text stringlengths 0 1.05M | meta dict |
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from files.filetype.AnalysisFactory import AnalysisFactory
from defusedxml import minidom, EntitiesForbidden, DTDForbidden
import files.filetype
class XMLFile(AnalysisFactory):
def buildMetadata(self):
AnalysisFactory.buildMetadata(self)
#print("Doing XMLFile analysis...")
try:
... | {
"repo_name": "plus-provenance/dataidentity",
"path": "files/filetype/XMLFile.py",
"copies": "1",
"size": "1853",
"license": "apache-2.0",
"hash": -3949150332309141500,
"line_mean": 40.1777777778,
"line_max": 92,
"alpha_frac": 0.5752833243,
"autogenerated": false,
"ratio": 4.443645083932854,
"c... |
from files import Document
'''
Reading class
author :Alexis Fossart
date : 06/10/2017
Class used to read document files from the disk
'''
class Reader:
@staticmethod
def read_file(file_path,
ignore_case=True,
ignore_stop_words=True,
stemming=True,
... | {
"repo_name": "Xia0ben/IQPlayground",
"path": "files/reader.py",
"copies": "1",
"size": "1308",
"license": "mit",
"hash": 140162721272055650,
"line_mean": 28.75,
"line_max": 72,
"alpha_frac": 0.4288990826,
"autogenerated": false,
"ratio": 5.404958677685951,
"config_test": false,
"has_no_keywo... |
from .files import File
from .response import Image, OutboundFax
class Outbound(object):
def __init__(self, client):
self.client = client
self.headers = {} ##
def deliver(self, fax_number, files, **kwargs):
"""Submit a fax to a single destination number."""
valid_keys = ['fa... | {
"repo_name": "interfax/interfax-python",
"path": "interfax/outbound.py",
"copies": "1",
"size": "3563",
"license": "mit",
"hash": -3499373160351959600,
"line_mean": 33.931372549,
"line_max": 155,
"alpha_frac": 0.5635700253,
"autogenerated": false,
"ratio": 3.856060606060606,
"config_test": fal... |
from files import filepath
LENGTH = 4
def helper(grid, row, col, row_inc, col_inc, length, acc):
if length == LENGTH:
return acc
if not (
0 <= row + row_inc < len(grid) and
0 <= col + col_inc < len(grid[row + row_inc])
):
return 0
return helper(
grid,
... | {
"repo_name": "mackorone/euler",
"path": "src/011.py",
"copies": "1",
"size": "1102",
"license": "mit",
"hash": 6579405076644728000,
"line_mean": 21.4897959184,
"line_max": 63,
"alpha_frac": 0.4328493648,
"autogenerated": false,
"ratio": 3.58957654723127,
"config_test": false,
"has_no_keyword... |
from files import find
def init(args):
path = args["root"] if "root" in args else "."
(rootdir, file) = find("strings.xml", path)
global root
root = rootdir
global resourceFiles
resourceFiles = {}
def close():
for storyboard, file in resourceFiles.iteritems():
file.write("\n</resources>")
file.close()
d... | {
"repo_name": "saminerve/localizable",
"path": "lib/android.py",
"copies": "1",
"size": "1093",
"license": "unlicense",
"hash": 6969936724673235000,
"line_mean": 29.3611111111,
"line_max": 146,
"alpha_frac": 0.6340347667,
"autogenerated": false,
"ratio": 3.096317280453258,
"config_test": false,... |
from .files import ImageSpecFieldFile
class BoundImageKitMeta(object):
def __init__(self, instance, spec_fields):
self.instance = instance
self.spec_fields = spec_fields
@property
def spec_files(self):
return [getattr(self.instance, n) for n in self.spec_fields]
class ImageKitMe... | {
"repo_name": "pcompassion/django-imagekit",
"path": "imagekit/models/fields/utils.py",
"copies": "1",
"size": "1214",
"license": "bsd-3-clause",
"hash": 5065109262089524000,
"line_mean": 27.9047619048,
"line_max": 68,
"alpha_frac": 0.5955518946,
"autogenerated": false,
"ratio": 4.033222591362127... |
from files import *
from loaders.gene_loader import GeneLoader
from loaders.disease_loader import DiseaseLoader
import csv
import gzip
from mod import MOD
class ZFIN(MOD):
species = "Danio rerio"
loadFile = "ZFIN_0.6.1_10.tar.gz"
@staticmethod
def gene_href(gene_id):
return "http://zfin.org/" ... | {
"repo_name": "alliance-genome/agr_prototype",
"path": "indexer/src/mods/zfin.py",
"copies": "2",
"size": "2125",
"license": "mit",
"hash": 5977716935892531000,
"line_mean": 33.2903225806,
"line_max": 85,
"alpha_frac": 0.5515294118,
"autogenerated": false,
"ratio": 3.309968847352025,
"config_te... |
from files import *
from mods.human import Human
class HomoLogLoader:
def __init__(self, mods):
path = "tmp"
S3File("mod-datadumps", "RefGenomeOrthologs.tar.gz", path).download()
TARFile(path, "RefGenomeOrthologs.tar.gz").extract_all()
self.homolog_data = CSVFile(path + "/" + "RefG... | {
"repo_name": "alliance-genome/agr_prototype",
"path": "indexer/src/loaders/homolog_loader.py",
"copies": "3",
"size": "2794",
"license": "mit",
"hash": 9023584838791477000,
"line_mean": 33.0731707317,
"line_max": 81,
"alpha_frac": 0.4831782391,
"autogenerated": false,
"ratio": 3.5501905972045744... |
from files import *
from mods import MOD
import re
class DiseaseLoader:
def get_data(self, disease_data):
disease_annots = {}
list_to_yield = []
dateProduced = disease_data['metaData']['dateProduced']
dataProvider = disease_data['metaData']['dataProvider']
release = None... | {
"repo_name": "alliance-genome/agr",
"path": "indexer/src/loaders/disease_loader.py",
"copies": "2",
"size": "7052",
"license": "mit",
"hash": 8681586463681025000,
"line_mean": 52.4242424242,
"line_max": 168,
"alpha_frac": 0.5475042541,
"autogenerated": false,
"ratio": 4.483153210425938,
"confi... |
from files import *
from obo_parser import *
import sys
import re
class DoLoader:
@staticmethod
def get_data():
path = "tmp";
S3File("mod-datadumps", "disease-ontology.obo", path).download()
do_data = TXTFile(path + "/disease-ontology.obo").get_data()
do_dataset = {}
c... | {
"repo_name": "nathandunn/agr",
"path": "indexer/src/loaders/do_loader.py",
"copies": "3",
"size": "2742",
"license": "mit",
"hash": 6441421321500631000,
"line_mean": 36.0540540541,
"line_max": 109,
"alpha_frac": 0.4361779723,
"autogenerated": false,
"ratio": 3.9567099567099566,
"config_test": ... |
from files import *
from obo_parser import *
import re
class SoLoader:
@staticmethod
def get_data():
path = "tmp";
S3File("mod-datadumps/data", "so.obo", path).download()
so_data = TXTFile(path + "/so.obo").get_data()
so_dataset = {}
creating_term = None
for ... | {
"repo_name": "nathandunn/agr",
"path": "indexer/src/loaders/so_loader.py",
"copies": "3",
"size": "1938",
"license": "mit",
"hash": 5785517953401799000,
"line_mean": 31.8644067797,
"line_max": 99,
"alpha_frac": 0.4422084623,
"autogenerated": false,
"ratio": 3.995876288659794,
"config_test": fa... |
from Files import *
from Search.Label import Label
import Constants as C
import random
class DataSetBase():
def __init__(self):
self.testingData = []
self.trainingData = []
self.testingLabels = []
self.trainingLabels = []
def getTrainingSize(self):
return len(s... | {
"repo_name": "maeotaku/leaf_recognition_sdk",
"path": "src/Data/DataSetBase.py",
"copies": "1",
"size": "1411",
"license": "mit",
"hash": 8450967407541376000,
"line_mean": 34.3,
"line_max": 128,
"alpha_frac": 0.5620127569,
"autogenerated": false,
"ratio": 4.750841750841751,
"config_test": fals... |
from Files import *
from Search.Label import *
from DataSetBase import DataSetBase
import Constants as C
import random
class DataSet(DataSetBase):
def __init__(self,):
DataSetBase.__init__(self)
self.data = []
self.labels = []
#uses the trainign set to train the kNN
def lo... | {
"repo_name": "maeotaku/leaf_recognition_sdk",
"path": "src/Data/DataSet.py",
"copies": "1",
"size": "4568",
"license": "mit",
"hash": 9073924873748855000,
"line_mean": 33.0970149254,
"line_max": 128,
"alpha_frac": 0.5814360771,
"autogenerated": false,
"ratio": 4.245353159851301,
"config_test":... |
from files import *
import re
class OMIMLoader:
def __init__(self):
path = "tmp";
S3File("mod-datadumps/data", "OMIM_diseases.txt", path).download()
self.omim_data = CSVFile(path + "/OMIM_diseases.txt").get_data()
def get_data(self):
omim_dataset = {}
for row in self... | {
"repo_name": "alliance-genome/agr_prototype",
"path": "indexer/src/loaders/omim_loader.py",
"copies": "3",
"size": "1459",
"license": "mit",
"hash": 8526817784219291000,
"line_mean": 27.6078431373,
"line_max": 74,
"alpha_frac": 0.4372858122,
"autogenerated": false,
"ratio": 3.943243243243243,
... |
from .files import (reader, tokens, nopen, header, is_newer_b, int_types)
import sys
from .pool import pool, pmap
from .fmt import fmt2header
if sys.version_info[0] == 3:
basestring = str
from itertools import groupby as igroupby
from operator import itemgetter
__version__ = "0.4.4"
def groupby(iterable, key=0,... | {
"repo_name": "pombredanne/toolshed",
"path": "toolshed/__init__.py",
"copies": "1",
"size": "1677",
"license": "bsd-2-clause",
"hash": -1201378235484273700,
"line_mean": 26.0483870968,
"line_max": 77,
"alpha_frac": 0.6440071556,
"autogenerated": false,
"ratio": 3.927400468384075,
"config_test"... |
from files.models import FilesystemUser, Group
from django.contrib import admin
class MultiDBModelAdmin(admin.ModelAdmin):
# A handy constant for the name of the alternate database.
using = 'files'
def save_model(self, request, obj, form, change):
# Tell Django to save objects to the 'other' data... | {
"repo_name": "LabAdvComp/tukey_portal",
"path": "tukey/files/admin.py",
"copies": "3",
"size": "1597",
"license": "apache-2.0",
"hash": 6008964547140999000,
"line_mean": 37.9512195122,
"line_max": 125,
"alpha_frac": 0.7138384471,
"autogenerated": false,
"ratio": 3.8668280871670704,
"config_tes... |
from FileState import FileState
from pUtil import tolog
def createFileStates(workDir, jobId, outFiles=None, inFiles=None, logFile=None, ftype="output"):
""" Create the initial file state dictionary """
# file list
if ftype == "output":
files = outFiles
files.append(logFile)
else:
... | {
"repo_name": "PanDAWMS/pilot",
"path": "FileStateClient.py",
"copies": "3",
"size": "2776",
"license": "apache-2.0",
"hash": -1075524648104306800,
"line_mean": 27.0404040404,
"line_max": 102,
"alpha_frac": 0.6833573487,
"autogenerated": false,
"ratio": 3.7513513513513512,
"config_test": false,... |
from FileState import FileState
from pUtil import tolog
def createFileStates(workDir, jobId, outFiles=None, inFiles=None, logFile=None, type="output"):
""" Create the initial file state dictionary """
# file list
if type == "output":
files = outFiles
files.append(logFile)
else:
... | {
"repo_name": "RRCKI/pilot",
"path": "FileStateClient.py",
"copies": "1",
"size": "2391",
"license": "apache-2.0",
"hash": 1239519654186825500,
"line_mean": 27.1294117647,
"line_max": 101,
"alpha_frac": 0.6796319532,
"autogenerated": false,
"ratio": 3.7127329192546585,
"config_test": false,
"... |
from filestore.api import register_handler, deregister_handler
from filestore.retrieve import HandlerBase
from chxtools.pims_readers.eiger import EigerImages
EIGER_MD_DICT = {
'y_pixel_size': 'entry/instrument/detector/y_pixel_size',
'x_pixel_size': 'entry/instrument/detector/x_pixel_size',
'detector_dista... | {
"repo_name": "sameera2004/chxtools",
"path": "chxtools/handlers.py",
"copies": "1",
"size": "1901",
"license": "bsd-3-clause",
"hash": 5479583125262889000,
"line_mean": 33.5636363636,
"line_max": 71,
"alpha_frac": 0.6443976854,
"autogenerated": false,
"ratio": 3.4068100358422937,
"config_test"... |
from FilesystemBase import FilesystemBase
from JumpScale import j
import os
class FilesystemDD(FilesystemBase):
def __init__(self, root, cmd_channel, ftproot, fsmanager):
"""
- (str) ftproot: the root as how the ftp client should use it
- (instance) cmd_channel: the FTPHandler class in... | {
"repo_name": "Jumpscale/jumpscale6_core",
"path": "apps/portalftpgateway/FilesystemDD.py",
"copies": "1",
"size": "6239",
"license": "bsd-2-clause",
"hash": 3602681355641097000,
"line_mean": 30.6700507614,
"line_max": 134,
"alpha_frac": 0.5696425709,
"autogenerated": false,
"ratio": 3.9993589743... |
from FilesystemBase import FilesystemBase
from JumpScale import j
import os
class FilesystemReal(FilesystemBase):
def __init__(self, root, cmd_channel, ftproot, cwd, readonly=False):
"""
- (str) root: the user "real" home directory (e.g. '/home/user')
- (instance) cmd_channel: the FTPH... | {
"repo_name": "Jumpscale/jumpscale6_core",
"path": "apps/portalftpgateway/_archive/FilesystemReal.py",
"copies": "1",
"size": "7630",
"license": "bsd-2-clause",
"hash": -6171074724058265000,
"line_mean": 31.6068376068,
"line_max": 134,
"alpha_frac": 0.5623853211,
"autogenerated": false,
"ratio": ... |
from FilesystemBase import FilesystemBase
from JumpScale import j
import os
class FilesystemReal(FilesystemBase):
def __init__(self, root, cmd_channel, ftproot, readonly=False, name="", ttype="", contentmanager=None):
"""
- (str) root: the real location on the filesystem which is the root of th... | {
"repo_name": "Jumpscale/jumpscale6_core",
"path": "apps/portalftpgateway/FilesystemReal.py",
"copies": "1",
"size": "10626",
"license": "bsd-2-clause",
"hash": -5304322420917019000,
"line_mean": 33.3883495146,
"line_max": 134,
"alpha_frac": 0.5572181442,
"autogenerated": false,
"ratio": 3.979775... |
from .filesystem import *
import sys
# Make a new file system, i.e., format the disk so that it
# is ready for other file system operations.
class MKFS():
def __init__(self, shell):
self.shell = shell
self.file_system = self.shell.file_system
def run(self):
self.file_system.initialize... | {
"repo_name": "LambentLight/bastion",
"path": "bastion/commands.py",
"copies": "1",
"size": "15848",
"license": "mit",
"hash": 3910247713362911000,
"line_mean": 32.3642105263,
"line_max": 139,
"alpha_frac": 0.5925668854,
"autogenerated": false,
"ratio": 3.884313725490196,
"config_test": false,
... |
from .filesystem import sha256, get_appdirs_path
import fiona
import os
import rasterio
import tempfile
import warnings
from rasterio.rio.helpers import coords, write_features
from rasterio.crs import CRS
import numpy as np
import rasterio.features
import rasterio.warp
def check_type(filepath):
"""Determine if ... | {
"repo_name": "cmutel/pandarus",
"path": "pandarus/conversion.py",
"copies": "1",
"size": "9839",
"license": "bsd-3-clause",
"hash": 6075362882392451000,
"line_mean": 37.4296875,
"line_max": 238,
"alpha_frac": 0.5873144948,
"autogenerated": false,
"ratio": 3.9494179044560416,
"config_test": fal... |
from FileTransfer import FtpFileTransfer
import os
import shutil
import prody
import plotly as py
import pandas as pd
import numpy as np
import seaborn as sns
import plotly.plotly as py
import plotly.tools as plotly_tools
import plotly.graph_objs as go
import plotly.offline as offline
import os
import matplotlib.pyp... | {
"repo_name": "dkoes/celpp",
"path": "Visualization.py",
"copies": "1",
"size": "4747",
"license": "mit",
"hash": -227568602118208580,
"line_mean": 28.1226993865,
"line_max": 151,
"alpha_frac": 0.5687802823,
"autogenerated": false,
"ratio": 3.2204884667571236,
"config_test": false,
"has_no_ke... |
from filetransfers.api import prepare_upload
from django.core.urlresolvers import reverse
from django.http import HttpResponseRedirect
from django.shortcuts import render_to_response
from django.template import RequestContext
from django.conf import settings
from .models import UploadModel
from .forms import UploadFor... | {
"repo_name": "klasy/SocialCode_Exercise_Project",
"path": "image_recognition/views.py",
"copies": "1",
"size": "1366",
"license": "bsd-3-clause",
"hash": -5297277965088494000,
"line_mean": 32.3170731707,
"line_max": 74,
"alpha_frac": 0.6808199122,
"autogenerated": false,
"ratio": 4.1646341463414... |
from filetree import FileContainer
## File tree item.
# An recursive structure of FileTrees
class FileTree(object):
## The constructor
#
# @param self The object pointer.
# @pararm filecontainer The file to store in the tree.
def __init__(self, filecontainer):
if not isinstance(filecontain... | {
"repo_name": "oddurk/scriptviewer",
"path": "filetree/FileTree.py",
"copies": "1",
"size": "1931",
"license": "mit",
"hash": 6439773129874890000,
"line_mean": 32.3103448276,
"line_max": 82,
"alpha_frac": 0.6209218022,
"autogenerated": false,
"ratio": 4.310267857142857,
"config_test": false,
... |
from fileupload.models import File
from django.contrib import admin
from django.http import HttpResponse
import tarfile
import shutil
from django.contrib import messages
from django.conf import settings
import os.path, time
def validate_size(files, maxsize):
total_size = 0
if len(files) > 1:
for file i... | {
"repo_name": "extremoburo/django-jquery-file-upload",
"path": "fileupload/admin.py",
"copies": "1",
"size": "2714",
"license": "mit",
"hash": -1131024846281398400,
"line_mean": 30.1954022989,
"line_max": 142,
"alpha_frac": 0.663596168,
"autogenerated": false,
"ratio": 3.921965317919075,
"confi... |
from fileupload.models import Picture, PictureForm
from django.views.generic import CreateView, DeleteView
from django.http import HttpResponse, HttpResponseRedirect
from django.utils import simplejson
from django.core.urlresolvers import reverse
# from django.conf import settings
def response_mimetype(request):
... | {
"repo_name": "carlitosvi/multiple_images",
"path": "fileupload/views.py",
"copies": "6",
"size": "2053",
"license": "mit",
"hash": -703079214848254600,
"line_mean": 30.5846153846,
"line_max": 86,
"alpha_frac": 0.6229907453,
"autogenerated": false,
"ratio": 4.206967213114754,
"config_test": fal... |
from ..file_utils import add_end_docstrings
from .base import PIPELINE_INIT_ARGS, Pipeline
@add_end_docstrings(PIPELINE_INIT_ARGS)
class TextGenerationPipeline(Pipeline):
"""
Language generation pipeline using any :obj:`ModelWithLMHead`. This pipeline predicts the words that will follow a
specified text p... | {
"repo_name": "huggingface/pytorch-transformers",
"path": "src/transformers/pipelines/text_generation.py",
"copies": "2",
"size": "8974",
"license": "apache-2.0",
"hash": -4371784275385012000,
"line_mean": 45.9842931937,
"line_max": 147,
"alpha_frac": 0.5843548028,
"autogenerated": false,
"ratio"... |
from fileutils import CompressedFile
from collections import Counter
from heapq import heapify, heappush, heappop
import queue
from bitstring import BitStream, ReadError
def open(filename, mode):
return CompressedFile(filename, mode, Huffman)
extension = ".hff"
class HuffmanNode():
def __init__(self, left=... | {
"repo_name": "dvlahovski/compresspy",
"path": "compresspy/huffman.py",
"copies": "1",
"size": "4354",
"license": "mit",
"hash": 6353323602524454000,
"line_mean": 29.661971831,
"line_max": 78,
"alpha_frac": 0.5590261828,
"autogenerated": false,
"ratio": 3.958181818181818,
"config_test": false,
... |
from fileutils import CompressedFile
def open(filename, mode):
return CompressedFile(filename, mode, LZW)
extension = ".lzw"
class LZW():
def __init__(self):
self.magic = b'\xba\xca'
#TODO limit dict
def compress(self, data):
dictionary = dict([(bytes([i]), i) for i in range(25... | {
"repo_name": "dvlahovski/compresspy",
"path": "compresspy/lzw.py",
"copies": "1",
"size": "2500",
"license": "mit",
"hash": 5230462333554364000,
"line_mean": 29.487804878,
"line_max": 78,
"alpha_frac": 0.508,
"autogenerated": false,
"ratio": 3.924646781789639,
"config_test": false,
"has_no_k... |
from fileUtils import *
from animation import *
# Race Strings:
# Lanius: "anaerobic"
# ?: "battle"
# Crystal: "crystal"
# Engi: "engi"
# Human: "human"
# Zoltan: "energy"
# Mantis: "mantis"
# Rockman: "rock"
# Slug: "slug"
class InitialCrewMember:
race = ""
name = ""
def __init__(self,f):
... | {
"repo_name": "Tsubashi/iOS-FTL-Save-Game-Editor",
"path": "crew.py",
"copies": "1",
"size": "5702",
"license": "mit",
"hash": 7714340177401657000,
"line_mean": 26.9509803922,
"line_max": 57,
"alpha_frac": 0.6767800772,
"autogenerated": false,
"ratio": 2.8199802176063304,
"config_test": false,
... |
from fileUtils import *
from enum import IntEnum, Enum
class StationDirection(IntEnum):
Down = 0
Right = 1
Up = 2
Left = 3
none = 4
RoomCount = {
"PLAYER_SHIP_HARD": {
"rooms": 17
,"squares": 48
,"doors": 26
}
, "PLAYER_SHIP_CIRCLE": {
"rooms": 16
, "squares": 4... | {
"repo_name": "Tsubashi/iOS-FTL-Save-Game-Editor",
"path": "rooms.py",
"copies": "1",
"size": "3185",
"license": "mit",
"hash": -3095637165540701700,
"line_mean": 19.6818181818,
"line_max": 49,
"alpha_frac": 0.6113029827,
"autogenerated": false,
"ratio": 2.9600371747211898,
"config_test": false... |
from fileUtils import *
from pprintpp import pprint as pp
class SystemList:
shields = 0
engines = 0
oxygen = 0
weapons = 0
drones = 0
medbay = 0
pilot = 0
sensors = 0
doors = 0
teleporter = 0
cloaking = 0
artillery = 0
battery = 0
cloneba... | {
"repo_name": "Tsubashi/iOS-FTL-Save-Game-Editor",
"path": "systems.py",
"copies": "1",
"size": "6587",
"license": "mit",
"hash": -824795336446681200,
"line_mean": 24.4324324324,
"line_max": 80,
"alpha_frac": 0.6476392895,
"autogenerated": false,
"ratio": 3.0132662397072276,
"config_test": fals... |
from .fileview import FileView, FileViewModel
import csv
from .model import Model
class CSVView(FileView):
def __init__(self, filestream, delimiter=';', lineterminator='\n'):
super(CSVView, self).__init__(filestream=filestream)
self.delimiter = delimiter
self.lineterminator = lineterminato... | {
"repo_name": "pdyban/dicombrowser",
"path": "dicomviewer/csvview.py",
"copies": "1",
"size": "1226",
"license": "apache-2.0",
"hash": 3377948710712610300,
"line_mean": 29.65,
"line_max": 88,
"alpha_frac": 0.5929853181,
"autogenerated": false,
"ratio": 4.2717770034843205,
"config_test": false,
... |
from .filings import Filing
from django.db import models
from django.template.defaultfilters import slugify
from calaccess_campaign_browser.utils.models import AllCapsNameMixin
import time
class Filer(AllCapsNameMixin):
"""
An entity that files campaign finance disclosure documents.
That includes candida... | {
"repo_name": "california-civic-data-coalition/django-calaccess-campaign-browser",
"path": "calaccess_campaign_browser/models/filers.py",
"copies": "3",
"size": "8245",
"license": "mit",
"hash": -7913295579061081000,
"line_mean": 29.0912408759,
"line_max": 79,
"alpha_frac": 0.5614311704,
"autogener... |
from filterable import Filterable
from functools import reduce
import numpy
class HasDocuments:
def __init__(self):
self.seen_documents = {}
self.viewed_documents = {}
self.marked_relevant_documents = {}
def add_seen_documents(self, *documents):
for document in documents:
self.seen_documen... | {
"repo_name": "fire-uta/iiix-data-parser",
"path": "has_documents.py",
"copies": "1",
"size": "7208",
"license": "mit",
"hash": -6978143433148660000,
"line_mean": 46.4210526316,
"line_max": 140,
"alpha_frac": 0.7407047725,
"autogenerated": false,
"ratio": 3.707818930041152,
"config_test": false... |
from filter import FilterException
from common import PluginType
from yapsy.IPlugin import IPlugin
import logging
class ContentLengthFilter(IPlugin):
category = PluginType.HEADER
id = "contentLength"
def __init__(self):
self.__log = logging.getLogger(__name__)
self.__conf = None
def... | {
"repo_name": "eghuro/crawlcheck",
"path": "src/checker/plugin/headers/contentLength.py",
"copies": "1",
"size": "1238",
"license": "mit",
"hash": 5318421642051629000,
"line_mean": 33.3888888889,
"line_max": 76,
"alpha_frac": 0.52180937,
"autogenerated": false,
"ratio": 4.991935483870968,
"conf... |
from filter import FilterException
from common import PluginType
from yapsy.IPlugin import IPlugin
import logging
class ExpectedType(IPlugin):
category = PluginType.HEADER
id = "expectedType"
def __init__(self):
self.__log = logging.getLogger(__name__)
self.__conf = None
self.__j... | {
"repo_name": "eghuro/crawlcheck",
"path": "src/checker/plugin/headers/expectedType.py",
"copies": "1",
"size": "1148",
"license": "mit",
"hash": -8890835037616451000,
"line_mean": 32.7647058824,
"line_max": 76,
"alpha_frac": 0.5540069686,
"autogenerated": false,
"ratio": 4.927038626609442,
"co... |
from filter import FilterException, Reschedule
from common import PluginType
from yapsy.IPlugin import IPlugin
import reppy
from reppy.robots import Robots
from reppy.cache import RobotsCache
from reppy.exceptions import ReppyException
from yapsy.IPlugin import IPlugin
import logging
import time
logging.getLogger("rep... | {
"repo_name": "eghuro/crawlcheck",
"path": "src/checker/plugin/filters/robots.py",
"copies": "1",
"size": "4568",
"license": "mit",
"hash": 8170928433341852000,
"line_mean": 36.1382113821,
"line_max": 79,
"alpha_frac": 0.5135726795,
"autogenerated": false,
"ratio": 4.1678832116788325,
"config_t... |
from ..filter import Filter
from scipy.ndimage.fourier import fourier_gaussian
from .base_microstructure_generator import _BaseMicrostructureGenerator
import numpy as np
class MicrostructureGenerator(_BaseMicrostructureGenerator):
"""
Generates n_samples number of a periodic random microstructures
with do... | {
"repo_name": "davidbrough1/pymks",
"path": "pymks/datasets/microstructure_generator.py",
"copies": "1",
"size": "3230",
"license": "mit",
"hash": 1699219593760080000,
"line_mean": 40.4102564103,
"line_max": 75,
"alpha_frac": 0.5334365325,
"autogenerated": false,
"ratio": 3.683010262257697,
"co... |
from .filter import Filter
import re
class PatternParser(object):
def __init__(self, tokens):
self.tokens = tokens
self.pos = 0
def parse_filter(self):
last_operator = Filter.__or__
result = None
negated = False
while self.has_tokens():
token = sel... | {
"repo_name": "pcapriotti/pledger",
"path": "pledger/pattern.py",
"copies": "1",
"size": "1493",
"license": "mit",
"hash": -7156243684149427000,
"line_mean": 26.6481481481,
"line_max": 77,
"alpha_frac": 0.4748827863,
"autogenerated": false,
"ratio": 4.456716417910448,
"config_test": false,
"h... |
from filter import Filter, Position
DEFAULT_FONT = '/usr/share/fonts/truetype/ttf-dejavu/DejaVuSans-Bold.ttf'
DEFAULT_FONT_COLOR = 'white'
DEFAULT_FONT_SIZE = '20'
class DrawBox(Filter):
name = 'drawbox'
args = ['w', 'h', 'color', 't']
def __init__(self, position=None, **kwargs):
kwargs.setdef... | {
"repo_name": "Remiii/remiii-ffmpeg-filters",
"path": "filters.py",
"copies": "1",
"size": "1167",
"license": "mit",
"hash": -464516113240708860,
"line_mean": 26.7857142857,
"line_max": 75,
"alpha_frac": 0.6118251928,
"autogenerated": false,
"ratio": 3.402332361516035,
"config_test": false,
"... |
from .filter import *
from collections import OrderedDict
from ..content.types.green_power_projects import GreenPowerProject
class GenericFilterSet(filters.FilterSet):
"""
The genric Filter form handling the filtering for all views: search,
content types and sustainability topic. The browse view might ext... | {
"repo_name": "AASHE/hub",
"path": "hub/apps/browse/filterset.py",
"copies": "1",
"size": "5931",
"license": "mit",
"hash": -5250894107393195000,
"line_mean": 34.0946745562,
"line_max": 79,
"alpha_frac": 0.712696004,
"autogenerated": false,
"ratio": 4.406389301634473,
"config_test": false,
"h... |
from filtering.anisotropic import *
from rivuletpy.utils.io import *
import matplotlib.pyplot as plt
from scipy import io as sio
try:
from skimage import filters
except ImportError:
from skimage import filter as filters
mat = sio.loadmat('tests/data/very-small-oof.mat', )
img = mat['img']
ostu_img = filters... | {
"repo_name": "RivuletStudio/rivuletpy",
"path": "tests/testoof.py",
"copies": "1",
"size": "2584",
"license": "bsd-3-clause",
"hash": -4805536274221730000,
"line_mean": 23.8461538462,
"line_max": 108,
"alpha_frac": 0.7174922601,
"autogenerated": false,
"ratio": 2.248912097476066,
"config_test"... |
from filtering.anisotropic import *
from rivuletpy.utils.io import *
import matplotlib.pyplot as plt
from scipy import io as sio
try:
from skimage import filters
except ImportError:
from skimage import filter as filters
# plot the gaussian kernel
nsig = 5
nmu = 5
kerlen = 101
kr = (kerlen - 1) / 2
X, Y, Z =... | {
"repo_name": "RivuletStudio/rivuletpy",
"path": "tests/testbg.py",
"copies": "1",
"size": "1287",
"license": "bsd-3-clause",
"hash": -2571282602189926400,
"line_mean": 25.2653061224,
"line_max": 59,
"alpha_frac": 0.567987568,
"autogenerated": false,
"ratio": 2.7209302325581395,
"config_test": ... |
from filterpy.kalman import KalmanFilter
from CO2simulation import CO2simulation
import common
import numpy as np
import visualizeCO2 as vco2
import matplotlib.pyplot as plt
from HiKF import HiKF
from numpy import dot, zeros, eye, isscalar
def CO2_kf_filter(CO2, param):
"""filter matrices initialization for KF"""
tr... | {
"repo_name": "judithyueli/pyFKF",
"path": "runCO2simulation.py",
"copies": "1",
"size": "3476",
"license": "mit",
"hash": 2366489444067328000,
"line_mean": 22.8150684932,
"line_max": 68,
"alpha_frac": 0.6530494822,
"autogenerated": false,
"ratio": 2.2425806451612904,
"config_test": false,
"h... |
from filterpy.kalman import UnscentedKalmanFilter as UKF
from filterpy.kalman import MerweScaledSigmaPoints
import numpy as np
observe_file = 'data02_observe.txt';
true_file = 'data02_true.txt'
fp = open(observe_file,'r')
observe_data = []
for line in fp.readlines():
line_data = line.split('\t')
line_data = line_... | {
"repo_name": "GeniusLight/KalmanGui",
"path": "filter/kalman/tests/test02_verification.py",
"copies": "1",
"size": "1846",
"license": "mit",
"hash": -3040409709235878000,
"line_mean": 26.9848484848,
"line_max": 65,
"alpha_frac": 0.6473456121,
"autogenerated": false,
"ratio": 2.221419975932611,
... |
from filters.base import BaseEntry, BaseListing, NotFoundError
import re
class VebEntry(BaseEntry):
def applies(self, soup):
return soup.find(class_='post-title') and soup.find(class_='post-content')
def extract_title(self, soup):
post = soup.find(class_='post-title')
title_link = post.find('a')
... | {
"repo_name": "kchodorow/blook",
"path": "filters/veb.py",
"copies": "1",
"size": "1217",
"license": "apache-2.0",
"hash": -6008296204676240000,
"line_mean": 28.6829268293,
"line_max": 78,
"alpha_frac": 0.6540673788,
"autogenerated": false,
"ratio": 3.4089635854341735,
"config_test": false,
"... |
from filters.base import BaseEntry, BaseListing, NotFoundError
import re
PREVIOUS_RE = re.compile('Previous ')
OLDER_RE = re.compile('Older ')
CONTINUE_RE = re.compile('continue reading')
NEXT_RE = re.compile('Next ')
class SiatEntry(BaseEntry):
def applies(self, soup):
return soup.find(class_='post')
def e... | {
"repo_name": "kchodorow/blook",
"path": "filters/siat.py",
"copies": "1",
"size": "3892",
"license": "apache-2.0",
"hash": 9221763687578183000,
"line_mean": 27.4087591241,
"line_max": 78,
"alpha_frac": 0.664696814,
"autogenerated": false,
"ratio": 3.3872932985204525,
"config_test": false,
"h... |
from filters.dummy_sink import DummySink
from filters.dummy_source import DummySource
from filters.logger_sink import LoggerSink
class TestGraphBuilder:
"""
A fake graph builder used only for testing
"""
def __init__(self):
self._filters = {}
source_filter = DummySource('dummy_source')... | {
"repo_name": "koolspin/rosetta",
"path": "test/test_graph_builder.py",
"copies": "1",
"size": "1319",
"license": "mit",
"hash": 2285534546059623400,
"line_mean": 36.6857142857,
"line_max": 66,
"alpha_frac": 0.639878696,
"autogenerated": false,
"ratio": 3.7685714285714287,
"config_test": false,... |
from filters.Filter import Filter, Settings, is_line_separate_record
class ContentFilter(Filter):
def apply(self, source):
"""
Performs filtration logic
@rtype : iter
@param source: iterable of strings, that represents content for filtration
@return: iterable of strings, re... | {
"repo_name": "EvilKhaosKat/simple-python-log-analyzer",
"path": "filters/ContentFilter.py",
"copies": "1",
"size": "1851",
"license": "apache-2.0",
"hash": 4840031767185237000,
"line_mean": 30.9137931034,
"line_max": 83,
"alpha_frac": 0.5775256618,
"autogenerated": false,
"ratio": 4.883905013192... |
from filters import Filter
class Node(list):
# get attributes of String class
_str_dir = dir('')
def __init__(self, *args):
self._before, self._after = [], []
self._text, self._type = '', ''
super(Node, self).__init__(*args)
def type(self, _type=None):
if _type is None... | {
"repo_name": "diNard/Saw",
"path": "saw/node.py",
"copies": "1",
"size": "2887",
"license": "mit",
"hash": 7938294320614748000,
"line_mean": 27.5841584158,
"line_max": 96,
"alpha_frac": 0.524419813,
"autogenerated": false,
"ratio": 4.077683615819209,
"config_test": false,
"has_no_keywords": ... |
from .filters import FILTERS as DEFAULT_FILTERS # noqa: F401
from .tests import TESTS as DEFAULT_TESTS # noqa: F401
from .utils import Cycler
from .utils import generate_lorem_ipsum
from .utils import Joiner
from .utils import Namespace
# defaults for the parser / lexer
BLOCK_START_STRING = "{%"
BLOCK_END_STRING = "... | {
"repo_name": "pallets/jinja2",
"path": "src/jinja2/defaults.py",
"copies": "1",
"size": "1065",
"license": "bsd-3-clause",
"hash": 1836582665250465300,
"line_mean": 24.3571428571,
"line_max": 61,
"alpha_frac": 0.6816901408,
"autogenerated": false,
"ratio": 3.1415929203539825,
"config_test": fa... |
from filters import Filters
from pixels import PIXELS
from chunks import create_ihdr_data, create_chunk, create_image_data
def filterer(scanlines, bpp):
original = [list(scanline.get('bytes')) for scanline in scanlines]
filtered = list(original)
def filter_byte(filter_type, current_byte, y, x):
ab... | {
"repo_name": "adregan/pnger",
"path": "encoder.py",
"copies": "1",
"size": "1670",
"license": "mit",
"hash": -421234745565364100,
"line_mean": 34.5319148936,
"line_max": 75,
"alpha_frac": 0.6035928144,
"autogenerated": false,
"ratio": 3.6784140969162995,
"config_test": false,
"has_no_keyword... |
from filters import KeywordFilter
from django.db.models import Q
class PrefixIDFilter(KeywordFilter):
"""
A string and an int, separated by a delimiter.
Values are split by the right-most occurrence of delimiter and ANDed
across prefix and ID. Must match exactly the prefix or the ID, or both, if
... | {
"repo_name": "peterbe/moztrap",
"path": "moztrap/view/lists/cases.py",
"copies": "5",
"size": "1818",
"license": "bsd-2-clause",
"hash": -3364542181802391600,
"line_mean": 30.3448275862,
"line_max": 79,
"alpha_frac": 0.5869086909,
"autogenerated": false,
"ratio": 4.488888888888889,
"config_tes... |
from filters import label
import numpy as np
from track_utils import prepare_costmat
from _munkres import munkres
from collections import Counter
def labels_map(lb0, lb1):
"""
lb0 and lb1 should have objects in the same locations but different labels.
Objects in lb0 can be smaller than lb1.
"""
lb... | {
"repo_name": "braysia/CellTK",
"path": "celltk/utils/labels_handling.py",
"copies": "1",
"size": "3179",
"license": "mit",
"hash": 1535220022291539500,
"line_mean": 29.8640776699,
"line_max": 96,
"alpha_frac": 0.6030198176,
"autogenerated": false,
"ratio": 3.185370741482966,
"config_test": fal... |
from .filters import MSAnd
from .instructions import SY
from .layer import DisplayPriority
class Lookup:
def __init__(self, id='', table=None, display=None, comment='',
instruction=None, rules=None,
display_priority=DisplayPriority.NotSet):
if rules is None:
r... | {
"repo_name": "LarsSchy/SMAC-M",
"path": "chart-installation/generate_map_files/mapgen/lookup.py",
"copies": "1",
"size": "3245",
"license": "mit",
"hash": -274443140794746180,
"line_mean": 29.9047619048,
"line_max": 78,
"alpha_frac": 0.5395993837,
"autogenerated": false,
"ratio": 4.5132127955493... |
from ...filters import sass
from ...utils import get_media_dirs
from django.conf import settings
from django.core.management.base import NoArgsCommand
from subprocess import Popen, PIPE
import os
import shutil
import sys
import __main__
_frameworks_dir = 'imported-sass-frameworks'
if hasattr(__main__, '__file__'):
... | {
"repo_name": "potatolondon/django-mediagenerator",
"path": "mediagenerator/management/commands/importsassframeworks.py",
"copies": "1",
"size": "2986",
"license": "bsd-3-clause",
"hash": 5481462669649623000,
"line_mean": 38.2894736842,
"line_max": 79,
"alpha_frac": 0.5559276624,
"autogenerated": f... |
from ...filters import sass
from ...utils import get_media_dirs
from django.conf import settings
from django.core.management.base import NoArgsCommand
from subprocess import Popen, PIPE
import os
import shutil
import sys
import __main__
_frameworks_dir = 'imported-sass-frameworks'
if hasattr(__main__, '__fi... | {
"repo_name": "brunogamacatao/portalsaladeaula",
"path": "mediagenerator/management/commands/importsassframeworks.py",
"copies": "2",
"size": "2956",
"license": "bsd-3-clause",
"hash": 3389288306528204000,
"line_mean": 38.4931506849,
"line_max": 79,
"alpha_frac": 0.550744249,
"autogenerated": false... |
from filters import val_ago, human_date
from flask import render_template, Flask
import datetime as dt
app = Flask(__name__)
def top_articles():
articles = [
{"title": "Google", "score": 150, "link": "http://google.com"},
{"title": "Yahoo", "score": 75, "link": "http://yahoo.com"},
{"title... | {
"repo_name": "datastax/cstar_perf",
"path": "frontend/cstar_perf/frontend/server/simple.py",
"copies": "2",
"size": "1208",
"license": "apache-2.0",
"hash": -211840468877939170,
"line_mean": 25.2608695652,
"line_max": 71,
"alpha_frac": 0.5836092715,
"autogenerated": false,
"ratio": 3.48126801152... |
from ..filterware import Filter
from ..items import PageItem
from . import ALLOWED_FILE_TYPES, OSPSpider
class CustomSpider(OSPSpider):
@classmethod
def from_crawler(cls, crawler, *args, **kwargs):
spider = super().from_crawler(crawler, *args, **kwargs)
spider.allowed_file_types = ALLOWED_FIL... | {
"repo_name": "opensyllabus/osp-scraper",
"path": "osp_scraper/spiders/CustomSpider.py",
"copies": "1",
"size": "2183",
"license": "apache-2.0",
"hash": -4923975613628877000,
"line_mean": 31.1029411765,
"line_max": 80,
"alpha_frac": 0.6074209803,
"autogenerated": false,
"ratio": 4.605485232067511... |
from fim import fpgrowth
from src.association_rules.association_rule import AssociationRule
class FPGrowth:
def __init__(self, transactions, support_threshold, min_set_size, max_set_size):
self.transactions = transactions
self.support_threshold = support_threshold
self.min_set_size = min_s... | {
"repo_name": "cuong19/AssociationRulesMiner",
"path": "src/association_rules/fpgrowth.py",
"copies": "1",
"size": "1357",
"license": "mit",
"hash": 5831413287126769000,
"line_mean": 37.7714285714,
"line_max": 93,
"alpha_frac": 0.5696389094,
"autogenerated": false,
"ratio": 3.5523560209424083,
... |
from fimiwal import db
import datetime
class Clients(db.Model):
"""
Database Model for Clients
"""
id = db.Column(db.Integer, primary_key=True)
email = db.Column(db.String(64))
date_added = db.Column(db.String(20))
ident = db.Column(db.String(50))
ip = db.Column(db.String(20))
os =... | {
"repo_name": "thatarchguy/Fimiwal",
"path": "fimiwal/models.py",
"copies": "1",
"size": "1897",
"license": "mit",
"hash": -4304885606426223000,
"line_mean": 27.3134328358,
"line_max": 76,
"alpha_frac": 0.6120189773,
"autogenerated": false,
"ratio": 3.2650602409638556,
"config_test": false,
"... |
from finance import db
from finance.models.account import Account
class Transaction(db.Model):
"""Transaction
Record of the transaction
"""
transaction_id = db.Column(db.Integer, primary_key=True)
account_debit_id = db.Column(db.Integer,
db.ForeignKey('account.ac... | {
"repo_name": "reinbach/finance",
"path": "api/finance/models/transaction.py",
"copies": "1",
"size": "2681",
"license": "bsd-3-clause",
"hash": 5903211069185538000,
"line_mean": 33.8181818182,
"line_max": 72,
"alpha_frac": 0.5374860127,
"autogenerated": false,
"ratio": 4.5363790186125215,
"con... |
from finance import db
from finance.models.account_type import AccountType
class Account(db.Model):
"""Account
The accounts all transactions happen in
eg: Income, expense, assets and liabilities
"""
account_id = db.Column(db.Integer, primary_key=True)
name = db.Column(db.String(50), unique=T... | {
"repo_name": "reinbach/finance",
"path": "api/finance/models/account.py",
"copies": "1",
"size": "2508",
"license": "bsd-3-clause",
"hash": 593465693134771600,
"line_mean": 31.5714285714,
"line_max": 78,
"alpha_frac": 0.5669856459,
"autogenerated": false,
"ratio": 4.229342327150085,
"config_te... |
from finance.settings import *
"""
Django tests are run with DEBUG=False by default
This screws up django debug toolbar middleware if we run with dev settings,
and screws up OPBEAT if we run with prod settings
Here I use settings without opbeat and django debug toolbar
"""
INSTALLED_APPS = (
'django.contrib.adm... | {
"repo_name": "trimailov/finance",
"path": "finance/settings/testing.py",
"copies": "1",
"size": "1216",
"license": "mit",
"hash": -5914977781656612000,
"line_mean": 30.1794871795,
"line_max": 75,
"alpha_frac": 0.7467105263,
"autogenerated": false,
"ratio": 3.8849840255591053,
"config_test": fa... |
from finance.settings import SIN_SUELDO
from efinance.models import Sueldo, Empleado
from datetime import date
import pdb
def generar_sueldos():
'''
se podria pasar como parametro un "payment date" para generar sueldos de
meses determinados.
devuelve true si ya se habian generado y false sino.
'... | {
"repo_name": "mfalcon/edujango",
"path": "efinance/utils.py",
"copies": "1",
"size": "1830",
"license": "apache-2.0",
"hash": -5709952089064563000,
"line_mean": 30.0169491525,
"line_max": 89,
"alpha_frac": 0.6054644809,
"autogenerated": false,
"ratio": 2.9140127388535033,
"config_test": false,... |
from financial_data_utils.libor.globalrates.service import Service
from financial_data_utils.libor.globalrates.parser import ParserHeaders, ParserValues
from collections import namedtuple
import datetime
class Libor :
Libor = namedtuple("Libor", ['date', 'overnight', 'week', 'month', 'month2', 'month3', 'month6'... | {
"repo_name": "creative-quant/financial-data-utils",
"path": "financial_data_utils/libor/libor.py",
"copies": "1",
"size": "1172",
"license": "apache-2.0",
"hash": -5947925402078549000,
"line_mean": 35.625,
"line_max": 113,
"alpha_frac": 0.5537542662,
"autogenerated": false,
"ratio": 3.6855345911... |
from financial_data_utils.options.yahoo.service import Service
import xml.etree.ElementTree as ET
import datetime
from string import Template
import math
from collections import namedtuple
LastTrade = namedtuple("LastTrade", ['symbol', 'close', 'datetime'])
Option = namedtuple("Option", ['symbol', 'strikePrice', 'last... | {
"repo_name": "creative-quant/financial-data-utils",
"path": "financial_data_utils/options/yahoo/finance.py",
"copies": "1",
"size": "2448",
"license": "apache-2.0",
"hash": 2044644361026216700,
"line_mean": 39.131147541,
"line_max": 183,
"alpha_frac": 0.5890522876,
"autogenerated": false,
"ratio... |
from finat.point_set import PointSet, UnknownPointSet
from functools import reduce
import numpy
import FIAT
import gem
from gem.interpreter import evaluate
from gem.utils import cached_property
from finat.finiteelementbase import FiniteElementBase
from finat.quadrature import make_quadrature, AbstractQuadratureRule... | {
"repo_name": "FInAT/FInAT",
"path": "finat/quadrature_element.py",
"copies": "1",
"size": "4789",
"license": "mit",
"hash": -7212250305334769000,
"line_mean": 35.2803030303,
"line_max": 93,
"alpha_frac": 0.654207559,
"autogenerated": false,
"ratio": 4.1535125758889855,
"config_test": false,
... |
from finch import Finch
from random import randint
from time import sleep
from threading import Timer
import threading
import time
import os
class Lighting:
def __init__(self):
self.max_deviation = 0.009
## Read data from the file : calib.txt ##
self.max_left = 0
self.max_right = 0
... | {
"repo_name": "Amanda1223/Finch",
"path": "_redo.py",
"copies": "1",
"size": "12941",
"license": "mit",
"hash": -8634331490846066000,
"line_mean": 33.0552631579,
"line_max": 129,
"alpha_frac": 0.5364345877,
"autogenerated": false,
"ratio": 3.7208165612420934,
"config_test": false,
"has_no_key... |
from finch import Finch
from time import sleep
f = Finch()
zAccel = f.acceleration()[2]
i_temp = f.temperature();
i_l_light, i_r_light = f.light();
alpha_light = 0.20
alpha2_light = 0.25
alpha_temp = 0.65
while zAccel > -0.7:
left_obstacle, right_obstacle = f.obstacle()
l_light, r_light = f.light()
temp = ... | {
"repo_name": "netfree/adoptabot",
"path": "server.py",
"copies": "1",
"size": "1170",
"license": "mit",
"hash": -6740469626882116000,
"line_mean": 15.9565217391,
"line_max": 78,
"alpha_frac": 0.5794871795,
"autogenerated": false,
"ratio": 1.9864176570458405,
"config_test": false,
"has_no_key... |
from finch import Finch
from time import sleep
finch = Finch()
class OurFinch: # Everything the finch is supposed to do!
# Initialising
def init(self):
finch.led(6, 6, 6)
finch.buzzer(1.0, 400)
sleep(0.1)
finch.buzzer(1.0, 600)
sleep(0.1)
finch.buzzer(1.0, 800)
sleep(0.1)
... | {
"repo_name": "Spiderfav/KonamiKoders",
"path": "KonamiKoders.py",
"copies": "1",
"size": "5925",
"license": "mit",
"hash": 8996740298172677000,
"line_mean": 31.4745762712,
"line_max": 89,
"alpha_frac": 0.5383966245,
"autogenerated": false,
"ratio": 3.381849315068493,
"config_test": false,
"h... |
from findARestaurant import findARestaurant
from models import Base, Restaurant
from flask import Flask, jsonify, request
from sqlalchemy.ext.declarative import declarative_base
from sqlalchemy.orm import relationship, sessionmaker
from sqlalchemy import create_engine
import sys
import codecs
sys.stdout = codecs.getwr... | {
"repo_name": "tuanvu216/udacity-course",
"path": "designing-restful-apis/Lesson_3/06_Adding Features to your Mashup/Solution Code/views.py",
"copies": "1",
"size": "2543",
"license": "mit",
"hash": 4459025618852885500,
"line_mean": 30.7875,
"line_max": 184,
"alpha_frac": 0.7070389304,
"autogenerat... |
from findatapy.market import MarketDataGenerator, Market, MarketDataRequest
def generate_market_data_for_tests():
# generate daily S&P500 data from Quandl
md_request = MarketDataRequest(start_date='01 Jan 2001', finish_date='01 Dec 2008',
tickers=['S&P500'], vendor_tickers=[... | {
"repo_name": "cuemacro/findatapy",
"path": "tests/generate_market_data_for_tests.py",
"copies": "1",
"size": "1067",
"license": "apache-2.0",
"hash": -5750704961983626000,
"line_mean": 40.0769230769,
"line_max": 113,
"alpha_frac": 0.6091846298,
"autogenerated": false,
"ratio": 3.60472972972973,
... |
from findatapy.market import Market, MarketDataRequest, MarketDataGenerator, IOEngine
market = Market(market_data_generator=MarketDataGenerator())
# in the config file, we can use keywords 'open', 'high', 'low', 'close' and 'volume' for Yahoo and Google finance data
# download equities data from Yahoo
md_request = M... | {
"repo_name": "kalaytan/findatapy",
"path": "findatapy/examples/arctic_example.py",
"copies": "1",
"size": "1151",
"license": "apache-2.0",
"hash": -4121249840252287000,
"line_mean": 41.6296296296,
"line_max": 119,
"alpha_frac": 0.6889661164,
"autogenerated": false,
"ratio": 3.162087912087912,
... |
from findatapy.market import Market, MarketDataRequest, MarketDataGenerator
market = Market(market_data_generator=MarketDataGenerator())
# choose run_example = 0 for everything
# run_example = 1 - download implied volatility data from Bloomberg for FX
# run_example = 2 - download implied volatility data (not in confi... | {
"repo_name": "kalaytan/findatapy",
"path": "findatapy/examples/fxvoldata_example.py",
"copies": "1",
"size": "2477",
"license": "apache-2.0",
"hash": 5036256424591114000,
"line_mean": 48.56,
"line_max": 117,
"alpha_frac": 0.6770286637,
"autogenerated": false,
"ratio": 3.724812030075188,
"confi... |
from findatapy.market import Market, MarketDataRequest, MarketDataGenerator
market = Market(market_data_generator=MarketDataGenerator())
# download event data from Bloomberg
# we have to use the special category "events" keyword for economic data events
# so findatapy can correctly identify them (given the underlying... | {
"repo_name": "kalaytan/findatapy",
"path": "findatapy/examples/eventsdata_example.py",
"copies": "1",
"size": "2457",
"license": "apache-2.0",
"hash": 8865889844903458000,
"line_mean": 50.2083333333,
"line_max": 140,
"alpha_frac": 0.6027676028,
"autogenerated": false,
"ratio": 4.041118421052632,... |
from findatapy.market import Market, MarketDataRequest, MarketDataGenerator
market = Market(market_data_generator=MarketDataGenerator())
# get the first release for GDP and also print the release date of that
md_request = MarketDataRequest(
start_date="01 Jun 2000", ... | {
"repo_name": "kalaytan/findatapy",
"path": "findatapy/examples/alfred_example.py",
"copies": "1",
"size": "2993",
"license": "apache-2.0",
"hash": -9150692333031893000,
"line_mean": 50.6034482759,
"line_max": 128,
"alpha_frac": 0.5212161711,
"autogenerated": false,
"ratio": 4.395007342143906,
... |
from findatapy.market import Market, MarketDataRequest, MarketDataGenerator
market = Market(market_data_generator=MarketDataGenerator())
# in the config file, we can use keywords 'open', 'high', 'low', 'close' and 'volume' for Yahoo and Google finance data
# download equities data from Yahoo
md_request = MarketDataR... | {
"repo_name": "kalaytan/findatapy",
"path": "findatapy/examples/equitiesdata_example.py",
"copies": "1",
"size": "1246",
"license": "apache-2.0",
"hash": 6700150648431021000,
"line_mean": 39.2258064516,
"line_max": 119,
"alpha_frac": 0.650882825,
"autogenerated": false,
"ratio": 3.432506887052341... |
from findatapy.timeseries import Calculations
from findatapy.util import LoggerManager
from findatapy.market import MarketDataRequest
import pandas
#######################################################################################################################
class FXCLSVolume(object):
def __init__(self,... | {
"repo_name": "cuemacro/findatapy",
"path": "findatapy/market/fxclsvolume.py",
"copies": "1",
"size": "2932",
"license": "apache-2.0",
"hash": -7162634822033342000,
"line_mean": 29.8736842105,
"line_max": 138,
"alpha_frac": 0.5078444748,
"autogenerated": false,
"ratio": 3.9891156462585036,
"con... |
from findCollisions import countCollisionsInList
data = []
def getData(cvc=False,cv=False):
inputFile = 'output_shortlist.txt'
data = []
with open(inputFile,'r') as f1:
for line in f1:
word = line.split(',')[0]
if cvc:
word = justTwoInitSylls_CVC(word)
... | {
"repo_name": "hchiam/cognateLanguage",
"path": "test_compare_CVC_CV.py",
"copies": "1",
"size": "1852",
"license": "mit",
"hash": 3549731714069737000,
"line_mean": 29.3606557377,
"line_max": 88,
"alpha_frac": 0.5847732181,
"autogenerated": false,
"ratio": 3.4487895716945998,
"config_test": fal... |
from finddirmakeifno import finddirmakeifno
from getfilecontents import readdatfile
from filemakeifno import filemakeifno
from ast import literal_eval
from os import getpid, system
from sys import exit
from re import search
def apppid():
return getpid()
def sessionsdatintegrety(contents):
print('This is c... | {
"repo_name": "Triballian/stakenannyb",
"path": "stakenannyb/isappsessioncurrentifnodo.py",
"copies": "1",
"size": "2180",
"license": "mit",
"hash": 2965737240173257700,
"line_mean": 32.5538461538,
"line_max": 114,
"alpha_frac": 0.6536697248,
"autogenerated": false,
"ratio": 3.745704467353952,
... |
from findDirsOfInterest import *
import re
import argparse
import matplotlib.pyplot as plt
import numpy as np
import scipy
from sklearn import metrics
def genereateHeatMap(localArgs):
inputFile = open(localArgs.input, 'r')
data = np.zeros((26,26))
header = inputFile.readline()
for line in inputFile:
... | {
"repo_name": "Mbornoe/PR-curves-with-heatmap-matlab",
"path": "generateHeatmap.py",
"copies": "1",
"size": "2967",
"license": "apache-2.0",
"hash": -1600570316592019200,
"line_mean": 35.1829268293,
"line_max": 232,
"alpha_frac": 0.6181327941,
"autogenerated": false,
"ratio": 3.2857142857142856,
... |
from finder import app
from flask.ext import sqlalchemy
db = sqlalchemy.SQLAlchemy(app)
class Card(db.Model):
__tablename__ = 'cards'
id = db.Column(db.Integer, primary_key=True)
multiverse_id = db.Column(db.Integer, nullable=False)
name = db.Column(db.Text, nullable=False)
cost = db.Column(db.Tex... | {
"repo_name": "numberoverzero/finder",
"path": "models.py",
"copies": "1",
"size": "2287",
"license": "mit",
"hash": 5661780103794786000,
"line_mean": 24.9886363636,
"line_max": 57,
"alpha_frac": 0.6191517272,
"autogenerated": false,
"ratio": 3.082210242587601,
"config_test": false,
"has_no_k... |
from .finder import Finder, TIME_LIMIT, MAX_RUNS
from pathfinding.core.util import backtrace
from pathfinding.core.diagonal_movement import DiagonalMovement
class BreadthFirstFinder(Finder):
def __init__(self, heuristic=None, weight=1,
diagonal_movement=DiagonalMovement.never,
tim... | {
"repo_name": "ironsmile/tank4eta",
"path": "pathfinding/finder/breadth_first.py",
"copies": "1",
"size": "1148",
"license": "mit",
"hash": 2527507454277553700,
"line_mean": 33.7878787879,
"line_max": 63,
"alpha_frac": 0.6106271777,
"autogenerated": false,
"ratio": 4.114695340501792,
"config_te... |
from .finder import Finder, TIME_LIMIT, MAX_RUNS
from pathfinding.core.util import backtrace
from pathfinding.core.diagonal_movement import DiagonalMovement
class BreadthFirstFinder(Finder):
def __init__(self, heuristic=None, weight=1,
diagonal_movement=DiagonalMovement.never,
ti... | {
"repo_name": "brean/python-pathfinding",
"path": "pathfinding/finder/breadth_first.py",
"copies": "1",
"size": "1177",
"license": "mit",
"hash": 169061935887465900,
"line_mean": 32.6285714286,
"line_max": 63,
"alpha_frac": 0.6066270178,
"autogenerated": false,
"ratio": 4.144366197183099,
"conf... |
from finder import (find_steps_modules,
find_text_specs,
find_before_all,
find_before_each,
find_after_all,
find_after_each,)
from runner import StoryRunner
from optparse import OptionParser
import sys
import os
def pyc... | {
"repo_name": "hugobr/pycukes",
"path": "pycukes/console.py",
"copies": "2",
"size": "3218",
"license": "mit",
"hash": 8612033745856035000,
"line_mean": 40.2564102564,
"line_max": 104,
"alpha_frac": 0.5574891237,
"autogenerated": false,
"ratio": 4.168393782383419,
"config_test": false,
"has_n... |
from finder import (
models,
parsers,
util
)
def process_card(card, scale=10, split=''):
'''
Pass 'left' or 'right' when processing a split card.
Processes and updates all additional fields (cmc, loyalty, tilde rules) on a card
that is already populated with basic data like mana cost, name... | {
"repo_name": "numberoverzero/finder",
"path": "controllers.py",
"copies": "1",
"size": "3053",
"license": "mit",
"hash": -2514012163010911000,
"line_mean": 33.6931818182,
"line_max": 104,
"alpha_frac": 0.6511627907,
"autogenerated": false,
"ratio": 3.8792884371029226,
"config_test": false,
"... |
from findex_common.static_variables import FileProtocols, user_agent
from wtforms import TextAreaField, SubmitField, Form, BooleanField, StringField, PasswordField, validators, SelectField, IntegerField
from wtforms.validators import DataRequired, Length, Email, Regexp, EqualTo
from wtforms.widgets import TextArea
cl... | {
"repo_name": "skftn/findex-gui",
"path": "findex_gui/controllers/admin/server/forms.py",
"copies": "1",
"size": "1812",
"license": "mit",
"hash": 5268038637683716000,
"line_mean": 46.6842105263,
"line_max": 151,
"alpha_frac": 0.6975717439,
"autogenerated": false,
"ratio": 4.3349282296650715,
"... |
from findex_gui.bin.config import config
from datetime import datetime
from flask_babel import gettext
from sqlalchemy_utils import escape_like
from sqlalchemy import func
from sqlalchemy_zdb import ZdbQuery
from findex_gui.web import app, db
from findex_gui.orm.models import Files, Resource
from findex_common.crawl.... | {
"repo_name": "skftn/findex-gui",
"path": "findex_gui/controllers/search/search.py",
"copies": "1",
"size": "6465",
"license": "mit",
"hash": -6900741903669354000,
"line_mean": 33.2063492063,
"line_max": 108,
"alpha_frac": 0.5523588554,
"autogenerated": false,
"ratio": 4.066037735849057,
"confi... |
from findex_gui.web import app
from furl import furl
from werkzeug.routing import BaseConverter
from findex_common.static_variables import PopcornParameters
class MetaImdbSearchConverter(BaseConverter):
"""The URL Converter for parsing popcorn arguments."""
def to_python(self, value):
lookup = Popcorn... | {
"repo_name": "skftn/findex-gui",
"path": "findex_gui/controllers/meta/converters.py",
"copies": "1",
"size": "1192",
"license": "mit",
"hash": -6136720608565181000,
"line_mean": 26.0909090909,
"line_max": 60,
"alpha_frac": 0.485738255,
"autogenerated": false,
"ratio": 4.182456140350877,
"confi... |
from findex_gui.web import app
from furl import furl
from werkzeug.routing import BaseConverter
from findex_common.static_variables import SearchParameters
class SearchUrlConverter(BaseConverter):
"""
The URL Converter for parsing search arguments.
Example: /search/die%20hard&cats=[movies]&type=[files]&si... | {
"repo_name": "skftn/findex-gui",
"path": "findex_gui/controllers/search/converters.py",
"copies": "1",
"size": "1334",
"license": "mit",
"hash": -384310834951538370,
"line_mean": 25.68,
"line_max": 76,
"alpha_frac": 0.4902548726,
"autogenerated": false,
"ratio": 4.16875,
"config_test": false,
... |
from findex_gui.web import app, themes
from findex_gui.controllers.admin.status.status import AdminStatusController
from findex_gui.controllers.user.decorators import admin_required
@app.route("/admin/status/overview")
@admin_required
def admin_status_overview():
results = AdminStatusController.overview()
ret... | {
"repo_name": "skftn/findex-gui",
"path": "findex_gui/controllers/admin/status/routes.py",
"copies": "1",
"size": "1261",
"license": "mit",
"hash": -7928021293041786000,
"line_mean": 32.1842105263,
"line_max": 92,
"alpha_frac": 0.7454401269,
"autogenerated": false,
"ratio": 3.697947214076246,
"... |
from findex_gui.web import db
from findex_gui.orm.models import NmapRule, ResourceGroup
from findex_gui.controllers.user.roles import role_req
class NmapController:
@staticmethod
@role_req("ADMIN")
def get(uid: str = None, limit: int = None, offset: int = None):
q = db.session.query(NmapRule)
... | {
"repo_name": "skftn/findex-gui",
"path": "findex_gui/controllers/nmap/nmap.py",
"copies": "1",
"size": "2284",
"license": "mit",
"hash": 4343912076940978000,
"line_mean": 31.1690140845,
"line_max": 96,
"alpha_frac": 0.5477232925,
"autogenerated": false,
"ratio": 4.1678832116788325,
"config_tes... |
from findex_gui.web import db
from findex_gui.orm.models import Post, User
from findex_gui.controllers.user.user import UserController
class NewsController:
@staticmethod
def get(uid: int = None, limit: int = 5, offset: int = 0):
q = db.session.query(Post)
if isinstance(uid, int):
... | {
"repo_name": "skftn/findex-gui",
"path": "findex_gui/controllers/news/news.py",
"copies": "1",
"size": "1678",
"license": "mit",
"hash": -5119102833298065000,
"line_mean": 30.0740740741,
"line_max": 74,
"alpha_frac": 0.5917759237,
"autogenerated": false,
"ratio": 3.9205607476635516,
"config_te... |
from findFileInfo import read_pos, coordinate_correct
from image import Image
def transformation(name, x_top_left, y_top_left):
""" Build the final perstective transformation matrix in a string.
Parameters
============
name : String
The name of the iamge, such as '1.23.tif'
x_topleft : ... | {
"repo_name": "suzhaoen/pkout",
"path": "package/transformation.py",
"copies": "1",
"size": "1613",
"license": "mit",
"hash": -3476916728871574000,
"line_mean": 30.26,
"line_max": 81,
"alpha_frac": 0.5796652201,
"autogenerated": false,
"ratio": 3.506521739130435,
"config_test": false,
"has_no... |
from findfiles import Window
from PySide import QtCore
#===================================================================================================
# test_basic_search
#===================================================================================================
def test_basic_search(qtbot, tmpdi... | {
"repo_name": "cherry-wb/SideTools",
"path": "examples/dialogs/findfiles_test.py",
"copies": "1",
"size": "1120",
"license": "apache-2.0",
"hash": -2675236462757234700,
"line_mean": 29.1666666667,
"line_max": 100,
"alpha_frac": 0.5133928571,
"autogenerated": false,
"ratio": 4.426877470355731,
"... |
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