Reset23/the-stack-v2-python · Datasets at Hugging Face

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/uebinRDHM_InputSetup_3.py

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gantian127/ueb_input_processing

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import os import netcdfFunctions, climateFunctions_2 from datetime import datetime import rdhmFunctions import callSubprocess """*********** Convert UEB NC files to XMRG with HRAP projection *****************""" workingDir = "/Projects/Tian_workspace/rdhm_ueb_modeling/McPhee_DOLC2/" watershedN = 'Mcphee_DOLC2' startDateTime = "1988/10/01 0" endDateTime = "2010/10/01" startYear = 1988 # datetime.strptime(startDateTime,"%Y/%m/%d %H").year endYear = 2010 # datetime.strptime(endDateTime,"%Y/%m/%d %H").year time_varName='time' #proj4_string: see the paper: Reed, S.M., and D.R. Maidment, "Coordinate Transformations for Using NEXRAD Data in GIS-based Hydrologic Modeling," Journal of Hydrologic Engineering, 4, 2, 174-182, April 1999 ## http://www.nws.noaa.gov/ohd/hrl/distmodel/hrap.htm#background proj4_string = 'PROJCS["Sphere_ARC_INFO_Stereographic_North_Pole",GEOGCS["GCS_Sphere_ARC_INFO",DATUM["Sphere_ARC_INFO",SPHEROID["Sphere_ARC_INFO",6370997,0]],PRIMEM["Greenwich",0],\ UNIT["degree",0.0174532925199433]],PROJECTION["Polar_Stereographic"],PARAMETER["latitude_of_origin",60.00681388888889],PARAMETER["central_meridian",-105],\ PARAMETER["scale_factor",1],PARAMETER["false_easting",0],PARAMETER["false_northing",0],UNIT["metre",1,AUTHORITY["EPSG","9001"]]]' ##proj4_string = '+proj=stere +lat_0=90.0 +lat_ts=60.0 +lon_0=-105.0 +k=1 +x_0=0.0 +y_0=0.0 +a=6371200 +b=6371200 +units=m +no_defs' ####site variables targetDirSiteV = workingDir+'SiteV/' siteVarFiles = ['{}{}'.format(watershedN, var) for var in ['CC30m.nc', 'Hcan30m.nc', 'LAI30m.nc', 'Aspect30m.tif', 'Slope30m.tif']] ueb_site_vars = ['ueb_cc', 'ueb_hcan', 'ueb_lai', 'ueb_aspect', 'ueb_slope'] #os.chdir(workingDir) os.chdir(targetDirSiteV) for indx in range(3): # convert nc to tif and project cmdString = "gdalwarp -t_srs \"" + proj4_string + "\" NETCDF:\"" + siteVarFiles[indx] + "\":Band1 " + ueb_site_vars[indx]+".tif" callSubprocess.callSubprocess(cmdString, 'project to Stereographic') cmdString = "gdal_translate -of AAIGrid " + ueb_site_vars[indx]+".tif " +ueb_site_vars[indx] + ".asc" callSubprocess.callSubprocess(cmdString, "nc to ascii") for indx in range(3, 5): # project raster cmdString = "gdalwarp -t_srs \"" + proj4_string + "\" " + siteVarFiles[indx] + " " + ueb_site_vars[indx] + ".tif" callSubprocess.callSubprocess(cmdString, 'project to Stereographic') cmdString = "gdal_translate -of AAIGrid " + ueb_site_vars[indx] + ".tif " + ueb_site_vars[indx] + ".asc" callSubprocess.callSubprocess(cmdString, "tif to ascii") #to xmrg #os.chdir(targetDirSiteV) cmdString = " for i in *.asc; do asctoxmrg -i $i -p ster -f par; done" callSubprocess.callSubprocess(cmdString, "ascii to xmrg") ### forcing #cbrfc forc inpVar = ["Prec", "Tair"] forcingTargetDir = workingDir+"Forcing/" os.chdir(forcingTargetDir) for indx in range(2): cmdString = "for i in "+inpVar[indx]+"*.nc; do gdalwarp -ot Float32 -s_srs EPSG:4326 -t_srs \"" + proj4_string + "\"" + " $i ueb${i:0:4}${i:12:2}${i:14:2}${i:8:4}${i:16:2}z.tif; done" callSubprocess.callSubprocess(cmdString, "project forcing") # ascii cmdString = "for i in *.tif; do gdal_translate -of AAIGrid $i ${i//.tif}.asc; done" callSubprocess.callSubprocess(cmdString, "tif to ascii") #to xmrg cmdString = "for i in *.asc; do asctoxmrg -i $i -f par -p ster; done" callSubprocess.callSubprocess(cmdString, "ascii to xmrg") #del intrm files cmdString = " rm -f *tif" callSubprocess.callSubprocess(cmdString, "delete intermediate files") cmdString = " rm -f *asc" callSubprocess.callSubprocess(cmdString, "delete intermediate files") cmdString = " rm -f *.xml *.prj" callSubprocess.callSubprocess(cmdString, "delete intermediate files") ##delete nc file to save space cmdString = " rm -f *.nc" #callSubprocess.callSinpVar = ["Prec", "Tair", "Tamin", "Tamax"] #max/min Ta inpVar = ["Tamin", "Tamax"] for indx in range(2): cmdString = "for i in "+inpVar[indx]+"*.nc; do gdalwarp -ot Float32 -s_srs EPSG:4326 -t_srs \"" + proj4_string + "\"" + " $i ueb${i:0:5}${i:13:2}${i:15:2}${i:9:4}${i:17:2}z.tif; done" callSubprocess.callSubprocess(cmdString, "project forcing") # ascii cmdString = "for i in *.tif; do gdal_translate -of AAIGrid $i ${i//.tif}.asc; done" callSubprocess.callSubprocess(cmdString, "tif to ascii") #to xmrg cmdString = "for i in *.asc; do asctoxmrg -i $i -f par -p ster; done" callSubprocess.callSubprocess(cmdString, "ascii to xmrg") #del intrm files cmdString = " rm -f *tif" callSubprocess.callSubprocess(cmdString, "delete intermediate files") cmdString = " rm -f *asc" callSubprocess.callSubprocess(cmdString, "delete intermediate files") cmdString = " rm -f *.xml *.prj" callSubprocess.callSubprocess(cmdString, "delete intermediate files") ##delete nc file to save space cmdString = " rm -f *.nc" #callSubprocess.callSubprocess(cmdString, "delete orig files") #NLDAS VP and WindS forcingTargetDir = workingDir+"Forcing2/" os.chdir(forcingTargetDir) startMonthDayHour = "10/01 0" endMonthDayHour = "10/01 0" #NLDAS VP and WindS for cYear in range(startYear,endYear): print cYear nldasinputForc = [watershedN+str(cYear + 1)+'VP.nc',watershedN+str(cYear + 1)+'windS10m.nc'] outVars = ["uebVp", "uebWindS"] nldasvarForc = ['VP', 'windS10'] startDateTime = str(cYear) + "/" + startMonthDayHour for indx in range(2): print nldasinputForc[indx] print nldasvarForc[indx] print startDateTime rdhmFunctions.create_multiple_Ascii_fromNetCDF(nldasinputForc[indx], outVars[indx], nldasvarForc[indx], 1, startDateTime=startDateTime, time_varName=time_varName,proj4_string=proj4_string) print 'done with create multiple netcdf' cmdString = "for i in *.asc; do asctoxmrg -i $i -f par -p ster; done" callSubprocess.callSubprocess(cmdString, "ascii to xmrg") # delete the ascii files # cmdString = " rm -f *.asc *asc.aux.xml *.prj" # callSubprocess.callSubprocess(cmdString, "delete ascii") # delete the ascii files cmdString = "find . -name '*.asc' -delete" # " rm -f *.asc " callSubprocess.callSubprocess(cmdString, "delete ascii") cmdString = "find . -name '*.asc.aux.xml' -delete" # " rm -f *asc.aux.xml" callSubprocess.callSubprocess(cmdString, "delete ascii") cmdString = "find . -name '*.prj' -delete" #" rm -f *.prj" callSubprocess.callSubprocess(cmdString, "delete ascii") print("done")

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# Not-tested yet import docx2pdf def doc2pdf(src, dst): docx2pdf.convert(src, dst) if __name__ == '__main__': doc2pdf("src.docx", "dst.pdf")

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import torch import numpy as np import matplotlib import seaborn as sns matplotlib.use('Agg') import matplotlib.pyplot as plt def confusion_matrix(output, target): try: from sklearn.metrics import confusion_matrix as cm except ImportError: raise RuntimeError("Confusion Matrix requires sklearn to be installed.") with torch.no_grad(): pred = torch.argmax(output, dim=1) assert pred.shape[0] == len(target) matrix = cm(target.cpu().numpy(), pred.cpu().numpy()) fig = plt.figure() sns.heatmap(matrix, annot=True, fmt="d") fig.canvas.draw() buf = np.asarray(fig.canvas.buffer_rgba(), dtype=np.uint8)[:, :, :3] image = torch.from_numpy(buf).permute(2, 0, 1) plt.close(fig) return image #TODO def roc_curve(output, target): try: from sklearn.metrics import roc_curve as rc except ImportError: raise RuntimeError("ROC Curve requires sklearn to be installed.") with torch.no_grad(): pred = torch.argmax(output, dim=1) assert pred.shape[0] == len(target) fpr, tpr, _ = rc(target.cpu().numpy(), output[:, 1].cpu().numpy()) fig = plt.figure() plt.plot(fpr, tpr) fig.canvas.draw() buf = np.asarray(fig.canvas.buffer_rgba(), dtype=np.uint8)[:, :, :3] image = torch.from_numpy(buf).permute(2, 0, 1) plt.close(fig) return image #TODO def precision_recall_curve(output, target): try: from sklearn.metrics import precision_recall_curve as prc except ImportError: raise RuntimeError("Precision Recall Curve requires sklearn to be installed.") with torch.no_grad(): pred = torch.argmax(output, dim=1) assert pred.shape[0] == len(target) fpr, tpr, _ = prc(target.cpu().numpy(), output[:, 1].cpu().numpy()) fig = plt.figure() plt.plot(fpr, tpr) fig.canvas.draw() buf = np.asarray(fig.canvas.buffer_rgba(), dtype=np.uint8)[:, :, :3] image = torch.from_numpy(buf).permute(2, 0, 1) plt.close(fig) return image

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lokhande-vishnu/cs861_ALIS_algo

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""" Created on Fri May 4 00:33:14 2018 @author: pydi """ import numpy as np import matplotlib.pyplot as plt x1 = np.random.normal(-1,1,50) x2 = np.random.normal(1,1,50) lab1 = np.random.choice(x1,5) # Negative points lab2 = np.random.choice(x2,5) # Positive points w = -1 eta = 0.1 for _ in range(10): for item in lab1: if item*w*(-1) < 0: w = w + eta*item*(-1) for item in lab2: if item*w*(1) < 0: w = w + item*eta*(1) r = np.arange(-7,7,0.01) g1 = .05*(1/np.sqrt(2*np.pi))*np.exp(-(r+1)**2/2) g2 = .05*(1/np.sqrt(2*np.pi))*np.exp(-(r-1)**2/2) plt.figure(111) x1_, = plt.plot(x1, np.zeros(x1.shape), 'rx', markersize=10) x2_, = plt.plot(x2, np.zeros(x1.shape), 'bx', markersize=10) lab1_, = plt.plot(lab1, np.zeros(lab1.shape), 'r8', markersize=8) lab2_, = plt.plot(lab2, np.zeros(lab2.shape), 'b8', markersize=8) g1_, = plt.plot(r, g1, 'r--', label = '- pt density') g2_, = plt.plot(r, g2, 'b--', label = '+ pt density') plt.axvline(x = w, color='k', label= 'trained classifier') plt.text(w, 0.02, 'trained classifier', rotation=90) l1 = 1+np.abs(w*x1) l2 = 1+np.abs(w*x2) xall = np.concatenate((x1,x2)) lall = np.concatenate((l1,l2)) lall = lall/np.sum(lall) #plt.plot(xall, lall, 'g*') for j in range(len(xall)): x = xall[j] loss = lall[j] g_, = plt.plot([xall[j], xall[j]], [0.0005, lall[j]], 'g-', label='sampling distribution') plt.ylabel('Probability Distribution') plt.xlabel('Data items') oplt.legend(handles=[g_, g1_, g2_]) plt.show()

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# -*- coding: utf-8 -*- # Generated by Django 1.9.1 on 2016-02-04 05:22 from __future__ import unicode_literals from django.conf import settings from django.db import migrations, models import django.db.models.deletion class Migration(migrations.Migration): dependencies = [ ('accounts', '0002_auto_20160129_1316'), ] operations = [ migrations.AlterField( model_name='accountaddon', name='author', field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.CASCADE, to=settings.AUTH_USER_MODEL), ), ]

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/priority.py

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sskhokhar/schedulingAlgos

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__author__ = 'Ahmad Zia' processes = int(input('Enter no. of process : ')) dict = {} process_id = [] for index in range(processes): arrival_t_input = int(input('Enter arrival time : ')) burst_t_input = int(input('Enter burst time : ')) priority_input = int(input('Enter priority : ')) process_id.append(index) dict[int(index)] = [arrival_t_input, burst_t_input,priority_input] print"Processes Arrival Time Burst Time Priority " for index in range(len(dict)): print index + 1, " | ", dict[int(index)][0], " | ", dict[int(index)][1], " | ", dict[int(index)][2] start_t = {} dict2 = dict.copy() time = 0 calWait = 0 cal_burst = 0 dict_index = 0 dict_arrival = 0 dict_burst = 0 dict_priority =0 p_index = 0 while 1: if len(dict) == 0: break for index in range(len(process_id)): dict_index = process_id[index] dict_arrival = dict[process_id[index]][0] dict_burst = dict[process_id[index]][1] dict_priority = dict[process_id[index]][2] p_index = index break for index in range(len(process_id)): if dict[dict_index][0] >= dict[process_id[index]][0] and dict[dict_index][2] > dict[process_id[index]][2]: dict_index = process_id[index] p_index = int(index) dict_arrival = dict[process_id[index]][0] dict_burst = dict[process_id[index]][1] dict_priority = dict[process_id[index]][2] del dict[dict_index] del process_id[p_index] check_arrival = 0 cal_burst = 0 while dict_burst != cal_burst: if dict_arrival <= time: cal_burst += 1 if check_arrival == 0: start_t[int(dict_index)] = time check_arrival = 1 time += 1 print "\nStart Time arrival Time waiting Time " for index in range(len(dict2)): ProcessWait = start_t[index] - dict2[int(index)][0] calWait += ProcessWait print start_t[int(index)], " ", (dict2[int(index)][0]), " ", ProcessWait print "\nThe average waiting time :", calWait / processes

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#! /usr/bin/env python # coding:utf-8 import urllib import urllib.request import http.cookiejar ##################################################### # 登录人人 loginurl = 'http://172.16.0.17:8080/2345explorer/login' class Login(object): def __init__(self): self.name = '' self.passwprd = '' self.cj = http.cookiejar.LWPCookieJar() self.opener = urllib.request.build_opener(urllib.request.HTTPCookieProcessor(self.cj)) urllib.request.install_opener(self.opener) def setLoginInfo(self, username, password): '''''设置用户登录信息''' self.name = username self.pwd = password def login(self): '''''登录网站''' loginparams = {'user': self.name, 'password': self.pwd, '__FORM_TOKEN':'414bb9165c56b8d4a914cabf', 'referer':'http://172.16.0.17:8080/2345explorer'} data = urllib.parse.urlencode(loginparams).encode('utf-8') print(data) req = urllib.request.Request(loginurl) response = urllib.request.urlopen(req, data) print(response.getcode()) # self.operate = self.opener.open(req) page = response.read() print(page) def is_login(self): url = 'http://172.16.0.17:8080/2345explorer/admin' if __name__ == '__main__': userlogin = Login() username = 'sunys' password = 'sunys' userlogin.setLoginInfo(username, password) userlogin.login()

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from .batchspawner import * from . import api

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# Реализовать функцию int_func(), принимающую слово из маленьких латинских букв и возвращающую его же, # но с прописной первой буквой. Например, print(int_func(‘text’)) -> Text. def err_msg(): return 'Нужно было ввести одно слово из маленьких латинских букв!' def is_valid(my_list): for i in range(0, len(my_list)): if 97 <= ord(my_list[i]) <= 122: # Проверка на маленькие латинские буквы и отсутствие пробела continue else: return False return True def int_func(my_str): my_str = list(my_str) if is_valid(my_str): my_str[0] = chr(ord(my_str[0]) - 32) # Переводим маленький символ в большой my_str = ''.join(my_str) # Собираем строку из списка return my_str else: return err_msg() word = input('Введите слово из маленьких латинских букв: ') word = int_func(word) print(word)

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class Node : def __init__( self, data ) : self.data = data self.next = None self.prev = None def get_data(self): return self.data class LinkedList : def __init__( self ) : self.head = None def add( self, data ) : cur = self.head node = Node( data ) if cur == None : self.head = node else: while cur.next!= None: cur=cur.next cur.next=node node.prev=cur def search( self, k ) : p = self.head if p != None : while p.next != None : if ( p.data == k ) : return p p = p.next if ( p.data == k ) : return p return None def remove( self, p ) : tmp = p.prev p.prev.next = p.next p.next.prev = p.prev def __str__( self ) : s = "" p = self.head if p != None : while p.next != None : s += str(p.data) s +=" " p = p.next s += str(p.data) return s #check if the linked list is a palindrome def is_palindrome(self): s = "" p = self.head if p != None : while p.next != None : s += str(p.data) s +=" " p = p.next s += str(p.data) reverse=s[::-1] #reverses string print s==reverse def is_palindrome_recurse(self): l = LinkedList() #build an array list based on the numbers in this list numList=[1,2,3,4,4,3,2,1] for num in numList: l.add(num) print "original list: " print l l.is_palindrome()

[ "ewei94@hotmail.com" ]

ewei94@hotmail.com

b76b26811352741d3b2bd34968d4d78280f6b8f0

204cc4d648ac2b632804212ec796a48be51447af

/employee/employee/settings.py

8126764823fc0a0adb280f20adc18b9ad92f7b9a

[]

no_license

ra-rownok/employee-register

dd2da96e1509faa06c1a3131b081366a961c72bd

7dede4e9319ed298e0c9a97f290dcd31bcc306f8

refs/heads/master

2022-12-07T23:04:15.519701

2020-08-14T01:52:17

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py

""" Django settings for employee project. Generated by 'django-admin startproject' using Django 3.0.7. For more information on this file, see https://docs.djangoproject.com/en/3.0/topics/settings/ For the full list of settings and their values, see https://docs.djangoproject.com/en/3.0/ref/settings/ """ import os # Build paths inside the project like this: os.path.join(BASE_DIR, ...) BASE_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__))) # Quick-start development settings - unsuitable for production # See https://docs.djangoproject.com/en/3.0/howto/deployment/checklist/ # SECURITY WARNING: keep the secret key used in production secret! SECRET_KEY = 'gnhcpq0pij*==v@obta$vk*@2u7box145=()5ld-s$d@%a5)ua' # SECURITY WARNING: don't run with debug turned on in production! DEBUG = True ALLOWED_HOSTS = [] # Application definition INSTALLED_APPS = [ 'django.contrib.admin', 'django.contrib.auth', 'django.contrib.contenttypes', 'django.contrib.sessions', 'django.contrib.messages', 'django.contrib.staticfiles', 'register', 'crispy_forms' ] CRISPY_TEMPLATE_PACK = 'bootstrap4' MIDDLEWARE = [ 'django.middleware.security.SecurityMiddleware', 'django.contrib.sessions.middleware.SessionMiddleware', 'django.middleware.common.CommonMiddleware', 'django.middleware.csrf.CsrfViewMiddleware', 'django.contrib.auth.middleware.AuthenticationMiddleware', 'django.contrib.messages.middleware.MessageMiddleware', 'django.middleware.clickjacking.XFrameOptionsMiddleware', ] ROOT_URLCONF = 'employee.urls' TEMPLATES = [ { 'BACKEND': 'django.template.backends.django.DjangoTemplates', 'DIRS': [], 'APP_DIRS': True, 'OPTIONS': { 'context_processors': [ 'django.template.context_processors.debug', 'django.template.context_processors.request', 'django.contrib.auth.context_processors.auth', 'django.contrib.messages.context_processors.messages', ], }, }, ] WSGI_APPLICATION = 'employee.wsgi.application' # Database # https://docs.djangoproject.com/en/3.0/ref/settings/#databases DATABASES = { 'default': { 'ENGINE': 'django.db.backends.sqlite3', 'NAME': os.path.join(BASE_DIR, 'db.sqlite3'), } } # Password validation # https://docs.djangoproject.com/en/3.0/ref/settings/#auth-password-validators AUTH_PASSWORD_VALIDATORS = [ { 'NAME': 'django.contrib.auth.password_validation.UserAttributeSimilarityValidator', }, { 'NAME': 'django.contrib.auth.password_validation.MinimumLengthValidator', }, { 'NAME': 'django.contrib.auth.password_validation.CommonPasswordValidator', }, { 'NAME': 'django.contrib.auth.password_validation.NumericPasswordValidator', }, ] # Internationalization # https://docs.djangoproject.com/en/3.0/topics/i18n/ LANGUAGE_CODE = 'en-us' TIME_ZONE = 'UTC' USE_I18N = True USE_L10N = True USE_TZ = True # Static files (CSS, JavaScript, Images) # https://docs.djangoproject.com/en/3.0/howto/static-files/ STATIC_URL = '/static/'

[ "reshadahamedr001@gmail.com" ]

reshadahamedr001@gmail.com

e23fdacbcb9a8777fd5779b693102edf79fde073

1cb3b625fc952b2f8e7ffa136eca3c9f89e48bef

/python programs/scratch_6.py

83f266c0bf5417b25282b1c43f65ebebb31c1c2b

[]

no_license

jjrocks78/shift

202c9aead0951bbb7ac2cc2c184d9b85d53fdcc0

f76421567dd25657f08c5c77cbae7d5aac19358d

refs/heads/master

2020-07-25T10:05:57.740457

2019-09-13T11:13:40

208,247,803

0

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UTF-8

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py

import cv2 import numpy as np from matplotlib import pyplot as plt img = cv2.imread('/home/cocoslabs/Downloads/Example for extracting text from image.jpg',0) ret,thresh1 = cv2.threshold(img,100,255,cv2.THRESH_BINARY) ret,thresh2 = cv2.threshold(img,100,255,cv2.THRESH_BINARY_INV) ret,thresh3 = cv2.threshold(img,100,255,cv2.THRESH_TRUNC) ret,thresh4 = cv2.threshold(img,100,255,cv2.THRESH_TOZERO) ret,thresh5 = cv2.threshold(img,100,255,cv2.THRESH_TOZERO_INV) titles = ['Original Image','BINARY','BINARY_INV','TRUNC','TOZERO','TOZERO_INV'] images = [img, thresh1, thresh2, thresh3, thresh4, thresh5] for i in range(0,6,1): plt.subplot(2,3,i+1) plt.imshow(images[i],'gray') plt.title(titles[i]) plt.xticks([]),plt.yticks([]) plt.show() cv2.waitKey(0)

[ "harrishjoshua1078@gmail.com" ]

harrishjoshua1078@gmail.com

6afb0f4c79a6e865b5e35a647444dfe4c69ae4a0

220dfe537ff6a851ff94c37bec684d11f868dbb2

/second/pytorch/pytorch/models/box_head.py

489f929b9419da024f72fdcffe6022cd58c6bb24

[ "MIT" ]

permissive

hyunjunChhoi/Rotation-aware-3D-vehicle-detector

2876664986529147d0abd82d35230b1775621681

cfc02fb3aa4a496acda2e42ec9983b98efd73988

refs/heads/master

2022-12-17T05:07:44.059610

2020-09-18T15:39:23

294,009,426

1

0

null

2020-09-18T12:54:11

2020-09-09T05:13:38

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5,089

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# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved. import torch from torch import nn from second.pytorch.models.rbox_head.roi_box_feature_extractors import make_roi_box_feature_extractor from second.pytorch.models.rbox_head.roi_box_predictors import make_roi_box_predictor from second.pytorch.models.rbox_head.inference import make_roi_box_post_processor from second.pytorch.models.rbox_head.loss import make_roi_box_loss_evaluator from maskrcnn_benchmark.structures import bounding_box import time class ROIBoxHead(torch.nn.Module): """ Generic Box Head class. """ def __init__(self, cfg, additional_info): super(ROIBoxHead, self).__init__() cfg.MODEL.ROI_BOX_HEAD.NUM_CLASSES = additional_info["NUM_CLASSES"] cfg.MODEL.ROI_HEADS.FG_IOU_THRESHOLD =additional_info["FG_IOU_THRESHOLD"] cfg.MODEL.ROI_HEADS.BG_IOU_THRESHOLD =additional_info["BG_IOU_THRESHOLD"] cfg.MODEL.ROI_HEADS.NMS = additional_info["NMS"] cfg.MODEL.ROI_HEADS.SCORE_THRESH = additional_info["SCORE_THRESH"] cfg.MODEL.ROI_BOX_HEAD.POOLER_SCALES = additional_info["POOLER_SCALE"] cfg.MODEL.ROI_BOX_HEAD.POOLER_RESOLUTION = additional_info["POOLER_RESOLUTION"] cfg.MODEL.BACKBONE.OUT_CHANNELS = additional_info["OUT_CHANNELS"] self.feature_extractor = make_roi_box_feature_extractor(cfg) self.predictor = make_roi_box_predictor(cfg) self.post_processor = make_roi_box_post_processor(cfg) self.loss_evaluator = make_roi_box_loss_evaluator(cfg) self.cfg = cfg def forward(self, feature_final, res, res_score, example=None, batch_idx=None, cc_loss=None, ll_loss=None, post_max_sizes=None, is_training=False): """ Arguments: features (list[Tensor]): feature-maps from possibly several levels proposals (list[BoxList]): proposal boxes targets (list[BoxList], optional): the ground-truth targets. Returns: x (Tensor): the result of the feature extractor proposals (list[BoxList]): during training, the subsampled proposals are returned. During testing, the predicted boxlists are returned losses (dict[Tensor]): During training, returns the losses for the head. During testing, returns an empty dict. """ # if self.cfg.TEST.CASCADE: recur_iter =1 targets=example features=feature_final #print(features[0].type) recur_proposals = res x = None for i in range(recur_iter): if is_training: # Faster R-CNN subsamples during training the proposals with a fixed # positive / negative ratio with torch.no_grad(): recur_proposals = self.loss_evaluator.subsample(recur_proposals, targets, batch_idx) #print("this is proposal") #print(len(recur_proposals)) #print(recur_proposals[0].bbox[0], recur_proposals[0].bbox[1]) # extract features that will be fed to the final classifier. The # feature_extractor generally corresponds to the pooler + heads #recur_proposals_before_feature #print(features[0].size()) #print("thisis lenght of fatures") #print(len(features)) torch.cuda.synchronize() t0=time.time() x = self.feature_extractor(features, recur_proposals) #print(x.size()) #print(x.type) # final classifier that converts the features into predictions class_logits, box_regression = self.predictor(x) #print("1") #print(class_logits.size()) #print(box_regression.size()) torch.cuda.synchronize() inference_time=time.time()-t0 print("{} seconds".format(time.time()-t0)) if not is_training: #print("2") recur_proposals, recur2, recur3, recur4 = self.post_processor((class_logits, box_regression), recur_proposals, res_score, post_max_sizes, recur_iter - i - 1) # result else: #print("3") loss_classifier, loss_box_reg = self.loss_evaluator( [class_logits], [box_regression], cc_loss, ll_loss, len(features) ) #recur_proposals = self.post_processor((class_logits, box_regression), recur_proposals, recur_iter - i - 1) # result if not is_training: #print("4") return inference_time, recur_proposals, recur2, recur3, recur4 return ( class_logits, recur_proposals, dict(loss_classifier=loss_classifier, loss_box_reg=loss_box_reg), ) def build_roi_box_head(cfg, additional_info): """ Constructs a new box head. By default, uses ROIBoxHead, but if it turns out not to be enough, just register a new class and make it a parameter in the config """ return ROIBoxHead(cfg, additional_info)

[ "numb0258@gmail.com" ]

numb0258@gmail.com

aabf561c5135f455e7f472fb53ec67efcd6c4a0d

c6cee3feca011c94be8d3e53515dfe5e6eba788c

/Code/visualization/visual.py

522b3df49075fee93857ea3d618652ef2bdba7e2

[]

no_license

mohsinkazmi/Capture-Internet-Dynamics-using-Prediction

7c7374dfa0efb20852c90f65b22a6b24deb281c8

6abcfbe220eb95e9e138300354a8aa50b078d46e

refs/heads/master

2021-01-10T06:06:24.702603

2016-02-22T20:54:52

52,290,174

0

null

UTF-8

Python

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1,060

py

from numpy import * import matplotlib.pyplot as plt from mpl_toolkits.mplot3d import Axes3D import pylab from numpy import genfromtxt my_data = genfromtxt('../../data/Ips.csv', delimiter=',', skip_header=0, usecols= (0,1, 2, 3, 4, 13, 14), skip_footer=0) #ip_id, ip, as, long., lati, att, id data = my_data[:,1:] target= my_data[:,0] print "Size of the data (rows, #attributes) ", my_data.shape fig1 = plt.figure(1) ax1 = fig1.add_subplot(111, projection='3d') ax1.scatter(my_data[:,2],my_data[:,6],my_data[:,5] ,c=target) ax1.set_xlabel('1st dimension (AS)') ax1.set_ylabel('2nd dimension (id)') ax1.set_zlabel('3rd dimension (att)') ax1.set_title("Vizualization of the dataset (3 out of 6 dimensions)") plt.draw() plt.figure(2) plt.scatter(my_data[:,3],my_data[:,4], c=target) plt.xlabel('longitude') plt.ylabel('latitude') plt.title("Vizualization of the dataset w.r.t Geolocation") plt.draw() plt.figure(3) plt.scatter(my_data[:,0],my_data[:,2], c=target) plt.xlabel('IP') plt.ylabel('AS') plt.title("Vizualization of the dataset w.r.t AS") plt.show()

[ "mohsin.kazmi14@gmail.com" ]

mohsin.kazmi14@gmail.com

8bd6bd860d3f1efab80d4bd642431685fad884fd

99d8cd53061a0207b81419d1517bc5bd818e0631

/98.validate-binary-search-tree.py

0b85f9badaae04cc84d0b1c6b176de91c7941e39

[]

no_license

SegFault2017/Leetcode2020

aa80c40b1a052185ee58fa928747814e24b9c5d8

7d4a7cee4ecebb67b98a2bdbf84df9896d59f136

refs/heads/master

2023-03-18T22:03:56.926077

2021-03-06T17:11:52

305,238,036

1

0

null

UTF-8

Python

false

980

py

# # @lc app=leetcode id=98 lang=python3 # # [98] Validate Binary Search Tree # # @lc code=start # Definition for a binary tree node. # class TreeNode: # def __init__(self, val=0, left=None, right=None): # self.val = val # self.left = left # self.right = right import math class Solution: def validate(self, node: 'TreeNode', low=-math.inf, hi=math.inf) -> bool: if not node: return True if node.val <= low or node.val >= hi: return False return self.validate(node.left, low, node.val) and self.validate(node.right, node.val, hi) def isValidBST(self, root: TreeNode) -> bool: """Strategy 1: DFS Runtime: O(n), where n is the number of nodes Space: O(h), where h is the height of the tree Args: root (TreeNode): [description] Returns: bool: [description] """ return self.validate(root) # @lc code=end

[ "ray.tangent42@gmail.com" ]

ray.tangent42@gmail.com

c1a5fcdbd9a18ccf38a47ea93b1336e39c8a81a5

cd7e2d655ce974a15cb139b7e475771959d5ad36

/manage.py

bb80999edad9ac3315b927b4f3143cc4d941f26d

[]

no_license

cmdantes/pms_win_3.0

2b4df5e13b7ed2dc9da2ad9b42389d9fa4a8ad82

cb97c3667868d72585e9cd55fb70ba5ce24215f5

refs/heads/master

2023-03-04T18:36:12.379009

2021-02-18T05:55:20

313,783,069

0

null

2020-11-23T00:31:57

2020-11-18T00:55:06

JavaScript

UTF-8

Python

false

627

py

#!/usr/bin/env python """Django's command-line utility for administrative tasks.""" import os import sys def main(): os.environ.setdefault('DJANGO_SETTINGS_MODULE', 'pms_win.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()

[ "danteschrisanmae@yahoo.com" ]

danteschrisanmae@yahoo.com

8376f3ba760e0968095243d0a6947b384dd9d9c9

d3efc82dfa61fb82e47c82d52c838b38b076084c

/utils/ETF/Redemption_SA/YW_ETFSS_SZSH_019.py

1b0fde97d8686e9b2f5c74c8d27dca8b23258a17

[]

no_license

nantongzyg/xtp_test

58ce9f328f62a3ea5904e6ed907a169ef2df9258

ca9ab5cee03d7a2f457a95fb0f4762013caa5f9f

refs/heads/master

2022-11-30T08:57:45.345460

2020-07-30T01:43:30

280,388,441

0

null

UTF-8

Python

false

6,493

py

#!/usr/bin/python # -*- encoding: utf-8 -*- import sys import time sys.path.append("/home/yhl2/workspace/xtp_test/ETF") from import_common import * sys.path.append("/home/yhl2/workspace/xtp_test/ETF/etf_service") from ETF_GetComponentShare import etf_get_all_component_stk class YW_ETFSS_SZSH_019(xtp_test_case): def test_YW_ETFSS_SZSH_019(self): # -----------ETF赎回------------- title = '深圳ETF赎回--允许现金替代：T-1日ETF拥股量1unit→T日赎回ETF' # 定义当前测试用例的期待值 # 期望状态：初始、未成交、部成、全成、部撤已报、部撤、已报待撤、已撤、废单、撤废、内部撤单 # xtp_ID和cancel_xtpID默认为0，不需要变动 case_goal = { 'case_ID': 'ATC-204-019', '期望状态': '全成', 'errorID': 0, 'errorMSG': '', '是否生成报单': '是', '是否是撤废': '否', 'xtp_ID': 0, 'cancel_xtpID': 0, } logger.warning(title + ', case_ID=' + case_goal['case_ID']) unit_info = { 'ticker': '189902', # etf代码 'etf_unit': 1, # etf赎回单位数 'etf_unit_sell': 1, # etf卖出单位数 'component_unit_sell': 1 # 成分股卖出单位数 } # -----------ETF赎回------------- # 参数：证券代码、市场、证券类型、证券状态、交易状态、买卖方向（Ｂ买Ｓ卖）、期望状态、Api stkparm = QueryEtfQty(unit_info['ticker'], '2', '14', '2', '0', 'B', case_goal['期望状态'], Api) # -----------查询ETF赎回前成分股持仓------------- component_stk_info = etf_get_all_component_stk(unit_info['ticker']) # 定义委托参数信息------------------------------------------ # 如果下单参数获取失败，则用例失败 if stkparm['返回结果'] is False: rs = { '用例测试结果': stkparm['返回结果'], '用例错误原因': '获取下单参数失败, ' + stkparm['错误原因'], } etf_query_log(case_goal, rs) self.assertEqual(rs['用例测试结果'], True) else: wt_reqs = { 'business_type': Api.const.XTP_BUSINESS_TYPE['XTP_BUSINESS_TYPE_ETF'], 'market': Api.const.XTP_MARKET_TYPE['XTP_MKT_SZ_A'], 'ticker': stkparm['证券代码'], 'side': Api.const.XTP_SIDE_TYPE['XTP_SIDE_REDEMPTION'], 'price_type': Api.const.XTP_PRICE_TYPE['XTP_PRICE_LIMIT'], 'quantity': int(unit_info['etf_unit'] * stkparm['最小申赎单位']), } EtfParmIni(Api, case_goal['期望状态'], wt_reqs['price_type']) CaseParmInsertMysql(case_goal, wt_reqs) rs = etfServiceTest(Api, case_goal, wt_reqs, component_stk_info) etf_creation_log(case_goal, rs) # --------二级市场，卖出etf----------- case_goal['期望状态'] = '废单' case_goal['errorID'] = 11010121 case_goal['errorMSG'] = 'Failed to check security quantity.' quantity = int(unit_info['etf_unit_sell'] * stkparm['最小申赎单位']) # 二级市场卖出的etf数量 quantity_list = split_etf_quantity(quantity) # 查询涨停价 limitup_px = getUpPrice(stkparm['证券代码']) rs = {} for etf_quantity in quantity_list: wt_reqs_etf = { 'business_type': Api.const.XTP_BUSINESS_TYPE['XTP_BUSINESS_TYPE_CASH'], 'market': Api.const.XTP_MARKET_TYPE['XTP_MKT_SZ_A'], 'ticker': stkparm['证券代码'], 'side': Api.const.XTP_SIDE_TYPE['XTP_SIDE_SELL'], 'price_type': Api.const.XTP_PRICE_TYPE['XTP_PRICE_BEST5_OR_CANCEL'], 'price': limitup_px, 'quantity': etf_quantity, } ParmIni(Api, case_goal['期望状态'], wt_reqs['price_type']) CaseParmInsertMysql(case_goal, wt_reqs) rs = serviceTest(Api, case_goal, wt_reqs_etf) if rs['用例测试结果'] is False: etf_sell_log(case_goal, rs) self.assertEqual(rs['用例测试结果'], True) return etf_sell_log(case_goal, rs) # ------------二级市场卖出成份股----------- case_goal['期望状态'] = '全成' case_goal['errorID'] = 0 case_goal['errorMSG'] = '' etf_component_info = QueryEtfComponentsInfoDB(stkparm['证券代码'],wt_reqs['market']) rs = {} for stk_info in etf_component_info: stk_code = stk_info[0] components_share = QueryEtfComponentsDB(stkparm['证券代码'], stk_code) components_total = int( components_share * unit_info['component_unit_sell']) quantity = get_valid_amount(components_total) limitup_px = getUpPrice(stk_code) wt_reqs = { 'business_type': Api.const.XTP_BUSINESS_TYPE['XTP_BUSINESS_TYPE_CASH'], 'market': Api.const.XTP_MARKET_TYPE['XTP_MKT_SZ_A'], 'ticker': stk_code, 'side': Api.const.XTP_SIDE_TYPE['XTP_SIDE_SELL'], 'price_type': Api.const.XTP_PRICE_TYPE['XTP_PRICE_BEST5_OR_CANCEL'], 'price': limitup_px, 'quantity': quantity, } ParmIni(Api, case_goal['期望状态'], wt_reqs['price_type']) rs = serviceTest(Api, case_goal, wt_reqs) if rs['用例测试结果'] is False: etf_components_sell_log(case_goal, rs) self.assertEqual(rs['用例测试结果'], True) etf_components_sell_log(case_goal, rs) self.assertEqual(rs['用例测试结果'], True) if __name__ == '__main__': unittest.main()

[ "418033945@qq.com" ]

418033945@qq.com

4f92dceb825c12f772496b1518c5f5311b176a33

565e369c3370a0e85324dd14a0fc9460a3220343

/data/emotes_set.py

b8b73a485d35ff720337a2d6b7a10f43f32b3e98

[]

no_license

phanirajl/twitch-emotes

803d7b99d36e6f7cd0908670f5a54423d383109e

c15ef564655d6fa0d4d79db0419f824581051de5

refs/heads/master

2020-03-21T19:51:44.585623

2018-06-28T05:32:34

null

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# use this script to genenrate {name:id} for global/subscriber emote set (id:code or code:id) import json from pprint import pprint import re def global_set(): with open('emotes_general.json','r') as f: data = json.load(f) f.close emotes = {} for k,v in data.iteritems(): emotes[int(v[u'id'])]=k with open('global_id_code.json','w') as f: json.dump(emotes,f) f.close e2 = {} for k,v in emotes.iteritems(): e2[v] = k with open('global_code_id.json','w') as f: json.dump(e2,f) f.close return def subscriber_set(): with open('subscriber.json','r') as f: data = json.load(f) f.close print len(data) emotes = {} for channel,value in data.iteritems(): for item in value['emotes']: emotes[unicode(item['id'])] = item['code'] print len(emotes) # it turns out the set we get include global ones # so we need to remove them first with open('global_id_code.json','r') as fglobal: emotes_global = json.load(fglobal) fglobal.close for key in emotes_global.keys(): if key in emotes.keys(): del emotes[key] rmk_list = [] for k,v in emotes.iteritems(): if not re.match("^[A-Za-z0-9_-]*$",v): rmk_list.append(k) for k in rmk_list: del emotes[k] with open('subscriber_id_code.json','w') as f: json.dump(emotes,f) f.close e2 = {} for k,v in emotes.iteritems(): e2[v] = k with open('global_code_id.json','w') as f: json.dump(e2,f) f.close return if __name__ == '__main__': global_set() subscriber_set()

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2023-02-03T09:14:24.036840

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# Generated by Django 3.0 on 2020-04-04 05:01 from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('App', '0006_auto_20200403_1841'), ] operations = [ migrations.AlterField( model_name='userprofile', name='secret_pin', field=models.CharField(blank=True, max_length=12, null=True), ), ]

[ "chukslord1@gmail.com" ]

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autoML-ICL/autotune-v1

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refs/heads/master

2020-03-20T02:09:47.352859

2019-04-19T10:02:57

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import pickle import argparse from ..core.RandomOptimiser import RandomOptimiser from ..core.SigOptimiser import SigOptimiser from ..benchmarks.mnist_problem import MnistProblem # from ..benchmarks.cifar_problem import CifarProblem # from ..benchmarks.svhn_problem import SvhnProblem parser = argparse.ArgumentParser(description='PyTorch Training') parser.add_argument('-i', '--input_dir', type=str, help='input dir') parser.add_argument('-o', '--output_dir', type=str, help='output dir') parser.add_argument('-res', '--n_resources', default=3, type=int, help='n_resources') args = parser.parse_args() print("Input directory: {}".format(args.input_dir)) print("Output directory: {}".format(args.output_dir)) print("# resources: {}".format(args.n_resources)) # Define problem instance problem = MnistProblem(args.input_dir, args.output_dir) problem.print_domain() # Define maximum units of resource assigned to each optimisation iteration n_resources = args.n_resources random_opt = RandomOptimiser() random_opt.run_optimization(problem, n_resources, max_iter=2, verbosity=True) sig_opt = SigOptimiser() sig_opt.run_optimization(problem, n_resources, max_iter=5, verbosity=True) filename = args.output_dir + 'results.pkl' with open(filename, 'wb') as f: pickle.dump([random_opt, sig_opt], f) print(sig_opt.arm_opt) print(sig_opt.fx_opt)

[ "leowyaoyang@gmail.com" ]

leowyaoyang@gmail.com

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/day_01/day01_test.py

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stain88/advent-of-code-2017

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import unittest from day01 import captcha_next, captcha_half class Day01Test(unittest.TestCase): def test_part_1_example_1(self): self.assertEqual(3, captcha_next("1122")) def test_part_1_example_2(self): self.assertEqual(4, captcha_next("1111")) def test_part_1_example_3(self): self.assertEqual(0, captcha_next("1234")) def test_part_1_example_4(self): self.assertEqual(9, captcha_next("91212129")) def test_part_2_example_1(self): self.assertEqual(6, captcha_half("1212")) def test_part_2_example_2(self): self.assertEqual(0, captcha_half("1221")) def test_part_2_example_3(self): self.assertEqual(4, captcha_half("123425")) def test_part_2_example_4(self): self.assertEqual(12, captcha_half("123123")) def test_part_2_example_5(self): self.assertEqual(4, captcha_half("12131415")) if __name__ == '__main__': unittest.main()

[ "marcbaghdadi@gmail.com" ]

marcbaghdadi@gmail.com

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/huaweicloud-sdk-osm/huaweicloudsdkosm/v2/model/incident_message_v2.py

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# coding: utf-8 import re import six class IncidentMessageV2: """ Attributes: openapi_types (dict): The key is attribute name and the value is attribute type. attribute_map (dict): The key is attribute name and the value is json key in definition. """ sensitive_list = [] openapi_types = { 'type': 'int', 'replier': 'str', 'content': 'str', 'message_id': 'str', 'replier_name': 'str', 'create_time': 'datetime', 'is_first_message': 'int', 'accessory_list': 'list[SimpleAccessoryV2]' } attribute_map = { 'type': 'type', 'replier': 'replier', 'content': 'content', 'message_id': 'message_id', 'replier_name': 'replier_name', 'create_time': 'create_time', 'is_first_message': 'is_first_message', 'accessory_list': 'accessory_list' } def __init__(self, type=None, replier=None, content=None, message_id=None, replier_name=None, create_time=None, is_first_message=None, accessory_list=None): """IncidentMessageV2 - a model defined in huaweicloud sdk""" self._type = None self._replier = None self._content = None self._message_id = None self._replier_name = None self._create_time = None self._is_first_message = None self._accessory_list = None self.discriminator = None if type is not None: self.type = type if replier is not None: self.replier = replier if content is not None: self.content = content if message_id is not None: self.message_id = message_id if replier_name is not None: self.replier_name = replier_name if create_time is not None: self.create_time = create_time if is_first_message is not None: self.is_first_message = is_first_message if accessory_list is not None: self.accessory_list = accessory_list @property def type(self): """Gets the type of this IncidentMessageV2. 类型，0客户留言 1华为工程师留言 :return: The type of this IncidentMessageV2. :rtype: int """ return self._type @type.setter def type(self, type): """Sets the type of this IncidentMessageV2. 类型，0客户留言 1华为工程师留言 :param type: The type of this IncidentMessageV2. :type: int """ self._type = type @property def replier(self): """Gets the replier of this IncidentMessageV2. 回复人ID :return: The replier of this IncidentMessageV2. :rtype: str """ return self._replier @replier.setter def replier(self, replier): """Sets the replier of this IncidentMessageV2. 回复人ID :param replier: The replier of this IncidentMessageV2. :type: str """ self._replier = replier @property def content(self): """Gets the content of this IncidentMessageV2. 留言内容 :return: The content of this IncidentMessageV2. :rtype: str """ return self._content @content.setter def content(self, content): """Sets the content of this IncidentMessageV2. 留言内容 :param content: The content of this IncidentMessageV2. :type: str """ self._content = content @property def message_id(self): """Gets the message_id of this IncidentMessageV2. 留言id :return: The message_id of this IncidentMessageV2. :rtype: str """ return self._message_id @message_id.setter def message_id(self, message_id): """Sets the message_id of this IncidentMessageV2. 留言id :param message_id: The message_id of this IncidentMessageV2. :type: str """ self._message_id = message_id @property def replier_name(self): """Gets the replier_name of this IncidentMessageV2. 回复人名称 :return: The replier_name of this IncidentMessageV2. :rtype: str """ return self._replier_name @replier_name.setter def replier_name(self, replier_name): """Sets the replier_name of this IncidentMessageV2. 回复人名称 :param replier_name: The replier_name of this IncidentMessageV2. :type: str """ self._replier_name = replier_name @property def create_time(self): """Gets the create_time of this IncidentMessageV2. 创建时间 :return: The create_time of this IncidentMessageV2. :rtype: datetime """ return self._create_time @create_time.setter def create_time(self, create_time): """Sets the create_time of this IncidentMessageV2. 创建时间 :param create_time: The create_time of this IncidentMessageV2. :type: datetime """ self._create_time = create_time @property def is_first_message(self): """Gets the is_first_message of this IncidentMessageV2. 是否是第一条留言 :return: The is_first_message of this IncidentMessageV2. :rtype: int """ return self._is_first_message @is_first_message.setter def is_first_message(self, is_first_message): """Sets the is_first_message of this IncidentMessageV2. 是否是第一条留言 :param is_first_message: The is_first_message of this IncidentMessageV2. :type: int """ self._is_first_message = is_first_message @property def accessory_list(self): """Gets the accessory_list of this IncidentMessageV2. 附件列表 :return: The accessory_list of this IncidentMessageV2. :rtype: list[SimpleAccessoryV2] """ return self._accessory_list @accessory_list.setter def accessory_list(self, accessory_list): """Sets the accessory_list of this IncidentMessageV2. 附件列表 :param accessory_list: The accessory_list of this IncidentMessageV2. :type: list[SimpleAccessoryV2] """ self._accessory_list = accessory_list def to_dict(self): """Returns the model properties as a dict""" result = {} for attr, _ in six.iteritems(self.openapi_types): value = getattr(self, attr) if isinstance(value, list): result[attr] = list(map( lambda x: x.to_dict() if hasattr(x, "to_dict") else x, value )) elif hasattr(value, "to_dict"): result[attr] = value.to_dict() elif isinstance(value, dict): result[attr] = dict(map( lambda item: (item[0], item[1].to_dict()) if hasattr(item[1], "to_dict") else item, value.items() )) else: if attr in self.sensitive_list: result[attr] = "****" else: result[attr] = value return result def to_str(self): import simplejson as json return json.dumps(self.to_dict()) def __repr__(self): """For `print` and `pprint`""" return self.to_str() def __eq__(self, other): """Returns true if both objects are equal""" if not isinstance(other, IncidentMessageV2): return False return self.__dict__ == other.__dict__ def __ne__(self, other): """Returns true if both objects are not equal""" return not self == other

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hwcloudsdk@huawei.com

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/tempest/tests/lib/test_tempest_lib.py

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permissive

ssameerr/tempest

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refs/heads/master

2023-08-08T05:00:45.998493

2016-06-08T13:13:48

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Apache-2.0

2023-02-15T02:18:34

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# -*- coding: utf-8 -*- # 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. """ test_tempest.lib ---------------------------------- Tests for `tempest.lib` module. """ from tempest.tests import base class TestTempest_lib(base.TestCase): def test_something(self): pass

[ "mtreinish@kortar.org" ]

mtreinish@kortar.org

05d8d286edc84c72c6bc6f7065b8301880e9d2de

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/doorcommand/serializers.py

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[]

no_license

nate998877/DoorCommandApi

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2023-03-18T11:28:54.221133

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from rest_framework.serializers import HyperlinkedModelSerializer from doorcommand.models import NewUser class NewUserSerializer(HyperlinkedModelSerializer): class Meta: model = NewUser fields = ['user_id', 'status', 'level'] class TmpPassSerializer(HyperlinkedModelSerializer): class Meta: model = NewUser fields = ['tmp_pass'] class UserSerializer(HyperlinkedModelSerializer): class Meta: model = NewUser

[ "nate998877@gmail.com" ]

nate998877@gmail.com

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poojadncla14/poojatasks

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refs/heads/master

2020-03-28T03:08:34.429820

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# Python class - 2 Online 21-05-2018 # Python -- uses # features , introduction # main compenents in Python programming # ------------------------------------- # Keywords and identifers # ----------------------- # library of words (Keywords) # pre defined # cannot be changed # should only purpose defined # cannot be deleted # Python 2.7 --> 31 Keywords # Python 3.6 --> 33 Keywords # mostly small case --> None , True , False # get keywords # ------------ # import keyword # keyword.kwlist # identifers # ---------- # library of words given by user/developer # names of compenents(datatypes , functions , classes , objects , files ) # rules # cannot use keyword # start with letter # cannot start with number or special char # start with small case ( recommended ) # can start with an underscore ( _ , __)(special) # Input - output # -------------- # > a = 10 ALLOWED # >>> 1 = "khan" not ALLOWED # File "<stdin>", line 1 # SyntaxError: can't assign to literal # >>> 1name = "Python" not ALLOWED # File "<stdin>", line 1 # 1name = "Python" # ^ # SyntaxError: invalid syntax # >>> name = "Python" ALLOWED # >>> NAME = "Python" ALLOWED but not recommended # >>> @name = "Python" not ALLOWED # File "<stdin>", line 1 # @name = "Python" # ^ # SyntaxError: invalid syntax # >>> name@ = "python" not ALLOWED # File "<stdin>", line 1 # name@ = "python" # ^ # SyntaxError: invalid syntax # >>> _name = "python" ALLOWED but special case # >>> __name = "python" ALLOWED but special case # ---------------------------------------------- # Variable # -------- # -> mini bucket to store values / data # -> name (identifier) # -> data ( many types) # -> memory location ( address where it is stored ) # -> var_name = < value > # -> datatypes--> type(var_name) # -> memory --> id(var_name) # var_name --> identifier # value --> data # = -> assignment operator # --------------------------------------------- # Data Types # ---------- # 5 datatypes # 2 independent --> numbers , Strings # 3 derived --> lists , tuples and dictionaries # Numbers --> integer , float , long , complex # int class # maximum possible integer in python

[ "poojadncla2514@gmail.com" ]

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/desafiodress/backend/migrations/0003_auto_20180402_1904.py

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pedro-valentim/django-rest-vue

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2020-03-11T17:17:11.675307

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# -*- coding: utf-8 -*- # Generated by Django 1.11 on 2018-04-02 19:04 from __future__ import unicode_literals from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('backend', '0002_auto_20180402_1901'), ] operations = [ migrations.AlterField( model_name='product', name='name', field=models.CharField(help_text='The name of the product.', max_length=60, verbose_name='Name'), ), ]

[ "pedrovalentim.leite@gmail.com" ]

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/test_calculation.py

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[]

no_license

A-ichi11/sample-python

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2023-06-22T11:35:17.427542

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import calculation def test_add_num_and_double(): cal = calculation.Cal() assert cal.add_num_and_double(1,1) == 4

[ "e.nakashima@gemcook.com" ]

e.nakashima@gemcook.com

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theXtroyer1221/Cloud-buffer

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# Copyright 2014 Google Inc. All Rights Reserved. # # 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. """Client for discovery based APIs. A client library for Google's discovery based APIs. """ from __future__ import absolute_import import six from six.moves import zip __author__ = "jcgregorio@google.com (Joe Gregorio)" __all__ = ["build", "build_from_document", "fix_method_name", "key2param"] from six import BytesIO from six.moves import http_client from six.moves.urllib.parse import urlencode, urlparse, urljoin, urlunparse, parse_qsl # Standard library imports import copy from collections import OrderedDict try: from email.generator import BytesGenerator except ImportError: from email.generator import Generator as BytesGenerator from email.mime.multipart import MIMEMultipart from email.mime.nonmultipart import MIMENonMultipart import json import keyword import logging import mimetypes import os import re # Third-party imports import httplib2 import uritemplate import google.api_core.client_options from google.auth.transport import mtls from google.auth.exceptions import MutualTLSChannelError try: import google_auth_httplib2 except ImportError: # pragma: NO COVER google_auth_httplib2 = None # Local imports from googleapiclient import _auth from googleapiclient import mimeparse from googleapiclient.errors import HttpError from googleapiclient.errors import InvalidJsonError from googleapiclient.errors import MediaUploadSizeError from googleapiclient.errors import UnacceptableMimeTypeError from googleapiclient.errors import UnknownApiNameOrVersion from googleapiclient.errors import UnknownFileType from googleapiclient.http import build_http from googleapiclient.http import BatchHttpRequest from googleapiclient.http import HttpMock from googleapiclient.http import HttpMockSequence from googleapiclient.http import HttpRequest from googleapiclient.http import MediaFileUpload from googleapiclient.http import MediaUpload from googleapiclient.model import JsonModel from googleapiclient.model import MediaModel from googleapiclient.model import RawModel from googleapiclient.schema import Schemas from googleapiclient._helpers import _add_query_parameter from googleapiclient._helpers import positional # The client library requires a version of httplib2 that supports RETRIES. httplib2.RETRIES = 1 logger = logging.getLogger(__name__) URITEMPLATE = re.compile("{[^}]*}") VARNAME = re.compile("[a-zA-Z0-9_-]+") DISCOVERY_URI = ( "https://www.googleapis.com/discovery/v1/apis/" "{api}/{apiVersion}/rest" ) V1_DISCOVERY_URI = DISCOVERY_URI V2_DISCOVERY_URI = ( "https://{api}.googleapis.com/$discovery/rest?" "version={apiVersion}" ) DEFAULT_METHOD_DOC = "A description of how to use this function" HTTP_PAYLOAD_METHODS = frozenset(["PUT", "POST", "PATCH"]) _MEDIA_SIZE_BIT_SHIFTS = {"KB": 10, "MB": 20, "GB": 30, "TB": 40} BODY_PARAMETER_DEFAULT_VALUE = {"description": "The request body.", "type": "object"} MEDIA_BODY_PARAMETER_DEFAULT_VALUE = { "description": ( "The filename of the media request body, or an instance " "of a MediaUpload object." ), "type": "string", "required": False, } MEDIA_MIME_TYPE_PARAMETER_DEFAULT_VALUE = { "description": ( "The MIME type of the media request body, or an instance " "of a MediaUpload object." ), "type": "string", "required": False, } _PAGE_TOKEN_NAMES = ("pageToken", "nextPageToken") # Parameters controlling mTLS behavior. See https://google.aip.dev/auth/4114. GOOGLE_API_USE_CLIENT_CERTIFICATE = "GOOGLE_API_USE_CLIENT_CERTIFICATE" GOOGLE_API_USE_MTLS_ENDPOINT = "GOOGLE_API_USE_MTLS_ENDPOINT" # Parameters accepted by the stack, but not visible via discovery. # TODO(dhermes): Remove 'userip' in 'v2'. STACK_QUERY_PARAMETERS = frozenset(["trace", "pp", "userip", "strict"]) STACK_QUERY_PARAMETER_DEFAULT_VALUE = {"type": "string", "location": "query"} # Library-specific reserved words beyond Python keywords. RESERVED_WORDS = frozenset(["body"]) # patch _write_lines to avoid munging '\r' into '\n' # ( https://bugs.python.org/issue18886 https://bugs.python.org/issue19003 ) class _BytesGenerator(BytesGenerator): _write_lines = BytesGenerator.write def fix_method_name(name): """Fix method names to avoid '$' characters and reserved word conflicts. Args: name: string, method name. Returns: The name with '_' appended if the name is a reserved word and '$' and '-' replaced with '_'. """ name = name.replace("$", "_").replace("-", "_") if keyword.iskeyword(name) or name in RESERVED_WORDS: return name + "_" else: return name def key2param(key): """Converts key names into parameter names. For example, converting "max-results" -> "max_results" Args: key: string, the method key name. Returns: A safe method name based on the key name. """ result = [] key = list(key) if not key[0].isalpha(): result.append("x") for c in key: if c.isalnum(): result.append(c) else: result.append("_") return "".join(result) @positional(2) def build( serviceName, version, http=None, discoveryServiceUrl=DISCOVERY_URI, developerKey=None, model=None, requestBuilder=HttpRequest, credentials=None, cache_discovery=True, cache=None, client_options=None, adc_cert_path=None, adc_key_path=None, num_retries=1, ): """Construct a Resource for interacting with an API. Construct a Resource object for interacting with an API. The serviceName and version are the names from the Discovery service. Args: serviceName: string, name of the service. version: string, the version of the service. http: httplib2.Http, An instance of httplib2.Http or something that acts like it that HTTP requests will be made through. discoveryServiceUrl: string, a URI Template that points to the location of the discovery service. It should have two parameters {api} and {apiVersion} that when filled in produce an absolute URI to the discovery document for that service. developerKey: string, key obtained from https://code.google.com/apis/console. model: googleapiclient.Model, converts to and from the wire format. requestBuilder: googleapiclient.http.HttpRequest, encapsulator for an HTTP request. credentials: oauth2client.Credentials or google.auth.credentials.Credentials, credentials to be used for authentication. cache_discovery: Boolean, whether or not to cache the discovery doc. cache: googleapiclient.discovery_cache.base.CacheBase, an optional cache object for the discovery documents. client_options: Mapping object or google.api_core.client_options, client options to set user options on the client. (1) The API endpoint should be set through client_options. If API endpoint is not set, `GOOGLE_API_USE_MTLS_ENDPOINT` environment variable can be used to control which endpoint to use. (2) client_cert_source is not supported, client cert should be provided using client_encrypted_cert_source instead. In order to use the provided client cert, `GOOGLE_API_USE_CLIENT_CERTIFICATE` environment variable must be set to `true`. More details on the environment variables are here: https://google.aip.dev/auth/4114 adc_cert_path: str, client certificate file path to save the application default client certificate for mTLS. This field is required if you want to use the default client certificate. `GOOGLE_API_USE_CLIENT_CERTIFICATE` environment variable must be set to `true` in order to use this field, otherwise this field doesn't nothing. More details on the environment variables are here: https://google.aip.dev/auth/4114 adc_key_path: str, client encrypted private key file path to save the application default client encrypted private key for mTLS. This field is required if you want to use the default client certificate. `GOOGLE_API_USE_CLIENT_CERTIFICATE` environment variable must be set to `true` in order to use this field, otherwise this field doesn't nothing. More details on the environment variables are here: https://google.aip.dev/auth/4114 num_retries: Integer, number of times to retry discovery with randomized exponential backoff in case of intermittent/connection issues. Returns: A Resource object with methods for interacting with the service. Raises: google.auth.exceptions.MutualTLSChannelError: if there are any problems setting up mutual TLS channel. """ params = {"api": serviceName, "apiVersion": version} if http is None: discovery_http = build_http() else: discovery_http = http service = None for discovery_url in _discovery_service_uri_options(discoveryServiceUrl, version): requested_url = uritemplate.expand(discovery_url, params) try: content = _retrieve_discovery_doc( requested_url, discovery_http, cache_discovery, cache, developerKey, num_retries=num_retries, ) service = build_from_document( content, base=discovery_url, http=http, developerKey=developerKey, model=model, requestBuilder=requestBuilder, credentials=credentials, client_options=client_options, adc_cert_path=adc_cert_path, adc_key_path=adc_key_path, ) break # exit if a service was created except HttpError as e: if e.resp.status == http_client.NOT_FOUND: continue else: raise e # If discovery_http was created by this function, we are done with it # and can safely close it if http is None: discovery_http.close() if service is None: raise UnknownApiNameOrVersion("name: %s version: %s" % (serviceName, version)) else: return service def _discovery_service_uri_options(discoveryServiceUrl, version): """ Returns Discovery URIs to be used for attemnting to build the API Resource. Args: discoveryServiceUrl: string, the Original Discovery Service URL preferred by the customer. version: string, API Version requested Returns: A list of URIs to be tried for the Service Discovery, in order. """ urls = [discoveryServiceUrl, V2_DISCOVERY_URI] # V1 Discovery won't work if the requested version is None if discoveryServiceUrl == V1_DISCOVERY_URI and version is None: logger.warning( "Discovery V1 does not support empty versions. Defaulting to V2..." ) urls.pop(0) return list(OrderedDict.fromkeys(urls)) def _retrieve_discovery_doc( url, http, cache_discovery, cache=None, developerKey=None, num_retries=1 ): """Retrieves the discovery_doc from cache or the internet. Args: url: string, the URL of the discovery document. http: httplib2.Http, An instance of httplib2.Http or something that acts like it through which HTTP requests will be made. cache_discovery: Boolean, whether or not to cache the discovery doc. cache: googleapiclient.discovery_cache.base.Cache, an optional cache object for the discovery documents. developerKey: string, Key for controlling API usage, generated from the API Console. num_retries: Integer, number of times to retry discovery with randomized exponential backoff in case of intermittent/connection issues. Returns: A unicode string representation of the discovery document. """ if cache_discovery: from . import discovery_cache if cache is None: cache = discovery_cache.autodetect() if cache: content = cache.get(url) if content: return content actual_url = url # REMOTE_ADDR is defined by the CGI spec [RFC3875] as the environment # variable that contains the network address of the client sending the # request. If it exists then add that to the request for the discovery # document to avoid exceeding the quota on discovery requests. if "REMOTE_ADDR" in os.environ: actual_url = _add_query_parameter(url, "userIp", os.environ["REMOTE_ADDR"]) if developerKey: actual_url = _add_query_parameter(url, "key", developerKey) logger.debug("URL being requested: GET %s", actual_url) # Execute this request with retries build into HttpRequest # Note that it will already raise an error if we don't get a 2xx response req = HttpRequest(http, HttpRequest.null_postproc, actual_url) resp, content = req.execute(num_retries=num_retries) try: content = content.decode("utf-8") except AttributeError: pass try: service = json.loads(content) except ValueError as e: logger.error("Failed to parse as JSON: " + content) raise InvalidJsonError() if cache_discovery and cache: cache.set(url, content) return content @positional(1) def build_from_document( service, base=None, future=None, http=None, developerKey=None, model=None, requestBuilder=HttpRequest, credentials=None, client_options=None, adc_cert_path=None, adc_key_path=None, ): """Create a Resource for interacting with an API. Same as `build()`, but constructs the Resource object from a discovery document that is it given, as opposed to retrieving one over HTTP. Args: service: string or object, the JSON discovery document describing the API. The value passed in may either be the JSON string or the deserialized JSON. base: string, base URI for all HTTP requests, usually the discovery URI. This parameter is no longer used as rootUrl and servicePath are included within the discovery document. (deprecated) future: string, discovery document with future capabilities (deprecated). http: httplib2.Http, An instance of httplib2.Http or something that acts like it that HTTP requests will be made through. developerKey: string, Key for controlling API usage, generated from the API Console. model: Model class instance that serializes and de-serializes requests and responses. requestBuilder: Takes an http request and packages it up to be executed. credentials: oauth2client.Credentials or google.auth.credentials.Credentials, credentials to be used for authentication. client_options: Mapping object or google.api_core.client_options, client options to set user options on the client. (1) The API endpoint should be set through client_options. If API endpoint is not set, `GOOGLE_API_USE_MTLS_ENDPOINT` environment variable can be used to control which endpoint to use. (2) client_cert_source is not supported, client cert should be provided using client_encrypted_cert_source instead. In order to use the provided client cert, `GOOGLE_API_USE_CLIENT_CERTIFICATE` environment variable must be set to `true`. More details on the environment variables are here: https://google.aip.dev/auth/4114 adc_cert_path: str, client certificate file path to save the application default client certificate for mTLS. This field is required if you want to use the default client certificate. `GOOGLE_API_USE_CLIENT_CERTIFICATE` environment variable must be set to `true` in order to use this field, otherwise this field doesn't nothing. More details on the environment variables are here: https://google.aip.dev/auth/4114 adc_key_path: str, client encrypted private key file path to save the application default client encrypted private key for mTLS. This field is required if you want to use the default client certificate. `GOOGLE_API_USE_CLIENT_CERTIFICATE` environment variable must be set to `true` in order to use this field, otherwise this field doesn't nothing. More details on the environment variables are here: https://google.aip.dev/auth/4114 Returns: A Resource object with methods for interacting with the service. Raises: google.auth.exceptions.MutualTLSChannelError: if there are any problems setting up mutual TLS channel. """ if client_options is None: client_options = google.api_core.client_options.ClientOptions() if isinstance(client_options, six.moves.collections_abc.Mapping): client_options = google.api_core.client_options.from_dict(client_options) if http is not None: # if http is passed, the user cannot provide credentials banned_options = [ (credentials, "credentials"), (client_options.credentials_file, "client_options.credentials_file"), ] for option, name in banned_options: if option is not None: raise ValueError("Arguments http and {} are mutually exclusive".format(name)) if isinstance(service, six.string_types): service = json.loads(service) elif isinstance(service, six.binary_type): service = json.loads(service.decode("utf-8")) if "rootUrl" not in service and isinstance(http, (HttpMock, HttpMockSequence)): logger.error( "You are using HttpMock or HttpMockSequence without" + "having the service discovery doc in cache. Try calling " + "build() without mocking once first to populate the " + "cache." ) raise InvalidJsonError() # If an API Endpoint is provided on client options, use that as the base URL base = urljoin(service["rootUrl"], service["servicePath"]) if client_options.api_endpoint: base = client_options.api_endpoint schema = Schemas(service) # If the http client is not specified, then we must construct an http client # to make requests. If the service has scopes, then we also need to setup # authentication. if http is None: # Does the service require scopes? scopes = list( service.get("auth", {}).get("oauth2", {}).get("scopes", {}).keys() ) # If so, then the we need to setup authentication if no developerKey is # specified. if scopes and not developerKey: # Make sure the user didn't pass multiple credentials if client_options.credentials_file and credentials: raise google.api_core.exceptions.DuplicateCredentialArgs( "client_options.credentials_file and credentials are mutually exclusive." ) # Check for credentials file via client options if client_options.credentials_file: credentials = _auth.credentials_from_file( client_options.credentials_file, scopes=client_options.scopes, quota_project_id=client_options.quota_project_id, ) # If the user didn't pass in credentials, attempt to acquire application # default credentials. if credentials is None: credentials = _auth.default_credentials( scopes=client_options.scopes, quota_project_id=client_options.quota_project_id, ) # The credentials need to be scoped. # If the user provided scopes via client_options don't override them if not client_options.scopes: credentials = _auth.with_scopes(credentials, scopes) # If credentials are provided, create an authorized http instance; # otherwise, skip authentication. if credentials: http = _auth.authorized_http(credentials) # If the service doesn't require scopes then there is no need for # authentication. else: http = build_http() # Obtain client cert and create mTLS http channel if cert exists. client_cert_to_use = None use_client_cert = os.getenv(GOOGLE_API_USE_CLIENT_CERTIFICATE, "false") if not use_client_cert in ("true", "false"): raise MutualTLSChannelError( "Unsupported GOOGLE_API_USE_CLIENT_CERTIFICATE value. Accepted values: true, false" ) if client_options and client_options.client_cert_source: raise MutualTLSChannelError( "ClientOptions.client_cert_source is not supported, please use ClientOptions.client_encrypted_cert_source." ) if use_client_cert == "true": if ( client_options and hasattr(client_options, "client_encrypted_cert_source") and client_options.client_encrypted_cert_source ): client_cert_to_use = client_options.client_encrypted_cert_source elif ( adc_cert_path and adc_key_path and mtls.has_default_client_cert_source() ): client_cert_to_use = mtls.default_client_encrypted_cert_source( adc_cert_path, adc_key_path ) if client_cert_to_use: cert_path, key_path, passphrase = client_cert_to_use() # The http object we built could be google_auth_httplib2.AuthorizedHttp # or httplib2.Http. In the first case we need to extract the wrapped # httplib2.Http object from google_auth_httplib2.AuthorizedHttp. http_channel = ( http.http if google_auth_httplib2 and isinstance(http, google_auth_httplib2.AuthorizedHttp) else http ) http_channel.add_certificate(key_path, cert_path, "", passphrase) # If user doesn't provide api endpoint via client options, decide which # api endpoint to use. if "mtlsRootUrl" in service and ( not client_options or not client_options.api_endpoint ): mtls_endpoint = urljoin(service["mtlsRootUrl"], service["servicePath"]) use_mtls_endpoint = os.getenv(GOOGLE_API_USE_MTLS_ENDPOINT, "auto") if not use_mtls_endpoint in ("never", "auto", "always"): raise MutualTLSChannelError( "Unsupported GOOGLE_API_USE_MTLS_ENDPOINT value. Accepted values: never, auto, always" ) # Switch to mTLS endpoint, if environment variable is "always", or # environment varibable is "auto" and client cert exists. if use_mtls_endpoint == "always" or ( use_mtls_endpoint == "auto" and client_cert_to_use ): base = mtls_endpoint if model is None: features = service.get("features", []) model = JsonModel("dataWrapper" in features) return Resource( http=http, baseUrl=base, model=model, developerKey=developerKey, requestBuilder=requestBuilder, resourceDesc=service, rootDesc=service, schema=schema, ) def _cast(value, schema_type): """Convert value to a string based on JSON Schema type. See http://tools.ietf.org/html/draft-zyp-json-schema-03 for more details on JSON Schema. Args: value: any, the value to convert schema_type: string, the type that value should be interpreted as Returns: A string representation of 'value' based on the schema_type. """ if schema_type == "string": if type(value) == type("") or type(value) == type(u""): return value else: return str(value) elif schema_type == "integer": return str(int(value)) elif schema_type == "number": return str(float(value)) elif schema_type == "boolean": return str(bool(value)).lower() else: if type(value) == type("") or type(value) == type(u""): return value else: return str(value) def _media_size_to_long(maxSize): """Convert a string media size, such as 10GB or 3TB into an integer. Args: maxSize: string, size as a string, such as 2MB or 7GB. Returns: The size as an integer value. """ if len(maxSize) < 2: return 0 units = maxSize[-2:].upper() bit_shift = _MEDIA_SIZE_BIT_SHIFTS.get(units) if bit_shift is not None: return int(maxSize[:-2]) << bit_shift else: return int(maxSize) def _media_path_url_from_info(root_desc, path_url): """Creates an absolute media path URL. Constructed using the API root URI and service path from the discovery document and the relative path for the API method. Args: root_desc: Dictionary; the entire original deserialized discovery document. path_url: String; the relative URL for the API method. Relative to the API root, which is specified in the discovery document. Returns: String; the absolute URI for media upload for the API method. """ return "%(root)supload/%(service_path)s%(path)s" % { "root": root_desc["rootUrl"], "service_path": root_desc["servicePath"], "path": path_url, } def _fix_up_parameters(method_desc, root_desc, http_method, schema): """Updates parameters of an API method with values specific to this library. Specifically, adds whatever global parameters are specified by the API to the parameters for the individual method. Also adds parameters which don't appear in the discovery document, but are available to all discovery based APIs (these are listed in STACK_QUERY_PARAMETERS). SIDE EFFECTS: This updates the parameters dictionary object in the method description. Args: method_desc: Dictionary with metadata describing an API method. Value comes from the dictionary of methods stored in the 'methods' key in the deserialized discovery document. root_desc: Dictionary; the entire original deserialized discovery document. http_method: String; the HTTP method used to call the API method described in method_desc. schema: Object, mapping of schema names to schema descriptions. Returns: The updated Dictionary stored in the 'parameters' key of the method description dictionary. """ parameters = method_desc.setdefault("parameters", {}) # Add in the parameters common to all methods. for name, description in six.iteritems(root_desc.get("parameters", {})): parameters[name] = description # Add in undocumented query parameters. for name in STACK_QUERY_PARAMETERS: parameters[name] = STACK_QUERY_PARAMETER_DEFAULT_VALUE.copy() # Add 'body' (our own reserved word) to parameters if the method supports # a request payload. if http_method in HTTP_PAYLOAD_METHODS and "request" in method_desc: body = BODY_PARAMETER_DEFAULT_VALUE.copy() body.update(method_desc["request"]) parameters["body"] = body return parameters def _fix_up_media_upload(method_desc, root_desc, path_url, parameters): """Adds 'media_body' and 'media_mime_type' parameters if supported by method. SIDE EFFECTS: If there is a 'mediaUpload' in the method description, adds 'media_upload' key to parameters. Args: method_desc: Dictionary with metadata describing an API method. Value comes from the dictionary of methods stored in the 'methods' key in the deserialized discovery document. root_desc: Dictionary; the entire original deserialized discovery document. path_url: String; the relative URL for the API method. Relative to the API root, which is specified in the discovery document. parameters: A dictionary describing method parameters for method described in method_desc. Returns: Triple (accept, max_size, media_path_url) where: - accept is a list of strings representing what content types are accepted for media upload. Defaults to empty list if not in the discovery document. - max_size is a long representing the max size in bytes allowed for a media upload. Defaults to 0L if not in the discovery document. - media_path_url is a String; the absolute URI for media upload for the API method. Constructed using the API root URI and service path from the discovery document and the relative path for the API method. If media upload is not supported, this is None. """ media_upload = method_desc.get("mediaUpload", {}) accept = media_upload.get("accept", []) max_size = _media_size_to_long(media_upload.get("maxSize", "")) media_path_url = None if media_upload: media_path_url = _media_path_url_from_info(root_desc, path_url) parameters["media_body"] = MEDIA_BODY_PARAMETER_DEFAULT_VALUE.copy() parameters["media_mime_type"] = MEDIA_MIME_TYPE_PARAMETER_DEFAULT_VALUE.copy() return accept, max_size, media_path_url def _fix_up_method_description(method_desc, root_desc, schema): """Updates a method description in a discovery document. SIDE EFFECTS: Changes the parameters dictionary in the method description with extra parameters which are used locally. Args: method_desc: Dictionary with metadata describing an API method. Value comes from the dictionary of methods stored in the 'methods' key in the deserialized discovery document. root_desc: Dictionary; the entire original deserialized discovery document. schema: Object, mapping of schema names to schema descriptions. Returns: Tuple (path_url, http_method, method_id, accept, max_size, media_path_url) where: - path_url is a String; the relative URL for the API method. Relative to the API root, which is specified in the discovery document. - http_method is a String; the HTTP method used to call the API method described in the method description. - method_id is a String; the name of the RPC method associated with the API method, and is in the method description in the 'id' key. - accept is a list of strings representing what content types are accepted for media upload. Defaults to empty list if not in the discovery document. - max_size is a long representing the max size in bytes allowed for a media upload. Defaults to 0L if not in the discovery document. - media_path_url is a String; the absolute URI for media upload for the API method. Constructed using the API root URI and service path from the discovery document and the relative path for the API method. If media upload is not supported, this is None. """ path_url = method_desc["path"] http_method = method_desc["httpMethod"] method_id = method_desc["id"] parameters = _fix_up_parameters(method_desc, root_desc, http_method, schema) # Order is important. `_fix_up_media_upload` needs `method_desc` to have a # 'parameters' key and needs to know if there is a 'body' parameter because it # also sets a 'media_body' parameter. accept, max_size, media_path_url = _fix_up_media_upload( method_desc, root_desc, path_url, parameters ) return path_url, http_method, method_id, accept, max_size, media_path_url def _urljoin(base, url): """Custom urljoin replacement supporting : before / in url.""" # In general, it's unsafe to simply join base and url. However, for # the case of discovery documents, we know: # * base will never contain params, query, or fragment # * url will never contain a scheme or net_loc. # In general, this means we can safely join on /; we just need to # ensure we end up with precisely one / joining base and url. The # exception here is the case of media uploads, where url will be an # absolute url. if url.startswith("http://") or url.startswith("https://"): return urljoin(base, url) new_base = base if base.endswith("/") else base + "/" new_url = url[1:] if url.startswith("/") else url return new_base + new_url # TODO(dhermes): Convert this class to ResourceMethod and make it callable class ResourceMethodParameters(object): """Represents the parameters associated with a method. Attributes: argmap: Map from method parameter name (string) to query parameter name (string). required_params: List of required parameters (represented by parameter name as string). repeated_params: List of repeated parameters (represented by parameter name as string). pattern_params: Map from method parameter name (string) to regular expression (as a string). If the pattern is set for a parameter, the value for that parameter must match the regular expression. query_params: List of parameters (represented by parameter name as string) that will be used in the query string. path_params: Set of parameters (represented by parameter name as string) that will be used in the base URL path. param_types: Map from method parameter name (string) to parameter type. Type can be any valid JSON schema type; valid values are 'any', 'array', 'boolean', 'integer', 'number', 'object', or 'string'. Reference: http://tools.ietf.org/html/draft-zyp-json-schema-03#section-5.1 enum_params: Map from method parameter name (string) to list of strings, where each list of strings is the list of acceptable enum values. """ def __init__(self, method_desc): """Constructor for ResourceMethodParameters. Sets default values and defers to set_parameters to populate. Args: method_desc: Dictionary with metadata describing an API method. Value comes from the dictionary of methods stored in the 'methods' key in the deserialized discovery document. """ self.argmap = {} self.required_params = [] self.repeated_params = [] self.pattern_params = {} self.query_params = [] # TODO(dhermes): Change path_params to a list if the extra URITEMPLATE # parsing is gotten rid of. self.path_params = set() self.param_types = {} self.enum_params = {} self.set_parameters(method_desc) def set_parameters(self, method_desc): """Populates maps and lists based on method description. Iterates through each parameter for the method and parses the values from the parameter dictionary. Args: method_desc: Dictionary with metadata describing an API method. Value comes from the dictionary of methods stored in the 'methods' key in the deserialized discovery document. """ for arg, desc in six.iteritems(method_desc.get("parameters", {})): param = key2param(arg) self.argmap[param] = arg if desc.get("pattern"): self.pattern_params[param] = desc["pattern"] if desc.get("enum"): self.enum_params[param] = desc["enum"] if desc.get("required"): self.required_params.append(param) if desc.get("repeated"): self.repeated_params.append(param) if desc.get("location") == "query": self.query_params.append(param) if desc.get("location") == "path": self.path_params.add(param) self.param_types[param] = desc.get("type", "string") # TODO(dhermes): Determine if this is still necessary. Discovery based APIs # should have all path parameters already marked with # 'location: path'. for match in URITEMPLATE.finditer(method_desc["path"]): for namematch in VARNAME.finditer(match.group(0)): name = key2param(namematch.group(0)) self.path_params.add(name) if name in self.query_params: self.query_params.remove(name) def createMethod(methodName, methodDesc, rootDesc, schema): """Creates a method for attaching to a Resource. Args: methodName: string, name of the method to use. methodDesc: object, fragment of deserialized discovery document that describes the method. rootDesc: object, the entire deserialized discovery document. schema: object, mapping of schema names to schema descriptions. """ methodName = fix_method_name(methodName) ( pathUrl, httpMethod, methodId, accept, maxSize, mediaPathUrl, ) = _fix_up_method_description(methodDesc, rootDesc, schema) parameters = ResourceMethodParameters(methodDesc) def method(self, **kwargs): # Don't bother with doc string, it will be over-written by createMethod. for name in six.iterkeys(kwargs): if name not in parameters.argmap: raise TypeError('Got an unexpected keyword argument "%s"' % name) # Remove args that have a value of None. keys = list(kwargs.keys()) for name in keys: if kwargs[name] is None: del kwargs[name] for name in parameters.required_params: if name not in kwargs: # temporary workaround for non-paging methods incorrectly requiring # page token parameter (cf. drive.changes.watch vs. drive.changes.list) if name not in _PAGE_TOKEN_NAMES or _findPageTokenName( _methodProperties(methodDesc, schema, "response") ): raise TypeError('Missing required parameter "%s"' % name) for name, regex in six.iteritems(parameters.pattern_params): if name in kwargs: if isinstance(kwargs[name], six.string_types): pvalues = [kwargs[name]] else: pvalues = kwargs[name] for pvalue in pvalues: if re.match(regex, pvalue) is None: raise TypeError( 'Parameter "%s" value "%s" does not match the pattern "%s"' % (name, pvalue, regex) ) for name, enums in six.iteritems(parameters.enum_params): if name in kwargs: # We need to handle the case of a repeated enum # name differently, since we want to handle both # arg='value' and arg=['value1', 'value2'] if name in parameters.repeated_params and not isinstance( kwargs[name], six.string_types ): values = kwargs[name] else: values = [kwargs[name]] for value in values: if value not in enums: raise TypeError( 'Parameter "%s" value "%s" is not an allowed value in "%s"' % (name, value, str(enums)) ) actual_query_params = {} actual_path_params = {} for key, value in six.iteritems(kwargs): to_type = parameters.param_types.get(key, "string") # For repeated parameters we cast each member of the list. if key in parameters.repeated_params and type(value) == type([]): cast_value = [_cast(x, to_type) for x in value] else: cast_value = _cast(value, to_type) if key in parameters.query_params: actual_query_params[parameters.argmap[key]] = cast_value if key in parameters.path_params: actual_path_params[parameters.argmap[key]] = cast_value body_value = kwargs.get("body", None) media_filename = kwargs.get("media_body", None) media_mime_type = kwargs.get("media_mime_type", None) if self._developerKey: actual_query_params["key"] = self._developerKey model = self._model if methodName.endswith("_media"): model = MediaModel() elif "response" not in methodDesc: model = RawModel() headers = {} headers, params, query, body = model.request( headers, actual_path_params, actual_query_params, body_value ) expanded_url = uritemplate.expand(pathUrl, params) url = _urljoin(self._baseUrl, expanded_url + query) resumable = None multipart_boundary = "" if media_filename: # Ensure we end up with a valid MediaUpload object. if isinstance(media_filename, six.string_types): if media_mime_type is None: logger.warning( "media_mime_type argument not specified: trying to auto-detect for %s", media_filename, ) media_mime_type, _ = mimetypes.guess_type(media_filename) if media_mime_type is None: raise UnknownFileType(media_filename) if not mimeparse.best_match([media_mime_type], ",".join(accept)): raise UnacceptableMimeTypeError(media_mime_type) media_upload = MediaFileUpload(media_filename, mimetype=media_mime_type) elif isinstance(media_filename, MediaUpload): media_upload = media_filename else: raise TypeError("media_filename must be str or MediaUpload.") # Check the maxSize if media_upload.size() is not None and media_upload.size() > maxSize > 0: raise MediaUploadSizeError("Media larger than: %s" % maxSize) # Use the media path uri for media uploads expanded_url = uritemplate.expand(mediaPathUrl, params) url = _urljoin(self._baseUrl, expanded_url + query) if media_upload.resumable(): url = _add_query_parameter(url, "uploadType", "resumable") if media_upload.resumable(): # This is all we need to do for resumable, if the body exists it gets # sent in the first request, otherwise an empty body is sent. resumable = media_upload else: # A non-resumable upload if body is None: # This is a simple media upload headers["content-type"] = media_upload.mimetype() body = media_upload.getbytes(0, media_upload.size()) url = _add_query_parameter(url, "uploadType", "media") else: # This is a multipart/related upload. msgRoot = MIMEMultipart("related") # msgRoot should not write out it's own headers setattr(msgRoot, "_write_headers", lambda self: None) # attach the body as one part msg = MIMENonMultipart(*headers["content-type"].split("/")) msg.set_payload(body) msgRoot.attach(msg) # attach the media as the second part msg = MIMENonMultipart(*media_upload.mimetype().split("/")) msg["Content-Transfer-Encoding"] = "binary" payload = media_upload.getbytes(0, media_upload.size()) msg.set_payload(payload) msgRoot.attach(msg) # encode the body: note that we can't use `as_string`, because # it plays games with `From ` lines. fp = BytesIO() g = _BytesGenerator(fp, mangle_from_=False) g.flatten(msgRoot, unixfrom=False) body = fp.getvalue() multipart_boundary = msgRoot.get_boundary() headers["content-type"] = ( "multipart/related; " 'boundary="%s"' ) % multipart_boundary url = _add_query_parameter(url, "uploadType", "multipart") logger.debug("URL being requested: %s %s" % (httpMethod, url)) return self._requestBuilder( self._http, model.response, url, method=httpMethod, body=body, headers=headers, methodId=methodId, resumable=resumable, ) docs = [methodDesc.get("description", DEFAULT_METHOD_DOC), "\n\n"] if len(parameters.argmap) > 0: docs.append("Args:\n") # Skip undocumented params and params common to all methods. skip_parameters = list(rootDesc.get("parameters", {}).keys()) skip_parameters.extend(STACK_QUERY_PARAMETERS) all_args = list(parameters.argmap.keys()) args_ordered = [key2param(s) for s in methodDesc.get("parameterOrder", [])] # Move body to the front of the line. if "body" in all_args: args_ordered.append("body") for name in all_args: if name not in args_ordered: args_ordered.append(name) for arg in args_ordered: if arg in skip_parameters: continue repeated = "" if arg in parameters.repeated_params: repeated = " (repeated)" required = "" if arg in parameters.required_params: required = " (required)" paramdesc = methodDesc["parameters"][parameters.argmap[arg]] paramdoc = paramdesc.get("description", "A parameter") if "$ref" in paramdesc: docs.append( (" %s: object, %s%s%s\n The object takes the" " form of:\n\n%s\n\n") % ( arg, paramdoc, required, repeated, schema.prettyPrintByName(paramdesc["$ref"]), ) ) else: paramtype = paramdesc.get("type", "string") docs.append( " %s: %s, %s%s%s\n" % (arg, paramtype, paramdoc, required, repeated) ) enum = paramdesc.get("enum", []) enumDesc = paramdesc.get("enumDescriptions", []) if enum and enumDesc: docs.append(" Allowed values\n") for (name, desc) in zip(enum, enumDesc): docs.append(" %s - %s\n" % (name, desc)) if "response" in methodDesc: if methodName.endswith("_media"): docs.append("\nReturns:\n The media object as a string.\n\n ") else: docs.append("\nReturns:\n An object of the form:\n\n ") docs.append(schema.prettyPrintSchema(methodDesc["response"])) setattr(method, "__doc__", "".join(docs)) return (methodName, method) def createNextMethod( methodName, pageTokenName="pageToken", nextPageTokenName="nextPageToken", isPageTokenParameter=True, ): """Creates any _next methods for attaching to a Resource. The _next methods allow for easy iteration through list() responses. Args: methodName: string, name of the method to use. pageTokenName: string, name of request page token field. nextPageTokenName: string, name of response page token field. isPageTokenParameter: Boolean, True if request page token is a query parameter, False if request page token is a field of the request body. """ methodName = fix_method_name(methodName) def methodNext(self, previous_request, previous_response): """Retrieves the next page of results. Args: previous_request: The request for the previous page. (required) previous_response: The response from the request for the previous page. (required) Returns: A request object that you can call 'execute()' on to request the next page. Returns None if there are no more items in the collection. """ # Retrieve nextPageToken from previous_response # Use as pageToken in previous_request to create new request. nextPageToken = previous_response.get(nextPageTokenName, None) if not nextPageToken: return None request = copy.copy(previous_request) if isPageTokenParameter: # Replace pageToken value in URI request.uri = _add_query_parameter( request.uri, pageTokenName, nextPageToken ) logger.debug("Next page request URL: %s %s" % (methodName, request.uri)) else: # Replace pageToken value in request body model = self._model body = model.deserialize(request.body) body[pageTokenName] = nextPageToken request.body = model.serialize(body) logger.debug("Next page request body: %s %s" % (methodName, body)) return request return (methodName, methodNext) class Resource(object): """A class for interacting with a resource.""" def __init__( self, http, baseUrl, model, requestBuilder, developerKey, resourceDesc, rootDesc, schema, ): """Build a Resource from the API description. Args: http: httplib2.Http, Object to make http requests with. baseUrl: string, base URL for the API. All requests are relative to this URI. model: googleapiclient.Model, converts to and from the wire format. requestBuilder: class or callable that instantiates an googleapiclient.HttpRequest object. developerKey: string, key obtained from https://code.google.com/apis/console resourceDesc: object, section of deserialized discovery document that describes a resource. Note that the top level discovery document is considered a resource. rootDesc: object, the entire deserialized discovery document. schema: object, mapping of schema names to schema descriptions. """ self._dynamic_attrs = [] self._http = http self._baseUrl = baseUrl self._model = model self._developerKey = developerKey self._requestBuilder = requestBuilder self._resourceDesc = resourceDesc self._rootDesc = rootDesc self._schema = schema self._set_service_methods() def _set_dynamic_attr(self, attr_name, value): """Sets an instance attribute and tracks it in a list of dynamic attributes. Args: attr_name: string; The name of the attribute to be set value: The value being set on the object and tracked in the dynamic cache. """ self._dynamic_attrs.append(attr_name) self.__dict__[attr_name] = value def __getstate__(self): """Trim the state down to something that can be pickled. Uses the fact that the instance variable _dynamic_attrs holds attrs that will be wiped and restored on pickle serialization. """ state_dict = copy.copy(self.__dict__) for dynamic_attr in self._dynamic_attrs: del state_dict[dynamic_attr] del state_dict["_dynamic_attrs"] return state_dict def __setstate__(self, state): """Reconstitute the state of the object from being pickled. Uses the fact that the instance variable _dynamic_attrs holds attrs that will be wiped and restored on pickle serialization. """ self.__dict__.update(state) self._dynamic_attrs = [] self._set_service_methods() def __enter__(self): return self def __exit__(self, exc_type, exc, exc_tb): self.close() def close(self): """Close httplib2 connections.""" # httplib2 leaves sockets open by default. # Cleanup using the `close` method. # https://github.com/httplib2/httplib2/issues/148 self._http.http.close() def _set_service_methods(self): self._add_basic_methods(self._resourceDesc, self._rootDesc, self._schema) self._add_nested_resources(self._resourceDesc, self._rootDesc, self._schema) self._add_next_methods(self._resourceDesc, self._schema) def _add_basic_methods(self, resourceDesc, rootDesc, schema): # If this is the root Resource, add a new_batch_http_request() method. if resourceDesc == rootDesc: batch_uri = "%s%s" % ( rootDesc["rootUrl"], rootDesc.get("batchPath", "batch"), ) def new_batch_http_request(callback=None): """Create a BatchHttpRequest object based on the discovery document. Args: callback: callable, A callback to be called for each response, of the form callback(id, response, exception). The first parameter is the request id, and the second is the deserialized response object. The third is an apiclient.errors.HttpError exception object if an HTTP error occurred while processing the request, or None if no error occurred. Returns: A BatchHttpRequest object based on the discovery document. """ return BatchHttpRequest(callback=callback, batch_uri=batch_uri) self._set_dynamic_attr("new_batch_http_request", new_batch_http_request) # Add basic methods to Resource if "methods" in resourceDesc: for methodName, methodDesc in six.iteritems(resourceDesc["methods"]): fixedMethodName, method = createMethod( methodName, methodDesc, rootDesc, schema ) self._set_dynamic_attr( fixedMethodName, method.__get__(self, self.__class__) ) # Add in _media methods. The functionality of the attached method will # change when it sees that the method name ends in _media. if methodDesc.get("supportsMediaDownload", False): fixedMethodName, method = createMethod( methodName + "_media", methodDesc, rootDesc, schema ) self._set_dynamic_attr( fixedMethodName, method.__get__(self, self.__class__) ) def _add_nested_resources(self, resourceDesc, rootDesc, schema): # Add in nested resources if "resources" in resourceDesc: def createResourceMethod(methodName, methodDesc): """Create a method on the Resource to access a nested Resource. Args: methodName: string, name of the method to use. methodDesc: object, fragment of deserialized discovery document that describes the method. """ methodName = fix_method_name(methodName) def methodResource(self): return Resource( http=self._http, baseUrl=self._baseUrl, model=self._model, developerKey=self._developerKey, requestBuilder=self._requestBuilder, resourceDesc=methodDesc, rootDesc=rootDesc, schema=schema, ) setattr(methodResource, "__doc__", "A collection resource.") setattr(methodResource, "__is_resource__", True) return (methodName, methodResource) for methodName, methodDesc in six.iteritems(resourceDesc["resources"]): fixedMethodName, method = createResourceMethod(methodName, methodDesc) self._set_dynamic_attr( fixedMethodName, method.__get__(self, self.__class__) ) def _add_next_methods(self, resourceDesc, schema): # Add _next() methods if and only if one of the names 'pageToken' or # 'nextPageToken' occurs among the fields of both the method's response # type either the method's request (query parameters) or request body. if "methods" not in resourceDesc: return for methodName, methodDesc in six.iteritems(resourceDesc["methods"]): nextPageTokenName = _findPageTokenName( _methodProperties(methodDesc, schema, "response") ) if not nextPageTokenName: continue isPageTokenParameter = True pageTokenName = _findPageTokenName(methodDesc.get("parameters", {})) if not pageTokenName: isPageTokenParameter = False pageTokenName = _findPageTokenName( _methodProperties(methodDesc, schema, "request") ) if not pageTokenName: continue fixedMethodName, method = createNextMethod( methodName + "_next", pageTokenName, nextPageTokenName, isPageTokenParameter, ) self._set_dynamic_attr( fixedMethodName, method.__get__(self, self.__class__) ) def _findPageTokenName(fields): """Search field names for one like a page token. Args: fields: container of string, names of fields. Returns: First name that is either 'pageToken' or 'nextPageToken' if one exists, otherwise None. """ return next( (tokenName for tokenName in _PAGE_TOKEN_NAMES if tokenName in fields), None ) def _methodProperties(methodDesc, schema, name): """Get properties of a field in a method description. Args: methodDesc: object, fragment of deserialized discovery document that describes the method. schema: object, mapping of schema names to schema descriptions. name: string, name of top-level field in method description. Returns: Object representing fragment of deserialized discovery document corresponding to 'properties' field of object corresponding to named field in method description, if it exists, otherwise empty dict. """ desc = methodDesc.get(name, {}) if "$ref" in desc: desc = schema.get(desc["$ref"], {}) return desc.get("properties", {})

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# Generated by Django 3.0.7 on 2020-07-08 16:03 from django.conf import settings from django.db import migrations, models import django.db.models.deletion class Migration(migrations.Migration): initial = True dependencies = [ ] operations = [ migrations.CreateModel( name='User', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('password', models.CharField(max_length=128, verbose_name='password')), ('last_login', models.DateTimeField(blank=True, null=True, verbose_name='last login')), ('email', models.EmailField(max_length=255, unique=True)), ('active', models.BooleanField(default=True)), ('staff', models.BooleanField(default=True)), ('admin', models.BooleanField(default=False)), ('timestamp', models.DateTimeField(auto_now_add=True)), ('branch', models.CharField(max_length=250, null=True)), ('branch_code', models.IntegerField(null=True)), ('region', models.CharField(max_length=250, null=True)), ('division', models.CharField(max_length=250, null=True)), ], options={ 'abstract': False, }, ), migrations.CreateModel( name='Expense', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('audit_period_start', models.DateField()), ('audit_period_end', models.DateField(blank=True, null=True)), ('para_no', models.CharField(default=0, max_length=5)), ('para_type', models.CharField(choices=[('সাধারন', 'সাধারন'), ('অগ্রিম', 'অগ্রিম'), ('খসড়া', 'খসড়া'), ('সংকলন', 'সংকলন')], default='সাধারন', max_length=100)), ('present_objection_status', models.CharField(choices=[('নিষ্পন্ন', 'নিষ্পন্ন'), ('অনিষ্পন্ন', 'অনিষ্পন্ন')], default='অনিষ্পন্ন', max_length=100)), ('audit_Objection_Title', models.CharField(max_length=100)), ('amount', models.CharField(default=0, max_length=10)), ('cause_of_objection', models.CharField(choices=[('ভাউচার নাই', 'ভাউচার নাই'), ('আর্থিক বিধি অনুসরণ করা হয় নাই', 'আর্থিক বিধি অনুসরণ করা হয় নাই'), ('তামাদি ঋণ', 'তামাদি ঋণ'), ('আয়কর', 'আয়কর'), ('বিভিন্ন প্রকার অনাদায়ী ঋণ', 'বিভিন্ন প্রকার অনাদায়ী ঋণ'), ('গৃহ নির্মাণ অগ্রীম(জমি ক্রয়)', 'গৃহ নির্মাণ অগ্রীম(জমি ক্রয়)'), ('লাঞ্চ সাবসিডি', 'লাঞ্চ সাবসিডি'), ('অতিরিক্ত সুদ প্রদান', 'অতিরিক্ত সুদ প্রদান'), ('উৎস কর কম কর্তন', 'উৎস কর কম কর্তন'), ('ইত্যাদি', 'ইত্যাদি')], default='আর্থিক বিধি অনুসরণ করা হয় নাই', max_length=100)), ('recommendation', models.CharField(max_length=250)), ('action', models.CharField(max_length=250)), ('issued_letter_no', models.CharField(default=0, max_length=5)), ('issued_letter_date', models.DateField(blank=True, null=True)), ('last_reply_no', models.CharField(max_length=5)), ('last_reply_date', models.DateField(blank=True, null=True)), ('comments', models.TextField(blank=True, max_length=200)), ('user', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to=settings.AUTH_USER_MODEL)), ], ), ]

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""" Makes it possible to do the compiled analysis in a subprocess. This has two goals: 1. Making it safer - Segfaults and RuntimeErrors as well as stdout/stderr can be ignored and dealt with. 2. Make it possible to handle different Python versions as well as virtualenvs. """ import os import sys import subprocess import socket import errno import traceback from functools import partial from threading import Thread try: from queue import Queue, Empty except ImportError: from Queue import Queue, Empty # python 2.7 from jedi._compatibility import queue, is_py3, force_unicode, \ pickle_dump, pickle_load, GeneralizedPopen, weakref from jedi import debug from jedi.cache import memoize_method from jedi.evaluate.compiled.subprocess import functions from jedi.evaluate.compiled.access import DirectObjectAccess, AccessPath, \ SignatureParam from jedi.api.exceptions import InternalError _MAIN_PATH = os.path.join(os.path.dirname(__file__), '__main__.py') def _enqueue_output(out, queue): for line in iter(out.readline, b''): queue.put(line) def _add_stderr_to_debug(stderr_queue): while True: # Try to do some error reporting from the subprocess and print its # stderr contents. try: line = stderr_queue.get_nowait() line = line.decode('utf-8', 'replace') debug.warning('stderr output: %s' % line.rstrip('\n')) except Empty: break def _get_function(name): return getattr(functions, name) def _cleanup_process(process, thread): try: process.kill() process.wait() except OSError: # Raised if the process is already killed. pass thread.join() for stream in [process.stdin, process.stdout, process.stderr]: try: stream.close() except OSError: # Raised if the stream is broken. pass class _EvaluatorProcess(object): def __init__(self, evaluator): self._evaluator_weakref = weakref.ref(evaluator) self._evaluator_id = id(evaluator) self._handles = {} def get_or_create_access_handle(self, obj): id_ = id(obj) try: return self.get_access_handle(id_) except KeyError: access = DirectObjectAccess(self._evaluator_weakref(), obj) handle = AccessHandle(self, access, id_) self.set_access_handle(handle) return handle def get_access_handle(self, id_): return self._handles[id_] def set_access_handle(self, handle): self._handles[handle.id] = handle class EvaluatorSameProcess(_EvaluatorProcess): """ Basically just an easy access to functions.py. It has the same API as EvaluatorSubprocess and does the same thing without using a subprocess. This is necessary for the Interpreter process. """ def __getattr__(self, name): return partial(_get_function(name), self._evaluator_weakref()) class EvaluatorSubprocess(_EvaluatorProcess): def __init__(self, evaluator, compiled_subprocess): super(EvaluatorSubprocess, self).__init__(evaluator) self._used = False self._compiled_subprocess = compiled_subprocess def __getattr__(self, name): func = _get_function(name) def wrapper(*args, **kwargs): self._used = True result = self._compiled_subprocess.run( self._evaluator_weakref(), func, args=args, kwargs=kwargs, ) # IMO it should be possible to create a hook in pickle.load to # mess with the loaded objects. However it's extremely complicated # to work around this so just do it with this call. ~ dave return self._convert_access_handles(result) return wrapper def _convert_access_handles(self, obj): if isinstance(obj, SignatureParam): return SignatureParam(*self._convert_access_handles(tuple(obj))) elif isinstance(obj, tuple): return tuple(self._convert_access_handles(o) for o in obj) elif isinstance(obj, list): return [self._convert_access_handles(o) for o in obj] elif isinstance(obj, AccessHandle): try: # Rewrite the access handle to one we're already having. obj = self.get_access_handle(obj.id) except KeyError: obj.add_subprocess(self) self.set_access_handle(obj) elif isinstance(obj, AccessPath): return AccessPath(self._convert_access_handles(obj.accesses)) return obj def __del__(self): if self._used and not self._compiled_subprocess.is_crashed: self._compiled_subprocess.delete_evaluator(self._evaluator_id) class CompiledSubprocess(object): is_crashed = False # Start with 2, gets set after _get_info. _pickle_protocol = 2 def __init__(self, executable): self._executable = executable self._evaluator_deletion_queue = queue.deque() self._cleanup_callable = lambda: None def __repr__(self): pid = os.getpid() return '<%s _executable=%r, _pickle_protocol=%r, is_crashed=%r, pid=%r>' % ( self.__class__.__name__, self._executable, self._pickle_protocol, self.is_crashed, pid, ) @memoize_method def _get_process(self): debug.dbg('Start environment subprocess %s', self._executable) parso_path = sys.modules['parso'].__file__ args = ( self._executable, _MAIN_PATH, os.path.dirname(os.path.dirname(parso_path)), '.'.join(str(x) for x in sys.version_info[:3]), ) process = GeneralizedPopen( args, stdin=subprocess.PIPE, stdout=subprocess.PIPE, stderr=subprocess.PIPE, # Use system default buffering on Python 2 to improve performance # (this is already the case on Python 3). bufsize=-1 ) self._stderr_queue = Queue() self._stderr_thread = t = Thread( target=_enqueue_output, args=(process.stderr, self._stderr_queue) ) t.daemon = True t.start() # Ensure the subprocess is properly cleaned up when the object # is garbage collected. self._cleanup_callable = weakref.finalize(self, _cleanup_process, process, t) return process def run(self, evaluator, function, args=(), kwargs={}): # Delete old evaluators. while True: try: evaluator_id = self._evaluator_deletion_queue.pop() except IndexError: break else: self._send(evaluator_id, None) assert callable(function) return self._send(id(evaluator), function, args, kwargs) def get_sys_path(self): return self._send(None, functions.get_sys_path, (), {}) def _kill(self): self.is_crashed = True self._cleanup_callable() def _send(self, evaluator_id, function, args=(), kwargs={}): if self.is_crashed: raise InternalError("The subprocess %s has crashed." % self._executable) if not is_py3: # Python 2 compatibility kwargs = {force_unicode(key): value for key, value in kwargs.items()} data = evaluator_id, function, args, kwargs try: pickle_dump(data, self._get_process().stdin, self._pickle_protocol) except (socket.error, IOError) as e: # Once Python2 will be removed we can just use `BrokenPipeError`. # Also, somehow in windows it returns EINVAL instead of EPIPE if # the subprocess dies. if e.errno not in (errno.EPIPE, errno.EINVAL): # Not a broken pipe raise self._kill() raise InternalError("The subprocess %s was killed. Maybe out of memory?" % self._executable) try: is_exception, traceback, result = pickle_load(self._get_process().stdout) except EOFError as eof_error: try: stderr = self._get_process().stderr.read().decode('utf-8', 'replace') except Exception as exc: stderr = '<empty/not available (%r)>' % exc self._kill() _add_stderr_to_debug(self._stderr_queue) raise InternalError( "The subprocess %s has crashed (%r, stderr=%s)." % ( self._executable, eof_error, stderr, )) _add_stderr_to_debug(self._stderr_queue) if is_exception: # Replace the attribute error message with a the traceback. It's # way more informative. result.args = (traceback,) raise result return result def delete_evaluator(self, evaluator_id): """ Currently we are not deleting evalutors instantly. They only get deleted once the subprocess is used again. It would probably a better solution to move all of this into a thread. However, the memory usage of a single evaluator shouldn't be that high. """ # With an argument - the evaluator gets deleted. self._evaluator_deletion_queue.append(evaluator_id) class Listener(object): def __init__(self, pickle_protocol): self._evaluators = {} # TODO refactor so we don't need to process anymore just handle # controlling. self._process = _EvaluatorProcess(Listener) self._pickle_protocol = pickle_protocol def _get_evaluator(self, function, evaluator_id): from jedi.evaluate import Evaluator try: evaluator = self._evaluators[evaluator_id] except KeyError: from jedi.api.environment import InterpreterEnvironment evaluator = Evaluator( # The project is not actually needed. Nothing should need to # access it. project=None, environment=InterpreterEnvironment() ) self._evaluators[evaluator_id] = evaluator return evaluator def _run(self, evaluator_id, function, args, kwargs): if evaluator_id is None: return function(*args, **kwargs) elif function is None: del self._evaluators[evaluator_id] else: evaluator = self._get_evaluator(function, evaluator_id) # Exchange all handles args = list(args) for i, arg in enumerate(args): if isinstance(arg, AccessHandle): args[i] = evaluator.compiled_subprocess.get_access_handle(arg.id) for key, value in kwargs.items(): if isinstance(value, AccessHandle): kwargs[key] = evaluator.compiled_subprocess.get_access_handle(value.id) return function(evaluator, *args, **kwargs) def listen(self): stdout = sys.stdout # Mute stdout. Nobody should actually be able to write to it, # because stdout is used for IPC. sys.stdout = open(os.devnull, 'w') stdin = sys.stdin if sys.version_info[0] > 2: stdout = stdout.buffer stdin = stdin.buffer # Python 2 opens streams in text mode on Windows. Set stdout and stdin # to binary mode. elif sys.platform == 'win32': import msvcrt msvcrt.setmode(stdout.fileno(), os.O_BINARY) msvcrt.setmode(stdin.fileno(), os.O_BINARY) while True: try: payload = pickle_load(stdin) except EOFError: # It looks like the parent process closed. # Don't make a big fuss here and just exit. exit(0) try: result = False, None, self._run(*payload) except Exception as e: result = True, traceback.format_exc(), e pickle_dump(result, stdout, self._pickle_protocol) class AccessHandle(object): def __init__(self, subprocess, access, id_): self.access = access self._subprocess = subprocess self.id = id_ def add_subprocess(self, subprocess): self._subprocess = subprocess def __repr__(self): try: detail = self.access except AttributeError: detail = '#' + str(self.id) return '<%s of %s>' % (self.__class__.__name__, detail) def __getstate__(self): return self.id def __setstate__(self, state): self.id = state def __getattr__(self, name): if name in ('id', 'access') or name.startswith('_'): raise AttributeError("Something went wrong with unpickling") #if not is_py3: print >> sys.stderr, name #print('getattr', name, file=sys.stderr) return partial(self._workaround, force_unicode(name)) def _workaround(self, name, *args, **kwargs): """ TODO Currently we're passing slice objects around. This should not happen. They are also the only unhashable objects that we're passing around. """ if args and isinstance(args[0], slice): return self._subprocess.get_compiled_method_return(self.id, name, *args, **kwargs) return self._cached_results(name, *args, **kwargs) @memoize_method def _cached_results(self, name, *args, **kwargs): #if type(self._subprocess) == EvaluatorSubprocess: #print(name, args, kwargs, #self._subprocess.get_compiled_method_return(self.id, name, *args, **kwargs) #) return self._subprocess.get_compiled_method_return(self.id, name, *args, **kwargs)

[ "dmitriy00vn@gmail.com" ]

dmitriy00vn@gmail.com

c9af6d37aa753e229cc5cd33fc24ed55f1baad39

e3e57e2ad8bb0b1d76d79c2c2e6c7ddab7bbd125

/scripts/modules/extractors/fodt/tpm2_part4_spt_routines_annex_fodt.py

57671f23b3d1de3dd364517b9cad63fef93032a5

[ "BSD-3-Clause", "LGPL-3.0-only", "BSD-2-Clause" ]

permissive

evolation/tpm2simulator

cc9d3bd715159515d747f651d508cf8ebd8fd02e

067874b096b329bbfa17f74edc6abc3a992c775b

refs/heads/development

2023-03-26T12:32:57.733648

2021-03-23T22:46:11

350,809,917

0

BSD-2-Clause

2021-03-23T18:04:09

null

UTF-8

Python

false

10,715

py

# -*- coding: utf-8 -*- import re from bs4 import Tag from modules import utils from modules import constants from modules import data_structures from modules.extractors.fodt.tpm2_partx_extraction_navigator_fodt import ExtractionNavigator class SptRoutinesAnnexFODT(ExtractionNavigator): """ """ def __init__(self): ExtractionNavigator.__init__(self) # Extracts function # Parameters: # main_entry # name_section # sub_path def extract_function(self, main_entry, name_section, sub_path): # find first function entry function = self.next_function(main_entry, 2, True) # iterate over function entries while function is not None: print " "*4 + "* " + function.get_text().strip() if (function.get_text().strip() == "RSA Files" or function.get_text().strip() == "Elliptic Curve Files" or function.get_text().strip() == "OpenSSL-Specific Files"): backup = function while function is not None: # find first function entry function = self.next_function(function, 3, True) if function is None: break print " "*8 + "- " + function.get_text().strip() if (function.get_text().strip() == "Alternative RSA Key Generation" or function.get_text().strip() == "Header Files" or function.get_text().strip() == "Source Files"): backup2 = function while True: # find first function entry function = self.next_function(function, 4, True) if function is None: function = backup2 break print " "*12 + ". " + function.get_text().strip() self.handle_files(sub_path, function) else: self.handle_files(sub_path, function) function = backup else: self.handle_files(sub_path, function) # find next function entry function = self.next_function(function, 2) # Handles file # Parameters: # sub_path # function def handle_files(self, sub_path, function): # find the entry of the module to be extracted entry = self.next_entry(function) # get all relevant code and comment blocks from the module f = self.extract_module(entry) f.name = function.get_text().strip() f.short_name = f.name.replace(".c", "") f.table_command = None f.table_response = None f.folder_name = sub_path self.functions.append(f) # Extract support routine annex code blocks # Parameters; # entry # style # Returns: # list of code blocks found in given part of file def extract_code_blocks(self, entry, style): code_blocks = data_structures.TPM2_Partx_File() style_nr = int(re.search("([0-9]+)", style).group(1)) cont = ExtractionNavigator.selector(entry) while cont: # if the current entry is a text:p, table:table, or test:list with the current style, # append it to code blocks if isinstance(entry, Tag) and entry.name == constants.XML_TEXT_P: element = data_structures.TPM2_Partx_CommentLine(entry.get_text()) code_blocks.append(element) # once elif isinstance(entry, Tag) and entry.name == constants.XML_TABLE_TABLE: table_rows = [] rows = entry.find_all(constants.XML_TABLE_TABLE_ROW) for i in range(0,len(rows)): r = [] cells = rows[i].find_all(constants.XML_TABLE_TABLE_CELL) for cell in cells: r.append(cell.get_text()) table_rows.append(r) element = data_structures.TPM2_Partx_Table("","", 0, table_rows) code_blocks.append(element) # once elif isinstance(entry, Tag) and entry.name == constants.XML_TEXT_LIST\ and entry.has_attr(constants.XML_TEXT_STYLE_NAME) \ and entry[constants.XML_TEXT_STYLE_NAME] == style: text_ps = entry.findAll(constants.XML_TEXT_P) for text_p in text_ps: if not isinstance(text_p, Tag): break utils.convert_indentation(text_p) text_p_text = text_p.get_text() element = data_structures.TPM2_Partx_CodeLine(text_p_text) code_blocks.append(element) # for every code line # add an empty line for readability element = data_structures.TPM2_Partx_CodeLine("") code_blocks.append(element) # once next_list = entry current_style_nr = style_nr cont = False while current_style_nr - style_nr < 2 or current_style_nr - style_nr > 4: if next_list: next_list = next_list.next_sibling.next_sibling else: break if next_list and next_list.has_attr(constants.XML_TEXT_STYLE_NAME): current_style = next_list[constants.XML_TEXT_STYLE_NAME] result = re.search("WWNum([0-9]+)", current_style) if result and int(result.group(1)) > style_nr: current_style_nr = int(result.group(1)) if current_style == style: cont = True break entry = entry.next_sibling.next_sibling return code_blocks # Extracts module # Parameters: # entry def extract_module(self, entry): # find out which text:style-name of the list to follow style = self.extract_list_style(entry) code_blocks = self.extract_code_blocks(entry, style) return code_blocks # Extracts list style # Parameters: # entry def extract_list_style(self, entry): style = None if (isinstance(entry, Tag) and entry.name == constants.XML_TEXT_LIST and entry.has_attr(constants.XML_TEXT_STYLE_NAME)): style = entry[constants.XML_TEXT_STYLE_NAME] elif (isinstance(entry, Tag) and entry.name == constants.XML_TEXT_P): """ propagate confusion: we need two next_sibling invocations to access the next sibling """ next_list = entry.next_sibling.next_sibling while (isinstance(next_list, Tag) and next_list.name == constants.XML_TEXT_LIST): # comment found: need to find the list with code entries tp = next_list.find(constants.XML_TEXT_P) if tp is not None: ts = tp.find(constants.XML_TEXT_SPAN) if (ts is not None and ts.has_attr(constants.XML_TEXT_STYLE_NAME) and ts[constants.XML_TEXT_STYLE_NAME].startswith(constants.XML_PREFIX_CODE_)): style = next_list[constants.XML_TEXT_STYLE_NAME] break next_list = next_list.find_next(constants.XML_TEXT_LIST) return style # Extract next function from annex # Parameters; # cur_function # num # first_intro # Returns: # string containing next function from annex # sub_section_number def next_function(self, cur_function, num, first_intro=False): function = cur_function.find_next(constants.XML_TEXT_H) while (isinstance(function, Tag) and function.has_attr(constants.XML_TEXT_OUTLINE_LEVEL) and int(function[constants.XML_TEXT_OUTLINE_LEVEL]) != num or (first_intro and function.get_text().strip() == "Introduction") or function.get_text().strip().endswith("Format")): function = function.find_next(constants.XML_TEXT_H) if function is None \ or (function.has_attr(constants.XML_TEXT_OUTLINE_LEVEL) and int(function[constants.XML_TEXT_OUTLINE_LEVEL]) < num): return None if function.get_text().strip() == "Introduction": return None return function # Extracts next entry # Parameters: # entry def next_entry(self, entry): while True: # do-while entry = entry.find_next(ExtractionNavigator.selector) if entry is not None: text_p = entry.find(constants.XML_TEXT_P) if text_p is not None: found = False text_span = text_p.find_all(constants.XML_TEXT_SPAN) for ts in text_span: if (ts is not None and ts.has_attr(constants.XML_TEXT_STYLE_NAME) and ts[constants.XML_TEXT_STYLE_NAME].startswith(constants.XML_PREFIX_CODE_)): found = True break if found: break return entry # Extracts section # Parameters: # entry # name_section # name_folder def extract_section(self, entry, name_section, name_folder): """ The method 'extract_section' is overwritten since this class looks for the 'annex' part of the supporting routines, which is indicated by the list's text:style-name 'WWNum2' instead of the general search criterion 'XML_TEXT_H' and 'constants.XML_TEXT_OUTLINE_LEVEL: 1'. """ cur_name = "" # find correct section while isinstance(entry, Tag) and cur_name != name_section: entry = entry.find_next(constants.XML_TEXT_LIST, {constants.XML_TEXT_STYLE_NAME: 'WWNum2'}) text_p = entry.find(constants.XML_TEXT_P) if text_p is not None: cur_name = text_p.get_text().strip() # couldn't find the right section if entry is None: return print("[+] Section name: {0}".format(entry.find(constants.XML_TEXT_P).get_text().strip())) self.extract_function(entry, name_section, name_folder)

[ "steffen.wagner@aisec.fraunhofer.de" ]

steffen.wagner@aisec.fraunhofer.de

1e6f7e681ec4b3fa4d1f5294d2dc8a703d0f98b1

25c3ebefefc7ecdacf5e9d528f12bdc8485cea06

/app/models.py

cbd56f17711cee6e7647efa521c40195a6c45b5d

[]

no_license

oldpotter/skl

0b3a4e523050c73cf708d6e8486048d49e6714cc

5f47e3f328e63e4de6caca0616a1804ffc9aafd9

refs/heads/master

2020-04-27T16:00:55.453185

2019-04-04T06:56:02

166,230,421

0

null

UTF-8

Python

false

1,197

py

# -*- coding: utf-8 -*- __author__ = 'op' from app import db, login from datetime import datetime from werkzeug.security import check_password_hash from flask_login import UserMixin class Rili(db.Model): id = db.Column(db.Integer, primary_key=True) date = db.Column(db.String(8), unique=True) jsonContent = db.Column(db.Text) class Lyric(db.Model): id = db.Column(db.Integer, primary_key=True) artist = db.Column(db.String(50)) song = db.Column(db.String(50)) album = db.Column(db.String(50)) content = db.Column(db.Text) class User(UserMixin, db.Model): id = db.Column(db.Integer, primary_key=True) username = db.Column(db.String(64), index=True, unique=True) password_hash = db.Column(db.String(128)) def check_password(self, password): return check_password_hash(self.password_hash, password) ''' 1: 茶会信息 2: 读经地信息 ''' class ContactType: CH = 0 DJD = 1 class Contact(db.Model): id = db.Column(db.Integer, primary_key=True) title = db.Column(db.String(500)) detail = db.Column(db.Text) type = db.Column(db.Integer) @login.user_loader def load_user(id): return User.query.get(int(id))

[ "oldpottertom@icloud.com" ]

oldpottertom@icloud.com

6f8b63672bb07ff3d11d0914e4646a88ced4360c

9d9e0f5779eecc8065aacb34baefc40515fe6118

/valid.py

9319a6fda573dec68957b0ea5bb75c47af46c524

[]

no_license

MuhamadAhsanul/ujian_kartu_kredit

ea0e10aa50f1582b2d9bf4753a599cd384e6822e

07fb8a91eb7f2d4aebad07f0351369d321ae0726

refs/heads/master

2020-09-08T10:42:40.080207

2019-11-12T05:48:15

221,111,199

0

null

UTF-8

Python

false

2,239

py

# import json # with open('ccNasabah.json', 'r') as x: # out = json.load(x) # print(out) [ {"nama": "Andi", "noCreditCard": 4253625879615781}, {"nama": "Budi", "noCreditCard": 5123-4567-8912-3455}, {"nama": "Caca", "noCreditCard": 525362587961578}, {"nama": "Deni", "noCreditCard": 42536258796157867}, {"nama": "Euis", "noCreditCard": 4424424424442442}, {"nama": "Fani", "noCreditCard": 4424424424442444}, {"nama": "Gaga", "noCreditCard": 5122236879543214}, {"nama": "Hari", "noCreditCard": 4424444424442444}, {"nama": "Inne", "noCreditCard": 5122-2368-7954-3213}, {"nama": "Janu", "noCreditCard": 61234-123-8912-3456}, {"nama": "Kiki", "noCreditCard": 5199-9967-7912-3457}, {"nama": "Luis", "noCreditCard": 1111222233334444}, {"nama": "Mira", "noCreditCard": 5123 - 4567 - 8912 - 3456}, {"nama": "Nuri", "noCreditCard": 4123356789123456}, {"nama": "Opik", "noCreditCard": 4123456789123454} ] class Klasifikasi: nama: "nama" nomor: "noCreditCard" valid: [ {4253625879615781, 4424424424442442, 5122-2368-7954-3213, 4123456789123454, 5123-4567-8912-3455, 4123356789123456} ] class Nasabah(): def __init__(self, nama, nomor): self.nama = nama self.nomor = nomor def valid(self, nomor): if self.nomor == 4253625879615781: return True elif self.nomor == 4424424424442442: return True elif self.nomor == 5122-2368-7954-3213: return True elif self.nomor == 4123456789123454: return True elif self.nomor == 5123-4567-8912-3455: return True elif self.nomor == 4123356789123456: return True else: return False Nasabah1 = Nasabah("Andi", "4253625879615781") Nasabah2 = Nasabah("Budi", "5123-4567-8912-3455") Nasabah3 = Nasabah("Caca", "0525362587961578") Nasabah4 = Nasabah("Deni", "42536258796157867") Nasabah5 = Nasabah("Euis", "4424424424442442") Nasabah6 = Nasabah Nasabah7 = Nasabah Nasabah8 = Nasabah Nasabah9 = Nasabah Nasabah10 = Nasabah Nasabah11 = Nasabah Nasabah12 = Nasabah Nasabah13 = Nasabah Nasabah14 = Nasabah Nasabah15 = Nasabah

[ "aahsaann@gmail.com" ]

aahsaann@gmail.com

85870acb391dad622b43af4cbafde335cca5fee6

7b77ca25963ae591d68f4abb5725f9fbc18e9ddd

/applications/persona/views.py

9a297e1c150962363c366ebbca885b44573e9a1d

[]

no_license

GabrielMartinez007/Empleados

30b0f8676f9f432fa12d054b3c991974c4ce936a

6f51398396fda42fc0939461c6efc4fc13a6b212

refs/heads/main

2023-02-27T17:42:20.410044

2021-02-02T18:54:29

335,373,007

0

null

UTF-8

Python

false

3,119

py

from django.shortcuts import render from django.views.generic import ListView, \ DetailView, \ CreateView, \ TemplateView, \ UpdateView, \ DeleteView from django.urls import reverse_lazy from .models import Empleado # Create your views here. class inicioView(TemplateView): """"Vista que carga ventana de inicio""" template_name = "inicio.html" class SuccessErasedView(TemplateView): template_name = "successErased.html" class ListAll(ListView): template_name = "persona/ListAll.html" paginate_by = 6 ordering = "first_Name" context_object_name = "Page" def get_queryset(self): palabra_clave = self.request.GET.get("key", " ") lista = Empleado.objects.filter( full_Name__icontains=palabra_clave ) return lista class EmpleadoDetail(DetailView): model = Empleado template_name = "persona/detailEmpleado.html" def get_context_data(self, **kwargs): context = super(EmpleadoDetail, self).get_context_data(**kwargs) context['titulo'] = "Empleado del mes" return context class ListByArea(ListView): template_name = "persona/ListBy.html" context_object_name = "departamento" def get_queryset(self): area = self.kwargs['short_name'] lista = Empleado.objects.filter( department__short_name=area ) return lista class Administrar(ListView): template_name = "persona/admin.html" model = Empleado paginate_by = 6 def get_queryset(self): palabra_clave = self.request.GET.get("key","") lista = Empleado.objects.filter( full_Name__icontains = palabra_clave ) return lista class DeleteEmpleado(DeleteView): template_name="persona/DeleteEmpleado.html" model = Empleado success_url = reverse_lazy("persona_app:erased") class UpdateEmpleado(UpdateView): template_name = "persona/UpdateEmpleado.html" model = Empleado fields = [ "first_Name", "last_Name", "job", "department", "Habilidades", "avatar", ] def post(self, request, *args, **kwargs): self.object = self.get_object() #logica..... print("metodo post **************************") print(request.POST) print(request.POST["first_Name"]) #logica...... return super().post(request, *args, **kwargs) def form_valid(self, form): return super(Add, self).form_valid(form) success_url = reverse_lazy("persona_app:erased") class CreateEmpleado(CreateView): template_name = "persona/CreateEmpleado.html" model = Empleado fields = [ "first_Name", "last_Name", "job", "department", "Habilidades", "avatar", ] success_url = reverse_lazy("persona_app:erased") def form_valid(self, form): nEmpleado = form.save(commit=False) nEmpleado.full_Name = nEmpleado.first_Name + " " + nEmpleado.last_Name nEmpleado.save() return super(CreateEmpleado, self).form_valid(form)

[ "lugiazekrom43@gmail.com" ]

lugiazekrom43@gmail.com

ca67db3e619336355690a55865974fc423a07f1e

6e7a8bb4805770b475af1b3146b494b1417c2461

/PythonAPI/simstar/road_work.py

875f1e5c37c171a2d5a1b5f090b5af15cb072360

[]

no_license

eFiniLan/final-2021

05d360ff64fad4a6c0fdfcc7de3f80061e0aa29e

57df36b3354935da0027380a541bb2521666df45

refs/heads/main

2023-06-03T11:39:23.932325

2021-06-25T20:17:57

null

0

null

UTF-8

Python

false

180

py

import msgpackrpc class RoadWork(): def __init__(self,client,ID): self._ID = int(ID) self.client = client def get_ID(self): return self._ID

[ "melih.dal@boun.edu.tr" ]

melih.dal@boun.edu.tr

de181756dfdb9c9fd888488fba3c1c235f923bf8

e97f3a3cf818380d6203b8c8080ab59e4c161685

/party.py

d70a0a401754595a5325331e34442dafed214b35

[]

no_license

tabualhsan/doctest

5b39738515670354ec22422b5f1cdd8d2d93865a

aa5d3548f3b6489dca0a3f7c9e4d081007fd4782

refs/heads/master

2023-02-21T23:21:02.983767

2021-01-25T20:37:18

332,880,214

0

null

UTF-8

Python

false

3,484

py

"""Flask site for Balloonicorn's Party.""" from flask import Flask, session, render_template, request, flash, redirect from flask_debugtoolbar import DebugToolbarExtension app = Flask(__name__) app.secret_key = "SECRETSECRETSECRET" def is_mel(name, email): """Is this user Mel? >>> is_mel('Mel Melitpolski', 'mel@ubermelon.com') True >>> is_mel('Judith Butler', 'judith@awesome.com') False >>> is_mel("Mel", "mel@ubermelon.com") True >>> is_mel(" ", "mel@ubermelon.com") True """ return name == "Mel Melitpolski" or email == "mel@ubermelon.com" def most_and_least_common_type(treats): """Given list of treats, return most and least common treat types. Return most and least common treat types in tuple of format (most, least). >>> treats = [{'type': 'dessert'}, {'type': 'dessert'}, {'type': 'appetizer'}, {'type': 'dessert'}, {'type': 'appetizer'},{'type': 'drink'}] >>> most_and_least_common_type(treats) ('dessert', 'drink') """ types = {} # Count number of each type for treat in treats: types[treat['type']] = types.get(treat['type'], 0) + 1 most_count = most_type = None least_count = least_type = None # Find most, least common for treat_type, count in types.items(): if most_count is None or count > most_count: most_count = count most_type = treat_type if least_count is None or count < least_count: least_count = count least_type = treat_type return (most_type, least_type) def get_treats(): """Return treats being brought to the party. One day, I'll move this into a database! -- Balloonicorn """ return [ {'type': 'dessert', 'description': 'Chocolate mousse', 'who': 'Leslie'}, {'type': 'dessert', 'description': 'Cardamom-Pear pie', 'who': 'Joel'}, {'type': 'appetizer', 'description': 'Humboldt Fog cheese', 'who': 'Meggie'}, {'type': 'dessert', 'description': 'Lemon bars', 'who': 'Bonnie'}, {'type': 'appetizer', 'description': 'Mini-enchiladas', 'who': 'Katie'}, {'type': 'drink', 'description': 'Sangria', 'who': 'Anges'}, {'type': 'dessert', 'description': 'Chocolate-raisin cookies', 'who': 'Henry'}, {'type': 'dessert', 'description': 'Brownies', 'who': 'Sarah'} ] @app.route("/") def homepage(): """Show homepage.""" return render_template("homepage.html") @app.route("/treats") def show_treats(): """Show treats people are bringing.""" treats = get_treats() most, least = most_and_least_common_type(get_treats()) return render_template("treats.html", treats=treats, most=most, least=least) @app.route("/rsvp", methods=['POST']) def rsvp(): """Register for the party.""" name = request.form.get("name") email = request.form.get("email") if not is_mel(name, email): session['rsvp'] = True flash("Yay!") return redirect("/") else: flash("Sorry, Mel. This is kind of awkward.") return redirect("/") if __name__ == "__main__": app.debug = True app.config['DEBUG_TB_INTERCEPT_REDIRECTS'] = False DebugToolbarExtension(app) app.run(host="0.0.0.0")

[ "jen@silverwire.ninja" ]

jen@silverwire.ninja

2aafbedb2948ab745b6afac25e89003fe4e183c4

a5e4d0b9df29569415f91b7c617c0d96300d203d

/run.py

3abc4efaa781a3c2a29ee35303e0ce923fd65851

[]

no_license

poptest/apiservice

884e543172b24d7296707cb12b4ce18cbdd2d9b2

cff4f03b7f0300656c62220127845a458a78ca03

refs/heads/master

2020-05-07T08:35:18.218575

2019-04-09T10:12:37

180,337,173

0

null

UTF-8

Python

false

65

py

from app import app app.run('0.0.0.0', port='6000', debug=True)

[ "mehuandiguo@126.com" ]

mehuandiguo@126.com

d9661648cf1f0eb2cf7d52f479fb5d525578407b

0a125a62bed94cf02c60c21a5455a254fb29055b

/web/gerl_admin/__init__.py

959ea70e3d311deb94116725b694fe18934d1478

[]

no_license

dizengrong/dzr_code_2017

2eb0f19e85b69f0cfd76f054c052387e5f7439ee

dac34a4c2441cce2b21dd8a1ca31126f4c50843c

refs/heads/master

2022-12-23T02:20:35.512552

2021-07-07T07:40:58

99,231,523

0

null

2022-12-16T05:54:47

2017-08-03T12:44:21

Erlang

UTF-8

Python

false

24

py

# *-* coding:utf-8 *-*

[ "dizengrong@gmail.com" ]

dizengrong@gmail.com

aa8fa7134387a593255b5130917522af84fb688c

d66eb5506167b68133470a590afedda3b409e5f6

/pyico.py

e12a589afaa90f0e917f5113f9249e8a4fd921c0

[]

no_license

w718328952/logtest

5e07a3fe5c56649e5561c0892c35d80fb6d5ad02

3136a074e10573dbdaed76ac684e80c919000120

refs/heads/master

2020-04-06T13:48:53.794031

2018-11-14T07:48:59

157,511,400

0

null

UTF-8

Python

false

354,756

py

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QtCore.qRegisterResourceData(0x01, qt_resource_struct, qt_resource_name, qt_resource_data) def qCleanupResources(): QtCore.qUnregisterResourceData(0x01, qt_resource_struct, qt_resource_name, qt_resource_data) qInitResources()

[ "wb.2009@163.com" ]

wb.2009@163.com

a72d692aa65ada981e2c3c633813d9f1aec3e26a

80cb36f83a7813b5e9e72dc07cdd60a83ec0a4ce

/sqlite3connection.py

7675d06f2e0b42596da290620ac43fc8a19ff19a

[ "MIT" ]

permissive

balajirama/login_registration

4e2036e57908cfca78592dec13c5242e28dc5c4b

b374c151076d57de2063b50796321a4f55a1e5c7

refs/heads/master

2021-07-05T07:56:40.580724

2020-11-07T22:46:32

196,668,729

0

1

null

UTF-8

Python

false

1,335

py

import sqlite3 def make_dict(arr1, arr2): result = [] if len(arr1) < 1: return result if len(arr1[0]) != len(arr2): raise Exception('columns and data do not match') for row in arr1: row_dict = dict() for j in range(len(row)): row_dict[arr2[j][0]] = row[j] result.append(row_dict) return result class SQLite3Connection: def __init__(self, db): connection = sqlite3.connect(db) connection.set_trace_callback(print) self.connection = connection def query_db(self, query, data=[]): cursor = self.connection.cursor() try: print("Running query:") cursor.execute(query, data) if query.lower().find("select") >= 0: res = cursor.fetchall() columns = cursor.description result = make_dict(res, columns) print("Query result:", result) return result else: self.connection.commit() if query.lower().find("insert") >= 0: return cursor.lastrowid except Exception as e: print("ERROR:", e) return False def __del__(self): self.connection.close() def connectToSQLite3(db): return SQLite3Connection(db)

[ "balajirama@users.noreply.github.com" ]

balajirama@users.noreply.github.com

3ae82201c0f7e5dd38718f5b558d1eea7bfe3aea

529edf91d79a841da707e694c19d00b743d022d8

/images/migrations/0003_image_total_likes.py

26eb75f2446049690320e245c36c268fb5954932

[]

no_license

youssieframadan/Bookmarks

88838ca4e3bfcc1ae70bc4662afb9336b08544d7

5a4ad1a8c916091e7f79a44c7f982695d7210aef

refs/heads/main

2023-08-25T15:54:18.179067

2021-10-20T13:26:39

419,342,155

0

null

UTF-8

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414

py

# Generated by Django 3.2.7 on 2021-10-19 15:44 from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('images', '0002_rename_imagemodel_image'), ] operations = [ migrations.AddField( model_name='image', name='total_likes', field=models.PositiveIntegerField(db_index=True, default=0), ), ]

[ "youssief.r@gmail.com" ]

youssief.r@gmail.com

a4c7a2d1b9ba19dc263d3f59ee293b54bfd56e85

60eaaf25f660fa326603f5b173294dc459a0595d

/experiment_MC2.py

4cf997b02817985086302a48f7f62f352c5aff23

[]

no_license

thuydung-icthust/Q_Learning_Connectivity

1ef46d62016d56ab2f96c0dae7f13f475ed8a2ae

bef4dcb12becc0a46eaa8268b9546af474218997

refs/heads/master

2023-07-02T06:49:41.365971

2021-08-02T04:08:16

286,622,585

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1

null

2020-08-11T02:09:08

2020-08-11T02:09:07

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from Node import Node import random from Network import Network import pandas as pd import Parameter as param from ast import literal_eval from MobileCharger import MobileCharger from Q__Learning import Q_learning from Inma import Inma def Test( file_name="data/thaydoitileguitin.csv", des_log="log/change_alpha/", size_tt=2, ord=0, s_ind=0, e_ind=5, alpha_p=0.2, theta_p=0.2, n_size=10, ): for index in range(s_ind, e_ind): df = pd.read_csv(file_name) node_pos = list(literal_eval(df.node_pos[index])) list_node = [] for i in range(len(node_pos)): location = node_pos[i] com_ran = df.commRange[index] energy = df.energy[index] energy_max = df.energy[index] prob = df.freq[index] node = Node( location=location, com_ran=com_ran, energy=energy, energy_max=energy_max, id=i, energy_thresh=0.4 * energy, prob=prob, ) list_node.append(node) mc = MobileCharger( energy=df.E_mc[index], capacity=df.E_max[index], e_move=df.e_move[index], e_self_charge=df.e_mc[index], velocity=df.velocity[index], ) target = [int(item) for item in df.target[index].split(",")] net = Network(list_node=list_node, mc=mc, target=target) print(len(net.node), len(net.target), max(net.target)) q_learning = Q_learning( network=net, alpha_p=alpha_p, theta_p=theta_p, nb_action=n_size * n_size, n_size=n_size, ) # inma = Inma() net.simulate(optimizer=q_learning, index=index, file_name=des_log) if __name__ == "__main__": filename = [ "data/thaydoitileguitin.csv", "data/thaydoisonode.csv", "data/thaydoinangluongmc.csv", ] des_log = [ "log/Lifetime/Frequency/", "log/Lifetime/NodeNum/", "log/Lifetime/PowerMC/", ] alpha, theta = (0.6, 0.3) test_index = 2 file_name = filename[test_index] des_log = des_log[test_index] for i in range(2, 4): file_to_log_infor = ( des_log + str(alpha) + "_" + str(theta) + "_" + str(i) + ".txt" ) print(file_to_log_infor) for m in range(0, 5): Test( file_name=file_name, des_log=file_to_log_infor, s_ind=i, e_ind=i + 1, alpha_p=alpha, theta_p=theta, )

[ "thuydungnguyen.ictk63@gmail.com" ]

thuydungnguyen.ictk63@gmail.com

eefda3e4f68c92ad23058fc49e2a6ba5e489fa45

3b74cd55d5ca236081a80dbbd34fce37a22b208e

/Quiz/Apply_filter.py

f947a556358c88c45a21dfbf7b35bec21113f6b3

[]

no_license

Zahrou/EDX

8f5961aadd4d6e0ce66522ea0a02f9eb27fcc546

f5c1c2241aae08fe0cd05dc586ddd22fa51949b8

refs/heads/master

2020-04-02T02:55:15.931274

2019-06-01T02:22:30

153,935,840

0

null

UTF-8

Python

false

769

py

def f(i): return i + 2 def g(i): return i > 5 def applyF_filterG(L, f, g): """ Assumes L is a list of integers Assume functions f and g are defined for you. f takes in an integer, applies a function, returns another integer g takes in an integer, applies a Boolean function, returns either True or False Mutates L such that, for each element i originally in L, L contains i if g(f(i)) returns True, and no other elements Returns the largest """ L1 = [] for i in L: s = f(i) if g(s) == True: L1.append(i) L.clear() for e in L1: L.append(e) if len(L) == 0: return -1 else: return max(L)

[ "zahro.madr@gmail.com" ]

zahro.madr@gmail.com

9358a2e8396486447cd6a920d3dab9fee2f2ecda

4a8e482142f2dedf4728098d1582672774e59295

/PlayerLogic/VQCQPlayer.py

df7782fd5fae92abccc2b145e9efde8e5ca48540

[]

no_license

omarcostahamido/tictactoe-roli

48b8c9db50278a2cb00f7406a8c4befa298843b0

d70c3d1c8bf3aa087c77c349adc10c781d3d37ab

refs/heads/master

2020-08-19T11:46:17.216411

2019-07-16T16:53:02

null

0

null

UTF-8

Python

false

7,579

py

# -*- coding: utf-8 -*- # Copyright 2019 IBM. # # 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. # ============================================================================= import logging import matplotlib.pyplot as plt from sklearn.model_selection import train_test_split from sklearn.datasets.base import load_data from sklearn.preprocessing import StandardScaler, MinMaxScaler from sklearn.decomposition import PCA from qiskit.aqua.input import ClassificationInput import numpy as np import random logger = logging.getLogger() logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s') class VQCQPlayer: def __init__(self): self.move = 0 self.data_file = 'data.csv' self.data_path = 'PlayerLogic' self.feature_dim = 9 # dimension of each data point sample_Total, training_input, test_input, class_labels = VQCQPlayer.userDefinedData(self.data_path, self.data_file, ['0', '1', '2', '3', '4', '5', '6', '7', '8'], training_size=6000, test_size=500, n=self.feature_dim, PLOT_DATA=False) temp = [test_input[k] for k in test_input] total_array = np.concatenate(temp) aqua_dict = { 'problem': {'name': 'classification'}, 'algorithm': { 'name': 'SVM' }, 'multiclass_extension': {'name': 'AllPairs'} } algo_input = ClassificationInput(training_input, test_input, total_array) from qiskit.aqua import QiskitAqua aqua_obj = QiskitAqua(aqua_dict, algo_input) self.algo_obj = aqua_obj.quantum_algorithm logger.info("Training the SVM....") aqua_obj.run() logger.info("Trained!") def take_turn(self, board): board = [x if x else 0 for x in board] to_predict = VQCQPlayer.singleDataItem(self.data_path, self.data_file, board, n=self.feature_dim) logger.info('Making prediction') self.move = self.algo_obj.predict(to_predict)[0] # if the move selected already contains a play, choose randomly if board[self.move]: spaces = [index for index, x in enumerate(board) if x == 0] self.move = random.choice(spaces) @staticmethod def userDefinedData(location, file, class_labels, training_size, test_size, n=2, PLOT_DATA=True): data, target, target_names = load_data(location, file) # sample_train is of the same form as data sample_train, sample_test, label_train, label_test = train_test_split( data, target, test_size=0.25, train_size=0.75, random_state=22) # Now we standarize for gaussian around 0 with unit variance std_scale = StandardScaler().fit(sample_train) sample_train = std_scale.transform(sample_train) sample_test = std_scale.transform(sample_test) # Now reduce number of features to number of qubits pca = PCA(n_components=n).fit(sample_train) sample_train = pca.transform(sample_train) sample_test = pca.transform(sample_test) # Samples are pairs of points samples = np.append(sample_train, sample_test, axis=0) minmax_scale = MinMaxScaler((-1, 1)).fit(samples) sample_train = minmax_scale.transform(sample_train) sample_test = minmax_scale.transform(sample_test) # If class labels are numeric if class_labels[0].isdigit(): # Pick training size number of samples from each distro training_input = {key: (sample_train[label_train == int(key), :])[:training_size] for k, key in enumerate(class_labels)} test_input = {key: (sample_test[label_test == int(key), :])[: test_size] for k, key in enumerate(class_labels)} else: # if they aren't training_input = {key: (sample_train[label_train == k, :])[:training_size] for k, key in enumerate(class_labels)} test_input = {key: (sample_train[label_train == k, :])[training_size:( training_size + test_size)] for k, key in enumerate(class_labels)} if PLOT_DATA: for k in range(0, 9): plt.scatter(sample_train[label_train == k, 0][:training_size], sample_train[label_train == k, 1][:training_size]) plt.title("PCA dim. reduced user dataset") plt.show() return sample_train, training_input, test_input, class_labels @staticmethod def singleDataItem(location, file, data, n=2): # load the old data so that this new example gets transformed correctly test_data, target, target_names = load_data(location, file) # Only use sample_train to help get the right shape for the new input sample_train, sample_test, label_train, label_test = train_test_split( test_data, target, test_size=0.25, train_size=0.75, random_state=22) # convert to np array to enable joining to other data data = np.array(data) # add the to be tested data onto the end of the overall data sample_train = np.vstack((sample_train, data)) # Now we standarize for gaussian around 0 with unit variance std_scale = StandardScaler().fit(sample_train) sample_train = std_scale.transform(sample_train) # Now reduce number of features to number of qubits pca = PCA(n_components=n).fit(sample_train) sample_train = pca.transform(sample_train) # Scale to the range (-1,+1) minmax_scale = MinMaxScaler((-1, 1)).fit(sample_train) sample_train = minmax_scale.transform(sample_train) # returns array which contains one array with is the 2 data points to use # OUTPUT IS READY TO BE PUT INTO SVM.PREDICT return [sample_train[-1]] def get_data_view(self, board, size=3): board = [x if x else 0 for x in board] # take this many elements to compare against test_str = ', '.join([str(x) for x in board[:size]]) # mapping from move to number of times that move was seen results_dict = {} file_path = self.data_path + '/data/' + self.data_file with open(file_path) as file: lines = file.readlines() # look at all the data for line in lines: # if this matches the current state of the board add to counts if line.startswith(test_str): move = line[-2:-1] if move not in results_dict: results_dict[move] = 0 results_dict[move] += 1 return results_dict

[ "madeleine.tod@ibm.com" ]

madeleine.tod@ibm.com

cf8da9eba1dbf16d89e8f4edbec9cf3a882a4551

746c4544fca849cddcf0a6c3efbcc2b1fd23eb6c

/charts/barchart_wage_age.py

f02a098e9f93d918e50ce35c0628046918cc5997

[]

no_license

jonasthiel/st101-intro-statistics

7603b1aaa42b7fcf7d01c8c81e62058fc44fbb16

6a240fc960129fbd44f7a840227d6c5560b054f3

refs/heads/main

2023-02-16T00:56:02.663632

2020-12-31T20:42:42

325,868,941

0

null

UTF-8

Python

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7,623

py

#Write a line of code to plot a barchart of Wage grouped by Age from plotting import * Age=[25, 26, 33, 29, 27, 21, 26, 35, 21, 37, 21, 38, 18, 19, 36, 30, 29, 24, 24, 36, 36, 27, 33, 23, 21, 26, 27, 27, 24, 26, 25, 24, 22, 25, 40, 39, 19, 31, 33, 30, 33, 27, 40, 32, 31, 35, 26, 34, 27, 34, 33, 20, 19, 40, 39, 39, 37, 18, 35, 20, 28, 31, 30, 29, 31, 18, 40, 20, 32, 20, 34, 34, 25, 29, 40, 40, 39, 36, 39, 34, 34, 35, 39, 38, 33, 32, 21, 29, 36, 33, 30, 39, 21, 19, 38, 30, 40, 36, 34, 28, 37, 29, 39, 25, 36, 33, 37, 19, 28, 26, 18, 22, 40, 20, 40, 20, 39, 29, 26, 26, 22, 37, 34, 29, 24, 23, 21, 19, 29, 30, 23, 40, 30, 30, 19, 39, 39, 25, 36, 38, 24, 32, 34, 33, 36, 30, 35, 26, 28, 23, 25, 23, 40, 20, 26, 26, 22, 23, 18, 36, 34, 36, 35, 40, 39, 39, 33, 22, 37, 20, 37, 35, 20, 23, 37, 32, 25, 35, 35, 22, 21, 31, 40, 26, 24, 29, 37, 19, 33, 31, 29, 27, 21, 19, 39, 34, 34, 40, 26, 39, 35, 31, 35, 24, 19, 27, 27, 20, 28, 30, 23, 21, 20, 26, 31, 24, 25, 25, 22, 32, 28, 36, 21, 38, 18, 25, 21, 33, 40, 19, 38, 33, 37, 32, 31, 31, 38, 19, 37, 37, 32, 36, 34, 35, 35, 35, 37, 35, 39, 34, 24, 25, 18, 40, 33, 32, 23, 25, 19, 39, 38, 36, 32, 27, 22, 40, 28, 29, 25, 36, 26, 28, 32, 34, 34, 21, 21, 32, 19, 35, 30, 35, 26, 31, 38, 34, 33, 35, 37, 38, 36, 40, 22, 30, 28, 28, 29, 36, 24, 28, 28, 28, 26, 21, 35, 22, 32, 28, 19, 33, 18, 22, 36, 26, 19, 26, 30, 27, 28, 24, 36, 37, 20, 32, 38, 39, 38, 30, 32, 30, 26, 23, 19, 29, 33, 34, 23, 30, 32, 40, 36, 29, 39, 34, 34, 22, 22, 22, 36, 38, 38, 30, 26, 40, 34, 21, 34, 38, 32, 35, 35, 26, 28, 20, 40, 23, 24, 26, 24, 39, 21, 33, 31, 39, 39, 20, 22, 18, 23, 36, 32, 37, 36, 26, 30, 30, 30, 21, 22, 40, 38, 22, 27, 23, 21, 22, 20, 30, 31, 40, 19, 32, 24, 21, 27, 32, 30, 34, 18, 25, 22, 40, 23, 19, 24, 24, 25, 40, 27, 29, 22, 39, 38, 34, 39, 30, 31, 33, 34, 25, 20, 20, 20, 20, 24, 19, 21, 31, 31, 29, 38, 39, 33, 40, 24, 38, 37, 18, 24, 38, 38, 22, 40, 21, 36, 30, 21, 30, 35, 20, 25, 25, 29, 30, 20, 29, 29, 31, 20, 26, 26, 38, 37, 39, 31, 35, 36, 30, 38, 36, 23, 39, 39, 20, 30, 34, 21, 23, 21, 33, 30, 33, 32, 36, 18, 31, 32, 25, 23, 23, 21, 34, 18, 40, 21, 29, 29, 21, 38, 35, 38, 32, 38, 27, 23, 33, 29, 19, 20, 35, 29, 27, 28, 20, 40, 35, 40, 40, 20, 36, 38, 28, 30, 30, 36, 29, 27, 25, 33, 19, 27, 28, 34, 36, 27, 40, 38, 37, 31, 33, 38, 36, 25, 23, 22, 23, 34, 26, 24, 28, 32, 22, 18, 29, 19, 21, 27, 28, 35, 30, 40, 28, 37, 34, 24, 40, 33, 29, 30, 36, 25, 26, 26, 28, 34, 39, 34, 26, 24, 33, 38, 37, 36, 34, 37, 33, 25, 27, 30, 26, 21, 40, 26, 25, 25, 40, 28, 35, 36, 39, 33, 36, 40, 32, 36, 26, 24, 36, 27, 28, 26, 37, 36, 37, 36, 20, 34, 30, 32, 40, 20, 31, 23, 27, 19, 24, 23, 24, 25, 36, 26, 33, 30, 27, 26, 28, 28, 21, 31, 24, 27, 24, 29, 29, 28, 22, 20, 23, 35, 30, 37, 31, 31, 21, 32, 29, 27, 27, 30, 39, 34, 23, 35, 39, 27, 40, 28, 36, 35, 38, 21, 18, 21, 38, 37, 24, 21, 25, 35, 27, 35, 24, 36, 32, 20] Wage=[17000, 13000, 28000, 45000, 28000, 1200, 15500, 26400, 14000, 35000, 16400, 50000, 2600, 9000, 27000, 150000, 32000, 22000, 65000, 56000, 6500, 30000, 70000, 9000, 6000, 34000, 40000, 30000, 6400, 87000, 20000, 45000, 4800, 34000, 75000, 26000, 4000, 50000, 63000, 14700, 45000, 42000, 10000, 40000, 70000, 14000, 54000, 14000, 23000, 24400, 27900, 4700, 8000, 19000, 17300, 45000, 3900, 2900, 138000, 2100, 60000, 55000, 45000, 40000, 45700, 90000, 40000, 13000, 30000, 2000, 75000, 60000, 70000, 41000, 42000, 31000, 39000, 104000, 52000, 20000, 59000, 66000, 63000, 32000, 11000, 16000, 6400, 17000, 47700, 5000, 25000, 35000, 20000, 14000, 29000, 267000, 31000, 27000, 64000, 39600, 267000, 7100, 33000, 31500, 40000, 23000, 3000, 14000, 44000, 15100, 2600, 6200, 50000, 3000, 25000, 2000, 38000, 22000, 20000, 2500, 1500, 42000, 30000, 27000, 7000, 11900, 27000, 24000, 4300, 30200, 2500, 30000, 70000, 38700, 8000, 36000, 66000, 24000, 95000, 39000, 20000, 23000, 56000, 25200, 62000, 12000, 13000, 35000, 35000, 14000, 24000, 12000, 14000, 31000, 40000, 22900, 12000, 14000, 1600, 12000, 80000, 90000, 126000, 1600, 100000, 8000, 71000, 40000, 42000, 40000, 120000, 35000, 1200, 4000, 32000, 8000, 14500, 65000, 15000, 3000, 2000, 23900, 1000, 22000, 18200, 8000, 30000, 23000, 30000, 27000, 70000, 40000, 18000, 3100, 57000, 25000, 32000, 10000, 4000, 49000, 93000, 35000, 49000, 40000, 5500, 30000, 25000, 5700, 6000, 30000, 42900, 8000, 5300, 90000, 85000, 15000, 17000, 5600, 11500, 52000, 1000, 42000, 2100, 50000, 1500, 40000, 28000, 5300, 149000, 3200, 12000, 83000, 45000, 31200, 25000, 72000, 70000, 7000, 23000, 40000, 40000, 28000, 10000, 48000, 20000, 60000, 19000, 25000, 39000, 68000, 2300, 23900, 5000, 16300, 80000, 45000, 12000, 9000, 1300, 35000, 35000, 47000, 32000, 18000, 20000, 20000, 23400, 48000, 8000, 5200, 33500, 22000, 22000, 52000, 104000, 28000, 13000, 12000, 15000, 53000, 27000, 50000, 13900, 23000, 28100, 23000, 12000, 55000, 83000, 31000, 33200, 45000, 3000, 18000, 11000, 41000, 36000, 33600, 38000, 45000, 53000, 24000, 3000, 37500, 7700, 4800, 29000, 6600, 12400, 20000, 2000, 1100, 55000, 13400, 10000, 6000, 6000, 16000, 19000, 8300, 52000, 58000, 27000, 25000, 80000, 10000, 22000, 18000, 21000, 8000, 15200, 15000, 5000, 50000, 89000, 7000, 65000, 58000, 42000, 55000, 40000, 14000, 36000, 30000, 7900, 6000, 1200, 10000, 54000, 12800, 35000, 34000, 40000, 45000, 9600, 3300, 39000, 22000, 40000, 68000, 24400, 1000, 10800, 8400, 50000, 22000, 20000, 20000, 1300, 9000, 14200, 32000, 65000, 18000, 18000, 3000, 16700, 1500, 1400, 15000, 55000, 42000, 70000, 35000, 21600, 5800, 35000, 5700, 1700, 40000, 40000, 45000, 25000, 13000, 6400, 11000, 4200, 30000, 32000, 120000, 10000, 19000, 12000, 13000, 37000, 40000, 38000, 60000, 3100, 16000, 18000, 130000, 5000, 5000, 35000, 1000, 14300, 100000, 20000, 33000, 8000, 9400, 87000, 2500, 12000, 12000, 33000, 16500, 25500, 7200, 2300, 3100, 2100, 3200, 45000, 40000, 3800, 30000, 12000, 62000, 45000, 46000, 50000, 40000, 13000, 50000, 23000, 4000, 40000, 25000, 16000, 3000, 80000, 27000, 68000, 3500, 1300, 10000, 46000, 5800, 24000, 12500, 50000, 48000, 29000, 19000, 26000, 30000, 10000, 10000, 20000, 43000, 105000, 55000, 5000, 65000, 68000, 38000, 47000, 48700, 6100, 55000, 30000, 5000, 3500, 23400, 11400, 7000, 1300, 80000, 65000, 45000, 19000, 3000, 17100, 22900, 31200, 35000, 3000, 5000, 1000, 36000, 4800, 60000, 9800, 30000, 85000, 18000, 24000, 60000, 30000, 2000, 39000, 12000, 10500, 60000, 36000, 10500, 3600, 1200, 28600, 48000, 20800, 5400, 9600, 30000, 30000, 20000, 6700, 30000, 3200, 42000, 37000, 5000, 18000, 20000, 14000, 12000, 18000, 3000, 13500, 35000, 38000, 30000, 36000, 66000, 45000, 32000, 46000, 80000, 27000, 4000, 21000, 7600, 16000, 10300, 27000, 19000, 14000, 19000, 3100, 20000, 2700, 27000, 7000, 13600, 75000, 35000, 36000, 25000, 6000, 36000, 50000, 46000, 3000, 37000, 40000, 30000, 48800, 19700, 16000, 14000, 12000, 25000, 25000, 28600, 17000, 31200, 57000, 23000, 23500, 46000, 18700, 26700, 9900, 16000, 3000, 52000, 51000, 14000, 14400, 27000, 26000, 60000, 25000, 6000, 20000, 3000, 69000, 24800, 12000, 3100, 18000, 20000, 267000, 28000, 9800, 18200, 80000, 6800, 21100, 20000, 68000, 20000, 45000, 8000, 40000, 31900, 28000, 24000, 2000, 32000, 11000, 20000, 5900, 16100, 23900, 40000, 37500, 11000, 55000, 37500, 60000, 23000, 9500, 34500, 4000, 9000, 11200, 35200, 30000, 18000, 21800, 19700, 16700, 12500, 11300, 4000, 39000, 32000, 14000, 65000, 50000, 2000, 30400, 22000, 1600, 56000, 40000, 85000, 9000, 10000, 19000, 5300, 5200, 43000, 60000, 50000, 38000, 267000, 15600, 1800, 17000, 45000, 31000, 5000, 8000, 43000, 103000, 45000, 8800, 26000, 47000, 40000, 8000] barchart(Age, Wage)

[ "41738638+jonasthiel@users.noreply.github.com" ]

41738638+jonasthiel@users.noreply.github.com

90183dc2e95fc8a7d4d677c104370a0fada22f44

81a7ab5346f8e656438b3b5ec9eef5b11e1e620f

/text_2.py

fd5372e456e304b2fc38fda8971532b3bab52712

[]

no_license

GetAlice/python

82396a2b0db55ebf865d7dd9010df8fe8b909455

299b2355ae4afda0f613f427e2b08d9e559d0cfc

refs/heads/master

2020-03-15T19:38:00.272797

2018-06-04T02:10:27

132,313,486

0

null

UTF-8

Python

false

900

py

cookie = 'anonymid=jfgfivcbazwm36; ' \ '_r01_=1; ' \ 'ln_uact=18689393892; ' \ 'ln_hurl=http://head.xiaonei.com/photos/0/0/men_main.gif; ' \ '_de=E0EDF5D325EC1DBA1D9123C741F918C1; ' \ 'depovince=GUZ; ' \ 'ick_login=6be5197b-c163-4429-b58e-75d2abc70648; jebecookies=48921195-5c61-4615-8cbb-51e19985e85c|||||; ' \ 'jebe_key=11bfc5d3-b7fe-42c5-906c-82a149aa932d%7Cd2d0ee61a963d41f217dde8146469b12%7C1522566662335%7C1%7C1524539451045' CookieList_1 = cookie.split(';') #print(b) dic1 = {} #print('\n',"#"*100,'\n') for CookieNum in CookieList_1: CookieList_2 = CookieNum.split('=') CookieKey_1 = CookieList_2[0] CookieValue_1 = CookieList_2[1] dic1[CookieKey_1] = CookieValue_1 #cc[c[0]] = c[1] print(str.ljust('keys:',15,' '),' \t','value:') print("#"*180) for keys,value in dic1.items(): print(str.ljust(keys,15,' '),'=\t',value)

[ "13537656018@163.com" ]

13537656018@163.com

ebaad1711387e4345c65fa0681b7f399491d8301

993ef8924418866f932396a58e3ad0c2a940ddd3

/Production/python/PrivateSamples/EMJ_UL17_mMed-2200_mDark-10_ctau-0p1_unflavored-down_cff.py

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[]

no_license

TreeMaker/TreeMaker

48d81f6c95a17828dbb599d29c15137cd6ef009a

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refs/heads/Run2_UL

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import FWCore.ParameterSet.Config as cms maxEvents = cms.untracked.PSet( input = cms.untracked.int32(-1) ) readFiles = cms.untracked.vstring() secFiles = cms.untracked.vstring() source = cms.Source ("PoolSource",fileNames = readFiles, secondaryFileNames = secFiles) readFiles.extend( [ 'root://cmseos.fnal.gov///store/group/lpcsusyhad/ExoEMJAnalysis2020/Signal.Oct.2021/UL17/step4_MINIAODv2_mMed-2200_mDark-10_ctau-0p1_unflavored-down_n-500_part-1.root', 'root://cmseos.fnal.gov///store/group/lpcsusyhad/ExoEMJAnalysis2020/Signal.Oct.2021/UL17/step4_MINIAODv2_mMed-2200_mDark-10_ctau-0p1_unflavored-down_n-500_part-10.root', 'root://cmseos.fnal.gov///store/group/lpcsusyhad/ExoEMJAnalysis2020/Signal.Oct.2021/UL17/step4_MINIAODv2_mMed-2200_mDark-10_ctau-0p1_unflavored-down_n-500_part-2.root', 'root://cmseos.fnal.gov///store/group/lpcsusyhad/ExoEMJAnalysis2020/Signal.Oct.2021/UL17/step4_MINIAODv2_mMed-2200_mDark-10_ctau-0p1_unflavored-down_n-500_part-3.root', 'root://cmseos.fnal.gov///store/group/lpcsusyhad/ExoEMJAnalysis2020/Signal.Oct.2021/UL17/step4_MINIAODv2_mMed-2200_mDark-10_ctau-0p1_unflavored-down_n-500_part-4.root', 'root://cmseos.fnal.gov///store/group/lpcsusyhad/ExoEMJAnalysis2020/Signal.Oct.2021/UL17/step4_MINIAODv2_mMed-2200_mDark-10_ctau-0p1_unflavored-down_n-500_part-5.root', 'root://cmseos.fnal.gov///store/group/lpcsusyhad/ExoEMJAnalysis2020/Signal.Oct.2021/UL17/step4_MINIAODv2_mMed-2200_mDark-10_ctau-0p1_unflavored-down_n-500_part-6.root', 'root://cmseos.fnal.gov///store/group/lpcsusyhad/ExoEMJAnalysis2020/Signal.Oct.2021/UL17/step4_MINIAODv2_mMed-2200_mDark-10_ctau-0p1_unflavored-down_n-500_part-7.root', 'root://cmseos.fnal.gov///store/group/lpcsusyhad/ExoEMJAnalysis2020/Signal.Oct.2021/UL17/step4_MINIAODv2_mMed-2200_mDark-10_ctau-0p1_unflavored-down_n-500_part-8.root', 'root://cmseos.fnal.gov///store/group/lpcsusyhad/ExoEMJAnalysis2020/Signal.Oct.2021/UL17/step4_MINIAODv2_mMed-2200_mDark-10_ctau-0p1_unflavored-down_n-500_part-9.root', ] )

[ "enochnotsocool@gmail.com" ]

enochnotsocool@gmail.com

c9fe6a43262930b71ccf027355c041006268fea6

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/src/visualize.py

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permissive

OumaimaHourrane/NLP-Project-Documents

cfc212cab5d6a389a26ae2cfa6bf74ae6a5084b2

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refs/heads/main

2023-03-22T15:59:46.096492

2021-03-13T11:02:12

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#!/usr/bin/env python3 # -*- coding: utf-8 -*- """ Created on Fri Aug 14 11:06:05 2020 @author: jonas & oumaima @title: visualisations """ import holoviews as hv from holoviews import opts, dim import holoviews.plotting.bokeh import numpy as np import panel as pn import pandas as pd import matplotlib.pyplot as plt import seaborn as sns import re import umap.umap_ as umap from wordcloud import WordCloud, STOPWORDS from wordcloud import WordCloud import wordcloud from collections import Counter, defaultdict #%% def disp_category(category, df, min_items): ''' Display Categorical charts ''' dff = df.groupby(category) class_ = dff.count().sort_values(by='PIMS_ID')['PIMS_ID'].reset_index() class_.columns=[category,'count'] class_= class_[class_['count']>=min_items][category] df = df[df[category].isin(class_)] labels = df[category] counts = defaultdict(int) for l in labels: counts[l] += 1 counts_df = pd.DataFrame.from_dict(counts, orient='index') counts_df.columns = ['count'] counts_df.sort_values('count', ascending=False, inplace=True) fig, ax = plt.subplots() ax = sns.barplot(x=counts_df.index, y=counts_df['count'], ax=ax) fig.set_size_inches(10,5) ax.set_xticklabels(ax.xaxis.get_majorticklabels(), rotation=-90); ax.set_title('Label: '+category.upper()) plt.show() return class_ #%% def scatter(category, df, min_items): ''' Display scatterplot ''' dff = df.groupby(category) class_ = dff.count().sort_values(by='PIMS_ID')['PIMS_ID'].reset_index() class_.columns=[category,'count'] class_= class_[class_['count']>=min_items][category] df = df[df[category].isin(class_)] labels = df[category] counts = defaultdict(int) for l in labels: counts[l] += 1 counts_df = pd.DataFrame.from_dict(counts, orient='index') counts_df.columns = ['count'] counts_df.sort_values('count', ascending=False, inplace=True) fig, ax = plt.subplots() sns.despine(fig, left=True, bottom=True) ax = sns.scatterplot(x=counts_df.index, y=counts_df['count'], palette="ch:r=-.2,d=.3_r", linewidth=0, data=df, ax=ax) ax.set_title('Label: '+category.upper()) plt.show() return class_ #%% import plotly.graph_objs as go from plotly.offline import iplot def plotly_bar(category, df, min_items): ''' Display Categorical charts ''' dff = df.groupby(category) class_ = dff.count().sort_values(by='PIMS_ID')['PIMS_ID'].reset_index() class_.columns=[category,'count'] class_= class_[class_['count']>=min_items][category] df = df[df[category].isin(class_)] labels = df[category] counts = defaultdict(int) for l in labels: counts[l] += 1 counts_df = pd.DataFrame.from_dict(counts, orient='index') counts_df.columns = ['count'] counts_df.sort_values('count', ascending=False, inplace=True) data = [go.Bar( x = counts_df.index, y = counts_df['count'] )] fig = go.Figure(data=data) iplot(fig) return fig def plotly_pie(category, df, min_items): ''' Display Categorical charts ''' dff = df.groupby(category) class_ = dff.count().sort_values(by='PIMS_ID')['PIMS_ID'].reset_index() class_.columns=[category,'count'] class_= class_[class_['count']>=min_items][category] df = df[df[category].isin(class_)] labels = df[category] counts = defaultdict(int) for l in labels: counts[l] += 1 counts_df = pd.DataFrame.from_dict(counts, orient='index') counts_df.columns = ['count'] counts_df.sort_values('count', ascending=False, inplace=True) data = [go.Pie( labels = counts_df.index, values = counts_df['count'], )] fig = go.Figure(data=data) iplot(fig) return fig def plotly_scatter(category, df, min_items): ''' Display Categorical charts ''' dff = df.groupby(category) class_ = dff.count().sort_values(by='PIMS_ID')['PIMS_ID'].reset_index() class_.columns=[category,'count'] class_= class_[class_['count']>=min_items][category] df = df[df[category].isin(class_)] labels = df[category] counts = defaultdict(int) for l in labels: counts[l] += 1 counts_df = pd.DataFrame.from_dict(counts, orient='index') counts_df.columns = ['count'] counts_df.sort_values('count', ascending=False, inplace=True) trace0 = go.Scatter( x = counts_df.index, y = counts_df['count'], mode = 'markers', name = 'markers' ) trace1 = go.Scatter( x = counts_df.index, y = counts_df['count'], mode = 'lines+markers', name = 'line+markers' ) trace2 = go.Scatter( x = counts_df.index, y = counts_df['count'], mode = 'lines', name = 'line' ) data = [trace0, trace1, trace2] fig = go.Figure(data=data) iplot(fig) return fig def plotly_radar(category, df, min_items): ''' Display Categorical charts ''' dff = df.groupby(category) class_ = dff.count().sort_values(by='PIMS_ID')['PIMS_ID'].reset_index() class_.columns=[category,'count'] class_= class_[class_['count']>=min_items][category] df = df[df[category].isin(class_)] labels = df[category] counts = defaultdict(int) for l in labels: counts[l] += 1 counts_df = pd.DataFrame.from_dict(counts, orient='index') counts_df.columns = ['count'] counts_df.sort_values('count', ascending=False, inplace=True) radar = go.Scatterpolar( r = counts_df['count'], theta = counts_df.index, fill = 'toself' ) data = [radar] fig = go.Figure(data=data) iplot(fig) return fig def chord_chard(data): """ Takes in processed dataframe for multilabel classification problem and computes label co-occurences. Draws chord chard using bokeh and local server. """ hv.extension('bokeh') hv.output(size=200) labels_only = data.drop(labels = ['PIMS_ID', 'project_description', 'logframe', 'all_text'], axis=1) cooccurrence_matrix = np.dot(labels_only.transpose(),labels_only) cooccurrence_matrix_diagonal = np.diagonal(cooccurrence_matrix) with np.errstate(divide='ignore', invalid='ignore'): cooccurrence_matrix_percentage = np.nan_to_num(np.true_divide(cooccurrence_matrix, cooccurrence_matrix_diagonal[:, None])) coocc = labels_only.T.dot(labels_only) diagonal = np.diagonal(coocc) co_per = np.nan_to_num(np.true_divide(coocc, diagonal[:, None])) df_co_per = pd.DataFrame(co_per) df_co_per = pd.DataFrame(data=co_per, columns=coocc.columns, index=coocc.index) #replace diagonal with 0: coocc.values[[np.arange(coocc.shape[0])]*2] = 0 coocc = coocc.mask(np.triu(np.ones(coocc.shape, dtype=np.bool_))) coocc = coocc.fillna(0) data = hv.Dataset((list(coocc.columns), list(coocc.index), coocc), ['source', 'target'], 'value').dframe() data['value'] = data['value'].astype(int) chord = hv.Chord(data) plot = chord.opts( node_color='index', edge_color='source', label_index='index', cmap='Category20', edge_cmap='Category20', width=400, height=400) bokeh_server = pn.Row(plot).show(port=1234) def Cramer_V(confusion_matrix): ''' Shows correlation between categorical columns (like heat mao for numeric columns) ''' import scipy.stats as ss chi2 = ss.chi2_contingency(confusion_matrix)[0] n = confusion_matrix.sum() phi2 = chi2/n r,k = confusion_matrix.shape phi2corr = max(0, phi2 - ((k-1)*(r-1))/(n-1)) rcorr = r - ((r-1)**2)/(n-1) kcorr = k - ((k-1)**2)/(n-1) return np.sqrt(phi2corr / min( (kcorr-1), (rcorr-1))) def genSankey(df,cat_cols=[],value_cols='',title='Sankey Diagram'): # maximum of 6 value cols -> 6 colors colorPalette = ['#4B8BBE','#306998','#FFE873','#FFD43B','#646464'] labelList = [] colorNumList = [] for catCol in cat_cols: labelListTemp = list(set(df[catCol].values)) colorNumList.append(len(labelListTemp)) labelList = labelList + labelListTemp # remove duplicates from labelList labelList = list(dict.fromkeys(labelList)) # define colors based on number of levels colorList = [] for idx, colorNum in enumerate(colorNumList): colorList = colorList + [colorPalette[idx]]*colorNum # transform df into a source-target pair for i in range(len(cat_cols)-1): if i==0: sourceTargetDf = df[[cat_cols[i],cat_cols[i+1],value_cols]] sourceTargetDf.columns = ['source','target','count'] else: tempDf = df[[cat_cols[i],cat_cols[i+1],value_cols]] tempDf.columns = ['source','target','count'] sourceTargetDf = pd.concat([sourceTargetDf,tempDf]) sourceTargetDf = sourceTargetDf.groupby(['source','target']).agg({'count':'sum'}).reset_index() # add index for source-target pair sourceTargetDf['sourceID'] = sourceTargetDf['source'].apply(lambda x: labelList.index(x)) sourceTargetDf['targetID'] = sourceTargetDf['target'].apply(lambda x: labelList.index(x)) # creating the sankey diagram data = dict( type='sankey', node = dict( pad = 15, thickness = 20, line = dict( color = "black", width = 0.5 ), label = labelList, color = colorList ), link = dict( source = sourceTargetDf['sourceID'], target = sourceTargetDf['targetID'], value = sourceTargetDf['count'] ) ) layout = dict( title = title, font = dict( size = 10 ) ) fig = dict(data=[data], layout=layout) return fig def draw_cloud(dataframe, column): # Join the different processed titles together. long_string = ','.join(list(dataframe[column])) # Create a WordCloud object wordcloud = WordCloud(background_color="white", max_words=5000, contour_width=6, contour_color='steelblue') # Generate a word cloud wordcloud.generate(long_string) # Visualize the word cloud return wordcloud.to_image() def plot_proj(embedding, lbs): """ Plot UMAP embeddings :param embedding: UMAP (or other) embeddings :param lbs: labels """ n = len(embedding) counter = Counter(lbs) for i in range(len(np.unique(lbs))): plt.plot(embedding[:, 0][lbs == i], embedding[:, 1][lbs == i], '.', alpha=0.5, label='cluster {}: {:.2f}%'.format(i, counter[i] / n * 100)) plt.legend()

[ "jonas.nothnagen@undp.sk" ]

jonas.nothnagen@undp.sk

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/test/functional/interface_bitcoin_cli.py

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[ "MIT" ]

permissive

Shadow0Bit/suscoin

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refs/heads/master

2023-05-08T18:00:23.116434

2021-05-26T10:50:59

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#!/usr/bin/env python3 # Copyright (c) 2017-2018 The Bitcoin Core developers # Distributed under the MIT software license, see the accompanying # file COPYING or http://www.opensource.org/licenses/mit-license.php. """Test suscoin-cli""" from test_framework.test_framework import BitcoinTestFramework from test_framework.util import assert_equal, assert_raises_process_error, get_auth_cookie class TestBitcoinCli(BitcoinTestFramework): def set_test_params(self): self.setup_clean_chain = True self.num_nodes = 1 def run_test(self): """Main test logic""" cli_response = self.nodes[0].cli("-version").send_cli() assert("Suscoin Core RPC client version" in cli_response) self.log.info("Compare responses from getwalletinfo RPC and `suscoin-cli getwalletinfo`") if self.is_wallet_compiled(): cli_response = self.nodes[0].cli.getwalletinfo() rpc_response = self.nodes[0].getwalletinfo() assert_equal(cli_response, rpc_response) self.log.info("Compare responses from getblockchaininfo RPC and `suscoin-cli getblockchaininfo`") cli_response = self.nodes[0].cli.getblockchaininfo() rpc_response = self.nodes[0].getblockchaininfo() assert_equal(cli_response, rpc_response) user, password = get_auth_cookie(self.nodes[0].datadir) self.log.info("Test -stdinrpcpass option") assert_equal(0, self.nodes[0].cli('-rpcuser=%s' % user, '-stdinrpcpass', input=password).getblockcount()) assert_raises_process_error(1, "Incorrect rpcuser or rpcpassword", self.nodes[0].cli('-rpcuser=%s' % user, '-stdinrpcpass', input="foo").echo) self.log.info("Test -stdin and -stdinrpcpass") assert_equal(["foo", "bar"], self.nodes[0].cli('-rpcuser=%s' % user, '-stdin', '-stdinrpcpass', input=password + "\nfoo\nbar").echo()) assert_raises_process_error(1, "Incorrect rpcuser or rpcpassword", self.nodes[0].cli('-rpcuser=%s' % user, '-stdin', '-stdinrpcpass', input="foo").echo) self.log.info("Test connecting to a non-existing server") assert_raises_process_error(1, "Could not connect to the server", self.nodes[0].cli('-rpcport=1').echo) self.log.info("Test connecting with non-existing RPC cookie file") assert_raises_process_error(1, "Could not locate RPC credentials", self.nodes[0].cli('-rpccookiefile=does-not-exist', '-rpcpassword=').echo) self.log.info("Make sure that -getinfo with arguments fails") assert_raises_process_error(1, "-getinfo takes no arguments", self.nodes[0].cli('-getinfo').help) self.log.info("Compare responses from `suscoin-cli -getinfo` and the RPCs data is retrieved from.") cli_get_info = self.nodes[0].cli('-getinfo').send_cli() if self.is_wallet_compiled(): wallet_info = self.nodes[0].getwalletinfo() network_info = self.nodes[0].getnetworkinfo() blockchain_info = self.nodes[0].getblockchaininfo() assert_equal(cli_get_info['version'], network_info['version']) assert_equal(cli_get_info['protocolversion'], network_info['protocolversion']) if self.is_wallet_compiled(): assert_equal(cli_get_info['walletversion'], wallet_info['walletversion']) assert_equal(cli_get_info['balance'], wallet_info['balance']) assert_equal(cli_get_info['blocks'], blockchain_info['blocks']) assert_equal(cli_get_info['timeoffset'], network_info['timeoffset']) assert_equal(cli_get_info['connections'], network_info['connections']) assert_equal(cli_get_info['proxy'], network_info['networks'][0]['proxy']) assert_equal(cli_get_info['difficulty'], blockchain_info['difficulty']) assert_equal(cli_get_info['testnet'], blockchain_info['chain'] == "test") if self.is_wallet_compiled(): assert_equal(cli_get_info['balance'], wallet_info['balance']) assert_equal(cli_get_info['keypoololdest'], wallet_info['keypoololdest']) assert_equal(cli_get_info['keypoolsize'], wallet_info['keypoolsize']) assert_equal(cli_get_info['paytxfee'], wallet_info['paytxfee']) assert_equal(cli_get_info['relayfee'], network_info['relayfee']) # unlocked_until is not tested because the wallet is not encrypted if __name__ == '__main__': TestBitcoinCli().main()

[ "joker.rafrom@gmail.com" ]

joker.rafrom@gmail.com

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[]

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gabriellaec/desoft-analise-exercicios

b77c6999424c5ce7e44086a12589a0ad43d6adca

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refs/heads/main

2023-01-31T17:19:42.050628

2020-12-16T05:21:31

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import math def calcula_pi(n): if n == 1: p = (6**(1/2)) return p p = 0 valores = list(range(n)) valores.remove(0) for a in (valores): p += (6/(a**2)) p = (p**(1/2)) return p

[ "you@example.com" ]

you@example.com

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/Mailbox/wsgi.py

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[]

no_license

jangwoni79/PostBox

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refs/heads/master

2022-11-18T23:02:25.847353

2020-07-20T11:43:28

281,048,982

0

null

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391

py

""" WSGI config for Mailbox project. It exposes the WSGI callable as a module-level variable named ``application``. For more information on this file, see https://docs.djangoproject.com/en/2.2/howto/deployment/wsgi/ """ import os from django.core.wsgi import get_wsgi_application os.environ.setdefault('DJANGO_SETTINGS_MODULE', 'Mailbox.settings') application = get_wsgi_application()

[ "s2018w17@e-mirim.hs.kr" ]

s2018w17@e-mirim.hs.kr

c49cb629b81dd8bab875ff2f9d3dbd0a5ce2d44e

fea2eff6ed6ff05879e071d52d978b1f2f322f31

/TensorFlow深度学习应用实践_源代码/08/8-1.py

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[]

no_license

GetMyPower/mypython

71ec8db85c82e33b893c5d53ac64a007951fd8f0

1846148e327e7d14ebb96c9fea4b47aa61762a69

refs/heads/master

2022-03-22T08:11:56.113905

2019-12-20T15:00:23

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0

null

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py

import tensorflow as tf input1 = tf.constant(1) print(input1) input2 = tf.Variable(2,tf.int32) print(input2) input2 = input1 sess = tf.Session() print(sess.run(input2))

[ "noreply@github.com" ]

GetMyPower.noreply@github.com

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/app.py

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[]

no_license

Zomma2/deployIBM

d5146a0546f476b2a90f32880103b27944165f27

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refs/heads/main

2023-06-05T03:17:03.976867

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3,292

py

from flask import Flask, request, render_template import requests # Flask constructor app = Flask(__name__,instance_relative_config=True) # A decorator used to tell the application # which URL is associated function @app.route('/', methods =["GET", "POST"]) def gfg(): if request.method == "POST": # getting input with name = fname in HTML form first_name = request.form.get("fname") # getting input with name = lname in HTML form return ''' <style> h1, input::-webkit-input-placeholder, button { font-family: "roboto", sans-serif; -webkit-transition: all 0.3s ease-in-out; transition: all 0.3s ease-in-out; } h1 { height: 100px; width: 100%; font-size: 18px; background: #18aa8d; color: white; line-height: 150%; border-radius: 3px 3px 0 0; box-shadow: 0 2px 5px 1px rgba(0, 0, 0, 0.2); } form { box-sizing: border-box; width: 260px; margin: 100px auto 0; box-shadow: 2px 2px 5px 1px rgba(0, 0, 0, 0.2); padding-bottom: 40px; border-radius: 3px; } form h1 { box-sizing: border-box; padding: 20px; } input { margin: 40px 25px; width: 200px; display: block; border: none; padding: 10px 0; border-bottom: solid 1px #1abc9c; transition: all 0.3s cubic-bezier(0.64, 0.09, 0.08, 1); background: linear-gradient(to bottom, rgba(255, 255, 255, 0) 96%, #1abc9c 4%); background-position: -200px 0; background-size: 200px 100%; background-repeat: no-repeat; color: #0e6252; } input:focus, input:valid { box-shadow: none; outline: none; background-position: 0 0; } input:focus::-webkit-input-placeholder, input:valid::-webkit-input-placeholder { color: #1abc9c; font-size: 11px; transform: translateY(-20px); visibility: visible !important; } button { border: none; background: #1abc9c; cursor: pointer; border-radius: 3px; padding: 6px; width: 200px; color: white; margin-left: 25px; box-shadow: 0 3px 6px 0 rgba(0, 0, 0, 0.2); } button:hover { transform: translateY(-3px); box-shadow: 0 6px 6px 0 rgba(0, 0, 0, 0.2); } .follow { width: 42px; height: 42px; border-radius: 50px; background: #03A9F4; display: inline-block; margin: 50px calc(50% - 21px); white-space: nowrap; padding: 13px; box-sizing: border-box; color: white; transition: all 0.2s ease; font-family: Roboto, sans-serif; text-decoration: none; box-shadow: 0 5px 6px 0 rgba(0, 0, 0, 0.2); } .follow i { margin-right: 20px; transition: margin-right 0.2s ease; } .follow:hover { width: 134px; transform: translateX(-50px); } .follow:hover i { margin-right: 10px; } </style> <form> <h1>Material Design Text Input With No Extra Markup</h1> </form> <form> <h1>Material Design Text Input With No Extra Markup</h1> </form> <form> <h1>Material Design Text Input With No Extra Markup</h1> </form> <form> <h1>Material Design Text Input With No Extra Markup</h1> </form> <link rel="stylesheet" href="//maxcdn.bootstrapcdn.com/font-awesome/4.3.0/css/font-awesome.min.css"> <link href='https://fonts.googleapis.com/css?family=Roboto:400' rel='stylesheet' type='text/css'> ''' return render_template("form.html") if __name__=='__main__': app.run()

[ "noreply@github.com" ]

Zomma2.noreply@github.com

685f5b50fe2191735f15da00d09ef6c8b2d29276

17e908c7de7819460c519b70a15ded97a75ad89b

/utils/log.py

d7dba77818e49f5f15114d935e1c8134ccc4a3f0

[]

no_license

emcoglab/ldm-core

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5cf70e4275460b67b89c49bf8fd9fea507da2c9f

refs/heads/main

2023-07-24T09:54:42.363720

2023-04-03T15:34:35

168,543,788

2

1

null

2023-07-21T03:35:33

2019-01-31T15:02:23

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UTF-8

Python

false

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py

from sys import stdout log_message = '%(asctime)s | %(levelname).2s | %(filename)s:%(lineno)d | \t%(message)s' date_format = "%Y-%m-%d %H:%M:%S" def print_progress(iteration: int, total: int, prefix: str = '', suffix: str = '', *, decimals: int = 1, bar_length: int = 100, clear_on_completion: bool = False): """ Call in a loop to create terminal progress bar. Based on https://gist.github.com/aubricus/f91fb55dc6ba5557fbab06119420dd6a @params: iteration - Required : current iteration (Int) total - Required : total iterations (Int) prefix - Optional : prefix string (Str) suffix - Optional : suffix string (Str) decimals - Optional : positive number of decimals in percent complete (Int) bar_length - Optional : character length of bar (Int) clear_on_completion - Optional : clear the bar when it reaches 100% (bool) """ full_char = '█' empty_char = '-' portion_complete = iteration / float(total) percents = f"{100 * portion_complete:.{decimals}f}%" filled_length = int(round(bar_length * portion_complete)) bar = (full_char * filled_length) + (empty_char * (bar_length - filled_length)) stdout.write(f'\r{prefix}|{bar}| {percents}{suffix}'), if iteration == total: stdout.write("\r" if clear_on_completion else "\n") stdout.flush()

[ "c.wingfield@lancaster.ac.uk" ]

c.wingfield@lancaster.ac.uk

95f171bbc154a65c80bf052125d739628093e175

504ecbf46271bcb6594743afa80b141dfe4c14b5

/pharma/migrations/0017_auto_20171111_2134.py

5e0fb9e4e0a24ec554101ee780f587cf2f4b9502

[]

no_license

projectworldsofficial/medstore

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refs/heads/master

2021-09-26T10:31:29.414959

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# -*- coding: utf-8 -*- # Generated by Django 1.11.6 on 2017-11-11 16:04 from __future__ import unicode_literals from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('pharma', '0016_auto_20171111_2128'), ] operations = [ migrations.AlterField( model_name='customer', name='c_id', field=models.IntegerField(unique=True), ), migrations.AlterField( model_name='medicine', name='m_id', field=models.IntegerField(unique=True), ), migrations.AlterField( model_name='purchase', name='p_id', field=models.IntegerField(unique=True), ), ]

[ "soham5959595@gmail.com" ]

soham5959595@gmail.com

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/pollexe/urls.py

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[]

no_license

sajalmia381/pollexe

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refs/heads/master

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from django.conf import settings from django.conf.urls.static import static from django.contrib import admin from django.urls import path, include urlpatterns = [ path('', include('account.urls', namespace='account')), path('', include('page.urls', namespace='page')), path('', include('blog.urls', namespace='blog')), path('', include('product.urls', namespace='product')), # admin path('admin/', admin.site.urls), # Third party path('summernote/', include('django_summernote.urls')), path('front-edit/', include('front.urls')), ] urlpatterns += static(settings.STATIC_URL, document_root=settings.STATIC_ROOT) urlpatterns += static(settings.MEDIA_URL, document_root=settings.MEDIA_ROOT)

[ "sajal_mia@ymail.com" ]

sajal_mia@ymail.com

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/xcodeproj/pbxproj/objects/__init__.py

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[]

no_license

topwo/XcodeScripts

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6fb8dd7455f657f1f21bd3bfbc2a0c151383b561

refs/heads/master

2020-11-26T18:39:38.509543

2018-04-28T11:34:36

2018-04-28T11:35:25

null

0

null

UTF-8

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702

py

#!/usr/bin/python # encoding:utf-8 # # copyright (c) Alex Lee, All rights reserved. import os import sys ModuleRoot = os.path.abspath(os.path.join(__file__, '../../../..')) if os.path.isdir(ModuleRoot) and not ModuleRoot in sys.path: sys.path.append(ModuleRoot) from xcodeproj.pbxproj.objects.buildfile import * from xcodeproj.pbxproj.objects.buildphase import * from xcodeproj.pbxproj.objects.fileref import * from xcodeproj.pbxproj.objects.group import * from xcodeproj.pbxproj.objects.project import * from xcodeproj.pbxproj.objects.target import * from xcodeproj.pbxproj.objects.config import * from xcodeproj.pbxproj.objects.dependency import * from xcodeproj.pbxproj.objects.proxy import *

[ "alexlee002@hotmail.com" ]

alexlee002@hotmail.com

5e0b811355d69d98aa4f260aafc4dacef13b4dd2

95fb4b8e51dd7a852d9ed9de067c1e929a71404a

/colour/models/rgb/datasets/sony.py

ed1b14ee7367d8cae14cb322f5cd81df68be3c15

[ "BSD-3-Clause" ]

permissive

zachlewis/colour

e9b1f6978dae157306536492a652b2fb9588894a

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refs/heads/develop

2021-04-25T22:08:34.617007

2020-11-29T23:18:48

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BSD-3-Clause

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py

# -*- coding: utf-8 -*- """ Sony Colourspaces ================= Defines the *Sony* colourspaces: - :attr:`colour.models.RGB_COLOURSPACE_S_GAMUT`. - :attr:`colour.models.RGB_COLOURSPACE_S_GAMUT3`. - :attr:`colour.models.RGB_COLOURSPACE_S_GAMUT3_CINE`. - :attr:`colour.models.RGB_COLOURSPACE_VENICE_S_GAMUT3`. - :attr:`colour.models.RGB_COLOURSPACE_VENICE_S_GAMUT3_CINE`. Notes ----- - The *Venice S-Gamut3* and *Venice S-Gamut3.Cine* primaries and whitepoint were derived with the following `Google Colab Notebook \ <https://colab.research.google.com/drive/1ZGTij7jT8eZRMPUkyWlv_x5ix5Q5twMB>`__. References ---------- - :cite:`Gaggioni` : Gaggioni, H., Dhanendra, P., Yamashita, J., Kawada, N., Endo, K., & Clark, C. (n.d.). S-Log: A new LUT for digital production mastering and interchange applications (Vol. 709, pp. 1-13). http://pro.sony.com/bbsccms/assets/files/mkt/cinema/solutions/slog_manual.pdf - :cite:`SonyCorporation` : Sony Corporation. (n.d.). S-Log Whitepaper (pp. 1-17). http://www.theodoropoulos.info/attachments/076_on%20S-Log.pdf - :cite:`SonyCorporationd` : Sony Corporation. (n.d.). Technical Summary for S-Gamut3.Cine/S-Log3 and S-Gamut3/S-Log3 (pp. 1-7). http://community.sony.com/sony/attachments/sony/\ large-sensor-camera-F5-F55/12359/2/\ TechnicalSummary_for_S-Gamut3Cine_S-Gamut3_S-Log3_V1_00.pdf - :cite:`SonyCorporatione` : Sony Corporation. (n.d.). S-Gamut3_S-Gamut3Cine_Matrix.xlsx. https://community.sony.com/sony/attachments/sony/\ large-sensor-camera-F5-F55/12359/3/S-Gamut3_S-Gamut3Cine_Matrix.xlsx - :cite:`SonyElectronicsCorporation2020` : Sony Electronics Corporation. (2020). IDT.Sony.Venice_SLog3_SGamut3.ctl. https://github.com/ampas/\ aces-dev/blob/710ecbe52c87ce9f4a1e02c8ddf7ea0d6b611cc8/transforms/ctl/idt/\ vendorSupplied/sony/IDT.Sony.Venice_SLog3_SGamut3.ctl - :cite:`SonyElectronicsCorporation2020a` : Sony Electronics Corporation. (2020). IDT.Sony.Venice_SLog3_SGamut3Cine.ctl. https://github.com/ampas/\ aces-dev/blob/710ecbe52c87ce9f4a1e02c8ddf7ea0d6b611cc8/transforms/ctl/idt/\ vendorSupplied/sony/IDT.Sony.Venice_SLog3_SGamut3Cine.ctl """ from __future__ import division, unicode_literals import numpy as np from colour.colorimetry import CCS_ILLUMINANTS from colour.models.rgb import (RGB_Colourspace, log_encoding_SLog2, log_decoding_SLog2, log_encoding_SLog3, log_decoding_SLog3, normalised_primary_matrix) __author__ = 'Colour Developers' __copyright__ = 'Copyright (C) 2013-2020 - Colour Developers' __license__ = 'New BSD License - https://opensource.org/licenses/BSD-3-Clause' __maintainer__ = 'Colour Developers' __email__ = 'colour-developers@colour-science.org' __status__ = 'Production' __all__ = [ 'PRIMARIES_S_GAMUT', 'WHITEPOINT_NAME_S_GAMUT', 'CCS_WHITEPOINT_S_GAMUT', 'MATRIX_S_GAMUT_TO_XYZ', 'MATRIX_XYZ_TO_S_GAMUT', 'RGB_COLOURSPACE_S_GAMUT', 'PRIMARIES_S_GAMUT3', 'WHITEPOINT_NAME_S_GAMUT3', 'CCS_WHITEPOINT_S_GAMUT3', 'MATRIX_S_GAMUT3_TO_XYZ', 'MATRIX_XYZ_TO_S_GAMUT3', 'RGB_COLOURSPACE_S_GAMUT3', 'PRIMARIES_S_GAMUT3_CINE', 'WHITEPOINT_NAME_S_GAMUT3_CINE', 'CCS_WHITEPOINT_S_GAMUT3_CINE', 'MATRIX_S_GAMUT3_CINE_TO_XYZ', 'MATRIX_XYZ_TO_S_GAMUT3_CINE', 'RGB_COLOURSPACE_S_GAMUT3_CINE', 'PRIMARIES_VENICE_S_GAMUT3', 'WHITEPOINT_NAME_VENICE_S_GAMUT3', 'CCS_WHITEPOINT_VENICE_S_GAMUT3', 'MATRIX_VENICE_S_GAMUT3_TO_XYZ', 'MATRIX_XYZ_TO_VENICE_S_GAMUT3', 'RGB_COLOURSPACE_VENICE_S_GAMUT3', 'PRIMARIES_VENICE_S_GAMUT3_CINE', 'WHITEPOINT_NAME_VENICE_S_GAMUT3_CINE', 'CCS_WHITEPOINT_VENICE_S_GAMUT3_CINE', 'MATRIX_VENICE_S_GAMUT3_CINE_TO_XYZ', 'MATRIX_XYZ_TO_VENICE_S_GAMUT3_CINE', 'RGB_COLOURSPACE_VENICE_S_GAMUT3_CINE' ] PRIMARIES_S_GAMUT = np.array([ [0.7300, 0.2800], [0.1400, 0.8550], [0.1000, -0.0500], ]) """ *S-Gamut* colourspace primaries. PRIMARIES_S_GAMUT : ndarray, (3, 2) """ WHITEPOINT_NAME_S_GAMUT = 'D65' """ *S-Gamut* colourspace whitepoint name. WHITEPOINT_NAME_S_GAMUT : unicode """ CCS_WHITEPOINT_S_GAMUT = (CCS_ILLUMINANTS[ 'CIE 1931 2 Degree Standard Observer'][WHITEPOINT_NAME_S_GAMUT]) """ *S-Gamut* colourspace whitepoint chromaticity coordinates. CCS_WHITEPOINT_S_GAMUT : ndarray """ MATRIX_S_GAMUT_TO_XYZ = np.array([ [0.7064827132, 0.1288010498, 0.1151721641], [0.2709796708, 0.7866064112, -0.0575860820], [-0.0096778454, 0.0046000375, 1.0941355587], ]) """ *S-Gamut* colourspace to *CIE XYZ* tristimulus values matrix. MATRIX_S_GAMUT_TO_XYZ : array_like, (3, 3) """ MATRIX_XYZ_TO_S_GAMUT = np.array([ [1.5073998991, -0.2458221374, -0.1716116808], [-0.5181517271, 1.3553912409, 0.1258786682], [0.0155116982, -0.0078727714, 0.9119163656], ]) """ *CIE XYZ* tristimulus values to *S-Gamut* colourspace matrix. MATRIX_XYZ_TO_S_GAMUT : array_like, (3, 3) """ RGB_COLOURSPACE_S_GAMUT = RGB_Colourspace( 'S-Gamut', PRIMARIES_S_GAMUT, CCS_WHITEPOINT_S_GAMUT, WHITEPOINT_NAME_S_GAMUT, MATRIX_S_GAMUT_TO_XYZ, MATRIX_XYZ_TO_S_GAMUT, log_encoding_SLog2, log_decoding_SLog2, ) RGB_COLOURSPACE_S_GAMUT.__doc__ = """ *S-Gamut* colourspace. References ---------- :cite:`Gaggioni`, :cite:`SonyCorporation` RGB_COLOURSPACE_S_GAMUT : RGB_Colourspace """ PRIMARIES_S_GAMUT3 = PRIMARIES_S_GAMUT """ *S-Gamut3* colourspace primaries. PRIMARIES_S_GAMUT3 : ndarray, (3, 2) """ WHITEPOINT_NAME_S_GAMUT3 = WHITEPOINT_NAME_S_GAMUT """ *S-Gamut3* colourspace whitepoint name. WHITEPOINT_NAME_S_GAMUT3 : unicode """ CCS_WHITEPOINT_S_GAMUT3 = CCS_WHITEPOINT_S_GAMUT """ *S-Gamut3* colourspace whitepoint chromaticity coordinates. CCS_WHITEPOINT_S_GAMUT3 : ndarray """ MATRIX_S_GAMUT3_TO_XYZ = MATRIX_S_GAMUT_TO_XYZ """ *S-Gamut3* colourspace to *CIE XYZ* tristimulus values matrix. MATRIX_S_GAMUT3_TO_XYZ : array_like, (3, 3) """ MATRIX_XYZ_TO_S_GAMUT3 = MATRIX_XYZ_TO_S_GAMUT """ *CIE XYZ* tristimulus values to *S-Gamut3* colourspace matrix. MATRIX_XYZ_TO_S_GAMUT3 : array_like, (3, 3) """ RGB_COLOURSPACE_S_GAMUT3 = RGB_Colourspace( 'S-Gamut3', PRIMARIES_S_GAMUT3, CCS_WHITEPOINT_S_GAMUT3, WHITEPOINT_NAME_S_GAMUT3, MATRIX_S_GAMUT3_TO_XYZ, MATRIX_XYZ_TO_S_GAMUT3, log_encoding_SLog3, log_decoding_SLog3, ) RGB_COLOURSPACE_S_GAMUT3.__doc__ = """ *S-Gamut3* colourspace. References ---------- :cite:`SonyCorporationd` RGB_COLOURSPACE_S_GAMUT3 : RGB_Colourspace """ PRIMARIES_S_GAMUT3_CINE = np.array([ [0.76600, 0.27500], [0.22500, 0.80000], [0.08900, -0.08700], ]) """ *S-Gamut3.Cine* colourspace primaries. PRIMARIES_S_GAMUT3_CINE : ndarray, (3, 2) """ WHITEPOINT_NAME_S_GAMUT3_CINE = WHITEPOINT_NAME_S_GAMUT """ *S-Gamut3.Cine* colourspace whitepoint name. WHITEPOINT_NAME_S_GAMUT3_CINE : unicode """ CCS_WHITEPOINT_S_GAMUT3_CINE = CCS_WHITEPOINT_S_GAMUT """ *S-Gamut3.Cine* colourspace whitepoint chromaticity coordinates. CCS_WHITEPOINT_S_GAMUT3_CINE : ndarray """ MATRIX_S_GAMUT3_CINE_TO_XYZ = np.array([ [0.5990839208, 0.2489255161, 0.1024464902], [0.2150758201, 0.8850685017, -0.1001443219], [-0.0320658495, -0.0276583907, 1.1487819910], ]) """ *S-Gamut3.Cine* colourspace to *CIE XYZ* tristimulus values matrix. MATRIX_S_GAMUT3_CINE_TO_XYZ : array_like, (3, 3) """ MATRIX_XYZ_TO_S_GAMUT3_CINE = np.array([ [1.8467789693, -0.5259861230, -0.2105452114], [-0.4441532629, 1.2594429028, 0.1493999729], [0.0408554212, 0.0156408893, 0.8682072487], ]) """ *CIE XYZ* tristimulus values to *S-Gamut3.Cine* colourspace matrix. MATRIX_XYZ_TO_S_GAMUT3_CINE : array_like, (3, 3) """ RGB_COLOURSPACE_S_GAMUT3_CINE = RGB_Colourspace( 'S-Gamut3.Cine', PRIMARIES_S_GAMUT3_CINE, CCS_WHITEPOINT_S_GAMUT3_CINE, WHITEPOINT_NAME_S_GAMUT3_CINE, MATRIX_S_GAMUT3_CINE_TO_XYZ, MATRIX_XYZ_TO_S_GAMUT3_CINE, log_encoding_SLog3, log_decoding_SLog3, ) RGB_COLOURSPACE_S_GAMUT3_CINE.__doc__ = """ *S-Gamut3.Cine* colourspace. References ---------- :cite:`SonyCorporatione` RGB_COLOURSPACE_S_GAMUT3_CINE : RGB_Colourspace """ PRIMARIES_VENICE_S_GAMUT3 = np.array([ [0.740464264304292, 0.279364374750660], [0.089241145423286, 0.893809528608105], [0.110488236673827, -0.052579333080476], ]) """ *Venice S-Gamut3* colourspace primaries. PRIMARIES_VENICE_S_GAMUT3 : ndarray, (3, 2) """ WHITEPOINT_NAME_VENICE_S_GAMUT3 = WHITEPOINT_NAME_S_GAMUT """ *Venice S-Gamut3* colourspace whitepoint name. WHITEPOINT_NAME_VENICE_S_GAMUT3 : unicode """ CCS_WHITEPOINT_VENICE_S_GAMUT3 = CCS_WHITEPOINT_S_GAMUT """ *Venice S-Gamut3* colourspace whitepoint chromaticity coordinates. CCS_WHITEPOINT_VENICE_S_GAMUT3 : ndarray """ MATRIX_VENICE_S_GAMUT3_TO_XYZ = normalised_primary_matrix( PRIMARIES_VENICE_S_GAMUT3, CCS_WHITEPOINT_VENICE_S_GAMUT3) """ *Venice S-Gamut3* colourspace to *CIE XYZ* tristimulus values matrix. MATRIX_VENICE_S_GAMUT3_TO_XYZ : array_like, (3, 3) """ MATRIX_XYZ_TO_VENICE_S_GAMUT3 = np.linalg.inv(MATRIX_VENICE_S_GAMUT3_TO_XYZ) """ *CIE XYZ* tristimulus values to *Venice S-Gamut3* colourspace matrix. MATRIX_XYZ_TO_VENICE_S_GAMUT3 : array_like, (3, 3) """ RGB_COLOURSPACE_VENICE_S_GAMUT3 = RGB_Colourspace( 'Venice S-Gamut3', PRIMARIES_VENICE_S_GAMUT3, CCS_WHITEPOINT_VENICE_S_GAMUT3, WHITEPOINT_NAME_VENICE_S_GAMUT3, MATRIX_VENICE_S_GAMUT3_TO_XYZ, MATRIX_XYZ_TO_VENICE_S_GAMUT3, log_encoding_SLog3, log_decoding_SLog3, ) RGB_COLOURSPACE_VENICE_S_GAMUT3.__doc__ = """ *Venice S-Gamut3* colourspace. References ---------- :cite:`SonyElectronicsCorporation2020` RGB_COLOURSPACE_VENICE_S_GAMUT3 : RGB_Colourspace """ PRIMARIES_VENICE_S_GAMUT3_CINE = np.array([ [0.775901871567345, 0.274502392854799], [0.188682902773355, 0.828684937020288], [0.101337382499301, -0.089187517306263], ]) """ *Venice S-Gamut3.Cine* colourspace primaries. PRIMARIES_VENICE_S_GAMUT3_CINE : ndarray, (3, 2) """ WHITEPOINT_NAME_VENICE_S_GAMUT3_CINE = WHITEPOINT_NAME_S_GAMUT """ *Venice S-Gamut3.Cine* colourspace whitepoint name. WHITEPOINT_NAME_VENICE_S_GAMUT3_CINE : unicode """ CCS_WHITEPOINT_VENICE_S_GAMUT3_CINE = CCS_WHITEPOINT_S_GAMUT """ *Venice S-Gamut3.Cine* colourspace whitepoint chromaticity coordinates. CCS_WHITEPOINT_VENICE_S_GAMUT3_CINE : ndarray """ MATRIX_VENICE_S_GAMUT3_CINE_TO_XYZ = normalised_primary_matrix( PRIMARIES_VENICE_S_GAMUT3_CINE, CCS_WHITEPOINT_VENICE_S_GAMUT3_CINE) """ *Venice S-Gamut3.Cine* colourspace to *CIE XYZ* tristimulus values matrix. MATRIX_VENICE_S_GAMUT3_CINE_TO_XYZ : array_like, (3, 3) """ MATRIX_XYZ_TO_VENICE_S_GAMUT3_CINE = np.linalg.inv( MATRIX_VENICE_S_GAMUT3_CINE_TO_XYZ) """ *CIE XYZ* tristimulus values to *Venice S-Gamut3.Cine* colourspace matrix. MATRIX_XYZ_TO_VENICE_S_GAMUT3_CINE : array_like, (3, 3) """ RGB_COLOURSPACE_VENICE_S_GAMUT3_CINE = RGB_Colourspace( 'Venice S-Gamut3.Cine', PRIMARIES_VENICE_S_GAMUT3_CINE, CCS_WHITEPOINT_VENICE_S_GAMUT3_CINE, WHITEPOINT_NAME_VENICE_S_GAMUT3_CINE, MATRIX_VENICE_S_GAMUT3_CINE_TO_XYZ, MATRIX_XYZ_TO_VENICE_S_GAMUT3_CINE, log_encoding_SLog3, log_decoding_SLog3, ) RGB_COLOURSPACE_VENICE_S_GAMUT3_CINE.__doc__ = """ *Venice S-Gamut3.Cine* colourspace. References ---------- :cite:`SonyElectronicsCorporation2020a` RGB_COLOURSPACE_VENICE_S_GAMUT3_CINE : RGB_Colourspace """

[ "thomas.mansencal@gmail.com" ]

thomas.mansencal@gmail.com

3d044de9966d419518ae75f3007bb5bd623f03b3

f6930b9b12c47c19d1ef5677342a3a69cfe5535e

/1st/toprint.py

06fe348b38df3b75a5245644dd0468c97cee9611

[]

no_license

tenzinsonam/matcher

5ae1e61ed053fd084dff011f18932aab8eb2f3e2

b8510f9d50d6a4718e2bb31c537c6564264f12f4

refs/heads/master

2021-05-16T17:38:50.004941

2018-02-05T12:07:42

102,978,950

0

null

UTF-8

Python

false

4,372

py

from pycparser import c_parser, c_ast, parse_file, c_generator class BinaryOpVisitor(c_ast.NodeVisitor): def __init__(self): self.values = [] def visit_BinaryOp(self,node): self.values.append(node) class IfVisitor(c_ast.NodeVisitor): def __init__(self): self.values = [] def visit_If(self,node): self.values.append(node) class UnaryOpVisitor(c_ast.NodeVisitor): def __init__(self): self.values = [] def visit_UnaryOp(self,node): self.values.append(node) class AssignmentVisitor(c_ast.NodeVisitor): def __init__(self): self.values = [] def visit_Assignment(self,node): self.values.append(node) class DeclVisitor(c_ast.NodeVisitor): def __init__(self): self.values = [] def visit_Decl(self,node): self.values.append(node) def hasChildren(node, p): chils = 0 for yname, y in node.children(): chils+=1 if chils is int(p): return 1 else: return 0 def hasChild(node, p): for yname, y in node.children(): if type(y).__name__==p: return 1 return 0 def rule0(node): nodelist = [] isFirst=1 selflist=[] x0=IfVisitor() x0.visit(node) if x0.values: for x1 in x0.values: x2=BinaryOpVisitor() x2.visit(x1) if x2.values: for x3 in x2.values: for x4 in x3.__slots__: if(getattr(x3,x4)=='=='): if isFirst: nodelist.append(x3) else: selflist.append(x3) temp = nodelist[:] if not isFirst: for m in nodelist: if m not in selflist: temp.remove(m) isFirst=0 nodelist = temp for m in nodelist: m.show() print(m.coord.line) def rule1(node): nodelist = [] isFirst=1 selflist=[] x0=AssignmentVisitor() x0.visit(node) if x0.values: for x1 in x0.values: x2=UnaryOpVisitor() x2.visit(x1) if x2.values: for x3 in x2.values: for x4 in x3.__slots__: if(getattr(x3,x4)=='p++'): if isFirst: nodelist.append(x3) else: selflist.append(x3) temp = nodelist[:] if not isFirst: for m in nodelist: if m not in selflist: temp.remove(m) isFirst=0 nodelist = temp for m in nodelist: m.show() print(m.coord.line) def rule2(node): nodelist = [] isFirst=1 selflist=[] x0=DeclVisitor() x0.visit(node) if x0.values: for x1 in x0.values: x2=hasChildren(x1,"2") if isFirst and x2: nodelist.append(x1) elif x2: selflist.append(x1) temp = nodelist[:] if not isFirst: for m in nodelist: if m not in selflist: temp.remove(m) isFirst=0 nodelist = temp selflist=[] x0=DeclVisitor() x0.visit(node) if x0.values: for x1 in x0.values: x2=hasChild(x1,"PtrDecl") if isFirst and x2: nodelist.append(x1) elif x2: selflist.append(x1) temp = nodelist[:] if not isFirst: for m in nodelist: if m not in selflist: temp.remove(m) isFirst=0 nodelist = temp for m in nodelist: m.show() print(m.coord.line) def rule3(node): nodelist = [] isFirst=1 selflist=[] x0=IfVisitor() x0.visit(node) if x0.values: for x1 in x0.values: x2=hasChild(x1,"Assignment") if isFirst and x2: nodelist.append(x1) elif x2: selflist.append(x1) temp = nodelist[:] if not isFirst: for m in nodelist: if m not in selflist: temp.remove(m) isFirst=0 nodelist = temp for m in nodelist: m.show() print(m.coord.line) def rule4(node): nodelist = [] isFirst=1 selflist=[] x0=AssignmentVisitor() x0.visit(node) if x0.values: for x1 in x0.values: x2=UnaryOpVisitor() x2.visit(x1) if x2.values: for x3 in x2.values: for x4 in x3.__slots__: if(getattr(x3,x4)=="*"): if isFirst: nodelist.append(x3) else: selflist.append(x3) temp = nodelist[:] if not isFirst: for m in nodelist: if m not in selflist: temp.remove(m) isFirst=0 nodelist = temp for m in nodelist: m.show() print(m.coord.line) def rule5(node): nodelist = [] isFirst=1 selflist=[] x0=AssignmentVisitor() x0.visit(node) if x0.values: for x1 in x0.values: x2=hasChild(x1,"Assignment") if isFirst and x2: nodelist.append(x1) elif x2: selflist.append(x1) temp = nodelist[:] if not isFirst: for m in nodelist: if m not in selflist: temp.remove(m) isFirst=0 nodelist = temp for m in nodelist: m.show() print(m.coord.line) ast = parse_file("sample.c") rule0(ast) rule1(ast) rule2(ast) rule3(ast) rule4(ast) rule5(ast)

[ "tenzinsonam008@gmail.com" ]

tenzinsonam008@gmail.com

d78a7f97e2bbf295b699f32b08fc0480aa10688a

67ae1b00411ad63726e0abb07ba82ac5b75fc32a

/findmusician/wsgi.py

e3e754c495255bd2fa5792053e4e437c249d3059

[]

no_license

SimonKorzonek/findmusician

e40429bf45115de0709ef6fe92ace3c5cd195660

fc23e0d6b5da7d98423accef5eb82b9b6c5516bc

refs/heads/main

2023-02-15T10:12:02.070458

2021-01-05T23:02:05

327,074,301

0

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401

py

""" WSGI config for findmusician project. It exposes the WSGI callable as a module-level variable named ``application``. For more information on this file, see https://docs.djangoproject.com/en/3.1/howto/deployment/wsgi/ """ import os from django.core.wsgi import get_wsgi_application os.environ.setdefault('DJANGO_SETTINGS_MODULE', 'findmusician.settings') application = get_wsgi_application()

[ "korzonek.szymon@gmail.com" ]

korzonek.szymon@gmail.com

69be95ec2717104dca1975260567cc9d867e4907

d0325f0cc1deae11a854cdb6b208414f609d0d68

/bin/cgdms

37d0efa8d42cf48a26cd0fc46de10e7250a761a4

[ "MIT" ]

permissive

avasquee/cgdms

800ca46851e82b0924e691af6dd7085325075f38

735919cb58a697bd4a27e4903a893a090f3cbe92

refs/heads/master

2023-08-19T07:58:36.088722

2021-09-03T10:05:36

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#!/usr/bin/env python # Argument handling # Author: Joe G Greener import argparse import pkg_resources parser = argparse.ArgumentParser(description=( "Differentiable molecular simulation of proteins with a coarse-grained potential. " "See https://github.com/psipred/cgdms for documentation and citation information. " f"This is version {pkg_resources.get_distribution('cgdms').version} of the software." )) subparsers = parser.add_subparsers(dest="mode", help="the mode to run cgdms in, run \"cgdms {mode} -h\" to see help for each") parser_makeinput = subparsers.add_parser("makeinput", description="Form an input protein data file.", help="form an input protein data file") parser_makeinput.add_argument("-i", "--input", required=True, help="PDB/mmCIF file, format guessed from extension") parser_makeinput.add_argument("-s", "--ss2", help="PSIPRED ss2 file, default fully coiled (not recommended)") parser_simulate = subparsers.add_parser("simulate", description="Run a coarse-grained simulation of a protein in the learned potential.", help="run a coarse-grained simulation of a protein in the learned potential") parser_simulate.add_argument("-i", "--input", required=True, help="input protein data file") parser_simulate.add_argument("-o", "--output", help="output PDB filepath, if this is not given then no PDB file is written") parser_simulate.add_argument("-s", "--startconf", required=True, choices=["native", "extended", "predss", "random", "helix"], help="starting conformation") parser_simulate.add_argument("-n", "--nsteps", required=True, type=float, help="number of simulation steps to run") parser_simulate.add_argument("-t", "--temperature", type=float, default=0.015, help="thermostat temperature, default 0.015") parser_simulate.add_argument("-c", "--coupling", type=float, default=25.0, help="thermostat coupling constant, default 25, set to 0 to run without a thermostat") parser_simulate.add_argument("-st", "--starttemperature", type=float, default=0.015, help="starting temperature, default 0.015") parser_simulate.add_argument("-ts", "--timestep", type=float, default=0.004, help="integrator time step, default 0.004") parser_simulate.add_argument("-r", "--report", type=int, default=10_000, help="interval for printing energy and writing PDB file, default 10_000") parser_simulate.add_argument("-p", "--parameters", help="parameter set to use, default is the trained model") parser_simulate.add_argument("-d", "--device", help="device to run on, default is \"cuda\" if it is available otherwise \"cpu\"") parser_simulate.add_argument("-v", "--verbosity", type=int, choices=[0, 1, 2], default=2, help="logging verbosity, default 2") parser_energy = subparsers.add_parser("energy", description="Calculate the energy of a structure in the learned potential.", help="calculate the energy of a structure in the learned potential") parser_energy.add_argument("-i", "--input", required=True, help="input protein data file") parser_energy.add_argument("-m", "--minsteps", type=float, default=0.0, help="number of minimisation steps to run, default 0") parser_energy.add_argument("-p", "--parameters", help="parameter set to use, default is the trained model") parser_energy.add_argument("-d", "--device", help="device to run on, default is \"cuda\" if it is available otherwise \"cpu\"") parser_energy.add_argument("-v", "--verbosity", type=int, choices=[0, 1, 2], default=0, help="logging verbosity, default 0") parser_thread = subparsers.add_parser("thread", description=("Calculate the energy in the learned potential of a set of sequences threaded " "onto a structure. Returns one energy per line."), help=("calculate the energy in the learned potential of a set of sequences threaded onto a " "structure")) parser_thread.add_argument("-i", "--input", required=True, help="input protein data file") parser_thread.add_argument("-s", "--sequences", required=True, help="file of sequences to thread, one per line") parser_thread.add_argument("-m", "--minsteps", type=float, default=100.0, help="number of minimisation steps to run for each sequence, default 100") parser_thread.add_argument("-p", "--parameters", help="parameter set to use, default is the trained model") parser_thread.add_argument("-d", "--device", help="device to run on, default is \"cuda\" if it is available otherwise \"cpu\"") parser_thread.add_argument("-v", "--verbosity", type=int, choices=[0, 1, 2], default=0, help="logging verbosity, default 0") parser_design = subparsers.add_parser("design", description="Carry out fixed backbone protein design in the learned potential.", help="carry out fixed backbone protein design in the learned potential") parser_design.add_argument("-i", "--input", required=True, help="input protein data file") parser_design.add_argument("-n", "--nmutations", type=float, default=2_000.0, help="number of mutations to trial, default 2_000") parser_design.add_argument("-m", "--minsteps", type=float, default=100.0, help="number of minimisation steps to run for each sequence, default 100") parser_design.add_argument("-nc", "--nocolor", action="store_false", help="do not print output in color") parser_design.add_argument("-p", "--parameters", help="parameter set to use, default is the trained model") parser_design.add_argument("-d", "--device", help="device to run on, default is \"cuda\" if it is available otherwise \"cpu\"") parser_design.add_argument("-v", "--verbosity", type=int, choices=[0, 1, 2], default=0, help="logging verbosity, default 0") parser_train = subparsers.add_parser("train", description="Train the model. This can take a couple of months... go and get a coffee?", help="train the model") parser_train.add_argument("-o", "--output", default="cgdms_params.pt", help="output learned parameter filepath, default \"cgdms_params.pt\"") parser_train.add_argument("-d", "--device", help="device to run on, default is \"cuda\" if it is available otherwise \"cpu\"") parser_train.add_argument("-v", "--verbosity", type=int, choices=[0, 1, 2], default=0, help="logging verbosity, default 0") args = parser.parse_args() for arg in ("nsteps", "temperature", "coupling", "starttemperature", "timestep", "report", "minsteps", "nmutations"): if arg in args.__dict__ and args.__dict__[arg] < 0: raise argparse.ArgumentTypeError(f"{arg} is {args.__dict__[arg]} but must be non-negative") # Imported after argument parsing because it takes a few seconds from cgdms import * if "device" in args.__dict__: if args.device is None: device = "cuda" if torch.cuda.is_available() else "cpu" else: device = args.device if args.mode == "makeinput": print_input_file(args.input, args.ss2) elif args.mode == "simulate": if args.output and os.path.exists(args.output): os.remove(args.output) if args.parameters: params = torch.load(args.parameters, map_location=device) else: params = torch.load(trained_model_file, map_location=device) native_coords, inters_flat, inters_ang, inters_dih, masses, seq = read_input_file(args.input, device=device) with torch.no_grad(): simulator = Simulator(params["distances"], params["angles"], params["dihedrals"]) if args.startconf == "native": coords = native_coords else: coords = starting_coords(seq, conformation=args.startconf, input_file=args.input, device=device) coords = simulator(coords.unsqueeze(0), inters_flat.unsqueeze(0), inters_ang.unsqueeze(0), inters_dih.unsqueeze(0), masses.unsqueeze(0), seq, native_coords.unsqueeze(0), int(args.nsteps), integrator="vel", timestep=args.timestep, start_temperature=args.starttemperature, thermostat_const=args.coupling, temperature=args.temperature, sim_filepath=args.output, report_n=args.report, verbosity=args.verbosity) elif args.mode == "energy": if args.parameters: params = torch.load(args.parameters, map_location=device) else: params = torch.load(trained_model_file, map_location=device) coords, inters_flat, inters_ang, inters_dih, masses, seq = read_input_file(args.input, device=device) with torch.no_grad(): simulator = Simulator(params["distances"], params["angles"], params["dihedrals"]) energy = simulator(coords.unsqueeze(0), inters_flat.unsqueeze(0), inters_ang.unsqueeze(0), inters_dih.unsqueeze(0), masses.unsqueeze(0), seq, coords.unsqueeze(0), int(args.minsteps), integrator="min", energy=True, verbosity=args.verbosity) print(round(energy.item(), 3)) elif args.mode == "thread": if args.parameters: params = torch.load(args.parameters, map_location=device) else: params = torch.load(trained_model_file, map_location=device) with torch.no_grad(): simulator = Simulator(params["distances"], params["angles"], params["dihedrals"]) with open(args.sequences) as f: for li, line in enumerate(f): if not line.startswith(">"): coords, inters_flat, inters_ang, inters_dih, masses, seq = read_input_file_threaded( args.input, line.rstrip(), device=device) energy = simulator(coords.unsqueeze(0), inters_flat.unsqueeze(0), inters_ang.unsqueeze(0), inters_dih.unsqueeze(0), masses.unsqueeze(0), seq, coords.unsqueeze(0), int(args.minsteps), integrator="min", energy=True, verbosity=args.verbosity) print(li + 1, round(energy.item(), 3)) elif args.mode == "design": if args.parameters: params = torch.load(args.parameters, map_location=device) else: params = torch.load(trained_model_file, map_location=device) with torch.no_grad(): simulator = Simulator(params["distances"], params["angles"], params["dihedrals"]) fixed_backbone_design(args.input, simulator, n_mutations=int(args.nmutations), n_min_steps=int(args.minsteps), print_color=args.nocolor, device=device, verbosity=args.verbosity) elif args.mode == "train": train(args.output, device=device, verbosity=args.verbosity) else: print("No mode selected, run \"cgdms -h\" to see help")

[ "jgreener@hotmail.co.uk" ]

jgreener@hotmail.co.uk

27791dff47ce4d430b69660ad95df2783f3233fd

c9ddbdb5678ba6e1c5c7e64adf2802ca16df778c

/cases/synthetic/coverage-big-3078.py

47f6110342d0bc97ffe7055c5477a7037e7b6e28

[]

no_license

Virtlink/ccbench-chocopy

c3f7f6af6349aff6503196f727ef89f210a1eac8

c7efae43bf32696ee2b2ee781bdfe4f7730dec3f

refs/heads/main

2023-04-07T15:07:12.464038

2022-02-03T15:42:39

451,969,776

0

null

UTF-8

Python

false

13,339

py

count:int = 0 count2:int = 0 count3:int = 0 count4:int = 0 count5:int = 0 def foo(s: str) -> int: return len(s) def foo2(s: str, s2: str) -> int: return len(s) def foo3(s: str, s2: str, s3: str) -> int: return len(s) def foo4(s: str, s2: str, s3: str, s4: str) -> int: return len(s) def foo5(s: str, s2: str, s3: str, s4: str, s5: str) -> int: return len(s) class bar(object): p: bool = True def baz(self:"bar", xx: [int]) -> str: global count x:int = 0 y:int = 1 def qux(y: int) -> object: nonlocal x if x > y: x = -1 for x in xx: self.p = x == 2 qux(0) # Yay! ChocoPy count = count + 1 while x <= 0: if self.p: xx[0] = xx[1] self.p = not self.p x = x + 1 elif foo("Long"[0]) == 1: self.p = self is None return "Nope" class bar2(object): p: bool = True p2: bool = True def baz(self:"bar2", xx: [int]) -> str: global count x:int = 0 y:int = 1 def qux(y: int) -> object: nonlocal x if x > y: x = -1 for x in xx: self.p = x == 2 qux(0) # Yay! ChocoPy count = count + 1 while x <= 0: if self.p: xx[0] = xx[1] self.p = not self.p x = x + 1 elif foo("Long"[0]) == 1: self.p = self is None return "Nope" def baz2(self:"bar2", xx: [int], xx2: [int]) -> str: global count x:int = 0 x2:int = 0 y:int = 1 y2:int = 1 def qux(y: int) -> object: nonlocal x if x > y: x = -1 def qux2(y: int, y2: int) -> object: nonlocal x nonlocal x2 if x > y: x = -1 for x in xx: self.p = x == 2 qux(0) # Yay! ChocoPy count = count + 1 while x <= 0: if self.p: xx[0] = xx[1] self.p = not self.p x = x + 1 elif foo("Long"[0]) == 1: self.p = self is None return "Nope" class bar3(object): p: bool = True p2: bool = True p3: bool = True def baz(self:"bar3", xx: [int]) -> str: global count x:int = 0 y:int = 1 def qux(y: int) -> object: nonlocal x if x > y: x = -1 for x in xx: self.p = x == 2 qux(0) # Yay! ChocoPy count = count + 1 while x <= 0: if self.p: xx[0] = xx[1] self.p = not self.p x = x + 1 elif foo("Long"[0]) == 1: self.p = self is None return "Nope" def baz2(self:"bar3", xx: [int], xx2: [int]) -> str: global count x:int = 0 x2:int = 0 y:int = 1 y2:int = 1 def qux(y: int) -> object: nonlocal x if x > y: x = -1 def qux2(y: int, y2: int) -> object: nonlocal x nonlocal x2 if x > y: x = -1 for x in xx: self.p = x == 2 qux(0) # Yay! ChocoPy count = count + 1 while x <= 0: if self.p: xx[0] = xx[1] self.p = not self.p x = x + 1 elif foo("Long"[0]) == 1: self.p = self is None return "Nope" def baz3(self:"bar3", xx: [int], xx2: [int], xx3: [int]) -> str: global count x:int = 0 x2:int = 0 x3:int = 0 y:int = 1 y2:int = 1 y3:int = 1 def qux(y: int) -> object: nonlocal x if x > y: x = -1 def qux2(y: int, y2: int) -> object: nonlocal x nonlocal x2 if x > y: x = -1 def qux3(y: int, y2: int, y3: int) -> object: nonlocal x nonlocal x2 nonlocal x3 if x > y: x = -1 for x in xx: self.p = x == 2 qux(0) # Yay! ChocoPy count = count + 1 while x <= 0: if self.p: xx[0] = xx[1] self.p = not self.p x = x + 1 elif foo("Long"[0]) == 1: self.p = self is None return "Nope" class bar4(object): p: bool = True p2: bool = True p3: bool = True p4: bool = True def baz(self:"bar4", xx: [int]) -> str: global count x:int = 0 y:int = 1 def qux(y: int) -> object: nonlocal x if x > y: x = -1 for x in xx: self.p = x == 2 qux(0) # Yay! ChocoPy count = count + 1 while x <= 0: if self.p: xx[0] = xx[1] self.p = not self.p x = x + 1 elif foo("Long"[0]) == 1: self.p = self is None return "Nope" def baz2(self:"bar4", xx: [int], xx2: [int]) -> str: global count x:int = 0 x2:int = 0 y:int = 1 y2:int = 1 def qux(y: int) -> object: nonlocal x if x > y: x = -1 def qux2(y: int, y2: int) -> object: nonlocal x nonlocal x2 if x > y: x = -1 for x in xx: self.p = x == 2 qux(0) # Yay! ChocoPy count = count + 1 while x <= 0: if self.p: xx[0] = xx[1] self.p = not self.p x = x + 1 elif foo("Long"[0]) == 1: self.p = self is None return "Nope" def baz3(self:"bar4", xx: [int], xx2: [int], xx3: [int]) -> str: global count x:int = 0 x2:int = 0 x3:int = 0 y:int = 1 y2:int = 1 y3:int = 1 def qux(y: int) -> object: nonlocal x if x > y: x = -1 def qux2(y: int, y2: int) -> object: nonlocal x nonlocal x2 if x > y: x = -1 def qux3(y: int, y2: int, y3: int) -> object: nonlocal x nonlocal x2 nonlocal x3 if x > y: x = -1 for x in xx: self.p = x == 2 qux(0) # Yay! ChocoPy count = count + 1 while x <= 0: if self.p: xx[0] = xx[1] self.p = not self.p x = x + 1 elif foo("Long"[0]) == 1: self.p = self is None return "Nope" def baz4(self:"bar4", xx: [int], xx2: [int], xx3: [int], xx4: [int]) -> str: global count x:int = 0 x2:int = 0 x3:int = 0 x4:int = 0 y:int = 1 y2:int = 1 y3:int = 1 y4:int = 1 def qux(y: int) -> object: nonlocal x if x > y: x = -1 def qux2(y: int, y2: int) -> object: nonlocal x nonlocal x2 if x > y: x = -1 def qux3(y: int, y2: int, y3: int) -> object: nonlocal x nonlocal x2 nonlocal x3 if x > y: x = -1 def qux4(y: int, y2: int, y3: int, y4: int) -> object: nonlocal x nonlocal x2 nonlocal x3 nonlocal x4 if x > y: x = -1 for x in xx: $Block qux(0) # Yay! ChocoPy count = count + 1 while x <= 0: if self.p: xx[0] = xx[1] self.p = not self.p x = x + 1 elif foo("Long"[0]) == 1: self.p = self is None return "Nope" class bar5(object): p: bool = True p2: bool = True p3: bool = True p4: bool = True p5: bool = True def baz(self:"bar5", xx: [int]) -> str: global count x:int = 0 y:int = 1 def qux(y: int) -> object: nonlocal x if x > y: x = -1 for x in xx: self.p = x == 2 qux(0) # Yay! ChocoPy count = count + 1 while x <= 0: if self.p: xx[0] = xx[1] self.p = not self.p x = x + 1 elif foo("Long"[0]) == 1: self.p = self is None return "Nope" def baz2(self:"bar5", xx: [int], xx2: [int]) -> str: global count x:int = 0 x2:int = 0 y:int = 1 y2:int = 1 def qux(y: int) -> object: nonlocal x if x > y: x = -1 def qux2(y: int, y2: int) -> object: nonlocal x nonlocal x2 if x > y: x = -1 for x in xx: self.p = x == 2 qux(0) # Yay! ChocoPy count = count + 1 while x <= 0: if self.p: xx[0] = xx[1] self.p = not self.p x = x + 1 elif foo("Long"[0]) == 1: self.p = self is None return "Nope" def baz3(self:"bar5", xx: [int], xx2: [int], xx3: [int]) -> str: global count x:int = 0 x2:int = 0 x3:int = 0 y:int = 1 y2:int = 1 y3:int = 1 def qux(y: int) -> object: nonlocal x if x > y: x = -1 def qux2(y: int, y2: int) -> object: nonlocal x nonlocal x2 if x > y: x = -1 def qux3(y: int, y2: int, y3: int) -> object: nonlocal x nonlocal x2 nonlocal x3 if x > y: x = -1 for x in xx: self.p = x == 2 qux(0) # Yay! ChocoPy count = count + 1 while x <= 0: if self.p: xx[0] = xx[1] self.p = not self.p x = x + 1 elif foo("Long"[0]) == 1: self.p = self is None return "Nope" def baz4(self:"bar5", xx: [int], xx2: [int], xx3: [int], xx4: [int]) -> str: global count x:int = 0 x2:int = 0 x3:int = 0 x4:int = 0 y:int = 1 y2:int = 1 y3:int = 1 y4:int = 1 def qux(y: int) -> object: nonlocal x if x > y: x = -1 def qux2(y: int, y2: int) -> object: nonlocal x nonlocal x2 if x > y: x = -1 def qux3(y: int, y2: int, y3: int) -> object: nonlocal x nonlocal x2 nonlocal x3 if x > y: x = -1 def qux4(y: int, y2: int, y3: int, y4: int) -> object: nonlocal x nonlocal x2 nonlocal x3 nonlocal x4 if x > y: x = -1 for x in xx: self.p = x == 2 qux(0) # Yay! ChocoPy count = count + 1 while x <= 0: if self.p: xx[0] = xx[1] self.p = not self.p x = x + 1 elif foo("Long"[0]) == 1: self.p = self is None return "Nope" def baz5(self:"bar5", xx: [int], xx2: [int], xx3: [int], xx4: [int], xx5: [int]) -> str: global count x:int = 0 x2:int = 0 x3:int = 0 x4:int = 0 x5:int = 0 y:int = 1 y2:int = 1 y3:int = 1 y4:int = 1 y5:int = 1 def qux(y: int) -> object: nonlocal x if x > y: x = -1 def qux2(y: int, y2: int) -> object: nonlocal x nonlocal x2 if x > y: x = -1 def qux3(y: int, y2: int, y3: int) -> object: nonlocal x nonlocal x2 nonlocal x3 if x > y: x = -1 def qux4(y: int, y2: int, y3: int, y4: int) -> object: nonlocal x nonlocal x2 nonlocal x3 nonlocal x4 if x > y: x = -1 def qux5(y: int, y2: int, y3: int, y4: int, y5: int) -> object: nonlocal x nonlocal x2 nonlocal x3 nonlocal x4 nonlocal x5 if x > y: x = -1 for x in xx: self.p = x == 2 qux(0) # Yay! ChocoPy count = count + 1 while x <= 0: if self.p: xx[0] = xx[1] self.p = not self.p x = x + 1 elif foo("Long"[0]) == 1: self.p = self is None return "Nope" print(bar().baz([1,2]))

[ "647530+Virtlink@users.noreply.github.com" ]

647530+Virtlink@users.noreply.github.com

ae5027a60607ce4d65a8d5738a6d24f4432c7bf6

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/MaoPao_sort.py

eb07fc546ac134445c071d07ade0167e1fd98938

[]

no_license

LYLthe/Data_Structure

0b231f73efb198e510f7cb38373b1aff941d63aa

5cefeb4e18d3545f9c712c8cce2a117fed62b435

refs/heads/master

2020-03-20T10:09:28.436414

2018-07-25T06:44:48

137,360,984

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UTF-8

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py

""" 冒泡排序时间复杂度：O（n*n）最优排序：O（n）稳定性：稳定 """ import time import random def new_num(my_list): for i in range(50): num = random.randint(0, 1000) my_list.append(num) return my_list # 开始时间 start_time = time.time() def bubble_sort_high(list_1): """升序排列""" for i in range(len(list_1)-1, 0, -1): for j in range(i): if list_1[j] > list_1[j+1]: list_1[j], list_1[j+1] = list_1[j+1], list_1[j] return list_1 def bubble_sort_low(list_2): """降序排列""" for i in range(len(list_2)-1, 0, -1): for j in range(i): if list_2[j] < list_2[j+1]: list_2[j], list_2[j+1] = list_2[j+1], list_2[j] return list_2 y_list = [] unsorted_list = new_num(y_list) print(unsorted_list) print("升序排列 ", bubble_sort_high(unsorted_list)) print("降序排列: ", bubble_sort_low(unsorted_list))

[ "2270779418@qq.com" ]

2270779418@qq.com

c4463b466523f98a0389beff01c3891c2fefadb3

e23a4f57ce5474d468258e5e63b9e23fb6011188

/125_algorithms/_exercises/templates/_algorithms_challenges/leetcode/LeetcodePythonProject_with_solution/leetcode_0751_0800/LeetCode792_NumberOfMatchingSubsequences.py

ce718c54dd28669b15ae5ae32138582fbd1dc330

[]

no_license

syurskyi/Python_Topics

52851ecce000cb751a3b986408efe32f0b4c0835

be331826b490b73f0a176e6abed86ef68ff2dd2b

refs/heads/master

2023-06-08T19:29:16.214395

2023-05-29T17:09:11

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3

2

null

2023-02-16T03:08:10

2019-11-09T02:58:47

Python

UTF-8

Python

false

1,018

py

''' Created on Apr 16, 2018 @author: tongq ''' c_ Solution(o.. ___ numMatchingSubseq S, words """ :type S: str :type words: List[str] :rtype: int """ hashmap # dict ___ i __ r..(26 c chr(o..('a')+i) hashmap[c] # list ___ word __ words: hashmap[word[0]].a..(word) count 0 ___ c __ S: d.. hashmap[c] size l..(d..) ___ i __ r..(size word d...p.. 0) __ l.. ? __ 1: count += 1 ____ hashmap[word[1]].a..(word[1:]) r.. count ___ test testCases [ [ 'abcde', ["a", "bb", "acd", "ace"], ], ] ___ s, words __ testCases: result numMatchingSubseq(s, words) print('result: %s' % result) print('-='*30+'-') __ _____ __ _____ Solution().test()

[ "sergejyurskyj@yahoo.com" ]

sergejyurskyj@yahoo.com

f15451932e3ba9e1a116e799caa28d8cafc0878c

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/src/pyvaillant/client_auth.py

b4576d3e428d15c6576ac911f9a18159b8312cbf

[ "MIT" ]

permissive

bodiroga/vsmart2homie

99b4329d11b1bcc9de563eba8ee1678380b4c2f1

4a7db9cd6585ebccfc2bf164ca12873fcd36901b

refs/heads/master

2020-12-02T00:14:41.213023

2020-01-25T20:51:34

230,826,105

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py

# Python library for managing a Vaillant / Bulex MiGo Thermostat # Based on the pyatmo library by Philippe Larduinat # Revised July 2019 # Public domain source code """ This API provides access to the Vaillant / Bulex smart thermostat This package can be used with Python3 applications PythonAPI Vaillant/Bulex REST data access """ import logging import time from . import _BASE_URL, NoDevice, postRequest LOG = logging.getLogger(__name__) # Common definitions _AUTH_REQ = _BASE_URL + "oauth2/token" _WEBHOOK_URL_ADD = _BASE_URL + "api/addwebhook" _WEBHOOK_URL_DROP = _BASE_URL + "api/dropwebhook" _DEFAULT_SCOPE = "read_station read_camera access_camera read_thermostat write_thermostat read_presence access_presence" _DEFAULT_APP_VERSION = "1.0.4.0" _DEFAULT_USER_PREFIX = "vaillant" class ClientAuth(object): """ Request authentication and keep access token available through token method. Renew it automatically if necessary Args: clientId (str): Application clientId delivered by Netatmo on dev.netatmo.com clientSecret (str): Application Secret key delivered by Netatmo on dev.netatmo.com username (str) password (str) scope (Optional[str]): Default value is 'read_station' read_station: to retrieve weather station data (Getstationsdata, Getmeasure) read_camera: to retrieve Welcome data (Gethomedata, Getcamerapicture) access_camera: to access the camera, the videos and the live stream. read_thermostat: to retrieve thermostat data (Getmeasure, Getthermostatsdata) write_thermostat: to set up the thermostat (Syncschedule, Setthermpoint) read_presence: to retrieve Presence data (Gethomedata, Getcamerapicture) read_homecoach: to retrieve Home Coache data (Gethomecoachsdata) access_presence: to access the live stream, any video stored on the SD card and to retrieve Presence's lightflood status Several value can be used at the same time, ie: 'read_station read_camera' """ def __init__( self, clientId, clientSecret, username, password, scope=_DEFAULT_SCOPE, app_version=_DEFAULT_APP_VERSION, user_prefix=_DEFAULT_USER_PREFIX ): postParams = { "grant_type": "password", "client_id": clientId, "client_secret": clientSecret, "username": username, "password": password, "scope": scope, } if user_prefix: postParams.update({"user_prefix": user_prefix}) if app_version: postParams.update({"app_version": app_version}) resp = postRequest(_AUTH_REQ, postParams) self._clientId = clientId self._clientSecret = clientSecret try: self._accessToken = resp["access_token"] except (KeyError): LOG.error("Netatmo API returned %s", resp["error"]) raise NoDevice("Authentication against Netatmo API failed") self.refreshToken = resp["refresh_token"] self._scope = resp["scope"] self.expiration = int(resp["expire_in"] + time.time() - 1800) @property def accessToken(self): if self.expiration < time.time(): # Token should be renewed postParams = { "grant_type": "refresh_token", "refresh_token": self.refreshToken, "client_id": self._clientId, "client_secret": self._clientSecret, } resp = postRequest(_AUTH_REQ, postParams) self._accessToken = resp["access_token"] self.refreshToken = resp["refresh_token"] self.expiration = int(resp["expire_in"] + time.time() - 1800) return self._accessToken

[ "riturrioz@gmail.com" ]

riturrioz@gmail.com

d6927765c0f6ebbf69b62da25a3e7947b7feab43

a5d0642bc4e484cc0fe73b304e6f27384a1d07a8

/testunittest/name/__init__.py

3730a0f040a5a630896636a3141752c7fcde75b9

[]

no_license

lijunyang0210/testunittest

1a3b8413bcef963c86ce3d42db594ef63034f555

5365ebf12c396aabd5d72d5dea98ed461eb4645b

refs/heads/master

2020-07-20T05:34:53.466950

2019-09-05T14:36:21

206,582,174

0

null

UTF-8

Python

false

73

py

# -*- coding: utf-8 -*- # Author : 李俊阳 # @Time : 2019/9/3 21:14

[ "lijunyang0210@126.com" ]

lijunyang0210@126.com

3ab3e27fb739a45761ef77b83f03b45a6dab15f9

b00efc53bec9b05f91703db81387325fae0a771e

/MAI/olymp/17.02.05/a.py

364918dd1e8451ebddaa61670614cbf7012cf250

[]

no_license

21zaber/MAI

ac88eb1dd4b8f6b9d184527a3b1824a05993a9e1

45f25bdd5996329fd05f3e0ec7eb1289443f17b5

refs/heads/master

2021-01-17T07:12:22.303754

2018-02-08T15:05:30

54,101,933

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UTF-8

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832

py

n = int(input()) q = n+3 t = [[[[0 for i in range(q)] for i in range(q)] for i in range(q)] for i in range(n+1)] # len vs max last t[1][0][0][0] = 1 for l in range(1, n): for vs in range(l+1): for mx in range(l): for lst in range(mx+1): c = 0 if t[l][vs][mx][lst] == 0: continue for i in range(vs+2): if i <= lst: t[l+1][vs][mx][i] += t[l][vs][mx][lst] c+=1 elif i >= mx: t[l+1][vs+1][i][i] += t[l][vs][mx][lst] c+=1 #print('l: {}, vs: {}, m: {}, lst: {}, c: {}'.format(l, vs, mx, lst, c)) ans = 0 for i in t[-1]: for j in i: for k in j: ans += k print(ans)

[ "zaber.eng@gmail.com" ]

zaber.eng@gmail.com

8e2fa93b471ea7b39d26ee5e82734a1cfc35e3eb

e5b224b9f2be43500271349d96ab8bf92824d55e

/0523/selc04.py

997979d0f6fe9c5a3515c21dae2cc1ef4a972b11

[]

no_license

byunwonju/2020_programming

c28f914dcffe7d74b7cbc5923197481410287cd1

3e0bec7b30ca7d2f90b557e0b78a9cb8734ed617

refs/heads/master

2022-11-18T05:33:45.577071

2020-07-25T02:46:02

256,646,439

0

null

UTF-8

Python

false

122

py

num = int(input("정수 입력:")) if num%2 ==0: print("짝수입니다.") else: print("홀수입니다.")

[ "noreply@github.com" ]

byunwonju.noreply@github.com

5550bfec020aeb4768c5366f4bf1d82e1c1d4201

e98e10df36810879d05cde11c5846dafafafdd76

/from_one_to_ten.py

0d513618ab437314f99fd0b2ba72fd117691615f

[]

no_license

wojtekidd/Python101

99fb576e5a0bc33a86b299adbebf238fca01b12c

abb0fdb1bc2582139b6f84eb1ba6be8095d0a050

refs/heads/master

2022-04-06T12:46:05.370984

2020-02-16T13:02:00

207,164,195

0

null

UTF-8

Python

false

274

py

from random import randint user_number = int(input("Give me a number from 1 to 10: ")) comp_number = randint(1,10) while True: if user_number == comp_number: print("You win!") else: print(f"You loose! Computer has chosen {comp_number}") break

[ "wojtek@Wojteks-MacBook-Air.local" ]

wojtek@Wojteks-MacBook-Air.local

630ded532beaa7555113b8688e55a536d630fc5b

9e97741db42ec8a71e6f3d28c1a389fd129083f0

/zipf.py

e686a0c51a0eef30cffb262fcb561cdb745ed2eb

[]

no_license

MatthewWolff/NLP_Genomics

1ad04fc74a8b5cb64bd6181e75963448658ededc

febe99cc6b86c0fc047073a1ca02f25cffb61413

refs/heads/master

2020-03-18T00:21:52.531282

2018-08-11T02:11:32

134,090,188

0

null

UTF-8

Python

false

6,466

py

def rep(x, y): # too lazy to go through and change R code + regex was being wonky -> 'rep$"([A-Z])", {1}([0-9])$' return list(x * y) codons = ["GCU", "GCC", "GCA", "GCG", "CGU", "CGC", "CGA", "CGG", "AGA", "AGG", "AAU", "AAC", "GAU", "GAC", "UGU", "UGC", "CAA", "CAG", "GAA", "GAG", "GGU", "GGC", "GGA", "GGG", "CAU", "CAC", "AUU", "AUC", "AUA", "UUA", "UUG", "CUU", "CUC", "CUA", "CUG", "AAA", "AAG", "AUG", "UUU", "UUC", "CCU", "CCC", "CCA", "CCG", "UCU", "UCC", "UCA", "UCG", "AGU", "AGC", "ACU", "ACC", "ACA", "ACG", "UGG", "UAU", "UAC", "GUU", "GUC", "GUA", "GUG", "UAA", "UGA", "UAG"] # 64 codons amino_acids = [item for sublist in # flatten this boi into a list of 64 amino acids 1-letter abbreviations [rep("A", 4), rep("R", 6), rep("N", 2), rep("D", 2), rep("C", 2), rep("Q", 2), rep("E", 2), rep("G", 4), rep("H", 2), rep("I", 3), rep("L", 6), rep("K", 2), rep("M", 1), rep("F", 2), rep("P", 4), rep("S", 6), rep("T", 4), rep("W", 1), rep("Y", 2), rep("V", 4), rep("*", 3)] for item in sublist] codon_table = dict((k, v) for k, v in zip(codons, amino_acids)) def translate(nucleotides): """ Translates DNA to RNA :param nucleotides: the DNA sequence :return: an RNA sequence """ nucleotides = nucleotides.replace("C", "X") nucleotides = nucleotides.replace("G", "C") nucleotides = nucleotides.replace("A", "U") nucleotides = nucleotides.replace("T", "A") nucleotides = nucleotides.replace("X", "G") return nucleotides.strip() # newline removal def ribosome(nucleotides, simplify): """ Attempts to translate a nucleotide sequence, but :param nucleotides: a DNA nucleotide sequence :param simplify: if true, when a sequence isn't a multiple of 3, it will condense codons into a proetin :return: either a RNA sequence or a protein sequence """ if len(nucleotides) % 3 == 0: return "".join([codon_table[nucleotides[i:i + 3]] for i in range(0, len(nucleotides), 3)]) else: if simplify: usable_length = len(nucleotides) - (len(nucleotides) % 3) print nucleotides return "".join([codon_table[nucleotides[i:i + 3]] for i in range(0, usable_length, 3)]) + \ nucleotides[-(len(nucleotides) % 3):] else: return nucleotides def unit_generator(input_file, size, simplify): """ Returns a semantic unit of a given size. Multiples of 3 will be protein sequences :param input_file: the location of the file that contains the sequence to be digested :param size: the size in nucleotides of the desired genetic unit :param simplify: if true, when a sequence isn't a multiple of 3, it will condense codons into a protein :return: a generator to supply genetic units from the sequence """ if size < 1 or int(size) != size: raise ValueError("Size must be positive integer") with open(input_file) as f: curr = f.read(size) while curr is not None: # gradually read whole sequence in chunks of a specified size seq = translate(curr) yield ribosome(seq, simplify) curr = f.read(size) def make_frequency_table(generator): """ Creates a table of the frequencies of certain sized chunks in a genome :param input_file: the location of the file that contains the sequence to be digested :param size: the size in nucleotides of the desired genetic unit :param simplify: if true, when a sequence isn't a multiple of 3, it will condense codons into a protein :return: a dictionary containing the table of frequencies """ gen = generator # default for straight DNA sequence freq_table = dict() unit = next(gen) counter = 0 while unit is not "": # form table from units if unit not in freq_table: freq_table[unit] = 0 freq_table[unit] += 1 unit = next(gen) counter += 1 s_t = sorted([(k, v) for k, v in freq_table.items()], key=lambda x: x[1], reverse=True) # sort by freq, descending return s_t, counter ########################################################################################### ## DNA SEQUENCE # frequencies = [make_frequency_table(unit_generator(input_file="nucs.fasta", size=siz, simplify=True)) for siz in sizes] # PROTEIN SEQUENCE input_file = "/Users/matthew/protein.fa" with open(input_file) as f: body = f.readlines() amino_acids = [] for line in body: if ">" in line: continue amino_acids.append(line.strip()) amino_acids = "".join(amino_acids) size = 4 # 4 amino acids freq_table = dict() counter = 0 for s in range(size): for i in range(0, len(amino_acids), size): # form table from units unit = amino_acids[i:i + size] if unit not in freq_table: freq_table[unit] = 0 freq_table[unit] += 1 counter += 1 frequencies = [sorted([(k, v) for k, v in freq_table.items()], key=lambda x: x[1], reverse=True)] # sort by descending with open("zipf.freq.txt", "wb") as o: # write frequencies to a file for y in frequencies[0]: o.write("{}\n".format(y[1])) ### RNA SEQUENCE # input_file = "rna.fa" # with open(input_file) as f: # body = f.readlines() # dna = [] # for line in body: # if ">" in line: # continue # dna.append(line.strip()) # amino_acids = ribosome(translate("".join(dna)), simplify=True) # print amino_acids[:20] # size = 4 # freq_table = dict() # counter = 0 # for s in range(size): # for i in range(0, len(amino_acids), size): # form table from units # unit = amino_acids[i:i + size] # if unit not in freq_table: # freq_table[unit] = 0 # freq_table[unit] += 1 # counter += 1 # frequencies = [sorted([(k, v) for k, v in freq_table.items()], key=lambda x: x[1], reverse=True)] # sort by descending for table in frequencies: # write zipf enumeration to a file rel_freq = list(map(lambda t: float(t[1]) / float(counter), table)) top_entry = rel_freq[0] zipf = list(map(lambda f: (f / top_entry) ** -1, rel_freq)) # pritn first 100 to 200 entries for each step in teh calculation print("table:", table[:100]) print("relative frequency:", rel_freq[:100]) print("zipf:", zipf[:200]) with open("zipf", "wb") as o: for y in zipf: o.write("{}\n".format(y))

[ "noreply@github.com" ]

MatthewWolff.noreply@github.com

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fdf5d76af2b8f4a9dc08af2ec8ed69ce7e063be4

/data_20210601.py

b6098affe8e4329409061d6080797aeeadb412e0

[]

no_license

tone0623/IQA-System

262ef66a4f1dc4b57bb794386139a24167a70990

51742c325f0a27642f3168a41a1465c7406fe4a1

refs/heads/main

2023-06-12T15:55:25.552257

2021-07-05T02:02:51

382,509,758

0

null

UTF-8

Python

false

12,020

py

#!/usr/bin/env python # -*- coding: utf-8 -*- from __future__ import absolute_import import math import joblib import glob import re import matplotlib.pyplot as plt import cv2 import numpy as np import numpy.random as rd from settings_20210601 import settings import os #コントラスト類似度計算 import contrastSimilarity as cont #ヒストグラム平坦化 import histgramEqualize as hist import difference as diff Number_of_images = 30 # ------------------------------------------- # Load pkl files or ".jpg" & ".csv" files # ------------------------------------------- def data_loader(mode='train', mask_out=False): """ Read wav files or Load pkl files """ ## Sort function for file name def numericalSort(value): numbers = re.compile(r'(\d+)') parts = numbers.split(value) parts[1::2] = map(int, parts[1::2]) return parts # Load settings args = settings() # Make folder if not os.path.exists(args.model_save_path): # Folder of model os.makedirs(args.model_save_path) if not os.path.exists(args.pkl_path): # Folder of train pkl os.makedirs(args.pkl_path) ex = "bmp" # File name if mode=='test': image_names = args.test_data_path + '/*.' + "png" eval_names = args.test_data_path + '/*.txt' pkl_image = args.pkl_path + '/test_image.pkl' pkl_eval = args.pkl_path + '/test_eval.pkl' pkl_mask = args.pkl_path + '/test_mask.pkl' pkl_target_image = args.pkl_path + '/target_image.pkl' pkl_target_mask = args.pkl_path + '/target_mask.pkl' mask_names = args.test_mask_path + '/*.' + "png" Number_of_images = args.test_data_num target_image_names = args.target_data_path + '/*.' + "bmp" target_mask_names = args.target_mask_path + '/*.' + "bmp" elif mode == 'eval': image_names = args.eval_data_path + '/*.' + "bmp" eval_names = args.eval_data_path + '/*.txt' pkl_image = args.pkl_path + '/eval_image.pkl' pkl_eval = args.pkl_path + '/eval_eval.pkl' pkl_mask = args.pkl_path + '/eval_mask.pkl' pkl_target_image = args.pkl_path + '/target_image.pkl' pkl_target_mask = args.pkl_path + '/target_mask.pkl' mask_names = args.eval_mask_path + '/*.' + "bmp" Number_of_images = args.eval_data_num target_image_names = args.target_data_path + '/*.' + "bmp" target_mask_names = args.target_mask_path + '/*.' + "bmp" else: image_names = args.train_data_path + '/*.' + "png" #すべてのtrainBMPファイルを読み込み eval_names = args.train_data_path + '/*.txt' #すべてのtraintxtファイルを読み込み pkl_image = args.pkl_path + '/train_image.pkl' pkl_eval = args.pkl_path + '/train_eval.pkl' pkl_mask = args.pkl_path + '/train_mask.pkl' pkl_target_image = args.pkl_path + '/target_image.pkl' pkl_target_mask = args.pkl_path + '/target_mask.pkl' mask_names = args.train_mask_path + '/*.' + "png" Number_of_images = args.train_data_num target_image_names = args.target_data_path + '/*.' + "bmp" target_mask_names = args.target_mask_path + '/*.' + "bmp" image_data = [] mask_data = [] target_image_data = [] target_mask_data = [] similarity = [] ## ~~~~~~~~~~~~~~~~~~~ ## No pkl files ## -> Read images & assesment values, and Create pkl files ## ~~~~~~~~~~~~~~~~~~~ if not (os.access(pkl_image, os.F_OK) and os.access(pkl_eval, os.F_OK) and os.access(pkl_mask, os.F_OK)): ## Read Image files print(' Load bmp file...') # Get image data for image_file in sorted(glob.glob(image_names), key=numericalSort): img = cv2.imread(image_file) #image_data.append(img.transpose(2,0,1)) image_data.append(img) #image_data = np.array(image_data) # Get evaluation data eval_data = [] for imgage_file in sorted(glob.glob(eval_names), key=numericalSort): eval_data = np.expand_dims(np.loadtxt(glob.glob(eval_names)[0], delimiter=',', dtype='float'), axis=1) for mask_file in sorted(glob.glob(mask_names), key=numericalSort): mask = cv2.imread(mask_file) #mask_data.append(mask.transpose(2, 0, 1)) mask_data.append(mask) #mask_data = np.array(mask_data) for target_image_file in sorted(glob.glob(target_image_names), key=numericalSort): mask = cv2.imread(target_image_file) #mask_data.append(mask.transpose(2, 0, 1)) target_image_data.append(mask) for target_mask_file in sorted(glob.glob(target_mask_names), key=numericalSort): mask = cv2.imread(target_mask_file) #mask_data.append(mask.transpose(2, 0, 1)) target_mask_data.append(mask) ## Create Pkl files print(' Create Pkl file...') with open(pkl_image, 'wb') as f: # Create clean pkl file joblib.dump(image_data, f, protocol=-1, compress=3) with open(pkl_eval, 'wb') as f: # Create noisy pkl file joblib.dump(eval_data, f, protocol=-1, compress=3) with open(pkl_mask, 'wb') as f: # Create clean pkl file joblib.dump(mask_data, f, protocol=-1, compress=3) with open(pkl_target_image, 'wb') as f: # Create clean pkl file joblib.dump(target_image_data, f, protocol=-1, compress=3) with open(pkl_target_mask, 'wb') as f: # Create clean pkl file joblib.dump(target_mask_data, f, protocol=-1, compress=3) else: #pklファイルの読み込み #if test == False: #train_pkl with open(pkl_image, 'rb') as f: # Load image pkl file print(' Load Image Pkl...') image_data = joblib.load(f) with open(pkl_eval, 'rb') as f: # Load evaluation pkl file print(' Load Evaluation Pkl...') eval_data = joblib.load(f) with open(pkl_mask, 'rb') as f: # Load image pkl file print(' Load Mask Pkl...') mask_data = joblib.load(f) with open(pkl_target_image, 'rb') as f: # Load image pkl file print(' Load Target Image Pkl...') target_image_data = joblib.load(f) with open(pkl_target_mask, 'rb') as f: # Load image pkl file print(' Load Target Mask Pkl...') target_mask_data = joblib.load(f) #マスクとのコントラスト類似度を取得　(画像枚数,3) & ヒストグラム平坦化 histimg = [] histmask = [] for i in range(Number_of_images): img1 = image_data[i] img2 = mask_data[i] similarity.append(cont.contrastSimilarity(img1, img2)) histimg.append(hist.histgramEqualize(img1)) histmask.append(hist.histgramEqualize(img2)) similarity = np.array(similarity) histimg = np.array(histimg) histmask = np.array(histmask) #差分画像のRGBごとの分散を取得 variance = [] for i in range(Number_of_images): img1 = histimg[i] img2 = histmask[i] variance.append(diff.variance(img1, img2)) variance = np.array(variance) # a = similarity[:, 0] # print(min(a)) # n, bins, patches = plt.hist(a) # plt.xlabel("Values") # plt.ylabel("Frequency") # plt.title("Histogram") # plt.show() #varianceの型がおかしい #劣化画像とマスク画像を結合(Number_of_images, 6, 128, 128) #image_data = np.concatenate((histimg.transpose(0,3,1,2), histmask.transpose(0,3,1,2)), axis=1) image_data = histimg.transpose(0,3,1,2) mask_data = histmask.transpose(0,3,1,2) target_image_data = np.array(target_image_data).transpose(0, 3, 1, 2) target_mask_data = np.array(target_mask_data).transpose(0, 3, 1, 2) if not mask_out: return image_data, eval_data, similarity, variance, target_image_data, target_mask_data if mask_out: return image_data, mask_data, eval_data, similarity, variance, target_image_data, target_mask_data class create_batch: """ Creating Batch Data for training """ ## Initialization # def __init__(self, image, mos, sim, var, batches, test=False): def __init__(self, image, mos, sim, var, batches, test=False): # Data Shaping #.copyで値渡しを行う => 代入だと参照渡しになってしまう self.image = image.copy() self.mos = mos.copy() self.sim = sim.copy() self.var = var.copy() # Random index ( for data scrambling) ind = np.array(range(self.image.shape[0])) if not test: rd.shuffle(ind) # Parameters self.i = 0 self.batch = batches self.iter_n = math.ceil(self.image.shape[0] / batches) # Batch num for each 1 Epoch remain = self.iter_n * batches - self.image.shape[0] self.rnd = np.r_[ind, np.random.choice(ind, remain)] # Reuse beggining of data when not enough data def shuffle(self): self.i = 0 rd.shuffle(self.rnd) def __iter__(self): return self def __len__(self): return self.iter_n ## Pop batch data def __next__(self): self.test = False index = self.rnd[self.i * self.batch: (self.i + 1) * self.batch] # Index of extracting data self.i += 1 if not self.test: return self.image[index], self.mos[index], self.sim[index], self.var[index] # Image & MOS else: return self.image[index], self.sim[index], self.var[index] # Image class create_batch_w_mask(create_batch): def __init__(self, image_s, mask_s, mos, sim, var, image_t, mask_t, batches, test=False): super(create_batch_w_mask, self).__init__(image_s, mos, sim, var, batches, test) self.mask = mask_s self.image_t = image_t self.mask_t = mask_t ind_s = np.array(range(self.image.shape[0])) ind_t = np.array(range(self.image_t.shape[0])) self.iter_n = math.ceil(self.image.shape[0] / batches) # Batch num for each 1 Epoch loop_num_s =math.ceil(self.iter_n * batches / image_s.shape[0]) loop_num_t = math.ceil(self.iter_n * batches / image_t.shape[0]) red_s = [] red_t = [] if not test: for i in range(loop_num_s): red_s.extend(rd.permutation(ind_s)) for i in range(loop_num_t): red_t.extend(rd.permutation(ind_t)) else: for i in range(loop_num_s): red_s.extend(ind_s) for i in range(loop_num_t): red_t.extend(ind_t) rnd_s = red_s[:self.iter_n * batches] rnd_t = red_t[:self.iter_n * batches] self.rnd_s = np.array(rnd_s) self.rnd_t = np.array(rnd_t) print('OK') def __next__(self): self.test = False index_s = self.rnd_s[self.i * self.batch: (self.i + 1) * self.batch] # Index of extracting data index_t = self.rnd_t[self.i * self.batch: (self.i + 1) * self.batch] # Index of extracting data self.i += 1 if not self.test: return self.image[index_s], self.mask[index_s], self.mos[index_s], self.sim[index_s], self.var[index_s], index_s, self.image_t[index_t], self.mask_t[index_t] # Image & MOS else: return self.image[index_s], self.mask[index_s], self.mos[index_s], self.sim[index_s], self.var[index_s], index_s # Image

[ "tone0623@icloud.com" ]

tone0623@icloud.com

21498c9b54373452b5aa80042dafbd03aaedf1f0

1682819d41445adf38f39591cc57b9af9b1e0dcf

/layer.py

bbf33d03495edc36b8a4e670132b4b2694cba649

[]

no_license

favalon/ZoomMovies

268a5490ddcc40fbf6e4ac3bae1d53c32b826383

b8f68a2a5186a074032bf7f3e746951bfde004c3

refs/heads/master

2021-01-03T00:58:36.465200

2020-02-11T21:30:21

239,847,897

0

null

UTF-8

Python

false

20,021

py

''' Created on Dec, 2018 @author: Zixiao Yu ''' import os import json import numpy import csv ''' Input files: movies800.json, reverseDict.json. Output files: output is 3 json files(layer1, layer2, layer3) in following format: not filter: All_final_layerindex with filters 1. genre_final_layerindex 2. agedown_to_ageup_layerindex Obtain the Input files from @Jian. Ask @Jian how to set up and the upload the output json files to S3 service. cluster_l1 and cluster_l2 is per-defined by @Fiona and @Di. if they change it, the cluster and tags name in these two need modify. ''' score_dict = {} #--------------initial parameter-------------- pirority_weight = 1 release_weight = 1 promotion_weight = 1 starRating_weight = 1 cluster_l1 =[["animal"], ["superhero", "star war"], ["magic and fantasy characters"], ["robots","vehicles","toys","foods","sports",], ["ordinary people"], ["alien", "space"],["monster", "ghost", "vampire"], ["princess", "prince", "queen", "king", "fairy", "elf", "mermaid", "smurf","snowman"]] cluster_l2 = ["PG-13 & LA", "PG & LA", "PG-13 & Animation", "PG & Animation"] tag2group = {} # # layer_min_cluster = 1 # l1_max_tags=0 # l2_max_tags=0 # l3_max_tags=0 # # l1_min_coverage = 0 l2_min_coverage = 0.99 # l3_min_coverage = 0 # # l1_single_max_coverage = 0 l2_single_max_coverage = 1 # l3_single_max_coverage = 0 # setting_flag = 2 # # if setting_flag == 1: # genre_name = 'ALL' # elif setting_flag ==2: # genre_filter = ['music', 'musician', 'musical','Musical','Music','Musician'] # genre_name = 'Music' # elif setting_flag ==3: # genre_filter = ['family'] # genre_name = 'Family' # elif setting_flag ==4: # genre_filter = ['action/adventure'] # genre_name = 'Adventure' # elif setting_flag ==5: # genre_filter = ['comedy'] # genre_name = 'Comedy' # else: # print('Error') #--------------initial end------------------- class movie(): ''' movie class id: movie id releaseData: movie release year startRating: movie Rating mainCharacter: movie main Character secCharacter : movie second Character genre: movie genres ageRange: movie age range isAnimate: the movie is animation or not isAge13 : is this movie recommend watching age under 13 layer2Cluster: movie Cluster name for layer2 in map (PG is under 13, PG-13 is above 13, Animation is animation, LA is Liveaction) promotion: movie have promotion score tag: all movie tags, include metadata from rovi + TCL manual data (manual tags need to extend by current manual tag parent tags and children tags) tags: the tag socre for each tag, main Character( and it's parents tags) score is 2, second Character score (and its' parents tags) is 1 get_score: calculate movie score under current cluster get_score_split: a help function to split the score ''' def __init__(self, data): self.id = data['id'] self.releaseDate = int(data['releasedDate']) self.starRating = int(round(float(data['starRating']))) self.mainCharacter = data['mainCharacter'] self.secCharacter = data['secondaryCharacter'] self.genre = data['tag'] self.ageRange = data['ageRange'] self.isAnimate = data["isAnimated"] self.isAge13 = data["age13"] #self.isAge13 = True # only use for test------------------------------------------------------------------------------ self.layer2Cluter = ("PG-13" if self.isAge13 else "PG" )+" & "+ ( "Animation" if self.isAnimate else "LA") if 'promotion' not in data: self.promotion = 0 else: self.promotion = data['promotion'] self.tag = data['tag']+self.mainCharacter+self.secCharacter for group_tag in self.mainCharacter: if group_tag in tag2group: self.tag += tag2group[group_tag] for group_tag in self.secCharacter: if group_tag in tag2group: self.tag += tag2group[group_tag] self.tag = list(set(self.tag)) self.tags={} #manual tags need to be extended by current manual tag's parent tags and children tags, use reverse_dict to find them for tag in self.tag: group = [] if tag in self.mainCharacter: self.tags[tag]=2 if tag in tag2group: for group_tag in tag2group[tag]: self.tags[group_tag] = 2 elif tag in self.secCharacter: self.tags[tag]= 1 if tag in tag2group: for group_tag in tag2group[tag]: if group_tag in self.tags and self.tags[group_tag] == 2: continue else: self.tags[group_tag] = 1 elif tag in self.tags: continue else: self.tags[tag]=0 self.filters = self.tag def get_score(self, clusters_name): ''' get the movie score in current cluster, score = w1*tags_score + w2*release_score + w3*rating_score + w4*promotion_score :param clusters_name: :return: score ''' score = 0 for cluster_name in clusters_name: if cluster_name not in self.tags: return score score_new = pirority_weight * self.tags[cluster_name] + release_weight * release_score(self.releaseDate)\ + starRating_weight * self.starRating+promotion_weight*self.promotion if cluster_name == self.mainCharacter and len(self.mainCharacter)>1: score_new -=1 score = max(score_new, score) return score def get_score_split(self, clusters_name): ''' get movie score in current cluster and get score in separate format for score evaluation. :param clusters_name: :return: score ''' character_score = 0 releasedate_score = 0 starRating_score = 0 total_score = 0 score_old = 0 score = [character_score,releasedate_score,starRating_score,total_score] for cluster_name in clusters_name: if cluster_name not in self.tags: score_new = -1 else: score_new = pirority_weight * self.tags[cluster_name] + release_weight * release_score(self.releaseDate)\ + starRating_weight * self.starRating+promotion_weight*self.promotion if cluster_name == self.mainCharacter and len(self.mainCharacter)>1: score_new -=1 if score_new > score_old: character_score = pirority_weight*self.tags[cluster_name] releasedate_score = release_score(self.releaseDate) starRating_score = starRating_weight * self.starRating total_score = character_score + releasedate_score+starRating_score score = "%f:%f:%f:%f" % (character_score,releasedate_score,starRating_score,total_score) score_old = max(score_new, score_old) return score,total_score def release_score(releaseDate): ''' :param releaseDate: :return: release data relative score ''' score = 0 if releaseDate > 2016: score =5 elif 2016>= releaseDate >2014: score =3 elif 2014 >= releaseDate >2010: score = 2 elif 2010 >= releaseDate > 2000: score = 1 else: score = 0 return score def file_read(filename, reverse_tag_dict): ''' load movies json data and reverse dict the reverse_tag_dict is use to find the parents/children tags for current manual tag :param filename: movies json data location :param reverse_tag_dict: :return: data and reverse_dict ''' with open (filename) as f: data = json.load(f) with open (reverse_tag_dict) as f: reverse_dict = json.load(f) return data, reverse_dict def data_initialize(data, reverse_dict_raw): ''' initial the movies by using movie class :param data: movies json data :param reverse_dict_raw: :return: movies ''' for key in reverse_dict_raw: tag2group[key] = reverse_dict_raw[key] movies = [] for key in data: movies.append(movie(data[key])) return movies def movies_filter(movies, filter_tags, filter_age_up= None, filter_age_down = None ): ''' get movie after filtered :param movies: all movies :param filter_tags: the movie with these tags will be keep :param filter_age_up: :param filter_age_down: :return: movies after filtered ''' result = [] if filter_tags ==None and filter_age_up != None: for movie in movies: if filter_age_down<=movie.ageRange <=filter_age_up: result.append(movie) else: continue elif filter_age_up != None and filter_tags != None: for movie in movies: for tag in filter_tags: if tag in movie.filters and filter_age_down<=movie.ageRange <=filter_age_up: result.append(movie) else: continue else: for movie in movies: for tag in filter_tags: if tag in movie.filters: result.append(movie) else: continue return result #--------------data convert end---------------------------- def layer_1_ranking(movies): ''' :param movies: :return: the layer 1 movies ranking under cluster name ''' results = {} for cluster_name in cluster_l1: str ='-' results[str.join(cluster_name)] = sort_layer(get_layer_1_ranking(movies, cluster_name), cluster_name) return results def get_layer_1_ranking(movies, clusters_name): ''' a help function for ranking :param movies: :param clusters_name: :return: ''' results = [] for cluster_name in clusters_name: for movie in movies : if cluster_name in movie.tags and movie not in results: results.append(movie) return results def sort_layer(movies, cluster_name): ''' sort movies in current cluster by using movies score :param movies: :param cluster_name: sort movie by current cluster name :return: sorted movies ''' cur_cluster_score_list = {} cur_dict = {} for movie in movies: score_split, total_score = movie.get_score_split(cluster_name) cur_cluster_score_list[movie.id] = [total_score, score_split] cur_cluster_score_list = sorted(cur_cluster_score_list.items(), key=lambda kv: kv[1][0], reverse= True) for cur in cur_cluster_score_list: cur_dict[cur[0]] = cur[1] if not score_dict.__contains__('-'.join(cluster_name)): score_dict['-'.join(cluster_name)] = cur_dict else: prv_cur_dict = score_dict[''.join(cluster_name)] cur_dict = Merge(prv_cur_dict,cur_dict) score_dict['-'.join(cluster_name)] = cur_dict return sorted(movies, key = lambda movie:movie.get_score(cluster_name),reverse=True) def Merge(dict1, dict2): # merge two dict res = {**dict1, **dict2} return res def my_rank(dict): for key in dict: value = dict[key][0] return value def layer_next_cluster(movies, parentTag): ''' Calculate the next layer cluster name and put the movie into these cluster Currently only use in layer 3 function example: 1. 100 movies have a same parentTag P. 2. get all the tags used by this 100 movies, tag_pool = [t1, t2, t3 ....] 3. 50 movies have t1, 48 movies have t2, 45 movies have t3 ...., no tn shared by more than 50 movies( t1 has the most share rate) 4. use 3 tags in tag_pool can get coverage rate more than l2_single_max_coverage then use this 3 tags for next layer clusters. coverage rate = (movies have these tags/ all movies) :param movies: current processing movies :param parentTag: the upper layer tag of current processing movies :return: ''' tags_pool = {} for movie in movies: for tag in movie.tags: if parentTag.__contains__(tag): continue elif tag not in tags_pool: tags_pool[tag] = 1 else: tags_pool[tag] = tags_pool[tag]+1 for tag in list(tags_pool): if layer_tag_converage(tags_pool[tag],len(movies)) > l2_single_max_coverage: tags_pool.pop(tag,None) result = get_next_cluster(tags_pool,movies) return result def layer_l2_cluster(movies): ''' put the movie into 4 different layer 2 clusters :param movies: :return: 4 different layer 2 clusters results ''' results = {} result_PG_Ani =[] result_PG_LA = [] result_PG13_Ani =[] result13_PG_LA = [] #"PG-13 & LA", "PG & LA", "PG-13 & Animation", "PG & Animation" for movie in movies: if movie.layer2Cluter == cluster_l2[0]: result13_PG_LA.append(movie) elif movie.layer2Cluter == cluster_l2[1]: result_PG_LA.append(movie) elif movie.layer2Cluter == cluster_l2[2]: result_PG13_Ani.append(movie) elif movie.layer2Cluter == cluster_l2[3]: result_PG_Ani.append(movie) else: continue results[cluster_l2[0]] = result13_PG_LA results[cluster_l2[1]] = result_PG_LA results[cluster_l2[2]] = result_PG13_Ani results[cluster_l2[3]] = result_PG_Ani return results def layer_tag_converage(cur_movies_number,len_movie): coverage = cur_movies_number/(len_movie) return coverage def get_next_cluster(tags,movies): ''' similar to layer_next_cluster :param tags: :param movies: :return: ''' cur_movie = {} cluster_movies_numbers = len(movies) next_all_cluster = {} next_cluster = [] sort_tags=sorted(tags.items(), key = lambda kv:kv[1], reverse=True) for tag in sort_tags: cur_cluster_movies = [] for movie in movies: if tag[0] in movie.tags: if movie not in cur_movie: cur_movie[movie] = 1 cur_cluster_movies.append(movie) next_all_cluster[tag[0]] = sort_layer(cur_cluster_movies,[tag[0]]) cur_moveies_numbers = len(cur_movie) next_cluster.append(tag) if (cur_moveies_numbers/ cluster_movies_numbers) > l2_min_coverage and len(next_all_cluster) > layer_min_cluster: break return next_all_cluster # initial movies data and reverse dict movies_raw, reverse_dict_raw=file_read("movie800.json", "reverseDict.json") movies=data_initialize(movies_raw, reverse_dict_raw) #use movie filter setting_flag = 1 age_down = 3 age_up = 5 if setting_flag == 1: genre_name = 'ALL' elif setting_flag ==2: genre_filter = ['music', 'musician', 'musical','Musical','Music','Musician'] genre_name = 'Music' elif setting_flag ==3: genre_filter = ['family'] genre_name = 'Family' elif setting_flag ==4: genre_filter = ['action/adventure'] genre_name = 'Adventure' elif setting_flag ==5: genre_filter = ['comedy'] genre_name = 'Comedy' else: print('Error') if setting_flag != 1: movies = movies_filter(movies, genre_filter,filter_age_up=age_up,filter_age_down=age_down) if age_up != None and setting_flag == 1: movies = movies_filter(movies, None, filter_age_up=age_up,filter_age_down=age_down) genre_name = str(age_down) + 'to' +str(age_up) #get layer 1 l1=layer_1_ranking(movies) results_l2 = {} results_l3 = {} # get layer 2 for cluster in l1: results_l2[cluster] = layer_l2_cluster(l1[cluster]) # get layer 3 for l1_tag in results_l2: parent = l1_tag.split("-") result_l3_part = {} for age_tage in results_l2[l1_tag]: result_l3_part[l1_tag +"+"+ age_tage] = layer_next_cluster(results_l2[l1_tag][age_tage], parent) results_l3[l1_tag] = result_l3_part print("end") # results_l2 = {} # result_l3 = {} # # for key in l1: # parent = [] # parent.append(key) # results_l2[key] = layer_next_cluster(l1[key], parent) # #results_l2.append(layer_next_cluster(l1[key], parent)) # # for tag_l1 in results_l2: # parent = [] # parent.append(tag_l1) # result_l3_part = {} # for tag_l2 in results_l2[tag_l1]: # parent.append(tag_l2) # result_l3_part[tag_l1+"-"+tag_l2] = layer_next_cluster(results_l2[tag_l1][tag_l2], parent) # result_l3[tag_l1] = result_l3_part # print(1) # final_l1 = {} final_l2 = {} final_l3 = {} # use pool to prevent movies repetition in layer 1 and layer 2 final_l1_pool = [] final_l2_pool = [] final_l1_count = {} final_l2_count = {} final_l3_count = {} final_l1_pool_correct = {} #get final layer 1 for cluster in l1: l1_part = [] l1_part_8 = [] count = 0 for movie in l1[cluster]: if movie.id in final_l1_pool: continue if count < 8: final_l1_pool.append(movie.id) l1_part_8.append(movie.id) count+=1 l1_part.append(movie.id) final_l1_pool_correct[cluster] = l1_part_8 final_l1[cluster]=l1_part final_l1_count[cluster] = count #get final layer 2 for cluster_1 in results_l2: skip_list = [] for cluster in final_l1_pool_correct: if cluster == cluster_1: continue for movie in final_l1_pool_correct[cluster]: skip_list.append(movie) for cluster_2 in results_l2[cluster_1]: l2_part = [] count = 0 for movie in results_l2[cluster_1][cluster_2]: if movie.id in final_l2_pool: continue if movie.id in skip_list: continue if count < 8: final_l2_pool.append(movie.id) count+=1 l2_part.append(movie.id) final_l2_count[cluster_1+"+"+cluster_2] = count final_l2[cluster_1+"+"+cluster_2] = l2_part # get final layer 3 for cluster_1 in results_l3: final_l3_pool = [] for cluster_2 in results_l3[cluster_1]: for cluster_3 in results_l3[cluster_1][cluster_2]: count = 0 l3_part = [] for movie in results_l3[cluster_1][cluster_2][cluster_3]: if movie.id in final_l3_pool: continue if count < 800: final_l3_pool.append(movie.id) count+=1 l3_part.append(movie.id) final_l3_count[cluster_2+"+"+cluster_3] = count final_l3[cluster_2+"+"+cluster_3] = l3_part if results_l3[cluster_1][cluster_2].__len__() == 0: final_l3_count[cluster_2+"+"+"none"] = count final_l3[cluster_2+"+"+"none"] = "" #store the score file in json file with open('score_dict.json','w')as f: json.dump(score_dict,f,indent=1, sort_keys=True) # store the result in json file result_l1 = json.dumps(list(final_l1.items())) result_l2 = json.dumps(list(final_l2.items())) result_l3 = json.dumps(list(final_l3.items())) with open(genre_name+'_final_l1.json','w+') as outfile: json.dump(final_l1,outfile,indent=4) #print(result_l1) with open(genre_name+'_final_l2.json','w+') as outfile: json.dump(final_l2,outfile,indent=4) with open(genre_name+'_final_l3.json','w+') as outfile: json.dump(final_l3,outfile,indent=4) # with open(genre_name+'_final_l1_count.json','w+') as outfile: # json.dump(final_l1_count,outfile,indent=4) # #print(result_l1) # # with open(genre_name+'_final_l2_count.json','w+') as outfile: # json.dump(final_l2_count,outfile,indent=4) # # with open(genre_name+'_final_l3_count.json','w+') as outfile: # json.dump(final_l3_count,outfile,indent=4) #print(result_l1)

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#!/usr/bin/env python # -*- coding: utf-8 -*- """ @Time :2019-04-23 下午 2:33 @Author : 罗林 @File : loginAction.py @desc : """ import requests import json from common.myConfig import ConfigUtils as conf from common.myCommon.Logger import getlog from common.myConfig import MysqlConfig as ms from common.mydb import MysqlClent User = 'fqhd001' Passwd = '5e81f67ed14a5443ec6a3682513f0b9b' mobile = '13699479886' app_passwd = 'll123456' DB = MysqlClent.get_conn('192.168.15.159', 3306, 'easyloan', 'easyloan', '78dk.com') web_URL = ms.get('easyloan_web_apiURL') app_URL = ms.get('easyloan_app_apiURL') LOGGER = getlog(__name__) API_TEST_HEADERS = {"Content-Type": "application/json"} rq = requests.Session() sign = conf.get('report', 'sign') def test_easyloan_web_login(): url = web_URL + '/api/78dk/web/login' querystring = json.dumps({"username": User, "password": Passwd}) response = rq.post(url, headers=API_TEST_HEADERS, data=querystring) LOGGER.info("token:【{}】".format(response.json()["data"]["token"])) return response.json()["data"]["token"] def test_easyloan_app_login(): url = app_URL + '/api/78dk/clientapp/login/pwLogin' querystring = json.dumps({"mobile": mobile, "password": app_passwd}) response = rq.post(url, headers=API_TEST_HEADERS, data=querystring) LOGGER.info("token:【{}】".format(response.json()["data"]["token"])) LOGGER.info(response.text) return response.json()["data"]["token"] def test_yygl_login(): pass if __name__ == '__main__': test_easyloan_app_login()

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# -*- coding: UTF-8 -*- ''' 题目：斐波那契数列。程序分析：斐波那契数列（Fibonacci sequence），又称黄金分割数列，指的是这样一个数列：0、1、1、2、3、5、8、13、21、34、……。在数学上，费波那契数列是以递归的方法来定义： F0 = 0 (n=0) F1 = 1 (n=1) Fn = F[n-1]+ F[n-2](n=>2) ''' def fib1(n): a,b = 1,1 for i in range(n-1): a,b = b,a+b return a # 输出了第10个斐波那契数列的数 print fib1(10) # 使用递归 def fib2(n): if n==1 or n==2: return 1 return fib2(n-1)+fib2(n-2) # 输出了第10个斐波那契数列的数 print fib2(10)

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import time from sklearn.feature_extraction.text import TfidfVectorizer from sklearn.preprocessing import Normalizer from sklearn.pipeline import make_pipeline from sklearn.feature_selection import SelectKBest from sklearn.metrics import accuracy_score from sklearn.model_selection import train_test_split from pa2b.aml_perceptron import Perceptron,SparsePerceptron # This function reads the corpus, returns a list of documents, and a list # of their corresponding polarity labels. def read_data(corpus_file): X = [] Y = [] with open(corpus_file, encoding='utf-8') as f: for line in f: _, y, _, x = line.split(maxsplit=3) X.append(x.strip()) Y.append(y) return X, Y if __name__ == '__main__': # Read all the documents. X, Y = read_data('data/all_sentiment_shuffled.txt') # Split into training and test parts. Xtrain, Xtest, Ytrain, Ytest = train_test_split(X, Y, test_size=0.2, random_state=0) # Set up the preprocessing steps and the classifier. pipeline = make_pipeline( TfidfVectorizer(), SelectKBest(k=1000), Normalizer(), # NB that this is our Perceptron, not sklearn.linear_model.Perceptron Perceptron() ) # Train the classifier. t0 = time.time() pipeline.fit(Xtrain, Ytrain) t1 = time.time() print('Training time: {:.2f} sec.'.format(t1-t0)) # Evaluate on the test set. Yguess = pipeline.predict(Xtest) print('Accuracy: {:.4f}.'.format(accuracy_score(Ytest, Yguess)))

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#!/usr/bin/env python3 # -*- coding: utf-8 -*- # # scrapenhl2 documentation build configuration file, created by # sphinx-quickstart on Sun Oct 1 17:47:07 2017. # # This file is execfile()d with the current directory set to its # containing dir. # # Note that not all possible configuration values are present in this # autogenerated file. # # All configuration values have a default; values that are commented out # serve to show the default. # If extensions (or modules to document with autodoc) are in another directory, # add these directories to sys.path here. If the directory is relative to the # documentation root, use os.path.abspath to make it absolute, like shown here. # import sys sys.path.insert(0, '../../') sys.path.insert(0, '../') sys.path.insert(0, './') sys.path.insert(0, '../../scrapenhl2/') sys.path.insert(0, '../../scrapenhl2/scrape/') sys.path.insert(0, '../../scrapenhl2/manipulate/') sys.path.insert(0, '../../scrapenhl2/plot/') # -- General configuration ------------------------------------------------ # If your documentation needs a minimal Sphinx version, state it here. # # needs_sphinx = '1.0' # Add any Sphinx extension module names here, as strings. They can be # extensions coming with Sphinx (named 'sphinx.ext.*') or your custom # ones. extensions = ['sphinx.ext.autodoc', 'sphinx.ext.todo'] # Add any paths that contain templates here, relative to this directory. templates_path = ['_templates'] # The suffix(es) of source filenames. # You can specify multiple suffix as a list of string: # # source_suffix = ['.rst', '.md'] source_suffix = '.rst' # The master toctree document. master_doc = 'index' # General information about the project. project = 'scrapenhl2' copyright = '2017, Muneeb Alam' author = 'Muneeb Alam' # The version info for the project you're documenting, acts as replacement for # |version| and |release|, also used in various other places throughout the # built documents. # # The short X.Y version. version = '0.4.1' # The full version, including alpha/beta/rc tags. release = version # The language for content autogenerated by Sphinx. Refer to documentation # for a list of supported languages. # # This is also used if you do content translation via gettext catalogs. # Usually you set "language" from the command line for these cases. language = None # List of patterns, relative to source directory, that match files and # directories to ignore when looking for source files. # This patterns also effect to html_static_path and html_extra_path exclude_patterns = [] # The name of the Pygments (syntax highlighting) style to use. pygments_style = 'sphinx' # If true, `todo` and `todoList` produce output, else they produce nothing. todo_include_todos = True # -- Options for HTML output ---------------------------------------------- # The theme to use for HTML and HTML Help pages. See the documentation for # a list of builtin themes. # html_theme = 'nature' # Theme options are theme-specific and customize the look and feel of a theme # further. For a list of options available for each theme, see the # documentation. # # html_theme_options = {} # Add any paths that contain custom static files (such as style sheets) here, # relative to this directory. They are copied after the builtin static files, # so a file named "default.css" will overwrite the builtin "default.css". html_static_path = ['_static'] # -- Options for HTMLHelp output ------------------------------------------ # Output file base name for HTML help builder. htmlhelp_basename = 'scrapenhl2doc' # -- Options for LaTeX output --------------------------------------------- latex_elements = { # The paper size ('letterpaper' or 'a4paper'). # # 'papersize': 'letterpaper', # The font size ('10pt', '11pt' or '12pt'). # # 'pointsize': '10pt', # Additional stuff for the LaTeX preamble. # # 'preamble': '', # Latex figure (float) alignment # # 'figure_align': 'htbp', } # Grouping the document tree into LaTeX files. List of tuples # (source start file, target name, title, # author, documentclass [howto, manual, or own class]). latex_documents = [ (master_doc, 'scrapenhl2.tex', 'scrapenhl2 Documentation', 'Muneeb Alam', 'manual'), ] # -- Options for manual page output --------------------------------------- # One entry per manual page. List of tuples # (source start file, name, description, authors, manual section). man_pages = [ (master_doc, 'scrapenhl2', 'scrapenhl2 Documentation', [author], 1) ] # -- Options for Texinfo output ------------------------------------------- # Grouping the document tree into Texinfo files. List of tuples # (source start file, target name, title, author, # dir menu entry, description, category) texinfo_documents = [ (master_doc, 'scrapenhl2', 'scrapenhl2 Documentation', author, 'scrapenhl2', 'One line description of project.', 'Miscellaneous'), ]

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# leetcode is premium problem # see https://www.geeksforgeeks.org/minimum-steps-reach-target-knight/ # https://www.hackerrank.com/challenges/knightl-on-chessboard/problem <-- slightly harder version of the same problem (SCROLL DOWN) # BFS class Cell: # don't have to use this, can just use a tuple also (x, y, dist) def __init__(self, x: int, y: int, dist: int): self.x = x self.y = y self.dist = dist from typing import Tuple from collections import deque class Solution: def inBoard(self, x: int, y: int) -> bool: return (0 <= x < 8) and (0 <= y < 8) def minKnightMoves(self, knight_pos: Tuple[int, int], target_pos: Tuple[int, int]) -> int: dirs = [ (1, 2), (2, 1), (-1, -2), (-2, -1), (-1, 2), (2, -1), (1, -2), (-2, 1) ] queue = deque() queue.append(Cell(knight_pos[0], knight_pos[1], 0)) visited = [[False] * 8 for _ in range(8)] visited[knight_pos[0]][knight_pos[1]] = True while queue: now = queue.popleft() if (now.x, now.y) == target_pos: return now.dist for i in range(8): next_x = now.x + dirs[i][0] next_y = now.y + dirs[i][1] if self.inBoard(next_x, next_y): if not visited[next_x][next_y]: visited[next_x][next_y] = True queue.append(Cell(next_x, next_y, now.dist + 1)) # https://www.hackerrank.com/challenges/knightl-on-chessboard/problem class Solution_hackerrank_mine_passall: def knightlOnAChessboard(self, n: int): out = [[0]*(n-1) for _ in range(n-1)] for i in range(1, n): for j in range(1, n): if out[j-1][i-1] != 0: # output array is symmetric out[i-1][j-1] = out[j-1][i-1] else: out[i-1][j-1] = makeMove(n, i, j) return out @staticmethod def inBoard(n: int, x: int, y: int) -> bool: return (0 <= x < n) and (0 <= y < n) @staticmethod def makeMove(n: int, a: int, b: int) -> int: dirs = [ (a, b), (b, a), (-a, b), (b, -a), (a, -b), (-b, a), (-a, -b), (-b, -a) ] queue = deque() queue.append(Cell(0, 0, 0)) visited = [[False] * n for _ in range(n)] visited[0][0] = True while queue: now = queue.popleft() if (now.x, now.y) == (n-1, n-1): return now.dist for i in range(8): next_x = now.x + dirs[i][0] next_y = now.y + dirs[i][1] if inBoard(n, next_x, next_y): # exploit symmetry of chess board (start from topleft, end at bottomright) # ONLY works in this special problem! (not for the generic leetcode problem above) # offers small speedup if visited[next_y][next_x]: visited[next_x][next_y] = True if not visited[next_x][next_y]: visited[next_x][next_y] = True queue.append(Cell(next_x, next_y, now.dist + 1)) return -1

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linmin001@e.ntu.edu.sg

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ariasamandi/courses

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"""courses URL Configuration The `urlpatterns` list routes URLs to views. For more information please see: https://docs.djangoproject.com/en/1.11/topics/http/urls/ Examples: Function views 1. Add an import: from my_app import views 2. Add a URL to urlpatterns: url(r'^$', views.home, name='home') Class-based views 1. Add an import: from other_app.views import Home 2. Add a URL to urlpatterns: url(r'^$', Home.as_view(), name='home') Including another URLconf 1. Import the include() function: from django.conf.urls import url, include 2. Add a URL to urlpatterns: url(r'^blog/', include('blog.urls')) """ from django.conf.urls import url, include from django.contrib import admin urlpatterns = [ url(r'^', include('apps.my_app.urls')), ]

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Dfs problem. each time we add one digit, we make sure it satifiy the condition. Code: class Solution: def numsSameConsecDiff(self, N, K): """ :type N: int :type K: int :rtype: List[int] """ if N == 1: return [i for i in range(10)] if K == 0: return list(map(int,[str(i)*N for i in range(1,10)])) res = [] def dfs(path,l): if l == N: res.append(path) return cur = path % 10 if cur + K < 10: dfs(path * 10 + cur + K, l + 1) if cur - K >= 0: dfs(path * 10 + cur - K, l + 1) for i in range(1,10): dfs(i,1) return res

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<<<<<<< HEAD from pygame.locals import * import pygame import logging as log class maze: def __init__(self, board): self.board = board self.boxSize = 10 class app: def __init__(self): log.basicConfig(level=log.DEBUG) log.info('setting board') board = [ [1, 1, 1, 1, 1, 1], [1, 0, 0, 1, 0, 1], [1, 1, 0, 1, 0, 1], [1, 0, 0, 1, 0, 1], [1, 0, 1, 0, 0, 1], [1, 1, 1, 1, 1, 1] ] self.maze = maze(board) log.info('init pyg') pygame.init() log.info('getting font') self.debugFont = pygame.font.Font(None, 20) log.info('init display') self.display = pygame.display.set_mode((800,600), pygame.HWSURFACE) pygame.display.set_caption('a maze') self.running = True while (self.running): pygame.event.pump() keys = pygame.key.get_pressed() if keys[K_ESCAPE]: log.info('hit escape') self.running = False w = len(self.maze.board[0]) h = len(self.maze.board) #log.info('drawing maze ({0},{1})'.format(w, h)) for x in range(w): for y in range(h): if self.maze.board[y][x]: box = Rect( x * self.maze.boxSize, y * self.maze.boxSize, self.maze.boxSize, self.maze.boxSize ) self.display.fill((255,255,0), box) pygame.display.flip() a = app() ======= import logging as log class Primes: def __init__(self): try: file = open('primes.bin', 'r') self._primes = file.read() close(file) except: self._primes = [] def save(self): file = open('primes.bin', 'w') file.write(self._primes) close(file) def findPrimes(self, value): def isPrime(self, value): foundNewPrime=False if self._primes[-1]**2 < value: for (p in findPrimes(self, value)): pass for i in range(len(self._primes)): if float(value)/self._primes[i] == int(value/self._primes[i]): return False return true def upTo(self, value): if (self._primes[-1] <= value): for (i in range(len(self._primes))): yield self._primes[i] else: for (p in findPrimes(self, value): yield p >>>>>>> 1994f3e2ff108c68c300463cd51de51047b9bc5e

[ "gbogumil@gmail.com" ]

gbogumil@gmail.com

d75833b190a19259f80442cc1117191339c61d5b

1c1e4761a008868d3b071780fe5bdfd6325a6a8e

/whatsapp_web_bot.py

5e3de03530f5b739ddb68257aa810ed0f2ea1d04

[]

no_license

dev-est/whatsapp_web_bot

8a368ef591a71ab44d1c1b90afddb393c8a4ce9f

cb115e68e4f5804d10bd736b0bd99d3a78e4cad7

refs/heads/master

2022-11-28T17:03:14.528441

2020-07-25T20:05:55

282,511,695

0

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py

import selenium from selenium import webdriver from selenium.webdriver.support.ui import WebDriverWait from selenium.webdriver.common.by import By from selenium.webdriver.support import expected_conditions as EC from webdriver_manager.chrome import ChromeDriverManager import time class whatsapp: def whatsapp_login(self): chrome_options = webdriver.ChromeOptions() chrome_options.add_argument("--window-size=1920,1080") chrome_options.add_argument("user-data-dir=YOUR-DIRECTORY-HERE") self.driver = webdriver.Chrome(ChromeDriverManager().install(),options=chrome_options) base_url = "https://web.whatsapp.com/" self.driver.get(base_url) def whatsapp_message(self,name,message): WebDriverWait(self.driver, 15).until(EC.presence_of_element_located((By.XPATH, f"//span[@title='{name}']"))).click() self.driver.find_element_by_xpath('//*[@id="main"]/footer/div[1]/div[2]/div/div[2]').send_keys(message) self.driver.find_element_by_xpath('//*[@id="main"]/footer/div[1]/div[3]/button').click() def whatsapp_close(self): self.driver.close() if __name__ == "__main__": #initialise login whatsapp = whatsapp() whatsapp.whatsapp_login() receive = input("Who would you like to message? ") message = input("Please enter your message ") whatsapp.whatsapp_message(receive,message) time.sleep(3) whatsapp.whatsapp_close()

[ "devrishi.sagar@gmail.com" ]

devrishi.sagar@gmail.com

82f8118697fc92a42d2c7448a0d8d17badaa4da5

17216898027c2b2ec895a3e266e920bcf63c618a

/setup.py

297dff8307bc2ef5086039d7eb9ca81b1d49b712

[ "MIT" ]

permissive

Boolean263/python-markdown-latuni

2086444308af3263ef4010bd5fd2c5ca248ce89e

a88a6de1673b5e1c3b7eaf07d95c5a2799d544f2

refs/heads/master

2023-02-21T15:50:56.437850

2021-01-25T11:59:43

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MIT

2021-01-25T11:59:44

2020-05-06T13:47:43

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py

#!/usr/bin/env python # -*- coding: utf-8 -*- # # This was originally based on the wonderful example at # https://github.com/navdeep-G/setup.py # It's been changed since then, but that's still a good site to check out. # Note: To use the 'upload' functionality of this file, you must: # $ pipenv install twine --dev import io import os import sys from shutil import rmtree from setuptools import find_packages, setup, Command from mdx_latuni import __version__ with open("README.md", "r") as f: long_description = f.read() with open("TROVE.txt", "r") as f: trove_classifiers = [x.rstrip() for x in f.readlines() if x and x[0] != '#'] here = os.path.abspath(os.path.dirname(__file__)) class UploadCommand(Command): """Support setup.py upload.""" description = 'Build and publish the package.' user_options = [] @staticmethod def status(s): """Prints things in bold.""" print('\033[1m{0}\033[0m'.format(s)) def initialize_options(self): pass def finalize_options(self): pass def run(self): try: self.status('Removing previous builds…') rmtree(os.path.join(here, 'dist')) except OSError: pass self.status('Building Source and Wheel (universal) distribution…') os.system('{0} setup.py sdist bdist_wheel --universal'.format(sys.executable)) self.status('Uploading the package to PyPI via Twine…') os.system('twine upload dist/*') self.status('Pushing git tags…') os.system('git tag v{0}'.format(__version__)) os.system('git push --tags') sys.exit() # Where the magic happens: setup( name="python-markdown-latuni", version=__version__, description="Format markdown to unicode bold/italic/etc text", long_description=long_description, long_description_content_type='text/markdown', author="David Perry", author_email="boolean263@protonmail.com", python_requires=">=3.6.0", url='https://github.com/Boolean263/python-markdown-latuni', # If the package has several modules: #packages=find_packages(exclude=["tests", "*.tests", "*.tests.*", "tests.*"]), # If the package is a single module: py_modules=['mdx_latuni'], entry_points={ 'console_scripts': [ 'md2latuni=mdx_latuni.__main__:main', ], }, install_requires=[ 'latuni', 'markdown', ], include_package_data=True, license='MIT', classifiers=trove_classifiers, # $ setup.py publish support. cmdclass={ 'upload': UploadCommand, }, )

[ "d.perry@utoronto.ca" ]

d.perry@utoronto.ca

bb86d0390075919840304aeeec10106cc7c997ee

3a0ec993dc97c485c394fd17faac6e03627abec3

/client/icons.py

32b19e107b9f62b5a2430dd995a44d1f2d2a8382

[]

no_license

hileamlakB/tuxcut

c49317bf8b02b9978caaee14a08debafbca3f191

a963f4fc64bac0935acef11f17f05f0aafada701

refs/heads/master

2022-12-10T15:20:15.301280

2020-08-27T11:57:00

290,762,337

0

null

2020-08-27T11:54:15

null

UTF-8

Python

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20,527

py

#---------------------------------------------------------------------- # This file was generated by /home/ahmed/.virtualenvs/TuxCut/bin/img2py # from wx.lib.embeddedimage import PyEmbeddedImage alias_32 = PyEmbeddedImage( b'iVBORw0KGgoAAAANSUhEUgAAACAAAAAgCAYAAABzenr0AAAABmJLR0QA/wD/AP+gvaeTAAAA' b'CXBIWXMAAA3XAAAN1wFCKJt4AAAAB3RJTUUH4QsMDi4LuoERgAAABE9JREFUWMPllW1MG3Uc' b'x7937R2Uuz7QByktYAtjYqEtPjFnYpkxi8kijhcmxr1QEvcCcEhi9I3GxARnssS98aUvzNT5' b'YhsvNDMx2WIUUMi2IsaFdXSkJ7Rot+FqHyi0/K/1zXW5HG2Bpiwm/pNv/pfL3e/z/d/v4YD/' b'+1LtNWD0+dGGgy3e1zxm2x+zfwXTD9TAwIFj7c80d10//FTvUQtnG3E1dRh+Wvjl8gMxMHDg' b'WPtzbT3+Q0/36sxmC93Z4WLojXxPh3mf+4fg1IW9NmB50u6+cqjnWbOmphYWkwWxWAwmo0nF' b'gmlv0Jj+nhb8fgCg9wButlqtM46XXNaruiDoLi3mgzeQy+XAsiw8j3axXbaOjwsPV9uA2W63' b'zw4ODrYaDAbK5/Ph0q0J/Lwxh3vJGCiKQjKVghoqpvCCuopwA03TE0NDQ82NjY2Uw+HAysoK' b'NBoN8rY8VsU4qCiF4GIwe2Vp7lS1a8AAYNbr9e5PpVJUX18fIpEIYrEYOI4DTdO4OPk9LHHt' b'5sTizMlPpz4fq6YBA4DZ7u7uVo7jYDabMT4+jkwmA5fLhXg8jrm5OUzPzCRWbq+8f+ba+VPV' 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#---------------------------------------------------------------------- cut_32 = PyEmbeddedImage( b'iVBORw0KGgoAAAANSUhEUgAAACAAAAAgCAYAAABzenr0AAAABmJLR0QA/wD/AP+gvaeTAAAA' b'CXBIWXMAAA3XAAAN1wFCKJt4AAAAB3RJTUUH4QsMDjABjhXHQQAABklJREFUWMO9lltsFNcd' b'xv9nLt6dmZ3Z2V0v6128xBcUOzgQ25uQmCqEIipEK/JQKVHUh0q9SEhJH4pbIVjRZNMiHAuH' b'Vm1TlYaoqaqi1jw0TVo1RK1ICUmKzS4QTNQYsBdf8GUvszuXnd25nNOH1FYUpcWLnX6Po29G' b'v/Od7/zPANxBqVTKe+zYwE5YoQYGBlqGho7cs1I/dSdDKBz4Lsdzrw0ODjav5IP+oPAyL8qv' b'rwnA8PAwzTLMN760a7fok7gXV7D6jeFQuKu9tT0+9JOh7asGuDVz8/GOjs6YIPig5Z6WnXdK' b'QZKFoZ7uRPS+zk0BkecHVg0gCNLXW1tafRgT6Nq0ufF/pXDk+JH1AVl+0OPxAsYEmpqiGwkh' b'aFUAruOMq1oZI4SAomiIx+Nf/G8pBDh5MNGbWO+6GAAA8oXFMkKIrArAsZSBTObSDMPQAACw' b'5f7usOjnhz7tO3r0aEj0+R7leREwxqCqJdcwzFdXvQX796dKqqb9pVDILacQjcZ2fDoFSfb9' b'KJHobXYcFxBCkL6UnnYs/OM1OYaOpRxOZzLLKTywpSci+n3LKQwODoo+QdjjEyQKYwzVagXr' b'uj7c399vrglAf3+qqOnqm4VCHiOEgKEZCIdDjy2lwAveQ93dPXHHcQEAYGR0ZNaxlIE1G0QA' b'AGrJSKYzF2eXUkj0bm0S/b6hVCrl5TjvU7I/SBNCwHYsohvam/v3p0prCpBMJgtaxfirUlIw' b'AABDMxAKBbbLAfm5np5Es23bAACQyVy8bWjVZ6EOUSs1qkUtOTJyYZZlGcAYw0OJh6MeD/ud' b'UDDEEkKAEAyKUnrvwIED858LQDKZLOiGdkbVtI8POiBoDIeEclkFhAAuX0nPqWX9ANQpqh6z' b'WjIOXhh5b5amacAYQ/cDCXT9xjhQFAX5fP7SoUOHsp8rQDKZLGiq+lalYhDLtoChGSCAIXM5' b'ky+XlLpXXzcAAIA1vvCDC/84C67rgG1b0NOdgNziIj548Nlr/xcAcfzqIDU5gQjGkDt3Hi4d' b'fh7Y354O/3z33t67AaDrMR/v6+P8lj3U6Zj+iakpuP3GGehgHYjwLCrnlchrs9N/qBfgjtfl' b'Kx1fEBuauBc4v/iYU7MDsluNRCUvPVHQcuWK/X5HRNrLNzBoLKeXWH9gHgGpVlTt1clzf/9Z' b'CgCvCuBEYlt7KNb0t/a22AahgaUIIZCdy4OzMGctqJXf26510O8RRoMSt56LxyHi9wEgBEWj' b'ak5cv/WBVlzYuS+drtxVB17q2uGTI41n7muLtoDrwI3phYXFourGw34oE8aa4j3f2pdOz1Xs' b'2q8Nr4DXiRxk5/Nudr6QE1mK67x3w4OCFPzjXZdQCqAX25ojLYZZrY5du3n29tXJTdmbt8Zc' b'2wGvIJSfe/ttFwDAcsifJIHHBUWH2evZsRtXPnz06nh2nAWgY/How6888sjjdQO81LXDx8vS' b'lzma0DcnZiY9jfLub197v1irmadMswYICHr+P9uHgRYYCqyybuCq5Zx4+oOLHxXyi7uuT8/P' b'NQkNfk6Qflg3QANvfyUi8+FFRdfLpdL3nzx92gUA8DBshAIMjm3bSwWjwC3Zll310FQFAXUN' b'AOCZ0dFpraj82axZIPiEdScSica6ADxedgdPUZ68ouaDrRvOLJtpzy4OATiWtVwsk1i3dKNS' b'lVjaJ/DM15ae63rlF/mSUZQ8rIRd9v76OoAhTBEMbq1mLK3+lz3btvtFb8wwq8Qya2eXf9su' b'Xy7p5UrOQwE0cN49J7v6gh9f2XjSNGtVmmAvASzXB0AwYNcBBOAdfuIJ+uUtW1tF0fubuN/b' b'OJ0rzel25YVP2mt29diComttIamZ9bNvHO/r4whm1jOAWYxdTLEUVReAYztvqUbNjgWEWHUu' b'd0UOiuc6o3KLolZMTTWHnxkdnf6k/5v/fPfUTK74LyCYurcpuDXCcGOiwL/eJHrCRUUrIGxf' b'rAvArDScmlpQZkQacd0xuatjndis6qaZXVTOZy+8873PmGbE1qy9H04tjgN26M1RqW1zzN/u' b'WDYpm9WP9qXTU3VPwl89tK27AaHfeRoYyXacmu3i02JL8+GlTnyWTnb1BRkBTrIM04soRNds' b'+4ZZob/69NXzCtytjvf1cfW+kwKgfrpxj2cl3n8DvarlTOUwVg8AAAAASUVORK5CYII=') #---------------------------------------------------------------------- exit_32 = PyEmbeddedImage( b'iVBORw0KGgoAAAANSUhEUgAAACAAAAAgCAYAAABzenr0AAAABmJLR0QA/wD/AP+gvaeTAAAA' b'CXBIWXMAAA3XAAAN1wFCKJt4AAAAB3RJTUUH4QsMDjAnXBhCvAAABidJREFUWMPtl12MXVUV' b'x39rnzvDTNuI08YM1kJpoU5rpyQi0giNxmDEF3wgKjwYKBKIiYmPEAUlakw0MRgT5EFMiCQN' 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b'yFxxp1WFQciq7wFIIlCjE5CK+bGulpCWc/yljRFTw+vvzrm+ZI/V+4JNraEHLV3HQs5b94ZU' b'PHA9wgoAYvKugKGi4IplmUri8rz9u1efvj9VT/F8znlXVdBnaRy0DoCmMMzlnAsNYoB1agqH' b'kOVrN8L1ISHPrqU4V3IPnZyY/G1bxNq+3gmk7NL5Rcc51AjAFEtJoyJCAoyQW0txNbfv+G+L' b'kbrKUWkhJOQyAkNRQIRb/lfVcFUM0NWi568E0BVYprofwNGbUbzr8HjYZQ7vuZQpjIwcFGvW' b'j+WTzj2f85ss4xFTV+HLSt5iACxD2az3DZ+cHD+WbGQ4kSBe2nfvA7GwtjsW1DYW44bedven' b'slOvjJTrrefLJ11vZd+4kiqkLV2FlICUQNYuo6c1ymJh67ndR062NuovRsujw7c1Nx2KW+od' b'YUO9tTVu3tkcityKRII3BBgZOSgWcu4PPb+aPqs5PJl2sKdvw5ZQJPDq4JHTA3Wr5zf+GN39' b'zdGv97ZHH+MK2wyGZiho45y1WzGrqx/9ZuMgBMB0+tk/J9Nf6+9ujc3lK+lYlAnJjIO9H97Q' b'fWUhfybwnZcuFP3yRRCSxGSGE2/a0mEN9bZFw8lM0fYEZRkUnwkSBCbcEk3ri810wy3Z4JFT' b'w32bmn/fHDKXiklNYgEN8ZAGBqAsCZwxMAA5x/NnM6WigLAJLE9SLgKU9iUuT2XtY+OJofGG' b'QViTqfFjF4x7PhNoCxm7goYO15MgAogAx5NIFzykCz6yto+M7SNt+yi4QhHVTEtEjDEGQXCn' b'Fuy/OrPx4zMTv5A3DAAAU3/5zUv8rgOBoK7sao2acDxZKSjr9LcEMIBYPKhzS+elN5PZ04su' b'/fgfP9nj3mxXzGpj4PALD7bEos9u62wKK5wj55RXNClLwcQZLJ3B0FCeTtnzb01lnplbmPjp' b'5V8nSvU7gZUArHojakMFYADQAWgt23a3du79wuc33tL9xZ6OeDhq6eCcVWobA0CEnO1gOpXz' b'r04nR7NvTzzzzos/ugDAB1Cq/hIAWR20HgADoFUBtBoEAA26bvR+/ImBSNftn1U0cyPjaoRE' b'OePmZ17zMrOvvf/G8VcWL/0rvcpwCUC5EcCaLlgFpyybs2WlvqZUrDKyfHwgdeU/IVu6JtkR' b'bk4AAAAASUVORK5CYII=') #---------------------------------------------------------------------- resume_32 = PyEmbeddedImage( b'iVBORw0KGgoAAAANSUhEUgAAACAAAAAgCAYAAABzenr0AAAABmJLR0QA/wD/AP+gvaeTAAAA' b'CXBIWXMAAA3XAAAN1wFCKJt4AAAAB3RJTUUH4QsMDjEzX9mngAAAA/NJREFUWMPtl+trW2UY' b'wJ/3pDknp8nSLt2lztKsuW2mtqZr7drR0Qs6GMhgk3wYVuYYDNTp0GmLoOA3RQZ+cH7wHxBH' b'GOqX7cOKDdYL2+o6pbS6tUmbNF3T5p7T05xz3osfanGRrPaS5NMeeOB94IXnx/s873MBeCL/' b'yOnLrl0vf1JvK7dfbu2gaVqvde++P17/qul776e2+nIBVDxqvNR+tLLGbD4xNDZ6uPqK4adU' b'KnPR9+FcpJQAurWD+4WdjW2ug95qcwy5rVaTx97izmH2an0XOtzQZRyZ/CEtlfwFGKMAwEAj' b'MRB4BKe6nt0tye2nhu7d6bR8KQ7HZe3db9+fXiwdANA8SyMxMAgcOnmkaV8i6zk9NDbaY/lC' b'fz2OcwPfvTOTKnoIWp0ub5UJo/wrDAhbBkEvo2ab09xobWrJZqSztm7e5eg2j0wMJZWiARxy' b'Or1VJoIKX2VAqASCXkYtjmdMjfXNnpQs9TuO8nvqOvhf7/uz2vYBHA6v2UgQA4DHKwVMsyDw' b'Mtdqd1c569xH0nL2rKPHYPF07Pjlnj+FtwzwnN3m3VGJEWMM/k8pJaCRNBh4mWtzNpvttQc7' b'o0rqzIFe0VR7fOetqRsJsmmA5ob9XpOIEaUMNq4EVJwCUcjpWu1N1XW77V2ZePy1Az1GqO6M' b'j8748zJ7fYBGa73XJBJEGYPNKqEYVJwEo0HTPe/0VFv32nolCZ9z9VQy17nE6IQP2AYA6rzG' b'LQL8C6KBghMgCmpFm9NT9fSu/d2JED3j6qtUT3Ykxvz+fBDuUQMTUjRVNRky8gOoMSfF/r4X' b'HSfaj30ef+rQn/2XHa8AA1QQgFAMhJCiqqpJIK1Mgb3WIh5v67NxHHfF+1mDq2AlJAQDJqxo' b'ZRYhHYh8LUg5gd4cG4lGYhEfybCPfB8HM4UBKCkKAEIciPwekHIC/XF84mFoMXQ9xXDB8p0H' b'gLcJgBAHBn0NKKrAhiamHoZi4eGMStdtYP8JgQbkcZV4PceAQOAtkFMF8E8GFsPx+RFZ1S74' b'BmYWNtUNV3OA25RrQW8GRTPA7fHZhblE9GdFyb39zWB4fkvteOMhQMBXmABTAW7dj0TDscW7' b'0op64doHocC25gFMNMCkYl3Hep0ImAjw20x0YS6+NC5p7I1rA4EHRRlIVv9u4RzQcQJQxsPv' b'4fjSfCI5uayQ877B4F9FnYhWXyAfgOP0wKgeJiOp2HwiPato+PzVgdm7JRnJ1sro2pcilINg' b'NB1bSC/PrKj0Td9g8HZJh1JKVwEo4yAUl5LRZG4OM7j49aXp4bLsBQohEIgup6IZHFY0esk3' b'GLxZtsWEIcjNLikBAuitq+9N33iyrJZL/gbvoO9htzrf6gAAAABJRU5ErkJggg==')

[ "a.3talla@gmail.com" ]

a.3talla@gmail.com

fd340134c630935c8dff1c7e83d8d2b1a4bd61dc

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/python/qt/close_dialog.py

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[]

no_license

akihikoy/ay_test

4907470889c9bda11cdc84e8231ef3156fda8bd7

a24dfb720960bfedb94be3b4d147e37616e7f39a

refs/heads/master

2023-09-02T19:24:47.832392

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#!/usr/bin/python #\file close_dialog.py #\brief certain python script #\author Akihiko Yamaguchi, info@akihikoy.net #\version 0.1 #\date Apr.01, 2017 # http://stackoverflow.com/questions/14834494/pyqt-clicking-x-doesnt-trigger-closeevent import sys from PyQt4 import QtGui, QtCore, uic class MainWindow(QtGui.QWidget): def __init__(self): QtGui.QWidget.__init__(self) # Set window size. self.resize(320, 240) # Set window title self.setWindowTitle("Hello World!") # Add a button btn= QtGui.QPushButton('Hello World!', self) btn.setToolTip('Click to quit!') btn.clicked.connect(self.close) btn.resize(btn.sizeHint()) btn.move(100, 80) def closeEvent(self, event): print("event") reply = QtGui.QMessageBox.question(self, 'Message', "Are you sure to quit?", QtGui.QMessageBox.Yes, QtGui.QMessageBox.No) if reply == QtGui.QMessageBox.Yes: event.accept() else: event.ignore() if __name__ == "__main__": app = QtGui.QApplication(sys.argv) win = MainWindow() win.show() sys.exit(app.exec_())

[ "info@akihikoy.net" ]

info@akihikoy.net

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e95322e4a14f3a0e6504ef3997f7fac1e2bce387

/utils.py

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[]

no_license

redhat12345/adversarial-domain-adaptation

c3af6dc9a038723f715ab883bbf2610ac1ee3a42

47ea0b7eb9a3743796f877d4b5e190af226fcad9

refs/heads/master

2020-03-29T16:19:21.201889

2018-09-23T23:38:57

null

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import tensorflow as tf import matplotlib.pyplot as plt plt.switch_backend('agg') def log(x, eps=1e-8): return tf.log(x + eps) def normalize(x, max_value): """ If x takes its values between 0 and max_value, normalize it between -1 and 1""" return (x / float(max_value)) * 2 - 1 def unnormalize(x): return (x + 1) / 2 def leaky_relu(x, alpha=0.05): return tf.maximum(x, alpha*x) def plot_images(index, X_source, X_target, X_s2s, X_t2t, X_s2t, X_t2s, X_cycle_s2s, X_cycle_t2t, Y_source_predict, Y_target_predict): plt.clf() plt.rcParams['figure.figsize'] = (20, 10) plt.subplot(2,4,1) plt.title(Y_target_predict[index]) plt.imshow(unnormalize(X_target[index])) plt.axis('off') plt.subplot(2,4,2) plt.imshow(X_t2s[index]) plt.axis('off') plt.subplot(2,4,3) plt.title("t2t direct") plt.imshow(X_t2t[index].reshape(32,32,3)) plt.axis('off') plt.subplot(2,4,4) plt.title("t2t cycle") plt.imshow(X_cycle_t2t[index].reshape(32,32,3)) plt.axis('off') plt.subplot(2,4,5) plt.title(Y_source_predict[index]) plt.imshow(unnormalize(X_source[index])) plt.axis('off') plt.subplot(2,4,6) plt.imshow(X_s2t[index]) plt.axis('off') plt.subplot(2,4,7) plt.title("s2s direct") plt.imshow(X_s2s[index]) plt.axis('off') plt.subplot(2,4,8) plt.title("s2s cycle") plt.imshow(X_cycle_s2s[index].reshape(32,32,3)) plt.axis('off')

[ "arthur.pesah@gmail.com" ]

arthur.pesah@gmail.com

02acda62b0acb6f8e73d02a5004433c4db8c0653

44fe52c822f73fdd8a66f4090bbe4b630024ae3c

/FlaskTraining/113SQLAlchemy/app.py

ce6664dfea88dd9644b27404d694223c23e3c528

[]

no_license

rohitvishal7/flask

69edfd076bd17e3e421ab65c6e622af335e4d97e

ca64d5c47c0ff669185ec347955baca578c8bb9c

refs/heads/master

2021-01-11T01:54:36.423409

2016-09-30T09:26:37

null

0

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py

from flask import Flask, request, flash, url_for, redirect, render_template from flask_sqlalchemy import SQLAlchemy app = Flask(__name__) app.config['SQLALCHEMY_DATABASE_URI'] = 'sqlite:///students.sqlite3' app.config['SECRET_KEY'] = "random string" db = SQLAlchemy(app) class students(db.Model): id = db.Column('student_id', db.Integer, primary_key=True) name = db.Column(db.String(100)) city = db.Column(db.String(50)) addr = db.Column(db.String(200)) pin = db.Column(db.String(10)) def __init__(self, name, city, addr, pin): self.name = name self.city = city self.addr = addr self.pin = pin @app.route('/') def show_all(): return render_template('show_all.html', students=students.query.all()) @app.route('/new', methods=['GET', 'POST']) def new(): if request.method == 'POST': if not request.form['name'] or not request.form['city'] or not request.form['addr']: flash('Please enter all the fields', 'error') else: student = students(request.form['name'], request.form['city'], request.form['addr'], request.form['pin']) db.session.add(student) db.session.commit() flash('Record was successfully added') return redirect(url_for('show_all')) return render_template('new.html') if __name__ == '__main__': db.create_all() app.run(debug=True)

[ "noreply@github.com" ]

rohitvishal7.noreply@github.com

4514eac9ff495b8f6a3dc717b7d4580f119de12d

2c55946200a55dc86951b2fc676d60600028614e

/settings.py

032b757d324e65d77d5aec1033b7fc2dd43ee2b0

[]

no_license

ahishn27/Practice

7b19106adb196dc9d53df6174162094056ec2946

cd6d476623cc0ffd41f5c6c1a4630e7f4dd7d72c

refs/heads/master

2020-04-17T03:08:19.808140

2019-02-04T09:13:33

166,168,325

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py

#Package imports import os import dotenv #searching the .env file in the directory found_dotenv = dotenv.find_dotenv('.env') #Loading the .env file to get access to the variables dotenv.load_dotenv(found_dotenv) #apply_functions def apply_func(func): return lambda x:func(x) #common function from_env = apply_func(os.getenv) # Accessing variables from .env file status = from_env('STATUS') secret_key = from_env('PASSWORD') #display statements print(status) print(secret_key)

[ "Ahish.N@42hertz.com" ]

Ahish.N@42hertz.com

6e49e63174591b977f3dedd690bd4266cfc1453c

9ba9491d26187838dd318f07e17abdc6ccb48c64

/core/templatetags/extras.py

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[ "Apache-2.0" ]

permissive

bugulin/gymgeek-web

dc4cfa819b6d13f306605d69ef0c0977768f0868

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refs/heads/master

2021-07-11T04:23:36.341115

2017-12-18T15:18:04

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428

py

from django import template from django.template.defaultfilters import stringfilter from django.utils.safestring import mark_safe from docutils.core import publish_parts register = template.Library() @register.filter(name='rst') @stringfilter def rst_to_html5(text): parts = publish_parts(text, writer_name='html5', settings_overrides={'initial_header_level': 2}) return mark_safe(parts['html_title'] + parts['body'])

[ "petriczech12@gmail.com" ]

petriczech12@gmail.com

cfebfef778ac23b6285c76677175d328f20cb65a

2d5753c42f2c20e03be8a1cf5aeb2469c24263a1

/misc/LSTMTagger.py

19cba5f91f3757d1badc77e8c2bac6eefa22fcb4

[]

no_license

jonathanhans31/seq-model

0c9ff91e888788e23b1f0f0565e93ac9efe78687

785f65d77c2e7d089e4d804f2136a2ccd417aa5e

refs/heads/master

2020-03-22T14:54:12.423105

2018-08-23T01:27:58

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UTF-8

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py

import torch import torch.nn as nn import torch.nn.functional as F import torch.optim as optim class Model(nn.Module): """docstring for Model""" def __init__(self, embedding_dim, hidden_dim, vocab_size, tagset_size): super(Model, self).__init__() self.hidden_dim = hidden_dim self.word_embeddings = nn.Embedding(vocab_size, embedding_dim) # The LSTM takes word embeddings as inputs and outputs hidden states with dimensionality hidden_dim self.lstm = nn.LSTM(embedding_dim, hidden_dim) # The linear layer that maps from hidden state space to tag space self.hidden2tag = nn.Linear(hidden_dim, tagset_size) self.hidden = self.init_hidden() def init_hidden(self): # The axes semantics are (num_layers, minibatch_size, hidden_dim) return (torch.zeros(1, 1, self.hidden_dim), torch.zeros(1, 1, self.hidden_dim)) def forward(self, sentence): embeds = self.word_embeddings(sentence) N_sequence = len(sentence) inputs = embeds.view(N_sequence, 1, -1) # Extract the feature in the sequence into lstm_out lstm_out, self.hidden = self.lstm(inputs, self.hidden) # Add a Linear Layer tag_space = self.hidden2tag(lstm_out.view(N_sequence, -1)) tag_scores = F.log_softmax(tag_space, dim=1) return tag_scores

[ "jonathanhans31@gmail.com" ]

jonathanhans31@gmail.com

a43822a9657a1661bdf8eec5626ddb1f8fb0ae2c

5a2fdbcfe7f9218e332ff506608cde78043256ff

/nova/db/sqlalchemy/migrate_repo/versions/279_fix_unique_constraint_for_compute_node.py

820fa3f696047c0989ac87fc9dbea37b9d0db2ec

[ "Apache-2.0" ]

permissive

starlingx-staging/stx-nova

6d4aad0899bad527d8765f6cc07971e40581e4d3

23e7930b35f8a0d61ee6c5798bbef1a281bfc070

refs/heads/master

2022-07-27T18:12:57.404225

2019-08-06T11:23:04

134,120,491

7

19

Apache-2.0

2022-07-06T19:52:40

2018-05-20T04:46:47

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UTF-8

Python

false

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py

# Copyright (c) Intel Corporation. # # 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 migrate import UniqueConstraint from sqlalchemy import MetaData, Table def upgrade(migrate_engine): meta = MetaData() meta.bind = migrate_engine compute_nodes = Table('compute_nodes', meta, autoload=True) # Drop the old UniqueConstraint ukey = UniqueConstraint('host', 'hypervisor_hostname', table=compute_nodes, name="uniq_compute_nodes0host0hypervisor_hostname") ukey.drop() # Add new UniqueConstraint ukey = UniqueConstraint( 'host', 'hypervisor_hostname', 'deleted', table=compute_nodes, name="uniq_compute_nodes0host0hypervisor_hostname0deleted") ukey.create()

[ "hejie.xu@intel.com" ]

hejie.xu@intel.com

4852b83b2264cd75b2dfc36bc578fc47b1f9e399

cf5efed6bc1e9bd27f94663d2443c6bdd1cb472a

/1-pack_web_static.py

1688b66bfe9161d9b0827db23d9332f8638567fd

[]

no_license

yulyzulu/AirBnB_clone_v2

593db702ede02ac17b6883b3e99b6e1eb36a33ee

1a40aec60996dc98ad9ff45f5e1224816ff6735b

refs/heads/master

2021-05-25T15:33:22.100621

2020-04-23T23:23:25

253,810,650

0

null

2020-04-07T14:02:36

2020-04-07T14:02:35

null

UTF-8

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false

682

py

#!/usr/bin/python3 """Module that execute functions""" from fabric.api import local from fabric.decorators import runs_once from datetime import datetime from os.path import getsize @runs_once def do_pack(): local("mkdir -p versions") date_time = datetime.now().strftime("%Y%m%d%H%M%S") command = local("tar -cvzf versions/web_static_{}.tgz ./web_stat\ ic".format(date_time)) if command.succeeded: size = getsize('versions/web_static_{}.tgz'.format(date_time)) print("web_static packed: versions/web_static_{}.tgz -> {}Byt\ es".format(date_time, size)) return ('versions/web_static_{}.tgz'.format(date_time)) else: return None

[ "yulyzulu05@gmail.com" ]

yulyzulu05@gmail.com

b9968479d3d506d21dff4da4876d0a85ef697e4a

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/applications/ks/ksData.py

8f3f11e57526eb15c59cd87c40677d2638a8d3ed

[]

no_license

dingxiong/research

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b7e82bec1cf7b23cfa840f3cb305a2682164d2f3

refs/heads/master

2021-03-13T01:50:57.594455

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py

from ksHelp import * case = 10 if case == 10: ksp = KSplot() fileName = '../../data/Ruslan/ks22h1t120.h5' a, T, nstp, theta, err = ksp.readPO(fileName, ksp.toStr('ppo', 1), False, hasNstp=False)

[ "dingxiong203@gmail.com" ]

dingxiong203@gmail.com

8087a586a08d86c2630e2cd577c77d550102a37d

3090c81bc67cb5e42a4bef0b460577c2695b3877

/fizzbuzz3/fizzbuzz_module.py

7512f2cc73eab5913191eaa8e66368479d91632e

[]

no_license

CodecoolBP20161/python-pair-programming-exercises-2nd-tw-adam_david

44f8b6146670fc2a455e29f6a8d354e62665cad4

f1be4b46849ab22f07d81038f90e8dfec697e555

refs/heads/master

2016-09-13T22:49:49.731694

2016-05-26T07:37:22

59,470,310

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py

def fizzbuzz(number): result = number if number % 3 == 0: result = str(result).replace(str(number), "") + "Fizz" if number % 5 == 0: result = str(result).replace(str(number), "") + "Buzz" return result def main(): for i in range(1, 101): print(fizzbuzz(i)) if __name__ == '__main__': main()

[ "feherkeee@gmail.com" ]

feherkeee@gmail.com

5953d5e80fc94ed4ad2ce7b9db46fa744fce156b

06d583192baa32a5b1e4c99296482d37962a2a23

/TSL2561.example.py

0f0fe1d74d03415ef98b102548c3f32371e3491a

[]

no_license

janheise/TSL2561

d2b7d70a7f7fd8996509369dca4e421cdb2c2c31

3fbed5d910bf5b11aba8603475b07f79007169b4

refs/heads/master

2016-09-05T16:06:27.185370

2013-02-01T14:55:48

7,959,402

42

5

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UTF-8

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py

#!/usr/bin/env python3 from TSL2561 import * tsl = TSL2561() if tsl.foundSensor(): print("Found sensor...") tsl.setGain(tsl.GAIN_16X); tsl.setTiming(tsl.INTEGRATIONTIME_13MS) x = tsl.getFullLuminosity() print("Full luminosity value: %d" % x) print("Full luminosity value: %#08x" % x) full = tsl.getLuminosity(tsl.FULLSPECTRUM) visible = tsl.getLuminosity(tsl.VISIBLE) infrared = tsl.getLuminosity(tsl.INFRARED) print("IR: %x" % infrared) print("Full: %x" % full ) print("Visible: %#x" % visible ) print("Visible, calculated: %#x" % (full - infrared) ) print("Lux: %d" % tsl.calculateLux(full, infrared) ) else: print("No sensor?")

[ "jan@janheise.de" ]

jan@janheise.de

bc152200d29fb65d3f15389a83a766eb2af27faf

1f874c6a515f7c86047378d507be652f18925eb5

/mergeLinksTXP.py

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[]

no_license

BeenleTian/TempCauseRelPro

b2325183123f80879e148e90b8b8462c34b9de86

4e554863ac4f5c8e5feb20bdc81c4517c1ce74db

refs/heads/master

2020-12-30T14:19:35.216223

2015-10-26T14:22:18

2015-10-26T14:22:32

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py

import sys import os def ensureDir(f): d = os.path.dirname(f) if not os.path.exists(d): os.makedirs(d) def getFieldValueTxp(fieldname, cols): fields = ["token", "token_id", "sent_id", "nr_pos", "nr_lemma", "nr_deps", "tmx_id", "tmx_type", "tmx_value", "nr_ner", "ev_class", "ev_id", "role1", "role2", "role3", "is_arg_pred", "has_semrole", "nr_chunk", "nr_main_verb", "nr_connective", "nr_morpho", "ev_tense+ev_aspect+ev_pol", "nr_coevent", "tlink"] if fieldname in fields: if fields.index(fieldname) < len(cols): return cols[fields.index(fieldname)] else: return "O" else: return "O" def printUsage(): print "usage: python mergeLinksTXP.py dir_txp dir_tlink dir_clink dir_output [-fixtlink]" print "or python mergeLinksTXP.py file_txp file_tlink file_clink dir_output [-fixtlink]" def mergeLinks(filetxp, filetlink, fileclink, outfile, fixtlink): ftxp = open(filetxp, 'r') ftlink = open(filetlink, 'r') fclink = open(fileclink, 'r') fout = open(outfile, 'w') txp_lines = ftxp.readlines() tlink_lines = ftlink.readlines() clink_lines = fclink.readlines() tlink_pairs = {} for line in tlink_lines: if line != "": cols = line.strip().split("\t") tlink_pairs[(cols[0], cols[1])] = cols[2] clinks = {} for line in clink_lines: if line.strip() != "": cols = line.strip().split("\t") if cols[2] == "CLINK": if cols[0] not in clinks: clinks[cols[0]] = [] clinks[cols[0]].append(cols[1]) if fixtlink: tlink_pairs[(cols[0], cols[1])] = "BEFORE" tlink_pairs[(cols[1], cols[0])] = "AFTER" elif cols[2] == "CLINK-R": if cols[1] not in clinks: clinks[cols[1]] = [] clinks[cols[1]].append(cols[0]) if fixtlink: tlink_pairs[(cols[0], cols[1])] = "AFTER" tlink_pairs[(cols[1], cols[0])] = "BEFORE" tlinks = {} for (source, target) in tlink_pairs: reltype = tlink_pairs[(source, target)] if source not in tlinks: tlinks[source] = [] tlinks[source].append((target, reltype)) #file descriptions fout.write(txp_lines[0]) fout.write(txp_lines[1]) fout.write(txp_lines[2].strip() + "\tclink\n") fout.write(txp_lines[3]) #DCT fout.write(txp_lines[4]) fout.write(txp_lines[5]) for line in txp_lines[6:]: if line.strip() == "": fout.write(line) else: cols = line.strip().split("\t") line_str = "\t".join(cols[0:-1]) + "\t" tmx_id = getFieldValueTxp("tmx_id", cols) ev_id = getFieldValueTxp("ev_id", cols) #tlink if tmx_id != "O" and tmx_id in tlinks: for (eid, reltype) in tlinks[tmx_id]: line_str += tmx_id + ":" + eid + ":" + reltype + "||" line_str = line_str[0:-2] elif ev_id != "O" and ev_id in tlinks: for (eid, reltype) in tlinks[ev_id]: line_str += ev_id + ":" + eid + ":" + reltype + "||" line_str = line_str[0:-2] else: line_str += "O" line_str += "\t" #clink if ev_id != "O" and ev_id in clinks: for eid in clinks[ev_id]: line_str += ev_id + ":" + eid + "||" line_str = line_str[0:-2] else: line_str += "O" fout.write(line_str + "\n") ftxp.close() ftlink.close() fclink.close() fout.close() #main if __name__ == '__main__': if len(sys.argv) < 5: printUsage() else: dir_out = sys.argv[4] if dir_out[-1] != "/": dir_out += "/" ensureDir(dir_out) fixtlink = False if len(sys.argv) > 5 and sys.argv[5] == "-fixtlink": fixtlink = True if os.path.isdir(sys.argv[1]) and os.path.isdir(sys.argv[2]) and os.path.isdir(sys.argv[3]): #input is directory name dirtxp = sys.argv[1] dirtlink = sys.argv[2] dirclink = sys.argv[3] if dirtxp[-1] != "/": dirtxp += "/" if dirtlink[-1] != "/": dirtlink += "/" if dirclink[-1] != "/": dirclink += "/" #for r, d, f in os.walk(dirtxp): for filename in os.listdir(dirtxp): if filename.endswith('.txp'): #print filename filetxp = os.path.join(dirtxp, filename) filetlink = os.path.join(dirtlink, filename + ".tlinks") fileclink = os.path.join(dirclink, filename + ".clinks") outfile = dir_out + os.path.basename(filename) mergeLinks(filetxp, filetlink, fileclink, outfile, fixtlink) elif os.path.isfile(sys.argv[1]) and os.path.isfile(sys.argv[2]) and os.path.isfile(sys.argv[3]): #input is file name filetxp = sys.argv[1] filetlink = sys.argv[2] fileclink = sys.argv[3] outfile = dir_out + os.path.basename(sys.argv[1]) mergeTlinks(filetxp, filetlink, fileclink, outfile, fixtlink) else: printUsage()

[ "paramita@fbk.eu" ]

paramita@fbk.eu

a9999691c3e277bd3c41bb28c97ea2216afad0fb

508cd804441ce076b318df056153870d2fe52e1b

/sphere.py

e43689710948ecd61748515c08b01fe57e116aba

[]

no_license

archibate/taichi_works

ffe80e6df27b7bcb3ce1c4b24e23ceeb0ac4ff8a

9aaae1de9fe53740030c6e24a0a57fc39d71dd71

refs/heads/master

2022-11-18T19:07:37.122093

2020-07-17T08:45:36

276,714,718

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UTF-8

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py

import taichi as ti import taichi_glsl as tl import random, math ti.init()#kernel_profiler=True) dt = 0.01 kMaxParticles = 1024 kResolution = 512 kKernelSize = 16 / 512 kKernelFactor = 0.5 / kKernelSize**2 kGravity = tl.vec(0.0, -0.0) kUseImage = False kBackgroundColor = 0x112f41 kParticleColor = 0x068587 kBoundaryColor = 0xebaca2 kParticleDisplaySize = 0.2 * kKernelSize * kResolution particle_pos = ti.Vector(2, ti.f32, kMaxParticles) particle_vel = ti.Vector(2, ti.f32, kMaxParticles) property_vel = ti.Vector(2, ti.f32, kMaxParticles) property_density = ti.var(ti.f32, kMaxParticles) property_force = ti.Vector(2, ti.f32, kMaxParticles) n_particles = ti.var(ti.i32, ()) if kUseImage: image = ti.Vector(3, ti.f32, (kResolution, kResolution)) @ti.func def smooth(distance): ret = 0.0 r2 = distance.norm_sqr() if r2 < kKernelSize**2: ret = ti.exp(-r2 * kKernelFactor) return ret @ti.func def grad_smooth(distance): ret = tl.vec2(0.0) r2 = distance.norm_sqr() if r2 < kKernelSize**2: ret = (-2 * kKernelFactor) * distance * ti.exp(-r2 * kKernelFactor) return ret @ti.func def alloc_particle(): ret = ti.atomic_add(n_particles[None], 1) assert ret < kMaxParticles return ret @ti.kernel def add_particle_at(mx: ti.f32, my: ti.f32, vx: ti.f32, vy: ti.f32): id = alloc_particle() particle_pos[id] = tl.vec(mx, my) particle_vel[id] = tl.vec(vx, vy) @ti.func def preupdate(rho, rho_0=1000, gamma=7.0, c_0=20.0): b = rho_0 * c_0**2 / gamma return b * ((rho / rho_0) ** gamma - 1.0) @ti.func def update_property(): for i in range(n_particles[None]): my_pos = particle_pos[i] property_vel[i] = particle_vel[i] property_density[i] = 1.0 for j in range(n_particles[None]): w = smooth(my_pos - particle_pos[j]) property_vel[i] += w * particle_vel[j] property_density[i] += w property_vel[i] /= property_density[i] for i in range(n_particles[None]): my_pos = particle_pos[i] property_force[i] = tl.vec2(0.0) for j in range(n_particles[None]): dw = grad_smooth(my_pos - particle_pos[j]) ds = particle_pos[j] - particle_pos[i] dv = particle_vel[j] - particle_vel[i] force = dw * property_density[j] * dv.dot(ds) property_force[i] += force @ti.kernel def substep(): update_property() for i in range(n_particles[None]): gravity = (0.5 - particle_pos[i]) * 2.0 particle_vel[i] += gravity * dt particle_vel[i] += property_force[i] * dt particle_vel[i] = tl.boundReflect(particle_pos[i], particle_vel[i], kKernelSize, 1 - kKernelSize, 0) particle_pos[i] += particle_vel[i] * dt particle_pressure[i] = preupdate(particle_density) @ti.kernel def update_image(): for i in ti.grouped(image): image[i] = tl.vec3(0) for i in range(n_particles[None]): pos = particle_pos[i] A = ti.floor(max(0, pos - kKernelSize)) * kResolution B = ti.ceil(min(1, pos + kKernelSize + 1)) * kResolution for pix in ti.grouped(ti.ndrange((A.x, B.x), (A.y, B.y))): pix_pos = pix / kResolution w = smooth(pix_pos - particle_pos[i]) image[pix].x += w last_mouse = tl.vec2(0.0) gui = ti.GUI('WCSPH', kResolution, background_color=kBackgroundColor) while gui.running: for e in gui.get_events(): if e.key == gui.ESCAPE: gui.running = False elif e.key == gui.LMB: if e.type == gui.PRESS: last_mouse = tl.vec(*gui.get_cursor_pos()) else: mouse = tl.vec(*gui.get_cursor_pos()) diff = (mouse - last_mouse) * 2.0 add_particle_at(mouse.x, mouse.y, diff.x, diff.y) elif e.key == 'r': a = random.random() * math.tau add_particle_at(math.cos(a) * 0.4 + 0.5, math.sin(a) * 0.4 + 0.5, 0, 0) substep() if kUseImage: update_image() gui.set_image(image) else: gui.circles(particle_pos.to_numpy()[:n_particles[None]], radius=kParticleDisplaySize, color=kParticleColor) gui.show()

[ "1931127624@qq.com" ]

1931127624@qq.com

3f933be9bb65ede470247841a0737d4ef523395d

8d8c276f32dbc3917bb64fc5d1d0e83e5c4884ce

/interviewBit/math/primeSum.py

844de1eb6c7c84cd983b9f2a7e18096b5f4e2c98

[]

no_license

UddhavNavneeth/DSA-practice

a29b1ca27d72a1af36fb9e4d2e515ac00c99eb38

9f7d03145a8f026420a7e4672098f7c7a0361570

refs/heads/master

2021-06-22T08:09:08.590179

2021-03-12T07:11:10

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2020-10-01T07:06:15

2019-08-25T17:47:34

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py

# Link to the question: # https://www.interviewbit.com/problems/prime-sum/ def isPrime(a): for i in range(2,int(math.sqrt(a))+1): if a%i==0: return False return True class Solution: # @param A : integer # @return a list of integers def primesum(self, A): ans=[] for i in range(2,A//2+1): if (isPrime(i) and isPrime(A-i)): ans.append(i) ans.append(A-i) break return ans

[ "uddhav.navneeth@gmail.com" ]

uddhav.navneeth@gmail.com

50be32c063b21f51fb59e29080e17d63f03faeea

77c2010bb9533ecbdfa46cd41c16ee5ae26e94fa

/library/migrations/0001_initial.py

d100e69ebfc03b3f1d153433b33548151de3b8ec

[]

no_license

dimansion/portfolio-django

b2cbb28dff97dd03cdf795f0bc661d39bcfae83d

2dffe0e8579b2a426cb7aceb1ee085933b122d90

refs/heads/master

2020-05-23T08:15:38.205372

2017-03-05T14:44:14

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UTF-8

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py

# -*- coding: utf-8 -*- # Generated by Django 1.9 on 2016-10-09 06:20 from __future__ import unicode_literals from django.db import migrations, models import django.db.models.deletion import django.utils.timezone class Migration(migrations.Migration): initial = True dependencies = [ ] operations = [ migrations.CreateModel( name='Book', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('image', models.ImageField(blank=True, null=True, upload_to='')), ('author', models.CharField(max_length=128, unique=True)), ('title', models.CharField(max_length=200)), ('synopsis', models.TextField()), ('created_date', models.DateTimeField(default=django.utils.timezone.now)), ('published_date', models.DateTimeField(blank=True, null=True)), ('slug', models.SlugField()), ], ), migrations.CreateModel( name='Category', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('name', models.CharField(max_length=128, unique=True)), ('slug', models.SlugField()), ], ), migrations.AddField( model_name='book', name='category', field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.CASCADE, to='library.Category'), ), ]

[ "dimansional@gmail.com" ]

dimansional@gmail.com

75ca5aefe50b77509bfaaec7f261eccde8978151

02de8f705f354f0b130177621b886c7079e9c1d3

/Task_10.py

42d3053218a84b96e7bb7142e17ed914c1713d97

[]

no_license

yekeenfatai/basecamp

d528e7984ff5e48c59dceab73e266b6374bf8a7d

1b0bf11d8628167a6ea50460eff0cf6bd76bca28

refs/heads/master

2023-06-17T11:41:52.742260

2021-07-18T21:46:49

387,271,980

0

null

UTF-8

Python

false

972

py

def frequentChr(word): """frequentChr: accept a string as input and returns the most frquently occured element as dictionary""" #Verifying that the input is type string try: #To ensure that the parameter is a string not an array if (type(word) in [list,set,dict]): return f"Note!: {word} is {type(word)}, please input a string" new = {} #iterating through the input for i in word: #Updating the dictionary (new). if (i in new): new[i] += 1 else: new[i] = 1 #Geting the element(s) with the highest frquency maxValue = max(new.values()) arr = [] for i,j in new.items(): if j == maxValue: arr.append({i:j}) #returning a list of elements(s) return arr #Raising a warning when input is not string except: return f"Note! : {word} is {type(word)}, please enter a string"

[ "yekeenfatai10@gmail.com" ]

yekeenfatai10@gmail.com

9ac566e98381467e354fc7fd6819e02e8ea73f10

f9069ee014718a2d8e072a4a9490c4b5415a8760

/38.py

8c2efdc596fdec7d66bde8aa9f20651c95d42613

[]

no_license

subhashl7/subhashpython

1e74aa03576c55caccf4624837e2eff05289a2f4

7bb4eb050fe88da72cd672459ff0fe5b3d8962e9

refs/heads/master

2020-03-24T06:41:02.970001

2018-08-31T07:15:27

142,537,499

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null

UTF-8

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false

83

py

N,K = input().split() N,K = int(N),int(K) N = N ^ K K = N ^ K N = N ^ K print(N,K)

[ "noreply@github.com" ]

subhashl7.noreply@github.com