a = array([[1,2,3],[4,-1,6],[-1,8,9]])\\n a\\n array([[ 1, 2, 3],\\n [ 4, -1, 6],\\n [-1, 8, 9]])\\n # Sum the diagonals.\\n accmap = array([[0,1,2],[2,0,1],[1,2,0]])\\n s = accum(accmap, a)\\n array([9, 7, 15])\\n # A 2D output, from sub-arrays with shapes and positions like this:\\n # [ (2,2) (2,1)]\\n # [ (1,2) (1,1)]\\n accmap = array([\\n [[0,0],[0,0],[0,1]],\\n [[0,0],[0,0],[0,1]],\\n [[1,0],[1,0],[1,1]],\\n ])\\n # Accumulate using a product.\\n accum(accmap, a, func=prod, dtype=float)\\n array([[ -8., 18.],\\n [ -8., 9.]])\\n # Same accmap, but create an array of lists of values.\\n accum(accmap, a, func=lambda x: x, dtype='O')\\n array([[[1, 2, 4, -1], [3, 6]],\\n [[-1, 8], [9]]], dtype=object)\\n \\\"\\\"\\\"\\n\\n if accmap.shape[:a.ndim] != a.shape:\\n raise ValueError(\\\"The initial dimensions of accmap must be the same as a.shape\\\")\\n if func is None:\\n func = np.sum\\n if dtype is None:\\n dtype = a.dtype\\n if accmap.shape == a.shape:\\n accmap = np.expand_dims(accmap, -1)\\n adims = tuple(range(a.ndim))\\n if size is None:\\n size = 1 + np.squeeze(np.apply_over_axes(np.max, accmap, axes=adims))\\n size = np.atleast_1d(size)\\n size=np.array(size, dtype=int)\\n # Create an array of python lists of values.\\n vals = np.empty(size, dtype='O')\\n for s in product(*[range(k) for k in size]):\\n vals[s] = []\\n for s in product(*[range(k) for k in a.shape]):\\n indx = tuple(accmap[s])\\n val = a[s]\\n vals[indx].append(val)\\n\\n # Create the output array.\\n out = np.empty(size, dtype=dtype)\\n for s in product(*[range(k) for k in size]):\\n if vals[s] == []:\\n out[s] = fill_value\\n else:\\n out[s] = func(vals[s])\\n\\n return out\\n\\n\\n\\ndef getIndex ( V, I):\\n \\\"\\\"\\\" this method finds for every element of 1d- NumPy array, the index in another 1d-NumPy array\\n based off of this StackOverflow answer http://stackoverflow.com/a/8251757/1735942\\n V is a numpy 1d array listing the variables of a factor in a PGM\\n I is the numpy list reprsenting the intersection of variables between two factors\\n\\n This method returns the index of the intersection variables in the list V \\n \\\"\\\"\\\"\\n index=np.argsort(V) #np.argsort gives the index ordering of an array that would result in sorted order\\n #http://docs.scipy.org/doc/numpy/reference/generated/numpy.argsort.html\\n sorted_v=V[index] #sorted version of V array\\n sorted_index=np.searchsorted( sorted_v, I) #i ndices where elements of I would be inserted into sorted_v to maintain order\\n #http://docs.scipy.org/doc/numpy/reference/generated/numpy.searchsorted.html\\n vindex=np.take(index, sorted_index, mode='clip') #Take elements from an array along an axis.\\\\\\n #http://docs.scipy.org/doc/numpy/reference/generated/numpy.take.html\\n #print vindex\\n return vindex.tolist()\\n\\ndef generateAlleleGenotypeMappers( numAlleles):\\n \\\"\\\"\\\" analogous to AssignmentToIndex and IndexToAssignment\\n this function maps alleles to genotypes and genotypes to alleles\\n each allele's id is its index in the list of alleles/list of allele freqs\\n Similar for genotypes, its id is its index in list of genotypes\\n\\n This function returns to numpy 2-d arrays. if n is the number of alleles\\n and m is the number of genotypes, then the following NumPy data structures\\n are returned\\n\\n allelesToGenotypes: n x n matrix that maps pairs of allele IDs to\\n genotype IDs -- if allelesToGenotypes[i, j] = k, then the genotype with\\n ID k comprises of the alleles with IDs i and j\\n\\n genotypesToAlleles: m x 2 matrix of allele IDs, where m is the number of\\n genotypes -- if genotypesToAlleles(k, :) = i, j, then the genotype with ID k\\n is comprised of the allele with ID i and the allele with ID j\\n\\n \\\"\\\"\\\"\\n allelesToGenotypes=np.zeros([numAlleles,numAlleles], dtype=np.int)\\n index=0\\n for i in range(numAlleles):\\n for j in range (i,numAlleles):\\n allelesToGenotypes[i, j] = index;\\n index+=1\\n\\n for i in range(numAlleles):\\n for j in range(0,i):\\n allelesToGenotypes[i,j] = allelesToGenotypes[j,i]\\n\\n\\n numGenotypes= (numAlleles * (numAlleles - 1))/2 + numAlleles\\n genotypesToAlleles=np.zeros([numGenotypes,2], dtype=np.int)\\n\\n index=0\\n for i in range(numGenotypes):\\n for j in range(i,numAlleles):\\n #print i, j\\n genotypesToAlleles[index, :] = [i, j];\\n index+=1\\n return ( allelesToGenotypes, genotypesToAlleles)\\n\\n\\ndef genotypeToIndex( geno, alleles='ACGT',ploidy=2):\\n \\\"\\\"\\\" given a string enumerating possible alleles\\n return the index of geno in enumerated list of genotypes\\n by default, the enumerated list is all 10 possibel genotypes\\\"\\\"\\\"\\n\\n genotypes= [ \\\"\\\".join(list(genotype)) for genotype in itertools.combinations_with_replacement(alleles, ploidy) ]\\n print genotypes\\n \\n try:\\n return genotypes.index(geno)\\n except ValueError:\\n print \\\"genotype not in list of genotypes.\\\"\\n \\n\\ndef indexToGenotype( index, alleles='ACGT', ploidy=2):\\n \\\"\\\"\\\" return genotype at a given index position after\\n enumerating all possible genotypes given string of alleles and\\n assigning to a list. By default the list contains all possible 10 genotypes\\\"\\\"\\\"\\n\\n \\n genotypes= [ \\\"\\\".join(list(genotype)) for genotype in itertools.combinations_with_replacement(alleles, ploidy) ]\\n \\n try:\\n return genotypes[index]\\n except IndexError:\\n print \\\"Index out of bounds, not a valid index for list of genotypes\\\"\\n\\n\\n\\ndef lognormalize(x):\\n \\\"\\\"\\\"http://atpassos.posterous.com/normalizing-log-probabilities-with-numpy\\n 'when working with probabilities it's very easy to get floating point underflows,\\n so most people use log probabilities. Probability multiplication is very easy in\\n log-space (it's just addition), but probability addition (or normalization) is harder,\\n and the linked post gives an equation to compute that. I used to implement it myself,\\n but today I learned that numpy does almost everything you need.'\\n\\n x is (natural) log list/array of numbers\\n this normalizes it in probabliity space\\\"\\\"\\\"\\n a=np.logaddexp.reduce(x)\\n return np.exp(x-a)\\n\"\n },\n {\n \"alpha_fraction\": 0.6626373529434204,\n \"alphanum_fraction\": 0.6725274920463562,\n \"avg_line_length\": 25.764705657958984,\n \"blob_id\": \"b8ba422539d63a40e51a28785a1acec6f66f6232\",\n \"content_id\": \"699408ae88a86444bb8d779c9baf87a651d0865d\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 910,\n \"license_type\": \"no_license\",\n \"max_line_length\": 114,\n \"num_lines\": 34,\n \"path\": \"/PythonNotebooks/testComputeExactMaxMarginalsBP.py\",\n \"repo_name\": \"indapa/pgmPy\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from Factor import *\\nfrom PGMcommon import *\\nfrom CliqueTree import *\\nfrom CliqueTreeOperations import *\\nfrom FactorOperations import *\\nimport scipy.io as sio\\nimport numpy as np\\nimport pprint\\nimport pdb\\nmatfile='/Users/amit/BC_Classes/PGM/Prog4/PA4Sample.mat'\\nmat_contents=sio.loadmat(matfile)\\nmat_struct=mat_contents['MaxMarginals']\\nval=mat_struct[0,0]\\ninput_factors = val['INPUT'][0]\\nfactorList=[]\\n\\nALPHABET=['a','b','c','d','e','f','g','h','i','j','k','l','m','n','o','p','q','r','s','t','u','v','w','x','y','z']\\n\\nfor tpl in input_factors:\\n (var, card, values)=tpl\\n #print var, card, values\\n f= Factor( var[0].tolist(), card[0].tolist(), values[0].tolist(), 'factor' )\\n #print f\\n factorList.append( f )\\n\\nMARGINALS= ComputeExactMarginalsBP( factorList, [], 1 )\\n\\nfor m in MARGINALS:\\n print m\\n print \\n\\nMAPAssignment=MaxDecoding( MARGINALS )\\n\\nprint [ALPHABET[idx] for idx in MAPAssignment]\\n\"\n },\n {\n \"alpha_fraction\": 0.6729958057403564,\n \"alphanum_fraction\": 0.6870604753494263,\n \"avg_line_length\": 29.80434799194336,\n \"blob_id\": \"f841b9c048f226eb153184190888b776b9c16e91\",\n \"content_id\": \"4050115e93c84fe585b4751c0c64b0e71efca4a8\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1422,\n \"license_type\": \"no_license\",\n \"max_line_length\": 83,\n \"num_lines\": 46,\n \"path\": \"/PythonNotebooks/testGetNextC.py\",\n \"repo_name\": \"indapa/pgmPy\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import scipy.io as sio\\nimport numpy as np\\nimport pprint\\nfrom Factor import *\\nfrom PGMcommon import *\\nfrom CliqueTree import *\\nfrom CliqueTreeOperations import *\\nfrom FactorOperations import *\\nimport pickle\\n\\n\\\"\\\"\\\" load the test data from the matlab file \\\"\\\"\\\"\\n\\nmatfile='/Users/amit/BC_Classes/PGM/Prog4/PA4Sample.mat'\\nmat_contents=sio.loadmat(matfile)\\nmat_struct=mat_contents['GetNextC']\\nnp.shape(mat_struct)\\nval=mat_struct[0,0] \\n\\ninput_edges = val['INPUT1']['edges'][0][0]\\ninput_cliqueList= val['INPUT1']['cliqueList'][0][0][0]\\nclique_list_factorObj=[]\\nfor tpl in input_cliqueList:\\n (var, card, values)=tpl\\n f= Factor( var[0].tolist(), card[0].tolist(), values[0].tolist(), 'factor' )\\n clique_list_factorObj.append(f)\\n\\nmessages=val['INPUT2']\\nmessageFactors=[]\\n(nrow,ncol)=np.shape(messages)\\nfor i in range( nrow ):\\n for j in range ( ncol ):\\n (var, card, values)=messages[i][j]\\n f=Factor( var[0].tolist(), card[0].tolist(), values[0].tolist(), 'factor' )\\n messageFactors.append(f)\\nMESSAGES= np.reshape( np.array ( messageFactors ), (nrow,ncol) )\\n\\n\\n\\\"\\\"\\\" dump it to Python pickle file \\\"\\\"\\\"\\nwith open('GetNextC.INPUT1.pickle', 'wb') as f:\\n pickle.dump(clique_list_factorObj,f)\\nwith open('GetNextC.INPUT2.pickle', 'wb') as f:\\n pickle.dump(MESSAGES, f)\\n\\nP=CliqueTree( clique_list_factorObj , input_edges, clique_list_factorObj, [])\\n(a,b)=getNextClique(P,MESSAGES)\\nprint 'a: ', a, ' b:', b\\n\\n\\n\\n\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.7124645709991455,\n \"alphanum_fraction\": 0.723796010017395,\n \"avg_line_length\": 25.148147583007812,\n \"blob_id\": \"3da136b5d711f3610dcdd7012ff1b9369c21a21b\",\n \"content_id\": \"2be847120a8d1e3734495ecd1244c22c27111867\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 706,\n \"license_type\": \"no_license\",\n \"max_line_length\": 80,\n \"num_lines\": 27,\n \"path\": \"/PythonNotebooks/testComputeExactMarginalsBP.py\",\n \"repo_name\": \"indapa/pgmPy\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from Factor import *\\nfrom PGMcommon import *\\nfrom CliqueTree import *\\nfrom CliqueTreeOperations import *\\nfrom FactorOperations import *\\nimport scipy.io as sio\\nimport numpy as np\\nimport pprint\\nimport pdb\\nmatfile='/Users/amit/BC_Classes/PGM/Prog4/PA4Sample.mat'\\nmat_contents=sio.loadmat(matfile)\\nmat_struct=mat_contents['ExactMarginal']\\nval=mat_struct[0,0]\\ninput_factors = val['INPUT'][0]\\nfactorList=[]\\nfor tpl in input_factors:\\n (var, card, values)=tpl\\n #print var, card, values\\n f= Factor( var[0].tolist(), card[0].tolist(), values[0].tolist(), 'factor' )\\n print f\\n factorList.append( f )\\n print\\nM=ComputeExactMarginalsBP( factorList )\\n\\n#for marginal in M:\\n# print marginal\\n# print\\n\"\n },\n {\n \"alpha_fraction\": 0.7310230731964111,\n \"alphanum_fraction\": 0.7384488582611084,\n \"avg_line_length\": 21.830188751220703,\n \"blob_id\": \"0732913f71d3a0e37ce1578a80734298d803125d\",\n \"content_id\": \"30737560acaabb2078c7491194efc40255b2bc76\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1212,\n \"license_type\": \"no_license\",\n \"max_line_length\": 82,\n \"num_lines\": 53,\n \"path\": \"/PythonNotebooks/testComputeExactMarginalsBP_SixPersonPedigree.py\",\n \"repo_name\": \"indapa/pgmPy\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from Factor import *\\nfrom PGMcommon import *\\nfrom CliqueTree import *\\nfrom CliqueTreeOperations import *\\nfrom FactorOperations import *\\nimport scipy.io as sio\\nimport numpy as np\\nimport pprint\\nimport pdb\\n\\nmatfile='/Users/indapa/software/PGM/Prog4/PA4Sample.mat'\\nmat_contents=sio.loadmat(matfile)\\n\\nmat_struct=mat_contents['SixPersonPedigree']\\nval=mat_struct[0]\\n\\nfactorList=[]\\nfor elem in val:\\n \\n (var, card, val) =elem\\n f= Factor( var[0].tolist(), card[0].tolist(), val[0].tolist(), 'factor' )\\n #print f\\n factorList.append(f)\\n#print\\n\\njointFactor = ComputeJointDistribution(factorList)\\n#print jointFactor\\n\\nMARGINALS= ComputeExactMarginalsBP( factorList, [], 1)\\nP=CreatePrunedInitCtree(factorList, [] )\\n(P, MESSAGES) = CliqueTreeCalibrate(P, isMax=1)\\njointDistribution=ComputeJointDistributionFromCalibratedCliqueTree(P, MESSAGES, 1)\\n\\nprint jointDistribution\\n\\n\\n #for marginal in MARGINALS:\\n #print marginal\\n#print\\n\\nMAPAssignment=MaxDecoding( MARGINALS )\\nprint MAPAssignment\\n\\n\\n #for m in MARGINALS:\\n #m.setVal( np.log( lognormalize(m.getVal() ) ) )\\n#print np.sum( lognormalize(m.getVal() ) )\\n\\n#print MAPAssignment\\n\\n #for marginal in MARGINALS:\\n #print marginal.getVal()\\n#print\\n\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.5498276948928833,\n \"alphanum_fraction\": 0.5565862655639648,\n \"avg_line_length\": 34.619049072265625,\n \"blob_id\": \"28b1213670945b618ae76007849239564e60561a\",\n \"content_id\": \"bc4b62dd851aee8a9a7b141e5692c63d02d25d65\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 7546,\n \"license_type\": \"no_license\",\n \"max_line_length\": 129,\n \"num_lines\": 210,\n \"path\": \"/CliqueTree.py\",\n \"repo_name\": \"indapa/pgmPy\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from Factor import *\\nfrom FactorOperations import *\\nimport numpy as np\\nimport networkx as nx\\nimport pdb\\n\\nclass CliqueTree(object):\\n 'represent a Clique tree'\\n\\n def __init__(self, nodeList=[], edges=[], factorList=[],evidence=[]):\\n self.nodeList=nodeList\\n self.edges=edges\\n self.factorList=factorList\\n self.evidence=evidence\\n self.card= []\\n self.factorInds= []\\n\\n\\n def toString(self):\\n \\n print 'nodes: ', self.nodeList\\n print 'card: ', self.card\\n print 'factorList: ', len( self.factorList)\\n print 'factorInds:', self.factorInds\\n print 'edges:\\\\n',self.edges\\n \\n \\n def setNodeList(self,nodeList):\\n self.nodeList=nodeList\\n\\n def setEdges(self,edges):\\n self.edges=edges\\n\\n def setFactorList(self,factorList):\\n self.factorList=factorList\\n #self.factorInds= len( factorList ) * [None]\\n\\n def setEvidence(self,evidence):\\n self.evidence=evidence\\n\\n\\n def setCard(self, cardinality):\\n self.card = cardinality\\n\\n def getNodeList(self):\\n return self.nodeList\\n\\n def getNodeCount(self):\\n return len(self.nodeList)\\n\\n\\n def getEdges(self):\\n return self.edges\\n\\n def getFactorList(self):\\n return self.factorList\\n\\n def getFactorCount(self):\\n return len(self.factorList)\\n \\n\\n def getEvidence(self):\\n return self.evidence\\n\\n def incorporateEvidence(self):\\n for j in range ( len(self.evidence)):\\n k=j+1\\n if self.evidence[j] > 0:\\n self.factorList=ObserveEvidence(self.factorList, np.matrix([[k, self.evidence[j] ]] ) )\\n \\n\\n def eliminateVar(self,Z,E,factorList):\\n \\\"\\\"\\\" a variable elimination function\\n based on https://github.com/indapa/PGM/blob/master/Prog4/EliminateVar.m\\n\\n Z is the variable to be eliminated. We base this code on the matlab file\\n linked to above as well as the Sum-product VE pseudo code in Koller and Friedman\\n page 298\\n\\n E is a numpy 2d matrix representing adjacency matrix of variables\\n It represents the induced VE graph\\n Once a variable is eliminated, its edges are removed from E\\n\\n \\\"\\\"\\\"\\n\\n useFactors = []#the index of the factor that contains the variable Z\\n scope = []\\n\\n #print 'Z: ', Z\\n\\n \\n #get a list containining the index in self.factorLlist of factors\\n #that contain the variable Z to be eliminated\\n # get the scope of variables from the factors that contain variable Z\\n for i in range (len(factorList)):\\n \\n if Z in factorList[i].getVar().tolist():\\n useFactors.append(i)#the ith factor is being currently involved in elimination\\n scope=list(set.union(set(scope), factorList[i].getVar().tolist() ))\\n\\n \\n # update edge map\\n \\\"\\\"\\\" These represent the induced edges for the VE graph.\\n once the variable Z is eliminated, its edges are removed from the graph\\n but in the process of elimination, we create a new factor. This\\n introduces fill edges (see pg. 307 Koller and Friedman)\\n Z is one based, but the indices in E are zero based, hence Z-1\\n also the variable names in scope are 1 based, so we subtract 1 when\\n updating the induced VE graph \\\"\\\"\\\"\\n\\n for i in range ( len(scope)):\\n for j in range ( len(scope)):\\n if i != j:\\n E[ scope[i]-1, scope[j]-1 ]=1\\n E[ scope[j]-1, scope[i]-1 ]=1\\n E[Z-1,:]=0\\n E[:,Z-1]=0\\n\\n #G=nx.from_numpy_matrix(E)\\n #print 'induced graph edges:\\\\n', (G.edges())\\n #nx.draw_shell(G)\\n #plt.show()\\n\\n \\n #these are the indices of factorList which are not involved in VE\\n unusedFactors= list( set.difference ( set(range(len(factorList))), set(useFactors) ) )\\n \\n newF=None\\n #check first if there are any unused factors left!\\n if len(unusedFactors) > 0:\\n newF=len(unusedFactors)*[None]\\n newmap=np.zeros(max(unusedFactors)+1,dtype=int).tolist()\\n \\n #newF is a new factor list, we populate it first\\n #with the unused factors\\n #newmap is maps the new location of ith unusedFactor\\n for i in range( len(unusedFactors)):\\n newF[i]=factorList[ unusedFactors[i] ]\\n newmap[ unusedFactors[i] ]= i\\n \\n #print 'newmap ', newmap,\\\"\\\\n\\\"\\n #print 'length of newmap: ', len(newmap), \\\"\\\\n\\\"\\n\\n newFactor = Factor( [], [], [], 'newFactor')\\n\\n #we multiple in all the factors that contain the variable Z\\n for i in range( len (useFactors)):\\n newFactor = FactorProduct(newFactor,factorList[ useFactors[i] ])\\n \\n\\n #then we marginalize Z out and obtain a new factor\\n #then append it the end of newF, the new factor list\\n newFactor = FactorMarginalization( newFactor,[Z] )\\n #print 'newFactor: ',newFactor\\n #newF(length(nonUseFactors)+1) = newFactor;\\n if newFactor != None:\\n newF.append ( newFactor )\\n\\n \\n\\n if newF != None:\\n factorList=newF\\n #return E\\n\\n ########################################################################\\n \\\"\\\"\\\" the remaining code builds the edges of the clique tree \\\"\\\"\\\"\\n\\n \\\"\\\"\\\" add new node with the factors that contain the variable Z\\n adding a new node represents new clique.\\n The scope of every factor generated during the variable elimination process is a clique pg. 309 Koller & Friedman \\\"\\\"\\\"\\n\\n self.nodeList.append ( scope )\\n \\n #newC is the total number of nodes in the clique tree\\n newC=len( self.nodeList )\\n #print 'newC: ', newC\\n\\n #factorInds are individual factors with one variable ... I think\\n self.factorInds.append ( len(unusedFactors) + 1 )\\n \\n\\n #print 'range( newC -1) ', range( newC-1 )\\n #print 'factorInds: ', self.factorInds\\n #print 'useFactors: ', useFactors\\n #pdb.set_trace()\\n \\\"\\\"\\\" we update the edges of the clique tree \\\"\\\"\\\"\\n for i in range( newC -1 ):\\n \\n #if self.factorInds [ i ] -1 in useFactors:\\n #there was the off by onoe erorr - the values in factorInds\\n #were one-based, need to subtract 1\\n if self.factorInds [ i ] -1 in useFactors:\\n \\n self.edges[ i, newC-1 ] = 1\\n self.edges [ newC-1, i ] = 1\\n self.factorInds[ i ] = 0\\n else:\\n if self.factorInds [i] != 0:\\n #print 'i: ', i\\n #print 'factorInds: ', self.factorInds\\n #print 'newmap: ', newmap\\n #print 'newmap [ self.factorInds[i] -1: ', newmap [ self.factorInds[i] -1 ]\\n #print 'self.factorInds[ i ] = newmap [ self.factorInds[i] - 1 ] + 1 '\\n if len(unusedFactors) > 0:\\n #self.factorInds[ i ] = newmap [ self.factorInds[i] -1 ] +1\\n self.factorInds[ i ] = newmap [ self.factorInds[i] -1 ] +1\\n #self.factorInds[ i ] = newmap [ self.factorInds[i] ]\\n \\n #print 'factorInds right before returning: ', self.factorInds\\n return E, factorList\\n\\n \\n \\n \\n \\n \\n \\n\\n\\n \\n\"\n },\n {\n \"alpha_fraction\": 0.6040363311767578,\n \"alphanum_fraction\": 0.6095243692398071,\n \"avg_line_length\": 32.891998291015625,\n \"blob_id\": \"5c1ec832317f91ec124a82ea127d3d09b357f2f2\",\n \"content_id\": \"7f8e61964fb1ca92ec0a9bb7bc030ecd890dca57\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 16946,\n \"license_type\": \"no_license\",\n \"max_line_length\": 125,\n \"num_lines\": 500,\n \"path\": \"/PedigreeFactors.py\",\n \"repo_name\": \"indapa/pgmPy\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\nimport numpy as np\\nfrom Factor import *\\nfrom PGMcommon import *\\nfrom FactorOperations import *\\nimport itertools\\n\\nclass PhenotypeFactor (object):\\n \\\"\\\"\\\" represents a factor that encodes Pr(phenotype|genotype)\\n for purposes here the variable to the left of the conditioning\\n bar is the first variable in the PhenotypeFactor var list. \\\"\\\"\\\"\\n\\n def __init__(self, isDominant, genotypeVar, phenotypeVar, name):\\n\\n #instantiate a Factor object\\n phenotype = Factor( [phenotypeVar, genotypeVar], [2, 3], [], name )\\n \\n phenotype.setVal( np.zeros ( np.prod(phenotype.getCard())).tolist() )\\n #this enumerates the values the factor can take\\n # since there are 2x3 cardinality, 6 possible assignments\\n assignments=IndexToAssignment( np.arange(np.prod(phenotype.getCard())), phenotype.getCard() )\\n val=val = np.zeros(np.prod(phenotype.getCard() ))\\n (nrows,ncols)=np.shape(assignments)\\n\\n for i in range(np.prod([2,3])):\\n #if its dominant, if you have at least one copy, you have the phenotype\\n (pheno,geno)=assignments[i]\\n if isDominant==1:\\n if pheno ==1: #affected\\n if geno ==1 or geno ==2:\\n val[i]=1\\n else:\\n val[i]=0\\n else:#uneffected\\n if geno == 3:\\n val[i]=1\\n\\n\\n if isDominant == 0:\\n if pheno == 1:\\n if geno==3:\\n val[i]=1\\n else:\\n if geno ==1 or geno == 2:\\n val[i]=1\\n\\n\\n phenotype.setVal( val.tolist() )\\n\\n self.phenotype=phenotype\\n\\n\\n\\n def getVar(self):\\n return self.phenotype.getVar()\\n def getCard(self):\\n return self.phenotype.getCard()\\n def getVal(self):\\n return self.phenotype.getVal()\\n\\n def getFactor(self):\\n return self.phenotype\\n\\n def __str__(self):\\n return self.phenotype.__str__()\\n\\n\\n\\nclass PhenotypeGivenGenotypeFactor(object):\\n \\\"\\\"\\\" construct factor of phenotype|genotype\\n #prob of being effected, given the ith genotype\\n #alphaList[i] is the prob of being effected given the ith genotype \\\"\\\"\\\"\\n def __init__(self,alphaList, phenotypeVar, genotypeVar , name):\\n self.phenotypeFactor=Factor( [ phenotypeVar, genotypeVar], [], [], name)\\n self.alpha=np.array ( alphaList)\\n\\n ngenotypes=len(alphaList)\\n self.phenotypeFactor.setCard( [2, ngenotypes])\\n\\n values=[x for x in range( np.prod(self.phenotypeFactor.getCard()))]\\n\\n for i in range( len(alphaList )):\\n\\n values[i]=alphaList[i]\\n values[i+1]=1-alphaList[i]\\n ctr=0\\n alphas=2*len(alphaList)*[None]\\n for i in range(len(alphaList)):\\n alphas[ctr]=alphaList[i];\\n ctr=ctr+1\\n alphas[ctr]=1-alphaList[i];\\n ctr=ctr+1\\n\\n values=alphas\\n self.phenotypeFactor.setVal( values)\\n\\n def getVar(self):\\n return self.phenotypeFactor.getVar()\\n def getCard(self):\\n return self.phenotypeFactor.getCard()\\n def getVal(self):\\n return self.phenotypeFactor.getVal()\\n def setVal(self,val):\\n self.phenotypeFactor.setVal(val)\\n def getFactor(self):\\n return self.phenotypeFactor\\n\\n\\n def __str__(self):\\n return self.phenotypeFactor.__str__()\\n\\n\\nclass GenotypeAlleleFreqFactor (object):\\n \\\"\\\"\\\" construct a factor that has the probability of each genotype\\n given allele frequencies Pr(genotype|allele_freq)\\\"\\\"\\\"\\n\\n def __init__(self, allelefreqs, genotypeVar, name):\\n self.allelefreq=allelefreqs\\n #number of alleles == number of allele frequencies passed in\\n numAlleles=len(allelefreqs)\\n self.allelesToGenotypes=None\\n self.genotypesToAlleles=None\\n self.genotypeFactor=None\\n\\n #map alleles to genotypes and genotyeps to alleles\\n (self.allelesToGenotypes, self.genotypesToAlleles)=generateAlleleGenotypeMappers(numAlleles)\\n (ngenos,ploidy)=np.shape(self.genotypesToAlleles)\\n\\n\\n self.genotypeFactor = Factor( [genotypeVar], [], [], name)\\n #the cardinality of the factor is the number of genotypes\\n self.genotypeFactor.setCard( [ngenos] )\\n\\n #set the values to zero initially\\n values=np.zeros( (np.prod(self.genotypeFactor.getCard()))).tolist()\\n \\n for i in range (ngenos):\\n alleles=self.genotypesToAlleles[i,:].tolist()\\n \\n\\n if alleles[0] == alleles[1]:\\n values[i]= np.prod( [ allelefreqs[j] for j in alleles ])\\n \\n else:\\n values[i]= np.prod( [ allelefreqs[j] for j in alleles ]) * 2\\n \\n self.genotypeFactor.setVal( values )\\n\\n\\n def getVar(self):\\n return self.genotypeFactor.getVar()\\n def getCard(self):\\n return self.genotypeFactor.getCard()\\n def getVal(self):\\n return self.genotypeFactor.getVal()\\n def setVal(self,val):\\n self.genotypeFactor.setVal(val)\\n def getFactor(self):\\n return self.genotypeFactor\\n\\n\\n def __str__(self):\\n return self.genotypeFactor.__str__()\\n\\nclass GenotypeGivenParentsFactor (object):\\n \\\"\\\"\\\" construct factor that has prob of genotype of child given both parents\\n Pr(g_child| g_mother, g_father \\\"\\\"\\\"\\n\\n def __init__(self,numAlleles, genotypeVarChild, genotypeVarParentOne, genotypeVarParentTwo, name):\\n self.genotypeFactor = Factor( [genotypeVarChild, genotypeVarParentOne, genotypeVarParentTwo ], [ ], [ ], name)\\n\\n #map alleles to genotypes and genotyeps to alleles\\n (self.allelesToGenotypes, self.genotypesToAlleles)=generateAlleleGenotypeMappers(numAlleles)\\n\\n (ngenos,ploidy)=np.shape(self.genotypesToAlleles)\\n \\n\\n \\n self.genotypeFactor.setCard([ ngenos,ngenos,ngenos ] )\\n #set the values to zero initially\\n values=np.zeros( (np.prod(self.genotypeFactor.getCard()))).tolist()\\n\\n #iterate thru variable assignments to random variables\\n #assign probablities based on Punnet square crosses\\n assignments=IndexToAssignment( np.arange(np.prod(self.genotypeFactor.getCard())), self.genotypeFactor.getCard() )-1\\n for z in range( np.prod(self.genotypeFactor.getCard() ) ):\\n curr_assign= assignments[z]\\n childAssignment=int(curr_assign[0])\\n\\n parent1gametes= self.genotypesToAlleles[curr_assign[1],:]\\n parent2gametes= self.genotypesToAlleles[curr_assign[2],:]\\n #print 'parental gametes: ', parent1gametes, parent2gametes\\n #print 'child assignment: ', childAssignment\\n #list of tuples containing list of zygote(genotype) tuples\\n zygote_list=list(itertools.product(parent1gametes,parent2gametes))\\n punnet_freq=[ self.allelesToGenotypes[zygote[0],zygote[1]] for zygote in zygote_list ]\\n histc={}\\n hist=[]\\n for g in range( ngenos):\\n histc[g]=0.\\n for x in punnet_freq:\\n histc[x]+=1.\\n #print histc.values()\\n for g in range (ngenos):\\n hist.append ( histc[g] )\\n #print punnet_freq\\n hist=(np.array ( hist)) /4\\n #print 'hist:', hist\\n #print zygote_list\\n values[z]=hist[childAssignment]\\n\\n self.genotypeFactor.setVal( values )\\n\\n def getVar(self):\\n return self.genotypeFactor.getVar()\\n def getCard(self):\\n return self.genotypeFactor.getCard()\\n def getVal(self):\\n return self.genotypeFactor.getVal()\\n def setVal(self, val):\\n self.genotypeFactor.setVal(val)\\n\\n def getFactor(self):\\n return self.genotypeFactor\\n def genotypeSlice(self):\\n pass\\n #see this http://stackoverflow.com/q/4257394/1735942\\n\\n def __str__(self):\\n return self.genotypeFactor.__str__()\\n\\n\\nclass ChildCopyGivenParentalsFactor(object):\\n \\\"\\\"\\\" this represents a de-coupled factor\\n given a parents two haplotypes, returns\\n factor whose values are the probablity\\n of inheriting (grand)paternal or (grand)maternal\\n haplotype. This allows for some more flexibility\\n in modeling inheritance, rather than clumping\\n a single parent's haplotype into a genotype\\n i.e. GenotypeGivenParentsFactor \\\"\\\"\\\"\\n\\n def __init__(self, numAlleles, geneCopyVarChild, geneCopyHapOne, geneCopyHapTwo):\\n self.numalleles=numAlleles\\n self.hapone=geneCopyVarChild\\n self.haptwo=geneCopyHapTwo\\n\\n #geneCopyFactor = struct('var', [], 'card', [], 'val', []);\\n self.geneCopyFactor=Factor( [geneCopyVarChild, geneCopyHapOne, geneCopyHapTwo ], [], [], 'child|hap1,hap2')\\n self.geneCopyFactor.setCard( [self.numalleles,self.numalleles,self.numalleles ])\\n values=np.zeros( np.prod([ self.numalleles,self.numalleles,self.numalleles])).tolist()\\n #this keeps track of what posiiton you are in the values list\\n index=0\\n #the number of iterations thru the nested for loops should be equal to numallels^3\\n\\n for i in range(numAlleles):\\n #iterate through alleles from\\n #grand(paternal) haplotype\\n for j in range(numAlleles):\\n #iterate through alleles from\\n #grand(maternal) haplotype\\n for k in range(numAlleles):\\n #iterate thru child alleles\\n print i, j, k\\n if j==k:#child has grandmotherhap\\n if i==k:#grandfatherhap is the same\\n values[index]=1\\n else:\\n values[index]=.5\\n elif i==k:#child has grandfather hap\\n values[index]=.5\\n else:\\n pass\\n index+=1\\n #print values\\n self.geneCopyFactor.setVal( values )\\n\\n def getVar(self):\\n return self.geneCopyFactor.getVar()\\n def getCard(self):\\n return self.geneCopyFactor.getCard()\\n def getVal(self):\\n return self.geneCopyFactor.getVal()\\n def getFactor(self):\\n return self.geneCopyFactor\\n def __str__(self):\\n return self.geneCopyFactor.__str__()\\n \\nclass ChildCopyGivenFreqFactor(object):\\n \\\"\\\"\\\" for a founder, its particular haplotype is proprortional to the\\n given allelel freq of the locus. This factor is part of the decoupled\\n Bayesian Genetic network , along with ChildCopyGivenParentalsFactor\\\"\\\"\\\"\\n \\n def __init__(self, alleleFreqs, geneCopyVar):\\n numAlleles = len(alleleFreqs)\\n self.geneCopyFactor=Factor( [geneCopyVar], [], [], 'founderHap')\\n self.geneCopyFactor.setCard ( [numAlleles])\\n self.geneCopyFactor.setVal( alleleFreqs )\\n #geneCopyFactor = struct('var', [], 'card', [], 'val', [])\\n #geneCopyFactor.var(1) = geneCopyVar;\\n #geneCopyFactor.card(1) = numAlleles;\\n #geneCopyFactor.val = alleleFreqs';\\n\\n\\n def getVar(self):\\n return self.geneCopyFactor.getVar()\\n def getCard(self):\\n return self.geneCopyFactor.getCard()\\n def getVal(self):\\n return self.geneCopyFactor.getVal()\\n def getFactor(self):\\n return self.genCopyFactor\\n def __str__(self):\\n return self.geneCopyFactor.__str__()\\n\\nclass phenotypeGivenHaplotypesFactor(object):\\n \\\"\\\"\\\" factor represents Pr(phenotype| paternal haplotype, maternal haplotype)\\n very similiar to PhenotypeGivenGenotypeFactor, but we are de-coupling into\\n paternal and maternal alleles rather than genotype\\\"\\\"\\\"\\n\\n def __init__(self, alphaList, numAlleles, geneCopyVarOne, geneCopyVarTwo, phenotypeVar):\\n \\n self.numalleles=numAlleles\\n self.alphaList=alphaList\\n self.phenotypeFactor=Factor([phenotypeVar,geneCopyVarOne, geneCopyVarTwo], [], [], 'phenotype| geneCopy1, geneCopy2')\\n\\n ngenos=len(alphaList)\\n self.phenotypeFactor.setCard( [ 2, numAlleles, numAlleles])\\n #phenotypeFactor.val = zeros(1, prod(phenotypeFactor.card));\\n values=np.zeros( (1, np.prod(self.phenotypeFactor.getCard()))).flatten().tolist()\\n\\n affectedAlphas=alphaList\\n unaffectedAlphas=[ 1- alpha for alpha in alphaList]\\n\\n\\n (allelesToGenotypes, genotypesToAlleles) = generateAlleleGenotypeMappers(numAlleles)\\n assignments=IndexToAssignment( np.arange(np.prod(self.phenotypeFactor.getCard())), self.phenotypeFactor.getCard() )-1\\n for z in range( np.prod(self.phenotypeFactor.getCard() ) ):\\n curr_assign= assignments[z]\\n curr_assign=assignments[z]\\n genotype_num=allelesToGenotypes[curr_assign[1], curr_assign[2]]\\n if curr_assign[0] == 0:\\n values[z] = affectedAlphas[genotype_num]\\n else:\\n values[z] = unaffectedAlphas[genotype_num]\\n self.phenotypeFactor.setVal( values )\\n\\n\\n #genotype_num=allelesToGenotypes(assignment(2), assignment(3));\\n\\n\\n def getVar(self):\\n return self.phenotypeFactor.getVar()\\n def getCard(self):\\n return self.phenotypeFactor.getCard()\\n def getVal(self):\\n return self.phenotypeFactor.getVal()\\n def getFactor(self):\\n return self.phenotypeFactor\\n def __str__(self):\\n return self.phenotypeFactor.__str__()\\n\\n def __str__(self):\\n return self.phenotypeFactor.__str__()\\n\\n\\n##########################\\n\\nclass Ped(object):\\n \\\"\\\"\\\" represents a pedigree record in a Ped file http://pngu.mgh.harvard.edu/~purcell/plink/data.shtml#ped \\\"\\\"\\\"\\n\\n def __init__(self,famid='.', indv='.', paternal='.', maternal='.', sex='.', phenotype='.'):\\n \\\"\\\"\\\" attributes of a Ped object \\\"\\\"\\\"\\n self.famid=famid\\n self.individ=indv\\n self.pid=paternal\\n self.mid=maternal\\n self.sex=sex\\n self.pheno=phenotype\\n\\n\\n def setfamid(self,famid):\\n self.famid=famid\\n\\n def setindvid(self,indv):\\n self.individ=indv\\n\\n def setmid(self,mid):\\n self.mid=mid\\n\\n def setpid(self,pid):\\n self.pid=pid\\n\\n def setsex(self,sex):\\n self.sex=sex\\n\\n def setpheno(self,pheno):\\n self.pheno=pheno\\n\\n\\n\\n def getfamid(self):\\n return self.famid\\n\\n def getid(self):\\n return self.individ\\n\\n def getmid(self):\\n return self.mid\\n\\n def getpid(self):\\n return self.pid\\n\\n def getsex(self):\\n return self.sex\\n\\n def getpheno(self):\\n return self.pheno\\n\\n\\n def isFounder(self):\\n return self.pid == '0' and self.mid == '0'\\n\\n def getParents(self):\\n\\n return ( self.pid, self.mid)\\n\\n\\n def __str__(self):\\n return \\\"\\\\t\\\".join( [ self.famid, self.individ, self.pid, self.mid, self.sex, self.pheno] )\\n\\n\\nclass Pedfile(object):\\n \\\"\\\"\\\" a Pedfile object has a list of Ped objects \\\"\\\"\\\"\\n\\n def __init__(self,filename):\\n self.filename=filename\\n self.fh=open(self.filename, 'r')\\n self.pedlist=[]\\n\\n def parsePedfile(self):\\n \\\"\\\"\\\" given a filehandle to a *.ped file read its contents and populate the list pedlist with Ped objects \\\"\\\"\\\"\\n for line in self.fh:\\n fields=line.strip().split('\\\\t')\\n (famid, indv, pid, mid, sex, pheno)=fields[0:6]\\n self.pedlist.append( Ped(famid, indv, pid, mid, sex, pheno) )\\n\\n \\n def returnFounders(self):\\n \\\"\\\"\\\" return the founders in a ped file (those with unknown paternal and maternids \\\"\\\"\\\"\\n founders=[]\\n\\n for pedobj in self.pedlist:\\n if pedobj.getpid() == \\\"0\\\":\\n founders.append(pedobj)\\n\\n return founders\\n\\n def returnFounderIds(self):\\n \\\"\\\"\\\" return the indiv ids of the founders in the ped file\\\"\\\"\\\"\\n founderids=[]\\n for pedobj in self.pedlist:\\n if pedobj.getpid() == \\\"0\\\":\\n founderids.append( pedobj.getid() )\\n return founderids\\n\\n def returnNonFounderIds(self):\\n \\\"\\\"\\\" return the indiv ids of the founders in the ped file\\\"\\\"\\\"\\n nonfounderids=[]\\n for pedobj in self.pedlist:\\n if pedobj.getpid() != \\\"0\\\":\\n nonfounderids.append( pedobj.getid() )\\n return nonfounderids\\n\\n def returnNonFounders(self):\\n \\\"\\\"\\\" return the founders in a ped file (those with unknown paternal and maternids \\\"\\\"\\\"\\n nonfounders=[]\\n\\n for pedobj in self.pedlist:\\n if pedobj.getpid() != \\\"0\\\":\\n nonfounders.append(pedobj)\\n\\n return nonfounders\\n\\n def returnIndivids(self):\\n \\\"\\\"\\\" return a list of indvi ids from the ped file \\\"\\\"\\\"\\n #samplelist=[]\\n return [ ped.getid() for ped in self.pedlist]\\n\\n def getPedList(self):\\n return self.pedlist\\n def getTotalSize(self):\\n return len(self.pedlist)\\n\\n def yieldMembers(self):\\n for pedobj in self.pedlist:\\n yield pedobj\\n\\n def __str__(self):\\n return \\\"\\\\n\\\".join( [ x.__str__() for x in self.pedlist ] )\\n\"\n },\n {\n \"alpha_fraction\": 0.6863157749176025,\n \"alphanum_fraction\": 0.7442105412483215,\n \"avg_line_length\": 29.645160675048828,\n \"blob_id\": \"0a1a76b17b4d700f9be7186e8dd219773d8cc43a\",\n \"content_id\": \"e8c8f724f79ebda14e822822476b89c63b38eef7\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 950,\n \"license_type\": \"no_license\",\n \"max_line_length\": 77,\n \"num_lines\": 31,\n \"path\": \"/PythonNotebooks/testFactorMaxMarginal.py\",\n \"repo_name\": \"indapa/pgmPy\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from Factor import *\\nfrom PGMcommon import *\\nfrom CliqueTree import *\\nfrom CliqueTreeOperations import *\\nfrom FactorOperations import *\\nimport scipy.io as sio\\nimport numpy as np\\nimport pprint\\nimport pdb\\nmatfile='/Users/amit/BC_Classes/PGM/Prog4/PA4Sample.mat'\\nmat_contents=sio.loadmat(matfile)\\nmat_struct=mat_contents['FactorMax']\\nval=mat_struct[0,0]\\ninput_factors = val['INPUT1'][0][0]\\nvar = input_factors[0].flatten().tolist()\\ncard=input_factors[1].flatten().tolist()\\nvalue=input_factors[2].flatten().tolist()\\nprint var\\nprint card\\nprint value\\nINPUT1= Factor( var, card, value, 'test')\\nINPUT2= val['INPUT2'].flatten()\\nprint INPUT1\\nprint INPUT2\\nprint FactorMaxMarginalization(INPUT1, INPUT2)\\n#example used in section 13.2 pg 555 of Friedman and Koller\\nprint \\\"=====\\\"\\npsi=Factor( [ 1,2,3], [3,2,2], [.25,.05,.15,.08,0,.09,.35,.07,.21,.16,0,.18])\\nmaxfactor= FactorMaxMarginalization(psi, [2])\\nprint maxfactor\\nprint IndexToAssignment(np.arange(6),[3,2])\\n\"\n },\n {\n \"alpha_fraction\": 0.7376237511634827,\n \"alphanum_fraction\": 0.7514851689338684,\n \"avg_line_length\": 19.612245559692383,\n \"blob_id\": \"86ff9b6732bcf620cf67d00014f02397c8fa240d\",\n \"content_id\": \"54f67628fbc30361e5623bc83d6eed66e3c68a05\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1010,\n \"license_type\": \"no_license\",\n \"max_line_length\": 78,\n \"num_lines\": 49,\n \"path\": \"/PythonNotebooks/testCliqueTreeOperations.py\",\n \"repo_name\": \"indapa/pgmPy\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\nimport numpy as np\\nfrom Factor import *\\nfrom PGMcommon import *\\nfrom PedigreeFactors import *\\nfrom FactorOperations import *\\nfrom GeneticNetworkFactory import *\\nfrom CliqueTree import *\\nimport networkx as nx\\nimport matplotlib.pyplot as plt\\nfrom CliqueTreeOperations import *\\n#to create a clique tree, we start with a list of factors\\n#and potentially some observed evidence\\nalphaList=[.8,.6,.1]\\nallelefreq=[.1,.9]\\nchrom='12'\\nposition=1000\\ng1=GeneticNetworkFactory('sixperson.ped',alphaList,allelefreq, chrom,position)\\ng1.constructNetwork()\\nfactorList=g1.getFactorList()\\n\\n#for f in factorList:\\n# print f\\n# print \\n#print \\\"+++++++++\\\"\\n\\ncTree = createCliqueTree(factorList)\\nG=nx.from_numpy_matrix( cTree.getEdges() )\\n\\nnx.draw_shell(G)\\nplt.show()\\n#print cTree.getEdges()\\n\\n#cTree.toString()\\n\\n\\nprunedCTree=PruneTree( cTree )\\nP=CliqueTreeInitialPotential( prunedCTree )\\n\\n#for f in P.getNodeList():\\n# print f\\n# print\\n\\n\\n\\n\\nG=nx.from_numpy_matrix( prunedCTree.getEdges() )\\nnx.draw_shell(G)\\nplt.show()\\n\"\n },\n {\n \"alpha_fraction\": 0.5923784971237183,\n \"alphanum_fraction\": 0.5969107151031494,\n \"avg_line_length\": 39.27850341796875,\n \"blob_id\": \"b5132ff6c2652a9dccd8fb63ae78206208620c59\",\n \"content_id\": \"371be786bccdbdfa6ed14e3f39ed6e62084ca22a\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 21623,\n \"license_type\": \"no_license\",\n \"max_line_length\": 172,\n \"num_lines\": 535,\n \"path\": \"/CliqueTreeOperations.py\",\n \"repo_name\": \"indapa/pgmPy\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import numpy as np\\nfrom CliqueTree import *\\nfrom FactorOperations import *\\n#import matplotlib.pyplot as plt\\nimport networkx as nx\\nimport pdb\\n\\ndef createCliqueTree( factorList,E=[]):\\n \\\"\\\"\\\" return a Clique Tree object given a list of factors\\n it peforms VE and returns the clique tree the VE\\n ordering defines. See Chapter 9 of Friedman and Koller\\n Probabilistic Graphical Models\\\"\\\"\\\"\\n\\n V=getUniqueVar(factorList)\\n \\n totalVars=len(V)\\n cardinality=np.zeros(len(V)).tolist()\\n for i in range(len(V)):\\n for j in range(len(factorList)):\\n try:\\n indx= factorList[j].getVar().tolist().index( V[i] )\\n cardinality[i]=factorList[j].getCard().tolist()[indx]\\n break\\n except:\\n continue\\n\\n edges=np.zeros( (totalVars, totalVars))\\n\\n\\n \\\"\\\"\\\" Set up adjacency matrix: for each factor, get the list of variables in its scope and create an edge between each variable in the factor \\\"\\\"\\\"\\n for f in factorList:\\n variableList=f.getVar()\\n for j in range(len(variableList) ):\\n for k in range (len(variableList) ):\\n edges[ variableList[j]-1, variableList[k]-1 ]=1\\n\\n (nrows,nedges)=np.shape(edges) \\n\\n C=CliqueTree()\\n C.setCard( cardinality )\\n C.setEdges(np.zeros( (totalVars, totalVars)))\\n C.setFactorList(factorList)\\n C.setEvidence(E)\\n C.setNodeList([])\\n #print 'length of factorList: ', len(factorList)\\n #print C.toString()\\n cliquesConsidered = 0\\n #pdb.set_trace()\\n while cliquesConsidered < len(V):\\n bestClique = 0\\n bestScore = sys.maxint\\n for i in range(nrows):\\n score=np.sum( edges[i,:] )\\n if score > 0 and score < bestScore:\\n bestScore = score\\n bestClique = i+1\\n cliquesConsidered+=1\\n \\n (edges, factorList)=C.eliminateVar(bestClique, edges, factorList)\\n\\n return C\\n\\n\\ndef PruneTree ( C ):\\n \\\"\\\"\\\" prune a clique tree by determing if neighboring cliques are \\n supersets of each other. E.g.: [A,B,E] -- [A,B] -- [A,D] \\n pruned: [A,B,E] -- [A,D] \\\"\\\"\\\"\\n\\n ctree_edges=C.getEdges()\\n (nrows,ncols)=np.shape( ctree_edges )\\n totalNodes=nrows\\n Cnodes=C.getNodeList()\\n \\n toRemove=[]\\n #print range( totalNodes )\\n\\n for i in range ( totalNodes ):\\n if i in toRemove: continue\\n #np.nonzero returns tuple, hence the [0]\\n #we collect the neighbors of the ith clique\\n neighborsI = np.nonzero ( ctree_edges[i,:] )[0].tolist()\\n for c in range ( len(neighborsI) ):\\n j= neighborsI[c]\\n assert ( i != j), 'i cannot equal j: PruneTree'\\n if j in toRemove: continue\\n #here is where we look for superset neighboring nodes in the CTree\\n if sum ( [ x in Cnodes[j] for x in Cnodes[i] ] ) == len( Cnodes[i] ):\\n for nk in neighborsI:\\n cnodes_i = set ( Cnodes[i] )\\n cnodes_nk= set ( Cnodes[nk] )\\n if len( list ( set.intersection( cnodes_i, cnodes_nk) ) ) == len (Cnodes[i]):\\n neighborsI_set=set( neighborsI )\\n nk_set=set( [nk] )\\n ctree_edges [ list( neighborsI_set - nk_set ), nk ] = 1\\n ctree_edges [ nk, list( neighborsI_set - nk_set )] = 1\\n break\\n ctree_edges[i,:]=0\\n ctree_edges[:,i]=0\\n toRemove.append(i)\\n toKeep = list ( set ( range( totalNodes ) ) - set ( toRemove ) )\\n for indx in toRemove:\\n Cnodes[indx]=[]\\n Cnodes=[ item for item in Cnodes if len(item) > 0 ]\\n ctree_edges= ctree_edges[np.ix_(toKeep, toKeep)]\\n\\n C.setNodeList( Cnodes )\\n C.setEdges( ctree_edges )\\n #pdb.set_trace()\\n #return the pruned tree with the updated nodes and edges\\n return C\\n\\ndef CliqueTreeObserveEvidence ( C, E ):\\n \\\"\\\"\\\" given a CliqueTree object C and list of values E, which represent evidence, update\\n the factors of the cliqueTree C to reflect the observed evidence.\\n Note that ObserveEvidence in FactorOperations assumes E is a Nx2 matrix,\\n here we build the Nx2 matrix by assuing the jth index of E is the evidence\\n for the variable j\\\"\\\"\\\"\\n factorList= C.getFactorList()\\n for j in range ( len (E)):\\n if E[j] > 0:\\n factorList=ObserveEvidence( factorList, np.array(np.matrix( [ j+1, E[j]] ) ) )\\n C.setFactorList(factorList)\\n #return the new CliqueTree object with the updated evidence\\n return C\\n\\n\\ndef CliqueTreeInitialPotential( C ):\\n \\\"\\\"\\\" given a clique tree object C, calculate the initial potentials for each of the cliques\\n the factors in the updated clique list are FActor objects\\\"\\\"\\\"\\n\\n \\n N= C.getNodeCount()\\n totalFactorCount=C.getFactorCount()\\n\\n nodeList=C.getNodeList()\\n factorList=C.getFactorList()\\n\\n cliqueList=[ Factor( [], [], [], str(i) ) for i in range(N) ]\\n #edges=np.zeros( (N,N) )\\n\\n \\\"\\\"\\\" First assign the factors to appropriate cliques\\n based on the skeleton cliqueTree cTree\\\"\\\"\\\"\\n\\n factorsUsed=np.zeros( totalFactorCount, dtype=int).tolist()\\n #pdb.set_trace()\\n for i in range(N):\\n cliqueList[i].setVar( nodeList[i] )\\n F=[]\\n \\\"\\\"\\\" we add factors to the clique if they are in the variable scope of the clique \\\"\\\"\\\"\\n for j in range( len(factorList) ):\\n if len( factorList[j].getVar().tolist() ) == len ( list( set.intersection ( set(cliqueList[i].getVar().tolist() ), set( factorList[j].getVar().tolist() ) ) ) ):\\n \\n if factorsUsed[j] == 0:\\n F.append( factorList[j] )\\n factorsUsed[j] = 1\\n #print F\\n #pdb.set_trace()\\n #F= [ f.getFactor() for f in F ]\\n cliqueList[i]=ComputeJointDistribution ( F )\\n #pdb.set_trace()\\n C.setNodeList(cliqueList)\\n #pdb.set_trace()\\n return C\\n\\ndef getNextClique(P, messages):\\n\\n \\\"\\\"\\\" we need to come up wih a proper message passing order. A clique is ready to pass\\n messages upward once its recieved all downstream messages from its neighbor (and vice versa)\\n its ready to transmit downstream once it recieves all its upstream messages\\n\\n the ith clique C_i is ready to transmit to its neighbor C_j when C_i recieves all its\\n messages from neigbors except C_j. In cTree message passing, each message is passed\\n once. To get the process started we start with our initial potential cTree, P\\n and an empty matrix of factors, representing messages passed between the nodes on the clique\\n tree \\\"\\\"\\\"\\n i=j=-1\\n edges=P.getEdges()\\n #print edges\\n (nrow, ncol) = np.shape(edges)\\n\\n for r in range(nrow):\\n \\n #we want to ignore nodes with only one neighbor\\n #becuae they are ready to pass messages\\n if np.sum(edges[r,:] ) == 1:\\n continue \\n\\n foundmatch=0\\n\\n for c in range(ncol):\\n if edges[r,c] == 1 and messages[r,c].getVarCount() == 0:\\n #list of indices indicating neighbors or r\\n #print 'r,c: ', r, ' ', c\\n #print 'edges[r,c]: ', edges[r,c]\\n Nbs=np.nonzero(edges[:,r])[0]\\n #print 'Nbs before:', Nbs\\n Nbs=Nbs[np.nonzero(Nbs!= c)[0]]\\n #print 'Nbs after: ', Nbs\\n allnbmp=1 #neighbors messages passed?\\n \\n #find all of r's neighbors have sent messages *to* r\\n for z in range( len(Nbs) ):\\n #print messages[Nbs[z],r].getVarCount()\\n if messages[ Nbs[z],r].getVarCount() == 0:\\n allnbmp=0\\n\\n if allnbmp == 1:\\n foundmatch=1\\n break\\n \\n if foundmatch==1:\\n #sys.stderr.write(\\\"found match!\\\\n\\\")\\n i=r\\n j=c\\n break\\n \\n return (i,j)\\n\\n\\ndef CliqueTreeCalibrate( P, isMax=False):\\n \\\"\\\"\\\" this function performs sum-product or max-product algorithm for clique tree calibration.\\n P is the CliqueTree object. isMax is a boolean flag that when set to True performs Max-Product\\n instead of the default Sum-Product. The function returns a calibrated clique tree in which the\\n values of the factors is set to final calibrated potentials.\\n\\n Once a tree is calibrated, in each clique (node) contains the marginal probability over the variables in\\n its scope. We can compute the marginal probability of a variable X by choosing a clique that contains the\\n variable of interest, and summing out non-query variables in the clique. See page 357 in Koller and Friedman\\n\\n B_i(C_i)= sum_{X-C_i} P_phi(X)\\n\\n The main advantage of clique tree calibration is that it facilitates the computation of posterior\\n probabliity of all variables in the graphical model with an efficient number of steps. See pg 358\\n of Koller and Friedman\\n\\n After calibration, each clique will contain the marginal (or max-mariginal, if isMax is set to True)\\n\\n \\\"\\\"\\\"\\n \\n np.set_printoptions(suppress=True)\\n ctree_edges=P.getEdges()\\n\\n ctree_cliqueList=P.getNodeList()\\n\\n \\\"\\\"\\\" if max-sum, we work in log space \\\"\\\"\\\"\\n if isMax == True:\\n ctree_cliqueList= [ LogFactor (factor) for factor in ctree_cliqueList ]\\n\\n \\n \\n N=P.getNodeCount() #Ni is the total number of nodes (cliques) in cTree\\n\\n #dummyFactor=Factor( [], [], [], 'factor')\\n #set up messsages to be passed\\n #MESSAGES[i,j] represents the message going from clique i to clique j\\n #MESSAGES will be a matrix of Factor objects\\n MESSAGES=np.tile( Factor( [], [], [], 'factor'), (N,N))\\n DUMMY=np.reshape( np.arange(N*N)+1, (N,N) )\\n \\n\\n \\\"\\\"\\\"While there are ready cliques to pass messages between, keep passing\\n messages. Use GetNextCliques to find cliques to pass messages between.\\n Once you have clique i that is ready to send message to clique\\n j, compute the message and put it in MESSAGES(i,j).\\n Remember that you only need an upward pass and a downward pass.\\\"\\\"\\\"\\n\\n \\\"\\\"\\\" leaf nodes are ready to pass messages right away\\n so we initialize MESSAGES with leaf message factors\\n recall, a node is a leave if row sum is equal to 1\\\"\\\"\\\"\\n for row in range(N):\\n rowsum= np.sum( ctree_edges[row,:] )\\n if rowsum ==1 :\\n #Returns a tuple of arrays, one for each dimension, we want the first, hence the [0]\\n leafnode=np.nonzero( ctree_edges[row,:] )[0].tolist()[0]\\n #I discovered NumPy set operations http://docs.scipy.org/doc/numpy/reference/routines.set.html\\n marginalize=np.setdiff1d( ctree_cliqueList[row].getVar(), ctree_cliqueList[leafnode].getVar() ).tolist()\\n sepset=np.intersect1d( ctree_cliqueList[row].getVar(), ctree_cliqueList[leafnode].getVar() ).tolist()\\n\\n \\\"\\\"\\\" if isMax is false, this is sumproduct, so we do factor marginalization \\\"\\\"\\\"\\n if isMax == 0:\\n #MESSAGES(row,leafnode)=FactorMarginalization(P.cliqueList(row),marginalize);\\n MESSAGES[row,leafnode]=FactorMarginalization(ctree_cliqueList[row], marginalize )\\n if np.sum( MESSAGES[row,leafnode].getVal() ) != 1:\\n newVal=MESSAGES[row,leafnode].getVal() / np.sum( MESSAGES[row,leafnode].getVal() )\\n MESSAGES[row,leafnode].setVal(newVal)\\n else:\\n \\\"\\\"\\\" if isMax is true, this is max-marginalization\\n don't normalize the value just yet\\\"\\\"\\\"\\n MESSAGES[row,leafnode]=FactorMaxMarginalization( ctree_cliqueList[row], marginalize )\\n\\n\\n \\n \\\"\\\"\\\" now that the leaf messages are initialized, we begin with the rest of the clique tree\\n now we do a single pass to arrive at the calibrated clique tree. We depend on\\n GetNextCliques to figure out which nodes i,j pass messages to each other\\\"\\\"\\\"\\n \\n while True:\\n (i,j)=getNextClique(P,MESSAGES)\\n if sum ( [ i, j] ) == -2:\\n break\\n #print 'i: ', i, 'j: ', j\\n \\\"\\\"\\\" similiar to above, we figure out the sepset and what variables to marginalize out\\n between the two cliques\\\"\\\"\\\"\\n marginalize=np.setdiff1d( ctree_cliqueList[i].getVar(), ctree_cliqueList[j].getVar() ).tolist()\\n sepset=np.intersect1d( ctree_cliqueList[i].getVar(), ctree_cliqueList[j].getVar() ).tolist()\\n\\n \\\"\\\"\\\" find all the incoming neighbors, except j \\\"\\\"\\\"\\n Nbs=np.nonzero( ctree_edges[:,i])[0] #returns a tuple ...\\n Nbs_minusj=[ elem for elem in Nbs if elem != j ]\\n #print 'Nbs_minusj: ', Nbs_minusj, ' [i]: ', [i]\\n #see numpy for matlab users http://www.scipy.org/NumPy_for_Matlab_Users\\n # these are incoming messages to the ith clique\\n Nbsfactors=MESSAGES[np.ix_(Nbs_minusj, [i] )].flatten().tolist()\\n #print DUMMY[np.ix_(Nbs_minusj, [i] )].flatten()\\n #for f in Nbsfactors:\\n #print f\\n \\\"\\\"\\\" this is sum/product \\\"\\\"\\\"\\n if isMax == 0:\\n #print 'total number of Nbs factors: ', len(Nbsfactors)\\n if len(Nbsfactors) == 1:\\n Nbsproduct=FactorProduct( Nbsfactors[0], IdentityFactor(Nbsfactors[0]) )\\n else:\\n Nbsproduct=ComputeJointDistribution( Nbsfactors )\\n #pdb.set_trace()\\n #val=Nbsproduct.getVal()\\n #rowcount=len(val)/3\\n #print Nbsproduct.getVar()\\n #print Nbsproduct.getCard()\\n #print np.reshape( val, (rowcount,3))\\n #now mulitply wiht the clique factor\\n \\n CliqueNbsproduct=FactorProduct( Nbsproduct, ctree_cliqueList[i] )\\n \\n CliqueMarginal= FactorMarginalization ( CliqueNbsproduct, marginalize )\\n \\n #normalize the marginal\\n newVal=CliqueMarginal.getVal() / np.sum( CliqueMarginal.getVal() )\\n\\n CliqueMarginal.setVal( newVal )\\n \\n MESSAGES[i,j] = CliqueMarginal\\n else:\\n if len(Nbsfactors) == 1:\\n Nbssum=Nbsfactors[0]\\n else:\\n Nbssum=reduce ( lambda x,y: FactorSum(x,y), Nbsfactors )\\n CliqueNbsSum=FactorSum( Nbssum, ctree_cliqueList[i] )\\n CliqueMarginal=FactorMaxMarginalization( CliqueNbsSum, marginalize )\\n MESSAGES[i,j] = CliqueMarginal\\n #print\\n\\n\\n\\n #######################################################################\\n \\\"\\\"\\\" once out the while True loop, the clique tree has been calibrated\\n here is where we compute final belifs (potentials) for the cliques and place them in \\\"\\\"\\\"\\n\\n for i in range ( len(ctree_cliqueList)):\\n Nbs=np.nonzero( ctree_edges[:,i])[0]#returns a tuple\\n Nbsfactors=MESSAGES[np.ix_(Nbs, [i])].flatten().tolist()\\n\\n if isMax == 0:\\n if len(Nbsfactors) == 1:\\n Nbsproduct=FactorProduct( Nbsfactors[0], IdentityFactor(Nbsfactors[0]) )\\n else:\\n Nbsproduct=ComputeJointDistribution ( Nbsfactors)\\n \\n CliqueNbsProduct=FactorProduct(Nbsproduct, ctree_cliqueList[i])\\n #pdb.set_trace()\\n ctree_cliqueList[i]=CliqueNbsProduct\\n else:\\n if len(Nbsfactors) == 1:\\n Nbssum=Nbsfactors[0]\\n else:\\n Nbssum=reduce ( lambda x,y: FactorSum(x,y), Nbsfactors )\\n CliqueNbsSum=FactorSum(Nbssum, ctree_cliqueList[i])\\n ctree_cliqueList[i]=CliqueNbsSum\\n \\n P.setNodeList( ctree_cliqueList )\\n #np.savetxt( 'numpy.cTree.edges.calibrated.txt',ctree_edges,fmt='%d', delimiter='\\\\t')\\n \\n #pdb.set_trace()\\n #return P\\n return (P, MESSAGES)\\n #for k in range(len(ctree_cliqueList)):\\n # print 'k: ', k\\n # print ctree_cliqueList[k]\\n #IndexToAssignment(1:prod(P.cliqueList(1).card), P.cliqueList(1).card)\\n # I=np.arange(np.prod( ctree_cliqueList[k].getCard() ))\\n # print IndexToAssignment( I, ctree_cliqueList[k].getCard() )\\n # print \\\"==\\\"\\n\\n #return P\\n\\n\\ndef CreatePrunedInitCtree(F,E=[]):\\n \\\"\\\"\\\" 1. create cTree from list of factors F and evidence E\\n 2. prune it\\n 3. compute initial potential of the tree\\n 4. return it\\\"\\\"\\\"\\n\\n cTree = createCliqueTree(F,E)\\n prunedCTree=PruneTree( cTree )\\n prunedCTree.incorporateEvidence()\\n return CliqueTreeInitialPotential( prunedCTree )\\n\\n \\n\\ndef ComputeExactMarginalsBP( F, E=[], isMax=False, computeJoint=0):\\n \\\"\\\"\\\" We take a list of Factor objects, observed Evidence E\\n and returns marignal proabilities for the variables in the\\n Bayesian network. If isMax is 1 it runs MAP inference ( *still need to\\n do this *) otherwise it runs exact inference using Sum/Product algorithm.\\n The ith element of the returned list represents the ith variable in the\\n network and its marginal prob of the variable\\n\\n Note, we implicitly create, prune, initialize, and calibrate a clique tree\\n constructed from the factor list F \\\"\\\"\\\"\\n\\n MARGINALS=[]\\n #pdb.set_trace()\\n P = CreatePrunedInitCtree(F,E)\\n #G=nx.from_numpy_matrix( P.getEdges() )\\n #nx.draw_shell(G)\\n #plt.show()\\n \\n #plt.savefig('cliqueTree.png', bbox_inches=0)\\n (P,MESSAGES) = CliqueTreeCalibrate(P,isMax)\\n #pdb.set_trace()\\n if computeJoint==1:\\n jointDistribution=ComputeJointDistributionFromCalibratedCliqueTree(P, MESSAGES, isMax)\\n else:\\n jointDistribution=None\\n #pdb.set_trace()\\n #P = CliqueTreeCalibrate(P,isMax)\\n cliqueList=P.getNodeList()\\n \\n fh=open('ExactMarginals.CliqueTree.log','a')\\n for i in range(len(cliqueList)):\\n out = \\\",\\\".join( map(str, cliqueList[i].getVar().tolist() )) \\n outstring= \\\"node \\\" + str(i) + \\\":\\\\t\\\" + out +'\\\\n'\\n fh.write(outstring)\\n fh.write(\\\"\\\\n\\\")\\n #np.savetxt( 'numpy.cTree.edges.calibrated.txt',P.getEdges(),fmt='%d', delimiter='\\\\t')\\n np.savetxt('ExactMarginals.CliqueTree.log',P.getEdges(),fmt='%d', delimiter='\\\\t')\\n \\n \\n \\n \\n \\\"\\\"\\\" get the list of unique variables \\\"\\\"\\\"\\n V=getUniqueVar(F)\\n \\n\\n for i in range ( len(V ) ):\\n for j in range ( len(cliqueList ) ):\\n if V[i] in cliqueList[j].getVar():\\n marginalize=np.setdiff1d ( cliqueList[j].getVar(), V[i] ).tolist()\\n if not marginalize:\\n MARGINALS.append( cliqueList[j] )\\n else:\\n if isMax == 0:\\n #mfactor=FactorMarginalization(P.cliqueList(j), marginalize);\\n mfactor=FactorMarginalization( cliqueList[j], marginalize )\\n newVal=mfactor.getVal() / np.sum( mfactor.getVal() )\\n mfactor.setVal( newVal )\\n MARGINALS.append ( mfactor )\\n else:\\n mfactor=FactorMaxMarginalization( cliqueList[j], marginalize )\\n MARGINALS.append( mfactor )\\n break\\n\\n \\n return (MARGINALS,jointDistribution)\\n\\ndef ComputeJointDistributionFromCalibratedCliqueTree( P, MESSAGES, isMax=0):\\n \\n \\\"\\\"\\\" this is a function to attempt to compute the joint distribution from\\n a calibrated clique tree (cTree). The arguments are: \\n 1. The calibrated cTree, P, which is a CliqueTree object\\n 2. The sepset beliefs are is the matrix MESSAGES\\n The MESSAGES matrix is a matrix of Factor objects\\n We can get the indices of the sepset messages\\n from the edges of the clique tree. \\n \\n This function attempts to implement equation 10.10 in Koller and Friedman\\n in section 10.2.3: A Calibrated Clique Tree as a Distribution\\n \\n P_\\\\Phi(X) = \\\\frac{ \\\\prod_{i \\\\in V_T} \\\\Beta_i(C_i) } { \\\\prod_{i-j} \\\\in E_T \\\\mu_i,j(S_i,j) }\\n \\n Basically A) multiply the clique beliefs \\n B) multiply the sepset beliefs\\n C) divide A/B \\n \\n \\n \\\"\\\"\\\"\\n cliqueFactors=P.getNodeList()\\n \\n \\\"\\\"\\\" if this is a max-marginal calibrated clique tree the values are in log space\\n Just re-exponentiate them \\\"\\\"\\\"\\n if isMax==1:\\n cliqueFactors = [ ExpFactorNormalize(c) for c in cliqueFactors ]\\n \\n \\\"\\\"\\\" this is the numerator \\\"\\\"\\\"\\n cliqueBeliefProducts=reduce(lambda x, y: FactorProduct(x,y), cliqueFactors)\\n \\n \\\"\\\"\\\" get the adjacency matrix of the clique tree \\\"\\\"\\\"\\n adj_matrix=P.getEdges()\\n \\n \\\"\\\"\\\" get the nonzero indices, then compute the product of the sepset beliefs \\\"\\\"\\\"\\n nonzero_rows=adj_matrix.nonzero()[0].tolist()\\n nonzero_cols=adj_matrix.nonzero()[1].tolist()\\n \\n \\n\\n \\n \\n sepsetBeliefsFactors= [ MESSAGES[x,y] for (x,y) in zip(nonzero_rows, nonzero_cols) ] \\n \\n \\\"\\\"\\\" if this is a max-marginal calibrated clique tree the values are in log space\\n Just re-exponentiate them \\\"\\\"\\\"\\n if isMax == 1:\\n sepsetBeliefsFactors = [ ExpFactorNormalize(c) for c in sepsetBeliefsFactors ]\\n \\n \\n \\n sepsetBeliefProducts= reduce( lambda x,y: FactorProduct(x,y), sepsetBeliefsFactors)\\n \\n \\\"\\\"\\\" the re-parameterization of the joint (clique tree invariant) \\n divide the clique beliefs by the sepset messages \\\"\\\"\\\"\\n jointDistrbution=FactorDiv(cliqueBeliefProducts, sepsetBeliefProducts)\\n \\n val=jointDistrbution.getVal()/np.sum( jointDistrbution.getVal() )\\n jointDistrbution.setVal( val )\\n \\n return jointDistrbution\\n \\n \\n \\n \\n \\n \\n \\n \\n\"\n },\n {\n \"alpha_fraction\": 0.6553258895874023,\n \"alphanum_fraction\": 0.6626390814781189,\n \"avg_line_length\": 47.35384750366211,\n \"blob_id\": \"052a0afcbd86e4459fa3a6420618a716e35992f8\",\n \"content_id\": \"ed61124800b8bd503bbb5d69a2e2582775581716\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 3145,\n \"license_type\": \"no_license\",\n \"max_line_length\": 194,\n \"num_lines\": 65,\n \"path\": \"/GeneticNetworkFactory.py\",\n \"repo_name\": \"indapa/pgmPy\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from Factor import *\\nfrom FactorOperations import *\\nfrom PedigreeFactors import *\\nimport itertools\\nimport numpy as np\\n\\\"\\\"\\\"\\\" Still not sure how this is going to work\\n This class is a factory for generating a genetic network\\n If we consider each location in the genome independent\\n we generate a new network for each position along an interval.\\n A network is a collection of factors, so we return a python\\n list of Pedigree factors (either GenotypeAlleleFreqFactor for founders\\n or GenotypeGivenParentsFactor for non-founders. Each phenotype is conditionally\\n independent given its genotoype, so each member of the pedigree has a\\n PhenotypeGivenGenotypeFactor\\\"\\\"\\\"\\n\\nclass GeneticNetworkFactory(object):\\n \\n\\n def __init__(self, pedfile, alphaList, allelefreq, chrom, position):\\n #parse pedfile\\n self.alphaList=alphaList\\n self.allelefreq=allelefreq\\n self.totalAlleles=len(allelefreq)\\n self.chrom=chrom\\n self.pos=position\\n\\n self.pedigree=Pedfile(pedfile)\\n self.pedigree.parsePedfile()\\n self.pedlist=self.pedigree.getPedList()\\n self.pedids=self.pedigree.returnIndivids()\\n #print self.pedids\\n\\n #list of factors that will comprise the Genetic network\\n self.totalFactors=self.pedigree.getTotalSize() * 2\\n self.factorList=self.totalFactors*[None]\\n\\n \\n def constructNetwork(self):\\n totalPeople=self.pedigree.getTotalSize()\\n for i in range( totalPeople ):\\n \\n \\n if self.pedlist[i].isFounder():\\n #print self.pedlist[i].getid()\\n self.factorList[i]=GenotypeAlleleFreqFactor(self.allelefreq,i+1,self.pedlist[i].getid() + \\\" genotype \\\")\\n #self.factorList[i]=GenotypeAlleleFreqFactor(self.allelefreq,self.pedlist[i].getid(),self.pedlist[i].getid())\\n #factorList(i)=genotypeGivenAlleleFreqsFactor(alleleFreqs,i);\\n else:\\n #3print self.pedlist[i].getParents(), self.pedlist[i].getid()\\n #GenotypeGivenParentsFactor(2,\\\"bart\\\",\\\"homer\\\",\\\"marge\\\",\\\"\\\"\\\"Bart | Homer, Marge \\\"\\\"\\\")\\n #self.factorList[i]=GenotypeGivenParentsFactor(self.totalAlleles, self.pedlist[i].getid(), self.pedlist[i].getParents()[0], self.pedlist[i].getParents()[1], \\\"child|Father,Child\\\")\\n parent1Index=self.pedids.index( self.pedlist[i].getParents()[0] )\\n parent2Index=self.pedids.index( self.pedlist[i].getParents()[1] )\\n child=self.pedlist[i].getid()\\n parent1name=self.pedlist[parent1Index].getid()\\n parent2name=self.pedlist[parent2Index].getid()\\n name=child+\\\" genotype |\\\"+parent1name+\\\",\\\"+parent2name\\n self.factorList[i]=GenotypeGivenParentsFactor(self.totalAlleles, i+1, parent1Index+1 , parent2Index+1 , name)\\n \\n name=self.pedlist[i].getid()+\\\" phenotype | \\\" + self.pedlist[i].getid() + \\\" genotype\\\"\\n\\n self.factorList[i+totalPeople]=PhenotypeGivenGenotypeFactor(self.alphaList,i+totalPeople+1,i+1, name )\\n\\n def getFactorList(self):\\n return self.factorList\\n\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.69027179479599,\n \"alphanum_fraction\": 0.6959942579269409,\n \"avg_line_length\": 26.41176414489746,\n \"blob_id\": \"9c2992617817dbf6c1fbdb56f4e689d9ea99368e\",\n \"content_id\": \"10d1a9842a0bf1c1fdead15c69d0ccf7db82f50d\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1398,\n \"license_type\": \"no_license\",\n \"max_line_length\": 114,\n \"num_lines\": 51,\n \"path\": \"/PythonNotebooks/ocr_MAP.py\",\n \"repo_name\": \"indapa/pgmPy\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from Factor import *\\nfrom PGMcommon import *\\nfrom CliqueTree import *\\nfrom CliqueTreeOperations import *\\nfrom FactorOperations import *\\nimport scipy.io as sio\\nimport numpy as np\\nimport pprint\\nimport pdb\\nimport matplotlib.pyplot as plt\\nimport networkx as nx\\nmatfile='/Users/amit/BC_Classes/PGM/Prog4/PA4Sample.mat'\\nmat_contents=sio.loadmat(matfile)\\nmat_struct=mat_contents['OCRNetworkToRun']\\nval=mat_struct\\nfactorList=[]\\n\\nALPHABET=['a','b','c','d','e','f','g','h','i','j','k','l','m','n','o','p','q','r','s','t','u','v','w','x','y','z']\\n\\nfor data in val:\\n \\n (var, card, values)=data[0]\\n f= Factor( var[0].tolist(), card[0].tolist(), values[0].tolist(), 'factor' )\\n factorList.append( f )\\n\\n#MARGINALS= ComputeExactMarginalsBP( factorList, [], 1 )\\n#MAPAssignment=MaxDecoding( MARGINALS )\\n#print \\\"\\\".join( [ALPHABET[idx] for idx in MAPAssignment] )\\n\\nMARGINALS= ComputeExactMarginalsBP( factorList, [], 1 )\\nfor m in MARGINALS:\\n log_val= m.getVal()\\n prob_val_normalized=np.log( lognormalize( log_val ) )\\n m.setVal(prob_val_normalized)\\n\\n\\nMAPAssignment=MaxDecoding( MARGINALS )\\nprint \\\"\\\".join( [ALPHABET[idx] for idx in MAPAssignment] )\\n\\nfor m in MARGINALS:\\n print np.sum( lognormalize(m.getVal() ) )\\n\\n\\n#V=getUniqueVar(factorList)\\n#print 'unique variables:'\\n#print V\\n\\n#cTree=CreatePrunedInitCtree(factorList)\\n#G=nx.from_numpy_matrix( cTree.getEdges() )\\n#nx.draw_shell(G)\\n#plt.show()\\n\"\n },\n {\n \"alpha_fraction\": 0.5952702760696411,\n \"alphanum_fraction\": 0.5993243455886841,\n \"avg_line_length\": 27.941177368164062,\n \"blob_id\": \"e6d8e78b6e65a7eea8f3f483a8ce9e82cf7a1392\",\n \"content_id\": \"3217b3e442a436bf70fc4fe7ed9919eb6a80733a\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1480,\n \"license_type\": \"no_license\",\n \"max_line_length\": 121,\n \"num_lines\": 51,\n \"path\": \"/Factor.py\",\n \"repo_name\": \"indapa/pgmPy\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\nimport numpy as np\\nclass Factor(object):\\n\\n \\\"\\\"\\\" Represents a factor in a PGM. A factor has variable scope, cardinality, value, and potentially a name.\\n A factor's values (which can potentially be multi-dimensional table, are represented as NumPy 1d-arrays.\\n See Chapter10 Friedman pg. 358 and Koller for more info. \\\"\\\"\\\"\\n\\n\\n\\n def __init__(self, var=[], card=[], val=[], name= 'None'):\\n \\\"\\\"\\\" a factor has list of variables, each with a cardinality, and for each possible assignment to its variable(s),\\n a position in the val array.\\\"\\\"\\\"\\n self.var= np.array(var)\\n self.card=np.array(card)\\n self.val=np.array(val)\\n self.name=name\\n\\n def __str__(self):\\n varstring= \\\" \\\".join ( map(str, self.var) )\\n cardstring=\\\" \\\".join ( map(str, self.card) )\\n valstring= \\\" \\\".join( map(str, self.val))\\n return \\\"\\\\n\\\".join( [ 'name: ' + self.name,'var: '+ varstring, 'card: '+ cardstring, 'val: ' + valstring])\\n\\n\\n def setVar(self, var):\\n self.var=np.array(var)\\n\\n def getVar(self):\\n return self.var\\n\\n def getVarCount(self):\\n return len( self.var.tolist() )\\n\\n def setVal(self, val):\\n self.val=np.array(val)\\n\\n def getVal(self):\\n return self.val\\n\\n def setCard(self,card):\\n self.card=np.array(card)\\n\\n def getCard(self):\\n return self.card\\n\\n def getName(self):\\n return self.name\\n\\n def setName(self, name):\\n self.name=name\\n\\n\\n\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.6409705877304077,\n \"alphanum_fraction\": 0.6484430432319641,\n \"avg_line_length\": 39.885555267333984,\n \"blob_id\": \"80f59e493196baae8ffed0576e2078272e0110c1\",\n \"content_id\": \"cdf59801c73aa21c25d1fb91b720b1549a6e36a7\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 36802,\n \"license_type\": \"no_license\",\n \"max_line_length\": 174,\n \"num_lines\": 900,\n \"path\": \"/FactorOperations.py\",\n \"repo_name\": \"indapa/pgmPy\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#!/usr/bin/env python\\nfrom Factor import *\\nimport numpy as np\\nfrom PGMcommon import *\\nimport sys\\nimport itertools\\nimport common\\nimport pdb\\n\\ndef IndexToAssignment( I, D):\\n\\n \\\"\\\"\\\" given and index I (a row vector representing the indices of values a factor object's val field\\n and D, an array representing the cadinality of variables in a factor object, this function produces\\n a matrix of assignments, one assignment per row. See https://github.com/indapa/PGM/blob/master/Prog1/IndexToAssignment.m \\\"\\\"\\\"\\n\\n a=np.reshape ( np.arange(np.prod(D)).repeat(len(D)), (np.prod(D),len(D)))\\n \\n\\n b=tmp=list( D[:-1] )\\n tmp.insert(0,1)\\n tmp =np.cumprod ( np.array (tmp) )\\n b=np.tile( np.cumprod(b), (len(I), 1))\\n #print b\\n\\n #print np.floor ( a /b )\\n c=np.tile ( D, ( len(I), 1) )\\n\\n assignment = np.mod ( np.floor( a/b), c) +1\\n return assignment\\n\\n\\ndef AssignmentToIndex ( A, D):\\n \\\"\\\"\\\" I = AssignmentToIndex(A, D) converts an assignment, A, over variables\\n with cardinality D to an index into the .val vector for a factor.\\n If A is a matrix then the function converts each row of A to an index.\\n See https://github.com/indapa/PGM/blob/master/Prog1/AssignmentToIndex.m \\\"\\\"\\\"\\n \\n D=D.flatten(0) #turn array into vector (note that this forces a copy), see http://www.scipy.org/NumPy_for_Matlab_Users#head-fd74115e6798fbf3a628094a55d1cb2b2b5cdd3c\\n I=np.array( [] )\\n (nrowA,ncolA)=np.shape(A)\\n\\n if nrowA== 1 or ncolA ==1: #if assginments are 1 row or 1 col\\n #sys.stderr.write(\\\"if block ...\\\\n\\\")\\n b=tmp=list( D[:-1] )\\n tmp.insert(0,1)\\n \\n tmp =np.cumprod ( np.array (tmp) )\\n tmp=(np.array(np.matrix(tmp)))\\n #print \\\"tmp: \\\", tmp\\n \\n a_flat=np.array ( np.matrix( A.flatten(0) ).transpose() )\\n #print \\\"a flat: \\\", a_flat\\n I= ( tmp * (a_flat-1) ) + 1\\n return I\\n \\n\\n else:\\n #sys.stderr.write(\\\"else block ...\\\\n\\\")\\n b=tmp=list( D[:-1] )\\n tmp.insert(0,1)\\n tmp =np.cumprod ( np.array (tmp) )\\n tmp = np.tile( tmp, (nrowA,1) )\\n #print tmp\\n #print (A-1)\\n I= np.sum( np.multiply(tmp, (A-1)), 1) + 1\\n\\n \\n return np.array( np.matrix( I ).transpose() )\\n\\n\\ndef SetValueOfAssignment( F, A, v, Vorder=None):\\n \\\"\\\"\\\" % SetValueOfAssignment Sets the value of a variable assignment in a factor.\\n%\\n% F = SetValueOfAssignment(F, A, v) sets the value of a variable assignment,\\n% A, in factor F to v. The order of the variables in A are assumed to be the\\n% same as the order in F.var.\\n%\\n% F = SetValueOfAssignment(F, A, v, VO) sets the value of a variable\\n% assignment, A, in factor F to v. The order of the variables in A are given\\n% by the vector VO. See https://github.com/indapa/PGM/blob/master/Prog1/SetValueOfAssignment.m \\\"\\\"\\\"\\n\\n \\n\\n if Vorder == None:\\n indx=AssignmentToIndex( A, F.getCard() )\\n else:\\n sys.stderr.write(\\\"assumes the order of variables in A are the sayme as in F.var ...\\\\n\\\")\\n pass\\n\\n #http://stackoverflow.com/a/5183720, How to make List from Numpy Matrix in Python\\n #http://stackoverflow.com/a/8373103, numpy function to set elements of array to a value given a list of indices\\n indices=np.array(indx-1).flatten().tolist()\\n zeros=np.zeros(len(A))\\n zeros[indices]=v\\n F.setVal( zeros.tolist() )\\n\\ndef GetValueOfAssignment( F, A, Vorder = None ):\\n \\\"\\\"\\\" % GetValueOfAssignment Gets the value of a variable assignment in a factor.\\n%\\n% v = GetValueOfAssignment(F, A) returns the value of a variable assignment,\\n% A, in factor F. The order of the variables in A are assumed to be the\\n% same as the order in F.var.\\n%\\n% v = GetValueOfAssignment(F, A, VO) gets the value of a variable assignment,\\n% A, in factor F. The order of the variables in A are given by the vector VO. See https://github.com/indapa/PGM/blob/master/Prog1/GetValueOfAssignment.m \\\"\\\"\\\"\\n\\n if Vorder == None:\\n indx= AssignmentToIndex ( A, F.getCard() )\\n else:\\n sys.stderr.write(\\\"The order of the variables in A are assumed to be the same as the order in F var\\\\n\\\")\\n pass\\n #pdb.set_trace()\\n indices=np.array(indx-1).flatten().tolist()\\n return np.array ( np.matrix ( F.getVal()[indices] ))\\n\\ndef FactorProduct ( A, B):\\n \\\"\\\"\\\" FactorProduct Computes the product of two factors.\\n% C = FactorProduct(A,B) computes the product between two factors, A and B,\\n% where each factor is defined over a set of variables with given dimension.\\n% The factor data structure has the following fields:\\n% .var Vector of variables in the factor, e.g. [1 2 3]\\n% .card Vector of cardinalities corresponding to .var, e.g. [2 2 2]\\n% .val Value table of size prod(.card)\\n%\\n% See also FactorMarginalization IndexToAssignment,\\n% AssignmentToIndex, and https://github.com/indapa/PGM/blob/master/Prog1/FactorProduct.m \\\"\\\"\\\"\\n\\n #print \\\"A: \\\", A\\n #print \\\"====\\\"\\n #print \\\"B: \\\", B\\n C=Factor()\\n\\n #check for empty factors\\n if len( A.getVar() ) == 0 :\\n sys.stderr.write(\\\"A factor is empty!\\\\n\\\")\\n return B\\n if len( B.getVar() ) == 0:\\n sys.stderr.write(\\\"B factor is empty!\\\\n\\\")\\n return A\\n\\n\\n #check of variables that in both A and B have the same cardinality\\n #print 'A.getVar(): ', A.getVar()\\n #print 'B.getVar(): ',B.getVar()\\n #setA= set( A.getVar() )\\n #setB= set( B.getVar() )\\n #intersect=np.array( list( setA.intersection(setB)))\\n intersect=np.intersect1d( A.getVar(), B.getVar() ).tolist()\\n #print \\\"Intersection of variables in FactorProduct \\\", intersect\\n #print \\\"A var: \\\", A.getVar()\\n #print \\\"B var: \\\", B.getVar()\\n\\n #if the intersection of variables in the two factors\\n #is non-zero, then make sure they have the same cardinality\\n if len(intersect) > 0:\\n #iA=np.nonzero(intersect - A.getVar()==0)[0].tolist() # see this http://stackoverflow.com/a/432146, return the index of something in an array?\\n iA=getIndex( A.getVar(), intersect )\\n #print \\\"iA: \\\", iA\\n #iB=np.nonzero(intersect - B.getVar()==0)[0].tolist()\\n iB = getIndex ( B.getVar(), intersect )\\n #print \\\"iB: \\\", iB\\n\\n # check to see if any of the comparisons in the array resulting from of a.getCard()[iA] == b.getCard()[iB] \\n # are all False. If so print an error and exit\\n if len( np.where( A.getCard()[iA].all() == B.getCard()[iB].all() ==False)[0].tolist() ) > 0:\\n sys.stderr.write(\\\"dimensionality mismatch in factors!\\\\n\\\")\\n sys.exit(1)\\n\\n #now set the variables of C to the union of variables in factors A and B\\n #print 'setA ' ,setA\\n #print 'setB ', setB\\n #print list( setA.union(setB) )\\n C.setVar( np.union1d ( A.getVar(), B.getVar() ).tolist() )\\n #C.setVar ( list( setA.union(setB) ) )\\n mapA=isMember(A.getVar(), C.getVar() )\\n mapB=isMember(B.getVar(), C.getVar() )\\n\\n \\n\\n #Set the cardinality of variables in C\\n C.setCard( np.zeros( len(C.getVar())).tolist() )\\n C.getCard()[mapA]=A.getCard()\\n C.getCard()[mapB]=B.getCard()\\n\\n #intitialize the values of the factor C to be zero\\n C.setVal( np.zeros(np.prod(C.getCard())).tolist() )\\n\\n #some helper indices to tell what indices of A and B values to multiply\\n assignments=IndexToAssignment( np.arange(np.prod(C.getCard())), C.getCard() ) #get the assignment of values of C\\n indxA=AssignmentToIndex( assignments[:,mapA], A.getCard())-1 # re-arrange the assignment of C, to what it would be in factor A\\n indxB=AssignmentToIndex( assignments[:,mapB], B.getCard())-1 # re-arange the assignment of C to what it would be in factorB\\n\\n \\n\\n c_val=A.getVal()[indxA.flatten().tolist()] * B.getVal()[indxB.flatten().tolist()] #now that we have the index into A.val and B.val vector, multiply them to factor product\\n C.setVal ( c_val.tolist() )\\n\\n return C\\n\\ndef FactorMarginalization(A,V):\\n \\\"\\\"\\\" FactorMarginalization Sums given variables out of a factor.\\n B = FactorMarginalization(A,V) computes the factor with the variables\\n in V summed out. The factor data structure has the following fields:\\n .var Vector of variables in the factor, e.g. [1 2 3]\\n .card Vector of cardinalities corresponding to .var, e.g. [2 2 2]\\n .val Value table of size prod(.card)\\n\\n The resultant factor should have at least one variable remaining or this\\n function will throw an error. See also FactorProduct, IndexToAssignment , and AssignmentToIndex\\n Based on matlab code found here: https://github.com/indapa/PGM/blob/master/Prog1/FactorMarginalization.m \\\"\\\"\\\"\\n\\n #the resulting factor after marginalizing out variables in python list V that are in \\n #the factor A\\n B=Factor()\\n\\n #check for empy factor or variable list\\n if len( A.getVar() ) == 0 or len(V) == 0:\\n return A\\n\\n #construct the variables of the marginalized factor by \\n #computing the set difference between A.var and V\\n #These variables in the difference set will be the scope of the new factor\\n setA=set( A.getVar() )\\n setV=set(V)\\n Bvar=np.array( list( setA.difference(setV)))\\n mapB=isMember(Bvar, A.getVar()) #indices of the variables of the new factor in the original factor A\\n #print mapB, Bvar\\n\\n #check to see if the new factor has empty scope\\n if len(Bvar) == 0:\\n sys.stderr.write(\\\"FactorMarginalization:Error, resultant factor has empty scope...\\\\n\\\")\\n return None\\n #set the marginalized factor's variable scope and cardinality\\n B.setVar( Bvar.tolist() )\\n B.setCard( A.getCard()[mapB] )\\n B.setVal( np.zeros(np.prod(B.getCard())).tolist() )\\n\\n #compute some helper indices\\n assignments=IndexToAssignment ( np.arange(np.prod(A.getCard()) ), A.getCard() )\\n #indxB tells which values in A to sum together when marginalizing out the variable(s) in B\\n indxB=AssignmentToIndex( assignments[:,mapB], B.getCard())-1\\n\\n #accum is a numpy implementation of matlab accumarray\\n #accumarray sums data in each group\\n #here the group(s) are defined in indxB\\n #indxB is a map to tell which value in A.val to map the sum to\\n #see http://blogs.mathworks.com/loren/2008/02/20/under-appreciated-accumarray/\\n marginal_vals=accum(indxB, A.getVal() )\\n \\n #set the marginal values to the new factor with teh variable(s) in V summed(marginalized) out\\n B.setVal( marginal_vals.tolist() )\\n return B\\n\\n\\n\\ndef ObserveEvidence (INPUTS, EVIDENCE):\\n\\n \\\"\\\"\\\" ObserveEvidence Modify a vector of factors given some evidence.\\n F = ObserveEvidence(INPUTS, EVIDENCE) sets all entries in the vector of factors,INPUTS,\\n that are not consistent with the evidence, E, to zero. F is a vector of\\n factors, each a data structure with the following fields:\\n .var Vector of variables in the factor, e.g. [1 2 3]\\n .card Vector of cardinalities corresponding to .var, e.g. [2 2 2]\\n .val Value table of size prod(.card)\\n EVIDENCE is an N-by-2 matrix, where each row consists of a variable/value pair.\\n Variables are in the first column and values are in the second column. \\\"\\\"\\\"\\n (nrows, ncols)=np.shape(EVIDENCE)\\n #total_factors=len(INPUTS)\\n #iterate through evidence\\n for i in range(nrows):\\n variable=EVIDENCE[i,0]\\n value=EVIDENCE[i,1]\\n #print 'var: ', variable, 'value: ', value\\n if int(value) == 0:\\n print \\\"Evidence is not set for variable: ', variable, ' in evidence matrix.\\\\n\\\"\\n continue\\n\\n for factor in INPUTS:\\n #the following returns a list\\n indx=np.where( factor.getVar() == variable )[0].tolist()\\n if indx: #if the indx is not empty, it contains the index value of the evidence variable in factor.val array\\n indx=indx[0]\\n \\n if value > factor.getCard()[indx] or value < 0:\\n sys.stderr.write(\\\"invalid evidene for variable X_'\\\" + str(variable) + \\\" = \\\" + str(value) + \\\"\\\\n\\\")\\n sys.exit(1)\\n\\n #get the assignments of variables for the factor\\n assignments=IndexToAssignment( np.arange(np.prod( factor.getCard() )), factor.getCard() )\\n # now get the indices in the assignments that don't agree with the observed value (evidence)\\n mask=np.where( assignments[:,indx] != value )[0].tolist()\\n #we are going to update the val array for the current factor\\n newvals=factor.getVal()\\n #set the mask indices to zero and reset the val array of the factor\\n newvals[mask]=0\\n factor.setVal( newvals.tolist() )\\n\\n #now check to see the validity of the updated values of the factor\\n #given the observed evidence. We cannot have all zero values for the factor!\\n zeroIndices=np.where ( factor.getVal() == 0)[0].tolist()\\n if len(zeroIndices) == len (factor.getVal() ):\\n sys.stderr.write(\\\"All variable values are zero, which is not possible.\\\\n\\\")\\n return INPUTS\\n\\ndef ComputeJointDistribution(INPUTS):\\n \\\"\\\"\\\" ComputeJointDistribution Computes the joint distribution defined by a set of given factors\\n\\n Joint = ComputeJointDistribution(INPUTS) computes the joint distribution\\n defined by a set of given factors\\n\\n Joint is a factor that encapsulates the joint distribution given by INPUTS\\n INPUTS is a vector of Factor objects containing the factors defining the distribution\\n\\n \\\"\\\"\\\"\\n\\n totalFactors = len(INPUTS)\\n #check for empty list of INPUTS\\n\\n if totalFactors== 0:\\n sys.stderr.write(\\\"Empty factor list given as input\\\\n\\\")\\n return Factor( [], [], [] )\\n \\n else:\\n # see http://docs.python.org/library/functions.html#reduce for description of Python reduce function\\n return reduce(lambda x, y: FactorProduct(x,y), INPUTS)\\n\\n\\ndef ComputeMarginal(V, F, E):\\n \\\"\\\"\\\"\\n ComputeMarginal Computes the marginal over a set of given variables\\n M = ComputeMarginal(V, F, E) computes the marginal over variables V\\n in the distribution induced by the set of factors F, given evidence E\\n\\n M is a factor containing the marginal over variables V\\n\\n V is a vector containing the variables in the marginal e.g. [1 2 3] for X_1, X_2 and X_3.\\n i.e. a result of FactorMarginalization\\n\\n F is a vector of factors (struct array) containing the factors\\n defining the distribution\\n\\n E is an N-by-2 matrix, each row being a variable/value pair.\\n Variables are in the first column and values are in the second column.\\n If there is no evidence, pass in the empty matrix [] for E.\\n\\n \\\"\\\"\\\"\\n totalFactors=len(F)\\n #reshape a 1d array to 1 x ncol array\\n #since ObserveEvidence requires Nx2 array, we reshape to a 2 column array\\n #see http://stackoverflow.com/a/12576163 for reshaping 1d array to 2d array\\n EVIDENCE= np.reshape( np.array ( E ), (-1,2) )\\n #print np.shape(EVIDENCE)\\n \\n if totalFactors == 0:\\n sys.stderr.write(\\\"empty factor list given as input.\\\\n\\\")\\n return Factor( [], [], [])\\n # union of all variables in list of factors F\\n variableList=[] # a list of of lists, where each element is a list containing the variables of the factor in F\\n for factor in F:\\n var=factor.getVar().tolist()\\n variableList.append( var )\\n\\n #get the union of variables across all the factor in F\\n #see this http://stackoverflow.com/a/2151553, Pythonic Way to Create Union of All Values Contained in Multiple Lists\\n union_variables = set().union(*variableList)\\n #print union_variables\\n #v contains the variables not in the list of variables in the marginal\\n v=list( union_variables.difference(V) )\\n \\n # compute the joint distribution, but then reduce it, given the evidence\\n # ComputeJointDistribution returns a factor, but ObserveEvidence expects a list\\n # of factors as the first argument, so hence the need for brackets [ ]\\n # ObserveEvidence returns a list, but we want the first element so thats why the [0]\\n jointE= ObserveEvidence ( [ComputeJointDistribution ( F )], EVIDENCE )[0]\\n\\n #now we need to re-normaize the joint, since observe evidence doesn't do it for us\\n jointE_normalizedVal = jointE.getVal()/np.sum( jointE.getVal() )\\n jointE.setVal( jointE_normalizedVal.tolist() )\\n\\n return FactorMarginalization ( jointE, v)\\n \\n\\ndef IdentityFactor( F ):\\n return Factor ( F.getVar().tolist(), F.getCard().tolist(), np.ones( np.prod( F.getCard() ) ), F.getName()+ '_identity' )\\n\\n\\n\\ndef SumProductEliminateVar(z, factorList):\\n\\n \\\"\\\"\\\" this is a non-graph based sum-product variable elimination function\\n z is a variable to eliminate\\n pass in a list of factors\\n\\n 1. figure out which factor contain z in their variable scope\\n 2. figure out which factors don't contain z in their scope\\n 3. mulitply in all factors that have z\\n 4. sum out z (marginalize) and return new factor with variable z eliminated\\\"\\\"\\\"\\n\\n useFactors = []# list of factors that contains the variable Z\\n unusedFactors=[] #list of factors that don't contain variable Z\\n scope = []\\n\\n \\\"\\\"\\\"get a list containining the index in self.factorLlist of factors\\n that contain the variable Z to be eliminated\\n get the scope of variables from the factors that contain variable Z \\\"\\\"\\\"\\n for fi in factorList:\\n if z in fi.getVar().tolist():\\n useFactors.append(fi)#the ith factor is being currently involved in elimination\\n scope=list(set.union(set(scope), fi.getVar().tolist() ))\\n else:\\n unusedFactors.append( fi )\\n\\n #for f in useFactors:\\n # print 'useFactor: ', f\\n #print '==='\\n #for f in unusedFactors:\\n # print 'unusedFactor: ', f\\n\\n psiFactor= ComputeJointDistribution ( useFactors )\\n tauFactor=FactorMarginalization( psiFactor,[z] )\\n\\n #print 'psiFactor: ', psiFactor\\n #print 'tauFactor: ', tauFactor\\n return unusedFactors + [ tauFactor ]\\n\\ndef SumProductVE ( Z, F ):\\n\\n \\\"\\\"\\\" A wrapper function for SumProductEliminateVar\\n sum-product variable elimination based on pseudocode algorithm 9.1 in Koller and Friedman\\n We are giving a list of variables to eliminate in Z (in the order we want to\\n elimiinate them) and a list of factors F\\n eliminate each one getting getting the marginal distribution of the last variable in the list\\n Z. \\\"\\\"\\\"\\n\\n for z in Z:\\n F=SumProductEliminateVar(z, F)\\n return reduce(lambda x, y: FactorProduct(x,y), F)\\n\\n\\ndef FactorMaxMarginalization( A, V ):\\n \\\"\\\"\\\" computes the factor with the variables in V *maxed* out.\\n The resulting factor will have all the variables in A minus\\n those variables in V. This is quite similiar to FactorMarginalization, but rather then summing out variables in V\\n we take the max. In the code, this translates passing np.max as the function to accum\\n See section 13.2 in Koller and Friedman for more information\\\"\\\"\\\"\\n\\n B=Factor()\\n #check for empy factor or variable list\\n if len( A.getVar() ) == 0 or len(V) == 0:\\n return A\\n Bvar=np.setdiff1d( A.getVar(), V)\\n mapB=isMember(Bvar, A.getVar())\\n\\n if len(Bvar) == 0:\\n sys.stderr.write(\\\"FactorMaxMarginalization: Error, resultant factor has empty scope...\\\\n\\\")\\n return np.max (A.getVal() )\\n #set the marginalized factor's variable scope and cardinality\\n B.setVar( Bvar.tolist() )\\n B.setCard( A.getCard()[mapB] )\\n B.setVal( np.zeros(np.prod(B.getCard())).tolist() )\\n\\n #compute some helper indices\\n assignments=IndexToAssignment ( np.arange(np.prod(A.getCard()) ), A.getCard() )\\n #indxB tells which values in A to sum together when marginalizing out the variable(s) in B\\n indxB=AssignmentToIndex( assignments[:,mapB], B.getCard())-1\\n\\n #here we pass in the function np.max\\n #NumPy and Python are awesome\\n max_vals=accum(indxB, A.getVal(), np.max )\\n B.setVal( max_vals.tolist() )\\n\\n return B\\n\\n\\ndef MaxProductEliminateVar(z, factorList):\\n\\n \\\"\\\"\\\" this is a non-graph based MAX-product variable elimination function\\n z is a variable to eliminate\\n pass in a list of factors\\n\\n 1. figure out which factor contain z in their variable scope\\n 2. figure out which factors don't contain z in their scope\\n 3. mulitply in all factors that have z\\n 4. max marginalize out z and return new factor with variable z eliminated\\\"\\\"\\\"\\n\\n useFactors = []# list of factors that contains the variable Z\\n unusedFactors=[] #list of factors that don't contain variable Z\\n scope = []\\n\\n \\\"\\\"\\\"get a list containining the index in self.factorLlist of factors\\n that contain the variable Z to be eliminated\\n get the scope of variables from the factors that contain variable Z \\\"\\\"\\\"\\n for fi in factorList:\\n if z in fi.getVar().tolist():\\n useFactors.append(fi)#the ith factor is being currently involved in elimination\\n scope=list(set.union(set(scope), fi.getVar().tolist() ))\\n else:\\n unusedFactors.append( fi )\\n\\n \\n \\\"\\\"\\\" psiFactor is an intermediate factor, prior to max-marginalization \\\"\\\"\\\"\\n psiFactor= ComputeJointDistribution ( useFactors )\\n tauFactor=FactorMaxMarginalization( psiFactor,[z] )\\n\\n \\n \\\"\\\"\\\" we return tuple consisting of\\n 1. a list factors that are unused, plus the result of max-marginal\\n such that the variable z is not eliminated from the list of factors remaining.\\n 2. For traceback, we return the intermediate factor generated in the process of eliminating\\n variable z. \\\"\\\"\\\"\\n return unusedFactors + [ tauFactor ], psiFactor\\n\\ndef TracebackMAP(FI, Z):\\n \\\"\\\"\\\"We are back-tracing to the most probable assingments here ...\\n See psuedo-code in Koller and Friedman page 557\\n\\n In order to return the most probable assignment from MaxProductVE\\n we take in a list of intermediate factors, FI, that were generated in the process\\n of MaxProductVE. Z is the same elimination ordering used as MaxProductVE.\\n We traceback our steps by iterating in reverse order the elimination ordering Z.\\n\\n Following arguments section 13.2.2 page 558 in Koller and Friedman, as one eliminates\\n variables you cannot determine their maximizing value. But you can compute their 'conditional'\\n maximizing value - their max value given the other variables not eliminate yet. Once\\n the last variable is eliminated, we can traceback to get the maximzing value of the remaining\\n variables. Hence the reason for iterating thru the elimination ordering Z in reverse order\\n \\n Returns a python dictionary with key: variable value: variable assignment in the MAP\\\"\\\"\\\"\\n\\n z_i=Z[-1]\\n f_i=FI[-1]\\n Z=Z[:-1]\\n FI=FI[:-1]\\n\\n #print 'z_i:', z_i\\n #print 'f_i:', f_i\\n\\n values=f_i.getVal().tolist()\\n fidx= IndexToAssignment( np.arange( np.prod( f_i.getCard() ) ), f_i.getCard() )\\n maxidx=values.index(max(values))\\n \\n\\n maxed_vars={} #key variable, value: max assignment value\\n\\n #print 'variable: ', z_i\\n #print 'max value: ', fidx.flatten()[maxidx]\\n maxed_vars[z_i]=int(fidx.flatten()[maxidx])\\n #print maxed_vars\\n #print\\n for (z, f) in itertools.izip( reversed(Z), reversed(FI) ):\\n #print z\\n #print f\\n #print 'setdiff: ', np.setdiff1d( f_i.getVar(), [z]).tolist()\\n \\n variables=np.setdiff1d( f_i.getVar(), [z]).tolist()\\n evidence=[ [v, maxed_vars[v] ] for v in variables]\\n #print 'Evidence: ',evidence\\n f=ObserveEvidence( [f], np.matrix(evidence) )[0]\\n #print f\\n values=f.getVal().tolist()\\n fidx= IndexToAssignment( np.arange( np.prod( f.getCard() ) ), f.getCard() )\\n #print fidx\\n #print max(values)\\n maxidx=values.index(max(values))\\n\\n maxed_vars[z]=int(fidx.flatten()[maxidx])\\n #print 'variable: ', z\\n #print 'max value: ', fidx.flatten()[maxidx]\\n \\n #print\\n #print maxed_vars\\n return maxed_vars\\n\\n\\n\\ndef MaxDecoding ( F ):\\n \\\"\\\"\\\" F is a list of max marginal factors passed in. The factors have a variable scope over a single variable only\\n So no backtracing is inovlved, we just get the index of the highest number in the value array.\\n The code here is based on https://github.com/indapa/PGM/blob/master/Prog4/MaxDecoding.m \\\"\\\"\\\"\\n ASSIGNMENTS=[]\\n for f in F:\\n values=f.getVal().tolist()\\n ASSIGNMENTS.append ( values.index( max(values) ) )\\n return ASSIGNMENTS\\n \\ndef MaxDecodingNonUniq ( F ):\\n \\\"\\\"\\\" F is a list of max marginal factors passed in. We don't assume that there is a unique\\n max value. So we get the indices of the non-uniq max value as a tuple and add it to \\\"\\\"\\\"\\n ASSIGNMENTS=[]\\n for f in F:\\n values=f.getVal().tolist()\\n maxvalue=max(values)\\n \\\"\\\"\\\" if the maxvalue is duplicated, we get the indices of where it resides in the value array \\\"\\\"\\\"\\n if common.isMaxDuplicated(values):\\n dup_indices_list=[dup for dup in sorted(common.list_duplicates(values)) ]\\n dup_values= [ x for (x, y) in dup_indices_list ]\\n dup_indices= [ y for (x, y) in dup_indices_list ]\\n non_uniq_max_indices=tuple(dup_indices [ dup_values.index(maxvalue) ])\\n ASSIGNMENTS.append ( non_uniq_max_indices )\\n else:\\n ASSIGNMENTS.append( values.index(maxvalue))\\n return ASSIGNMENTS\\n\\n\\ndef posterior_genotypes_values(factorList, ALPHABET,samplenames,bedstring,fh):\\n \\\"\\\"\\\" given the factorlist of posterior marginals, the genotype alphabet, samplenames,bedstring position,\\n and prettybase file handle, print to file the posterior marginals for all 10 possibel genotypes\\n for each sample. \\\"\\\"\\\"\\n genotype_factors=factorList[0:len(samplenames)]\\n sample_factorObj_zip=zip(samplenames, genotype_factors)\\n #print bedstring\\n for sample, f in sample_factorObj_zip:\\n #print sample, \\\": \\\"\\n #values=f.getVal().tolist()\\n \\n #prob_val_normalized=( lognormalize( f.getVal() ) )\\n prob_val_normalized=f.getVal()/np.sum(f.getVal())\\n #print sample\\n #val=f.getVal()\\n #print np.sum(val)\\n #print val/np.sum(val)\\n #pdb.set_trace()\\n #print prob_val_normalized.tolist()\\n #genotype_probZip=zip(ALPHABET,values)\\n posteriors=[]\\n #print prob_val_normalized.tolist()\\n for posterior_val in prob_val_normalized.tolist():\\n #for posterior_val in values:\\n posteriors.append(str(posterior_val))\\n #posteriors.append(str(round(posterior_val,5) ))\\n #print posteriors\\n gstring=\\\"\\\\t\\\".join(posteriors)\\n #print gstring\\n outstring=\\\"\\\\t\\\".join([bedstring, sample,gstring])\\n \\n fh.write(outstring + \\\"\\\\n\\\")\\n \\n\\n \\ndef MaxProductVE ( Z, F ):\\n\\n \\\"\\\"\\\" A wrapper function for MaxProductEliminateVar\\n sum-product variable elimination based on pseudocode algorithm 9.1 in Koller and Friedman\\n We are giving a list of variables to eliminate in Z (in the order we want to\\n elimiinate them) and a list of factors F\\n eliminate each one getting getting the marginal distribution of the last variable in the list\\n Z.\\n\\n Returns the probabliity of the MAP configuration as well as the variable assignments of the MAP configuration\\\"\\\"\\\"\\n intermediateMaxFactors=[]\\n for z in Z:\\n (F, intermediateFactor)=MaxProductEliminateVar(z, F)\\n intermediateMaxFactors.append ( intermediateFactor )\\n \\n #intermediateMaxFactors.append ( intermediateFactor )\\n \\n #MaxDecodingBT( intermediateMaxFactors, Z )\\n bt_results=TracebackMAP( intermediateMaxFactors, Z )\\n return (reduce(lambda x, y: FactorProduct(x,y), F), bt_results)\\n\\n\\ndef FactorSum ( A, B):\\n \\\"\\\"\\\" FactorSum Computes the sum of two factors.\\n% Similiar to FactorProduct\\n We would use this in log space where multiplication becomes addition\\n% Based on the code here https://github.com/indapa/PGM/blob/master/Prog4/FactorSum.m \\\"\\\"\\\"\\n\\n\\n C=Factor()\\n\\n #check for empty factors\\n if len( A.getVar() ) == 0 :\\n sys.stderr.write(\\\"A factor is empty!\\\\n\\\")\\n return B\\n if len( B.getVar() ) == 0:\\n sys.stderr.write(\\\"B factor is empty!\\\\n\\\")\\n return A\\n\\n\\n #check of variables that in both A and B have the same cardinality\\n #print 'A.getVar(): ', A.getVar()\\n #print 'B.getVar(): ',B.getVar()\\n #setA= set( A.getVar() )\\n #setB= set( B.getVar() )\\n #intersect=np.array( list( setA.intersection(setB)))\\n intersect=np.intersect1d( A.getVar(), B.getVar() ).tolist()\\n #print \\\"Intersection of variables in FactorProduct \\\", intersect\\n #print \\\"A var: \\\", A.getVar()\\n #print \\\"B var: \\\", B.getVar()\\n\\n #if the intersection of variables in the two factors\\n #is non-zero, then make sure they have the same cardinality\\n if len(intersect) > 0:\\n #iA=np.nonzero(intersect - A.getVar()==0)[0].tolist() # see this http://stackoverflow.com/a/432146, return the index of something in an array?\\n iA=getIndex( A.getVar(), intersect )\\n #print \\\"iA: \\\", iA\\n #iB=np.nonzero(intersect - B.getVar()==0)[0].tolist()\\n iB = getIndex ( B.getVar(), intersect )\\n #print \\\"iB: \\\", iB\\n\\n # check to see if any of the comparisons in the array resulting from of a.getCard()[iA] == b.getCard()[iB]\\n # are all False. If so print an error and exit\\n if len( np.where( A.getCard()[iA].all() == B.getCard()[iB].all() ==False)[0].tolist() ) > 0:\\n sys.stderr.write(\\\"dimensionality mismatch in factors!\\\\n\\\")\\n sys.exit(1)\\n\\n #now set the variables of C to the union of variables in factors A and B\\n #print 'setA ' ,setA\\n #print 'setB ', setB\\n #print list( setA.union(setB) )\\n C.setVar( np.union1d ( A.getVar(), B.getVar() ).tolist() )\\n #C.setVar ( list( setA.union(setB) ) )\\n mapA=isMember(A.getVar(), C.getVar() )\\n mapB=isMember(B.getVar(), C.getVar() )\\n\\n\\n\\n #Set the cardinality of variables in C\\n C.setCard( np.zeros( len(C.getVar())).tolist() )\\n C.getCard()[mapA]=A.getCard()\\n C.getCard()[mapB]=B.getCard()\\n\\n #intitialize the values of the factor C to be zero\\n C.setVal( np.zeros(np.prod(C.getCard())).tolist() )\\n\\n #some helper indices to tell what indices of A and B values to multiply\\n assignments=IndexToAssignment( np.arange(np.prod(C.getCard())), C.getCard() ) #get the assignment of values of C\\n indxA=AssignmentToIndex( assignments[:,mapA], A.getCard())-1 # re-arrange the assignment of C, to what it would be in factor A\\n indxB=AssignmentToIndex( assignments[:,mapB], B.getCard())-1 # re-arange the assignment of C to what it would be in factorB\\n #print 'indxA ', indxA\\n #print 'indxB ', indxB\\n\\n\\n c_val=A.getVal()[indxA.flatten().tolist()] + B.getVal()[indxB.flatten().tolist()] #now that we have the index into A.val and B.val vector, multiply them to factor product\\n C.setVal ( c_val.tolist() )\\n\\n return C\\n\\n\\ndef LogFactor( F ):\\n \\\"\\\"\\\" return a factor whose values are the natural log of the orginal factor F \\\"\\\"\\\"\\n \\n return Factor ( F.getVar().tolist(), F.getCard().tolist(), np.log ( F.getVal() ).tolist(), F.getName() )\\n\\n\\ndef ExpFactorNormalize ( logF ):\\n \\\"\\\"\\\" exponentiate a factor to probablity space from log space\\n Since moving from log space to probablity space incures a decrease in dynamic range,\\n factors should be normalized before applying the transform. One trick we use here is\\n to shift every entry by the maximum entry. For example: phi[i] = exp{logPhi[i] -c}\\n The value of c is max(logPhi). This type of transformation ensures the resulting factor\\n has a maximum entry of 1 and prevents overflow. See page 360 of Koller and Friedman text\\\"\\\"\\\"\\n logPhi=logF.getVal()\\n #phi=lognormalize( logPhi )\\n phi=np.exp(logPhi-np.max(logPhi) )\\n logF.setVal( phi )\\n return logF\\n\\ndef ExpFactor( logF ):\\n \\\"\\\"\\\" similiar to above, but don't normalize \\\"\\\"\\\"\\n logPhi=logF.getVal()\\n phi=np.exp( logPhi )\\n logF.setVal( phi )\\n return logF\\n\\n\\n\\n\\n\\n\\ndef FactorDiv ( A, B):\\n \\\"\\\"\\\" FactorProduct Computes the dividend of two factors.\\n% Similiar to Factor Product, but if we divide 0/0, return 0\\n see page 365 in Koller and Friedman for definition of FactorDivision \\\"\\\"\\\"\\n\\n #print \\\"A: \\\", A\\n #print \\\"====\\\"\\n #print \\\"B: \\\", B\\n C=Factor()\\n\\n #check for empty factors\\n if len( A.getVar() ) == 0 :\\n sys.stderr.write(\\\"A factor is empty!\\\\n\\\")\\n return B\\n if len( B.getVar() ) == 0:\\n sys.stderr.write(\\\"B factor is empty!\\\\n\\\")\\n return A\\n\\n\\n #check of variables that in both A and B have the same cardinality\\n #print 'A.getVar(): ', A.getVar()\\n #print 'B.getVar(): ',B.getVar()\\n #setA= set( A.getVar() )\\n #setB= set( B.getVar() )\\n #intersect=np.array( list( setA.intersection(setB)))\\n intersect=np.intersect1d( A.getVar(), B.getVar() ).tolist()\\n #print \\\"Intersection of variables in FactorProduct \\\", intersect\\n #print \\\"A var: \\\", A.getVar()\\n #print \\\"B var: \\\", B.getVar()\\n\\n #if the intersection of variables in the two factors\\n #is non-zero, then make sure they have the same cardinality\\n if len(intersect) > 0:\\n #iA=np.nonzero(intersect - A.getVar()==0)[0].tolist() # see this http://stackoverflow.com/a/432146, return the index of something in an array?\\n iA=getIndex( A.getVar(), intersect )\\n #print \\\"iA: \\\", iA\\n #iB=np.nonzero(intersect - B.getVar()==0)[0].tolist()\\n iB = getIndex ( B.getVar(), intersect )\\n #print \\\"iB: \\\", iB\\n\\n # check to see if any of the comparisons in the array resulting from of a.getCard()[iA] == b.getCard()[iB] \\n # are all False. If so print an error and exit\\n if len( np.where( A.getCard()[iA].all() == B.getCard()[iB].all() ==False)[0].tolist() ) > 0:\\n sys.stderr.write(\\\"dimensionality mismatch in factors!\\\\n\\\")\\n sys.exit(1)\\n\\n #now set the variables of C to the union of variables in factors A and B\\n #print 'setA ' ,setA\\n #print 'setB ', setB\\n #print list( setA.union(setB) )\\n C.setVar( np.union1d ( A.getVar(), B.getVar() ).tolist() )\\n #C.setVar ( list( setA.union(setB) ) )\\n mapA=isMember(A.getVar(), C.getVar() )\\n mapB=isMember(B.getVar(), C.getVar() )\\n\\n \\n\\n #Set the cardinality of variables in C\\n C.setCard( np.zeros( len(C.getVar())).tolist() )\\n C.getCard()[mapA]=A.getCard()\\n C.getCard()[mapB]=B.getCard()\\n\\n #intitialize the values of the factor C to be zero\\n C.setVal( np.zeros(np.prod(C.getCard())).tolist() )\\n\\n #some helper indices to tell what indices of A and B values to multiply\\n assignments=IndexToAssignment( np.arange(np.prod(C.getCard())), C.getCard() ) #get the assignment of values of C\\n indxA=AssignmentToIndex( assignments[:,mapA], A.getCard())-1 # re-arrange the assignment of C, to what it would be in factor A\\n indxB=AssignmentToIndex( assignments[:,mapB], B.getCard())-1 # re-arange the assignment of C to what it would be in factorB\\n \\n numerator=A.getVal()[indxA.flatten().tolist()]\\n denominator=B.getVal()[indxB.flatten().tolist()]\\n \\n #print numerator\\n #print denominator\\n #print zip(numerator, denominator)\\n val= map( lambda x: common.zerodiv_tuple(x), zip(numerator,denominator) )\\n #print val\\n C.setVal ( val )\\n \\n return C\\n\\n\\n\\n\\n\\n\\ndef variableStride( f ):\\n \\\"\\\"\\\" given a Factor object f, calculate its variable stride in value array of the factor \\\"\\\"\\\"\\n strides=[]\\n iF=IndexToAssignment ( np.arange(np.prod(f.getCard()) ), f.getCard() )\\n variables=f.getVar()\\n cardinalties=f.getCard()\\n \\n \\n for i in range(0, len(variables) ):\\n #assignment_slice=iF[:,i]\\n #var_card=cardinalties[i]\\n #print variables[i], cardinalties[i]\\n curr_stride=iF[:,i]\\n if cardinalties[i] > 1:\\n stride=np.where(curr_stride==2)\\n else:\\n stride=0\\n strides.append(stride)\\n continue\\n #print variables[i], cardinalties[i], stride[0][0]\\n strides.append( stride[0][0] )\\n #print \\n \\n return strides\\n\\n\\n\\n\\ndef IndexOfAssignment( f, strides, assignment):\\n \\\"\\\"\\\" given a Factor object f and the strides of each of the variables of f and \\n a list of assignments of those variables, return the position in the value array of that assignment\\n see page 358 box 10.a in Friedman and Koller text on how efficiently map a particular variable\\n assignment to the and index in the value array of a factor\\n \\\"\\\"\\\"\\n \\n idx=0\\n \\n #cardinalities=f.getCard()\\n for (ass, stride) in zip( assignment, strides):\\n #print ass, stride\\n idx +=(ass *stride)\\n\\n return idx\\n\\n\\n\\n\\n\\n\"\n }\n]"},"num_files":{"kind":"number","value":17,"string":"17"}}},{"rowIdx":2051,"cells":{"repo_name":{"kind":"string","value":"JulinaM/Deep-Networks-for-Graph-Representation"},"repo_url":{"kind":"string","value":"https://github.com/JulinaM/Deep-Networks-for-Graph-Representation"},"snapshot_id":{"kind":"string","value":"1b698ef96b612d95e48e10051e215d5068c637f2"},"revision_id":{"kind":"string","value":"30430344c198117a8fe79f841d2fe8ac5a12206a"},"directory_id":{"kind":"string","value":"b27f405120762a5f32f3eb10ed739d0298ea5c98"},"branch_name":{"kind":"string","value":"refs/heads/main"},"visit_date":{"kind":"string","value":"2023-03-29T21:48:40.396374"},"revision_date":{"kind":"string","value":"2021-04-07T08:09:47"},"committer_date":{"kind":"string","value":"2021-04-07T08:09:47"},"github_id":{"kind":"null"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.5860384702682495,"alphanum_fraction":0.5926457643508911,"avg_line_length":30.926605224609375,"blob_id":"2a140f398ddbf1ffedc9cb406ee87230e7013aaf","content_id":"bde05c68ab394d7bcd7f82600fa9126232e7cc22","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":3481,"license_type":"no_license","max_line_length":141,"num_lines":109,"path":"/src/autoencoder.py","repo_name":"JulinaM/Deep-Networks-for-Graph-Representation","src_encoding":"UTF-8","text":"import numpy as np\nimport torch\nimport torch.autograd as ag\nimport torch.nn as nn\nimport torch.optim as optim\nfrom torchsummary import summary\nimport torchvision\nimport torchvision.transforms as transforms\nimport torchvision.datasets as datasets\n\nfrom scipy.optimize import minimize, NonlinearConstraint\nimport random\n\nimport matplotlib.pyplot as plt\nfrom sklearn.metrics import mean_squared_error\n\nfrom math import sqrt\nimport time\n\ndef timeit(method):\n def timed(*args, **kw):\n ts = time.time()\n result = method(*args, **kw)\n te = time.time()\n if 'log_time' in kw:\n name = kw.get('log_name', method.__name__.upper())\n kw['log_time'][name] = int((te - ts) * 1000)\n else:\n print('%r %2.2f ms' % \\\n (method.__name__, (te - ts) * 1000))\n return result\n return timed\n\nclass GaussianNoise(nn.Module):\n def __init__(self, stddev):\n super().__init__()\n self.stddev = stddev\n\n def forward(self, din):\n if self.training:\n return din + torch.randn(din.size()) * self.stddev\n return din\n\nclass DropoutNoise(nn.Module):\n def __init__(self, p):\n super().__init__()\n self.p = p\n self.device = torch.device(\"cuda\" if torch.cuda.is_available() else \"cpu\")\n def forward(self, x):\n t = torch.rand(x.size()).to(self.device)\n a = t > self.p\n \n return(x*a)\n\nclass BasicBlock(nn.Module):\n def __init__(self, input_shape, n_neurons, activation='relu', noise=None, noise_arg=None):\n super().__init__()\n self.n_neurons = n_neurons\n self.input_shape = input_shape\n \n self.has_noise = False\n \n if noise=='gaussian':\n self.has_noise = True\n self.noise = GaussianNoise(noise_arg)\n elif noise=='dropout':\n self.has_noise = True\n self.noise = DropoutNoise(noise_arg)\n \n self.dense_layer = nn.Linear(self.input_shape, self.n_neurons)\n \n activations_map = {'relu':nn.ReLU, 'tanh':nn.Tanh, 'sigmoid':nn.Sigmoid}\n self.activation = activations_map[activation]()\n\n def forward(self, features):\n x=features\n \n if self.has_noise:\n x = self.noise(x)\n\n x = self.dense_layer(features)\n x = self.activation(x)\n \n return(x)\n\nclass SDAE(nn.Module):\n def __init__(self, features, input_shape, hidden_layers, activation='relu', last_activation='relu', noise_type='dropout', noise_arg=0.2):\n super().__init__()\n self.features = features\n\n self.inputs = [input_shape] + hidden_layers\n \n n = len(self.inputs)\n encoder_units = [BasicBlock(self.inputs[0], self.inputs[1], activation=activation, noise=noise_type, noise_arg=noise_arg)]\n encoder_units.extend([BasicBlock(self.inputs[i], self.inputs[i+1], activation=activation) for i in range(1, n-1)])\n \n self.encoder = nn.Sequential(*encoder_units)\n \n decoder_units = [BasicBlock(self.inputs[i], self.inputs[i-1], activation=activation) for i in range(n-1,1,-1)]\n decoder_units.append(BasicBlock(self.inputs[1], self.inputs[0], activation=last_activation))\n \n self.decoder = nn.Sequential(*decoder_units)\n \n def forward(self, idx):\n encoded = self.encoder(self.features[idx])\n \n decoded = self.decoder(encoded)\n \n return(decoded)\n\n"},{"alpha_fraction":0.5990557670593262,"alphanum_fraction":0.6121699810028076,"avg_line_length":28.183673858642578,"blob_id":"1e6dbeafe604000312ac7da086d6def3c6682800","content_id":"beb7dc830d76e123e5347a2c87070a78127e9b55","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":5719,"license_type":"no_license","max_line_length":168,"num_lines":196,"path":"/src/dgnr.py","repo_name":"JulinaM/Deep-Networks-for-Graph-Representation","src_encoding":"UTF-8","text":"import numpy as np\nimport torch\nimport torch.autograd as ag\nimport torch.nn as nn\nimport torch.optim as optim\nfrom torchsummary import summary\nimport torchvision\nimport torchvision.transforms as transforms\nimport torchvision.datasets as datasets\n\nfrom scipy.optimize import minimize, NonlinearConstraint\nimport random\n\nimport matplotlib.pyplot as plt\nfrom sklearn.metrics import mean_squared_error\n\nfrom math import sqrt\nimport time\n\nfrom autoencoder import SDAE\nfrom utils import *\nfrom random_graphs import connected_components\n\ndef timeit(method):\n def timed(*args, **kw):\n ts = time.time()\n result = method(*args, **kw)\n te = time.time()\n if 'log_time' in kw:\n name = kw.get('log_name', method.__name__.upper())\n kw['log_time'][name] = int((te - ts) * 1000)\n else:\n print('%r %2.2f ms' % \\\n (method.__name__, (te - ts) * 1000))\n return result\n return timed\n\ndef normalize(M):\n #Put diagonal elements to 0\n M = M - np.diag(np.diag(M))\n \n #Normalizing by row\n D_inv = np.diag(np.reciprocal(np.sum(M,axis=0)))\n M = np.dot(D_inv, M)\n\n return M\n\ndef zero_one_normalisation(matrix, e=1e-5):\n M = np.max(matrix)\n m = np.min(matrix)\n r = (matrix-m) / (M-m + e)\n return(r)\n\ndef PCO(A, K, alpha):\n \"\"\"\n For a graph represented by its adjacency matrix *A*, computes the co-occurence matrix by random \n surfing on the graph with returns. 1-alpha is the probability to make, at each step, a return \n to the original step.\n \"\"\"\n A=np.array(A, dtype=float)\n \n #The adjacency matrix A is first normalized\n A=normalize(A) \n \n n=A.shape[0]\n \n I=np.eye(n)\n \n P=I\n M=np.zeros((n, n))\n \n for i in range(K):\n P = alpha*np.dot(P,A) + (1-alpha)*I\n M = M+P\n \n return(M)\n\ndef PPMI(M):\n \"\"\"Computes the shifted positive pointwise mutual information (PPMI) matrix\n from the co-occurence matrix (PCO) of a graph.\"\"\"\n \n M=normalize(M)\n cols = np.sum(M, axis=0)\n rows = np.sum(M, axis=1).reshape((-1,1))\n s = np.sum(rows)\n \n P = s*M\n P /= cols\n P /= rows\n \n #P[np.where(P<0)] = 1.0\n P = np.log(P)\n\n #To avoid NaN when applying log\n P[np.isnan(P)] = 0.0\n P[np.isinf(P)] = 0.0\n P[np.isneginf(P)] = 0.0\n P[np.where(P<0)] = 0.0\n \n return(P)\n\ndef sdae(input_net, input_number, hidden_layers, n_epochs=100, batch_size=1, activation='sigmoid', last_activation='sigmoid'):\n #hidden_layers=[500,200,100]\n #input_numer=784\n # use gpu if available\n device = torch.device(\"cuda\" if torch.cuda.is_available() else \"cpu\")\n\n normalized_input_net = zero_one_normalisation(input_net)\n tensor_net = torch.Tensor(normalized_input_net).to(device)\n N = tensor_net.size()[0]\n idx = torch.arange(N).long()\n\n model = SDAE(tensor_net, input_number, hidden_layers, activation=activation, last_activation=last_activation).to(device)\n\n # create an optimizer object\n # Adam optimizer with learning rate 1e-3\n optimizer = optim.Adam(model.parameters(), lr=1e-3)\n\n # mean-squared error loss\n criterion = nn.MSELoss()\n\n #summary(model, (input_number,))\n \n train = torch.utils.data.TensorDataset(idx, idx)\n train_loader = torch.utils.data.DataLoader(train, batch_size=batch_size, shuffle=False)\n\n for epoch in range(n_epochs): # loop over the dataset multiple times\n\n running_loss = 0.0\n for i, data in enumerate(train_loader, 0):\n # get the inputs; data is a list of [inputs, labels]\n idx, _ = data\n \n idx=idx.long().to(device)\n inputs=tensor_net[idx]\n\n #inputs=torch.flatten(inputs)\n # zero the parameter gradients\n optimizer.zero_grad()\n\n # forward + backward + optimize\n outputs = model(idx)\n \n loss = criterion(outputs, inputs)\n loss.backward()\n optimizer.step()\n\n # print statistics\n running_loss += loss.item()\n\n print('[%d, %5d] loss: %.5f' %\n (epoch + 1, i + 1, running_loss / input_number))\n\n print('Finished Training')\n \n return(model, train_loader, tensor_net)\n\ndef get_embeddings(train_loader, N, model, size_encoded=100):\n trainiter = iter(train_loader)\n embeddings = np.zeros((N, size_encoded))\n\n for i,q in enumerate(trainiter):\n idx = q[0]\n for j in idx:\n embedded = model.encoder(model.features[j]).cpu().detach().numpy()\n embeddings[j,:] = embedded.reshape((size_encoded,))\n \n return(embeddings)\n \n@timeit\ndef dngr_pipeline(network, N, hidden_layers, K=10, alpha=0.2, n_epochs=100, batch_size=1, activation='sigmoid', last_activation='sigmoid'):\n ppmi_net = PPMI(PCO(network, K, alpha))\n model, train_loader, tensor_net = sdae(ppmi_net, N, hidden_layers, n_epochs=n_epochs, batch_size=batch_size, activation=activation, last_activation=last_activation)\n \n print(\"[*] Visualizing an example's output...\")\n trainiter = iter(train_loader)\n idx, _ = trainiter.next()\n\n print(tensor_net[idx])\n print(model(idx))\n\n print(mean_squared_error(tensor_net[idx].cpu().detach().numpy(), model(idx).cpu().detach().numpy()))\n \n print(\"[*] Getting the embeddings and visualizing t-SNE...\")\n embeddings=get_embeddings(train_loader, N, model, size_encoded=hidden_layers[-1])\n \n cmps = connected_components(network)\n targets = [0 for i in range(N)]\n\n for i, cmp in enumerate(cmps):\n for n in cmp:\n targets[n] = i\n \n visualize_TSNE(embeddings, targets)\n \n return(embeddings, model, train_loader)"},{"alpha_fraction":0.5961456298828125,"alphanum_fraction":0.6111348867416382,"avg_line_length":23.851064682006836,"blob_id":"9bd7d5e5b68e0a57b356adcb319bc583c5f5883b","content_id":"bb474ab01a8c3c3e959aa88f93564cd6616d0e5f","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":2335,"license_type":"no_license","max_line_length":98,"num_lines":94,"path":"/src/random_graphs.py","repo_name":"JulinaM/Deep-Networks-for-Graph-Representation","src_encoding":"UTF-8","text":"import numpy as np\nimport torch\nimport torch.autograd as ag\nimport torch.nn as nn\nimport torch.optim as optim\nfrom torchsummary import summary\nimport torchvision\nimport torchvision.transforms as transforms\nimport torchvision.datasets as datasets\n\nfrom scipy.optimize import minimize, NonlinearConstraint\nimport random\n\nimport matplotlib.pyplot as plt\nfrom sklearn.metrics import mean_squared_error\n\nfrom math import sqrt\nimport time\n\ndef random_graph(p, size=(100,100)):\n return(np.array([[int(random.random() < p) for i in range(size[1])] for j in range(size[0])]))\n\ndef random_undirected_graph(p, size=(100,100)):\n graph = random_graph(p, size=size)\n graph[np.arange(size[0]),np.arange(size[1])]=0 #nullify the diagonal\n graph = np.maximum(graph, graph.T) #make it symmetric\n \n return(graph)\n\ndef random_graph_with_fixed_components(p, nodes_per_component=[50,50]):\n nodes_per_component = np.array(nodes_per_component)\n n_nodes = nodes_per_component.sum()\n n_cmp = nodes_per_component.shape[0]\n \n graph = np.zeros((n_nodes, n_nodes))\n nodes = np.arange(n_nodes)\n np.random.shuffle(nodes)\n \n cmp_nodes = []\n acc=0\n \n for i in range(n_cmp):\n cmp = nodes[acc:(acc+nodes_per_component[i])]\n cmp_nodes.append(cmp)\n acc += nodes_per_component[i]\n \n size = cmp.shape[0]\n submatrix=np.ix_(cmp,cmp)\n\n graph[submatrix] = random_undirected_graph(p, (size,size))\n \n return(graph)\n\ndef neighbors(adj, i):\n return (np.where(adj[i,:]==1)[0])\n\ndef dfs(adj, i):\n n = adj.shape[0] #number of nodes in the graph\n visited = [False for k in range(n)]\n \n stack = [i]\n \n while(len(stack)>0):\n k = stack.pop()\n neighborhood = neighbors(adj, k)\n visited[k] = True\n \n for n in neighborhood:\n if not visited[n]:\n stack.append(n)\n \n return(np.where(visited))\n\ndef connected_components(adj):\n n = adj.shape[0]\n \n visited = np.array([0 for k in range(n)])\n s = np.sum(visited)\n \n comp=[]\n \n while s<n:\n i = np.where(1-visited)[0][0]\n \n cmp = dfs(adj, i)\n visited[cmp] = 1\n s = np.sum(visited)\n \n comp.append(list(cmp[0]))\n \n return(np.array(comp))\n\nif __name__ == '__main__':\n pass"},{"alpha_fraction":0.5650569796562195,"alphanum_fraction":0.5818243026733398,"avg_line_length":25.16666603088379,"blob_id":"bef4e8073443578ea40a6c86402a1a4e2b8cf5b1","content_id":"f1a2ab4b4cb3f6e4e80227602e20b69bfd0eb937","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":2982,"license_type":"no_license","max_line_length":100,"num_lines":114,"path":"/src/utils.py","repo_name":"JulinaM/Deep-Networks-for-Graph-Representation","src_encoding":"UTF-8","text":"import numpy as np\nimport torch\nimport time\nfrom sklearn.manifold import TSNE\n\nimport matplotlib.pyplot as plt\n\nfrom sklearn.metrics import roc_auc_score, accuracy_score, confusion_matrix, average_precision_score\n\nfrom scipy.spatial.distance import pdist, squareform\n\ndef compute_pr_auc(P,S):\n y_pred = S.clone().detach()\n\n y_pred[y_pred < 0.] = 0.\n y_pred[y_pred > 1.] = 1.\n \n y_pred = S.cpu().detach().numpy().reshape((-1,))\n y_true = P.cpu().detach().numpy().reshape((-1,))\n\n return(average_precision_score(y_true, y_pred))\n\ndef compute_confusion_matrix(y_true, y_pred):\n y_pred = y_pred.clone().detach()\n\n y_pred[y_pred >= 0.5] = 1.\n y_pred[y_pred < 0.5] = 0.\n\n y_pred = y_pred.cpu().detach().numpy().reshape((-1,))\n y_true = y_true.cpu().detach().numpy().reshape((-1,))\n\n return(confusion_matrix(y_true, y_pred))\n\ndef compute_auc(P,S):\n y_pred = S.clone().detach()\n\n y_pred[y_pred < 0.] = 0.\n y_pred[y_pred > 1.] = 1.\n\t\n y_pred = S.cpu().detach().numpy().reshape((-1,))\n y_true = P.cpu().detach().numpy().reshape((-1,))\n\n return(roc_auc_score(y_true, y_pred))\n\ndef compute_accuracy(y_true, y_pred):\n y_pred = y_pred.clone().detach()\n\n y_pred[y_pred >= 0.5] = 1.\n y_pred[y_pred < 0.5] = 0.\n\n y_pred = y_pred.cpu().detach().numpy().reshape((-1,))\n y_true = y_true.cpu().detach().numpy().reshape((-1,))\n\n return(accuracy_score(y_true, y_pred))\n\n\ndef timeit(method):\n def timed(*args, **kw):\n ts = time.time()\n result = method(*args, **kw)\n te = time.time()\n if 'log_time' in kw:\n name = kw.get('log_name', method.__name__.upper())\n kw['log_time'][name] = int((te - ts) * 1000)\n else:\n print('%r %2.2f ms' % \\\n (method.__name__, (te - ts) * 1000))\n return result\n return timed\n\ndef visualize_TSNE(embeddings,target):\n tsne = TSNE(n_components=2, init='pca',\n random_state=0, perplexity=30)\n data = tsne.fit_transform(embeddings)\n #plt.figure(figsize=(12, 6))\n plt.title(\"TSNE visualization of the embeddings\")\n plt.scatter(data[:,0],data[:,1],c=target)\n\n return\n\ndef compute_similarity(net):\n M = 1 - pdist(net, metric='Jaccard')\n M = squareform(M)\n M = M + np.eye(*M.shape)\n M[np.isnan(M)] = 0.\n\n return(M)\n\ndef readnet(net_path):\n\treturn(np.genfromtxt(net_path,delimiter='\\t'))\n\ndef extract_samples(K, tensor):\n \"\"\"\n Extract K random samples from tensor.\n\n Parameters\n ----------\n K : int\n Wanted number of samples\n tensor : tensor of any size\n tensor from which extract the samples \n (the first dimension will be considered as the sample dim)\n\n Returns\n -------\n samples : tensor of same type as the tensor parameter of shape (K,...)\n the K samples extracted from tensor\n\n \"\"\"\n perm = torch.randperm(tensor.size(0))\n idx = perm[:K]\n samples = tensor[idx]\n \n return (samples)"},{"alpha_fraction":0.5544765591621399,"alphanum_fraction":0.5700565576553345,"avg_line_length":29.828947067260742,"blob_id":"1feb19138e66607907ba3391f057dd6b0549b984","content_id":"24b18bc730f47568c1cd4e73dceaf10b06d04f34","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":9371,"license_type":"no_license","max_line_length":149,"num_lines":304,"path":"/src/pu_learner.py","repo_name":"JulinaM/Deep-Networks-for-Graph-Representation","src_encoding":"UTF-8","text":"import numpy as np\nimport torch\nimport torch.autograd as ag\nimport torch.nn as nn\nimport torch.optim as optim\nfrom torchsummary import summary\nimport torchvision\nimport torchvision.transforms as transforms\nimport torchvision.datasets as datasets\n\nfrom scipy.optimize import minimize, NonlinearConstraint\nimport random\n\nimport matplotlib.pyplot as plt\nfrom sklearn.metrics import mean_squared_error\n\nfrom math import sqrt\nimport time\n\nfrom autoencoder import *\nfrom utils import *\nfrom random_graphs import *\nfrom dgnr import *\n\ndef old_pu_learning(x, y, P, k = 7, alpha = 0.2, gamma = 0.3, maxiter=1000):\n Fd = x.shape[1]\n Ft = y.shape[1]\n Nd = x.shape[0]\n Nt = y.shape[0]\n \n #Number of variables\n N_variables = Fd * k + Ft * k\n \n print(\"Number of variables:\", N_variables) \n print(\"Finding positive and negative examples...\")\n \n Ipos = np.where(P==1.)\n Ineg = np.where(P==0.)\n\n print(\"Number of positive examples:\", Ipos[0].shape[0])\n print(\"Number of negative/unlabelled examples:\", Ineg[0].shape[0])\n \n alpha_rac = sqrt(alpha)\n \n @timeit\n def objective(z):\n H = z[:Fd*k].reshape((Fd,k))\n W = z[-Ft*k:].reshape((Ft,k))\n \n M = P - (x @ H @ np.transpose(W) @ np.transpose(y))\n \n M[Ineg] *= alpha_rac\n \n L = torch.sum(M**2) + gamma/2 * (np.sum(H**2, axis=(0,1)) + np.sum(W**2, axis=(0,1)))\n print(L)\n\n return(L)\n \n def constraint(z):\n H = z[:Fd*k].reshape((Fd,k))\n W = z[-Ft*k:].reshape((Ft,k))\n S = x @ H @ np.transpose(W) @ np.transpose(y)\n S = S.reshape((-1,))\n \n return(S)\n \n nlc = NonlinearConstraint(constraint, np.zeros(Nt*Nd), np.ones(Nt*Nd))\n\n print(\"Going to minimize... Maximum number of iterations:\", maxiter)\n res=minimize(objective, x0 = np.random.randn(N_variables), options={'maxiter':maxiter, 'disp':'True'}, constraints=[nlc], method='trust-constr')\n \n print(\"\\n\\nSolved.\")\n \n z=res['x']\n H = z[:Fd*k].reshape((Fd,k))\n W = z[-Ft*k:].reshape((Ft,k))\n\n print(\"Now computing Z=HW^T, then will compute S...\")\n \n S = x @ H @ np.transpose(W) @ np.transpose(y)\n \n return(S)\n\ndef pu_learning(x, y, P, pos_train_mask, neg_train_mask, k = 7, alpha = 0.2, gamma = 0.3, maxiter=1000, lr=0.1):\n Fd = x.shape[1]\n Ft = y.shape[1]\n Nd = x.shape[0]\n Nt = y.shape[0]\n \n device = torch.device(\"cuda\" if torch.cuda.is_available() else \"cpu\")\n\n #Number of variables\n N_variables = Fd * k + Ft * k\n \n print(\"Number of variables:\", N_variables) \n print(\"Finding positive and negative examples...\")\n \n P = torch.Tensor(P).to(device)\n x = torch.Tensor(x).to(device)\n y = torch.Tensor(y).to(device)\n \n x_norm = torch.linalg.norm(x)\n y_norm = torch.linalg.norm(y)\n\n Ipos = pos_train_mask\n Ineg = neg_train_mask\n train_mask = torch.logical_or(Ipos,Ineg)\n\n print(\"Number of positive examples:\", P[Ipos].size()[0])\n print(\"Number of negative/unlabelled examples:\", P[Ineg].size()[0])\n \n alpha_rac = sqrt(alpha)\n \n def objective(H,W):\n M = P - torch.chain_matmul(x, H, torch.transpose(W, 0, 1), torch.transpose(y, 0, 1))\n \n M[Ineg] *= alpha_rac\n M[~train_mask] = 0.\n \n L = torch.sum(M**2) + gamma/2 * (torch.sum(H**2) + torch.sum(W**2))\n\n return(L)\n \n def constraint(z):\n z = torch.Tensor(z).to(device)\n H = z[:Fd*k].resize(Fd,k)\n W = z[-Ft*k:].resize(Ft,k)\n\n S = torch.chain_matmul(x, H, torch.transpose(W, 0, 1), torch.transpose(y, 0, 1))\n S = S.reshape((-1,)).cpu().detach().numpy()\n \n return(S)\n \n #nlc = NonlinearConstraint(constraint, np.zeros(Nt*Nd), np.ones(Nt*Nd))\n\n print(\"Going to minimize... Maximum number of iterations:\", maxiter)\n #res=minimize(objective, x0 = np.random.randn(N_variables), options={'maxiter':maxiter, 'disp':'True'}, constraints=[nlc], method='trust-constr')\n W = ag.Variable(torch.rand(Ft,k).to(device)/y_norm, requires_grad=True)\n H = ag.Variable(torch.rand(Fd,k).to(device)/x_norm, requires_grad=True)\n \n opt = torch.optim.Adam([H,W], lr=lr)\n\n for i in range(maxiter):\n # Zeroing gradients\n opt.zero_grad()\n\n # Evaluating the objective\n obj = objective(H,W)\n\n # Calculate gradients\n obj.backward() \n opt.step()\n if i%1000==0: \n S = torch.chain_matmul(x, H, torch.transpose(W,0,1), torch.transpose(y,0,1))\n auc = compute_auc(P[train_mask],S[train_mask])\n print(\"Objective:\", obj, \"(auc:\", auc, \")\")\n\n print(\"\\n\\nSolved.\")\n \n print(\"Now computing Z=HW^T, then will compute S...\")\n \n S = torch.chain_matmul(x, H, torch.transpose(W,0,1), torch.transpose(y,0,1))\n \n return(S, H, W)\n\ndef get_train_test_masks(P, train_size=0.8):\n P = torch.Tensor(P)\n Ipos = (P == 1.)\n Ineg = (P == 0.)\n\n pos_train = Ipos * torch.rand(P.size())\n pos_train[Ineg] = 1.\n pos_train = pos_train < train_size\n train_neg_rel_size = torch.sum(pos_train) / torch.sum(Ineg)\n \n neg_train = Ineg * torch.rand(P.size())\n neg_train[Ipos] = 1.\n neg_train = neg_train < train_neg_rel_size\n\n train = pos_train + neg_train\n test = ~train\n pos_test = torch.logical_and(test, Ipos)\n neg_test = torch.logical_and(test, Ineg)\n\n return(pos_train, neg_train, pos_test, neg_test)\n\ndef new_pu_learning(x, y, P, k = 7, alpha = 0.2, gamma = 0.3, maxiter=1000, lr=1e-3, batch_size=100):\n Fd = x.shape[1]\n Ft = y.shape[1]\n Nd = x.shape[0]\n Nt = y.shape[0]\n \n device = torch.device(\"cuda\" if torch.cuda.is_available() else \"cpu\")\n\n #Number of variables\n N_variables = Fd * k + Ft * k\n N_examples = Nd*Nt\n \n P = torch.Tensor(P).to(device)\n cartesian_product = torch.Tensor([[u, v] for u in x for v in y]).to(device)\n \n print(\"Spliting train and test sets...\")\n pos_train, neg_train, pos_test, neg_test = get_train_test_masks(P, train_size=0.8)\n\n train_mask = torch.logical_or(pos_train, neg_train)\n\n flat_train_mask = train_mask.flatten()\n\n print(\"Building the train loader...\")\n train = torch.utils.data.TensorDataset(cartesian_product[flat_train_mask], P[train_mask].flatten())\n train_loader = torch.utils.data.DataLoader(train, batch_size=batch_size, shuffle=False)\n\n print(\"Number of variables:\", N_variables)\n print(\"Finding positive and negative examples...\")\n \n x = torch.Tensor(x).to(device)\n y = torch.Tensor(y).to(device)\n \n print(\"Number of train examples:\", P.size()[0])\n print(\"Number of positive examples in train set:\", P[pos_train].size()[0])\n print(\"Number of negative/unlabelled examples in train set:\", P[neg_train].size()[0])\n \n alpha_rac = sqrt(alpha)\n \n def objective(a, H, W, b, P):\n M = P.clone().detach()\n for i in range(P.size()[0]):\n s = torch.chain_matmul(a[i].reshape(1,Fd), H, torch.transpose(W, 0, 1), torch.transpose(b[i].reshape(1,Ft), 0, 1))\n M[i] -= s.item()\n\n Ineg = (P==0.)\n\n M[Ineg] *= alpha_rac\n \n L = torch.mean(M**2) + gamma/2 * (torch.sum(H**2) + torch.sum(W**2))\n\n return(L)\n \n def objective_prime(a, H, W, b, P):\n M = P - torch.einsum('ij,jk,kl,li->i', a, H, torch.transpose(W, 0, 1), torch.transpose(b, 0, 1))\n \n Ineg = (P==0.)\n\n M[Ineg] *= alpha_rec\n L = torch.mean(M**2) + gamma/2 * (torch.sum(H**2) + torch.sum(W**2))\n\n return(L)\n\n def total_loss(x,H,W,y,P):\n M = P - torch.chain_matmul(x, H, torch.transpose(W, 0, 1), torch.transpose(y, 0, 1))\n\n M[~train_mask] = 0.\n\n M[neg_train] *= alpha_rac\n\n L = torch.mean(M**2) + gamma/2 * (torch.sum(H**2) + torch.sum(W**2))\n\n return(L)\n\n print(\"Going to minimize... Maximum number of epochs:\", maxiter)\n \n W = torch.zeros(Ft,k).to(device)\n W /= torch.linalg.norm(W)*torch.linalg.norm(y) #for initial W and H not to be too big\n H = torch.zeros(Fd,k).to(device)\n H /= torch.linalg.norm(H)*torch.linalg.norm(x)\n\n W = ag.Variable(W, requires_grad=True)\n H = ag.Variable(H, requires_grad=True)\n \n opt = torch.optim.Adam([H,W], lr=lr)\n \n batch_num = N_examples//batch_size\n\n for k in range(maxiter):\n for i, batch in enumerate(train_loader, 0):\n # Zeroing gradients\n opt.zero_grad()\n\n inputs, labels = batch\n\n a, b = inputs[:,0,:], inputs[:,1,:]\n \n # Evaluating the objective\n obj = objective(a,H,W,b,labels)\n\n # Calculate gradients\n obj.backward() \n opt.step()\n \n if i%(batch_size//4) == 0:\n S = torch.chain_matmul(x, H, torch.transpose(W,0,1), torch.transpose(y,0,1))\n stdm = torch.std(S[train_mask])\n auc = compute_auc(P[train_mask],S[train_mask])\n loss = total_loss(x,H,W,y,P)\n\n print(\"[epoch=\",k,\", batch_num=\",i,\"]\",\"Objective: \", loss.item(), \"(standard deviation: \", stdm.item(), \", auc: \", auc.item(), \")\")\n\n print(\"\\n\\nSolved.\")\n \n print(\"Now computing Z=HW^T, then will compute S...\")\n \n S = torch.chain_matmul(x, H, torch.transpose(W,0,1), torch.transpose(y,0,1))\n \n return(S, H, W)"},{"alpha_fraction":0.5642725825309753,"alphanum_fraction":0.5769230723381042,"avg_line_length":34.26258850097656,"blob_id":"4f9305052e62adc12225284a46cfae829924c69c","content_id":"4707245c67a3e5d43eb3d30d2e3924f81b39cec2","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":9802,"license_type":"no_license","max_line_length":171,"num_lines":278,"path":"/src/pu_learning.py","repo_name":"JulinaM/Deep-Networks-for-Graph-Representation","src_encoding":"UTF-8","text":"import torch\nimport torch.nn as nn\nimport torch.optim as optim\n\nfrom math import sqrt\nfrom sklearn.model_selection import KFold\n\nfrom autoencoder import *\nfrom utils import *\nfrom random_graphs import *\nfrom dgnr import *\n\ndef get_train_test_masks(P, train_size=0.8, test_balance=True):\n P = torch.Tensor(P)\n Ipos = (P == 1.)\n Ineg = (P == 0.)\n\n pos_train = Ipos * torch.rand(P.size())\n pos_train[Ineg] = 1.\n pos_train = pos_train < train_size\n train_neg_rel_size = torch.sum(pos_train) / torch.sum(Ineg)\n \n neg_train = Ineg * torch.rand(P.size())\n neg_train[Ipos] = 1.\n neg_train = neg_train < train_neg_rel_size\n\n train = pos_train + neg_train\n\n if not test_balance:\n test = ~train\n pos_test = torch.logical_and(test, Ipos)\n neg_test = torch.logical_and(test, Ineg)\n else:\n test = ~train\n pos_test = torch.logical_and(test,Ipos)\n neg_test = torch.logical_and(test, Ineg)\n\n num_pos_test = torch.sum(pos_test)\n test_neg_rel_size = num_pos_test / torch.sum(neg_test)\n \n neg_test = neg_test * torch.rand(P.size())\n neg_test[train] = 1.\n neg_test[Ipos] = 1.\n \n neg_test = neg_test < test_neg_rel_size\n\n return(pos_train, neg_train, pos_test, neg_test)\n\nclass CustomMSELoss(nn.Module):\n def __init__(self, alpha=0.2):\n super(CustomMSELoss, self).__init__()\n self.alpha=sqrt(alpha)\n\n def forward(self, inputs, targets):\n #comment out if your model contains a sigmoid or equivalent activation layer\n neg_mask = (targets == 0.)\n \n M = (targets-inputs)**2\n M[neg_mask] *= self.alpha\n\n loss_res = torch.mean(M)\n\n return loss_res\n\nclass PU_Learner(nn.Module):\n def __init__(self, k, Fd, Ft, X, Y, Nd, Nt, activation='identity', has_bias=False):\n super().__init__()\n self.k = k\n self.Fd = Fd\n self.Ft = Ft\n \n self.H = torch.nn.Parameter(torch.randn(Fd, k)*1/sqrt(k))\n self.W = torch.nn.Parameter(torch.randn(k, Ft)*1/sqrt(k))\n if not has_bias:\n self.b_x = torch.zeros(Nd)\n self.b_y = torch.zeros(Nt)\n else:\n self.b_x = torch.nn.Parameter(torch.randn(Nd))\n self.b_y = torch.nn.Parameter(torch.randn(Nt))\n\n self.X = (X - X.mean(0))/(X.std(0)+1e-7)\n self.Y = (Y - Y.mean(0))/(Y.std(0)+1e-7)\n\n activ_dict = {'sigmoid': torch.nn.Sigmoid, 'identity': torch.nn.Identity}\n self.activation = activ_dict[activation]()\n\n def forward(self, id_x, id_y):\n \tdot = torch.einsum('ij,jk,kl,li->i', self.X[id_x], self.H, self.W, torch.transpose(self.Y[id_y], 1, 0))\n\n \treturn(self.activation(dot + self.b_x[id_x] + self.b_y[id_y]))\n\ndef pu_learning(k, x, y, P, pos_train, neg_train, pos_test, neg_test, n_epochs=100, batch_size=100, lr=1e-3, alpha=1.0, gamma=0., activation='identity'):\n #hidden_layers=[500,200,100]\n #input_numer=784\n # use gpu if available\n device = torch.device(\"cuda\" if torch.cuda.is_available() else \"cpu\")\n\n Fd = x.shape[1]\n Ft = y.shape[1]\n Nd = x.shape[0]\n Nt = y.shape[0]\n \n #Number of variables\n N_variables = Fd * k + Ft * k\n\n cartesian_product = torch.Tensor([[i, j] for i in range(Nd) for j in range(Nt)]).long().to(device)\n\n x = torch.Tensor(x).to(device)\n y = torch.Tensor(y).to(device)\n\n P = torch.Tensor(P).to(device)\n\n train_mask = torch.logical_or(pos_train, neg_train)\n test_mask = torch.logical_or(pos_test, neg_test)\n flat_train_mask = train_mask.flatten()\n\n print(\"Building the train loader...\")\n train = torch.utils.data.TensorDataset(cartesian_product[flat_train_mask], P[train_mask].flatten())\n train_loader = torch.utils.data.DataLoader(train, batch_size=batch_size, shuffle=True)\n \n batch_num = len(train_loader)\n\n print(\"Number of variables:\", N_variables)\n print(\"Finding positive and negative examples...\") \n\n print(\"Number of train examples:\", P[train_mask].size()[0])\n print(\"Number of positive examples in train set:\", P[pos_train].size()[0])\n print(\"Number of negative/unlabelled examples in train set:\", P[neg_train].size()[0])\n\n model = PU_Learner(k, Fd, Ft, x, y, Nd, Nt, activation=activation).to(device)\n\n # create an optimizer object\n # Adam optimizer with learning rate 1e-3\n optimizer = optim.Adam(model.parameters(), lr=lr, weight_decay=gamma)\n\n # mean-squared error loss\n criterion = CustomMSELoss(alpha=alpha)\n\n for epoch in range(n_epochs): # loop over the dataset multiple times\n\n running_loss = 0.0\n for i, data in enumerate(train_loader, 0):\n # get the inputs; data is a list of [inputs, labels]\n inputs, labels = data\n \n inputs=inputs.to(device)\n \n id_x_batch, id_y_batch = inputs[:,0], inputs[:,1]\n\n # zero the parameter gradients\n optimizer.zero_grad()\n\n # forward + backward + optimize\n outputs = model(id_x_batch, id_y_batch)\n \n loss = criterion(outputs, labels)\n loss.backward()\n optimizer.step()\n\n # print statistics\n running_loss += loss.item()\n \n S = model.activation(torch.chain_matmul(model.X, model.H, model.W, torch.transpose(model.Y,0,1)) + model.b_x.unsqueeze(-1).expand(-1,Nt) + model.b_y.expand(Nd,-1))\n \"\"\"print(S)\n print(model.H)\n print(model.W)\n print(model.b_x)\n print(model.b_y)\"\"\"\n auc = compute_auc(P[train_mask].clone(), S[train_mask].clone())\n acc = compute_accuracy(P[train_mask].clone(), S[train_mask].clone())\n\n print('[%d] loss: %.3f, auc: %.3f, acc: %.3f' %\n (epoch + 1, running_loss / (batch_num), auc, acc))\n running_loss = 0.0\n\n print('Finished Training')\n print(\"Now computing Z=HW^T, then will compute S...\")\n \n print(x.size(), model.H.size(), model.W.size(), y.size())\n S = model.activation(torch.chain_matmul(model.X, model.H, model.W, torch.transpose(model.Y,0,1)) + model.b_x.unsqueeze(-1).expand(-1,Nt) + model.b_y.expand(Nd,-1))\n \n return(S, model.H, model.W, model.b_x, model.b_y, train_mask, test_mask)\n\ndef pu_learning_new(k, x, y, P, n_epochs=100, batch_size=100, lr=1e-5, train_size=0.8, alpha=1.0, gamma=0., test_balance=True, activation='identity'):\n print(\"Spliting train and test sets...\")\n pos_train, neg_train, pos_test, neg_test = get_train_test_masks(P, train_size=train_size, test_balance=test_balance)\n \n return(pu_learning(k, x, y, P, pos_train, neg_train, pos_test, neg_test, \n n_epochs=n_epochs, batch_size=batch_size, lr=lr, \n alpha=alpha, gamma=gamma, activation=activation))\n\ndef cross_validate(k, x, y, P, N_folds, n_epochs=100, batch_size=100, lr=1e-5, train_size=0.8, alpha=1.0, gamma=0., activation='identity'):\n pos_mask = (P==1)\n neg_mask = (P==0)\n \n N_pos = pos_mask.sum()\n N_neg = neg_mask.sum()\n \n N = min(N_pos, N_neg)\n \n pos_idx = pos_mask.nonzero()\n neg_idx = neg_mask.nonzero()\n \n pos_idx = extract_samples(N, pos_idx)\n neg_idx = extract_samples(N, neg_idx)\n \n kfold = KFold(n_splits=N_folds, shuffle=False)\n \n kfold_pos = list(kfold.split(pos_idx))\n kfold_neg = list(kfold.split(neg_idx))\n \n S_auc = 0\n S_acc = 0\n S_pr = 0\n \n S_sol = 0\n\n for fold in range(N_folds):\n print(\"Fold %d\" % (fold+1))\n print(\"Preparing the masks...\")\n pos_train_idx = pos_idx[kfold_pos[fold][0]]\n #print(pos_train_idx.max(0))\n pos_test_idx = pos_idx[kfold_pos[fold][1]]\n neg_train_idx = neg_idx[kfold_neg[fold][0]]\n neg_test_idx = neg_idx[kfold_neg[fold][1]]\n \n pos_train_mask = torch.zeros(pos_mask.size(),dtype=bool)\n pos_train_mask[pos_train_idx[:,0],pos_train_idx[:,1]] = True\n \n pos_test_mask = torch.zeros(pos_mask.size(),dtype=bool)\n pos_test_mask[pos_test_idx[:,0],pos_test_idx[:,1]] = True\n \n neg_train_mask = torch.zeros(neg_mask.size(),dtype=bool)\n neg_train_mask[neg_train_idx[:,0],neg_train_idx[:,1]] = True\n \n neg_test_mask = torch.zeros(neg_mask.size(),dtype=bool)\n neg_test_mask[neg_test_idx[:,0],neg_test_idx[:,1]] = True\n \n test_mask = torch.logical_or(pos_test_mask, neg_test_mask)\n \n print(\"Starting to learn...\")\n S, H, W, b_x, b_y, _, _ = pu_learning(k, x, y, P, \n pos_train_mask, neg_train_mask, pos_test_mask, neg_test_mask, \n n_epochs=n_epochs, batch_size=batch_size, lr=lr, \n alpha=alpha, gamma=gamma, activation=activation)\n \n print(\"Evaluating on test set...\")\n auc, pr, acc, _ = eval_test_set(P, S, test_mask)\n \n S_auc += auc\n S_acc += acc\n S_pr += pr\n\n S_sol += S * auc\n\n return(S_sol/S_auc, S_auc/N_folds, S_pr/N_folds, S_acc/N_folds)\n\ndef eval_test_set(P, S, test):\n print(\"Evaluation on the test set...\")\n print(\"Test set statistics:\")\n n_pos = int(P[test].sum().item())\n n_neg = int((1-P[test]).sum().item())\n\n print(\"Number of positive examples:\", n_pos)\n print(\"Number of negative/unlabelled examples:\", n_neg)\n \n auc = compute_auc(P[test],S[test])\n pr = compute_pr_auc(P[test], S[test])\n acc = compute_accuracy(P[test],S[test])\n confusion = compute_confusion_matrix(P[test], S[test])\n \n print(\"\\nROC auc: %f\" % auc)\n print(\"PR auc: %f\" % pr)\n print(\"Accuracy: %f\" % acc)\n print(\"Confusion matrix:\")\n print(confusion)\n \n return(auc,pr,acc,confusion)"}],"string":"[\n {\n \"alpha_fraction\": 0.5860384702682495,\n \"alphanum_fraction\": 0.5926457643508911,\n \"avg_line_length\": 30.926605224609375,\n \"blob_id\": \"2a140f398ddbf1ffedc9cb406ee87230e7013aaf\",\n \"content_id\": \"bde05c68ab394d7bcd7f82600fa9126232e7cc22\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 3481,\n \"license_type\": \"no_license\",\n \"max_line_length\": 141,\n \"num_lines\": 109,\n \"path\": \"/src/autoencoder.py\",\n \"repo_name\": \"JulinaM/Deep-Networks-for-Graph-Representation\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import numpy as np\\nimport torch\\nimport torch.autograd as ag\\nimport torch.nn as nn\\nimport torch.optim as optim\\nfrom torchsummary import summary\\nimport torchvision\\nimport torchvision.transforms as transforms\\nimport torchvision.datasets as datasets\\n\\nfrom scipy.optimize import minimize, NonlinearConstraint\\nimport random\\n\\nimport matplotlib.pyplot as plt\\nfrom sklearn.metrics import mean_squared_error\\n\\nfrom math import sqrt\\nimport time\\n\\ndef timeit(method):\\n def timed(*args, **kw):\\n ts = time.time()\\n result = method(*args, **kw)\\n te = time.time()\\n if 'log_time' in kw:\\n name = kw.get('log_name', method.__name__.upper())\\n kw['log_time'][name] = int((te - ts) * 1000)\\n else:\\n print('%r %2.2f ms' % \\\\\\n (method.__name__, (te - ts) * 1000))\\n return result\\n return timed\\n\\nclass GaussianNoise(nn.Module):\\n def __init__(self, stddev):\\n super().__init__()\\n self.stddev = stddev\\n\\n def forward(self, din):\\n if self.training:\\n return din + torch.randn(din.size()) * self.stddev\\n return din\\n\\nclass DropoutNoise(nn.Module):\\n def __init__(self, p):\\n super().__init__()\\n self.p = p\\n self.device = torch.device(\\\"cuda\\\" if torch.cuda.is_available() else \\\"cpu\\\")\\n def forward(self, x):\\n t = torch.rand(x.size()).to(self.device)\\n a = t > self.p\\n \\n return(x*a)\\n\\nclass BasicBlock(nn.Module):\\n def __init__(self, input_shape, n_neurons, activation='relu', noise=None, noise_arg=None):\\n super().__init__()\\n self.n_neurons = n_neurons\\n self.input_shape = input_shape\\n \\n self.has_noise = False\\n \\n if noise=='gaussian':\\n self.has_noise = True\\n self.noise = GaussianNoise(noise_arg)\\n elif noise=='dropout':\\n self.has_noise = True\\n self.noise = DropoutNoise(noise_arg)\\n \\n self.dense_layer = nn.Linear(self.input_shape, self.n_neurons)\\n \\n activations_map = {'relu':nn.ReLU, 'tanh':nn.Tanh, 'sigmoid':nn.Sigmoid}\\n self.activation = activations_map[activation]()\\n\\n def forward(self, features):\\n x=features\\n \\n if self.has_noise:\\n x = self.noise(x)\\n\\n x = self.dense_layer(features)\\n x = self.activation(x)\\n \\n return(x)\\n\\nclass SDAE(nn.Module):\\n def __init__(self, features, input_shape, hidden_layers, activation='relu', last_activation='relu', noise_type='dropout', noise_arg=0.2):\\n super().__init__()\\n self.features = features\\n\\n self.inputs = [input_shape] + hidden_layers\\n \\n n = len(self.inputs)\\n encoder_units = [BasicBlock(self.inputs[0], self.inputs[1], activation=activation, noise=noise_type, noise_arg=noise_arg)]\\n encoder_units.extend([BasicBlock(self.inputs[i], self.inputs[i+1], activation=activation) for i in range(1, n-1)])\\n \\n self.encoder = nn.Sequential(*encoder_units)\\n \\n decoder_units = [BasicBlock(self.inputs[i], self.inputs[i-1], activation=activation) for i in range(n-1,1,-1)]\\n decoder_units.append(BasicBlock(self.inputs[1], self.inputs[0], activation=last_activation))\\n \\n self.decoder = nn.Sequential(*decoder_units)\\n \\n def forward(self, idx):\\n encoded = self.encoder(self.features[idx])\\n \\n decoded = self.decoder(encoded)\\n \\n return(decoded)\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.5990557670593262,\n \"alphanum_fraction\": 0.6121699810028076,\n \"avg_line_length\": 28.183673858642578,\n \"blob_id\": \"1e6dbeafe604000312ac7da086d6def3c6682800\",\n \"content_id\": \"beb7dc830d76e123e5347a2c87070a78127e9b55\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 5719,\n \"license_type\": \"no_license\",\n \"max_line_length\": 168,\n \"num_lines\": 196,\n \"path\": \"/src/dgnr.py\",\n \"repo_name\": \"JulinaM/Deep-Networks-for-Graph-Representation\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import numpy as np\\nimport torch\\nimport torch.autograd as ag\\nimport torch.nn as nn\\nimport torch.optim as optim\\nfrom torchsummary import summary\\nimport torchvision\\nimport torchvision.transforms as transforms\\nimport torchvision.datasets as datasets\\n\\nfrom scipy.optimize import minimize, NonlinearConstraint\\nimport random\\n\\nimport matplotlib.pyplot as plt\\nfrom sklearn.metrics import mean_squared_error\\n\\nfrom math import sqrt\\nimport time\\n\\nfrom autoencoder import SDAE\\nfrom utils import *\\nfrom random_graphs import connected_components\\n\\ndef timeit(method):\\n def timed(*args, **kw):\\n ts = time.time()\\n result = method(*args, **kw)\\n te = time.time()\\n if 'log_time' in kw:\\n name = kw.get('log_name', method.__name__.upper())\\n kw['log_time'][name] = int((te - ts) * 1000)\\n else:\\n print('%r %2.2f ms' % \\\\\\n (method.__name__, (te - ts) * 1000))\\n return result\\n return timed\\n\\ndef normalize(M):\\n #Put diagonal elements to 0\\n M = M - np.diag(np.diag(M))\\n \\n #Normalizing by row\\n D_inv = np.diag(np.reciprocal(np.sum(M,axis=0)))\\n M = np.dot(D_inv, M)\\n\\n return M\\n\\ndef zero_one_normalisation(matrix, e=1e-5):\\n M = np.max(matrix)\\n m = np.min(matrix)\\n r = (matrix-m) / (M-m + e)\\n return(r)\\n\\ndef PCO(A, K, alpha):\\n \\\"\\\"\\\"\\n For a graph represented by its adjacency matrix *A*, computes the co-occurence matrix by random \\n surfing on the graph with returns. 1-alpha is the probability to make, at each step, a return \\n to the original step.\\n \\\"\\\"\\\"\\n A=np.array(A, dtype=float)\\n \\n #The adjacency matrix A is first normalized\\n A=normalize(A) \\n \\n n=A.shape[0]\\n \\n I=np.eye(n)\\n \\n P=I\\n M=np.zeros((n, n))\\n \\n for i in range(K):\\n P = alpha*np.dot(P,A) + (1-alpha)*I\\n M = M+P\\n \\n return(M)\\n\\ndef PPMI(M):\\n \\\"\\\"\\\"Computes the shifted positive pointwise mutual information (PPMI) matrix\\n from the co-occurence matrix (PCO) of a graph.\\\"\\\"\\\"\\n \\n M=normalize(M)\\n cols = np.sum(M, axis=0)\\n rows = np.sum(M, axis=1).reshape((-1,1))\\n s = np.sum(rows)\\n \\n P = s*M\\n P /= cols\\n P /= rows\\n \\n #P[np.where(P<0)] = 1.0\\n P = np.log(P)\\n\\n #To avoid NaN when applying log\\n P[np.isnan(P)] = 0.0\\n P[np.isinf(P)] = 0.0\\n P[np.isneginf(P)] = 0.0\\n P[np.where(P<0)] = 0.0\\n \\n return(P)\\n\\ndef sdae(input_net, input_number, hidden_layers, n_epochs=100, batch_size=1, activation='sigmoid', last_activation='sigmoid'):\\n #hidden_layers=[500,200,100]\\n #input_numer=784\\n # use gpu if available\\n device = torch.device(\\\"cuda\\\" if torch.cuda.is_available() else \\\"cpu\\\")\\n\\n normalized_input_net = zero_one_normalisation(input_net)\\n tensor_net = torch.Tensor(normalized_input_net).to(device)\\n N = tensor_net.size()[0]\\n idx = torch.arange(N).long()\\n\\n model = SDAE(tensor_net, input_number, hidden_layers, activation=activation, last_activation=last_activation).to(device)\\n\\n # create an optimizer object\\n # Adam optimizer with learning rate 1e-3\\n optimizer = optim.Adam(model.parameters(), lr=1e-3)\\n\\n # mean-squared error loss\\n criterion = nn.MSELoss()\\n\\n #summary(model, (input_number,))\\n \\n train = torch.utils.data.TensorDataset(idx, idx)\\n train_loader = torch.utils.data.DataLoader(train, batch_size=batch_size, shuffle=False)\\n\\n for epoch in range(n_epochs): # loop over the dataset multiple times\\n\\n running_loss = 0.0\\n for i, data in enumerate(train_loader, 0):\\n # get the inputs; data is a list of [inputs, labels]\\n idx, _ = data\\n \\n idx=idx.long().to(device)\\n inputs=tensor_net[idx]\\n\\n #inputs=torch.flatten(inputs)\\n # zero the parameter gradients\\n optimizer.zero_grad()\\n\\n # forward + backward + optimize\\n outputs = model(idx)\\n \\n loss = criterion(outputs, inputs)\\n loss.backward()\\n optimizer.step()\\n\\n # print statistics\\n running_loss += loss.item()\\n\\n print('[%d, %5d] loss: %.5f' %\\n (epoch + 1, i + 1, running_loss / input_number))\\n\\n print('Finished Training')\\n \\n return(model, train_loader, tensor_net)\\n\\ndef get_embeddings(train_loader, N, model, size_encoded=100):\\n trainiter = iter(train_loader)\\n embeddings = np.zeros((N, size_encoded))\\n\\n for i,q in enumerate(trainiter):\\n idx = q[0]\\n for j in idx:\\n embedded = model.encoder(model.features[j]).cpu().detach().numpy()\\n embeddings[j,:] = embedded.reshape((size_encoded,))\\n \\n return(embeddings)\\n \\n@timeit\\ndef dngr_pipeline(network, N, hidden_layers, K=10, alpha=0.2, n_epochs=100, batch_size=1, activation='sigmoid', last_activation='sigmoid'):\\n ppmi_net = PPMI(PCO(network, K, alpha))\\n model, train_loader, tensor_net = sdae(ppmi_net, N, hidden_layers, n_epochs=n_epochs, batch_size=batch_size, activation=activation, last_activation=last_activation)\\n \\n print(\\\"[*] Visualizing an example's output...\\\")\\n trainiter = iter(train_loader)\\n idx, _ = trainiter.next()\\n\\n print(tensor_net[idx])\\n print(model(idx))\\n\\n print(mean_squared_error(tensor_net[idx].cpu().detach().numpy(), model(idx).cpu().detach().numpy()))\\n \\n print(\\\"[*] Getting the embeddings and visualizing t-SNE...\\\")\\n embeddings=get_embeddings(train_loader, N, model, size_encoded=hidden_layers[-1])\\n \\n cmps = connected_components(network)\\n targets = [0 for i in range(N)]\\n\\n for i, cmp in enumerate(cmps):\\n for n in cmp:\\n targets[n] = i\\n \\n visualize_TSNE(embeddings, targets)\\n \\n return(embeddings, model, train_loader)\"\n },\n {\n \"alpha_fraction\": 0.5961456298828125,\n \"alphanum_fraction\": 0.6111348867416382,\n \"avg_line_length\": 23.851064682006836,\n \"blob_id\": \"9bd7d5e5b68e0a57b356adcb319bc583c5f5883b\",\n \"content_id\": \"bb474ab01a8c3c3e959aa88f93564cd6616d0e5f\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 2335,\n \"license_type\": \"no_license\",\n \"max_line_length\": 98,\n \"num_lines\": 94,\n \"path\": \"/src/random_graphs.py\",\n \"repo_name\": \"JulinaM/Deep-Networks-for-Graph-Representation\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import numpy as np\\nimport torch\\nimport torch.autograd as ag\\nimport torch.nn as nn\\nimport torch.optim as optim\\nfrom torchsummary import summary\\nimport torchvision\\nimport torchvision.transforms as transforms\\nimport torchvision.datasets as datasets\\n\\nfrom scipy.optimize import minimize, NonlinearConstraint\\nimport random\\n\\nimport matplotlib.pyplot as plt\\nfrom sklearn.metrics import mean_squared_error\\n\\nfrom math import sqrt\\nimport time\\n\\ndef random_graph(p, size=(100,100)):\\n return(np.array([[int(random.random() < p) for i in range(size[1])] for j in range(size[0])]))\\n\\ndef random_undirected_graph(p, size=(100,100)):\\n graph = random_graph(p, size=size)\\n graph[np.arange(size[0]),np.arange(size[1])]=0 #nullify the diagonal\\n graph = np.maximum(graph, graph.T) #make it symmetric\\n \\n return(graph)\\n\\ndef random_graph_with_fixed_components(p, nodes_per_component=[50,50]):\\n nodes_per_component = np.array(nodes_per_component)\\n n_nodes = nodes_per_component.sum()\\n n_cmp = nodes_per_component.shape[0]\\n \\n graph = np.zeros((n_nodes, n_nodes))\\n nodes = np.arange(n_nodes)\\n np.random.shuffle(nodes)\\n \\n cmp_nodes = []\\n acc=0\\n \\n for i in range(n_cmp):\\n cmp = nodes[acc:(acc+nodes_per_component[i])]\\n cmp_nodes.append(cmp)\\n acc += nodes_per_component[i]\\n \\n size = cmp.shape[0]\\n submatrix=np.ix_(cmp,cmp)\\n\\n graph[submatrix] = random_undirected_graph(p, (size,size))\\n \\n return(graph)\\n\\ndef neighbors(adj, i):\\n return (np.where(adj[i,:]==1)[0])\\n\\ndef dfs(adj, i):\\n n = adj.shape[0] #number of nodes in the graph\\n visited = [False for k in range(n)]\\n \\n stack = [i]\\n \\n while(len(stack)>0):\\n k = stack.pop()\\n neighborhood = neighbors(adj, k)\\n visited[k] = True\\n \\n for n in neighborhood:\\n if not visited[n]:\\n stack.append(n)\\n \\n return(np.where(visited))\\n\\ndef connected_components(adj):\\n n = adj.shape[0]\\n \\n visited = np.array([0 for k in range(n)])\\n s = np.sum(visited)\\n \\n comp=[]\\n \\n while s<n:\\n i = np.where(1-visited)[0][0]\\n \\n cmp = dfs(adj, i)\\n visited[cmp] = 1\\n s = np.sum(visited)\\n \\n comp.append(list(cmp[0]))\\n \\n return(np.array(comp))\\n\\nif __name__ == '__main__':\\n pass\"\n },\n {\n \"alpha_fraction\": 0.5650569796562195,\n \"alphanum_fraction\": 0.5818243026733398,\n \"avg_line_length\": 25.16666603088379,\n \"blob_id\": \"bef4e8073443578ea40a6c86402a1a4e2b8cf5b1\",\n \"content_id\": \"f1a2ab4b4cb3f6e4e80227602e20b69bfd0eb937\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 2982,\n \"license_type\": \"no_license\",\n \"max_line_length\": 100,\n \"num_lines\": 114,\n \"path\": \"/src/utils.py\",\n \"repo_name\": \"JulinaM/Deep-Networks-for-Graph-Representation\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import numpy as np\\nimport torch\\nimport time\\nfrom sklearn.manifold import TSNE\\n\\nimport matplotlib.pyplot as plt\\n\\nfrom sklearn.metrics import roc_auc_score, accuracy_score, confusion_matrix, average_precision_score\\n\\nfrom scipy.spatial.distance import pdist, squareform\\n\\ndef compute_pr_auc(P,S):\\n y_pred = S.clone().detach()\\n\\n y_pred[y_pred < 0.] = 0.\\n y_pred[y_pred > 1.] = 1.\\n \\n y_pred = S.cpu().detach().numpy().reshape((-1,))\\n y_true = P.cpu().detach().numpy().reshape((-1,))\\n\\n return(average_precision_score(y_true, y_pred))\\n\\ndef compute_confusion_matrix(y_true, y_pred):\\n y_pred = y_pred.clone().detach()\\n\\n y_pred[y_pred >= 0.5] = 1.\\n y_pred[y_pred < 0.5] = 0.\\n\\n y_pred = y_pred.cpu().detach().numpy().reshape((-1,))\\n y_true = y_true.cpu().detach().numpy().reshape((-1,))\\n\\n return(confusion_matrix(y_true, y_pred))\\n\\ndef compute_auc(P,S):\\n y_pred = S.clone().detach()\\n\\n y_pred[y_pred < 0.] = 0.\\n y_pred[y_pred > 1.] = 1.\\n\\t\\n y_pred = S.cpu().detach().numpy().reshape((-1,))\\n y_true = P.cpu().detach().numpy().reshape((-1,))\\n\\n return(roc_auc_score(y_true, y_pred))\\n\\ndef compute_accuracy(y_true, y_pred):\\n y_pred = y_pred.clone().detach()\\n\\n y_pred[y_pred >= 0.5] = 1.\\n y_pred[y_pred < 0.5] = 0.\\n\\n y_pred = y_pred.cpu().detach().numpy().reshape((-1,))\\n y_true = y_true.cpu().detach().numpy().reshape((-1,))\\n\\n return(accuracy_score(y_true, y_pred))\\n\\n\\ndef timeit(method):\\n def timed(*args, **kw):\\n ts = time.time()\\n result = method(*args, **kw)\\n te = time.time()\\n if 'log_time' in kw:\\n name = kw.get('log_name', method.__name__.upper())\\n kw['log_time'][name] = int((te - ts) * 1000)\\n else:\\n print('%r %2.2f ms' % \\\\\\n (method.__name__, (te - ts) * 1000))\\n return result\\n return timed\\n\\ndef visualize_TSNE(embeddings,target):\\n tsne = TSNE(n_components=2, init='pca',\\n random_state=0, perplexity=30)\\n data = tsne.fit_transform(embeddings)\\n #plt.figure(figsize=(12, 6))\\n plt.title(\\\"TSNE visualization of the embeddings\\\")\\n plt.scatter(data[:,0],data[:,1],c=target)\\n\\n return\\n\\ndef compute_similarity(net):\\n M = 1 - pdist(net, metric='Jaccard')\\n M = squareform(M)\\n M = M + np.eye(*M.shape)\\n M[np.isnan(M)] = 0.\\n\\n return(M)\\n\\ndef readnet(net_path):\\n\\treturn(np.genfromtxt(net_path,delimiter='\\\\t'))\\n\\ndef extract_samples(K, tensor):\\n \\\"\\\"\\\"\\n Extract K random samples from tensor.\\n\\n Parameters\\n ----------\\n K : int\\n Wanted number of samples\\n tensor : tensor of any size\\n tensor from which extract the samples \\n (the first dimension will be considered as the sample dim)\\n\\n Returns\\n -------\\n samples : tensor of same type as the tensor parameter of shape (K,...)\\n the K samples extracted from tensor\\n\\n \\\"\\\"\\\"\\n perm = torch.randperm(tensor.size(0))\\n idx = perm[:K]\\n samples = tensor[idx]\\n \\n return (samples)\"\n },\n {\n \"alpha_fraction\": 0.5544765591621399,\n \"alphanum_fraction\": 0.5700565576553345,\n \"avg_line_length\": 29.828947067260742,\n \"blob_id\": \"1feb19138e66607907ba3391f057dd6b0549b984\",\n \"content_id\": \"24b18bc730f47568c1cd4e73dceaf10b06d04f34\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 9371,\n \"license_type\": \"no_license\",\n \"max_line_length\": 149,\n \"num_lines\": 304,\n \"path\": \"/src/pu_learner.py\",\n \"repo_name\": \"JulinaM/Deep-Networks-for-Graph-Representation\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import numpy as np\\nimport torch\\nimport torch.autograd as ag\\nimport torch.nn as nn\\nimport torch.optim as optim\\nfrom torchsummary import summary\\nimport torchvision\\nimport torchvision.transforms as transforms\\nimport torchvision.datasets as datasets\\n\\nfrom scipy.optimize import minimize, NonlinearConstraint\\nimport random\\n\\nimport matplotlib.pyplot as plt\\nfrom sklearn.metrics import mean_squared_error\\n\\nfrom math import sqrt\\nimport time\\n\\nfrom autoencoder import *\\nfrom utils import *\\nfrom random_graphs import *\\nfrom dgnr import *\\n\\ndef old_pu_learning(x, y, P, k = 7, alpha = 0.2, gamma = 0.3, maxiter=1000):\\n Fd = x.shape[1]\\n Ft = y.shape[1]\\n Nd = x.shape[0]\\n Nt = y.shape[0]\\n \\n #Number of variables\\n N_variables = Fd * k + Ft * k\\n \\n print(\\\"Number of variables:\\\", N_variables) \\n print(\\\"Finding positive and negative examples...\\\")\\n \\n Ipos = np.where(P==1.)\\n Ineg = np.where(P==0.)\\n\\n print(\\\"Number of positive examples:\\\", Ipos[0].shape[0])\\n print(\\\"Number of negative/unlabelled examples:\\\", Ineg[0].shape[0])\\n \\n alpha_rac = sqrt(alpha)\\n \\n @timeit\\n def objective(z):\\n H = z[:Fd*k].reshape((Fd,k))\\n W = z[-Ft*k:].reshape((Ft,k))\\n \\n M = P - (x @ H @ np.transpose(W) @ np.transpose(y))\\n \\n M[Ineg] *= alpha_rac\\n \\n L = torch.sum(M**2) + gamma/2 * (np.sum(H**2, axis=(0,1)) + np.sum(W**2, axis=(0,1)))\\n print(L)\\n\\n return(L)\\n \\n def constraint(z):\\n H = z[:Fd*k].reshape((Fd,k))\\n W = z[-Ft*k:].reshape((Ft,k))\\n S = x @ H @ np.transpose(W) @ np.transpose(y)\\n S = S.reshape((-1,))\\n \\n return(S)\\n \\n nlc = NonlinearConstraint(constraint, np.zeros(Nt*Nd), np.ones(Nt*Nd))\\n\\n print(\\\"Going to minimize... Maximum number of iterations:\\\", maxiter)\\n res=minimize(objective, x0 = np.random.randn(N_variables), options={'maxiter':maxiter, 'disp':'True'}, constraints=[nlc], method='trust-constr')\\n \\n print(\\\"\\\\n\\\\nSolved.\\\")\\n \\n z=res['x']\\n H = z[:Fd*k].reshape((Fd,k))\\n W = z[-Ft*k:].reshape((Ft,k))\\n\\n print(\\\"Now computing Z=HW^T, then will compute S...\\\")\\n \\n S = x @ H @ np.transpose(W) @ np.transpose(y)\\n \\n return(S)\\n\\ndef pu_learning(x, y, P, pos_train_mask, neg_train_mask, k = 7, alpha = 0.2, gamma = 0.3, maxiter=1000, lr=0.1):\\n Fd = x.shape[1]\\n Ft = y.shape[1]\\n Nd = x.shape[0]\\n Nt = y.shape[0]\\n \\n device = torch.device(\\\"cuda\\\" if torch.cuda.is_available() else \\\"cpu\\\")\\n\\n #Number of variables\\n N_variables = Fd * k + Ft * k\\n \\n print(\\\"Number of variables:\\\", N_variables) \\n print(\\\"Finding positive and negative examples...\\\")\\n \\n P = torch.Tensor(P).to(device)\\n x = torch.Tensor(x).to(device)\\n y = torch.Tensor(y).to(device)\\n \\n x_norm = torch.linalg.norm(x)\\n y_norm = torch.linalg.norm(y)\\n\\n Ipos = pos_train_mask\\n Ineg = neg_train_mask\\n train_mask = torch.logical_or(Ipos,Ineg)\\n\\n print(\\\"Number of positive examples:\\\", P[Ipos].size()[0])\\n print(\\\"Number of negative/unlabelled examples:\\\", P[Ineg].size()[0])\\n \\n alpha_rac = sqrt(alpha)\\n \\n def objective(H,W):\\n M = P - torch.chain_matmul(x, H, torch.transpose(W, 0, 1), torch.transpose(y, 0, 1))\\n \\n M[Ineg] *= alpha_rac\\n M[~train_mask] = 0.\\n \\n L = torch.sum(M**2) + gamma/2 * (torch.sum(H**2) + torch.sum(W**2))\\n\\n return(L)\\n \\n def constraint(z):\\n z = torch.Tensor(z).to(device)\\n H = z[:Fd*k].resize(Fd,k)\\n W = z[-Ft*k:].resize(Ft,k)\\n\\n S = torch.chain_matmul(x, H, torch.transpose(W, 0, 1), torch.transpose(y, 0, 1))\\n S = S.reshape((-1,)).cpu().detach().numpy()\\n \\n return(S)\\n \\n #nlc = NonlinearConstraint(constraint, np.zeros(Nt*Nd), np.ones(Nt*Nd))\\n\\n print(\\\"Going to minimize... Maximum number of iterations:\\\", maxiter)\\n #res=minimize(objective, x0 = np.random.randn(N_variables), options={'maxiter':maxiter, 'disp':'True'}, constraints=[nlc], method='trust-constr')\\n W = ag.Variable(torch.rand(Ft,k).to(device)/y_norm, requires_grad=True)\\n H = ag.Variable(torch.rand(Fd,k).to(device)/x_norm, requires_grad=True)\\n \\n opt = torch.optim.Adam([H,W], lr=lr)\\n\\n for i in range(maxiter):\\n # Zeroing gradients\\n opt.zero_grad()\\n\\n # Evaluating the objective\\n obj = objective(H,W)\\n\\n # Calculate gradients\\n obj.backward() \\n opt.step()\\n if i%1000==0: \\n S = torch.chain_matmul(x, H, torch.transpose(W,0,1), torch.transpose(y,0,1))\\n auc = compute_auc(P[train_mask],S[train_mask])\\n print(\\\"Objective:\\\", obj, \\\"(auc:\\\", auc, \\\")\\\")\\n\\n print(\\\"\\\\n\\\\nSolved.\\\")\\n \\n print(\\\"Now computing Z=HW^T, then will compute S...\\\")\\n \\n S = torch.chain_matmul(x, H, torch.transpose(W,0,1), torch.transpose(y,0,1))\\n \\n return(S, H, W)\\n\\ndef get_train_test_masks(P, train_size=0.8):\\n P = torch.Tensor(P)\\n Ipos = (P == 1.)\\n Ineg = (P == 0.)\\n\\n pos_train = Ipos * torch.rand(P.size())\\n pos_train[Ineg] = 1.\\n pos_train = pos_train < train_size\\n train_neg_rel_size = torch.sum(pos_train) / torch.sum(Ineg)\\n \\n neg_train = Ineg * torch.rand(P.size())\\n neg_train[Ipos] = 1.\\n neg_train = neg_train < train_neg_rel_size\\n\\n train = pos_train + neg_train\\n test = ~train\\n pos_test = torch.logical_and(test, Ipos)\\n neg_test = torch.logical_and(test, Ineg)\\n\\n return(pos_train, neg_train, pos_test, neg_test)\\n\\ndef new_pu_learning(x, y, P, k = 7, alpha = 0.2, gamma = 0.3, maxiter=1000, lr=1e-3, batch_size=100):\\n Fd = x.shape[1]\\n Ft = y.shape[1]\\n Nd = x.shape[0]\\n Nt = y.shape[0]\\n \\n device = torch.device(\\\"cuda\\\" if torch.cuda.is_available() else \\\"cpu\\\")\\n\\n #Number of variables\\n N_variables = Fd * k + Ft * k\\n N_examples = Nd*Nt\\n \\n P = torch.Tensor(P).to(device)\\n cartesian_product = torch.Tensor([[u, v] for u in x for v in y]).to(device)\\n \\n print(\\\"Spliting train and test sets...\\\")\\n pos_train, neg_train, pos_test, neg_test = get_train_test_masks(P, train_size=0.8)\\n\\n train_mask = torch.logical_or(pos_train, neg_train)\\n\\n flat_train_mask = train_mask.flatten()\\n\\n print(\\\"Building the train loader...\\\")\\n train = torch.utils.data.TensorDataset(cartesian_product[flat_train_mask], P[train_mask].flatten())\\n train_loader = torch.utils.data.DataLoader(train, batch_size=batch_size, shuffle=False)\\n\\n print(\\\"Number of variables:\\\", N_variables)\\n print(\\\"Finding positive and negative examples...\\\")\\n \\n x = torch.Tensor(x).to(device)\\n y = torch.Tensor(y).to(device)\\n \\n print(\\\"Number of train examples:\\\", P.size()[0])\\n print(\\\"Number of positive examples in train set:\\\", P[pos_train].size()[0])\\n print(\\\"Number of negative/unlabelled examples in train set:\\\", P[neg_train].size()[0])\\n \\n alpha_rac = sqrt(alpha)\\n \\n def objective(a, H, W, b, P):\\n M = P.clone().detach()\\n for i in range(P.size()[0]):\\n s = torch.chain_matmul(a[i].reshape(1,Fd), H, torch.transpose(W, 0, 1), torch.transpose(b[i].reshape(1,Ft), 0, 1))\\n M[i] -= s.item()\\n\\n Ineg = (P==0.)\\n\\n M[Ineg] *= alpha_rac\\n \\n L = torch.mean(M**2) + gamma/2 * (torch.sum(H**2) + torch.sum(W**2))\\n\\n return(L)\\n \\n def objective_prime(a, H, W, b, P):\\n M = P - torch.einsum('ij,jk,kl,li->i', a, H, torch.transpose(W, 0, 1), torch.transpose(b, 0, 1))\\n \\n Ineg = (P==0.)\\n\\n M[Ineg] *= alpha_rec\\n L = torch.mean(M**2) + gamma/2 * (torch.sum(H**2) + torch.sum(W**2))\\n\\n return(L)\\n\\n def total_loss(x,H,W,y,P):\\n M = P - torch.chain_matmul(x, H, torch.transpose(W, 0, 1), torch.transpose(y, 0, 1))\\n\\n M[~train_mask] = 0.\\n\\n M[neg_train] *= alpha_rac\\n\\n L = torch.mean(M**2) + gamma/2 * (torch.sum(H**2) + torch.sum(W**2))\\n\\n return(L)\\n\\n print(\\\"Going to minimize... Maximum number of epochs:\\\", maxiter)\\n \\n W = torch.zeros(Ft,k).to(device)\\n W /= torch.linalg.norm(W)*torch.linalg.norm(y) #for initial W and H not to be too big\\n H = torch.zeros(Fd,k).to(device)\\n H /= torch.linalg.norm(H)*torch.linalg.norm(x)\\n\\n W = ag.Variable(W, requires_grad=True)\\n H = ag.Variable(H, requires_grad=True)\\n \\n opt = torch.optim.Adam([H,W], lr=lr)\\n \\n batch_num = N_examples//batch_size\\n\\n for k in range(maxiter):\\n for i, batch in enumerate(train_loader, 0):\\n # Zeroing gradients\\n opt.zero_grad()\\n\\n inputs, labels = batch\\n\\n a, b = inputs[:,0,:], inputs[:,1,:]\\n \\n # Evaluating the objective\\n obj = objective(a,H,W,b,labels)\\n\\n # Calculate gradients\\n obj.backward() \\n opt.step()\\n \\n if i%(batch_size//4) == 0:\\n S = torch.chain_matmul(x, H, torch.transpose(W,0,1), torch.transpose(y,0,1))\\n stdm = torch.std(S[train_mask])\\n auc = compute_auc(P[train_mask],S[train_mask])\\n loss = total_loss(x,H,W,y,P)\\n\\n print(\\\"[epoch=\\\",k,\\\", batch_num=\\\",i,\\\"]\\\",\\\"Objective: \\\", loss.item(), \\\"(standard deviation: \\\", stdm.item(), \\\", auc: \\\", auc.item(), \\\")\\\")\\n\\n print(\\\"\\\\n\\\\nSolved.\\\")\\n \\n print(\\\"Now computing Z=HW^T, then will compute S...\\\")\\n \\n S = torch.chain_matmul(x, H, torch.transpose(W,0,1), torch.transpose(y,0,1))\\n \\n return(S, H, W)\"\n },\n {\n \"alpha_fraction\": 0.5642725825309753,\n \"alphanum_fraction\": 0.5769230723381042,\n \"avg_line_length\": 34.26258850097656,\n \"blob_id\": \"4f9305052e62adc12225284a46cfae829924c69c\",\n \"content_id\": \"4707245c67a3e5d43eb3d30d2e3924f81b39cec2\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 9802,\n \"license_type\": \"no_license\",\n \"max_line_length\": 171,\n \"num_lines\": 278,\n \"path\": \"/src/pu_learning.py\",\n \"repo_name\": \"JulinaM/Deep-Networks-for-Graph-Representation\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import torch\\nimport torch.nn as nn\\nimport torch.optim as optim\\n\\nfrom math import sqrt\\nfrom sklearn.model_selection import KFold\\n\\nfrom autoencoder import *\\nfrom utils import *\\nfrom random_graphs import *\\nfrom dgnr import *\\n\\ndef get_train_test_masks(P, train_size=0.8, test_balance=True):\\n P = torch.Tensor(P)\\n Ipos = (P == 1.)\\n Ineg = (P == 0.)\\n\\n pos_train = Ipos * torch.rand(P.size())\\n pos_train[Ineg] = 1.\\n pos_train = pos_train < train_size\\n train_neg_rel_size = torch.sum(pos_train) / torch.sum(Ineg)\\n \\n neg_train = Ineg * torch.rand(P.size())\\n neg_train[Ipos] = 1.\\n neg_train = neg_train < train_neg_rel_size\\n\\n train = pos_train + neg_train\\n\\n if not test_balance:\\n test = ~train\\n pos_test = torch.logical_and(test, Ipos)\\n neg_test = torch.logical_and(test, Ineg)\\n else:\\n test = ~train\\n pos_test = torch.logical_and(test,Ipos)\\n neg_test = torch.logical_and(test, Ineg)\\n\\n num_pos_test = torch.sum(pos_test)\\n test_neg_rel_size = num_pos_test / torch.sum(neg_test)\\n \\n neg_test = neg_test * torch.rand(P.size())\\n neg_test[train] = 1.\\n neg_test[Ipos] = 1.\\n \\n neg_test = neg_test < test_neg_rel_size\\n\\n return(pos_train, neg_train, pos_test, neg_test)\\n\\nclass CustomMSELoss(nn.Module):\\n def __init__(self, alpha=0.2):\\n super(CustomMSELoss, self).__init__()\\n self.alpha=sqrt(alpha)\\n\\n def forward(self, inputs, targets):\\n #comment out if your model contains a sigmoid or equivalent activation layer\\n neg_mask = (targets == 0.)\\n \\n M = (targets-inputs)**2\\n M[neg_mask] *= self.alpha\\n\\n loss_res = torch.mean(M)\\n\\n return loss_res\\n\\nclass PU_Learner(nn.Module):\\n def __init__(self, k, Fd, Ft, X, Y, Nd, Nt, activation='identity', has_bias=False):\\n super().__init__()\\n self.k = k\\n self.Fd = Fd\\n self.Ft = Ft\\n \\n self.H = torch.nn.Parameter(torch.randn(Fd, k)*1/sqrt(k))\\n self.W = torch.nn.Parameter(torch.randn(k, Ft)*1/sqrt(k))\\n if not has_bias:\\n self.b_x = torch.zeros(Nd)\\n self.b_y = torch.zeros(Nt)\\n else:\\n self.b_x = torch.nn.Parameter(torch.randn(Nd))\\n self.b_y = torch.nn.Parameter(torch.randn(Nt))\\n\\n self.X = (X - X.mean(0))/(X.std(0)+1e-7)\\n self.Y = (Y - Y.mean(0))/(Y.std(0)+1e-7)\\n\\n activ_dict = {'sigmoid': torch.nn.Sigmoid, 'identity': torch.nn.Identity}\\n self.activation = activ_dict[activation]()\\n\\n def forward(self, id_x, id_y):\\n \\tdot = torch.einsum('ij,jk,kl,li->i', self.X[id_x], self.H, self.W, torch.transpose(self.Y[id_y], 1, 0))\\n\\n \\treturn(self.activation(dot + self.b_x[id_x] + self.b_y[id_y]))\\n\\ndef pu_learning(k, x, y, P, pos_train, neg_train, pos_test, neg_test, n_epochs=100, batch_size=100, lr=1e-3, alpha=1.0, gamma=0., activation='identity'):\\n #hidden_layers=[500,200,100]\\n #input_numer=784\\n # use gpu if available\\n device = torch.device(\\\"cuda\\\" if torch.cuda.is_available() else \\\"cpu\\\")\\n\\n Fd = x.shape[1]\\n Ft = y.shape[1]\\n Nd = x.shape[0]\\n Nt = y.shape[0]\\n \\n #Number of variables\\n N_variables = Fd * k + Ft * k\\n\\n cartesian_product = torch.Tensor([[i, j] for i in range(Nd) for j in range(Nt)]).long().to(device)\\n\\n x = torch.Tensor(x).to(device)\\n y = torch.Tensor(y).to(device)\\n\\n P = torch.Tensor(P).to(device)\\n\\n train_mask = torch.logical_or(pos_train, neg_train)\\n test_mask = torch.logical_or(pos_test, neg_test)\\n flat_train_mask = train_mask.flatten()\\n\\n print(\\\"Building the train loader...\\\")\\n train = torch.utils.data.TensorDataset(cartesian_product[flat_train_mask], P[train_mask].flatten())\\n train_loader = torch.utils.data.DataLoader(train, batch_size=batch_size, shuffle=True)\\n \\n batch_num = len(train_loader)\\n\\n print(\\\"Number of variables:\\\", N_variables)\\n print(\\\"Finding positive and negative examples...\\\") \\n\\n print(\\\"Number of train examples:\\\", P[train_mask].size()[0])\\n print(\\\"Number of positive examples in train set:\\\", P[pos_train].size()[0])\\n print(\\\"Number of negative/unlabelled examples in train set:\\\", P[neg_train].size()[0])\\n\\n model = PU_Learner(k, Fd, Ft, x, y, Nd, Nt, activation=activation).to(device)\\n\\n # create an optimizer object\\n # Adam optimizer with learning rate 1e-3\\n optimizer = optim.Adam(model.parameters(), lr=lr, weight_decay=gamma)\\n\\n # mean-squared error loss\\n criterion = CustomMSELoss(alpha=alpha)\\n\\n for epoch in range(n_epochs): # loop over the dataset multiple times\\n\\n running_loss = 0.0\\n for i, data in enumerate(train_loader, 0):\\n # get the inputs; data is a list of [inputs, labels]\\n inputs, labels = data\\n \\n inputs=inputs.to(device)\\n \\n id_x_batch, id_y_batch = inputs[:,0], inputs[:,1]\\n\\n # zero the parameter gradients\\n optimizer.zero_grad()\\n\\n # forward + backward + optimize\\n outputs = model(id_x_batch, id_y_batch)\\n \\n loss = criterion(outputs, labels)\\n loss.backward()\\n optimizer.step()\\n\\n # print statistics\\n running_loss += loss.item()\\n \\n S = model.activation(torch.chain_matmul(model.X, model.H, model.W, torch.transpose(model.Y,0,1)) + model.b_x.unsqueeze(-1).expand(-1,Nt) + model.b_y.expand(Nd,-1))\\n \\\"\\\"\\\"print(S)\\n print(model.H)\\n print(model.W)\\n print(model.b_x)\\n print(model.b_y)\\\"\\\"\\\"\\n auc = compute_auc(P[train_mask].clone(), S[train_mask].clone())\\n acc = compute_accuracy(P[train_mask].clone(), S[train_mask].clone())\\n\\n print('[%d] loss: %.3f, auc: %.3f, acc: %.3f' %\\n (epoch + 1, running_loss / (batch_num), auc, acc))\\n running_loss = 0.0\\n\\n print('Finished Training')\\n print(\\\"Now computing Z=HW^T, then will compute S...\\\")\\n \\n print(x.size(), model.H.size(), model.W.size(), y.size())\\n S = model.activation(torch.chain_matmul(model.X, model.H, model.W, torch.transpose(model.Y,0,1)) + model.b_x.unsqueeze(-1).expand(-1,Nt) + model.b_y.expand(Nd,-1))\\n \\n return(S, model.H, model.W, model.b_x, model.b_y, train_mask, test_mask)\\n\\ndef pu_learning_new(k, x, y, P, n_epochs=100, batch_size=100, lr=1e-5, train_size=0.8, alpha=1.0, gamma=0., test_balance=True, activation='identity'):\\n print(\\\"Spliting train and test sets...\\\")\\n pos_train, neg_train, pos_test, neg_test = get_train_test_masks(P, train_size=train_size, test_balance=test_balance)\\n \\n return(pu_learning(k, x, y, P, pos_train, neg_train, pos_test, neg_test, \\n n_epochs=n_epochs, batch_size=batch_size, lr=lr, \\n alpha=alpha, gamma=gamma, activation=activation))\\n\\ndef cross_validate(k, x, y, P, N_folds, n_epochs=100, batch_size=100, lr=1e-5, train_size=0.8, alpha=1.0, gamma=0., activation='identity'):\\n pos_mask = (P==1)\\n neg_mask = (P==0)\\n \\n N_pos = pos_mask.sum()\\n N_neg = neg_mask.sum()\\n \\n N = min(N_pos, N_neg)\\n \\n pos_idx = pos_mask.nonzero()\\n neg_idx = neg_mask.nonzero()\\n \\n pos_idx = extract_samples(N, pos_idx)\\n neg_idx = extract_samples(N, neg_idx)\\n \\n kfold = KFold(n_splits=N_folds, shuffle=False)\\n \\n kfold_pos = list(kfold.split(pos_idx))\\n kfold_neg = list(kfold.split(neg_idx))\\n \\n S_auc = 0\\n S_acc = 0\\n S_pr = 0\\n \\n S_sol = 0\\n\\n for fold in range(N_folds):\\n print(\\\"Fold %d\\\" % (fold+1))\\n print(\\\"Preparing the masks...\\\")\\n pos_train_idx = pos_idx[kfold_pos[fold][0]]\\n #print(pos_train_idx.max(0))\\n pos_test_idx = pos_idx[kfold_pos[fold][1]]\\n neg_train_idx = neg_idx[kfold_neg[fold][0]]\\n neg_test_idx = neg_idx[kfold_neg[fold][1]]\\n \\n pos_train_mask = torch.zeros(pos_mask.size(),dtype=bool)\\n pos_train_mask[pos_train_idx[:,0],pos_train_idx[:,1]] = True\\n \\n pos_test_mask = torch.zeros(pos_mask.size(),dtype=bool)\\n pos_test_mask[pos_test_idx[:,0],pos_test_idx[:,1]] = True\\n \\n neg_train_mask = torch.zeros(neg_mask.size(),dtype=bool)\\n neg_train_mask[neg_train_idx[:,0],neg_train_idx[:,1]] = True\\n \\n neg_test_mask = torch.zeros(neg_mask.size(),dtype=bool)\\n neg_test_mask[neg_test_idx[:,0],neg_test_idx[:,1]] = True\\n \\n test_mask = torch.logical_or(pos_test_mask, neg_test_mask)\\n \\n print(\\\"Starting to learn...\\\")\\n S, H, W, b_x, b_y, _, _ = pu_learning(k, x, y, P, \\n pos_train_mask, neg_train_mask, pos_test_mask, neg_test_mask, \\n n_epochs=n_epochs, batch_size=batch_size, lr=lr, \\n alpha=alpha, gamma=gamma, activation=activation)\\n \\n print(\\\"Evaluating on test set...\\\")\\n auc, pr, acc, _ = eval_test_set(P, S, test_mask)\\n \\n S_auc += auc\\n S_acc += acc\\n S_pr += pr\\n\\n S_sol += S * auc\\n\\n return(S_sol/S_auc, S_auc/N_folds, S_pr/N_folds, S_acc/N_folds)\\n\\ndef eval_test_set(P, S, test):\\n print(\\\"Evaluation on the test set...\\\")\\n print(\\\"Test set statistics:\\\")\\n n_pos = int(P[test].sum().item())\\n n_neg = int((1-P[test]).sum().item())\\n\\n print(\\\"Number of positive examples:\\\", n_pos)\\n print(\\\"Number of negative/unlabelled examples:\\\", n_neg)\\n \\n auc = compute_auc(P[test],S[test])\\n pr = compute_pr_auc(P[test], S[test])\\n acc = compute_accuracy(P[test],S[test])\\n confusion = compute_confusion_matrix(P[test], S[test])\\n \\n print(\\\"\\\\nROC auc: %f\\\" % auc)\\n print(\\\"PR auc: %f\\\" % pr)\\n print(\\\"Accuracy: %f\\\" % acc)\\n print(\\\"Confusion matrix:\\\")\\n print(confusion)\\n \\n return(auc,pr,acc,confusion)\"\n }\n]"},"num_files":{"kind":"number","value":6,"string":"6"}}},{"rowIdx":2052,"cells":{"repo_name":{"kind":"string","value":"tebeka/rs2019-words"},"repo_url":{"kind":"string","value":"https://github.com/tebeka/rs2019-words"},"snapshot_id":{"kind":"string","value":"aa24557f2697ce28fecb8d1941810d7588a7b9dc"},"revision_id":{"kind":"string","value":"8f26e1c2d6c14a4167ebada3a60f144c426408aa"},"directory_id":{"kind":"string","value":"6e5f7ac5a27c0f811ab516c283125436f23921a8"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"string","value":"2022-06-26T20:30:54.134796"},"revision_date":{"kind":"string","value":"2022-06-14T06:41:50"},"committer_date":{"kind":"string","value":"2022-06-14T06:41:50"},"github_id":{"kind":"number","value":175226520,"string":"175,226,520"},"star_events_count":{"kind":"number","value":1,"string":"1"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"string","value":"BSD-3-Clause"},"gha_created_at":{"kind":"string","value":"2019-03-12T14:16:43"},"gha_updated_at":{"kind":"string","value":"2021-12-26T06:14:27"},"gha_pushed_at":{"kind":"string","value":"2022-06-14T06:41:55"},"gha_language":{"kind":"string","value":"Python"},"files":{"kind":"list like","value":[{"alpha_fraction":0.6830188632011414,"alphanum_fraction":0.7283018827438354,"avg_line_length":13.722222328186035,"blob_id":"f1a1fbb62e5cc9aeabee13d0de78dfa68857d530","content_id":"ac398db76ef4766a42fd0f75de22839c50cdaf58","detected_licenses":["BSD-3-Clause"],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":265,"license_type":"permissive","max_line_length":86,"num_lines":18,"path":"/README.md","repo_name":"tebeka/rs2019-words","src_encoding":"UTF-8","text":"# Reversim 2019 Top Words\n\nA small survey on [Reversim 2019 proposals](https://summit2019.reversim.com/proposals)\n\nResults [here](words.txt)\n\n## Depedencies\n\nSee [requirements.txt](requirements.txt)\n\n## Running\n\n python words.py\n\n\n## Licence\n\n[BSD](LICENSE.txt)\n"},{"alpha_fraction":0.6297151446342468,"alphanum_fraction":0.6420323252677917,"avg_line_length":23.50943374633789,"blob_id":"01c4c9c37429976de3112dd6fe2ed7054208890c","content_id":"0b2ba6c65a657267e8507ecb1fac89f47c8093eb","detected_licenses":["BSD-3-Clause"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1299,"license_type":"permissive","max_line_length":69,"num_lines":53,"path":"/words.py","repo_name":"tebeka/rs2019-words","src_encoding":"UTF-8","text":"import bz2\nfrom collections import Counter\n\nimport spacy\nfrom bs4 import BeautifulSoup\nfrom spacy.parts_of_speech import PUNCT, SPACE, SYM\n\n\ndef is_word(tok):\n if tok.is_stop:\n return False\n if tok.pos in {PUNCT, SPACE, SYM}:\n return False\n\n text = tok.text\n if text in stop_words:\n return False\n\n # \"that's\" is tokenized to [\"that\", \"'s\"]\n return text[:1].isalnum()\n\n\ndef top_words(nlp, words, n=20):\n text = '\\n'.join(words)\n doc = nlp(text)\n counts = Counter(tok.text.lower() for tok in doc if is_word(tok))\n total = sum(counts.values())\n for word, count in counts.most_common(40):\n percent = count / total * 100\n print(f'{word:<20}{percent:.2f}%')\n\n\nnlp = spacy.load('en')\n# Custom(?) stop words\nstop_words = {'i', 'in', 'talk', 'we', 'the', 'it'}\n\nwith bz2.open('proposals.html.bz2') as fp:\n soup = BeautifulSoup(fp, 'lxml')\n\ntitles = soup('h4')\nprint(f'Total of {len(titles)} submissions')\n\ntitle_words = [t.text.lower() for t in titles]\nprint('\\nTitle words:')\ntop_words(nlp, title_words)\n\nabstracts = soup('div', class_='session__abstract')\nabstract_words = [a.text.lower() for a in abstracts]\nprint('\\nAbstract words:')\ntop_words(nlp, abstract_words)\n\nprint('\\nAll words:')\ntop_words(nlp, title_words + abstract_words)\n"},{"alpha_fraction":0.460317462682724,"alphanum_fraction":0.6190476417541504,"avg_line_length":14.75,"blob_id":"8ca3362c460059ba6057e362c4cf70c590fcf285","content_id":"27071f01ad5ecb9e25f1944825710610b4eeccf4","detected_licenses":["BSD-3-Clause"],"is_generated":false,"is_vendor":false,"language":"Text","length_bytes":63,"license_type":"permissive","max_line_length":22,"num_lines":4,"path":"/requirements.txt","repo_name":"tebeka/rs2019-words","src_encoding":"UTF-8","text":"beautifulsoup4 ~= 4.11\nipython ~= 8.4\nspacy ~= 3.3\nlxml ~= 4.9\n"}],"string":"[\n {\n \"alpha_fraction\": 0.6830188632011414,\n \"alphanum_fraction\": 0.7283018827438354,\n \"avg_line_length\": 13.722222328186035,\n \"blob_id\": \"f1a1fbb62e5cc9aeabee13d0de78dfa68857d530\",\n \"content_id\": \"ac398db76ef4766a42fd0f75de22839c50cdaf58\",\n \"detected_licenses\": [\n \"BSD-3-Clause\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 265,\n \"license_type\": \"permissive\",\n \"max_line_length\": 86,\n \"num_lines\": 18,\n \"path\": \"/README.md\",\n \"repo_name\": \"tebeka/rs2019-words\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# Reversim 2019 Top Words\\n\\nA small survey on [Reversim 2019 proposals](https://summit2019.reversim.com/proposals)\\n\\nResults [here](words.txt)\\n\\n## Depedencies\\n\\nSee [requirements.txt](requirements.txt)\\n\\n## Running\\n\\n python words.py\\n\\n\\n## Licence\\n\\n[BSD](LICENSE.txt)\\n\"\n },\n {\n \"alpha_fraction\": 0.6297151446342468,\n \"alphanum_fraction\": 0.6420323252677917,\n \"avg_line_length\": 23.50943374633789,\n \"blob_id\": \"01c4c9c37429976de3112dd6fe2ed7054208890c\",\n \"content_id\": \"0b2ba6c65a657267e8507ecb1fac89f47c8093eb\",\n \"detected_licenses\": [\n \"BSD-3-Clause\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1299,\n \"license_type\": \"permissive\",\n \"max_line_length\": 69,\n \"num_lines\": 53,\n \"path\": \"/words.py\",\n \"repo_name\": \"tebeka/rs2019-words\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import bz2\\nfrom collections import Counter\\n\\nimport spacy\\nfrom bs4 import BeautifulSoup\\nfrom spacy.parts_of_speech import PUNCT, SPACE, SYM\\n\\n\\ndef is_word(tok):\\n if tok.is_stop:\\n return False\\n if tok.pos in {PUNCT, SPACE, SYM}:\\n return False\\n\\n text = tok.text\\n if text in stop_words:\\n return False\\n\\n # \\\"that's\\\" is tokenized to [\\\"that\\\", \\\"'s\\\"]\\n return text[:1].isalnum()\\n\\n\\ndef top_words(nlp, words, n=20):\\n text = '\\\\n'.join(words)\\n doc = nlp(text)\\n counts = Counter(tok.text.lower() for tok in doc if is_word(tok))\\n total = sum(counts.values())\\n for word, count in counts.most_common(40):\\n percent = count / total * 100\\n print(f'{word:<20}{percent:.2f}%')\\n\\n\\nnlp = spacy.load('en')\\n# Custom(?) stop words\\nstop_words = {'i', 'in', 'talk', 'we', 'the', 'it'}\\n\\nwith bz2.open('proposals.html.bz2') as fp:\\n soup = BeautifulSoup(fp, 'lxml')\\n\\ntitles = soup('h4')\\nprint(f'Total of {len(titles)} submissions')\\n\\ntitle_words = [t.text.lower() for t in titles]\\nprint('\\\\nTitle words:')\\ntop_words(nlp, title_words)\\n\\nabstracts = soup('div', class_='session__abstract')\\nabstract_words = [a.text.lower() for a in abstracts]\\nprint('\\\\nAbstract words:')\\ntop_words(nlp, abstract_words)\\n\\nprint('\\\\nAll words:')\\ntop_words(nlp, title_words + abstract_words)\\n\"\n },\n {\n \"alpha_fraction\": 0.460317462682724,\n \"alphanum_fraction\": 0.6190476417541504,\n \"avg_line_length\": 14.75,\n \"blob_id\": \"8ca3362c460059ba6057e362c4cf70c590fcf285\",\n \"content_id\": \"27071f01ad5ecb9e25f1944825710610b4eeccf4\",\n \"detected_licenses\": [\n \"BSD-3-Clause\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Text\",\n \"length_bytes\": 63,\n \"license_type\": \"permissive\",\n \"max_line_length\": 22,\n \"num_lines\": 4,\n \"path\": \"/requirements.txt\",\n \"repo_name\": \"tebeka/rs2019-words\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"beautifulsoup4 ~= 4.11\\nipython ~= 8.4\\nspacy ~= 3.3\\nlxml ~= 4.9\\n\"\n }\n]"},"num_files":{"kind":"number","value":3,"string":"3"}}},{"rowIdx":2053,"cells":{"repo_name":{"kind":"string","value":"nihar-mukhiya/text-generator"},"repo_url":{"kind":"string","value":"https://github.com/nihar-mukhiya/text-generator"},"snapshot_id":{"kind":"string","value":"af2a5ecad74d9b94132a8547d94672117394f954"},"revision_id":{"kind":"string","value":"2d34ca11e6e8e34a1891a7fdaf5d2e988dc51714"},"directory_id":{"kind":"string","value":"15959118ecbb6a497806ef426bc2c4739a7ef7eb"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"string","value":"2020-03-28T08:20:18.200660"},"revision_date":{"kind":"string","value":"2018-09-10T09:55:08"},"committer_date":{"kind":"string","value":"2018-09-10T09:55:08"},"github_id":{"kind":"number","value":147958582,"string":"147,958,582"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.419205904006958,"alphanum_fraction":0.4302862286567688,"avg_line_length":12.064934730529785,"blob_id":"8536907f601ed9ae8b9c979a9c232c35961a4766","content_id":"be18b0ccb0a24c3cd70d9aa7cdfee271c25c62b9","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1083,"license_type":"no_license","max_line_length":48,"num_lines":77,"path":"/tg.py","repo_name":"nihar-mukhiya/text-generator","src_encoding":"UTF-8","text":"\r\nimport pprint\r\n\r\n\r\n\r\nf = open(\"test.txt\")\r\nmessage = f.read()\r\nlist = message.split()\r\n#print(list)\r\ncounts = {}\r\nprint(list)\r\nstart_at = -1\r\ni = 1\r\nmy_set = set(list)\r\nfor w in my_set:\r\n print(w)\r\n w = {}\r\nprint(w)\r\nfor word in list:\r\n if(word not in counts.keys()):\r\n p = list.index(word, start_at + 1)\r\n start_at = p\r\n p+=1\r\n\r\n\r\n\r\n\r\n else:\r\n if(list.index(word) != (len(list) - 1)):\r\n p =list.index(word, start_at + 1)\r\n\r\n p+=1\r\n else:\r\n p = list.index(word)\r\n\r\n\r\n\r\n m = (list[p])\r\n\r\n w[i] = m\r\n i+=1\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n #counts[word] = []\r\n #counts[word] = p\r\n #print(counts[word])\r\n\"\"\"\r\n if word in counts:\r\n\r\n counts[word] += 1\r\n p = list.index(word, start_at + 1)\r\n start_at = p\r\n\r\n print(p)\r\n else:\r\n\r\n counts[word] = 1\r\n #print(counts)\r\n #p = list.index(word)\r\n #print(p)\r\n print(counts)\r\n\r\n p+=1\r\n print(p)\r\n next = list[p]\r\n print(next)\r\n #pprint.pprint(counts)\r\n\r\n\"\"\""},{"alpha_fraction":0.45306122303009033,"alphanum_fraction":0.5061224699020386,"avg_line_length":13.4375,"blob_id":"d204769b195a01d1edc148998b1dbedabed1b6ed","content_id":"9e23f67f4ffee3464aead1b10299ccb5fe02b56e","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":245,"license_type":"no_license","max_line_length":55,"num_lines":16,"path":"/matmul.py","repo_name":"nihar-mukhiya/text-generator","src_encoding":"UTF-8","text":"\"\"\"\r\n\r\nthis program displays probability\r\n\r\n\r\nimport numpy as np\r\na = [0.6, 0.4]\r\n\r\nb = [[0.7, 0.3], [0.6, 0.4]]\r\nn = int(input(\"prediction of how many ahead u want: \"))\r\nwhile(n):\r\n x = np.matmul(a, b)\r\n a = x\r\n n-=1\r\n print(x)\r\n\"\"\""}],"string":"[\n {\n \"alpha_fraction\": 0.419205904006958,\n \"alphanum_fraction\": 0.4302862286567688,\n \"avg_line_length\": 12.064934730529785,\n \"blob_id\": \"8536907f601ed9ae8b9c979a9c232c35961a4766\",\n \"content_id\": \"be18b0ccb0a24c3cd70d9aa7cdfee271c25c62b9\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1083,\n \"license_type\": \"no_license\",\n \"max_line_length\": 48,\n \"num_lines\": 77,\n \"path\": \"/tg.py\",\n \"repo_name\": \"nihar-mukhiya/text-generator\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"\\r\\nimport pprint\\r\\n\\r\\n\\r\\n\\r\\nf = open(\\\"test.txt\\\")\\r\\nmessage = f.read()\\r\\nlist = message.split()\\r\\n#print(list)\\r\\ncounts = {}\\r\\nprint(list)\\r\\nstart_at = -1\\r\\ni = 1\\r\\nmy_set = set(list)\\r\\nfor w in my_set:\\r\\n print(w)\\r\\n w = {}\\r\\nprint(w)\\r\\nfor word in list:\\r\\n if(word not in counts.keys()):\\r\\n p = list.index(word, start_at + 1)\\r\\n start_at = p\\r\\n p+=1\\r\\n\\r\\n\\r\\n\\r\\n\\r\\n else:\\r\\n if(list.index(word) != (len(list) - 1)):\\r\\n p =list.index(word, start_at + 1)\\r\\n\\r\\n p+=1\\r\\n else:\\r\\n p = list.index(word)\\r\\n\\r\\n\\r\\n\\r\\n m = (list[p])\\r\\n\\r\\n w[i] = m\\r\\n i+=1\\r\\n\\r\\n\\r\\n\\r\\n\\r\\n\\r\\n\\r\\n\\r\\n\\r\\n\\r\\n\\r\\n\\r\\n #counts[word] = []\\r\\n #counts[word] = p\\r\\n #print(counts[word])\\r\\n\\\"\\\"\\\"\\r\\n if word in counts:\\r\\n\\r\\n counts[word] += 1\\r\\n p = list.index(word, start_at + 1)\\r\\n start_at = p\\r\\n\\r\\n print(p)\\r\\n else:\\r\\n\\r\\n counts[word] = 1\\r\\n #print(counts)\\r\\n #p = list.index(word)\\r\\n #print(p)\\r\\n print(counts)\\r\\n\\r\\n p+=1\\r\\n print(p)\\r\\n next = list[p]\\r\\n print(next)\\r\\n #pprint.pprint(counts)\\r\\n\\r\\n\\\"\\\"\\\"\"\n },\n {\n \"alpha_fraction\": 0.45306122303009033,\n \"alphanum_fraction\": 0.5061224699020386,\n \"avg_line_length\": 13.4375,\n \"blob_id\": \"d204769b195a01d1edc148998b1dbedabed1b6ed\",\n \"content_id\": \"9e23f67f4ffee3464aead1b10299ccb5fe02b56e\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 245,\n \"license_type\": \"no_license\",\n \"max_line_length\": 55,\n \"num_lines\": 16,\n \"path\": \"/matmul.py\",\n \"repo_name\": \"nihar-mukhiya/text-generator\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"\\\"\\\"\\\"\\r\\n\\r\\nthis program displays probability\\r\\n\\r\\n\\r\\nimport numpy as np\\r\\na = [0.6, 0.4]\\r\\n\\r\\nb = [[0.7, 0.3], [0.6, 0.4]]\\r\\nn = int(input(\\\"prediction of how many ahead u want: \\\"))\\r\\nwhile(n):\\r\\n x = np.matmul(a, b)\\r\\n a = x\\r\\n n-=1\\r\\n print(x)\\r\\n\\\"\\\"\\\"\"\n }\n]"},"num_files":{"kind":"number","value":2,"string":"2"}}},{"rowIdx":2054,"cells":{"repo_name":{"kind":"string","value":"beallio/media-server-status"},"repo_url":{"kind":"string","value":"https://github.com/beallio/media-server-status"},"snapshot_id":{"kind":"string","value":"6c23ba34c5b81f291f20a803db0e3e5d9ba249fa"},"revision_id":{"kind":"string","value":"50936dd807cc3bccf40f6521cf00c35413bf6ed2"},"directory_id":{"kind":"string","value":"49a664d37799db9d9e93208939afa9d19632ef1b"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"string","value":"2021-01-13T02:37:23.340474"},"revision_date":{"kind":"string","value":"2015-01-04T07:15:47"},"committer_date":{"kind":"string","value":"2015-01-04T07:15:47"},"github_id":{"kind":"number","value":24974710,"string":"24,974,710"},"star_events_count":{"kind":"number","value":2,"string":"2"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.5072992444038391,"alphanum_fraction":0.6970803141593933,"avg_line_length":15.606060981750488,"blob_id":"00bfae7cfef839c25e4111d932eb99e7d1dfacd7","content_id":"e570a145f75e6306ec40d9083497f68d6bd8992b","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Text","length_bytes":548,"license_type":"no_license","max_line_length":24,"num_lines":33,"path":"/requirements.txt","repo_name":"beallio/media-server-status","src_encoding":"UTF-8","text":"Babel==1.3\nFlask==0.10.1\nFlask-Assets==0.10\nFlask-Babel==0.9\nFlask-Images==2.0.0\nFlask-Mail==0.9.0\nFlask-OpenID==1.2.1\nFlask-SQLAlchemy==2.0\nFlask-WTF==0.10.2\nJinja2==2.7.3\nMarkupSafe==0.23\nPIL==1.1.7\nPillow==2.5.3\nSQLAlchemy==0.9.7\nWTForms==2.0.1\nWerkzeug==0.9.6\nargparse==1.2.1\nblinker==1.3\ncertifi==14.05.14\nflup==1.0.2\ngunicorn==19.1.1\nitsdangerous==0.24\npillowcase==2.0.0\npsutil==2.1.1\npy-sonic==0.2.2\npython-forecastio==1.2.1\npython-openid==2.2.5\npytz==2014.7\nrequests==2.4.0\nspeaklater==1.3\nwebassets==0.10.1\nwsgiref==0.1.2\nxmltodict==0.9.0\n"},{"alpha_fraction":0.7245013117790222,"alphanum_fraction":0.7467067837715149,"avg_line_length":30.270587921142578,"blob_id":"f3173e37dfc481dd141b1f9bf3ea860682c0a389","content_id":"de367bcfd765680edace5aeb1d0f222e7feab7df","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":2657,"license_type":"no_license","max_line_length":161,"num_lines":85,"path":"/README.md","repo_name":"beallio/media-server-status","src_encoding":"UTF-8","text":"# Server Status #\n\n## Screenshots ##\n\n#### Now Playing ####\n\n\n\n#### Recently Added ####\n\n\n\n## Introduction ##\nServer status dashboard written in python 2.7, using flask on the backend, and bootstrap and jQuery for design.\n\n\n## Setup ##\n\nInstallation instructions are for a Debian-based distro. You will need to adjust accordingly to your linux-based setup.\n\nRun the following commands (assuming the following is not installed on your system)\n\n sudo apt-get update && sudo apt-get -y upgrade\n sudo apt-get install python-dev libjpeg-dev zlib1g-dev libpng12-dev pip virtualenv virtualenvwrapper git\n\nNote the image libraries are in support of Pillow\n\nNow to setup the folder to contain the app and virtual environment\n\n cd mkdir /var/www/serverstatus\n mkvirtualenv venv\n \nClone the repository to your system\n\n sudo git clone https://bitbucket.org/beallio/media-server-dashboard.git\n\n\nInstall additional python requirements in virtual environment\n\n pip install -r requirements.txt\n\nSetup config file\n \n vim config.py\n \nMove setup file outside of root app directory (by default the app assumes the location is \"/var\". \nYou'll need to adjust the import in serverstatus/__init__.py if you place it elsewhere).\n\n sudo mv config.py /var/config.py\n \nChange permissions the user that will run gunicorn and the WSGI (e.g. $APPUSER/$APPGROUP)\n\n sudo chown $APPUSER:$APPGROUP /var/config.py\n\nRun test server to ensure repository and python requirements installed correctly\n\n ./__init__.py\n\n\n### Gunicorn on Apache ### \n\n sudo -u $USER gunicorn wsgi:application -b $INTERNAL_IP:$PORT --workers=5\n\n$USER = user dedicated to running application (e.g. 'www', 'status', 'flask')\n\n$INTERNAL_IP = Internal IP address of your server (e.g. '10.0.10.1')\n\n$PORT = internal port Gunicorn will run on\n\n\n### Apache Configuration Edits for Proxying ###\n\n ProxyPass /$SUBPATH http://$INTERNAL_IP:$PORT\n\n ProxyPassReverse /$SUBPATH http://$INTERNAL_IP:$PORT\n\nEnsure Apache module [\"mod_proxy\"](http://httpd.apache.org/docs/2.2/mod/mod_proxy.html) is installed \n\nFor security it's recommended you move \"config.py\" from a web accessible directory \nto a protected directory, ensuring $USER has read privileges\n\n\n\n### Acknowledgement ###\nLast, but not least, kudos to this [person](http://d4rk.co/) for the inspiration."},{"alpha_fraction":0.48670491576194763,"alphanum_fraction":0.4942648708820343,"avg_line_length":30.442623138427734,"blob_id":"9b09ba0289bd7ce056d105f6839d3eea19a5bbdb","content_id":"1e33c2fbcc3db14ea5a41f300f5e0874efb7f5ed","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"JavaScript","length_bytes":3836,"license_type":"no_license","max_line_length":82,"num_lines":122,"path":"/serverstatus/static/js/functions.js","repo_name":"beallio/media-server-status","src_encoding":"UTF-8","text":"var api_base_url = window.location.href + \"api/\";\nvar html_base_url = window.location.href + \"html/\";\n\n// Auto refresh elements\n(function ($) {\n $(document).ready(function () {\n $.ajaxSetup(\n {\n cache: false\n });\n\n var $systeminfo = $(\".system-info\");\n var $storage = $(\".storage\");\n var $weather = $(\".weather\");\n var $services = $(\".services\");\n var $media = $(\".media\");\n\n\n function load_systeminfo() {\n $systeminfo.load(\"html/system_info\", function () {\n var $transcodes = $(\".transcodes\");\n $transcodes.load(\"html/plex_transcodes\");\n });\n\n }\n\n var load_storage = $storage.load(\"html/storage\");\n var load_services = $services.load(\"html/services\");\n var load_weather = $weather.load(\"html/forecast\");\n var load_media = $media.load(\"html/media\");\n\n function get_server_ip() {\n $.getJSON(api_base_url + \"ip_address\", function (data) {\n $(\"#server_ip\").text(data.wan_ip);\n });\n }\n\n function get_client_ip() {\n $.getJSON('http://api.hostip.info/get_json.php', function (data) {\n $(\"#client_ip\").text(data.ip);\n });\n }\n\n // FUNCTIONS TO UPDATE NETWORK SPEED AND PING\n function update_ping() {\n $.getJSON(api_base_url + \"ping\", function (data) {\n $(\"#ping\").text(data.ping + \" ms\");\n });\n }\n\n function update_network_speed() {\n var $downspeed = $(\"#download\");\n var $downspeed_progressbar = $(\"#progress-bar-down\");\n var $upspeed = $(\"#upload\");\n var $upspeed_progressbar = $(\"#progress-bar-up\");\n $.getJSON(api_base_url + \"network_speed\", function (data) {\n var up = data.up.toFixed(2);\n var down = data.down.toFixed(2);\n $downspeed.text(down + \" Mbps\");\n $upspeed.text(up + \" Mbps\");\n var down_progressbar_width = down * (10 / 6);\n var up_progressbar_width = up * (10 / 6);\n $downspeed_progressbar.css(\"width\", down_progressbar_width + \"%\");\n $upspeed_progressbar.css(\"width\", up_progressbar_width + \"%\");\n });\n };\n\n // END FUNCTIONS TO UPDATE NETWORK SPEED AND PING\n\n function on_local_network(url) {\n var client_ip = getJson('http://api.hostip.info/get_json.php').ip;\n var server_ip = getJson(api_base_url + \"ip_address\").wan_ip;\n console.log(client_ip, server_ip, client_ip === server_ip);\n return client_ip === server_ip;\n };\n\n // Load at start of page\n load_systeminfo();\n load_storage;\n load_services;\n load_weather;\n load_media;\n\n update_network_speed();\n update_ping();\n //get_server_ip();\n //get_client_ip();\n\n // Refresh every 30 seconds\n var refreshId = setInterval(function () {\n load_systeminfo();\n }, 30000);\n\n // Refresh every 1 minute\n var refreshId = setInterval(function () {\n update_network_speed();\n update_ping();\n\n load_media;\n }, 60000);\n\n // Refresh every 10 minutes\n var refreshId = setInterval(function () {\n //get_server_ip();\n //get_client_ip();\n load_storage;\n load_weather;\n load_services;\n }, 600000);\n });\n\n\n // Enable bootstrap tooltips\n $(function () {\n $(\"[rel=tooltip]\").tooltip();\n $(\"[rel=popover]\").popover();\n });\n\n $(document).ready(function () {\n $(\"body\").tooltip({ selector: '[data-toggle=tooltip]' });\n });\n})(jQuery);\n"},{"alpha_fraction":0.6516736149787903,"alphanum_fraction":0.6516736149787903,"avg_line_length":14.949999809265137,"blob_id":"15cb92fce1b380048fc243c0b5c3da97243eeb6c","content_id":"0ff5cbb5b54c1ee06c077732ecc9939856e2cab5","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":956,"license_type":"no_license","max_line_length":69,"num_lines":60,"path":"/serverstatus/assets/exceptions.py","repo_name":"beallio/media-server-status","src_encoding":"UTF-8","text":"\"\"\"\nCustom exceptions for managing different servers\n\"\"\"\n\n\nclass MissingConfigFile(Exception):\n \"\"\"\n Config file not found\n \"\"\"\n pass\n\n\nclass MissingForecastIOKey(Exception):\n \"\"\"\n No Forecast.IO API key found\n \"\"\"\n pass\n\n\nclass PlexAPIKeyNotFound(Exception):\n \"\"\"\n No Plex API key found\n \"\"\"\n pass\n\n\nclass MissingConfigValue(Exception):\n \"\"\"\n General exception catch all for missing config values\n \"\"\"\n pass\n\n\nclass PlexConnectionError(Exception):\n \"\"\"\n Error connecting to specified Plex server\n \"\"\"\n pass\n\n\nclass PlexAPIDataError(Exception):\n \"\"\"\n Plex returned malformed data, or data in a format unfamiliar with\n (perhaps an API change)\n \"\"\"\n pass\n\n\nclass PlexImageError(Exception):\n \"\"\"\n Error retrieving image cover from Plex server\n \"\"\"\n pass\n\n\nclass SubsonicConnectionError(Exception):\n \"\"\"\n Error connection to specified Subsonic server\n \"\"\"\n pass"},{"alpha_fraction":0.5866013169288635,"alphanum_fraction":0.6096950173377991,"avg_line_length":38.068084716796875,"blob_id":"e3b79c02c351ce456c46bec4909aeec5004dd883","content_id":"598d806dc4a8cdba0c1da972d5768451c2880977","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":9180,"license_type":"no_license","max_line_length":116,"num_lines":235,"path":"/serverstatus/assets/sysinfo.py","repo_name":"beallio/media-server-status","src_encoding":"UTF-8","text":"import datetime\nimport subprocess\nimport os\nimport time\nimport urllib2\nfrom collections import OrderedDict\nfrom math import floor, log\nimport logging\n\nimport psutil\n\n\nlogger = logging.getLogger(__name__)\n\n\ndef convert_bytes(value, unit, output_str=False, decimals=2, auto_determine=False):\n \"\"\"\n\n :param value: int\n :param unit: str\n :param output_str: bool\n :param decimals: int\n :param auto_determine: bool\n :return: str or int or float\n \"\"\"\n assert any([type(value) == int, type(value) == float, type(value) is long])\n assert all([type(decimals) is int, type(output_str) is bool, type(auto_determine) is bool, value >= 0])\n conversions = dict(B=0, KB=1, MB=2, GB=3, TB=4, PB=5, EB=6, ZB=7, YB=8)\n assert unit in conversions\n base = 1024.0\n converted_value = float(value) / base ** conversions[unit]\n if auto_determine and value > 0:\n # Generate automatic prefix by bytes\n base_power = floor(log(float(value)) / log(base))\n swap_conversion_values = {conversions[x]: x for x in conversions}\n while base_power not in swap_conversion_values:\n # future proofing. Not really necessary.\n base_power -= base_power\n unit = swap_conversion_values[base_power]\n converted_value = value / base ** conversions[unit]\n if output_str:\n if decimals < 0:\n decimals = 0\n return '{:,.{decimal}f} {unit}'.format(converted_value, decimal=decimals, unit=unit)\n else:\n return converted_value\n\n\ndef get_wan_ip(site='http://myip.dnsdynamic.org/'):\n return urllib2.urlopen(site).read()\n\n\ndef get_partitions(partitions=None):\n if partitions is None:\n partitions = psutil.disk_partitions(all=True)\n return {p[1]: psutil.disk_usage(p[1]) for p in partitions if p[0] != 0}\n\n\ndef get_ping(host=\"8.8.8.8\", kind='avg', num=4):\n # solution from http://stackoverflow.com/questions/316866/ping-a-site-in-python\n \"\"\"\n returns ping time to selected site\n host: site, ip address to ping\n kind:\n num: number of pings to host\n\n :param host: string\n :param kind: string\n :param num: int\n :return: float\n \"\"\"\n assert kind in ['max', 'avg', 'mdev', 'min']\n assert type(int(num)) is int\n ping = subprocess.Popen([\"ping\", \"-c\", str(num), host], stdout=subprocess.PIPE, stderr=subprocess.PIPE)\n out, error = ping.communicate()\n out = out.split('\\n')\n try:\n out = [x for x in out if x.startswith('rtt')][0]\n out_mapped = zip(out.split()[1].split('/'), out.split()[3].split('/'))\n out_mapped = {x[0]: x[1] for x in out_mapped}\n out = out_mapped[kind]\n except IndexError:\n # most likely no ping returned, system offline\n out = 0\n return float(out)\n\n\ndef get_system_uptime():\n def append_type(x, kind):\n \"\"\"\n Return 0 if days/hours/minutes equals 0 otherwise append correct plural \"s\" to type\n ex. if systems up for 2 hours, returns \"2 hours\" likewise return \"1 hour\" if system has been up for 1 hour\n \"\"\"\n assert type(x) is int and type(kind) is str\n if x == 0:\n return x\n else:\n return '{} {}'.format(str(x), kind + 's' if x != 1 else kind)\n\n boot_time = datetime.datetime.fromtimestamp(psutil.boot_time()).replace(microsecond=0)\n time_now = datetime.datetime.now().replace(microsecond=0)\n delta = time_now - boot_time\n formatted_time = str(delta).split(',')\n try:\n # System's been up a day or more\n hours = formatted_time[1].strip().split(':')\n except IndexError:\n # System's been up for less than day\n hours = formatted_time[0].strip().split(':')\n formatted_time[0] = 0\n hours.pop(2)\n hours, mins = [int(hour) for hour in hours]\n formatted_time = dict(days=formatted_time[0], hours=append_type(hours, 'hour'), min=append_type(mins, 'minute'))\n output = dict(\n boottime=boot_time,\n uptime=delta,\n uptime_formatted=formatted_time)\n return output\n\n\ndef return_network_io():\n \"\"\"\n returns Network bytes sent, and received\n :rtype : list\n \"\"\"\n network_io = psutil.net_io_counters()\n return [network_io.bytes_sent, network_io.bytes_recv]\n\n\ndef get_network_speed(sleep=1):\n assert type(sleep) is int\n start_time = datetime.datetime.now()\n start_data = return_network_io()\n time.sleep(sleep)\n time_delta = datetime.datetime.now() - start_time\n end_data = return_network_io()\n bits = 8\n return dict(up=convert_bytes((end_data[0] - start_data[0]) / time_delta.seconds * bits, 'MB'),\n down=convert_bytes((end_data[1] - start_data[1]) / time_delta.seconds * bits, 'MB'))\n\n\ndef get_total_system_space(digits=1):\n \"\"\"\n returns total system disk space formatted, ex.\n {'total': '8,781.9 GB', 'used': '3,023.0 GB', 'pct': 34.4, 'free': '5,313.4 GB'}\n\n :rtype : dict\n :param digits: int\n :return: dict\n \"\"\"\n assert type(digits) is int\n all_partitions = psutil.disk_partitions(all=True)\n # limit total disk space to those paritions mounted in \"/dev/\"\n partitions_to_keep = [partition for partition in all_partitions if partition.device.startswith('/dev/')]\n partitions = get_partitions(partitions_to_keep)\n disk_space = dict(total=sum([partitions[partition].total for partition in partitions]),\n used=sum([partitions[partition].used for partition in partitions]),\n free=sum([partitions[partition].free for partition in partitions]))\n disk_space_formatted = {k: convert_bytes(disk_space[k], 'GB', True, digits, True) for k in disk_space}\n disk_space_formatted['pct'] = round(float(disk_space['used']) / float(disk_space['total']) * 100.0, digits)\n return disk_space_formatted\n\n\ndef get_partitions_space(partitions, digits=1, sort='alpha'):\n \"\"\"\n {'Home': {'total': '168.8 GB', 'pct': 44.4, 'free': '85.3 GB', 'used': '74.9 GB'},\n 'Incoming': {'total': '293.3 GB', 'pct': 48.2, 'free': '137.0 GB', 'used': '141.4 GB'}}\n :param partitions:\n :param digits:\n :return:\n \"\"\"\n assert type(partitions) is dict\n system_partitions = get_partitions()\n # return disk space for each partition listed in config\n # test if listed partition actually exists in system first to avoid throwing an error\n disk_space = {p: system_partitions[partitions[p]] for p in partitions if partitions[p] in system_partitions}\n disk_space_formatted = {p: dict(total=convert_bytes(disk_space[p].total, 'GB', True, digits, True),\n used=convert_bytes(disk_space[p].used, 'GB', True, digits, True),\n free=convert_bytes(disk_space[p].free, 'GB', True, digits, True)) for p in\n disk_space}\n for p in disk_space:\n disk_space_formatted[p]['pct'] = round(float(disk_space[p].used) / float(disk_space[p].total) * 100.0,\n digits)\n if sort.lower() == 'alpha':\n # place in ordered dictionary so paths always display in alphabetical order on page\n disk_space_formatted = OrderedDict(sorted(disk_space_formatted.items(), key=lambda x: x[0]))\n return disk_space_formatted\n\n\ndef get_load_average():\n os_averages = os.getloadavg()\n cpu_count = psutil.cpu_count()\n final_averages = [average / cpu_count for average in os_averages]\n return final_averages\n\n\nclass GetSystemInfo(object):\n def __init__(self):\n pass\n\n def get_info(self):\n \"\"\"\n Returns system information in a dictionary\n mem_total: Total RAM in the system in megabytes as float, ex. \"7876.88671875\"\n mem_available: Unused RAM in the system in megabytes as float, ex. \"4623.8671875\"\n mem_used_pct: mem_available / mem_total as float, ex. \"41.3\"\n load_avg: tuple of avg loads at 1 min, 5 min, and 15 min, respectively, ex. \"(0.52, 0.51, 0.43)\"\n partitions: dictionary of partitions on system, truncated ex, {''/mnt/Entertainment'':\n sdiskusage(total=56955559936, used=15403667456, free=38635122688, percent=27.0)}\n uptime_formatted: dictionary of uptime split in days, hours, min, ex.\n {'hours': '2 hours', 'days': '6 days', 'min': '26 minutes'}\n :return: dict\n \"\"\"\n mem_info = psutil.virtual_memory()\n system_uptime = get_system_uptime()\n load_avg = get_load_average()\n return dict(mem_total=convert_bytes(mem_info[0], 'MB'),\n mem_available=convert_bytes(mem_info[1], 'MB'),\n mem_used_pct=mem_info[2],\n mem_bars=self._memory_bars(mem_info[2]),\n load_avg=load_avg,\n uptime_formatted=system_uptime['uptime_formatted'])\n\n @staticmethod\n def _memory_bars(val_pct):\n mid = 50\n upper = 80\n ret = dict(xmin=min(val_pct, mid),\n xmid=min(val_pct - mid, upper - mid),\n xmax=min(val_pct - upper, 100 - upper))\n return {k: max(ret[k], 0) for k in ret}\n\n\nif __name__ == '__main__':\n pass"},{"alpha_fraction":0.5777337551116943,"alphanum_fraction":0.5846654176712036,"avg_line_length":33.149757385253906,"blob_id":"fb315c2adfa750709b46f81628d5f8fc4f119d6d","content_id":"78361ff94d37ff8962d209a246658a039ed0094c","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":7069,"license_type":"no_license","max_line_length":87,"num_lines":207,"path":"/serverstatus/views.py","repo_name":"beallio/media-server-status","src_encoding":"UTF-8","text":"\"\"\"\nRouting file for flask app\nHandles routing for requests\n\"\"\"\n\nimport json\nimport datetime\n\nfrom flask import render_template, Response, request\n\nfrom serverstatus import app\nfrom assets import apifunctions\n\n\n@app.route('/')\n@app.route('/index')\ndef index():\n \"\"\"\n Base index view at \"http://www.example.com/\"\n \"\"\"\n start_time = datetime.datetime.now()\n return render_template('index.html',\n title=app.config['WEBSITE_TITLE'],\n time=datetime.datetime.now() - start_time,\n testing=app.config['TESTING'])\n\n\n@app.route('/api/<data>', methods=['GET'])\ndef get_json(data):\n \"\"\"\n Returns API data data based on \"http://www.example.com/api/<data>\" \n call where <data> is function is a function in the APIFunction \n class in the apifunctions module. \n Returns data in JSON format.\n \"\"\"\n values, status = BACKENDCALLS.get_data(data)\n json_data = json.dumps(values)\n # set mimetype to prevent client side manipulation since we're not using\n # jsonify\n return Response(json_data, status=status, mimetype='application/json')\n\n\n@app.route('/html/<data>')\ndef html_generator(data):\n \"\"\"\n Returns html rendered jinja templates based on \"http://www.example.com/html/<data>\"\n call where <data> is a jinja template in the \"templates\" directory.\n Returns rendered html in plain text to client, so we use this data to \n load divs via jQuery on the client side\n \"\"\"\n values, status = BACKENDCALLS.get_data(data)\n start = datetime.datetime.now()\n rendered_html = render_template(data + '.html', values=values)\n app.logger.debug(\n 'Render time for {}: {}'.format(data, datetime.datetime.now() - start))\n # set mimetype to prevent users browser from rendering rendered HTML\n return Response(rendered_html, status=status, mimetype='text/plain')\n\n\n@app.route('/img/<data>')\ndef get_img_data(data):\n \"\"\"\n Returns image to client based on \"http://www.example.com/img/<data>\"\n request where <data> is a flask request such as \n \"http://www.example.com/img/subsonic?cover=28102\"\n \"\"\"\n start = datetime.datetime.now()\n resp = BACKENDCALLS.get_image_data(request)\n app.logger.debug('Image request time for {}: {}'\n .format(data, datetime.datetime.now() - start))\n return resp\n\n\nclass BackEndCalls(object):\n \"\"\"\n Provides access points into the API Functions of the backend.\n Also loads API configs to remedy issues where the config hasn't been\n loaded for a particular server.\n\n Provides access for images requests to Plex and Subsonic\n \"\"\"\n\n def __init__(self):\n self.api_functions = None\n self.api_functions = self.get_api_functions()\n\n def get_api_functions(self):\n \"\"\"\n Provides access to API Functions module through class\n :return: API_Functions\n \"\"\"\n self._load_apis()\n return self.api_functions\n\n def get_data(self, data):\n \"\"\"\n From flask request at http://servername.com/api/{api_call} fetches\n {api_call} from apifunctions module, and returns data.\n\n Disallows public access to any function in apifunctions starting with\n \"_\" (underscore)\n :type data: unicode or LocalProxy\n :return:\n \"\"\"\n values = None\n status = 404\n values = getattr(self.api_functions, str(data).lstrip('_'))()\n status = 200\n \"\"\"\n try:\n values = getattr(self.api_functions, str(data).lstrip('_'))()\n status = 200\n except (AttributeError, TypeError) as err:\n app.logger.error(err)\n # no api function for call, return empty json\n except:\n app.logger.error('An unknown error occurred')\"\"\"\n return values, status\n\n def get_image_data(self, flask_request):\n \"\"\"\n Parses flask request from\n http://servername.com/img/{plex | subsonic}?14569852 where\n {plex|subsonic} is the server requested. Routes request to appropriate\n server to get thumbnail image data\n\n :type flask_request: werkzeug.local.Request\n :return:\n \"\"\"\n\n def parse_request(request_args):\n parsed_values = dict()\n for arg in request_args:\n if request_args[arg] == '':\n parsed_values['plex_id'] = arg\n continue\n try:\n parsed_values[arg] = bool(request_args[arg])\n except ValueError:\n parsed_values[arg] = request_args[arg]\n return parsed_values\n\n resp = Response('null', status=404, mimetype='text/plain')\n # convert to string since flask requests returns unicode\n data_low = str(flask_request.view_args.get('data', None).lower())\n if data_low == 'plex':\n args = parse_request(flask_request.args)\n resp = Response(\n self.api_functions._get_plex_cover_art(args), status=200,\n mimetype='image/jpeg')\n elif data_low == 'subsonic':\n resp = Response(self._check_subsonic_request(flask_request),\n status=200,\n mimetype='image/jpeg')\n return resp\n\n def _load_apis(self):\n \"\"\"\n Check if api_functions is set, set if not.\n\n :return:\n \"\"\"\n if self.api_functions is None:\n self.api_functions = apifunctions.APIFunctions(app.config)\n\n def _check_subsonic_request(self, request_args):\n \"\"\"\n Parses flask request to determine parameters for requesting cover art\n from Subsonic server\n\n Parameters\n ----------\n request_args : flask.Request.args\n Description of parameter `request_args`.\n \"\"\"\n query_string = request_args.query_string\n args = request_args.args\n try:\n # check if only cover id was submitted\n # e.g. /img/subsonic?28102\n cover_id = int(query_string)\n cover_size = None\n except ValueError:\n try:\n # check if cover id is included in request_args\n # e.g. /img/subsonic?cover=28102\n cover_id = args['cover']\n except KeyError:\n # we need a cover to look up\n raise\n try:\n # check if cover size is included in request_args\n # e.g. /img/subsonic?cover=28102&size=145\n cover_size = args['size']\n try:\n # check if cover size is an integer\n cover_size = int(cover_size)\n except ValueError:\n # incorrect cover size requested\n cover_size = None\n except KeyError:\n # cover size not included in request_args\n cover_size = None\n return self.api_functions._get_subsonic_cover_art(cover_id, cover_size)\n\n\nBACKENDCALLS = BackEndCalls()\n"},{"alpha_fraction":0.6527777910232544,"alphanum_fraction":0.6666666865348816,"avg_line_length":23.08333396911621,"blob_id":"c934c507496df510fc29a9e1b7d12f68b7359168","content_id":"637e6b8d9639a50f6ca139041aad5c3a1aa66dce","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":288,"license_type":"no_license","max_line_length":78,"num_lines":12,"path":"/__init__.py","repo_name":"beallio/media-server-status","src_encoding":"UTF-8","text":"#!/usr/bin/env python\n\"\"\"\nMain initializing file. If called from command line starts WSGI debug testing\nserver\n\"\"\"\n\nif __name__ == '__main__':\n from serverstatus import app\n\n app.config.update(DEBUG=True, TESTING=True)\n app.run(host='0.0.0.0')\n print 'Test server running...'"},{"alpha_fraction":0.5970109701156616,"alphanum_fraction":0.5996797680854797,"avg_line_length":33.063636779785156,"blob_id":"bc8fed43354f05bfed25c31e3b677957ef5b2f14","content_id":"d6154379f7b27c5cb27798d22fc103589208ae7e","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":3747,"license_type":"no_license","max_line_length":78,"num_lines":110,"path":"/serverstatus/__init__.py","repo_name":"beallio/media-server-status","src_encoding":"UTF-8","text":"\"\"\"\nInitialize and setup flask app\n\"\"\"\n\nimport imp\nimport os\nimport logging\nimport logging.handlers as handlers\n\nfrom flask import Flask\n\n\napp = Flask(__name__)\n\n# update config for flask app\napp.config.update(\n APPNAME='server_status',\n LOGGINGMODE=logging.DEBUG,\n APPLOCATION=os.path.join(os.path.dirname(os.path.dirname(\n os.path.realpath(__file__)))),\n LOG_LOCATION='/tmp',\n TEMP_LOCATION='/tmp',\n CONFIG_LOCATION='/var/config.py')\napp.config['TEMP_IMAGES'] = os.path.join(app.config['TEMP_LOCATION'],\n 'flask-images')\napp.config['APP_MODULESLOCATION'] = os.path.join(app.config['APPLOCATION'],\n 'serverstatus')\n\nimport views\nimport assets\nfrom assets.exceptions import MissingConfigFile\nfrom assets.services import SubSonic\n\n\ndef _setup_logger():\n \"\"\"\n Setup application logging object\n\n :return: logging object\n \"\"\"\n mod_logger = None\n # use dir name thrice to return to base module path\n log_directory = app.config.get('LOG_LOCATION', None)\n log_location = os.path.join(log_directory,\n '_'.join([app.config['APPNAME'], '.log']))\n if not os.path.isdir(log_directory):\n try:\n os.mkdir(log_directory)\n except IOError:\n pass\n if os.path.isdir(log_directory):\n file_handler = handlers.RotatingFileHandler(filename=log_location,\n maxBytes=3145728)\n formatter = logging.Formatter(\n '%(asctime)s %(name)-12s %(levelname)-8s %(message)s',\n \"%Y-%m-%d %H:%M:%S\")\n file_handler.setFormatter(formatter)\n logging.getLogger('').addHandler(file_handler)\n mod_logger = logging.getLogger(__name__)\n mod_logger.setLevel(app.config['LOGGINGMODE'])\n mod_logger.debug('LOGGER initialized at {}'.format(log_location))\n return mod_logger\n\n\ndef _load_config_file(mod_logger=None):\n def gen_contents(config_data):\n # list module contents\n \"\"\"\n Generator to return modules from config file\n :type config_data: __builtin__.module\n \"\"\"\n mods = dir(config_data)\n for config_attrib in mods:\n # exclude objects that aren't our data\n if not config_attrib.startswith('__'):\n # create dict object since flask app config only accepts dicts\n # on updates\n config_value = getattr(config_data, config_attrib)\n if config_attrib in app.config:\n mod_logger.warning(\n 'Overwriting existing config value {} with {}'.format(\n config_attrib, config_value))\n result = {config_attrib: config_value}\n yield result\n\n # import config file\n config_location = app.config.get('CONFIG_LOCATION', None)\n try:\n config_data_file = imp.load_source('config', config_location)\n for data in gen_contents(config_data_file):\n app.config.update(data)\n if mod_logger:\n mod_logger.info(\n 'Config file loaded from {}'.format(config_location))\n except IOError as e:\n errs = dict(err=e.strerror, dir_location=config_location)\n logger_msg = ('{err}: Configuration file could not be found at '\n '\"{dir_location}\"').format(**errs)\n mod_logger.critical(logger_msg)\n raise MissingConfigFile(logger_msg)\n\n\nlogger = _setup_logger() # initialize LOGGER\n\n# import config data from config file into flask app object\n_load_config_file(logger)\n\n# remove initialization functions from namespace\ndel _load_config_file\ndel _setup_logger\n"},{"alpha_fraction":0.6148949861526489,"alphanum_fraction":0.6518141031265259,"avg_line_length":26.068965911865234,"blob_id":"f3e46170b51b636549f3b9e3e4a037c71b6ad42c","content_id":"abbb507fc628673b5d51c7d2f7aa052eeb3de0e1","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1571,"license_type":"no_license","max_line_length":79,"num_lines":58,"path":"/config.py","repo_name":"beallio/media-server-status","src_encoding":"UTF-8","text":"\"\"\"\nInternal configuration file for Server Status app\nChange the values according to your own server setup.\n\nBy default, the app is set to initialize the config file from \"/var/config.py\"\nIf you wish to change the location you'll need to change the location of the\nfile in serverstatus/__init__.py\n\nFor ForecastIO you'll need to go to https://developer.forecast.io/ and sign up\nfor an API key (at the time of writing the first 1,000 calls/day to the API are\nfree.\n\n\n\"\"\"\n\nSUBSONIC_INFO = dict(\n url='http://192.168.0.1',\n serverpath='/rest',\n port=4040,\n user='user',\n password='password',\n api=1.8,\n appname='py-sonic',\n external_url='http://www.example.com/subsonic'\n)\n\nPLEX_INFO = dict(\n external_url='http://www.example.com/plex',\n internal_url='http://192.168.0.1',\n internal_port=32400,\n user='user',\n password='password',\n auth_token='AUTH_TOKEN',\n local_network_auth=False\n)\n\nSERVERSYNC_INFO = dict(\n lockfile_path='/tmp/server_sync.lockfile')\n\nCRASHPLAN_INFO = dict(\n logfile_path='/usr/local/crashplan/log/app.log')\n\nPARTITIONS = dict(Partition_Name_1='/mnt/partition1',\n Partition_Name_2='/mnt/partition2',\n Partition_Name_3='/mnt/partition3',\n Root='/',\n Home='/home')\n\nINTERNAL_IP = 'http://192.168.0.1'\nWEATHER = dict(\n Forecast_io_API_key='FORECASTIOKEY',\n Latitude=37.8030,\n Longitude=-122.4360,\n units='us')\nSERVER_URL = 'http://www.example.com'\nDEBUG = False\nSECRET_KEY = 'my secret'\nWEBSITE_TITLE = 'Your title here'\n\n"},{"alpha_fraction":0.6029059290885925,"alphanum_fraction":0.6035446524620056,"avg_line_length":30.315000534057617,"blob_id":"143b48c1fca147ea94faed0f1302431eb3930787","content_id":"1f8e07a9c04ee7de49b6f32e34ce9c5a839d9140","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":6263,"license_type":"no_license","max_line_length":80,"num_lines":200,"path":"/serverstatus/assets/apifunctions.py","repo_name":"beallio/media-server-status","src_encoding":"UTF-8","text":"\"\"\"\nServes as backend for returning information about server to jQuery and Jinja\ntemplates. Data is returned in the form of dicts to mimic JSON formatting.\n\"\"\"\nfrom collections import OrderedDict\nimport logging\n\nfrom serverstatus.assets.weather import Forecast\nfrom serverstatus.assets.services import CheckCrashPlan, ServerSync, Plex, \\\n SubSonic\nfrom serverstatus.assets.sysinfo import GetSystemInfo, get_network_speed, \\\n get_ping, get_wan_ip, get_partitions_space, get_total_system_space\nimport serverstatus.assets.wrappers as wrappers\n\n\nclass APIFunctions(object):\n \"\"\"\n Serves as backend for returning information about server to jQuery and Jinja\n templates. Data is returned in the form of dicts to mimic JSON formatting.\n\n Any function within the APIFunctions class maybe called externally as long\n as the function does not start with \"_\". For example, a user/website may\n return data from http://foobar.com/api/system_info but not\n http://foobar.com/api/_get_plex_cover_art\n\n Examples to return data:\n To return system info:\n http://foobar.com/api/system_info\n\n To return network speed:\n http://foobar.com/api/network_speed\n \"\"\"\n def __init__(self, config):\n self.logger = LOGGER\n LOGGER.debug('{} initialized'.format(__name__))\n self.config = config\n self.subsonic = None\n self.plex = None\n self.server_sync = None\n self.crashplan = None\n self.weather = None\n\n @staticmethod\n @wrappers.logger('debug')\n def system_info():\n \"\"\"\n Returns data for system info section (memory, load, uptime)\n\n :return: dict\n \"\"\"\n get_system_info = GetSystemInfo()\n output = get_system_info.get_info()\n return output\n\n @staticmethod\n @wrappers.logger('debug')\n def network_speed():\n \"\"\"\n Returns server network speed. Sleep defines the length of time in\n between polling for network IO data to calculate speed based off delta\n\n :return: dict\n \"\"\"\n return get_network_speed(sleep=5)\n\n @staticmethod\n @wrappers.logger('debug')\n def ping():\n \"\"\"\n Returns ping from Google DNS (default)\n\n :return: dict\n \"\"\"\n return dict(ping='{:.0f}'.format(get_ping()))\n\n @wrappers.logger('debug')\n def storage(self):\n \"\"\"\n Returns formatted storage data based off options selected in Config file\n\n :return: dict\n \"\"\"\n paths = get_partitions_space(self.config['PARTITIONS'])\n return dict(total=get_total_system_space(), paths=paths)\n\n @wrappers.logger('debug')\n def ip_address(self):\n \"\"\"\n Returns servers internal and external IP addresses\n\n :return: dict\n \"\"\"\n return dict(wan_ip=get_wan_ip(), internal_ip=self.config['INTERNAL_IP'])\n\n @wrappers.logger('debug')\n def services(self):\n \"\"\"\n Returns sorted status mappings for servers listed in config file\n :return: dict\n \"\"\"\n self._load_configs()\n servers = [self.plex, self.subsonic, self.server_sync, self.crashplan]\n servers_mapped = [getattr(server, 'status_mapping') for server in\n servers]\n servers_dict = OrderedDict()\n for server in servers_mapped:\n servers_dict = OrderedDict(servers_dict.items() + server.items())\n return servers_dict\n\n @wrappers.logger('debug')\n def media(self):\n \"\"\"\n Returns now playing data for Plex and Subsonic (if any), and recently\n added items for both\n\n :return: dict\n \"\"\"\n self._load_configs()\n subsonic = self.subsonic\n plex = self.plex\n return dict(\n subsonic_nowplaying=subsonic.now_playing(),\n plex_nowplaying=plex.now_playing(),\n subsonic_recentlyadded=subsonic.recently_added(num_results=6),\n plex_recentlyadded=plex.recently_added(num_results=6))\n\n @wrappers.logger('debug')\n def forecast(self):\n \"\"\"\n Gets forecast data from forecast.io\n\n :return: dict\n \"\"\"\n self._load_configs()\n self.weather.reload_data()\n return self.weather.get_data()\n\n @wrappers.logger('debug')\n def plex_transcodes(self):\n \"\"\"\n Gets number of transcodes from Plex\n\n :return: dict\n \"\"\"\n self._load_configs()\n return dict(plex_transcodes=self.plex.transcodes)\n\n def _get_plex_cover_art(self, args):\n \"\"\"\n Gets Plex cover art passing flask requests into Plex class\n\n :return: image\n \"\"\"\n self._load_configs()\n return self.plex.get_cover_image(**args)\n\n def _get_subsonic_cover_art(self, cover_id, size):\n \"\"\"\n Gets subsonic cover art passing flask requests into Subsonic class\n\n :return: image\n \"\"\"\n self._load_configs()\n cover_id = int(cover_id)\n return self.subsonic.get_cover_art(cover_id, size)\n\n def _load_configs(self):\n \"\"\"\n Loads config data for Service subclasses if not already loaded to\n prevent errors.\n :return: Service class\n \"\"\"\n if self.subsonic is None:\n try:\n self.subsonic = SubSonic(self.config['SUBSONIC_INFO'])\n except KeyError:\n LOGGER.debug('Subsonic not loaded yet')\n if self.plex is None:\n try:\n self.plex = Plex(self.config['PLEX_INFO'])\n except KeyError:\n LOGGER.debug('Plex not loaded yet')\n if self.server_sync is None:\n try:\n self.server_sync = ServerSync(self.config['SERVERSYNC_INFO'])\n except KeyError:\n LOGGER.debug('Server Sync not loaded yet')\n if self.crashplan is None:\n try:\n self.crashplan = CheckCrashPlan(self.config['CRASHPLAN_INFO'])\n except KeyError:\n LOGGER.debug('CrashPlan not loaded yet')\n if self.weather is None:\n try:\n self.weather = Forecast(self.config['WEATHER'])\n except KeyError:\n LOGGER.debug('weather not loaded yet')\n\n\nLOGGER = logging.getLogger(__name__)\n"},{"alpha_fraction":0.6300366520881653,"alphanum_fraction":0.636884868144989,"avg_line_length":31.538860321044922,"blob_id":"18c1e1f8f33dac2920ba62e898caba0aa842bf14","content_id":"263d3362b3d20892229e879c8db7559950f2ffde","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":6279,"license_type":"no_license","max_line_length":78,"num_lines":193,"path":"/serverstatus/tests/test_serverstatus.py","repo_name":"beallio/media-server-status","src_encoding":"UTF-8","text":"import urllib2\nimport unittest\nfrom collections import OrderedDict\nfrom copy import deepcopy\n\nfrom flask import Flask\nfrom flask.ext.testing import LiveServerTestCase\n\nfrom serverstatus import app\nfrom serverstatus.assets.apifunctions import APIFunctions\nfrom serverstatus.assets.services import ServerSync, SubSonic\nfrom serverstatus.assets.weather import Forecast\n\n\nclass TestApiFunctions(unittest.TestCase):\n def setUp(self):\n self.app = app.test_client()\n self.apifunctions = APIFunctions(app.config)\n\n def test_ping(self):\n self.assertTrue(isinstance(self.apifunctions.ping(), dict))\n\n def test_system_info(self):\n self.assertTrue(isinstance(self.apifunctions.system_info(), dict))\n\n def test_storage(self):\n self.assertTrue(isinstance(self.apifunctions.storage(), dict))\n\n def test_network_speed(self):\n self.assertTrue(isinstance(self.apifunctions.network_speed(), dict))\n\n def test_services(self):\n self.assertTrue(isinstance(self.apifunctions.services(), OrderedDict))\n\n def test_weather(self):\n self.assertTrue(isinstance(self.apifunctions.forecast(), dict))\n\n def test_media(self):\n results = self.apifunctions.media()\n self.assertIsInstance(results, dict)\n for key in results:\n if 'plex_nowplaying' in key:\n self.plex_nowplaying(results[key])\n if 'plex_recentlyadded' in key:\n self.plex_recentlyadded(results[key])\n if 'subsonic_nowplaying' in key:\n self.subsonic_nowplaying(results[key])\n\n def test_plex_transcodes(self):\n self.assertTrue(isinstance(self.apifunctions.plex_transcodes(), dict))\n\n def plex_recentlyadded(self, result):\n self.assertIsInstance(result, dict)\n for vid_type in result:\n self.assertIsInstance(result[vid_type], list)\n for video in result[vid_type]:\n self.assertIsInstance(video, dict)\n\n def subsonic_recentlyadded(self, result):\n self.assertIsInstance(result, list)\n for album in result:\n self.assertIsInstance(result[album], dict)\n\n def plex_nowplaying(self, result):\n if not result:\n self.assertIs(result, None)\n if result:\n self.assertIsInstance(result, list)\n for video in result:\n self.assertIsInstance(video, dict)\n\n def subsonic_nowplaying(self, result):\n if not result:\n self.assertIs(result, None)\n if result:\n for key in result:\n self.assertIsInstance(result[key], dict)\n\n\nclass TestSubSonicServer(unittest.TestCase):\n def setUp(self):\n self.app = app.test_client()\n self.config = app.config['SUBSONIC_INFO']\n self.config_test_values = dict(\n url='http://192.168.1.100',\n port=40,\n user='guestuser',\n password='password',\n serverpath='/subbybad/'\n )\n\n def est_bad_config_values(self):\n for key in self.config_test_values:\n config = deepcopy(self.config)\n config[key] = self.config_test_values[key]\n self.subsonic = SubSonic(config)\n print key, self.config_test_values[key]\n self.assertTrue(self.subsonic.connection_status)\n\n def test_bad_server_url(self):\n bad_url = 'http://192.168.1.100'\n config = deepcopy(self.config)\n config['url'] = bad_url\n self.subsonic = SubSonic(config)\n self.assertFalse(self.subsonic.connection_status)\n\n def test_bad_port(self):\n config = deepcopy(self.config)\n config['port'] = 40\n self.subsonic = SubSonic(config)\n self.assertFalse(self.subsonic.connection_status)\n\n def test_bad_username(self):\n config = deepcopy(self.config)\n config['user'] = 'guestuser'\n self.subsonic = SubSonic(config)\n self.assertFalse(self.subsonic.connection_status)\n\n def test_bad_password(self):\n config = deepcopy(self.config)\n config['password'] = 'password'\n self.subsonic = SubSonic(config)\n self.assertFalse(self.subsonic.connection_status)\n\n def test_bad_serverpath(self):\n config = deepcopy(self.config)\n config['serverpath'] = '/subbybad/'\n self.subsonic = SubSonic(config)\n self.assertFalse(self.subsonic.connection_status)\n\n\nclass TestForecastIO(unittest.TestCase):\n def setUp(self):\n self.app = app.test_client()\n self.config = app.config['WEATHER']\n\n def test_bad_apikey(self):\n config = deepcopy(self.config)\n config['Forecast_io_API_key'] = 'thisisabadkey'\n with self.assertRaises(ValueError):\n Forecast(config)\n\n\nclass TestServerSync(unittest.TestCase):\n def setUp(self):\n self.app = app.test_client()\n self.config = app.config['SERVERSYNC_INFO']\n\n def test_no_lockfile_path(self):\n config = deepcopy(self.config)\n del config['lockfile_path']\n serversync = ServerSync(config)\n self.assertFalse(serversync.connection_status)\n\n def test_bad_lockfile_path(self):\n config = deepcopy(self.config)\n config['lockfile_path'] = '/tmp/badfile.lock'\n serversync = ServerSync(config)\n self.assertFalse(serversync.connection_status)\n\n\nclass TestLiveServer(LiveServerTestCase):\n server_address = 'http://192.168.1.101/status/'\n\n def create_app(self):\n self.app = Flask(__name__)\n self.app.config.update(TESTING=True, LIVESERVER_PORT=8943)\n return self.app\n\n def test_server_is_up_and_running(self):\n response = urllib2.urlopen(TestLiveServer.server_address)\n self.assertEqual(response.code, 200)\n\n\n\"\"\"\nclass TestDebugServer(flaskTestCase):\n def create_app(self):\n app = Flask(__name__)\n app.config['TESTING'] = True\n return app\n\n def test_some_json(self):\n functions_to_test = (func for func in dir(APIFunctions) if not\n func.startswith('_'))\n for func in functions_to_test:\n test_api = '/api/' + func\n response = self.client.get(test_api)\n print 'hi'\n self.assertEquals(response.json, dict())\n\"\"\"\n\nif __name__ == '__main__':\n unittest.main()"},{"alpha_fraction":0.5412545204162598,"alphanum_fraction":0.5444556474685669,"avg_line_length":39.60304260253906,"blob_id":"6a931ffce662672dd2b25f35ea791d6fc04a2fae","content_id":"8b6cc241a4151aba0d6fc31a33dfbc7f2add7687","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":34675,"license_type":"no_license","max_line_length":80,"num_lines":854,"path":"/serverstatus/assets/services.py","repo_name":"beallio/media-server-status","src_encoding":"UTF-8","text":"import os\nimport logging\nimport urllib2\nimport urlparse\nfrom collections import OrderedDict\nfrom operator import itemgetter\nfrom time import localtime, strftime\nimport datetime\nfrom cStringIO import StringIO\n\nfrom PIL import Image, ImageOps\nimport libsonic\nimport xmltodict\n\nfrom serverstatus import app\nimport serverstatus.assets.exceptions as exceptions\n\n\nLOGGER = logging.getLogger(__name__)\n\n\nclass Service(object):\n def __init__(self, service_config):\n assert isinstance(service_config, dict)\n self.logger = LOGGER\n self.logger.debug(\n '{} class initialized'.format(self.__class__.__name__))\n self.service_config = service_config\n self._services_status_mapping = self._status_mappings_dict()\n self._service_name = None\n self._connect_status = None\n self._server_full_url = None\n self._resolved_status_mapping = dict()\n self._temp_img_dir = app.config.get('TEMP_IMAGES', '/tmp')\n\n @property\n def service_name(self):\n return self._service_name\n\n @property\n def status_mapping(self):\n self._resolved_status_mapping = self._map_connection_status()\n return self._resolved_status_mapping\n\n @property\n def connection_status(self):\n self._connect_status = self._test_server_connection()\n return self._connect_status\n\n @property\n def server_full_url(self):\n return self._server_full_url\n\n @property\n def external_url(self):\n return self._get_config_attrib('external_url')\n\n @staticmethod\n def convert_date_fmt(date_str, fmt_str_in, fmt_str_out):\n dt_value = datetime.datetime.strptime(date_str, fmt_str_in)\n return dt_value.strftime(fmt_str_out)\n\n def _test_server_connection(self):\n # method to be overridden by subclasses\n return\n\n def _map_connection_status(self):\n service_name = self._service_name\n output = {service_name: dict()}\n try:\n output = {service_name: self._services_status_mapping[\n str(self.connection_status)]}\n output[service_name][\n 'title'] = self._add_service_name_to_status_mapping()\n if self.external_url:\n output[service_name]['external_url'] = self.external_url\n except KeyError:\n pass\n return output\n\n def _add_service_name_to_status_mapping(self):\n delim = '-'\n service_name = self._service_name\n if delim in service_name:\n title = service_name.split(delim)\n title = ' '.join([w.title() for w in title])\n else:\n title = service_name.title()\n return title\n\n def _get_config_attrib(self, attrib):\n try:\n return self.service_config[attrib]\n except KeyError:\n # Config attribute not found\n return None\n\n @staticmethod\n def _status_mappings_dict():\n return dict(\n False=dict(\n text='Offline',\n icon='icon-off icon-white',\n css_class='btn_mod btn btn-xs btn-danger',\n ),\n True=dict(\n text='Online',\n icon='icon-ok icon-white',\n css_class='btn_mod btn btn-xs btn-success',\n ),\n ServerSyncActive=dict(\n text='Online',\n icon='icon-download icon-white',\n css_class='btn_mod btn btn-xs btn-success',\n ),\n BackupServerActive=dict(\n text='Active',\n icon='icon-upload icon-white',\n css_class='btn_mod btn btn-xs btn-success',\n ),\n Waiting=dict(\n text='Pending',\n icon='icon-pause icon-white',\n css_class='btn_mod btn btn-xs btn-warning',\n )\n )\n\n def _log_warning_for_missing_config_value(self, cls_name, config_val,\n default):\n # Log warning that config value for plex is missing from config file.\n # Using default value instead\n self.logger.warning(\n ('{config_val} missing from config value for {cls_name}. '\n 'Using {default} instead').\n format(cls_name=cls_name, default=default, config_val=config_val))\n\n @staticmethod\n def _convert_xml_to_json(resp_output):\n return xmltodict.parse(resp_output)\n\n @staticmethod\n def _build_external_img_path(service_name):\n base_path = 'img/'\n return ''.join([base_path, service_name, '?'])\n\n def _test_file_path(self, file_path_key):\n # //TODO Needed\n output = None\n try:\n file_path = self.service_config[file_path_key]\n if os.path.exists(file_path):\n output = file_path\n except KeyError as err:\n self.logger.error(err)\n finally:\n return output\n\n\nclass SubSonic(Service):\n def __init__(self, server_info):\n Service.__init__(self, server_info)\n self._service_name = 'subsonic'\n self.conn = libsonic.Connection(baseUrl=self.service_config['url'],\n username=self.service_config['user'],\n password=self.service_config[\n 'password'],\n port=self.service_config['port'],\n appName=self.service_config['appname'],\n apiVersion=self.service_config['api'],\n serverPath=self.service_config[\n 'serverpath'])\n self._connect_status = self._test_server_connection()\n self._server_full_url = self._get_server_full_url()\n self._resolved_status_mapping = self._map_connection_status()\n self._img_base_url = self._build_external_img_path(\n self._service_name) + 'cover='\n\n def recently_added(self, num_results=None):\n \"\"\"\n Returns recently added entries.\n\n :param num_results: number of recently added results to return\n :type num_results: int\n :return: list of [dict]\n \"\"\"\n\n def recently_added_generator(num):\n recently_added = self.conn.getAlbumList(\"newest\", num)['albumList'][\n 'album']\n for album in recently_added:\n yield album\n return\n\n if num_results is None:\n num_results = 10\n return [self._get_entry_info(entry, min_size=145, max_size=500) for\n entry in recently_added_generator(num_results)]\n\n def get_cover_art(self, cover_art_id, size=None):\n assert isinstance(cover_art_id, int)\n if any([size is None, size <= 0, type(size) is not int]):\n return self.conn.getCoverArt(aid=cover_art_id)\n else:\n if size > 2000:\n # set max limit on size of photo returned\n size = 2000\n return self.conn.getCoverArt(aid=cover_art_id, size=size)\n\n def now_playing(self):\n \"\"\"\n Returns now playing entries from Subsonic server in list format. Each\n entry in list represents one song currently playing from server. Each\n entry in list is a dict\n\n :returns: list of [dict]\n \"\"\"\n entries = []\n now_playing = self.conn.getNowPlaying()\n try:\n many_songs_playing = isinstance(now_playing['nowPlaying']['entry'],\n list)\n except (KeyError, TypeError):\n # no songs playing\n return None\n if many_songs_playing:\n # multiple songs playing\n entries = [self._get_entry_info(entry) for entry in\n now_playing['nowPlaying']['entry']]\n elif not many_songs_playing:\n # single song playing\n entries.append(\n self._get_entry_info(now_playing['nowPlaying']['entry']))\n # remove entries from now playing if user hasn't touched them or\n # playlist auto advanced in X min\n results = [self._get_entry_info(entry, max_size=800) for entry in\n entries if entry['minutesAgo'] <= 10]\n if results:\n return results\n else:\n return None\n\n def set_output_directory(self, directory):\n # //TODO remove extraneous code\n self._temp_img_dir = directory\n return self._temp_img_dir == directory\n\n def _test_server_connection(self):\n \"\"\"\n Test if we're able to connect to Subsonic server.\n\n :return: bool - True if able to connect, false otherwise\n :raise: exceptions.SubsonicConnectionError\n \"\"\"\n connection_status = False\n try:\n connection_status = self.conn.ping()\n assert connection_status\n except AssertionError:\n err = 'Unable to reach Subsonic server'\n self.logger.error(err)\n # raise exceptions.SubsonicConnectionError(err)\n finally:\n return connection_status\n\n def _create_cover_art_file(self, cover_art_id, size=None):\n \"\"\"\n size in get_cover_art method for subsonic returns a square image with\n dimensions in pixels equal to size\n :param cover_art_id:\n :return:\n \"\"\"\n # set default image size in pixels\n if size is None:\n size = 600\n img_data = self.conn.getCoverArt(aid=cover_art_id, size=size)\n cover_dir = self._temp_img_dir # temp storage for created image files\n filename = 'cover'\n ext = '.jpg'\n short_filepath = filename + str(cover_art_id) + '_' + str(size) + ext\n full_filepath = os.path.join(cover_dir, short_filepath)\n if not os.path.exists(cover_dir):\n # check if filepath exists. Attempt to create if it doesn't\n try:\n os.mkdir(cover_dir)\n except IOError:\n self.logger.error(\n 'Failed to create cover art directory: {}'.format(\n full_filepath))\n return\n if not os.path.isfile(full_filepath):\n self.logger.info('Write cover art file: {}'.format(full_filepath))\n with open(full_filepath, 'wb') as img_file:\n img_file.write(img_data.read())\n return full_filepath\n\n def _get_entry_info(self, entry, min_size=None, max_size=None):\n \"\"\"\n appends URL coverart link to Subsonic entry dict\n :param entry: subsonic entry\n :type entry: dict\n :return: dict\n \"\"\"\n assert type(entry) == dict\n if min_size:\n min_size = 145\n if max_size:\n max_size = 1200\n # create url link to thumbnail coverart, and full-size coverart\n cover_art_link = [''.join([self._img_base_url,\n str(entry.get('coverArt', entry['id'])),\n '&size=',\n str(size)]) for size in (min_size, max_size)]\n entry.update(coverArtExternalLink_sm=cover_art_link[0],\n coverArtExternalLink_xl=cover_art_link[1])\n try:\n created_date = self.convert_date_fmt(entry[u'created'],\n '%Y-%m-%dT%H:%M:%S.%fZ',\n '%m/%d/%Y %I:%M%p')\n except ValueError as dt_conv_err:\n self.logger.error('Error converting date: {}'.format(dt_conv_err))\n else:\n entry[u'created'] = created_date\n try:\n # Return progress on currently playing song(s). No good way to do\n # this since Subsonic doesn't have access to this info through\n # it's API. Calculate progress by taking last time\n # song was accessed divide by progress\n entry['progress'] = min(\n float(entry['minutesAgo']) / float(entry['duration'] / 60), 1)\n except KeyError:\n entry['progress'] = 1\n finally:\n entry.update(progress_pct='{:.2%}'.format(entry['progress']),\n progress=entry['progress'] * 100)\n return entry\n\n def _get_server_full_url(self):\n serverpath = self.service_config['serverpath'].strip('/')\n try:\n serverpath, _ = serverpath.split('/')\n except ValueError as err:\n self.logger.warning(\n 'Issue parsing Subsonic server path: {}'.format(err))\n return '{url}:{port:d}/{path}'.format(url=self.service_config['url'],\n port=self.service_config['port'],\n path=serverpath)\n\n\nclass CheckCrashPlan(Service):\n def __init__(self, server_info):\n Service.__init__(self, server_info)\n self._service_name = 'backups'\n self.file_path = self._test_file_path('logfile_path')\n self._connect_status = self._test_server_connection()\n self._resolved_status_mapping = self._map_connection_status()\n\n def _test_server_connection(self):\n items_to_keep = ['scanning', 'backupenabled']\n with open(self.file_path, 'r') as log_file:\n items = [line.lower().split() for line in log_file.readlines()\n for x in items_to_keep if x in line.lower()]\n # remove \"=\" from list\n for item in items:\n item.remove('=')\n items_values = [True if item[1] == 'true' else False for item in items]\n if all(items_values):\n return 'BackupServerActive'\n elif any(items_values):\n return 'Waiting'\n else:\n return False\n\n\nclass ServerSync(Service):\n def __init__(self, server_info):\n Service.__init__(self, server_info)\n self.server_info = server_info\n self.lockfile_path = self.server_info.get('lockfile_path', None)\n self._service_name = 'server-sync'\n self._connect_status = self._test_server_connection()\n self._resolved_status_mapping = self._map_connection_status()\n\n def _test_server_connection(self):\n try:\n return os.path.exists(self.lockfile_path)\n except TypeError:\n self.logger.debug('Server Sync Lockfile does not exist at {}'.\n format(self.lockfile_path))\n return False\n\n\nclass Plex(Service):\n \"\"\"\n Note: Plex requires a PlexPass for access to the server API. Plex won't\n allow you to connect to API otherwise\n\n Provides media metadata information from Plex\n \"\"\"\n url_scheme = 'http://'\n\n def __init__(self, server_config):\n Service.__init__(self, server_config)\n assert type(server_config) is dict\n self.service_config = server_config\n self._service_name = 'plex'\n self.server_internal_url_and_port = self._get_full_url_and_port\n try:\n self._server_full_url = server_config['external_url']\n except KeyError as err:\n self.logger.error(\n 'Missing config value {config_value} from {cls}'.format(\n config_value='external_url',\n cls=self.__class__.__name__))\n raise exceptions.MissingConfigValue(err)\n self._connect_status = self._test_server_connection()\n self._resolved_status_mapping = self._map_connection_status()\n self._transcodes = 0\n self._cover_mapping = dict()\n self._img_base_url = self._build_external_img_path(self._service_name)\n\n def recently_added(self, num_results=None):\n \"\"\"\n\n :type num_results: int or unknown\n :return: dict of [lists]\n \"\"\"\n\n def process_video_data(videos):\n # sort the recently added list by date in descending order\n videos = sorted(videos, key=itemgetter('@addedAt'), reverse=True)\n # trim the list to the number of results we want\n videos_trimmed = videos[:num_results]\n return [self._get_video_data(video) for video in videos_trimmed]\n\n if not self._connect_status:\n return None\n if any([num_results is None, type(num_results) is not int]):\n # Check if correct for maximum number of results is entered\n # if not set default\n num_results = 6\n api_call = 'recentlyadded'\n json_data = self._get_xml_convert_to_json(api_call)\n # the media value we want are contained in lists so loop through the\n # MediaContainer, find the lists of data, and return each value in\n # the lists. The lists contain Movies and Shows separately.\n\n movies = [media for value in json_data['MediaContainer'] if\n type(json_data['MediaContainer'][value]) == list for\n media in json_data['MediaContainer'][value] if\n media['@type'] != 'season']\n tv_shows = [media for value in json_data['MediaContainer'] if\n type(json_data['MediaContainer'][value]) == list for\n media in json_data['MediaContainer'][value] if\n media['@type'] == 'season']\n # remove extra data\n del json_data\n return dict(Movies=process_video_data(movies),\n TVShows=process_video_data(tv_shows))\n\n def now_playing(self):\n \"\"\"\n Returns now playing data from Plex server in a JSON-like dictionary\n\n :return: dict()\n \"\"\"\n\n def generate_video_data(vid_data, api_call=None):\n \"\"\"\n Generator function for creating relevant video data. Takes JSON\n data, checks if is data is an OrderedDict\n then grabs the relevant data if the video is a TV show or Movie.\n \"\"\"\n # In JSON form Plex returns multiple videos as a list of\n # OrderedDicts, and a single video as an OrderedDict\n # Convert the single video to a list for processing\n if isinstance(vid_data, OrderedDict):\n video_list = list()\n video_list.append(vid_data)\n elif isinstance(vid_data, list):\n video_list = vid_data\n else:\n # Plex returned data that we haven't seen before.\n # Raise exception to warn user.\n msg = (\n 'Plex returned API data that does not match to known '\n 'standards.Plex return data as {} when it should return a '\n 'list or OrderedDict').format(type(vid_data))\n self.logger.error(msg)\n raise exceptions.PlexAPIDataError(msg)\n for video in video_list:\n # Grab relevant data about Video from JSON data, send the API\n # call to calculate _transcodes, otherwise it will skip and\n # return 0\n yield self._get_video_data(video, api_call)\n return\n\n self._transcodes = 0 # reset serverinfo count\n api_call = 'nowplaying'\n now_playing_relevant_data = list()\n json_data = self._get_xml_convert_to_json(api_call)\n if not int(json_data['MediaContainer']['@size']):\n # Nothing is currently playing in plex\n return None\n for vid in generate_video_data(json_data['MediaContainer']['Video'],\n api_call):\n now_playing_relevant_data.append(vid)\n return now_playing_relevant_data\n\n def get_cover_image(self, plex_id, thumbnail=None, local=None):\n \"\"\"\n Returns binary jpeg object for Plex item found local temp directory as\n set in config file. Checks request argument against mapped value from\n Plex item ID\n\n :param plex_id: metadata coverart ID that corresponds to mapping\n dictionary\n :type plex_id: str\n :param thumbnail: boolean values that tells us to return thumbnail\n image if True. Returns full scale image if False\n :type thumbnail: bool or NoneType\n :param local: boolean value that tells us to pull image from Plex\n server or return local copy\n :type local: bool or NoneType\n :return: binary\n :raises: exceptions.PlexImageError\n \"\"\"\n\n def open_image(ext):\n try:\n return open(os.path.join(self._temp_img_dir, plex_id + ext),\n 'rb')\n except IOError as img_err:\n raise exceptions.PlexImageError(img_err)\n\n thumbnail = thumbnail is not None\n local = local is not None\n if self._cover_mapping is None:\n # if _cover_mapping is empty we need to initialize Now Playing\n self.now_playing()\n if thumbnail:\n resp = open_image('.thumbnail')\n elif local:\n resp = open_image('.jpg')\n else:\n try:\n resp = urllib2.urlopen(\n urlparse.urljoin(self.server_internal_url_and_port,\n self._cover_mapping[plex_id]))\n except (TypeError, urllib2.HTTPError) as err:\n raise exceptions.PlexImageError(err)\n return resp\n\n @property\n def transcodes(self):\n \"\"\"\n Returns number of current number of Plex transcode sessions\n\n >>> 0\n >>> 1\n\n :return: int\n \"\"\"\n server_info = self.plex_server_info()\n self._transcodes = server_info.get('transcoderActiveVideoSessions', 0)\n return self._transcodes\n\n def plex_server_info(self):\n json_show_data = self._get_xml_convert_to_json('serverinfo')\n server_data = json_show_data.get('MediaContainer', None)\n data_dict = {str(key.strip('@')): server_data[key] for key in\n server_data if type(server_data[key]) is unicode or\n type(server_data[key]) is str}\n for key in data_dict:\n try:\n data_dict[key] = int(data_dict[key])\n except ValueError:\n if ',' in data_dict[key]:\n split_values = data_dict[key].split(',')\n data_dict[key] = [int(val) for val in split_values]\n return data_dict\n\n def _test_server_connection(self):\n \"\"\"\n Test if connection to Plex is active or not\n >>> True\n >>> False\n :return: bool\n \"\"\"\n resp = None\n try:\n if self.service_config['local_network_auth']:\n # local network authentication required\n # // TODO Need to complete code for authorization if necessary\n pass\n except KeyError:\n pass\n resp = self._get_plex_api_data('serverinfo')\n is_connectable = resp is not None\n if not is_connectable:\n self.logger.error('Could not connect to Plex server')\n return is_connectable\n\n def _get_api_url_suffix(self, url_suffix):\n \"\"\"\n https://code.google.com/p/plex-api/wiki/PlexWebAPIOverview\n contains information required Plex HTTP APIs\n\n serverinfo: Transcode bitrateinfo, myPlexauthentication info\n nowplaying: This will retrieve the \"Now Playing\" Information of the PMS.\n librarysections: Contains all of the sections on the PMS. This acts as\n a directory and you are able to \"walk\" through it.\n prefs: Gets the server preferences\n servers: get the local List of servers\n ondeck: Show ondeck list\n channels_all: Returns all channels installed in Plex Server\n channels_recentlyviewed: Get listing of recently viewed channels\n recentlyadded: Gets listing of recently added media, in descending\n order by date added\n metadata: Returns metadata from media, e.g. /library/metadata/<val>\n when <val> is an integer tied to a specific episode or movie\n\n >>> '/library/recentlyAdded'\n\n :param the_data_were_looking_for:\n :return:\n \"\"\"\n url_api_mapping = dict(\n serverinfo='/',\n nowplaying='/status/sessions',\n librarysections='/library/sections',\n prefs='/:/prefs',\n servers='/servers',\n ondeck='/library/onDeck',\n channels_all='/channels/all',\n recentlyadded='/library/recentlyAdded',\n metadata='/library/metadata/'\n )\n try:\n results = url_api_mapping[url_suffix]\n except KeyError as err:\n self.logger.error(err)\n raise exceptions.PlexAPIKeyNotFound(err)\n return results\n\n @property\n def _get_full_url_and_port(self):\n \"\"\"\n builds out internal url with port\n\n >>> 'http://localhost:32400'\n >>> 'http://192.168.0.1:32400'\n\n :return: str\n \"\"\"\n port = str(self.service_config.get('internal_port', '32400'))\n if port != self.service_config.get('internal_port') or str(port) != \\\n self.service_config.get('internal_port'):\n self._log_warning_for_missing_config_value(\n cls_name=self.__class__.__name__, default=port,\n config_val='port')\n try:\n internal_url = self.service_config['internal_url'].replace(\n Plex.url_scheme, '').lstrip('/')\n except KeyError:\n internal_url = 'localhost'\n self._log_warning_for_missing_config_value(\n cls_name=self.__class__.__name__,\n default=internal_url, config_val='internal_url')\n return ''.join([Plex.url_scheme, internal_url, ':', port])\n\n def _get_plex_api_data(self, api_call, api_suffix=None):\n \"\"\"\n Call plex api, and return XML data\n\n For /status/sessions:\n >>> '<MediaContainer size=\"0\"></MediaContainer>'\n\n :param api_call:\n :return: str\n :raises: exceptions.PlexConnectionError\n \"\"\"\n if api_suffix is None:\n # no extra api call for this\n api_suffix = ''\n try:\n full_api_call = ''.join(\n [self._get_api_url_suffix(api_call), api_suffix])\n resp = urllib2.urlopen(\n urlparse.urljoin(self.server_internal_url_and_port,\n full_api_call))\n output = resp.read()\n except urllib2.URLError as err:\n self.logger.error('Error connecting to Plex')\n raise exceptions.PlexConnectionError(err)\n else:\n resp.close()\n return output\n\n def _get_xml_convert_to_json(self, api_key, api_suffix=None):\n \"\"\"\n Gets Plex data based on api key and converts Plex XML response to JSON\n format\n\n :type api_key: str\n :type api_suffix: unknown or str\n :return:\n \"\"\"\n xml_data = self._get_plex_api_data(api_key, api_suffix)\n return self._convert_xml_to_json(xml_data)\n\n def _get_video_data(self, video, get_type=None):\n is_now_playing = get_type == 'nowplaying'\n # need a separate dict for section mapping since Plex returns different\n # data for Now Playing and Recently Added\n library_section_mapping = {'1': 'Movies', '2': 'TV Shows'}\n # need a separate dict for section mapping since Plex returns different\n # data for Now Playing and Recently Added\n # all the video.gets below are to handle the different mappings\n # Plex sends for Now Playing/Recently Added.\n vidtype = video.get('@librarySectionTitle',\n library_section_mapping.get(\n video.get('@librarySectionID', 0)))\n if vidtype == 'TV Shows':\n video_data = self._get_tv_show_data(video, get_type)\n elif vidtype == 'Movies':\n release_date = video['@originallyAvailableAt']\n video_data = dict(showtitle=video['@title'],\n summary=video['@summary'],\n releasedate=self.convert_date_fmt(release_date,\n '%Y-%m-%d',\n '%m/%d/%Y'))\n else:\n # encountered an unexpected video type\n msg = 'Unexpected media type {} encountered'.format(vidtype)\n self.logger.error(msg)\n raise exceptions.PlexAPIDataError(msg)\n if is_now_playing:\n # only applicable if we want to retrieve now playing data from Plex\n plex_path_to_art = video.get('@grandparentThumb', video['@thumb'])\n try:\n # this is only relevant for videos that are currently playing\n video_data['progress'] = (float(video['@viewOffset']) / float(\n video['@duration'])) * 100.0\n except KeyError:\n # video's not playing - not an issue\n video_data['progress'] = 0\n # add common elements to video dict\n else:\n plex_path_to_art = video['@thumb']\n self._save_cover_art(self.server_internal_url_and_port +\n plex_path_to_art)\n arturlmapped_value = os.path.basename(plex_path_to_art)\n video_data.update(type=vidtype,\n art_external_url=''.join([self._img_base_url,\n arturlmapped_value]),\n added_at=strftime('%m/%d/%Y %I:%M %p',\n localtime(int(video['@addedAt']))))\n # converts direct plex http link to thumbnail to internal mapping\n # security through obfuscation /s\n self._cover_mapping[arturlmapped_value] = plex_path_to_art\n video_data['rating'] = float(video.get('@rating', 0))\n return video_data\n\n def _save_cover_art(self, cover_loc):\n # retrieve image data from Plex server metadata\n img_data = StringIO(urllib2.urlopen(\n urlparse.urljoin(self.server_internal_url_and_port,\n cover_loc)).read())\n # check if temp directory exists, if not attempt to create directory\n if not os.path.exists(self._temp_img_dir):\n try:\n os.mkdir(self._temp_img_dir)\n self.logger.info('Creating temporary image directory {}'.\n format(self._temp_img_dir))\n except OSError as err:\n self.logger.error(('Failure creating temporary image directory'\n ' {}.\\nError message {}').format(\n self._temp_img_dir, err))\n raise\n img = Image.open(img_data)\n exts = ('.jpg', '.thumbnail')\n sizes = [(568, 852), (144, 214)]\n # create filepaths to temp images in temp directory\n img_filepaths = [os.path.join(self._temp_img_dir, ''.join(\n [str(cover_loc.split('/')[-1]), ext])) for ext in exts]\n # index 0 = size tuple\n # index 1 = path to file\n size_and_fps = zip(sizes, img_filepaths)\n for img_file in size_and_fps:\n # preserve original file for multiple manipulations\n temp_img = img.copy()\n size = img_file[0]\n filepath = img_file[1]\n if not os.path.exists(filepath):\n # create plex cover art file if file does not exist\n try:\n temp_img = ImageOps.fit(image=temp_img, size=size,\n method=Image.ANTIALIAS)\n temp_img.save(filepath, \"JPEG\")\n self.logger.info(\n 'Write image file: {}'.format(filepath))\n except IOError as pil_err:\n self.logger.error(\n 'Image file write failure at {}. Reason: {}'.\n format(filepath, pil_err))\n else:\n self.logger.debug('Image file already exists at: {}'.\n format(filepath))\n return img_filepaths[0]\n\n def _get_tv_show_data(self, video, get_type=None):\n is_now_playing = get_type == 'nowplaying'\n video_data = dict(showtitle=\n video.get('@parentTitle',\n video.get('@grandparentTitle')),\n episode_number=int(video.get('@leafCount',\n video.get('@index'))),\n summary=video.get('@parentSummary',\n video.get('@summary'))\n if video['@summary'] != '' else 'Not available',\n season=video['@title'] if\n video['@title'].lower() == 'specials'\n else int(video['@title'].lstrip('Season ')) if not\n is_now_playing else int(video['@parentIndex']))\n if isinstance(video_data['season'], int):\n video_data['season'] = '{0:02d}'.format(video_data['season'])\n if not is_now_playing:\n json_show_data = self._get_xml_convert_to_json('serverinfo',\n video['@key'].\n lstrip('/'))\n video = json_show_data['MediaContainer']\n video_data.update(rating=video.get('@grandparentContentRating', ''),\n studio=video['@grandparentStudio'])\n try:\n # if there's more than one episode in the season\n video = video['Video'][\n int(video_data['episode_number']) - 1]\n except KeyError:\n # first show in season\n video = video['Video']\n # get originally date playing on TV\n try:\n aired_date = video['@originallyAvailableAt']\n aired_date = self.convert_date_fmt(aired_date, \"%Y-%m-%d\",\n \"%m/%d/%Y\")\n except KeyError:\n aired_date = 'Not available'\n video_data.update(title=video['@title'], aired_date=aired_date)\n\n # Set individual show summary to parent summary if show summary does\n # not exist\n if video['@summary'] != '':\n video_data['summary'] = video['@summary']\n return video_data\n"},{"alpha_fraction":0.6156351566314697,"alphanum_fraction":0.6188924908638,"avg_line_length":33.13888931274414,"blob_id":"162c8da2be6af14f740776746536ce3f6e2824e8","content_id":"e6fbf2ba73122d4cbb62bcb18f46cbe70bfb6349","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1228,"license_type":"no_license","max_line_length":94,"num_lines":36,"path":"/setup.py","repo_name":"beallio/media-server-status","src_encoding":"UTF-8","text":"#!/usr/bin/env python\nimport os\n\ntry:\n from setuptools import setup\nexcept ImportError:\n from distutils.core import setup\n\nreadme_file = 'README.md'\nreadme_file_full_path = os.path.join(os.path.dirname(os.path.realpath(__file__)), readme_file)\nwith open(readme_file_full_path, 'r') as f:\n readme_contents = f.read()\nif not readme_contents:\n readme_contents = ''\n\nsetup(name='server-status',\n version='0.0.1',\n author='David Beall',\n author_email='david@beallio.com',\n url='http://ww.beallio.com',\n description='Server Status',\n long_description='{}'.format(readme_contents),\n packages=['serverstatus'],\n package_dir={'serverstatus': 'serverstatus'},\n classifiers=[\n 'Development Status :: 4 - Beta',\n 'Intended Audience :: System Administrators',\n 'Intended Audience :: Information Technology',\n 'License :: OSI Approved :: GNU General Public License (GPL)',\n 'Natural Language :: English',\n 'Operating System :: POSIX',\n 'Programming Language :: Python',\n 'Topic :: Software Development :: Libraries :: Python Modules',\n 'Topic :: Software Development :: Libraries',\n 'Topic :: System',\n ])"},{"alpha_fraction":0.5667939186096191,"alphanum_fraction":0.5687022805213928,"avg_line_length":23.395349502563477,"blob_id":"ccb08695a52f2fa560b09365fb1637e59bcd4653","content_id":"0ccdc40b87970f030b22c9559fc7840d452d1e3e","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1048,"license_type":"no_license","max_line_length":68,"num_lines":43,"path":"/serverstatus/assets/wrappers.py","repo_name":"beallio/media-server-status","src_encoding":"UTF-8","text":"\"\"\"\nfunction wrappers module\n\"\"\"\n\nimport logging\nfrom inspect import stack, getmodule\n\n\ndef logger(log_type):\n \"\"\"\n decorator to log output of functions\n :param log_type: logger level as string (debug, warn, info, etc)\n :type log_type: str\n \"\"\"\n def log_decorator(func):\n \"\"\"\n wrapped function\n \"\"\"\n def wrapped(*args, **kwargs):\n # preserve calling module name for LOGGER\n frm = stack()[1]\n mod = getmodule(frm[0])\n wrapped_logger = logging.getLogger(mod.__name__)\n result = func(*args, **kwargs)\n try:\n getattr(wrapped_logger, log_type)(result)\n except AttributeError as err:\n wrapped_logger.error(err)\n return result\n\n return wrapped\n\n return log_decorator\n\n\ndef log_args(function):\n \"\"\"\n Logs arguments passed to function\n \"\"\"\n def wrapper(*args, **kwargs):\n print 'Arguments:', args, kwargs\n return function(*args, **kwargs)\n return wrapper"},{"alpha_fraction":0.49355217814445496,"alphanum_fraction":0.5064478516578674,"avg_line_length":43.894737243652344,"blob_id":"9f8ec88ff5f9f77ce5bf63ecfd596edb736829c5","content_id":"cbd1a9ad9c65d43a32a5e96cf91f04e24026ea61","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":5120,"license_type":"no_license","max_line_length":106,"num_lines":114,"path":"/serverstatus/assets/weather.py","repo_name":"beallio/media-server-status","src_encoding":"UTF-8","text":"# coding=utf-8\nfrom collections import namedtuple\nfrom time import localtime, strftime\nimport logging\n\nimport forecastio\n\nfrom serverstatus.assets.exceptions import MissingForecastIOKey\n\n\nLOGGER = logging.getLogger(__name__)\n\n\nclass Forecast(object):\n def __init__(self, weather_config):\n assert type(weather_config) is dict\n self.logger = LOGGER\n self.logger.debug(\n '{} class initialized'.format(self.__class__.__name__))\n self.forcastio_link_url = 'http://forecast.io/#/f/'\n try:\n self.api_key = weather_config['Forecast_io_API_key']\n except KeyError:\n raise MissingForecastIOKey('No ForecastIO API key found. API key required for weather data')\n # default weather to Stanford, CA and US units\n self.lat = weather_config.get('Latitude', 37.4225)\n self.lng = weather_config.get('Longitude', 122.1653)\n self.units = weather_config.get('units', 'us')\n self.forecast = self._get_forecast_io()\n\n def get_data(self):\n json = self.forecast.json\n current = json['currently']\n hourly = json['hourly']\n minutely = json['minutely']\n daily = json['daily']['data'][0]\n output = dict(current_summary=current['summary'],\n current_summary_icon=self._get_weather_icons(current['icon']),\n current_temp=u'{:0.0f}°'.format(round(current['temperature'], 0)),\n feels_like_temp=u'{:0.0f}°'.format(round(current['apparentTemperature'], 0)),\n current_windspeed='{:0.0f}'.format(round(current['windSpeed'], 0)),\n minutely_summary=minutely['summary'],\n hourly_summary=hourly['summary'],\n sunset=self._convert_time_to_text(daily['sunsetTime']),\n sunrise=self._convert_time_to_text(daily['sunriseTime']),\n url_link='{url}{lat},{lng}'.format(\n url=self.forcastio_link_url,\n lat=self.lat, lng=self.lng))\n if output['current_windspeed'] != 0:\n output['current_windbearing'] = self._get_wind_bearing_text(current['windBearing'])\n return output\n\n def reload_data(self):\n self.forecast.update()\n\n def _get_forecast_io(self):\n return forecastio.load_forecast(self.api_key, self.lat, self.lng,\n units=self.units)\n\n @staticmethod\n def _get_weather_icons(weather_icon):\n assert type(weather_icon) is unicode\n weather_icon = weather_icon.replace(\"-\", \"_\")\n weather_mappings = dict(clear_day='B',\n clear_night='C',\n rain='R',\n snow='W',\n sleet='X',\n wind='F',\n fog='L',\n cloudy='N',\n partly_cloudy_day='H',\n partly_cloudy_night='I')\n assert weather_icon in weather_mappings\n return weather_mappings[weather_icon]\n\n @staticmethod\n def _get_wind_bearing_text(degrees):\n # normalize windbearing so N starts at 0 degrees\n deg_norm = (float(degrees) + 11.25) / 22.5\n # convert range of windbearing degrees to lookup patterns\n deg_norm_lookup = int(deg_norm) + int((deg_norm // 1) > 0)\n direction_mappings = {1: ('North', 'N'),\n 2: ('North-northeast', 'NNE'),\n 3: ('Northeast', 'NE'),\n 4: ('East-northeast', 'ENE'),\n 5: ('East', 'E'),\n 6: ('East-southeast', 'ESE'),\n 7: ('Southeast', 'SE'),\n 8: ('South-southeast', 'SSE'),\n 9: ('South', 'S'),\n 10: ('South-southwest', 'SSW'),\n 11: ('Southwest', 'SW'),\n 12: ('West-southwest', 'WSW'),\n 13: ('West', 'W'),\n 14: ('West-northwest', 'WNW'),\n 15: ('Northwest', 'NW'),\n 16: ('North-northwest', 'NNW')}\n try:\n bearing_text = direction_mappings[int(deg_norm_lookup)]\n except KeyError:\n # Key values exceeds max in dictionary, which means it's blowing North\n bearing_text = direction_mappings[1]\n # output namedtuple for Cardinal direction, and abbrevation text\n return namedtuple(typename='bearing_text', field_names=['cardinal', 'abbrev'])._make(bearing_text)\n\n @staticmethod\n def _convert_time_to_text(time_var):\n assert type(time_var) is int\n time_var = strftime('%I:%M %p', localtime(time_var))\n # Remove '0' values from time if less than 10hrs or 10mins\n if time_var.startswith('0'):\n time_var = time_var[1:]\n return time_var\n"},{"alpha_fraction":0.7539432048797607,"alphanum_fraction":0.7570977807044983,"avg_line_length":36.235294342041016,"blob_id":"eed5b3839bec997e087fb490b153d8a5fdcd44d8","content_id":"05099ee7654eb0dc456546bd239f64166fe1e260","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":634,"license_type":"no_license","max_line_length":78,"num_lines":17,"path":"/wsgi.py","repo_name":"beallio/media-server-status","src_encoding":"UTF-8","text":"\"\"\"\nAPACHE MOD_WSGI Load script\nSome of the variables in this file may need to be adjusted depending on\nserver setup and/or location of virtual environment and application\n\"\"\"\nimport sys\nimport os\n\nPROJECT_DIR = '/var/www/status' # change to the root of your app\n# 'venv/bin' is the location of the project's virtual environment\nVIRTUAL_ENV_DIR = 'venv/bin'\nPACKAGES = 'lib/python2.7/site-packages'\n\nactivate_this = os.path.join(PROJECT_DIR, VIRTUAL_ENV_DIR, 'activate_this.py')\nexecfile(activate_this, dict(__file__=activate_this))\nsys.path.append(PROJECT_DIR)\nsys.path.append(os.path.join(PROJECT_DIR, VIRTUAL_ENV_DIR, PACKAGES))\n\n"}],"string":"[\n {\n \"alpha_fraction\": 0.5072992444038391,\n \"alphanum_fraction\": 0.6970803141593933,\n \"avg_line_length\": 15.606060981750488,\n \"blob_id\": \"00bfae7cfef839c25e4111d932eb99e7d1dfacd7\",\n \"content_id\": \"e570a145f75e6306ec40d9083497f68d6bd8992b\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Text\",\n \"length_bytes\": 548,\n \"license_type\": \"no_license\",\n \"max_line_length\": 24,\n \"num_lines\": 33,\n \"path\": \"/requirements.txt\",\n \"repo_name\": \"beallio/media-server-status\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"Babel==1.3\\nFlask==0.10.1\\nFlask-Assets==0.10\\nFlask-Babel==0.9\\nFlask-Images==2.0.0\\nFlask-Mail==0.9.0\\nFlask-OpenID==1.2.1\\nFlask-SQLAlchemy==2.0\\nFlask-WTF==0.10.2\\nJinja2==2.7.3\\nMarkupSafe==0.23\\nPIL==1.1.7\\nPillow==2.5.3\\nSQLAlchemy==0.9.7\\nWTForms==2.0.1\\nWerkzeug==0.9.6\\nargparse==1.2.1\\nblinker==1.3\\ncertifi==14.05.14\\nflup==1.0.2\\ngunicorn==19.1.1\\nitsdangerous==0.24\\npillowcase==2.0.0\\npsutil==2.1.1\\npy-sonic==0.2.2\\npython-forecastio==1.2.1\\npython-openid==2.2.5\\npytz==2014.7\\nrequests==2.4.0\\nspeaklater==1.3\\nwebassets==0.10.1\\nwsgiref==0.1.2\\nxmltodict==0.9.0\\n\"\n },\n {\n \"alpha_fraction\": 0.7245013117790222,\n \"alphanum_fraction\": 0.7467067837715149,\n \"avg_line_length\": 30.270587921142578,\n \"blob_id\": \"f3173e37dfc481dd141b1f9bf3ea860682c0a389\",\n \"content_id\": \"de367bcfd765680edace5aeb1d0f222e7feab7df\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 2657,\n \"license_type\": \"no_license\",\n \"max_line_length\": 161,\n \"num_lines\": 85,\n \"path\": \"/README.md\",\n \"repo_name\": \"beallio/media-server-status\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# Server Status #\\n\\n## Screenshots ##\\n\\n#### Now Playing ####\\n\\n\\n\\n#### Recently Added ####\\n\\n\\n\\n## Introduction ##\\nServer status dashboard written in python 2.7, using flask on the backend, and bootstrap and jQuery for design.\\n\\n\\n## Setup ##\\n\\nInstallation instructions are for a Debian-based distro. You will need to adjust accordingly to your linux-based setup.\\n\\nRun the following commands (assuming the following is not installed on your system)\\n\\n sudo apt-get update && sudo apt-get -y upgrade\\n sudo apt-get install python-dev libjpeg-dev zlib1g-dev libpng12-dev pip virtualenv virtualenvwrapper git\\n\\nNote the image libraries are in support of Pillow\\n\\nNow to setup the folder to contain the app and virtual environment\\n\\n cd mkdir /var/www/serverstatus\\n mkvirtualenv venv\\n \\nClone the repository to your system\\n\\n sudo git clone https://bitbucket.org/beallio/media-server-dashboard.git\\n\\n\\nInstall additional python requirements in virtual environment\\n\\n pip install -r requirements.txt\\n\\nSetup config file\\n \\n vim config.py\\n \\nMove setup file outside of root app directory (by default the app assumes the location is \\\"/var\\\". \\nYou'll need to adjust the import in serverstatus/__init__.py if you place it elsewhere).\\n\\n sudo mv config.py /var/config.py\\n \\nChange permissions the user that will run gunicorn and the WSGI (e.g. $APPUSER/$APPGROUP)\\n\\n sudo chown $APPUSER:$APPGROUP /var/config.py\\n\\nRun test server to ensure repository and python requirements installed correctly\\n\\n ./__init__.py\\n\\n\\n### Gunicorn on Apache ### \\n\\n sudo -u $USER gunicorn wsgi:application -b $INTERNAL_IP:$PORT --workers=5\\n\\n$USER = user dedicated to running application (e.g. 'www', 'status', 'flask')\\n\\n$INTERNAL_IP = Internal IP address of your server (e.g. '10.0.10.1')\\n\\n$PORT = internal port Gunicorn will run on\\n\\n\\n### Apache Configuration Edits for Proxying ###\\n\\n ProxyPass /$SUBPATH http://$INTERNAL_IP:$PORT\\n\\n ProxyPassReverse /$SUBPATH http://$INTERNAL_IP:$PORT\\n\\nEnsure Apache module [\\\"mod_proxy\\\"](http://httpd.apache.org/docs/2.2/mod/mod_proxy.html) is installed \\n\\nFor security it's recommended you move \\\"config.py\\\" from a web accessible directory \\nto a protected directory, ensuring $USER has read privileges\\n\\n\\n\\n### Acknowledgement ###\\nLast, but not least, kudos to this [person](http://d4rk.co/) for the inspiration.\"\n },\n {\n \"alpha_fraction\": 0.48670491576194763,\n \"alphanum_fraction\": 0.4942648708820343,\n \"avg_line_length\": 30.442623138427734,\n \"blob_id\": \"9b09ba0289bd7ce056d105f6839d3eea19a5bbdb\",\n \"content_id\": \"1e33c2fbcc3db14ea5a41f300f5e0874efb7f5ed\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"JavaScript\",\n \"length_bytes\": 3836,\n \"license_type\": \"no_license\",\n \"max_line_length\": 82,\n \"num_lines\": 122,\n \"path\": \"/serverstatus/static/js/functions.js\",\n \"repo_name\": \"beallio/media-server-status\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"var api_base_url = window.location.href + \\\"api/\\\";\\nvar html_base_url = window.location.href + \\\"html/\\\";\\n\\n// Auto refresh elements\\n(function ($) {\\n $(document).ready(function () {\\n $.ajaxSetup(\\n {\\n cache: false\\n });\\n\\n var $systeminfo = $(\\\".system-info\\\");\\n var $storage = $(\\\".storage\\\");\\n var $weather = $(\\\".weather\\\");\\n var $services = $(\\\".services\\\");\\n var $media = $(\\\".media\\\");\\n\\n\\n function load_systeminfo() {\\n $systeminfo.load(\\\"html/system_info\\\", function () {\\n var $transcodes = $(\\\".transcodes\\\");\\n $transcodes.load(\\\"html/plex_transcodes\\\");\\n });\\n\\n }\\n\\n var load_storage = $storage.load(\\\"html/storage\\\");\\n var load_services = $services.load(\\\"html/services\\\");\\n var load_weather = $weather.load(\\\"html/forecast\\\");\\n var load_media = $media.load(\\\"html/media\\\");\\n\\n function get_server_ip() {\\n $.getJSON(api_base_url + \\\"ip_address\\\", function (data) {\\n $(\\\"#server_ip\\\").text(data.wan_ip);\\n });\\n }\\n\\n function get_client_ip() {\\n $.getJSON('http://api.hostip.info/get_json.php', function (data) {\\n $(\\\"#client_ip\\\").text(data.ip);\\n });\\n }\\n\\n // FUNCTIONS TO UPDATE NETWORK SPEED AND PING\\n function update_ping() {\\n $.getJSON(api_base_url + \\\"ping\\\", function (data) {\\n $(\\\"#ping\\\").text(data.ping + \\\" ms\\\");\\n });\\n }\\n\\n function update_network_speed() {\\n var $downspeed = $(\\\"#download\\\");\\n var $downspeed_progressbar = $(\\\"#progress-bar-down\\\");\\n var $upspeed = $(\\\"#upload\\\");\\n var $upspeed_progressbar = $(\\\"#progress-bar-up\\\");\\n $.getJSON(api_base_url + \\\"network_speed\\\", function (data) {\\n var up = data.up.toFixed(2);\\n var down = data.down.toFixed(2);\\n $downspeed.text(down + \\\" Mbps\\\");\\n $upspeed.text(up + \\\" Mbps\\\");\\n var down_progressbar_width = down * (10 / 6);\\n var up_progressbar_width = up * (10 / 6);\\n $downspeed_progressbar.css(\\\"width\\\", down_progressbar_width + \\\"%\\\");\\n $upspeed_progressbar.css(\\\"width\\\", up_progressbar_width + \\\"%\\\");\\n });\\n };\\n\\n // END FUNCTIONS TO UPDATE NETWORK SPEED AND PING\\n\\n function on_local_network(url) {\\n var client_ip = getJson('http://api.hostip.info/get_json.php').ip;\\n var server_ip = getJson(api_base_url + \\\"ip_address\\\").wan_ip;\\n console.log(client_ip, server_ip, client_ip === server_ip);\\n return client_ip === server_ip;\\n };\\n\\n // Load at start of page\\n load_systeminfo();\\n load_storage;\\n load_services;\\n load_weather;\\n load_media;\\n\\n update_network_speed();\\n update_ping();\\n //get_server_ip();\\n //get_client_ip();\\n\\n // Refresh every 30 seconds\\n var refreshId = setInterval(function () {\\n load_systeminfo();\\n }, 30000);\\n\\n // Refresh every 1 minute\\n var refreshId = setInterval(function () {\\n update_network_speed();\\n update_ping();\\n\\n load_media;\\n }, 60000);\\n\\n // Refresh every 10 minutes\\n var refreshId = setInterval(function () {\\n //get_server_ip();\\n //get_client_ip();\\n load_storage;\\n load_weather;\\n load_services;\\n }, 600000);\\n });\\n\\n\\n // Enable bootstrap tooltips\\n $(function () {\\n $(\\\"[rel=tooltip]\\\").tooltip();\\n $(\\\"[rel=popover]\\\").popover();\\n });\\n\\n $(document).ready(function () {\\n $(\\\"body\\\").tooltip({ selector: '[data-toggle=tooltip]' });\\n });\\n})(jQuery);\\n\"\n },\n {\n \"alpha_fraction\": 0.6516736149787903,\n \"alphanum_fraction\": 0.6516736149787903,\n \"avg_line_length\": 14.949999809265137,\n \"blob_id\": \"15cb92fce1b380048fc243c0b5c3da97243eeb6c\",\n \"content_id\": \"0ff5cbb5b54c1ee06c077732ecc9939856e2cab5\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 956,\n \"license_type\": \"no_license\",\n \"max_line_length\": 69,\n \"num_lines\": 60,\n \"path\": \"/serverstatus/assets/exceptions.py\",\n \"repo_name\": \"beallio/media-server-status\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"\\\"\\\"\\\"\\nCustom exceptions for managing different servers\\n\\\"\\\"\\\"\\n\\n\\nclass MissingConfigFile(Exception):\\n \\\"\\\"\\\"\\n Config file not found\\n \\\"\\\"\\\"\\n pass\\n\\n\\nclass MissingForecastIOKey(Exception):\\n \\\"\\\"\\\"\\n No Forecast.IO API key found\\n \\\"\\\"\\\"\\n pass\\n\\n\\nclass PlexAPIKeyNotFound(Exception):\\n \\\"\\\"\\\"\\n No Plex API key found\\n \\\"\\\"\\\"\\n pass\\n\\n\\nclass MissingConfigValue(Exception):\\n \\\"\\\"\\\"\\n General exception catch all for missing config values\\n \\\"\\\"\\\"\\n pass\\n\\n\\nclass PlexConnectionError(Exception):\\n \\\"\\\"\\\"\\n Error connecting to specified Plex server\\n \\\"\\\"\\\"\\n pass\\n\\n\\nclass PlexAPIDataError(Exception):\\n \\\"\\\"\\\"\\n Plex returned malformed data, or data in a format unfamiliar with\\n (perhaps an API change)\\n \\\"\\\"\\\"\\n pass\\n\\n\\nclass PlexImageError(Exception):\\n \\\"\\\"\\\"\\n Error retrieving image cover from Plex server\\n \\\"\\\"\\\"\\n pass\\n\\n\\nclass SubsonicConnectionError(Exception):\\n \\\"\\\"\\\"\\n Error connection to specified Subsonic server\\n \\\"\\\"\\\"\\n pass\"\n },\n {\n \"alpha_fraction\": 0.5866013169288635,\n \"alphanum_fraction\": 0.6096950173377991,\n \"avg_line_length\": 38.068084716796875,\n \"blob_id\": \"e3b79c02c351ce456c46bec4909aeec5004dd883\",\n \"content_id\": \"598d806dc4a8cdba0c1da972d5768451c2880977\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 9180,\n \"license_type\": \"no_license\",\n \"max_line_length\": 116,\n \"num_lines\": 235,\n \"path\": \"/serverstatus/assets/sysinfo.py\",\n \"repo_name\": \"beallio/media-server-status\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import datetime\\nimport subprocess\\nimport os\\nimport time\\nimport urllib2\\nfrom collections import OrderedDict\\nfrom math import floor, log\\nimport logging\\n\\nimport psutil\\n\\n\\nlogger = logging.getLogger(__name__)\\n\\n\\ndef convert_bytes(value, unit, output_str=False, decimals=2, auto_determine=False):\\n \\\"\\\"\\\"\\n\\n :param value: int\\n :param unit: str\\n :param output_str: bool\\n :param decimals: int\\n :param auto_determine: bool\\n :return: str or int or float\\n \\\"\\\"\\\"\\n assert any([type(value) == int, type(value) == float, type(value) is long])\\n assert all([type(decimals) is int, type(output_str) is bool, type(auto_determine) is bool, value >= 0])\\n conversions = dict(B=0, KB=1, MB=2, GB=3, TB=4, PB=5, EB=6, ZB=7, YB=8)\\n assert unit in conversions\\n base = 1024.0\\n converted_value = float(value) / base ** conversions[unit]\\n if auto_determine and value > 0:\\n # Generate automatic prefix by bytes\\n base_power = floor(log(float(value)) / log(base))\\n swap_conversion_values = {conversions[x]: x for x in conversions}\\n while base_power not in swap_conversion_values:\\n # future proofing. Not really necessary.\\n base_power -= base_power\\n unit = swap_conversion_values[base_power]\\n converted_value = value / base ** conversions[unit]\\n if output_str:\\n if decimals < 0:\\n decimals = 0\\n return '{:,.{decimal}f} {unit}'.format(converted_value, decimal=decimals, unit=unit)\\n else:\\n return converted_value\\n\\n\\ndef get_wan_ip(site='http://myip.dnsdynamic.org/'):\\n return urllib2.urlopen(site).read()\\n\\n\\ndef get_partitions(partitions=None):\\n if partitions is None:\\n partitions = psutil.disk_partitions(all=True)\\n return {p[1]: psutil.disk_usage(p[1]) for p in partitions if p[0] != 0}\\n\\n\\ndef get_ping(host=\\\"8.8.8.8\\\", kind='avg', num=4):\\n # solution from http://stackoverflow.com/questions/316866/ping-a-site-in-python\\n \\\"\\\"\\\"\\n returns ping time to selected site\\n host: site, ip address to ping\\n kind:\\n num: number of pings to host\\n\\n :param host: string\\n :param kind: string\\n :param num: int\\n :return: float\\n \\\"\\\"\\\"\\n assert kind in ['max', 'avg', 'mdev', 'min']\\n assert type(int(num)) is int\\n ping = subprocess.Popen([\\\"ping\\\", \\\"-c\\\", str(num), host], stdout=subprocess.PIPE, stderr=subprocess.PIPE)\\n out, error = ping.communicate()\\n out = out.split('\\\\n')\\n try:\\n out = [x for x in out if x.startswith('rtt')][0]\\n out_mapped = zip(out.split()[1].split('/'), out.split()[3].split('/'))\\n out_mapped = {x[0]: x[1] for x in out_mapped}\\n out = out_mapped[kind]\\n except IndexError:\\n # most likely no ping returned, system offline\\n out = 0\\n return float(out)\\n\\n\\ndef get_system_uptime():\\n def append_type(x, kind):\\n \\\"\\\"\\\"\\n Return 0 if days/hours/minutes equals 0 otherwise append correct plural \\\"s\\\" to type\\n ex. if systems up for 2 hours, returns \\\"2 hours\\\" likewise return \\\"1 hour\\\" if system has been up for 1 hour\\n \\\"\\\"\\\"\\n assert type(x) is int and type(kind) is str\\n if x == 0:\\n return x\\n else:\\n return '{} {}'.format(str(x), kind + 's' if x != 1 else kind)\\n\\n boot_time = datetime.datetime.fromtimestamp(psutil.boot_time()).replace(microsecond=0)\\n time_now = datetime.datetime.now().replace(microsecond=0)\\n delta = time_now - boot_time\\n formatted_time = str(delta).split(',')\\n try:\\n # System's been up a day or more\\n hours = formatted_time[1].strip().split(':')\\n except IndexError:\\n # System's been up for less than day\\n hours = formatted_time[0].strip().split(':')\\n formatted_time[0] = 0\\n hours.pop(2)\\n hours, mins = [int(hour) for hour in hours]\\n formatted_time = dict(days=formatted_time[0], hours=append_type(hours, 'hour'), min=append_type(mins, 'minute'))\\n output = dict(\\n boottime=boot_time,\\n uptime=delta,\\n uptime_formatted=formatted_time)\\n return output\\n\\n\\ndef return_network_io():\\n \\\"\\\"\\\"\\n returns Network bytes sent, and received\\n :rtype : list\\n \\\"\\\"\\\"\\n network_io = psutil.net_io_counters()\\n return [network_io.bytes_sent, network_io.bytes_recv]\\n\\n\\ndef get_network_speed(sleep=1):\\n assert type(sleep) is int\\n start_time = datetime.datetime.now()\\n start_data = return_network_io()\\n time.sleep(sleep)\\n time_delta = datetime.datetime.now() - start_time\\n end_data = return_network_io()\\n bits = 8\\n return dict(up=convert_bytes((end_data[0] - start_data[0]) / time_delta.seconds * bits, 'MB'),\\n down=convert_bytes((end_data[1] - start_data[1]) / time_delta.seconds * bits, 'MB'))\\n\\n\\ndef get_total_system_space(digits=1):\\n \\\"\\\"\\\"\\n returns total system disk space formatted, ex.\\n {'total': '8,781.9 GB', 'used': '3,023.0 GB', 'pct': 34.4, 'free': '5,313.4 GB'}\\n\\n :rtype : dict\\n :param digits: int\\n :return: dict\\n \\\"\\\"\\\"\\n assert type(digits) is int\\n all_partitions = psutil.disk_partitions(all=True)\\n # limit total disk space to those paritions mounted in \\\"/dev/\\\"\\n partitions_to_keep = [partition for partition in all_partitions if partition.device.startswith('/dev/')]\\n partitions = get_partitions(partitions_to_keep)\\n disk_space = dict(total=sum([partitions[partition].total for partition in partitions]),\\n used=sum([partitions[partition].used for partition in partitions]),\\n free=sum([partitions[partition].free for partition in partitions]))\\n disk_space_formatted = {k: convert_bytes(disk_space[k], 'GB', True, digits, True) for k in disk_space}\\n disk_space_formatted['pct'] = round(float(disk_space['used']) / float(disk_space['total']) * 100.0, digits)\\n return disk_space_formatted\\n\\n\\ndef get_partitions_space(partitions, digits=1, sort='alpha'):\\n \\\"\\\"\\\"\\n {'Home': {'total': '168.8 GB', 'pct': 44.4, 'free': '85.3 GB', 'used': '74.9 GB'},\\n 'Incoming': {'total': '293.3 GB', 'pct': 48.2, 'free': '137.0 GB', 'used': '141.4 GB'}}\\n :param partitions:\\n :param digits:\\n :return:\\n \\\"\\\"\\\"\\n assert type(partitions) is dict\\n system_partitions = get_partitions()\\n # return disk space for each partition listed in config\\n # test if listed partition actually exists in system first to avoid throwing an error\\n disk_space = {p: system_partitions[partitions[p]] for p in partitions if partitions[p] in system_partitions}\\n disk_space_formatted = {p: dict(total=convert_bytes(disk_space[p].total, 'GB', True, digits, True),\\n used=convert_bytes(disk_space[p].used, 'GB', True, digits, True),\\n free=convert_bytes(disk_space[p].free, 'GB', True, digits, True)) for p in\\n disk_space}\\n for p in disk_space:\\n disk_space_formatted[p]['pct'] = round(float(disk_space[p].used) / float(disk_space[p].total) * 100.0,\\n digits)\\n if sort.lower() == 'alpha':\\n # place in ordered dictionary so paths always display in alphabetical order on page\\n disk_space_formatted = OrderedDict(sorted(disk_space_formatted.items(), key=lambda x: x[0]))\\n return disk_space_formatted\\n\\n\\ndef get_load_average():\\n os_averages = os.getloadavg()\\n cpu_count = psutil.cpu_count()\\n final_averages = [average / cpu_count for average in os_averages]\\n return final_averages\\n\\n\\nclass GetSystemInfo(object):\\n def __init__(self):\\n pass\\n\\n def get_info(self):\\n \\\"\\\"\\\"\\n Returns system information in a dictionary\\n mem_total: Total RAM in the system in megabytes as float, ex. \\\"7876.88671875\\\"\\n mem_available: Unused RAM in the system in megabytes as float, ex. \\\"4623.8671875\\\"\\n mem_used_pct: mem_available / mem_total as float, ex. \\\"41.3\\\"\\n load_avg: tuple of avg loads at 1 min, 5 min, and 15 min, respectively, ex. \\\"(0.52, 0.51, 0.43)\\\"\\n partitions: dictionary of partitions on system, truncated ex, {''/mnt/Entertainment'':\\n sdiskusage(total=56955559936, used=15403667456, free=38635122688, percent=27.0)}\\n uptime_formatted: dictionary of uptime split in days, hours, min, ex.\\n {'hours': '2 hours', 'days': '6 days', 'min': '26 minutes'}\\n :return: dict\\n \\\"\\\"\\\"\\n mem_info = psutil.virtual_memory()\\n system_uptime = get_system_uptime()\\n load_avg = get_load_average()\\n return dict(mem_total=convert_bytes(mem_info[0], 'MB'),\\n mem_available=convert_bytes(mem_info[1], 'MB'),\\n mem_used_pct=mem_info[2],\\n mem_bars=self._memory_bars(mem_info[2]),\\n load_avg=load_avg,\\n uptime_formatted=system_uptime['uptime_formatted'])\\n\\n @staticmethod\\n def _memory_bars(val_pct):\\n mid = 50\\n upper = 80\\n ret = dict(xmin=min(val_pct, mid),\\n xmid=min(val_pct - mid, upper - mid),\\n xmax=min(val_pct - upper, 100 - upper))\\n return {k: max(ret[k], 0) for k in ret}\\n\\n\\nif __name__ == '__main__':\\n pass\"\n },\n {\n \"alpha_fraction\": 0.5777337551116943,\n \"alphanum_fraction\": 0.5846654176712036,\n \"avg_line_length\": 33.149757385253906,\n \"blob_id\": \"fb315c2adfa750709b46f81628d5f8fc4f119d6d\",\n \"content_id\": \"78361ff94d37ff8962d209a246658a039ed0094c\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 7069,\n \"license_type\": \"no_license\",\n \"max_line_length\": 87,\n \"num_lines\": 207,\n \"path\": \"/serverstatus/views.py\",\n \"repo_name\": \"beallio/media-server-status\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"\\\"\\\"\\\"\\nRouting file for flask app\\nHandles routing for requests\\n\\\"\\\"\\\"\\n\\nimport json\\nimport datetime\\n\\nfrom flask import render_template, Response, request\\n\\nfrom serverstatus import app\\nfrom assets import apifunctions\\n\\n\\n@app.route('/')\\n@app.route('/index')\\ndef index():\\n \\\"\\\"\\\"\\n Base index view at \\\"http://www.example.com/\\\"\\n \\\"\\\"\\\"\\n start_time = datetime.datetime.now()\\n return render_template('index.html',\\n title=app.config['WEBSITE_TITLE'],\\n time=datetime.datetime.now() - start_time,\\n testing=app.config['TESTING'])\\n\\n\\n@app.route('/api/<data>', methods=['GET'])\\ndef get_json(data):\\n \\\"\\\"\\\"\\n Returns API data data based on \\\"http://www.example.com/api/<data>\\\" \\n call where <data> is function is a function in the APIFunction \\n class in the apifunctions module. \\n Returns data in JSON format.\\n \\\"\\\"\\\"\\n values, status = BACKENDCALLS.get_data(data)\\n json_data = json.dumps(values)\\n # set mimetype to prevent client side manipulation since we're not using\\n # jsonify\\n return Response(json_data, status=status, mimetype='application/json')\\n\\n\\n@app.route('/html/<data>')\\ndef html_generator(data):\\n \\\"\\\"\\\"\\n Returns html rendered jinja templates based on \\\"http://www.example.com/html/<data>\\\"\\n call where <data> is a jinja template in the \\\"templates\\\" directory.\\n Returns rendered html in plain text to client, so we use this data to \\n load divs via jQuery on the client side\\n \\\"\\\"\\\"\\n values, status = BACKENDCALLS.get_data(data)\\n start = datetime.datetime.now()\\n rendered_html = render_template(data + '.html', values=values)\\n app.logger.debug(\\n 'Render time for {}: {}'.format(data, datetime.datetime.now() - start))\\n # set mimetype to prevent users browser from rendering rendered HTML\\n return Response(rendered_html, status=status, mimetype='text/plain')\\n\\n\\n@app.route('/img/<data>')\\ndef get_img_data(data):\\n \\\"\\\"\\\"\\n Returns image to client based on \\\"http://www.example.com/img/<data>\\\"\\n request where <data> is a flask request such as \\n \\\"http://www.example.com/img/subsonic?cover=28102\\\"\\n \\\"\\\"\\\"\\n start = datetime.datetime.now()\\n resp = BACKENDCALLS.get_image_data(request)\\n app.logger.debug('Image request time for {}: {}'\\n .format(data, datetime.datetime.now() - start))\\n return resp\\n\\n\\nclass BackEndCalls(object):\\n \\\"\\\"\\\"\\n Provides access points into the API Functions of the backend.\\n Also loads API configs to remedy issues where the config hasn't been\\n loaded for a particular server.\\n\\n Provides access for images requests to Plex and Subsonic\\n \\\"\\\"\\\"\\n\\n def __init__(self):\\n self.api_functions = None\\n self.api_functions = self.get_api_functions()\\n\\n def get_api_functions(self):\\n \\\"\\\"\\\"\\n Provides access to API Functions module through class\\n :return: API_Functions\\n \\\"\\\"\\\"\\n self._load_apis()\\n return self.api_functions\\n\\n def get_data(self, data):\\n \\\"\\\"\\\"\\n From flask request at http://servername.com/api/{api_call} fetches\\n {api_call} from apifunctions module, and returns data.\\n\\n Disallows public access to any function in apifunctions starting with\\n \\\"_\\\" (underscore)\\n :type data: unicode or LocalProxy\\n :return:\\n \\\"\\\"\\\"\\n values = None\\n status = 404\\n values = getattr(self.api_functions, str(data).lstrip('_'))()\\n status = 200\\n \\\"\\\"\\\"\\n try:\\n values = getattr(self.api_functions, str(data).lstrip('_'))()\\n status = 200\\n except (AttributeError, TypeError) as err:\\n app.logger.error(err)\\n # no api function for call, return empty json\\n except:\\n app.logger.error('An unknown error occurred')\\\"\\\"\\\"\\n return values, status\\n\\n def get_image_data(self, flask_request):\\n \\\"\\\"\\\"\\n Parses flask request from\\n http://servername.com/img/{plex | subsonic}?14569852 where\\n {plex|subsonic} is the server requested. Routes request to appropriate\\n server to get thumbnail image data\\n\\n :type flask_request: werkzeug.local.Request\\n :return:\\n \\\"\\\"\\\"\\n\\n def parse_request(request_args):\\n parsed_values = dict()\\n for arg in request_args:\\n if request_args[arg] == '':\\n parsed_values['plex_id'] = arg\\n continue\\n try:\\n parsed_values[arg] = bool(request_args[arg])\\n except ValueError:\\n parsed_values[arg] = request_args[arg]\\n return parsed_values\\n\\n resp = Response('null', status=404, mimetype='text/plain')\\n # convert to string since flask requests returns unicode\\n data_low = str(flask_request.view_args.get('data', None).lower())\\n if data_low == 'plex':\\n args = parse_request(flask_request.args)\\n resp = Response(\\n self.api_functions._get_plex_cover_art(args), status=200,\\n mimetype='image/jpeg')\\n elif data_low == 'subsonic':\\n resp = Response(self._check_subsonic_request(flask_request),\\n status=200,\\n mimetype='image/jpeg')\\n return resp\\n\\n def _load_apis(self):\\n \\\"\\\"\\\"\\n Check if api_functions is set, set if not.\\n\\n :return:\\n \\\"\\\"\\\"\\n if self.api_functions is None:\\n self.api_functions = apifunctions.APIFunctions(app.config)\\n\\n def _check_subsonic_request(self, request_args):\\n \\\"\\\"\\\"\\n Parses flask request to determine parameters for requesting cover art\\n from Subsonic server\\n\\n Parameters\\n ----------\\n request_args : flask.Request.args\\n Description of parameter `request_args`.\\n \\\"\\\"\\\"\\n query_string = request_args.query_string\\n args = request_args.args\\n try:\\n # check if only cover id was submitted\\n # e.g. /img/subsonic?28102\\n cover_id = int(query_string)\\n cover_size = None\\n except ValueError:\\n try:\\n # check if cover id is included in request_args\\n # e.g. /img/subsonic?cover=28102\\n cover_id = args['cover']\\n except KeyError:\\n # we need a cover to look up\\n raise\\n try:\\n # check if cover size is included in request_args\\n # e.g. /img/subsonic?cover=28102&size=145\\n cover_size = args['size']\\n try:\\n # check if cover size is an integer\\n cover_size = int(cover_size)\\n except ValueError:\\n # incorrect cover size requested\\n cover_size = None\\n except KeyError:\\n # cover size not included in request_args\\n cover_size = None\\n return self.api_functions._get_subsonic_cover_art(cover_id, cover_size)\\n\\n\\nBACKENDCALLS = BackEndCalls()\\n\"\n },\n {\n \"alpha_fraction\": 0.6527777910232544,\n \"alphanum_fraction\": 0.6666666865348816,\n \"avg_line_length\": 23.08333396911621,\n \"blob_id\": \"c934c507496df510fc29a9e1b7d12f68b7359168\",\n \"content_id\": \"637e6b8d9639a50f6ca139041aad5c3a1aa66dce\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 288,\n \"license_type\": \"no_license\",\n \"max_line_length\": 78,\n \"num_lines\": 12,\n \"path\": \"/__init__.py\",\n \"repo_name\": \"beallio/media-server-status\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#!/usr/bin/env python\\n\\\"\\\"\\\"\\nMain initializing file. If called from command line starts WSGI debug testing\\nserver\\n\\\"\\\"\\\"\\n\\nif __name__ == '__main__':\\n from serverstatus import app\\n\\n app.config.update(DEBUG=True, TESTING=True)\\n app.run(host='0.0.0.0')\\n print 'Test server running...'\"\n },\n {\n \"alpha_fraction\": 0.5970109701156616,\n \"alphanum_fraction\": 0.5996797680854797,\n \"avg_line_length\": 33.063636779785156,\n \"blob_id\": \"bc8fed43354f05bfed25c31e3b677957ef5b2f14\",\n \"content_id\": \"d6154379f7b27c5cb27798d22fc103589208ae7e\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 3747,\n \"license_type\": \"no_license\",\n \"max_line_length\": 78,\n \"num_lines\": 110,\n \"path\": \"/serverstatus/__init__.py\",\n \"repo_name\": \"beallio/media-server-status\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"\\\"\\\"\\\"\\nInitialize and setup flask app\\n\\\"\\\"\\\"\\n\\nimport imp\\nimport os\\nimport logging\\nimport logging.handlers as handlers\\n\\nfrom flask import Flask\\n\\n\\napp = Flask(__name__)\\n\\n# update config for flask app\\napp.config.update(\\n APPNAME='server_status',\\n LOGGINGMODE=logging.DEBUG,\\n APPLOCATION=os.path.join(os.path.dirname(os.path.dirname(\\n os.path.realpath(__file__)))),\\n LOG_LOCATION='/tmp',\\n TEMP_LOCATION='/tmp',\\n CONFIG_LOCATION='/var/config.py')\\napp.config['TEMP_IMAGES'] = os.path.join(app.config['TEMP_LOCATION'],\\n 'flask-images')\\napp.config['APP_MODULESLOCATION'] = os.path.join(app.config['APPLOCATION'],\\n 'serverstatus')\\n\\nimport views\\nimport assets\\nfrom assets.exceptions import MissingConfigFile\\nfrom assets.services import SubSonic\\n\\n\\ndef _setup_logger():\\n \\\"\\\"\\\"\\n Setup application logging object\\n\\n :return: logging object\\n \\\"\\\"\\\"\\n mod_logger = None\\n # use dir name thrice to return to base module path\\n log_directory = app.config.get('LOG_LOCATION', None)\\n log_location = os.path.join(log_directory,\\n '_'.join([app.config['APPNAME'], '.log']))\\n if not os.path.isdir(log_directory):\\n try:\\n os.mkdir(log_directory)\\n except IOError:\\n pass\\n if os.path.isdir(log_directory):\\n file_handler = handlers.RotatingFileHandler(filename=log_location,\\n maxBytes=3145728)\\n formatter = logging.Formatter(\\n '%(asctime)s %(name)-12s %(levelname)-8s %(message)s',\\n \\\"%Y-%m-%d %H:%M:%S\\\")\\n file_handler.setFormatter(formatter)\\n logging.getLogger('').addHandler(file_handler)\\n mod_logger = logging.getLogger(__name__)\\n mod_logger.setLevel(app.config['LOGGINGMODE'])\\n mod_logger.debug('LOGGER initialized at {}'.format(log_location))\\n return mod_logger\\n\\n\\ndef _load_config_file(mod_logger=None):\\n def gen_contents(config_data):\\n # list module contents\\n \\\"\\\"\\\"\\n Generator to return modules from config file\\n :type config_data: __builtin__.module\\n \\\"\\\"\\\"\\n mods = dir(config_data)\\n for config_attrib in mods:\\n # exclude objects that aren't our data\\n if not config_attrib.startswith('__'):\\n # create dict object since flask app config only accepts dicts\\n # on updates\\n config_value = getattr(config_data, config_attrib)\\n if config_attrib in app.config:\\n mod_logger.warning(\\n 'Overwriting existing config value {} with {}'.format(\\n config_attrib, config_value))\\n result = {config_attrib: config_value}\\n yield result\\n\\n # import config file\\n config_location = app.config.get('CONFIG_LOCATION', None)\\n try:\\n config_data_file = imp.load_source('config', config_location)\\n for data in gen_contents(config_data_file):\\n app.config.update(data)\\n if mod_logger:\\n mod_logger.info(\\n 'Config file loaded from {}'.format(config_location))\\n except IOError as e:\\n errs = dict(err=e.strerror, dir_location=config_location)\\n logger_msg = ('{err}: Configuration file could not be found at '\\n '\\\"{dir_location}\\\"').format(**errs)\\n mod_logger.critical(logger_msg)\\n raise MissingConfigFile(logger_msg)\\n\\n\\nlogger = _setup_logger() # initialize LOGGER\\n\\n# import config data from config file into flask app object\\n_load_config_file(logger)\\n\\n# remove initialization functions from namespace\\ndel _load_config_file\\ndel _setup_logger\\n\"\n },\n {\n \"alpha_fraction\": 0.6148949861526489,\n \"alphanum_fraction\": 0.6518141031265259,\n \"avg_line_length\": 26.068965911865234,\n \"blob_id\": \"f3e46170b51b636549f3b9e3e4a037c71b6ad42c\",\n \"content_id\": \"abbb507fc628673b5d51c7d2f7aa052eeb3de0e1\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1571,\n \"license_type\": \"no_license\",\n \"max_line_length\": 79,\n \"num_lines\": 58,\n \"path\": \"/config.py\",\n \"repo_name\": \"beallio/media-server-status\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"\\\"\\\"\\\"\\nInternal configuration file for Server Status app\\nChange the values according to your own server setup.\\n\\nBy default, the app is set to initialize the config file from \\\"/var/config.py\\\"\\nIf you wish to change the location you'll need to change the location of the\\nfile in serverstatus/__init__.py\\n\\nFor ForecastIO you'll need to go to https://developer.forecast.io/ and sign up\\nfor an API key (at the time of writing the first 1,000 calls/day to the API are\\nfree.\\n\\n\\n\\\"\\\"\\\"\\n\\nSUBSONIC_INFO = dict(\\n url='http://192.168.0.1',\\n serverpath='/rest',\\n port=4040,\\n user='user',\\n password='password',\\n api=1.8,\\n appname='py-sonic',\\n external_url='http://www.example.com/subsonic'\\n)\\n\\nPLEX_INFO = dict(\\n external_url='http://www.example.com/plex',\\n internal_url='http://192.168.0.1',\\n internal_port=32400,\\n user='user',\\n password='password',\\n auth_token='AUTH_TOKEN',\\n local_network_auth=False\\n)\\n\\nSERVERSYNC_INFO = dict(\\n lockfile_path='/tmp/server_sync.lockfile')\\n\\nCRASHPLAN_INFO = dict(\\n logfile_path='/usr/local/crashplan/log/app.log')\\n\\nPARTITIONS = dict(Partition_Name_1='/mnt/partition1',\\n Partition_Name_2='/mnt/partition2',\\n Partition_Name_3='/mnt/partition3',\\n Root='/',\\n Home='/home')\\n\\nINTERNAL_IP = 'http://192.168.0.1'\\nWEATHER = dict(\\n Forecast_io_API_key='FORECASTIOKEY',\\n Latitude=37.8030,\\n Longitude=-122.4360,\\n units='us')\\nSERVER_URL = 'http://www.example.com'\\nDEBUG = False\\nSECRET_KEY = 'my secret'\\nWEBSITE_TITLE = 'Your title here'\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.6029059290885925,\n \"alphanum_fraction\": 0.6035446524620056,\n \"avg_line_length\": 30.315000534057617,\n \"blob_id\": \"143b48c1fca147ea94faed0f1302431eb3930787\",\n \"content_id\": \"1f8e07a9c04ee7de49b6f32e34ce9c5a839d9140\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 6263,\n \"license_type\": \"no_license\",\n \"max_line_length\": 80,\n \"num_lines\": 200,\n \"path\": \"/serverstatus/assets/apifunctions.py\",\n \"repo_name\": \"beallio/media-server-status\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"\\\"\\\"\\\"\\nServes as backend for returning information about server to jQuery and Jinja\\ntemplates. Data is returned in the form of dicts to mimic JSON formatting.\\n\\\"\\\"\\\"\\nfrom collections import OrderedDict\\nimport logging\\n\\nfrom serverstatus.assets.weather import Forecast\\nfrom serverstatus.assets.services import CheckCrashPlan, ServerSync, Plex, \\\\\\n SubSonic\\nfrom serverstatus.assets.sysinfo import GetSystemInfo, get_network_speed, \\\\\\n get_ping, get_wan_ip, get_partitions_space, get_total_system_space\\nimport serverstatus.assets.wrappers as wrappers\\n\\n\\nclass APIFunctions(object):\\n \\\"\\\"\\\"\\n Serves as backend for returning information about server to jQuery and Jinja\\n templates. Data is returned in the form of dicts to mimic JSON formatting.\\n\\n Any function within the APIFunctions class maybe called externally as long\\n as the function does not start with \\\"_\\\". For example, a user/website may\\n return data from http://foobar.com/api/system_info but not\\n http://foobar.com/api/_get_plex_cover_art\\n\\n Examples to return data:\\n To return system info:\\n http://foobar.com/api/system_info\\n\\n To return network speed:\\n http://foobar.com/api/network_speed\\n \\\"\\\"\\\"\\n def __init__(self, config):\\n self.logger = LOGGER\\n LOGGER.debug('{} initialized'.format(__name__))\\n self.config = config\\n self.subsonic = None\\n self.plex = None\\n self.server_sync = None\\n self.crashplan = None\\n self.weather = None\\n\\n @staticmethod\\n @wrappers.logger('debug')\\n def system_info():\\n \\\"\\\"\\\"\\n Returns data for system info section (memory, load, uptime)\\n\\n :return: dict\\n \\\"\\\"\\\"\\n get_system_info = GetSystemInfo()\\n output = get_system_info.get_info()\\n return output\\n\\n @staticmethod\\n @wrappers.logger('debug')\\n def network_speed():\\n \\\"\\\"\\\"\\n Returns server network speed. Sleep defines the length of time in\\n between polling for network IO data to calculate speed based off delta\\n\\n :return: dict\\n \\\"\\\"\\\"\\n return get_network_speed(sleep=5)\\n\\n @staticmethod\\n @wrappers.logger('debug')\\n def ping():\\n \\\"\\\"\\\"\\n Returns ping from Google DNS (default)\\n\\n :return: dict\\n \\\"\\\"\\\"\\n return dict(ping='{:.0f}'.format(get_ping()))\\n\\n @wrappers.logger('debug')\\n def storage(self):\\n \\\"\\\"\\\"\\n Returns formatted storage data based off options selected in Config file\\n\\n :return: dict\\n \\\"\\\"\\\"\\n paths = get_partitions_space(self.config['PARTITIONS'])\\n return dict(total=get_total_system_space(), paths=paths)\\n\\n @wrappers.logger('debug')\\n def ip_address(self):\\n \\\"\\\"\\\"\\n Returns servers internal and external IP addresses\\n\\n :return: dict\\n \\\"\\\"\\\"\\n return dict(wan_ip=get_wan_ip(), internal_ip=self.config['INTERNAL_IP'])\\n\\n @wrappers.logger('debug')\\n def services(self):\\n \\\"\\\"\\\"\\n Returns sorted status mappings for servers listed in config file\\n :return: dict\\n \\\"\\\"\\\"\\n self._load_configs()\\n servers = [self.plex, self.subsonic, self.server_sync, self.crashplan]\\n servers_mapped = [getattr(server, 'status_mapping') for server in\\n servers]\\n servers_dict = OrderedDict()\\n for server in servers_mapped:\\n servers_dict = OrderedDict(servers_dict.items() + server.items())\\n return servers_dict\\n\\n @wrappers.logger('debug')\\n def media(self):\\n \\\"\\\"\\\"\\n Returns now playing data for Plex and Subsonic (if any), and recently\\n added items for both\\n\\n :return: dict\\n \\\"\\\"\\\"\\n self._load_configs()\\n subsonic = self.subsonic\\n plex = self.plex\\n return dict(\\n subsonic_nowplaying=subsonic.now_playing(),\\n plex_nowplaying=plex.now_playing(),\\n subsonic_recentlyadded=subsonic.recently_added(num_results=6),\\n plex_recentlyadded=plex.recently_added(num_results=6))\\n\\n @wrappers.logger('debug')\\n def forecast(self):\\n \\\"\\\"\\\"\\n Gets forecast data from forecast.io\\n\\n :return: dict\\n \\\"\\\"\\\"\\n self._load_configs()\\n self.weather.reload_data()\\n return self.weather.get_data()\\n\\n @wrappers.logger('debug')\\n def plex_transcodes(self):\\n \\\"\\\"\\\"\\n Gets number of transcodes from Plex\\n\\n :return: dict\\n \\\"\\\"\\\"\\n self._load_configs()\\n return dict(plex_transcodes=self.plex.transcodes)\\n\\n def _get_plex_cover_art(self, args):\\n \\\"\\\"\\\"\\n Gets Plex cover art passing flask requests into Plex class\\n\\n :return: image\\n \\\"\\\"\\\"\\n self._load_configs()\\n return self.plex.get_cover_image(**args)\\n\\n def _get_subsonic_cover_art(self, cover_id, size):\\n \\\"\\\"\\\"\\n Gets subsonic cover art passing flask requests into Subsonic class\\n\\n :return: image\\n \\\"\\\"\\\"\\n self._load_configs()\\n cover_id = int(cover_id)\\n return self.subsonic.get_cover_art(cover_id, size)\\n\\n def _load_configs(self):\\n \\\"\\\"\\\"\\n Loads config data for Service subclasses if not already loaded to\\n prevent errors.\\n :return: Service class\\n \\\"\\\"\\\"\\n if self.subsonic is None:\\n try:\\n self.subsonic = SubSonic(self.config['SUBSONIC_INFO'])\\n except KeyError:\\n LOGGER.debug('Subsonic not loaded yet')\\n if self.plex is None:\\n try:\\n self.plex = Plex(self.config['PLEX_INFO'])\\n except KeyError:\\n LOGGER.debug('Plex not loaded yet')\\n if self.server_sync is None:\\n try:\\n self.server_sync = ServerSync(self.config['SERVERSYNC_INFO'])\\n except KeyError:\\n LOGGER.debug('Server Sync not loaded yet')\\n if self.crashplan is None:\\n try:\\n self.crashplan = CheckCrashPlan(self.config['CRASHPLAN_INFO'])\\n except KeyError:\\n LOGGER.debug('CrashPlan not loaded yet')\\n if self.weather is None:\\n try:\\n self.weather = Forecast(self.config['WEATHER'])\\n except KeyError:\\n LOGGER.debug('weather not loaded yet')\\n\\n\\nLOGGER = logging.getLogger(__name__)\\n\"\n },\n {\n \"alpha_fraction\": 0.6300366520881653,\n \"alphanum_fraction\": 0.636884868144989,\n \"avg_line_length\": 31.538860321044922,\n \"blob_id\": \"18c1e1f8f33dac2920ba62e898caba0aa842bf14\",\n \"content_id\": \"263d3362b3d20892229e879c8db7559950f2ffde\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 6279,\n \"license_type\": \"no_license\",\n \"max_line_length\": 78,\n \"num_lines\": 193,\n \"path\": \"/serverstatus/tests/test_serverstatus.py\",\n \"repo_name\": \"beallio/media-server-status\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import urllib2\\nimport unittest\\nfrom collections import OrderedDict\\nfrom copy import deepcopy\\n\\nfrom flask import Flask\\nfrom flask.ext.testing import LiveServerTestCase\\n\\nfrom serverstatus import app\\nfrom serverstatus.assets.apifunctions import APIFunctions\\nfrom serverstatus.assets.services import ServerSync, SubSonic\\nfrom serverstatus.assets.weather import Forecast\\n\\n\\nclass TestApiFunctions(unittest.TestCase):\\n def setUp(self):\\n self.app = app.test_client()\\n self.apifunctions = APIFunctions(app.config)\\n\\n def test_ping(self):\\n self.assertTrue(isinstance(self.apifunctions.ping(), dict))\\n\\n def test_system_info(self):\\n self.assertTrue(isinstance(self.apifunctions.system_info(), dict))\\n\\n def test_storage(self):\\n self.assertTrue(isinstance(self.apifunctions.storage(), dict))\\n\\n def test_network_speed(self):\\n self.assertTrue(isinstance(self.apifunctions.network_speed(), dict))\\n\\n def test_services(self):\\n self.assertTrue(isinstance(self.apifunctions.services(), OrderedDict))\\n\\n def test_weather(self):\\n self.assertTrue(isinstance(self.apifunctions.forecast(), dict))\\n\\n def test_media(self):\\n results = self.apifunctions.media()\\n self.assertIsInstance(results, dict)\\n for key in results:\\n if 'plex_nowplaying' in key:\\n self.plex_nowplaying(results[key])\\n if 'plex_recentlyadded' in key:\\n self.plex_recentlyadded(results[key])\\n if 'subsonic_nowplaying' in key:\\n self.subsonic_nowplaying(results[key])\\n\\n def test_plex_transcodes(self):\\n self.assertTrue(isinstance(self.apifunctions.plex_transcodes(), dict))\\n\\n def plex_recentlyadded(self, result):\\n self.assertIsInstance(result, dict)\\n for vid_type in result:\\n self.assertIsInstance(result[vid_type], list)\\n for video in result[vid_type]:\\n self.assertIsInstance(video, dict)\\n\\n def subsonic_recentlyadded(self, result):\\n self.assertIsInstance(result, list)\\n for album in result:\\n self.assertIsInstance(result[album], dict)\\n\\n def plex_nowplaying(self, result):\\n if not result:\\n self.assertIs(result, None)\\n if result:\\n self.assertIsInstance(result, list)\\n for video in result:\\n self.assertIsInstance(video, dict)\\n\\n def subsonic_nowplaying(self, result):\\n if not result:\\n self.assertIs(result, None)\\n if result:\\n for key in result:\\n self.assertIsInstance(result[key], dict)\\n\\n\\nclass TestSubSonicServer(unittest.TestCase):\\n def setUp(self):\\n self.app = app.test_client()\\n self.config = app.config['SUBSONIC_INFO']\\n self.config_test_values = dict(\\n url='http://192.168.1.100',\\n port=40,\\n user='guestuser',\\n password='password',\\n serverpath='/subbybad/'\\n )\\n\\n def est_bad_config_values(self):\\n for key in self.config_test_values:\\n config = deepcopy(self.config)\\n config[key] = self.config_test_values[key]\\n self.subsonic = SubSonic(config)\\n print key, self.config_test_values[key]\\n self.assertTrue(self.subsonic.connection_status)\\n\\n def test_bad_server_url(self):\\n bad_url = 'http://192.168.1.100'\\n config = deepcopy(self.config)\\n config['url'] = bad_url\\n self.subsonic = SubSonic(config)\\n self.assertFalse(self.subsonic.connection_status)\\n\\n def test_bad_port(self):\\n config = deepcopy(self.config)\\n config['port'] = 40\\n self.subsonic = SubSonic(config)\\n self.assertFalse(self.subsonic.connection_status)\\n\\n def test_bad_username(self):\\n config = deepcopy(self.config)\\n config['user'] = 'guestuser'\\n self.subsonic = SubSonic(config)\\n self.assertFalse(self.subsonic.connection_status)\\n\\n def test_bad_password(self):\\n config = deepcopy(self.config)\\n config['password'] = 'password'\\n self.subsonic = SubSonic(config)\\n self.assertFalse(self.subsonic.connection_status)\\n\\n def test_bad_serverpath(self):\\n config = deepcopy(self.config)\\n config['serverpath'] = '/subbybad/'\\n self.subsonic = SubSonic(config)\\n self.assertFalse(self.subsonic.connection_status)\\n\\n\\nclass TestForecastIO(unittest.TestCase):\\n def setUp(self):\\n self.app = app.test_client()\\n self.config = app.config['WEATHER']\\n\\n def test_bad_apikey(self):\\n config = deepcopy(self.config)\\n config['Forecast_io_API_key'] = 'thisisabadkey'\\n with self.assertRaises(ValueError):\\n Forecast(config)\\n\\n\\nclass TestServerSync(unittest.TestCase):\\n def setUp(self):\\n self.app = app.test_client()\\n self.config = app.config['SERVERSYNC_INFO']\\n\\n def test_no_lockfile_path(self):\\n config = deepcopy(self.config)\\n del config['lockfile_path']\\n serversync = ServerSync(config)\\n self.assertFalse(serversync.connection_status)\\n\\n def test_bad_lockfile_path(self):\\n config = deepcopy(self.config)\\n config['lockfile_path'] = '/tmp/badfile.lock'\\n serversync = ServerSync(config)\\n self.assertFalse(serversync.connection_status)\\n\\n\\nclass TestLiveServer(LiveServerTestCase):\\n server_address = 'http://192.168.1.101/status/'\\n\\n def create_app(self):\\n self.app = Flask(__name__)\\n self.app.config.update(TESTING=True, LIVESERVER_PORT=8943)\\n return self.app\\n\\n def test_server_is_up_and_running(self):\\n response = urllib2.urlopen(TestLiveServer.server_address)\\n self.assertEqual(response.code, 200)\\n\\n\\n\\\"\\\"\\\"\\nclass TestDebugServer(flaskTestCase):\\n def create_app(self):\\n app = Flask(__name__)\\n app.config['TESTING'] = True\\n return app\\n\\n def test_some_json(self):\\n functions_to_test = (func for func in dir(APIFunctions) if not\\n func.startswith('_'))\\n for func in functions_to_test:\\n test_api = '/api/' + func\\n response = self.client.get(test_api)\\n print 'hi'\\n self.assertEquals(response.json, dict())\\n\\\"\\\"\\\"\\n\\nif __name__ == '__main__':\\n unittest.main()\"\n },\n {\n \"alpha_fraction\": 0.5412545204162598,\n \"alphanum_fraction\": 0.5444556474685669,\n \"avg_line_length\": 39.60304260253906,\n \"blob_id\": \"6a931ffce662672dd2b25f35ea791d6fc04a2fae\",\n \"content_id\": \"8b6cc241a4151aba0d6fc31a33dfbc7f2add7687\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 34675,\n \"license_type\": \"no_license\",\n \"max_line_length\": 80,\n \"num_lines\": 854,\n \"path\": \"/serverstatus/assets/services.py\",\n \"repo_name\": \"beallio/media-server-status\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import os\\nimport logging\\nimport urllib2\\nimport urlparse\\nfrom collections import OrderedDict\\nfrom operator import itemgetter\\nfrom time import localtime, strftime\\nimport datetime\\nfrom cStringIO import StringIO\\n\\nfrom PIL import Image, ImageOps\\nimport libsonic\\nimport xmltodict\\n\\nfrom serverstatus import app\\nimport serverstatus.assets.exceptions as exceptions\\n\\n\\nLOGGER = logging.getLogger(__name__)\\n\\n\\nclass Service(object):\\n def __init__(self, service_config):\\n assert isinstance(service_config, dict)\\n self.logger = LOGGER\\n self.logger.debug(\\n '{} class initialized'.format(self.__class__.__name__))\\n self.service_config = service_config\\n self._services_status_mapping = self._status_mappings_dict()\\n self._service_name = None\\n self._connect_status = None\\n self._server_full_url = None\\n self._resolved_status_mapping = dict()\\n self._temp_img_dir = app.config.get('TEMP_IMAGES', '/tmp')\\n\\n @property\\n def service_name(self):\\n return self._service_name\\n\\n @property\\n def status_mapping(self):\\n self._resolved_status_mapping = self._map_connection_status()\\n return self._resolved_status_mapping\\n\\n @property\\n def connection_status(self):\\n self._connect_status = self._test_server_connection()\\n return self._connect_status\\n\\n @property\\n def server_full_url(self):\\n return self._server_full_url\\n\\n @property\\n def external_url(self):\\n return self._get_config_attrib('external_url')\\n\\n @staticmethod\\n def convert_date_fmt(date_str, fmt_str_in, fmt_str_out):\\n dt_value = datetime.datetime.strptime(date_str, fmt_str_in)\\n return dt_value.strftime(fmt_str_out)\\n\\n def _test_server_connection(self):\\n # method to be overridden by subclasses\\n return\\n\\n def _map_connection_status(self):\\n service_name = self._service_name\\n output = {service_name: dict()}\\n try:\\n output = {service_name: self._services_status_mapping[\\n str(self.connection_status)]}\\n output[service_name][\\n 'title'] = self._add_service_name_to_status_mapping()\\n if self.external_url:\\n output[service_name]['external_url'] = self.external_url\\n except KeyError:\\n pass\\n return output\\n\\n def _add_service_name_to_status_mapping(self):\\n delim = '-'\\n service_name = self._service_name\\n if delim in service_name:\\n title = service_name.split(delim)\\n title = ' '.join([w.title() for w in title])\\n else:\\n title = service_name.title()\\n return title\\n\\n def _get_config_attrib(self, attrib):\\n try:\\n return self.service_config[attrib]\\n except KeyError:\\n # Config attribute not found\\n return None\\n\\n @staticmethod\\n def _status_mappings_dict():\\n return dict(\\n False=dict(\\n text='Offline',\\n icon='icon-off icon-white',\\n css_class='btn_mod btn btn-xs btn-danger',\\n ),\\n True=dict(\\n text='Online',\\n icon='icon-ok icon-white',\\n css_class='btn_mod btn btn-xs btn-success',\\n ),\\n ServerSyncActive=dict(\\n text='Online',\\n icon='icon-download icon-white',\\n css_class='btn_mod btn btn-xs btn-success',\\n ),\\n BackupServerActive=dict(\\n text='Active',\\n icon='icon-upload icon-white',\\n css_class='btn_mod btn btn-xs btn-success',\\n ),\\n Waiting=dict(\\n text='Pending',\\n icon='icon-pause icon-white',\\n css_class='btn_mod btn btn-xs btn-warning',\\n )\\n )\\n\\n def _log_warning_for_missing_config_value(self, cls_name, config_val,\\n default):\\n # Log warning that config value for plex is missing from config file.\\n # Using default value instead\\n self.logger.warning(\\n ('{config_val} missing from config value for {cls_name}. '\\n 'Using {default} instead').\\n format(cls_name=cls_name, default=default, config_val=config_val))\\n\\n @staticmethod\\n def _convert_xml_to_json(resp_output):\\n return xmltodict.parse(resp_output)\\n\\n @staticmethod\\n def _build_external_img_path(service_name):\\n base_path = 'img/'\\n return ''.join([base_path, service_name, '?'])\\n\\n def _test_file_path(self, file_path_key):\\n # //TODO Needed\\n output = None\\n try:\\n file_path = self.service_config[file_path_key]\\n if os.path.exists(file_path):\\n output = file_path\\n except KeyError as err:\\n self.logger.error(err)\\n finally:\\n return output\\n\\n\\nclass SubSonic(Service):\\n def __init__(self, server_info):\\n Service.__init__(self, server_info)\\n self._service_name = 'subsonic'\\n self.conn = libsonic.Connection(baseUrl=self.service_config['url'],\\n username=self.service_config['user'],\\n password=self.service_config[\\n 'password'],\\n port=self.service_config['port'],\\n appName=self.service_config['appname'],\\n apiVersion=self.service_config['api'],\\n serverPath=self.service_config[\\n 'serverpath'])\\n self._connect_status = self._test_server_connection()\\n self._server_full_url = self._get_server_full_url()\\n self._resolved_status_mapping = self._map_connection_status()\\n self._img_base_url = self._build_external_img_path(\\n self._service_name) + 'cover='\\n\\n def recently_added(self, num_results=None):\\n \\\"\\\"\\\"\\n Returns recently added entries.\\n\\n :param num_results: number of recently added results to return\\n :type num_results: int\\n :return: list of [dict]\\n \\\"\\\"\\\"\\n\\n def recently_added_generator(num):\\n recently_added = self.conn.getAlbumList(\\\"newest\\\", num)['albumList'][\\n 'album']\\n for album in recently_added:\\n yield album\\n return\\n\\n if num_results is None:\\n num_results = 10\\n return [self._get_entry_info(entry, min_size=145, max_size=500) for\\n entry in recently_added_generator(num_results)]\\n\\n def get_cover_art(self, cover_art_id, size=None):\\n assert isinstance(cover_art_id, int)\\n if any([size is None, size <= 0, type(size) is not int]):\\n return self.conn.getCoverArt(aid=cover_art_id)\\n else:\\n if size > 2000:\\n # set max limit on size of photo returned\\n size = 2000\\n return self.conn.getCoverArt(aid=cover_art_id, size=size)\\n\\n def now_playing(self):\\n \\\"\\\"\\\"\\n Returns now playing entries from Subsonic server in list format. Each\\n entry in list represents one song currently playing from server. Each\\n entry in list is a dict\\n\\n :returns: list of [dict]\\n \\\"\\\"\\\"\\n entries = []\\n now_playing = self.conn.getNowPlaying()\\n try:\\n many_songs_playing = isinstance(now_playing['nowPlaying']['entry'],\\n list)\\n except (KeyError, TypeError):\\n # no songs playing\\n return None\\n if many_songs_playing:\\n # multiple songs playing\\n entries = [self._get_entry_info(entry) for entry in\\n now_playing['nowPlaying']['entry']]\\n elif not many_songs_playing:\\n # single song playing\\n entries.append(\\n self._get_entry_info(now_playing['nowPlaying']['entry']))\\n # remove entries from now playing if user hasn't touched them or\\n # playlist auto advanced in X min\\n results = [self._get_entry_info(entry, max_size=800) for entry in\\n entries if entry['minutesAgo'] <= 10]\\n if results:\\n return results\\n else:\\n return None\\n\\n def set_output_directory(self, directory):\\n # //TODO remove extraneous code\\n self._temp_img_dir = directory\\n return self._temp_img_dir == directory\\n\\n def _test_server_connection(self):\\n \\\"\\\"\\\"\\n Test if we're able to connect to Subsonic server.\\n\\n :return: bool - True if able to connect, false otherwise\\n :raise: exceptions.SubsonicConnectionError\\n \\\"\\\"\\\"\\n connection_status = False\\n try:\\n connection_status = self.conn.ping()\\n assert connection_status\\n except AssertionError:\\n err = 'Unable to reach Subsonic server'\\n self.logger.error(err)\\n # raise exceptions.SubsonicConnectionError(err)\\n finally:\\n return connection_status\\n\\n def _create_cover_art_file(self, cover_art_id, size=None):\\n \\\"\\\"\\\"\\n size in get_cover_art method for subsonic returns a square image with\\n dimensions in pixels equal to size\\n :param cover_art_id:\\n :return:\\n \\\"\\\"\\\"\\n # set default image size in pixels\\n if size is None:\\n size = 600\\n img_data = self.conn.getCoverArt(aid=cover_art_id, size=size)\\n cover_dir = self._temp_img_dir # temp storage for created image files\\n filename = 'cover'\\n ext = '.jpg'\\n short_filepath = filename + str(cover_art_id) + '_' + str(size) + ext\\n full_filepath = os.path.join(cover_dir, short_filepath)\\n if not os.path.exists(cover_dir):\\n # check if filepath exists. Attempt to create if it doesn't\\n try:\\n os.mkdir(cover_dir)\\n except IOError:\\n self.logger.error(\\n 'Failed to create cover art directory: {}'.format(\\n full_filepath))\\n return\\n if not os.path.isfile(full_filepath):\\n self.logger.info('Write cover art file: {}'.format(full_filepath))\\n with open(full_filepath, 'wb') as img_file:\\n img_file.write(img_data.read())\\n return full_filepath\\n\\n def _get_entry_info(self, entry, min_size=None, max_size=None):\\n \\\"\\\"\\\"\\n appends URL coverart link to Subsonic entry dict\\n :param entry: subsonic entry\\n :type entry: dict\\n :return: dict\\n \\\"\\\"\\\"\\n assert type(entry) == dict\\n if min_size:\\n min_size = 145\\n if max_size:\\n max_size = 1200\\n # create url link to thumbnail coverart, and full-size coverart\\n cover_art_link = [''.join([self._img_base_url,\\n str(entry.get('coverArt', entry['id'])),\\n '&size=',\\n str(size)]) for size in (min_size, max_size)]\\n entry.update(coverArtExternalLink_sm=cover_art_link[0],\\n coverArtExternalLink_xl=cover_art_link[1])\\n try:\\n created_date = self.convert_date_fmt(entry[u'created'],\\n '%Y-%m-%dT%H:%M:%S.%fZ',\\n '%m/%d/%Y %I:%M%p')\\n except ValueError as dt_conv_err:\\n self.logger.error('Error converting date: {}'.format(dt_conv_err))\\n else:\\n entry[u'created'] = created_date\\n try:\\n # Return progress on currently playing song(s). No good way to do\\n # this since Subsonic doesn't have access to this info through\\n # it's API. Calculate progress by taking last time\\n # song was accessed divide by progress\\n entry['progress'] = min(\\n float(entry['minutesAgo']) / float(entry['duration'] / 60), 1)\\n except KeyError:\\n entry['progress'] = 1\\n finally:\\n entry.update(progress_pct='{:.2%}'.format(entry['progress']),\\n progress=entry['progress'] * 100)\\n return entry\\n\\n def _get_server_full_url(self):\\n serverpath = self.service_config['serverpath'].strip('/')\\n try:\\n serverpath, _ = serverpath.split('/')\\n except ValueError as err:\\n self.logger.warning(\\n 'Issue parsing Subsonic server path: {}'.format(err))\\n return '{url}:{port:d}/{path}'.format(url=self.service_config['url'],\\n port=self.service_config['port'],\\n path=serverpath)\\n\\n\\nclass CheckCrashPlan(Service):\\n def __init__(self, server_info):\\n Service.__init__(self, server_info)\\n self._service_name = 'backups'\\n self.file_path = self._test_file_path('logfile_path')\\n self._connect_status = self._test_server_connection()\\n self._resolved_status_mapping = self._map_connection_status()\\n\\n def _test_server_connection(self):\\n items_to_keep = ['scanning', 'backupenabled']\\n with open(self.file_path, 'r') as log_file:\\n items = [line.lower().split() for line in log_file.readlines()\\n for x in items_to_keep if x in line.lower()]\\n # remove \\\"=\\\" from list\\n for item in items:\\n item.remove('=')\\n items_values = [True if item[1] == 'true' else False for item in items]\\n if all(items_values):\\n return 'BackupServerActive'\\n elif any(items_values):\\n return 'Waiting'\\n else:\\n return False\\n\\n\\nclass ServerSync(Service):\\n def __init__(self, server_info):\\n Service.__init__(self, server_info)\\n self.server_info = server_info\\n self.lockfile_path = self.server_info.get('lockfile_path', None)\\n self._service_name = 'server-sync'\\n self._connect_status = self._test_server_connection()\\n self._resolved_status_mapping = self._map_connection_status()\\n\\n def _test_server_connection(self):\\n try:\\n return os.path.exists(self.lockfile_path)\\n except TypeError:\\n self.logger.debug('Server Sync Lockfile does not exist at {}'.\\n format(self.lockfile_path))\\n return False\\n\\n\\nclass Plex(Service):\\n \\\"\\\"\\\"\\n Note: Plex requires a PlexPass for access to the server API. Plex won't\\n allow you to connect to API otherwise\\n\\n Provides media metadata information from Plex\\n \\\"\\\"\\\"\\n url_scheme = 'http://'\\n\\n def __init__(self, server_config):\\n Service.__init__(self, server_config)\\n assert type(server_config) is dict\\n self.service_config = server_config\\n self._service_name = 'plex'\\n self.server_internal_url_and_port = self._get_full_url_and_port\\n try:\\n self._server_full_url = server_config['external_url']\\n except KeyError as err:\\n self.logger.error(\\n 'Missing config value {config_value} from {cls}'.format(\\n config_value='external_url',\\n cls=self.__class__.__name__))\\n raise exceptions.MissingConfigValue(err)\\n self._connect_status = self._test_server_connection()\\n self._resolved_status_mapping = self._map_connection_status()\\n self._transcodes = 0\\n self._cover_mapping = dict()\\n self._img_base_url = self._build_external_img_path(self._service_name)\\n\\n def recently_added(self, num_results=None):\\n \\\"\\\"\\\"\\n\\n :type num_results: int or unknown\\n :return: dict of [lists]\\n \\\"\\\"\\\"\\n\\n def process_video_data(videos):\\n # sort the recently added list by date in descending order\\n videos = sorted(videos, key=itemgetter('@addedAt'), reverse=True)\\n # trim the list to the number of results we want\\n videos_trimmed = videos[:num_results]\\n return [self._get_video_data(video) for video in videos_trimmed]\\n\\n if not self._connect_status:\\n return None\\n if any([num_results is None, type(num_results) is not int]):\\n # Check if correct for maximum number of results is entered\\n # if not set default\\n num_results = 6\\n api_call = 'recentlyadded'\\n json_data = self._get_xml_convert_to_json(api_call)\\n # the media value we want are contained in lists so loop through the\\n # MediaContainer, find the lists of data, and return each value in\\n # the lists. The lists contain Movies and Shows separately.\\n\\n movies = [media for value in json_data['MediaContainer'] if\\n type(json_data['MediaContainer'][value]) == list for\\n media in json_data['MediaContainer'][value] if\\n media['@type'] != 'season']\\n tv_shows = [media for value in json_data['MediaContainer'] if\\n type(json_data['MediaContainer'][value]) == list for\\n media in json_data['MediaContainer'][value] if\\n media['@type'] == 'season']\\n # remove extra data\\n del json_data\\n return dict(Movies=process_video_data(movies),\\n TVShows=process_video_data(tv_shows))\\n\\n def now_playing(self):\\n \\\"\\\"\\\"\\n Returns now playing data from Plex server in a JSON-like dictionary\\n\\n :return: dict()\\n \\\"\\\"\\\"\\n\\n def generate_video_data(vid_data, api_call=None):\\n \\\"\\\"\\\"\\n Generator function for creating relevant video data. Takes JSON\\n data, checks if is data is an OrderedDict\\n then grabs the relevant data if the video is a TV show or Movie.\\n \\\"\\\"\\\"\\n # In JSON form Plex returns multiple videos as a list of\\n # OrderedDicts, and a single video as an OrderedDict\\n # Convert the single video to a list for processing\\n if isinstance(vid_data, OrderedDict):\\n video_list = list()\\n video_list.append(vid_data)\\n elif isinstance(vid_data, list):\\n video_list = vid_data\\n else:\\n # Plex returned data that we haven't seen before.\\n # Raise exception to warn user.\\n msg = (\\n 'Plex returned API data that does not match to known '\\n 'standards.Plex return data as {} when it should return a '\\n 'list or OrderedDict').format(type(vid_data))\\n self.logger.error(msg)\\n raise exceptions.PlexAPIDataError(msg)\\n for video in video_list:\\n # Grab relevant data about Video from JSON data, send the API\\n # call to calculate _transcodes, otherwise it will skip and\\n # return 0\\n yield self._get_video_data(video, api_call)\\n return\\n\\n self._transcodes = 0 # reset serverinfo count\\n api_call = 'nowplaying'\\n now_playing_relevant_data = list()\\n json_data = self._get_xml_convert_to_json(api_call)\\n if not int(json_data['MediaContainer']['@size']):\\n # Nothing is currently playing in plex\\n return None\\n for vid in generate_video_data(json_data['MediaContainer']['Video'],\\n api_call):\\n now_playing_relevant_data.append(vid)\\n return now_playing_relevant_data\\n\\n def get_cover_image(self, plex_id, thumbnail=None, local=None):\\n \\\"\\\"\\\"\\n Returns binary jpeg object for Plex item found local temp directory as\\n set in config file. Checks request argument against mapped value from\\n Plex item ID\\n\\n :param plex_id: metadata coverart ID that corresponds to mapping\\n dictionary\\n :type plex_id: str\\n :param thumbnail: boolean values that tells us to return thumbnail\\n image if True. Returns full scale image if False\\n :type thumbnail: bool or NoneType\\n :param local: boolean value that tells us to pull image from Plex\\n server or return local copy\\n :type local: bool or NoneType\\n :return: binary\\n :raises: exceptions.PlexImageError\\n \\\"\\\"\\\"\\n\\n def open_image(ext):\\n try:\\n return open(os.path.join(self._temp_img_dir, plex_id + ext),\\n 'rb')\\n except IOError as img_err:\\n raise exceptions.PlexImageError(img_err)\\n\\n thumbnail = thumbnail is not None\\n local = local is not None\\n if self._cover_mapping is None:\\n # if _cover_mapping is empty we need to initialize Now Playing\\n self.now_playing()\\n if thumbnail:\\n resp = open_image('.thumbnail')\\n elif local:\\n resp = open_image('.jpg')\\n else:\\n try:\\n resp = urllib2.urlopen(\\n urlparse.urljoin(self.server_internal_url_and_port,\\n self._cover_mapping[plex_id]))\\n except (TypeError, urllib2.HTTPError) as err:\\n raise exceptions.PlexImageError(err)\\n return resp\\n\\n @property\\n def transcodes(self):\\n \\\"\\\"\\\"\\n Returns number of current number of Plex transcode sessions\\n\\n >>> 0\\n >>> 1\\n\\n :return: int\\n \\\"\\\"\\\"\\n server_info = self.plex_server_info()\\n self._transcodes = server_info.get('transcoderActiveVideoSessions', 0)\\n return self._transcodes\\n\\n def plex_server_info(self):\\n json_show_data = self._get_xml_convert_to_json('serverinfo')\\n server_data = json_show_data.get('MediaContainer', None)\\n data_dict = {str(key.strip('@')): server_data[key] for key in\\n server_data if type(server_data[key]) is unicode or\\n type(server_data[key]) is str}\\n for key in data_dict:\\n try:\\n data_dict[key] = int(data_dict[key])\\n except ValueError:\\n if ',' in data_dict[key]:\\n split_values = data_dict[key].split(',')\\n data_dict[key] = [int(val) for val in split_values]\\n return data_dict\\n\\n def _test_server_connection(self):\\n \\\"\\\"\\\"\\n Test if connection to Plex is active or not\\n >>> True\\n >>> False\\n :return: bool\\n \\\"\\\"\\\"\\n resp = None\\n try:\\n if self.service_config['local_network_auth']:\\n # local network authentication required\\n # // TODO Need to complete code for authorization if necessary\\n pass\\n except KeyError:\\n pass\\n resp = self._get_plex_api_data('serverinfo')\\n is_connectable = resp is not None\\n if not is_connectable:\\n self.logger.error('Could not connect to Plex server')\\n return is_connectable\\n\\n def _get_api_url_suffix(self, url_suffix):\\n \\\"\\\"\\\"\\n https://code.google.com/p/plex-api/wiki/PlexWebAPIOverview\\n contains information required Plex HTTP APIs\\n\\n serverinfo: Transcode bitrateinfo, myPlexauthentication info\\n nowplaying: This will retrieve the \\\"Now Playing\\\" Information of the PMS.\\n librarysections: Contains all of the sections on the PMS. This acts as\\n a directory and you are able to \\\"walk\\\" through it.\\n prefs: Gets the server preferences\\n servers: get the local List of servers\\n ondeck: Show ondeck list\\n channels_all: Returns all channels installed in Plex Server\\n channels_recentlyviewed: Get listing of recently viewed channels\\n recentlyadded: Gets listing of recently added media, in descending\\n order by date added\\n metadata: Returns metadata from media, e.g. /library/metadata/<val>\\n when <val> is an integer tied to a specific episode or movie\\n\\n >>> '/library/recentlyAdded'\\n\\n :param the_data_were_looking_for:\\n :return:\\n \\\"\\\"\\\"\\n url_api_mapping = dict(\\n serverinfo='/',\\n nowplaying='/status/sessions',\\n librarysections='/library/sections',\\n prefs='/:/prefs',\\n servers='/servers',\\n ondeck='/library/onDeck',\\n channels_all='/channels/all',\\n recentlyadded='/library/recentlyAdded',\\n metadata='/library/metadata/'\\n )\\n try:\\n results = url_api_mapping[url_suffix]\\n except KeyError as err:\\n self.logger.error(err)\\n raise exceptions.PlexAPIKeyNotFound(err)\\n return results\\n\\n @property\\n def _get_full_url_and_port(self):\\n \\\"\\\"\\\"\\n builds out internal url with port\\n\\n >>> 'http://localhost:32400'\\n >>> 'http://192.168.0.1:32400'\\n\\n :return: str\\n \\\"\\\"\\\"\\n port = str(self.service_config.get('internal_port', '32400'))\\n if port != self.service_config.get('internal_port') or str(port) != \\\\\\n self.service_config.get('internal_port'):\\n self._log_warning_for_missing_config_value(\\n cls_name=self.__class__.__name__, default=port,\\n config_val='port')\\n try:\\n internal_url = self.service_config['internal_url'].replace(\\n Plex.url_scheme, '').lstrip('/')\\n except KeyError:\\n internal_url = 'localhost'\\n self._log_warning_for_missing_config_value(\\n cls_name=self.__class__.__name__,\\n default=internal_url, config_val='internal_url')\\n return ''.join([Plex.url_scheme, internal_url, ':', port])\\n\\n def _get_plex_api_data(self, api_call, api_suffix=None):\\n \\\"\\\"\\\"\\n Call plex api, and return XML data\\n\\n For /status/sessions:\\n >>> '<MediaContainer size=\\\"0\\\"></MediaContainer>'\\n\\n :param api_call:\\n :return: str\\n :raises: exceptions.PlexConnectionError\\n \\\"\\\"\\\"\\n if api_suffix is None:\\n # no extra api call for this\\n api_suffix = ''\\n try:\\n full_api_call = ''.join(\\n [self._get_api_url_suffix(api_call), api_suffix])\\n resp = urllib2.urlopen(\\n urlparse.urljoin(self.server_internal_url_and_port,\\n full_api_call))\\n output = resp.read()\\n except urllib2.URLError as err:\\n self.logger.error('Error connecting to Plex')\\n raise exceptions.PlexConnectionError(err)\\n else:\\n resp.close()\\n return output\\n\\n def _get_xml_convert_to_json(self, api_key, api_suffix=None):\\n \\\"\\\"\\\"\\n Gets Plex data based on api key and converts Plex XML response to JSON\\n format\\n\\n :type api_key: str\\n :type api_suffix: unknown or str\\n :return:\\n \\\"\\\"\\\"\\n xml_data = self._get_plex_api_data(api_key, api_suffix)\\n return self._convert_xml_to_json(xml_data)\\n\\n def _get_video_data(self, video, get_type=None):\\n is_now_playing = get_type == 'nowplaying'\\n # need a separate dict for section mapping since Plex returns different\\n # data for Now Playing and Recently Added\\n library_section_mapping = {'1': 'Movies', '2': 'TV Shows'}\\n # need a separate dict for section mapping since Plex returns different\\n # data for Now Playing and Recently Added\\n # all the video.gets below are to handle the different mappings\\n # Plex sends for Now Playing/Recently Added.\\n vidtype = video.get('@librarySectionTitle',\\n library_section_mapping.get(\\n video.get('@librarySectionID', 0)))\\n if vidtype == 'TV Shows':\\n video_data = self._get_tv_show_data(video, get_type)\\n elif vidtype == 'Movies':\\n release_date = video['@originallyAvailableAt']\\n video_data = dict(showtitle=video['@title'],\\n summary=video['@summary'],\\n releasedate=self.convert_date_fmt(release_date,\\n '%Y-%m-%d',\\n '%m/%d/%Y'))\\n else:\\n # encountered an unexpected video type\\n msg = 'Unexpected media type {} encountered'.format(vidtype)\\n self.logger.error(msg)\\n raise exceptions.PlexAPIDataError(msg)\\n if is_now_playing:\\n # only applicable if we want to retrieve now playing data from Plex\\n plex_path_to_art = video.get('@grandparentThumb', video['@thumb'])\\n try:\\n # this is only relevant for videos that are currently playing\\n video_data['progress'] = (float(video['@viewOffset']) / float(\\n video['@duration'])) * 100.0\\n except KeyError:\\n # video's not playing - not an issue\\n video_data['progress'] = 0\\n # add common elements to video dict\\n else:\\n plex_path_to_art = video['@thumb']\\n self._save_cover_art(self.server_internal_url_and_port +\\n plex_path_to_art)\\n arturlmapped_value = os.path.basename(plex_path_to_art)\\n video_data.update(type=vidtype,\\n art_external_url=''.join([self._img_base_url,\\n arturlmapped_value]),\\n added_at=strftime('%m/%d/%Y %I:%M %p',\\n localtime(int(video['@addedAt']))))\\n # converts direct plex http link to thumbnail to internal mapping\\n # security through obfuscation /s\\n self._cover_mapping[arturlmapped_value] = plex_path_to_art\\n video_data['rating'] = float(video.get('@rating', 0))\\n return video_data\\n\\n def _save_cover_art(self, cover_loc):\\n # retrieve image data from Plex server metadata\\n img_data = StringIO(urllib2.urlopen(\\n urlparse.urljoin(self.server_internal_url_and_port,\\n cover_loc)).read())\\n # check if temp directory exists, if not attempt to create directory\\n if not os.path.exists(self._temp_img_dir):\\n try:\\n os.mkdir(self._temp_img_dir)\\n self.logger.info('Creating temporary image directory {}'.\\n format(self._temp_img_dir))\\n except OSError as err:\\n self.logger.error(('Failure creating temporary image directory'\\n ' {}.\\\\nError message {}').format(\\n self._temp_img_dir, err))\\n raise\\n img = Image.open(img_data)\\n exts = ('.jpg', '.thumbnail')\\n sizes = [(568, 852), (144, 214)]\\n # create filepaths to temp images in temp directory\\n img_filepaths = [os.path.join(self._temp_img_dir, ''.join(\\n [str(cover_loc.split('/')[-1]), ext])) for ext in exts]\\n # index 0 = size tuple\\n # index 1 = path to file\\n size_and_fps = zip(sizes, img_filepaths)\\n for img_file in size_and_fps:\\n # preserve original file for multiple manipulations\\n temp_img = img.copy()\\n size = img_file[0]\\n filepath = img_file[1]\\n if not os.path.exists(filepath):\\n # create plex cover art file if file does not exist\\n try:\\n temp_img = ImageOps.fit(image=temp_img, size=size,\\n method=Image.ANTIALIAS)\\n temp_img.save(filepath, \\\"JPEG\\\")\\n self.logger.info(\\n 'Write image file: {}'.format(filepath))\\n except IOError as pil_err:\\n self.logger.error(\\n 'Image file write failure at {}. Reason: {}'.\\n format(filepath, pil_err))\\n else:\\n self.logger.debug('Image file already exists at: {}'.\\n format(filepath))\\n return img_filepaths[0]\\n\\n def _get_tv_show_data(self, video, get_type=None):\\n is_now_playing = get_type == 'nowplaying'\\n video_data = dict(showtitle=\\n video.get('@parentTitle',\\n video.get('@grandparentTitle')),\\n episode_number=int(video.get('@leafCount',\\n video.get('@index'))),\\n summary=video.get('@parentSummary',\\n video.get('@summary'))\\n if video['@summary'] != '' else 'Not available',\\n season=video['@title'] if\\n video['@title'].lower() == 'specials'\\n else int(video['@title'].lstrip('Season ')) if not\\n is_now_playing else int(video['@parentIndex']))\\n if isinstance(video_data['season'], int):\\n video_data['season'] = '{0:02d}'.format(video_data['season'])\\n if not is_now_playing:\\n json_show_data = self._get_xml_convert_to_json('serverinfo',\\n video['@key'].\\n lstrip('/'))\\n video = json_show_data['MediaContainer']\\n video_data.update(rating=video.get('@grandparentContentRating', ''),\\n studio=video['@grandparentStudio'])\\n try:\\n # if there's more than one episode in the season\\n video = video['Video'][\\n int(video_data['episode_number']) - 1]\\n except KeyError:\\n # first show in season\\n video = video['Video']\\n # get originally date playing on TV\\n try:\\n aired_date = video['@originallyAvailableAt']\\n aired_date = self.convert_date_fmt(aired_date, \\\"%Y-%m-%d\\\",\\n \\\"%m/%d/%Y\\\")\\n except KeyError:\\n aired_date = 'Not available'\\n video_data.update(title=video['@title'], aired_date=aired_date)\\n\\n # Set individual show summary to parent summary if show summary does\\n # not exist\\n if video['@summary'] != '':\\n video_data['summary'] = video['@summary']\\n return video_data\\n\"\n },\n {\n \"alpha_fraction\": 0.6156351566314697,\n \"alphanum_fraction\": 0.6188924908638,\n \"avg_line_length\": 33.13888931274414,\n \"blob_id\": \"162c8da2be6af14f740776746536ce3f6e2824e8\",\n \"content_id\": \"e6fbf2ba73122d4cbb62bcb18f46cbe70bfb6349\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1228,\n \"license_type\": \"no_license\",\n \"max_line_length\": 94,\n \"num_lines\": 36,\n \"path\": \"/setup.py\",\n \"repo_name\": \"beallio/media-server-status\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#!/usr/bin/env python\\nimport os\\n\\ntry:\\n from setuptools import setup\\nexcept ImportError:\\n from distutils.core import setup\\n\\nreadme_file = 'README.md'\\nreadme_file_full_path = os.path.join(os.path.dirname(os.path.realpath(__file__)), readme_file)\\nwith open(readme_file_full_path, 'r') as f:\\n readme_contents = f.read()\\nif not readme_contents:\\n readme_contents = ''\\n\\nsetup(name='server-status',\\n version='0.0.1',\\n author='David Beall',\\n author_email='david@beallio.com',\\n url='http://ww.beallio.com',\\n description='Server Status',\\n long_description='{}'.format(readme_contents),\\n packages=['serverstatus'],\\n package_dir={'serverstatus': 'serverstatus'},\\n classifiers=[\\n 'Development Status :: 4 - Beta',\\n 'Intended Audience :: System Administrators',\\n 'Intended Audience :: Information Technology',\\n 'License :: OSI Approved :: GNU General Public License (GPL)',\\n 'Natural Language :: English',\\n 'Operating System :: POSIX',\\n 'Programming Language :: Python',\\n 'Topic :: Software Development :: Libraries :: Python Modules',\\n 'Topic :: Software Development :: Libraries',\\n 'Topic :: System',\\n ])\"\n },\n {\n \"alpha_fraction\": 0.5667939186096191,\n \"alphanum_fraction\": 0.5687022805213928,\n \"avg_line_length\": 23.395349502563477,\n \"blob_id\": \"ccb08695a52f2fa560b09365fb1637e59bcd4653\",\n \"content_id\": \"0ccdc40b87970f030b22c9559fc7840d452d1e3e\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1048,\n \"license_type\": \"no_license\",\n \"max_line_length\": 68,\n \"num_lines\": 43,\n \"path\": \"/serverstatus/assets/wrappers.py\",\n \"repo_name\": \"beallio/media-server-status\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"\\\"\\\"\\\"\\nfunction wrappers module\\n\\\"\\\"\\\"\\n\\nimport logging\\nfrom inspect import stack, getmodule\\n\\n\\ndef logger(log_type):\\n \\\"\\\"\\\"\\n decorator to log output of functions\\n :param log_type: logger level as string (debug, warn, info, etc)\\n :type log_type: str\\n \\\"\\\"\\\"\\n def log_decorator(func):\\n \\\"\\\"\\\"\\n wrapped function\\n \\\"\\\"\\\"\\n def wrapped(*args, **kwargs):\\n # preserve calling module name for LOGGER\\n frm = stack()[1]\\n mod = getmodule(frm[0])\\n wrapped_logger = logging.getLogger(mod.__name__)\\n result = func(*args, **kwargs)\\n try:\\n getattr(wrapped_logger, log_type)(result)\\n except AttributeError as err:\\n wrapped_logger.error(err)\\n return result\\n\\n return wrapped\\n\\n return log_decorator\\n\\n\\ndef log_args(function):\\n \\\"\\\"\\\"\\n Logs arguments passed to function\\n \\\"\\\"\\\"\\n def wrapper(*args, **kwargs):\\n print 'Arguments:', args, kwargs\\n return function(*args, **kwargs)\\n return wrapper\"\n },\n {\n \"alpha_fraction\": 0.49355217814445496,\n \"alphanum_fraction\": 0.5064478516578674,\n \"avg_line_length\": 43.894737243652344,\n \"blob_id\": \"9f8ec88ff5f9f77ce5bf63ecfd596edb736829c5\",\n \"content_id\": \"cbd1a9ad9c65d43a32a5e96cf91f04e24026ea61\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 5120,\n \"license_type\": \"no_license\",\n \"max_line_length\": 106,\n \"num_lines\": 114,\n \"path\": \"/serverstatus/assets/weather.py\",\n \"repo_name\": \"beallio/media-server-status\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# coding=utf-8\\nfrom collections import namedtuple\\nfrom time import localtime, strftime\\nimport logging\\n\\nimport forecastio\\n\\nfrom serverstatus.assets.exceptions import MissingForecastIOKey\\n\\n\\nLOGGER = logging.getLogger(__name__)\\n\\n\\nclass Forecast(object):\\n def __init__(self, weather_config):\\n assert type(weather_config) is dict\\n self.logger = LOGGER\\n self.logger.debug(\\n '{} class initialized'.format(self.__class__.__name__))\\n self.forcastio_link_url = 'http://forecast.io/#/f/'\\n try:\\n self.api_key = weather_config['Forecast_io_API_key']\\n except KeyError:\\n raise MissingForecastIOKey('No ForecastIO API key found. API key required for weather data')\\n # default weather to Stanford, CA and US units\\n self.lat = weather_config.get('Latitude', 37.4225)\\n self.lng = weather_config.get('Longitude', 122.1653)\\n self.units = weather_config.get('units', 'us')\\n self.forecast = self._get_forecast_io()\\n\\n def get_data(self):\\n json = self.forecast.json\\n current = json['currently']\\n hourly = json['hourly']\\n minutely = json['minutely']\\n daily = json['daily']['data'][0]\\n output = dict(current_summary=current['summary'],\\n current_summary_icon=self._get_weather_icons(current['icon']),\\n current_temp=u'{:0.0f}°'.format(round(current['temperature'], 0)),\\n feels_like_temp=u'{:0.0f}°'.format(round(current['apparentTemperature'], 0)),\\n current_windspeed='{:0.0f}'.format(round(current['windSpeed'], 0)),\\n minutely_summary=minutely['summary'],\\n hourly_summary=hourly['summary'],\\n sunset=self._convert_time_to_text(daily['sunsetTime']),\\n sunrise=self._convert_time_to_text(daily['sunriseTime']),\\n url_link='{url}{lat},{lng}'.format(\\n url=self.forcastio_link_url,\\n lat=self.lat, lng=self.lng))\\n if output['current_windspeed'] != 0:\\n output['current_windbearing'] = self._get_wind_bearing_text(current['windBearing'])\\n return output\\n\\n def reload_data(self):\\n self.forecast.update()\\n\\n def _get_forecast_io(self):\\n return forecastio.load_forecast(self.api_key, self.lat, self.lng,\\n units=self.units)\\n\\n @staticmethod\\n def _get_weather_icons(weather_icon):\\n assert type(weather_icon) is unicode\\n weather_icon = weather_icon.replace(\\\"-\\\", \\\"_\\\")\\n weather_mappings = dict(clear_day='B',\\n clear_night='C',\\n rain='R',\\n snow='W',\\n sleet='X',\\n wind='F',\\n fog='L',\\n cloudy='N',\\n partly_cloudy_day='H',\\n partly_cloudy_night='I')\\n assert weather_icon in weather_mappings\\n return weather_mappings[weather_icon]\\n\\n @staticmethod\\n def _get_wind_bearing_text(degrees):\\n # normalize windbearing so N starts at 0 degrees\\n deg_norm = (float(degrees) + 11.25) / 22.5\\n # convert range of windbearing degrees to lookup patterns\\n deg_norm_lookup = int(deg_norm) + int((deg_norm // 1) > 0)\\n direction_mappings = {1: ('North', 'N'),\\n 2: ('North-northeast', 'NNE'),\\n 3: ('Northeast', 'NE'),\\n 4: ('East-northeast', 'ENE'),\\n 5: ('East', 'E'),\\n 6: ('East-southeast', 'ESE'),\\n 7: ('Southeast', 'SE'),\\n 8: ('South-southeast', 'SSE'),\\n 9: ('South', 'S'),\\n 10: ('South-southwest', 'SSW'),\\n 11: ('Southwest', 'SW'),\\n 12: ('West-southwest', 'WSW'),\\n 13: ('West', 'W'),\\n 14: ('West-northwest', 'WNW'),\\n 15: ('Northwest', 'NW'),\\n 16: ('North-northwest', 'NNW')}\\n try:\\n bearing_text = direction_mappings[int(deg_norm_lookup)]\\n except KeyError:\\n # Key values exceeds max in dictionary, which means it's blowing North\\n bearing_text = direction_mappings[1]\\n # output namedtuple for Cardinal direction, and abbrevation text\\n return namedtuple(typename='bearing_text', field_names=['cardinal', 'abbrev'])._make(bearing_text)\\n\\n @staticmethod\\n def _convert_time_to_text(time_var):\\n assert type(time_var) is int\\n time_var = strftime('%I:%M %p', localtime(time_var))\\n # Remove '0' values from time if less than 10hrs or 10mins\\n if time_var.startswith('0'):\\n time_var = time_var[1:]\\n return time_var\\n\"\n },\n {\n \"alpha_fraction\": 0.7539432048797607,\n \"alphanum_fraction\": 0.7570977807044983,\n \"avg_line_length\": 36.235294342041016,\n \"blob_id\": \"eed5b3839bec997e087fb490b153d8a5fdcd44d8\",\n \"content_id\": \"05099ee7654eb0dc456546bd239f64166fe1e260\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 634,\n \"license_type\": \"no_license\",\n \"max_line_length\": 78,\n \"num_lines\": 17,\n \"path\": \"/wsgi.py\",\n \"repo_name\": \"beallio/media-server-status\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"\\\"\\\"\\\"\\nAPACHE MOD_WSGI Load script\\nSome of the variables in this file may need to be adjusted depending on\\nserver setup and/or location of virtual environment and application\\n\\\"\\\"\\\"\\nimport sys\\nimport os\\n\\nPROJECT_DIR = '/var/www/status' # change to the root of your app\\n# 'venv/bin' is the location of the project's virtual environment\\nVIRTUAL_ENV_DIR = 'venv/bin'\\nPACKAGES = 'lib/python2.7/site-packages'\\n\\nactivate_this = os.path.join(PROJECT_DIR, VIRTUAL_ENV_DIR, 'activate_this.py')\\nexecfile(activate_this, dict(__file__=activate_this))\\nsys.path.append(PROJECT_DIR)\\nsys.path.append(os.path.join(PROJECT_DIR, VIRTUAL_ENV_DIR, PACKAGES))\\n\\n\"\n }\n]"},"num_files":{"kind":"number","value":16,"string":"16"}}},{"rowIdx":2055,"cells":{"repo_name":{"kind":"string","value":"cnu-cse-datacom/2-packetcapture-201502038"},"repo_url":{"kind":"string","value":"https://github.com/cnu-cse-datacom/2-packetcapture-201502038"},"snapshot_id":{"kind":"string","value":"bbd25c2802ddde56b72d581111e255f93663c69a"},"revision_id":{"kind":"string","value":"271a219eddefdd1a67ef91e0b115c3949e7b7247"},"directory_id":{"kind":"string","value":"6e0116ff609c2b31eda5718bd141852394f0e6f2"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"string","value":"2020-04-29T01:52:45.914054"},"revision_date":{"kind":"string","value":"2019-03-23T09:42:56"},"committer_date":{"kind":"string","value":"2019-03-23T09:42:56"},"github_id":{"kind":"number","value":175744966,"string":"175,744,966"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.5444238185882568,"alphanum_fraction":0.5891568660736084,"avg_line_length":33.650001525878906,"blob_id":"b3a582f7d0f04506dcd8e46edb9ef903c8e3daa2","content_id":"e571a73c3fc3fe632e21eeb4bdc70ffdde65be1b","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":4851,"license_type":"no_license","max_line_length":90,"num_lines":140,"path":"/DC02_02_201502038_KimJeongWoo.py","repo_name":"cnu-cse-datacom/2-packetcapture-201502038","src_encoding":"UTF-8","text":"import socket\nimport struct\n\ndef parsing_ip_header(data):\n ip_header = struct.unpack(\"!6c6c2cccHHHccHccccccccHHIIHHHH\",data)\n ether_src = convert_ip_address(ip_header[0:6])\n ether_dest = convert_ip_address(ip_header[6:12])\n ip_head = \"0x\"+convert_ip_address(ip_header[12:13])\n ip_version = int(convert_ip_address(ip_header[14:15]),16) >> 4\n ip_HLEN = int(convert_ip_address(ip_header[14:15]),16) & 0xf\n differentiated_service_codepoint = int(convert_ip_address(ip_header[15:16]),16) >> 2 \n Explicit_Congestion_Notification = int(convert_ip_address(ip_header[15:16]),16) & 0x11\n total_length = convert_ip_int(ip_header[16:17])\n Identification = convert_ip_int(ip_header[17:18])\n flag = convert_hex(ip_header[18:19])\n Reserved_bit = (int(flag,16) >> 15) & 0x1\n not_fragment = (int(flag,16) >> 14) & 0x1\n fragments = (int(flag,16) >> 13) & 0x1\n fragments_offset = int(flag,16) & 0x1fff\n Time_to_live = convert_ip_address(ip_header[19:20])\n Protocol = convert_ip_address(ip_header[20:21]) \n Header_checksum = convert_hex(ip_header[21:22])\n source_ip = convert_ip(ip_header[22:26])\n dest_ip = convert_ip(ip_header[26:30])\n #tcp_parsing\n source_port = convert_ip_int(ip_header[30:31])\n dest_port = convert_ip_int(ip_header[31:32])\n sequence_number = convert_ip_int(ip_header[32:33])\n udp_length = sequence_number >> 16\n udp_check = sequence_number & 0xff\n acknowledgment = convert_ip_int(ip_header[33:34])\n header_length = int(convert_hex(ip_header[34:35]),16) >> 12\n _flag = hex(int(convert_hex(ip_header[34:35]),16) & 0xfff)\n Reserved = ((int(_flag,16)) >> 9) & 0x111\n Nonce = ((int(_flag,16)) >> 8) & 0x1\n CWR = ((int(_flag,16)) >> 7) & 0x1\n ECN = ((int(_flag,16)) >> 6) & 0x1\n URG = ((int(_flag,16)) >> 5) & 0x1\n ACK = ((int(_flag,16)) >> 4) & 0x1\n PUSH = ((int(_flag,16)) >> 3) & 0x1\n Reset = ((int(_flag,16)) >> 2) & 0x1\n SYN = ((int(_flag,16)) >> 1) & 0x1\n FIN = int(_flag,16) & 0x1\n window = convert_ip_int(ip_header[35:36])\n checkSum = convert_ip_int(ip_header[36:37])\n urgentpointer = convert_ip_int(ip_header[37:38])\n \n print(\"===============ETH===============\")\n print(\"src_mac_address: \",ether_src)\n print(\"dest_mac_address: \",ether_dest)\n print(\"IP Header: \",ip_head)\n print(\"===============IPH===============\")\n print(\"ip_version: \",ip_version)\n \n print(\"ip_HLEN: \",ip_HLEN)\n \n print(\"differentiated_service_codepoint: \",differentiated_service_codepoint) \n print(\"Explicit_Congestion_Notification: \",Explicit_Congestion_Notification)\n\n print(\"Total Length: \",total_length) \n \n print(\"Identification: \",Identification)\n \n print(\"Flag: \",flag)\n \n print(\"Reserved_bit: \",Reserved_bit)\n print(\"not_fragment: \",not_fragment)\n print(\"fragments: \",fragments)\n print(\"fragments_offset: \",fragments_offset)\n print(\"Time_to_live: \",Time_to_live)\n print(\"Protocol\",int(Protocol,16))\n print(\"Header_checksum\",Header_checksum)\n print(\"source_ip: \",source_ip)\n print(\"dest_ip: \",dest_ip)\n\n if int(Protocol) == 6 :\n print(\"===============tcp===============\")\n print(\"source_poert: \",source_port)\n print(\"dest_port\",dest_port)\n print(\"sequence_number: \",sequence_number)\n print(\"acknowledgment: \",acknowledgment)\n print(\"header_length: \",header_length)\n print(\"Flag: \",_flag)\n print(\"reserved: \",Reserved)\n print(\"Nonce: \",Nonce)\n print(\"CWR: \",CWR)\n print(\"ECN: \",ECN)\n print(\"URG: \",URG)\n print(\"ACK: \",ACK)\n print(\"push: \",PUSH)\n print(\"Reset: \",Reset)\n print(\"SYN: \",SYN)\n print(\"FIN: \",FIN)\n print(\"window: \",window)\n print(\"checkSum: \",checkSum)\n print(\"urgentPointer: \",urgentpointer)\n\n if int(Protocol) == 11 :\n print(\"===============UDP===============\")\n print(\"source_port: \",source_port)\n print(\"dest_port: \",dest_port)\n print(\"UDP length: \",udp_length)\n print(\"UDP Checksum: \",udp_check)\n\ndef convert_ip_address(data):\n ip_addr = list()\n for i in data:\n ip_addr.append(i.hex()) \n ip_addr = \":\".join(ip_addr)\n return ip_addr\n\ndef convert_byte(data):\n byte = list()\n for i in data:\n byte.append(i.hex())\n return byte\n\ndef convert_ip_int(data):\n ip_int = list()\n for i in data:\n ip_int.append(i)\n return ip_int[0]\n\ndef convert_hex(data):\n ip_flag = list()\n for i in data:\n ip_flag.append(i)\n return hex(ip_flag[0])\n\ndef convert_ip(data):\n ip = list()\n for i in data:\n ip.append(int(i.hex(),16))\n return ip\n\nrecv_socket = socket.socket(socket.PF_PACKET,socket.SOCK_RAW,socket.ntohs(0x0800))\n\ndata = recv_socket.recvfrom(65565)\nwhile True:\n\tparsing_ip_header(data[0][0:54])\n"}],"string":"[\n {\n \"alpha_fraction\": 0.5444238185882568,\n \"alphanum_fraction\": 0.5891568660736084,\n \"avg_line_length\": 33.650001525878906,\n \"blob_id\": \"b3a582f7d0f04506dcd8e46edb9ef903c8e3daa2\",\n \"content_id\": \"e571a73c3fc3fe632e21eeb4bdc70ffdde65be1b\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 4851,\n \"license_type\": \"no_license\",\n \"max_line_length\": 90,\n \"num_lines\": 140,\n \"path\": \"/DC02_02_201502038_KimJeongWoo.py\",\n \"repo_name\": \"cnu-cse-datacom/2-packetcapture-201502038\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import socket\\nimport struct\\n\\ndef parsing_ip_header(data):\\n ip_header = struct.unpack(\\\"!6c6c2cccHHHccHccccccccHHIIHHHH\\\",data)\\n ether_src = convert_ip_address(ip_header[0:6])\\n ether_dest = convert_ip_address(ip_header[6:12])\\n ip_head = \\\"0x\\\"+convert_ip_address(ip_header[12:13])\\n ip_version = int(convert_ip_address(ip_header[14:15]),16) >> 4\\n ip_HLEN = int(convert_ip_address(ip_header[14:15]),16) & 0xf\\n differentiated_service_codepoint = int(convert_ip_address(ip_header[15:16]),16) >> 2 \\n Explicit_Congestion_Notification = int(convert_ip_address(ip_header[15:16]),16) & 0x11\\n total_length = convert_ip_int(ip_header[16:17])\\n Identification = convert_ip_int(ip_header[17:18])\\n flag = convert_hex(ip_header[18:19])\\n Reserved_bit = (int(flag,16) >> 15) & 0x1\\n not_fragment = (int(flag,16) >> 14) & 0x1\\n fragments = (int(flag,16) >> 13) & 0x1\\n fragments_offset = int(flag,16) & 0x1fff\\n Time_to_live = convert_ip_address(ip_header[19:20])\\n Protocol = convert_ip_address(ip_header[20:21]) \\n Header_checksum = convert_hex(ip_header[21:22])\\n source_ip = convert_ip(ip_header[22:26])\\n dest_ip = convert_ip(ip_header[26:30])\\n #tcp_parsing\\n source_port = convert_ip_int(ip_header[30:31])\\n dest_port = convert_ip_int(ip_header[31:32])\\n sequence_number = convert_ip_int(ip_header[32:33])\\n udp_length = sequence_number >> 16\\n udp_check = sequence_number & 0xff\\n acknowledgment = convert_ip_int(ip_header[33:34])\\n header_length = int(convert_hex(ip_header[34:35]),16) >> 12\\n _flag = hex(int(convert_hex(ip_header[34:35]),16) & 0xfff)\\n Reserved = ((int(_flag,16)) >> 9) & 0x111\\n Nonce = ((int(_flag,16)) >> 8) & 0x1\\n CWR = ((int(_flag,16)) >> 7) & 0x1\\n ECN = ((int(_flag,16)) >> 6) & 0x1\\n URG = ((int(_flag,16)) >> 5) & 0x1\\n ACK = ((int(_flag,16)) >> 4) & 0x1\\n PUSH = ((int(_flag,16)) >> 3) & 0x1\\n Reset = ((int(_flag,16)) >> 2) & 0x1\\n SYN = ((int(_flag,16)) >> 1) & 0x1\\n FIN = int(_flag,16) & 0x1\\n window = convert_ip_int(ip_header[35:36])\\n checkSum = convert_ip_int(ip_header[36:37])\\n urgentpointer = convert_ip_int(ip_header[37:38])\\n \\n print(\\\"===============ETH===============\\\")\\n print(\\\"src_mac_address: \\\",ether_src)\\n print(\\\"dest_mac_address: \\\",ether_dest)\\n print(\\\"IP Header: \\\",ip_head)\\n print(\\\"===============IPH===============\\\")\\n print(\\\"ip_version: \\\",ip_version)\\n \\n print(\\\"ip_HLEN: \\\",ip_HLEN)\\n \\n print(\\\"differentiated_service_codepoint: \\\",differentiated_service_codepoint) \\n print(\\\"Explicit_Congestion_Notification: \\\",Explicit_Congestion_Notification)\\n\\n print(\\\"Total Length: \\\",total_length) \\n \\n print(\\\"Identification: \\\",Identification)\\n \\n print(\\\"Flag: \\\",flag)\\n \\n print(\\\"Reserved_bit: \\\",Reserved_bit)\\n print(\\\"not_fragment: \\\",not_fragment)\\n print(\\\"fragments: \\\",fragments)\\n print(\\\"fragments_offset: \\\",fragments_offset)\\n print(\\\"Time_to_live: \\\",Time_to_live)\\n print(\\\"Protocol\\\",int(Protocol,16))\\n print(\\\"Header_checksum\\\",Header_checksum)\\n print(\\\"source_ip: \\\",source_ip)\\n print(\\\"dest_ip: \\\",dest_ip)\\n\\n if int(Protocol) == 6 :\\n print(\\\"===============tcp===============\\\")\\n print(\\\"source_poert: \\\",source_port)\\n print(\\\"dest_port\\\",dest_port)\\n print(\\\"sequence_number: \\\",sequence_number)\\n print(\\\"acknowledgment: \\\",acknowledgment)\\n print(\\\"header_length: \\\",header_length)\\n print(\\\"Flag: \\\",_flag)\\n print(\\\"reserved: \\\",Reserved)\\n print(\\\"Nonce: \\\",Nonce)\\n print(\\\"CWR: \\\",CWR)\\n print(\\\"ECN: \\\",ECN)\\n print(\\\"URG: \\\",URG)\\n print(\\\"ACK: \\\",ACK)\\n print(\\\"push: \\\",PUSH)\\n print(\\\"Reset: \\\",Reset)\\n print(\\\"SYN: \\\",SYN)\\n print(\\\"FIN: \\\",FIN)\\n print(\\\"window: \\\",window)\\n print(\\\"checkSum: \\\",checkSum)\\n print(\\\"urgentPointer: \\\",urgentpointer)\\n\\n if int(Protocol) == 11 :\\n print(\\\"===============UDP===============\\\")\\n print(\\\"source_port: \\\",source_port)\\n print(\\\"dest_port: \\\",dest_port)\\n print(\\\"UDP length: \\\",udp_length)\\n print(\\\"UDP Checksum: \\\",udp_check)\\n\\ndef convert_ip_address(data):\\n ip_addr = list()\\n for i in data:\\n ip_addr.append(i.hex()) \\n ip_addr = \\\":\\\".join(ip_addr)\\n return ip_addr\\n\\ndef convert_byte(data):\\n byte = list()\\n for i in data:\\n byte.append(i.hex())\\n return byte\\n\\ndef convert_ip_int(data):\\n ip_int = list()\\n for i in data:\\n ip_int.append(i)\\n return ip_int[0]\\n\\ndef convert_hex(data):\\n ip_flag = list()\\n for i in data:\\n ip_flag.append(i)\\n return hex(ip_flag[0])\\n\\ndef convert_ip(data):\\n ip = list()\\n for i in data:\\n ip.append(int(i.hex(),16))\\n return ip\\n\\nrecv_socket = socket.socket(socket.PF_PACKET,socket.SOCK_RAW,socket.ntohs(0x0800))\\n\\ndata = recv_socket.recvfrom(65565)\\nwhile True:\\n\\tparsing_ip_header(data[0][0:54])\\n\"\n }\n]"},"num_files":{"kind":"number","value":1,"string":"1"}}},{"rowIdx":2056,"cells":{"repo_name":{"kind":"string","value":"marty-Wallace/FibbonacciServer"},"repo_url":{"kind":"string","value":"https://github.com/marty-Wallace/FibbonacciServer"},"snapshot_id":{"kind":"string","value":"5eb10dcbde29fc9470fde30b36e82030543ca3f8"},"revision_id":{"kind":"string","value":"bee68eda66535349fcf3b0579a33d1721cf79b34"},"directory_id":{"kind":"string","value":"87efed27c2654d6f5181e4eec7e4c1e2e5ea1764"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"string","value":"2020-06-20T16:04:39.742452"},"revision_date":{"kind":"string","value":"2017-03-03T07:00:07"},"committer_date":{"kind":"string","value":"2017-03-03T07:00:07"},"github_id":{"kind":"number","value":81610047,"string":"81,610,047"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.6461588740348816,"alphanum_fraction":0.6516926884651184,"avg_line_length":38.89610290527344,"blob_id":"4c5f704ac0776b10bcb5ddabe68e372f4f959051","content_id":"69066ad46bca611da030d2efc4c1c6c438aaef36","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":3072,"license_type":"no_license","max_line_length":108,"num_lines":77,"path":"/Fibonacci/fib_server.py","repo_name":"marty-Wallace/FibbonacciServer","src_encoding":"UTF-8","text":"from socketserver import ThreadingMixIn, TCPServer, BaseRequestHandler\n\n\nclass FibonacciThreadedTCPServer(ThreadingMixIn, TCPServer):\n \"\"\"\n FibonacciThreadedTCPServer used to serve concurrent TCP requests for a fibonacci\n number. The server holds the lookup table fib_dict shared by each instance of\n FibonacciThreadedTCPRequestHandler to make optimized calculations.\n \"\"\"\n\n def __init__(self, server_address):\n TCPServer.__init__(self, server_address, FibonacciThreadedTCPRequestHandler, bind_and_activate=True)\n self.fib_dict = {0: 0, 1: 1, 2: 1}\n\n\nclass FibonacciThreadedTCPRequestHandler(BaseRequestHandler):\n \"\"\"\n FibonacciThreadedTCPRequestHandler class for our server. One instance will be created to\n serve each request that comes into the server. Must override the handle() method which will\n be called by the server on each new instance for each incoming request\n \"\"\"\n\n def handle(self):\n \"\"\"\n reads in an integer from the incoming socket connection, calculates the fibonacci value of\n that number then returns that value to the socket\n\n :return: None\n \"\"\"\n\n data = self.request.recv(1024).strip()\n print('Serving new request, data=%s' % data)\n try:\n num = int(data)\n if num < 0:\n raise ValueError\n except ValueError:\n self.request.sendall(bytes('Must send a valid number >= 0\\n', 'ascii'))\n return\n\n # calculate the result of fib(num)\n result = self.calc_fib(self.server.fib_dict, num)\n # encode into bytes\n ret = bytes(str(result) + '\\n', 'ascii')\n # return result\n self.request.sendall(ret)\n\n @staticmethod\n def calc_fib(fib_dict, n):\n \"\"\"\n Calculates the fibonacci value of n in an optimized way using a lookup table\n and a linear calculation. Since the fib_table is a dictionary shared between\n multiple threads we can only write to the dict. Any type of read->modify->write\n sequence may be interrupted mid-execution, creating a race condition. If n is in\n the fib_dict we can simply return it, otherwise we can begin calculating each value\n of fib between the current highest value ( which is fib(len(fib_dict)-1) ) and n.\n\n :param fib_dict: the dictionary of fib numbers shared between threads\n :param n: the value of fib to calculate\n :return: fib(n)\n \"\"\"\n length = len(fib_dict)\n while length <= n:\n fib_dict[length] = fib_dict[length - 1] + fib_dict[length - 2]\n length = len(fib_dict)\n return fib_dict[n]\n\n# if module is imported this code won't run\nif __name__ == '__main__':\n # port of 0 will request an open port from the kernel\n HOST, PORT = 'localhost', 0\n\n with FibonacciThreadedTCPServer((HOST, PORT)) as server:\n ip, port = server.server_address\n print(\"Starting FibServer at %s:%d\" % (ip, port))\n print(\"Waiting for fibonacci requests...\")\n server.serve_forever()\n"},{"alpha_fraction":0.5699896216392517,"alphanum_fraction":0.5748847126960754,"avg_line_length":36.273685455322266,"blob_id":"425d3c69d8e8431d6d7481a4f1ea64a8e72f1533","content_id":"1cadb6a432d08fe7bc7a2996e866ea91499752b0","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":10623,"license_type":"no_license","max_line_length":116,"num_lines":285,"path":"/Fibonacci/fib_client.py","repo_name":"marty-Wallace/FibbonacciServer","src_encoding":"UTF-8","text":"import socket\nimport sys\nimport getopt\n\nfrom threading import Thread\nfrom random import randint\n\n\nclass FibClient(object):\n \"\"\"\n Base Class for the AutoClient and HumanClient to extend from. Implements some of the shared methods/attributes\n \"\"\"\n def __init__(self, ip, port):\n self.ip = ip\n self.port = port\n\n @staticmethod\n def receive_from_sock(sock, buffer_size):\n \"\"\"\n Generator function to yield the current buffer received from sock.\n Can be used in the form of b''.join(recv_all(sock, buffer_size)) to\n receive the full transmission from a socket\n\n :param sock: the socket to receive data from\n :param buffer_size: the size of the buffer to load on each yield\n :return: yields the current buffer as a byte object\n \"\"\"\n message_buffer = sock.recv(buffer_size)\n while message_buffer:\n yield message_buffer\n message_buffer = sock.recv(buffer_size)\n\n @staticmethod\n def receive_all_from_sock(sock, buffer_size=2048):\n \"\"\"\n Builds the full message received from a socket in bytes\n\n :param sock: the socket to receive data from\n :param buffer_size: the size of the buffer to load while building full result, defaults to 2048\n :return: byte object containing full message\n \"\"\"\n return b''.join(FibClient.receive_from_sock(sock, buffer_size))\n\n def get_fibonacci_number(self, number):\n \"\"\"\n Make a request to the fib server for a single fib number. If there is a socket or value error, return None\n\n :param number: the fib number to request from the server\n :return: fib of n, if an error occurs then None\n \"\"\"\n sock = socket.socket(socket.AF_INET, socket.SOCK_STREAM)\n sock.connect((self.ip, self.port))\n response = None\n try:\n sock.sendall(bytes(str(number), 'ascii'))\n response = int(FibClient.receive_all_from_sock(sock))\n except socket.error as err:\n print(err, file=sys.stderr)\n except ValueError as err:\n print(err, file=sys.stderr)\n finally:\n sock.close()\n return response\n\n\nclass AutoClient(FibClient):\n \"\"\"\n Class to do automated testing on the fibonacci server. Capable of spinning up multiple threads\n and requesting random fib numbers then testing their correctness.\n \"\"\"\n\n def _test_fib(self, number, verbose, silent):\n \"\"\"\n Requests a single fib number from the server then does the calculation locally to\n ensure that the number is correct\n\n :param number: the fib number to request/test\n :param verbose flag if the printing level is high\n :param silent flag if the printing level is for errors only\n :return: None\n \"\"\"\n\n def local_fib(n):\n \"\"\"\n Generate the fib number locally to test against the server's result\n :param n: the fib number to generate\n :return: fib of n\n \"\"\"\n a, b = 1, 1\n for i in range(n-1):\n a, b = b, a+b\n return a\n\n # get server result\n result = self.get_fibonacci_number(number)\n # server errors will return None so check for None\n if result is None:\n if verbose:\n print('Received None from server')\n return None\n\n if not silent:\n print('Received result %d from server for fib(%d)' % (result, number))\n\n # get local result\n local_result = local_fib(number)\n if verbose:\n print('Calculated local value to be %d for fib(%d)' % (local_result, number))\n\n # compare results\n if result != local_result:\n # even on silent we will display errors of this kind.\n # if we enter this block it means the server is returning wrong numbers\n print(\"Server returned %d for fib(%d) should have been %d\" % (result, number, local_result))\n\n def connect(self, num_threads=15, fib_min=1, fib_max=2000, verbose=False, silent=False):\n \"\"\"\n Runs some automated tests on the server by spinning up multiple concurrent clients, one to a thread,\n each requesting a random fib number and double checking the results returned by the server\n\n :param num_threads: the number of threads/clients to spin up concurrently. Defaults to 15\n :param fib_min: the minimum fib number to request from the server. Defaults to 1\n :param fib_max: the maximum fib number to request from the server. Defaults to 2000\n :param verbose: sets the highest level of printing out whats going on\n :param silent: sets the lowest level of printing out whats going on\n :return: None\n \"\"\"\n threads = []\n\n for i in range(num_threads):\n num = randint(fib_min, fib_max)\n if verbose:\n print('Starting thread with target number %d' % num)\n threads.append(Thread(target=self._test_fib, args=(num, verbose, silent)))\n\n for thread in threads:\n thread.start()\n\n\nclass HumanClient(FibClient):\n\n def __init__(self, ip, port):\n super().__init__(ip, port)\n\n def connect(self):\n \"\"\"\n A loop that allows a human to repeatedly request fib numbers from the server.\n\n :return: None\n \"\"\"\n while True:\n bad_input = True\n num = 0\n while bad_input:\n try:\n num = int(input('Please enter which fibonacci number you would like: '))\n if num <= 0:\n print(\"Please enter a positive number. Negative fibonacci numbers are undefined.\")\n else:\n bad_input = False\n except ValueError as err:\n print(\"Please enter a number\")\n continue\n fib = self.get_fibonacci_number(num)\n if fib is None:\n print('Error: None returned by get_fibonacci_number(%s, %d, %d)' % (ip, port, num))\n continue\n print(\"Fib of %d is %d\" % (num, fib))\n print() # blank line\n\n\ndef usage(message=''):\n \"\"\"\n Displays a set of messages describing how to use the program\n :param message: an optional message to display at the beggining of the output\n :return: None\n \"\"\"\n if message != '':\n print(message)\n\n print('fib_client.py improper usage')\n print('Usage: python fib_client.py --port=<portnumber> [options] ')\n print('Options are:')\n print(' -i, --ip= ip address of the fib server, defaults to localhost')\n print(' -p, --port= port address of the server, required argument')\n print(' -a, --auto sets that we are going to use the auto tester client rather than the human client')\n print(' -t, --threads= only applies to the auto tester and it sets how many concurrent requests to make')\n print(' -l, --low= sets the lowest fib number to randomly request for the auto client defaults to 1')\n print(' -h, --high= sets the highest fib number to randomly request for the auto client defaults to 2000')\n print(' -s, --silent sets the output level to silent for auto-testing (useful for large numbers)')\n print(' -v, --verbose sets output level to verbose for auto-testing')\n print(' --help requests this usage screen')\n exit()\n\n\ndef main():\n \"\"\"\n Reads in opts and args from the command line and then takes the appropriate action\n to either start up the human client or the auto-tester client.\n \"\"\"\n\n ip = '127.0.0.1' # ip address of the server\n port = -1 # port of the server must be set by args\n auto = False # flag to run auto_client over human_client\n threads = 15 # number of threads to run auto_client with\n low = 1 # lowest fib number to request with auto_client\n high = 2000 # highest fib number to request with auto_client\n silent = False # print nothing during auto_testing\n verbose = False # print everything during auto-testing\n\n # reads in all opts and args and sets appropriate variables\n try:\n opts, args = getopt.getopt(sys.argv[1:], \"i:p:at:l:h:sv\",\n [\"ip=\", \"port=\", \"auto\", \"threads=\", \"low=\", \"high=\", \"silent\", \"verbose\"])\n except getopt.GetoptError:\n usage()\n for o, a in opts:\n # ip address\n if o in ('-i', '--ip'):\n ip = a\n # port number\n elif o in ('-p', '--port'):\n try:\n port = int(a)\n except ValueError:\n usage(\"Port must be a number\")\n # auto client\n elif o in ('-a', '--auto'):\n auto = True\n # threads\n elif o in ('-t', '--threads'):\n try:\n threads = int(a)\n except ValueError:\n usage(\"Number of threads must be a number\")\n # low value\n elif o in ('-l', '--low'):\n try:\n low = int(a)\n if low < 1:\n raise ValueError\n except ValueError:\n usage(\"Low must be a number greater than 0\")\n # high value\n elif o in ('-h', '--high'):\n try:\n high = int(a)\n if high < 1:\n raise ValueError\n except ValueError:\n usage(\"High must be a number greater than 0\")\n # verbose\n elif o in ('-v', '--verbose'):\n if silent:\n usage('Cannot set both verbose and silent to be true')\n verbose = True\n # silent\n elif o in ('-s', '--silent'):\n if verbose:\n usage('Cannot set both verbose and silent to be true')\n silent = True\n # any other args/opts show usage\n else:\n usage()\n\n # ensure port is set\n if port == -1:\n usage('The port number must be set')\n\n # make sure our numbers make sense, take low if they don't\n if high < low:\n high = low\n\n if auto:\n if verbose:\n print('Target server at %s:%d' % (ip, port))\n print('Starting %d threads requesting numbers between %d-%d' % (threads, low, high))\n\n AutoClient(ip, port).connect(num_threads=threads, fib_min=low, fib_max=high, verbose=verbose, silent=silent)\n else:\n HumanClient(ip, port).connect()\n\n# Won't run if code is imported\nif __name__ == '__main__':\n main()\n"},{"alpha_fraction":0.6936936974525452,"alphanum_fraction":0.7162162065505981,"avg_line_length":25.058822631835938,"blob_id":"1971c1c6c2a8374379d1733f3c454aa2b1e4a4f3","content_id":"014d173d1e0cebb7ce4e14872f72aa1ed43bdc24","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":444,"license_type":"no_license","max_line_length":91,"num_lines":17,"path":"/example_client.py","repo_name":"marty-Wallace/FibbonacciServer","src_encoding":"UTF-8","text":"from Fibonacci import HumanClient, AutoClient\n\n'''\nExample file showing how to use and how to test out the Fibonacci client\n'''\n\nip = 'localhost'\nport = int(input('Please enter the port number of the Fibonacci server: '))\n\ntest_auto = True\n\nif test_auto:\n client = AutoClient(ip, port)\n client.connect(num_threads=50, fib_min=4000, fib_max=5000, verbose=False, silent=False)\nelse:\n client = HumanClient(ip, port)\n client.connect()\n\n"},{"alpha_fraction":0.7815126180648804,"alphanum_fraction":0.7857142686843872,"avg_line_length":22.600000381469727,"blob_id":"eb341dfb76934920a74a40af33303c35a56b2c59","content_id":"8aa14ea7435790ee0ba6c25dd598fbe506686b61","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":238,"license_type":"no_license","max_line_length":52,"num_lines":10,"path":"/example_server.py","repo_name":"marty-Wallace/FibbonacciServer","src_encoding":"UTF-8","text":"from Fibonacci import FibonacciThreadedTCPServer\n\n'''\nExample file showing how to use the Fibonacci server\n'''\n\naddress = ('localhost', 0)\nserver = FibonacciThreadedTCPServer(address)\nprint(server.server_address)\nserver.serve_forever()\n\n\n"},{"alpha_fraction":0.752136766910553,"alphanum_fraction":0.752136766910553,"avg_line_length":28.25,"blob_id":"0aa9e98be13cfab094cc5f0fa2e8bedccc82421e","content_id":"3b293e570539489cae2ffab4dd5dda2b8abea57e","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":117,"license_type":"no_license","max_line_length":63,"num_lines":4,"path":"/Fibonacci/__init__.py","repo_name":"marty-Wallace/FibbonacciServer","src_encoding":"UTF-8","text":"from .fib_server import *\nfrom .fib_client import *\n\n__all__ = [FibonacciThreadedTCPServer, AutoClient, HumanClient]\n"},{"alpha_fraction":0.7276967763900757,"alphanum_fraction":0.7411078810691833,"avg_line_length":49.44117736816406,"blob_id":"03a89c93317f814e39b413804a7748c3282019a8","content_id":"18234fd3d6f5c85eec49267a01c2dd23155e6914","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":1715,"license_type":"no_license","max_line_length":397,"num_lines":34,"path":"/README.md","repo_name":"marty-Wallace/FibbonacciServer","src_encoding":"UTF-8","text":"# FibonacciServer\nA class assignment to create a multi-threaded fibonacci server/client\n\n\nMy implementation of a school assignment with the following requirements\n\n>Given that our Fibonacci calculation looks like:\n>```\n>def fib(n):\n> if n == 0:\n> return 0\n> elif n == 1:\n> return 1\n> else:\n> return fib(n-1) + fib(n-2)\n>```\n>\n>Using Python, design a socket server that will accept an integer(properly packed) and return a fibonacci value for the integer. Design a\nreliable protocol and implement both a client and server for calculating our Fibonacci values. Ensure that you can have more than one calculation occurring at any moment.\n\n####Implementation\n\nThe server is set up to serve many concurrent Fibonacci requests for very large values up to around fib(100000). The server uses a lookup table that is shared among each thread. All fibonacci numbers are calculated using a linear definition rather than a recursive one and each value is stored in the cache table. To keep the dictionary \"safe\" the data is written to the dictionary in the form of:\n```\ndef calc_fib(fib_dict, n):\n length = len(fib_dict)\n while length <= n:\n fib_dict[length] = fib_dict[length - 1] + fib_dict[length - 2]\n length = len(fib_dict)\nreturn fib_dict[n]\n```\nIn this format it is possible for many threads to write to the same location in the dictionary but since each number is based on the previous two numbers the data will stay intact. The length is updated to the length of the actual dict at the end of each loop iteration to avoid doing work done in other threads (as opposed to length += 1). \n\nhttp://stackoverflow.com/questions/42564437/why-is-this-python-code-not-thread-safe\n"},{"alpha_fraction":0.7823365926742554,"alphanum_fraction":0.7927677035331726,"avg_line_length":129.72727966308594,"blob_id":"d25ca74ee16705848b922c873d0502e214d60d53","content_id":"fa97b36312e2f0b76b1611dfbff37a463fb3c08d","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":1438,"license_type":"no_license","max_line_length":727,"num_lines":11,"path":"/Fibonacci/README.md","repo_name":"marty-Wallace/FibbonacciServer","src_encoding":"UTF-8","text":"##Fibonacci module \n\n###fib_server\nfib_server.py contains two classes **FibonacciThreadedTCPRequestHandler** and **FibonacciThreadedTCPServer**. Which can be implemented by following the example in *test_client.py*. I have optimized the calculations of the fibonacci numbers as far as I can and on my Dell Inspirion I am able to have 50 threads requesting fib numbers up to fib(50000) concurrently without any timeouts or incorrect answers.\n\n###fib_client\nfib_client.py also contains two classes as well as command line main function which accepts several args and options for it's auto tester function. An example of how to use the two fib_client classes is available in *test_client.py*. The two classes are **HumanClient** and **AutoClient**. **HumanClient** runs a loop forever requesting a number from the user then requesting the fib value of that number from the server. **AutoClient** accepts several parameters such as the number of threads/concurrent requests to use, the minimum and maximum fib values to request and the level of verbosity it should use when printing out (printing all the numbers when requesting 100 fib(50000)'s will fill up your terminal very quickly).\n\nTo view the command line opts and args for the auto tester simply run _python fib_client.py --help_.\n\nTo run an instance of the server from the command line simply run _python fib_server.py_. It will request a port number from the kernel automatically.\n"}],"string":"[\n {\n \"alpha_fraction\": 0.6461588740348816,\n \"alphanum_fraction\": 0.6516926884651184,\n \"avg_line_length\": 38.89610290527344,\n \"blob_id\": \"4c5f704ac0776b10bcb5ddabe68e372f4f959051\",\n \"content_id\": \"69066ad46bca611da030d2efc4c1c6c438aaef36\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 3072,\n \"license_type\": \"no_license\",\n \"max_line_length\": 108,\n \"num_lines\": 77,\n \"path\": \"/Fibonacci/fib_server.py\",\n \"repo_name\": \"marty-Wallace/FibbonacciServer\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from socketserver import ThreadingMixIn, TCPServer, BaseRequestHandler\\n\\n\\nclass FibonacciThreadedTCPServer(ThreadingMixIn, TCPServer):\\n \\\"\\\"\\\"\\n FibonacciThreadedTCPServer used to serve concurrent TCP requests for a fibonacci\\n number. The server holds the lookup table fib_dict shared by each instance of\\n FibonacciThreadedTCPRequestHandler to make optimized calculations.\\n \\\"\\\"\\\"\\n\\n def __init__(self, server_address):\\n TCPServer.__init__(self, server_address, FibonacciThreadedTCPRequestHandler, bind_and_activate=True)\\n self.fib_dict = {0: 0, 1: 1, 2: 1}\\n\\n\\nclass FibonacciThreadedTCPRequestHandler(BaseRequestHandler):\\n \\\"\\\"\\\"\\n FibonacciThreadedTCPRequestHandler class for our server. One instance will be created to\\n serve each request that comes into the server. Must override the handle() method which will\\n be called by the server on each new instance for each incoming request\\n \\\"\\\"\\\"\\n\\n def handle(self):\\n \\\"\\\"\\\"\\n reads in an integer from the incoming socket connection, calculates the fibonacci value of\\n that number then returns that value to the socket\\n\\n :return: None\\n \\\"\\\"\\\"\\n\\n data = self.request.recv(1024).strip()\\n print('Serving new request, data=%s' % data)\\n try:\\n num = int(data)\\n if num < 0:\\n raise ValueError\\n except ValueError:\\n self.request.sendall(bytes('Must send a valid number >= 0\\\\n', 'ascii'))\\n return\\n\\n # calculate the result of fib(num)\\n result = self.calc_fib(self.server.fib_dict, num)\\n # encode into bytes\\n ret = bytes(str(result) + '\\\\n', 'ascii')\\n # return result\\n self.request.sendall(ret)\\n\\n @staticmethod\\n def calc_fib(fib_dict, n):\\n \\\"\\\"\\\"\\n Calculates the fibonacci value of n in an optimized way using a lookup table\\n and a linear calculation. Since the fib_table is a dictionary shared between\\n multiple threads we can only write to the dict. Any type of read->modify->write\\n sequence may be interrupted mid-execution, creating a race condition. If n is in\\n the fib_dict we can simply return it, otherwise we can begin calculating each value\\n of fib between the current highest value ( which is fib(len(fib_dict)-1) ) and n.\\n\\n :param fib_dict: the dictionary of fib numbers shared between threads\\n :param n: the value of fib to calculate\\n :return: fib(n)\\n \\\"\\\"\\\"\\n length = len(fib_dict)\\n while length <= n:\\n fib_dict[length] = fib_dict[length - 1] + fib_dict[length - 2]\\n length = len(fib_dict)\\n return fib_dict[n]\\n\\n# if module is imported this code won't run\\nif __name__ == '__main__':\\n # port of 0 will request an open port from the kernel\\n HOST, PORT = 'localhost', 0\\n\\n with FibonacciThreadedTCPServer((HOST, PORT)) as server:\\n ip, port = server.server_address\\n print(\\\"Starting FibServer at %s:%d\\\" % (ip, port))\\n print(\\\"Waiting for fibonacci requests...\\\")\\n server.serve_forever()\\n\"\n },\n {\n \"alpha_fraction\": 0.5699896216392517,\n \"alphanum_fraction\": 0.5748847126960754,\n \"avg_line_length\": 36.273685455322266,\n \"blob_id\": \"425d3c69d8e8431d6d7481a4f1ea64a8e72f1533\",\n \"content_id\": \"1cadb6a432d08fe7bc7a2996e866ea91499752b0\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 10623,\n \"license_type\": \"no_license\",\n \"max_line_length\": 116,\n \"num_lines\": 285,\n \"path\": \"/Fibonacci/fib_client.py\",\n \"repo_name\": \"marty-Wallace/FibbonacciServer\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import socket\\nimport sys\\nimport getopt\\n\\nfrom threading import Thread\\nfrom random import randint\\n\\n\\nclass FibClient(object):\\n \\\"\\\"\\\"\\n Base Class for the AutoClient and HumanClient to extend from. Implements some of the shared methods/attributes\\n \\\"\\\"\\\"\\n def __init__(self, ip, port):\\n self.ip = ip\\n self.port = port\\n\\n @staticmethod\\n def receive_from_sock(sock, buffer_size):\\n \\\"\\\"\\\"\\n Generator function to yield the current buffer received from sock.\\n Can be used in the form of b''.join(recv_all(sock, buffer_size)) to\\n receive the full transmission from a socket\\n\\n :param sock: the socket to receive data from\\n :param buffer_size: the size of the buffer to load on each yield\\n :return: yields the current buffer as a byte object\\n \\\"\\\"\\\"\\n message_buffer = sock.recv(buffer_size)\\n while message_buffer:\\n yield message_buffer\\n message_buffer = sock.recv(buffer_size)\\n\\n @staticmethod\\n def receive_all_from_sock(sock, buffer_size=2048):\\n \\\"\\\"\\\"\\n Builds the full message received from a socket in bytes\\n\\n :param sock: the socket to receive data from\\n :param buffer_size: the size of the buffer to load while building full result, defaults to 2048\\n :return: byte object containing full message\\n \\\"\\\"\\\"\\n return b''.join(FibClient.receive_from_sock(sock, buffer_size))\\n\\n def get_fibonacci_number(self, number):\\n \\\"\\\"\\\"\\n Make a request to the fib server for a single fib number. If there is a socket or value error, return None\\n\\n :param number: the fib number to request from the server\\n :return: fib of n, if an error occurs then None\\n \\\"\\\"\\\"\\n sock = socket.socket(socket.AF_INET, socket.SOCK_STREAM)\\n sock.connect((self.ip, self.port))\\n response = None\\n try:\\n sock.sendall(bytes(str(number), 'ascii'))\\n response = int(FibClient.receive_all_from_sock(sock))\\n except socket.error as err:\\n print(err, file=sys.stderr)\\n except ValueError as err:\\n print(err, file=sys.stderr)\\n finally:\\n sock.close()\\n return response\\n\\n\\nclass AutoClient(FibClient):\\n \\\"\\\"\\\"\\n Class to do automated testing on the fibonacci server. Capable of spinning up multiple threads\\n and requesting random fib numbers then testing their correctness.\\n \\\"\\\"\\\"\\n\\n def _test_fib(self, number, verbose, silent):\\n \\\"\\\"\\\"\\n Requests a single fib number from the server then does the calculation locally to\\n ensure that the number is correct\\n\\n :param number: the fib number to request/test\\n :param verbose flag if the printing level is high\\n :param silent flag if the printing level is for errors only\\n :return: None\\n \\\"\\\"\\\"\\n\\n def local_fib(n):\\n \\\"\\\"\\\"\\n Generate the fib number locally to test against the server's result\\n :param n: the fib number to generate\\n :return: fib of n\\n \\\"\\\"\\\"\\n a, b = 1, 1\\n for i in range(n-1):\\n a, b = b, a+b\\n return a\\n\\n # get server result\\n result = self.get_fibonacci_number(number)\\n # server errors will return None so check for None\\n if result is None:\\n if verbose:\\n print('Received None from server')\\n return None\\n\\n if not silent:\\n print('Received result %d from server for fib(%d)' % (result, number))\\n\\n # get local result\\n local_result = local_fib(number)\\n if verbose:\\n print('Calculated local value to be %d for fib(%d)' % (local_result, number))\\n\\n # compare results\\n if result != local_result:\\n # even on silent we will display errors of this kind.\\n # if we enter this block it means the server is returning wrong numbers\\n print(\\\"Server returned %d for fib(%d) should have been %d\\\" % (result, number, local_result))\\n\\n def connect(self, num_threads=15, fib_min=1, fib_max=2000, verbose=False, silent=False):\\n \\\"\\\"\\\"\\n Runs some automated tests on the server by spinning up multiple concurrent clients, one to a thread,\\n each requesting a random fib number and double checking the results returned by the server\\n\\n :param num_threads: the number of threads/clients to spin up concurrently. Defaults to 15\\n :param fib_min: the minimum fib number to request from the server. Defaults to 1\\n :param fib_max: the maximum fib number to request from the server. Defaults to 2000\\n :param verbose: sets the highest level of printing out whats going on\\n :param silent: sets the lowest level of printing out whats going on\\n :return: None\\n \\\"\\\"\\\"\\n threads = []\\n\\n for i in range(num_threads):\\n num = randint(fib_min, fib_max)\\n if verbose:\\n print('Starting thread with target number %d' % num)\\n threads.append(Thread(target=self._test_fib, args=(num, verbose, silent)))\\n\\n for thread in threads:\\n thread.start()\\n\\n\\nclass HumanClient(FibClient):\\n\\n def __init__(self, ip, port):\\n super().__init__(ip, port)\\n\\n def connect(self):\\n \\\"\\\"\\\"\\n A loop that allows a human to repeatedly request fib numbers from the server.\\n\\n :return: None\\n \\\"\\\"\\\"\\n while True:\\n bad_input = True\\n num = 0\\n while bad_input:\\n try:\\n num = int(input('Please enter which fibonacci number you would like: '))\\n if num <= 0:\\n print(\\\"Please enter a positive number. Negative fibonacci numbers are undefined.\\\")\\n else:\\n bad_input = False\\n except ValueError as err:\\n print(\\\"Please enter a number\\\")\\n continue\\n fib = self.get_fibonacci_number(num)\\n if fib is None:\\n print('Error: None returned by get_fibonacci_number(%s, %d, %d)' % (ip, port, num))\\n continue\\n print(\\\"Fib of %d is %d\\\" % (num, fib))\\n print() # blank line\\n\\n\\ndef usage(message=''):\\n \\\"\\\"\\\"\\n Displays a set of messages describing how to use the program\\n :param message: an optional message to display at the beggining of the output\\n :return: None\\n \\\"\\\"\\\"\\n if message != '':\\n print(message)\\n\\n print('fib_client.py improper usage')\\n print('Usage: python fib_client.py --port=<portnumber> [options] ')\\n print('Options are:')\\n print(' -i, --ip= ip address of the fib server, defaults to localhost')\\n print(' -p, --port= port address of the server, required argument')\\n print(' -a, --auto sets that we are going to use the auto tester client rather than the human client')\\n print(' -t, --threads= only applies to the auto tester and it sets how many concurrent requests to make')\\n print(' -l, --low= sets the lowest fib number to randomly request for the auto client defaults to 1')\\n print(' -h, --high= sets the highest fib number to randomly request for the auto client defaults to 2000')\\n print(' -s, --silent sets the output level to silent for auto-testing (useful for large numbers)')\\n print(' -v, --verbose sets output level to verbose for auto-testing')\\n print(' --help requests this usage screen')\\n exit()\\n\\n\\ndef main():\\n \\\"\\\"\\\"\\n Reads in opts and args from the command line and then takes the appropriate action\\n to either start up the human client or the auto-tester client.\\n \\\"\\\"\\\"\\n\\n ip = '127.0.0.1' # ip address of the server\\n port = -1 # port of the server must be set by args\\n auto = False # flag to run auto_client over human_client\\n threads = 15 # number of threads to run auto_client with\\n low = 1 # lowest fib number to request with auto_client\\n high = 2000 # highest fib number to request with auto_client\\n silent = False # print nothing during auto_testing\\n verbose = False # print everything during auto-testing\\n\\n # reads in all opts and args and sets appropriate variables\\n try:\\n opts, args = getopt.getopt(sys.argv[1:], \\\"i:p:at:l:h:sv\\\",\\n [\\\"ip=\\\", \\\"port=\\\", \\\"auto\\\", \\\"threads=\\\", \\\"low=\\\", \\\"high=\\\", \\\"silent\\\", \\\"verbose\\\"])\\n except getopt.GetoptError:\\n usage()\\n for o, a in opts:\\n # ip address\\n if o in ('-i', '--ip'):\\n ip = a\\n # port number\\n elif o in ('-p', '--port'):\\n try:\\n port = int(a)\\n except ValueError:\\n usage(\\\"Port must be a number\\\")\\n # auto client\\n elif o in ('-a', '--auto'):\\n auto = True\\n # threads\\n elif o in ('-t', '--threads'):\\n try:\\n threads = int(a)\\n except ValueError:\\n usage(\\\"Number of threads must be a number\\\")\\n # low value\\n elif o in ('-l', '--low'):\\n try:\\n low = int(a)\\n if low < 1:\\n raise ValueError\\n except ValueError:\\n usage(\\\"Low must be a number greater than 0\\\")\\n # high value\\n elif o in ('-h', '--high'):\\n try:\\n high = int(a)\\n if high < 1:\\n raise ValueError\\n except ValueError:\\n usage(\\\"High must be a number greater than 0\\\")\\n # verbose\\n elif o in ('-v', '--verbose'):\\n if silent:\\n usage('Cannot set both verbose and silent to be true')\\n verbose = True\\n # silent\\n elif o in ('-s', '--silent'):\\n if verbose:\\n usage('Cannot set both verbose and silent to be true')\\n silent = True\\n # any other args/opts show usage\\n else:\\n usage()\\n\\n # ensure port is set\\n if port == -1:\\n usage('The port number must be set')\\n\\n # make sure our numbers make sense, take low if they don't\\n if high < low:\\n high = low\\n\\n if auto:\\n if verbose:\\n print('Target server at %s:%d' % (ip, port))\\n print('Starting %d threads requesting numbers between %d-%d' % (threads, low, high))\\n\\n AutoClient(ip, port).connect(num_threads=threads, fib_min=low, fib_max=high, verbose=verbose, silent=silent)\\n else:\\n HumanClient(ip, port).connect()\\n\\n# Won't run if code is imported\\nif __name__ == '__main__':\\n main()\\n\"\n },\n {\n \"alpha_fraction\": 0.6936936974525452,\n \"alphanum_fraction\": 0.7162162065505981,\n \"avg_line_length\": 25.058822631835938,\n \"blob_id\": \"1971c1c6c2a8374379d1733f3c454aa2b1e4a4f3\",\n \"content_id\": \"014d173d1e0cebb7ce4e14872f72aa1ed43bdc24\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 444,\n \"license_type\": \"no_license\",\n \"max_line_length\": 91,\n \"num_lines\": 17,\n \"path\": \"/example_client.py\",\n \"repo_name\": \"marty-Wallace/FibbonacciServer\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from Fibonacci import HumanClient, AutoClient\\n\\n'''\\nExample file showing how to use and how to test out the Fibonacci client\\n'''\\n\\nip = 'localhost'\\nport = int(input('Please enter the port number of the Fibonacci server: '))\\n\\ntest_auto = True\\n\\nif test_auto:\\n client = AutoClient(ip, port)\\n client.connect(num_threads=50, fib_min=4000, fib_max=5000, verbose=False, silent=False)\\nelse:\\n client = HumanClient(ip, port)\\n client.connect()\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.7815126180648804,\n \"alphanum_fraction\": 0.7857142686843872,\n \"avg_line_length\": 22.600000381469727,\n \"blob_id\": \"eb341dfb76934920a74a40af33303c35a56b2c59\",\n \"content_id\": \"8aa14ea7435790ee0ba6c25dd598fbe506686b61\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 238,\n \"license_type\": \"no_license\",\n \"max_line_length\": 52,\n \"num_lines\": 10,\n \"path\": \"/example_server.py\",\n \"repo_name\": \"marty-Wallace/FibbonacciServer\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from Fibonacci import FibonacciThreadedTCPServer\\n\\n'''\\nExample file showing how to use the Fibonacci server\\n'''\\n\\naddress = ('localhost', 0)\\nserver = FibonacciThreadedTCPServer(address)\\nprint(server.server_address)\\nserver.serve_forever()\\n\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.752136766910553,\n \"alphanum_fraction\": 0.752136766910553,\n \"avg_line_length\": 28.25,\n \"blob_id\": \"0aa9e98be13cfab094cc5f0fa2e8bedccc82421e\",\n \"content_id\": \"3b293e570539489cae2ffab4dd5dda2b8abea57e\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 117,\n \"license_type\": \"no_license\",\n \"max_line_length\": 63,\n \"num_lines\": 4,\n \"path\": \"/Fibonacci/__init__.py\",\n \"repo_name\": \"marty-Wallace/FibbonacciServer\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from .fib_server import *\\nfrom .fib_client import *\\n\\n__all__ = [FibonacciThreadedTCPServer, AutoClient, HumanClient]\\n\"\n },\n {\n \"alpha_fraction\": 0.7276967763900757,\n \"alphanum_fraction\": 0.7411078810691833,\n \"avg_line_length\": 49.44117736816406,\n \"blob_id\": \"03a89c93317f814e39b413804a7748c3282019a8\",\n \"content_id\": \"18234fd3d6f5c85eec49267a01c2dd23155e6914\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 1715,\n \"license_type\": \"no_license\",\n \"max_line_length\": 397,\n \"num_lines\": 34,\n \"path\": \"/README.md\",\n \"repo_name\": \"marty-Wallace/FibbonacciServer\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# FibonacciServer\\nA class assignment to create a multi-threaded fibonacci server/client\\n\\n\\nMy implementation of a school assignment with the following requirements\\n\\n>Given that our Fibonacci calculation looks like:\\n>```\\n>def fib(n):\\n> if n == 0:\\n> return 0\\n> elif n == 1:\\n> return 1\\n> else:\\n> return fib(n-1) + fib(n-2)\\n>```\\n>\\n>Using Python, design a socket server that will accept an integer(properly packed) and return a fibonacci value for the integer. Design a\\nreliable protocol and implement both a client and server for calculating our Fibonacci values. Ensure that you can have more than one calculation occurring at any moment.\\n\\n####Implementation\\n\\nThe server is set up to serve many concurrent Fibonacci requests for very large values up to around fib(100000). The server uses a lookup table that is shared among each thread. All fibonacci numbers are calculated using a linear definition rather than a recursive one and each value is stored in the cache table. To keep the dictionary \\\"safe\\\" the data is written to the dictionary in the form of:\\n```\\ndef calc_fib(fib_dict, n):\\n length = len(fib_dict)\\n while length <= n:\\n fib_dict[length] = fib_dict[length - 1] + fib_dict[length - 2]\\n length = len(fib_dict)\\nreturn fib_dict[n]\\n```\\nIn this format it is possible for many threads to write to the same location in the dictionary but since each number is based on the previous two numbers the data will stay intact. The length is updated to the length of the actual dict at the end of each loop iteration to avoid doing work done in other threads (as opposed to length += 1). \\n\\nhttp://stackoverflow.com/questions/42564437/why-is-this-python-code-not-thread-safe\\n\"\n },\n {\n \"alpha_fraction\": 0.7823365926742554,\n \"alphanum_fraction\": 0.7927677035331726,\n \"avg_line_length\": 129.72727966308594,\n \"blob_id\": \"d25ca74ee16705848b922c873d0502e214d60d53\",\n \"content_id\": \"fa97b36312e2f0b76b1611dfbff37a463fb3c08d\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 1438,\n \"license_type\": \"no_license\",\n \"max_line_length\": 727,\n \"num_lines\": 11,\n \"path\": \"/Fibonacci/README.md\",\n \"repo_name\": \"marty-Wallace/FibbonacciServer\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"##Fibonacci module \\n\\n###fib_server\\nfib_server.py contains two classes **FibonacciThreadedTCPRequestHandler** and **FibonacciThreadedTCPServer**. Which can be implemented by following the example in *test_client.py*. I have optimized the calculations of the fibonacci numbers as far as I can and on my Dell Inspirion I am able to have 50 threads requesting fib numbers up to fib(50000) concurrently without any timeouts or incorrect answers.\\n\\n###fib_client\\nfib_client.py also contains two classes as well as command line main function which accepts several args and options for it's auto tester function. An example of how to use the two fib_client classes is available in *test_client.py*. The two classes are **HumanClient** and **AutoClient**. **HumanClient** runs a loop forever requesting a number from the user then requesting the fib value of that number from the server. **AutoClient** accepts several parameters such as the number of threads/concurrent requests to use, the minimum and maximum fib values to request and the level of verbosity it should use when printing out (printing all the numbers when requesting 100 fib(50000)'s will fill up your terminal very quickly).\\n\\nTo view the command line opts and args for the auto tester simply run _python fib_client.py --help_.\\n\\nTo run an instance of the server from the command line simply run _python fib_server.py_. It will request a port number from the kernel automatically.\\n\"\n }\n]"},"num_files":{"kind":"number","value":7,"string":"7"}}},{"rowIdx":2057,"cells":{"repo_name":{"kind":"string","value":"sstollenwerk/roguelike_learn"},"repo_url":{"kind":"string","value":"https://github.com/sstollenwerk/roguelike_learn"},"snapshot_id":{"kind":"string","value":"2317bc457ca2c6fd1efc53fc41d57a71ce4fbd6c"},"revision_id":{"kind":"string","value":"148891b8da9a5517533062ef1d0548f50e467055"},"directory_id":{"kind":"string","value":"a639cd77ff940b3274107312dda8b363d30f6213"},"branch_name":{"kind":"string","value":"refs/heads/main"},"visit_date":{"kind":"string","value":"2023-04-29T17:45:59.362969"},"revision_date":{"kind":"string","value":"2021-05-16T06:32:30"},"committer_date":{"kind":"string","value":"2021-05-16T06:32:30"},"github_id":{"kind":"number","value":367771111,"string":"367,771,111"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.6532663106918335,"alphanum_fraction":0.6557788848876953,"avg_line_length":22.41176414489746,"blob_id":"dd88cd660d0ee39f9e9450820ccc2a9f3888ac29","content_id":"2f76626f592eb3f0524e949e42a6de1bb4b613b7","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":398,"license_type":"no_license","max_line_length":74,"num_lines":17,"path":"/entity.py","repo_name":"sstollenwerk/roguelike_learn","src_encoding":"UTF-8","text":"from dataclasses import dataclass, asdict, replace\n\nfrom actions import EscapeAction, MovementAction\nfrom basic_types import Color\n\n\n@dataclass\nclass Entity:\n x: int\n y: int\n string: str # len == 1\n fg: Color\n\n def move(self, action: MovementAction):\n ##return replace(self, x=self.x + action.dx, y=self.y + action.dy)\n self.x += action.dx\n self.y += action.dy\n"},{"alpha_fraction":0.7857142686843872,"alphanum_fraction":0.795918345451355,"avg_line_length":31.66666603088379,"blob_id":"f51fb45929ee6ce8c825c5e881959964e28778ba","content_id":"5e0181216e075d18ebc2f2030269dae8101e2d57","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":98,"license_type":"no_license","max_line_length":78,"num_lines":3,"path":"/README.md","repo_name":"sstollenwerk/roguelike_learn","src_encoding":"UTF-8","text":"# roguelike_learn\n\ngoing off of the http://www.rogueliketutorials.com/tutorials/tcod/v2/ tutorial\n"},{"alpha_fraction":0.5867508053779602,"alphanum_fraction":0.6340693831443787,"avg_line_length":24.360000610351562,"blob_id":"ad6f4ff611dbf71a531608b564669cd8baec4168","content_id":"5899a6c5fab85ed3eaefe3039976300f6bc7a25d","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":634,"license_type":"no_license","max_line_length":78,"num_lines":25,"path":"/tile_types.py","repo_name":"sstollenwerk/roguelike_learn","src_encoding":"UTF-8","text":"import numpy as np # type: ignore\n\nfrom basic_types import Color, graphic_dt, tile_dt\n\n\ndef new_tile(\n *, # Enforce the use of keywords, so that parameter order doesn't matter.\n walkable: bool,\n transparent: bool,\n dark: tuple[int, Color, Color],\n) -> np.ndarray:\n \"\"\"Helper function for defining individual tile types\"\"\"\n return np.array((walkable, transparent, dark), dtype=tile_dt)\n\n\nfloor = new_tile(\n walkable=True,\n transparent=True,\n dark=(ord(\" \"), (255, 255, 255), (50, 50, 150)),\n)\nwall = new_tile(\n walkable=False,\n transparent=False,\n dark=(ord(\" \"), (255, 255, 255), (0, 0, 100)),\n)\n"},{"alpha_fraction":0.6348797082901001,"alphanum_fraction":0.6348797082901001,"avg_line_length":24.866666793823242,"blob_id":"2bb85afc9106173063254003bac9c25cbf483042","content_id":"ff047a4490fdce039c13f1556bc7de1ca7f5a599","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1164,"license_type":"no_license","max_line_length":65,"num_lines":45,"path":"/engine.py","repo_name":"sstollenwerk/roguelike_learn","src_encoding":"UTF-8","text":"from typing import Iterable, Any\nfrom dataclasses import dataclass, asdict\n\nfrom tcod.context import Context\nfrom tcod.console import Console\n\nfrom actions import EscapeAction, MovementAction\nfrom entity import Entity\nfrom input_handlers import EventHandler\nfrom game_map import GameMap\n\n\nclass Engine:\n def __init__(\n self,\n entities: list[Entity],\n event_handler: EventHandler,\n game_map: GameMap,\n player: Entity,\n ):\n if player not in entities:\n entities += [player]\n self.entities = entities\n self.event_handler = event_handler\n self.player = player\n self.game_map = game_map\n\n def handle_events(self, events: Iterable[Any]) -> None:\n for event in events:\n action = self.event_handler.dispatch(event)\n\n if action is None:\n continue\n\n action.perform(self, self.player)\n\n def render(self, console: Console, context: Context) -> None:\n self.game_map.render(console)\n\n for entity in self.entities:\n console.print(**asdict(entity))\n\n context.present(console)\n\n console.clear()\n"},{"alpha_fraction":0.5859246850013733,"alphanum_fraction":0.5941080451011658,"avg_line_length":25.565217971801758,"blob_id":"6abab909900304aec4d15ecdb9938d62c6426077","content_id":"00028583e8d32569c5994a1c8fd3e9046bb09906","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":611,"license_type":"no_license","max_line_length":75,"num_lines":23,"path":"/basic_types.py","repo_name":"sstollenwerk/roguelike_learn","src_encoding":"UTF-8","text":"import numpy as np # type: ignore\n\n\nColor = tuple[int, int, int]\n\n\n# Tile graphics structured type compatible with Console.tiles_rgb.\ngraphic_dt = np.dtype(\n [\n (\"ch\", np.int32), # Unicode codepoint.\n (\"fg\", \"3B\"), # 3 unsigned bytes, for RGB colors.\n (\"bg\", \"3B\"),\n ]\n)\n\n# Tile struct used for statically defined tile data.\ntile_dt = np.dtype(\n [\n (\"walkable\", np.bool), # True if this tile can be walked over.\n (\"transparent\", np.bool), # True if this tile doesn't block FOV.\n (\"dark\", graphic_dt), # Graphics for when this tile is not in FOV.\n ]\n)\n"}],"string":"[\n {\n \"alpha_fraction\": 0.6532663106918335,\n \"alphanum_fraction\": 0.6557788848876953,\n \"avg_line_length\": 22.41176414489746,\n \"blob_id\": \"dd88cd660d0ee39f9e9450820ccc2a9f3888ac29\",\n \"content_id\": \"2f76626f592eb3f0524e949e42a6de1bb4b613b7\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 398,\n \"license_type\": \"no_license\",\n \"max_line_length\": 74,\n \"num_lines\": 17,\n \"path\": \"/entity.py\",\n \"repo_name\": \"sstollenwerk/roguelike_learn\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from dataclasses import dataclass, asdict, replace\\n\\nfrom actions import EscapeAction, MovementAction\\nfrom basic_types import Color\\n\\n\\n@dataclass\\nclass Entity:\\n x: int\\n y: int\\n string: str # len == 1\\n fg: Color\\n\\n def move(self, action: MovementAction):\\n ##return replace(self, x=self.x + action.dx, y=self.y + action.dy)\\n self.x += action.dx\\n self.y += action.dy\\n\"\n },\n {\n \"alpha_fraction\": 0.7857142686843872,\n \"alphanum_fraction\": 0.795918345451355,\n \"avg_line_length\": 31.66666603088379,\n \"blob_id\": \"f51fb45929ee6ce8c825c5e881959964e28778ba\",\n \"content_id\": \"5e0181216e075d18ebc2f2030269dae8101e2d57\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 98,\n \"license_type\": \"no_license\",\n \"max_line_length\": 78,\n \"num_lines\": 3,\n \"path\": \"/README.md\",\n \"repo_name\": \"sstollenwerk/roguelike_learn\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# roguelike_learn\\n\\ngoing off of the http://www.rogueliketutorials.com/tutorials/tcod/v2/ tutorial\\n\"\n },\n {\n \"alpha_fraction\": 0.5867508053779602,\n \"alphanum_fraction\": 0.6340693831443787,\n \"avg_line_length\": 24.360000610351562,\n \"blob_id\": \"ad6f4ff611dbf71a531608b564669cd8baec4168\",\n \"content_id\": \"5899a6c5fab85ed3eaefe3039976300f6bc7a25d\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 634,\n \"license_type\": \"no_license\",\n \"max_line_length\": 78,\n \"num_lines\": 25,\n \"path\": \"/tile_types.py\",\n \"repo_name\": \"sstollenwerk/roguelike_learn\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import numpy as np # type: ignore\\n\\nfrom basic_types import Color, graphic_dt, tile_dt\\n\\n\\ndef new_tile(\\n *, # Enforce the use of keywords, so that parameter order doesn't matter.\\n walkable: bool,\\n transparent: bool,\\n dark: tuple[int, Color, Color],\\n) -> np.ndarray:\\n \\\"\\\"\\\"Helper function for defining individual tile types\\\"\\\"\\\"\\n return np.array((walkable, transparent, dark), dtype=tile_dt)\\n\\n\\nfloor = new_tile(\\n walkable=True,\\n transparent=True,\\n dark=(ord(\\\" \\\"), (255, 255, 255), (50, 50, 150)),\\n)\\nwall = new_tile(\\n walkable=False,\\n transparent=False,\\n dark=(ord(\\\" \\\"), (255, 255, 255), (0, 0, 100)),\\n)\\n\"\n },\n {\n \"alpha_fraction\": 0.6348797082901001,\n \"alphanum_fraction\": 0.6348797082901001,\n \"avg_line_length\": 24.866666793823242,\n \"blob_id\": \"2bb85afc9106173063254003bac9c25cbf483042\",\n \"content_id\": \"ff047a4490fdce039c13f1556bc7de1ca7f5a599\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1164,\n \"license_type\": \"no_license\",\n \"max_line_length\": 65,\n \"num_lines\": 45,\n \"path\": \"/engine.py\",\n \"repo_name\": \"sstollenwerk/roguelike_learn\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from typing import Iterable, Any\\nfrom dataclasses import dataclass, asdict\\n\\nfrom tcod.context import Context\\nfrom tcod.console import Console\\n\\nfrom actions import EscapeAction, MovementAction\\nfrom entity import Entity\\nfrom input_handlers import EventHandler\\nfrom game_map import GameMap\\n\\n\\nclass Engine:\\n def __init__(\\n self,\\n entities: list[Entity],\\n event_handler: EventHandler,\\n game_map: GameMap,\\n player: Entity,\\n ):\\n if player not in entities:\\n entities += [player]\\n self.entities = entities\\n self.event_handler = event_handler\\n self.player = player\\n self.game_map = game_map\\n\\n def handle_events(self, events: Iterable[Any]) -> None:\\n for event in events:\\n action = self.event_handler.dispatch(event)\\n\\n if action is None:\\n continue\\n\\n action.perform(self, self.player)\\n\\n def render(self, console: Console, context: Context) -> None:\\n self.game_map.render(console)\\n\\n for entity in self.entities:\\n console.print(**asdict(entity))\\n\\n context.present(console)\\n\\n console.clear()\\n\"\n },\n {\n \"alpha_fraction\": 0.5859246850013733,\n \"alphanum_fraction\": 0.5941080451011658,\n \"avg_line_length\": 25.565217971801758,\n \"blob_id\": \"6abab909900304aec4d15ecdb9938d62c6426077\",\n \"content_id\": \"00028583e8d32569c5994a1c8fd3e9046bb09906\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 611,\n \"license_type\": \"no_license\",\n \"max_line_length\": 75,\n \"num_lines\": 23,\n \"path\": \"/basic_types.py\",\n \"repo_name\": \"sstollenwerk/roguelike_learn\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import numpy as np # type: ignore\\n\\n\\nColor = tuple[int, int, int]\\n\\n\\n# Tile graphics structured type compatible with Console.tiles_rgb.\\ngraphic_dt = np.dtype(\\n [\\n (\\\"ch\\\", np.int32), # Unicode codepoint.\\n (\\\"fg\\\", \\\"3B\\\"), # 3 unsigned bytes, for RGB colors.\\n (\\\"bg\\\", \\\"3B\\\"),\\n ]\\n)\\n\\n# Tile struct used for statically defined tile data.\\ntile_dt = np.dtype(\\n [\\n (\\\"walkable\\\", np.bool), # True if this tile can be walked over.\\n (\\\"transparent\\\", np.bool), # True if this tile doesn't block FOV.\\n (\\\"dark\\\", graphic_dt), # Graphics for when this tile is not in FOV.\\n ]\\n)\\n\"\n }\n]"},"num_files":{"kind":"number","value":5,"string":"5"}}},{"rowIdx":2058,"cells":{"repo_name":{"kind":"string","value":"dimbler/Zabbix"},"repo_url":{"kind":"string","value":"https://github.com/dimbler/Zabbix"},"snapshot_id":{"kind":"string","value":"cd81064b099a383b1de4ebdded2a2db4996dddba"},"revision_id":{"kind":"string","value":"34a00da5acce21fa418c6bd29f4471396a62dcfa"},"directory_id":{"kind":"string","value":"d71713677ec27bf50d0db7b21317e6d3b4573bcf"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"string","value":"2021-05-06T02:46:24.217903"},"revision_date":{"kind":"string","value":"2017-12-18T12:02:14"},"committer_date":{"kind":"string","value":"2017-12-18T12:02:14"},"github_id":{"kind":"number","value":114636232,"string":"114,636,232"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.6751569509506226,"alphanum_fraction":0.6920179128646851,"avg_line_length":32.18452453613281,"blob_id":"b6b65a538cf167a57b9ddb3d8e375c6c8ce3722c","content_id":"dca652f3fa07204de6262e8d5e247143be071980","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":5607,"license_type":"no_license","max_line_length":154,"num_lines":168,"path":"/send_traf_down.py","repo_name":"dimbler/Zabbix","src_encoding":"UTF-8","text":"#!/usr/bin/env python\n# coding: utf-8\n\n#\n# import needed modules.\n# pyzabbix is needed, see https://github.com/lukecyca/pyzabbix\n#\n# Pillow is also needed, see https://github.com/python-pillow/Pillow\n#\n#\nimport argparse\nimport ConfigParser\nimport os\nimport os.path\nimport distutils.util\nimport requests\nimport time\nimport sys\nfrom cStringIO import StringIO\nfrom PIL import Image\nfrom pyzabbix import ZabbixAPI\nimport cStringIO\n\nusername = \"root\"\npassword = \"zabbix123\"\ngraphid = 14931\napi = \"http://localhost\"\nperiod=9600\n\ndef getGraph(graphid, username, password, api, period):\n zapi = ZabbixAPI(url='http://localhost', user='root', password='zabbix123')\n zapi.session.verify = False\n\n # Find graph from API\n graph = zapi.graph.get(output=\"extend\", graphids=graphid)\n\n if graph:\n #print(format(graph))\n # Set width and height\n width = graph[0]['width']\n height = graph[0]['height']\n\n # Select the right graph generator according to graph type\n # type 3 = Exploded graph\n if graph[0]['graphtype'] == \"3\":\n generator = \"chart6.php\"\n # type 2 = Pie graph\n elif graph[0]['graphtype'] == \"2\":\n generator = \"chart6.php\"\n # type 1 = Stacked graph\n elif graph[0]['graphtype'] == \"1\":\n generator = \"chart2.php\"\n # type 0 = Normal graph\n elif graph[0]['graphtype'] == \"0\":\n generator = \"chart2.php\"\n # catch-all in case someone invents a new type/generator\n else:\n generator = \"chart2.php\"\n\n # Set login URL for the Frontend (frontend access is needed, as we cannot retrieve graph images via the API)\n loginurl = api + \"/index.php\"\n # Data that needs to be posted to the Frontend to log in\n logindata = {'autologin' : '1', 'name' : username, 'password' : password, 'enter' : 'Sign in'}\n # We need to fool the frontend into thinking we are a real browser\n headers = {'User-Agent' : 'Mozilla/5.0 (Windows NT 5.1; rv:31.0) Gecko/20100101 Firefox/31.0', 'Content-type' : 'application/x-www-form-urlencoded'}\n\n # setup a session object so we can reuse session cookies\n session=requests.session()\n verify=False\n\n # Login to the frontend\n login=session.post(loginurl, params=logindata, headers=headers, verify=verify)\n\n # See if we logged in successfully\n try:\n if session.cookies['zbx_sessionid']:\n\n # Build the request for the graph\n graphurl = api + \"/\" + generator + \"?graphid=\" + str(graphid) + \"&period=\" + str(period)\n\n\n # get the graph\n graphreq = session.get(graphurl,verify=verify)\n # read the data as an image\n graphpng = Image.open(StringIO(graphreq.content))\n memf = cStringIO.StringIO()\n graphpng.save(memf, \"JPEG\")\n return memf\n\n except:\n sys.exit(\"Error: Could not log in to retrieve graph\")\n else:\n sys.exit(\"Error: Could not find graphid \"+ graphid)\n\n\n# Arguments parser\nparser = argparse.ArgumentParser(description='Send Zabbix notification with Graphics')\nparser.add_argument('recipient', metavar=('Recipient'), type=str, help='Email recepient')\nparser.add_argument('subject', metavar=('Subject'), type=str, help='Subject you want to push.')\nparser.add_argument('message', metavar=('Message'), type=str, help='Message you want to push.')\n\n# Argument processing\nargs = parser.parse_args()\nrecipient = args.recipient\nsubject = args.subject\nmessage = args.message\n\nfrom email.MIMEMultipart import MIMEMultipart\nfrom email.MIMEText import MIMEText\nfrom email.MIMEImage import MIMEImage\n\n# Define these once; use them twice!\nstrFrom = 'zabbix_gis_gmp@sitonica.ru'\nstrTo = recipient\n\n# Create the root message and fill in the from, to, and subject headers\nmsgRoot = MIMEMultipart('related')\nmsgRoot['Subject'] = subject\nmsgRoot['From'] = strFrom\nmsgRoot['To'] = strTo\nmsgRoot.preamble = 'This is a multi-part message in MIME format.'\n\n# Encapsulate the plain and HTML versions of the message body in an\n# 'alternative' part, so message agents can decide which they want to display.\nmsgAlternative = MIMEMultipart('alternative')\nmsgRoot.attach(msgAlternative)\n\nmsgText = MIMEText('This is the alternative plain text message.')\nmsgAlternative.attach(msgText)\n\nzapi = ZabbixAPI(url='http://localhost', user='root', password='zabbix123')\nzapi.session.verify = False\n\ntrig = zapi.trigger.get(output='extend',\n itemids = ['135536','135537'],\n only_true=1,\n)\n\nif trig:\n message += \"<br><b>Присутствуют проблемы доступа к СМЭВ</b><br>\"\n\n# We reference the image in the IMG SRC attribute by the ID we give it below\nmsgText = MIMEText(message+'<br><img src=\"cid:image1\"><br><br><img src=\"cid:image2\"><br><br><img src=\"cid:image3\"><br>', 'html')\nmsgAlternative.attach(msgText)\n\n# This example assumes the image is in the current directory\ngraphImage1 = getGraph(graphid, username, password, api, period)\nmsgImage1 = MIMEImage(graphImage1.getvalue())\nmsgImage1.add_header('Content-ID', '<image1>')\nmsgRoot.attach(msgImage1)\n\ngraphImage2 = getGraph(18485, username, password, api, period)\nmsgImage2 = MIMEImage(graphImage2.getvalue())\nmsgImage2.add_header('Content-ID', '<image2>')\nmsgRoot.attach(msgImage2)\n\ngraphImage3 = getGraph(11706, username, password, api, period)\nmsgImage3 = MIMEImage(graphImage3.getvalue())\nmsgImage3.add_header('Content-ID', '<image3>')\nmsgRoot.attach(msgImage3)\n\n# Send the email (this example assumes SMTP authentication is required)\n\nimport smtplib\nsmtp = smtplib.SMTP('localhost', 25)\nsmtp.ehlo()\nsmtp.sendmail(strFrom, strTo, msgRoot.as_string())\nsmtp.quit()\n"}],"string":"[\n {\n \"alpha_fraction\": 0.6751569509506226,\n \"alphanum_fraction\": 0.6920179128646851,\n \"avg_line_length\": 32.18452453613281,\n \"blob_id\": \"b6b65a538cf167a57b9ddb3d8e375c6c8ce3722c\",\n \"content_id\": \"dca652f3fa07204de6262e8d5e247143be071980\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 5607,\n \"license_type\": \"no_license\",\n \"max_line_length\": 154,\n \"num_lines\": 168,\n \"path\": \"/send_traf_down.py\",\n \"repo_name\": \"dimbler/Zabbix\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#!/usr/bin/env python\\n# coding: utf-8\\n\\n#\\n# import needed modules.\\n# pyzabbix is needed, see https://github.com/lukecyca/pyzabbix\\n#\\n# Pillow is also needed, see https://github.com/python-pillow/Pillow\\n#\\n#\\nimport argparse\\nimport ConfigParser\\nimport os\\nimport os.path\\nimport distutils.util\\nimport requests\\nimport time\\nimport sys\\nfrom cStringIO import StringIO\\nfrom PIL import Image\\nfrom pyzabbix import ZabbixAPI\\nimport cStringIO\\n\\nusername = \\\"root\\\"\\npassword = \\\"zabbix123\\\"\\ngraphid = 14931\\napi = \\\"http://localhost\\\"\\nperiod=9600\\n\\ndef getGraph(graphid, username, password, api, period):\\n zapi = ZabbixAPI(url='http://localhost', user='root', password='zabbix123')\\n zapi.session.verify = False\\n\\n # Find graph from API\\n graph = zapi.graph.get(output=\\\"extend\\\", graphids=graphid)\\n\\n if graph:\\n #print(format(graph))\\n # Set width and height\\n width = graph[0]['width']\\n height = graph[0]['height']\\n\\n # Select the right graph generator according to graph type\\n # type 3 = Exploded graph\\n if graph[0]['graphtype'] == \\\"3\\\":\\n generator = \\\"chart6.php\\\"\\n # type 2 = Pie graph\\n elif graph[0]['graphtype'] == \\\"2\\\":\\n generator = \\\"chart6.php\\\"\\n # type 1 = Stacked graph\\n elif graph[0]['graphtype'] == \\\"1\\\":\\n generator = \\\"chart2.php\\\"\\n # type 0 = Normal graph\\n elif graph[0]['graphtype'] == \\\"0\\\":\\n generator = \\\"chart2.php\\\"\\n # catch-all in case someone invents a new type/generator\\n else:\\n generator = \\\"chart2.php\\\"\\n\\n # Set login URL for the Frontend (frontend access is needed, as we cannot retrieve graph images via the API)\\n loginurl = api + \\\"/index.php\\\"\\n # Data that needs to be posted to the Frontend to log in\\n logindata = {'autologin' : '1', 'name' : username, 'password' : password, 'enter' : 'Sign in'}\\n # We need to fool the frontend into thinking we are a real browser\\n headers = {'User-Agent' : 'Mozilla/5.0 (Windows NT 5.1; rv:31.0) Gecko/20100101 Firefox/31.0', 'Content-type' : 'application/x-www-form-urlencoded'}\\n\\n # setup a session object so we can reuse session cookies\\n session=requests.session()\\n verify=False\\n\\n # Login to the frontend\\n login=session.post(loginurl, params=logindata, headers=headers, verify=verify)\\n\\n # See if we logged in successfully\\n try:\\n if session.cookies['zbx_sessionid']:\\n\\n # Build the request for the graph\\n graphurl = api + \\\"/\\\" + generator + \\\"?graphid=\\\" + str(graphid) + \\\"&period=\\\" + str(period)\\n\\n\\n # get the graph\\n graphreq = session.get(graphurl,verify=verify)\\n # read the data as an image\\n graphpng = Image.open(StringIO(graphreq.content))\\n memf = cStringIO.StringIO()\\n graphpng.save(memf, \\\"JPEG\\\")\\n return memf\\n\\n except:\\n sys.exit(\\\"Error: Could not log in to retrieve graph\\\")\\n else:\\n sys.exit(\\\"Error: Could not find graphid \\\"+ graphid)\\n\\n\\n# Arguments parser\\nparser = argparse.ArgumentParser(description='Send Zabbix notification with Graphics')\\nparser.add_argument('recipient', metavar=('Recipient'), type=str, help='Email recepient')\\nparser.add_argument('subject', metavar=('Subject'), type=str, help='Subject you want to push.')\\nparser.add_argument('message', metavar=('Message'), type=str, help='Message you want to push.')\\n\\n# Argument processing\\nargs = parser.parse_args()\\nrecipient = args.recipient\\nsubject = args.subject\\nmessage = args.message\\n\\nfrom email.MIMEMultipart import MIMEMultipart\\nfrom email.MIMEText import MIMEText\\nfrom email.MIMEImage import MIMEImage\\n\\n# Define these once; use them twice!\\nstrFrom = 'zabbix_gis_gmp@sitonica.ru'\\nstrTo = recipient\\n\\n# Create the root message and fill in the from, to, and subject headers\\nmsgRoot = MIMEMultipart('related')\\nmsgRoot['Subject'] = subject\\nmsgRoot['From'] = strFrom\\nmsgRoot['To'] = strTo\\nmsgRoot.preamble = 'This is a multi-part message in MIME format.'\\n\\n# Encapsulate the plain and HTML versions of the message body in an\\n# 'alternative' part, so message agents can decide which they want to display.\\nmsgAlternative = MIMEMultipart('alternative')\\nmsgRoot.attach(msgAlternative)\\n\\nmsgText = MIMEText('This is the alternative plain text message.')\\nmsgAlternative.attach(msgText)\\n\\nzapi = ZabbixAPI(url='http://localhost', user='root', password='zabbix123')\\nzapi.session.verify = False\\n\\ntrig = zapi.trigger.get(output='extend',\\n itemids = ['135536','135537'],\\n only_true=1,\\n)\\n\\nif trig:\\n message += \\\"<br><b>Присутствуют проблемы доступа к СМЭВ</b><br>\\\"\\n\\n# We reference the image in the IMG SRC attribute by the ID we give it below\\nmsgText = MIMEText(message+'<br><img src=\\\"cid:image1\\\"><br><br><img src=\\\"cid:image2\\\"><br><br><img src=\\\"cid:image3\\\"><br>', 'html')\\nmsgAlternative.attach(msgText)\\n\\n# This example assumes the image is in the current directory\\ngraphImage1 = getGraph(graphid, username, password, api, period)\\nmsgImage1 = MIMEImage(graphImage1.getvalue())\\nmsgImage1.add_header('Content-ID', '<image1>')\\nmsgRoot.attach(msgImage1)\\n\\ngraphImage2 = getGraph(18485, username, password, api, period)\\nmsgImage2 = MIMEImage(graphImage2.getvalue())\\nmsgImage2.add_header('Content-ID', '<image2>')\\nmsgRoot.attach(msgImage2)\\n\\ngraphImage3 = getGraph(11706, username, password, api, period)\\nmsgImage3 = MIMEImage(graphImage3.getvalue())\\nmsgImage3.add_header('Content-ID', '<image3>')\\nmsgRoot.attach(msgImage3)\\n\\n# Send the email (this example assumes SMTP authentication is required)\\n\\nimport smtplib\\nsmtp = smtplib.SMTP('localhost', 25)\\nsmtp.ehlo()\\nsmtp.sendmail(strFrom, strTo, msgRoot.as_string())\\nsmtp.quit()\\n\"\n }\n]"},"num_files":{"kind":"number","value":1,"string":"1"}}},{"rowIdx":2059,"cells":{"repo_name":{"kind":"string","value":"LiquidNalee/MiniPkmnShowdown"},"repo_url":{"kind":"string","value":"https://github.com/LiquidNalee/MiniPkmnShowdown"},"snapshot_id":{"kind":"string","value":"fadb560ad7a7e0ab599910b046cf0d9062326555"},"revision_id":{"kind":"string","value":"56520e351f984fee710860b0949a19eefa8ee05f"},"directory_id":{"kind":"string","value":"71d9b9fd559e05fd0d961b505973a1e86e5b7f3c"},"branch_name":{"kind":"string","value":"refs/heads/main"},"visit_date":{"kind":"string","value":"2023-02-13T05:12:13.285627"},"revision_date":{"kind":"string","value":"2021-01-11T17:44:54"},"committer_date":{"kind":"string","value":"2021-01-11T17:44:54"},"github_id":{"kind":"number","value":325296231,"string":"325,296,231"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.5402510166168213,"alphanum_fraction":0.5512703061103821,"avg_line_length":47.04411697387695,"blob_id":"4d9d411e31e91cdb6db2f0a89436e44ee82e0cb7","content_id":"dfc0e92419f727f075b6071763436d6991f687c1","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":3267,"license_type":"permissive","max_line_length":168,"num_lines":68,"path":"/models/pkmn/moves/PokemonMove.py","repo_name":"LiquidNalee/MiniPkmnShowdown","src_encoding":"UTF-8","text":"from enum import Enum\nfrom os.path import join\nfrom json import load\n\nfrom models.pkmn.types.PokemonType import PokemonType\nfrom models.pkmn.stats.StatsDict import StatsDict\n\nfrom database.DatabaseConfig import database_dir\n\n\nclass MoveCategory(Enum):\n Physical = \"[Ph]\"\n Special = \"[Sp]\"\n Status = \"[St]\"\n\n\nclass PokemonMove:\n\n def __init__(self, name: str, move_type: PokemonType, category: MoveCategory, pp: int,\n power: int = 0, accuracy: int = 100, priority: int = 0, effect_rate: int = 0,\n self_stat_mod: StatsDict = None, trgt_stat_mod: StatsDict = None):\n self.name = name\n self.type = move_type\n self.category = category\n self.pp = pp\n self.max_pp = pp\n self.power = power\n self.accuracy = accuracy\n self.priority = priority\n self.effect_rate = effect_rate\n self.self_stat_mod = self_stat_mod if self_stat_mod is not None else StatsDict()\n self.trgt_stat_mod = trgt_stat_mod if trgt_stat_mod is not None else StatsDict()\n\n def __str__(self):\n prio_str = f\"prio:{'+' if self.priority > 0 else ''}{self.priority}\"\n return f\"{str(self.type):^15} {self.category.value}{self.pp:>9}/{self.max_pp:<3}\\n\" \\\n f\"{self.name:^34}\\n\" \\\n f\" {str(self.power):>3}BP -{str(self.accuracy) + '% acc.':^15}- {prio_str:>8} \\n\" \\\n f\"{'-':^34}\" if self.effect_rate == 0 else \\\n f\"{self.effect_rate:<3}%: \" if self.effect_rate != 100 else \"\" \\\n + f\"{', '.join([key + ' x' + val for key, val in self.self_stat_mod if val != 0]):^20} [Self]\" \\\n if self.self_stat_mod != StatsDict() else \\\n f\"{', '.join([key + ' x' + val for key, val in self.trgt_stat_mod if val != 0]):^18} [Target]\" \\\n if self.trgt_stat_mod != StatsDict() else \\\n \"\"\n\n @staticmethod\n def fromDb(name: str):\n with open(join(str(database_dir), \"moves\", f\"{name.lower()}.json\")) as move_data_file:\n move_data = load(move_data_file)\n return PokemonMove(\n name=name,\n move_type=PokemonType[move_data[\"type\"]],\n category=MoveCategory[move_data[\"category\"]],\n pp=int(move_data[\"pp\"]),\n power=int(move_data[\"power\"])\n if \"power\" in move_data and move_data[\"power\"] is not None else 0,\n accuracy=int(move_data[\"accuracy\"])\n if \"accuracy\" in move_data and move_data[\"accuracy\"] is not None else 100,\n priority=int(move_data[\"priority\"])\n if \"priority\" in move_data and move_data[\"priority\"] else 0,\n effect_rate=int(move_data[\"effect_rate\"])\n if \"effect_rate\" in move_data and move_data[\"effect_rate\"] is not None else 0,\n self_stat_mod=StatsDict(move_data[\"self_stat_mod\"])\n if \"self_stat_mod\" in move_data and move_data[\"self_stat_mode\"] is not None else StatsDict(),\n trgt_stat_mod=StatsDict(move_data[\"trgt_stat_mod\"])\n if \"trgt_stat_mod\" in move_data and move_data[\"trgt_stat_mode\"] else StatsDict()\n )\n"},{"alpha_fraction":0.7914438247680664,"alphanum_fraction":0.7914438247680664,"avg_line_length":17.799999237060547,"blob_id":"954d472d89e9073e7c52ba6242c78676f01bd807","content_id":"01a702e295e2571e5deb314e8cd3c745c12f5092","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Makefile","length_bytes":187,"license_type":"permissive","max_line_length":47,"num_lines":10,"path":"/Makefile","repo_name":"LiquidNalee/MiniPkmnShowdown","src_encoding":"UTF-8","text":"build:\n\tdocker build -t minishowdown:latest .\n\nrun:\n\tdocker run -d --name minishowdown minishowdown\n\nclean:\n\tdocker stop minishowdown\n\tdocker rm minishowdown\n\tdocker image rm minishowdown"},{"alpha_fraction":0.49754709005355835,"alphanum_fraction":0.5299889445304871,"avg_line_length":40.56578826904297,"blob_id":"3cef88bfa9bc6e012796d2e14d7412eff13deae4","content_id":"c708bf83ee5d447ca884a24a67222f7821aaa032","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":6319,"license_type":"permissive","max_line_length":105,"num_lines":152,"path":"/tests/models/game/battle/test_BattleGameState.py","repo_name":"LiquidNalee/MiniPkmnShowdown","src_encoding":"UTF-8","text":"from unittest import TestCase\n\nfrom models.game.battle.BattleGameState import BattleGameState\nfrom models.game.trainer.PokemonTrainer import PokemonTrainer\nfrom models.game.trainer.utils.ArenaBadge import ArenaBadge\nfrom models.pkmn.PokemonModel import PokemonModel\nfrom models.pkmn.moves.PokemonMove import MoveCategory, PokemonMove\nfrom models.pkmn.natures.PokemonNature import PokemonNature\nfrom models.pkmn.stats.StatsDict import StatsDict\nfrom models.pkmn.types.PokemonType import PokemonType\n\n\nclass TestBattleGameState(TestCase):\n\n def setUp(self) -> None:\n self.Pikachu = PokemonModel(\n name=\"Pikachu\",\n types=(PokemonType.Electric, None),\n level=100,\n nature=PokemonNature.Jolly,\n moves=[\n PokemonMove(\n name=\"Volt Tackle\",\n move_type=PokemonType.Electric,\n category=MoveCategory.Physical,\n pp=24,\n power=120\n ),\n PokemonMove(\n name=\"Iron Tail\",\n move_type=PokemonType.Steel,\n category=MoveCategory.Physical,\n pp=24,\n power=100,\n accuracy=75\n ),\n PokemonMove(\n name=\"Thunderbolt\",\n move_type=PokemonType.Electric,\n category=MoveCategory.Special,\n pp=24,\n power=90\n )\n ],\n base_stats=StatsDict(hp=35, atk=55, phys_def=40, spe_atk=50, spe_def=50, spd=90),\n evs=StatsDict(hp=0, atk=252, phys_def=0, spe_atk=4, spe_def=0, spd=252),\n ivs=StatsDict(hp=31, atk=31, phys_def=31, spe_atk=31, spe_def=31, spd=31)\n )\n self.Charizard = PokemonModel(\n name=\"Charizard\",\n types=(PokemonType.Fire, PokemonType.Flying),\n level=100,\n nature=PokemonNature.Jolly,\n moves=[\n PokemonMove(\n name=\"Fire Blast\",\n move_type=PokemonType.Fire,\n category=MoveCategory.Special,\n pp=8,\n power=110,\n accuracy=85\n ),\n PokemonMove(\n name=\"Hurricane\",\n move_type=PokemonType.Flying,\n category=MoveCategory.Special,\n pp=16,\n power=110,\n accuracy=70\n )\n ],\n base_stats=StatsDict(hp=78, atk=84, phys_def=78, spe_atk=109, spe_def=85, spd=100),\n evs=StatsDict(hp=0, atk=0, phys_def=0, spe_atk=252, spe_def=4, spd=252),\n ivs=StatsDict(hp=31, atk=31, phys_def=31, spe_atk=31, spe_def=31, spd=31)\n )\n self.Pidgeot = PokemonModel(\n name=\"Pidgeot\",\n types=(PokemonType.Flying, PokemonType.Normal),\n level=100,\n nature=PokemonNature.Jolly,\n moves=[\n PokemonMove(\n name=\"Double Edge\",\n move_type=PokemonType.Normal,\n category=MoveCategory.Physical,\n pp=24,\n power=120\n ),\n PokemonMove(\n name=\"Brave Bird\",\n move_type=PokemonType.Flying,\n category=MoveCategory.Physical,\n pp=24,\n power=120\n )\n ],\n base_stats=StatsDict(hp=83, atk=80, phys_def=75, spe_atk=70, spe_def=70, spd=101),\n evs=StatsDict(hp=0, atk=252, phys_def=0, spe_atk=0, spe_def=4, spd=252),\n ivs=StatsDict(hp=31, atk=31, phys_def=31, spe_atk=31, spe_def=31, spd=31)\n )\n self.Blastoise = PokemonModel(\n name=\"Blastoise\",\n types=(PokemonType.Water, None),\n level=100,\n nature=PokemonNature.Modest,\n moves=[\n PokemonMove(\n name=\"Hydro Pump\",\n move_type=PokemonType.Water,\n category=MoveCategory.Special,\n pp=8,\n power=110,\n accuracy=80\n ),\n PokemonMove(\n name=\"Ice Beam\",\n move_type=PokemonType.Ice,\n category=MoveCategory.Special,\n pp=16,\n power=90\n )\n ],\n base_stats=StatsDict(hp=79, atk=83, phys_def=100, spe_atk=85, spe_def=105, spd=78),\n evs=StatsDict(hp=252, atk=0, phys_def=0, spe_atk=252, spe_def=4, spd=0),\n ivs=StatsDict(hp=31, atk=31, phys_def=31, spe_atk=31, spe_def=31, spd=31)\n )\n self.Red = PokemonTrainer(\n name=\"Red\",\n team=[self.Pikachu, self.Charizard],\n badges=[ArenaBadge.Boulder, ArenaBadge.Cascade, ArenaBadge.Thunder, ArenaBadge.Rainbow,\n ArenaBadge.Soul, ArenaBadge.Marsh, ArenaBadge.Marsh, ArenaBadge.Earth]\n )\n self.Blue = PokemonTrainer(\n name=\"Blue\",\n team=[self.Pidgeot, self.Blastoise],\n badges=[ArenaBadge.Boulder, ArenaBadge.Cascade, ArenaBadge.Thunder, ArenaBadge.Rainbow,\n ArenaBadge.Soul, ArenaBadge.Marsh, ArenaBadge.Marsh, ArenaBadge.Earth]\n )\n self.BattleGameState = BattleGameState(player=self.Red, opponent=self.Blue)\n\n def test_battle_game_state(self):\n\n assert self.BattleGameState.player.name == \"Red\" and self.BattleGameState.opponent.name == \"Blue\"\n assert self.BattleGameState.turn == 1\n assert self.BattleGameState.getPlayerActivePkmn() == self.Pikachu\n assert self.BattleGameState.getOpponentActivePkmn() == self.Pidgeot\n self.BattleGameState.setPlayerActivePkmn(1)\n assert self.BattleGameState.getPlayerActivePkmn() == self.Charizard\n assert self.BattleGameState.getOpponentActivePkmn() == self.Pidgeot\n self.BattleGameState.setOpponentActivePkmn(1)\n assert self.BattleGameState.getPlayerActivePkmn() == self.Charizard\n assert self.BattleGameState.getOpponentActivePkmn() == self.Blastoise\n\n"},{"alpha_fraction":0.6862886548042297,"alphanum_fraction":0.6961396932601929,"avg_line_length":57.61971664428711,"blob_id":"003e87c83f1b6010c83cdc0819d2299d7c93a6bf","content_id":"a7e8757dd8e587e24156e95d5ada6d5000ba1660","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":12486,"license_type":"permissive","max_line_length":111,"num_lines":213,"path":"/engine/pkmn/types/ClassicTypesRuleSet.py","repo_name":"LiquidNalee/MiniPkmnShowdown","src_encoding":"UTF-8","text":"from pandas import DataFrame\nfrom engine.pkmn.types.TypesBaseRuleSet import TypesBaseRuleSet\nfrom models.pkmn.types.PokemonType import PokemonType\n\n\nclass ClassicTypesRuleSet(TypesBaseRuleSet):\n\n def __init__(self):\n # Init all at 1\n type_effectiveness_chart = DataFrame({ref_pkmn_type: {pkmn_type: float(1) for pkmn_type in PokemonType}\n for ref_pkmn_type in PokemonType})\n\n # Normal is:\n # ineffective against\n type_effectiveness_chart[PokemonType.Normal][PokemonType.Ghost] = float(0)\n # not very effective against\n type_effectiveness_chart[PokemonType.Normal][PokemonType.Steel] = float(.5)\n type_effectiveness_chart[PokemonType.Normal][PokemonType.Rock] = float(.5)\n\n # Fire is:\n # very effective against\n type_effectiveness_chart[PokemonType.Fire][PokemonType.Steel] = float(2)\n type_effectiveness_chart[PokemonType.Fire][PokemonType.Grass] = float(2)\n type_effectiveness_chart[PokemonType.Fire][PokemonType.Ice] = float(2)\n type_effectiveness_chart[PokemonType.Fire][PokemonType.Bug] = float(2)\n # not very effective against\n type_effectiveness_chart[PokemonType.Fire][PokemonType.Fire] = float(.5)\n type_effectiveness_chart[PokemonType.Fire][PokemonType.Water] = float(.5)\n type_effectiveness_chart[PokemonType.Fire][PokemonType.Rock] = float(.5)\n type_effectiveness_chart[PokemonType.Fire][PokemonType.Dragon] = float(.5)\n\n # Water is:\n # very effective against\n type_effectiveness_chart[PokemonType.Water][PokemonType.Fire] = float(2)\n type_effectiveness_chart[PokemonType.Water][PokemonType.Ground] = float(2)\n type_effectiveness_chart[PokemonType.Water][PokemonType.Rock] = float(2)\n # not very effective against\n type_effectiveness_chart[PokemonType.Water][PokemonType.Water] = float(.5)\n type_effectiveness_chart[PokemonType.Water][PokemonType.Grass] = float(.5)\n type_effectiveness_chart[PokemonType.Water][PokemonType.Dragon] = float(.5)\n\n # Electric is:\n # ineffective against\n type_effectiveness_chart[PokemonType.Electric][PokemonType.Ground] = float(0)\n # very effective against\n type_effectiveness_chart[PokemonType.Electric][PokemonType.Water] = float(2)\n type_effectiveness_chart[PokemonType.Electric][PokemonType.Flying] = float(2)\n # not very effective against\n type_effectiveness_chart[PokemonType.Electric][PokemonType.Electric] = float(.5)\n type_effectiveness_chart[PokemonType.Electric][PokemonType.Grass] = float(.5)\n type_effectiveness_chart[PokemonType.Electric][PokemonType.Dragon] = float(.5)\n\n # Grass is:\n # very effective against\n type_effectiveness_chart[PokemonType.Grass][PokemonType.Water] = float(2)\n type_effectiveness_chart[PokemonType.Grass][PokemonType.Ground] = float(2)\n type_effectiveness_chart[PokemonType.Grass][PokemonType.Rock] = float(2)\n # not very effective against\n type_effectiveness_chart[PokemonType.Grass][PokemonType.Fire] = float(.5)\n type_effectiveness_chart[PokemonType.Grass][PokemonType.Grass] = float(.5)\n type_effectiveness_chart[PokemonType.Grass][PokemonType.Poison] = float(.5)\n type_effectiveness_chart[PokemonType.Grass][PokemonType.Flying] = float(.5)\n type_effectiveness_chart[PokemonType.Grass][PokemonType.Bug] = float(.5)\n type_effectiveness_chart[PokemonType.Grass][PokemonType.Dragon] = float(.5)\n type_effectiveness_chart[PokemonType.Grass][PokemonType.Steel] = float(.5)\n\n # Ice is:\n # very effective against\n type_effectiveness_chart[PokemonType.Ice][PokemonType.Grass] = float(2)\n type_effectiveness_chart[PokemonType.Ice][PokemonType.Ground] = float(2)\n type_effectiveness_chart[PokemonType.Ice][PokemonType.Flying] = float(2)\n type_effectiveness_chart[PokemonType.Ice][PokemonType.Dragon] = float(2)\n # not very effective against\n type_effectiveness_chart[PokemonType.Ice][PokemonType.Fire] = float(.5)\n type_effectiveness_chart[PokemonType.Ice][PokemonType.Water] = float(.5)\n type_effectiveness_chart[PokemonType.Ice][PokemonType.Ice] = float(.5)\n type_effectiveness_chart[PokemonType.Ice][PokemonType.Steel] = float(.5)\n\n # Fighting is:\n # ineffective against\n type_effectiveness_chart[PokemonType.Fighting][PokemonType.Ghost] = float(0)\n # very effective against\n type_effectiveness_chart[PokemonType.Fighting][PokemonType.Normal] = float(2)\n type_effectiveness_chart[PokemonType.Fighting][PokemonType.Ice] = float(2)\n type_effectiveness_chart[PokemonType.Fighting][PokemonType.Rock] = float(2)\n type_effectiveness_chart[PokemonType.Fighting][PokemonType.Dark] = float(2)\n type_effectiveness_chart[PokemonType.Fighting][PokemonType.Steel] = float(2)\n # not very effective against\n type_effectiveness_chart[PokemonType.Fighting][PokemonType.Poison] = float(.5)\n type_effectiveness_chart[PokemonType.Fighting][PokemonType.Flying] = float(.5)\n type_effectiveness_chart[PokemonType.Fighting][PokemonType.Psychic] = float(.5)\n type_effectiveness_chart[PokemonType.Fighting][PokemonType.Bug] = float(.5)\n type_effectiveness_chart[PokemonType.Fighting][PokemonType.Fairy] = float(.5)\n\n # Poison is:\n # ineffective against\n type_effectiveness_chart[PokemonType.Poison][PokemonType.Steel] = float(0)\n # very effective against\n type_effectiveness_chart[PokemonType.Poison][PokemonType.Grass] = float(2)\n type_effectiveness_chart[PokemonType.Poison][PokemonType.Fairy] = float(2)\n # not very effective against\n type_effectiveness_chart[PokemonType.Poison][PokemonType.Poison] = float(.5)\n type_effectiveness_chart[PokemonType.Poison][PokemonType.Ground] = float(.5)\n type_effectiveness_chart[PokemonType.Poison][PokemonType.Rock] = float(.5)\n type_effectiveness_chart[PokemonType.Poison][PokemonType.Ghost] = float(.5)\n\n # Ground is:\n # ineffective against\n type_effectiveness_chart[PokemonType.Ground][PokemonType.Flying] = float(0)\n # very effective against\n type_effectiveness_chart[PokemonType.Ground][PokemonType.Fire] = float(2)\n type_effectiveness_chart[PokemonType.Ground][PokemonType.Electric] = float(2)\n type_effectiveness_chart[PokemonType.Ground][PokemonType.Poison] = float(2)\n type_effectiveness_chart[PokemonType.Ground][PokemonType.Rock] = float(2)\n type_effectiveness_chart[PokemonType.Ground][PokemonType.Steel] = float(2)\n # not very effective against\n type_effectiveness_chart[PokemonType.Ground][PokemonType.Grass] = float(.5)\n type_effectiveness_chart[PokemonType.Ground][PokemonType.Bug] = float(.5)\n\n # Flying is:\n # very effective against\n type_effectiveness_chart[PokemonType.Flying][PokemonType.Grass] = float(2)\n type_effectiveness_chart[PokemonType.Flying][PokemonType.Fighting] = float(2)\n type_effectiveness_chart[PokemonType.Flying][PokemonType.Bug] = float(2)\n # not very effective against\n type_effectiveness_chart[PokemonType.Flying][PokemonType.Electric] = float(.5)\n type_effectiveness_chart[PokemonType.Flying][PokemonType.Rock] = float(.5)\n type_effectiveness_chart[PokemonType.Flying][PokemonType.Steel] = float(.5)\n\n # Psychic is:\n # ineffective against\n type_effectiveness_chart[PokemonType.Psychic][PokemonType.Dark] = float(0)\n # very effective against\n type_effectiveness_chart[PokemonType.Psychic][PokemonType.Poison] = float(2)\n type_effectiveness_chart[PokemonType.Psychic][PokemonType.Fighting] = float(2)\n # not very effective against\n type_effectiveness_chart[PokemonType.Psychic][PokemonType.Psychic] = float(.5)\n type_effectiveness_chart[PokemonType.Psychic][PokemonType.Steel] = float(.5)\n\n # Bug is:\n # very effective against\n type_effectiveness_chart[PokemonType.Bug][PokemonType.Grass] = float(2)\n type_effectiveness_chart[PokemonType.Bug][PokemonType.Psychic] = float(2)\n type_effectiveness_chart[PokemonType.Bug][PokemonType.Dark] = float(2)\n # not very effective against\n type_effectiveness_chart[PokemonType.Bug][PokemonType.Fire] = float(.5)\n type_effectiveness_chart[PokemonType.Bug][PokemonType.Fighting] = float(.5)\n type_effectiveness_chart[PokemonType.Bug][PokemonType.Poison] = float(.5)\n type_effectiveness_chart[PokemonType.Bug][PokemonType.Flying] = float(.5)\n type_effectiveness_chart[PokemonType.Bug][PokemonType.Rock] = float(.5)\n type_effectiveness_chart[PokemonType.Bug][PokemonType.Ghost] = float(.5)\n type_effectiveness_chart[PokemonType.Bug][PokemonType.Steel] = float(.5)\n type_effectiveness_chart[PokemonType.Bug][PokemonType.Fairy] = float(.5)\n\n # Rock is:\n # very effective against\n type_effectiveness_chart[PokemonType.Rock][PokemonType.Fire] = float(2)\n type_effectiveness_chart[PokemonType.Rock][PokemonType.Ice] = float(2)\n type_effectiveness_chart[PokemonType.Rock][PokemonType.Flying] = float(2)\n type_effectiveness_chart[PokemonType.Rock][PokemonType.Bug] = float(2)\n # not very effective against\n type_effectiveness_chart[PokemonType.Rock][PokemonType.Fighting] = float(.5)\n type_effectiveness_chart[PokemonType.Rock][PokemonType.Ground] = float(.5)\n type_effectiveness_chart[PokemonType.Rock][PokemonType.Steel] = float(.5)\n\n # Ghost is:\n # ineffective against\n type_effectiveness_chart[PokemonType.Ghost][PokemonType.Normal] = float(0)\n # very effective against\n type_effectiveness_chart[PokemonType.Ghost][PokemonType.Psychic] = float(2)\n type_effectiveness_chart[PokemonType.Ghost][PokemonType.Ghost] = float(2)\n # not very effective against\n type_effectiveness_chart[PokemonType.Ghost][PokemonType.Dark] = float(.5)\n\n # Dragon is:\n # ineffective against\n type_effectiveness_chart[PokemonType.Dragon][PokemonType.Fairy] = float(0)\n # very effective against\n type_effectiveness_chart[PokemonType.Dragon][PokemonType.Dragon] = float(2)\n # not very effective against\n type_effectiveness_chart[PokemonType.Dragon][PokemonType.Steel] = float(.5)\n\n # Dark is:\n # very effective against\n type_effectiveness_chart[PokemonType.Dark][PokemonType.Psychic] = float(2)\n type_effectiveness_chart[PokemonType.Dark][PokemonType.Ghost] = float(2)\n # not very effective against\n type_effectiveness_chart[PokemonType.Dark][PokemonType.Fighting] = float(.5)\n type_effectiveness_chart[PokemonType.Dark][PokemonType.Dark] = float(.5)\n type_effectiveness_chart[PokemonType.Dark][PokemonType.Fairy] = float(.5)\n\n # Steel is:\n # very effective against\n type_effectiveness_chart[PokemonType.Steel][PokemonType.Ice] = float(2)\n type_effectiveness_chart[PokemonType.Steel][PokemonType.Rock] = float(2)\n type_effectiveness_chart[PokemonType.Steel][PokemonType.Fairy] = float(2)\n # not very effective against\n type_effectiveness_chart[PokemonType.Steel][PokemonType.Fire] = float(.5)\n type_effectiveness_chart[PokemonType.Steel][PokemonType.Water] = float(.5)\n type_effectiveness_chart[PokemonType.Steel][PokemonType.Electric] = float(.5)\n type_effectiveness_chart[PokemonType.Steel][PokemonType.Steel] = float(.5)\n\n # Fairy is:\n # very effective against\n type_effectiveness_chart[PokemonType.Fairy][PokemonType.Fighting] = float(2)\n type_effectiveness_chart[PokemonType.Fairy][PokemonType.Dark] = float(2)\n type_effectiveness_chart[PokemonType.Fairy][PokemonType.Dragon] = float(2)\n # not very effective against\n type_effectiveness_chart[PokemonType.Fairy][PokemonType.Fire] = float(.5)\n type_effectiveness_chart[PokemonType.Fairy][PokemonType.Poison] = float(.5)\n type_effectiveness_chart[PokemonType.Fairy][PokemonType.Steel] = float(.5)\n\n super().__init__(type_effectiveness_chart=type_effectiveness_chart)\n"},{"alpha_fraction":0.5425220131874084,"alphanum_fraction":0.5451287031173706,"avg_line_length":40.47297286987305,"blob_id":"bbbdafe4f3acd16c681e34d7d039daaed72851eb","content_id":"bd3bf742a6db194b679cc20a3143801bf39b5ee8","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":3069,"license_type":"permissive","max_line_length":120,"num_lines":74,"path":"/database/DatabaseConfig.py","repo_name":"LiquidNalee/MiniPkmnShowdown","src_encoding":"UTF-8","text":"from os.path import join, dirname, realpath\nfrom pathlib import Path\nfrom typing import List\nfrom json import dump\nfrom requests import request\nfrom re import sub\n\ndatabase_dir = Path(dirname(realpath(__file__)))\n__pokeApi_url = \"https://pokeapi.co/api/v2/\"\n\n\ndef updatePkmnDatabase(pkmn_list: List):\n for pkmn_name, pkmn_data in getPkmnDatabase(pkmn_list).items():\n print(f\"Uploaded {pkmn_name}.json\")\n with open(join(database_dir, \"pkmn\", f\"{pkmn_name}.json\"), mode='w') as pkmn_data_file:\n dump(pkmn_data, pkmn_data_file)\n\n\ndef getPkmnDatabase(pkmn_list: List[str]) -> {}:\n db = {}\n for pkmn in pkmn_list:\n res = request(\"GET\", f\"{__pokeApi_url}/pokemon/{pkmn}\")\n\n if res.status_code == 200:\n pkmn_json = {\n \"type\": {str(pkmn_type[\"slot\"] - 1): pkmn_type[\"type\"][\"name\"].capitalize()\n for pkmn_type in res.json()[\"types\"]},\n \"base_stats\": {__convertApiStatNameToDbStatName(pkmn_stat[\"stat\"][\"name\"]): pkmn_stat[\"base_stat\"]\n for pkmn_stat in res.json()[\"stats\"]}\n }\n db[res.json()[\"name\"]] = pkmn_json\n return db\n\n\ndef updateMoveDatabase(move_list: List):\n for move_name, move_data in getMoveDatabase(move_list).items():\n print(f\"Uploaded {move_name.lower()}.json\")\n with open(join(database_dir, \"moves\", f\"{move_name.lower()}.json\"), mode='w') as move_data_file:\n dump(move_data, move_data_file)\n\n\ndef getMoveDatabase(move_list: List[str]) -> {}:\n db = {}\n for move in move_list:\n move_url = sub('\\\\s', '-', move.lower())\n res = request(\"GET\", f\"{__pokeApi_url}/move/{move_url}\")\n\n if res.status_code == 200:\n move_json = {\n \"type\": res.json()[\"type\"][\"name\"].capitalize(),\n \"category\": res.json()[\"damage_class\"][\"name\"].capitalize(),\n \"pp\": res.json()[\"pp\"],\n \"power\": res.json()[\"power\"],\n \"accuracy\": res.json()[\"accuracy\"],\n \"priority\": res.json()[\"priority\"],\n \"effect_rate\": res.json()[\"effect_chance\"],\n \"self_stat_mod\": {__convertApiStatNameToDbStatName(pkmn_stat[\"stat\"][\"name\"]): pkmn_stat[\"change\"]\n for pkmn_stat in res.json()[\"stat_changes\"]} if res.json()[\"target\"][\"name\"] == \"user\"\n else {},\n \"trgt_stat_mod\": {__convertApiStatNameToDbStatName(pkmn_stat[\"stat\"][\"name\"]): pkmn_stat[\"change\"]\n for pkmn_stat in res.json()[\"stat_changes\"]} if res.json()[\"target\"][\"name\"] != \"user\"\n else {}\n }\n db[move] = move_json\n return db\n\n\ndef __convertApiStatNameToDbStatName(api_stat: str) -> str:\n return \"atk\" if api_stat == \"attack\" \\\n else \"phys_def\" if api_stat == \"defense\" \\\n else \"spe_atk\" if api_stat == \"special-attack\" \\\n else \"spe_def\" if api_stat == \"special-defense\" \\\n else \"spd\" if api_stat == \"speed\" \\\n else \"hp\"\n"},{"alpha_fraction":0.6633986830711365,"alphanum_fraction":0.6633986830711365,"avg_line_length":37.25,"blob_id":"aa5b9721a95d829d81ef13270225cd7736f9644c","content_id":"e4e12cd6e9461c77cb375bb7da6a9807cc9e9d61","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":612,"license_type":"permissive","max_line_length":92,"num_lines":16,"path":"/models/pkmn/PokemonBaseModel.py","repo_name":"LiquidNalee/MiniPkmnShowdown","src_encoding":"UTF-8","text":"from models.pkmn.stats.StatsDict import StatsDict\nfrom models.pkmn.types.PokemonType import PokemonType, format_types_tuple, type_equals\n\n\nclass PokemonBaseModel:\n\n def __init__(self, name: str, types: (PokemonType, PokemonType), base_stats: StatsDict):\n self.name = name\n self.type = format_types_tuple(types)\n self.base_stats = base_stats\n\n def __eq__(self, other):\n if self.__class__ != other.__class__:\n return NotImplementedError\n return self.name == other.name and type_equals(self.type, other.type) \\\n and self.base_stats == other.base_stats\n"},{"alpha_fraction":0.7446808218955994,"alphanum_fraction":0.7446808218955994,"avg_line_length":30,"blob_id":"6ac61a64f7cef1b3d25d2b29d0e6c52661d7cd27","content_id":"00050388debf012360c916d942911f973b600195","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Shell","length_bytes":94,"license_type":"permissive","max_line_length":72,"num_lines":3,"path":"/run_tests.sh","repo_name":"LiquidNalee/MiniPkmnShowdown","src_encoding":"UTF-8","text":"make build\nmake run\ndocker run -a stdin -a stdout -i -t minishowdown python -m pytest tests/\n\n"},{"alpha_fraction":0.7653429508209229,"alphanum_fraction":0.7689530849456787,"avg_line_length":18.85714340209961,"blob_id":"c24e7384ea2c44628f167ee77fba7b59e038f56e","content_id":"9ecc07e6494676e554e7966d7bf8865f855d8f72","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":277,"license_type":"permissive","max_line_length":70,"num_lines":14,"path":"/README.md","repo_name":"LiquidNalee/MiniPkmnShowdown","src_encoding":"UTF-8","text":"1st time:\n\npython -m minishowdown -p trainer_example.json --update_db True\n\nelse:\n\npython -m minishowdown -p trainer_example.json\n\nfor a tougher battle:\n\npython -m minishowdown -p trainer_example.json -o trainer_example.json\n\n\nFeel free to write your own teams, pkmns and moves"},{"alpha_fraction":0.4875912368297577,"alphanum_fraction":0.5352798104286194,"avg_line_length":36.3636360168457,"blob_id":"03f6035d410e9c49c9c5964a014410220f8c369b","content_id":"b8b0e75c46459ac5a07a847afea0a2ae86318208","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":2055,"license_type":"permissive","max_line_length":116,"num_lines":55,"path":"/tests/database/test_DatabaseInit.py","repo_name":"LiquidNalee/MiniPkmnShowdown","src_encoding":"UTF-8","text":"from unittest import TestCase\n\nfrom database.DatabaseConfig import getPkmnDatabase\n\nfrom models.game.trainer.PokemonTrainer import PokemonTrainer\nfrom models.pkmn.natures.PokemonNature import PokemonNature\nfrom models.pkmn.stats.StatsDict import StatsDict\nfrom models.pkmn.types.PokemonType import PokemonType\n\n\nclass TestDatabaseInit(TestCase):\n\n def test_database_init(self):\n trainer_json = {\n \"name\": \"Red\",\n \"team\": {\n \"0\": {\n \"name\": \"Scizor\",\n \"level\": 100,\n \"nature\": \"Adamant\",\n \"moves\": [\"Bullet Punch\"],\n \"evs\": {\"hp\": 120, \"atk\": 252, \"phys_def\": 0, \"spe_atk\": 0, \"spe_def\": 0, \"spd\": 136},\n \"ivs\": {\"hp\": 31, \"atk\": 31, \"phys_def\": 31, \"spe_atk\": 31, \"spe_def\": 31, \"spd\": 31}\n }\n }\n }\n trainer = PokemonTrainer.fromJson(trainer_json)\n\n assert trainer.name == \"Red\"\n assert trainer.team[1] is None\n assert trainer.team[0].name == \"Scizor\"\n assert trainer.team[0].level == 100\n assert trainer.team[0]._nature == PokemonNature.Adamant\n assert trainer.team[0].moves[0].type == PokemonType.Steel\n assert trainer.team[0].moves[0].power == 40\n assert trainer.team[0].moves[0].accuracy == 100\n assert trainer.team[0].base_stats == StatsDict(hp=70, atk=130, phys_def=100, spe_atk=55, spe_def=80, spd=65)\n assert trainer.team[0].stats == StatsDict(hp=311, atk=394, phys_def=236, spe_atk=131, spe_def=196, spd=200)\n\n def test_database_update(self):\n db = getPkmnDatabase([\"tyranitar\"])\n\n assert \"tyranitar\" in db\n expected_json = {\n \"type\": {\"0\": \"rock\", \"1\": \"dark\"},\n \"base_stats\": {\n \"hp\": 100,\n \"atk\": 134,\n \"phys_def\": 110,\n \"spe_atk\": 95,\n \"spe_def\": 100,\n \"spd\": 61\n }\n }\n assert db[\"tyranitar\"] == expected_json\n"},{"alpha_fraction":0.6279069781303406,"alphanum_fraction":0.6376594305038452,"avg_line_length":45.36521911621094,"blob_id":"7e97dae375103b69683e4c7453dd35282ab2df61","content_id":"4fa09cbfdc2533bfd728b0d882e0440d32b39148","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":5332,"license_type":"permissive","max_line_length":114,"num_lines":115,"path":"/engine/game/BattleEngine.py","repo_name":"LiquidNalee/MiniPkmnShowdown","src_encoding":"UTF-8","text":"from random import randint\n\nfrom engine.game import InputHandler\nfrom engine.game.BattleDisplay import displayPlayers, displayBattleGameState, displayUsedMove, \\\n displaySwitch, displayEndOfBattle\nfrom engine.pkmn.types.TypesBaseRuleSet import TypesBaseRuleSet\nfrom models.game.battle.BattleGameState import BattleGameState\nfrom models.pkmn.PokemonModel import PokemonModel\nfrom models.pkmn.moves.PokemonMove import PokemonMove, MoveCategory\nfrom models.pkmn.stats.StatsDict import StatsDict\n\n\nclass BattleEngine:\n\n def __init__(self, battleGameState: BattleGameState, typesRuleSet: TypesBaseRuleSet):\n self.gameState = battleGameState\n self.typesRuleSet = typesRuleSet\n\n def startGame(self) -> bool:\n displayPlayers(self.gameState)\n # Lead Phase\n player_pkmn_selection = InputHandler.pkmnSelection(self.gameState.player.team)\n self.gameState.setPlayerActivePkmn(player_pkmn_selection)\n\n # Battle Phase\n self.__battlePhase()\n\n win = not self.gameState.player.hasLost()\n displayEndOfBattle(win, self.gameState)\n return win\n\n def __battlePhase(self):\n while not self.gameState.player.hasLost() and not self.gameState.opponent.hasLost():\n # Move Selection Phase\n if self.gameState.getPlayerActivePkmn().isKO():\n self.__switchPlayerPokemon()\n if self.gameState.getOpponentActivePkmn().isKO():\n self.__switchOpponentPokemon()\n\n displayBattleGameState(self.gameState)\n plyr_move, plyr_switch = InputHandler.turnDecision(self.gameState.getPlayerActivePkmn(),\n self.gameState.player.team)\n rand = randint(0, len(self.gameState.getOpponentActivePkmn().moves) - 1)\n opponent_move = self.gameState.getOpponentActivePkmn().moves[rand]\n self.gameState.setTurnState(plyr_move=plyr_move, opponent_move=opponent_move)\n\n if plyr_switch:\n self.__switchPlayerPokemon(plyr_switch)\n\n first, second = self.__getMoveOrder()\n self.__useMove(first[0], first[1], second[0])\n if not second[0].isKO() and second[1] is not None:\n self.__useMove(second[0], second[1], first[0])\n self.gameState.turn += 1\n\n def __useMove(self, caster: PokemonModel, caster_move: PokemonMove, trgt: PokemonModel) \\\n -> bool:\n damage = 0\n type_effectiveness = 1\n if caster_move.category != MoveCategory.Status:\n offensive_stat = caster.stats.atk if caster_move.category == MoveCategory.Physical \\\n else caster.stats.spe_atk\n defensive_stat = trgt.stats.phys_def if caster_move.category == MoveCategory.Physical \\\n else trgt.stats.spe_def\n damage = (((2 * caster.level / 5 + 2) * caster_move.power * offensive_stat / defensive_stat) / 50 + 2)\n type_effectiveness = self.typesRuleSet.getEffectiveness(caster_move.type, trgt.type)\n modifier = (1.5 if caster_move.type == caster.type else 1) \\\n * type_effectiveness \\\n * randint(85, 100) / 100 \\\n * (1 if randint(0, 100) <= caster_move.accuracy else 0)\n damage = int(damage * modifier)\n\n if damage != 0:\n trgt.takeDamage(damage)\n displayUsedMove(caster, caster_move, trgt, type_effectiveness, damage)\n\n if randint(0, 100) <= caster_move.effect_rate:\n for stat_key in StatsDict.__dict__.keys():\n caster.stats[stat_key] *= caster_move.self_stat_mod[stat_key]\n trgt.stats[stat_key] *= caster_move.trgt_stat_mod[stat_key]\n\n return True\n\n def __switchPlayerPokemon(self, selection: int = None):\n out = self.gameState.getPlayerActivePkmn()\n coming_in = self.gameState.setPlayerActivePkmn(InputHandler.pkmnSelection(self.gameState.player.team)) \\\n if selection is None else selection\n displaySwitch(player_name=self.gameState.player.name, out=out, coming_in=coming_in)\n\n def __switchOpponentPokemon(self):\n out = self.gameState.getOpponentActivePkmn()\n coming_in = self.gameState.sendNextOpponentActivePkmn()\n displaySwitch(player_name=self.gameState.opponent.name, out=out, coming_in=coming_in)\n\n def __getMoveOrder(self) -> ((PokemonModel, PokemonMove), (PokemonModel, PokemonMove)):\n move_order = self.gameState.getTurnState()\n (plyr_pkmn, plyr_move), (opponent_pkmn, opponent_move) = move_order\n if plyr_move is None:\n return move_order[1], move_order[0]\n\n if plyr_move.priority == opponent_move.priority:\n if plyr_pkmn.stats.spd == opponent_pkmn.stats.spd:\n if randint(0, 1) == 1:\n move_order = move_order[1], move_order[0]\n else:\n if plyr_pkmn.stats.spd < opponent_pkmn.stats.spd:\n move_order = move_order[1], move_order[0]\n else:\n if plyr_move.priority < opponent_move.priority:\n move_order = move_order[1], move_order[0]\n\n return move_order\n\n def __getActivePkmns(self):\n return self.gameState.getPlayerActivePkmn(), self.gameState.getOpponentActivePkmn()\n"},{"alpha_fraction":0.5573957562446594,"alphanum_fraction":0.5628212690353394,"avg_line_length":42.775001525878906,"blob_id":"9012645dce48f392af14f29a18cff640fb91ea51","content_id":"1e429fd728f1f813e961afc4d1675988cdce736a","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":3506,"license_type":"permissive","max_line_length":111,"num_lines":80,"path":"/models/pkmn/PokemonModel.py","repo_name":"LiquidNalee/MiniPkmnShowdown","src_encoding":"UTF-8","text":"from typing import List\nfrom os.path import join\nfrom json import load\n\nfrom models.pkmn.PokemonBaseModel import PokemonBaseModel\nfrom models.pkmn.stats.StatsDict import StatsDict\nfrom models.pkmn.types.PokemonType import PokemonType\nfrom models.pkmn.natures.PokemonNature import PokemonNature\nfrom models.pkmn.moves.PokemonMove import PokemonMove\n\nfrom database.DatabaseConfig import database_dir\n\n\nclass PokemonModel(PokemonBaseModel):\n\n __bar_len = 50\n\n def __init__(self, name: str, types: (PokemonType, PokemonType), level: int, nature: PokemonNature,\n moves: List[PokemonMove], base_stats: StatsDict, evs: StatsDict, ivs: StatsDict):\n super().__init__(name=name, types=types, base_stats=base_stats)\n self.level = level\n self._nature = nature\n self.moves = moves\n self._evs = evs\n self._ivs = ivs\n self.stats = self.__stats_compute()\n self.max_hp = self.stats.hp\n\n def __str__(self):\n hp_percentage = self.stats.hp / self.max_hp\n ticks = int(hp_percentage * self.__bar_len + .5)\n return f\"{self.name} (lvl.{self.level}):\\n\" \\\n f\"{'█'.join('' for _ in range(ticks))}{'▁'.join('' for _ in range(self.__bar_len - ticks))}\\n\" \\\n f\"{self.stats.hp}/{self.max_hp} ({int(hp_percentage * 100)}%)\"\n\n def moveListAsStr(self) -> str:\n split_lines = [str(move).splitlines() for move in self.moves]\n return \"\\n\".join([\"| |\".join([split_lines[x][y] for x in range(len(split_lines))])\n for y in range(len(split_lines[0]))])\n\n def takeDamage(self, damage: int):\n self.stats.hp -= min(damage, self.stats.hp)\n\n def isKO(self):\n return self.stats.hp == 0\n\n @staticmethod\n def __compute_stat_baseline(level: int, base_stat: int, iv: int, ev: int) -> int:\n return int((2 * base_stat + iv + ev / 4) * level / 100)\n\n def __stats_compute(self) -> StatsDict:\n stat_values = StatsDict(**{\n stat_key:\n self.__compute_stat_baseline(level=self.level, base_stat=self.base_stats.hp,\n iv=self._ivs.hp, ev=self._evs.hp) + self.level + 10\n if stat_key == \"hp\" else\n self.__compute_stat_baseline(level=self.level, base_stat=self.base_stats[stat_key],\n iv=self._ivs[stat_key], ev=self._evs[stat_key]) + 5\n for stat_key in self.base_stats.__dict__.keys()\n })\n self._nature.apply_modifier(stat_values)\n return stat_values\n\n @staticmethod\n def fromJson(json: {}):\n keys = [\"name\", \"level\", \"nature\", \"moves\", \"evs\", \"ivs\"]\n if all(key in json for key in keys):\n with open(join(str(database_dir), \"pkmn\", f\"{json['name'].lower()}.json\")) as pkmn_data_file:\n pkmn_data = load(pkmn_data_file)\n return PokemonModel(\n name=json[\"name\"],\n types=(PokemonType[pkmn_data[\"type\"]['0']],\n PokemonType[pkmn_data[\"type\"]['1']] if 1 in pkmn_data[\"type\"] else None),\n level=int(json[\"level\"]),\n nature=PokemonNature[json[\"nature\"]],\n moves=[PokemonMove.fromDb(move) for move in json[\"moves\"]],\n base_stats=StatsDict(**pkmn_data[\"base_stats\"]),\n evs=StatsDict(**json[\"evs\"]),\n ivs=StatsDict(**json[\"ivs\"])\n )\n"},{"alpha_fraction":0.7233532667160034,"alphanum_fraction":0.7281436920166016,"avg_line_length":45.38888931274414,"blob_id":"604bd5509dacceef377a1be8700e4463a7310828","content_id":"bb88ebce0383ecf88b0064f6f10bff7567f159b3","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":835,"license_type":"permissive","max_line_length":117,"num_lines":18,"path":"/engine/pkmn/types/TypesBaseRuleSet.py","repo_name":"LiquidNalee/MiniPkmnShowdown","src_encoding":"UTF-8","text":"from pandas import DataFrame\nfrom models.pkmn.types.PokemonType import PokemonType\n\n\nclass TypesBaseRuleSet:\n\n # .loc on DataFrame: effectiveness of attack on defense\n # .iloc on DataFrame: effectiveness of defense on attack\n\n def __init__(self, type_effectiveness_chart: DataFrame):\n self.type_effectiveness_chart = type_effectiveness_chart\n\n def __getitem__(self, item: PokemonType) -> (DataFrame, DataFrame):\n return self.type_effectiveness_chart.loc(item), self.type_effectiveness_chart.iloc(item)\n\n def getEffectiveness(self, attack_type: PokemonType, defender_type: (PokemonType, PokemonType)) -> float:\n return self.type_effectiveness_chart[attack_type][defender_type[0]] \\\n * self.type_effectiveness_chart[attack_type][defender_type[1]] if defender_type[1] is not None else 1\n"},{"alpha_fraction":0.746835470199585,"alphanum_fraction":0.746835470199585,"avg_line_length":25.33333396911621,"blob_id":"60f4d48d5de00c627956b2631bed1b714132f04d","content_id":"a5c50dde53326514e1899cc8145ab1086720ce9e","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Shell","length_bytes":79,"license_type":"permissive","max_line_length":58,"num_lines":3,"path":"/run.sh","repo_name":"LiquidNalee/MiniPkmnShowdown","src_encoding":"UTF-8","text":"make build\nmake run\ndocker run -a stdin -a stdout -i -t minishowdown /bin/bash\n"},{"alpha_fraction":0.5025380849838257,"alphanum_fraction":0.5332769155502319,"avg_line_length":39.75862121582031,"blob_id":"f911cbd3e09e6e573aabdcd86a7d86bba2d37eef","content_id":"ff82f110841d97891d07e450cc2a862946c2614f","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":3546,"license_type":"permissive","max_line_length":114,"num_lines":87,"path":"/tests/models/game/trainer/test_PokemonTrainer.py","repo_name":"LiquidNalee/MiniPkmnShowdown","src_encoding":"UTF-8","text":"from unittest import TestCase\n\nfrom models.game.trainer.PokemonTrainer import PokemonTrainer\nfrom models.pkmn.PokemonModel import PokemonModel\nfrom models.pkmn.moves.PokemonMove import PokemonMove, MoveCategory\nfrom models.pkmn.stats.StatsDict import StatsDict\nfrom models.pkmn.types.PokemonType import PokemonType\nfrom models.pkmn.natures.PokemonNature import PokemonNature\nfrom models.game.trainer.utils.ArenaBadge import ArenaBadge\n\n\nclass TestPokemonTrainer(TestCase):\n\n def setUp(self) -> None:\n self.Pikachu = PokemonModel(\n name=\"Pikachu\",\n types=(PokemonType.Electric, None),\n level=100,\n nature=PokemonNature.Jolly,\n moves=[\n PokemonMove(\n name=\"Volt Tackle\",\n move_type=PokemonType.Electric,\n category=MoveCategory.Physical,\n pp=24,\n power=120\n ),\n PokemonMove(\n name=\"Iron Tail\",\n move_type=PokemonType.Steel,\n category=MoveCategory.Physical,\n pp=24,\n power=100,\n accuracy=75\n ),\n PokemonMove(\n name=\"Thunderbolt\",\n move_type=PokemonType.Electric,\n category=MoveCategory.Special,\n pp=24,\n power=90\n )\n ],\n base_stats=StatsDict(hp=35, atk=55, phys_def=40, spe_atk=50, spe_def=50, spd=90),\n evs=StatsDict(hp=0, atk=252, phys_def=0, spe_atk=4, spe_def=0, spd=252),\n ivs=StatsDict(hp=31, atk=31, phys_def=31, spe_atk=31, spe_def=31, spd=31)\n )\n self.Charizard = PokemonModel(\n name=\"Charizard\",\n types=(PokemonType.Fire, PokemonType.Flying),\n level=100,\n nature=PokemonNature.Jolly,\n moves=[\n PokemonMove(\n name=\"Fire Blast\",\n move_type=PokemonType.Fire,\n category=MoveCategory.Special,\n pp=8,\n power=110,\n accuracy=85\n ),\n PokemonMove(\n name=\"Hurricane\",\n move_type=PokemonType.Flying,\n category=MoveCategory.Special,\n pp=16,\n power=110,\n accuracy=70\n )\n ],\n base_stats=StatsDict(hp=78, atk=84, phys_def=78, spe_atk=109, spe_def=85, spd=100),\n evs=StatsDict(hp=0, atk=0, phys_def=0, spe_atk=252, spe_def=4, spd=252),\n ivs=StatsDict(hp=31, atk=31, phys_def=31, spe_atk=31, spe_def=31, spd=31)\n )\n self.Red = PokemonTrainer(\n name=\"Red\",\n team=[self.Pikachu, self.Charizard],\n badges=[ArenaBadge.Boulder, ArenaBadge.Cascade, ArenaBadge.Thunder, ArenaBadge.Rainbow,\n ArenaBadge.Soul, ArenaBadge.Marsh, ArenaBadge.Marsh, ArenaBadge.Earth]\n )\n\n def testPokemonTrainer(self):\n assert self.Red.team[0] == self.Pikachu\n assert self.Red.team[1] == self.Charizard\n assert self.Red.team[2] is None and self.Red.team[5] is None\n assert self.Red.badges == [ArenaBadge.Boulder, ArenaBadge.Cascade, ArenaBadge.Thunder, ArenaBadge.Rainbow,\n ArenaBadge.Soul, ArenaBadge.Marsh, ArenaBadge.Marsh, ArenaBadge.Earth]\n"},{"alpha_fraction":0.4969214200973511,"alphanum_fraction":0.541832685470581,"avg_line_length":40.83333206176758,"blob_id":"3800ad9560142d58301516486fd9b6dde3b697e1","content_id":"b88026726652f9bc3c9130c07f302cbefe4f6c8d","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":2761,"license_type":"permissive","max_line_length":107,"num_lines":66,"path":"/tests/models/pkmn/test_PokemonModel.py","repo_name":"LiquidNalee/MiniPkmnShowdown","src_encoding":"UTF-8","text":"from unittest import TestCase\nfrom models.pkmn.PokemonModel import PokemonModel\nfrom models.pkmn.moves.PokemonMove import PokemonMove, MoveCategory\nfrom models.pkmn.types.PokemonType import PokemonType, type_equals\nfrom models.pkmn.natures.PokemonNature import PokemonNature\nfrom models.pkmn.stats.StatsDict import StatsDict\n\n\nclass TestPokemonModel(TestCase):\n\n def test_pokemon_model(self):\n scizor = PokemonModel(\n name=\"Scizor\",\n types=(PokemonType.Bug, PokemonType.Steel),\n level=100,\n nature=PokemonNature.Adamant,\n moves=[\n PokemonMove(\n name=\"Bullet Punch\",\n move_type=PokemonType.Steel,\n category=MoveCategory.Physical,\n pp=48,\n power=40,\n priority=1\n ),\n PokemonMove(\n name=\"U-Turn\",\n move_type=PokemonType.Bug,\n category=MoveCategory.Physical,\n pp=32,\n power=70\n ),\n PokemonMove(\n name=\"Steel Beam\",\n move_type=PokemonType.Steel,\n category=MoveCategory.Special,\n pp=8,\n power=140,\n accuracy=95\n ),\n PokemonMove(\n name=\"Swords Dance\",\n move_type=PokemonType.Normal,\n category=MoveCategory.Status,\n pp=32,\n effect_rate=100,\n self_stat_mod=StatsDict(atk=2)\n )\n ],\n base_stats=StatsDict(hp=70, atk=130, phys_def=100, spe_atk=55, spe_def=80, spd=65),\n evs=StatsDict(hp=120, atk=252, phys_def=0, spe_atk=0, spe_def=0, spd=136),\n ivs=StatsDict(hp=31, atk=31, phys_def=31, spe_atk=31, spe_def=31, spd=31)\n )\n\n assert scizor.name == \"Scizor\"\n assert type_equals(scizor.type, (PokemonType.Steel, PokemonType.Bug))\n assert scizor.level == 100\n assert scizor._nature == PokemonNature.Adamant\n assert not scizor._nature == PokemonNature.Jolly\n assert scizor.base_stats == StatsDict(hp=70, atk=130, phys_def=100, spe_atk=55, spe_def=80, spd=65)\n assert scizor.base_stats.atk == 130\n assert scizor._evs == StatsDict(hp=120, atk=252, phys_def=0, spe_atk=0, spe_def=0, spd=136)\n assert scizor._ivs == StatsDict(hp=31, atk=31, phys_def=31, spe_atk=31, spe_def=31, spd=31)\n\n expected_stat_values = StatsDict(hp=311, atk=394, phys_def=236, spe_atk=131, spe_def=196, spd=200)\n assert scizor.stats == expected_stat_values\n"},{"alpha_fraction":0.5978332757949829,"alphanum_fraction":0.6360822319984436,"avg_line_length":41.271026611328125,"blob_id":"37435514e7c23d33377737ec64d839fe4b09ea0b","content_id":"18c9af6c1f1a3f6f84b893fbf28a5befe06a7632","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":4523,"license_type":"permissive","max_line_length":108,"num_lines":107,"path":"/tests/models/pkmn/test_PokemonBaseModel.py","repo_name":"LiquidNalee/MiniPkmnShowdown","src_encoding":"UTF-8","text":"from unittest import TestCase\nfrom models.pkmn.PokemonBaseModel import PokemonBaseModel\nfrom models.pkmn.types.PokemonType import PokemonType, type_equals\nfrom models.pkmn.stats.StatsDict import StatsDict\n\n\nclass TestPokemonBaseModel(TestCase):\n\n def test_double_type_pokemon(self):\n scizor = PokemonBaseModel(\n name=\"Scizor\",\n types=(PokemonType.Bug, PokemonType.Steel),\n base_stats=StatsDict(hp=70, atk=130, phys_def=100, spe_atk=55, spe_def=80, spd=65)\n )\n\n assert scizor.name == \"Scizor\"\n assert type_equals(scizor.type, (PokemonType.Bug, PokemonType.Steel))\n assert scizor.base_stats == StatsDict(hp=70, atk=130, phys_def=100, spe_atk=55, spe_def=80, spd=65)\n assert scizor.base_stats.atk == 130\n\n def test_double_type_pokemon_valid_comparison(self):\n scizor = PokemonBaseModel(\n name=\"Scizor\",\n types=(PokemonType.Bug, PokemonType.Steel),\n base_stats=StatsDict(hp=70, atk=130, phys_def=100, spe_atk=55, spe_def=80, spd=65)\n )\n\n definitely_not_scizor = PokemonBaseModel(\n name=\"Scizor\",\n types=(PokemonType.Steel, PokemonType.Bug),\n base_stats=StatsDict(hp=70, atk=130, phys_def=100, spe_atk=55, spe_def=80, spd=65)\n )\n\n assert scizor.name == definitely_not_scizor.name\n assert type_equals(scizor.type, definitely_not_scizor.type)\n assert scizor.base_stats == definitely_not_scizor.base_stats\n assert scizor.base_stats.atk == definitely_not_scizor.base_stats.atk\n assert scizor == definitely_not_scizor\n\n def test_double_type_pokemon_invalid_comparison(self):\n scizor = PokemonBaseModel(\n name=\"Scizor\",\n types=(PokemonType.Bug, PokemonType.Steel),\n base_stats=StatsDict(hp=70, atk=130, phys_def=100, spe_atk=55, spe_def=80, spd=65)\n )\n\n crawdaunt = PokemonBaseModel(\n name=\"Crawdaunt\",\n types=(PokemonType.Water, PokemonType.Dark),\n base_stats=StatsDict(hp=63, atk=130, phys_def=85, spe_atk=90, spe_def=55, spd=55)\n )\n\n assert scizor.name != crawdaunt.name\n assert not type_equals(scizor.type, crawdaunt.type)\n assert scizor.base_stats != crawdaunt.base_stats\n assert scizor.base_stats.atk == crawdaunt.base_stats.atk\n assert scizor != crawdaunt\n\n def test_simple_type_pokemon(self):\n blissey = PokemonBaseModel(\n name=\"Blissey\",\n types=(PokemonType.Normal, None),\n base_stats=StatsDict(hp=255, atk=10, phys_def=10, spe_atk=75, spe_def=135, spd=55)\n )\n\n assert blissey.name == \"Blissey\"\n assert type_equals(blissey.type, (PokemonType.Normal, None))\n assert blissey.base_stats == StatsDict(hp=255, atk=10, phys_def=10, spe_atk=75, spe_def=135, spd=55)\n assert blissey.base_stats.hp == 255\n\n def test_simple_type_pokemon_valid_comparison(self):\n blissey = PokemonBaseModel(\n name=\"Blissey\",\n types=(PokemonType.Normal, None),\n base_stats=StatsDict(hp=255, atk=10, phys_def=10, spe_atk=75, spe_def=135, spd=55)\n )\n\n definitely_not_blissey = PokemonBaseModel(\n name=\"Blissey\",\n types=(None, PokemonType.Normal),\n base_stats=StatsDict(hp=255, atk=10, phys_def=10, spe_atk=75, spe_def=135, spd=55)\n )\n\n assert blissey.name == definitely_not_blissey.name\n assert type_equals(blissey.type, definitely_not_blissey.type)\n assert blissey.base_stats == definitely_not_blissey.base_stats\n assert blissey.base_stats.atk == definitely_not_blissey.base_stats.atk\n assert blissey == definitely_not_blissey\n\n def test_simple_type_pokemon_invalid_comparison(self):\n blissey = PokemonBaseModel(\n name=\"Blissey\",\n types=(PokemonType.Normal, None),\n base_stats=StatsDict(hp=255, atk=10, phys_def=10, spe_atk=75, spe_def=135, spd=55)\n )\n\n barraskewda = PokemonBaseModel(\n name=\"Barraskewda\",\n types=(PokemonType.Water, None),\n base_stats=StatsDict(hp=61, atk=123, phys_def=60, spe_atk=60, spe_def=50, spd=136)\n )\n\n assert blissey.name != barraskewda.name\n assert not type_equals(blissey.type, barraskewda.type)\n assert blissey.base_stats != barraskewda.base_stats\n assert blissey.base_stats.atk != barraskewda.base_stats.atk\n assert blissey != barraskewda\n"},{"alpha_fraction":0.5142965912818909,"alphanum_fraction":0.5432710647583008,"avg_line_length":40.96799850463867,"blob_id":"1a011e917beb88a49cd39fe9430fad2c2e1c0e89","content_id":"afbe8def605979165cb2d74d9f5f358ae73d9cc9","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":5246,"license_type":"permissive","max_line_length":119,"num_lines":125,"path":"/tests/engine/game/test_BattleEngine.py","repo_name":"LiquidNalee/MiniPkmnShowdown","src_encoding":"UTF-8","text":"import builtins\nfrom unittest import TestCase\nimport mock\n\nfrom engine.game import InputHandler\nfrom engine.game.BattleEngine import BattleEngine\nfrom engine.pkmn.types.ClassicTypesRuleSet import ClassicTypesRuleSet\nfrom models.game.battle.BattleGameState import BattleGameState\nfrom models.game.trainer.PokemonTrainer import PokemonTrainer\nfrom models.game.trainer.utils.ArenaBadge import ArenaBadge\nfrom models.pkmn.PokemonModel import PokemonModel\nfrom models.pkmn.moves.PokemonMove import PokemonMove, MoveCategory\nfrom models.pkmn.natures.PokemonNature import PokemonNature\nfrom models.pkmn.stats.StatsDict import StatsDict\nfrom models.pkmn.types.PokemonType import PokemonType\n\n\nclass TestBattleEngine(TestCase):\n\n def setUp(self) -> None:\n self.Pikachu = PokemonModel(\n name=\"Pikachu\",\n types=(PokemonType.Electric, None),\n level=100,\n nature=PokemonNature.Jolly,\n moves=[\n PokemonMove(\n name=\"Volt Tackle\",\n move_type=PokemonType.Electric,\n category=MoveCategory.Physical,\n pp=24,\n power=120\n ),\n PokemonMove(\n name=\"Iron Tail\",\n move_type=PokemonType.Steel,\n category=MoveCategory.Physical,\n pp=24,\n power=100,\n accuracy=75\n ),\n PokemonMove(\n name=\"Thunderbolt\",\n move_type=PokemonType.Electric,\n category=MoveCategory.Special,\n pp=24,\n power=90\n )\n ],\n base_stats=StatsDict(hp=35, atk=55, phys_def=40, spe_atk=50, spe_def=50, spd=90),\n evs=StatsDict(hp=0, atk=252, phys_def=0, spe_atk=4, spe_def=0, spd=252),\n ivs=StatsDict(hp=31, atk=31, phys_def=31, spe_atk=31, spe_def=31, spd=31)\n )\n self.Pidgeot = PokemonModel(\n name=\"Pidgeot\",\n types=(PokemonType.Flying, PokemonType.Normal),\n level=100,\n nature=PokemonNature.Jolly,\n moves=[\n PokemonMove(\n name=\"Double Edge\",\n move_type=PokemonType.Normal,\n category=MoveCategory.Physical,\n pp=24,\n power=120\n ),\n PokemonMove(\n name=\"Brave Bird\",\n move_type=PokemonType.Flying,\n category=MoveCategory.Physical,\n pp=24,\n power=120\n )\n ],\n base_stats=StatsDict(hp=83, atk=80, phys_def=75, spe_atk=70, spe_def=70, spd=101),\n evs=StatsDict(hp=0, atk=252, phys_def=0, spe_atk=0, spe_def=4, spd=252),\n ivs=StatsDict(hp=31, atk=31, phys_def=31, spe_atk=31, spe_def=31, spd=31)\n )\n self.Blastoise = PokemonModel(\n name=\"Blastoise\",\n types=(PokemonType.Water, None),\n level=100,\n nature=PokemonNature.Modest,\n moves=[\n PokemonMove(\n name=\"Hydro Pump\",\n move_type=PokemonType.Water,\n category=MoveCategory.Special,\n pp=8,\n power=110,\n accuracy=80\n ),\n PokemonMove(\n name=\"Ice Beam\",\n move_type=PokemonType.Ice,\n category=MoveCategory.Special,\n pp=16,\n power=90\n )\n ],\n base_stats=StatsDict(hp=79, atk=83, phys_def=100, spe_atk=85, spe_def=105, spd=78),\n evs=StatsDict(hp=252, atk=0, phys_def=0, spe_atk=252, spe_def=4, spd=0),\n ivs=StatsDict(hp=31, atk=31, phys_def=31, spe_atk=31, spe_def=31, spd=31)\n )\n self.Red = PokemonTrainer(\n name=\"Red\",\n team=[self.Pikachu],\n badges=[ArenaBadge.Boulder, ArenaBadge.Cascade, ArenaBadge.Thunder, ArenaBadge.Rainbow,\n ArenaBadge.Soul, ArenaBadge.Marsh, ArenaBadge.Marsh, ArenaBadge.Earth]\n )\n self.Blue = PokemonTrainer(\n name=\"Blue\",\n team=[self.Pidgeot, self.Blastoise],\n badges=[ArenaBadge.Boulder, ArenaBadge.Cascade, ArenaBadge.Thunder, ArenaBadge.Rainbow,\n ArenaBadge.Soul, ArenaBadge.Marsh, ArenaBadge.Marsh, ArenaBadge.Earth]\n )\n self.BattleGameState = BattleGameState(player=self.Red, opponent=self.Blue)\n\n def test_red_blue_battle(self):\n with mock.patch.object(InputHandler, 'getCancelableNumberInput', return_value=0):\n with mock.patch.object(InputHandler, 'getNumberInput', return_value=0):\n with mock.patch.object(InputHandler, 'getDecisionType', return_value='m'):\n with mock.patch.object(builtins, 'input', return_value=''):\n engine = BattleEngine(battleGameState=self.BattleGameState, typesRuleSet=ClassicTypesRuleSet())\n assert not engine.startGame()\n"},{"alpha_fraction":0.5457690358161926,"alphanum_fraction":0.5751765966415405,"avg_line_length":37.97190856933594,"blob_id":"f8f45e1e151f7b12d136629e7ba7b33ce6b2320b","content_id":"2ff07a9a51b2b151e410045e5b43264302815449","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":6937,"license_type":"permissive","max_line_length":118,"num_lines":178,"path":"/miniShowdown.py","repo_name":"LiquidNalee/MiniPkmnShowdown","src_encoding":"UTF-8","text":"from argparse import ArgumentParser\nfrom json import load\n\nfrom database.DatabaseConfig import updatePkmnDatabase, updateMoveDatabase\n\nfrom engine.game.BattleEngine import BattleEngine\nfrom engine.pkmn.types.ClassicTypesRuleSet import ClassicTypesRuleSet\nfrom models.game.battle.BattleGameState import BattleGameState\nfrom models.game.trainer.PokemonTrainer import PokemonTrainer\nfrom models.game.trainer.utils.ArenaBadge import ArenaBadge\nfrom models.pkmn.PokemonModel import PokemonModel\nfrom models.pkmn.moves.PokemonMove import PokemonMove, MoveCategory\nfrom models.pkmn.natures.PokemonNature import PokemonNature\nfrom models.pkmn.stats.StatsDict import StatsDict\nfrom models.pkmn.types.PokemonType import PokemonType\n\nparser = ArgumentParser()\nparser.add_argument(\"--update_db\", \"-u\", help=\"Fill out Pkmn info as json in database folder for future use\",\n type=bool, required=False)\nparser.add_argument(\"--player_trainer_json\", \"-p\", help=\"Path to player's pokemon trainer json\",\n type=str, required=False)\nparser.add_argument(\"--opponent_trainer_json\", \"-o\", help=\"Path to opponent's pokemon trainer json\",\n type=str, required=False)\nargs = parser.parse_args()\n\n\ndef setUpDefaultTeams():\n pikachu = PokemonModel(\n name=\"Pikachu\",\n types=(PokemonType.Electric, None),\n level=100,\n nature=PokemonNature.Jolly,\n moves=[\n PokemonMove(\n name=\"Volt Tackle\",\n move_type=PokemonType.Electric,\n category=MoveCategory.Physical,\n pp=24,\n power=120\n ),\n PokemonMove(\n name=\"Iron Tail\",\n move_type=PokemonType.Steel,\n category=MoveCategory.Physical,\n pp=24,\n power=100,\n accuracy=75\n ),\n PokemonMove(\n name=\"Thunderbolt\",\n move_type=PokemonType.Electric,\n category=MoveCategory.Special,\n pp=24,\n power=90\n )\n ],\n base_stats=StatsDict(hp=35, atk=55, phys_def=40, spe_atk=50, spe_def=50, spd=90),\n evs=StatsDict(hp=0, atk=252, phys_def=0, spe_atk=4, spe_def=0, spd=252),\n ivs=StatsDict(hp=31, atk=31, phys_def=31, spe_atk=31, spe_def=31, spd=31)\n )\n charizard = PokemonModel(\n name=\"Charizard\",\n types=(PokemonType.Fire, PokemonType.Flying),\n level=100,\n nature=PokemonNature.Jolly,\n moves=[\n PokemonMove(\n name=\"Fire Blast\",\n move_type=PokemonType.Fire,\n category=MoveCategory.Special,\n pp=8,\n power=110,\n accuracy=85\n ),\n PokemonMove(\n name=\"Hurricane\",\n move_type=PokemonType.Flying,\n category=MoveCategory.Special,\n pp=16,\n power=110,\n accuracy=70\n )\n ],\n base_stats=StatsDict(hp=78, atk=84, phys_def=78, spe_atk=109, spe_def=85, spd=100),\n evs=StatsDict(hp=0, atk=0, phys_def=0, spe_atk=252, spe_def=4, spd=252),\n ivs=StatsDict(hp=31, atk=31, phys_def=31, spe_atk=31, spe_def=31, spd=31)\n )\n pidgeot = PokemonModel(\n name=\"Pidgeot\",\n types=(PokemonType.Flying, PokemonType.Normal),\n level=100,\n nature=PokemonNature.Jolly,\n moves=[\n PokemonMove(\n name=\"Double Edge\",\n move_type=PokemonType.Normal,\n category=MoveCategory.Physical,\n pp=24,\n power=120\n ),\n PokemonMove(\n name=\"Brave Bird\",\n move_type=PokemonType.Flying,\n category=MoveCategory.Physical,\n pp=24,\n power=120\n )\n ],\n base_stats=StatsDict(hp=83, atk=80, phys_def=75, spe_atk=70, spe_def=70, spd=101),\n evs=StatsDict(hp=0, atk=252, phys_def=0, spe_atk=0, spe_def=4, spd=252),\n ivs=StatsDict(hp=31, atk=31, phys_def=31, spe_atk=31, spe_def=31, spd=31)\n )\n blastoise = PokemonModel(\n name=\"Blastoise\",\n types=(PokemonType.Water, None),\n level=100,\n nature=PokemonNature.Modest,\n moves=[\n PokemonMove(\n name=\"Hydro Pump\",\n move_type=PokemonType.Water,\n category=MoveCategory.Special,\n pp=8,\n power=110,\n accuracy=80\n ),\n PokemonMove(\n name=\"Ice Beam\",\n move_type=PokemonType.Ice,\n category=MoveCategory.Special,\n pp=16,\n power=90\n )\n ],\n base_stats=StatsDict(hp=79, atk=83, phys_def=100, spe_atk=85, spe_def=105, spd=78),\n evs=StatsDict(hp=252, atk=0, phys_def=0, spe_atk=252, spe_def=4, spd=0),\n ivs=StatsDict(hp=31, atk=31, phys_def=31, spe_atk=31, spe_def=31, spd=31)\n )\n red = PokemonTrainer(\n name=\"Red\",\n team=[pikachu, charizard],\n badges=[ArenaBadge.Boulder, ArenaBadge.Cascade, ArenaBadge.Thunder, ArenaBadge.Rainbow,\n ArenaBadge.Soul, ArenaBadge.Marsh, ArenaBadge.Marsh, ArenaBadge.Earth]\n )\n blue = PokemonTrainer(\n name=\"Blue\",\n team=[pidgeot, blastoise],\n badges=[ArenaBadge.Boulder, ArenaBadge.Cascade, ArenaBadge.Thunder, ArenaBadge.Rainbow,\n ArenaBadge.Soul, ArenaBadge.Marsh, ArenaBadge.Marsh, ArenaBadge.Earth]\n )\n return red, blue\n\n\ndef main():\n if args.update_db:\n updatePkmnDatabase([str(_) for _ in range(10)])\n updateMoveDatabase([\"Swords Dance\", \"Meteor Mash\", \"Close Combat\", \"Mach Punch\", \"Aura Sphere\", \"Bug Bite\",\n \"Hydro Pump\", \"Surf\", \"Waterfall\", \"Moonblast\", \"Play Rough\", \"Solar Beam\", \"Wood Hammer\",\n \"Stone Edge\", \"Meteor Gem\", \"Sludge Bomb\", \"Poison Jab\", \"Draco Meteor\", \"Outrage\",\n \"Dragon Dance\", \"Psychic\", \"Zen Headbutt\", \"Mystical Fire\", \"Fire Blast\", \"Flare Blitz\",\n \"Hurricane\", \"Brave Bird\", \"Earthquake\", \"Earth Power\"])\n\n player, opponent = setUpDefaultTeams()\n\n if args.player_trainer_json:\n with open(args.player_trainer_json) as player_trainer_json_file:\n player = PokemonTrainer.fromJson(load(player_trainer_json_file))\n if args.opponent_trainer_json:\n with open(args.opponent_trainer_json) as opponent_trainer_json_file:\n opponent = PokemonTrainer.fromJson(load(opponent_trainer_json_file))\n\n engine = BattleEngine(battleGameState=BattleGameState(player=player, opponent=opponent),\n typesRuleSet=ClassicTypesRuleSet())\n engine.startGame()\n\n\nif __name__ == \"__main__\":\n main()\n"},{"alpha_fraction":0.5387858152389526,"alphanum_fraction":0.5716694593429565,"avg_line_length":24.23404312133789,"blob_id":"7650a23911a77fc3e477c36157928db60618e627","content_id":"343f5a4bf2e820b398e2200103635d6acb678983","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1186,"license_type":"permissive","max_line_length":106,"num_lines":47,"path":"/models/pkmn/types/PokemonType.py","repo_name":"LiquidNalee/MiniPkmnShowdown","src_encoding":"UTF-8","text":"from enum import Enum\nfrom re import sub\n\n\nclass PokemonType(Enum):\n Normal = 1\n Fighting = 2\n Flying = 3\n Poison = 4\n Ground = 5\n Rock = 6\n Bug = 7\n Ghost = 8\n Psychic = 9\n Grass = 10\n Fire = 11\n Water = 12\n Electric = 13\n Ice = 14\n Dragon = 15\n Steel = 16\n Dark = 17\n Fairy = 18\n\n def __lt__(self, other):\n if self.__class__ != other.__class__:\n return NotImplementedError\n return self.value < other.value\n\n def __str__(self):\n return sub(\"PokemonType\\\\.\", \"\", super().__str__())\n\n\ndef format_types_tuple(types: (PokemonType, PokemonType)):\n if types[0] is None:\n if types[1] is None:\n raise Exception(\"PokemonBaseModel - init: Unhandled type (None; None)\")\n else:\n return types[1], None\n else:\n if types[0] == types[1]:\n raise Exception(f\"PokemonBaseModel - init: Unhandled type ({str(types[0])}; {str(types[1])})\")\n return types if types[1] is None or types[0] < types[1] else (types[1], types[0])\n\n\ndef type_equals(self, other: (PokemonType, PokemonType)):\n return format_types_tuple(self) == format_types_tuple(other)\n"},{"alpha_fraction":0.6798893213272095,"alphanum_fraction":0.6881918907165527,"avg_line_length":37.71428680419922,"blob_id":"d3ffcb376c94525d59eb73a4840fa904c2c46a14","content_id":"8d202128c06a12dfc60c761811fd0a24f9121a0c","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":2168,"license_type":"permissive","max_line_length":113,"num_lines":56,"path":"/engine/game/BattleDisplay.py","repo_name":"LiquidNalee/MiniPkmnShowdown","src_encoding":"UTF-8","text":"from re import sub, M\nfrom models.game.battle.BattleGameState import BattleGameState\nfrom models.pkmn.PokemonModel import PokemonModel\nfrom models.pkmn.moves.PokemonMove import PokemonMove\n\n__separation_line = '-'.join('' for _ in range(150))\n\n\ndef __shiftDisplayBox(box: str, shift: int):\n return sub(\"^\", \"\\t\".join(\"\" for _ in range(shift)), box, flags=M)\n\n\ndef __displaySideBySide(box_1: str, box_2: str):\n split_lines = (box_1.splitlines(), box_2.splitlines())\n print(\"\\n\".join([f\"{split_lines[0][_]:<50}{split_lines[1][_]:>50}\" for _ in range(len(split_lines[0]))]))\n\n\ndef displayPlayers(battleGameState: BattleGameState):\n __displaySideBySide(str(battleGameState.player), str(battleGameState.opponent))\n\n\ndef displayBattleGameState(battleGameState: BattleGameState):\n displayPlayers(battleGameState)\n print(f\"Turn: {battleGameState.turn}\\n\")\n __displaySideBySide(str(battleGameState.getPlayerActivePkmn()), str(battleGameState.getOpponentActivePkmn()))\n print(f\"{__separation_line}\")\n print(battleGameState.getPlayerActivePkmn().moveListAsStr())\n print(f\"{__separation_line}\")\n\n\ndef displayUsedMove(caster: PokemonModel, caster_move: PokemonMove, trgt: PokemonModel,\n type_effectiveness: float, damage: int):\n print(f\"{caster.name} uses {caster_move.name}\")\n if type_effectiveness != 1:\n print(\"It's super effective!\" if type_effectiveness > 1\n else f\"It doesn't affect {trgt.name}\" if type_effectiveness == 0\n else \"It's not very effective...\")\n if damage != 0:\n print(f\"{trgt.name} loses {damage} HP\")\n if trgt.isKO():\n print(f\"{trgt.name} is K.O !\")\n input()\n\n\ndef displaySwitch(player_name: str, out: PokemonModel, coming_in: PokemonModel):\n print(f\"{out.name} goes back into its PokeBall.\")\n print(f\"{player_name} sends {coming_in.name} out !\")\n input()\n\n\ndef displayEndOfBattle(win: bool, battleGameState: BattleGameState):\n print(\"# Finished #\")\n displayPlayers(battleGameState)\n print(f\"Winner: {battleGameState.player.name if win else battleGameState.opponent.name}\")\n print(f\"{'-'.join(__separation_line)}\")\n input()\n"},{"alpha_fraction":0.6985074877738953,"alphanum_fraction":0.7008955478668213,"avg_line_length":39.85365676879883,"blob_id":"438e0de04a4cd506c9b73a3bb09b9af06e069f68","content_id":"07b0a88620977d804617a27caf0dbc68f04679e6","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1675,"license_type":"permissive","max_line_length":79,"num_lines":41,"path":"/models/game/battle/BattleGameState.py","repo_name":"LiquidNalee/MiniPkmnShowdown","src_encoding":"UTF-8","text":"from models.game.trainer.PokemonTrainer import PokemonTrainer\nfrom models.pkmn.PokemonModel import PokemonModel\nfrom models.pkmn.moves.PokemonMove import PokemonMove\n\n\nclass BattleGameState:\n\n def __init__(self, player: PokemonTrainer, opponent: PokemonTrainer):\n self.turn = 1\n self.player = player.makeCopy()\n self.__player_active_pkmn_slot = 0\n self.player_move_selection = None\n self.opponent = opponent.makeCopy()\n self.opponent_move_selection = None\n self.__opponent_active_pkmn_slot = 0\n\n def getPlayerActivePkmn(self) -> PokemonModel:\n return self.player.team[self.__player_active_pkmn_slot]\n\n def setPlayerActivePkmn(self, index: int) -> PokemonModel:\n self.__player_active_pkmn_slot = index\n return self.player.team[self.__player_active_pkmn_slot]\n\n def getOpponentActivePkmn(self) -> PokemonModel:\n return self.opponent.team[self.__opponent_active_pkmn_slot]\n\n def setOpponentActivePkmn(self, index: int) -> PokemonModel:\n self.__opponent_active_pkmn_slot = index\n return self.opponent.team[self.__opponent_active_pkmn_slot]\n\n def sendNextOpponentActivePkmn(self) -> PokemonModel:\n self.__opponent_active_pkmn_slot += 1\n return self.opponent.team[self.__opponent_active_pkmn_slot]\n\n def getTurnState(self):\n return (self.getPlayerActivePkmn(), self.player_move_selection),\\\n (self.getOpponentActivePkmn(), self.opponent_move_selection)\n\n def setTurnState(self, plyr_move: PokemonMove, opponent_move: PokemonMove):\n self.player_move_selection = plyr_move\n self.opponent_move_selection = opponent_move\n"},{"alpha_fraction":0.5681179761886597,"alphanum_fraction":0.5730336904525757,"avg_line_length":37.486488342285156,"blob_id":"c6787e6d18561174603430d8f5be3cdee7ae0515","content_id":"b059d225782a761fe809c888cc8d5da86be95347","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1424,"license_type":"permissive","max_line_length":100,"num_lines":37,"path":"/models/game/trainer/PokemonTrainer.py","repo_name":"LiquidNalee/MiniPkmnShowdown","src_encoding":"UTF-8","text":"from typing import List\nfrom models.game.trainer.utils.ArenaBadge import ArenaBadge\n\nfrom models.pkmn.PokemonModel import PokemonModel\n\n\nclass PokemonTrainer:\n\n def __init__(self, name: str, team: List[PokemonModel], badges: List[ArenaBadge]):\n self.name = name\n self.team = [team[i] if i < len(team) else None for i in range(6)]\n self.badges = list(badges)\n self.badges.sort()\n\n def __str__(self):\n team_str_list = [f\"{x}. {self.team[x].name} ({self.team[x].stats.hp}/{self.team[x].max_hp})\"\n for x in range(len(self.team)) if self.team[x] is not None]\n return f\"Trainer: {self.name}\\n\" \\\n f\"{' - '.join(team_str_list[0:2])}\\n\" \\\n f\"{' - '.join(team_str_list[2:4])}\\n\" \\\n f\"{' - '.join(team_str_list[4:6])}\\n\"\n\n def hasLost(self):\n return all(pkmn.isKO() if pkmn is not None else True for pkmn in self.team)\n\n def makeCopy(self):\n return PokemonTrainer(name=self.name, team=list(self.team), badges=list(self.badges))\n\n @staticmethod\n def fromJson(json: {}):\n if \"name\" in json and \"team\" in json:\n return PokemonTrainer(\n name=json[\"name\"],\n team=[PokemonModel.fromJson(json[\"team\"][_]) for _ in json[\"team\"]],\n badges=[]\n )\n raise AttributeError(\"PokemonTrainer - fromJson: Invalid JSON Input\")\n"},{"alpha_fraction":0.729411780834198,"alphanum_fraction":0.7326797246932983,"avg_line_length":49.16393280029297,"blob_id":"0d3fd58d8049f1cb8f7db401db8a97237491bf3b","content_id":"8876830097963204fb93a583be0a14fa2161bbdb","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":3060,"license_type":"permissive","max_line_length":116,"num_lines":61,"path":"/models/pkmn/natures/PokemonNature.py","repo_name":"LiquidNalee/MiniPkmnShowdown","src_encoding":"UTF-8","text":"from enum import Enum\n\nfrom models.pkmn.stats.StatsDict import StatsDict\n\n\n# Bonus/Malus percentage from natures\nnature_base_modifier = 100\nnature_bonus = 10\nnature_bonus_modifier = nature_base_modifier + nature_bonus\nnature_malus = 10\nnature_malus_modifier = nature_base_modifier - nature_malus\n\n\nclass _PokemonNatureImplm:\n\n def __init__(self, hp: int = nature_base_modifier,\n atk: int = nature_base_modifier, phys_def: int = nature_base_modifier,\n spe_atk: int = nature_base_modifier, spe_def: int = nature_base_modifier,\n spd: int = nature_base_modifier):\n super().__init__()\n self.__stats_table = StatsDict(hp=hp, atk=atk, phys_def=phys_def, spe_atk=spe_atk, spe_def=spe_def, spd=spd)\n\n def apply_modifier(self, stats: StatsDict):\n for stat_key in self.__stats_table.__dict__.keys():\n stats[stat_key] *= self.__stats_table[stat_key] / 100\n\n\nclass PokemonNature(Enum):\n Lonely = _PokemonNatureImplm(atk=nature_bonus_modifier, phys_def=nature_malus_modifier)\n Adamant = _PokemonNatureImplm(atk=nature_bonus_modifier, spe_atk=nature_malus_modifier)\n Naughty = _PokemonNatureImplm(atk=nature_bonus_modifier, spe_def=nature_malus_modifier)\n Brave = _PokemonNatureImplm(atk=nature_bonus_modifier, spd=nature_malus_modifier)\n\n Bold = _PokemonNatureImplm(phys_def=nature_bonus_modifier, atk=nature_malus_modifier)\n Impish = _PokemonNatureImplm(phys_def=nature_bonus_modifier, spe_atk=nature_malus_modifier)\n Lax = _PokemonNatureImplm(phys_def=nature_bonus_modifier, spe_def=nature_malus_modifier)\n Relaxed = _PokemonNatureImplm(phys_def=nature_bonus_modifier, spd=nature_malus_modifier)\n\n Modest = _PokemonNatureImplm(spe_atk=nature_bonus_modifier, atk=nature_malus_modifier)\n Mild = _PokemonNatureImplm(spe_atk=nature_bonus_modifier, phys_def=nature_malus_modifier)\n Rash = _PokemonNatureImplm(spe_atk=nature_bonus_modifier, spe_def=nature_malus_modifier)\n Quiet = _PokemonNatureImplm(spe_atk=nature_bonus_modifier, spd=nature_malus_modifier)\n\n Calm = _PokemonNatureImplm(spe_def=nature_bonus_modifier, atk=nature_malus_modifier)\n Gentle = _PokemonNatureImplm(spe_def=nature_bonus_modifier, phys_def=nature_malus_modifier)\n Careful = _PokemonNatureImplm(spe_def=nature_bonus_modifier, spe_atk=nature_malus_modifier)\n Sassy = _PokemonNatureImplm(spe_def=nature_bonus_modifier, spd=nature_malus_modifier)\n\n Timid = _PokemonNatureImplm(spd=nature_bonus_modifier, atk=nature_malus_modifier)\n Hasty = _PokemonNatureImplm(spd=nature_bonus_modifier, phys_def=nature_malus_modifier)\n Jolly = _PokemonNatureImplm(spd=nature_bonus_modifier, spe_atk=nature_malus_modifier)\n Naive = _PokemonNatureImplm(spd=nature_bonus_modifier, spe_def=nature_malus_modifier)\n\n Quirky = _PokemonNatureImplm()\n Docile = _PokemonNatureImplm()\n Hardy = _PokemonNatureImplm()\n Bashful = _PokemonNatureImplm()\n Serious = _PokemonNatureImplm()\n\n def apply_modifier(self, stats: StatsDict):\n self.value.apply_modifier(stats)\n"},{"alpha_fraction":0.5120481848716736,"alphanum_fraction":0.5192770957946777,"avg_line_length":30.846153259277344,"blob_id":"2a4f7584fe78e81fd9259bbf384f37c024681e68","content_id":"374f8123a9618f449dc0ea8805621fc614597310","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":830,"license_type":"permissive","max_line_length":119,"num_lines":26,"path":"/models/pkmn/stats/StatsDict.py","repo_name":"LiquidNalee/MiniPkmnShowdown","src_encoding":"UTF-8","text":"\n\nclass StatsDict:\n\n def __init__(self, hp: int = 0, atk: int = 0, phys_def: int = 0, spe_atk: int = 0, spe_def: int = 0, spd: int = 0):\n self.hp = int(hp)\n self.atk = int(atk)\n self.phys_def = int(phys_def)\n self.spe_atk = int(spe_atk)\n self.spe_def = int(spe_def)\n self.spd = int(spd)\n\n def __eq__(self, other):\n if self.__class__ != other.__class__:\n return NotImplementedError\n return self.__dict__ == other.__dict__\n\n def __getitem__(self, item: str):\n return self.__dict__[item]\n\n def __setitem__(self, key, value):\n self.__dict__[key] = int(value)\n\n @classmethod\n def from_json(cls, json: {}):\n keys = cls.__dict__.keys()\n if all(keys) in json:\n return StatsDict(**{key: json[key] for key in keys})\n"},{"alpha_fraction":0.4727272689342499,"alphanum_fraction":0.6818181872367859,"avg_line_length":14.857142448425293,"blob_id":"e233bf4b74f01ad24a13050b2ac86b580e7781ab","content_id":"522033f22f21144dcc803b82caa609f241df7f18","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Text","length_bytes":110,"license_type":"permissive","max_line_length":22,"num_lines":7,"path":"/requirements.txt","repo_name":"LiquidNalee/MiniPkmnShowdown","src_encoding":"UTF-8","text":"pandas==1.0.3\nnumpy==1.18.2\npython-dateutil==2.8.1\nmock~=4.0.3\npathlib~=1.0.1\nrequests~=2.23.0\nargparse~=1.4.0"},{"alpha_fraction":0.5749621391296387,"alphanum_fraction":0.5790005326271057,"avg_line_length":27.299999237060547,"blob_id":"10099c5e6d66dbc75e0e549ee8d44af52f0079b9","content_id":"6ccdb14e244394ced4c7200587cf044f4b8a7c3d","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1981,"license_type":"permissive","max_line_length":92,"num_lines":70,"path":"/engine/game/InputHandler.py","repo_name":"LiquidNalee/MiniPkmnShowdown","src_encoding":"UTF-8","text":"from typing import List\n\nfrom models.pkmn.PokemonModel import PokemonModel\nfrom models.pkmn.moves.PokemonMove import PokemonMove\n\n\ndef repeatOnError(*exceptions):\n def checking(function):\n def checked(*args, **kwargs):\n while True:\n try:\n result = function(*args, **kwargs)\n except exceptions as ex:\n print(\"Invalid Input!\")\n else:\n return result\n\n return checked\n\n return checking\n\n\n@repeatOnError(NotImplementedError)\ndef getDecisionType():\n i = input(\"Enter 'm' to use a move or 's' to switch out: \")\n if i != \"m\" and i != \"s\":\n raise NotImplementedError()\n return i\n\n\n@repeatOnError(ValueError)\ndef getNumberInput(max_range: int):\n i = input(f'Enter your selection (0 - {max_range - 1}): ')\n val = int(i)\n if val < 0 or val >= max_range:\n raise ValueError\n return val\n\n\n@repeatOnError(ValueError)\ndef getCancelableNumberInput(max_range: int):\n i = input(f'Enter your selection (0 - {max_range - 1}) or Cancel (C): ')\n if i == \"C\":\n return -1\n val = int(i)\n if val < 0 or val >= max_range:\n raise ValueError\n return val\n\n\ndef pkmnSelection(team: List[PokemonModel]) -> int:\n print(\"\\nChoose a Pkmn.\")\n while True:\n i = getNumberInput(len([_ for _ in team if _ is not None]))\n if team[i].isKO():\n print(f\"{team[i].name} is K.O ! It cannot fight anymore...\")\n else:\n break\n return i\n\n\ndef turnDecision(active_pkmn: PokemonModel, team: List[PokemonModel]) -> (PokemonMove, int):\n while True:\n t = getDecisionType()\n max_range = len([_ for _ in active_pkmn.moves if _ is not None]) if t == \"m\" \\\n else len([_ for _ in team if _ is not None])\n i = getCancelableNumberInput(max_range=max_range)\n if i != -1:\n break\n return (active_pkmn.moves[i], None) if t == \"m\" else (None, i)\n"},{"alpha_fraction":0.5261538624763489,"alphanum_fraction":0.5507692098617554,"avg_line_length":18.058822631835938,"blob_id":"30918d05131bed246946bdd41a9591e10729e937","content_id":"ae4df15d8b072d29429511e89eff6003beb102af","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":325,"license_type":"permissive","max_line_length":45,"num_lines":17,"path":"/models/game/trainer/utils/ArenaBadge.py","repo_name":"LiquidNalee/MiniPkmnShowdown","src_encoding":"UTF-8","text":"from enum import Enum\n\n\nclass ArenaBadge(Enum):\n Boulder = 1\n Cascade = 2\n Thunder = 3\n Rainbow = 4\n Soul = 5\n Marsh = 6\n Volcano = 7\n Earth = 8\n\n def __lt__(self, other):\n if self.__class__ != other.__class__:\n return NotImplementedError\n return self.value < other.value\n\n"}],"string":"[\n {\n \"alpha_fraction\": 0.5402510166168213,\n \"alphanum_fraction\": 0.5512703061103821,\n \"avg_line_length\": 47.04411697387695,\n \"blob_id\": \"4d9d411e31e91cdb6db2f0a89436e44ee82e0cb7\",\n \"content_id\": \"dfc0e92419f727f075b6071763436d6991f687c1\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 3267,\n \"license_type\": \"permissive\",\n \"max_line_length\": 168,\n \"num_lines\": 68,\n \"path\": \"/models/pkmn/moves/PokemonMove.py\",\n \"repo_name\": \"LiquidNalee/MiniPkmnShowdown\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from enum import Enum\\nfrom os.path import join\\nfrom json import load\\n\\nfrom models.pkmn.types.PokemonType import PokemonType\\nfrom models.pkmn.stats.StatsDict import StatsDict\\n\\nfrom database.DatabaseConfig import database_dir\\n\\n\\nclass MoveCategory(Enum):\\n Physical = \\\"[Ph]\\\"\\n Special = \\\"[Sp]\\\"\\n Status = \\\"[St]\\\"\\n\\n\\nclass PokemonMove:\\n\\n def __init__(self, name: str, move_type: PokemonType, category: MoveCategory, pp: int,\\n power: int = 0, accuracy: int = 100, priority: int = 0, effect_rate: int = 0,\\n self_stat_mod: StatsDict = None, trgt_stat_mod: StatsDict = None):\\n self.name = name\\n self.type = move_type\\n self.category = category\\n self.pp = pp\\n self.max_pp = pp\\n self.power = power\\n self.accuracy = accuracy\\n self.priority = priority\\n self.effect_rate = effect_rate\\n self.self_stat_mod = self_stat_mod if self_stat_mod is not None else StatsDict()\\n self.trgt_stat_mod = trgt_stat_mod if trgt_stat_mod is not None else StatsDict()\\n\\n def __str__(self):\\n prio_str = f\\\"prio:{'+' if self.priority > 0 else ''}{self.priority}\\\"\\n return f\\\"{str(self.type):^15} {self.category.value}{self.pp:>9}/{self.max_pp:<3}\\\\n\\\" \\\\\\n f\\\"{self.name:^34}\\\\n\\\" \\\\\\n f\\\" {str(self.power):>3}BP -{str(self.accuracy) + '% acc.':^15}- {prio_str:>8} \\\\n\\\" \\\\\\n f\\\"{'-':^34}\\\" if self.effect_rate == 0 else \\\\\\n f\\\"{self.effect_rate:<3}%: \\\" if self.effect_rate != 100 else \\\"\\\" \\\\\\n + f\\\"{', '.join([key + ' x' + val for key, val in self.self_stat_mod if val != 0]):^20} [Self]\\\" \\\\\\n if self.self_stat_mod != StatsDict() else \\\\\\n f\\\"{', '.join([key + ' x' + val for key, val in self.trgt_stat_mod if val != 0]):^18} [Target]\\\" \\\\\\n if self.trgt_stat_mod != StatsDict() else \\\\\\n \\\"\\\"\\n\\n @staticmethod\\n def fromDb(name: str):\\n with open(join(str(database_dir), \\\"moves\\\", f\\\"{name.lower()}.json\\\")) as move_data_file:\\n move_data = load(move_data_file)\\n return PokemonMove(\\n name=name,\\n move_type=PokemonType[move_data[\\\"type\\\"]],\\n category=MoveCategory[move_data[\\\"category\\\"]],\\n pp=int(move_data[\\\"pp\\\"]),\\n power=int(move_data[\\\"power\\\"])\\n if \\\"power\\\" in move_data and move_data[\\\"power\\\"] is not None else 0,\\n accuracy=int(move_data[\\\"accuracy\\\"])\\n if \\\"accuracy\\\" in move_data and move_data[\\\"accuracy\\\"] is not None else 100,\\n priority=int(move_data[\\\"priority\\\"])\\n if \\\"priority\\\" in move_data and move_data[\\\"priority\\\"] else 0,\\n effect_rate=int(move_data[\\\"effect_rate\\\"])\\n if \\\"effect_rate\\\" in move_data and move_data[\\\"effect_rate\\\"] is not None else 0,\\n self_stat_mod=StatsDict(move_data[\\\"self_stat_mod\\\"])\\n if \\\"self_stat_mod\\\" in move_data and move_data[\\\"self_stat_mode\\\"] is not None else StatsDict(),\\n trgt_stat_mod=StatsDict(move_data[\\\"trgt_stat_mod\\\"])\\n if \\\"trgt_stat_mod\\\" in move_data and move_data[\\\"trgt_stat_mode\\\"] else StatsDict()\\n )\\n\"\n },\n {\n \"alpha_fraction\": 0.7914438247680664,\n \"alphanum_fraction\": 0.7914438247680664,\n \"avg_line_length\": 17.799999237060547,\n \"blob_id\": \"954d472d89e9073e7c52ba6242c78676f01bd807\",\n \"content_id\": \"01a702e295e2571e5deb314e8cd3c745c12f5092\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Makefile\",\n \"length_bytes\": 187,\n \"license_type\": \"permissive\",\n \"max_line_length\": 47,\n \"num_lines\": 10,\n \"path\": \"/Makefile\",\n \"repo_name\": \"LiquidNalee/MiniPkmnShowdown\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"build:\\n\\tdocker build -t minishowdown:latest .\\n\\nrun:\\n\\tdocker run -d --name minishowdown minishowdown\\n\\nclean:\\n\\tdocker stop minishowdown\\n\\tdocker rm minishowdown\\n\\tdocker image rm minishowdown\"\n },\n {\n \"alpha_fraction\": 0.49754709005355835,\n \"alphanum_fraction\": 0.5299889445304871,\n \"avg_line_length\": 40.56578826904297,\n \"blob_id\": \"3cef88bfa9bc6e012796d2e14d7412eff13deae4\",\n \"content_id\": \"c708bf83ee5d447ca884a24a67222f7821aaa032\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 6319,\n \"license_type\": \"permissive\",\n \"max_line_length\": 105,\n \"num_lines\": 152,\n \"path\": \"/tests/models/game/battle/test_BattleGameState.py\",\n \"repo_name\": \"LiquidNalee/MiniPkmnShowdown\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from unittest import TestCase\\n\\nfrom models.game.battle.BattleGameState import BattleGameState\\nfrom models.game.trainer.PokemonTrainer import PokemonTrainer\\nfrom models.game.trainer.utils.ArenaBadge import ArenaBadge\\nfrom models.pkmn.PokemonModel import PokemonModel\\nfrom models.pkmn.moves.PokemonMove import MoveCategory, PokemonMove\\nfrom models.pkmn.natures.PokemonNature import PokemonNature\\nfrom models.pkmn.stats.StatsDict import StatsDict\\nfrom models.pkmn.types.PokemonType import PokemonType\\n\\n\\nclass TestBattleGameState(TestCase):\\n\\n def setUp(self) -> None:\\n self.Pikachu = PokemonModel(\\n name=\\\"Pikachu\\\",\\n types=(PokemonType.Electric, None),\\n level=100,\\n nature=PokemonNature.Jolly,\\n moves=[\\n PokemonMove(\\n name=\\\"Volt Tackle\\\",\\n move_type=PokemonType.Electric,\\n category=MoveCategory.Physical,\\n pp=24,\\n power=120\\n ),\\n PokemonMove(\\n name=\\\"Iron Tail\\\",\\n move_type=PokemonType.Steel,\\n category=MoveCategory.Physical,\\n pp=24,\\n power=100,\\n accuracy=75\\n ),\\n PokemonMove(\\n name=\\\"Thunderbolt\\\",\\n move_type=PokemonType.Electric,\\n category=MoveCategory.Special,\\n pp=24,\\n power=90\\n )\\n ],\\n base_stats=StatsDict(hp=35, atk=55, phys_def=40, spe_atk=50, spe_def=50, spd=90),\\n evs=StatsDict(hp=0, atk=252, phys_def=0, spe_atk=4, spe_def=0, spd=252),\\n ivs=StatsDict(hp=31, atk=31, phys_def=31, spe_atk=31, spe_def=31, spd=31)\\n )\\n self.Charizard = PokemonModel(\\n name=\\\"Charizard\\\",\\n types=(PokemonType.Fire, PokemonType.Flying),\\n level=100,\\n nature=PokemonNature.Jolly,\\n moves=[\\n PokemonMove(\\n name=\\\"Fire Blast\\\",\\n move_type=PokemonType.Fire,\\n category=MoveCategory.Special,\\n pp=8,\\n power=110,\\n accuracy=85\\n ),\\n PokemonMove(\\n name=\\\"Hurricane\\\",\\n move_type=PokemonType.Flying,\\n category=MoveCategory.Special,\\n pp=16,\\n power=110,\\n accuracy=70\\n )\\n ],\\n base_stats=StatsDict(hp=78, atk=84, phys_def=78, spe_atk=109, spe_def=85, spd=100),\\n evs=StatsDict(hp=0, atk=0, phys_def=0, spe_atk=252, spe_def=4, spd=252),\\n ivs=StatsDict(hp=31, atk=31, phys_def=31, spe_atk=31, spe_def=31, spd=31)\\n )\\n self.Pidgeot = PokemonModel(\\n name=\\\"Pidgeot\\\",\\n types=(PokemonType.Flying, PokemonType.Normal),\\n level=100,\\n nature=PokemonNature.Jolly,\\n moves=[\\n PokemonMove(\\n name=\\\"Double Edge\\\",\\n move_type=PokemonType.Normal,\\n category=MoveCategory.Physical,\\n pp=24,\\n power=120\\n ),\\n PokemonMove(\\n name=\\\"Brave Bird\\\",\\n move_type=PokemonType.Flying,\\n category=MoveCategory.Physical,\\n pp=24,\\n power=120\\n )\\n ],\\n base_stats=StatsDict(hp=83, atk=80, phys_def=75, spe_atk=70, spe_def=70, spd=101),\\n evs=StatsDict(hp=0, atk=252, phys_def=0, spe_atk=0, spe_def=4, spd=252),\\n ivs=StatsDict(hp=31, atk=31, phys_def=31, spe_atk=31, spe_def=31, spd=31)\\n )\\n self.Blastoise = PokemonModel(\\n name=\\\"Blastoise\\\",\\n types=(PokemonType.Water, None),\\n level=100,\\n nature=PokemonNature.Modest,\\n moves=[\\n PokemonMove(\\n name=\\\"Hydro Pump\\\",\\n move_type=PokemonType.Water,\\n category=MoveCategory.Special,\\n pp=8,\\n power=110,\\n accuracy=80\\n ),\\n PokemonMove(\\n name=\\\"Ice Beam\\\",\\n move_type=PokemonType.Ice,\\n category=MoveCategory.Special,\\n pp=16,\\n power=90\\n )\\n ],\\n base_stats=StatsDict(hp=79, atk=83, phys_def=100, spe_atk=85, spe_def=105, spd=78),\\n evs=StatsDict(hp=252, atk=0, phys_def=0, spe_atk=252, spe_def=4, spd=0),\\n ivs=StatsDict(hp=31, atk=31, phys_def=31, spe_atk=31, spe_def=31, spd=31)\\n )\\n self.Red = PokemonTrainer(\\n name=\\\"Red\\\",\\n team=[self.Pikachu, self.Charizard],\\n badges=[ArenaBadge.Boulder, ArenaBadge.Cascade, ArenaBadge.Thunder, ArenaBadge.Rainbow,\\n ArenaBadge.Soul, ArenaBadge.Marsh, ArenaBadge.Marsh, ArenaBadge.Earth]\\n )\\n self.Blue = PokemonTrainer(\\n name=\\\"Blue\\\",\\n team=[self.Pidgeot, self.Blastoise],\\n badges=[ArenaBadge.Boulder, ArenaBadge.Cascade, ArenaBadge.Thunder, ArenaBadge.Rainbow,\\n ArenaBadge.Soul, ArenaBadge.Marsh, ArenaBadge.Marsh, ArenaBadge.Earth]\\n )\\n self.BattleGameState = BattleGameState(player=self.Red, opponent=self.Blue)\\n\\n def test_battle_game_state(self):\\n\\n assert self.BattleGameState.player.name == \\\"Red\\\" and self.BattleGameState.opponent.name == \\\"Blue\\\"\\n assert self.BattleGameState.turn == 1\\n assert self.BattleGameState.getPlayerActivePkmn() == self.Pikachu\\n assert self.BattleGameState.getOpponentActivePkmn() == self.Pidgeot\\n self.BattleGameState.setPlayerActivePkmn(1)\\n assert self.BattleGameState.getPlayerActivePkmn() == self.Charizard\\n assert self.BattleGameState.getOpponentActivePkmn() == self.Pidgeot\\n self.BattleGameState.setOpponentActivePkmn(1)\\n assert self.BattleGameState.getPlayerActivePkmn() == self.Charizard\\n assert self.BattleGameState.getOpponentActivePkmn() == self.Blastoise\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.6862886548042297,\n \"alphanum_fraction\": 0.6961396932601929,\n \"avg_line_length\": 57.61971664428711,\n \"blob_id\": \"003e87c83f1b6010c83cdc0819d2299d7c93a6bf\",\n \"content_id\": \"a7e8757dd8e587e24156e95d5ada6d5000ba1660\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 12486,\n \"license_type\": \"permissive\",\n \"max_line_length\": 111,\n \"num_lines\": 213,\n \"path\": \"/engine/pkmn/types/ClassicTypesRuleSet.py\",\n \"repo_name\": \"LiquidNalee/MiniPkmnShowdown\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from pandas import DataFrame\\nfrom engine.pkmn.types.TypesBaseRuleSet import TypesBaseRuleSet\\nfrom models.pkmn.types.PokemonType import PokemonType\\n\\n\\nclass ClassicTypesRuleSet(TypesBaseRuleSet):\\n\\n def __init__(self):\\n # Init all at 1\\n type_effectiveness_chart = DataFrame({ref_pkmn_type: {pkmn_type: float(1) for pkmn_type in PokemonType}\\n for ref_pkmn_type in PokemonType})\\n\\n # Normal is:\\n # ineffective against\\n type_effectiveness_chart[PokemonType.Normal][PokemonType.Ghost] = float(0)\\n # not very effective against\\n type_effectiveness_chart[PokemonType.Normal][PokemonType.Steel] = float(.5)\\n type_effectiveness_chart[PokemonType.Normal][PokemonType.Rock] = float(.5)\\n\\n # Fire is:\\n # very effective against\\n type_effectiveness_chart[PokemonType.Fire][PokemonType.Steel] = float(2)\\n type_effectiveness_chart[PokemonType.Fire][PokemonType.Grass] = float(2)\\n type_effectiveness_chart[PokemonType.Fire][PokemonType.Ice] = float(2)\\n type_effectiveness_chart[PokemonType.Fire][PokemonType.Bug] = float(2)\\n # not very effective against\\n type_effectiveness_chart[PokemonType.Fire][PokemonType.Fire] = float(.5)\\n type_effectiveness_chart[PokemonType.Fire][PokemonType.Water] = float(.5)\\n type_effectiveness_chart[PokemonType.Fire][PokemonType.Rock] = float(.5)\\n type_effectiveness_chart[PokemonType.Fire][PokemonType.Dragon] = float(.5)\\n\\n # Water is:\\n # very effective against\\n type_effectiveness_chart[PokemonType.Water][PokemonType.Fire] = float(2)\\n type_effectiveness_chart[PokemonType.Water][PokemonType.Ground] = float(2)\\n type_effectiveness_chart[PokemonType.Water][PokemonType.Rock] = float(2)\\n # not very effective against\\n type_effectiveness_chart[PokemonType.Water][PokemonType.Water] = float(.5)\\n type_effectiveness_chart[PokemonType.Water][PokemonType.Grass] = float(.5)\\n type_effectiveness_chart[PokemonType.Water][PokemonType.Dragon] = float(.5)\\n\\n # Electric is:\\n # ineffective against\\n type_effectiveness_chart[PokemonType.Electric][PokemonType.Ground] = float(0)\\n # very effective against\\n type_effectiveness_chart[PokemonType.Electric][PokemonType.Water] = float(2)\\n type_effectiveness_chart[PokemonType.Electric][PokemonType.Flying] = float(2)\\n # not very effective against\\n type_effectiveness_chart[PokemonType.Electric][PokemonType.Electric] = float(.5)\\n type_effectiveness_chart[PokemonType.Electric][PokemonType.Grass] = float(.5)\\n type_effectiveness_chart[PokemonType.Electric][PokemonType.Dragon] = float(.5)\\n\\n # Grass is:\\n # very effective against\\n type_effectiveness_chart[PokemonType.Grass][PokemonType.Water] = float(2)\\n type_effectiveness_chart[PokemonType.Grass][PokemonType.Ground] = float(2)\\n type_effectiveness_chart[PokemonType.Grass][PokemonType.Rock] = float(2)\\n # not very effective against\\n type_effectiveness_chart[PokemonType.Grass][PokemonType.Fire] = float(.5)\\n type_effectiveness_chart[PokemonType.Grass][PokemonType.Grass] = float(.5)\\n type_effectiveness_chart[PokemonType.Grass][PokemonType.Poison] = float(.5)\\n type_effectiveness_chart[PokemonType.Grass][PokemonType.Flying] = float(.5)\\n type_effectiveness_chart[PokemonType.Grass][PokemonType.Bug] = float(.5)\\n type_effectiveness_chart[PokemonType.Grass][PokemonType.Dragon] = float(.5)\\n type_effectiveness_chart[PokemonType.Grass][PokemonType.Steel] = float(.5)\\n\\n # Ice is:\\n # very effective against\\n type_effectiveness_chart[PokemonType.Ice][PokemonType.Grass] = float(2)\\n type_effectiveness_chart[PokemonType.Ice][PokemonType.Ground] = float(2)\\n type_effectiveness_chart[PokemonType.Ice][PokemonType.Flying] = float(2)\\n type_effectiveness_chart[PokemonType.Ice][PokemonType.Dragon] = float(2)\\n # not very effective against\\n type_effectiveness_chart[PokemonType.Ice][PokemonType.Fire] = float(.5)\\n type_effectiveness_chart[PokemonType.Ice][PokemonType.Water] = float(.5)\\n type_effectiveness_chart[PokemonType.Ice][PokemonType.Ice] = float(.5)\\n type_effectiveness_chart[PokemonType.Ice][PokemonType.Steel] = float(.5)\\n\\n # Fighting is:\\n # ineffective against\\n type_effectiveness_chart[PokemonType.Fighting][PokemonType.Ghost] = float(0)\\n # very effective against\\n type_effectiveness_chart[PokemonType.Fighting][PokemonType.Normal] = float(2)\\n type_effectiveness_chart[PokemonType.Fighting][PokemonType.Ice] = float(2)\\n type_effectiveness_chart[PokemonType.Fighting][PokemonType.Rock] = float(2)\\n type_effectiveness_chart[PokemonType.Fighting][PokemonType.Dark] = float(2)\\n type_effectiveness_chart[PokemonType.Fighting][PokemonType.Steel] = float(2)\\n # not very effective against\\n type_effectiveness_chart[PokemonType.Fighting][PokemonType.Poison] = float(.5)\\n type_effectiveness_chart[PokemonType.Fighting][PokemonType.Flying] = float(.5)\\n type_effectiveness_chart[PokemonType.Fighting][PokemonType.Psychic] = float(.5)\\n type_effectiveness_chart[PokemonType.Fighting][PokemonType.Bug] = float(.5)\\n type_effectiveness_chart[PokemonType.Fighting][PokemonType.Fairy] = float(.5)\\n\\n # Poison is:\\n # ineffective against\\n type_effectiveness_chart[PokemonType.Poison][PokemonType.Steel] = float(0)\\n # very effective against\\n type_effectiveness_chart[PokemonType.Poison][PokemonType.Grass] = float(2)\\n type_effectiveness_chart[PokemonType.Poison][PokemonType.Fairy] = float(2)\\n # not very effective against\\n type_effectiveness_chart[PokemonType.Poison][PokemonType.Poison] = float(.5)\\n type_effectiveness_chart[PokemonType.Poison][PokemonType.Ground] = float(.5)\\n type_effectiveness_chart[PokemonType.Poison][PokemonType.Rock] = float(.5)\\n type_effectiveness_chart[PokemonType.Poison][PokemonType.Ghost] = float(.5)\\n\\n # Ground is:\\n # ineffective against\\n type_effectiveness_chart[PokemonType.Ground][PokemonType.Flying] = float(0)\\n # very effective against\\n type_effectiveness_chart[PokemonType.Ground][PokemonType.Fire] = float(2)\\n type_effectiveness_chart[PokemonType.Ground][PokemonType.Electric] = float(2)\\n type_effectiveness_chart[PokemonType.Ground][PokemonType.Poison] = float(2)\\n type_effectiveness_chart[PokemonType.Ground][PokemonType.Rock] = float(2)\\n type_effectiveness_chart[PokemonType.Ground][PokemonType.Steel] = float(2)\\n # not very effective against\\n type_effectiveness_chart[PokemonType.Ground][PokemonType.Grass] = float(.5)\\n type_effectiveness_chart[PokemonType.Ground][PokemonType.Bug] = float(.5)\\n\\n # Flying is:\\n # very effective against\\n type_effectiveness_chart[PokemonType.Flying][PokemonType.Grass] = float(2)\\n type_effectiveness_chart[PokemonType.Flying][PokemonType.Fighting] = float(2)\\n type_effectiveness_chart[PokemonType.Flying][PokemonType.Bug] = float(2)\\n # not very effective against\\n type_effectiveness_chart[PokemonType.Flying][PokemonType.Electric] = float(.5)\\n type_effectiveness_chart[PokemonType.Flying][PokemonType.Rock] = float(.5)\\n type_effectiveness_chart[PokemonType.Flying][PokemonType.Steel] = float(.5)\\n\\n # Psychic is:\\n # ineffective against\\n type_effectiveness_chart[PokemonType.Psychic][PokemonType.Dark] = float(0)\\n # very effective against\\n type_effectiveness_chart[PokemonType.Psychic][PokemonType.Poison] = float(2)\\n type_effectiveness_chart[PokemonType.Psychic][PokemonType.Fighting] = float(2)\\n # not very effective against\\n type_effectiveness_chart[PokemonType.Psychic][PokemonType.Psychic] = float(.5)\\n type_effectiveness_chart[PokemonType.Psychic][PokemonType.Steel] = float(.5)\\n\\n # Bug is:\\n # very effective against\\n type_effectiveness_chart[PokemonType.Bug][PokemonType.Grass] = float(2)\\n type_effectiveness_chart[PokemonType.Bug][PokemonType.Psychic] = float(2)\\n type_effectiveness_chart[PokemonType.Bug][PokemonType.Dark] = float(2)\\n # not very effective against\\n type_effectiveness_chart[PokemonType.Bug][PokemonType.Fire] = float(.5)\\n type_effectiveness_chart[PokemonType.Bug][PokemonType.Fighting] = float(.5)\\n type_effectiveness_chart[PokemonType.Bug][PokemonType.Poison] = float(.5)\\n type_effectiveness_chart[PokemonType.Bug][PokemonType.Flying] = float(.5)\\n type_effectiveness_chart[PokemonType.Bug][PokemonType.Rock] = float(.5)\\n type_effectiveness_chart[PokemonType.Bug][PokemonType.Ghost] = float(.5)\\n type_effectiveness_chart[PokemonType.Bug][PokemonType.Steel] = float(.5)\\n type_effectiveness_chart[PokemonType.Bug][PokemonType.Fairy] = float(.5)\\n\\n # Rock is:\\n # very effective against\\n type_effectiveness_chart[PokemonType.Rock][PokemonType.Fire] = float(2)\\n type_effectiveness_chart[PokemonType.Rock][PokemonType.Ice] = float(2)\\n type_effectiveness_chart[PokemonType.Rock][PokemonType.Flying] = float(2)\\n type_effectiveness_chart[PokemonType.Rock][PokemonType.Bug] = float(2)\\n # not very effective against\\n type_effectiveness_chart[PokemonType.Rock][PokemonType.Fighting] = float(.5)\\n type_effectiveness_chart[PokemonType.Rock][PokemonType.Ground] = float(.5)\\n type_effectiveness_chart[PokemonType.Rock][PokemonType.Steel] = float(.5)\\n\\n # Ghost is:\\n # ineffective against\\n type_effectiveness_chart[PokemonType.Ghost][PokemonType.Normal] = float(0)\\n # very effective against\\n type_effectiveness_chart[PokemonType.Ghost][PokemonType.Psychic] = float(2)\\n type_effectiveness_chart[PokemonType.Ghost][PokemonType.Ghost] = float(2)\\n # not very effective against\\n type_effectiveness_chart[PokemonType.Ghost][PokemonType.Dark] = float(.5)\\n\\n # Dragon is:\\n # ineffective against\\n type_effectiveness_chart[PokemonType.Dragon][PokemonType.Fairy] = float(0)\\n # very effective against\\n type_effectiveness_chart[PokemonType.Dragon][PokemonType.Dragon] = float(2)\\n # not very effective against\\n type_effectiveness_chart[PokemonType.Dragon][PokemonType.Steel] = float(.5)\\n\\n # Dark is:\\n # very effective against\\n type_effectiveness_chart[PokemonType.Dark][PokemonType.Psychic] = float(2)\\n type_effectiveness_chart[PokemonType.Dark][PokemonType.Ghost] = float(2)\\n # not very effective against\\n type_effectiveness_chart[PokemonType.Dark][PokemonType.Fighting] = float(.5)\\n type_effectiveness_chart[PokemonType.Dark][PokemonType.Dark] = float(.5)\\n type_effectiveness_chart[PokemonType.Dark][PokemonType.Fairy] = float(.5)\\n\\n # Steel is:\\n # very effective against\\n type_effectiveness_chart[PokemonType.Steel][PokemonType.Ice] = float(2)\\n type_effectiveness_chart[PokemonType.Steel][PokemonType.Rock] = float(2)\\n type_effectiveness_chart[PokemonType.Steel][PokemonType.Fairy] = float(2)\\n # not very effective against\\n type_effectiveness_chart[PokemonType.Steel][PokemonType.Fire] = float(.5)\\n type_effectiveness_chart[PokemonType.Steel][PokemonType.Water] = float(.5)\\n type_effectiveness_chart[PokemonType.Steel][PokemonType.Electric] = float(.5)\\n type_effectiveness_chart[PokemonType.Steel][PokemonType.Steel] = float(.5)\\n\\n # Fairy is:\\n # very effective against\\n type_effectiveness_chart[PokemonType.Fairy][PokemonType.Fighting] = float(2)\\n type_effectiveness_chart[PokemonType.Fairy][PokemonType.Dark] = float(2)\\n type_effectiveness_chart[PokemonType.Fairy][PokemonType.Dragon] = float(2)\\n # not very effective against\\n type_effectiveness_chart[PokemonType.Fairy][PokemonType.Fire] = float(.5)\\n type_effectiveness_chart[PokemonType.Fairy][PokemonType.Poison] = float(.5)\\n type_effectiveness_chart[PokemonType.Fairy][PokemonType.Steel] = float(.5)\\n\\n super().__init__(type_effectiveness_chart=type_effectiveness_chart)\\n\"\n },\n {\n \"alpha_fraction\": 0.5425220131874084,\n \"alphanum_fraction\": 0.5451287031173706,\n \"avg_line_length\": 40.47297286987305,\n \"blob_id\": \"bbbdafe4f3acd16c681e34d7d039daaed72851eb\",\n \"content_id\": \"bd3bf742a6db194b679cc20a3143801bf39b5ee8\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 3069,\n \"license_type\": \"permissive\",\n \"max_line_length\": 120,\n \"num_lines\": 74,\n \"path\": \"/database/DatabaseConfig.py\",\n \"repo_name\": \"LiquidNalee/MiniPkmnShowdown\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from os.path import join, dirname, realpath\\nfrom pathlib import Path\\nfrom typing import List\\nfrom json import dump\\nfrom requests import request\\nfrom re import sub\\n\\ndatabase_dir = Path(dirname(realpath(__file__)))\\n__pokeApi_url = \\\"https://pokeapi.co/api/v2/\\\"\\n\\n\\ndef updatePkmnDatabase(pkmn_list: List):\\n for pkmn_name, pkmn_data in getPkmnDatabase(pkmn_list).items():\\n print(f\\\"Uploaded {pkmn_name}.json\\\")\\n with open(join(database_dir, \\\"pkmn\\\", f\\\"{pkmn_name}.json\\\"), mode='w') as pkmn_data_file:\\n dump(pkmn_data, pkmn_data_file)\\n\\n\\ndef getPkmnDatabase(pkmn_list: List[str]) -> {}:\\n db = {}\\n for pkmn in pkmn_list:\\n res = request(\\\"GET\\\", f\\\"{__pokeApi_url}/pokemon/{pkmn}\\\")\\n\\n if res.status_code == 200:\\n pkmn_json = {\\n \\\"type\\\": {str(pkmn_type[\\\"slot\\\"] - 1): pkmn_type[\\\"type\\\"][\\\"name\\\"].capitalize()\\n for pkmn_type in res.json()[\\\"types\\\"]},\\n \\\"base_stats\\\": {__convertApiStatNameToDbStatName(pkmn_stat[\\\"stat\\\"][\\\"name\\\"]): pkmn_stat[\\\"base_stat\\\"]\\n for pkmn_stat in res.json()[\\\"stats\\\"]}\\n }\\n db[res.json()[\\\"name\\\"]] = pkmn_json\\n return db\\n\\n\\ndef updateMoveDatabase(move_list: List):\\n for move_name, move_data in getMoveDatabase(move_list).items():\\n print(f\\\"Uploaded {move_name.lower()}.json\\\")\\n with open(join(database_dir, \\\"moves\\\", f\\\"{move_name.lower()}.json\\\"), mode='w') as move_data_file:\\n dump(move_data, move_data_file)\\n\\n\\ndef getMoveDatabase(move_list: List[str]) -> {}:\\n db = {}\\n for move in move_list:\\n move_url = sub('\\\\\\\\s', '-', move.lower())\\n res = request(\\\"GET\\\", f\\\"{__pokeApi_url}/move/{move_url}\\\")\\n\\n if res.status_code == 200:\\n move_json = {\\n \\\"type\\\": res.json()[\\\"type\\\"][\\\"name\\\"].capitalize(),\\n \\\"category\\\": res.json()[\\\"damage_class\\\"][\\\"name\\\"].capitalize(),\\n \\\"pp\\\": res.json()[\\\"pp\\\"],\\n \\\"power\\\": res.json()[\\\"power\\\"],\\n \\\"accuracy\\\": res.json()[\\\"accuracy\\\"],\\n \\\"priority\\\": res.json()[\\\"priority\\\"],\\n \\\"effect_rate\\\": res.json()[\\\"effect_chance\\\"],\\n \\\"self_stat_mod\\\": {__convertApiStatNameToDbStatName(pkmn_stat[\\\"stat\\\"][\\\"name\\\"]): pkmn_stat[\\\"change\\\"]\\n for pkmn_stat in res.json()[\\\"stat_changes\\\"]} if res.json()[\\\"target\\\"][\\\"name\\\"] == \\\"user\\\"\\n else {},\\n \\\"trgt_stat_mod\\\": {__convertApiStatNameToDbStatName(pkmn_stat[\\\"stat\\\"][\\\"name\\\"]): pkmn_stat[\\\"change\\\"]\\n for pkmn_stat in res.json()[\\\"stat_changes\\\"]} if res.json()[\\\"target\\\"][\\\"name\\\"] != \\\"user\\\"\\n else {}\\n }\\n db[move] = move_json\\n return db\\n\\n\\ndef __convertApiStatNameToDbStatName(api_stat: str) -> str:\\n return \\\"atk\\\" if api_stat == \\\"attack\\\" \\\\\\n else \\\"phys_def\\\" if api_stat == \\\"defense\\\" \\\\\\n else \\\"spe_atk\\\" if api_stat == \\\"special-attack\\\" \\\\\\n else \\\"spe_def\\\" if api_stat == \\\"special-defense\\\" \\\\\\n else \\\"spd\\\" if api_stat == \\\"speed\\\" \\\\\\n else \\\"hp\\\"\\n\"\n },\n {\n \"alpha_fraction\": 0.6633986830711365,\n \"alphanum_fraction\": 0.6633986830711365,\n \"avg_line_length\": 37.25,\n \"blob_id\": \"aa5b9721a95d829d81ef13270225cd7736f9644c\",\n \"content_id\": \"e4e12cd6e9461c77cb375bb7da6a9807cc9e9d61\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 612,\n \"license_type\": \"permissive\",\n \"max_line_length\": 92,\n \"num_lines\": 16,\n \"path\": \"/models/pkmn/PokemonBaseModel.py\",\n \"repo_name\": \"LiquidNalee/MiniPkmnShowdown\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from models.pkmn.stats.StatsDict import StatsDict\\nfrom models.pkmn.types.PokemonType import PokemonType, format_types_tuple, type_equals\\n\\n\\nclass PokemonBaseModel:\\n\\n def __init__(self, name: str, types: (PokemonType, PokemonType), base_stats: StatsDict):\\n self.name = name\\n self.type = format_types_tuple(types)\\n self.base_stats = base_stats\\n\\n def __eq__(self, other):\\n if self.__class__ != other.__class__:\\n return NotImplementedError\\n return self.name == other.name and type_equals(self.type, other.type) \\\\\\n and self.base_stats == other.base_stats\\n\"\n },\n {\n \"alpha_fraction\": 0.7446808218955994,\n \"alphanum_fraction\": 0.7446808218955994,\n \"avg_line_length\": 30,\n \"blob_id\": \"6ac61a64f7cef1b3d25d2b29d0e6c52661d7cd27\",\n \"content_id\": \"00050388debf012360c916d942911f973b600195\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Shell\",\n \"length_bytes\": 94,\n \"license_type\": \"permissive\",\n \"max_line_length\": 72,\n \"num_lines\": 3,\n \"path\": \"/run_tests.sh\",\n \"repo_name\": \"LiquidNalee/MiniPkmnShowdown\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"make build\\nmake run\\ndocker run -a stdin -a stdout -i -t minishowdown python -m pytest tests/\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.7653429508209229,\n \"alphanum_fraction\": 0.7689530849456787,\n \"avg_line_length\": 18.85714340209961,\n \"blob_id\": \"c24e7384ea2c44628f167ee77fba7b59e038f56e\",\n \"content_id\": \"9ecc07e6494676e554e7966d7bf8865f855d8f72\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 277,\n \"license_type\": \"permissive\",\n \"max_line_length\": 70,\n \"num_lines\": 14,\n \"path\": \"/README.md\",\n \"repo_name\": \"LiquidNalee/MiniPkmnShowdown\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"1st time:\\n\\npython -m minishowdown -p trainer_example.json --update_db True\\n\\nelse:\\n\\npython -m minishowdown -p trainer_example.json\\n\\nfor a tougher battle:\\n\\npython -m minishowdown -p trainer_example.json -o trainer_example.json\\n\\n\\nFeel free to write your own teams, pkmns and moves\"\n },\n {\n \"alpha_fraction\": 0.4875912368297577,\n \"alphanum_fraction\": 0.5352798104286194,\n \"avg_line_length\": 36.3636360168457,\n \"blob_id\": \"03f6035d410e9c49c9c5964a014410220f8c369b\",\n \"content_id\": \"b8b0e75c46459ac5a07a847afea0a2ae86318208\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 2055,\n \"license_type\": \"permissive\",\n \"max_line_length\": 116,\n \"num_lines\": 55,\n \"path\": \"/tests/database/test_DatabaseInit.py\",\n \"repo_name\": \"LiquidNalee/MiniPkmnShowdown\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from unittest import TestCase\\n\\nfrom database.DatabaseConfig import getPkmnDatabase\\n\\nfrom models.game.trainer.PokemonTrainer import PokemonTrainer\\nfrom models.pkmn.natures.PokemonNature import PokemonNature\\nfrom models.pkmn.stats.StatsDict import StatsDict\\nfrom models.pkmn.types.PokemonType import PokemonType\\n\\n\\nclass TestDatabaseInit(TestCase):\\n\\n def test_database_init(self):\\n trainer_json = {\\n \\\"name\\\": \\\"Red\\\",\\n \\\"team\\\": {\\n \\\"0\\\": {\\n \\\"name\\\": \\\"Scizor\\\",\\n \\\"level\\\": 100,\\n \\\"nature\\\": \\\"Adamant\\\",\\n \\\"moves\\\": [\\\"Bullet Punch\\\"],\\n \\\"evs\\\": {\\\"hp\\\": 120, \\\"atk\\\": 252, \\\"phys_def\\\": 0, \\\"spe_atk\\\": 0, \\\"spe_def\\\": 0, \\\"spd\\\": 136},\\n \\\"ivs\\\": {\\\"hp\\\": 31, \\\"atk\\\": 31, \\\"phys_def\\\": 31, \\\"spe_atk\\\": 31, \\\"spe_def\\\": 31, \\\"spd\\\": 31}\\n }\\n }\\n }\\n trainer = PokemonTrainer.fromJson(trainer_json)\\n\\n assert trainer.name == \\\"Red\\\"\\n assert trainer.team[1] is None\\n assert trainer.team[0].name == \\\"Scizor\\\"\\n assert trainer.team[0].level == 100\\n assert trainer.team[0]._nature == PokemonNature.Adamant\\n assert trainer.team[0].moves[0].type == PokemonType.Steel\\n assert trainer.team[0].moves[0].power == 40\\n assert trainer.team[0].moves[0].accuracy == 100\\n assert trainer.team[0].base_stats == StatsDict(hp=70, atk=130, phys_def=100, spe_atk=55, spe_def=80, spd=65)\\n assert trainer.team[0].stats == StatsDict(hp=311, atk=394, phys_def=236, spe_atk=131, spe_def=196, spd=200)\\n\\n def test_database_update(self):\\n db = getPkmnDatabase([\\\"tyranitar\\\"])\\n\\n assert \\\"tyranitar\\\" in db\\n expected_json = {\\n \\\"type\\\": {\\\"0\\\": \\\"rock\\\", \\\"1\\\": \\\"dark\\\"},\\n \\\"base_stats\\\": {\\n \\\"hp\\\": 100,\\n \\\"atk\\\": 134,\\n \\\"phys_def\\\": 110,\\n \\\"spe_atk\\\": 95,\\n \\\"spe_def\\\": 100,\\n \\\"spd\\\": 61\\n }\\n }\\n assert db[\\\"tyranitar\\\"] == expected_json\\n\"\n },\n {\n \"alpha_fraction\": 0.6279069781303406,\n \"alphanum_fraction\": 0.6376594305038452,\n \"avg_line_length\": 45.36521911621094,\n \"blob_id\": \"7e97dae375103b69683e4c7453dd35282ab2df61\",\n \"content_id\": \"4fa09cbfdc2533bfd728b0d882e0440d32b39148\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 5332,\n \"license_type\": \"permissive\",\n \"max_line_length\": 114,\n \"num_lines\": 115,\n \"path\": \"/engine/game/BattleEngine.py\",\n \"repo_name\": \"LiquidNalee/MiniPkmnShowdown\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from random import randint\\n\\nfrom engine.game import InputHandler\\nfrom engine.game.BattleDisplay import displayPlayers, displayBattleGameState, displayUsedMove, \\\\\\n displaySwitch, displayEndOfBattle\\nfrom engine.pkmn.types.TypesBaseRuleSet import TypesBaseRuleSet\\nfrom models.game.battle.BattleGameState import BattleGameState\\nfrom models.pkmn.PokemonModel import PokemonModel\\nfrom models.pkmn.moves.PokemonMove import PokemonMove, MoveCategory\\nfrom models.pkmn.stats.StatsDict import StatsDict\\n\\n\\nclass BattleEngine:\\n\\n def __init__(self, battleGameState: BattleGameState, typesRuleSet: TypesBaseRuleSet):\\n self.gameState = battleGameState\\n self.typesRuleSet = typesRuleSet\\n\\n def startGame(self) -> bool:\\n displayPlayers(self.gameState)\\n # Lead Phase\\n player_pkmn_selection = InputHandler.pkmnSelection(self.gameState.player.team)\\n self.gameState.setPlayerActivePkmn(player_pkmn_selection)\\n\\n # Battle Phase\\n self.__battlePhase()\\n\\n win = not self.gameState.player.hasLost()\\n displayEndOfBattle(win, self.gameState)\\n return win\\n\\n def __battlePhase(self):\\n while not self.gameState.player.hasLost() and not self.gameState.opponent.hasLost():\\n # Move Selection Phase\\n if self.gameState.getPlayerActivePkmn().isKO():\\n self.__switchPlayerPokemon()\\n if self.gameState.getOpponentActivePkmn().isKO():\\n self.__switchOpponentPokemon()\\n\\n displayBattleGameState(self.gameState)\\n plyr_move, plyr_switch = InputHandler.turnDecision(self.gameState.getPlayerActivePkmn(),\\n self.gameState.player.team)\\n rand = randint(0, len(self.gameState.getOpponentActivePkmn().moves) - 1)\\n opponent_move = self.gameState.getOpponentActivePkmn().moves[rand]\\n self.gameState.setTurnState(plyr_move=plyr_move, opponent_move=opponent_move)\\n\\n if plyr_switch:\\n self.__switchPlayerPokemon(plyr_switch)\\n\\n first, second = self.__getMoveOrder()\\n self.__useMove(first[0], first[1], second[0])\\n if not second[0].isKO() and second[1] is not None:\\n self.__useMove(second[0], second[1], first[0])\\n self.gameState.turn += 1\\n\\n def __useMove(self, caster: PokemonModel, caster_move: PokemonMove, trgt: PokemonModel) \\\\\\n -> bool:\\n damage = 0\\n type_effectiveness = 1\\n if caster_move.category != MoveCategory.Status:\\n offensive_stat = caster.stats.atk if caster_move.category == MoveCategory.Physical \\\\\\n else caster.stats.spe_atk\\n defensive_stat = trgt.stats.phys_def if caster_move.category == MoveCategory.Physical \\\\\\n else trgt.stats.spe_def\\n damage = (((2 * caster.level / 5 + 2) * caster_move.power * offensive_stat / defensive_stat) / 50 + 2)\\n type_effectiveness = self.typesRuleSet.getEffectiveness(caster_move.type, trgt.type)\\n modifier = (1.5 if caster_move.type == caster.type else 1) \\\\\\n * type_effectiveness \\\\\\n * randint(85, 100) / 100 \\\\\\n * (1 if randint(0, 100) <= caster_move.accuracy else 0)\\n damage = int(damage * modifier)\\n\\n if damage != 0:\\n trgt.takeDamage(damage)\\n displayUsedMove(caster, caster_move, trgt, type_effectiveness, damage)\\n\\n if randint(0, 100) <= caster_move.effect_rate:\\n for stat_key in StatsDict.__dict__.keys():\\n caster.stats[stat_key] *= caster_move.self_stat_mod[stat_key]\\n trgt.stats[stat_key] *= caster_move.trgt_stat_mod[stat_key]\\n\\n return True\\n\\n def __switchPlayerPokemon(self, selection: int = None):\\n out = self.gameState.getPlayerActivePkmn()\\n coming_in = self.gameState.setPlayerActivePkmn(InputHandler.pkmnSelection(self.gameState.player.team)) \\\\\\n if selection is None else selection\\n displaySwitch(player_name=self.gameState.player.name, out=out, coming_in=coming_in)\\n\\n def __switchOpponentPokemon(self):\\n out = self.gameState.getOpponentActivePkmn()\\n coming_in = self.gameState.sendNextOpponentActivePkmn()\\n displaySwitch(player_name=self.gameState.opponent.name, out=out, coming_in=coming_in)\\n\\n def __getMoveOrder(self) -> ((PokemonModel, PokemonMove), (PokemonModel, PokemonMove)):\\n move_order = self.gameState.getTurnState()\\n (plyr_pkmn, plyr_move), (opponent_pkmn, opponent_move) = move_order\\n if plyr_move is None:\\n return move_order[1], move_order[0]\\n\\n if plyr_move.priority == opponent_move.priority:\\n if plyr_pkmn.stats.spd == opponent_pkmn.stats.spd:\\n if randint(0, 1) == 1:\\n move_order = move_order[1], move_order[0]\\n else:\\n if plyr_pkmn.stats.spd < opponent_pkmn.stats.spd:\\n move_order = move_order[1], move_order[0]\\n else:\\n if plyr_move.priority < opponent_move.priority:\\n move_order = move_order[1], move_order[0]\\n\\n return move_order\\n\\n def __getActivePkmns(self):\\n return self.gameState.getPlayerActivePkmn(), self.gameState.getOpponentActivePkmn()\\n\"\n },\n {\n \"alpha_fraction\": 0.5573957562446594,\n \"alphanum_fraction\": 0.5628212690353394,\n \"avg_line_length\": 42.775001525878906,\n \"blob_id\": \"9012645dce48f392af14f29a18cff640fb91ea51\",\n \"content_id\": \"1e429fd728f1f813e961afc4d1675988cdce736a\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 3506,\n \"license_type\": \"permissive\",\n \"max_line_length\": 111,\n \"num_lines\": 80,\n \"path\": \"/models/pkmn/PokemonModel.py\",\n \"repo_name\": \"LiquidNalee/MiniPkmnShowdown\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from typing import List\\nfrom os.path import join\\nfrom json import load\\n\\nfrom models.pkmn.PokemonBaseModel import PokemonBaseModel\\nfrom models.pkmn.stats.StatsDict import StatsDict\\nfrom models.pkmn.types.PokemonType import PokemonType\\nfrom models.pkmn.natures.PokemonNature import PokemonNature\\nfrom models.pkmn.moves.PokemonMove import PokemonMove\\n\\nfrom database.DatabaseConfig import database_dir\\n\\n\\nclass PokemonModel(PokemonBaseModel):\\n\\n __bar_len = 50\\n\\n def __init__(self, name: str, types: (PokemonType, PokemonType), level: int, nature: PokemonNature,\\n moves: List[PokemonMove], base_stats: StatsDict, evs: StatsDict, ivs: StatsDict):\\n super().__init__(name=name, types=types, base_stats=base_stats)\\n self.level = level\\n self._nature = nature\\n self.moves = moves\\n self._evs = evs\\n self._ivs = ivs\\n self.stats = self.__stats_compute()\\n self.max_hp = self.stats.hp\\n\\n def __str__(self):\\n hp_percentage = self.stats.hp / self.max_hp\\n ticks = int(hp_percentage * self.__bar_len + .5)\\n return f\\\"{self.name} (lvl.{self.level}):\\\\n\\\" \\\\\\n f\\\"{'█'.join('' for _ in range(ticks))}{'▁'.join('' for _ in range(self.__bar_len - ticks))}\\\\n\\\" \\\\\\n f\\\"{self.stats.hp}/{self.max_hp} ({int(hp_percentage * 100)}%)\\\"\\n\\n def moveListAsStr(self) -> str:\\n split_lines = [str(move).splitlines() for move in self.moves]\\n return \\\"\\\\n\\\".join([\\\"| |\\\".join([split_lines[x][y] for x in range(len(split_lines))])\\n for y in range(len(split_lines[0]))])\\n\\n def takeDamage(self, damage: int):\\n self.stats.hp -= min(damage, self.stats.hp)\\n\\n def isKO(self):\\n return self.stats.hp == 0\\n\\n @staticmethod\\n def __compute_stat_baseline(level: int, base_stat: int, iv: int, ev: int) -> int:\\n return int((2 * base_stat + iv + ev / 4) * level / 100)\\n\\n def __stats_compute(self) -> StatsDict:\\n stat_values = StatsDict(**{\\n stat_key:\\n self.__compute_stat_baseline(level=self.level, base_stat=self.base_stats.hp,\\n iv=self._ivs.hp, ev=self._evs.hp) + self.level + 10\\n if stat_key == \\\"hp\\\" else\\n self.__compute_stat_baseline(level=self.level, base_stat=self.base_stats[stat_key],\\n iv=self._ivs[stat_key], ev=self._evs[stat_key]) + 5\\n for stat_key in self.base_stats.__dict__.keys()\\n })\\n self._nature.apply_modifier(stat_values)\\n return stat_values\\n\\n @staticmethod\\n def fromJson(json: {}):\\n keys = [\\\"name\\\", \\\"level\\\", \\\"nature\\\", \\\"moves\\\", \\\"evs\\\", \\\"ivs\\\"]\\n if all(key in json for key in keys):\\n with open(join(str(database_dir), \\\"pkmn\\\", f\\\"{json['name'].lower()}.json\\\")) as pkmn_data_file:\\n pkmn_data = load(pkmn_data_file)\\n return PokemonModel(\\n name=json[\\\"name\\\"],\\n types=(PokemonType[pkmn_data[\\\"type\\\"]['0']],\\n PokemonType[pkmn_data[\\\"type\\\"]['1']] if 1 in pkmn_data[\\\"type\\\"] else None),\\n level=int(json[\\\"level\\\"]),\\n nature=PokemonNature[json[\\\"nature\\\"]],\\n moves=[PokemonMove.fromDb(move) for move in json[\\\"moves\\\"]],\\n base_stats=StatsDict(**pkmn_data[\\\"base_stats\\\"]),\\n evs=StatsDict(**json[\\\"evs\\\"]),\\n ivs=StatsDict(**json[\\\"ivs\\\"])\\n )\\n\"\n },\n {\n \"alpha_fraction\": 0.7233532667160034,\n \"alphanum_fraction\": 0.7281436920166016,\n \"avg_line_length\": 45.38888931274414,\n \"blob_id\": \"604bd5509dacceef377a1be8700e4463a7310828\",\n \"content_id\": \"bb88ebce0383ecf88b0064f6f10bff7567f159b3\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 835,\n \"license_type\": \"permissive\",\n \"max_line_length\": 117,\n \"num_lines\": 18,\n \"path\": \"/engine/pkmn/types/TypesBaseRuleSet.py\",\n \"repo_name\": \"LiquidNalee/MiniPkmnShowdown\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from pandas import DataFrame\\nfrom models.pkmn.types.PokemonType import PokemonType\\n\\n\\nclass TypesBaseRuleSet:\\n\\n # .loc on DataFrame: effectiveness of attack on defense\\n # .iloc on DataFrame: effectiveness of defense on attack\\n\\n def __init__(self, type_effectiveness_chart: DataFrame):\\n self.type_effectiveness_chart = type_effectiveness_chart\\n\\n def __getitem__(self, item: PokemonType) -> (DataFrame, DataFrame):\\n return self.type_effectiveness_chart.loc(item), self.type_effectiveness_chart.iloc(item)\\n\\n def getEffectiveness(self, attack_type: PokemonType, defender_type: (PokemonType, PokemonType)) -> float:\\n return self.type_effectiveness_chart[attack_type][defender_type[0]] \\\\\\n * self.type_effectiveness_chart[attack_type][defender_type[1]] if defender_type[1] is not None else 1\\n\"\n },\n {\n \"alpha_fraction\": 0.746835470199585,\n \"alphanum_fraction\": 0.746835470199585,\n \"avg_line_length\": 25.33333396911621,\n \"blob_id\": \"60f4d48d5de00c627956b2631bed1b714132f04d\",\n \"content_id\": \"a5c50dde53326514e1899cc8145ab1086720ce9e\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Shell\",\n \"length_bytes\": 79,\n \"license_type\": \"permissive\",\n \"max_line_length\": 58,\n \"num_lines\": 3,\n \"path\": \"/run.sh\",\n \"repo_name\": \"LiquidNalee/MiniPkmnShowdown\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"make build\\nmake run\\ndocker run -a stdin -a stdout -i -t minishowdown /bin/bash\\n\"\n },\n {\n \"alpha_fraction\": 0.5025380849838257,\n \"alphanum_fraction\": 0.5332769155502319,\n \"avg_line_length\": 39.75862121582031,\n \"blob_id\": \"f911cbd3e09e6e573aabdcd86a7d86bba2d37eef\",\n \"content_id\": \"ff82f110841d97891d07e450cc2a862946c2614f\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 3546,\n \"license_type\": \"permissive\",\n \"max_line_length\": 114,\n \"num_lines\": 87,\n \"path\": \"/tests/models/game/trainer/test_PokemonTrainer.py\",\n \"repo_name\": \"LiquidNalee/MiniPkmnShowdown\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from unittest import TestCase\\n\\nfrom models.game.trainer.PokemonTrainer import PokemonTrainer\\nfrom models.pkmn.PokemonModel import PokemonModel\\nfrom models.pkmn.moves.PokemonMove import PokemonMove, MoveCategory\\nfrom models.pkmn.stats.StatsDict import StatsDict\\nfrom models.pkmn.types.PokemonType import PokemonType\\nfrom models.pkmn.natures.PokemonNature import PokemonNature\\nfrom models.game.trainer.utils.ArenaBadge import ArenaBadge\\n\\n\\nclass TestPokemonTrainer(TestCase):\\n\\n def setUp(self) -> None:\\n self.Pikachu = PokemonModel(\\n name=\\\"Pikachu\\\",\\n types=(PokemonType.Electric, None),\\n level=100,\\n nature=PokemonNature.Jolly,\\n moves=[\\n PokemonMove(\\n name=\\\"Volt Tackle\\\",\\n move_type=PokemonType.Electric,\\n category=MoveCategory.Physical,\\n pp=24,\\n power=120\\n ),\\n PokemonMove(\\n name=\\\"Iron Tail\\\",\\n move_type=PokemonType.Steel,\\n category=MoveCategory.Physical,\\n pp=24,\\n power=100,\\n accuracy=75\\n ),\\n PokemonMove(\\n name=\\\"Thunderbolt\\\",\\n move_type=PokemonType.Electric,\\n category=MoveCategory.Special,\\n pp=24,\\n power=90\\n )\\n ],\\n base_stats=StatsDict(hp=35, atk=55, phys_def=40, spe_atk=50, spe_def=50, spd=90),\\n evs=StatsDict(hp=0, atk=252, phys_def=0, spe_atk=4, spe_def=0, spd=252),\\n ivs=StatsDict(hp=31, atk=31, phys_def=31, spe_atk=31, spe_def=31, spd=31)\\n )\\n self.Charizard = PokemonModel(\\n name=\\\"Charizard\\\",\\n types=(PokemonType.Fire, PokemonType.Flying),\\n level=100,\\n nature=PokemonNature.Jolly,\\n moves=[\\n PokemonMove(\\n name=\\\"Fire Blast\\\",\\n move_type=PokemonType.Fire,\\n category=MoveCategory.Special,\\n pp=8,\\n power=110,\\n accuracy=85\\n ),\\n PokemonMove(\\n name=\\\"Hurricane\\\",\\n move_type=PokemonType.Flying,\\n category=MoveCategory.Special,\\n pp=16,\\n power=110,\\n accuracy=70\\n )\\n ],\\n base_stats=StatsDict(hp=78, atk=84, phys_def=78, spe_atk=109, spe_def=85, spd=100),\\n evs=StatsDict(hp=0, atk=0, phys_def=0, spe_atk=252, spe_def=4, spd=252),\\n ivs=StatsDict(hp=31, atk=31, phys_def=31, spe_atk=31, spe_def=31, spd=31)\\n )\\n self.Red = PokemonTrainer(\\n name=\\\"Red\\\",\\n team=[self.Pikachu, self.Charizard],\\n badges=[ArenaBadge.Boulder, ArenaBadge.Cascade, ArenaBadge.Thunder, ArenaBadge.Rainbow,\\n ArenaBadge.Soul, ArenaBadge.Marsh, ArenaBadge.Marsh, ArenaBadge.Earth]\\n )\\n\\n def testPokemonTrainer(self):\\n assert self.Red.team[0] == self.Pikachu\\n assert self.Red.team[1] == self.Charizard\\n assert self.Red.team[2] is None and self.Red.team[5] is None\\n assert self.Red.badges == [ArenaBadge.Boulder, ArenaBadge.Cascade, ArenaBadge.Thunder, ArenaBadge.Rainbow,\\n ArenaBadge.Soul, ArenaBadge.Marsh, ArenaBadge.Marsh, ArenaBadge.Earth]\\n\"\n },\n {\n \"alpha_fraction\": 0.4969214200973511,\n \"alphanum_fraction\": 0.541832685470581,\n \"avg_line_length\": 40.83333206176758,\n \"blob_id\": \"3800ad9560142d58301516486fd9b6dde3b697e1\",\n \"content_id\": \"b88026726652f9bc3c9130c07f302cbefe4f6c8d\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 2761,\n \"license_type\": \"permissive\",\n \"max_line_length\": 107,\n \"num_lines\": 66,\n \"path\": \"/tests/models/pkmn/test_PokemonModel.py\",\n \"repo_name\": \"LiquidNalee/MiniPkmnShowdown\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from unittest import TestCase\\nfrom models.pkmn.PokemonModel import PokemonModel\\nfrom models.pkmn.moves.PokemonMove import PokemonMove, MoveCategory\\nfrom models.pkmn.types.PokemonType import PokemonType, type_equals\\nfrom models.pkmn.natures.PokemonNature import PokemonNature\\nfrom models.pkmn.stats.StatsDict import StatsDict\\n\\n\\nclass TestPokemonModel(TestCase):\\n\\n def test_pokemon_model(self):\\n scizor = PokemonModel(\\n name=\\\"Scizor\\\",\\n types=(PokemonType.Bug, PokemonType.Steel),\\n level=100,\\n nature=PokemonNature.Adamant,\\n moves=[\\n PokemonMove(\\n name=\\\"Bullet Punch\\\",\\n move_type=PokemonType.Steel,\\n category=MoveCategory.Physical,\\n pp=48,\\n power=40,\\n priority=1\\n ),\\n PokemonMove(\\n name=\\\"U-Turn\\\",\\n move_type=PokemonType.Bug,\\n category=MoveCategory.Physical,\\n pp=32,\\n power=70\\n ),\\n PokemonMove(\\n name=\\\"Steel Beam\\\",\\n move_type=PokemonType.Steel,\\n category=MoveCategory.Special,\\n pp=8,\\n power=140,\\n accuracy=95\\n ),\\n PokemonMove(\\n name=\\\"Swords Dance\\\",\\n move_type=PokemonType.Normal,\\n category=MoveCategory.Status,\\n pp=32,\\n effect_rate=100,\\n self_stat_mod=StatsDict(atk=2)\\n )\\n ],\\n base_stats=StatsDict(hp=70, atk=130, phys_def=100, spe_atk=55, spe_def=80, spd=65),\\n evs=StatsDict(hp=120, atk=252, phys_def=0, spe_atk=0, spe_def=0, spd=136),\\n ivs=StatsDict(hp=31, atk=31, phys_def=31, spe_atk=31, spe_def=31, spd=31)\\n )\\n\\n assert scizor.name == \\\"Scizor\\\"\\n assert type_equals(scizor.type, (PokemonType.Steel, PokemonType.Bug))\\n assert scizor.level == 100\\n assert scizor._nature == PokemonNature.Adamant\\n assert not scizor._nature == PokemonNature.Jolly\\n assert scizor.base_stats == StatsDict(hp=70, atk=130, phys_def=100, spe_atk=55, spe_def=80, spd=65)\\n assert scizor.base_stats.atk == 130\\n assert scizor._evs == StatsDict(hp=120, atk=252, phys_def=0, spe_atk=0, spe_def=0, spd=136)\\n assert scizor._ivs == StatsDict(hp=31, atk=31, phys_def=31, spe_atk=31, spe_def=31, spd=31)\\n\\n expected_stat_values = StatsDict(hp=311, atk=394, phys_def=236, spe_atk=131, spe_def=196, spd=200)\\n assert scizor.stats == expected_stat_values\\n\"\n },\n {\n \"alpha_fraction\": 0.5978332757949829,\n \"alphanum_fraction\": 0.6360822319984436,\n \"avg_line_length\": 41.271026611328125,\n \"blob_id\": \"37435514e7c23d33377737ec64d839fe4b09ea0b\",\n \"content_id\": \"18c9af6c1f1a3f6f84b893fbf28a5befe06a7632\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 4523,\n \"license_type\": \"permissive\",\n \"max_line_length\": 108,\n \"num_lines\": 107,\n \"path\": \"/tests/models/pkmn/test_PokemonBaseModel.py\",\n \"repo_name\": \"LiquidNalee/MiniPkmnShowdown\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from unittest import TestCase\\nfrom models.pkmn.PokemonBaseModel import PokemonBaseModel\\nfrom models.pkmn.types.PokemonType import PokemonType, type_equals\\nfrom models.pkmn.stats.StatsDict import StatsDict\\n\\n\\nclass TestPokemonBaseModel(TestCase):\\n\\n def test_double_type_pokemon(self):\\n scizor = PokemonBaseModel(\\n name=\\\"Scizor\\\",\\n types=(PokemonType.Bug, PokemonType.Steel),\\n base_stats=StatsDict(hp=70, atk=130, phys_def=100, spe_atk=55, spe_def=80, spd=65)\\n )\\n\\n assert scizor.name == \\\"Scizor\\\"\\n assert type_equals(scizor.type, (PokemonType.Bug, PokemonType.Steel))\\n assert scizor.base_stats == StatsDict(hp=70, atk=130, phys_def=100, spe_atk=55, spe_def=80, spd=65)\\n assert scizor.base_stats.atk == 130\\n\\n def test_double_type_pokemon_valid_comparison(self):\\n scizor = PokemonBaseModel(\\n name=\\\"Scizor\\\",\\n types=(PokemonType.Bug, PokemonType.Steel),\\n base_stats=StatsDict(hp=70, atk=130, phys_def=100, spe_atk=55, spe_def=80, spd=65)\\n )\\n\\n definitely_not_scizor = PokemonBaseModel(\\n name=\\\"Scizor\\\",\\n types=(PokemonType.Steel, PokemonType.Bug),\\n base_stats=StatsDict(hp=70, atk=130, phys_def=100, spe_atk=55, spe_def=80, spd=65)\\n )\\n\\n assert scizor.name == definitely_not_scizor.name\\n assert type_equals(scizor.type, definitely_not_scizor.type)\\n assert scizor.base_stats == definitely_not_scizor.base_stats\\n assert scizor.base_stats.atk == definitely_not_scizor.base_stats.atk\\n assert scizor == definitely_not_scizor\\n\\n def test_double_type_pokemon_invalid_comparison(self):\\n scizor = PokemonBaseModel(\\n name=\\\"Scizor\\\",\\n types=(PokemonType.Bug, PokemonType.Steel),\\n base_stats=StatsDict(hp=70, atk=130, phys_def=100, spe_atk=55, spe_def=80, spd=65)\\n )\\n\\n crawdaunt = PokemonBaseModel(\\n name=\\\"Crawdaunt\\\",\\n types=(PokemonType.Water, PokemonType.Dark),\\n base_stats=StatsDict(hp=63, atk=130, phys_def=85, spe_atk=90, spe_def=55, spd=55)\\n )\\n\\n assert scizor.name != crawdaunt.name\\n assert not type_equals(scizor.type, crawdaunt.type)\\n assert scizor.base_stats != crawdaunt.base_stats\\n assert scizor.base_stats.atk == crawdaunt.base_stats.atk\\n assert scizor != crawdaunt\\n\\n def test_simple_type_pokemon(self):\\n blissey = PokemonBaseModel(\\n name=\\\"Blissey\\\",\\n types=(PokemonType.Normal, None),\\n base_stats=StatsDict(hp=255, atk=10, phys_def=10, spe_atk=75, spe_def=135, spd=55)\\n )\\n\\n assert blissey.name == \\\"Blissey\\\"\\n assert type_equals(blissey.type, (PokemonType.Normal, None))\\n assert blissey.base_stats == StatsDict(hp=255, atk=10, phys_def=10, spe_atk=75, spe_def=135, spd=55)\\n assert blissey.base_stats.hp == 255\\n\\n def test_simple_type_pokemon_valid_comparison(self):\\n blissey = PokemonBaseModel(\\n name=\\\"Blissey\\\",\\n types=(PokemonType.Normal, None),\\n base_stats=StatsDict(hp=255, atk=10, phys_def=10, spe_atk=75, spe_def=135, spd=55)\\n )\\n\\n definitely_not_blissey = PokemonBaseModel(\\n name=\\\"Blissey\\\",\\n types=(None, PokemonType.Normal),\\n base_stats=StatsDict(hp=255, atk=10, phys_def=10, spe_atk=75, spe_def=135, spd=55)\\n )\\n\\n assert blissey.name == definitely_not_blissey.name\\n assert type_equals(blissey.type, definitely_not_blissey.type)\\n assert blissey.base_stats == definitely_not_blissey.base_stats\\n assert blissey.base_stats.atk == definitely_not_blissey.base_stats.atk\\n assert blissey == definitely_not_blissey\\n\\n def test_simple_type_pokemon_invalid_comparison(self):\\n blissey = PokemonBaseModel(\\n name=\\\"Blissey\\\",\\n types=(PokemonType.Normal, None),\\n base_stats=StatsDict(hp=255, atk=10, phys_def=10, spe_atk=75, spe_def=135, spd=55)\\n )\\n\\n barraskewda = PokemonBaseModel(\\n name=\\\"Barraskewda\\\",\\n types=(PokemonType.Water, None),\\n base_stats=StatsDict(hp=61, atk=123, phys_def=60, spe_atk=60, spe_def=50, spd=136)\\n )\\n\\n assert blissey.name != barraskewda.name\\n assert not type_equals(blissey.type, barraskewda.type)\\n assert blissey.base_stats != barraskewda.base_stats\\n assert blissey.base_stats.atk != barraskewda.base_stats.atk\\n assert blissey != barraskewda\\n\"\n },\n {\n \"alpha_fraction\": 0.5142965912818909,\n \"alphanum_fraction\": 0.5432710647583008,\n \"avg_line_length\": 40.96799850463867,\n \"blob_id\": \"1a011e917beb88a49cd39fe9430fad2c2e1c0e89\",\n \"content_id\": \"afbe8def605979165cb2d74d9f5f358ae73d9cc9\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 5246,\n \"license_type\": \"permissive\",\n \"max_line_length\": 119,\n \"num_lines\": 125,\n \"path\": \"/tests/engine/game/test_BattleEngine.py\",\n \"repo_name\": \"LiquidNalee/MiniPkmnShowdown\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import builtins\\nfrom unittest import TestCase\\nimport mock\\n\\nfrom engine.game import InputHandler\\nfrom engine.game.BattleEngine import BattleEngine\\nfrom engine.pkmn.types.ClassicTypesRuleSet import ClassicTypesRuleSet\\nfrom models.game.battle.BattleGameState import BattleGameState\\nfrom models.game.trainer.PokemonTrainer import PokemonTrainer\\nfrom models.game.trainer.utils.ArenaBadge import ArenaBadge\\nfrom models.pkmn.PokemonModel import PokemonModel\\nfrom models.pkmn.moves.PokemonMove import PokemonMove, MoveCategory\\nfrom models.pkmn.natures.PokemonNature import PokemonNature\\nfrom models.pkmn.stats.StatsDict import StatsDict\\nfrom models.pkmn.types.PokemonType import PokemonType\\n\\n\\nclass TestBattleEngine(TestCase):\\n\\n def setUp(self) -> None:\\n self.Pikachu = PokemonModel(\\n name=\\\"Pikachu\\\",\\n types=(PokemonType.Electric, None),\\n level=100,\\n nature=PokemonNature.Jolly,\\n moves=[\\n PokemonMove(\\n name=\\\"Volt Tackle\\\",\\n move_type=PokemonType.Electric,\\n category=MoveCategory.Physical,\\n pp=24,\\n power=120\\n ),\\n PokemonMove(\\n name=\\\"Iron Tail\\\",\\n move_type=PokemonType.Steel,\\n category=MoveCategory.Physical,\\n pp=24,\\n power=100,\\n accuracy=75\\n ),\\n PokemonMove(\\n name=\\\"Thunderbolt\\\",\\n move_type=PokemonType.Electric,\\n category=MoveCategory.Special,\\n pp=24,\\n power=90\\n )\\n ],\\n base_stats=StatsDict(hp=35, atk=55, phys_def=40, spe_atk=50, spe_def=50, spd=90),\\n evs=StatsDict(hp=0, atk=252, phys_def=0, spe_atk=4, spe_def=0, spd=252),\\n ivs=StatsDict(hp=31, atk=31, phys_def=31, spe_atk=31, spe_def=31, spd=31)\\n )\\n self.Pidgeot = PokemonModel(\\n name=\\\"Pidgeot\\\",\\n types=(PokemonType.Flying, PokemonType.Normal),\\n level=100,\\n nature=PokemonNature.Jolly,\\n moves=[\\n PokemonMove(\\n name=\\\"Double Edge\\\",\\n move_type=PokemonType.Normal,\\n category=MoveCategory.Physical,\\n pp=24,\\n power=120\\n ),\\n PokemonMove(\\n name=\\\"Brave Bird\\\",\\n move_type=PokemonType.Flying,\\n category=MoveCategory.Physical,\\n pp=24,\\n power=120\\n )\\n ],\\n base_stats=StatsDict(hp=83, atk=80, phys_def=75, spe_atk=70, spe_def=70, spd=101),\\n evs=StatsDict(hp=0, atk=252, phys_def=0, spe_atk=0, spe_def=4, spd=252),\\n ivs=StatsDict(hp=31, atk=31, phys_def=31, spe_atk=31, spe_def=31, spd=31)\\n )\\n self.Blastoise = PokemonModel(\\n name=\\\"Blastoise\\\",\\n types=(PokemonType.Water, None),\\n level=100,\\n nature=PokemonNature.Modest,\\n moves=[\\n PokemonMove(\\n name=\\\"Hydro Pump\\\",\\n move_type=PokemonType.Water,\\n category=MoveCategory.Special,\\n pp=8,\\n power=110,\\n accuracy=80\\n ),\\n PokemonMove(\\n name=\\\"Ice Beam\\\",\\n move_type=PokemonType.Ice,\\n category=MoveCategory.Special,\\n pp=16,\\n power=90\\n )\\n ],\\n base_stats=StatsDict(hp=79, atk=83, phys_def=100, spe_atk=85, spe_def=105, spd=78),\\n evs=StatsDict(hp=252, atk=0, phys_def=0, spe_atk=252, spe_def=4, spd=0),\\n ivs=StatsDict(hp=31, atk=31, phys_def=31, spe_atk=31, spe_def=31, spd=31)\\n )\\n self.Red = PokemonTrainer(\\n name=\\\"Red\\\",\\n team=[self.Pikachu],\\n badges=[ArenaBadge.Boulder, ArenaBadge.Cascade, ArenaBadge.Thunder, ArenaBadge.Rainbow,\\n ArenaBadge.Soul, ArenaBadge.Marsh, ArenaBadge.Marsh, ArenaBadge.Earth]\\n )\\n self.Blue = PokemonTrainer(\\n name=\\\"Blue\\\",\\n team=[self.Pidgeot, self.Blastoise],\\n badges=[ArenaBadge.Boulder, ArenaBadge.Cascade, ArenaBadge.Thunder, ArenaBadge.Rainbow,\\n ArenaBadge.Soul, ArenaBadge.Marsh, ArenaBadge.Marsh, ArenaBadge.Earth]\\n )\\n self.BattleGameState = BattleGameState(player=self.Red, opponent=self.Blue)\\n\\n def test_red_blue_battle(self):\\n with mock.patch.object(InputHandler, 'getCancelableNumberInput', return_value=0):\\n with mock.patch.object(InputHandler, 'getNumberInput', return_value=0):\\n with mock.patch.object(InputHandler, 'getDecisionType', return_value='m'):\\n with mock.patch.object(builtins, 'input', return_value=''):\\n engine = BattleEngine(battleGameState=self.BattleGameState, typesRuleSet=ClassicTypesRuleSet())\\n assert not engine.startGame()\\n\"\n },\n {\n \"alpha_fraction\": 0.5457690358161926,\n \"alphanum_fraction\": 0.5751765966415405,\n \"avg_line_length\": 37.97190856933594,\n \"blob_id\": \"f8f45e1e151f7b12d136629e7ba7b33ce6b2320b\",\n \"content_id\": \"2ff07a9a51b2b151e410045e5b43264302815449\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 6937,\n \"license_type\": \"permissive\",\n \"max_line_length\": 118,\n \"num_lines\": 178,\n \"path\": \"/miniShowdown.py\",\n \"repo_name\": \"LiquidNalee/MiniPkmnShowdown\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from argparse import ArgumentParser\\nfrom json import load\\n\\nfrom database.DatabaseConfig import updatePkmnDatabase, updateMoveDatabase\\n\\nfrom engine.game.BattleEngine import BattleEngine\\nfrom engine.pkmn.types.ClassicTypesRuleSet import ClassicTypesRuleSet\\nfrom models.game.battle.BattleGameState import BattleGameState\\nfrom models.game.trainer.PokemonTrainer import PokemonTrainer\\nfrom models.game.trainer.utils.ArenaBadge import ArenaBadge\\nfrom models.pkmn.PokemonModel import PokemonModel\\nfrom models.pkmn.moves.PokemonMove import PokemonMove, MoveCategory\\nfrom models.pkmn.natures.PokemonNature import PokemonNature\\nfrom models.pkmn.stats.StatsDict import StatsDict\\nfrom models.pkmn.types.PokemonType import PokemonType\\n\\nparser = ArgumentParser()\\nparser.add_argument(\\\"--update_db\\\", \\\"-u\\\", help=\\\"Fill out Pkmn info as json in database folder for future use\\\",\\n type=bool, required=False)\\nparser.add_argument(\\\"--player_trainer_json\\\", \\\"-p\\\", help=\\\"Path to player's pokemon trainer json\\\",\\n type=str, required=False)\\nparser.add_argument(\\\"--opponent_trainer_json\\\", \\\"-o\\\", help=\\\"Path to opponent's pokemon trainer json\\\",\\n type=str, required=False)\\nargs = parser.parse_args()\\n\\n\\ndef setUpDefaultTeams():\\n pikachu = PokemonModel(\\n name=\\\"Pikachu\\\",\\n types=(PokemonType.Electric, None),\\n level=100,\\n nature=PokemonNature.Jolly,\\n moves=[\\n PokemonMove(\\n name=\\\"Volt Tackle\\\",\\n move_type=PokemonType.Electric,\\n category=MoveCategory.Physical,\\n pp=24,\\n power=120\\n ),\\n PokemonMove(\\n name=\\\"Iron Tail\\\",\\n move_type=PokemonType.Steel,\\n category=MoveCategory.Physical,\\n pp=24,\\n power=100,\\n accuracy=75\\n ),\\n PokemonMove(\\n name=\\\"Thunderbolt\\\",\\n move_type=PokemonType.Electric,\\n category=MoveCategory.Special,\\n pp=24,\\n power=90\\n )\\n ],\\n base_stats=StatsDict(hp=35, atk=55, phys_def=40, spe_atk=50, spe_def=50, spd=90),\\n evs=StatsDict(hp=0, atk=252, phys_def=0, spe_atk=4, spe_def=0, spd=252),\\n ivs=StatsDict(hp=31, atk=31, phys_def=31, spe_atk=31, spe_def=31, spd=31)\\n )\\n charizard = PokemonModel(\\n name=\\\"Charizard\\\",\\n types=(PokemonType.Fire, PokemonType.Flying),\\n level=100,\\n nature=PokemonNature.Jolly,\\n moves=[\\n PokemonMove(\\n name=\\\"Fire Blast\\\",\\n move_type=PokemonType.Fire,\\n category=MoveCategory.Special,\\n pp=8,\\n power=110,\\n accuracy=85\\n ),\\n PokemonMove(\\n name=\\\"Hurricane\\\",\\n move_type=PokemonType.Flying,\\n category=MoveCategory.Special,\\n pp=16,\\n power=110,\\n accuracy=70\\n )\\n ],\\n base_stats=StatsDict(hp=78, atk=84, phys_def=78, spe_atk=109, spe_def=85, spd=100),\\n evs=StatsDict(hp=0, atk=0, phys_def=0, spe_atk=252, spe_def=4, spd=252),\\n ivs=StatsDict(hp=31, atk=31, phys_def=31, spe_atk=31, spe_def=31, spd=31)\\n )\\n pidgeot = PokemonModel(\\n name=\\\"Pidgeot\\\",\\n types=(PokemonType.Flying, PokemonType.Normal),\\n level=100,\\n nature=PokemonNature.Jolly,\\n moves=[\\n PokemonMove(\\n name=\\\"Double Edge\\\",\\n move_type=PokemonType.Normal,\\n category=MoveCategory.Physical,\\n pp=24,\\n power=120\\n ),\\n PokemonMove(\\n name=\\\"Brave Bird\\\",\\n move_type=PokemonType.Flying,\\n category=MoveCategory.Physical,\\n pp=24,\\n power=120\\n )\\n ],\\n base_stats=StatsDict(hp=83, atk=80, phys_def=75, spe_atk=70, spe_def=70, spd=101),\\n evs=StatsDict(hp=0, atk=252, phys_def=0, spe_atk=0, spe_def=4, spd=252),\\n ivs=StatsDict(hp=31, atk=31, phys_def=31, spe_atk=31, spe_def=31, spd=31)\\n )\\n blastoise = PokemonModel(\\n name=\\\"Blastoise\\\",\\n types=(PokemonType.Water, None),\\n level=100,\\n nature=PokemonNature.Modest,\\n moves=[\\n PokemonMove(\\n name=\\\"Hydro Pump\\\",\\n move_type=PokemonType.Water,\\n category=MoveCategory.Special,\\n pp=8,\\n power=110,\\n accuracy=80\\n ),\\n PokemonMove(\\n name=\\\"Ice Beam\\\",\\n move_type=PokemonType.Ice,\\n category=MoveCategory.Special,\\n pp=16,\\n power=90\\n )\\n ],\\n base_stats=StatsDict(hp=79, atk=83, phys_def=100, spe_atk=85, spe_def=105, spd=78),\\n evs=StatsDict(hp=252, atk=0, phys_def=0, spe_atk=252, spe_def=4, spd=0),\\n ivs=StatsDict(hp=31, atk=31, phys_def=31, spe_atk=31, spe_def=31, spd=31)\\n )\\n red = PokemonTrainer(\\n name=\\\"Red\\\",\\n team=[pikachu, charizard],\\n badges=[ArenaBadge.Boulder, ArenaBadge.Cascade, ArenaBadge.Thunder, ArenaBadge.Rainbow,\\n ArenaBadge.Soul, ArenaBadge.Marsh, ArenaBadge.Marsh, ArenaBadge.Earth]\\n )\\n blue = PokemonTrainer(\\n name=\\\"Blue\\\",\\n team=[pidgeot, blastoise],\\n badges=[ArenaBadge.Boulder, ArenaBadge.Cascade, ArenaBadge.Thunder, ArenaBadge.Rainbow,\\n ArenaBadge.Soul, ArenaBadge.Marsh, ArenaBadge.Marsh, ArenaBadge.Earth]\\n )\\n return red, blue\\n\\n\\ndef main():\\n if args.update_db:\\n updatePkmnDatabase([str(_) for _ in range(10)])\\n updateMoveDatabase([\\\"Swords Dance\\\", \\\"Meteor Mash\\\", \\\"Close Combat\\\", \\\"Mach Punch\\\", \\\"Aura Sphere\\\", \\\"Bug Bite\\\",\\n \\\"Hydro Pump\\\", \\\"Surf\\\", \\\"Waterfall\\\", \\\"Moonblast\\\", \\\"Play Rough\\\", \\\"Solar Beam\\\", \\\"Wood Hammer\\\",\\n \\\"Stone Edge\\\", \\\"Meteor Gem\\\", \\\"Sludge Bomb\\\", \\\"Poison Jab\\\", \\\"Draco Meteor\\\", \\\"Outrage\\\",\\n \\\"Dragon Dance\\\", \\\"Psychic\\\", \\\"Zen Headbutt\\\", \\\"Mystical Fire\\\", \\\"Fire Blast\\\", \\\"Flare Blitz\\\",\\n \\\"Hurricane\\\", \\\"Brave Bird\\\", \\\"Earthquake\\\", \\\"Earth Power\\\"])\\n\\n player, opponent = setUpDefaultTeams()\\n\\n if args.player_trainer_json:\\n with open(args.player_trainer_json) as player_trainer_json_file:\\n player = PokemonTrainer.fromJson(load(player_trainer_json_file))\\n if args.opponent_trainer_json:\\n with open(args.opponent_trainer_json) as opponent_trainer_json_file:\\n opponent = PokemonTrainer.fromJson(load(opponent_trainer_json_file))\\n\\n engine = BattleEngine(battleGameState=BattleGameState(player=player, opponent=opponent),\\n typesRuleSet=ClassicTypesRuleSet())\\n engine.startGame()\\n\\n\\nif __name__ == \\\"__main__\\\":\\n main()\\n\"\n },\n {\n \"alpha_fraction\": 0.5387858152389526,\n \"alphanum_fraction\": 0.5716694593429565,\n \"avg_line_length\": 24.23404312133789,\n \"blob_id\": \"7650a23911a77fc3e477c36157928db60618e627\",\n \"content_id\": \"343f5a4bf2e820b398e2200103635d6acb678983\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1186,\n \"license_type\": \"permissive\",\n \"max_line_length\": 106,\n \"num_lines\": 47,\n \"path\": \"/models/pkmn/types/PokemonType.py\",\n \"repo_name\": \"LiquidNalee/MiniPkmnShowdown\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from enum import Enum\\nfrom re import sub\\n\\n\\nclass PokemonType(Enum):\\n Normal = 1\\n Fighting = 2\\n Flying = 3\\n Poison = 4\\n Ground = 5\\n Rock = 6\\n Bug = 7\\n Ghost = 8\\n Psychic = 9\\n Grass = 10\\n Fire = 11\\n Water = 12\\n Electric = 13\\n Ice = 14\\n Dragon = 15\\n Steel = 16\\n Dark = 17\\n Fairy = 18\\n\\n def __lt__(self, other):\\n if self.__class__ != other.__class__:\\n return NotImplementedError\\n return self.value < other.value\\n\\n def __str__(self):\\n return sub(\\\"PokemonType\\\\\\\\.\\\", \\\"\\\", super().__str__())\\n\\n\\ndef format_types_tuple(types: (PokemonType, PokemonType)):\\n if types[0] is None:\\n if types[1] is None:\\n raise Exception(\\\"PokemonBaseModel - init: Unhandled type (None; None)\\\")\\n else:\\n return types[1], None\\n else:\\n if types[0] == types[1]:\\n raise Exception(f\\\"PokemonBaseModel - init: Unhandled type ({str(types[0])}; {str(types[1])})\\\")\\n return types if types[1] is None or types[0] < types[1] else (types[1], types[0])\\n\\n\\ndef type_equals(self, other: (PokemonType, PokemonType)):\\n return format_types_tuple(self) == format_types_tuple(other)\\n\"\n },\n {\n \"alpha_fraction\": 0.6798893213272095,\n \"alphanum_fraction\": 0.6881918907165527,\n \"avg_line_length\": 37.71428680419922,\n \"blob_id\": \"d3ffcb376c94525d59eb73a4840fa904c2c46a14\",\n \"content_id\": \"8d202128c06a12dfc60c761811fd0a24f9121a0c\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 2168,\n \"license_type\": \"permissive\",\n \"max_line_length\": 113,\n \"num_lines\": 56,\n \"path\": \"/engine/game/BattleDisplay.py\",\n \"repo_name\": \"LiquidNalee/MiniPkmnShowdown\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from re import sub, M\\nfrom models.game.battle.BattleGameState import BattleGameState\\nfrom models.pkmn.PokemonModel import PokemonModel\\nfrom models.pkmn.moves.PokemonMove import PokemonMove\\n\\n__separation_line = '-'.join('' for _ in range(150))\\n\\n\\ndef __shiftDisplayBox(box: str, shift: int):\\n return sub(\\\"^\\\", \\\"\\\\t\\\".join(\\\"\\\" for _ in range(shift)), box, flags=M)\\n\\n\\ndef __displaySideBySide(box_1: str, box_2: str):\\n split_lines = (box_1.splitlines(), box_2.splitlines())\\n print(\\\"\\\\n\\\".join([f\\\"{split_lines[0][_]:<50}{split_lines[1][_]:>50}\\\" for _ in range(len(split_lines[0]))]))\\n\\n\\ndef displayPlayers(battleGameState: BattleGameState):\\n __displaySideBySide(str(battleGameState.player), str(battleGameState.opponent))\\n\\n\\ndef displayBattleGameState(battleGameState: BattleGameState):\\n displayPlayers(battleGameState)\\n print(f\\\"Turn: {battleGameState.turn}\\\\n\\\")\\n __displaySideBySide(str(battleGameState.getPlayerActivePkmn()), str(battleGameState.getOpponentActivePkmn()))\\n print(f\\\"{__separation_line}\\\")\\n print(battleGameState.getPlayerActivePkmn().moveListAsStr())\\n print(f\\\"{__separation_line}\\\")\\n\\n\\ndef displayUsedMove(caster: PokemonModel, caster_move: PokemonMove, trgt: PokemonModel,\\n type_effectiveness: float, damage: int):\\n print(f\\\"{caster.name} uses {caster_move.name}\\\")\\n if type_effectiveness != 1:\\n print(\\\"It's super effective!\\\" if type_effectiveness > 1\\n else f\\\"It doesn't affect {trgt.name}\\\" if type_effectiveness == 0\\n else \\\"It's not very effective...\\\")\\n if damage != 0:\\n print(f\\\"{trgt.name} loses {damage} HP\\\")\\n if trgt.isKO():\\n print(f\\\"{trgt.name} is K.O !\\\")\\n input()\\n\\n\\ndef displaySwitch(player_name: str, out: PokemonModel, coming_in: PokemonModel):\\n print(f\\\"{out.name} goes back into its PokeBall.\\\")\\n print(f\\\"{player_name} sends {coming_in.name} out !\\\")\\n input()\\n\\n\\ndef displayEndOfBattle(win: bool, battleGameState: BattleGameState):\\n print(\\\"# Finished #\\\")\\n displayPlayers(battleGameState)\\n print(f\\\"Winner: {battleGameState.player.name if win else battleGameState.opponent.name}\\\")\\n print(f\\\"{'-'.join(__separation_line)}\\\")\\n input()\\n\"\n },\n {\n \"alpha_fraction\": 0.6985074877738953,\n \"alphanum_fraction\": 0.7008955478668213,\n \"avg_line_length\": 39.85365676879883,\n \"blob_id\": \"438e0de04a4cd506c9b73a3bb09b9af06e069f68\",\n \"content_id\": \"07b0a88620977d804617a27caf0dbc68f04679e6\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1675,\n \"license_type\": \"permissive\",\n \"max_line_length\": 79,\n \"num_lines\": 41,\n \"path\": \"/models/game/battle/BattleGameState.py\",\n \"repo_name\": \"LiquidNalee/MiniPkmnShowdown\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from models.game.trainer.PokemonTrainer import PokemonTrainer\\nfrom models.pkmn.PokemonModel import PokemonModel\\nfrom models.pkmn.moves.PokemonMove import PokemonMove\\n\\n\\nclass BattleGameState:\\n\\n def __init__(self, player: PokemonTrainer, opponent: PokemonTrainer):\\n self.turn = 1\\n self.player = player.makeCopy()\\n self.__player_active_pkmn_slot = 0\\n self.player_move_selection = None\\n self.opponent = opponent.makeCopy()\\n self.opponent_move_selection = None\\n self.__opponent_active_pkmn_slot = 0\\n\\n def getPlayerActivePkmn(self) -> PokemonModel:\\n return self.player.team[self.__player_active_pkmn_slot]\\n\\n def setPlayerActivePkmn(self, index: int) -> PokemonModel:\\n self.__player_active_pkmn_slot = index\\n return self.player.team[self.__player_active_pkmn_slot]\\n\\n def getOpponentActivePkmn(self) -> PokemonModel:\\n return self.opponent.team[self.__opponent_active_pkmn_slot]\\n\\n def setOpponentActivePkmn(self, index: int) -> PokemonModel:\\n self.__opponent_active_pkmn_slot = index\\n return self.opponent.team[self.__opponent_active_pkmn_slot]\\n\\n def sendNextOpponentActivePkmn(self) -> PokemonModel:\\n self.__opponent_active_pkmn_slot += 1\\n return self.opponent.team[self.__opponent_active_pkmn_slot]\\n\\n def getTurnState(self):\\n return (self.getPlayerActivePkmn(), self.player_move_selection),\\\\\\n (self.getOpponentActivePkmn(), self.opponent_move_selection)\\n\\n def setTurnState(self, plyr_move: PokemonMove, opponent_move: PokemonMove):\\n self.player_move_selection = plyr_move\\n self.opponent_move_selection = opponent_move\\n\"\n },\n {\n \"alpha_fraction\": 0.5681179761886597,\n \"alphanum_fraction\": 0.5730336904525757,\n \"avg_line_length\": 37.486488342285156,\n \"blob_id\": \"c6787e6d18561174603430d8f5be3cdee7ae0515\",\n \"content_id\": \"b059d225782a761fe809c888cc8d5da86be95347\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1424,\n \"license_type\": \"permissive\",\n \"max_line_length\": 100,\n \"num_lines\": 37,\n \"path\": \"/models/game/trainer/PokemonTrainer.py\",\n \"repo_name\": \"LiquidNalee/MiniPkmnShowdown\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from typing import List\\nfrom models.game.trainer.utils.ArenaBadge import ArenaBadge\\n\\nfrom models.pkmn.PokemonModel import PokemonModel\\n\\n\\nclass PokemonTrainer:\\n\\n def __init__(self, name: str, team: List[PokemonModel], badges: List[ArenaBadge]):\\n self.name = name\\n self.team = [team[i] if i < len(team) else None for i in range(6)]\\n self.badges = list(badges)\\n self.badges.sort()\\n\\n def __str__(self):\\n team_str_list = [f\\\"{x}. {self.team[x].name} ({self.team[x].stats.hp}/{self.team[x].max_hp})\\\"\\n for x in range(len(self.team)) if self.team[x] is not None]\\n return f\\\"Trainer: {self.name}\\\\n\\\" \\\\\\n f\\\"{' - '.join(team_str_list[0:2])}\\\\n\\\" \\\\\\n f\\\"{' - '.join(team_str_list[2:4])}\\\\n\\\" \\\\\\n f\\\"{' - '.join(team_str_list[4:6])}\\\\n\\\"\\n\\n def hasLost(self):\\n return all(pkmn.isKO() if pkmn is not None else True for pkmn in self.team)\\n\\n def makeCopy(self):\\n return PokemonTrainer(name=self.name, team=list(self.team), badges=list(self.badges))\\n\\n @staticmethod\\n def fromJson(json: {}):\\n if \\\"name\\\" in json and \\\"team\\\" in json:\\n return PokemonTrainer(\\n name=json[\\\"name\\\"],\\n team=[PokemonModel.fromJson(json[\\\"team\\\"][_]) for _ in json[\\\"team\\\"]],\\n badges=[]\\n )\\n raise AttributeError(\\\"PokemonTrainer - fromJson: Invalid JSON Input\\\")\\n\"\n },\n {\n \"alpha_fraction\": 0.729411780834198,\n \"alphanum_fraction\": 0.7326797246932983,\n \"avg_line_length\": 49.16393280029297,\n \"blob_id\": \"0d3fd58d8049f1cb8f7db401db8a97237491bf3b\",\n \"content_id\": \"8876830097963204fb93a583be0a14fa2161bbdb\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 3060,\n \"license_type\": \"permissive\",\n \"max_line_length\": 116,\n \"num_lines\": 61,\n \"path\": \"/models/pkmn/natures/PokemonNature.py\",\n \"repo_name\": \"LiquidNalee/MiniPkmnShowdown\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from enum import Enum\\n\\nfrom models.pkmn.stats.StatsDict import StatsDict\\n\\n\\n# Bonus/Malus percentage from natures\\nnature_base_modifier = 100\\nnature_bonus = 10\\nnature_bonus_modifier = nature_base_modifier + nature_bonus\\nnature_malus = 10\\nnature_malus_modifier = nature_base_modifier - nature_malus\\n\\n\\nclass _PokemonNatureImplm:\\n\\n def __init__(self, hp: int = nature_base_modifier,\\n atk: int = nature_base_modifier, phys_def: int = nature_base_modifier,\\n spe_atk: int = nature_base_modifier, spe_def: int = nature_base_modifier,\\n spd: int = nature_base_modifier):\\n super().__init__()\\n self.__stats_table = StatsDict(hp=hp, atk=atk, phys_def=phys_def, spe_atk=spe_atk, spe_def=spe_def, spd=spd)\\n\\n def apply_modifier(self, stats: StatsDict):\\n for stat_key in self.__stats_table.__dict__.keys():\\n stats[stat_key] *= self.__stats_table[stat_key] / 100\\n\\n\\nclass PokemonNature(Enum):\\n Lonely = _PokemonNatureImplm(atk=nature_bonus_modifier, phys_def=nature_malus_modifier)\\n Adamant = _PokemonNatureImplm(atk=nature_bonus_modifier, spe_atk=nature_malus_modifier)\\n Naughty = _PokemonNatureImplm(atk=nature_bonus_modifier, spe_def=nature_malus_modifier)\\n Brave = _PokemonNatureImplm(atk=nature_bonus_modifier, spd=nature_malus_modifier)\\n\\n Bold = _PokemonNatureImplm(phys_def=nature_bonus_modifier, atk=nature_malus_modifier)\\n Impish = _PokemonNatureImplm(phys_def=nature_bonus_modifier, spe_atk=nature_malus_modifier)\\n Lax = _PokemonNatureImplm(phys_def=nature_bonus_modifier, spe_def=nature_malus_modifier)\\n Relaxed = _PokemonNatureImplm(phys_def=nature_bonus_modifier, spd=nature_malus_modifier)\\n\\n Modest = _PokemonNatureImplm(spe_atk=nature_bonus_modifier, atk=nature_malus_modifier)\\n Mild = _PokemonNatureImplm(spe_atk=nature_bonus_modifier, phys_def=nature_malus_modifier)\\n Rash = _PokemonNatureImplm(spe_atk=nature_bonus_modifier, spe_def=nature_malus_modifier)\\n Quiet = _PokemonNatureImplm(spe_atk=nature_bonus_modifier, spd=nature_malus_modifier)\\n\\n Calm = _PokemonNatureImplm(spe_def=nature_bonus_modifier, atk=nature_malus_modifier)\\n Gentle = _PokemonNatureImplm(spe_def=nature_bonus_modifier, phys_def=nature_malus_modifier)\\n Careful = _PokemonNatureImplm(spe_def=nature_bonus_modifier, spe_atk=nature_malus_modifier)\\n Sassy = _PokemonNatureImplm(spe_def=nature_bonus_modifier, spd=nature_malus_modifier)\\n\\n Timid = _PokemonNatureImplm(spd=nature_bonus_modifier, atk=nature_malus_modifier)\\n Hasty = _PokemonNatureImplm(spd=nature_bonus_modifier, phys_def=nature_malus_modifier)\\n Jolly = _PokemonNatureImplm(spd=nature_bonus_modifier, spe_atk=nature_malus_modifier)\\n Naive = _PokemonNatureImplm(spd=nature_bonus_modifier, spe_def=nature_malus_modifier)\\n\\n Quirky = _PokemonNatureImplm()\\n Docile = _PokemonNatureImplm()\\n Hardy = _PokemonNatureImplm()\\n Bashful = _PokemonNatureImplm()\\n Serious = _PokemonNatureImplm()\\n\\n def apply_modifier(self, stats: StatsDict):\\n self.value.apply_modifier(stats)\\n\"\n },\n {\n \"alpha_fraction\": 0.5120481848716736,\n \"alphanum_fraction\": 0.5192770957946777,\n \"avg_line_length\": 30.846153259277344,\n \"blob_id\": \"2a4f7584fe78e81fd9259bbf384f37c024681e68\",\n \"content_id\": \"374f8123a9618f449dc0ea8805621fc614597310\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 830,\n \"license_type\": \"permissive\",\n \"max_line_length\": 119,\n \"num_lines\": 26,\n \"path\": \"/models/pkmn/stats/StatsDict.py\",\n \"repo_name\": \"LiquidNalee/MiniPkmnShowdown\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"\\n\\nclass StatsDict:\\n\\n def __init__(self, hp: int = 0, atk: int = 0, phys_def: int = 0, spe_atk: int = 0, spe_def: int = 0, spd: int = 0):\\n self.hp = int(hp)\\n self.atk = int(atk)\\n self.phys_def = int(phys_def)\\n self.spe_atk = int(spe_atk)\\n self.spe_def = int(spe_def)\\n self.spd = int(spd)\\n\\n def __eq__(self, other):\\n if self.__class__ != other.__class__:\\n return NotImplementedError\\n return self.__dict__ == other.__dict__\\n\\n def __getitem__(self, item: str):\\n return self.__dict__[item]\\n\\n def __setitem__(self, key, value):\\n self.__dict__[key] = int(value)\\n\\n @classmethod\\n def from_json(cls, json: {}):\\n keys = cls.__dict__.keys()\\n if all(keys) in json:\\n return StatsDict(**{key: json[key] for key in keys})\\n\"\n },\n {\n \"alpha_fraction\": 0.4727272689342499,\n \"alphanum_fraction\": 0.6818181872367859,\n \"avg_line_length\": 14.857142448425293,\n \"blob_id\": \"e233bf4b74f01ad24a13050b2ac86b580e7781ab\",\n \"content_id\": \"522033f22f21144dcc803b82caa609f241df7f18\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Text\",\n \"length_bytes\": 110,\n \"license_type\": \"permissive\",\n \"max_line_length\": 22,\n \"num_lines\": 7,\n \"path\": \"/requirements.txt\",\n \"repo_name\": \"LiquidNalee/MiniPkmnShowdown\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"pandas==1.0.3\\nnumpy==1.18.2\\npython-dateutil==2.8.1\\nmock~=4.0.3\\npathlib~=1.0.1\\nrequests~=2.23.0\\nargparse~=1.4.0\"\n },\n {\n \"alpha_fraction\": 0.5749621391296387,\n \"alphanum_fraction\": 0.5790005326271057,\n \"avg_line_length\": 27.299999237060547,\n \"blob_id\": \"10099c5e6d66dbc75e0e549ee8d44af52f0079b9\",\n \"content_id\": \"6ccdb14e244394ced4c7200587cf044f4b8a7c3d\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1981,\n \"license_type\": \"permissive\",\n \"max_line_length\": 92,\n \"num_lines\": 70,\n \"path\": \"/engine/game/InputHandler.py\",\n \"repo_name\": \"LiquidNalee/MiniPkmnShowdown\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from typing import List\\n\\nfrom models.pkmn.PokemonModel import PokemonModel\\nfrom models.pkmn.moves.PokemonMove import PokemonMove\\n\\n\\ndef repeatOnError(*exceptions):\\n def checking(function):\\n def checked(*args, **kwargs):\\n while True:\\n try:\\n result = function(*args, **kwargs)\\n except exceptions as ex:\\n print(\\\"Invalid Input!\\\")\\n else:\\n return result\\n\\n return checked\\n\\n return checking\\n\\n\\n@repeatOnError(NotImplementedError)\\ndef getDecisionType():\\n i = input(\\\"Enter 'm' to use a move or 's' to switch out: \\\")\\n if i != \\\"m\\\" and i != \\\"s\\\":\\n raise NotImplementedError()\\n return i\\n\\n\\n@repeatOnError(ValueError)\\ndef getNumberInput(max_range: int):\\n i = input(f'Enter your selection (0 - {max_range - 1}): ')\\n val = int(i)\\n if val < 0 or val >= max_range:\\n raise ValueError\\n return val\\n\\n\\n@repeatOnError(ValueError)\\ndef getCancelableNumberInput(max_range: int):\\n i = input(f'Enter your selection (0 - {max_range - 1}) or Cancel (C): ')\\n if i == \\\"C\\\":\\n return -1\\n val = int(i)\\n if val < 0 or val >= max_range:\\n raise ValueError\\n return val\\n\\n\\ndef pkmnSelection(team: List[PokemonModel]) -> int:\\n print(\\\"\\\\nChoose a Pkmn.\\\")\\n while True:\\n i = getNumberInput(len([_ for _ in team if _ is not None]))\\n if team[i].isKO():\\n print(f\\\"{team[i].name} is K.O ! It cannot fight anymore...\\\")\\n else:\\n break\\n return i\\n\\n\\ndef turnDecision(active_pkmn: PokemonModel, team: List[PokemonModel]) -> (PokemonMove, int):\\n while True:\\n t = getDecisionType()\\n max_range = len([_ for _ in active_pkmn.moves if _ is not None]) if t == \\\"m\\\" \\\\\\n else len([_ for _ in team if _ is not None])\\n i = getCancelableNumberInput(max_range=max_range)\\n if i != -1:\\n break\\n return (active_pkmn.moves[i], None) if t == \\\"m\\\" else (None, i)\\n\"\n },\n {\n \"alpha_fraction\": 0.5261538624763489,\n \"alphanum_fraction\": 0.5507692098617554,\n \"avg_line_length\": 18.058822631835938,\n \"blob_id\": \"30918d05131bed246946bdd41a9591e10729e937\",\n \"content_id\": \"ae4df15d8b072d29429511e89eff6003beb102af\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 325,\n \"license_type\": \"permissive\",\n \"max_line_length\": 45,\n \"num_lines\": 17,\n \"path\": \"/models/game/trainer/utils/ArenaBadge.py\",\n \"repo_name\": \"LiquidNalee/MiniPkmnShowdown\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from enum import Enum\\n\\n\\nclass ArenaBadge(Enum):\\n Boulder = 1\\n Cascade = 2\\n Thunder = 3\\n Rainbow = 4\\n Soul = 5\\n Marsh = 6\\n Volcano = 7\\n Earth = 8\\n\\n def __lt__(self, other):\\n if self.__class__ != other.__class__:\\n return NotImplementedError\\n return self.value < other.value\\n\\n\"\n }\n]"},"num_files":{"kind":"number","value":27,"string":"27"}}},{"rowIdx":2060,"cells":{"repo_name":{"kind":"string","value":"firstcase/theSecretForest"},"repo_url":{"kind":"string","value":"https://github.com/firstcase/theSecretForest"},"snapshot_id":{"kind":"string","value":"d8ab550e357e6411fa5b0ef9b42022bee6646cf6"},"revision_id":{"kind":"string","value":"f475527cfacb85c604951d89b840a0195b88f8ba"},"directory_id":{"kind":"string","value":"69be2c21357dcd8254716c63d896905ebb6fa17f"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"string","value":"2023-01-10T01:44:14.003939"},"revision_date":{"kind":"string","value":"2020-11-06T15:54:50"},"committer_date":{"kind":"string","value":"2020-11-06T15:54:50"},"github_id":{"kind":"number","value":309050666,"string":"309,050,666"},"star_events_count":{"kind":"number","value":1,"string":"1"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.4482758641242981,"alphanum_fraction":0.5517241358757019,"avg_line_length":13.5,"blob_id":"5f38c8c5f7f685f5bbc1d4d4abe43ff39b06578e","content_id":"2316b9945ca815007a7bda3c05e1fbdd8dd2ef18","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":45,"license_type":"no_license","max_line_length":19,"num_lines":2,"path":"/README.md","repo_name":"firstcase/theSecretForest","src_encoding":"UTF-8","text":"# 비밀의 숲 프로젝트(11/1~)\nstart!!!\n"},{"alpha_fraction":0.5865615606307983,"alphanum_fraction":0.6276996731758118,"avg_line_length":29.38541603088379,"blob_id":"7040f205527aaef568cb2dcd605c280ee8a7674c","content_id":"bff0437f107b0da066c8742471220b3b069785b3","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":3121,"license_type":"no_license","max_line_length":206,"num_lines":96,"path":"/app.py","repo_name":"firstcase/theSecretForest","src_encoding":"UTF-8","text":"from flask import Flask, render_template\nimport requests\nfrom bs4 import BeautifulSoup\nfrom pymongo import MongoClient\nimport urllib3\nimport json\n\napp = Flask(__name__)\n\n\n@app.route('/')\ndef home():\n return render_template('index.html')\n\n\n@app.route('/task1')\ndef my_page():\n print(step1())\n print(step3(step2('https://news.v.daum.net/v/20201106110404888')))\n return 'This is My Page!'\n\n#url을 변경해서기 검색 쿼리를 변경하고, 각 뉴스의 url을 가져오기\ndef step1():\n # URL을 읽어서 HTML를 받아오고,\n headers = {\n 'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64)AppleWebKit/537.36 (KHTML, like Gecko) Chrome/73.0.3683.86 Safari/537.36'}\n data = requests.get('https://search.daum.net/search?w=news&nil_search=btn&DA=NTB&enc=utf8&cluster=y&cluster_page=1&q=%EA%B2%80%EC%B0%B0%EC%B4%9D%EC%9E%A5%20%EC%9C%A4%EC%84%9D%EC%97%B4', headers=headers)\n\n #clusterResultUL > li.fst > div.wrap_cont > div > span.f_nb.date > a\n # clusterResultUL > li.fst > div.wrap_cont > div > span.f_nb.date > a\n # clusterResultUL > li:nth-child(2) > div.wrap_cont > div > span.f_nb.date > a\n soup = BeautifulSoup(data.text, 'html.parser')\n\n links = soup.select('#clusterResultUL > li > div.wrap_cont > div > span.f_nb.date > a')\n news_link = []\n for link in links:\n news_link.append(link['href'])\n\n return news_link\n\n\n#가져온 url에서 본문 text 가져오기\ndef step2(news_link):\n headers = {\n 'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64)AppleWebKit/537.36 (KHTML, like Gecko) Chrome/73.0.3683.86 Safari/537.36'}\n data = requests.get(news_link,headers=headers)\n\n soup = BeautifulSoup(data.text, 'html.parser')\n contents = soup.select('#harmonyContainer > section > p')\n news_contents = []\n for content in contents:\n news_contents.append(content.getText())\n one_content = \" \".join(news_contents)\n return one_content\n\n\n#가져온 text를 분석기로 보내서 나온 인물명을 총장명칭과 함께 저장하기\ndef step3(text):\n openApiURL = \"http://aiopen.etri.re.kr:8000/WiseNLU\"\n\n accessKey = \"*****\"\n analysisCode = \"ner\"\n\n requestJson = {\n \"access_key\": accessKey,\n \"argument\": {\n \"text\": text,\n \"analysis_code\": analysisCode\n }\n }\n\n http = urllib3.PoolManager()\n response = http.request(\n \"POST\",\n openApiURL,\n headers={\"Content-Type\": \"application/json; charset=UTF-8\"},\n body=json.dumps(requestJson)\n )\n\n api_doc = str(response.data, \"utf-8\")\n print(api_doc)\n json_data = json.loads(api_doc)\n print(json_data)\n\n api_results = []\n# return_object > sentence(배열) 반복문을 돌면서 0(딕셔너리) key 'NE'(배열) 내 요소는 딕서녀리 'type' : PS_NAME 딕셔너리의 text key의 밸\n for sentence in json_data['return_object']['sentence']:\n for a in sentence['NE']:\n if a['type'] == 'PS_NAME':\n api_results.append(a['text'])\n\n return api_results\n\n\nif __name__ == '__main__':\n app.run('0.0.0.0', port=5000, debug=True)\n"}],"string":"[\n {\n \"alpha_fraction\": 0.4482758641242981,\n \"alphanum_fraction\": 0.5517241358757019,\n \"avg_line_length\": 13.5,\n \"blob_id\": \"5f38c8c5f7f685f5bbc1d4d4abe43ff39b06578e\",\n \"content_id\": \"2316b9945ca815007a7bda3c05e1fbdd8dd2ef18\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 45,\n \"license_type\": \"no_license\",\n \"max_line_length\": 19,\n \"num_lines\": 2,\n \"path\": \"/README.md\",\n \"repo_name\": \"firstcase/theSecretForest\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# 비밀의 숲 프로젝트(11/1~)\\nstart!!!\\n\"\n },\n {\n \"alpha_fraction\": 0.5865615606307983,\n \"alphanum_fraction\": 0.6276996731758118,\n \"avg_line_length\": 29.38541603088379,\n \"blob_id\": \"7040f205527aaef568cb2dcd605c280ee8a7674c\",\n \"content_id\": \"bff0437f107b0da066c8742471220b3b069785b3\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 3121,\n \"license_type\": \"no_license\",\n \"max_line_length\": 206,\n \"num_lines\": 96,\n \"path\": \"/app.py\",\n \"repo_name\": \"firstcase/theSecretForest\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from flask import Flask, render_template\\nimport requests\\nfrom bs4 import BeautifulSoup\\nfrom pymongo import MongoClient\\nimport urllib3\\nimport json\\n\\napp = Flask(__name__)\\n\\n\\n@app.route('/')\\ndef home():\\n return render_template('index.html')\\n\\n\\n@app.route('/task1')\\ndef my_page():\\n print(step1())\\n print(step3(step2('https://news.v.daum.net/v/20201106110404888')))\\n return 'This is My Page!'\\n\\n#url을 변경해서기 검색 쿼리를 변경하고, 각 뉴스의 url을 가져오기\\ndef step1():\\n # URL을 읽어서 HTML를 받아오고,\\n headers = {\\n 'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64)AppleWebKit/537.36 (KHTML, like Gecko) Chrome/73.0.3683.86 Safari/537.36'}\\n data = requests.get('https://search.daum.net/search?w=news&nil_search=btn&DA=NTB&enc=utf8&cluster=y&cluster_page=1&q=%EA%B2%80%EC%B0%B0%EC%B4%9D%EC%9E%A5%20%EC%9C%A4%EC%84%9D%EC%97%B4', headers=headers)\\n\\n #clusterResultUL > li.fst > div.wrap_cont > div > span.f_nb.date > a\\n # clusterResultUL > li.fst > div.wrap_cont > div > span.f_nb.date > a\\n # clusterResultUL > li:nth-child(2) > div.wrap_cont > div > span.f_nb.date > a\\n soup = BeautifulSoup(data.text, 'html.parser')\\n\\n links = soup.select('#clusterResultUL > li > div.wrap_cont > div > span.f_nb.date > a')\\n news_link = []\\n for link in links:\\n news_link.append(link['href'])\\n\\n return news_link\\n\\n\\n#가져온 url에서 본문 text 가져오기\\ndef step2(news_link):\\n headers = {\\n 'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64)AppleWebKit/537.36 (KHTML, like Gecko) Chrome/73.0.3683.86 Safari/537.36'}\\n data = requests.get(news_link,headers=headers)\\n\\n soup = BeautifulSoup(data.text, 'html.parser')\\n contents = soup.select('#harmonyContainer > section > p')\\n news_contents = []\\n for content in contents:\\n news_contents.append(content.getText())\\n one_content = \\\" \\\".join(news_contents)\\n return one_content\\n\\n\\n#가져온 text를 분석기로 보내서 나온 인물명을 총장명칭과 함께 저장하기\\ndef step3(text):\\n openApiURL = \\\"http://aiopen.etri.re.kr:8000/WiseNLU\\\"\\n\\n accessKey = \\\"*****\\\"\\n analysisCode = \\\"ner\\\"\\n\\n requestJson = {\\n \\\"access_key\\\": accessKey,\\n \\\"argument\\\": {\\n \\\"text\\\": text,\\n \\\"analysis_code\\\": analysisCode\\n }\\n }\\n\\n http = urllib3.PoolManager()\\n response = http.request(\\n \\\"POST\\\",\\n openApiURL,\\n headers={\\\"Content-Type\\\": \\\"application/json; charset=UTF-8\\\"},\\n body=json.dumps(requestJson)\\n )\\n\\n api_doc = str(response.data, \\\"utf-8\\\")\\n print(api_doc)\\n json_data = json.loads(api_doc)\\n print(json_data)\\n\\n api_results = []\\n# return_object > sentence(배열) 반복문을 돌면서 0(딕셔너리) key 'NE'(배열) 내 요소는 딕서녀리 'type' : PS_NAME 딕셔너리의 text key의 밸\\n for sentence in json_data['return_object']['sentence']:\\n for a in sentence['NE']:\\n if a['type'] == 'PS_NAME':\\n api_results.append(a['text'])\\n\\n return api_results\\n\\n\\nif __name__ == '__main__':\\n app.run('0.0.0.0', port=5000, debug=True)\\n\"\n }\n]"},"num_files":{"kind":"number","value":2,"string":"2"}}},{"rowIdx":2061,"cells":{"repo_name":{"kind":"string","value":"stats94/championship-bot"},"repo_url":{"kind":"string","value":"https://github.com/stats94/championship-bot"},"snapshot_id":{"kind":"string","value":"b369a6ca3439a5ffcc86abedf203718ebc0aefbf"},"revision_id":{"kind":"string","value":"3cf1bd91c63fd5d8e19e9764f3608eca5b8ce2eb"},"directory_id":{"kind":"string","value":"c4d2683882b666f2701faa194fa9874d8195ace6"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"string","value":"2020-09-02T05:55:38.017064"},"revision_date":{"kind":"string","value":"2019-11-02T12:14:56"},"committer_date":{"kind":"string","value":"2019-11-02T12:14:56"},"github_id":{"kind":"number","value":219148801,"string":"219,148,801"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.6404494643211365,"alphanum_fraction":0.6853932738304138,"avg_line_length":28.66666603088379,"blob_id":"4c9328936c8e061b7f1a14dfcd025537189c7628","content_id":"8cd704d538b042435022b0ee65b0059e342086d1","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":89,"license_type":"no_license","max_line_length":51,"num_lines":3,"path":"/config.py","repo_name":"stats94/championship-bot","src_encoding":"UTF-8","text":"api_key = **APIKEY**\nendpoint = 'https://api-football-v1.p.rapidapi.com'\nleague_id = 565\n"},{"alpha_fraction":0.5471124649047852,"alphanum_fraction":0.5501520037651062,"avg_line_length":25.31999969482422,"blob_id":"ab3971f875c3fdc023e86940d5e134195c9415ff","content_id":"eb49ac6fc477f9cfe2271b8841e2cc35587a744e","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":658,"license_type":"no_license","max_line_length":78,"num_lines":25,"path":"/api_service.py","repo_name":"stats94/championship-bot","src_encoding":"UTF-8","text":"import requests;\nimport config;\n\nclass api_service:\n endpoint = config.endpoint\n api_key = config.api_key\n\n def get(self, url):\n response = requests.get(url, headers={'X-RapidAPI-Key': self.api_key})\n \n '''\n api element is just a wrapper.\n \n api: {\n results: 0 -> Number of results\n fixtures/standing etc: [] -> array with data\n }\n '''\n json = response.json()\n return json['api']\n\n def get_table(self, league_id):\n url = '{}/v2/leagueTable/{}'.format(self.endpoint, league_id)\n response = self.get(url)\n return response['standings']\n"},{"alpha_fraction":0.5595390796661377,"alphanum_fraction":0.5608194470405579,"avg_line_length":44.94117736816406,"blob_id":"75630dfe668b76bd6ee8da7a1c576dce5e7fca44","content_id":"48b826a17412fa413783e447151405f29023ce8e","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":781,"license_type":"no_license","max_line_length":261,"num_lines":17,"path":"/bot.py","repo_name":"stats94/championship-bot","src_encoding":"UTF-8","text":"from api_service import api_service\nimport config\n\nclass bot:\n api_service = api_service()\n league_id = config.league_id\n\n def build_table(self):\n # The standings array is wrapped in another array\n table_data = self.api_service.get_table(self.league_id)[0]\n\n headers = '|Pos|Team|Pl|W|D|L|Form|GD|Pts|\\n:-:|:--|:-:|:-:|:-:|:-:|:--|:-:|:-:'\n\n # Position | Team Name | Played | Won | Drawn | Lost | Form | GD | Points |\n teams = list(map(lambda team: '{}|{}|{}|{}|{}|{}|{}|{}|{}'.format(team['rank'], team['teamName'], team['all']['matchsPlayed'], team['all']['win'], team['all']['draw'], team['all']['lose'], team['forme'], team['goalsDiff'], team['points']), table_data))\n\n return '{}\\n{}'.format(headers, '\\n'.join(teams))\n"}],"string":"[\n {\n \"alpha_fraction\": 0.6404494643211365,\n \"alphanum_fraction\": 0.6853932738304138,\n \"avg_line_length\": 28.66666603088379,\n \"blob_id\": \"4c9328936c8e061b7f1a14dfcd025537189c7628\",\n \"content_id\": \"8cd704d538b042435022b0ee65b0059e342086d1\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 89,\n \"license_type\": \"no_license\",\n \"max_line_length\": 51,\n \"num_lines\": 3,\n \"path\": \"/config.py\",\n \"repo_name\": \"stats94/championship-bot\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"api_key = **APIKEY**\\nendpoint = 'https://api-football-v1.p.rapidapi.com'\\nleague_id = 565\\n\"\n },\n {\n \"alpha_fraction\": 0.5471124649047852,\n \"alphanum_fraction\": 0.5501520037651062,\n \"avg_line_length\": 25.31999969482422,\n \"blob_id\": \"ab3971f875c3fdc023e86940d5e134195c9415ff\",\n \"content_id\": \"eb49ac6fc477f9cfe2271b8841e2cc35587a744e\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 658,\n \"license_type\": \"no_license\",\n \"max_line_length\": 78,\n \"num_lines\": 25,\n \"path\": \"/api_service.py\",\n \"repo_name\": \"stats94/championship-bot\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import requests;\\nimport config;\\n\\nclass api_service:\\n endpoint = config.endpoint\\n api_key = config.api_key\\n\\n def get(self, url):\\n response = requests.get(url, headers={'X-RapidAPI-Key': self.api_key})\\n \\n '''\\n api element is just a wrapper.\\n \\n api: {\\n results: 0 -> Number of results\\n fixtures/standing etc: [] -> array with data\\n }\\n '''\\n json = response.json()\\n return json['api']\\n\\n def get_table(self, league_id):\\n url = '{}/v2/leagueTable/{}'.format(self.endpoint, league_id)\\n response = self.get(url)\\n return response['standings']\\n\"\n },\n {\n \"alpha_fraction\": 0.5595390796661377,\n \"alphanum_fraction\": 0.5608194470405579,\n \"avg_line_length\": 44.94117736816406,\n \"blob_id\": \"75630dfe668b76bd6ee8da7a1c576dce5e7fca44\",\n \"content_id\": \"48b826a17412fa413783e447151405f29023ce8e\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 781,\n \"license_type\": \"no_license\",\n \"max_line_length\": 261,\n \"num_lines\": 17,\n \"path\": \"/bot.py\",\n \"repo_name\": \"stats94/championship-bot\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from api_service import api_service\\nimport config\\n\\nclass bot:\\n api_service = api_service()\\n league_id = config.league_id\\n\\n def build_table(self):\\n # The standings array is wrapped in another array\\n table_data = self.api_service.get_table(self.league_id)[0]\\n\\n headers = '|Pos|Team|Pl|W|D|L|Form|GD|Pts|\\\\n:-:|:--|:-:|:-:|:-:|:-:|:--|:-:|:-:'\\n\\n # Position | Team Name | Played | Won | Drawn | Lost | Form | GD | Points |\\n teams = list(map(lambda team: '{}|{}|{}|{}|{}|{}|{}|{}|{}'.format(team['rank'], team['teamName'], team['all']['matchsPlayed'], team['all']['win'], team['all']['draw'], team['all']['lose'], team['forme'], team['goalsDiff'], team['points']), table_data))\\n\\n return '{}\\\\n{}'.format(headers, '\\\\n'.join(teams))\\n\"\n }\n]"},"num_files":{"kind":"number","value":3,"string":"3"}}},{"rowIdx":2062,"cells":{"repo_name":{"kind":"string","value":"fikirmulu/ITC172_python2"},"repo_url":{"kind":"string","value":"https://github.com/fikirmulu/ITC172_python2"},"snapshot_id":{"kind":"string","value":"3302f253c2e6ae1a7731392fcc01f547931f4779"},"revision_id":{"kind":"string","value":"ee3509f9f86d60e9792670274890eb080210f4a7"},"directory_id":{"kind":"string","value":"7ae8d203e4716047405b79dd7c58710867fecc6a"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"string","value":"2020-04-18T04:40:07.125399"},"revision_date":{"kind":"string","value":"2019-03-04T20:06:06"},"committer_date":{"kind":"string","value":"2019-03-04T20:06:06"},"github_id":{"kind":"number","value":167247752,"string":"167,247,752"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.7405660152435303,"alphanum_fraction":0.7405660152435303,"avg_line_length":39.33333206176758,"blob_id":"214b212c96f268ea7402d5ddcb680c2a7a187211","content_id":"9dc3c86d19169e8b8d670d455041adc0dc8aa4f7","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":848,"license_type":"no_license","max_line_length":86,"num_lines":21,"path":"/club/views.py","repo_name":"fikirmulu/ITC172_python2","src_encoding":"UTF-8","text":"\nfrom django.shortcuts import render\nfrom.models import Meeting, MeetingMinutes, Resource, Event\n# Create your views here.\ndef index (request):\n return render(request, 'club/index.html')\n# importing all theobjects under the productstype\ndef clubmeetings(request):\n meetings_list=Meeting.objects.all()\n return render (request,'club/meetings.html', {'meetings_list': meetings_list})\n\ndef clubminutes(request):\n minutes_list=MeetingMinutes.objects.all()\n return render (request,'club/minutes.html', {'minutes_list': minutes_list}) \n\ndef clubresources (request):\n resources_list=Resource.objects.all()\n return render (request,'club/resources.html', {'resources_list': resources_list}) \n\ndef clubevents (request):\n events_list=Resource.objects.all()\n return render (request,'club/events.html', {'events_list': events_list}) "},{"alpha_fraction":0.7098321318626404,"alphanum_fraction":0.7134292721748352,"avg_line_length":33.020408630371094,"blob_id":"e94b2764914e06956012c77055bbb1e11d64ab8e","content_id":"51d206225a346e50be74e624f1d83c108a168a2e","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1668,"license_type":"no_license","max_line_length":84,"num_lines":49,"path":"/pythonclubproject/club/views.py","repo_name":"fikirmulu/ITC172_python2","src_encoding":"UTF-8","text":"\nfrom django.shortcuts import render, get_object_or_404\nfrom.models import Meeting, MeetingMinutes, Resource, Event \nfrom.forms import ResourceForm\nfrom django.contrib.auth.decorators import login_required\n\n\n# Create your views here.\ndef index (request):\n return render(request, 'club/index.html')\n# importing all theobjects under the productstype\ndef clubresources(request):\n resources_list=Resource.objects.all()\n return render(request,'club/resources.html', {'resources_list': resources_list})\n\ndef getmeeting(request):\n meeting_list=Meeting.objects.all()\n return render (request,'club/meetings.html', {'meeting_list': meeting_list}) \n\ndef meetingdetail(request, id):\n detail=get_object_or_404(Meeting, pk=id)\n context = {'detail': detail}\n return render (request, 'club/details.html', context=context)\n\ndef clubminutes (request):\n minutes_list=MeetingMinutes.objects.all()\n return render (request,'club/minutes.html', {'minutes_list': minutes_list}) \n\ndef clubevents (request):\n events_list=Resource.objects.all()\n return render (request,'club/events.html', {'events_list': events_list}) \n#form view\n@login_required\ndef newResource(request):\n form=ResourceForm\n if request.method=='POST':\n form=ResourceForm(request.POST)\n if form.is_valid():\n post=form.save(commit=True)\n post.save()\n form=ResourceForm()\n else:\n form=ResourceForm()\n return render(request, 'club/newresource.html', {'form':form})\n\ndef loginmessage(request):\n return render(request, 'club/loginmessage.html')\n\ndef logoutmessage(request):\n return render(request, 'club/logoutmessage.html')\n"},{"alpha_fraction":0.5206611752510071,"alphanum_fraction":0.5730027556419373,"avg_line_length":19.16666603088379,"blob_id":"18ebe3a85329d715f7bf896225ff9566dcca2205","content_id":"f3d030628732919795758a0c44c65a6e2353c9c2","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":363,"license_type":"no_license","max_line_length":47,"num_lines":18,"path":"/pythonclubproject/club/migrations/0002_auto_20190207_0913.py","repo_name":"fikirmulu/ITC172_python2","src_encoding":"UTF-8","text":"# Generated by Django 2.1.4 on 2019-02-07 09:13\n\nfrom django.db import migrations\n\n\nclass Migration(migrations.Migration):\n\n dependencies = [\n ('club', '0001_initial'),\n ]\n\n operations = [\n migrations.RenameField(\n model_name='meeting',\n old_name='meetingttitle',\n new_name='meetingtitle',\n ),\n ]\n"},{"alpha_fraction":0.7105538249015808,"alphanum_fraction":0.7105538249015808,"avg_line_length":30.866666793823242,"blob_id":"a07e8971f1a1203942dd6e4c97f4b14038492995","content_id":"bdfa98cb0da795a95f3cd4e1471dfd9d8876bcae","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":957,"license_type":"no_license","max_line_length":66,"num_lines":30,"path":"/pythonclubproject/club/tests.py","repo_name":"fikirmulu/ITC172_python2","src_encoding":"UTF-8","text":"\nfrom django.test import TestCase\nfrom .models import Resource, Meeting, Event\nfrom django.urls import reverse\n\n# Create your tests here.\n# model tests\n\nclass ResourceTest(TestCase):\n def test_stringOutput(self):\n resource=Resource(resourcename='computer')\n self.assertEqual(str(resource), resource.resourcename)\n\n def test_tablename(self):\n self.assertEqual(str(Resource._meta.db_table), 'resource')\n\nclass MeetingTest(TestCase):\n def test_stringOutput(self):\n meeting=Meeting(meetingtitle='salary increment')\n self.assertEqual(str(meeting), meeting.meetingtitle)\n\n def test_tablename(self):\n self.assertEqual(str(Meeting._meta.db_table), 'meeting')\n\nclass EnentTest(TestCase):\n def test_stringOutput(self):\n event=Event(eventtitle='New years')\n self.assertEqual(str(event), event.eventtitle)\n\n def test_tablename(self):\n self.assertEqual(str(Event._meta.db_table), 'event')\n"},{"alpha_fraction":0.6655948758125305,"alphanum_fraction":0.6655948758125305,"avg_line_length":24.91666603088379,"blob_id":"47b39d228f7634c84015c09cbf45608c8fcfd09f","content_id":"98d5547c3de7dde0758bbafe2a36dece3589eec1","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":311,"license_type":"no_license","max_line_length":65,"num_lines":12,"path":"/club/urls.py","repo_name":"fikirmulu/ITC172_python2","src_encoding":"UTF-8","text":"\nfrom django.urls import path\nfrom . import views\n\n\nurlpatterns = [\n path('', views.index, name='index'),\n path('clubmeetings/', views.clubmeetings, name='meetings'),\n path('clubminutes/', views.clubminutes, name='minutes'),\n path('clubresources/', views.clubresources, name='resource'),\n \n \n]"}],"string":"[\n {\n \"alpha_fraction\": 0.7405660152435303,\n \"alphanum_fraction\": 0.7405660152435303,\n \"avg_line_length\": 39.33333206176758,\n \"blob_id\": \"214b212c96f268ea7402d5ddcb680c2a7a187211\",\n \"content_id\": \"9dc3c86d19169e8b8d670d455041adc0dc8aa4f7\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 848,\n \"license_type\": \"no_license\",\n \"max_line_length\": 86,\n \"num_lines\": 21,\n \"path\": \"/club/views.py\",\n \"repo_name\": \"fikirmulu/ITC172_python2\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"\\nfrom django.shortcuts import render\\nfrom.models import Meeting, MeetingMinutes, Resource, Event\\n# Create your views here.\\ndef index (request):\\n return render(request, 'club/index.html')\\n# importing all theobjects under the productstype\\ndef clubmeetings(request):\\n meetings_list=Meeting.objects.all()\\n return render (request,'club/meetings.html', {'meetings_list': meetings_list})\\n\\ndef clubminutes(request):\\n minutes_list=MeetingMinutes.objects.all()\\n return render (request,'club/minutes.html', {'minutes_list': minutes_list}) \\n\\ndef clubresources (request):\\n resources_list=Resource.objects.all()\\n return render (request,'club/resources.html', {'resources_list': resources_list}) \\n\\ndef clubevents (request):\\n events_list=Resource.objects.all()\\n return render (request,'club/events.html', {'events_list': events_list}) \"\n },\n {\n \"alpha_fraction\": 0.7098321318626404,\n \"alphanum_fraction\": 0.7134292721748352,\n \"avg_line_length\": 33.020408630371094,\n \"blob_id\": \"e94b2764914e06956012c77055bbb1e11d64ab8e\",\n \"content_id\": \"51d206225a346e50be74e624f1d83c108a168a2e\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1668,\n \"license_type\": \"no_license\",\n \"max_line_length\": 84,\n \"num_lines\": 49,\n \"path\": \"/pythonclubproject/club/views.py\",\n \"repo_name\": \"fikirmulu/ITC172_python2\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"\\nfrom django.shortcuts import render, get_object_or_404\\nfrom.models import Meeting, MeetingMinutes, Resource, Event \\nfrom.forms import ResourceForm\\nfrom django.contrib.auth.decorators import login_required\\n\\n\\n# Create your views here.\\ndef index (request):\\n return render(request, 'club/index.html')\\n# importing all theobjects under the productstype\\ndef clubresources(request):\\n resources_list=Resource.objects.all()\\n return render(request,'club/resources.html', {'resources_list': resources_list})\\n\\ndef getmeeting(request):\\n meeting_list=Meeting.objects.all()\\n return render (request,'club/meetings.html', {'meeting_list': meeting_list}) \\n\\ndef meetingdetail(request, id):\\n detail=get_object_or_404(Meeting, pk=id)\\n context = {'detail': detail}\\n return render (request, 'club/details.html', context=context)\\n\\ndef clubminutes (request):\\n minutes_list=MeetingMinutes.objects.all()\\n return render (request,'club/minutes.html', {'minutes_list': minutes_list}) \\n\\ndef clubevents (request):\\n events_list=Resource.objects.all()\\n return render (request,'club/events.html', {'events_list': events_list}) \\n#form view\\n@login_required\\ndef newResource(request):\\n form=ResourceForm\\n if request.method=='POST':\\n form=ResourceForm(request.POST)\\n if form.is_valid():\\n post=form.save(commit=True)\\n post.save()\\n form=ResourceForm()\\n else:\\n form=ResourceForm()\\n return render(request, 'club/newresource.html', {'form':form})\\n\\ndef loginmessage(request):\\n return render(request, 'club/loginmessage.html')\\n\\ndef logoutmessage(request):\\n return render(request, 'club/logoutmessage.html')\\n\"\n },\n {\n \"alpha_fraction\": 0.5206611752510071,\n \"alphanum_fraction\": 0.5730027556419373,\n \"avg_line_length\": 19.16666603088379,\n \"blob_id\": \"18ebe3a85329d715f7bf896225ff9566dcca2205\",\n \"content_id\": \"f3d030628732919795758a0c44c65a6e2353c9c2\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 363,\n \"license_type\": \"no_license\",\n \"max_line_length\": 47,\n \"num_lines\": 18,\n \"path\": \"/pythonclubproject/club/migrations/0002_auto_20190207_0913.py\",\n \"repo_name\": \"fikirmulu/ITC172_python2\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# Generated by Django 2.1.4 on 2019-02-07 09:13\\n\\nfrom django.db import migrations\\n\\n\\nclass Migration(migrations.Migration):\\n\\n dependencies = [\\n ('club', '0001_initial'),\\n ]\\n\\n operations = [\\n migrations.RenameField(\\n model_name='meeting',\\n old_name='meetingttitle',\\n new_name='meetingtitle',\\n ),\\n ]\\n\"\n },\n {\n \"alpha_fraction\": 0.7105538249015808,\n \"alphanum_fraction\": 0.7105538249015808,\n \"avg_line_length\": 30.866666793823242,\n \"blob_id\": \"a07e8971f1a1203942dd6e4c97f4b14038492995\",\n \"content_id\": \"bdfa98cb0da795a95f3cd4e1471dfd9d8876bcae\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 957,\n \"license_type\": \"no_license\",\n \"max_line_length\": 66,\n \"num_lines\": 30,\n \"path\": \"/pythonclubproject/club/tests.py\",\n \"repo_name\": \"fikirmulu/ITC172_python2\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"\\nfrom django.test import TestCase\\nfrom .models import Resource, Meeting, Event\\nfrom django.urls import reverse\\n\\n# Create your tests here.\\n# model tests\\n\\nclass ResourceTest(TestCase):\\n def test_stringOutput(self):\\n resource=Resource(resourcename='computer')\\n self.assertEqual(str(resource), resource.resourcename)\\n\\n def test_tablename(self):\\n self.assertEqual(str(Resource._meta.db_table), 'resource')\\n\\nclass MeetingTest(TestCase):\\n def test_stringOutput(self):\\n meeting=Meeting(meetingtitle='salary increment')\\n self.assertEqual(str(meeting), meeting.meetingtitle)\\n\\n def test_tablename(self):\\n self.assertEqual(str(Meeting._meta.db_table), 'meeting')\\n\\nclass EnentTest(TestCase):\\n def test_stringOutput(self):\\n event=Event(eventtitle='New years')\\n self.assertEqual(str(event), event.eventtitle)\\n\\n def test_tablename(self):\\n self.assertEqual(str(Event._meta.db_table), 'event')\\n\"\n },\n {\n \"alpha_fraction\": 0.6655948758125305,\n \"alphanum_fraction\": 0.6655948758125305,\n \"avg_line_length\": 24.91666603088379,\n \"blob_id\": \"47b39d228f7634c84015c09cbf45608c8fcfd09f\",\n \"content_id\": \"98d5547c3de7dde0758bbafe2a36dece3589eec1\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 311,\n \"license_type\": \"no_license\",\n \"max_line_length\": 65,\n \"num_lines\": 12,\n \"path\": \"/club/urls.py\",\n \"repo_name\": \"fikirmulu/ITC172_python2\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"\\nfrom django.urls import path\\nfrom . import views\\n\\n\\nurlpatterns = [\\n path('', views.index, name='index'),\\n path('clubmeetings/', views.clubmeetings, name='meetings'),\\n path('clubminutes/', views.clubminutes, name='minutes'),\\n path('clubresources/', views.clubresources, name='resource'),\\n \\n \\n]\"\n }\n]"},"num_files":{"kind":"number","value":5,"string":"5"}}},{"rowIdx":2063,"cells":{"repo_name":{"kind":"string","value":"eppoha/BGC_Comparative"},"repo_url":{"kind":"string","value":"https://github.com/eppoha/BGC_Comparative"},"snapshot_id":{"kind":"string","value":"3a0cfab41f4c3d2790f254a9ab2a80e048c87f8a"},"revision_id":{"kind":"string","value":"2c562a8a2b13e136ebba6a7e453c4e37a85519f7"},"directory_id":{"kind":"string","value":"b428f37e3c93258638d318ddced59fa004acbff9"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"string","value":"2022-04-06T06:45:36.204120"},"revision_date":{"kind":"string","value":"2019-12-30T10:35:26"},"committer_date":{"kind":"string","value":"2019-12-30T10:35:26"},"github_id":{"kind":"number","value":257168848,"string":"257,168,848"},"star_events_count":{"kind":"number","value":3,"string":"3"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"string","value":"2020-04-20T04:13:36"},"gha_updated_at":{"kind":"string","value":"2019-12-30T10:39:34"},"gha_pushed_at":{"kind":"string","value":"2019-12-30T10:39:31"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.5076754093170166,"alphanum_fraction":0.5244883298873901,"avg_line_length":41.765625,"blob_id":"cf1e1ab4f50abbbb0aca7267a0cbf7a33acb24bf","content_id":"33b7db6a0e503ab3276caccc0e17b918c06c7485","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":2736,"license_type":"no_license","max_line_length":85,"num_lines":64,"path":"/Evaluation.py","repo_name":"eppoha/BGC_Comparative","src_encoding":"UTF-8","text":"import torch\n\n\nclass Result_Eval(object):\n def __init__(self, num_classes):\n self.num_classes = num_classes\n self.mask = torch.zeros(1, dtype=torch.long)\n self.y_hat = torch.zeros(1, dtype=torch.long)\n self.y = torch.zeros(1, dtype=torch.long)\n self.class_dict = {1: \"OBJ\", 2: \"SUB\", 3: \"ATTR\", 4: \"SENTI\", 5: \"KW\"}\n self.truth = {\"OBJ\": 0, \"SUB\": 0, \"ATTR\": 0, \"SENTI\": 0, \"KW\": 0}\n self.prediction = {\"OBJ\": 0, \"SUB\": 0, \"ATTR\": 0, \"SENTI\": 0, \"KW\": 0}\n self.correct = {\"OBJ\": 0, \"SUB\": 0, \"ATTR\": 0, \"SENTI\": 0, \"KW\": 0}\n\n def add(self, output, target, attention_mask):\n self.y = torch.cat((self.y, target.to(\"cpu\")))\n self.y_hat = torch.cat((self.y_hat, output.to(\"cpu\")))\n attention_mask = attention_mask.view(-1)\n self.mask = torch.cat((self.mask, attention_mask.to(\"cpu\")))\n\n def get_dict(self, temp_y):\n res_dict, index, n = [{}, {}, {}, {}, {}, {}], 0, temp_y.size(0)\n while index < n:\n if temp_y[index] == 0 or temp_y[index] >= 6:\n index += 1\n continue\n s_index = index\n while index < n and temp_y[index] == temp_y[s_index]:\n index += 1\n res_dict[temp_y[s_index]][s_index] = index - s_index\n return res_dict\n\n def eval_model(self):\n index = (self.mask == 1)\n temp_y, temp_y_hat = self.y[index], self.y_hat[index]\n\n y_dict = self.get_dict(temp_y)\n for c in range(1, self.num_classes):\n self.truth[self.class_dict[c]] = len(y_dict[c])\n\n y_hat_dict = self.get_dict(temp_y_hat)\n for c in range(1, self.num_classes):\n self.prediction[self.class_dict[c]] = len(y_hat_dict[c])\n\n for c in range(1, self.num_classes):\n for key, value in y_hat_dict[c].items():\n if key in y_dict[c] and value == y_dict[c][key]:\n self.correct[self.class_dict[c]] += 1\n F_measure = 0\n for value in self.class_dict.values():\n if self.prediction[value] == 0 or self.truth[value] == 0:\n continue\n\n Precision = self.correct[value] / self.prediction[value]\n Recall = self.correct[value] / self.truth[value]\n if Precision == 0 and Recall == 0:\n continue\n F = 2 * Precision * Recall / (Precision + Recall)\n F_measure += F\n\n print(\"class-type {} precision value is {:.2f}\".format(value, Precision))\n print(\"class-type {} Recall value is: {:.2f}\".format(value, Recall))\n print(\"class-type {} F1_Measure value is: {:.2f}\".format(value, F))\n print(\"Final F_Measure is {:.2f}\".format(F_measure))"},{"alpha_fraction":0.5492755770683289,"alphanum_fraction":0.5654614567756653,"avg_line_length":41.79888153076172,"blob_id":"90d39100651412d1747e74e4afc3270fa7693872","content_id":"2fdc54669bfafd9a66c6d65c9a9de05ae908f9af","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":7661,"license_type":"no_license","max_line_length":129,"num_lines":179,"path":"/Model.py","repo_name":"eppoha/BGC_Comparative","src_encoding":"UTF-8","text":"import torch\nimport torch.nn as nn\n\nfrom pytorch_pretrained_bert import BertModel, BertTokenizer\n\n\nclass BERT_Cell(nn.Module):\n def __init__(self, model_path):\n super(BERT_Cell, self).__init__()\n self.bert = BertModel.from_pretrained(model_path)\n self.hidden_size = self.bert.config.hidden_size\n self.hidden_dropout_prob = self.bert.config.hidden_dropout_prob\n\n def forward(self, input_ids, token_type_ids, attention_mask):\n self.bert.eval()\n # encoded_layers shape: [layers, batch_size, tokens, hidden_size]\n encoded_layers, _ = self.bert(input_ids, token_type_ids, attention_mask)\n\n # Concatenate the tensors for all layers. We use `stack` here to\n # create a new dimension in the tensor.\n token_embeddings = torch.stack(encoded_layers, dim=0)\n\n # token_embeddings size is [encode_layers, batch_size, seq_len, hidden_size]\n token_embeddings = token_embeddings.permute(1, 2, 0, 3)\n # x_embedding = torch.cat((token_embeddings[:, :, -4, :], token_embeddings[:, :, -3, :],\n # token_embeddings[:, :, -2, :], token_embeddings[:, :, -1, :]), dim=2)\n x_embedding = torch.cat((token_embeddings[:, :, -1, :], token_embeddings[:, :, -2, :]), dim=2)\n # x_embedding = token_embeddings[:, :, -1, :]\n return x_embedding\n\n\nclass BiGRU_Cell(nn.Module):\n def __init__(self, config):\n super(BiGRU_Cell, self).__init__()\n # define hyper-parameters\n self.input_size = config.input_size\n self.hidden_size = config.hidden_size\n self.num_layer = config.num_layers\n self.batch_size = config.batch_size\n self.device = config.device\n\n self.gru = nn.GRU(config.input_size, config.hidden_size, config.num_layers,\n batch_first=True, bidirectional=True)\n\n def forward(self, x):\n h0 = torch.zeros(self.num_layer * 2, x.size(0), self.hidden_size).to(self.device)\n\n # x shape is [batch_size, token_size, bert_embedding_size]\n output, _ = self.gru(x, h0)\n return output\n\n\nclass CRF_Cell(nn.Module):\n def __init__(self, config):\n super(CRF_Cell, self).__init__()\n # tag_size = num_classes + start tag and stop tag\n self.tag_size = config.num_classes + 2\n self.device = config.device\n self.f = nn.Sigmoid()\n self.target_to_index = {\"OTHERS\": 0, \"OBJ\": 1, \"SUB\": 2, \"ATTR\": 3,\n \"SENTI\": 4, \"KW\": 5, \"START\": 6, \"STOP\": 7}\n self.transitions = nn.Parameter(torch.ones(self.tag_size, self.tag_size), requires_grad=True)\n\n # change the type\n def log_sum_exp(self, vec):\n max_score = vec[0, torch.argmax(vec, dim=1)]\n n, m = vec.size(0), vec.size(1)\n max_score_broadcast = max_score.view(-1, 1).expand(n, m)\n # print(max_score + torch.log(torch.sum(torch.exp(vec - max_score_broadcast))))\n return max_score + torch.log(torch.sum(torch.exp(vec - max_score_broadcast)))\n\n def viterbi_decode(self, word_feature, input_ids):\n index, decode_ids, each_seq_ids = 0, [], []\n forward_var = torch.full((1, self.tag_size), -1000000).to(self.device)\n\n # '[CLS]' id is 101 and '[SEP]' id is 102\n for feat in word_feature:\n step_best_ids = [] # store current step max value's last tag\n step_best_value = [] # store current step each tag max value\n\n # if feat is '[CLS]' init forward_var\n if input_ids[index] == 101:\n forward_var = torch.full((1, self.tag_size), -100000).to(self.device)\n forward_var[0][self.target_to_index['START']] = 0\n index += 1\n continue\n\n # if feature is \"[SEP]\" need get sequence tags\n if input_ids[index] == 102:\n seq_stop_var = forward_var + self.transitions[self.target_to_index['STOP']]\n current_id = torch.argmax(seq_stop_var).item()\n\n # find the best tag path\n path_ids = [current_id]\n for i in range(len(each_seq_ids) - 1, 0, -1):\n step_ids = each_seq_ids[i]\n path_ids.insert(0, step_ids[path_ids[0]])\n\n # 6, 7 denote start and stop\n path_ids.insert(0, 6)\n path_ids.append(7)\n\n # add each sequence tags to all tags\n decode_ids.extend(path_ids)\n each_seq_ids = []\n index += 1\n continue\n\n # else using viterbi algorithm\n for next_tag in range(self.tag_size):\n current_var = forward_var + self.transitions[next_tag]\n current_best_id = torch.argmax(current_var)\n\n step_best_ids.append(current_best_id)\n step_best_value.append(current_var[0][current_best_id].view(1))\n\n forward_var = (feat + torch.cat(step_best_value)).view(1, -1)\n each_seq_ids.append(step_best_ids)\n index += 1\n return torch.tensor(decode_ids, dtype=torch.long).to(self.device)\n\n def truth_path_loss(self, word_feature, input_ids, tag_col):\n # score should be loss back\n batch_score, seq_score = torch.zeros(1).to(self.device), torch.zeros(1).to(self.device)\n\n # using 6 and 7 instead of -1\n tag_col[input_ids == 101] = 6\n tag_col[input_ids == 102] = 7\n\n for index, feat in enumerate(word_feature):\n if tag_col[index] == 6:\n seq_score = torch.zeros(1).to(self.device)\n continue\n\n # end the sequence tag score\n if tag_col[index] == 7:\n seq_score -= self.transitions[tag_col[index], tag_col[index - 1]]\n batch_score += seq_score\n continue\n\n # seq_score = seq_score + self.f(feat[tag_col[index]]) + self.f(self.transitions[tag_col[index + 1], tag_col[index]])\n seq_score = seq_score + feat[tag_col[index]] + self.transitions[tag_col[index + 1], tag_col[index]]\n\n return batch_score\n\n def all_path_loss(self, word_feature, input_ids):\n forward_var = torch.zeros(self.tag_size, 1).to(self.device)\n all_path_score = torch.zeros(1).to(self.device)\n\n for index, feat in enumerate(word_feature):\n if input_ids[index] == 101:\n # forward_var = feat.view(self.tag_size, 1)\n forward_var = torch.zeros(self.tag_size, 1).to(self.device)\n\n # forward_var = torch.full((1, self.tag_size), -100000).to(self.device)\n # forward_var[0][self.target_to_index['START']] = 0\n continue\n\n if input_ids[index] == 102:\n forward_var = forward_var.view(1, self.tag_size)\n all_path_score += self.log_sum_exp(forward_var)\n continue\n\n # expand to n * n\n forward_var = forward_var.expand(self.tag_size, self.tag_size)\n # feat = self.f(feat.view(1, -1))\n feat = feat.view(1, -1)\n emission = feat.expand(self.tag_size, self.tag_size)\n\n # score = forward_var + emission + self.f(torch.t(self.transitions))\n score = forward_var + emission + torch.t(self.transitions)\n forward_var = self.log_sum_exp(score).view(self.tag_size, 1)\n\n return all_path_score\n\n def loss(self, word_feature, input_ids, target_col):\n truth_path_score = self.truth_path_loss(word_feature, input_ids, target_col)\n all_path_score = self.all_path_loss(word_feature, input_ids)\n return all_path_score - truth_path_score\n"},{"alpha_fraction":0.5853132009506226,"alphanum_fraction":0.593952476978302,"avg_line_length":28,"blob_id":"6fa0c87eaaa466d064db2ec5092800b4d373121e","content_id":"c5c55afd739c6544491023555e9a7cae3f9e5eee","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":463,"license_type":"no_license","max_line_length":41,"num_lines":16,"path":"/Config.py","repo_name":"eppoha/BGC_Comparative","src_encoding":"UTF-8","text":"class Config(object):\n def __init__(self, args):\n self.input_size = args.input\n self.hidden_size = args.hidden\n\n self.num_layers = args.layer\n self.num_classes = 6\n\n self.epochs = args.epoch\n self.batch_size = args.batch\n self.device = args.device\n\n self.train_data_path = args.train\n self.test_data_path = args.test\n self.bert_model_path = args.bert\n self.hidden_dropout_prob = 0.05"},{"alpha_fraction":0.6379280686378479,"alphanum_fraction":0.6478105187416077,"avg_line_length":39.75694274902344,"blob_id":"351031850fd803873a736ff8f086417213e10c68","content_id":"797b9946b663294f689328532b791c5bba17a7cd","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":5869,"license_type":"no_license","max_line_length":102,"num_lines":144,"path":"/Main.py","repo_name":"eppoha/BGC_Comparative","src_encoding":"UTF-8","text":"import torch\nimport torch.nn as nn\nimport torch.optim as optim\nimport torch.nn.functional as F\n\nimport os\nimport argparse\nimport Model\nimport MyData\nimport DataProcess\n# import PreProcess\nimport Config\nimport Evaluation\nimport matplotlib.pyplot as plt\nimport matplotlib\nimport Bert_GRU_CRF_Model\n\nfrom pytorch_pretrained_bert import BertAdam\n\n\n# padding data and return input_ids, token_type_ids, attention_mask\ndef padding_data(data, target, maxLen):\n input_ids = [line + [0] * (maxLen - len(line)) for line in data]\n token_type_ids = [[0] * maxLen for _ in data]\n attention_mask = [[1] * len(line) + [0] * (maxLen - len(line)) for line in data]\n target_col = [line + [-1] * (maxLen - len(line)) for line in target]\n return input_ids, token_type_ids, attention_mask, target_col\n\n\ndef TrainModel(model, optimizer, train_loader, maxLen, device, epoch):\n epoch_loss, t = 0, 0\n for index, (data, target) in enumerate(train_loader):\n # through data to get input_ids, token_type_ids, attention_mask\n if index >= 10 and index % 10 == 0:\n print(\"index: \", index)\n input_ids, token_type_ids, attention_mask, target_col = padding_data(data, target, maxLen)\n\n input_ids = torch.tensor(input_ids).long().to(device)\n token_type_ids = torch.tensor(token_type_ids).long().to(device)\n attention_mask = torch.tensor(attention_mask).long().to(device)\n target_col = torch.tensor(target_col).to(device)\n\n loss = model(input_ids, token_type_ids, attention_mask, target_col)\n epoch_loss += loss.item()\n\n optimizer.zero_grad()\n loss.backward()\n optimizer.step()\n t = index\n\n print(\"Loss: {}\".format(epoch_loss / t))\n\n\ndef TestModel(model, test_loader, maxLen, device, epoch):\n total, correct = 0, 0\n res_eval = Evaluation.Result_Eval(6)\n with torch.no_grad():\n for index, (data, target) in enumerate(test_loader):\n # through data to get input_ids, token_type_ids, attention_mask\n input_ids, token_type_ids, attention_mask, target_col = padding_data(data, target, maxLen)\n\n input_ids = torch.tensor(input_ids).long().to(device)\n token_type_ids = torch.tensor(token_type_ids).long().to(device)\n attention_mask = torch.tensor(attention_mask).long().to(device)\n target_col = torch.tensor(target_col).to(device)\n\n target_col = target_col[attention_mask == 1]\n\n output = model(input_ids, token_type_ids, attention_mask)\n\n total += torch.sum(attention_mask == 1).item()\n correct += torch.sum(target_col == output).item()\n attention_mask = attention_mask[attention_mask == 1]\n\n res_eval.add(output, target_col, attention_mask)\n res_eval.eval_model()\n print(\"ACC: {:.2f}%, correct/total: {}/{}\".format(correct / total * 100, correct, total))\n\n\ndef TerminalParser():\n # define train data path and test data path\n train_data_path = \"./result/char_train.data\"\n test_data_path = \"./result/char_test.data\"\n bert_model_path = \"/home/zhliu/RTX/modeling_bert/bert-base-chinese.tar.gz\"\n # bert_model_path = \"C:\\\\Users\\\\curry\\\\Desktop\\\\modeling_bert\\\\bert-base-chinese.tar.gz\"\n\n # define parse parameters\n parser = argparse.ArgumentParser()\n parser.description = 'choose train data and test data file path'\n parser.add_argument('--train', help='train data file path', default=train_data_path)\n parser.add_argument('--test', help='test data file path', default=test_data_path)\n parser.add_argument('--bert', help='bert model file path', default=bert_model_path)\n parser.add_argument('--batch', help='input data batch size', default=5)\n parser.add_argument('--input', help='input data size', default=768)\n parser.add_argument('--hidden', help='gru hidden size', default=100)\n parser.add_argument('--layer', help='the number of gru layer', default=3)\n parser.add_argument('--epoch', help='the number of run times', default=100)\n parser.add_argument('--device', help='run program in device type', default='cuda')\n # parser.add_argument('--device', help='run program in device type', default='cpu')\n args = parser.parse_args()\n\n config_obj = Config.Config(args)\n return config_obj\n\n\ndef main():\n # get some configure and hyper-parameters\n args = TerminalParser()\n\n # get standard data file\n if not os.path.exists(args.train_data_path) or not os.path.exists(args.test_data_path):\n PreProcess.pre_process_main()\n\n train_path = \"./result/char_train.data\"\n test_path = \"./result/char_test.data\"\n\n # get vocab and max sequence length\n vocab, maxLen = DataProcess.get_vocab(train_path, test_path)\n maxLen += 10\n\n # get train data and test data BERT\n train_data, train_target = DataProcess.get_bert_data(train_path)\n test_data, test_target = DataProcess.get_bert_data(test_path)\n\n # define train data and test data\n train_loader = MyData.get_loader(train_data, train_target, args.batch_size)\n test_loader = MyData.get_loader(test_data, test_target, args.batch_size)\n\n # define model and optimizer\n model = Bert_GRU_CRF_Model.BGCM(args).to(args.device)\n optimizer = optim.Adam([{'params': model.fc2.parameters(), 'lr': 0.001},\n {'params': model.fc1.parameters(), 'lr': 0.001},\n {'params': model.bert.parameters(), 'lr': 2e-5},\n {'params': model.gru.parameters(), 'lr': 0.001},\n {'params': model.crf.parameters(), 'lr': 0.001}], weight_decay=0.01)\n\n # train model and test model\n for epoch in range(args.epochs):\n TrainModel(model, optimizer, train_loader, maxLen, args.device, epoch)\n TestModel(model, test_loader, maxLen, args.device, epoch)\n\n\nif __name__ == \"__main__\":\n main()\n"},{"alpha_fraction":0.6370157599449158,"alphanum_fraction":0.6398852467536926,"avg_line_length":23.821428298950195,"blob_id":"5c175d39c3aaf68daf4edf0f15fc2f4a098342dd","content_id":"902dba4540e0ba200c0ea42193dfe18c13374c17","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":697,"license_type":"no_license","max_line_length":86,"num_lines":28,"path":"/MyData.py","repo_name":"eppoha/BGC_Comparative","src_encoding":"UTF-8","text":"import numpy as np\nimport torch\nfrom torch.utils.data import Dataset, DataLoader\n\n\nclass MyData(Dataset):\n def __init__(self, data, target):\n self.data = data\n self.target = target\n\n def __len__(self):\n return len(self.data)\n\n def __getitem__(self, index):\n data = self.data[index]\n target = self.target[index]\n return [data, target]\n\n\ndef collate_fn(data):\n input, target = list(list(zip(*data))[0]), list(list(zip(*data))[1])\n return input, target\n\n\ndef get_loader(data, target, batch_size):\n dataset = MyData(data, target)\n dataloader = DataLoader(dataset, batch_size, shuffle=False, collate_fn=collate_fn)\n return dataloader\n\n\n"},{"alpha_fraction":0.6316171288490295,"alphanum_fraction":0.6403190493583679,"avg_line_length":32.65853500366211,"blob_id":"806b4e816fb2533686ab5e082e5fc184ca0dc77c","content_id":"12ae6f7ca003535e1959b5ad74ae75c95c65d11a","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1379,"license_type":"no_license","max_line_length":82,"num_lines":41,"path":"/Bert_GRU_CRF_Model.py","repo_name":"eppoha/BGC_Comparative","src_encoding":"UTF-8","text":"import torch\nimport torch.nn as nn\nimport torch.optim as optim\nimport torch.nn.functional as F\n\nimport Main\nimport Evaluation\nfrom Model import BERT_Cell, BiGRU_Cell, CRF_Cell\n\n\nclass BGCM(nn.Module):\n def __init__(self, config):\n super(BGCM, self).__init__()\n self.bert = BERT_Cell(config.bert_model_path)\n self.dropout = nn.Dropout(0.1)\n\n self.gru = BiGRU_Cell(config)\n self.fc1 = nn.Linear(config.input_size, 2 * config.hidden_size)\n self.fc2 = nn.Linear(2 * config.hidden_size, config.num_classes + 2)\n self.crf = CRF_Cell(config)\n\n def forward(self, input_ids, token_type_ids, attention_mask, target_col=None):\n x_word_embedding = self.bert(input_ids, token_type_ids, attention_mask)\n x_word_embedding = self.dropout(x_word_embedding)\n\n bert_feature = self.fc1(x_word_embedding)\n word_feature = self.gru(x_word_embedding)\n\n emission_prob = self.fc2(word_feature + bert_feature)\n\n features = emission_prob[attention_mask == 1]\n sequence_ids = input_ids[attention_mask == 1]\n\n if target_col is None:\n output = self.crf.viterbi_decode(features, sequence_ids)\n return output\n\n else:\n sequence_tags = target_col[attention_mask == 1]\n loss = self.crf.loss(features, sequence_ids, sequence_tags)\n return loss"},{"alpha_fraction":0.5480672121047974,"alphanum_fraction":0.5579842329025269,"avg_line_length":32.619049072265625,"blob_id":"5bcae6497b195d8a90394f76ec7affe058513e76","content_id":"b294695e03ceedd2b83d25e1cb6cc940a551e728","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":4945,"license_type":"no_license","max_line_length":85,"num_lines":147,"path":"/PreProcess.py","repo_name":"eppoha/BGC_Comparative","src_encoding":"UTF-8","text":"import os\nimport re\nimport numpy as np\nfrom stanfordcorenlp import StanfordCoreNLP\n\n\ndef process_label(path, type, inverse_class_dict):\n label_col, last_doc = [], \"\"\n\n with open(path, 'r', encoding='gb18030', errors='ignore') as f:\n for line in f.readlines():\n word_list = list(filter(None, line.split()))\n\n # type == 0 denote train label\n if type == 0:\n doc_num = word_list[0]\n tag_col = word_list[1:]\n\n # type == 1 denote test label\n else:\n doc_num = word_list[1]\n tag_col = word_list[-5:]\n\n sentence_tag = {}\n for index, tag_word in enumerate(tag_col):\n temp_list = []\n if tag_word == \"NULL\":\n continue\n\n if tag_word.find(\"|\") != -1:\n temp_list = tag_word.split('|')\n\n elif tag_word.find(\"...\") != -1:\n temp_list = tag_word.split('...')\n\n elif tag_word.find(\"、\") != -1:\n temp_list = tag_word.split('、')\n\n else:\n temp_list = [tag_word]\n\n for token in temp_list:\n sentence_tag[token] = inverse_class_dict[index + 1]\n\n if doc_num == last_doc:\n for key, value in sentence_tag.items():\n if key not in label_col[-1]:\n label_col[-1][key] = value\n else:\n label_col.append(sentence_tag)\n\n last_doc = doc_num\n return label_col\n\n\ndef process_data(path, tag_col, class_dict):\n input_data, target = [], []\n pattern = r'<DOC[0-9]+>\\t([\\s\\S]*?)</DOC[0-9]+>'\n with open(path, \"r\", encoding='gb18030', errors='ignore') as f:\n file_data = f.read()\n data = re.findall(pattern, file_data)\n\n # error label col or file error\n if len(data) != len(tag_col):\n print(\"Please check your label collection !\")\n\n for index, doc in enumerate(data):\n label = np.zeros(len(doc), dtype=int)\n\n for key, value in tag_col[index].items():\n s_index = doc.find(key)\n e_index = s_index + len(key)\n\n label[s_index: e_index] = class_dict[value]\n\n input_data.append(doc)\n target.append(label.tolist())\n\n return input_data, target\n\n\ndef char_feature(input_data, target):\n return input_data, target\n\n\ndef token_feature(input_data, target):\n stanford_nlp = StanfordCoreNLP('C:\\\\stanford-corenlp-full-2018-10-05', lang='zh')\n\n final_data, final_target = [], []\n for i, doc in enumerate(input_data):\n token_list, index = stanford_nlp.word_tokenize(doc), 0\n temp_target = [0] * len(token_list)\n\n for j in range(len(token_list)):\n class_count = np.zeros(6)\n for k in range(len(token_list[j])):\n class_count[target[i][index]] += 1\n index += 1\n temp_target[j] = np.argmax(class_count).item()\n\n final_data.append(token_list)\n final_target.append(temp_target)\n return final_data, final_target\n\n\ndef store_process_data(data, target, path):\n write_str = \"\"\n for i in range(len(data)):\n for j in range(len(data[i])):\n write_str += data[i][j] + ' ' + str(target[i][j]) + '\\n'\n write_str += '\\n'\n with open(path, 'w', encoding='utf8', errors='ignore') as f:\n f.write(write_str)\n\n\ndef pre_process_main():\n train_data_path = \"./data/train_data.txt\"\n train_label_path = \"./data/train_label.txt\"\n test_data_path = \"./data/test_data.txt\"\n test_label_path = \"./data/test_label.txt\"\n\n class_dict = {\"OTHERS\": 0, \"OBJ\": 1, \"SUB\": 2, \"ATTR\": 3, \"SENTI\": 4, \"KW\": 5}\n inverse_class_dict = {v: k for k, v in class_dict.items()}\n print(inverse_class_dict)\n\n # get train data label and test data label\n train_tag = process_label(train_label_path, 0, inverse_class_dict)\n test_tag = process_label(test_label_path, 1, inverse_class_dict)\n\n # get train data and label\n train_data, train_target = process_data(train_data_path, train_tag, class_dict)\n test_data, test_target = process_data(test_data_path, test_tag, class_dict)\n\n # # get token feature\n # train_final_data, train_final_target = token_feature(train_data, train_target)\n # test_final_data, test_final_target = token_feature(test_data, test_target)\n\n # get char feature\n train_final_data, train_final_target = char_feature(train_data, train_target)\n test_final_data, test_final_target = char_feature(test_data, test_target)\n\n # store pre-process data and target\n store_train_path = \"./result/char_train.data\"\n store_test_path = \"./result/char_test.data\"\n\n store_process_data(train_final_data, train_final_target, store_train_path)\n store_process_data(test_final_data, test_final_target, store_test_path)"}],"string":"[\n {\n \"alpha_fraction\": 0.5076754093170166,\n \"alphanum_fraction\": 0.5244883298873901,\n \"avg_line_length\": 41.765625,\n \"blob_id\": \"cf1e1ab4f50abbbb0aca7267a0cbf7a33acb24bf\",\n \"content_id\": \"33b7db6a0e503ab3276caccc0e17b918c06c7485\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 2736,\n \"license_type\": \"no_license\",\n \"max_line_length\": 85,\n \"num_lines\": 64,\n \"path\": \"/Evaluation.py\",\n \"repo_name\": \"eppoha/BGC_Comparative\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import torch\\n\\n\\nclass Result_Eval(object):\\n def __init__(self, num_classes):\\n self.num_classes = num_classes\\n self.mask = torch.zeros(1, dtype=torch.long)\\n self.y_hat = torch.zeros(1, dtype=torch.long)\\n self.y = torch.zeros(1, dtype=torch.long)\\n self.class_dict = {1: \\\"OBJ\\\", 2: \\\"SUB\\\", 3: \\\"ATTR\\\", 4: \\\"SENTI\\\", 5: \\\"KW\\\"}\\n self.truth = {\\\"OBJ\\\": 0, \\\"SUB\\\": 0, \\\"ATTR\\\": 0, \\\"SENTI\\\": 0, \\\"KW\\\": 0}\\n self.prediction = {\\\"OBJ\\\": 0, \\\"SUB\\\": 0, \\\"ATTR\\\": 0, \\\"SENTI\\\": 0, \\\"KW\\\": 0}\\n self.correct = {\\\"OBJ\\\": 0, \\\"SUB\\\": 0, \\\"ATTR\\\": 0, \\\"SENTI\\\": 0, \\\"KW\\\": 0}\\n\\n def add(self, output, target, attention_mask):\\n self.y = torch.cat((self.y, target.to(\\\"cpu\\\")))\\n self.y_hat = torch.cat((self.y_hat, output.to(\\\"cpu\\\")))\\n attention_mask = attention_mask.view(-1)\\n self.mask = torch.cat((self.mask, attention_mask.to(\\\"cpu\\\")))\\n\\n def get_dict(self, temp_y):\\n res_dict, index, n = [{}, {}, {}, {}, {}, {}], 0, temp_y.size(0)\\n while index < n:\\n if temp_y[index] == 0 or temp_y[index] >= 6:\\n index += 1\\n continue\\n s_index = index\\n while index < n and temp_y[index] == temp_y[s_index]:\\n index += 1\\n res_dict[temp_y[s_index]][s_index] = index - s_index\\n return res_dict\\n\\n def eval_model(self):\\n index = (self.mask == 1)\\n temp_y, temp_y_hat = self.y[index], self.y_hat[index]\\n\\n y_dict = self.get_dict(temp_y)\\n for c in range(1, self.num_classes):\\n self.truth[self.class_dict[c]] = len(y_dict[c])\\n\\n y_hat_dict = self.get_dict(temp_y_hat)\\n for c in range(1, self.num_classes):\\n self.prediction[self.class_dict[c]] = len(y_hat_dict[c])\\n\\n for c in range(1, self.num_classes):\\n for key, value in y_hat_dict[c].items():\\n if key in y_dict[c] and value == y_dict[c][key]:\\n self.correct[self.class_dict[c]] += 1\\n F_measure = 0\\n for value in self.class_dict.values():\\n if self.prediction[value] == 0 or self.truth[value] == 0:\\n continue\\n\\n Precision = self.correct[value] / self.prediction[value]\\n Recall = self.correct[value] / self.truth[value]\\n if Precision == 0 and Recall == 0:\\n continue\\n F = 2 * Precision * Recall / (Precision + Recall)\\n F_measure += F\\n\\n print(\\\"class-type {} precision value is {:.2f}\\\".format(value, Precision))\\n print(\\\"class-type {} Recall value is: {:.2f}\\\".format(value, Recall))\\n print(\\\"class-type {} F1_Measure value is: {:.2f}\\\".format(value, F))\\n print(\\\"Final F_Measure is {:.2f}\\\".format(F_measure))\"\n },\n {\n \"alpha_fraction\": 0.5492755770683289,\n \"alphanum_fraction\": 0.5654614567756653,\n \"avg_line_length\": 41.79888153076172,\n \"blob_id\": \"90d39100651412d1747e74e4afc3270fa7693872\",\n \"content_id\": \"2fdc54669bfafd9a66c6d65c9a9de05ae908f9af\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 7661,\n \"license_type\": \"no_license\",\n \"max_line_length\": 129,\n \"num_lines\": 179,\n \"path\": \"/Model.py\",\n \"repo_name\": \"eppoha/BGC_Comparative\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import torch\\nimport torch.nn as nn\\n\\nfrom pytorch_pretrained_bert import BertModel, BertTokenizer\\n\\n\\nclass BERT_Cell(nn.Module):\\n def __init__(self, model_path):\\n super(BERT_Cell, self).__init__()\\n self.bert = BertModel.from_pretrained(model_path)\\n self.hidden_size = self.bert.config.hidden_size\\n self.hidden_dropout_prob = self.bert.config.hidden_dropout_prob\\n\\n def forward(self, input_ids, token_type_ids, attention_mask):\\n self.bert.eval()\\n # encoded_layers shape: [layers, batch_size, tokens, hidden_size]\\n encoded_layers, _ = self.bert(input_ids, token_type_ids, attention_mask)\\n\\n # Concatenate the tensors for all layers. We use `stack` here to\\n # create a new dimension in the tensor.\\n token_embeddings = torch.stack(encoded_layers, dim=0)\\n\\n # token_embeddings size is [encode_layers, batch_size, seq_len, hidden_size]\\n token_embeddings = token_embeddings.permute(1, 2, 0, 3)\\n # x_embedding = torch.cat((token_embeddings[:, :, -4, :], token_embeddings[:, :, -3, :],\\n # token_embeddings[:, :, -2, :], token_embeddings[:, :, -1, :]), dim=2)\\n x_embedding = torch.cat((token_embeddings[:, :, -1, :], token_embeddings[:, :, -2, :]), dim=2)\\n # x_embedding = token_embeddings[:, :, -1, :]\\n return x_embedding\\n\\n\\nclass BiGRU_Cell(nn.Module):\\n def __init__(self, config):\\n super(BiGRU_Cell, self).__init__()\\n # define hyper-parameters\\n self.input_size = config.input_size\\n self.hidden_size = config.hidden_size\\n self.num_layer = config.num_layers\\n self.batch_size = config.batch_size\\n self.device = config.device\\n\\n self.gru = nn.GRU(config.input_size, config.hidden_size, config.num_layers,\\n batch_first=True, bidirectional=True)\\n\\n def forward(self, x):\\n h0 = torch.zeros(self.num_layer * 2, x.size(0), self.hidden_size).to(self.device)\\n\\n # x shape is [batch_size, token_size, bert_embedding_size]\\n output, _ = self.gru(x, h0)\\n return output\\n\\n\\nclass CRF_Cell(nn.Module):\\n def __init__(self, config):\\n super(CRF_Cell, self).__init__()\\n # tag_size = num_classes + start tag and stop tag\\n self.tag_size = config.num_classes + 2\\n self.device = config.device\\n self.f = nn.Sigmoid()\\n self.target_to_index = {\\\"OTHERS\\\": 0, \\\"OBJ\\\": 1, \\\"SUB\\\": 2, \\\"ATTR\\\": 3,\\n \\\"SENTI\\\": 4, \\\"KW\\\": 5, \\\"START\\\": 6, \\\"STOP\\\": 7}\\n self.transitions = nn.Parameter(torch.ones(self.tag_size, self.tag_size), requires_grad=True)\\n\\n # change the type\\n def log_sum_exp(self, vec):\\n max_score = vec[0, torch.argmax(vec, dim=1)]\\n n, m = vec.size(0), vec.size(1)\\n max_score_broadcast = max_score.view(-1, 1).expand(n, m)\\n # print(max_score + torch.log(torch.sum(torch.exp(vec - max_score_broadcast))))\\n return max_score + torch.log(torch.sum(torch.exp(vec - max_score_broadcast)))\\n\\n def viterbi_decode(self, word_feature, input_ids):\\n index, decode_ids, each_seq_ids = 0, [], []\\n forward_var = torch.full((1, self.tag_size), -1000000).to(self.device)\\n\\n # '[CLS]' id is 101 and '[SEP]' id is 102\\n for feat in word_feature:\\n step_best_ids = [] # store current step max value's last tag\\n step_best_value = [] # store current step each tag max value\\n\\n # if feat is '[CLS]' init forward_var\\n if input_ids[index] == 101:\\n forward_var = torch.full((1, self.tag_size), -100000).to(self.device)\\n forward_var[0][self.target_to_index['START']] = 0\\n index += 1\\n continue\\n\\n # if feature is \\\"[SEP]\\\" need get sequence tags\\n if input_ids[index] == 102:\\n seq_stop_var = forward_var + self.transitions[self.target_to_index['STOP']]\\n current_id = torch.argmax(seq_stop_var).item()\\n\\n # find the best tag path\\n path_ids = [current_id]\\n for i in range(len(each_seq_ids) - 1, 0, -1):\\n step_ids = each_seq_ids[i]\\n path_ids.insert(0, step_ids[path_ids[0]])\\n\\n # 6, 7 denote start and stop\\n path_ids.insert(0, 6)\\n path_ids.append(7)\\n\\n # add each sequence tags to all tags\\n decode_ids.extend(path_ids)\\n each_seq_ids = []\\n index += 1\\n continue\\n\\n # else using viterbi algorithm\\n for next_tag in range(self.tag_size):\\n current_var = forward_var + self.transitions[next_tag]\\n current_best_id = torch.argmax(current_var)\\n\\n step_best_ids.append(current_best_id)\\n step_best_value.append(current_var[0][current_best_id].view(1))\\n\\n forward_var = (feat + torch.cat(step_best_value)).view(1, -1)\\n each_seq_ids.append(step_best_ids)\\n index += 1\\n return torch.tensor(decode_ids, dtype=torch.long).to(self.device)\\n\\n def truth_path_loss(self, word_feature, input_ids, tag_col):\\n # score should be loss back\\n batch_score, seq_score = torch.zeros(1).to(self.device), torch.zeros(1).to(self.device)\\n\\n # using 6 and 7 instead of -1\\n tag_col[input_ids == 101] = 6\\n tag_col[input_ids == 102] = 7\\n\\n for index, feat in enumerate(word_feature):\\n if tag_col[index] == 6:\\n seq_score = torch.zeros(1).to(self.device)\\n continue\\n\\n # end the sequence tag score\\n if tag_col[index] == 7:\\n seq_score -= self.transitions[tag_col[index], tag_col[index - 1]]\\n batch_score += seq_score\\n continue\\n\\n # seq_score = seq_score + self.f(feat[tag_col[index]]) + self.f(self.transitions[tag_col[index + 1], tag_col[index]])\\n seq_score = seq_score + feat[tag_col[index]] + self.transitions[tag_col[index + 1], tag_col[index]]\\n\\n return batch_score\\n\\n def all_path_loss(self, word_feature, input_ids):\\n forward_var = torch.zeros(self.tag_size, 1).to(self.device)\\n all_path_score = torch.zeros(1).to(self.device)\\n\\n for index, feat in enumerate(word_feature):\\n if input_ids[index] == 101:\\n # forward_var = feat.view(self.tag_size, 1)\\n forward_var = torch.zeros(self.tag_size, 1).to(self.device)\\n\\n # forward_var = torch.full((1, self.tag_size), -100000).to(self.device)\\n # forward_var[0][self.target_to_index['START']] = 0\\n continue\\n\\n if input_ids[index] == 102:\\n forward_var = forward_var.view(1, self.tag_size)\\n all_path_score += self.log_sum_exp(forward_var)\\n continue\\n\\n # expand to n * n\\n forward_var = forward_var.expand(self.tag_size, self.tag_size)\\n # feat = self.f(feat.view(1, -1))\\n feat = feat.view(1, -1)\\n emission = feat.expand(self.tag_size, self.tag_size)\\n\\n # score = forward_var + emission + self.f(torch.t(self.transitions))\\n score = forward_var + emission + torch.t(self.transitions)\\n forward_var = self.log_sum_exp(score).view(self.tag_size, 1)\\n\\n return all_path_score\\n\\n def loss(self, word_feature, input_ids, target_col):\\n truth_path_score = self.truth_path_loss(word_feature, input_ids, target_col)\\n all_path_score = self.all_path_loss(word_feature, input_ids)\\n return all_path_score - truth_path_score\\n\"\n },\n {\n \"alpha_fraction\": 0.5853132009506226,\n \"alphanum_fraction\": 0.593952476978302,\n \"avg_line_length\": 28,\n \"blob_id\": \"6fa0c87eaaa466d064db2ec5092800b4d373121e\",\n \"content_id\": \"c5c55afd739c6544491023555e9a7cae3f9e5eee\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 463,\n \"license_type\": \"no_license\",\n \"max_line_length\": 41,\n \"num_lines\": 16,\n \"path\": \"/Config.py\",\n \"repo_name\": \"eppoha/BGC_Comparative\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"class Config(object):\\n def __init__(self, args):\\n self.input_size = args.input\\n self.hidden_size = args.hidden\\n\\n self.num_layers = args.layer\\n self.num_classes = 6\\n\\n self.epochs = args.epoch\\n self.batch_size = args.batch\\n self.device = args.device\\n\\n self.train_data_path = args.train\\n self.test_data_path = args.test\\n self.bert_model_path = args.bert\\n self.hidden_dropout_prob = 0.05\"\n },\n {\n \"alpha_fraction\": 0.6379280686378479,\n \"alphanum_fraction\": 0.6478105187416077,\n \"avg_line_length\": 39.75694274902344,\n \"blob_id\": \"351031850fd803873a736ff8f086417213e10c68\",\n \"content_id\": \"797b9946b663294f689328532b791c5bba17a7cd\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 5869,\n \"license_type\": \"no_license\",\n \"max_line_length\": 102,\n \"num_lines\": 144,\n \"path\": \"/Main.py\",\n \"repo_name\": \"eppoha/BGC_Comparative\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import torch\\nimport torch.nn as nn\\nimport torch.optim as optim\\nimport torch.nn.functional as F\\n\\nimport os\\nimport argparse\\nimport Model\\nimport MyData\\nimport DataProcess\\n# import PreProcess\\nimport Config\\nimport Evaluation\\nimport matplotlib.pyplot as plt\\nimport matplotlib\\nimport Bert_GRU_CRF_Model\\n\\nfrom pytorch_pretrained_bert import BertAdam\\n\\n\\n# padding data and return input_ids, token_type_ids, attention_mask\\ndef padding_data(data, target, maxLen):\\n input_ids = [line + [0] * (maxLen - len(line)) for line in data]\\n token_type_ids = [[0] * maxLen for _ in data]\\n attention_mask = [[1] * len(line) + [0] * (maxLen - len(line)) for line in data]\\n target_col = [line + [-1] * (maxLen - len(line)) for line in target]\\n return input_ids, token_type_ids, attention_mask, target_col\\n\\n\\ndef TrainModel(model, optimizer, train_loader, maxLen, device, epoch):\\n epoch_loss, t = 0, 0\\n for index, (data, target) in enumerate(train_loader):\\n # through data to get input_ids, token_type_ids, attention_mask\\n if index >= 10 and index % 10 == 0:\\n print(\\\"index: \\\", index)\\n input_ids, token_type_ids, attention_mask, target_col = padding_data(data, target, maxLen)\\n\\n input_ids = torch.tensor(input_ids).long().to(device)\\n token_type_ids = torch.tensor(token_type_ids).long().to(device)\\n attention_mask = torch.tensor(attention_mask).long().to(device)\\n target_col = torch.tensor(target_col).to(device)\\n\\n loss = model(input_ids, token_type_ids, attention_mask, target_col)\\n epoch_loss += loss.item()\\n\\n optimizer.zero_grad()\\n loss.backward()\\n optimizer.step()\\n t = index\\n\\n print(\\\"Loss: {}\\\".format(epoch_loss / t))\\n\\n\\ndef TestModel(model, test_loader, maxLen, device, epoch):\\n total, correct = 0, 0\\n res_eval = Evaluation.Result_Eval(6)\\n with torch.no_grad():\\n for index, (data, target) in enumerate(test_loader):\\n # through data to get input_ids, token_type_ids, attention_mask\\n input_ids, token_type_ids, attention_mask, target_col = padding_data(data, target, maxLen)\\n\\n input_ids = torch.tensor(input_ids).long().to(device)\\n token_type_ids = torch.tensor(token_type_ids).long().to(device)\\n attention_mask = torch.tensor(attention_mask).long().to(device)\\n target_col = torch.tensor(target_col).to(device)\\n\\n target_col = target_col[attention_mask == 1]\\n\\n output = model(input_ids, token_type_ids, attention_mask)\\n\\n total += torch.sum(attention_mask == 1).item()\\n correct += torch.sum(target_col == output).item()\\n attention_mask = attention_mask[attention_mask == 1]\\n\\n res_eval.add(output, target_col, attention_mask)\\n res_eval.eval_model()\\n print(\\\"ACC: {:.2f}%, correct/total: {}/{}\\\".format(correct / total * 100, correct, total))\\n\\n\\ndef TerminalParser():\\n # define train data path and test data path\\n train_data_path = \\\"./result/char_train.data\\\"\\n test_data_path = \\\"./result/char_test.data\\\"\\n bert_model_path = \\\"/home/zhliu/RTX/modeling_bert/bert-base-chinese.tar.gz\\\"\\n # bert_model_path = \\\"C:\\\\\\\\Users\\\\\\\\curry\\\\\\\\Desktop\\\\\\\\modeling_bert\\\\\\\\bert-base-chinese.tar.gz\\\"\\n\\n # define parse parameters\\n parser = argparse.ArgumentParser()\\n parser.description = 'choose train data and test data file path'\\n parser.add_argument('--train', help='train data file path', default=train_data_path)\\n parser.add_argument('--test', help='test data file path', default=test_data_path)\\n parser.add_argument('--bert', help='bert model file path', default=bert_model_path)\\n parser.add_argument('--batch', help='input data batch size', default=5)\\n parser.add_argument('--input', help='input data size', default=768)\\n parser.add_argument('--hidden', help='gru hidden size', default=100)\\n parser.add_argument('--layer', help='the number of gru layer', default=3)\\n parser.add_argument('--epoch', help='the number of run times', default=100)\\n parser.add_argument('--device', help='run program in device type', default='cuda')\\n # parser.add_argument('--device', help='run program in device type', default='cpu')\\n args = parser.parse_args()\\n\\n config_obj = Config.Config(args)\\n return config_obj\\n\\n\\ndef main():\\n # get some configure and hyper-parameters\\n args = TerminalParser()\\n\\n # get standard data file\\n if not os.path.exists(args.train_data_path) or not os.path.exists(args.test_data_path):\\n PreProcess.pre_process_main()\\n\\n train_path = \\\"./result/char_train.data\\\"\\n test_path = \\\"./result/char_test.data\\\"\\n\\n # get vocab and max sequence length\\n vocab, maxLen = DataProcess.get_vocab(train_path, test_path)\\n maxLen += 10\\n\\n # get train data and test data BERT\\n train_data, train_target = DataProcess.get_bert_data(train_path)\\n test_data, test_target = DataProcess.get_bert_data(test_path)\\n\\n # define train data and test data\\n train_loader = MyData.get_loader(train_data, train_target, args.batch_size)\\n test_loader = MyData.get_loader(test_data, test_target, args.batch_size)\\n\\n # define model and optimizer\\n model = Bert_GRU_CRF_Model.BGCM(args).to(args.device)\\n optimizer = optim.Adam([{'params': model.fc2.parameters(), 'lr': 0.001},\\n {'params': model.fc1.parameters(), 'lr': 0.001},\\n {'params': model.bert.parameters(), 'lr': 2e-5},\\n {'params': model.gru.parameters(), 'lr': 0.001},\\n {'params': model.crf.parameters(), 'lr': 0.001}], weight_decay=0.01)\\n\\n # train model and test model\\n for epoch in range(args.epochs):\\n TrainModel(model, optimizer, train_loader, maxLen, args.device, epoch)\\n TestModel(model, test_loader, maxLen, args.device, epoch)\\n\\n\\nif __name__ == \\\"__main__\\\":\\n main()\\n\"\n },\n {\n \"alpha_fraction\": 0.6370157599449158,\n \"alphanum_fraction\": 0.6398852467536926,\n \"avg_line_length\": 23.821428298950195,\n \"blob_id\": \"5c175d39c3aaf68daf4edf0f15fc2f4a098342dd\",\n \"content_id\": \"902dba4540e0ba200c0ea42193dfe18c13374c17\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 697,\n \"license_type\": \"no_license\",\n \"max_line_length\": 86,\n \"num_lines\": 28,\n \"path\": \"/MyData.py\",\n \"repo_name\": \"eppoha/BGC_Comparative\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import numpy as np\\nimport torch\\nfrom torch.utils.data import Dataset, DataLoader\\n\\n\\nclass MyData(Dataset):\\n def __init__(self, data, target):\\n self.data = data\\n self.target = target\\n\\n def __len__(self):\\n return len(self.data)\\n\\n def __getitem__(self, index):\\n data = self.data[index]\\n target = self.target[index]\\n return [data, target]\\n\\n\\ndef collate_fn(data):\\n input, target = list(list(zip(*data))[0]), list(list(zip(*data))[1])\\n return input, target\\n\\n\\ndef get_loader(data, target, batch_size):\\n dataset = MyData(data, target)\\n dataloader = DataLoader(dataset, batch_size, shuffle=False, collate_fn=collate_fn)\\n return dataloader\\n\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.6316171288490295,\n \"alphanum_fraction\": 0.6403190493583679,\n \"avg_line_length\": 32.65853500366211,\n \"blob_id\": \"806b4e816fb2533686ab5e082e5fc184ca0dc77c\",\n \"content_id\": \"12ae6f7ca003535e1959b5ad74ae75c95c65d11a\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1379,\n \"license_type\": \"no_license\",\n \"max_line_length\": 82,\n \"num_lines\": 41,\n \"path\": \"/Bert_GRU_CRF_Model.py\",\n \"repo_name\": \"eppoha/BGC_Comparative\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import torch\\nimport torch.nn as nn\\nimport torch.optim as optim\\nimport torch.nn.functional as F\\n\\nimport Main\\nimport Evaluation\\nfrom Model import BERT_Cell, BiGRU_Cell, CRF_Cell\\n\\n\\nclass BGCM(nn.Module):\\n def __init__(self, config):\\n super(BGCM, self).__init__()\\n self.bert = BERT_Cell(config.bert_model_path)\\n self.dropout = nn.Dropout(0.1)\\n\\n self.gru = BiGRU_Cell(config)\\n self.fc1 = nn.Linear(config.input_size, 2 * config.hidden_size)\\n self.fc2 = nn.Linear(2 * config.hidden_size, config.num_classes + 2)\\n self.crf = CRF_Cell(config)\\n\\n def forward(self, input_ids, token_type_ids, attention_mask, target_col=None):\\n x_word_embedding = self.bert(input_ids, token_type_ids, attention_mask)\\n x_word_embedding = self.dropout(x_word_embedding)\\n\\n bert_feature = self.fc1(x_word_embedding)\\n word_feature = self.gru(x_word_embedding)\\n\\n emission_prob = self.fc2(word_feature + bert_feature)\\n\\n features = emission_prob[attention_mask == 1]\\n sequence_ids = input_ids[attention_mask == 1]\\n\\n if target_col is None:\\n output = self.crf.viterbi_decode(features, sequence_ids)\\n return output\\n\\n else:\\n sequence_tags = target_col[attention_mask == 1]\\n loss = self.crf.loss(features, sequence_ids, sequence_tags)\\n return loss\"\n },\n {\n \"alpha_fraction\": 0.5480672121047974,\n \"alphanum_fraction\": 0.5579842329025269,\n \"avg_line_length\": 32.619049072265625,\n \"blob_id\": \"5bcae6497b195d8a90394f76ec7affe058513e76\",\n \"content_id\": \"b294695e03ceedd2b83d25e1cb6cc940a551e728\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 4945,\n \"license_type\": \"no_license\",\n \"max_line_length\": 85,\n \"num_lines\": 147,\n \"path\": \"/PreProcess.py\",\n \"repo_name\": \"eppoha/BGC_Comparative\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import os\\nimport re\\nimport numpy as np\\nfrom stanfordcorenlp import StanfordCoreNLP\\n\\n\\ndef process_label(path, type, inverse_class_dict):\\n label_col, last_doc = [], \\\"\\\"\\n\\n with open(path, 'r', encoding='gb18030', errors='ignore') as f:\\n for line in f.readlines():\\n word_list = list(filter(None, line.split()))\\n\\n # type == 0 denote train label\\n if type == 0:\\n doc_num = word_list[0]\\n tag_col = word_list[1:]\\n\\n # type == 1 denote test label\\n else:\\n doc_num = word_list[1]\\n tag_col = word_list[-5:]\\n\\n sentence_tag = {}\\n for index, tag_word in enumerate(tag_col):\\n temp_list = []\\n if tag_word == \\\"NULL\\\":\\n continue\\n\\n if tag_word.find(\\\"|\\\") != -1:\\n temp_list = tag_word.split('|')\\n\\n elif tag_word.find(\\\"...\\\") != -1:\\n temp_list = tag_word.split('...')\\n\\n elif tag_word.find(\\\"、\\\") != -1:\\n temp_list = tag_word.split('、')\\n\\n else:\\n temp_list = [tag_word]\\n\\n for token in temp_list:\\n sentence_tag[token] = inverse_class_dict[index + 1]\\n\\n if doc_num == last_doc:\\n for key, value in sentence_tag.items():\\n if key not in label_col[-1]:\\n label_col[-1][key] = value\\n else:\\n label_col.append(sentence_tag)\\n\\n last_doc = doc_num\\n return label_col\\n\\n\\ndef process_data(path, tag_col, class_dict):\\n input_data, target = [], []\\n pattern = r'<DOC[0-9]+>\\\\t([\\\\s\\\\S]*?)</DOC[0-9]+>'\\n with open(path, \\\"r\\\", encoding='gb18030', errors='ignore') as f:\\n file_data = f.read()\\n data = re.findall(pattern, file_data)\\n\\n # error label col or file error\\n if len(data) != len(tag_col):\\n print(\\\"Please check your label collection !\\\")\\n\\n for index, doc in enumerate(data):\\n label = np.zeros(len(doc), dtype=int)\\n\\n for key, value in tag_col[index].items():\\n s_index = doc.find(key)\\n e_index = s_index + len(key)\\n\\n label[s_index: e_index] = class_dict[value]\\n\\n input_data.append(doc)\\n target.append(label.tolist())\\n\\n return input_data, target\\n\\n\\ndef char_feature(input_data, target):\\n return input_data, target\\n\\n\\ndef token_feature(input_data, target):\\n stanford_nlp = StanfordCoreNLP('C:\\\\\\\\stanford-corenlp-full-2018-10-05', lang='zh')\\n\\n final_data, final_target = [], []\\n for i, doc in enumerate(input_data):\\n token_list, index = stanford_nlp.word_tokenize(doc), 0\\n temp_target = [0] * len(token_list)\\n\\n for j in range(len(token_list)):\\n class_count = np.zeros(6)\\n for k in range(len(token_list[j])):\\n class_count[target[i][index]] += 1\\n index += 1\\n temp_target[j] = np.argmax(class_count).item()\\n\\n final_data.append(token_list)\\n final_target.append(temp_target)\\n return final_data, final_target\\n\\n\\ndef store_process_data(data, target, path):\\n write_str = \\\"\\\"\\n for i in range(len(data)):\\n for j in range(len(data[i])):\\n write_str += data[i][j] + ' ' + str(target[i][j]) + '\\\\n'\\n write_str += '\\\\n'\\n with open(path, 'w', encoding='utf8', errors='ignore') as f:\\n f.write(write_str)\\n\\n\\ndef pre_process_main():\\n train_data_path = \\\"./data/train_data.txt\\\"\\n train_label_path = \\\"./data/train_label.txt\\\"\\n test_data_path = \\\"./data/test_data.txt\\\"\\n test_label_path = \\\"./data/test_label.txt\\\"\\n\\n class_dict = {\\\"OTHERS\\\": 0, \\\"OBJ\\\": 1, \\\"SUB\\\": 2, \\\"ATTR\\\": 3, \\\"SENTI\\\": 4, \\\"KW\\\": 5}\\n inverse_class_dict = {v: k for k, v in class_dict.items()}\\n print(inverse_class_dict)\\n\\n # get train data label and test data label\\n train_tag = process_label(train_label_path, 0, inverse_class_dict)\\n test_tag = process_label(test_label_path, 1, inverse_class_dict)\\n\\n # get train data and label\\n train_data, train_target = process_data(train_data_path, train_tag, class_dict)\\n test_data, test_target = process_data(test_data_path, test_tag, class_dict)\\n\\n # # get token feature\\n # train_final_data, train_final_target = token_feature(train_data, train_target)\\n # test_final_data, test_final_target = token_feature(test_data, test_target)\\n\\n # get char feature\\n train_final_data, train_final_target = char_feature(train_data, train_target)\\n test_final_data, test_final_target = char_feature(test_data, test_target)\\n\\n # store pre-process data and target\\n store_train_path = \\\"./result/char_train.data\\\"\\n store_test_path = \\\"./result/char_test.data\\\"\\n\\n store_process_data(train_final_data, train_final_target, store_train_path)\\n store_process_data(test_final_data, test_final_target, store_test_path)\"\n }\n]"},"num_files":{"kind":"number","value":7,"string":"7"}}},{"rowIdx":2064,"cells":{"repo_name":{"kind":"string","value":"kennneth1/Pokemon-Data-Analysis"},"repo_url":{"kind":"string","value":"https://github.com/kennneth1/Pokemon-Data-Analysis"},"snapshot_id":{"kind":"string","value":"22c67fe2c42948dcc9873bd8a36191bb5d65da0a"},"revision_id":{"kind":"string","value":"405267d4a65dc963251e0a5f28a4c04312d8eeb5"},"directory_id":{"kind":"string","value":"aa4f664db8c305a2200d2eb7c42729c5c718e6a3"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"string","value":"2020-04-03T14:38:19.301424"},"revision_date":{"kind":"string","value":"2018-10-30T05:52:36"},"committer_date":{"kind":"string","value":"2018-10-30T05:52:36"},"github_id":{"kind":"number","value":155329013,"string":"155,329,013"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.6350482106208801,"alphanum_fraction":0.651125431060791,"avg_line_length":23.773332595825195,"blob_id":"6ca530a000c761ff7dbd428001aaa98d22ede460","content_id":"8e2ea65dd820e282a9b4fe47d649a13742c444f9","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1866,"license_type":"no_license","max_line_length":77,"num_lines":75,"path":"/Pokemon.py","repo_name":"kennneth1/Pokemon-Data-Analysis","src_encoding":"UTF-8","text":"import os\nimport pandas as pd\nimport numpy as np\nimport matplotlib.pyplot as plt\nfrom numpy.polynomial.polynomial import polyfit\nimport seaborn as sns\n\ndataset = pd.read_csv(os.path.expanduser(\"~/Desktop/Pokemon/Pokemon.csv\"))\ndata = dataset.loc[:, \"Name\":\"Legendary\"]\nattack_by_type = {}\n\n\n#Removes all entries of Pokemon with more an irregular name\ndef data_cleaner(df):\n\n names = df['Name']\n bool_mask = ~(names.str.contains(' '))\n cleaned_data = df[bool_mask]\n return cleaned_data\n\n\ndef attack_plotter():\n\n poke_types = data['Type 1'].unique()\n\n for type in poke_types:\n selected_rows = data[data['Type 1'] == type]\n mean = selected_rows['Attack'].mean()\n attack_by_type[type] = mean\n average_attack = pd.DataFrame().append(attack_by_type, ignore_index=True)\n\n fig = plt.figure(figsize=(8, 8))\n ax = fig.add_subplot(1, 1, 1)\n\n bar_positions = np.arange(18) + 0.75\n bar_heights = average_attack.iloc[0].values\n ax.bar(bar_positions, bar_heights, 0.5)\n\n tick_positions = range(1,19)\n ax.set_xticks(tick_positions)\n\n ax.set_xticklabels(list(average_attack.columns.values), rotation=90)\n plt.legend(loc=\"upper left\")\n ax.set_title(\"Pokemon Types vs. Attack\")\n plt.show()\n\n\n#Finding relationship between tankiness and damage output\n\ndef hp_vs_attack():\n attack = data['Attack']\n hp = data['HP']\n\n fig = plt.figure(figsize=(8, 8))\n ax = fig.add_subplot(1, 1, 1)\n\n sns.regplot(attack, hp)\n ax.set_xlabel(\"Attack\")\n ax.set_ylabel(\"Health Points\")\n plt.show()\n\n\n#Explores whether speed makes you stronger\ndef speed_vs_attack():\n\n defense = data['Defense']\n attack = data['Attack']\n\n fig = plt.figure(figsize=(8, 8))\n ax = fig.add_subplot(1, 1, 1)\n\n ax.scatter(defense, attack)\n ax.set_xlabel(\"Defense\")\n ax.set_ylabel(\"Attack\")\n plt.show()\n\n\n\n\n\n\n\n\n"},{"alpha_fraction":0.805042028427124,"alphanum_fraction":0.805042028427124,"avg_line_length":44.769229888916016,"blob_id":"f48b7039303cb4ad04ae7cb0bc2c506fc77488b2","content_id":"652b8e33f8a80b51c11cafe9f6d4bafba28266e2","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":595,"license_type":"no_license","max_line_length":114,"num_lines":13,"path":"/README.md","repo_name":"kennneth1/Pokemon-Data-Analysis","src_encoding":"UTF-8","text":"# Pokemon-Data-Analysis\n\nThis program takes the Pokemon.csv file, cleans the entry names, and explores/visualizes the dataset\n\nattack_plotter() aggregates Pokemon data by \"Type\", calculates the mean of that group, then generates a bar plot.\n\n*(Dragon type pokemon tend to have base attack stats)\n\nhp_vs_attack() and speed_vs_attack() compares important pokemon stats to visualize trends and notable correlations\n\nhp_vs_attack shows weak correlation, whereas speed_vs_attack has a strong upwards correlation\n\nThe distribution curve shows that the attack stat falls within a standard distribution\n"}],"string":"[\n {\n \"alpha_fraction\": 0.6350482106208801,\n \"alphanum_fraction\": 0.651125431060791,\n \"avg_line_length\": 23.773332595825195,\n \"blob_id\": \"6ca530a000c761ff7dbd428001aaa98d22ede460\",\n \"content_id\": \"8e2ea65dd820e282a9b4fe47d649a13742c444f9\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1866,\n \"license_type\": \"no_license\",\n \"max_line_length\": 77,\n \"num_lines\": 75,\n \"path\": \"/Pokemon.py\",\n \"repo_name\": \"kennneth1/Pokemon-Data-Analysis\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import os\\nimport pandas as pd\\nimport numpy as np\\nimport matplotlib.pyplot as plt\\nfrom numpy.polynomial.polynomial import polyfit\\nimport seaborn as sns\\n\\ndataset = pd.read_csv(os.path.expanduser(\\\"~/Desktop/Pokemon/Pokemon.csv\\\"))\\ndata = dataset.loc[:, \\\"Name\\\":\\\"Legendary\\\"]\\nattack_by_type = {}\\n\\n\\n#Removes all entries of Pokemon with more an irregular name\\ndef data_cleaner(df):\\n\\n names = df['Name']\\n bool_mask = ~(names.str.contains(' '))\\n cleaned_data = df[bool_mask]\\n return cleaned_data\\n\\n\\ndef attack_plotter():\\n\\n poke_types = data['Type 1'].unique()\\n\\n for type in poke_types:\\n selected_rows = data[data['Type 1'] == type]\\n mean = selected_rows['Attack'].mean()\\n attack_by_type[type] = mean\\n average_attack = pd.DataFrame().append(attack_by_type, ignore_index=True)\\n\\n fig = plt.figure(figsize=(8, 8))\\n ax = fig.add_subplot(1, 1, 1)\\n\\n bar_positions = np.arange(18) + 0.75\\n bar_heights = average_attack.iloc[0].values\\n ax.bar(bar_positions, bar_heights, 0.5)\\n\\n tick_positions = range(1,19)\\n ax.set_xticks(tick_positions)\\n\\n ax.set_xticklabels(list(average_attack.columns.values), rotation=90)\\n plt.legend(loc=\\\"upper left\\\")\\n ax.set_title(\\\"Pokemon Types vs. Attack\\\")\\n plt.show()\\n\\n\\n#Finding relationship between tankiness and damage output\\n\\ndef hp_vs_attack():\\n attack = data['Attack']\\n hp = data['HP']\\n\\n fig = plt.figure(figsize=(8, 8))\\n ax = fig.add_subplot(1, 1, 1)\\n\\n sns.regplot(attack, hp)\\n ax.set_xlabel(\\\"Attack\\\")\\n ax.set_ylabel(\\\"Health Points\\\")\\n plt.show()\\n\\n\\n#Explores whether speed makes you stronger\\ndef speed_vs_attack():\\n\\n defense = data['Defense']\\n attack = data['Attack']\\n\\n fig = plt.figure(figsize=(8, 8))\\n ax = fig.add_subplot(1, 1, 1)\\n\\n ax.scatter(defense, attack)\\n ax.set_xlabel(\\\"Defense\\\")\\n ax.set_ylabel(\\\"Attack\\\")\\n plt.show()\\n\\n\\n\\n\\n\\n\\n\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.805042028427124,\n \"alphanum_fraction\": 0.805042028427124,\n \"avg_line_length\": 44.769229888916016,\n \"blob_id\": \"f48b7039303cb4ad04ae7cb0bc2c506fc77488b2\",\n \"content_id\": \"652b8e33f8a80b51c11cafe9f6d4bafba28266e2\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 595,\n \"license_type\": \"no_license\",\n \"max_line_length\": 114,\n \"num_lines\": 13,\n \"path\": \"/README.md\",\n \"repo_name\": \"kennneth1/Pokemon-Data-Analysis\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# Pokemon-Data-Analysis\\n\\nThis program takes the Pokemon.csv file, cleans the entry names, and explores/visualizes the dataset\\n\\nattack_plotter() aggregates Pokemon data by \\\"Type\\\", calculates the mean of that group, then generates a bar plot.\\n\\n*(Dragon type pokemon tend to have base attack stats)\\n\\nhp_vs_attack() and speed_vs_attack() compares important pokemon stats to visualize trends and notable correlations\\n\\nhp_vs_attack shows weak correlation, whereas speed_vs_attack has a strong upwards correlation\\n\\nThe distribution curve shows that the attack stat falls within a standard distribution\\n\"\n }\n]"},"num_files":{"kind":"number","value":2,"string":"2"}}},{"rowIdx":2065,"cells":{"repo_name":{"kind":"string","value":"KhaoulaDER/holbertonschool-backend-user-data"},"repo_url":{"kind":"string","value":"https://github.com/KhaoulaDER/holbertonschool-backend-user-data"},"snapshot_id":{"kind":"string","value":"9b4d10983c2a7eb0e256b61ff0c48d3323cfecf5"},"revision_id":{"kind":"string","value":"ffd54178c296811573b93f194d2d9232d70b3409"},"directory_id":{"kind":"string","value":"3d0f70909a2aa11f6df9d3e71e7dd94176646bfc"},"branch_name":{"kind":"string","value":"refs/heads/main"},"visit_date":{"kind":"string","value":"2023-07-23T13:43:56.221636"},"revision_date":{"kind":"string","value":"2021-09-03T16:17:00"},"committer_date":{"kind":"string","value":"2021-09-03T16:17:00"},"github_id":{"kind":"number","value":402711137,"string":"402,711,137"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.6667270660400391,"alphanum_fraction":0.7013505101203918,"avg_line_length":26.824716567993164,"blob_id":"97a39f794ee5abda6f4486227ecc75fda64cda3f","content_id":"8d50e6f37febf9b96b19a8e9ff2aee6cc3b88a00","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":22084,"license_type":"no_license","max_line_length":363,"num_lines":793,"path":"/0x03-user_authentication_service/README.md","repo_name":"KhaoulaDER/holbertonschool-backend-user-data","src_encoding":"UTF-8","text":"# 0x03. User authentication service\n\n\n\nIn the industry, you should **not** implement your own authentication system and use a module or framework that doing it for you (like in Python-Flask: [Flask-User](https://intranet.hbtn.io/rltoken/r1XmxzZ-clc7laax6Tm7WQ \"Flask-User\")). Here, for the learning purpose, we will walk through each step of this mechanism to understand it by doing.\n\n## Resources\n\n**Read or watch:**\n\n- [Flask documentation](https://intranet.hbtn.io/rltoken/LSFQS3aarknJpMZVr9Je1Q \"Flask documentation\")\n- [Requests module](https://intranet.hbtn.io/rltoken/PqxwI-hQOe4b4Hhah4fbVg \"Requests module\")\n- [HTTP status codes](https://intranet.hbtn.io/rltoken/QoqUvOM9taMBOVaeB_g06g \"HTTP status codes\")\n\n## Learning Objectives\n\nAt the end of this project, you are expected to be able to [explain to anyone](https://intranet.hbtn.io/rltoken/IAeORv21eo25XYJByjx_bg \"explain to anyone\"), **without the help of Google**:\n\n- How to declare API routes in a Flask app\n- How to get and set cookies\n- How to retrieve request form data\n- How to return various HTTP status codes\n\n\n## Setup\n\nYou will need to install `bcrypt`\n\n```\npip3 install bcrypt\n\n```\n\n## Tasks\n\n### 0. User model\n\n\nIn this task you will create a SQLAlchemy model named `User` for a database table named `users` (by using the [mapping declaration](https://intranet.hbtn.io/rltoken/IF5xw2va364LrJEntCXLlg \"mapping declaration\") of SQLAlchemy).\n\nThe model will have the following attributes:\n\n- `id`, the integer primary key\n- `email`, a non-nullable string\n- `hashed_password`, a non-nullable string\n- `session_id`, a nullable string\n- `reset_token`, a nullable string\n\n```\nbob@dylan:~$ cat main.py\n#!/usr/bin/env python3\n\"\"\"\nMain file\n\"\"\"\nfrom user import User\n\nprint(User.__tablename__)\n\nfor column in User.__table__.columns:\n print(\"{}: {}\".format(column, column.type))\n\nbob@dylan:~$ python3 main.py\nusers\nusers.id: INTEGER\nusers.email: VARCHAR(250)\nusers.hashed_password: VARCHAR(250)\nusers.session_id: VARCHAR(250)\nusers.reset_token: VARCHAR(250)\nbob@dylan:~$ \n\n```\n\n\n### 1. create user\n\n\nIn this task, you will complete the `DB` class provided below to implement the `add_user` method.\n\n```\n\"\"\"DB module\n\"\"\"\nfrom sqlalchemy import create_engine\nfrom sqlalchemy.ext.declarative import declarative_base\nfrom sqlalchemy.orm import sessionmaker\nfrom sqlalchemy.orm.session import Session\n\nfrom user import Base\n\n\nclass DB:\n \"\"\"DB class\n \"\"\"\n\n def __init__(self) -> None:\n \"\"\"Initialize a new DB instance\n \"\"\"\n self._engine = create_engine(\"sqlite:///a.db\", echo=True)\n Base.metadata.drop_all(self._engine)\n Base.metadata.create_all(self._engine)\n self.__session = None\n\n @property\n def _session(self) -> Session:\n \"\"\"Memoized session object\n \"\"\"\n if self.__session is None:\n DBSession = sessionmaker(bind=self._engine)\n self.__session = DBSession()\n return self.__session\n\n```\n\nNote that `DB._session` is a private property and hence should NEVER be used from outside the `DB` class.\n\nImplement the `add_user` method, which has two required string arguments: `email` and `hashed_password`, and returns a `User` object. The method should save the user to the database. No validations are required at this stage.\n\n```\nbob@dylan:~$ cat main.py\n#!/usr/bin/env python3\n\"\"\"\nMain file\n\"\"\"\n\nfrom db import DB\nfrom user import User\n\nmy_db = DB()\n\nuser_1 = my_db.add_user(\"test@test.com\", \"SuperHashedPwd\")\nprint(user_1.id)\n\nuser_2 = my_db.add_user(\"test1@test.com\", \"SuperHashedPwd1\")\nprint(user_2.id)\n\nbob@dylan:~$ python3 main.py\n1\n2\nbob@dylan:~$\n\n```\n\n\n### 2. Find user\n\n\nIn this task you will implement the `DB.find_user_by` method. This method takes in arbitrary keyword arguments and returns the first row found in the `users` table as filtered by the method’s input arguments. No validation of input arguments required at this point.\n\nMake sure that SQLAlchemy’s `NoResultFound` and `InvalidRequestError` are raised when no results are found, or when wrong query arguments are passed, respectively.\n\n**Warning:**\n\n- `NoResultFound` has been moved from `sqlalchemy.orm.exc` to `sqlalchemy.exc` between the version 1.3.x and 1.4.x of SQLAchemy - please make sure you are importing it from `sqlalchemy.orm.exc`\n\n```\nbob@dylan:~$ cat main.py\n#!/usr/bin/env python3\n\"\"\"\nMain file\n\"\"\"\nfrom db import DB\nfrom user import User\n\nfrom sqlalchemy.exc import InvalidRequestError\nfrom sqlalchemy.orm.exc import NoResultFound\n\n\nmy_db = DB()\n\nuser = my_db.add_user(\"test@test.com\", \"PwdHashed\")\nprint(user.id)\n\nfind_user = my_db.find_user_by(email=\"test@test.com\")\nprint(find_user.id)\n\ntry:\n find_user = my_db.find_user_by(email=\"test2@test.com\")\n print(find_user.id)\nexcept NoResultFound:\n print(\"Not found\")\n\ntry:\n find_user = my_db.find_user_by(no_email=\"test@test.com\")\n print(find_user.id)\nexcept InvalidRequestError:\n print(\"Invalid\") \n\nbob@dylan:~$ python3 main.py\n1\n1\nNot found\nInvalid\nbob@dylan:~$ \n\n```\n\n\n### 3. update user\n\n\nIn this task, you will implement the `DB.update_user` method that takes as argument a required `user_id` integer and arbitrary keyword arguments, and returns `None`.\n\nThe method will use `find_user_by` to locate the user to update, then will update the user’s attributes as passed in the method’s arguments then commit changes to the database.\n\nIf an argument that does not correspond to a user attribute is passed, raise a `ValueError`.\n\n```\nbob@dylan:~$ cat main.py\n#!/usr/bin/env python3\n\"\"\"\nMain file\n\"\"\"\nfrom db import DB\nfrom user import User\n\nfrom sqlalchemy.exc import InvalidRequestError\nfrom sqlalchemy.orm.exc import NoResultFound\n\n\nmy_db = DB()\n\nemail = 'test@test.com'\nhashed_password = \"hashedPwd\"\n\nuser = my_db.add_user(email, hashed_password)\nprint(user.id)\n\ntry:\n my_db.update_user(user.id, hashed_password='NewPwd')\n print(\"Password updated\")\nexcept ValueError:\n print(\"Error\")\n\nbob@dylan:~$ python3 main.py\n1\nPassword updated\nbob@dylan:~$ \n\n```\n\n\n### 4. Hash password\n\n\nIn this task you will define a `_hash_password` method that takes in a `password` string arguments and returns bytes.\n\nThe returned bytes is a salted hash of the input password, hashed with `bcrypt.hashpw`.\n\n```\nbob@dylan:~$ cat main.py\n#!/usr/bin/env python3\n\"\"\"\nMain file\n\"\"\"\nfrom auth import _hash_password\n\nprint(_hash_password(\"Hello Holberton\"))\n\nbob@dylan:~$ python3 main.py\nb'$2b$12$eUDdeuBtrD41c8dXvzh95ehsWYCCAi4VH1JbESzgbgZT.eMMzi.G2'\nbob@dylan:~$\n\n```\n\n\n### 5. Register user\n\n\nIn this task, you will implement the `Auth.register_user` in the `Auth` class provided below:\n\n```\nfrom db import DB\n\n\nclass Auth:\n \"\"\"Auth class to interact with the authentication database.\n \"\"\"\n\n def __init__(self):\n self._db = DB()\n\n```\n\nNote that `Auth._db` is a private property and should NEVER be used from outside the class.\n\n`Auth.register_user` should take mandatory `email` and `password` string arguments and return a `User` object.\n\nIf a user already exist with the passed email, raise a `ValueError` with the message `User <user's email> already exists`.\n\nIf not, hash the password with `_hash_password`, save the user to the database using `self._db` and return the `User` object.\n\n```\nbob@dylan:~$ cat main.py\n#!/usr/bin/env python3\n\"\"\"\nMain file\n\"\"\"\nfrom auth import Auth\n\nemail = 'me@me.com'\npassword = 'mySecuredPwd'\n\nauth = Auth()\n\ntry:\n user = auth.register_user(email, password)\n print(\"successfully created a new user!\")\nexcept ValueError as err:\n print(\"could not create a new user: {}\".format(err))\n\ntry:\n user = auth.register_user(email, password)\n print(\"successfully created a new user!\")\nexcept ValueError as err:\n print(\"could not create a new user: {}\".format(err)) \n\nbob@dylan:~$ python3 main.py\nsuccessfully created a new user!\ncould not create a new user: User me@me.com already exists\nbob@dylan:~$\n\n```\n\n\n### 6. Basic Flask app\n\n\nIn this task, you will set up a basic Flask app.\n\nCreate a Flask app that has a single `GET` route (`\"/\"`) and use `flask.jsonify` to return a JSON payload of the form:\n\n```\n{\"message\": \"Bienvenue\"}\n\n```\n\nAdd the following code at the end of the module:\n\n```\nif __name__ == \"__main__\":\n app.run(host=\"0.0.0.0\", port=\"5000\")\n\n```\n\n\n### 7. Register user\n\n\nIn this task, you will implement the end-point to register a user. Define a `users` function that implements the `POST /users` route.\n\nImport the `Auth` object and instantiate it at the root of the module as such:\n\n```\nfrom auth import Auth\n\n\nAUTH = Auth()\n\n```\n\nThe end-point should expect two form data fields: `\"email\"` and `\"password\"`. If the user does not exist, the end-point should register it and respond with the following JSON payload:\n\n```\n{\"email\": \"<registered email>\", \"message\": \"user created\"}\n\n```\n\nIf the user is already registered, catch the exception and return a JSON payload of the form\n\n```\n{\"message\": \"email already registered\"}\n\n```\n\nand return a 400 status code\n\nRemember that you should only use `AUTH` in this app. `DB` is a lower abstraction that is proxied by `Auth`.\n\n_Terminal 1:_\n\n```\nbob@dylan:~$ python3 app.py \n* Serving Flask app \"app\" (lazy loading)\n * Environment: production\n WARNING: This is a development server. Do not use it in a production deployment.\n Use a production WSGI server instead.\n * Debug mode: off\n * Running on http://0.0.0.0:5000/ (Press CTRL+C to quit)\n\n\n```\n\nTerminal 2:\n\n```\nbob@dylan:~$ curl -XPOST localhost:5000/users -d 'email=bob@me.com' -d 'password=mySuperPwd' -v\nNote: Unnecessary use of -X or --request, POST is already inferred.\n* Trying 127.0.0.1...\n* TCP_NODELAY set\n* Connected to localhost (127.0.0.1) port 5000 (#0)\n> POST /users HTTP/1.1\n> Host: localhost:5000\n> User-Agent: curl/7.58.0\n> Accept: */*\n> Content-Length: 40\n> Content-Type: application/x-www-form-urlencoded\n> \n* upload completely sent off: 40 out of 40 bytes\n* HTTP 1.0, assume close after body\n< HTTP/1.0 200 OK\n< Content-Type: application/json\n< Content-Length: 52\n< Server: Werkzeug/1.0.1 Python/3.7.3\n< Date: Wed, 19 Aug 2020 00:03:18 GMT\n< \n{\"email\":\"bob@me.com\",\"message\":\"user created\"}\n\nbob@dylan:~$\nbob@dylan:~$ curl -XPOST localhost:5000/users -d 'email=bob@me.com' -d 'password=mySuperPwd' -v\nNote: Unnecessary use of -X or --request, POST is already inferred.\n* Trying 127.0.0.1...\n* TCP_NODELAY set\n* Connected to localhost (127.0.0.1) port 5000 (#0)\n> POST /users HTTP/1.1\n> Host: localhost:5000\n> User-Agent: curl/7.58.0\n> Accept: */*\n> Content-Length: 40\n> Content-Type: application/x-www-form-urlencoded\n> \n* upload completely sent off: 40 out of 40 bytes\n* HTTP 1.0, assume close after body\n< HTTP/1.0 400 BAD REQUEST\n< Content-Type: application/json\n< Content-Length: 39\n< Server: Werkzeug/1.0.1 Python/3.7.3\n< Date: Wed, 19 Aug 2020 00:03:33 GMT\n< \n{\"message\":\"email already registered\"}\nbob@dylan:~$\n\n```\n\n\n### 8. Credentials validation\n\n\nIn this task, you will implement the `Auth.valid_login` method. It should expect `email` and `password` required arguments and return a boolean.\n\nTry locating the user by email. If it exists, check the password with `bcrypt.checkpw`. If it matches return `True`. In any other case, return `False`.\n\n```\nbob@dylan:~$ cat main.py\n#!/usr/bin/env python3\n\"\"\"\nMain file\n\"\"\"\nfrom auth import Auth\n\nemail = 'bob@bob.com'\npassword = 'MyPwdOfBob'\nauth = Auth()\n\nauth.register_user(email, password)\n\nprint(auth.valid_login(email, password))\n\nprint(auth.valid_login(email, \"WrongPwd\"))\n\nprint(auth.valid_login(\"unknown@email\", password))\n\nbob@dylan:~$ python3 main.py\nTrue\nFalse\nFalse\nbob@dylan:~$ \n\n```\n\n\n### 9. Generate UUIDs\n\n\nIn this task you will implement a `_generate_uuid` function in the `auth` module. The function should return a string representation of a new UUID. Use the `uuid` module.\n\nNote that the method is private to the `auth` module and should **NOT** be used outside of it.\n\n\n### 10. Get session ID\n\n\nIn this task, you will implement the `Auth.create_session` method. It takes an `email` string argument and returns the session ID as a string.\n\nThe method should find the user corresponding to the email, generate a new UUID and store it in the database as the user’s `session_id`, then return the session ID.\n\nRemember that only public methods of `self._db` can be used.\n\n```\nbob@dylan:~$ cat main.py\n#!/usr/bin/env python3\n\"\"\"\nMain file\n\"\"\"\nfrom auth import Auth\n\nemail = 'bob@bob.com'\npassword = 'MyPwdOfBob'\nauth = Auth()\n\nauth.register_user(email, password)\n\nprint(auth.create_session(email))\nprint(auth.create_session(\"unknown@email.com\"))\n\nbob@dylan:~$ python3 main.py\n5a006849-343e-4a48-ba4e-bbd523fcca58\nNone\nbob@dylan:~$ \n\n```\n\n\n### 11. Log in\n\n\nIn this task, you will implement a `login` function to respond to the `POST /sessions` route.\n\nThe request is expected to contain form data with `\"email\"` and a `\"password\"` fields.\n\nIf the login information is incorrect, use `flask.abort` to respond with a 401 HTTP status.\n\nOtherwise, create a new session for the user, store it the session ID as a cookie with key `\"session_id\"` on the response and return a JSON payload of the form\n\n```\n{\"email\": \"<user email>\", \"message\": \"logged in\"}\n\n```\n\n```\nbob@dylan:~$ curl -XPOST localhost:5000/users -d 'email=bob@bob.com' -d 'password=mySuperPwd'\n{\"email\":\"bob@bob.com\",\"message\":\"user created\"}\nbob@dylan:~$ \nbob@dylan:~$ curl -XPOST localhost:5000/sessions -d 'email=bob@bob.com' -d 'password=mySuperPwd' -v\nNote: Unnecessary use of -X or --request, POST is already inferred.\n* Trying 127.0.0.1...\n* TCP_NODELAY set\n* Connected to localhost (127.0.0.1) port 5000 (#0)\n> POST /sessions HTTP/1.1\n> Host: localhost:5000\n> User-Agent: curl/7.58.0\n> Accept: */*\n> Content-Length: 37\n> Content-Type: application/x-www-form-urlencoded\n> \n* upload completely sent off: 37 out of 37 bytes\n* HTTP 1.0, assume close after body\n< HTTP/1.0 200 OK\n< Content-Type: application/json\n< Content-Length: 46\n< Set-Cookie: session_id=163fe508-19a2-48ed-a7c8-d9c6e56fabd1; Path=/\n< Server: Werkzeug/1.0.1 Python/3.7.3\n< Date: Wed, 19 Aug 2020 00:12:34 GMT\n< \n{\"email\":\"bob@bob.com\",\"message\":\"logged in\"}\n* Closing connection 0\nbob@dylan:~$ \nbob@dylan:~$ curl -XPOST localhost:5000/sessions -d 'email=bob@bob.com' -d 'password=BlaBla' -v\nNote: Unnecessary use of -X or --request, POST is already inferred.\n* Trying 127.0.0.1...\n* TCP_NODELAY set\n* Connected to localhost (127.0.0.1) port 5000 (#0)\n> POST /sessions HTTP/1.1\n> Host: localhost:5000\n> User-Agent: curl/7.58.0\n> Accept: */*\n> Content-Length: 34\n> Content-Type: application/x-www-form-urlencoded\n> \n* upload completely sent off: 34 out of 34 bytes\n* HTTP 1.0, assume close after body\n< HTTP/1.0 401 UNAUTHORIZED\n< Content-Type: text/html; charset=utf-8\n< Content-Length: 338\n< Server: Werkzeug/1.0.1 Python/3.7.3\n< Date: Wed, 19 Aug 2020 00:12:45 GMT\n< \n<!DOCTYPE HTML PUBLIC \"-//W3C//DTD HTML 3.2 Final//EN\">\n<title>401 Unauthorized \n\"}\n\n```\n\nIf the session ID is invalid or the user does not exist, respond with a 403 HTTP status.\n\n```\nbob@dylan:~$ curl -XPOST localhost:5000/sessions -d 'email=bob@bob.com' -d 'password=mySuperPwd' -v\nNote: Unnecessary use of -X or --request, POST is already inferred.\n* Trying 127.0.0.1...\n* TCP_NODELAY set\n* Connected to localhost (127.0.0.1) port 5000 (#0)\n> POST /sessions HTTP/1.1\n> Host: localhost:5000\n> User-Agent: curl/7.58.0\n> Accept: */*\n> Content-Length: 37\n> Content-Type: application/x-www-form-urlencoded\n> \n* upload completely sent off: 37 out of 37 bytes\n* HTTP 1.0, assume close after body\n< HTTP/1.0 200 OK\n< Content-Type: application/json\n< Content-Length: 46\n< Set-Cookie: session_id=75c89af8-1729-44d9-a592-41b5e59de9a1; Path=/\n< Server: Werkzeug/1.0.1 Python/3.7.3\n< Date: Wed, 19 Aug 2020 00:15:57 GMT\n< \n{\"email\":\"bob@bob.com\",\"message\":\"logged in\"}\n* Closing connection 0\nbob@dylan:~$\nbob@dylan:~$ curl -XGET localhost:5000/profile -b \"session_id=75c89af8-1729-44d9-a592-41b5e59de9a1\"\n{\"email\": \"bob@bob.com\"}\nbob@dylan:~$ \nbob@dylan:~$ curl -XGET localhost:5000/profile -b \"session_id=nope\" -v\nNote: Unnecessary use of -X or --request, GET is already inferred.\n* Trying 127.0.0.1...\n* TCP_NODELAY set\n* Connected to localhost (127.0.0.1) port 5000 (#0)\n> GET /profile HTTP/1.1\n> Host: localhost:5000\n> User-Agent: curl/7.58.0\n> Accept: */*\n> Cookie: session_id=75c89af8-1729-44d9-a592-41b5e59de9a\n> \n* HTTP 1.0, assume close after body\n< HTTP/1.0 403 FORBIDDEN\n< Content-Type: text/html; charset=utf-8\n< Content-Length: 234\n< Server: Werkzeug/1.0.1 Python/3.7.3\n< Date: Wed, 19 Aug 2020 00:16:43 GMT\n< \n\n403 Forbidden \n\", \"reset_token\": \"\"}\n\n```\n\n\n### 18. Update password\n\n\nIn this task, you will implement the `Auth.update_password` method. It takes `reset_token` string argument and a `password` string argument and returns `None`.\n\nUse the `reset_token` to find the corresponding user. If it does not exist, raise a `ValueError` exception.\n\nOtherwise, hash the password and update the user’s `hashed_password` field with the new hashed password and the `reset_token` field to `None`.\n\n\n\n### 19. Update password end-point\n\n\nIn this task you will implement the `update_password` function in the `app` module to respond to the `PUT /reset_password` route.\n\nThe request is expected to contain form data with fields `\"email\"`, `\"reset_token\"` and `\"new_password\"`.\n\nUpdate the password. If the token is invalid, catch the exception and respond with a 403 HTTP code.\n\nIf the token is valid, respond with a 200 HTTP code and the following JSON payload:\n\n```\n{\"email\": \"\", \"message\": \"Password updated\"}\n\n```\n\n\n### 20. End-to-end integration test\n\n\nStart your app. Open a new terminal window.\n\nCreate a new module called `main.py`. Create one function for each of the following tasks. Use the `requests` module to query your web server for the corresponding end-point. Use `assert` to validate the response’s expected status code and payload (if any) for each task.\n\n- `register_user(email: str, password: str) -> None`\n- `log_in_wrong_password(email: str, password: str) -> None`\n- `log_in(email: str, password: str) -> str`\n- `profile_unlogged() -> None`\n- `profile_logged(session_id: str) -> None`\n- `log_out(session_id: str) -> None`\n- `reset_password_token(email: str) -> str`\n- `update_password(email: str, reset_token: str, new_password: str) -> None`\n\nThen copy the following code at the end of the `main` module:\n\n```\nEMAIL = \"guillaume@holberton.io\"\nPASSWD = \"b4l0u\"\nNEW_PASSWD = \"t4rt1fl3tt3\"\n\n\nif __name__ == \"__main__\":\n\n register_user(EMAIL, PASSWD)\n log_in_wrong_password(EMAIL, NEW_PASSWD)\n profile_unlogged()\n session_id = log_in(EMAIL, PASSWD)\n profile_logged(session_id)\n log_out(session_id)\n reset_token = reset_password_token(EMAIL)\n update_password(EMAIL, reset_token, NEW_PASSWD)\n log_in(EMAIL, NEW_PASSWD)\n\n```\n\nRun `python main.py`. If everything is correct, you should see no output.\n\n"},{"alpha_fraction":0.600247859954834,"alphanum_fraction":0.6114002466201782,"avg_line_length":27.02083396911621,"blob_id":"bf0c5a76f1df5584883b2672ebff364e9ca32a9f","content_id":"3830d34065b48f8eb54d8e2fca1aa5bbd77c266d","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":4035,"license_type":"no_license","max_line_length":71,"num_lines":144,"path":"/0x03-user_authentication_service/app.py","repo_name":"KhaoulaDER/holbertonschool-backend-user-data","src_encoding":"UTF-8","text":"#!/usr/bin/env python3\n\"\"\" Route module for the API \"\"\"\n\nfrom flask import Flask, jsonify, request, abort, redirect, url_for\nfrom sqlalchemy.orm.exc import NoResultFound\nfrom auth import Auth\n\n\napp = Flask(__name__)\nAUTH = Auth()\n\n\n@app.route('/', methods=['GET'], strict_slashes=False)\ndef status() -> str:\n \"\"\" GET /status\n Return:\n - JSON payload\n \"\"\"\n return jsonify({\"message\": \"Bienvenue\"})\n\n\n@app.route('/users', methods=['POST'], strict_slashes=False)\ndef new_user() -> str:\n \"\"\" POST /users\n Registers new user with email and pswd in request form-data,\n or finds if user already registered based on email\n Return:\n - JSON payload\n \"\"\"\n\n # Get data from form request, change to request.get_json() for body\n email = request.form.get(\"email\")\n password = request.form.get(\"password\")\n\n try:\n new_user = AUTH.register_user(email, password)\n if new_user is not None:\n return jsonify({\n \"email\": new_user.email,\n \"message\": \"user created\"\n })\n except ValueRrror:\n return jsonify({\n \"message\": \"email already registered\"\n }), 400\n\n\n@app.route('/sessions', methods=['POST'], strict_slashes=False)\ndef login() -> str:\n \"\"\" POST /sessions\n Creates new session for user, stores as cookie\n Email and pswd fields in x-www-form-urlencoded request\n Return:\n - JSON payload\n \"\"\"\n email = request.form.get(\"email\")\n password = request.form.get(\"password\")\n valid_user = AUTH.valid_login(email, password)\n\n if not valid_user:\n abort(401)\n session_id = AUTH.create_session(email)\n message = {\"email\": email, \"message\": \"logged in\"}\n response = jsonify(message)\n response.set_cookie(\"session_id\", session_id)\n return response\n\n\n@app.route('/sessions', methods=['DELETE'], strict_slashes=False)\ndef logout():\n \"\"\" DELETE /sessions\n Destroys session by finding session_id (key in cookie)\n Return:\n - Redirects user to status route (GET /)\n \"\"\"\n user_cookie = request.cookies.get(\"session_id\", None)\n user = AUTH.get_user_from_session_id(user_cookie)\n if user_cookie is None or user is None:\n abort(403)\n AUTH.destroy_session(user.id)\n return redirect('/')\n\n\n@app.route('/profile', methods=['GET'], strict_slashes=False)\ndef profile() -> str:\n \"\"\" GET /profile\n Return:\n - Use session_id to find the user.\n - 403 if session ID is invalid\n \"\"\"\n user_cookie = request.cookies.get(\"session_id\", None)\n if user_cookie is None:\n abort(403)\n user = AUTH.get_user_from_session_id(user_cookie)\n if user is None:\n abort(403)\n return jsonify({\"email\": user.email}), 200\n\n\n@app.route('/reset_password', methods=['POST'], strict_slashes=False)\ndef get_reset_password_token() -> str:\n \"\"\" POST /reset_password\n - email\n Return:\n - Generate a Token\n - 403 if email not registered\n \"\"\"\n user_request = request.form\n user_email = user_request.get('email')\n is_registered = AUTH.create_session(user_email)\n\n if not is_registered:\n abort(403)\n\n token = AUTH.get_reset_password_token(user_email)\n message = {\"email\": user_email, \"reset_token\": token}\n return jsonify(message)\n\n\n@app.route('/reset_password', methods=['PUT'], strict_slashes=False)\ndef update_password() -> str:\n \"\"\" PUT /reset_password\n - email\n - reset_token\n - new_password\n Return:\n - Update the password\n - 403 if token is invalid\n \"\"\"\n user_email = request.form.get('email')\n reset_token = request.form.get('reset_token')\n new_password = request.form.get('new_password')\n\n try:\n AUTH.update_password(reset_token, new_password)\n except Exception:\n abort(403)\n\n message = {\"email\": user_email, \"message\": \"Password updated\"}\n return jsonify(message), 200\n\n\nif __name__ == \"__main__\":\n app.run(host=\"0.0.0.0\", port=\"5000\")\n"},{"alpha_fraction":0.587193489074707,"alphanum_fraction":0.5885558724403381,"avg_line_length":31.477876663208008,"blob_id":"ebe998f2067c42d8e86196870ff2d2ad3a6b88ef","content_id":"61e70a8e8c7a5553e423bac8566f5335c208bf76","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":3670,"license_type":"no_license","max_line_length":76,"num_lines":113,"path":"/0x03-user_authentication_service/auth.py","repo_name":"KhaoulaDER/holbertonschool-backend-user-data","src_encoding":"UTF-8","text":"#!/usr/bin/env python3\n\"\"\" Authentication\n\"\"\"\nfrom bcrypt import hashpw, gensalt, checkpw\nfrom db import DB\nfrom user import User\nfrom sqlalchemy.orm.exc import NoResultFound\nfrom sqlalchemy.exc import InvalidRequestError\nfrom uuid import uuid4\nfrom typing import Union\n\n\ndef _hash_password(password: str) -> str:\n \"\"\" Takes in string arg, converts to unicode\n Returns salted, hashed pswd as bytestring\n \"\"\"\n return hashpw(password.encode('utf-8'), gensalt())\n\n\ndef _generate_uuid() -> str:\n \"\"\" Generates UUID\n Returns string representation of new UUID\n \"\"\"\n return str(uuid4())\n\n\nclass Auth:\n \"\"\"Auth class to interact with the authentication database.\n \"\"\"\n\n def __init__(self):\n \"\"\" Instance \"\"\"\n self._db = DB()\n\n def register_user(self, email: str, password: str) -> User:\n \"\"\" Registers and returns a new user if email isn't listed\"\"\"\n try:\n self._db.find_user_by(email=email)\n raise ValueError(f\"User {email} already exists\")\n except NoResultFound:\n hashed_password = _hash_password(password)\n new_user = self._db.add_user(email, hashed_password)\n return new_user\n\n def valid_login(self, email: str, password: str) -> bool:\n \"\"\" Checks if user pswd is valid, locating by email \"\"\"\n try:\n found_user = self._db.find_user_by(email=email)\n return checkpw(\n password.encode('utf-8'),\n found_user.hashed_password\n )\n except NoResultFound:\n return False\n\n def create_session(self, email: str) -> str:\n \"\"\" Creates session ID using UUID, finds user by email \"\"\"\n try:\n found_user = self._db.find_user_by(email=email)\n except NoResultFound:\n return None\n\n session_id = _generate_uuid()\n self._db.update_user(found_user.id, session_id=session_id)\n return session_id\n\n def get_user_from_session_id(self, session_id: str) -> Union[str, None]:\n \"\"\" Finds user by session_id \"\"\"\n if session_id is None:\n return None\n try:\n found_user = self._db.find_user_by(session_id=session_id)\n return found_user\n except NoResultFound:\n return None\n\n def destroy_session(self, user_id: str) -> None:\n \"\"\" Updates user's session_id to None\"\"\"\n if user_id is None:\n return None\n try:\n found_user = self._db.find_user_by(id=user_id)\n self._db.update_user(found_user.id, session_id=None)\n except NoResultFound:\n return None\n\n def get_reset_password_token(self, email: str) -> str:\n \"\"\" Finds user by email, updates user's reset_toke with UUID \"\"\"\n try:\n found_user = self._db.find_user_by(email=email)\n except NoResultFound:\n raise ValueError\n\n reset_token = _generate_uuid()\n self._db.update_user(found_user.id, reset_token=reset_token)\n return reset_token\n\n def update_password(self, reset_token: str, password: str) -> None:\n \"\"\" Use the reset_token to find the corresponding user.\n If it does not exist, raise a ValueError exception.\n \"\"\"\n if reset_token is None or password is None:\n return None\n\n try:\n user = self._db.find_user_by(reset_token=reset_token)\n except NoResultFound:\n raise ValueError\n\n hashed_password = _hash_password(password)\n self._db.update_user(user.id,\n hashed_password=hashed_password,\n reset_token=None)\n"}],"string":"[\n {\n \"alpha_fraction\": 0.6667270660400391,\n \"alphanum_fraction\": 0.7013505101203918,\n \"avg_line_length\": 26.824716567993164,\n \"blob_id\": \"97a39f794ee5abda6f4486227ecc75fda64cda3f\",\n \"content_id\": \"8d50e6f37febf9b96b19a8e9ff2aee6cc3b88a00\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 22084,\n \"license_type\": \"no_license\",\n \"max_line_length\": 363,\n \"num_lines\": 793,\n \"path\": \"/0x03-user_authentication_service/README.md\",\n \"repo_name\": \"KhaoulaDER/holbertonschool-backend-user-data\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# 0x03. User authentication service\\n\\n\\n\\nIn the industry, you should **not** implement your own authentication system and use a module or framework that doing it for you (like in Python-Flask: [Flask-User](https://intranet.hbtn.io/rltoken/r1XmxzZ-clc7laax6Tm7WQ \\\"Flask-User\\\")). Here, for the learning purpose, we will walk through each step of this mechanism to understand it by doing.\\n\\n## Resources\\n\\n**Read or watch:**\\n\\n- [Flask documentation](https://intranet.hbtn.io/rltoken/LSFQS3aarknJpMZVr9Je1Q \\\"Flask documentation\\\")\\n- [Requests module](https://intranet.hbtn.io/rltoken/PqxwI-hQOe4b4Hhah4fbVg \\\"Requests module\\\")\\n- [HTTP status codes](https://intranet.hbtn.io/rltoken/QoqUvOM9taMBOVaeB_g06g \\\"HTTP status codes\\\")\\n\\n## Learning Objectives\\n\\nAt the end of this project, you are expected to be able to [explain to anyone](https://intranet.hbtn.io/rltoken/IAeORv21eo25XYJByjx_bg \\\"explain to anyone\\\"), **without the help of Google**:\\n\\n- How to declare API routes in a Flask app\\n- How to get and set cookies\\n- How to retrieve request form data\\n- How to return various HTTP status codes\\n\\n\\n## Setup\\n\\nYou will need to install `bcrypt`\\n\\n```\\npip3 install bcrypt\\n\\n```\\n\\n## Tasks\\n\\n### 0. User model\\n\\n\\nIn this task you will create a SQLAlchemy model named `User` for a database table named `users` (by using the [mapping declaration](https://intranet.hbtn.io/rltoken/IF5xw2va364LrJEntCXLlg \\\"mapping declaration\\\") of SQLAlchemy).\\n\\nThe model will have the following attributes:\\n\\n- `id`, the integer primary key\\n- `email`, a non-nullable string\\n- `hashed_password`, a non-nullable string\\n- `session_id`, a nullable string\\n- `reset_token`, a nullable string\\n\\n```\\nbob@dylan:~$ cat main.py\\n#!/usr/bin/env python3\\n\\\"\\\"\\\"\\nMain file\\n\\\"\\\"\\\"\\nfrom user import User\\n\\nprint(User.__tablename__)\\n\\nfor column in User.__table__.columns:\\n print(\\\"{}: {}\\\".format(column, column.type))\\n\\nbob@dylan:~$ python3 main.py\\nusers\\nusers.id: INTEGER\\nusers.email: VARCHAR(250)\\nusers.hashed_password: VARCHAR(250)\\nusers.session_id: VARCHAR(250)\\nusers.reset_token: VARCHAR(250)\\nbob@dylan:~$ \\n\\n```\\n\\n\\n### 1. create user\\n\\n\\nIn this task, you will complete the `DB` class provided below to implement the `add_user` method.\\n\\n```\\n\\\"\\\"\\\"DB module\\n\\\"\\\"\\\"\\nfrom sqlalchemy import create_engine\\nfrom sqlalchemy.ext.declarative import declarative_base\\nfrom sqlalchemy.orm import sessionmaker\\nfrom sqlalchemy.orm.session import Session\\n\\nfrom user import Base\\n\\n\\nclass DB:\\n \\\"\\\"\\\"DB class\\n \\\"\\\"\\\"\\n\\n def __init__(self) -> None:\\n \\\"\\\"\\\"Initialize a new DB instance\\n \\\"\\\"\\\"\\n self._engine = create_engine(\\\"sqlite:///a.db\\\", echo=True)\\n Base.metadata.drop_all(self._engine)\\n Base.metadata.create_all(self._engine)\\n self.__session = None\\n\\n @property\\n def _session(self) -> Session:\\n \\\"\\\"\\\"Memoized session object\\n \\\"\\\"\\\"\\n if self.__session is None:\\n DBSession = sessionmaker(bind=self._engine)\\n self.__session = DBSession()\\n return self.__session\\n\\n```\\n\\nNote that `DB._session` is a private property and hence should NEVER be used from outside the `DB` class.\\n\\nImplement the `add_user` method, which has two required string arguments: `email` and `hashed_password`, and returns a `User` object. The method should save the user to the database. No validations are required at this stage.\\n\\n```\\nbob@dylan:~$ cat main.py\\n#!/usr/bin/env python3\\n\\\"\\\"\\\"\\nMain file\\n\\\"\\\"\\\"\\n\\nfrom db import DB\\nfrom user import User\\n\\nmy_db = DB()\\n\\nuser_1 = my_db.add_user(\\\"test@test.com\\\", \\\"SuperHashedPwd\\\")\\nprint(user_1.id)\\n\\nuser_2 = my_db.add_user(\\\"test1@test.com\\\", \\\"SuperHashedPwd1\\\")\\nprint(user_2.id)\\n\\nbob@dylan:~$ python3 main.py\\n1\\n2\\nbob@dylan:~$\\n\\n```\\n\\n\\n### 2. Find user\\n\\n\\nIn this task you will implement the `DB.find_user_by` method. This method takes in arbitrary keyword arguments and returns the first row found in the `users` table as filtered by the method’s input arguments. No validation of input arguments required at this point.\\n\\nMake sure that SQLAlchemy’s `NoResultFound` and `InvalidRequestError` are raised when no results are found, or when wrong query arguments are passed, respectively.\\n\\n**Warning:**\\n\\n- `NoResultFound` has been moved from `sqlalchemy.orm.exc` to `sqlalchemy.exc` between the version 1.3.x and 1.4.x of SQLAchemy - please make sure you are importing it from `sqlalchemy.orm.exc`\\n\\n```\\nbob@dylan:~$ cat main.py\\n#!/usr/bin/env python3\\n\\\"\\\"\\\"\\nMain file\\n\\\"\\\"\\\"\\nfrom db import DB\\nfrom user import User\\n\\nfrom sqlalchemy.exc import InvalidRequestError\\nfrom sqlalchemy.orm.exc import NoResultFound\\n\\n\\nmy_db = DB()\\n\\nuser = my_db.add_user(\\\"test@test.com\\\", \\\"PwdHashed\\\")\\nprint(user.id)\\n\\nfind_user = my_db.find_user_by(email=\\\"test@test.com\\\")\\nprint(find_user.id)\\n\\ntry:\\n find_user = my_db.find_user_by(email=\\\"test2@test.com\\\")\\n print(find_user.id)\\nexcept NoResultFound:\\n print(\\\"Not found\\\")\\n\\ntry:\\n find_user = my_db.find_user_by(no_email=\\\"test@test.com\\\")\\n print(find_user.id)\\nexcept InvalidRequestError:\\n print(\\\"Invalid\\\") \\n\\nbob@dylan:~$ python3 main.py\\n1\\n1\\nNot found\\nInvalid\\nbob@dylan:~$ \\n\\n```\\n\\n\\n### 3. update user\\n\\n\\nIn this task, you will implement the `DB.update_user` method that takes as argument a required `user_id` integer and arbitrary keyword arguments, and returns `None`.\\n\\nThe method will use `find_user_by` to locate the user to update, then will update the user’s attributes as passed in the method’s arguments then commit changes to the database.\\n\\nIf an argument that does not correspond to a user attribute is passed, raise a `ValueError`.\\n\\n```\\nbob@dylan:~$ cat main.py\\n#!/usr/bin/env python3\\n\\\"\\\"\\\"\\nMain file\\n\\\"\\\"\\\"\\nfrom db import DB\\nfrom user import User\\n\\nfrom sqlalchemy.exc import InvalidRequestError\\nfrom sqlalchemy.orm.exc import NoResultFound\\n\\n\\nmy_db = DB()\\n\\nemail = 'test@test.com'\\nhashed_password = \\\"hashedPwd\\\"\\n\\nuser = my_db.add_user(email, hashed_password)\\nprint(user.id)\\n\\ntry:\\n my_db.update_user(user.id, hashed_password='NewPwd')\\n print(\\\"Password updated\\\")\\nexcept ValueError:\\n print(\\\"Error\\\")\\n\\nbob@dylan:~$ python3 main.py\\n1\\nPassword updated\\nbob@dylan:~$ \\n\\n```\\n\\n\\n### 4. Hash password\\n\\n\\nIn this task you will define a `_hash_password` method that takes in a `password` string arguments and returns bytes.\\n\\nThe returned bytes is a salted hash of the input password, hashed with `bcrypt.hashpw`.\\n\\n```\\nbob@dylan:~$ cat main.py\\n#!/usr/bin/env python3\\n\\\"\\\"\\\"\\nMain file\\n\\\"\\\"\\\"\\nfrom auth import _hash_password\\n\\nprint(_hash_password(\\\"Hello Holberton\\\"))\\n\\nbob@dylan:~$ python3 main.py\\nb'$2b$12$eUDdeuBtrD41c8dXvzh95ehsWYCCAi4VH1JbESzgbgZT.eMMzi.G2'\\nbob@dylan:~$\\n\\n```\\n\\n\\n### 5. Register user\\n\\n\\nIn this task, you will implement the `Auth.register_user` in the `Auth` class provided below:\\n\\n```\\nfrom db import DB\\n\\n\\nclass Auth:\\n \\\"\\\"\\\"Auth class to interact with the authentication database.\\n \\\"\\\"\\\"\\n\\n def __init__(self):\\n self._db = DB()\\n\\n```\\n\\nNote that `Auth._db` is a private property and should NEVER be used from outside the class.\\n\\n`Auth.register_user` should take mandatory `email` and `password` string arguments and return a `User` object.\\n\\nIf a user already exist with the passed email, raise a `ValueError` with the message `User already exists`.\\n\\nIf not, hash the password with `_hash_password`, save the user to the database using `self._db` and return the `User` object.\\n\\n```\\nbob@dylan:~$ cat main.py\\n#!/usr/bin/env python3\\n\\\"\\\"\\\"\\nMain file\\n\\\"\\\"\\\"\\nfrom auth import Auth\\n\\nemail = 'me@me.com'\\npassword = 'mySecuredPwd'\\n\\nauth = Auth()\\n\\ntry:\\n user = auth.register_user(email, password)\\n print(\\\"successfully created a new user!\\\")\\nexcept ValueError as err:\\n print(\\\"could not create a new user: {}\\\".format(err))\\n\\ntry:\\n user = auth.register_user(email, password)\\n print(\\\"successfully created a new user!\\\")\\nexcept ValueError as err:\\n print(\\\"could not create a new user: {}\\\".format(err)) \\n\\nbob@dylan:~$ python3 main.py\\nsuccessfully created a new user!\\ncould not create a new user: User me@me.com already exists\\nbob@dylan:~$\\n\\n```\\n\\n\\n### 6. Basic Flask app\\n\\n\\nIn this task, you will set up a basic Flask app.\\n\\nCreate a Flask app that has a single `GET` route (`\\\"/\\\"`) and use `flask.jsonify` to return a JSON payload of the form:\\n\\n```\\n{\\\"message\\\": \\\"Bienvenue\\\"}\\n\\n```\\n\\nAdd the following code at the end of the module:\\n\\n```\\nif __name__ == \\\"__main__\\\":\\n app.run(host=\\\"0.0.0.0\\\", port=\\\"5000\\\")\\n\\n```\\n\\n\\n### 7. Register user\\n\\n\\nIn this task, you will implement the end-point to register a user. Define a `users` function that implements the `POST /users` route.\\n\\nImport the `Auth` object and instantiate it at the root of the module as such:\\n\\n```\\nfrom auth import Auth\\n\\n\\nAUTH = Auth()\\n\\n```\\n\\nThe end-point should expect two form data fields: `\\\"email\\\"` and `\\\"password\\\"`. If the user does not exist, the end-point should register it and respond with the following JSON payload:\\n\\n```\\n{\\\"email\\\": \\\"\\\", \\\"message\\\": \\\"user created\\\"}\\n\\n```\\n\\nIf the user is already registered, catch the exception and return a JSON payload of the form\\n\\n```\\n{\\\"message\\\": \\\"email already registered\\\"}\\n\\n```\\n\\nand return a 400 status code\\n\\nRemember that you should only use `AUTH` in this app. `DB` is a lower abstraction that is proxied by `Auth`.\\n\\n_Terminal 1:_\\n\\n```\\nbob@dylan:~$ python3 app.py \\n* Serving Flask app \\\"app\\\" (lazy loading)\\n * Environment: production\\n WARNING: This is a development server. Do not use it in a production deployment.\\n Use a production WSGI server instead.\\n * Debug mode: off\\n * Running on http://0.0.0.0:5000/ (Press CTRL+C to quit)\\n\\n\\n```\\n\\nTerminal 2:\\n\\n```\\nbob@dylan:~$ curl -XPOST localhost:5000/users -d 'email=bob@me.com' -d 'password=mySuperPwd' -v\\nNote: Unnecessary use of -X or --request, POST is already inferred.\\n* Trying 127.0.0.1...\\n* TCP_NODELAY set\\n* Connected to localhost (127.0.0.1) port 5000 (#0)\\n> POST /users HTTP/1.1\\n> Host: localhost:5000\\n> User-Agent: curl/7.58.0\\n> Accept: */*\\n> Content-Length: 40\\n> Content-Type: application/x-www-form-urlencoded\\n> \\n* upload completely sent off: 40 out of 40 bytes\\n* HTTP 1.0, assume close after body\\n< HTTP/1.0 200 OK\\n< Content-Type: application/json\\n< Content-Length: 52\\n< Server: Werkzeug/1.0.1 Python/3.7.3\\n< Date: Wed, 19 Aug 2020 00:03:18 GMT\\n< \\n{\\\"email\\\":\\\"bob@me.com\\\",\\\"message\\\":\\\"user created\\\"}\\n\\nbob@dylan:~$\\nbob@dylan:~$ curl -XPOST localhost:5000/users -d 'email=bob@me.com' -d 'password=mySuperPwd' -v\\nNote: Unnecessary use of -X or --request, POST is already inferred.\\n* Trying 127.0.0.1...\\n* TCP_NODELAY set\\n* Connected to localhost (127.0.0.1) port 5000 (#0)\\n> POST /users HTTP/1.1\\n> Host: localhost:5000\\n> User-Agent: curl/7.58.0\\n> Accept: */*\\n> Content-Length: 40\\n> Content-Type: application/x-www-form-urlencoded\\n> \\n* upload completely sent off: 40 out of 40 bytes\\n* HTTP 1.0, assume close after body\\n< HTTP/1.0 400 BAD REQUEST\\n< Content-Type: application/json\\n< Content-Length: 39\\n< Server: Werkzeug/1.0.1 Python/3.7.3\\n< Date: Wed, 19 Aug 2020 00:03:33 GMT\\n< \\n{\\\"message\\\":\\\"email already registered\\\"}\\nbob@dylan:~$\\n\\n```\\n\\n\\n### 8. Credentials validation\\n\\n\\nIn this task, you will implement the `Auth.valid_login` method. It should expect `email` and `password` required arguments and return a boolean.\\n\\nTry locating the user by email. If it exists, check the password with `bcrypt.checkpw`. If it matches return `True`. In any other case, return `False`.\\n\\n```\\nbob@dylan:~$ cat main.py\\n#!/usr/bin/env python3\\n\\\"\\\"\\\"\\nMain file\\n\\\"\\\"\\\"\\nfrom auth import Auth\\n\\nemail = 'bob@bob.com'\\npassword = 'MyPwdOfBob'\\nauth = Auth()\\n\\nauth.register_user(email, password)\\n\\nprint(auth.valid_login(email, password))\\n\\nprint(auth.valid_login(email, \\\"WrongPwd\\\"))\\n\\nprint(auth.valid_login(\\\"unknown@email\\\", password))\\n\\nbob@dylan:~$ python3 main.py\\nTrue\\nFalse\\nFalse\\nbob@dylan:~$ \\n\\n```\\n\\n\\n### 9. Generate UUIDs\\n\\n\\nIn this task you will implement a `_generate_uuid` function in the `auth` module. The function should return a string representation of a new UUID. Use the `uuid` module.\\n\\nNote that the method is private to the `auth` module and should **NOT** be used outside of it.\\n\\n\\n### 10. Get session ID\\n\\n\\nIn this task, you will implement the `Auth.create_session` method. It takes an `email` string argument and returns the session ID as a string.\\n\\nThe method should find the user corresponding to the email, generate a new UUID and store it in the database as the user’s `session_id`, then return the session ID.\\n\\nRemember that only public methods of `self._db` can be used.\\n\\n```\\nbob@dylan:~$ cat main.py\\n#!/usr/bin/env python3\\n\\\"\\\"\\\"\\nMain file\\n\\\"\\\"\\\"\\nfrom auth import Auth\\n\\nemail = 'bob@bob.com'\\npassword = 'MyPwdOfBob'\\nauth = Auth()\\n\\nauth.register_user(email, password)\\n\\nprint(auth.create_session(email))\\nprint(auth.create_session(\\\"unknown@email.com\\\"))\\n\\nbob@dylan:~$ python3 main.py\\n5a006849-343e-4a48-ba4e-bbd523fcca58\\nNone\\nbob@dylan:~$ \\n\\n```\\n\\n\\n### 11. Log in\\n\\n\\nIn this task, you will implement a `login` function to respond to the `POST /sessions` route.\\n\\nThe request is expected to contain form data with `\\\"email\\\"` and a `\\\"password\\\"` fields.\\n\\nIf the login information is incorrect, use `flask.abort` to respond with a 401 HTTP status.\\n\\nOtherwise, create a new session for the user, store it the session ID as a cookie with key `\\\"session_id\\\"` on the response and return a JSON payload of the form\\n\\n```\\n{\\\"email\\\": \\\"\\\", \\\"message\\\": \\\"logged in\\\"}\\n\\n```\\n\\n```\\nbob@dylan:~$ curl -XPOST localhost:5000/users -d 'email=bob@bob.com' -d 'password=mySuperPwd'\\n{\\\"email\\\":\\\"bob@bob.com\\\",\\\"message\\\":\\\"user created\\\"}\\nbob@dylan:~$ \\nbob@dylan:~$ curl -XPOST localhost:5000/sessions -d 'email=bob@bob.com' -d 'password=mySuperPwd' -v\\nNote: Unnecessary use of -X or --request, POST is already inferred.\\n* Trying 127.0.0.1...\\n* TCP_NODELAY set\\n* Connected to localhost (127.0.0.1) port 5000 (#0)\\n> POST /sessions HTTP/1.1\\n> Host: localhost:5000\\n> User-Agent: curl/7.58.0\\n> Accept: */*\\n> Content-Length: 37\\n> Content-Type: application/x-www-form-urlencoded\\n> \\n* upload completely sent off: 37 out of 37 bytes\\n* HTTP 1.0, assume close after body\\n< HTTP/1.0 200 OK\\n< Content-Type: application/json\\n< Content-Length: 46\\n< Set-Cookie: session_id=163fe508-19a2-48ed-a7c8-d9c6e56fabd1; Path=/\\n< Server: Werkzeug/1.0.1 Python/3.7.3\\n< Date: Wed, 19 Aug 2020 00:12:34 GMT\\n< \\n{\\\"email\\\":\\\"bob@bob.com\\\",\\\"message\\\":\\\"logged in\\\"}\\n* Closing connection 0\\nbob@dylan:~$ \\nbob@dylan:~$ curl -XPOST localhost:5000/sessions -d 'email=bob@bob.com' -d 'password=BlaBla' -v\\nNote: Unnecessary use of -X or --request, POST is already inferred.\\n* Trying 127.0.0.1...\\n* TCP_NODELAY set\\n* Connected to localhost (127.0.0.1) port 5000 (#0)\\n> POST /sessions HTTP/1.1\\n> Host: localhost:5000\\n> User-Agent: curl/7.58.0\\n> Accept: */*\\n> Content-Length: 34\\n> Content-Type: application/x-www-form-urlencoded\\n> \\n* upload completely sent off: 34 out of 34 bytes\\n* HTTP 1.0, assume close after body\\n< HTTP/1.0 401 UNAUTHORIZED\\n< Content-Type: text/html; charset=utf-8\\n< Content-Length: 338\\n< Server: Werkzeug/1.0.1 Python/3.7.3\\n< Date: Wed, 19 Aug 2020 00:12:45 GMT\\n< \\n\\n401 Unauthorized \\n\\\"}\\n\\n```\\n\\nIf the session ID is invalid or the user does not exist, respond with a 403 HTTP status.\\n\\n```\\nbob@dylan:~$ curl -XPOST localhost:5000/sessions -d 'email=bob@bob.com' -d 'password=mySuperPwd' -v\\nNote: Unnecessary use of -X or --request, POST is already inferred.\\n* Trying 127.0.0.1...\\n* TCP_NODELAY set\\n* Connected to localhost (127.0.0.1) port 5000 (#0)\\n> POST /sessions HTTP/1.1\\n> Host: localhost:5000\\n> User-Agent: curl/7.58.0\\n> Accept: */*\\n> Content-Length: 37\\n> Content-Type: application/x-www-form-urlencoded\\n> \\n* upload completely sent off: 37 out of 37 bytes\\n* HTTP 1.0, assume close after body\\n< HTTP/1.0 200 OK\\n< Content-Type: application/json\\n< Content-Length: 46\\n< Set-Cookie: session_id=75c89af8-1729-44d9-a592-41b5e59de9a1; Path=/\\n< Server: Werkzeug/1.0.1 Python/3.7.3\\n< Date: Wed, 19 Aug 2020 00:15:57 GMT\\n< \\n{\\\"email\\\":\\\"bob@bob.com\\\",\\\"message\\\":\\\"logged in\\\"}\\n* Closing connection 0\\nbob@dylan:~$\\nbob@dylan:~$ curl -XGET localhost:5000/profile -b \\\"session_id=75c89af8-1729-44d9-a592-41b5e59de9a1\\\"\\n{\\\"email\\\": \\\"bob@bob.com\\\"}\\nbob@dylan:~$ \\nbob@dylan:~$ curl -XGET localhost:5000/profile -b \\\"session_id=nope\\\" -v\\nNote: Unnecessary use of -X or --request, GET is already inferred.\\n* Trying 127.0.0.1...\\n* TCP_NODELAY set\\n* Connected to localhost (127.0.0.1) port 5000 (#0)\\n> GET /profile HTTP/1.1\\n> Host: localhost:5000\\n> User-Agent: curl/7.58.0\\n> Accept: */*\\n> Cookie: session_id=75c89af8-1729-44d9-a592-41b5e59de9a\\n> \\n* HTTP 1.0, assume close after body\\n< HTTP/1.0 403 FORBIDDEN\\n< Content-Type: text/html; charset=utf-8\\n< Content-Length: 234\\n< Server: Werkzeug/1.0.1 Python/3.7.3\\n< Date: Wed, 19 Aug 2020 00:16:43 GMT\\n< \\n\\n403 Forbidden \\n\\\", \\\"reset_token\\\": \\\"\\\"}\\n\\n```\\n\\n\\n### 18. Update password\\n\\n\\nIn this task, you will implement the `Auth.update_password` method. It takes `reset_token` string argument and a `password` string argument and returns `None`.\\n\\nUse the `reset_token` to find the corresponding user. If it does not exist, raise a `ValueError` exception.\\n\\nOtherwise, hash the password and update the user’s `hashed_password` field with the new hashed password and the `reset_token` field to `None`.\\n\\n\\n\\n### 19. Update password end-point\\n\\n\\nIn this task you will implement the `update_password` function in the `app` module to respond to the `PUT /reset_password` route.\\n\\nThe request is expected to contain form data with fields `\\\"email\\\"`, `\\\"reset_token\\\"` and `\\\"new_password\\\"`.\\n\\nUpdate the password. If the token is invalid, catch the exception and respond with a 403 HTTP code.\\n\\nIf the token is valid, respond with a 200 HTTP code and the following JSON payload:\\n\\n```\\n{\\\"email\\\": \\\"\\\", \\\"message\\\": \\\"Password updated\\\"}\\n\\n```\\n\\n\\n### 20. End-to-end integration test\\n\\n\\nStart your app. Open a new terminal window.\\n\\nCreate a new module called `main.py`. Create one function for each of the following tasks. Use the `requests` module to query your web server for the corresponding end-point. Use `assert` to validate the response’s expected status code and payload (if any) for each task.\\n\\n- `register_user(email: str, password: str) -> None`\\n- `log_in_wrong_password(email: str, password: str) -> None`\\n- `log_in(email: str, password: str) -> str`\\n- `profile_unlogged() -> None`\\n- `profile_logged(session_id: str) -> None`\\n- `log_out(session_id: str) -> None`\\n- `reset_password_token(email: str) -> str`\\n- `update_password(email: str, reset_token: str, new_password: str) -> None`\\n\\nThen copy the following code at the end of the `main` module:\\n\\n```\\nEMAIL = \\\"guillaume@holberton.io\\\"\\nPASSWD = \\\"b4l0u\\\"\\nNEW_PASSWD = \\\"t4rt1fl3tt3\\\"\\n\\n\\nif __name__ == \\\"__main__\\\":\\n\\n register_user(EMAIL, PASSWD)\\n log_in_wrong_password(EMAIL, NEW_PASSWD)\\n profile_unlogged()\\n session_id = log_in(EMAIL, PASSWD)\\n profile_logged(session_id)\\n log_out(session_id)\\n reset_token = reset_password_token(EMAIL)\\n update_password(EMAIL, reset_token, NEW_PASSWD)\\n log_in(EMAIL, NEW_PASSWD)\\n\\n```\\n\\nRun `python main.py`. If everything is correct, you should see no output.\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.600247859954834,\n \"alphanum_fraction\": 0.6114002466201782,\n \"avg_line_length\": 27.02083396911621,\n \"blob_id\": \"bf0c5a76f1df5584883b2672ebff364e9ca32a9f\",\n \"content_id\": \"3830d34065b48f8eb54d8e2fca1aa5bbd77c266d\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 4035,\n \"license_type\": \"no_license\",\n \"max_line_length\": 71,\n \"num_lines\": 144,\n \"path\": \"/0x03-user_authentication_service/app.py\",\n \"repo_name\": \"KhaoulaDER/holbertonschool-backend-user-data\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#!/usr/bin/env python3\\n\\\"\\\"\\\" Route module for the API \\\"\\\"\\\"\\n\\nfrom flask import Flask, jsonify, request, abort, redirect, url_for\\nfrom sqlalchemy.orm.exc import NoResultFound\\nfrom auth import Auth\\n\\n\\napp = Flask(__name__)\\nAUTH = Auth()\\n\\n\\n@app.route('/', methods=['GET'], strict_slashes=False)\\ndef status() -> str:\\n \\\"\\\"\\\" GET /status\\n Return:\\n - JSON payload\\n \\\"\\\"\\\"\\n return jsonify({\\\"message\\\": \\\"Bienvenue\\\"})\\n\\n\\n@app.route('/users', methods=['POST'], strict_slashes=False)\\ndef new_user() -> str:\\n \\\"\\\"\\\" POST /users\\n Registers new user with email and pswd in request form-data,\\n or finds if user already registered based on email\\n Return:\\n - JSON payload\\n \\\"\\\"\\\"\\n\\n # Get data from form request, change to request.get_json() for body\\n email = request.form.get(\\\"email\\\")\\n password = request.form.get(\\\"password\\\")\\n\\n try:\\n new_user = AUTH.register_user(email, password)\\n if new_user is not None:\\n return jsonify({\\n \\\"email\\\": new_user.email,\\n \\\"message\\\": \\\"user created\\\"\\n })\\n except ValueRrror:\\n return jsonify({\\n \\\"message\\\": \\\"email already registered\\\"\\n }), 400\\n\\n\\n@app.route('/sessions', methods=['POST'], strict_slashes=False)\\ndef login() -> str:\\n \\\"\\\"\\\" POST /sessions\\n Creates new session for user, stores as cookie\\n Email and pswd fields in x-www-form-urlencoded request\\n Return:\\n - JSON payload\\n \\\"\\\"\\\"\\n email = request.form.get(\\\"email\\\")\\n password = request.form.get(\\\"password\\\")\\n valid_user = AUTH.valid_login(email, password)\\n\\n if not valid_user:\\n abort(401)\\n session_id = AUTH.create_session(email)\\n message = {\\\"email\\\": email, \\\"message\\\": \\\"logged in\\\"}\\n response = jsonify(message)\\n response.set_cookie(\\\"session_id\\\", session_id)\\n return response\\n\\n\\n@app.route('/sessions', methods=['DELETE'], strict_slashes=False)\\ndef logout():\\n \\\"\\\"\\\" DELETE /sessions\\n Destroys session by finding session_id (key in cookie)\\n Return:\\n - Redirects user to status route (GET /)\\n \\\"\\\"\\\"\\n user_cookie = request.cookies.get(\\\"session_id\\\", None)\\n user = AUTH.get_user_from_session_id(user_cookie)\\n if user_cookie is None or user is None:\\n abort(403)\\n AUTH.destroy_session(user.id)\\n return redirect('/')\\n\\n\\n@app.route('/profile', methods=['GET'], strict_slashes=False)\\ndef profile() -> str:\\n \\\"\\\"\\\" GET /profile\\n Return:\\n - Use session_id to find the user.\\n - 403 if session ID is invalid\\n \\\"\\\"\\\"\\n user_cookie = request.cookies.get(\\\"session_id\\\", None)\\n if user_cookie is None:\\n abort(403)\\n user = AUTH.get_user_from_session_id(user_cookie)\\n if user is None:\\n abort(403)\\n return jsonify({\\\"email\\\": user.email}), 200\\n\\n\\n@app.route('/reset_password', methods=['POST'], strict_slashes=False)\\ndef get_reset_password_token() -> str:\\n \\\"\\\"\\\" POST /reset_password\\n - email\\n Return:\\n - Generate a Token\\n - 403 if email not registered\\n \\\"\\\"\\\"\\n user_request = request.form\\n user_email = user_request.get('email')\\n is_registered = AUTH.create_session(user_email)\\n\\n if not is_registered:\\n abort(403)\\n\\n token = AUTH.get_reset_password_token(user_email)\\n message = {\\\"email\\\": user_email, \\\"reset_token\\\": token}\\n return jsonify(message)\\n\\n\\n@app.route('/reset_password', methods=['PUT'], strict_slashes=False)\\ndef update_password() -> str:\\n \\\"\\\"\\\" PUT /reset_password\\n - email\\n - reset_token\\n - new_password\\n Return:\\n - Update the password\\n - 403 if token is invalid\\n \\\"\\\"\\\"\\n user_email = request.form.get('email')\\n reset_token = request.form.get('reset_token')\\n new_password = request.form.get('new_password')\\n\\n try:\\n AUTH.update_password(reset_token, new_password)\\n except Exception:\\n abort(403)\\n\\n message = {\\\"email\\\": user_email, \\\"message\\\": \\\"Password updated\\\"}\\n return jsonify(message), 200\\n\\n\\nif __name__ == \\\"__main__\\\":\\n app.run(host=\\\"0.0.0.0\\\", port=\\\"5000\\\")\\n\"\n },\n {\n \"alpha_fraction\": 0.587193489074707,\n \"alphanum_fraction\": 0.5885558724403381,\n \"avg_line_length\": 31.477876663208008,\n \"blob_id\": \"ebe998f2067c42d8e86196870ff2d2ad3a6b88ef\",\n \"content_id\": \"61e70a8e8c7a5553e423bac8566f5335c208bf76\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 3670,\n \"license_type\": \"no_license\",\n \"max_line_length\": 76,\n \"num_lines\": 113,\n \"path\": \"/0x03-user_authentication_service/auth.py\",\n \"repo_name\": \"KhaoulaDER/holbertonschool-backend-user-data\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#!/usr/bin/env python3\\n\\\"\\\"\\\" Authentication\\n\\\"\\\"\\\"\\nfrom bcrypt import hashpw, gensalt, checkpw\\nfrom db import DB\\nfrom user import User\\nfrom sqlalchemy.orm.exc import NoResultFound\\nfrom sqlalchemy.exc import InvalidRequestError\\nfrom uuid import uuid4\\nfrom typing import Union\\n\\n\\ndef _hash_password(password: str) -> str:\\n \\\"\\\"\\\" Takes in string arg, converts to unicode\\n Returns salted, hashed pswd as bytestring\\n \\\"\\\"\\\"\\n return hashpw(password.encode('utf-8'), gensalt())\\n\\n\\ndef _generate_uuid() -> str:\\n \\\"\\\"\\\" Generates UUID\\n Returns string representation of new UUID\\n \\\"\\\"\\\"\\n return str(uuid4())\\n\\n\\nclass Auth:\\n \\\"\\\"\\\"Auth class to interact with the authentication database.\\n \\\"\\\"\\\"\\n\\n def __init__(self):\\n \\\"\\\"\\\" Instance \\\"\\\"\\\"\\n self._db = DB()\\n\\n def register_user(self, email: str, password: str) -> User:\\n \\\"\\\"\\\" Registers and returns a new user if email isn't listed\\\"\\\"\\\"\\n try:\\n self._db.find_user_by(email=email)\\n raise ValueError(f\\\"User {email} already exists\\\")\\n except NoResultFound:\\n hashed_password = _hash_password(password)\\n new_user = self._db.add_user(email, hashed_password)\\n return new_user\\n\\n def valid_login(self, email: str, password: str) -> bool:\\n \\\"\\\"\\\" Checks if user pswd is valid, locating by email \\\"\\\"\\\"\\n try:\\n found_user = self._db.find_user_by(email=email)\\n return checkpw(\\n password.encode('utf-8'),\\n found_user.hashed_password\\n )\\n except NoResultFound:\\n return False\\n\\n def create_session(self, email: str) -> str:\\n \\\"\\\"\\\" Creates session ID using UUID, finds user by email \\\"\\\"\\\"\\n try:\\n found_user = self._db.find_user_by(email=email)\\n except NoResultFound:\\n return None\\n\\n session_id = _generate_uuid()\\n self._db.update_user(found_user.id, session_id=session_id)\\n return session_id\\n\\n def get_user_from_session_id(self, session_id: str) -> Union[str, None]:\\n \\\"\\\"\\\" Finds user by session_id \\\"\\\"\\\"\\n if session_id is None:\\n return None\\n try:\\n found_user = self._db.find_user_by(session_id=session_id)\\n return found_user\\n except NoResultFound:\\n return None\\n\\n def destroy_session(self, user_id: str) -> None:\\n \\\"\\\"\\\" Updates user's session_id to None\\\"\\\"\\\"\\n if user_id is None:\\n return None\\n try:\\n found_user = self._db.find_user_by(id=user_id)\\n self._db.update_user(found_user.id, session_id=None)\\n except NoResultFound:\\n return None\\n\\n def get_reset_password_token(self, email: str) -> str:\\n \\\"\\\"\\\" Finds user by email, updates user's reset_toke with UUID \\\"\\\"\\\"\\n try:\\n found_user = self._db.find_user_by(email=email)\\n except NoResultFound:\\n raise ValueError\\n\\n reset_token = _generate_uuid()\\n self._db.update_user(found_user.id, reset_token=reset_token)\\n return reset_token\\n\\n def update_password(self, reset_token: str, password: str) -> None:\\n \\\"\\\"\\\" Use the reset_token to find the corresponding user.\\n If it does not exist, raise a ValueError exception.\\n \\\"\\\"\\\"\\n if reset_token is None or password is None:\\n return None\\n\\n try:\\n user = self._db.find_user_by(reset_token=reset_token)\\n except NoResultFound:\\n raise ValueError\\n\\n hashed_password = _hash_password(password)\\n self._db.update_user(user.id,\\n hashed_password=hashed_password,\\n reset_token=None)\\n\"\n }\n]"},"num_files":{"kind":"number","value":3,"string":"3"}}},{"rowIdx":2066,"cells":{"repo_name":{"kind":"string","value":"dsande30/COSC483_PA3"},"repo_url":{"kind":"string","value":"https://github.com/dsande30/COSC483_PA3"},"snapshot_id":{"kind":"string","value":"549b9d1213db5a4bba35a83b67cf032b19d1fda4"},"revision_id":{"kind":"string","value":"515d4d3dc9e1e96286a032b6c55ca9f7e4721afc"},"directory_id":{"kind":"string","value":"0b2030425df45f2b65cc9e6f063a2ecd19de1814"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"string","value":"2021-08-24T10:02:19.218198"},"revision_date":{"kind":"string","value":"2017-12-09T04:58:23"},"committer_date":{"kind":"string","value":"2017-12-09T04:58:23"},"github_id":{"kind":"number","value":113354184,"string":"113,354,184"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"string","value":"2017-12-06T18:43:15"},"gha_updated_at":{"kind":"string","value":"2017-12-06T19:47:18"},"gha_pushed_at":{"kind":"string","value":"2017-12-09T04:59:14"},"gha_language":{"kind":"string","value":"Python"},"files":{"kind":"list like","value":[{"alpha_fraction":0.6085432171821594,"alphanum_fraction":0.613006055355072,"avg_line_length":32.37234115600586,"blob_id":"7c806e1d694f8713bd699e58a8f140a3b9739d73","content_id":"b50338a8fcd79074a6a7ba5a98065aa1c79f4355","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":3137,"license_type":"no_license","max_line_length":121,"num_lines":94,"path":"/unlock.py","repo_name":"dsande30/COSC483_PA3","src_encoding":"UTF-8","text":"import argparse\nimport subprocess\nimport os\nimport sys\nfrom Crypto.Random import random\n\ndef getFlags():\n #parse command line args\n parser = argparse.ArgumentParser()\n parser.add_argument(\"-d\", dest = 'directory', help=\"Enter directory to lock\", required = True)\n parser.add_argument(\"-p\", dest = 'pubKeyFile', help=\"Enter action public key file\", required = True)\n parser.add_argument(\"-r\", dest = 'privKeyFile', help= \"Enter action private key file\", required=True)\n parser.add_argument(\"-vk\", dest = 'valFile', help= \"Enter validate pubkey file\", required=True)\n args = parser.parse_args()\n return args\n\ndef pubVerify(args):\n dest = args.pubKeyFile + \"-casig\"\n command = \"python2.7 rsa-validate.py -k \" + args.valFile + \" -m \" + args.pubKeyFile + \" -s \" + dest\n returnVal = subprocess.check_output([command], shell=True)\n return returnVal.strip()\n\ndef symVerify(args):\n command = \"python2.7 rsa-validate.py -k \" + args.pubKeyFile + \" -m symManifest -s symManifest-casig\"\n returnVal = subprocess.check_output([command], shell=True)\n return returnVal.strip()\n\ndef encVerify(key, file, currentdir):\n file = file[:-4]\n command = \"python2.7 \" + currentdir + \"/cbcmac-validate-2.py -k \" + str(key) + \" -m \" + file + \" -t \" + file + \"-tag\"\n result = subprocess.check_output([command], shell=True)\n return result.strip()\n\ndef decDir(directory, key):\n currentdir = os.getcwd()\n newlist = []\n for letter in currentdir:\n newlist.append(letter)\n for i in range(0, len(newlist)):\n if newlist[i] == ' ':\n newlist[i] = \"\\ \"\n currentdir = ''.join(newlist)\n\n for root, dirs, files in os.walk(directory):\n os.chdir(directory)\n #tags\n for file in files:\n if file[-4:] == \"-tag\":\n encIntegrity = encVerify(key, file, currentdir)\n if encIntegrity != \"True\":\n sys.exit(\"Bad file detected: %s\" % file)\n os.remove(file)\n\n os.chdir(\"..\")\n for root, dirs, files in os.walk(directory):\n #for files\n os.chdir(directory)\n for file in files:\n decFile(file.strip(), key, currentdir)\n\ndef decFile(file, key, currentdir):\n command = \"python2.7 \" + currentdir + \"/cbc-dec.py -k \" + str(key) + \" -i \" + file + \" -o \" + file\n subprocess.call([command], shell=True)\n\ndef decManifest(args, key):\n command = \"python2.7 rsa-dec.py -k \" + args.privKeyFile + \" -i \" + str(key)\n result = subprocess.check_output([command], shell=True)\n return result.strip()\n\ndef readManifest():\n fd = open(\"symManifest\", \"rb\")\n key = fd.readline()\n fd.close()\n return key.strip()\n\ndef main():\n args = getFlags()\n lockIntegrity = pubVerify(args)\n if lockIntegrity != \"True\":\n print(\"Locking Party's Public Key Was Unverified\")\n exit()\n symIntegrity = symVerify(args)\n if symIntegrity != \"True\":\n print(\"Symmetric Key Manifest Was Unverified\")\n exit()\n\n key = readManifest()\n aesKey = decManifest(args, key)\n decDir(args.directory, aesKey)\n\n\n\nif __name__ == \"__main__\":\n main()\n"},{"alpha_fraction":0.5534505844116211,"alphanum_fraction":0.5659675002098083,"avg_line_length":23.840335845947266,"blob_id":"e482044ed9b3adfa8433edb7cbdad9a25a91b32c","content_id":"e4921fdda793b2ea72356c18fc523d7dfe1f7720","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":2956,"license_type":"no_license","max_line_length":91,"num_lines":119,"path":"/rsa-enc.py","repo_name":"dsande30/COSC483_PA3","src_encoding":"UTF-8","text":"#RSA Encrypt\nimport sys\nimport argparse\nfrom Crypto.Util import number\nfrom Crypto.Random import random\nimport fractions\nimport binascii\n\ndef getFlags():\n #parse command line args\n parser = argparse.ArgumentParser()\n parser.add_argument(\"-k\", dest = 'keyFile', help=\"Enter Key file\", required = True)\n parser.add_argument(\"-i\", dest = 'inputFile', help=\"Enter input file\", required = True)\n args = parser.parse_args()\n return args\n\n#Encrypts the messag eafter padding\ndef Encrypt(m, contents):\n #print \"M: %d\" % m\n #rint \"N: %d\" % contents[1]\n #rint \"e: %d\" % contents[2]\n return pow(m, contents[2], contents[1])\n #return ((m**contents[2]) % contents[1])\n\n#NOTE: This will change with proper message\ndef writeOutput(outputFile, paddedM):\n o = open(outputFile, 'wb')\n o.write(str(paddedM))\n o.close()\n\n#Reads in the key file\ndef readKey(keyFile):\n key = open(keyFile, 'rb')\n numBits = key.readline()\n N = key.readline()\n e = key.readline()\n key.close()\n numBits = numBits.strip()\n N = N.strip()\n e = e.strip()\n return int(numBits), int(N), int(e)\n\n#in this instance we don't need input file\n'''\n#Reads in the input file\ndef readInput(inputFile):\n i = open(inputFile, 'rb')\n m = i.readline()\n i.close()\n m = str(m)\n return m\n'''\n\n#Function pads the message and prepares for encryption\ndef pad(message, r):\n M = \"\"\n M += str(ord(b'\\x00')) + str(ord(b'\\x02'))\n test = 0\n\n\n #Gets r random bits for padding\n while test == 0:\n test = 1\n rand = random.getrandbits(r)\n rand = str(rand)\n length = len(rand)\n randlength = 0\n list = []\n for x in rand:\n list.append(x)\n for i in range(0, len(list)):\n if list[i] == \"0\":\n string = str(random.getrandbits(30))\n if string[0:1] != 0:\n list[i] = string[0:1]\n #print(\"Replacing with %s\" % list[i])\n #randlength += int(x).bit_length()\n rand = int(''.join(list))\n randlength = rand.bit_length()\n if randlength != r:\n test = 0\n\n M += str(rand) + str(ord(b'\\x00'))\n message = message.strip()\n messageLen = 0\n\n M += message\n\n bitLength = 0\n for i in range(0, len(M)):\n bitLength += int(M[i]).bit_length()\n if M[i] == \"0\":\n bitLength += 1\n\n #DEBUGGING\n #print \"Rand: %s\" % rand\n #print randlength\n #print \"r - 24 = %d\" % (r - 24)\n #print \"Message after pad: %s\" % message\n #print \"messageLen: %d\" % messageLen\n #print \"What's M: %s\" % M\n #print \"bitLength: %d\" % bitLength\n\n return int(M)\n\n\n\ndef main():\n args = getFlags()\n contents = readKey(args.keyFile)\n message = args.inputFile\n paddedM = pad(message, int(contents[0]) / 2)\n c = Encrypt(paddedM, contents)\n print(c)\n return\n #writeOutput(args.outputFile, c)\n\nif __name__ == \"__main__\":\n\tmain()\n"},{"alpha_fraction":0.5502625703811646,"alphanum_fraction":0.5622655749320984,"avg_line_length":24.634614944458008,"blob_id":"f203aeb61df2361da07512e5154db30e1a8cb116","content_id":"9f9214e71baf418e92edf77c6e3b0fa19887139d","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":2666,"license_type":"no_license","max_line_length":104,"num_lines":104,"path":"/rsa-keygen.py","repo_name":"dsande30/COSC483_PA3","src_encoding":"UTF-8","text":"#RSA Key Generation\nimport sys\nimport argparse\nfrom Crypto.Util import number\nimport fractions\nimport subprocess\n\ndef getFlags():\n #parse command line args\n parser = argparse.ArgumentParser()\n parser.add_argument(\"-p\", dest = 'publicFile', help=\"Enter public key file\", required = True)\n parser.add_argument(\"-s\", dest = 'secretFile', help=\"Enter private key file\", required = True)\n parser.add_argument(\"-n\", dest = 'numBits', type=int, help= \"Enter num of bits file\", required=True)\n parser.add_argument(\"-c\", dest = 'caFile', help=\"Enter CA private key\")\n args = parser.parse_args()\n\n return args\n\ndef variableGenerator(numBits):\n #to make p and q\n p = 0\n q = 0\n l = (numBits / 2)\n while(p ==0 and q == 0):\n p = number.getPrime(l)\n q = number.getPrime(l)\n #confirm lengths are the same, not the values\n if p.bit_length() != q.bit_length() or p == q:\n p = 0\n q = 0\n\n p = int(p)\n q = int(q)\n\n N = p * q\n order = (p-1)*(q-1)\n\n #calculate e: coprime to order\n ePrimes = [3,5,7,17,257, 65537]\n booly = 0\n for x in ePrimes:\n if(fractions.gcd(order, x) == 1):\n booly = 1\n e = x\n break\n if booly == 0:\n sys.exit(\"No coprime\")\n\n #d is inverse of e mod order\n #NOTE: if this is not allowed, let me know. I was unsure.\n d = number.inverse(e, order)\n\n #print \"P: %d\" % p\n #print \"Q: %d\" % q\n #print \"N: %d\" % N\n #print \"Order: %d\" % order\n\n return N, d, e\n\ndef writeFiles(args, keys):\n pub = open(args.publicFile, 'w')\n priv = open(args.secretFile, 'w')\n\n #Write public key\n pub.write(\"%d\\n\" % args.numBits)\n pub.write(\"%d\\n\" % keys[0])\n pub.write(\"%d\\n\" % keys[2])\n\n #Write private key\n priv.write(\"%d\\n\" % args.numBits)\n priv.write(\"%d\\n\" % keys[0])\n priv.write(\"%d\\n\" % keys[1])\n\n #close files\n pub.close()\n priv.close()\n\n #Read CA key\n if args.caFile is not None:\n CA = open(args.caFile, \"r\")\n caNumBits = CA.readline()\n caN = CA.readline()\n caD = CA.readline()\n CA.close()\n else:\n args.caFile = args.secretFile\n priv = open(args.secretFile, \"r\")\n caNumBits = priv.readline()\n caN = priv.readline()\n caD = priv.readline()\n priv.close()\n dest = args.publicFile + \"-casig\"\n\n command = \"python2.7 rsa-sign.py -k \" + args.caFile + \" -m \" + args.publicFile + \" -s \" + dest\n subprocess.call([command], shell=True)\n\n\ndef main():\n args = getFlags()\n keys = variableGenerator(args.numBits)\n writeFiles(args, keys)\n\nif __name__ == \"__main__\":\n\tmain()\n"},{"alpha_fraction":0.5432525873184204,"alphanum_fraction":0.5542099475860596,"avg_line_length":23.08333396911621,"blob_id":"062247b54cb5baa49d9b69f16e8833d32edb7f62","content_id":"9be988974c5ac22cd026078f8eed08a029a8e9f4","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1734,"license_type":"no_license","max_line_length":92,"num_lines":72,"path":"/rsa-validate.py","repo_name":"dsande30/COSC483_PA3","src_encoding":"UTF-8","text":"import argparse\nfrom Crypto.Hash import SHA256\n\ndef getFlags():\n #parse command line args\n parser = argparse.ArgumentParser()\n parser.add_argument(\"-k\", dest = 'keyFile', help=\"Enter key file\", required = True)\n parser.add_argument(\"-m\", dest = 'msgFile', help=\"Enter message file\", required = True)\n parser.add_argument(\"-s\", dest = 'sigFile', help= \"Enter signature file\", required=True)\n args = parser.parse_args()\n return args\n\ndef openFiles(args):\n #keyFile\n fd = open(args.keyFile, \"r\")\n numBits = fd.readline()\n numBits = int(numBits.strip())\n N = fd.readline()\n N = int(N.strip())\n pubKey = fd.readline()\n pubKey = int(pubKey.strip())\n keyTuple = (numBits, N, pubKey)\n fd.close()\n\n #msgFile\n msg = \"\"\n fd = open(args.msgFile, \"rb\")\n while True:\n string = fd.readline()\n if string == \"\":\n break\n msg += string\n fd.close()\n\n #sigFile\n fd = open(args.sigFile, \"r\")\n sig = \"\"\n while True:\n string = fd.readline()\n if string == \"\":\n break\n sig += string\n sig = int(sig)\n fd.close()\n\n return (keyTuple, msg, sig)\n\ndef hash(message):\n h = SHA256.new()\n h.update(message)\n return h\n\ndef verify(h, sig, N, e):\n result = pow(sig, e, N)\n #print(\"Validating %s\\n\\n%s\" % (result, (int(h.hexdigest(), 16) % N)))\n if result == (int(h.hexdigest(), 16) % N):\n return 1\n else:\n return 0\n\ndef main():\n args = getFlags()\n results = openFiles(args)\n h = hash(results[1])\n value = verify(h, results[2], results[0][1], results[0][2])\n if value == 1:\n print(\"True\")\n else:\n print(\"False\")\n\nif __name__ == \"__main__\":\n main()\n"},{"alpha_fraction":0.5396214127540588,"alphanum_fraction":0.5556625127792358,"avg_line_length":23.93600082397461,"blob_id":"0d58b9fd3c45c0c8415ee2093e1d7e45c46dbfb7","content_id":"5b7a7102cf4553c07672a51cc4a03b7fbe85cf7c","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":3117,"license_type":"no_license","max_line_length":91,"num_lines":125,"path":"/cbc-enc.py","repo_name":"dsande30/COSC483_PA3","src_encoding":"UTF-8","text":"#CBC - ENC\n\nimport binascii\nimport getopt\nimport sys\nimport os\nfrom Crypto.Random import random\nfrom Crypto.Cipher import AES\nimport argparse\n\n#Pads the plaintext\ndef pad(message):\n if len(message) > 16:\n if len(message) % 16 != 0:\n message += \"0\" * (16 - (len(message) % 16))\n elif len(message) < 16:\n message += \"0\" * (16 - len(message))\n return message\n\n#XOR function\ndef xor(blocks, IV, key32):\n message = []\n cipher = AES.new(key32, AES.MODE_ECB)\n priorBlock = IV\n for currentBlock in blocks:\n ciphertext = cipher.encrypt(str(priorBlock))\n text = \"\"\n text += \"\".join(chr(ord(a)^ord(b)) for a,b in zip(currentBlock, ciphertext))\n priorBlock = text\n message += text\n return message\n\ndef main(argv):\n keyfile = ''\n inputfile = ''\n outputfile = ''\n ivfile = ''\n\n parser = argparse.ArgumentParser()\n parser.add_argument(\"-k\", dest = 'keyfile', help=\"Enter key file\", required = True)\n parser.add_argument(\"-i\", dest = 'inputfile', help=\"Enter input file\", required = True)\n parser.add_argument(\"-o\", dest = 'outputfile', help= \"Enter ouput file\", required=True)\n args = parser.parse_args()\n\n #Opens Files\n #k = open(args.keyfile, 'rb')\n i = open(args.inputfile, 'rb')\n if ivfile != \"\":\n v = open(ivfile, 'rb')\n\n s = []\n key = \"\"\n plaintext = \"\"\n IV = \"\"\n\n #reads in key\n key = args.keyfile\n\n #read in input\n while True:\n string = i.readline()\n if string == \"\":\n break\n plaintext += string\n\n i.close()\n os.remove(args.inputfile)\n\n #Reads in from the input file, key file, and optional IV file\n try:\n if ivfile != \"\":\n byte3 = v.read(1)\n if ivfile != \"\":\n while byte3 != \"\":\n IV += byte3\n byte3 = v.read(1)\n finally:\n if ivfile != \"\":\n v.close()\n\n #Pads the plaintext if needed\n plaintext = pad(plaintext)\n\n blocks = []\n\n\n #Separates the plaintext into blocks of 16 bytes\n x = 0\n check = plaintext[:]\n while len(check) > 0:\n slicelen = min(len(plaintext), 16)\n blocks.append(check[0:slicelen])\n check = check[slicelen:]\n x += 1\n\n #Generates IV if no file specified\n if ivfile == \"\":\n test = 0\n while test == 0:\n IV = str(random.getrandbits(64))\n if len(IV.encode('utf-8')) == 16:\n test = 1\n\n #Gets correct key and Then XORs text\n #key32 = \"\".join([ ' ' if x >= len(s) else s[x] for x in range(32)])\n key32 = key.strip()\n\n #Gets rid of any newline chars in the IV and unhexlifies it if\n #read in from a file\n IV = IV.rstrip(\"\\r\") #FIXME \\n\n if ivfile != \"\":\n IV = binascii.unhexlify(IV)\n\n #Calls the XOR function for the ciphertext\n ciphertext = xor(blocks, IV, key32)\n\n #Only the ciphertext appears in the output file\n o = open(args.outputfile, 'wb')\n o.write(str(IV))\n o.write(\"\\n\")\n o.write(\"\".join(ciphertext))\n o.close()\n\nif __name__ == \"__main__\":\n main(sys.argv[1:])\n"},{"alpha_fraction":0.6232368350028992,"alphanum_fraction":0.6299183368682861,"avg_line_length":32.25925827026367,"blob_id":"2140d4b5ed0b32db8fc4485f226fab7e58e3d13e","content_id":"7e557b49882b6ea64b68846eb976106ad436b187","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":2694,"license_type":"no_license","max_line_length":125,"num_lines":81,"path":"/lock.py","repo_name":"dsande30/COSC483_PA3","src_encoding":"UTF-8","text":"import os\nimport argparse\nfrom Crypto.Random import random\nimport subprocess\n\ndef getFlags():\n #parse command line args\n parser = argparse.ArgumentParser()\n parser.add_argument(\"-d\", dest = 'directory', help=\"Enter directory to lock\", required = True)\n parser.add_argument(\"-p\", dest = 'pubKeyFile', help=\"Enter action public key file\", required = True)\n parser.add_argument(\"-r\", dest = 'privKeyFile', help= \"Enter action private key file\", required=True)\n parser.add_argument(\"-vk\", dest = 'valFile', help= \"Enter validate pubkey file\", required=True)\n args = parser.parse_args()\n return args\n\ndef verifyUnlocker(args):\n command = \"python2.7 rsa-validate.py -k \" + args.valFile + \" -m \" + args.pubKeyFile + \" -s \" + args.pubKeyFile + \"-casig\"\n #print(\"Command: %s\" % command)\n result = subprocess.check_output([command], shell=True)\n if(result.strip() == \"True\"):\n #print(\"Verified\")\n return\n else:\n sys.exit(\"Unverified unlocker\")\n\ndef randAESKey():\n val = random.getrandbits(128)\n val = str(val)\n val = val[0:16]\n return int(val)\n\ndef rsaEnc(args, key):\n command = \"python2.7 rsa-enc.py -k \" + args.pubKeyFile + \" -i \" + str(key)\n result = subprocess.check_output([command], shell=True)\n return result.strip()\n\ndef printManifest(encryptedKey):\n fd = open(\"symManifest\", \"w\")\n fd.write(encryptedKey)\n fd.close()\n\ndef signManifest(lock_priv):\n command = \"python2.7 rsa-sign.py -k \" + lock_priv + \" -m symManifest -s symManifest-casig\"\n subprocess.call([command], shell=True)\n\ndef encryptDir(directory, key):\n currentdir = os.getcwd()\n newlist = []\n for letter in currentdir:\n newlist.append(letter)\n for i in range(0, len(newlist)):\n if newlist[i] == ' ':\n newlist[i] = \"\\ \"\n currentdir = ''.join(newlist)\n\n\n for root, dirs, files in os.walk(directory):\n os.chdir(directory)\n for file in files:\n encryptFile(file, key, currentdir)\n tagFile(file, key, currentdir)\n\ndef encryptFile(file, key, currentdir):\n command = \"python2.7 \" + currentdir + \"/cbc-enc.py -k \" + str(key) + \" -i \" + file + \" -o \" + file\n subprocess.call([command], shell=True)\n\ndef tagFile(file, key, currentdir):\n command = \"python2.7 \" + currentdir + \"/cbcmac-tag_2.py -k \" + str(key) + \" -m \" + file + \" -t \" + file + \"-tag\"\n subprocess.call([command], shell=True)\n\ndef main():\n args = getFlags()\n check = verifyUnlocker(args)\n key = randAESKey()\n encryptedKey = rsaEnc(args, key)\n printManifest(encryptedKey)\n signManifest(args.privKeyFile)\n encryptDir(args.directory, key)\n\nif __name__ == \"__main__\":\n main()\n"},{"alpha_fraction":0.5744485259056091,"alphanum_fraction":0.5900735259056091,"avg_line_length":25.536584854125977,"blob_id":"6ab30a3f54c3bfed40d428013eedcf2aeb7fc438","content_id":"74b10b0aa192b904890c9c06f4c419445511e4a5","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":2176,"license_type":"no_license","max_line_length":91,"num_lines":82,"path":"/cbcmac-tag_2.py","repo_name":"dsande30/COSC483_PA3","src_encoding":"UTF-8","text":"import argparse\nfrom Crypto.Cipher import AES\n\ndef getFlags():\n #parse command line args\n parser = argparse.ArgumentParser()\n parser.add_argument(\"-k\", dest = 'keyFile', help=\"Enter key file\", required = True)\n parser.add_argument(\"-m\", dest = 'msgFile', help=\"Enter message file\", required = True)\n parser.add_argument(\"-t\", dest = 'tagFile', help= \"Enter tag file\", required=True)\n args = parser.parse_args()\n return args\n\ndef getInfo(args):\n #fd = open(args.keyFile)\n key = args.keyFile\n #fd.close()\n\n fd = open(args.msgFile)\n msg = \"\"\n while True:\n string = fd.readline()\n if string == \"\":\n break\n msg += string\n fd.close()\n msg = msg.strip()\n return (key, msg)\n\n#Pads the plaintext\ndef pad(message):\n if len(message) > 16:\n if len(message) % 16 != 0:\n message += \"0\" * (16 - (len(message) % 16))\n elif len(message) < 16:\n message += \"0\" * (16 - len(message))\n return message\n\n#XOR function\ndef xor(blocks, key32):\n message = []\n cipher = AES.new(key32, AES.MODE_ECB)\n priorBlock = blocks[0]\n message = \"\"\n for currentBlock in blocks[1:]:\n ciphertext = cipher.encrypt(str(priorBlock))\n text = \"\"\n text += \"\".join(chr(ord(a)^ord(b)) for a,b in zip(currentBlock, ciphertext))\n priorBlock = text\n message += text\n return message\n\ndef blockify(plaintext):\n #Separates the plaintext into blocks of 16 bytes\n x = 0\n blocks = []\n length = len(plaintext)\n while(len(str(length)) < 16):\n length = \"0\" + str(length)\n blocks.append(length)\n check = plaintext[:]\n while len(check) > 0:\n slicelen = min(len(plaintext), 16)\n blocks.append(check[0:slicelen])\n check = check[slicelen:]\n x += 1\n return blocks\n\ndef writeFile(oFile, ciphertext):\n fd = open(oFile, \"wb\")\n fd.write(ciphertext)\n fd.close()\n\ndef main():\n args = getFlags()\n results = getInfo(args)\n paddedmsg = pad(results[1])\n blocks = blockify(paddedmsg)\n ciphertext = xor(blocks, results[0])\n writeFile(args.tagFile, ciphertext)\n\nif __name__ == \"__main__\":\n main()\n"},{"alpha_fraction":0.5597867369651794,"alphanum_fraction":0.5738766193389893,"avg_line_length":23.542055130004883,"blob_id":"34a43830106b3f2aed823511b322f755d530b1bf","content_id":"4790755e3b19f69f3f127ba967a9eaeb82d90033","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":2626,"license_type":"no_license","max_line_length":91,"num_lines":107,"path":"/cbcmac-validate.py","repo_name":"dsande30/COSC483_PA3","src_encoding":"UTF-8","text":"import argparse\nfrom Crypto.Cipher import AES\nimport binascii\nimport difflib\n\ndef getFlags():\n #parse command line args\n parser = argparse.ArgumentParser()\n parser.add_argument(\"-k\", dest = 'keyFile', help=\"Enter key file\", required = True)\n parser.add_argument(\"-m\", dest = 'msgFile', help=\"Enter message file\", required = True)\n parser.add_argument(\"-t\", dest = 'tagFile', help= \"Enter tag file\", required=True)\n args = parser.parse_args()\n return args\n\ndef readTag(tagFile):\n t = open(tagFile, 'rb')\n tag = \"\"\n while True:\n string = t.readline()\n if string == \"\":\n break\n tag += string\n t.close()\n return tag\n\ndef readKey(keyFile):\n key = open(keyFile, 'rb')\n validKey = key.readline().strip()\n key.close()\n return validKey\n\ndef readInput(msgFile):\n i = open(msgFile, 'r')\n m = \"\"\n while True:\n string = i.readline()\n if string == \"\":\n break\n m += string\n m = m.strip()\n i.close()\n return m\n\n#Pads the plaintext\ndef pad(message):\n if len(message) > 16:\n if len(message) % 16 != 0:\n message += \"0\" * (16 - (len(message) % 16))\n elif len(message) < 16:\n message += \"0\" * (16 - len(message))\n return message\n\n#XOR function\ndef xor(blocks, key32):\n message = []\n cipher = AES.new(key32, AES.MODE_ECB)\n priorBlock = blocks[0]\n message = \"\"\n for currentBlock in blocks[1:]:\n ciphertext = cipher.encrypt(str(priorBlock))\n text = \"\"\n text += \"\".join(chr(ord(a)^ord(b)) for a,b in zip(currentBlock, ciphertext))\n priorBlock = text\n message += text\n return message\n\ndef blockify(plaintext):\n #Separates the plaintext into blocks of 16 bytes\n x = 0\n blocks = []\n length = len(plaintext)\n while(len(str(length)) < 16):\n length = \"0\" + str(length)\n blocks.append(length)\n check = plaintext[:]\n while len(check) > 0:\n slicelen = min(len(plaintext), 16)\n blocks.append(check[0:slicelen])\n check = check[slicelen:]\n x += 1\n return blocks\n\ndef verify(key, message, tag):\n message = pad(str(message))\n blocks = blockify(message)\n compMsg = xor(blocks, key)\n if tag == compMsg:\n return 1\n else:\n return 0\n\ndef main():\n args = getFlags()\n key = readKey(args.keyFile)\n tag = readTag(args.tagFile)\n message = readInput(args.msgFile)\n validity = verify(key, message, tag)\n if validity == 1:\n print(\"True\")\n return 1\n else:\n print(\"False\")\n return 0\n\n\nif __name__ == \"__main__\":\n main()\n"},{"alpha_fraction":0.5954098105430603,"alphanum_fraction":0.6019672155380249,"avg_line_length":24.41666603088379,"blob_id":"12cae38c1253ffab18fa94a8d06081805dd49cc5","content_id":"a6585b892f684a552c7614a2ac7be8b03924f72f","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1525,"license_type":"no_license","max_line_length":92,"num_lines":60,"path":"/rsa-sign.py","repo_name":"dsande30/COSC483_PA3","src_encoding":"UTF-8","text":"import argparse\nfrom Crypto.Hash import SHA256\n\ndef getFlags():\n #parse command line args\n parser = argparse.ArgumentParser()\n parser.add_argument(\"-k\", dest = 'keyFile', help=\"Enter key file\", required = True)\n parser.add_argument(\"-m\", dest = 'msgFile', help=\"Enter message file\", required = True)\n parser.add_argument(\"-s\", dest = 'sigFile', help= \"Enter signature file\", required=True)\n args = parser.parse_args()\n return args\n\ndef readKey(keyFile):\n key = open(keyFile, 'rb')\n numBits = key.readline()\n N = key.readline()\n d = key.readline()\n key.close()\n numBits = numBits.strip()\n N = N.strip()\n d = d.strip()\n return int(numBits), int(N), int(d)\n\ndef readInput(inputFile):\n i = open(inputFile, 'r')\n m = \"\"\n while True:\n string = i.readline()\n if string == \"\":\n break\n m += string\n i.close()\n return m\n\ndef writeOutput(sigFile, signature):\n s = open(sigFile, 'wb')\n s.write(str(signature))\n s.close()\n\ndef doHash(message):\n h = SHA256.new()\n h.update(message)\n #print(\"Hash: %s\" % h.hexdigest())\n return h\n\ndef sign(h, N, d):\n signature = pow(int(h.hexdigest(), 16), d, N)\n return signature\n\ndef main():\n args = getFlags()\n contents = readKey(args.keyFile)\n message = readInput(args.msgFile)\n h = doHash(message)\n signature = sign(h, contents[1], contents[2])\n #print(\"Writing: \\n%s\" % signature)\n writeOutput(args.sigFile, signature)\n\nif __name__ == \"__main__\":\n main()\n"},{"alpha_fraction":0.567480742931366,"alphanum_fraction":0.5700514316558838,"avg_line_length":20.550724029541016,"blob_id":"e8f962b22537a12e4e05b6523b3c77732aae39f1","content_id":"56eb1a01d46169b2af0a9f06fa3e2bf51592686a","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1556,"license_type":"no_license","max_line_length":91,"num_lines":69,"path":"/rsa-dec.py","repo_name":"dsande30/COSC483_PA3","src_encoding":"UTF-8","text":"#RSA Decrypt\r\nimport sys\r\nimport argparse\r\nfrom Crypto.Util import number\r\nimport fractions\r\n\r\ndef getFlags():\r\n #parse command line args\r\n parser = argparse.ArgumentParser()\r\n parser.add_argument(\"-k\", dest = 'keyFile', help=\"Enter Key file\", required = True)\r\n parser.add_argument(\"-i\", dest = 'inputFile', help=\"Enter input file\", required = True)\r\n args = parser.parse_args()\r\n\r\n return args\r\n\r\n#Reads in key file\r\ndef readKey(keyFile):\r\n key = open(keyFile, 'rb')\r\n numBits = key.readline()\r\n numBits = numBits.strip()\r\n N = key.readline()\r\n N = N.strip()\r\n d = key.readline()\r\n d = d.strip()\r\n key.close()\r\n return numBits, N, d\r\n\r\n#Reads in Input File\r\ndef readInput(inputFile):\r\n inp = open(inputFile, 'rb')\r\n c = inp.readline()\r\n c = c.strip()\r\n return c\r\n\r\n#Decrypts the file\r\ndef Dec(key, c):\r\n c = int(c)\r\n d = int(key[2])\r\n N = int(key[1])\r\n #print \"C: %d\" % c\r\n #print(\"N: %d\" % N)\r\n #print(\"d: %d\" % d)\r\n m = pow(c, d, N)\r\n return m\r\n\r\n#Writes the output to the designated output file\r\ndef writeOutput(outputFile, m):\r\n out = open(outputFile, 'wb')\r\n out.write(\"%d\" %m)\r\n out.close()\r\n\r\n#Removes the padding to reveal the original message\r\ndef unpad(m):\r\n #print m\r\n r, M = m.split(\"0\", 1)\r\n M = M.strip()\r\n return M\r\n\r\ndef main():\r\n args = getFlags()\r\n key = readKey(args.keyFile)\r\n message = args.inputFile\r\n m = Dec(key, message)\r\n m = unpad(str(m))\r\n print(str(m))\r\n return\r\n\r\nif __name__ == \"__main__\":\r\n\tmain()\r\n"},{"alpha_fraction":0.5854460000991821,"alphanum_fraction":0.5962441563606262,"avg_line_length":23.482759475708008,"blob_id":"e8633f16843656ad8c8d0011817d0854a20e7c09","content_id":"d817185c57e28bffb6b36dee19e42fc24f3d5b47","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":2130,"license_type":"no_license","max_line_length":91,"num_lines":87,"path":"/cbc-dec.py","repo_name":"dsande30/COSC483_PA3","src_encoding":"UTF-8","text":"##CBC - DEC\n\nimport binascii\nimport getopt\nimport sys\nimport os\nimport argparse\nfrom Crypto.Random import random\nfrom Crypto.Cipher import AES\n\n#XOR function\ndef xor(blocks, IV, key32):\n message = []\n cipher = AES.new(key32, AES.MODE_ECB)\n priorBlock = IV\n for currentBlock in blocks:\n ciphertext = cipher.encrypt(str(priorBlock))\n text = \"\"\n text += \"\".join(chr(ord(a)^ord(b)) for a,b in zip(currentBlock, ciphertext))\n priorBlock = currentBlock\n message += text\n return message\n\ndef main(argv):\n keyfile = ''\n inputfile = ''\n outputfile = ''\n ivfile = ''\n\n #Reads flags from command line\n parser = argparse.ArgumentParser()\n parser.add_argument(\"-k\", dest = 'keyfile', help=\"Enter key file\", required = True)\n parser.add_argument(\"-i\", dest = 'inputfile', help=\"Enter input file\", required = True)\n parser.add_argument(\"-o\", dest = 'outputfile', help= \"Enter ouput file\", required=True)\n args = parser.parse_args()\n\n #Opens Files\n i = open(args.inputfile, 'rb')\n\n\n s = []\n key = \"\"\n ciphertext = \"\"\n\n #Takes the IV from the Encryption Part\n key = args.keyfile\n IV = i.readline()\n\n while True:\n string = i.readline()\n if string == \"\":\n break\n ciphertext += str(string)\n\n i.close()\n os.remove(args.inputfile)\n\n\n blocks = []\n\n #Splits up the ciphertext into blocks of 16 bytes\n x = 0\n check = ciphertext[:]\n while len(check) > 0:\n slicelen = min(len(ciphertext), 16)\n blocks.append(check[0:slicelen])\n check = check[slicelen:]\n x += 1\n\n #Gets correct key\n #key32 = \"\".join([ ' ' if x >= len(s) else s[x] for x in range(32)])\n key32 = key\n #print(\"Key %s\" % key32)\n\n #Strips any newline characters from the IV so that it is the right size\n IV = IV.rstrip(\"\\n\\r\")\n #print(\"IV %s\" % IV)\n\n #Calls the XOR function to get the original plaintext\n plaintext = xor(blocks, IV, key32)\n\n o = open(args.outputfile, 'wb')\n o.write(repr(\"\".join(plaintext)))\n o.close()\n\nif __name__ == \"__main__\":\n main(sys.argv[1:])\n"}],"string":"[\n {\n \"alpha_fraction\": 0.6085432171821594,\n \"alphanum_fraction\": 0.613006055355072,\n \"avg_line_length\": 32.37234115600586,\n \"blob_id\": \"7c806e1d694f8713bd699e58a8f140a3b9739d73\",\n \"content_id\": \"b50338a8fcd79074a6a7ba5a98065aa1c79f4355\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 3137,\n \"license_type\": \"no_license\",\n \"max_line_length\": 121,\n \"num_lines\": 94,\n \"path\": \"/unlock.py\",\n \"repo_name\": \"dsande30/COSC483_PA3\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import argparse\\nimport subprocess\\nimport os\\nimport sys\\nfrom Crypto.Random import random\\n\\ndef getFlags():\\n #parse command line args\\n parser = argparse.ArgumentParser()\\n parser.add_argument(\\\"-d\\\", dest = 'directory', help=\\\"Enter directory to lock\\\", required = True)\\n parser.add_argument(\\\"-p\\\", dest = 'pubKeyFile', help=\\\"Enter action public key file\\\", required = True)\\n parser.add_argument(\\\"-r\\\", dest = 'privKeyFile', help= \\\"Enter action private key file\\\", required=True)\\n parser.add_argument(\\\"-vk\\\", dest = 'valFile', help= \\\"Enter validate pubkey file\\\", required=True)\\n args = parser.parse_args()\\n return args\\n\\ndef pubVerify(args):\\n dest = args.pubKeyFile + \\\"-casig\\\"\\n command = \\\"python2.7 rsa-validate.py -k \\\" + args.valFile + \\\" -m \\\" + args.pubKeyFile + \\\" -s \\\" + dest\\n returnVal = subprocess.check_output([command], shell=True)\\n return returnVal.strip()\\n\\ndef symVerify(args):\\n command = \\\"python2.7 rsa-validate.py -k \\\" + args.pubKeyFile + \\\" -m symManifest -s symManifest-casig\\\"\\n returnVal = subprocess.check_output([command], shell=True)\\n return returnVal.strip()\\n\\ndef encVerify(key, file, currentdir):\\n file = file[:-4]\\n command = \\\"python2.7 \\\" + currentdir + \\\"/cbcmac-validate-2.py -k \\\" + str(key) + \\\" -m \\\" + file + \\\" -t \\\" + file + \\\"-tag\\\"\\n result = subprocess.check_output([command], shell=True)\\n return result.strip()\\n\\ndef decDir(directory, key):\\n currentdir = os.getcwd()\\n newlist = []\\n for letter in currentdir:\\n newlist.append(letter)\\n for i in range(0, len(newlist)):\\n if newlist[i] == ' ':\\n newlist[i] = \\\"\\\\ \\\"\\n currentdir = ''.join(newlist)\\n\\n for root, dirs, files in os.walk(directory):\\n os.chdir(directory)\\n #tags\\n for file in files:\\n if file[-4:] == \\\"-tag\\\":\\n encIntegrity = encVerify(key, file, currentdir)\\n if encIntegrity != \\\"True\\\":\\n sys.exit(\\\"Bad file detected: %s\\\" % file)\\n os.remove(file)\\n\\n os.chdir(\\\"..\\\")\\n for root, dirs, files in os.walk(directory):\\n #for files\\n os.chdir(directory)\\n for file in files:\\n decFile(file.strip(), key, currentdir)\\n\\ndef decFile(file, key, currentdir):\\n command = \\\"python2.7 \\\" + currentdir + \\\"/cbc-dec.py -k \\\" + str(key) + \\\" -i \\\" + file + \\\" -o \\\" + file\\n subprocess.call([command], shell=True)\\n\\ndef decManifest(args, key):\\n command = \\\"python2.7 rsa-dec.py -k \\\" + args.privKeyFile + \\\" -i \\\" + str(key)\\n result = subprocess.check_output([command], shell=True)\\n return result.strip()\\n\\ndef readManifest():\\n fd = open(\\\"symManifest\\\", \\\"rb\\\")\\n key = fd.readline()\\n fd.close()\\n return key.strip()\\n\\ndef main():\\n args = getFlags()\\n lockIntegrity = pubVerify(args)\\n if lockIntegrity != \\\"True\\\":\\n print(\\\"Locking Party's Public Key Was Unverified\\\")\\n exit()\\n symIntegrity = symVerify(args)\\n if symIntegrity != \\\"True\\\":\\n print(\\\"Symmetric Key Manifest Was Unverified\\\")\\n exit()\\n\\n key = readManifest()\\n aesKey = decManifest(args, key)\\n decDir(args.directory, aesKey)\\n\\n\\n\\nif __name__ == \\\"__main__\\\":\\n main()\\n\"\n },\n {\n \"alpha_fraction\": 0.5534505844116211,\n \"alphanum_fraction\": 0.5659675002098083,\n \"avg_line_length\": 23.840335845947266,\n \"blob_id\": \"e482044ed9b3adfa8433edb7cbdad9a25a91b32c\",\n \"content_id\": \"e4921fdda793b2ea72356c18fc523d7dfe1f7720\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 2956,\n \"license_type\": \"no_license\",\n \"max_line_length\": 91,\n \"num_lines\": 119,\n \"path\": \"/rsa-enc.py\",\n \"repo_name\": \"dsande30/COSC483_PA3\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#RSA Encrypt\\nimport sys\\nimport argparse\\nfrom Crypto.Util import number\\nfrom Crypto.Random import random\\nimport fractions\\nimport binascii\\n\\ndef getFlags():\\n #parse command line args\\n parser = argparse.ArgumentParser()\\n parser.add_argument(\\\"-k\\\", dest = 'keyFile', help=\\\"Enter Key file\\\", required = True)\\n parser.add_argument(\\\"-i\\\", dest = 'inputFile', help=\\\"Enter input file\\\", required = True)\\n args = parser.parse_args()\\n return args\\n\\n#Encrypts the messag eafter padding\\ndef Encrypt(m, contents):\\n #print \\\"M: %d\\\" % m\\n #rint \\\"N: %d\\\" % contents[1]\\n #rint \\\"e: %d\\\" % contents[2]\\n return pow(m, contents[2], contents[1])\\n #return ((m**contents[2]) % contents[1])\\n\\n#NOTE: This will change with proper message\\ndef writeOutput(outputFile, paddedM):\\n o = open(outputFile, 'wb')\\n o.write(str(paddedM))\\n o.close()\\n\\n#Reads in the key file\\ndef readKey(keyFile):\\n key = open(keyFile, 'rb')\\n numBits = key.readline()\\n N = key.readline()\\n e = key.readline()\\n key.close()\\n numBits = numBits.strip()\\n N = N.strip()\\n e = e.strip()\\n return int(numBits), int(N), int(e)\\n\\n#in this instance we don't need input file\\n'''\\n#Reads in the input file\\ndef readInput(inputFile):\\n i = open(inputFile, 'rb')\\n m = i.readline()\\n i.close()\\n m = str(m)\\n return m\\n'''\\n\\n#Function pads the message and prepares for encryption\\ndef pad(message, r):\\n M = \\\"\\\"\\n M += str(ord(b'\\\\x00')) + str(ord(b'\\\\x02'))\\n test = 0\\n\\n\\n #Gets r random bits for padding\\n while test == 0:\\n test = 1\\n rand = random.getrandbits(r)\\n rand = str(rand)\\n length = len(rand)\\n randlength = 0\\n list = []\\n for x in rand:\\n list.append(x)\\n for i in range(0, len(list)):\\n if list[i] == \\\"0\\\":\\n string = str(random.getrandbits(30))\\n if string[0:1] != 0:\\n list[i] = string[0:1]\\n #print(\\\"Replacing with %s\\\" % list[i])\\n #randlength += int(x).bit_length()\\n rand = int(''.join(list))\\n randlength = rand.bit_length()\\n if randlength != r:\\n test = 0\\n\\n M += str(rand) + str(ord(b'\\\\x00'))\\n message = message.strip()\\n messageLen = 0\\n\\n M += message\\n\\n bitLength = 0\\n for i in range(0, len(M)):\\n bitLength += int(M[i]).bit_length()\\n if M[i] == \\\"0\\\":\\n bitLength += 1\\n\\n #DEBUGGING\\n #print \\\"Rand: %s\\\" % rand\\n #print randlength\\n #print \\\"r - 24 = %d\\\" % (r - 24)\\n #print \\\"Message after pad: %s\\\" % message\\n #print \\\"messageLen: %d\\\" % messageLen\\n #print \\\"What's M: %s\\\" % M\\n #print \\\"bitLength: %d\\\" % bitLength\\n\\n return int(M)\\n\\n\\n\\ndef main():\\n args = getFlags()\\n contents = readKey(args.keyFile)\\n message = args.inputFile\\n paddedM = pad(message, int(contents[0]) / 2)\\n c = Encrypt(paddedM, contents)\\n print(c)\\n return\\n #writeOutput(args.outputFile, c)\\n\\nif __name__ == \\\"__main__\\\":\\n\\tmain()\\n\"\n },\n {\n \"alpha_fraction\": 0.5502625703811646,\n \"alphanum_fraction\": 0.5622655749320984,\n \"avg_line_length\": 24.634614944458008,\n \"blob_id\": \"f203aeb61df2361da07512e5154db30e1a8cb116\",\n \"content_id\": \"9f9214e71baf418e92edf77c6e3b0fa19887139d\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 2666,\n \"license_type\": \"no_license\",\n \"max_line_length\": 104,\n \"num_lines\": 104,\n \"path\": \"/rsa-keygen.py\",\n \"repo_name\": \"dsande30/COSC483_PA3\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#RSA Key Generation\\nimport sys\\nimport argparse\\nfrom Crypto.Util import number\\nimport fractions\\nimport subprocess\\n\\ndef getFlags():\\n #parse command line args\\n parser = argparse.ArgumentParser()\\n parser.add_argument(\\\"-p\\\", dest = 'publicFile', help=\\\"Enter public key file\\\", required = True)\\n parser.add_argument(\\\"-s\\\", dest = 'secretFile', help=\\\"Enter private key file\\\", required = True)\\n parser.add_argument(\\\"-n\\\", dest = 'numBits', type=int, help= \\\"Enter num of bits file\\\", required=True)\\n parser.add_argument(\\\"-c\\\", dest = 'caFile', help=\\\"Enter CA private key\\\")\\n args = parser.parse_args()\\n\\n return args\\n\\ndef variableGenerator(numBits):\\n #to make p and q\\n p = 0\\n q = 0\\n l = (numBits / 2)\\n while(p ==0 and q == 0):\\n p = number.getPrime(l)\\n q = number.getPrime(l)\\n #confirm lengths are the same, not the values\\n if p.bit_length() != q.bit_length() or p == q:\\n p = 0\\n q = 0\\n\\n p = int(p)\\n q = int(q)\\n\\n N = p * q\\n order = (p-1)*(q-1)\\n\\n #calculate e: coprime to order\\n ePrimes = [3,5,7,17,257, 65537]\\n booly = 0\\n for x in ePrimes:\\n if(fractions.gcd(order, x) == 1):\\n booly = 1\\n e = x\\n break\\n if booly == 0:\\n sys.exit(\\\"No coprime\\\")\\n\\n #d is inverse of e mod order\\n #NOTE: if this is not allowed, let me know. I was unsure.\\n d = number.inverse(e, order)\\n\\n #print \\\"P: %d\\\" % p\\n #print \\\"Q: %d\\\" % q\\n #print \\\"N: %d\\\" % N\\n #print \\\"Order: %d\\\" % order\\n\\n return N, d, e\\n\\ndef writeFiles(args, keys):\\n pub = open(args.publicFile, 'w')\\n priv = open(args.secretFile, 'w')\\n\\n #Write public key\\n pub.write(\\\"%d\\\\n\\\" % args.numBits)\\n pub.write(\\\"%d\\\\n\\\" % keys[0])\\n pub.write(\\\"%d\\\\n\\\" % keys[2])\\n\\n #Write private key\\n priv.write(\\\"%d\\\\n\\\" % args.numBits)\\n priv.write(\\\"%d\\\\n\\\" % keys[0])\\n priv.write(\\\"%d\\\\n\\\" % keys[1])\\n\\n #close files\\n pub.close()\\n priv.close()\\n\\n #Read CA key\\n if args.caFile is not None:\\n CA = open(args.caFile, \\\"r\\\")\\n caNumBits = CA.readline()\\n caN = CA.readline()\\n caD = CA.readline()\\n CA.close()\\n else:\\n args.caFile = args.secretFile\\n priv = open(args.secretFile, \\\"r\\\")\\n caNumBits = priv.readline()\\n caN = priv.readline()\\n caD = priv.readline()\\n priv.close()\\n dest = args.publicFile + \\\"-casig\\\"\\n\\n command = \\\"python2.7 rsa-sign.py -k \\\" + args.caFile + \\\" -m \\\" + args.publicFile + \\\" -s \\\" + dest\\n subprocess.call([command], shell=True)\\n\\n\\ndef main():\\n args = getFlags()\\n keys = variableGenerator(args.numBits)\\n writeFiles(args, keys)\\n\\nif __name__ == \\\"__main__\\\":\\n\\tmain()\\n\"\n },\n {\n \"alpha_fraction\": 0.5432525873184204,\n \"alphanum_fraction\": 0.5542099475860596,\n \"avg_line_length\": 23.08333396911621,\n \"blob_id\": \"062247b54cb5baa49d9b69f16e8833d32edb7f62\",\n \"content_id\": \"9be988974c5ac22cd026078f8eed08a029a8e9f4\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1734,\n \"license_type\": \"no_license\",\n \"max_line_length\": 92,\n \"num_lines\": 72,\n \"path\": \"/rsa-validate.py\",\n \"repo_name\": \"dsande30/COSC483_PA3\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import argparse\\nfrom Crypto.Hash import SHA256\\n\\ndef getFlags():\\n #parse command line args\\n parser = argparse.ArgumentParser()\\n parser.add_argument(\\\"-k\\\", dest = 'keyFile', help=\\\"Enter key file\\\", required = True)\\n parser.add_argument(\\\"-m\\\", dest = 'msgFile', help=\\\"Enter message file\\\", required = True)\\n parser.add_argument(\\\"-s\\\", dest = 'sigFile', help= \\\"Enter signature file\\\", required=True)\\n args = parser.parse_args()\\n return args\\n\\ndef openFiles(args):\\n #keyFile\\n fd = open(args.keyFile, \\\"r\\\")\\n numBits = fd.readline()\\n numBits = int(numBits.strip())\\n N = fd.readline()\\n N = int(N.strip())\\n pubKey = fd.readline()\\n pubKey = int(pubKey.strip())\\n keyTuple = (numBits, N, pubKey)\\n fd.close()\\n\\n #msgFile\\n msg = \\\"\\\"\\n fd = open(args.msgFile, \\\"rb\\\")\\n while True:\\n string = fd.readline()\\n if string == \\\"\\\":\\n break\\n msg += string\\n fd.close()\\n\\n #sigFile\\n fd = open(args.sigFile, \\\"r\\\")\\n sig = \\\"\\\"\\n while True:\\n string = fd.readline()\\n if string == \\\"\\\":\\n break\\n sig += string\\n sig = int(sig)\\n fd.close()\\n\\n return (keyTuple, msg, sig)\\n\\ndef hash(message):\\n h = SHA256.new()\\n h.update(message)\\n return h\\n\\ndef verify(h, sig, N, e):\\n result = pow(sig, e, N)\\n #print(\\\"Validating %s\\\\n\\\\n%s\\\" % (result, (int(h.hexdigest(), 16) % N)))\\n if result == (int(h.hexdigest(), 16) % N):\\n return 1\\n else:\\n return 0\\n\\ndef main():\\n args = getFlags()\\n results = openFiles(args)\\n h = hash(results[1])\\n value = verify(h, results[2], results[0][1], results[0][2])\\n if value == 1:\\n print(\\\"True\\\")\\n else:\\n print(\\\"False\\\")\\n\\nif __name__ == \\\"__main__\\\":\\n main()\\n\"\n },\n {\n \"alpha_fraction\": 0.5396214127540588,\n \"alphanum_fraction\": 0.5556625127792358,\n \"avg_line_length\": 23.93600082397461,\n \"blob_id\": \"0d58b9fd3c45c0c8415ee2093e1d7e45c46dbfb7\",\n \"content_id\": \"5b7a7102cf4553c07672a51cc4a03b7fbe85cf7c\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 3117,\n \"license_type\": \"no_license\",\n \"max_line_length\": 91,\n \"num_lines\": 125,\n \"path\": \"/cbc-enc.py\",\n \"repo_name\": \"dsande30/COSC483_PA3\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#CBC - ENC\\n\\nimport binascii\\nimport getopt\\nimport sys\\nimport os\\nfrom Crypto.Random import random\\nfrom Crypto.Cipher import AES\\nimport argparse\\n\\n#Pads the plaintext\\ndef pad(message):\\n if len(message) > 16:\\n if len(message) % 16 != 0:\\n message += \\\"0\\\" * (16 - (len(message) % 16))\\n elif len(message) < 16:\\n message += \\\"0\\\" * (16 - len(message))\\n return message\\n\\n#XOR function\\ndef xor(blocks, IV, key32):\\n message = []\\n cipher = AES.new(key32, AES.MODE_ECB)\\n priorBlock = IV\\n for currentBlock in blocks:\\n ciphertext = cipher.encrypt(str(priorBlock))\\n text = \\\"\\\"\\n text += \\\"\\\".join(chr(ord(a)^ord(b)) for a,b in zip(currentBlock, ciphertext))\\n priorBlock = text\\n message += text\\n return message\\n\\ndef main(argv):\\n keyfile = ''\\n inputfile = ''\\n outputfile = ''\\n ivfile = ''\\n\\n parser = argparse.ArgumentParser()\\n parser.add_argument(\\\"-k\\\", dest = 'keyfile', help=\\\"Enter key file\\\", required = True)\\n parser.add_argument(\\\"-i\\\", dest = 'inputfile', help=\\\"Enter input file\\\", required = True)\\n parser.add_argument(\\\"-o\\\", dest = 'outputfile', help= \\\"Enter ouput file\\\", required=True)\\n args = parser.parse_args()\\n\\n #Opens Files\\n #k = open(args.keyfile, 'rb')\\n i = open(args.inputfile, 'rb')\\n if ivfile != \\\"\\\":\\n v = open(ivfile, 'rb')\\n\\n s = []\\n key = \\\"\\\"\\n plaintext = \\\"\\\"\\n IV = \\\"\\\"\\n\\n #reads in key\\n key = args.keyfile\\n\\n #read in input\\n while True:\\n string = i.readline()\\n if string == \\\"\\\":\\n break\\n plaintext += string\\n\\n i.close()\\n os.remove(args.inputfile)\\n\\n #Reads in from the input file, key file, and optional IV file\\n try:\\n if ivfile != \\\"\\\":\\n byte3 = v.read(1)\\n if ivfile != \\\"\\\":\\n while byte3 != \\\"\\\":\\n IV += byte3\\n byte3 = v.read(1)\\n finally:\\n if ivfile != \\\"\\\":\\n v.close()\\n\\n #Pads the plaintext if needed\\n plaintext = pad(plaintext)\\n\\n blocks = []\\n\\n\\n #Separates the plaintext into blocks of 16 bytes\\n x = 0\\n check = plaintext[:]\\n while len(check) > 0:\\n slicelen = min(len(plaintext), 16)\\n blocks.append(check[0:slicelen])\\n check = check[slicelen:]\\n x += 1\\n\\n #Generates IV if no file specified\\n if ivfile == \\\"\\\":\\n test = 0\\n while test == 0:\\n IV = str(random.getrandbits(64))\\n if len(IV.encode('utf-8')) == 16:\\n test = 1\\n\\n #Gets correct key and Then XORs text\\n #key32 = \\\"\\\".join([ ' ' if x >= len(s) else s[x] for x in range(32)])\\n key32 = key.strip()\\n\\n #Gets rid of any newline chars in the IV and unhexlifies it if\\n #read in from a file\\n IV = IV.rstrip(\\\"\\\\r\\\") #FIXME \\\\n\\n if ivfile != \\\"\\\":\\n IV = binascii.unhexlify(IV)\\n\\n #Calls the XOR function for the ciphertext\\n ciphertext = xor(blocks, IV, key32)\\n\\n #Only the ciphertext appears in the output file\\n o = open(args.outputfile, 'wb')\\n o.write(str(IV))\\n o.write(\\\"\\\\n\\\")\\n o.write(\\\"\\\".join(ciphertext))\\n o.close()\\n\\nif __name__ == \\\"__main__\\\":\\n main(sys.argv[1:])\\n\"\n },\n {\n \"alpha_fraction\": 0.6232368350028992,\n \"alphanum_fraction\": 0.6299183368682861,\n \"avg_line_length\": 32.25925827026367,\n \"blob_id\": \"2140d4b5ed0b32db8fc4485f226fab7e58e3d13e\",\n \"content_id\": \"7e557b49882b6ea64b68846eb976106ad436b187\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 2694,\n \"license_type\": \"no_license\",\n \"max_line_length\": 125,\n \"num_lines\": 81,\n \"path\": \"/lock.py\",\n \"repo_name\": \"dsande30/COSC483_PA3\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import os\\nimport argparse\\nfrom Crypto.Random import random\\nimport subprocess\\n\\ndef getFlags():\\n #parse command line args\\n parser = argparse.ArgumentParser()\\n parser.add_argument(\\\"-d\\\", dest = 'directory', help=\\\"Enter directory to lock\\\", required = True)\\n parser.add_argument(\\\"-p\\\", dest = 'pubKeyFile', help=\\\"Enter action public key file\\\", required = True)\\n parser.add_argument(\\\"-r\\\", dest = 'privKeyFile', help= \\\"Enter action private key file\\\", required=True)\\n parser.add_argument(\\\"-vk\\\", dest = 'valFile', help= \\\"Enter validate pubkey file\\\", required=True)\\n args = parser.parse_args()\\n return args\\n\\ndef verifyUnlocker(args):\\n command = \\\"python2.7 rsa-validate.py -k \\\" + args.valFile + \\\" -m \\\" + args.pubKeyFile + \\\" -s \\\" + args.pubKeyFile + \\\"-casig\\\"\\n #print(\\\"Command: %s\\\" % command)\\n result = subprocess.check_output([command], shell=True)\\n if(result.strip() == \\\"True\\\"):\\n #print(\\\"Verified\\\")\\n return\\n else:\\n sys.exit(\\\"Unverified unlocker\\\")\\n\\ndef randAESKey():\\n val = random.getrandbits(128)\\n val = str(val)\\n val = val[0:16]\\n return int(val)\\n\\ndef rsaEnc(args, key):\\n command = \\\"python2.7 rsa-enc.py -k \\\" + args.pubKeyFile + \\\" -i \\\" + str(key)\\n result = subprocess.check_output([command], shell=True)\\n return result.strip()\\n\\ndef printManifest(encryptedKey):\\n fd = open(\\\"symManifest\\\", \\\"w\\\")\\n fd.write(encryptedKey)\\n fd.close()\\n\\ndef signManifest(lock_priv):\\n command = \\\"python2.7 rsa-sign.py -k \\\" + lock_priv + \\\" -m symManifest -s symManifest-casig\\\"\\n subprocess.call([command], shell=True)\\n\\ndef encryptDir(directory, key):\\n currentdir = os.getcwd()\\n newlist = []\\n for letter in currentdir:\\n newlist.append(letter)\\n for i in range(0, len(newlist)):\\n if newlist[i] == ' ':\\n newlist[i] = \\\"\\\\ \\\"\\n currentdir = ''.join(newlist)\\n\\n\\n for root, dirs, files in os.walk(directory):\\n os.chdir(directory)\\n for file in files:\\n encryptFile(file, key, currentdir)\\n tagFile(file, key, currentdir)\\n\\ndef encryptFile(file, key, currentdir):\\n command = \\\"python2.7 \\\" + currentdir + \\\"/cbc-enc.py -k \\\" + str(key) + \\\" -i \\\" + file + \\\" -o \\\" + file\\n subprocess.call([command], shell=True)\\n\\ndef tagFile(file, key, currentdir):\\n command = \\\"python2.7 \\\" + currentdir + \\\"/cbcmac-tag_2.py -k \\\" + str(key) + \\\" -m \\\" + file + \\\" -t \\\" + file + \\\"-tag\\\"\\n subprocess.call([command], shell=True)\\n\\ndef main():\\n args = getFlags()\\n check = verifyUnlocker(args)\\n key = randAESKey()\\n encryptedKey = rsaEnc(args, key)\\n printManifest(encryptedKey)\\n signManifest(args.privKeyFile)\\n encryptDir(args.directory, key)\\n\\nif __name__ == \\\"__main__\\\":\\n main()\\n\"\n },\n {\n \"alpha_fraction\": 0.5744485259056091,\n \"alphanum_fraction\": 0.5900735259056091,\n \"avg_line_length\": 25.536584854125977,\n \"blob_id\": \"6ab30a3f54c3bfed40d428013eedcf2aeb7fc438\",\n \"content_id\": \"74b10b0aa192b904890c9c06f4c419445511e4a5\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 2176,\n \"license_type\": \"no_license\",\n \"max_line_length\": 91,\n \"num_lines\": 82,\n \"path\": \"/cbcmac-tag_2.py\",\n \"repo_name\": \"dsande30/COSC483_PA3\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import argparse\\nfrom Crypto.Cipher import AES\\n\\ndef getFlags():\\n #parse command line args\\n parser = argparse.ArgumentParser()\\n parser.add_argument(\\\"-k\\\", dest = 'keyFile', help=\\\"Enter key file\\\", required = True)\\n parser.add_argument(\\\"-m\\\", dest = 'msgFile', help=\\\"Enter message file\\\", required = True)\\n parser.add_argument(\\\"-t\\\", dest = 'tagFile', help= \\\"Enter tag file\\\", required=True)\\n args = parser.parse_args()\\n return args\\n\\ndef getInfo(args):\\n #fd = open(args.keyFile)\\n key = args.keyFile\\n #fd.close()\\n\\n fd = open(args.msgFile)\\n msg = \\\"\\\"\\n while True:\\n string = fd.readline()\\n if string == \\\"\\\":\\n break\\n msg += string\\n fd.close()\\n msg = msg.strip()\\n return (key, msg)\\n\\n#Pads the plaintext\\ndef pad(message):\\n if len(message) > 16:\\n if len(message) % 16 != 0:\\n message += \\\"0\\\" * (16 - (len(message) % 16))\\n elif len(message) < 16:\\n message += \\\"0\\\" * (16 - len(message))\\n return message\\n\\n#XOR function\\ndef xor(blocks, key32):\\n message = []\\n cipher = AES.new(key32, AES.MODE_ECB)\\n priorBlock = blocks[0]\\n message = \\\"\\\"\\n for currentBlock in blocks[1:]:\\n ciphertext = cipher.encrypt(str(priorBlock))\\n text = \\\"\\\"\\n text += \\\"\\\".join(chr(ord(a)^ord(b)) for a,b in zip(currentBlock, ciphertext))\\n priorBlock = text\\n message += text\\n return message\\n\\ndef blockify(plaintext):\\n #Separates the plaintext into blocks of 16 bytes\\n x = 0\\n blocks = []\\n length = len(plaintext)\\n while(len(str(length)) < 16):\\n length = \\\"0\\\" + str(length)\\n blocks.append(length)\\n check = plaintext[:]\\n while len(check) > 0:\\n slicelen = min(len(plaintext), 16)\\n blocks.append(check[0:slicelen])\\n check = check[slicelen:]\\n x += 1\\n return blocks\\n\\ndef writeFile(oFile, ciphertext):\\n fd = open(oFile, \\\"wb\\\")\\n fd.write(ciphertext)\\n fd.close()\\n\\ndef main():\\n args = getFlags()\\n results = getInfo(args)\\n paddedmsg = pad(results[1])\\n blocks = blockify(paddedmsg)\\n ciphertext = xor(blocks, results[0])\\n writeFile(args.tagFile, ciphertext)\\n\\nif __name__ == \\\"__main__\\\":\\n main()\\n\"\n },\n {\n \"alpha_fraction\": 0.5597867369651794,\n \"alphanum_fraction\": 0.5738766193389893,\n \"avg_line_length\": 23.542055130004883,\n \"blob_id\": \"34a43830106b3f2aed823511b322f755d530b1bf\",\n \"content_id\": \"4790755e3b19f69f3f127ba967a9eaeb82d90033\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 2626,\n \"license_type\": \"no_license\",\n \"max_line_length\": 91,\n \"num_lines\": 107,\n \"path\": \"/cbcmac-validate.py\",\n \"repo_name\": \"dsande30/COSC483_PA3\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import argparse\\nfrom Crypto.Cipher import AES\\nimport binascii\\nimport difflib\\n\\ndef getFlags():\\n #parse command line args\\n parser = argparse.ArgumentParser()\\n parser.add_argument(\\\"-k\\\", dest = 'keyFile', help=\\\"Enter key file\\\", required = True)\\n parser.add_argument(\\\"-m\\\", dest = 'msgFile', help=\\\"Enter message file\\\", required = True)\\n parser.add_argument(\\\"-t\\\", dest = 'tagFile', help= \\\"Enter tag file\\\", required=True)\\n args = parser.parse_args()\\n return args\\n\\ndef readTag(tagFile):\\n t = open(tagFile, 'rb')\\n tag = \\\"\\\"\\n while True:\\n string = t.readline()\\n if string == \\\"\\\":\\n break\\n tag += string\\n t.close()\\n return tag\\n\\ndef readKey(keyFile):\\n key = open(keyFile, 'rb')\\n validKey = key.readline().strip()\\n key.close()\\n return validKey\\n\\ndef readInput(msgFile):\\n i = open(msgFile, 'r')\\n m = \\\"\\\"\\n while True:\\n string = i.readline()\\n if string == \\\"\\\":\\n break\\n m += string\\n m = m.strip()\\n i.close()\\n return m\\n\\n#Pads the plaintext\\ndef pad(message):\\n if len(message) > 16:\\n if len(message) % 16 != 0:\\n message += \\\"0\\\" * (16 - (len(message) % 16))\\n elif len(message) < 16:\\n message += \\\"0\\\" * (16 - len(message))\\n return message\\n\\n#XOR function\\ndef xor(blocks, key32):\\n message = []\\n cipher = AES.new(key32, AES.MODE_ECB)\\n priorBlock = blocks[0]\\n message = \\\"\\\"\\n for currentBlock in blocks[1:]:\\n ciphertext = cipher.encrypt(str(priorBlock))\\n text = \\\"\\\"\\n text += \\\"\\\".join(chr(ord(a)^ord(b)) for a,b in zip(currentBlock, ciphertext))\\n priorBlock = text\\n message += text\\n return message\\n\\ndef blockify(plaintext):\\n #Separates the plaintext into blocks of 16 bytes\\n x = 0\\n blocks = []\\n length = len(plaintext)\\n while(len(str(length)) < 16):\\n length = \\\"0\\\" + str(length)\\n blocks.append(length)\\n check = plaintext[:]\\n while len(check) > 0:\\n slicelen = min(len(plaintext), 16)\\n blocks.append(check[0:slicelen])\\n check = check[slicelen:]\\n x += 1\\n return blocks\\n\\ndef verify(key, message, tag):\\n message = pad(str(message))\\n blocks = blockify(message)\\n compMsg = xor(blocks, key)\\n if tag == compMsg:\\n return 1\\n else:\\n return 0\\n\\ndef main():\\n args = getFlags()\\n key = readKey(args.keyFile)\\n tag = readTag(args.tagFile)\\n message = readInput(args.msgFile)\\n validity = verify(key, message, tag)\\n if validity == 1:\\n print(\\\"True\\\")\\n return 1\\n else:\\n print(\\\"False\\\")\\n return 0\\n\\n\\nif __name__ == \\\"__main__\\\":\\n main()\\n\"\n },\n {\n \"alpha_fraction\": 0.5954098105430603,\n \"alphanum_fraction\": 0.6019672155380249,\n \"avg_line_length\": 24.41666603088379,\n \"blob_id\": \"12cae38c1253ffab18fa94a8d06081805dd49cc5\",\n \"content_id\": \"a6585b892f684a552c7614a2ac7be8b03924f72f\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1525,\n \"license_type\": \"no_license\",\n \"max_line_length\": 92,\n \"num_lines\": 60,\n \"path\": \"/rsa-sign.py\",\n \"repo_name\": \"dsande30/COSC483_PA3\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import argparse\\nfrom Crypto.Hash import SHA256\\n\\ndef getFlags():\\n #parse command line args\\n parser = argparse.ArgumentParser()\\n parser.add_argument(\\\"-k\\\", dest = 'keyFile', help=\\\"Enter key file\\\", required = True)\\n parser.add_argument(\\\"-m\\\", dest = 'msgFile', help=\\\"Enter message file\\\", required = True)\\n parser.add_argument(\\\"-s\\\", dest = 'sigFile', help= \\\"Enter signature file\\\", required=True)\\n args = parser.parse_args()\\n return args\\n\\ndef readKey(keyFile):\\n key = open(keyFile, 'rb')\\n numBits = key.readline()\\n N = key.readline()\\n d = key.readline()\\n key.close()\\n numBits = numBits.strip()\\n N = N.strip()\\n d = d.strip()\\n return int(numBits), int(N), int(d)\\n\\ndef readInput(inputFile):\\n i = open(inputFile, 'r')\\n m = \\\"\\\"\\n while True:\\n string = i.readline()\\n if string == \\\"\\\":\\n break\\n m += string\\n i.close()\\n return m\\n\\ndef writeOutput(sigFile, signature):\\n s = open(sigFile, 'wb')\\n s.write(str(signature))\\n s.close()\\n\\ndef doHash(message):\\n h = SHA256.new()\\n h.update(message)\\n #print(\\\"Hash: %s\\\" % h.hexdigest())\\n return h\\n\\ndef sign(h, N, d):\\n signature = pow(int(h.hexdigest(), 16), d, N)\\n return signature\\n\\ndef main():\\n args = getFlags()\\n contents = readKey(args.keyFile)\\n message = readInput(args.msgFile)\\n h = doHash(message)\\n signature = sign(h, contents[1], contents[2])\\n #print(\\\"Writing: \\\\n%s\\\" % signature)\\n writeOutput(args.sigFile, signature)\\n\\nif __name__ == \\\"__main__\\\":\\n main()\\n\"\n },\n {\n \"alpha_fraction\": 0.567480742931366,\n \"alphanum_fraction\": 0.5700514316558838,\n \"avg_line_length\": 20.550724029541016,\n \"blob_id\": \"e8f962b22537a12e4e05b6523b3c77732aae39f1\",\n \"content_id\": \"56eb1a01d46169b2af0a9f06fa3e2bf51592686a\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1556,\n \"license_type\": \"no_license\",\n \"max_line_length\": 91,\n \"num_lines\": 69,\n \"path\": \"/rsa-dec.py\",\n \"repo_name\": \"dsande30/COSC483_PA3\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#RSA Decrypt\\r\\nimport sys\\r\\nimport argparse\\r\\nfrom Crypto.Util import number\\r\\nimport fractions\\r\\n\\r\\ndef getFlags():\\r\\n #parse command line args\\r\\n parser = argparse.ArgumentParser()\\r\\n parser.add_argument(\\\"-k\\\", dest = 'keyFile', help=\\\"Enter Key file\\\", required = True)\\r\\n parser.add_argument(\\\"-i\\\", dest = 'inputFile', help=\\\"Enter input file\\\", required = True)\\r\\n args = parser.parse_args()\\r\\n\\r\\n return args\\r\\n\\r\\n#Reads in key file\\r\\ndef readKey(keyFile):\\r\\n key = open(keyFile, 'rb')\\r\\n numBits = key.readline()\\r\\n numBits = numBits.strip()\\r\\n N = key.readline()\\r\\n N = N.strip()\\r\\n d = key.readline()\\r\\n d = d.strip()\\r\\n key.close()\\r\\n return numBits, N, d\\r\\n\\r\\n#Reads in Input File\\r\\ndef readInput(inputFile):\\r\\n inp = open(inputFile, 'rb')\\r\\n c = inp.readline()\\r\\n c = c.strip()\\r\\n return c\\r\\n\\r\\n#Decrypts the file\\r\\ndef Dec(key, c):\\r\\n c = int(c)\\r\\n d = int(key[2])\\r\\n N = int(key[1])\\r\\n #print \\\"C: %d\\\" % c\\r\\n #print(\\\"N: %d\\\" % N)\\r\\n #print(\\\"d: %d\\\" % d)\\r\\n m = pow(c, d, N)\\r\\n return m\\r\\n\\r\\n#Writes the output to the designated output file\\r\\ndef writeOutput(outputFile, m):\\r\\n out = open(outputFile, 'wb')\\r\\n out.write(\\\"%d\\\" %m)\\r\\n out.close()\\r\\n\\r\\n#Removes the padding to reveal the original message\\r\\ndef unpad(m):\\r\\n #print m\\r\\n r, M = m.split(\\\"0\\\", 1)\\r\\n M = M.strip()\\r\\n return M\\r\\n\\r\\ndef main():\\r\\n args = getFlags()\\r\\n key = readKey(args.keyFile)\\r\\n message = args.inputFile\\r\\n m = Dec(key, message)\\r\\n m = unpad(str(m))\\r\\n print(str(m))\\r\\n return\\r\\n\\r\\nif __name__ == \\\"__main__\\\":\\r\\n\\tmain()\\r\\n\"\n },\n {\n \"alpha_fraction\": 0.5854460000991821,\n \"alphanum_fraction\": 0.5962441563606262,\n \"avg_line_length\": 23.482759475708008,\n \"blob_id\": \"e8633f16843656ad8c8d0011817d0854a20e7c09\",\n \"content_id\": \"d817185c57e28bffb6b36dee19e42fc24f3d5b47\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 2130,\n \"license_type\": \"no_license\",\n \"max_line_length\": 91,\n \"num_lines\": 87,\n \"path\": \"/cbc-dec.py\",\n \"repo_name\": \"dsande30/COSC483_PA3\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"##CBC - DEC\\n\\nimport binascii\\nimport getopt\\nimport sys\\nimport os\\nimport argparse\\nfrom Crypto.Random import random\\nfrom Crypto.Cipher import AES\\n\\n#XOR function\\ndef xor(blocks, IV, key32):\\n message = []\\n cipher = AES.new(key32, AES.MODE_ECB)\\n priorBlock = IV\\n for currentBlock in blocks:\\n ciphertext = cipher.encrypt(str(priorBlock))\\n text = \\\"\\\"\\n text += \\\"\\\".join(chr(ord(a)^ord(b)) for a,b in zip(currentBlock, ciphertext))\\n priorBlock = currentBlock\\n message += text\\n return message\\n\\ndef main(argv):\\n keyfile = ''\\n inputfile = ''\\n outputfile = ''\\n ivfile = ''\\n\\n #Reads flags from command line\\n parser = argparse.ArgumentParser()\\n parser.add_argument(\\\"-k\\\", dest = 'keyfile', help=\\\"Enter key file\\\", required = True)\\n parser.add_argument(\\\"-i\\\", dest = 'inputfile', help=\\\"Enter input file\\\", required = True)\\n parser.add_argument(\\\"-o\\\", dest = 'outputfile', help= \\\"Enter ouput file\\\", required=True)\\n args = parser.parse_args()\\n\\n #Opens Files\\n i = open(args.inputfile, 'rb')\\n\\n\\n s = []\\n key = \\\"\\\"\\n ciphertext = \\\"\\\"\\n\\n #Takes the IV from the Encryption Part\\n key = args.keyfile\\n IV = i.readline()\\n\\n while True:\\n string = i.readline()\\n if string == \\\"\\\":\\n break\\n ciphertext += str(string)\\n\\n i.close()\\n os.remove(args.inputfile)\\n\\n\\n blocks = []\\n\\n #Splits up the ciphertext into blocks of 16 bytes\\n x = 0\\n check = ciphertext[:]\\n while len(check) > 0:\\n slicelen = min(len(ciphertext), 16)\\n blocks.append(check[0:slicelen])\\n check = check[slicelen:]\\n x += 1\\n\\n #Gets correct key\\n #key32 = \\\"\\\".join([ ' ' if x >= len(s) else s[x] for x in range(32)])\\n key32 = key\\n #print(\\\"Key %s\\\" % key32)\\n\\n #Strips any newline characters from the IV so that it is the right size\\n IV = IV.rstrip(\\\"\\\\n\\\\r\\\")\\n #print(\\\"IV %s\\\" % IV)\\n\\n #Calls the XOR function to get the original plaintext\\n plaintext = xor(blocks, IV, key32)\\n\\n o = open(args.outputfile, 'wb')\\n o.write(repr(\\\"\\\".join(plaintext)))\\n o.close()\\n\\nif __name__ == \\\"__main__\\\":\\n main(sys.argv[1:])\\n\"\n }\n]"},"num_files":{"kind":"number","value":11,"string":"11"}}},{"rowIdx":2067,"cells":{"repo_name":{"kind":"string","value":"YoonKiBum/programmers"},"repo_url":{"kind":"string","value":"https://github.com/YoonKiBum/programmers"},"snapshot_id":{"kind":"string","value":"edba69b9fa59ef879cfdab4e255dc51f1afddb85"},"revision_id":{"kind":"string","value":"f46e8387180d4ba705278d859b75a67a7978cf9e"},"directory_id":{"kind":"string","value":"3d71e8dcae76711526a4b76940b0a68b3700c0da"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"string","value":"2023-03-17T15:07:30.284287"},"revision_date":{"kind":"string","value":"2021-02-23T10:44:43"},"committer_date":{"kind":"string","value":"2021-02-23T10:44:43"},"github_id":{"kind":"number","value":312974339,"string":"312,974,339"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.4661017060279846,"alphanum_fraction":0.5885122418403625,"avg_line_length":33.25806427001953,"blob_id":"389a65eecf0760c996a72a33922d85c63e2666d0","content_id":"6cf21376f20d0a774fb99ee560530c762543f2fe","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":1510,"license_type":"no_license","max_line_length":48,"num_lines":31,"path":"/README.md","repo_name":"YoonKiBum/programmers","src_encoding":"UTF-8","text":"# programmers\n
\n\n### 코딩테스트 연습 (Python 소스코드)\n\n### Level 1\n * 크레인 인형뽑기 게임: ([Python 코드](/Level1/64061.py))\n * 두 개 뽑아서 더하기: ([Python 코드](/Level1/68644.py))\n * 완주하지 못한 선수: ([Python 코드](/Level1/42576.py))\n * 모의고사: ([Python 코드](/Level1/42840.py))\n * k번째 수: ([Python 코드](/Level1/42748.py))\n * 체육복: ([Python 코드](/Level1/42862.py))\n * 2016년: ([Python 코드](/Level1/12901.py))\n * 3진법 뒤집기: ([Python 코드](/Level1/68935.py))\n * 가운데 글자 가져오기: ([Python 코드](/Level1/12903.py))\n * 같은 숫자는 싫어: ([Python 코드](/Level1/12906.py))\n \n### Level 2\n * 다리를 지나는 트럭: ([Python 코드](/Level2/42583.py))\n * 주식가격: ([Python 코드](/Level2/42584.py))\n * 스킬트리: ([Python 코드](/Level2/49993.py))\n### 카카오공채\n * 자물쇠와 열쇠: ([Python 코드](/카카오공채/60059.py))\n * 기둥과 보 설치: ([Python 코드](/카카오공채/60061.py))\n * 문자열 압축: ([Python 코드](/카카오공채/60057.py))\n * 괄호 변환: ([Python 코드](/카카오공채/60058.py))\n * 블록 이동하기: ([Python 코드](/카카오공채/60063.py))\n * 실패율: ([Python 코드](/카카오공채/42889.py))\n * 가사 검색: ([Python 코드](/카카오공채/60060.py))\n * 무지의 먹방 라이브: ([Python 코드](/카카오공채/42891.py))\n * 외벽 점검: ([Python 코드](/카카오공채/60062.py))\n"},{"alpha_fraction":0.44736841320991516,"alphanum_fraction":0.4583333432674408,"avg_line_length":25.823530197143555,"blob_id":"10174d7e3620bd33fcf72f52c1c178c178582adc","content_id":"500b40da1e65650180a3280566130fcd45ed1572","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":456,"license_type":"no_license","max_line_length":46,"num_lines":17,"path":"/Level2/49993.py","repo_name":"YoonKiBum/programmers","src_encoding":"UTF-8","text":"import copy\ndef solution(skill, skill_trees):\n count = 0\n check = [0] * len(skill)\n for word in skill_trees:\n copyskill = list(copy.deepcopy(skill))\n check = True\n for i in word:\n if i in copyskill:\n res = copyskill[0]\n if res != i:\n check = False\n break\n copyskill.pop(0)\n if check: \n count += 1\n return count\n"},{"alpha_fraction":0.6192052960395813,"alphanum_fraction":0.6291390657424927,"avg_line_length":24.16666603088379,"blob_id":"ed2837d7ad12ce569757025fbb8e849d5d9914bd","content_id":"db5bd041bef13d865896451ff73483fc84a3e5a5","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":302,"license_type":"no_license","max_line_length":48,"num_lines":12,"path":"/Level1/68644.py","repo_name":"YoonKiBum/programmers","src_encoding":"UTF-8","text":"from itertools import combinations\n\ndef solution(numbers):\n answer = []\n for combination in combinations(numbers, 2):\n x = int(combination[0])\n y = int(combination[1])\n answer.append(x+y)\n answer = set(answer)\n answer = list(answer)\n answer.sort()\n return answer\n"},{"alpha_fraction":0.43499043583869934,"alphanum_fraction":0.45984703302383423,"avg_line_length":33.86666488647461,"blob_id":"01ac47fc0ca59d5d93853ebc9ae7624507261619","content_id":"bef4a9ab3a4b8c108198f2104bda22ecab3706c6","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1120,"license_type":"no_license","max_line_length":119,"num_lines":30,"path":"/카카오공채/60061.py","repo_name":"YoonKiBum/programmers","src_encoding":"UTF-8","text":"# https://programmers.co.kr/learn/courses/30/lessons/60061\ndef check(answer):\n for i in range(len(answer)):\n x, y, a = answer[i]\n if a == 0: # 기둥 인 경우\n if y == 0 or [x-1, y, 1] in answer or [x, y, 1] in answer or [x, y-1, 0] in answer:\n continue\n else:\n return False\n elif a == 1: # 보 인 경우\n if [x, y-1, 0] in answer or [x+1, y-1, 0] in answer or ([x-1, y, 1] in answer and [x+1, y , 1] in answer): \n continue\n else:\n return False\n return True\n\ndef solution(n, build_frame):\n answer = []\n for i in range(len(build_frame)):\n x, y, a, b = build_frame[i]\n if b == 1: # 설치인 경우\n answer.append([x, y, a])\n if check(answer) == False: # 조건에서 어긋난 경우\n answer.pop()\n elif b == 0: # 삭제인 경우\n answer.remove([x, y, a])\n if check(answer) == False: # 조건에서 어긋난 경우\n answer.append([x, y, a])\n \n return sorted(answer)\n"},{"alpha_fraction":0.446153849363327,"alphanum_fraction":0.4703296720981598,"avg_line_length":31.5,"blob_id":"a326dbf5a7459cc4a978a862155a4376673344ff","content_id":"121567e46450f25d6f3092ba7882f867f7c7186c","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":455,"license_type":"no_license","max_line_length":79,"num_lines":14,"path":"/Level1/64061.py","repo_name":"YoonKiBum/programmers","src_encoding":"UTF-8","text":"def solution(board, moves):\n answer = [-1]\n count = 0\n for i in range(len(moves)):\n for j in range(len(board)):\n if board[j][moves[i]-1] != 0:\n answer.append(board[j][moves[i]-1])\n board[j][moves[i]-1] = 0\n break\n if len(answer) >= 3 and answer[len(answer)-1] == answer[len(answer)-2]:\n answer.pop()\n answer.pop()\n count += 2\n return count\n"},{"alpha_fraction":0.4358353614807129,"alphanum_fraction":0.4479418992996216,"avg_line_length":23.294116973876953,"blob_id":"a11d325699728c74421ad4ec97f2ad18a42dec95","content_id":"43d9f5b991d938615cfa8d0193fbdeba5caecb88","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":413,"license_type":"no_license","max_line_length":36,"num_lines":17,"path":"/카카오공채/42889.py","repo_name":"YoonKiBum/programmers","src_encoding":"UTF-8","text":"def solution(N, stages):\n total = len(stages)\n arr = []\n ans = []\n for i in range(1, N + 1):\n temp = stages.count(i)\n if total > 0:\n fail = temp / total\n total -= temp\n arr.append((fail, -(i)))\n else:\n arr.append((0, -(i)))\n arr.sort(reverse = True)\n \n for i in range(len(arr)):\n ans.append(-(arr[i][1]))\n return ans\n"},{"alpha_fraction":0.3840177655220032,"alphanum_fraction":0.4694783687591553,"avg_line_length":30.034482955932617,"blob_id":"80add779e8e57fbfb7a79531157d111e840f7207","content_id":"df1539b6db799fc1ec199d8ab3b7ca7c67703984","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":901,"license_type":"no_license","max_line_length":58,"num_lines":29,"path":"/Level1/42840.py","repo_name":"YoonKiBum/programmers","src_encoding":"UTF-8","text":"# https://programmers.co.kr/learn/courses/30/lessons/42840\ndef solution(answers):\n answer = []\n people_1 = [1, 2, 3, 4, 5] * 2000\n people_2 = [2, 1, 2, 3, 2, 4, 2, 5] * 2000\n people_3 = [3, 3, 1, 1, 2, 2, 4, 4, 5, 5] * 1000\n num_of_1 = 0; num_of_2 = 0; num_of_3 = 0\n \n for i in range(len(answers)):\n if answers[i] == people_1[i]:\n num_of_1 += 1\n if answers[i] == people_2[i]:\n num_of_2 += 1\n if answers[i] == people_3[i]:\n num_of_3 += 1\n \n temp = [(num_of_1,1), (num_of_2,2), (num_of_3,3)] \n temp.sort(reverse = True)\n temp.append((-1, -1))\n \n for i in range(3):\n if temp[i][0] != temp[i+1][0]:\n answer.append(temp[i][1])\n answer.sort()\n return answer\n elif temp[i][0] == temp[i+1][0]:\n answer.append(temp[i][1])\n answer.sort()\n return answer\n\n"},{"alpha_fraction":0.5360000133514404,"alphanum_fraction":0.5440000295639038,"avg_line_length":24,"blob_id":"4d5080e45ec7385d55b86e0dc3f4b357cd04b522","content_id":"9c485825aebefb31e69640a0bc5c232726ece56e","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":250,"license_type":"no_license","max_line_length":39,"num_lines":10,"path":"/Level1/42748.py","repo_name":"YoonKiBum/programmers","src_encoding":"UTF-8","text":"def solution(array, commands):\n n = len(commands)\n answer = []\n for i in range(n):\n start, end, count = commands[i]\n temp = array[start-1:end]\n temp.sort()\n answer.append(temp[count-1])\n \n return answer\n"},{"alpha_fraction":0.35738831758499146,"alphanum_fraction":0.4536082446575165,"avg_line_length":23.25,"blob_id":"a9cf860a174d6f44a9e897edaa2526a7c04f7de6","content_id":"b49850c5d0c5a8efbea09d56c478e137ea6e5542","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":291,"license_type":"no_license","max_line_length":60,"num_lines":12,"path":"/Level1/12901.py","repo_name":"YoonKiBum/programmers","src_encoding":"UTF-8","text":"def solution(a, b):\n month = [31, 29, 31, 30, 31, 30, 31, 31, 30, 31, 30, 31]\n ans = ['FRI','SAT','SUN','MON','TUE','WED','THU']\n index = a - 1 \n day = b - 1\n \n sum = 0\n for i in range(index):\n sum += month[i]\n sum += day\n sum = sum % 7\n return ans[sum]\n"},{"alpha_fraction":0.43091654777526855,"alphanum_fraction":0.45690834522247314,"avg_line_length":31.488889694213867,"blob_id":"847ca7e2654788621c1a2914e563351241d300c3","content_id":"da68286cc13e68f17555905be5135deb46ce0bc8","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1482,"license_type":"no_license","max_line_length":67,"num_lines":45,"path":"/카카오공채/60063.py","repo_name":"YoonKiBum/programmers","src_encoding":"UTF-8","text":"from collections import deque\n\ndef can_move(pos, graph):\n next_pos = []\n pos = list(pos)\n lx, ly, rx, ry = pos[0][0], pos[0][1], pos[1][0], pos[1][1]\n dx = [-1, 1, 0, 0]\n dy = [0, 0, -1, 1]\n for i in range(4):\n nlx, nly, nrx, nry = lx+dx[i], ly+dy[i], rx+dx[i], ry+dy[i]\n if graph[nlx][nly] == 0 and graph[nrx][nry] == 0:\n next_pos.append({(nlx, nly), (nrx, nry)})\n if lx == rx: # 가로인 경우\n for i in [-1, 1]:\n if graph[lx+i][ly] == 0 and graph[rx+i][ry] == 0:\n next_pos.append({(lx,ly), (lx+i, ly)})\n next_pos.append({(rx, ry), (rx+i, ry)})\n elif ly == ry: # 세로인 경우\n for i in [-1, 1]:\n if graph[lx][ly+i] == 0 and graph[rx][ry+i] == 0:\n next_pos.append({(lx, ly), (lx, ly+i)})\n next_pos.append({(rx, ry), (rx, ry+i)})\n return next_pos\n\ndef solution(board):\n n = len(board) + 2\n m = len(board)\n graph = [[1]*n for _ in range(n)]\n for i in range(m):\n for j in range(m):\n graph[i+1][j+1] = board[i][j]\n q = deque()\n visited = []\n pos = {(1, 1), (1, 2)}\n q.append((pos, 0))\n visited.append(pos)\n while q:\n pos, cost = q.popleft()\n if (m, m) in pos:\n return cost\n for next_pos in can_move(pos, graph):\n if next_pos not in visited:\n q.append((next_pos, cost+1))\n visited.append(next_pos)\n return 0\n"},{"alpha_fraction":0.49077489972114563,"alphanum_fraction":0.5129151344299316,"avg_line_length":26.100000381469727,"blob_id":"8b577448f1d6521cde1cab13d53b910cc7f1f024","content_id":"57423838cee8e0ab8338166bc1ae53a64992141c","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":542,"license_type":"no_license","max_line_length":39,"num_lines":20,"path":"/Level1/42862.py","repo_name":"YoonKiBum/programmers","src_encoding":"UTF-8","text":"def solution(n, lost, reserve):\n lost.sort()\n reserve.sort()\n count = 0\n lost = set(lost)\n reserve = set(reserve)\n temp1 = lost - reserve\n temp2 = reserve - lost\n lost = list(temp1)\n reserve = list(temp2)\n for i in range(len(lost)):\n if len(reserve) <= 0:\n break\n if lost[i] - 1 in reserve:\n reserve.remove(lost[i]-1)\n count += 1\n elif lost[i] + 1 in reserve:\n reserve.remove(lost[i] + 1)\n count += 1\n return n - (len(lost) - count)\n"},{"alpha_fraction":0.3531745970249176,"alphanum_fraction":0.3769841194152832,"avg_line_length":18.384614944458008,"blob_id":"b6647bf18555789bbb087f31d0dcf2a584d857fd","content_id":"bac1a4b438b884c1326c8146b1b3d8139387d74f","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":252,"license_type":"no_license","max_line_length":47,"num_lines":13,"path":"/Level1/68935.py","repo_name":"YoonKiBum/programmers","src_encoding":"UTF-8","text":"def solution(n):\n arr = []\n while True:\n if n == 0:\n break\n i = n % 3\n arr.append(i)\n n = n // 3\n \n sum = 0\n for i in range(len(arr)):\n sum += (3 ** i) * arr[len(arr) - i - 1]\n return sum\n"}],"string":"[\n {\n \"alpha_fraction\": 0.4661017060279846,\n \"alphanum_fraction\": 0.5885122418403625,\n \"avg_line_length\": 33.25806427001953,\n \"blob_id\": \"389a65eecf0760c996a72a33922d85c63e2666d0\",\n \"content_id\": \"6cf21376f20d0a774fb99ee560530c762543f2fe\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 1510,\n \"license_type\": \"no_license\",\n \"max_line_length\": 48,\n \"num_lines\": 31,\n \"path\": \"/README.md\",\n \"repo_name\": \"YoonKiBum/programmers\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# programmers\\n
\\n\\n### 코딩테스트 연습 (Python 소스코드)\\n\\n### Level 1\\n * 크레인 인형뽑기 게임: ([Python 코드](/Level1/64061.py))\\n * 두 개 뽑아서 더하기: ([Python 코드](/Level1/68644.py))\\n * 완주하지 못한 선수: ([Python 코드](/Level1/42576.py))\\n * 모의고사: ([Python 코드](/Level1/42840.py))\\n * k번째 수: ([Python 코드](/Level1/42748.py))\\n * 체육복: ([Python 코드](/Level1/42862.py))\\n * 2016년: ([Python 코드](/Level1/12901.py))\\n * 3진법 뒤집기: ([Python 코드](/Level1/68935.py))\\n * 가운데 글자 가져오기: ([Python 코드](/Level1/12903.py))\\n * 같은 숫자는 싫어: ([Python 코드](/Level1/12906.py))\\n \\n### Level 2\\n * 다리를 지나는 트럭: ([Python 코드](/Level2/42583.py))\\n * 주식가격: ([Python 코드](/Level2/42584.py))\\n * 스킬트리: ([Python 코드](/Level2/49993.py))\\n### 카카오공채\\n * 자물쇠와 열쇠: ([Python 코드](/카카오공채/60059.py))\\n * 기둥과 보 설치: ([Python 코드](/카카오공채/60061.py))\\n * 문자열 압축: ([Python 코드](/카카오공채/60057.py))\\n * 괄호 변환: ([Python 코드](/카카오공채/60058.py))\\n * 블록 이동하기: ([Python 코드](/카카오공채/60063.py))\\n * 실패율: ([Python 코드](/카카오공채/42889.py))\\n * 가사 검색: ([Python 코드](/카카오공채/60060.py))\\n * 무지의 먹방 라이브: ([Python 코드](/카카오공채/42891.py))\\n * 외벽 점검: ([Python 코드](/카카오공채/60062.py))\\n\"\n },\n {\n \"alpha_fraction\": 0.44736841320991516,\n \"alphanum_fraction\": 0.4583333432674408,\n \"avg_line_length\": 25.823530197143555,\n \"blob_id\": \"10174d7e3620bd33fcf72f52c1c178c178582adc\",\n \"content_id\": \"500b40da1e65650180a3280566130fcd45ed1572\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 456,\n \"license_type\": \"no_license\",\n \"max_line_length\": 46,\n \"num_lines\": 17,\n \"path\": \"/Level2/49993.py\",\n \"repo_name\": \"YoonKiBum/programmers\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import copy\\ndef solution(skill, skill_trees):\\n count = 0\\n check = [0] * len(skill)\\n for word in skill_trees:\\n copyskill = list(copy.deepcopy(skill))\\n check = True\\n for i in word:\\n if i in copyskill:\\n res = copyskill[0]\\n if res != i:\\n check = False\\n break\\n copyskill.pop(0)\\n if check: \\n count += 1\\n return count\\n\"\n },\n {\n \"alpha_fraction\": 0.6192052960395813,\n \"alphanum_fraction\": 0.6291390657424927,\n \"avg_line_length\": 24.16666603088379,\n \"blob_id\": \"ed2837d7ad12ce569757025fbb8e849d5d9914bd\",\n \"content_id\": \"db5bd041bef13d865896451ff73483fc84a3e5a5\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 302,\n \"license_type\": \"no_license\",\n \"max_line_length\": 48,\n \"num_lines\": 12,\n \"path\": \"/Level1/68644.py\",\n \"repo_name\": \"YoonKiBum/programmers\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from itertools import combinations\\n\\ndef solution(numbers):\\n answer = []\\n for combination in combinations(numbers, 2):\\n x = int(combination[0])\\n y = int(combination[1])\\n answer.append(x+y)\\n answer = set(answer)\\n answer = list(answer)\\n answer.sort()\\n return answer\\n\"\n },\n {\n \"alpha_fraction\": 0.43499043583869934,\n \"alphanum_fraction\": 0.45984703302383423,\n \"avg_line_length\": 33.86666488647461,\n \"blob_id\": \"01ac47fc0ca59d5d93853ebc9ae7624507261619\",\n \"content_id\": \"bef4a9ab3a4b8c108198f2104bda22ecab3706c6\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1120,\n \"license_type\": \"no_license\",\n \"max_line_length\": 119,\n \"num_lines\": 30,\n \"path\": \"/카카오공채/60061.py\",\n \"repo_name\": \"YoonKiBum/programmers\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# https://programmers.co.kr/learn/courses/30/lessons/60061\\ndef check(answer):\\n for i in range(len(answer)):\\n x, y, a = answer[i]\\n if a == 0: # 기둥 인 경우\\n if y == 0 or [x-1, y, 1] in answer or [x, y, 1] in answer or [x, y-1, 0] in answer:\\n continue\\n else:\\n return False\\n elif a == 1: # 보 인 경우\\n if [x, y-1, 0] in answer or [x+1, y-1, 0] in answer or ([x-1, y, 1] in answer and [x+1, y , 1] in answer): \\n continue\\n else:\\n return False\\n return True\\n\\ndef solution(n, build_frame):\\n answer = []\\n for i in range(len(build_frame)):\\n x, y, a, b = build_frame[i]\\n if b == 1: # 설치인 경우\\n answer.append([x, y, a])\\n if check(answer) == False: # 조건에서 어긋난 경우\\n answer.pop()\\n elif b == 0: # 삭제인 경우\\n answer.remove([x, y, a])\\n if check(answer) == False: # 조건에서 어긋난 경우\\n answer.append([x, y, a])\\n \\n return sorted(answer)\\n\"\n },\n {\n \"alpha_fraction\": 0.446153849363327,\n \"alphanum_fraction\": 0.4703296720981598,\n \"avg_line_length\": 31.5,\n \"blob_id\": \"a326dbf5a7459cc4a978a862155a4376673344ff\",\n \"content_id\": \"121567e46450f25d6f3092ba7882f867f7c7186c\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 455,\n \"license_type\": \"no_license\",\n \"max_line_length\": 79,\n \"num_lines\": 14,\n \"path\": \"/Level1/64061.py\",\n \"repo_name\": \"YoonKiBum/programmers\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"def solution(board, moves):\\n answer = [-1]\\n count = 0\\n for i in range(len(moves)):\\n for j in range(len(board)):\\n if board[j][moves[i]-1] != 0:\\n answer.append(board[j][moves[i]-1])\\n board[j][moves[i]-1] = 0\\n break\\n if len(answer) >= 3 and answer[len(answer)-1] == answer[len(answer)-2]:\\n answer.pop()\\n answer.pop()\\n count += 2\\n return count\\n\"\n },\n {\n \"alpha_fraction\": 0.4358353614807129,\n \"alphanum_fraction\": 0.4479418992996216,\n \"avg_line_length\": 23.294116973876953,\n \"blob_id\": \"a11d325699728c74421ad4ec97f2ad18a42dec95\",\n \"content_id\": \"43d9f5b991d938615cfa8d0193fbdeba5caecb88\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 413,\n \"license_type\": \"no_license\",\n \"max_line_length\": 36,\n \"num_lines\": 17,\n \"path\": \"/카카오공채/42889.py\",\n \"repo_name\": \"YoonKiBum/programmers\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"def solution(N, stages):\\n total = len(stages)\\n arr = []\\n ans = []\\n for i in range(1, N + 1):\\n temp = stages.count(i)\\n if total > 0:\\n fail = temp / total\\n total -= temp\\n arr.append((fail, -(i)))\\n else:\\n arr.append((0, -(i)))\\n arr.sort(reverse = True)\\n \\n for i in range(len(arr)):\\n ans.append(-(arr[i][1]))\\n return ans\\n\"\n },\n {\n \"alpha_fraction\": 0.3840177655220032,\n \"alphanum_fraction\": 0.4694783687591553,\n \"avg_line_length\": 30.034482955932617,\n \"blob_id\": \"80add779e8e57fbfb7a79531157d111e840f7207\",\n \"content_id\": \"df1539b6db799fc1ec199d8ab3b7ca7c67703984\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 901,\n \"license_type\": \"no_license\",\n \"max_line_length\": 58,\n \"num_lines\": 29,\n \"path\": \"/Level1/42840.py\",\n \"repo_name\": \"YoonKiBum/programmers\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# https://programmers.co.kr/learn/courses/30/lessons/42840\\ndef solution(answers):\\n answer = []\\n people_1 = [1, 2, 3, 4, 5] * 2000\\n people_2 = [2, 1, 2, 3, 2, 4, 2, 5] * 2000\\n people_3 = [3, 3, 1, 1, 2, 2, 4, 4, 5, 5] * 1000\\n num_of_1 = 0; num_of_2 = 0; num_of_3 = 0\\n \\n for i in range(len(answers)):\\n if answers[i] == people_1[i]:\\n num_of_1 += 1\\n if answers[i] == people_2[i]:\\n num_of_2 += 1\\n if answers[i] == people_3[i]:\\n num_of_3 += 1\\n \\n temp = [(num_of_1,1), (num_of_2,2), (num_of_3,3)] \\n temp.sort(reverse = True)\\n temp.append((-1, -1))\\n \\n for i in range(3):\\n if temp[i][0] != temp[i+1][0]:\\n answer.append(temp[i][1])\\n answer.sort()\\n return answer\\n elif temp[i][0] == temp[i+1][0]:\\n answer.append(temp[i][1])\\n answer.sort()\\n return answer\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.5360000133514404,\n \"alphanum_fraction\": 0.5440000295639038,\n \"avg_line_length\": 24,\n \"blob_id\": \"4d5080e45ec7385d55b86e0dc3f4b357cd04b522\",\n \"content_id\": \"9c485825aebefb31e69640a0bc5c232726ece56e\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 250,\n \"license_type\": \"no_license\",\n \"max_line_length\": 39,\n \"num_lines\": 10,\n \"path\": \"/Level1/42748.py\",\n \"repo_name\": \"YoonKiBum/programmers\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"def solution(array, commands):\\n n = len(commands)\\n answer = []\\n for i in range(n):\\n start, end, count = commands[i]\\n temp = array[start-1:end]\\n temp.sort()\\n answer.append(temp[count-1])\\n \\n return answer\\n\"\n },\n {\n \"alpha_fraction\": 0.35738831758499146,\n \"alphanum_fraction\": 0.4536082446575165,\n \"avg_line_length\": 23.25,\n \"blob_id\": \"a9cf860a174d6f44a9e897edaa2526a7c04f7de6\",\n \"content_id\": \"b49850c5d0c5a8efbea09d56c478e137ea6e5542\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 291,\n \"license_type\": \"no_license\",\n \"max_line_length\": 60,\n \"num_lines\": 12,\n \"path\": \"/Level1/12901.py\",\n \"repo_name\": \"YoonKiBum/programmers\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"def solution(a, b):\\n month = [31, 29, 31, 30, 31, 30, 31, 31, 30, 31, 30, 31]\\n ans = ['FRI','SAT','SUN','MON','TUE','WED','THU']\\n index = a - 1 \\n day = b - 1\\n \\n sum = 0\\n for i in range(index):\\n sum += month[i]\\n sum += day\\n sum = sum % 7\\n return ans[sum]\\n\"\n },\n {\n \"alpha_fraction\": 0.43091654777526855,\n \"alphanum_fraction\": 0.45690834522247314,\n \"avg_line_length\": 31.488889694213867,\n \"blob_id\": \"847ca7e2654788621c1a2914e563351241d300c3\",\n \"content_id\": \"da68286cc13e68f17555905be5135deb46ce0bc8\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1482,\n \"license_type\": \"no_license\",\n \"max_line_length\": 67,\n \"num_lines\": 45,\n \"path\": \"/카카오공채/60063.py\",\n \"repo_name\": \"YoonKiBum/programmers\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from collections import deque\\n\\ndef can_move(pos, graph):\\n next_pos = []\\n pos = list(pos)\\n lx, ly, rx, ry = pos[0][0], pos[0][1], pos[1][0], pos[1][1]\\n dx = [-1, 1, 0, 0]\\n dy = [0, 0, -1, 1]\\n for i in range(4):\\n nlx, nly, nrx, nry = lx+dx[i], ly+dy[i], rx+dx[i], ry+dy[i]\\n if graph[nlx][nly] == 0 and graph[nrx][nry] == 0:\\n next_pos.append({(nlx, nly), (nrx, nry)})\\n if lx == rx: # 가로인 경우\\n for i in [-1, 1]:\\n if graph[lx+i][ly] == 0 and graph[rx+i][ry] == 0:\\n next_pos.append({(lx,ly), (lx+i, ly)})\\n next_pos.append({(rx, ry), (rx+i, ry)})\\n elif ly == ry: # 세로인 경우\\n for i in [-1, 1]:\\n if graph[lx][ly+i] == 0 and graph[rx][ry+i] == 0:\\n next_pos.append({(lx, ly), (lx, ly+i)})\\n next_pos.append({(rx, ry), (rx, ry+i)})\\n return next_pos\\n\\ndef solution(board):\\n n = len(board) + 2\\n m = len(board)\\n graph = [[1]*n for _ in range(n)]\\n for i in range(m):\\n for j in range(m):\\n graph[i+1][j+1] = board[i][j]\\n q = deque()\\n visited = []\\n pos = {(1, 1), (1, 2)}\\n q.append((pos, 0))\\n visited.append(pos)\\n while q:\\n pos, cost = q.popleft()\\n if (m, m) in pos:\\n return cost\\n for next_pos in can_move(pos, graph):\\n if next_pos not in visited:\\n q.append((next_pos, cost+1))\\n visited.append(next_pos)\\n return 0\\n\"\n },\n {\n \"alpha_fraction\": 0.49077489972114563,\n \"alphanum_fraction\": 0.5129151344299316,\n \"avg_line_length\": 26.100000381469727,\n \"blob_id\": \"8b577448f1d6521cde1cab13d53b910cc7f1f024\",\n \"content_id\": \"57423838cee8e0ab8338166bc1ae53a64992141c\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 542,\n \"license_type\": \"no_license\",\n \"max_line_length\": 39,\n \"num_lines\": 20,\n \"path\": \"/Level1/42862.py\",\n \"repo_name\": \"YoonKiBum/programmers\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"def solution(n, lost, reserve):\\n lost.sort()\\n reserve.sort()\\n count = 0\\n lost = set(lost)\\n reserve = set(reserve)\\n temp1 = lost - reserve\\n temp2 = reserve - lost\\n lost = list(temp1)\\n reserve = list(temp2)\\n for i in range(len(lost)):\\n if len(reserve) <= 0:\\n break\\n if lost[i] - 1 in reserve:\\n reserve.remove(lost[i]-1)\\n count += 1\\n elif lost[i] + 1 in reserve:\\n reserve.remove(lost[i] + 1)\\n count += 1\\n return n - (len(lost) - count)\\n\"\n },\n {\n \"alpha_fraction\": 0.3531745970249176,\n \"alphanum_fraction\": 0.3769841194152832,\n \"avg_line_length\": 18.384614944458008,\n \"blob_id\": \"b6647bf18555789bbb087f31d0dcf2a584d857fd\",\n \"content_id\": \"bac1a4b438b884c1326c8146b1b3d8139387d74f\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 252,\n \"license_type\": \"no_license\",\n \"max_line_length\": 47,\n \"num_lines\": 13,\n \"path\": \"/Level1/68935.py\",\n \"repo_name\": \"YoonKiBum/programmers\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"def solution(n):\\n arr = []\\n while True:\\n if n == 0:\\n break\\n i = n % 3\\n arr.append(i)\\n n = n // 3\\n \\n sum = 0\\n for i in range(len(arr)):\\n sum += (3 ** i) * arr[len(arr) - i - 1]\\n return sum\\n\"\n }\n]"},"num_files":{"kind":"number","value":12,"string":"12"}}},{"rowIdx":2068,"cells":{"repo_name":{"kind":"string","value":"leying95/stereopy"},"repo_url":{"kind":"string","value":"https://github.com/leying95/stereopy"},"snapshot_id":{"kind":"string","value":"0638be0586d056fc5a396c57359303a49f6cf639"},"revision_id":{"kind":"string","value":"1580a88a091a2ebc0f177ea73409e2c4b4dd4c7e"},"directory_id":{"kind":"string","value":"6c87cf3f76566cde6ec6d86891cae649b3fc1582"},"branch_name":{"kind":"string","value":"refs/heads/main"},"visit_date":{"kind":"string","value":"2023-03-29T22:12:40.346022"},"revision_date":{"kind":"string","value":"2021-04-09T03:17:09"},"committer_date":{"kind":"string","value":"2021-04-09T03:17:09"},"github_id":{"kind":"number","value":358531712,"string":"358,531,712"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"string","value":"MIT"},"gha_created_at":{"kind":"string","value":"2021-04-16T08:36:07"},"gha_updated_at":{"kind":"string","value":"2021-04-15T12:44:28"},"gha_pushed_at":{"kind":"string","value":"2021-04-15T13:25:58"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.40083393454551697,"alphanum_fraction":0.5601885318756104,"avg_line_length":25.257143020629883,"blob_id":"7bd2f370968ac513aa8f45d4b85f38dba0a2b29f","content_id":"e13c71464e3fbf9b2020ffb3cba140cc0bc8926e","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":6558,"license_type":"permissive","max_line_length":199,"num_lines":210,"path":"/stereo/plots/plot_data_description.md","repo_name":"leying95/stereopy","src_encoding":"UTF-8","text":"# 绘图数据需求\n\n以 AnnData 为参照获取对应的输入数据\n\n## plot_spatial_distribution\n\n### 所需 AnnData 数据：\n\n- 图像坐标信息： \n - `spatial_data = np.array(adata.obsm[\"spatial\"])`\n\n- 图像散点数值信息： \n - `color_data = np.array(adata.obs_vector(key))`\n - 其中 key 为散点所需呈现的数据种类，如 total_counts, n_genes_by_counts，可利用的数据种类都在 `adata.obs.keys()`\n\n### 实际所需数据格式：\n\n- 图像坐标信息demo：\n \n ```Text\n array([[ 256, -91],[ 185, -157],[ 257, -288],...,[ 151, -246],[ 290, -141],[ 177, -132]])\n ```\n\n- 图像散点数值信息demo：\n \n ```Text\n array([3582., 1773., 2283., ..., 4062., 4371., 1172.], dtype=float32)\n ```\n\n其中散点数值和坐标信息一一对应\n\n## plot_spatial_cluster && plot_cluster_umap\n\n这两个函数整合成了 plot_cluster_result，区别在于所用的 spatial data （pos_key） 不同， plot_spatial_cluster 使用的是 spatial 空间数据，plot_cluster_umap 使用的是 X_umap 的主成分值数据\n\n### 所需 AnnData 数据：\n\n- 图像坐标信息： \n - `spatial_data = np.array(adata.obsm[pos_key])`\n\n- 图像散点数值信息： \n - `color_data = np.array(adata.obs_vector(key))`\n - 其中 key 为散点所需呈现的数据种类，可利用的数据种类都在 adata.obs.keys()，此处用到的主要是聚类相关数据，如 [\"phenograph\", \"leiden\"]\n - 在 cluster 相关的图像中，散点数据属于 categorical 数据\n\n### 实际所需数据格式：\n\n- 图像坐标信息demo：\n \n spatial:\n\n ```Text\n array([[ 256, -91],[ 185, -157],[ 257, -288],...,[ 151, -246],[ 290, -141],[ 177, -132]])\n ```\n\n umap：\n \n ```Text\n array([[-2.234908 , 3.7087667 ], [ 3.7431364 , 2.003201 ], [ 4.849478 , -0.21215418], ..., [ 6.861894 , 1.7589074 ], [-0.4605783 , 4.0366364 ], [ 7.3391566 , -0.40746352]], dtype=float32)\n ```\n\n- 图像散点数值信息demo：\n \n ```Text\n ['0', '3', '5', '3', '2', ..., '4', '3', '6', '1', '5']\n Length: 22726\n Categories (10, object): ['0', '1', '2', '3', ..., '6', '7', '8', '9']\n ```\n\n其中散点数值和坐标信息一一对应\n\n\n## plot_to_select_filter_value\n\n### 所需 AnnData 数据\n\n- `x = adata.obs_vector(var1)`\n- `y = adata.obs_vector(var2)`\n\nvar1 var2 可以是任意两个 obs_key 中的值\n\n### 实际所需数据格式\n\n```Text\narray([3582., 1773., 2283., ..., 4062., 4371., 1172.], dtype=float32)\n```\n\n## plot_variable_gene\n\n### 所需 AnnData 数据：\n\n- `adata.var.highly_variable`\n- `adata.var.means`\n- `adata.var.dispersions`\n- `adata.var.dispersions_norm`\n\n### 实际所需数据格式\n\npandas.core.series.Series\n\n例如： adata.var.means:\n\n```Text\nAL355102.2 0.012042\nSLC25A2 0.000596\n ... \nAC069214.1 0.009608\nAL356056.1 0.001655\nName: means, Length: 33304, dtype: float64\n```\n\n## plot_expression_difference\n\n### 所需 AnnData 数据\n\n- 聚类得到的类名： `group_names = adata.uns[\"rank_genes_groups\"]['names'].dtype.names`\n- 在各个类名（group_name in group_names）的基础上获取各个类的基因列表('names')和分数('scores')：\n - `gene_names = adata.uns[\"rank_genes_groups\"]['names'][group_name][:number_of_gene_to_show]`\n - `scores = adata.uns[\"rank_genes_groups\"]['scores'][group_name][:number_of_gene_to_show]`\n\n### 实际所需数据格式：\n\n- 聚类得到的类名：\n\n ```Text\n tuple('0', '1', '2', '3', '4', '5', '6', '7', '8', '9')\n ```\n- 各个类名对应的基因列表和分数列表：\n \n ```Text\n numpy.ndarray\n \n array(['TUBB4B', 'SLC12A2', 'EPHB3', ..., 'TFF3', 'TIMP1', 'OLFM4'],\n dtype=object)\n \n array([ 28.094688, 27.638664, 24.523687, ..., -41.63738 , -42.894638, -48.384773], dtype=float32)\n ```\n\n## plot_violin_distribution\n\n### 所需 AnnData 数据\n\n- `adata.obs['total_counts']`\n- `adata.obs['n_genes_by_counts']`\n- `adata.obs['pct_counts_mt']`\n\n### 实际所需数据格式\n\npandas.core.series.Series\n\n例如： total_counts:\n\n```Text\n256-91 3582.0\n185-157 1773.0\n ... \n290-141 4371.0\n177-132 1172.0\nName: total_counts, Length: 22726, dtype: float32\n```\n\n## plot_heatmap_maker_genes\n\n### 所需 AnnData 数据：\n\n- 聚类得到的类名： `marker_clusters = adata.uns[\"rank_genes_groups\"]['names'].dtype.names`\n- 在各个类名（cluster in marker_clusters）的基础上获取各个类的基因列表('names'):\n - `genes_array = adata.uns[\"rank_genes_groups\"]['names'][group_name][:number_of_gene_to_show]`\n- 设定表达量矩阵（热图矩阵）\n - 矩阵index： `adata.obs_name`\n - 整合各个类的基因列表，获取 uniq gene list，然后获取这些uniq gene 的表达量来构建 pandas.DataFrame\n - 表达量： `exp_matrix = adata.X[tuple([slice(None), adata.var.index.get_indexer(uniq_gene_names)])]`\n - pd.DataFrame: `pd.DataFrame(exp_matrix, columns=uniq_gene_names, index=adata.obs_names)`\n - 添加 obs 列在最开头： `pd.concat([draw_df, adata.obs[cluster_method]], axis=1)`\n \n\n### 实际所需数据格式：\n\n- 聚类得到的类名：\n\n ```Text\n tuple('0', '1', '2', '3', '4', '5', '6', '7', '8', '9')\n ```\n\n- 各个类名对应的基因列表：\n \n ```Text\n numpy.ndarray\n \n array(['TUBB4B', 'SLC12A2', 'EPHB3', ..., 'TFF3', 'TIMP1', 'OLFM4'],\n dtype=object)\n ```\n\n- 表达量矩阵最终效果：\n \n ```Text\n TUBB4B SLC12A2 EPHB3 MT-ND1 FTX NAALADL2 \n phenograph \n 0 3.758313 1.884562 2.705292 4.040148 2.498723 2.238069 \n 0 3.118562 1.224227 1.758388 3.311160 1.758388 0.000000 \n 0 2.790583 0.000000 0.000000 3.175375 0.000000 0.000000 \n 0 0.000000 1.885036 1.885036 3.821939 0.000000 0.000000 \n 0 2.596922 0.000000 2.596922 3.644590 2.596922 2.596922 \n ... ... ... ... ... ... ... \n 9 3.172084 1.570598 0.000000 4.186041 1.570598 0.000000 \n 9 0.000000 1.847625 0.000000 3.893912 0.000000 2.458688 \n 9 2.681648 2.681648 0.000000 3.339970 1.314215 1.314215 \n 9 1.955572 1.955572 0.000000 3.229691 1.955572 0.000000 \n 9 2.963927 1.721601 1.721601 3.176694 1.721601 0.000000 \n ```\n\n\n"},{"alpha_fraction":0.5407407283782959,"alphanum_fraction":0.614814817905426,"avg_line_length":15.875,"blob_id":"6be96570692f13225dce46515d9ca9c98fef1296","content_id":"0a956633adf2311ac4c74e39451ffd2cbcbd1029","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":135,"license_type":"permissive","max_line_length":25,"num_lines":8,"path":"/stereo/plots/_plot_basic/__init__.py","repo_name":"leying95/stereopy","src_encoding":"UTF-8","text":"#!/usr/bin/env python3\n# coding: utf-8\n\"\"\"\n@author: Shixu He heshixu@genomics.cn\n@last modified by: Shixu He\n@file:__init__.py.py\n@time:2021/03/15\n\"\"\"\n"},{"alpha_fraction":0.8245614171028137,"alphanum_fraction":0.8245614171028137,"avg_line_length":27.5,"blob_id":"07e56b8199fa5930875326eee974fd0b94d0cbaa","content_id":"a08af99a95386dcc9a13b89532990ab6cd210c1f","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":57,"license_type":"permissive","max_line_length":45,"num_lines":2,"path":"/README.md","repo_name":"leying95/stereopy","src_encoding":"UTF-8","text":"# stereopy\nA toolkit of spatial transcriptomic analysis.\n"},{"alpha_fraction":0.576362669467926,"alphanum_fraction":0.582298994064331,"avg_line_length":30.94827651977539,"blob_id":"da5efc016b2d7c7a1cc9131a627d2377e1ae0157","content_id":"66c073cd335fd0fa657926a18e9d780efb70e29a","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1853,"license_type":"permissive","max_line_length":78,"num_lines":58,"path":"/stereo/log_manager.py","repo_name":"leying95/stereopy","src_encoding":"UTF-8","text":"#!/usr/bin/env python3\n# coding: utf-8\n\"\"\"\n@author: Ping Qiu qiuping1@genomics.cn\n@last modified by: Ping Qiu\n@file:log_manager.py\n@time:2021/03/05\n\"\"\"\n\nimport logging\nfrom .config import stereo_conf\n\n\nclass LogManager(object):\n def __init__(self, log_path=None, level=None):\n self.level_map = {'debug': logging.DEBUG,\n 'info': logging.INFO,\n 'warning': logging.WARNING,\n 'error': logging.ERROR,\n 'critical': logging.CRITICAL}\n self.format = stereo_conf.log_format\n self.formatter = logging.Formatter(self.format, \"%Y-%m-%d %H:%M:%S\")\n self.log_path = log_path\n self.level = level.lower() if level else stereo_conf.log_level.lower()\n if self.log_path:\n self.file_handler = logging.FileHandler(self.log_path)\n self.file_handler.setLevel(self.level_map[self.level])\n self.file_handler.setFormatter(self.formatter)\n else:\n self.stream_handler = logging.StreamHandler()\n self.stream_handler.setLevel(self.level_map[self.level])\n self.stream_handler.setFormatter(self.formatter)\n\n def get_logger(self, name=\"Spateo\"):\n \"\"\"\n get logger object\n :param name: logger name\n :return: logger object\n \"\"\"\n alogger = logging.getLogger(name)\n alogger.propagate = 0\n alogger.setLevel(self.level_map[self.level])\n self._add_handler(alogger)\n return alogger\n\n def _add_handler(self, alogger):\n \"\"\"\n add handler of logger\n :param logger: logger object\n :return:\n \"\"\"\n if self.log_path:\n alogger.addHandler(self.file_handler)\n else:\n alogger.addHandler(self.stream_handler)\n\n\nlogger = LogManager().get_logger(name='Spateo')\n"},{"alpha_fraction":0.5441176295280457,"alphanum_fraction":0.5572336912155151,"avg_line_length":34.42253494262695,"blob_id":"223b8ada9eb9f510c9b68f7895d4f42a65b81f8e","content_id":"0299148833875c5536949e7ad7ae0d0f9b9dafff","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":2516,"license_type":"permissive","max_line_length":117,"num_lines":71,"path":"/stereo/tools/neighbors.py","repo_name":"leying95/stereopy","src_encoding":"UTF-8","text":"#!/usr/bin/env python3\n# coding: utf-8\n\"\"\"\n@author: Ping Qiu qiuping1@genomics.cn\n@last modified by: Ping Qiu\n@file:neighbors.py\n@time:2021/03/23\n\"\"\"\nfrom scipy.sparse import coo_matrix\nfrom sklearn.neighbors import NearestNeighbors\nimport igraph as ig\nimport numpy as np\nfrom umap.umap_ import fuzzy_simplicial_set\n\n\nclass Neighbors(object):\n def __init__(self, x, n_neighbors):\n self.x = x\n self.n_neighbors = n_neighbors\n\n def find_n_neighbors(self):\n nbrs = NearestNeighbors(n_neighbors=self.n_neighbors + 1, algorithm='ball_tree').fit(self.x)\n dists, indices = nbrs.kneighbors(self.x)\n nn_idx = indices[:, 1:]\n nn_dist = dists[:, 1:]\n return nn_idx, nn_dist\n\n def get_igraph_from_knn(self, nn_idx, nn_dist):\n j = nn_idx.ravel().astype(int)\n dist = nn_dist.ravel()\n i = np.repeat(np.arange(nn_idx.shape[0]), self.n_neighbors)\n\n vertex = list(range(nn_dist.shape[0]))\n edges = list(tuple(zip(i, j)))\n G = ig.Graph()\n G.add_vertices(vertex)\n G.add_edges(edges)\n G.es['weight'] = dist\n return G\n\n def get_parse_distances(self, nn_idx, nn_dist):\n n_obs = self.x.shape[0]\n rows = np.zeros((n_obs * self.n_neighbors), dtype=np.int64)\n cols = np.zeros((n_obs * self.n_neighbors), dtype=np.int64)\n vals = np.zeros((n_obs * self.n_neighbors), dtype=np.float64)\n\n for i in range(nn_idx.shape[0]):\n for j in range(self.n_neighbors):\n if nn_idx[i, j] == -1:\n continue # We didn't get the full knn for i\n if nn_idx[i, j] == i:\n val = 0.0\n else:\n val = nn_dist[i, j]\n\n rows[i * self.n_neighbors + j] = i\n cols[i * self.n_neighbors + j] = nn_idx[i, j]\n vals[i * self.n_neighbors + j] = val\n\n distances = coo_matrix((vals, (rows, cols)), shape=(n_obs, n_obs))\n distances.eliminate_zeros()\n return distances.tocsr()\n\n def get_connectivities(self, nn_idx, nn_dist):\n n_obs = self.x.shape[0]\n x = coo_matrix(([], ([], [])), shape=(n_obs, 1))\n connectivities = fuzzy_simplicial_set(x, self.n_neighbors, None, None, knn_indices=nn_idx, knn_dists=nn_dist,\n set_op_mix_ratio=1.0, local_connectivity=1.0)\n if isinstance(connectivities, tuple):\n connectivities = connectivities[0]\n return connectivities.tocsr()\n\n"},{"alpha_fraction":0.5665071606636047,"alphanum_fraction":0.5779904127120972,"avg_line_length":18.716981887817383,"blob_id":"75c8c1af025576b41fdaa21b6c25ecd8e15afd72","content_id":"cd7efb2f1f96eb9937d843ad9cef415c0aff5d4f","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1045,"license_type":"permissive","max_line_length":107,"num_lines":53,"path":"/stereo/core/stereo_data.py","repo_name":"leying95/stereopy","src_encoding":"UTF-8","text":"#!/usr/bin/env python3\n# coding: utf-8\n\"\"\"\n@author: Ping Qiu qiuping1@genomics.cn\n@last modified by: Ping Qiu\n@file:stereo_data.py\n@time:2021/03/22\n\"\"\"\n\n\nclass StereoData(object):\n def __init__(self, raw_file=None, exp_matrix=None, genes=None, bins=None, position=None, partitions=1):\n self.index = None\n self.index_file = None\n self.exp_matrix = exp_matrix\n self.genes = genes\n self.bins = bins\n self.position = position\n self.raw_file = raw_file\n self.partitions = partitions\n\n def filter_genes(self):\n pass\n\n def filter_bins(self):\n pass\n\n def search(self):\n pass\n\n def combine_bins(self, bin_size, step):\n pass\n\n def select_by_genes(self, gene_list):\n pass\n\n def select_by_position(self, x_min, y_min, x_max, y_max, bin_size):\n pass\n\n def transform_matrix(self):\n pass\n\n def get_genes(self):\n pass\n\n def get_bins(self):\n pass\n\n def split_data(self):\n pass\n\n def sparse2array(self):\n pass\n"},{"alpha_fraction":0.6382660865783691,"alphanum_fraction":0.6636771559715271,"avg_line_length":29.409090042114258,"blob_id":"b9472f782f76c2f6c8aaa8802826cc4656afb1ba","content_id":"ed031fae5add10b548834f898ab95a813e1f9395","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":669,"license_type":"permissive","max_line_length":71,"num_lines":22,"path":"/stereo/preprocess/qc.py","repo_name":"leying95/stereopy","src_encoding":"UTF-8","text":"#!/usr/bin/env python3\n# coding: utf-8\n\"\"\"\n@author: Ping Qiu qiuping1@genomics.cn\n@last modified by: Ping Qiu\n@file:qc.py\n@time:2021/03/26\n\"\"\"\nfrom scipy.sparse import issparse\nimport numpy as np\n\n\ndef cal_qc(andata):\n exp_matrix = andata.X.toarray() if issparse(andata.X) else andata.X\n total_count = exp_matrix.sum(1)\n n_gene_by_count = np.count_nonzero(exp_matrix, axis=1)\n mt_index = andata.var_names.str.startswith('MT-')\n mt_count = np.array(andata.X[:, mt_index].sum(1)).reshape(-1)\n andata.obs['total_counts'] = total_count\n andata.obs['pct_counts_mt'] = mt_count / total_count * 100\n andata.obs['n_genes_by_counts'] = n_gene_by_count\n return andata\n"},{"alpha_fraction":0.5326364636421204,"alphanum_fraction":0.5358884930610657,"avg_line_length":25.411043167114258,"blob_id":"57ec9a317b271c5001152cd0804fe0de76566362","content_id":"5e726176ef70882e7b7c303bdb60a84d1c62f300","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":4305,"license_type":"permissive","max_line_length":114,"num_lines":163,"path":"/stereo/config.py","repo_name":"leying95/stereopy","src_encoding":"UTF-8","text":"#!/usr/bin/env python3\n# coding: utf-8\n\"\"\"\n@author: Ping Qiu qiuping1@genomics.cn\n@last modified by: Ping Qiu\n@file:config.py\n@time:2021/03/05\n\"\"\"\nfrom typing import Union, Optional\nfrom pathlib import Path\nimport os\nfrom matplotlib import rcParams, rcParamsDefault\n\n\nclass StereoConfig(object):\n \"\"\"\n config of stereo.\n \"\"\"\n def __init__(\n self,\n file_format: str = \"h5ad\",\n auto_show: bool = True,\n n_jobs=1,\n log_file: Union[str, Path, None] = None,\n log_level: str = \"info\",\n log_format: str = \"%(asctime)s %(name)s %(levelname)s: %(message)s\",\n output: str = \"./output\",\n data_dir: str = None\n ):\n self._file_format = file_format\n self._auto_show = auto_show\n self._n_jobs = n_jobs\n self._log_file = log_file\n self._log_level = log_level\n self._log_format = log_format\n self.out_dir = output\n self.data_dir = data_dir if data_dir else os.path.join(os.path.dirname(os.path.abspath(__file__)), 'data')\n\n @property\n def log_file(self) -> Union[str, Path, None]:\n \"\"\"\n get the file path of log.\n :return:\n \"\"\"\n return self._log_file\n\n @log_file.setter\n def log_file(self, value):\n \"\"\"\n set file path of log.\n :param value: value of log file path\n :return:\n \"\"\"\n if value:\n dir_path = os.path.dirname(value)\n if not os.path.exists(dir_path):\n raise FileExistsError(\"folder does not exist, please check!\")\n self._log_file = value\n\n @property\n def log_format(self) -> str:\n \"\"\"\n get the format of log.\n :return:\n \"\"\"\n return self._log_format\n\n @log_format.setter\n def log_format(self, value):\n \"\"\"\n set file path of log.\n :param value: value of log format\n :return:\n \"\"\"\n self._log_format = value\n\n @property\n def log_level(self) -> str:\n \"\"\"\n get log level\n :return:\n \"\"\"\n return self._log_level\n\n @log_level.setter\n def log_level(self, value):\n \"\"\"\n set log level\n :param value: the value of log level\n :return:\n \"\"\"\n if value.lower() not in ['info', 'warning', 'debug', 'error', 'critical']:\n print('the log level is out of range, please check and it is not modified.')\n else:\n self._log_level = value\n\n @property\n def auto_show(self):\n \"\"\"\n Auto show figures if `auto_show == True` (default `True`).\n :return:\n \"\"\"\n return self._auto_show\n\n @auto_show.setter\n def auto_show(self, value):\n \"\"\"\n set value of auto_show\n :param value: value of auto_show\n :return:\n \"\"\"\n self._auto_show = value\n\n @property\n def file_format(self) -> str:\n \"\"\"\n file format of saving anndata object\n :return:\n \"\"\"\n return self._file_format\n\n @file_format.setter\n def file_format(self, value):\n \"\"\"\n set the value of file format\n :param value: the value of file format\n :return:\n \"\"\"\n self._file_format = value\n\n @property\n def n_jobs(self) -> int:\n return self._n_jobs\n\n @n_jobs.setter\n def n_jobs(self, value):\n self._n_jobs = value\n\n @staticmethod\n def set_plot_param(fontsize: int = 14, figsize: Optional[int] = None, color_map: Optional[str] = None,\n facecolor: Optional[str] = None, transparent: bool = False,):\n if fontsize is not None:\n rcParams['font.size'] = fontsize\n if color_map is not None:\n rcParams['image.cmap'] = color_map\n if figsize is not None:\n rcParams['figure.figsize'] = figsize\n if facecolor is not None:\n rcParams['figure.facecolor'] = facecolor\n rcParams['axes.facecolor'] = facecolor\n if transparent is not None:\n rcParams[\"savefig.transparent\"] = transparent\n\n @staticmethod\n def set_rcparams_defaults():\n \"\"\"\n reset `matplotlib.rcParams` to defaults.\n :return:\n \"\"\"\n rcParams.update(rcParamsDefault)\n\n\nstereo_conf = StereoConfig()\n"},{"alpha_fraction":0.552388072013855,"alphanum_fraction":0.5629907250404358,"avg_line_length":33.834495544433594,"blob_id":"5cf9c6e4a72c0d946056b70efefaa0185bdaeffa","content_id":"e13b730eda2fc60a16a1c52046d3725d072fd48c","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":20531,"license_type":"permissive","max_line_length":155,"num_lines":574,"path":"/stereo/plots/plot_utils.py","repo_name":"leying95/stereopy","src_encoding":"UTF-8","text":"#!/usr/bin/env python3\n# coding: utf-8\n\"\"\"\n@author: Shixu He heshixu@genomics.cn\n@last modified by: Shixu He\n@file:plot_utils.py\n@time:2021/03/15\n\"\"\"\n\nfrom anndata import AnnData\nimport pandas as pd\nimport numpy as np\nimport math\n\nfrom matplotlib.colors import Normalize, ListedColormap\nfrom matplotlib import gridspec\nfrom matplotlib.cm import get_cmap\nfrom matplotlib.axes import Axes\nimport matplotlib.pyplot as plt\nimport seaborn\n\nfrom ._plot_basic.scatter_plt import scatter, plot_cluster_result\nfrom ._plot_basic.heatmap_plt import heatmap, _plot_categories_as_colorblocks, _plot_gene_groups_brackets\n\nfrom typing import Optional, Sequence, Union\n\nfrom ..log_manager import logger\n\n\ndef plot_spatial_distribution(\n adata: AnnData,\n obs_key: list = [\"total_counts\", \"n_genes_by_counts\"],\n ncols=2,\n dot_size=None,\n color_list=None,\n invert_y=False\n): # scatter plot, 表达矩阵空间分布\n \"\"\"\n Plot spatial distribution of specified obs data.\n ============ Arguments ============\n :param adata: AnnData object.\n :param obs_key: specified obs key list, for example: [\"total_counts\", \"n_genes_by_counts\"]\n :param ncols: numbr of plot columns.\n :param dot_size: marker size.\n :param cmap: Color map.\n :param invert_y: whether to invert y-axis.\n ============ Return ============\n None\n ============ Example ============\n plot_spatial_distribution(adata=adata)\n \"\"\"\n # sc.pl.embedding(adata, basis=\"spatial\", color=[\"total_counts\", \"n_genes_by_counts\"],size=30)\n\n if dot_size is None:\n dot_size = 120000 / adata.shape[0]\n\n ncols = min(ncols, len(obs_key))\n nrows = np.ceil(len(obs_key) / ncols).astype(int)\n # each panel will have the size of rcParams['figure.figsize']\n fig = plt.figure(figsize=(ncols * 10, nrows * 8))\n left = 0.2 / ncols\n bottom = 0.13 / nrows\n axs = gridspec.GridSpec(\n nrows=nrows,\n ncols=ncols,\n left=left,\n right=1 - (ncols - 1) * left - 0.01 / ncols,\n bottom=bottom,\n top=1 - (nrows - 1) * bottom - 0.1 / nrows,\n # hspace=hspace,\n # wspace=wspace,\n )\n\n if color_list is None:\n cmap = get_cmap()\n else:\n cmap = ListedColormap(color_list)\n # 把特定值改为 np.nan 之后，可以利用 cmap.set_bad(\"white\") 来遮盖掉这部分数据\n\n # 散点图上每个点的坐标数据来自于 adata 的 obsm[\"spatial\"]，每个点的颜色（数值）数据来自于 adata 的 obs_vector()\n for i, key in enumerate(obs_key):\n # color_data = np.asarray(adata.obs_vector(key), dtype=float)\n color_data = adata.obs_vector(key)\n order = np.argsort(~pd.isnull(color_data), kind=\"stable\")\n spatial_data = np.array(adata.obsm[\"spatial\"])[:, 0: 2]\n color_data = color_data[order]\n spatial_data = spatial_data[order, :]\n\n # color_data 是图像中各个点的值，也对应了每个点的颜色。data_points则对应了各个点的坐标\n ax = fig.add_subplot(axs[i]) # ax = plt.subplot(axs[i]) || ax = fig.add_subplot(axs[1, 1]))\n ax.set_title(key)\n ax.set_yticks([])\n ax.set_xticks([])\n ax.set_xlabel(\"spatial1\")\n ax.set_ylabel(\"spatial2\")\n pathcollection = scatter(\n spatial_data[:, 0],\n spatial_data[:, 1],\n ax=ax,\n marker=\".\",\n dot_colors=color_data,\n dot_size=dot_size,\n cmap=cmap,\n )\n plt.colorbar(\n pathcollection,\n ax=ax,\n pad=0.01,\n fraction=0.08,\n aspect=30,\n )\n ax.autoscale_view()\n if invert_y:\n ax.invert_yaxis()\n\n\ndef plot_spatial_cluster(\n adata: AnnData,\n obs_key: list = [\"phenograph\"],\n plot_cluster: list = None,\n bad_color=\"lightgrey\",\n ncols=2,\n dot_size=None,\n invert_y=False,\n color_list=['violet', 'turquoise', 'tomato', 'teal',\n 'tan', 'silver', 'sienna', 'red', 'purple',\n 'plum', 'pink', 'orchid', 'orangered', 'orange',\n 'olive', 'navy', 'maroon', 'magenta', 'lime',\n 'lightgreen', 'lightblue', 'lavender', 'khaki',\n 'indigo', 'grey', 'green', 'gold', 'fuchsia',\n 'darkgreen', 'darkblue', 'cyan', 'crimson', 'coral',\n 'chocolate', 'chartreuse', 'brown', 'blue', 'black',\n 'beige', 'azure', 'aquamarine', 'aqua']): # scatter plot, 聚类后表达矩阵空间分布\n \"\"\"\n Plot spatial distribution of specified obs data.\n ============ Arguments ============\n :param adata: AnnData object.\n :param obs_key: specified obs cluster key list, for example: [\"phenograph\"].\n :param plot_cluster: the name list of clusters to show.\n :param ncols: numbr of plot columns.\n :param dot_size: marker size.\n :param cmap: Color map.\n :param invert_y: whether to invert y-axis.\n ============ Return ============\n None.\n ============ Example ============\n plot_spatial_cluster(adata = adata)\n \"\"\"\n # sc.pl.embedding(adata, basis=\"spatial\", color=[\"total_counts\", \"n_genes_by_counts\"],size=30)\n\n if isinstance(obs_key, str):\n obs_key = [\"obs_key\"]\n\n plot_cluster_result(adata, obs_key=obs_key, pos_key=\"spatial\", plot_cluster=plot_cluster, bad_color=bad_color,\n ncols=ncols, dot_size=dot_size, invert_y=invert_y, color_list=color_list)\n\n\ndef plot_to_select_filter_value(\n adata: AnnData,\n x=[\"total_counts\", \"total_counts\"],\n y=[\"pct_counts_mt\", \"n_genes_by_counts\"],\n ncols=1,\n **kwargs): # scatter plot, 线粒体分布图\n \"\"\"\n Plot .\n ============ Arguments ============\n :param adata: AnnData object.\n :param x, y: obs key pairs for drawing. For example, assume x=[\"a\", \"a\", \"b\"] and y=[\"c\", \"d\", \"e\"], the output plots will include \"a-c\", \"a-d\", \"b-e\".\n ============ Return ============\n None.\n ============ Example ============\n plot_spatial_cluster(adata = adata)\n \"\"\"\n # sc.pl.scatter(adata, x='total_counts', y='pct_counts_mt')\n # sc.pl.scatter(adata, x='total_counts', y='n_genes_by_counts')\n if isinstance(x, str):\n x = [x]\n if isinstance(y, str):\n y = [y]\n\n width = 20\n height = 10\n nrows = math.ceil(len(x) / ncols)\n\n doc_color = \"gray\"\n\n fig = plt.figure(figsize=(width, height))\n axs = gridspec.GridSpec(\n nrows=nrows,\n ncols=ncols,\n )\n for i, (xi, yi) in enumerate(zip(x, y)):\n draw_data = np.c_[adata.obs_vector(xi), adata.obs_vector(yi)]\n dot_size = 120000 / draw_data.shape[0]\n ax = fig.add_subplot(axs[i])\n # ax.set_title()\n # ax.set_yticks([])\n # ax.set_xticks([])\n ax.set_xlabel(xi)\n ax.set_ylabel(yi)\n scatter(\n draw_data[:, 0],\n draw_data[:, 1],\n ax=ax,\n marker=\".\",\n dot_colors=doc_color,\n dot_size=dot_size\n )\n\n\ndef plot_variable_gene(adata: AnnData, logarize=False): # scatter plot, 表达量差异-均值图\n \"\"\"\n Copied from scanpy and modified.\n \"\"\"\n # 该图像需要前置数据处理：sc.pp.highly_variable_genes(adata, min_mean=0.0125, max_mean=3, min_disp=0.5)\n # 再画图：sc.pl.highly_variable_genes(adata)\n\n result = adata.var\n gene_subset = result.highly_variable\n means = result.means\n var_or_disp = result.dispersions\n var_or_disp_norm = result.dispersions_norm\n width = 10\n height = 10\n\n plt.figure(figsize=(2 * width, height))\n plt.subplots_adjust(wspace=0.3)\n for idx, d in enumerate([var_or_disp_norm, var_or_disp]):\n plt.subplot(1, 2, idx + 1)\n for label, color, mask in zip(\n ['highly variable genes', 'other genes'],\n ['black', 'grey'],\n [gene_subset, ~gene_subset],\n ):\n if False:\n means_, var_or_disps_ = np.log10(means[mask]), np.log10(d[mask])\n else:\n means_, var_or_disps_ = means[mask], d[mask]\n plt.scatter(means_, var_or_disps_, label=label, c=color, s=1)\n if logarize: # there's a bug in autoscale\n plt.xscale('log')\n plt.yscale('log')\n y_min = np.min(var_or_disp)\n y_min = 0.95 * y_min if y_min > 0 else 1e-1\n plt.xlim(0.95 * np.min(means), 1.05 * np.max(means))\n plt.ylim(y_min, 1.05 * np.max(var_or_disp))\n if idx == 0:\n plt.legend()\n plt.xlabel(('$log_{10}$ ' if False else '') + 'mean expressions of genes')\n data_type = 'dispersions'\n plt.ylabel(\n ('$log_{10}$ ' if False else '')\n + '{} of genes'.format(data_type)\n + (' (normalized)' if idx == 0 else ' (not normalized)')\n )\n\n\ndef plot_cluster_umap(\n adata: AnnData,\n obs_key: list = [\"phenograph\"],\n plot_cluster: list = None,\n bad_color=\"lightgrey\",\n ncols=2,\n dot_size=None,\n invert_y=False,\n color_list=['violet', 'turquoise', 'tomato', 'teal',\n 'tan', 'silver', 'sienna', 'red', 'purple',\n 'plum', 'pink', 'orchid', 'orangered', 'orange',\n 'olive', 'navy', 'maroon', 'magenta', 'lime',\n 'lightgreen', 'lightblue', 'lavender', 'khaki',\n 'indigo', 'grey', 'green', 'gold', 'fuchsia',\n 'darkgreen', 'darkblue', 'cyan', 'crimson', 'coral',\n 'chocolate', 'chartreuse', 'brown', 'blue', 'black',\n 'beige', 'azure', 'aquamarine', 'aqua',\n ]\n): # scatter plot，聚类结果PCA/umap图\n \"\"\"\n Plot spatial distribution of specified obs data.\n ============ Arguments ============\n :param adata: AnnData object.\n :param obs_key: specified obs cluster key list, for example: [\"phenograph\"].\n :param plot_cluster: the name list of clusters to show.\n :param ncols: numbr of plot columns.\n :param dot_size: marker size.\n :param cmap: Color map.\n :param invert_y: whether to invert y-axis.\n ============ Return ============\n None.\n ============ Example ============\n plot_cluster_umap(adata = adata)\n \"\"\"\n\n if (isinstance(obs_key, str)):\n obs_key = [obs_key]\n\n plot_cluster_result(adata, obs_key=obs_key, pos_key=\"X_umap\", plot_cluster=plot_cluster, bad_color=bad_color,\n ncols=ncols, dot_size=dot_size, invert_y=invert_y, color_list=color_list)\n\n\ndef plot_expression_difference(\n adata: AnnData,\n groups: Union[str, Sequence[str]] = None,\n n_genes: int = 20,\n key: Optional[str] = 'rank_genes_groups',\n fontsize: int = 8,\n ncols: int = 4,\n sharey: bool = True,\n show: Optional[bool] = None,\n save: Optional[bool] = None,\n ax: Optional[Axes] = None,\n **kwds,\n): # scatter plot, 差异基因显著性图，类碎石图\n \"\"\"\n Copied from scanpy and modified.\n \"\"\"\n\n # 调整图像 panel/grid 相关参数\n if 'n_panels_per_row' in kwds:\n n_panels_per_row = kwds['n_panels_per_row']\n else:\n n_panels_per_row = ncols\n group_names = adata.uns[key]['names'].dtype.names if groups is None else groups\n # one panel for each group\n # set up the figure\n n_panels_x = min(n_panels_per_row, len(group_names))\n n_panels_y = np.ceil(len(group_names) / n_panels_x).astype(int)\n\n # 初始化图像\n width = 10\n height = 10\n fig = plt.figure(\n figsize=(\n n_panels_x * width, # rcParams['figure.figsize'][0],\n n_panels_y * height, # rcParams['figure.figsize'][1],\n )\n )\n gs = gridspec.GridSpec(nrows=n_panels_y, ncols=n_panels_x, wspace=0.22, hspace=0.3)\n\n ax0 = None\n ymin = np.Inf\n ymax = -np.Inf\n for count, group_name in enumerate(group_names):\n gene_names = adata.uns[key]['names'][group_name][:n_genes]\n scores = adata.uns[key]['scores'][group_name][:n_genes]\n\n # Setting up axis, calculating y bounds\n if sharey:\n ymin = min(ymin, np.min(scores))\n ymax = max(ymax, np.max(scores))\n\n if ax0 is None:\n ax = fig.add_subplot(gs[count])\n ax0 = ax\n else:\n ax = fig.add_subplot(gs[count], sharey=ax0)\n else:\n ymin = np.min(scores)\n ymax = np.max(scores)\n ymax += 0.3 * (ymax - ymin)\n\n ax = fig.add_subplot(gs[count])\n ax.set_ylim(ymin, ymax)\n\n ax.set_xlim(-0.9, n_genes - 0.1)\n\n # Making labels\n for ig, gene_name in enumerate(gene_names):\n ax.text(\n ig,\n scores[ig],\n gene_name,\n rotation='vertical',\n verticalalignment='bottom',\n horizontalalignment='center',\n fontsize=fontsize,\n )\n\n ax.set_title('{} vs. {}'.format(group_name, \"Others\"))\n if count >= n_panels_x * (n_panels_y - 1):\n ax.set_xlabel('ranking')\n\n # print the 'score' label only on the first panel per row.\n if count % n_panels_x == 0:\n ax.set_ylabel('score')\n\n if sharey is True:\n ymax += 0.3 * (ymax - ymin)\n ax.set_ylim(ymin, ymax)\n\n\ndef plot_violin_distribution(adata): # 小提琴统计图\n \"\"\"\n 绘制数据的分布小提琴图。\n ============ Arguments ============\n :param adata: AnnData object.\n ============ Return ============\n None\n \"\"\"\n _, axs = plt.subplots(1, 3, figsize=(15, 4))\n seaborn.violinplot(y=adata.obs['total_counts'], ax=axs[0])\n seaborn.violinplot(y=adata.obs['n_genes_by_counts'], ax=axs[1])\n seaborn.violinplot(y=adata.obs['pct_counts_mt'], ax=axs[2])\n\n\ndef plot_heatmap_maker_genes(\n adata: AnnData = None,\n cluster_method=\"phenograph\",\n marker_uns_key=None,\n num_show_gene=8,\n show_labels=True,\n order_cluster=True,\n marker_clusters=None,\n cluster_colors_array=None,\n **kwargs\n): # heatmap, 差异基因热图\n \"\"\"\n 绘制 Marker gene 的热图。热图中每一行代表一个 bin 的所有基因的表达量，所有的 bin 会根据所属的 cluster 进行聚集， cluster 具体展示在热图的左侧，用颜色区分。\n ============ Arguments ============\n :param adata: AnnData object.\n :param cluster_methpd: method used in clustering. for example: phenograph, leiden\n :param marker_uns_key: the key of adata.uns, the default value is \"marker_genes\"\n :param num_show_gene: number of genes to show in each cluster.\n :param show_labels: show gene name on axis.\n :param order_cluster: reorder the cluster list in plot (y axis).\n :param marker_clusters: the list of clusters to show on the heatmap.\n :param cluster_colors_array: the list of colors in the color block on the left of heatmap.\n ============ Return ============\n\n ============ Example ============\n plot_heatmap_maker_genes(adata=adata, marker_uns_key = \"rank_genes_groups\", figsize = (20, 10))\n \"\"\"\n\n if marker_uns_key is None:\n marker_uns_key = 'marker_genes' # \"rank_genes_groups\" in original scanpy pipeline\n\n # if cluster_method is None:\n # cluster_method = str(adata.uns[marker_uns_key]['params']['groupby'])\n\n # cluster_colors_array = adata.uns[\"phenograph_colors\"]\n\n if marker_clusters is None:\n marker_clusters = adata.uns[marker_uns_key]['names'].dtype.names\n\n if not set(marker_clusters).issubset(set(adata.uns[marker_uns_key]['names'].dtype.names)):\n marker_clusters = adata.uns[marker_uns_key]['names'].dtype.names\n\n gene_names_dict = {} # dict in which each cluster is the keyand the num_show_gene are the values\n\n for cluster in marker_clusters:\n # get all genes that are 'non-nan'\n genes_array = adata.uns[marker_uns_key]['names'][cluster]\n genes_array = genes_array[~pd.isnull(genes_array)]\n\n if len(genes_array) == 0:\n logger.warning(\"Cluster {} has no genes.\".format(cluster))\n continue\n gene_names_dict[cluster] = list(genes_array[:num_show_gene])\n\n adata._sanitize()\n\n gene_names = []\n gene_group_labels = []\n gene_group_positions = []\n start = 0\n for label, gene_list in gene_names_dict.items():\n if isinstance(gene_list, str):\n gene_list = [gene_list]\n gene_names.extend(list(gene_list))\n gene_group_labels.append(label)\n gene_group_positions.append((start, start + len(gene_list) - 1))\n start += len(gene_list)\n\n # 此处获取所有绘图所需的数据 （表达量矩阵）\n draw_df = pd.DataFrame(index=adata.obs_names)\n uniq_gene_names = np.unique(gene_names)\n draw_df = pd.concat(\n [draw_df, pd.DataFrame(adata.X[tuple([slice(None), adata.var.index.get_indexer(uniq_gene_names)])],\n columns=uniq_gene_names, index=adata.obs_names)],\n axis=1\n )\n\n # add obs values\n draw_df = pd.concat([draw_df, adata.obs[cluster_method]], axis=1)\n\n # reorder columns to given order (including duplicates keys if present)\n draw_df = draw_df[list([cluster_method]) + list(uniq_gene_names)]\n draw_df = draw_df[gene_names].set_index(draw_df[cluster_method].astype('category'))\n if order_cluster:\n draw_df = draw_df.sort_index()\n\n # From scanpy\n # define a layout of 2 rows x 3 columns\n # first row is for 'brackets' (if no brackets needed, the height of this row\n # is zero) second row is for main content. This second row is divided into\n # three axes:\n # first ax is for the categories defined by `cluster_method`\n # second ax is for the heatmap\n # fourth ax is for colorbar\n\n kwargs.setdefault(\"figsize\", (10, 10))\n kwargs.setdefault(\"colorbar_width\", 0.2)\n colorbar_width = kwargs.get(\"colorbar_width\")\n figsize = kwargs.get(\"figsize\")\n\n cluster_block_width = kwargs.setdefault(\"cluster_block_width\", 0.2) if order_cluster else 0\n if figsize is None:\n height = 6\n if show_labels:\n heatmap_width = len(gene_names) * 0.3\n else:\n heatmap_width = 8\n width = heatmap_width + cluster_block_width\n else:\n width, height = figsize\n heatmap_width = width - cluster_block_width\n\n if gene_group_positions is not None and len(gene_group_positions) > 0:\n # add some space in case 'brackets' want to be plotted on top of the image\n height_ratios = [0.15, height]\n else:\n height_ratios = [0, height]\n\n width_ratios = [\n cluster_block_width,\n heatmap_width,\n colorbar_width,\n ]\n\n fig = plt.figure(figsize=(width, height))\n\n axs = gridspec.GridSpec(\n nrows=2,\n ncols=3,\n width_ratios=width_ratios,\n wspace=0.15 / width,\n hspace=0.13 / height,\n height_ratios=height_ratios,\n )\n\n heatmap_ax = fig.add_subplot(axs[1, 1])\n\n width, height = fig.get_size_inches()\n max_cbar_height = 4.0\n if height > max_cbar_height:\n # to make the colorbar shorter, the\n # ax is split and the lower portion is used.\n axs2 = gridspec.GridSpecFromSubplotSpec(2, 1, subplot_spec=axs[1, 2],\n height_ratios=[height - max_cbar_height, max_cbar_height],\n )\n heatmap_cbar_ax = fig.add_subplot(axs2[1])\n else:\n heatmap_cbar_ax = fig.add_subplot(axs[1, 2])\n\n heatmap(df=draw_df, ax=heatmap_ax,\n norm=Normalize(vmin=None, vmax=None), plot_colorbar=True, colorbar_ax=heatmap_cbar_ax,\n show_labels=True, plot_hline=True)\n\n if order_cluster:\n _plot_categories_as_colorblocks(\n fig.add_subplot(axs[1, 0]), draw_df, colors=cluster_colors_array, orientation='left'\n )\n\n # plot cluster legends on top of heatmap_ax (if given)\n if gene_group_positions is not None and len(gene_group_positions) > 0:\n _plot_gene_groups_brackets(\n fig.add_subplot(axs[0, 1], sharex=heatmap_ax),\n group_positions=gene_group_positions,\n group_labels=gene_group_labels,\n rotation=None,\n left_adjustment=-0.3,\n right_adjustment=0.3,\n )\n\n # plt.savefig()\n"},{"alpha_fraction":0.5822505354881287,"alphanum_fraction":0.5927923321723938,"avg_line_length":32.99166488647461,"blob_id":"a8e3e35c6156f10d95e13736868dfb21b8d5ee67","content_id":"3526ea0c74b7e911d1ee4dc7c4cc474d0dd5b8eb","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":4087,"license_type":"permissive","max_line_length":117,"num_lines":120,"path":"/stereo/tools/cluster.py","repo_name":"leying95/stereopy","src_encoding":"UTF-8","text":"#!/usr/bin/env python3\n# coding: utf-8\n\"\"\"\n@author: Ping Qiu qiuping1@genomics.cn\n@last modified by: Ping Qiu\n@file:cluster.py\n@time:2021/03/19\n\"\"\"\nimport leidenalg as la\nfrom sklearn.decomposition import PCA\nfrom scipy.sparse import coo_matrix\nfrom sklearn.neighbors import NearestNeighbors\nimport igraph as ig\nimport numpy as np\nfrom umap.umap_ import fuzzy_simplicial_set\n\n\nclass Neighbors(object):\n def __init__(self, x, n_neighbors):\n self.x = x\n self.n_neighbors = n_neighbors\n\n def find_n_neighbors(self):\n nbrs = NearestNeighbors(n_neighbors=self.n_neighbors + 1, algorithm='ball_tree').fit(self.x)\n dists, indices = nbrs.kneighbors(self.x)\n nn_idx = indices[:, 1:]\n nn_dist = dists[:, 1:]\n return nn_idx, nn_dist\n\n def get_igraph_from_knn(self, nn_idx, nn_dist):\n j = nn_idx.ravel().astype(int)\n dist = nn_dist.ravel()\n i = np.repeat(np.arange(nn_idx.shape[0]), self.n_neighbors)\n\n vertex = list(range(nn_dist.shape[0]))\n edges = list(tuple(zip(i, j)))\n G = ig.Graph()\n G.add_vertices(vertex)\n G.add_edges(edges)\n G.es['weight'] = dist\n return G\n\n def get_parse_distances(self, nn_idx, nn_dist):\n n_obs = self.x.shape[0]\n rows = np.zeros((n_obs * self.n_neighbors), dtype=np.int64)\n cols = np.zeros((n_obs * self.n_neighbors), dtype=np.int64)\n vals = np.zeros((n_obs * self.n_neighbors), dtype=np.float64)\n\n for i in range(nn_idx.shape[0]):\n for j in range(self.n_neighbors):\n if nn_idx[i, j] == -1:\n continue # We didn't get the full knn for i\n if nn_idx[i, j] == i:\n val = 0.0\n else:\n val = nn_dist[i, j]\n\n rows[i * self.n_neighbors + j] = i\n cols[i * self.n_neighbors + j] = nn_idx[i, j]\n vals[i * self.n_neighbors + j] = val\n\n distances = coo_matrix((vals, (rows, cols)), shape=(n_obs, n_obs))\n distances.eliminate_zeros()\n return distances.tocsr()\n\n def get_connectivities(self, nn_idx, nn_dist):\n n_obs = self.x.shape[0]\n x = coo_matrix(([], ([], [])), shape=(n_obs, 1))\n connectivities = fuzzy_simplicial_set(x, self.n_neighbors, None, None, knn_indices=nn_idx, knn_dists=nn_dist,\n set_op_mix_ratio=1.0, local_connectivity=1.0)\n if isinstance(connectivities, tuple):\n connectivities = connectivities[0]\n return connectivities.tocsr()\n\n\ndef run_neighbors(x, neighbors=30):\n neighbor = Neighbors(x, neighbors)\n nn_idx, nn_dist = neighbor.find_n_neighbors()\n return neighbor, nn_idx, nn_dist\n\n\ndef run_louvain(x, neighbor, nn_idx, nn_dist):\n g = neighbor.get_igraph_from_knn(nn_idx, nn_dist)\n louvain_partition = g.community_multilevel(weights=g.es['weight'], return_levels=False)\n clusters = np.arange(x.shape[0])\n for i in range(len(louvain_partition)):\n clusters[louvain_partition[i]] = str(i)\n return clusters\n\n\ndef run_knn_leiden(x, neighbor, nn_idx, nn_dist, diff=1):\n g = neighbor.get_igraph_from_knn(nn_idx, nn_dist)\n optimiser = la.Optimiser()\n leiden_partition = la.ModularityVertexPartition(g, weights=g.es['weight'])\n while diff > 0:\n diff = optimiser.optimise_partition(leiden_partition, n_iterations=10)\n clusters = np.arange(x.shape[0])\n for i in range(len(leiden_partition)):\n clusters[leiden_partition[i]] = str(i)\n return clusters\n\n\ndef run_cluster(x, method='leiden', do_pca=True, n_pcs=30):\n \"\"\"\n :param x: np.array, shape: (m, n)，m个bin， n为embedding\n :param method:\n :param do_pca:\n :param n_pcs:\n :return:\n \"\"\"\n if do_pca:\n pca_obj = PCA(n_components=n_pcs)\n x = pca_obj.fit_transform(x)\n\n neighbor, nn_idx, nn_dist = run_neighbors(x)\n if method == 'leiden':\n cluster = run_knn_leiden(x, neighbor, nn_idx, nn_dist)\n else:\n cluster = run_louvain(x, neighbor, nn_idx, nn_dist)\n return cluster\n"},{"alpha_fraction":0.5596755146980286,"alphanum_fraction":0.5709463357925415,"avg_line_length":36.02822494506836,"blob_id":"e7cc0ef7656786a8185b9d2de04832ad295a73f2","content_id":"f68ab32909c095d79527096c45e06fecb5e95b9b","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":18936,"license_type":"permissive","max_line_length":158,"num_lines":496,"path":"/stereo/plots/plots.py","repo_name":"leying95/stereopy","src_encoding":"UTF-8","text":"#!/usr/bin/env python3\n# coding: utf-8\n\"\"\"\n@author: Ping Qiu qiuping1@genomics.cn\n@last modified by: Ping Qiu\n@file:plots.py\n@time:2021/03/31\n\"\"\"\nfrom matplotlib.cm import get_cmap\nimport matplotlib.pyplot as plt\nfrom matplotlib.colors import ListedColormap, to_hex, Normalize\nfrom matplotlib import gridspec\nfrom ._plot_basic.get_stereo_data import get_cluster_res, get_reduce_x, get_position_array, get_degs_res\nimport numpy as np\nimport pandas as pd\nfrom anndata import AnnData\nfrom ._plot_basic.scatter_plt import scatter\nimport seaborn\nfrom typing import Optional, Sequence, Union\nfrom matplotlib.axes import Axes\nfrom ._plot_basic.heatmap_plt import heatmap, plot_categories_as_colorblocks, plot_gene_groups_brackets\nfrom ..log_manager import logger\nfrom scipy.sparse import issparse\n\n\ndef plot_spatial_cluster(\n adata: AnnData,\n obs_key: list = [\"phenograph\"],\n pos_key: str = \"spatial\",\n plot_cluster: list = None,\n bad_color: str = \"lightgrey\",\n ncols: int = 2,\n dot_size: int = None,\n color_list=['violet', 'turquoise', 'tomato', 'teal','tan', 'silver', 'sienna', 'red', 'purple', 'plum', 'pink',\n 'orchid', 'orangered', 'orange', 'olive', 'navy', 'maroon', 'magenta', 'lime',\n 'lightgreen', 'lightblue', 'lavender', 'khaki', 'indigo', 'grey', 'green', 'gold', 'fuchsia',\n 'darkgreen', 'darkblue', 'cyan', 'crimson', 'coral', 'chocolate', 'chartreuse', 'brown', 'blue', 'black',\n 'beige', 'azure', 'aquamarine', 'aqua',\n ],\n): # scatter plot, 聚类后表达矩阵空间分布\n \"\"\"\n Plot spatial distribution of specified obs data.\n ============ Arguments ============\n :param adata: AnnData object.\n :param obs_key: specified obs cluster key list, for example: [\"phenograph\"].\n :param pos_key: the coordinates of data points for scatter plots. the data points are stored in adata.obsm[pos_key]. choice: \"spatial\", \"X_umap\", \"X_pca\".\n :param plot_cluster: the name list of clusters to show.\n :param bad_color: the name list of clusters to show.\n :param ncols: numbr of plot columns.\n :param dot_size: marker size.\n :param color_list: whether to invert y-axis.\n ============ Return ============\n None.\n ============ Example ============\n plot_spatial_cluster(adata = adata)\n \"\"\"\n # sc.pl.embedding(adata, basis=\"spatial\", color=[\"total_counts\", \"n_genes_by_counts\"],size=30)\n\n if dot_size is None:\n dot_size = 120000 / adata.shape[0]\n\n ncols = min(ncols, len(obs_key))\n nrows = np.ceil(len(obs_key) / ncols).astype(int)\n # each panel will have the size of rcParams['figure.figsize']\n fig = plt.figure(figsize=(ncols * 10, nrows * 8))\n left = 0.2 / ncols\n bottom = 0.13 / nrows\n axs = gridspec.GridSpec(\n nrows=nrows,\n ncols=ncols,\n left=left,\n right=1 - (ncols - 1) * left - 0.01 / ncols,\n bottom=bottom,\n top=1 - (nrows - 1) * bottom - 0.1 / nrows,\n # hspace=hspace,\n # wspace=wspace,\n )\n\n if color_list is None:\n cmap = get_cmap()\n else:\n cmap = ListedColormap(color_list)\n cmap.set_bad(bad_color)\n # 把特定值改为 np.nan 之后，可以利用 cmap.set_bad(\"white\") 来遮盖掉这部分数据\n\n for i, key in enumerate(obs_key):\n # color_data = adata.obs_vector(key) # TODO replace by get_cluster_res\n color_data = get_cluster_res(adata, data_key=key)\n pc_logic = False\n\n # color_data = np.asarray(color_data_raw, dtype=float)\n order = np.argsort(~pd.isnull(color_data), kind=\"stable\")\n# spatial_data = np.array(adata.obsm[pos_key])[:, 0: 2]\n spatial_data = get_reduce_x(data=adata, data_key=pos_key)[:, 0:2] if pos_key != 'spatial' \\\n else get_position_array(adata, pos_key)\n color_data = color_data[order]\n spatial_data = spatial_data[order, :]\n\n color_dict = {}\n has_na = False\n if pd.api.types.is_categorical_dtype(color_data):\n pc_logic = True\n if plot_cluster is None:\n plot_cluster = list(color_data.categories)\n if pc_logic:\n cluster_n = len(np.unique(color_data))\n if len(color_list) < cluster_n:\n color_list = color_list * cluster_n\n cmap = ListedColormap(color_list)\n cmap.set_bad(bad_color)\n if len(color_data.categories) > len(plot_cluster):\n color_data = color_data.replace(color_data.categories.difference(plot_cluster), np.nan)\n has_na = True\n color_dict = {str(k): to_hex(v) for k, v in enumerate(color_list)}\n print(color_dict)\n color_data = color_data.map(color_dict)\n if pd.api.types.is_categorical_dtype(color_data):\n color_data = pd.Categorical(color_data)\n if has_na:\n color_data = color_data.add_categories([to_hex(bad_color)])\n color_data = color_data.fillna(to_hex(bad_color))\n # color_dict[\"NA\"]\n\n # color_data 是图像中各个点的值，也对应了每个点的颜色。data_points则对应了各个点的坐标\n ax = fig.add_subplot(axs[i]) # ax = plt.subplot(axs[i]) || ax = fig.add_subplot(axs[1, 1]))\n ax.set_title(key)\n ax.set_yticks([])\n ax.set_xticks([])\n ax.set_xlabel(\"spatial1\")\n ax.set_ylabel(\"spatial2\")\n pathcollection = scatter(\n spatial_data[:, 0],\n spatial_data[:, 1],\n ax=ax,\n marker=\".\",\n dot_colors=color_data,\n dot_size=dot_size\n )\n if pc_logic:\n box = ax.get_position()\n ax.set_position([box.x0, box.y0, box.width * 0.91, box.height])\n # -------------modified by qiuping1@genomics.cn-------------\n # valid_cate = color_data.categories\n # cat_num = len(adata.obs_vector(key).categories)\n # for label in adata.obs_vector(key).categories:\n categories = get_cluster_res(adata, data_key=key).categories\n cat_num = len(categories)\n for label in categories:\n # --------modified end------------------\n ax.scatter([], [], c=color_dict[label], label=label)\n ax.legend(\n frameon=False,\n loc='center left',\n bbox_to_anchor=(1, 0.5),\n ncol=(1 if cat_num <= 14 else 2 if cat_num <= 30 else 3),\n # fontsize=legend_fontsize,\n )\n else:\n plt.colorbar(pathcollection, ax=ax, pad=0.01, fraction=0.08, aspect=30)\n ax.autoscale_view()\n\n\ndef plot_violin_distribution(adata): # 小提琴统计图\n \"\"\"\n 绘制数据的分布小提琴图。\n ============ Arguments ============\n :param adata: AnnData object.\n ============ Return ============\n None\n \"\"\"\n _, axs = plt.subplots(1, 3, figsize=(15, 4))\n seaborn.violinplot(y=adata.obs['total_counts'], ax=axs[0])\n seaborn.violinplot(y=adata.obs['n_genes_by_counts'], ax=axs[1])\n seaborn.violinplot(y=adata.obs['pct_counts_mt'], ax=axs[2])\n\n\ndef plot_degs(\n adata: AnnData,\n groups: Union[str, Sequence[str]] = 'all',\n n_genes: int = 20,\n key: Optional[str] = 'find_marker',\n fontsize: int = 8,\n ncols: int = 4,\n sharey: bool = True,\n ax: Optional[Axes] = None,\n **kwds,\n): # scatter plot, 差异基因显著性图，类碎石图\n \"\"\"\n Copied from scanpy and modified.\n \"\"\"\n\n # 调整图像 panel/grid 相关参数\n if 'n_panels_per_row' in kwds:\n n_panels_per_row = kwds['n_panels_per_row']\n else:\n n_panels_per_row = ncols\n # group_names = adata.uns[key]['names'].dtype.names if groups is None else groups\n if groups == 'all':\n group_names = list(adata.uns[key].keys())\n else:\n group_names = [groups] if isinstance(groups, str) else groups\n # one panel for each group\n # set up the figure\n n_panels_x = min(n_panels_per_row, len(group_names))\n n_panels_y = np.ceil(len(group_names) / n_panels_x).astype(int)\n # 初始化图像\n width = 10\n height = 10\n fig = plt.figure(\n figsize=(\n n_panels_x * width, # rcParams['figure.figsize'][0],\n n_panels_y * height, # rcParams['figure.figsize'][1],\n )\n )\n gs = gridspec.GridSpec(nrows=n_panels_y, ncols=n_panels_x, wspace=0.22, hspace=0.3)\n\n ax0 = None\n ymin = np.Inf\n ymax = -np.Inf\n for count, group_name in enumerate(group_names):\n result = get_degs_res(adata, data_key=key, group_key=group_name, top_k=n_genes)\n gene_names = result.genes.values\n scores = result.scores.values\n # Setting up axis, calculating y bounds\n if sharey:\n ymin = min(ymin, np.min(scores))\n ymax = max(ymax, np.max(scores))\n\n if ax0 is None:\n ax = fig.add_subplot(gs[count])\n ax0 = ax\n else:\n ax = fig.add_subplot(gs[count], sharey=ax0)\n else:\n ymin = np.min(scores)\n ymax = np.max(scores)\n ymax += 0.3 * (ymax - ymin)\n\n ax = fig.add_subplot(gs[count])\n ax.set_ylim(ymin, ymax)\n\n ax.set_xlim(-0.9, n_genes - 0.1)\n\n # Making labels\n for ig, gene_name in enumerate(gene_names):\n ax.text(\n ig,\n scores[ig],\n gene_name,\n rotation='vertical',\n verticalalignment='bottom',\n horizontalalignment='center',\n fontsize=fontsize,\n )\n\n ax.set_title(group_name)\n if count >= n_panels_x * (n_panels_y - 1):\n ax.set_xlabel('ranking')\n\n # print the 'score' label only on the first panel per row.\n if count % n_panels_x == 0:\n ax.set_ylabel('score')\n\n if sharey is True:\n ymax += 0.3 * (ymax - ymin)\n ax.set_ylim(ymin, ymax)\n\n\ndef plot_spatial_distribution(\n adata: AnnData,\n obs_key: list = [\"total_counts\", \"n_genes_by_counts\"],\n ncols=2,\n dot_size=None,\n color_list=None,\n invert_y=False\n): # scatter plot, 表达矩阵空间分布\n \"\"\"\n Plot spatial distribution of specified obs data.\n ============ Arguments ============\n :param adata: AnnData object.\n :param obs_key: specified obs key list, for example: [\"total_counts\", \"n_genes_by_counts\"]\n :param ncols: numbr of plot columns.\n :param dot_size: marker size.\n :param color_list: Color list.\n :param invert_y: whether to invert y-axis.\n ============ Return ============\n None\n ============ Example ============\n plot_spatial_distribution(adata=adata)\n \"\"\"\n # sc.pl.embedding(adata, basis=\"spatial\", color=[\"total_counts\", \"n_genes_by_counts\"],size=30)\n\n if dot_size is None:\n dot_size = 120000 / adata.shape[0]\n\n ncols = min(ncols, len(obs_key))\n nrows = np.ceil(len(obs_key) / ncols).astype(int)\n # each panel will have the size of rcParams['figure.figsize']\n fig = plt.figure(figsize=(ncols * 10, nrows * 8))\n left = 0.2 / ncols\n bottom = 0.13 / nrows\n axs = gridspec.GridSpec(\n nrows=nrows,\n ncols=ncols,\n left=left,\n right=1 - (ncols - 1) * left - 0.01 / ncols,\n bottom=bottom,\n top=1 - (nrows - 1) * bottom - 0.1 / nrows,\n # hspace=hspace,\n # wspace=wspace,\n )\n\n if color_list is None:\n cmap = get_cmap()\n else:\n cmap = ListedColormap(color_list)\n # 把特定值改为 np.nan 之后，可以利用 cmap.set_bad(\"white\") 来遮盖掉这部分数据\n\n # 散点图上每个点的坐标数据来自于 adata 的 obsm[\"spatial\"]，每个点的颜色（数值）数据来自于 adata 的 obs_vector()\n for i, key in enumerate(obs_key):\n # color_data = np.asarray(adata.obs_vector(key), dtype=float)\n color_data = adata.obs_vector(key)\n order = np.argsort(~pd.isnull(color_data), kind=\"stable\")\n spatial_data = np.array(adata.obsm[\"spatial\"])[:, 0: 2]\n color_data = color_data[order]\n spatial_data = spatial_data[order, :]\n\n # color_data 是图像中各个点的值，也对应了每个点的颜色。data_points则对应了各个点的坐标\n ax = fig.add_subplot(axs[i]) # ax = plt.subplot(axs[i]) || ax = fig.add_subplot(axs[1, 1]))\n ax.set_title(key)\n ax.set_yticks([])\n ax.set_xticks([])\n ax.set_xlabel(\"spatial1\")\n ax.set_ylabel(\"spatial2\")\n pathcollection = scatter(\n spatial_data[:, 0],\n spatial_data[:, 1],\n ax=ax,\n marker=\".\",\n dot_colors=color_data,\n dot_size=dot_size,\n cmap=cmap,\n )\n plt.colorbar(\n pathcollection,\n ax=ax,\n pad=0.01,\n fraction=0.08,\n aspect=30,\n )\n ax.autoscale_view()\n if invert_y:\n ax.invert_yaxis()\n\n\ndef plot_heatmap_maker_genes(\n adata: AnnData = None,\n cluster_method=\"phenograph\",\n marker_uns_key=None,\n num_show_gene=8,\n show_labels=True,\n order_cluster=True,\n marker_clusters=None,\n cluster_colors_array=None,\n **kwargs\n): # heatmap, 差异基因热图\n \"\"\"\n 绘制 Marker gene 的热图。热图中每一行代表一个 bin 的所有基因的表达量，所有的 bin 会根据所属的 cluster 进行聚集， cluster 具体展示在热图的左侧，用颜色区分。\n ============ Arguments ============\n :param adata: AnnData object.\n :param cluster_method: method used in clustering. for example: phenograph, leiden\n :param marker_uns_key: the key of adata.uns, the default value is \"marker_genes\"\n :param num_show_gene: number of genes to show in each cluster.\n :param show_labels: show gene name on axis.\n :param order_cluster: reorder the cluster list in plot (y axis).\n :param marker_clusters: the list of clusters to show on the heatmap.\n :param cluster_colors_array: the list of colors in the color block on the left of heatmap.\n ============ Return ============\n\n ============ Example ============\n plot_heatmap_maker_genes(adata=adata, marker_uns_key = \"rank_genes_groups\", figsize = (20, 10))\n \"\"\"\n if marker_uns_key is None:\n marker_uns_key = 'marker_genes' # \"rank_genes_groups\" in original scanpy pipeline\n marker_res = adata.uns[marker_uns_key]\n default_cluster = [i for i in marker_res.keys()]\n if marker_clusters is None:\n marker_clusters = default_cluster\n if not set(marker_clusters).issubset(set(default_cluster)):\n marker_clusters = default_cluster\n\n gene_names_dict = {} # dict in which each cluster is the keyand the num_show_gene are the values\n\n for cluster in marker_clusters:\n top_marker = marker_res[cluster].top_k_marker(top_k_genes=num_show_gene, sort_key='scores')\n genes_array = top_marker['genes'].values\n if len(genes_array) == 0:\n logger.warning(\"Cluster {} has no genes.\".format(cluster))\n continue\n gene_names_dict[cluster] = genes_array\n gene_names = []\n gene_group_labels = []\n gene_group_positions = []\n start = 0\n for label, gene_list in gene_names_dict.items():\n if isinstance(gene_list, str):\n gene_list = [gene_list]\n gene_names.extend(list(gene_list))\n gene_group_labels.append(label)\n gene_group_positions.append((start, start + len(gene_list) - 1))\n start += len(gene_list)\n\n # 此处获取所有绘图所需的数据 （表达量矩阵）\n uniq_gene_names = np.unique(gene_names)\n exp_matrix = adata.X.toarray() if issparse(adata.X) else adata.X\n draw_df = pd.DataFrame(exp_matrix[:, adata.var.index.get_indexer(uniq_gene_names)],\n columns=uniq_gene_names, index=adata.obs_names)\n # add obs values\n cluster_data = adata.uns[cluster_method].cluster.set_index('bins')\n draw_df = pd.concat([draw_df, cluster_data], axis=1)\n draw_df = draw_df[gene_names].set_index(draw_df['cluster'].astype('category'))\n if order_cluster:\n draw_df = draw_df.sort_index()\n kwargs.setdefault(\"figsize\", (10, 10))\n kwargs.setdefault(\"colorbar_width\", 0.2)\n colorbar_width = kwargs.get(\"colorbar_width\")\n figsize = kwargs.get(\"figsize\")\n\n cluster_block_width = kwargs.setdefault(\"cluster_block_width\", 0.2) if order_cluster else 0\n if figsize is None:\n height = 6\n if show_labels:\n heatmap_width = len(gene_names) * 0.3\n else:\n heatmap_width = 8\n width = heatmap_width + cluster_block_width\n else:\n width, height = figsize\n heatmap_width = width - cluster_block_width\n\n if gene_group_positions is not None and len(gene_group_positions) > 0:\n # add some space in case 'brackets' want to be plotted on top of the image\n height_ratios = [0.15, height]\n else:\n height_ratios = [0, height]\n\n width_ratios = [\n cluster_block_width,\n heatmap_width,\n colorbar_width,\n ]\n\n fig = plt.figure(figsize=(width, height))\n\n axs = gridspec.GridSpec(\n nrows=2,\n ncols=3,\n width_ratios=width_ratios,\n wspace=0.15 / width,\n hspace=0.13 / height,\n height_ratios=height_ratios,\n )\n\n heatmap_ax = fig.add_subplot(axs[1, 1])\n\n width, height = fig.get_size_inches()\n max_cbar_height = 4.0\n if height > max_cbar_height:\n # to make the colorbar shorter, the\n # ax is split and the lower portion is used.\n axs2 = gridspec.GridSpecFromSubplotSpec(2, 1, subplot_spec=axs[1, 2],\n height_ratios=[height - max_cbar_height, max_cbar_height],\n )\n heatmap_cbar_ax = fig.add_subplot(axs2[1])\n else:\n heatmap_cbar_ax = fig.add_subplot(axs[1, 2])\n\n heatmap(df=draw_df, ax=heatmap_ax,\n norm=Normalize(vmin=None, vmax=None), plot_colorbar=True, colorbar_ax=heatmap_cbar_ax,\n show_labels=True, plot_hline=True)\n\n if order_cluster:\n plot_categories_as_colorblocks(\n fig.add_subplot(axs[1, 0]), draw_df, colors=cluster_colors_array, orientation='left'\n )\n\n # plot cluster legends on top of heatmap_ax (if given)\n if gene_group_positions is not None and len(gene_group_positions) > 0:\n plot_gene_groups_brackets(\n fig.add_subplot(axs[0, 1], sharex=heatmap_ax),\n group_positions=gene_group_positions,\n group_labels=gene_group_labels,\n rotation=None,\n left_adjustment=-0.3,\n right_adjustment=0.3,\n )\n"},{"alpha_fraction":0.6450777053833008,"alphanum_fraction":0.6709844470024109,"avg_line_length":19.3157901763916,"blob_id":"e0b8821e51448972842b0596d7ba29c224772cd5","content_id":"6e56426ee185d43f05f283d62f55808b97650c56","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":386,"license_type":"permissive","max_line_length":53,"num_lines":19,"path":"/stereo/utils/__init__.py","repo_name":"leying95/stereopy","src_encoding":"UTF-8","text":"#!/usr/bin/env python3\n# coding: utf-8\n\"\"\"\n@author: Ping Qiu qiuping1@genomics.cn\n@last modified by: Ping Qiu\n@file:__init__.py.py\n@time:2021/03/05\n\"\"\"\nimport shutil\nimport os\nfrom .correlation import pearson_corr, spearmanr_corr\nfrom .data_helper import select_group\n\n\ndef remove_file(path):\n if os.path.isfile(path):\n os.remove(path)\n if os.path.isdir(path):\n shutil.rmtree(path)\n"},{"alpha_fraction":0.6289620995521545,"alphanum_fraction":0.6656308174133301,"avg_line_length":31.836734771728516,"blob_id":"929008472630fdf635cba821106fb912cf41f0c5","content_id":"d99b946e6893eb24287dce6f23965fb054385454","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1609,"license_type":"permissive","max_line_length":112,"num_lines":49,"path":"/stereo/utils/correlation.py","repo_name":"leying95/stereopy","src_encoding":"UTF-8","text":"#!/usr/bin/env python3\n# coding: utf-8\n\"\"\"\n@author: Ping Qiu qiuping1@genomics.cn\n@last modified by: Ping Qiu\n@file:correlation.py\n@time:2021/03/11\n\"\"\"\nimport numpy as np\nimport pandas as pd\nfrom scipy import stats\n\n\ndef pearson(arr1, arr2):\n \"\"\"\n calculate pearson correlation between two numpy arrays.\n :param arr1: one array, the feature is a column. the shape is `m * n`\n :param arr2: the other array, the feature is a column. the shape is `m * k`\n :return: a pearson score np.array , the shape is `k * n`\n \"\"\"\n assert arr1.shape[0] == arr2.shape[0]\n n = arr1.shape[0]\n sums = np.multiply.outer(arr2.sum(0), arr1.sum(0))\n stds = np.multiply.outer(arr2.std(0), arr1.std(0))\n return (arr2.T.dot(arr1) - sums / n) / stds / n\n\n\ndef pearson_corr(df1, df2):\n \"\"\"\n calculate pearson correlation between two dataframes.\n :param df1: one dataframe\n :param df2: the other dataframe\n :return: a pearson score dataframe, the index is the columns of `df1`, the columns is the columns of `df2`\n \"\"\"\n v1, v2 = df1.values, df2.values\n corr_matrix = pearson(v1, v2)\n return pd.DataFrame(corr_matrix, df2.columns, df1.columns)\n\n\ndef spearmanr_corr(df1, df2):\n \"\"\"\n calculate pearson correlation between two dataframes.\n :param df1: one dataframe\n :param df2: the other dataframe\n :return: a spearmanr score dataframe, the index is the columns of `df1`, the columns is the columns of `df2`\n \"\"\"\n score, pvalue = stats.spearmanr(df1.values, df2.values)\n score = score[df1.shape[1]:, 0:df1.shape[1]]\n return pd.DataFrame(score, df2.columns, df1.columns)\n"},{"alpha_fraction":0.5926466584205627,"alphanum_fraction":0.5964400172233582,"avg_line_length":35.07368469238281,"blob_id":"88d22d27b7f2d3e25e5c1a50cc04b09fd00b9a0c","content_id":"dd127ef9b878183a451a018bf664e3130c5144eb","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":3427,"license_type":"permissive","max_line_length":118,"num_lines":95,"path":"/stereo/core/stereo_result.py","repo_name":"leying95/stereopy","src_encoding":"UTF-8","text":"#!/usr/bin/env python3\n# coding: utf-8\n\"\"\"\n@author: Ping Qiu qiuping1@genomics.cn\n@last modified by: Ping Qiu\n@file:stereo_result.py\n@time:2021/03/18\n\"\"\"\nfrom typing import Optional\nimport numpy as np\nimport pandas as pd\nfrom ..log_manager import logger\n\n\nclass StereoResult(object):\n def __init__(self, name: str = 'stereo', param: Optional[dict] = None):\n self.name = name\n self.params = {} if param is None else param\n\n def update_params(self, v):\n self.params = v\n\n def __str__(self):\n class_info = f'{self.__class__.__name__} of {self.name}. \\n'\n class_info += f' params: {self.params}\\n'\n return class_info\n\n def __repr__(self):\n return self.__str__()\n\n\nclass DimReduceResult(StereoResult):\n def __init__(self, name: str = 'dim_reduce', param: Optional[dict] = None, x_reduce: Optional[np.ndarray] = None,\n variance_pca: Optional[np.ndarray] = None, variance_ratio: Optional[np.ndarray] = None,\n pcs: Optional[np.ndarray] = None):\n super(DimReduceResult, self).__init__(name, param)\n self.x_reduce = x_reduce\n self.variance_pca = variance_pca\n self.variance_ratio = variance_ratio\n self.pcs = pcs\n\n\nclass FindMarkerResult(StereoResult):\n def __init__(self, name: str = 'find_marker', param: Optional[dict] = None,\n degs_data: Optional[pd.DataFrame] = None):\n super(FindMarkerResult, self).__init__(name, param)\n self.degs_data = degs_data\n\n def __str__(self):\n info = super(FindMarkerResult, self).__str__()\n if self.degs_data is not None:\n info += f' result: a DataFrame which has `genes`,`pvalues`,`pvalues_adj`, `log2fc`, `score` columns.\\n'\n info += f' the shape is: {self.degs_data.shape}'\n return info\n\n def top_k_marker(self, top_k_genes=10, sort_key='pvalues', ascend=False):\n \"\"\"\n obtain the first k significantly different genes\n :param top_k_genes: the number of top k\n :param sort_key: sort by the column\n :param ascend: the ascend order of sorting.\n :return:\n \"\"\"\n if self.degs_data is not None:\n top_k_data = self.degs_data.sort_values(by=sort_key, ascending=ascend).head(top_k_genes)\n return top_k_data\n else:\n logger.warning('the result of degs is None, return None.')\n return None\n\n\nclass CellTypeResult(StereoResult):\n def __init__(self, name='cell_type_anno', param=None, anno_data=None):\n super(CellTypeResult, self).__init__(name=name, param=param)\n self.anno_data = anno_data\n\n def __str__(self):\n info = super(CellTypeResult, self).__str__()\n if self.anno_data is not None:\n info += f' result: a DataFrame which has `cells`,`cell type`,`corr_score` columns.\\n'\n info += f' the shape is: {self.anno_data.shape}'\n return info\n\n\nclass ClusterResult(StereoResult):\n def __init__(self, name='cluster', param=None, cluster_info=None):\n super(ClusterResult, self).__init__(name=name, param=param)\n self.cluster = cluster_info\n\n def __str__(self):\n info = super(ClusterResult, self).__str__()\n if self.cluster is not None:\n info += f' result: a DataFrame which has `cells`,`cluster` columns.\\n'\n info += f' the shape is: {self.cluster.shape}'\n return info\n"},{"alpha_fraction":0.5367646813392639,"alphanum_fraction":0.6102941036224365,"avg_line_length":16,"blob_id":"91821cce15c5c57d0d9f7879ebe521c065656519","content_id":"726bfa3d8ddd4c38dd355f36eb882616ac52e353","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":136,"license_type":"permissive","max_line_length":25,"num_lines":8,"path":"/stereo/core/__init__.py","repo_name":"leying95/stereopy","src_encoding":"UTF-8","text":"#!/usr/bin/env python3\n# coding: utf-8\n\"\"\"\n@author: Ping Qiu qiuping1@genomics.cn\n@last modified by: Ping Qiu\n@file:__init__.py.py\n@time:2021/03/17\n\"\"\"\n"},{"alpha_fraction":0.5546501278877258,"alphanum_fraction":0.5627103447914124,"avg_line_length":31.63005828857422,"blob_id":"c3432564975ba70a1548330bb225b99d38d4b4bf","content_id":"050413ffad7b852cc1e8d0feae37c28313c3be0a","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":11290,"license_type":"permissive","max_line_length":101,"num_lines":346,"path":"/stereo/plots/_plot_basic/heatmap_plt.py","repo_name":"leying95/stereopy","src_encoding":"UTF-8","text":"#!/usr/bin/env python3\n# coding: utf-8\n\"\"\"\n@author: Shixu He heshixu@genomics.cn\n@last modified by: Shixu He\n@file:heatmap_plt.py\n@time:2021/03/15\n\"\"\"\n\nfrom matplotlib.cm import get_cmap\nfrom matplotlib.axes import Axes\nimport matplotlib.pyplot as plt\nfrom matplotlib.colors import Normalize\nfrom matplotlib import gridspec\n\nfrom anndata import AnnData\nimport numpy as np\nimport pandas as pd\n\nfrom typing import List, Iterable, Sequence, Optional, Tuple\nfrom typing_extensions import Literal\n\nfrom ...log_manager import logger\n\n\ndef heatmap(df: pd.DataFrame = None, ax: Axes = None, cmap=None, norm=None, plot_colorbar=False,\n colorbar_ax: Axes = None, show_labels=True, plot_hline=False, **kwargs):\n \"\"\"\n :param df:\n :param ax:\n :param cmap:\n :param norm:\n :param plot_colorbar:\n :param colorbar_ax:\n :param show_labels:\n :param plot_hline:\n :param kwargs:\n :return:\n \"\"\"\n\n if norm == None:\n norm = Normalize(vmin=None, vmax=None)\n if (plot_colorbar and colorbar_ax == None):\n logger.warning(\"Colorbar ax is not provided.\")\n plot_colorbar = False\n\n kwargs.setdefault('interpolation', 'nearest')\n\n im = ax.imshow(df.values, aspect='auto', norm=norm, **kwargs)\n\n ax.set_ylim(df.shape[0] - 0.5, -0.5)\n ax.set_xlim(-0.5, df.shape[1] - 0.5)\n ax.tick_params(axis='y', left=False, labelleft=False)\n ax.set_ylabel('')\n ax.grid(False)\n\n if show_labels:\n ax.tick_params(axis='x', labelsize='small')\n ax.set_xticks(np.arange(df.shape[1]))\n ax.set_xticklabels(list(df.columns), rotation=90)\n else:\n ax.tick_params(axis='x', labelbottom=False, bottom=False)\n\n if plot_colorbar:\n plt.colorbar(im, cax=colorbar_ax)\n\n if plot_hline:\n line_coord = (\n np.cumsum(df.index.value_counts(sort=False))[:-1] - 0.5\n )\n ax.hlines(\n line_coord,\n -0.5,\n df.shape[1] - 0.5,\n lw=1,\n color='black',\n zorder=10,\n clip_on=False,\n )\n\n\ndef plot_categories_as_colorblocks(\n groupby_ax: Axes,\n obs_tidy: pd.DataFrame,\n colors=None,\n orientation: Literal['top', 'bottom', 'left', 'right'] = 'left',\n cmap_name: str = 'tab20',\n):\n \"\"\"from scanpy\"\"\"\n\n groupby = obs_tidy.index.name\n from matplotlib.colors import ListedColormap, BoundaryNorm\n\n if colors is None:\n groupby_cmap = plt.get_cmap(cmap_name)\n else:\n groupby_cmap = ListedColormap(colors, groupby + '_cmap')\n norm = BoundaryNorm(np.arange(groupby_cmap.N + 1) - 0.5, groupby_cmap.N)\n\n # determine groupby label positions such that they appear\n # centered next/below to the color code rectangle assigned to the category\n value_sum = 0\n ticks = [] # list of centered position of the labels\n labels = []\n label2code = {} # dictionary of numerical values asigned to each label\n for code, (label, value) in enumerate(\n obs_tidy.index.value_counts(sort=False).iteritems()\n ):\n ticks.append(value_sum + (value / 2))\n labels.append(label)\n value_sum += value\n label2code[label] = code\n\n groupby_ax.grid(False)\n\n if orientation == 'left':\n groupby_ax.imshow(\n np.array([[label2code[lab] for lab in obs_tidy.index]]).T,\n aspect='auto',\n cmap=groupby_cmap,\n norm=norm,\n )\n if len(labels) > 1:\n groupby_ax.set_yticks(ticks)\n groupby_ax.set_yticklabels(labels)\n\n # remove y ticks\n groupby_ax.tick_params(axis='y', left=False, labelsize='small')\n # remove x ticks and labels\n groupby_ax.tick_params(axis='x', bottom=False, labelbottom=False)\n\n # remove surrounding lines\n groupby_ax.spines['right'].set_visible(False)\n groupby_ax.spines['top'].set_visible(False)\n groupby_ax.spines['left'].set_visible(False)\n groupby_ax.spines['bottom'].set_visible(False)\n\n groupby_ax.set_ylabel(groupby)\n else:\n groupby_ax.imshow(\n np.array([[label2code[lab] for lab in obs_tidy.index]]),\n aspect='auto',\n cmap=groupby_cmap,\n norm=norm,\n )\n if len(labels) > 1:\n groupby_ax.set_xticks(ticks)\n if max([len(str(x)) for x in labels]) < 3:\n # if the labels are small do not rotate them\n rotation = 0\n else:\n rotation = 90\n groupby_ax.set_xticklabels(labels, rotation=rotation)\n\n # remove x ticks\n groupby_ax.tick_params(axis='x', bottom=False, labelsize='small')\n # remove y ticks and labels\n groupby_ax.tick_params(axis='y', left=False, labelleft=False)\n\n # remove surrounding lines\n groupby_ax.spines['right'].set_visible(False)\n groupby_ax.spines['top'].set_visible(False)\n groupby_ax.spines['left'].set_visible(False)\n groupby_ax.spines['bottom'].set_visible(False)\n\n groupby_ax.set_xlabel(groupby)\n\n return label2code, ticks, labels, groupby_cmap, norm\n\n\ndef plot_gene_groups_brackets(\n gene_groups_ax: Axes,\n group_positions: Iterable[Tuple[int, int]],\n group_labels: Sequence[str],\n left_adjustment: float = -0.3,\n right_adjustment: float = 0.3,\n rotation: Optional[float] = None,\n orientation: Literal['top', 'right'] = 'top',\n):\n \"\"\"from scanpy\"\"\"\n import matplotlib.patches as patches\n from matplotlib.path import Path\n\n # get the 'brackets' coordinates as lists of start and end positions\n\n left = [x[0] + left_adjustment for x in group_positions]\n right = [x[1] + right_adjustment for x in group_positions]\n\n # verts and codes are used by PathPatch to make the brackets\n verts = []\n codes = []\n if orientation == 'top':\n # rotate labels if any of them is longer than 4 characters\n if rotation is None and group_labels:\n if max([len(x) for x in group_labels]) > 4:\n rotation = 90\n else:\n rotation = 0\n for idx in range(len(left)):\n verts.append((left[idx], 0)) # lower-left\n verts.append((left[idx], 0.6)) # upper-left\n verts.append((right[idx], 0.6)) # upper-right\n verts.append((right[idx], 0)) # lower-right\n\n codes.append(Path.MOVETO)\n codes.append(Path.LINETO)\n codes.append(Path.LINETO)\n codes.append(Path.LINETO)\n\n try:\n group_x_center = left[idx] + float(right[idx] - left[idx]) / 2\n gene_groups_ax.text(\n group_x_center,\n 1.1,\n group_labels[idx],\n ha='center',\n va='bottom',\n rotation=rotation,\n )\n except:\n pass\n else:\n top = left\n bottom = right\n for idx in range(len(top)):\n verts.append((0, top[idx])) # upper-left\n verts.append((0.15, top[idx])) # upper-right\n verts.append((0.15, bottom[idx])) # lower-right\n verts.append((0, bottom[idx])) # lower-left\n\n codes.append(Path.MOVETO)\n codes.append(Path.LINETO)\n codes.append(Path.LINETO)\n codes.append(Path.LINETO)\n\n try:\n diff = bottom[idx] - top[idx]\n group_y_center = top[idx] + float(diff) / 2\n if diff * 2 < len(group_labels[idx]):\n # cut label to fit available space\n group_labels[idx] = group_labels[idx][: int(diff * 2)] + \".\"\n gene_groups_ax.text(\n 0.6,\n group_y_center,\n group_labels[idx],\n ha='right',\n va='center',\n rotation=270,\n fontsize='small',\n )\n except Exception as e:\n print('problems {}'.format(e))\n pass\n\n path = Path(verts, codes)\n\n patch = patches.PathPatch(path, facecolor='none', lw=1.5)\n\n gene_groups_ax.add_patch(patch)\n gene_groups_ax.grid(False)\n gene_groups_ax.axis('off')\n # remove y ticks\n gene_groups_ax.tick_params(axis='y', left=False, labelleft=False)\n # remove x ticks and labels\n gene_groups_ax.tick_params(\n axis='x', bottom=False, labelbottom=False, labeltop=False\n )\n\n\ndef _check_indices(\n dim_df: pd.DataFrame,\n alt_index: pd.Index,\n dim: \"Literal['obs', 'var']\",\n keys: List[str],\n alias_index: pd.Index = None,\n use_raw: bool = False,\n):\n \"\"\"from scanpy\"\"\"\n if use_raw:\n alt_repr = \"adata.raw\"\n else:\n alt_repr = \"adata\"\n\n alt_dim = (\"obs\", \"var\")[dim == \"obs\"]\n\n alias_name = None\n if alias_index is not None:\n alt_names = pd.Series(alt_index, index=alias_index)\n alias_name = alias_index.name\n alt_search_repr = f\"{alt_dim}['{alias_name}']\"\n else:\n alt_names = pd.Series(alt_index, index=alt_index)\n alt_search_repr = f\"{alt_dim}_names\"\n\n col_keys = []\n index_keys = []\n index_aliases = []\n not_found = []\n\n # check that adata.obs does not contain duplicated columns\n # if duplicated columns names are present, they will\n # be further duplicated when selecting them.\n if not dim_df.columns.is_unique:\n dup_cols = dim_df.columns[dim_df.columns.duplicated()].tolist()\n raise ValueError(\n f\"adata.{dim} contains duplicated columns. Please rename or remove \"\n \"these columns first.\\n`\"\n f\"Duplicated columns {dup_cols}\"\n )\n\n if not alt_index.is_unique:\n raise ValueError(\n f\"{alt_repr}.{alt_dim}_names contains duplicated items\\n\"\n f\"Please rename these {alt_dim} names first for example using \"\n f\"`adata.{alt_dim}_names_make_unique()`\"\n )\n\n # use only unique keys, otherwise duplicated keys will\n # further duplicate when reordering the keys later in the function\n for key in np.unique(keys):\n if key in dim_df.columns:\n col_keys.append(key)\n if key in alt_names.index:\n raise KeyError(\n f\"The key '{key}' is found in both adata.{dim} and {alt_repr}.{alt_search_repr}.\"\n )\n elif key in alt_names.index:\n val = alt_names[key]\n if isinstance(val, pd.Series):\n # while var_names must be unique, adata.var[gene_symbols] does not\n # It's still ambiguous to refer to a duplicated entry though.\n assert alias_index is not None\n raise KeyError(\n f\"Found duplicate entries for '{key}' in {alt_repr}.{alt_search_repr}.\"\n )\n index_keys.append(val)\n index_aliases.append(key)\n else:\n not_found.append(key)\n if len(not_found) > 0:\n raise KeyError(\n f\"Could not find keys '{not_found}' in columns of `adata.{dim}` or in\"\n f\" {alt_repr}.{alt_search_repr}.\"\n )\n\n return col_keys, index_keys, index_aliases\n"}],"string":"[\n {\n \"alpha_fraction\": 0.40083393454551697,\n \"alphanum_fraction\": 0.5601885318756104,\n \"avg_line_length\": 25.257143020629883,\n \"blob_id\": \"7bd2f370968ac513aa8f45d4b85f38dba0a2b29f\",\n \"content_id\": \"e13c71464e3fbf9b2020ffb3cba140cc0bc8926e\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 6558,\n \"license_type\": \"permissive\",\n \"max_line_length\": 199,\n \"num_lines\": 210,\n \"path\": \"/stereo/plots/plot_data_description.md\",\n \"repo_name\": \"leying95/stereopy\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# 绘图数据需求\\n\\n以 AnnData 为参照获取对应的输入数据\\n\\n## plot_spatial_distribution\\n\\n### 所需 AnnData 数据：\\n\\n- 图像坐标信息： \\n - `spatial_data = np.array(adata.obsm[\\\"spatial\\\"])`\\n\\n- 图像散点数值信息： \\n - `color_data = np.array(adata.obs_vector(key))`\\n - 其中 key 为散点所需呈现的数据种类，如 total_counts, n_genes_by_counts，可利用的数据种类都在 `adata.obs.keys()`\\n\\n### 实际所需数据格式：\\n\\n- 图像坐标信息demo：\\n \\n ```Text\\n array([[ 256, -91],[ 185, -157],[ 257, -288],...,[ 151, -246],[ 290, -141],[ 177, -132]])\\n ```\\n\\n- 图像散点数值信息demo：\\n \\n ```Text\\n array([3582., 1773., 2283., ..., 4062., 4371., 1172.], dtype=float32)\\n ```\\n\\n其中散点数值和坐标信息一一对应\\n\\n## plot_spatial_cluster && plot_cluster_umap\\n\\n这两个函数整合成了 plot_cluster_result，区别在于所用的 spatial data （pos_key） 不同， plot_spatial_cluster 使用的是 spatial 空间数据，plot_cluster_umap 使用的是 X_umap 的主成分值数据\\n\\n### 所需 AnnData 数据：\\n\\n- 图像坐标信息： \\n - `spatial_data = np.array(adata.obsm[pos_key])`\\n\\n- 图像散点数值信息： \\n - `color_data = np.array(adata.obs_vector(key))`\\n - 其中 key 为散点所需呈现的数据种类，可利用的数据种类都在 adata.obs.keys()，此处用到的主要是聚类相关数据，如 [\\\"phenograph\\\", \\\"leiden\\\"]\\n - 在 cluster 相关的图像中，散点数据属于 categorical 数据\\n\\n### 实际所需数据格式：\\n\\n- 图像坐标信息demo：\\n \\n spatial:\\n\\n ```Text\\n array([[ 256, -91],[ 185, -157],[ 257, -288],...,[ 151, -246],[ 290, -141],[ 177, -132]])\\n ```\\n\\n umap：\\n \\n ```Text\\n array([[-2.234908 , 3.7087667 ], [ 3.7431364 , 2.003201 ], [ 4.849478 , -0.21215418], ..., [ 6.861894 , 1.7589074 ], [-0.4605783 , 4.0366364 ], [ 7.3391566 , -0.40746352]], dtype=float32)\\n ```\\n\\n- 图像散点数值信息demo：\\n \\n ```Text\\n ['0', '3', '5', '3', '2', ..., '4', '3', '6', '1', '5']\\n Length: 22726\\n Categories (10, object): ['0', '1', '2', '3', ..., '6', '7', '8', '9']\\n ```\\n\\n其中散点数值和坐标信息一一对应\\n\\n\\n## plot_to_select_filter_value\\n\\n### 所需 AnnData 数据\\n\\n- `x = adata.obs_vector(var1)`\\n- `y = adata.obs_vector(var2)`\\n\\nvar1 var2 可以是任意两个 obs_key 中的值\\n\\n### 实际所需数据格式\\n\\n```Text\\narray([3582., 1773., 2283., ..., 4062., 4371., 1172.], dtype=float32)\\n```\\n\\n## plot_variable_gene\\n\\n### 所需 AnnData 数据：\\n\\n- `adata.var.highly_variable`\\n- `adata.var.means`\\n- `adata.var.dispersions`\\n- `adata.var.dispersions_norm`\\n\\n### 实际所需数据格式\\n\\npandas.core.series.Series\\n\\n例如： adata.var.means:\\n\\n```Text\\nAL355102.2 0.012042\\nSLC25A2 0.000596\\n ... \\nAC069214.1 0.009608\\nAL356056.1 0.001655\\nName: means, Length: 33304, dtype: float64\\n```\\n\\n## plot_expression_difference\\n\\n### 所需 AnnData 数据\\n\\n- 聚类得到的类名： `group_names = adata.uns[\\\"rank_genes_groups\\\"]['names'].dtype.names`\\n- 在各个类名（group_name in group_names）的基础上获取各个类的基因列表('names')和分数('scores')：\\n - `gene_names = adata.uns[\\\"rank_genes_groups\\\"]['names'][group_name][:number_of_gene_to_show]`\\n - `scores = adata.uns[\\\"rank_genes_groups\\\"]['scores'][group_name][:number_of_gene_to_show]`\\n\\n### 实际所需数据格式：\\n\\n- 聚类得到的类名：\\n\\n ```Text\\n tuple('0', '1', '2', '3', '4', '5', '6', '7', '8', '9')\\n ```\\n- 各个类名对应的基因列表和分数列表：\\n \\n ```Text\\n numpy.ndarray\\n \\n array(['TUBB4B', 'SLC12A2', 'EPHB3', ..., 'TFF3', 'TIMP1', 'OLFM4'],\\n dtype=object)\\n \\n array([ 28.094688, 27.638664, 24.523687, ..., -41.63738 , -42.894638, -48.384773], dtype=float32)\\n ```\\n\\n## plot_violin_distribution\\n\\n### 所需 AnnData 数据\\n\\n- `adata.obs['total_counts']`\\n- `adata.obs['n_genes_by_counts']`\\n- `adata.obs['pct_counts_mt']`\\n\\n### 实际所需数据格式\\n\\npandas.core.series.Series\\n\\n例如： total_counts:\\n\\n```Text\\n256-91 3582.0\\n185-157 1773.0\\n ... \\n290-141 4371.0\\n177-132 1172.0\\nName: total_counts, Length: 22726, dtype: float32\\n```\\n\\n## plot_heatmap_maker_genes\\n\\n### 所需 AnnData 数据：\\n\\n- 聚类得到的类名： `marker_clusters = adata.uns[\\\"rank_genes_groups\\\"]['names'].dtype.names`\\n- 在各个类名（cluster in marker_clusters）的基础上获取各个类的基因列表('names'):\\n - `genes_array = adata.uns[\\\"rank_genes_groups\\\"]['names'][group_name][:number_of_gene_to_show]`\\n- 设定表达量矩阵（热图矩阵）\\n - 矩阵index： `adata.obs_name`\\n - 整合各个类的基因列表，获取 uniq gene list，然后获取这些uniq gene 的表达量来构建 pandas.DataFrame\\n - 表达量： `exp_matrix = adata.X[tuple([slice(None), adata.var.index.get_indexer(uniq_gene_names)])]`\\n - pd.DataFrame: `pd.DataFrame(exp_matrix, columns=uniq_gene_names, index=adata.obs_names)`\\n - 添加 obs 列在最开头： `pd.concat([draw_df, adata.obs[cluster_method]], axis=1)`\\n \\n\\n### 实际所需数据格式：\\n\\n- 聚类得到的类名：\\n\\n ```Text\\n tuple('0', '1', '2', '3', '4', '5', '6', '7', '8', '9')\\n ```\\n\\n- 各个类名对应的基因列表：\\n \\n ```Text\\n numpy.ndarray\\n \\n array(['TUBB4B', 'SLC12A2', 'EPHB3', ..., 'TFF3', 'TIMP1', 'OLFM4'],\\n dtype=object)\\n ```\\n\\n- 表达量矩阵最终效果：\\n \\n ```Text\\n TUBB4B SLC12A2 EPHB3 MT-ND1 FTX NAALADL2 \\n phenograph \\n 0 3.758313 1.884562 2.705292 4.040148 2.498723 2.238069 \\n 0 3.118562 1.224227 1.758388 3.311160 1.758388 0.000000 \\n 0 2.790583 0.000000 0.000000 3.175375 0.000000 0.000000 \\n 0 0.000000 1.885036 1.885036 3.821939 0.000000 0.000000 \\n 0 2.596922 0.000000 2.596922 3.644590 2.596922 2.596922 \\n ... ... ... ... ... ... ... \\n 9 3.172084 1.570598 0.000000 4.186041 1.570598 0.000000 \\n 9 0.000000 1.847625 0.000000 3.893912 0.000000 2.458688 \\n 9 2.681648 2.681648 0.000000 3.339970 1.314215 1.314215 \\n 9 1.955572 1.955572 0.000000 3.229691 1.955572 0.000000 \\n 9 2.963927 1.721601 1.721601 3.176694 1.721601 0.000000 \\n ```\\n\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.5407407283782959,\n \"alphanum_fraction\": 0.614814817905426,\n \"avg_line_length\": 15.875,\n \"blob_id\": \"6be96570692f13225dce46515d9ca9c98fef1296\",\n \"content_id\": \"0a956633adf2311ac4c74e39451ffd2cbcbd1029\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 135,\n \"license_type\": \"permissive\",\n \"max_line_length\": 25,\n \"num_lines\": 8,\n \"path\": \"/stereo/plots/_plot_basic/__init__.py\",\n \"repo_name\": \"leying95/stereopy\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#!/usr/bin/env python3\\n# coding: utf-8\\n\\\"\\\"\\\"\\n@author: Shixu He heshixu@genomics.cn\\n@last modified by: Shixu He\\n@file:__init__.py.py\\n@time:2021/03/15\\n\\\"\\\"\\\"\\n\"\n },\n {\n \"alpha_fraction\": 0.8245614171028137,\n \"alphanum_fraction\": 0.8245614171028137,\n \"avg_line_length\": 27.5,\n \"blob_id\": \"07e56b8199fa5930875326eee974fd0b94d0cbaa\",\n \"content_id\": \"a08af99a95386dcc9a13b89532990ab6cd210c1f\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 57,\n \"license_type\": \"permissive\",\n \"max_line_length\": 45,\n \"num_lines\": 2,\n \"path\": \"/README.md\",\n \"repo_name\": \"leying95/stereopy\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# stereopy\\nA toolkit of spatial transcriptomic analysis.\\n\"\n },\n {\n \"alpha_fraction\": 0.576362669467926,\n \"alphanum_fraction\": 0.582298994064331,\n \"avg_line_length\": 30.94827651977539,\n \"blob_id\": \"da5efc016b2d7c7a1cc9131a627d2377e1ae0157\",\n \"content_id\": \"66c073cd335fd0fa657926a18e9d780efb70e29a\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1853,\n \"license_type\": \"permissive\",\n \"max_line_length\": 78,\n \"num_lines\": 58,\n \"path\": \"/stereo/log_manager.py\",\n \"repo_name\": \"leying95/stereopy\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#!/usr/bin/env python3\\n# coding: utf-8\\n\\\"\\\"\\\"\\n@author: Ping Qiu qiuping1@genomics.cn\\n@last modified by: Ping Qiu\\n@file:log_manager.py\\n@time:2021/03/05\\n\\\"\\\"\\\"\\n\\nimport logging\\nfrom .config import stereo_conf\\n\\n\\nclass LogManager(object):\\n def __init__(self, log_path=None, level=None):\\n self.level_map = {'debug': logging.DEBUG,\\n 'info': logging.INFO,\\n 'warning': logging.WARNING,\\n 'error': logging.ERROR,\\n 'critical': logging.CRITICAL}\\n self.format = stereo_conf.log_format\\n self.formatter = logging.Formatter(self.format, \\\"%Y-%m-%d %H:%M:%S\\\")\\n self.log_path = log_path\\n self.level = level.lower() if level else stereo_conf.log_level.lower()\\n if self.log_path:\\n self.file_handler = logging.FileHandler(self.log_path)\\n self.file_handler.setLevel(self.level_map[self.level])\\n self.file_handler.setFormatter(self.formatter)\\n else:\\n self.stream_handler = logging.StreamHandler()\\n self.stream_handler.setLevel(self.level_map[self.level])\\n self.stream_handler.setFormatter(self.formatter)\\n\\n def get_logger(self, name=\\\"Spateo\\\"):\\n \\\"\\\"\\\"\\n get logger object\\n :param name: logger name\\n :return: logger object\\n \\\"\\\"\\\"\\n alogger = logging.getLogger(name)\\n alogger.propagate = 0\\n alogger.setLevel(self.level_map[self.level])\\n self._add_handler(alogger)\\n return alogger\\n\\n def _add_handler(self, alogger):\\n \\\"\\\"\\\"\\n add handler of logger\\n :param logger: logger object\\n :return:\\n \\\"\\\"\\\"\\n if self.log_path:\\n alogger.addHandler(self.file_handler)\\n else:\\n alogger.addHandler(self.stream_handler)\\n\\n\\nlogger = LogManager().get_logger(name='Spateo')\\n\"\n },\n {\n \"alpha_fraction\": 0.5441176295280457,\n \"alphanum_fraction\": 0.5572336912155151,\n \"avg_line_length\": 34.42253494262695,\n \"blob_id\": \"223b8ada9eb9f510c9b68f7895d4f42a65b81f8e\",\n \"content_id\": \"0299148833875c5536949e7ad7ae0d0f9b9dafff\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 2516,\n \"license_type\": \"permissive\",\n \"max_line_length\": 117,\n \"num_lines\": 71,\n \"path\": \"/stereo/tools/neighbors.py\",\n \"repo_name\": \"leying95/stereopy\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#!/usr/bin/env python3\\n# coding: utf-8\\n\\\"\\\"\\\"\\n@author: Ping Qiu qiuping1@genomics.cn\\n@last modified by: Ping Qiu\\n@file:neighbors.py\\n@time:2021/03/23\\n\\\"\\\"\\\"\\nfrom scipy.sparse import coo_matrix\\nfrom sklearn.neighbors import NearestNeighbors\\nimport igraph as ig\\nimport numpy as np\\nfrom umap.umap_ import fuzzy_simplicial_set\\n\\n\\nclass Neighbors(object):\\n def __init__(self, x, n_neighbors):\\n self.x = x\\n self.n_neighbors = n_neighbors\\n\\n def find_n_neighbors(self):\\n nbrs = NearestNeighbors(n_neighbors=self.n_neighbors + 1, algorithm='ball_tree').fit(self.x)\\n dists, indices = nbrs.kneighbors(self.x)\\n nn_idx = indices[:, 1:]\\n nn_dist = dists[:, 1:]\\n return nn_idx, nn_dist\\n\\n def get_igraph_from_knn(self, nn_idx, nn_dist):\\n j = nn_idx.ravel().astype(int)\\n dist = nn_dist.ravel()\\n i = np.repeat(np.arange(nn_idx.shape[0]), self.n_neighbors)\\n\\n vertex = list(range(nn_dist.shape[0]))\\n edges = list(tuple(zip(i, j)))\\n G = ig.Graph()\\n G.add_vertices(vertex)\\n G.add_edges(edges)\\n G.es['weight'] = dist\\n return G\\n\\n def get_parse_distances(self, nn_idx, nn_dist):\\n n_obs = self.x.shape[0]\\n rows = np.zeros((n_obs * self.n_neighbors), dtype=np.int64)\\n cols = np.zeros((n_obs * self.n_neighbors), dtype=np.int64)\\n vals = np.zeros((n_obs * self.n_neighbors), dtype=np.float64)\\n\\n for i in range(nn_idx.shape[0]):\\n for j in range(self.n_neighbors):\\n if nn_idx[i, j] == -1:\\n continue # We didn't get the full knn for i\\n if nn_idx[i, j] == i:\\n val = 0.0\\n else:\\n val = nn_dist[i, j]\\n\\n rows[i * self.n_neighbors + j] = i\\n cols[i * self.n_neighbors + j] = nn_idx[i, j]\\n vals[i * self.n_neighbors + j] = val\\n\\n distances = coo_matrix((vals, (rows, cols)), shape=(n_obs, n_obs))\\n distances.eliminate_zeros()\\n return distances.tocsr()\\n\\n def get_connectivities(self, nn_idx, nn_dist):\\n n_obs = self.x.shape[0]\\n x = coo_matrix(([], ([], [])), shape=(n_obs, 1))\\n connectivities = fuzzy_simplicial_set(x, self.n_neighbors, None, None, knn_indices=nn_idx, knn_dists=nn_dist,\\n set_op_mix_ratio=1.0, local_connectivity=1.0)\\n if isinstance(connectivities, tuple):\\n connectivities = connectivities[0]\\n return connectivities.tocsr()\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.5665071606636047,\n \"alphanum_fraction\": 0.5779904127120972,\n \"avg_line_length\": 18.716981887817383,\n \"blob_id\": \"75c8c1af025576b41fdaa21b6c25ecd8e15afd72\",\n \"content_id\": \"cd7efb2f1f96eb9937d843ad9cef415c0aff5d4f\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1045,\n \"license_type\": \"permissive\",\n \"max_line_length\": 107,\n \"num_lines\": 53,\n \"path\": \"/stereo/core/stereo_data.py\",\n \"repo_name\": \"leying95/stereopy\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#!/usr/bin/env python3\\n# coding: utf-8\\n\\\"\\\"\\\"\\n@author: Ping Qiu qiuping1@genomics.cn\\n@last modified by: Ping Qiu\\n@file:stereo_data.py\\n@time:2021/03/22\\n\\\"\\\"\\\"\\n\\n\\nclass StereoData(object):\\n def __init__(self, raw_file=None, exp_matrix=None, genes=None, bins=None, position=None, partitions=1):\\n self.index = None\\n self.index_file = None\\n self.exp_matrix = exp_matrix\\n self.genes = genes\\n self.bins = bins\\n self.position = position\\n self.raw_file = raw_file\\n self.partitions = partitions\\n\\n def filter_genes(self):\\n pass\\n\\n def filter_bins(self):\\n pass\\n\\n def search(self):\\n pass\\n\\n def combine_bins(self, bin_size, step):\\n pass\\n\\n def select_by_genes(self, gene_list):\\n pass\\n\\n def select_by_position(self, x_min, y_min, x_max, y_max, bin_size):\\n pass\\n\\n def transform_matrix(self):\\n pass\\n\\n def get_genes(self):\\n pass\\n\\n def get_bins(self):\\n pass\\n\\n def split_data(self):\\n pass\\n\\n def sparse2array(self):\\n pass\\n\"\n },\n {\n \"alpha_fraction\": 0.6382660865783691,\n \"alphanum_fraction\": 0.6636771559715271,\n \"avg_line_length\": 29.409090042114258,\n \"blob_id\": \"b9472f782f76c2f6c8aaa8802826cc4656afb1ba\",\n \"content_id\": \"ed031fae5add10b548834f898ab95a813e1f9395\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 669,\n \"license_type\": \"permissive\",\n \"max_line_length\": 71,\n \"num_lines\": 22,\n \"path\": \"/stereo/preprocess/qc.py\",\n \"repo_name\": \"leying95/stereopy\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#!/usr/bin/env python3\\n# coding: utf-8\\n\\\"\\\"\\\"\\n@author: Ping Qiu qiuping1@genomics.cn\\n@last modified by: Ping Qiu\\n@file:qc.py\\n@time:2021/03/26\\n\\\"\\\"\\\"\\nfrom scipy.sparse import issparse\\nimport numpy as np\\n\\n\\ndef cal_qc(andata):\\n exp_matrix = andata.X.toarray() if issparse(andata.X) else andata.X\\n total_count = exp_matrix.sum(1)\\n n_gene_by_count = np.count_nonzero(exp_matrix, axis=1)\\n mt_index = andata.var_names.str.startswith('MT-')\\n mt_count = np.array(andata.X[:, mt_index].sum(1)).reshape(-1)\\n andata.obs['total_counts'] = total_count\\n andata.obs['pct_counts_mt'] = mt_count / total_count * 100\\n andata.obs['n_genes_by_counts'] = n_gene_by_count\\n return andata\\n\"\n },\n {\n \"alpha_fraction\": 0.5326364636421204,\n \"alphanum_fraction\": 0.5358884930610657,\n \"avg_line_length\": 25.411043167114258,\n \"blob_id\": \"57ec9a317b271c5001152cd0804fe0de76566362\",\n \"content_id\": \"5e726176ef70882e7b7c303bdb60a84d1c62f300\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 4305,\n \"license_type\": \"permissive\",\n \"max_line_length\": 114,\n \"num_lines\": 163,\n \"path\": \"/stereo/config.py\",\n \"repo_name\": \"leying95/stereopy\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#!/usr/bin/env python3\\n# coding: utf-8\\n\\\"\\\"\\\"\\n@author: Ping Qiu qiuping1@genomics.cn\\n@last modified by: Ping Qiu\\n@file:config.py\\n@time:2021/03/05\\n\\\"\\\"\\\"\\nfrom typing import Union, Optional\\nfrom pathlib import Path\\nimport os\\nfrom matplotlib import rcParams, rcParamsDefault\\n\\n\\nclass StereoConfig(object):\\n \\\"\\\"\\\"\\n config of stereo.\\n \\\"\\\"\\\"\\n def __init__(\\n self,\\n file_format: str = \\\"h5ad\\\",\\n auto_show: bool = True,\\n n_jobs=1,\\n log_file: Union[str, Path, None] = None,\\n log_level: str = \\\"info\\\",\\n log_format: str = \\\"%(asctime)s %(name)s %(levelname)s: %(message)s\\\",\\n output: str = \\\"./output\\\",\\n data_dir: str = None\\n ):\\n self._file_format = file_format\\n self._auto_show = auto_show\\n self._n_jobs = n_jobs\\n self._log_file = log_file\\n self._log_level = log_level\\n self._log_format = log_format\\n self.out_dir = output\\n self.data_dir = data_dir if data_dir else os.path.join(os.path.dirname(os.path.abspath(__file__)), 'data')\\n\\n @property\\n def log_file(self) -> Union[str, Path, None]:\\n \\\"\\\"\\\"\\n get the file path of log.\\n :return:\\n \\\"\\\"\\\"\\n return self._log_file\\n\\n @log_file.setter\\n def log_file(self, value):\\n \\\"\\\"\\\"\\n set file path of log.\\n :param value: value of log file path\\n :return:\\n \\\"\\\"\\\"\\n if value:\\n dir_path = os.path.dirname(value)\\n if not os.path.exists(dir_path):\\n raise FileExistsError(\\\"folder does not exist, please check!\\\")\\n self._log_file = value\\n\\n @property\\n def log_format(self) -> str:\\n \\\"\\\"\\\"\\n get the format of log.\\n :return:\\n \\\"\\\"\\\"\\n return self._log_format\\n\\n @log_format.setter\\n def log_format(self, value):\\n \\\"\\\"\\\"\\n set file path of log.\\n :param value: value of log format\\n :return:\\n \\\"\\\"\\\"\\n self._log_format = value\\n\\n @property\\n def log_level(self) -> str:\\n \\\"\\\"\\\"\\n get log level\\n :return:\\n \\\"\\\"\\\"\\n return self._log_level\\n\\n @log_level.setter\\n def log_level(self, value):\\n \\\"\\\"\\\"\\n set log level\\n :param value: the value of log level\\n :return:\\n \\\"\\\"\\\"\\n if value.lower() not in ['info', 'warning', 'debug', 'error', 'critical']:\\n print('the log level is out of range, please check and it is not modified.')\\n else:\\n self._log_level = value\\n\\n @property\\n def auto_show(self):\\n \\\"\\\"\\\"\\n Auto show figures if `auto_show == True` (default `True`).\\n :return:\\n \\\"\\\"\\\"\\n return self._auto_show\\n\\n @auto_show.setter\\n def auto_show(self, value):\\n \\\"\\\"\\\"\\n set value of auto_show\\n :param value: value of auto_show\\n :return:\\n \\\"\\\"\\\"\\n self._auto_show = value\\n\\n @property\\n def file_format(self) -> str:\\n \\\"\\\"\\\"\\n file format of saving anndata object\\n :return:\\n \\\"\\\"\\\"\\n return self._file_format\\n\\n @file_format.setter\\n def file_format(self, value):\\n \\\"\\\"\\\"\\n set the value of file format\\n :param value: the value of file format\\n :return:\\n \\\"\\\"\\\"\\n self._file_format = value\\n\\n @property\\n def n_jobs(self) -> int:\\n return self._n_jobs\\n\\n @n_jobs.setter\\n def n_jobs(self, value):\\n self._n_jobs = value\\n\\n @staticmethod\\n def set_plot_param(fontsize: int = 14, figsize: Optional[int] = None, color_map: Optional[str] = None,\\n facecolor: Optional[str] = None, transparent: bool = False,):\\n if fontsize is not None:\\n rcParams['font.size'] = fontsize\\n if color_map is not None:\\n rcParams['image.cmap'] = color_map\\n if figsize is not None:\\n rcParams['figure.figsize'] = figsize\\n if facecolor is not None:\\n rcParams['figure.facecolor'] = facecolor\\n rcParams['axes.facecolor'] = facecolor\\n if transparent is not None:\\n rcParams[\\\"savefig.transparent\\\"] = transparent\\n\\n @staticmethod\\n def set_rcparams_defaults():\\n \\\"\\\"\\\"\\n reset `matplotlib.rcParams` to defaults.\\n :return:\\n \\\"\\\"\\\"\\n rcParams.update(rcParamsDefault)\\n\\n\\nstereo_conf = StereoConfig()\\n\"\n },\n {\n \"alpha_fraction\": 0.552388072013855,\n \"alphanum_fraction\": 0.5629907250404358,\n \"avg_line_length\": 33.834495544433594,\n \"blob_id\": \"5cf9c6e4a72c0d946056b70efefaa0185bdaeffa\",\n \"content_id\": \"e13b730eda2fc60a16a1c52046d3725d072fd48c\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 20531,\n \"license_type\": \"permissive\",\n \"max_line_length\": 155,\n \"num_lines\": 574,\n \"path\": \"/stereo/plots/plot_utils.py\",\n \"repo_name\": \"leying95/stereopy\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#!/usr/bin/env python3\\n# coding: utf-8\\n\\\"\\\"\\\"\\n@author: Shixu He heshixu@genomics.cn\\n@last modified by: Shixu He\\n@file:plot_utils.py\\n@time:2021/03/15\\n\\\"\\\"\\\"\\n\\nfrom anndata import AnnData\\nimport pandas as pd\\nimport numpy as np\\nimport math\\n\\nfrom matplotlib.colors import Normalize, ListedColormap\\nfrom matplotlib import gridspec\\nfrom matplotlib.cm import get_cmap\\nfrom matplotlib.axes import Axes\\nimport matplotlib.pyplot as plt\\nimport seaborn\\n\\nfrom ._plot_basic.scatter_plt import scatter, plot_cluster_result\\nfrom ._plot_basic.heatmap_plt import heatmap, _plot_categories_as_colorblocks, _plot_gene_groups_brackets\\n\\nfrom typing import Optional, Sequence, Union\\n\\nfrom ..log_manager import logger\\n\\n\\ndef plot_spatial_distribution(\\n adata: AnnData,\\n obs_key: list = [\\\"total_counts\\\", \\\"n_genes_by_counts\\\"],\\n ncols=2,\\n dot_size=None,\\n color_list=None,\\n invert_y=False\\n): # scatter plot, 表达矩阵空间分布\\n \\\"\\\"\\\"\\n Plot spatial distribution of specified obs data.\\n ============ Arguments ============\\n :param adata: AnnData object.\\n :param obs_key: specified obs key list, for example: [\\\"total_counts\\\", \\\"n_genes_by_counts\\\"]\\n :param ncols: numbr of plot columns.\\n :param dot_size: marker size.\\n :param cmap: Color map.\\n :param invert_y: whether to invert y-axis.\\n ============ Return ============\\n None\\n ============ Example ============\\n plot_spatial_distribution(adata=adata)\\n \\\"\\\"\\\"\\n # sc.pl.embedding(adata, basis=\\\"spatial\\\", color=[\\\"total_counts\\\", \\\"n_genes_by_counts\\\"],size=30)\\n\\n if dot_size is None:\\n dot_size = 120000 / adata.shape[0]\\n\\n ncols = min(ncols, len(obs_key))\\n nrows = np.ceil(len(obs_key) / ncols).astype(int)\\n # each panel will have the size of rcParams['figure.figsize']\\n fig = plt.figure(figsize=(ncols * 10, nrows * 8))\\n left = 0.2 / ncols\\n bottom = 0.13 / nrows\\n axs = gridspec.GridSpec(\\n nrows=nrows,\\n ncols=ncols,\\n left=left,\\n right=1 - (ncols - 1) * left - 0.01 / ncols,\\n bottom=bottom,\\n top=1 - (nrows - 1) * bottom - 0.1 / nrows,\\n # hspace=hspace,\\n # wspace=wspace,\\n )\\n\\n if color_list is None:\\n cmap = get_cmap()\\n else:\\n cmap = ListedColormap(color_list)\\n # 把特定值改为 np.nan 之后，可以利用 cmap.set_bad(\\\"white\\\") 来遮盖掉这部分数据\\n\\n # 散点图上每个点的坐标数据来自于 adata 的 obsm[\\\"spatial\\\"]，每个点的颜色（数值）数据来自于 adata 的 obs_vector()\\n for i, key in enumerate(obs_key):\\n # color_data = np.asarray(adata.obs_vector(key), dtype=float)\\n color_data = adata.obs_vector(key)\\n order = np.argsort(~pd.isnull(color_data), kind=\\\"stable\\\")\\n spatial_data = np.array(adata.obsm[\\\"spatial\\\"])[:, 0: 2]\\n color_data = color_data[order]\\n spatial_data = spatial_data[order, :]\\n\\n # color_data 是图像中各个点的值，也对应了每个点的颜色。data_points则对应了各个点的坐标\\n ax = fig.add_subplot(axs[i]) # ax = plt.subplot(axs[i]) || ax = fig.add_subplot(axs[1, 1]))\\n ax.set_title(key)\\n ax.set_yticks([])\\n ax.set_xticks([])\\n ax.set_xlabel(\\\"spatial1\\\")\\n ax.set_ylabel(\\\"spatial2\\\")\\n pathcollection = scatter(\\n spatial_data[:, 0],\\n spatial_data[:, 1],\\n ax=ax,\\n marker=\\\".\\\",\\n dot_colors=color_data,\\n dot_size=dot_size,\\n cmap=cmap,\\n )\\n plt.colorbar(\\n pathcollection,\\n ax=ax,\\n pad=0.01,\\n fraction=0.08,\\n aspect=30,\\n )\\n ax.autoscale_view()\\n if invert_y:\\n ax.invert_yaxis()\\n\\n\\ndef plot_spatial_cluster(\\n adata: AnnData,\\n obs_key: list = [\\\"phenograph\\\"],\\n plot_cluster: list = None,\\n bad_color=\\\"lightgrey\\\",\\n ncols=2,\\n dot_size=None,\\n invert_y=False,\\n color_list=['violet', 'turquoise', 'tomato', 'teal',\\n 'tan', 'silver', 'sienna', 'red', 'purple',\\n 'plum', 'pink', 'orchid', 'orangered', 'orange',\\n 'olive', 'navy', 'maroon', 'magenta', 'lime',\\n 'lightgreen', 'lightblue', 'lavender', 'khaki',\\n 'indigo', 'grey', 'green', 'gold', 'fuchsia',\\n 'darkgreen', 'darkblue', 'cyan', 'crimson', 'coral',\\n 'chocolate', 'chartreuse', 'brown', 'blue', 'black',\\n 'beige', 'azure', 'aquamarine', 'aqua']): # scatter plot, 聚类后表达矩阵空间分布\\n \\\"\\\"\\\"\\n Plot spatial distribution of specified obs data.\\n ============ Arguments ============\\n :param adata: AnnData object.\\n :param obs_key: specified obs cluster key list, for example: [\\\"phenograph\\\"].\\n :param plot_cluster: the name list of clusters to show.\\n :param ncols: numbr of plot columns.\\n :param dot_size: marker size.\\n :param cmap: Color map.\\n :param invert_y: whether to invert y-axis.\\n ============ Return ============\\n None.\\n ============ Example ============\\n plot_spatial_cluster(adata = adata)\\n \\\"\\\"\\\"\\n # sc.pl.embedding(adata, basis=\\\"spatial\\\", color=[\\\"total_counts\\\", \\\"n_genes_by_counts\\\"],size=30)\\n\\n if isinstance(obs_key, str):\\n obs_key = [\\\"obs_key\\\"]\\n\\n plot_cluster_result(adata, obs_key=obs_key, pos_key=\\\"spatial\\\", plot_cluster=plot_cluster, bad_color=bad_color,\\n ncols=ncols, dot_size=dot_size, invert_y=invert_y, color_list=color_list)\\n\\n\\ndef plot_to_select_filter_value(\\n adata: AnnData,\\n x=[\\\"total_counts\\\", \\\"total_counts\\\"],\\n y=[\\\"pct_counts_mt\\\", \\\"n_genes_by_counts\\\"],\\n ncols=1,\\n **kwargs): # scatter plot, 线粒体分布图\\n \\\"\\\"\\\"\\n Plot .\\n ============ Arguments ============\\n :param adata: AnnData object.\\n :param x, y: obs key pairs for drawing. For example, assume x=[\\\"a\\\", \\\"a\\\", \\\"b\\\"] and y=[\\\"c\\\", \\\"d\\\", \\\"e\\\"], the output plots will include \\\"a-c\\\", \\\"a-d\\\", \\\"b-e\\\".\\n ============ Return ============\\n None.\\n ============ Example ============\\n plot_spatial_cluster(adata = adata)\\n \\\"\\\"\\\"\\n # sc.pl.scatter(adata, x='total_counts', y='pct_counts_mt')\\n # sc.pl.scatter(adata, x='total_counts', y='n_genes_by_counts')\\n if isinstance(x, str):\\n x = [x]\\n if isinstance(y, str):\\n y = [y]\\n\\n width = 20\\n height = 10\\n nrows = math.ceil(len(x) / ncols)\\n\\n doc_color = \\\"gray\\\"\\n\\n fig = plt.figure(figsize=(width, height))\\n axs = gridspec.GridSpec(\\n nrows=nrows,\\n ncols=ncols,\\n )\\n for i, (xi, yi) in enumerate(zip(x, y)):\\n draw_data = np.c_[adata.obs_vector(xi), adata.obs_vector(yi)]\\n dot_size = 120000 / draw_data.shape[0]\\n ax = fig.add_subplot(axs[i])\\n # ax.set_title()\\n # ax.set_yticks([])\\n # ax.set_xticks([])\\n ax.set_xlabel(xi)\\n ax.set_ylabel(yi)\\n scatter(\\n draw_data[:, 0],\\n draw_data[:, 1],\\n ax=ax,\\n marker=\\\".\\\",\\n dot_colors=doc_color,\\n dot_size=dot_size\\n )\\n\\n\\ndef plot_variable_gene(adata: AnnData, logarize=False): # scatter plot, 表达量差异-均值图\\n \\\"\\\"\\\"\\n Copied from scanpy and modified.\\n \\\"\\\"\\\"\\n # 该图像需要前置数据处理：sc.pp.highly_variable_genes(adata, min_mean=0.0125, max_mean=3, min_disp=0.5)\\n # 再画图：sc.pl.highly_variable_genes(adata)\\n\\n result = adata.var\\n gene_subset = result.highly_variable\\n means = result.means\\n var_or_disp = result.dispersions\\n var_or_disp_norm = result.dispersions_norm\\n width = 10\\n height = 10\\n\\n plt.figure(figsize=(2 * width, height))\\n plt.subplots_adjust(wspace=0.3)\\n for idx, d in enumerate([var_or_disp_norm, var_or_disp]):\\n plt.subplot(1, 2, idx + 1)\\n for label, color, mask in zip(\\n ['highly variable genes', 'other genes'],\\n ['black', 'grey'],\\n [gene_subset, ~gene_subset],\\n ):\\n if False:\\n means_, var_or_disps_ = np.log10(means[mask]), np.log10(d[mask])\\n else:\\n means_, var_or_disps_ = means[mask], d[mask]\\n plt.scatter(means_, var_or_disps_, label=label, c=color, s=1)\\n if logarize: # there's a bug in autoscale\\n plt.xscale('log')\\n plt.yscale('log')\\n y_min = np.min(var_or_disp)\\n y_min = 0.95 * y_min if y_min > 0 else 1e-1\\n plt.xlim(0.95 * np.min(means), 1.05 * np.max(means))\\n plt.ylim(y_min, 1.05 * np.max(var_or_disp))\\n if idx == 0:\\n plt.legend()\\n plt.xlabel(('$log_{10}$ ' if False else '') + 'mean expressions of genes')\\n data_type = 'dispersions'\\n plt.ylabel(\\n ('$log_{10}$ ' if False else '')\\n + '{} of genes'.format(data_type)\\n + (' (normalized)' if idx == 0 else ' (not normalized)')\\n )\\n\\n\\ndef plot_cluster_umap(\\n adata: AnnData,\\n obs_key: list = [\\\"phenograph\\\"],\\n plot_cluster: list = None,\\n bad_color=\\\"lightgrey\\\",\\n ncols=2,\\n dot_size=None,\\n invert_y=False,\\n color_list=['violet', 'turquoise', 'tomato', 'teal',\\n 'tan', 'silver', 'sienna', 'red', 'purple',\\n 'plum', 'pink', 'orchid', 'orangered', 'orange',\\n 'olive', 'navy', 'maroon', 'magenta', 'lime',\\n 'lightgreen', 'lightblue', 'lavender', 'khaki',\\n 'indigo', 'grey', 'green', 'gold', 'fuchsia',\\n 'darkgreen', 'darkblue', 'cyan', 'crimson', 'coral',\\n 'chocolate', 'chartreuse', 'brown', 'blue', 'black',\\n 'beige', 'azure', 'aquamarine', 'aqua',\\n ]\\n): # scatter plot，聚类结果PCA/umap图\\n \\\"\\\"\\\"\\n Plot spatial distribution of specified obs data.\\n ============ Arguments ============\\n :param adata: AnnData object.\\n :param obs_key: specified obs cluster key list, for example: [\\\"phenograph\\\"].\\n :param plot_cluster: the name list of clusters to show.\\n :param ncols: numbr of plot columns.\\n :param dot_size: marker size.\\n :param cmap: Color map.\\n :param invert_y: whether to invert y-axis.\\n ============ Return ============\\n None.\\n ============ Example ============\\n plot_cluster_umap(adata = adata)\\n \\\"\\\"\\\"\\n\\n if (isinstance(obs_key, str)):\\n obs_key = [obs_key]\\n\\n plot_cluster_result(adata, obs_key=obs_key, pos_key=\\\"X_umap\\\", plot_cluster=plot_cluster, bad_color=bad_color,\\n ncols=ncols, dot_size=dot_size, invert_y=invert_y, color_list=color_list)\\n\\n\\ndef plot_expression_difference(\\n adata: AnnData,\\n groups: Union[str, Sequence[str]] = None,\\n n_genes: int = 20,\\n key: Optional[str] = 'rank_genes_groups',\\n fontsize: int = 8,\\n ncols: int = 4,\\n sharey: bool = True,\\n show: Optional[bool] = None,\\n save: Optional[bool] = None,\\n ax: Optional[Axes] = None,\\n **kwds,\\n): # scatter plot, 差异基因显著性图，类碎石图\\n \\\"\\\"\\\"\\n Copied from scanpy and modified.\\n \\\"\\\"\\\"\\n\\n # 调整图像 panel/grid 相关参数\\n if 'n_panels_per_row' in kwds:\\n n_panels_per_row = kwds['n_panels_per_row']\\n else:\\n n_panels_per_row = ncols\\n group_names = adata.uns[key]['names'].dtype.names if groups is None else groups\\n # one panel for each group\\n # set up the figure\\n n_panels_x = min(n_panels_per_row, len(group_names))\\n n_panels_y = np.ceil(len(group_names) / n_panels_x).astype(int)\\n\\n # 初始化图像\\n width = 10\\n height = 10\\n fig = plt.figure(\\n figsize=(\\n n_panels_x * width, # rcParams['figure.figsize'][0],\\n n_panels_y * height, # rcParams['figure.figsize'][1],\\n )\\n )\\n gs = gridspec.GridSpec(nrows=n_panels_y, ncols=n_panels_x, wspace=0.22, hspace=0.3)\\n\\n ax0 = None\\n ymin = np.Inf\\n ymax = -np.Inf\\n for count, group_name in enumerate(group_names):\\n gene_names = adata.uns[key]['names'][group_name][:n_genes]\\n scores = adata.uns[key]['scores'][group_name][:n_genes]\\n\\n # Setting up axis, calculating y bounds\\n if sharey:\\n ymin = min(ymin, np.min(scores))\\n ymax = max(ymax, np.max(scores))\\n\\n if ax0 is None:\\n ax = fig.add_subplot(gs[count])\\n ax0 = ax\\n else:\\n ax = fig.add_subplot(gs[count], sharey=ax0)\\n else:\\n ymin = np.min(scores)\\n ymax = np.max(scores)\\n ymax += 0.3 * (ymax - ymin)\\n\\n ax = fig.add_subplot(gs[count])\\n ax.set_ylim(ymin, ymax)\\n\\n ax.set_xlim(-0.9, n_genes - 0.1)\\n\\n # Making labels\\n for ig, gene_name in enumerate(gene_names):\\n ax.text(\\n ig,\\n scores[ig],\\n gene_name,\\n rotation='vertical',\\n verticalalignment='bottom',\\n horizontalalignment='center',\\n fontsize=fontsize,\\n )\\n\\n ax.set_title('{} vs. {}'.format(group_name, \\\"Others\\\"))\\n if count >= n_panels_x * (n_panels_y - 1):\\n ax.set_xlabel('ranking')\\n\\n # print the 'score' label only on the first panel per row.\\n if count % n_panels_x == 0:\\n ax.set_ylabel('score')\\n\\n if sharey is True:\\n ymax += 0.3 * (ymax - ymin)\\n ax.set_ylim(ymin, ymax)\\n\\n\\ndef plot_violin_distribution(adata): # 小提琴统计图\\n \\\"\\\"\\\"\\n 绘制数据的分布小提琴图。\\n ============ Arguments ============\\n :param adata: AnnData object.\\n ============ Return ============\\n None\\n \\\"\\\"\\\"\\n _, axs = plt.subplots(1, 3, figsize=(15, 4))\\n seaborn.violinplot(y=adata.obs['total_counts'], ax=axs[0])\\n seaborn.violinplot(y=adata.obs['n_genes_by_counts'], ax=axs[1])\\n seaborn.violinplot(y=adata.obs['pct_counts_mt'], ax=axs[2])\\n\\n\\ndef plot_heatmap_maker_genes(\\n adata: AnnData = None,\\n cluster_method=\\\"phenograph\\\",\\n marker_uns_key=None,\\n num_show_gene=8,\\n show_labels=True,\\n order_cluster=True,\\n marker_clusters=None,\\n cluster_colors_array=None,\\n **kwargs\\n): # heatmap, 差异基因热图\\n \\\"\\\"\\\"\\n 绘制 Marker gene 的热图。热图中每一行代表一个 bin 的所有基因的表达量，所有的 bin 会根据所属的 cluster 进行聚集， cluster 具体展示在热图的左侧，用颜色区分。\\n ============ Arguments ============\\n :param adata: AnnData object.\\n :param cluster_methpd: method used in clustering. for example: phenograph, leiden\\n :param marker_uns_key: the key of adata.uns, the default value is \\\"marker_genes\\\"\\n :param num_show_gene: number of genes to show in each cluster.\\n :param show_labels: show gene name on axis.\\n :param order_cluster: reorder the cluster list in plot (y axis).\\n :param marker_clusters: the list of clusters to show on the heatmap.\\n :param cluster_colors_array: the list of colors in the color block on the left of heatmap.\\n ============ Return ============\\n\\n ============ Example ============\\n plot_heatmap_maker_genes(adata=adata, marker_uns_key = \\\"rank_genes_groups\\\", figsize = (20, 10))\\n \\\"\\\"\\\"\\n\\n if marker_uns_key is None:\\n marker_uns_key = 'marker_genes' # \\\"rank_genes_groups\\\" in original scanpy pipeline\\n\\n # if cluster_method is None:\\n # cluster_method = str(adata.uns[marker_uns_key]['params']['groupby'])\\n\\n # cluster_colors_array = adata.uns[\\\"phenograph_colors\\\"]\\n\\n if marker_clusters is None:\\n marker_clusters = adata.uns[marker_uns_key]['names'].dtype.names\\n\\n if not set(marker_clusters).issubset(set(adata.uns[marker_uns_key]['names'].dtype.names)):\\n marker_clusters = adata.uns[marker_uns_key]['names'].dtype.names\\n\\n gene_names_dict = {} # dict in which each cluster is the keyand the num_show_gene are the values\\n\\n for cluster in marker_clusters:\\n # get all genes that are 'non-nan'\\n genes_array = adata.uns[marker_uns_key]['names'][cluster]\\n genes_array = genes_array[~pd.isnull(genes_array)]\\n\\n if len(genes_array) == 0:\\n logger.warning(\\\"Cluster {} has no genes.\\\".format(cluster))\\n continue\\n gene_names_dict[cluster] = list(genes_array[:num_show_gene])\\n\\n adata._sanitize()\\n\\n gene_names = []\\n gene_group_labels = []\\n gene_group_positions = []\\n start = 0\\n for label, gene_list in gene_names_dict.items():\\n if isinstance(gene_list, str):\\n gene_list = [gene_list]\\n gene_names.extend(list(gene_list))\\n gene_group_labels.append(label)\\n gene_group_positions.append((start, start + len(gene_list) - 1))\\n start += len(gene_list)\\n\\n # 此处获取所有绘图所需的数据 （表达量矩阵）\\n draw_df = pd.DataFrame(index=adata.obs_names)\\n uniq_gene_names = np.unique(gene_names)\\n draw_df = pd.concat(\\n [draw_df, pd.DataFrame(adata.X[tuple([slice(None), adata.var.index.get_indexer(uniq_gene_names)])],\\n columns=uniq_gene_names, index=adata.obs_names)],\\n axis=1\\n )\\n\\n # add obs values\\n draw_df = pd.concat([draw_df, adata.obs[cluster_method]], axis=1)\\n\\n # reorder columns to given order (including duplicates keys if present)\\n draw_df = draw_df[list([cluster_method]) + list(uniq_gene_names)]\\n draw_df = draw_df[gene_names].set_index(draw_df[cluster_method].astype('category'))\\n if order_cluster:\\n draw_df = draw_df.sort_index()\\n\\n # From scanpy\\n # define a layout of 2 rows x 3 columns\\n # first row is for 'brackets' (if no brackets needed, the height of this row\\n # is zero) second row is for main content. This second row is divided into\\n # three axes:\\n # first ax is for the categories defined by `cluster_method`\\n # second ax is for the heatmap\\n # fourth ax is for colorbar\\n\\n kwargs.setdefault(\\\"figsize\\\", (10, 10))\\n kwargs.setdefault(\\\"colorbar_width\\\", 0.2)\\n colorbar_width = kwargs.get(\\\"colorbar_width\\\")\\n figsize = kwargs.get(\\\"figsize\\\")\\n\\n cluster_block_width = kwargs.setdefault(\\\"cluster_block_width\\\", 0.2) if order_cluster else 0\\n if figsize is None:\\n height = 6\\n if show_labels:\\n heatmap_width = len(gene_names) * 0.3\\n else:\\n heatmap_width = 8\\n width = heatmap_width + cluster_block_width\\n else:\\n width, height = figsize\\n heatmap_width = width - cluster_block_width\\n\\n if gene_group_positions is not None and len(gene_group_positions) > 0:\\n # add some space in case 'brackets' want to be plotted on top of the image\\n height_ratios = [0.15, height]\\n else:\\n height_ratios = [0, height]\\n\\n width_ratios = [\\n cluster_block_width,\\n heatmap_width,\\n colorbar_width,\\n ]\\n\\n fig = plt.figure(figsize=(width, height))\\n\\n axs = gridspec.GridSpec(\\n nrows=2,\\n ncols=3,\\n width_ratios=width_ratios,\\n wspace=0.15 / width,\\n hspace=0.13 / height,\\n height_ratios=height_ratios,\\n )\\n\\n heatmap_ax = fig.add_subplot(axs[1, 1])\\n\\n width, height = fig.get_size_inches()\\n max_cbar_height = 4.0\\n if height > max_cbar_height:\\n # to make the colorbar shorter, the\\n # ax is split and the lower portion is used.\\n axs2 = gridspec.GridSpecFromSubplotSpec(2, 1, subplot_spec=axs[1, 2],\\n height_ratios=[height - max_cbar_height, max_cbar_height],\\n )\\n heatmap_cbar_ax = fig.add_subplot(axs2[1])\\n else:\\n heatmap_cbar_ax = fig.add_subplot(axs[1, 2])\\n\\n heatmap(df=draw_df, ax=heatmap_ax,\\n norm=Normalize(vmin=None, vmax=None), plot_colorbar=True, colorbar_ax=heatmap_cbar_ax,\\n show_labels=True, plot_hline=True)\\n\\n if order_cluster:\\n _plot_categories_as_colorblocks(\\n fig.add_subplot(axs[1, 0]), draw_df, colors=cluster_colors_array, orientation='left'\\n )\\n\\n # plot cluster legends on top of heatmap_ax (if given)\\n if gene_group_positions is not None and len(gene_group_positions) > 0:\\n _plot_gene_groups_brackets(\\n fig.add_subplot(axs[0, 1], sharex=heatmap_ax),\\n group_positions=gene_group_positions,\\n group_labels=gene_group_labels,\\n rotation=None,\\n left_adjustment=-0.3,\\n right_adjustment=0.3,\\n )\\n\\n # plt.savefig()\\n\"\n },\n {\n \"alpha_fraction\": 0.5822505354881287,\n \"alphanum_fraction\": 0.5927923321723938,\n \"avg_line_length\": 32.99166488647461,\n \"blob_id\": \"a8e3e35c6156f10d95e13736868dfb21b8d5ee67\",\n \"content_id\": \"3526ea0c74b7e911d1ee4dc7c4cc474d0dd5b8eb\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 4087,\n \"license_type\": \"permissive\",\n \"max_line_length\": 117,\n \"num_lines\": 120,\n \"path\": \"/stereo/tools/cluster.py\",\n \"repo_name\": \"leying95/stereopy\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#!/usr/bin/env python3\\n# coding: utf-8\\n\\\"\\\"\\\"\\n@author: Ping Qiu qiuping1@genomics.cn\\n@last modified by: Ping Qiu\\n@file:cluster.py\\n@time:2021/03/19\\n\\\"\\\"\\\"\\nimport leidenalg as la\\nfrom sklearn.decomposition import PCA\\nfrom scipy.sparse import coo_matrix\\nfrom sklearn.neighbors import NearestNeighbors\\nimport igraph as ig\\nimport numpy as np\\nfrom umap.umap_ import fuzzy_simplicial_set\\n\\n\\nclass Neighbors(object):\\n def __init__(self, x, n_neighbors):\\n self.x = x\\n self.n_neighbors = n_neighbors\\n\\n def find_n_neighbors(self):\\n nbrs = NearestNeighbors(n_neighbors=self.n_neighbors + 1, algorithm='ball_tree').fit(self.x)\\n dists, indices = nbrs.kneighbors(self.x)\\n nn_idx = indices[:, 1:]\\n nn_dist = dists[:, 1:]\\n return nn_idx, nn_dist\\n\\n def get_igraph_from_knn(self, nn_idx, nn_dist):\\n j = nn_idx.ravel().astype(int)\\n dist = nn_dist.ravel()\\n i = np.repeat(np.arange(nn_idx.shape[0]), self.n_neighbors)\\n\\n vertex = list(range(nn_dist.shape[0]))\\n edges = list(tuple(zip(i, j)))\\n G = ig.Graph()\\n G.add_vertices(vertex)\\n G.add_edges(edges)\\n G.es['weight'] = dist\\n return G\\n\\n def get_parse_distances(self, nn_idx, nn_dist):\\n n_obs = self.x.shape[0]\\n rows = np.zeros((n_obs * self.n_neighbors), dtype=np.int64)\\n cols = np.zeros((n_obs * self.n_neighbors), dtype=np.int64)\\n vals = np.zeros((n_obs * self.n_neighbors), dtype=np.float64)\\n\\n for i in range(nn_idx.shape[0]):\\n for j in range(self.n_neighbors):\\n if nn_idx[i, j] == -1:\\n continue # We didn't get the full knn for i\\n if nn_idx[i, j] == i:\\n val = 0.0\\n else:\\n val = nn_dist[i, j]\\n\\n rows[i * self.n_neighbors + j] = i\\n cols[i * self.n_neighbors + j] = nn_idx[i, j]\\n vals[i * self.n_neighbors + j] = val\\n\\n distances = coo_matrix((vals, (rows, cols)), shape=(n_obs, n_obs))\\n distances.eliminate_zeros()\\n return distances.tocsr()\\n\\n def get_connectivities(self, nn_idx, nn_dist):\\n n_obs = self.x.shape[0]\\n x = coo_matrix(([], ([], [])), shape=(n_obs, 1))\\n connectivities = fuzzy_simplicial_set(x, self.n_neighbors, None, None, knn_indices=nn_idx, knn_dists=nn_dist,\\n set_op_mix_ratio=1.0, local_connectivity=1.0)\\n if isinstance(connectivities, tuple):\\n connectivities = connectivities[0]\\n return connectivities.tocsr()\\n\\n\\ndef run_neighbors(x, neighbors=30):\\n neighbor = Neighbors(x, neighbors)\\n nn_idx, nn_dist = neighbor.find_n_neighbors()\\n return neighbor, nn_idx, nn_dist\\n\\n\\ndef run_louvain(x, neighbor, nn_idx, nn_dist):\\n g = neighbor.get_igraph_from_knn(nn_idx, nn_dist)\\n louvain_partition = g.community_multilevel(weights=g.es['weight'], return_levels=False)\\n clusters = np.arange(x.shape[0])\\n for i in range(len(louvain_partition)):\\n clusters[louvain_partition[i]] = str(i)\\n return clusters\\n\\n\\ndef run_knn_leiden(x, neighbor, nn_idx, nn_dist, diff=1):\\n g = neighbor.get_igraph_from_knn(nn_idx, nn_dist)\\n optimiser = la.Optimiser()\\n leiden_partition = la.ModularityVertexPartition(g, weights=g.es['weight'])\\n while diff > 0:\\n diff = optimiser.optimise_partition(leiden_partition, n_iterations=10)\\n clusters = np.arange(x.shape[0])\\n for i in range(len(leiden_partition)):\\n clusters[leiden_partition[i]] = str(i)\\n return clusters\\n\\n\\ndef run_cluster(x, method='leiden', do_pca=True, n_pcs=30):\\n \\\"\\\"\\\"\\n :param x: np.array, shape: (m, n)，m个bin， n为embedding\\n :param method:\\n :param do_pca:\\n :param n_pcs:\\n :return:\\n \\\"\\\"\\\"\\n if do_pca:\\n pca_obj = PCA(n_components=n_pcs)\\n x = pca_obj.fit_transform(x)\\n\\n neighbor, nn_idx, nn_dist = run_neighbors(x)\\n if method == 'leiden':\\n cluster = run_knn_leiden(x, neighbor, nn_idx, nn_dist)\\n else:\\n cluster = run_louvain(x, neighbor, nn_idx, nn_dist)\\n return cluster\\n\"\n },\n {\n \"alpha_fraction\": 0.5596755146980286,\n \"alphanum_fraction\": 0.5709463357925415,\n \"avg_line_length\": 36.02822494506836,\n \"blob_id\": \"e7cc0ef7656786a8185b9d2de04832ad295a73f2\",\n \"content_id\": \"f68ab32909c095d79527096c45e06fecb5e95b9b\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 18936,\n \"license_type\": \"permissive\",\n \"max_line_length\": 158,\n \"num_lines\": 496,\n \"path\": \"/stereo/plots/plots.py\",\n \"repo_name\": \"leying95/stereopy\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#!/usr/bin/env python3\\n# coding: utf-8\\n\\\"\\\"\\\"\\n@author: Ping Qiu qiuping1@genomics.cn\\n@last modified by: Ping Qiu\\n@file:plots.py\\n@time:2021/03/31\\n\\\"\\\"\\\"\\nfrom matplotlib.cm import get_cmap\\nimport matplotlib.pyplot as plt\\nfrom matplotlib.colors import ListedColormap, to_hex, Normalize\\nfrom matplotlib import gridspec\\nfrom ._plot_basic.get_stereo_data import get_cluster_res, get_reduce_x, get_position_array, get_degs_res\\nimport numpy as np\\nimport pandas as pd\\nfrom anndata import AnnData\\nfrom ._plot_basic.scatter_plt import scatter\\nimport seaborn\\nfrom typing import Optional, Sequence, Union\\nfrom matplotlib.axes import Axes\\nfrom ._plot_basic.heatmap_plt import heatmap, plot_categories_as_colorblocks, plot_gene_groups_brackets\\nfrom ..log_manager import logger\\nfrom scipy.sparse import issparse\\n\\n\\ndef plot_spatial_cluster(\\n adata: AnnData,\\n obs_key: list = [\\\"phenograph\\\"],\\n pos_key: str = \\\"spatial\\\",\\n plot_cluster: list = None,\\n bad_color: str = \\\"lightgrey\\\",\\n ncols: int = 2,\\n dot_size: int = None,\\n color_list=['violet', 'turquoise', 'tomato', 'teal','tan', 'silver', 'sienna', 'red', 'purple', 'plum', 'pink',\\n 'orchid', 'orangered', 'orange', 'olive', 'navy', 'maroon', 'magenta', 'lime',\\n 'lightgreen', 'lightblue', 'lavender', 'khaki', 'indigo', 'grey', 'green', 'gold', 'fuchsia',\\n 'darkgreen', 'darkblue', 'cyan', 'crimson', 'coral', 'chocolate', 'chartreuse', 'brown', 'blue', 'black',\\n 'beige', 'azure', 'aquamarine', 'aqua',\\n ],\\n): # scatter plot, 聚类后表达矩阵空间分布\\n \\\"\\\"\\\"\\n Plot spatial distribution of specified obs data.\\n ============ Arguments ============\\n :param adata: AnnData object.\\n :param obs_key: specified obs cluster key list, for example: [\\\"phenograph\\\"].\\n :param pos_key: the coordinates of data points for scatter plots. the data points are stored in adata.obsm[pos_key]. choice: \\\"spatial\\\", \\\"X_umap\\\", \\\"X_pca\\\".\\n :param plot_cluster: the name list of clusters to show.\\n :param bad_color: the name list of clusters to show.\\n :param ncols: numbr of plot columns.\\n :param dot_size: marker size.\\n :param color_list: whether to invert y-axis.\\n ============ Return ============\\n None.\\n ============ Example ============\\n plot_spatial_cluster(adata = adata)\\n \\\"\\\"\\\"\\n # sc.pl.embedding(adata, basis=\\\"spatial\\\", color=[\\\"total_counts\\\", \\\"n_genes_by_counts\\\"],size=30)\\n\\n if dot_size is None:\\n dot_size = 120000 / adata.shape[0]\\n\\n ncols = min(ncols, len(obs_key))\\n nrows = np.ceil(len(obs_key) / ncols).astype(int)\\n # each panel will have the size of rcParams['figure.figsize']\\n fig = plt.figure(figsize=(ncols * 10, nrows * 8))\\n left = 0.2 / ncols\\n bottom = 0.13 / nrows\\n axs = gridspec.GridSpec(\\n nrows=nrows,\\n ncols=ncols,\\n left=left,\\n right=1 - (ncols - 1) * left - 0.01 / ncols,\\n bottom=bottom,\\n top=1 - (nrows - 1) * bottom - 0.1 / nrows,\\n # hspace=hspace,\\n # wspace=wspace,\\n )\\n\\n if color_list is None:\\n cmap = get_cmap()\\n else:\\n cmap = ListedColormap(color_list)\\n cmap.set_bad(bad_color)\\n # 把特定值改为 np.nan 之后，可以利用 cmap.set_bad(\\\"white\\\") 来遮盖掉这部分数据\\n\\n for i, key in enumerate(obs_key):\\n # color_data = adata.obs_vector(key) # TODO replace by get_cluster_res\\n color_data = get_cluster_res(adata, data_key=key)\\n pc_logic = False\\n\\n # color_data = np.asarray(color_data_raw, dtype=float)\\n order = np.argsort(~pd.isnull(color_data), kind=\\\"stable\\\")\\n# spatial_data = np.array(adata.obsm[pos_key])[:, 0: 2]\\n spatial_data = get_reduce_x(data=adata, data_key=pos_key)[:, 0:2] if pos_key != 'spatial' \\\\\\n else get_position_array(adata, pos_key)\\n color_data = color_data[order]\\n spatial_data = spatial_data[order, :]\\n\\n color_dict = {}\\n has_na = False\\n if pd.api.types.is_categorical_dtype(color_data):\\n pc_logic = True\\n if plot_cluster is None:\\n plot_cluster = list(color_data.categories)\\n if pc_logic:\\n cluster_n = len(np.unique(color_data))\\n if len(color_list) < cluster_n:\\n color_list = color_list * cluster_n\\n cmap = ListedColormap(color_list)\\n cmap.set_bad(bad_color)\\n if len(color_data.categories) > len(plot_cluster):\\n color_data = color_data.replace(color_data.categories.difference(plot_cluster), np.nan)\\n has_na = True\\n color_dict = {str(k): to_hex(v) for k, v in enumerate(color_list)}\\n print(color_dict)\\n color_data = color_data.map(color_dict)\\n if pd.api.types.is_categorical_dtype(color_data):\\n color_data = pd.Categorical(color_data)\\n if has_na:\\n color_data = color_data.add_categories([to_hex(bad_color)])\\n color_data = color_data.fillna(to_hex(bad_color))\\n # color_dict[\\\"NA\\\"]\\n\\n # color_data 是图像中各个点的值，也对应了每个点的颜色。data_points则对应了各个点的坐标\\n ax = fig.add_subplot(axs[i]) # ax = plt.subplot(axs[i]) || ax = fig.add_subplot(axs[1, 1]))\\n ax.set_title(key)\\n ax.set_yticks([])\\n ax.set_xticks([])\\n ax.set_xlabel(\\\"spatial1\\\")\\n ax.set_ylabel(\\\"spatial2\\\")\\n pathcollection = scatter(\\n spatial_data[:, 0],\\n spatial_data[:, 1],\\n ax=ax,\\n marker=\\\".\\\",\\n dot_colors=color_data,\\n dot_size=dot_size\\n )\\n if pc_logic:\\n box = ax.get_position()\\n ax.set_position([box.x0, box.y0, box.width * 0.91, box.height])\\n # -------------modified by qiuping1@genomics.cn-------------\\n # valid_cate = color_data.categories\\n # cat_num = len(adata.obs_vector(key).categories)\\n # for label in adata.obs_vector(key).categories:\\n categories = get_cluster_res(adata, data_key=key).categories\\n cat_num = len(categories)\\n for label in categories:\\n # --------modified end------------------\\n ax.scatter([], [], c=color_dict[label], label=label)\\n ax.legend(\\n frameon=False,\\n loc='center left',\\n bbox_to_anchor=(1, 0.5),\\n ncol=(1 if cat_num <= 14 else 2 if cat_num <= 30 else 3),\\n # fontsize=legend_fontsize,\\n )\\n else:\\n plt.colorbar(pathcollection, ax=ax, pad=0.01, fraction=0.08, aspect=30)\\n ax.autoscale_view()\\n\\n\\ndef plot_violin_distribution(adata): # 小提琴统计图\\n \\\"\\\"\\\"\\n 绘制数据的分布小提琴图。\\n ============ Arguments ============\\n :param adata: AnnData object.\\n ============ Return ============\\n None\\n \\\"\\\"\\\"\\n _, axs = plt.subplots(1, 3, figsize=(15, 4))\\n seaborn.violinplot(y=adata.obs['total_counts'], ax=axs[0])\\n seaborn.violinplot(y=adata.obs['n_genes_by_counts'], ax=axs[1])\\n seaborn.violinplot(y=adata.obs['pct_counts_mt'], ax=axs[2])\\n\\n\\ndef plot_degs(\\n adata: AnnData,\\n groups: Union[str, Sequence[str]] = 'all',\\n n_genes: int = 20,\\n key: Optional[str] = 'find_marker',\\n fontsize: int = 8,\\n ncols: int = 4,\\n sharey: bool = True,\\n ax: Optional[Axes] = None,\\n **kwds,\\n): # scatter plot, 差异基因显著性图，类碎石图\\n \\\"\\\"\\\"\\n Copied from scanpy and modified.\\n \\\"\\\"\\\"\\n\\n # 调整图像 panel/grid 相关参数\\n if 'n_panels_per_row' in kwds:\\n n_panels_per_row = kwds['n_panels_per_row']\\n else:\\n n_panels_per_row = ncols\\n # group_names = adata.uns[key]['names'].dtype.names if groups is None else groups\\n if groups == 'all':\\n group_names = list(adata.uns[key].keys())\\n else:\\n group_names = [groups] if isinstance(groups, str) else groups\\n # one panel for each group\\n # set up the figure\\n n_panels_x = min(n_panels_per_row, len(group_names))\\n n_panels_y = np.ceil(len(group_names) / n_panels_x).astype(int)\\n # 初始化图像\\n width = 10\\n height = 10\\n fig = plt.figure(\\n figsize=(\\n n_panels_x * width, # rcParams['figure.figsize'][0],\\n n_panels_y * height, # rcParams['figure.figsize'][1],\\n )\\n )\\n gs = gridspec.GridSpec(nrows=n_panels_y, ncols=n_panels_x, wspace=0.22, hspace=0.3)\\n\\n ax0 = None\\n ymin = np.Inf\\n ymax = -np.Inf\\n for count, group_name in enumerate(group_names):\\n result = get_degs_res(adata, data_key=key, group_key=group_name, top_k=n_genes)\\n gene_names = result.genes.values\\n scores = result.scores.values\\n # Setting up axis, calculating y bounds\\n if sharey:\\n ymin = min(ymin, np.min(scores))\\n ymax = max(ymax, np.max(scores))\\n\\n if ax0 is None:\\n ax = fig.add_subplot(gs[count])\\n ax0 = ax\\n else:\\n ax = fig.add_subplot(gs[count], sharey=ax0)\\n else:\\n ymin = np.min(scores)\\n ymax = np.max(scores)\\n ymax += 0.3 * (ymax - ymin)\\n\\n ax = fig.add_subplot(gs[count])\\n ax.set_ylim(ymin, ymax)\\n\\n ax.set_xlim(-0.9, n_genes - 0.1)\\n\\n # Making labels\\n for ig, gene_name in enumerate(gene_names):\\n ax.text(\\n ig,\\n scores[ig],\\n gene_name,\\n rotation='vertical',\\n verticalalignment='bottom',\\n horizontalalignment='center',\\n fontsize=fontsize,\\n )\\n\\n ax.set_title(group_name)\\n if count >= n_panels_x * (n_panels_y - 1):\\n ax.set_xlabel('ranking')\\n\\n # print the 'score' label only on the first panel per row.\\n if count % n_panels_x == 0:\\n ax.set_ylabel('score')\\n\\n if sharey is True:\\n ymax += 0.3 * (ymax - ymin)\\n ax.set_ylim(ymin, ymax)\\n\\n\\ndef plot_spatial_distribution(\\n adata: AnnData,\\n obs_key: list = [\\\"total_counts\\\", \\\"n_genes_by_counts\\\"],\\n ncols=2,\\n dot_size=None,\\n color_list=None,\\n invert_y=False\\n): # scatter plot, 表达矩阵空间分布\\n \\\"\\\"\\\"\\n Plot spatial distribution of specified obs data.\\n ============ Arguments ============\\n :param adata: AnnData object.\\n :param obs_key: specified obs key list, for example: [\\\"total_counts\\\", \\\"n_genes_by_counts\\\"]\\n :param ncols: numbr of plot columns.\\n :param dot_size: marker size.\\n :param color_list: Color list.\\n :param invert_y: whether to invert y-axis.\\n ============ Return ============\\n None\\n ============ Example ============\\n plot_spatial_distribution(adata=adata)\\n \\\"\\\"\\\"\\n # sc.pl.embedding(adata, basis=\\\"spatial\\\", color=[\\\"total_counts\\\", \\\"n_genes_by_counts\\\"],size=30)\\n\\n if dot_size is None:\\n dot_size = 120000 / adata.shape[0]\\n\\n ncols = min(ncols, len(obs_key))\\n nrows = np.ceil(len(obs_key) / ncols).astype(int)\\n # each panel will have the size of rcParams['figure.figsize']\\n fig = plt.figure(figsize=(ncols * 10, nrows * 8))\\n left = 0.2 / ncols\\n bottom = 0.13 / nrows\\n axs = gridspec.GridSpec(\\n nrows=nrows,\\n ncols=ncols,\\n left=left,\\n right=1 - (ncols - 1) * left - 0.01 / ncols,\\n bottom=bottom,\\n top=1 - (nrows - 1) * bottom - 0.1 / nrows,\\n # hspace=hspace,\\n # wspace=wspace,\\n )\\n\\n if color_list is None:\\n cmap = get_cmap()\\n else:\\n cmap = ListedColormap(color_list)\\n # 把特定值改为 np.nan 之后，可以利用 cmap.set_bad(\\\"white\\\") 来遮盖掉这部分数据\\n\\n # 散点图上每个点的坐标数据来自于 adata 的 obsm[\\\"spatial\\\"]，每个点的颜色（数值）数据来自于 adata 的 obs_vector()\\n for i, key in enumerate(obs_key):\\n # color_data = np.asarray(adata.obs_vector(key), dtype=float)\\n color_data = adata.obs_vector(key)\\n order = np.argsort(~pd.isnull(color_data), kind=\\\"stable\\\")\\n spatial_data = np.array(adata.obsm[\\\"spatial\\\"])[:, 0: 2]\\n color_data = color_data[order]\\n spatial_data = spatial_data[order, :]\\n\\n # color_data 是图像中各个点的值，也对应了每个点的颜色。data_points则对应了各个点的坐标\\n ax = fig.add_subplot(axs[i]) # ax = plt.subplot(axs[i]) || ax = fig.add_subplot(axs[1, 1]))\\n ax.set_title(key)\\n ax.set_yticks([])\\n ax.set_xticks([])\\n ax.set_xlabel(\\\"spatial1\\\")\\n ax.set_ylabel(\\\"spatial2\\\")\\n pathcollection = scatter(\\n spatial_data[:, 0],\\n spatial_data[:, 1],\\n ax=ax,\\n marker=\\\".\\\",\\n dot_colors=color_data,\\n dot_size=dot_size,\\n cmap=cmap,\\n )\\n plt.colorbar(\\n pathcollection,\\n ax=ax,\\n pad=0.01,\\n fraction=0.08,\\n aspect=30,\\n )\\n ax.autoscale_view()\\n if invert_y:\\n ax.invert_yaxis()\\n\\n\\ndef plot_heatmap_maker_genes(\\n adata: AnnData = None,\\n cluster_method=\\\"phenograph\\\",\\n marker_uns_key=None,\\n num_show_gene=8,\\n show_labels=True,\\n order_cluster=True,\\n marker_clusters=None,\\n cluster_colors_array=None,\\n **kwargs\\n): # heatmap, 差异基因热图\\n \\\"\\\"\\\"\\n 绘制 Marker gene 的热图。热图中每一行代表一个 bin 的所有基因的表达量，所有的 bin 会根据所属的 cluster 进行聚集， cluster 具体展示在热图的左侧，用颜色区分。\\n ============ Arguments ============\\n :param adata: AnnData object.\\n :param cluster_method: method used in clustering. for example: phenograph, leiden\\n :param marker_uns_key: the key of adata.uns, the default value is \\\"marker_genes\\\"\\n :param num_show_gene: number of genes to show in each cluster.\\n :param show_labels: show gene name on axis.\\n :param order_cluster: reorder the cluster list in plot (y axis).\\n :param marker_clusters: the list of clusters to show on the heatmap.\\n :param cluster_colors_array: the list of colors in the color block on the left of heatmap.\\n ============ Return ============\\n\\n ============ Example ============\\n plot_heatmap_maker_genes(adata=adata, marker_uns_key = \\\"rank_genes_groups\\\", figsize = (20, 10))\\n \\\"\\\"\\\"\\n if marker_uns_key is None:\\n marker_uns_key = 'marker_genes' # \\\"rank_genes_groups\\\" in original scanpy pipeline\\n marker_res = adata.uns[marker_uns_key]\\n default_cluster = [i for i in marker_res.keys()]\\n if marker_clusters is None:\\n marker_clusters = default_cluster\\n if not set(marker_clusters).issubset(set(default_cluster)):\\n marker_clusters = default_cluster\\n\\n gene_names_dict = {} # dict in which each cluster is the keyand the num_show_gene are the values\\n\\n for cluster in marker_clusters:\\n top_marker = marker_res[cluster].top_k_marker(top_k_genes=num_show_gene, sort_key='scores')\\n genes_array = top_marker['genes'].values\\n if len(genes_array) == 0:\\n logger.warning(\\\"Cluster {} has no genes.\\\".format(cluster))\\n continue\\n gene_names_dict[cluster] = genes_array\\n gene_names = []\\n gene_group_labels = []\\n gene_group_positions = []\\n start = 0\\n for label, gene_list in gene_names_dict.items():\\n if isinstance(gene_list, str):\\n gene_list = [gene_list]\\n gene_names.extend(list(gene_list))\\n gene_group_labels.append(label)\\n gene_group_positions.append((start, start + len(gene_list) - 1))\\n start += len(gene_list)\\n\\n # 此处获取所有绘图所需的数据 （表达量矩阵）\\n uniq_gene_names = np.unique(gene_names)\\n exp_matrix = adata.X.toarray() if issparse(adata.X) else adata.X\\n draw_df = pd.DataFrame(exp_matrix[:, adata.var.index.get_indexer(uniq_gene_names)],\\n columns=uniq_gene_names, index=adata.obs_names)\\n # add obs values\\n cluster_data = adata.uns[cluster_method].cluster.set_index('bins')\\n draw_df = pd.concat([draw_df, cluster_data], axis=1)\\n draw_df = draw_df[gene_names].set_index(draw_df['cluster'].astype('category'))\\n if order_cluster:\\n draw_df = draw_df.sort_index()\\n kwargs.setdefault(\\\"figsize\\\", (10, 10))\\n kwargs.setdefault(\\\"colorbar_width\\\", 0.2)\\n colorbar_width = kwargs.get(\\\"colorbar_width\\\")\\n figsize = kwargs.get(\\\"figsize\\\")\\n\\n cluster_block_width = kwargs.setdefault(\\\"cluster_block_width\\\", 0.2) if order_cluster else 0\\n if figsize is None:\\n height = 6\\n if show_labels:\\n heatmap_width = len(gene_names) * 0.3\\n else:\\n heatmap_width = 8\\n width = heatmap_width + cluster_block_width\\n else:\\n width, height = figsize\\n heatmap_width = width - cluster_block_width\\n\\n if gene_group_positions is not None and len(gene_group_positions) > 0:\\n # add some space in case 'brackets' want to be plotted on top of the image\\n height_ratios = [0.15, height]\\n else:\\n height_ratios = [0, height]\\n\\n width_ratios = [\\n cluster_block_width,\\n heatmap_width,\\n colorbar_width,\\n ]\\n\\n fig = plt.figure(figsize=(width, height))\\n\\n axs = gridspec.GridSpec(\\n nrows=2,\\n ncols=3,\\n width_ratios=width_ratios,\\n wspace=0.15 / width,\\n hspace=0.13 / height,\\n height_ratios=height_ratios,\\n )\\n\\n heatmap_ax = fig.add_subplot(axs[1, 1])\\n\\n width, height = fig.get_size_inches()\\n max_cbar_height = 4.0\\n if height > max_cbar_height:\\n # to make the colorbar shorter, the\\n # ax is split and the lower portion is used.\\n axs2 = gridspec.GridSpecFromSubplotSpec(2, 1, subplot_spec=axs[1, 2],\\n height_ratios=[height - max_cbar_height, max_cbar_height],\\n )\\n heatmap_cbar_ax = fig.add_subplot(axs2[1])\\n else:\\n heatmap_cbar_ax = fig.add_subplot(axs[1, 2])\\n\\n heatmap(df=draw_df, ax=heatmap_ax,\\n norm=Normalize(vmin=None, vmax=None), plot_colorbar=True, colorbar_ax=heatmap_cbar_ax,\\n show_labels=True, plot_hline=True)\\n\\n if order_cluster:\\n plot_categories_as_colorblocks(\\n fig.add_subplot(axs[1, 0]), draw_df, colors=cluster_colors_array, orientation='left'\\n )\\n\\n # plot cluster legends on top of heatmap_ax (if given)\\n if gene_group_positions is not None and len(gene_group_positions) > 0:\\n plot_gene_groups_brackets(\\n fig.add_subplot(axs[0, 1], sharex=heatmap_ax),\\n group_positions=gene_group_positions,\\n group_labels=gene_group_labels,\\n rotation=None,\\n left_adjustment=-0.3,\\n right_adjustment=0.3,\\n )\\n\"\n },\n {\n \"alpha_fraction\": 0.6450777053833008,\n \"alphanum_fraction\": 0.6709844470024109,\n \"avg_line_length\": 19.3157901763916,\n \"blob_id\": \"e0b8821e51448972842b0596d7ba29c224772cd5\",\n \"content_id\": \"6e56426ee185d43f05f283d62f55808b97650c56\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 386,\n \"license_type\": \"permissive\",\n \"max_line_length\": 53,\n \"num_lines\": 19,\n \"path\": \"/stereo/utils/__init__.py\",\n \"repo_name\": \"leying95/stereopy\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#!/usr/bin/env python3\\n# coding: utf-8\\n\\\"\\\"\\\"\\n@author: Ping Qiu qiuping1@genomics.cn\\n@last modified by: Ping Qiu\\n@file:__init__.py.py\\n@time:2021/03/05\\n\\\"\\\"\\\"\\nimport shutil\\nimport os\\nfrom .correlation import pearson_corr, spearmanr_corr\\nfrom .data_helper import select_group\\n\\n\\ndef remove_file(path):\\n if os.path.isfile(path):\\n os.remove(path)\\n if os.path.isdir(path):\\n shutil.rmtree(path)\\n\"\n },\n {\n \"alpha_fraction\": 0.6289620995521545,\n \"alphanum_fraction\": 0.6656308174133301,\n \"avg_line_length\": 31.836734771728516,\n \"blob_id\": \"929008472630fdf635cba821106fb912cf41f0c5\",\n \"content_id\": \"d99b946e6893eb24287dce6f23965fb054385454\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1609,\n \"license_type\": \"permissive\",\n \"max_line_length\": 112,\n \"num_lines\": 49,\n \"path\": \"/stereo/utils/correlation.py\",\n \"repo_name\": \"leying95/stereopy\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#!/usr/bin/env python3\\n# coding: utf-8\\n\\\"\\\"\\\"\\n@author: Ping Qiu qiuping1@genomics.cn\\n@last modified by: Ping Qiu\\n@file:correlation.py\\n@time:2021/03/11\\n\\\"\\\"\\\"\\nimport numpy as np\\nimport pandas as pd\\nfrom scipy import stats\\n\\n\\ndef pearson(arr1, arr2):\\n \\\"\\\"\\\"\\n calculate pearson correlation between two numpy arrays.\\n :param arr1: one array, the feature is a column. the shape is `m * n`\\n :param arr2: the other array, the feature is a column. the shape is `m * k`\\n :return: a pearson score np.array , the shape is `k * n`\\n \\\"\\\"\\\"\\n assert arr1.shape[0] == arr2.shape[0]\\n n = arr1.shape[0]\\n sums = np.multiply.outer(arr2.sum(0), arr1.sum(0))\\n stds = np.multiply.outer(arr2.std(0), arr1.std(0))\\n return (arr2.T.dot(arr1) - sums / n) / stds / n\\n\\n\\ndef pearson_corr(df1, df2):\\n \\\"\\\"\\\"\\n calculate pearson correlation between two dataframes.\\n :param df1: one dataframe\\n :param df2: the other dataframe\\n :return: a pearson score dataframe, the index is the columns of `df1`, the columns is the columns of `df2`\\n \\\"\\\"\\\"\\n v1, v2 = df1.values, df2.values\\n corr_matrix = pearson(v1, v2)\\n return pd.DataFrame(corr_matrix, df2.columns, df1.columns)\\n\\n\\ndef spearmanr_corr(df1, df2):\\n \\\"\\\"\\\"\\n calculate pearson correlation between two dataframes.\\n :param df1: one dataframe\\n :param df2: the other dataframe\\n :return: a spearmanr score dataframe, the index is the columns of `df1`, the columns is the columns of `df2`\\n \\\"\\\"\\\"\\n score, pvalue = stats.spearmanr(df1.values, df2.values)\\n score = score[df1.shape[1]:, 0:df1.shape[1]]\\n return pd.DataFrame(score, df2.columns, df1.columns)\\n\"\n },\n {\n \"alpha_fraction\": 0.5926466584205627,\n \"alphanum_fraction\": 0.5964400172233582,\n \"avg_line_length\": 35.07368469238281,\n \"blob_id\": \"88d22d27b7f2d3e25e5c1a50cc04b09fd00b9a0c\",\n \"content_id\": \"dd127ef9b878183a451a018bf664e3130c5144eb\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 3427,\n \"license_type\": \"permissive\",\n \"max_line_length\": 118,\n \"num_lines\": 95,\n \"path\": \"/stereo/core/stereo_result.py\",\n \"repo_name\": \"leying95/stereopy\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#!/usr/bin/env python3\\n# coding: utf-8\\n\\\"\\\"\\\"\\n@author: Ping Qiu qiuping1@genomics.cn\\n@last modified by: Ping Qiu\\n@file:stereo_result.py\\n@time:2021/03/18\\n\\\"\\\"\\\"\\nfrom typing import Optional\\nimport numpy as np\\nimport pandas as pd\\nfrom ..log_manager import logger\\n\\n\\nclass StereoResult(object):\\n def __init__(self, name: str = 'stereo', param: Optional[dict] = None):\\n self.name = name\\n self.params = {} if param is None else param\\n\\n def update_params(self, v):\\n self.params = v\\n\\n def __str__(self):\\n class_info = f'{self.__class__.__name__} of {self.name}. \\\\n'\\n class_info += f' params: {self.params}\\\\n'\\n return class_info\\n\\n def __repr__(self):\\n return self.__str__()\\n\\n\\nclass DimReduceResult(StereoResult):\\n def __init__(self, name: str = 'dim_reduce', param: Optional[dict] = None, x_reduce: Optional[np.ndarray] = None,\\n variance_pca: Optional[np.ndarray] = None, variance_ratio: Optional[np.ndarray] = None,\\n pcs: Optional[np.ndarray] = None):\\n super(DimReduceResult, self).__init__(name, param)\\n self.x_reduce = x_reduce\\n self.variance_pca = variance_pca\\n self.variance_ratio = variance_ratio\\n self.pcs = pcs\\n\\n\\nclass FindMarkerResult(StereoResult):\\n def __init__(self, name: str = 'find_marker', param: Optional[dict] = None,\\n degs_data: Optional[pd.DataFrame] = None):\\n super(FindMarkerResult, self).__init__(name, param)\\n self.degs_data = degs_data\\n\\n def __str__(self):\\n info = super(FindMarkerResult, self).__str__()\\n if self.degs_data is not None:\\n info += f' result: a DataFrame which has `genes`,`pvalues`,`pvalues_adj`, `log2fc`, `score` columns.\\\\n'\\n info += f' the shape is: {self.degs_data.shape}'\\n return info\\n\\n def top_k_marker(self, top_k_genes=10, sort_key='pvalues', ascend=False):\\n \\\"\\\"\\\"\\n obtain the first k significantly different genes\\n :param top_k_genes: the number of top k\\n :param sort_key: sort by the column\\n :param ascend: the ascend order of sorting.\\n :return:\\n \\\"\\\"\\\"\\n if self.degs_data is not None:\\n top_k_data = self.degs_data.sort_values(by=sort_key, ascending=ascend).head(top_k_genes)\\n return top_k_data\\n else:\\n logger.warning('the result of degs is None, return None.')\\n return None\\n\\n\\nclass CellTypeResult(StereoResult):\\n def __init__(self, name='cell_type_anno', param=None, anno_data=None):\\n super(CellTypeResult, self).__init__(name=name, param=param)\\n self.anno_data = anno_data\\n\\n def __str__(self):\\n info = super(CellTypeResult, self).__str__()\\n if self.anno_data is not None:\\n info += f' result: a DataFrame which has `cells`,`cell type`,`corr_score` columns.\\\\n'\\n info += f' the shape is: {self.anno_data.shape}'\\n return info\\n\\n\\nclass ClusterResult(StereoResult):\\n def __init__(self, name='cluster', param=None, cluster_info=None):\\n super(ClusterResult, self).__init__(name=name, param=param)\\n self.cluster = cluster_info\\n\\n def __str__(self):\\n info = super(ClusterResult, self).__str__()\\n if self.cluster is not None:\\n info += f' result: a DataFrame which has `cells`,`cluster` columns.\\\\n'\\n info += f' the shape is: {self.cluster.shape}'\\n return info\\n\"\n },\n {\n \"alpha_fraction\": 0.5367646813392639,\n \"alphanum_fraction\": 0.6102941036224365,\n \"avg_line_length\": 16,\n \"blob_id\": \"91821cce15c5c57d0d9f7879ebe521c065656519\",\n \"content_id\": \"726bfa3d8ddd4c38dd355f36eb882616ac52e353\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 136,\n \"license_type\": \"permissive\",\n \"max_line_length\": 25,\n \"num_lines\": 8,\n \"path\": \"/stereo/core/__init__.py\",\n \"repo_name\": \"leying95/stereopy\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#!/usr/bin/env python3\\n# coding: utf-8\\n\\\"\\\"\\\"\\n@author: Ping Qiu qiuping1@genomics.cn\\n@last modified by: Ping Qiu\\n@file:__init__.py.py\\n@time:2021/03/17\\n\\\"\\\"\\\"\\n\"\n },\n {\n \"alpha_fraction\": 0.5546501278877258,\n \"alphanum_fraction\": 0.5627103447914124,\n \"avg_line_length\": 31.63005828857422,\n \"blob_id\": \"c3432564975ba70a1548330bb225b99d38d4b4bf\",\n \"content_id\": \"050413ffad7b852cc1e8d0feae37c28313c3be0a\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 11290,\n \"license_type\": \"permissive\",\n \"max_line_length\": 101,\n \"num_lines\": 346,\n \"path\": \"/stereo/plots/_plot_basic/heatmap_plt.py\",\n \"repo_name\": \"leying95/stereopy\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#!/usr/bin/env python3\\n# coding: utf-8\\n\\\"\\\"\\\"\\n@author: Shixu He heshixu@genomics.cn\\n@last modified by: Shixu He\\n@file:heatmap_plt.py\\n@time:2021/03/15\\n\\\"\\\"\\\"\\n\\nfrom matplotlib.cm import get_cmap\\nfrom matplotlib.axes import Axes\\nimport matplotlib.pyplot as plt\\nfrom matplotlib.colors import Normalize\\nfrom matplotlib import gridspec\\n\\nfrom anndata import AnnData\\nimport numpy as np\\nimport pandas as pd\\n\\nfrom typing import List, Iterable, Sequence, Optional, Tuple\\nfrom typing_extensions import Literal\\n\\nfrom ...log_manager import logger\\n\\n\\ndef heatmap(df: pd.DataFrame = None, ax: Axes = None, cmap=None, norm=None, plot_colorbar=False,\\n colorbar_ax: Axes = None, show_labels=True, plot_hline=False, **kwargs):\\n \\\"\\\"\\\"\\n :param df:\\n :param ax:\\n :param cmap:\\n :param norm:\\n :param plot_colorbar:\\n :param colorbar_ax:\\n :param show_labels:\\n :param plot_hline:\\n :param kwargs:\\n :return:\\n \\\"\\\"\\\"\\n\\n if norm == None:\\n norm = Normalize(vmin=None, vmax=None)\\n if (plot_colorbar and colorbar_ax == None):\\n logger.warning(\\\"Colorbar ax is not provided.\\\")\\n plot_colorbar = False\\n\\n kwargs.setdefault('interpolation', 'nearest')\\n\\n im = ax.imshow(df.values, aspect='auto', norm=norm, **kwargs)\\n\\n ax.set_ylim(df.shape[0] - 0.5, -0.5)\\n ax.set_xlim(-0.5, df.shape[1] - 0.5)\\n ax.tick_params(axis='y', left=False, labelleft=False)\\n ax.set_ylabel('')\\n ax.grid(False)\\n\\n if show_labels:\\n ax.tick_params(axis='x', labelsize='small')\\n ax.set_xticks(np.arange(df.shape[1]))\\n ax.set_xticklabels(list(df.columns), rotation=90)\\n else:\\n ax.tick_params(axis='x', labelbottom=False, bottom=False)\\n\\n if plot_colorbar:\\n plt.colorbar(im, cax=colorbar_ax)\\n\\n if plot_hline:\\n line_coord = (\\n np.cumsum(df.index.value_counts(sort=False))[:-1] - 0.5\\n )\\n ax.hlines(\\n line_coord,\\n -0.5,\\n df.shape[1] - 0.5,\\n lw=1,\\n color='black',\\n zorder=10,\\n clip_on=False,\\n )\\n\\n\\ndef plot_categories_as_colorblocks(\\n groupby_ax: Axes,\\n obs_tidy: pd.DataFrame,\\n colors=None,\\n orientation: Literal['top', 'bottom', 'left', 'right'] = 'left',\\n cmap_name: str = 'tab20',\\n):\\n \\\"\\\"\\\"from scanpy\\\"\\\"\\\"\\n\\n groupby = obs_tidy.index.name\\n from matplotlib.colors import ListedColormap, BoundaryNorm\\n\\n if colors is None:\\n groupby_cmap = plt.get_cmap(cmap_name)\\n else:\\n groupby_cmap = ListedColormap(colors, groupby + '_cmap')\\n norm = BoundaryNorm(np.arange(groupby_cmap.N + 1) - 0.5, groupby_cmap.N)\\n\\n # determine groupby label positions such that they appear\\n # centered next/below to the color code rectangle assigned to the category\\n value_sum = 0\\n ticks = [] # list of centered position of the labels\\n labels = []\\n label2code = {} # dictionary of numerical values asigned to each label\\n for code, (label, value) in enumerate(\\n obs_tidy.index.value_counts(sort=False).iteritems()\\n ):\\n ticks.append(value_sum + (value / 2))\\n labels.append(label)\\n value_sum += value\\n label2code[label] = code\\n\\n groupby_ax.grid(False)\\n\\n if orientation == 'left':\\n groupby_ax.imshow(\\n np.array([[label2code[lab] for lab in obs_tidy.index]]).T,\\n aspect='auto',\\n cmap=groupby_cmap,\\n norm=norm,\\n )\\n if len(labels) > 1:\\n groupby_ax.set_yticks(ticks)\\n groupby_ax.set_yticklabels(labels)\\n\\n # remove y ticks\\n groupby_ax.tick_params(axis='y', left=False, labelsize='small')\\n # remove x ticks and labels\\n groupby_ax.tick_params(axis='x', bottom=False, labelbottom=False)\\n\\n # remove surrounding lines\\n groupby_ax.spines['right'].set_visible(False)\\n groupby_ax.spines['top'].set_visible(False)\\n groupby_ax.spines['left'].set_visible(False)\\n groupby_ax.spines['bottom'].set_visible(False)\\n\\n groupby_ax.set_ylabel(groupby)\\n else:\\n groupby_ax.imshow(\\n np.array([[label2code[lab] for lab in obs_tidy.index]]),\\n aspect='auto',\\n cmap=groupby_cmap,\\n norm=norm,\\n )\\n if len(labels) > 1:\\n groupby_ax.set_xticks(ticks)\\n if max([len(str(x)) for x in labels]) < 3:\\n # if the labels are small do not rotate them\\n rotation = 0\\n else:\\n rotation = 90\\n groupby_ax.set_xticklabels(labels, rotation=rotation)\\n\\n # remove x ticks\\n groupby_ax.tick_params(axis='x', bottom=False, labelsize='small')\\n # remove y ticks and labels\\n groupby_ax.tick_params(axis='y', left=False, labelleft=False)\\n\\n # remove surrounding lines\\n groupby_ax.spines['right'].set_visible(False)\\n groupby_ax.spines['top'].set_visible(False)\\n groupby_ax.spines['left'].set_visible(False)\\n groupby_ax.spines['bottom'].set_visible(False)\\n\\n groupby_ax.set_xlabel(groupby)\\n\\n return label2code, ticks, labels, groupby_cmap, norm\\n\\n\\ndef plot_gene_groups_brackets(\\n gene_groups_ax: Axes,\\n group_positions: Iterable[Tuple[int, int]],\\n group_labels: Sequence[str],\\n left_adjustment: float = -0.3,\\n right_adjustment: float = 0.3,\\n rotation: Optional[float] = None,\\n orientation: Literal['top', 'right'] = 'top',\\n):\\n \\\"\\\"\\\"from scanpy\\\"\\\"\\\"\\n import matplotlib.patches as patches\\n from matplotlib.path import Path\\n\\n # get the 'brackets' coordinates as lists of start and end positions\\n\\n left = [x[0] + left_adjustment for x in group_positions]\\n right = [x[1] + right_adjustment for x in group_positions]\\n\\n # verts and codes are used by PathPatch to make the brackets\\n verts = []\\n codes = []\\n if orientation == 'top':\\n # rotate labels if any of them is longer than 4 characters\\n if rotation is None and group_labels:\\n if max([len(x) for x in group_labels]) > 4:\\n rotation = 90\\n else:\\n rotation = 0\\n for idx in range(len(left)):\\n verts.append((left[idx], 0)) # lower-left\\n verts.append((left[idx], 0.6)) # upper-left\\n verts.append((right[idx], 0.6)) # upper-right\\n verts.append((right[idx], 0)) # lower-right\\n\\n codes.append(Path.MOVETO)\\n codes.append(Path.LINETO)\\n codes.append(Path.LINETO)\\n codes.append(Path.LINETO)\\n\\n try:\\n group_x_center = left[idx] + float(right[idx] - left[idx]) / 2\\n gene_groups_ax.text(\\n group_x_center,\\n 1.1,\\n group_labels[idx],\\n ha='center',\\n va='bottom',\\n rotation=rotation,\\n )\\n except:\\n pass\\n else:\\n top = left\\n bottom = right\\n for idx in range(len(top)):\\n verts.append((0, top[idx])) # upper-left\\n verts.append((0.15, top[idx])) # upper-right\\n verts.append((0.15, bottom[idx])) # lower-right\\n verts.append((0, bottom[idx])) # lower-left\\n\\n codes.append(Path.MOVETO)\\n codes.append(Path.LINETO)\\n codes.append(Path.LINETO)\\n codes.append(Path.LINETO)\\n\\n try:\\n diff = bottom[idx] - top[idx]\\n group_y_center = top[idx] + float(diff) / 2\\n if diff * 2 < len(group_labels[idx]):\\n # cut label to fit available space\\n group_labels[idx] = group_labels[idx][: int(diff * 2)] + \\\".\\\"\\n gene_groups_ax.text(\\n 0.6,\\n group_y_center,\\n group_labels[idx],\\n ha='right',\\n va='center',\\n rotation=270,\\n fontsize='small',\\n )\\n except Exception as e:\\n print('problems {}'.format(e))\\n pass\\n\\n path = Path(verts, codes)\\n\\n patch = patches.PathPatch(path, facecolor='none', lw=1.5)\\n\\n gene_groups_ax.add_patch(patch)\\n gene_groups_ax.grid(False)\\n gene_groups_ax.axis('off')\\n # remove y ticks\\n gene_groups_ax.tick_params(axis='y', left=False, labelleft=False)\\n # remove x ticks and labels\\n gene_groups_ax.tick_params(\\n axis='x', bottom=False, labelbottom=False, labeltop=False\\n )\\n\\n\\ndef _check_indices(\\n dim_df: pd.DataFrame,\\n alt_index: pd.Index,\\n dim: \\\"Literal['obs', 'var']\\\",\\n keys: List[str],\\n alias_index: pd.Index = None,\\n use_raw: bool = False,\\n):\\n \\\"\\\"\\\"from scanpy\\\"\\\"\\\"\\n if use_raw:\\n alt_repr = \\\"adata.raw\\\"\\n else:\\n alt_repr = \\\"adata\\\"\\n\\n alt_dim = (\\\"obs\\\", \\\"var\\\")[dim == \\\"obs\\\"]\\n\\n alias_name = None\\n if alias_index is not None:\\n alt_names = pd.Series(alt_index, index=alias_index)\\n alias_name = alias_index.name\\n alt_search_repr = f\\\"{alt_dim}['{alias_name}']\\\"\\n else:\\n alt_names = pd.Series(alt_index, index=alt_index)\\n alt_search_repr = f\\\"{alt_dim}_names\\\"\\n\\n col_keys = []\\n index_keys = []\\n index_aliases = []\\n not_found = []\\n\\n # check that adata.obs does not contain duplicated columns\\n # if duplicated columns names are present, they will\\n # be further duplicated when selecting them.\\n if not dim_df.columns.is_unique:\\n dup_cols = dim_df.columns[dim_df.columns.duplicated()].tolist()\\n raise ValueError(\\n f\\\"adata.{dim} contains duplicated columns. Please rename or remove \\\"\\n \\\"these columns first.\\\\n`\\\"\\n f\\\"Duplicated columns {dup_cols}\\\"\\n )\\n\\n if not alt_index.is_unique:\\n raise ValueError(\\n f\\\"{alt_repr}.{alt_dim}_names contains duplicated items\\\\n\\\"\\n f\\\"Please rename these {alt_dim} names first for example using \\\"\\n f\\\"`adata.{alt_dim}_names_make_unique()`\\\"\\n )\\n\\n # use only unique keys, otherwise duplicated keys will\\n # further duplicate when reordering the keys later in the function\\n for key in np.unique(keys):\\n if key in dim_df.columns:\\n col_keys.append(key)\\n if key in alt_names.index:\\n raise KeyError(\\n f\\\"The key '{key}' is found in both adata.{dim} and {alt_repr}.{alt_search_repr}.\\\"\\n )\\n elif key in alt_names.index:\\n val = alt_names[key]\\n if isinstance(val, pd.Series):\\n # while var_names must be unique, adata.var[gene_symbols] does not\\n # It's still ambiguous to refer to a duplicated entry though.\\n assert alias_index is not None\\n raise KeyError(\\n f\\\"Found duplicate entries for '{key}' in {alt_repr}.{alt_search_repr}.\\\"\\n )\\n index_keys.append(val)\\n index_aliases.append(key)\\n else:\\n not_found.append(key)\\n if len(not_found) > 0:\\n raise KeyError(\\n f\\\"Could not find keys '{not_found}' in columns of `adata.{dim}` or in\\\"\\n f\\\" {alt_repr}.{alt_search_repr}.\\\"\\n )\\n\\n return col_keys, index_keys, index_aliases\\n\"\n }\n]"},"num_files":{"kind":"number","value":16,"string":"16"}}},{"rowIdx":2069,"cells":{"repo_name":{"kind":"string","value":"5l1v3r1/gg-1"},"repo_url":{"kind":"string","value":"https://github.com/5l1v3r1/gg-1"},"snapshot_id":{"kind":"string","value":"cc80c441841295c81fd02ec4e3fb946c5d7fd1d3"},"revision_id":{"kind":"string","value":"59d6c5e2f7cae749e5c2918f6e745ab17289c2c1"},"directory_id":{"kind":"string","value":"24ebc32fbefaab193b2d8ad66d3736981c932ced"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"string","value":"2022-04-20T17:54:24.132367"},"revision_date":{"kind":"string","value":"2020-04-21T05:02:56"},"committer_date":{"kind":"string","value":"2020-04-21T05:02:56"},"github_id":{"kind":"null"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.6551724076271057,"alphanum_fraction":0.6551724076271057,"avg_line_length":13.5,"blob_id":"11abda5e3fa3b52ec2a707a788d639c69d9e2244","content_id":"7a9e5be7a71c2582b80934cf4e939b10c82f1b10","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":29,"license_type":"no_license","max_line_length":16,"num_lines":2,"path":"/ty.py","repo_name":"5l1v3r1/gg-1","src_encoding":"UTF-8","text":"print('HW')\nprint('TESTING')\n"}],"string":"[\n {\n \"alpha_fraction\": 0.6551724076271057,\n \"alphanum_fraction\": 0.6551724076271057,\n \"avg_line_length\": 13.5,\n \"blob_id\": \"11abda5e3fa3b52ec2a707a788d639c69d9e2244\",\n \"content_id\": \"7a9e5be7a71c2582b80934cf4e939b10c82f1b10\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 29,\n \"license_type\": \"no_license\",\n \"max_line_length\": 16,\n \"num_lines\": 2,\n \"path\": \"/ty.py\",\n \"repo_name\": \"5l1v3r1/gg-1\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"print('HW')\\nprint('TESTING')\\n\"\n }\n]"},"num_files":{"kind":"number","value":1,"string":"1"}}},{"rowIdx":2070,"cells":{"repo_name":{"kind":"string","value":"vaibhavj08/Limitingservice"},"repo_url":{"kind":"string","value":"https://github.com/vaibhavj08/Limitingservice"},"snapshot_id":{"kind":"string","value":"d1592899789ead7524e71f4545d14f3ac26d2a03"},"revision_id":{"kind":"string","value":"b383103dee5efba59394f3403de206b7ab0f4121"},"directory_id":{"kind":"string","value":"7bec193bcf445e3cf959b8b6c56f261a71e2a1e5"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"string","value":"2023-08-05T20:37:45.947169"},"revision_date":{"kind":"string","value":"2020-07-17T11:57:33"},"committer_date":{"kind":"string","value":"2020-07-17T11:57:33"},"github_id":{"kind":"number","value":277577260,"string":"277,577,260"},"star_events_count":{"kind":"number","value":1,"string":"1"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"string","value":"2020-07-06T15:18:26"},"gha_updated_at":{"kind":"string","value":"2020-07-17T12:01:01"},"gha_pushed_at":{"kind":"string","value":"2021-09-22T19:26:13"},"gha_language":{"kind":"string","value":"Python"},"files":{"kind":"list like","value":[{"alpha_fraction":0.4639175236225128,"alphanum_fraction":0.6907216310501099,"avg_line_length":15.166666984558105,"blob_id":"a93c311ef955061e185e085c0e9bca17fc303c3a","content_id":"2647df0b927943297ea236a6b9409a4469cbb284","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Text","length_bytes":97,"license_type":"no_license","max_line_length":16,"num_lines":6,"path":"/requirements.txt","repo_name":"vaibhavj08/Limitingservice","src_encoding":"UTF-8","text":"Django==3.0.8\nrequests==2.24.0\ngunicorn==20.0.4\nfastapi==0.59.0\nratelimit==2.2.1\nuvicorn==0.11.5\n"},{"alpha_fraction":0.7213114500045776,"alphanum_fraction":0.75,"avg_line_length":17.769229888916016,"blob_id":"7e13d0158a745124e87ee31a1bd2c5f142e1cab3","content_id":"b8cf1ab15854fee75f3cf9ace7e6d7ffa17ded31","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":244,"license_type":"no_license","max_line_length":44,"num_lines":13,"path":"/number.py","repo_name":"vaibhavj08/Limitingservice","src_encoding":"UTF-8","text":"from fastapi import FastAPI\nimport random\nfrom ratelimit import limits,sleep_and_retry\n\none_minute=60\napp = FastAPI()\n\n\n@app.get('/get_number')\n@sleep_and_retry\n@limits(calls=5,period=one_minute)\ndef numbers():\n return random.randint(1,100)\n"},{"alpha_fraction":0.6482494473457336,"alphanum_fraction":0.662472665309906,"avg_line_length":27.13846206665039,"blob_id":"5bc4cd0ffd6e51c47516cc76f59a953de3f5616b","content_id":"4e8cb2cd19f978568fe87ba60c69fce253166c9d","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1828,"license_type":"no_license","max_line_length":93,"num_lines":65,"path":"/api_call/views.py","repo_name":"vaibhavj08/Limitingservice","src_encoding":"UTF-8","text":"from django.shortcuts import render,redirect\nfrom django.http import HttpResponse\nimport requests\nfrom django.contrib import auth\nfrom django.contrib.auth.models import User\n\n\n# Create your views here.\n#function to signup\ndef signup(request):\n if request.method == 'POST':\n username = request.POST.get('username')\n password = request.POST.get('password')\n user = User.objects.create_user(username = username,password = password)\n user.save()\n return redirect('/')\n else:\n return render(request,'home.html')\n\n#function to login\ndef login(request):\n if request.method == 'POST':\n username = request.POST.get('username')\n password = request.POST.get('password')\n user = auth.authenticate(username =username,password = password)\n\n if user is not None:\n auth.login(request,user)\n return redirect('/api_call')\n else:\n return HttpResponse(\"[0-9]+)/$', views.Blogs, base_name=\"blog-detail\")\n \nurlpatterns = [\n url(r'^', include(api_router.urls)),\n]\n"}],"string":"[\n {\n \"alpha_fraction\": 0.7755555510520935,\n \"alphanum_fraction\": 0.7777777910232544,\n \"avg_line_length\": 25.352941513061523,\n \"blob_id\": \"90a133788ded10d3e3deaf8521f3633e403f332d\",\n \"content_id\": \"720ab063eab3a65269e0b259f3a30b1acb056c90\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 450,\n \"license_type\": \"no_license\",\n \"max_line_length\": 45,\n \"num_lines\": 17,\n \"path\": \"/myapp/blog/views.py\",\n \"repo_name\": \"abdulazeeznaji/funny-learn\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: utf-8 -*-\\nfrom __future__ import unicode_literals\\n\\nfrom django.shortcuts import render\\n\\n# Create your views here.\\n\\nfrom blog.models import Blog\\nfrom rest_framework import generics, viewsets\\nfrom rest_framework.response import Response\\nfrom rest_framework.reverse import reverse\\nfrom blog.serializers import BlogSerializer\\n \\n \\nclass Blogs(viewsets.ModelViewSet):\\n queryset = Blog.objects.all()\\n serializer_class = BlogSerializer\\n\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.6887755393981934,\n \"alphanum_fraction\": 0.6989796161651611,\n \"avg_line_length\": 25.200000762939453,\n \"blob_id\": \"d0b5d45c1a62b212a496551a26d1af21bb36d7ed\",\n \"content_id\": \"fbe918cf218acb973c4290aae6b1c636a877a9a1\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 392,\n \"license_type\": \"no_license\",\n \"max_line_length\": 81,\n \"num_lines\": 15,\n \"path\": \"/myapp/blog/models.py\",\n \"repo_name\": \"abdulazeeznaji/funny-learn\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: utf-8 -*-\\nfrom __future__ import unicode_literals\\n\\nfrom django.db import models\\nfrom users.models import User\\n \\n \\nclass Blog(models.Model):\\n created = models.DateTimeField(auto_now_add=True)\\n name = models.CharField(max_length=100, unique=True, blank=False, null=False)\\n isComplete = models.BooleanField(default=False)\\n\\n \\n class Meta:\\n ordering = ('created',)\"\n },\n {\n \"alpha_fraction\": 0.5142857432365417,\n \"alphanum_fraction\": 0.5857142806053162,\n \"avg_line_length\": 16.625,\n \"blob_id\": \"ff67e4313ae04304520ebe9ae02857346abb26e3\",\n \"content_id\": \"cdc2331ad9f80dbafc2b708142b6ca56f8f01f17\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"JavaScript\",\n \"length_bytes\": 140,\n \"license_type\": \"no_license\",\n \"max_line_length\": 46,\n \"num_lines\": 8,\n \"path\": \"/myapp/src/lib/services.js\",\n \"repo_name\": \"abdulazeeznaji/funny-learn\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"const baseUrl = 'http://127.0.0.1:8000/blogs/'\\n\\n\\nexport const getBlogs = () =>{\\n return fetch(baseUrl)\\n .then(res => res.json() )\\n\\n}\"\n },\n {\n \"alpha_fraction\": 0.47457626461982727,\n \"alphanum_fraction\": 0.47457626461982727,\n \"avg_line_length\": 12.354838371276855,\n \"blob_id\": \"5ae00bd08c6806d020662cdf855bbf8db7fb839c\",\n \"content_id\": \"c3760d27b6b76c04915deec088e3583aad7f85d6\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"JavaScript\",\n \"length_bytes\": 413,\n \"license_type\": \"no_license\",\n \"max_line_length\": 46,\n \"num_lines\": 31,\n \"path\": \"/myapp/src/Main.js\",\n \"repo_name\": \"abdulazeeznaji/funny-learn\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import React from 'react'\\nimport {getBlogs} from './lib/services'\\n\\n\\n\\n class Main extends React.Component{\\n constructor(){\\n super()\\n this.state = {\\n blogs:[]\\n }\\n }\\n componentWillMount(){\\n getBlogs()\\n .then(blogs => this.setState({blogs}))\\n }\\n\\n render(){\\n return (\\n [0-9]+)/$', views.Blogs, base_name=\\\"blog-detail\\\")\\n \\nurlpatterns = [\\n url(r'^', include(api_router.urls)),\\n]\\n\"\n }\n]"},"num_files":{"kind":"number","value":6,"string":"6"}}},{"rowIdx":2072,"cells":{"repo_name":{"kind":"string","value":"owenvvv/Steam_helper"},"repo_url":{"kind":"string","value":"https://github.com/owenvvv/Steam_helper"},"snapshot_id":{"kind":"string","value":"97129ddc348bb699349b2dbbae9f1ddc80342bcc"},"revision_id":{"kind":"string","value":"7af451bf067a079ff271a0608f69f85cf0fa7f64"},"directory_id":{"kind":"string","value":"99a2e7ed0f8bf12db72824cfc416d79b122d8193"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"string","value":"2021-05-18T19:14:33.166248"},"revision_date":{"kind":"string","value":"2020-03-31T02:59:46"},"committer_date":{"kind":"string","value":"2020-03-31T03:02:28"},"github_id":{"kind":"number","value":251373679,"string":"251,373,679"},"star_events_count":{"kind":"number","value":2,"string":"2"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.6763636469841003,"alphanum_fraction":0.6818181872367859,"avg_line_length":38.35714340209961,"blob_id":"070cf9b39620a91a425864d158114dc1bb2ca743","content_id":"6eaed83edd4e2e6164d29aae6d37ce4830b811e6","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":550,"license_type":"no_license","max_line_length":122,"num_lines":14,"path":"/steam-scraper/test.py","repo_name":"owenvvv/Steam_helper","src_encoding":"UTF-8","text":"from scrapy.loader.processors import Compose, Join, MapCompose, TakeFirst\nimport pandas as pd\n\"\"\"\npipi = Compose(lambda x: x[0], str.upper)\nprint(pipi(['iss', 'nus', 'mtech', 'ebac']))\n\npipi = MapCompose(lambda x: x[0], str.upper)\nprint(pipi(['iss', 'nus', 'mtech', 'ebac']))\n\"\"\"\nsteam_id = pd.read_csv(\"D:\\\\NUS BA\\\\class\\\\nlp\\\\Project\\\\steam-scraper-master\\\\steam\\\\spiders\\\\steam_id.csv\", header=None)\nsteam_id = list(steam_id.iloc[:,0])\nprint(len(steam_id))\nprint(len(list(set(steam_id))))\n#steam_id .to_csv(\"steam_id.csv\",header=False,index=False)"},{"alpha_fraction":0.6060332655906677,"alphanum_fraction":0.6141618490219116,"avg_line_length":36.154361724853516,"blob_id":"85cf4caf09664ac2ea9b2dc2871cf2bb4e4edebe","content_id":"d8eddcdf22b48569ec90d899ceefb2974130786e","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":5536,"license_type":"no_license","max_line_length":116,"num_lines":149,"path":"/recommendegine.py","repo_name":"owenvvv/Steam_helper","src_encoding":"UTF-8","text":"import pickle as pk\nimport pandas as pd\nimport pandas as pd\nimport numpy as np\nimport nltk\nfrom nltk.corpus import stopwords\nfrom nltk.tokenize import word_tokenize\nfrom nltk import pos_tag\nfrom pytorch_pretrained_bert import BertTokenizer, BertModel, BertForMaskedLM\nfrom scipy.spatial.distance import cosine\nimport torch\n\nmystopwords = stopwords.words(\"English\") + ['game', 'play', 'steam']\nWNlemma = nltk.WordNetLemmatizer()\nnn = ['NN', 'NNS', 'NNP', 'NNPS', 'CD']\n\ntokenizer = BertTokenizer.from_pretrained('bert-base-uncased')\nmodel = BertModel.from_pretrained('bert-base-uncased')\nmodel.eval()\n\nDoc2vec = pk.load(open('./data/des2vec.pkl', 'rb'))\nAspect = pd.read_csv('./data/Ratewithaspect.csv', index_col=0)\nAspect = Aspect.reset_index()\nTagSmall = pd.read_csv('./data/Tagsmall.csv')\nDatasmall = pd.read_csv('./data/steam_small.csv', index_col=0)\ndescrip1 = pk.load(open('./data/short_descrip.pkl', 'rb'))\nkeywords = pd.read_excel('./data/keywords.xlsx')\n\nkeywords_class = {'Gameplay': list(keywords[keywords['Gameplay'].isnull() == False]['Gameplay']),\n 'Market': list(keywords[keywords['Market'].isnull() == False]['Market']),\n 'Narrative': list(keywords[keywords['Narrative'].isnull() == False]['Narrative']),\n 'Social': list(keywords[keywords['Social'].isnull() == False]['Social']),\n 'Graphics': list(keywords[keywords['Graphics'].isnull() == False]['Graphics']),\n 'Technical': list(keywords[keywords['Technical'].isnull() == False]['Technical']),\n 'Audio': list(keywords[keywords['Audio'].isnull() == False]['Audio']),\n 'Content': list(keywords[keywords['Content'].isnull() == False]['Content'])}\nTagnames = []\nDatasmall['avgscore'] = Datasmall.apply(\n lambda row: row.positive_ratings / (row.positive_ratings + row.negative_ratings), axis=1)\n\napplist = Datasmall['appid']\nfor tag in list(TagSmall.columns):\n Tagnames.append(tag.replace('_', ' '))\n\n\ndef recommend(query, tags):\n query = query.lower()\n #print(query)\n selectaspect = []\n for key in keywords_class.keys():\n for word in keywords_class[key]:\n if word.lower() in query.split(' '):\n selectaspect.append(key)\n print(key)\n\n genre = tags.get('genre')\n for g in genre:\n query=query + ' '+ str(g)\n characters = tags.get('characters')\n for c in characters:\n query = query + ' '+ str(c)\n print(query)\n selecttag = []\n for tags in Tagnames:\n if tags in query:\n selecttag.append(tags)\n print(tags)\n status = []\n finalids = applist\n if len(selecttag) > 0:\n for tag in selecttag:\n finalids = TagSmall[(TagSmall[tag.replace(' ', '_')] > 5) & (TagSmall['appid'].isin(finalids))]['appid']\n else:\n finalids = []\n\n # 1 dont have aspect\n # 2 have aspect\n # 3 dont match\n\n if len(finalids) > 5:\n if len(selectaspect) == 0:\n status.append(1)\n status.append(selecttag[0])\n return list(\n Datasmall[Datasmall['appid'].isin(finalids)].sort_values('avgscore', ascending=False)['appid'][\n 0:5]), status\n else:\n status.append(2)\n status.append(selecttag[0])\n status.append(selectaspect[0])\n return list(\n Aspect[Aspect['gameid'].isin(finalids)].sort_values(selectaspect[0], ascending=False)['gameid'][\n 0:5]), status\n else:\n status.append(3)\n gameids = recomend_by_keyword(demand=query, dataframe=descrip1, n=5)\n if gameids!= '':\n return gameids,status\n return list(recomend_by_description(demand=query, dataframe=Doc2vec, n=5)), status\n\n\ndef recomend_by_description(demand, dataframe, n):\n print('use similar result')\n marked_text = \"[CLS] \" + demand + \" [SEP]\"\n tokenized_text = tokenizer.tokenize(marked_text)\n if len(tokenized_text) > 512:\n tokenized_text = tokenized_text[:512]\n indexed_tokens = tokenizer.convert_tokens_to_ids(tokenized_text)\n segments_ids = [1] * len(tokenized_text)\n tokens_tensor = torch.tensor([indexed_tokens])\n segments_tensors = torch.tensor([segments_ids])\n with torch.no_grad():\n encoded_layers, _ = model(tokens_tensor, segments_tensors)\n token_vecs = encoded_layers[11][0]\n sentence_embedding = torch.mean(token_vecs, dim=0)\n cos = []\n for i in range(len(dataframe)):\n tmp = cosine(sentence_embedding, dataframe.iloc[i][1])\n cos.append(tmp)\n dataframe['cos'] = cos\n dataframe.sort_values(by=['cos'], inplace=True, ascending=False, )\n return dataframe[:n]['appid'].values\n\n\ndef pre_process(text):\n try:\n tokens = nltk.word_tokenize(text)\n tokens = [t[0] for t in pos_tag(tokens) if t[1] in nn]\n tokens = [WNlemma.lemmatize(t.lower()) for t in tokens]\n tokens = [t for t in tokens if t not in mystopwords]\n return tokens\n except Exception:\n return ('')\n\n\ndef recomend_by_keyword(demand, dataframe, n):\n demand = list(set(pre_process(demand)))\n nums = []\n for i in range(len(dataframe)):\n num = 0\n for j in range(len(demand)):\n num += dataframe.iloc[i][1].count(demand[j])\n nums.append(num)\n dataframe['nums'] = nums\n dataframe.sort_values(by=['nums'], ascending=False, inplace=True)\n if dataframe.iloc[n]['nums'] != 0:\n return list(dataframe[:n]['appid'])\n else:\n return ''\n"},{"alpha_fraction":0.5998193025588989,"alphanum_fraction":0.6097561120986938,"avg_line_length":23.511110305786133,"blob_id":"522b7e2c3c44750c89e8ad52e066c0cec744952d","content_id":"ba0fae03291061eec5d2a4bb2ae61f76783c02da","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1107,"license_type":"no_license","max_line_length":86,"num_lines":45,"path":"/main.py","repo_name":"owenvvv/Steam_helper","src_encoding":"UTF-8","text":"import json\n\nfrom flask import Flask, request,render_template\nfrom geventwebsocket.handler import WebSocketHandler\nfrom gevent.pywsgi import WSGIServer\nimport intention\n\n\nhelper_session = []\n\n\napp = Flask(__name__)\n\n\n@app.route('/msg')\ndef msg():\n global helper_session\n\t# \n user_socker = request.environ.get('wsgi.websocket')\n # \n while 1:\n \t# \n msg = user_socker.receive()\n result={}\n result['message']=msg\n print(msg)\n\n r_text, new_session = intention.response(result, helper_session)\n # If only one sentence return, change it into a list.\n r_text_return=[]\n if not isinstance(r_text, list):\n r_text_return.append(r_text)\n else:\n r_text_return=r_text\n\n helper_session.extend(new_session)\n\t\t# Packed in a dict\n res = {\"msg\" : r_text_return}\n # Sent to client\n user_socker.send(json.dumps(res))\n \nif __name__ == '__main__':\t\n http_server = WSGIServer(('127.0.0.1', 5000), app, handler_class=WebSocketHandler)\n # Start Listening:\n http_server.serve_forever()\n "},{"alpha_fraction":0.7573735117912292,"alphanum_fraction":0.7696447968482971,"avg_line_length":62.6301383972168,"blob_id":"11804dd9a9c2840722082ded5a8339069a46004c","content_id":"0b92f979c9abad125e28886eec9a29975eaa6357","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":4647,"license_type":"no_license","max_line_length":879,"num_lines":73,"path":"/README.md","repo_name":"owenvvv/Steam_helper","src_encoding":"UTF-8","text":"# SECTION 1 : PROJECT TITLE\n### Steam Helper\n\n# SECTION 2 : EXECUTIVE SUMMARY / PAPER ABSTRACT\nSteam Helper is a Chatbot that can recommend steam games for users in two ways. For users who have forgotten the game name, the helper will find out the most similar games according to the paragraphs they provided. For users who are looking for new games, the helper will recommend games according to their preferences in category, price, age and others.\n\nThere are two parts in the web chat interface based on Flask Socket, Language Understanding and Language Generation. In the first part, we applied Support Vector Machines to detect user intentions and Conditional Random Field to extract the key aspect of the user requirements. If the user is asking for recommendation or matching, the aspects or the game description will be passed to the backend recommendation engine. The response for other types of intentions will be collected from the preset corpus following a set of rules.\n\nThe recommend engine provides three solutions in different levels. In the document level, we classified untagged user reviews into two general categories (recommended and unrecommended). Normally, each review has 10 sentences, although the tone of the entire document is positive, there are still negative complaints about certain aspects in some sentences. Therefore, in the sentence level, Entity & Aspect Mining and Sentiment Mining will be used to further discover the user’s attitudes toward different perspectives of the game. These sentiments will be quantified as scores for evaluating games. The games with high rating in the aspects emphasized by user will be recommended. If user a paragraph of game description for matching, in this level, deep learning model will be used for sentence embedding. The recommended games will be those with the highest similarity score.\n\n\n# SECTION 3 : CREDITS / PROJECT CONTRIBUTION\n| Official Full Name | Student ID (MTech Applicable)| Work Items (Who Did What) | Email (Optional) |\n| :---: | :---: | :---: | :---: |\n| Guanlan Jiang | A0198451W | Language Understanding and Generation | e0401992@u.nus.edu |\n| Li Tiancheng | A0198530Y | Recommendation Engine | e0402071@u.nus.edu |\n| Ng Siew Pheng | A0198525R | Language Understanding and Generation | e0402066@u.nus.edu |\n| Ruowen Li | A0198423X | UI, Recommendation Engine | e0401964@u.nus.edu |\n\n\n# SECTION 4 : VIDEO OF SYSTEM MODELLING & USE CASE DEMO\nhttps://drive.google.com/file/d/1Vb8sBB_PotAl4JL2sbHBVcyx84CDhVRv/view\n\n# SECTION 5 : INSTRUCTION GUIDE\n\n## Conda Environment\nTo set up the environment\n1. git clone https://github.com/owenvvv/Steam_helper.git\n2. cd PLP-CA10-Steam_Helper\n3. conda env create --file environment.yaml\n4. conda activate Steam_Helper\n5. python -m spacy download en_core_web_sm\n6. python -m nltk.downloader \n7. conda install pytorch -c pytorch\n\n## Start Chatbot\n1. python main.py \n2. Use index.html in Front-end folder to chat with chatbox\n# SECTION 6 : Models\n\n## Intent Detection\n\n### Data\nFilename: Code/data/intent_queries.json\n- This fields contains a list of questions (column - Query) with its intent label (column - Intent)\n- A total of 13 intents namely:\n\t- commonQ (.how, .assist, .name) > general chitchat questions to the chatbot\n\t- recommend (including .price, .age) > ask chatbot to recommend games. .price and .age is to detect user asking for aspect of the game recommended\n\t- response.abusive > abusive comments from user. this will trigger a positive response\n\t- response.negative > negative sentiment feedback from user about the chat\n\t\n- If new questions with its intent label is added, we need to re-train the intent detection model. \n\n### Train Model\n- Please use model/build_intent_model_json.ipynb to train the model\n- The model will be saved to intent_SGDClassifier_v2.pkl file to be used by the chatbot app.\n\n## Slot Detection\n\n### Data\nFilename: Code/data/intent_queries.json\n- This fields contains a list of questions (column - Query) with its intent label (column - Intent)\n- A total of 9 intents namely:\n\t- commonQ (.how, .assist, .name) > general chitchat questions to the chatbot\n\t- recommend (including .price, .age) > ask chatbot to recommend games. .price and .age is to detect user asking for aspect of the game recommended\n\t- response.abusive > abusive comments from user. this will trigger a positive response\n\t- response.negative > negative sentiment feedback from user about the chat\n\t\n- If new questions with its intent label is added, we need to re-train the intent detection model. \n\n### Train model\n- Please use Code/model/SlotFillerCRF.ipynb to train the model\n- The model will be saved to recommend_game.crfsuite file to be used by the chatbot app.\n"},{"alpha_fraction":0.7133382558822632,"alphanum_fraction":0.7397445440292358,"avg_line_length":41.40625,"blob_id":"772ae11249aa5e774395b89a9d3f6128bfb9f2a8","content_id":"6b9fc65581ce8eb05444924a15073789b33ee3a1","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":8146,"license_type":"no_license","max_line_length":374,"num_lines":192,"path":"/steam-scraper/README.md","repo_name":"owenvvv/Steam_helper","src_encoding":"UTF-8","text":"# Steam Scraper\n\nThis repository contains [Scrapy](https://github.com/scrapy/scrapy) spiders for **crawling products** and **scraping all user-submitted reviews** from the [Steam game store](https://steampowered.com).\nA few scripts for more easily managing and deploying the spiders are included as well.\n\nThis repository contains code accompanying the *Scraping the Steam Game Store* article published on the [Scrapinghub blog](https://blog.scrapinghub.com/2017/07/07/scraping-the-steam-game-store-with-scrapy/) and the [Intoli blog](https://intoli.com/blog/steam-scraper/).\n\n## Installation\n\nAfter cloning the repository with\n```bash\ngit clone git@github.com:prncc/steam-scraper.git\n```\nstart and activate a Python 3.6+ virtualenv with\n```bash\ncd steam-scraper\nvirtualenv -p python3.6 env\n. env/bin/activate\n```\nInstall Python requirements via:\n```bash\npip install -r requirements.txt\n```\n\nBy the way, on macOS you can install Python 3.6 via [homebrew](https://brew.sh):\n ```bash\n brew install python3\n```\nOn Ubuntu you can use [instructions posted on askubuntu.com](https://askubuntu.com/questions/865554/how-do-i-install-python-3-6-using-apt-get).\n\n## Crawling the Products\n\nThe purpose of `ProductSpider` is to discover product pages on the [Steam product listing](http://store.steampowered.com/search/?sort_by=Released_DESC) and extract useful metadata from them.\nA neat feature of this spider is that it automatically navigates through Steam's age verification checkpoints.\nYou can initiate the multi-hour crawl with\n```bash\nscrapy crawl products -o output/products_all.jl --logfile=output/products_all.log --loglevel=INFO -s JOBDIR=output/products_all_job -s HTTPCACHE_ENABLED=False\n```\nWhen it completes you should have metadata for all games on Steam in `output/products_all.jl`.\nHere's some example output:\n```python\n{\n 'app_name': 'Cold Fear™',\n 'developer': 'Darkworks',\n 'early_access': False,\n 'genres': ['Action'],\n 'id': '15270',\n 'metascore': 66,\n 'n_reviews': 172,\n 'price': 9.99,\n 'publisher': 'Ubisoft',\n 'release_date': '2005-03-28',\n 'reviews_url': 'http://steamcommunity.com/app/15270/reviews/?browsefilter=mostrecent&p=1',\n 'sentiment': 'Very Positive',\n 'specs': ['Single-player'],\n 'tags': ['Horror', 'Action', 'Survival Horror', 'Zombies', 'Third Person', 'Third-Person Shooter'],\n 'title': 'Cold Fear™',\n 'url': 'http://store.steampowered.com/app/15270/Cold_Fear/'\n }\n```\n\n## Extracting the Reviews\n\nThe purpose of `ReviewSpider` is to scrape all user-submitted reviews of a particular product from the [Steam community portal](http://steamcommunity.com/). \nBy default, it starts from URLs listed in its `test_urls` parameter:\n```python\nclass ReviewSpider(scrapy.Spider):\n name = 'reviews'\n test_urls = [\n \"http://steamcommunity.com/app/316790/reviews/?browsefilter=mostrecent&p=1\", # Grim Fandango\n \"http://steamcommunity.com/app/207610/reviews/?browsefilter=mostrecent&p=1\", # The Walking Dead\n \"http://steamcommunity.com/app/414700/reviews/?browsefilter=mostrecent&p=1\" # Outlast 2\n ]\n```\nIt can alternatively ingest a text file containing URLs such as\n```\nhttp://steamcommunity.com/app/316790/reviews/?browsefilter=mostrecent&p=1\nhttp://steamcommunity.com/app/207610/reviews/?browsefilter=mostrecent&p=1\nhttp://steamcommunity.com/app/414700/reviews/?browsefilter=mostrecent&p=1\n```\nvia the `url_file` command line argument:\n```bash\nscrapy crawl reviews -o reviews.jl -a url_file=url_file.txt -s JOBDIR=output/reviews\n```\nAn output sample:\n```python\n{\n 'date': '2017-06-04',\n 'early_access': False,\n 'found_funny': 5,\n 'found_helpful': 0,\n 'found_unhelpful': 1,\n 'hours': 9.8,\n 'page': 3,\n 'page_order': 7,\n 'product_id': '414700',\n 'products': 179,\n 'recommended': True,\n 'text': '3 spooky 5 me',\n 'user_id': '76561198116659822',\n 'username': 'Fowler'\n}\n```\n\nIf you want to get all the reviews for all products, `split_review_urls.py` will remove duplicate entries from `products_all.jl` and shuffle `review_url`s into several text files.\nThis provides a convenient way to split up your crawl into manageable pieces.\nThe whole job takes a few days with Steam's generous rate limits.\n\n## Deploying to a Remote Server\n\nThis section briefly explains how to run the crawl on one or more t1.micro AWS instances.\n\nFirst, create an Ubuntu 16.04 t1.micro instance and name it `scrapy-runner-01` in your `~/.ssh/config` file:\n```\nHost scrapy-runner-01\n User ubuntu\n HostName \n IdentityFile ~/.ssh/id_rsa\n```\nA hostname of this form is expected by the `scrapydee.sh` helper script included in this repository.\nMake sure you can connect with `ssh scrappy-runner-01`.\n\n### Remote Server Setup\n\nThe tool that will actually run the crawl is [scrapyd](http://scrapyd.readthedocs.io/en/stable/) running on the remote server.\nTo set things up first install Python 3.6:\n```bash\nsudo add-apt-repository ppa:jonathonf/python-3.6\nsudo apt update\nsudo apt install python3.6 python3.6-dev virtualenv python-pip\n```\nThen, install scrapyd and the remaining requirements in a dedicated `run` directory on the remote server: \n```bash\nmkdir run && cd run\nvirtualenv -p python3.6 env\n. env/bin/activate\npip install scrapy scrapyd botocore smart_getenv \n```\nYou can run `scrapyd` from the virtual environment with\n```bash\nscrapyd --logfile /home/ubuntu/run/scrapyd.log &\n```\nYou may wish to use something like [screen](https://www.gnu.org/software/screen/) to keep the process alive if you disconnect from the server.\n\n### Controlling the Job\n\nYou can issue commands to the scrapyd process running on the remote machine using a simple [HTTP JSON API](http://scrapyd.readthedocs.io/en/stable/index.html).\nFirst, create an egg for this project:\n```bash\npython setup.py bdist_egg\n```\nCopy the egg and your review url file to `scrapy-runner-01` via\n```bash\nscp output/review_urls_01.txt scrapy-runner-01:/home/ubuntu/run/\nscp dist/steam_scraper-1.0-py3.6.egg scrapy-runner-01:/home/ubuntu/run\n```\nand add it to scrapyd's job directory via \n```bash\nssh -f scrapy-runner-01 'cd /home/ubuntu/run && curl http://localhost:6800/addversion.json -F project=steam -F egg=@steam_scraper-1.0-py3.6.egg'\n```\nOpening port 6800 to TCP traffic coming from your home IP would allow you to issue this command without going through SSH.\nIf this command doesn't work, you may need to edit `scrapyd.conf` to contain\n```\nbind_address = 0.0.0.0\n```\nin the `[scrapyd]` section.\nThis is a good time to mention that there exists a [scrapyd-client](https://github.com/scrapy/scrapyd-client) project for deploying eggs to scrapyd equipped servers.\nI chose not to use it because it doesn't know about servers already set up in `~/.ssh/config` and so requires repetitive configuration.\n\nFinally, start the job with something like\n```bash\nssh scrapy-runner-01 'curl http://localhost:6800/schedule.json -d project=steam -d spider=reviews -d url_file=\"/home/ubuntu/run/review_urls_01.txt\" -d jobid=part_01 -d setting=FEED_URI=\"s3://'$STEAM_S3_BUCKET'/%(name)s/part_01/%(time)s.jl\" -d setting=AWS_ACCESS_KEY_ID='$AWS_ACCESS_KEY_ID' -d setting=AWS_SECRET_ACCESS_KEY='$AWS_SECRET_ACCESS_KEY' -d setting=LOG_LEVEL=INFO'\n```\nThis command assumes you have set up an S3 bucket and the `AWS_ACCESS_KEY_ID` and `AWS_SECRET_ACCESS_KEY` environment variables.\nIt should be pretty easy to customize it for non-S3 output, however.\n\nThe `scrapydee.sh` helper script included in the `scripts` directory of this repository has some shortcuts for issuing commands to scrapyd-equipped servers with hostnames of the form `scrapy-runner-01`.\nFor example, the command\n```bash\n./scripts/scrapydee.sh status 1\n# Executing status()...\n# On server(s): 1.\n```\nwill run the `status()` function defined in `scrapydee.sh` on `scrapy-runner-01`.\nSee that file for more command examples.\nYou can also run each of the included commands on multiple servers:\nFirst, change the `all()` function within `scrapydee.sh` to match the number of servers you have configured.\nThen, issue a command such as\n```bash\n./scripts/scrapydee.sh status all\n```\nThe output is a bit messy, but it's a quick and easy way to run this job.\n"},{"alpha_fraction":0.5150588154792786,"alphanum_fraction":0.5317646861076355,"avg_line_length":30.71641731262207,"blob_id":"0df52da082c9e342e3693867fefc1901162a9a3e","content_id":"abe8619c41a52cd2e40a99213e12bb1f29e8e8d3","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":4250,"license_type":"no_license","max_line_length":124,"num_lines":134,"path":"/slotfiller.py","repo_name":"owenvvv/Steam_helper","src_encoding":"UTF-8","text":"import pycrfsuite\nimport en_core_web_sm\nimport nltk\nwnl = nltk.WordNetLemmatizer()\nnlp = en_core_web_sm.load()\n\ndef input_prep(text):\n data_List = []\n\n for sequence in text:\n wordList=[]\n posList=[]\n tagList = []\n sentlist=[]\n\n text = sequence.strip().lower()\n tokens = nltk.word_tokenize(text)\n tokens = [wnl.lemmatize(t.lower(), pos='v') for t in tokens]\n text = \" \".join(tokens)\n tokenList = text.split()\n\n for tok in tokenList:\n wordList.append(tok)\n tagList.append('O')\n\n sent = ' '.join(wordList)\n sent_nlp = nlp(sent) #POS tag\n\n for token in sent_nlp:\n posList.append(token.tag_) #retrieve tag\n\n for idx,word in enumerate(wordList):\n sentlist.append((word,posList[idx],tagList[idx]))\n\n data_List.append(sentlist)\n return data_List\n\n\ndef word2features(sent, i): # function to create feature vector to represent each word\n word = sent[i][0]\n postag = sent[i][1]\n features = [ # for all words\n 'bias',\n 'word.lower=' + word.lower(),\n # 'word[-3:]=' + word[-3:],\n 'word.isupper=%s' % word.isupper(),\n 'word.istitle=%s' % word.istitle(),\n 'word.isdigit=%s' % word.isdigit(),\n 'postag=' + postag,\n 'postag[:2]=' + postag[:2], # what is the POS tag for the next 2 word token\n ]\n if i > 0: # if not \n word1 = sent[i - 1][0]\n postag1 = sent[i - 1][1]\n features.extend([\n '-1:word.lower=' + word1.lower(),\n '-1:word.istitle=%s' % word1.istitle(),\n '-1:word.isupper=%s' % word1.isupper(),\n '-1:word.isdigit=%s' % word1.isdigit(),\n '-1:postag=' + postag1,\n '-1:postag[:2]=' + postag1[:2],\n ])\n else:\n features.append('BOS') # beginning of statement\n\n if i < len(sent) - 1: # if not <\\S>\n word1 = sent[i + 1][0]\n postag1 = sent[i + 1][1]\n features.extend([\n '+1:word.lower=' + word1.lower(),\n '+1:word.istitle=%s' % word1.istitle(),\n '+1:word.isupper=%s' % word1.isupper(),\n '+1:word.isdigit=%s' % word1.isdigit(),\n '+1:postag=' + postag1,\n '+1:postag[:2]=' + postag1[:2],\n ])\n else:\n features.append('EOS')\n\n return features\n\n\ndef sent2features(sent):\n return [word2features(sent, i) for i in range(len(sent))]\n\n\ndef sent2labels(sent):\n return [label for token, postag, label in sent]\n\n\ndef sent2tokens(sent):\n return [token for token, postag, label in sent]\n\ndef extract(text):\n tagger = pycrfsuite.Tagger()\n tagger.open('model/recommend_game.crfsuite')\n text_split = text.replace(' and', '.').split('.')\n sentence = input_prep(text_split)\n features = [sent2features(s) for s in sentence]\n tagList = [tagger.tag(s) for s in features]\n print(tagList)\n for idx_sent, sent in enumerate(tagList):\n for idx_word, word in enumerate(sent):\n if word != 'O':\n words = sentence[idx_sent][idx_word]\n words_new = (words[0], words[2], word)\n sentence[idx_sent][idx_word] = words_new\n #print(sentence)\n ratingList = []\n genreList = []\n priceList = []\n ageList = []\n characterList = []\n for idx_sent, sent in enumerate(sentence):\n for idx_word, word in enumerate(sent):\n if 'genre' in word[2]:\n genreList.append(word[0])\n elif 'age' in word[2]:\n if word[0].isdigit():\n ageList.append(word[0])\n elif 'price' in word[2]:\n if 'free' in word[0]:\n priceList.append('0')\n else:\n if word[0].replace('$','').isdigit():\n priceList.append(word[0].replace('$',''))\n elif 'rating' in word[2]:\n ratingList.append(word[0])\n elif 'character' in word[2]:\n characterList.append(word[0])\n\n entitylist = {'genre': genreList, 'age': ageList, 'price': priceList, 'rating': ratingList, 'characters': characterList}\n #print(f\"entitylist: {entitylist}\")\n return sentence, entitylist\n"},{"alpha_fraction":0.5550034046173096,"alphanum_fraction":0.5632368922233582,"avg_line_length":41.23456954956055,"blob_id":"fc1ea2e5e9124f6f666c36a0afeb0694430757e7","content_id":"c33c4d03358c7b16bee9121f3422bfbbd7f92b08","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":20526,"license_type":"no_license","max_line_length":141,"num_lines":486,"path":"/intention.py","repo_name":"owenvvv/Steam_helper","src_encoding":"UTF-8","text":"import pandas as pd\nimport pickle as pk\nimport re\nimport random\nfrom nltk.tokenize import word_tokenize, sent_tokenize\nimport slotfiller as sf\nimport nltk\n\nwnl = nltk.WordNetLemmatizer()\nfrom nltk.corpus import stopwords\n\nmystopwords = stopwords.words(\"english\")\nimport recommendegine\n\nmodel_filename = 'model/intent_SGDClassifier_v2.pkl'\nclassifier_probability_threshold = 0.35\n\nprice_words = ['cheap', 'cheaper', 'cheapest']\nother_words = ['other', 'another', 'different']\n\nintent_enc = {\n 'commonQ.assist': 0,\n 'commonQ.how': 1,\n 'commonQ.name': 2,\n 'commonQ.wait': 3,\n 'recommend.game': 4,\n 'game.age': 5,\n 'game.price': 6,\n 'response.abusive': 7,\n 'response.negative': 8,\n 'response.incorrect': 9,\n 'game.release_date': 10,\n 'game.platforms\"': 11,\n 'response.positive': 12,\n 'game.details': 13\n}\n\nintent_dec = {\n -1: 'unknown',\n 0: 'commonQ.assist',\n 1: 'commonQ.how',\n 2: 'commonQ.name',\n 3: 'commonQ.wait',\n 4: 'recommend.game',\n 5: 'game.age',\n 6: 'game.price',\n 7: 'response.abusive',\n 8: 'response.negative',\n 9: 'response.incorrect',\n 10: 'game.release_date',\n 11: 'game.platforms',\n 12: 'response.positive',\n 13: 'game.details'\n}\n\ngamesDF = pd.read_csv(\"./data/steam_small.csv\", encoding=\"utf-8\")\n\n\ndef retrieve_last_session(session):\n last_session = ''\n if len(session) > 0:\n last_session = session[len(session) - 1] # retrieve last session details\n\n return last_session\n\n\ndef clean_text(text, lemma=True):\n text = re.sub(r\"what's\", \"what is \", text)\n text = re.sub(r\"\\'s\", \" \", text)\n text = re.sub(r\"\\'ve\", \" have \", text)\n text = re.sub(r\"can't\", \"can not \", text)\n text = re.sub(r\"n't\", \" not \", text)\n text = re.sub(r\"i'm\", \"i am \", text)\n text = re.sub(r\"\\'re\", \" are \", text)\n text = re.sub(r\"\\'d\", \" would \", text)\n text = re.sub(r\"\\'ll\", \" will \", text)\n text = re.sub(r\"\\'scuse\", \" excuse \", text)\n text = re.sub('"', '', text)\n text = re.sub('\\
', '', text)\n text = re.sub('etc.', 'etc', text)\n # text = re.sub('\\W', ' ', text)\n text = re.sub('\\s+', ' ', text)\n text = re.sub('\\', ' ', text)\n text = re.sub('\\', '', text)\n text = re.sub('\\<\\/strong\\>', '', text)\n text = text.strip(' ')\n if lemma:\n tokens = word_tokenize(text)\n tokens = [wnl.lemmatize(t.lower(), pos='v') for t in tokens]\n text = \" \".join(tokens)\n return text\n\n\ndef detect_intent(query):\n text = [str(query['message'])]\n queryDF = pd.DataFrame(text, columns=['Query'])\n # Load trained Intent Detection Model\n intent_model = pk.load(open(model_filename, 'rb'))\n result = intent_model.predict(queryDF.Query)\n result_proba = intent_model.predict_proba(queryDF.Query)\n classes = list(intent_model.classes_)\n class_proba = result_proba[0][classes.index(result[0])]\n # print(f\"intent: {result[0]}; probability: {class_proba}\")\n if result[0] == 4:\n if class_proba >= classifier_probability_threshold:\n intent = result[0]\n else:\n intent = -1\n else:\n intent = result[0]\n return intent\n\n\ndef response(query, helper_session):\n name_part1 = ['Hi, my name is Stella.', 'Hello, my name is Stella.']\n wait_part1 = ['Sure!', 'Of course!', 'No problem!', 'Okay.']\n wait_part2 = ['I will wait for you.', 'Whenever you are ready.', 'Write back when you are ready.',\n 'Just write back when you are ready.']\n assist_part1 = ['How can I help you?', 'What can I do for you today?', 'How can I assist you?',\n 'Do you need help finding games?', 'Would you like me to recommend you a game?']\n hru = ['Feeling great!', 'I am feeling awesome.', 'Feeling Good!', 'I am doing great']\n recmd_part1 = ['I found this game - ', 'You might be interested in this game - ',\n 'I can suggest this game - ', 'Maybe you will be interested in - ']\n recmd_part2 = ['I found this game about your requirement on <> -']\n recmd_part3 = ['You may like this <> game which is good on its <> aspect -']\n recmd_part4 = ['I found this game - ',\n 'I would recommend the game because you like <> game - ']\n abusive_resp = ['Please refrain from using such language',\n 'Let''s be nice to each other and refrain from using such strong words']\n negative_part1 = ['I am sorry.', 'My apologise.']\n negative_part2 = ['Can you tell me what is wrong?', 'What did I get wrong?', 'How can I correct myself?',\n 'How can I fix this?']\n price_part1 = ['The price of the game is $<>', 'It costs $<>', '$<
Unauthorized
\nThe server could not verify that you are authorized to access the URL requested. You either supplied the wrong credentials (e.g. a bad password), or your browser doesn't understand how to supply the credentials required.
\n* Closing connection 0\nbob@dylan:~$ \n\n```\n\n\n\n### 12. Find user by session ID\n\n\nIn this task, you will implement the `Auth.get_user_from_session_id` method. It takes a single `session_id` string argument and returns the corresponding `User` or `None`.\n\nIf the session ID is `None` or no user is found, return `None`. Otherwise return the corresponding user.\n\nRemember to only use public methods of `self._db`.\n\n\n\n### 13. Destroy session\n\n\n\nIn this task, you will implement `Auth.destroy_session`. The method takes a single `user_id` integer argument and returns `None`.\n\nThe method updates the corresponding user’s session ID to `None`.\n\nRemember to only use public methods of `self._db`.\n\n\n\n### 14. Log out\n\n\nIn this task, you will implement a `logout` function to respond to the `DELETE /sessions` route.\n\nThe request is expected to contain the session ID as a cookie with key `\"session_id\"`.\n\nFind the user with the requested session ID. If the user exists destroy the session and redirect the user to `GET /`. If the user does not exist, respond with a 403 HTTP status.\n\n\n\n### 15. User profile\n\n\nIn this task, you will implement a `profile` function to respond to the `GET /profile` route.\n\nThe request is expected to contain a `session_id` cookie. Use it to find the user. If the user exist, respond with a 200 HTTP status and the following JSON payload:\n\n```\n{\"email\": \"Forbidden
\nYou don't have the permission to access the requested resource. It is either read-protected or not readable by the server.
\n* Closing connection 0\n\nbob@dylan:~$ \n\n```\n\n\n\n### 16. Generate reset password token\n\n\nIn this task, you will implement the `Auth.get_reset_password_token` method. It take an `email` string argument and returns a string.\n\nFind the user corresponding to the email. If the user does not exist, raise a `ValueError` exception. If it exists, generate a UUID and update the user’s `reset_token` database field. Return the token.\n\n\n\n### 17. Get reset password token\n\n\nIn this task, you will implement a `get_reset_password_token` function to respond to the `POST /reset_password` route.\n\nThe request is expected to contain form data with the `\"email\"` field.\n\nIf the email is not registered, respond with a 403 status code. Otherwise, generate a token and respond with a 200 HTTP status and the following JSON payload:\n\n```\n{\"email\": \"Unauthorized
\\nThe server could not verify that you are authorized to access the URL requested. You either supplied the wrong credentials (e.g. a bad password), or your browser doesn't understand how to supply the credentials required.
\\n* Closing connection 0\\nbob@dylan:~$ \\n\\n```\\n\\n\\n\\n### 12. Find user by session ID\\n\\n\\nIn this task, you will implement the `Auth.get_user_from_session_id` method. It takes a single `session_id` string argument and returns the corresponding `User` or `None`.\\n\\nIf the session ID is `None` or no user is found, return `None`. Otherwise return the corresponding user.\\n\\nRemember to only use public methods of `self._db`.\\n\\n\\n\\n### 13. Destroy session\\n\\n\\n\\nIn this task, you will implement `Auth.destroy_session`. The method takes a single `user_id` integer argument and returns `None`.\\n\\nThe method updates the corresponding user’s session ID to `None`.\\n\\nRemember to only use public methods of `self._db`.\\n\\n\\n\\n### 14. Log out\\n\\n\\nIn this task, you will implement a `logout` function to respond to the `DELETE /sessions` route.\\n\\nThe request is expected to contain the session ID as a cookie with key `\\\"session_id\\\"`.\\n\\nFind the user with the requested session ID. If the user exists destroy the session and redirect the user to `GET /`. If the user does not exist, respond with a 403 HTTP status.\\n\\n\\n\\n### 15. User profile\\n\\n\\nIn this task, you will implement a `profile` function to respond to the `GET /profile` route.\\n\\nThe request is expected to contain a `session_id` cookie. Use it to find the user. If the user exist, respond with a 200 HTTP status and the following JSON payload:\\n\\n```\\n{\\\"email\\\": \\\"Forbidden
\\nYou don't have the permission to access the requested resource. It is either read-protected or not readable by the server.
\\n* Closing connection 0\\n\\nbob@dylan:~$ \\n\\n```\\n\\n\\n\\n### 16. Generate reset password token\\n\\n\\nIn this task, you will implement the `Auth.get_reset_password_token` method. It take an `email` string argument and returns a string.\\n\\nFind the user corresponding to the email. If the user does not exist, raise a `ValueError` exception. If it exists, generate a UUID and update the user’s `reset_token` database field. Return the token.\\n\\n\\n\\n### 17. Get reset password token\\n\\n\\nIn this task, you will implement a `get_reset_password_token` function to respond to the `POST /reset_password` route.\\n\\nThe request is expected to contain form data with the `\\\"email\\\"` field.\\n\\nIf the email is not registered, respond with a 403 status code. Otherwise, generate a token and respond with a 200 HTTP status and the following JSON payload:\\n\\n```\\n{\\\"email\\\": \\\"\n\n### 코딩테스트 연습 (Python 소스코드)\n\n### Level 1\n * 크레인 인형뽑기 게임: ([Python 코드](/Level1/64061.py))\n * 두 개 뽑아서 더하기: ([Python 코드](/Level1/68644.py))\n * 완주하지 못한 선수: ([Python 코드](/Level1/42576.py))\n * 모의고사: ([Python 코드](/Level1/42840.py))\n * k번째 수: ([Python 코드](/Level1/42748.py))\n * 체육복: ([Python 코드](/Level1/42862.py))\n * 2016년: ([Python 코드](/Level1/12901.py))\n * 3진법 뒤집기: ([Python 코드](/Level1/68935.py))\n * 가운데 글자 가져오기: ([Python 코드](/Level1/12903.py))\n * 같은 숫자는 싫어: ([Python 코드](/Level1/12906.py))\n \n### Level 2\n * 다리를 지나는 트럭: ([Python 코드](/Level2/42583.py))\n * 주식가격: ([Python 코드](/Level2/42584.py))\n * 스킬트리: ([Python 코드](/Level2/49993.py))\n### 카카오공채\n * 자물쇠와 열쇠: ([Python 코드](/카카오공채/60059.py))\n * 기둥과 보 설치: ([Python 코드](/카카오공채/60061.py))\n * 문자열 압축: ([Python 코드](/카카오공채/60057.py))\n * 괄호 변환: ([Python 코드](/카카오공채/60058.py))\n * 블록 이동하기: ([Python 코드](/카카오공채/60063.py))\n * 실패율: ([Python 코드](/카카오공채/42889.py))\n * 가사 검색: ([Python 코드](/카카오공채/60060.py))\n * 무지의 먹방 라이브: ([Python 코드](/카카오공채/42891.py))\n * 외벽 점검: ([Python 코드](/카카오공채/60062.py))\n"},{"alpha_fraction":0.44736841320991516,"alphanum_fraction":0.4583333432674408,"avg_line_length":25.823530197143555,"blob_id":"10174d7e3620bd33fcf72f52c1c178c178582adc","content_id":"500b40da1e65650180a3280566130fcd45ed1572","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":456,"license_type":"no_license","max_line_length":46,"num_lines":17,"path":"/Level2/49993.py","repo_name":"YoonKiBum/programmers","src_encoding":"UTF-8","text":"import copy\ndef solution(skill, skill_trees):\n count = 0\n check = [0] * len(skill)\n for word in skill_trees:\n copyskill = list(copy.deepcopy(skill))\n check = True\n for i in word:\n if i in copyskill:\n res = copyskill[0]\n if res != i:\n check = False\n break\n copyskill.pop(0)\n if check: \n count += 1\n return count\n"},{"alpha_fraction":0.6192052960395813,"alphanum_fraction":0.6291390657424927,"avg_line_length":24.16666603088379,"blob_id":"ed2837d7ad12ce569757025fbb8e849d5d9914bd","content_id":"db5bd041bef13d865896451ff73483fc84a3e5a5","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":302,"license_type":"no_license","max_line_length":48,"num_lines":12,"path":"/Level1/68644.py","repo_name":"YoonKiBum/programmers","src_encoding":"UTF-8","text":"from itertools import combinations\n\ndef solution(numbers):\n answer = []\n for combination in combinations(numbers, 2):\n x = int(combination[0])\n y = int(combination[1])\n answer.append(x+y)\n answer = set(answer)\n answer = list(answer)\n answer.sort()\n return answer\n"},{"alpha_fraction":0.43499043583869934,"alphanum_fraction":0.45984703302383423,"avg_line_length":33.86666488647461,"blob_id":"01ac47fc0ca59d5d93853ebc9ae7624507261619","content_id":"bef4a9ab3a4b8c108198f2104bda22ecab3706c6","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1120,"license_type":"no_license","max_line_length":119,"num_lines":30,"path":"/카카오공채/60061.py","repo_name":"YoonKiBum/programmers","src_encoding":"UTF-8","text":"# https://programmers.co.kr/learn/courses/30/lessons/60061\ndef check(answer):\n for i in range(len(answer)):\n x, y, a = answer[i]\n if a == 0: # 기둥 인 경우\n if y == 0 or [x-1, y, 1] in answer or [x, y, 1] in answer or [x, y-1, 0] in answer:\n continue\n else:\n return False\n elif a == 1: # 보 인 경우\n if [x, y-1, 0] in answer or [x+1, y-1, 0] in answer or ([x-1, y, 1] in answer and [x+1, y , 1] in answer): \n continue\n else:\n return False\n return True\n\ndef solution(n, build_frame):\n answer = []\n for i in range(len(build_frame)):\n x, y, a, b = build_frame[i]\n if b == 1: # 설치인 경우\n answer.append([x, y, a])\n if check(answer) == False: # 조건에서 어긋난 경우\n answer.pop()\n elif b == 0: # 삭제인 경우\n answer.remove([x, y, a])\n if check(answer) == False: # 조건에서 어긋난 경우\n answer.append([x, y, a])\n \n return sorted(answer)\n"},{"alpha_fraction":0.446153849363327,"alphanum_fraction":0.4703296720981598,"avg_line_length":31.5,"blob_id":"a326dbf5a7459cc4a978a862155a4376673344ff","content_id":"121567e46450f25d6f3092ba7882f867f7c7186c","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":455,"license_type":"no_license","max_line_length":79,"num_lines":14,"path":"/Level1/64061.py","repo_name":"YoonKiBum/programmers","src_encoding":"UTF-8","text":"def solution(board, moves):\n answer = [-1]\n count = 0\n for i in range(len(moves)):\n for j in range(len(board)):\n if board[j][moves[i]-1] != 0:\n answer.append(board[j][moves[i]-1])\n board[j][moves[i]-1] = 0\n break\n if len(answer) >= 3 and answer[len(answer)-1] == answer[len(answer)-2]:\n answer.pop()\n answer.pop()\n count += 2\n return count\n"},{"alpha_fraction":0.4358353614807129,"alphanum_fraction":0.4479418992996216,"avg_line_length":23.294116973876953,"blob_id":"a11d325699728c74421ad4ec97f2ad18a42dec95","content_id":"43d9f5b991d938615cfa8d0193fbdeba5caecb88","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":413,"license_type":"no_license","max_line_length":36,"num_lines":17,"path":"/카카오공채/42889.py","repo_name":"YoonKiBum/programmers","src_encoding":"UTF-8","text":"def solution(N, stages):\n total = len(stages)\n arr = []\n ans = []\n for i in range(1, N + 1):\n temp = stages.count(i)\n if total > 0:\n fail = temp / total\n total -= temp\n arr.append((fail, -(i)))\n else:\n arr.append((0, -(i)))\n arr.sort(reverse = True)\n \n for i in range(len(arr)):\n ans.append(-(arr[i][1]))\n return ans\n"},{"alpha_fraction":0.3840177655220032,"alphanum_fraction":0.4694783687591553,"avg_line_length":30.034482955932617,"blob_id":"80add779e8e57fbfb7a79531157d111e840f7207","content_id":"df1539b6db799fc1ec199d8ab3b7ca7c67703984","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":901,"license_type":"no_license","max_line_length":58,"num_lines":29,"path":"/Level1/42840.py","repo_name":"YoonKiBum/programmers","src_encoding":"UTF-8","text":"# https://programmers.co.kr/learn/courses/30/lessons/42840\ndef solution(answers):\n answer = []\n people_1 = [1, 2, 3, 4, 5] * 2000\n people_2 = [2, 1, 2, 3, 2, 4, 2, 5] * 2000\n people_3 = [3, 3, 1, 1, 2, 2, 4, 4, 5, 5] * 1000\n num_of_1 = 0; num_of_2 = 0; num_of_3 = 0\n \n for i in range(len(answers)):\n if answers[i] == people_1[i]:\n num_of_1 += 1\n if answers[i] == people_2[i]:\n num_of_2 += 1\n if answers[i] == people_3[i]:\n num_of_3 += 1\n \n temp = [(num_of_1,1), (num_of_2,2), (num_of_3,3)] \n temp.sort(reverse = True)\n temp.append((-1, -1))\n \n for i in range(3):\n if temp[i][0] != temp[i+1][0]:\n answer.append(temp[i][1])\n answer.sort()\n return answer\n elif temp[i][0] == temp[i+1][0]:\n answer.append(temp[i][1])\n answer.sort()\n return answer\n\n"},{"alpha_fraction":0.5360000133514404,"alphanum_fraction":0.5440000295639038,"avg_line_length":24,"blob_id":"4d5080e45ec7385d55b86e0dc3f4b357cd04b522","content_id":"9c485825aebefb31e69640a0bc5c232726ece56e","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":250,"license_type":"no_license","max_line_length":39,"num_lines":10,"path":"/Level1/42748.py","repo_name":"YoonKiBum/programmers","src_encoding":"UTF-8","text":"def solution(array, commands):\n n = len(commands)\n answer = []\n for i in range(n):\n start, end, count = commands[i]\n temp = array[start-1:end]\n temp.sort()\n answer.append(temp[count-1])\n \n return answer\n"},{"alpha_fraction":0.35738831758499146,"alphanum_fraction":0.4536082446575165,"avg_line_length":23.25,"blob_id":"a9cf860a174d6f44a9e897edaa2526a7c04f7de6","content_id":"b49850c5d0c5a8efbea09d56c478e137ea6e5542","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":291,"license_type":"no_license","max_line_length":60,"num_lines":12,"path":"/Level1/12901.py","repo_name":"YoonKiBum/programmers","src_encoding":"UTF-8","text":"def solution(a, b):\n month = [31, 29, 31, 30, 31, 30, 31, 31, 30, 31, 30, 31]\n ans = ['FRI','SAT','SUN','MON','TUE','WED','THU']\n index = a - 1 \n day = b - 1\n \n sum = 0\n for i in range(index):\n sum += month[i]\n sum += day\n sum = sum % 7\n return ans[sum]\n"},{"alpha_fraction":0.43091654777526855,"alphanum_fraction":0.45690834522247314,"avg_line_length":31.488889694213867,"blob_id":"847ca7e2654788621c1a2914e563351241d300c3","content_id":"da68286cc13e68f17555905be5135deb46ce0bc8","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1482,"license_type":"no_license","max_line_length":67,"num_lines":45,"path":"/카카오공채/60063.py","repo_name":"YoonKiBum/programmers","src_encoding":"UTF-8","text":"from collections import deque\n\ndef can_move(pos, graph):\n next_pos = []\n pos = list(pos)\n lx, ly, rx, ry = pos[0][0], pos[0][1], pos[1][0], pos[1][1]\n dx = [-1, 1, 0, 0]\n dy = [0, 0, -1, 1]\n for i in range(4):\n nlx, nly, nrx, nry = lx+dx[i], ly+dy[i], rx+dx[i], ry+dy[i]\n if graph[nlx][nly] == 0 and graph[nrx][nry] == 0:\n next_pos.append({(nlx, nly), (nrx, nry)})\n if lx == rx: # 가로인 경우\n for i in [-1, 1]:\n if graph[lx+i][ly] == 0 and graph[rx+i][ry] == 0:\n next_pos.append({(lx,ly), (lx+i, ly)})\n next_pos.append({(rx, ry), (rx+i, ry)})\n elif ly == ry: # 세로인 경우\n for i in [-1, 1]:\n if graph[lx][ly+i] == 0 and graph[rx][ry+i] == 0:\n next_pos.append({(lx, ly), (lx, ly+i)})\n next_pos.append({(rx, ry), (rx, ry+i)})\n return next_pos\n\ndef solution(board):\n n = len(board) + 2\n m = len(board)\n graph = [[1]*n for _ in range(n)]\n for i in range(m):\n for j in range(m):\n graph[i+1][j+1] = board[i][j]\n q = deque()\n visited = []\n pos = {(1, 1), (1, 2)}\n q.append((pos, 0))\n visited.append(pos)\n while q:\n pos, cost = q.popleft()\n if (m, m) in pos:\n return cost\n for next_pos in can_move(pos, graph):\n if next_pos not in visited:\n q.append((next_pos, cost+1))\n visited.append(next_pos)\n return 0\n"},{"alpha_fraction":0.49077489972114563,"alphanum_fraction":0.5129151344299316,"avg_line_length":26.100000381469727,"blob_id":"8b577448f1d6521cde1cab13d53b910cc7f1f024","content_id":"57423838cee8e0ab8338166bc1ae53a64992141c","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":542,"license_type":"no_license","max_line_length":39,"num_lines":20,"path":"/Level1/42862.py","repo_name":"YoonKiBum/programmers","src_encoding":"UTF-8","text":"def solution(n, lost, reserve):\n lost.sort()\n reserve.sort()\n count = 0\n lost = set(lost)\n reserve = set(reserve)\n temp1 = lost - reserve\n temp2 = reserve - lost\n lost = list(temp1)\n reserve = list(temp2)\n for i in range(len(lost)):\n if len(reserve) <= 0:\n break\n if lost[i] - 1 in reserve:\n reserve.remove(lost[i]-1)\n count += 1\n elif lost[i] + 1 in reserve:\n reserve.remove(lost[i] + 1)\n count += 1\n return n - (len(lost) - count)\n"},{"alpha_fraction":0.3531745970249176,"alphanum_fraction":0.3769841194152832,"avg_line_length":18.384614944458008,"blob_id":"b6647bf18555789bbb087f31d0dcf2a584d857fd","content_id":"bac1a4b438b884c1326c8146b1b3d8139387d74f","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":252,"license_type":"no_license","max_line_length":47,"num_lines":13,"path":"/Level1/68935.py","repo_name":"YoonKiBum/programmers","src_encoding":"UTF-8","text":"def solution(n):\n arr = []\n while True:\n if n == 0:\n break\n i = n % 3\n arr.append(i)\n n = n // 3\n \n sum = 0\n for i in range(len(arr)):\n sum += (3 ** i) * arr[len(arr) - i - 1]\n return sum\n"}],"string":"[\n {\n \"alpha_fraction\": 0.4661017060279846,\n \"alphanum_fraction\": 0.5885122418403625,\n \"avg_line_length\": 33.25806427001953,\n \"blob_id\": \"389a65eecf0760c996a72a33922d85c63e2666d0\",\n \"content_id\": \"6cf21376f20d0a774fb99ee560530c762543f2fe\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 1510,\n \"license_type\": \"no_license\",\n \"max_line_length\": 48,\n \"num_lines\": 31,\n \"path\": \"/README.md\",\n \"repo_name\": \"YoonKiBum/programmers\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# programmers\\n
\\n\\n### 코딩테스트 연습 (Python 소스코드)\\n\\n### Level 1\\n * 크레인 인형뽑기 게임: ([Python 코드](/Level1/64061.py))\\n * 두 개 뽑아서 더하기: ([Python 코드](/Level1/68644.py))\\n * 완주하지 못한 선수: ([Python 코드](/Level1/42576.py))\\n * 모의고사: ([Python 코드](/Level1/42840.py))\\n * k번째 수: ([Python 코드](/Level1/42748.py))\\n * 체육복: ([Python 코드](/Level1/42862.py))\\n * 2016년: ([Python 코드](/Level1/12901.py))\\n * 3진법 뒤집기: ([Python 코드](/Level1/68935.py))\\n * 가운데 글자 가져오기: ([Python 코드](/Level1/12903.py))\\n * 같은 숫자는 싫어: ([Python 코드](/Level1/12906.py))\\n \\n### Level 2\\n * 다리를 지나는 트럭: ([Python 코드](/Level2/42583.py))\\n * 주식가격: ([Python 코드](/Level2/42584.py))\\n * 스킬트리: ([Python 코드](/Level2/49993.py))\\n### 카카오공채\\n * 자물쇠와 열쇠: ([Python 코드](/카카오공채/60059.py))\\n * 기둥과 보 설치: ([Python 코드](/카카오공채/60061.py))\\n * 문자열 압축: ([Python 코드](/카카오공채/60057.py))\\n * 괄호 변환: ([Python 코드](/카카오공채/60058.py))\\n * 블록 이동하기: ([Python 코드](/카카오공채/60063.py))\\n * 실패율: ([Python 코드](/카카오공채/42889.py))\\n * 가사 검색: ([Python 코드](/카카오공채/60060.py))\\n * 무지의 먹방 라이브: ([Python 코드](/카카오공채/42891.py))\\n * 외벽 점검: ([Python 코드](/카카오공채/60062.py))\\n\"\n },\n {\n \"alpha_fraction\": 0.44736841320991516,\n \"alphanum_fraction\": 0.4583333432674408,\n \"avg_line_length\": 25.823530197143555,\n \"blob_id\": \"10174d7e3620bd33fcf72f52c1c178c178582adc\",\n \"content_id\": \"500b40da1e65650180a3280566130fcd45ed1572\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 456,\n \"license_type\": \"no_license\",\n \"max_line_length\": 46,\n \"num_lines\": 17,\n \"path\": \"/Level2/49993.py\",\n \"repo_name\": \"YoonKiBum/programmers\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import copy\\ndef solution(skill, skill_trees):\\n count = 0\\n check = [0] * len(skill)\\n for word in skill_trees:\\n copyskill = list(copy.deepcopy(skill))\\n check = True\\n for i in word:\\n if i in copyskill:\\n res = copyskill[0]\\n if res != i:\\n check = False\\n break\\n copyskill.pop(0)\\n if check: \\n count += 1\\n return count\\n\"\n },\n {\n \"alpha_fraction\": 0.6192052960395813,\n \"alphanum_fraction\": 0.6291390657424927,\n \"avg_line_length\": 24.16666603088379,\n \"blob_id\": \"ed2837d7ad12ce569757025fbb8e849d5d9914bd\",\n \"content_id\": \"db5bd041bef13d865896451ff73483fc84a3e5a5\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 302,\n \"license_type\": \"no_license\",\n \"max_line_length\": 48,\n \"num_lines\": 12,\n \"path\": \"/Level1/68644.py\",\n \"repo_name\": \"YoonKiBum/programmers\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from itertools import combinations\\n\\ndef solution(numbers):\\n answer = []\\n for combination in combinations(numbers, 2):\\n x = int(combination[0])\\n y = int(combination[1])\\n answer.append(x+y)\\n answer = set(answer)\\n answer = list(answer)\\n answer.sort()\\n return answer\\n\"\n },\n {\n \"alpha_fraction\": 0.43499043583869934,\n \"alphanum_fraction\": 0.45984703302383423,\n \"avg_line_length\": 33.86666488647461,\n \"blob_id\": \"01ac47fc0ca59d5d93853ebc9ae7624507261619\",\n \"content_id\": \"bef4a9ab3a4b8c108198f2104bda22ecab3706c6\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1120,\n \"license_type\": \"no_license\",\n \"max_line_length\": 119,\n \"num_lines\": 30,\n \"path\": \"/카카오공채/60061.py\",\n \"repo_name\": \"YoonKiBum/programmers\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# https://programmers.co.kr/learn/courses/30/lessons/60061\\ndef check(answer):\\n for i in range(len(answer)):\\n x, y, a = answer[i]\\n if a == 0: # 기둥 인 경우\\n if y == 0 or [x-1, y, 1] in answer or [x, y, 1] in answer or [x, y-1, 0] in answer:\\n continue\\n else:\\n return False\\n elif a == 1: # 보 인 경우\\n if [x, y-1, 0] in answer or [x+1, y-1, 0] in answer or ([x-1, y, 1] in answer and [x+1, y , 1] in answer): \\n continue\\n else:\\n return False\\n return True\\n\\ndef solution(n, build_frame):\\n answer = []\\n for i in range(len(build_frame)):\\n x, y, a, b = build_frame[i]\\n if b == 1: # 설치인 경우\\n answer.append([x, y, a])\\n if check(answer) == False: # 조건에서 어긋난 경우\\n answer.pop()\\n elif b == 0: # 삭제인 경우\\n answer.remove([x, y, a])\\n if check(answer) == False: # 조건에서 어긋난 경우\\n answer.append([x, y, a])\\n \\n return sorted(answer)\\n\"\n },\n {\n \"alpha_fraction\": 0.446153849363327,\n \"alphanum_fraction\": 0.4703296720981598,\n \"avg_line_length\": 31.5,\n \"blob_id\": \"a326dbf5a7459cc4a978a862155a4376673344ff\",\n \"content_id\": \"121567e46450f25d6f3092ba7882f867f7c7186c\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 455,\n \"license_type\": \"no_license\",\n \"max_line_length\": 79,\n \"num_lines\": 14,\n \"path\": \"/Level1/64061.py\",\n \"repo_name\": \"YoonKiBum/programmers\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"def solution(board, moves):\\n answer = [-1]\\n count = 0\\n for i in range(len(moves)):\\n for j in range(len(board)):\\n if board[j][moves[i]-1] != 0:\\n answer.append(board[j][moves[i]-1])\\n board[j][moves[i]-1] = 0\\n break\\n if len(answer) >= 3 and answer[len(answer)-1] == answer[len(answer)-2]:\\n answer.pop()\\n answer.pop()\\n count += 2\\n return count\\n\"\n },\n {\n \"alpha_fraction\": 0.4358353614807129,\n \"alphanum_fraction\": 0.4479418992996216,\n \"avg_line_length\": 23.294116973876953,\n \"blob_id\": \"a11d325699728c74421ad4ec97f2ad18a42dec95\",\n \"content_id\": \"43d9f5b991d938615cfa8d0193fbdeba5caecb88\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 413,\n \"license_type\": \"no_license\",\n \"max_line_length\": 36,\n \"num_lines\": 17,\n \"path\": \"/카카오공채/42889.py\",\n \"repo_name\": \"YoonKiBum/programmers\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"def solution(N, stages):\\n total = len(stages)\\n arr = []\\n ans = []\\n for i in range(1, N + 1):\\n temp = stages.count(i)\\n if total > 0:\\n fail = temp / total\\n total -= temp\\n arr.append((fail, -(i)))\\n else:\\n arr.append((0, -(i)))\\n arr.sort(reverse = True)\\n \\n for i in range(len(arr)):\\n ans.append(-(arr[i][1]))\\n return ans\\n\"\n },\n {\n \"alpha_fraction\": 0.3840177655220032,\n \"alphanum_fraction\": 0.4694783687591553,\n \"avg_line_length\": 30.034482955932617,\n \"blob_id\": \"80add779e8e57fbfb7a79531157d111e840f7207\",\n \"content_id\": \"df1539b6db799fc1ec199d8ab3b7ca7c67703984\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 901,\n \"license_type\": \"no_license\",\n \"max_line_length\": 58,\n \"num_lines\": 29,\n \"path\": \"/Level1/42840.py\",\n \"repo_name\": \"YoonKiBum/programmers\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# https://programmers.co.kr/learn/courses/30/lessons/42840\\ndef solution(answers):\\n answer = []\\n people_1 = [1, 2, 3, 4, 5] * 2000\\n people_2 = [2, 1, 2, 3, 2, 4, 2, 5] * 2000\\n people_3 = [3, 3, 1, 1, 2, 2, 4, 4, 5, 5] * 1000\\n num_of_1 = 0; num_of_2 = 0; num_of_3 = 0\\n \\n for i in range(len(answers)):\\n if answers[i] == people_1[i]:\\n num_of_1 += 1\\n if answers[i] == people_2[i]:\\n num_of_2 += 1\\n if answers[i] == people_3[i]:\\n num_of_3 += 1\\n \\n temp = [(num_of_1,1), (num_of_2,2), (num_of_3,3)] \\n temp.sort(reverse = True)\\n temp.append((-1, -1))\\n \\n for i in range(3):\\n if temp[i][0] != temp[i+1][0]:\\n answer.append(temp[i][1])\\n answer.sort()\\n return answer\\n elif temp[i][0] == temp[i+1][0]:\\n answer.append(temp[i][1])\\n answer.sort()\\n return answer\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.5360000133514404,\n \"alphanum_fraction\": 0.5440000295639038,\n \"avg_line_length\": 24,\n \"blob_id\": \"4d5080e45ec7385d55b86e0dc3f4b357cd04b522\",\n \"content_id\": \"9c485825aebefb31e69640a0bc5c232726ece56e\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 250,\n \"license_type\": \"no_license\",\n \"max_line_length\": 39,\n \"num_lines\": 10,\n \"path\": \"/Level1/42748.py\",\n \"repo_name\": \"YoonKiBum/programmers\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"def solution(array, commands):\\n n = len(commands)\\n answer = []\\n for i in range(n):\\n start, end, count = commands[i]\\n temp = array[start-1:end]\\n temp.sort()\\n answer.append(temp[count-1])\\n \\n return answer\\n\"\n },\n {\n \"alpha_fraction\": 0.35738831758499146,\n \"alphanum_fraction\": 0.4536082446575165,\n \"avg_line_length\": 23.25,\n \"blob_id\": \"a9cf860a174d6f44a9e897edaa2526a7c04f7de6\",\n \"content_id\": \"b49850c5d0c5a8efbea09d56c478e137ea6e5542\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 291,\n \"license_type\": \"no_license\",\n \"max_line_length\": 60,\n \"num_lines\": 12,\n \"path\": \"/Level1/12901.py\",\n \"repo_name\": \"YoonKiBum/programmers\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"def solution(a, b):\\n month = [31, 29, 31, 30, 31, 30, 31, 31, 30, 31, 30, 31]\\n ans = ['FRI','SAT','SUN','MON','TUE','WED','THU']\\n index = a - 1 \\n day = b - 1\\n \\n sum = 0\\n for i in range(index):\\n sum += month[i]\\n sum += day\\n sum = sum % 7\\n return ans[sum]\\n\"\n },\n {\n \"alpha_fraction\": 0.43091654777526855,\n \"alphanum_fraction\": 0.45690834522247314,\n \"avg_line_length\": 31.488889694213867,\n \"blob_id\": \"847ca7e2654788621c1a2914e563351241d300c3\",\n \"content_id\": \"da68286cc13e68f17555905be5135deb46ce0bc8\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1482,\n \"license_type\": \"no_license\",\n \"max_line_length\": 67,\n \"num_lines\": 45,\n \"path\": \"/카카오공채/60063.py\",\n \"repo_name\": \"YoonKiBum/programmers\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from collections import deque\\n\\ndef can_move(pos, graph):\\n next_pos = []\\n pos = list(pos)\\n lx, ly, rx, ry = pos[0][0], pos[0][1], pos[1][0], pos[1][1]\\n dx = [-1, 1, 0, 0]\\n dy = [0, 0, -1, 1]\\n for i in range(4):\\n nlx, nly, nrx, nry = lx+dx[i], ly+dy[i], rx+dx[i], ry+dy[i]\\n if graph[nlx][nly] == 0 and graph[nrx][nry] == 0:\\n next_pos.append({(nlx, nly), (nrx, nry)})\\n if lx == rx: # 가로인 경우\\n for i in [-1, 1]:\\n if graph[lx+i][ly] == 0 and graph[rx+i][ry] == 0:\\n next_pos.append({(lx,ly), (lx+i, ly)})\\n next_pos.append({(rx, ry), (rx+i, ry)})\\n elif ly == ry: # 세로인 경우\\n for i in [-1, 1]:\\n if graph[lx][ly+i] == 0 and graph[rx][ry+i] == 0:\\n next_pos.append({(lx, ly), (lx, ly+i)})\\n next_pos.append({(rx, ry), (rx, ry+i)})\\n return next_pos\\n\\ndef solution(board):\\n n = len(board) + 2\\n m = len(board)\\n graph = [[1]*n for _ in range(n)]\\n for i in range(m):\\n for j in range(m):\\n graph[i+1][j+1] = board[i][j]\\n q = deque()\\n visited = []\\n pos = {(1, 1), (1, 2)}\\n q.append((pos, 0))\\n visited.append(pos)\\n while q:\\n pos, cost = q.popleft()\\n if (m, m) in pos:\\n return cost\\n for next_pos in can_move(pos, graph):\\n if next_pos not in visited:\\n q.append((next_pos, cost+1))\\n visited.append(next_pos)\\n return 0\\n\"\n },\n {\n \"alpha_fraction\": 0.49077489972114563,\n \"alphanum_fraction\": 0.5129151344299316,\n \"avg_line_length\": 26.100000381469727,\n \"blob_id\": \"8b577448f1d6521cde1cab13d53b910cc7f1f024\",\n \"content_id\": \"57423838cee8e0ab8338166bc1ae53a64992141c\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 542,\n \"license_type\": \"no_license\",\n \"max_line_length\": 39,\n \"num_lines\": 20,\n \"path\": \"/Level1/42862.py\",\n \"repo_name\": \"YoonKiBum/programmers\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"def solution(n, lost, reserve):\\n lost.sort()\\n reserve.sort()\\n count = 0\\n lost = set(lost)\\n reserve = set(reserve)\\n temp1 = lost - reserve\\n temp2 = reserve - lost\\n lost = list(temp1)\\n reserve = list(temp2)\\n for i in range(len(lost)):\\n if len(reserve) <= 0:\\n break\\n if lost[i] - 1 in reserve:\\n reserve.remove(lost[i]-1)\\n count += 1\\n elif lost[i] + 1 in reserve:\\n reserve.remove(lost[i] + 1)\\n count += 1\\n return n - (len(lost) - count)\\n\"\n },\n {\n \"alpha_fraction\": 0.3531745970249176,\n \"alphanum_fraction\": 0.3769841194152832,\n \"avg_line_length\": 18.384614944458008,\n \"blob_id\": \"b6647bf18555789bbb087f31d0dcf2a584d857fd\",\n \"content_id\": \"bac1a4b438b884c1326c8146b1b3d8139387d74f\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 252,\n \"license_type\": \"no_license\",\n \"max_line_length\": 47,\n \"num_lines\": 13,\n \"path\": \"/Level1/68935.py\",\n \"repo_name\": \"YoonKiBum/programmers\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"def solution(n):\\n arr = []\\n while True:\\n if n == 0:\\n break\\n i = n % 3\\n arr.append(i)\\n n = n // 3\\n \\n sum = 0\\n for i in range(len(arr)):\\n sum += (3 ** i) * arr[len(arr) - i - 1]\\n return sum\\n\"\n }\n]"},"num_files":{"kind":"number","value":12,"string":"12"}}},{"rowIdx":2068,"cells":{"repo_name":{"kind":"string","value":"leying95/stereopy"},"repo_url":{"kind":"string","value":"https://github.com/leying95/stereopy"},"snapshot_id":{"kind":"string","value":"0638be0586d056fc5a396c57359303a49f6cf639"},"revision_id":{"kind":"string","value":"1580a88a091a2ebc0f177ea73409e2c4b4dd4c7e"},"directory_id":{"kind":"string","value":"6c87cf3f76566cde6ec6d86891cae649b3fc1582"},"branch_name":{"kind":"string","value":"refs/heads/main"},"visit_date":{"kind":"string","value":"2023-03-29T22:12:40.346022"},"revision_date":{"kind":"string","value":"2021-04-09T03:17:09"},"committer_date":{"kind":"string","value":"2021-04-09T03:17:09"},"github_id":{"kind":"number","value":358531712,"string":"358,531,712"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"string","value":"MIT"},"gha_created_at":{"kind":"string","value":"2021-04-16T08:36:07"},"gha_updated_at":{"kind":"string","value":"2021-04-15T12:44:28"},"gha_pushed_at":{"kind":"string","value":"2021-04-15T13:25:58"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.40083393454551697,"alphanum_fraction":0.5601885318756104,"avg_line_length":25.257143020629883,"blob_id":"7bd2f370968ac513aa8f45d4b85f38dba0a2b29f","content_id":"e13c71464e3fbf9b2020ffb3cba140cc0bc8926e","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":6558,"license_type":"permissive","max_line_length":199,"num_lines":210,"path":"/stereo/plots/plot_data_description.md","repo_name":"leying95/stereopy","src_encoding":"UTF-8","text":"# 绘图数据需求\n\n以 AnnData 为参照获取对应的输入数据\n\n## plot_spatial_distribution\n\n### 所需 AnnData 数据：\n\n- 图像坐标信息： \n - `spatial_data = np.array(adata.obsm[\"spatial\"])`\n\n- 图像散点数值信息： \n - `color_data = np.array(adata.obs_vector(key))`\n - 其中 key 为散点所需呈现的数据种类，如 total_counts, n_genes_by_counts，可利用的数据种类都在 `adata.obs.keys()`\n\n### 实际所需数据格式：\n\n- 图像坐标信息demo：\n \n ```Text\n array([[ 256, -91],[ 185, -157],[ 257, -288],...,[ 151, -246],[ 290, -141],[ 177, -132]])\n ```\n\n- 图像散点数值信息demo：\n \n ```Text\n array([3582., 1773., 2283., ..., 4062., 4371., 1172.], dtype=float32)\n ```\n\n其中散点数值和坐标信息一一对应\n\n## plot_spatial_cluster && plot_cluster_umap\n\n这两个函数整合成了 plot_cluster_result，区别在于所用的 spatial data （pos_key） 不同， plot_spatial_cluster 使用的是 spatial 空间数据，plot_cluster_umap 使用的是 X_umap 的主成分值数据\n\n### 所需 AnnData 数据：\n\n- 图像坐标信息： \n - `spatial_data = np.array(adata.obsm[pos_key])`\n\n- 图像散点数值信息： \n - `color_data = np.array(adata.obs_vector(key))`\n - 其中 key 为散点所需呈现的数据种类，可利用的数据种类都在 adata.obs.keys()，此处用到的主要是聚类相关数据，如 [\"phenograph\", \"leiden\"]\n - 在 cluster 相关的图像中，散点数据属于 categorical 数据\n\n### 实际所需数据格式：\n\n- 图像坐标信息demo：\n \n spatial:\n\n ```Text\n array([[ 256, -91],[ 185, -157],[ 257, -288],...,[ 151, -246],[ 290, -141],[ 177, -132]])\n ```\n\n umap：\n \n ```Text\n array([[-2.234908 , 3.7087667 ], [ 3.7431364 , 2.003201 ], [ 4.849478 , -0.21215418], ..., [ 6.861894 , 1.7589074 ], [-0.4605783 , 4.0366364 ], [ 7.3391566 , -0.40746352]], dtype=float32)\n ```\n\n- 图像散点数值信息demo：\n \n ```Text\n ['0', '3', '5', '3', '2', ..., '4', '3', '6', '1', '5']\n Length: 22726\n Categories (10, object): ['0', '1', '2', '3', ..., '6', '7', '8', '9']\n ```\n\n其中散点数值和坐标信息一一对应\n\n\n## plot_to_select_filter_value\n\n### 所需 AnnData 数据\n\n- `x = adata.obs_vector(var1)`\n- `y = adata.obs_vector(var2)`\n\nvar1 var2 可以是任意两个 obs_key 中的值\n\n### 实际所需数据格式\n\n```Text\narray([3582., 1773., 2283., ..., 4062., 4371., 1172.], dtype=float32)\n```\n\n## plot_variable_gene\n\n### 所需 AnnData 数据：\n\n- `adata.var.highly_variable`\n- `adata.var.means`\n- `adata.var.dispersions`\n- `adata.var.dispersions_norm`\n\n### 实际所需数据格式\n\npandas.core.series.Series\n\n例如： adata.var.means:\n\n```Text\nAL355102.2 0.012042\nSLC25A2 0.000596\n ... \nAC069214.1 0.009608\nAL356056.1 0.001655\nName: means, Length: 33304, dtype: float64\n```\n\n## plot_expression_difference\n\n### 所需 AnnData 数据\n\n- 聚类得到的类名： `group_names = adata.uns[\"rank_genes_groups\"]['names'].dtype.names`\n- 在各个类名（group_name in group_names）的基础上获取各个类的基因列表('names')和分数('scores')：\n - `gene_names = adata.uns[\"rank_genes_groups\"]['names'][group_name][:number_of_gene_to_show]`\n - `scores = adata.uns[\"rank_genes_groups\"]['scores'][group_name][:number_of_gene_to_show]`\n\n### 实际所需数据格式：\n\n- 聚类得到的类名：\n\n ```Text\n tuple('0', '1', '2', '3', '4', '5', '6', '7', '8', '9')\n ```\n- 各个类名对应的基因列表和分数列表：\n \n ```Text\n numpy.ndarray\n \n array(['TUBB4B', 'SLC12A2', 'EPHB3', ..., 'TFF3', 'TIMP1', 'OLFM4'],\n dtype=object)\n \n array([ 28.094688, 27.638664, 24.523687, ..., -41.63738 , -42.894638, -48.384773], dtype=float32)\n ```\n\n## plot_violin_distribution\n\n### 所需 AnnData 数据\n\n- `adata.obs['total_counts']`\n- `adata.obs['n_genes_by_counts']`\n- `adata.obs['pct_counts_mt']`\n\n### 实际所需数据格式\n\npandas.core.series.Series\n\n例如： total_counts:\n\n```Text\n256-91 3582.0\n185-157 1773.0\n ... \n290-141 4371.0\n177-132 1172.0\nName: total_counts, Length: 22726, dtype: float32\n```\n\n## plot_heatmap_maker_genes\n\n### 所需 AnnData 数据：\n\n- 聚类得到的类名： `marker_clusters = adata.uns[\"rank_genes_groups\"]['names'].dtype.names`\n- 在各个类名（cluster in marker_clusters）的基础上获取各个类的基因列表('names'):\n - `genes_array = adata.uns[\"rank_genes_groups\"]['names'][group_name][:number_of_gene_to_show]`\n- 设定表达量矩阵（热图矩阵）\n - 矩阵index： `adata.obs_name`\n - 整合各个类的基因列表，获取 uniq gene list，然后获取这些uniq gene 的表达量来构建 pandas.DataFrame\n - 表达量： `exp_matrix = adata.X[tuple([slice(None), adata.var.index.get_indexer(uniq_gene_names)])]`\n - pd.DataFrame: `pd.DataFrame(exp_matrix, columns=uniq_gene_names, index=adata.obs_names)`\n - 添加 obs 列在最开头： `pd.concat([draw_df, adata.obs[cluster_method]], axis=1)`\n \n\n### 实际所需数据格式：\n\n- 聚类得到的类名：\n\n ```Text\n tuple('0', '1', '2', '3', '4', '5', '6', '7', '8', '9')\n ```\n\n- 各个类名对应的基因列表：\n \n ```Text\n numpy.ndarray\n \n array(['TUBB4B', 'SLC12A2', 'EPHB3', ..., 'TFF3', 'TIMP1', 'OLFM4'],\n dtype=object)\n ```\n\n- 表达量矩阵最终效果：\n \n ```Text\n TUBB4B SLC12A2 EPHB3 MT-ND1 FTX NAALADL2 \n phenograph \n 0 3.758313 1.884562 2.705292 4.040148 2.498723 2.238069 \n 0 3.118562 1.224227 1.758388 3.311160 1.758388 0.000000 \n 0 2.790583 0.000000 0.000000 3.175375 0.000000 0.000000 \n 0 0.000000 1.885036 1.885036 3.821939 0.000000 0.000000 \n 0 2.596922 0.000000 2.596922 3.644590 2.596922 2.596922 \n ... ... ... ... ... ... ... \n 9 3.172084 1.570598 0.000000 4.186041 1.570598 0.000000 \n 9 0.000000 1.847625 0.000000 3.893912 0.000000 2.458688 \n 9 2.681648 2.681648 0.000000 3.339970 1.314215 1.314215 \n 9 1.955572 1.955572 0.000000 3.229691 1.955572 0.000000 \n 9 2.963927 1.721601 1.721601 3.176694 1.721601 0.000000 \n ```\n\n\n"},{"alpha_fraction":0.5407407283782959,"alphanum_fraction":0.614814817905426,"avg_line_length":15.875,"blob_id":"6be96570692f13225dce46515d9ca9c98fef1296","content_id":"0a956633adf2311ac4c74e39451ffd2cbcbd1029","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":135,"license_type":"permissive","max_line_length":25,"num_lines":8,"path":"/stereo/plots/_plot_basic/__init__.py","repo_name":"leying95/stereopy","src_encoding":"UTF-8","text":"#!/usr/bin/env python3\n# coding: utf-8\n\"\"\"\n@author: Shixu He heshixu@genomics.cn\n@last modified by: Shixu He\n@file:__init__.py.py\n@time:2021/03/15\n\"\"\"\n"},{"alpha_fraction":0.8245614171028137,"alphanum_fraction":0.8245614171028137,"avg_line_length":27.5,"blob_id":"07e56b8199fa5930875326eee974fd0b94d0cbaa","content_id":"a08af99a95386dcc9a13b89532990ab6cd210c1f","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":57,"license_type":"permissive","max_line_length":45,"num_lines":2,"path":"/README.md","repo_name":"leying95/stereopy","src_encoding":"UTF-8","text":"# stereopy\nA toolkit of spatial transcriptomic analysis.\n"},{"alpha_fraction":0.576362669467926,"alphanum_fraction":0.582298994064331,"avg_line_length":30.94827651977539,"blob_id":"da5efc016b2d7c7a1cc9131a627d2377e1ae0157","content_id":"66c073cd335fd0fa657926a18e9d780efb70e29a","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1853,"license_type":"permissive","max_line_length":78,"num_lines":58,"path":"/stereo/log_manager.py","repo_name":"leying95/stereopy","src_encoding":"UTF-8","text":"#!/usr/bin/env python3\n# coding: utf-8\n\"\"\"\n@author: Ping Qiu qiuping1@genomics.cn\n@last modified by: Ping Qiu\n@file:log_manager.py\n@time:2021/03/05\n\"\"\"\n\nimport logging\nfrom .config import stereo_conf\n\n\nclass LogManager(object):\n def __init__(self, log_path=None, level=None):\n self.level_map = {'debug': logging.DEBUG,\n 'info': logging.INFO,\n 'warning': logging.WARNING,\n 'error': logging.ERROR,\n 'critical': logging.CRITICAL}\n self.format = stereo_conf.log_format\n self.formatter = logging.Formatter(self.format, \"%Y-%m-%d %H:%M:%S\")\n self.log_path = log_path\n self.level = level.lower() if level else stereo_conf.log_level.lower()\n if self.log_path:\n self.file_handler = logging.FileHandler(self.log_path)\n self.file_handler.setLevel(self.level_map[self.level])\n self.file_handler.setFormatter(self.formatter)\n else:\n self.stream_handler = logging.StreamHandler()\n self.stream_handler.setLevel(self.level_map[self.level])\n self.stream_handler.setFormatter(self.formatter)\n\n def get_logger(self, name=\"Spateo\"):\n \"\"\"\n get logger object\n :param name: logger name\n :return: logger object\n \"\"\"\n alogger = logging.getLogger(name)\n alogger.propagate = 0\n alogger.setLevel(self.level_map[self.level])\n self._add_handler(alogger)\n return alogger\n\n def _add_handler(self, alogger):\n \"\"\"\n add handler of logger\n :param logger: logger object\n :return:\n \"\"\"\n if self.log_path:\n alogger.addHandler(self.file_handler)\n else:\n alogger.addHandler(self.stream_handler)\n\n\nlogger = LogManager().get_logger(name='Spateo')\n"},{"alpha_fraction":0.5441176295280457,"alphanum_fraction":0.5572336912155151,"avg_line_length":34.42253494262695,"blob_id":"223b8ada9eb9f510c9b68f7895d4f42a65b81f8e","content_id":"0299148833875c5536949e7ad7ae0d0f9b9dafff","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":2516,"license_type":"permissive","max_line_length":117,"num_lines":71,"path":"/stereo/tools/neighbors.py","repo_name":"leying95/stereopy","src_encoding":"UTF-8","text":"#!/usr/bin/env python3\n# coding: utf-8\n\"\"\"\n@author: Ping Qiu qiuping1@genomics.cn\n@last modified by: Ping Qiu\n@file:neighbors.py\n@time:2021/03/23\n\"\"\"\nfrom scipy.sparse import coo_matrix\nfrom sklearn.neighbors import NearestNeighbors\nimport igraph as ig\nimport numpy as np\nfrom umap.umap_ import fuzzy_simplicial_set\n\n\nclass Neighbors(object):\n def __init__(self, x, n_neighbors):\n self.x = x\n self.n_neighbors = n_neighbors\n\n def find_n_neighbors(self):\n nbrs = NearestNeighbors(n_neighbors=self.n_neighbors + 1, algorithm='ball_tree').fit(self.x)\n dists, indices = nbrs.kneighbors(self.x)\n nn_idx = indices[:, 1:]\n nn_dist = dists[:, 1:]\n return nn_idx, nn_dist\n\n def get_igraph_from_knn(self, nn_idx, nn_dist):\n j = nn_idx.ravel().astype(int)\n dist = nn_dist.ravel()\n i = np.repeat(np.arange(nn_idx.shape[0]), self.n_neighbors)\n\n vertex = list(range(nn_dist.shape[0]))\n edges = list(tuple(zip(i, j)))\n G = ig.Graph()\n G.add_vertices(vertex)\n G.add_edges(edges)\n G.es['weight'] = dist\n return G\n\n def get_parse_distances(self, nn_idx, nn_dist):\n n_obs = self.x.shape[0]\n rows = np.zeros((n_obs * self.n_neighbors), dtype=np.int64)\n cols = np.zeros((n_obs * self.n_neighbors), dtype=np.int64)\n vals = np.zeros((n_obs * self.n_neighbors), dtype=np.float64)\n\n for i in range(nn_idx.shape[0]):\n for j in range(self.n_neighbors):\n if nn_idx[i, j] == -1:\n continue # We didn't get the full knn for i\n if nn_idx[i, j] == i:\n val = 0.0\n else:\n val = nn_dist[i, j]\n\n rows[i * self.n_neighbors + j] = i\n cols[i * self.n_neighbors + j] = nn_idx[i, j]\n vals[i * self.n_neighbors + j] = val\n\n distances = coo_matrix((vals, (rows, cols)), shape=(n_obs, n_obs))\n distances.eliminate_zeros()\n return distances.tocsr()\n\n def get_connectivities(self, nn_idx, nn_dist):\n n_obs = self.x.shape[0]\n x = coo_matrix(([], ([], [])), shape=(n_obs, 1))\n connectivities = fuzzy_simplicial_set(x, self.n_neighbors, None, None, knn_indices=nn_idx, knn_dists=nn_dist,\n set_op_mix_ratio=1.0, local_connectivity=1.0)\n if isinstance(connectivities, tuple):\n connectivities = connectivities[0]\n return connectivities.tocsr()\n\n"},{"alpha_fraction":0.5665071606636047,"alphanum_fraction":0.5779904127120972,"avg_line_length":18.716981887817383,"blob_id":"75c8c1af025576b41fdaa21b6c25ecd8e15afd72","content_id":"cd7efb2f1f96eb9937d843ad9cef415c0aff5d4f","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1045,"license_type":"permissive","max_line_length":107,"num_lines":53,"path":"/stereo/core/stereo_data.py","repo_name":"leying95/stereopy","src_encoding":"UTF-8","text":"#!/usr/bin/env python3\n# coding: utf-8\n\"\"\"\n@author: Ping Qiu qiuping1@genomics.cn\n@last modified by: Ping Qiu\n@file:stereo_data.py\n@time:2021/03/22\n\"\"\"\n\n\nclass StereoData(object):\n def __init__(self, raw_file=None, exp_matrix=None, genes=None, bins=None, position=None, partitions=1):\n self.index = None\n self.index_file = None\n self.exp_matrix = exp_matrix\n self.genes = genes\n self.bins = bins\n self.position = position\n self.raw_file = raw_file\n self.partitions = partitions\n\n def filter_genes(self):\n pass\n\n def filter_bins(self):\n pass\n\n def search(self):\n pass\n\n def combine_bins(self, bin_size, step):\n pass\n\n def select_by_genes(self, gene_list):\n pass\n\n def select_by_position(self, x_min, y_min, x_max, y_max, bin_size):\n pass\n\n def transform_matrix(self):\n pass\n\n def get_genes(self):\n pass\n\n def get_bins(self):\n pass\n\n def split_data(self):\n pass\n\n def sparse2array(self):\n pass\n"},{"alpha_fraction":0.6382660865783691,"alphanum_fraction":0.6636771559715271,"avg_line_length":29.409090042114258,"blob_id":"b9472f782f76c2f6c8aaa8802826cc4656afb1ba","content_id":"ed031fae5add10b548834f898ab95a813e1f9395","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":669,"license_type":"permissive","max_line_length":71,"num_lines":22,"path":"/stereo/preprocess/qc.py","repo_name":"leying95/stereopy","src_encoding":"UTF-8","text":"#!/usr/bin/env python3\n# coding: utf-8\n\"\"\"\n@author: Ping Qiu qiuping1@genomics.cn\n@last modified by: Ping Qiu\n@file:qc.py\n@time:2021/03/26\n\"\"\"\nfrom scipy.sparse import issparse\nimport numpy as np\n\n\ndef cal_qc(andata):\n exp_matrix = andata.X.toarray() if issparse(andata.X) else andata.X\n total_count = exp_matrix.sum(1)\n n_gene_by_count = np.count_nonzero(exp_matrix, axis=1)\n mt_index = andata.var_names.str.startswith('MT-')\n mt_count = np.array(andata.X[:, mt_index].sum(1)).reshape(-1)\n andata.obs['total_counts'] = total_count\n andata.obs['pct_counts_mt'] = mt_count / total_count * 100\n andata.obs['n_genes_by_counts'] = n_gene_by_count\n return andata\n"},{"alpha_fraction":0.5326364636421204,"alphanum_fraction":0.5358884930610657,"avg_line_length":25.411043167114258,"blob_id":"57ec9a317b271c5001152cd0804fe0de76566362","content_id":"5e726176ef70882e7b7c303bdb60a84d1c62f300","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":4305,"license_type":"permissive","max_line_length":114,"num_lines":163,"path":"/stereo/config.py","repo_name":"leying95/stereopy","src_encoding":"UTF-8","text":"#!/usr/bin/env python3\n# coding: utf-8\n\"\"\"\n@author: Ping Qiu qiuping1@genomics.cn\n@last modified by: Ping Qiu\n@file:config.py\n@time:2021/03/05\n\"\"\"\nfrom typing import Union, Optional\nfrom pathlib import Path\nimport os\nfrom matplotlib import rcParams, rcParamsDefault\n\n\nclass StereoConfig(object):\n \"\"\"\n config of stereo.\n \"\"\"\n def __init__(\n self,\n file_format: str = \"h5ad\",\n auto_show: bool = True,\n n_jobs=1,\n log_file: Union[str, Path, None] = None,\n log_level: str = \"info\",\n log_format: str = \"%(asctime)s %(name)s %(levelname)s: %(message)s\",\n output: str = \"./output\",\n data_dir: str = None\n ):\n self._file_format = file_format\n self._auto_show = auto_show\n self._n_jobs = n_jobs\n self._log_file = log_file\n self._log_level = log_level\n self._log_format = log_format\n self.out_dir = output\n self.data_dir = data_dir if data_dir else os.path.join(os.path.dirname(os.path.abspath(__file__)), 'data')\n\n @property\n def log_file(self) -> Union[str, Path, None]:\n \"\"\"\n get the file path of log.\n :return:\n \"\"\"\n return self._log_file\n\n @log_file.setter\n def log_file(self, value):\n \"\"\"\n set file path of log.\n :param value: value of log file path\n :return:\n \"\"\"\n if value:\n dir_path = os.path.dirname(value)\n if not os.path.exists(dir_path):\n raise FileExistsError(\"folder does not exist, please check!\")\n self._log_file = value\n\n @property\n def log_format(self) -> str:\n \"\"\"\n get the format of log.\n :return:\n \"\"\"\n return self._log_format\n\n @log_format.setter\n def log_format(self, value):\n \"\"\"\n set file path of log.\n :param value: value of log format\n :return:\n \"\"\"\n self._log_format = value\n\n @property\n def log_level(self) -> str:\n \"\"\"\n get log level\n :return:\n \"\"\"\n return self._log_level\n\n @log_level.setter\n def log_level(self, value):\n \"\"\"\n set log level\n :param value: the value of log level\n :return:\n \"\"\"\n if value.lower() not in ['info', 'warning', 'debug', 'error', 'critical']:\n print('the log level is out of range, please check and it is not modified.')\n else:\n self._log_level = value\n\n @property\n def auto_show(self):\n \"\"\"\n Auto show figures if `auto_show == True` (default `True`).\n :return:\n \"\"\"\n return self._auto_show\n\n @auto_show.setter\n def auto_show(self, value):\n \"\"\"\n set value of auto_show\n :param value: value of auto_show\n :return:\n \"\"\"\n self._auto_show = value\n\n @property\n def file_format(self) -> str:\n \"\"\"\n file format of saving anndata object\n :return:\n \"\"\"\n return self._file_format\n\n @file_format.setter\n def file_format(self, value):\n \"\"\"\n set the value of file format\n :param value: the value of file format\n :return:\n \"\"\"\n self._file_format = value\n\n @property\n def n_jobs(self) -> int:\n return self._n_jobs\n\n @n_jobs.setter\n def n_jobs(self, value):\n self._n_jobs = value\n\n @staticmethod\n def set_plot_param(fontsize: int = 14, figsize: Optional[int] = None, color_map: Optional[str] = None,\n facecolor: Optional[str] = None, transparent: bool = False,):\n if fontsize is not None:\n rcParams['font.size'] = fontsize\n if color_map is not None:\n rcParams['image.cmap'] = color_map\n if figsize is not None:\n rcParams['figure.figsize'] = figsize\n if facecolor is not None:\n rcParams['figure.facecolor'] = facecolor\n rcParams['axes.facecolor'] = facecolor\n if transparent is not None:\n rcParams[\"savefig.transparent\"] = transparent\n\n @staticmethod\n def set_rcparams_defaults():\n \"\"\"\n reset `matplotlib.rcParams` to defaults.\n :return:\n \"\"\"\n rcParams.update(rcParamsDefault)\n\n\nstereo_conf = StereoConfig()\n"},{"alpha_fraction":0.552388072013855,"alphanum_fraction":0.5629907250404358,"avg_line_length":33.834495544433594,"blob_id":"5cf9c6e4a72c0d946056b70efefaa0185bdaeffa","content_id":"e13b730eda2fc60a16a1c52046d3725d072fd48c","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":20531,"license_type":"permissive","max_line_length":155,"num_lines":574,"path":"/stereo/plots/plot_utils.py","repo_name":"leying95/stereopy","src_encoding":"UTF-8","text":"#!/usr/bin/env python3\n# coding: utf-8\n\"\"\"\n@author: Shixu He heshixu@genomics.cn\n@last modified by: Shixu He\n@file:plot_utils.py\n@time:2021/03/15\n\"\"\"\n\nfrom anndata import AnnData\nimport pandas as pd\nimport numpy as np\nimport math\n\nfrom matplotlib.colors import Normalize, ListedColormap\nfrom matplotlib import gridspec\nfrom matplotlib.cm import get_cmap\nfrom matplotlib.axes import Axes\nimport matplotlib.pyplot as plt\nimport seaborn\n\nfrom ._plot_basic.scatter_plt import scatter, plot_cluster_result\nfrom ._plot_basic.heatmap_plt import heatmap, _plot_categories_as_colorblocks, _plot_gene_groups_brackets\n\nfrom typing import Optional, Sequence, Union\n\nfrom ..log_manager import logger\n\n\ndef plot_spatial_distribution(\n adata: AnnData,\n obs_key: list = [\"total_counts\", \"n_genes_by_counts\"],\n ncols=2,\n dot_size=None,\n color_list=None,\n invert_y=False\n): # scatter plot, 表达矩阵空间分布\n \"\"\"\n Plot spatial distribution of specified obs data.\n ============ Arguments ============\n :param adata: AnnData object.\n :param obs_key: specified obs key list, for example: [\"total_counts\", \"n_genes_by_counts\"]\n :param ncols: numbr of plot columns.\n :param dot_size: marker size.\n :param cmap: Color map.\n :param invert_y: whether to invert y-axis.\n ============ Return ============\n None\n ============ Example ============\n plot_spatial_distribution(adata=adata)\n \"\"\"\n # sc.pl.embedding(adata, basis=\"spatial\", color=[\"total_counts\", \"n_genes_by_counts\"],size=30)\n\n if dot_size is None:\n dot_size = 120000 / adata.shape[0]\n\n ncols = min(ncols, len(obs_key))\n nrows = np.ceil(len(obs_key) / ncols).astype(int)\n # each panel will have the size of rcParams['figure.figsize']\n fig = plt.figure(figsize=(ncols * 10, nrows * 8))\n left = 0.2 / ncols\n bottom = 0.13 / nrows\n axs = gridspec.GridSpec(\n nrows=nrows,\n ncols=ncols,\n left=left,\n right=1 - (ncols - 1) * left - 0.01 / ncols,\n bottom=bottom,\n top=1 - (nrows - 1) * bottom - 0.1 / nrows,\n # hspace=hspace,\n # wspace=wspace,\n )\n\n if color_list is None:\n cmap = get_cmap()\n else:\n cmap = ListedColormap(color_list)\n # 把特定值改为 np.nan 之后，可以利用 cmap.set_bad(\"white\") 来遮盖掉这部分数据\n\n # 散点图上每个点的坐标数据来自于 adata 的 obsm[\"spatial\"]，每个点的颜色（数值）数据来自于 adata 的 obs_vector()\n for i, key in enumerate(obs_key):\n # color_data = np.asarray(adata.obs_vector(key), dtype=float)\n color_data = adata.obs_vector(key)\n order = np.argsort(~pd.isnull(color_data), kind=\"stable\")\n spatial_data = np.array(adata.obsm[\"spatial\"])[:, 0: 2]\n color_data = color_data[order]\n spatial_data = spatial_data[order, :]\n\n # color_data 是图像中各个点的值，也对应了每个点的颜色。data_points则对应了各个点的坐标\n ax = fig.add_subplot(axs[i]) # ax = plt.subplot(axs[i]) || ax = fig.add_subplot(axs[1, 1]))\n ax.set_title(key)\n ax.set_yticks([])\n ax.set_xticks([])\n ax.set_xlabel(\"spatial1\")\n ax.set_ylabel(\"spatial2\")\n pathcollection = scatter(\n spatial_data[:, 0],\n spatial_data[:, 1],\n ax=ax,\n marker=\".\",\n dot_colors=color_data,\n dot_size=dot_size,\n cmap=cmap,\n )\n plt.colorbar(\n pathcollection,\n ax=ax,\n pad=0.01,\n fraction=0.08,\n aspect=30,\n )\n ax.autoscale_view()\n if invert_y:\n ax.invert_yaxis()\n\n\ndef plot_spatial_cluster(\n adata: AnnData,\n obs_key: list = [\"phenograph\"],\n plot_cluster: list = None,\n bad_color=\"lightgrey\",\n ncols=2,\n dot_size=None,\n invert_y=False,\n color_list=['violet', 'turquoise', 'tomato', 'teal',\n 'tan', 'silver', 'sienna', 'red', 'purple',\n 'plum', 'pink', 'orchid', 'orangered', 'orange',\n 'olive', 'navy', 'maroon', 'magenta', 'lime',\n 'lightgreen', 'lightblue', 'lavender', 'khaki',\n 'indigo', 'grey', 'green', 'gold', 'fuchsia',\n 'darkgreen', 'darkblue', 'cyan', 'crimson', 'coral',\n 'chocolate', 'chartreuse', 'brown', 'blue', 'black',\n 'beige', 'azure', 'aquamarine', 'aqua']): # scatter plot, 聚类后表达矩阵空间分布\n \"\"\"\n Plot spatial distribution of specified obs data.\n ============ Arguments ============\n :param adata: AnnData object.\n :param obs_key: specified obs cluster key list, for example: [\"phenograph\"].\n :param plot_cluster: the name list of clusters to show.\n :param ncols: numbr of plot columns.\n :param dot_size: marker size.\n :param cmap: Color map.\n :param invert_y: whether to invert y-axis.\n ============ Return ============\n None.\n ============ Example ============\n plot_spatial_cluster(adata = adata)\n \"\"\"\n # sc.pl.embedding(adata, basis=\"spatial\", color=[\"total_counts\", \"n_genes_by_counts\"],size=30)\n\n if isinstance(obs_key, str):\n obs_key = [\"obs_key\"]\n\n plot_cluster_result(adata, obs_key=obs_key, pos_key=\"spatial\", plot_cluster=plot_cluster, bad_color=bad_color,\n ncols=ncols, dot_size=dot_size, invert_y=invert_y, color_list=color_list)\n\n\ndef plot_to_select_filter_value(\n adata: AnnData,\n x=[\"total_counts\", \"total_counts\"],\n y=[\"pct_counts_mt\", \"n_genes_by_counts\"],\n ncols=1,\n **kwargs): # scatter plot, 线粒体分布图\n \"\"\"\n Plot .\n ============ Arguments ============\n :param adata: AnnData object.\n :param x, y: obs key pairs for drawing. For example, assume x=[\"a\", \"a\", \"b\"] and y=[\"c\", \"d\", \"e\"], the output plots will include \"a-c\", \"a-d\", \"b-e\".\n ============ Return ============\n None.\n ============ Example ============\n plot_spatial_cluster(adata = adata)\n \"\"\"\n # sc.pl.scatter(adata, x='total_counts', y='pct_counts_mt')\n # sc.pl.scatter(adata, x='total_counts', y='n_genes_by_counts')\n if isinstance(x, str):\n x = [x]\n if isinstance(y, str):\n y = [y]\n\n width = 20\n height = 10\n nrows = math.ceil(len(x) / ncols)\n\n doc_color = \"gray\"\n\n fig = plt.figure(figsize=(width, height))\n axs = gridspec.GridSpec(\n nrows=nrows,\n ncols=ncols,\n )\n for i, (xi, yi) in enumerate(zip(x, y)):\n draw_data = np.c_[adata.obs_vector(xi), adata.obs_vector(yi)]\n dot_size = 120000 / draw_data.shape[0]\n ax = fig.add_subplot(axs[i])\n # ax.set_title()\n # ax.set_yticks([])\n # ax.set_xticks([])\n ax.set_xlabel(xi)\n ax.set_ylabel(yi)\n scatter(\n draw_data[:, 0],\n draw_data[:, 1],\n ax=ax,\n marker=\".\",\n dot_colors=doc_color,\n dot_size=dot_size\n )\n\n\ndef plot_variable_gene(adata: AnnData, logarize=False): # scatter plot, 表达量差异-均值图\n \"\"\"\n Copied from scanpy and modified.\n \"\"\"\n # 该图像需要前置数据处理：sc.pp.highly_variable_genes(adata, min_mean=0.0125, max_mean=3, min_disp=0.5)\n # 再画图：sc.pl.highly_variable_genes(adata)\n\n result = adata.var\n gene_subset = result.highly_variable\n means = result.means\n var_or_disp = result.dispersions\n var_or_disp_norm = result.dispersions_norm\n width = 10\n height = 10\n\n plt.figure(figsize=(2 * width, height))\n plt.subplots_adjust(wspace=0.3)\n for idx, d in enumerate([var_or_disp_norm, var_or_disp]):\n plt.subplot(1, 2, idx + 1)\n for label, color, mask in zip(\n ['highly variable genes', 'other genes'],\n ['black', 'grey'],\n [gene_subset, ~gene_subset],\n ):\n if False:\n means_, var_or_disps_ = np.log10(means[mask]), np.log10(d[mask])\n else:\n means_, var_or_disps_ = means[mask], d[mask]\n plt.scatter(means_, var_or_disps_, label=label, c=color, s=1)\n if logarize: # there's a bug in autoscale\n plt.xscale('log')\n plt.yscale('log')\n y_min = np.min(var_or_disp)\n y_min = 0.95 * y_min if y_min > 0 else 1e-1\n plt.xlim(0.95 * np.min(means), 1.05 * np.max(means))\n plt.ylim(y_min, 1.05 * np.max(var_or_disp))\n if idx == 0:\n plt.legend()\n plt.xlabel(('$log_{10}$ ' if False else '') + 'mean expressions of genes')\n data_type = 'dispersions'\n plt.ylabel(\n ('$log_{10}$ ' if False else '')\n + '{} of genes'.format(data_type)\n + (' (normalized)' if idx == 0 else ' (not normalized)')\n )\n\n\ndef plot_cluster_umap(\n adata: AnnData,\n obs_key: list = [\"phenograph\"],\n plot_cluster: list = None,\n bad_color=\"lightgrey\",\n ncols=2,\n dot_size=None,\n invert_y=False,\n color_list=['violet', 'turquoise', 'tomato', 'teal',\n 'tan', 'silver', 'sienna', 'red', 'purple',\n 'plum', 'pink', 'orchid', 'orangered', 'orange',\n 'olive', 'navy', 'maroon', 'magenta', 'lime',\n 'lightgreen', 'lightblue', 'lavender', 'khaki',\n 'indigo', 'grey', 'green', 'gold', 'fuchsia',\n 'darkgreen', 'darkblue', 'cyan', 'crimson', 'coral',\n 'chocolate', 'chartreuse', 'brown', 'blue', 'black',\n 'beige', 'azure', 'aquamarine', 'aqua',\n ]\n): # scatter plot，聚类结果PCA/umap图\n \"\"\"\n Plot spatial distribution of specified obs data.\n ============ Arguments ============\n :param adata: AnnData object.\n :param obs_key: specified obs cluster key list, for example: [\"phenograph\"].\n :param plot_cluster: the name list of clusters to show.\n :param ncols: numbr of plot columns.\n :param dot_size: marker size.\n :param cmap: Color map.\n :param invert_y: whether to invert y-axis.\n ============ Return ============\n None.\n ============ Example ============\n plot_cluster_umap(adata = adata)\n \"\"\"\n\n if (isinstance(obs_key, str)):\n obs_key = [obs_key]\n\n plot_cluster_result(adata, obs_key=obs_key, pos_key=\"X_umap\", plot_cluster=plot_cluster, bad_color=bad_color,\n ncols=ncols, dot_size=dot_size, invert_y=invert_y, color_list=color_list)\n\n\ndef plot_expression_difference(\n adata: AnnData,\n groups: Union[str, Sequence[str]] = None,\n n_genes: int = 20,\n key: Optional[str] = 'rank_genes_groups',\n fontsize: int = 8,\n ncols: int = 4,\n sharey: bool = True,\n show: Optional[bool] = None,\n save: Optional[bool] = None,\n ax: Optional[Axes] = None,\n **kwds,\n): # scatter plot, 差异基因显著性图，类碎石图\n \"\"\"\n Copied from scanpy and modified.\n \"\"\"\n\n # 调整图像 panel/grid 相关参数\n if 'n_panels_per_row' in kwds:\n n_panels_per_row = kwds['n_panels_per_row']\n else:\n n_panels_per_row = ncols\n group_names = adata.uns[key]['names'].dtype.names if groups is None else groups\n # one panel for each group\n # set up the figure\n n_panels_x = min(n_panels_per_row, len(group_names))\n n_panels_y = np.ceil(len(group_names) / n_panels_x).astype(int)\n\n # 初始化图像\n width = 10\n height = 10\n fig = plt.figure(\n figsize=(\n n_panels_x * width, # rcParams['figure.figsize'][0],\n n_panels_y * height, # rcParams['figure.figsize'][1],\n )\n )\n gs = gridspec.GridSpec(nrows=n_panels_y, ncols=n_panels_x, wspace=0.22, hspace=0.3)\n\n ax0 = None\n ymin = np.Inf\n ymax = -np.Inf\n for count, group_name in enumerate(group_names):\n gene_names = adata.uns[key]['names'][group_name][:n_genes]\n scores = adata.uns[key]['scores'][group_name][:n_genes]\n\n # Setting up axis, calculating y bounds\n if sharey:\n ymin = min(ymin, np.min(scores))\n ymax = max(ymax, np.max(scores))\n\n if ax0 is None:\n ax = fig.add_subplot(gs[count])\n ax0 = ax\n else:\n ax = fig.add_subplot(gs[count], sharey=ax0)\n else:\n ymin = np.min(scores)\n ymax = np.max(scores)\n ymax += 0.3 * (ymax - ymin)\n\n ax = fig.add_subplot(gs[count])\n ax.set_ylim(ymin, ymax)\n\n ax.set_xlim(-0.9, n_genes - 0.1)\n\n # Making labels\n for ig, gene_name in enumerate(gene_names):\n ax.text(\n ig,\n scores[ig],\n gene_name,\n rotation='vertical',\n verticalalignment='bottom',\n horizontalalignment='center',\n fontsize=fontsize,\n )\n\n ax.set_title('{} vs. {}'.format(group_name, \"Others\"))\n if count >= n_panels_x * (n_panels_y - 1):\n ax.set_xlabel('ranking')\n\n # print the 'score' label only on the first panel per row.\n if count % n_panels_x == 0:\n ax.set_ylabel('score')\n\n if sharey is True:\n ymax += 0.3 * (ymax - ymin)\n ax.set_ylim(ymin, ymax)\n\n\ndef plot_violin_distribution(adata): # 小提琴统计图\n \"\"\"\n 绘制数据的分布小提琴图。\n ============ Arguments ============\n :param adata: AnnData object.\n ============ Return ============\n None\n \"\"\"\n _, axs = plt.subplots(1, 3, figsize=(15, 4))\n seaborn.violinplot(y=adata.obs['total_counts'], ax=axs[0])\n seaborn.violinplot(y=adata.obs['n_genes_by_counts'], ax=axs[1])\n seaborn.violinplot(y=adata.obs['pct_counts_mt'], ax=axs[2])\n\n\ndef plot_heatmap_maker_genes(\n adata: AnnData = None,\n cluster_method=\"phenograph\",\n marker_uns_key=None,\n num_show_gene=8,\n show_labels=True,\n order_cluster=True,\n marker_clusters=None,\n cluster_colors_array=None,\n **kwargs\n): # heatmap, 差异基因热图\n \"\"\"\n 绘制 Marker gene 的热图。热图中每一行代表一个 bin 的所有基因的表达量，所有的 bin 会根据所属的 cluster 进行聚集， cluster 具体展示在热图的左侧，用颜色区分。\n ============ Arguments ============\n :param adata: AnnData object.\n :param cluster_methpd: method used in clustering. for example: phenograph, leiden\n :param marker_uns_key: the key of adata.uns, the default value is \"marker_genes\"\n :param num_show_gene: number of genes to show in each cluster.\n :param show_labels: show gene name on axis.\n :param order_cluster: reorder the cluster list in plot (y axis).\n :param marker_clusters: the list of clusters to show on the heatmap.\n :param cluster_colors_array: the list of colors in the color block on the left of heatmap.\n ============ Return ============\n\n ============ Example ============\n plot_heatmap_maker_genes(adata=adata, marker_uns_key = \"rank_genes_groups\", figsize = (20, 10))\n \"\"\"\n\n if marker_uns_key is None:\n marker_uns_key = 'marker_genes' # \"rank_genes_groups\" in original scanpy pipeline\n\n # if cluster_method is None:\n # cluster_method = str(adata.uns[marker_uns_key]['params']['groupby'])\n\n # cluster_colors_array = adata.uns[\"phenograph_colors\"]\n\n if marker_clusters is None:\n marker_clusters = adata.uns[marker_uns_key]['names'].dtype.names\n\n if not set(marker_clusters).issubset(set(adata.uns[marker_uns_key]['names'].dtype.names)):\n marker_clusters = adata.uns[marker_uns_key]['names'].dtype.names\n\n gene_names_dict = {} # dict in which each cluster is the keyand the num_show_gene are the values\n\n for cluster in marker_clusters:\n # get all genes that are 'non-nan'\n genes_array = adata.uns[marker_uns_key]['names'][cluster]\n genes_array = genes_array[~pd.isnull(genes_array)]\n\n if len(genes_array) == 0:\n logger.warning(\"Cluster {} has no genes.\".format(cluster))\n continue\n gene_names_dict[cluster] = list(genes_array[:num_show_gene])\n\n adata._sanitize()\n\n gene_names = []\n gene_group_labels = []\n gene_group_positions = []\n start = 0\n for label, gene_list in gene_names_dict.items():\n if isinstance(gene_list, str):\n gene_list = [gene_list]\n gene_names.extend(list(gene_list))\n gene_group_labels.append(label)\n gene_group_positions.append((start, start + len(gene_list) - 1))\n start += len(gene_list)\n\n # 此处获取所有绘图所需的数据 （表达量矩阵）\n draw_df = pd.DataFrame(index=adata.obs_names)\n uniq_gene_names = np.unique(gene_names)\n draw_df = pd.concat(\n [draw_df, pd.DataFrame(adata.X[tuple([slice(None), adata.var.index.get_indexer(uniq_gene_names)])],\n columns=uniq_gene_names, index=adata.obs_names)],\n axis=1\n )\n\n # add obs values\n draw_df = pd.concat([draw_df, adata.obs[cluster_method]], axis=1)\n\n # reorder columns to given order (including duplicates keys if present)\n draw_df = draw_df[list([cluster_method]) + list(uniq_gene_names)]\n draw_df = draw_df[gene_names].set_index(draw_df[cluster_method].astype('category'))\n if order_cluster:\n draw_df = draw_df.sort_index()\n\n # From scanpy\n # define a layout of 2 rows x 3 columns\n # first row is for 'brackets' (if no brackets needed, the height of this row\n # is zero) second row is for main content. This second row is divided into\n # three axes:\n # first ax is for the categories defined by `cluster_method`\n # second ax is for the heatmap\n # fourth ax is for colorbar\n\n kwargs.setdefault(\"figsize\", (10, 10))\n kwargs.setdefault(\"colorbar_width\", 0.2)\n colorbar_width = kwargs.get(\"colorbar_width\")\n figsize = kwargs.get(\"figsize\")\n\n cluster_block_width = kwargs.setdefault(\"cluster_block_width\", 0.2) if order_cluster else 0\n if figsize is None:\n height = 6\n if show_labels:\n heatmap_width = len(gene_names) * 0.3\n else:\n heatmap_width = 8\n width = heatmap_width + cluster_block_width\n else:\n width, height = figsize\n heatmap_width = width - cluster_block_width\n\n if gene_group_positions is not None and len(gene_group_positions) > 0:\n # add some space in case 'brackets' want to be plotted on top of the image\n height_ratios = [0.15, height]\n else:\n height_ratios = [0, height]\n\n width_ratios = [\n cluster_block_width,\n heatmap_width,\n colorbar_width,\n ]\n\n fig = plt.figure(figsize=(width, height))\n\n axs = gridspec.GridSpec(\n nrows=2,\n ncols=3,\n width_ratios=width_ratios,\n wspace=0.15 / width,\n hspace=0.13 / height,\n height_ratios=height_ratios,\n )\n\n heatmap_ax = fig.add_subplot(axs[1, 1])\n\n width, height = fig.get_size_inches()\n max_cbar_height = 4.0\n if height > max_cbar_height:\n # to make the colorbar shorter, the\n # ax is split and the lower portion is used.\n axs2 = gridspec.GridSpecFromSubplotSpec(2, 1, subplot_spec=axs[1, 2],\n height_ratios=[height - max_cbar_height, max_cbar_height],\n )\n heatmap_cbar_ax = fig.add_subplot(axs2[1])\n else:\n heatmap_cbar_ax = fig.add_subplot(axs[1, 2])\n\n heatmap(df=draw_df, ax=heatmap_ax,\n norm=Normalize(vmin=None, vmax=None), plot_colorbar=True, colorbar_ax=heatmap_cbar_ax,\n show_labels=True, plot_hline=True)\n\n if order_cluster:\n _plot_categories_as_colorblocks(\n fig.add_subplot(axs[1, 0]), draw_df, colors=cluster_colors_array, orientation='left'\n )\n\n # plot cluster legends on top of heatmap_ax (if given)\n if gene_group_positions is not None and len(gene_group_positions) > 0:\n _plot_gene_groups_brackets(\n fig.add_subplot(axs[0, 1], sharex=heatmap_ax),\n group_positions=gene_group_positions,\n group_labels=gene_group_labels,\n rotation=None,\n left_adjustment=-0.3,\n right_adjustment=0.3,\n )\n\n # plt.savefig()\n"},{"alpha_fraction":0.5822505354881287,"alphanum_fraction":0.5927923321723938,"avg_line_length":32.99166488647461,"blob_id":"a8e3e35c6156f10d95e13736868dfb21b8d5ee67","content_id":"3526ea0c74b7e911d1ee4dc7c4cc474d0dd5b8eb","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":4087,"license_type":"permissive","max_line_length":117,"num_lines":120,"path":"/stereo/tools/cluster.py","repo_name":"leying95/stereopy","src_encoding":"UTF-8","text":"#!/usr/bin/env python3\n# coding: utf-8\n\"\"\"\n@author: Ping Qiu qiuping1@genomics.cn\n@last modified by: Ping Qiu\n@file:cluster.py\n@time:2021/03/19\n\"\"\"\nimport leidenalg as la\nfrom sklearn.decomposition import PCA\nfrom scipy.sparse import coo_matrix\nfrom sklearn.neighbors import NearestNeighbors\nimport igraph as ig\nimport numpy as np\nfrom umap.umap_ import fuzzy_simplicial_set\n\n\nclass Neighbors(object):\n def __init__(self, x, n_neighbors):\n self.x = x\n self.n_neighbors = n_neighbors\n\n def find_n_neighbors(self):\n nbrs = NearestNeighbors(n_neighbors=self.n_neighbors + 1, algorithm='ball_tree').fit(self.x)\n dists, indices = nbrs.kneighbors(self.x)\n nn_idx = indices[:, 1:]\n nn_dist = dists[:, 1:]\n return nn_idx, nn_dist\n\n def get_igraph_from_knn(self, nn_idx, nn_dist):\n j = nn_idx.ravel().astype(int)\n dist = nn_dist.ravel()\n i = np.repeat(np.arange(nn_idx.shape[0]), self.n_neighbors)\n\n vertex = list(range(nn_dist.shape[0]))\n edges = list(tuple(zip(i, j)))\n G = ig.Graph()\n G.add_vertices(vertex)\n G.add_edges(edges)\n G.es['weight'] = dist\n return G\n\n def get_parse_distances(self, nn_idx, nn_dist):\n n_obs = self.x.shape[0]\n rows = np.zeros((n_obs * self.n_neighbors), dtype=np.int64)\n cols = np.zeros((n_obs * self.n_neighbors), dtype=np.int64)\n vals = np.zeros((n_obs * self.n_neighbors), dtype=np.float64)\n\n for i in range(nn_idx.shape[0]):\n for j in range(self.n_neighbors):\n if nn_idx[i, j] == -1:\n continue # We didn't get the full knn for i\n if nn_idx[i, j] == i:\n val = 0.0\n else:\n val = nn_dist[i, j]\n\n rows[i * self.n_neighbors + j] = i\n cols[i * self.n_neighbors + j] = nn_idx[i, j]\n vals[i * self.n_neighbors + j] = val\n\n distances = coo_matrix((vals, (rows, cols)), shape=(n_obs, n_obs))\n distances.eliminate_zeros()\n return distances.tocsr()\n\n def get_connectivities(self, nn_idx, nn_dist):\n n_obs = self.x.shape[0]\n x = coo_matrix(([], ([], [])), shape=(n_obs, 1))\n connectivities = fuzzy_simplicial_set(x, self.n_neighbors, None, None, knn_indices=nn_idx, knn_dists=nn_dist,\n set_op_mix_ratio=1.0, local_connectivity=1.0)\n if isinstance(connectivities, tuple):\n connectivities = connectivities[0]\n return connectivities.tocsr()\n\n\ndef run_neighbors(x, neighbors=30):\n neighbor = Neighbors(x, neighbors)\n nn_idx, nn_dist = neighbor.find_n_neighbors()\n return neighbor, nn_idx, nn_dist\n\n\ndef run_louvain(x, neighbor, nn_idx, nn_dist):\n g = neighbor.get_igraph_from_knn(nn_idx, nn_dist)\n louvain_partition = g.community_multilevel(weights=g.es['weight'], return_levels=False)\n clusters = np.arange(x.shape[0])\n for i in range(len(louvain_partition)):\n clusters[louvain_partition[i]] = str(i)\n return clusters\n\n\ndef run_knn_leiden(x, neighbor, nn_idx, nn_dist, diff=1):\n g = neighbor.get_igraph_from_knn(nn_idx, nn_dist)\n optimiser = la.Optimiser()\n leiden_partition = la.ModularityVertexPartition(g, weights=g.es['weight'])\n while diff > 0:\n diff = optimiser.optimise_partition(leiden_partition, n_iterations=10)\n clusters = np.arange(x.shape[0])\n for i in range(len(leiden_partition)):\n clusters[leiden_partition[i]] = str(i)\n return clusters\n\n\ndef run_cluster(x, method='leiden', do_pca=True, n_pcs=30):\n \"\"\"\n :param x: np.array, shape: (m, n)，m个bin， n为embedding\n :param method:\n :param do_pca:\n :param n_pcs:\n :return:\n \"\"\"\n if do_pca:\n pca_obj = PCA(n_components=n_pcs)\n x = pca_obj.fit_transform(x)\n\n neighbor, nn_idx, nn_dist = run_neighbors(x)\n if method == 'leiden':\n cluster = run_knn_leiden(x, neighbor, nn_idx, nn_dist)\n else:\n cluster = run_louvain(x, neighbor, nn_idx, nn_dist)\n return cluster\n"},{"alpha_fraction":0.5596755146980286,"alphanum_fraction":0.5709463357925415,"avg_line_length":36.02822494506836,"blob_id":"e7cc0ef7656786a8185b9d2de04832ad295a73f2","content_id":"f68ab32909c095d79527096c45e06fecb5e95b9b","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":18936,"license_type":"permissive","max_line_length":158,"num_lines":496,"path":"/stereo/plots/plots.py","repo_name":"leying95/stereopy","src_encoding":"UTF-8","text":"#!/usr/bin/env python3\n# coding: utf-8\n\"\"\"\n@author: Ping Qiu qiuping1@genomics.cn\n@last modified by: Ping Qiu\n@file:plots.py\n@time:2021/03/31\n\"\"\"\nfrom matplotlib.cm import get_cmap\nimport matplotlib.pyplot as plt\nfrom matplotlib.colors import ListedColormap, to_hex, Normalize\nfrom matplotlib import gridspec\nfrom ._plot_basic.get_stereo_data import get_cluster_res, get_reduce_x, get_position_array, get_degs_res\nimport numpy as np\nimport pandas as pd\nfrom anndata import AnnData\nfrom ._plot_basic.scatter_plt import scatter\nimport seaborn\nfrom typing import Optional, Sequence, Union\nfrom matplotlib.axes import Axes\nfrom ._plot_basic.heatmap_plt import heatmap, plot_categories_as_colorblocks, plot_gene_groups_brackets\nfrom ..log_manager import logger\nfrom scipy.sparse import issparse\n\n\ndef plot_spatial_cluster(\n adata: AnnData,\n obs_key: list = [\"phenograph\"],\n pos_key: str = \"spatial\",\n plot_cluster: list = None,\n bad_color: str = \"lightgrey\",\n ncols: int = 2,\n dot_size: int = None,\n color_list=['violet', 'turquoise', 'tomato', 'teal','tan', 'silver', 'sienna', 'red', 'purple', 'plum', 'pink',\n 'orchid', 'orangered', 'orange', 'olive', 'navy', 'maroon', 'magenta', 'lime',\n 'lightgreen', 'lightblue', 'lavender', 'khaki', 'indigo', 'grey', 'green', 'gold', 'fuchsia',\n 'darkgreen', 'darkblue', 'cyan', 'crimson', 'coral', 'chocolate', 'chartreuse', 'brown', 'blue', 'black',\n 'beige', 'azure', 'aquamarine', 'aqua',\n ],\n): # scatter plot, 聚类后表达矩阵空间分布\n \"\"\"\n Plot spatial distribution of specified obs data.\n ============ Arguments ============\n :param adata: AnnData object.\n :param obs_key: specified obs cluster key list, for example: [\"phenograph\"].\n :param pos_key: the coordinates of data points for scatter plots. the data points are stored in adata.obsm[pos_key]. choice: \"spatial\", \"X_umap\", \"X_pca\".\n :param plot_cluster: the name list of clusters to show.\n :param bad_color: the name list of clusters to show.\n :param ncols: numbr of plot columns.\n :param dot_size: marker size.\n :param color_list: whether to invert y-axis.\n ============ Return ============\n None.\n ============ Example ============\n plot_spatial_cluster(adata = adata)\n \"\"\"\n # sc.pl.embedding(adata, basis=\"spatial\", color=[\"total_counts\", \"n_genes_by_counts\"],size=30)\n\n if dot_size is None:\n dot_size = 120000 / adata.shape[0]\n\n ncols = min(ncols, len(obs_key))\n nrows = np.ceil(len(obs_key) / ncols).astype(int)\n # each panel will have the size of rcParams['figure.figsize']\n fig = plt.figure(figsize=(ncols * 10, nrows * 8))\n left = 0.2 / ncols\n bottom = 0.13 / nrows\n axs = gridspec.GridSpec(\n nrows=nrows,\n ncols=ncols,\n left=left,\n right=1 - (ncols - 1) * left - 0.01 / ncols,\n bottom=bottom,\n top=1 - (nrows - 1) * bottom - 0.1 / nrows,\n # hspace=hspace,\n # wspace=wspace,\n )\n\n if color_list is None:\n cmap = get_cmap()\n else:\n cmap = ListedColormap(color_list)\n cmap.set_bad(bad_color)\n # 把特定值改为 np.nan 之后，可以利用 cmap.set_bad(\"white\") 来遮盖掉这部分数据\n\n for i, key in enumerate(obs_key):\n # color_data = adata.obs_vector(key) # TODO replace by get_cluster_res\n color_data = get_cluster_res(adata, data_key=key)\n pc_logic = False\n\n # color_data = np.asarray(color_data_raw, dtype=float)\n order = np.argsort(~pd.isnull(color_data), kind=\"stable\")\n# spatial_data = np.array(adata.obsm[pos_key])[:, 0: 2]\n spatial_data = get_reduce_x(data=adata, data_key=pos_key)[:, 0:2] if pos_key != 'spatial' \\\n else get_position_array(adata, pos_key)\n color_data = color_data[order]\n spatial_data = spatial_data[order, :]\n\n color_dict = {}\n has_na = False\n if pd.api.types.is_categorical_dtype(color_data):\n pc_logic = True\n if plot_cluster is None:\n plot_cluster = list(color_data.categories)\n if pc_logic:\n cluster_n = len(np.unique(color_data))\n if len(color_list) < cluster_n:\n color_list = color_list * cluster_n\n cmap = ListedColormap(color_list)\n cmap.set_bad(bad_color)\n if len(color_data.categories) > len(plot_cluster):\n color_data = color_data.replace(color_data.categories.difference(plot_cluster), np.nan)\n has_na = True\n color_dict = {str(k): to_hex(v) for k, v in enumerate(color_list)}\n print(color_dict)\n color_data = color_data.map(color_dict)\n if pd.api.types.is_categorical_dtype(color_data):\n color_data = pd.Categorical(color_data)\n if has_na:\n color_data = color_data.add_categories([to_hex(bad_color)])\n color_data = color_data.fillna(to_hex(bad_color))\n # color_dict[\"NA\"]\n\n # color_data 是图像中各个点的值，也对应了每个点的颜色。data_points则对应了各个点的坐标\n ax = fig.add_subplot(axs[i]) # ax = plt.subplot(axs[i]) || ax = fig.add_subplot(axs[1, 1]))\n ax.set_title(key)\n ax.set_yticks([])\n ax.set_xticks([])\n ax.set_xlabel(\"spatial1\")\n ax.set_ylabel(\"spatial2\")\n pathcollection = scatter(\n spatial_data[:, 0],\n spatial_data[:, 1],\n ax=ax,\n marker=\".\",\n dot_colors=color_data,\n dot_size=dot_size\n )\n if pc_logic:\n box = ax.get_position()\n ax.set_position([box.x0, box.y0, box.width * 0.91, box.height])\n # -------------modified by qiuping1@genomics.cn-------------\n # valid_cate = color_data.categories\n # cat_num = len(adata.obs_vector(key).categories)\n # for label in adata.obs_vector(key).categories:\n categories = get_cluster_res(adata, data_key=key).categories\n cat_num = len(categories)\n for label in categories:\n # --------modified end------------------\n ax.scatter([], [], c=color_dict[label], label=label)\n ax.legend(\n frameon=False,\n loc='center left',\n bbox_to_anchor=(1, 0.5),\n ncol=(1 if cat_num <= 14 else 2 if cat_num <= 30 else 3),\n # fontsize=legend_fontsize,\n )\n else:\n plt.colorbar(pathcollection, ax=ax, pad=0.01, fraction=0.08, aspect=30)\n ax.autoscale_view()\n\n\ndef plot_violin_distribution(adata): # 小提琴统计图\n \"\"\"\n 绘制数据的分布小提琴图。\n ============ Arguments ============\n :param adata: AnnData object.\n ============ Return ============\n None\n \"\"\"\n _, axs = plt.subplots(1, 3, figsize=(15, 4))\n seaborn.violinplot(y=adata.obs['total_counts'], ax=axs[0])\n seaborn.violinplot(y=adata.obs['n_genes_by_counts'], ax=axs[1])\n seaborn.violinplot(y=adata.obs['pct_counts_mt'], ax=axs[2])\n\n\ndef plot_degs(\n adata: AnnData,\n groups: Union[str, Sequence[str]] = 'all',\n n_genes: int = 20,\n key: Optional[str] = 'find_marker',\n fontsize: int = 8,\n ncols: int = 4,\n sharey: bool = True,\n ax: Optional[Axes] = None,\n **kwds,\n): # scatter plot, 差异基因显著性图，类碎石图\n \"\"\"\n Copied from scanpy and modified.\n \"\"\"\n\n # 调整图像 panel/grid 相关参数\n if 'n_panels_per_row' in kwds:\n n_panels_per_row = kwds['n_panels_per_row']\n else:\n n_panels_per_row = ncols\n # group_names = adata.uns[key]['names'].dtype.names if groups is None else groups\n if groups == 'all':\n group_names = list(adata.uns[key].keys())\n else:\n group_names = [groups] if isinstance(groups, str) else groups\n # one panel for each group\n # set up the figure\n n_panels_x = min(n_panels_per_row, len(group_names))\n n_panels_y = np.ceil(len(group_names) / n_panels_x).astype(int)\n # 初始化图像\n width = 10\n height = 10\n fig = plt.figure(\n figsize=(\n n_panels_x * width, # rcParams['figure.figsize'][0],\n n_panels_y * height, # rcParams['figure.figsize'][1],\n )\n )\n gs = gridspec.GridSpec(nrows=n_panels_y, ncols=n_panels_x, wspace=0.22, hspace=0.3)\n\n ax0 = None\n ymin = np.Inf\n ymax = -np.Inf\n for count, group_name in enumerate(group_names):\n result = get_degs_res(adata, data_key=key, group_key=group_name, top_k=n_genes)\n gene_names = result.genes.values\n scores = result.scores.values\n # Setting up axis, calculating y bounds\n if sharey:\n ymin = min(ymin, np.min(scores))\n ymax = max(ymax, np.max(scores))\n\n if ax0 is None:\n ax = fig.add_subplot(gs[count])\n ax0 = ax\n else:\n ax = fig.add_subplot(gs[count], sharey=ax0)\n else:\n ymin = np.min(scores)\n ymax = np.max(scores)\n ymax += 0.3 * (ymax - ymin)\n\n ax = fig.add_subplot(gs[count])\n ax.set_ylim(ymin, ymax)\n\n ax.set_xlim(-0.9, n_genes - 0.1)\n\n # Making labels\n for ig, gene_name in enumerate(gene_names):\n ax.text(\n ig,\n scores[ig],\n gene_name,\n rotation='vertical',\n verticalalignment='bottom',\n horizontalalignment='center',\n fontsize=fontsize,\n )\n\n ax.set_title(group_name)\n if count >= n_panels_x * (n_panels_y - 1):\n ax.set_xlabel('ranking')\n\n # print the 'score' label only on the first panel per row.\n if count % n_panels_x == 0:\n ax.set_ylabel('score')\n\n if sharey is True:\n ymax += 0.3 * (ymax - ymin)\n ax.set_ylim(ymin, ymax)\n\n\ndef plot_spatial_distribution(\n adata: AnnData,\n obs_key: list = [\"total_counts\", \"n_genes_by_counts\"],\n ncols=2,\n dot_size=None,\n color_list=None,\n invert_y=False\n): # scatter plot, 表达矩阵空间分布\n \"\"\"\n Plot spatial distribution of specified obs data.\n ============ Arguments ============\n :param adata: AnnData object.\n :param obs_key: specified obs key list, for example: [\"total_counts\", \"n_genes_by_counts\"]\n :param ncols: numbr of plot columns.\n :param dot_size: marker size.\n :param color_list: Color list.\n :param invert_y: whether to invert y-axis.\n ============ Return ============\n None\n ============ Example ============\n plot_spatial_distribution(adata=adata)\n \"\"\"\n # sc.pl.embedding(adata, basis=\"spatial\", color=[\"total_counts\", \"n_genes_by_counts\"],size=30)\n\n if dot_size is None:\n dot_size = 120000 / adata.shape[0]\n\n ncols = min(ncols, len(obs_key))\n nrows = np.ceil(len(obs_key) / ncols).astype(int)\n # each panel will have the size of rcParams['figure.figsize']\n fig = plt.figure(figsize=(ncols * 10, nrows * 8))\n left = 0.2 / ncols\n bottom = 0.13 / nrows\n axs = gridspec.GridSpec(\n nrows=nrows,\n ncols=ncols,\n left=left,\n right=1 - (ncols - 1) * left - 0.01 / ncols,\n bottom=bottom,\n top=1 - (nrows - 1) * bottom - 0.1 / nrows,\n # hspace=hspace,\n # wspace=wspace,\n )\n\n if color_list is None:\n cmap = get_cmap()\n else:\n cmap = ListedColormap(color_list)\n # 把特定值改为 np.nan 之后，可以利用 cmap.set_bad(\"white\") 来遮盖掉这部分数据\n\n # 散点图上每个点的坐标数据来自于 adata 的 obsm[\"spatial\"]，每个点的颜色（数值）数据来自于 adata 的 obs_vector()\n for i, key in enumerate(obs_key):\n # color_data = np.asarray(adata.obs_vector(key), dtype=float)\n color_data = adata.obs_vector(key)\n order = np.argsort(~pd.isnull(color_data), kind=\"stable\")\n spatial_data = np.array(adata.obsm[\"spatial\"])[:, 0: 2]\n color_data = color_data[order]\n spatial_data = spatial_data[order, :]\n\n # color_data 是图像中各个点的值，也对应了每个点的颜色。data_points则对应了各个点的坐标\n ax = fig.add_subplot(axs[i]) # ax = plt.subplot(axs[i]) || ax = fig.add_subplot(axs[1, 1]))\n ax.set_title(key)\n ax.set_yticks([])\n ax.set_xticks([])\n ax.set_xlabel(\"spatial1\")\n ax.set_ylabel(\"spatial2\")\n pathcollection = scatter(\n spatial_data[:, 0],\n spatial_data[:, 1],\n ax=ax,\n marker=\".\",\n dot_colors=color_data,\n dot_size=dot_size,\n cmap=cmap,\n )\n plt.colorbar(\n pathcollection,\n ax=ax,\n pad=0.01,\n fraction=0.08,\n aspect=30,\n )\n ax.autoscale_view()\n if invert_y:\n ax.invert_yaxis()\n\n\ndef plot_heatmap_maker_genes(\n adata: AnnData = None,\n cluster_method=\"phenograph\",\n marker_uns_key=None,\n num_show_gene=8,\n show_labels=True,\n order_cluster=True,\n marker_clusters=None,\n cluster_colors_array=None,\n **kwargs\n): # heatmap, 差异基因热图\n \"\"\"\n 绘制 Marker gene 的热图。热图中每一行代表一个 bin 的所有基因的表达量，所有的 bin 会根据所属的 cluster 进行聚集， cluster 具体展示在热图的左侧，用颜色区分。\n ============ Arguments ============\n :param adata: AnnData object.\n :param cluster_method: method used in clustering. for example: phenograph, leiden\n :param marker_uns_key: the key of adata.uns, the default value is \"marker_genes\"\n :param num_show_gene: number of genes to show in each cluster.\n :param show_labels: show gene name on axis.\n :param order_cluster: reorder the cluster list in plot (y axis).\n :param marker_clusters: the list of clusters to show on the heatmap.\n :param cluster_colors_array: the list of colors in the color block on the left of heatmap.\n ============ Return ============\n\n ============ Example ============\n plot_heatmap_maker_genes(adata=adata, marker_uns_key = \"rank_genes_groups\", figsize = (20, 10))\n \"\"\"\n if marker_uns_key is None:\n marker_uns_key = 'marker_genes' # \"rank_genes_groups\" in original scanpy pipeline\n marker_res = adata.uns[marker_uns_key]\n default_cluster = [i for i in marker_res.keys()]\n if marker_clusters is None:\n marker_clusters = default_cluster\n if not set(marker_clusters).issubset(set(default_cluster)):\n marker_clusters = default_cluster\n\n gene_names_dict = {} # dict in which each cluster is the keyand the num_show_gene are the values\n\n for cluster in marker_clusters:\n top_marker = marker_res[cluster].top_k_marker(top_k_genes=num_show_gene, sort_key='scores')\n genes_array = top_marker['genes'].values\n if len(genes_array) == 0:\n logger.warning(\"Cluster {} has no genes.\".format(cluster))\n continue\n gene_names_dict[cluster] = genes_array\n gene_names = []\n gene_group_labels = []\n gene_group_positions = []\n start = 0\n for label, gene_list in gene_names_dict.items():\n if isinstance(gene_list, str):\n gene_list = [gene_list]\n gene_names.extend(list(gene_list))\n gene_group_labels.append(label)\n gene_group_positions.append((start, start + len(gene_list) - 1))\n start += len(gene_list)\n\n # 此处获取所有绘图所需的数据 （表达量矩阵）\n uniq_gene_names = np.unique(gene_names)\n exp_matrix = adata.X.toarray() if issparse(adata.X) else adata.X\n draw_df = pd.DataFrame(exp_matrix[:, adata.var.index.get_indexer(uniq_gene_names)],\n columns=uniq_gene_names, index=adata.obs_names)\n # add obs values\n cluster_data = adata.uns[cluster_method].cluster.set_index('bins')\n draw_df = pd.concat([draw_df, cluster_data], axis=1)\n draw_df = draw_df[gene_names].set_index(draw_df['cluster'].astype('category'))\n if order_cluster:\n draw_df = draw_df.sort_index()\n kwargs.setdefault(\"figsize\", (10, 10))\n kwargs.setdefault(\"colorbar_width\", 0.2)\n colorbar_width = kwargs.get(\"colorbar_width\")\n figsize = kwargs.get(\"figsize\")\n\n cluster_block_width = kwargs.setdefault(\"cluster_block_width\", 0.2) if order_cluster else 0\n if figsize is None:\n height = 6\n if show_labels:\n heatmap_width = len(gene_names) * 0.3\n else:\n heatmap_width = 8\n width = heatmap_width + cluster_block_width\n else:\n width, height = figsize\n heatmap_width = width - cluster_block_width\n\n if gene_group_positions is not None and len(gene_group_positions) > 0:\n # add some space in case 'brackets' want to be plotted on top of the image\n height_ratios = [0.15, height]\n else:\n height_ratios = [0, height]\n\n width_ratios = [\n cluster_block_width,\n heatmap_width,\n colorbar_width,\n ]\n\n fig = plt.figure(figsize=(width, height))\n\n axs = gridspec.GridSpec(\n nrows=2,\n ncols=3,\n width_ratios=width_ratios,\n wspace=0.15 / width,\n hspace=0.13 / height,\n height_ratios=height_ratios,\n )\n\n heatmap_ax = fig.add_subplot(axs[1, 1])\n\n width, height = fig.get_size_inches()\n max_cbar_height = 4.0\n if height > max_cbar_height:\n # to make the colorbar shorter, the\n # ax is split and the lower portion is used.\n axs2 = gridspec.GridSpecFromSubplotSpec(2, 1, subplot_spec=axs[1, 2],\n height_ratios=[height - max_cbar_height, max_cbar_height],\n )\n heatmap_cbar_ax = fig.add_subplot(axs2[1])\n else:\n heatmap_cbar_ax = fig.add_subplot(axs[1, 2])\n\n heatmap(df=draw_df, ax=heatmap_ax,\n norm=Normalize(vmin=None, vmax=None), plot_colorbar=True, colorbar_ax=heatmap_cbar_ax,\n show_labels=True, plot_hline=True)\n\n if order_cluster:\n plot_categories_as_colorblocks(\n fig.add_subplot(axs[1, 0]), draw_df, colors=cluster_colors_array, orientation='left'\n )\n\n # plot cluster legends on top of heatmap_ax (if given)\n if gene_group_positions is not None and len(gene_group_positions) > 0:\n plot_gene_groups_brackets(\n fig.add_subplot(axs[0, 1], sharex=heatmap_ax),\n group_positions=gene_group_positions,\n group_labels=gene_group_labels,\n rotation=None,\n left_adjustment=-0.3,\n right_adjustment=0.3,\n )\n"},{"alpha_fraction":0.6450777053833008,"alphanum_fraction":0.6709844470024109,"avg_line_length":19.3157901763916,"blob_id":"e0b8821e51448972842b0596d7ba29c224772cd5","content_id":"6e56426ee185d43f05f283d62f55808b97650c56","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":386,"license_type":"permissive","max_line_length":53,"num_lines":19,"path":"/stereo/utils/__init__.py","repo_name":"leying95/stereopy","src_encoding":"UTF-8","text":"#!/usr/bin/env python3\n# coding: utf-8\n\"\"\"\n@author: Ping Qiu qiuping1@genomics.cn\n@last modified by: Ping Qiu\n@file:__init__.py.py\n@time:2021/03/05\n\"\"\"\nimport shutil\nimport os\nfrom .correlation import pearson_corr, spearmanr_corr\nfrom .data_helper import select_group\n\n\ndef remove_file(path):\n if os.path.isfile(path):\n os.remove(path)\n if os.path.isdir(path):\n shutil.rmtree(path)\n"},{"alpha_fraction":0.6289620995521545,"alphanum_fraction":0.6656308174133301,"avg_line_length":31.836734771728516,"blob_id":"929008472630fdf635cba821106fb912cf41f0c5","content_id":"d99b946e6893eb24287dce6f23965fb054385454","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1609,"license_type":"permissive","max_line_length":112,"num_lines":49,"path":"/stereo/utils/correlation.py","repo_name":"leying95/stereopy","src_encoding":"UTF-8","text":"#!/usr/bin/env python3\n# coding: utf-8\n\"\"\"\n@author: Ping Qiu qiuping1@genomics.cn\n@last modified by: Ping Qiu\n@file:correlation.py\n@time:2021/03/11\n\"\"\"\nimport numpy as np\nimport pandas as pd\nfrom scipy import stats\n\n\ndef pearson(arr1, arr2):\n \"\"\"\n calculate pearson correlation between two numpy arrays.\n :param arr1: one array, the feature is a column. the shape is `m * n`\n :param arr2: the other array, the feature is a column. the shape is `m * k`\n :return: a pearson score np.array , the shape is `k * n`\n \"\"\"\n assert arr1.shape[0] == arr2.shape[0]\n n = arr1.shape[0]\n sums = np.multiply.outer(arr2.sum(0), arr1.sum(0))\n stds = np.multiply.outer(arr2.std(0), arr1.std(0))\n return (arr2.T.dot(arr1) - sums / n) / stds / n\n\n\ndef pearson_corr(df1, df2):\n \"\"\"\n calculate pearson correlation between two dataframes.\n :param df1: one dataframe\n :param df2: the other dataframe\n :return: a pearson score dataframe, the index is the columns of `df1`, the columns is the columns of `df2`\n \"\"\"\n v1, v2 = df1.values, df2.values\n corr_matrix = pearson(v1, v2)\n return pd.DataFrame(corr_matrix, df2.columns, df1.columns)\n\n\ndef spearmanr_corr(df1, df2):\n \"\"\"\n calculate pearson correlation between two dataframes.\n :param df1: one dataframe\n :param df2: the other dataframe\n :return: a spearmanr score dataframe, the index is the columns of `df1`, the columns is the columns of `df2`\n \"\"\"\n score, pvalue = stats.spearmanr(df1.values, df2.values)\n score = score[df1.shape[1]:, 0:df1.shape[1]]\n return pd.DataFrame(score, df2.columns, df1.columns)\n"},{"alpha_fraction":0.5926466584205627,"alphanum_fraction":0.5964400172233582,"avg_line_length":35.07368469238281,"blob_id":"88d22d27b7f2d3e25e5c1a50cc04b09fd00b9a0c","content_id":"dd127ef9b878183a451a018bf664e3130c5144eb","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":3427,"license_type":"permissive","max_line_length":118,"num_lines":95,"path":"/stereo/core/stereo_result.py","repo_name":"leying95/stereopy","src_encoding":"UTF-8","text":"#!/usr/bin/env python3\n# coding: utf-8\n\"\"\"\n@author: Ping Qiu qiuping1@genomics.cn\n@last modified by: Ping Qiu\n@file:stereo_result.py\n@time:2021/03/18\n\"\"\"\nfrom typing import Optional\nimport numpy as np\nimport pandas as pd\nfrom ..log_manager import logger\n\n\nclass StereoResult(object):\n def __init__(self, name: str = 'stereo', param: Optional[dict] = None):\n self.name = name\n self.params = {} if param is None else param\n\n def update_params(self, v):\n self.params = v\n\n def __str__(self):\n class_info = f'{self.__class__.__name__} of {self.name}. \\n'\n class_info += f' params: {self.params}\\n'\n return class_info\n\n def __repr__(self):\n return self.__str__()\n\n\nclass DimReduceResult(StereoResult):\n def __init__(self, name: str = 'dim_reduce', param: Optional[dict] = None, x_reduce: Optional[np.ndarray] = None,\n variance_pca: Optional[np.ndarray] = None, variance_ratio: Optional[np.ndarray] = None,\n pcs: Optional[np.ndarray] = None):\n super(DimReduceResult, self).__init__(name, param)\n self.x_reduce = x_reduce\n self.variance_pca = variance_pca\n self.variance_ratio = variance_ratio\n self.pcs = pcs\n\n\nclass FindMarkerResult(StereoResult):\n def __init__(self, name: str = 'find_marker', param: Optional[dict] = None,\n degs_data: Optional[pd.DataFrame] = None):\n super(FindMarkerResult, self).__init__(name, param)\n self.degs_data = degs_data\n\n def __str__(self):\n info = super(FindMarkerResult, self).__str__()\n if self.degs_data is not None:\n info += f' result: a DataFrame which has `genes`,`pvalues`,`pvalues_adj`, `log2fc`, `score` columns.\\n'\n info += f' the shape is: {self.degs_data.shape}'\n return info\n\n def top_k_marker(self, top_k_genes=10, sort_key='pvalues', ascend=False):\n \"\"\"\n obtain the first k significantly different genes\n :param top_k_genes: the number of top k\n :param sort_key: sort by the column\n :param ascend: the ascend order of sorting.\n :return:\n \"\"\"\n if self.degs_data is not None:\n top_k_data = self.degs_data.sort_values(by=sort_key, ascending=ascend).head(top_k_genes)\n return top_k_data\n else:\n logger.warning('the result of degs is None, return None.')\n return None\n\n\nclass CellTypeResult(StereoResult):\n def __init__(self, name='cell_type_anno', param=None, anno_data=None):\n super(CellTypeResult, self).__init__(name=name, param=param)\n self.anno_data = anno_data\n\n def __str__(self):\n info = super(CellTypeResult, self).__str__()\n if self.anno_data is not None:\n info += f' result: a DataFrame which has `cells`,`cell type`,`corr_score` columns.\\n'\n info += f' the shape is: {self.anno_data.shape}'\n return info\n\n\nclass ClusterResult(StereoResult):\n def __init__(self, name='cluster', param=None, cluster_info=None):\n super(ClusterResult, self).__init__(name=name, param=param)\n self.cluster = cluster_info\n\n def __str__(self):\n info = super(ClusterResult, self).__str__()\n if self.cluster is not None:\n info += f' result: a DataFrame which has `cells`,`cluster` columns.\\n'\n info += f' the shape is: {self.cluster.shape}'\n return info\n"},{"alpha_fraction":0.5367646813392639,"alphanum_fraction":0.6102941036224365,"avg_line_length":16,"blob_id":"91821cce15c5c57d0d9f7879ebe521c065656519","content_id":"726bfa3d8ddd4c38dd355f36eb882616ac52e353","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":136,"license_type":"permissive","max_line_length":25,"num_lines":8,"path":"/stereo/core/__init__.py","repo_name":"leying95/stereopy","src_encoding":"UTF-8","text":"#!/usr/bin/env python3\n# coding: utf-8\n\"\"\"\n@author: Ping Qiu qiuping1@genomics.cn\n@last modified by: Ping Qiu\n@file:__init__.py.py\n@time:2021/03/17\n\"\"\"\n"},{"alpha_fraction":0.5546501278877258,"alphanum_fraction":0.5627103447914124,"avg_line_length":31.63005828857422,"blob_id":"c3432564975ba70a1548330bb225b99d38d4b4bf","content_id":"050413ffad7b852cc1e8d0feae37c28313c3be0a","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":11290,"license_type":"permissive","max_line_length":101,"num_lines":346,"path":"/stereo/plots/_plot_basic/heatmap_plt.py","repo_name":"leying95/stereopy","src_encoding":"UTF-8","text":"#!/usr/bin/env python3\n# coding: utf-8\n\"\"\"\n@author: Shixu He heshixu@genomics.cn\n@last modified by: Shixu He\n@file:heatmap_plt.py\n@time:2021/03/15\n\"\"\"\n\nfrom matplotlib.cm import get_cmap\nfrom matplotlib.axes import Axes\nimport matplotlib.pyplot as plt\nfrom matplotlib.colors import Normalize\nfrom matplotlib import gridspec\n\nfrom anndata import AnnData\nimport numpy as np\nimport pandas as pd\n\nfrom typing import List, Iterable, Sequence, Optional, Tuple\nfrom typing_extensions import Literal\n\nfrom ...log_manager import logger\n\n\ndef heatmap(df: pd.DataFrame = None, ax: Axes = None, cmap=None, norm=None, plot_colorbar=False,\n colorbar_ax: Axes = None, show_labels=True, plot_hline=False, **kwargs):\n \"\"\"\n :param df:\n :param ax:\n :param cmap:\n :param norm:\n :param plot_colorbar:\n :param colorbar_ax:\n :param show_labels:\n :param plot_hline:\n :param kwargs:\n :return:\n \"\"\"\n\n if norm == None:\n norm = Normalize(vmin=None, vmax=None)\n if (plot_colorbar and colorbar_ax == None):\n logger.warning(\"Colorbar ax is not provided.\")\n plot_colorbar = False\n\n kwargs.setdefault('interpolation', 'nearest')\n\n im = ax.imshow(df.values, aspect='auto', norm=norm, **kwargs)\n\n ax.set_ylim(df.shape[0] - 0.5, -0.5)\n ax.set_xlim(-0.5, df.shape[1] - 0.5)\n ax.tick_params(axis='y', left=False, labelleft=False)\n ax.set_ylabel('')\n ax.grid(False)\n\n if show_labels:\n ax.tick_params(axis='x', labelsize='small')\n ax.set_xticks(np.arange(df.shape[1]))\n ax.set_xticklabels(list(df.columns), rotation=90)\n else:\n ax.tick_params(axis='x', labelbottom=False, bottom=False)\n\n if plot_colorbar:\n plt.colorbar(im, cax=colorbar_ax)\n\n if plot_hline:\n line_coord = (\n np.cumsum(df.index.value_counts(sort=False))[:-1] - 0.5\n )\n ax.hlines(\n line_coord,\n -0.5,\n df.shape[1] - 0.5,\n lw=1,\n color='black',\n zorder=10,\n clip_on=False,\n )\n\n\ndef plot_categories_as_colorblocks(\n groupby_ax: Axes,\n obs_tidy: pd.DataFrame,\n colors=None,\n orientation: Literal['top', 'bottom', 'left', 'right'] = 'left',\n cmap_name: str = 'tab20',\n):\n \"\"\"from scanpy\"\"\"\n\n groupby = obs_tidy.index.name\n from matplotlib.colors import ListedColormap, BoundaryNorm\n\n if colors is None:\n groupby_cmap = plt.get_cmap(cmap_name)\n else:\n groupby_cmap = ListedColormap(colors, groupby + '_cmap')\n norm = BoundaryNorm(np.arange(groupby_cmap.N + 1) - 0.5, groupby_cmap.N)\n\n # determine groupby label positions such that they appear\n # centered next/below to the color code rectangle assigned to the category\n value_sum = 0\n ticks = [] # list of centered position of the labels\n labels = []\n label2code = {} # dictionary of numerical values asigned to each label\n for code, (label, value) in enumerate(\n obs_tidy.index.value_counts(sort=False).iteritems()\n ):\n ticks.append(value_sum + (value / 2))\n labels.append(label)\n value_sum += value\n label2code[label] = code\n\n groupby_ax.grid(False)\n\n if orientation == 'left':\n groupby_ax.imshow(\n np.array([[label2code[lab] for lab in obs_tidy.index]]).T,\n aspect='auto',\n cmap=groupby_cmap,\n norm=norm,\n )\n if len(labels) > 1:\n groupby_ax.set_yticks(ticks)\n groupby_ax.set_yticklabels(labels)\n\n # remove y ticks\n groupby_ax.tick_params(axis='y', left=False, labelsize='small')\n # remove x ticks and labels\n groupby_ax.tick_params(axis='x', bottom=False, labelbottom=False)\n\n # remove surrounding lines\n groupby_ax.spines['right'].set_visible(False)\n groupby_ax.spines['top'].set_visible(False)\n groupby_ax.spines['left'].set_visible(False)\n groupby_ax.spines['bottom'].set_visible(False)\n\n groupby_ax.set_ylabel(groupby)\n else:\n groupby_ax.imshow(\n np.array([[label2code[lab] for lab in obs_tidy.index]]),\n aspect='auto',\n cmap=groupby_cmap,\n norm=norm,\n )\n if len(labels) > 1:\n groupby_ax.set_xticks(ticks)\n if max([len(str(x)) for x in labels]) < 3:\n # if the labels are small do not rotate them\n rotation = 0\n else:\n rotation = 90\n groupby_ax.set_xticklabels(labels, rotation=rotation)\n\n # remove x ticks\n groupby_ax.tick_params(axis='x', bottom=False, labelsize='small')\n # remove y ticks and labels\n groupby_ax.tick_params(axis='y', left=False, labelleft=False)\n\n # remove surrounding lines\n groupby_ax.spines['right'].set_visible(False)\n groupby_ax.spines['top'].set_visible(False)\n groupby_ax.spines['left'].set_visible(False)\n groupby_ax.spines['bottom'].set_visible(False)\n\n groupby_ax.set_xlabel(groupby)\n\n return label2code, ticks, labels, groupby_cmap, norm\n\n\ndef plot_gene_groups_brackets(\n gene_groups_ax: Axes,\n group_positions: Iterable[Tuple[int, int]],\n group_labels: Sequence[str],\n left_adjustment: float = -0.3,\n right_adjustment: float = 0.3,\n rotation: Optional[float] = None,\n orientation: Literal['top', 'right'] = 'top',\n):\n \"\"\"from scanpy\"\"\"\n import matplotlib.patches as patches\n from matplotlib.path import Path\n\n # get the 'brackets' coordinates as lists of start and end positions\n\n left = [x[0] + left_adjustment for x in group_positions]\n right = [x[1] + right_adjustment for x in group_positions]\n\n # verts and codes are used by PathPatch to make the brackets\n verts = []\n codes = []\n if orientation == 'top':\n # rotate labels if any of them is longer than 4 characters\n if rotation is None and group_labels:\n if max([len(x) for x in group_labels]) > 4:\n rotation = 90\n else:\n rotation = 0\n for idx in range(len(left)):\n verts.append((left[idx], 0)) # lower-left\n verts.append((left[idx], 0.6)) # upper-left\n verts.append((right[idx], 0.6)) # upper-right\n verts.append((right[idx], 0)) # lower-right\n\n codes.append(Path.MOVETO)\n codes.append(Path.LINETO)\n codes.append(Path.LINETO)\n codes.append(Path.LINETO)\n\n try:\n group_x_center = left[idx] + float(right[idx] - left[idx]) / 2\n gene_groups_ax.text(\n group_x_center,\n 1.1,\n group_labels[idx],\n ha='center',\n va='bottom',\n rotation=rotation,\n )\n except:\n pass\n else:\n top = left\n bottom = right\n for idx in range(len(top)):\n verts.append((0, top[idx])) # upper-left\n verts.append((0.15, top[idx])) # upper-right\n verts.append((0.15, bottom[idx])) # lower-right\n verts.append((0, bottom[idx])) # lower-left\n\n codes.append(Path.MOVETO)\n codes.append(Path.LINETO)\n codes.append(Path.LINETO)\n codes.append(Path.LINETO)\n\n try:\n diff = bottom[idx] - top[idx]\n group_y_center = top[idx] + float(diff) / 2\n if diff * 2 < len(group_labels[idx]):\n # cut label to fit available space\n group_labels[idx] = group_labels[idx][: int(diff * 2)] + \".\"\n gene_groups_ax.text(\n 0.6,\n group_y_center,\n group_labels[idx],\n ha='right',\n va='center',\n rotation=270,\n fontsize='small',\n )\n except Exception as e:\n print('problems {}'.format(e))\n pass\n\n path = Path(verts, codes)\n\n patch = patches.PathPatch(path, facecolor='none', lw=1.5)\n\n gene_groups_ax.add_patch(patch)\n gene_groups_ax.grid(False)\n gene_groups_ax.axis('off')\n # remove y ticks\n gene_groups_ax.tick_params(axis='y', left=False, labelleft=False)\n # remove x ticks and labels\n gene_groups_ax.tick_params(\n axis='x', bottom=False, labelbottom=False, labeltop=False\n )\n\n\ndef _check_indices(\n dim_df: pd.DataFrame,\n alt_index: pd.Index,\n dim: \"Literal['obs', 'var']\",\n keys: List[str],\n alias_index: pd.Index = None,\n use_raw: bool = False,\n):\n \"\"\"from scanpy\"\"\"\n if use_raw:\n alt_repr = \"adata.raw\"\n else:\n alt_repr = \"adata\"\n\n alt_dim = (\"obs\", \"var\")[dim == \"obs\"]\n\n alias_name = None\n if alias_index is not None:\n alt_names = pd.Series(alt_index, index=alias_index)\n alias_name = alias_index.name\n alt_search_repr = f\"{alt_dim}['{alias_name}']\"\n else:\n alt_names = pd.Series(alt_index, index=alt_index)\n alt_search_repr = f\"{alt_dim}_names\"\n\n col_keys = []\n index_keys = []\n index_aliases = []\n not_found = []\n\n # check that adata.obs does not contain duplicated columns\n # if duplicated columns names are present, they will\n # be further duplicated when selecting them.\n if not dim_df.columns.is_unique:\n dup_cols = dim_df.columns[dim_df.columns.duplicated()].tolist()\n raise ValueError(\n f\"adata.{dim} contains duplicated columns. Please rename or remove \"\n \"these columns first.\\n`\"\n f\"Duplicated columns {dup_cols}\"\n )\n\n if not alt_index.is_unique:\n raise ValueError(\n f\"{alt_repr}.{alt_dim}_names contains duplicated items\\n\"\n f\"Please rename these {alt_dim} names first for example using \"\n f\"`adata.{alt_dim}_names_make_unique()`\"\n )\n\n # use only unique keys, otherwise duplicated keys will\n # further duplicate when reordering the keys later in the function\n for key in np.unique(keys):\n if key in dim_df.columns:\n col_keys.append(key)\n if key in alt_names.index:\n raise KeyError(\n f\"The key '{key}' is found in both adata.{dim} and {alt_repr}.{alt_search_repr}.\"\n )\n elif key in alt_names.index:\n val = alt_names[key]\n if isinstance(val, pd.Series):\n # while var_names must be unique, adata.var[gene_symbols] does not\n # It's still ambiguous to refer to a duplicated entry though.\n assert alias_index is not None\n raise KeyError(\n f\"Found duplicate entries for '{key}' in {alt_repr}.{alt_search_repr}.\"\n )\n index_keys.append(val)\n index_aliases.append(key)\n else:\n not_found.append(key)\n if len(not_found) > 0:\n raise KeyError(\n f\"Could not find keys '{not_found}' in columns of `adata.{dim}` or in\"\n f\" {alt_repr}.{alt_search_repr}.\"\n )\n\n return col_keys, index_keys, index_aliases\n"}],"string":"[\n {\n \"alpha_fraction\": 0.40083393454551697,\n \"alphanum_fraction\": 0.5601885318756104,\n \"avg_line_length\": 25.257143020629883,\n \"blob_id\": \"7bd2f370968ac513aa8f45d4b85f38dba0a2b29f\",\n \"content_id\": \"e13c71464e3fbf9b2020ffb3cba140cc0bc8926e\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 6558,\n \"license_type\": \"permissive\",\n \"max_line_length\": 199,\n \"num_lines\": 210,\n \"path\": \"/stereo/plots/plot_data_description.md\",\n \"repo_name\": \"leying95/stereopy\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# 绘图数据需求\\n\\n以 AnnData 为参照获取对应的输入数据\\n\\n## plot_spatial_distribution\\n\\n### 所需 AnnData 数据：\\n\\n- 图像坐标信息： \\n - `spatial_data = np.array(adata.obsm[\\\"spatial\\\"])`\\n\\n- 图像散点数值信息： \\n - `color_data = np.array(adata.obs_vector(key))`\\n - 其中 key 为散点所需呈现的数据种类，如 total_counts, n_genes_by_counts，可利用的数据种类都在 `adata.obs.keys()`\\n\\n### 实际所需数据格式：\\n\\n- 图像坐标信息demo：\\n \\n ```Text\\n array([[ 256, -91],[ 185, -157],[ 257, -288],...,[ 151, -246],[ 290, -141],[ 177, -132]])\\n ```\\n\\n- 图像散点数值信息demo：\\n \\n ```Text\\n array([3582., 1773., 2283., ..., 4062., 4371., 1172.], dtype=float32)\\n ```\\n\\n其中散点数值和坐标信息一一对应\\n\\n## plot_spatial_cluster && plot_cluster_umap\\n\\n这两个函数整合成了 plot_cluster_result，区别在于所用的 spatial data （pos_key） 不同， plot_spatial_cluster 使用的是 spatial 空间数据，plot_cluster_umap 使用的是 X_umap 的主成分值数据\\n\\n### 所需 AnnData 数据：\\n\\n- 图像坐标信息： \\n - `spatial_data = np.array(adata.obsm[pos_key])`\\n\\n- 图像散点数值信息： \\n - `color_data = np.array(adata.obs_vector(key))`\\n - 其中 key 为散点所需呈现的数据种类，可利用的数据种类都在 adata.obs.keys()，此处用到的主要是聚类相关数据，如 [\\\"phenograph\\\", \\\"leiden\\\"]\\n - 在 cluster 相关的图像中，散点数据属于 categorical 数据\\n\\n### 实际所需数据格式：\\n\\n- 图像坐标信息demo：\\n \\n spatial:\\n\\n ```Text\\n array([[ 256, -91],[ 185, -157],[ 257, -288],...,[ 151, -246],[ 290, -141],[ 177, -132]])\\n ```\\n\\n umap：\\n \\n ```Text\\n array([[-2.234908 , 3.7087667 ], [ 3.7431364 , 2.003201 ], [ 4.849478 , -0.21215418], ..., [ 6.861894 , 1.7589074 ], [-0.4605783 , 4.0366364 ], [ 7.3391566 , -0.40746352]], dtype=float32)\\n ```\\n\\n- 图像散点数值信息demo：\\n \\n ```Text\\n ['0', '3', '5', '3', '2', ..., '4', '3', '6', '1', '5']\\n Length: 22726\\n Categories (10, object): ['0', '1', '2', '3', ..., '6', '7', '8', '9']\\n ```\\n\\n其中散点数值和坐标信息一一对应\\n\\n\\n## plot_to_select_filter_value\\n\\n### 所需 AnnData 数据\\n\\n- `x = adata.obs_vector(var1)`\\n- `y = adata.obs_vector(var2)`\\n\\nvar1 var2 可以是任意两个 obs_key 中的值\\n\\n### 实际所需数据格式\\n\\n```Text\\narray([3582., 1773., 2283., ..., 4062., 4371., 1172.], dtype=float32)\\n```\\n\\n## plot_variable_gene\\n\\n### 所需 AnnData 数据：\\n\\n- `adata.var.highly_variable`\\n- `adata.var.means`\\n- `adata.var.dispersions`\\n- `adata.var.dispersions_norm`\\n\\n### 实际所需数据格式\\n\\npandas.core.series.Series\\n\\n例如： adata.var.means:\\n\\n```Text\\nAL355102.2 0.012042\\nSLC25A2 0.000596\\n ... \\nAC069214.1 0.009608\\nAL356056.1 0.001655\\nName: means, Length: 33304, dtype: float64\\n```\\n\\n## plot_expression_difference\\n\\n### 所需 AnnData 数据\\n\\n- 聚类得到的类名： `group_names = adata.uns[\\\"rank_genes_groups\\\"]['names'].dtype.names`\\n- 在各个类名（group_name in group_names）的基础上获取各个类的基因列表('names')和分数('scores')：\\n - `gene_names = adata.uns[\\\"rank_genes_groups\\\"]['names'][group_name][:number_of_gene_to_show]`\\n - `scores = adata.uns[\\\"rank_genes_groups\\\"]['scores'][group_name][:number_of_gene_to_show]`\\n\\n### 实际所需数据格式：\\n\\n- 聚类得到的类名：\\n\\n ```Text\\n tuple('0', '1', '2', '3', '4', '5', '6', '7', '8', '9')\\n ```\\n- 各个类名对应的基因列表和分数列表：\\n \\n ```Text\\n numpy.ndarray\\n \\n array(['TUBB4B', 'SLC12A2', 'EPHB3', ..., 'TFF3', 'TIMP1', 'OLFM4'],\\n dtype=object)\\n \\n array([ 28.094688, 27.638664, 24.523687, ..., -41.63738 , -42.894638, -48.384773], dtype=float32)\\n ```\\n\\n## plot_violin_distribution\\n\\n### 所需 AnnData 数据\\n\\n- `adata.obs['total_counts']`\\n- `adata.obs['n_genes_by_counts']`\\n- `adata.obs['pct_counts_mt']`\\n\\n### 实际所需数据格式\\n\\npandas.core.series.Series\\n\\n例如： total_counts:\\n\\n```Text\\n256-91 3582.0\\n185-157 1773.0\\n ... \\n290-141 4371.0\\n177-132 1172.0\\nName: total_counts, Length: 22726, dtype: float32\\n```\\n\\n## plot_heatmap_maker_genes\\n\\n### 所需 AnnData 数据：\\n\\n- 聚类得到的类名： `marker_clusters = adata.uns[\\\"rank_genes_groups\\\"]['names'].dtype.names`\\n- 在各个类名（cluster in marker_clusters）的基础上获取各个类的基因列表('names'):\\n - `genes_array = adata.uns[\\\"rank_genes_groups\\\"]['names'][group_name][:number_of_gene_to_show]`\\n- 设定表达量矩阵（热图矩阵）\\n - 矩阵index： `adata.obs_name`\\n - 整合各个类的基因列表，获取 uniq gene list，然后获取这些uniq gene 的表达量来构建 pandas.DataFrame\\n - 表达量： `exp_matrix = adata.X[tuple([slice(None), adata.var.index.get_indexer(uniq_gene_names)])]`\\n - pd.DataFrame: `pd.DataFrame(exp_matrix, columns=uniq_gene_names, index=adata.obs_names)`\\n - 添加 obs 列在最开头： `pd.concat([draw_df, adata.obs[cluster_method]], axis=1)`\\n \\n\\n### 实际所需数据格式：\\n\\n- 聚类得到的类名：\\n\\n ```Text\\n tuple('0', '1', '2', '3', '4', '5', '6', '7', '8', '9')\\n ```\\n\\n- 各个类名对应的基因列表：\\n \\n ```Text\\n numpy.ndarray\\n \\n array(['TUBB4B', 'SLC12A2', 'EPHB3', ..., 'TFF3', 'TIMP1', 'OLFM4'],\\n dtype=object)\\n ```\\n\\n- 表达量矩阵最终效果：\\n \\n ```Text\\n TUBB4B SLC12A2 EPHB3 MT-ND1 FTX NAALADL2 \\n phenograph \\n 0 3.758313 1.884562 2.705292 4.040148 2.498723 2.238069 \\n 0 3.118562 1.224227 1.758388 3.311160 1.758388 0.000000 \\n 0 2.790583 0.000000 0.000000 3.175375 0.000000 0.000000 \\n 0 0.000000 1.885036 1.885036 3.821939 0.000000 0.000000 \\n 0 2.596922 0.000000 2.596922 3.644590 2.596922 2.596922 \\n ... ... ... ... ... ... ... \\n 9 3.172084 1.570598 0.000000 4.186041 1.570598 0.000000 \\n 9 0.000000 1.847625 0.000000 3.893912 0.000000 2.458688 \\n 9 2.681648 2.681648 0.000000 3.339970 1.314215 1.314215 \\n 9 1.955572 1.955572 0.000000 3.229691 1.955572 0.000000 \\n 9 2.963927 1.721601 1.721601 3.176694 1.721601 0.000000 \\n ```\\n\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.5407407283782959,\n \"alphanum_fraction\": 0.614814817905426,\n \"avg_line_length\": 15.875,\n \"blob_id\": \"6be96570692f13225dce46515d9ca9c98fef1296\",\n \"content_id\": \"0a956633adf2311ac4c74e39451ffd2cbcbd1029\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 135,\n \"license_type\": \"permissive\",\n \"max_line_length\": 25,\n \"num_lines\": 8,\n \"path\": \"/stereo/plots/_plot_basic/__init__.py\",\n \"repo_name\": \"leying95/stereopy\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#!/usr/bin/env python3\\n# coding: utf-8\\n\\\"\\\"\\\"\\n@author: Shixu He heshixu@genomics.cn\\n@last modified by: Shixu He\\n@file:__init__.py.py\\n@time:2021/03/15\\n\\\"\\\"\\\"\\n\"\n },\n {\n \"alpha_fraction\": 0.8245614171028137,\n \"alphanum_fraction\": 0.8245614171028137,\n \"avg_line_length\": 27.5,\n \"blob_id\": \"07e56b8199fa5930875326eee974fd0b94d0cbaa\",\n \"content_id\": \"a08af99a95386dcc9a13b89532990ab6cd210c1f\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 57,\n \"license_type\": \"permissive\",\n \"max_line_length\": 45,\n \"num_lines\": 2,\n \"path\": \"/README.md\",\n \"repo_name\": \"leying95/stereopy\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# stereopy\\nA toolkit of spatial transcriptomic analysis.\\n\"\n },\n {\n \"alpha_fraction\": 0.576362669467926,\n \"alphanum_fraction\": 0.582298994064331,\n \"avg_line_length\": 30.94827651977539,\n \"blob_id\": \"da5efc016b2d7c7a1cc9131a627d2377e1ae0157\",\n \"content_id\": \"66c073cd335fd0fa657926a18e9d780efb70e29a\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1853,\n \"license_type\": \"permissive\",\n \"max_line_length\": 78,\n \"num_lines\": 58,\n \"path\": \"/stereo/log_manager.py\",\n \"repo_name\": \"leying95/stereopy\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#!/usr/bin/env python3\\n# coding: utf-8\\n\\\"\\\"\\\"\\n@author: Ping Qiu qiuping1@genomics.cn\\n@last modified by: Ping Qiu\\n@file:log_manager.py\\n@time:2021/03/05\\n\\\"\\\"\\\"\\n\\nimport logging\\nfrom .config import stereo_conf\\n\\n\\nclass LogManager(object):\\n def __init__(self, log_path=None, level=None):\\n self.level_map = {'debug': logging.DEBUG,\\n 'info': logging.INFO,\\n 'warning': logging.WARNING,\\n 'error': logging.ERROR,\\n 'critical': logging.CRITICAL}\\n self.format = stereo_conf.log_format\\n self.formatter = logging.Formatter(self.format, \\\"%Y-%m-%d %H:%M:%S\\\")\\n self.log_path = log_path\\n self.level = level.lower() if level else stereo_conf.log_level.lower()\\n if self.log_path:\\n self.file_handler = logging.FileHandler(self.log_path)\\n self.file_handler.setLevel(self.level_map[self.level])\\n self.file_handler.setFormatter(self.formatter)\\n else:\\n self.stream_handler = logging.StreamHandler()\\n self.stream_handler.setLevel(self.level_map[self.level])\\n self.stream_handler.setFormatter(self.formatter)\\n\\n def get_logger(self, name=\\\"Spateo\\\"):\\n \\\"\\\"\\\"\\n get logger object\\n :param name: logger name\\n :return: logger object\\n \\\"\\\"\\\"\\n alogger = logging.getLogger(name)\\n alogger.propagate = 0\\n alogger.setLevel(self.level_map[self.level])\\n self._add_handler(alogger)\\n return alogger\\n\\n def _add_handler(self, alogger):\\n \\\"\\\"\\\"\\n add handler of logger\\n :param logger: logger object\\n :return:\\n \\\"\\\"\\\"\\n if self.log_path:\\n alogger.addHandler(self.file_handler)\\n else:\\n alogger.addHandler(self.stream_handler)\\n\\n\\nlogger = LogManager().get_logger(name='Spateo')\\n\"\n },\n {\n \"alpha_fraction\": 0.5441176295280457,\n \"alphanum_fraction\": 0.5572336912155151,\n \"avg_line_length\": 34.42253494262695,\n \"blob_id\": \"223b8ada9eb9f510c9b68f7895d4f42a65b81f8e\",\n \"content_id\": \"0299148833875c5536949e7ad7ae0d0f9b9dafff\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 2516,\n \"license_type\": \"permissive\",\n \"max_line_length\": 117,\n \"num_lines\": 71,\n \"path\": \"/stereo/tools/neighbors.py\",\n \"repo_name\": \"leying95/stereopy\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#!/usr/bin/env python3\\n# coding: utf-8\\n\\\"\\\"\\\"\\n@author: Ping Qiu qiuping1@genomics.cn\\n@last modified by: Ping Qiu\\n@file:neighbors.py\\n@time:2021/03/23\\n\\\"\\\"\\\"\\nfrom scipy.sparse import coo_matrix\\nfrom sklearn.neighbors import NearestNeighbors\\nimport igraph as ig\\nimport numpy as np\\nfrom umap.umap_ import fuzzy_simplicial_set\\n\\n\\nclass Neighbors(object):\\n def __init__(self, x, n_neighbors):\\n self.x = x\\n self.n_neighbors = n_neighbors\\n\\n def find_n_neighbors(self):\\n nbrs = NearestNeighbors(n_neighbors=self.n_neighbors + 1, algorithm='ball_tree').fit(self.x)\\n dists, indices = nbrs.kneighbors(self.x)\\n nn_idx = indices[:, 1:]\\n nn_dist = dists[:, 1:]\\n return nn_idx, nn_dist\\n\\n def get_igraph_from_knn(self, nn_idx, nn_dist):\\n j = nn_idx.ravel().astype(int)\\n dist = nn_dist.ravel()\\n i = np.repeat(np.arange(nn_idx.shape[0]), self.n_neighbors)\\n\\n vertex = list(range(nn_dist.shape[0]))\\n edges = list(tuple(zip(i, j)))\\n G = ig.Graph()\\n G.add_vertices(vertex)\\n G.add_edges(edges)\\n G.es['weight'] = dist\\n return G\\n\\n def get_parse_distances(self, nn_idx, nn_dist):\\n n_obs = self.x.shape[0]\\n rows = np.zeros((n_obs * self.n_neighbors), dtype=np.int64)\\n cols = np.zeros((n_obs * self.n_neighbors), dtype=np.int64)\\n vals = np.zeros((n_obs * self.n_neighbors), dtype=np.float64)\\n\\n for i in range(nn_idx.shape[0]):\\n for j in range(self.n_neighbors):\\n if nn_idx[i, j] == -1:\\n continue # We didn't get the full knn for i\\n if nn_idx[i, j] == i:\\n val = 0.0\\n else:\\n val = nn_dist[i, j]\\n\\n rows[i * self.n_neighbors + j] = i\\n cols[i * self.n_neighbors + j] = nn_idx[i, j]\\n vals[i * self.n_neighbors + j] = val\\n\\n distances = coo_matrix((vals, (rows, cols)), shape=(n_obs, n_obs))\\n distances.eliminate_zeros()\\n return distances.tocsr()\\n\\n def get_connectivities(self, nn_idx, nn_dist):\\n n_obs = self.x.shape[0]\\n x = coo_matrix(([], ([], [])), shape=(n_obs, 1))\\n connectivities = fuzzy_simplicial_set(x, self.n_neighbors, None, None, knn_indices=nn_idx, knn_dists=nn_dist,\\n set_op_mix_ratio=1.0, local_connectivity=1.0)\\n if isinstance(connectivities, tuple):\\n connectivities = connectivities[0]\\n return connectivities.tocsr()\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.5665071606636047,\n \"alphanum_fraction\": 0.5779904127120972,\n \"avg_line_length\": 18.716981887817383,\n \"blob_id\": \"75c8c1af025576b41fdaa21b6c25ecd8e15afd72\",\n \"content_id\": \"cd7efb2f1f96eb9937d843ad9cef415c0aff5d4f\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1045,\n \"license_type\": \"permissive\",\n \"max_line_length\": 107,\n \"num_lines\": 53,\n \"path\": \"/stereo/core/stereo_data.py\",\n \"repo_name\": \"leying95/stereopy\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#!/usr/bin/env python3\\n# coding: utf-8\\n\\\"\\\"\\\"\\n@author: Ping Qiu qiuping1@genomics.cn\\n@last modified by: Ping Qiu\\n@file:stereo_data.py\\n@time:2021/03/22\\n\\\"\\\"\\\"\\n\\n\\nclass StereoData(object):\\n def __init__(self, raw_file=None, exp_matrix=None, genes=None, bins=None, position=None, partitions=1):\\n self.index = None\\n self.index_file = None\\n self.exp_matrix = exp_matrix\\n self.genes = genes\\n self.bins = bins\\n self.position = position\\n self.raw_file = raw_file\\n self.partitions = partitions\\n\\n def filter_genes(self):\\n pass\\n\\n def filter_bins(self):\\n pass\\n\\n def search(self):\\n pass\\n\\n def combine_bins(self, bin_size, step):\\n pass\\n\\n def select_by_genes(self, gene_list):\\n pass\\n\\n def select_by_position(self, x_min, y_min, x_max, y_max, bin_size):\\n pass\\n\\n def transform_matrix(self):\\n pass\\n\\n def get_genes(self):\\n pass\\n\\n def get_bins(self):\\n pass\\n\\n def split_data(self):\\n pass\\n\\n def sparse2array(self):\\n pass\\n\"\n },\n {\n \"alpha_fraction\": 0.6382660865783691,\n \"alphanum_fraction\": 0.6636771559715271,\n \"avg_line_length\": 29.409090042114258,\n \"blob_id\": \"b9472f782f76c2f6c8aaa8802826cc4656afb1ba\",\n \"content_id\": \"ed031fae5add10b548834f898ab95a813e1f9395\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 669,\n \"license_type\": \"permissive\",\n \"max_line_length\": 71,\n \"num_lines\": 22,\n \"path\": \"/stereo/preprocess/qc.py\",\n \"repo_name\": \"leying95/stereopy\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#!/usr/bin/env python3\\n# coding: utf-8\\n\\\"\\\"\\\"\\n@author: Ping Qiu qiuping1@genomics.cn\\n@last modified by: Ping Qiu\\n@file:qc.py\\n@time:2021/03/26\\n\\\"\\\"\\\"\\nfrom scipy.sparse import issparse\\nimport numpy as np\\n\\n\\ndef cal_qc(andata):\\n exp_matrix = andata.X.toarray() if issparse(andata.X) else andata.X\\n total_count = exp_matrix.sum(1)\\n n_gene_by_count = np.count_nonzero(exp_matrix, axis=1)\\n mt_index = andata.var_names.str.startswith('MT-')\\n mt_count = np.array(andata.X[:, mt_index].sum(1)).reshape(-1)\\n andata.obs['total_counts'] = total_count\\n andata.obs['pct_counts_mt'] = mt_count / total_count * 100\\n andata.obs['n_genes_by_counts'] = n_gene_by_count\\n return andata\\n\"\n },\n {\n \"alpha_fraction\": 0.5326364636421204,\n \"alphanum_fraction\": 0.5358884930610657,\n \"avg_line_length\": 25.411043167114258,\n \"blob_id\": \"57ec9a317b271c5001152cd0804fe0de76566362\",\n \"content_id\": \"5e726176ef70882e7b7c303bdb60a84d1c62f300\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 4305,\n \"license_type\": \"permissive\",\n \"max_line_length\": 114,\n \"num_lines\": 163,\n \"path\": \"/stereo/config.py\",\n \"repo_name\": \"leying95/stereopy\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#!/usr/bin/env python3\\n# coding: utf-8\\n\\\"\\\"\\\"\\n@author: Ping Qiu qiuping1@genomics.cn\\n@last modified by: Ping Qiu\\n@file:config.py\\n@time:2021/03/05\\n\\\"\\\"\\\"\\nfrom typing import Union, Optional\\nfrom pathlib import Path\\nimport os\\nfrom matplotlib import rcParams, rcParamsDefault\\n\\n\\nclass StereoConfig(object):\\n \\\"\\\"\\\"\\n config of stereo.\\n \\\"\\\"\\\"\\n def __init__(\\n self,\\n file_format: str = \\\"h5ad\\\",\\n auto_show: bool = True,\\n n_jobs=1,\\n log_file: Union[str, Path, None] = None,\\n log_level: str = \\\"info\\\",\\n log_format: str = \\\"%(asctime)s %(name)s %(levelname)s: %(message)s\\\",\\n output: str = \\\"./output\\\",\\n data_dir: str = None\\n ):\\n self._file_format = file_format\\n self._auto_show = auto_show\\n self._n_jobs = n_jobs\\n self._log_file = log_file\\n self._log_level = log_level\\n self._log_format = log_format\\n self.out_dir = output\\n self.data_dir = data_dir if data_dir else os.path.join(os.path.dirname(os.path.abspath(__file__)), 'data')\\n\\n @property\\n def log_file(self) -> Union[str, Path, None]:\\n \\\"\\\"\\\"\\n get the file path of log.\\n :return:\\n \\\"\\\"\\\"\\n return self._log_file\\n\\n @log_file.setter\\n def log_file(self, value):\\n \\\"\\\"\\\"\\n set file path of log.\\n :param value: value of log file path\\n :return:\\n \\\"\\\"\\\"\\n if value:\\n dir_path = os.path.dirname(value)\\n if not os.path.exists(dir_path):\\n raise FileExistsError(\\\"folder does not exist, please check!\\\")\\n self._log_file = value\\n\\n @property\\n def log_format(self) -> str:\\n \\\"\\\"\\\"\\n get the format of log.\\n :return:\\n \\\"\\\"\\\"\\n return self._log_format\\n\\n @log_format.setter\\n def log_format(self, value):\\n \\\"\\\"\\\"\\n set file path of log.\\n :param value: value of log format\\n :return:\\n \\\"\\\"\\\"\\n self._log_format = value\\n\\n @property\\n def log_level(self) -> str:\\n \\\"\\\"\\\"\\n get log level\\n :return:\\n \\\"\\\"\\\"\\n return self._log_level\\n\\n @log_level.setter\\n def log_level(self, value):\\n \\\"\\\"\\\"\\n set log level\\n :param value: the value of log level\\n :return:\\n \\\"\\\"\\\"\\n if value.lower() not in ['info', 'warning', 'debug', 'error', 'critical']:\\n print('the log level is out of range, please check and it is not modified.')\\n else:\\n self._log_level = value\\n\\n @property\\n def auto_show(self):\\n \\\"\\\"\\\"\\n Auto show figures if `auto_show == True` (default `True`).\\n :return:\\n \\\"\\\"\\\"\\n return self._auto_show\\n\\n @auto_show.setter\\n def auto_show(self, value):\\n \\\"\\\"\\\"\\n set value of auto_show\\n :param value: value of auto_show\\n :return:\\n \\\"\\\"\\\"\\n self._auto_show = value\\n\\n @property\\n def file_format(self) -> str:\\n \\\"\\\"\\\"\\n file format of saving anndata object\\n :return:\\n \\\"\\\"\\\"\\n return self._file_format\\n\\n @file_format.setter\\n def file_format(self, value):\\n \\\"\\\"\\\"\\n set the value of file format\\n :param value: the value of file format\\n :return:\\n \\\"\\\"\\\"\\n self._file_format = value\\n\\n @property\\n def n_jobs(self) -> int:\\n return self._n_jobs\\n\\n @n_jobs.setter\\n def n_jobs(self, value):\\n self._n_jobs = value\\n\\n @staticmethod\\n def set_plot_param(fontsize: int = 14, figsize: Optional[int] = None, color_map: Optional[str] = None,\\n facecolor: Optional[str] = None, transparent: bool = False,):\\n if fontsize is not None:\\n rcParams['font.size'] = fontsize\\n if color_map is not None:\\n rcParams['image.cmap'] = color_map\\n if figsize is not None:\\n rcParams['figure.figsize'] = figsize\\n if facecolor is not None:\\n rcParams['figure.facecolor'] = facecolor\\n rcParams['axes.facecolor'] = facecolor\\n if transparent is not None:\\n rcParams[\\\"savefig.transparent\\\"] = transparent\\n\\n @staticmethod\\n def set_rcparams_defaults():\\n \\\"\\\"\\\"\\n reset `matplotlib.rcParams` to defaults.\\n :return:\\n \\\"\\\"\\\"\\n rcParams.update(rcParamsDefault)\\n\\n\\nstereo_conf = StereoConfig()\\n\"\n },\n {\n \"alpha_fraction\": 0.552388072013855,\n \"alphanum_fraction\": 0.5629907250404358,\n \"avg_line_length\": 33.834495544433594,\n \"blob_id\": \"5cf9c6e4a72c0d946056b70efefaa0185bdaeffa\",\n \"content_id\": \"e13b730eda2fc60a16a1c52046d3725d072fd48c\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 20531,\n \"license_type\": \"permissive\",\n \"max_line_length\": 155,\n \"num_lines\": 574,\n \"path\": \"/stereo/plots/plot_utils.py\",\n \"repo_name\": \"leying95/stereopy\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#!/usr/bin/env python3\\n# coding: utf-8\\n\\\"\\\"\\\"\\n@author: Shixu He heshixu@genomics.cn\\n@last modified by: Shixu He\\n@file:plot_utils.py\\n@time:2021/03/15\\n\\\"\\\"\\\"\\n\\nfrom anndata import AnnData\\nimport pandas as pd\\nimport numpy as np\\nimport math\\n\\nfrom matplotlib.colors import Normalize, ListedColormap\\nfrom matplotlib import gridspec\\nfrom matplotlib.cm import get_cmap\\nfrom matplotlib.axes import Axes\\nimport matplotlib.pyplot as plt\\nimport seaborn\\n\\nfrom ._plot_basic.scatter_plt import scatter, plot_cluster_result\\nfrom ._plot_basic.heatmap_plt import heatmap, _plot_categories_as_colorblocks, _plot_gene_groups_brackets\\n\\nfrom typing import Optional, Sequence, Union\\n\\nfrom ..log_manager import logger\\n\\n\\ndef plot_spatial_distribution(\\n adata: AnnData,\\n obs_key: list = [\\\"total_counts\\\", \\\"n_genes_by_counts\\\"],\\n ncols=2,\\n dot_size=None,\\n color_list=None,\\n invert_y=False\\n): # scatter plot, 表达矩阵空间分布\\n \\\"\\\"\\\"\\n Plot spatial distribution of specified obs data.\\n ============ Arguments ============\\n :param adata: AnnData object.\\n :param obs_key: specified obs key list, for example: [\\\"total_counts\\\", \\\"n_genes_by_counts\\\"]\\n :param ncols: numbr of plot columns.\\n :param dot_size: marker size.\\n :param cmap: Color map.\\n :param invert_y: whether to invert y-axis.\\n ============ Return ============\\n None\\n ============ Example ============\\n plot_spatial_distribution(adata=adata)\\n \\\"\\\"\\\"\\n # sc.pl.embedding(adata, basis=\\\"spatial\\\", color=[\\\"total_counts\\\", \\\"n_genes_by_counts\\\"],size=30)\\n\\n if dot_size is None:\\n dot_size = 120000 / adata.shape[0]\\n\\n ncols = min(ncols, len(obs_key))\\n nrows = np.ceil(len(obs_key) / ncols).astype(int)\\n # each panel will have the size of rcParams['figure.figsize']\\n fig = plt.figure(figsize=(ncols * 10, nrows * 8))\\n left = 0.2 / ncols\\n bottom = 0.13 / nrows\\n axs = gridspec.GridSpec(\\n nrows=nrows,\\n ncols=ncols,\\n left=left,\\n right=1 - (ncols - 1) * left - 0.01 / ncols,\\n bottom=bottom,\\n top=1 - (nrows - 1) * bottom - 0.1 / nrows,\\n # hspace=hspace,\\n # wspace=wspace,\\n )\\n\\n if color_list is None:\\n cmap = get_cmap()\\n else:\\n cmap = ListedColormap(color_list)\\n # 把特定值改为 np.nan 之后，可以利用 cmap.set_bad(\\\"white\\\") 来遮盖掉这部分数据\\n\\n # 散点图上每个点的坐标数据来自于 adata 的 obsm[\\\"spatial\\\"]，每个点的颜色（数值）数据来自于 adata 的 obs_vector()\\n for i, key in enumerate(obs_key):\\n # color_data = np.asarray(adata.obs_vector(key), dtype=float)\\n color_data = adata.obs_vector(key)\\n order = np.argsort(~pd.isnull(color_data), kind=\\\"stable\\\")\\n spatial_data = np.array(adata.obsm[\\\"spatial\\\"])[:, 0: 2]\\n color_data = color_data[order]\\n spatial_data = spatial_data[order, :]\\n\\n # color_data 是图像中各个点的值，也对应了每个点的颜色。data_points则对应了各个点的坐标\\n ax = fig.add_subplot(axs[i]) # ax = plt.subplot(axs[i]) || ax = fig.add_subplot(axs[1, 1]))\\n ax.set_title(key)\\n ax.set_yticks([])\\n ax.set_xticks([])\\n ax.set_xlabel(\\\"spatial1\\\")\\n ax.set_ylabel(\\\"spatial2\\\")\\n pathcollection = scatter(\\n spatial_data[:, 0],\\n spatial_data[:, 1],\\n ax=ax,\\n marker=\\\".\\\",\\n dot_colors=color_data,\\n dot_size=dot_size,\\n cmap=cmap,\\n )\\n plt.colorbar(\\n pathcollection,\\n ax=ax,\\n pad=0.01,\\n fraction=0.08,\\n aspect=30,\\n )\\n ax.autoscale_view()\\n if invert_y:\\n ax.invert_yaxis()\\n\\n\\ndef plot_spatial_cluster(\\n adata: AnnData,\\n obs_key: list = [\\\"phenograph\\\"],\\n plot_cluster: list = None,\\n bad_color=\\\"lightgrey\\\",\\n ncols=2,\\n dot_size=None,\\n invert_y=False,\\n color_list=['violet', 'turquoise', 'tomato', 'teal',\\n 'tan', 'silver', 'sienna', 'red', 'purple',\\n 'plum', 'pink', 'orchid', 'orangered', 'orange',\\n 'olive', 'navy', 'maroon', 'magenta', 'lime',\\n 'lightgreen', 'lightblue', 'lavender', 'khaki',\\n 'indigo', 'grey', 'green', 'gold', 'fuchsia',\\n 'darkgreen', 'darkblue', 'cyan', 'crimson', 'coral',\\n 'chocolate', 'chartreuse', 'brown', 'blue', 'black',\\n 'beige', 'azure', 'aquamarine', 'aqua']): # scatter plot, 聚类后表达矩阵空间分布\\n \\\"\\\"\\\"\\n Plot spatial distribution of specified obs data.\\n ============ Arguments ============\\n :param adata: AnnData object.\\n :param obs_key: specified obs cluster key list, for example: [\\\"phenograph\\\"].\\n :param plot_cluster: the name list of clusters to show.\\n :param ncols: numbr of plot columns.\\n :param dot_size: marker size.\\n :param cmap: Color map.\\n :param invert_y: whether to invert y-axis.\\n ============ Return ============\\n None.\\n ============ Example ============\\n plot_spatial_cluster(adata = adata)\\n \\\"\\\"\\\"\\n # sc.pl.embedding(adata, basis=\\\"spatial\\\", color=[\\\"total_counts\\\", \\\"n_genes_by_counts\\\"],size=30)\\n\\n if isinstance(obs_key, str):\\n obs_key = [\\\"obs_key\\\"]\\n\\n plot_cluster_result(adata, obs_key=obs_key, pos_key=\\\"spatial\\\", plot_cluster=plot_cluster, bad_color=bad_color,\\n ncols=ncols, dot_size=dot_size, invert_y=invert_y, color_list=color_list)\\n\\n\\ndef plot_to_select_filter_value(\\n adata: AnnData,\\n x=[\\\"total_counts\\\", \\\"total_counts\\\"],\\n y=[\\\"pct_counts_mt\\\", \\\"n_genes_by_counts\\\"],\\n ncols=1,\\n **kwargs): # scatter plot, 线粒体分布图\\n \\\"\\\"\\\"\\n Plot .\\n ============ Arguments ============\\n :param adata: AnnData object.\\n :param x, y: obs key pairs for drawing. For example, assume x=[\\\"a\\\", \\\"a\\\", \\\"b\\\"] and y=[\\\"c\\\", \\\"d\\\", \\\"e\\\"], the output plots will include \\\"a-c\\\", \\\"a-d\\\", \\\"b-e\\\".\\n ============ Return ============\\n None.\\n ============ Example ============\\n plot_spatial_cluster(adata = adata)\\n \\\"\\\"\\\"\\n # sc.pl.scatter(adata, x='total_counts', y='pct_counts_mt')\\n # sc.pl.scatter(adata, x='total_counts', y='n_genes_by_counts')\\n if isinstance(x, str):\\n x = [x]\\n if isinstance(y, str):\\n y = [y]\\n\\n width = 20\\n height = 10\\n nrows = math.ceil(len(x) / ncols)\\n\\n doc_color = \\\"gray\\\"\\n\\n fig = plt.figure(figsize=(width, height))\\n axs = gridspec.GridSpec(\\n nrows=nrows,\\n ncols=ncols,\\n )\\n for i, (xi, yi) in enumerate(zip(x, y)):\\n draw_data = np.c_[adata.obs_vector(xi), adata.obs_vector(yi)]\\n dot_size = 120000 / draw_data.shape[0]\\n ax = fig.add_subplot(axs[i])\\n # ax.set_title()\\n # ax.set_yticks([])\\n # ax.set_xticks([])\\n ax.set_xlabel(xi)\\n ax.set_ylabel(yi)\\n scatter(\\n draw_data[:, 0],\\n draw_data[:, 1],\\n ax=ax,\\n marker=\\\".\\\",\\n dot_colors=doc_color,\\n dot_size=dot_size\\n )\\n\\n\\ndef plot_variable_gene(adata: AnnData, logarize=False): # scatter plot, 表达量差异-均值图\\n \\\"\\\"\\\"\\n Copied from scanpy and modified.\\n \\\"\\\"\\\"\\n # 该图像需要前置数据处理：sc.pp.highly_variable_genes(adata, min_mean=0.0125, max_mean=3, min_disp=0.5)\\n # 再画图：sc.pl.highly_variable_genes(adata)\\n\\n result = adata.var\\n gene_subset = result.highly_variable\\n means = result.means\\n var_or_disp = result.dispersions\\n var_or_disp_norm = result.dispersions_norm\\n width = 10\\n height = 10\\n\\n plt.figure(figsize=(2 * width, height))\\n plt.subplots_adjust(wspace=0.3)\\n for idx, d in enumerate([var_or_disp_norm, var_or_disp]):\\n plt.subplot(1, 2, idx + 1)\\n for label, color, mask in zip(\\n ['highly variable genes', 'other genes'],\\n ['black', 'grey'],\\n [gene_subset, ~gene_subset],\\n ):\\n if False:\\n means_, var_or_disps_ = np.log10(means[mask]), np.log10(d[mask])\\n else:\\n means_, var_or_disps_ = means[mask], d[mask]\\n plt.scatter(means_, var_or_disps_, label=label, c=color, s=1)\\n if logarize: # there's a bug in autoscale\\n plt.xscale('log')\\n plt.yscale('log')\\n y_min = np.min(var_or_disp)\\n y_min = 0.95 * y_min if y_min > 0 else 1e-1\\n plt.xlim(0.95 * np.min(means), 1.05 * np.max(means))\\n plt.ylim(y_min, 1.05 * np.max(var_or_disp))\\n if idx == 0:\\n plt.legend()\\n plt.xlabel(('$log_{10}$ ' if False else '') + 'mean expressions of genes')\\n data_type = 'dispersions'\\n plt.ylabel(\\n ('$log_{10}$ ' if False else '')\\n + '{} of genes'.format(data_type)\\n + (' (normalized)' if idx == 0 else ' (not normalized)')\\n )\\n\\n\\ndef plot_cluster_umap(\\n adata: AnnData,\\n obs_key: list = [\\\"phenograph\\\"],\\n plot_cluster: list = None,\\n bad_color=\\\"lightgrey\\\",\\n ncols=2,\\n dot_size=None,\\n invert_y=False,\\n color_list=['violet', 'turquoise', 'tomato', 'teal',\\n 'tan', 'silver', 'sienna', 'red', 'purple',\\n 'plum', 'pink', 'orchid', 'orangered', 'orange',\\n 'olive', 'navy', 'maroon', 'magenta', 'lime',\\n 'lightgreen', 'lightblue', 'lavender', 'khaki',\\n 'indigo', 'grey', 'green', 'gold', 'fuchsia',\\n 'darkgreen', 'darkblue', 'cyan', 'crimson', 'coral',\\n 'chocolate', 'chartreuse', 'brown', 'blue', 'black',\\n 'beige', 'azure', 'aquamarine', 'aqua',\\n ]\\n): # scatter plot，聚类结果PCA/umap图\\n \\\"\\\"\\\"\\n Plot spatial distribution of specified obs data.\\n ============ Arguments ============\\n :param adata: AnnData object.\\n :param obs_key: specified obs cluster key list, for example: [\\\"phenograph\\\"].\\n :param plot_cluster: the name list of clusters to show.\\n :param ncols: numbr of plot columns.\\n :param dot_size: marker size.\\n :param cmap: Color map.\\n :param invert_y: whether to invert y-axis.\\n ============ Return ============\\n None.\\n ============ Example ============\\n plot_cluster_umap(adata = adata)\\n \\\"\\\"\\\"\\n\\n if (isinstance(obs_key, str)):\\n obs_key = [obs_key]\\n\\n plot_cluster_result(adata, obs_key=obs_key, pos_key=\\\"X_umap\\\", plot_cluster=plot_cluster, bad_color=bad_color,\\n ncols=ncols, dot_size=dot_size, invert_y=invert_y, color_list=color_list)\\n\\n\\ndef plot_expression_difference(\\n adata: AnnData,\\n groups: Union[str, Sequence[str]] = None,\\n n_genes: int = 20,\\n key: Optional[str] = 'rank_genes_groups',\\n fontsize: int = 8,\\n ncols: int = 4,\\n sharey: bool = True,\\n show: Optional[bool] = None,\\n save: Optional[bool] = None,\\n ax: Optional[Axes] = None,\\n **kwds,\\n): # scatter plot, 差异基因显著性图，类碎石图\\n \\\"\\\"\\\"\\n Copied from scanpy and modified.\\n \\\"\\\"\\\"\\n\\n # 调整图像 panel/grid 相关参数\\n if 'n_panels_per_row' in kwds:\\n n_panels_per_row = kwds['n_panels_per_row']\\n else:\\n n_panels_per_row = ncols\\n group_names = adata.uns[key]['names'].dtype.names if groups is None else groups\\n # one panel for each group\\n # set up the figure\\n n_panels_x = min(n_panels_per_row, len(group_names))\\n n_panels_y = np.ceil(len(group_names) / n_panels_x).astype(int)\\n\\n # 初始化图像\\n width = 10\\n height = 10\\n fig = plt.figure(\\n figsize=(\\n n_panels_x * width, # rcParams['figure.figsize'][0],\\n n_panels_y * height, # rcParams['figure.figsize'][1],\\n )\\n )\\n gs = gridspec.GridSpec(nrows=n_panels_y, ncols=n_panels_x, wspace=0.22, hspace=0.3)\\n\\n ax0 = None\\n ymin = np.Inf\\n ymax = -np.Inf\\n for count, group_name in enumerate(group_names):\\n gene_names = adata.uns[key]['names'][group_name][:n_genes]\\n scores = adata.uns[key]['scores'][group_name][:n_genes]\\n\\n # Setting up axis, calculating y bounds\\n if sharey:\\n ymin = min(ymin, np.min(scores))\\n ymax = max(ymax, np.max(scores))\\n\\n if ax0 is None:\\n ax = fig.add_subplot(gs[count])\\n ax0 = ax\\n else:\\n ax = fig.add_subplot(gs[count], sharey=ax0)\\n else:\\n ymin = np.min(scores)\\n ymax = np.max(scores)\\n ymax += 0.3 * (ymax - ymin)\\n\\n ax = fig.add_subplot(gs[count])\\n ax.set_ylim(ymin, ymax)\\n\\n ax.set_xlim(-0.9, n_genes - 0.1)\\n\\n # Making labels\\n for ig, gene_name in enumerate(gene_names):\\n ax.text(\\n ig,\\n scores[ig],\\n gene_name,\\n rotation='vertical',\\n verticalalignment='bottom',\\n horizontalalignment='center',\\n fontsize=fontsize,\\n )\\n\\n ax.set_title('{} vs. {}'.format(group_name, \\\"Others\\\"))\\n if count >= n_panels_x * (n_panels_y - 1):\\n ax.set_xlabel('ranking')\\n\\n # print the 'score' label only on the first panel per row.\\n if count % n_panels_x == 0:\\n ax.set_ylabel('score')\\n\\n if sharey is True:\\n ymax += 0.3 * (ymax - ymin)\\n ax.set_ylim(ymin, ymax)\\n\\n\\ndef plot_violin_distribution(adata): # 小提琴统计图\\n \\\"\\\"\\\"\\n 绘制数据的分布小提琴图。\\n ============ Arguments ============\\n :param adata: AnnData object.\\n ============ Return ============\\n None\\n \\\"\\\"\\\"\\n _, axs = plt.subplots(1, 3, figsize=(15, 4))\\n seaborn.violinplot(y=adata.obs['total_counts'], ax=axs[0])\\n seaborn.violinplot(y=adata.obs['n_genes_by_counts'], ax=axs[1])\\n seaborn.violinplot(y=adata.obs['pct_counts_mt'], ax=axs[2])\\n\\n\\ndef plot_heatmap_maker_genes(\\n adata: AnnData = None,\\n cluster_method=\\\"phenograph\\\",\\n marker_uns_key=None,\\n num_show_gene=8,\\n show_labels=True,\\n order_cluster=True,\\n marker_clusters=None,\\n cluster_colors_array=None,\\n **kwargs\\n): # heatmap, 差异基因热图\\n \\\"\\\"\\\"\\n 绘制 Marker gene 的热图。热图中每一行代表一个 bin 的所有基因的表达量，所有的 bin 会根据所属的 cluster 进行聚集， cluster 具体展示在热图的左侧，用颜色区分。\\n ============ Arguments ============\\n :param adata: AnnData object.\\n :param cluster_methpd: method used in clustering. for example: phenograph, leiden\\n :param marker_uns_key: the key of adata.uns, the default value is \\\"marker_genes\\\"\\n :param num_show_gene: number of genes to show in each cluster.\\n :param show_labels: show gene name on axis.\\n :param order_cluster: reorder the cluster list in plot (y axis).\\n :param marker_clusters: the list of clusters to show on the heatmap.\\n :param cluster_colors_array: the list of colors in the color block on the left of heatmap.\\n ============ Return ============\\n\\n ============ Example ============\\n plot_heatmap_maker_genes(adata=adata, marker_uns_key = \\\"rank_genes_groups\\\", figsize = (20, 10))\\n \\\"\\\"\\\"\\n\\n if marker_uns_key is None:\\n marker_uns_key = 'marker_genes' # \\\"rank_genes_groups\\\" in original scanpy pipeline\\n\\n # if cluster_method is None:\\n # cluster_method = str(adata.uns[marker_uns_key]['params']['groupby'])\\n\\n # cluster_colors_array = adata.uns[\\\"phenograph_colors\\\"]\\n\\n if marker_clusters is None:\\n marker_clusters = adata.uns[marker_uns_key]['names'].dtype.names\\n\\n if not set(marker_clusters).issubset(set(adata.uns[marker_uns_key]['names'].dtype.names)):\\n marker_clusters = adata.uns[marker_uns_key]['names'].dtype.names\\n\\n gene_names_dict = {} # dict in which each cluster is the keyand the num_show_gene are the values\\n\\n for cluster in marker_clusters:\\n # get all genes that are 'non-nan'\\n genes_array = adata.uns[marker_uns_key]['names'][cluster]\\n genes_array = genes_array[~pd.isnull(genes_array)]\\n\\n if len(genes_array) == 0:\\n logger.warning(\\\"Cluster {} has no genes.\\\".format(cluster))\\n continue\\n gene_names_dict[cluster] = list(genes_array[:num_show_gene])\\n\\n adata._sanitize()\\n\\n gene_names = []\\n gene_group_labels = []\\n gene_group_positions = []\\n start = 0\\n for label, gene_list in gene_names_dict.items():\\n if isinstance(gene_list, str):\\n gene_list = [gene_list]\\n gene_names.extend(list(gene_list))\\n gene_group_labels.append(label)\\n gene_group_positions.append((start, start + len(gene_list) - 1))\\n start += len(gene_list)\\n\\n # 此处获取所有绘图所需的数据 （表达量矩阵）\\n draw_df = pd.DataFrame(index=adata.obs_names)\\n uniq_gene_names = np.unique(gene_names)\\n draw_df = pd.concat(\\n [draw_df, pd.DataFrame(adata.X[tuple([slice(None), adata.var.index.get_indexer(uniq_gene_names)])],\\n columns=uniq_gene_names, index=adata.obs_names)],\\n axis=1\\n )\\n\\n # add obs values\\n draw_df = pd.concat([draw_df, adata.obs[cluster_method]], axis=1)\\n\\n # reorder columns to given order (including duplicates keys if present)\\n draw_df = draw_df[list([cluster_method]) + list(uniq_gene_names)]\\n draw_df = draw_df[gene_names].set_index(draw_df[cluster_method].astype('category'))\\n if order_cluster:\\n draw_df = draw_df.sort_index()\\n\\n # From scanpy\\n # define a layout of 2 rows x 3 columns\\n # first row is for 'brackets' (if no brackets needed, the height of this row\\n # is zero) second row is for main content. This second row is divided into\\n # three axes:\\n # first ax is for the categories defined by `cluster_method`\\n # second ax is for the heatmap\\n # fourth ax is for colorbar\\n\\n kwargs.setdefault(\\\"figsize\\\", (10, 10))\\n kwargs.setdefault(\\\"colorbar_width\\\", 0.2)\\n colorbar_width = kwargs.get(\\\"colorbar_width\\\")\\n figsize = kwargs.get(\\\"figsize\\\")\\n\\n cluster_block_width = kwargs.setdefault(\\\"cluster_block_width\\\", 0.2) if order_cluster else 0\\n if figsize is None:\\n height = 6\\n if show_labels:\\n heatmap_width = len(gene_names) * 0.3\\n else:\\n heatmap_width = 8\\n width = heatmap_width + cluster_block_width\\n else:\\n width, height = figsize\\n heatmap_width = width - cluster_block_width\\n\\n if gene_group_positions is not None and len(gene_group_positions) > 0:\\n # add some space in case 'brackets' want to be plotted on top of the image\\n height_ratios = [0.15, height]\\n else:\\n height_ratios = [0, height]\\n\\n width_ratios = [\\n cluster_block_width,\\n heatmap_width,\\n colorbar_width,\\n ]\\n\\n fig = plt.figure(figsize=(width, height))\\n\\n axs = gridspec.GridSpec(\\n nrows=2,\\n ncols=3,\\n width_ratios=width_ratios,\\n wspace=0.15 / width,\\n hspace=0.13 / height,\\n height_ratios=height_ratios,\\n )\\n\\n heatmap_ax = fig.add_subplot(axs[1, 1])\\n\\n width, height = fig.get_size_inches()\\n max_cbar_height = 4.0\\n if height > max_cbar_height:\\n # to make the colorbar shorter, the\\n # ax is split and the lower portion is used.\\n axs2 = gridspec.GridSpecFromSubplotSpec(2, 1, subplot_spec=axs[1, 2],\\n height_ratios=[height - max_cbar_height, max_cbar_height],\\n )\\n heatmap_cbar_ax = fig.add_subplot(axs2[1])\\n else:\\n heatmap_cbar_ax = fig.add_subplot(axs[1, 2])\\n\\n heatmap(df=draw_df, ax=heatmap_ax,\\n norm=Normalize(vmin=None, vmax=None), plot_colorbar=True, colorbar_ax=heatmap_cbar_ax,\\n show_labels=True, plot_hline=True)\\n\\n if order_cluster:\\n _plot_categories_as_colorblocks(\\n fig.add_subplot(axs[1, 0]), draw_df, colors=cluster_colors_array, orientation='left'\\n )\\n\\n # plot cluster legends on top of heatmap_ax (if given)\\n if gene_group_positions is not None and len(gene_group_positions) > 0:\\n _plot_gene_groups_brackets(\\n fig.add_subplot(axs[0, 1], sharex=heatmap_ax),\\n group_positions=gene_group_positions,\\n group_labels=gene_group_labels,\\n rotation=None,\\n left_adjustment=-0.3,\\n right_adjustment=0.3,\\n )\\n\\n # plt.savefig()\\n\"\n },\n {\n \"alpha_fraction\": 0.5822505354881287,\n \"alphanum_fraction\": 0.5927923321723938,\n \"avg_line_length\": 32.99166488647461,\n \"blob_id\": \"a8e3e35c6156f10d95e13736868dfb21b8d5ee67\",\n \"content_id\": \"3526ea0c74b7e911d1ee4dc7c4cc474d0dd5b8eb\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 4087,\n \"license_type\": \"permissive\",\n \"max_line_length\": 117,\n \"num_lines\": 120,\n \"path\": \"/stereo/tools/cluster.py\",\n \"repo_name\": \"leying95/stereopy\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#!/usr/bin/env python3\\n# coding: utf-8\\n\\\"\\\"\\\"\\n@author: Ping Qiu qiuping1@genomics.cn\\n@last modified by: Ping Qiu\\n@file:cluster.py\\n@time:2021/03/19\\n\\\"\\\"\\\"\\nimport leidenalg as la\\nfrom sklearn.decomposition import PCA\\nfrom scipy.sparse import coo_matrix\\nfrom sklearn.neighbors import NearestNeighbors\\nimport igraph as ig\\nimport numpy as np\\nfrom umap.umap_ import fuzzy_simplicial_set\\n\\n\\nclass Neighbors(object):\\n def __init__(self, x, n_neighbors):\\n self.x = x\\n self.n_neighbors = n_neighbors\\n\\n def find_n_neighbors(self):\\n nbrs = NearestNeighbors(n_neighbors=self.n_neighbors + 1, algorithm='ball_tree').fit(self.x)\\n dists, indices = nbrs.kneighbors(self.x)\\n nn_idx = indices[:, 1:]\\n nn_dist = dists[:, 1:]\\n return nn_idx, nn_dist\\n\\n def get_igraph_from_knn(self, nn_idx, nn_dist):\\n j = nn_idx.ravel().astype(int)\\n dist = nn_dist.ravel()\\n i = np.repeat(np.arange(nn_idx.shape[0]), self.n_neighbors)\\n\\n vertex = list(range(nn_dist.shape[0]))\\n edges = list(tuple(zip(i, j)))\\n G = ig.Graph()\\n G.add_vertices(vertex)\\n G.add_edges(edges)\\n G.es['weight'] = dist\\n return G\\n\\n def get_parse_distances(self, nn_idx, nn_dist):\\n n_obs = self.x.shape[0]\\n rows = np.zeros((n_obs * self.n_neighbors), dtype=np.int64)\\n cols = np.zeros((n_obs * self.n_neighbors), dtype=np.int64)\\n vals = np.zeros((n_obs * self.n_neighbors), dtype=np.float64)\\n\\n for i in range(nn_idx.shape[0]):\\n for j in range(self.n_neighbors):\\n if nn_idx[i, j] == -1:\\n continue # We didn't get the full knn for i\\n if nn_idx[i, j] == i:\\n val = 0.0\\n else:\\n val = nn_dist[i, j]\\n\\n rows[i * self.n_neighbors + j] = i\\n cols[i * self.n_neighbors + j] = nn_idx[i, j]\\n vals[i * self.n_neighbors + j] = val\\n\\n distances = coo_matrix((vals, (rows, cols)), shape=(n_obs, n_obs))\\n distances.eliminate_zeros()\\n return distances.tocsr()\\n\\n def get_connectivities(self, nn_idx, nn_dist):\\n n_obs = self.x.shape[0]\\n x = coo_matrix(([], ([], [])), shape=(n_obs, 1))\\n connectivities = fuzzy_simplicial_set(x, self.n_neighbors, None, None, knn_indices=nn_idx, knn_dists=nn_dist,\\n set_op_mix_ratio=1.0, local_connectivity=1.0)\\n if isinstance(connectivities, tuple):\\n connectivities = connectivities[0]\\n return connectivities.tocsr()\\n\\n\\ndef run_neighbors(x, neighbors=30):\\n neighbor = Neighbors(x, neighbors)\\n nn_idx, nn_dist = neighbor.find_n_neighbors()\\n return neighbor, nn_idx, nn_dist\\n\\n\\ndef run_louvain(x, neighbor, nn_idx, nn_dist):\\n g = neighbor.get_igraph_from_knn(nn_idx, nn_dist)\\n louvain_partition = g.community_multilevel(weights=g.es['weight'], return_levels=False)\\n clusters = np.arange(x.shape[0])\\n for i in range(len(louvain_partition)):\\n clusters[louvain_partition[i]] = str(i)\\n return clusters\\n\\n\\ndef run_knn_leiden(x, neighbor, nn_idx, nn_dist, diff=1):\\n g = neighbor.get_igraph_from_knn(nn_idx, nn_dist)\\n optimiser = la.Optimiser()\\n leiden_partition = la.ModularityVertexPartition(g, weights=g.es['weight'])\\n while diff > 0:\\n diff = optimiser.optimise_partition(leiden_partition, n_iterations=10)\\n clusters = np.arange(x.shape[0])\\n for i in range(len(leiden_partition)):\\n clusters[leiden_partition[i]] = str(i)\\n return clusters\\n\\n\\ndef run_cluster(x, method='leiden', do_pca=True, n_pcs=30):\\n \\\"\\\"\\\"\\n :param x: np.array, shape: (m, n)，m个bin， n为embedding\\n :param method:\\n :param do_pca:\\n :param n_pcs:\\n :return:\\n \\\"\\\"\\\"\\n if do_pca:\\n pca_obj = PCA(n_components=n_pcs)\\n x = pca_obj.fit_transform(x)\\n\\n neighbor, nn_idx, nn_dist = run_neighbors(x)\\n if method == 'leiden':\\n cluster = run_knn_leiden(x, neighbor, nn_idx, nn_dist)\\n else:\\n cluster = run_louvain(x, neighbor, nn_idx, nn_dist)\\n return cluster\\n\"\n },\n {\n \"alpha_fraction\": 0.5596755146980286,\n \"alphanum_fraction\": 0.5709463357925415,\n \"avg_line_length\": 36.02822494506836,\n \"blob_id\": \"e7cc0ef7656786a8185b9d2de04832ad295a73f2\",\n \"content_id\": \"f68ab32909c095d79527096c45e06fecb5e95b9b\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 18936,\n \"license_type\": \"permissive\",\n \"max_line_length\": 158,\n \"num_lines\": 496,\n \"path\": \"/stereo/plots/plots.py\",\n \"repo_name\": \"leying95/stereopy\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#!/usr/bin/env python3\\n# coding: utf-8\\n\\\"\\\"\\\"\\n@author: Ping Qiu qiuping1@genomics.cn\\n@last modified by: Ping Qiu\\n@file:plots.py\\n@time:2021/03/31\\n\\\"\\\"\\\"\\nfrom matplotlib.cm import get_cmap\\nimport matplotlib.pyplot as plt\\nfrom matplotlib.colors import ListedColormap, to_hex, Normalize\\nfrom matplotlib import gridspec\\nfrom ._plot_basic.get_stereo_data import get_cluster_res, get_reduce_x, get_position_array, get_degs_res\\nimport numpy as np\\nimport pandas as pd\\nfrom anndata import AnnData\\nfrom ._plot_basic.scatter_plt import scatter\\nimport seaborn\\nfrom typing import Optional, Sequence, Union\\nfrom matplotlib.axes import Axes\\nfrom ._plot_basic.heatmap_plt import heatmap, plot_categories_as_colorblocks, plot_gene_groups_brackets\\nfrom ..log_manager import logger\\nfrom scipy.sparse import issparse\\n\\n\\ndef plot_spatial_cluster(\\n adata: AnnData,\\n obs_key: list = [\\\"phenograph\\\"],\\n pos_key: str = \\\"spatial\\\",\\n plot_cluster: list = None,\\n bad_color: str = \\\"lightgrey\\\",\\n ncols: int = 2,\\n dot_size: int = None,\\n color_list=['violet', 'turquoise', 'tomato', 'teal','tan', 'silver', 'sienna', 'red', 'purple', 'plum', 'pink',\\n 'orchid', 'orangered', 'orange', 'olive', 'navy', 'maroon', 'magenta', 'lime',\\n 'lightgreen', 'lightblue', 'lavender', 'khaki', 'indigo', 'grey', 'green', 'gold', 'fuchsia',\\n 'darkgreen', 'darkblue', 'cyan', 'crimson', 'coral', 'chocolate', 'chartreuse', 'brown', 'blue', 'black',\\n 'beige', 'azure', 'aquamarine', 'aqua',\\n ],\\n): # scatter plot, 聚类后表达矩阵空间分布\\n \\\"\\\"\\\"\\n Plot spatial distribution of specified obs data.\\n ============ Arguments ============\\n :param adata: AnnData object.\\n :param obs_key: specified obs cluster key list, for example: [\\\"phenograph\\\"].\\n :param pos_key: the coordinates of data points for scatter plots. the data points are stored in adata.obsm[pos_key]. choice: \\\"spatial\\\", \\\"X_umap\\\", \\\"X_pca\\\".\\n :param plot_cluster: the name list of clusters to show.\\n :param bad_color: the name list of clusters to show.\\n :param ncols: numbr of plot columns.\\n :param dot_size: marker size.\\n :param color_list: whether to invert y-axis.\\n ============ Return ============\\n None.\\n ============ Example ============\\n plot_spatial_cluster(adata = adata)\\n \\\"\\\"\\\"\\n # sc.pl.embedding(adata, basis=\\\"spatial\\\", color=[\\\"total_counts\\\", \\\"n_genes_by_counts\\\"],size=30)\\n\\n if dot_size is None:\\n dot_size = 120000 / adata.shape[0]\\n\\n ncols = min(ncols, len(obs_key))\\n nrows = np.ceil(len(obs_key) / ncols).astype(int)\\n # each panel will have the size of rcParams['figure.figsize']\\n fig = plt.figure(figsize=(ncols * 10, nrows * 8))\\n left = 0.2 / ncols\\n bottom = 0.13 / nrows\\n axs = gridspec.GridSpec(\\n nrows=nrows,\\n ncols=ncols,\\n left=left,\\n right=1 - (ncols - 1) * left - 0.01 / ncols,\\n bottom=bottom,\\n top=1 - (nrows - 1) * bottom - 0.1 / nrows,\\n # hspace=hspace,\\n # wspace=wspace,\\n )\\n\\n if color_list is None:\\n cmap = get_cmap()\\n else:\\n cmap = ListedColormap(color_list)\\n cmap.set_bad(bad_color)\\n # 把特定值改为 np.nan 之后，可以利用 cmap.set_bad(\\\"white\\\") 来遮盖掉这部分数据\\n\\n for i, key in enumerate(obs_key):\\n # color_data = adata.obs_vector(key) # TODO replace by get_cluster_res\\n color_data = get_cluster_res(adata, data_key=key)\\n pc_logic = False\\n\\n # color_data = np.asarray(color_data_raw, dtype=float)\\n order = np.argsort(~pd.isnull(color_data), kind=\\\"stable\\\")\\n# spatial_data = np.array(adata.obsm[pos_key])[:, 0: 2]\\n spatial_data = get_reduce_x(data=adata, data_key=pos_key)[:, 0:2] if pos_key != 'spatial' \\\\\\n else get_position_array(adata, pos_key)\\n color_data = color_data[order]\\n spatial_data = spatial_data[order, :]\\n\\n color_dict = {}\\n has_na = False\\n if pd.api.types.is_categorical_dtype(color_data):\\n pc_logic = True\\n if plot_cluster is None:\\n plot_cluster = list(color_data.categories)\\n if pc_logic:\\n cluster_n = len(np.unique(color_data))\\n if len(color_list) < cluster_n:\\n color_list = color_list * cluster_n\\n cmap = ListedColormap(color_list)\\n cmap.set_bad(bad_color)\\n if len(color_data.categories) > len(plot_cluster):\\n color_data = color_data.replace(color_data.categories.difference(plot_cluster), np.nan)\\n has_na = True\\n color_dict = {str(k): to_hex(v) for k, v in enumerate(color_list)}\\n print(color_dict)\\n color_data = color_data.map(color_dict)\\n if pd.api.types.is_categorical_dtype(color_data):\\n color_data = pd.Categorical(color_data)\\n if has_na:\\n color_data = color_data.add_categories([to_hex(bad_color)])\\n color_data = color_data.fillna(to_hex(bad_color))\\n # color_dict[\\\"NA\\\"]\\n\\n # color_data 是图像中各个点的值，也对应了每个点的颜色。data_points则对应了各个点的坐标\\n ax = fig.add_subplot(axs[i]) # ax = plt.subplot(axs[i]) || ax = fig.add_subplot(axs[1, 1]))\\n ax.set_title(key)\\n ax.set_yticks([])\\n ax.set_xticks([])\\n ax.set_xlabel(\\\"spatial1\\\")\\n ax.set_ylabel(\\\"spatial2\\\")\\n pathcollection = scatter(\\n spatial_data[:, 0],\\n spatial_data[:, 1],\\n ax=ax,\\n marker=\\\".\\\",\\n dot_colors=color_data,\\n dot_size=dot_size\\n )\\n if pc_logic:\\n box = ax.get_position()\\n ax.set_position([box.x0, box.y0, box.width * 0.91, box.height])\\n # -------------modified by qiuping1@genomics.cn-------------\\n # valid_cate = color_data.categories\\n # cat_num = len(adata.obs_vector(key).categories)\\n # for label in adata.obs_vector(key).categories:\\n categories = get_cluster_res(adata, data_key=key).categories\\n cat_num = len(categories)\\n for label in categories:\\n # --------modified end------------------\\n ax.scatter([], [], c=color_dict[label], label=label)\\n ax.legend(\\n frameon=False,\\n loc='center left',\\n bbox_to_anchor=(1, 0.5),\\n ncol=(1 if cat_num <= 14 else 2 if cat_num <= 30 else 3),\\n # fontsize=legend_fontsize,\\n )\\n else:\\n plt.colorbar(pathcollection, ax=ax, pad=0.01, fraction=0.08, aspect=30)\\n ax.autoscale_view()\\n\\n\\ndef plot_violin_distribution(adata): # 小提琴统计图\\n \\\"\\\"\\\"\\n 绘制数据的分布小提琴图。\\n ============ Arguments ============\\n :param adata: AnnData object.\\n ============ Return ============\\n None\\n \\\"\\\"\\\"\\n _, axs = plt.subplots(1, 3, figsize=(15, 4))\\n seaborn.violinplot(y=adata.obs['total_counts'], ax=axs[0])\\n seaborn.violinplot(y=adata.obs['n_genes_by_counts'], ax=axs[1])\\n seaborn.violinplot(y=adata.obs['pct_counts_mt'], ax=axs[2])\\n\\n\\ndef plot_degs(\\n adata: AnnData,\\n groups: Union[str, Sequence[str]] = 'all',\\n n_genes: int = 20,\\n key: Optional[str] = 'find_marker',\\n fontsize: int = 8,\\n ncols: int = 4,\\n sharey: bool = True,\\n ax: Optional[Axes] = None,\\n **kwds,\\n): # scatter plot, 差异基因显著性图，类碎石图\\n \\\"\\\"\\\"\\n Copied from scanpy and modified.\\n \\\"\\\"\\\"\\n\\n # 调整图像 panel/grid 相关参数\\n if 'n_panels_per_row' in kwds:\\n n_panels_per_row = kwds['n_panels_per_row']\\n else:\\n n_panels_per_row = ncols\\n # group_names = adata.uns[key]['names'].dtype.names if groups is None else groups\\n if groups == 'all':\\n group_names = list(adata.uns[key].keys())\\n else:\\n group_names = [groups] if isinstance(groups, str) else groups\\n # one panel for each group\\n # set up the figure\\n n_panels_x = min(n_panels_per_row, len(group_names))\\n n_panels_y = np.ceil(len(group_names) / n_panels_x).astype(int)\\n # 初始化图像\\n width = 10\\n height = 10\\n fig = plt.figure(\\n figsize=(\\n n_panels_x * width, # rcParams['figure.figsize'][0],\\n n_panels_y * height, # rcParams['figure.figsize'][1],\\n )\\n )\\n gs = gridspec.GridSpec(nrows=n_panels_y, ncols=n_panels_x, wspace=0.22, hspace=0.3)\\n\\n ax0 = None\\n ymin = np.Inf\\n ymax = -np.Inf\\n for count, group_name in enumerate(group_names):\\n result = get_degs_res(adata, data_key=key, group_key=group_name, top_k=n_genes)\\n gene_names = result.genes.values\\n scores = result.scores.values\\n # Setting up axis, calculating y bounds\\n if sharey:\\n ymin = min(ymin, np.min(scores))\\n ymax = max(ymax, np.max(scores))\\n\\n if ax0 is None:\\n ax = fig.add_subplot(gs[count])\\n ax0 = ax\\n else:\\n ax = fig.add_subplot(gs[count], sharey=ax0)\\n else:\\n ymin = np.min(scores)\\n ymax = np.max(scores)\\n ymax += 0.3 * (ymax - ymin)\\n\\n ax = fig.add_subplot(gs[count])\\n ax.set_ylim(ymin, ymax)\\n\\n ax.set_xlim(-0.9, n_genes - 0.1)\\n\\n # Making labels\\n for ig, gene_name in enumerate(gene_names):\\n ax.text(\\n ig,\\n scores[ig],\\n gene_name,\\n rotation='vertical',\\n verticalalignment='bottom',\\n horizontalalignment='center',\\n fontsize=fontsize,\\n )\\n\\n ax.set_title(group_name)\\n if count >= n_panels_x * (n_panels_y - 1):\\n ax.set_xlabel('ranking')\\n\\n # print the 'score' label only on the first panel per row.\\n if count % n_panels_x == 0:\\n ax.set_ylabel('score')\\n\\n if sharey is True:\\n ymax += 0.3 * (ymax - ymin)\\n ax.set_ylim(ymin, ymax)\\n\\n\\ndef plot_spatial_distribution(\\n adata: AnnData,\\n obs_key: list = [\\\"total_counts\\\", \\\"n_genes_by_counts\\\"],\\n ncols=2,\\n dot_size=None,\\n color_list=None,\\n invert_y=False\\n): # scatter plot, 表达矩阵空间分布\\n \\\"\\\"\\\"\\n Plot spatial distribution of specified obs data.\\n ============ Arguments ============\\n :param adata: AnnData object.\\n :param obs_key: specified obs key list, for example: [\\\"total_counts\\\", \\\"n_genes_by_counts\\\"]\\n :param ncols: numbr of plot columns.\\n :param dot_size: marker size.\\n :param color_list: Color list.\\n :param invert_y: whether to invert y-axis.\\n ============ Return ============\\n None\\n ============ Example ============\\n plot_spatial_distribution(adata=adata)\\n \\\"\\\"\\\"\\n # sc.pl.embedding(adata, basis=\\\"spatial\\\", color=[\\\"total_counts\\\", \\\"n_genes_by_counts\\\"],size=30)\\n\\n if dot_size is None:\\n dot_size = 120000 / adata.shape[0]\\n\\n ncols = min(ncols, len(obs_key))\\n nrows = np.ceil(len(obs_key) / ncols).astype(int)\\n # each panel will have the size of rcParams['figure.figsize']\\n fig = plt.figure(figsize=(ncols * 10, nrows * 8))\\n left = 0.2 / ncols\\n bottom = 0.13 / nrows\\n axs = gridspec.GridSpec(\\n nrows=nrows,\\n ncols=ncols,\\n left=left,\\n right=1 - (ncols - 1) * left - 0.01 / ncols,\\n bottom=bottom,\\n top=1 - (nrows - 1) * bottom - 0.1 / nrows,\\n # hspace=hspace,\\n # wspace=wspace,\\n )\\n\\n if color_list is None:\\n cmap = get_cmap()\\n else:\\n cmap = ListedColormap(color_list)\\n # 把特定值改为 np.nan 之后，可以利用 cmap.set_bad(\\\"white\\\") 来遮盖掉这部分数据\\n\\n # 散点图上每个点的坐标数据来自于 adata 的 obsm[\\\"spatial\\\"]，每个点的颜色（数值）数据来自于 adata 的 obs_vector()\\n for i, key in enumerate(obs_key):\\n # color_data = np.asarray(adata.obs_vector(key), dtype=float)\\n color_data = adata.obs_vector(key)\\n order = np.argsort(~pd.isnull(color_data), kind=\\\"stable\\\")\\n spatial_data = np.array(adata.obsm[\\\"spatial\\\"])[:, 0: 2]\\n color_data = color_data[order]\\n spatial_data = spatial_data[order, :]\\n\\n # color_data 是图像中各个点的值，也对应了每个点的颜色。data_points则对应了各个点的坐标\\n ax = fig.add_subplot(axs[i]) # ax = plt.subplot(axs[i]) || ax = fig.add_subplot(axs[1, 1]))\\n ax.set_title(key)\\n ax.set_yticks([])\\n ax.set_xticks([])\\n ax.set_xlabel(\\\"spatial1\\\")\\n ax.set_ylabel(\\\"spatial2\\\")\\n pathcollection = scatter(\\n spatial_data[:, 0],\\n spatial_data[:, 1],\\n ax=ax,\\n marker=\\\".\\\",\\n dot_colors=color_data,\\n dot_size=dot_size,\\n cmap=cmap,\\n )\\n plt.colorbar(\\n pathcollection,\\n ax=ax,\\n pad=0.01,\\n fraction=0.08,\\n aspect=30,\\n )\\n ax.autoscale_view()\\n if invert_y:\\n ax.invert_yaxis()\\n\\n\\ndef plot_heatmap_maker_genes(\\n adata: AnnData = None,\\n cluster_method=\\\"phenograph\\\",\\n marker_uns_key=None,\\n num_show_gene=8,\\n show_labels=True,\\n order_cluster=True,\\n marker_clusters=None,\\n cluster_colors_array=None,\\n **kwargs\\n): # heatmap, 差异基因热图\\n \\\"\\\"\\\"\\n 绘制 Marker gene 的热图。热图中每一行代表一个 bin 的所有基因的表达量，所有的 bin 会根据所属的 cluster 进行聚集， cluster 具体展示在热图的左侧，用颜色区分。\\n ============ Arguments ============\\n :param adata: AnnData object.\\n :param cluster_method: method used in clustering. for example: phenograph, leiden\\n :param marker_uns_key: the key of adata.uns, the default value is \\\"marker_genes\\\"\\n :param num_show_gene: number of genes to show in each cluster.\\n :param show_labels: show gene name on axis.\\n :param order_cluster: reorder the cluster list in plot (y axis).\\n :param marker_clusters: the list of clusters to show on the heatmap.\\n :param cluster_colors_array: the list of colors in the color block on the left of heatmap.\\n ============ Return ============\\n\\n ============ Example ============\\n plot_heatmap_maker_genes(adata=adata, marker_uns_key = \\\"rank_genes_groups\\\", figsize = (20, 10))\\n \\\"\\\"\\\"\\n if marker_uns_key is None:\\n marker_uns_key = 'marker_genes' # \\\"rank_genes_groups\\\" in original scanpy pipeline\\n marker_res = adata.uns[marker_uns_key]\\n default_cluster = [i for i in marker_res.keys()]\\n if marker_clusters is None:\\n marker_clusters = default_cluster\\n if not set(marker_clusters).issubset(set(default_cluster)):\\n marker_clusters = default_cluster\\n\\n gene_names_dict = {} # dict in which each cluster is the keyand the num_show_gene are the values\\n\\n for cluster in marker_clusters:\\n top_marker = marker_res[cluster].top_k_marker(top_k_genes=num_show_gene, sort_key='scores')\\n genes_array = top_marker['genes'].values\\n if len(genes_array) == 0:\\n logger.warning(\\\"Cluster {} has no genes.\\\".format(cluster))\\n continue\\n gene_names_dict[cluster] = genes_array\\n gene_names = []\\n gene_group_labels = []\\n gene_group_positions = []\\n start = 0\\n for label, gene_list in gene_names_dict.items():\\n if isinstance(gene_list, str):\\n gene_list = [gene_list]\\n gene_names.extend(list(gene_list))\\n gene_group_labels.append(label)\\n gene_group_positions.append((start, start + len(gene_list) - 1))\\n start += len(gene_list)\\n\\n # 此处获取所有绘图所需的数据 （表达量矩阵）\\n uniq_gene_names = np.unique(gene_names)\\n exp_matrix = adata.X.toarray() if issparse(adata.X) else adata.X\\n draw_df = pd.DataFrame(exp_matrix[:, adata.var.index.get_indexer(uniq_gene_names)],\\n columns=uniq_gene_names, index=adata.obs_names)\\n # add obs values\\n cluster_data = adata.uns[cluster_method].cluster.set_index('bins')\\n draw_df = pd.concat([draw_df, cluster_data], axis=1)\\n draw_df = draw_df[gene_names].set_index(draw_df['cluster'].astype('category'))\\n if order_cluster:\\n draw_df = draw_df.sort_index()\\n kwargs.setdefault(\\\"figsize\\\", (10, 10))\\n kwargs.setdefault(\\\"colorbar_width\\\", 0.2)\\n colorbar_width = kwargs.get(\\\"colorbar_width\\\")\\n figsize = kwargs.get(\\\"figsize\\\")\\n\\n cluster_block_width = kwargs.setdefault(\\\"cluster_block_width\\\", 0.2) if order_cluster else 0\\n if figsize is None:\\n height = 6\\n if show_labels:\\n heatmap_width = len(gene_names) * 0.3\\n else:\\n heatmap_width = 8\\n width = heatmap_width + cluster_block_width\\n else:\\n width, height = figsize\\n heatmap_width = width - cluster_block_width\\n\\n if gene_group_positions is not None and len(gene_group_positions) > 0:\\n # add some space in case 'brackets' want to be plotted on top of the image\\n height_ratios = [0.15, height]\\n else:\\n height_ratios = [0, height]\\n\\n width_ratios = [\\n cluster_block_width,\\n heatmap_width,\\n colorbar_width,\\n ]\\n\\n fig = plt.figure(figsize=(width, height))\\n\\n axs = gridspec.GridSpec(\\n nrows=2,\\n ncols=3,\\n width_ratios=width_ratios,\\n wspace=0.15 / width,\\n hspace=0.13 / height,\\n height_ratios=height_ratios,\\n )\\n\\n heatmap_ax = fig.add_subplot(axs[1, 1])\\n\\n width, height = fig.get_size_inches()\\n max_cbar_height = 4.0\\n if height > max_cbar_height:\\n # to make the colorbar shorter, the\\n # ax is split and the lower portion is used.\\n axs2 = gridspec.GridSpecFromSubplotSpec(2, 1, subplot_spec=axs[1, 2],\\n height_ratios=[height - max_cbar_height, max_cbar_height],\\n )\\n heatmap_cbar_ax = fig.add_subplot(axs2[1])\\n else:\\n heatmap_cbar_ax = fig.add_subplot(axs[1, 2])\\n\\n heatmap(df=draw_df, ax=heatmap_ax,\\n norm=Normalize(vmin=None, vmax=None), plot_colorbar=True, colorbar_ax=heatmap_cbar_ax,\\n show_labels=True, plot_hline=True)\\n\\n if order_cluster:\\n plot_categories_as_colorblocks(\\n fig.add_subplot(axs[1, 0]), draw_df, colors=cluster_colors_array, orientation='left'\\n )\\n\\n # plot cluster legends on top of heatmap_ax (if given)\\n if gene_group_positions is not None and len(gene_group_positions) > 0:\\n plot_gene_groups_brackets(\\n fig.add_subplot(axs[0, 1], sharex=heatmap_ax),\\n group_positions=gene_group_positions,\\n group_labels=gene_group_labels,\\n rotation=None,\\n left_adjustment=-0.3,\\n right_adjustment=0.3,\\n )\\n\"\n },\n {\n \"alpha_fraction\": 0.6450777053833008,\n \"alphanum_fraction\": 0.6709844470024109,\n \"avg_line_length\": 19.3157901763916,\n \"blob_id\": \"e0b8821e51448972842b0596d7ba29c224772cd5\",\n \"content_id\": \"6e56426ee185d43f05f283d62f55808b97650c56\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 386,\n \"license_type\": \"permissive\",\n \"max_line_length\": 53,\n \"num_lines\": 19,\n \"path\": \"/stereo/utils/__init__.py\",\n \"repo_name\": \"leying95/stereopy\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#!/usr/bin/env python3\\n# coding: utf-8\\n\\\"\\\"\\\"\\n@author: Ping Qiu qiuping1@genomics.cn\\n@last modified by: Ping Qiu\\n@file:__init__.py.py\\n@time:2021/03/05\\n\\\"\\\"\\\"\\nimport shutil\\nimport os\\nfrom .correlation import pearson_corr, spearmanr_corr\\nfrom .data_helper import select_group\\n\\n\\ndef remove_file(path):\\n if os.path.isfile(path):\\n os.remove(path)\\n if os.path.isdir(path):\\n shutil.rmtree(path)\\n\"\n },\n {\n \"alpha_fraction\": 0.6289620995521545,\n \"alphanum_fraction\": 0.6656308174133301,\n \"avg_line_length\": 31.836734771728516,\n \"blob_id\": \"929008472630fdf635cba821106fb912cf41f0c5\",\n \"content_id\": \"d99b946e6893eb24287dce6f23965fb054385454\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1609,\n \"license_type\": \"permissive\",\n \"max_line_length\": 112,\n \"num_lines\": 49,\n \"path\": \"/stereo/utils/correlation.py\",\n \"repo_name\": \"leying95/stereopy\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#!/usr/bin/env python3\\n# coding: utf-8\\n\\\"\\\"\\\"\\n@author: Ping Qiu qiuping1@genomics.cn\\n@last modified by: Ping Qiu\\n@file:correlation.py\\n@time:2021/03/11\\n\\\"\\\"\\\"\\nimport numpy as np\\nimport pandas as pd\\nfrom scipy import stats\\n\\n\\ndef pearson(arr1, arr2):\\n \\\"\\\"\\\"\\n calculate pearson correlation between two numpy arrays.\\n :param arr1: one array, the feature is a column. the shape is `m * n`\\n :param arr2: the other array, the feature is a column. the shape is `m * k`\\n :return: a pearson score np.array , the shape is `k * n`\\n \\\"\\\"\\\"\\n assert arr1.shape[0] == arr2.shape[0]\\n n = arr1.shape[0]\\n sums = np.multiply.outer(arr2.sum(0), arr1.sum(0))\\n stds = np.multiply.outer(arr2.std(0), arr1.std(0))\\n return (arr2.T.dot(arr1) - sums / n) / stds / n\\n\\n\\ndef pearson_corr(df1, df2):\\n \\\"\\\"\\\"\\n calculate pearson correlation between two dataframes.\\n :param df1: one dataframe\\n :param df2: the other dataframe\\n :return: a pearson score dataframe, the index is the columns of `df1`, the columns is the columns of `df2`\\n \\\"\\\"\\\"\\n v1, v2 = df1.values, df2.values\\n corr_matrix = pearson(v1, v2)\\n return pd.DataFrame(corr_matrix, df2.columns, df1.columns)\\n\\n\\ndef spearmanr_corr(df1, df2):\\n \\\"\\\"\\\"\\n calculate pearson correlation between two dataframes.\\n :param df1: one dataframe\\n :param df2: the other dataframe\\n :return: a spearmanr score dataframe, the index is the columns of `df1`, the columns is the columns of `df2`\\n \\\"\\\"\\\"\\n score, pvalue = stats.spearmanr(df1.values, df2.values)\\n score = score[df1.shape[1]:, 0:df1.shape[1]]\\n return pd.DataFrame(score, df2.columns, df1.columns)\\n\"\n },\n {\n \"alpha_fraction\": 0.5926466584205627,\n \"alphanum_fraction\": 0.5964400172233582,\n \"avg_line_length\": 35.07368469238281,\n \"blob_id\": \"88d22d27b7f2d3e25e5c1a50cc04b09fd00b9a0c\",\n \"content_id\": \"dd127ef9b878183a451a018bf664e3130c5144eb\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 3427,\n \"license_type\": \"permissive\",\n \"max_line_length\": 118,\n \"num_lines\": 95,\n \"path\": \"/stereo/core/stereo_result.py\",\n \"repo_name\": \"leying95/stereopy\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#!/usr/bin/env python3\\n# coding: utf-8\\n\\\"\\\"\\\"\\n@author: Ping Qiu qiuping1@genomics.cn\\n@last modified by: Ping Qiu\\n@file:stereo_result.py\\n@time:2021/03/18\\n\\\"\\\"\\\"\\nfrom typing import Optional\\nimport numpy as np\\nimport pandas as pd\\nfrom ..log_manager import logger\\n\\n\\nclass StereoResult(object):\\n def __init__(self, name: str = 'stereo', param: Optional[dict] = None):\\n self.name = name\\n self.params = {} if param is None else param\\n\\n def update_params(self, v):\\n self.params = v\\n\\n def __str__(self):\\n class_info = f'{self.__class__.__name__} of {self.name}. \\\\n'\\n class_info += f' params: {self.params}\\\\n'\\n return class_info\\n\\n def __repr__(self):\\n return self.__str__()\\n\\n\\nclass DimReduceResult(StereoResult):\\n def __init__(self, name: str = 'dim_reduce', param: Optional[dict] = None, x_reduce: Optional[np.ndarray] = None,\\n variance_pca: Optional[np.ndarray] = None, variance_ratio: Optional[np.ndarray] = None,\\n pcs: Optional[np.ndarray] = None):\\n super(DimReduceResult, self).__init__(name, param)\\n self.x_reduce = x_reduce\\n self.variance_pca = variance_pca\\n self.variance_ratio = variance_ratio\\n self.pcs = pcs\\n\\n\\nclass FindMarkerResult(StereoResult):\\n def __init__(self, name: str = 'find_marker', param: Optional[dict] = None,\\n degs_data: Optional[pd.DataFrame] = None):\\n super(FindMarkerResult, self).__init__(name, param)\\n self.degs_data = degs_data\\n\\n def __str__(self):\\n info = super(FindMarkerResult, self).__str__()\\n if self.degs_data is not None:\\n info += f' result: a DataFrame which has `genes`,`pvalues`,`pvalues_adj`, `log2fc`, `score` columns.\\\\n'\\n info += f' the shape is: {self.degs_data.shape}'\\n return info\\n\\n def top_k_marker(self, top_k_genes=10, sort_key='pvalues', ascend=False):\\n \\\"\\\"\\\"\\n obtain the first k significantly different genes\\n :param top_k_genes: the number of top k\\n :param sort_key: sort by the column\\n :param ascend: the ascend order of sorting.\\n :return:\\n \\\"\\\"\\\"\\n if self.degs_data is not None:\\n top_k_data = self.degs_data.sort_values(by=sort_key, ascending=ascend).head(top_k_genes)\\n return top_k_data\\n else:\\n logger.warning('the result of degs is None, return None.')\\n return None\\n\\n\\nclass CellTypeResult(StereoResult):\\n def __init__(self, name='cell_type_anno', param=None, anno_data=None):\\n super(CellTypeResult, self).__init__(name=name, param=param)\\n self.anno_data = anno_data\\n\\n def __str__(self):\\n info = super(CellTypeResult, self).__str__()\\n if self.anno_data is not None:\\n info += f' result: a DataFrame which has `cells`,`cell type`,`corr_score` columns.\\\\n'\\n info += f' the shape is: {self.anno_data.shape}'\\n return info\\n\\n\\nclass ClusterResult(StereoResult):\\n def __init__(self, name='cluster', param=None, cluster_info=None):\\n super(ClusterResult, self).__init__(name=name, param=param)\\n self.cluster = cluster_info\\n\\n def __str__(self):\\n info = super(ClusterResult, self).__str__()\\n if self.cluster is not None:\\n info += f' result: a DataFrame which has `cells`,`cluster` columns.\\\\n'\\n info += f' the shape is: {self.cluster.shape}'\\n return info\\n\"\n },\n {\n \"alpha_fraction\": 0.5367646813392639,\n \"alphanum_fraction\": 0.6102941036224365,\n \"avg_line_length\": 16,\n \"blob_id\": \"91821cce15c5c57d0d9f7879ebe521c065656519\",\n \"content_id\": \"726bfa3d8ddd4c38dd355f36eb882616ac52e353\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 136,\n \"license_type\": \"permissive\",\n \"max_line_length\": 25,\n \"num_lines\": 8,\n \"path\": \"/stereo/core/__init__.py\",\n \"repo_name\": \"leying95/stereopy\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#!/usr/bin/env python3\\n# coding: utf-8\\n\\\"\\\"\\\"\\n@author: Ping Qiu qiuping1@genomics.cn\\n@last modified by: Ping Qiu\\n@file:__init__.py.py\\n@time:2021/03/17\\n\\\"\\\"\\\"\\n\"\n },\n {\n \"alpha_fraction\": 0.5546501278877258,\n \"alphanum_fraction\": 0.5627103447914124,\n \"avg_line_length\": 31.63005828857422,\n \"blob_id\": \"c3432564975ba70a1548330bb225b99d38d4b4bf\",\n \"content_id\": \"050413ffad7b852cc1e8d0feae37c28313c3be0a\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 11290,\n \"license_type\": \"permissive\",\n \"max_line_length\": 101,\n \"num_lines\": 346,\n \"path\": \"/stereo/plots/_plot_basic/heatmap_plt.py\",\n \"repo_name\": \"leying95/stereopy\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#!/usr/bin/env python3\\n# coding: utf-8\\n\\\"\\\"\\\"\\n@author: Shixu He heshixu@genomics.cn\\n@last modified by: Shixu He\\n@file:heatmap_plt.py\\n@time:2021/03/15\\n\\\"\\\"\\\"\\n\\nfrom matplotlib.cm import get_cmap\\nfrom matplotlib.axes import Axes\\nimport matplotlib.pyplot as plt\\nfrom matplotlib.colors import Normalize\\nfrom matplotlib import gridspec\\n\\nfrom anndata import AnnData\\nimport numpy as np\\nimport pandas as pd\\n\\nfrom typing import List, Iterable, Sequence, Optional, Tuple\\nfrom typing_extensions import Literal\\n\\nfrom ...log_manager import logger\\n\\n\\ndef heatmap(df: pd.DataFrame = None, ax: Axes = None, cmap=None, norm=None, plot_colorbar=False,\\n colorbar_ax: Axes = None, show_labels=True, plot_hline=False, **kwargs):\\n \\\"\\\"\\\"\\n :param df:\\n :param ax:\\n :param cmap:\\n :param norm:\\n :param plot_colorbar:\\n :param colorbar_ax:\\n :param show_labels:\\n :param plot_hline:\\n :param kwargs:\\n :return:\\n \\\"\\\"\\\"\\n\\n if norm == None:\\n norm = Normalize(vmin=None, vmax=None)\\n if (plot_colorbar and colorbar_ax == None):\\n logger.warning(\\\"Colorbar ax is not provided.\\\")\\n plot_colorbar = False\\n\\n kwargs.setdefault('interpolation', 'nearest')\\n\\n im = ax.imshow(df.values, aspect='auto', norm=norm, **kwargs)\\n\\n ax.set_ylim(df.shape[0] - 0.5, -0.5)\\n ax.set_xlim(-0.5, df.shape[1] - 0.5)\\n ax.tick_params(axis='y', left=False, labelleft=False)\\n ax.set_ylabel('')\\n ax.grid(False)\\n\\n if show_labels:\\n ax.tick_params(axis='x', labelsize='small')\\n ax.set_xticks(np.arange(df.shape[1]))\\n ax.set_xticklabels(list(df.columns), rotation=90)\\n else:\\n ax.tick_params(axis='x', labelbottom=False, bottom=False)\\n\\n if plot_colorbar:\\n plt.colorbar(im, cax=colorbar_ax)\\n\\n if plot_hline:\\n line_coord = (\\n np.cumsum(df.index.value_counts(sort=False))[:-1] - 0.5\\n )\\n ax.hlines(\\n line_coord,\\n -0.5,\\n df.shape[1] - 0.5,\\n lw=1,\\n color='black',\\n zorder=10,\\n clip_on=False,\\n )\\n\\n\\ndef plot_categories_as_colorblocks(\\n groupby_ax: Axes,\\n obs_tidy: pd.DataFrame,\\n colors=None,\\n orientation: Literal['top', 'bottom', 'left', 'right'] = 'left',\\n cmap_name: str = 'tab20',\\n):\\n \\\"\\\"\\\"from scanpy\\\"\\\"\\\"\\n\\n groupby = obs_tidy.index.name\\n from matplotlib.colors import ListedColormap, BoundaryNorm\\n\\n if colors is None:\\n groupby_cmap = plt.get_cmap(cmap_name)\\n else:\\n groupby_cmap = ListedColormap(colors, groupby + '_cmap')\\n norm = BoundaryNorm(np.arange(groupby_cmap.N + 1) - 0.5, groupby_cmap.N)\\n\\n # determine groupby label positions such that they appear\\n # centered next/below to the color code rectangle assigned to the category\\n value_sum = 0\\n ticks = [] # list of centered position of the labels\\n labels = []\\n label2code = {} # dictionary of numerical values asigned to each label\\n for code, (label, value) in enumerate(\\n obs_tidy.index.value_counts(sort=False).iteritems()\\n ):\\n ticks.append(value_sum + (value / 2))\\n labels.append(label)\\n value_sum += value\\n label2code[label] = code\\n\\n groupby_ax.grid(False)\\n\\n if orientation == 'left':\\n groupby_ax.imshow(\\n np.array([[label2code[lab] for lab in obs_tidy.index]]).T,\\n aspect='auto',\\n cmap=groupby_cmap,\\n norm=norm,\\n )\\n if len(labels) > 1:\\n groupby_ax.set_yticks(ticks)\\n groupby_ax.set_yticklabels(labels)\\n\\n # remove y ticks\\n groupby_ax.tick_params(axis='y', left=False, labelsize='small')\\n # remove x ticks and labels\\n groupby_ax.tick_params(axis='x', bottom=False, labelbottom=False)\\n\\n # remove surrounding lines\\n groupby_ax.spines['right'].set_visible(False)\\n groupby_ax.spines['top'].set_visible(False)\\n groupby_ax.spines['left'].set_visible(False)\\n groupby_ax.spines['bottom'].set_visible(False)\\n\\n groupby_ax.set_ylabel(groupby)\\n else:\\n groupby_ax.imshow(\\n np.array([[label2code[lab] for lab in obs_tidy.index]]),\\n aspect='auto',\\n cmap=groupby_cmap,\\n norm=norm,\\n )\\n if len(labels) > 1:\\n groupby_ax.set_xticks(ticks)\\n if max([len(str(x)) for x in labels]) < 3:\\n # if the labels are small do not rotate them\\n rotation = 0\\n else:\\n rotation = 90\\n groupby_ax.set_xticklabels(labels, rotation=rotation)\\n\\n # remove x ticks\\n groupby_ax.tick_params(axis='x', bottom=False, labelsize='small')\\n # remove y ticks and labels\\n groupby_ax.tick_params(axis='y', left=False, labelleft=False)\\n\\n # remove surrounding lines\\n groupby_ax.spines['right'].set_visible(False)\\n groupby_ax.spines['top'].set_visible(False)\\n groupby_ax.spines['left'].set_visible(False)\\n groupby_ax.spines['bottom'].set_visible(False)\\n\\n groupby_ax.set_xlabel(groupby)\\n\\n return label2code, ticks, labels, groupby_cmap, norm\\n\\n\\ndef plot_gene_groups_brackets(\\n gene_groups_ax: Axes,\\n group_positions: Iterable[Tuple[int, int]],\\n group_labels: Sequence[str],\\n left_adjustment: float = -0.3,\\n right_adjustment: float = 0.3,\\n rotation: Optional[float] = None,\\n orientation: Literal['top', 'right'] = 'top',\\n):\\n \\\"\\\"\\\"from scanpy\\\"\\\"\\\"\\n import matplotlib.patches as patches\\n from matplotlib.path import Path\\n\\n # get the 'brackets' coordinates as lists of start and end positions\\n\\n left = [x[0] + left_adjustment for x in group_positions]\\n right = [x[1] + right_adjustment for x in group_positions]\\n\\n # verts and codes are used by PathPatch to make the brackets\\n verts = []\\n codes = []\\n if orientation == 'top':\\n # rotate labels if any of them is longer than 4 characters\\n if rotation is None and group_labels:\\n if max([len(x) for x in group_labels]) > 4:\\n rotation = 90\\n else:\\n rotation = 0\\n for idx in range(len(left)):\\n verts.append((left[idx], 0)) # lower-left\\n verts.append((left[idx], 0.6)) # upper-left\\n verts.append((right[idx], 0.6)) # upper-right\\n verts.append((right[idx], 0)) # lower-right\\n\\n codes.append(Path.MOVETO)\\n codes.append(Path.LINETO)\\n codes.append(Path.LINETO)\\n codes.append(Path.LINETO)\\n\\n try:\\n group_x_center = left[idx] + float(right[idx] - left[idx]) / 2\\n gene_groups_ax.text(\\n group_x_center,\\n 1.1,\\n group_labels[idx],\\n ha='center',\\n va='bottom',\\n rotation=rotation,\\n )\\n except:\\n pass\\n else:\\n top = left\\n bottom = right\\n for idx in range(len(top)):\\n verts.append((0, top[idx])) # upper-left\\n verts.append((0.15, top[idx])) # upper-right\\n verts.append((0.15, bottom[idx])) # lower-right\\n verts.append((0, bottom[idx])) # lower-left\\n\\n codes.append(Path.MOVETO)\\n codes.append(Path.LINETO)\\n codes.append(Path.LINETO)\\n codes.append(Path.LINETO)\\n\\n try:\\n diff = bottom[idx] - top[idx]\\n group_y_center = top[idx] + float(diff) / 2\\n if diff * 2 < len(group_labels[idx]):\\n # cut label to fit available space\\n group_labels[idx] = group_labels[idx][: int(diff * 2)] + \\\".\\\"\\n gene_groups_ax.text(\\n 0.6,\\n group_y_center,\\n group_labels[idx],\\n ha='right',\\n va='center',\\n rotation=270,\\n fontsize='small',\\n )\\n except Exception as e:\\n print('problems {}'.format(e))\\n pass\\n\\n path = Path(verts, codes)\\n\\n patch = patches.PathPatch(path, facecolor='none', lw=1.5)\\n\\n gene_groups_ax.add_patch(patch)\\n gene_groups_ax.grid(False)\\n gene_groups_ax.axis('off')\\n # remove y ticks\\n gene_groups_ax.tick_params(axis='y', left=False, labelleft=False)\\n # remove x ticks and labels\\n gene_groups_ax.tick_params(\\n axis='x', bottom=False, labelbottom=False, labeltop=False\\n )\\n\\n\\ndef _check_indices(\\n dim_df: pd.DataFrame,\\n alt_index: pd.Index,\\n dim: \\\"Literal['obs', 'var']\\\",\\n keys: List[str],\\n alias_index: pd.Index = None,\\n use_raw: bool = False,\\n):\\n \\\"\\\"\\\"from scanpy\\\"\\\"\\\"\\n if use_raw:\\n alt_repr = \\\"adata.raw\\\"\\n else:\\n alt_repr = \\\"adata\\\"\\n\\n alt_dim = (\\\"obs\\\", \\\"var\\\")[dim == \\\"obs\\\"]\\n\\n alias_name = None\\n if alias_index is not None:\\n alt_names = pd.Series(alt_index, index=alias_index)\\n alias_name = alias_index.name\\n alt_search_repr = f\\\"{alt_dim}['{alias_name}']\\\"\\n else:\\n alt_names = pd.Series(alt_index, index=alt_index)\\n alt_search_repr = f\\\"{alt_dim}_names\\\"\\n\\n col_keys = []\\n index_keys = []\\n index_aliases = []\\n not_found = []\\n\\n # check that adata.obs does not contain duplicated columns\\n # if duplicated columns names are present, they will\\n # be further duplicated when selecting them.\\n if not dim_df.columns.is_unique:\\n dup_cols = dim_df.columns[dim_df.columns.duplicated()].tolist()\\n raise ValueError(\\n f\\\"adata.{dim} contains duplicated columns. Please rename or remove \\\"\\n \\\"these columns first.\\\\n`\\\"\\n f\\\"Duplicated columns {dup_cols}\\\"\\n )\\n\\n if not alt_index.is_unique:\\n raise ValueError(\\n f\\\"{alt_repr}.{alt_dim}_names contains duplicated items\\\\n\\\"\\n f\\\"Please rename these {alt_dim} names first for example using \\\"\\n f\\\"`adata.{alt_dim}_names_make_unique()`\\\"\\n )\\n\\n # use only unique keys, otherwise duplicated keys will\\n # further duplicate when reordering the keys later in the function\\n for key in np.unique(keys):\\n if key in dim_df.columns:\\n col_keys.append(key)\\n if key in alt_names.index:\\n raise KeyError(\\n f\\\"The key '{key}' is found in both adata.{dim} and {alt_repr}.{alt_search_repr}.\\\"\\n )\\n elif key in alt_names.index:\\n val = alt_names[key]\\n if isinstance(val, pd.Series):\\n # while var_names must be unique, adata.var[gene_symbols] does not\\n # It's still ambiguous to refer to a duplicated entry though.\\n assert alias_index is not None\\n raise KeyError(\\n f\\\"Found duplicate entries for '{key}' in {alt_repr}.{alt_search_repr}.\\\"\\n )\\n index_keys.append(val)\\n index_aliases.append(key)\\n else:\\n not_found.append(key)\\n if len(not_found) > 0:\\n raise KeyError(\\n f\\\"Could not find keys '{not_found}' in columns of `adata.{dim}` or in\\\"\\n f\\\" {alt_repr}.{alt_search_repr}.\\\"\\n )\\n\\n return col_keys, index_keys, index_aliases\\n\"\n }\n]"},"num_files":{"kind":"number","value":16,"string":"16"}}},{"rowIdx":2069,"cells":{"repo_name":{"kind":"string","value":"5l1v3r1/gg-1"},"repo_url":{"kind":"string","value":"https://github.com/5l1v3r1/gg-1"},"snapshot_id":{"kind":"string","value":"cc80c441841295c81fd02ec4e3fb946c5d7fd1d3"},"revision_id":{"kind":"string","value":"59d6c5e2f7cae749e5c2918f6e745ab17289c2c1"},"directory_id":{"kind":"string","value":"24ebc32fbefaab193b2d8ad66d3736981c932ced"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"string","value":"2022-04-20T17:54:24.132367"},"revision_date":{"kind":"string","value":"2020-04-21T05:02:56"},"committer_date":{"kind":"string","value":"2020-04-21T05:02:56"},"github_id":{"kind":"null"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.6551724076271057,"alphanum_fraction":0.6551724076271057,"avg_line_length":13.5,"blob_id":"11abda5e3fa3b52ec2a707a788d639c69d9e2244","content_id":"7a9e5be7a71c2582b80934cf4e939b10c82f1b10","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":29,"license_type":"no_license","max_line_length":16,"num_lines":2,"path":"/ty.py","repo_name":"5l1v3r1/gg-1","src_encoding":"UTF-8","text":"print('HW')\nprint('TESTING')\n"}],"string":"[\n {\n \"alpha_fraction\": 0.6551724076271057,\n \"alphanum_fraction\": 0.6551724076271057,\n \"avg_line_length\": 13.5,\n \"blob_id\": \"11abda5e3fa3b52ec2a707a788d639c69d9e2244\",\n \"content_id\": \"7a9e5be7a71c2582b80934cf4e939b10c82f1b10\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 29,\n \"license_type\": \"no_license\",\n \"max_line_length\": 16,\n \"num_lines\": 2,\n \"path\": \"/ty.py\",\n \"repo_name\": \"5l1v3r1/gg-1\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"print('HW')\\nprint('TESTING')\\n\"\n }\n]"},"num_files":{"kind":"number","value":1,"string":"1"}}},{"rowIdx":2070,"cells":{"repo_name":{"kind":"string","value":"vaibhavj08/Limitingservice"},"repo_url":{"kind":"string","value":"https://github.com/vaibhavj08/Limitingservice"},"snapshot_id":{"kind":"string","value":"d1592899789ead7524e71f4545d14f3ac26d2a03"},"revision_id":{"kind":"string","value":"b383103dee5efba59394f3403de206b7ab0f4121"},"directory_id":{"kind":"string","value":"7bec193bcf445e3cf959b8b6c56f261a71e2a1e5"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"string","value":"2023-08-05T20:37:45.947169"},"revision_date":{"kind":"string","value":"2020-07-17T11:57:33"},"committer_date":{"kind":"string","value":"2020-07-17T11:57:33"},"github_id":{"kind":"number","value":277577260,"string":"277,577,260"},"star_events_count":{"kind":"number","value":1,"string":"1"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"string","value":"2020-07-06T15:18:26"},"gha_updated_at":{"kind":"string","value":"2020-07-17T12:01:01"},"gha_pushed_at":{"kind":"string","value":"2021-09-22T19:26:13"},"gha_language":{"kind":"string","value":"Python"},"files":{"kind":"list like","value":[{"alpha_fraction":0.4639175236225128,"alphanum_fraction":0.6907216310501099,"avg_line_length":15.166666984558105,"blob_id":"a93c311ef955061e185e085c0e9bca17fc303c3a","content_id":"2647df0b927943297ea236a6b9409a4469cbb284","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Text","length_bytes":97,"license_type":"no_license","max_line_length":16,"num_lines":6,"path":"/requirements.txt","repo_name":"vaibhavj08/Limitingservice","src_encoding":"UTF-8","text":"Django==3.0.8\nrequests==2.24.0\ngunicorn==20.0.4\nfastapi==0.59.0\nratelimit==2.2.1\nuvicorn==0.11.5\n"},{"alpha_fraction":0.7213114500045776,"alphanum_fraction":0.75,"avg_line_length":17.769229888916016,"blob_id":"7e13d0158a745124e87ee31a1bd2c5f142e1cab3","content_id":"b8cf1ab15854fee75f3cf9ace7e6d7ffa17ded31","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":244,"license_type":"no_license","max_line_length":44,"num_lines":13,"path":"/number.py","repo_name":"vaibhavj08/Limitingservice","src_encoding":"UTF-8","text":"from fastapi import FastAPI\nimport random\nfrom ratelimit import limits,sleep_and_retry\n\none_minute=60\napp = FastAPI()\n\n\n@app.get('/get_number')\n@sleep_and_retry\n@limits(calls=5,period=one_minute)\ndef numbers():\n return random.randint(1,100)\n"},{"alpha_fraction":0.6482494473457336,"alphanum_fraction":0.662472665309906,"avg_line_length":27.13846206665039,"blob_id":"5bc4cd0ffd6e51c47516cc76f59a953de3f5616b","content_id":"4e8cb2cd19f978568fe87ba60c69fce253166c9d","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1828,"license_type":"no_license","max_line_length":93,"num_lines":65,"path":"/api_call/views.py","repo_name":"vaibhavj08/Limitingservice","src_encoding":"UTF-8","text":"from django.shortcuts import render,redirect\nfrom django.http import HttpResponse\nimport requests\nfrom django.contrib import auth\nfrom django.contrib.auth.models import User\n\n\n# Create your views here.\n#function to signup\ndef signup(request):\n if request.method == 'POST':\n username = request.POST.get('username')\n password = request.POST.get('password')\n user = User.objects.create_user(username = username,password = password)\n user.save()\n return redirect('/')\n else:\n return render(request,'home.html')\n\n#function to login\ndef login(request):\n if request.method == 'POST':\n username = request.POST.get('username')\n password = request.POST.get('password')\n user = auth.authenticate(username =username,password = password)\n\n if user is not None:\n auth.login(request,user)\n return redirect('/api_call')\n else:\n return HttpResponse(\"
403 Forbidden
Wrong credential
\")\n else:\n return render(request,'login.html')\n\n\ncount = 0\nhour_request_count=300\n\n#function to call the api\ndef api_call(request):\n if request.user.is_anonymous:\n return redirect('/')\n global count\n\n url = 'http://127.0.0.1:8000/get_number'\n try:\n response = requests.get(url,timeout=2)\n count = count+1\n print('count:',count)\n\n except requests.exceptions.ReadTimeout:\n return render(request,'api.html',{'response':'403 Call limit exausted for a minute'})\n\n return render(request,'api.html',{'response':response.text})\n\n#function to logout\ndef logout(request):\n auth.logout(request)\n return redirect('/')\n\n\n#function to check the remaining calls in an hour\ndef remaining_call(request):\n r_call = hour_request_count-count\n return HttpResponse(r_call)"},{"alpha_fraction":0.7444444298744202,"alphanum_fraction":0.7444444298744202,"avg_line_length":17,"blob_id":"d6bca9261bc7479b1cdbace49151a8517ae11ff1","content_id":"b1d9880dd5385fa031b513be50e878336d776bc0","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":90,"license_type":"no_license","max_line_length":33,"num_lines":5,"path":"/api_call/apps.py","repo_name":"vaibhavj08/Limitingservice","src_encoding":"UTF-8","text":"from django.apps import AppConfig\n\n\nclass ApiCallConfig(AppConfig):\n name = 'api_call'\n"},{"alpha_fraction":0.7361111044883728,"alphanum_fraction":0.7731481194496155,"avg_line_length":53,"blob_id":"3b2ebfa41a153b9a0751b3f8dbcf18efd1f5a6ce","content_id":"be433755714a87dd19ca723d1b9fdec8fdf9f38c","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Text","length_bytes":216,"license_type":"no_license","max_line_length":101,"num_lines":4,"path":"/README.txt","repo_name":"vaibhavj08/Limitingservice","src_encoding":"UTF-8","text":"# Limitingservice\n#run \"uvicorn number:app --reload\" and \"python manage.py runserver 8001\" in different terminal\n\nRUN pip install -r requirements.txt && uvicorn number:app --reload && python manage.py runserver 8001\n"},{"alpha_fraction":0.6545960903167725,"alphanum_fraction":0.6545960903167725,"avg_line_length":35,"blob_id":"ab7d7fcaf3360e245d01f1241988e3d15d4fefde","content_id":"592f7fad370acaf7a23b82ab0fe5c73594a23c13","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":359,"license_type":"no_license","max_line_length":83,"num_lines":10,"path":"/api_call/urls.py","repo_name":"vaibhavj08/Limitingservice","src_encoding":"UTF-8","text":"from django.urls import path\nfrom . import views\n\nurlpatterns = [\n path('', views.login,name = 'login'),\n path('signup/', views.signup,name = 'signup'),\n path('api_call/', views.api_call,name = 'api_call'),\n path('api_call/remaining_call/', views.remaining_call,name = 'remaining_call'),\n path('api_call/logout/',views.logout,name = 'logout')\n]"}],"string":"[\n {\n \"alpha_fraction\": 0.4639175236225128,\n \"alphanum_fraction\": 0.6907216310501099,\n \"avg_line_length\": 15.166666984558105,\n \"blob_id\": \"a93c311ef955061e185e085c0e9bca17fc303c3a\",\n \"content_id\": \"2647df0b927943297ea236a6b9409a4469cbb284\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Text\",\n \"length_bytes\": 97,\n \"license_type\": \"no_license\",\n \"max_line_length\": 16,\n \"num_lines\": 6,\n \"path\": \"/requirements.txt\",\n \"repo_name\": \"vaibhavj08/Limitingservice\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"Django==3.0.8\\nrequests==2.24.0\\ngunicorn==20.0.4\\nfastapi==0.59.0\\nratelimit==2.2.1\\nuvicorn==0.11.5\\n\"\n },\n {\n \"alpha_fraction\": 0.7213114500045776,\n \"alphanum_fraction\": 0.75,\n \"avg_line_length\": 17.769229888916016,\n \"blob_id\": \"7e13d0158a745124e87ee31a1bd2c5f142e1cab3\",\n \"content_id\": \"b8cf1ab15854fee75f3cf9ace7e6d7ffa17ded31\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 244,\n \"license_type\": \"no_license\",\n \"max_line_length\": 44,\n \"num_lines\": 13,\n \"path\": \"/number.py\",\n \"repo_name\": \"vaibhavj08/Limitingservice\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from fastapi import FastAPI\\nimport random\\nfrom ratelimit import limits,sleep_and_retry\\n\\none_minute=60\\napp = FastAPI()\\n\\n\\n@app.get('/get_number')\\n@sleep_and_retry\\n@limits(calls=5,period=one_minute)\\ndef numbers():\\n return random.randint(1,100)\\n\"\n },\n {\n \"alpha_fraction\": 0.6482494473457336,\n \"alphanum_fraction\": 0.662472665309906,\n \"avg_line_length\": 27.13846206665039,\n \"blob_id\": \"5bc4cd0ffd6e51c47516cc76f59a953de3f5616b\",\n \"content_id\": \"4e8cb2cd19f978568fe87ba60c69fce253166c9d\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1828,\n \"license_type\": \"no_license\",\n \"max_line_length\": 93,\n \"num_lines\": 65,\n \"path\": \"/api_call/views.py\",\n \"repo_name\": \"vaibhavj08/Limitingservice\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from django.shortcuts import render,redirect\\nfrom django.http import HttpResponse\\nimport requests\\nfrom django.contrib import auth\\nfrom django.contrib.auth.models import User\\n\\n\\n# Create your views here.\\n#function to signup\\ndef signup(request):\\n if request.method == 'POST':\\n username = request.POST.get('username')\\n password = request.POST.get('password')\\n user = User.objects.create_user(username = username,password = password)\\n user.save()\\n return redirect('/')\\n else:\\n return render(request,'home.html')\\n\\n#function to login\\ndef login(request):\\n if request.method == 'POST':\\n username = request.POST.get('username')\\n password = request.POST.get('password')\\n user = auth.authenticate(username =username,password = password)\\n\\n if user is not None:\\n auth.login(request,user)\\n return redirect('/api_call')\\n else:\\n return HttpResponse(\\\"403 Forbidden
Wrong credential
\\\")\\n else:\\n return render(request,'login.html')\\n\\n\\ncount = 0\\nhour_request_count=300\\n\\n#function to call the api\\ndef api_call(request):\\n if request.user.is_anonymous:\\n return redirect('/')\\n global count\\n\\n url = 'http://127.0.0.1:8000/get_number'\\n try:\\n response = requests.get(url,timeout=2)\\n count = count+1\\n print('count:',count)\\n\\n except requests.exceptions.ReadTimeout:\\n return render(request,'api.html',{'response':'403 Call limit exausted for a minute'})\\n\\n return render(request,'api.html',{'response':response.text})\\n\\n#function to logout\\ndef logout(request):\\n auth.logout(request)\\n return redirect('/')\\n\\n\\n#function to check the remaining calls in an hour\\ndef remaining_call(request):\\n r_call = hour_request_count-count\\n return HttpResponse(r_call)\"\n },\n {\n \"alpha_fraction\": 0.7444444298744202,\n \"alphanum_fraction\": 0.7444444298744202,\n \"avg_line_length\": 17,\n \"blob_id\": \"d6bca9261bc7479b1cdbace49151a8517ae11ff1\",\n \"content_id\": \"b1d9880dd5385fa031b513be50e878336d776bc0\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 90,\n \"license_type\": \"no_license\",\n \"max_line_length\": 33,\n \"num_lines\": 5,\n \"path\": \"/api_call/apps.py\",\n \"repo_name\": \"vaibhavj08/Limitingservice\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from django.apps import AppConfig\\n\\n\\nclass ApiCallConfig(AppConfig):\\n name = 'api_call'\\n\"\n },\n {\n \"alpha_fraction\": 0.7361111044883728,\n \"alphanum_fraction\": 0.7731481194496155,\n \"avg_line_length\": 53,\n \"blob_id\": \"3b2ebfa41a153b9a0751b3f8dbcf18efd1f5a6ce\",\n \"content_id\": \"be433755714a87dd19ca723d1b9fdec8fdf9f38c\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Text\",\n \"length_bytes\": 216,\n \"license_type\": \"no_license\",\n \"max_line_length\": 101,\n \"num_lines\": 4,\n \"path\": \"/README.txt\",\n \"repo_name\": \"vaibhavj08/Limitingservice\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# Limitingservice\\n#run \\\"uvicorn number:app --reload\\\" and \\\"python manage.py runserver 8001\\\" in different terminal\\n\\nRUN pip install -r requirements.txt && uvicorn number:app --reload && python manage.py runserver 8001\\n\"\n },\n {\n \"alpha_fraction\": 0.6545960903167725,\n \"alphanum_fraction\": 0.6545960903167725,\n \"avg_line_length\": 35,\n \"blob_id\": \"ab7d7fcaf3360e245d01f1241988e3d15d4fefde\",\n \"content_id\": \"592f7fad370acaf7a23b82ab0fe5c73594a23c13\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 359,\n \"license_type\": \"no_license\",\n \"max_line_length\": 83,\n \"num_lines\": 10,\n \"path\": \"/api_call/urls.py\",\n \"repo_name\": \"vaibhavj08/Limitingservice\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from django.urls import path\\nfrom . import views\\n\\nurlpatterns = [\\n path('', views.login,name = 'login'),\\n path('signup/', views.signup,name = 'signup'),\\n path('api_call/', views.api_call,name = 'api_call'),\\n path('api_call/remaining_call/', views.remaining_call,name = 'remaining_call'),\\n path('api_call/logout/',views.logout,name = 'logout')\\n]\"\n }\n]"},"num_files":{"kind":"number","value":6,"string":"6"}}},{"rowIdx":2071,"cells":{"repo_name":{"kind":"string","value":"abdulazeeznaji/funny-learn"},"repo_url":{"kind":"string","value":"https://github.com/abdulazeeznaji/funny-learn"},"snapshot_id":{"kind":"string","value":"c66b38e94b02f9b1b191d460ff150708ff21bddb"},"revision_id":{"kind":"string","value":"35ba422bd83a69e4ec16b1edf714d45c06af3d0c"},"directory_id":{"kind":"string","value":"2aac3e68c7b084a956c0045bbad0062f612a717e"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"string","value":"2018-02-08T04:59:07.083135"},"revision_date":{"kind":"string","value":"2017-07-10T15:49:37"},"committer_date":{"kind":"string","value":"2017-07-10T15:49:37"},"github_id":{"kind":"number","value":96327213,"string":"96,327,213"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.7755555510520935,"alphanum_fraction":0.7777777910232544,"avg_line_length":25.352941513061523,"blob_id":"90a133788ded10d3e3deaf8521f3633e403f332d","content_id":"720ab063eab3a65269e0b259f3a30b1acb056c90","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":450,"license_type":"no_license","max_line_length":45,"num_lines":17,"path":"/myapp/blog/views.py","repo_name":"abdulazeeznaji/funny-learn","src_encoding":"UTF-8","text":"# -*- coding: utf-8 -*-\nfrom __future__ import unicode_literals\n\nfrom django.shortcuts import render\n\n# Create your views here.\n\nfrom blog.models import Blog\nfrom rest_framework import generics, viewsets\nfrom rest_framework.response import Response\nfrom rest_framework.reverse import reverse\nfrom blog.serializers import BlogSerializer\n \n \nclass Blogs(viewsets.ModelViewSet):\n queryset = Blog.objects.all()\n serializer_class = BlogSerializer\n\n\n"},{"alpha_fraction":0.6887755393981934,"alphanum_fraction":0.6989796161651611,"avg_line_length":25.200000762939453,"blob_id":"d0b5d45c1a62b212a496551a26d1af21bb36d7ed","content_id":"fbe918cf218acb973c4290aae6b1c636a877a9a1","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":392,"license_type":"no_license","max_line_length":81,"num_lines":15,"path":"/myapp/blog/models.py","repo_name":"abdulazeeznaji/funny-learn","src_encoding":"UTF-8","text":"# -*- coding: utf-8 -*-\nfrom __future__ import unicode_literals\n\nfrom django.db import models\nfrom users.models import User\n \n \nclass Blog(models.Model):\n created = models.DateTimeField(auto_now_add=True)\n name = models.CharField(max_length=100, unique=True, blank=False, null=False)\n isComplete = models.BooleanField(default=False)\n\n \n class Meta:\n ordering = ('created',)"},{"alpha_fraction":0.5142857432365417,"alphanum_fraction":0.5857142806053162,"avg_line_length":16.625,"blob_id":"ff67e4313ae04304520ebe9ae02857346abb26e3","content_id":"cdc2331ad9f80dbafc2b708142b6ca56f8f01f17","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"JavaScript","length_bytes":140,"license_type":"no_license","max_line_length":46,"num_lines":8,"path":"/myapp/src/lib/services.js","repo_name":"abdulazeeznaji/funny-learn","src_encoding":"UTF-8","text":"const baseUrl = 'http://127.0.0.1:8000/blogs/'\n\n\nexport const getBlogs = () =>{\n return fetch(baseUrl)\n .then(res => res.json() )\n\n}"},{"alpha_fraction":0.47457626461982727,"alphanum_fraction":0.47457626461982727,"avg_line_length":12.354838371276855,"blob_id":"5ae00bd08c6806d020662cdf855bbf8db7fb839c","content_id":"c3760d27b6b76c04915deec088e3583aad7f85d6","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"JavaScript","length_bytes":413,"license_type":"no_license","max_line_length":46,"num_lines":31,"path":"/myapp/src/Main.js","repo_name":"abdulazeeznaji/funny-learn","src_encoding":"UTF-8","text":"import React from 'react'\nimport {getBlogs} from './lib/services'\n\n\n\n class Main extends React.Component{\n constructor(){\n super()\n this.state = {\n blogs:[]\n }\n }\n componentWillMount(){\n getBlogs()\n .then(blogs => this.setState({blogs}))\n }\n\n render(){\n return (\n\n
\n\n )\n\n\n }\n\n}\n\n\nmodule.exports = Main"},{"alpha_fraction":0.6880733966827393,"alphanum_fraction":0.6880733966827393,"avg_line_length":23.22222137451172,"blob_id":"4a47f3502938fece2a1c70101e2ec444e8ccc447","content_id":"632f6f379df3c86118104b13654e3c0d080cd368","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":218,"license_type":"no_license","max_line_length":56,"num_lines":9,"path":"/myapp/blog/serializers.py","repo_name":"abdulazeeznaji/funny-learn","src_encoding":"UTF-8","text":"from rest_framework import serializers\n \nfrom blog.models import Blog\n \nclass BlogSerializer(serializers.ModelSerializer):\n\n class Meta:\n model = Blog\n fields = ('id', 'created', 'name', 'isComplete')\n"},{"alpha_fraction":0.7341463565826416,"alphanum_fraction":0.7390244007110596,"avg_line_length":33.16666793823242,"blob_id":"e371d03bbfd08f43e6eaaec7ca666f6b95733329","content_id":"18d2f61b8d386ce8d01f5c55506bf57d1bf79083","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":410,"license_type":"no_license","max_line_length":86,"num_lines":12,"path":"/myapp/blog/urls.py","repo_name":"abdulazeeznaji/funny-learn","src_encoding":"UTF-8","text":"from django.conf.urls import url, include\nfrom rest_framework import routers\nfrom rest_framework.urlpatterns import format_suffix_patterns\nfrom blog import views\n\napi_router = routers.DefaultRouter()\napi_router.register(r'blogs', views.Blogs, base_name=\"blogs\")\n#api_router.register(r'^blogs/(?P\\n
\\n\\n )\\n\\n\\n }\\n\\n}\\n\\n\\nmodule.exports = Main\"\n },\n {\n \"alpha_fraction\": 0.6880733966827393,\n \"alphanum_fraction\": 0.6880733966827393,\n \"avg_line_length\": 23.22222137451172,\n \"blob_id\": \"4a47f3502938fece2a1c70101e2ec444e8ccc447\",\n \"content_id\": \"632f6f379df3c86118104b13654e3c0d080cd368\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 218,\n \"license_type\": \"no_license\",\n \"max_line_length\": 56,\n \"num_lines\": 9,\n \"path\": \"/myapp/blog/serializers.py\",\n \"repo_name\": \"abdulazeeznaji/funny-learn\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from rest_framework import serializers\\n \\nfrom blog.models import Blog\\n \\nclass BlogSerializer(serializers.ModelSerializer):\\n\\n class Meta:\\n model = Blog\\n fields = ('id', 'created', 'name', 'isComplete')\\n\"\n },\n {\n \"alpha_fraction\": 0.7341463565826416,\n \"alphanum_fraction\": 0.7390244007110596,\n \"avg_line_length\": 33.16666793823242,\n \"blob_id\": \"e371d03bbfd08f43e6eaaec7ca666f6b95733329\",\n \"content_id\": \"18d2f61b8d386ce8d01f5c55506bf57d1bf79083\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 410,\n \"license_type\": \"no_license\",\n \"max_line_length\": 86,\n \"num_lines\": 12,\n \"path\": \"/myapp/blog/urls.py\",\n \"repo_name\": \"abdulazeeznaji/funny-learn\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from django.conf.urls import url, include\\nfrom rest_framework import routers\\nfrom rest_framework.urlpatterns import format_suffix_patterns\\nfrom blog import views\\n\\napi_router = routers.DefaultRouter()\\napi_router.register(r'blogs', views.Blogs, base_name=\\\"blogs\\\")\\n#api_router.register(r'^blogs/(?P', '', text)\n text = re.sub('etc.', 'etc', text)\n # text = re.sub('\\W', ' ', text)\n text = re.sub('\\s+', ' ', text)\n text = re.sub('\\