text stringlengths 0 1.05M | meta dict |
|---|---|
__author__ = 'lloy3317'
import re
import pprint
pp = pprint.PrettyPrinter(indent=4)
fileToRead = "./library-before/3.9custom/esri/css/esri.css"
saveToFile = "extract-urls-from-css.txt"
itemsArr = []
try:
with open(fileToRead, 'rb') as data:
fileContent = ""
for line in data:
fileC... | {
"repo_name": "lheberlie/grunt-optimizer-cleanup",
"path": "extract-urls.py",
"copies": "1",
"size": "1068",
"license": "apache-2.0",
"hash": 4365547295857204000,
"line_mean": 23.2954545455,
"line_max": 72,
"alpha_frac": 0.6039325843,
"autogenerated": false,
"ratio": 3.4563106796116503,
"config... |
__author__ = 'lloy3317'
import re, string
apiDirectoryName = "3.9custom"
#removeURL = "http://js.arcgis.com/3.9compact/"
removeURL = "http://heb.esri.com/js/playground-js/esrijs-playground/reduce-optimizer-sample/"
fileToRead = "app-traffic.har"
fileToSave = "api-files-to-keep.txt"
urlItems = []
try:
with ope... | {
"repo_name": "lheberlie/grunt-optimizer-cleanup",
"path": "parse_urls_from_har.py",
"copies": "1",
"size": "2106",
"license": "apache-2.0",
"hash": -4893123727009128000,
"line_mean": 32.9838709677,
"line_max": 110,
"alpha_frac": 0.5788224122,
"autogenerated": false,
"ratio": 3.551433389544688,
... |
'''@author: lockrecv@gmail.com'''
import json
from src.domain.Server import Server
class PowerOn:
'''Power On Configuration Utility'''
def __init__(self, cfile):
self.system_email = None
self.system_cc = []
self.monitor_servers = []
self.load(cfile)
def load(self, cfile):... | {
"repo_name": "ylcrow/poweron",
"path": "src/util/PowerOn.py",
"copies": "1",
"size": "1024",
"license": "mit",
"hash": 956048694717747500,
"line_mean": 26.7027027027,
"line_max": 80,
"alpha_frac": 0.55859375,
"autogenerated": false,
"ratio": 4.031496062992126,
"config_test": false,
"has_no_k... |
__author__ = 'loliveira'
from flask import g, jsonify
from flask_restful import Resource
from app import db
from conf.auth import auth
from app.resources import parser
from app.models.UserModel import Task
from datetime import date
class TaskResource(Resource):
@staticmethod
@auth.login_required
def ge... | {
"repo_name": "processos-2015-1/api",
"path": "app/resources/task_resource.py",
"copies": "1",
"size": "4201",
"license": "mit",
"hash": -2022878918279510500,
"line_mean": 30.3507462687,
"line_max": 217,
"alpha_frac": 0.5872411331,
"autogenerated": false,
"ratio": 4.039423076923077,
"config_tes... |
'''Author Lolmattylol
Creation date 08/09/2017
Verion No 1.01
Contact info reddit:lolmattylol
if you modify this for the better, please consider sharing with the community over at reddit.com/r/prisonarchitect
Version No Date of Change Author Change
1.00 08/09/2017 ... | {
"repo_name": "lolmattylol/DeathRowPrison",
"path": "DeathRowGUI.py",
"copies": "1",
"size": "2608",
"license": "mit",
"hash": -754029234337433500,
"line_mean": 39.3968253968,
"line_max": 351,
"alpha_frac": 0.6211656442,
"autogenerated": false,
"ratio": 3.2118226600985222,
"config_test": false,... |
__author__ = 'lolo'
"""
Django settings for taskbuster project.
Generated by 'django-admin startproject' using Django 1.8.
For more information on this file, see
https://docs.djangoproject.com/en/1.8/topics/settings/
For the full list of settings and their values, see
https://docs.djangoproject.com/en/1.8/ref/setti... | {
"repo_name": "jeuvreyl/taskbuster",
"path": "taskbuster/settings/base.py",
"copies": "1",
"size": "3365",
"license": "mit",
"hash": -6114638933714500000,
"line_mean": 24.6946564885,
"line_max": 71,
"alpha_frac": 0.6808320951,
"autogenerated": false,
"ratio": 3.5835995740149094,
"config_test": ... |
__author__ = "longboardtard"
__email__ = "ltjbour at gmail.com"
__copyright__ = "The MIT License (MIT)"
__copyright_link__ = "http://opensource.org/licenses/MIT"
from os.path import split, join, exists
from os import mkdir
class PurgeIRCLog(object):
"""This class allows you to remove certain lines from IRC logs... | {
"repo_name": "longboardtard/PurgeIRCLog",
"path": "purgeirclog.py",
"copies": "1",
"size": "3510",
"license": "mit",
"hash": 5405957077437158000,
"line_mean": 34.1,
"line_max": 91,
"alpha_frac": 0.6116809117,
"autogenerated": false,
"ratio": 4.228915662650603,
"config_test": false,
"has_no_k... |
__author__ = "Loran425"
class Node(object):
def __init__(self, value, left=None, right=None):
self.value = value
self.left = left
self.right = right
def reverse(self, recursive=False):
temp = self.left
self.left = self.right
self.right = temp
if recursi... | {
"repo_name": "DakRomo/2017Challenges",
"path": "challenge_4/python/Loran425/src/main.py",
"copies": "5",
"size": "1641",
"license": "mit",
"hash": -8306574628099491000,
"line_mean": 29.3888888889,
"line_max": 77,
"alpha_frac": 0.578305911,
"autogenerated": false,
"ratio": 3.3421588594704685,
"... |
__author__ = 'lorcan'
import string, httplib2
# Variables to hold file URLs
SPEECH_URL = "http://mf2.dit.ie/gettysburg.txt"
STOPWORDS_URL = "http://mf2.dit.ie/stopwords.txt"
def makeWordList(gFile, stopWords):
"""Create a list of words from the file while excluding stop words."""
speech = [] # list of spee... | {
"repo_name": "Eurus90/arch-configs-programming",
"path": "gettysburg/gettysburg.py",
"copies": "1",
"size": "3228",
"license": "mit",
"hash": 8501945330083896000,
"line_mean": 38.3780487805,
"line_max": 120,
"alpha_frac": 0.6381660471,
"autogenerated": false,
"ratio": 4.175937904269081,
"confi... |
__author__ = 'lorcan'
# get int from user
# get a base from user to convert int to
# get BASE_X string
# convert BASE_X string back to integer
# get int from user
myStr = input("Enter an integer to convert binary: ")
myInt = int(myStr)
# get a base from user to convert int to
baseStr = input("\nChoose Base 2,8,16 t... | {
"repo_name": "Eurus90/arch-configs-programming",
"path": "Integer_Binary_conversion/integer_binary_conversion.py",
"copies": "1",
"size": "1288",
"license": "mit",
"hash": -1022023615629452400,
"line_mean": 22.8518518519,
"line_max": 55,
"alpha_frac": 0.5760869565,
"autogenerated": false,
"ratio... |
__author__ = 'lorenzo'
from flankers.tagmeapi.tagMeService import TagMeService
from flankers.tools import retrieve_json
def find_related_concepts(text):
"""
Find related concept in taxonomy from a text
:param text: a given abstract or title
:return: a list of taxonomy keywords (see http://taxonomy.pr... | {
"repo_name": "mr-niels-christensen/rdfendpoints",
"path": "flankers/textsemantics.py",
"copies": "3",
"size": "2503",
"license": "apache-2.0",
"hash": -1502121893421519400,
"line_mean": 33.2876712329,
"line_max": 111,
"alpha_frac": 0.5960846984,
"autogenerated": false,
"ratio": 3.929356357927786... |
__author__ = 'lorenzo'
from pymongo import MongoClient
from config.config import _CRAWLING_POST, _TEMP_SECRET
def dump_articles():
connection = MongoClient('localhost', 27017)
db = connection.PTEST_BACKUP
results = db.crawling.find({}, {'_id': False})
"""
{
"_id" : ObjectId("54dd29... | {
"repo_name": "mr-niels-christensen/rdfendpoints",
"path": "scripts/remote/uploadmongo.py",
"copies": "3",
"size": "1333",
"license": "apache-2.0",
"hash": -8516284729905603000,
"line_mean": 30.023255814,
"line_max": 114,
"alpha_frac": 0.6166541635,
"autogenerated": false,
"ratio": 3.235436893203... |
__author__ = 'lorenzo'
import random
import uuid
from datagenerator.generator import generate_object
class SubSystem(object):
name = None
def __init__(self, attrs):
"""
Factory for subsystems components
:param attrs: a dictionary with the instance attributes
"""
for... | {
"repo_name": "Mec-iS/chronostriples-backup",
"path": "scripts/factory.py",
"copies": "3",
"size": "6563",
"license": "apache-2.0",
"hash": 6567881947368565000,
"line_mean": 31.1764705882,
"line_max": 123,
"alpha_frac": 0.5527959774,
"autogenerated": false,
"ratio": 4.0437461491065925,
"config_... |
__author__ = 'lorenzo'
import webapp2
import json
from flankers.errors import format_message
from config.config import _HYDRA_VOCAB, _SERVICE
_CONTENT_TYPE = 'application/ld+json'
class HydraVocabulary(webapp2.RequestHandler):
def get(self):
"""
publish the HYDRA ApiDocumentation vocabulary
... | {
"repo_name": "mr-niels-christensen/rdfendpoints",
"path": "hydra/handlers.py",
"copies": "3",
"size": "5768",
"license": "apache-2.0",
"hash": -7147001760902149000,
"line_mean": 44.0703125,
"line_max": 161,
"alpha_frac": 0.5806171983,
"autogenerated": false,
"ratio": 4.149640287769784,
"config... |
__author__ = 'Lothas'
import sys
import os
# Get parent directory by joining this file's path [os.path.dirname(os.path.abspath(__file__))] with '..' [os.pardir]
parentDir = os.path.abspath(os.path.dirname(os.path.abspath(__file__))+'\\'+os.pardir)
sys.path.insert(0, parentDir) # Add the parent directory where 'vrep' ... | {
"repo_name": "lothas/vrep-python-ai",
"path": "TEST-line-follower/RunTrial.py",
"copies": "1",
"size": "2990",
"license": "mit",
"hash": 304070548945291650,
"line_mean": 32.2222222222,
"line_max": 117,
"alpha_frac": 0.6712374582,
"autogenerated": false,
"ratio": 2.786579683131407,
"config_test... |
__author__ = 'Lothilius'
# coding: utf-8
from sqlalchemy import BigInteger, Column, Date, DateTime, Enum, Float, Index, Integer, Numeric, SmallInteger, String, Text, VARBINARY, text
from sqlalchemy.ext.declarative import declarative_base
from datetime import datetime, timedelta
Base = declarative_base()
metadata = Ba... | {
"repo_name": "Lothilius/oiPy",
"path": "Pyoi.py",
"copies": "1",
"size": "44528",
"license": "mit",
"hash": -1676867831684835600,
"line_mean": 42.484375,
"line_max": 140,
"alpha_frac": 0.6757096658,
"autogenerated": false,
"ratio": 3.327952167414051,
"config_test": false,
"has_no_keywords": ... |
__author__ = 'Lothilius'
from selenium import webdriver, common
from authentication import salesforce_login_staging
import sys
baseurl = "https://cs13.salesforce.com/500W000000329Pb"
browser = webdriver.Firefox()
browser.get(baseurl)
browser.maximize_window()
username, pw = salesforce_login_staging()
# Login func... | {
"repo_name": "Lothilius/BizApps_Se-Testing",
"path": "base.py",
"copies": "1",
"size": "2449",
"license": "mit",
"hash": 853576611783827500,
"line_mean": 28.5060240964,
"line_max": 115,
"alpha_frac": 0.6953858718,
"autogenerated": false,
"ratio": 3.382596685082873,
"config_test": false,
"has... |
__author__ = 'Lothilius'
from selenium.webdriver.support.select import Select
from selenium import webdriver, common
from authentication import salesforce_login_staging
import sys
import string
import random
baseurl = "https://cs13.salesforce.com/005?retURL=%2Fui%2Fsetup%2FSetup%3Fsetupid%3DUsers&setupid=ManageUsers"... | {
"repo_name": "Lothilius/BizApps_Se-Testing",
"path": "contact_creation.py",
"copies": "1",
"size": "5144",
"license": "mit",
"hash": 9136601377198232000,
"line_mean": 32.1870967742,
"line_max": 110,
"alpha_frac": 0.6518273717,
"autogenerated": false,
"ratio": 3.4523489932885907,
"config_test":... |
__author__ = 'Lothilius'
from sqlalchemy.orm import sessionmaker
from sqlalchemy import desc
from Pyoi import *
from authentication import mysql_engine_prod, mysql_engine_test
import numpy as np
import random
import sys
like_start = current_time.strftime('%Y-%m-%d %H:%M:%S')
user_id = 13
def start_up_engine(enviro... | {
"repo_name": "Lothilius/oiPy",
"path": "Event_count.py",
"copies": "1",
"size": "2139",
"license": "mit",
"hash": -1813891568590823700,
"line_mean": 24.1647058824,
"line_max": 92,
"alpha_frac": 0.6428237494,
"autogenerated": false,
"ratio": 3.5413907284768213,
"config_test": false,
"has_no_k... |
__author__ = 'Lothilius'
import csv
import os
import numpy as np
import matplotlib.pyplot as plt
import skimage as ski
import math
import getpass
import time
from skimage import data, filter
from skimage.color import rgb2gray
from skimage.transform import hough_circle
from skimage.feature import peak_local_max
from s... | {
"repo_name": "Lothilius/thezeemancometh",
"path": "Zeeman.py",
"copies": "1",
"size": "28380",
"license": "mit",
"hash": -717271526736205000,
"line_mean": 33.568818514,
"line_max": 136,
"alpha_frac": 0.6187103594,
"autogenerated": false,
"ratio": 3.126928162185985,
"config_test": false,
"has... |
__author__ = 'lothilius'
import csv
import os
import numpy as np
import matplotlib.pyplot as plt
#Pull data from CSV file
def arrayFromFile(filename):
"""Given an external file containing numbers,
create an array from those numbers."""
dataArray = []
with open(filename, 'r+') as csvfile:
... | {
"repo_name": "Lothilius/ortho-positronium",
"path": "monty.py",
"copies": "1",
"size": "4582",
"license": "mit",
"hash": -3029414494854184400,
"line_mean": 24.8870056497,
"line_max": 110,
"alpha_frac": 0.6126145788,
"autogenerated": false,
"ratio": 3.5880971025841815,
"config_test": false,
"... |
__author__ = 'Lothilius'
import json
import unicodedata
import authentication as oath
import re
from datetime import datetime
import urllib2
import numpy as np
url = 'https://graph.facebook.com/v2.2/100004568139047/events/not_replied?fields=id&limit=200'
response = oath.twitterreq(url)
message = json.load(response)
... | {
"repo_name": "Lothilius/oiPy",
"path": "fb_grab_events.py",
"copies": "1",
"size": "4485",
"license": "mit",
"hash": 3232095711468115000,
"line_mean": 33.5,
"line_max": 125,
"alpha_frac": 0.5342251951,
"autogenerated": false,
"ratio": 4.092153284671533,
"config_test": false,
"has_no_keywords... |
__author__ = 'lovci'
from six.moves import urllib as urllib
import sqlite3
import os
class Scraper(object):
base_url = None
source = "unknown"
def store(self, identifier, page, source=None):
if source is None:
source = self.source
self.db_con.execute('INSERT INTO Webdata VAL... | {
"repo_name": "mlovci/bioscraping",
"path": "bioscraping/_base.py",
"copies": "1",
"size": "1382",
"license": "mit",
"hash": 4319896766671592000,
"line_mean": 28.4042553191,
"line_max": 105,
"alpha_frac": 0.6041968162,
"autogenerated": false,
"ratio": 3.971264367816092,
"config_test": false,
... |
__author__ = 'lovci'
import Bio
from diff_binding.core import encoding
def maf2Dict(multipleAlignment, id = None):
"""
store multiple-alignment information
in a dictionary
"""
data = dict()
chrom = multipleAlignment[0].id.split(".")[1]
genome_start = multipleAlignment[0].annotations['sta... | {
"repo_name": "YeoLab/gscripts",
"path": "gscripts/conservation/maf_mucking.py",
"copies": "1",
"size": "1331",
"license": "mit",
"hash": -8937477054211451000,
"line_mean": 34.0526315789,
"line_max": 93,
"alpha_frac": 0.6326070624,
"autogenerated": false,
"ratio": 3.6366120218579234,
"config_te... |
__author__ = 'lovci'
"""a tool to extract ranges from indexed .maf file, adapted from bx-python / scripts / maf_tile.py and \
http://biopython.org/wiki/Phylo_cookbook"""
import bx
import bx.align.maf
from Bio import Phylo
import pyfasta
from collections import defaultdict
import os, sys
import socket
if "tscc" in s... | {
"repo_name": "YeoLab/gscripts",
"path": "gscripts/conservation/maf_handler.py",
"copies": "1",
"size": "7886",
"license": "mit",
"hash": 4474757115412179500,
"line_mean": 37.8472906404,
"line_max": 113,
"alpha_frac": 0.5621354299,
"autogenerated": false,
"ratio": 3.4801412180052957,
"config_te... |
__author__ = 'lovci'
import matplotlib
import pylab
import numpy as np
import pandas as pd
import itertools
import seaborn
seaborn.set_style({'axes.axisbelow': True,
'axes.edgecolor': '.15',
'axes.facecolor': 'white',
'axes.grid': False,
'axes.labelc... | {
"repo_name": "YeoLab/gscripts",
"path": "gscripts/general/analysis_tools.py",
"copies": "1",
"size": "16605",
"license": "mit",
"hash": -6253131048799558000,
"line_mean": 39.5,
"line_max": 118,
"alpha_frac": 0.5834387233,
"autogenerated": false,
"ratio": 4.07985257985258,
"config_test": false,... |
__author__ = 'lp1osti'
from fJmodel.fJmodel import FJmodel
from fJmodel.kindata import KinData
from fJmodel.sauron import sauron
import numpy as np
import matplotlib.pylab as plt
import matplotlib.gridspec as gridspec
def plot3galaxies():
# get the data
k1 = KinData('/Users/lp1osti/Dropbox/fJ_CALIFA/data/N... | {
"repo_name": "lposti/pyfJmod",
"path": "plot.py",
"copies": "1",
"size": "5521",
"license": "bsd-3-clause",
"hash": -6950474143932455000,
"line_mean": 44.2540983607,
"line_max": 113,
"alpha_frac": 0.5578699511,
"autogenerated": false,
"ratio": 2.7010763209393347,
"config_test": false,
"has_n... |
__author__ = 'lqrz'
import codecs
import logging
import glob
import sys
logger = logging.getLogger('')
hdlr = logging.FileHandler('decompoundingEvaluation.log')
formatter = logging.Formatter('%(asctime)s %(levelname)s %(message)s')
hdlr.setFormatter(formatter)
logger.addHandler(hdlr)
logger.setLevel(logging.DEBUG)
if... | {
"repo_name": "jodaiber/semantic_compound_splitting",
"path": "visualization_and_test/evaluateDecompounding.py",
"copies": "1",
"size": "6816",
"license": "apache-2.0",
"hash": 5682791659761857000,
"line_mean": 37.2921348315,
"line_max": 172,
"alpha_frac": 0.5790786385,
"autogenerated": false,
"r... |
__author__ = 'lqrz'
import codecs
import logging
# import glob
import sys
logger = logging.getLogger('')
hdlr = logging.FileHandler('decompoundingEvaluation.log')
formatter = logging.Formatter('%(asctime)s %(levelname)s %(message)s')
hdlr.setFormatter(formatter)
logger.addHandler(hdlr)
logger.setLevel(logging.DEBUG)
... | {
"repo_name": "jodaiber/semantic_compound_splitting",
"path": "visualization_and_test/evaluateMosesDecompounding.py",
"copies": "1",
"size": "4246",
"license": "apache-2.0",
"hash": 4365826757861938700,
"line_mean": 36.9196428571,
"line_max": 142,
"alpha_frac": 0.5984455959,
"autogenerated": false,... |
__author__ = 'lqrz'
import codecs
import sys
if __name__ == '__main__':
# mosesResults = 'MT/mosesCompound_full_results' #TODO:hardcoded
# outFile = 'MT/pastedResults_mod' #TODO:hardcoded
if len(sys.argv)==3:
mosesResults = sys.argv[1]
outFile = sys.argv[2]
elif len(sys.argv)>1:
... | {
"repo_name": "jodaiber/semantic_compound_splitting",
"path": "visualization_and_test/preprocessMosesDecompounding.py",
"copies": "1",
"size": "1104",
"license": "apache-2.0",
"hash": -95343220095210740,
"line_mean": 28.8648648649,
"line_max": 68,
"alpha_frac": 0.5226449275,
"autogenerated": false,... |
__author__ = 'lqrz'
import cPickle as pickle
import gensim
import itertools
import random
from annoy import AnnoyIndex
import sys
import argparse
import time
import datetime
import numpy as np
import threading
import Queue
def timestamp():
return datetime.datetime.fromtimestamp(time.time()).strftime('%Y-%m-%d %H... | {
"repo_name": "jodaiber/semantic_compound_splitting",
"path": "visualization_and_test/evaluate_candidates_mt.py",
"copies": "1",
"size": "5396",
"license": "apache-2.0",
"hash": 6509282020002703000,
"line_mean": 31.703030303,
"line_max": 138,
"alpha_frac": 0.6375092661,
"autogenerated": false,
"r... |
__author__ = 'lqrz'
import os
import sys
from sklearn.decomposition import PCA as sklearnPCA
from matplotlib import pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
from mpl_toolkits.mplot3d import proj3d
import numpy as np
import pickle
import random
from nltk import FreqDist
from nltk.corpus import PlaintextCor... | {
"repo_name": "jodaiber/semantic_compound_splitting",
"path": "visualization_and_test/pca.py",
"copies": "1",
"size": "6611",
"license": "apache-2.0",
"hash": -6017394135225718000,
"line_mean": 26.8945147679,
"line_max": 103,
"alpha_frac": 0.5906821963,
"autogenerated": false,
"ratio": 3.13020833... |
__author__ = 'lren'
from apiclient.discovery import build
import base64
class sourceServer(object):
SOURCE_DISCOVERY_SERVICE_URL = "https://annoserver-test.appspot.com/_ah/api/discovery/v1/apis/copy_api/v1/rest"
source_server = build("copy_api", "v1", discoveryServiceUrl=SOURCE_DISCOVERY_SERVICE_URL)
ite... | {
"repo_name": "usersource/tasks",
"path": "tasks_phonegap/Tasks/cordova/plugins/io.usersource.anno/tools/copytool3/copytool2.py",
"copies": "3",
"size": "5284",
"license": "mpl-2.0",
"hash": 8235259084837916000,
"line_mean": 40.6062992126,
"line_max": 125,
"alpha_frac": 0.6118470855,
"autogenerated... |
__author__ = 'lselvy'
from data_services.models import BaseFactData, DimExecution, DimRun, DimReplication, DimChannel
from django.core.exceptions import ObjectDoesNotExist
from django.db.models.query import QuerySet
import json
import time
import itertools
class RunData(object):
"""
This is the RunData Class.... | {
"repo_name": "vecnet/vnetsource",
"path": "data_services/utils/run_data.py",
"copies": "2",
"size": "20025",
"license": "mpl-2.0",
"hash": -8341748405936263000,
"line_mean": 43.5,
"line_max": 164,
"alpha_frac": 0.5375780275,
"autogenerated": false,
"ratio": 4.551136363636363,
"config_test": fa... |
__author__ = 'lsteng'
# Copyright 2015 SICS Swedish ICT AB
#
# 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 applic... | {
"repo_name": "nigsics/perf-kvm",
"path": "guest-client/command_parse.py",
"copies": "1",
"size": "3504",
"license": "apache-2.0",
"hash": 3721598719651088400,
"line_mean": 32.380952381,
"line_max": 264,
"alpha_frac": 0.6198630137,
"autogenerated": false,
"ratio": 3.727659574468085,
"config_tes... |
__author__ = 'Lstevens'
import os
import errno
import re
import argparse
import textwrap
from PIL import ImageFont
from PIL import Image
from PIL import ImageDraw
from xlrd import open_workbook
"""
Creates image files with xlsform question text.
Run on command line with "-f" parameter which is path to xlsform file.
... | {
"repo_name": "VinACE/openclinica_scripts",
"path": "xlsform_images/xlsform_images.py",
"copies": "1",
"size": "9789",
"license": "mit",
"hash": -2213388204877450500,
"line_mean": 38.3172690763,
"line_max": 80,
"alpha_frac": 0.6122177955,
"autogenerated": false,
"ratio": 3.890699523052464,
"con... |
__author__ = 'Lstevens'
# stdlib modules
from xml.etree import ElementTree as et
import hashlib
import re
import logging
# pypi modules
import requests
import xmltodict
logging.basicConfig(
filename='webservices.log',
format='%(asctime)s | %(levelname)s | %(name)s | %(funcName)s | Line:%(lineno)d | %... | {
"repo_name": "VinACE/openclinica_scripts",
"path": "webservices/python/oc_webservices.py",
"copies": "2",
"size": "24311",
"license": "mit",
"hash": 2464724185090012700,
"line_mean": 40.4173764906,
"line_max": 103,
"alpha_frac": 0.6017852001,
"autogenerated": false,
"ratio": 3.861340533672173,
... |
__author__ = 'Lstevens'
# stdlib
import unittest
import collections
import datetime
import uuid
# local
import oc_webservices
"""
These objects are used by oc_ws_test to create common tests and set common
value used by the oc_ws_test tests. The GenericCallFailures TestCase will not
run on its own, it requires that t... | {
"repo_name": "lindsay-stevens-kirby/openclinica_scripts",
"path": "webservices/python/oc_ws_test_generic.py",
"copies": "2",
"size": "14951",
"license": "mit",
"hash": -8049799275842070000,
"line_mean": 42.9764705882,
"line_max": 98,
"alpha_frac": 0.5947428266,
"autogenerated": false,
"ratio": 3... |
__author__ = 'Lstevens'
import os
import errno
import re
import argparse
import textwrap
from PIL import ImageFont
from PIL import Image
from PIL import ImageDraw
from xlrd import open_workbook
"""
Creates image files with xlsform question text.
Run on command line with "-f" parameter which is path to... | {
"repo_name": "lindsay-stevens-kirby/openclinica_scripts",
"path": "xlsform_images/xlsform_images.py",
"copies": "1",
"size": "10117",
"license": "mit",
"hash": -5853454334801502000,
"line_mean": 38.476,
"line_max": 80,
"alpha_frac": 0.5983987348,
"autogenerated": false,
"ratio": 3.96123727486296... |
__author__ = "Luc Anselin luc.anselin@asu.edu, \
Pedro V. Amaral pedro.amaral@asu.edu, \
David C. Folch david.folch@asu.edu"
import numpy as np
import numpy.linalg as la
from pysal import lag_spatial
from utils import spdot, spbroadcast
from user_output import check_constant
def robust_vm(reg, gwk=Non... | {
"repo_name": "google-code-export/pysal",
"path": "pysal/spreg/robust.py",
"copies": "5",
"size": "5079",
"license": "bsd-3-clause",
"hash": 1925723912866846200,
"line_mean": 30.3518518519,
"line_max": 117,
"alpha_frac": 0.5369167159,
"autogenerated": false,
"ratio": 2.9511911679256246,
"config... |
__author__ = "Luc Anselin luc.anselin@asu.edu, \
Pedro V. Amaral pedro.amaral@asu.edu, \
David C. Folch david.folch@asu.edu"
import numpy as np
import numpy.linalg as la
from pysal.lib.weights.spatial_lag import lag_spatial
from .utils import spdot, spbroadcast
from .user_output import check_constant
... | {
"repo_name": "lixun910/pysal",
"path": "pysal/model/spreg/robust.py",
"copies": "1",
"size": "5306",
"license": "bsd-3-clause",
"hash": -6143841669241517000,
"line_mean": 30.3964497041,
"line_max": 132,
"alpha_frac": 0.5422163588,
"autogenerated": false,
"ratio": 2.9105869445968184,
"config_te... |
from math import sqrt
from numbers import Number
from sys import exit
# Define the class.
class Quadratic:
def __add__(self, other): # Add quadratics.
a,b,c = [m + n for m,n in zip(self.coeffs, other.coeffs)]
return Quadratic(a, b, c)
def f(self, x):
a,b,c = [n for n in self.coeffs]
return ... | {
"repo_name": "h93xV2/Miscellaneous",
"path": "Math/Quadratic/quadratic.py",
"copies": "1",
"size": "2459",
"license": "mit",
"hash": -8735423609211299000,
"line_mean": 31.3552631579,
"line_max": 71,
"alpha_frac": 0.5851972346,
"autogenerated": false,
"ratio": 2.769144144144144,
"config_test": ... |
__author__ = 'Lucas Ou-Yang'
# -*- coding: utf-8 -*-
import json
from django.shortcuts import render_to_response, RequestContext
from django.http import HttpResponse, Http404
from link.models import Link
from socialrank.settings import get_root_url
LINK_DELIM = "&$$"
def render_with_context(request, template, co... | {
"repo_name": "codelucas/socialrank",
"path": "link/views.py",
"copies": "1",
"size": "2169",
"license": "apache-2.0",
"hash": -5226822411086594000,
"line_mean": 23.9425287356,
"line_max": 66,
"alpha_frac": 0.5638543107,
"autogenerated": false,
"ratio": 4.203488372093023,
"config_test": false,
... |
__author__ = 'Lucas Ou-Yang'
from django.db import models
from django.utils import timezone
from datetime import datetime
# -*- coding: utf-8 -*-
class Link(models.Model):
"""
abstraction of a web link
likes are the # of facebook shares that
any particular url has.
located @: http://graph.facebo... | {
"repo_name": "codelucas/socialrank",
"path": "link/models.py",
"copies": "1",
"size": "3156",
"license": "apache-2.0",
"hash": -861039630756139100,
"line_mean": 27.1875,
"line_max": 66,
"alpha_frac": 0.5560836502,
"autogenerated": false,
"ratio": 3.905940594059406,
"config_test": false,
"has... |
__author__ = 'Lucas Schuermann'
from baseneuron import BaseNeuron
import numpy as np
import pycuda.gpuarray as garray
from pycuda.tools import dtype_to_ctype
import pycuda.driver as cuda
from pycuda.compiler import SourceModule
import os.path
import neurokernel.LPU.neurons as neurons
class HodgkinHuxley_Euler(BaseNe... | {
"repo_name": "cerrno/neurokernel",
"path": "neurokernel/LPU/neurons/HodgkinHuxley_Euler.py",
"copies": "1",
"size": "3774",
"license": "bsd-3-clause",
"hash": -7837788410782808000,
"line_mean": 38.3125,
"line_max": 83,
"alpha_frac": 0.59936407,
"autogenerated": false,
"ratio": 3.050929668552951,... |
__author__ = 'luchenhua'
EtoF = {'bread': 'du pain', 'wine': 'du vin', 'eats': 'mange', 'drinks': 'bois', 'likes': 'aime', 1: 'un',
'6.00': '6.00'}
print(EtoF)
print(EtoF.keys())
print(EtoF.keys)
del EtoF[1]
print(EtoF)
def translateWord(word, dictionary):
if word in dictionary:
return dictionary... | {
"repo_name": "luchenhua/MIT-OCW-600",
"path": "src/lect06.py",
"copies": "1",
"size": "2011",
"license": "mit",
"hash": 6120141481359215000,
"line_mean": 17.2818181818,
"line_max": 106,
"alpha_frac": 0.5251118846,
"autogenerated": false,
"ratio": 2.785318559556787,
"config_test": false,
"has... |
__author__ = 'luchenhua'
def withinEpsilon(x, y, epsilon):
return abs(x - y) <= epsilon
print(withinEpsilon(2, 3, 1))
def f(x):
x += 1
print('x = ', x)
return x
x = 3
z = f(x)
print('z =', z)
print('x =', x)
def f1(x):
def g():
x = 'abc'
print('x =', x)
x += 1
prin... | {
"repo_name": "luchenhua/MIT-OCW-600",
"path": "src/lect04.py",
"copies": "1",
"size": "1294",
"license": "mit",
"hash": -6690646528331457000,
"line_mean": 16.0263157895,
"line_max": 77,
"alpha_frac": 0.4899536321,
"autogenerated": false,
"ratio": 2.88195991091314,
"config_test": false,
"has_... |
__author__ = 'luchenhua'
x = 100
divisors = ()
print(divisors)
for i in range(1, x):
if x % i == 0:
divisors = divisors + (i,)
print(divisors)
print(divisors)
print(divisors[0] + divisors[1])
print(divisors[2:4])
Techs = ['MIT', 'Cal Tech']
Ivys = ['Harvard', 'Yale', 'Brown']
Univs = []
Univs.app... | {
"repo_name": "luchenhua/MIT-OCW-600",
"path": "src/lect05.py",
"copies": "1",
"size": "2132",
"license": "mit",
"hash": 4648036331703998000,
"line_mean": 16.1935483871,
"line_max": 106,
"alpha_frac": 0.5530018762,
"autogenerated": false,
"ratio": 2.302375809935205,
"config_test": false,
"has... |
__author__ = 'Lucian'
from const import values, fibonacci_weight
# intel quad core i7 3770k, average speed of check 56000 combinations of cards per second
# For proper operation of these methods need to sort descending cards (method sort_high_to_low into sort.py)
# No checks for invalid or missing card, you shoul... | {
"repo_name": "nodermann/holdem_poker_combinations",
"path": "poker_combinations.py",
"copies": "1",
"size": "4844",
"license": "mit",
"hash": 8314471976923660000,
"line_mean": 30.9659863946,
"line_max": 128,
"alpha_frac": 0.4948389761,
"autogenerated": false,
"ratio": 3.3545706371191137,
"conf... |
__author__ = 'Ludmal.DESILVA'
from lxml import html
import re
import image_parser
import logging
extract_patterns = 'id:articleImage|' \
'id:displayFrame|' \
'class:cnnArticleGalleryPhotoContainer|' \
'class:article-entry|' \
'class:storyBody... | {
"repo_name": "ludmal/pylib",
"path": "html_parser.py",
"copies": "1",
"size": "4453",
"license": "mit",
"hash": -330531368095289860,
"line_mean": 24.591954023,
"line_max": 85,
"alpha_frac": 0.5187514035,
"autogenerated": false,
"ratio": 3.59983831851253,
"config_test": false,
"has_no_keyword... |
__author__ = 'Ludmal.DESILVA'
import os, email, smtplib
from email.mime.text import MIMEText
from email.mime.multipart import MIMEMultipart
from email.mime.application import MIMEApplication
path = os.path.dirname(__file__)
#modify this to change the Template Directory
TEMPLATE_DIR = '/templates/'
class EmailTempla... | {
"repo_name": "ludmal/pylib",
"path": "mail.py",
"copies": "1",
"size": "3499",
"license": "mit",
"hash": -7846322134993492000,
"line_mean": 34.3434343434,
"line_max": 132,
"alpha_frac": 0.6133180909,
"autogenerated": false,
"ratio": 3.9536723163841807,
"config_test": false,
"has_no_keywords"... |
__author__ = 'lugan'
class EightQueen():
def __init__(self):
self.chess = []
self.nextLevel = True
self.count = 0
def isConflict(self, sourceIndex, targetIndex, targetValue):
if sourceIndex == targetIndex:
return True
if self.chess[sourceIndex] == targetV... | {
"repo_name": "linewx/anticyclone",
"path": "anticyclone/exam/eightqueen.py",
"copies": "1",
"size": "2842",
"license": "apache-2.0",
"hash": -5724218385081544000,
"line_mean": 23.9298245614,
"line_max": 88,
"alpha_frac": 0.5024630542,
"autogenerated": false,
"ratio": 3.9472222222222224,
"confi... |
__author__ = 'lugan'
class Vertex():
def __init__(self, value):
self.value = value
self.processed = False
self.discovered = False
self.distance = float('Inf')
self.startTime = None
self.endTime = None
def clean(self):
self.processed = False
self.... | {
"repo_name": "linewx/anticyclone",
"path": "anticyclone/clrs/graph.py",
"copies": "1",
"size": "6311",
"license": "apache-2.0",
"hash": -8068544641987877000,
"line_mean": 25.8553191489,
"line_max": 95,
"alpha_frac": 0.5764538108,
"autogenerated": false,
"ratio": 3.893275755706354,
"config_test... |
__author__ = 'lugan'
from datetime import datetime
def steps(n:int):
if n == 1:
return 1
if n == 2:
return 2
else:
return steps(n-1) + steps(n-2)
def bottomUpSteps(n:int):
steps = {1:1, 2:2}
for i in range(3,n+1):
steps[i] = steps[i-1] + steps[i-2]
return ste... | {
"repo_name": "linewx/anticyclone",
"path": "anticyclone/exam/dp.py",
"copies": "1",
"size": "1081",
"license": "apache-2.0",
"hash": -2931330706203512000,
"line_mean": 17.3220338983,
"line_max": 42,
"alpha_frac": 0.5078630897,
"autogenerated": false,
"ratio": 3.0195530726256985,
"config_test":... |
__author__ = 'lugan'
import math
class Sort():
def sort(self, list_object:list, reverse:bool=False):
pass
class InsertionSort(Sort):
def sort(self, list_object:list, reverse:bool=False):
toSortList = list(list_object)
for x in range(1, len(toSortList)):
key = toSortList[x... | {
"repo_name": "linewx/anticyclone",
"path": "anticyclone/clrs/sort.py",
"copies": "1",
"size": "6306",
"license": "apache-2.0",
"hash": 5893880584696796000,
"line_mean": 29.4685990338,
"line_max": 84,
"alpha_frac": 0.5444021567,
"autogenerated": false,
"ratio": 3.6303972366148534,
"config_test"... |
__author__ = 'lugan'
"""
"""
class MergeSort():
def sort(self, list_object:list, reversePair:list):
if len(list_object) <= 1:
return list(list_object)
else:
n = int(len(list_object)/2)
pSortedList = self.sort(list_object[:n], reversePair)
sSortedLi... | {
"repo_name": "linewx/anticyclone",
"path": "anticyclone/exam/chapter2_4.py",
"copies": "1",
"size": "1233",
"license": "apache-2.0",
"hash": 4699558116383562000,
"line_mean": 26.4222222222,
"line_max": 78,
"alpha_frac": 0.5166261152,
"autogenerated": false,
"ratio": 3.3505434782608696,
"config... |
__author__ = 'luigolas'
from package.image_set import ImageSet
import re
from sklearn.cross_validation import ShuffleSplit
from itertools import chain
from sklearn.utils import safe_indexing
import numpy as np
class Dataset(object):
"""
:param probe:
:param gallery:
:param train_size:
:param test... | {
"repo_name": "Luigolas/PyReID",
"path": "package/dataset.py",
"copies": "1",
"size": "6818",
"license": "mit",
"hash": 3127932456547076000,
"line_mean": 35.6559139785,
"line_max": 120,
"alpha_frac": 0.5775887357,
"autogenerated": false,
"ratio": 3.5017976373908577,
"config_test": true,
"has_... |
__author__ = 'luigolas'
import numpy as np
from itertools import islice, takewhile, count
import sys
import time
def safe_ln(x, minval=0.0000000001):
return np.log(x.clip(min=minval))
def status(percent, flush=True):
sys.stdout.write("%3d%%\r" % percent)
if flush:
sys.stdout.flush()
else:
... | {
"repo_name": "Luigolas/PyReID",
"path": "package/utilities.py",
"copies": "1",
"size": "2474",
"license": "mit",
"hash": -129015082243109090,
"line_mean": 20.5217391304,
"line_max": 82,
"alpha_frac": 0.5578011318,
"autogenerated": false,
"ratio": 3.4171270718232045,
"config_test": false,
"ha... |
__author__ = 'luigolas'
import numpy as np
from scipy.stats import cumfreq
class Statistics():
"""
Position List: for each element in probe, find its same ids in gallery. Format: np.array([[2,14],[1,2],...])
Mean List: Calculate means of position list by axis 0. Format: np.array([1.52, 4.89])
Mode_li... | {
"repo_name": "Luigolas/PyReID",
"path": "package/statistics.py",
"copies": "1",
"size": "4681",
"license": "mit",
"hash": -4135605483136304000,
"line_mean": 36.448,
"line_max": 120,
"alpha_frac": 0.5671864986,
"autogenerated": false,
"ratio": 3.5515933232169954,
"config_test": true,
"has_no_... |
__author__ = 'luigolas'
import numpy as np
import cv2
from package.utilities import safe_ln, FileNotFoundError
# from package.app import DB
CS_IIP = 1
CS_BGR = 2
CS_HSV = 3
CS_YCrCb = 4
colorspace_name = ["", "IIP", "BGR", "HSV", "YCrCb"]
iipA = np.asarray([[27.07439, -0.2280783, -1.806681],
[-5.... | {
"repo_name": "Luigolas/PyReID",
"path": "package/image.py",
"copies": "1",
"size": "6013",
"license": "mit",
"hash": 3063440526375903000,
"line_mean": 31.8579234973,
"line_max": 96,
"alpha_frac": 0.5762514552,
"autogenerated": false,
"ratio": 3.1865394806571277,
"config_test": false,
"has_no... |
__author__ = 'luigolas'
import os
from package.image import Image
from package.utilities import ImagesNotFoundError, NotADirectoryError
class ImageSet(object):
def __init__(self, folder_name, name_ids=2):
self.path = ImageSet._valid_directory(folder_name)
self.name = "_".join(self.path.split("/")... | {
"repo_name": "Luigolas/PyReID",
"path": "package/image_set.py",
"copies": "1",
"size": "2387",
"license": "mit",
"hash": -825669467288118400,
"line_mean": 30.4078947368,
"line_max": 82,
"alpha_frac": 0.5643066611,
"autogenerated": false,
"ratio": 3.776898734177215,
"config_test": true,
"has_... |
__author__ = 'luissaguas'
import frappe
from frappe import _
from jasper_erpnext_report.utils.utils import jaspersession_get_value,get_expiry_in_seconds,\
get_jasper_data, get_jasper_session_expiry_seconds, getFrappeVersion
from jasper_erpnext_report.utils.file import remove_directory
#call from bench frappe --pyth... | {
"repo_name": "saguas/jasper_erpnext_report",
"path": "jasper_erpnext_report/utils/scheduler.py",
"copies": "1",
"size": "9611",
"license": "mit",
"hash": 5201823479195407000,
"line_mean": 27.4378698225,
"line_max": 147,
"alpha_frac": 0.7021121631,
"autogenerated": false,
"ratio": 2.8638259833134... |
__author__ = 'luissaguas'
import frappe, os, re
import fluorine as fluor
"""
client file loader
for each module read files with extension js
special atention to files in client/compatibility
ignore files in tests, in public in private and server
files in lib first and inside lib alphabetic order
other folders deepest... | {
"repo_name": "saguas/fluorine",
"path": "fluorine/utils/react_file_loader.py",
"copies": "1",
"size": "5052",
"license": "mit",
"hash": -1551541359308046300,
"line_mean": 30.1851851852,
"line_max": 162,
"alpha_frac": 0.674584323,
"autogenerated": false,
"ratio": 2.7927031509121063,
"config_tes... |
__author__ = 'luissaguas'
import re, telnetlib
class MemcachedStats:
_client = None
_key_regex = re.compile(ur'ITEM (.*) \[(.*); (.*)\]')
_slab_regex = re.compile(ur'STAT items:(.*):number')
_stat_regex = re.compile(ur"STAT (.*) (.*)\r")
def __init__(self, host='localhost', port='11211'):
self._host = host
... | {
"repo_name": "saguas/jasper_erpnext_report",
"path": "jasper_erpnext_report/utils/memcache_stats.py",
"copies": "1",
"size": "1412",
"license": "mit",
"hash": -4394721600494989300,
"line_mean": 27.24,
"line_max": 71,
"alpha_frac": 0.6635977337,
"autogenerated": false,
"ratio": 2.9233954451345756... |
__author__ = 'luissaguas'
#import json
from jnius import PythonJavaClass, java_method
import frappe, re, os
class FrappeTask(PythonJavaClass):
__javainterfaces__ = ['IFrappeTask']
def read_config(self):
config = frappe.get_conf() or {}
curr_site = os.path.join("currentsite.txt")
config.default_site = frapp... | {
"repo_name": "saguas/jasper_erpnext_report",
"path": "jasper_erpnext_report/core/FrappeTask.py",
"copies": "1",
"size": "2201",
"license": "mit",
"hash": 4014088926257898000,
"line_mean": 22.9347826087,
"line_max": 93,
"alpha_frac": 0.6778736938,
"autogenerated": false,
"ratio": 2.95833333333333... |
__author__ = 'luissaguas'
#from fluorine.utils.packages_path import get_package_path
from jinja2 import FileSystemLoader, TemplateNotFound
import re, os, frappe
def delimeter_match(m):
#print m.group(0)
if m.group(0).startswith("{{%"):
#print m.group(2)
source = "{% endraw %}\n{{"+ m.group(2) +"}}{% raw %}\n... | {
"repo_name": "saguas/fluorine",
"path": "fluorine/utils/fjinja.py",
"copies": "1",
"size": "2206",
"license": "mit",
"hash": -7992195068647324000,
"line_mean": 35.1803278689,
"line_max": 188,
"alpha_frac": 0.6314596555,
"autogenerated": false,
"ratio": 2.906455862977602,
"config_test": false,
... |
__author__ = "Luka Avbreht"
import queue
class Node():
# TODO Probably havinf left and right node in init is kinda stupid, idk
def __init__(self, value, parent=None):
"""
Class that creates the structure for Avl to work on (only called once)
"""
self.value = value
sel... | {
"repo_name": "jO-Osko/PSA2",
"path": "naloge/dn1/tree/LukaAvbreht/Node.py",
"copies": "1",
"size": "2693",
"license": "mit",
"hash": -7904417687996097000,
"line_mean": 30.3139534884,
"line_max": 141,
"alpha_frac": 0.4756776829,
"autogenerated": false,
"ratio": 3.581117021276596,
"config_test":... |
__author__ = 'LukaAvbreht, SamoKralj'
from tkinter import *
from igra import *
from PIL import ImageTk,Image
import threading
import time
import random
class tkmlin():
def __init__(self,master):
self.master = master
self.master.minsize(width=1300, height=700)
self.bg = 'LightYellow2' #'Lem... | {
"repo_name": "LukaAvbreht/Nine-Mens-Morris",
"path": "Main.py",
"copies": "1",
"size": "42601",
"license": "mit",
"hash": 671384022358815200,
"line_mean": 47.3526734926,
"line_max": 178,
"alpha_frac": 0.5488918169,
"autogenerated": false,
"ratio": 2.9411113417756556,
"config_test": true,
"ha... |
__author__ = 'LukaAvbreht, SamoKralj'
IGRALEC_ENA = "B"
IGRALEC_DVA = "C"
def nasprotnik(igralec):
""" Pove nasprotnega igralca. Koristno pri metodi poteza. """
if igralec == IGRALEC_ENA:
return IGRALEC_DVA
elif igralec == IGRALEC_DVA:
return IGRALEC_ENA
else:
1/0 #Sesuje igro,... | {
"repo_name": "LukaAvbreht/Nine-Mens-Morris",
"path": "igra.py",
"copies": "1",
"size": "12171",
"license": "mit",
"hash": 4034851588597075000,
"line_mean": 40.3367346939,
"line_max": 125,
"alpha_frac": 0.4424786043,
"autogenerated": false,
"ratio": 2.831314072693383,
"config_test": false,
"h... |
__author__ = 'lukas.bitter', 'Nicloas Gonin', 'Nils Ryter'
# !/usr/bin/env python
# -*- coding: utf-8 -*-
import cv2
import numpy as np
import sys
from matplotlib import pyplot as plt
# Definition of feature postition on the trackbar:
numHarrisCorner = 1
numSIFT = 2
numSURF = 3
numORB = 4
def nothing(x):
pass
de... | {
"repo_name": "LukasBitter/Wooden-Forsaken-Wrench",
"path": "featuresVisualisation.py",
"copies": "1",
"size": "3632",
"license": "apache-2.0",
"hash": -9126736634902727000,
"line_mean": 29.0165289256,
"line_max": 92,
"alpha_frac": 0.5864537445,
"autogenerated": false,
"ratio": 3.455756422454805,... |
import json
from httplib2 import Http
import BaseHTTPServer
from BaseHTTPServer import *
# Users will be used for a very basic authorization:
# Whenever a user authorizes, well check whether his chosen nickname is available.
# If it is available, well grant him permisson to use the chat under that nickname,
# and if ... | {
"repo_name": "vergilius/hive-demo",
"path": "hive-backend/backend.py",
"copies": "2",
"size": "3540",
"license": "bsd-3-clause",
"hash": -385435992118254200,
"line_mean": 31.4770642202,
"line_max": 106,
"alpha_frac": 0.5624293785,
"autogenerated": false,
"ratio": 3.5649546827794563,
"config_te... |
__author__ = 'lukasz'
class WebParser(object):
def __init__(self):
self.nested = False
@staticmethod
def getParser(source_id):
if source_id == 'cnn':
from backend.parsers.cnn import CNNParser
return CNNParser()
elif source_id == 'gua':
from backend.parsers.guardian import GuardianP... | {
"repo_name": "ldrozdz/Webforming",
"path": "backend/parsers/__init__.py",
"copies": "1",
"size": "1048",
"license": "apache-2.0",
"hash": 1851812334962265900,
"line_mean": 30.7878787879,
"line_max": 62,
"alpha_frac": 0.679389313,
"autogenerated": false,
"ratio": 3.8529411764705883,
"config_tes... |
__author__ = 'luke.beer'
import subprocess
import threading
import logging
import socket
import time
import questions
import states
class Executor(threading.Thread):
def __init__(self, r, channel):
threading.Thread.__init__(self)
self.redis = r
self.channel = channel
self.pubsub =... | {
"repo_name": "lukebeer/budweiser",
"path": "budweiser/budweiser.py",
"copies": "1",
"size": "2185",
"license": "mit",
"hash": 1665179541357204200,
"line_mean": 31.6119402985,
"line_max": 113,
"alpha_frac": 0.576201373,
"autogenerated": false,
"ratio": 3.9087656529516996,
"config_test": false,
... |
__author__ = 'luke Berezynskyj <eat.lemons@gmail.com>'
import logging
import nltk.corpus
import nltk.tokenize.punkt
import nltk.stem.snowball
import string
class Verify:
def __init__(self, threshold=0.5):
self.threshold = threshold
def setup(self):
try:
self.stopwords = nltk.co... | {
"repo_name": "lukebeer/SIPCallRecordVerify",
"path": "src/verify.py",
"copies": "1",
"size": "1519",
"license": "mit",
"hash": -4772211471105906000,
"line_mean": 37,
"line_max": 112,
"alpha_frac": 0.6385780118,
"autogenerated": false,
"ratio": 3.75990099009901,
"config_test": false,
"has_no_... |
__author__ = 'luke Berezynskyj <eat.lemons@gmail.com>'
import os
import sys
import json
import urllib
import urllib2
import logging as logger
import subprocess
def wav_to_flac(wav=None):
if os.path.isfile(wav):
logger.info("Converting %s to flac" % wav)
flac = '%s.flac' % wav[:-4]
subpro... | {
"repo_name": "lukebeer/SIPCallRecordVerify",
"path": "src/speechtools.py",
"copies": "1",
"size": "1355",
"license": "mit",
"hash": 4101838582170735000,
"line_mean": 28.4782608696,
"line_max": 95,
"alpha_frac": 0.6280442804,
"autogenerated": false,
"ratio": 3.1957547169811322,
"config_test": f... |
__author__ = 'luke Berezynskyj <eat.lemons@gmail.com>'
import re
import logging
import subprocess
import pjsua as pj
from time import sleep
class CallHandler(pj.CallCallback):
def __init__(self, call=None):
self.lib = pj.Lib.instance()
pj.CallCallback.__init__(self, call)
self.wait_for_h... | {
"repo_name": "lukebeer/SIPCallRecordVerify",
"path": "src/callhandler.py",
"copies": "1",
"size": "2569",
"license": "mit",
"hash": 7357118698749728000,
"line_mean": 37.9393939394,
"line_max": 97,
"alpha_frac": 0.5496302063,
"autogenerated": false,
"ratio": 3.8573573573573574,
"config_test": f... |
__author__ = 'luke Berezynskyj <eat.lemons@gmail.com>'
import re
import logging
import threading
import pjsua as pj
from time import sleep
from callhandler import CallHandler
class AccountHandler(pj.AccountCallback):
sem = None
def __init__(self, account):
self.lib = pj.Lib.instance()
self.... | {
"repo_name": "lukebeer/SIPCallRecordVerify",
"path": "src/accounthandler.py",
"copies": "1",
"size": "1943",
"license": "mit",
"hash": 5292704775264743000,
"line_mean": 32.5172413793,
"line_max": 75,
"alpha_frac": 0.5800308801,
"autogenerated": false,
"ratio": 3.545620437956204,
"config_test":... |
import numpy as np
import os.path as op
import datetime
import calendar
from .utils import _load_mne_locs
from ...utils import logger, warn
from ..utils import _read_segments_file
from ..base import BaseRaw
from ..meas_info import _empty_info
from ..constants import FIFF
def read_raw_artemis123(input_fname, preload... | {
"repo_name": "nicproulx/mne-python",
"path": "mne/io/artemis123/artemis123.py",
"copies": "2",
"size": "10688",
"license": "bsd-3-clause",
"hash": -1372411386760608800,
"line_mean": 38.1501831502,
"line_max": 79,
"alpha_frac": 0.5567926647,
"autogenerated": false,
"ratio": 3.887959257911968,
"... |
import numpy as np
import os.path as op
import datetime
import calendar
from .utils import _load_mne_locs, _read_pos
from ...utils import logger, warn
from ..utils import _read_segments_file
from ..base import BaseRaw
from ..meas_info import _empty_info, _make_dig_points
from ..constants import FIFF
from ...chpi impo... | {
"repo_name": "jaeilepp/mne-python",
"path": "mne/io/artemis123/artemis123.py",
"copies": "1",
"size": "17812",
"license": "bsd-3-clause",
"hash": -4046031667826443300,
"line_mean": 39.5740318907,
"line_max": 79,
"alpha_frac": 0.5200426679,
"autogenerated": false,
"ratio": 3.8747008918860124,
"... |
import numpy as np
import os.path as op
import datetime
import calendar
from .utils import _load_mne_locs, _read_pos
from ...utils import logger, warn, verbose, _check_fname
from ..utils import _read_segments_file
from ..base import BaseRaw
from ..meas_info import _empty_info
from .._digitization import _make_dig_poi... | {
"repo_name": "mne-tools/mne-python",
"path": "mne/io/artemis123/artemis123.py",
"copies": "7",
"size": "18633",
"license": "bsd-3-clause",
"hash": -5283901014423896000,
"line_mean": 39.3311688312,
"line_max": 79,
"alpha_frac": 0.5037836097,
"autogenerated": false,
"ratio": 3.8198031980319804,
... |
import numpy as np
import os.path as op
import datetime
import calendar
from .utils import _load_mne_locs, _read_pos
from ...utils import logger, warn, verbose
from ..utils import _read_segments_file
from ..base import BaseRaw
from ..meas_info import _empty_info, _make_dig_points
from ..constants import FIFF
from ...... | {
"repo_name": "teonlamont/mne-python",
"path": "mne/io/artemis123/artemis123.py",
"copies": "2",
"size": "17831",
"license": "bsd-3-clause",
"hash": -4335025033146626600,
"line_mean": 39.433106576,
"line_max": 79,
"alpha_frac": 0.520441927,
"autogenerated": false,
"ratio": 3.8796779808529154,
"... |
__author__ = 'Luke Cossey'
import os
import re
def print_list(list):
for i in list:
print i
bad_names = ['AUX', 'PRN', 'NUL', 'CON', 'COM0', 'COM1', 'COM2', 'COM3', 'COM4', 'COM5', 'COM6', 'COM7', 'COM8', 'COM9', 'LPT0', 'LPT1', 'LPT2', 'LPT3', 'LPT4', 'LPT5', 'LPT6', 'LPT7', 'LPT8', 'LPT9']
bad_chars = ... | {
"repo_name": "Numerical-Brass/skydrivepro-validation",
"path": "validate_skydrive.py",
"copies": "1",
"size": "3757",
"license": "mit",
"hash": 2813079974252257300,
"line_mean": 48.4473684211,
"line_max": 200,
"alpha_frac": 0.4788394996,
"autogenerated": false,
"ratio": 3.7987866531850356,
"co... |
__author__ = 'Luke Merrett'
from EnvironmentObjects.environment import Environment
from PetObjects.pet import Pet
console_options = None
environment = None
myPet = None
def run_option(x):
if x in console_options:
console_options[x]()
else:
print("You didn\'t enter an option")
wait()
... | {
"repo_name": "lukemerrett/PythonPet",
"path": "pythonpet.py",
"copies": "1",
"size": "1676",
"license": "mit",
"hash": 48464378870653200,
"line_mean": 23.6617647059,
"line_max": 91,
"alpha_frac": 0.5960620525,
"autogenerated": false,
"ratio": 3.1742424242424243,
"config_test": false,
"has_no... |
__author__ = 'Luke Merrett'
from random import randint
from Helpers import datehelper
class Age:
__minimum_potential_lifespan_in_seconds = 86400 # 1 day
__total_potential_lifespan_in_seconds = 31536000 # 1 year
__birth_date = None
__lifespan_in_seconds = None
def __init__(self):
self.__... | {
"repo_name": "lukemerrett/PythonPet",
"path": "PetObjects/age.py",
"copies": "1",
"size": "1727",
"license": "mit",
"hash": 3704107637654240000,
"line_mean": 37.4,
"line_max": 110,
"alpha_frac": 0.6340474812,
"autogenerated": false,
"ratio": 3.6588983050847457,
"config_test": false,
"has_no_... |
__author__ = 'Luke Merrett'
import random
import settings
from clients.steamapi import SteamApiClient
from clients import installed_games
def get_total_playtime_for_last_two_weeks():
"""
Calculates the total time in minutes played in the last two weeks
:return: The total playtime in minutes for the last t... | {
"repo_name": "lukemerrett/SteamProgress",
"path": "analytics/playtime.py",
"copies": "1",
"size": "1983",
"license": "mit",
"hash": 1447511661056062200,
"line_mean": 29.0454545455,
"line_max": 72,
"alpha_frac": 0.636913767,
"autogenerated": false,
"ratio": 3.6186131386861313,
"config_test": fa... |
__author__ = 'Luke Merrett'
import settings
from evernote.api.client import EvernoteClient
import evernote.edam.type.ttypes as Types
class EvernoteOperations:
__client = None
def __init__(self):
self.__client = EvernoteClient(token=settings.developer_token, sandbox=settings.sandbox)
def print_li... | {
"repo_name": "lukemerrett/EvernotePy",
"path": "evernoteclient/operations.py",
"copies": "1",
"size": "1354",
"license": "mit",
"hash": -5149916850017991000,
"line_mean": 30.511627907,
"line_max": 96,
"alpha_frac": 0.623338257,
"autogenerated": false,
"ratio": 3.6495956873315363,
"config_test"... |
__author__ = 'Luke Merrett'
import settings
import datetime
import pygal
import webbrowser
from peewee import *
from clients.steamapi import SteamApiClient
from collections import defaultdict, OrderedDict
from datetime import date
from dateutil.relativedelta import relativedelta
db = SqliteDatabase(settings.sqlite_da... | {
"repo_name": "lukemerrett/SteamProgress",
"path": "database/playtime_operations.py",
"copies": "1",
"size": "3289",
"license": "mit",
"hash": -9154200304903423000,
"line_mean": 34.3655913978,
"line_max": 117,
"alpha_frac": 0.6460930374,
"autogenerated": false,
"ratio": 3.7804597701149425,
"con... |
__author__ = 'Luke Merrett'
import settings
valid_interfaces = {
'ISteamUser': [
'GetPlayerSummaries'
],
'IPlayerService': [
'GetOwnedGames'
]
}
def get_player_summary():
return __get_url('ISteamUser', 'GetPlayerSummaries', 'v0002', {
'steamids': settings.steam_user_id
... | {
"repo_name": "lukemerrett/SteamProgress",
"path": "builders/urlbuilder.py",
"copies": "1",
"size": "1279",
"license": "mit",
"hash": -5699415490222892000,
"line_mean": 28.0909090909,
"line_max": 90,
"alpha_frac": 0.6426896013,
"autogenerated": false,
"ratio": 3.739766081871345,
"config_test": ... |
__author__ = 'Luke Merrett'
import unittest
from analytics import playtime
class PlaytimeTests(unittest.TestCase):
def test_get_total_playtime_for_last_two_weeks_returns_playtime(self):
playtime_in_minutes = playtime.get_total_playtime_for_last_two_weeks()
self.assertTrue(playtime_in_minutes > 0)
... | {
"repo_name": "lukemerrett/SteamProgress",
"path": "unittests/playtimetests.py",
"copies": "1",
"size": "1658",
"license": "mit",
"hash": -4045462117138670600,
"line_mean": 39.4390243902,
"line_max": 86,
"alpha_frac": 0.6604342581,
"autogenerated": false,
"ratio": 3.283168316831683,
"config_tes... |
__author__ = 'Luke Merrett'
steam_webapi_key = 'Get your key here http://steamcommunity.com/dev'
registered_domain = 'The domain used to register above'
steam_user_id = 'Enter your user id here'
steam_user_folder = 'Enter your user folder here, eg C:\\Program Files (x86)\\Steam\\userdata\\22222222'
# Maybe you brough... | {
"repo_name": "lukemerrett/SteamProgress",
"path": "settings.py",
"copies": "1",
"size": "1276",
"license": "mit",
"hash": 1208464840595486500,
"line_mean": 34.4444444444,
"line_max": 118,
"alpha_frac": 0.75,
"autogenerated": false,
"ratio": 3.4768392370572205,
"config_test": false,
"has_no_k... |
__author__ = 'Luke'
import numpy as np
import time
import http.client, urllib.parse
from pprint import pprint
API_KEY = "H671BFO41N0TP246"
n_spine = 8.0
fields = list(map(lambda x: "field"+x, map(str, range(1, 9))))
headers = {"Content-type": "application/x-www-form-urlencoded",
"Accept": "text/plain"}
def m... | {
"repo_name": "jcuroboclub/White-Roofs",
"path": "fakeUpdate.py",
"copies": "1",
"size": "1326",
"license": "mit",
"hash": -2232769110665545200,
"line_mean": 34.8648648649,
"line_max": 81,
"alpha_frac": 0.5490196078,
"autogenerated": false,
"ratio": 3.970059880239521,
"config_test": false,
"h... |
__author__ = "Luke"
import numpy as np
import time
import httplib, urllib
from pprint import pprint
import os
SERVER_UPDATE_LIMIT = 16
MAX_RETRIES = 25
lastSentList = {}
def uploadData(data, APIKey):
try:
lastSent = lastSentList[APIKey]
if ((time.time() - lastSent) < SERVER_UPDATE_LIMIT):
... | {
"repo_name": "jcuroboclub/White-Roofs",
"path": "Pi/ThingSpeak.py",
"copies": "1",
"size": "2225",
"license": "mit",
"hash": 1318788846648294400,
"line_mean": 30.338028169,
"line_max": 78,
"alpha_frac": 0.5608988764,
"autogenerated": false,
"ratio": 4.075091575091575,
"config_test": false,
"... |
__author__ = 'luke'
from boto.kinesis.exceptions import ResourceInUseException, ResourceNotFoundException
import time
class Stream(object):
active = 'ACTIVE'
def __init__(self, conn, stream_name='dervish', shard_count=1, timeout=-1, retry_pause=1):
self.conn = conn
self.stream_name = stream... | {
"repo_name": "lsamaha/dervisher",
"path": "dervisher/stream.py",
"copies": "1",
"size": "2048",
"license": "bsd-3-clause",
"hash": -7733880312788726000,
"line_mean": 31.5079365079,
"line_max": 94,
"alpha_frac": 0.5966796875,
"autogenerated": false,
"ratio": 4.031496062992126,
"config_test": fa... |
_author_ = 'Luke'
from price_parsing import *
def normalize(xTrain, yTrain, xTest, yTest):
# time factor to normalize time data to
firstTime = xTrain[0]
for i in range(0, len(xTrain)):
xTrain[i] = xTrain[i] - firstTime
for i in range(0, len(xTest)):
xTest[i] = xTest[i] - firstTime
... | {
"repo_name": "will-cromar/needy",
"path": "normalizer.py",
"copies": "1",
"size": "1718",
"license": "mit",
"hash": -2914093002310429000,
"line_mean": 27.6333333333,
"line_max": 117,
"alpha_frac": 0.6257275902,
"autogenerated": false,
"ratio": 3.0140350877192983,
"config_test": true,
"has_no... |
import ts3
from pathlib import Path
import time
import random
user = 'serveradmin' # server query password
password = '' # server query user
host = '' # server query host
port = 10011 # server query port
interval = 600 # Joke, insult interval - (secon... | {
"repo_name": "LukeBob/teamspeak-tools",
"path": "Joke-bot.py",
"copies": "1",
"size": "2360",
"license": "mit",
"hash": -3085730035313520600,
"line_mean": 28.8734177215,
"line_max": 120,
"alpha_frac": 0.5724576271,
"autogenerated": false,
"ratio": 3.704866562009419,
"config_test": false,
"ha... |
__author__ = 'Luk'
from unittest import TestCase
from hs_core.hydroshare import utils
from hs_core.models import GenericResource
from django.contrib.auth.models import User
import importlib
class TestGetSerializer(TestCase):
def setUp(self):
pass
def tearDown(self):
User.objects.all().delet... | {
"repo_name": "hydroshare/hydroshare_temp",
"path": "hs_core/tests/api/native/test_get_serializer.py",
"copies": "1",
"size": "1266",
"license": "bsd-3-clause",
"hash": 3374903916680725500,
"line_mean": 27.1333333333,
"line_max": 114,
"alpha_frac": 0.6548183254,
"autogenerated": false,
"ratio": 4... |
__author__ = 'Lunzhy'
from bs4 import BeautifulSoup
import re
import json
import datetime
_Chinese_number = {'一': '1', '二': '2', '三': '3', '四': '4', '五': '5', '六': '6',
'七': '7', '八': '8', '九': '9', '十': '10', '十一': '11', '十二': '12'}
def _get_number_out(href):
patt = re.compile(r'\d+')
mat... | {
"repo_name": "lunzhy/PyShanbay",
"path": "pyshanbay/page_parser.py",
"copies": "1",
"size": "7550",
"license": "mit",
"hash": 4403033068201856500,
"line_mean": 31.9691629956,
"line_max": 96,
"alpha_frac": 0.5589257082,
"autogenerated": false,
"ratio": 3.2824561403508774,
"config_test": false,
... |
__author__ = 'Lunzhy'
from pyshanbay.shanbay import VisitShanbay
from pyshanbay import page_parser as parser
import json
def test_bs():
shanbay = VisitShanbay()
shanbay.login()
page_members = shanbay.members()
total_page = parser.total_page_members(page_members)
members_names = []
for page i... | {
"repo_name": "lunzhy/PyShanbay",
"path": "tests/test_parse.py",
"copies": "1",
"size": "1635",
"license": "mit",
"hash": -8124875305947776000,
"line_mean": 23.7878787879,
"line_max": 61,
"alpha_frac": 0.650764526,
"autogenerated": false,
"ratio": 3.193359375,
"config_test": false,
"has_no_ke... |
__author__ = 'Lunzhy'
import urllib.parse
import urllib.request
import http.cookiejar
import copy
from urllib.parse import urlsplit
from urllib.parse import urljoin
from urllib import request
import datetime
import json
from pyshanbay.utils import ShanbayConnectException
class VisitShanbay:
def __init__(self, use... | {
"repo_name": "lunzhy/PyShanbay",
"path": "pyshanbay/shanbay.py",
"copies": "1",
"size": "7822",
"license": "mit",
"hash": 5275939351292206000,
"line_mean": 37.9154228856,
"line_max": 100,
"alpha_frac": 0.6025313219,
"autogenerated": false,
"ratio": 3.61460258780037,
"config_test": false,
"ha... |
import eventlet
import time
from oslo.config import cfg
from models import Instance
from bcec_vm_ha.utils import green_ping as ping
VMHA_OPTIONS = [
cfg.StrOpt('default_gateway',
deprecated_group="DEFAULT",
default='',
help='Default Gateway to check the connectivity.... | {
"repo_name": "luogangyi/bcec-vm-ha",
"path": "bcec_vm_ha/ping_ckeck.py",
"copies": "1",
"size": "3286",
"license": "apache-2.0",
"hash": 138684238353478450,
"line_mean": 26.8474576271,
"line_max": 76,
"alpha_frac": 0.5416920268,
"autogenerated": false,
"ratio": 3.8432748538011694,
"config_test... |
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