text stringlengths 0 1.05M | meta dict |
|---|---|
__author__ = 'korantin'
from nltk.util import ngrams
from sys import argv
from itertools import *
from codecs import open
from yaml.representer import Representer
from yaml import load,dump,add_representer
from collections import defaultdict
def everygrams(sequence, min_len=1, max_len=-1,pad_left=False,pad_right=Fals... | {
"repo_name": "Krolov18/Languages",
"path": "Kalaba_resolution/essai.py",
"copies": "1",
"size": "2628",
"license": "apache-2.0",
"hash": -1951115191478936800,
"line_mean": 36,
"line_max": 87,
"alpha_frac": 0.58073115,
"autogenerated": false,
"ratio": 3.3580562659846547,
"config_test": false,
... |
__author__ = 'kosala atapattu'
import time
from ansible import errors
def net_interface_list(values=[]):
return ','.join(str(':'.join(i)) for i in values)
def array_to_csv(values=[]):
return ','.join(values)
def get_image_name (values, resttime, strict):
from datetime import datetime
from ansible imp... | {
"repo_name": "Actifio/ansible_appaware_mount",
"path": "filter_plugins/custom.py",
"copies": "1",
"size": "6245",
"license": "mit",
"hash": 3486639176747987000,
"line_mean": 37.7888198758,
"line_max": 107,
"alpha_frac": 0.5409127302,
"autogenerated": false,
"ratio": 4.2253044654939105,
"config... |
__author__ = 'kosci'
import sys
from nose.tools import assert_equal
sys.path.append("../../")
from gfxlcd.driver.null.null_page import NullPage
from gfxlcd.driver.hd44780 import HD44780
from charlcd.buffered import CharLCD
class TestChip(object):
def setUp(self):
self.gfx_lcd = NullPage(132, 16, None, Fa... | {
"repo_name": "bkosciow/gfxlcd",
"path": "gfxlcd/tests/test_hd44780.py",
"copies": "1",
"size": "1244",
"license": "mit",
"hash": 1439217463563834000,
"line_mean": 28.619047619,
"line_max": 70,
"alpha_frac": 0.5795819936,
"autogenerated": false,
"ratio": 2.9689737470167064,
"config_test": false... |
__author__ = 'Kovachev'
from django.contrib.auth.decorators import login_required
from django.shortcuts import render_to_response, RequestContext, HttpResponseRedirect
from apps.post.models import Post
from apps.post.forms import UploadForm
from django.contrib.auth.models import User
from apps.member.models import Memb... | {
"repo_name": "Lyudmil-Kovachev/vertuto",
"path": "vertuto/apps/post/views.py",
"copies": "1",
"size": "1238",
"license": "mit",
"hash": -4584593536844360700,
"line_mean": 35.4411764706,
"line_max": 96,
"alpha_frac": 0.7140549273,
"autogenerated": false,
"ratio": 4.154362416107382,
"config_test... |
__author__ = 'Kovachev'
from django.db import models
from django.contrib.auth.models import User
from django.db.models.signals import post_save
from django_resized import ResizedImageField
class Member(models.Model):
user = models.OneToOneField(User)
name = models.CharField(max_length=100)
avatar = Resiz... | {
"repo_name": "Lyudmil-Kovachev/vertuto",
"path": "vertuto/apps/member/models.py",
"copies": "1",
"size": "1265",
"license": "mit",
"hash": 6692146326953250000,
"line_mean": 34.1388888889,
"line_max": 119,
"alpha_frac": 0.7249011858,
"autogenerated": false,
"ratio": 3.6350574712643677,
"config_... |
__author__ = 'Kovachev'
from django.db import models
from django import forms
from apps.member.models import Member
from tinymce.widgets import TinyMCE
from django_resized import ResizedImageField
CAT = (
('3D Modeling', '3D Modeling and Animation'),
('Game Development', 'Game Development'),
('Programming... | {
"repo_name": "Lyudmil-Kovachev/vertuto",
"path": "vertuto/apps/post/models.py",
"copies": "1",
"size": "2100",
"license": "mit",
"hash": 296589505136251700,
"line_mean": 38.641509434,
"line_max": 137,
"alpha_frac": 0.6966666667,
"autogenerated": false,
"ratio": 3.4768211920529803,
"config_test... |
__author__ = 'Kovachev'
from django.http import HttpResponseRedirect
from django.shortcuts import render_to_response
from django.template import RequestContext
from django.contrib.auth.decorators import login_required
#from apps.member.forms import RegistrationForm
#from apps.member.forms import LoginForm
from apps.me... | {
"repo_name": "Lyudmil-Kovachev/vertuto",
"path": "vertuto/apps/member/views.py",
"copies": "1",
"size": "1577",
"license": "mit",
"hash": -9106937065181342000,
"line_mean": 37.487804878,
"line_max": 110,
"alpha_frac": 0.6975269499,
"autogenerated": false,
"ratio": 3.9623115577889445,
"config_t... |
__author__ = 'Kovachev'
from django import forms
from apps.post.models import Post
from tinymce.widgets import TinyMCE
from django.contrib.auth.models import User
from apps.member.models import Member
from django.utils.encoding import smart_unicode
from PIL import Image
import StringIO
from django_resized.forms import... | {
"repo_name": "Lyudmil-Kovachev/vertuto",
"path": "vertuto/apps/post/forms.py",
"copies": "1",
"size": "1731",
"license": "mit",
"hash": 6436994332455192000,
"line_mean": 35.829787234,
"line_max": 130,
"alpha_frac": 0.6874638937,
"autogenerated": false,
"ratio": 3.5544147843942504,
"config_test... |
import os
import argparse
import struct
#The allowed file extensions
EXTENSIONS = [".exe", ".dll"]
def check_dir(directory):
try:
resultSet = set()
#Getting every entry in directory
for entry in os.listdir(directory):
fullpath = os.path.join(directory, entry)
#We are parsing only the files
#NOTE... | {
"repo_name": "kovleventer/FoD",
"path": "test/windows_arch_checker.py",
"copies": "1",
"size": "2378",
"license": "mit",
"hash": -4407691134901919000,
"line_mean": 26.0227272727,
"line_max": 162,
"alpha_frac": 0.6820857864,
"autogenerated": false,
"ratio": 3.1580345285524567,
"config_test": fa... |
__author__ = "Kozo Nishida"
__email__ = "knishida@riken.jp"
__version__ = "0.1.0"
__license__ = "MIT"
API_BASE = "http://rest.kegg.jp/"
import requests
import pandas as pd
from StringIO import StringIO
#from progressbar import ProgressBar
def search_pathway_object(cpd_ids):
map_list = requests.get('http://rest.k... | {
"repo_name": "kozo2/keggutil",
"path": "keggutil.py",
"copies": "1",
"size": "1650",
"license": "mit",
"hash": 6513739521357998000,
"line_mean": 33.375,
"line_max": 91,
"alpha_frac": 0.6048484848,
"autogenerated": false,
"ratio": 2.8947368421052633,
"config_test": false,
"has_no_keywords": f... |
__author__ = 'kpaskov'
from os import listdir
from datetime import datetime
from math import floor
method_to_times = {}
file_to_times = {}
root_file = '/Users/kpaskov/sgd-ng2_log/backend'
file_names = [x for x in listdir(root_file) if not x.startswith('.')]
for file_name in file_names:
print(file_name)
f = op... | {
"repo_name": "yeastgenome/SGDFrontend",
"path": "src/sgd/frontend/yeastgenome/performance_aggregate.py",
"copies": "1",
"size": "2683",
"license": "mit",
"hash": -3464591315456055300,
"line_mean": 36.2638888889,
"line_max": 90,
"alpha_frac": 0.581438688,
"autogenerated": false,
"ratio": 3.127039... |
__author__ = 'kpaskov'
import os
import sys
import httplib
import base64
import json
import new
import unittest
import sauceclient
from selenium import webdriver
from sauceclient import SauceClient
# import env variables
USERNAME = os.environ.get('SAUCE_USERNAME')
ACCESS_KEY = os.environ.get('SAUCE_ACCESS_KEY')
# poi... | {
"repo_name": "yeastgenome/SGDFrontend",
"path": "src/sgd/frontend/yeastgenome/tests/features/environment.py",
"copies": "1",
"size": "1805",
"license": "mit",
"hash": -3694588262623973400,
"line_mean": 33.0566037736,
"line_max": 157,
"alpha_frac": 0.6254847645,
"autogenerated": false,
"ratio": 3... |
__author__ = 'kpaskov'
import re
from urllib.parse import urlparse
from behave import step
from selenium.common.exceptions import NoSuchElementException
@step('I visit "{url}" for "{obj}"')
def visit_page_for(context, url, obj):
context.browser.get(context.base_url + url.replace('?', obj))
@step('I click the but... | {
"repo_name": "yeastgenome/SGDFrontend",
"path": "src/sgd/frontend/yeastgenome/tests/features/steps/__init__.py",
"copies": "1",
"size": "5859",
"license": "mit",
"hash": 3079942762400451000,
"line_mean": 37.0454545455,
"line_max": 131,
"alpha_frac": 0.6651305684,
"autogenerated": false,
"ratio":... |
__author__ = 'kpiorno'
import os
import math
from textwrap import dedent
from xml.dom.minidom import parse
from itertools import *
from kivy.graphics import *
from kivy.core.image import Image
from kivy.resources import resource_find
from kivy3dgui.objloader import ObjFile
from kivy.uix.widget import Widget
from kivy... | {
"repo_name": "kpiorno/kivy3dgui",
"path": "kivy3dgui/node.py",
"copies": "1",
"size": "26232",
"license": "mit",
"hash": -5566642357997231000,
"line_mean": 37.6902654867,
"line_max": 120,
"alpha_frac": 0.4947773711,
"autogenerated": false,
"ratio": 3.9458483754512637,
"config_test": false,
"... |
__author__ = 'kra869'
# coding=utf-8
from collections import namedtuple
import struct
import sys
import os
Message = namedtuple('Message', ['msg', 'params'])
Push = namedtuple('Push', "package, hash");
HEADER_STRUCT = "BL"
NAME = str(os.getpid())
def debug(msg):
sys.stderr.write(NAME + ":" + msg + "\n")
de... | {
"repo_name": "mikaelbrandin/armory",
"path": "client/protocol.py",
"copies": "1",
"size": "1743",
"license": "apache-2.0",
"hash": -6946125019994953000,
"line_mean": 20.0120481928,
"line_max": 67,
"alpha_frac": 0.5949512335,
"autogenerated": false,
"ratio": 3.3583815028901736,
"config_test": f... |
__author__ = 'kra869'
from . import base_client
import os
import getpass
import sys
import subprocess
class Client(base_client.IOClient):
PUSH = "ssh {server} \"cd {path}; armory-push\""
PULL = "ssh {server} \"cd {path}; armory-pull\""
def __init__(self, uri):
base_client.IOClient.__init__(self, u... | {
"repo_name": "mikaelbrandin/armory",
"path": "client/ssh_client.py",
"copies": "1",
"size": "1184",
"license": "apache-2.0",
"hash": 8484870045023240000,
"line_mean": 25.9318181818,
"line_max": 68,
"alpha_frac": 0.5329391892,
"autogenerated": false,
"ratio": 3.9335548172757475,
"config_test": ... |
__author__ = 'kra869'
import os
import subprocess
import sys
import pwd
from . import exceptions
from . import utils
from . import configurations
from . import output;
class StartException(exceptions.ArmoryException):
def __init__(self, msg):
super(StartException, self).__init__(msg)
class StopExcepti... | {
"repo_name": "mikaelbrandin/armory",
"path": "client/startstop.py",
"copies": "1",
"size": "5497",
"license": "apache-2.0",
"hash": -4204123184758665700,
"line_mean": 29.5444444444,
"line_max": 142,
"alpha_frac": 0.6276150628,
"autogenerated": false,
"ratio": 3.659786950732357,
"config_test": ... |
__author__ = 'kra869'
import os
import configparser
from . import utils
def directory_filter(args):
return os.getcwd();
def init(context):
parser = context.register_command('init', command_init, help='Initialize a new repository', directory_filter=directory_filter)
parser.add_argument('repository', me... | {
"repo_name": "mikaelbrandin/armory",
"path": "client/init.py",
"copies": "1",
"size": "1868",
"license": "apache-2.0",
"hash": 7130668096345215000,
"line_mean": 27.7538461538,
"line_max": 130,
"alpha_frac": 0.6852248394,
"autogenerated": false,
"ratio": 4.169642857142857,
"config_test": true,
... |
__author__ = 'kra869'
import os
def init(context):
parser = context.register_command('status', command_status, aliases=['ps', 'stat'], help='Show status information for one or more modules')
parser.add_argument('modules', metavar='MODULE', nargs='*')
return None
def sizeof_fmt(num, suffix='B'):
for... | {
"repo_name": "mikaelbrandin/armory",
"path": "client/status.py",
"copies": "1",
"size": "1899",
"license": "apache-2.0",
"hash": 6630313525134508000,
"line_mean": 27.7878787879,
"line_max": 143,
"alpha_frac": 0.5592417062,
"autogenerated": false,
"ratio": 3.331578947368421,
"config_test": fals... |
__author__ = 'kra869'
import subprocess
import hashlib
import os
from ar.semantic_version import Spec as VersionSpec
from . import output
def register_scheme(scheme):
for method in [s for s in dir(urlparse) if s.startswith('uses_')]:
getattr(urlparse, method).append(scheme)
def cmd(cmd):
proc = su... | {
"repo_name": "mikaelbrandin/armory",
"path": "client/utils.py",
"copies": "1",
"size": "2218",
"license": "apache-2.0",
"hash": -3661036570090213000,
"line_mean": 25.734939759,
"line_max": 105,
"alpha_frac": 0.5734896303,
"autogenerated": false,
"ratio": 3.804459691252144,
"config_test": false... |
__author__ = 'kra869'
import argparse
import os
def is_armory_central_repo_dir(dir):
if not dir.endswith(os.sep):
dir += os.sep
if not os.path.isdir(dir):
return False
elif not os.access(dir, os.R_OK):
return False
elif not os.access(dir, os.W_OK):
return... | {
"repo_name": "mikaelbrandin/armory",
"path": "repository/context.py",
"copies": "1",
"size": "2318",
"license": "apache-2.0",
"hash": 2585743804371583000,
"line_mean": 36.0327868852,
"line_max": 212,
"alpha_frac": 0.6354616048,
"autogenerated": false,
"ratio": 4.024305555555555,
"config_test":... |
__author__ = 'Krager'
from enum import Enum
class Genre(Enum):
deliveryServiceJap = "宅配"
foodJap = "グルメ"
hotelAndJapaneseHotel = "ホテル・旅館"
hotel = "ホテル"
japaneseHotel = "旅館"
hairSalon = "ヘアサロン"
relaxation = "リラクゼーション"
otherCoupon = "その他のクーポン"
spa = "エステ"
lesson = "レッスン"
leisur... | {
"repo_name": "AJLiu/SPCSAI-CouponPurchasePrediction",
"path": "model/Genre.py",
"copies": "1",
"size": "1484",
"license": "mit",
"hash": -5934200556893375000,
"line_mean": 22.25,
"line_max": 36,
"alpha_frac": 0.5833333333,
"autogenerated": false,
"ratio": 1.6582466567607728,
"config_test": fal... |
import sys
import os
import tables
import tarfile
import fnmatch
import random
import numpy
import numpy as np
from scipy.io import wavfile
import theano
import theano.tensor as T
from theano.tensor.shared_randomstreams import RandomStreams
from midify import lpc_analysis, lpc_to_lsf, lpc_synthesis
from midify import ... | {
"repo_name": "kastnerkyle/speech_density",
"path": "speech_lstmrbm.py",
"copies": "1",
"size": "18687",
"license": "bsd-3-clause",
"hash": 1900937371227716000,
"line_mean": 38.8443496802,
"line_max": 91,
"alpha_frac": 0.6011665864,
"autogenerated": false,
"ratio": 3.275547765118317,
"config_te... |
__author__ = 'krawallmieze'
from baseparser import BaseParser
from BeautifulSoup import BeautifulSoup, Tag
class TAZParser(BaseParser):
domains = ['www.taz.de']
feeder_pat = '.+\/!\d{7}'
feeder_pages = ['http://www.taz.de/']
def _parse(self, html):
soup = BeautifulSoup(html, convertEntiti... | {
"repo_name": "catcosmo/newsdiffs",
"path": "parsers/taz.py",
"copies": "1",
"size": "2420",
"license": "mit",
"hash": 1877839333568659000,
"line_mean": 39.35,
"line_max": 130,
"alpha_frac": 0.5466942149,
"autogenerated": false,
"ratio": 3.884430176565008,
"config_test": false,
"has_no_keywor... |
__author__ = 'krishnaa'
import urllib2
import base64
import sys
import xml.etree.ElementTree as ET
def getOrgs(url,authtoken,method):
print authtoken
handler = urllib2.HTTPSHandler()
opener = urllib2.build_opener(handler)
url = url + '/api/org'
request = urllib2.Request(url)
request.add_header(... | {
"repo_name": "krisdigitx/python-vcloud-automation",
"path": "vcloud-automation/vcore/getOrgs.py",
"copies": "1",
"size": "1117",
"license": "apache-2.0",
"hash": -2670606874920178700,
"line_mean": 26.95,
"line_max": 93,
"alpha_frac": 0.6374216652,
"autogenerated": false,
"ratio": 3.5460317460317... |
__author__ = 'krishnaa'
from getvAPPDetails import getvAPPDetails
def checkVM(vm_name,url,authtoken,method):
print "checking if VM exists inside the VAPP"
deploy_vapp_status = getvAPPDetails(url,authtoken,method)
"""
while True:
deploy_vapp_status = getvAPPDetails(url,authtoken,method)
... | {
"repo_name": "krisdigitx/python-vcloud-automation",
"path": "vcloud-automation/vcore/checkVM.py",
"copies": "1",
"size": "1211",
"license": "apache-2.0",
"hash": 2527121446379791000,
"line_mean": 30.8684210526,
"line_max": 117,
"alpha_frac": 0.5788604459,
"autogenerated": false,
"ratio": 3.56176... |
__author__ = 'krishnaa'
import time
from addVM import addVM
from taskStatus import taskStatus
from getVAPP import getVAPP
from vmReconf import vmReconf
def processVM(vapp_name,vapp_desc,vapp_href,vdc_href,authtoken,new_vm_name,vm_ip,vm_network):
task_href = addVM(vapp_name,vapp_desc,vapp_href,vdc_href,authtoke... | {
"repo_name": "krisdigitx/python-vcloud-automation",
"path": "vcloud-automation/vcore/processVM.py",
"copies": "1",
"size": "1270",
"license": "apache-2.0",
"hash": 7960327105062449000,
"line_mean": 28.5348837209,
"line_max": 93,
"alpha_frac": 0.6078740157,
"autogenerated": false,
"ratio": 3.4324... |
__author__ = 'krishnaa'
import urllib2
import base64
import sys
import xml.etree.ElementTree as ET
def addVM(vapp_name,vapp_desc,vapp_href,template_url,authtoken,method):
handler = urllib2.HTTPSHandler()
opener = urllib2.build_opener(handler)
url = vapp_href + '/action/recomposeVApp'
request = urllib2... | {
"repo_name": "krisdigitx/python-vcloud-automation",
"path": "vcloud-automation/vcore/addVM.py",
"copies": "1",
"size": "2186",
"license": "apache-2.0",
"hash": -6618916672909655000,
"line_mean": 34.8524590164,
"line_max": 117,
"alpha_frac": 0.5777676121,
"autogenerated": false,
"ratio": 3.673949... |
__author__ = 'krishnaa'
import urllib2
import base64
import sys
import xml.etree.ElementTree as ET
def checkVAPP(vapp_name,url,authtoken,method):
handler = urllib2.HTTPSHandler()
opener = urllib2.build_opener(handler)
request = urllib2.Request(url)
request.add_header("Accept",'application/*+xml;versio... | {
"repo_name": "krisdigitx/python-vcloud-automation",
"path": "vcloud-automation/vcore/checkVAPP.py",
"copies": "1",
"size": "1272",
"license": "apache-2.0",
"hash": -7599311445588182000,
"line_mean": 29.3095238095,
"line_max": 120,
"alpha_frac": 0.6218553459,
"autogenerated": false,
"ratio": 3.45... |
__author__ = 'krishnaa'
import urllib2
import base64
import sys
import xml.etree.ElementTree as ET
def deleteVM(vapp_name,vapp_href,vm_href,authtoken,method):
handler = urllib2.HTTPSHandler()
opener = urllib2.build_opener(handler)
url = vapp_href + '/action/recomposeVApp'
request = urllib2.Request(url... | {
"repo_name": "krisdigitx/python-vcloud-automation",
"path": "vcloud-automation/vcore/deleteVM.py",
"copies": "1",
"size": "1809",
"license": "apache-2.0",
"hash": -3040129244220563000,
"line_mean": 35.9387755102,
"line_max": 117,
"alpha_frac": 0.5721393035,
"autogenerated": false,
"ratio": 3.890... |
__author__ = 'krishnaa'
import urllib2
import base64
import sys
import xml.etree.ElementTree as ET
def deployVapp(vapp_name,vapp_desc,vapp_poweron,vapp_deploy,url,authtoken,method,template_url):
handler = urllib2.HTTPSHandler()
opener = urllib2.build_opener(handler)
url = url + '/action/instantiateVAppTem... | {
"repo_name": "krisdigitx/python-vcloud-automation",
"path": "vcloud-automation/vcore/deployVapp.py",
"copies": "1",
"size": "1961",
"license": "apache-2.0",
"hash": 5548412749339733000,
"line_mean": 39.0408163265,
"line_max": 117,
"alpha_frac": 0.5471698113,
"autogenerated": false,
"ratio": 4.11... |
__author__ = 'krishnaa'
import urllib2
import base64
import sys
import xml.etree.ElementTree as ET
def getCatalog(url,authtoken,method,vapp_name):
handler = urllib2.HTTPSHandler()
opener = urllib2.build_opener(handler)
request = urllib2.Request(url)
request.add_header("Accept",'application/*+xml;versi... | {
"repo_name": "krisdigitx/python-vcloud-automation",
"path": "vcloud-automation/vcore/getCatalog.py",
"copies": "1",
"size": "1063",
"license": "apache-2.0",
"hash": -7326033599133311000,
"line_mean": 30.2647058824,
"line_max": 118,
"alpha_frac": 0.6509877705,
"autogenerated": false,
"ratio": 3.4... |
__author__ = 'krishnaa'
import urllib2
import base64
import sys
import xml.etree.ElementTree as ET
def getVDC(url,authtoken,vdc_lookup,catalog):
method = 'GET'
handler = urllib2.HTTPSHandler()
opener = urllib2.build_opener(handler)
request = urllib2.Request(url)
request.add_header("Accept",'applic... | {
"repo_name": "krisdigitx/python-vcloud-automation",
"path": "vcloud-automation/vcore/getVDC.py",
"copies": "1",
"size": "1361",
"license": "apache-2.0",
"hash": -929611736063884500,
"line_mean": 29.9545454545,
"line_max": 89,
"alpha_frac": 0.6260102866,
"autogenerated": false,
"ratio": 3.4808184... |
__author__ = 'krishnaa'
import urllib2
import base64
import sys
import xml.etree.ElementTree as ET
def poweroffVM(vm_href,authtoken,method):
handler = urllib2.HTTPSHandler()
opener = urllib2.build_opener(handler)
url = vm_href + '/action/undeploy'
request = urllib2.Request(url)
request.add_header(... | {
"repo_name": "krisdigitx/python-vcloud-automation",
"path": "vcloud-automation/vcore/poweroffVM.py",
"copies": "1",
"size": "1552",
"license": "apache-2.0",
"hash": 1775096907728628000,
"line_mean": 33.5111111111,
"line_max": 107,
"alpha_frac": 0.6166237113,
"autogenerated": false,
"ratio": 3.78... |
__author__ = 'krishnaa'
import urllib2
import base64
import sys
import xml.etree.ElementTree as ET
def vmReconf(vm_href,authtoken,method,vm_name,vm_ip,vm_network):
handler = urllib2.HTTPSHandler()
opener = urllib2.build_opener(handler)
url = vm_href + '/action/reconfigureVm'
request = urllib2.Request(... | {
"repo_name": "krisdigitx/python-vcloud-automation",
"path": "vcloud-automation/vcore/vmReconf.py",
"copies": "1",
"size": "3709",
"license": "apache-2.0",
"hash": 8282214888982520000,
"line_mean": 38.0421052632,
"line_max": 135,
"alpha_frac": 0.5335669992,
"autogenerated": false,
"ratio": 3.9042... |
__author__ = 'krishnab'
import numpy as np
import pandas as pd
from bokeh.plotting import figure, output_file, show
from bokeh.layouts import gridplot
from operator import add, sub
from .ColumnSpecs import MODEL_RUN_COLUMNS, EXPORT_COLUMNS_FOR_CSV
from .PlotComposerOverallAttrition import PlotComposerOverallAttrition
f... | {
"repo_name": "university-gender-evolution/py-university-gender-dynamics-pkg",
"path": "pyugend/Comparison.py",
"copies": "1",
"size": "45862",
"license": "mit",
"hash": -7469582392523791000,
"line_mean": 43.0980769231,
"line_max": 95,
"alpha_frac": 0.4762548515,
"autogenerated": false,
"ratio": ... |
__author__ = 'krishnab'
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
# CONSTANTS
line_colors = ['#7fc97f', '#beaed4', '#fdc086','#386cb0','#f0027f','#ffff99']
class Comparison():
def __init__(self, model_list):
self.name = 'All Models'
self.label = 'All Models'
... | {
"repo_name": "00krishna-research/py_university_gender_dynamics_pkg",
"path": "pyugend/Comparison.py",
"copies": "1",
"size": "14670",
"license": "mit",
"hash": 3197880970051462700,
"line_mean": 44.84375,
"line_max": 176,
"alpha_frac": 0.5648943422,
"autogenerated": false,
"ratio": 3.144020574367... |
__author__ = 'krishnab'
from operator import neg, truediv
import numpy as np
import pandas as pd
from numpy.random import binomial
from models.Models import Base_model
class Basic_stochastic_model(Base_model):
def __init__(self, **kwds):
Base_model.__init__(self, **kwds)
self.name = "Stochastic ... | {
"repo_name": "00krishna-research/py_university_gender_dynamics_pkg",
"path": "pyugend/BasicStochasticModelHPDeptSizeShrinks.py",
"copies": "1",
"size": "13334",
"license": "mit",
"hash": 8841023194995153000,
"line_mean": 46.2836879433,
"line_max": 118,
"alpha_frac": 0.5088495575,
"autogenerated": ... |
__author__ = 'krishnab'
from operator import neg, truediv
import numpy as np
import pandas as pd
from numpy.random import binomial
from models.Models import Base_model
class Basic_stochastic_model_fixed_promotion(Base_model):
def __init__(self, **kwds):
Base_model.__init__(self, **kwds)
self.nam... | {
"repo_name": "00krishna-research/py_university_gender_dynamics_pkg",
"path": "pyugend/BasicStochasticModelFixedPromotionDeptSizeStable.py",
"copies": "1",
"size": "13110",
"license": "mit",
"hash": 5464408429953944000,
"line_mean": 46.5,
"line_max": 118,
"alpha_frac": 0.5110602593,
"autogenerated"... |
__author__ = 'krishnab'
from operator import neg, truediv
import numpy as np
import pandas as pd
from numpy.random import binomial
from models.Models import Base_model
class Stochastic_model_with_promotion_and_first_hiring(Base_model):
def __init__(self, **kwds):
Base_model.__init__(self, **kwds)
... | {
"repo_name": "00krishna-research/py_university_gender_dynamics_pkg",
"path": "pyugend/StochasticModelWithPromotionAndFirstHiring.py",
"copies": "2",
"size": "12426",
"license": "mit",
"hash": 7317824180443879000,
"line_mean": 46.427480916,
"line_max": 167,
"alpha_frac": 0.5218895864,
"autogenerate... |
__author__ = 'krishnab'
# -*- coding: utf-8 -*-
'''
.. :module:: main.py
:module: main simulation module
:synopsis: This module contains the main() function for running the
simulation. This is the main file to run when executing this program.
:author: krishna bhogaonker <cyclotomiq@gmail.com>
... | {
"repo_name": "00krishna-research/py3k_friendship_simulator",
"path": "py3k_friendship_simulator/main.py",
"copies": "1",
"size": "6745",
"license": "bsd-3-clause",
"hash": -3577940852091260000,
"line_mean": 24.2621722846,
"line_max": 105,
"alpha_frac": 0.5648628614,
"autogenerated": false,
"rati... |
__author__ = 'krishnab'
# -*- coding: utf-8 -*-
'''
.. :module:: Sociomatrix.py
:module: Sociomatrix class
:synopsis: This module contains the Sociomatrix class to track
friendships in a simulation. This class allows me to pass friendship
changes to the object, and lets the object internally handle... | {
"repo_name": "00krishna-research/py3k_friendship_simulator",
"path": "py3k_friendship_simulator/Sociomatrix.py",
"copies": "1",
"size": "1743",
"license": "bsd-3-clause",
"hash": -6431249297061538000,
"line_mean": 20.8,
"line_max": 79,
"alpha_frac": 0.6069994263,
"autogenerated": false,
"ratio":... |
__author__ = 'Krishna Mudragada'
from collections import namedtuple
from operator import itemgetter
from pprint import pformat
class Node(namedtuple('Node', 'location left_child right_child')):
def __repr__(self):
return pformat(tuple(self))
def kdtree(point_list, depth=0):
try:
k = len(point_... | {
"repo_name": "mudragada/util-scripts",
"path": "Algos/KDTreeNode.py",
"copies": "1",
"size": "1097",
"license": "mit",
"hash": 1446431294700106500,
"line_mean": 29.5,
"line_max": 77,
"alpha_frac": 0.6362807657,
"autogenerated": false,
"ratio": 3.5387096774193547,
"config_test": false,
"has_n... |
__author__ = 'Krishna Mudragada'
import logging,time
class EuclidGCD:
def __init__(self):
logging.basicConfig(format='%(asctime)s %(message)s')
logging.getLogger().setLevel(logging.INFO)
logging.info("Initializing EuclidGCD..")
self.numberList = []
def addToList(self, number ):
... | {
"repo_name": "mudragada/util-scripts",
"path": "Algos/EuclidGCD.py",
"copies": "1",
"size": "1365",
"license": "mit",
"hash": 1106261380074822800,
"line_mean": 30.7674418605,
"line_max": 77,
"alpha_frac": 0.5545787546,
"autogenerated": false,
"ratio": 3.5362694300518136,
"config_test": false,
... |
from __future__ import division
import collections
import math
class Model:
def __init__(self, arffFile):
self.trainingFile = arffFile
self.features = {} #all feature names and their possible values (including the class label)
self.featureNameList = [] ... | {
"repo_name": "applecool/AI",
"path": "Naive Bayes in 50 lines/new_nb.py",
"copies": "1",
"size": "3516",
"license": "mit",
"hash": -2250884819957675000,
"line_mean": 59.6379310345,
"line_max": 175,
"alpha_frac": 0.5435153584,
"autogenerated": false,
"ratio": 4.656953642384106,
"config_test": f... |
__author__ = 'krishnasagar'
from django import forms
# Refer for forms.MultipleChoiceField always, its helpful -
# http://www.programcreek.com/python/example/58199/django.forms.MultipleChoiceField
class TrackForm(forms.Form):
def __init__(self, *args, **kwargs):
if 'choices' in kwargs:
choic... | {
"repo_name": "krishnasagar14/Project",
"path": "MusicApp/forms.py",
"copies": "1",
"size": "1975",
"license": "mit",
"hash": -5776447059622591000,
"line_mean": 49.6666666667,
"line_max": 116,
"alpha_frac": 0.5660759494,
"autogenerated": false,
"ratio": 4.398663697104677,
"config_test": false,
... |
__author__ = 'krishnasagar'
import requests
from django.core.cache import cache
class MusicTrack:
def __init__(self):
self.baseUrl = 'http://104.197.128.152:8000/v1/tracks?page=%s'
self.trackUrl = 'http://104.197.128.152:8000/v1/tracks/%s'
self.url = 'http://104.197.128.152:8000/v1/tracks... | {
"repo_name": "krishnasagar14/Project",
"path": "MusicApp/Music_Repo.py",
"copies": "1",
"size": "5305",
"license": "mit",
"hash": -7550833784666533000,
"line_mean": 33.6732026144,
"line_max": 93,
"alpha_frac": 0.5208294062,
"autogenerated": false,
"ratio": 3.816546762589928,
"config_test": fal... |
__author__ = 'krish'
import logging
# Change log level to suppress annoying IPv6 error
logging.getLogger("scapy.runtime").setLevel(logging.ERROR)
from scapy.automaton import Automaton, ATMT
class OpenFlowSession(Automaton):
# store request reply session as a map
# add the xid to subsequent requests
# st... | {
"repo_name": "krish7919/openflow-test",
"path": "src/of_automata.py",
"copies": "1",
"size": "1222",
"license": "mit",
"hash": -1721508958880341200,
"line_mean": 22.0566037736,
"line_max": 58,
"alpha_frac": 0.6170212766,
"autogenerated": false,
"ratio": 3.521613832853026,
"config_test": false,... |
__author__ = 'krish'
import logging
from struct import pack
from scapy.all import Packet, ShortEnumField, XByteField, ByteEnumField, ShortField, IntField, LongField, ByteField, XIntField, BitField
from scapy.layers.inet import IP, TCP
from scapy.packet import bind_layers
# Change log level to suppress annoying IPv6... | {
"repo_name": "krish7919/openflow-test",
"path": "src/of_protocol.py",
"copies": "1",
"size": "5974",
"license": "mit",
"hash": 3354579546362795000,
"line_mean": 31.2918918919,
"line_max": 137,
"alpha_frac": 0.5482089053,
"autogenerated": false,
"ratio": 3.6338199513381997,
"config_test": false... |
__author__ = 'kris'
class Stack(object):
def __init__(self, size=16):
self.stack = []
self.size = size
self.top = -1
def setSize(self, size):
print 'Now, size is', size
self.size = size
def isEmpty(self):
if self.top == -1:
return True
... | {
"repo_name": "dutwfk/pytest",
"path": "base/stack.py",
"copies": "1",
"size": "1286",
"license": "mit",
"hash": 2468001895555503600,
"line_mean": 18.7846153846,
"line_max": 54,
"alpha_frac": 0.4712286159,
"autogenerated": false,
"ratio": 3.6123595505617976,
"config_test": false,
"has_no_keyw... |
__author__ = 'Kristen'
# set (Kristen = 'KGerring')
from sympy import *
from pprint import pprint
#{'⊤': Tautology, \u22A5 True :⊨\u22A8 dict(TT='true', TF='true', FT='true', FF='true'),
#'<-', '⊂': Implies(y, x), 'x<<y, (x if y)', dict(TT='true', TF='true', FT='false', FF='true'),
#('->', ⊃): Implies(x, y) '(if x... | {
"repo_name": "KGerring/RevealMe",
"path": "Docs/RM2.py",
"copies": "1",
"size": "5806",
"license": "mit",
"hash": 1959152226482395600,
"line_mean": 54.9108910891,
"line_max": 456,
"alpha_frac": 0.5185054011,
"autogenerated": false,
"ratio": 2.4091296928327646,
"config_test": false,
"has_no_k... |
__author__ = 'Kristian Hinnenthal'
import json
import time
import tests.example_datatypes as ex
import twisted.internet.defer as defer
import unittest
class MaStaServerTester(object):
def __init__(self):
self.rpc = rpc.RpcLayer(u'amqp://fg-cn-sandman1.cs.upb.de:5672')
def test_deploy(self):
... | {
"repo_name": "CN-UPB/OpenBarista",
"path": "components/decaf-masta/tests/masta_server_test.py",
"copies": "1",
"size": "1080",
"license": "mpl-2.0",
"hash": 1014982284940072600,
"line_mean": 24.7380952381,
"line_max": 92,
"alpha_frac": 0.6518518519,
"autogenerated": false,
"ratio": 3.22388059701... |
__author__ = 'Kristin'
from django.shortcuts import render_to_response
from django.http import HttpResponseRedirect
from django.contrib import auth
from django.core.context_processors import csrf
from .forms import RegistrationForm
#Registration functions
def home(request):
return render_to_response('intro_text... | {
"repo_name": "KBratland/django_final",
"path": "Fruit_Finder/views.py",
"copies": "1",
"size": "1771",
"license": "apache-2.0",
"hash": 4042427308313460700,
"line_mean": 23.6111111111,
"line_max": 103,
"alpha_frac": 0.6871823828,
"autogenerated": false,
"ratio": 3.9977426636568847,
"config_tes... |
from datetime import datetime
from lxml import html
from juriscraper.OpinionSite import OpinionSite
class Site(OpinionSite):
def __init__(self, *args, **kwargs):
super(Site, self).__init__(*args, **kwargs)
self.court_id = self.__module__
self.url = 'http://www.state.il.us/court/Opinions/... | {
"repo_name": "m4h7/juriscraper",
"path": "juriscraper/opinions/united_states/state/illappct.py",
"copies": "2",
"size": "2183",
"license": "bsd-2-clause",
"hash": -1539632523310365000,
"line_mean": 35.3833333333,
"line_max": 119,
"alpha_frac": 0.5748969308,
"autogenerated": false,
"ratio": 3.384... |
from datetime import datetime
from lxml import html
from juriscraper.OpinionSite import OpinionSite
class Site(OpinionSite):
def __init__(self):
super(Site, self).__init__()
self.court_id = self.__module__
self.url = 'http://www.state.il.us/court/Opinions/recent_appellate.asp'
se... | {
"repo_name": "brianwc/juriscraper",
"path": "opinions/united_states/state/illappct.py",
"copies": "1",
"size": "2151",
"license": "bsd-2-clause",
"hash": -3017610357542220000,
"line_mean": 34.85,
"line_max": 119,
"alpha_frac": 0.5741515574,
"autogenerated": false,
"ratio": 3.392744479495268,
"... |
from datetime import datetime
from lxml import html
from juriscraper.OpinionSite import OpinionSite
from juriscraper.lib.string_utils import titlecase
class Site(OpinionSite):
def __init__(self, *args, **kwargs):
super(Site, self).__init__(*args, **kwargs)
self.court_id = self.__modul... | {
"repo_name": "m4h7/juriscraper",
"path": "juriscraper/opinions/united_states/state/ark.py",
"copies": "2",
"size": "2181",
"license": "bsd-2-clause",
"hash": 6980496607665161000,
"line_mean": 36.9464285714,
"line_max": 100,
"alpha_frac": 0.5878037597,
"autogenerated": false,
"ratio": 3.365740740... |
import re
from lxml import html
import time
from datetime import date
from juriscraper.OpinionSite import OpinionSite
from juriscraper.lib.string_utils import titlecase
class Site(OpinionSite):
def __init__(self, *args, **kwargs):
super(Site, self).__init__(*args, **kwargs)
self.c... | {
"repo_name": "Andr3iC/juriscraper",
"path": "opinions/united_states/state/nj.py",
"copies": "2",
"size": "2600",
"license": "bsd-2-clause",
"hash": 4317837264893861000,
"line_mean": 39.935483871,
"line_max": 108,
"alpha_frac": 0.5619230769,
"autogenerated": false,
"ratio": 3.5470668485675305,
... |
__author__ = 'Kristof Speeckaert'
import PyPDF2
import logging
from wand.image import Image as wandImage
from PIL import Image, ImageChops
from io import BufferedRandom, BytesIO
log = logging.getLogger(__name__)
log.addHandler(logging.NullHandler())
def split_pdf(src_filename, pdf_res, page_list=None... | {
"repo_name": "kspeeckaert/pyPdfCompare",
"path": "pyPdfCompare.py",
"copies": "1",
"size": "6219",
"license": "bsd-2-clause",
"hash": 3741969022081800700,
"line_mean": 37.8653846154,
"line_max": 121,
"alpha_frac": 0.6335423702,
"autogenerated": false,
"ratio": 3.669026548672566,
"config_test":... |
__author__ = 'Krivenko'
from model.contact import Contact
from random import randrange
def test_modify_contact_firstname(app,db,check_ui):
if app.contact.count()==0:
app.contact.create_contact( Contact(firstname="Alex", middlename="a", lastname="Kriv", nickname="sd", title="fdf",
... | {
"repo_name": "KrivenkoAlexander/python_tr",
"path": "test/test_modify_contact.py",
"copies": "1",
"size": "2503",
"license": "apache-2.0",
"hash": -5392162229204051000,
"line_mean": 59.6097560976,
"line_max": 159,
"alpha_frac": 0.5806841046,
"autogenerated": false,
"ratio": 3.202319587628866,
... |
__author__ = 'Krivenko'
from model.contact import Contact
import random
def test_del_contact(app,db,check_ui):
if len(db.get_contact_list())==0:
app.contact.create_contact( Contact(firstname="Alex", middlename="a", lastname="Kriv", nickname="sd", title="fdf",
... | {
"repo_name": "KrivenkoAlexander/python_tr",
"path": "test/test_del_contact.py",
"copies": "1",
"size": "1272",
"license": "apache-2.0",
"hash": -2709003356101652500,
"line_mean": 62.6,
"line_max": 159,
"alpha_frac": 0.5479559748,
"autogenerated": false,
"ratio": 3.5138121546961325,
"config_tes... |
__author__ = 'Krivenko'
from model.contact import Contact
class ContactHelper:
def __init__(self,app):
self.app = app
def init_new_user(self):
wd = self.app.wd
wd.find_element_by_link_text("add new").click()
def change_fields(self,field_name,text):
wd = self.app.wd
... | {
"repo_name": "KrivenkoAlexander/python_tr",
"path": "fixture/contact.py",
"copies": "1",
"size": "8687",
"license": "apache-2.0",
"hash": 2291712939147453700,
"line_mean": 40.5645933014,
"line_max": 153,
"alpha_frac": 0.6331299643,
"autogenerated": false,
"ratio": 3.418732782369146,
"config_te... |
__author__ = 'Krivenko'
from model.group import Group
class GroupHelper:
def __init__(self,app):
self.app=app
def Open_groups_page(self):
wd = self.app.wd
if not( wd.current_url.endswith("/group.php") and len(wd.find_elements_by_name("new"))>0):
wd.find_element_by_link_tex... | {
"repo_name": "KrivenkoAlexander/python_tr",
"path": "fixture/group.py",
"copies": "1",
"size": "3935",
"license": "apache-2.0",
"hash": 5347333655956659000,
"line_mean": 30.7338709677,
"line_max": 98,
"alpha_frac": 0.5941550191,
"autogenerated": false,
"ratio": 3.4187662901824503,
"config_test... |
__author__ = 'Krivenko'
from sys import maxsize
class Contact:
def __init__(self,firstname=None, middlename=None, lastname=None, nickname=None, title=None, company=None, address=None, homephone=None, mobilephone=None, workphone=None,secondaryphone=None,
fax=None,byear=None, ayear=None, addr... | {
"repo_name": "KrivenkoAlexander/python_tr",
"path": "model/contact.py",
"copies": "1",
"size": "2113",
"license": "apache-2.0",
"hash": 3123861938726135300,
"line_mean": 38.1296296296,
"line_max": 194,
"alpha_frac": 0.645054425,
"autogenerated": false,
"ratio": 3.5996592844974447,
"config_test... |
__author__ = 'Krivenko'
class SessionHelper:
def __init__(self,app):
self.app=app
def Login(self, username, password):
wd = self.app.wd
self.app.open_home_page()
wd.find_element_by_name("user").click()
wd.find_element_by_name("user").clear()
wd.find_element_by_... | {
"repo_name": "KrivenkoAlexander/python_tr",
"path": "fixture/session.py",
"copies": "1",
"size": "1475",
"license": "apache-2.0",
"hash": 5252058817132640000,
"line_mean": 27.9215686275,
"line_max": 73,
"alpha_frac": 0.5688135593,
"autogenerated": false,
"ratio": 3.329571106094808,
"config_tes... |
__author__ = 'Krivenko'
import mysql.connector
from model.group import Group
from model.contact import Contact
class DbFixture():
def __init__(self,host,name , user, password):
self.host=host
self.name= name
self. user= user
self.password = password
self.connection = mysql... | {
"repo_name": "KrivenkoAlexander/python_tr",
"path": "fixture/db.py",
"copies": "1",
"size": "2110",
"license": "apache-2.0",
"hash": 2739957145862802000,
"line_mean": 38.0925925926,
"line_max": 194,
"alpha_frac": 0.6180094787,
"autogenerated": false,
"ratio": 3.914656771799629,
"config_test": ... |
__author__ = 'krolev'
import os
import shlex
import argparse
import codecs
import subprocess
import re
import string
import urllib.request
import urllib.error
from bs4 import BeautifulSoup
from pyinotify import ProcessEvent, Notifier, ALL_EVENTS, WatchManager
import sqlite3
caractère_special = (' : ', ';')
net=... | {
"repo_name": "Krolov18/Languages",
"path": "Projet_media/Collecteur_texte 2.py",
"copies": "2",
"size": "6433",
"license": "apache-2.0",
"hash": -7603577026249327000,
"line_mean": 35.6171428571,
"line_max": 230,
"alpha_frac": 0.6471598002,
"autogenerated": false,
"ratio": 3.1212859230394545,
"... |
__author__ = "Krolev"
Nombres = {}
Dizaines = {}
#[Nombres.update({x:""}) for x in range(0,100000000000)]
centaines = {100:{"cent":"sâ"}}
milliers = {1000:{"mille":"mil"}}
millions = {1000000:{"million":"miljô"}}
milliards = {1000000000:{"milliard":"miljar"}}
dico ={}
def generer_dizaines(dico):
unites = {0:["zéro",... | {
"repo_name": "Krolov18/Languages",
"path": "Nombres/brouillon_1.py",
"copies": "1",
"size": "2868",
"license": "apache-2.0",
"hash": -2390775074868584400,
"line_mean": 27.1782178218,
"line_max": 190,
"alpha_frac": 0.5737877723,
"autogenerated": false,
"ratio": 2.0773722627737228,
"config_test"... |
__author__ = 'krolev'
y='''
class Nombres:
"""
1 - système 10^3 = on découpe l'intégral en séquences de trois unités avec un séquence incomplète à gauche si le reste
de la division est différent de 0.
Distinguons deux systèmes de représentations chiffrés. Le système court et le système long.
Cette... | {
"repo_name": "Krolov18/Languages",
"path": "Nombres/Nombres 2.py",
"copies": "1",
"size": "16762",
"license": "apache-2.0",
"hash": 2034507743464797700,
"line_mean": 58.8315412186,
"line_max": 908,
"alpha_frac": 0.6047445037,
"autogenerated": false,
"ratio": 2.754165979211351,
"config_test": f... |
__author__ = 'Krylik'
import argparse
import re
import os
import xml.etree.ElementTree as ET
from xml.dom import minidom
from shutil import copytree, ignore_patterns
argparser = argparse.ArgumentParser()
argparser.add_argument('indir',
metavar='input',
type=str,
... | {
"repo_name": "Krylik/Pidgin2AdiumEmoticons",
"path": "emoticonset_builder/__main__.py",
"copies": "1",
"size": "2429",
"license": "mit",
"hash": 1199312557671326700,
"line_mean": 36.96875,
"line_max": 111,
"alpha_frac": 0.6492383697,
"autogenerated": false,
"ratio": 3.6416791604197902,
"config... |
from decimal import Decimal
import hashlib
import logging
import time
import datetime
from django.utils import six
from six.moves.urllib.request import Request, urlopen
from six.moves.urllib.parse import urlencode
from django.contrib.sites.models import Site
from django.core.exceptions import ImproperlyConfigured
fro... | {
"repo_name": "pawciobiel/django-getpaid",
"path": "getpaid/backends/przelewy24/__init__.py",
"copies": "1",
"size": "7280",
"license": "mit",
"hash": -1711662172358539800,
"line_mean": 42.0769230769,
"line_max": 126,
"alpha_frac": 0.6145604396,
"autogenerated": false,
"ratio": 3.4034595605423097... |
from decimal import Decimal
import hashlib
import logging
import time
import urllib
import urllib2
import datetime
from django.contrib.sites.models import Site
from django.core.exceptions import ImproperlyConfigured
from django.core.urlresolvers import reverse
from django.utils.translation import ugettext_lazy as _
f... | {
"repo_name": "KrzysiekJ/django-getpaid",
"path": "getpaid/backends/przelewy24/__init__.py",
"copies": "1",
"size": "7203",
"license": "mit",
"hash": -2923699248689714700,
"line_mean": 42.3915662651,
"line_max": 126,
"alpha_frac": 0.6050256837,
"autogenerated": false,
"ratio": 3.4763513513513513,... |
__author__ = 'ksmith'
from physicsTable import *
from physicsTable.constants import *
import pygame as pg
import copy
sc = pg.display.set_mode((1000,620))
def checkN(tb,goalret,kapv=20,kapb=15,kapm=50000,perr=25):
i = 0
while True:
i += 1
ntb = makeNoisy(tb,kapv,kapb,kapm,perr)
ntb.set... | {
"repo_name": "kasmith/cbmm-project-christmas",
"path": "python-trials/checkNoisy.py",
"copies": "1",
"size": "1305",
"license": "mit",
"hash": 1949431421712494300,
"line_mean": 25.6530612245,
"line_max": 58,
"alpha_frac": 0.5540229885,
"autogenerated": false,
"ratio": 2.8744493392070485,
"conf... |
__author__ = 'ksmith'
# Based on http://psiturk.readthedocs.org/en/latest/retrieving.html
from sqlalchemy import create_engine, MetaData, Table
import json
import pandas as pd
# Production
db_url = "mysql://root:@56Bayes@localhost:3396/experiments"
table_name = 'basicRG_final'
# Test
#db_url = 'sqlite:///participant... | {
"repo_name": "kasmith/cbmm-project-christmas",
"path": "psiturk-rg-cont/grabData.py",
"copies": "5",
"size": "1740",
"license": "mit",
"hash": -5949114358001453000,
"line_mean": 30.6545454545,
"line_max": 70,
"alpha_frac": 0.7327586207,
"autogenerated": false,
"ratio": 3.4523809523809526,
"con... |
__author__ = 'kszalai'
try:
import traceback
import argparse
import textwrap
except ImportError as err:
traceback.print_exc()
exit(128)
class HistogrammerCommandline:
def __init__(self):
# predefinied paths
self.parser = argparse.ArgumentParser(prog="histogrammer",
... | {
"repo_name": "KAMI911/histogrammer",
"path": "libs/HistogrammerCommandline.py",
"copies": "1",
"size": "3311",
"license": "mpl-2.0",
"hash": 2147558777568749000,
"line_mean": 37.5,
"line_max": 114,
"alpha_frac": 0.540320145,
"autogenerated": false,
"ratio": 4.414666666666666,
"config_test": fa... |
__author__ = 'kszalai'
try:
import traceback
import textwrap
import glob
import os
import logging
import datetime
import numpy as np
import cv2
import multiprocessing
import pyexiv2
from datetime import date
except ImportError as err:
traceback.print_exc()
exit(128)
... | {
"repo_name": "KAMI911/histogrammer",
"path": "libs/HistogrammerWorkflow.py",
"copies": "1",
"size": "6068",
"license": "mpl-2.0",
"hash": -8683023225361506000,
"line_mean": 43.6176470588,
"line_max": 118,
"alpha_frac": 0.5901450231,
"autogenerated": false,
"ratio": 3.9072762395363814,
"config_... |
__author__ = 'kszalai'
try:
import traceback
import argparse
import textwrap
import glob
import logging
import logging.config
import datetime
from libs import Logging, timing, HistogrammerCommandline, HistogrammerWorkflow
from datetime import date
except ImportError as e... | {
"repo_name": "KAMI911/histogrammer",
"path": "histogrammer.py",
"copies": "1",
"size": "1773",
"license": "mpl-2.0",
"hash": 2496600894313843000,
"line_mean": 36.5434782609,
"line_max": 122,
"alpha_frac": 0.5329949239,
"autogenerated": false,
"ratio": 5.008474576271187,
"config_test": false,
... |
import os
import logging
import pandas as pd
from math import ceil, pi, exp, log, sqrt, radians, cos, sin, asin
# from pyproj import Proj
import numpy as np
from collections import defaultdict
# from IPython.display import Markdown
logging.basicConfig(format='%(asctime)s\t\t%(message)s', level=logging.DEBUG)
# Gene... | {
"repo_name": "KTH-dESA/PyOnSSET",
"path": "onsset/onsset.py",
"copies": "1",
"size": "198624",
"license": "mit",
"hash": -7874797436666233000,
"line_mean": 61.2841015992,
"line_max": 264,
"alpha_frac": 0.48614971,
"autogenerated": false,
"ratio": 3.6336760455160806,
"config_test": false,
"ha... |
__author__ = 'ktisha'
import os
import sys
import imp
PYTHON_VERSION_MAJOR = sys.version_info[0]
PYTHON_VERSION_MINOR = sys.version_info[1]
ENABLE_DEBUG_LOGGING = False
if os.getenv("UTRUNNER_ENABLE_DEBUG_LOGGING"):
ENABLE_DEBUG_LOGGING = True
def debug(what):
if ENABLE_DEBUG_LOGGING:
sys.stdout.writelines(... | {
"repo_name": "adedayo/intellij-community",
"path": "python/helpers/pycharm/pycharm_run_utils.py",
"copies": "61",
"size": "1126",
"license": "apache-2.0",
"hash": -3209528105456312000,
"line_mean": 25.8095238095,
"line_max": 62,
"alpha_frac": 0.6998223801,
"autogenerated": false,
"ratio": 2.8797... |
__author__ = 'ktisha'
import os
import sys
PYTHON_VERSION_MAJOR = sys.version_info[0]
PYTHON_VERSION_MINOR = sys.version_info[1]
ENABLE_DEBUG_LOGGING = False
if os.getenv("UTRUNNER_ENABLE_DEBUG_LOGGING"):
ENABLE_DEBUG_LOGGING = True
def debug(what):
if ENABLE_DEBUG_LOGGING:
sys.stdout.writelines(str(what) +... | {
"repo_name": "dahlstrom-g/intellij-community",
"path": "python/helpers/pycharm/pycharm_run_utils.py",
"copies": "21",
"size": "1297",
"license": "apache-2.0",
"hash": 9018276485258260000,
"line_mean": 24.94,
"line_max": 64,
"alpha_frac": 0.6854279106,
"autogenerated": false,
"ratio": 2.967963386... |
__author__ = 'kuasha'
"""
230,75-270,125
237,82 - 266,122
29x40
"""
import numpy as np
from scipy import misc
from sklearn import datasets
from sklearn import svm
from sklearn import cluster
img=misc.imread("/Users/kuasha/Downloads/people.jpg")
print img.shape
print img.dtype
start = [(77, 230), (127, 270)]
cell_w... | {
"repo_name": "kuasha/ml",
"path": "load.py",
"copies": "1",
"size": "1137",
"license": "mit",
"hash": 7761200531349404000,
"line_mean": 19.6727272727,
"line_max": 102,
"alpha_frac": 0.6437994723,
"autogenerated": false,
"ratio": 2.8496240601503757,
"config_test": false,
"has_no_keywords": fa... |
__author__ = 'kuhn'
__doc__ = """<Header>
<MdCreator>DGD2CMDI</MdCreator>
<MdCreationDate>2015-05-07+02:00</MdCreationDate>
<MdSelfLink>file:/home/kuhn/Data/IDS/svn_rev1233/dgd2_data/metadata/events/extern/PF/PF--_E_00127_extern.xml</MdSelfLink>
<MdProfile>clarin.eu:cr1:p_1430905751592</MdProfil... | {
"repo_name": "fkuhn/dgd2cmdi",
"path": "src/dgd2cmdi/cmdiheader.py",
"copies": "1",
"size": "1679",
"license": "bsd-3-clause",
"hash": -8866503331166438000,
"line_mean": 37.1590909091,
"line_max": 145,
"alpha_frac": 0.7153067302,
"autogenerated": false,
"ratio": 2.87008547008547,
"config_test"... |
import sys
import urllib2
import re
import time
def find_link(url):
sys.stdout.write("Wait a Minute its retrieving.")
try:
if url[0:4]!="http":
url="http://" + url
f=(urllib2.urlopen(url)).read()
k=re.findall('(src|href)="(\/view_video.php\S+)"',f)
k=se... | {
"repo_name": "pornvd/pornvd.github.io",
"path": "_posts/new.py",
"copies": "1",
"size": "2932",
"license": "mit",
"hash": -2767370005538809000,
"line_mean": 34.675,
"line_max": 132,
"alpha_frac": 0.4140518417,
"autogenerated": false,
"ratio": 3.7930142302716687,
"config_test": false,
"has_no... |
__author__ = 'kunal'
import numpy as np
import pandas as pd
from sklearn import preprocessing as pp
from sklearn.feature_extraction.text import CountVectorizer
#import pylab as P
import matplotlib.pyplot as plt
from sklearn.learning_curve import learning_curve
from sklearn.cross_validation import train_test_split
d... | {
"repo_name": "kv-kunalvyas/sfcc",
"path": "algorithms/auxiliary.py",
"copies": "1",
"size": "8928",
"license": "mit",
"hash": -2848121423971691500,
"line_mean": 49.1573033708,
"line_max": 109,
"alpha_frac": 0.6368727599,
"autogenerated": false,
"ratio": 2.86337395766517,
"config_test": true,
... |
"""
A Python wrapper to access Amazon Web Service(AWS) E-Commerce Serive APIs,
based upon pyamazon (http://www.josephson.org/projects/pyamazon/), enhanced
to meet the latest AWS specification(http://www.amazon.com/webservices).
This module defines the following classes:
- `Bag`, a generic container for the python ob... | {
"repo_name": "OAButton/tricorder",
"path": "plugins/python/ecs.py",
"copies": "2",
"size": "35455",
"license": "bsd-3-clause",
"hash": 2837627427961869300,
"line_mean": 35.8555093555,
"line_max": 549,
"alpha_frac": 0.6557890283,
"autogenerated": false,
"ratio": 3.7478858350951376,
"config_test... |
__author__ = 'kuro'
import argparse
import codecs
import json
import re
import os
import django
from django.conf import settings as django_settings
from django.template import Template, Context
from models import CantonKey
SUPPORTED_FORMAT = ['ibus', 'cin', 'json']
def deploy(options):
if not hasattr(options, ... | {
"repo_name": "lamsaitat/cantonhk-input",
"path": "src/cantonhk.py",
"copies": "1",
"size": "4508",
"license": "mit",
"hash": 8852318945686451000,
"line_mean": 31.9124087591,
"line_max": 130,
"alpha_frac": 0.5900621118,
"autogenerated": false,
"ratio": 3.7194719471947195,
"config_test": false,
... |
"""
Molecular line object
"""
from moleidoscope.linker import Linker
class Line:
""" Line class."""
def __init__(self, p1, p2):
self.p1 = p1
self.p2 = p2
self.name = str(p1) + '_' + str(p2)
self.vec = [p2[0] - p1[0], p2[1] - p1[1], p2[2] - p1[2]]
def grid(self, size):
... | {
"repo_name": "kbsezginel/Moleidoscope",
"path": "moleidoscope/line.py",
"copies": "1",
"size": "1316",
"license": "mit",
"hash": 5153809964255488000,
"line_mean": 28.2444444444,
"line_max": 64,
"alpha_frac": 0.5045592705,
"autogenerated": false,
"ratio": 2.758909853249476,
"config_test": false... |
"""
Animation of molecules
"""
import os
import mdtraj
import nglview
import tempfile
from .output import write_pdb
def animate(frames, gui=False, delete=True,):
"""
Creates nglview widget for given list of molecule files (frames).
"""
T = mdtraj.load(frames, top=frames[0])
view = nglview.show_mdt... | {
"repo_name": "kbsezginel/Moleidoscope",
"path": "moleidoscope/animate.py",
"copies": "1",
"size": "1025",
"license": "mit",
"hash": -7302266104830199000,
"line_mean": 26.7027027027,
"line_max": 91,
"alpha_frac": 0.647804878,
"autogenerated": false,
"ratio": 3.3279220779220777,
"config_test": f... |
"""
HostDesigner integration (read library)
"""
import os
import numpy as np
def read_library(library_path, rename='N'):
"""
Read HostDesigner linker library.
"""
with open(library_path, 'r') as library_file:
lib_lines = library_file.readlines()
connectivity_index = []
connectivity = ... | {
"repo_name": "kbsezginel/Moleidoscope",
"path": "moleidoscope/hd.py",
"copies": "1",
"size": "3354",
"license": "mit",
"hash": 4750423599717493000,
"line_mean": 39.4096385542,
"line_max": 104,
"alpha_frac": 0.6115086464,
"autogenerated": false,
"ratio": 3.5987124463519313,
"config_test": false... |
"""
Visualization methods using nglview backend
"""
import os
import math
import tempfile
import nglview
def show(*args, camera='perspective', move='auto', div=5, distance=(-10, -10), axis=0, caps=True, save=None, group=True):
"""
Show given structures using nglview
- camera: 'perspective' / 'orthogra... | {
"repo_name": "kbsezginel/Moleidoscope",
"path": "moleidoscope/visualize.py",
"copies": "1",
"size": "4191",
"license": "mit",
"hash": 5546931487064929000,
"line_mean": 36.4196428571,
"line_max": 121,
"alpha_frac": 0.6366022429,
"autogenerated": false,
"ratio": 3.452224052718287,
"config_test":... |
import direct.directbase.DirectStart
from panda3d.core import Filename,Buffer,Shader
from panda3d.core import PandaNode,NodePath
from panda3d.core import AmbientLight,DirectionalLight
from panda3d.core import TextNode,Point3,Vec4
from direct.showbase.DirectObject import DirectObject
from direct.filter.CommonFilters im... | {
"repo_name": "ToonTownInfiniteRepo/ToontownInfinite",
"path": "Panda3D-1.9.0/samples/Glow-Filter/Tut-Glow-Basic.py",
"copies": "3",
"size": "4208",
"license": "mit",
"hash": 1328168453467299600,
"line_mean": 36.5714285714,
"line_max": 98,
"alpha_frac": 0.6442490494,
"autogenerated": false,
"rati... |
import direct.directbase.DirectStart
from panda3d.core import Filename,Buffer,Shader
from panda3d.core import PandaNode,NodePath
from panda3d.core import ColorBlendAttrib
from panda3d.core import AmbientLight,DirectionalLight
from panda3d.core import TextNode,Point3,Vec4
from direct.showbase.DirectObject import Direct... | {
"repo_name": "francholi/PandaExamples",
"path": "Glow-Filter/Tut-Glow-Advanced.py",
"copies": "3",
"size": "5837",
"license": "mit",
"hash": -6447775855570020000,
"line_mean": 38.1744966443,
"line_max": 89,
"alpha_frac": 0.6695220147,
"autogenerated": false,
"ratio": 3.379849449913144,
"config... |
from direct.directbase import DirectStart
from direct.showbase.DirectObject import DirectObject
from direct.gui.DirectGui import *
from direct.interval.IntervalGlobal import *
from panda3d.core import lookAt
from panda3d.core import GeomVertexFormat, GeomVertexData
from panda3d.core import Geom, GeomTriangles, GeomVer... | {
"repo_name": "toontownfunserver/Panda3D-1.9.0",
"path": "samples/Procedural-Cube/Tut-Procedural-Cube.py",
"copies": "3",
"size": "5398",
"license": "bsd-3-clause",
"hash": 8708560885073936000,
"line_mean": 27.2617801047,
"line_max": 89,
"alpha_frac": 0.7128566136,
"autogenerated": false,
"ratio"... |
from direct.directbase import DirectStart
from panda3d.core import Filename,InternalName
from panda3d.core import GeomVertexArrayFormat, GeomVertexFormat
from panda3d.core import Geom, GeomNode, GeomTrifans, GeomTristrips
from panda3d.core import GeomVertexReader, GeomVertexWriter
from panda3d.core import GeomVertexR... | {
"repo_name": "toontownfunserver/Panda3D-1.9.0",
"path": "samples/Fractal-Plants/Tut-Fractal-Plants.py",
"copies": "3",
"size": "12802",
"license": "bsd-3-clause",
"hash": 5910772495791416000,
"line_mean": 28.9112149533,
"line_max": 143,
"alpha_frac": 0.7500390564,
"autogenerated": false,
"ratio"... |
import direct.directbase.DirectStart
from panda3d.core import PandaNode,LightNode,TextNode
from panda3d.core import Filename
from panda3d.core import NodePath
from panda3d.core import Shader
from panda3d.core import Point3,Vec4
from direct.task.Task import Task
from direct.actor.Actor import Actor
from direct.gui.Ons... | {
"repo_name": "toontownfunserver/Panda3D-1.9.0",
"path": "samples/Cartoon-Shader/Tut-Cartoon-Advanced.py",
"copies": "3",
"size": "6259",
"license": "bsd-3-clause",
"hash": -322477642376203300,
"line_mean": 40.1776315789,
"line_max": 104,
"alpha_frac": 0.6751877297,
"autogenerated": false,
"ratio... |
import pandas as pd
import numpy as np
from sklearn.naive_bayes import MultinomialNB
from sklearn.feature_selection import RFECV
from sklearn import linear_model
from sklearn.preprocessing import LabelEncoder
from sklearn.feature_extraction.text import TfidfVectorizer
from sklearn.utils import check_arrays
from scipy i... | {
"repo_name": "kastnerkyle/kaggle-kdd2014",
"path": "clf.py",
"copies": "1",
"size": "3005",
"license": "bsd-3-clause",
"hash": -301095394529852400,
"line_mean": 26.8240740741,
"line_max": 78,
"alpha_frac": 0.6628951747,
"autogenerated": false,
"ratio": 2.954768928220256,
"config_test": false,
... |
from collections import defaultdict
import copy
import nltk
import pandas as pd
import os
import numpy as np
from functools import partial
import string
NLTK_PACKAGES = ['punkt', 'word2vec_sample', 'cmudict']
START_SYMBOL = '<s>'
END_SYMBOL = '</s>'
_WORD2VEC = None
_CMU_DICT = None
BLACKLIST = ['"', '``', "''"]
DY... | {
"repo_name": "kastnerkyle/pachet_experiments",
"path": "markov_finite.py",
"copies": "1",
"size": "11670",
"license": "bsd-3-clause",
"hash": 5559183153541452000,
"line_mean": 33.2228739003,
"line_max": 146,
"alpha_frac": 0.5928020566,
"autogenerated": false,
"ratio": 3.629860031104199,
"confi... |
from dagbldr.datasets import make_ocr
from dagbldr.datasets import minibatch_iterator
from dagbldr.utils import convert_to_one_hot
from dagbldr.utils import add_datasets_to_graph
from dagbldr.utils import get_params_and_grads
from dagbldr.utils import TrainingLoop
from dagbldr.optimizers import adadelta
from dagbldr.no... | {
"repo_name": "dagbldr/dagbldr",
"path": "examples/deprecated/bitmap_attention/bitmap_attention.py",
"copies": "2",
"size": "2615",
"license": "bsd-3-clause",
"hash": -2746229617671590400,
"line_mean": 38.0298507463,
"line_max": 80,
"alpha_frac": 0.6940726577,
"autogenerated": false,
"ratio": 3.0... |
from __future__ import print_function
import __main__ as main
import os
import re
import shutil
import numpy as np
import glob
import numbers
import theano
import sys
import warnings
import inspect
import zipfile
import time
import pprint
try:
import cPickle as pickle
except ImportError:
import pickle
from coll... | {
"repo_name": "dribnet/dagbldr",
"path": "dagbldr/utils/training_utils.py",
"copies": "1",
"size": "30507",
"license": "bsd-3-clause",
"hash": -4123039051299305000,
"line_mean": 37.5676359039,
"line_max": 80,
"alpha_frac": 0.5952076573,
"autogenerated": false,
"ratio": 3.7948749844508023,
"conf... |
from theano import tensor
import theano
import numpy as np
from ..utils import concatenate, as_shared
from ..core import get_logger, get_type, set_shared
from .nodes import projection
from .nodes import np_tanh_fan_uniform
from .nodes import np_variance_scaled_uniform
from .nodes import np_normal
from .nodes import np... | {
"repo_name": "dagbldr/dagbldr",
"path": "dagbldr/nodes/recurrent_nodes.py",
"copies": "2",
"size": "10731",
"license": "bsd-3-clause",
"hash": 3455824099043429000,
"line_mean": 37.325,
"line_max": 80,
"alpha_frac": 0.5608983319,
"autogenerated": false,
"ratio": 3.5734265734265733,
"config_test... |
from theano.sandbox.rng_mrg import MRG_RandomStreams
from theano import tensor
from ..utils import concatenate
from ..core import get_logger, get_type
logger = get_logger()
_type = get_type()
'''
def embedding(list_of_index_inputs, max_index, proj_dim, graph, name,
random_state=None, strict=True, init_... | {
"repo_name": "kastnerkyle/dagbldr",
"path": "dagbldr/nodes/stochastic_nodes.py",
"copies": "2",
"size": "4400",
"license": "bsd-3-clause",
"hash": -1089256488831256200,
"line_mean": 42.5643564356,
"line_max": 79,
"alpha_frac": 0.6004545455,
"autogenerated": false,
"ratio": 3.5256410256410255,
... |
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