package
stringlengths 1
122
| pacakge-description
stringlengths 0
1.3M
|
|---|---|
angle-emb
|
EN |简体中文AnglE📐: Angle-optimized Text EmbeddingsIt is Angle 📐, not Angel 👼.🔥A New SOTAfor Semantic Textual Similarity!🔥Our universal sentence embeddingWhereIsAI/UAE-Large-V1achieves SOTA on theMTEB Leaderboardwith an average score of 64.64!📊 Results on MTEB Leaderboard [click to expand]📊 Results on STS benchmark [click to expand]🤗 Pretrained Models🤗 HFLoRA WeightDependent BackboneLLMLanguagePromptPooling StrategyExamplesWhereIsAI/UAE-Large-V1NNNENPrompts.Cfor retrieval purposes,Nonefor othersclsSeanLee97/angle-llama-13b-nliYNousResearch/Llama-2-13b-hfYENPrompts.Alast token/SeanLee97/angle-llama-7b-nli-v2YNousResearch/Llama-2-7b-hfYENPrompts.Alast token/SeanLee97/angle-llama-7b-nli-20231027YNousResearch/Llama-2-7b-hfYENPrompts.Alast token/SeanLee97/angle-bert-base-uncased-nli-en-v1NNNENNcls_avg/SeanLee97/angle-roberta-wwm-base-zhnli-v1NNNZH-CNNcls/SeanLee97/angle-llama-7b-zhnli-v1YNousResearch/Llama-2-7b-hfYZH-CNPrompts.Blast token/💡 If the selected model is a LoRA weight, it must specify the corresponding dependent backbone.For our STS Experiment, please refer tohttps://github.com/SeanLee97/AnglE/tree/main/examples/NLIResultsEnglish STS ResultsModelSTS12STS13STS14STS15STS16STSBenchmarkSICKRelatednessAvg.SeanLee97/angle-llama-7b-nli-2023102778.6890.5885.4989.5686.9188.9281.1885.90SeanLee97/angle-llama-7b-nli-v279.0090.5685.7989.4387.0088.9780.9485.96SeanLee97/angle-llama-13b-nli79.3390.6586.8990.4587.3289.6981.3286.52SeanLee97/angle-bert-base-uncased-nli-en-v175.0985.5680.6686.4482.4785.1681.2382.37Chinese STS ResultsModelATECBQLCQMCPAWSXSTS-BSOHU-ddSOHU-dcAvg.^shibing624/text2vec-bge-large-chinese38.4161.3471.7235.1576.4471.8163.1559.72^shibing624/text2vec-base-chinese-paraphrase44.8963.5874.2440.9078.9376.7063.3063.08SeanLee97/angle-roberta-wwm-base-zhnli-v149.4972.4778.3359.1377.1472.3660.5367.06SeanLee97/angle-llama-7b-zhnli-v150.4471.9578.9056.5781.1168.1152.0265.59^ denotes baselines, their results are retrieved from:https://github.com/shibing624/text2vecUsageAnglE supports two APIs, one is thetransformersAPI, the other is theAnglEAPI. If you want to use theAnglEAPI, please install AnglE first:python-mpipinstall-Uangle-embUAEFor Retrieval PurposesFor retrieval purposes, please use the promptPrompts.C.fromangle_embimportAnglE,Promptsangle=AnglE.from_pretrained('WhereIsAI/UAE-Large-V1',pooling_strategy='cls').cuda()angle.set_prompt(prompt=Prompts.C)vec=angle.encode({'text':'hello world'},to_numpy=True)print(vec)vecs=angle.encode([{'text':'hello world1'},{'text':'hello world2'}],to_numpy=True)print(vecs)For non-Retrieval Purposesfromangle_embimportAnglEangle=AnglE.from_pretrained('WhereIsAI/UAE-Large-V1',pooling_strategy='cls').cuda()vec=angle.encode('hello world',to_numpy=True)print(vec)vecs=angle.encode(['hello world1','hello world2'],to_numpy=True)print(vecs)Difference between retrieval and non-retrieval sentence embeddings. [click to expand]In UAE, we use different approaches for retrieval and non-retrieval tasks, each serving a different purpose.Retrieval tasks aim to find relevant documents, and as a result, the related documents may not have strict semantic similarities to each other.For instance, when querying "How about ChatGPT?", the related documents are those that contain information related to "ChatGPT," such as "ChatGPT is amazing..." or "ChatGPT is bad....".Conversely,non-retrieval tasks, such as semantic textual similarity, require sentences that are semantically similar.For example, a sentence semantically similar to "How about ChatGPT?" could be "What is your opinion about ChatGPT?".To distinguish between these two types of tasks, we use different prompts.For retrieval tasks, we use the prompt "Represent this sentence for searching relevant passages: {text}" (Prompts.C in angle_emb).For non-retrieval tasks, we set the prompt to empty, i.e., just input your text without specifying a prompt.So, if your scenario is retrieval-related, it is highly recommended to set the prompt with angle.set_prompt(prompt=Prompts.C). If not, leave the prompt empty or use angle.set_prompt(prompt=None).Angle-LLaMAAnglEfromangle_embimportAnglE,Promptsangle=AnglE.from_pretrained('NousResearch/Llama-2-7b-hf',pretrained_lora_path='SeanLee97/angle-llama-7b-nli-v2')print('All predefined prompts:',Prompts.list_prompts())angle.set_prompt(prompt=Prompts.A)print('prompt:',angle.prompt)vec=angle.encode({'text':'hello world'},to_numpy=True)print(vec)vecs=angle.encode([{'text':'hello world1'},{'text':'hello world2'}],to_numpy=True)print(vecs)transformersfromangle_embimportAnglEfromtransformersimportAutoModelForCausalLM,AutoTokenizerfrompeftimportPeftModel,PeftConfigpeft_model_id='SeanLee97/angle-llama-7b-nli-v2'config=PeftConfig.from_pretrained(peft_model_id)tokenizer=AutoTokenizer.from_pretrained(config.base_model_name_or_path)model=AutoModelForCausalLM.from_pretrained(config.base_model_name_or_path).bfloat16().cuda()model=PeftModel.from_pretrained(model,peft_model_id).cuda()defdecorate_text(text:str):returnPrompts.A.format(text=text)inputs='hello world!'tok=tokenizer([decorate_text(inputs)],return_tensors='pt')fork,vintok.items():tok[k]=v.cuda()vec=model(output_hidden_states=True,**tok).hidden_states[-1][:,-1].float().detach().cpu().numpy()print(vec)Angle-BERTAnglEfromangle_embimportAnglEangle=AnglE.from_pretrained('SeanLee97/angle-bert-base-uncased-nli-en-v1',pooling_strategy='cls_avg').cuda()vec=angle.encode('hello world',to_numpy=True)print(vec)vecs=angle.encode(['hello world1','hello world2'],to_numpy=True)print(vecs)transformersimporttorchfromtransformersimportAutoModel,AutoTokenizermodel_id='SeanLee97/angle-bert-base-uncased-nli-en-v1'tokenizer=AutoTokenizer.from_pretrained(model_id)model=AutoModel.from_pretrained(model_id).cuda()inputs='hello world!'tok=tokenizer([inputs],return_tensors='pt')fork,vintok.items():tok[k]=v.cuda()hidden_state=model(**tok).last_hidden_statevec=(hidden_state[:,0]+torch.mean(hidden_state,dim=1))/2.0print(vec)Custom Train1. Data PrepationWe support two dataset formats:DatasetFormats.A: it is a pair format with three columns:text1,text2, andlabel(0/1).DatasetFormats.B: it is a triple format with three columns:text,positive, andnegative.positiveandnegativestore the positive and negative samples oftext.DatasetFormats.C: it is a pair format with two columns:text,positive.positivestore the positive sample oftext.You need to prepare your data into huggingfacedatasets.Datasetin one of the formats in terms of your supervised data.2. TrainUseangle-trainerto train your AnglE model in cli mode. Usage:CUDA_VISIBLE_DEVICES=0 angle-trainer --help3. Examplefromdatasetsimportload_datasetfromangle_embimportAnglE,AngleDataTokenizer# 1. load pretrained modelangle=AnglE.from_pretrained('SeanLee97/angle-bert-base-uncased-nli-en-v1',max_length=128,pooling_strategy='cls').cuda()# 2. load dataset# `text1`, `text2`, and `label` are three required columns.ds=load_dataset('mteb/stsbenchmark-sts')ds=ds.map(lambdaobj:{"text1":str(obj["sentence1"]),"text2":str(obj['sentence2']),"label":obj['score']})ds=ds.select_columns(["text1","text2","label"])# 3. transform datatrain_ds=ds['train'].shuffle().map(AngleDataTokenizer(angle.tokenizer,angle.max_length),num_proc=8)valid_ds=ds['validation'].map(AngleDataTokenizer(angle.tokenizer,angle.max_length),num_proc=8)test_ds=ds['test'].map(AngleDataTokenizer(angle.tokenizer,angle.max_length),num_proc=8)# 4. fitangle.fit(train_ds=train_ds,valid_ds=valid_ds,output_dir='ckpts/sts-b',batch_size=32,epochs=5,learning_rate=2e-5,save_steps=100,eval_steps=1000,warmup_steps=0,gradient_accumulation_steps=1,loss_kwargs={'w1':1.0,'w2':1.0,'w3':1.0,'cosine_tau':20,'ibn_tau':20,'angle_tau':1.0},fp16=True,logging_steps=100)# 5. evaluatecorrcoef,accuracy=angle.evaluate(test_ds,device=angle.device)print('corrcoef:',corrcoef)CitationYou are welcome to use our code and pre-trained models. If you use our code and pre-trained models, please support us by citing our work as follows:@article{li2023angle,title={AnglE-optimized Text Embeddings},author={Li, Xianming and Li, Jing},journal={arXiv preprint arXiv:2309.12871},year={2023}}ChangeLogs📅Description2024 Feb 7support training with only positive pairs (DatasetFormats.C)2024 Jan 11refactor to supportangle-trainerand BeLLM2023 Dec 4Release a universal English sentence embedding model:WhereIsAI/UAE-Large-V12023 Nov 2Release an English pretrained model:SeanLee97/angle-llama-13b-nli2023 Oct 28Release two chinese pretrained models:SeanLee97/angle-roberta-wwm-base-zhnli-v1andSeanLee97/angle-llama-7b-zhnli-v1; Add chinese README.md
|
angle-headings
|
Angle HeadingsA lightweight Python class for representing and performing calculations with angles.This is a small class meant to simplify common operations with angle measures. The convention used for the arithmetic and comparison operations is meant to capture the idea that we are primarily interested in the smallest angle between two measures, regardless of the numbers, themselves. In particular this includes the following conventions:Angles that differ by an integer number of revolutions are considered equivalent.Output angle values are limited in size to±1/2full revolution. For example, radian angle measures are restricted to the interval(-π,π], while degree angle measures are restricted to(-180,180].Angle comparisons are based on the smallest angle between the two input angles, and on whether the first angle is closer to being clockwise or counterclockwise from the first. By convention we say thatA > Bif the smallest angle betweenAandBplacesAcounterclockwise relative toB, andA < Bif the smallest angle betweenAandBplacesAclockwise relative toB.Radian, degree, and gradian measure (or any arbitrary subdivision of the circle) are all supported. Methods perform calculations and return results using the measure of their own angle object, converting other angles or floats when necessary.Installation and UsageThis package can be downloaded fromPyPIusing the following console command:$ pip install angle-headingsIt can then be imported into a Python program as theangle_headingspackage.Since this package defines only a single class, it is recommended to usefromangle_headingsimportAngleto avoid the need for theangle_headingsprefix.Theangle_headings.AngleClassThe following is a brief description of selected attributes, custom methods, and overloaded methods for theangle_headings.Angleclass.Attributesmeasure (float)-- Current measure of the angle, always normalized to±1/2full revolutions.mod (float)-- Measure of a complete revolution (e.g.2πfor radian measure,360for degree measure).unit (str)-- Name of the unit of measure.Methods__init__([measure[, mod]])--angle_headings.Angleclass constructor. Accepts the following keyword arguments:measure (float) [0.0]-- Initial angle measure.mod (int, float, or str) ["radians"]-- Specifies measure unit. A numerical argument is treated as the measure of a full revolution, while a string argument is taken as the name of a standard unit (radians, degrees, or gradians).convert(mod)-- Returns the angle's measure converted to a different unit.reldiff(other)-- Returns a relative difference between this and another angles' measures, normalized so that 0 represents equality and 1 represents diametrically opposed angles. This is meant to be used as an alternative to direct equality comparisons due to thefloatmeasures.float-Valued Operatorsabs(A)-- Returns the absolute value of an angle's measure.int(A)-- Returns an angle's measure, cast as an integer.float(A)-- Returns an angle's measure, cast as a float.round(A)-- Returns an angle's measure, rounded to the nearest integer.angle_headings.Angle-Valued OperatorsUnary Operators+A-- Returns an exact copy of theangle_headings.Angleobject.-A-- Returns a copy of theangle_headings.Angleobject with its measure negated.Overloaded Binary OperatorsEach of the following operators accepts either anotherangle_headings.Angleobject or afloatas its second argument. If given anotherangle_headings.Angle, the secondangle_headings.Angleis converted to the firstangle_headings.Angle's unit before the operation is performed. If given afloat, the number is used directly.A + B-- Returns anangle_headings.Angleobject with the sum of two angles' measures.A - B-- Returns anangle_headings.Angleobject with the difference between two angles' measures.Scalar OperatorsA * b-- Returns anangle_headings.Angleobject with its measure multiplied by a scalar.A / b-- Returns anangle_headings.Angleobject with its measure divided by a scalar.A // b-- Returns anangle_headings.Angleobject with its measure floor divided by a scalar.A ** b-- Returns anangle_headings.Angleobject with its measure raised to a scalar power.Overloaded Boolean OperatorsEach of the following operators accepts either anotherangle_headings.Angleobject or afloatas its second argument. If given anotherangle_headings.Angle, the secondangle_headings.Angleis converted to the firstangle_headings.Angle's unit before the operation is performed. If given afloat, the number is used directly.Equality ComparisonsDue to the fact that each angle's measure is stored as afloat, it is not recommended to directly test measure equality, and to instead make use of theAngle.reldiff()method.A == B-- Tests for equality of two measures (after unit conversion and normalization).A != B-- Tests for inequality of two measures.Order ComparisonsThe following comparisons are based on the smallest angle between two given measures.A > B-- ReturnsTrueif and only if the smallest angle betweenAandBplacesAcounterclockwise relative toB.A >= B-- ReturnsTrueif and only ifA > BorA == B.A < B-- ReturnsTrueif and only if the smallest angle betweenAandBplacesAclockwise relative toB.A <= B-- ReturnsTrueif and only ifA < BorA == B.
|
anglend
|
No description available on PyPI.
|
angler
|
anglerangler(named for 'adjointnonlineargradients') is a package for simulating and optimizing optical structures.It provides a finite-difference frequency-domain (FDFD) solver for simulating for linear and nonlinear devices in the frequency domain.It also provides an easy to use package for adjoint-based inverse design and optimization of linear and nonlinear devices. For example, you can inverse design optical switches to transport power to different ports for different input powers:angleris released as part of a paperAdjoint method and inverse design for nonlinear optical devices, which can be viewedhere.InstallationOne can install the most stable version ofanglerand all of its dependencies (apart from MKL) usingpip install anglerAlternatively, to use the most current versiongit clone https://github.com/fancompute/angler.git
pip install -e anglerAnd then this directory can be added to path to import angler, i.e.import sys
sys.path.append('path/to/angler')Make angler fasterThe most computationally expensive operation inangleris the sparse linear system solve. This is done withscipy.sparse.linalg.spsolve()by default. If MKL is installed,anglerinstead uses this with a python wrapperpyMKL, which makes things significantly faster, depending on the problem. The best way to install MKL, if using anaconda, isconda install MKL(pyMKL does not work when MKL is pip installed.)Examples / QuickstartThere are several jupyter notebook examples in theNotebooks/directory.For a good introduction, try:Notebooks/Splitter.ipynbFor more specific applications:Electromagnetic simulationsFor modeling linear devices with our FDFD solver (no optimization), seeNotebooks/Linear_system.ipynbFor modeling nonlinear devices with FDFD (no optimization), seeNotebooks/Nonlinear_system.ipynbInverse design & optimizationFor examples of optimizing linear devices, seeNotebooks/Splitter.ipynb
Notebooks/Accelerator.ipynbFor examples of optimizing nonlinear devices, seeNotebooks/2_port.ipynb
Notebooks/3_port.ipynb
Notebooks/T_port.ipynbPackage Structureanglerprovides two main classes,SimulationandOptimization, which perform most of the functionality.Generally,Simulationobjects are used to perform FDFD simulations, andOptimizationclasses run inverse design and optimization algorithms overSimulations. To learn more about howanglerworks and how to use it, please take a look atangler/README.mdfor a more detailed explanation.TestsTo run all tests:python -m unittest discover testsOr to run individually:python tests/individual_test.pyContributingangleris under development and we welcome suggestions, pull-requests, feature-requests, etc.If you contribute a new feature, please also write a few tests and document your changes inangler/README.mdor the wiki.Authorsanglerwas written by Tyler Hughes, Momchil Minkov, and Ian Williamson.CitingIf you useangler, please cite us using@misc{hughes2018adjoint,
Author = {Tyler W. Hughes and Momchil Minkov and Ian A. D. Williamson and Shanhui Fan},
Title = {Adjoint method and inverse design for nonlinear nanophotonic devices},
Year = {2018},
Eprint = {arXiv:1811.01255},
}LicenseThis project is licensed under the MIT License - see theLICENSE.mdfile for details. Copyright 2018 Tyler Hughes.Acknowledgmentsour logo was made byNadine GilmerRIP Ian's contributions before the code mergeWe made use of a lot of code snippets (and advice) fromJerry Shi
|
anglerfish
|
Anglerfish is a simple multipurpose K.I.S.S. Python 3 Helper
Library to help Developers create Apps or Scripts faster, better and easily.
|
angles
|
The Angles module defines several classes for representing angles, and positions
on a sphere. It also has several functions for performing common operations
on angles, such as unit conversion, normalization, creating string
representations and others.The position of M100 reported by SIMBAD is “12 22 54.899 +15 49 20.57”. We can
easily parse these coordinates as follows:>>>from__future__importprint_function>>>fromanglesimportAngularPosition>>>a=AngularPosition.from_hd("12 22 54.899 +15 49 20.57")>>>a.alpha3.24157813039>>>a.delta0.276152636198>>>print(a.alpha)+12HH22MM54.899SS>>>print(a.delta)+15DD49MM20.570SS>>>a.alpha.hms.hms(1,12,22,54.899)>>>a.delta.dms.dms(1,15,49,20.57)>>>a.alpha.dms.dms(1,185,43,43.485)>>>a.delta.hms.hms(1,1,3,17.371)>>>a.alpha.r,a.alpha.d,a.alpha.h,a.alpha.arcs(3.2415781303913653,185.72874583333328,12.381916388888886,668623.4849999998)>>>a.delta.r,a.delta.d,a.delta.h,a.delta.arcs(0.27615263619797403,15.822380555555556,1.0548253703703705,56960.57)InstallationUsepiporeasy_install:$ pip install anglesor,$ easy_install anglesTests are in the filetest_angles.py.ExamplesSome examples are given below. For more details see docstrings of functions and
classes.Unit conversionConvert between radians, degrees, hours and arc-seconds.>>>importmath>>>fromanglesimportr2d,r2arcs,h2r,h2d,d2arcs>>>r2d(math.pi)180.0>>>r2arcs(math.pi)648000.0>>>h2r(12.0)3.141592653589793>>>h2d(12.0)180.0>>>d2arcs(1.0)3600.0Normalizing anglesNormalize value between two limits usingnormalize.>>>fromanglesimportnormalize>>>normalize(-180,-180,180)-180.0>>>normalize(180,-180,180)-180.0>>>normalize(180,-180,180,b=True)180.0>>>normalize(181,-180,180)-179.0>>>normalize(181,-180,180,b=True)179.0>>>normalize(-180,0,360)180.0>>>normalize(36,0,24)12.0>>>normalize(368.5,-180,180)8.5>>>normalize(-100,-90,90)80.0>>>normalize(-100,-90,90,b=True)-80.0>>>normalize(100,-90,90,b=True)80.0>>>normalize(181,-90,90,b=True)-1.0>>>normalize(270,-90,90,b=True)-90.0>>>normalize(271,-90,90,b=True)-89.0Normalizing angles on a sphereSimplify point on sphere to simplest representation usingnormalize_sphere.>>>fromanglesimportnormalize_sphere>>>normalize_sphere(180,91)(0.0,89.0000000000001)>>>normalize_sphere(180,-91)(0.0,-89.0000000000001)>>>normalize_sphere(0,91)(180.0,89.0000000000001)>>>normalize_sphere(0,-91)(180.0,-89.0000000000001)>>>normalize_sphere(120,280)(119.99999999999999,-80.00000000000003)>>>normalize_sphere(375,45)# 25 hours ,45 degrees(14.999999999999966,44.99999999999999)>>>normalize_sphere(-375,-45)(345.00000000000006,-44.99999999999999)Sexagesimal representationConvert decimal value into sexagesimal representation.>>>fromanglesimportdeci2sexa>>>deci2sexa(-11.2345678)(-1,11,14,4.444)>>>deci2sexa(-11.2345678,pre=5)(-1,11,14,4.44408)>>>deci2sexa(-11.2345678,pre=4)(-1,11,14,4.4441)>>>deci2sexa(-11.2345678,pre=4,trunc=True)(-1,11,14,4.444)>>>deci2sexa(-11.2345678,pre=1)(-1,11,14,4.4)>>>deci2sexa(-11.2345678,pre=0)(-1,11,14,4.0)>>>deci2sexa(-11.2345678,pre=-1)(-1,11,14,0.0)>>>x=23+59/60.0+59.99999/3600.0>>>deci2sexa(x,pre=3,lower=0,upper=24)(1,24,0,0.0)>>>deci2sexa(x,pre=3,lower=0,upper=24,upper_trim=True)(1,0,0,0.0)>>>deci2sexa(x,pre=5,lower=0,upper=24,upper_trim=True)(1,23,59,59.99999)Formatting anglesFormat an angle into various string representations usingfmt_angle.>>>fromanglesimportfmt_angle>>>fmt_angle(12.348978659,pre=4,trunc=True)'+12 20 56.3231'>>>fmt_angle(12.348978659,pre=5)'+12 20 56.32317'>>>fmt_angle(12.348978659,s1='HH ',s2='MM ',s3='SS',pre=5)'+12HH 20MM 56.32317SS'>>>x=23+59/60.0+59.99999/3600.0>>>fmt_angle(x)'+24 00 00.000'>>>fmt_angle(x,lower=0,upper=24,upper_trim=True)'+00 00 00.000'>>>fmt_angle(x,pre=5)'+23 59 59.99999'>>>fmt_angle(-x,lower=0,upper=24,upper_trim=True)'+00 00 00.000'>>>fmt_angle(-x)'-24 00 00.000'Parsing sexagesimal stringsParse a sexagesimal number from a string usingphmsdms.>>>fromanglesimportphmsdms>>>phmsdms("12")=={...'parts':[12.0,None,None],...'sign':1,...'units':'degrees',...'vals':[12.0,0.0,0.0]...}True>>>phmsdms("12h")=={...'parts':[12.0,None,None],...'sign':1,...'units':'hours',...'vals':[12.0,0.0,0.0]...}True>>>phmsdms("12d13m14.56")=={...'parts':[12.0,13.0,14.56],...'sign':1,...'units':'degrees',...'vals':[12.0,13.0,14.56]...}True>>>phmsdms("12d14.56ss")=={...'parts':[12.0,None,14.56],...'sign':1,...'units':'degrees',...'vals':[12.0,0.0,14.56]...}True>>>phmsdms("14.56ss")=={...'parts':[None,None,14.56],...'sign':1,...'units':'degrees',...'vals':[0.0,0.0,14.56]...}True>>>phmsdms("12h13m12.4s")=={...'parts':[12.0,13.0,12.4],...'sign':1,...'units':'hours',...'vals':[12.0,13.0,12.4]...}True>>>phmsdms("12:13:12.4s")=={...'parts':[12.0,13.0,12.4],...'sign':1,...'units':'degrees',...'vals':[12.0,13.0,12.4]...}TrueParse string containing angular positionParse coordinates of a point on sphere usingpposition.>>>fromanglesimportpposition>>>ra,de=pposition("12 22 54.899 +15 49 20.57")>>>ra12.38191638888889>>>de15.822380555555556>>>pposition("12 22 54.899 +15 49 20.57",details=True)# doctest: +SKIP{'y':15.822380555555556,'x':12.38191638888889,'numvals':6,'raw_x':{'vals':[12.0,22.0,54.899],'units':'degrees','parts':[12.0,22.0,54.899],'sign':1},'raw_y':{'vals':[15.0,49.0,20.57],'units':'degrees','parts':[15.0,49.0,20.57],'sign':1}}Separation angle along a great circleFind angular separation along a great circle usingsep. This function
uses vectors to find the angle of separation.>>>fromanglesimportr2d,d2r,sep>>>r2d(sep(0,0,0,d2r(90.0)))90.0>>>r2d(sep(0,d2r(45.0),0,d2r(90.0)))45.00000000000001>>>r2d(sep(0,d2r(-45.0),0,d2r(90.0)))135.0>>>r2d(sep(0,d2r(-90.0),0,d2r(90.0)))180.0>>>r2d(sep(d2r(45.0),d2r(-90.0),d2r(45.0),d2r(90.0)))180.0>>>r2d(sep(0,0,d2r(90.0),0))90.0>>>r2d(sep(0,d2r(45.0),d2r(90.0),d2r(45.0)))60.00000000000001>>>importmath>>>90.0*math.cos(d2r(45.0))# Distance along latitude circle.63.63961030678928Bearing between two pointsFind bearing of one point with respect to another usingbear. Likesepthis function uses vectors.>>>fromanglesimportbear,r2d,d2r>>>bear(0,0,0,-d2r(90.0))3.141592653589793>>>bear(0,-d2r(90.0),0,0)0.0>>>bear(0,-d2r(45.0),0,0)0.0>>>bear(0,-d2r(89.678),0,0)0.0>>>r2d(bear(d2r(45.0),d2r(45.0),d2r(46.0),d2r(45.0)))89.64644212193384>>>r2d(bear(d2r(45.0),d2r(45.0),d2r(44.0),d2r(45.0)))-89.64644212193421Angle classClass for representing an angle, conversion between different
units, generating string representations.>>>from__future__importprint_function>>>fromanglesimportAngle>>>a=Angle(sg="12h34m16.592849219")>>>a.r,a.d,a.h,a.arcs# doctest: +NORMALIZE_WHITESPACE(3.291152306055805,188.56913687174583,12.571275791449722,678848.892738285)>>>a.hms.sign,a.hms.hh,a.hms.mm,a.hms.ss(1,12,34,16.593)>>>a.hms.hms(1,12,34,16.593)>>>a.h12.571275791449722>>>a.dms.sign,a.dms.dd,a.dms.mm,a.dms.ss(1,188,34,8.893)>>>a.dms.dms(1,188,34,8.893)>>>a.d188.56913687174583>>>print(a.ounit)hours>>>print(a)+123416.593>>>a.pre,a.trunc(3,False)>>>a.pre=4>>>print(a)+123416.5928>>>a.pre=3>>>a.trunc=True>>>print(a)+123416.592>>>a.ounit="degrees">>>print(a)+1883408.892>>>a.ounit="radians">>>print(a)# doctest: +SKIP3.29115230606>>>a.ounit="degrees">>>a.s1="DD ">>>a.s2="MM ">>>a.s3="SS">>>print(a)+188DD34MM08.892SS>>>a=Angle(r=10)>>>a.d,a.h,a.r,a.arcs,a.ounit# doctest: +NORMALIZE_WHITESPACE(572.9577951308232,38.197186342054884,10,2062648.0624709637,'radians')>>>a.d=10>>>a.d,a.h,a.r,a.arcs,a.ounit# doctest: +NORMALIZE_WHITESPACE(10.0,0.6666666666666666,0.17453292519943295,36000.0,'radians')>>>a.dms.mm=60>>>a.d,a.h,a.r,a.arcs,a.ounit# doctest: +NORMALIZE_WHITESPACE(11.0,0.7333333333333333,0.19198621771937624,39600.0,'radians')>>>a.dms.dms=(1,12,10,5.234)>>>a.d,a.h,a.r,a.arcs,a.ounit# doctest: +NORMALIZE_WHITESPACE(12.168120555555557,0.8112080370370371,0.21237376747404604,43805.234000000004,'radians')>>>a.hms.hms=(1,1,1,1)>>>a.d,a.h,a.r,a.arcs,a.ounit# doctest: +NORMALIZE_WHITESPACE(15.254166666666668,1.0169444444444444,0.2662354329813017,54915.00000000001,'radians')>>>print(a)# doctest: +SKIP0.266235432981>>>a.ounit='hours'>>>print(a)+010101.000>>>a.ounit='degrees'>>>print(a)+151515.000Class for longitudinal anglesA subclass ofAnglethat is normalized to the range[0, 24), i.e., a
Right Ascension like angle. Theounitattribute is always “hours”.>>>from__future__importprint_function>>>fromanglesimportAlphaAngle>>>a=AlphaAngle(d=180.5)>>>print(a)+12HH02MM00.000SS>>>a=AlphaAngle(h=12.0)>>>print(a)+12HH00MM00.000SS>>>a=AlphaAngle(h=-12.0)>>>a=AlphaAngle("12h14m23.4s")>>>print(a)+12HH14MM23.400SS>>>a.r,a.d,a.h,a.arcs(3.204380873430289,183.5975,12.239833333333333,660951.0)>>>a=AlphaAngle(h=12.54678345)>>>a.hms.hms(1,12,32,48.42)>>>a.hms.sign,a.hms.hh,a.hms.mm,a.hms.ss(1,12,32,48.42)>>>print(a)+12HH32MM48.420SS>>>a.pre=5>>>a.hms.hms(1,12,32,48.42042)>>>print(a)+12HH32MM48.42042SS>>>a.s1=" : ">>>a.s2=" : ">>>a.s3="">>>print(a)+12:32:48.42042>>>a.pre=3>>>a.dms.dms(1,188,12,6.306)>>>a=AlphaAngle(h=25.0)>>>print(a)+01HH00MM00.000SS>>>a=AlphaAngle(h=-1.0)>>>print(a)+23HH00MM00.000SS>>>a.hms.hh=23>>>a.hms.mm=59>>>a.hms.ss=59.99999>>>a.hms.hms(1,0,0,0.0)>>>print(a)+00HH00MM00.000SS>>>a.pre=5>>>a.hms.hms(1,23,59,59.99999)>>>print(a)+23HH59MM59.99999SSClass for latitudinal anglesA subclass ofAnglethat is normalized to the range[-90,90], i.e., a
Declination like angle. Theounitattribute is always “degrees”.>>>from__future__importprint_function>>>fromanglesimportDeltaAngle>>>a=DeltaAngle(d=-45.0)>>>print(a)-45DD00MM00.000SS>>>a=DeltaAngle(d=180.0)>>>print(a)+00DD00MM00.000SS>>>a=DeltaAngle(h=12.0)>>>print(a)+00DD00MM00.000SS>>>a=DeltaAngle(sg="91d")>>>print(a)+89DD00MM00.000SS>>>a=DeltaAngle("12d23m14.2s")>>>print(a)+12DD23MM14.200SS>>>a.r,a.d,a.h,a.arcs(0.2161987825813487,12.387277777777777,0.8258185185185185,44594.2)>>>a=DeltaAngle(d=12.1987546)>>>a.dms.dms(1,12,11,55.517)>>>a.pre=5>>>a.dms.dms(1,12,11,55.51656)>>>a.dms.dd,a.dms.mm,a.dms.ss(12,11,55.51656)>>>a.pre=0>>>a.dms.dms(1,12,11,56.0)>>>a=DeltaAngle(d=12.3459876)>>>a.s1=" : ">>>a.s2=" : ">>>a.s3="">>>print(a)+12:20:45.555>>>a=DeltaAngle(d=-91.0)>>>print(a)-89DD00MM00.000SS>>>a=DeltaAngle(d=91.0)>>>print(a)+89DD00MM00.000SS>>>a.dms.sign=1>>>a.dms.dd=89>>>a.dms.mm=59>>>a.dms.ss=59.9999>>>a.pre=3>>>print(a)+90DD00MM00.000SS>>>a.pre=5>>>print(a)+89DD59MM59.99990SS>>>a.dms.dms=(1,0,0,0.0)>>>a.dms.dd=89>>>a.dms.mm=60>>>a.dms.ss=60>>>a.pre=3>>>print(a)+89DD59MM00.000SSClass for points on a unit sphereA class for representing a point on a sphere. The input angle values are
normalized to get the simplest representation of the coordinates of the point.>>>from__future__importprint_function>>>fromanglesimportAngularPosition,r2d>>>a=AngularPosition.from_hd("12 22 54.899 +15 49 20.57")>>>print(a)+12HH22MM54.899SS+15DD49MM20.570SS>>>a=AngularPosition.from_hd("12dd 22 54.899 +15 49 20.57")>>>print(a)+00HH49MM31.660SS+15DD49MM20.570SS>>>a=AngularPosition.from_hd("12d 22 54.899 +15 49 20.57")>>>print(a)+00HH49MM31.660SS+15DD49MM20.570SS>>>a=AngularPosition(alpha=165,delta=-91)# alpha should flip by 180 degrees>>>round(a.alpha.d,12),round(a.delta.d,12)(345.0,-89.0)>>>a.delta.d=-91# alpha should now do another 180 flip and come back to 165>>>round(a.alpha.d,12),round(a.delta.d,12)(165.0,-89.0)>>>a.delta.d=89# there should be no change in normalized angles>>>round(a.alpha.d,12),round(a.delta.d,12)(165.0,89.0)>>>a.alpha.d=-180# alpha should normalize to 180 delta shouldn't change>>>round(a.alpha.d,12),round(a.delta.d,12)(180.0,89.0)>>>pos1=AngularPosition(alpha=12.0,delta=90.0)>>>pos2=AngularPosition(alpha=12.0,delta=0.0)>>>r2d(pos2.bear(pos1))0.0>>>r2d(pos1.bear(pos2))0.0>>>r2d(pos1.sep(pos2))90.0>>>pos1.alpha.h=0.0>>>pos2.alpha.h=0.0>>>r2d(pos1.sep(pos2))90.0>>>r2d(pos2.bear(pos1))0.0>>>r2d(pos1.bear(pos2))0.0CreditsSome of the functions are adapted from theTPMC library byJeffrey
W. Percival.LicenseReleased under BSD; see LICENSE.txt.For comments and suggestions, email to userprasanthhnin thegmail.comdomain.
|
anglewrapper
|
Angle WrapperA simple Python only toolbox for wrapping angles to $\pm180^\circ$, $\left[0^\circ, 360^\circ\right]$, $\pm\pi$, or $\left[0, 2\pi\right]$. Wraps single values, tuples, lists, and other various iterable types that implement the__iter__attribute such as NumPy arrays and Pandas data series.To install:pip install anglewrapperTo run:from anglewrapper import wrap
wrap.to_180(270)This package has no external dependancies to run in Python-only mode. Development and testing requirespytestorunittestinstalled in the local environment as well as numpy.Read me update to trigger automatic release update.This package is serving a few purposes:Writing good Python codeSome basic "agile" workflow practice includingShort lived branches for specific featuresUnit testingCode formatting and lintingContinuous integration and continuous delivery to PyPI via GitHub ActionsBuilding, testing, and delivering Python packagesSome basic C++ practice and packaging it into libraries and/or Python packages
|
anglicize
|
A simple package to help sort non-English names.Free software: BSD 2-Clause LicenseInstallationpip install anglicizeYou can also install the in-development version with:pip install https://github.com/rciorba/python-anglicize/archive/master.zipDocumentationThis library provides one function, which takes a string and substitutes characters.To use:# call the function directly:
anglicize("Łukasz") == "Lukasz"
# or use it to sort a list:
sorted(["Ana", "Łukasz", "Zack"], key=anglicize) == ["Ana", "Łukasz", "Zack"]
# there we go, that's much better than this:
sorted(["Ana", "Łukasz", "Zack"]) == ["Ana", "Zack", "Łukasz"]RationaleThe purpose of this library is to help you sort non-English names writen in Latin-based alphabets.Different languages have wildly different rules for sorting, for exampleÖcomes afterZin
Finnish but afterOin Hungarian. The approach taken here is to treat visually similar letters
the same, so basicallyÖÔÓÒṌṎ(and others) should all becomeO.Handling letters that have little similarity to A-ZThe German ß is the main issue here. I chose to handle it like an S, mostly because it’s different
enough from B (the most similar visually) and because it’s well known as a version of S to most
Europeans.Languages coveredAlbanianAzerbaijaniBosnianBulgarian transliterationCroatianDutchEstonianFinnishFrenchGagauzGermanHungarianIcelandicLatvianLithuanianLuxembourgishMontenegrinNorwegianPolishPortugueseRomanianSerbianSpanishSwedishTatarTurkishTurkmenContributingDo you know a language written in a Latin alphabet and want to check it’s correctly handled? Have a
look intests/test_anglicize.py. If the language is there please check all “special” letters are
handled. This list has been mostly compiled off of Wikipedia, so I would not be surprised to hear
about errors :)You can either make the changes and submit a PR or just create an issue mentioning
- language
- characters which need handlingDevelopmentTo run tests for all Python environments run:toxChangelog0.0.3 (2020-03-08)Fix rationale example.0.0.2 (2020-03-08)Fix readme example.0.0.1 (2020-03-07)First release on PyPI.
|
anglisano
|
Failed to fetch description. HTTP Status Code: 404
|
anglo
|
🪐 A modern lightweight micro web framework for Python 3.About|Installation|Usage|Features|Contributors|LicenseAboutNext:InstallationAnglois anopen sourceframework use for deploying and developing,web applicationswith modern and lightweight integration. It was created to build web applications easily and reliable.It also comes with alot of differentfeaturesthat you may want to check out. Anglo was mainlybuilt at the top ofWSGI Environment. It serves as a full wrapper for WSGI that makes yourproduction easier. The API wrapper for Anglo is simmilar to famous web framework,Flask andDjango.Learn MoreInstallationUsageFeaturesContributorsLicenseAnglo is license underMIT
|
anglr
|
Planar angle mathematics library for Python.This library contains many different functions for converting between units, comparing angles, and doing angle arithmetic.Links:PyPIGitHubQuickstart:pip3 install anglr.RationaleConsider the following trivial angle comparison code:importmathheading=get_compass_value()# angle in radians normalized to $[0, 2*pi)$iftarget-math.pi/4<=heading<=target+math.pi/4:print("Facing the target")else:print("Not facing the target")Angle code is everywhere. The above is totally, utterlywrong(consider what happens whentargetis 0), yet this could easily be overlooked while writing and during code review.With anglr, there is a better way:importmathfromanglrimportAngleheading=Angle(get_compass_value())ifheading.angle_between(target)<=math.pi/4:print("Facing the target")else:print("Not facing the target")Much better - this will now correctly take modular arithmetic into account when comparing angles.ExamplesAngle creation:frommathimportpifromanglrimportAngleprint(Angle())print(Angle(87*pi/2))print(Angle(pi/2,"radians"))print(Angle(Angle(pi/2,"radians")))# same as aboveprint(Angle(64.2,"degrees"))print(Angle(384.9,"gradians"))print(Angle(4.5,"hours"))print(Angle(203.8,"arcminutes"))print(Angle(42352.7,"arcseconds"))print(Angle((56,32),"vector"))# angle in standard position - counterclockwise from positive X-axisAngle conversion:fromanglrimportAnglex=Angle(58.3)print([x],str(x),x.radians,x.degrees,x.gradians,x.hours,x.arcminutes,x.arcseconds,x.vector,x.x,x.y)print(complex(x))print(float(x))print(int(x))x.radians=pi/2print(x.dump())x.degrees=64.2print(x.dump())x.gradians=384.9print(x.dump())x.hours=4.5print(x.dump())x.arcminutes=203.8print(x.dump())x.arcseconds=42352.7print(x.dump())x.vector=(56,32)print(x.dump())Angle arithmetic:frommathimportpifromanglrimportAngleprint(Angle(pi/6)+Angle(2*pi/3))print(x*2+Angle(3*pi/4)/4+5*Angle(pi/3))print(-abs(+Angle(pi)))print(round(Angle(-75.87)))print(Angle(-4.3)<=Angle(pi/4)>Angle(0.118)==Angle(0.118))print(Angle(-870.3,"gradians").normalized())print(Angle(-870.3,"gradians").normalized(0))# same as aboveprint(Angle(-870.3,"gradians").normalized(0,2*pi))# same as aboveprint(Angle(-870.3,"gradians").normalized(-pi,pi))print(Angle(-870.3,"gradians").normalized(-pi,0))print(Angle(1,"degrees").angle_between_clockwise(Angle(0,"degrees")))print(Angle(1,"degrees").angle_between(Angle(0,"degrees")))print(Angle(0,"degrees").angle_within(Angle(-45,"degrees"),Angle(45,"degrees")))print(Angle(-1,"degrees").angle_within(Angle(-1,"degrees"),Angle(1,"degrees"),strictly_within=True))print(Angle(-1,"degrees").angle_to(Angle(180,"degrees")))print(Angle(0,"degrees").angle_to(Angle(180,"degrees")))To run all of the above as tests, simply runpython3 tests.pyin the project directory.InstallingThe easiest way to install this is usingpip3 install anglr.Otherwise, download the source distribution fromPyPI, and extract the archive.In the folder, runpython3 setup.py install.RequirementsThis library requires Python 3.2 or higher to run.AuthorsUberi <[email protected]> (Anthony Zhang)Please report bugs and suggestions at theissue tracker!LicenseCopyright 2014-2015Anthony Zhang (Uberi).The source code is available online atGitHub.This program is made available under the 3-clause BSD license. SeeLICENSE.txtfor more information.
|
angmom-suite
|
angmom_suiteangmom_suiteis a python package for working with phenomenological spin and angular momentum operatorsInstallation viapipInstallangmom_suiteusingpip(if using a shared machine, add the--userargument afterinstall)pip install angmom_suiteUpdatingUpdate the code usingpip(if using a shared machine, add the--userargument afterinstall)pip install angmom_suite --upgradeInstallation withpipeditable installOnly do this if you are developing (i.e. changing) the code.Clone a copy of this repository, preferably while within a directory called gitmkdir -p git; cd git
git clone https://gitlab.com/chilton-group/angmom_suiteNavigate to the package directorycd angmom_suite/packagesand install the package in editable mode (if using a shared machine, add the--userargument afterinstall)pip install -e .When you're done developing (i.e. your changes have been merged to the master),
or if you just want to use the current release version of the package, uninstall usingpippip uninstall angmom_suiteand follow the Installation viapipinstructions above.UsageTheangmom_suitecommand line interface can be invoked withangmom_suite -hwhich prints a list of available subprograms.Alternatively, the individual submodules can be imported into a python program or script as per usual.Building a.whlfile (Advanced)Only do this if you are told to.To build a copy of theangmom_suite.whlfile, move to thepackagedirectory.Now run./build_binaries.shThen install the.whlfile withpip(if using a shared machine, add the--userargument afterinstall)pip install dist/*.whlDocumentationThedocumentationfor this package is hosted by gitlab, and is automatically generated whenever new code is committed to themainbranch. The automatic generation of this documentation relies on a common layout for comments and docstrings within the code, seecontributingfor more information.DevelopmentBefore making changes to this repository, please follow the steps outlined in theChilton group wiki.BugsIf you believe you have a bug,please check that you are using the most up to date version of the code.If that does not fix the problem, please create an issue on GitLab detailing the following:The commands you enteredThe error messageRemember to simplify the problem as much as possible in order to provide a minimum working example, e.g. an example for a small molecule rather than one with 100000 atoms.Then, look at the code, try and figure out what you think is wrong if possible, and include this in your issue.
|
ango
|
For using API functionalities of Ango-Hub platform.from ango.sdk import SDK
# Init SDK with API key for detailed functioanlities of Ango API https://docs.ango.ai/api/api-documentation
sdk = SDK(api_key="10541bc8-bed8-4775-8ffc-323eabfcc9ae")
# Upload from local files
files = ["/home/ofk/Pictures/samples/0003.DCM", "/home/ofk/Pictures/samples/0009.DCM"]
response = sdk.upload_files("61f8d94a79002950df12234a", files) # With Project ID
print(response)
# Or upload from hosted resources
files = [{
"data": "https://i.imgur.com/OB0y6MR.jpg",
"externalId": "111"
},
{
"data": "https://i.imgur.com/CzXTtJV.jpg",
"externalId": "112"
}]
response = sdk.upload_files_cloud("61f8d94a79002950df12234a", files) # With Project ID
print(response)For developing custom plugins that can be integrated to Ango-Hub platform.from ango import plugin
# Create callback function for your plugin.
# Input and output definitions are set on Ango-Hub on plugin register
def callback(data):
result = model(data)
return result
p = plugins.Plugin("<YOUR_PLUGIN_ID>", "<YOUR_API_KEY>", callback)
plugin.run(p)
|
angola
|
AngolaAngolaAPIdbxql_to_aqlparse_dict_mutationsgen_xidCollectionCollectionItemCollectionActiveRecordMixinConnectionimport angola
#--- connect
db = angola.db(hosts="http://host:8529", username="root", password:str)
#--- select collection
coll = db.select_collection('test')
#--- insert item
coll.insert({k:v, ...})
#--- insert item with custom _key
coll.insert({k:v,...}, _key='awesome')Query{
"_modified_at:$datetime": "+2hh"
}Format:YYYY: Year
MM: Month
DD: Date
HH: Hour
mm: Min
ss: seconds
ISODATE: YYYY-MM-DDTHH:mm:ss$AND and $ORfilters = {
"$or": [
{ // query between dates
"_created_at:$lt": "@@CURRDATE() -2days",
"_created_at:$gt": "@@CURRDATE() +2days"
}
]
}InsertUpdateDeleteCollectionSubCollectionOperatorsCustom Operators
|
angora
|
angorais my personal data science python development library collection.Quick links:GitHub HomepageOnline DocumentationPyPI downloadInstallIssue submit and feature requestAPI reference and source codeInstallangorais released on PyPI, so all you need is:$pipinstallangoraTo upgrade to latest version:$pipinstall--upgradeangoraangoradoesn’t force user to install all pre-requisite third party packages. You can install it when you see the error message and when you need it.
|
angorapy
|
Anthropomorphic Goal-Oriented Robotic Control for Neuroscientific ModelingAngoraPyis an open source modeling library forgoal-oriented researchinneuroscience. It provides a simple interface to train deep neural network models of the human brain on various, customizable, sensorimotor tasks, using reinforcement learning. It thereby empowers goal-driven modeling to surpass the sensory domain and enter that of sensori_motor_ control, closing the perception-action loop.AngoraPyis designed to require no deeper understanding of reinforcement learning. It employs state-of-the-art machine learning techniques, optimized for distributed computation scaling from local workstations to high-performance computing clusters. We aim to hide as much of this under the hood of an intuitive, high-level API but preserve the option for customizing most aspects of the pipeline.This library is developed as part of theHuman Brain ProjectatCCN Maastricht. It is an effort to build software by neuroscientists, for neuroscientists. If you have suggestions, requests or questions, feel free toopen an issue.:sparkles: FeaturesSupported Task SettingsDiscrete Action Spaces (Categorical, MultiCategorical)Continuous Action Spaces (Beta, Gaussian)Discrete State SpacesContinuous State SpacesSupported Model TypesRecurrent NetworksConvolutional NetworksRecurrent+Convolutional NetworksSupported Model TrainingLocal Distributed TrainingHPC Distributed TrainingTraining BackendProximal Policy OptimizationAsymmetric Policy/Value NetworksTruncated Backpropagation Through TimeEntrypoints & DeploymentPyPI PackageDocker filesSource code📥 InstallationAngoraPy is available on PyPI. First, install requirements:sudoaptinstallswiglibopenmpi-devThen install AngoraPy from pip.pipinstallangorapyFrom sourceAlternatively, you can download this repository or the source code of any previous release or branch and install from source, using pip.pipinstall-e.This way, if you make changes to the source code, these will be recognized in the installation (without the need to reinstall).DockerAlternatively, you can install AngoraPy and all its dependencies in a docker container using the Dockerfile provided in this repository (/docker/Dockerfile). To this end, download the repository and build the docker image from the /docker directory:sudodockerbuild-tangorapy:masterhttps://github.com/ccnmaastricht/angorapy.git#master-f-<DockerfileTo install different versions, replace#masterin the source by the tag/branch of the respective version you want to install.🚀 Getting StartedThe scriptstrain.py,evaluate.pyandobserve.pyprovide ready-made scripts for training and evaluating an agent in any environment. Withpretrain.py, it is possible to pretrain the visual component.benchmark.pyprovides functionality for training a batch of agents possibly using different configs for comparison of strategies.Training an AgentThetrain.pycommandline interface provides a convenient entry-point for running all sorts of experiments using the builtin models and environments in angorapy. You can train an agent on any environment with optional hyperparameters. Additionally, a monitor will be automatically linked to the training of the agent. For more detail consult theREADME on monitoring.Base usage oftrain.pyis as follows:python train.py ENV --architecture MODEL
For instance, trainingLunarLanderContinuous-v2using thedeeperarchitecture is possible by running:python train.py LunarLanderContinuous-v2 --architecture deeper
For more advanced options like custom hyperparameters, consultpython train.py -hEvaluating and Observing an AgentThere are two more entry points for evaluating and observing an agent:evaluate.pyandobserve.py. General usage is as followspython evaluate.py ID
Where ID is the agent's ID given when its created (train.pyprints this outt, in custom scripts get it withagent.agent_id).Writing a Training ScriptTo train agents with custom models, environments, etc. you write your own script. The following is a minimal example:fromangorapyimportmake_taskfromangorapy.modelsimportget_model_builderfromangorapy.agent.ppo_agentimportPPOAgentenv=make_task("LunarLanderContinuous-v2")model_builder=get_model_builder("simple","ffn")agent=PPOAgent(model_builder,env)agent.drill(100,10,512)For more details, consult theexamples.🎓 DocumentationDetailed documentation of AngoraPy is provided in the READMEs of most subpackages. Additionally, we provideexamples and tutorialsthat get you started with writing your own scripts using AngoraPy. For further readings on specific modules, consult the following READMEs:Agent[WIP]EnvironmentsModelsAnalysisMonitoringIf you are missing a documentation for a specific part of AngoraPy, feel free to open an issue and we will do our best to add it.🔀 Distributed ComputationPPO is an asynchronous algorithm, allowing multiple parallel workers to generate experience independently.
We allow parallel gathering and optimization through MPI. Agents will automatically distribute their workers evenly on
the available CPU cores, while optimization is distributed over all available GPUs. If no GPUs are available, all CPUs
share the task of optimizing.Distribution is possible locally on your workstation and on HPC sites.💻 Local Distributed Computing with MPITo use MPI locally, you need to have a running MPI implementation, e.g. Open MPI 4 on Ubuntu.
To executetrain.pyvia MPI, runmpirun-np12--use-hwthread-cpuspython3train.py...where, in this example, 12 is the number of locally available CPU threads and--use-hwthread-cpusmakes available threads (as opposed to only cores). Usage oftrain.pyis as described previously.:cloud: Distributed Training on SLURM-based HPC clustersPlease note that the following is optimized and tested on the specific cluster we use, but should extend to at least
any SLURM based setup.On any SLURM-based HPC cluster you may submit your job with sbatch usising the following script template:#!/bin/bash -l#SBATCH --job-name="angorapy"#SBATCH --account=xxx#SBATCH --time=24:00:00#SBATCH --nodes=32#SBATCH --ntasks-per-core=1#SBATCH --ntasks-per-node=12#SBATCH --cpus-per-task=1#SBATCH --partition=normal#SBATCH --constraint=gpu&startx#SBATCH --hint=nomultithreadexportOMP_NUM_THREADS=$SLURM_CPUS_PER_TASKexportCRAY_CUDA_MPS=1# load virtual environmentsource${HOME}/robovenv/bin/activateexportDISPLAY=:0
srunpython3-utrain.py...The number of parallel workers will equal the number of nodes times the number of CPUs per node
(32 x 12 = 384 in the template above).🔗 Citing AngoraPyIf you use AngoraPy for your research, please cite us as followsWeidler, T., & Senden, M. (2020). AngoraPy: Anthropomorphic Goal-Oriented Robotic Control for Neuroscientific Modeling [Computer software]
Or using bibtex@software{angorapy2020,
author = {Weidler, Tonio and Senden, Mario},
month = {3},
title = {{AngoraPy: Anthropomorphic Goal-Oriented Robotic Control for Neuroscientific Modeling}},
year = {2020}
}
|
angou-binance
|
No description available on PyPI.
|
angou-bitfinex
|
No description available on PyPI.
|
angou-bitmex
|
No description available on PyPI.
|
angou-huobi
|
No description available on PyPI.
|
angou-okex
|
No description available on PyPI.
|
angou-poloniex
|
No description available on PyPI.
|
angquick
|
UNKNOWN
|
angr
|
angrangr is a platform-agnostic binary analysis framework.
It is brought to you bythe Computer Security Lab at UC Santa Barbara,SEFCOM at Arizona State University, their associated CTF team,Shellphish, the open source community, [email protected] LinksHomepage:https://angr.ioProject repository:https://github.com/angr/angrDocumentation:https://docs.angr.ioAPI Documentation:https://api.angr.io/en/latest/What is angr?angr is a suite of Python 3 libraries that let you load a binary and do a lot of cool things to it:Disassembly and intermediate-representation liftingProgram instrumentationSymbolic executionControl-flow analysisData-dependency analysisValue-set analysis (VSA)DecompilationThe most common angr operation is loading a binary:p = angr.Project('/bin/bash')If you do this in an enhanced REPL like IPython, you can use tab-autocomplete to browse thetop-level-accessible methodsand their docstrings.The short version of "how to install angr" ismkvirtualenv --python=$(which python3) angr && python -m pip install angr.Exampleangr does a lot of binary analysis stuff.
To get you started, here's a simple example of using symbolic execution to get a flag in a CTF challenge.importangrproject=angr.Project("angr-doc/examples/defcamp_r100/r100",auto_load_libs=False)@project.hook(0x400844)defprint_flag(state):print("FLAG SHOULD BE:",state.posix.dumps(0))project.terminate_execution()project.execute()Quick StartInstall InstructionsDocumentation asHTMLand sources in the angrGithub repositoryDive right in:top-level-accessible methodsExamples using angr to solve CTF challenges.API Referenceawesome-angr repo
|
angrcli
|
none
|
angrdbg
|
No description available on PyPI.
|
angreal
|
AngrealDocs are available here.Angreal is meant to:allow the consistent creation of projectsprovide consistent methods for interacting with projectsQuick StartInstall viapipInitialize a project from a templateUse the template$:pipinstall'angreal>=2'#pip install angreal will also work$:angrealinithttps://github.com/angreal/pythonWhat is it?Angreal is an attempt to solve two problems that I was running into in
both my personal and professional life as a data scientist and software
developer. I do things often enough that they needed automation, I
don't do things so often that I remember all of the steps/commands I
might need to get them done. Angreal solves this problem by allowing me
to remember by forgetting : I only have to remember the command to do
something not the actual steps to complete the task.How does it solve these challenges ?Angreal provides a way to template the structure of projects and a way
of executing methods for interacting with that project in a consistent
manner. These methods (called tasks) travel with the project so while
templated initially, they're customizable to the project - allowing some
level of flexibility in how a task functions between projects.Why 2.0 ?The original angreal was built on top of a number of python modules that
were under active development and used by a number of other projects.
The nature of the application itself meant that core application found
itself in dependency hell regularly - and became rather annoying to use.
The 2.0.0 release is a complete rewrite that usesRustto provide a compiled binary with the goal that it will
require no external python dependencies.
|
angrgdb
|
No description available on PyPI.
|
angrivhid97
|
Ejemplo de clase de ejercicio de la tarea 4This program is free software: You can redistribute it and/or modify it under the terms of license by the Free Software Foundation, either version 3 of the License(at your option) any other version.
|
angr-management
|
angr ManagementThis is the GUI for angr.
Launch it and analyze some binaries!Some screenshots:InstallationPortable, pre-built executableThe easiest way to run angr-management is by grabbing a bundled release from the releases page:https://github.com/angr/angr-management/releasesBuilds can be extracted and then run from anywhere.
Note that builds are currently unsigned.From PyPITo install angr-management, use pip:pip install angr-managementangr-management can then be run with the commandangr-management.Development InstallSeeangr-devfor how to set up a development environment for the angr suite.
angr-management is included by default and checked out toangr-managementdirectory.
If you encounter dependency issues, re-runningsetup.shorsetup.batfrom angr-dev will ensure all dependencies are installed.angr-management can then be run withangr-managementorpython start.py.FLIRT signatures: For now, please manually clone FLIRT signatures by runninggit clone --recurse-submodules https://github.com/angr/angr-management, which will clone theflirt_signaturessubmodule.UsageShortcutsLoad a new binary:Ctrl+OLoad a new Docker ImageCtrl+Shift+OLoad a Trace FileCtrl+Shift+TSave angr database... :Ctrl+SSave angr database as... :Ctrl+Shift+SDecompile:F5Documentation:Alt+HNext Tab:Ctrl+TabPrevious Tab:Ctrl+Shift+TabConfigurationConfiguration files locations vary by platform.Windows:~\AppData\Local\angr-management\config.tomlmacOS:~/Library/Preferences/angr-management/config.tomlLinux:~/.config/angr-management/config.tomlPluginsPlugins may be installed by placing a subdirectory underplugins. The directory must contain an__init__.pylike that inTestPlugin:from .test_plugin import TestPlugin
PLUGIN_CLS_NAME = TestPlugin.__name__This also allows you to import a plugin class from another package entirely. The plugin itself should inherit fromBasePlugin. Callbacks and events are a work in progress, so the API is subject to change. SeeTestPluginfor an example of a multithreaded plugin sample.ScriptingTake a look athttps://docs.angr.io/extending-angr/angr_management!Building with PyInstallerTo build a portable executable using PyInstaller, install angr management into a python envrionment with thepyinstallerextra.
Do not install anything in editable mode (pip's-e), as PyInstaller currentlyfails to bundlemodules installed with editable mode.
Then, runpyinstaller angr-management.spec.If things go wrong, the best bet is to reference the nightly build pipeline and thePyInstaller docs.
The CI environment that produces nightly builds is at.github/workflows/nightly-build.ymland.github/workflows/nightly-build.sh.
|
angrop
|
angropangrop is a rop gadget finder and chain builderOverviewangrop is a tool to automatically generate rop chains.It is built on top of angr's symbolic execution engine, and uses constraint solving for generating chains and understanding the effects of gadgets.angrop should support all the architectures supported by angr, although more testing needs to be done.Typically, it can generate rop chains (especially long chains) faster than humans.It includes functions to generate chains which are commonly used in exploitation and CTF's, such as setting registers, and calling functions.UsageThe ROP analysis finds rop gadgets and can automatically build rop chains.>>>importangr,angrop>>>p=angr.Project("/bin/ls")>>>rop=p.analyses.ROP()>>>rop.find_gadgets()>>>chain=rop.set_regs(rax=0x1337,rbx=0x56565656)>>>chain.payload_str()b'\xb32@\x00\x00\x00\x00\x007\x13\x00\x00\x00\x00\x00\x00\xa1\x18@\x00\x00\x00\x00\x00VVVV\x00\x00\x00\x00'>>>chain.print_payload_code()chain=b""chain+=p64(0x410b23)# pop rax; retchain+=p64(0x1337)chain+=p64(0x404dc0)# pop rbx; retchain+=p64(0x56565656)Chains# angrop includes methods to create certain common chains# setting registerschain=rop.set_regs(rax=0x1337,rbx=0x56565656)# writing to memory# writes "/bin/sh\0" to address 0x61b100chain=rop.write_to_mem(0x61b100,b"/bin/sh\0")# calling functionschain=rop.func_call("read",[0,0x804f000,0x100])# adding values to memorychain=rop.add_to_mem(0x804f124,0x41414141)# chains can be added together to chain operationschain=rop.write_to_mem(0x61b100,b"/home/ctf/flag\x00")+rop.func_call("open",[0x61b100,os.O_RDONLY])+...# chains can be printed for copy pasting into exploits>>>chain.print_payload_code()chain=b""chain+=p64(0x410b23)# pop rax; retchain+=p64(0x74632f656d6f682f)chain+=p64(0x404dc0)# pop rbx; retchain+=p64(0x61b0f8)chain+=p64(0x40ab63)# mov qword ptr [rbx + 8], rax; add rsp, 0x10; pop rbx; ret...GadgetsGadgets contain a lot of information:For example look at how the following code translates into a gadget0x403be4:andebp,edi0x403be6:movQWORDPTR[rbx+0x90],rax0x403bed:xoreax,eax0x403bef:addrsp,0x100x403bf3:poprbx0x403bf4:ret>>>print(rop.gadgets[0])Gadget0x403be4Stackchange:0x20Changedregisters:set(['rbx','rax','rbp'])Poppedregisters:set(['rbx'])Registerdependencies:rbp:[rdi,rbp]Memorywrite:address(64bits)dependson:['rbx']data(64bits)dependson:['rax']The dependencies describe what registers affect the final value of another register.
In the example above, the final value of rbp depends on both rdi and rbp.
Dependencies are analyzed for registers and for memory actions.
All of the information is stored as properties in the gadgets, so it is easy to iterate over them and find gadgets which fit your needs.>>>forginrop.gadgets:if"rax"ing.popped_regsand"rbx"noting.changed_regs:print(g)Gadget0x4032b3Stackchange:0x10Changedregisters:set(['rax'])Poppedregisters:set(['rax'])Registerdependencies:TODO'sAllow strings to be passed as arguments to func_call(), which are then written to memory and referenced.Add a function for open, read, write (for ctf's)Allow using of angr objects such as BVV, BVS to make using symbolic values easyThe segment analysis for finding executable addresses seems to break on non-elf binaries often, such as PE files, kernel modules.Allow setting constraints on the generated chain e.g. bytes that are valid.Common gotchasMake sure to import angrop before calling proj.analyses.ROP()Make sure to call find_gadets() before trying to make chains
|
angr-pwntools
|
pwntools - CTF toolkitpwntools logoPwntools is a CTF framework and exploit development library. Written in
Python, it is designed for rapid prototyping and development, and
intended to make exploit writing as simple as possible.frompwnimport*context(arch='i386',os='linux')r=remote('exploitme.example.com',31337)# EXPLOIT CODE GOES HEREr.send(asm(shellcraft.sh()))r.interactive()DocumentationOur documentation is available atdocs.pwntools.comA series of tutorials is alsoavailable
onlineTo get you started, we’ve provided some example solutions for past CTF
challenges in ourwrite-ups
repository.InstallationPwntools is best supported on 64-bit Ubuntu LTS releases (14.04, 16.04,
18.04, and 20.04). Most functionality should work on any Posix-like
distribution (Debian, Arch, FreeBSD, OSX, etc.).Python3 is suggested, but Pwntools still works with Python 2.7. Most of
the functionality of pwntools is self-contained and Python-only. You
should be able to get running quickly withapt-getupdateapt-getinstallpython3python3-pippython3-devgitlibssl-devlibffi-devbuild-essentialpython3-mpipinstall--upgradepippython3-mpipinstall--upgradepwntoolsHowever, some of the features (assembling/disassembling foreign
architectures) require non-Python dependencies. For more information,
see thecomplete installation instructions
here.ContributionSeeCONTRIBUTING.mdContact and CommunityIf you have any questions not worthy of abug
report, join the
Discord server athttps://discord.gg/96VA2zvjCB
|
angr-utils
|
Various utilities for angr binary analysis framework
|
angryduckchool
|
OOP Learning Example by Angryduck
|
angryduckschool
|
วิธีติดตั้งเปิด CMD / Terminalpipinstallangryduckschoolวิธีเล่นเปิด IDLE ขึ้นมาแล้วพิมพ์…fromangryschoolimportStudent,SpecialStudentprint('========1 Jan========')student0=SpecialStudent('Mark Zuckerberg','Bill Gates')student0.AskEXP()student0.ShowEXP()student1=Student('Albert')print(student1.name)student1.Hello()print('------------')student2=Student('Steve')print(student2.name)student2.Hello()print('========2 Jan========')print('------Angryduck: Who want to learn coding?---(Give 10 exp)----')student1.AddEXP(10)print('========3 Jan========')student1.name='Albert Einstein'print('Exp of each student : ')print(student1.name,student1.exp)print(student2.name,student2.exp)print('========4 Jan========')foriinrange(5):student2.Coding()student1.ShowEXP()student2.ShowEXP()พัฒนาโดย: Angryduck888 FB: N/A
YouTube: N/A
|
angryexception
|
angryexceptionAn exception handler that tells you that you're stupid.Installationpip install angryexceptionYou will also need to have either libespeak, sapi5, or nsss speech engines installed.Usagefromangryexceptionimportinstallinstall()# Create an exceptionraiseException()
|
angry-gadget
|
No description available on PyPI.
|
angrylibs
|
Angry LibsHave a fluffy time by making some slimy choicesTo get started, take a look at the. If you want to see what's new, check out the!ContributingAll of Angry Libs is open source! You can get started with the following links:
|
angry-logger
|
Angry Logging Made EasyDo you want to show your logger to be more passive aggressive? maybe just actual aggressive? This is the library for
you.InstallationYou can install via pip!pipinstallangry-loggerUsageWhen deciding your project needs more aggression, all you have to do is tell the Angry Logger to go to town. Like so.importangry_loggerangry_logger.start()If you're not a fan of naughty words, you can tell the angry logger to be less of a potty mouth.importangry_loggerangry_logger.start(potty_mouth=False)From here, use your logging as you normally would.importangry_loggerimportloggingangry_logger.start(potty_mouth=False)logging.basicConfig(level=logging.DEBUG)test_logger=logging.getLogger("test_logger")test_logger.debug("this is a test debug message")test_logger.info("this is a test info message")test_logger.warning("this is a test warning message")test_logger.error("this is a test error message")This will output your new normal, information hidden behind abuse.DEBUG:test_logger:Can I go home now? this is a test debug message
INFO:test_logger:this is a test info message. But what do you mean by that?
WARNING:test_logger:Did you do something stupid? Look: this is a test warning message
ERROR:test_logger:this is a test error message????? Are you *****ING kidding me??
|
angry-purple-tiger
|
angry-purple-tigerAnimal-based digests for humans... in Python.OverviewAngry Purple Tiger generates animal-based hash digests meant to be memorable and human-readable. Angry Purple Tiger is apt for anthropomorphizing project names, crypto addresses, UUIDs, or any complex string of characters that need to be displayed in a user interface.This is a Python port of Helium's originalJavaScript implementation.Installationpip install angry-purple-tigerUsagefromangry_purple_tigerimportanimal_hash# input strings (like wallet addresses) must be encodedname=animal_hash('112CuoXo7WCcp6GGwDNBo6H5nKXGH45UNJ39iEefdv2mwmnwdFt8'.encode())print(name)# feisty-glass-dalmation
|
angrytest
|
This is the readme
Now included init py script.Functions :
callPrint(num)
sayHi(name)
talklToMe(name)Import :
from angryziber import pypitestangry as pUse :
p.callPrint()
p.callPrint(10)
p.talklToMe(‘Danny’)Updated Licence Agreement (c) 2017.
Updated README
|
angr-z3
|
Failed to fetch description. HTTP Status Code: 404
|
angr-zelos-target
|
Zelos Concrete Execution Engine for angrProvides support for usingzelos(a python-based binary instrumentation and emulation platform) as a concrete execution engine inangrvia thesymbioninterface. Symbion provides an interface that enablesangrto get and set program state from an external execution engine. Conversely, this enableszelosto take advantage of the symbolic execution capabilities ofangr.InstallationYou first needangrwithsymbion. Their documentation recommends installation in a separate virtual environment, as several python packages are customized, includingunicorn. This is the boilerplate to setup angr in a new virtual environment (**). Refer to their documentation for more comprehensive instructions.$sudoapt-getinstallpython3-devlibffi-devbuild-essentialcmakegdb-multiarch
$gitclonehttps://github.com/angr/angr-targets.git
$python3-mvenv~/.venv/angr&&source~/.venv/angr/bin/activate(angr)$pipinstallwheel&&pipinstallangr&&pipinstall-eangr-targets(**) As of this writing, thepiprelease ofsymbionis not working. Instead, use the development version, which already includesangr-targets:$gitclonehttps://github.com/angr/angr-dev.git
$cdangr-dev&&./setup.sh-i-eangr
$source~/.virtualenvs/angr/bin/activateOnce you have theangrenvironment setup, install theangr-zelos-targetpackage within the environment to enablezelosas a concrete target:(angr)$pipinstallangr-zelos-targetInstall thezelos emulatorin a separate virtual environment, e.g.:(zelos)$pipinstallzelosBasic UsageWrite yourangrscripts as you usually would, but specify thezelosconcrete target when creating the project:fromangr_zelos_targetimportZelosConcreteTarget...zelos_target=ZelosConcreteTarget()project=angr.Project(filepath,concrete_target=zelos_target,use_sim_procedures=True,)Use theangr.exploration_techniques.Symbionexploration technique when you want to concretely execution inzelos.Before running yourangrscript, start thezeloszdbserveron the target binary:(zelos)$python-mzelos.zdbserverFILENAMEThezdbserverandangrscripts can run on the same system, but be sure to run them in separate python environments, as both packages use different versions of theunicornCPU emulator.Symbion Tutorial: "Fusing Concrete and Symbolic Execution"As an example, we have reimplemented thesymbion tutorialusing thezelosconcrete engine. In that tutorial, the goal is to force execution of a binary down the path that prints "Executing stage 2 fake malware V2" instead of the default message:$./not_packed_elf64[+]Parsingmalwareconfiguration[+]Virtualenvironmentdetected!Thenot_packed_elf64binary is duplicated from theangr-binariesrepository. The reimplemented tutorialexamplescript will concretely execute up to the decision point, solve for a value that will ultimately drive excution to the desired path, write that value into zelos, then resume execution in zelos. The basic workflow is to start the binary via thezelos.zdbserver, then run theangrscript that utilizes thezdbserver, for instance:Terminal 1 (zelos):(zelos)$python-mzelos.zdbservernot_packed_elf64Terminal 2 (angr):(angr)$python3-mangr_zelos_target.exampleTerminal 2 Output:[0]Createdangr_zelosprojectfor'angr_zelos_target/example/not_packed_elf64'[1]Gottodecisionpointconcretely.[2]Symbolicallyfindingsecondstage@0x400bb6[3]Executingconcretelyuntilexit@0x65310d[4]DONE.Terminal 1 Output:[main] [SYSCALL]brk(addr=0x0)->0x900000a4[main] [SYSCALL]openat(dirfd=0xffffff9c,pathname=0xb229170("not_packed_elf64"),flags=0x80000)->18...
...
[main] [SYSCALL]brk(addr=0x90022000)->0x90022000Breakpoint"bp_400af3"[StdOut]:'bytearray(b'[+]Parsingmalwareconfiguration\n\n[+]Executingstage2fakemalwareV2\n\n')'[main] [SYSCALL]write(fd=0x1,buf=0x90000310("[+]Parsing malware configuration [+] Executing stage 2 fake malware V2"),count=0x3a)->3a[main] [SYSCALL]exit_group(status=0x0)->voidLicenseAGPL v3
|
angst
|
Angst— Angular statisticsAngstis awork-in-progressPython package for statistics on the sphere.InstallationInstall the package with pip:pip install angst
|
angstrom
|
No description available on PyPI.
|
anguilla-iml
|
anguillaanguillais a mapping and interactive machine learning package for digital musical instrument design in Python.This is an early stage project. Currently, the main interface is theIMLclass, which allows adding input-output pairs (IML.add) and subsequently mapping points in the input space to outputs (IML.map).anguillais designed to be modular and hackable. AnIMLobject is composed of several exchangeable parts:anEmbeddingembeds input points into a feature spaceanNNSearchimplements nearest-neighbor search in the feature spaceanInterpolatecombines a set of output points using the distances of their corresponding input points from a neighboring query point.python -m anguilla serverwill expose the Python API overOpen Sound Control(OSC) usingiipyper.For examples and tutorials of how to useanguilla, see ourexamples repo(TBC).Installanguillacan be installed viaPyPI:pipinstallanguillaDevelopSee theiil-devrepo for a recommended dev environment.It's also possible to developanguillain isolation. You will needPoetryand your Python environment manager of choice. Withconda, for example:condacreate-nanguilla-envpython=3.10poetry
condaactivateanguilla-envthen:[email protected]:Intelligent-Instruments-Lab/anguilla.gitcdanguilla
poetryinstallContactanguillais developed by theIntelligent Instruments Lab. Get in touch tocollaborate:◦iil.is◦Facebook◦Instagram◦X (Twitter)◦YouTube◦Discord◦GitHub◦LinkedIn◦Email◦FundingThe Intelligent Instruments project (INTENT) is funded by the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (Grant agreement No. 101001848).
|
anguine
|
No description available on PyPI.
|
anguis
|
anguisLatet anguis in herba(Virgil,Eclogues, 3, 93)anguisis a generic key-store library in Python.Currently, the following backends are supported:filesystemEtcdGitRedismemcachedSFTPSqliteAWS S3Google DriveRationaleTODOInstallationFrom source:$ python setup.py installFrom PyPI:$ pip3 install anguisExample of usagefrom anguis.fs import AnguisFS
cache = AnguisFS()
cache['foo'] = 'bar'
print(cache['foo'])
# bar
del(cache['foo'])
print(cache['foo'])
# NoneHistory0.3.7 (2021-02-05)Add serialize/unserialize support.0.3.6 (2021-02-05)AWS S3 support.0.3.5 (2021-02-03)Partial support for Google Drive.0.3.4 (2021-02-03)Partial support for memcached.0.3.3 (2021-02-03)Fix imports.0.3.2 (2021-02-03)Restructure.0.3.0 (2021-02-03)Dict-like behavior, added support for Sqlite, package restructured.
|
angular2tmpl
|
Convert AngularJS templates to Jinja2 templates for SEO.The basic idea is to create a version of an Angular-powered website that can be
rendered on the server for consumption by search engines. This is accomplished
in two parts:Use angulart2tmpl to convert Angular templates to Jinja2 templates. This may
require implementing custom Angular directives in Python (usingxml.dom.minidom).Implement a Python WSGI app that gathers the necessary data using the same
API that powers your Angular app and passes it to the generated Jinja2
templates.This project expressly does not intend to be a full implementation of AngularJS
in Python. Instead, it intends to implement a minimal subset of Angular
sufficient to provide server-side rendering for the purposes of SEO. The
resulting server-rendered sites need not be interactive, but they should look
roughly the same as their JavaScript-based counterparts.FeaturesReuses existing Angular templates and backend APIAvoids the expense and complexity of running a headless browserCompatible with PaaS platforms such as Google App EngineStatusangular2tmpl is pre-alpha software. It currently implements averyminimal
subset of thengandngRoutemodules and makes little attempt to address
edge cases. No guarantees are made at this time about maintaining backwards
compatibility. Unit tests are still a twinkle in its eye.That said, angular2tmpl does currently satisfy the needs of the site that it was
built for.Installation & DependenciesInstallation is easy:pip install angular2tmplThe only dependencies are Jinja2 and html5lib, both of which will be
automatically installed. angular2tmpl was built on Python 2.7, but with the
intention of making conversion with 2to3 fairly painless. If you try it, let me
know how it goes.UsageJust runangular2tmpl. Try--helpto see the available flags and default
values, then run it on each of your Angular templates. angular2tmpl directives
are intended to be similar to Angular directives while staying Pythonic and
taking advantage of the reduced complexity that comes from non-interactive
rendering. Seemodules/ng.pyfor examples.Due to differences in the semantics of Angular vs. Jinja2 expressions, some
modifications to the default Jinja2 environment and your template data are
necessary:Angular is extremely generous about ignoring errors and missing values in
templates. To emulate this behavior, set theundefinedproperty of your
Jinja2 environment object toangular2tmpl.jinja2.PermissiveUndefined.JavaScript objects allow access to non-existent properties and treatfoo.barandfoo['bar']the same way. To get the same behavior out of
your template variables, convert them usingangular2tmpl.jinja2.js_data.BackgroundFor more information about how Google handles JavaScript-heavy sites and how to
make it request a special server-rendered version of your site, seehttps://developers.google.com/webmasters/ajax-crawling/docs/specification. For
more information about other approaches to making Angular work within the bounds
of this specification, seehttp://www.ng-newsletter.com/posts/serious-angular-seo.html.Disclaimersangular2tmpl is not affiliated in any way with Google or AngularJS.
|
angular-django
|
Angular Djangois a framework to work inAngularas inDjango. Use the Django classes in Angular to buildformsanddatagrids in minutes.A demo is available on the website..Angular-django consists oftwo packages: a package forAngularand an optional package forDjango. To install
the Angular package:$npmiangular-djangoTo install the Django package:$pipinstall-Uangular-djangoFull instructions are availableon the website..FeaturesSome features available:Use the methods and filters available in the Django Rest Framework to work with the API.Build forms in minutes. Includes validation on frontend and backend. Selector choices are built with the server.Easy-to-implement filtering, paging, and searching listings.Use your Django classes and types in Angular. The library will transform the API values to the correct types.
|
angular-gettext-babel
|
Angular Gettext BabelA babel extractor for use with angular-gettext (https://angular-gettext.rocketeer.be/)This is a very simple extractor that does not attempt to deal with anything but
html templates that have translate directives embedded in them.Changelog0.3 - 2015-07-07Add support for comments0.2 - 2015-07-07Add support for pluralisation0.1 - 2015-06-23Initial upload to PyPI and githubhttps://github.com/neillc/angular-gettext-babel
|
anguria
|
anguria - Specrun Report Smart ParserPython solution to convert Specrun XML report to dictionary for further analysis
|
angus-framework
|
No description available on PyPI.
|
angushyxtesttttt
|
my-project
|
angus-sdk-python
|
No description available on PyPI.
|
angus-web-visu
|
IntroductionA very simple web server that:Grab video camera framesSend it to Angus.ai to analyseGet back results (states and events)Add computed information on a new layer (above original video)Provide a server with 3 endpoints (on port 8888):http://localhost:8888/mjpega video stream with resultshttp://localhost:8888/notificationsan event source endpoint for eventshttp://localhost:8888/index.htmla landing pageInstallation and usage$>pipinstallangus-web-visu$>python-mangusvisu.webinterface.server
|
anhdhanhdh
|
My first Python package with a slightly longer description
|
anhelper
|
说明用于android设备远程实时控制的工具整合包。封装了minicap、minicap_sdk32、minitouch、ADBKeyboard的预编译包支持多线程（threading）中资源自动分配，但应避免在多进程（multiprocessing）中使用支持多设备连接支持安卓设备的实时截图(延迟约30~40ms)支持修改分辨率支持监听屏幕旋转支持监听输入框弹出内置触控点坐标变换支持中文输入包含一个远程控制demo支持安卓系统版本android<=12, sdk<=32适用场景有一定实时性要求的安卓游戏自动控制项目需要从不同线程控制、获取屏幕内容的多线程项目安装pipinstallanhelperDemo运行demo需要确保已经通过adb连接安卓设备anhelper-demo已知问题实体机上可能存在输入设备写入权限问题，导致minitouch无法运行。需要adb获取root权限。部分机器需要手动在设置中开启ADBKeyboard并且手动切换输入法才可用。用于安卓控制的同类开源项目推荐uiautomator2scrcpyQtScrcpyminidevice在python项目中使用Devicefromanhelperimportdevicedevice.listDevices(){'127.0.0.1:16416': ['device',
'product:SDY-AN00',
'model:SDY_AN00',
'device:SDY-AN00',
'transport_id:24'],
'127.0.0.1:21513': ['device',
'product:SM-S9010',
'model:SM_S9010',
'device:SM-S9010',
'transport_id:23']}# 通过网络连接设备device.connectDevice('127.0.0.1',port=16416)Truedevice.listDevices(){'127.0.0.1:16416': ['device',
'product:SDY-AN00',
'model:SDY_AN00',
'device:SDY-AN00',
'transport_id:24'],
'127.0.0.1:21513': ['device',
'product:SM-S9010',
'model:SM_S9010',
'device:SM-S9010',
'transport_id:23']}# 获取adb连接的第一个设备# getDevice已对多线程进行了优化，不同线程中调用不会重复构建实例dev=device.getDevice()# 检查是否处于输入法输入状态dev.getIMEInputActive()False# 获取屏幕显示参数dev.getWM(){'width': 1280, 'height': 720, 'density': 240}%%time# 获取屏幕方向（顺时针旋转）dev.getOrientation()CPU times: total: 0 ns
Wall time: 86.9 ms
0# 修改分辨率dev.setWM(720,1280,fit_orientation=True)dev.getWM(){'width': 1280, 'height': 720, 'density': 240}dev.setWM(**device.CONST.TABLET_720P,fit_orientation=True)dev.getWM(){'width': 1280, 'height': 720, 'density': 240}imefromanhelperimportime# 获取默认设备的ADBKeyboard输入法对象mime=ime.getIME()# 检查ADBKeyboard是否是默认输入法mime.getSelected()False%%time# 等待输入完成mime.inputSafe('你好')正在安装ADBkeyboard。。。ok
CPU times: total: 15.6 ms
Wall time: 540 ms
'Broadcasting: Intent { act=ADB_INPUT_B64 flg=0x400000 (has extras) }\r\nBroadcast completed: result=0'%%time# 输入且不等待完成mime.input('你好')CPU times: total: 15.6 ms
Wall time: 3.91 ms
<Popen: returncode: None args: 'adb -s 127.0.0.1:16416 shell "am broadcast -...>## 多设备mime2=ime.getIME(list(device.listDevices().keys())[1])mime2.input('再见')<Popen: returncode: None args: 'adb -s 127.0.0.1:21513 shell "am broadcast -...>Minicapfromanhelperimportminicapfromanhelper.utils.visualizehelperimport*# 获取默认设备的minicap输入法对象mcap=minicap.getMinicap()# 截图默认返回cv2格式BGR矩阵# sync=True 获取当前时间之后的第一帧imat=mcap.cap(sync=True)imshow(imat)%%time# 对于静态画面minicap不会发送新的帧，所以同步截图设置了1秒超时imat=mcap.cap(sync=True)CPU times: total: 15.6 ms
Wall time: 37.1 ms%%time# sync=False 跳过等待直接从缓存中取帧imat=mcap.cap(sync=False)CPU times: total: 15.6 ms
Wall time: 15.6 ms# 用完记得关mcap.close()Minitouchfromanhelperimportminitouchimporttime# 获取默认设备的minicap输入法对象touch=minitouch.getMinitouch()%%time# 由于触控设备通常支持多个触控点，使用useContact()自动分配触控点，以避免冲突# 所有的触控操作推荐使用比例坐标而非绝对坐标# 比例坐标：x = 绝对坐标x/屏幕宽度, y=绝对坐标y/屏幕高度, 0 <= x,y <= 1withtouch.useContact()asc:c.swipe(0.5,0.2,0.5,0.4,duration_ms=3000)print(c.id)withtouch.useContact()asc:print(c.id)c.tap(1000,500)c.tap(0.5,0.5)正在部署minitouch。。。ok
9
8
CPU times: total: 78.1 ms
Wall time: 1.94 s%%time# 同一个触控点的操作会覆盖掉上一个操作未完成的部分withtouch.useContact()asc:c.swipe(0.5,0.2,0.5,0.4,duration_ms=3000)time.sleep(2)print(c.inuse)c.swipe(0.5,0.2,0.5,0.4,duration_ms=3000)True
CPU times: total: 78.1 ms
Wall time: 2.01 s%%timewithtouch.useContact()asc:c.swipe(0.5,0.4,0.5,0.6,duration_ms=3000)CPU times: total: 46.9 ms
Wall time: 53.7 ms%%timewithtouch.useContact()asc:c.tap(0.9,0.7)CPU times: total: 0 ns
Wall time: 976 µs# 绝对坐标也可以使用但不推荐，坐标原点为旋转后的屏幕左上角，与截图坐标一致withtouch.useContact()asc:c.tap(700,500)# 用完记得关touch.close()WebUI（Demo）fromanhelperimportwebuifromIPython.displayimportIFrame# 创建一个webui，绑定默认设备（连接的第一个），可以使用不同的device_id来绑定不同设备# webui可以在网页中同步显示设备屏幕的内容# divice_id 可以通过 device.listDevices()获取ui=webui.WebUI(device_id=None)ui.start()# 检查webui是否正在运行ui.is_alive()TrueIFrame(ui.url,width='100%',height='400px')127.0.0.1 - - [29/Jul/2023 23:56:15] "GET / HTTP/1.1" 200 -
正在部署minicap。。。ok
127.0.0.1 - - [29/Jul/2023 23:56:16] "GET /video_feed HTTP/1.1" 200 -ui2=webui.WebUI(device_id=None,port=5001)ui2.start()ui2.is_alive()TrueIFrame(ui2.url,width='100%',height='400px')127.0.0.1 - - [29/Jul/2023 23:56:20] "GET / HTTP/1.1" 200 -
127.0.0.1 - - [29/Jul/2023 23:56:20] "GET /video_feed HTTP/1.1" 200 -# 关闭webui# 多个webui可以指向同一个设备，可以分别创建和关闭ui2.stop()ui.stop()包含开源项目许可声明minicapminitouchADBKeyBoardvuepure.cssfontawesomeNone
|
anhengtimuflag
|
No description available on PyPI.
|
anhima
|
Documentation:http://anhima.readthedocs.orgExamples:http://nbviewer.ipython.org/github/alimanfoo/anhima/tree/master/examples/Source:http://github.com/alimanfoo/anhimaMailing list:https://groups.google.com/forum/#!forum/anhimaRelease notes:https://github.com/alimanfoo/anhima/releasesSee also [information for developers](https://github.com/alimanfoo/anhima/blob/master/DEVELOP.md).
|
anhSMSwrap
|
ALL RIGHTS TO THE ORIGINAL CREATOR TEZMEN!
|
ania
|
/\ (_)/\_______//\ \ | '_ \| |/_` |/ ____ \| | | | | (_| |/_/ \_\_| |_|_|\__,_|Busca, disfruta y descarga anime mediante la línea de comandos en cualquier sistema operativo.InstalacionpipinstallaniaUsoaniaConfiguración para desarrolloPrerequisitosPython^3.8Poetry# Clonamos el repositoriogitclonehttps://github.com/ania-cli/ania.git# Nos movemos al directorio 'ania'cdania# Instalamos las dependenciaspoetryinstall# Activamos el entorno virtualpoetryshell# Para ejecutar la app usamos el siguiente comandopoetryrunaniaAuthor@migueweb
|
ani-cache
|
No description available on PyPI.
|
anicli
|
Failed to fetch description. HTTP Status Code: 404
|
ani-cli
|
No description available on PyPI.
|
anicli_api
|
# anicli-apiПрограммный интерфейс набора парсеров аниме с различных источников.Присутствует поддержка sync и async методов с помощью `httpx` библиотеки.Парсеры работают на REST-API (если у источника есть доступ) или если такой интерфейсотсутствует, то с помощью parsel, chompjs, jmespath, regex библиотек.# install`pip install anicli-api`# OverviewСтруктура проекта- source - наборы модулей для извлечения информации об аниме тайтлов из источников- player - наборы модулей для извлечения прямой ссылки на видеоПодробнее про `source` и `player` смотрите ниже.```anicli_api├── base.py - базовый класс модуля-парсера├── _http.py - предварительно сконфигурированные классы httpx.Client и httpx.AsyncClient├── _logger.py - логгер├── player - модули получения ссылок на видео│ ├── __template__.py - шаблон модуля PlayerExtractor│ ├── ... ready-made модули│ ...├── source - модули парсеров с источников│ ├── parsers/... автоматически сгенерированные парсеры html страниц│ ├── __template__.py - шаблон для экстрактора│ ├─ ... ready-made парсеры│ ...└── tools - прочие модули```Схематичный принцип работы модуля из директории `source`префикс `a_` обозначает асинхронный метод```mermaidflowchart TDE[Extractor] -->|"search(<QUERY>) | a_search(<QUERY>)"| S(Search)E -->|"ongoing() | a_ongoing()"| O(Ongoing)O -->|"get_anime() | a_get_anime()"| A[Anime]S -->|"ongoing() | a_ongoing()"| AA -->|"get_episodes() | a_get_episodes()"|Ep[Episode]Ep -->|"get_sources() | get_sources()"|So[Source]So -->|"get_videos() | a_get_videos()"|V[Video]```# quickstart```pythonfrom anicli_api.source.animego import Extractorfrom anicli_api.tools import cliif __name__ == '__main__':cli(Extractor())```> Этот модуль реализован для простого ручного тестирования модулей и "имитирует" потенциальное настоящее приложениеПример своей реализации```pythonfrom anicli_api.source.animego import Extractor # can usage any sourcedef _print_to_rows(items):print(*[f"{i}) {r}" for i, r in enumerate(items)], sep="\n")if __name__ == "__main__":ex = Extractor()print("PRESS CTRL + C for exit app")while True:results = ex.search(input("search query > "))if not results:print("Not founded, try again")continue_print_to_rows(results)anime = results[int(input("anime > "))].get_anime()print(anime)episodes = anime.get_episodes()_print_to_rows(episodes)episode = episodes[int(input("episode > "))]sources = episode.get_sources()_print_to_rows(sources)source = sources[int(input("source > "))]videos = source.get_videos()_print_to_rows(videos)video = videos[int(input("video > "))]print(video.type, video.quality, video.url, video.headers)```Также, можно использовать отдельно экстракторы видео> Эти модули минимально реализуют получение ссылок на видео с минимальными метаданными не стремиться> стать заменой yt-dlp```pythonimport asynciofrom anicli_api.player.sibnet import SibNetasync def main():videos = await SibNet().a_parse(URL)print(*videos)if __name__ == '__main__':URL = 'https://video.sibnet.ru/shell.php?videoid=432356'print(*SibNet().parse(URL))# asyncio too!asyncio.run(main())```С asyncio аналогично, но **все** методы получения объектов имеют префикс `a_`:```pythonimport asynciofrom anicli_api.source.animego import Extractor # или любой другой источникasync def main():ex = Extractor()prompt = input("search query > ")# a_ - async prefix.# simular in Ongoing, Anime, Episode, Source, Video objectsresults = await ex.a_search(prompt)print(*[f"{i}) {r}" for i, r in enumerate(results)], sep="\n")if __name__ == '__main__':asyncio.run(main())```# source description- name - имя модуля- type - тип источника получения данных.- **NO** - неофициальный (парсинг html документов и запросы недокументированным API методам)- **YES** - официальный (rest-api)- note - примечания- dubbers - тип озвучек.- many - от различных авторов.- subtitles - только субтитры.- author - своя| name | url | official api | dubbers | note ||----------------|----------------------------|--------------|-------------------|------------------------------------------------------------------------------------------------------------------------|| animego | https://animego.org | NO | many | источники kodik, animego, не работает на IP отличных от СНГ || animania | https://animania.online | NO | many | источник kodik, не работает на IP отличных от СНГ || animejoy | https://animejoy.ru | NO | subtitles | **имеет cloudflare**, требуется реализация обхода или предварительное получения cookies и headers, много источников || sovetromantica | https://sovetromantica.com | NO | subtitles, author | не на все тайтлы есть видео, у себя хостят || anilibria | https://anilibria.tv | YES | author | || animevost | https://animevost.org | YES | author | || jutsu | https://jut.su | NO | author | Один вид озвучки. Сжатый 1080. (DEV NOTE): запуск видео зависим от используемого user-agent заголовка в API интерфейсе |# players description> Требует дополнения и дополнительные тесты- name - имя плеера- max quality - максимальное разрешение выдаваемое источником. Это может быть 0 (аудио, без видео), 144, 240, 360, 480, 720, 1080- note - примечания| name | max quality | note ||----------------|--------------------------------------------------------------|-------------------------------------------------------------------------|| kodik | 720 (на старых тайтлах (ранние One Peace, Evangelion) - 480) | **работает только на IP СНГ** || aniboom | 1080 | **работает только на IP СНГ**. Иногда не возвращает mpd ссылку на видео || sibnet | 480 | || animejoy | 1080 | только актуальные ongoing, потом видео удаляются с серверов || csst | 1080 | || dzen | 1080 | || mailru | | || okru | | || sovetromantica | 1080 | не на все тайтлы присутствуют видео || vkcom | 1080 (какого качества автор зальет видео) | CDN сервера в РФ, в других странах загружается медленнее || nuum | 1080 | проект от wasd.tv |## loggingНастройка логгера идет через ключ `anicli-api````pythonimport logginglogger = logging.getLogger('anicli-api')```## http path### sourceЕсли по какой-то либо причине вас не устраивают настройки по умолчанию - то вы можете задатьконфигурацию http клиентов для экстракторов```pythonfrom anicli_api.source.animego import Extractorimport httpx# не обязательно настраивать все клиенты, зависит от режима использования# например, если вы будете использовать только asyncio - настраивайте только http_async_clientmy_client = httpx.Client(headers={"user-agent": "007"}, proxies="http:127.0.0.1:8080")my_async_client = httpx.AsyncClient(headers={"user-agent": "007"}, proxies="http:127.0.0.1:8080")# настройки клиентов будут передаваться всем объектам кроме методов Source.get_videos()# и Source.a_get_videos()ex = Extractor(http_client=my_client, http_async_client=my_async_client)# изменение http клиента для объектаresults = ex.search("lain")result = results[0]result.http = my_clientresult.http_async = my_async_client...```### playerВ player для модификации httpx клиентов (Client, AsyncioClient) необходимо передать kwargs аргументы:```pythonfrom anicli_api.source.animego import Extractorsources = (Extractor().search("lain")[0].get_anime().get_episodes()[0].get_sources())videos = sources[0].get_videos(transport=None, # reset to default httpx.HTTPTransportheaders={"User-Agent": "i'm crushing :("})```## Структуры объектовПриведены поля, которые **гарантированно** возвращаются в API интерфейсе библиотеки,в некоторых источниках могут присутствовать дополнительные поля или атрибуты дляиспользования во внутренних методах.Например, в `anilibria` и `animevost` поля почти идентичны ответам API.В `animego.Anime` есть сырой несериализованный `raw_json` для извлечения дополнительных метаданных.### Search- url: str - URL на тайтл- title: str - имя найденного тайтла- thumbnail: str - изображение### Ongoing- url: str - URL на тайтл- title: str - имя найденного тайтла- thumbnail: str - изображение### Anime- title: str - имя тайтла (на русском)- thumbnail: str - изображение- description: Optional[str] - описание тайтла### Episode- title: str - имя эпизода- num: str - номер эпизода### Source- url: str - ссылка на источник- title: str - даббер или имя источника### VideoОбъект `Video`, полученный из `Source.get_video` (или `Source.a_get_video`)имеет следующую структуру:* type - тип видео (m3u8, mp4, mpd, audio)* quality - разрешение видео (0, 144, 240, 360, 480, 720, 1080)* url - прямая ссылка на видео* headers - заголовки требуемые для получения видео.Если возвращает пустой словарь - заголовки не нужны# Примечания- Парсеры из директории[anicli_api/source/parsers](anicli_api/source/parsers) автоматически генерируются с помощью[ssc_gen](https://github.com/vypivshiy/selector_schema_codegen),настройки хранятся в [libanime_schema](https://github.com/libanime/libanime_schema)- Для модификаций парсеров из директории `anicli_api/source/parsers`используйте наследование, чтобы не потерять изменения при перегенерации библиотекой `ssc_gen`.Пример из модуля [animejoy](anicli_api/source/animejoy.py):```pythonfrom anicli_api.source.parsers.animejoy_parser import PlayerUrlsView as PlayerUrlsViewOldfrom parsel import Selectorclass PlayerUrlsView(PlayerUrlsViewOld):def _parse_url(self, part: Selector) -> str:val_0 = part.attrib["data-file"]# maybe exclude https: prefixreturn f"https:{val_0}" if val_0.startswith("//") else val_0```- Проект разработан преимущественно на личное, некоммерческое использование с client-sideстороны.Автор проекта не несет ответственности за поломки, убытки в высоко нагруженных проектах и решениепредоставляется "Как есть" в соответствии с [MIT](LIENSE) лицензией.- Основная цель этого проекта — связать автоматизацию и эффективность извлечения того,что предоставляется пользователю в Интернете.Весь контент, доступный в рамках проекта, размещается на внешних неаффилированных источниках.- **Этот проект не включает инструменты кеширования и сохранения всех полученных данных,только готовые реализации парсеров и программные интерфейсы**
|
anicli-ru
|
anicli-ruСкрипт для поиска и просмотра аниме из терминала с русской озвучкой или субтитрами для linux систем,
написанный на python.https://github.com/vypivshiy/ani-cli-ru/assets/59173419/bf7e78bd-cdd1-4871-a5b3-f48e6ed7ec28УстановкаРекомендуется использовать pipxЕсли вам нужен только программный интерфейс парсеров или информация про используемые источники -anicli-apipipxinstallgit+https://github.com/vypivshiy/ani-cli-ru.git@devОбновление:pipxrunpipanicli-ruinstallanicli-apieggellaanicli-UПоддерживаемыеплееры
-mpv(рекомендуется)-vlc(малотестов,несовсемиисточникамиработает)ОпциональноЕсли вы будете использовать плеер без поддержки настройки http заголовков - рекомендуется
дополнительно установитьffmpegдля перенаправления видео потока.Usage:anicli-ruКлючи запуска-s--source-выбористочника.Поумолчанию"animego"-q--quality-минимальновыбранноеразрешениевидео.Доступны:0,144,240,360,480,720,1080.Поумолчанию1080Например,есливыустановили1080итакоевидеоотсутстует-выведетмаксимальнодопустимое--ffmpeg-использоватьffmpegдляперенаправлениявидеопотокаввидеоплеер
-p--player-какойвидеоплеериспользовать.доступны"vlc","mpv".Поумолчанию"mpv"--m3u-дляSLICE-режимапросмотрасоздаватьплейлист(ЭКСПЕРИМЕНТАЛЬНЫЙРЕЖИМ,СОБИРАЕТВИДЕОМЕДЛЕННО)--m3u-size-максимальныйразмерm3uплейлиста.Поумолчанию12Отличия от старой версии:Клиент основан на prompt-toolkit, реализована надстройкаeggellaApi интерфейс парсераи Cli клиента
разделены в отдельные репозитории. Также, API интерфейс поддерживает asyncio!http клиент заменен сrequestsнаhttpxсо следующими модификациями:http2протокол по умолчаниюминимальные надстройки headers для работыretry-connect подключенияобнаружение ddos защиты источникапарсеры работают в связкеparsel,chompjs,jmespathиregexбиблиотекRoadmapминимальная реализациявыбор источникаffmpeg адаптерконфигурация http клиента (прокси, таймаут)кешированиесинхронизация с shikimoriпоиск и переключение по нескольким источникам в одной сессии (без перезапуска)конфигурация приложениясистема плагинов, кастомизация (?)простой http сервер-прослойка для передачи видео в плееры
|
aniclustermap
|
ANIclustermapOverviewANIclustermap is easy-to-use tool for drawing ANI(Average Nucleotide Identity) clustermap between all-vs-all microbial genomes.
ANI between all-vs-all genomes are calculated byfastANI(orskani) and clustermap is drawn using seaborn.Fig1. ANI clustermap between all-vs-all 33 genomes.Fig2. ANI clustermap between all-vs-all 18 genomes. If no similarity detected by fastANI, filled in gray.InstallationPython 3.8 or lateris required for installation.fastANIorskaniis required to calculate ANI.Install bioconda package:conda install -c conda-forge -c bioconda aniclustermapInstall PyPI stable package:pip install aniclustermapWorkflowDescription of ANIclustermap's automated workflow.Calculate ANI between all-vs-all microbial genomes by fastANI (or skani).If no similarity detected by fastANI, NA is output. In that case, NA is replaced by 0.0.If previous result available at the time of re-run, reuse previous result.Clustering ANI matrix by scipy's UPGMA method.Using clustered matrix, draw ANI clustermap by seaborn.UsageBasic CommandANIclustermap -i [Genome fasta directory] -o [output directory]Options-i I, --indir I Input genome fasta directory (*.fa|*.fna[.gz]|*.fasta)
-o O, --outdir O Output directory
-m , --mode ANI calculation mode ('fastani'[default]|'skani')
-t , --thread_num Thread number parameter (Default: MaxThread - 1)
--overwrite Overwrite previous ANI calculation result (Default: OFF)
--fig_width Figure width (Default: 10)
--fig_height Figure height (Default: 10)
--dendrogram_ratio Dendrogram ratio to figsize (Default: 0.15)
--cmap_colors cmap interpolation colors parameter (Default: 'lime,yellow,red')
--cmap_gamma cmap gamma parameter (Default: 1.0)
--cmap_ranges Range values (e.g. 80,90,95,100) for discrete cmap (Default: None)
--cbar_pos Colorbar position (Default: (0.02, 0.8, 0.05, 0.18))
--annotation Show ANI value annotation (Default: OFF)
-v, --version Print version information
-h, --help Show this help message and exitExample Command7 genomes minimal dataset. Clickhereto download dataset (Size=3.6MB).ANIclustermap -i ./minimal_dataset/ -o ./ANIclustermap_resultOutput ContentsANIclustermap outputs 3 types of files.ANIclustermap.[png|svg](example1,example2)ANI clustermap result figure.ANIclustermap_matrix.tsv(example)Clustered all-vs-all ANI matrix.ANIclustermap_dendrogram.nwk(example)Newick format clustering dendrogram.GalleryExample gallery of 33 genomes normal dataset.If you want to try it for yourself, clickhereto donwload dataset (Size=63.5MB).Normal parameter:ANIclustermap -i ./normal_dataset -o ./ANIclustermap_result \
--fig_width 15Change cmap_gamma parameter:ANIclustermap -i ./normal_dataset -o ./ANIclustermap_result \
--fig_width 15 --cmap_gamma 0.5Change cmap_colors(=white,orange,red) paramter:ANIclustermap -i ./normal_dataset -o ./ANIclustermap_result \
--fig_width 15 --cmap_colors white,orange,redChange cmap_ranges paramter:ANIclustermap -i ./normal_dataset -o ./ANIclustermap_result \
--fig_width 15 --cmap_ranges 80,85,90,92.5,95,97.5,100Seethis issuefor more details.Add ANI value annotation parameter:ANIclustermap -i ./normal_dataset -o ./ANIclustermap_result \
--fig_width 20 --fig_height 15 --annotation
|
anicode
|
A quick unicode search toolFree software: MIT License <https://opensource.org/licenses/MIT>Documentation:https://anicode.readthedocs.ioUsageCreditsThis package was created withCookiecutter.
|
anicons
|
Anicons_pyA semi automated solution for most of your degenerate needs.Requirementspython 3.7.7
(thats what i used but anything above 3 should be fine i hope )
jikanpy | To get data and posters of the folder
pyfiglet | For the awesome ascii art
PyInquirer | For the interactive title chooser
PIL | pillow for the image conversion processInstructionsThis step assumes that you have python and pip installedplace anicons.py on the same level as your anime folder like:Anime
Naruto
.
.
.
anicons.pyopen cmd ,powershell or a terminal and type :pip install -r requirements.txt
python anicons.py
|
anicration
|
AnicrationTo install, do :
$ python setup.py installTo install a editable version(in the setup.py directory):
$ pip install -e .Dependencies:Tweepy (3.5.0)
requests (2.13.0)
|
anid
|
anidanidis a cli to download animes fromanimefire.netInstalationpip install anidUsageTo use you need to pass the anime name, the number of episodes and optionally the episode to start the downloadUsage: anid [OPTIONS] ANIME
Options:
-e, --episodes INTEGER Number of episodes [required]
-s, --start INTEGER Number of episodes
--help Show this message and exit.If you want download a anime you will search in theanimefire.netand open the url with player and copy the anime name in urlIn this exemplehttps://animefire.net/animes/mob-psycho-100/1you will copy "mod-psycho-100" and put in the command, and the number of episodes, like this:In mod pyscho 100 case:https://animefire.net/animes/mob-psycho-100/1Copy "mod-psycho-100" and put in command, and the number of episodes, like this:anid "mob-psycho-100" -e 12LicenseThis project use MITlicenseAbout MeTelegram:@exebixelEmail:[email protected]
|
anidado
|
UNKNOWN
|
anidado2
|
UNKNOWN
|
anidado_sinnick
|
UNKNOWN
|
anidb
|
UNKNOWN
|
anidbcli
|
Anidbcli is a simple command line interface for managing your anime collection on your local computer or NAS (using only ssh).RequirementsPython 3.6or newer (version 3.5 seems to work as well)Key featuresed2k hashing library utilizing multiple coresadding anime to mylistutilize data from anidb to move/rename the filesmoves/renames the subtitle and other files with same extensionencryptionInstallationThe package can be installed automatically using pip.pipinstallanidbclipipinstall--upgradeanidbcli#updatePackage can be also installed from source like this.pythonsetup.pyinstallAfter installation anidbcli can be invoked like a python modulepython-manidbclior directly by typing following in the command lineanidbcliQuickstartThe basic syntax isanidbcli[OPTIONS]ed2k/api[OPTIONS]ARGSIf you want to just generate ed2k links for mkv and mp4 files recursively for given folders and copy them to clipboard, use:anidbcli-r-emkv,mp4ed2k-c"path/to/directory""path/to/directory2"Where-ris recursive-ecomma separated list of extensions, that are treated as anime filesTo add all mkv files from directory resursively to mylist use:anidbcli-r-emkvapi-u"username"-p"password"-k"apikey"-a"path/to/directory"Where“password”is your anidb password“username”is your anidb username“apikey”is anidb upd api key, that you can set athttps://anidb.net/user/setting. If no key is provided, unencrypted connection will be used.Optionally, if you don’t provide password or username, you will be prompted to input them.anidbcli-r-emkvapi-k"apikey"-a"path/to/directory"Enteryourusername:"username"Enteryourpassword:"password"To set files to a specified state use:anidbcli-r-emkvapi-u"username"-p"password"-k"apikey"--state0--show-ed2k-a"path/to/directory"Where“show-ed2k”is an optional parameter to show/print out ed2k links, while adding/renaming files.“state”is your desired MyList file state (seehttps://wiki.anidb.net/Filestates).The number 0 can be substituted for different states:0 is unknown (default)1 is internal storage2 is external storage3 is deleted4 is remote storageTo rename all mkv and mp4 files in directory recursively using data from api you can callanidbcli-r-emkv,mp4api-u"username"-p"password"-k"apikey"-sr"%ep_no% - %ep_english% [%g_name%]""path/to/directory"Where“-r”rename using provided format string“-s”prepend original file path to each renamed file. Without this flag the files would me moved to current directory.“-U”use with -a (-aU). Adds the files to mylist as unwatched.Also along with the parameter “-r” you can use one of the following parameters:“-h”Create hardlinks instead of renaming.“-l”Create softlinks instead of renaming.“-t”Save session info instead of logging out (session lifetime is 35 minutes after last command). Use for subsequent calls of anidbcli to avoid api bans.Anidbcli should be called with all the parameters as usual. If the session was saved before more than 35 minutes, a new session is created instead.You can also move watched anime from unwatched directory to watched directory and add it to mylist at the same time using following command.anidbcli-r-emkv,mp4api-u"username"-p"password"-k"apikey"-xr"watched/%a_english%/%ep_no% - %ep_english% [%g_name%]""unwatched/anime1""unwatched/anime2"Where“-x”Delete empty folders after moving all files away.NOTE: All files with same name and different extension (fx. subtitle files) will be renamed/moved as well.Selected usable tags:%md5%- md5 hash of file.%sha1%- sha1 hash of file.%crc32%- crc32 hash of file.%resolution%- file resolution, for example “1920x1080”%aired%- Episode aired date. Only option that needs “–date-format” option. You can find list of available tags athttps://docs.python.org/3.6/library/time.html#time.strftime.%year%- Year, the anime was aired. Can be a timespan, if the anime was aired several years “1990-2005” etc.%a_romaji%- Anime title in romaji.%a_kanji%- Anime title in kanji.%a_english%- English anime title.%ep_no%- Episode number. Prepends the necessary zeros, fx. 001, 01%ep_english%- English episode name.%ep_romaji%- Episode name in romaji.%ep_kanji%- Episode name in kanji.%g_name%- Group that released the anime. fx. HorribleSubs.%g_sname%- Short group name.Complete list of usable tags in format string:%fid%,%aid%,%eid%,%gid%,%lid%,%status%,%size%,%ed2k%,%md5%,%sha1%,%crc32%,%color_depth%,%quality%,%source%,%audio_codec%,%audio_bitrate%,%video_codec%,%video_bitrate%,%resolution%,%filetype%,%dub_language%,%sub_language%,%length%,%aired%,%filename%,%ep_total%,%ep_last%,%year%,%a_type%,%a_categories%,%a_romaji%,%a_kanji%,%a_english%,%a_other%,%a_short%,%a_synonyms%,%ep_no%,%ep_english%,%ep_romaji%,%ep_kanji%,%g_name%,%g_sname%,%version%,%censored%
|
anidb-mv
|
anidb-mv, or amv for short, is a command line client for AniDB. It issimilar to the standard mv command in Unix, but in addition to moving
the files, it also tries to register them at AniDB. If a file isn’t
found on AniDB, information about it is saved in a local database, and
amv tries to register it the next time to command is used.
|
anidex
|
A Python client library for anidex!
|
anidl
|
No description available on PyPI.
|
ani-donut
|
No description available on PyPI.
|
anidouga-anidb.py
|
No description available on PyPI.
|
aniemore
|
Aniemore- это открытая библиотека искусственного интеллекта для потоковой аналитики эмоциональных оттенков речи человека.Основные технические параметрыОбъем набора данных Russian Emotional Speech Dialogues содержит более 3000 аудиофрагментов представляющих 200 различных людей;Модели способны распознавать эмоции в зашумленных аудиофайлах длительностью в 3 секунды;Скорость обработки и ответа модели составляет не более 5 секунд;Пословная ошибка модели WER 30%;Совокупная точность модели 75%Диапазон распознавания эмоций: злость, отвращение, страх, счастье, интерес, грусть, нейтрально;Акустические возможности - 3 уровня.ОписаниеAniemore - это библиотека для Python, которая позволяет добавить в ваше
программное обеспечение возможность определять эмоциональный фон речи человека, как в голосе,
так и в тексте. Для этого в библиотеке разработано два соответсвующих модуля - Voice и Text.Aniemore содержит свой собственный датасет RESD (Russian Emotional Speech Dialogues) и другие
наборы данных разного объема, которые вы можете использовать для обучения своих моделей.ДатасетПримечаниеRESD7 эмоций, 4 часа аудиозаписей диалоговстудийное качествоRESD_AnnotatedRESD + speech-to-text аннотацииREPV2000 голосовых сообщений (.ogg), 200 актеров, 2 нейтральные фразы, 5 эмоцийREPV-S140 голосовых сообщений (.ogg) "Привет, как дела?" с разными эмоциямиВы можете использовать готовые предобученные модели из библиотеки:МодельТочностьГолосовые моделиwav2vec2-xlsr-53-russian-emotion-recognition73%wav2vec2-emotion-russian-resd75%wavlm-emotion-russian-resd82%hubert-emotion-russian-resd75%unispeech-sat-emotion-russian-resd Copied72%wavlm-bert-base81%wavlm-bert-fusion83%Текстовые моделиrubert-base-emotion-russian-cedr-m774%rubert-tiny2-russian-emotion-detection85%rubert-large-emotion-russian-cedr-m776%rubert-tiny-emotion-russian-cedr-m772%Показатели моделей в разрезе эмоцийУстановкаpipinstallaniemoreМинимальные требования к оборудованиюАрхитектураЦПУОЗУSSDWave2Vec22 ядра8 ГБ40 ГБWaveLM2 ядра8 ГБ40 ГБHubert2 ядра8 ГБ40 ГБUniSpeechSAT2 ядра8 ГБ40 ГБBert_Tiny/Bert_Tiny22 ядра4 ГБ40 ГБBert_Base2 ядра4 ГБ40 ГБBert_Large2 ядра8 ГБ40 ГБWavLM Bert Base2 ядра16 ГБ40 ГБWavLM Bert Fusion2 ядра16 ГБ40 ГБWhisper Tiny2 ядра4 ГБ40 ГБWhisper Base2 ядра4 ГБ40 ГБWhisper Small2 ядра4 ГБ40 ГБWhisper Medium2 ядра8 ГБ40 ГБWhisper Large2 ядра16 ГБ40 ГБTextEnhancer2 ядра4 ГБ40 ГБПример использованияНиже приведены простые примеры использования библиотеки. Для более детальных примеров, в том числезагрузка cобственной модели- смотрите сделанный для этогоGoogle ColabРаспознавание эмоций в текстеimporttorchfromaniemore.recognizers.textimportTextRecognizerfromaniemore.modelsimportHuggingFaceModelmodel=HuggingFaceModel.Text.Bert_Tiny2device='cuda'iftorch.cuda.is_available()else'cpu'tr=TextRecognizer(model=model,device=device)tr.recognize('это работает? :(',return_single_label=True)Распознавание эмоций в голосеimporttorchfromaniemore.recognizers.voiceimportVoiceRecognizerfromaniemore.modelsimportHuggingFaceModelmodel=HuggingFaceModel.Voice.WavLMdevice='cuda'iftorch.cuda.is_available()else'cpu'vr=VoiceRecognizer(model=model,device=device)vr.recognize('/content/ваш-звуковой-файл.wav',return_single_label=True)Распознавание эмоций (мультимодальный метод)importtorchfromaniemore.recognizers.multimodalimportVoiceTextRecognizerfromaniemore.utils.speech2textimportSmallSpeech2Textfromaniemore.modelsimportHuggingFaceModelmodel=HuggingFaceModel.MultiModal.WavLMBertFusions2t_model=SmallSpeech2Text()text=SmallSpeech2Text.recognize('/content/ваш-звуковой-файл.wav').textdevice='cuda'iftorch.cuda.is_available()else'cpu'vtr=VoiceTextRecognizer(model=model,device=device)vtr.recognize(('/content/ваш-звуковой-файл.wav',text),return_single_label=True)Распознавание эмоций (мультимодальный метод с автоматическим распознаванием речи)importtorchfromaniemore.recognizers.multimodalimportMultiModalRecognizerfromaniemore.utils.speech2textimportSmallSpeech2Textfromaniemore.modelsimportHuggingFaceModelmodel=HuggingFaceModel.MultiModal.WavLMBertFusiondevice='cuda'iftorch.cuda.is_available()else'cpu'mr=MultiModalRecognizer(model=model,s2t_model=SmallSpeech2Text(),device=device)mr.recognize('/content/ваш-звуковой-файл.wav',return_single_label=True)Доп. ссылкиВсе модели и датасеты, а так же примеры их использования вы можете посмотреть в нашемHuggingFace профилеАффилированостьAniemore (Artem Nikita Ilya EMOtion REcognition)Разработка открытой библиотеки произведена коллективом авторов на базе ООО "Социальный код".
Результаты работы получены за счет гранта Фонда содействия развитию малых форм предприятий в научно-технической сфере (Договор №1ГУКодИИС12-D7/72697
от 22.12.2021).ЦитированиеДля цитировация воспользуйтесь пунктомCite this repositoryв правом менюAboutэтого проекта, или скопируйте информацию ниже:@software{Lubenets_Aniemore,author={Lubenets, Ilya and Davidchuk, Nikita and Amentes, Artem},license={MIT},title={{Aniemore}},url={https://github.com/aniemore/Aniemore}}
|
aniffinity
|
aniffinity“An-knee-fin-knee-tea”.Calculate affinity between anime list users.What is this?Calculate affinity between a user and another user on anime list
services. Refer to thedocsfor more info.InstallpipinstallaniffinityDependenciesjson-api-docrequestsExample UsagefromaniffinityimportAniffinityaf=Aniffinity("Xinil",base_service="MyAnimeList")affinity,shared=af.calculate_affinity("Josh",service="AniList")print(affinity)# 32.15230953451651print(shared)# 31Available ServicesAniListKitsuMyAnimeListFor more info, read thedocs.DocumentationDocumentation athttps://aniffinity.readthedocs.ioLegal StuffLicensed under MIT. SeeLICENSEfor more info.Cat Gif
|
ani-file
|
ani_file.ani file (animated cursor) reader and writer written in python 3.Was trying to batch extract the frame of some .ani file I got but noticed that there were no library to do so in python so I created one.Starting pointOpen ANI file in similar manner to builtin.open():
from ani_file import ani_file
f = ani_file.open(file,mode)filecan be string or file-like object.mode can be:"r"or"rb"to read an existing .ani file."w"or"wb"to create a new .ani file.Will overwrite existing file if given same nameRead .aniAvailable getter:getframesinfo()(NOT IMPLEMENTED YET): dictionary of info about number of frames, display sequence of frames, display rate of framesgetnframes(): return number of framesgetseq(): return list of sequence in which the frames appeargetrate(): return list of display rate for each framegetframesdata(): return list of binary data of each framegetauthor(): Get name of artist/corporation if presentgetname(): Get ani file name (Not the name of the .ani file) if presentExtract and save frames into .ico files:saveframestofile(outputpath,filenameprefix): Save to specified path. Name of each file will be filenameprefix + index from 0Write .aniAvailable getter (NOT IMPLEMENTED YET):Same as for read .aniAvailable setter:setframespath(framespath): set list of .ico files that make the frames of the final .ani file. The only function that you really need to write an .ani filesetseq(seq): set seqsetrate(rate): set ratesetauthor(iart): set name of artistsetname(inam): set name of the ani fileExample (INCOMING).ani file structure explain (INCOMING)Code based on wave.py athttps://github.com/python/cpython/blob/3.10/Lib/wave.py
|
anifolds
|
Anicons_pyA semi automated solution for most of your degenerate needs.Requirementspython 3.7.7
(thats what i used but anything above 3 should be fine i hope )
jikanpy | To get data and posters of the folder
pyfiglet | For the awesome ascii art
PyInquirer | For the interactive title chooser
PIL | pillow for the image conversion processInstructionsThis step assumes that you have python and pip installedplace anicons.py on the same level as your anime folder like:Anime
Naruto
.
.
.
anicons.pyopen cmd ,powershell or a terminal and type :pip install -r requirements.txt
python anicons.py
|
anifolers
|
Anicons_pyA semi automated solution for most of your degenerate needs.Requirementspython 3.7.7
(thats what i used but anything above 3 should be fine i hope )
jikanpy | To get data and posters of the folder
pyfiglet | For the awesome ascii art
PyInquirer | For the interactive title chooser
PIL | pillow for the image conversion processInstructionsThis step assumes that you have python and pip installedplace anicons.py on the same level as your anime folder like:Anime
Naruto
.
.
.
anicons.pyopen cmd ,powershell or a terminal and type :pip install -r requirements.txt
python anicons.py
|
anigapdf
|
This is the homepage of our project.
|
anigmo
|
# anigmo: Artificial Intelligence in abstract logic games[anigmo](https://github.com/cwoebker/anigmo) is an AI library that can be used to play abstract logic games.[](http://travis-ci.org/cwoebker/anigmo)—## Naming ##Why anigmo?Because.## What is this? ##A library.## InstallationIt’s as simple as that:$ pip install anigmo(This doesn’t work yet)## UsageGo look at the code for now.## Features ##Everything you ever wished for.## Documentation ##If you actually want to learn about this library check out the [documentation](http://cwoebker.github.io/anigmo)## Contribute[Fork and contribute!](http://github.com/cwoebker/anigmo)—For questions and suggestions, feel free to shoot me an email <[email protected]>Follow [@cwoebker](http://twitter.com/cwoebker)—Copyright (c) 2013, Cecil Woebker.
License: BSD (see LICENSE for details)
|
aniindex
|
No description available on PyPI.
|
aniinfo
|
No description available on PyPI.
|
aniket
|
Mathematics operation package with Addition, Subtraction, Multiplication, Division
|
anikimiapi
|
AniKimi APIA Simple, LightWeight, Statically-Typed Python3 API wrapper for GogoAnimeThe v2 of gogoanimeapi (depreciated)Made with JavaScript and Python3from anikimiapi import AniKimi
anime = AniKimi(
gogoanime_token="dbakbihihrkqnk3",
auth_token="EKWBIH4NJTO309U4HKTHI39U9TJ5OJ0UU5J9"
)
# Getting Anime Links
anime_link = anime.get_episode_link(animeid="clannad-dub", episode_num=3)
print(anime_link.link_hdp)
print(anime_link.link_720p)
print(anime_link.link_streamsb) # And many more...Features of AniKimiCustom url changing option.Statically-Typed, No more annoying JSON responses.Autocomplete supported by most IDE's.Complete solution.Faster response.Less CPU consumption.For full usage instructions, Head over to theGitHub Page.
|
anikom15
|
Copyright (C) 2010, 2011 Westley MartinezCopying and distribution of this file, with or without modification,
are permitted in any medium without royalty provided the copyright
notice and this notice are preserved. This file is offered as-is,
without any warranty.Installation InstructionsRequires Python and pygame.On POSIX:python setup.py installAlternatively, you may wish to build an rpm package with:python setup.py bdist_rpmOn Windows:python setup.py bdist_wininstYou may then run the installer in the dist directory.How to PlayUse the arrow keys to move and the spacebar to fire bullets.What’s NewTechnically it’s the first release….Known BugsNoneReport bugs [email protected]
|
anikore
|
Anikore API for Python.
|
anilibria.py
|
anilibria.pyО библиотекеanilibria.py - это RESTful и Websocket обёртка для API anilibria.tv.Вы можете ей пользоваться для получение уведомлений о выходе новой серии, получение информации о тайтлах и других вещей.Установкаpip install --upgrade anilibria.pyС использование poetry:poetry add anilibria.pyИспользование методов клиентаВ библиотеке реализована поддержка RESTful API.
Список всех возможных методов вы можете увидетьздесь <https://anilibriapy.readthedocs.io/ru/latest/client.html>__.. code-block:: pythonimport asynciofrom anilibria import AniLibriaClientasync def main():
# Создание клиента
client = AniLibriaClient(proxy="http://0.0.0.0:80") # proxy - необязательный аргумент# Получение тайтла по его коду
title = await client.get_title(code="kimetsu-no-yaiba-yuukaku-hen")
# Вывод описание тайтла
print(title.description) # Все атрибуты вы можете найти в документации моделейasyncio.run(main())Использование WebsocketАПИ Анилибрии имеет вебсокет, к которому можно подключиться... code-block:: pythonfrom anilibria import AniLibriaClient, Connectclient = AniLibriaClient()@client.on(Connect) # Или client.listen(name="on_connect")
async def connected(event: Connect):
print("Подключено к АПИ")client.start()Все модели события вы можете найтиздесь <https://anilibriapy.readthedocs.io/ru/latest/events.html>_Использование с другими библиотеками
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
Вы также можете использовать эту библиотеку вместе с:discord.pyи его форкахaiogramи с другими.Примеры использования представленыздесь <https://github.com/Damego/anilibria.py/tree/main/examples>__Документация
^^^^^^^^^^^^Официальная документация API <https://github.com/anilibria/docs/blob/master/api_v3.md>__Документация библиотеки <https://anilibriapy.readthedocs.io/ru/latest/>__
|
anilist-man
|
Anilist Mananilist-man: python command-line tool for managing your data onAniList, made by@ayushsehrawatin Typer.ContentsWhy?InstallationUsageWhy?anilist-manis a tool which canEasily update progress in few stepsRemove the hassle of finding via search by chapterHas custom name for better user friendly and easier to navigateInstallationUsageTodoRegister on pypi ( python main.py -> some_command )Fix--not in cli ( due to some issue not showing )Add more support and commandsSimply codeFix saving of file issueUsage of codeUsage of code for personal use ( editing , etc ) is allowed but user should give credits to this repository
|
anilistpy
|
AnilistpyAn easy to use python3 wrapper for anilist.co APIv2 (UNOFFICIAL)InstallingInstalling from pypipip install anilistpyInstalling from gitpip install git+https://github.com/anilistpy/anilistpyInstalling from git (Unstable / Development branch)pip install git+https://github.com/anilistpy/anilistpy@devGetting startedImportingimportanilistpyor manually import the method/class you needfromanilistpyimportAnimeMore Documenation and Exampleshere(note: the Documenation is still being updated, if you need help make a issue)Change log 0.0.4 -> 0.0.5added wrappers for mutation apimore minor stuffs
|
anilistwrappy
|
anilistWrapPYName: anilistWrapPYVersion: v0.0.15Edit: 23 May 2022By: Dank-del (Sayan Biswas) (C)anilistWrapPY is an unofficialpythonwrapper foranilistAPI.Table of contentsanilistWrapPYTable of contentsSupported python versionsFeaturesGetting startedHow to useAiringAnimeCharacterMangaMediaUserSupport and ContributionsLinksLicenseSupported python versionsThis library, needs python 3.7 or higher version to be installed.FeaturesUses official anilist API endpoints, which makes this library:Easy to updateGuaranteed to match the docsNo third party endpointsNo need to serialize and deserialize data outside of libraryIt's in pure python, no need to install any kind of plugin or include any kind of additional files.It uses GraphQL to fetch data on AniList servers. The AniList GraphQL API provides quick and powerful access to over 500k anime and manga entries, including character, staff, and live airing data.Anilist Client: Using a client makes it easier to fetch every type of data you want from the servers. You only need to import client and you are ready to go!Getting startedYou can easily download the library with the standardpip installcommand:pipinstallanilistWrapPYYou may want to visit our pypi pagehere.How to useAiringAnimeCharacterMangaMediaUserAiring>>>fromanilistWrapPYimportaniWrapPYClient>>>c=aniWrapPYClient()>>>c.Airing("The Detective Is Already Dead")Anime>>>fromanilistWrapPYimportaniWrapPYClient>>>c=aniWrapPYClient()>>>c.Anime("Kanojo mo kanojo")Character>>>fromanilistWrapPYimportaniWrapPYClient>>>c=aniWrapPYClient()>>>c.Character("Rin tohsaka")Manga>>>fromanilistWrapPYimportaniWrapPYClient>>>c=aniWrapPYClient()>>>c.Manga("Classroom of the elite")Media>>>fromanilistWrapPYimportaniWrapPYClient>>>c=aniWrapPYClient()>>>c.Media("Talentless Nana")User>>>fromanilistWrapPYimportaniWrapPYClient>>>c=aniWrapPYClient()>>>c.User("mimiee")Support and ContributionsIf you think you have found a bug or have a feature request, feel free to use ourissue tracker. Before opening a new issue, please search to see if your problem has already been reported or not. Try to be as detailed as possible in your issue reports.If you need help using AniList APIs or have other questions about this library, we suggest you to join ourtelegram community. Please do not use the GitHub issue tracker for personal support requests.Having a problem with library? Wanna talk with repository's owner? Contact theMaintainer!Want to have a cool multi-purpose Telegram bot in your groups? You can addNana[ナナ]with full features of AniList API!LinksOfficial websiteAniList github orgAniList GraphQL docsSupport chatMaintainer's TelegramNana [ナナ]LicenseThe anilistWrapPY project is under theUnlicense. You can find the license filehere.
|
anillo
|
No description available on PyPI.
|
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.