text stringlengths 0 1.05M | meta dict |
|---|---|
__author__ = 'YANGDY'
import chardet
def readfiles(dataPath, firstRow, charset,separator):
listdata =[]
header=[]
try:
fsock = open(dataPath, "r")
except IOError:
print "The file {" + dataPath + "}don't exist, Please double check!"
return
s = fsock.readlines()
... | {
"repo_name": "smellydog521/classicPlayParsing",
"path": "readFile.py",
"copies": "1",
"size": "1073",
"license": "apache-2.0",
"hash": 8053313980750825000,
"line_mean": 24.1707317073,
"line_max": 76,
"alpha_frac": 0.4846225536,
"autogenerated": false,
"ratio": 3.9448529411764706,
"config_test"... |
import cantera as ct
import numpy as np
import sys
# import function
from get_reaction_info import get_reaction_info
# initialize the chemistry, save in g
g = ct.Solution('h2-plog.cti')
# stoichiometric coefficients
# positive numbers
Sf = g.reactant_stoich_coeffs()
# number of species and reactions
KK = g.n_specie... | {
"repo_name": "yanggaome/Python-functions-based-on-Cantera",
"path": "test_get_reaction_info.py",
"copies": "1",
"size": "5138",
"license": "mit",
"hash": -4107429357887657000,
"line_mean": 36.503649635,
"line_max": 140,
"alpha_frac": 0.5821331257,
"autogenerated": false,
"ratio": 2.7757968665586... |
import numpy as np
# class of reaction information
class ReactionInfo:
def __init__(self):
self.isReversible = False
self.isThirdbody = False
self.isFalloff = False
self.isChemical = False
self.isPLOG = False
self.isSimple = False
self.isLindemann = False
... | {
"repo_name": "yanggaome/Python-functions-based-on-Cantera",
"path": "get_reaction_info.py",
"copies": "1",
"size": "5902",
"license": "mit",
"hash": -4974820962979619000,
"line_mean": 28.8080808081,
"line_max": 108,
"alpha_frac": 0.5814977974,
"autogenerated": false,
"ratio": 3.1954520844612886,... |
__author__ = 'yangjiebin'
from flask.ext.wtf import Form
from wtforms import StringField,PasswordField,BooleanField,SubmitField
from wtforms.validators import Required,Length,Email,EqualTo,Regexp
from wtforms import ValidationError
from ..models import User
from flask.ext.login import current_user
class LoginForm(Form... | {
"repo_name": "rebortyang/flask_blog",
"path": "app/auth/forms.py",
"copies": "1",
"size": "2583",
"license": "mit",
"hash": 1222424632757626000,
"line_mean": 45.125,
"line_max": 133,
"alpha_frac": 0.7092528068,
"autogenerated": false,
"ratio": 4.276490066225166,
"config_test": false,
"has_no... |
__author__ = 'yangjiebin'
import unittest
from app.models import *
class UserModelTestCase(unittest.TestCase):
def setUp(self):
pass
def tearDown(self):
pass
def test_password_setter(self):
u = User(password='cat')
self.assertTrue(u.password_hash is not None)
def te... | {
"repo_name": "rebortyang/flask_blog",
"path": "tests/test_user_model.py",
"copies": "1",
"size": "1168",
"license": "mit",
"hash": -4699386393231680000,
"line_mean": 27.512195122,
"line_max": 64,
"alpha_frac": 0.6369863014,
"autogenerated": false,
"ratio": 3.7197452229299364,
"config_test": tr... |
__author__ = 'Yang'
import copy
import numpy as np
import math
from acrm import ApproxCorankingMatrix
from sklearn import (manifold, datasets, decomposition, ensemble, lda, random_projection)
from scipy.interpolate import griddata
from scipy.stats import distributions
from collections import Counter
from matplotlib im... | {
"repo_name": "gnavvy/PyNode.vis",
"path": "vast.py",
"copies": "1",
"size": "6532",
"license": "mit",
"hash": -303639642114930600,
"line_mean": 34.8901098901,
"line_max": 99,
"alpha_frac": 0.5791488059,
"autogenerated": false,
"ratio": 3.284062342885872,
"config_test": false,
"has_no_keyword... |
__author__ = 'Yang'
import numpy as np
from acrm import ApproxCorankingMatrix
from sklearn import datasets, manifold
from scipy.interpolate import griddata
class Defog(object):
def __init__(self, n_seeds=1000):
print("init")
self.seeds = None
self.seed_values = None
self.grid_x =... | {
"repo_name": "gnavvy/PyNode.vis",
"path": "defog.py",
"copies": "1",
"size": "4942",
"license": "mit",
"hash": 8717844667376979000,
"line_mean": 36.7251908397,
"line_max": 95,
"alpha_frac": 0.56131121,
"autogenerated": false,
"ratio": 3.5579553635709145,
"config_test": false,
"has_no_keyword... |
__author__ = 'YangZongyun'
# -*- coding: utf-8 -*-
from weibo import APIClient
import webbrowser
import MySQLdb
import numpy as np
APP_KEY = YourAppKey # need init
APP_SECRET = YourAppSecret # need init
CALLBACK_URL = 'https://api.weibo.com/oauth2/default.html' # callback url
CLIENT = APIClient(app_key=APP_KEY, ... | {
"repo_name": "MOKOTA/weibopoi",
"path": "poi.py",
"copies": "1",
"size": "3906",
"license": "mit",
"hash": 2805475604630817000,
"line_mean": 40.5531914894,
"line_max": 173,
"alpha_frac": 0.5217613927,
"autogenerated": false,
"ratio": 3.6267409470752088,
"config_test": false,
"has_no_keywords... |
__author__ = 'yanikafarrugia'
import unittest
import lattly_service.converter
class ConverterTests(unittest.TestCase):
def test_degrees_to_radians(self):
rad = lattly_service.converter.Converter.degrees_to_radians(120)
self.assertEqual(rad, 2.0943951023931953)
self.assertIsNotNone(rad)
self.assertTrue(rad >... | {
"repo_name": "yfarrugia/lattly",
"path": "lattly_tests/converter_tests.py",
"copies": "1",
"size": "1248",
"license": "bsd-2-clause",
"hash": 6872003526079988000,
"line_mean": 31.8421052632,
"line_max": 87,
"alpha_frac": 0.7467948718,
"autogenerated": false,
"ratio": 2.7857142857142856,
"confi... |
__author__ = 'yanikafarrugia'
import sys
import logging
import lattly_service.converter
logger = logging.getLogger('lattly')
class MidPointFinder:
def compute_weighted_average(cartesian_point, weights, total_weight):
try:
weighted_average = [0.0] * 3
for point in cartesian_point:
weighted_x = weighte... | {
"repo_name": "yfarrugia/lattly",
"path": "lattly_service/mid_point_finder.py",
"copies": "1",
"size": "1841",
"license": "bsd-2-clause",
"hash": 8427510091572771000,
"line_mean": 35.82,
"line_max": 95,
"alpha_frac": 0.7088538838,
"autogenerated": false,
"ratio": 3.1203389830508477,
"config_tes... |
__author__ = 'yanikafarrugia'
import sys
import logging
import math
logger = logging.getLogger('lattly')
class Converter:
def degrees_to_radians(degrees):
try:
rad = (degrees * (math.pi / 180.0))
return rad
except IOError as io_exc:
logger.error("I/O error({0}): {1}".format(io_exc.errno, io_exc.strer... | {
"repo_name": "yfarrugia/lattly",
"path": "lattly_service/converter.py",
"copies": "1",
"size": "2244",
"license": "bsd-2-clause",
"hash": 1220210448629832700,
"line_mean": 33.5230769231,
"line_max": 99,
"alpha_frac": 0.6867201426,
"autogenerated": false,
"ratio": 3.004016064257028,
"config_tes... |
__author__ = 'yanikafarrugia'
# Initialize the Flask application
# app = Flask(__name__)
# logger = logging.getLogger('lattly')
# @app.route('/')
# def index():
# return "Hello, World!"
# Point FindCenterMidPoint(List<Point> points, Point midPoint);
# Point FindMidPoint(List<Point> points);
# @app.route('/get... | {
"repo_name": "yfarrugia/lattly",
"path": "lattly_api/mid_point_finder.py",
"copies": "1",
"size": "1468",
"license": "bsd-2-clause",
"hash": 6406796602323953000,
"line_mean": 26.6981132075,
"line_max": 65,
"alpha_frac": 0.6294277929,
"autogenerated": false,
"ratio": 2.839458413926499,
"config_... |
__author__ = 'Yanir Taflev'
from applitools.eyes import Eyes
from selenium import webdriver
import unittest
class Test(unittest.TestCase):
eyes = 0
driver = 0
def setUp(self):
self.eyes = Eyes()
self.eyes.api_key = APPLITOOLS_APIKEY
self.driver = webdriver.Firefox()
def tear... | {
"repo_name": "yanirta/applitools.examples",
"path": "Python/test/applitools_site_unittest.py",
"copies": "1",
"size": "1132",
"license": "apache-2.0",
"hash": -8116442332698093000,
"line_mean": 29.5945945946,
"line_max": 113,
"alpha_frac": 0.6254416961,
"autogenerated": false,
"ratio": 3.7733333... |
__author__ = 'yanivshalev'
from hydro.conf.settings import *
ALL = 'ALL'
class Configuration(object):
_conf = {}
def set(self, key, val):
self._conf[key] = val
def get(self, key):
return self._conf[key]
@property
def conf(self):
return self._conf
class Configurator(ob... | {
"repo_name": "Convertro/Hydro",
"path": "src/hydro/common/configurator.py",
"copies": "1",
"size": "2481",
"license": "mit",
"hash": 7978269530035552000,
"line_mean": 28.5357142857,
"line_max": 65,
"alpha_frac": 0.4740024184,
"autogenerated": false,
"ratio": 3.793577981651376,
"config_test": t... |
__author__ = 'yanli'
# Args
# 1: cluster check window (in seconds)
# 2: cluster count
# 3: csv trace file name
# 4: (optional) cluster file name, without which the even divier will be used as the baseline
import sys
import filegrouping
from datetime import timedelta
replay_check_window = timedelta(seconds = int(sys.... | {
"repo_name": "mlogic/data-grouping",
"path": "src/replay_trace.py",
"copies": "1",
"size": "1761",
"license": "bsd-3-clause",
"hash": -7020819108714060000,
"line_mean": 35.7083333333,
"line_max": 181,
"alpha_frac": 0.6541737649,
"autogenerated": false,
"ratio": 3.529058116232465,
"config_test"... |
__author__ = 'Yan'
import pandas
import sklearn.metrics
import statistics
from sklearn import tree
from sklearn.cross_validation import train_test_split
from sklearn.tree import DecisionTreeClassifier
from io import StringIO
from IPython.display import Image
import pydotplus
# bug fix for display formats to... | {
"repo_name": "yan-duarte/yan-duarte.github.io",
"path": "archives/mlda-assignment1.py",
"copies": "1",
"size": "3516",
"license": "mit",
"hash": -4503582648145283600,
"line_mean": 41.4320987654,
"line_max": 146,
"alpha_frac": 0.7403299204,
"autogenerated": false,
"ratio": 3.2051048313582498,
"... |
__author__ = 'Yan'
import numpy
import pandas
import matplotlib.pyplot as plt
import statsmodels.api as sm
import statsmodels.formula.api as smf
import seaborn
import statistics
# bug fix for display formats to avoid run time errors
pandas.set_option('display.float_format', lambda x:'%.2f'%x)
#load the ... | {
"repo_name": "yan-duarte/yan-duarte.github.io",
"path": "archives/rmp-assignment4.py",
"copies": "1",
"size": "3804",
"license": "mit",
"hash": -4161805459781190700,
"line_mean": 46.7692307692,
"line_max": 146,
"alpha_frac": 0.7192429022,
"autogenerated": false,
"ratio": 3.1647254575707153,
"c... |
__author__ = 'Yan'
import numpy
import pandas
import matplotlib.pyplot as plt
import statsmodels.api as sm
import statsmodels.formula.api as smf
import seaborn
# bug fix for display formats to avoid run time errors
pandas.set_option('display.float_format', lambda x:'%.2f'%x)
#load the data
data = pandas... | {
"repo_name": "yan-duarte/yan-duarte.github.io",
"path": "archives/rmp-assignment3.py",
"copies": "1",
"size": "3576",
"license": "mit",
"hash": -6549848870751938000,
"line_mean": 39.1264367816,
"line_max": 102,
"alpha_frac": 0.6546420582,
"autogenerated": false,
"ratio": 3.134092900964067,
"co... |
__author__ = 'Yan'
import pandas
import statistics
import numpy as np
import matplotlib.pylab as plt
from sklearn.cross_validation import train_test_split
from sklearn import preprocessing
from sklearn.cluster import KMeans
# bug fix for display formats to avoid run time errors
pandas.set_option('display.f... | {
"repo_name": "yan-duarte/yan-duarte.github.io",
"path": "archives/mlda-assignment4.py",
"copies": "1",
"size": "5898",
"license": "mit",
"hash": 24415688442889030,
"line_mean": 33.7454545455,
"line_max": 104,
"alpha_frac": 0.7490674805,
"autogenerated": false,
"ratio": 3.2712146422628954,
"con... |
__author__ = 'yaoml'
#coding=utf-8
import requests
import json
import ConfigParser
def testKQLogin(username,password):
postdata = {'username':username,'password':password,'this_is_the_login_form':'1'}
r = requests.post('http://kq.channelsoft.com:49527/iclock/accounts/login/', postdata)
print r.text == 'res... | {
"repo_name": "yaoml/attendanceTool",
"path": "checkRecords.py",
"copies": "1",
"size": "1299",
"license": "apache-2.0",
"hash": -2867279413864590300,
"line_mean": 32.3333333333,
"line_max": 138,
"alpha_frac": 0.688221709,
"autogenerated": false,
"ratio": 2.9725400457665905,
"config_test": fals... |
import ImageGrab # from PIL
import time
import numpy as np
import string
from PIL import Image, ImageChops
from PIL.GifImagePlugin import getheader, getdata
import os
def intToBin(i):
# int to binary
i1 = i % 256
i2 = int(i / 256)
return chr(i1) + chr(i2)
def getheaderAnim(im):
# generate the h... | {
"repo_name": "Yaoshicn/decaptcha",
"path": "giftool.py",
"copies": "2",
"size": "5297",
"license": "mit",
"hash": -8078543352921098000,
"line_mean": 27.6324324324,
"line_max": 75,
"alpha_frac": 0.5365301114,
"autogenerated": false,
"ratio": 3.3461781427668984,
"config_test": false,
"has_no_k... |
from __future__ import division
import time
import urllib2
import socks
from sockshandler import SocksiPyHandler
from PIL import Image, ImageEnhance, ImageFilter, ImageGrab
class Decaptcha:
def __init__(self, new_img_id, counter, number):
while counter < number:
print 'Now processing pic no %d... | {
"repo_name": "Yaoshicn/decaptcha",
"path": "decaptcha.py",
"copies": "2",
"size": "5364",
"license": "mit",
"hash": 742515316389685600,
"line_mean": 43.3305785124,
"line_max": 143,
"alpha_frac": 0.5415734526,
"autogenerated": false,
"ratio": 3.7069799585349,
"config_test": false,
"has_no_key... |
import os
from numpy import *
from time import sleep
def loadDataSet(fileName):
dataMat = []
labelMat = []
fr = open(fileName)
for line in fr.readlines():
lineArr = line.strip().split('\t')
dataMat.append([float(lineArr[0]), float(lineArr[1])])
labelMat.append(float... | {
"repo_name": "Garantion/decaptcha",
"path": "svmMLiA.py",
"copies": "2",
"size": "17464",
"license": "mit",
"hash": -7737606334588233000,
"line_mean": 38.5197215777,
"line_max": 120,
"alpha_frac": 0.529489235,
"autogenerated": false,
"ratio": 3.0006872852233677,
"config_test": true,
"has_no_... |
__author__ = 'yarden'
from sys import argv
import os
from collections import defaultdict
import csv
import sqlite3 as sql
META_FILENAME = 'meta.csv'
TRANSLATE_FILENAME = 'translate.csv'
KB_FILENAME = 'kb.csv'
ENC_DIR = 'encounters'
CG_DB = 'cg.sqlite'
conn = None
root = None
tags_map = {}
def parse_info(filename)... | {
"repo_name": "yarden-livnat/cg",
"path": "scripts/tag.py",
"copies": "1",
"size": "5553",
"license": "mit",
"hash": -2034667547752004600,
"line_mean": 27.192893401,
"line_max": 116,
"alpha_frac": 0.4635332253,
"autogenerated": false,
"ratio": 4.162668665667167,
"config_test": false,
"has_no_... |
__author__ = 'yarden'
from sys import argv
import os
from collections import defaultdict
import csv
tags = dict()
types = defaultdict(int)
fields = [set() for i in range(5)]
def parse_info(filename):
return filename[:filename.find('.')]
def parse_file(d, filename):
enc = parse_info(filename)
with ope... | {
"repo_name": "yarden-livnat/cg",
"path": "scripts/extract.py",
"copies": "1",
"size": "1624",
"license": "mit",
"hash": -6526635420952618000,
"line_mean": 22.5507246377,
"line_max": 54,
"alpha_frac": 0.4593596059,
"autogenerated": false,
"ratio": 3.6825396825396823,
"config_test": false,
"ha... |
__author__ = 'yarden'
from sys import argv
import os
from collections import defaultdict
import csv
tags = dict()
types = defaultdict(int)
temp = dict()
fields = [set() for i in range(5)]
def parse_info(filename):
return filename[:filename.find('.')]
def parse_file(d, filename):
enc = parse_info(filenam... | {
"repo_name": "yarden-livnat/cg",
"path": "scripts/process.py",
"copies": "1",
"size": "2371",
"license": "mit",
"hash": -4978702656082067000,
"line_mean": 25.0549450549,
"line_max": 68,
"alpha_frac": 0.4462252214,
"autogenerated": false,
"ratio": 3.8057784911717496,
"config_test": false,
"ha... |
__author__ = 'yarden'
from sys import argv
import os
from collections import defaultdict
import re
import csv
encounters = dict()
tags = dict()
types = defaultdict(int)
pattern = re.compile('._ADT(\d+)_REG([^_]+)_ENC(\d+)_DOC(\d+)_AGE([^\.]+)')
fields = [set() for i in range(5)]
class Patient:
def __init__(sel... | {
"repo_name": "yarden-livnat/cg",
"path": "scripts/process.prev.py",
"copies": "1",
"size": "2905",
"license": "mit",
"hash": 1392244379996110300,
"line_mean": 23.2166666667,
"line_max": 75,
"alpha_frac": 0.5005163511,
"autogenerated": false,
"ratio": 3.2530795072788354,
"config_test": false,
... |
__author__ = 'yarden'
import csv
import sqlite3 as sql
CG_DB = 'cg.sqlite'
root = '/Users/yarden/data/cg/topaz'
enc2doc = dict()
values = []
def parse(filename):
print 'parse ', filename
with open(root + '/' + filename) as o:
f = csv.DictReader(o)
for row in f:
e = int(row['En... | {
"repo_name": "yarden-livnat/cg",
"path": "scripts/detector.py",
"copies": "1",
"size": "1185",
"license": "mit",
"hash": 1196621477518456000,
"line_mean": 24.2340425532,
"line_max": 103,
"alpha_frac": 0.6033755274,
"autogenerated": false,
"ratio": 3.143236074270557,
"config_test": false,
"ha... |
__author__ = 'yarden'
import os
import re
import csv
from sys import argv
from collections import namedtuple
import yaml
from utils.eyaml import eyaml_load
NodeCoord = namedtuple('NodeCoord', 'group row col node')
MPI_PATTERN = '.*\.mpiP'
PROC_PATTERN = 'xtdb2proc'
QSTAT_PATTERN = 'qstat.*before'
NETTILE_PATTERN = ... | {
"repo_name": "LLNL/DragonView",
"path": "app/data/sim/dump_net.py",
"copies": "2",
"size": "8535",
"license": "bsd-2-clause",
"hash": 2168092726388678700,
"line_mean": 28.7386759582,
"line_max": 99,
"alpha_frac": 0.5282952548,
"autogenerated": false,
"ratio": 3.0201698513800426,
"config_test":... |
__author__ = 'yashar'
from django.db import models
from django.contrib.auth.models import User
from django.forms import ModelForm
from django import forms
from django.forms.widgets import RadioSelect, Textarea
from import_export import resources
from survey.forms import clean_to_zero
SEX_CHOICES = \
(
(... | {
"repo_name": "leifos/treconomics",
"path": "treconomics_project/diversity/models.py",
"copies": "1",
"size": "3250",
"license": "mit",
"hash": -7197958036689595000,
"line_mean": 29.1018518519,
"line_max": 186,
"alpha_frac": 0.5913846154,
"autogenerated": false,
"ratio": 3.6931818181818183,
"co... |
__author__ = 'Yasoob'
from youtube_dl.postprocessor.ffmpeg import FFmpegPostProcessor
from PyQt4 import QtCore
import os
import math
class FFmpegVideoConvertorPP(FFmpegPostProcessor):
def __init__(self, outpath, downloader=None, preferedformat=None):
super(FFmpegVideoConvertorPP, self).__init__(downloader... | {
"repo_name": "janusnic/youtube-dl-GUI",
"path": "Threads/PostProcessor.py",
"copies": "3",
"size": "3271",
"license": "mit",
"hash": -7015311272076103000,
"line_mean": 30.4615384615,
"line_max": 107,
"alpha_frac": 0.5811678386,
"autogenerated": false,
"ratio": 3.7727797001153403,
"config_test"... |
__author__ = 'ycb'
from array_add_edit_view import *
from html_dic import *
from func_to_html_add_edit_view import *
import os
if __name__ == '__main__':
out_dir = os.path.join(os.getcwd(), '../../templates')
bianliang_arr = globals().copy().keys()
for bianliang in bianliang_arr:
if bianliang.star... | {
"repo_name": "jiaxiaolei/pycate",
"path": "script/add_edit_view/gen_add_edit_view_html.py",
"copies": "1",
"size": "3384",
"license": "mit",
"hash": 453856297448206400,
"line_mean": 43.5263157895,
"line_max": 97,
"alpha_frac": 0.4497635934,
"autogenerated": false,
"ratio": 3.5961742826780023,
... |
__author__ = 'ycchang'
import sys
import json
import os
import time
from httplib2 import Http
class Utility:
def __init__(self):
pass
@staticmethod
def execute_until_timeout(function, timeout, *parameters):
for counter in xrange(0, timeout+1):
time.sleep(1)
resul... | {
"repo_name": "cloudawan/cloudone_template",
"path": "cassandra/template/cluster - old.py",
"copies": "1",
"size": "11089",
"license": "apache-2.0",
"hash": 800120398837135000,
"line_mean": 40.531835206,
"line_max": 174,
"alpha_frac": 0.5793128325,
"autogenerated": false,
"ratio": 4.0873571691854... |
__author__ = 'ycchang'
import sys
import json
import os
import time
import copy
from httplib2 import Http
class Utility:
def __init__(self):
pass
@staticmethod
def execute_until_timeout(function, timeout, *parameters):
for counter in xrange(0, timeout+1):
time.sleep(1)
... | {
"repo_name": "cloudawan/cloudawan_install",
"path": "kubernetes1.2/roles/master/files/third_party_service_template/rabbitmq/template/cluster.py",
"copies": "2",
"size": "20350",
"license": "apache-2.0",
"hash": -1487233895492684800,
"line_mean": 46.546728972,
"line_max": 193,
"alpha_frac": 0.6047665... |
## https://github.com/annaeg/square-with-gravity
import ugfx
import pyb
import buttons
# IMU is the Inertial Measurement Unit combines accelerometer and gyroscope.
# This uses the https://github.com/emfcamp/Mk3-Firmware/blob/master/lib/imu.py
from imu import IMU
SCREEN_WIDTH = 320
SCREEN_HEIGHT = 240
# More delay w... | {
"repo_name": "annaeg/square-with-gravity",
"path": "square-with-gravity/main.py",
"copies": "1",
"size": "8705",
"license": "mit",
"hash": 8921495870153347000,
"line_mean": 34.2429149798,
"line_max": 137,
"alpha_frac": 0.5684089604,
"autogenerated": false,
"ratio": 3.159709618874773,
"config_t... |
__author__ = 'Yeob'
# Import flask dependencies
from flask import Blueprint, request, render_template, \
flash, g, session, redirect, url_for
# Import password / encryption helper tools
from werkzeug import check_password_hash, generate_password_hash
# Import the database object from the main app mo... | {
"repo_name": "ckc6842/my-hot-spot",
"path": "LargeApp/app/mod_auth/controllers.py",
"copies": "1",
"size": "1247",
"license": "mit",
"hash": 1540079000400510700,
"line_mean": 28.023255814,
"line_max": 75,
"alpha_frac": 0.6776263031,
"autogenerated": false,
"ratio": 3.7223880597014927,
"config_... |
__author__ = 'Yeob'
# Import the database object (db) from the main application module
# We will define this inside /app/__init__.py in the next sections.
from app import db
# Define a base model for other database tables to inherit
class Base(db.Model):
__abstract__ = True
id = db.Column(db.Inte... | {
"repo_name": "ckc6842/my-hot-spot",
"path": "LargeApp/app/mod_auth/models.py",
"copies": "1",
"size": "1358",
"license": "mit",
"hash": 7045509686354335000,
"line_mean": 32.1463414634,
"line_max": 80,
"alpha_frac": 0.6134020619,
"autogenerated": false,
"ratio": 3.8579545454545454,
"config_test... |
__author__ = 'yeray'
# Always prefer setuptools over distutils
from setuptools import setup, find_packages
# To use a consistent encoding
from codecs import open
from os import path
here = path.abspath(path.dirname(__file__))
# Get the long description from the relevant file
with open(path.join(here, 'DESCRIPTION.rs... | {
"repo_name": "enanablancaynumeros/mullpy",
"path": "setup.py",
"copies": "1",
"size": "3367",
"license": "mit",
"hash": 325473625047620860,
"line_mean": 34.4526315789,
"line_max": 79,
"alpha_frac": 0.6560736561,
"autogenerated": false,
"ratio": 4.10609756097561,
"config_test": false,
"has_no... |
__author__ = 'yetone'
import inspect
import argparse
from script_manager.compat import text_type, getargspec
from script_manager.compat.typing import Optional, Union, Tuple, List, _GenericAlias
from script_manager.utils import parse_docstring
ACTION = str
ACTION_STORE = 'store' # type: ACTION
ACTION_APPEND = 'appen... | {
"repo_name": "yetone/script-manager",
"path": "script_manager/command.py",
"copies": "1",
"size": "3388",
"license": "mit",
"hash": 2989264838294768000,
"line_mean": 28.982300885,
"line_max": 89,
"alpha_frac": 0.5661157025,
"autogenerated": false,
"ratio": 4.1066666666666665,
"config_test": fa... |
__author__ = 'yetone'
import sys
import argparse
from script_manager.command import Command
from script_manager.utils import parse_docstring
class Manager(object):
def __init__(self, description=None):
self._command_map = {}
self.docstring = parse_docstring(description)
self.arg_parser = ... | {
"repo_name": "yetone/script-manager",
"path": "script_manager/__init__.py",
"copies": "1",
"size": "1283",
"license": "mit",
"hash": -3662748962049385500,
"line_mean": 26.2978723404,
"line_max": 69,
"alpha_frac": 0.5837879969,
"autogenerated": false,
"ratio": 4.073015873015873,
"config_test": ... |
__author__ = 'yezhihua'
#!/usr/bin/env python
# -*- coding: utf-8 -*-
import os
import MySQLdb
import ConfigParser
configfile = os.path.abspath(os.path.dirname(__name__)) + '/config.ini'
'''
class Singleton:
"""
http://www.mindviewinc.com/Books/Python3Patterns/Index.php
"""
def __init__(self, klass):
s... | {
"repo_name": "deevarvar/myLab",
"path": "baidu_code/cinema_monitor/database.py",
"copies": "1",
"size": "1621",
"license": "mit",
"hash": 7000462819858988000,
"line_mean": 26.0333333333,
"line_max": 134,
"alpha_frac": 0.5879086983,
"autogenerated": false,
"ratio": 3.7093821510297484,
"config_t... |
__author__ = 'yfrank'
from pdb import InterfaceSelector
from pdb import get_sequences
from Bio.PDB import PDBParser
from utils import ispdbid
from utils import isecodid
from utils import handleError
from pdb import MotifSelector
from pdb import ConnectorPDB
from pdb import select_structure
from pdb import is_single_d... | {
"repo_name": "yotamfr/prot2vec",
"path": "src/python/models.py",
"copies": "1",
"size": "13080",
"license": "mit",
"hash": 5601298558125772000,
"line_mean": 24.0574712644,
"line_max": 120,
"alpha_frac": 0.5395259939,
"autogenerated": false,
"ratio": 3.465818759936407,
"config_test": false,
"... |
__author__ = 'yicong'
import csv
import bpy
import bmesh
D = bpy.data
C = bpy.context
O = bpy.ops
def delete_all():
for obj in D.objects:
obj.select = True
if O.object.delete() == {'FINISHED'}:
return 0
else:
return -1
def set_unit_metric():
'''METRIC, DEGREE
display as ... | {
"repo_name": "Yc-Chen/Blender_OpenCV",
"path": "read_and_proctex.py",
"copies": "1",
"size": "2147",
"license": "mit",
"hash": 4644077808190999000,
"line_mean": 26.5256410256,
"line_max": 148,
"alpha_frac": 0.6436888682,
"autogenerated": false,
"ratio": 2.9573002754820936,
"config_test": false... |
__author__ = 'yicong'
import cv2
import numpy as np
import csv
import os
import sys
COIN_RADIUS = 0.02
imgfn = sys.argv[1]
img = cv2.imread(imgfn, 0)
# img = cv2.flip(img, 1)
def bpfilter(img, lf, hf):
imgblur1 = cv2.GaussianBlur(img, (lf, lf), -1)
imgblur2 = cv2.GaussianBlur(img, (hf, hf), -1)
imgdiff... | {
"repo_name": "Yc-Chen/Blender_OpenCV",
"path": "imgproc.py",
"copies": "1",
"size": "1073",
"license": "mit",
"hash": -2843093078324439000,
"line_mean": 28,
"line_max": 106,
"alpha_frac": 0.6458527493,
"autogenerated": false,
"ratio": 2.542654028436019,
"config_test": false,
"has_no_keywords... |
__author__ = 'Yifan Peng'
from distutils.core import setup
setup(
name = 'bllipbioc',
version = '1.0.dev1',
description = 'Parses the BioC file using bllip parser.',
author = 'Yifan Peng',
author_email = 'yifan.peng@nih.gov',
keywords = ['bioc'],
license = 'BSD 3-clause license',
url = ... | {
"repo_name": "yfpeng/pengyifan-bllip",
"path": "setup.py",
"copies": "1",
"size": "1358",
"license": "bsd-3-clause",
"hash": -673246009353260500,
"line_mean": 36.75,
"line_max": 79,
"alpha_frac": 0.5861561119,
"autogenerated": false,
"ratio": 4.140243902439025,
"config_test": false,
"has_no_... |
__author__ = 'Yifei'
def z_array(s):
"""
Z-algorithm used in BM-Search
:param s: the string from which to extract
:return: a list of the length of prefix-substring
"""
assert len(s) > 1
n = len(s)
z = [0] * n
z[0] = n
l, r = 0, 0
for i in range(1, n):
if i > r:
... | {
"repo_name": "BHFaction/SanBot",
"path": "src/pySanbot/util/boyer_moore_search.py",
"copies": "1",
"size": "6491",
"license": "mit",
"hash": -1796923376506159000,
"line_mean": 28.371040724,
"line_max": 84,
"alpha_frac": 0.5216453551,
"autogenerated": false,
"ratio": 3.276627965673902,
"config_... |
__author__ = 'Yifu Huang'
import sys
sys.path.append("..")
from azureStorage import *
from azureCloudService import *
from azureVirtualMachines import *
from azure.servicemanagement import *
class AzureImpl():
"""
Azure cloud service management
For logic: besides resources created by this program itself,... | {
"repo_name": "mshubian/BAK_open-hackathon",
"path": "open-hackathon/src/hackathon/azureautodeploy/azureImpl.py",
"copies": "1",
"size": "17305",
"license": "apache-2.0",
"hash": 4423930129574189600,
"line_mean": 54.1114649682,
"line_max": 118,
"alpha_frac": 0.5492632187,
"autogenerated": false,
... |
__author__ = 'Yifu Huang'
import sys
sys.path.append("..")
from azureUtil import *
from hackathon.database.models import *
from hackathon.log import *
class AzureStorage:
"""
Azure storage is used for azure virtual machines to store their disks
Note that the number of azure storage account of user may hav... | {
"repo_name": "mshubian/BAK_open-hackathon",
"path": "open-hackathon/src/hackathon/azureautodeploy/azureStorage.py",
"copies": "1",
"size": "4067",
"license": "apache-2.0",
"hash": 8691141884308024000,
"line_mean": 46.8588235294,
"line_max": 118,
"alpha_frac": 0.5719203344,
"autogenerated": false,
... |
__author__ = 'Yifu Huang'
import sys
sys.path.append("..")
from azureUtil import *
from hackathon.log import *
from hackathon.database.models import *
class AzureCloudService:
"""
Azure cloud service is used as DNS for azure virtual machines
Note that the public ports of virtual machines on the same clou... | {
"repo_name": "mshubian/BAK_open-hackathon",
"path": "open-hackathon/src/hackathon/azureautodeploy/azureCloudService.py",
"copies": "1",
"size": "3544",
"license": "apache-2.0",
"hash": -3398081697934699500,
"line_mean": 45.038961039,
"line_max": 118,
"alpha_frac": 0.6001693002,
"autogenerated": fa... |
__author__ = 'Yifu Huang'
import sys
sys.path.append("..")
from azureImpl import *
from hackathon.functions import *
from hackathon.enum import *
def set_expr_status(e_id, status):
expr = db_adapter.get_object(Experiment, e_id)
expr.status = status
db_adapter.commit()
if __name__ == "__main__":
ar... | {
"repo_name": "mshubian/BAK_open-hackathon",
"path": "open-hackathon/src/hackathon/azureautodeploy/azureCreateAsync.py",
"copies": "1",
"size": "1106",
"license": "apache-2.0",
"hash": 6518970970021836000,
"line_mean": 28.1315789474,
"line_max": 69,
"alpha_frac": 0.6446654611,
"autogenerated": fals... |
# import libraries
import numpy
import matplotlib.pyplot
from Bandit import Bandit
def play_three_armed_bandit(mean_1, mean_2, mean_3, epsilon, number_of_play):
bandits = [Bandit(mean_1), Bandit(mean_2), Bandit(mean_3)]
data = numpy.empty(number_of_play)
for play in range(number_of_play):
# epsilon-greedy is a... | {
"repo_name": "GitYiheng/reinforcement_learning_test",
"path": "test00_previous_files/three_armed_bandit.py",
"copies": "1",
"size": "4984",
"license": "mit",
"hash": 8232834269773194000,
"line_mean": 41.9655172414,
"line_max": 110,
"alpha_frac": 0.7363563403,
"autogenerated": false,
"ratio": 3.1... |
__author__ = 'yilinhe'
from DBConnector import createSqlString, executeQueries
def getMatch(match):
'''
return a dictionary of match result:
{matchId:match_id, winner:team100, team_100:{p1:champ1 ... p5:champ5}, team_200:{p1:champ1 ... p5:champ5} }
'''
# Store the participants info relates to this... | {
"repo_name": "yilinhe/MOBA-TeamCompDecoding",
"path": "lol-data-collection/MatchStore.py",
"copies": "1",
"size": "1624",
"license": "mit",
"hash": -4094455225543152000,
"line_mean": 28,
"line_max": 111,
"alpha_frac": 0.6336206897,
"autogenerated": false,
"ratio": 3.4775160599571735,
"config_t... |
__author__ = 'yilinhe'
import time
from riotwatcher import RiotWatcher
from MatchStore import storeMatchInfo, getMatch
from PlayerInfoCollector import getPlayerIds, getPlayerMatchHistory, getPlayerFamilarity, loadPlayerIdsFromFile
from DBConnector import getMatchFromDB
f = open('configuration.txt')
api_key = f.read()... | {
"repo_name": "yilinhe/MOBA-TeamCompDecoding",
"path": "lol-data-collection/GameCollector.py",
"copies": "1",
"size": "2097",
"license": "mit",
"hash": -1698899774805248500,
"line_mean": 35.1724137931,
"line_max": 119,
"alpha_frac": 0.606103958,
"autogenerated": false,
"ratio": 3.9491525423728815... |
__author__ = "Yinchong Yang"
__copyright__ = "Siemens AG, 2017"
__licencse__ = "MIT"
__version__ = "0.1"
"""
MIT License
Copyright (c) 2017 Siemens AG
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Soft... | {
"repo_name": "Tuyki/TT_RNN",
"path": "Datasets/Datasets.py",
"copies": "1",
"size": "5213",
"license": "mit",
"hash": 2629420330205101000,
"line_mean": 34.462585034,
"line_max": 103,
"alpha_frac": 0.6268943027,
"autogenerated": false,
"ratio": 3.3872644574398962,
"config_test": false,
"has_n... |
__author__ = 'yinjun'
class Queue:
# initialize your data structure here.
def __init__(self):
self.s1 = []
self.s2 = []
self.length = 0
# @param x, an integer
# @return nothing
def push(self, x):
self.length +=1
self.s1.append(x)
... | {
"repo_name": "shootsoft/practice",
"path": "LeetCode/python/211-240/232-implement-queue-using-stacks/solution.py",
"copies": "1",
"size": "1045",
"license": "apache-2.0",
"hash": -4549283301385547000,
"line_mean": 17.6785714286,
"line_max": 42,
"alpha_frac": 0.4708133971,
"autogenerated": false,
... |
__author__ = 'yinjun'
class Solution:
def jump(self, A):
if A==None or A == []:
return 0
n = len(A)
steps = [0 for i in range(n)]
start = 0
end = 0
jumps = 0
while end < n-1:
jumps += 1
farthest = end
for ... | {
"repo_name": "shootsoft/practice",
"path": "lintcode/NineChapters/04/jump-game-ii.py",
"copies": "1",
"size": "1087",
"license": "apache-2.0",
"hash": 966219457367453400,
"line_mean": 19.9038461538,
"line_max": 62,
"alpha_frac": 0.3909843606,
"autogenerated": false,
"ratio": 3.283987915407855,
... |
__author__ = 'yinjun'
class Solution:
"""
Get all distinct N-Queen solutions
@param n: The number of queens
@return: All distinct solutions
"""
def solveNQueens(self, n):
# write your code here
self.results=[]
self.solve(n, [])
return self.results
def solve(... | {
"repo_name": "shootsoft/practice",
"path": "lintcode/NineChapters/07/n-queens.py",
"copies": "1",
"size": "1627",
"license": "apache-2.0",
"hash": 724484755947615900,
"line_mean": 23.6515151515,
"line_max": 61,
"alpha_frac": 0.3859864782,
"autogenerated": false,
"ratio": 4.494475138121547,
"co... |
__author__ = 'yinjun'
class Solution:
"""
Get all distinct N-Queen solutions
@param n: The number of queens
@return: All distinct solutions
"""
def totalNQueens(self, n):
# write your code here
self.results=0
self.solve(n, [])
return self.results
def solve(s... | {
"repo_name": "shootsoft/practice",
"path": "LeetCode/python/031-060/051-n-queens-ii/solution.py",
"copies": "1",
"size": "1255",
"license": "apache-2.0",
"hash": -5692043262232838000,
"line_mean": 24.612244898,
"line_max": 61,
"alpha_frac": 0.3832669323,
"autogenerated": false,
"ratio": 4.648148... |
__author__ = 'yinjun'
class Solution:
# @return a string
def minWindow(self, S, T):
#print S, T
lS = len(S)
lT = len(T)
if lT > lS:
return ""
c = self.countTZan(T)
self.szan = {}
end = c
if end > lS:
end = lS
s... | {
"repo_name": "shootsoft/practice",
"path": "LeetCode/python/061-090/076-minimum-window-substring/solution.py",
"copies": "1",
"size": "1949",
"license": "apache-2.0",
"hash": -3513234084328816600,
"line_mean": 19.7446808511,
"line_max": 55,
"alpha_frac": 0.361723961,
"autogenerated": false,
"rat... |
__author__ = 'yinjun'
class Solution:
"""
@param A : a list of integers
@param target : an integer to be searched
@return : a list of length 2, [index1, index2]
"""
def searchRange(self, A, target):
# write your code here
length = len(A)
start = 0
end = length -... | {
"repo_name": "shootsoft/practice",
"path": "LeetCode/python/031-060/032-search-for-a-range/range.py",
"copies": "1",
"size": "1339",
"license": "apache-2.0",
"hash": -1782259824901111300,
"line_mean": 22.1034482759,
"line_max": 51,
"alpha_frac": 0.4398805078,
"autogenerated": false,
"ratio": 3.7... |
__author__ = 'yinjun'
class Solution:
"""
@param A : a list of integers
@param target : an integer to be searched
@return : an integer
"""
def search(self, A, target):
# write your code here
length = len(A)
if length == 0:
return -1
start = 0
... | {
"repo_name": "shootsoft/practice",
"path": "lintcode/NineChapters/02/search-in-rotated-sorted-array.py",
"copies": "1",
"size": "1032",
"license": "apache-2.0",
"hash": -3805745715569354000,
"line_mean": 21.9555555556,
"line_max": 58,
"alpha_frac": 0.4118217054,
"autogenerated": false,
"ratio": ... |
__author__ = 'yinjun'
class Solution:
"""
@param A: An integer array.
@param B: An integer array.
@return: a double whose format is *.5 or *.0
"""
def findMedianSortedArrays(self, A, B):
# write your code here
lenA = len(A)
lenB = len(B)
l = lenA + lenB
... | {
"repo_name": "shootsoft/practice",
"path": "LeetCode/python/001-030/002-median-of-two-sorted-arrays/median.py",
"copies": "1",
"size": "1573",
"license": "apache-2.0",
"hash": 4630040704985550000,
"line_mean": 26.6140350877,
"line_max": 112,
"alpha_frac": 0.5219326128,
"autogenerated": false,
"r... |
__author__ = 'yinjun'
class Solution:
"""
@param A: An integer array.
@param k: A positive integer (k <= length(A))
@param target: Integer
@return a list of lists of integer
"""
def kSumII(self, A, k, target):
# write your code here
A.sort()
self.results=[]
... | {
"repo_name": "shootsoft/practice",
"path": "lintcode/NineChapters/07/k-sum-ii.py",
"copies": "1",
"size": "1227",
"license": "apache-2.0",
"hash": -5099827566841763000,
"line_mean": 24.0408163265,
"line_max": 60,
"alpha_frac": 0.3903830481,
"autogenerated": false,
"ratio": 3.996742671009772,
"... |
__author__ = 'yinjun'
class Solution:
# @param A a list of integers
# @return nothing, sort in place
def sortColors(self, A):
# p0 = 0
# p1 = self.count(A, 0)
# p2 = p1 + self.count(A, 1)
p0 = self.count(A, 0)
p = [0, p0, p0 + self.count(A, 1)]
l = len(A)
... | {
"repo_name": "shootsoft/practice",
"path": "LeetCode/python/061-090/075-sort-colors/solution.py",
"copies": "1",
"size": "1164",
"license": "apache-2.0",
"hash": 644234732746157700,
"line_mean": 21.4038461538,
"line_max": 61,
"alpha_frac": 0.3694158076,
"autogenerated": false,
"ratio": 3.3837209... |
__author__ = 'yinjun'
class Solution:
# @param num, a list of integer
# @return a list of integer
def nextPermutation(self, target):
self.target = target
self.find = False
self.result = []
length = len(target)
if length <= 1:
return target
else:... | {
"repo_name": "shootsoft/practice",
"path": "LeetCode/python/031-060/031-next-permutation/nextpermutation.py",
"copies": "1",
"size": "1153",
"license": "apache-2.0",
"hash": -8597167078437154000,
"line_mean": 21.1730769231,
"line_max": 51,
"alpha_frac": 0.4761491761,
"autogenerated": false,
"rat... |
__author__ = 'yinjun'
class Solution:
# @param s, a string
# @return a list of lists of string
def partition(self, s):
# write your code here
n = len(s)
if n == 0:
return []
if n == 1:
return [[n]]
self.partition_init(s)
self.parti... | {
"repo_name": "shootsoft/practice",
"path": "lintcode/NineChapters/07/palindrome-partitioning.py",
"copies": "1",
"size": "1475",
"license": "apache-2.0",
"hash": 8814302771913705000,
"line_mean": 21.3636363636,
"line_max": 101,
"alpha_frac": 0.4522033898,
"autogenerated": false,
"ratio": 3.29241... |
__author__ = 'yinjun'
class Solution:
# @param s, a string
# @return an integer
def minCut(self, s):
# write your code here
if s == None or s =="":
return 0
l = len(s)
r = self.getAllPalindrome(s, l)
f = [0 for i in range(l+1)]
for i in range(l... | {
"repo_name": "shootsoft/practice",
"path": "lintcode/NineChapters/04/palindrome-partitioning-ii.py",
"copies": "2",
"size": "1027",
"license": "apache-2.0",
"hash": 8248344565909904000,
"line_mean": 20.3958333333,
"line_max": 91,
"alpha_frac": 0.4420642648,
"autogenerated": false,
"ratio": 3.112... |
__author__ = 'yinjun'
class Solution:
# @param start, a string
# @param end, a string
# @param dict, a set of string
# @return an integer
def ladderLength(self, start, end, dict):
# write your code here
###fuck fuck fuck
if start == "nanny" and end =="aloud":
ret... | {
"repo_name": "shootsoft/practice",
"path": "lintcode/NineChapters/07/word-ladder.py",
"copies": "1",
"size": "3297",
"license": "apache-2.0",
"hash": -7426805351432559000,
"line_mean": 23.7969924812,
"line_max": 85,
"alpha_frac": 0.4027904155,
"autogenerated": false,
"ratio": 4.07540173053152,
... |
__author__ = 'yinjun'
class VersionControl:
@classmethod
def isBadVersion(cls, id):
return False
#class VersionControl:
# @classmethod
# def isBadVersion(cls, id)
# # Run unit tests to check whether verison `id` is a bad version
# # return true if unit tests passed else false.
# Yo... | {
"repo_name": "shootsoft/practice",
"path": "lintcode/NineChapters/02/first-bad-version.py",
"copies": "1",
"size": "1130",
"license": "apache-2.0",
"hash": -424004776145602560,
"line_mean": 24.1333333333,
"line_max": 78,
"alpha_frac": 0.5407079646,
"autogenerated": false,
"ratio": 4.312977099236... |
__author__ = 'yinjun'
# Definition for a binary tree node
# class TreeNode:
# def __init__(self, x):
# self.val = x
# self.left = None
# self.right = None
class BSTIterator:
# @param root, a binary search tree's root node
def __init__(self, root):
stack = []
dict ... | {
"repo_name": "shootsoft/practice",
"path": "LeetCode/python/151-180/173-binary-search-tree-iterator/solution.py",
"copies": "1",
"size": "1980",
"license": "apache-2.0",
"hash": 1129313986016841300,
"line_mean": 26.9014084507,
"line_max": 65,
"alpha_frac": 0.4777777778,
"autogenerated": false,
"... |
__author__ = 'yinjun'
# Definition for a binary tree node
# class TreeNode:
# def __init__(self, x):
# self.val = x
# self.left = None
# self.right = None
class Solution:
# @param root, a tree node
# @return a tree node
def recoverTree(self, root):
d = self.depth(root)... | {
"repo_name": "shootsoft/practice",
"path": "LeetCode/python/091-120/099-recover-binary-search-tree/solution.py",
"copies": "1",
"size": "3399",
"license": "apache-2.0",
"hash": -3392071288945607700,
"line_mean": 25.3488372093,
"line_max": 146,
"alpha_frac": 0.4919093851,
"autogenerated": false,
... |
__author__ = 'yinjun'
# Definition for a binary tree node.
class TreeNode:
def __init__(self, x):
self.val = x
self.left = None
self.right = None
class Solution:
# @param {TreeNode} root
# @return {integer[]}
def postorderTraversal(self, root):
stack = []
dict ... | {
"repo_name": "shootsoft/practice",
"path": "lintcode/NineChapters/03/binary-tree-postorder-travesal.py",
"copies": "1",
"size": "1383",
"license": "apache-2.0",
"hash": -4541358986846288000,
"line_mean": 23.7142857143,
"line_max": 87,
"alpha_frac": 0.4844540853,
"autogenerated": false,
"ratio": ... |
__author__ = 'yinjun'
# Definition for a binary tree node.
# class TreeNode:
# def __init__(self, x):
# self.val = x
# self.left = None
# self.right = None
class Solution:
# @param {TreeNode} root
# @return {integer[]}
def postorderTraversal(self, root):
stack = []
... | {
"repo_name": "shootsoft/practice",
"path": "LeetCode/python/121-150/145-binary-tree-postorder-traversal/solution.py",
"copies": "1",
"size": "1410",
"license": "apache-2.0",
"hash": -337247661422070400,
"line_mean": 23.7543859649,
"line_max": 87,
"alpha_frac": 0.475177305,
"autogenerated": false,
... |
__author__ = 'yinjun'
# Definition for a Directed graph node
# class DirectedGraphNode:
# def __init__(self, x):
# self.label = x
# self.neighbors = []
class Solution:
"""
@param graph: A list of Directed graph node
@return: A list of integer
"""
def topSort(self, graph):
... | {
"repo_name": "shootsoft/practice",
"path": "lintcode/NineChapters/07/topological-sorting.py",
"copies": "1",
"size": "1918",
"license": "apache-2.0",
"hash": 6497023798589986000,
"line_mean": 18.9791666667,
"line_max": 47,
"alpha_frac": 0.4947862357,
"autogenerated": false,
"ratio": 3.5716945996... |
__author__ = 'yinjun'
# Definition for singly-linked list.
# class ListNode:
# def __init__(self, x):
# self.val = x
# self.next = None
class Solution:
# @param head, a ListNode
# @param m, an integer
# @param n, an integer
# @return a ListNode
def reverseBetween(self, head, m,... | {
"repo_name": "shootsoft/practice",
"path": "LeetCode/python/091-120/095-reverse-linked-list-ii/solution.py",
"copies": "1",
"size": "2026",
"license": "apache-2.0",
"hash": -7601219732802764000,
"line_mean": 17.9439252336,
"line_max": 55,
"alpha_frac": 0.4407699901,
"autogenerated": false,
"rati... |
__author__ = 'yinjun'
# Definition for singly-linked list.
# class ListNode:
# def __init__(self, x):
# self.val = x
# self.next = None
# Definition for a binary tree node.
# class TreeNode:
# def __init__(self, x):
# self.val = x
# self.left = None
# self.right = None
... | {
"repo_name": "shootsoft/practice",
"path": "lintcode/NineChapters/06/convert-sorted-list-to-binary-search-tree.py",
"copies": "1",
"size": "1085",
"license": "apache-2.0",
"hash": -877573501074643700,
"line_mean": 23.6590909091,
"line_max": 60,
"alpha_frac": 0.5142857143,
"autogenerated": false,
... |
__author__ = 'yinjun'
import os
import imp
import time
class SimpleLeetLoader:
def loadDirs(self):
os.chdir(os.path.dirname(os.path.abspath(__file__)))
#print os.path.dirname(os.path.abspath(__file__))
#print os.getcwd()
dirs = os.listdir(os.getcwd())
code = {}
fo... | {
"repo_name": "shootsoft/practice",
"path": "LeetCode/python/run.py",
"copies": "1",
"size": "2419",
"license": "apache-2.0",
"hash": 1372786291216010000,
"line_mean": 26.5,
"line_max": 76,
"alpha_frac": 0.4105002067,
"autogenerated": false,
"ratio": 4.28141592920354,
"config_test": false,
"h... |
__author__ = 'yinjun'
import unittest
import os
import imp
class TestSolutionFuncs(unittest.TestCase):
def setUp(self):
path = os.getcwd() + '/solution.py'
so = imp.load_source('solution', path)
self.s = so.Solution()
# common = os.path.dirname(os.path.dirname(os.getcwd())) + '/c... | {
"repo_name": "shootsoft/practice",
"path": "LeetCode/python/151-180/168-excel-sheet-column-title/test.py",
"copies": "1",
"size": "1174",
"license": "apache-2.0",
"hash": 1790970824549588200,
"line_mean": 25.0888888889,
"line_max": 88,
"alpha_frac": 0.6192504259,
"autogenerated": false,
"ratio":... |
__author__ = 'yinjun'
class Solution:
"""
@param A: An integer array.
@param k: a positive integer (k <= length(A))
@param target: integer
@return an integer
"""
def kSum(self, A, k, target):
# write your code here
self.result = []
cur = []
A.sort()
... | {
"repo_name": "shootsoft/practice",
"path": "lintcode/NineChapters/05/ksum.py",
"copies": "1",
"size": "2866",
"license": "apache-2.0",
"hash": 475462229075276600,
"line_mean": 27.9595959596,
"line_max": 121,
"alpha_frac": 0.394277739,
"autogenerated": false,
"ratio": 3.105092091007584,
"config... |
__author__ = 'yinjun'
class Solution:
"""
@param nums: The rotated sorted array
@return: nothing
"""
def recoverRotatedSortedArray(self, nums):
# write your code here
length = len(nums)
minPos = self.findMin(nums, length)
#print minPos, nums[minPos]
if minP... | {
"repo_name": "shootsoft/practice",
"path": "lintcode/NineChapters/02/recover-rotated-sorted-array.py",
"copies": "1",
"size": "1624",
"license": "apache-2.0",
"hash": -8611206806480620000,
"line_mean": 22.2,
"line_max": 71,
"alpha_frac": 0.4642857143,
"autogenerated": false,
"ratio": 3.390396659... |
__author__ = 'yinjun'
"""
Definition of ListNode
class ListNode(object):
def __init__(self, val, next=None):
self.val = val
self.next = next
"""
class Solution:
"""
@param head: The first node of linked list.
@param x: an integer
@return: a ListNode
"""
def partition(self, ... | {
"repo_name": "shootsoft/practice",
"path": "lintcode/NineChapters/06/partition-list.py",
"copies": "1",
"size": "1317",
"license": "apache-2.0",
"hash": 1861621437646046200,
"line_mean": 20.5901639344,
"line_max": 56,
"alpha_frac": 0.4039483675,
"autogenerated": false,
"ratio": 3.658333333333333... |
__author__ = 'yinjun'
"""
Definition of TreeNode:
class TreeNode:
def __init__(self, val):
this.val = val
this.left, this.right = None, None
"""
class Solution:
"""
@param root: The root of the binary search tree.
@param value: Remove the node with given value.
@return: The root of ... | {
"repo_name": "shootsoft/practice",
"path": "lintcode/NineChapters/03/remove-node-in-binary-search-tree.py",
"copies": "1",
"size": "2034",
"license": "apache-2.0",
"hash": 3311081851591152600,
"line_mean": 21.3516483516,
"line_max": 62,
"alpha_frac": 0.5073746313,
"autogenerated": false,
"ratio"... |
__author__ = 'yinjun'
"""
Definition of TreeNode:
class TreeNode:
def __init__(self, val):
this.val = val
this.left, this.right = None, None
Example of iterate a tree:
iterator = Solution(root)
while iterator.hasNext():
node = iterator.next()
do something for node
"""
class Solution:
#... | {
"repo_name": "shootsoft/practice",
"path": "lintcode/NineChapters/03/binary-search-tree-iterator.py",
"copies": "1",
"size": "2031",
"license": "apache-2.0",
"hash": -4089421949239902000,
"line_mean": 25.0384615385,
"line_max": 70,
"alpha_frac": 0.5022156573,
"autogenerated": false,
"ratio": 3.9... |
__author__ = 'yinjun'
"""
Definition of TreeNode:
class TreeNode:
def __init__(self, val):
this.val = val
this.left, this.right = None, None
"""
class TreeNode:
def __init__(self, x):
self.val = x
self.left = None
self.right = None
class Solution:
"""
@param ro... | {
"repo_name": "shootsoft/practice",
"path": "lintcode/NineChapters/03/binary-tree-inorder-travesal.py",
"copies": "1",
"size": "1825",
"license": "apache-2.0",
"hash": -3312740210622172700,
"line_mean": 23.3466666667,
"line_max": 65,
"alpha_frac": 0.4717808219,
"autogenerated": false,
"ratio": 3.... |
__author__ = 'yinjun'
"""
Definition of TreeNode:
class TreeNode:
def __init__(self, val):
this.val = val
this.left, this.right = None, None
"""
# example
# int pre[] = {7, 10, 4, 3, 1, 2, 8, 11};
# int in[] = {4, 10, 3, 1, 7, 11, 8, 2};
class Solution:
"""
@param preorder : A list of int... | {
"repo_name": "shootsoft/practice",
"path": "lintcode/NineChapters/03/construct-binary-tree-from-preorder-and-inorder-traversal.py",
"copies": "1",
"size": "1086",
"license": "apache-2.0",
"hash": 2766350670019911000,
"line_mean": 24.2790697674,
"line_max": 74,
"alpha_frac": 0.5515653775,
"autogene... |
__author__ = 'yinjun'
"""
Definition of TreeNode:
class TreeNode:
def __init__(self, val):
this.val = val
this.left, this.right = None, None
"""
class Solution:
"""
@param preorder : A list of integers that preorder traversal of a tree
@param inorder : A list of integers that inorder ... | {
"repo_name": "shootsoft/practice",
"path": "LeetCode/python/091-120/solution.py",
"copies": "1",
"size": "1441",
"license": "apache-2.0",
"hash": -4616760258602606000,
"line_mean": 28.4285714286,
"line_max": 106,
"alpha_frac": 0.5954198473,
"autogenerated": false,
"ratio": 3.4806763285024154,
... |
__author__ = 'yinjun'
'''
'''
class ListNode:
def __init__(self, x):
self.val = x
self.next = None
def toList(self):
v = [self.val]
c = self.next
while c!=None:
v.append(c.val)
c = c.next
def __str__(self):
self.toLit()
retu... | {
"repo_name": "shootsoft/practice",
"path": "LeetCode/python/common/listnode.py",
"copies": "1",
"size": "1124",
"license": "apache-2.0",
"hash": -3747055708155854300,
"line_mean": 17.4426229508,
"line_max": 44,
"alpha_frac": 0.4190391459,
"autogenerated": false,
"ratio": 3.73421926910299,
"con... |
__author__ = 'yinjun'
"""
Definition of TreeNode:
class TreeNode:
def __init__(self, val):
this.val = val
this.left, this.right = None, None
"""
class Solution:
"""
@param root: The root of binary tree.
@return: True if the binary tree is BST, or false
"""
def isValidBST(self... | {
"repo_name": "shootsoft/practice",
"path": "LeetCode/python/091-120/098-validate-binary-search-tree/solution.py",
"copies": "2",
"size": "1620",
"license": "apache-2.0",
"hash": 4669972247571896000,
"line_mean": 32.0612244898,
"line_max": 111,
"alpha_frac": 0.5833333333,
"autogenerated": false,
... |
__author__ = 'yinjun'
"""
Definition of TreeNode:
class TreeNode:
def __init__(self, val):
this.val = val
this.left, this.right = None, None
"""
class Solution:
"""
@param root: The root of binary tree.
@return: A list of list of integer include
the zig zag level order t... | {
"repo_name": "shootsoft/practice",
"path": "lintcode/NineChapters/03/binary-tree-zigzag-level-order-traversal.py",
"copies": "2",
"size": "1120",
"license": "apache-2.0",
"hash": 4120611876891264000,
"line_mean": 18.6666666667,
"line_max": 67,
"alpha_frac": 0.4276785714,
"autogenerated": false,
... |
__author__ = 'yinjun'
'''
Point object
'''
class Point:
###
# Init object
###
def __init__(self, x, y):
self.x = x
self.y = y
self.distance = None
'''
Obtain approximate distance
'''
def getDistance(self):
if self.distance == None:
self.dis... | {
"repo_name": "shootsoft/practice",
"path": "companyA/KPoint.py",
"copies": "1",
"size": "5236",
"license": "apache-2.0",
"hash": -1916101715160356900,
"line_mean": 23.4719626168,
"line_max": 142,
"alpha_frac": 0.4745989305,
"autogenerated": false,
"ratio": 4.132596685082873,
"config_test": fal... |
__author__ = 'yinjun'
"""
@see http://blog.csdn.net/u011095253/article/details/9248073
@see http://www.jiuzhang.com/solutions/interleaving-string/
"""
class Solution:
"""
@params s1, s2, s3: Three strings as description.
@return: return True if s3 is formed by the interleaving of
s1 and s2 or ... | {
"repo_name": "shootsoft/practice",
"path": "lintcode/NineChapters/05/interleaving-string.py",
"copies": "1",
"size": "1179",
"license": "apache-2.0",
"hash": -6591409453400733000,
"line_mean": 27.0952380952,
"line_max": 80,
"alpha_frac": 0.4826123834,
"autogenerated": false,
"ratio": 2.691780821... |
__author__ = 'yinjun'
'''
@see http://www.cnblogs.com/lishiblog/p/4183806.html
@see http://www.jiuzhang.com/solutions/backpack/
'''
class Solution:
# @param m: An integer m denotes the size of a backpack
# @param A: Given n items with size A[i]
# @return: The maximum size
def backPack(self, m, A):
... | {
"repo_name": "shootsoft/practice",
"path": "lintcode/NineChapters/05/backpack.py",
"copies": "1",
"size": "1217",
"license": "apache-2.0",
"hash": -6847385652687949000,
"line_mean": 37.03125,
"line_max": 459,
"alpha_frac": 0.580115037,
"autogenerated": false,
"ratio": 2.448692152917505,
"confi... |
__author__ = 'Yin'
from carbon import getModeCarbonFootprint, carbonFootprintForMode
from common import Inside_polygon,berkeley_area,getConfirmationModeQuery
from get_database import get_section_db,get_profile_db
# Note that all the points here are returned in (lng, lat) format, which is the
# GeoJSON format.
def car... | {
"repo_name": "sdsingh/e-mission-server",
"path": "CFC_WebApp/main/visualize.py",
"copies": "1",
"size": "2459",
"license": "bsd-3-clause",
"hash": 5952661239416880000,
"line_mean": 40.6779661017,
"line_max": 134,
"alpha_frac": 0.6059373729,
"autogenerated": false,
"ratio": 3.512857142857143,
"... |
__author__ = 'Yin'
from pymongo import MongoClient
from common import Is_date, Is_place, get_mode_share_by_distance, berkeley_area
from tripManager import travel_time
from get_database import get_section_db,get_profile_db
# from commute import get_morning_commute_sections
from dateutil import parser
def get_Alluser_mo... | {
"repo_name": "sdsingh/e-mission-server",
"path": "CFC_WebApp/main/modeshare.py",
"copies": "1",
"size": "1225",
"license": "bsd-3-clause",
"hash": -4568252594557710300,
"line_mean": 46.1153846154,
"line_max": 144,
"alpha_frac": 0.6220408163,
"autogenerated": false,
"ratio": 3.0472636815920398,
... |
__author__ = 'Yin'
from pymongo import MongoClient
from home import detect_home, detect_home_from_db
from home_2 import detect_home_2, detect_home_from_db_2
from tripManager import calDistance
from common import Is_weekday, get_static_pnts, most_common_2, calculate_appearance_rate, Is_date, Is_place_2
from dateutil imp... | {
"repo_name": "sdsingh/e-mission-server",
"path": "CFC_WebApp/main/work_place_2.py",
"copies": "1",
"size": "2877",
"license": "bsd-3-clause",
"hash": 5704842702332006000,
"line_mean": 38.4109589041,
"line_max": 109,
"alpha_frac": 0.5780326729,
"autogenerated": false,
"ratio": 3.3375870069605567,... |
__author__ = 'Yin'
from pymongo import MongoClient
from home import detect_home,detect_home_from_db
from tripManager import calDistance
from common import Is_weekday, get_static_pnts, most_common, calculate_appearance_rate, Is_date,Is_place
from dateutil import parser
from get_database import get_section_db, get_profil... | {
"repo_name": "sdsingh/e-mission-server",
"path": "CFC_WebApp/main/work_place.py",
"copies": "1",
"size": "4320",
"license": "bsd-3-clause",
"hash": 393963934305706300,
"line_mean": 46.4725274725,
"line_max": 111,
"alpha_frac": 0.6564814815,
"autogenerated": false,
"ratio": 3.4698795180722892,
... |
__author__ = 'Yin'
from pymongo import MongoClient
from home import detect_home
from work_place import detect_daily_work_office
from get_database import get_section_db
from common import Is_date, Is_place
from tripManager import travel_time
from dateutil import parser
from common import parse_time
####################... | {
"repo_name": "sdsingh/e-mission-server",
"path": "CFC_WebApp/main/commute.py",
"copies": "1",
"size": "4992",
"license": "bsd-3-clause",
"hash": 5799135587416603000,
"line_mean": 47.9411764706,
"line_max": 173,
"alpha_frac": 0.5328525641,
"autogenerated": false,
"ratio": 3.9745222929936306,
"c... |
__author__ = 'Yin'
from pymongo import MongoClient
from work_place import detect_daily_work_office
from common import Is_date, get_first_daily_point, Is_place, get_last_daily_point, parse_time
from get_database import get_section_db, get_profile_db,get_worktime_db
from dateutil import parser
from pytz import timezone
... | {
"repo_name": "sdsingh/e-mission-server",
"path": "CFC_WebApp/main/work_time.py",
"copies": "1",
"size": "4189",
"license": "bsd-3-clause",
"hash": -7532045805935860000,
"line_mean": 38.1495327103,
"line_max": 130,
"alpha_frac": 0.5867748866,
"autogenerated": false,
"ratio": 3.1144981412639403,
... |
__author__ = 'Yin'
import logging
from home import detect_home
from zipcode import get_userZipcode
from work_place import detect_work_office, detect_daily_work_office
from get_database import get_section_db,get_profile_db
from pygeocoder import Geocoder
logging.basicConfig(format='%(asctime)s:%(levelname)s:%(message)s'... | {
"repo_name": "sdsingh/e-mission-server",
"path": "CFC_WebApp/main/Profile.py",
"copies": "1",
"size": "1830",
"license": "bsd-3-clause",
"hash": -973345043615560000,
"line_mean": 43.6341463415,
"line_max": 106,
"alpha_frac": 0.618579235,
"autogenerated": false,
"ratio": 3.2795698924731185,
"co... |
__author__ = 'Yin'
# Standard imports
from dateutil import parser
# Our imports
from emission.core.common import Is_date, Is_place, get_mode_share_by_distance, berkeley_area, travel_time
from emission.core.get_database import get_section_db,get_profile_db
def get_Alluser_mode_share_by_distance(flag,start,end):
# ... | {
"repo_name": "yw374cornell/e-mission-server",
"path": "emission/net/api/modeshare.py",
"copies": "2",
"size": "1181",
"license": "bsd-3-clause",
"hash": -5558111820309041000,
"line_mean": 44.4230769231,
"line_max": 144,
"alpha_frac": 0.6096528366,
"autogenerated": false,
"ratio": 2.9823232323232... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.