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/Exercise/22.return_function.py
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# -*- coding:utf-8 -*- # 可变参数求和 # def calc_sum(*args): # ax = 0 # for i in args: # ax = ax + i # return ax # def lazy_sum(*args): # def sum(): # ax = 0 # for i in args: # ax = ax + i # return ax # return sum # print(calc_sum(1,2,3,4,5)) # f = lazy_sum(1,2,3,4,5) # print(f) # print(f()) # 闭包 # def count(): # fs = [] # for i in range(1, 4): # # print(i) # def f(): # return i * i # # print(f) # fs.append(f) # # print(fs) # return fs # f1, f2, f3 = count() # print(11111111111) # print(f1()) # print(2222222222222) # print(f2()) # print(3333333333333) # print(f3()) # 全部都是9!原因就在于返回的函数引用了变量i,但它并非立刻执行。等到3个函数都返回时,它们所引用的变量i已经变成了3,因此最终结果为9。 # 1 # <function count.<locals>.f at 0x000002D93D70E280> # [<function count.<locals>.f at 0x000002D93D70E280>] # 2 # <function count.<locals>.f at 0x000002D93D70E310> # [<function count.<locals>.f at 0x000002D93D70E280>, <function count.<locals>.f at 0x000002D93D70E310>] # 3 # <function count.<locals>.f at 0x000002D93D70E3A0> # [<function count.<locals>.f at 0x000002D93D70E280>, <function count.<locals>.f at 0x000002D93D70E310>, <function count.<locals>.f at 0x000002D93D70E3A0>] # 11111111111 # 9 # 2222222222222 # 9 # 3333333333333 # 9 # def count(): # def f(j): # def g(): # return j * j # return g # fs = [] # for i in range(1, 4): # print(fs) # print(i) # print(f(i)) # fs.append(f(i)) # f(i)立刻被执行,因此i的当前值被传入f() # print(9999999) # print(fs) # return fs # f1, f2, f3 = count() # print(111111) # print(f1) # print(f2) # print(f3) # print(f1()) # print(f2()) # print(f3()) # PS python .\Exercise\22.return_function.py # [] # 1 # <function count.<locals>.f.<locals>.g at 0x000001E53793E310> # 9999999 # [<function count.<locals>.f.<locals>.g at 0x000001E53793E310>] # 2 # <function count.<locals>.f.<locals>.g at 0x000001E53793E3A0> # 9999999 # [<function count.<locals>.f.<locals>.g at 0x000001E53793E310>, <function count.<locals>.f.<locals>.g at 0x000001E53793E3A0>] # 3 # <function count.<locals>.f.<locals>.g at 0x000001E53793E430> # 9999999 # [<function count.<locals>.f.<locals>.g at 0x000001E53793E310>, <function count.<locals>.f.<locals>.g at 0x000001E53793E3A0>, <function count.<locals>.f.<locals>.g at # 0x000001E53793E430>] # 111111 # 1 # 4 # 9 # lambda 缩减代码 # def count(): # def f(j): # return lambda : j * j # fs = [] # for i in range(1, 4): # fs.append(f(i)) # return fs # f1, f2, f3 = count() # print(f1()) # print(f2()) # print(f3()) # 练习 # 利用闭包返回一个计数器函数,每次调用它返回递增整数: def createCounter(): i = 0 # 先定义一个变量作为初始值 def counter(): nonlocal i # 声明变量i非内部函数的局部变量,否则内部函数只能引用,一旦修改会视其为局部变量,报错“局部变量在赋值之前被引用”。 i = i + 1 # 每调用一次内部函数,对i + 1 ======= 重点是修改全局变量的值! return i return counter # f1 = createCounter() # print(777777) # print(f1) # print(f1(), f1(), f1()) # f2 = createCounter() # print(f2) # print(f2(),f2(),f2()) # 测试: counterA = createCounter() print(counterA(), counterA(), counterA(), counterA(), counterA()) # 1 2 3 4 5 counterB = createCounter() if [counterB(), counterB(), counterB(), counterB()] == [1, 2, 3, 4]: print('测试通过!') else: print('测试失败!')
eecf1d418155f7ae27b4dce7f4c4aa384bb413b4
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/testDjango/views.py
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fxma/testDjango
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da2bb8e647d5987e3a7ca3fd58f904e88d2bcf11
refs/heads/master
2020-04-11T18:42:05.876201
2018-12-16T14:39:23
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from django.http import HttpResponse,Http404 import time import datetime from django.shortcuts import render from django.shortcuts import render_to_response import MySQLdb # def hello(request): # return HttpResponse("hello world!") def hello(request): context = dict() context['hello'] = 'Hello World!' return render(request, 'hello.html', context) def current_time(request): # return HttpResponse("Current time is: "+time.strftime('%Y-%m-%d %H:%M:%S')) now = datetime.datetime.now() html = "<html><body>It is now %s.</body></html>" % now return HttpResponse(html) def hours_ahead(request, offset): try: offset = int(offset) except ValueError: raise Http404() dt = datetime.datetime.now() + datetime.timedelta(hours=offset) html = "<html><body>In %s hour(s), it will be %s.</body></html>" % (offset, dt) return HttpResponse(html) def book_list(request): db = MySQLdb.connect(user='test', db='testdb', passwd='test', host='localhost') cursor = db.cursor() cursor.execute('SELECT name FROM books ORDER BY name') names = [row[0] for row in cursor.fetchall()] db.close() return render_to_response('book_list.html', {'names': names})
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/web/models.py
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[]
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coolestcat/higweb
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refs/heads/master
2021-01-19T00:30:15.817902
2015-04-19T22:57:10
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from __future__ import unicode_literals from tastypie.utils.timezone import now from django.db import models class Alias(models.Model): aliassernum = models.IntegerField(db_column='AliasSerNum', primary_key=True) # Field name made lowercase. aliasname = models.CharField(db_column='AliasName', unique=True, max_length=100) # Field name made lowercase. aliastype = models.CharField(db_column='AliasType', max_length=25) # Field name made lowercase. aliasupdate = models.IntegerField(db_column='AliasUpdate') # Field name made lowercase. lastupdated = models.DateTimeField(db_column='LastUpdated') # Field name made lowercase. class Meta: managed = False db_table = 'Alias' class Aliasexpression(models.Model): aliasexpressionsernum = models.IntegerField(db_column='AliasExpressionSerNum', primary_key=True) # Field name made lowercase. aliassernum = models.IntegerField(db_column='AliasSerNum') # Field name made lowercase. expressionname = models.CharField(db_column='ExpressionName', max_length=100) # Field name made lowercase. class Meta: managed = False db_table = 'AliasExpression' class Appointment(models.Model): appointmentsernum = models.IntegerField(db_column='AppointmentSerNum', primary_key=True) # Field name made lowercase. patientsernum = models.IntegerField(db_column='PatientSerNum') # Field name made lowercase. appointmentid = models.IntegerField(db_column='AppointmentId', blank=True, null=True) # Field name made lowercase. diagnosissernum = models.IntegerField(db_column='DiagnosisSerNum') # Field name made lowercase. prioritysernum = models.IntegerField(db_column='PrioritySerNum') # Field name made lowercase. aliassernum = models.IntegerField(db_column='AliasSerNum', blank=True, null=True) # Field name made lowercase. aliasexpressionsernum = models.IntegerField(db_column='AliasExpressionSerNum') # Field name made lowercase. status = models.CharField(db_column='Status', max_length=50, blank=True) # Field name made lowercase. scheduledstarttime = models.DateTimeField(db_column='ScheduledStartTime', blank=True, null=True) # Field name made lowercase. scheduledendtime = models.DateTimeField(db_column='ScheduledEndTime', blank=True, null=True) # Field name made lowercase. lastupdated = models.DateTimeField(db_column='LastUpdated') # Field name made lowercase. class Meta: managed = False db_table = 'Appointment' class Cron(models.Model): profile = models.IntegerField(db_column='Profile') # Field name made lowercase. nextcron = models.DateField(db_column='NextCron') # Field name made lowercase. repeatoption = models.CharField(db_column='RepeatOption', max_length=25) # Field name made lowercase. repeattime = models.TimeField(db_column='RepeatTime') # Field name made lowercase. lastcron = models.DateTimeField(db_column='LastCron') # Field name made lowercase. class Meta: managed = False db_table = 'Cron' class Diagnosis(models.Model): diagnosissernum = models.IntegerField(db_column='DiagnosisSerNum', primary_key=True) # Field name made lowercase. patientsernum = models.IntegerField(db_column='PatientSerNum') # Field name made lowercase. diagnosisid = models.CharField(db_column='DiagnosisId', max_length=25, blank=True) # Field name made lowercase. diagnosiscreationdate = models.DateTimeField(db_column='DiagnosisCreationDate', blank=True, null=True) # Field name made lowercase. diagnosiscode = models.CharField(db_column='DiagnosisCode', max_length=25, blank=True) # Field name made lowercase. description = models.TextField(db_column='Description') # Field name made lowercase. lastupdated = models.DateTimeField(db_column='LastUpdated') # Field name made lowercase. class Meta: managed = False db_table = 'Diagnosis' class Doctor(models.Model): doctorsernum = models.IntegerField(db_column='DoctorSerNum', primary_key=True) # Field name made lowercase. oncologistflag = models.IntegerField(db_column='OncologistFlag') # Field name made lowercase. class Meta: managed = False db_table = 'Doctor' class Document(models.Model): documentsernum = models.IntegerField(db_column='DocumentSerNum', primary_key=True) # Field name made lowercase. patientsernum = models.IntegerField(db_column='PatientSerNum') # Field name made lowercase. documentid = models.CharField(db_column='DocumentId', max_length=30) # Field name made lowercase. diagnosissernum = models.IntegerField(db_column='DiagnosisSerNum') # Field name made lowercase. prioritysernum = models.IntegerField(db_column='PrioritySerNum') # Field name made lowercase. approvalstatus = models.CharField(db_column='ApprovalStatus', max_length=11) # Field name made lowercase. approvedbysernum = models.IntegerField(db_column='ApprovedBySerNum', blank=True, null=True) # Field name made lowercase. approvedtimestamp = models.DateTimeField(db_column='ApprovedTimeStamp', blank=True, null=True) # Field name made lowercase. authoredbysernum = models.IntegerField(db_column='AuthoredBySerNum') # Field name made lowercase. dateofservice = models.DateTimeField(db_column='DateOfService') # Field name made lowercase. aliassernum = models.IntegerField(db_column='AliasSerNum') # Field name made lowercase. aliasexpressionsernum = models.IntegerField(db_column='AliasExpressionSerNum') # Field name made lowercase. printed = models.CharField(db_column='Printed', max_length=5, blank=True) # Field name made lowercase. signedbysernum = models.IntegerField(db_column='SignedBySerNum', blank=True, null=True) # Field name made lowercase. signedtimestamp = models.DateTimeField(db_column='SignedTimeStamp', blank=True, null=True) # Field name made lowercase. supervisedbysernum = models.IntegerField(db_column='SupervisedBySerNum', blank=True, null=True) # Field name made lowercase. createdbysernum = models.IntegerField(db_column='CreatedBySerNum') # Field name made lowercase. createdtimestamp = models.DateTimeField(db_column='CreatedTimeStamp') # Field name made lowercase. lastupdated = models.DateTimeField(db_column='LastUpdated') # Field name made lowercase. class Meta: managed = False db_table = 'Document' class Field(models.Model): fieldsernum = models.IntegerField(db_column='FieldSerNum', primary_key=True) # Field name made lowercase. plansernum = models.IntegerField(db_column='PlanSerNum') # Field name made lowercase. fieldid = models.IntegerField(db_column='FieldId') # Field name made lowercase. fieldcreationdate = models.DateTimeField(db_column='FieldCreationDate') # Field name made lowercase. gantryrtn = models.FloatField(db_column='GantryRtn') # Field name made lowercase. lastupdated = models.DateTimeField(db_column='LastUpdated') # Field name made lowercase. class Meta: managed = False db_table = 'Field' class Patient(models.Model): patientsernum = models.IntegerField(db_column='PatientSerNum', primary_key=True) # Field name made lowercase. dateofbirth = models.TextField(db_column='DateOfBirth', blank=True) # Field name made lowercase. This field type is a guess. sex = models.CharField(db_column='Sex', max_length=11, blank=True) # Field name made lowercase. postalcode = models.CharField(db_column='PostalCode', max_length=25) # Field name made lowercase. lastupdated = models.DateTimeField(db_column='LastUpdated') # Field name made lowercase. class Meta: managed = False db_table = 'Patient' class Patientdoctor(models.Model): patientdoctorsernum = models.IntegerField(db_column='PatientDoctorSerNum', primary_key=True) # Field name made lowercase. patientsernum = models.IntegerField(db_column='PatientSerNum') # Field name made lowercase. doctorsernum = models.IntegerField(db_column='DoctorSerNum') # Field name made lowercase. oncologistflag = models.IntegerField(db_column='OncologistFlag') # Field name made lowercase. primaryflag = models.IntegerField(db_column='PrimaryFlag') # Field name made lowercase. lastupdated = models.DateTimeField(db_column='LastUpdated') # Field name made lowercase. class Meta: managed = False db_table = 'PatientDoctor' class Patientlocation(models.Model): patientlocationsernum = models.IntegerField(db_column='PatientLocationSerNum', primary_key=True) # Field name made lowercase. appointmentsernum = models.IntegerField(db_column='AppointmentSerNum') # Field name made lowercase. patientlocationid = models.IntegerField(db_column='PatientLocationId') # Field name made lowercase. resourceser = models.IntegerField(db_column='ResourceSer') # Field name made lowercase. revcount = models.IntegerField(db_column='RevCount') # Field name made lowercase. checkedinflag = models.IntegerField(db_column='CheckedInFlag') # Field name made lowercase. arrivaldatetime = models.DateTimeField(db_column='ArrivalDateTime') # Field name made lowercase. lastupdated = models.DateTimeField(db_column='LastUpdated') # Field name made lowercase. class Meta: managed = False db_table = 'PatientLocation' class Patientlocationmh(models.Model): patientlocationmhsernum = models.IntegerField(db_column='PatientLocationMHSerNum', primary_key=True) # Field name made lowercase. appointmentsernum = models.IntegerField(db_column='AppointmentSerNum') # Field name made lowercase. patientlocationid = models.IntegerField(db_column='PatientLocationId') # Field name made lowercase. resourceser = models.IntegerField(db_column='ResourceSer') # Field name made lowercase. revcount = models.IntegerField(db_column='RevCount') # Field name made lowercase. checkedinflag = models.IntegerField(db_column='CheckedInFlag') # Field name made lowercase. arrivaldatetime = models.DateTimeField(db_column='ArrivalDateTime') # Field name made lowercase. lastupdated = models.DateTimeField(db_column='LastUpdated') # Field name made lowercase. class Meta: managed = False db_table = 'PatientLocationMH' class Plan(models.Model): plansernum = models.IntegerField(db_column='PlanSerNum', primary_key=True) # Field name made lowercase. patientsernum = models.IntegerField(db_column='PatientSerNum') # Field name made lowercase. planid = models.IntegerField(db_column='PlanId') # Field name made lowercase. diagnosissernum = models.IntegerField(db_column='DiagnosisSerNum') # Field name made lowercase. prioritysernum = models.IntegerField(db_column='PrioritySerNum') # Field name made lowercase. aliassernum = models.IntegerField(db_column='AliasSerNum') # Field name made lowercase. aliasexpressionsernum = models.IntegerField(db_column='AliasExpressionSerNum') # Field name made lowercase. plancreationdate = models.DateTimeField(db_column='PlanCreationDate') # Field name made lowercase. status = models.CharField(db_column='Status', max_length=100) # Field name made lowercase. lastupdated = models.DateTimeField(db_column='LastUpdated') # Field name made lowercase. class Meta: managed = False db_table = 'Plan' class Priority(models.Model): prioritysernum = models.IntegerField(db_column='PrioritySerNum', primary_key=True) # Field name made lowercase. patientsernum = models.IntegerField(db_column='PatientSerNum') # Field name made lowercase. priorityid = models.CharField(db_column='PriorityId', max_length=25, blank=True) # Field name made lowercase. prioritydatetime = models.DateTimeField(db_column='PriorityDateTime', blank=True, null=True) # Field name made lowercase. prioritycode = models.CharField(db_column='PriorityCode', max_length=25, blank=True) # Field name made lowercase. lastupdated = models.DateTimeField(db_column='LastUpdated') # Field name made lowercase. class Meta: managed = False db_table = 'Priority' class Staff(models.Model): staffsernum = models.IntegerField(db_column='StaffSerNum', primary_key=True) # Field name made lowercase. lastupdated = models.DateTimeField(db_column='LastUpdated') # Field name made lowercase. class Meta: managed = False db_table = 'Staff' class Study(models.Model): studysernum = models.IntegerField(db_column='StudySerNum', primary_key=True) # Field name made lowercase. usersernum = models.IntegerField(db_column='UserSerNum') # Field name made lowercase. studyname = models.CharField(db_column='StudyName', max_length=100) # Field name made lowercase. relativeplot = models.IntegerField(db_column='RelativePlot') # Field name made lowercase. binwidth = models.IntegerField(db_column='BinWidth') # Field name made lowercase. thresholdtype = models.CharField(db_column='ThresholdType', max_length=100) # Field name made lowercase. thresholdpercent = models.IntegerField(db_column='ThresholdPercent', blank=True, null=True) # Field name made lowercase. histdataseriestype = models.CharField(db_column='HistDataSeriesType', max_length=25) # Field name made lowercase. histdatastartdate = models.DateField(db_column='HistDataStartDate') # Field name made lowercase. histdataenddate = models.DateField(db_column='HistDataEndDate') # Field name made lowercase. currdataseriestype = models.CharField(db_column='CurrDataSeriesType', max_length=25) # Field name made lowercase. currdatastartdate = models.DateField(db_column='CurrDataStartDate') # Field name made lowercase. class Meta: managed = False db_table = 'Study' class Studydiagnosisfilter(models.Model): studydiagnosisfiltersernum = models.IntegerField(db_column='StudyDiagnosisFilterSerNum', primary_key=True) # Field name made lowercase. studysernum = models.IntegerField(db_column='StudySerNum') # Field name made lowercase. filtername = models.TextField(db_column='FilterName') # Field name made lowercase. class Meta: managed = False db_table = 'StudyDiagnosisFilter' class Studypriorityfilter(models.Model): studypriorityfiltersernum = models.IntegerField(db_column='StudyPriorityFilterSerNum', primary_key=True) # Field name made lowercase. studysernum = models.IntegerField(db_column='StudySerNum') # Field name made lowercase. filtername = models.CharField(db_column='FilterName', max_length=1000) # Field name made lowercase. class Meta: managed = False db_table = 'StudyPriorityFilter' class Studythreshold(models.Model): thresholdsernum = models.IntegerField(db_column='ThresholdSerNum', primary_key=True) # Field name made lowercase. studysernum = models.IntegerField(db_column='StudySerNum') # Field name made lowercase. minimum = models.IntegerField(db_column='Minimum') # Field name made lowercase. maximum = models.IntegerField(db_column='Maximum') # Field name made lowercase. class Meta: managed = False db_table = 'StudyThreshold' class Task(models.Model): tasksernum = models.IntegerField(db_column='TaskSerNum', primary_key=True) # Field name made lowercase. patientsernum = models.IntegerField(db_column='PatientSerNum') # Field name made lowercase. taskid = models.IntegerField(db_column='TaskId', blank=True, null=True) # Field name made lowercase. diagnosissernum = models.IntegerField(db_column='DiagnosisSerNum') # Field name made lowercase. prioritysernum = models.IntegerField(db_column='PrioritySerNum') # Field name made lowercase. aliassernum = models.IntegerField(db_column='AliasSerNum') # Field name made lowercase. aliasexpressionsernum = models.IntegerField(db_column='AliasExpressionSerNum') # Field name made lowercase. status = models.CharField(db_column='Status', max_length=50) # Field name made lowercase. duedatetime = models.DateTimeField(db_column='DueDateTime', blank=True, null=True) # Field name made lowercase. creationdate = models.DateTimeField(db_column='CreationDate', blank=True, null=True) # Field name made lowercase. completiondate = models.DateTimeField(db_column='CompletionDate', blank=True, null=True) # Field name made lowercase. lastupdated = models.DateTimeField(db_column='LastUpdated') # Field name made lowercase. class Meta: managed = False db_table = 'Task' class Timedelaystudy(models.Model): timedelaystudysernum = models.IntegerField(db_column='TimeDelayStudySerNum', primary_key=True) # Field name made lowercase. studysernum = models.IntegerField(db_column='StudySerNum') # Field name made lowercase. startaliassernum = models.IntegerField(db_column='StartAliasSerNum') # Field name made lowercase. starttimestampname = models.CharField(db_column='StartTimeStampName', max_length=100) # Field name made lowercase. startstatuses = models.CharField(db_column='StartStatuses', max_length=100, blank=True) # Field name made lowercase. endaliassernum = models.IntegerField(db_column='EndAliasSerNum') # Field name made lowercase. endtimestampname = models.CharField(db_column='EndTimeStampName', max_length=100) # Field name made lowercase. endstatuses = models.CharField(db_column='EndStatuses', max_length=100) # Field name made lowercase. class Meta: managed = False db_table = 'TimeDelayStudy' class Treatmentfieldhstry(models.Model): treatmentfieldhstrysernum = models.IntegerField(db_column='TreatmentFieldHstrySerNum', primary_key=True) # Field name made lowercase. plansernum = models.IntegerField(db_column='PlanSerNum') # Field name made lowercase. treatmentfieldhstryid = models.IntegerField(db_column='TreatmentFieldHstryId') # Field name made lowercase. treatmentdatetime = models.DateTimeField(db_column='TreatmentDateTime') # Field name made lowercase. gantryrtn = models.FloatField(db_column='GantryRtn') # Field name made lowercase. lastupdated = models.DateTimeField(db_column='LastUpdated') # Field name made lowercase. class Meta: managed = False db_table = 'TreatmentFieldHstry' class Treatmentparameterstudy(models.Model): treatmentparameterstudysernum = models.IntegerField(db_column='TreatmentParameterStudySerNum', primary_key=True) # Field name made lowercase. studysernum = models.IntegerField(db_column='StudySerNum') # Field name made lowercase. aliassernum = models.IntegerField(db_column='AliasSerNum') # Field name made lowercase. treatmentparameterfield = models.CharField(db_column='TreatmentParameterField', max_length=100) # Field name made lowercase. treatmentparameterdisplayname = models.CharField(db_column='TreatmentParameterDisplayName', max_length=100) # Field name made lowercase. treatmentparameterunits = models.CharField(db_column='TreatmentParameterUnits', max_length=100) # Field name made lowercase. planstatus = models.CharField(db_column='PlanStatus', max_length=100) # Field name made lowercase. polarplot = models.IntegerField(db_column='PolarPlot') # Field name made lowercase. class Meta: managed = False db_table = 'TreatmentParameterStudy' class User(models.Model): usersernum = models.IntegerField(db_column='UserSerNum', primary_key=True) # Field name made lowercase. class Meta: managed = False db_table = 'User' class Venue(models.Model): venuesernum = models.IntegerField(db_column='VenueSerNum', primary_key=True) # Field name made lowercase. venuename = models.CharField(db_column='VenueName', max_length=50) # Field name made lowercase. resourceser = models.IntegerField(db_column='ResourceSer') # Field name made lowercase. class Meta: managed = False db_table = 'Venue' class Entry(models.Model): pub_date = models.DateTimeField(default=now) title = models.CharField(max_length=200) def __unicode__(self): return self.title
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refs/heads/main
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# Analizador Léxico by Elmer Jaén import matplotlib.pyplot as plt def table(list_show): fig, ax = plt.subplots(1,1) plt.rcParams.update({'font.size': 18}) #ch3eange font size # row_labels is optional row_labels=['Palabras reservadas:', 'Identificadores:', 'Operadores lógicos matemáticos:','Números positivos y negativos:'] ax.axis('tight') ax.axis('off') the_table = ax.table(cellText=list_show, rowLabels=row_labels, loc="center", cellLoc='center') the_table.scale(2,3) #change table scale for i in range(0, 4): the_table[(i, -1)].set_facecolor("#56b5fd") plt.show() reserved_keywords = ['If', 'Else', 'Declare', 'Dim', 'Integer'] operators = ['+', '-', '*', '/', '=', '==', 'and', 'or', 'not'] def show_results(data_list): list_show = [] k = 0 for i in data_list: string = "" list_show.append([]) for j in i: string += str(j) + ", " string = string[:-2] if list_show: list_show[k].append(string) else: list_show.append(string) k += 1 table(list_show) def classify(data): keywords_in_data = [] operators_in_data = [] numbers_in_data = [] identifiers_in_data = [] IDENTIFIERS = [] # get all reserverd keywords for i in reserved_keywords: for j, k in enumerate(data): if i in k: keywords_in_data.append(i) # get all the possible identifiers that are neither in # reserved_keywords nor in operators for i in data: if i.isidentifier() == True and i not in reserved_keywords and i not in operators: identifiers_in_data.append(i) for i, j in enumerate(identifiers_in_data): if j[0] != "_": IDENTIFIERS.append(j) # get all the operators for i in operators: for j, k in enumerate(data): if i == k: operators_in_data.append(i) # get all the negative and positive numbers for i, j in enumerate(data): if j == "" or j == "-": continue elif j.isnumeric() == True: numbers_in_data.append(int(j)) # for negative numbers elif j[0] == "-" and j[1].isnumeric(): numbers_in_data.append(int(j)) return keywords_in_data, IDENTIFIERS, operators_in_data, numbers_in_data # extract word for word def extract_words(data): data2 = [] string = "" data_size = len(data)-1 for i, j in enumerate(data): j_size = len(j)-1 for k, m in enumerate(j): # delete " " and \n if m != " " and m != "\n": if m == "\t": continue else: string += m else: data2.append(string) string = "" return data2 def run(): data = [] print("\nA continuación ingrese una cadena. Escriba 'exit' al terminar.\n") while True: string = input() if string == 'exit': break else: data.append(string+'\n') data_list = classify(extract_words(data)) show_results(data_list) if __name__ == '__main__': run()
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/Chapter4Lists/Proj1.py
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def comma(inputlist): outputstring='' outputstring+=inputlist[0] for i in range(1,len(inputlist)-1): outputstring+=','+inputlist[i] outputstring+=',and '+inputlist[len(inputlist)-1] return outputstring mylist=['apples','bananas', 'tofu', 'cats', 'dogs', 'mice', 'yogurt'] string=comma(mylist) print(string)
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# -*- coding: utf-8 -*- from __future__ import unicode_literals from django.db import models, migrations class Migration(migrations.Migration): dependencies = [ ('profile', '0026_auto_20150915_2314'), ] operations = [ migrations.AlterField( model_name='company', name='about', field=models.CharField(max_length=1400), ), ]
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/TocTable_algorithm.py
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# -*- coding: utf-8 -*- """ /*************************************************************************** TocTable A QGIS plugin TocTable Generated by Plugin Builder: http://g-sherman.github.io/Qgis-Plugin-Builder/ ------------------- begin : 2020-11-23 copyright : (C) 2020 by Giulio Fattori email : [email protected] ***************************************************************************/ /*************************************************************************** * * * This program is free software; you can redistribute it and/or modify * * it under the terms of the GNU General Public License as published by * * the Free Software Foundation; either version 2 of the License, or * * (at your option) any later version. * * * ***************************************************************************/ """ __author__ = 'Giulio Fattori' __date__ = '2020-11-23' __copyright__ = '(C) 2020 by Giulio Fattori' # This will get replaced with a git SHA1 when you do a git archive __revision__ = '$Format:%H$' from PyQt5.QtCore import QCoreApplication, QVariant from qgis.core import (QgsProcessing, QgsProject, QgsField, QgsFields, QgsFeature, QgsFeatureSink, QgsMapLayerType, QgsWkbTypes, QgsLayerTreeGroup, QgsLayerTreeLayer, QgsProcessingException, QgsProcessingAlgorithm, QgsProcessingParameterField, QgsProcessingParameterFeatureSource, QgsProcessingParameterFeatureSink) import datetime #questo per l'icona dell'algoritmo di processing import os import inspect from qgis.PyQt.QtGui import QIcon class TocTableAlgorithm(QgsProcessingAlgorithm): """ TOC algorithm retrieve info from Metadata and some attributes of each layer and collect it's in a table. """ INPUT_F = 'INPUT_F' OUTPUT = 'OUTPUT' def tr(self, string): """ Returns a translatable string with the self.tr() function. """ return QCoreApplication.translate('Processing', string) #icona dell'algoritmo di processing def icon(self): cmd_folder = os.path.split(inspect.getfile(inspect.currentframe()))[0] icon = QIcon(os.path.join(os.path.join(cmd_folder, 'icon.png'))) return icon def createInstance(self): return TocTableAlgorithm() def name(self): """ Returns the algorithm name, used for identifying the algorithm. This string should be fixed for the algorithm, and must not be localised. The name should be unique within each provider. Names should contain lowercase alphanumeric characters only and no spaces or other formatting characters. """ return 'Toc Table' def displayName(self): """ Returns the translated algorithm name, which should be used for any user-visible display of the algorithm name. """ return self.tr('Toc Table') def group(self): """ Returns the name of the group this algorithm belongs to. This string should be localised. """ return '' def groupId(self): """ Returns the unique ID of the group this algorithm belongs to. This string should be fixed for the algorithm, and must not be localised. The group id should be unique within each provider. Group id should contain lowercase alphanumeric characters only and no spaces or other formatting characters. """ return '' def shortHelpString(self): """ Returns a localised short helper string for the algorithm. This string should provide a basic description about what the algorithm does and the parameters and outputs associated with it.. """ return self.tr("The algorithm retrieves some properties and metadata of the project layers and \ inserts them in a table so that they can be inserted in the prints. Keeps track\ of the order of layers in the project and any groups\n \ Questo algoritmo recupera alcuni metadati e proprietà dei layer del progetto e\ li raccoglie in una tabella così da poterli inserire nelle stampe.\ Tiene traccia dell'ordine dei layer nel progetto e degli eventuali gruppi") def initAlgorithm(self, config=None): """ Here we define the inputs and output of the algorithm, along with some other properties. """ # We add a feature sink in which to store our processed features (this # usually takes the form of a newly created vector layer when the # algorithm is run in QGIS). self.addParameter( QgsProcessingParameterFeatureSink( self.OUTPUT, self.tr('Project_Layers_Table ' + str(datetime.datetime.now().strftime("%d-%m-%Y %H:%M:%S"))) ) ) self.addParameter( QgsProcessingParameterField( self.INPUT_F, self.tr('Campi da inserire nella TocTable'), 'Layer_N;Layer_Group_Level;Layer_Storage;Layer_Name;Geometry_Not_Valid;Layer_Crs;Layer_Type;Layer_Type_Name;Layer_Source;Raster_type;Raster_data_type;Raster_Info_dim;Raster_extent;Raster_Info_res;Raster_NoDataValue;Layer_Feature_Count;Layer_Meta_Parent_Id;Layer_Meta_Identifier;Layer_Meta_Title;Layer_Meta_Type;Layer_Meta_Language;Layer_Meta_Abstract', allowMultiple = True ) ) def processAlgorithm(self, parameters, context, feedback): """ Here is where the processing itself takes place. """ i_fields = self.parameterAsMatrix( parameters, self.INPUT_F, context) #CREA TABELLA CONTENUTI PROGETTO #per altri campi occorre vedere quali si serve aggiungere #funzione iterativa per posizione layer nella TOC def get_group_layers(group, level): level = level + group.name() + ' - '#' >> ' for child in group.children(): if isinstance(child, QgsLayerTreeGroup): get_group_layers(child, level) else: TOC_dict [child.name()] = level #print(lev) #dizionario delle posizioni TOC_dict ={} root = QgsProject.instance().layerTreeRoot() for child in root.children(): level = 'root - ' #' >> ' if isinstance(child, QgsLayerTreeGroup): get_group_layers(child, level) elif isinstance(child, QgsLayerTreeLayer): #lev = level #+ child.name()) TOC_dict[child.name()] = level #abort if TOC is empty #feedback.pushInfo (str(TOC_dict)) #feedback.pushInfo (str(not bool(TOC_dict))) if not bool(TOC_dict): raise QgsProcessingException('Invalid input value: EMPY PROJECT') #parametro denominazione tabella risultante report = 'Project_Layers_Table' fields = QgsFields() for item in i_fields: if item in ('Layer_N','Geometry_Not_Valid','Layer_Type','Layer_Feature_Count'): fields.append(QgsField(item, QVariant.Int)) else: fields.append(QgsField(item, QVariant.String)) (sink, dest_id) = self.parameterAsSink( parameters, self.OUTPUT, context, fields) # If sink was not created, throw an exception to indicate that the algorithm # encountered a fatal error. The exception text can be any string, but in this # case we use the pre-built invalidSinkError method to return a standard # helper text for when a sink cannot be evaluated if sink is None: raise QgsProcessingException(self.invalidSinkError(parameters, self.OUTPUT)) feat = QgsFeature() count = 1 for layer in QgsProject.instance().mapLayers().values(): if layer.name().find("Project_Layers_Table") == -1: Layer_N = count count += 1 Layer_Name = layer.name() Layer_Group_Level = TOC_dict.get(Layer_Name) Layer_Crs = layer.crs().authid() Layer_Source = layer.source() Layer_Meta_Parent_Id = layer.metadata().parentIdentifier() Layer_Meta_Identifier = layer.metadata().identifier() Layer_Meta_Title = layer.metadata().title() Layer_Meta_Type = layer.metadata().type() Layer_Meta_Language = layer.metadata().language() Layer_Meta_Abstract = layer.metadata().abstract() Raster_type = Raster_data_type = Raster_Info_dim = '-' Raster_extent = Raster_Info_res = Raster_NoDataValue = '-' if layer.type() is not QgsMapLayerType.RasterLayer: Layer_Feature_Count = layer.featureCount() Layer_Type = layer.wkbType() Layer_Storage = layer.storageType() Layer_Type_Name = QgsWkbTypes.displayString(layer.wkbType()) Geometry_Not_Valid = 0 for f in layer.getFeatures(): if not f.geometry().isGeosValid(): Geometry_Not_Valid += 1 else: Layer_Type = (0) Layer_Type_Name = QgsMapLayerType.RasterLayer.name Layer_Storage = '' Layer_Feature_Count = 'nan' Geometry_Not_Valid = 0 gh = layer.height() gw = layer.width() Raster_extent = layer.extent().toString() provider = layer.dataProvider() gpx = layer.rasterUnitsPerPixelX() gpy = layer.rasterUnitsPerPixelY() block = provider.block(1, layer.extent(), gpy, gpx) for band in range(1, layer.bandCount()+1): #print('Band ', band, layer.dataProvider().sourceNoDataValue(band)) Raster_NoDataValue = Raster_NoDataValue + 'Band ' + str(band) + ': ' + str(layer.dataProvider().sourceNoDataValue(band)) + ' ' Raster_data_type = type(provider.sourceNoDataValue(band)).__name__ Raster_type = layer.renderer().type() #feedback.pushInfo(str(gh)+' x '+str(gw)+' - '+ str(gpx)+' x '+str(gpy)) Raster_Info_dim = str(gh) + ' x '+ str(gw) Raster_Info_res = str(gpx) + ' x ' + str(gpy) campi = [] for item in i_fields: campi.append(vars()[item]) feat.setAttributes(campi) sink.addFeature(feat, QgsFeatureSink.FastInsert) return {self.OUTPUT: dest_id}
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import webbrowser class Movie(): """This class provides a way to store movie related information""" def __init__(self,movie_title,movie_storyline,poster_image,trailer_youtube): """ This docstring explains the constructor method, it's inputs and outputs if any """ self.title = movie_title self.storyline = movie_storyline self.poster_image_url = poster_image self.trailer_youtube_url = trailer_youtube def show_trailer(self): """ This docstring explains what the show_trailer function does """ webbrowser.open(self.trailer_youtube_url)
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from .abs_cust import AbsCust class NullCust(AbsCust): def __init__(self,cust_type): self._cust_type = cust_type @property def name(self): return None @name.setter def name(self, name): pass def send_invoice(self): print('Customer type "%s" not found.' % self._cust_type)
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from __future__ import unicode_literals from django.db import models from django.core.exceptions import ObjectDoesNotExist import bcrypt, re EMAIL_REGEX = re.compile(r'^[a-zA-Z0-9.+_-]+@[a-zA-Z0-9._-]+\.[a-zA-Z]+$') class UserManager(models.Manager): def validate_reg(self, request): errors = self.validate_inputs(request) if errors: return (False, errors) pw_hash = bcrypt.hashpw(request.POST['password'].encode(), bcrypt.gensalt()) user = self.create(first_name=request.POST['first_name'], last_name=request.POST['last_name'], email=request.POST['email'], password=pw_hash) return (True, user) def validate_login(self, request): try: user = User.objects.get(email=request.POST['email']) password = request.POST['password'].encode() if bcrypt.hashpw(password, user.password.encode()): return (True, user) except ObjectDoesNotExist: pass return (False, ["Invalid login."]) def validate_inputs(self, request): errors = [] if not request.POST['first_name']: errors.append('First name cannot be blank.') if not request.POST['email']: errors.append('Please enter an email.') elif not EMAIL_REGEX.match(request.POST['email']): errors.append('Invalid email.') if len(request.POST['password']) < 8: errors.append('Password must be at least 8 characters.') if request.POST['password'] != request.POST['confirm']: errors.append('Password and password confirm must match.') return errors class User(models.Model): first_name = models.CharField(max_length = 50) last_name = models.CharField(max_length = 50) email = models.CharField(max_length = 50) password = models.CharField(max_length = 255) created_at = models.DateTimeField(auto_now_add=True) updated_at = models.DateTimeField(auto_now=True) objects = UserManager()
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class News: ''' news class to define news Objects ''' def __init__(self, id, title, overview): self.id = id self.title = title self.overview = overview
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from django.contrib import admin from django.urls import path, include from django.conf.urls import url from django.conf import settings from django.conf.urls.static import static from rest_framework import permissions from drf_yasg.views import get_schema_view from drf_yasg import openapi from rest_framework.authtoken import views schema_view = get_schema_view( openapi.Info( title="Snippets API", default_version='v1', description="Test description", terms_of_service="https://www.google.com/policies/terms/", contact=openapi.Contact(email="[email protected]"), license=openapi.License(name="BSD License"), ), public=True, permission_classes=(permissions.AllowAny,), ) urlpatterns = [ path('accounts/', include('accounts.urls')), path('blog/', include('blog.urls')), path('edoc/', include('edoc.urls')), path('admin/', admin.site.urls), # urls for documenting the api url(r'^swagger(?P<format>\.json|\.yaml)$', schema_view.without_ui(cache_timeout=0), name='schema-json'), url(r'^swagger/$', schema_view.with_ui('swagger', cache_timeout=0), name='schema-swagger-ui'), url(r'^redoc/$', schema_view.with_ui('redoc', cache_timeout=0), name='schema-redoc'), ] # serving media files only during developement if settings.DEBUG: urlpatterns += static(settings.MEDIA_URL, document_root=settings.MEDIA_ROOT)
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# -*- coding: utf-8 -*- from simple_perms import PermissionLogic, register from helpers.mixins import BasicPermissionLogicMixin class UserPermissionLogic(BasicPermissionLogicMixin, PermissionLogic): def view(self, user, user_to_view, *args): if user_to_view == user: return True if user.is_client or user.is_professional: return False if user.is_administrator or user.is_advisor or user.is_manager: return True return self.admin_permission(user, user_to_view, *args) def change(self, user, user_to_modify, *args): if user_to_modify == user: return True if user.is_client or user.is_professional: return False if user.is_administrator: return True # Allow same group modifications if user_to_modify.group is not None and user_to_modify.group.is_member(user): if user.is_advisor and user_to_modify.is_advisor: return True if user.is_manager and ( user_to_modify.is_advisor or user_to_modify.is_manager ): return True if (user.is_advisor or user.is_manager) and user_to_modify.is_client: return True if ( user.is_manager and user_to_modify.is_advisor and user_to_modify.group.admin_group == user.group and user.group.is_admin ): return True if ( user.is_manager and user_to_modify.is_manager and user_to_modify.group == user.group ): return True return self.admin_permission(user, user_to_modify, *args) def change_user_type(self, user, *args): """ Perm for user to change user_type for user_modified Parameters ---------- user : User args : Dict(user_modified, to_user_type) """ user_modified = args[0]["user_modified"] to_user_type = args[0]["to_user_type"] if user.is_client or user.is_professional: return False if user_modified.is_client or user_modified.is_professional: return False if to_user_type == "client" or to_user_type == "professional": return False if user.is_administrator: return True if user.is_manager: if ( user_modified.is_advisor or user_modified.is_superadvisor or user_modified.is_manager and user_modified.group.is_member(user) ): if to_user_type in ["advisor", "superadvisor", "manager"]: return True if ( user.is_superadvisor and to_user_type in ["advisor", "superadvisor"] and user_modified.is_advisor ): return True return self.admin_permission(user, user_modified, *args) register("user", UserPermissionLogic) register("accounts/user", UserPermissionLogic) class RgpdConsentPermissionLogic(BasicPermissionLogicMixin, PermissionLogic): def view(self, user, rgpdconsent, *args): if rgpdconsent.user == user: return True return self.admin_permission(user, rgpdconsent, *args) change = view register("rgpdconsent", RgpdConsentPermissionLogic) register("accounts/rgpdconsent", RgpdConsentPermissionLogic) class GroupPermissionLogic(BasicPermissionLogicMixin, PermissionLogic): def view(self, user, group, *args): if user.is_anonymous: return False if user.is_administrator: return True if user.is_advisor or user.is_manager: return True return self.admin_permission(user, group, *args) def create(self, user, group, group_data, *args): if user.is_anonymous: return False if user.is_administrator: return True if user.is_manager: if not group_data: return False if user.group is not None: if group is not None: if group.admin_group.pk == user.group.pk: return True return self.admin_permission(user, None, *args) def change(self, user, group, *args): if user.is_anonymous: return False if user.is_administrator: return True if ( user.is_manager and user.group is not None and group.admin_group == user.group ): return True return self.admin_permission(user, group, *args) def partial_change(self, user, group, *args): """ change only some fiels on group """ if user.is_advisor and user.group is not None and group == user.group: return True return self.admin_permission(user, group, *args) register("group", GroupPermissionLogic) register("accounts/group", GroupPermissionLogic) class GroupPlacePermissionLogic(BasicPermissionLogicMixin, PermissionLogic): def view(self, user, group, *args): if user.is_anonymous: return False if user.is_expert: return True return self.admin_permission(user, group, *args) register("group_place", GroupPlacePermissionLogic) register("accounts/group_place", GroupPlacePermissionLogic)
aacc12eabb0b4eb5e62e7da5668c3ba88bb40c61
2f5797309b741938dca213353f042c77825b0936
/server_run.py
35559759cb860a0476b02c5e749109bf2aeb1303
[]
no_license
electramite/RPi_dashboard
0def396c04ea99a5f8345363e37ffd421dad8067
02cb5a959e9ad86e15184283602b10407264cba7
refs/heads/main
2022-12-30T13:44:01.199658
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2020-10-20T08:36:06
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from flask import render_template, url_for, request import RPi.GPIO as GPIO import time GPIO.setwarnings(False) GPIO.setmode(GPIO.BCM) trig = 17 echo = 27 GPIO.setup(trig, GPIO.OUT) GPIO.setup(echo, GPIO.IN) from flask import Flask app = Flask(__name__) @app.route('/') def index(): distance = sensor_1() return render_template("sensor.html", distance=distance) def sensor_1(): GPIO.output(trig, True) time.sleep(0.00001) GPIO.output(trig, False) while GPIO.input(echo)==0: pulse_s = time.time() while GPIO.input(echo)==1: pulse_e = time.time() pulse_d = pulse_e - pulse_s d = 34000*pulse_d/2 return int(d) if __name__ == "__main__": app.run(host = '0.0.0.0',port=4556,debug=True)
03692f50ed9e909b7858f410645b5c90ff1c95ed
c385a69705301f50b45d46f71b808654d7450ad6
/python_wheel/lbj_db/lbj_db/entity/ret_find.py
23bc1de9ae084c4d4a0213afab1b5e780b3032c5
[]
no_license
libaojie/python_package
c411c60c84be1f42221f98c5f140486dc5508b21
4bb0ab793c119153e9ee476274d8908c23e33a30
refs/heads/master
2023-05-26T12:23:07.226332
2023-05-22T06:19:06
2023-05-22T06:19:06
159,101,700
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2023-02-16T06:52:26
2018-11-26T03:00:49
Python
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py
#!/usr/bin/env python # -*- coding: utf-8 -*- """ @Comment : 查询sql列表结果 @Time : 2020/02/08 20:47 @Author : libaojie @File : ret_find.py @Software : PyCharm """ class RetFind(object): """ 查询列表结果 """ def __init__(self): self._page_size = None # 当前页面 self._page_num = None # 每页数量 self._page_total = None # 一共页数 self._total = None # 数据总量 self._data = None # 数据列表 @property def page_size(self): """ 当前页面 :return: """ return self._page_size @page_size.setter def page_size(self, _page_size): self._page_size = _page_size @property def page_num(self): """ 每页数量 :return: """ return self._page_num @page_num.setter def page_num(self, _page_num): self._page_num = _page_num @property def page_total(self): """ 一共页数 :return: """ return self._page_total @page_total.setter def page_total(self, _page_total): self._page_total = _page_total @property def data(self): """ 数据列表 :return: """ return self._data @data.setter def data(self, _data): self._data = _data @property def total(self): """ 数据总数量 :return: """ return self._total @total.setter def total(self, _total): self._total = _total
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6d26b320905ba93ee02f9ba95a76b3839ae3e2c1
/archinstaller.py
e09ce0bff0dab7b10df5c2841484901e01a5e273
[]
no_license
accountDBBackup/arch
3ecfb39adce321e5874a8963e4c9c923c7d4848e
3c6d51198746e5bbc769055223297abbeae4e334
refs/heads/main
2023-07-06T20:34:36.264595
2021-08-05T21:13:04
2021-08-05T21:13:04
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py
import os import subprocess import fileinput import pwd import afterchroot def welcome(): print("Welcome to to the Arch Installer!") system_clock_sync = "timedatectl set-ntp true" print(f"Running `{system_clock_sync}` command to sync the system clock!") subprocess.run(system_clock_sync, shell=True) def format_disks(): pass def mount_partitions(): pass def update_mirrors(): print("Refreshing mirrorlist...") subprocess.run( "reflector --latest 30 --sort rate --save /etc/pacman.d/mirrorlist", shell=True) def install_arch_essentails(): kernels = ["linux", "linux-lts", "linux linux-lts"] while not ((choice := input("\t(1) linux\n\t(2) linux-lts\n\t(3) both\nChose a kernel: ")) in [1, 2, 3]): pass choice = int(choice) print(f"Installing: {kernels[choice-1].replace(' ', ' and ')}") subprocess.run( f"pacstrap /mnt base {kernels[choice -1]} linux-firmware git python", shell=True) def generate_fstab(): subprocess.run("genfstab -U /mnt >> /mnt/etc/fstab", shell=True) def chroot(): subprocess.run("arch-chroot /mnt /bin/bash", shell=True) def main(): afterchroot.main() if __name__ == "__main__": main()
f0704c277601046e7ecff140c4ce76723f895a6f
e6dab5aa1754ff13755a1f74a28a201681ab7e1c
/.parts/lib/python2.7/test/outstanding_bugs.py
5a947e5deea9d551dd5f2994869ab7dd70a83e94
[]
no_license
ronkagan/Euler_1
67679203a9510147320f7c6513eefd391630703e
022633cc298475c4f3fd0c6e2bde4f4728713995
refs/heads/master
2021-01-06T20:45:52.901025
2014-09-06T22:34:16
2014-09-06T22:34:16
23,744,842
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Python
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py
/home/action/.parts/packages/python2/2.7.6/lib/python2.7/test/outstanding_bugs.py
abe1990e419bae2b1a5e5c3b386ec31e385780da
679bf42c14ef2b7ea5d682ad6f1ffc6e488028c0
/server_tcp.py
1b23cfc1e10d15eb48863613e93cb0d2bb774fa0
[]
no_license
pers9727/lrs_protocol
0b67086adbcaae271037989fd3e28667f30b72bc
330d758fc3d7546709e15714a0a303a8320d1f8e
refs/heads/master
2023-02-05T03:41:57.031536
2020-12-28T12:08:54
2020-12-28T12:08:54
324,732,792
1
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UTF-8
Python
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py
import socket import threading from _thread import * import pickle import os import work_with_files module_file = '/home/roman/lrs_protocol/module_information/' commands_file = '/home/roman/lrs_protocol/commands.txt' ip_type_file = f'{os.getcwd()}/ip_type.txt' print_lock = threading.Lock() port = 65432 def threaded(conn, ip_addr): ip_family = '10.42.43.' conn.send(pickle.dumps('0')) module_data = f'{module_file}{ip_addr[len(ip_family):]}.txt' while True: # Get data from client data_to_receive = conn.recv(4096) # If data is None -> close connection if not data_to_receive: print('[LOG] Connection closed') print_lock.release() break # Data is getting else: # Write new data to new_data new_data = pickle.loads(data_to_receive) # Write ip_type to ip_type_data ip_type_data = f'{ip_addr} {new_data[0]}' if ip_type_data not in list(ip_type_file): work_with_files.write(ip_type_file, ip_type_data, 'a') # Write commands to file and check if command in file continue, else write for i in new_data[2]: if '\n' in i: if i[:-1] in list('/home/pi/lrs_protocol/commands.txt'): continue else: work_with_files.write(commands_file, str(i[:-1]) + '\n', 'a') else: if i in list('/home/pi/lrs_protocol/commands.txt'): continue else: work_with_files.write(commands_file, str(i) + '\n', 'a') # Write new_data to .txt file for new module for i in new_data: work_with_files.write(module_data, str(i) + '\n', 'a') # Create file with ip_type list of modules ''' if os.path.exists(ip_type_file) and os.stat(ip_type_file).st_size > 0: work_with_files.write(ip_type_file, ip_type_data, 'a') else: work_with_files.write(ip_type_file, ip_type_data, 'w')''' conn.close() def main_client(port): host = '' sock = socket.socket(socket.AF_INET, socket.SOCK_STREAM) sock.setsockopt(socket.SOL_SOCKET, socket.SO_REUSEADDR, 1) print("[LOG] Socket created") try: sock.bind((host, port)) except socket.error as msg: print("[LOG] ", msg) print("[LOG] Socket binded to port: ", port) sock.listen(5) while True: conn, addr = sock.accept() print_lock.acquire() print('[LOG] Connected with client: ', addr[0]) start_new_thread(threaded, (conn, addr[0])) if __name__ == '__main__': try: main_client(port) except KeyboardInterrupt: print('[LOG] Server stopped! Exit from protocol') exit()
2d800fba44b77304483de1a550b1a877daeeda5d
fe61c7ac89c2a486066d36bdc99b70c3a7098e59
/Message.py
1bbc1d8e16a6b71e8ede7e0835d3272922516cdc
[]
no_license
figarodoe/MauMau
9f149508a1b504c88847a2b5da5fa495fd01a09c
592bb1c6339735383a639a9c4e333e491fb2f611
refs/heads/master
2021-01-12T02:22:04.037120
2017-01-10T06:46:58
2017-01-10T06:46:58
null
0
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null
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UTF-8
Python
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'''Markup but not''' def Clear(): import os from sys import platform if platform == "win32": os.system('cls') # For Windows else: os.system('clear') # For Linux/OS X
0eab4d6b9baf06f0c6515a1c93b578c02de52a07
ce68ff8c06a47cb5a26dce7f42f5a80c35ef5409
/06-Faces/detection.py
70a971742b20deba4af9dda6be9a17a70b01ce43
[]
no_license
lyukov/computer_vision_intro
9421062c0ad77ab96b2c79e5879744b78f4c0c54
008ed8705bd98259691110413579a5afd87e0ab5
refs/heads/master
2022-03-27T05:50:18.456057
2019-12-17T12:02:20
2019-12-17T12:02:20
225,220,873
0
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from skimage.io import imread, imshow import numpy as np import pandas as pd import os from skimage.transform import resize from skimage import img_as_float from keras.layers import Convolution2D, MaxPooling2D from keras.layers import Dense, Activation, Flatten, Dropout from keras.models import Sequential from keras.optimizers import Adam import keras def normalize(img): img -= img.mean() img /= np.sqrt((img**2).mean()) def prepare_img(image, tg_size): img = resize(image, (tg_size, tg_size)) if len(img.shape) == 2: normalize(img) return np.array([img, img, img]).transpose((1,2,0)) else: for i in range(img.shape[2]): normalize(img[:,:,i]) return img def get_data_shapes_filenames(directory, tg_size=128): filenames = sorted(os.listdir(directory)) result = np.zeros((len(filenames), tg_size, tg_size, 3)) shapes = np.zeros((len(filenames), 2)) for i, filename in enumerate(filenames): file_path = os.path.join(directory, filename) img = img_as_float(imread(file_path)) prepared = prepare_img(img, tg_size) result[i] = prepared shapes[i] = img.shape[:2] return result, shapes, filenames def train_detector(train_gt, train_img_dir, fast_train=True): y = pd.DataFrame(train_gt).transpose().values data, shapes, filenames = get_data_shapes_filenames(train_img_dir) model = Sequential([ Convolution2D( 64, (3, 3), activation='relu', input_shape=(128, 128, 3), kernel_initializer='normal'), MaxPooling2D( pool_size=(2,2), strides=(2,2)), Convolution2D( 128, (3, 3), activation='relu', kernel_initializer='normal'), MaxPooling2D( pool_size=(2,2), strides=(2,2)), Convolution2D( 256, (3, 3), activation='relu', kernel_initializer='normal'), MaxPooling2D( pool_size=(2,2), strides=(2,2)), Flatten(), Dense(64, activation='relu'), Dropout(0.25), Dense(28) ]) adam = Adam(lr=0.0003) model.compile(loss='mean_squared_error', optimizer=adam, metrics=['mean_absolute_error']) model.fit(data, y, epochs=1) return model # returns dict: {filename -> [number]} def detect(model, test_img_dir): data, shapes, filenames = get_data_shapes_filenames(test_img_dir) answers = [] batch_size = 500 for i in range((len(data) + batch_size - 1) // batch_size): answers.extend(model.predict(data[i*batch_size : min((i+1)*batch_size, len(data))])) return {filenames[i] : answers[i] * shapes[i, 0] for i in range(len(filenames))}
e79168b08e0286fa92b3cb329528a55e4ca1e1de
94d653498dc75690b847df9f560ee75a1cb177d5
/calculator.py
50f1e373bc4efee1b8e9fea4a26efd6d5b10ca1b
[]
no_license
weelis/shiyanlouplus
28bf09eb422ab1cb73b363ce6df4b36f945ed124
9ba7b9006221d017656670e620d12b1f4c2909fc
refs/heads/master
2020-04-27T23:36:07.823231
2019-03-10T06:45:56
2019-03-10T06:45:56
174,782,254
0
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UTF-8
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py
#!/usr/bin/env python3 import sys try: salary = int(sys.argv[1]) salary_tax = salary - 3500 if salary_tax <= 1500: tax = salary_tax * 0.03 elif salary_tax > 1500 and salary_tax <= 4500: tax = salary_tax * 0.1 - 105 elif salary_tax > 4500 and salary_tax <= 9000: tax = salary_tax * 0.2 - 555 elif salary_tax > 9000 and salary_tax <= 35000: tax = salary_tax * 0.25 - 1005 elif salary_tax > 35000 and salary <= 55000: tax = salary_tax * 0.3 - 2755 elif salary_tax > 55000 and salary <= 80000: tax = salary_tax * 0.35 - 5505 else: tax = salary_tax * 0.45 - 13505 print(format(tax, ".2f")) except: print("Parameter Error")
a6d93d5e249b23f47e659301e4c8403aef94ee45
63f1c3161651ba76434ef241eed933788a0836c5
/autorally/autorally_core/src/chronyStatus/chronyStatus.py
0fda2de26ce3e42f0713501d7722d321a597a7cd
[]
no_license
27Apoorva/RBE502Project
0bd64706a5ff26cb791c11eff96d75bd41e024be
056330cd91667a3eeceddb668672cf4e5e2bc3cd
refs/heads/master
2021-08-30T04:30:09.326153
2017-12-13T04:00:38
2017-12-13T04:00:38
112,425,430
1
0
null
2017-12-16T01:50:43
2017-11-29T04:13:25
Makefile
UTF-8
Python
false
false
5,012
py
#!/usr/bin/env python # Software License Agreement (BSD License) # Copyright (c) 2016, Georgia Institute of Technology # All rights reserved. # # Redistribution and use in source and binary forms, with or without # modification, are permitted provided that the following conditions are met: # # 1. Redistributions of source code must retain the above copyright notice, this # list of conditions and the following disclaimer. # 2. Redistributions in binary form must reproduce the above copyright notice, # this list of conditions and the following disclaimer in the documentation # and/or other materials provided with the distribution. # # THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" # AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE # IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE # DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE # FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL # DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR # SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER # CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, # OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE # OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. """ @package chronyStatus Acquires and publishes to /diagnostics the current state of chrony time sychronization and information about available timesyn sources. On startup the node verifies that the installed version of chrony is at least chronyMinVersion. """ import os import socket import rospy import commands from diagnostic_msgs.msg import DiagnosticArray, DiagnosticStatus, KeyValue from subprocess import check_output import subprocess """ @return chrony version number, if available Get current chrony version number by using chronyc interface """ def checkChronyVersion(): try: versionText = check_output("chronyc -v", shell=True); lines = versionText.split(' ') if lines[2] == 'version': return lines[3] except subprocess.CalledProcessError as e: rospy.logerr('chronyStatus: subprocess error:' + e.output) except ValueError: rospy.logerr('chrony version check failed, version unkown') """ @param status the diganostic array to add information to Queries and adds to diganostics the current tracking status of chronyd using chronyc """ def getTracking(status): try: trackingText = check_output("chronyc tracking", shell=True); for line in trackingText.split('\n'): if len(line): #split on first : to separate data field name from value because some values can have : in them info = line.split(':', 1) status.values.append(KeyValue(key=info[0], value=info[1])) except subprocess.CalledProcessError as e: rospy.logerr(e.output) status.values.append(KeyValue(key=e.output, value=chr(2))) """ @param status the diganostic array to add information to Queries and adds to diagnostics the current sources information from chronyd using chronyc """ def getSources(status): try: sourcesText = check_output("chronyc sources", shell=True); lines = sourcesText.split('\n') status.level = 1 for line in lines[3:]: if len(line): tok = line.split() text = 'ModeState:' + tok[0] + ' Stratum:' + tok[2] + ' Poll:' + tok[3] + ' Reach:' + tok[4] +\ ' LastRx:' + tok[5] + ' Last Sample:' + ''.join(tok[6:]) status.values.append(KeyValue(key='source '+tok[1], value=text)) #M = tok[0][0] #S = tok[0][1] #all is good if we are synchronizing to a source if tok[0][1] == '*': status.level = 0 #print M, S except subprocess.CalledProcessError as e: rospy.logerr(e.output) status.values.append(KeyValue(key=e.output, value=chr(2))) if __name__ == '__main__': hostname = socket.gethostname() rospy.init_node('chronyStatus_'+hostname) pub = rospy.Publisher('/diagnostics', DiagnosticArray, queue_size=1, latch=True) array = DiagnosticArray() status = DiagnosticStatus(name='ChronyStatus',\ level=0,\ hardware_id=hostname) array.status = [status] rate = rospy.Rate(0.2) # query and publish chrony information once every 5 seconds chronyVersion = checkChronyVersion() #chronyMinVersion = 1.29 #publish error and exit if chronyMinVersion is not satisfied #if chronyVersion < chronyMinVersion: # rospy.logerr('ChronyStatus requires chrony version ' + str(chronyMinVersion) + \ # ' or greater, version ' + str(chronyVersion) + ' detected, exiting') #else: while not rospy.is_shutdown(): status.values = [] status.values.append(KeyValue(key='chrony version', value=chronyVersion) ) getTracking(status) getSources(status) pub.publish(array) rate.sleep()
d19d3271cd6125027f3d50770dd7a814ce0ebf43
af9d2aa777f9a311f309f1036ebc141e7f936c2f
/core/migrations/0002_auto_20200929_1344.py
fc83f09aaa626ed540f263173034c781930cf548
[]
no_license
oopaze/testes-unitarios-django
d20c0de8f565c2f0e3f557159af8a6912d401fc9
1b31b9cfa3641ffa4cf5dcc1d9fb8299c9b27734
refs/heads/master
2022-12-24T13:32:36.460162
2020-10-07T04:50:37
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301,927,563
0
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null
2020-10-07T04:50:38
2020-10-07T04:35:34
Python
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Python
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py
# Generated by Django 3.1.1 on 2020-09-29 13:44 from django.db import migrations class Migration(migrations.Migration): dependencies = [ ('core', '0001_initial'), ] operations = [ migrations.RenameField( model_name='sorvete', old_name='unidade', new_name='unidades', ), ]
1670cf15584af1d803a46c989f7bbbd0b31521a2
acb8eb49908d0d8417dfd08ddb5340f938d34214
/pretrain_data/aliagn_trained_vecs.py
f066a1d3594f355d74784e4b76da16e720f71a8b
[]
no_license
zhuxiangru/multimudal-bert
11577b783150754ff3e01bd03d915f51a7407ec2
ef05fccb2315a6feaadab5f162a72a105f06092a
refs/heads/master
2022-10-31T02:34:53.874507
2020-06-15T09:23:27
2020-06-15T09:23:27
268,139,353
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1
null
null
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UTF-8
Python
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import sys from urllib import parse import os import json from multiprocessing import Pool import html5lib import time import re def get_entity_id_dict(infilename): entity2id_dict = {} index = 0 with open(infilename, "r", encoding = "utf-8") as infile: for line in infile: line_list = line.strip().split() if line_list[0] not in entity2id_dict: entity2id_dict[line_list[0]] = None return entity2id_dict def generate_alias_entity2index_file(entity2id_dict, alias_entity_file, \ output_alias_name2uri_file, output_alias_uri2index_file, type_option = ""): index = -1 with open(output_alias_name2uri_file, "w", encoding = "utf-8") as output_name2uri_file: with open(output_alias_uri2index_file, "w", encoding = "utf-8") as output_uri2index_file: with open(alias_entity_file, "r", encoding = "utf-8") as infile: for line in infile: index += 1 if index == 0: continue line_list = line.strip().split() if line_list[0] in entity2id_dict: output_name2uri_file.write("%s\t%s%s\n" % (line_list[0], type_option, str(index))) output_uri2index_file.write("%s%s\t%s\n" % (type_option, str(index), str(index - 1))) if __name__ == '__main__': if len(sys.argv) < 6: print ("Usage: python3 aliagn_trained_vecs.py all_entity2id_infilename alias_entity_file output_name2uri_file output_uri2index_file type_option") exit(0) all_entity2id_infilename = sys.argv[1] alias_entity_file = sys.argv[2] output_name2uri_file = sys.argv[3] output_uri2index_file = sys.argv[4] type_option = sys.argv[5] if type_option == "entity": type_option = "Q" elif type_option == "image": type_option = "I" else: type_option = "" all_entity2id_dict = get_entity_id_dict(all_entity2id_infilename) generate_alias_entity2index_file(all_entity2id_dict, alias_entity_file, \ output_name2uri_file, output_uri2index_file, type_option)
cccb674d3a60d939b4eefbb72d10130d2db2932b
96d14f70deb5164e294475402ef50f6e39712a1c
/ex27.py
3483e6dea39c2be6c4ec4c23d9e6292bed2e1cf0
[]
no_license
jagdishrenuke/Project_python
bafc1b4cf058d36a990c9b4857b0cd635492d919
79284d5f6f05c24aff7181c53c8d8318739f86db
refs/heads/master
2020-04-23T12:22:55.461500
2015-03-16T17:25:03
2015-03-16T17:25:03
32,340,875
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0
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py
ten_things = "apple orange crows telephone light sugar" print "wait there are not 10 things in that list." stuff = ten_things.split(' ') more_stuff = ["day","night","song","girl","frisbee","cool","banana","boy"] while len(stuff) != 10: next_one = more_stuff.pop() print "Adding: ",next_one stuff.append(next_one) print "there are %d items now." % len(stuff) print "We have : ",stuff print "Let's do something with the stuff..." print stuff[1] print stuff[-1] print stuff.pop() print ' '.join(stuff) print '#'.join(stuff[3:5])
c5599204c2088d413cd3a990459617d0b80417da
cefa2d235896b31f84456160787eebf55f3ccc84
/Generate_code.py
180024b5ee42331eefcc14afe34458337c3410be
[]
no_license
Unbeaten123/Take-others-as-mine
eaebb4bd5595a81183a106a3968fc235955e8998
26227cd558b52259dce45fb7d586a5fe172c44aa
refs/heads/master
2021-01-10T15:20:53.147238
2016-04-27T14:55:21
2016-04-27T14:55:21
53,040,946
0
0
null
2016-04-04T06:06:12
2016-03-03T10:13:29
JavaScript
UTF-8
Python
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720
py
from elaphe import barcode def get_code39(info): bc = barcode('code39', info, options=dict(includetext=True), scale=3, margin=10) bc.save('code39.png', quality=95) def get_QRcode(info): bc = barcode('QRcode', info, options=dict(version=9, eclevel='M'), margin=10, scale=5) bc.save('QRcode.png', quality=95) choice = raw_input('''Choose what kind of code you want to generate(input a number): 1.Code39 2.QRcode ''') info = raw_input("Input a string that you want to generate: ") if int(choice)==1: try: get_code39(info) print "Done!" except: print "Error occurred!" else: try: get_QRcode(info) print "Done!" except: print "Error occurred!"
b3fb5072be2c9803b039ffc66f3bf3a06a4247b1
4755dabdcff6a45b9c15bf9ea814c6b8037874bd
/devel/lib/python2.7/dist-packages/snakebot_position_control/msg/__init__.py
7e50b3d802aa4cf5d4063bde91254d3fba75ff3c
[]
no_license
Rallstad/RobotSnake
676a97bdfde0699736d613e73d539929a0c2b492
37ee6d5af0458b855acf7c2b83e0ee17833dbfd1
refs/heads/master
2023-01-03T05:46:46.268422
2018-05-27T16:01:47
2018-05-27T16:01:47
308,665,980
2
0
null
null
null
null
UTF-8
Python
false
false
38
py
from ._PositionControlEffort import *
976cddf10f6864ba5c9a7a761545d47337c3af20
4789ee577801e55bb6209345df6ddd1adff58aa9
/skyline/boundary/boundary_alerters.py
0f63c5c74e6d30f89ea03ffca79842f2fafdab45
[ "MIT" ]
permissive
bastienboutonnet/skyline
76767fdad5eb9b9ee9bb65bfcee05e2551061fbe
7f19fcc7ac1177b4a0a4663d6e645be63ceea452
refs/heads/master
2023-04-25T01:57:17.955874
2021-04-11T09:20:30
2021-04-11T09:20:30
null
0
0
null
null
null
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UTF-8
Python
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from __future__ import division import logging import traceback # @modified 20201207 - Task #3878: Add metric_trigger and alert_threshold to Boundary alerts # hashlib not used # import hashlib from smtplib import SMTP # @added 20200122: Feature #3396: http_alerter from ast import literal_eval import requests import boundary_alerters try: import urllib2 except ImportError: import urllib.request import urllib.error # @added 20191023 - Task #3290: Handle urllib2 in py3 # Branch #3262: py3 # Use urlretrieve try: import urllib2 as urllib except ImportError: from urllib import request as urllib import re from requests.utils import quote from time import time import datetime import os.path import sys # @added 20181126 - Task #2742: Update Boundary # Feature #2618: alert_slack # Added dt, redis, gmtime and strftime import datetime as dt # import redis from time import (gmtime, strftime) # @added 20201127 - Feature #3820: HORIZON_SHARDS from os import uname python_version = int(sys.version_info[0]) # @modified 20201207 - Task #3878: Add metric_trigger and alert_threshold to Boundary alerts # charset no longer used # from email import charset if python_version == 2: from email.MIMEMultipart import MIMEMultipart from email.MIMEText import MIMEText from email.MIMEImage import MIMEImage if python_version == 3: from email.mime.multipart import MIMEMultipart from email.mime.text import MIMEText from email.mime.image import MIMEImage sys.path.append(os.path.join(os.path.dirname(os.path.realpath(__file__)), os.pardir)) sys.path.insert(0, os.path.dirname(__file__)) if True: import settings # @added 20181126 - Task #2742: Update Boundary # Feature #2034: analyse_derivatives # Feature #2618: alert_slack from skyline_functions import ( write_data_to_file, in_list, is_derivative_metric, get_graphite_graph_image, # @added 20191030 - Bug #3266: py3 Redis binary objects not strings # Branch #3262: py3 # Added a single functions to deal with Redis connection and the # charset='utf-8', decode_responses=True arguments required in py3 get_redis_conn_decoded, # @modified 20191105 - Branch #3002: docker # Branch #3262: py3 get_graphite_port, get_graphite_render_uri, get_graphite_custom_headers, # @added 20200122: Feature #3396: http_alerter get_redis_conn, # @added 20200825 - Feature #3704: Add alert to anomalies add_panorama_alert, # @added 20201013 - Feature #3780: skyline_functions - sanitise_graphite_url encode_graphite_metric_name) # @added 20201127 - Feature #3820: HORIZON_SHARDS try: HORIZON_SHARDS = settings.HORIZON_SHARDS.copy() except: HORIZON_SHARDS = {} this_host = str(uname()[1]) HORIZON_SHARD = 0 if HORIZON_SHARDS: HORIZON_SHARD = HORIZON_SHARDS[this_host] skyline_app = 'boundary' skyline_app_logger = '%sLog' % skyline_app logger = logging.getLogger(skyline_app_logger) skyline_app_logfile = '%s/%s.log' % (settings.LOG_PATH, skyline_app) """ Create any alerter you want here. The function is invoked from trigger_alert. 7 arguments will be passed in as strings: alerter, datapoint, metric_name, expiration_time, metric_trigger, algorithm, metric_timestamp """ # FULL_DURATION to hours so that Boundary surfaces the relevant timeseries data # in the graph try: full_duration_seconds = int(settings.FULL_DURATION) except: full_duration_seconds = 86400 full_duration_in_hours = full_duration_seconds / 60 / 60 try: graphite_previous_hours = int(settings.BOUNDARY_SMTP_OPTS['graphite_previous_hours']) except: graphite_previous_hours = full_duration_in_hours try: graphite_graph_line_color = int(settings.BOUNDARY_SMTP_OPTS['graphite_graph_line_color']) except: graphite_graph_line_color = 'pink' # @added 20200122 - Branch #3002: docker try: DOCKER_FAKE_EMAIL_ALERTS = settings.DOCKER_FAKE_EMAIL_ALERTS except: DOCKER_FAKE_EMAIL_ALERTS = False def alert_smtp(datapoint, metric_name, expiration_time, metric_trigger, algorithm, metric_timestamp, alert_threshold): sender = settings.BOUNDARY_SMTP_OPTS['sender'] matched_namespaces = [] for namespace in settings.BOUNDARY_SMTP_OPTS['recipients']: CHECK_MATCH_PATTERN = namespace check_match_pattern = re.compile(CHECK_MATCH_PATTERN) pattern_match = check_match_pattern.match(metric_name) if pattern_match: matched_namespaces.append(namespace) matched_recipients = [] for namespace in matched_namespaces: for recipients in settings.BOUNDARY_SMTP_OPTS['recipients'][namespace]: matched_recipients.append(recipients) def unique_noHash(seq): seen = set() return [x for x in seq if str(x) not in seen and not seen.add(str(x))] recipients = unique_noHash(matched_recipients) # Backwards compatibility if type(recipients) is str: recipients = [recipients] # @added 20180524 - Task #2384: Change alerters to cc other recipients # The alerters did send an individual email to each recipient. This would be # more useful if one email was sent with the first smtp recipient being the # to recipient and the subsequent recipients were add in cc. primary_recipient = False cc_recipients = False if recipients: for i_recipient in recipients: if not primary_recipient: primary_recipient = str(i_recipient) if primary_recipient != i_recipient: if not cc_recipients: cc_recipients = str(i_recipient) else: new_cc_recipients = '%s,%s' % (str(cc_recipients), str(i_recipient)) cc_recipients = str(new_cc_recipients) logger.info( 'alert_smtp - will send to primary_recipient :: %s, cc_recipients :: %s' % (str(primary_recipient), str(cc_recipients))) alert_algo = str(algorithm) alert_context = alert_algo.upper() # @added 20191008 - Feature #3194: Add CUSTOM_ALERT_OPTS to settings try: main_alert_title = settings.CUSTOM_ALERT_OPTS['main_alert_title'] except: main_alert_title = 'Skyline' try: app_alert_context = settings.CUSTOM_ALERT_OPTS['boundary_alert_heading'] except: app_alert_context = 'Boundary' # @modified 20191002 - Feature #3194: Add CUSTOM_ALERT_OPTS to settings # Use alert_context # unencoded_graph_title = 'Skyline Boundary - %s at %s hours - %s - %s' % ( # alert_context, graphite_previous_hours, metric_name, datapoint) # @modified 20201207 - Task #3878: Add metric_trigger and alert_threshold to Boundary alerts # unencoded_graph_title = '%s %s - %s at %s hours - %s - %s' % ( # main_alert_title, app_alert_context, alert_context, graphite_previous_hours, metric_name, datapoint) unencoded_graph_title = '%s %s - %s %s %s times - %s' % ( main_alert_title, app_alert_context, alert_context, str(metric_trigger), str(alert_threshold), str(datapoint)) # @added 20181126 - Task #2742: Update Boundary # Feature #2034: analyse_derivatives # Added deriative functions to convert the values of metrics strictly # increasing monotonically to their deriative products in alert graphs and # specify it in the graph_title known_derivative_metric = False try: # @modified 20180519 - Feature #2378: Add redis auth to Skyline and rebrow # @modified 20191030 - Bug #3266: py3 Redis binary objects not strings # Branch #3262: py3 # Use get_redis_conn_decoded # if settings.REDIS_PASSWORD: # # @modified 20191022 - Bug #3266: py3 Redis binary objects not strings # # Branch #3262: py3 # # REDIS_ALERTER_CONN = redis.StrictRedis(password=settings.REDIS_PASSWORD, unix_socket_path=settings.REDIS_SOCKET_PATH) # REDIS_ALERTER_CONN = redis.StrictRedis(password=settings.REDIS_PASSWORD, unix_socket_path=settings.REDIS_SOCKET_PATH, charset='utf-8', decode_responses=True) # else: # # REDIS_ALERTER_CONN = redis.StrictRedis(unix_socket_path=settings.REDIS_SOCKET_PATH) # REDIS_ALERTER_CONN = redis.StrictRedis(unix_socket_path=settings.REDIS_SOCKET_PATH, charset='utf-8', decode_responses=True) REDIS_ALERTER_CONN = get_redis_conn_decoded(skyline_app) except: logger.error('error :: alert_smtp - redis connection failed') # @modified 20191022 - Bug #3266: py3 Redis binary objects not strings # Branch #3262: py3 try: derivative_metrics = list(REDIS_ALERTER_CONN.smembers('derivative_metrics')) except: derivative_metrics = [] redis_metric_name = '%s%s' % (settings.FULL_NAMESPACE, str(metric_name)) if redis_metric_name in derivative_metrics: known_derivative_metric = True if known_derivative_metric: try: non_derivative_monotonic_metrics = settings.NON_DERIVATIVE_MONOTONIC_METRICS except: non_derivative_monotonic_metrics = [] skip_derivative = in_list(redis_metric_name, non_derivative_monotonic_metrics) if skip_derivative: known_derivative_metric = False known_derivative_metric = is_derivative_metric(skyline_app, metric_name) if known_derivative_metric: # @modified 20191002 - Feature #3194: Add CUSTOM_ALERT_OPTS to settings # unencoded_graph_title = 'Skyline Boundary - %s at %s hours - derivative graph - %s - %s' % ( # alert_context, graphite_previous_hours, metric_name, datapoint) # @modified 20201207 - Task #3878: Add metric_trigger and alert_threshold to Boundary alerts # unencoded_graph_title = '%s %s - %s at %s hours - derivative graph - %s - %s' % ( # main_alert_title, app_alert_context, alert_context, graphite_previous_hours, metric_name, datapoint) unencoded_graph_title = '%s %s - %s %s %s times - derivative graph - %s' % ( main_alert_title, app_alert_context, alert_context, str(metric_trigger), str(alert_threshold), str(datapoint)) graph_title_string = quote(unencoded_graph_title, safe='') graph_title = '&title=%s' % graph_title_string # @added 20181126 - Bug #2498: Incorrect scale in some graphs # Task #2742: Update Boundary # If -xhours is used the scale is incorrect if x hours > than first # retention period, passing from and until renders the graph with the # correct scale. graphite_port = '80' if settings.GRAPHITE_PORT != '': graphite_port = str(settings.GRAPHITE_PORT) until_timestamp = int(time()) from_seconds_ago = graphite_previous_hours * 3600 from_timestamp = until_timestamp - from_seconds_ago graphite_from = dt.datetime.fromtimestamp(int(from_timestamp)).strftime('%H:%M_%Y%m%d') logger.info('graphite_from - %s' % str(graphite_from)) graphite_until = dt.datetime.fromtimestamp(int(until_timestamp)).strftime('%H:%M_%Y%m%d') logger.info('graphite_until - %s' % str(graphite_until)) # @modified 20191022 - Task #3294: py3 - handle system parameter in Graphite cactiStyle # graphite_target = 'target=cactiStyle(%s)' # @added 20201013 - Feature #3780: skyline_functions - sanitise_graphite_url encoded_graphite_metric_name = encode_graphite_metric_name(skyline_app, metric_name) # @modified 20201013 - Feature #3780: skyline_functions - sanitise_graphite_url # graphite_target = 'target=cactiStyle(%s,%%27si%%27)' % metric_name graphite_target = 'target=cactiStyle(%s,%%27si%%27)' % encoded_graphite_metric_name if known_derivative_metric: # @modified 20191022 - Task #3294: py3 - handle system parameter in Graphite cactiStyle # graphite_target = 'target=cactiStyle(nonNegativeDerivative(%s))' # @modified 20201013 - Feature #3780: skyline_functions - sanitise_graphite_url # graphite_target = 'target=cactiStyle(nonNegativeDerivative(%s),%%27si%%27)' % metric_name graphite_target = 'target=cactiStyle(nonNegativeDerivative(%s),%%27si%%27)' % encoded_graphite_metric_name # @modified 20190520 - Branch #3002: docker # Use GRAPHITE_RENDER_URI # link = '%s://%s:%s/render/?from=%s&until=%s&%s%s%s&colorList=%s' % ( # settings.GRAPHITE_PROTOCOL, settings.GRAPHITE_HOST, graphite_port, # str(graphite_from), str(graphite_until), graphite_target, # settings.GRAPHITE_GRAPH_SETTINGS, graph_title, # graphite_graph_line_color) link = '%s://%s:%s/%s/?from=%s&until=%s&%s%s%s&colorList=%s' % ( settings.GRAPHITE_PROTOCOL, settings.GRAPHITE_HOST, graphite_port, settings.GRAPHITE_RENDER_URI, str(graphite_from), str(graphite_until), graphite_target, settings.GRAPHITE_GRAPH_SETTINGS, graph_title, graphite_graph_line_color) content_id = metric_name image_data = None image_file = '%s/%s.%s.%s.alert_smtp.png' % ( settings.SKYLINE_TMP_DIR, skyline_app, str(until_timestamp), metric_name) if settings.BOUNDARY_SMTP_OPTS.get('embed-images'): image_data = get_graphite_graph_image(skyline_app, link, image_file) if settings.BOUNDARY_SMTP_OPTS.get('embed-images_disabled3290'): # @modified 20191021 - Task #3290: Handle urllib2 in py3 # Branch #3262: py3 if python_version == 2: try: # @modified 20170913 - Task #2160: Test skyline with bandit # Added nosec to exclude from bandit tests # image_data = urllib2.urlopen(link).read() # nosec image_data = None except urllib2.URLError: image_data = None if python_version == 3: try: # image_data = urllib.request.urlopen(link).read() # nosec image_data = None except: logger.error(traceback.format_exc()) logger.error('error :: boundary_alerters :: alert_smtp :: failed to urlopen %s' % str(link)) image_data = None # If we failed to get the image or if it was explicitly disabled, # use the image URL instead of the content. if image_data is None: img_tag = '<img src="%s"/>' % link else: img_tag = '<img src="cid:%s"/>' % content_id # @modified 20191002 - Feature #3194: Add CUSTOM_ALERT_OPTS to settings # body = '%s :: %s <br> Next alert in: %s seconds <br> skyline Boundary alert - %s <br><a href="%s">%s</a>' % ( # datapoint, metric_name, expiration_time, alert_context, link, img_tag) body = '%s :: %s <br> Next alert in: %s seconds <br> %s %s alert - %s <br><a href="%s">%s</a>' % ( main_alert_title, app_alert_context, expiration_time, datapoint, metric_name, alert_context, link, img_tag) # @added 20200122 - Branch #3002: docker # Do not try to alert if the settings are default send_email_alert = True if 'your_domain.com' in str(sender): logger.info('alert_smtp - sender is not configured, not sending alert') send_email_alert = False if 'your_domain.com' in str(primary_recipient): logger.info('alert_smtp - sender is not configured, not sending alert') send_email_alert = False if 'example.com' in str(sender): logger.info('alert_smtp - sender is not configured, not sending alert') send_email_alert = False if 'example.com' in str(primary_recipient): logger.info('alert_smtp - sender is not configured, not sending alert') send_email_alert = False if DOCKER_FAKE_EMAIL_ALERTS: logger.info('alert_smtp - DOCKER_FAKE_EMAIL_ALERTS is set to %s, not executing SMTP command' % str(DOCKER_FAKE_EMAIL_ALERTS)) send_email_alert = False # @added 20200122 - Feature #3406: Allow for no_email SMTP_OPTS no_email = False if str(sender) == 'no_email': send_email_alert = False no_email = True if str(primary_recipient) == 'no_email': send_email_alert = False no_email = True if no_email: logger.info('alert_smtp - no_email is set in BOUNDARY_SMTP_OPTS, not executing SMTP command') # @modified 20180524 - Task #2384: Change alerters to cc other recipients # Do not send to each recipient, send to primary_recipient and cc the other # recipients, thereby sending only one email # for recipient in recipients: # @modified 20200122 - Feature #3406: Allow for no_email SMTP_OPTS # if primary_recipient: if primary_recipient and send_email_alert: logger.info( 'alert_smtp - will send to primary_recipient :: %s, cc_recipients :: %s' % (str(primary_recipient), str(cc_recipients))) msg = MIMEMultipart('alternative') # @modified 20191002 - Feature #3194: Add CUSTOM_ALERT_OPTS to settings # msg['Subject'] = '[Skyline alert] ' + 'Boundary ALERT - ' + alert_context + ' - ' + datapoint + ' - ' + metric_name # @modified 20201207 - Task #3878: Add metric_trigger and alert_threshold to Boundary alerts # msg['Subject'] = '[' + main_alert_title + ' alert] ' + app_alert_context + ' ALERT - ' + alert_context + ' - ' + datapoint + ' - ' + metric_name email_subject = '[%s alert] %s ALERT - %s' % ( main_alert_title, app_alert_context, alert_context, metric_name) msg['Subject'] = email_subject msg['From'] = sender # @modified 20180524 - Task #2384: Change alerters to cc other recipients # msg['To'] = recipient msg['To'] = primary_recipient # @added 20180524 - Task #2384: Change alerters to cc other recipients # Added Cc if cc_recipients: msg['Cc'] = cc_recipients msg.attach(MIMEText(body, 'html')) if image_data is not None: # msg_attachment = MIMEImage(image_data) fp = open(image_file, 'rb') msg_attachment = MIMEImage(fp.read()) fp.close() msg_attachment.add_header('Content-ID', '<%s>' % content_id) msg.attach(msg_attachment) s = SMTP('127.0.0.1') # @modified 20180524 - Task #2384: Change alerters to cc other recipients # Send to primary_recipient and cc_recipients # s.sendmail(sender, recipient, msg.as_string()) try: if cc_recipients: s.sendmail(sender, [primary_recipient, cc_recipients], msg.as_string()) else: s.sendmail(sender, primary_recipient, msg.as_string()) except: logger.error(traceback.format_exc()) logger.error( 'error :: alert_smtp - could not send email to primary_recipient :: %s, cc_recipients :: %s' % (str(primary_recipient), str(cc_recipients))) s.quit() # @added 20200825 - Feature #3704: Add alert to anomalies if settings.PANORAMA_ENABLED: added_panorama_alert_event = add_panorama_alert(skyline_app, int(metric_timestamp), metric_name) if not added_panorama_alert_event: logger.error( 'error :: failed to add Panorama alert event - panorama.alert.%s.%s' % ( str(metric_timestamp), metric_name)) def alert_pagerduty(datapoint, metric_name, expiration_time, metric_trigger, algorithm, metric_timestamp, alert_threshold): if settings.PAGERDUTY_ENABLED: import pygerduty pager = pygerduty.PagerDuty(settings.BOUNDARY_PAGERDUTY_OPTS['subdomain'], settings.BOUNDARY_PAGERDUTY_OPTS['auth_token']) # @modified 20201207 - Task #3878: Add metric_trigger and alert_threshold to Boundary alerts # pager.trigger_incident(settings.BOUNDARY_PAGERDUTY_OPTS['key'], 'Anomalous metric: %s (value: %s) - %s' % (metric_name, datapoint, algorithm)) pager.trigger_incident(settings.BOUNDARY_PAGERDUTY_OPTS['key'], 'Anomalous metric: %s (value: %s) - %s %s %s times' % ( metric_name, str(datapoint), algorithm, str(metric_trigger), str(alert_threshold))) # @added 20200825 - Feature #3704: Add alert to anomalies if settings.PANORAMA_ENABLED: added_panorama_alert_event = add_panorama_alert(skyline_app, int(metric_timestamp), metric_name) if not added_panorama_alert_event: logger.error( 'error :: failed to add Panorama alert event - panorama.alert.%s.%s' % ( str(metric_timestamp), metric_name)) else: return False def alert_hipchat(datapoint, metric_name, expiration_time, metric_trigger, algorithm, metric_timestamp): if settings.HIPCHAT_ENABLED: sender = settings.BOUNDARY_HIPCHAT_OPTS['sender'] import hipchat hipster = hipchat.HipChat(token=settings.BOUNDARY_HIPCHAT_OPTS['auth_token']) # Allow for absolute path metric namespaces but also allow for and match # match wildcard namepaces if there is not an absolute path metric namespace rooms = 'unknown' notify_rooms = [] matched_rooms = [] try: rooms = settings.BOUNDARY_HIPCHAT_OPTS['rooms'][metric_name] notify_rooms.append(rooms) except: for room in settings.BOUNDARY_HIPCHAT_OPTS['rooms']: CHECK_MATCH_PATTERN = room check_match_pattern = re.compile(CHECK_MATCH_PATTERN) pattern_match = check_match_pattern.match(metric_name) if pattern_match: matched_rooms.append(room) if matched_rooms != []: for i_metric_name in matched_rooms: rooms = settings.BOUNDARY_HIPCHAT_OPTS['rooms'][i_metric_name] notify_rooms.append(rooms) alert_algo = str(algorithm) alert_context = alert_algo.upper() unencoded_graph_title = 'Skyline Boundary - %s at %s hours - %s - %s' % ( alert_context, graphite_previous_hours, metric_name, datapoint) graph_title_string = quote(unencoded_graph_title, safe='') graph_title = '&title=%s' % graph_title_string # @modified 20170706 - Support #2072: Make Boundary hipchat alerts show fixed timeframe graphite_now = int(time()) target_seconds = int((graphite_previous_hours * 60) * 60) from_timestamp = str(graphite_now - target_seconds) until_timestamp = str(graphite_now) graphite_from = datetime.datetime.fromtimestamp(int(from_timestamp)).strftime('%H:%M_%Y%m%d') graphite_until = datetime.datetime.fromtimestamp(int(until_timestamp)).strftime('%H:%M_%Y%m%d') if settings.GRAPHITE_PORT != '': # link = '%s://%s:%s/render/?from=-%shours&target=cactiStyle(%s)%s%s&colorList=%s' % ( # settings.GRAPHITE_PROTOCOL, settings.GRAPHITE_HOST, settings.GRAPHITE_PORT, # graphite_previous_hours, metric_name, settings.GRAPHITE_GRAPH_SETTINGS, # @modified 20190520 - Branch #3002: docker # Use GRAPHITE_RENDER_URI # link = '%s://%s:%s/render/?from=%s&until=%s&target=cactiStyle(%s)%s%s&colorList=%s' % ( # settings.GRAPHITE_PROTOCOL, settings.GRAPHITE_HOST, settings.GRAPHITE_PORT, # graphite_from, graphite_until, metric_name, settings.GRAPHITE_GRAPH_SETTINGS, # graph_title, graphite_graph_line_color) # @modified 20200417 - Task #3294: py3 - handle system parameter in Graphite cactiStyle # link = '%s://%s:%s/%s/?from=%s&until=%s&target=cactiStyle(%s)%s%s&colorList=%s' % ( link = '%s://%s:%s/%s/?from=%s&until=%s&target=cactiStyle(%s,%%27si%%27)%s%s&colorList=%s' % ( settings.GRAPHITE_PROTOCOL, settings.GRAPHITE_HOST, settings.GRAPHITE_PORT, settings.GRAPHITE_RENDER_URI, graphite_from, graphite_until, metric_name, settings.GRAPHITE_GRAPH_SETTINGS, graph_title, graphite_graph_line_color) else: # link = '%s://%s/render/?from=-%shour&target=cactiStyle(%s)%s%s&colorList=%s' % ( # settings.GRAPHITE_PROTOCOL, settings.GRAPHITE_HOST, graphite_previous_hours, # @modified 20190520 - Branch #3002: docker # Use GRAPHITE_RENDER_URI # link = '%s://%s/render/?from=%s&until=%s&target=cactiStyle(%s)%s%s&colorList=%s' % ( # settings.GRAPHITE_PROTOCOL, settings.GRAPHITE_HOST, graphite_from, graphite_until, # metric_name, settings.GRAPHITE_GRAPH_SETTINGS, graph_title, # graphite_graph_line_color) # @modified 20200417 - Task #3294: py3 - handle system parameter in Graphite cactiStyle # link = '%s://%s/%s/?from=%s&until=%s&target=cactiStyle(%s)%s%s&colorList=%s' % ( link = '%s://%s/%s/?from=%s&until=%s&target=cactiStyle(%s,%%27si%%27)%s%s&colorList=%s' % ( settings.GRAPHITE_PROTOCOL, settings.GRAPHITE_HOST, settings.GRAPHITE_RENDER_URI, graphite_from, graphite_until, metric_name, settings.GRAPHITE_GRAPH_SETTINGS, graph_title, graphite_graph_line_color) embed_graph = "<a href='" + link + "'><img height='308' src='" + link + "'>" + metric_name + "</a>" for rooms in notify_rooms: for room in rooms: hipster.method('rooms/message', method='POST', parameters={'room_id': room, 'from': 'skyline', 'color': settings.BOUNDARY_HIPCHAT_OPTS['color'], 'message': '%s - Boundary - %s - Anomalous metric: %s (value: %s) at %s hours %s' % (sender, algorithm, metric_name, datapoint, graphite_previous_hours, embed_graph)}) else: return False def alert_syslog(datapoint, metric_name, expiration_time, metric_trigger, algorithm, metric_timestamp, alert_threshold): if settings.SYSLOG_ENABLED: import sys import syslog syslog_ident = settings.SYSLOG_OPTS['ident'] # @modified 20201207 - Task #3878: Add metric_trigger and alert_threshold to Boundary alerts # message = str('Boundary - Anomalous metric: %s (value: %s) - %s' % (metric_name, datapoint, algorithm)) message = 'Boundary - Anomalous metric: %s (value: %s) - %s with %s %s times' % ( metric_name, str(datapoint), algorithm, str(metric_trigger), str(alert_threshold)) if sys.version_info[:2] == (2, 6): syslog.openlog(syslog_ident, syslog.LOG_PID, syslog.LOG_LOCAL4) elif sys.version_info[:2] == (2, 7): syslog.openlog(ident='skyline', logoption=syslog.LOG_PID, facility=syslog.LOG_LOCAL4) elif sys.version_info[:1] == (3): syslog.openlog(ident='skyline', logoption=syslog.LOG_PID, facility=syslog.LOG_LOCAL4) else: syslog.openlog(syslog_ident, syslog.LOG_PID, syslog.LOG_LOCAL4) syslog.syslog(4, message) else: return False # @added 20181126 - Task #2742: Update Boundary # Feature #2618: alert_slack def alert_slack(datapoint, metric_name, expiration_time, metric_trigger, algorithm, metric_timestamp, alert_threshold): if not settings.SLACK_ENABLED: return False # @modified 20200701 - Task #3612: Upgrade to slack v2 # Task #3608: Update Skyline to Python 3.8.3 and deps # Task #3556: Update deps # slackclient v2 has a version function, < v2 does not # from slackclient import SlackClient try: from slack import version as slackVersion slack_version = slackVersion.__version__ except: slack_version = '1.3' if slack_version == '1.3': from slackclient import SlackClient else: from slack import WebClient metric = metric_name logger.info('alert_slack - anomalous metric :: metric: %s - %s' % (metric, algorithm)) base_name = metric alert_algo = str(algorithm) alert_context = alert_algo.upper() # The known_derivative_metric state is determine in case we need to surface # the png image from Graphite if the Ionosphere image is not available for # some reason. This will result in Skyline at least still sending an alert # to slack, even if some gear fails in Ionosphere or slack alerting is used # without Ionosphere enabled. Yes not DRY but multiprocessing and spawn # safe. known_derivative_metric = False # try: # if settings.REDIS_PASSWORD: # # @modified 20191022 - Bug #3266: py3 Redis binary objects not strings # # Branch #3262: py3 # # REDIS_ALERTER_CONN = redis.StrictRedis(password=settings.REDIS_PASSWORD, unix_socket_path=settings.REDIS_SOCKET_PATH) # REDIS_ALERTER_CONN = redis.StrictRedis(password=settings.REDIS_PASSWORD, unix_socket_path=settings.REDIS_SOCKET_PATH, charset='utf-8', decode_responses=True) # else: # # REDIS_ALERTER_CONN = redis.StrictRedis(unix_socket_path=settings.REDIS_SOCKET_PATH) # REDIS_ALERTER_CONN = redis.StrictRedis(unix_socket_path=settings.REDIS_SOCKET_PATH, charset='utf-8', decode_responses=True) # except: # logger.error('error :: alert_slack - redis connection failed') # try: # derivative_metrics = list(REDIS_ALERTER_CONN.smembers('derivative_metrics')) # except: # derivative_metrics = [] # @modified 20201207 - Task #3878: Add metric_trigger and alert_threshold to Boundary alerts # redis_metric_name not used # redis_metric_name = '%s%s' % (settings.FULL_NAMESPACE, str(base_name)) # if redis_metric_name in derivative_metrics: # known_derivative_metric = True known_derivative_metric = is_derivative_metric(skyline_app, str(base_name)) # if known_derivative_metric: # try: # non_derivative_monotonic_metrics = settings.NON_DERIVATIVE_MONOTONIC_METRICS # except: # non_derivative_monotonic_metrics = [] # skip_derivative = in_list(redis_metric_name, non_derivative_monotonic_metrics) # if skip_derivative: # known_derivative_metric = False # @added 20191008 - Feature #3194: Add CUSTOM_ALERT_OPTS to settings try: main_alert_title = settings.CUSTOM_ALERT_OPTS['main_alert_title'] except: main_alert_title = 'Skyline' try: app_alert_context = settings.CUSTOM_ALERT_OPTS['boundary_alert_heading'] except: app_alert_context = 'Boundary' if known_derivative_metric: # @modified 20191008 - Feature #3194: Add CUSTOM_ALERT_OPTS to settings # unencoded_graph_title = 'Skyline Boundary - ALERT %s at %s hours - derivative graph - %s' % ( # alert_context, str(graphite_previous_hours), metric) # slack_title = '*Skyline Boundary - ALERT* %s on %s at %s hours - derivative graph - %s' % ( # alert_context, metric, str(graphite_previous_hours), datapoint) # @modified 20201207 - Task #3878: Add metric_trigger and alert_threshold to Boundary alerts # unencoded_graph_title = '%s %s - ALERT %s at %s hours - derivative graph - %s' % ( # main_alert_title, app_alert_context, alert_context, str(graphite_previous_hours), metric) # slack_title = '*%s %s - ALERT* %s on %s at %s hours - derivative graph - %s' % ( # main_alert_title, app_alert_context, alert_context, metric, str(graphite_previous_hours), datapoint) unencoded_graph_title = '%s %s - ALERT %s %s %s times - derivative graph - %s' % ( main_alert_title, app_alert_context, alert_context, str(metric_trigger), str(alert_threshold), metric) slack_title = '*%s %s - ALERT* %s %s %s times on %s - derivative graph - %s' % ( main_alert_title, app_alert_context, alert_context, str(metric_trigger), str(alert_threshold), metric, str(datapoint)) else: # unencoded_graph_title = 'Skyline Boundary - ALERT %s at %s hours - %s' % ( # alert_context, str(graphite_previous_hours), metric) # slack_title = '*Skyline Boundary - ALERT* %s on %s at %s hours - %s' % ( # alert_context, metric, str(graphite_previous_hours), datapoint) # @modified 20201207 - Task #3878: Add metric_trigger and alert_threshold to Boundary alerts # unencoded_graph_title = '%s %s - ALERT %s at %s hours - %s' % ( # main_alert_title, app_alert_context, alert_context, str(graphite_previous_hours), metric) # slack_title = '*%s %s - ALERT* %s on %s at %s hours - %s' % ( # main_alert_title, app_alert_context, alert_context, metric, str(graphite_previous_hours), datapoint) unencoded_graph_title = '%s %s - ALERT %s %s %s times - %s' % ( main_alert_title, app_alert_context, alert_context, str(metric_trigger), str(alert_threshold), metric) slack_title = '*%s %s - ALERT* %s %s %s times on %s - %s' % ( main_alert_title, app_alert_context, alert_context, str(metric_trigger), str(alert_threshold), metric, str(datapoint)) graph_title_string = quote(unencoded_graph_title, safe='') graph_title = '&title=%s' % graph_title_string until_timestamp = int(time()) target_seconds = int((graphite_previous_hours * 60) * 60) from_timestamp = str(until_timestamp - target_seconds) graphite_from = dt.datetime.fromtimestamp(int(from_timestamp)).strftime('%H:%M_%Y%m%d') logger.info('graphite_from - %s' % str(graphite_from)) graphite_until = dt.datetime.fromtimestamp(int(until_timestamp)).strftime('%H:%M_%Y%m%d') logger.info('graphite_until - %s' % str(graphite_until)) # @added 20181025 - Feature #2618: alert_slack # Added date and time info so you do not have to mouseover the slack # message to determine the time at which the alert came in timezone = strftime("%Z", gmtime()) # @modified 20181029 - Feature #2618: alert_slack # Use the standard UNIX data format # human_anomaly_time = dt.datetime.fromtimestamp(int(until_timestamp)).strftime('%Y-%m-%d %H:%M:%S') human_anomaly_time = dt.datetime.fromtimestamp(int(until_timestamp)).strftime('%c') slack_time_string = '%s %s' % (human_anomaly_time, timezone) # @added 20191106 - Branch #3262: py3 # Branch #3002: docker graphite_port = get_graphite_port(skyline_app) graphite_render_uri = get_graphite_render_uri(skyline_app) graphite_custom_headers = get_graphite_custom_headers(skyline_app) # @added 20201013 - Feature #3780: skyline_functions - sanitise_graphite_url encoded_graphite_metric_name = encode_graphite_metric_name(skyline_app, metric_name) if settings.GRAPHITE_PORT != '': if known_derivative_metric: # @modified 20190520 - Branch #3002: docker # Use GRAPHITE_RENDER_URI # link = '%s://%s:%s/render/?from=%s&until=%s&target=cactiStyle(nonNegativeDerivative(%s))%s%s&colorList=orange' % ( # settings.GRAPHITE_PROTOCOL, settings.GRAPHITE_HOST, # settings.GRAPHITE_PORT, str(graphite_from), str(graphite_until), # metric, settings.GRAPHITE_GRAPH_SETTINGS, graph_title) # @modified 20191022 - Task #3294: py3 - handle system parameter in Graphite cactiStyle # link = '%s://%s:%s/%s/?from=%s&until=%s&target=cactiStyle(nonNegativeDerivative(%s))%s%s&colorList=orange' % ( link = '%s://%s:%s/%s/?from=%s&until=%s&target=cactiStyle(nonNegativeDerivative(%s),%%27si%%27)%s%s&colorList=orange' % ( settings.GRAPHITE_PROTOCOL, settings.GRAPHITE_HOST, # @modified 20201207 - Task #3878: Add metric_trigger and alert_threshold to Boundary alerts # Branch #3262: py3 # Branch #3002: docker # settings.GRAPHITE_PORT, settings.GRAPHITE_RENDER_URI, graphite_port, graphite_render_uri, str(graphite_from), str(graphite_until), # @modified 20201013 - Feature #3780: skyline_functions - sanitise_graphite_url # metric, settings.GRAPHITE_GRAPH_SETTINGS, graph_title) encoded_graphite_metric_name, settings.GRAPHITE_GRAPH_SETTINGS, graph_title) else: # @modified 20190520 - Branch #3002: docker # Use GRAPHITE_RENDER_URI # link = '%s://%s:%s/render/?from=%s&until=%s&target=cactiStyle(%s)%s%s&colorList=orange' % ( # settings.GRAPHITE_PROTOCOL, settings.GRAPHITE_HOST, # settings.GRAPHITE_PORT, str(graphite_from), str(graphite_until), # metric, settings.GRAPHITE_GRAPH_SETTINGS, graph_title) # @modified 20191022 - Task #3294: py3 - handle system parameter in Graphite cactiStyle # link = '%s://%s:%s/%s/?from=%s&until=%s&target=cactiStyle(%s)%s%s&colorList=orange' % ( link = '%s://%s:%s/%s/?from=%s&until=%s&target=cactiStyle(%s,%%27si%%27)%s%s&colorList=orange' % ( settings.GRAPHITE_PROTOCOL, settings.GRAPHITE_HOST, # @modified 20201207 - Task #3878: Add metric_trigger and alert_threshold to Boundary alerts # Branch #3262: py3 # Branch #3002: docker # settings.GRAPHITE_PORT, settings.GRAPHITE_RENDER_URI, graphite_port, graphite_render_uri, # str(graphite_from), str(graphite_until), metric, # @modified 20201013 - Feature #3780: skyline_functions - sanitise_graphite_url str(graphite_from), str(graphite_until), encoded_graphite_metric_name, settings.GRAPHITE_GRAPH_SETTINGS, graph_title) else: if known_derivative_metric: # @modified 20190520 - Branch #3002: docker # Use GRAPHITE_RENDER_URI # link = '%s://%s/render/?from=%s&until=%s&target=cactiStyle(nonNegativeDerivative(%s))%s%s&colorList=orange' % ( # settings.GRAPHITE_PROTOCOL, settings.GRAPHITE_HOST, # str(graphite_from), str(graphite_until), metric, # settings.GRAPHITE_GRAPH_SETTINGS, graph_title) # @modified 20191022 - Task #3294: py3 - handle system parameter in Graphite cactiStyle # link = '%s://%s/%s/?from=%s&until=%s&target=cactiStyle(nonNegativeDerivative(%s))%s%s&colorList=orange' % ( link = '%s://%s/%s/?from=%s&until=%s&target=cactiStyle(nonNegativeDerivative(%s),%%27si%%27)%s%s&colorList=orange' % ( settings.GRAPHITE_PROTOCOL, settings.GRAPHITE_HOST, settings.GRAPHITE_RENDER_URI, str(graphite_from), # @modified 20201013 - Feature #3780: skyline_functions - sanitise_graphite_url # str(graphite_until), metric, settings.GRAPHITE_GRAPH_SETTINGS, str(graphite_until), encoded_graphite_metric_name, settings.GRAPHITE_GRAPH_SETTINGS, graph_title) else: # @modified 20190520 - Branch #3002: docker # Use GRAPHITE_RENDER_URI # link = '%s://%s/render/?from=%s&until=%s&target=cactiStyle(%s)%s%s&colorList=orange' % ( # settings.GRAPHITE_PROTOCOL, settings.GRAPHITE_HOST, # str(graphite_from), str(graphite_until), metric, # settings.GRAPHITE_GRAPH_SETTINGS, graph_title) # @modified 20191022 - Task #3294: py3 - handle system parameter in Graphite cactiStyle # link = '%s://%s/%s/?from=%s&until=%s&target=cactiStyle(%s)%s%s&colorList=orange' % ( link = '%s://%s/%s/?from=%s&until=%s&target=cactiStyle(%s,%%27si%%27)%s%s&colorList=orange' % ( settings.GRAPHITE_PROTOCOL, settings.GRAPHITE_HOST, settings.GRAPHITE_RENDER_URI, str(graphite_from), # @modified 20201013 - Feature #3780: skyline_functions - sanitise_graphite_url # str(graphite_until), metric, settings.GRAPHITE_GRAPH_SETTINGS, str(graphite_until), encoded_graphite_metric_name, settings.GRAPHITE_GRAPH_SETTINGS, graph_title) # slack does not allow embedded images, nor will it fetch links behind # authentication so Skyline uploads a png graphite image with the message image_file = None # Fetch the png from Graphite # @modified 20191021 - Task #3290: Handle urllib2 in py3 # Branch #3262: py3 image_file = '%s/%s.%s.graphite.%sh.png' % ( settings.SKYLINE_TMP_DIR, base_name, skyline_app, str(int(graphite_previous_hours))) if python_version == 22: try: # image_data = urllib2.urlopen(link).read() # nosec image_data = None # except urllib2.URLError: except: logger.error(traceback.format_exc()) logger.error('error :: alert_slack - failed to get image graph') logger.error('error :: alert_slack - %s' % str(link)) image_data = None if python_version == 33: try: image_file = '%s/%s.%s.graphite.%sh.png' % ( settings.SKYLINE_TMP_DIR, base_name, skyline_app, str(int(graphite_previous_hours))) # urllib.request.urlretrieve(link, image_file) image_data = 'retrieved' image_data = None except: try: # @added 20191022 - Task #3294: py3 - handle system parameter in Graphite cactiStyle image_data = None original_traceback = traceback.format_exc() if 'cactiStyle' in link: metric_replace = '%s,%%27si%%27' % metric original_link = link link = link.replace(metric, metric_replace) logger.info('link replaced with cactiStyle system parameter added - %s' % str(link)) urllib.request.urlretrieve(link, image_file) image_data = 'retrieved' except: new_trackback = traceback.format_exc() logger.error(original_traceback) logger.error('error :: boundary_alerters :: alert_slack :: failed to urlopen %s' % str(original_link)) logger.error(new_trackback) logger.error('error :: boundary_alerters :: alert_slack :: failed to urlopen with system parameter added %s' % str(link)) image_data = None # @added 20191025 - image_data = get_graphite_graph_image(skyline_app, link, image_file) if image_data == 'disabled_for_testing': image_file = '%s/%s.%s.graphite.%sh.png' % ( settings.SKYLINE_TMP_DIR, base_name, skyline_app, str(int(graphite_previous_hours))) if image_data != 'retrieved': try: write_data_to_file(skyline_app, image_file, 'w', image_data) logger.info('alert_slack - added Graphite image :: %s' % ( image_file)) except: logger.info(traceback.format_exc()) logger.error( 'error :: alert_slack - failed to add %s Graphite image' % ( image_file)) image_file = None try: filename = os.path.basename(image_file) except: filename = None try: bot_user_oauth_access_token = settings.BOUNDARY_SLACK_OPTS['bot_user_oauth_access_token'] except: logger.error('error :: alert_slack - could not determine bot_user_oauth_access_token') return False # Allow for absolute path metric namespaces but also allow for and match # match wildcard namepaces if there is not an absolute path metric namespace channels = 'unknown' notify_channels = [] matched_channels = [] try: channels = settings.BOUNDARY_SLACK_OPTS['channels'][metric_name] notify_channels.append(channels) except: for channel in settings.BOUNDARY_SLACK_OPTS['channels']: CHECK_MATCH_PATTERN = channel check_match_pattern = re.compile(CHECK_MATCH_PATTERN) pattern_match = check_match_pattern.match(metric_name) if pattern_match: matched_channels.append(channel) if matched_channels != []: for i_metric_name in matched_channels: channels = settings.BOUNDARY_SLACK_OPTS['channels'][i_metric_name] notify_channels.append(channels) if not notify_channels: logger.error('error :: alert_slack - could not determine channel') return False else: channels = notify_channels try: icon_emoji = settings.BOUNDARY_SLACK_OPTS['icon_emoji'] except: icon_emoji = ':chart_with_upwards_trend:' try: # @modified 20200701 - Task #3612: Upgrade to slack v2 # Task #3608: Update Skyline to Python 3.8.3 and deps # Task #3556: Update deps # sc = SlackClient(bot_user_oauth_access_token) if slack_version == '1.3': sc = SlackClient(bot_user_oauth_access_token) else: sc = WebClient(bot_user_oauth_access_token, timeout=10) except: logger.info(traceback.format_exc()) logger.error('error :: alert_slack - could not initiate SlackClient') return False # @added 20200815 - Bug #3676: Boundary slack alert errors # Task #3608: Update Skyline to Python 3.8.3 and deps # Task #3612: Upgrade to slack v2 # Strange only Boundary slack messages are erroring on a tuple or part # thereof, mirage_alerters using the same method are fine??? # The server responded with: {'ok': False, 'error': 'invalid_channel', 'channel': "('#skyline'"} # This fix handles converting tuple items into list items where the channel # is a tuple. channels_list = [] for channel in channels: if type(channel) == tuple: for ichannel in channel: channels_list.append(str(ichannel)) else: channels_list.append(str(channel)) if channels_list: channels = channels_list for channel in channels: initial_comment = slack_title + ' :: <' + link + '|graphite image link>\nFor anomaly at ' + slack_time_string # @added 20201127 - Feature #3820: HORIZON_SHARDS # Add the origin and shard for debugging purposes if HORIZON_SHARDS: initial_comment = initial_comment + ' - from ' + this_host + ' (shard ' + str(HORIZON_SHARD) + ')' try: # slack does not allow embedded images, nor links behind authentication # or color text, so we have jump through all the API hoops to end up # having to upload an image with a very basic message. if os.path.isfile(image_file): # @modified 20200701 - Task #3612: Upgrade to slack v2 # Task #3608: Update Skyline to Python 3.8.3 and deps # Task #3556: Update deps if slack_version == '1.3': slack_file_upload = sc.api_call( 'files.upload', filename=filename, channels=channel, initial_comment=initial_comment, file=open(image_file, 'rb')) else: slack_file_upload = sc.files_upload( filename=filename, channels=channel, initial_comment=initial_comment, file=open(image_file, 'rb')) if not slack_file_upload['ok']: logger.error('error :: alert_slack - failed to send slack message with file upload') logger.error('error :: alert_slack - slack_file_upload - %s' % str(slack_file_upload)) try: os.remove(image_file) except OSError: logger.error('error - failed to remove %s, continuing' % image_file) pass else: send_text = initial_comment + ' :: error :: there was no graph image to upload' send_message = sc.api_call( 'chat.postMessage', channel=channel, icon_emoji=icon_emoji, text=send_text) if not send_message['ok']: logger.error('error :: alert_slack - failed to send slack message') else: logger.info('alert_slack - sent slack message') except: logger.info(traceback.format_exc()) logger.error('error :: alert_slack - could not upload file') return False # @added 20200825 - Feature #3704: Add alert to anomalies if settings.PANORAMA_ENABLED: added_panorama_alert_event = add_panorama_alert(skyline_app, int(metric_timestamp), metric_name) if not added_panorama_alert_event: logger.error( 'error :: failed to add Panorama alert event - panorama.alert.%s.%s' % ( str(metric_timestamp), metric_name)) # @added 20200122: Feature #3396: http_alerter def alert_http(alerter, datapoint, metric_name, expiration_time, metric_trigger, algorithm, metric_timestamp, alert_threshold): """ Called by :func:`~trigger_alert` and sends and resend anomalies to a http endpoint. """ if settings.HTTP_ALERTERS_ENABLED: alerter_name = alerter alerter_enabled = False try: alerter_enabled = settings.HTTP_ALERTERS_OPTS[alerter_name]['enabled'] except: logger.error(traceback.format_exc()) logger.error('error :: alert_http failed to determine the enabled from settings.HTTP_ALERTERS_OPTS for alerter - %s and metric %s with algorithm %s' % ( str(alerter), str(metric_name), algorithm)) if not alerter_enabled: logger.info('alert_http - %s enabled %s, not alerting' % ( str(alerter_name), str(alerter_enabled))) return alerter_endpoint = False try: alerter_endpoint = settings.HTTP_ALERTERS_OPTS[alerter_name]['endpoint'] except: logger.error(traceback.format_exc()) logger.error('error :: alert_http failed to determine the endpoint from settings.HTTP_ALERTERS_OPTS for alert - %s and metric %s with algorithm %s' % ( str(alerter), str(metric_name), algorithm)) if not alerter_endpoint: logger.error('alert_http - no endpoint set for %s, not alerting' % ( str(alerter_name))) return alerter_token = None try: alerter_token = settings.HTTP_ALERTERS_OPTS[alerter_name]['token'] except: pass source = 'boundary' metric_alert_dict = {} alert_data_dict = {} try: timestamp_str = str(metric_timestamp) value_str = str(datapoint) full_duration_str = str(int(full_duration_seconds)) expiry_str = str(expiration_time) metric_alert_dict = { "metric": metric_name, "algorithm": algorithm, "timestamp": timestamp_str, "value": value_str, "full_duration": full_duration_str, "expiry": expiry_str, # @added 20201207 - Task #3878: Add metric_trigger and alert_threshold to Boundary alerts "metric_trigger": metric_trigger, "alert_threshold": alert_threshold, "source": str(source), "token": str(alerter_token) } # @modified 20200302: Feature #3396: http_alerter # Add the token as an independent entity from the alert # alert_data_dict = {"status": {}, "data": {"alert": metric_alert_dict}} alerter_token_str = str(alerter_token) # @modified 20201127 - Feature #3820: HORIZON_SHARDS # Add the origin and shard to status for debugging purposes if not HORIZON_SHARDS: alert_data_dict = {"status": {}, "data": {"token": alerter_token_str, "alert": metric_alert_dict}} else: alert_data_dict = {"status": {"origin": this_host, "shard": HORIZON_SHARD}, "data": {"token": alerter_token_str, "alert": metric_alert_dict}} logger.info('alert_http :: alert_data_dict to send - %s' % str(alert_data_dict)) except: logger.error(traceback.format_exc()) logger.error('error :: alert_http failed to construct the alert data for %s from alert - %s and metric - %s' % ( str(alerter_name), str(algorithm), str(metric_name))) return in_resend_queue = False redis_set = '%s.http_alerter.queue' % str(source) resend_queue = None previous_attempts = 0 REDIS_HTTP_ALERTER_CONN_DECODED = get_redis_conn_decoded(skyline_app) try: resend_queue = REDIS_HTTP_ALERTER_CONN_DECODED.smembers(redis_set) except Exception as e: logger.error('error :: alert_http :: could not query Redis for %s - %s' % (redis_set, e)) if REDIS_HTTP_ALERTER_CONN_DECODED: try: del REDIS_HTTP_ALERTER_CONN_DECODED except: pass if resend_queue: try: for index, resend_item in enumerate(resend_queue): resend_item_list = literal_eval(resend_item) # resend_alert = literal_eval(resend_item_list[0]) # resend_metric = literal_eval(resend_item_list[1]) resend_metric_alert_dict = literal_eval(resend_item_list[2]) if resend_metric_alert_dict['metric'] == metric_name: if int(resend_metric_alert_dict['timestamp']) == int(metric_timestamp): previous_attempts = int(resend_metric_alert_dict['attempts']) in_resend_queue = True break except: logger.error(traceback.format_exc()) logger.error('error :: alert_http failed iterate to resend_queue') # REDIS_HTTP_ALERTER_CONN = None # if in_resend_queue: # REDIS_HTTP_ALERTER_CONN = get_redis_conn(skyline_app) REDIS_HTTP_ALERTER_CONN = get_redis_conn(skyline_app) add_to_resend_queue = False fail_alerter = False if alert_data_dict and alerter_endpoint: # @modified 20200403 - Feature #3396: http_alerter # Changed timeouts from 2, 2 to 5, 20 connect_timeout = 5 read_timeout = 20 if requests.__version__ >= '2.4.0': use_timeout = (int(connect_timeout), int(read_timeout)) else: use_timeout = int(connect_timeout) if settings.ENABLE_DEBUG: logger.debug('debug :: use_timeout - %s' % (str(use_timeout))) response = None try: response = requests.post(alerter_endpoint, json=alert_data_dict, timeout=use_timeout) except: logger.error(traceback.format_exc()) logger.error('error :: failed to post alert to %s - %s' % ( str(alerter_name), str(alert_data_dict))) add_to_resend_queue = True response = None if in_resend_queue: try: REDIS_HTTP_ALERTER_CONN.srem(redis_set, str(resend_item)) logger.info('alert_http :: alert removed from %s' % ( str(redis_set))) except: logger.error(traceback.format_exc()) logger.error('error :: alert_http :: failed remove %s from Redis set %s' % ( str(resend_item), redis_set)) # @added 20200310 - Feature #3396: http_alerter # When the response code is 401 the response object appears to be # False, although the response.code and response.reason are set try: if response.status_code != 200: logger.error('error :: alert_http :: %s %s responded with status code %s and reason %s' % ( str(alerter_name), str(alerter_endpoint), str(response.status_code), str(response.reason))) add_to_resend_queue = True fail_alerter = True except: logger.error(traceback.format_exc()) logger.error('error :: alert_http :: failed determine response.status_code') if response: if response.status_code == 200: logger.info('alert_http :: alert sent to %s - %s' % ( str(alerter_endpoint), str(alert_data_dict))) if in_resend_queue: logger.info('alert_http :: alert removed from %s after %s attempts to send' % ( str(redis_set), str(previous_attempts))) try: del REDIS_HTTP_ALERTER_CONN except: pass # @added 20200825 - Feature #3704: Add alert to anomalies if settings.PANORAMA_ENABLED: added_panorama_alert_event = add_panorama_alert(skyline_app, int(metric_timestamp), metric_name) if not added_panorama_alert_event: logger.error( 'error :: failed to add Panorama alert event - panorama.alert.%s.%s' % ( str(metric_timestamp), metric_name)) return else: logger.error('error :: alert_http :: %s %s responded with status code %s and reason %s' % ( str(alerter_name), str(alerter_endpoint), str(response.status_code), str(response.reason))) add_to_resend_queue = True fail_alerter = True else: logger.error('error :: alert_http :: %s %s did not respond' % ( str(alerter_name), str(alerter_endpoint))) add_to_resend_queue = True fail_alerter = True number_of_send_attempts = previous_attempts + 1 metric_alert_dict['attempts'] = number_of_send_attempts if add_to_resend_queue: data = [alerter, datapoint, metric_name, expiration_time, metric_trigger, algorithm, metric_timestamp, str(metric_alert_dict)] logger.info('alert_http :: adding alert to %s after %s attempts to send - %s' % ( str(redis_set), str(number_of_send_attempts), str(metric_alert_dict))) try: # redis_conn.sadd(redis_set, str(metric_alert_dict)) REDIS_HTTP_ALERTER_CONN.sadd(redis_set, str(data)) except: logger.error(traceback.format_exc()) logger.error('error :: alert_http :: failed to add %s from Redis set %s' % ( str(metric_alert_dict), redis_set)) # Create a Redis if there was a bad or no response from the # alerter_endpoint, to ensure that Boundary does not loop through # every alert in the queue for an alerter_endpoint, if the # alerter_endpoint is down if fail_alerter: alerter_endpoint_cache_key = 'http_alerter.down.%s' % str(alerter_name) logger.error('error :: alert_http :: alerter_endpoint %s failed adding Redis key %s' % ( str(alerter_endpoint), str(alerter_endpoint_cache_key))) if REDIS_HTTP_ALERTER_CONN: try: failed_timestamp = int(time()) REDIS_HTTP_ALERTER_CONN.setex(alerter_endpoint_cache_key, 60, failed_timestamp) except: logger.error(traceback.format_exc()) logger.error('error :: failed to set Redis key %s' % alerter_endpoint_cache_key) try: del REDIS_HTTP_ALERTER_CONN except: pass else: logger.info('alert_http :: settings.HTTP_ALERTERS_ENABLED not enabled nothing to do') return # @modified 20201207 - Task #3878: Add metric_trigger and alert_threshold to Boundary alerts # def trigger_alert(alerter, datapoint, metric_name, expiration_time, metric_trigger, algorithm, metric_timestamp): def trigger_alert(alerter, datapoint, metric_name, expiration_time, metric_trigger, algorithm, metric_timestamp, alert_threshold): if alerter == 'smtp': strategy = 'alert_smtp' # @added 20200122: Feature #3396: http_alerter # Added http_alerter elif 'http_alerter' in alerter: strategy = 'alert_http' else: strategy = 'alert_%s' % alerter try: if strategy == 'alert_http': # @modified 20201207 - Task #3878: Add metric_trigger and alert_threshold to Boundary alerts getattr(boundary_alerters, strategy)(alerter, datapoint, metric_name, expiration_time, metric_trigger, algorithm, metric_timestamp, alert_threshold) else: getattr(boundary_alerters, strategy)(datapoint, metric_name, expiration_time, metric_trigger, algorithm, metric_timestamp, alert_threshold) except: logger.error(traceback.format_exc()) logger.error('error :: alerters - %s - getattr error' % strategy)
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# import package import numpy as np from pandas import DataFrame import pandas as pd import re from dateutil import relativedelta import datetime as dt # 1.1 def df_groupby(df, groupkey, col, func, res_col_name, asint=False, dup=False): """ :param df: 一个df 征对 1+ 用户 :param groupkey: df中聚合分类的变量名 :param col: df中待聚合的变量名,字符串或者列表 :param func: 聚合方式,支持sum /max /min /avg /count/ distinct_count :param res_col_name: 聚合结果列名,字符串或者列表 :param asint: if asint=True ,聚合结果转为int ;default asint=False; :param dup: if dup=True ,变量取值去重 ;default dup=False; :return:df_res df """ # dropna all row df = df.dropna(axis=0, how='all') # reformat type try: if func != 'count' and func != 'distinct_count': df[col] = df[col].astype('float32') except ValueError: print('the col could not convert string to float!') # duplicate the col if dup: df = df.drop_duplicates(df.columns) # compatible str if type(col) != list: col = [col] if type(res_col_name) != list: res_col_name = [res_col_name] if type(func) != list: func = [func] # agg index df_res = DataFrame(df[groupkey].unique(), columns=[groupkey]) for i in func: if i == 'sum': df_res_ago = DataFrame(df.groupby(groupkey)[col].sum()) elif i == 'max': df_res_ago = DataFrame(df.groupby(groupkey)[col].max()) elif i == 'min': df_res_ago = DataFrame(df.groupby(groupkey)[col].min()) elif i == 'avg': df_res_ago = DataFrame(df.groupby(groupkey)[col].mean()) elif i == 'std': df_res_ago = DataFrame(df.groupby(groupkey)[col].std()) elif i == 'count': df_res_ago = DataFrame(df.groupby(groupkey)[col].count()) elif i == 'distinct_count': df_res_ago = DataFrame(df.groupby(groupkey)[col].nunique()) else: print('input func error!') df_res_ago = df_res_ago.reset_index() df_res = pd.merge(df_res, df_res_ago, how='left', on=groupkey) columns_list = [groupkey] columns_list.extend(res_col_name) df_res.columns = columns_list if asint: df_res[res_col_name] = df_res[res_col_name].astype(int) return df_res # use example # df_groupby(df,'appl_no', 'phone_gray_score', 'sum', 'phone_gray_score_sum', dup=False, asint=False) # df_groupby(df,'appl_no', ['phone_gray_score'], ['sum'], ['phone_gray_score_sum'], dup=False, asint=False) # df_groupby(df,'appl_no', ['register_cnt','phone_gray_score'], ['sum'], ['register_cnt_sum','phone_gray_score_sum'], dup=False, asint=False) # df_groupby(df,'appl_no', ['register_cnt','phone_gray_score'], ['sum','avg','count'], ['register_cnt_sum','phone_gray_score_sum','register_cnt_avg','phone_gray_score_avg','register_cnt_count','phone_gray_score_count'], dup=False, asint=False) # 1.2.1 def col_dummy(x, col, dummy_dict=[]): """ function about:变量编码功能函数集 by boysgs @20171103 :param x: 一个数值 :param col: df中需重新编码的变量名 :param dummy_dict: 列表,变量所有取值组成,示例['value_1','value_2'] :return:col_dummy_dict """ dummy_dict_sorted = sorted(dummy_dict) dummy_dict_sorted_key = np.array(['_'.join(['if', col, i]) for i in dummy_dict_sorted]) dummy_dict_sorted_value = [0] * len(dummy_dict_sorted_key) col_dummy_zip = zip(dummy_dict_sorted_key, dummy_dict_sorted_value) col_dummy_dict = dict((a, b) for a, b in col_dummy_zip) # if x in dummy_dict_sorted: col_dummy_dict['_'.join(['if', col, x])] = 1 return col_dummy_dict # use example # df = pd.DataFrame({'col1': [1, np.nan, 2, 3], 'col2': [3, 4, 5, 1], 'col3': ['s', 'a', 'c', 'd']}) # dummy_dict = ['a', 'b', 'c', 'd', 's'] # col = 'col3' # DataFrame(list(df[col].apply(lambda x: col_dummy(x, col, dummy_dict)))) # 1.2.2 def col_dummy_lb(x, lb_trans, sorted_dummy_varname_list=[]): """ function about:变量编码功能函数集(使用LabelBinarizer方法) by boysgs @20171103 :param x: 一个数值 :param lb_trans: 一个变量利用preprocessing.LabelBinarizer 方法生成的对象 :param sorted_dummy_varname_list: 列表,升序排列的变量所有取值组成,示例['value_1','value_2'] :return:col_dummy_dict 字典 """ dummy_value = lb_trans.transform(str([x])) col_dummy_dict = dict(zip(sorted_dummy_varname_list, dummy_value[0])) return col_dummy_dict # 2.1 def meetOneCondition(x,symbol = '=',threshold = ('None','b')): """ # 输入: # 变量名:年龄 # 符号:=,!=,>,< , >=, <= , in , not in,like, not like # 阈值:10,(10,11),'%10%' # 输出 # 满足条件输出1,否则输出0 """ if pd.isnull(x) or x == '': if symbol in ['!=','not in ','not like'] and threshold!='None': return 1 elif threshold=='None': if symbol == '=': return 1 elif symbol == '!=': return 0 else: return 0 elif symbol == '=': if threshold=='None': return 0 elif x == threshold: return 1 else: return 0 elif symbol == '!=': if threshold=='None': return 1 elif x != threshold: return 1 else: return 0 elif symbol == '>': if x > threshold: return 1 else: return 0 elif symbol == '<': if x < threshold: return 1 else: return 0 elif symbol == '>=': if x >= threshold: return 1 else: return 0 elif symbol == '<=': if x <= threshold: return 1 else: return 0 elif symbol == 'in': if x in threshold: return 1 else: return 0 elif symbol == 'not in': if x not in threshold: return 1 else: return 0 elif symbol == 'like': if threshold[0] == '%' and threshold[-1] == '%': if threshold[1:-1] in x: return 1 else: return 0 if threshold[0] == '%' and threshold[-1] != '%': if threshold[1:] == x[len(x)-len(threshold[1:]):]: return 1 else: return 0 if threshold[0] != '%' and threshold[-1] == '%': if threshold[0:-1] == x[0:len(threshold[0:-1])]: return 1 else: return 0 else: return 'you need cheack your "like" threshold' elif symbol == 'not like': if threshold[0] == '%' and threshold[-1] == '%': if threshold[1:-1] not in x: return 1 else: return 0 if threshold[0] == '%' and threshold[-1] != '%': if threshold[1:] != x[len(x)-len(threshold[1:]):]: return 1 else: return 0 if threshold[0] != '%' and threshold[-1] == '%': if threshold[0:-1] != x[0:len(threshold[0:-1])]: return 1 else: return 0 else: return 'you need cheack your "not like" threshold' elif symbol =='regex': if re.search(threshold,x): return 1 else: return 0 else: return 'please contact the developer for increaing then type of the symbol' # test: # x = 'abcde' # meetOneCondition(x,'=','abcd2') # meetOneCondition(x,'like','abc%') # meetOneCondition(x,'like','%abc') # meetOneCondition(x,'regex','b|adz|z') # 2.2 def meetMultiCondition(condition = ((),'and',())): """ # 输入 # 多个条件,单个条件参考meetOneCondition中的 # 例子 condition = ( ('age','>=',18), 'and', ( ('age','<=',40),'or',('gender','=','female') ) ) # 输出 # 满足条件输出1,否则输出0 """ if 'and' in condition: a = [k for k in condition if k!='and'] b = [] for l in range(len(a)): b.append(meetMultiCondition(a[l])) if 0 in b: return 0 else: return 1 if 'or' in condition: a = [k for k in condition if k != 'or'] b = [] for l in range(len(a)): b.append(meetMultiCondition(a[l])) if 1 in b: return 1 else: return 0 else: return meetOneCondition(condition[0],condition[1],condition[2]) # test # zz ='abcde' # yy = 10 # xx = 5 # meetMultiCondition(((zz,'=','abc'),'or',(yy,'>',7))) # 2.3 def singleConditionalAssignment(conditon =('z','=',('None','b')),assig1=1, assig2=0): """ # 单条件赋值 # 输入 # 参考meetOneCondition的输入 # 例如:conditon = ('age','>=',18) # 输出: # 满足条件assig1 # 不满足条件assig2 """ if meetOneCondition(conditon[0],conditon[1],conditon[2])==1: return assig1 elif meetOneCondition(conditon[0], conditon[1], conditon[2]) == 0: return assig2 else: return meetOneCondition(conditon[0],conditon[1],conditon[2]) # test # singleConditionalAssignment((x, '=', 'abcde'), 5, 1) # 2.4 def multiConditionalAssignment(condition = (),assig1 = 1,assig2 = 0): """ # 多个条件赋值 ###输入 ##多个条件类似meetMultiCondition的输入 ###输出: ##满足条件assig1 ##不满足条件assig2 """ if meetMultiCondition(condition)==1: return assig1 else: return assig2 # test # xx=5 # multiConditionalAssignment(condition =((zz,'=','abcde'),'and',( (yy,'>',10), 'or', (xx,'=',5) )),assig1 = 999,assig2 = 0) # 2.5 def multiConditionalMultAssignment(condition = ((('zz','not in', ('硕士','博士')),1),(('zz','not in', ('硕士','博士')),2)),assig = 0): """ ####多个条件多个赋值 ###输入 ##多个条件类似meetMultiCondition的输入,再加一满足的取值 ###输出: ##满足条件输出输入目标值 ##不满足条件assig """ for l in condition: if meetMultiCondition(l[0])==1: return l[1] return assig # test # multiConditionalMultAssignment((((zz,'=','abcdef'),1),((zz,'=','abcde'),2)),3) # 3.1 def substring(string,length,pos_start=0): """ function about : 字符串截取 by dabao @20171106 :param string: 被截取字段 :param length: 截取长度 :param pos_start: 从第几位开始截取,defualt=0 :return: a string :substr """ pos_end = length + pos_start if string is np.NaN: return np.NaN else: str_type = type(string) if str_type==str: substr = string[pos_start:pos_end] else: string = str(string) substr = string[pos_start:pos_end] return substr # test # string=370321199103050629 # length=4 # pos_start=6 # substring(string,length,pos_start) # string=np.NaN # 3.2 def charindex(substr,string,pos_start=0): """ function about : 字符串位置查询 by dabao @20171106 :param substr :param string: substr 在 string 起始位置 :param pos_start: 查找substr的开始位置,default=0 :return: a int :substr_index """ if string is np.NaN: return np.NaN else: substr = str(substr) string = str(string) substr_index = string.find(substr,pos_start) return substr_index # test # string='370321199103050629' # substr='1991' # charindex(substr,string) # string.find(substr,0) # 3.3 def trim(string,substr=' ',method='both'): """ function about : 删除空格或其他指定字符串 by dabao @20171106 :param string: a string :param substr: 在string两端删除的指定字符串,default=' ' :param method: 删除方式:left 删除左边, right 删除右边, both 删除两边 :return: a string :string_alter """ if string is np.NaN: return np.NaN else: substr = str(substr) string = str(string) if method in ['left','right','both']: if method =='left': string_alter = string.lstrip(substr) elif method == 'right': string_alter = string.rstrip(substr) elif method == 'both': string_alter = string.strip(substr) else: string_alter = string.strip(substr) print("Warning: method must be in ['left','right','both']! If not, the function will be acting as 'both'") return string_alter # test: # string=' OPPO,HUAWEI,VIVO,HUAWEI ' # trim(string) # (4)计算字符串长度:SQL中的LEN()函数 ,python自带 len() # (5)字符串转换为大、小写:SQL 中的 LOWCASE,UPPER 语句,python自带函数 string.upper(),string.lower() # 3.4 def OnlyCharNum(s,oth=''): # 只显示字母与数字 s2 = s.lower() fomart = 'abcdefghijklmnopqrstuvwxyz0123456789' for c in s2: if not c in fomart: s = s.replace(c,'') return s # 4.1 def dateformat(date,symbol): """ 输入: 变量名:时间,按照格式接收10位、19位 可选:'year','month','day','hour','minute','second' 输出 满足条件输出值,否则报错 """ if pd.isnull(date): return np.NaN date = str(date) if len(date)==10: date=date+' 00:00:00' date=dt.datetime.strptime(date,'%Y-%m-%d %H:%M:%S') if symbol in ['year','month','day','hour','minute','second']: if symbol =='year': datetime_elect = date.year elif symbol == 'month': datetime_elect = date.month elif symbol == 'day': datetime_elect = date.day elif symbol == 'hour': datetime_elect = date.hour elif symbol == 'minute': datetime_elect = date.minute elif symbol == 'second': datetime_elect = date.second else: datetime_elect = np.NaN print("Warning: symbol must be in ['year','month','day','hour','minute','second']! If not, the function will be acting as 'both'") return datetime_elect # test1: # dateformat('2017-09-25 12:58:45','day') # dateformat('2017-09-25 12:58:45','hour') # dateformat('2017-09-25','day') # dateformat(null,'hour') # 4.2 def datediff(symbol,date_begin,date_end): """ 输入: 变量名:时间,按照格式接收10位、19位 可选:'year','month','day','hour','minute','second' 输出 满足条件输出值,否则报错 """ if pd.isnull(date_begin) or pd.isnull(date_end): return np.NaN date_begin = str(date_begin) date_end = str(date_end) if len(date_begin)==4: date_begin=date_begin+'-01-01 00:00:00' if len(date_end)==4: date_end=date_end+'-01-01 00:00:00' if len(date_begin)==7: date_begin=date_begin+'-01 00:00:00' if len(date_end)==7: date_end=date_end+'-01 00:00:00' if len(date_begin)==10: date_begin=date_begin+' 00:00:00' if len(date_end)==10: date_end=date_end+' 00:00:00' date_begin=dt.datetime.strptime(date_begin,'%Y-%m-%d %H:%M:%S') date_end=dt.datetime.strptime(date_end,'%Y-%m-%d %H:%M:%S') if symbol in ['year','month','day','hour','minute','second']: r = relativedelta.relativedelta(date_end,date_begin) if symbol =='year': datetime_diff=r.years elif symbol == 'month': datetime_diff=r.years*12+r.months elif symbol == 'day': datetime_diff = (date_end-date_begin).days elif symbol == 'hour': datetime_days = (date_end-date_begin).days datetime_seconds = (date_end-date_begin).seconds datetime_diff = datetime_seconds/3600+datetime_days*24 elif symbol == 'minute': datetime_days = (date_end-date_begin).days datetime_seconds = (date_end-date_begin).seconds datetime_diff=datetime_seconds/60+datetime_days*24*60 elif symbol == 'second': datetime_days = (date_end-date_begin).days datetime_seconds = (date_end-date_begin).seconds datetime_diff=datetime_seconds+datetime_days*24*60*60 else: datetime_diff = np.NaN print("Warning: symbol must be in ['year','month','day','hour','minute','second']! If not, the function will be acting as 'both'") return datetime_diff # test # datediff('month','2013','2017-09-25 12:58:45') # datediff('day','2017-09-25','2017-12-30') # datediff('hour','2017-09-15 10:58:45','2017-09-25 12:58:45') # datediff('day','2017-09-25','2017-12-30 12:58:45')
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/test/test_codat_data_contracts_datasets_journal_entry_paged_response_model.py
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procurify/codat-python-sdk
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""" Codat API [What's changed in our Swagger](https://docs.codat.io/docs/new-swagger-ui) # noqa: E501 The version of the OpenAPI document: v1 Generated by: https://openapi-generator.tech """ import sys import unittest import codat_python_sdk from codat_python_sdk.model.codat_data_contracts_datasets_journal_entry import CodatDataContractsDatasetsJournalEntry from codat_python_sdk.model.codat_data_contracts_datasets_journal_entry_paged_response_links_model import CodatDataContractsDatasetsJournalEntryPagedResponseLinksModel globals()['CodatDataContractsDatasetsJournalEntry'] = CodatDataContractsDatasetsJournalEntry globals()['CodatDataContractsDatasetsJournalEntryPagedResponseLinksModel'] = CodatDataContractsDatasetsJournalEntryPagedResponseLinksModel from codat_python_sdk.model.codat_data_contracts_datasets_journal_entry_paged_response_model import CodatDataContractsDatasetsJournalEntryPagedResponseModel class TestCodatDataContractsDatasetsJournalEntryPagedResponseModel(unittest.TestCase): """CodatDataContractsDatasetsJournalEntryPagedResponseModel unit test stubs""" def setUp(self): pass def tearDown(self): pass def testCodatDataContractsDatasetsJournalEntryPagedResponseModel(self): """Test CodatDataContractsDatasetsJournalEntryPagedResponseModel""" # FIXME: construct object with mandatory attributes with example values # model = CodatDataContractsDatasetsJournalEntryPagedResponseModel() # noqa: E501 pass if __name__ == '__main__': unittest.main()
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[]
no_license
NovaCentrix/chris-resistance-tester
938890d4811c1a0b0d8a764b604dc5395b405962
c90e053f8ee465889b89100c10833ecbce064549
refs/heads/master
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#!/usr/bin/env python3 # The MAIN code takes a bunch of images # (typically oscope screen-shots, for example) # and adds some text to the screen and # saves it in an output file with a new name. # The FIX_ONLY code solves some quirk with # the Rigol PNG format which causes imagemagick # to hiccup. Simply reading it and saving it # in Python solves the problem. import sys from PIL import Image, ImageDraw, ImageFont def fix_only(argv): if len(argv) < 2: print('Usage: rigol-fix-png <fname>') exit(0) fname = argv[1] outfname = 'fix-' + fname img = Image.open(fname) img.save(outfname) fontdir = '/Users/rclott/fonts/d2codingfont/D2Coding-Ver1.3.2-20180524/D2Coding/' fontfile = 'D2Coding-Ver1.3.2-20180524.ttf' fontpath = fontdir + fontfile def main(argv): if len(argv) < 4: print('Usage: rigol-fix-png <input-file> <label> <output-file>') exit(0) fname_in = argv[1] label = argv[2].upper() fname_out = argv[3] img = Image.open(fname_in) w,h = img.size font = ImageFont.truetype("Keyboard", 28) draw = ImageDraw.Draw(img) #label = 'xmt-075'.upper() xpos = 0.125 * w ypos = 0.75 * h xoff = 7 yoff = 7 textposn = (xpos, ypos) box = draw.textbbox( textposn, label, font=font ) bbox = ( box[0]-xoff, box[1]-yoff, box[2]+xoff, box[3]+yoff ) draw.rectangle(bbox, fill='gray', outline='gold', width=3) draw.text( textposn, label , fill='white' , font=font) img.save(fname_out) if __name__ == "__main__": #main(sys.argv) fix_only(sys.argv)
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/class/cp05_class_01.py
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[]
no_license
ederortega/python_t01
747ea8966cbcc075c9bc6d9c1dd0d756731dabe0
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2020-11-19T03:44:46
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class ASimpleClass: pass # constructor # print type
ea7af78e34c8acc6637fb1902a7c88c16081361f
0daa78054f5d5b505047aaa28ecbbea1662f9c53
/loop.py
047a171e01830a7b9011b773017a51188177d3eb
[]
no_license
WindWalker19/Python_for_everybody
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a2302f2ed4fcc334a096dda22b4ff6e7603c7c22
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2020-05-13T21:17:40
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#A while loop with break. while True: line = input("> ") if line == "done": print(line) break print("Blastoff") while True: line = input("> ") if line[0] == "#": continue # The continue would ask to go to the top of the loop without executing the code after it. print("hello") if line == "done": break print("Blastoff")
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193d84db39e014990c171b09a592b944e91cb524
/sendmail.py
981308e8c194eb9ddcb8a095182054098b8297db
[]
no_license
trungdungit45/idsoftware
66543e1d0731b08e260ba586c6ec3964b53ddc61
59acddea1a3dedfe0835faea46334db2c58bac5e
refs/heads/master
2020-03-21T12:00:38.184951
2018-07-14T02:56:57
2018-07-14T02:56:57
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from Alert.sendmail import send_message from Detection.comparetime import compareTime import datetime def readIP(): f = open("Log/snifflog.log","r") list = [] f1 = f.readlines() for x in f1: list.append(x) f.close() return list def checkLog(_listAlert, _listAlertStack): ip = readIP() for ift in ip: _lineLog = ift _warning, _root, _ipsource, _iptarget, _attack, _time, _timeStart, _date = _lineLog.split(':') strcontent = _timeStart +' WA' + _attack + ' ' + _time + ' from '+ _ipsource + ' to ' + _iptarget + ' ' + _date if (strcontent not in _listAlert and strcontent not in _listAlertStack): _listAlert.append(strcontent) if (compareTime(_timeStart, datetime.datetime.now().strftime('%H%M%S'))._time <= 60 and strcontent in _listAlert and strcontent not in _listAlertStack): try: send_message(strcontent, 'Warning System') _listAlert.remove(strcontent) _listAlertStack.append(strcontent) except: print('')
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/pyautest/golden_file_test.py
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[ "MIT" ]
permissive
higumachan/pyautest
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3f7fb55570397349e6dce77d49cff8ac1b965bf4
refs/heads/master
2020-04-22T09:53:46.973050
2019-03-06T13:49:56
2019-03-06T13:49:56
170,286,860
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import inspect from pathlib import Path from typing import List, Any from pyautest.adapter import basic_adapters from pyautest.adapter.base_adapter import BaseAdapter class GoldenFileTest: def __init__(self, file_directory: Path, adapters: List[BaseAdapter]): self.file_directory = file_directory self.adapters = adapters def __call__(self, name: str, obj: Any) -> bool: test_function_name = self._find_code_stack() if test_function_name is None: raise Exception("not found test function in call stack") adapter = self._find_adapter(obj) if adapter is None: raise Exception(f'not found adapter "{type(obj)}"') filepath = self.file_directory / test_function_name / f"{name}.{adapter.file_extension}" if not filepath.exists(): filepath.parent.mkdir(parents=True, exist_ok=True) adapter.save(obj, filepath) return True other = adapter.load(filepath) return adapter.equal(obj, other) def _find_adapter(self, obj: Any) -> BaseAdapter: for adapter in self.adapters: for cls in adapter.target_classes: if isinstance(obj, cls): return adapter return None @staticmethod def _find_code_stack(): framerecords = inspect.stack() for framerecord in framerecords: name = framerecord[0].f_code.co_name # type: str if name.startswith("test"): return name return None _default_gold_file_test = GoldenFileTest(Path('.') / "pyautest_assets", basic_adapters) def golden_file_test(name: str, obj: Any) -> bool: return _default_gold_file_test(name, obj)
b5abfe01419986db825a86397318c45516c2d8f0
814df4c836843382dc9aecc907da7e2d8e824b53
/Decryption_Server.py
96d28a363a72f441e1d8b007236ed04a4704894e
[]
no_license
Aditya-Ramachandran/RSA_Cryptography
ed6909dc359a6f949f0a91d24ed047354918df63
18f6b1a30250573286488244cc832d0883ebba10
refs/heads/master
2022-12-09T21:31:37.320591
2020-09-08T16:23:11
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from __future__ import unicode_literals import socket from math import sqrt import random from random import randint as rand import pickle host = socket.gethostname() port = 5000 s = socket.socket() s.bind((host, port)) s.listen(2) def gcd(a, b): if b == 0: return a else: return gcd(b, a % b) def mod_inverse(a, m): for x in range(1, m): if (a * x) % m == 1: return x return -1 def isprime(n): if n < 2: return False elif n == 2: return True else: for i in range(1, int(sqrt(n)) + 1): if n % i == 0: return False return True #initial two random numbers p,q p = rand(1, 1000) q = rand(1, 1000) def generate_keypair(p, q,keysize): # keysize is the bit length of n so it must be in range(nMin,nMax+1). # << is bitwise operator # x << y is same as multiplying x by 2**y # i am doing this so that p and q values have similar bit-length. # this will generate an n value that's hard to factorize into p and q. nMin = 1<<(keysize-1) nMax = (1<<keysize) - 1 primes=[2] # we choose two prime numbers in range(start, stop) so that the difference of bit lengths is at most 2. start = 1<<(keysize//2-1) stop = 1<<(keysize//2+1) if start >= stop: return [] for i in range(3, stop + 1, 2): for p in primes: if i % p == 0: break else: primes.append(i) while(primes and primes[0] < start): del primes[0] #choosing p and q from the generated prime numbers. while primes: p = random.choice(primes) primes.remove(p) q_values = [q for q in primes if nMin <= p * q <= nMax] if q_values: q = random.choice(q_values) break n = p * q phi = (p - 1) * (q - 1) #generate public key 1<e<phi(n) e = random.randrange(1, phi) g = gcd(e, phi) #as long as gcd(1,phi(n)) is not 1, keep generating e while True: e = random.randrange(1, phi) g = gcd(e, phi) #generate private key d = mod_inverse(e, phi) if g==1 and e!=d: break #public key (e,n) #private key (d,n) return ((e, n), (d, n)) def decrypt(msg_ciphertext, package): d, n = package msg_plaintext = [chr(pow(c, d, n)) for c in msg_ciphertext] # No need to use ord() since c is now a number # After decryption, we cast it back to character # to be joined in a string for the final result return (''.join(msg_plaintext)) public, private = generate_keypair(p, q, 8) print(host) conn, address = s.accept() print("Connected to: " + str(address)) conn.send(str(public[0]).encode()) conn.send(str(public[1]).encode()) print("Public Key: ",public) while True: encoded_data = pickle.loads(conn.recv(1024*4)) for i in range(len(encoded_data)): encoded_data[i]=int(encoded_data[i]) if not encoded_data: break #print(''.join(map(lambda x: str(x), encoded_data))) decoded_data = decrypt(encoded_data, private) print("Client : " + str(decoded_data)) conn.close()
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d9a84de5d6abc39a6a0352695e1495108f9a677e
/hab/cutdown/nichromeCutdownController.py
2452cb4839d832112fd60d9081bf145860a4abab
[]
no_license
wmsi/hab-scripts
9f60169881937ad1efb399902a70c6c08171a188
1d2e6756ab3a18e79d55ba09e6be9352d4cf71b8
refs/heads/master
2021-01-01T19:41:14.389885
2018-03-02T13:53:24
2018-03-02T13:53:24
98,650,044
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#!/usr/bin/env python """ ################################################################################ Written by Nicholas Sullo while working at WMSI 8/17/2015 Modified heavily by Mckenna Cisler ([email protected]) while working at WMSI 7/31/2017, to use the nichrome cutdown method Refer to http://abyz.co.uk/rpi/pigpio/ for more information and example code for the pigpio library IMPLEMENTATION NOTE (Mckenna): An obvious solution to reading the logfile data is to keep the file open over the entire course of the program, using log.readlines() to only read the NEW lines. However, my fear with this solution is if the file somehow gets corrupted or overwritten from the beginning, in which case the program, sitting at a seek position 500 lines down, has to wait for 500 telem strings before parsing another, at which point we may be thousands of feet above the desired cutdown. ################################################################################ """ import time import re import sys import re from nichromeControl import Nichrome ################################ CONSTANTS #################################### MAX_ALTITUDE = 480 # Set the maximum altitude (in meters) HERE! HAB_TELEM_FILE = '/home/pi/pits/tracker/telemetry.txt' HAB_TELEM_BACKUP = '/home/pi/pits/tracker/telemetrydata.txt' # where to dump log data ############################################################################### def loginfo(msg): newMsg = time.strftime("%x %X %Z | ") + msg print newMsg def process_telemetry_string(telem, nichrome): """ Extracts and anaylzes the altitude from a raw telemetry string """ telemFields = telem.split(",") try: # Check to make sure the string is actually the telemetry data. # This will have to be changed based on what you name your payload if re.match("\$\$\w{1,10}", telemFields[0]) != None: # The 6th field in the telemetry string is the altitude # (Turn the string altitude value into an integer) alt = int(telemFields[5]) loginfo("altitude: {:>4} m (target: {} m)".format(alt, MAX_ALTITUDE)) # Make sure this altitude is not larger than the predetermined cut down altitude if alt >= MAX_ALTITUDE: nichrome.activate() return True # Continue on parsing errors except IndexError or ValueError: return False # not done if we're below max altitude return False def main(): loginfo("Starting controller...") nichrome = Nichrome() """ Reads telemetry lines from a logfile and transfers them to a backup file """ while True: # continually deactivate nichrome to make sure we don't get any spikes nichrome.deactivate() # Make sure to re-open files becasue otherwise, if one is deleted, # we will stop writing to it # This opens the log file the Pi in the sky saves to with open(HAB_TELEM_FILE, 'r+') as log: # This opens a file to move the telemetry data to with open(HAB_TELEM_BACKUP, 'a') as logout: # Read what lines we have # (from the seek position, which we enforce to be 0) log.seek(0) telemetry = log.readlines() # IMMEDIATELY remove the lines we just read # (I was inclined to delete the lines after everything had # finished with the idea that if the lines below had an exception, # we could re-read the data. However, I realized that it is likely # that something about that data caused the error, so it's best # to skip it the next time around. Additionally, clearning them # below has a chance of overwriting a new line of data that had # been added to the file in the interim, though this is unlikely) log.seek(0) log.truncate() # transfer lines from log file to logout file logout.writelines(telemetry) # process the lines for line in telemetry: done = process_telemetry_string(line, nichrome) # After we lose the balloon, there is no reason for this # program to continue running, so break out of all loops if done: loginfo("Keeping nichrome pulled low after cutdown.") keepNichromeLow(nichrome) # delay for a short bit time.sleep(0.25) def keepNichromeLow(nichrome): """ Sleeps forever, periodically forcing nichrome to stay low (deactivated) """ while True: loginfo("Deactivating nichrome again...") nichrome.deactivate() time.sleep(2) def create_telemetry_file(): """ Creates the telemetry file if it isn't there """ loginfo("Creating telem file if it doesn't exist...") with open(HAB_TELEM_FILE, "w"): pass while True: # restart on any exception try: create_telemetry_file() main() break # if we finish gracefully, quit except SyntaxError as e: loginfo("SYNTAX ERROR: {}".format(e)) break except KeyboardInterrupt: break except: exc_type, exc_value, exc_traceback = sys.exc_info() loginfo("RUNTIME ERROR ({}): {}".format(exc_type, exc_value)) continue
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ea759ab6c37c83c06c0af127fa3169e912ef25d2
/cnn_cascade_lasagne.py
be272bde0110dcc0da710b2caddd7d8bf9a23e2f
[]
no_license
Soledad89/Cascade-CNN-Face-Detection
74d1178fc042b91a46ddc5affe9e1d190d813e70
a75bcb74f763bdba851398c6096dbc058f5c2021
refs/heads/master
2021-01-12T06:51:29.560884
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# -*- coding: utf-8 -*- """ Created on Tue May 31 20:20:22 2016 @author: Kostya """ from lasagne.nonlinearities import softmax, rectify as relu from lasagne import layers from lasagne import updates from lasagne import regularization from lasagne import objectives from time import time from six.moves import cPickle as pickle from util import Util as util from sklearn.cross_validation import train_test_split import theano import theano.tensor as T import scipy as sp import sys sys.setrecursionlimit(10000) class Cnn(object): net = None subnet = None nn_name = '' l_rates = [] max_epochs = 120 batch_size = 256 verbose = 0 eta = None __train_fn__ = None # create classifcation nets def __build_12_net__(self): network = layers.InputLayer((None, 3, 12, 12), input_var=self.__input_var__) network = layers.dropout(network, p=0.1) network = layers.Conv2DLayer(network,num_filters=16,filter_size=(3,3),stride=1,nonlinearity=relu) network = layers.batch_norm(network) network = layers.MaxPool2DLayer(network, pool_size = (3,3),stride = 2) network = layers.DropoutLayer(network,p=0.3) network = layers.DenseLayer(network,num_units = 16,nonlinearity = relu) network = layers.batch_norm(network) network = layers.DropoutLayer(network,p=0.3) network = layers.DenseLayer(network,num_units = 2, nonlinearity = softmax) return network def __build_24_net__(self): network = layers.InputLayer((None, 3, 24, 24), input_var=self.__input_var__) network = layers.dropout(network, p=0.1) network = layers.Conv2DLayer(network,num_filters=64,filter_size=(5,5),stride=1,nonlinearity=relu) network = layers.batch_norm(network) network = layers.MaxPool2DLayer(network, pool_size = (3,3),stride = 2) network = layers.DropoutLayer(network,p=0.5) network = layers.batch_norm(network) network = layers.DenseLayer(network,num_units = 64,nonlinearity = relu) network = layers.DropoutLayer(network,p=0.5) network = layers.DenseLayer(network,num_units = 2, nonlinearity = softmax) return network def __build_48_net__(self): network = layers.InputLayer((None, 3, 48, 48), input_var=self.__input_var__) network = layers.Conv2DLayer(network,num_filters=64,filter_size=(5,5),stride=1,nonlinearity=relu) network = layers.MaxPool2DLayer(network, pool_size = (3,3),stride = 2) network = layers.batch_norm(network) network = layers.Conv2DLayer(network,num_filters=64,filter_size=(5,5),stride=1,nonlinearity=relu) network = layers.batch_norm(network) network = layers.MaxPool2DLayer(network, pool_size = (3,3),stride = 2) network = layers.Conv2DLayer(network,num_filters=64,filter_size=(3,3),stride=1,nonlinearity=relu) network = layers.batch_norm(network) network = layers.MaxPool2DLayer(network, pool_size = (3,3),stride = 2) network = layers.DenseLayer(network,num_units = 256,nonlinearity = relu) network = layers.DenseLayer(network,num_units = 2, nonlinearity = softmax) return network def __build_12_calib_net__(self): network = layers.InputLayer((None, 3, 12, 12), input_var=self.__input_var__) network = layers.Conv2DLayer(network,num_filters=16,filter_size=(3,3),stride=1,nonlinearity=relu) network = layers.MaxPool2DLayer(network, pool_size = (3,3),stride = 2) network = layers.DenseLayer(network,num_units = 128,nonlinearity = relu) network = layers.DenseLayer(network,num_units = 45, nonlinearity = softmax) return network def __build_24_calib_net__(self): network = layers.InputLayer((None, 3, 24, 24), input_var=self.__input_var__) network = layers.Conv2DLayer(network,num_filters=32,filter_size=(5,5),stride=1,nonlinearity=relu) network = layers.MaxPool2DLayer(network, pool_size = (3,3),stride = 2) network = layers.DenseLayer(network,num_units = 64,nonlinearity = relu) network = layers.DenseLayer(network,num_units = 45, nonlinearity = softmax) return network def __build_48_calib_net__(self): network = layers.InputLayer((None, 3, 48, 48), input_var=self.__input_var__) network = layers.Conv2DLayer(network,num_filters=64,filter_size=(5,5),stride=1,nonlinearity=relu) network = layers.batch_norm(layers.MaxPool2DLayer(network, pool_size = (3,3),stride = 2)) network = layers.Conv2DLayer(network,num_filters=64,filter_size=(5,5),stride=1,nonlinearity=relu) network = layers.batch_norm(layers.MaxPool2DLayer(network, pool_size = (3,3),stride = 2)) network = layers.DenseLayer(network,num_units = 256,nonlinearity = relu) network = layers.DenseLayer(network,num_units = 45, nonlinearity = softmax) return network def __build_loss_train__fn__(self): # create loss function prediction = layers.get_output(self.net) loss = objectives.categorical_crossentropy(prediction, self.__target_var__) loss = loss.mean() + 1e-4 * regularization.regularize_network_params(self.net, regularization.l2) val_acc = T.mean(T.eq(T.argmax(prediction, axis=1), self.__target_var__),dtype=theano.config.floatX) # create parameter update expressions params = layers.get_all_params(self.net, trainable=True) self.eta = theano.shared(sp.array(sp.float32(0.05), dtype=sp.float32)) update_rule = updates.nesterov_momentum(loss, params, learning_rate=self.eta, momentum=0.9) # compile training function that updates parameters and returns training loss self.__train_fn__ = theano.function([self.__input_var__,self.__target_var__], loss, updates=update_rule) self.__predict_fn__ = theano.function([self.__input_var__], layers.get_output(self.net,deterministic=True)) self.__val_fn__ = theano.function([self.__input_var__,self.__target_var__], [loss,val_acc]) def __init__(self,nn_name,batch_size=1024,freeze=1,l_rates = sp.float32(0.05)*sp.ones(512,dtype=sp.float32),verbose = 1,subnet= None): self.nn_name = nn_name self.subnet = subnet if subnet != None and freeze: self.subnet.__freeze__() self.batch_size = batch_size self.verbose = verbose self.l_rates = l_rates self.__input_var__ = T.tensor4('X'+self.nn_name[:2]) self.__target_var__ = T.ivector('y+'+self.nn_name[:2]) self.max_epochs = self.l_rates.shape[0] if self.nn_name == '12-net': self.net = self.__build_12_net__() elif self.nn_name == '24-net': self.net = self.__build_24_net__() elif self.nn_name == '48-net': self.net = self.__build_48_net__() elif self.nn_name =='12-calib_net': self.net = self.__build_12_calib_net__() elif self.nn_name =='24-calib_net': self.net = self.__build_24_calib_net__() elif self.nn_name =='48-calib_net': self.net = self.__build_48_calib_net__() self.__build_loss_train__fn__() def iterate_minibatches(self,X, y, batchsize, shuffle=False): assert len(X) == len(y) if shuffle: indices = sp.arange(len(X)) sp.random.shuffle(indices) for start_idx in range(0, len(X) - batchsize + 1, batchsize): if shuffle: excerpt = indices[start_idx:start_idx + batchsize] else: excerpt = slice(start_idx, start_idx + batchsize) yield X[excerpt], y[excerpt] def __freeze__(self): for layer in layers.get_all_layers(self.net): for param in layer.params: layer.params[param].discard('trainable') def train_on_hdd(self,rootdir = '12-net/'): print(self.nn_name,'training start...','data folder',rootdir) mean_acc = 0 total_time = 0 bpaths = util.get_files(rootdir = rootdir,fexpr = '*.npz') m = len(bpaths) r = len(util.load_from_npz(bpaths [-1])) total_len = m * len(util.load_from_npz(bpaths [0])) print('data input size is around',total_len) for epoch in range(self.max_epochs): self.eta.set_value(self.l_rates[epoch]) t_loss = 0 start = time() for bpath in bpaths: batch = util.load_from_npz(bpath) items,labels = batch[:,0],batch[:,1] items = sp.array([e.astype(sp.float32) for e in items]) labels = labels.astype(sp.int32) X_train, X_val, y_train, y_val = train_test_split(items,labels,test_size = 0.25) t_loss += self.__train_fn__ (X_train,y_train) val_acc = 0 val_batches = 0 for xval,yval in self.iterate_minibatches(X_val,y_val,16): err, acc = self.__val_fn__(xval, yval) val_acc += acc val_batches += 1 if self.verbose: dur = time() - start a0 = 100*(val_acc/val_batches) mean_acc += a0 total_time += dur print("epoch %d out of %d \t loss %g \t acсuracy %g \t time %d s \t" % (epoch + 1,self.max_epochs, t_loss / (total_len),a0,dur)) m = (total_time)//60 s = total_time - 60 * m h = m//60 m = m - 60 * h mean_acc = mean_acc / self.max_epochs print('Training end with total time %d h %d m %d s and mean accouracy over epochs %g' % (h,m,s,mean_acc)) def fit(self,X,y): X = X.astype(sp.float32) y = y.astype(sp.int32) total_time = 0 mean_acc = 0 print(self.nn_name,'training start...') for epoch in range(self.max_epochs): self.eta.set_value(self.l_rates[epoch]) t_loss = 0 start = time() for input_batch, target in self.iterate_minibatches(X,y,self.batch_size): X_train, X_val, y_train, y_val = train_test_split(input_batch, target,test_size = 0.1) t_loss += self.__train_fn__ (X_train,y_train) val_acc = 0 val_batches = 0 for xval,yval in self.iterate_minibatches(X_val,y_val,16): err, acc = self.__val_fn__(xval, yval) val_acc += acc val_batches += 1 if self.verbose: dur = time() - start a0 = 100*(val_acc/val_batches) mean_acc += a0 total_time += dur print("epoch %d out of %d \t loss %g \t acсuracy %g \t time %d s \t" % (epoch + 1,self.max_epochs, t_loss / (len(X)),100*(val_acc/val_batches),dur)) m = (total_time)//60 s = total_time - 60 * m h = m//60 m = m - 60 * h mean_acc = mean_acc / self.max_epochs print('Training end with total time %d h %d m %d s and mean accouracy over epochs %g' % (h,m,s,mean_acc)) def predict(self,X): proba = self.predict_proba(X=X) y_pred = sp.argmax(proba,axis=1) return sp.array(y_pred) def predict_proba(self,X,X12 = None,X24 = None): proba = [] N = max(1,self.batch_size) for x_chunk in [X[i:i + N] for i in range(0, len(X), N)]: chunk_proba = self.__predict_fn__(x_chunk) for p in chunk_proba: proba.append(p) return sp.array(proba) def __save_model_old__(self,model_name = nn_name+'.pickle'): with open(model_name, 'wb') as f: pickle.dump(self, f, -1) def __load_model_old__(self,model_name = nn_name+'.pickle'): with open(model_name, 'rb') as f: model = pickle.load(f) f.close() return model def save_model(self,model_name = nn_name+'.npz'): sp.savez(model_name, *layers.get_all_param_values(self.net)) def load_model(self,model_name = nn_name+'.npz'): print(model_name,'is loaded') with sp.load(model_name) as f: param_values = [f['arr_%d' % i] for i in range(len(f.files))] layers.set_all_param_values(self.net, param_values) return self
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from sdk import Attachment class Message: def __init__(self, recipient, message, notification_type=None): if type(message) is str: message = {'text': message} elif type(message) is Attachment: message = {'attachment': message.json} self.json = {k: (v) for k, v in locals().items() if v is not None} del self.json['self'] if len(self.json) == 0: raise ValueError('Both text and attachment are None') for k, v in self.json.items(): if hasattr(v, 'json'): self.json[k] = v.json
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from rest_framework import generics from blog.models import BlogEntry from blog.serializers import BlogSerializer class BlogAPIList(generics.ListAPIView): queryset = BlogEntry.objects.filter(status=BlogEntry.PUBLISHED) serializer_class = BlogSerializer class BlogAPIDetail(generics.RetrieveAPIView): queryset = BlogEntry.objects.filter(status=BlogEntry.PUBLISHED) serializer_class = BlogSerializer
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# -*- coding: utf-8 -*- # Generated by Django 1.10.6 on 2017-03-12 23:45 from __future__ import unicode_literals from django.db import migrations, models import utils.dates import uuid class Migration(migrations.Migration): initial = True dependencies = [ ] operations = [ migrations.CreateModel( name='Region', fields=[ ('id', models.UUIDField(default=uuid.uuid4, editable=False, primary_key=True, serialize=False)), ('created_at', models.DateTimeField(default=utils.dates.utcnow)), ('name', models.CharField(max_length=200)), ], ), ]
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"""cars URL Configuration The `urlpatterns` list routes URLs to views. For more information please see: https://docs.djangoproject.com/en/3.1/topics/http/urls/ Examples: Function views 1. Add an import: from my_app import views 2. Add a URL to urlpatterns: path('', views.home, name='home') Class-based views 1. Add an import: from other_app.views import Home 2. Add a URL to urlpatterns: path('', Home.as_view(), name='home') Including another URLconf 1. Import the include() function: from django.urls import include, path 2. Add a URL to urlpatterns: path('blog/', include('blog.urls')) """ from django.contrib import admin from django.urls import path from carsapi.views import CarsView, PopularCarsView, Rate urlpatterns = [ path('admin/', admin.site.urls), path('cars/', CarsView.as_view(), name='cars'), path('popular/', PopularCarsView.as_view(), name='popular'), path('rate/', Rate.as_view(), name='rate') ]
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import numpy as np import matplotlib.pyplot as plt plt.figure (1) index = [0.3,0.8] plt.bar(index,[0.212,0.002],0.25,alpha = 0.8,color = 'b') plt.ylabel('time(ms)') plt.title('') plt.xticks( np.add(index,0.5 * 0.25),('train','test')) plt.legend() #plt.savefig('wind_Power_Usage_Diagram.png',dpi = 600) plt.show()
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import numpy as np import matplotlib.pyplot as plt class simulation: def __init__(self,action_num,method): self.action_num = action_num self._method = method self.ACTIONS = [[0,1],[i for i in range(action_num)]] if self._method == 'Q': self.Q_values = [[0.0, 0.0], [0.0 for i in range(action_num)]] else: self.Q1_values = [[0.0,0.0],[0.0 for i in range(action_num)]] self.Q2_values = [[0.0, 0.0], [0.0 for i in range(action_num)]] def choose_action(self,state): e = np.random.random() if e < EPSILON: action = np.random.choice(self.ACTIONS[state]) else: if self._method == 'Q': action = np.random.choice(np.flatnonzero(self.Q_values[state] == np.max(self.Q_values[state]))) else: action_values = np.array(self.Q1_values[state])+np.array(self.Q2_values[state]) action = np.random.choice(np.flatnonzero(action_values == np.max(action_values))) return action def determine_transition(self,cur_state,action): next_state = None ended = True if cur_state == 0: reward = 0 if action == 0: next_state = 1 ended = False if cur_state == 1: reward = np.random.normal(-0.1, 1) return next_state,reward,ended def update_QValues(self,curr_state,action,reward,next_state): if self._method == 'Q': if next_state == None: self.Q_values[curr_state][action] += ALFA * (reward - self.Q_values[curr_state][action]) else: max_nextQValue = np.max(self.Q_values[next_state]) self.Q_values[curr_state][action] += ALFA * ( reward + GAMMA * max_nextQValue - self.Q_values[curr_state][action]) else: e = np.random.random() if e<0.5: if next_state == None: self.Q1_values[curr_state][action]+=ALFA*(reward-self.Q1_values[curr_state][action]) else: max_nextQValue = self.Q2_values[next_state][np.argmax(self.Q1_values[next_state])] self.Q1_values[curr_state][action] += ALFA * (reward + GAMMA*max_nextQValue- self.Q1_values[curr_state][action]) else: if next_state == None: self.Q2_values[curr_state][action]+=ALFA*(reward-self.Q2_values[curr_state][action]) else: max_nextQValue = self.Q1_values[next_state][np.argmax(self.Q2_values[next_state])] self.Q2_values[curr_state][action] += ALFA * (reward + GAMMA*max_nextQValue- self.Q2_values[curr_state][action]) def run_simulation(self): episode_direction = [] for episode in range(EPISODES): curr_state = 0 while True: action = self.choose_action(curr_state) next_state, reward, episode_ended= self.determine_transition(curr_state, action) self.update_QValues(curr_state,action,reward,next_state) if episode_ended: episode_direction.append(1 if curr_state == 1 else 0) break curr_state = next_state return 100*np.divide(np.cumsum(episode_direction),np.arange(1,EPISODES+1)) EPSILON = 0.1 B_ACTION_CHOICE = [1,2,5,10,100] ALFA = 0.1 GAMMA = 1 EPISODES = 300 RUNS = 10000 Percentage_left_actions = np.zeros((len(B_ACTION_CHOICE),EPISODES)) method = 'DQ' # Use Q if using just Q and use 'DQ' if using Double-Q for run in range(RUNS): if run in np.arange(0,RUNS,RUNS/10): print('Run number = {}'.format(run)) for i,action_num in enumerate(B_ACTION_CHOICE): Sim = simulation(action_num,method) Percentage_left_actions[i,:]+=Sim.run_simulation() Percentage_left_actions/=RUNS fig = plt.figure(figsize=(8,10)) Actions_Plot = plt.subplot() for i,action_choice in enumerate(B_ACTION_CHOICE): Actions_Plot.plot(np.arange(1,EPISODES+1),Percentage_left_actions[i],label = '{}'.format(action_choice)) Actions_Plot.set_xticks([1,100,200,300]) Actions_Plot.set_yticks([0,5,25,50,75,100]) Actions_Plot.set_ylabel('% left actions from A') Actions_Plot.set_xlabel('Episodes') Actions_Plot.legend(title = 'Number of actions in B')
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#!/sw/bin/python2.7 ''' zbdump - a tcpdump-like tool for ZigBee/IEEE 802.15.4 networks Compatible with Wireshark 1.1.2 and later ([email protected]) The -p flag adds CACE PPI headers to the PCAP ([email protected]) ''' import sys import signal import argparse from killerbee import * def interrupt(signum, frame): global packetcount global kb global pd, dt kb.sniffer_off() kb.close() if pd: pd.close() if dt: dt.close() print("{0} packets captured".format(packetcount)) sys.exit(0) # PcapDumper, only used if -w is specified pd = None # DainTreeDumper, only used if -W is specified dt = None # Global packetcount = 0 # Command-line arguments parser = argparse.ArgumentParser(description=__doc__) parser.add_argument('-i', '--iface', '--dev', action='store', dest='devstring') #parser.add_argument('-g', '--gps', '--ignore', action='append', dest='ignore') parser.add_argument('-w', '--pcapfile', action='store') parser.add_argument('-W', '--dsnafile', action='store') parser.add_argument('-p', '--ppi', action='store_true') parser.add_argument('-c', '-f', '--channel', action='store', type=int, default=None) parser.add_argument('-n', '--count', action='store', type=int, default=-1) parser.add_argument('-D', action='store_true', dest='showdev') args = parser.parse_args() if args.showdev: show_dev() sys.exit(0) if args.channel == None: print >>sys.stderr, "ERROR: Must specify a channel." sys.exit(1) if args.pcapfile is None and args.dsnafile is None: print >>sys.stderr, "ERROR: Must specify a savefile with -w (libpcap) or -W (Daintree SNA)" sys.exit(1) elif args.pcapfile is not None: pd = PcapDumper(DLT_IEEE802_15_4, args.pcapfile, ppi=args.ppi) elif args.dsnafile is not None: dt = DainTreeDumper(args.dsnafile) kb = KillerBee(device=args.devstring) signal.signal(signal.SIGINT, interrupt) if not kb.is_valid_channel(args.channel): print >>sys.stderr, "ERROR: Must specify a valid IEEE 802.15.4 channel for the selected device." kb.close() sys.exit(1) kb.set_channel(args.channel) kb.sniffer_on() print("zbdump: listening on \'{0}\', link-type DLT_IEEE802_15_4, capture size 127 bytes".format(kb.get_dev_info()[0])) rf_freq_mhz = (args.channel - 10) * 5 + 2400 while args.count != packetcount: packet = kb.pnext() # packet[1] is True if CRC is correct, check removed to have promiscous capture regardless of CRC if packet != None: # and packet[1]: packetcount+=1 if pd: pd.pcap_dump(packet['bytes'], ant_dbm=packet['dbm'], freq_mhz=rf_freq_mhz) if dt: dt.pwrite(packet['bytes']) kb.sniffer_off() kb.close() if pd: pd.close() if dt: dt.close() print("{0} packets captured".format(packetcount))
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version_info = (0, 8, 2) __version__ = version = '.'.join(map(str, version_info)) __project__ = PROJECT = 'django-summernote' __author__ = AUTHOR = "Park Hyunwoo <[email protected]>" default_app_config = 'django_summernote.apps.DjangoSummernoteConfig'
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def search_el(arr, left_idx, right_idx, el): middle_idx = (left_idx + right_idx) / 2 if arr[middle_idx] == el: return middle_idx if left_idx == right_idx: return False elif arr[middle_idx] < el: return search_el(arr, middle_idx + 1, right_idx, el) elif arr[middle_idx] > el: return search_el(arr, left_idx, middle_idx - 1, el) def binary_search(arr, el): left_idx = 0 right_idx = len(arr) - 1 idx = search_el(arr, left_idx, right_idx, el) return idx if __name__ == "__main__": arr = [1,2,3,4,5,6,7,8] el = 7 #idx = 6 el = 2 el = 0 el = 9 el = 8 el = 1 idx = binary_search(arr, el) print(idx, arr[idx])
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# coding=utf-8 # *** WARNING: this file was generated by the Pulumi SDK Generator. *** # *** Do not edit by hand unless you're certain you know what you are doing! *** import warnings import pulumi import pulumi.runtime from typing import Any, Mapping, Optional, Sequence, Union, overload from ... import _utilities from . import outputs __all__ = [ 'GetEventSubscriptionResult', 'AwaitableGetEventSubscriptionResult', 'get_event_subscription', ] @pulumi.output_type class GetEventSubscriptionResult: """ Event Subscription """ def __init__(__self__, dead_letter_destination=None, destination=None, event_delivery_schema=None, expiration_time_utc=None, filter=None, id=None, labels=None, name=None, provisioning_state=None, retry_policy=None, topic=None, type=None): if dead_letter_destination and not isinstance(dead_letter_destination, dict): raise TypeError("Expected argument 'dead_letter_destination' to be a dict") pulumi.set(__self__, "dead_letter_destination", dead_letter_destination) if destination and not isinstance(destination, dict): raise TypeError("Expected argument 'destination' to be a dict") pulumi.set(__self__, "destination", destination) if event_delivery_schema and not isinstance(event_delivery_schema, str): raise TypeError("Expected argument 'event_delivery_schema' to be a str") pulumi.set(__self__, "event_delivery_schema", event_delivery_schema) if expiration_time_utc and not isinstance(expiration_time_utc, str): raise TypeError("Expected argument 'expiration_time_utc' to be a str") pulumi.set(__self__, "expiration_time_utc", expiration_time_utc) if filter and not isinstance(filter, dict): raise TypeError("Expected argument 'filter' to be a dict") pulumi.set(__self__, "filter", filter) if id and not isinstance(id, str): raise TypeError("Expected argument 'id' to be a str") pulumi.set(__self__, "id", id) if labels and not isinstance(labels, list): raise TypeError("Expected argument 'labels' to be a list") pulumi.set(__self__, "labels", labels) if name and not isinstance(name, str): raise TypeError("Expected argument 'name' to be a str") pulumi.set(__self__, "name", name) if provisioning_state and not isinstance(provisioning_state, str): raise TypeError("Expected argument 'provisioning_state' to be a str") pulumi.set(__self__, "provisioning_state", provisioning_state) if retry_policy and not isinstance(retry_policy, dict): raise TypeError("Expected argument 'retry_policy' to be a dict") pulumi.set(__self__, "retry_policy", retry_policy) if topic and not isinstance(topic, str): raise TypeError("Expected argument 'topic' to be a str") pulumi.set(__self__, "topic", topic) if type and not isinstance(type, str): raise TypeError("Expected argument 'type' to be a str") pulumi.set(__self__, "type", type) @property @pulumi.getter(name="deadLetterDestination") def dead_letter_destination(self) -> Optional['outputs.StorageBlobDeadLetterDestinationResponse']: """ The DeadLetter destination of the event subscription. """ return pulumi.get(self, "dead_letter_destination") @property @pulumi.getter def destination(self) -> Optional[Any]: """ Information about the destination where events have to be delivered for the event subscription. """ return pulumi.get(self, "destination") @property @pulumi.getter(name="eventDeliverySchema") def event_delivery_schema(self) -> Optional[str]: """ The event delivery schema for the event subscription. """ return pulumi.get(self, "event_delivery_schema") @property @pulumi.getter(name="expirationTimeUtc") def expiration_time_utc(self) -> Optional[str]: """ Expiration time of the event subscription. """ return pulumi.get(self, "expiration_time_utc") @property @pulumi.getter def filter(self) -> Optional['outputs.EventSubscriptionFilterResponse']: """ Information about the filter for the event subscription. """ return pulumi.get(self, "filter") @property @pulumi.getter def id(self) -> str: """ Fully qualified identifier of the resource """ return pulumi.get(self, "id") @property @pulumi.getter def labels(self) -> Optional[Sequence[str]]: """ List of user defined labels. """ return pulumi.get(self, "labels") @property @pulumi.getter def name(self) -> str: """ Name of the resource """ return pulumi.get(self, "name") @property @pulumi.getter(name="provisioningState") def provisioning_state(self) -> str: """ Provisioning state of the event subscription. """ return pulumi.get(self, "provisioning_state") @property @pulumi.getter(name="retryPolicy") def retry_policy(self) -> Optional['outputs.RetryPolicyResponse']: """ The retry policy for events. This can be used to configure maximum number of delivery attempts and time to live for events. """ return pulumi.get(self, "retry_policy") @property @pulumi.getter def topic(self) -> str: """ Name of the topic of the event subscription. """ return pulumi.get(self, "topic") @property @pulumi.getter def type(self) -> str: """ Type of the resource """ return pulumi.get(self, "type") class AwaitableGetEventSubscriptionResult(GetEventSubscriptionResult): # pylint: disable=using-constant-test def __await__(self): if False: yield self return GetEventSubscriptionResult( dead_letter_destination=self.dead_letter_destination, destination=self.destination, event_delivery_schema=self.event_delivery_schema, expiration_time_utc=self.expiration_time_utc, filter=self.filter, id=self.id, labels=self.labels, name=self.name, provisioning_state=self.provisioning_state, retry_policy=self.retry_policy, topic=self.topic, type=self.type) def get_event_subscription(event_subscription_name: Optional[str] = None, scope: Optional[str] = None, opts: Optional[pulumi.InvokeOptions] = None) -> AwaitableGetEventSubscriptionResult: """ Event Subscription :param str event_subscription_name: Name of the event subscription :param str scope: The scope of the event subscription. The scope can be a subscription, or a resource group, or a top level resource belonging to a resource provider namespace, or an EventGrid topic. For example, use '/subscriptions/{subscriptionId}/' for a subscription, '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}' for a resource group, and '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/{resourceProviderNamespace}/{resourceType}/{resourceName}' for a resource, and '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.EventGrid/topics/{topicName}' for an EventGrid topic. """ __args__ = dict() __args__['eventSubscriptionName'] = event_subscription_name __args__['scope'] = scope if opts is None: opts = pulumi.InvokeOptions() if opts.version is None: opts.version = _utilities.get_version() __ret__ = pulumi.runtime.invoke('azure-native:eventgrid/v20200101preview:getEventSubscription', __args__, opts=opts, typ=GetEventSubscriptionResult).value return AwaitableGetEventSubscriptionResult( dead_letter_destination=__ret__.dead_letter_destination, destination=__ret__.destination, event_delivery_schema=__ret__.event_delivery_schema, expiration_time_utc=__ret__.expiration_time_utc, filter=__ret__.filter, id=__ret__.id, labels=__ret__.labels, name=__ret__.name, provisioning_state=__ret__.provisioning_state, retry_policy=__ret__.retry_policy, topic=__ret__.topic, type=__ret__.type)
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from rest_framework.viewsets import ModelViewSet from rest_framework.authentication import TokenAuthentication from rest_framework.permissions import IsAuthenticated # Create your views here. from contribution import serializers from core.models import Contribution class ContributionViewSet(ModelViewSet): """Manage Contributions in the db""" serializer_class = serializers.ContributionSerializer queryset = Contribution.objects.all() authentication_classes = (TokenAuthentication,) permission_classes = (IsAuthenticated,) def get_queryset(self): return self.queryset.filter(user=self.request.user) def perform_create(self, serializer): serializer.save(user=self.request.user) # class CreateContribution(CreateAPIView): # serializer_class = ContributionSerializer
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"""Test shell utils""" # pylint: disable=protected-access import logging import pytest from six.moves import zip from ultron8.utils.shell import quote_unix logger = logging.getLogger(__name__) @pytest.mark.utilsonly @pytest.mark.unittest class TestShellUtilsTestCase: def test_quote_unix(self): arguments = ["foo", "foo bar", "foo1 bar1", '"foo"', '"foo" "bar"', "'foo bar'"] expected_values = [ """ foo """, """ 'foo bar' """, """ 'foo1 bar1' """, """ '"foo"' """, """ '"foo" "bar"' """, """ ''"'"'foo bar'"'"'' """, ] for argument, expected_value in zip(arguments, expected_values): actual_value = quote_unix(value=argument) expected_value = expected_value.lstrip() assert actual_value == expected_value.strip()
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"""test_community URL Configuration The `urlpatterns` list routes URLs to views. For more information please see: https://docs.djangoproject.com/en/3.1/topics/http/urls/ Examples: Function views 1. Add an import: from my_app import views 2. Add a URL to urlpatterns: path('', views.home, name='home') Class-based views 1. Add an import: from other_app.views import Home 2. Add a URL to urlpatterns: path('', Home.as_view(), name='home') Including another URLconf 1. Import the include() function: from django.urls import include, path 2. Add a URL to urlpatterns: path('blog/', include('blog.urls')) """ from django.contrib import admin from django.urls import path, include from user.views import home urlpatterns = [ path('admin/', admin.site.urls), path('user/', include('user.urls')), path('', home), ]
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# Authored By: Jessie Burton #001356971 import RunRoute import UI # Created using PyCharm Community Edition 2020.1.3 x64 on a Lenovo Laptop Running Windows 10 on AMD hardware # only run this code if I am running as the main entry point of the application if __name__ == '__main__': # * Driver Main Class-- The dominate time complexity is O(n^3), worst case * class Main: # The primary use of dict data structure was used because 0(1) search feature and ability to self adjust its size to fit the data # Main Algorithm used is the Greedy Algorithm, self adjusting # O(n^2) + O(n^3) delivery_data = RunRoute.run_route() # O(n) UI.run_ui(delivery_data)
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import urllib.request import urllib from urllib.request import urlopen from bs4 import BeautifulSoup import pandas as pd def get_text(tag): if tag: return tag.text return None def crawling_indeed(): links_df = pd.read_csv("indeed_links.csv") hdr = {'User-Agent': 'Mozilla/5.0'} columns = ['company_name', 'nb_reviews', 'nb_jobs', 'overall_rating', 'work_life_balance', 'compensation_benefits', 'job_security', 'management', 'culture'] result_pd = pd.DataFrame(columns=columns) for index, row in links_df.iterrows(): link = row['link'] req = urllib.request.Request(link, headers=hdr) response = urlopen(req) soup = BeautifulSoup(response, 'html.parser') company_name = get_text(soup.select_one(".cmp-company-name")) nb_reviews = get_text( soup.select_one("#cmp-menu-container > ul > li:nth-of-type(2) > a > div")) nb_jobs = get_text( soup.select_one("#cmp-menu-container > ul > li:nth-of-type(5) > a > div")) overall_rating = get_text( soup.select_one(".cmp-average-rating")) work_life_balance = get_text( soup.select_one("#cmp-reviews-attributes > dd:nth-of-type(1) > span.cmp-star-rating")) compensation_benefits = get_text( soup.select_one("#cmp-reviews-attributes > dd:nth-of-type(2) > span.cmp-star-rating")) job_security = get_text( soup.select_one("#cmp-reviews-attributes > dd:nth-of-type(3) > span.cmp-star-rating")) management = get_text( soup.select_one("#cmp-reviews-attributes > dd:nth-of-type(4) > span.cmp-star-rating")) culture = get_text( soup.select_one("#cmp-reviews-attributes > dd:nth-of-type(5) > span.cmp-star-rating")) result_pd.loc[index] = [company_name, nb_reviews, nb_jobs, overall_rating, work_life_balance, compensation_benefits, job_security, management, culture] result_pd.to_csv("indeed_crawling_result.csv", index=False) crawling_indeed()
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import sys import numpy as np ftrain = str(sys.argv[1]) ftest = str(sys.argv[2]) fval = str(sys.argv[3]) # input file names traindata = [] with open('{0}'.format(ftrain), 'r') as f: # read training data nline = 0 for line in f.readlines(): nline = nline + 1 arr = line.replace('\n', '').split(',') traindata.append(map(int, arr)) traindata = np.array(traindata) mean, std = [], [] nfeat = len(traindata[0]) for i in range(nfeat): # find mean and std for each features of all training data mean.append(np.mean(traindata[:, i])) std.append(np.std(traindata[:, i])) testdata, valdata = [], [] normtrain, normtest, normval = [], [], [] with open('{0}'.format(ftest), 'r') as f: # read test data nline = 0 for line in f.readlines(): nline = nline + 1 arr = line.replace('\n', '').split(',') testdata.append(map(int, arr)) with open('{0}'.format(fval), 'r') as f: # read validation data nline = 0 for line in f.readlines(): nline = nline + 1 arr = line.replace('\n', '').split(',') valdata.append(map(int, arr)) testdata = np.array(testdata) valdata = np.array(valdata) for i in range(nfeat): # normalize data based on mean and std of training data if (std[i] != 0.0): traindata[:, i] = (traindata[:, i] - mean[i]) / float(std[i]) testdata[:, i] = (testdata[:, i] - mean[i]) / float(std[i]) valdata[:, i] = (valdata[:, i] - mean[i]) / float(std[i]) np.savetxt('norm_train.txt', traindata) np.savetxt('norm_test.txt', testdata) np.savetxt('norm_val.txt', valdata) np.savetxt('mean.txt', mean) np.savetxt('std.txt', std) # save normalized data into files
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from operator import attrgetter class User: def __init__(self, user_id): self.user_id = user_id def __repr__(self): return 'User({})'.format(self.user_id) # Przykład users = [User(23), User(3), User(99)] print(users) # Sortowanie według pola user-id print(sorted(users, key=attrgetter('user_id')))
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from dynamic.urls import urls from dynamic.utils import Response from utils import url_not_found def get_view_func_from_urls(environ, urls): for url in urls: if environ['PATH_INFO'].split('?')[0].strip('/') == url[0] and environ['REQUEST_METHOD'] == url[1]: return url[2] def generate_wsgi_response(start_response, response: Response): start_response(str(response.status), response.headers) return bytes(str(response.data), 'utf-8') def dispatch(environ, start_response): view_func = get_view_func_from_urls(environ, urls) if view_func: response = view_func(environ) return generate_wsgi_response(start_response, response) else: return url_not_found(start_response, environ['REQUEST_URI'])
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#Stephen Barton Jr #Python Programming, star pattern #22 APR 2019 def main(): for i in range(1,6): for j in range(1,i+1): print("*", end = " ") print() main()
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# Generated by Django 2.0.6 on 2018-07-05 23:29 from django.db import migrations, models import django.db.models.deletion class Migration(migrations.Migration): initial = True dependencies = [ ] operations = [ migrations.CreateModel( name='Cities', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('name', models.CharField(max_length=255)), ('latitude', models.DecimalField(decimal_places=8, max_digits=10)), ('longitude', models.DecimalField(decimal_places=8, max_digits=11)), ], ), migrations.CreateModel( name='Countries', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('name', models.CharField(max_length=255)), ('code', models.CharField(max_length=10)), ], ), migrations.CreateModel( name='States', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('name', models.CharField(max_length=255)), ('code', models.CharField(max_length=10)), ('country', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='location_management.Countries')), ], ), migrations.AddField( model_name='cities', name='country', field=models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='location_management.Countries'), ), migrations.AddField( model_name='cities', name='state', field=models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='location_management.States'), ), ]
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# -*- coding: utf-8 -*- """ Tencent is pleased to support the open source community by making 蓝鲸智云PaaS平台社区版 (BlueKing PaaS Community Edition) available. Copyright (C) 2017-2019 THL A29 Limited, a Tencent company. All rights reserved. Licensed under the MIT License (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://opensource.org/licenses/MIT Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. """ # noqa class ConfFixture(object): """ 登录模块项目变量汇总 """ ################# # 浏览器参数说明 # ################# # 登录模块,可选项为 components 目录下的模块,如 qcloud_tlogin BACKEND_TYPE = None # 用户验证 Backend qcloud_tlogin.backends.QPtloginBackend USER_BACKEND = None # 用户登录验证中间件 qcloud_tlogin.middlewares.LoginRequiredMiddleware LOGIN_REQUIRED_MIDDLEWARE = None # 用户模型 qcloud_tlogin.models.UserProxy USER_MODEL = None # 登录平台弹窗链接 http://xxxx.com/accounts/login_page/ CONSOLE_LOGIN_URL = None # 登录平台链接 http://login.o.qcloud.com LOGIN_URL = None # 内嵌式的登录平台链接(可嵌入弹框、IFrame)http://xxx.com/plain/ LOGIN_PLAIN_URL = None # 是否提供内嵌式的统一登录页面 HAS_PLAIN = True # 跳转至登录平台是否加跨域前缀标识 # http://xxx.com/login/?c_url={CROSS_PREFIX}http%3A//xxx.com%3A8000/ ADD_CROSS_PREFIX = True CROSS_PREFIX = '' # 跳转至登录平台是否加上APP_CODE # http://xxx.com/login/?c_url=http%3A//xxx.com%3A8000/&app_code=xxx ADD_APP_CODE = True # http://xxx.com/login/?c_url=http%3A//xxx.com%3A8000/&{APP_KEY}=xxx APP_KEY = 'app_code' SETTINGS_APP_KEY = 'APP_CODE' # 跳转至登录平台,回调参数名称 # http://xxx.com/login/?{C_URL}=http%3A//xxx.com%3A8000/ C_URL = 'c_url' # 内嵌式的登录平台的尺寸大小,决定前端适配的弹框大小 IFRAME_HEIGHT = 490 IFRAME_WIDTH = 460 ############### # 微信参数说明 # ############### # 登录模块 weixin WEIXIN_BACKEND_TYPE = None # 用户认证中间件 bk_ticket.middlewares.LoginRequiredMiddleware WEIXIN_MIDDLEWARE = None # 用户认证 Backend bk_ticket.backends.TicketBackend WEIXIN_BACKEND = None # 用户信息链接 http://xxx.com/user/weixin/get_user_info/ WEIXIN_INFO_URL = None # 用户 OAUTH 认证链接 https://xxx.com/connect/oauth2/authorize WEIXIN_OAUTH_URL = None # 在微信端的应用ID 'xxxx' WEIXIN_APP_ID = None
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name = "John Smith" print(name.lower()) print(name.upper()) print(name.title())
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import psyco psyco.full() class memoize: def __init__(self, function): self.function = function self.memoized = {} def __call__(self, *args): if args not in self.memoized: self.memoized[args] = self.function(*args) return self.memoized[args] def clear(self): self.memoized = {} def alloc(size, default = 0): return [default] * size def alloc2(r, c, default = 0): return [alloc(c, default)] * r def isset(a, bit): return ((a >> bit) & 1) > 0 def dig(c): return ord(c) - 48 def abs(x): if x<0: return -x; return x def area(x1, y1, x2, y2, x3, y3): return abs((x3-x1)*(y2-y1) - (x2-x1)*(y3-y1))/2 def bisection(f, lo, hi): """ finds the integer x where f(x)=0. assumes f is monotounous. """ while lo < hi: mid = (lo+hi)//2 midval = f(mid) if midval < 0: lo = mid+1 elif midval > 0: hi = mid else: return mid return None def minarg(f, args): min_val = None min_arg = None for a in args: temp=f(a) if min_arg==None or temp<min_val: min_val=temp min_arg=a return min_arg, min_val #mat[i] = lowest row for the row currently at position i def solve(): c=0 for i in range(N): #print mat, c #print "i=", i if mat[i]>i: for j in range(i+1, N): if mat[j]<=i: #print "replace", i, " with ", j mat.insert(i, mat[j]) #print mat del mat[j+1] #mat[j]=None c+=j-i break return c from time import time if __name__ == "__main__": def getInts(): return map(int, input.readline().rstrip('\n').split(' ')) def getFloats(): return map(float, input.readline().rstrip('\n').split(' ')) def getMatrix(rows): return [getInts() for _ in range(rows)] input, output = open("d:/gcj/in", "r"), open('d:/gcj/output', 'w') start_time=time() for case in range(1, int(input.readline()) + 1): N, = getInts() mat=[[int(d) for d in input.readline().rstrip('\n')] for _ in range(N)] for i in range(N): j=N-1 while j>0 and mat[i][j]==0: j-=1 mat[i]=j s="Case #%d: %d\n" % (case, solve()) print s output.write(s) print time()-start_time
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from selenium.webdriver.firefox.webdriver import WebDriver from fixture.session import SessionHelper from fixture.group import GroupHelper from fixture.new_cont import NContHelper class Application: def __init__(self): self.wd = WebDriver(capabilities={"marionette": False}) self.session = SessionHelper(self) self.group = GroupHelper(self) self.new_cont = NContHelper(self) def is_valid(self): try: self.wd.current_url return True except: return False def open_home_page(self): wd = self.wd wd.get("http://localhost/addressbook/") def destroy(self): self.wd.quit()
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config.bind('t', 'set-cmd-text -s :open -t') config.bind('O', 'set-cmd-text :open {url:pretty}') config.bind('h', 'tab-prev') config.bind('gT', 'tab-prev') config.bind('l', 'tab-next') config.bind('gt', 'tab-next') config.bind('b', 'set-cmd-text -s :tab-select') config.bind('gi', 'hint inputs') config.bind('<Ctrl-i>', 'open-editor', mode='insert') # config.bind('<Ctrl-u>', 'rl-unix-line-discard', mode='insert') # config.bind('<Ctrl-a>', 'rl-beginning-of-line', mode='insert') # config.bind('<Ctrl-e>', 'rl-end-of-line', mode='insert') # config.bind('<Ctrl-w>', 'rl-end-word-rubout', mode='insert') # c.content.proxy = 'socks://localhost:13659' # c.content.proxy = 'socks://localhost:1086' c.content.proxy = 'system' c.url.searchengines = { "g": "https://www.google.com/search?q={}", "d": "https://duckduckgo.com/?q={}", "b": "https://bing.com/search?q={}", "DEFAULT": "https://www.google.com/search?q={}", } c.tabs.position = 'left' c.auto_save.session = True # c.content.headers.user_agent = 'Mozilla/5.0 (X11; Linux x86_64; rv:83.0) Gecko/20100101 Firefox/99.0' # c.content.headers.user_agent = 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/83.0.0.0 Safari/537.36' c.content.headers.user_agent = 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/112.0.0.0 Safari/537.36' c.tabs.show = 'never' c.tabs.background = True c.aliases['np'] = 'set content.proxy none' c.aliases['p'] = 'set content.proxy "socks://localhost:13659"' c.aliases['readability'] = 'spawn --userscript readability-js' c.colors.webpage.darkmode.enabled = True # c.load_autoconfig(False)
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# a=[1,2,13,15,78,9,10,19,61,51,41,4] # b=[] # i=0 # sum=0 # while i<len(a): # k=a[i] # if k%2==0: # b.append(k) # sum=sum+1 # i=i+1 # print(b) # print(sum)
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import gym import numpy as np from agent import REINFORCEAgent scores = [] EPISODES = 1000 env = gym.make('CartPole-v0') agent = REINFORCEAgent(0.95, [4], 16, 16, 2, lr=1e-3) for episode in range(EPISODES): score = 0 done = False state = env.reset() while not done: action = agent.choose_action(state) next_state, reward, done, _ = env.step(action) agent.store_transition(state, action, reward, next_state, done) state = next_state score += reward agent.learn() agent.clear_memory() scores.append(score) print(f'Episode: {episode}, Score: {score}, Avg Score: {np.mean(scores[-100:])}')
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# encoding: utf-8 import datetime from south.db import db from south.v2 import SchemaMigration from django.db import models class Migration(SchemaMigration): def forwards(self, orm): # Adding field 'TidalEnergyParameter.ordering' db.add_column('scenario_tidalenergyparameter', 'ordering', self.gf('django.db.models.fields.IntegerField')(null=True, blank=True), keep_default=False) # Adding field 'PelagicConservationParameter.ordering' db.add_column('scenario_pelagicconservationparameter', 'ordering', self.gf('django.db.models.fields.IntegerField')(null=True, blank=True), keep_default=False) # Adding field 'OffshoreConservationParameter.ordering' db.add_column('scenario_offshoreconservationparameter', 'ordering', self.gf('django.db.models.fields.IntegerField')(null=True, blank=True), keep_default=False) # Adding field 'NearshoreConservationParameter.ordering' db.add_column('scenario_nearshoreconservationparameter', 'ordering', self.gf('django.db.models.fields.IntegerField')(null=True, blank=True), keep_default=False) # Adding field 'WaveEnergyParameter.ordering' db.add_column('scenario_waveenergyparameter', 'ordering', self.gf('django.db.models.fields.IntegerField')(null=True, blank=True), keep_default=False) def backwards(self, orm): # Deleting field 'TidalEnergyParameter.ordering' db.delete_column('scenario_tidalenergyparameter', 'ordering') # Deleting field 'PelagicConservationParameter.ordering' db.delete_column('scenario_pelagicconservationparameter', 'ordering') # Deleting field 'OffshoreConservationParameter.ordering' db.delete_column('scenario_offshoreconservationparameter', 'ordering') # Deleting field 'NearshoreConservationParameter.ordering' db.delete_column('scenario_nearshoreconservationparameter', 'ordering') # Deleting field 'WaveEnergyParameter.ordering' db.delete_column('scenario_waveenergyparameter', 'ordering') models = { 'auth.group': { 'Meta': {'object_name': 'Group'}, 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'name': ('django.db.models.fields.CharField', [], {'unique': 'True', 'max_length': '80'}), 'permissions': ('django.db.models.fields.related.ManyToManyField', [], {'to': "orm['auth.Permission']", 'symmetrical': 'False', 'blank': 'True'}) }, 'auth.permission': { 'Meta': {'ordering': "('content_type__app_label', 'content_type__model', 'codename')", 'unique_together': "(('content_type', 'codename'),)", 'object_name': 'Permission'}, 'codename': ('django.db.models.fields.CharField', [], {'max_length': '100'}), 'content_type': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['contenttypes.ContentType']"}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'name': ('django.db.models.fields.CharField', [], {'max_length': '50'}) }, 'auth.user': { 'Meta': {'object_name': 'User'}, 'date_joined': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime.now'}), 'email': ('django.db.models.fields.EmailField', [], {'max_length': '75', 'blank': 'True'}), 'first_name': ('django.db.models.fields.CharField', [], {'max_length': '30', 'blank': 'True'}), 'groups': ('django.db.models.fields.related.ManyToManyField', [], {'to': "orm['auth.Group']", 'symmetrical': 'False', 'blank': 'True'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'is_active': ('django.db.models.fields.BooleanField', [], {'default': 'True'}), 'is_staff': ('django.db.models.fields.BooleanField', [], {'default': 'False'}), 'is_superuser': ('django.db.models.fields.BooleanField', [], {'default': 'False'}), 'last_login': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime.now'}), 'last_name': ('django.db.models.fields.CharField', [], {'max_length': '30', 'blank': 'True'}), 'password': ('django.db.models.fields.CharField', [], {'max_length': '128'}), 'user_permissions': ('django.db.models.fields.related.ManyToManyField', [], {'to': "orm['auth.Permission']", 'symmetrical': 'False', 'blank': 'True'}), 'username': ('django.db.models.fields.CharField', [], {'unique': 'True', 'max_length': '30'}) }, 'contenttypes.contenttype': { 'Meta': {'ordering': "('name',)", 'unique_together': "(('app_label', 'model'),)", 'object_name': 'ContentType', 'db_table': "'django_content_type'"}, 'app_label': ('django.db.models.fields.CharField', [], {'max_length': '100'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'model': ('django.db.models.fields.CharField', [], {'max_length': '100'}), 'name': ('django.db.models.fields.CharField', [], {'max_length': '100'}) }, 'scenario.category': { 'Meta': {'object_name': 'Category'}, 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'name': ('django.db.models.fields.CharField', [], {'max_length': '70'}), 'short_name': ('django.db.models.fields.CharField', [], {'max_length': '70', 'null': 'True', 'blank': 'True'}) }, 'scenario.chlorophyl': { 'Meta': {'object_name': 'Chlorophyl'}, 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'name': ('django.db.models.fields.CharField', [], {'max_length': '30'}), 'short_name': ('django.db.models.fields.CharField', [], {'max_length': '30', 'null': 'True', 'blank': 'True'}) }, 'scenario.conservationobjective': { 'Meta': {'object_name': 'ConservationObjective'}, 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'objective': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['scenario.Objective']", 'null': 'True', 'blank': 'True'}) }, 'scenario.conservationsite': { 'Meta': {'object_name': 'ConservationSite'}, 'content_type': ('django.db.models.fields.related.ForeignKey', [], {'blank': 'True', 'related_name': "'scenario_conservationsite_related'", 'null': 'True', 'to': "orm['contenttypes.ContentType']"}), 'date_created': ('django.db.models.fields.DateTimeField', [], {'auto_now_add': 'True', 'blank': 'True'}), 'date_modified': ('django.db.models.fields.DateTimeField', [], {'auto_now': 'True', 'blank': 'True'}), 'description': ('django.db.models.fields.TextField', [], {'null': 'True', 'blank': 'True'}), 'geometry_final': ('django.contrib.gis.db.models.fields.PolygonField', [], {'srid': '32610', 'null': 'True', 'blank': 'True'}), 'geometry_orig': ('django.contrib.gis.db.models.fields.PolygonField', [], {'srid': '32610', 'null': 'True', 'blank': 'True'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'manipulators': ('django.db.models.fields.TextField', [], {'null': 'True', 'blank': 'True'}), 'name': ('django.db.models.fields.CharField', [], {'max_length': "'255'"}), 'object_id': ('django.db.models.fields.PositiveIntegerField', [], {'null': 'True', 'blank': 'True'}), 'sharing_groups': ('django.db.models.fields.related.ManyToManyField', [], {'blank': 'True', 'related_name': "'scenario_conservationsite_related'", 'null': 'True', 'symmetrical': 'False', 'to': "orm['auth.Group']"}), 'user': ('django.db.models.fields.related.ForeignKey', [], {'related_name': "'scenario_conservationsite_related'", 'to': "orm['auth.User']"}) }, 'scenario.depthclass': { 'Meta': {'object_name': 'DepthClass'}, 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'name': ('django.db.models.fields.CharField', [], {'max_length': '30'}), 'short_name': ('django.db.models.fields.CharField', [], {'max_length': '30', 'null': 'True', 'blank': 'True'}) }, 'scenario.energyobjective': { 'Meta': {'object_name': 'EnergyObjective'}, 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'objective': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['scenario.Objective']", 'null': 'True', 'blank': 'True'}) }, 'scenario.geomorphology': { 'Meta': {'object_name': 'Geomorphology'}, 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'name': ('django.db.models.fields.CharField', [], {'max_length': '30'}), 'short_name': ('django.db.models.fields.CharField', [], {'max_length': '30', 'null': 'True', 'blank': 'True'}) }, 'scenario.mos': { 'Meta': {'object_name': 'MOS'}, 'content_type': ('django.db.models.fields.related.ForeignKey', [], {'blank': 'True', 'related_name': "'scenario_mos_related'", 'null': 'True', 'to': "orm['contenttypes.ContentType']"}), 'date_created': ('django.db.models.fields.DateTimeField', [], {'auto_now_add': 'True', 'blank': 'True'}), 'date_modified': ('django.db.models.fields.DateTimeField', [], {'auto_now': 'True', 'blank': 'True'}), 'description': ('django.db.models.fields.TextField', [], {'null': 'True', 'blank': 'True'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'input_chlorophyl_pelagic_conservation': ('django.db.models.fields.related.ManyToManyField', [], {'symmetrical': 'False', 'to': "orm['scenario.Chlorophyl']", 'null': 'True', 'blank': 'True'}), 'input_depth_class_offshore_conservation': ('django.db.models.fields.related.ManyToManyField', [], {'blank': 'True', 'related_name': "'MOSOffshoreConservationDepthClass'", 'null': 'True', 'symmetrical': 'False', 'to': "orm['scenario.DepthClass']"}), 'input_dist_astoria_tidal_energy': ('django.db.models.fields.FloatField', [], {'null': 'True', 'blank': 'True'}), 'input_dist_astoria_wave_energy': ('django.db.models.fields.FloatField', [], {'null': 'True', 'blank': 'True'}), 'input_dist_astoria_wind_energy': ('django.db.models.fields.FloatField', [], {'null': 'True', 'blank': 'True'}), 'input_dist_hoquium_tidal_energy': ('django.db.models.fields.FloatField', [], {'null': 'True', 'blank': 'True'}), 'input_dist_hoquium_wave_energy': ('django.db.models.fields.FloatField', [], {'null': 'True', 'blank': 'True'}), 'input_dist_hoquium_wind_energy': ('django.db.models.fields.FloatField', [], {'null': 'True', 'blank': 'True'}), 'input_dist_port_tidal_energy': ('django.db.models.fields.FloatField', [], {'null': 'True', 'blank': 'True'}), 'input_dist_port_wave_energy': ('django.db.models.fields.FloatField', [], {'null': 'True', 'blank': 'True'}), 'input_dist_port_wind_energy': ('django.db.models.fields.FloatField', [], {'null': 'True', 'blank': 'True'}), 'input_dist_shore_tidal_energy': ('django.db.models.fields.FloatField', [], {'null': 'True', 'blank': 'True'}), 'input_dist_shore_wave_energy': ('django.db.models.fields.FloatField', [], {'null': 'True', 'blank': 'True'}), 'input_dist_shore_wind_energy': ('django.db.models.fields.FloatField', [], {'null': 'True', 'blank': 'True'}), 'input_ecosystem_nearshore_conservation': ('django.db.models.fields.related.ManyToManyField', [], {'symmetrical': 'False', 'to': "orm['scenario.NearshoreEcosystem']", 'null': 'True', 'blank': 'True'}), 'input_exposure_nearshore_conservation': ('django.db.models.fields.related.ManyToManyField', [], {'symmetrical': 'False', 'to': "orm['scenario.NearshoreExposure']", 'null': 'True', 'blank': 'True'}), 'input_geomorphology_offshore_conservation': ('django.db.models.fields.related.ManyToManyField', [], {'blank': 'True', 'related_name': "'MOSOffshoreConservationGeomorphology'", 'null': 'True', 'symmetrical': 'False', 'to': "orm['scenario.Geomorphology']"}), 'input_max_depth_tidal_energy': ('django.db.models.fields.FloatField', [], {'null': 'True', 'blank': 'True'}), 'input_max_depth_wave_energy': ('django.db.models.fields.FloatField', [], {'null': 'True', 'blank': 'True'}), 'input_max_depth_wind_energy': ('django.db.models.fields.FloatField', [], {'null': 'True', 'blank': 'True'}), 'input_max_tidalmax_tidal_energy': ('django.db.models.fields.FloatField', [], {'null': 'True', 'blank': 'True'}), 'input_max_tidalmean_tidal_energy': ('django.db.models.fields.FloatField', [], {'null': 'True', 'blank': 'True'}), 'input_max_wavesummer_wave_energy': ('django.db.models.fields.FloatField', [], {'null': 'True', 'blank': 'True'}), 'input_max_wavewinter_wave_energy': ('django.db.models.fields.FloatField', [], {'null': 'True', 'blank': 'True'}), 'input_min_depth_tidal_energy': ('django.db.models.fields.FloatField', [], {'null': 'True', 'blank': 'True'}), 'input_min_depth_wave_energy': ('django.db.models.fields.FloatField', [], {'null': 'True', 'blank': 'True'}), 'input_min_depth_wind_energy': ('django.db.models.fields.FloatField', [], {'null': 'True', 'blank': 'True'}), 'input_min_tidalmax_tidal_energy': ('django.db.models.fields.FloatField', [], {'null': 'True', 'blank': 'True'}), 'input_min_tidalmean_tidal_energy': ('django.db.models.fields.FloatField', [], {'null': 'True', 'blank': 'True'}), 'input_min_wavesummer_wave_energy': ('django.db.models.fields.FloatField', [], {'null': 'True', 'blank': 'True'}), 'input_min_wavewinter_wave_energy': ('django.db.models.fields.FloatField', [], {'null': 'True', 'blank': 'True'}), 'input_objectives': ('django.db.models.fields.related.ManyToManyField', [], {'symmetrical': 'False', 'to': "orm['scenario.Objective']", 'null': 'True', 'blank': 'True'}), 'input_objectives_conservation': ('django.db.models.fields.related.ManyToManyField', [], {'symmetrical': 'False', 'to': "orm['scenario.ConservationObjective']", 'null': 'True', 'blank': 'True'}), 'input_objectives_energy': ('django.db.models.fields.related.ManyToManyField', [], {'symmetrical': 'False', 'to': "orm['scenario.EnergyObjective']", 'null': 'True', 'blank': 'True'}), 'input_parameters_nearshore_conservation': ('django.db.models.fields.related.ManyToManyField', [], {'to': "orm['scenario.NearshoreConservationParameter']", 'symmetrical': 'False'}), 'input_parameters_offshore_conservation': ('django.db.models.fields.related.ManyToManyField', [], {'to': "orm['scenario.OffshoreConservationParameter']", 'symmetrical': 'False'}), 'input_parameters_pelagic_conservation': ('django.db.models.fields.related.ManyToManyField', [], {'to': "orm['scenario.PelagicConservationParameter']", 'symmetrical': 'False'}), 'input_parameters_tidal_energy': ('django.db.models.fields.related.ManyToManyField', [], {'symmetrical': 'False', 'to': "orm['scenario.TidalEnergyParameter']", 'null': 'True', 'blank': 'True'}), 'input_parameters_wave_energy': ('django.db.models.fields.related.ManyToManyField', [], {'to': "orm['scenario.WaveEnergyParameter']", 'symmetrical': 'False'}), 'input_parameters_wind_energy': ('django.db.models.fields.related.ManyToManyField', [], {'to': "orm['scenario.WindEnergyParameter']", 'symmetrical': 'False'}), 'input_substrate_nearshore_conservation': ('django.db.models.fields.related.ManyToManyField', [], {'symmetrical': 'False', 'to': "orm['scenario.NearshoreSubstrate']", 'null': 'True', 'blank': 'True'}), 'input_substrate_offshore_conservation': ('django.db.models.fields.related.ManyToManyField', [], {'blank': 'True', 'related_name': "'MOSOffshoreConservationSubstrate'", 'null': 'True', 'symmetrical': 'False', 'to': "orm['scenario.Substrate']"}), 'input_substrate_tidal_energy': ('django.db.models.fields.related.ManyToManyField', [], {'symmetrical': 'False', 'to': "orm['scenario.TidalSubstrate']", 'null': 'True', 'blank': 'True'}), 'input_substrate_wave_energy': ('django.db.models.fields.related.ManyToManyField', [], {'blank': 'True', 'related_name': "'MOSWaveEnergySubstrate'", 'null': 'True', 'symmetrical': 'False', 'to': "orm['scenario.Substrate']"}), 'input_substrate_wind_energy': ('django.db.models.fields.related.ManyToManyField', [], {'blank': 'True', 'related_name': "'MOSWindEnergySubstrate'", 'null': 'True', 'symmetrical': 'False', 'to': "orm['scenario.Substrate']"}), 'input_upwelling_pelagic_conservation': ('django.db.models.fields.related.ManyToManyField', [], {'symmetrical': 'False', 'to': "orm['scenario.Upwelling']", 'null': 'True', 'blank': 'True'}), 'input_wind_potential_wind_energy': ('django.db.models.fields.related.ManyToManyField', [], {'symmetrical': 'False', 'to': "orm['scenario.WindPotential']", 'null': 'True', 'blank': 'True'}), 'name': ('django.db.models.fields.CharField', [], {'max_length': "'255'"}), 'object_id': ('django.db.models.fields.PositiveIntegerField', [], {'null': 'True', 'blank': 'True'}), 'overlap_geom': ('django.contrib.gis.db.models.fields.MultiPolygonField', [], {'srid': '32610', 'null': 'True', 'blank': 'True'}), 'scenarios': ('django.db.models.fields.related.ManyToManyField', [], {'symmetrical': 'False', 'to': "orm['scenario.Scenario']", 'null': 'True', 'blank': 'True'}), 'sharing_groups': ('django.db.models.fields.related.ManyToManyField', [], {'blank': 'True', 'related_name': "'scenario_mos_related'", 'null': 'True', 'symmetrical': 'False', 'to': "orm['auth.Group']"}), 'support_file': ('django.db.models.fields.files.FileField', [], {'max_length': '100', 'null': 'True', 'blank': 'True'}), 'user': ('django.db.models.fields.related.ForeignKey', [], {'related_name': "'scenario_mos_related'", 'to': "orm['auth.User']"}) }, 'scenario.nearshoreconservationparameter': { 'Meta': {'object_name': 'NearshoreConservationParameter'}, 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'ordering': ('django.db.models.fields.IntegerField', [], {'null': 'True', 'blank': 'True'}), 'parameter': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['scenario.Parameter']", 'null': 'True', 'blank': 'True'}) }, 'scenario.nearshoreconservationparameterarea': { 'Meta': {'object_name': 'NearshoreConservationParameterArea'}, 'area': ('django.db.models.fields.FloatField', [], {'null': 'True', 'blank': 'True'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'name': ('django.db.models.fields.CharField', [], {'max_length': '70'}) }, 'scenario.nearshoreecosystem': { 'Meta': {'object_name': 'NearshoreEcosystem'}, 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'name': ('django.db.models.fields.CharField', [], {'max_length': '30'}), 'short_name': ('django.db.models.fields.CharField', [], {'max_length': '30', 'null': 'True', 'blank': 'True'}) }, 'scenario.nearshoreexposure': { 'Meta': {'object_name': 'NearshoreExposure'}, 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'name': ('django.db.models.fields.CharField', [], {'max_length': '30'}), 'short_name': ('django.db.models.fields.CharField', [], {'max_length': '30', 'null': 'True', 'blank': 'True'}) }, 'scenario.nearshoresubstrate': { 'Meta': {'object_name': 'NearshoreSubstrate'}, 'color': ('django.db.models.fields.CharField', [], {'default': "'778B1A55'", 'max_length': '8'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'name': ('django.db.models.fields.CharField', [], {'max_length': '30'}), 'short_name': ('django.db.models.fields.CharField', [], {'max_length': '30', 'null': 'True', 'blank': 'True'}) }, 'scenario.objective': { 'Meta': {'object_name': 'Objective'}, 'color': ('django.db.models.fields.CharField', [], {'default': "'778B1A55'", 'max_length': '8'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'name': ('django.db.models.fields.CharField', [], {'max_length': '70'}), 'short_name': ('django.db.models.fields.CharField', [], {'max_length': '70', 'null': 'True', 'blank': 'True'}) }, 'scenario.offshoreconservationparameter': { 'Meta': {'object_name': 'OffshoreConservationParameter'}, 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'ordering': ('django.db.models.fields.IntegerField', [], {'null': 'True', 'blank': 'True'}), 'parameter': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['scenario.Parameter']", 'null': 'True', 'blank': 'True'}) }, 'scenario.offshoreconservationparameterarea': { 'Meta': {'object_name': 'OffshoreConservationParameterArea'}, 'area': ('django.db.models.fields.FloatField', [], {'null': 'True', 'blank': 'True'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'name': ('django.db.models.fields.CharField', [], {'max_length': '70'}) }, 'scenario.parameter': { 'Meta': {'object_name': 'Parameter'}, 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'name': ('django.db.models.fields.CharField', [], {'max_length': '70'}), 'short_name': ('django.db.models.fields.CharField', [], {'max_length': '70', 'null': 'True', 'blank': 'True'}) }, 'scenario.pelagicconservationparameter': { 'Meta': {'object_name': 'PelagicConservationParameter'}, 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'ordering': ('django.db.models.fields.IntegerField', [], {'null': 'True', 'blank': 'True'}), 'parameter': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['scenario.Parameter']", 'null': 'True', 'blank': 'True'}) }, 'scenario.pelagicconservationparameterarea': { 'Meta': {'object_name': 'PelagicConservationParameterArea'}, 'area': ('django.db.models.fields.FloatField', [], {'null': 'True', 'blank': 'True'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'name': ('django.db.models.fields.CharField', [], {'max_length': '70'}) }, 'scenario.scenario': { 'Meta': {'object_name': 'Scenario'}, 'content_type': ('django.db.models.fields.related.ForeignKey', [], {'blank': 'True', 'related_name': "'scenario_scenario_related'", 'null': 'True', 'to': "orm['contenttypes.ContentType']"}), 'date_created': ('django.db.models.fields.DateTimeField', [], {'auto_now_add': 'True', 'blank': 'True'}), 'date_modified': ('django.db.models.fields.DateTimeField', [], {'auto_now': 'True', 'blank': 'True'}), 'geometry_final': ('django.contrib.gis.db.models.fields.MultiPolygonField', [], {'srid': '32610', 'null': 'True', 'blank': 'True'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'input_chlorophyl': ('django.db.models.fields.related.ManyToManyField', [], {'symmetrical': 'False', 'to': "orm['scenario.Chlorophyl']", 'null': 'True', 'blank': 'True'}), 'input_depth_class': ('django.db.models.fields.related.ManyToManyField', [], {'symmetrical': 'False', 'to': "orm['scenario.DepthClass']", 'null': 'True', 'blank': 'True'}), 'input_dist_astoria': ('django.db.models.fields.FloatField', [], {'null': 'True', 'blank': 'True'}), 'input_dist_hoquium': ('django.db.models.fields.FloatField', [], {'null': 'True', 'blank': 'True'}), 'input_dist_port': ('django.db.models.fields.FloatField', [], {'null': 'True', 'blank': 'True'}), 'input_dist_shore': ('django.db.models.fields.FloatField', [], {'null': 'True', 'blank': 'True'}), 'input_geomorphology': ('django.db.models.fields.related.ManyToManyField', [], {'symmetrical': 'False', 'to': "orm['scenario.Geomorphology']", 'null': 'True', 'blank': 'True'}), 'input_max_depth': ('django.db.models.fields.FloatField', [], {'null': 'True', 'blank': 'True'}), 'input_max_tidalmax': ('django.db.models.fields.FloatField', [], {'null': 'True', 'blank': 'True'}), 'input_max_tidalmean': ('django.db.models.fields.FloatField', [], {'null': 'True', 'blank': 'True'}), 'input_max_wavesummer': ('django.db.models.fields.FloatField', [], {'null': 'True', 'blank': 'True'}), 'input_max_wavewinter': ('django.db.models.fields.FloatField', [], {'null': 'True', 'blank': 'True'}), 'input_min_depth': ('django.db.models.fields.FloatField', [], {'null': 'True', 'blank': 'True'}), 'input_min_tidalmax': ('django.db.models.fields.FloatField', [], {'null': 'True', 'blank': 'True'}), 'input_min_tidalmean': ('django.db.models.fields.FloatField', [], {'null': 'True', 'blank': 'True'}), 'input_min_wavesummer': ('django.db.models.fields.FloatField', [], {'null': 'True', 'blank': 'True'}), 'input_min_wavewinter': ('django.db.models.fields.FloatField', [], {'null': 'True', 'blank': 'True'}), 'input_nearshore_ecosystem': ('django.db.models.fields.related.ManyToManyField', [], {'symmetrical': 'False', 'to': "orm['scenario.NearshoreEcosystem']", 'null': 'True', 'blank': 'True'}), 'input_nearshore_exposure': ('django.db.models.fields.related.ManyToManyField', [], {'symmetrical': 'False', 'to': "orm['scenario.NearshoreExposure']", 'null': 'True', 'blank': 'True'}), 'input_nearshore_substrate': ('django.db.models.fields.related.ManyToManyField', [], {'symmetrical': 'False', 'to': "orm['scenario.NearshoreSubstrate']", 'null': 'True', 'blank': 'True'}), 'input_objective': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['scenario.Objective']"}), 'input_parameters': ('django.db.models.fields.related.ManyToManyField', [], {'symmetrical': 'False', 'to': "orm['scenario.Parameter']", 'null': 'True', 'blank': 'True'}), 'input_substrate': ('django.db.models.fields.related.ManyToManyField', [], {'symmetrical': 'False', 'to': "orm['scenario.Substrate']", 'null': 'True', 'blank': 'True'}), 'input_tidal_substrate': ('django.db.models.fields.related.ManyToManyField', [], {'symmetrical': 'False', 'to': "orm['scenario.TidalSubstrate']", 'null': 'True', 'blank': 'True'}), 'input_upwelling': ('django.db.models.fields.related.ManyToManyField', [], {'symmetrical': 'False', 'to': "orm['scenario.Upwelling']", 'null': 'True', 'blank': 'True'}), 'input_wind_potential': ('django.db.models.fields.related.ManyToManyField', [], {'symmetrical': 'False', 'to': "orm['scenario.WindPotential']", 'null': 'True', 'blank': 'True'}), 'name': ('django.db.models.fields.CharField', [], {'max_length': "'255'"}), 'object_id': ('django.db.models.fields.PositiveIntegerField', [], {'null': 'True', 'blank': 'True'}), 'output_area': ('django.db.models.fields.FloatField', [], {'null': 'True', 'blank': 'True'}), 'output_geom': ('django.contrib.gis.db.models.fields.MultiPolygonField', [], {'srid': '32610', 'null': 'True', 'blank': 'True'}), 'output_mapcalc': ('django.db.models.fields.CharField', [], {'max_length': '720', 'null': 'True', 'blank': 'True'}), 'output_report': ('django.db.models.fields.TextField', [], {'null': 'True', 'blank': 'True'}), 'sharing_groups': ('django.db.models.fields.related.ManyToManyField', [], {'blank': 'True', 'related_name': "'scenario_scenario_related'", 'null': 'True', 'symmetrical': 'False', 'to': "orm['auth.Group']"}), 'user': ('django.db.models.fields.related.ForeignKey', [], {'related_name': "'scenario_scenario_related'", 'to': "orm['auth.User']"}) }, 'scenario.substrate': { 'Meta': {'object_name': 'Substrate'}, 'color': ('django.db.models.fields.CharField', [], {'default': "'778B1A55'", 'max_length': '8'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'name': ('django.db.models.fields.CharField', [], {'max_length': '30'}), 'short_name': ('django.db.models.fields.CharField', [], {'max_length': '30', 'null': 'True', 'blank': 'True'}) }, 'scenario.tidalenergyparameter': { 'Meta': {'object_name': 'TidalEnergyParameter'}, 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'ordering': ('django.db.models.fields.IntegerField', [], {'null': 'True', 'blank': 'True'}), 'parameter': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['scenario.Parameter']", 'null': 'True', 'blank': 'True'}) }, 'scenario.tidalenergyparameterarea': { 'Meta': {'object_name': 'TidalEnergyParameterArea'}, 'area': ('django.db.models.fields.FloatField', [], {'null': 'True', 'blank': 'True'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'name': ('django.db.models.fields.CharField', [], {'max_length': '70'}) }, 'scenario.tidalsubstrate': { 'Meta': {'object_name': 'TidalSubstrate'}, 'color': ('django.db.models.fields.CharField', [], {'default': "'778B1A55'", 'max_length': '8'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'name': ('django.db.models.fields.CharField', [], {'max_length': '30'}), 'short_name': ('django.db.models.fields.CharField', [], {'max_length': '30', 'null': 'True', 'blank': 'True'}) }, 'scenario.upwelling': { 'Meta': {'object_name': 'Upwelling'}, 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'name': ('django.db.models.fields.CharField', [], {'max_length': '30'}), 'short_name': ('django.db.models.fields.CharField', [], {'max_length': '30', 'null': 'True', 'blank': 'True'}) }, 'scenario.waveenergyparameter': { 'Meta': {'object_name': 'WaveEnergyParameter'}, 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'ordering': ('django.db.models.fields.IntegerField', [], {'null': 'True', 'blank': 'True'}), 'parameter': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['scenario.Parameter']", 'null': 'True', 'blank': 'True'}) }, 'scenario.waveenergyparameterarea': { 'Meta': {'object_name': 'WaveEnergyParameterArea'}, 'area': ('django.db.models.fields.FloatField', [], {'null': 'True', 'blank': 'True'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'name': ('django.db.models.fields.CharField', [], {'max_length': '70'}) }, 'scenario.windenergyparameter': { 'Meta': {'object_name': 'WindEnergyParameter'}, 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'ordering': ('django.db.models.fields.IntegerField', [], {'null': 'True', 'blank': 'True'}), 'parameter': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['scenario.Parameter']", 'null': 'True', 'blank': 'True'}) }, 'scenario.windenergyparameterarea': { 'Meta': {'object_name': 'WindEnergyParameterArea'}, 'area': ('django.db.models.fields.FloatField', [], {'null': 'True', 'blank': 'True'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'name': ('django.db.models.fields.CharField', [], {'max_length': '70'}) }, 'scenario.windenergysite': { 'Meta': {'object_name': 'WindEnergySite'}, 'content_type': ('django.db.models.fields.related.ForeignKey', [], {'blank': 'True', 'related_name': "'scenario_windenergysite_related'", 'null': 'True', 'to': "orm['contenttypes.ContentType']"}), 'date_created': ('django.db.models.fields.DateTimeField', [], {'auto_now_add': 'True', 'blank': 'True'}), 'date_modified': ('django.db.models.fields.DateTimeField', [], {'auto_now': 'True', 'blank': 'True'}), 'description': ('django.db.models.fields.TextField', [], {'null': 'True', 'blank': 'True'}), 'geometry_final': ('django.contrib.gis.db.models.fields.PolygonField', [], {'srid': '32610', 'null': 'True', 'blank': 'True'}), 'geometry_orig': ('django.contrib.gis.db.models.fields.PolygonField', [], {'srid': '32610', 'null': 'True', 'blank': 'True'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'manipulators': ('django.db.models.fields.TextField', [], {'null': 'True', 'blank': 'True'}), 'name': ('django.db.models.fields.CharField', [], {'max_length': "'255'"}), 'object_id': ('django.db.models.fields.PositiveIntegerField', [], {'null': 'True', 'blank': 'True'}), 'sharing_groups': ('django.db.models.fields.related.ManyToManyField', [], {'blank': 'True', 'related_name': "'scenario_windenergysite_related'", 'null': 'True', 'symmetrical': 'False', 'to': "orm['auth.Group']"}), 'user': ('django.db.models.fields.related.ForeignKey', [], {'related_name': "'scenario_windenergysite_related'", 'to': "orm['auth.User']"}) }, 'scenario.windpotential': { 'Meta': {'object_name': 'WindPotential'}, 'density': ('django.db.models.fields.CharField', [], {'max_length': '30'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'name': ('django.db.models.fields.CharField', [], {'max_length': '30'}), 'short_name': ('django.db.models.fields.CharField', [], {'max_length': '30', 'null': 'True', 'blank': 'True'}), 'speed': ('django.db.models.fields.CharField', [], {'max_length': '30'}) } } complete_apps = ['scenario']
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/tagcreator/indirect/rvg_indirect_analog.py
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[]
no_license
sebasalvarez13/ww-tag-generation
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#!/usr/bin/env python3 import csv import os.path from os import path from tagcreator.indirect.indirect_analog_features import features class RvgIndirectAnalog: def __init__(self, line): self.line = line self.tag_start = "GenericRevGate" self.controls_list = ["CMD", "Faults", "ManAngle", "Status"] self.setpoints_list = ["MPM", "FltrWgt"] self.measurements_list = ["AngleSts", "LevelTrans", "ProductAvailable", "Status"] self.verify_list = ["BedDepth", "Hole", "PA", "PN", "Pos", "PosSp"] def setpoints(self): dict_data = [] for setpoint in self.setpoints_list: dict1 = features() dict1[":IndirectAnalog"] = "{}{}Sp{}".format(self.tag_start, self.line, setpoint) dict_data.append(dict1) return(dict_data) def measurements(self): dict_data = self.setpoints() for measurement in self.measurements_list: dict1 = features() dict1[":IndirectAnalog"] = "{}{}{}".format(self.tag_start, self.line, measurement) dict_data.append(dict1) return(dict_data) def verify(self): dict_data = self.measurements() for verify in self.verify_list: dict1 = features() dict1[":IndirectAnalog"] = "GenericEngRevGate{}Verify{}".format(self.line, verify) dict_data.append(dict1) return(dict_data) def control(self): dict_data = self.verify() for control in self.controls_list: dict1 = features() dict1[":IndirectAnalog"] = "{}Control{}".format(self.tag_start, control) dict_data.append(dict1) return(dict_data) def module_exists(self): file_path = "/mnt/c/Projects/ww-tag-generation/csv-files/indirect/rvg_indirect_analog.csv" if path.exists(file_path): return True else: return False def create_csv(self): csv_file = "csv-files/indirect/rvg_indirect_analog.csv" if self.module_exists() != True: dict_data = self.control() csv_columns = list(dict_data[0].keys()) try: with open(csv_file, 'w') as csvfile: writer = csv.DictWriter(csvfile, fieldnames=csv_columns) writer.writeheader() for data in dict_data: writer.writerow(data) except IOError as e: print(e) else: dict_data = self.verify() csv_columns = list(dict_data[0].keys()) try: with open(csv_file, 'a') as csvfile: writer = csv.DictWriter(csvfile, fieldnames=csv_columns) #writer.writeheader() for data in dict_data: writer.writerow(data) except IOError as e: print(e) if __name__ == "__main__": wm = RvgIndirectAnalog('A') wm.create_csv()
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/evaluate.py
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kubumiro/CNN-Python-Framework
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refs/heads/master
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def model_predict(model, X, y)
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/solutions_python/Problem_145/601.py
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dr-dos-ok/Code_Jam_Webscraper
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refs/heads/master
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#!/usr/bin/env python3 from fractions import gcd from math import log rounds = int(input()) for i in range(rounds): n, d = input().split('/') n = int(n) d = int(d) g = gcd(n,d) n = n//g d = d//g if log(d,2) != round( log(d,2)): print("Case #{}: impossible".format(i+1)) continue; while n!=1 : n -= 1 g = gcd(n,d) n = n // g d = d // g print("Case #{}: {}".format(i+1,int(log(d,2))))
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/nld_from_csv.py
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benjaminestes/bq-stat
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2022-02-19T17:08:57.224444
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#!/usr/bin/env python # coding=utf-8 """Given a CSV file from Stat's ranking ranking export, create a newline-delimited JSON file corresponding with BQ schema.""" from sys import stdin import csv import json def map_row_to_schema(row): """Associate a value from a Stat CSV export with the correct identifier from BQ schema. When first adding a client to this system we may have historical data that we want to import. That data comes from Stat's ranking export. We need to map values from Stat's data into the schema we've design to interface with Data Studio. This function handles that mapping. Args: row: A dict extracted from Stat's ranking CSV, that corresponds with a single observation of a keyword ranking. Returns: A dict representing data for a single keyword observation that complies with the BQ schema of our client tables. Keys that were missing from Stat's response get None/NULL values. """ return { "timestamp": row["Date"] + " 00:00", "keyword": row["Keyword"], "market": row["Market"], "location": row["Location"], "device": row["Device"], "rank": row["Rank"], "base_rank": row["Rank"], "url": row["URL"] if row["URL"] else None, "advertiser_competition": row["Advertiser Competition"], "gms": row["Global Monthly Searches"], "rms": row["Regional Monthly Searches"], "cpc": row["CPC"], "tags": [tag.strip() for tag in row["Tags"].split("/")] if row["Tags"] else [], } def csv_reader(): """If called from shell, assume Stat CSV file is fed from stdin. Returns: An iterable yielding a dict for each row in the Stat CSV. """ return csv.DictReader(stdin, delimiter="\t") def main(): """Creat an object corresponding to Stat's CSV export, and write a JSON object for each observation in Stat's response.""" # Stat's API outputs a single row for each instance of a keyword, # in the sense you'd take it looking at their GUI. That means only # a single ranking page is included. # # However, this script is for importing historical data which we # get from a ranking export. The ranking export is a CSV which # includes a row for each ranking page. It will also include an # empty row for an observation of no ranking page. We want to make # sure at most a single observation is included to match what we # get from the API. # # This emits a line for the first instance of a "key". By default # this will be the best-ranking page. However, Stat could change # this in the future. seen = set() for row in csv_reader(): r = map_row_to_schema(row) key = (r["timestamp"], r["keyword"], r["market"], r["location"], r["device"]) if key not in seen: seen.add(key) print(json.dumps(r)) if __name__ == "__main__": main()
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/helper.py
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import numpy as np def fetch_medal_tally(df, year, country): medal_df = df.drop_duplicates(subset=['Team', 'NOC', 'Games', 'Year', 'City', 'Sport', 'Event', 'Medal']) flag = 0 if year == 'Overall' and country == 'Overall': temp_df = medal_df if year == 'Overall' and country != 'Overall': flag = 1 temp_df = medal_df[medal_df['region'] == country] if year != 'Overall' and country == 'Overall': temp_df = medal_df[medal_df['Year'] == int(year)] if year != 'Overall' and country != 'Overall': temp_df = medal_df[(medal_df['Year'] == int(year)) & (medal_df['region'] == country)] if flag == 1: x = temp_df.groupby('Year').sum()[['Gold', 'Silver', 'Bronze']].sort_values('Year').reset_index() else: x = temp_df.groupby('region').sum()[['Gold', 'Silver', 'Bronze']].sort_values('Gold', ascending=False).reset_index() x['total'] = x['Gold'] + x['Silver'] + x['Bronze'] x['Gold'] = x['Gold'].astype('int') x['Silver'] = x['Silver'].astype('int') x['Bronze'] = x['Bronze'].astype('int') x['total'] = x['total'].astype('int') return x def medal_tally(df): medal_tally = df.drop_duplicates(subset=['Team', 'NOC', 'Games', 'Year', 'City', 'Sport', 'Event', 'Medal']) medal_tally = medal_tally.groupby('region').sum()[['Gold', 'Silver', 'Bronze']].sort_values('Gold', ascending=False).reset_index() medal_tally['total'] = medal_tally['Gold'] + medal_tally['Silver'] + medal_tally['Bronze'] medal_tally['Gold'] = medal_tally['Gold'].astype('int') medal_tally['Silver'] = medal_tally['Silver'].astype('int') medal_tally['Bronze'] = medal_tally['Bronze'].astype('int') medal_tally['total'] = medal_tally['total'].astype('int') return medal_tally def country_year_list(df): years = df['Year'].unique().tolist() years.sort() years.insert(0, 'Overall') country = np.unique(df['region'].dropna().values).tolist() country.sort() country.insert(0, 'Overall') return years, country def data_over_time(df, col): nations_over_time = df.drop_duplicates(['Year', col])['Year'].value_counts().reset_index().sort_values('index') nations_over_time.rename(columns={'index': 'Edition', 'Year': col}, inplace=True) return nations_over_time def most_successful(df, sport): temp_df = df.dropna(subset=['Medal']) if sport != 'Overall': temp_df = temp_df[temp_df['Sport'] == sport] x = temp_df['Name'].value_counts().reset_index().head(15).merge(df, left_on='index', right_on='Name', how='left')[ ['index', 'Name_x', 'Sport', 'region']].drop_duplicates('index') x.rename(columns={'index': 'Name', 'Name_x': 'Medals'}, inplace=True) return x def yearwise_medal_tally(df, country): temp_df = df.dropna(subset=['Medal']) temp_df.drop_duplicates(subset=['Team', 'NOC', 'Games', 'Year', 'City', 'Sport', 'Event', 'Medal'], inplace=True) new_df = temp_df[temp_df['region'] == country] final_df = new_df.groupby('Year').count()['Medal'].reset_index() return final_df def country_event_heatmap(df, country): temp_df = df.dropna(subset=['Medal']) temp_df.drop_duplicates(subset=['Team', 'NOC', 'Games', 'Year', 'City', 'Sport', 'Event', 'Medal'], inplace=True) new_df = temp_df[temp_df['region'] == country] pt = new_df.pivot_table(index='Sport', columns='Year', values='Medal', aggfunc='count').fillna(0) return pt def most_successful_countrywise(df, country): temp_df = df.dropna(subset=['Medal']) temp_df = temp_df[temp_df['region'] == country] x = temp_df['Name'].value_counts().reset_index().head(10).merge(df, left_on='index', right_on='Name', how='left')[ ['index', 'Name_x', 'Sport']].drop_duplicates('index') x.rename(columns={'index':'Name','Name_x':'Medals'},inplace=True) return x def weight_v_height(df, sport): athlete_df = df.drop_duplicates(subset=['Name','region']) athlete_df['Medal'].fillna('No Medal',inplace=True) if sport != 'Overall': temp_df = athlete_df[athlete_df['Sport']==sport] return temp_df else: return athlete_df def men_vs_women(df): athlete_df = df.drop_duplicates(subset=['Name', 'region']) men = athlete_df[athlete_df['Sex']=='M'].groupby('Year').count()['Name'].reset_index() women = athlete_df[athlete_df['Sex'] == 'F'].groupby('Year').count()['Name'].reset_index() final = men.merge(women,on='Year',how='left') final.rename(columns={'Name_x':'Male','Name_y':'Female'},inplace=True) final.fillna(0,inplace=True) return final
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/1.딥러닝과러닝머신/2고급/1-1.텍스트형식&바이너리형식.py
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[]
no_license
goodlucky1215/artificial-intelligence
469f6ec931dcd30aae4b9d2782588e2468a3635f
07c5fd009ca86c6ceb0f5ce9c960aeb1ffcd435a
refs/heads/master
2022-04-24T22:57:33.094666
2020-04-29T13:00:59
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#데이터가져오기 import requests r=requests.get("http://api.aoikujira.com/time/get.php") #텍스트 형식으로 데이터 추출하기 text= r.text print(text) #바이너리 형식으로 데이터 추출하기 bin = r.content print(bin)
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/src/cython_catkin_example/setup.py
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[]
no_license
vbillys/cython_catkin_example
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ee5a7a43828f3c3fba31002a5ebe275fbc312d83
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from setuptools import setup from distutils.sysconfig import get_python_lib import glob import os import sys if os.path.exists('readme.rst'): print("""The setup.py script should be executed from the build directory. Please see the file 'readme.rst' for further instructions.""") sys.exit(1) setup( name = "cython_catkin_example", package_dir = {'': 'src'}, data_files = [(get_python_lib(), glob.glob('src/*.so')) #,('bin', ['bin/cython_catkin_example']) ], author = 'Marco Esposito', description = 'Example of Cython and catkin integration', license = 'Apache', keywords = 'cmake cython build', url = 'http://github.com/marcoesposito1988/cython_catkin_example', zip_safe = False, )
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/python/problem-string/two_characters.py
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[]
no_license
hyunjun/practice
72e83de6a1d5e04ddcd16526f16110ea2dd00373
5376dd48b1cefb4faba9d2ef6a8a497b6b1d6c67
refs/heads/master
2023-08-31T07:00:37.320351
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2023-08-17T07:29:24
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# https://www.hackerrank.com/challenges/two-characters from collections import Counter from collections import defaultdict def alternate(s): if s is None or 0 == len(s): return 0 consecutiveSet = set() for i, c in enumerate(s): if 0 == i: continue if s[i - 1] == c: consecutiveSet.add(c) #print(consecutiveSet) def isAlternating(cand): for i, c in enumerate(cand): if 0 == i: continue if cand[i - 1] == c: return False return True cntDict = Counter([c for c in s if c not in consecutiveSet]) cntCharDict = defaultdict(list) for c, cnt in cntDict.items(): cntCharDict[cnt].append(c) sortedCntCharList = sorted(cntCharDict.items(), key=lambda t: t[0], reverse=True) #print(sortedCntCharList) for i, (cnt1, charList1) in enumerate(sortedCntCharList): for j, (cnt2, charList2) in enumerate(sortedCntCharList): if j < i or 1 < abs(cnt1 - cnt2): continue for ch1 in charList1: for ch2 in charList2: if ch1 == ch2: continue cand = [c for c in s if c == ch1 or c == ch2] #print(cand) if isAlternating(cand): return len(cand) return 0 data = [('abaacdabd', 4), ('beabeefeab', 5), ('asdcbsdcagfsdbgdfanfghbsfdab', 8), ('asvkugfiugsalddlasguifgukvsa', 0), ] for s, expected in data: real = alternate(s) print('{}, expected {}, real {}, result {}'.format(s, expected, real, expected == real))
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0178c69ef9fc5e49cadeaadddb4839eeff3f4a2a
/examples/sac.py
edb4bb7454feec8eb93576ef06326455a559076a
[]
no_license
YangHaha11514/rlkit
3b17de2b4861e12b8c13c849410b7fab335157df
8c2ee5d1602423e352724a0b0845c646688f98df
refs/heads/master
2020-03-14T06:22:53.568011
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2018-04-29T09:46:53
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""" Run PyTorch Soft Actor Critic on HalfCheetahEnv. NOTE: You need PyTorch 0.3 or more (to have torch.distributions) """ import gym import numpy as np import rlkit.torch.pytorch_util as ptu from rlkit.envs.wrappers import NormalizedBoxEnv from rlkit.launchers.launcher_util import setup_logger from rlkit.torch.sac.policies import TanhGaussianPolicy from rlkit.torch.sac.sac import SoftActorCritic from rlkit.torch.networks import FlattenMlp def experiment(variant): env = NormalizedBoxEnv(gym.make('HalfCheetah-v1')) obs_dim = int(np.prod(env.observation_space.shape)) action_dim = int(np.prod(env.action_space.shape)) net_size = variant['net_size'] qf = FlattenMlp( hidden_sizes=[net_size, net_size], input_size=obs_dim + action_dim, output_size=1, ) vf = FlattenMlp( hidden_sizes=[net_size, net_size], input_size=obs_dim, output_size=1, ) policy = TanhGaussianPolicy( hidden_sizes=[net_size, net_size], obs_dim=obs_dim, action_dim=action_dim, ) algorithm = SoftActorCritic( env=env, policy=policy, qf=qf, vf=vf, **variant['algo_params'] ) if ptu.gpu_enabled(): algorithm.cuda() algorithm.train() if __name__ == "__main__": # noinspection PyTypeChecker variant = dict( algo_params=dict( num_epochs=1000, num_steps_per_epoch=1000, num_steps_per_eval=1000, batch_size=128, max_path_length=999, discount=0.99, soft_target_tau=0.001, policy_lr=3E-4, qf_lr=3E-4, vf_lr=3E-4, ), net_size=300, ) setup_logger('name-of-experiment', variant=variant) experiment(variant)
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/src/core/scoring/apps/online/apps/search_engines/management/commands/search_yandex.py
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daritorius/scoring-example
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# -*- coding: utf-8 -*- from core.main.base.modules.Singleton import Singleton from core.scoring.apps.online.apps.search_engines.actions.YandexActions import YandexActions from django.core.management import BaseCommand from django.utils.translation import ugettext_lazy as _ class Data(object): __metaclass__ = Singleton def __init__(self): setattr(self, 'profile_first_name', 'Иван') setattr(self, 'profile_second_name', 'Иванович') setattr(self, 'profile_third_name', 'Иванов') setattr(self, 'profile_birthday', '17-09-1986') class Command(BaseCommand): actions = YandexActions() def handle(self, *args, **options): data = Data() self.actions.check_simple_search(data)
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/fbseries.py
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def fibonacci(n): if(n <= 1): return n else: return(fibonacci(n-1) + fibonacci(n-2)) n = int(input("Enter no of terms:")) print("Fibonacci sequence:") for i in range(n): print (fibonacci(i))
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# -*- coding: utf-8 -*- from proj.core.utils.crispymixin import * from .models import * class FeedForm(CrispyModelForm): content = forms.CharField(widget=forms.Textarea()) class Meta: model = Feed fields = ('content',) def get_layout(self, *args, **kwargs): self.helper.label_class = 'sr-only' self.helper.field_class = '' self.helper.form_method = 'post' return Layout( Div( Field('content', rows=2, placeholder=u'Напишите, что у вас нового'), css_class='col-md-12' ), StrictButton(u'<i class="fa fa-share"></i> Отправить', type='submit', css_class='btn-primary', name='post', value='1'), )
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/app.py
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from flask import Flask,render_template import sqlite3 app = Flask(__name__) @app.route('/') def index(): return render_template("index.html") @app.route('/index') def home(): #return render_template("index.html") return index() @app.route('/movie') def movie(): datalist = [] conn = sqlite3.connect("movie.db") cur = conn.cursor() sql = "select * from movie250" data = cur.execute(sql) for item in data: datalist.append(item) cur.close() conn.close() return render_template("movie.html",movies = datalist) @app.route('/score') def score(): score = [] #评分 num = [] #每个评分所统计出的电影数量 conn = sqlite3.connect("movie.db") cur = conn.cursor() sql = "select score,count(score) from movie250 group by score" data = cur.execute(sql) for item in data: score.append(str(item[0])+"分") num.append(item[1]) cur.close() conn.close() return render_template("score.html",score = score,num = num) @app.route('/word') def word(): return render_template("word.html") @app.route('/team') def team(): return render_template("team.html") if __name__ == '__main__': app.run()
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#!/usr/bin/env python import os import sys if __name__ == "__main__": os.environ.setdefault("DJANGO_SETTINGS_MODULE", "csvt05.settings") try: from django.core.management import execute_from_command_line except ImportError: # The above import may fail for some other reason. Ensure that the # issue is really that Django is missing to avoid masking other # exceptions on Python 2. try: import django except ImportError: raise ImportError( "Couldn't import Django. Are you sure it's installed and " "available on your PYTHONPATH environment variable? Did you " "forget to activate a virtual environment?" ) raise execute_from_command_line(sys.argv)
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/initial.py
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prathyu0398/Freshworks_assignment
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import threading from threading import * import time import json #https://github.com/sriharsha9598/CRD-operations-of-a-file-based-key-value-data-store f=open("data.json",) d=json.load(f) def create(key, value, timeout=0): if key in d: print("error: this key already exists") # error message1 else: if (key.isalpha()): if len(d) < (1024 * 1020 * 1024) and value <= ( 16 * 1024 * 1024): if timeout == 0: l = [value, timeout] else: l = [value, time.time() + timeout] if len(key) <= 32: # constraints for input key_name capped at 32chars d[key] = l else: print("Error: Memory limit exceeded!! ") # error message2 else: print( "Error: Invalind key_name!! key_name must contain only alphabets and no special characters or numbers") # error message3 def read(key): if key not in d: print("Error: given key does not exist in database. Please enter a valid key") # error message4 else: b = d[key] if b[1] != 0: if time.time() < b[1]: stri = str(key) + ":" + str( b[0]) return stri else: print("Error: time-to-live of", key, "has expired") # error message5 else: stri = str(key) + ":" + str(b[0]) return stri def delete(key): if key not in d: print("Error: Given key does not exist in database. Please enter a valid key") # error message4 else: b = d[key] if b[1] != 0: if time.time() < b[1]: # comparing the current time with expiry time del d[key] print("key is successfully deleted") else: print("error: time-to-live of", key, "has expired") # error message5 else: del d[key] print("key is successfully deleted") def modify(key, value): b = d[key] if b[1] != 0: if time.time() < b[1]: if key not in d: print("error: given key does not exist in database. Please enter a valid key") # error message6 else: l = [] l.append(value) l.append(b[1]) d[key] = l else: print("error: time-to-live of", key, "has expired") # error message5 else: if key not in d: print("error: given key does not exist in database. Please enter a valid key") # error message6 else: l = [] l.append(value) l.append(b[1]) d[key] = l
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/Source/Interfaces/GraylogInterface.py
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from . import _Interface from collections import deque import logging import threading import socket import json import time class GraylogInterface(_Interface.Interface): def __init__(self, graylog_address=None, graylog_port=None, **kwargs): super().__init__(**kwargs) self.gl_address = graylog_address self.gl_port = graylog_port def _send_message(self, msg, retries=3, **kwargs): """ Send a single message to a graylog input; the socket must be closed after each individual message, otherwise Graylog will interpret it as a single large message. :param msg: dict """ msg_string = json.dumps(msg) if not msg_string: return while True: try: sock = self._connect_to_graylog_input() except OSError as e: # For issue: OSError: [Errno 99] Cannot assign requested address #6 if retries: logging.error("Error connecting to graylog: {}. Retrying {} more times".format(e, retries)) retries -= 1 time.sleep(30) else: logging.error("Error connecting to graylog: {}. Giving up for this message: {}".format( e, msg_string)) self.unsuccessfully_sent += 1 return else: break try: sock.sendall(msg_string.encode()) except Exception as e: self.unsuccessfully_sent += 1 logging.error("Error sending message to graylog: {}.".format(e)) sock.close() self.successfully_sent += 1 def _connect_to_graylog_input(self): """ Return a socket connected to the Graylog input. """ s = socket.socket(socket.AF_INET, socket.SOCK_STREAM) s.connect((self.gl_address, int(self.gl_port))) return s
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/delfin/drivers/dell_emc/unity/unity.py
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# Copyright 2020 The SODA Authors. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. from oslo_log import log from delfin.common import constants from delfin.drivers import driver from delfin.drivers.dell_emc.unity import rest_handler, alert_handler, consts from delfin.drivers.dell_emc.unity.alert_handler import AlertHandler LOG = log.getLogger(__name__) class UNITYStorDriver(driver.StorageDriver): def __init__(self, **kwargs): super().__init__(**kwargs) self.rest_handler = rest_handler.RestHandler(**kwargs) self.rest_handler.login() def reset_connection(self, context, **kwargs): self.rest_handler.logout() self.rest_handler.verify = kwargs.get('verify', False) self.rest_handler.login() def close_connection(self): self.rest_handler.logout() def get_storage(self, context): system_info = self.rest_handler.get_storage() capacity = self.rest_handler.get_capacity() version_info = self.rest_handler.get_soft_version() disk_info = self.rest_handler.get_disk_info() status = constants.StorageStatus.OFFLINE if system_info is not None and capacity is not None: system_entries = system_info.get('entries') for system in system_entries: name = system.get('content').get('name') model = system.get('content').get('model') serial_number = system.get('content').get('serialNumber') health_value = system.get('content').get('health').get('value') if health_value in consts.HEALTH_OK: status = constants.StorageStatus.NORMAL else: status = constants.StorageStatus.ABNORMAL break capacity_info = capacity.get('entries') for per_capacity in capacity_info: free = per_capacity.get('content').get('sizeFree') total = per_capacity.get('content').get('sizeTotal') used = per_capacity.get('content').get('sizeUsed') subs = per_capacity.get('content').get('sizeSubscribed') break soft_version = version_info.get('entries') for soft_info in soft_version: version = soft_info.get('content').get('id') break disk_entrier = disk_info.get('entries') raw = 0 for disk in disk_entrier: raw = raw + int(disk.get('content').get('rawSize')) result = { 'name': name, 'vendor': 'DELL EMC', 'model': model, 'status': status, 'serial_number': serial_number, 'firmware_version': version, 'location': '', 'subscribed_capacity': int(subs), 'total_capacity': int(total), 'raw_capacity': int(raw), 'used_capacity': int(used), 'free_capacity': int(free) } return result def list_storage_pools(self, context): pool_info = self.rest_handler.get_all_pools() pool_list = [] pool_type = constants.StorageType.BLOCK if pool_info is not None: pool_entries = pool_info.get('entries') for pool in pool_entries: health_value = pool.get('content').get('health').get('value') if health_value in consts.HEALTH_OK: status = constants.StorageStatus.NORMAL else: status = constants.StorageStatus.ABNORMAL p = { 'name': pool.get('content').get('name'), 'storage_id': self.storage_id, 'native_storage_pool_id': str( pool.get('content').get('id')), 'description': pool.get('content').get('description'), 'status': status, 'storage_type': pool_type, 'total_capacity': int(pool.get('content'). get('sizeTotal')), 'subscribed_capacity': int(pool.get('content').get( 'sizeSubscribed')), 'used_capacity': int(pool.get('content').get('sizeUsed')), 'free_capacity': int(pool.get('content').get('sizeFree')) } pool_list.append(p) return pool_list def volume_handler(self, volumes, volume_list): if volumes is not None: vol_entries = volumes.get('entries') for volume in vol_entries: total = volume.get('content').get('sizeTotal') used = volume.get('content').get('sizeAllocated') vol_type = constants.VolumeType.THICK if volume.get('content').get('isThinEnabled') is True: vol_type = constants.VolumeType.THIN compressed = True deduplicated = volume.get('content').\ get('isAdvancedDedupEnabled') health_value = volume.get('content').get('health').get('value') if health_value in consts.HEALTH_OK: status = constants.StorageStatus.NORMAL else: status = constants.StorageStatus.ABNORMAL v = { 'name': volume.get('content').get('name'), 'storage_id': self.storage_id, 'description': volume.get('content').get('description'), 'status': status, 'native_volume_id': str(volume.get('content').get('id')), 'native_storage_pool_id': volume.get('content').get('pool').get('id'), 'wwn': volume.get('content').get('wwn'), 'type': vol_type, 'total_capacity': int(total), 'used_capacity': int(used), 'free_capacity': int(total - used), 'compressed': compressed, 'deduplicated': deduplicated } volume_list.append(v) def list_volumes(self, context): page_size = 1 volume_list = [] while True: luns = self.rest_handler.get_all_luns(page_size) if 'entries' not in luns: break if len(luns['entries']) < 1: break self.volume_handler(luns, volume_list) page_size = page_size + 1 return volume_list def list_alerts(self, context, query_para=None): page_size = 1 alert_model_list = [] while True: alert_list = self.rest_handler.get_all_alerts(page_size) if 'entries' not in alert_list: break if len(alert_list['entries']) < 1: break alert_handler.AlertHandler() \ .parse_queried_alerts(alert_model_list, alert_list, query_para) page_size = page_size + 1 return alert_model_list def add_trap_config(self, context, trap_config): pass def remove_trap_config(self, context, trap_config): pass @staticmethod def parse_alert(context, alert): return AlertHandler.parse_alert(context, alert) def clear_alert(self, context, alert): return self.rest_handler.remove_alert(context, alert)
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/panel/config/admin/management_data/CustomPages/Member.py
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lazypanda10117/CICSA-Ranking-Platform
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from cicsa_ranking.models import Member from .AbstractCustomClass import AbstractCustomClass from panel.component.CustomElements import Choices from misc.CustomFunctions import MiscFunctions, RequestFunctions, LogFunctions class MemberView(AbstractCustomClass): def __init__(self, request): self.base_class = Member self.validation_table = { 'base_table_invalid': {'_state'}, 'base_form_invalid': {'_state', 'id'}, } super().__init__(request, self.base_class, self.validation_table) # View Process Functions def abstractFormProcess(self, action, **kwargs): try: post_dict = dict(self.request.POST) dispatcher = super().populateDispatcher() if dispatcher.get(action): member_id = kwargs.pop('id', None) member = self.useAPI(self.base_class).editSelf(id=member_id) else: member = self.base_class() member.member_name = RequestFunctions.getSingleRequestObj(post_dict, 'member_name') member.member_school = RequestFunctions.getSingleRequestObj(post_dict, 'member_school') member.member_email = RequestFunctions.getSingleRequestObj(post_dict, 'member_email') member.member_status = RequestFunctions.getSingleRequestObj(post_dict, 'member_status') if not action == 'delete': member.save() LogFunctions.generateLog( self.request, 'admin', LogFunctions.makeLogQuery(self.base_class, action.title(), id=member.id)) if action == 'delete': member.delete() except Exception: print({"Error": "Cannot Process " + action.title() + " Request."}) # View Generating Functions # Form Generating Functions def getFieldData(self, **kwargs): action = kwargs.pop('action') element_id = kwargs.pop('element_id') field_data_dispatcher = self.populateDispatcher() if field_data_dispatcher.get(action): field_data = MiscFunctions.filterDict(self.useAPI(self.base_class).getSelf(id=element_id).__dict__.items(), self.validation_table['base_form_invalid']) return field_data return None def getChoiceData(self): choice_data = dict() choice_data["member_status"] = Choices().getStatusChoices() choice_data["member_school"] = Choices().getSchoolChoices() return choice_data def getDBMap(self, data): return None def getMultiChoiceData(self): return None def getSearchElement(self, **kwargs): return None # Table Generating Functions def getTableSpecificHeader(self): return [field.name for field in self.base_class._meta.get_fields() if field.name not in self.validation_table['base_table_invalid']] def getTableRowContent(self, content): field_data = MiscFunctions.filterDict(self.useAPI(self.base_class).getSelf(id=content.id).__dict__.items(), self.validation_table['base_table_invalid']) field_data = self.updateChoiceAsValue(field_data, self.getChoiceData()) field_data = MiscFunctions.grabValueAsList(field_data) return field_data
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/code/private_ip_finder/poc001/private_ip_finder.py
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#!/usr/bin/env python3 import socket import traceback def get_ip()->str: ip_address = None try: s = socket.socket(socket.AF_INET, socket.SOCK_DGRAM) s.connect(("8.8.8.8", 443)) ip_address = '{}'.format(s.getsockname()[0]) s.close() except: traceback.print_exc() return ip_address if __name__ == '__main__': print(get_ip()) # EOF
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#Set la 1 container,tuy nhien ko su dung nhieu bang list hay tuple #Duoc gioi han boi {}, tat ca nhung gi nam trong do la nhung phan tu cua Set #Cac phan tu cua Set duoc phan cach nhau boi dau , #Set khong chua nhieu hon 1 phan tu trung lap #chi chua hashable object set_1={69,96} print(set_1) #{96,69} set_2={'HowKteam'} print(set_2) #{'HowKteam'} #unhashable type:list #khong chay voi list #khong chay voi set trong set set_2={1,2,{'HowKteam'}} #Typeerror set_2={1,1,1} print(set_2) #{1} set_2=set((1,2,3)) #{1,2,3} set_2=set('HowKteam') #{'t','m','H','o','e','a','K','w'} print({1,2,3,4}-{2,3}) #{1,4} print({1,2,3,4} & {{4,5}) #{4} print({1,2,3} | {4,5}) #{1,2,3,4,5} print({1,2,3}^{3,4}) #{1,2,4} set1={1,2,3,4} set1.remove(1) #{2,3,4} set1.discard(5) #{1,2,3,4},giong remove nhung phan tu ko co trong set ko bao loi set1.add(5) #{1,2,3,4,5}
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/217. Contains Duplicate.py
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class Solution: def containsDuplicate(self, nums: List[int]) -> bool: # s = set() # for n in nums: # if n in s: # return True # s.add(n) # return False return not (len(set(nums)) == len(nums))
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/fusion_map/urls.py
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""" fusion_map URL Configuration """ from django.urls import path from main import api, views urlpatterns = [ path('', views.index), path('api/1/locations/add', api.add_location), path('api/1/locations/removeall', api.remove_all), ]
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/K-Means Clustering with word embedded data/RunKMeans.py
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KashishNarang94/DataMiningCSE506
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import KMeansImplement QuestionNo=[2,3,4,5] flag_normalize=[0,1] KMeansImplement.Kmeans(flag_normalize[0],QuestionNo[0]) KMeansImplement.Kmeans(flag_normalize[1],QuestionNo[1]) KMeansImplement.Kmeans(flag_normalize[0],QuestionNo[2]) KMeansImplement.Kmeans(flag_normalize[0],QuestionNo[3])
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/manage.py
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2023-01-24T06:38:32.783453
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#!/usr/bin/env python """Django's command-line utility for administrative tasks.""" import os import sys def main(): os.environ.setdefault('DJANGO_SETTINGS_MODULE', 'oceantt.settings') try: from django.core.management import execute_from_command_line except ImportError as exc: raise ImportError( "Couldn't import Django. Are you sure it's installed and " "available on your PYTHONPATH environment variable? Did you " "forget to activate a virtual environment?" ) from exc execute_from_command_line(sys.argv) if __name__ == '__main__': main()
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/src/navigation/scripts/nav_stack/Serial_node.py
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[]
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Team-Anveshak/aurora2018
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#!/usr/bin/env python import string import rospy import serial from rover_msgs.msg import enc from geometry_msgs.msg import Twist pwm=0 port='/dev/ttyACM0' try: ser = serial.Serial(port=port, baudrate=57600, timeout=1) except serial.serialutil.SerialException: pass class Serial(object): def __init__(self,ser): self._ser=ser def callback(self,msg): pwm=msg.linear.x self._ser.write('pwm') rospy.loginfo(pwm) def callback(msg): rospy.loginfo("ok") pwm = msg.linear.x #ser.write('pwm') def main(): rospy.init_node("Serial_node") #try: #ser = serial.Serial(port=port, baudrate=57600, timeout=1) #except serial.serialutil.SerialException: #pass rospy.sleep(3) pub=rospy.Publisher("Encoder",enc, queue_size=10) #classcall=Serial(ser) rospy.Subscriber('/cmd_vel_mux/input/teleop', Twist, callback) rate = rospy.Rate(10) # 10hz while not rospy.is_shutdown(): encvalue=enc() #encvalue.left=2 #encvalue.right=3 line = ser.readline() lineparts = string.split(line,',') #linesparts = lineparts[0].replace(",","") if(lineparts[0]=='e'): #encvalue.left=float(lineparts[1]) #encvalue.right=float(lineparts[2]) try: encvalue.left=float(lineparts[1]) encvalue.right=float(lineparts[2]) rospy.loginfo(float(lineparts[1])) except (ValueError,IndexError): pass rospy.loginfo('running') pub.publish(encvalue) rate.sleep() rospy.spin ser.write('pwm') #rospy.spin #classcall=Serial(pub,ser) #rospy.Subscriber('/cmd_vel', Twist, classcall.callback) #rospy.spin if __name__ == '__main__': try: main() except rospy.ROSInterruptException: pass
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/old/demo/onelinkmanipulator_demo_PID.py
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2021-04-09T03:18:58.858708
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# -*- coding: utf-8 -*- """ Created on Sun Mar 6 15:27:04 2016 @author: alex """ import numpy as np ########################### # Load libs ########################### from AlexRobotics.dynamic import Manipulator from AlexRobotics.control import linear from AlexRobotics.control import ComputedTorque from AlexRobotics.planning import RandomTree from AlexRobotics.control import DPO ########################### # Objectives ########################### x_start = np.array([-3.0, 0.0]) x_goal = np.array([ 0.0, 0.0]) ########################### # Create objects ########################### Robot = Manipulator.OneLinkManipulator() PD = linear.PD( kp = 5 , kd = 2 ) PID = linear.PID( kp = 5 , kd = 2 , ki = 4 ) CTC = ComputedTorque.ComputedTorqueController( Robot ) SLD = ComputedTorque.SlidingModeController( Robot ) RRT = RandomTree.RRT( Robot , x_start ) VI = DPO.ValueIteration1DOF( Robot , 'quadratic' ) ############################ # Params ############################ tmax = 8 # max motor torque Robot.u_ub = np.array([ tmax]) # Control Upper Bounds Robot.u_lb = np.array([-tmax]) # Control Lower Bounds RRT.x_start = x_start RRT.discretizeactions( 3 ) RRT.dt = 0.1 RRT.goal_radius = 0.3 RRT.max_nodes = 5000 RRT.max_solution_time = 5 RRT.dyna_plot = True RRT.dyna_node_no_update = 10 RRT.traj_ctl_kp = 25 RRT.traj_ctl_kd = 10 PID.dt = 0.001 CTC.w0 = 2 SLD.lam = 1 SLD.nab = 0 SLD.D = 5 ########################### # Offline Plannning ########################### #RRT.find_path_to_goal( x_goal ) #RRT.plot_2D_Tree() ########################### # Offline Optimization ########################### #VI.first_step() #VI.load_data( 'data/' + 'R1' + 'quadratic' ) #VI.compute_steps(1) # ## Plot Value Iteration Results #ValueIterationAlgo.plot_raw() #ValueIterationAlgo.plot_J_nice( 2 ) ########################### # Assign controller ########################### #Robot.ctl = PD.ctl Robot.ctl = PID.ctl #Robot.ctl = CTC.ctl #Robot.ctl = SLD.ctl #Robot.ctl = RRT.trajectory_controller #VI.assign_interpol_controller() ########################### # Simulation ########################### Robot.plotAnimation( x_start , tf=10, n=10001, solver='euler' ) ########################### # Plots ########################### Robot.Sim.phase_plane_trajectory() #Robot.Sim.phase_plane_trajectory( PP_OL = False , PP_CL = True ) Robot.Sim.plot_CL() ########################### # and more ########################### #from AlexRobotics.dynamic import CustomManipulator #BoeingArm = CustomManipulator.BoeingArm() #BoeingArm.plot3DAnimation( x0 = np.array([0.2,0,0,0,0,0]) ) # Hold script in console import matplotlib.pyplot as plt plt.show()
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/core/migrations/0003_pontosturisticos_atracoes.py
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[]
no_license
agmguerra/pontos_turisticos
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2020-08-14T14:18:39.406632
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# Generated by Django 2.2.6 on 2019-10-15 01:51 from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('atracoes', '0001_initial'), ('core', '0002_pontosturisticos_aprovado'), ] operations = [ migrations.AddField( model_name='pontosturisticos', name='atracoes', field=models.ManyToManyField(to='atracoes.Atracao'), ), ]
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/fts_base/wizard/__init__.py
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Therp/fulltextsearch
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import fts_config
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/__init__.py
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dilkuwor/empproj
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from flask import Flask from flask_restful import Api from timeapi.resources.employee import Employee, EmployeeCollection from timeapi.resources.project import Project, ProjectCollection from timeapi.resources.project_employee import ProjectEmployee from apispec import APISpec from flask_apispec.extension import FlaskApiSpec app = Flask(__name__) api = Api(app) api = Api(app) api.add_resource(Employee, '/employees/<string:employee_id>') api.add_resource(EmployeeCollection, '/employees') api.add_resource(ProjectCollection, '/projects') api.add_resource(Project, '/projects/<string:project_id>') api.add_resource(ProjectEmployee, '/projects/<string:project_id>/employees') app.config.update({ 'APISPEC_SPEC': APISpec( title='timeapi', version='v1', plugins=['apispec.ext.marshmallow'], ), 'APISPEC_SWAGGER_URL': '/spec/', }) docs = FlaskApiSpec(app) docs.register(Employee) docs.register(EmployeeCollection) docs.register(ProjectCollection) docs.register(Project) docs.register(ProjectEmployee) ''' if __name__ == '__main__': app.run(debug=True) '''
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/PythonAndCoding/tweettweet.py
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animeshsrivastava246/PythonWork
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import tweepy,time auth = tweepy.OAuthHandler(consumer_key, consumer_secret) auth.set_access_token(access_token, access_token_secret) api = tweepy.API(auth) user=api.me() def limit_handler(cursor): try: while True: yield cursor.next() except tweepy.RateLimitError: time.sleep(300)#miliseconds for follower in limit_handler(tweepy.Cursor(api.followers).items()): print(follower.name) #print(user.followers_count) #print(user.screen_name) #print(user.name) #public_tweets = api.home_timeline() #for tweet in public_tweets: # print(tweet.text) # Tweepy.org DOCUMENTATION
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/postGRE_script.py
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CodeyBank/simple-database-using-postgres
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import psycopg2 def create_table(): connection = psycopg2.connect("dbname='shop' user='postgres' password='Thebossm@#995' host='localhost' port='5432'") cur = connection.cursor() cur.execute("CREATE TABLE IF NOT EXISTS store (item TEXT, quantity INTEGER, price REAL)") connection.commit() connection.close() def insert(item, quantity, price): connection = psycopg2.connect("dbname='shop' user='postgres' password='Thebossm@#995' host='localhost' port='5432'") cur = connection.cursor() cur.execute("INSERT INTO store VALUES('%s', '%s', '%s')" %(item, quantity, price)) #cur.execute("INSERT INTO store VALUES(%s, %s, %s)", (item, quantity, price)) #Alternative method to avoid database injections from hackers connection.commit() connection.close() #insert("Coffee cup", 10, 2.5) # This function deletes a row. pass the row item as an argument def delete_item(item): connection = psycopg2.connect("dbname='shop' user='postgres' password='Thebossm@#995' host='localhost' port='5432'") cur = connection.cursor() cur.execute("DELETE FROM store WHERE item=%s", (item,)) #when there is only one parameter, always end with ',' connection.commit() connection.close() def view_db(): connection = psycopg2.connect("dbname='shop' user='postgres' password='Thebossm@#995' host='localhost' port='5432'") cur = connection.cursor() cur.execute("SELECT * FROM store") rows = cur.fetchall() # .fetchall() methodReturns the rows of a DB as a list of a tuples connection.close() return rows def update_db(quantity, price, item): connection = psycopg2.connect("dbname='shop' user='postgres' password='Thebossm@#995' host='localhost' port='5432'") cur = connection.cursor() cur.execute("UPDATE store SET quantity=%s, price=%s WHERE item=%s", (quantity, price, item)) rows = cur.fetchall() # .fetchall() methodReturns the rows of a DB as a list of a tuples connection.close() return rows create_table() delete_item("Orange") print(view_db())
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DataEconomistDK/Recession-Predictor
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2021-04-23T17:42:23.682241
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""" This module gets data from FRED and Yahoo Finance, builds some features, and saves the data into the respective filepaths. """ import re from io import StringIO import json from datetime import datetime, timedelta import requests as req import pandas as pd import RecessionPredictor_paths as path class YahooData: """ Retrieves data from Yahoo Finance. Original code source: https://stackoverflow.com/questions/44225771/scraping-historical-data-from-yahoo-finance-with-python """ timeout = 2 crumb_link = 'https://finance.yahoo.com/quote/{0}/history?p={0}' crumble_regex = r'CrumbStore":{"crumb":"(.*?)"}' quote_link = 'https://query1.finance.yahoo.com/v7/finance/download/{quote}?period1={dfrom}&period2={dto}&interval=1mo&events=history&crumb={crumb}' def __init__(self, symbol, days_back=7): """ symbol: ticker symbol for the asset to be pulled. """ self.symbol = str(symbol) self.session = req.Session() self.dt = timedelta(days=days_back) def get_crumb(self): """ Original code source: https://stackoverflow.com/questions/44225771/scraping-historical-data-from-yahoo-finance-with-python """ response = self.session.get(self.crumb_link.format(self.symbol), timeout=self.timeout) response.raise_for_status() match = re.search(self.crumble_regex, response.text) if not match: raise ValueError('Could not get crumb from Yahoo Finance') else: self.crumb = match.group(1) def get_quote(self): """ Original code source: https://stackoverflow.com/questions/44225771/scraping-historical-data-from-yahoo-finance-with-python """ if not hasattr(self, 'crumb') or len(self.session.cookies) == 0: self.get_crumb() now = datetime.utcnow() dateto = int(now.timestamp()) datefrom = -630961200 # line in original code: datefrom = int((now - self.dt).timestamp()) url = self.quote_link.format(quote=self.symbol, dfrom=datefrom, dto=dateto, crumb=self.crumb) response = self.session.get(url) response.raise_for_status() return pd.read_csv(StringIO(response.text), parse_dates=['Date']) class DataSeries: """ Contains methods and objects to retrieve data from FRED and Yahoo Finance. """ def __init__(self): self.dates = [] self.values = [] def fred_response(self, params): """ Makes requests to the FRED API. params: dictionary, FRED API parameters. """ params = dict(params) fred_request = req.get(url='https://api.stlouisfed.org/fred/series/observations', params=params) fred_json = json.loads(fred_request.text)['observations'] for observation in fred_json: self.dates.append(str(observation['date'])) self.values.append(float(observation['value'])) def yahoo_response(self, series_id): """ Retrieves data from Yahoo Finance, and performs timestamp adjustments. series_id: ticker symbol for the asset to be pulled. """ series_id = str(series_id) series_dataframe = YahooData(series_id).get_quote()[::-1] series_dataframe.reset_index(inplace=True) series_dataframe.drop('index', axis=1, inplace=True) most_recent_day = datetime.strptime(str(series_dataframe['Date'][0])[:10], '%Y-%m-%d').day if most_recent_day != 1: series_dataframe = series_dataframe[1:] series_dataframe.reset_index(inplace=True) series_dataframe.drop('index', axis=1, inplace=True) self.dates.extend([str(series_dataframe['Date'][index])[:10] for index in range(0, len(series_dataframe))]) self.values.extend([float(series_dataframe['Adj Close'][index]) for index in range(0, len(series_dataframe))]) class MakeDataset: """ The manager class for this module. """ def __init__(self): """ fred_series_ids: identifiers for FRED data series. yahoo series_ids: identifiers for Yahoo Finance data series. """ self.fred_series_ids = {'Non-farm_Payrolls': 'PAYEMS', 'Civilian_Unemployment_Rate': 'UNRATE', 'Effective_Fed_Funds': 'FEDFUNDS', 'CPI_All_Items': 'CPIAUCSL', '10Y_Treasury_Rate': 'GS10', '5Y_Treasury_Rate': 'GS5', '3_Month_T-Bill_Rate': 'TB3MS', 'IPI': 'INDPRO'} self.yahoo_series_ids = {'S&P_500_Index': '^GSPC'} self.primary_dictionary_output = {} self.primary_df_output = pd.DataFrame() self.shortest_series_name = '' self.shortest_series_length = 1000000 self.secondary_df_output = pd.DataFrame() def get_fred_data(self): """ Cycles through "fred_series"ids" to get data from the FRED API. """ import time now = datetime.now() month = now.strftime('%m') year = now.year most_recent_date = '{}-{}-07'.format(year, month) print('\nGetting data from FRED API as of {}...'.format(most_recent_date)) for series_name in list(self.fred_series_ids.keys()): series_data = DataSeries() series_id = self.fred_series_ids[series_name] print('\t|--Getting data for {}({}).'.format(series_name, series_id)) params = {'series_id': series_id, 'api_key': path.fred_api_key, 'file_type': 'json', 'sort_order': 'desc', 'realtime_start': most_recent_date, 'realtime_end': most_recent_date} success = False while success == False: try: series_data.fred_response(params) except json.JSONDecodeError: delay = 5 print('\t --CONNECTION ERROR--', '\n\t Sleeping for {} seconds.'.format(delay)) time.sleep(delay) else: success = True self.primary_dictionary_output[series_name] = series_data print('Finished getting data from FRED API!') def get_yahoo_data(self): """ Cycles through "yahoo_series"ids" to get data from the Yahoo Finance. """ import time print('\nGetting data from Yahoo Finance...') for series_name in list(self.yahoo_series_ids.keys()): series_data = DataSeries() series_id = self.yahoo_series_ids[series_name] print('\t|--Getting data for {}({}).'.format(series_name, series_id)) success = False while success == False: try: series_data.yahoo_response(series_id) except req.HTTPError: delay = 5 print('\t --CONNECTION ERROR--', '\n\t Sleeping for {} seconds.'.format(delay)) time.sleep(delay) else: success = True self.primary_dictionary_output[series_name] = series_data print('Finished getting data from Yahoo Finance!') def find_shortest_series(self): """ Finds the length and name of the shortes series in the primary dataset. """ for series_name in self.primary_dictionary_output.keys(): series_data = self.primary_dictionary_output[series_name] if len(series_data.dates) < self.shortest_series_length: self.shortest_series_length = len(series_data.dates) self.shortest_series_name = series_name def combine_primary_data(self): """ Combines primary data into a single dictionary (such that each series is the same length and is time-matched to each other) and saves it as a json object. """ print('\nCombining primary dataset...') now = datetime.now() current_month = int(now.strftime('%m')) current_year = now.year dates = [] for months_ago in range(0, self.shortest_series_length): if current_month < 10: dates.append('{}-0{}-01'.format(current_year, current_month)) else: dates.append('{}-{}-01'.format(current_year, current_month)) if current_month == 1: current_month = 12 current_year -= 1 else: current_month -= 1 self.primary_df_output['Dates'] = dates for series_name in self.primary_dictionary_output.keys(): series_data = self.primary_dictionary_output[series_name] self.primary_df_output[series_name] = series_data.values[:self.shortest_series_length] print('Finished combining primary dataset!') print('\t|--Saving primary dataset to {}'.format(path.data_primary)) self.primary_df_output.to_json(path.data_primary) self.primary_df_output.to_json(path.data_primary_most_recent) print('\nPrimary dataset saved to {}'.format(path.data_primary_most_recent)) def get_primary_data(self): """ Gets primary data from FRED API and Yahoo Finance. """ print('\nGetting primary data from APIs...') self.get_fred_data() self.get_yahoo_data() self.find_shortest_series() self.combine_primary_data() def calculate_secondary_data(self): """ Builds some features from the primary dataset to create a secondary dataset. """ dates = [] payrolls_3mo = [] payrolls_12mo = [] unemployment_rate = [] unemployment_rate_12mo_chg = [] real_fed_funds = [] real_fed_funds_12mo = [] CPI_3mo = [] CPI_12mo = [] treasury_10Y_12mo = [] treasury_3M_12mo = [] treasury_10Y_3M_spread = [] treasury_10Y_5Y_spread = [] treasury_10Y_3M_spread_12mo = [] sp_500_3mo = [] sp_500_12mo = [] IPI_3mo = [] IPI_12mo = [] for index in range(0, len(self.primary_df_output) - 12): dates.append(self.primary_df_output['Dates'][index]) payrolls_3mo_pct_chg = (self.primary_df_output['Non-farm_Payrolls'][index] / self.primary_df_output['Non-farm_Payrolls'][index + 3]) - 1 payrolls_3mo.append(((1 + payrolls_3mo_pct_chg) ** 4) - 1) payrolls_12mo.append((self.primary_df_output['Non-farm_Payrolls'][index] / self.primary_df_output['Non-farm_Payrolls'][index + 12]) - 1) unemployment_rate.append(self.primary_df_output['Civilian_Unemployment_Rate'][index]) unemployment_rate_12mo_chg.append((self.primary_df_output['Civilian_Unemployment_Rate'][index]) - self.primary_df_output['Civilian_Unemployment_Rate'][index + 12]) CPI_3mo_pct_chg = (self.primary_df_output['CPI_All_Items'][index] / self.primary_df_output['CPI_All_Items'][index + 3]) - 1 CPI_3mo.append(((1 + CPI_3mo_pct_chg) ** 4) - 1) CPI_12mo_pct_chg = (self.primary_df_output['CPI_All_Items'][index] / self.primary_df_output['CPI_All_Items'][index + 12]) - 1 CPI_12mo.append(CPI_12mo_pct_chg) real_fed_funds.append(self.primary_df_output['Effective_Fed_Funds'][index] - (CPI_12mo_pct_chg * 100)) real_fed_funds_12mo.append(self.primary_df_output['Effective_Fed_Funds'][index] - self.primary_df_output['Effective_Fed_Funds'][index + 12]) treasury_10Y_12mo.append(self.primary_df_output['10Y_Treasury_Rate'][index] - self.primary_df_output['10Y_Treasury_Rate'][index + 12]) treasury_3M_12mo.append(self.primary_df_output['3_Month_T-Bill_Rate'][index] - self.primary_df_output['3_Month_T-Bill_Rate'][index + 12]) treasury_10Y_3M_spread_today = (self.primary_df_output['10Y_Treasury_Rate'][index] - self.primary_df_output['3_Month_T-Bill_Rate'][index]) treasury_10Y_3M_spread.append(treasury_10Y_3M_spread_today) treasury_10Y_3M_spread_12mo_ago = (self.primary_df_output['10Y_Treasury_Rate'][index + 12] - self.primary_df_output['3_Month_T-Bill_Rate'][index + 12]) treasury_10Y_3M_spread_12mo.append(treasury_10Y_3M_spread_today - treasury_10Y_3M_spread_12mo_ago) treasury_10Y_5Y_spread_today = (self.primary_df_output['10Y_Treasury_Rate'][index] - self.primary_df_output['5Y_Treasury_Rate'][index]) treasury_10Y_5Y_spread.append(treasury_10Y_5Y_spread_today) sp_500_3mo.append((self.primary_df_output['S&P_500_Index'][index] / self.primary_df_output['S&P_500_Index'][index + 3]) - 1) sp_500_12mo.append((self.primary_df_output['S&P_500_Index'][index] / self.primary_df_output['S&P_500_Index'][index +12]) - 1) IPI_3mo_pct_chg = (self.primary_df_output['IPI'][index] / self.primary_df_output['IPI'][index + 3]) - 1 IPI_3mo.append(((1 + IPI_3mo_pct_chg) ** 4) - 1) IPI_12mo_pct_chg = (self.primary_df_output['IPI'][index] / self.primary_df_output['IPI'][index + 12]) - 1 IPI_12mo.append(IPI_12mo_pct_chg) self.secondary_df_output = pd.DataFrame({ 'Dates': dates, 'Payrolls_3mo_pct_chg_annualized': payrolls_3mo, 'Payrolls_12mo_pct_chg': payrolls_12mo, 'Unemployment_Rate': unemployment_rate, 'Unemployment_Rate_12mo_chg': unemployment_rate_12mo_chg, 'Real_Fed_Funds_Rate': real_fed_funds, 'Real_Fed_Funds_Rate_12mo_chg': real_fed_funds_12mo, 'CPI_3mo_pct_chg_annualized': CPI_3mo, 'CPI_12mo_pct_chg': CPI_12mo, '10Y_Treasury_Rate_12mo_chg': treasury_10Y_12mo, '3M_Treasury_Rate_12mo_chg': treasury_3M_12mo, '3M_10Y_Treasury_Spread': treasury_10Y_3M_spread, '3M_10Y_Treasury_Spread_12mo_chg': treasury_10Y_3M_spread_12mo, '5Y_10Y_Treasury_Spread': treasury_10Y_5Y_spread, 'S&P_500_3mo_chg': sp_500_3mo, 'S&P_500_12mo_chg': sp_500_12mo, 'IPI_3mo_pct_chg_annualized': IPI_3mo, 'IPI_12mo_pct_chg': IPI_12mo}) def create_secondary_data(self): """ Creates and saves the secondary dataset as a json object. """ print('\nCreating secondary dataset from "primary_dataset_most_recent.json"') self.primary_df_output = pd.read_json(path.data_primary_most_recent) self.primary_df_output.sort_index(inplace=True) self.calculate_secondary_data() print('Finished creating secondary dataset!') print('\t|--Saving secondary dataset to {}'.format(path.data_secondary)) self.secondary_df_output.to_json(path.data_secondary) self.secondary_df_output.to_json(path.data_secondary_most_recent) print('\nSecondary dataset saved to {}'.format(path.data_secondary_most_recent)) def get_all_data(self): """ Gets data from primary sources (FRED and Yahoo Finance), then performs preliminary manipulations before saving the data. """ self.get_primary_data() self.create_secondary_data() # FRED citations #U.S. Bureau of Labor Statistics, All Employees: Total Nonfarm Payrolls [PAYEMS], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/PAYEMS #U.S. Bureau of Labor Statistics, Civilian Unemployment Rate [UNRATE], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/UNRATE #Board of Governors of the Federal Reserve System (US), Effective Federal Funds Rate [FEDFUNDS], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/FEDFUNDS #U.S. Bureau of Labor Statistics, Consumer Price Index for All Urban Consumers: All Items [CPIAUCSL], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/CPIAUCSL #Board of Governors of the Federal Reserve System (US), 10-Year Treasury Constant Maturity Rate [GS10], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/GS10 #Board of Governors of the Federal Reserve System (US), 5-Year Treasury Constant Maturity Rate [GS5], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/GS5 #Board of Governors of the Federal Reserve System (US), 3-Month Treasury Bill: Secondary Market Rate [TB3MS], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/TB3MS #Board of Governors of the Federal Reserve System (US), Industrial Production Index [INDPRO], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/INDPRO #MIT License # #Copyright (c) 2019 Terrence Zhang # #Permission is hereby granted, free of charge, to any person obtaining a copy #of this software and associated documentation files (the "Software"), to deal #in the Software without restriction, including without limitation the rights #to use, copy, modify, merge, publish, distribute, sublicense, and/or sell #copies of the Software, and to permit persons to whom the Software is #furnished to do so, subject to the following conditions: # #The above copyright notice and this permission notice shall be included in all #copies or substantial portions of the Software. # #THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR #IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, #FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE #AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER #LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, #OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE #SOFTWARE.
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/own/visualizer.py
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#!/usr/bin/env python3 import numpy as np from matplotlib import pyplot as plt from external import lab3 import warnings class Visualizer(): """ Declares functions used for visualization. """ def __init__(self): pass def visualize_corresp(self, view_1, view_2, p_index): """ Displays the correspondences between the 2 given View objects. """ proj_1 = view_1.projections[:, p_index] proj_2 = view_2.projections[:, p_index] lab3.show_corresp(view_1.image, view_2.image, proj_1, proj_2, vertical=False) plt.title(f'Cameras {view_1.id} ({view_1.camera_center[0,0]:.0f}, {view_1.camera_center[1,0]:.0f}, {view_1.camera_center[2,0]:.0f})' f' and {view_2.id} ({view_2.camera_center[0,0]:.0f}, {view_2.camera_center[1,0]:.0f}, {view_2.camera_center[2,0]:.0f})') #plt.show() def visualize_3d_points(self, book_keeper, m, estimate_color=True): """ Displays a point cloud. --- Input: point_cloud : [int, int] [Nx3] matrix representing the 3D points in the point cloud (N = number of 3D points) """ if estimate_color: est_col = self.estimate_color(book_keeper.Q) z_hat = np.array([0, 0, 1]).reshape(3, 1) point_cloud = book_keeper.P.T # nx3 n = book_keeper.P.shape[1] # only 3d points fig_3d = plt.figure('3d point cloud') ax_3d = fig_3d.gca(projection='3d') if estimate_color: ax_3d.scatter(point_cloud[:, 0], point_cloud[:, 1], point_cloud[:, 2], color=est_col[book_keeper.index_3d_2d]) else: ax_3d.scatter(point_cloud[:, 0], point_cloud[:, 1], point_cloud[:, 2], color=(0, 0, 1)) fig = plt.figure() ax = fig.gca(projection='3d') # Existing 3d points ax.scatter(point_cloud[0:n-m, 0], point_cloud[0:n-m, 1], point_cloud[0:n-m, 2], color=(0, 0, 1)) # Newly added 3d points ax.scatter(point_cloud[n-m:, 0], point_cloud[n-m:, 1], point_cloud[n-m:, 2], color=(1, 0, 1)) for view_idx in range(len(book_keeper.Q)): if book_keeper.Q[view_idx].id == 0: # origin camera pose ax.scatter(book_keeper.Q[view_idx].camera_center[0], book_keeper.Q[view_idx].camera_center[1], book_keeper.Q[view_idx].camera_center[2], color=(0, 1, 0)) ax.text(book_keeper.Q[view_idx].camera_center[0, 0], book_keeper.Q[view_idx].camera_center[1, 0], book_keeper.Q[view_idx].camera_center[2, 0], f'C{book_keeper.Q[view_idx].id}') ax.quiver(0, 0, 0, 0, 0, 1) elif view_idx == len(book_keeper.Q) - 1: # newly added camera pose ax.scatter(book_keeper.Q[view_idx].camera_center[0], book_keeper.Q[view_idx].camera_center[1], book_keeper.Q[view_idx].camera_center[2], color=(1, 0, 0)) ax.text(book_keeper.Q[view_idx].camera_center[0, 0], book_keeper.Q[view_idx].camera_center[1, 0], book_keeper.Q[view_idx].camera_center[2, 0], f'C{book_keeper.Q[view_idx].id}') view_direction = book_keeper.Q[view_idx].rotation_matrix.T @ z_hat ax.quiver(book_keeper.Q[view_idx].camera_center[0], book_keeper.Q[view_idx].camera_center[1], book_keeper.Q[view_idx].camera_center[2], view_direction[0], view_direction[1], view_direction[2]) else: # already added camera poses ax.scatter(book_keeper.Q[view_idx].camera_center[0], book_keeper.Q[view_idx].camera_center[1], book_keeper.Q[view_idx].camera_center[2], color=(0, 0, 0)) ax.text(book_keeper.Q[view_idx].camera_center[0, 0], book_keeper.Q[view_idx].camera_center[1, 0], book_keeper.Q[view_idx].camera_center[2, 0], f'C{book_keeper.Q[view_idx].id}') view_direction = book_keeper.Q[view_idx].rotation_matrix.T @ z_hat ax.quiver(book_keeper.Q[view_idx].camera_center[0], book_keeper.Q[view_idx].camera_center[1], book_keeper.Q[view_idx].camera_center[2], view_direction[0], view_direction[1], view_direction[2]) ax.set_xlabel('X') ax.set_ylabel('Y') ax.set_zlabel('Z') var = str(len(book_keeper.Q)) # plt.savefig('images/' + var + '_plot.png', bbox_inches='tight', dpi=250) # plt.close('all') plt.show() def visualize_reprojection(self, view, points_3d): """ Visualize reprojection of already triangulated 3d points on top of view.image. ------ Inputs: view : View points_3d : 3xN """ lab3.imshow(view.image) reproj = lab3.project(points_3d, view.camera_matrix) plt.scatter(reproj[0, :], reproj[1, :], color=(1, 0, 0)) # plt.show() def estimate_color(self, view): """ Estimates the color for 3D points in a point cloud. --- Input view : [View, View] List of view objects --- Output: estimated_color : [Nx3] matrix representing the normalized rgb color for every 3D point (N = number of 3D points) """ num_3d_points = view[0].projections.shape[1] num_cameras = len(view) estimated_color = np.zeros((num_3d_points, 3)) for point_idx in range(num_3d_points): color_sum = np.zeros((3)) num_views_visible = 0 for camera_idx in range(num_cameras): pixel_x = round(view[camera_idx].projections[0][point_idx]) pixel_y = round(view[camera_idx].projections[1][point_idx]) if pixel_x != -1: color_sum += view[camera_idx].image[pixel_y, pixel_x] num_views_visible += 1 with warnings.catch_warnings(): warnings.simplefilter("ignore", category=RuntimeWarning) # ignore a warning with nanmean estimated_color[point_idx] = color_sum/(255*num_views_visible) return estimated_color def visualize_camera_centers(self, R_est, t_est, R_gt, t_gt): fig = plt.figure() ax = fig.gca(projection='3d') gt_cameras = np.zeros([R_gt.shape[0], 3, 1]) est_cameras = np.zeros([R_est.shape[0], 3, 1]) for i in range(R_gt.shape[0]): gt_cameras[i, ...] = -R_gt[i, ...].T @ t_gt[i, ...] est_cameras[i, ...] = -R_est[i, ...].T @ t_est[i, ...] ax.scatter(gt_cameras[:, 0], gt_cameras[:, 1], gt_cameras[:, 2], color=(1, 0, 0)) ax.scatter(est_cameras[:, 0], est_cameras[:, 1], est_cameras[:, 2], color=(0, 0, 1)) ax.set_xlabel('X') ax.set_ylabel('Y') ax.set_zlabel('Z') plt.show() def visualize_interest_points(self, view): """ Displays the 2D projections of the given View object on the actual image. """ plt.imshow(view.image) plt.scatter(view.projections[0, :], view.projections[1, :], c='r', label='o') plt.show()
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/bak/download.py
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# -*- coding: utf-8 -*- # @Author: yuqing5 # date: 20151023 import tushare as ts from sqlalchemy import create_engine import datetime import time import pandas as pd import os import cPickle from pandas import DataFrame import pandas.io.sql as SQL import sys sys.path.append('./utility/') from tool_decorator import local_memcached def date2str(date): return date.strftime("%Y-%m-%d") class DownLoad(object): ''' 1.下载历史数据 2. 更新每天数据 3. 装载历史数据 ''' def __init__(self): self.basic = ts.get_stock_basics() self.engine = create_engine('mysql://root:[email protected]/stock_info?charset=utf8') self.connection = self.engine.connect() @staticmethod def date2str(today=None): if today == None: today =datetime.date.today() return today.strftime("%Y-%m-%d") def down_history(self, stock, index=False): ''' 下载历史至今天的数据,可以用于下载新股票 date,open,high,close,low,volume,amount ''' print '--'*10,"downing ",stock,'--'*10 date = self.basic.ix[stock]['timeToMarket'] #20100115 竟然是个整数 start_year = date/10000 today =datetime.date.today() end_year = int(today.strftime("%Y")) suffix = "-" + str(date)[4:6] + "-" + str(date)[6:8] raw_data = None #针对次新股,今年的股票 if start_year == end_year: raw_data = ts.get_h_data(stock,index) for year in range(start_year, end_year): start = str(year) + suffix right = datetime.datetime.strptime(str(year+1) + suffix, "%Y-%m-%d")-datetime.timedelta(days=1) #跨年的应该没有那天上市的公司,所以不存在bug end = right.strftime("%Y-%m-%d") print start, "-----",end data = ts.get_h_data(stock,start=start,end=end,index=index) if data is None: print None else: print data.shape raw_data = pd.concat([raw_data, data], axis=0) #看看是否需要补充最后一段时间的数据 if (year+1) == end_year and end < today.strftime("%Y-%m-%d"): this_year_start = str(year+1) + suffix print this_year_start, "-------",today.strftime("%Y-%m-%d") data = ts.get_h_data(stock, start=this_year_start, end=today.strftime("%Y-%m-%d"),index=index) if data is None: print None else: print data.shape raw_data = pd.concat([raw_data, data], axis=0) raw_data = raw_data.sort_index(ascending=True) raw_data.to_sql('day_'+stock, self.engine) return raw_data def down_all_day_stick(self): ''' 下载所有股票的历史数据 ''' for stock in self.basic.index: try: print stock self.down_history(stock) except Exception ,ex: print Exception, ";",ex def append_days(self,stock, start, end): ''' 添加stock,指定时间范围内的数据 ''' data = ts.get_h_data(stock,start=start,end=end) data = data.sort_index(ascending=True) data.to_sql('day_'+stock, self.engine,if_exists='append') def append_all_days(self, start=None, end=None): ''' 添加所有股票数据 ''' if start == None: start = datetime.datetime.today() end = start for stock in self.basic['code']: self.append_days(stock, start, end) def load_data(self, stock): ''' 加载股票历史数据 ''' search_sql = "select * from {0}".format('day_'+stock) raw_data = SQL.read_sql(search_sql, self.engine) return raw_data def check_is_new_stock(self, stock): ''' 检测该股票是否为新上市股票 结果不需要该函数 ''' check_sql = "show tables like '{0}'".format('day_'+stock) result = self.connection.execute(check_sql) if result.first() == None: return True else: return False #默认为近3年数据 def down_period(self, stock,start=None,end=None): raw_data = ts.get_hist_data(stock,start,end) return raw_data #新股如603861 有问题 #封装一下ts接口,同一天不要重复获取数据 class TS(object): @staticmethod @local_memcached def memchaced_data(funcname, fileprefix): ''' 使用方法 1. funcname ts的方法名 2. fileprefix 该方法缓存的文件名字 ''' raw_data = funcname() return raw_data if __name__ == '__main__': # dl = DownLoad() # dl.down_all_day_stick() # raw_data = dl.load_data('000001') # print raw_data TS()