text stringlengths 0 1.05M | meta dict |
|---|---|
import os.path as op
from nose.tools import assert_true
import numpy as np
from numpy.testing import assert_allclose
from mne import Epochs, read_evokeds, pick_types
from mne.io.compensator import make_compensator, get_current_comp
from mne.io import Raw
from mne.utils import _TempDir, requires_mne, run_subprocess
b... | {
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import os.path as op
from nose.tools import assert_true
from numpy.testing import assert_array_almost_equal
from nose.tools import assert_raises
import numpy as np
from scipy import linalg
import warnings
from mne.cov import regularize, whiten_evoked
from mne import (read_cov, write_cov, Epochs, merge_events,
... | {
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import os.path as op
import numpy as np
from numpy.testing import (assert_array_almost_equal, assert_array_equal,
assert_almost_equal)
from nose.tools import assert_true, assert_raises
import warnings
from mne.datasets import testing
from mne import read_forward_solution
from mne.simulatio... | {
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import os.path as op
import numpy as np
from numpy.testing import (assert_array_almost_equal, assert_array_equal,
assert_equal, assert_allclose)
from nose.tools import assert_true, assert_raises
import warnings
from mne.datasets import testing
from mne import read_forward_solution
from mne... | {
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import os.path as op
import numpy as np
from numpy.testing import assert_array_almost_equal
from nose.tools import assert_true, assert_raises
import warnings
from mne.datasets import testing
from mne import read_label, read_forward_solution
from mne.time_frequency import morlet
from mne.simulation import generate_sp... | {
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import warnings
import os.path as op
from nose.tools import assert_true
from mne import io, Epochs, read_events, pick_types
from mne.utils import requires_sklearn
from mne.decoding import time_generalization
data_dir = op.join(op.dirname(__file__), '..', '..', 'io', 'tests', 'data')
raw_fname = op.join(data_dir, 't... | {
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"path": "mne/decoding/tests/test_time_gen.py",
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import warnings
import os.path as op
from nose.tools import assert_true
from mne import io, Epochs, read_events, pick_types
from mne.utils import _TempDir, requires_sklearn
from mne.decoding import time_generalization
tempdir = _TempDir()
data_dir = op.join(op.dirname(__file__), '..', '..', 'io', 'tests', 'data')
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import numpy as np
from ..utils import logger, verbose
@verbose
def is_equal(first, second, verbose=None):
"""Check if 2 python structures are the same.
Designed to handle dict, list, np.ndarray etc.
"""
all_equal = True
# Check all keys in first dict
if type(first) != type(second):
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import numpy as np
from ..utils import logger, verbose
@verbose
def is_equal(first, second, verbose=None):
""" Says if 2 python structures are the same. Designed to
handle dict, list, np.ndarray etc.
"""
all_equal = True
# Check all keys in first dict
if type(first) != type(second):
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from copy import deepcopy
import numpy as np
from scipy import linalg, signal
from ..source_estimate import SourceEstimate
from ..minimum_norm.inverse import combine_xyz, _prepare_forward
from ..forward import compute_orient_prior, is_fixed_orient, _to_fixed_ori
from ..io.pick import pick_channels_evoked
from .mxne_o... | {
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import numpy as np
from .utils import logger, verbose
@verbose
def read_dip(fname, verbose=None):
"""Read .dip file from Neuromag/xfit or MNE
Parameters
----------
fname : str
The name of the .dip file.
verbose : bool, str, int, or None
If not None, override default verbose leve... | {
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import os.path as op
from nose.tools import assert_true, assert_raises
import numpy as np
from numpy.testing import assert_array_almost_equal
from mne import io, Epochs, read_events, pick_types
from mne.decoding.csp import CSP
from mne.utils import requires_sklearn
data_dir = op.join(op.dirname(__file__), '..', '..... | {
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import os.path as op
import pytest
import numpy as np
from numpy.testing import (assert_array_almost_equal, assert_array_equal,
assert_equal)
from mne import io, Epochs, read_events, pick_types
from mne.decoding.csp import CSP, _ajd_pham, SPoC
from mne.utils import requires_sklearn
data_d... | {
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"c... |
import os.path as op
from nose.tools import assert_true, assert_raises, assert_equal
import numpy as np
from numpy.testing import assert_array_almost_equal, assert_array_equal
from mne import io, Epochs, read_events, pick_types
from mne.decoding.csp import CSP, _ajd_pham
from mne.utils import requires_sklearn, slow_... | {
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import os.path as op
from nose.tools import assert_true, assert_raises
import numpy as np
from numpy.testing import assert_array_almost_equal
from mne import io, Epochs, read_events, pick_types
from mne.decoding.csp import CSP
from mne.utils import requires_sklearn
data_dir = op.join(op.dirname(__file__), '..', '..... | {
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__author__ = 'alexandre'
#from .. import strings
# def test_filter_objlist(olist, fieldname, fieldval):
# """
# Returns a list with of the objetcts in olist that have a fieldname valued as fieldval
#
# @param olist: list of objects
# @param fieldname: string
# @param fieldval: anything
#
# @r... | {
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__author__ = 'Alexandre'
import cPickle
import numpy as np
import os
import random
from math import exp
from time import time, sleep
from GSkernel import load_AA_matrix, GS_kernel, compute_psi_dict
from GSkernel_fast import GS_gram_matrix_fast
def GS_kernel_naive(str1, str2, sigmaPos, sigmaAA, L, amino_acids, aa_des... | {
"repo_name": "aldro61/microbiome-summer-school-2017",
"path": "exercises/code/GSkernel_source/benchmark/bench.py",
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"ratio... |
__author__ = 'alexandre'
import os
import os.path as op
import logging
import subprocess
from boyle.nifti.storage import save_niigz
from boyle.files.names import get_temp_file, get_temp_dir
log = logging.getLogger(__name__)
class FslViewCaller(object):
fslview_bin = op.join(os.environ['FSLDIR'], 'bi... | {
"repo_name": "Neurita/cajal",
"path": "cajal/fslview.py",
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"has_no_... |
__author__ = 'alexandre'
import os.path as op
from datetime import datetime, timedelta
from collections import Counter
from operator import itemgetter
import dataset
import sqlalchemy
class VoterAlreadyVoted(Exception):
pass
class VoteRoundNotFound(Exception):
pass
class VoteRoundIsFinis... | {
"repo_name": "PythonSanSebastian/pyper_the_bot",
"path": "implants/vote_rounds.py",
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"size": "10736",
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"alpha_frac": 0.5397727273,
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__author__ = 'alexandre'
import pandas as pd
from gdrive import get_spreadsheet, get_worksheet, worksheet_to_dict
def get_ws_data(api_key_file, doc_key, ws_tab_idx, header=None):
""" Return the content of the spreadsheet in the ws_tab_idx tab of the spreadsheet with doc_key
as a pandas DataFrame.
Pa... | {
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"path": "implants/sponsors_agreements_factory.py",
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__author__ = 'Alexandre'
import ply.lex as lex
reserved_words = (
'color',
'point',
'line',
'circle',
'rect',
'ellipse',
'customshape',
'text',
'rotate',
'scale',
'translate',
'hide',
'if',
'while',
'for',
'step',
'apply',
'rgb',
'hex',
'name',
'x',
'y',
'p1',
'p2',
'f... | {
"repo_name": "thedarkmammouth/PNP",
"path": "lex.py",
"copies": "2",
"size": "2038",
"license": "mit",
"hash": 6396340051251862000,
"line_mean": 14.8062015504,
"line_max": 75,
"alpha_frac": 0.5574092247,
"autogenerated": false,
"ratio": 2.5036855036855035,
"config_test": false,
"has_no_keywo... |
__author__ = "Alexan Mardigian"
__version__ = "1.0.0"
import os
import time
import tingbot
from tingbot import *
SAVEFILE = 'saved_font.sav'
def load_fonts():
x = 0
f = {}
path = "./fonts/"
files = os.listdir(path)
for filename in files:
if filename.endswith(".ttf"):
... | {
"repo_name": "Techno-Hwizrdry/clok",
"path": "clok.tingapp/main.py",
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... |
__author__ = "Alexan Mardigian"
__version__ = "1.2.3"
from argparse import ArgumentParser
from time import sleep
import json
import requests
import sys
PWNED_API_URL = "https://haveibeenpwned.com/api/v3/%s/%s?truncateResponse=%s"
HEADERS = {
"User-Agent": "checkpwnedemails",
"hibp-api-key... | {
"repo_name": "Techno-Hwizrdry/checkpwnedemails",
"path": "checkpwnedemails.py",
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__author__ = "alex balzer <abalzer22@gmail.com>"
__version__ = "0.1.0"
# TODO: need to come up with different ways that you can mess with the vectors for each node so that you can create various matrices that all have relavance to specific applications.
class vectree(object):
def __init__(self,root):
self.root = r... | {
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__author__ = "Alex Baranov"
from oriented_packing import oriented_packer, oriented_container_selector
from copy import deepcopy
from box import Box
class RPacker(object):
"""
Class is used to rectangular elements to the rectangular containers.
"""
def __init__(self, **kwargs):
"""
Cr... | {
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__author__ = 'Alex Baranov'
import numpy as np
import itertools as iter
__PRINT_DEBUG = False
class InequalitiesSolver(object):
last_system = None
last_found_fundamental_system = None
min_random = 1
max_random = 1000
def find_foundamental_system_of_solution(self, system):
"""
Se... | {
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__author__ = 'Alex Baranov'
import unittest
from time import *
import numpy as np
from ..discrete.inequalities import chernikov as c
class TestFind_system_of_fundamental_solutions(unittest.TestCase):
def _test_pulp(self):
import pulp as p
prob = p.LpProblem("The Whiskas Problem", p.LpMinimize)
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__author__ = 'Alex Baranov'
from copy import deepcopy
from json import JSONEncoder
class Box(object):
"""Represents the box element"""
@staticmethod
def from_json_dict(d):
"""
Parses the box from the JSON dict
"""
return Box(d['size'], bottom_left=d['polus'], ... | {
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__author__ = 'Alex Baranov'
from box import Box
from itertools import permutations
from operator import itemgetter
from copy import deepcopy
def orthogonal_packer(container, rect, axes_priorities=None, allowed_rotation_axes=None, **kwargs):
"""
Packs rect to the container. Rotation of packed are al... | {
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__author__ = "Alex Baranov"
from inequalities import chernikov as c
from permutations import *
import numpy as np
def find_minimum(goal_func,
constraints_system,
combinatorial_set,
add_constraints=True,
series_count=3,
e... | {
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"path": "pyopt/discrete/randomsearch.py",
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"autogenerated": false,
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"config_t... |
__author__ = 'Alex Baranov'
from oriented_packing import oriented_packer
from operator import itemgetter
from itertools import ifilter
def get_non_blocking_boxes(current_box, all_boxes, packed_boxes):
"""
Get boxes that are not allowed to block with the current box.
"""
result = []
... | {
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__author__ = "Alex Baranov"
from random import randrange
from visual import *
from reports import ReportsBuilder
class BoxDrawer(object):
"""
Draws the boxes
"""
def __init__(self, packing_params=None, display_labels=True, **kwargs):
"""
Start the box drawing.
... | {
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"autogenerated": false,
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__author__ = 'Alex Baranov'
from reports import ReportsBuilder
from pdp_packing import stable_non_blocking_container_selector
from orthogonal_packing import orthogonal_packer
from drawer import BoxDrawer
from rpacker import RPacker
from box import Box
from optparse import OptionParser
# define the command... | {
"repo_name": "stonelake/pyoptimization",
"path": "pyopt/packing/rectangular/pdphelper.py",
"copies": "1",
"size": "8217",
"license": "apache-2.0",
"hash": -3984635566719759000,
"line_mean": 39.085,
"line_max": 115,
"alpha_frac": 0.5635876841,
"autogenerated": false,
"ratio": 3.935344827586207,
... |
__author__ = "Alex Baranov"
import itertools as it
from combinatorial_set import CombinatorialSet
class PermutationSet(CombinatorialSet):
"""
Describes the set of permutations
"""
def __init__(self, s=()):
super(PermutationSet, self).__init__(s)
def __iter__(self):
... | {
"repo_name": "stonelake/pyoptimization",
"path": "pyopt/discrete/permutations.py",
"copies": "1",
"size": "1611",
"license": "apache-2.0",
"hash": 3052014972508641000,
"line_mean": 28.3962264151,
"line_max": 113,
"alpha_frac": 0.5834885164,
"autogenerated": false,
"ratio": 4.120204603580563,
"... |
__author__ = 'Alex Berriman <aberriman@formcorp.com.au>'
import sys
import formcorp.api
# FormCorp configurations
public_key = ''
private_key = ''
form_id = 0
# Initialise the module
formcorp.api.init(private_key, public_key)
# Set the form id
formcorp.api.set_form_id(form_id)
print "==============================... | {
"repo_name": "formcorp/python-formcorp",
"path": "sample-app.py",
"copies": "1",
"size": "1392",
"license": "apache-2.0",
"hash": 5252192670987343000,
"line_mean": 25.7692307692,
"line_max": 82,
"alpha_frac": 0.6293103448,
"autogenerated": false,
"ratio": 3.462686567164179,
"config_test": fals... |
__author__ = 'Alex Breshears'
__license__ = '''
Copyright (C) 2012 Alex Breshears
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 Software without restriction, including without limitation the rights to
us... | {
"repo_name": "t3hi3x/p-k.co",
"path": "shorturls/admin.py",
"copies": "1",
"size": "1450",
"license": "mit",
"hash": -3901632474489135000,
"line_mean": 38.2162162162,
"line_max": 79,
"alpha_frac": 0.7875862069,
"autogenerated": false,
"ratio": 4.178674351585014,
"config_test": false,
"has_no... |
__author__ = 'Alex Breshears'
from shorturls.utils import *
from django.http import Http404, HttpResponse, HttpResponseRedirect
from django.template import Context, RequestContext
from django.template.loader import get_template
from chartit import PivotChart, PivotDataPool
from django.db.models import Count
from djang... | {
"repo_name": "t3hi3x/p-k.co",
"path": "ajax/views.py",
"copies": "1",
"size": "6081",
"license": "mit",
"hash": 9220784576119864000,
"line_mean": 33.9540229885,
"line_max": 168,
"alpha_frac": 0.6625555007,
"autogenerated": false,
"ratio": 2.949078564500485,
"config_test": false,
"has_no_keyw... |
__author__ = 'alexei'
from telnetlib import Telnet
class JamesHelper:
def __init__(self, app):
self.app = app
def ensure_user_exists(self, username, password):
james_config = self.app.config['james']
session = JamesHelper.Session(
james_config['host'], james_config['port'... | {
"repo_name": "barancev/python_training_mantis",
"path": "fixture/james.py",
"copies": "1",
"size": "1732",
"license": "apache-2.0",
"hash": 320728738823281300,
"line_mean": 32.9803921569,
"line_max": 107,
"alpha_frac": 0.5750577367,
"autogenerated": false,
"ratio": 3.848888888888889,
"config_t... |
__author__ = 'alexei'
class SessionHelper:
def __init__(self, app):
self.app = app
def login(self, username, password):
wd = self.app.wd
self.app.open_home_page()
wd.find_element_by_name("username").click()
wd.find_element_by_name("username").clear()
wd.find_e... | {
"repo_name": "barancev/python_training_mantis",
"path": "fixture/session.py",
"copies": "1",
"size": "1456",
"license": "apache-2.0",
"hash": 5158036655489781000,
"line_mean": 29.3541666667,
"line_max": 78,
"alpha_frac": 0.5776098901,
"autogenerated": false,
"ratio": 3.466666666666667,
"config... |
__author__ = 'Alexendar Perez'
#####################
# #
# Introduction #
# #
#####################
"""check which genes the gRNAs used for training data in CRISPR ML task are hitting in mm10"""
#################
# #
# Libraries #
# #
#########... | {
"repo_name": "lzamparo/crisprML",
"path": "src/gRNA_data_gene_check.py",
"copies": "1",
"size": "4157",
"license": "bsd-3-clause",
"hash": -6554842826290211000,
"line_mean": 30.9769230769,
"line_max": 178,
"alpha_frac": 0.6050036084,
"autogenerated": false,
"ratio": 3.5867126833477134,
"config... |
__author__ = 'Alexendar Perez'
#####################
# #
# Introduction #
# #
#####################
"""compute specificity score, Hamming, and Levinstein distance neighborhoods for strings"""
#################
# #
# Libraries #
# #
############... | {
"repo_name": "lzamparo/crisprML",
"path": "src/specificity_score_distance_neighbors.py",
"copies": "1",
"size": "16743",
"license": "bsd-3-clause",
"hash": 1234933588811401200,
"line_mean": 33.1018329939,
"line_max": 150,
"alpha_frac": 0.6780146927,
"autogenerated": false,
"ratio": 2.99624194702... |
__author__ = 'Alexendar Perez'
#####################
# #
# Introduction #
# #
#####################
"""extract candidate gRNAs for cutting efficiency screen"""
#################
# #
# Libraries #
# #
#################
import sys
import argpars... | {
"repo_name": "lzamparo/crisprML",
"path": "src/extract_screening_gRNAs.py",
"copies": "1",
"size": "4855",
"license": "bsd-3-clause",
"hash": 9107329105069600000,
"line_mean": 30.7320261438,
"line_max": 224,
"alpha_frac": 0.5274974253,
"autogenerated": false,
"ratio": 3.5155684286748734,
"conf... |
__author__ = 'Alexendar Perez'
#####################
# #
# Introduction #
# #
#####################
"""select gRNAs from a set that meet certain annotation requirements"""
#################
# #
# Libraries #
# #
#################
import sys
im... | {
"repo_name": "lzamparo/crisprML",
"path": "src/gRNA_from_annotations.py",
"copies": "1",
"size": "9584",
"license": "bsd-3-clause",
"hash": 6337414569868282000,
"line_mean": 37.0317460317,
"line_max": 162,
"alpha_frac": 0.6044449082,
"autogenerated": false,
"ratio": 4.0507185122569735,
"config... |
import numpy as np
from scipy import sparse
import igraph
from sklearn.base import BaseEstimator, RegressorMixin
from sklearn.utils.validation import NotFittedError, check_X_y, check_array
class MultiIsotonicRegressor(BaseEstimator, RegressorMixin):
"""Regress a target value as a non-decreasing function of each ... | {
"repo_name": "alexfields/multiisotonic",
"path": "multiisotonic.py",
"copies": "1",
"size": "4968",
"license": "bsd-3-clause",
"hash": 4078524916012369000,
"line_mean": 40.7478991597,
"line_max": 142,
"alpha_frac": 0.5841384863,
"autogenerated": false,
"ratio": 3.8098159509202456,
"config_test... |
__author__ = 'Alex Frank'
from scipy import stats
import numpy as np
import json
def main():
timestamps = []
bottom_norms = []
top_norms = []
# expects norms.dat in same directory. Can be changed to be a command-line arg
f = open('norms.dat', 'r')
for line in f:
words = line.split(' '... | {
"repo_name": "acic2015/findr",
"path": "deprecated/linearReg.py",
"copies": "1",
"size": "1037",
"license": "mit",
"hash": -6715648850382036000,
"line_mean": 24.2926829268,
"line_max": 130,
"alpha_frac": 0.5949855352,
"autogenerated": false,
"ratio": 3.575862068965517,
"config_test": false,
... |
import re
import os
import numpy as np
import pandas as pd
from operator import itemgetter
from itertools import groupby
# ========================================= Loads the skeletal data and labels =================================================================
# Returns: a dataframe with the whole training set f... | {
"repo_name": "AlexGidiotis/Multimodal-Gesture-Recognition-with-LSTMs-and-CTC",
"path": "skeletal_network/skeletal_feature_extraction.py",
"copies": "1",
"size": "14319",
"license": "mit",
"hash": -7257514341169482000,
"line_mean": 45.1903225806,
"line_max": 145,
"alpha_frac": 0.6271387667,
"autoge... |
__author__ = 'Alex Gusev <alex@flancer64.com>'
from prxgt.const import ATTR_TYPE_INT
from prxgt.domain.attribute import Attribute
from prxgt.domain.meta.entity import Entity
ATTR_ID_NAME = "id"
class Instance(Entity):
"""
Entity instance representation.
"""
def __init__(self, id_=None, attrs=None):
... | {
"repo_name": "praxigento/teq_test_db_schema_attrs",
"path": "prxgt/domain/instance.py",
"copies": "1",
"size": "1217",
"license": "mit",
"hash": 4806697462854603000,
"line_mean": 21.5555555556,
"line_max": 60,
"alpha_frac": 0.5579293344,
"autogenerated": false,
"ratio": 3.733128834355828,
"con... |
__author__ = 'Alex Gusev <alex@flancer64.com>'
from prxgt.domain.filter.filter import Filter
from prxgt.domain.filter.filter_rule import FilterRule
from prxgt.domain.filter.condition import Condition
class ConditionRule(FilterRule):
"""
ConditionRule представляет собой логическое условие (AND, OR, NOT), приме... | {
"repo_name": "praxigento/teq_test_db_schema_attrs",
"path": "prxgt/domain/filter/condition_rule.py",
"copies": "1",
"size": "1305",
"license": "mit",
"hash": -1540374810823010000,
"line_mean": 28.1463414634,
"line_max": 112,
"alpha_frac": 0.622278057,
"autogenerated": false,
"ratio": 3.125654450... |
__author__ = 'Alex Gusev <alex@flancer64.com>'
import json
import logging
class Config:
_filename = None
_data = None
def __init__(self, filename='config.json'):
self._filename = filename
def load(self):
cfg_file = open(self._filename)
self._data = json.load(cfg_file)
... | {
"repo_name": "praxigento/teq_test_db_schema_attrs",
"path": "prxgt/config.py",
"copies": "1",
"size": "1262",
"license": "mit",
"hash": -7290052338089364000,
"line_mean": 29.7804878049,
"line_max": 79,
"alpha_frac": 0.6283676704,
"autogenerated": false,
"ratio": 3.5649717514124295,
"config_tes... |
__author__ = 'Alex Gusev <alex@flancer64.com>'
import prxgt.const as const
from prxgt.domain.meta.attribute import Attribute as AttributeBase
class Attribute(AttributeBase):
"""
Attribute model contains data.
"""
def __init__(self, name=None, type_=None, value=None):
super(Attribute, self).__... | {
"repo_name": "praxigento/teq_test_db_schema_attrs",
"path": "prxgt/domain/attribute.py",
"copies": "1",
"size": "1049",
"license": "mit",
"hash": 5439268651677813000,
"line_mean": 25.25,
"line_max": 75,
"alpha_frac": 0.5510009533,
"autogenerated": false,
"ratio": 3.870848708487085,
"config_tes... |
__author__ = 'Alex Gusev <alex@flancer64.com>'
import unittest
import os
from mock import Mock
from prxgt.config import Config
from prxgt.repo.repository import Repository
from prxgt.domain.instance import Instance
from prxgt.domain.attribute import Attribute
ATTR_NAME = "a0"
INST_ID = 0
ATTR_TYPE = "som type"
ATTR... | {
"repo_name": "praxigento/teq_test_db_schema_attrs",
"path": "prxgt/repo/test_repository.py",
"copies": "1",
"size": "3483",
"license": "mit",
"hash": 1471161916735666700,
"line_mean": 28.7777777778,
"line_max": 95,
"alpha_frac": 0.6032156187,
"autogenerated": false,
"ratio": 3.7858695652173915,
... |
__author__ = 'Alex Gusev <alex@flancer64.com>'
import unittest
from prxgt.domain.filter.alias import Alias
from prxgt.domain.filter.condition import Condition
from prxgt.domain.filter.condition_rule import ConditionRule
from prxgt.domain.filter.filter import Filter
from prxgt.domain.filter.function import Function
fro... | {
"repo_name": "praxigento/teq_test_db_schema_attrs",
"path": "prxgt/domain/filter/test_condition_rule.py",
"copies": "1",
"size": "1902",
"license": "mit",
"hash": -6450459622406062000,
"line_mean": 34.2407407407,
"line_max": 95,
"alpha_frac": 0.6388012618,
"autogenerated": false,
"ratio": 3.5418... |
__author__ = 'Alex Gusev <alex@flancer64.com>'
import unittest
import prxgt.const as const
from prxgt.repo.generator import Generator
class Test(unittest.TestCase):
def test_init(self):
# tests
gene = Generator()
self.assertIsNotNone(gene)
return
def test_get_value(self):
... | {
"repo_name": "praxigento/teq_test_db_schema_attrs",
"path": "prxgt/repo/test_generator.py",
"copies": "1",
"size": "1512",
"license": "mit",
"hash": 9222583931975565000,
"line_mean": 29.26,
"line_max": 64,
"alpha_frac": 0.6302910053,
"autogenerated": false,
"ratio": 3.7241379310344827,
"config... |
__author__ = 'Alex Gusev <alex@flancer64.com>'
from prxgt.domain.filter.expression import Expression
from prxgt.domain.filter.filter_rule import FilterRule
from prxgt.domain.filter.function import Function
class FunctionRule(Expression, FilterRule):
"""
FunctionRule представляет собой функцию с некоторым на... | {
"repo_name": "praxigento/teq_test_db_schema_attrs",
"path": "prxgt/domain/filter/function_rule.py",
"copies": "1",
"size": "1309",
"license": "mit",
"hash": 2784788847880604000,
"line_mean": 25.6222222222,
"line_max": 78,
"alpha_frac": 0.6135225376,
"autogenerated": false,
"ratio": 3.12793733681... |
__author__ = 'Alex Gusev <alex@flancer64.com>'
from prxgt.domain.filter.filter import Filter
from prxgt.domain.instance import Instance
from prxgt.proc.base import ProcessorBase
from prxgt.repo.repository import Repository
from prxgt.proc.filtrator import Filtrator
class RepoProcessor(ProcessorBase):
"""
Sim... | {
"repo_name": "praxigento/teq_test_db_schema_attrs",
"path": "prxgt/proc/repo.py",
"copies": "1",
"size": "1573",
"license": "mit",
"hash": 1691764970543538700,
"line_mean": 32.4680851064,
"line_max": 78,
"alpha_frac": 0.6649713922,
"autogenerated": false,
"ratio": 3.8935643564356437,
"config_t... |
__author__ = 'Alex Gusev <alex@flancer64.com>'
import random
import string
import prxgt.const as const
TYPE_DEC = const.ATTR_TYPE_DEC
TYPE_INT = const.ATTR_TYPE_INT
TYPE_STR = const.ATTR_TYPE_STR
TYPE_TXT = const.ATTR_TYPE_TXT
class Generator(object):
"""
Values generator for various types data.
Прос... | {
"repo_name": "praxigento/teq_test_db_schema_attrs",
"path": "prxgt/repo/generator.py",
"copies": "1",
"size": "1946",
"license": "mit",
"hash": 4943983617352146000,
"line_mean": 23.4782608696,
"line_max": 79,
"alpha_frac": 0.6477205447,
"autogenerated": false,
"ratio": 2.5475113122171944,
"con... |
__author__ = 'alexis.koalla@orange.com'
from flask import request
from S3.bucket import S3Bucket
from Log import Log
from subprocess import PIPE, Popen
import simplejson as json
from model.chunk import Chunk
from model.osd import OSD
from model.pg import PG
from model.S3Object import S3Object
import requests
import r... | {
"repo_name": "inkscope/inkscope",
"path": "inkscopeCtrl/S3ObjectCtrl.py",
"copies": "1",
"size": "22021",
"license": "apache-2.0",
"hash": 6564030995216200000,
"line_mean": 44.7817047817,
"line_max": 251,
"alpha_frac": 0.5517914718,
"autogenerated": false,
"ratio": 3.52392382781245,
"config_te... |
__author__ = 'Alexis.Koalla@orange.com'
import json
class PG:
#""" Definition de la classe """
def __init__(self,pgid,state,acting, up, acting_primary, up_primary):
self.pgid=pgid
self.state= state
self.up = up
self.acting=acting
self.acting_primary=acting_primary
... | {
"repo_name": "abrefort/inkscope-debian",
"path": "inkscopeCtrl/model/pg.py",
"copies": "2",
"size": "1030",
"license": "apache-2.0",
"hash": 8806410706835295000,
"line_mean": 24.1219512195,
"line_max": 147,
"alpha_frac": 0.6038834951,
"autogenerated": false,
"ratio": 3.388157894736842,
"config... |
from .cygmm import cy_gmm
import numpy as np
def gmm(x, n_clusters=10, max_num_iterations=100, covariance_bound=None,
init_mode='rand', init_priors=None, init_means=None, init_covars=None,
n_repetitions=1, verbose=False):
"""Fit a Gaussian mixture model
Parameters
----------
x : [n_sa... | {
"repo_name": "menpo/cyvlfeat",
"path": "cyvlfeat/gmm/gmm.py",
"copies": "1",
"size": "5190",
"license": "bsd-2-clause",
"hash": 4039682227487087600,
"line_mean": 43.7413793103,
"line_max": 80,
"alpha_frac": 0.6337186898,
"autogenerated": false,
"ratio": 3.9709257842387147,
"config_test": false... |
from .cygmm import cy_gmm
import numpy as np
def gmm(X, n_clusters=10, max_num_iterations=100, covariance_bound=None,
init_mode='rand', init_priors=None, init_means=None, init_covars=None,
n_repetitions=1, verbose=False):
"""Fit a Gaussian mixture model
Parameters
----------
X : [n_sa... | {
"repo_name": "simmimourya1/cyvlfeat",
"path": "cyvlfeat/gmm/gmm.py",
"copies": "1",
"size": "5191",
"license": "bsd-2-clause",
"hash": -7215718410456610000,
"line_mean": 43.75,
"line_max": 80,
"alpha_frac": 0.6337892506,
"autogenerated": false,
"ratio": 3.971690895179801,
"config_test": false,... |
import numpy as np
from numpy.testing import assert_allclose
from nose.tools import raises
from cyvlfeat.gmm import gmm
np.random.seed(1)
X = np.random.randn(1000, 2)
X[500:] *= (2, 3)
X[500:] += (4, 4)
def test_gmm_2_clusters_rand_init():
means, covars, priors, LL, posteriors = gmm(X, n_clusters=2)
assert_... | {
"repo_name": "simmimourya1/cyvlfeat",
"path": "cyvlfeat/gmm/tests/test_gmm.py",
"copies": "1",
"size": "1063",
"license": "bsd-2-clause",
"hash": -4474160106751692300,
"line_mean": 29.3714285714,
"line_max": 67,
"alpha_frac": 0.6208842897,
"autogenerated": false,
"ratio": 2.513002364066194,
"c... |
__author__ = 'alexjch'
import signal
try:
import bluetooth as bt
except:
pass
BUFF_SIZE = 1024
def find_device(device_name):
discovered = bt.discover_devices()
target = [d for d in discovered if bt.lookup_name(d) == device_name]
return target.pop() if len(target) else None
class BTAgent(object):... | {
"repo_name": "alexjch/car_monitor",
"path": "src/CarMonitor/bt_spp_comm.py",
"copies": "1",
"size": "1174",
"license": "mit",
"hash": -5435883681817516000,
"line_mean": 23.9787234043,
"line_max": 72,
"alpha_frac": 0.5868824532,
"autogenerated": false,
"ratio": 3.811688311688312,
"config_test":... |
__author__ = 'alexjch'
import sys
import time
import signal
import argparse
from bt_spp_comm import BTAgent as bta, find_device
SLEEP_TIME = 5
def arguments_parser():
ap = argparse.ArgumentParser(description="ODBII communication tool")
device_id_group = ap.add_mutually_exclusive_group(required=True)
devi... | {
"repo_name": "alexjch/car_monitor",
"path": "src/CarMonitor/main.py",
"copies": "1",
"size": "2724",
"license": "mit",
"hash": -4279480341377723000,
"line_mean": 33.05,
"line_max": 114,
"alpha_frac": 0.6196769457,
"autogenerated": false,
"ratio": 3.788595271210014,
"config_test": false,
"has... |
__author__ = 'alexjch'
import os
import sqlite3
CREATE_DB = '''CREATE TABLE telemetry (ID INTEGER PRIMARY KEY AUTOINCREMENT,
STREAM TEXT,
Timestamp DATETIME DEFAULT CURRENT_TIMESTAMP)'''
DB_INSERT = '''INSERT INTO telemetry (STREAM) value... | {
"repo_name": "alexjch/car_monitor",
"path": "src/CarMonitor/db.py",
"copies": "1",
"size": "1131",
"license": "mit",
"hash": 4809279743270470000,
"line_mean": 28.7631578947,
"line_max": 87,
"alpha_frac": 0.5862068966,
"autogenerated": false,
"ratio": 3.913494809688581,
"config_test": false,
... |
import web
from web import http
import pycurl, random, re, cStringIO, types, urllib
import urlparse as _urlparse
from lxml import etree
from md5 import md5
from datetime import datetime
def url_encode(url):
return http.urlencode(url)
def url_unquote(url):
return urllib.unquote_plus(url)
def url_parse(url)... | {
"repo_name": "Nitecon/webframe",
"path": "webframe/view/helpers/utils.py",
"copies": "1",
"size": "2775",
"license": "apache-2.0",
"hash": -3515031585155694600,
"line_mean": 26.76,
"line_max": 98,
"alpha_frac": 0.6299099099,
"autogenerated": false,
"ratio": 3.2685512367491167,
"config_test": f... |
# TODO:
# - if the module submitted is in quoted HTML then it must unquoted
# - bad idea to catch generic exceptions
import web, os, sys
from app.models import modules
from app.helpers import utils
from app.helpers import image
def submit(module_url, tags=''):
success, err_msg = False, ''
try:
... | {
"repo_name": "Nitecon/webframe",
"path": "models/submission.py",
"copies": "4",
"size": "3556",
"license": "apache-2.0",
"hash": -7427854764305517000,
"line_mean": 33.1923076923,
"line_max": 109,
"alpha_frac": 0.6217660292,
"autogenerated": false,
"ratio": 3.9776286353467563,
"config_test": fa... |
from config import db
from app.helpers import tag_cloud
import re, sets
def get_tags(module_id):
return db.select('tags',
vars = dict(id=module_id),
what = 'tag',
where = 'module_id=$id')
def get_tag_cloud():
"""Return a tag cloud of most popular modules."""
tags... | {
"repo_name": "minixalpha/SourceLearning",
"path": "webpy/sample/googlemodules/src/app/models/tags.py",
"copies": "4",
"size": "1344",
"license": "apache-2.0",
"hash": -1345021795168026000,
"line_mean": 27.8666666667,
"line_max": 69,
"alpha_frac": 0.556547619,
"autogenerated": false,
"ratio": 3.3... |
import web
from config import db
def add(module_id, vote, user_ip):
if already_voted(module_id, user_ip):
success = True
else:
success = False
if module_id and -5 <= vote <= 5:
db.insert('votes',
module_id=module_id, vote=vote, ip=user_ip,
... | {
"repo_name": "Nitecon/webframe",
"path": "models/votes.py",
"copies": "4",
"size": "1315",
"license": "apache-2.0",
"hash": 1158601321032302600,
"line_mean": 30.925,
"line_max": 84,
"alpha_frac": 0.5209125475,
"autogenerated": false,
"ratio": 3.53494623655914,
"config_test": false,
"has_no_k... |
import web
from config import db
def get_latest(offset=0, limit=20):
has_next = False
t = list(db.select('forum_threads',
what = 'id, id as idd, title, author, content, datetime_created,\
(select count(id) from forum_threads where reply_to = idd) as no_replies,\
(select max(d... | {
"repo_name": "minixalpha/SourceLearning",
"path": "webpy/sample/googlemodules/src/app_forum/models/threads.py",
"copies": "3",
"size": "1573",
"license": "apache-2.0",
"hash": -200995408655756960,
"line_mean": 26.6,
"line_max": 103,
"alpha_frac": 0.5715193897,
"autogenerated": false,
"ratio": 3.... |
import web
from config import db
from app.helpers import utils
def get_latest():
"""Get latest comments on modules."""
return db.select('comments',
what = 'content, module_id',
order = 'datetime_created desc',
limit = 4)
def get_comments(module_id):
return db.sel... | {
"repo_name": "minixalpha/SourceLearning",
"path": "webpy/sample/googlemodules/src/app/models/comments.py",
"copies": "4",
"size": "1453",
"license": "apache-2.0",
"hash": 3135923185789532000,
"line_mean": 30.2888888889,
"line_max": 84,
"alpha_frac": 0.5911906401,
"autogenerated": false,
"ratio":... |
# TODO:
# - should be made into a class
import Image, cStringIO, os
def save(fi, filename, min_width=30, min_height=20, max_width=460, max_height=420, max_kb=40):
im = get_image_object(fi)
width, height = im.size
if min_width <= width <= max_width and min_height <= height <= max_height:
... | {
"repo_name": "minixalpha/SourceLearning",
"path": "webpy/sample/googlemodules/src/app/helpers/image.py",
"copies": "4",
"size": "1038",
"license": "apache-2.0",
"hash": -7869711781367444000,
"line_mean": 26.1081081081,
"line_max": 94,
"alpha_frac": 0.5712909441,
"autogenerated": false,
"ratio": ... |
"""Framework & steps:
# 1. Parse XML, retrieve all book titles / authors /
Get books from Gutenberg (desc)
wget geonames (wget -r -np -k -nd http://download.geonames.org/export/dump/)
"""
if __name__ == "__main__":
from os import chdir
from os import walk
import logging
import psycopg2
# Se... | {
"repo_name": "Bixbeat/gutenberg-place-mentions",
"path": "main.py",
"copies": "1",
"size": "1650",
"license": "mit",
"hash": -5208668671090769000,
"line_mean": 32.6734693878,
"line_max": 98,
"alpha_frac": 0.6878787879,
"autogenerated": false,
"ratio": 3.459119496855346,
"config_test": false,
... |
__author__ = 'Alex Malyshev <malyshevalex@gmail.com>'
from collections import MutableSet
from .serializers import JsonSerializer
DEFAULT_SERIALIZER = JsonSerializer()
class StringSet(MutableSet):
def __init__(self, *args):
self.data = set()
for arg in args:
self.add(arg)
def ad... | {
"repo_name": "malyshevalex/django-stringset",
"path": "__init__.py",
"copies": "1",
"size": "1234",
"license": "mit",
"hash": -8970118726305730000,
"line_mean": 25.2553191489,
"line_max": 116,
"alpha_frac": 0.5875202593,
"autogenerated": false,
"ratio": 4.140939597315437,
"config_test": false,... |
__author__ = 'Alex'
from PyQt4.QtGui import *
from PyQt4.phonon import Phonon
import sys
from PyQt4 import uic
class Window(QMainWindow):
def __init__(self, parent=None):
super(Window, self).__init__(parent)
#SE CARGA LA VISTA O INTERFAZ GRAFICA
uic.loadUi("window.ui",self)
#LLAM... | {
"repo_name": "AlexEnriquez/PyQtPlayer",
"path": "app.py",
"copies": "1",
"size": "1540",
"license": "bsd-3-clause",
"hash": -6670854179914911000,
"line_mean": 27,
"line_max": 113,
"alpha_frac": 0.6181818182,
"autogenerated": false,
"ratio": 3.484162895927602,
"config_test": false,
"has_no_ke... |
__author__ = 'Alex'
from PyQt4.QtGui import *
import sys
import json
import requests,base64
from PyQt4 import uic
import threading
class Window(QWidget):
def __init__(self,parent=None):
QWidget.__init__(self)
authThread=threading.Thread(target=self.Auth())
uiThread=threading.Thread(target=s... | {
"repo_name": "AlexEnriquez/PyQtMail",
"path": "PyQtMail/app.py",
"copies": "1",
"size": "3071",
"license": "mit",
"hash": 2534850358112260600,
"line_mean": 33.1222222222,
"line_max": 138,
"alpha_frac": 0.5789645067,
"autogenerated": false,
"ratio": 3.513729977116705,
"config_test": false,
"h... |
__author__ = 'Alex'
from sys import maxsize
class Infos:
def __init__(self, firstname = None ,middelname = None,lastname = None,nickname = None, title = None,company = None,address = None,home = None,mobile = None,
fax= None,homepage = None,day_Birthday= None,month_Birthday= None,year_Bi... | {
"repo_name": "Alex-Chizhov/python_training",
"path": "home_works/model/info_contact.py",
"copies": "1",
"size": "2232",
"license": "apache-2.0",
"hash": -2943863213501133000,
"line_mean": 41.9423076923,
"line_max": 225,
"alpha_frac": 0.5389784946,
"autogenerated": false,
"ratio": 3.7014925373134... |
__author__ = 'Alex'
from sys import maxsize
class Infos:
def __init__(self, firstname = None ,middelname = None,lastname = None,nickname = None, title = None,company = None,address = None,home = None,mobile = None,
fax= None,homepage = None,day_Birthday= None,month_Birthday= None,year_B... | {
"repo_name": "Alex-Chizhov/python_training",
"path": "error/home_works/model/info_contact.py",
"copies": "1",
"size": "1888",
"license": "apache-2.0",
"hash": 9159035586713218000,
"line_mean": 39.1914893617,
"line_max": 161,
"alpha_frac": 0.5391949153,
"autogenerated": false,
"ratio": 3.86094069... |
_author__ = 'alex'
import sys
import xml.dom.minidom as dom
from floyd import floyd_algs
def get_Res_Matrix(length,nodes,nets_d,elem_type):
Res = [[[] for j in range(length)] for i in range(length)]
for i in range(nodes.length):
if nodes[i].nodeType != elem_type: continue
name = nodes[i].nodeName
if name == "d... | {
"repo_name": "BaydinAlexey/proglangs_baydin",
"path": "main.py",
"copies": "1",
"size": "2159",
"license": "mit",
"hash": -703794670920265500,
"line_mean": 29.4084507042,
"line_max": 119,
"alpha_frac": 0.6215840667,
"autogenerated": false,
"ratio": 2.604342581423402,
"config_test": false,
"h... |
__author__ = 'Alex'
class Infos:
def __init__(self, firstname,middelname,lastname,nickname, title,company,addres,home,mobile,
fax,homepage,day_Birthday,month_Birthday,year_Birthday,day_Anniversary,
month_Anniversary,year_Anniversary,address2,phone2,notes,work,ph... | {
"repo_name": "Alex-Chizhov/python_training",
"path": "home_work_6/model/info_contact.py",
"copies": "5",
"size": "1267",
"license": "apache-2.0",
"hash": 5434086529490704000,
"line_mean": 37.3939393939,
"line_max": 97,
"alpha_frac": 0.5272296764,
"autogenerated": false,
"ratio": 3.92260061919504... |
__author__ = 'alex'
from cement.core import foundation, controller
from SearchManager import SearchManager
from InteractionManager import OutputInteraction
import time
# define an application base controller
class FindForMeBasedController(controller.CementBaseController):
# Define command line arguments and defa... | {
"repo_name": "masterpiece91/FindForMe",
"path": "FindForMe/FindForMe.py",
"copies": "1",
"size": "4916",
"license": "mit",
"hash": -5424051461285300000,
"line_mean": 35.1544117647,
"line_max": 118,
"alpha_frac": 0.5374288039,
"autogenerated": false,
"ratio": 4.5602968460111315,
"config_test": ... |
__author__ = 'Alex'
from datetime import date, timedelta
import pyFWI.FWIFunctions as FWI
import sqlite3
conn = sqlite3.connect('FWI.db')
cur = conn.cursor()
start = date(2015, 8, 19)
end = date(2015, 8, 22)
for i in range(1,(end-start).days+1):
yesterday = start + timedelta(days=i-1)
today = start + timedel... | {
"repo_name": "parko636/pyfwi",
"path": "fwi_batch.py",
"copies": "1",
"size": "1241",
"license": "bsd-3-clause",
"hash": -9044822394350220000,
"line_mean": 33.5,
"line_max": 140,
"alpha_frac": 0.5938759065,
"autogenerated": false,
"ratio": 2.537832310838446,
"config_test": false,
"has_no_key... |
__author__ = 'alex'
from gmail import Gmail
import datetime
import re
class EmailHandler():
def __init__(self, username, password ):
self.g = Gmail()
self.g.login(username, password)
def logout(self):
self.g.logout()
def get_sent_mail(self):
return self.g.sent_mail()
... | {
"repo_name": "aparij/EmailGrammar",
"path": "email_handler.py",
"copies": "1",
"size": "1362",
"license": "mit",
"hash": 6391883427681816000,
"line_mean": 29.2666666667,
"line_max": 108,
"alpha_frac": 0.5007342144,
"autogenerated": false,
"ratio": 4.242990654205608,
"config_test": false,
"ha... |
__author__ = 'Alex'
from lexer import *
from ast import *
import exception
class Parser(object):
def __init__(self, tokens):
self.tokens = tokens
self.position = 0
self.length = len(tokens)
def error(self, message, *args):
line, col = self.token.line_col
raise excepti... | {
"repo_name": "AlexYukikaze/JSONx",
"path": "JSONx/parser.py",
"copies": "1",
"size": "5847",
"license": "mit",
"hash": -6650881494309548000,
"line_mean": 32.0338983051,
"line_max": 98,
"alpha_frac": 0.5560116299,
"autogenerated": false,
"ratio": 4.004794520547946,
"config_test": false,
"has_... |
__author__ = 'Alex'
from Movement import Movement
class BaseCommand:
def __init__(self, movement):
assert isinstance(movement, Movement)
self.name = 'unknown'
self.m = movement
def execute(selfself):pass
class Forward(BaseCommand):
def __init__(self, movement):
assert isi... | {
"repo_name": "RobotTurtles/mid-level-routines",
"path": "Apps/TurtleCommands.py",
"copies": "1",
"size": "1101",
"license": "apache-2.0",
"hash": 749848484552750600,
"line_mean": 21.9375,
"line_max": 45,
"alpha_frac": 0.6076294278,
"autogenerated": false,
"ratio": 3.682274247491639,
"config_te... |
__author__ = 'alex'
import glob
import os
import itertools
import fnmatch
import mmap
import re
import contextlib
import InteractionManager
from Common import Common
from os.path import join, getsize
# This object will contain all properties for a result item
class ResultController:
def __init__(self):
s... | {
"repo_name": "masterpiece91/FindForMe",
"path": "FindForMe/SearchManager.py",
"copies": "1",
"size": "21841",
"license": "mit",
"hash": -26934375619215664,
"line_mean": 51.5048076923,
"line_max": 121,
"alpha_frac": 0.524609679,
"autogenerated": false,
"ratio": 5.208919627951348,
"config_test":... |
__author__ = 'Alex'
import JSONx.utils as utils
import JSONx
import os
class JSONxLoaderException(Exception):
def __init__(self, message, file_path):
super(JSONxLoaderException, self).__init__(message)
self.message = message
self.file = file_path
class JSONxLoader(object):
def __in... | {
"repo_name": "AlexYukikaze/JSONx",
"path": "JSONxLoader/loader.py",
"copies": "1",
"size": "3574",
"license": "mit",
"hash": -2078804446673174800,
"line_mean": 33.0380952381,
"line_max": 119,
"alpha_frac": 0.5540011192,
"autogenerated": false,
"ratio": 3.6845360824742266,
"config_test": true,
... |
__author__ = 'alex'
import os
import subprocess
from colorama import Style, init, Back, Fore
from Common import Common
class OutputInteraction:
def __init__(self):
self.common_tools = Common()
def request_result_item(self, search_directory, result_dictionary, input_message):
message_tool = N... | {
"repo_name": "masterpiece91/FindForMe",
"path": "FindForMe/InteractionManager.py",
"copies": "1",
"size": "4029",
"license": "mit",
"hash": -7291795230444833000,
"line_mean": 50,
"line_max": 120,
"alpha_frac": 0.5395879871,
"autogenerated": false,
"ratio": 4.9496314496314495,
"config_test": fa... |
__author__ = 'alex'
import requests
from collections import Counter
from lxml import objectify
from xml.etree import ElementTree
class Error:
""" AtD Error Object
These are to be returned in a list by checkText()
Available properties are: string, description, precontext, type, url
and suggestions.
... | {
"repo_name": "aparij/EmailGrammar",
"path": "atd_processing.py",
"copies": "1",
"size": "2191",
"license": "mit",
"hash": 2498054354055019500,
"line_mean": 29.8591549296,
"line_max": 79,
"alpha_frac": 0.5960748517,
"autogenerated": false,
"ratio": 3.7452991452991453,
"config_test": false,
"h... |
__author__ = 'alex'
import requests
from lxml import objectify
class GrammarChecker():
USELESS_RULES = ["WHITESPACE_RULE", "EN_UNPAIRED_BRACKETS", "EN_QUOTES", 'COMMA_PARENTHESIS_WHITESPACE']
USELESS_CATEGORY = ["Capitalization"]
def __init__(self, url, lang='en-US'):
self.url = url
self... | {
"repo_name": "aparij/EmailGrammar",
"path": "check_grammar.py",
"copies": "1",
"size": "1311",
"license": "mit",
"hash": 7479280391510994000,
"line_mean": 35.4166666667,
"line_max": 123,
"alpha_frac": 0.5751334859,
"autogenerated": false,
"ratio": 3.8558823529411765,
"config_test": false,
"h... |
__author__ = 'alex'
import requests
from .market import Market
from private_markets import cryptsy
class Cryptsy(Market):
def __init__(self):
super(Cryptsy, self).__init__()
self.update_rate = 60
self.fees = {"buy": {"fee": 0.002, "coin": "s_coin"}, "sell": {"fee": 0.003, "coin": "s_coin"... | {
"repo_name": "acontry/altcoin-arbitrage",
"path": "arbitrage/public_markets/cryptsy.py",
"copies": "1",
"size": "1609",
"license": "mit",
"hash": -6515328082566921000,
"line_mean": 37.3095238095,
"line_max": 103,
"alpha_frac": 0.5599751398,
"autogenerated": false,
"ratio": 3.5755555555555554,
... |
__author__ = 'alex'
import requests
from .market import Market
class Vircurex(Market):
def __init__(self):
super(Vircurex, self).__init__()
self.update_rate = 60
self.update_prices()
# self.triangular_arbitrage()
def update_depth(self):
url = 'https://api.vircurex.com/... | {
"repo_name": "acontry/altcoin-arbitrage",
"path": "arbitrage/public_markets/vircurex.py",
"copies": "1",
"size": "1456",
"license": "mit",
"hash": -9162045229499139000,
"line_mean": 31.3555555556,
"line_max": 74,
"alpha_frac": 0.5350274725,
"autogenerated": false,
"ratio": 3.3781902552204177,
... |
__author__ = 'Alex'
# noinspection PyMethodMayBeStatic
class JSONxVisitor(object):
def visit(self, node):
method_name = 'visit_' + node.__class__.__name__
method = getattr(self, method_name, self.visit_generic)
return method(node)
def visit_generic(self, node):
raise RuntimeEr... | {
"repo_name": "AlexYukikaze/JSONx",
"path": "JSONx/ast.py",
"copies": "1",
"size": "3242",
"license": "mit",
"hash": 247735780426796380,
"line_mean": 24.5275590551,
"line_max": 75,
"alpha_frac": 0.578038248,
"autogenerated": false,
"ratio": 3.8321513002364065,
"config_test": false,
"has_no_ke... |
__author__ = 'alex'
# This function is terrible don't use it
def triangular_arbitrage(self):
self.prices.pop('current', None)
self.prices.pop('last_updated', None)
for pair1 in self.prices:
pair1_name = pair1
if pair1_name[1] != 'BTC':
continue
for pair2 in self.prices... | {
"repo_name": "acontry/altcoin-arbitrage",
"path": "arbitrage/observers/triangulartraderbot.py",
"copies": "1",
"size": "2230",
"license": "mit",
"hash": 697730117431501400,
"line_mean": 42.7450980392,
"line_max": 110,
"alpha_frac": 0.4502242152,
"autogenerated": false,
"ratio": 3.741610738255033... |
__author__ = 'alex parij'
import requests
import simplejson as json
class API(object):
def __init__(self, base_url=None, api_key=None, cid=None, minor_rev=None, locale='en_US', currency_code='USD'):
self._base_url = base_url
self._store = {
"apiKey": api_key,
"cid": ci... | {
"repo_name": "aparij/eanapi",
"path": "eanapi/api.py",
"copies": "1",
"size": "4328",
"license": "mit",
"hash": -4297231479979952600,
"line_mean": 26.7435897436,
"line_max": 115,
"alpha_frac": 0.530961183,
"autogenerated": false,
"ratio": 3.67402376910017,
"config_test": false,
"has_no_keywo... |
__author__ = 'Alex Parkinson, Matt van Breugel'
global version
version = 'v0.1'
import urllib2
from lxml import html
from datetime import datetime, date, timedelta
import pytz
import pyFWI.FWIFunctions as FWI
import sqlite3
def is_dst(zonename):
"""
Description
-----------
Hmm...
... | {
"repo_name": "parko636/pyfwi",
"path": "bomScrape.py",
"copies": "1",
"size": "3734",
"license": "bsd-3-clause",
"hash": -3095798737715038700,
"line_mean": 38.7340425532,
"line_max": 164,
"alpha_frac": 0.5747188002,
"autogenerated": false,
"ratio": 3.0961857379767825,
"config_test": false,
"... |
__author__ = 'Alex P'
from google.appengine.ext import ndb
class user(ndb.Model):
uniqueGivenID = ndb.StringProperty() #good for checking isCurrentUser.
nickname = ndb.StringProperty()
picture = ndb.BlobKeyProperty()
pictureURL = ndb.StringProperty()
numSlogans = ndb.IntegerProperty()
email = ... | {
"repo_name": "petestreet/raygun-app-backend",
"path": "models.py",
"copies": "1",
"size": "1735",
"license": "mit",
"hash": -3978981187050640400,
"line_mean": 41.3414634146,
"line_max": 115,
"alpha_frac": 0.734870317,
"autogenerated": false,
"ratio": 3.6914893617021276,
"config_test": false,
... |
__author__ = 'Alex P'
import os
import logging
import webapp2
import models
import jinja2
template_path = os.path.join(os.path.dirname(__file__))
jinja2_env = jinja2.Environment(
loader=jinja2.FileSystemLoader(template_path),
autoescape=True
)
#a helper class
class Handler(webapp2.RequestHandler):
def... | {
"repo_name": "petestreet/raygun-app-backend",
"path": "frontsite.py",
"copies": "1",
"size": "1516",
"license": "mit",
"hash": -2402039631711540000,
"line_mean": 26.0892857143,
"line_max": 82,
"alpha_frac": 0.6965699208,
"autogenerated": false,
"ratio": 3.429864253393665,
"config_test": false,... |
__author__ = 'alexrdz'
import unicodecsv, csv
import xlrd
import datetime
from models import MonederoUser
from models import PreAccountStatement
from StatementProcessor import StatementProcessor
def parse(xlsfile, name_of_sheet):
"""
:param xlsfile: Excel file to be read
:param name_of_sheet: Name of... | {
"repo_name": "EnriqueRE/Estado-de-Cuenta",
"path": "Transaction Uploader/UserList.py",
"copies": "1",
"size": "4232",
"license": "apache-2.0",
"hash": 1684654630050975500,
"line_mean": 28.3888888889,
"line_max": 97,
"alpha_frac": 0.6368147448,
"autogenerated": false,
"ratio": 3.7551020408163267,... |
from natto import MeCab
# 31 + 32
with open("verbs.txt", "w+"): pass
text = open("neko.txt","r+")
res_file = open("verbs.txt", "a+")
reader = text.readlines()
for line in reader:
with MeCab('-F%f[0],%f[6]') as nm:
for n in nm.parse(line, as_nodes=True):
if not n.is_eos() and n.is_nor(... | {
"repo_name": "yasutaka/nlp_100",
"path": "alex/31-33.py",
"copies": "1",
"size": "1258",
"license": "mit",
"hash": 8824542614189609000,
"line_mean": 27.3170731707,
"line_max": 66,
"alpha_frac": 0.46921797,
"autogenerated": false,
"ratio": 2.6770601336302895,
"config_test": false,
"has_no_key... |
__author__ = 'Alex Rogozhnikov'
import functools
from ..einops import TransformRecipe, _prepare_transformation_recipe
from .. import EinopsError
class RearrangeMixin:
"""
Rearrange layer behaves identically to einops.rearrange operation.
:param pattern: str, rearrangement pattern
:param axes_length... | {
"repo_name": "arogozhnikov/einops",
"path": "einops/layers/__init__.py",
"copies": "1",
"size": "2689",
"license": "mit",
"hash": 3885976044842920400,
"line_mean": 34.3815789474,
"line_max": 120,
"alpha_frac": 0.6355522499,
"autogenerated": false,
"ratio": 3.9955423476968797,
"config_test": fa... |
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