text stringlengths 0 1.05M | meta dict |
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#!/bin/python
"""
https://www.hackerrank.com/challenges/ctci-find-the-running-median/problem
"""
# heapq given for historical reasons
# it works. but not as fast in python
# as insort implementation version
import heapq
from bisect import insort
def _insert(a_item, min_heap, max_heap, n):
if n%2:
... | {
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#!/bin/python
# Implementation of mmwall's "Poor man's RPC"
# The goal is do RPC to change wallpaper remotely without relying on an additional custom client-server layer.
# This cannot be done in pure python, so some pre-existing external tools are used.
import subprocess
import shutil
import os
import platform
REM... | {
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"path": "src/set_wallpaper_remote.py",
"copies": "1",
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#!/bin/python
import argparse
from lxml import etree
from datetime import datetime
import numpy as np
import os
import plotting
########################################################################
class TrackPoint:
def __init__(self):
self.time = datetime.min
self.lat = -1
self.lon = ... | {
"repo_name": "s-kanev/runstats",
"path": "stats.py",
"copies": "1",
"size": "7044",
"license": "mit",
"hash": 8229880255692796000,
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#!/bin/python
import argparse
import json
import logging
import socket
import time
import kombu
def accept(port):
sock = socket.socket()
sock.setsockopt(socket.SOL_SOCKET, socket.SO_REUSEADDR, 1)
sock.bind(('0.0.0.0', port))
sock.listen(1)
return sock.accept()
def main(url, port, queue_name):
... | {
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"path": "caravan_pathfinder.py",
"copies": "1",
"size": "2252",
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#!/bin/python
import argparse
import logging
import os
import yaml
from collections import OrderedDict
if __name__ == "__main__":
parser = argparse.ArgumentParser(description = "Creates a module.yaml file for each of the specified directories")
parser.add_argument("--loglevel", default = "INFO", choices = ["D... | {
"repo_name": "bdecoste/cct_module",
"path": "generate_module.py",
"copies": "3",
"size": "2215",
"license": "apache-2.0",
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#!/bin/python
import argparse
import notes
def parse_args():
"""
Parses the arguments
"""
# Parsers declaration
parser = argparse.ArgumentParser()
subparsers = parser.add_subparsers(help='commands', dest='subparser')
# List notes
list_parser = subparsers.add_parser('list', help='List... | {
"repo_name": "nocternology/takenote",
"path": "src/cli.py",
"copies": "1",
"size": "1846",
"license": "mit",
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#!/bin/python
import argparse
import os
import os.path
import sys
import zipfile
import re
import io
from PIL import Image
# In Memory zipfile
class InMemZip(object):
def __init__(self):
self.byteBuf = io.BytesIO()
def write(self, filename, data):
with zipfile.ZipFile(self.byteBuf, 'a') as tm... | {
"repo_name": "imdn/scripts",
"path": "comic-tool.py",
"copies": "1",
"size": "11563",
"license": "unlicense",
"hash": 4783435693594784000,
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"has_... |
#! /bin/python
import argparse
import os
PYBABEL = 'pybabel'
PATH_TRANSLATIONS = 'translations'
parse = argparse.ArgumentParser(description='Quick translate')
parse.add_argument(
'-a',
'--action',
help='Action to execute',
required=True,
choices=['init', 'update', 'compile']
)
parse.add_argumen... | {
"repo_name": "jhbez/ProjectV",
"path": "app/tr.py",
"copies": "1",
"size": "1139",
"license": "apache-2.0",
"hash": 7693003945767278000,
"line_mean": 32.5,
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"autogenerated": false,
"ratio": 3.430722891566265,
"config_test": false,
"has_no_keywords"... |
#!/bin/python
import argparse
import ossn
import sys
if __name__ == '__main__':
# Parse our arguments
parser = argparse.ArgumentParser()
parser.add_argument('ossn', help='Path to OSSN')
output_group = parser.add_mutually_exclusive_group()
output_group.add_argument("--yaml", help="output to YAML",
... | {
"repo_name": "nkinder/ossn-tools",
"path": "test.py",
"copies": "1",
"size": "1192",
"license": "apache-2.0",
"hash": -1477975601357538800,
"line_mean": 26.7209302326,
"line_max": 68,
"alpha_frac": 0.5553691275,
"autogenerated": false,
"ratio": 3.6564417177914113,
"config_test": false,
"has_... |
#!/bin/python
import argparse
import requests
"""
A simple script to post nagios notifications to slack
Similar to https://raw.github.com/tinyspeck/services-examples/master/nagios.pl
But adds proxy support
Note: If your internal proxy only exposes an http interface, you will need to be running a modern version of u... | {
"repo_name": "al4/python-slack_nagios",
"path": "slack_nagios.py",
"copies": "1",
"size": "2175",
"license": "mit",
"hash": 4747048161564671000,
"line_mean": 34.0806451613,
"line_max": 230,
"alpha_frac": 0.6611494253,
"autogenerated": false,
"ratio": 3.6189683860232944,
"config_test": false,
... |
#!/bin/python
import argparse
import struct
MAX_FILENAME = 64
def main():
parser = argparse.ArgumentParser(description='Packages several binary files into a ultra simple archive format.')
parser.add_argument('outfile')
parser.add_argument('endianness', choices=['big','little'])
parser.add_argument('file', nargs=... | {
"repo_name": "whitingjp/pak",
"path": "src/pak.py",
"copies": "1",
"size": "1204",
"license": "mit",
"hash": 631735352813919000,
"line_mean": 23.08,
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#!/bin/python
import argparse
import sys
def check_color(value):
if value.upper() in ("YW", "NW"):
return value.upper()
if len(value.split(',')) == 3:
return value
raise argparse.ArgumentTypeError("%s is an invalid color/schema" % value)
def restyle(data, color="NW", direction="RL", same... | {
"repo_name": "gems-uff/noworkflow",
"path": "capture/noworkflow/resources/helper/df_style.py",
"copies": "1",
"size": "2204",
"license": "mit",
"hash": -7603655065335817000,
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#!/bin/python
import argparse
import sys
from befh.exchanges.gateway import ExchangeGateway
from befh.exchanges.bitmex import ExchGwBitmex
from befh.exchanges.btcc import ExchGwBtccSpot, ExchGwBtccFuture
from befh.exchanges.bitfinex import ExchGwBitfinex
from befh.exchanges.okcoin import ExchGwOkCoin
from befh.exchan... | {
"repo_name": "Aurora-Team/BitcoinExchangeFH",
"path": "befh/bitcoinexchangefh.py",
"copies": "1",
"size": "7458",
"license": "apache-2.0",
"hash": 4447363816198641700,
"line_mean": 42.6140350877,
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"... |
#!/bin/python
import argparse
import sys
parser = argparse.ArgumentParser(description="converts biallelic haploid vcf to fasta")
parser.add_argument('-i', action="store", dest="input_vcf", type=str)
parser.add_argument('-o', action="store", dest="output_fasta", type=str)
try:
options=parser.parse_args()
except:
... | {
"repo_name": "ruidlpm/Utils",
"path": "vcf2fasta.py",
"copies": "1",
"size": "2372",
"license": "mit",
"hash": 8060590860016512000,
"line_mean": 23.2040816327,
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"config_test": false,
"has_no_keyword... |
#!/bin/python
import argparse
import tempfile
import os
import shutil
import serial
import serial.tools.list_ports as list_ports
import sys
import unittest
from kubos import init, target, build, flash, clean
from kubos.test.utils import get_arg_list, KubosTestCase
class SDKIntegrationTest(KubosTestCase):
uart_re... | {
"repo_name": "kyleparrott/kubos-sdk",
"path": "kubos/test/integration/test.py",
"copies": "1",
"size": "2998",
"license": "apache-2.0",
"hash": 886412486139964900,
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"line_max": 134,
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"ratio": 3.756892230576441,
"conf... |
#! /bin/python
import argparse
import zmq
import numpy as np
import time
np.set_printoptions(threshold=np.nan)
context = zmq.Context()
parser = argparse.ArgumentParser()
parser.add_argument('input_port')
parser.add_argument('fusion_port')
parser.add_argument('identity')
args = parser.parse_args()
# Socket to recei... | {
"repo_name": "benghaem/senmo-process",
"path": "examples/process-ecg.py",
"copies": "2",
"size": "1078",
"license": "mit",
"hash": -8663846155703644000,
"line_mean": 19.7307692308,
"line_max": 64,
"alpha_frac": 0.6753246753,
"autogenerated": false,
"ratio": 2.6486486486486487,
"config_test": f... |
#!bin/python
import argparse
import numpy as np
import pandas as pd
def select_chair(df, area1, date, start_time, end_time,
area2=None, area3=None, mode="all"):
"""
Select chairs by their area of expertise and whether they give a talk
in the session they are supposed to chair.
The ... | {
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"path": "code/chair_selection.py",
"copies": "1",
"size": "7610",
"license": "mit",
"hash": -1088291429898854000,
"line_mean": 34.7276995305,
"line_max": 98,
"alpha_frac": 0.5868593955,
"autogenerated": false,
"ratio": 3.918640576725026,
"config_t... |
#!/bin/python
import base64
from itertools import *
import sys
import getopt
from hashlib import *
class colors:
red = "\033[1;31m"
white = "\033[1;37m"
normal = "\033[0;00m"
blue = "\033[1;34m"
green = "\033[1;32m"
lightblue = "\033[0;34m"
def main(argv):
charset = ''
ch_length = ''
out_file_name =... | {
"repo_name": "BlacKnight-RH/b_f0rc3r",
"path": "b_f0rc3r.py",
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"hash": 6791885720410222000,
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"has_no_keyw... |
#!/bin/python
import base64
import copy
from trex_stl_lib.api import *
from trex_stl_lib.services.trex_stl_ap import *
from trex_stl_lib.utils import text_tables, parsing_opts
from trex_stl_lib.utils.parsing_opts import ArgumentPack, ArgumentGroup, is_valid_file, check_mac_addr, check_ipv4_addr, MUTEX
from scapy.contr... | {
"repo_name": "dimagol/trex-core",
"path": "scripts/automation/trex_control_plane/stl/trex_stl_lib/trex_stl_wlc.py",
"copies": "2",
"size": "39551",
"license": "apache-2.0",
"hash": -2704871740456318500,
"line_mean": 38.3934262948,
"line_max": 191,
"alpha_frac": 0.5476473414,
"autogenerated": false... |
#!/bin/python
import bit_bootstrappable_decryption
import logging
class BootstrappableDecryption(object):
def __init__(self, short_odd_modulus, log=logging.getLogger(__name__)):
self.__log = log
self.__log.info("Creating BoostrappableDecryption with odd_modulus={odd_mod}".format(odd_mod=short_odd_... | {
"repo_name": "UMComp4140ATeam/Raymond",
"path": "src/bootstrappable_decryption.py",
"copies": "1",
"size": "1077",
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"hash": -1161800992498359000,
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"autogenerated": false,
"ratio": 3.6508474576271186,
"conf... |
#!/bin/python
import calendar
import time
import feedparser
def cTL(tidutc):
return time.localtime(calendar.timegm(tidutc))
def cTU(tidloc):
return time.mktime(tidloc)
def sjekkFeed(feed, lesttall):
antallNyePoster = 0;
sammendrag = []
tittler = []
linker = []
datoer = []
tidlocup = ... | {
"repo_name": "joards/simple-python-rss-to-mail",
"path": "hentrss.py",
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"license": "mit",
"hash": -5203836871509949000,
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"ratio": 3.0311804008908685,
"config_test": false,
"h... |
#!/bin/python
import ciphertext
import logging
import math
import numpy
class HomomorphicArithmetic(object):
def __init__(self, dimension, odd_modulus, log=logging.getLogger(__name__)):
self.__dimension = dimension
self.__odd_modulus = odd_modulus
self.__log = log
self.__log.info("... | {
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#!/bin/python
import ck.kernel as ck
import copy
import re
import argparse
import os
import json
#######################################
# Description:
#
# KERNEL = xgemm client
# INPUT = SIZE (M,N,K); PRECISION
# OUTPUT = CONFIGURATION
#######################################
'''
Set interval or Resolutio... | {
"repo_name": "ctuning/ck-math",
"path": "script/explore-clblast-matrix-size/clblast-client-benchmarking-multilibs.py",
"copies": "1",
"size": "9190",
"license": "bsd-3-clause",
"hash": -2456647809949266400,
"line_mean": 30.4726027397,
"line_max": 132,
"alpha_frac": 0.5210010881,
"autogenerated": f... |
#!/bin/python
import ck.kernel as ck
import copy
import re
import argparse
import os
#######################################
# Description:
#
# KERNEL = xgemm client
# INPUT = SIZE (M,N,K); PRECISION
# OUTPUT = CONFIGURATION
#######################################
'''
Set interval or Resolution 25%
Set re... | {
"repo_name": "ctuning/ck-math",
"path": "script/explore-acl-matrix-size/acl-client-benchmarking.py",
"copies": "1",
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#!/bin/python
import ck.kernel as ck
import copy
import re
import argparse
import os.path
import json
#######################################
# Description:
#
# KERNEL = Xgemm
# INPUT = SIZE (M,N,K); PRECISION
# OUTPUT = CONFIGURATION
#######################################
'''
Set interval or Resolution... | {
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#!/bin/python
import collections
from collections import Counter
from sys import argv
script, filename1, filename2, filename3 = argv
import re
from Bio import SeqIO
p = open(filename1) #HMMTOP output file
record_dict = SeqIO.index(filename2, "fasta") #FASTA file
outfile = open(filename3, "w+") #Filename for extract... | {
"repo_name": "zamanianlab/50HGI",
"path": "scripts/auxillary/HMMTOP_extract.py",
"copies": "1",
"size": "2480",
"license": "mit",
"hash": 6619480532153885000,
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"autogenerated": false,
"ratio": 2.6467449306296693,
"config_tes... |
#!/bin/python
import ConfigParser
import requests
import sys
import os
# read the api key from the config file
def getApiKey():
config = ConfigParser.ConfigParser()
config.read('lifx.cfg')
return config.get('api key', 'key')
def getInstructions():
return "Instructions:"
#TODO add instructi... | {
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"has_no_keyword... |
#!/bin/python
import couchdb, sys, json, os, glob, time, csv
import matplotlib.pyplot as plt
import numpy as np
from uuid import uuid4
# This script creates/replaces a fake database
# Variables
db_name = 'traveler_db'
path_to_file = os.path.dirname(os.path.realpath(__file__))
def unique_filename(upload_file):
... | {
"repo_name": "mwsmith2/traveler-db",
"path": "scripts/enter_old_nmr_data.py",
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"size": "2167",
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"config_test"... |
#!/bin/python
import couchdb, sys, json, os, glob, time
import matplotlib.pyplot as plt
import numpy as np
from uuid import uuid4
# This script creates/replaces a fake database
# Variables
db_name = 'fake_traveler_db'
width = [25.0, 0.2]
length = [140.0, 0.2]
loc = ['uw', 'ky', 'fnal', 'cornell']
author = ['Matthias... | {
"repo_name": "mwsmith2/traveler-db",
"path": "scripts/make_fake_xtal_db.py",
"copies": "1",
"size": "4064",
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"line_mean": 27.0275862069,
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"autogenerated": false,
"ratio": 2.8222222222222224,
"config_test"... |
#! bin/python
import csv, json, requests, sys, time
from bs4 import BeautifulSoup
filepath = "IRONMAN_Results"
raceURLS = [("im_arizona_2014","http://www.ironman.com/triathlon/events/americas/ironman/arizona/results.aspx"),
("im_austrailia_2015","http://www.ironman.com/triathlon/events/asiapac/ironman/au... | {
"repo_name": "SwimByteRun/IronScrape",
"path": "IronScrape.py",
"copies": "1",
"size": "9885",
"license": "mit",
"hash": 7616510947165475000,
"line_mean": 53.3186813187,
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"autogenerated": false,
"ratio": 3.2146341463414636,
"config_test": false,
"h... |
#!/bin/python
import csv
from label_map import gold_labels, mturk_labels
class ControlsGrader():
"""
Implements embedded control quality estimation.
estimate_data_labels returns a set of approved labels for each tweet, where the label is approved if it was provided by a worker who correctly labeled the control twe... | {
"repo_name": "manosai/tweepy",
"path": "assignment_4/embedded_controls.py",
"copies": "1",
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#!/bin/python
import csv
import json
def get_bool(entry):
if entry == "y":
return True;
if entry == "n":
return False;
raise Exception("Unexpected boolean: " + entry);
def is_present(entry):
return entry and not entry == "na"
def get_images(pictures, credits):
images = [];
fo... | {
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"path": "assets/original_data/extract_data.py",
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"line_mean": 30.2753623188,
"line_max": 98,
"alpha_frac": 0.593141798,
"autogenerated": false,
"ratio": 3.4975688816855754... |
#!/bin/python
import csv
import operator
from label_map import mturk_labels
class MajorityVoteGrader():
"""
Implements majority vote quality estimation.
estimate_data_labels returns the most popular label for each tweet
estimate_worker_qualities returns, for each worker, the proportion of labels which matched th... | {
"repo_name": "manosai/tweepy",
"path": "assignment_4/majority_vote_template.py",
"copies": "1",
"size": "2996",
"license": "mit",
"hash": -4499466325474759700,
"line_mean": 40.6111111111,
"line_max": 110,
"alpha_frac": 0.7009345794,
"autogenerated": false,
"ratio": 3.18384697130712,
"config_te... |
#!/bin/python
import csv
import operator
import numpy as np
import matplotlib.pyplot as plt
#Read the data from the csvs that were output by quality_estimation.py
tweet_data = [row for row in csv.DictReader(open('data_quality_estimates.csv'))]
worker_data = [row for row in csv.DictReader(open('worker_quality_estimate... | {
"repo_name": "manosai/tweepy",
"path": "assignment_4/analysis_template.py",
"copies": "1",
"size": "2951",
"license": "mit",
"hash": -8736425082707636000,
"line_mean": 47.3770491803,
"line_max": 135,
"alpha_frac": 0.7133175195,
"autogenerated": false,
"ratio": 3.2607734806629836,
"config_test"... |
#!/bin/python
import csv
import sys
f = open(sys.argv[1], 'rb')
cr = csv.reader(f)
cr.next()
lRefs = [];
for row in cr:
lRefs.append(row[4])
dGamesPerRef = {};
dFoulsPerRef = {};
dAFoulsPerRef = {};
dHFoulsPerRef = {};
dYellowsPerRef = {};
dAYellowsPerRef = {};
dHYellowsPerRef = {};
dRedsPerRef = {};
dARedsPe... | {
"repo_name": "jsmithedin/Scottish-Football-Analysis",
"path": "scripts/refsOverSeason.py",
"copies": "1",
"size": "1988",
"license": "mit",
"hash": 6007706390170227000,
"line_mean": 24.8181818182,
"line_max": 353,
"alpha_frac": 0.5819919517,
"autogenerated": false,
"ratio": 2.4757160647571608,
... |
#!/bin/python
import csv
data_file = "_data/projects.csv"
def add_to_set(input_list,output_set):
for el in input_list:
el = el.strip()
if el:
output_set.add(el.strip())
def main():
#Initialise the main dictionary
data = {}
tags = set()
... | {
"repo_name": "tejpochiraju/tejpochiraju.github.io",
"path": "tag_pages.py",
"copies": "1",
"size": "3013",
"license": "mit",
"hash": -1236609783463576800,
"line_mean": 31.3978494624,
"line_max": 98,
"alpha_frac": 0.5675406572,
"autogenerated": false,
"ratio": 3.385393258426966,
"config_test": ... |
#!/bin/python
import daemon
import zmq
import os
import sys
import subprocess
import argparse
import json
import logging
logger = logging.getLogger('gdam_netcdf_subscriber')
import lockfile
def parse_args():
parser = argparse.ArgumentParser(
description='Listens for GDAM to process new glider binary ... | {
"repo_name": "USF-COT/glider_netcdf_writer",
"path": "scripts/scripts-bin/gdam_netcdf_subscriber.py",
"copies": "1",
"size": "4588",
"license": "mit",
"hash": 1095737028299349200,
"line_mean": 23.6666666667,
"line_max": 76,
"alpha_frac": 0.5810810811,
"autogenerated": false,
"ratio": 3.823333333... |
#!/bin/python
import dash_core_components as dcc
import dash_html_components as html
import datetime
allStyle = {
'width': '1100',
'margin-left': 'auto',
'margin-right': 'auto',
'font-family': 'overpass',
'background-color': '#F3F3F3'
}
def getLay... | {
"repo_name": "Gab0/gekkoJaponicus",
"path": "promoterz/webServer/layout.py",
"copies": "1",
"size": "2566",
"license": "mit",
"hash": 2444019061845647400,
"line_mean": 28.4942528736,
"line_max": 127,
"alpha_frac": 0.5416991426,
"autogenerated": false,
"ratio": 3.881996974281392,
"config_test":... |
#!/bin/python
import dash_core_components as dcc
from evaluation.gekko.statistics import epochStatisticsNames, periodicStatisticsNames
def updateWorldGraph(app, WORLD):
environmentData = [
{
}
]
populationGroupData = [
{
'x': [locale.position[0]],
'y': [lo... | {
"repo_name": "Gab0/gekkoJaponicus",
"path": "promoterz/webServer/graphs.py",
"copies": "1",
"size": "4130",
"license": "mit",
"hash": 3132296835316437500,
"line_mean": 24.9748427673,
"line_max": 85,
"alpha_frac": 0.4682808717,
"autogenerated": false,
"ratio": 4.105367793240557,
"config_test": ... |
#!/bin/python
import datetime
import constants
onClickJS = '''
function zp(num,count) {
var ret = num + '';
while(ret.length < count) {
ret = "0" + ret;
}
return ret;
}
function doClick(ev, msec, pts) {
d = new Date(msec);
top.location = "../logs/" + d.getFullYear() + "." + zp(1+d... | {
"repo_name": "shalinmangar/solr-perf-tools",
"path": "src/python/graphutils.py",
"copies": "1",
"size": "13797",
"license": "apache-2.0",
"hash": 2307369374098576000,
"line_mean": 44.0849673203,
"line_max": 211,
"alpha_frac": 0.6152507973,
"autogenerated": false,
"ratio": 3.003701284563466,
"c... |
#!/bin/python
import datetime
class channel:
class channel_type:
DEAD = 0
LIVE = 1
HELP = 2
def __init__(self, channel_id=0, source_id=0, source_chat_id='',\
target_id=0, target_chat_id='', public=0, type=channel_type.DEAD, match=0):
"""
Constructor
... | {
"repo_name": "gavincyi/Telex",
"path": "src/channel.py",
"copies": "1",
"size": "3372",
"license": "apache-2.0",
"hash": -8937159047453514000,
"line_mean": 27.1,
"line_max": 92,
"alpha_frac": 0.5014827995,
"autogenerated": false,
"ratio": 4.127294981640147,
"config_test": false,
"has_no_keyw... |
#!/bin/python
import datetime
class contact:
def __init__(self, chat_id='', phone_number='', first_name='', last_name=''):
"""
Constructor
"""
curr_datetime = datetime.datetime.now()
self.date = curr_datetime.strftime("%Y%m%d")
self.time = curr_datetime.strftime("%H... | {
"repo_name": "gavincyi/Telex",
"path": "src/contact.py",
"copies": "1",
"size": "2231",
"license": "apache-2.0",
"hash": -8735639732793733000,
"line_mean": 25.8795180723,
"line_max": 81,
"alpha_frac": 0.5087404751,
"autogenerated": false,
"ratio": 4.170093457943925,
"config_test": false,
"ha... |
#!/bin/python
import datetime
class user_state:
class states:
UNDEF = 0
START = 1
QUERY_PENDING_MSG = 2
QUERY_PENDING_CONFIRM = 3
RESPONSE_PENDING_ID = 4
RESPONSE_PENDING_MSG = 5
RESPONSE_PENDING_CONFIRM = 6
MATCH_PENDING_ID = 7
MATCH_PENDING... | {
"repo_name": "gavincyi/Telex",
"path": "src/user_state.py",
"copies": "1",
"size": "7512",
"license": "apache-2.0",
"hash": -5896506084598837000,
"line_mean": 30.3,
"line_max": 111,
"alpha_frac": 0.5090521832,
"autogenerated": false,
"ratio": 4.372526193247963,
"config_test": false,
"has_no_... |
#!/bin/python
import datetime
class message():
def __init__(self, msg_id=0, channel_id=0, source_id=0, source_chat_id='',\
msg=''):
curr_datetime = datetime.datetime.now()
self.date = curr_datetime.strftime("%Y%m%d")
self.time = curr_datetime.strftime("%H:%M:%S.%f %z")
... | {
"repo_name": "gavincyi/Telex",
"path": "src/message.py",
"copies": "1",
"size": "2393",
"license": "apache-2.0",
"hash": 7252492162518465000,
"line_mean": 27.8313253012,
"line_max": 80,
"alpha_frac": 0.4918512328,
"autogenerated": false,
"ratio": 4.183566433566433,
"config_test": false,
"has... |
#!/bin/python
import dropbox2, u1file
import os, sys, traceback
class Universal_Use():
def __init__(self):
pass
def user_data(self):
output = []
dropbox2.log_in_or_out(True)
output.append('\nDropbox:')
output.append(dropbox2.user_data())
output.append(str(dropbox2.file_data('')))
output.append('\nUbu... | {
"repo_name": "bry012/Combicloud",
"path": "combicloud.py",
"copies": "1",
"size": "4310",
"license": "mit",
"hash": -3899792733567703000,
"line_mean": 30.9259259259,
"line_max": 135,
"alpha_frac": 0.6856148492,
"autogenerated": false,
"ratio": 2.7824402840542284,
"config_test": false,
"has_n... |
#!/bin/python
import fabric.api
from fabric.contrib.files import exists as remote_exists
from cloudify import ctx
def retrieve(agent_packages):
ctx.logger.info('Downloading Cloudify Agents...')
for agent, source in agent_packages.items():
# if source is not a downloadable link, it will not be downl... | {
"repo_name": "Cloudify-PS/cloudify-manager-blueprints",
"path": "components/nginx/scripts/retrieve_agents.py",
"copies": "3",
"size": "1706",
"license": "apache-2.0",
"hash": -1737819390044796200,
"line_mean": 38.6744186047,
"line_max": 78,
"alpha_frac": 0.5949589683,
"autogenerated": false,
"ra... |
#! /bin/python
import feedparser
from Downloader.ResourceDownloader import ResourceDownloader
from Util.LoggerFactory.LoggerFactory import LoggerFactory
class ImagesDownloader:
_projectRoot = '../../../'
_logger = LoggerFactory().getLogger('ImagesDownloader')
_rd = ResourceDownloader()
def __i... | {
"repo_name": "PodSearch/PodSearch",
"path": "src/ImagesDownloader/ImagesDownloader.py",
"copies": "1",
"size": "1493",
"license": "bsd-3-clause",
"hash": -208393209558971900,
"line_mean": 30.1041666667,
"line_max": 86,
"alpha_frac": 0.6383121232,
"autogenerated": false,
"ratio": 4.27793696275071... |
#!/bin/python
import fnmatch
import os
import re
import shutil
import subprocess
if (not os.path.exists("tools")):
os.sys.exit("ERROR: This script should be started from the root of the git repo.")
matches = []
for root, dirnames, filenames in os.walk('.'):
for filename in fnmatch.filter(filenames, '*.cpp'):
if ... | {
"repo_name": "agusbena/godot",
"path": "tools/translations/extract.py",
"copies": "1",
"size": "1743",
"license": "mit",
"hash": -2358954399415718000,
"line_mean": 22.5540540541,
"line_max": 112,
"alpha_frac": 0.6316695353,
"autogenerated": false,
"ratio": 2.8295454545454546,
"config_test": fa... |
#!/bin/python
import fnmatch
import os
import shutil
import subprocess
import sys
line_nb = False
for arg in sys.argv[1:]:
if arg == "--with-line-nb":
print("Enabling line numbers in the context locations.")
line_nb = True
else:
os.sys.exit("Non supported argument '" + arg + "'. Abor... | {
"repo_name": "Paulloz/godot",
"path": "editor/translations/extract.py",
"copies": "3",
"size": "6252",
"license": "mit",
"hash": -2880749051287174700,
"line_mean": 32.2553191489,
"line_max": 118,
"alpha_frac": 0.5291106846,
"autogenerated": false,
"ratio": 3.6076168493941143,
"config_test": fa... |
#!/bin/python
import fnmatch
import os
import shutil
import subprocess
import sys
line_nb = False
for arg in sys.argv[1:]:
if (arg == "--with-line-nb"):
print("Enabling line numbers in the context locations.")
line_nb = True
else:
os.sys.exit("Non supported argument '" + arg + "'. Ab... | {
"repo_name": "Marqin/godot",
"path": "editor/translations/extract.py",
"copies": "25",
"size": "3756",
"license": "mit",
"hash": 5517608039721165000,
"line_mean": 29.7868852459,
"line_max": 117,
"alpha_frac": 0.5604366347,
"autogenerated": false,
"ratio": 3.5601895734597155,
"config_test": fal... |
#!/bin/python
import fnmatch
import os
import shutil
import subprocess
import sys
line_nb = False
for arg in sys.argv[1:]:
if (arg == "--with-line-nb"):
print("Enabling line numbers in the context locations.")
line_nb = True
else:
os.sys.exit("Non supported argument '" + arg + "'. Aborting.")
if (not os.p... | {
"repo_name": "est31/godot",
"path": "tools/translations/extract.py",
"copies": "4",
"size": "3162",
"license": "mit",
"hash": -9170374170648537000,
"line_mean": 25.5714285714,
"line_max": 114,
"alpha_frac": 0.6299810247,
"autogenerated": false,
"ratio": 2.9277777777777776,
"config_test": false... |
#!/bin/python
import fnmatch
import os
latencies = []
# dir_modifier = "retime"
dir_modifier = "done_23"
target = "aws" # ONLY USE THIS SCRIPT FOR AWS TARGET "aws" or "zynq"
if ("zynq" in target):
rootdir = os.environ['SPATIAL_HOME']
elif ("aws" in target):
rootdir = os.environ['RPT_HOME']
algs = []
for item in... | {
"repo_name": "stanford-ppl/spatial-lang",
"path": "utilities/aws_scraper.py",
"copies": "1",
"size": "3278",
"license": "mit",
"hash": 4880265593375868000,
"line_mean": 32.793814433,
"line_max": 126,
"alpha_frac": 0.5976205003,
"autogenerated": false,
"ratio": 2.513803680981595,
"config_test":... |
#!/bin/python
import getopt, getpass, gmail, re, signal, sys, urllib2, time
from pylms.server import Server
from pylms.player import Player
_example = 'start.py -u someuser@gmail.com -s squeezeserver.host'
_refresh_seconds = 60
_services = {
'bandcamp': ['https://\w+\.bandcamp\.com/track/[\w-]+', 'http:', '"(//\w... | {
"repo_name": "bgrindy/pygmail2lms",
"path": "start.py",
"copies": "1",
"size": "3618",
"license": "mit",
"hash": 7747323713795061000,
"line_mean": 32.1926605505,
"line_max": 117,
"alpha_frac": 0.5655058043,
"autogenerated": false,
"ratio": 3.478846153846154,
"config_test": false,
"has_no_key... |
#!/bin/python
import getopt
import glob
import os
import sys
# only rename if -r specified
rename = False
# directory of files to rename - cwd by default
filedir = os.getcwd()
# base file name
base = ""
# file number
num = 1
# number of zeroes to pad file number with
pad = 0
# glob pattern
pattern = ""
# get cm... | {
"repo_name": "milesdave/f2all",
"path": "f2all.py",
"copies": "1",
"size": "1804",
"license": "mit",
"hash": -2817981505994643500,
"line_mean": 21,
"line_max": 79,
"alpha_frac": 0.6313747228,
"autogenerated": false,
"ratio": 3.042158516020236,
"config_test": false,
"has_no_keywords": false,
... |
##!/bin/python
import getopt
import json
import os
# import random
import shutil
import sys
import time
class CommandLine(object):
def __init__(self):
self.quiz = False
self.topic = ""
self.section = ""
self.randomQ = False
self.all_questions =... | {
"repo_name": "Alovia/QuickQuiz",
"path": "quickquiz.py",
"copies": "1",
"size": "7195",
"license": "apache-2.0",
"hash": 9055331040703000000,
"line_mean": 27.78,
"line_max": 100,
"alpha_frac": 0.5669214732,
"autogenerated": false,
"ratio": 3.9729431253451133,
"config_test": false,
"has_no_ke... |
#!/bin/python
import glob
import numpy as np
import matplotlib.pyplot as plt
import paths
NUM_RECORDINGS = 594
DATA_DIR = paths.MSRC_12
# OUTPUT_DATA_DIR = './data'
# Notes:
# -Tagstream times are sort of in the middle of the gesture, but
# not really; they're sometimes very close to the beginning or
# the end; ... | {
"repo_name": "dblalock/clean-datasets",
"path": "readMSRC12.py",
"copies": "1",
"size": "4469",
"license": "mit",
"hash": -8616942050990089000,
"line_mean": 28.9932885906,
"line_max": 75,
"alpha_frac": 0.6775565003,
"autogenerated": false,
"ratio": 2.7299938912645083,
"config_test": false,
"... |
#!/bin/python
import glob
import os
import re
import shutil
import traceback
import datetime
import requests
import sys
import time
import constants
import graphutils
import utils
SLACK = '-enable-slack-bot' in sys.argv and 'SLACK_BOT_TOKEN' in os.environ
QUICK = '-quick' in sys.argv
CLOUD_TEST_ONLY = '-cloud-test-... | {
"repo_name": "shalinmangar/solr-perf-tools",
"path": "src/python/bench.py",
"copies": "1",
"size": "56673",
"license": "apache-2.0",
"hash": -1924065468843384000,
"line_mean": 45.9925373134,
"line_max": 225,
"alpha_frac": 0.5704303637,
"autogenerated": false,
"ratio": 3.5844032635506924,
"conf... |
#!/bin/python
import glob, re, shutil, fileinput, os
def toUpper(pattern):
return pattern.group(1).upper()
def replaceInFile(filename, pattern, replacement):
for line in fileinput.FileInput(filename, inplace=1):
print re.sub(pattern, replacement, line),
sourceProjectName = "EmptyExample"
sourceModelPath = ... | {
"repo_name": "shiffman/ofxFaceTracker",
"path": "update-projects.py",
"copies": "1",
"size": "2811",
"license": "mit",
"hash": 2348334601746966000,
"line_mean": 36.48,
"line_max": 87,
"alpha_frac": 0.7524012807,
"autogenerated": false,
"ratio": 3.483271375464684,
"config_test": false,
"has_n... |
#!/bin/python
import glob, re, shutil, fileinput, os
def toUpper(pattern):
return pattern.group(1).upper()
def replaceInFile(filename, pattern, replacement):
for line in fileinput.FileInput(filename, inplace=1):
print re.sub(pattern, replacement, line),
sourceProjectName = "EmptyExample"
# windows code::block... | {
"repo_name": "Giladx/ofxFaceTracker",
"path": "update-projects.py",
"copies": "1",
"size": "1694",
"license": "mit",
"hash": -7400561086733730000,
"line_mean": 34.3125,
"line_max": 74,
"alpha_frac": 0.7621015348,
"autogenerated": false,
"ratio": 3.3021442495126707,
"config_test": false,
"has... |
#!/bin/python
import hashlib
from multiprocessing import cpu_count
import os
import os.path
import shutil
import subprocess
import urllib2
OPENSSL_VERSION = "1.0.2a"
if cpu_count() > 2:
MAKE_OPT = "-j%d" % (cpu_count() / 2)
else:
MAKE_OPT = ""
ARCHS = [
("i386", "iphonesimulator", "darwin-i386-cc"),
("x86_64"... | {
"repo_name": "nowsecure/nscrypto-cpp",
"path": "external/build-libcrypto.py",
"copies": "1",
"size": "5183",
"license": "mit",
"hash": 6366736894106841000,
"line_mean": 27.9553072626,
"line_max": 122,
"alpha_frac": 0.6511672776,
"autogenerated": false,
"ratio": 2.7805793991416308,
"config_test... |
#!/bin/python
import httplib2
import os
import io
from apiclient import discovery
from apiclient.http import MediaIoBaseDownload
from oauth2client import client, file, tools
from oauth2client.file import Storage
import openpyxl
from openpyxl import Workbook
# import employees
try:
import argparse
flags = ... | {
"repo_name": "countable-web/satchel",
"path": "services/accounting/payment.py",
"copies": "1",
"size": "9070",
"license": "mit",
"hash": -1972241027427195400,
"line_mean": 36.949790795,
"line_max": 104,
"alpha_frac": 0.5095920617,
"autogenerated": false,
"ratio": 4.329355608591886,
"config_tes... |
#!/bin/python
import io
import os
import re
from subprocess import CalledProcessError, check_call, check_output
# before anything else, cd to repo root
repo_root = check_output('git rev-parse --show-toplevel', shell=True)
repo_root = repo_root.strip()
os.chdir(repo_root)
def shell(cmd):
check_call(cmd, shell=True... | {
"repo_name": "lcary/nbd",
"path": "scripts/test_install.py",
"copies": "1",
"size": "1100",
"license": "mit",
"hash": -4673482198605067000,
"line_mean": 21.9166666667,
"line_max": 69,
"alpha_frac": 0.6718181818,
"autogenerated": false,
"ratio": 3.1884057971014492,
"config_test": false,
"has_... |
#!/bin/python
import io
import os
import re
import setuptools
from subprocess import check_call, check_output
import sys
# before anything else, cd to repo root
repo_root = check_output('git rev-parse --show-toplevel', shell=True)
repo_root = repo_root.strip()
os.chdir(repo_root)
def shell(cmd):
check_call(cmd, s... | {
"repo_name": "lcary/nbd",
"path": "scripts/pypi_upload.py",
"copies": "1",
"size": "1885",
"license": "mit",
"hash": 8547762006753921000,
"line_mean": 28.453125,
"line_max": 88,
"alpha_frac": 0.6663129973,
"autogenerated": false,
"ratio": 3.162751677852349,
"config_test": false,
"has_no_keyw... |
#!/bin/python
import jinja2
import os
import re
def _extract_role(node):
"""Return the site.pp content of a specific node"""
manifest = ''
in_manifest = False
with open('site.pp', 'r') as site_pp:
for line in site_pp:
if in_manifest == True and re.search('^}', line):
break
if in_manif... | {
"repo_name": "Spredzy/infra-ci",
"path": "ci.py",
"copies": "1",
"size": "1775",
"license": "apache-2.0",
"hash": -5689808370207390000,
"line_mean": 28.5833333333,
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"autogenerated": false,
"ratio": 3.3239700374531833,
"config_test": false,
"has_no_k... |
#!/bin/python
import json
from enum import Enum
class State(Enum):
QUESTION = 0
ANSWERS = 1
CORRECT = 2
IMAGE = 3
def new_question():
return {'answers' : []}
questions_list = []
state = State.CORRECT
question_id = 0
answer_id = 0
with open('questions.txt', 'r') as q:
question_dict = new_que... | {
"repo_name": "atrookey/atrookey.github.io",
"path": "qgen.py",
"copies": "1",
"size": "1283",
"license": "mit",
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"has... |
#!/bin/python
import json
from pprint import pprint as pp
import Monstr.Core.Utils as Utils
import Monstr.Core.DB as DB
import Monstr.Core.BaseModule as BaseModule
from Monstr.Core.DB import Column, Integer, String, Text, DateTime
class SSB(BaseModule.BaseModule):
name = 'SSB'
table_schemas = {'main': (Co... | {
"repo_name": "tier-one-monitoring/monstr",
"path": "Monstr/Modules/SSB/SSB.py",
"copies": "1",
"size": "6595",
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"con... |
#!/bin/python
import json
import sys
import time
import requests
def update_provider_context(manager_ip):
username = "{{ ctx.node.properties.admin_username }}"
password = "{{ ctx.node.properties.admin_password }}"
auth = (username, password)
headers = {"Tenant": "default_tenant", 'Content-Type': 'ap... | {
"repo_name": "Cloudify-PS/cloudify-manager-blueprints",
"path": "components/manager-ip-setter/scripts/update-provider-context.py",
"copies": "2",
"size": "1891",
"license": "apache-2.0",
"hash": -7487261991867401000,
"line_mean": 30,
"line_max": 78,
"alpha_frac": 0.5684822845,
"autogenerated": fal... |
#!/bin/python
import json
jsonin = './tl_2010_36061_tract10.geojson'
jsonout = './staic/jsonout.geojson'
results = '../../Data/Test/2015-aggregated/heriarchical-clusters.csv'
# results = "./Combined_Results.csv"
def insert(infile, outfile):
clusterAssignments = {}
i = 0
for line in open(infile):
... | {
"repo_name": "xuther/nyc-taxi-data",
"path": "visualization/061/addclusterdata.py",
"copies": "1",
"size": "1042",
"license": "mit",
"hash": -5194791326702067000,
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"ratio": 3.7347670250896057,
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#!/bin/python
import logging
import math
import numpy
import simple_error_distribution
import rvg
'''
Generates the secret keys, the evaluation key, and the public key that will be used in the homomorphic encryption scheme.
'''
class SomewhatHomomorphicKeygen(object):
def __init__(self, dimension, multiplicative_... | {
"repo_name": "UMComp4140ATeam/Raymond",
"path": "src/somewhat_homomorphic_keygen.py",
"copies": "1",
"size": "5254",
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"hash": 3921744029806720500,
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"autogenerated": false,
"ratio": 4.173153296266879,
"conf... |
#!/bin/python
import logging
import psutil
import time
import socket
class process_info:
def __init__(self, name):
self.active = False
self.name = name
self.connections = {}
class connection_info:
def __init__(self):
self.valid = False
self.established = False
... | {
"repo_name": "frans-fuerst/netusage",
"path": "netusage.py",
"copies": "1",
"size": "3422",
"license": "mit",
"hash": 7308450125682498000,
"line_mean": 28.7565217391,
"line_max": 100,
"alpha_frac": 0.5207481005,
"autogenerated": false,
"ratio": 4.293601003764115,
"config_test": false,
"has_n... |
#!bin/python
#import logging
#log_filename = 'smser.log'
import sys
import traceback
import signal
import smpplib
import threading
import settings
from time import sleep
import datetime
import random
from service.amqp import Publisher, Consumer
import logging
import json
logging.basicConfig(
file... | {
"repo_name": "rdl-telecom/billing",
"path": "smser.py",
"copies": "1",
"size": "4777",
"license": "unlicense",
"hash": 1933270183893430000,
"line_mean": 34.3851851852,
"line_max": 118,
"alpha_frac": 0.5698136906,
"autogenerated": false,
"ratio": 3.8555286521388217,
"config_test": false,
"has... |
#!/bin/python
import math
import bdn
"""
Single Layer Rosenblatt (1957) Perceptron implementation
The Ronseblatt perceptron always converges to a correct solution, if the
problem can be learned by a single-layer net, no matter how the initial
weights are chosen.
Here such weights are chosen as random positive values... | {
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"path": "perceptron/perceptron.py",
"copies": "1",
"size": "4489",
"license": "mit",
"hash": -8485604780396280000,
"line_mean": 31.7664233577,
"line_max": 93,
"alpha_frac": 0.6259746046,
"autogenerated": false,
"ratio": 3.201854493580599,
"config_test": false,
"ha... |
#!/bin/python
import math
import numpy
import simple_error_distribution
import somewhat_homomorphic_keygen
import rvg
class BootstrappableKeygen(object):
def __init__(self, short_dimension, long_dimension, multiplicative_depth, short_odd_modulus, long_odd_modulus, matrix_rows, short_seed=1, long_seed=1):
... | {
"repo_name": "UMComp4140ATeam/Raymond",
"path": "src/bootstrappable_keygen.py",
"copies": "1",
"size": "2735",
"license": "mit",
"hash": -657079731894406100,
"line_mean": 44.6,
"line_max": 192,
"alpha_frac": 0.6259597806,
"autogenerated": false,
"ratio": 3.7672176308539944,
"config_test": fals... |
#!/bin/python
import math
import os
import random
import re
import sys
# Complete the climbingLeaderboard function below.
def _getinitRank(arr):
initRank = [0] * len(arr)
initRank[0] = 1
for i in range(1, len(arr)):
if arr[i-1] == arr[i]:
initRank[i] = initRank[i-1]
else:
... | {
"repo_name": "MithileshCParab/HackerRank-10DaysOfStatistics",
"path": "Problem Solving/Algorithms/Implementation/climbing_the_leaderboard.py",
"copies": "1",
"size": "1616",
"license": "apache-2.0",
"hash": 2822227921186163700,
"line_mean": 22.7647058824,
"line_max": 51,
"alpha_frac": 0.5327970297,
... |
#!/bin/python
import math
import os
import random
import re
import sys
# Complete the triplets function below.
# Complete the triplets function below.
def _binarySearch(arr, key):
if arr[0] > key:
return 0
elif arr[len(arr)-1] <= key:
return len(arr)
else:
low = 0
high = le... | {
"repo_name": "MithileshCParab/HackerRank-10DaysOfStatistics",
"path": "Interview Preparation Kit/Search/triple_sum.py",
"copies": "1",
"size": "1545",
"license": "apache-2.0",
"hash": 3911219815874529000,
"line_mean": 26.1052631579,
"line_max": 54,
"alpha_frac": 0.5145631068,
"autogenerated": fals... |
#!/bin/python
import math
import os
import random
import re
import sys
DCT = {
')': '(',
']': '[',
'}': '{'
}
BRACKETS = DCT.values() + DCT.keys()
def ast_bracket(expr):
stack = []
for br in expr:
if br in BRACKETS:
if stack:
sym = DCT.get(br, Non... | {
"repo_name": "codecakes/algorithms_monk",
"path": "stacks/ast_brackets.py",
"copies": "1",
"size": "1389",
"license": "mit",
"hash": 2798854284607811000,
"line_mean": 23.8035714286,
"line_max": 97,
"alpha_frac": 0.4384449244,
"autogenerated": false,
"ratio": 3.9685714285714284,
"config_test": ... |
#!/bin/python
import math
def SumOfFactors(f_1, f_2):
for key in f_2.keys():
if (key in f_1):
f_1[key] += f_2[key]
else:
f_1[key] = f_2[key]
return f_1;
def PrimeFactorsOfNumber(n):
sqrt_n = int(math.sqrt(n))
if (n == sqrt_n * sqrt_n):
# Perfect square
return SumOfFactors(
P... | {
"repo_name": "aawc/ProjectEuler",
"path": "05/evenlyDivisible.py",
"copies": "1",
"size": "1404",
"license": "mit",
"hash": 803839657825577600,
"line_mean": 22.7966101695,
"line_max": 50,
"alpha_frac": 0.6153846154,
"autogenerated": false,
"ratio": 3.106194690265487,
"config_test": false,
"h... |
#!/bin/python
import matplotlib
matplotlib.use('TKAgg')
import numpy as np
from matplotlib import pyplot as plt
import time, sys
import matplotlib.animation as animation
WIDTH = 32
HEIGHT = 32
np.set_printoptions(precision=2, suppress=True, linewidth=200, threshold=2000)
np.random.seed(1000)
arrA = np.random.rando... | {
"repo_name": "gregfriedland/AuroraV6",
"path": "src/bzr.py",
"copies": "1",
"size": "1515",
"license": "mit",
"hash": 3958660957119631400,
"line_mean": 23.0476190476,
"line_max": 78,
"alpha_frac": 0.6191419142,
"autogenerated": false,
"ratio": 2.416267942583732,
"config_test": false,
"has_no... |
#!/bin/python
import matplotlib.pyplot as plt
from matplotlib.widgets import Button
from matplotlib.patches import Rectangle
import matplotlib.gridspec as gridspec
import cPickle
#import random
imgloc = '../images/v012-penn.10-1hA5D1-cropb.png'
currimg=plt.imread(imgloc)
square = 13
data=[]
resd={'dot':0,'noise':1,... | {
"repo_name": "davharris/leafpuppy",
"path": "bg_trainer.py",
"copies": "1",
"size": "1766",
"license": "bsd-3-clause",
"hash": 5900344820123743000,
"line_mean": 31.1090909091,
"line_max": 109,
"alpha_frac": 0.6359003398,
"autogenerated": false,
"ratio": 2.8622366288492707,
"config_test": false... |
#!/bin/python
import Monstr.Core.Utils as Utils
import Monstr.Core.DB as DB
import Monstr.Core.BaseModule as BaseModule
from datetime import timedelta
import json
from Monstr.Core.DB import Column, Integer, String, DateTime, Text, UniqueConstraint
from sqlalchemy.sql import func
class PhedexErrors(BaseModule.BaseM... | {
"repo_name": "tier-one-monitoring/monstr",
"path": "Monstr/Modules/PhedexErrors/PhedexErrors.py",
"copies": "1",
"size": "6670",
"license": "apache-2.0",
"hash": -1436613626996143000,
"line_mean": 47.3405797101,
"line_max": 152,
"alpha_frac": 0.4625187406,
"autogenerated": false,
"ratio": 4.4825... |
#!/bin/python
import mysql.connector
from datetime import datetime, date, time, timedelta
import pytz
from tzlocal import get_localzone
localtz = get_localzone()
#schedule follows format:
#schedule = [{"DayOfWeek" : 0, "OnTime" : time(10, 00, 00, tzinfo=localtz), "OffTime" : time(13, 0, 0, tzinfo=localtz), "State": "... | {
"repo_name": "fowie/PiCoolerControl",
"path": "MySQL.py",
"copies": "1",
"size": "1895",
"license": "apache-2.0",
"hash": -8617479239223989000,
"line_mean": 34.7547169811,
"line_max": 278,
"alpha_frac": 0.6860158311,
"autogenerated": false,
"ratio": 2.93343653250774,
"config_test": false,
"h... |
#!./bin/python
import numpy as np
import cv2
#640 x 426
cap = cv2.VideoCapture(0)
# take first frame of the video
ret,frame = cap.read()
# setup initial location of window
r,h,c,w = 250,90,400,125 # simply hardcoded the values
track_window = (c,r,w,h)
# set up the ROI for tracking
roi = frame[r:r+h, c:c+w]
hsv_ro... | {
"repo_name": "progrn/tracking",
"path": "meanshift.py",
"copies": "1",
"size": "1294",
"license": "mit",
"hash": -3372558278592417300,
"line_mean": 24.88,
"line_max": 80,
"alpha_frac": 0.6282843895,
"autogenerated": false,
"ratio": 2.651639344262295,
"config_test": false,
"has_no_keywords": ... |
#!/bin/python
import numpy as np
import datetime
import inspect
import hashlib
import uuid
# ================================================================
# Constants
# ================================================================
# ================================================================
# Functions
#... | {
"repo_name": "dblalock/flock",
"path": "python/utils/misc.py",
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"has_... |
#!/bin/python
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.widgets import Button
import random
imgloc = '../images/v012-penn.10-1hA5D1-cropb.png'
currimg=plt.imread(imgloc)
square = 21
data=[]
resd={'dot':0,'noise':1,'vein':2}
currbox=0
def moveCurrBox(img, width):
w=int(width/2)
#i=... | {
"repo_name": "davharris/leafpuppy",
"path": "learnset_creator.py",
"copies": "1",
"size": "1982",
"license": "bsd-3-clause",
"hash": 7580600653205965000,
"line_mean": 22.0465116279,
"line_max": 59,
"alpha_frac": 0.6362260343,
"autogenerated": false,
"ratio": 2.6497326203208558,
"config_test": ... |
#!/bin/python
import numpy as np
import matplotlib.pyplot as plt
import math
from PIL import Image, ImageDraw
# FUNCTIONS
class Line:
def __init__(self, xs, ys, xe, ye, pxs, pys, pxe, pye):
self.xs=xs
self.ys=ys
self.xe=xe
self.ye=ye
self.pxs=math.floor((pxs+3)*100)
... | {
"repo_name": "ploth/landmarkCreation",
"path": "landmarkCreation.py",
"copies": "1",
"size": "7945",
"license": "mit",
"hash": -5153707802070077000,
"line_mean": 31.1659919028,
"line_max": 197,
"alpha_frac": 0.613593455,
"autogenerated": false,
"ratio": 2.2975708502024292,
"config_test": false... |
#!/bin/python
import numpy as np
import os
import inspect
from scipy.misc import imresize
# ================================================================
# Constants
# ================================================================
# ================================================================
# Functions
# ... | {
"repo_name": "dblalock/clean-datasets",
"path": "utils.py",
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"autogenerated": false,
"ratio": 3.004794885455514,
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"has_no_... |
#!/bin/python
import numpy as np
import tensorflow as tf
import algorithms
class KuhnPokerCRMPlayer(algorithms.CRMPlayer):
"""
"""
def __init__(self, num_players=2):
"""
Args:
num_players:
"""
self.graph = tf.Graph()
self.num_players = num_play... | {
"repo_name": "DMRookie/RoomAI",
"path": "models/crm/crm_fivecardstud/CRMForFiveCardStud.py",
"copies": "1",
"size": "5884",
"license": "mit",
"hash": 2925932285751964700,
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"line_max": 122,
"alpha_frac": 0.5193745751,
"autogenerated": false,
"ratio": 3.4530516431924885,... |
#!/bin/python
import numpy as np
class Environment(object):
def __init__(self, state):
self.state = state
self.intrinsic_dynamics = lambda x: x
def evolve(self, evolution_function=None):
if evolution_function == None:
evolution_function = self.intrinsic_dynamics
sel... | {
"repo_name": "corcra/pRLy",
"path": "MDP/agents.py",
"copies": "1",
"size": "2904",
"license": "mit",
"hash": 7846640716998874000,
"line_mean": 32.7674418605,
"line_max": 73,
"alpha_frac": 0.5826446281,
"autogenerated": false,
"ratio": 4.366917293233083,
"config_test": false,
"has_no_keyword... |
#!/bin/python
import numpy as np
# generate 3D points around points in pts_center using gaussian distribution
def generate_points(pts_center, pts_sigma, pts_fixed, pts_num, axis_range):
# allocate mem for points
points = np.zeros([4, pts_num.sum()])
istart = 0
for i in range(pts_center.shape[1]):
... | {
"repo_name": "ivankreso/stereo-vision",
"path": "scripts/stereo_model_sba/generate_3d_points.py",
"copies": "1",
"size": "2622",
"license": "bsd-3-clause",
"hash": -8150057295518705000,
"line_mean": 37,
"line_max": 90,
"alpha_frac": 0.501525553,
"autogenerated": false,
"ratio": 2.664634146341463... |
#!/bin/python
import numpy
import test_utils
import unittest
from src import bootstrappable_keygen
class MockSomewhatHomomorphicKeygen(object):
def generate_keys(self):
return numpy.array([1, 2, 3, 4], dtype=numpy.integer), {(0, 0): [4, 3], (0, 1): [1, 0], (1, 0): [2, 1], (1, 1): [3, 0]}, None
class Boo... | {
"repo_name": "UMComp4140ATeam/Raymond",
"path": "tst/bootstrappable_keygen_test.py",
"copies": "1",
"size": "2054",
"license": "mit",
"hash": 5056427419776653000,
"line_mean": 37.7735849057,
"line_max": 137,
"alpha_frac": 0.5457643622,
"autogenerated": false,
"ratio": 3.25,
"config_test": true... |
#!/bin/python
import numpy
import test_utils
import unittest
from src import somewhat_homomorphic_keygen
class SomewhatHomomorphicKeygenTest(unittest.TestCase):
def test_keygen(self):
self.maxDiff = None
# Need to reduce odd modulus check for tests so object initialization doesn't through errors
... | {
"repo_name": "UMComp4140ATeam/Raymond",
"path": "tst/somewhat_homomorphic_keygen_test.py",
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"hash": 7241480097407283000,
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"autogenerated": false,
"ratio": 3.3540983606557377,
... |
#!/bin/python
import os, fnmatch
from subprocess import call
class RunPandoc():
def runPandoc(self, fileName):
pandoc="C:\\Program Files (x86)\\Pandoc\\bin\\pandoc.exe"
paramData={"fileName": fileName, "ext1":"md", "ext2":"html"}
markdownName="%(fileName)s.%(ext1)s" % paramData
htmlName="%(fileName)s.%(ext2... | {
"repo_name": "donlee888/JsObjects",
"path": "Python/PandocConvert/PandocConvert.py",
"copies": "2",
"size": "1118",
"license": "mit",
"hash": 7997837273954380000,
"line_mean": 33.9375,
"line_max": 78,
"alpha_frac": 0.6887298748,
"autogenerated": false,
"ratio": 3.122905027932961,
"config_test"... |
#!/bin/python
import os, functools, subprocess, sys
def target_sort(a, b):
if a == b:
return 0
# all target is first
if a == 'all':
return -1
if b == 'all':
return 1
# .PHONY is last
if a == '.PHONY':
return 1
if b == '.PHONY':
return -1
# Sor... | {
"repo_name": "MarkZH/Genetic_Chess",
"path": "create_Makefile.py",
"copies": "1",
"size": "7756",
"license": "mit",
"hash": -910171520029627600,
"line_mean": 39.3958333333,
"line_max": 153,
"alpha_frac": 0.5582774626,
"autogenerated": false,
"ratio": 3.238413361169102,
"config_test": false,
... |
#!/bin/python
import os
from cStringIO import StringIO as IO
def scan_block(G, P, G_index, start_col, R, r, c):
gr = G_index
gc = start_col
pr = 0
pc = 0
# O(r*c)
# matrix traversal
while gr < R and gc < C:
while pc < c and pr < r:
if G[gr][gc] != P[pr][pc]:
... | {
"repo_name": "codecakes/algorithms_monk",
"path": "search/grid_pattern_search.py",
"copies": "1",
"size": "2437",
"license": "mit",
"hash": 3753589240874153000,
"line_mean": 28.0119047619,
"line_max": 91,
"alpha_frac": 0.4677882643,
"autogenerated": false,
"ratio": 2.856975381008206,
"config_t... |
#!/bin/python
import os
from flask import Flask, Response, request, abort, render_template_string, send_from_directory
import Image
import StringIO
app = Flask(__name__)
WIDTH = 1000
HEIGHT = 800
TEMPLATE = '''
<!DOCTYPE html>
<html>
<head>
<title></title>
<meta charset="utf-8" />
<style>
body {
mar... | {
"repo_name": "akshayub/NITKart",
"path": "Images/server.py",
"copies": "1",
"size": "2603",
"license": "mit",
"hash": -7879664205809767000,
"line_mean": 25.5612244898,
"line_max": 226,
"alpha_frac": 0.5535920092,
"autogenerated": false,
"ratio": 3.367399741267788,
"config_test": false,
"has_... |
#!/bin/python
import os
from os.path import dirname, join, exists, relpath, splitext
import json
from json_tools import list_field_paths, field_by_path
from shutil import copy
from utils import get_answer
from bisect import insort_left
from codecs import open as copen
from sys import platform
if platform == "win32":
... | {
"repo_name": "Seagull42/Starbound_RU",
"path": "tools/merge_from_mod.py",
"copies": "10",
"size": "9072",
"license": "apache-2.0",
"hash": -2663091135598319600,
"line_mean": 36.643153527,
"line_max": 87,
"alpha_frac": 0.6604938272,
"autogenerated": false,
"ratio": 3.7737104825291183,
"config_t... |
#!/bin/python
import os
import couchdb
import simplejson
basepath = os.path.dirname(__file__)
conf_file = open(os.path.join(basepath, '../traveler/config.json'))
conf = simplejson.loads(conf_file.read())
img_types = conf['image_types']
s = couchdb.Server(conf['db_url'])
s.resource.credentials = (conf['db_user'], con... | {
"repo_name": "mwsmith2/traveler-db",
"path": "scripts/correct_opt_img.py",
"copies": "1",
"size": "1208",
"license": "mit",
"hash": 8019437176952397000,
"line_mean": 18.4838709677,
"line_max": 67,
"alpha_frac": 0.4966887417,
"autogenerated": false,
"ratio": 3.63855421686747,
"config_test": fal... |
#!/bin/python
import os
import glob
import numpy as np
import matplotlib.pyplot as plt
import paths
from ..utils.files import ensureDirExists
NUM_RECORDINGS = 594
DATA_DIR = paths.MSRC_12
# OUTPUT_DATA_DIR = './data'
join = os.path.join
FIG_SAVE_DIR = join('figs','msrc')
SAVE_DIR_LINE_GRAPH = join(FIG_SAVE_DIR, 'l... | {
"repo_name": "dblalock/dig",
"path": "python/dig/datasets/msrc.py",
"copies": "2",
"size": "6204",
"license": "mit",
"hash": -6428818928532626000,
"line_mean": 28.1267605634,
"line_max": 82,
"alpha_frac": 0.6803675048,
"autogenerated": false,
"ratio": 2.7009142359599476,
"config_test": false,
... |
#!/bin/python
import os
import kombu
from collections import namedtuple
class Config(object):
""" Get parameters from environment, or defaults if not specified. """
# Flask DEBUG setting - not used.
DEBUG = False
# Logging.
LOG_THRESHOLD_LEVEL = os.getenv('LOG_THRESHOLD_LEVEL', 'ERROR') ... | {
"repo_name": "LandRegistry/register-publisher",
"path": "config.py",
"copies": "1",
"size": "3279",
"license": "mit",
"hash": -8675215683456979000,
"line_mean": 43.9178082192,
"line_max": 148,
"alpha_frac": 0.7005184507,
"autogenerated": false,
"ratio": 3.466173361522199,
"config_test": true,
... |
#!/bin/python
import os
import re
import sys
import errno
directives = {
'_UNICODE': {
'regex': r'_UNICODE\(0x([A-Fa-f0-9]{4})\)',
'parser': lambda m:
unichr(int(m.group(1), 16))
}
}
def line_repl(ln):
ret = ln.decode('utf-8');
if re.match(r'^\s*$', ret) or ret == '':
return '';
# Replace end of line... | {
"repo_name": "eerotal/nsbcomp",
"path": "nsbcomp/compiler.py",
"copies": "1",
"size": "1346",
"license": "bsd-3-clause",
"hash": 3283949570731522000,
"line_mean": 19.7076923077,
"line_max": 57,
"alpha_frac": 0.6144130758,
"autogenerated": false,
"ratio": 2.8158995815899583,
"config_test": fals... |
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