text stringlengths 0 1.05M | meta dict |
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__author__ = 'Mirko Rossini'
import unittest
from integrationtest_support import IntegrationTestSupport
from pybuilder.errors import BuildFailedException
from common import BUILD_FILE_TEMPLATE
BUILD_FILE_TEMPLATE = """
from pybuilder.core import use_plugin, init
from pybuilder_django_enhanced_plugin import django_t... | {
"repo_name": "MirkoRossini/pybuilder_django_enhanced_plugin",
"path": "src/integrationtest/python/django_test_fail_if_project_missing_tests.py",
"copies": "1",
"size": "1134",
"license": "bsd-3-clause",
"hash": 7635204198209177000,
"line_mean": 25.3720930233,
"line_max": 104,
"alpha_frac": 0.6904761... |
__author__ = 'Miroslaw Horbal'
__email__ = 'miroslaw@gmail.com'
__date__ = 'December 1, 2013'
__website__ = 'http://pastebin.com/gaPnVwNH#'
# Notes
# Dec 2, 2013: Updated the parser to fix the bug noticed by kinnskogr
# on the kaggle forums. The fix involves directly assigning
# clicks to qu... | {
"repo_name": "charlesjlee/Kaggle",
"path": "Yandex_web_search/Code/parse_sessions.py",
"copies": "1",
"size": "2461",
"license": "mit",
"hash": 1844813109685428200,
"line_mean": 36.303030303,
"line_max": 90,
"alpha_frac": 0.5205201138,
"autogenerated": false,
"ratio": 3.366621067031464,
"confi... |
__author__ = "Mislav Novakovic <mislav.novakovic@sartura.hr>"
__copyright__ = "Copyright 2017, Deutsche Telekom AG"
__license__ = "BSD 3-Clause"
import yang as ly
import sys
ctx = None
try:
ctx = ly.Context("/etc/sysrepo/yang")
module = ctx.load_module("turing-machine", None)
if module is None:
p... | {
"repo_name": "PavolVican/libyang",
"path": "swig/python/examples/xpath.py",
"copies": "1",
"size": "1162",
"license": "bsd-3-clause",
"hash": -2653521428397626000,
"line_mean": 31.2777777778,
"line_max": 113,
"alpha_frac": 0.6101549053,
"autogenerated": false,
"ratio": 3.1236559139784945,
"con... |
__author__ = "Mislav Novakovic <mislav.novakovic@sartura.hr>"
__copyright__ = "Copyright 2017, Deutsche Telekom AG"
__license__ = "BSD 3-Clause"
import yang as ly
import sys
try:
ctx = ly.Context("/etc/sysrepo/yang")
except Exception as e:
print(e)
sys.exit()
ctx.load_module("iana-if-type", None)
ctx.loa... | {
"repo_name": "sartura/libyang",
"path": "swig/python/examples/subtype.py",
"copies": "1",
"size": "1461",
"license": "bsd-3-clause",
"hash": -7024405435779415000,
"line_mean": 30.085106383,
"line_max": 125,
"alpha_frac": 0.6639288159,
"autogenerated": false,
"ratio": 2.875984251968504,
"config... |
__author__ = "Mislav Novakovic <mislav.novakovic@sartura.hr>"
__copyright__ = "Copyright 2017, Deutsche Telekom AG"
__license__ = "BSD 3-Clause"
import yang as ly
ctx = None
try:
ctx = ly.Context("/etc/sysrepo2/yang")
except Exception as e:
print(e)
errors = ly.get_ly_errors(ctx)
for err in errors:
... | {
"repo_name": "PavolVican/libyang",
"path": "swig/python/examples/context.py",
"copies": "2",
"size": "1051",
"license": "bsd-3-clause",
"hash": 9187382899741111000,
"line_mean": 25.275,
"line_max": 102,
"alpha_frac": 0.6251189343,
"autogenerated": false,
"ratio": 3.0552325581395348,
"config_te... |
__author__ = 'MISSCATLADY'
import datetime
from models import *
from widgets import SelectTimeWidget
from django import forms
from django.shortcuts import render
from django.http import HttpResponse
from django.forms.extras.widgets import SelectDateWidget
from django.http import HttpResponse, HttpResponseRedirect
from... | {
"repo_name": "CSC301H-Fall2013/JuakStore",
"path": "Storefront/juakstore/search.py",
"copies": "1",
"size": "5425",
"license": "mit",
"hash": 3081659325441254400,
"line_mean": 41.390625,
"line_max": 101,
"alpha_frac": 0.5616589862,
"autogenerated": false,
"ratio": 4.179506933744221,
"config_te... |
__author__ = 'MisturDust319'
import requests, re
from bs4 import BeautifulSoup
import winsound
#find the section of the website where the data is coming from
def getSection(html):
#given a web soup, find the "up" link, which is the current segment
link = html.find_all("link", rel="up")
#isolate the section... | {
"repo_name": "MisturDust319/TaeKimJapansesVocabExtractor",
"path": "taeKimVocab.py",
"copies": "1",
"size": "4207",
"license": "mit",
"hash": 3845066365276878300,
"line_mean": 34.025,
"line_max": 125,
"alpha_frac": 0.5660242684,
"autogenerated": false,
"ratio": 3.5953806672369546,
"config_test... |
__author__ = 'mitch, eric'
import logging
import wikipedia
import urllib3.contrib.pyopenssl
import flickrapi
import flickrapi.shorturl
import googlemaps
import gevent
import gevent.monkey
from pyteaser import Summarize
from settings import FLICKR_API, FLICKR_API_SECRET, GOOGLEMAPS_API
from collections import defaultdic... | {
"repo_name": "QuicklyRainbow/FieldGuideAU",
"path": "Flask_App/utils/processutils.py",
"copies": "1",
"size": "3741",
"license": "mit",
"hash": -5810621186746096000,
"line_mean": 36.0396039604,
"line_max": 107,
"alpha_frac": 0.6148088746,
"autogenerated": false,
"ratio": 3.5325779036827196,
"c... |
"""
This tool snaps multiple target features to input features based on a user specified SQL criteria and search radius.
Import this script into an ArcGIS Toolbox.
Note: The tool uses the ArcGIS default scratch geodatabase.
"""
import arcpy
import os
import datetime
#date string
today = datetime.datetime.now().strftim... | {
"repo_name": "mitchh300/CustomTools",
"path": "SnapNearFeatures.py",
"copies": "1",
"size": "2373",
"license": "unlicense",
"hash": 6673108364971709000,
"line_mean": 39.9137931034,
"line_max": 134,
"alpha_frac": 0.7560050569,
"autogenerated": false,
"ratio": 3.520771513353116,
"config_test": f... |
import arcpy
#Get feature from user
feature = arcpy.GetParameterAsText(0)
#Get field from user
field = arcpy.GetParameterAsText(1)
#Boolean used for check box
ischecked = arcpy.GetParameterAsText(2)
#Lists
field_list = set()
shapes = set()
#Count for messages
count = 0
if str(ischecked) == 'tr... | {
"repo_name": "mitchh300/CustomTools",
"path": "Delete_Dups.py",
"copies": "1",
"size": "1697",
"license": "unlicense",
"hash": 6167662417564512000,
"line_mean": 34.1063829787,
"line_max": 125,
"alpha_frac": 0.6269888038,
"autogenerated": false,
"ratio": 3.737885462555066,
"config_test": false,... |
__author__ = 'mithunbanerjee'
#!/usr/bin/env python
"""
Lab Credential:
IP address = 50.76.53.27
pynet-rtr1 (Cisco 881) snmp_port=7961, ssh_port=22
pynet-rtr2 (Cisco 881) snmp_port=8061, ssh_port=8022
pynet-sw1 (Arista vEOS switch) ssh_port=8222, eapi_port=8243
pynet-sw2 (Arista vEOS switch) ssh_port=8322, eapi_port=8... | {
"repo_name": "mith1979/ansible_automation",
"path": "week2/SNMP/wk2_ex_4_snmp_basic.py",
"copies": "1",
"size": "2187",
"license": "apache-2.0",
"hash": -6822490727130220000,
"line_mean": 26.3375,
"line_max": 131,
"alpha_frac": 0.6977594879,
"autogenerated": false,
"ratio": 2.4965753424657535,
... |
"""@author: mje."""
import cPickle as Pickle
import os
import socket
import mne
import networkx as nx
import numpy as np
import numpy.random as npr
from nitime import TimeSeries
from nitime.analysis import CoherenceAnalyzer
# from mne.stats import fdr_correction
# Permutation test.
def permutation_test(a, b, num_s... | {
"repo_name": "MadsJensen/Hyp_MEG_MNE_2",
"path": "network_analysis.py",
"copies": "1",
"size": "6555",
"license": "bsd-3-clause",
"hash": 5275953961366066000,
"line_mean": 30.0663507109,
"line_max": 79,
"alpha_frac": 0.5647597254,
"autogenerated": false,
"ratio": 3.1944444444444446,
"config_te... |
__author__ = 'mk'
from random import randint
from tkinter import *
class App:
def __init__(self, master):
frame = Frame(master)
frame.pack()
self.male = Radiobutton(master, text='male', variable=v, value=1)
self.male.pack(anchor=W)
self.female = Radiobutton(m... | {
"repo_name": "mattzjack/mattzjack.github.io",
"path": "latin_name/latin_name_generator.py",
"copies": "1",
"size": "17307",
"license": "unlicense",
"hash": -7064301715446458000,
"line_mean": 30.2290502793,
"line_max": 115,
"alpha_frac": 0.7238689548,
"autogenerated": false,
"ratio": 1.9094218887... |
__author__ = 'MKT1'
from utils.http import request
SEARCHER = ("www.google.com", "www.baidu.com", "www.sogou.com")
BAIDU_BASIC = "http://www.baidu.com/#ie=utf-8&wd="
SOGOU_BASIC = "http://www.sogou.com/web?ie=utf-8&query="
GOOGLE_BASIC = "http://www.google.com/search?q="
class Searcher(object):
def... | {
"repo_name": "wha000tif/Pencil",
"path": "libs/searcher.py",
"copies": "1",
"size": "1345",
"license": "mit",
"hash": -652940424149489200,
"line_mean": 23.3773584906,
"line_max": 64,
"alpha_frac": 0.5338289963,
"autogenerated": false,
"ratio": 3.225419664268585,
"config_test": false,
"has_no... |
__author__ = 'mlaptev'
def append_range_to_list_elements(initial_range, initial_set):
result_set = set()
for s in initial_set:
for r in initial_range:
set_to_append = set(s)
if r not in set_to_append:
set_to_append.add(r)
list_to_append = list(se... | {
"repo_name": "MikeLaptev/sandbox_python",
"path": "stepic/discrete_math/combinations.py",
"copies": "1",
"size": "1080",
"license": "apache-2.0",
"hash": -5215110188364000000,
"line_mean": 31.7272727273,
"line_max": 88,
"alpha_frac": 0.5777777778,
"autogenerated": false,
"ratio": 3.1764705882352... |
__author__ = 'mlissner'
from requests.models import Request, Response
from requests.exceptions import ConnectionError
class MockRequest(Request):
def __init__(self, url=None):
super(Request, self).__init__()
self.url = url
def get(self):
r = Response()
try:
r._con... | {
"repo_name": "Andr3iC/juriscraper",
"path": "tests/__init__.py",
"copies": "1",
"size": "1077",
"license": "bsd-2-clause",
"hash": 5552707706735096000,
"line_mean": 26.6153846154,
"line_max": 68,
"alpha_frac": 0.5747446611,
"autogenerated": false,
"ratio": 4.378048780487805,
"config_test": fal... |
__author__ = "mlklm"
__date__ = "$28 juil. 2015 11:35:31$"
__HOST__ = '0.0.0.0'
__PORT__ = 1977
from metafile import metafile
from myfile import myfile
from urllib.parse import urlparse
import cgi
import codecs
import http.server
import mimetypes
import re
class AEFS(http.server.BaseHTTPRequestHandler):
d... | {
"repo_name": "mlklm/AEFS",
"path": "aefs.py",
"copies": "1",
"size": "5358",
"license": "unlicense",
"hash": 8714991127498274000,
"line_mean": 33.3461538462,
"line_max": 103,
"alpha_frac": 0.4918797835,
"autogenerated": false,
"ratio": 4.009730538922156,
"config_test": false,
"has_no_keyword... |
__author__ = "mlklm"
__date__ = "$30 juil. 2015 09:59:26$"
__NS__ = "AEFS"
import os
import random
import re
from simplecrypt import decrypt
from simplecrypt import encrypt
import uuid
class myfile:
def __init__(self):
self.base_path = os.path.dirname(__file__) + "/../uploads/"
def write_(self,... | {
"repo_name": "mlklm/AEFS",
"path": "myfile.py",
"copies": "1",
"size": "1828",
"license": "unlicense",
"hash": -4160354256553860600,
"line_mean": 25.1285714286,
"line_max": 82,
"alpha_frac": 0.5333698031,
"autogenerated": false,
"ratio": 3.5913555992141455,
"config_test": false,
"has_no_keyw... |
__author__ = "mlklm"
__date__ = "$30 juil. 2015 13:46:05$"
import time
import json
class metafile :
def __init__(self,jsonstr=None):
if jsonstr is not None :
djson = json.loads(jsonstr)
self.burnafterreading = djson['burnafterreading']
self.expiration = djson['expir... | {
"repo_name": "mlklm/AEFS",
"path": "metafile.py",
"copies": "1",
"size": "1502",
"license": "unlicense",
"hash": -4431815788203680300,
"line_mean": 33.1590909091,
"line_max": 68,
"alpha_frac": 0.5778961385,
"autogenerated": false,
"ratio": 4.115068493150685,
"config_test": false,
"has_no_key... |
__author__ = 'mll-001'
import sys
import urllib2
from urllib2 import Request, urlopen, URLError, HTTPError
print "helle python"
print "hello tonny good study"
X = 'Span'
def func():
X = 'NI!'
print(X)
def nested():
print (X)
nested()
func()
print(X)
print('#######################... | {
"repo_name": "JohnnyHao/Py-Spider",
"path": "HelloPython.py",
"copies": "1",
"size": "1204",
"license": "apache-2.0",
"hash": -1536401780954271200,
"line_mean": 20.1403508772,
"line_max": 79,
"alpha_frac": 0.5282392027,
"autogenerated": false,
"ratio": 3.7625,
"config_test": false,
"has_no_k... |
__author__ = "mmcmahon13"
import json
from .blocks import get_farthest_ancestor, NEXTBLOCK, NEXT
from __ids__ import *
from .survey_exceptions import *
__surveyGen__ = IdGenerator("s")
class Survey:
"""
Contains the components of a survey:
A survey is defined as a list of blocks and a list of branching ... | {
"repo_name": "SurveyMan/SMPy",
"path": "surveyman/survey/surveys.py",
"copies": "1",
"size": "4500",
"license": "apache-2.0",
"hash": 134390234135526200,
"line_mean": 39.5495495495,
"line_max": 119,
"alpha_frac": 0.6228888889,
"autogenerated": false,
"ratio": 4.433497536945813,
"config_test": ... |
__author__ = 'mmeisinger'
import json
import psycopg2
from psycopg2 import OperationalError, ProgrammingError, DatabaseError, IntegrityError
from psycopg2.extensions import ISOLATION_LEVEL_AUTOCOMMIT
from py2neo import neo4j
DATABASE = "ion_sterling_ion"
RESOURCES = "ion_sterling_resources"
ASSOCS = "ion_sterling_r... | {
"repo_name": "ooici/pyon",
"path": "prototype/neo4j/ion2neo.py",
"copies": "1",
"size": "2176",
"license": "bsd-2-clause",
"hash": -4257405309832139000,
"line_mean": 30.5362318841,
"line_max": 107,
"alpha_frac": 0.5988051471,
"autogenerated": false,
"ratio": 3.2526158445440956,
"config_test": ... |
__author__ = 'mmikofski'
try:
from setuptools import setup
except ImportError:
from distutils.core import setup
from pvmismatch import __version__, __name__, __email__, __url__
import os
README = 'README.rst'
try:
with open(os.path.join(os.path.dirname(__file__), README), 'r') as readme:
README = ... | {
"repo_name": "SunPower/PVMismatch",
"path": "setup.py",
"copies": "1",
"size": "1992",
"license": "bsd-3-clause",
"hash": -5268795507864777000,
"line_mean": 27.8695652174,
"line_max": 78,
"alpha_frac": 0.6019076305,
"autogenerated": false,
"ratio": 3.4285714285714284,
"config_test": false,
"... |
__author__ = 'mmoisen'
from abc import ABCMeta
import time
try:
import RPi.GPIO as io
io.setmode(io.BCM)
except ImportError:
print "run this on the RPi"
class Probe(object):
BASE_DIR = '/sys/bus/w1/devices/'
RETRY_MAX = 5
def __init__(self, probe_type, file_name):
if not probe_type i... | {
"repo_name": "mkmoisen/brew",
"path": "models.py",
"copies": "1",
"size": "2736",
"license": "mit",
"hash": -583612438646223900,
"line_mean": 28.4193548387,
"line_max": 119,
"alpha_frac": 0.5486111111,
"autogenerated": false,
"ratio": 3.3945409429280398,
"config_test": false,
"has_no_keyword... |
__author__ = 'mmoisen'
import peewee
from settings import db
from fermentation import FermentationHost, FermentationFermentor, FermentationFermwrap, FermentationProbe, \
FermentationTemperature, FermentationSchedule, FermentationFermwrapHistory
import os
from settings import BREW_PROPERTIES_FILE, hostnames
tab... | {
"repo_name": "mkmoisen/brew",
"path": "fermentation/init_db.py",
"copies": "1",
"size": "1723",
"license": "mit",
"hash": -2964863605421261300,
"line_mean": 25.5230769231,
"line_max": 108,
"alpha_frac": 0.6970400464,
"autogenerated": false,
"ratio": 3.619747899159664,
"config_test": false,
"... |
__author__ = 'mmoisen'
import peewee
import json
import socket
from models import Probe, Heater
from settings import BaseModel, get_db, BREW_PROPERTIES_FILE
import traceback
import sys
import logging
import logging.handlers
LOG_FILENAME = 'brew.log'
logger = logging.getLogger('Logger')
logger.setLevel(logging.DEB... | {
"repo_name": "mkmoisen/brew",
"path": "fermentation/fermentation.py",
"copies": "1",
"size": "46398",
"license": "mit",
"hash": 873917690162779600,
"line_mean": 39.5940507437,
"line_max": 153,
"alpha_frac": 0.5581490581,
"autogenerated": false,
"ratio": 3.7940960013083656,
"config_test": false... |
__author__ = 'mmoisen'
import sys
import time
import os
from models import Probe
from datetime import datetime
import logging
LOG_FILENAME = 'ds18b20.log'
logger = logging.getLogger('test_ds18b20')
logger.setLevel(logging.DEBUG)
handler = logging.FileHandler(LOG_FILENAME)
formatter = logging.Formatter('%(asctime)s ... | {
"repo_name": "mkmoisen/brew",
"path": "test_ds18b20.py",
"copies": "1",
"size": "1387",
"license": "mit",
"hash": 2366301954753899000,
"line_mean": 28.5319148936,
"line_max": 114,
"alpha_frac": 0.6286950252,
"autogenerated": false,
"ratio": 3.5292620865139948,
"config_test": false,
"has_no_k... |
__author__ = 'mmoisen'
import threading
import time
import json
class API(object):
updated = False
@classmethod
def listen(cls):
time.sleep(10)
cls.updated = True
'''
t = threading.Thread(name="api", target=API.listen)
i = 0
t.start()
while not API.updated:
print i, "updated = ", API... | {
"repo_name": "mkmoisen/brew",
"path": "fermentation/thread_test.py",
"copies": "1",
"size": "1158",
"license": "mit",
"hash": 8667130928718766000,
"line_mean": 18,
"line_max": 105,
"alpha_frac": 0.6355785838,
"autogenerated": false,
"ratio": 3.181318681318681,
"config_test": false,
"has_no_k... |
__author__ = 'mmoisen'
import unittest
from fermentation import ScheduleIncrease, Schedule
from datetime import datetime, timedelta
from fermentation import FermentationHost, FermentationFermentor, FermentationProbe, FermentationFermwrap, \
FermentationTemperature, FermentationSchedule
from fermentation import Pro... | {
"repo_name": "mkmoisen/brew",
"path": "fermentation/tests.py",
"copies": "1",
"size": "66812",
"license": "mit",
"hash": -8557317393833123000,
"line_mean": 47.6266375546,
"line_max": 177,
"alpha_frac": 0.4885200263,
"autogenerated": false,
"ratio": 3.8952891791044775,
"config_test": true,
"h... |
__author__ = 'mmoisen'
from bottle import Bottle, route, run, template, debug, post, request
from datetime import datetime, timedelta
import os
import sys
app = Bottle()
from fermentation.init_db import drop_and_create_tables, drop_brew_properties
@app.route('/hai')
def hai():
print "haiii'"
@app.route('/a... | {
"repo_name": "mkmoisen/brew",
"path": "test_controller.py",
"copies": "1",
"size": "1457",
"license": "mit",
"hash": 9146480864474138000,
"line_mean": 21.78125,
"line_max": 121,
"alpha_frac": 0.6719286205,
"autogenerated": false,
"ratio": 3.2963800904977374,
"config_test": false,
"has_no_key... |
__author__ = 'M'
from setuptools import setup
import codecs
long_description = 'pytest-testlink is a plugin for py.test that reports to testlink'
VERSION = '0.3'
PYPI_VERSION = '0.3'
setup(
name='pytest-testlink',
description=long_description,
long_description=long_description,
version=VERSION,
u... | {
"repo_name": "manojklm/pytest-testlink",
"path": "setup.py",
"copies": "1",
"size": "1508",
"license": "mit",
"hash": -1762344656220024800,
"line_mean": 33.2727272727,
"line_max": 89,
"alpha_frac": 0.6193633952,
"autogenerated": false,
"ratio": 3.916883116883117,
"config_test": true,
"has_no... |
__author__ = 'm'
def rewrite_attributes(self, attribute_names, variables, skip_none=True):
"""
Rewrite variables specified in attributes list to the object
:param self: object to rewrite the values to
:param attribute_names: list of attributes names acceptable by the object
:param variables: dicti... | {
"repo_name": "mrozo/PyNas",
"path": "PyNasHelpers.py",
"copies": "1",
"size": "1583",
"license": "bsd-3-clause",
"hash": 7593042762231206000,
"line_mean": 36.6904761905,
"line_max": 80,
"alpha_frac": 0.6790903348,
"autogenerated": false,
"ratio": 4.885802469135802,
"config_test": false,
"has... |
__author__ = 'mnowotka'
from random import shuffle as shuf
from itertools import product
from pypoker.card import Card
from pypoker.hand import Hand
#------------------------------------------------------------------------------
class Deck(list):
def __init__(self, start="2", end="A", from_list=None):
... | {
"repo_name": "mnowotka/pypoker",
"path": "pypoker/deck.py",
"copies": "1",
"size": "1538",
"license": "apache-2.0",
"hash": -712136447291224000,
"line_mean": 29.1568627451,
"line_max": 79,
"alpha_frac": 0.4720416125,
"autogenerated": false,
"ratio": 3.76039119804401,
"config_test": false,
"h... |
__author__ = 'mnowotka'
import re
from random import randint
try:
from termcolor import colored
except ImportError:
colored = None
#------------------------------------------------------------------------------
class CardException(Exception):
pass
#------------------------------------------------------... | {
"repo_name": "mnowotka/pypoker",
"path": "pypoker/card.py",
"copies": "1",
"size": "5627",
"license": "apache-2.0",
"hash": 1022564365257077200,
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"alpha_frac": 0.4544162076,
"autogenerated": false,
"ratio": 3.6586475942782837,
"config_test": false,
... |
__author__ = 'mnowotka'
#------------------------------------------------------------------------------
class PokerEvaluator(object):
def sklansky_rank(self, hand):
"""
Description here: http://en.wikipedia.org/wiki/Texas_hold_%27em_starting_hands
"""
if len(hand) != 2:
... | {
"repo_name": "mnowotka/pypoker",
"path": "pypoker/evaluator.py",
"copies": "1",
"size": "2148",
"license": "apache-2.0",
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"alpha_frac": 0.4180633147,
"autogenerated": false,
"ratio": 3.5328947368421053,
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__author__ = 'mnu'
import logging
from django.core.urlresolvers import reverse
from django.http import HttpResponseRedirect
from django.views.generic import TemplateView, View
from google.appengine.api import users
from .forms import SourceForm
from .models import Source
logger = logging.getLogger('django')
class... | {
"repo_name": "manuel-alvarez/stateprices",
"path": "sources/views.py",
"copies": "1",
"size": "1927",
"license": "mit",
"hash": -7001007934416502000,
"line_mean": 31.1166666667,
"line_max": 89,
"alpha_frac": 0.6222106902,
"autogenerated": false,
"ratio": 4.1530172413793105,
"config_test": fals... |
__author__ = 'Moch'
#!/usr/bin/env python
# coding: utf-8
# import os
#
# for (k, v) in os.environ.items():
# # print "%s=%s" % (k, v)
# # print("%s = %s" % (k, v))
# print ",".join(k)
#
# import sys
#
# print "\n".join(sys.modules.keys())
# import os
# import urllib2
# request = urllib2.Request('http... | {
"repo_name": "snownothing/Python",
"path": "DiveIntoPython2/DiveIntoPython2.py",
"copies": "1",
"size": "2021",
"license": "mit",
"hash": -8813268272920265000,
"line_mean": 21.1208791209,
"line_max": 73,
"alpha_frac": 0.5534028813,
"autogenerated": false,
"ratio": 2.8512747875354107,
"config_t... |
"""Author model for Zinnia"""
from django.apps import apps
from django.conf import settings
from django.db import models
from django.urls import reverse
from zinnia.managers import EntryRelatedPublishedManager
from zinnia.managers import entries_published
def safe_get_user_model():
"""
Safe loading of the Us... | {
"repo_name": "Fantomas42/django-blog-zinnia",
"path": "zinnia/models/author.py",
"copies": "1",
"size": "1677",
"license": "bsd-3-clause",
"hash": 6643440783679945000,
"line_mean": 25.619047619,
"line_max": 78,
"alpha_frac": 0.6231365534,
"autogenerated": false,
"ratio": 4.289002557544757,
"co... |
__author__ = 'Modified by :aqeel'
# Copyright 2010-2014 Google
# 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 applicab... | {
"repo_name": "aqeel13932/DM",
"path": "HW12/ShortestPathFinder.py",
"copies": "1",
"size": "4960",
"license": "mit",
"hash": -4955127769302747000,
"line_mean": 45.3551401869,
"line_max": 91,
"alpha_frac": 0.6286290323,
"autogenerated": false,
"ratio": 4.3777581641659316,
"config_test": false,
... |
__author__ = 'Module Author'
def func_a():
pass
def func_b(arg1):
pass
def func_c(arg1, arg2) -> None:
pass
def func_d(arg1, arg2, arg3) -> int:
pass
def func_e(arg1, arg2, arg3, arg4) -> str:
pass
def func_f(arg1, arg2: int, arg3, arg4, arg5: int=123) -> bytes:
pass
def func_g(arg1, arg... | {
"repo_name": "prusnak/micropython-extmod-generator",
"path": "example/example.py",
"copies": "1",
"size": "1073",
"license": "mit",
"hash": -1427547865900667400,
"line_mean": 16.3064516129,
"line_max": 74,
"alpha_frac": 0.5507921715,
"autogenerated": false,
"ratio": 2.642857142857143,
"config_... |
__author__ = 'Mogeng'
from tripManager import calDistance
import numpy as np
class Dtw(object):
def __init__(self, seq1, seq2, distance_func=None):
'''
seq1, seq2 are two lists,
distance_func is a function for calculating
the local distance between two elements.
'''
... | {
"repo_name": "sdsingh/e-mission-server",
"path": "CFC_WebApp/main/DTW.py",
"copies": "1",
"size": "7758",
"license": "bsd-3-clause",
"hash": 4781045221101060000,
"line_mean": 32.0127659574,
"line_max": 83,
"alpha_frac": 0.4930394432,
"autogenerated": false,
"ratio": 3.14471017430077,
"config_t... |
__author__ = 'Mogeng'
# Standard imports
import numpy as np
# Our imports
import emission.core.common as ec
class Dtw(object):
def __init__(self, seq1, seq2, distance_func=None):
'''
seq1, seq2 are two lists,
distance_func is a function for calculating
the local distance between tw... | {
"repo_name": "joshzarrabi/e-mission-server",
"path": "emission/analysis/modelling/tour_model/trajectory_matching/DTW.py",
"copies": "2",
"size": "7819",
"license": "bsd-3-clause",
"hash": 3831408109945158000,
"line_mean": 31.8529411765,
"line_max": 83,
"alpha_frac": 0.4939250544,
"autogenerated": ... |
__author__ = 'mogui <mogui83@gmail.com>'
#
# Driver Constants
#
NAME = "OrientDB Python binary client (pyorient)"
VERSION = "1.4.2a"
SUPPORTED_PROTOCOL = 29
#
# Binary Types
#
# Types Constants
BOOLEAN = 1 # Single byte: 1 = true, 0 = false
BYTE = 2
SHORT = 3
INT = 4
LONG = 5
BYTES = 6 # Used for bina... | {
"repo_name": "optimuspaul/pyorient",
"path": "pyorient/constants.py",
"copies": "2",
"size": "4564",
"license": "apache-2.0",
"hash": -6822433584190255000,
"line_mean": 28.2564102564,
"line_max": 81,
"alpha_frac": 0.6069237511,
"autogenerated": false,
"ratio": 3.096336499321574,
"config_test":... |
__author__ = 'mogui <mogui83@gmail.com>'
#
# Driver Constants
#
NAME = "OrientDB Python binary client (pyorient)"
VERSION = "1.4.3"
SUPPORTED_PROTOCOL = 30
#
# Binary Types
#
# Types Constants
BOOLEAN = 1 # Single byte: 1 = true, 0 = false
BYTE = 2
SHORT = 3
INT = 4
LONG = 5
BYTES = 6 # Used for binar... | {
"repo_name": "ziyangzeng/pyorient",
"path": "pyorient/constants.py",
"copies": "1",
"size": "4563",
"license": "apache-2.0",
"hash": 4936013817814717000,
"line_mean": 28.25,
"line_max": 81,
"alpha_frac": 0.6068376068,
"autogenerated": false,
"ratio": 3.0977596741344198,
"config_test": false,
... |
__author__ = 'mogui <mogui83@gmail.com>'
#
# Driver Constants
#
NAME = "OrientDB Python binary client (pyorient)"
VERSION = "1.4.6"
SUPPORTED_PROTOCOL = 32
#
# Binary Types
#
# Types Constants
BOOLEAN = 1 # Single byte: 1 = true, 0 = false
BYTE = 2
SHORT = 3
INT = 4
LONG = 5
BYTES = 6 # Used for binar... | {
"repo_name": "lebedov/pyorient",
"path": "pyorient/constants.py",
"copies": "1",
"size": "4440",
"license": "apache-2.0",
"hash": -1906828345304425200,
"line_mean": 27.6451612903,
"line_max": 81,
"alpha_frac": 0.6018018018,
"autogenerated": false,
"ratio": 3.0897703549060545,
"config_test": fa... |
__author__ = 'mogui <mogui83@gmail.com>'
#
# Driver Constants
#
NAME = "OrientDB Python binary client (pyorient)"
VERSION = "1.5.3b"
SUPPORTED_PROTOCOL = 36
#
# Binary Types
#
# Types Constants
BOOLEAN = 1 # Single byte: 1 = true, 0 = false
BYTE = 2
SHORT = 3
INT = 4
LONG = 5
BYTES = 6 # Used for bina... | {
"repo_name": "Ostico/pyorient",
"path": "pyorient/constants.py",
"copies": "1",
"size": "4441",
"license": "apache-2.0",
"hash": 3936720325726169000,
"line_mean": 27.6516129032,
"line_max": 81,
"alpha_frac": 0.6018914659,
"autogenerated": false,
"ratio": 3.088317107093185,
"config_test": false... |
__author__ = 'mogui <mogui83@gmail.com>'
#
# Driver Constants
#
NAME = "OrientDB Python binary client (pyorient)"
VERSION = "1.5.5"
SUPPORTED_PROTOCOL = 36
#
# Binary Types
#
# Types Constants
BOOLEAN = 1 # Single byte: 1 = true, 0 = false
BYTE = 2
SHORT = 3
INT = 4
LONG = 5
BYTES = 6 # Used for binar... | {
"repo_name": "mogui/pyorient",
"path": "pyorient/constants.py",
"copies": "2",
"size": "4440",
"license": "apache-2.0",
"hash": -5590646958252619000,
"line_mean": 27.6451612903,
"line_max": 81,
"alpha_frac": 0.6018018018,
"autogenerated": false,
"ratio": 3.0897703549060545,
"config_test": fals... |
__author__ = 'mohammad'
import random
import string
import collections
import datetime
import itertools
import numpy
import datetime
import sys
import math
sys.path.append('../OpenStreetMap')
sys.path.append('../LookAhead')
from datetime import timedelta
from pymongo import MongoClient
from bson.objectid import Object... | {
"repo_name": "rosenjens/monad",
"path": "DynamicRoute/dynamicRoutes.py",
"copies": "1",
"size": "10642",
"license": "apache-2.0",
"hash": -5917443822539026000,
"line_mean": 44.6738197425,
"line_max": 188,
"alpha_frac": 0.4492576583,
"autogenerated": false,
"ratio": 4.561508786969567,
"config_t... |
__author__ = 'Mohammad'
import numpy as np
import tensorflow as tf
from tensorflow.contrib import learn, rnn
from data_loader import get_related_answers
# Parameters
embedding_dim = 300
word2vec_file = 'data/GoogleNews-vectors-negative300.bin'
learning_rate = 0.001
training_iters = 5000
batch_size = 128
display_step ... | {
"repo_name": "MohammadChavosh/VQA",
"path": "relate_to_question.py",
"copies": "1",
"size": "8048",
"license": "apache-2.0",
"hash": 2560217180115316700,
"line_mean": 43.7111111111,
"line_max": 144,
"alpha_frac": 0.6180417495,
"autogenerated": false,
"ratio": 3.683295194508009,
"config_test": ... |
__author__ = 'Mohammad'
import os
import numpy as np
import tensorflow as tf
from tensorflow.contrib import learn, rnn
from data_loader import get_related_answers, get_vqa_data, load_image
# Parameters
embedding_dim = 300
word2vec_file = 'data/GoogleNews-vectors-negative300.bin'
learning_rate = 0.001
batch_size = 8
d... | {
"repo_name": "MohammadChavosh/VQA",
"path": "train_without_finetune.py",
"copies": "1",
"size": "12076",
"license": "apache-2.0",
"hash": -677985856641459100,
"line_mean": 48.9008264463,
"line_max": 218,
"alpha_frac": 0.6435905929,
"autogenerated": false,
"ratio": 3.3656633221850614,
"config_t... |
__author__ = 'Mohammad'
import random
import json
import skimage.io
import skimage.transform
import skimage.color
def load_image(path, size=224):
img = skimage.io.imread(path)
if len(img.shape) == 2:
img = skimage.color.gray2rgb(img)
short_edge = min(img.shape[:2])
yy = int((img.shape[0] - short_edge) / 2)
xx... | {
"repo_name": "MohammadChavosh/VQA",
"path": "data_loader.py",
"copies": "1",
"size": "2474",
"license": "apache-2.0",
"hash": -8906363723146622000,
"line_mean": 37.65625,
"line_max": 92,
"alpha_frac": 0.7158447858,
"autogenerated": false,
"ratio": 2.9915356711003627,
"config_test": false,
"h... |
__author__ = 'Mohammad'
import tensorflow as tf
from train import load_related_train_data, load_data, batch_size, get_batch_for_test, display_step
def run():
questions_vocab_processor, answers_vocab_processor, max_question_length = load_related_train_data()
questions, answers, images_paths = load_data(questi... | {
"repo_name": "MohammadChavosh/VQA",
"path": "loader.py",
"copies": "1",
"size": "3139",
"license": "apache-2.0",
"hash": 7781891764321538000,
"line_mean": 45.8507462687,
"line_max": 167,
"alpha_frac": 0.6052883084,
"autogenerated": false,
"ratio": 3.7458233890214796,
"config_test": false,
"h... |
__author__ = 'Mohammadreza Ghanavati'
__email__ = "mohammadreza.ghanavati@informatik.uni-heidelberg.de"
from unidiff import parse_unidiff, LINE_TYPE_ADD, LINE_TYPE_DELETE
def findSeed(failingSeed, diffFilePath):
"""
Finds seed statement for the passing version from diff file and the seed statement of the fa... | {
"repo_name": "heiqs/crashfinder-plugin",
"path": "resources/diff.py",
"copies": "1",
"size": "2345",
"license": "mit",
"hash": -5541529045682273000,
"line_mean": 40.875,
"line_max": 109,
"alpha_frac": 0.6191897655,
"autogenerated": false,
"ratio": 4.217625899280575,
"config_test": false,
"ha... |
__author__ = "Mohit Sharma"
__credits__= "Charlie Mydlarz, Justin Salamon, Mohit Sharma"
__version__ = "0.1"
__status__ = "Development"
import dbus
import dbus.service
import sys
from wicd import misc
from wicd.translations import _
from blessings import Terminal
from tabulate import tabulate
class Wifi(object):
... | {
"repo_name": "Mohitsharma44/pywifi",
"path": "wifi.py",
"copies": "1",
"size": "10423",
"license": "mit",
"hash": 1903592347785468000,
"line_mean": 40.0354330709,
"line_max": 96,
"alpha_frac": 0.4723208289,
"autogenerated": false,
"ratio": 4.483010752688172,
"config_test": false,
"has_no_key... |
__author__ = 'mohnish'
from matplotlib.pyplot import *
from numpy import *
unit_step = lambda x: -1 if x < 0 else 1
converter = lambda x: '*' if x == 1 else 'o'
training_data = genfromtxt(open("data\demoTrain.csv","r"),delimiter=",", dtype="f8")[:]
expected_outcomes = genfromtxt(open("data\demoTarget.csv","r"),del... | {
"repo_name": "navinpai/CS706",
"path": "ScikitTry.py",
"copies": "1",
"size": "1324",
"license": "mit",
"hash": 7948750605269268000,
"line_mean": 27.8043478261,
"line_max": 92,
"alpha_frac": 0.6276435045,
"autogenerated": false,
"ratio": 3.3350125944584383,
"config_test": false,
"has_no_keyw... |
__author__ = 'mohnish'
from numpy import *
from matplotlib.pyplot import *
color_map = {1: "ro", 2: "bo", 3: "go"}
unit_step = lambda x: 0 if x < 0 else 1
data = genfromtxt(open("multiclassdata.csv","r"),delimiter=",", dtype="f8")[:]
def max_value_plus_index(l):
max_value = max(l)
max_value_index = l.index(m... | {
"repo_name": "navinpai/CS706",
"path": "MLPerceptron.py",
"copies": "1",
"size": "2016",
"license": "mit",
"hash": -8583532109392437000,
"line_mean": 25.5394736842,
"line_max": 81,
"alpha_frac": 0.5902777778,
"autogenerated": false,
"ratio": 2.510585305105853,
"config_test": false,
"has_no_k... |
__author__ = 'mohnish'
from numpy import *
from matplotlib.pyplot import *
color_map = {1: "ro", 2: "bo", 3: "go"}
unit_step = lambda x: 0 if x < 0 else 1
data = genfromtxt(open("multiclassdatatest.csv","r"),delimiter=",", dtype="f8")[:]
def max_value_plus_index(l):
max_value = max(l)
max_value_index = l.ind... | {
"repo_name": "navinpai/CS706",
"path": "MLPerceptronTest.py",
"copies": "1",
"size": "1067",
"license": "mit",
"hash": 6579150154809051000,
"line_mean": 27.8648648649,
"line_max": 82,
"alpha_frac": 0.671977507,
"autogenerated": false,
"ratio": 2.7714285714285714,
"config_test": false,
"has_n... |
__author__ = 'MOITIE Roderic'
from Tools import Vertex, PrioQueue
class Graph(object):
"""
Graphe represente par une liste de sommets
"""
def __init__(self):
self._vertices = []
def add_vertex(self, v):
self._vertices.append(v)
def read(self, file_name):
"""
... | {
"repo_name": "adrien-bellaiche/Repartition_Unpreferred",
"path": "ford_fulkerson.py",
"copies": "1",
"size": "3903",
"license": "mit",
"hash": -6108946845126017000,
"line_mean": 29.7401574803,
"line_max": 107,
"alpha_frac": 0.5070458622,
"autogenerated": false,
"ratio": 3.544959128065395,
"con... |
__author__ = 'MOITIE Roderic'
class Vertex(object):
"""
Classe representant les sommets
"""
"""
Variables de classe pour les couleurs de marquage
"""
WHITE = 0
GREY = 1
BLACK = 2
def __init__(self, label, distance=0):
"""
Constructeur
"""
self.l... | {
"repo_name": "adrien-bellaiche/Repartition_Unpreferred",
"path": "Tools.py",
"copies": "1",
"size": "2920",
"license": "mit",
"hash": 4317486884750483000,
"line_mean": 22.36,
"line_max": 109,
"alpha_frac": 0.4993150685,
"autogenerated": false,
"ratio": 3.403263403263403,
"config_test": false,
... |
__author__ = 'mojosaurus'
import sys
from com.demimojo.netflix.loader import Constants
from sklearn.preprocessing import normalize
import csv
from com import logger
import glob
from scipy.sparse import lil_matrix
import numpy as np
class PreProcess():
def __init__(self):
logger.info("Starting pre-procesi... | {
"repo_name": "mojosaurus/netflix-project",
"path": "com/demimojo/netflix/matrix/preprocessing.py",
"copies": "1",
"size": "4272",
"license": "apache-2.0",
"hash": -7862415544619996000,
"line_mean": 36.1565217391,
"line_max": 129,
"alpha_frac": 0.5922284644,
"autogenerated": false,
"ratio": 3.880... |
"""This module exports the Rstylelint plugin class."""
import re
import sublime
import os
from os.path import basename
from SublimeLinter.lint import Linter, util
def _make_text_safeish(text, method='decode'):
# The unicode decode here is because sublime converts to unicode inside
# insert in such... | {
"repo_name": "mom1/SublimeLinter-contrib-rstylelint",
"path": "linter.py",
"copies": "1",
"size": "3479",
"license": "mit",
"hash": 3016880412385242600,
"line_mean": 37.8,
"line_max": 113,
"alpha_frac": 0.6213420041,
"autogenerated": false,
"ratio": 3.434517766497462,
"config_test": false,
"... |
__author__ = 'mongolrgata'
import binascii
import json
import os
import re
import sys
import tempfile
import byteshift
import dearcer
import parcker
def import_json(json_filename):
"""
:param json_filename:
:type json_filename: str
:return:
"""
with open(json_filename, 'rt', encoding='utf-8... | {
"repo_name": "mongolrgata/cool-beauty-tools",
"path": ".ws2-tools/w2jImport/w2jImport.py",
"copies": "1",
"size": "1929",
"license": "mit",
"hash": 5536807300425556000,
"line_mean": 25.4246575342,
"line_max": 98,
"alpha_frac": 0.5370658372,
"autogenerated": false,
"ratio": 3.314432989690722,
"... |
__author__ = 'mongolrgata'
import binascii
import json
import re
import sys
import os
def merge(a, b, path=None):
if path is None: path = []
for key in b:
if key in a:
if isinstance(a[key], dict) and isinstance(b[key], dict):
merge(a[key], b[key], path + [str(key)])
... | {
"repo_name": "mongolrgata/mongolrgata-junkbox",
"path": "w2jMerge/w2jMerge.py",
"copies": "1",
"size": "1316",
"license": "mit",
"hash": 1051668676828359800,
"line_mean": 24.8039215686,
"line_max": 118,
"alpha_frac": 0.5098784195,
"autogenerated": false,
"ratio": 3.0892018779342725,
"config_te... |
__author__ = 'mongolrgata'
import binascii
import json
import re
import sys
def rotr8(int8, shift):
"""
:param int8:
:type int8: int
:param shift:
:type shift: int
:return:
:rtype: int
"""
return (int8 >> shift) | (int8 << (8 - shift) & 0xff)
def shift_decode(string):
"""
... | {
"repo_name": "mongolrgata/cool-beauty-tools",
"path": ".ws2-tools/ws2json/ws2json.py",
"copies": "1",
"size": "2128",
"license": "mit",
"hash": 2454531605858635300,
"line_mean": 21.8817204301,
"line_max": 89,
"alpha_frac": 0.4962406015,
"autogenerated": false,
"ratio": 3.325,
"config_test": fa... |
__author__ = 'mongolrgata'
import json
import os
import sys
def dict_merge(dict1, dict2):
"""
:param dict1:
:type dict1: dict
:param dict2:
:type dict2: dict
:return:
"""
for key in dict2:
if key in dict1:
if isinstance(dict1[key], dict) and isinstance(dict2[key],... | {
"repo_name": "mongolrgata/cool-beauty-tools",
"path": ".ws2-tools/w2jMerge/w2jMerge.py",
"copies": "1",
"size": "1295",
"license": "mit",
"hash": -6164711685605547000,
"line_mean": 20.9491525424,
"line_max": 97,
"alpha_frac": 0.5698841699,
"autogenerated": false,
"ratio": 3.5,
"config_test": f... |
__author__ = 'mongolrgata'
import os
import struct
import sys
def read_unsigned_int32(file):
"""
:param file:
:type file: io.FileIO
:return:
:rtype: int
"""
return struct.unpack('<L', file.read(4))[0]
def extract_png(pna_filename):
"""
:param pna_filename:
:type pna_filenam... | {
"repo_name": "mongolrgata/cool-beauty-tools",
"path": ".pna-tools/ePNA/ePNA.py",
"copies": "1",
"size": "1267",
"license": "mit",
"hash": -6549846147279906000,
"line_mean": 21.625,
"line_max": 108,
"alpha_frac": 0.5588003157,
"autogenerated": false,
"ratio": 3.175438596491228,
"config_test": f... |
__author__ = 'mongolrgata'
import os
import struct
import sys
NUL_CHAR16 = chr(0).encode('utf-16le')
def read_unsigned_int32(file):
"""
:param file:
:type file: io.FileIO
:return:
:rtype: int
"""
return struct.unpack('<L', file.read(4))[0]
def read_filename(file):
"""
:param f... | {
"repo_name": "mongolrgata/cool-beauty-tools",
"path": ".arc-tools/dearcer/dearcer.py",
"copies": "1",
"size": "1877",
"license": "mit",
"hash": -1538531850915452400,
"line_mean": 19.1827956989,
"line_max": 86,
"alpha_frac": 0.5652637187,
"autogenerated": false,
"ratio": 3.3045774647887325,
"co... |
__author__ = 'mongolrgata'
import os
import struct
import sys
NUL_CHAR16 = chr(0).encode('utf-16le')
def write_unsigned_int32(file, value):
"""
:param file:
:type file: io.FileIO
:param value:
:type value: int
:return:
:rtype: int
"""
return file.write(struct.pack('<L', value))
... | {
"repo_name": "mongolrgata/cool-beauty-tools",
"path": ".arc-tools/parcker/parcker.py",
"copies": "1",
"size": "2333",
"license": "mit",
"hash": 171659694679910140,
"line_mean": 22.33,
"line_max": 114,
"alpha_frac": 0.5953707673,
"autogenerated": false,
"ratio": 3.3139204545454546,
"config_test... |
__author__ = 'mongolrgata'
import os
import sys
import tempfile
import dearcer
import parcker
bad_prefixes = [
'A小鳥',
'Bあげは',
'C天音',
'D亜紗',
'E夜瑠',
'Fひばり',
'Gほたる',
'H朱莉',
'I佳奈子',
'J達也',
'K柾次',
'L鯨',
'M碧',
'Nイスカ',
'O早苗',
'P亮子',
'Q由佳',
'Rハット',
... | {
"repo_name": "mongolrgata/cool-beauty-tools",
"path": "localeFixer/localeFixer.py",
"copies": "1",
"size": "3039",
"license": "mit",
"hash": -4694707255742714000,
"line_mean": 22.64,
"line_max": 120,
"alpha_frac": 0.4707275804,
"autogenerated": false,
"ratio": 3.456140350877193,
"config_test":... |
__author__ = 'mongolrgata'
import sys
def rotr8(int8, shift_size):
"""
:param int8:
:type int8: int
:param shift_size:
:type shift_size: int
:return:
:rtype: int
"""
return (int8 >> shift_size) | (int8 << (8 - shift_size) & 0xff)
def shift_decode(string):
"""
:param str... | {
"repo_name": "mongolrgata/cool-beauty-tools",
"path": ".ws2-tools/byteshift/byteshift.py",
"copies": "1",
"size": "1311",
"license": "mit",
"hash": -8666138742060044000,
"line_mean": 16.9589041096,
"line_max": 67,
"alpha_frac": 0.5514874142,
"autogenerated": false,
"ratio": 3.1743341404358354,
... |
__author__ = 'monk-ee'
"""This module provides an interface to the billing report
in the amazon S3 billing bucket.
"""
import os
import boto
import zipfile
from boto.s3.connection import S3Connection
from datetime import datetime
from boto.s3.key import Key
from flask import flash
from barnacles import app
class Fe... | {
"repo_name": "monk-ee/barnacles",
"path": "barnacles/modules/fetch.py",
"copies": "1",
"size": "2464",
"license": "apache-2.0",
"hash": -149741412495304740,
"line_mean": 37.5,
"line_max": 167,
"alpha_frac": 0.6176948052,
"autogenerated": false,
"ratio": 3.955056179775281,
"config_test": true,
... |
__author__ = "Monte Goode"
__author__ = "Karan Vahi"
import time
from sqlalchemy import exc
from Pegasus.db.base_loader import BaseLoader
from Pegasus.db.schema import *
class DashboardLoader(BaseLoader):
MAX_RETRIES = 10 # maximum number of retries in case of operational errors that arise because of databas... | {
"repo_name": "pegasus-isi/pegasus",
"path": "packages/pegasus-python/src/Pegasus/db/dashboard_loader.py",
"copies": "1",
"size": "13908",
"license": "apache-2.0",
"hash": -3473493743086703000,
"line_mean": 32.9219512195,
"line_max": 136,
"alpha_frac": 0.533649698,
"autogenerated": false,
"ratio"... |
__author__ = "Monte Goode"
__author__ = "Karan Vahi"
import time
from sqlalchemy import exc, orm
from Pegasus.db.base_loader import BaseLoader
from Pegasus.db.schema import *
from Pegasus.netlogger import util
class WorkflowLoader(BaseLoader):
"""Load into the Stampede SQL schema through SQLAlchemy.
Param... | {
"repo_name": "pegasus-isi/pegasus",
"path": "packages/pegasus-python/src/Pegasus/db/workflow_loader.py",
"copies": "1",
"size": "45010",
"license": "apache-2.0",
"hash": 1065218631475402000,
"line_mean": 34.7931583134,
"line_max": 136,
"alpha_frac": 0.5353840683,
"autogenerated": false,
"ratio":... |
__author__ = "Monte Goode"
import logging
import time
from sqlalchemy import orm
from Pegasus.db import connection
from Pegasus.db.schema import *
log = logging.getLogger(__name__)
"""
Module to expunge a workflow and the associated data from
a stampede schema database in the case of running with the replay
option... | {
"repo_name": "pegasus-isi/pegasus",
"path": "packages/pegasus-python/src/Pegasus/db/expunge.py",
"copies": "1",
"size": "3760",
"license": "apache-2.0",
"hash": -4865273342474853000,
"line_mean": 30.3333333333,
"line_max": 87,
"alpha_frac": 0.6417553191,
"autogenerated": false,
"ratio": 3.664717... |
__author__ = 'moonkey'
from keras import models, layers
import logging
import numpy as np
# from src.data_util.synth_prepare import SynthGen
import keras.backend as K
import tensorflow as tf
def squeeze_dim(x, axis=-1):
return K.squeeze(x, axis=axis)
def squeeze_dim_shape(input_shape, axis=-1):
if axis == ... | {
"repo_name": "dashayushman/air-script",
"path": "src/model/cnn.py",
"copies": "1",
"size": "4374",
"license": "mit",
"hash": 6412278035037202000,
"line_mean": 32.9069767442,
"line_max": 79,
"alpha_frac": 0.5105166895,
"autogenerated": false,
"ratio": 3.8537444933920706,
"config_test": false,
... |
__author__ = 'moonkey'
#from keras import models, layers
import logging
import numpy as np
# from src.data_util.synth_prepare import SynthGen
#import keras.backend as K
import tensorflow as tf
def var_random(name, shape, regularizable=False):
'''
Initialize a random variable using xavier initialization.
... | {
"repo_name": "da03/Attention-OCR",
"path": "src/model/cnn.py",
"copies": "1",
"size": "5033",
"license": "mit",
"hash": 6154679094570008000,
"line_mean": 29.6890243902,
"line_max": 106,
"alpha_frac": 0.6181204053,
"autogenerated": false,
"ratio": 3.1915028535193404,
"config_test": false,
"ha... |
__author__ = 'moonkey'
import logging
import numpy as np
# from src.data_util.synth_prepare import SynthGen
import tensorflow as tf
def var_random(name, shape, regularizable=False):
'''
Initialize a random variable using xavier initialization.
Add regularization if regularizable=True
:param name:
... | {
"repo_name": "jvpoulos/Attention-OCR",
"path": "src/model/cnn.py",
"copies": "1",
"size": "5032",
"license": "mit",
"hash": 5114765222818953000,
"line_mean": 30.0617283951,
"line_max": 106,
"alpha_frac": 0.6158585056,
"autogenerated": false,
"ratio": 3.17877447883765,
"config_test": false,
"... |
__author__ = 'moonkey'
import os
import numpy as np
from PIL import Image
from collections import Counter
import cPickle
import random
from bucketdata import BucketData
class DataGen(object):
GO = 1
EOS = 2
def __init__(self,
data_root, annotation_fn,
evaluate = False,
... | {
"repo_name": "dashayushman/air-script",
"path": "src/data_util/data_gen_original.py",
"copies": "1",
"size": "5333",
"license": "mit",
"hash": 4018030062194023400,
"line_mean": 36.0347222222,
"line_max": 108,
"alpha_frac": 0.4740296269,
"autogenerated": false,
"ratio": 3.7137883008356547,
"con... |
__author__ = 'moonkey'
import os
import numpy as np
from PIL import Image
from collections import Counter
import pickle as cPickle
import random, math
from data_util.bucketdata import BucketData
class DataGen(object):
GO = 1
EOS = 2
def __init__(self,
data_root, annotation_fn,
eva... | {
"repo_name": "jvpoulos/Attention-OCR",
"path": "src/data_util/data_gen.py",
"copies": "1",
"size": "7051",
"license": "mit",
"hash": 2884980561224070700,
"line_mean": 36.9032258065,
"line_max": 111,
"alpha_frac": 0.4724074337,
"autogenerated": false,
"ratio": 3.4965277777777777,
"config_test":... |
__author__ = 'moonkey'
import os
import numpy as np
from PIL import Image
from collections import Counter
import pickle as cPickle
import random, math
from data_util.bucketdata import BucketData
class DataGen(object):
GO = 1
EOS = 2
def __init__(self,
data_root, annotation_fn,
... | {
"repo_name": "da03/Attention-OCR",
"path": "src/data_util/data_gen.py",
"copies": "1",
"size": "5682",
"license": "mit",
"hash": 7739982919184089000,
"line_mean": 37.3918918919,
"line_max": 126,
"alpha_frac": 0.4868004224,
"autogenerated": false,
"ratio": 3.63531669865643,
"config_test": true,... |
__author__ = 'moonkey'
import os
import numpy as np
from PIL import Image
from collections import Counter
import pickle as cPickle
import random
import math
class BucketData(object):
def __init__(self):
self.max_width = 0
self.max_label_len = 0
self.data_list = []
self.data_len_lis... | {
"repo_name": "jvpoulos/Attention-OCR",
"path": "src/data_util/bucketdata.py",
"copies": "1",
"size": "4604",
"license": "mit",
"hash": 294744919712322700,
"line_mean": 38.6982758621,
"line_max": 87,
"alpha_frac": 0.545178106,
"autogenerated": false,
"ratio": 3.4905231235784684,
"config_test": ... |
__author__ = 'moonkey'
import os
import numpy as np
from PIL import Image
# from keras.preprocessing.sequence import pad_sequences
from collections import Counter
import pickle as cPickle
import random
import math
class BucketData(object):
def __init__(self):
self.max_width = 0
self.max_label_len ... | {
"repo_name": "da03/Attention-OCR",
"path": "src/data_util/bucketdata.py",
"copies": "1",
"size": "4662",
"license": "mit",
"hash": -4039684739158413300,
"line_mean": 38.8461538462,
"line_max": 87,
"alpha_frac": 0.5486915487,
"autogenerated": false,
"ratio": 3.5,
"config_test": false,
"has_no... |
__author__ = 'moonkey'
import sys, argparse, logging
import numpy as np
from PIL import Image
import tensorflow as tf
tf.logging.set_verbosity(tf.logging.ERROR)
sess = tf.Session(config=tf.ConfigProto(allow_soft_placement=True))
import keras.backend as K
K.set_session(sess)
from model.model import Model
import exp... | {
"repo_name": "dashayushman/air-script",
"path": "src/launcher.py",
"copies": "1",
"size": "7758",
"license": "mit",
"hash": -8508304938098553000,
"line_mean": 48.7307692308,
"line_max": 80,
"alpha_frac": 0.5449858211,
"autogenerated": false,
"ratio": 4.348654708520179,
"config_test": true,
"... |
__author__ = 'moonkey'
import sys, argparse, logging
import numpy as np
from PIL import Image
import tensorflow as tf
tf.logging.set_verbosity(tf.logging.ERROR)
from model.model import Model
import exp_config
def process_args(args, defaults):
parser = argparse.ArgumentParser()
parser.add_argument('--gpu-i... | {
"repo_name": "jvpoulos/Attention-OCR",
"path": "src/launcher.py",
"copies": "1",
"size": "8908",
"license": "mit",
"hash": 7677901486465389000,
"line_mean": 52.6686746988,
"line_max": 100,
"alpha_frac": 0.5405253705,
"autogenerated": false,
"ratio": 4.420843672456575,
"config_test": true,
"h... |
__author__ = 'morita'
import pandas as pd
import numpy as np
from matplotlib import pyplot as plt
from collections import Counter, defaultdict
import seaborn as sns
from nltk import word_tokenize
from nltk.stem import WordNetLemmatizer
from nltk.stem.porter import *
from wordcloud import WordCloud
from sklearn.naive_... | {
"repo_name": "bluegrapes/DAT8Coursework",
"path": "project2/code/rf.py",
"copies": "1",
"size": "4529",
"license": "apache-2.0",
"hash": -3712705877107039000,
"line_mean": 29.6013513514,
"line_max": 124,
"alpha_frac": 0.6517995142,
"autogenerated": false,
"ratio": 3.4155354449472095,
"config_t... |
__author__ = 'mori.yuichiro'
from Crypto.Cipher import AES
from Crypto import Random
import StringIO
import binascii
class Encryptor():
"""
PKCS7 compatible encryption / decryption
"""
def __init__(self, encryption_key, initial_vector):
self.encryption_key = encryption_key
self... | {
"repo_name": "ymorired/s4backup",
"path": "crypt.py",
"copies": "1",
"size": "3250",
"license": "mit",
"hash": -425828046279591230,
"line_mean": 34.3260869565,
"line_max": 123,
"alpha_frac": 0.5898461538,
"autogenerated": false,
"ratio": 3.6931818181818183,
"config_test": false,
"has_no_keyw... |
__author__ = 'mori.yuichiro'
import os
import errno
import hashlib
def mkdir_p(path):
try:
os.makedirs(path)
except OSError as exc: # Python >2.5
if exc.errno == errno.EEXIST and os.path.isdir(path):
pass
else:
raise
def calc_md5_from_filename(file_path, blo... | {
"repo_name": "ymorired/s4backup",
"path": "util.py",
"copies": "1",
"size": "1499",
"license": "mit",
"hash": -485417270203695600,
"line_mean": 21.0441176471,
"line_max": 61,
"alpha_frac": 0.5857238159,
"autogenerated": false,
"ratio": 3.059183673469388,
"config_test": false,
"has_no_keyword... |
__author__ = 'mori.yuichiro'
import unittest
import os
import subprocess
import filecmp
import binascii
from crypt import Encryptor
BASE_TESTFILE_DIR = os.path.join(os.getcwd(), 'test')
class EncryptorTest(unittest.TestCase):
def setUp(self):
pass
def tearDown(self):
pass
def test_e... | {
"repo_name": "ymorired/s4backup",
"path": "test/crypt_test.py",
"copies": "1",
"size": "4811",
"license": "mit",
"hash": 1151850725096301700,
"line_mean": 31.5067567568,
"line_max": 113,
"alpha_frac": 0.5487424652,
"autogenerated": false,
"ratio": 2.7570200573065904,
"config_test": true,
"ha... |
__author__ = 'Morten'
from PIL import Image
from PIL import ExifTags
import PIL
import os, shutil, hashlib, time
#Folder to start search from:
root_folder = "/Users/Morten/"
#Folder to place Photos folder:
dest_folder = "/Users/Morten/Desktop/"
#Picture minimum size:
min_width = 500
min_height = 500
#Prepare hash list... | {
"repo_name": "MTelling/ImageSorter",
"path": "main.py",
"copies": "1",
"size": "5133",
"license": "mit",
"hash": 7444759425495576000,
"line_mean": 25.7395833333,
"line_max": 96,
"alpha_frac": 0.5735437366,
"autogenerated": false,
"ratio": 3.765957446808511,
"config_test": false,
"has_no_keyw... |
__author__ = 'moshebasanchig'
from base_classes import Base
import pandas as pd
class Transformers(Base):
def __init__(self):
self._execution_plan = None
def combine(self, stream1, stream2, left_on=None, right_on=None, how='inner', suffixes=('_x', '_y')):
"""
takes two input streams ... | {
"repo_name": "Convertro/Hydro",
"path": "src/hydro/transformers.py",
"copies": "1",
"size": "1552",
"license": "mit",
"hash": 4423127675036154400,
"line_mean": 33.4888888889,
"line_max": 109,
"alpha_frac": 0.6095360825,
"autogenerated": false,
"ratio": 4.1386666666666665,
"config_test": false,... |
__author__ = 'moshebasanchig'
from hydro.base_classes import PlanObject
from hydro.base_classes import OptimizerBase
class GeoQueriesOptimizer(OptimizerBase):
def get_plan(self, source_id, params, conf):
"""
a plan is a simple tuple
"""
plans = {
'geo_widget': {'plan':... | {
"repo_name": "Convertro/Hydro",
"path": "src/sample/geo_queries/optimizer.py",
"copies": "1",
"size": "1030",
"license": "mit",
"hash": -272291020079069980,
"line_mean": 32.2580645161,
"line_max": 64,
"alpha_frac": 0.5796116505,
"autogenerated": false,
"ratio": 3.772893772893773,
"config_test"... |
__author__ = 'moshebasanchig'
from hydro.connectors.base_classes import DBBaseConnector, DSN, CONNECTION_STRING
import pyodbc
from hydro.exceptions import HydroException
class VerticaConnector(DBBaseConnector):
"""
implementation of Vertica connector, base function that need to be implemented are _connect, _... | {
"repo_name": "Convertro/Hydro",
"path": "src/hydro/connectors/vertica.py",
"copies": "1",
"size": "1286",
"license": "mit",
"hash": -3609402788754154000,
"line_mean": 38,
"line_max": 116,
"alpha_frac": 0.6391912908,
"autogenerated": false,
"ratio": 3.9207317073170733,
"config_test": false,
"... |
__author__ = 'moshebasanchig'
from importlib import import_module
from base_classes import Base, HydroCommandTemplate
from hydro.common.utils import create_cache_key
from copy import deepcopy
class QueryEngine(Base):
def __init__(self, modules_dir, connection_handler, cache_engine, execution_plan, logger):
... | {
"repo_name": "Convertro/Hydro",
"path": "src/hydro/query_engine.py",
"copies": "1",
"size": "4408",
"license": "mit",
"hash": 2774901463674206700,
"line_mean": 39.4403669725,
"line_max": 123,
"alpha_frac": 0.6379310345,
"autogenerated": false,
"ratio": 4.0664206642066425,
"config_test": false,... |
__author__ = 'moshebasanchig'
from importlib import import_module
from base_classes import Base
from connectors.base_classes import ConnectorBase
from hydro.exceptions import HydroException
DSN = 'dsn'
class ConnectionPool(Base):
CONN_POOL_SIZE = 1
pool = []
logical_names = set([])
def __init__(self... | {
"repo_name": "Convertro/Hydro",
"path": "src/hydro/connector_factory.py",
"copies": "1",
"size": "2702",
"license": "mit",
"hash": -3209430530716585500,
"line_mean": 30.7882352941,
"line_max": 104,
"alpha_frac": 0.606957809,
"autogenerated": false,
"ratio": 3.938775510204082,
"config_test": fa... |
__author__ = 'moshebasanchig'
import pandas as pd
from hydro.exceptions import HydroException
DSN = 'dsn'
CONNECTION_STRING = 'connection string'
class ConnectorBase(object):
_conn = None
def __init__(self):
self.logger = None
def _verify_connection_definitions(self):
raise HydroExcep... | {
"repo_name": "Convertro/Hydro",
"path": "src/hydro/connectors/base_classes.py",
"copies": "1",
"size": "2921",
"license": "mit",
"hash": 8225646737028235000,
"line_mean": 27.637254902,
"line_max": 116,
"alpha_frac": 0.5950017117,
"autogenerated": false,
"ratio": 4.385885885885886,
"config_test... |
__author__ = 'mosquito'
from functools import wraps
from flask import flash, redirect, jsonify, \
session, url_for, Blueprint, make_response
from project import db
from project.models import Appointment
################
#### config ####
################
api_blueprint = Blueprint('api', __name__)
###############... | {
"repo_name": "internetmosquito/flask-scheduler",
"path": "project/api/views.py",
"copies": "1",
"size": "2239",
"license": "apache-2.0",
"hash": 323681483326720200,
"line_mean": 28.4605263158,
"line_max": 91,
"alpha_frac": 0.5810629745,
"autogenerated": false,
"ratio": 3.8208191126279862,
"con... |
__author__ = 'mosquito'
import datetime
from flask import Flask, render_template, request
from flask.ext.sqlalchemy import SQLAlchemy
from flask.ext.bcrypt import Bcrypt
app = Flask(__name__)
app.config.from_pyfile('_config.py')
bcrypt = Bcrypt(app)
db = SQLAlchemy(app)
from project.users.views import users_blueprint... | {
"repo_name": "internetmosquito/flask-scheduler",
"path": "project/__init__.py",
"copies": "1",
"size": "1451",
"license": "apache-2.0",
"hash": -8158274114256666000,
"line_mean": 32,
"line_max": 65,
"alpha_frac": 0.6657477602,
"autogenerated": false,
"ratio": 3.5915841584158414,
"config_test":... |
__author__ = 'mosquito'
import datetime
from project import db
class Appointment(db.Model):
__tablename__ = "appointments"
appointment_id = db.Column(db.Integer, primary_key=True)
name = db.Column(db.String, nullable=False)
due_date = db.Column(db.DateTime, nullable=False)
priority = db.Column(... | {
"repo_name": "internetmosquito/flask-scheduler",
"path": "project/models.py",
"copies": "1",
"size": "1445",
"license": "apache-2.0",
"hash": 1309898843073300000,
"line_mean": 29.125,
"line_max": 78,
"alpha_frac": 0.6415224913,
"autogenerated": false,
"ratio": 3.4569377990430623,
"config_test"... |
__author__ = 'mosquito'
import logging
from logging import Formatter, FileHandler
from amazon.api import AmazonAPI
import bottlenose.api
import urllib2
from urllib2 import URLError
from scrapy.selector import Selector
import json
import os
import sys
from time import sleep
import xlwt
from view.button import Button
fro... | {
"repo_name": "internetmosquito/amazon_product_searcher",
"path": "main.py",
"copies": "1",
"size": "19324",
"license": "mit",
"hash": -7683355009636793000,
"line_mean": 42.6207674944,
"line_max": 123,
"alpha_frac": 0.5021217139,
"autogenerated": false,
"ratio": 4.279007971656333,
"config_test"... |
__author__ = 'mosquito'
import os
import unittest
from views import app, db
from _config import basedir
from models import RegisteredMail
TEST_DB = 'test.db'
class MainTests(unittest.TestCase):
############################
#### setup and teardown ####
############################
# executed prior t... | {
"repo_name": "internetmosquito/bloowatch_site",
"path": "test_main.py",
"copies": "1",
"size": "1655",
"license": "mit",
"hash": 8223059160421405000,
"line_mean": 27.0677966102,
"line_max": 74,
"alpha_frac": 0.5685800604,
"autogenerated": false,
"ratio": 3.778538812785388,
"config_test": true,... |
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