hexsha
string
size
int64
ext
string
lang
string
max_stars_repo_path
string
max_stars_repo_name
string
max_stars_repo_head_hexsha
string
max_stars_repo_licenses
list
max_stars_count
int64
max_stars_repo_stars_event_min_datetime
string
max_stars_repo_stars_event_max_datetime
string
max_issues_repo_path
string
max_issues_repo_name
string
max_issues_repo_head_hexsha
string
max_issues_repo_licenses
list
max_issues_count
int64
max_issues_repo_issues_event_min_datetime
string
max_issues_repo_issues_event_max_datetime
string
max_forks_repo_path
string
max_forks_repo_name
string
max_forks_repo_head_hexsha
string
max_forks_repo_licenses
list
max_forks_count
int64
max_forks_repo_forks_event_min_datetime
string
max_forks_repo_forks_event_max_datetime
string
content
string
avg_line_length
float64
max_line_length
int64
alphanum_fraction
float64
qsc_code_num_words_quality_signal
int64
qsc_code_num_chars_quality_signal
float64
qsc_code_mean_word_length_quality_signal
float64
qsc_code_frac_words_unique_quality_signal
float64
qsc_code_frac_chars_top_2grams_quality_signal
float64
qsc_code_frac_chars_top_3grams_quality_signal
float64
qsc_code_frac_chars_top_4grams_quality_signal
float64
qsc_code_frac_chars_dupe_5grams_quality_signal
float64
qsc_code_frac_chars_dupe_6grams_quality_signal
float64
qsc_code_frac_chars_dupe_7grams_quality_signal
float64
qsc_code_frac_chars_dupe_8grams_quality_signal
float64
qsc_code_frac_chars_dupe_9grams_quality_signal
float64
qsc_code_frac_chars_dupe_10grams_quality_signal
float64
qsc_code_frac_chars_replacement_symbols_quality_signal
float64
qsc_code_frac_chars_digital_quality_signal
float64
qsc_code_frac_chars_whitespace_quality_signal
float64
qsc_code_size_file_byte_quality_signal
float64
qsc_code_num_lines_quality_signal
float64
qsc_code_num_chars_line_max_quality_signal
float64
qsc_code_num_chars_line_mean_quality_signal
float64
qsc_code_frac_chars_alphabet_quality_signal
float64
qsc_code_frac_chars_comments_quality_signal
float64
qsc_code_cate_xml_start_quality_signal
float64
qsc_code_frac_lines_dupe_lines_quality_signal
float64
qsc_code_cate_autogen_quality_signal
float64
qsc_code_frac_lines_long_string_quality_signal
float64
qsc_code_frac_chars_string_length_quality_signal
float64
qsc_code_frac_chars_long_word_length_quality_signal
float64
qsc_code_frac_lines_string_concat_quality_signal
float64
qsc_code_cate_encoded_data_quality_signal
float64
qsc_code_frac_chars_hex_words_quality_signal
float64
qsc_code_frac_lines_prompt_comments_quality_signal
float64
qsc_code_frac_lines_assert_quality_signal
float64
qsc_codepython_cate_ast_quality_signal
float64
qsc_codepython_frac_lines_func_ratio_quality_signal
float64
qsc_codepython_cate_var_zero_quality_signal
bool
qsc_codepython_frac_lines_pass_quality_signal
float64
qsc_codepython_frac_lines_import_quality_signal
float64
qsc_codepython_frac_lines_simplefunc_quality_signal
float64
qsc_codepython_score_lines_no_logic_quality_signal
float64
qsc_codepython_frac_lines_print_quality_signal
float64
qsc_code_num_words
int64
qsc_code_num_chars
int64
qsc_code_mean_word_length
int64
qsc_code_frac_words_unique
null
qsc_code_frac_chars_top_2grams
int64
qsc_code_frac_chars_top_3grams
int64
qsc_code_frac_chars_top_4grams
int64
qsc_code_frac_chars_dupe_5grams
int64
qsc_code_frac_chars_dupe_6grams
int64
qsc_code_frac_chars_dupe_7grams
int64
qsc_code_frac_chars_dupe_8grams
int64
qsc_code_frac_chars_dupe_9grams
int64
qsc_code_frac_chars_dupe_10grams
int64
qsc_code_frac_chars_replacement_symbols
int64
qsc_code_frac_chars_digital
int64
qsc_code_frac_chars_whitespace
int64
qsc_code_size_file_byte
int64
qsc_code_num_lines
int64
qsc_code_num_chars_line_max
int64
qsc_code_num_chars_line_mean
int64
qsc_code_frac_chars_alphabet
int64
qsc_code_frac_chars_comments
int64
qsc_code_cate_xml_start
int64
qsc_code_frac_lines_dupe_lines
int64
qsc_code_cate_autogen
int64
qsc_code_frac_lines_long_string
int64
qsc_code_frac_chars_string_length
int64
qsc_code_frac_chars_long_word_length
int64
qsc_code_frac_lines_string_concat
null
qsc_code_cate_encoded_data
int64
qsc_code_frac_chars_hex_words
int64
qsc_code_frac_lines_prompt_comments
int64
qsc_code_frac_lines_assert
int64
qsc_codepython_cate_ast
int64
qsc_codepython_frac_lines_func_ratio
int64
qsc_codepython_cate_var_zero
int64
qsc_codepython_frac_lines_pass
int64
qsc_codepython_frac_lines_import
int64
qsc_codepython_frac_lines_simplefunc
int64
qsc_codepython_score_lines_no_logic
int64
qsc_codepython_frac_lines_print
int64
effective
string
hits
int64
4a6b2e5b7cf0173afb424be4c44105af0dae9900
7,577
py
Python
scripts/utils/import_languages.py
mozilla-releng/staging-mozilla-vpn-client
f31d3762a607ccf2d7c6a016f7b800305fbf0113
[ "Apache-2.0" ]
null
null
null
scripts/utils/import_languages.py
mozilla-releng/staging-mozilla-vpn-client
f31d3762a607ccf2d7c6a016f7b800305fbf0113
[ "Apache-2.0" ]
null
null
null
scripts/utils/import_languages.py
mozilla-releng/staging-mozilla-vpn-client
f31d3762a607ccf2d7c6a016f7b800305fbf0113
[ "Apache-2.0" ]
null
null
null
#! /usr/bin/env python3 # This Source Code Form is subject to the terms of the Mozilla Public # License, v. 2.0. If a copy of the MPL was not distributed with this # file, You can obtain one at http://mozilla.org/MPL/2.0/. import argparse import xml.etree.ElementTree as ET import os import sys import shutil import ate...
35.57277
121
0.665171
1,057
7,577
4.705771
0.305582
0.021713
0.028146
0.026538
0.205468
0.145959
0.090269
0.060314
0.060314
0.020105
0
0.025207
0.17276
7,577
212
122
35.740566
0.768347
0.112973
0
0.18239
0
0.018868
0.440794
0.121696
0
0
0
0
0
1
0.018868
false
0.006289
0.056604
0
0.08805
0.062893
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
4a6e93c38ff63c100497bb656432f8f40340791b
1,026
py
Python
cogs/filter.py
Velgaster/Discord-User-Vote
4aacc0bf01a11b948fa5355a3775ef8c7ae9751e
[ "MIT" ]
null
null
null
cogs/filter.py
Velgaster/Discord-User-Vote
4aacc0bf01a11b948fa5355a3775ef8c7ae9751e
[ "MIT" ]
null
null
null
cogs/filter.py
Velgaster/Discord-User-Vote
4aacc0bf01a11b948fa5355a3775ef8c7ae9751e
[ "MIT" ]
null
null
null
from discord.ext import commands import discord def setup(client): client.add_cog(KeyWordFilter(client)) class KeyWordFilter(commands.Cog): def __init__(self, client): self.client = client self.log_ch = self.client.get_channel(int(self.client.SETTINGS.LOG_CHANNEL)) @commands.Cog.listene...
35.37931
84
0.665692
141
1,026
4.730496
0.404255
0.089955
0.058471
0.076462
0.08096
0.08096
0
0
0
0
0
0
0.210526
1,026
28
85
36.642857
0.823457
0
0
0
0
0
0.061404
0
0
0
0
0
0
1
0.090909
false
0
0.090909
0
0.227273
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
4a6fe4cb292136ed5cb190cbef1dbace08d2c9c3
1,975
py
Python
api/app.py
sai-krishna-msk/KickAssist
7fb256e3ef4beff231332f6491ebb975f3fe4b43
[ "MIT" ]
null
null
null
api/app.py
sai-krishna-msk/KickAssist
7fb256e3ef4beff231332f6491ebb975f3fe4b43
[ "MIT" ]
7
2021-06-08T21:18:49.000Z
2022-03-12T00:24:33.000Z
api/app.py
sai-krishna-msk/KickAssist
7fb256e3ef4beff231332f6491ebb975f3fe4b43
[ "MIT" ]
null
null
null
from ml_model.model import KickModel import numpy as np import pandas as pd import eli5 import joblib import flask from flask import Flask, render_template, request, jsonify app = Flask(__name__) model_oh = joblib.load('ml_model/estimators/model_oh.sav') model_hel = joblib.load('ml_model/estimators/model_hel.sav') e...
33.474576
132
0.716456
261
1,975
5.141762
0.302682
0.031297
0.044709
0.063338
0.395678
0.395678
0.264531
0.264531
0.264531
0.264531
0
0.003005
0.157468
1,975
59
133
33.474576
0.803486
0
0
0
0
0.020833
0.243927
0.144737
0
0
0
0
0
1
0.041667
false
0
0.145833
0
0.229167
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
4a70669d9d055da240cf688e557bf0a87257569e
2,810
py
Python
snowddl/resolver/primary_key.py
littleK0i/SnowDDL
b24cb3676e41fec8876d61a101ba242e7272a18f
[ "Apache-2.0" ]
21
2022-02-10T16:52:03.000Z
2022-03-18T15:27:18.000Z
snowddl/resolver/primary_key.py
littleK0i/SnowDDL
b24cb3676e41fec8876d61a101ba242e7272a18f
[ "Apache-2.0" ]
null
null
null
snowddl/resolver/primary_key.py
littleK0i/SnowDDL
b24cb3676e41fec8876d61a101ba242e7272a18f
[ "Apache-2.0" ]
1
2022-03-05T11:02:42.000Z
2022-03-05T11:02:42.000Z
from snowddl.blueprint import PrimaryKeyBlueprint from snowddl.resolver.abc_schema_object_resolver import AbstractSchemaObjectResolver, ResolveResult, ObjectType class PrimaryKeyResolver(AbstractSchemaObjectResolver): def get_object_type(self) -> ObjectType: return ObjectType.PRIMARY_KEY def get_exis...
36.973684
111
0.5879
307
2,810
5.175896
0.218241
0.056639
0.053493
0.052863
0.293266
0.28068
0.24292
0.221523
0.178729
0.178729
0
0
0.279359
2,810
75
112
37.466667
0.784691
0
0
0.206897
0
0
0.238434
0.044128
0
0
0
0
0
1
0.103448
false
0
0.034483
0.034483
0.275862
0.086207
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
4a713700e9c156f74125bcaeca0299290201d914
675
py
Python
modules/module0/02_datastructures_and_geometry/datastructures_2b.py
tetov/ITA19
1af68a8885caf83acd98f4136d0286539ccbe63b
[ "MIT" ]
7
2019-11-13T20:29:54.000Z
2020-02-26T14:30:54.000Z
modules/module0/02_datastructures_and_geometry/datastructures_2b.py
GeneKao/ITA19
c4b10dc183599eed4ed60d922b6ef5922d173bdb
[ "MIT" ]
4
2019-11-07T20:57:51.000Z
2020-03-04T11:43:18.000Z
modules/module0/02_datastructures_and_geometry/datastructures_2b.py
GeneKao/ITA19
c4b10dc183599eed4ed60d922b6ef5922d173bdb
[ "MIT" ]
6
2019-10-30T13:25:54.000Z
2020-02-14T14:06:09.000Z
import os import compas from compas.datastructures import Mesh from compas_rhino.artists import MeshArtist HERE = os.path.dirname(__file__) DATA = os.path.join(HERE, 'data') FILE = os.path.join(DATA, 'faces.obj') mesh = Mesh.from_obj(FILE) artist = MeshArtist(mesh, layer="Mesh") artist.draw_vertices( color={ke...
25
94
0.722963
107
675
4.392523
0.392523
0.085106
0.051064
0.076596
0.085106
0
0
0
0
0
0
0.032534
0.134815
675
26
95
25.961538
0.77226
0
0
0
0
0
0.025185
0
0
0
0
0
0
1
0
false
0
0.222222
0
0.222222
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
4a73c0e8a1979c239e091749b325602ad4a40468
5,620
py
Python
setup.py
IntuitionEngineeringTeam/RedBlackPy
99630408153bea7494415c402eb2d9881f3168ee
[ "Apache-2.0" ]
12
2018-08-24T20:46:38.000Z
2022-01-20T16:25:23.000Z
setup.py
IntuitionEngineeringTeam/RedBlackPy
99630408153bea7494415c402eb2d9881f3168ee
[ "Apache-2.0" ]
1
2019-04-02T04:19:58.000Z
2019-04-02T04:19:58.000Z
setup.py
IntuitionEngineeringTeam/RedBlackPy
99630408153bea7494415c402eb2d9881f3168ee
[ "Apache-2.0" ]
3
2018-07-05T22:47:27.000Z
2019-05-25T06:40:40.000Z
# # Created by Soldoskikh Kirill. # Copyright 2018 Intuition. All rights reserved. # import os import platform from setuptools import setup from setuptools.command.build_ext import build_ext from distutils.extension import Extension from Cython.Build import cythonize from rbp_setup_tools.code_generation import gener...
44.251969
108
0.57242
604
5,620
5.10596
0.31457
0.032101
0.057069
0.034047
0.357977
0.289559
0.259079
0.182555
0.182555
0.182555
0
0.014856
0.269395
5,620
126
109
44.603175
0.73624
0.070996
0
0.29
0
0
0.287085
0.179428
0
0
0
0
0
1
0
false
0
0.08
0
0.08
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
4a7405fc354c53785ef8307b7ce20355175f5c8f
7,320
py
Python
conversationkg/kgs/writers.py
INDElab/conversationkg
8bfe09b0afb4954f633a9287f723c61dcd21ce46
[ "Apache-2.0" ]
3
2021-01-18T10:07:44.000Z
2021-05-27T07:39:35.000Z
conversationkg/kgs/writers.py
INDElab/conversationkg
8bfe09b0afb4954f633a9287f723c61dcd21ce46
[ "Apache-2.0" ]
3
2020-12-09T23:20:27.000Z
2021-03-06T11:08:24.000Z
conversationkg/kgs/writers.py
INDElab/conversationkg
8bfe09b0afb4954f633a9287f723c61dcd21ce46
[ "Apache-2.0" ]
1
2021-02-19T12:10:11.000Z
2021-02-19T12:10:11.000Z
from ..conversations.corpus import Conversation from ..conversations.emails import Email from collections import Counter import matplotlib import pandas as pd import json class JSONWriter: def __init__(self, kg): self.kg = kg self.entities = kg.entities() self.triples = kg.triples ...
30.247934
124
0.454645
747
7,320
4.287818
0.228916
0.019981
0.022479
0.024352
0.280674
0.234468
0.191383
0.114268
0.114268
0.114268
0
0.009716
0.451639
7,320
242
125
30.247934
0.788241
0.008197
0
0.150943
0
0
0.070572
0.025086
0
0
0
0
0
1
0.081761
false
0.012579
0.044025
0
0.18239
0.012579
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
4a74f67398645a5ea142cd4ebc8cc51cbdd14233
590
py
Python
model-test.py
shikew/Handwriting-calculator
5e0da9f8ceac6dcc815139c6855dfc6fb5af909f
[ "Apache-2.0" ]
null
null
null
model-test.py
shikew/Handwriting-calculator
5e0da9f8ceac6dcc815139c6855dfc6fb5af909f
[ "Apache-2.0" ]
null
null
null
model-test.py
shikew/Handwriting-calculator
5e0da9f8ceac6dcc815139c6855dfc6fb5af909f
[ "Apache-2.0" ]
1
2019-09-11T11:48:47.000Z
2019-09-11T11:48:47.000Z
import numpy as np from PIL import Image from keras.models import load_model img_gray = Image.open('1002.png') number = np.array(img_gray) print(number.shape) print('准备的图片的shape:',number.flatten().shape) print('原number:',number) number = number.astype('float32') number = number/255 #归一化 number = number.flatten() pri...
28.095238
48
0.749153
86
590
5.034884
0.534884
0.110855
0
0
0
0
0
0
0
0
0
0.027933
0.089831
590
21
49
28.095238
0.778399
0.240678
0
0
0
0
0.146396
0
0
0
0
0
0
1
0
false
0
0.214286
0
0.214286
0.357143
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
4a75b7b70277fd3cd807924be5321a95f06ea318
72,121
py
Python
iblviewer/volume.py
nantille/iblviewer
a5dad67e8f4b99a535297ba0803caf07b1107ca1
[ "MIT" ]
null
null
null
iblviewer/volume.py
nantille/iblviewer
a5dad67e8f4b99a535297ba0803caf07b1107ca1
[ "MIT" ]
null
null
null
iblviewer/volume.py
nantille/iblviewer
a5dad67e8f4b99a535297ba0803caf07b1107ca1
[ "MIT" ]
null
null
null
from dataclasses import dataclass, field from typing import Mapping, List, Any from datetime import datetime import logging import pandas as pd import glob import numpy as np import logging import os from collections import OrderedDict import nrrd import vtk import vedo from vtk.util.numpy_support import numpy_to_vtk ...
39.867883
119
0.609892
8,950
72,121
4.792626
0.118994
0.018044
0.007134
0.001958
0.232643
0.179023
0.152049
0.123257
0.109619
0.093346
0
0.008817
0.309605
72,121
1,809
120
39.867883
0.852607
0.282484
0
0.244094
0
0
0.014437
0.002358
0
0
0
0.002764
0
1
0.07185
false
0.003937
0.021654
0
0.207677
0.003937
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
4a76ff4e7600c0692264f843891e33f896e8b3a4
12,670
py
Python
modeling/dataset.py
LaudateCorpus1/ml-cread
b5d5aa87faa0ddad0b41b6b0672395a8bf6147ae
[ "AML" ]
18
2021-05-25T17:06:46.000Z
2021-11-08T09:47:48.000Z
modeling/dataset.py
LaudateCorpus1/ml-cread
b5d5aa87faa0ddad0b41b6b0672395a8bf6147ae
[ "AML" ]
null
null
null
modeling/dataset.py
LaudateCorpus1/ml-cread
b5d5aa87faa0ddad0b41b6b0672395a8bf6147ae
[ "AML" ]
6
2021-06-03T21:29:34.000Z
2022-03-26T11:38:37.000Z
# # For licensing see accompanying LICENSE file. # Copyright (C) 2021 Apple Inc. All Rights Reserved. # ''' Dataset file ''' import sys import time import json import copy from itertools import chain from tqdm import tqdm, trange import torch from torch.utils.data import DataLoader, RandomSampler SPECIAL_TOKENS = {...
38.510638
139
0.728808
1,791
12,670
4.839754
0.125628
0.035994
0.024919
0.035302
0.332833
0.278034
0.23731
0.203392
0.176857
0.165321
0
0.009073
0.156196
12,670
328
140
38.628049
0.801702
0.126598
0
0.134199
0
0
0.110381
0.002281
0
0
0
0.003049
0.04329
1
0.051948
false
0.004329
0.034632
0.008658
0.125541
0.004329
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
4a770f589bb75a8f2ce9da24f74f5b68103d69bf
2,431
py
Python
hy/lex/lexer.py
schuster-rainer/hy
d969ed63d67c4a9070fd41a8fbff35da845e0619
[ "MIT" ]
12
2015-01-01T21:21:31.000Z
2021-06-14T19:51:59.000Z
hy/lex/lexer.py
schuster-rainer/hy
d969ed63d67c4a9070fd41a8fbff35da845e0619
[ "MIT" ]
null
null
null
hy/lex/lexer.py
schuster-rainer/hy
d969ed63d67c4a9070fd41a8fbff35da845e0619
[ "MIT" ]
2
2016-01-17T21:59:29.000Z
2016-09-06T20:56:41.000Z
# Copyright (c) 2013 Nicolas Dandrimont <nicolas.dandrimont@crans.org> # # 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 use,...
34.239437
76
0.667626
369
2,431
4.373984
0.471545
0.049566
0.026022
0.024783
0.045849
0.037175
0
0
0
0
0
0.006477
0.174414
2,431
70
77
34.728571
0.797708
0.534348
0
0
0
0
0.527978
0
0
0
0
0
0
1
0
false
0
0.030303
0
0.030303
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
4a77208eebfdf92ef53ffabde97b664e8625e12d
1,319
py
Python
week6/shuffle.py
solideveloper/afs-210
2ba0bb7c7617cd3169907458f657696a6987689d
[ "Apache-2.0" ]
1
2022-01-06T01:22:17.000Z
2022-01-06T01:22:17.000Z
week6/shuffle.py
solideveloper/afs-210
2ba0bb7c7617cd3169907458f657696a6987689d
[ "Apache-2.0" ]
null
null
null
week6/shuffle.py
solideveloper/afs-210
2ba0bb7c7617cd3169907458f657696a6987689d
[ "Apache-2.0" ]
null
null
null
# Python provides a built-in method called random.shuffle that will shuffle the list data type. Do not use this. # For this assignment, you are to create your own shuffle algorithm that will take as input a sorted list and randomly shuffle the items before returning the list. Try to make your algorithm as efficient a...
54.958333
217
0.749052
222
1,319
4.45045
0.513514
0.035425
0.126518
0.121457
0.121457
0.121457
0.121457
0.121457
0.121457
0.121457
0
0.021257
0.179682
1,319
24
218
54.958333
0.891867
0.683093
0
0.307692
0
0
0
0
0
0
0
0
0
1
0.076923
false
0
0.076923
0
0.230769
0.384615
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
4a79466df9295fa5ad7c3a62c359310229ec684a
5,647
py
Python
tadataka/dataset/new_tsukuba.py
IshitaTakeshi/Tadataka
852c7afb904503005e51884408e1492ef0be836f
[ "Apache-2.0" ]
54
2019-11-15T16:30:34.000Z
2022-01-13T15:18:54.000Z
tadataka/dataset/new_tsukuba.py
IshitaTakeshi/Tadataka
852c7afb904503005e51884408e1492ef0be836f
[ "Apache-2.0" ]
11
2019-02-28T08:28:24.000Z
2020-04-07T04:47:12.000Z
tadataka/dataset/new_tsukuba.py
IshitaTakeshi/Tadataka
852c7afb904503005e51884408e1492ef0be836f
[ "Apache-2.0" ]
1
2020-02-26T13:59:40.000Z
2020-02-26T13:59:40.000Z
import csv import os from pathlib import Path from xml.etree import ElementTree as ET from tqdm import tqdm from scipy.spatial.transform import Rotation from skimage.io import imread import numpy as np from tadataka.camera import CameraModel, CameraParameters, FOV from tadataka.dataset.frame import Frame from tadatak...
34.644172
81
0.673278
777
5,647
4.646075
0.239382
0.037673
0.015235
0.016621
0.20554
0.100831
0.018837
0
0
0
0
0.009914
0.214096
5,647
162
82
34.858025
0.803515
0.098282
0
0
0
0
0.04234
0
0
0
0
0.006173
0.018868
1
0.113208
false
0
0.113208
0.018868
0.301887
0.028302
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
4a798e4f49354ed1b300d7ffad5bbb4e1e929e1a
2,015
py
Python
krogon/maybe.py
enamrik/krogon
a41a10ed346b7198509929ed9ba1e9fcf778dc78
[ "MIT" ]
1
2020-03-02T14:17:02.000Z
2020-03-02T14:17:02.000Z
krogon/maybe.py
enamrik/krogon
a41a10ed346b7198509929ed9ba1e9fcf778dc78
[ "MIT" ]
null
null
null
krogon/maybe.py
enamrik/krogon
a41a10ed346b7198509929ed9ba1e9fcf778dc78
[ "MIT" ]
null
null
null
from typing import Callable, TypeVar, Union, Tuple from krogon.infix import Infix A = TypeVar('A') B = TypeVar('B') E = TypeVar('E') Maybe = Union[Tuple['just', A], Tuple['nothing']] def just(value=None): return "just", value def nothing(): return "nothing", None def from_value(value) -> Maybe[B]: r...
24.573171
93
0.629777
291
2,015
4.19244
0.168385
0.039344
0.054098
0.041803
0.27377
0.188525
0.169672
0.169672
0.140984
0.140984
0
0.007653
0.221836
2,015
81
94
24.876543
0.770408
0
0
0.214286
0
0
0.058561
0
0
0
0
0
0
1
0.178571
false
0
0.035714
0.089286
0.5
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
4a7c6e1277408f69b722e24dda7d218cc70dda0f
1,192
py
Python
migrations/versions/576712576c48_added_model_for_photo_comments.py
Torniojaws/vortech-backend
f775a97eeae089fa720088d86fe92d40bc5d65bc
[ "MIT" ]
null
null
null
migrations/versions/576712576c48_added_model_for_photo_comments.py
Torniojaws/vortech-backend
f775a97eeae089fa720088d86fe92d40bc5d65bc
[ "MIT" ]
93
2017-09-01T22:24:10.000Z
2021-12-22T14:07:06.000Z
migrations/versions/576712576c48_added_model_for_photo_comments.py
Torniojaws/vortech-backend
f775a97eeae089fa720088d86fe92d40bc5d65bc
[ "MIT" ]
null
null
null
"""Added model for photo comments Revision ID: 576712576c48 Revises: 75bb906df167 Create Date: 2018-03-30 02:06:22.877079 """ from alembic import op import sqlalchemy as sa # revision identifiers, used by Alembic. revision = '576712576c48' down_revision = '75bb906df167' branch_labels = None depends_o...
30.564103
81
0.672819
134
1,192
5.947761
0.492537
0.060226
0.075282
0.105395
0.283563
0.223338
0.110414
0.110414
0
0
0
0.058645
0.170302
1,192
38
82
31.368421
0.747219
0.261745
0
0
0
0
0.191697
0
0
0
0
0
0
1
0.1
false
0
0.1
0
0.2
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
4a7f99985562db134bffd977ed750d635522a7a2
12,364
py
Python
usaspending_api/etl/helpers.py
truthiswill/usaspending-api
bd7d915442e2ec94cc830c480ceeffd4479be6c0
[ "CC0-1.0" ]
null
null
null
usaspending_api/etl/helpers.py
truthiswill/usaspending-api
bd7d915442e2ec94cc830c480ceeffd4479be6c0
[ "CC0-1.0" ]
3
2020-02-12T01:16:46.000Z
2021-06-10T20:36:57.000Z
usaspending_api/etl/helpers.py
truthiswill/usaspending-api
bd7d915442e2ec94cc830c480ceeffd4479be6c0
[ "CC0-1.0" ]
null
null
null
from datetime import datetime import warnings import logging from django.db.models import Q, Case, Value, When from django.core.cache import caches, CacheKeyWarning import django.apps from usaspending_api.references.models import Agency, Location, RefCountryCode from usaspending_api.references.helpers import canonica...
38.397516
119
0.63604
1,612
12,364
4.656328
0.230769
0.031974
0.021316
0.015321
0.111111
0.061151
0.021583
0.021583
0.021583
0.021583
0
0.006403
0.280006
12,364
321
120
38.517134
0.836778
0.260514
0
0.105263
0
0
0.088818
0.014158
0
0
0
0
0
1
0.063158
false
0
0.052632
0
0.210526
0.005263
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
4a80119456047b966a3757d7fd0f105dc0f5c4f6
9,193
py
Python
code/mapplot.py
young-astronomer/vlpy
7fd434d307a7cc3593f84a7c6c2f4a4a86865afe
[ "Apache-2.0" ]
null
null
null
code/mapplot.py
young-astronomer/vlpy
7fd434d307a7cc3593f84a7c6c2f4a4a86865afe
[ "Apache-2.0" ]
null
null
null
code/mapplot.py
young-astronomer/vlpy
7fd434d307a7cc3593f84a7c6c2f4a4a86865afe
[ "Apache-2.0" ]
null
null
null
#!/usr/bin/env python3 # -*- coding: utf-8 -*- """ Created on Wed Oct 21 11:11:56 2020 This program is use to plot polarization map from vlbi fits image. You should specify the input fits images by -i or --infile, output file by -o or --output, contour levs by -l or --levs contour base by -c or --cmul polarization...
30.042484
101
0.617753
1,524
9,193
3.694226
0.22769
0.019893
0.020782
0.019183
0.286856
0.187034
0.171226
0.126465
0.117052
0.117052
0
0.051597
0.175677
9,193
306
102
30.042484
0.691343
0.186011
0
0.087866
0
0.012552
0.103694
0.003034
0
0
0
0
0
1
0.050209
false
0
0.033473
0
0.104603
0.008368
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
4a81890c9e9eec4855a38a91238cf619244d9278
2,174
py
Python
umbrella/api/v1/router.py
pizhi/umbrella
95027e6e11a6c8df2ab5f7c202b0c1d2183f839a
[ "Apache-2.0" ]
1
2018-01-13T11:45:24.000Z
2018-01-13T11:45:24.000Z
umbrella/api/v1/router.py
pizhi/umbrella
95027e6e11a6c8df2ab5f7c202b0c1d2183f839a
[ "Apache-2.0" ]
null
null
null
umbrella/api/v1/router.py
pizhi/umbrella
95027e6e11a6c8df2ab5f7c202b0c1d2183f839a
[ "Apache-2.0" ]
2
2018-01-01T11:39:49.000Z
2018-08-07T07:16:45.000Z
# Copyright 2011 OpenStack Foundation # All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); you may # not use this file except in compliance with the License. You may obtain # a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless requ...
36.233333
78
0.559798
224
2,174
5.303571
0.450893
0.074074
0.123737
0.159091
0.356061
0.277778
0.247475
0
0
0
0
0.006949
0.338086
2,174
59
79
36.847458
0.818624
0.297608
0
0.363636
0
0
0.129973
0.013926
0
0
0
0
0
1
0.030303
false
0
0.060606
0
0.121212
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
4a8279873b5f73ab9eb14c009ec624c039c590a5
943
py
Python
exemples/test_thomson_simu.py
butala/TomograPy
a1da41f1e0b7406a1b770e56428789c54175de20
[ "CECILL-B" ]
7
2016-07-05T08:31:42.000Z
2022-03-31T20:24:13.000Z
exemples/test_thomson_simu.py
esoubrie/TomograPy
a1da41f1e0b7406a1b770e56428789c54175de20
[ "CECILL-B" ]
null
null
null
exemples/test_thomson_simu.py
esoubrie/TomograPy
a1da41f1e0b7406a1b770e56428789c54175de20
[ "CECILL-B" ]
4
2018-08-14T01:54:21.000Z
2022-03-10T19:44:43.000Z
#!/usr/bin/env python import time import numpy as np import tomograpy import lo # object obj = tomograpy.centered_cubic_map(10, 64) obj[:] = tomograpy.phantom.shepp_logan(obj.shape) # data radius = 200 a = tomograpy.fov(obj, radius) data = tomograpy.centered_stack(a, 128, n_images=60, radius=radius, max_lon=np.pi) # m...
30.419355
82
0.680806
155
943
4.077419
0.451613
0.075949
0.042722
0.071203
0.075949
0
0
0
0
0
0
0.032967
0.131495
943
30
83
31.433333
0.738706
0.112407
0
0.136364
0
0
0.094089
0
0
0
0
0
0
1
0
false
0
0.181818
0
0.181818
0.136364
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
4a845cfff802e634071ade849b849c82adc47ef1
395
py
Python
interactive_grabcut/repo/drag2draw.py
hiankun/py_sandbox
6623edd0c8ab17641e1ce09fba7da34c4865fc4f
[ "MIT" ]
null
null
null
interactive_grabcut/repo/drag2draw.py
hiankun/py_sandbox
6623edd0c8ab17641e1ce09fba7da34c4865fc4f
[ "MIT" ]
null
null
null
interactive_grabcut/repo/drag2draw.py
hiankun/py_sandbox
6623edd0c8ab17641e1ce09fba7da34c4865fc4f
[ "MIT" ]
null
null
null
# source: https://www.youtube.com/watch?v=U0sVp1xLiyo from tkinter import * def paint(event): color = 'red' x1, y1 = (event.x-1), (event.y-1) x2, y2 = (event.x+1), (event.y+1) c.create_oval(x1,y1,x2,y2,fill=color,outline=color) master = Tk() c = Canvas(master, width=600, height=400, bg='white') c.pa...
21.944444
55
0.648101
67
395
3.80597
0.671642
0.031373
0.054902
0.094118
0.109804
0.109804
0
0
0
0
0
0.062315
0.146835
395
17
56
23.235294
0.694362
0.129114
0
0
0
0
0.055556
0
0
0
0
0
0
1
0.090909
false
0
0.090909
0
0.181818
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
4a861f0810192c03917c1a4cb2de99fa5681f49e
14,913
py
Python
neutronclient/osc/v2/vpnaas/ipsec_site_connection.py
slawqo/python-neutronclient
ee08644c5f2424a40c70010dcf0fa2ad84809bfc
[ "Apache-2.0" ]
120
2015-01-07T00:38:58.000Z
2021-12-26T13:05:53.000Z
neutronclient/osc/v2/vpnaas/ipsec_site_connection.py
slawqo/python-neutronclient
ee08644c5f2424a40c70010dcf0fa2ad84809bfc
[ "Apache-2.0" ]
1
2021-08-11T18:42:30.000Z
2021-08-11T22:25:21.000Z
neutronclient/osc/v2/vpnaas/ipsec_site_connection.py
slawqo/python-neutronclient
ee08644c5f2424a40c70010dcf0fa2ad84809bfc
[ "Apache-2.0" ]
153
2015-01-05T16:50:50.000Z
2021-09-13T12:01:23.000Z
# Copyright 2017 FUJITSU LIMITED # All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); you may # not use this file except in compliance with the License. You may obtain # a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless req...
39.768
79
0.632468
1,720
14,913
5.191279
0.153488
0.068317
0.078732
0.030239
0.465562
0.381454
0.329376
0.321425
0.287266
0.279875
0
0.002105
0.267284
14,913
374
80
39.874332
0.815045
0.040502
0
0.339506
0
0
0.229181
0.03331
0
0
0
0
0
1
0.040123
false
0
0.030864
0.003086
0.135802
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
4a893fcf944a3942d0a9e7e6cc93c141d9894e31
13,620
py
Python
sushichef.py
RechercheTech/sushi-chef-arvind-gupta-toys
2b381d8942c16ed16b4a44d8fc020fe0a81a18c0
[ "MIT" ]
1
2020-05-10T06:16:48.000Z
2020-05-10T06:16:48.000Z
sushichef.py
RechercheTech/sushi-chef-arvind-gupta-toys
2b381d8942c16ed16b4a44d8fc020fe0a81a18c0
[ "MIT" ]
5
2019-10-04T11:35:21.000Z
2020-05-25T14:19:41.000Z
sushichef.py
RechercheTech/sushi-chef-arvind-gupta-toys
2b381d8942c16ed16b4a44d8fc020fe0a81a18c0
[ "MIT" ]
3
2019-09-24T00:15:00.000Z
2020-02-06T16:25:36.000Z
#!/usr/bin/env python import os import requests import re import shutil from arvind import ArvindVideo, ArvindLanguage, YOUTUBE_CACHE_DIR from bs4 import BeautifulSoup from bs4.element import NavigableString from ricecooker.chefs import SushiChef from ricecooker.classes.files import YouTubeVideoFile from ricecooker...
37.01087
113
0.606608
1,583
13,620
4.933039
0.217309
0.026892
0.014086
0.011525
0.257011
0.189141
0.134076
0.101165
0.054296
0.034575
0
0.004099
0.301395
13,620
367
114
37.111717
0.816605
0.093906
0
0.174242
0
0
0.125216
0.010208
0
0
0
0
0
1
0.041667
false
0.015152
0.041667
0
0.121212
0.056818
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
4a89890f028ab800ae7dcb96dcff01c0b7e8d98a
1,184
py
Python
90-subsets-ii.py
yuenliou/leetcode
e8a1c6cae6547cbcb6e8494be6df685f3e7c837c
[ "MIT" ]
null
null
null
90-subsets-ii.py
yuenliou/leetcode
e8a1c6cae6547cbcb6e8494be6df685f3e7c837c
[ "MIT" ]
null
null
null
90-subsets-ii.py
yuenliou/leetcode
e8a1c6cae6547cbcb6e8494be6df685f3e7c837c
[ "MIT" ]
null
null
null
#!/usr/local/bin/python3.7 # -*- coding: utf-8 -*- from typing import List class Solution: def subsetsWithDup(self, nums: List[int]) -> List[List[int]]: """ 题解:https://leetcode-cn.com/problems/subsets/solution/c-zong-jie-liao-hui-su-wen-ti-lei-xing-dai-ni-gao-/ """ def backtrack(sta...
19.733333
112
0.516047
147
1,184
4.102041
0.585034
0.016584
0.014925
0.059701
0.109453
0.109453
0
0
0
0
0
0.028501
0.318412
1,184
59
113
20.067797
0.718711
0.15625
0
0
0
0
0.011111
0
0
0
0
0
0
1
0.142857
false
0
0.047619
0
0.285714
0.047619
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
4a8a19db97a47f9f1fc1395728868b9d716366fe
450
py
Python
tools/output_tool.py
climberwb/bert-pli
0e6eda7a23b7502c86eab4c0d889fad1bbb57155
[ "MIT" ]
5
2020-12-24T01:46:40.000Z
2022-03-18T19:15:10.000Z
tools/output_tool.py
climberwb/bert-pli
0e6eda7a23b7502c86eab4c0d889fad1bbb57155
[ "MIT" ]
1
2021-04-05T14:27:24.000Z
2021-04-05T14:27:24.000Z
tools/output_tool.py
climberwb/bert-pli
0e6eda7a23b7502c86eab4c0d889fad1bbb57155
[ "MIT" ]
4
2020-12-28T09:20:13.000Z
2021-12-10T13:33:21.000Z
import json from .accuracy_tool import gen_micro_macro_result def null_output_function(data, config, *args, **params): return "" def basic_output_function(data, config, *args, **params): which = config.get("output", "output_value").replace(" ", "").split(",") temp = gen_micro_macro_result(da...
25
77
0.653333
57
450
4.929825
0.561404
0.05694
0.092527
0.135231
0.241993
0.241993
0
0
0
0
0
0
0.211111
450
17
78
26.470588
0.791549
0
0
0
0
0
0.046189
0
0
0
0
0
0
1
0.181818
false
0
0.181818
0.090909
0.545455
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
4a8ae0336fc8e8f4551cb0d621a28672bac709c0
27,100
py
Python
python/drydock_provisioner/ingester/plugins/deckhand.py
Vjrx/airship-drydock
315fb9864e6d55a66d5266f76c160be55d22c98b
[ "Apache-2.0" ]
14
2018-05-19T11:58:22.000Z
2019-05-10T12:31:36.000Z
python/drydock_provisioner/ingester/plugins/deckhand.py
Vjrx/airship-drydock
315fb9864e6d55a66d5266f76c160be55d22c98b
[ "Apache-2.0" ]
10
2019-11-12T17:21:16.000Z
2021-11-10T18:16:06.000Z
python/drydock_provisioner/ingester/plugins/deckhand.py
Vjrx/airship-drydock
315fb9864e6d55a66d5266f76c160be55d22c98b
[ "Apache-2.0" ]
11
2018-06-05T16:21:18.000Z
2019-04-03T11:44:34.000Z
# Copyright 2017 AT&T Intellectual Property. All other rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required...
37.225275
108
0.573579
3,009
27,100
5.01429
0.168827
0.020414
0.016901
0.017895
0.258218
0.213746
0.178685
0.156482
0.139515
0.124934
0
0.003407
0.328561
27,100
727
109
37.276479
0.825786
0.146384
0
0.178344
0
0
0.104372
0.002126
0
0
0
0
0
1
0.046709
false
0
0.027601
0.006369
0.121019
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
4a8ca4ac28e4f99e7596ac67b54b694b5e38191d
5,517
py
Python
porting_tools/package_xml_porter.py
nreplogle/ros2-migration-tools
8e422731dea52df19da6de780319a17516f60f7c
[ "Apache-2.0" ]
92
2018-10-17T22:18:01.000Z
2022-03-19T22:03:16.000Z
porting_tools/package_xml_porter.py
nreplogle/ros2-migration-tools
8e422731dea52df19da6de780319a17516f60f7c
[ "Apache-2.0" ]
12
2019-02-21T22:29:15.000Z
2021-06-28T22:33:31.000Z
porting_tools/package_xml_porter.py
nreplogle/ros2-migration-tools
8e422731dea52df19da6de780319a17516f60f7c
[ "Apache-2.0" ]
19
2018-10-18T11:47:07.000Z
2022-02-04T18:41:03.000Z
# Copyright 2019 Amazon.com, Inc. or its affiliates. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"). # You may not use this file except in compliance with the License. # A copy of the License is located at # # http://www.apache.org/licenses/LICENSE-2.0 # # or in the "licens...
39.12766
104
0.649085
700
5,517
4.922857
0.278571
0.092571
0.037725
0.040627
0.219385
0.189495
0.172084
0.163088
0.130006
0.088799
0
0.00498
0.235635
5,517
140
105
39.407143
0.812189
0.236542
0
0.1625
0
0
0.103672
0.017987
0.0125
0
0
0
0
1
0.1375
false
0
0.0375
0
0.225
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
4a8eaddf7ae51bc116bee8d180b8c5c1f2cfecaf
4,739
py
Python
endpoints/api/permission_models_interface.py
giuseppe/quay
a1b7e4b51974edfe86f66788621011eef2667e6a
[ "Apache-2.0" ]
2,027
2019-11-12T18:05:48.000Z
2022-03-31T22:25:04.000Z
endpoints/api/permission_models_interface.py
giuseppe/quay
a1b7e4b51974edfe86f66788621011eef2667e6a
[ "Apache-2.0" ]
496
2019-11-12T18:13:37.000Z
2022-03-31T10:43:45.000Z
endpoints/api/permission_models_interface.py
giuseppe/quay
a1b7e4b51974edfe86f66788621011eef2667e6a
[ "Apache-2.0" ]
249
2019-11-12T18:02:27.000Z
2022-03-22T12:19:19.000Z
import sys from abc import ABCMeta, abstractmethod from collections import namedtuple from six import add_metaclass class SaveException(Exception): def __init__(self, other): self.traceback = sys.exc_info() super(SaveException, self).__init__(str(other)) class DeleteException(Exception): de...
21.15625
99
0.556447
432
4,739
5.791667
0.162037
0.08793
0.082734
0.097122
0.640687
0.605516
0.559952
0.533573
0.498401
0.439249
0
0
0.358303
4,739
223
100
21.251121
0.822756
0.226208
0
0.5
0
0
0.083361
0
0
0
0
0
0
1
0.159574
false
0
0.042553
0.031915
0.319149
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
4a8f1c2b21e9f7321bc8056b973b7bad4e6c12de
754
py
Python
configs/mot/tracktor/tracktor_faster-rcnn_r50_fpn_4e_mot17-public.py
sht47/mmtracking
5a25e418e9c598d1b576bce8702f5e156cbbefe7
[ "Apache-2.0" ]
12
2021-09-05T20:47:16.000Z
2022-03-23T07:00:35.000Z
configs/mot/tracktor/tracktor_faster-rcnn_r50_fpn_4e_mot17-public.py
hellock/mmtracking
a22a36b2055d80cf4a7a5ef3913849abb56defcb
[ "Apache-2.0" ]
2
2021-09-06T13:20:09.000Z
2022-01-13T05:36:14.000Z
configs/mot/tracktor/tracktor_faster-rcnn_r50_fpn_4e_mot17-public.py
hellock/mmtracking
a22a36b2055d80cf4a7a5ef3913849abb56defcb
[ "Apache-2.0" ]
1
2021-07-15T00:26:35.000Z
2021-07-15T00:26:35.000Z
_base_ = ['./tracktor_faster-rcnn_r50_fpn_4e_mot17-public-half.py'] model = dict( pretrains=dict( detector= # noqa: E251 'https://download.openmmlab.com/mmtracking/mot/faster_rcnn/faster-rcnn_r50_fpn_4e_mot17-ffa52ae7.pth' # noqa: E501 )) data_root = 'data/MOT17/' test_set = 'test' data = dict...
41.888889
123
0.708223
101
754
4.950495
0.425743
0.112
0.12
0.09
0.482
0.412
0.32
0.196
0.196
0
0
0.033281
0.16313
754
17
124
44.352941
0.759113
0.027851
0
0
0
0.058824
0.467123
0.310959
0
0
0
0
0
1
0
false
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
4a8f5a90f2c6e24db504d3e023a88b1bddaccca9
2,277
py
Python
browserstack/first_sample_build.py
Shaimyst/scrive_test
38e3ea0192885d1776d24afdbea110d73adc4e8b
[ "MIT" ]
null
null
null
browserstack/first_sample_build.py
Shaimyst/scrive_test
38e3ea0192885d1776d24afdbea110d73adc4e8b
[ "MIT" ]
null
null
null
browserstack/first_sample_build.py
Shaimyst/scrive_test
38e3ea0192885d1776d24afdbea110d73adc4e8b
[ "MIT" ]
null
null
null
from threading import Thread from time import sleep from selenium import webdriver from selenium.webdriver.common.keys import Keys from selenium.webdriver.common.desired_capabilities import DesiredCapabilities from selenium.common.exceptions import TimeoutException from selenium.webdriver.support.ui import WebDriverWai...
42.166667
149
0.700044
277
2,277
5.66065
0.465704
0.045918
0.053571
0.044005
0.131378
0.131378
0.131378
0.131378
0.096939
0
0
0.011111
0.16996
2,277
54
150
42.166667
0.818519
0.158103
0
0.137255
0
0.039216
0.358264
0.023013
0
0
0
0
0
1
0.019608
false
0.019608
0.156863
0
0.176471
0.019608
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
4a914cd003bec02fcf0ace8e2f7e5de8208c8146
11,024
py
Python
ISM_catalog_profile/scripts/ISM/ISM.py
rhmdnd/compliance-trestle-demos
1d92c91cca1d23cf707f82f035b2d58ec67c953a
[ "Apache-2.0" ]
10
2021-09-03T05:07:19.000Z
2022-03-26T13:24:51.000Z
ISM_catalog_profile/scripts/ISM/ISM.py
rhmdnd/compliance-trestle-demos
1d92c91cca1d23cf707f82f035b2d58ec67c953a
[ "Apache-2.0" ]
null
null
null
ISM_catalog_profile/scripts/ISM/ISM.py
rhmdnd/compliance-trestle-demos
1d92c91cca1d23cf707f82f035b2d58ec67c953a
[ "Apache-2.0" ]
4
2021-12-14T22:15:06.000Z
2022-03-29T16:16:19.000Z
#!/usr/bin/env python3 # # -*- mode:python; coding:utf-8 -*- # Copyright (c) 2020 IBM Corp. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # https://www.apache.org...
42.4
119
0.642144
1,375
11,024
4.947636
0.267636
0.017492
0.01029
0.022931
0.108923
0.062766
0.054388
0.030869
0
0
0
0.007886
0.263788
11,024
259
120
42.563707
0.830335
0.24873
0
0.081761
0
0.006289
0.119175
0.003604
0
0
0
0.007722
0.006289
1
0.075472
false
0
0.106918
0
0.232704
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
4a9405edbd8cfdcda2cba6e2d4bef4fc6c17c93b
806
py
Python
setup.py
cyberjunky/python-garminconnect-aio
fb913a15107edee5c5530f3bded7c553ec57923b
[ "MIT" ]
11
2021-06-08T14:55:33.000Z
2022-02-03T03:12:14.000Z
setup.py
cyberjunky/python-garminconnect-aio
fb913a15107edee5c5530f3bded7c553ec57923b
[ "MIT" ]
1
2021-08-07T09:24:35.000Z
2021-08-07T17:30:40.000Z
setup.py
cyberjunky/python-garminconnect-aio
fb913a15107edee5c5530f3bded7c553ec57923b
[ "MIT" ]
2
2021-06-04T15:34:22.000Z
2021-10-02T19:48:13.000Z
#!/usr/bin/env python from setuptools import setup with open("README.md") as readme_file: readme = readme_file.read() setup( author="Ron Klinkien", author_email="ron@cyberjunky.nl", classifiers=[ "Programming Language :: Python :: 3", "License :: OSI Approved :: MIT License", ...
29.851852
67
0.666253
92
806
5.728261
0.695652
0.091082
0
0
0
0
0
0
0
0
0
0.010654
0.184864
806
26
68
31
0.791476
0.024814
0
0
0
0
0.457325
0
0
0
0
0
0
1
0
false
0
0.045455
0
0.045455
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
4a940fa45e0ab9b5f708abce624a09bc0ed42b1a
9,513
py
Python
nova/tests/unit/virt/libvirt/fake_imagebackend.py
ChameleonCloud/nova
4bb9421b02b71f2b218278aa6f97abace871b111
[ "Apache-2.0" ]
1
2016-07-18T22:05:01.000Z
2016-07-18T22:05:01.000Z
nova/tests/unit/virt/libvirt/fake_imagebackend.py
ChameleonCloud/nova
4bb9421b02b71f2b218278aa6f97abace871b111
[ "Apache-2.0" ]
null
null
null
nova/tests/unit/virt/libvirt/fake_imagebackend.py
ChameleonCloud/nova
4bb9421b02b71f2b218278aa6f97abace871b111
[ "Apache-2.0" ]
1
2021-11-12T03:55:41.000Z
2021-11-12T03:55:41.000Z
# Copyright 2012 Grid Dynamics # All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); you may # not use this file except in compliance with the License. You may obtain # a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by...
41.723684
79
0.654157
1,222
9,513
4.930442
0.252864
0.014606
0.022407
0.027386
0.159502
0.098091
0.06639
0.045145
0.045145
0.045145
0
0.001602
0.278146
9,513
227
80
41.907489
0.875783
0.44087
0
0.119565
0
0
0.065813
0.054811
0
0
0
0
0
1
0.119565
false
0
0.173913
0.021739
0.380435
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
4a95eafd7882de8499fc568c3c76a78f53505995
6,671
py
Python
ershoufang/crawler_v2.py
zlikun/python-crawler-lianjia
7e7bf0cbd333486ee62ac015e72b96d6003c8713
[ "Apache-2.0" ]
2
2018-10-25T05:52:33.000Z
2021-12-22T06:39:30.000Z
ershoufang/crawler_v2.py
zlikun/python-crawler-lianjia
7e7bf0cbd333486ee62ac015e72b96d6003c8713
[ "Apache-2.0" ]
null
null
null
ershoufang/crawler_v2.py
zlikun/python-crawler-lianjia
7e7bf0cbd333486ee62ac015e72b96d6003c8713
[ "Apache-2.0" ]
2
2019-02-02T14:38:26.000Z
2020-07-21T01:57:17.000Z
""" 第二版:多进程二手房信息爬虫 1. 将爬虫分解为下载任务和解析任务(可以继续分解,但在本案中意义不大)两部分,两部分各使用一个子进程,相互通过数据管道通信 2. 下载任务内部不使用队列,使用任务管道实现(在多进程:主进程、子进程、子进程内部进程池等场景下,队列并不好用)任务管理和通信 3. 解析任务从与下载任务间的管道中获取数据,解析并保存 问题:当目标被爬完后,怎样让爬虫停止? """ import csv import datetime import logging import multiprocessing as mp import re import time from collections import O...
28.75431
115
0.582072
787
6,671
4.799238
0.349428
0.021181
0.022505
0.015886
0.186391
0.085782
0.041303
0.041303
0.041303
0.041303
0
0.005758
0.271024
6,671
231
116
28.878788
0.770923
0.180033
0
0.172727
0
0
0.183037
0.004978
0
0
0
0
0
1
0.072727
false
0
0.090909
0
0.227273
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
4a960357ff5666b9fe043faf558321c7ac02d8e5
8,415
py
Python
desktop/core/ext-py/pyu2f-0.1.4/pyu2f/convenience/customauthenticator.py
yetsun/hue
2e48f0cc70e233ee0e1b40733d4b2a18d8836c66
[ "Apache-2.0" ]
5,079
2015-01-01T03:39:46.000Z
2022-03-31T07:38:22.000Z
desktop/core/ext-py/pyu2f-0.1.4/pyu2f/convenience/customauthenticator.py
yetsun/hue
2e48f0cc70e233ee0e1b40733d4b2a18d8836c66
[ "Apache-2.0" ]
4,640
2015-07-08T16:19:08.000Z
2019-12-02T15:01:27.000Z
desktop/core/ext-py/pyu2f-0.1.4/pyu2f/convenience/customauthenticator.py
yetsun/hue
2e48f0cc70e233ee0e1b40733d4b2a18d8836c66
[ "Apache-2.0" ]
2,033
2015-01-04T07:18:02.000Z
2022-03-28T19:55:47.000Z
# Copyright 2016 Google Inc. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or ag...
34.487705
80
0.684848
1,007
8,415
5.506455
0.278054
0.028855
0.032462
0.025248
0.224707
0.118305
0.07899
0.065284
0.039315
0.039315
0
0.017181
0.225312
8,415
243
81
34.62963
0.83341
0.319786
0
0.048
0
0
0.117035
0
0
0
0.002154
0
0
1
0.064
false
0
0.08
0
0.208
0.016
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
4a9667d37782748097516470365e83980101a92e
1,681
py
Python
kive/portal/management/commands/graph_kive.py
dmacmillan/Kive
76bc8f289f66fb133f78cb6d5689568b7d015915
[ "BSD-3-Clause" ]
1
2021-12-22T06:10:01.000Z
2021-12-22T06:10:01.000Z
kive/portal/management/commands/graph_kive.py
dmacmillan/Kive
76bc8f289f66fb133f78cb6d5689568b7d015915
[ "BSD-3-Clause" ]
null
null
null
kive/portal/management/commands/graph_kive.py
dmacmillan/Kive
76bc8f289f66fb133f78cb6d5689568b7d015915
[ "BSD-3-Clause" ]
null
null
null
import itertools import os from django.conf import settings from django.core.management import call_command from django.core.management.base import BaseCommand class Command(BaseCommand): help = 'Generates class diagrams.' def handle(self, *args, **options): if 'django_extensions' not in settings.IN...
38.204545
86
0.543129
185
1,681
4.816216
0.421622
0.026936
0.03367
0.053872
0.040404
0
0
0
0
0
0
0.000898
0.337299
1,681
43
87
39.093023
0.798923
0
0
0.054054
0
0
0.149911
0
0
0
0
0
0
1
0.027027
false
0
0.135135
0
0.216216
0.027027
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
4a971f56d894bd93c1e6642fd2fd7e799cec7a1d
8,543
py
Python
summary.py
rpls/openlane_summary
5057fab80a4acaf08e6503ced7abb932684145a5
[ "Apache-2.0" ]
null
null
null
summary.py
rpls/openlane_summary
5057fab80a4acaf08e6503ced7abb932684145a5
[ "Apache-2.0" ]
null
null
null
summary.py
rpls/openlane_summary
5057fab80a4acaf08e6503ced7abb932684145a5
[ "Apache-2.0" ]
null
null
null
#!/usr/bin/env python3 import argparse import os import glob import csv import sys import re from shutil import which import datetime def is_tool(name): return which(name) is not None def check_path(path): paths = glob.glob(path) if len(paths) == 0: exit("file not found: %s" % path) if len(pa...
40.29717
164
0.628
1,209
8,543
4.303557
0.205128
0.029983
0.034595
0.05247
0.365751
0.317701
0.302518
0.302518
0.262156
0.192773
0
0.009484
0.234812
8,543
211
165
40.488152
0.786446
0.078661
0
0.166667
0
0
0.242582
0.006112
0
0
0
0
0
1
0.038462
false
0
0.051282
0.00641
0.115385
0.076923
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
4a9a27b8be786f9438239fbfe717a4e94dce8571
992
py
Python
var/spack/repos/builtin/packages/py-cupy/package.py
player1537-forks/spack
822b7632222ec5a91dc7b7cda5fc0e08715bd47c
[ "ECL-2.0", "Apache-2.0", "MIT-0", "MIT" ]
11
2015-10-04T02:17:46.000Z
2018-02-07T18:23:00.000Z
var/spack/repos/builtin/packages/py-cupy/package.py
player1537-forks/spack
822b7632222ec5a91dc7b7cda5fc0e08715bd47c
[ "ECL-2.0", "Apache-2.0", "MIT-0", "MIT" ]
22
2017-08-01T22:45:10.000Z
2022-03-10T07:46:31.000Z
var/spack/repos/builtin/packages/py-cupy/package.py
player1537-forks/spack
822b7632222ec5a91dc7b7cda5fc0e08715bd47c
[ "ECL-2.0", "Apache-2.0", "MIT-0", "MIT" ]
4
2016-06-10T17:57:39.000Z
2018-09-11T04:59:38.000Z
# Copyright 2013-2022 Lawrence Livermore National Security, LLC and other # Spack Project Developers. See the top-level COPYRIGHT file for details. # # SPDX-License-Identifier: (Apache-2.0 OR MIT) from spack import * class PyCupy(PythonPackage): """CuPy is an open-source array library accelerated with NVIDIA...
35.428571
95
0.704637
134
992
5.164179
0.656716
0.09104
0.052023
0.08237
0.096821
0.066474
0
0
0
0
0
0.07443
0.160282
992
27
96
36.740741
0.756303
0.455645
0
0
0
0
0.398058
0.16699
0
0
0
0
0
1
0
false
0
0.083333
0
0.333333
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
4a9acf16b780b19cf351bb2d89e76f1956c1db38
1,742
py
Python
simple_rest_client/decorators.py
cfytrok/python-simple-rest-client
4896e8226ffe194625c63773ea6f49531293b308
[ "MIT" ]
null
null
null
simple_rest_client/decorators.py
cfytrok/python-simple-rest-client
4896e8226ffe194625c63773ea6f49531293b308
[ "MIT" ]
null
null
null
simple_rest_client/decorators.py
cfytrok/python-simple-rest-client
4896e8226ffe194625c63773ea6f49531293b308
[ "MIT" ]
null
null
null
import logging from functools import wraps import status from httpx import exceptions from .exceptions import AuthError, ClientConnectionError, ClientError, NotFoundError, ServerError logger = logging.getLogger(__name__) def validate_response(response): error_suffix = " response={!r}".format(response) if r...
29.033333
97
0.675086
184
1,742
6.190217
0.315217
0.048288
0.083407
0.084284
0.468832
0.358209
0.247586
0.187884
0.187884
0.187884
0
0.006803
0.240528
1,742
59
98
29.525424
0.854119
0
0
0.409091
0
0
0.061424
0.053387
0
0
0
0
0
1
0.090909
false
0
0.113636
0
0.295455
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
4a9cba0b5388d429f06edbee8329e6af7d50f140
674
py
Python
tests/test_vendcrawler.py
josetaas/vendcrawler
5cb497d0741f6dbd29a6e41fa9f1cb3374e8f062
[ "MIT" ]
null
null
null
tests/test_vendcrawler.py
josetaas/vendcrawler
5cb497d0741f6dbd29a6e41fa9f1cb3374e8f062
[ "MIT" ]
null
null
null
tests/test_vendcrawler.py
josetaas/vendcrawler
5cb497d0741f6dbd29a6e41fa9f1cb3374e8f062
[ "MIT" ]
null
null
null
import unittest from vendcrawler.scripts.vendcrawler import VendCrawler class TestVendCrawlerMethods(unittest.TestCase): def test_get_links(self): links = VendCrawler('a', 'b', 'c').get_links(2) self.assertEqual(links, ['https://sarahserver.net/?module=vendor&p=1', ...
32.095238
73
0.615727
81
674
4.888889
0.506173
0.090909
0.050505
0.070707
0.247475
0.161616
0
0
0
0
0
0.009747
0.238872
674
20
74
33.7
0.762183
0
0
0
0
0
0.178042
0.031157
0
0
0
0
0.133333
1
0.133333
false
0
0.133333
0
0.333333
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
4aa366c3a95eb19c5533d5c2db8cc7a7e0760866
1,331
py
Python
tests/Python/test_all_configs_output.py
lopippo/IsoSpec
dfc6d7dac213f174fb9c61a5ee018d3f6174febc
[ "BSD-2-Clause" ]
27
2016-05-10T21:27:35.000Z
2022-03-30T08:11:36.000Z
tests/Python/test_all_configs_output.py
lopippo/IsoSpec
dfc6d7dac213f174fb9c61a5ee018d3f6174febc
[ "BSD-2-Clause" ]
30
2017-08-08T14:24:56.000Z
2022-03-30T12:44:11.000Z
tests/Python/test_all_configs_output.py
lopippo/IsoSpec
dfc6d7dac213f174fb9c61a5ee018d3f6174febc
[ "BSD-2-Clause" ]
10
2017-06-26T12:14:00.000Z
2020-11-01T13:45:14.000Z
def binom(n, k): """Quickly adapted from https://stackoverflow.com/questions/26560726/python-binomial-coefficient""" if k < 0 or k > n: return 0 if k == 0 or k == n: return 1 total_ways = 1 for i in range(min(k, n - k)): total_ways = total_ways * (n - i) // (i + 1) return...
28.319149
103
0.602554
177
1,331
4.338983
0.412429
0.052083
0.071615
0.015625
0.096354
0.036458
0.036458
0
0
0
0
0.061053
0.286251
1,331
46
104
28.934783
0.747368
0.164538
0
0.057143
0
0
0.052007
0
0
0
0
0
0.085714
1
0.114286
false
0
0.057143
0
0.314286
0.028571
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
4aa38327240010c87a37f52f085b58c65fe79f76
5,090
py
Python
tractseg/models/UNet_Pytorch_Regression.py
soichih/TractSeg
f78d0c6dc998905e593cbf4346745467e30d1979
[ "Apache-2.0" ]
null
null
null
tractseg/models/UNet_Pytorch_Regression.py
soichih/TractSeg
f78d0c6dc998905e593cbf4346745467e30d1979
[ "Apache-2.0" ]
null
null
null
tractseg/models/UNet_Pytorch_Regression.py
soichih/TractSeg
f78d0c6dc998905e593cbf4346745467e30d1979
[ "Apache-2.0" ]
null
null
null
# Copyright 2017 Division of Medical Image Computing, German Cancer Research Center (DKFZ) # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 #...
40.07874
167
0.678978
876
5,090
3.638128
0.184932
0.076875
0.062127
0.033888
0.285849
0.220897
0.151867
0.075306
0.026985
0
0
0.079717
0.221218
5,090
126
168
40.396825
0.724268
0.180943
0
0
0
0
0
0
0
0
0
0
0
1
0.024096
false
0
0.192771
0
0.240964
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
4aa4605e775071451ff4f02953c5854fc600fb27
1,619
py
Python
platform/core/polyaxon/sidecar/sidecar/__main__.py
hackerwins/polyaxon
ff56a098283ca872abfbaae6ba8abba479ffa394
[ "Apache-2.0" ]
null
null
null
platform/core/polyaxon/sidecar/sidecar/__main__.py
hackerwins/polyaxon
ff56a098283ca872abfbaae6ba8abba479ffa394
[ "Apache-2.0" ]
null
null
null
platform/core/polyaxon/sidecar/sidecar/__main__.py
hackerwins/polyaxon
ff56a098283ca872abfbaae6ba8abba479ffa394
[ "Apache-2.0" ]
null
null
null
import argparse import time from kubernetes.client.rest import ApiException from polyaxon_client.client import PolyaxonClient from polyaxon_k8s.manager import K8SManager from sidecar import settings from sidecar.monitor import is_pod_running if __name__ == '__main__': parser = argparse.ArgumentParser() pars...
27.440678
79
0.6084
173
1,619
5.404624
0.398844
0.069519
0.072727
0.034225
0.051337
0
0
0
0
0
0
0.009901
0.313774
1,619
58
80
27.913793
0.831683
0.017912
0
0.196078
0
0
0.06927
0
0
0
0
0
0
1
0
false
0
0.137255
0
0.137255
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
4aa4e20dc8b2673c6655b3fbcb68df91576905a0
615
py
Python
simple_robot_tests/src/test_odometry.py
plusangel/simple_robot
d9ad5ed8cd592f4aee14df13465435279b4d60d7
[ "MIT" ]
1
2022-03-02T14:55:27.000Z
2022-03-02T14:55:27.000Z
simple_robot_tests/src/test_odometry.py
plusangel/simple_robot
d9ad5ed8cd592f4aee14df13465435279b4d60d7
[ "MIT" ]
null
null
null
simple_robot_tests/src/test_odometry.py
plusangel/simple_robot
d9ad5ed8cd592f4aee14df13465435279b4d60d7
[ "MIT" ]
null
null
null
#! /usr/bin/env python import rospy from nav_msgs.msg import Odometry class OdomTopicReader(object): def __init__(self, topic_name = '/odom'): self._topic_name = topic_name self._sub = rospy.Subscriber(self._topic_name, Odometry, self.topic_callback) self._odomdata = Odometry() def to...
26.73913
85
0.681301
76
615
5.105263
0.473684
0.092784
0.100515
0
0
0
0
0
0
0
0
0.004124
0.211382
615
22
86
27.954545
0.795876
0.034146
0
0
0
0
0.057336
0.035413
0
0
0
0
0
1
0.125
false
0
0.125
0
0.3125
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
4aa9aadd40d912fb75115061e304f8eab10a0530
15,044
py
Python
docs/generate_example_images.py
KhaledSharif/kornia
9bae28e032b092b065658117723a82816d09dbac
[ "ECL-2.0", "Apache-2.0" ]
null
null
null
docs/generate_example_images.py
KhaledSharif/kornia
9bae28e032b092b065658117723a82816d09dbac
[ "ECL-2.0", "Apache-2.0" ]
null
null
null
docs/generate_example_images.py
KhaledSharif/kornia
9bae28e032b092b065658117723a82816d09dbac
[ "ECL-2.0", "Apache-2.0" ]
null
null
null
import importlib import math import os from pathlib import Path from typing import Optional, Tuple import cv2 import numpy as np import requests import torch import kornia as K def read_img_from_url(url: str, resize_to: Optional[Tuple[int, int]] = None) -> torch.Tensor: # perform request response = requests...
42.982857
120
0.545865
2,137
15,044
3.688348
0.160037
0.028165
0.00609
0.005075
0.5
0.466125
0.401294
0.383025
0.345724
0.335321
0
0.065241
0.266419
15,044
349
121
43.106017
0.648967
0.085283
0
0.272727
0
0.006993
0.183005
0.006492
0
0
0
0.002865
0
1
0.01049
false
0
0.059441
0
0.076923
0.027972
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
4aa9bb3cf3909a79588350f79db082251d5ab096
3,318
py
Python
forte/processors/data_augment/algorithms/embedding_similarity_replacement_op.py
Pushkar-Bhuse/forte
b7402330cf0b2b26fe56234f0ae43c89b31c0082
[ "Apache-2.0" ]
null
null
null
forte/processors/data_augment/algorithms/embedding_similarity_replacement_op.py
Pushkar-Bhuse/forte
b7402330cf0b2b26fe56234f0ae43c89b31c0082
[ "Apache-2.0" ]
null
null
null
forte/processors/data_augment/algorithms/embedding_similarity_replacement_op.py
Pushkar-Bhuse/forte
b7402330cf0b2b26fe56234f0ae43c89b31c0082
[ "Apache-2.0" ]
null
null
null
# Copyright 2020 The Forte Authors. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable ...
36.065217
77
0.676311
436
3,318
5.004587
0.417431
0.027498
0.019248
0.021998
0.070119
0.055454
0.055454
0.023831
0
0
0
0.005223
0.249849
3,318
91
78
36.461538
0.871434
0.465943
0
0
0
0
0.040198
0.01979
0
0
0
0
0
1
0.04878
false
0
0.170732
0
0.292683
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
4aaa0768bd968c91cbf077505e1dc0e7ee6365c8
34,840
py
Python
ion_functions/qc/qc_functions.py
steinermg/ion-functions
cea532ad9af51e86768572c8deb48547d99567c5
[ "Apache-2.0" ]
10
2015-04-03T15:32:21.000Z
2018-11-21T11:57:26.000Z
ion_functions/qc/qc_functions.py
steinermg/ion-functions
cea532ad9af51e86768572c8deb48547d99567c5
[ "Apache-2.0" ]
8
2015-01-07T15:19:22.000Z
2015-12-08T18:14:04.000Z
ion_functions/qc/qc_functions.py
steinermg/ion-functions
cea532ad9af51e86768572c8deb48547d99567c5
[ "Apache-2.0" ]
17
2015-01-14T16:23:00.000Z
2021-07-19T08:26:52.000Z
#!/usr/bin/env python """ @package ion_functions.qc_functions @file ion_functions/qc_functions.py @author Christopher Mueller @brief Module containing QC functions ported from matlab samples in DPS documents """ from ion_functions.qc.qc_extensions import stuckvalues, spikevalues, gradientvalues, ntp_to_month import ...
37.746479
215
0.632319
4,920
34,840
4.411179
0.16687
0.028752
0.012441
0.010137
0.403032
0.352624
0.307331
0.265079
0.234253
0.22232
0
0.048972
0.27147
34,840
922
216
37.787419
0.806083
0.503502
0
0.270588
0
0
0.07296
0
0
0
0
0
0
1
0.052941
false
0
0.029412
0.005882
0.164706
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
4aaa32daecbc845e7f79a56464fde4fa9e4bd81d
10,702
py
Python
datatest/__past__/api08.py
avshalomt2/datatest
f622b0e990b53c73f56730a9009b39af7653df20
[ "Apache-2.0" ]
null
null
null
datatest/__past__/api08.py
avshalomt2/datatest
f622b0e990b53c73f56730a9009b39af7653df20
[ "Apache-2.0" ]
null
null
null
datatest/__past__/api08.py
avshalomt2/datatest
f622b0e990b53c73f56730a9009b39af7653df20
[ "Apache-2.0" ]
null
null
null
"""Backward compatibility for version 0.8 API.""" from __future__ import absolute_import import inspect import datatest from datatest._compatibility import itertools from datatest._compatibility.collections.abc import Sequence from datatest._load.get_reader import get_reader from datatest._load.load_csv import load_cs...
36.03367
86
0.652775
1,262
10,702
5.306656
0.183043
0.018814
0.014335
0.014932
0.289682
0.217112
0.197999
0.189637
0.189637
0.168135
0
0.004884
0.253784
10,702
296
87
36.155405
0.833709
0.122127
0
0.199095
0
0
0.058418
0
0.004525
0
0
0
0.004525
1
0.095023
false
0
0.085973
0.004525
0.312217
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
4aabc93bad87b0dbf891bc8cb36cc3c5cdca1038
5,975
py
Python
python/scripts/compare_events.py
tvogels01/arthur-redshift-etl
477f822d16cd3a86b3bf95cfa28915cb7470a6e4
[ "MIT" ]
null
null
null
python/scripts/compare_events.py
tvogels01/arthur-redshift-etl
477f822d16cd3a86b3bf95cfa28915cb7470a6e4
[ "MIT" ]
44
2021-11-22T02:18:41.000Z
2022-03-28T02:13:32.000Z
python/scripts/compare_events.py
tvogels01/arthur-redshift-etl
477f822d16cd3a86b3bf95cfa28915cb7470a6e4
[ "MIT" ]
null
null
null
""" This script compares events from two ETLs to highlight differences in elapsed times or row counts. * Pre-requisites You need to have a list of events for each ETL. Arthur can provide this using the "query_events" command. For example: ``` arthur.py query_events -p development 37ACEC7440AB4620 -q > 37ACEC7440AB46...
33.948864
101
0.654226
813
5,975
4.672817
0.302583
0.047907
0.042116
0.052645
0.146618
0.136878
0.093446
0.071335
0.063175
0.038431
0
0.031347
0.247197
5,975
175
102
34.142857
0.81325
0.31046
0
0.049505
0
0
0.053771
0
0
0
0
0
0.009901
1
0.069307
false
0
0.059406
0
0.257426
0.089109
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
4aacfc97b162e67687e0053e093dc275ef1915a8
4,163
py
Python
harness/drifter.py
cmu-sei/augur-code
d8c1e29ce3276037b26b65ea316d251752529449
[ "BSD-3-Clause" ]
null
null
null
harness/drifter.py
cmu-sei/augur-code
d8c1e29ce3276037b26b65ea316d251752529449
[ "BSD-3-Clause" ]
null
null
null
harness/drifter.py
cmu-sei/augur-code
d8c1e29ce3276037b26b65ea316d251752529449
[ "BSD-3-Clause" ]
null
null
null
# Augur: A Step Towards Realistic Drift Detection in Production MLSystems - Code # Copyright 2022 Carnegie Mellon University. # # NO WARRANTY. THIS CARNEGIE MELLON UNIVERSITY AND SOFTWARE ENGINEERING INSTITUTE MATERIAL IS FURNISHED ON AN "AS-IS" BASIS. CARNEGIE MELLON UNIVERSITY MAKES NO WARRANTIES OF ANY KIND, EITH...
54.064935
513
0.764833
571
4,163
5.432574
0.367776
0.034816
0.031593
0.017408
0.048678
0.019987
0
0
0
0
0
0.012669
0.146769
4,163
76
514
54.776316
0.86036
0.544319
0
0
0
0
0.119395
0.023231
0
0
0
0
0
1
0.057143
false
0
0.171429
0
0.257143
0.028571
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
4aae62b164701dc61724cb01ba008cf15083826f
8,528
py
Python
network/baselines_archive/resnet_3d101.py
xuyu0010/ARID_v1
b03d0975f41547e8aa78929b8e26a62248f8e18f
[ "CC-BY-4.0" ]
5
2020-06-24T07:33:36.000Z
2021-11-30T17:52:08.000Z
network/baselines_archive/resnet_3d101.py
xuyu0010/ARID_v1
b03d0975f41547e8aa78929b8e26a62248f8e18f
[ "CC-BY-4.0" ]
1
2022-03-29T05:23:24.000Z
2022-03-29T06:19:57.000Z
network/baselines_archive/resnet_3d101.py
xuyu0010/ARID_v1
b03d0975f41547e8aa78929b8e26a62248f8e18f
[ "CC-BY-4.0" ]
3
2021-02-06T10:56:30.000Z
2022-01-18T18:50:12.000Z
import torch import torch.nn as nn import torch.nn.functional as F from torch.autograd import Variable import math from functools import partial import logging import os try: from . import initializer from .utils import load_state except: import initializer from utils import load_state __all__ = ['Re...
31.238095
124
0.533654
960
8,528
4.569792
0.208333
0.031001
0.027354
0.028721
0.338728
0.278778
0.193526
0.164349
0.148393
0.129701
0
0.034629
0.363391
8,528
272
125
31.352941
0.773439
0.010671
0
0.293839
0
0
0.02871
0.004034
0
0
0
0
0.004739
1
0.056872
false
0
0.061611
0.009479
0.189573
0.004739
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
4ab01eaed0874fd5f366410cee4ae62597dd8de5
4,167
py
Python
tests/ninety_nine_problems/test_miscellaneous_problems.py
gecBurton/inference_logic
2531d8f8fb0154b3bd42ac86eccc44d7038f6ef6
[ "MIT" ]
3
2020-10-19T20:35:24.000Z
2020-10-21T07:13:02.000Z
tests/ninety_nine_problems/test_miscellaneous_problems.py
gecBurton/inference_logic
2531d8f8fb0154b3bd42ac86eccc44d7038f6ef6
[ "MIT" ]
2
2020-11-10T16:54:13.000Z
2020-11-10T18:51:31.000Z
tests/ninety_nine_problems/test_miscellaneous_problems.py
gecBurton/inference_logic
2531d8f8fb0154b3bd42ac86eccc44d7038f6ef6
[ "MIT" ]
1
2020-10-21T07:13:14.000Z
2020-10-21T07:13:14.000Z
import pytest from inference_logic import Rule, Variable, search from inference_logic.data_structures import Assert, Assign @pytest.mark.xfail def test_90(): r""" P90 (**) Eight queens problem This is a classical problem in computer science. The objective is to place eight queens on a chessboard so ...
35.313559
88
0.538037
718
4,167
3.083565
0.213092
0.009937
0.007227
0.023487
0.165312
0.148148
0.116531
0.081301
0.081301
0.055104
0
0.018905
0.276458
4,167
117
89
35.615385
0.715423
0.545956
0
0.173913
0
0
0.024289
0
0
0
0
0
0.108696
1
0.021739
false
0
0.065217
0
0.086957
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
4ab03ce1ed84ecb90d03ef035bc80050cf57b143
4,856
py
Python
airbus_cobot_gui/src/airbus_cobot_gui/diagnostics/diagnostics.py
ipa320/airbus_coop
974564807ba5d24096e237a9991311608a390da1
[ "Apache-2.0" ]
4
2017-10-15T23:32:24.000Z
2019-12-26T12:31:53.000Z
airbus_cobot_gui/src/airbus_cobot_gui/diagnostics/diagnostics.py
ipa320/airbus_coop
974564807ba5d24096e237a9991311608a390da1
[ "Apache-2.0" ]
6
2017-09-05T13:52:00.000Z
2017-12-01T14:18:27.000Z
airbus_cobot_gui/src/airbus_cobot_gui/diagnostics/diagnostics.py
ipa320/airbus_coop
974564807ba5d24096e237a9991311608a390da1
[ "Apache-2.0" ]
4
2017-09-04T08:14:36.000Z
2017-09-18T07:22:21.000Z
#!/usr/bin/env python # # Copyright 2015 Airbus # Copyright 2017 Fraunhofer Institute for Manufacturing Engineering and Automation (IPA) # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # ...
35.97037
150
0.691928
595
4,856
5.438655
0.356303
0.02225
0.012361
0.017614
0.061805
0.046354
0.025958
0.025958
0
0
0
0.00709
0.215815
4,856
134
151
36.238806
0.8427
0.225494
0
0.071429
0
0
0.079925
0.021529
0
0
0
0
0
1
0.083333
false
0
0.166667
0
0.309524
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
4ab14530560ea0c6ff68422c45af6c1228280da2
758
py
Python
graphgallery/functional/dense/onehot.py
dongzizhu/GraphGallery
c65eab42daeb52de5019609fe7b368e30863b4ae
[ "MIT" ]
1
2020-07-29T08:00:32.000Z
2020-07-29T08:00:32.000Z
graphgallery/functional/dense/onehot.py
dongzizhu/GraphGallery
c65eab42daeb52de5019609fe7b368e30863b4ae
[ "MIT" ]
null
null
null
graphgallery/functional/dense/onehot.py
dongzizhu/GraphGallery
c65eab42daeb52de5019609fe7b368e30863b4ae
[ "MIT" ]
null
null
null
import numpy as np from ..transform import DenseTransform from ..decorators import multiple from ..transform import Transform __all__ = ['onehot', 'Onehot'] @Transform.register() class Onehot(DenseTransform): def __init__(self, depth=None): super().__init__() self.collect(locals()...
25.266667
84
0.634565
99
758
4.69697
0.535354
0.055914
0.08172
0
0
0
0
0
0
0
0
0.008651
0.237467
758
29
85
26.137931
0.795848
0.047493
0
0
0
0
0.09607
0
0
0
0
0
0
1
0.15
false
0
0.2
0.05
0.5
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
4ab3a002c74475748d23b9510c6318a19949f281
752
py
Python
lesson06/liqi/test.py
herrywen-nanj/51reboot
1130c79a360e1b548a6eaad176eb60f8bed22f40
[ "Apache-2.0" ]
null
null
null
lesson06/liqi/test.py
herrywen-nanj/51reboot
1130c79a360e1b548a6eaad176eb60f8bed22f40
[ "Apache-2.0" ]
null
null
null
lesson06/liqi/test.py
herrywen-nanj/51reboot
1130c79a360e1b548a6eaad176eb60f8bed22f40
[ "Apache-2.0" ]
null
null
null
import configparser ''' config = configparser.ConfigParser() config.read('db.ini') print(config.sections()) print(dict(config['mysqld'])['symbolic-links']) ''' def ReadConfig(filename, section, key=None): print(filename) config = configparser.ConfigParser() config.read(filename) print(config.section...
22.117647
53
0.640957
86
752
5.511628
0.383721
0.118143
0.126582
0.151899
0.2827
0
0
0
0
0
0
0
0.204787
752
34
54
22.117647
0.792642
0
0
0.1
0
0
0.104746
0
0
0
0
0
0
1
0.05
false
0
0.05
0
0.3
0.2
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
4ab3ac9ae685aecfb387f1a734cc96132d725108
1,947
py
Python
core/forms.py
xUndero/noc
9fb34627721149fcf7064860bd63887e38849131
[ "BSD-3-Clause" ]
1
2019-09-20T09:36:48.000Z
2019-09-20T09:36:48.000Z
core/forms.py
ewwwcha/noc
aba08dc328296bb0e8e181c2ac9a766e1ec2a0bb
[ "BSD-3-Clause" ]
null
null
null
core/forms.py
ewwwcha/noc
aba08dc328296bb0e8e181c2ac9a766e1ec2a0bb
[ "BSD-3-Clause" ]
null
null
null
# -*- coding: utf-8 -*- # --------------------------------------------------------------------- # Forms wrapper # --------------------------------------------------------------------- # Copyright (C) 2007-2019 The NOC Project # See LICENSE for details # ------------------------------------------------------------------...
32.45
83
0.558295
207
1,947
5.101449
0.396135
0.042614
0.039773
0.028409
0.090909
0.049242
0
0
0
0
0
0.005976
0.226502
1,947
59
84
33
0.695219
0.214689
0
0.058824
0
0
0.04829
0.026828
0
0
0
0
0
1
0.147059
false
0
0.117647
0
0.382353
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
4ab43c897df779b46c4155028b30eff4d2ad17d1
1,990
py
Python
ersteops/unit/views.py
Prescrypto/ErsteOps
0b744173fb4f500003c96c4dcb26fb67d6eaa5ec
[ "MIT" ]
null
null
null
ersteops/unit/views.py
Prescrypto/ErsteOps
0b744173fb4f500003c96c4dcb26fb67d6eaa5ec
[ "MIT" ]
33
2017-11-24T19:44:57.000Z
2022-02-12T07:02:53.000Z
ersteops/unit/views.py
Prescrypto/ErsteOps
0b744173fb4f500003c96c4dcb26fb67d6eaa5ec
[ "MIT" ]
1
2017-12-11T09:15:04.000Z
2017-12-11T09:15:04.000Z
import json from django.shortcuts import get_object_or_404 from django.core import serializers from django.http import HttpResponse from .models import Unit from .utils import UNIT_LIST_FIELD BAD_REQUEST = HttpResponse(json.dumps({'error': 'Bad Request'}), status=400, content_type='application/json') def unit_json_li...
39.019608
123
0.665327
248
1,990
5.133065
0.262097
0.032993
0.08641
0.102121
0.456402
0.42498
0.42498
0.42498
0.371563
0.371563
0
0.012755
0.21206
1,990
50
124
39.8
0.799107
0.061307
0
0.4
0
0
0.114116
0
0
0
0
0
0
1
0.075
false
0
0.15
0
0.4
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
4ab74d6454f4022c0cd33cf7aa9d2924c227290a
2,394
py
Python
src/action/tests/test_logic.py
uts-cic/ontask_b
b313e2352c77b40655f41dd5acba3a7635e6f3b3
[ "MIT" ]
3
2018-08-24T10:48:40.000Z
2020-05-29T06:33:23.000Z
src/action/tests/test_logic.py
Lukahm/ontask
f16bdaa06ea450ee56d4581340e611b1076bed16
[ "MIT" ]
null
null
null
src/action/tests/test_logic.py
Lukahm/ontask
f16bdaa06ea450ee56d4581340e611b1076bed16
[ "MIT" ]
null
null
null
# -*- coding: utf-8 -*- from __future__ import unicode_literals, print_function import os from django.conf import settings from django.shortcuts import reverse from django.core.management import call_command import test from dataops import pandas_db from workflow.models import Workflow class EmailActionTracking(te...
38.612903
202
0.704678
229
2,394
7.227074
0.528384
0.019335
0.022961
0.030211
0
0
0
0
0
0
0
0.057589
0.223893
2,394
61
203
39.245902
0.833154
0.105681
0
0
0
0
0.342081
0.280694
0
0
0
0
0.023256
1
0.069767
false
0
0.186047
0
0.418605
0.023256
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
4ab90259acfbeda3412addc434ad2001de65b77a
5,371
py
Python
obniz/parts/Moving/StepperMotor/__init__.py
izm51/obniz-python-sdk
40a738b5fe2c0a415cdc09f46d28c143982bfb07
[ "MIT" ]
11
2019-03-22T12:02:11.000Z
2021-01-21T04:57:18.000Z
obniz/parts/Moving/StepperMotor/__init__.py
izm51/obniz-python-sdk
40a738b5fe2c0a415cdc09f46d28c143982bfb07
[ "MIT" ]
5
2019-03-02T08:28:25.000Z
2021-02-02T22:06:37.000Z
obniz/parts/Moving/StepperMotor/__init__.py
izm51/obniz-python-sdk
40a738b5fe2c0a415cdc09f46d28c143982bfb07
[ "MIT" ]
3
2019-07-20T06:55:09.000Z
2019-12-04T05:05:00.000Z
from attrdict import AttrDefault import asyncio class StepperMotor: def __init__(self): self.keys = ['a', 'b', 'aa', 'bb', 'common'] self.required_keys = ['a', 'b', 'aa', 'bb'] self._step_instructions = AttrDefault(bool, { '1': [[0, 1, 1, 1], [1, 0, 1, 1], [1, 1...
37.559441
135
0.571216
677
5,371
4.333826
0.149188
0.018405
0.014315
0.014997
0.470688
0.388548
0.339809
0.339809
0.282549
0.200409
0
0.038289
0.294917
5,371
143
136
37.559441
0.736467
0
0
0.209677
0
0
0.021035
0
0
0
0
0
0
1
0.080645
false
0
0.016129
0.032258
0.153226
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
4abb8389f46537b21c77c0aa5024c68649d338e4
2,241
py
Python
opennem/utils/scrapyd.py
paulculmsee/opennem
9ebe4ab6d3b97bdeebc352e075bbd5c22a8ddea1
[ "MIT" ]
22
2020-06-30T05:27:21.000Z
2022-02-21T12:13:51.000Z
opennem/utils/scrapyd.py
paulculmsee/opennem
9ebe4ab6d3b97bdeebc352e075bbd5c22a8ddea1
[ "MIT" ]
71
2020-08-07T13:06:30.000Z
2022-03-15T06:44:49.000Z
opennem/utils/scrapyd.py
paulculmsee/opennem
9ebe4ab6d3b97bdeebc352e075bbd5c22a8ddea1
[ "MIT" ]
13
2020-06-30T03:28:32.000Z
2021-12-30T08:17:16.000Z
#!/usr/bin/env python """ Srapyd control methods """ import logging from typing import Any, Dict, List from urllib.parse import urljoin from opennem.settings import settings from opennem.utils.http import http from opennem.utils.scrapy import get_spiders logger = logging.getLogger("scrapyd.client") def get_jobs() ...
23.103093
87
0.635431
291
2,241
4.762887
0.292096
0.018038
0.046176
0.054113
0.239538
0.196248
0.11544
0.11544
0.11544
0.11544
0
0
0.227577
2,241
96
88
23.34375
0.800693
0.019188
0
0.237288
0
0
0.135678
0.010964
0
0
0
0
0
1
0.084746
false
0
0.101695
0
0.355932
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
4abf6af83131868287dda032df11a21439ed9d49
1,164
py
Python
tutorials/W2D2_LinearSystems/solutions/W2D2_Tutorial1_Solution_437c0b24.py
liuxiaomiao123/NeuroMathAcademy
16a7969604a300bf9fbb86f8a5b26050ebd14c65
[ "CC-BY-4.0" ]
2
2020-07-03T04:39:09.000Z
2020-07-12T02:08:31.000Z
tutorials/W2D2_LinearSystems/solutions/W2D2_Tutorial1_Solution_437c0b24.py
NinaHKivanani/course-content
3c91dd1a669cebce892486ba4f8086b1ef2e1e49
[ "CC-BY-4.0" ]
1
2020-06-22T22:57:03.000Z
2020-06-22T22:57:03.000Z
tutorials/W2D2_LinearSystems/solutions/W2D2_Tutorial1_Solution_437c0b24.py
NinaHKivanani/course-content
3c91dd1a669cebce892486ba4f8086b1ef2e1e49
[ "CC-BY-4.0" ]
1
2021-03-29T21:08:26.000Z
2021-03-29T21:08:26.000Z
def integrate_exponential(a, x0, dt, T): """Compute solution of the differential equation xdot=a*x with initial condition x0 for a duration T. Use time step dt for numerical solution. Args: a (scalar): parameter of xdot (xdot=a*x) x0 (scalar): initial condition (x at time 0) dt (scalar): timeste...
27.714286
80
0.640893
199
1,164
3.733668
0.39196
0.026918
0.032301
0.061911
0.069987
0.069987
0
0
0
0
0
0.02718
0.241409
1,164
42
81
27.714286
0.81427
0.579897
0
0
0
0
0.019868
0
0
0
0
0
0
1
0.055556
false
0
0
0
0.111111
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
4abf7b9f84deaebd77faef58a9ebbc8bcdd69360
1,199
py
Python
PyTemp/gis/shapefile_to_geojson.py
SwaggerKhan/PatrolGis
89b1a398ffd6171ac35ea9d023bce98a0fc7e930
[ "MIT" ]
null
null
null
PyTemp/gis/shapefile_to_geojson.py
SwaggerKhan/PatrolGis
89b1a398ffd6171ac35ea9d023bce98a0fc7e930
[ "MIT" ]
null
null
null
PyTemp/gis/shapefile_to_geojson.py
SwaggerKhan/PatrolGis
89b1a398ffd6171ac35ea9d023bce98a0fc7e930
[ "MIT" ]
null
null
null
import json import geojson import geopandas as gpd class SaveToGeoJSON: __name_counter = 0 def file_name(self): if self.__name_counter == 0: self.__name_counter = 1 return "./out"+str(self.__name_counter)+".json" elif self.__name_counter == 1: self.__name_co...
31.552632
95
0.605505
149
1,199
4.496644
0.375839
0.131343
0.156716
0.047761
0.092537
0.092537
0.092537
0
0
0
0
0.012761
0.281068
1,199
38
96
31.552632
0.764501
0
0
0.064516
0
0
0.083333
0
0
0
0
0
0
1
0.096774
false
0
0.096774
0
0.451613
0.032258
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
4ac2c549f6e7bc96012e6af6cdb10885c9451aa4
543
py
Python
torch_geometric/read/ply.py
DL-85/pytorch_geometric
eb12a94a667e881c4a6bff26b0453428bcb72393
[ "MIT" ]
2
2019-10-10T07:01:07.000Z
2020-11-04T06:26:42.000Z
torch_geometric/read/ply.py
cloudyyyyy/pytorch_geometric
61d389b5f8ee700dda4d18cadca72f24c978fce1
[ "MIT" ]
null
null
null
torch_geometric/read/ply.py
cloudyyyyy/pytorch_geometric
61d389b5f8ee700dda4d18cadca72f24c978fce1
[ "MIT" ]
1
2019-10-31T01:15:03.000Z
2019-10-31T01:15:03.000Z
import torch from plyfile import PlyData from torch_geometric.data import Data def read_ply(path): with open(path, 'rb') as f: data = PlyData.read(f) pos = ([torch.tensor(data['vertex'][axis]) for axis in ['x', 'y', 'z']]) pos = torch.stack(pos, dim=-1) face = None if 'face' in data: ...
23.608696
76
0.607735
81
543
4.037037
0.444444
0.04893
0
0
0
0
0
0
0
0
0
0.004878
0.244936
543
22
77
24.681818
0.792683
0
0
0
0
0
0.060773
0
0
0
0
0
0
1
0.0625
false
0
0.1875
0
0.3125
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
4ac4732c076aba6b6bc386af069168643221a2c1
2,679
py
Python
ml-agents/mlagents/trainers/brain_conversion_utils.py
ranguera/ml-agents
68779b407b32fce2ea14b16ef1bc26dea7d5e5a8
[ "Apache-2.0" ]
2
2019-12-13T22:00:11.000Z
2019-12-14T00:47:32.000Z
ml-agents/mlagents/trainers/brain_conversion_utils.py
almartson/ml-agents
ee748705b777ddd365c55065366e83596c615811
[ "Apache-2.0" ]
null
null
null
ml-agents/mlagents/trainers/brain_conversion_utils.py
almartson/ml-agents
ee748705b777ddd365c55065366e83596c615811
[ "Apache-2.0" ]
null
null
null
from mlagents.trainers.brain import BrainInfo, BrainParameters, CameraResolution from mlagents.envs.base_env import BatchedStepResult, AgentGroupSpec from mlagents.envs.exception import UnityEnvironmentException import numpy as np from typing import List def step_result_to_brain_info( step_result: BatchedStepResu...
37.732394
87
0.670773
373
2,679
4.538874
0.273458
0.076787
0.030715
0.037212
0.222682
0.161843
0.114589
0.090963
0.090963
0.054341
0
0.010244
0.234789
2,679
70
88
38.271429
0.81561
0
0
0.090909
0
0
0.050765
0.009705
0
0
0
0
0
1
0.030303
false
0
0.075758
0
0.136364
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
4ac65a293f32905c196e86dcfb72e76e3b1b85d2
853
py
Python
mrdc_ws/src/mrdc_serial/setup.py
SoonerRobotics/MRDC22
00c1360138e468bf313eefc93fbde11f289ece82
[ "MIT" ]
null
null
null
mrdc_ws/src/mrdc_serial/setup.py
SoonerRobotics/MRDC22
00c1360138e468bf313eefc93fbde11f289ece82
[ "MIT" ]
1
2021-12-01T01:21:22.000Z
2021-12-01T01:21:22.000Z
mrdc_ws/src/mrdc_serial/setup.py
SoonerRobotics/MRDC22
00c1360138e468bf313eefc93fbde11f289ece82
[ "MIT" ]
1
2021-09-28T23:43:07.000Z
2021-09-28T23:43:07.000Z
from setuptools import find_packages, setup from glob import glob import os package_name = 'mrdc_serial' setup( name=package_name, version='1.0.0', packages=find_packages(), data_files=[ ('share/ament_index/resource_index/packages', ['resource/' + package_name]), ('share/' + p...
28.433333
85
0.630715
96
853
5.427083
0.5
0.105566
0.06142
0
0
0
0
0
0
0
0
0.004545
0.22626
853
29
86
29.413793
0.784848
0
0
0.074074
0
0
0.357562
0.127784
0
0
0
0
0
1
0
false
0
0.111111
0
0.111111
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
43493e4caf41318515d94514d68ea22bde6fccc6
5,219
py
Python
PytorchRouting/Examples/run_experiments.py
oleksost/RoutingNetworks
7e3e9219b7389d5af2a832a4882bc9fda0e7fd21
[ "Apache-2.0" ]
63
2018-07-19T20:12:55.000Z
2022-03-31T14:59:37.000Z
PytorchRouting/Examples/run_experiments.py
oleksost/RoutingNetworks
7e3e9219b7389d5af2a832a4882bc9fda0e7fd21
[ "Apache-2.0" ]
2
2019-08-08T18:28:13.000Z
2019-09-24T16:46:22.000Z
PytorchRouting/Examples/run_experiments.py
oleksost/RoutingNetworks
7e3e9219b7389d5af2a832a4882bc9fda0e7fd21
[ "Apache-2.0" ]
16
2018-07-25T05:56:51.000Z
2021-01-09T02:47:05.000Z
""" This file defines some simple experiments to illustrate how Pytorch-Routing functions. """ import numpy as np import tqdm import torch from PytorchRouting.DecisionLayers import REINFORCE, QLearning, SARSA, ActorCritic, GumbelSoftmax, PerTaskAssignment, \ WPL, AAC, AdvantageLearning, RELAX, EGreedyREINFORCE, EGr...
46.185841
119
0.650699
628
5,219
5.19586
0.286624
0.055164
0.082746
0.06068
0.415569
0.378486
0.30616
0.267545
0.267545
0.267545
0
0.030038
0.234528
5,219
112
120
46.598214
0.786733
0.147729
0
0.158537
0
0
0.078151
0.013581
0
0
0
0
0
1
0.036585
false
0
0.073171
0
0.134146
0.02439
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
434b79d3907786ef5e26df8cc123133e8b35acdc
6,670
py
Python
code/image-manipulation.py
rgeirhos/object-recognition
4679f7c60665bd9fb274c6c4372fc0fa34b51485
[ "CC-BY-4.0" ]
33
2017-06-22T21:51:25.000Z
2021-09-03T01:59:58.000Z
code/image-manipulation.py
rgeirhos/object-recognition
4679f7c60665bd9fb274c6c4372fc0fa34b51485
[ "CC-BY-4.0" ]
null
null
null
code/image-manipulation.py
rgeirhos/object-recognition
4679f7c60665bd9fb274c6c4372fc0fa34b51485
[ "CC-BY-4.0" ]
20
2017-06-24T01:48:19.000Z
2021-05-12T08:41:23.000Z
#!/usr/bin/env python from skimage.color import rgb2gray from skimage.io import imread, imsave from scipy.misc import toimage import numpy as np import wrapper as wr ########################################################### # IMAGE IO ########################################################### def imload_rgb(pa...
31.913876
75
0.556822
777
6,670
4.651223
0.24453
0.07554
0.021583
0.024903
0.247371
0.180133
0.164638
0.164638
0.128113
0.128113
0
0.01496
0.228336
6,670
208
76
32.067308
0.687196
0.367916
0
0.060606
0
0
0.090938
0.007417
0
0
0
0
0.045455
1
0.136364
false
0
0.075758
0
0.348485
0.015152
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
434cb653784b20b7295c5b100050122451d7d139
4,855
py
Python
emmet-core/emmet/core/vasp/calc_types.py
espottesmith/emmet
bd28b91d240da9f0c996a2b2efb7e67da9176a09
[ "BSD-3-Clause-LBNL" ]
null
null
null
emmet-core/emmet/core/vasp/calc_types.py
espottesmith/emmet
bd28b91d240da9f0c996a2b2efb7e67da9176a09
[ "BSD-3-Clause-LBNL" ]
78
2020-11-16T06:46:43.000Z
2022-03-28T03:02:51.000Z
emmet-core/emmet/core/vasp/calc_types.py
utf/emmet
27a51a7ad4c300e280de5ba9b59a311dd77cffdd
[ "BSD-3-Clause-LBNL" ]
null
null
null
""" Module to define various calculation types as Enums for VASP """ import datetime from itertools import groupby, product from pathlib import Path from typing import Dict, Iterator, List import bson import numpy as np from monty.json import MSONable from monty.serialization import loadfn from pydantic import BaseMod...
28.391813
98
0.618332
600
4,855
4.836667
0.296667
0.038594
0.048243
0.022398
0.230875
0.215713
0.206065
0.206065
0.171606
0.091661
0
0.007198
0.256025
4,855
170
99
28.558824
0.796235
0.132441
0
0.077586
0
0.008621
0.173086
0.021453
0
0
0
0
0
1
0.034483
false
0
0.12069
0
0.206897
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
434df89c1b80cf68699882387250cf1a06bd4617
4,165
py
Python
models/train_classifier.py
YiWang-Evonne/disaster_response
824f646920ac85a01419101e17e92f592a505782
[ "MIT" ]
null
null
null
models/train_classifier.py
YiWang-Evonne/disaster_response
824f646920ac85a01419101e17e92f592a505782
[ "MIT" ]
null
null
null
models/train_classifier.py
YiWang-Evonne/disaster_response
824f646920ac85a01419101e17e92f592a505782
[ "MIT" ]
null
null
null
import sys import pandas as pd from sqlalchemy import create_engine import nltk nltk.download(['punkt', 'wordnet', 'averaged_perceptron_tagger']) import re from nltk.tokenize import word_tokenize from nltk.stem import WordNetLemmatizer from sklearn.metrics import classification_report from sklearn.metrics import confus...
30.181159
96
0.657143
511
4,165
5.162427
0.34638
0.033359
0.006823
0.018196
0.058378
0.017437
0
0
0
0
0
0.006213
0.227131
4,165
138
97
30.181159
0.813296
0.12605
0
0
0
0.0125
0.175208
0.037504
0
0
0
0
0
1
0.0875
false
0
0.2
0
0.3375
0.1
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
434e8c387b837394ff0f03da5e59c67d77ad7f7c
7,456
py
Python
experimental/attentive_uncertainty/toy_regression/datasets.py
miksu/edward2
973acdb23701f320ebaee8a56fc44d4414acfa4e
[ "Apache-2.0" ]
null
null
null
experimental/attentive_uncertainty/toy_regression/datasets.py
miksu/edward2
973acdb23701f320ebaee8a56fc44d4414acfa4e
[ "Apache-2.0" ]
null
null
null
experimental/attentive_uncertainty/toy_regression/datasets.py
miksu/edward2
973acdb23701f320ebaee8a56fc44d4414acfa4e
[ "Apache-2.0" ]
null
null
null
# coding=utf-8 # Copyright 2019 The Edward2 Authors. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law o...
37.467337
80
0.666309
1,062
7,456
4.428437
0.245763
0.039124
0.068467
0.034446
0.233893
0.143525
0.088454
0.073783
0.065703
0.015735
0
0.016679
0.244099
7,456
198
81
37.656566
0.817779
0.450644
0
0.056818
0
0
0.01463
0.005903
0
0
0
0
0
1
0.034091
false
0
0.068182
0
0.136364
0.011364
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
434ee97c218201d658ac3ee9f3df8bd8d8383c79
1,287
py
Python
critiquebrainz/frontend/views/index.py
shagun6/critiquebrainz
b7ae41fb09ff4dd4e34847b294fbee4ccc76bad5
[ "Apache-2.0" ]
null
null
null
critiquebrainz/frontend/views/index.py
shagun6/critiquebrainz
b7ae41fb09ff4dd4e34847b294fbee4ccc76bad5
[ "Apache-2.0" ]
null
null
null
critiquebrainz/frontend/views/index.py
shagun6/critiquebrainz
b7ae41fb09ff4dd4e34847b294fbee4ccc76bad5
[ "Apache-2.0" ]
1
2019-10-20T05:48:53.000Z
2019-10-20T05:48:53.000Z
from flask import Blueprint, render_template from flask_babel import format_number import critiquebrainz.db.users as db_users import critiquebrainz.db.review as db_review from bs4 import BeautifulSoup from markdown import markdown DEFAULT_CACHE_EXPIRATION = 10 * 60 # seconds frontend_bp = Blueprint('frontend', __nam...
31.390244
110
0.740482
163
1,287
5.576687
0.380368
0.044004
0.049505
0.082508
0
0
0
0
0
0
0
0.006446
0.156177
1,287
40
111
32.175
0.830571
0.059052
0
0
0
0
0.094606
0.017427
0
0
0
0
0
1
0.12
false
0
0.24
0.08
0.48
0.08
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
434fad48264cdf3b340402e86c40cd6b6db05bc8
2,406
py
Python
Enigma/Enigma-master/GBS/gbsHelper.py
Q-Alpha/Hackathon2020
c0ed45b4c1cc4f475f83786e641b859dad94f863
[ "MIT" ]
12
2020-07-23T17:11:22.000Z
2022-02-03T12:44:56.000Z
Enigma/Enigma-master/GBS/gbsHelper.py
Q-Alpha/Hackathon2020
c0ed45b4c1cc4f475f83786e641b859dad94f863
[ "MIT" ]
1
2020-07-28T13:35:51.000Z
2020-07-28T13:35:51.000Z
Enigma/Enigma-master/GBS/gbsHelper.py
Q-Alpha/Hackathon2020
c0ed45b4c1cc4f475f83786e641b859dad94f863
[ "MIT" ]
25
2020-07-22T14:32:17.000Z
2021-09-08T11:43:55.000Z
import strawberryfields as sf from strawberryfields import ops from strawberryfields.utils import random_interferometer from strawberryfields.apps import data, sample, subgraph, plot import plotly import networkx as nx import numpy as np class GBS: def __init__(self, samples =[], min_pho = 16, max_pho = 30, subgra...
34.869565
101
0.554032
365
2,406
3.528767
0.29863
0.02795
0.016304
0.025621
0.13354
0.052795
0.052795
0
0
0
0
0.05622
0.305071
2,406
68
102
35.382353
0.714115
0.082294
0
0
0
0
0.004543
0
0
0
0
0
0
1
0.076923
false
0
0.134615
0
0.288462
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
434fcaaddceb714a13ca57fae4621f94efbd1d3d
10,781
py
Python
happy/HappyNodeJoin.py
jenniexie/happy
6ba01586e20bb3e4f92e180fd8dce3752519f7c9
[ "Apache-2.0" ]
null
null
null
happy/HappyNodeJoin.py
jenniexie/happy
6ba01586e20bb3e4f92e180fd8dce3752519f7c9
[ "Apache-2.0" ]
null
null
null
happy/HappyNodeJoin.py
jenniexie/happy
6ba01586e20bb3e4f92e180fd8dce3752519f7c9
[ "Apache-2.0" ]
null
null
null
#!/usr/bin/env python # # Copyright (c) 2015-2017 Nest Labs, Inc. # All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licen...
35.463816
102
0.626472
1,384
10,781
4.666185
0.195087
0.04088
0.037163
0.022143
0.324094
0.227005
0.177454
0.111799
0.078043
0.065655
0
0.014068
0.274743
10,781
303
103
35.580858
0.811869
0.228457
0
0.180233
0
0
0.096893
0
0
0
0
0
0
1
0.093023
false
0
0.063953
0.011628
0.186047
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
434feac939e1b8979a11ce2e5fb237601f1fd855
46,866
py
Python
__init__.py
SDRAST/Data_Reduction
f007d716b5c28c086910a81206cffaf37ff6368c
[ "Apache-2.0" ]
null
null
null
__init__.py
SDRAST/Data_Reduction
f007d716b5c28c086910a81206cffaf37ff6368c
[ "Apache-2.0" ]
null
null
null
__init__.py
SDRAST/Data_Reduction
f007d716b5c28c086910a81206cffaf37ff6368c
[ "Apache-2.0" ]
null
null
null
# -*- coding: utf-8 -*- """ Modules to support data reduction in Python. The main purpose of the base module ``Data_Reduction`` is to provide a suplerclass with a good set of attributes and methods to cover all common needs. The base module is also able to read data from a text file as a ``numpy`` structured array. ...
35.370566
91
0.615307
6,185
46,866
4.582215
0.147615
0.021453
0.015349
0.006986
0.167672
0.118239
0.09181
0.077661
0.047281
0.035073
0
0.016119
0.275914
46,866
1,324
92
35.397281
0.819036
0.431912
0
0.195688
0
0
0.118994
0.011487
0
0
0
0
0
1
0.056385
false
0.019901
0.031509
0
0.139303
0.018242
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
435242d1a3384ab078fa9b2a0a84286b9581b8f8
8,483
py
Python
Context_Guided_RelRep/train.py
Huda-Hakami/Context-Guided-Relation-Embeddings
520ce89fe7bad3aba2f3eb112329300625bb55f7
[ "Apache-2.0" ]
1
2019-10-06T03:54:53.000Z
2019-10-06T03:54:53.000Z
Context_Guided_RelRep/train.py
Huda-Hakami/Context-Guided-Relation-Embeddings
520ce89fe7bad3aba2f3eb112329300625bb55f7
[ "Apache-2.0" ]
null
null
null
Context_Guided_RelRep/train.py
Huda-Hakami/Context-Guided-Relation-Embeddings
520ce89fe7bad3aba2f3eb112329300625bb55f7
[ "Apache-2.0" ]
null
null
null
import numpy as np from wordreps import WordReps from algebra import cosine, normalize import tensorflow as tf import random from dataset import DataSet import CGRE_Model from Eval import eval_SemEval import sklearn.preprocessing # ============ End Imports ============ class Training(): def __init__(self): # Compo...
37.870536
150
0.707651
1,352
8,483
4.190828
0.191568
0.057183
0.039005
0.039534
0.283975
0.249735
0.240205
0.195376
0.129721
0.104659
0
0.021547
0.11918
8,483
223
151
38.040359
0.736751
0.196393
0
0.012422
0
0.006211
0.099388
0.027011
0
0
0
0
0
1
0.043478
false
0
0.055901
0
0.124224
0.049689
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
43525bbf3ff2f6151c746e2a0599b8ee3f2bbfcc
1,071
py
Python
synch_integrate.py
HerculesJack/grtrans
bc005307d81dac1bdb9520e776e7627126dd690a
[ "MIT" ]
25
2016-02-11T01:52:14.000Z
2021-06-16T02:15:42.000Z
synch_integrate.py
RAnantua/grtrans
a0353a8516335412b27fe4866eabafcfc0fe498f
[ "MIT" ]
6
2016-11-10T15:25:20.000Z
2018-01-18T15:15:57.000Z
synch_integrate.py
RAnantua/grtrans
a0353a8516335412b27fe4866eabafcfc0fe498f
[ "MIT" ]
6
2016-02-11T14:13:01.000Z
2022-03-10T01:56:02.000Z
from radtrans_integrate import radtrans_integrate from polsynchemis import polsynchemis import numpy as np import scipy.integrate # calculate synchrotron emissivity for given coefficients def synch_jarho(nu,n,B,T,theta): if ((np.isscalar(nu)==False) & (np.isscalar(n)==True)): n = n + np.zeros(len(nu)) ...
36.931034
109
0.659197
171
1,071
4.040936
0.391813
0.196816
0.057887
0.069465
0.028944
0
0
0
0
0
0
0.033822
0.171802
1,071
28
110
38.25
0.745209
0.051354
0
0
0
0
0
0
0
0
0
0
0
1
0.08
false
0
0.16
0
0.32
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
435728a0cb21ad40d2d8c25c033f2746e09d0952
4,239
py
Python
apps/dash-port-analytics/app/ui/tab_map_controls.py
JeroenvdSande/dash-sample-apps
106fa24693cfdaf47c06466a0aed78e642344f91
[ "MIT" ]
2,332
2019-05-10T18:24:20.000Z
2022-03-30T21:46:29.000Z
apps/dash-port-analytics/app/ui/tab_map_controls.py
JeroenvdSande/dash-sample-apps
106fa24693cfdaf47c06466a0aed78e642344f91
[ "MIT" ]
384
2019-05-09T19:19:56.000Z
2022-03-12T00:58:24.000Z
apps/dash-port-analytics/app/ui/tab_map_controls.py
JeroenvdSande/dash-sample-apps
106fa24693cfdaf47c06466a0aed78e642344f91
[ "MIT" ]
3,127
2019-05-16T17:20:45.000Z
2022-03-31T17:59:07.000Z
import dash_core_components as dcc import dash_html_components as html from config import strings def make_tab_port_map_controls( port_arr: list, port_val: str, vessel_types_arr: list, vessel_type_val: str, year_arr: list, year_val: int, month_arr: list, month_val: int, ) -> html.Div: ...
38.889908
88
0.420854
359
4,239
4.844011
0.18663
0.056354
0.057504
0.098332
0.46406
0.46406
0.384704
0.384704
0.384704
0.317999
0
0
0.493041
4,239
108
89
39.25
0.809214
0.105685
0
0.55914
0
0
0.15325
0.113132
0
0
0
0
0
1
0.010753
false
0
0.032258
0
0.053763
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
435a70dd7b6f4dda69b0f2a7703c3f754714213d
22,429
py
Python
graphql_compiler/compiler/workarounds/orientdb_query_execution.py
0xflotus/graphql-compiler
0c892f5254d0cf3d03a68012080d0b736bc49913
[ "Apache-2.0" ]
null
null
null
graphql_compiler/compiler/workarounds/orientdb_query_execution.py
0xflotus/graphql-compiler
0c892f5254d0cf3d03a68012080d0b736bc49913
[ "Apache-2.0" ]
1
2019-04-18T18:23:16.000Z
2019-04-18T18:23:16.000Z
graphql_compiler/compiler/workarounds/orientdb_query_execution.py
0xflotus/graphql-compiler
0c892f5254d0cf3d03a68012080d0b736bc49913
[ "Apache-2.0" ]
1
2019-11-21T02:38:27.000Z
2019-11-21T02:38:27.000Z
# Copyright 2018-present Kensho Technologies, LLC. """Workarounds for OrientDB scheduler issue that causes poor query planning for certain queries. For purposes of query planning, the OrientDB query planner ignores "where:" clauses that hit indexes but do not use the "=" operator. For example, "CONTAINS" can be used t...
58.257143
100
0.664452
2,854
22,429
5.033987
0.160827
0.035707
0.037029
0.013782
0.361453
0.316002
0.262616
0.214311
0.171574
0.162595
0
0.001066
0.289045
22,429
384
101
58.408854
0.899912
0.456418
0
0.36612
0
0
0.05754
0
0
0
0
0.005208
0.060109
1
0.043716
false
0.016393
0.021858
0
0.10929
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
435b03494c0e0f08adce48e2055f1eb32e5446ba
3,763
py
Python
traffic_light/core.py
ofalk/cleware-traffic-light
be319fec8e190811463ade8aabc37ca2b4f17e57
[ "MIT" ]
null
null
null
traffic_light/core.py
ofalk/cleware-traffic-light
be319fec8e190811463ade8aabc37ca2b4f17e57
[ "MIT" ]
null
null
null
traffic_light/core.py
ofalk/cleware-traffic-light
be319fec8e190811463ade8aabc37ca2b4f17e57
[ "MIT" ]
null
null
null
from enum import IntEnum import functools import usb.core import usb.util from traffic_light.error import TrafficLightError, MultipleTrafficLightsError BM_REQUEST_TYPE = 0x21 B_REQUEST = 0x09 W_VALUE = 0x200 W_INDEX = 0x00 ID_VENDOR = 0x0d50 ID_PRODUCT = 0x0008 INTERFACE = 0 class Color(IntEnum): RED = 0x10 ...
32.439655
122
0.60962
435
3,763
5.147126
0.358621
0.03573
0.014739
0.033497
0.103618
0.084859
0.032157
0
0
0
0
0.017557
0.303747
3,763
115
123
32.721739
0.837023
0.155195
0
0.154762
0
0
0.09041
0
0
0
0.016468
0
0
1
0.107143
false
0
0.059524
0
0.321429
0.035714
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
435b7f5d139890173dc2cf9019b51215cc554d6e
3,646
py
Python
sdk/cognitivelanguage/azure-ai-language-conversations/samples/async/sample_analyze_orchestration_app_luis_response_async.py
dubiety/azure-sdk-for-python
62ffa839f5d753594cf0fe63668f454a9d87a346
[ "MIT" ]
1
2022-02-01T18:50:12.000Z
2022-02-01T18:50:12.000Z
sdk/cognitivelanguage/azure-ai-language-conversations/samples/async/sample_analyze_orchestration_app_luis_response_async.py
ellhe-blaster/azure-sdk-for-python
82193ba5e81cc5e5e5a5239bba58abe62e86f469
[ "MIT" ]
null
null
null
sdk/cognitivelanguage/azure-ai-language-conversations/samples/async/sample_analyze_orchestration_app_luis_response_async.py
ellhe-blaster/azure-sdk-for-python
82193ba5e81cc5e5e5a5239bba58abe62e86f469
[ "MIT" ]
null
null
null
# coding=utf-8 # ------------------------------------ # Copyright (c) Microsoft Corporation. # Licensed under the MIT License. # ------------------------------------ """ FILE: sample_analyze_orchestration_app_luis_response_async.py DESCRIPTION: This sample demonstrates how to analyze user query using an orchestra...
39.630435
106
0.637685
372
3,646
6
0.36828
0.048387
0.061828
0.072581
0.228943
0.167563
0.084229
0.043011
0
0
0
0.002911
0.246297
3,646
92
107
39.630435
0.809316
0.328305
0
0
0
0
0.259564
0.055944
0
0
0
0
0
1
0
false
0
0.078431
0
0.078431
0.176471
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
435f04515eafc16cb9b3781591916aadd65a8bd3
2,499
py
Python
intro/deploy.py
terziev-viktor/SolidityCourse
6f10852e94eec69438c5e577795d317694227337
[ "MIT" ]
null
null
null
intro/deploy.py
terziev-viktor/SolidityCourse
6f10852e94eec69438c5e577795d317694227337
[ "MIT" ]
null
null
null
intro/deploy.py
terziev-viktor/SolidityCourse
6f10852e94eec69438c5e577795d317694227337
[ "MIT" ]
null
null
null
import json from web3 import Web3 from solcx import compile_standard, install_solc with open("./SimpleStorage.sol", "r") as file: simple_storage_src = file.read() # install solcx install_solc("0.8.0") # compile the source compiled_sol = compile_standard( { "language": "Solidity", "sources": ...
31.2375
147
0.708283
293
2,499
5.832765
0.368601
0.032183
0.018724
0.038619
0.250439
0.218841
0.129901
0.0866
0.0866
0.0866
0
0.045933
0.163665
2,499
79
148
31.632911
0.77177
0.109244
0
0
0
0
0.198825
0.058292
0
0
0.048803
0
0
1
0
false
0
0.058824
0
0.058824
0.058824
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
4361a9278aa18283e07b14ec0d517fca7051b980
9,550
py
Python
info_popup.py
cartazio/SublimeHaskell
e6f12ea69de939d12212a6ec594bf0aae0603f6d
[ "MIT" ]
2
2021-07-07T16:41:48.000Z
2021-11-17T11:08:50.000Z
info_popup.py
cartazio/SublimeHaskell
e6f12ea69de939d12212a6ec594bf0aae0603f6d
[ "MIT" ]
null
null
null
info_popup.py
cartazio/SublimeHaskell
e6f12ea69de939d12212a6ec594bf0aae0603f6d
[ "MIT" ]
null
null
null
import urllib.parse import webbrowser import json from xml.etree import ElementTree import sublime import SublimeHaskell.sublime_haskell_common as Common import SublimeHaskell.internals.utils as Utils import SublimeHaskell.internals.unicode_opers as UnicodeOpers import SublimeHaskell.symbols as symbols import Sublim...
42.070485
126
0.566387
1,087
9,550
4.789328
0.23827
0.030734
0.006915
0.00922
0.145601
0.119093
0.078371
0.062236
0.062236
0.062236
0
0.006048
0.324817
9,550
226
127
42.256637
0.801334
0.093717
0
0.136095
0
0
0.07837
0.024846
0
0
0
0.004425
0
1
0.065089
false
0.011834
0.118343
0
0.236686
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
4361a9d08c25b0f208bbec15d3be738264785d14
4,126
py
Python
modules/google_home_lights.py
artizanatweb/ghome-assistant
dba2bc58979ebae48afc71c356ae2d40b8830eee
[ "Apache-2.0" ]
null
null
null
modules/google_home_lights.py
artizanatweb/ghome-assistant
dba2bc58979ebae48afc71c356ae2d40b8830eee
[ "Apache-2.0" ]
null
null
null
modules/google_home_lights.py
artizanatweb/ghome-assistant
dba2bc58979ebae48afc71c356ae2d40b8830eee
[ "Apache-2.0" ]
null
null
null
#!/usr/bin/env python # Copyright (C) 2017 Seeed Technology Limited # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by ...
24.128655
74
0.542414
547
4,126
4.025594
0.261426
0.061308
0.045413
0.029973
0.311989
0.266122
0.231608
0.21753
0.144414
0.144414
0
0.042773
0.342705
4,126
171
75
24.128655
0.769174
0.145904
0
0.347826
0
0
0.003704
0
0
0
0
0
0
1
0.121739
false
0
0.06087
0
0.191304
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
43626cff0461fc1edbacac7b7a76a2f308ada971
5,016
py
Python
tensortools/optimize/mncp_hals.py
klmcguir/tensortools
38262f5bad9d3171286e34e5f15d196752dda939
[ "MIT" ]
null
null
null
tensortools/optimize/mncp_hals.py
klmcguir/tensortools
38262f5bad9d3171286e34e5f15d196752dda939
[ "MIT" ]
null
null
null
tensortools/optimize/mncp_hals.py
klmcguir/tensortools
38262f5bad9d3171286e34e5f15d196752dda939
[ "MIT" ]
null
null
null
""" Nonnegative CP decomposition by Hierarchical alternating least squares (HALS). With support for missing data. """ import numpy as np import scipy as sci from scipy import linalg from tensortools.operations import unfold, khatri_rao from tensortools.tensors import KTensor from tensortools.optimize import FitResult...
40.780488
94
0.60626
617
5,016
4.860616
0.388979
0.035012
0.023008
0.024008
0.132044
0.086029
0.058686
0
0
0
0
0.007922
0.245016
5,016
123
95
40.780488
0.783998
0.692185
0
0
0
0
0.009174
0
0
0
0
0
0
1
0.038462
false
0
0.269231
0
0.346154
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
4363164b554bb6ade5f87250305647778400993f
18,079
py
Python
raredecay/tools/data_tools.py
jonas-eschle/raredecay
6285f91e0819d01c80125f50b24e60ee5353ae2e
[ "Apache-2.0" ]
7
2016-11-19T17:28:07.000Z
2020-12-29T19:49:37.000Z
raredecay/tools/data_tools.py
mayou36/raredecay
5b319ada66ebe54f81e216efad81fc9f06237a30
[ "Apache-2.0" ]
23
2017-03-13T19:13:58.000Z
2021-05-30T21:48:50.000Z
raredecay/tools/data_tools.py
jonas-eschle/raredecay
6285f91e0819d01c80125f50b24e60ee5353ae2e
[ "Apache-2.0" ]
5
2016-12-17T19:24:13.000Z
2021-05-31T14:32:34.000Z
""" @author: Jonas Eschle "Mayou36" DEPRECEATED! USE OTHER MODULES LIKE rd.data, rd.ml, rd.reweight, rd.score and rd.stat DEPRECEATED!DEPRECEATED!DEPRECEATED!DEPRECEATED!DEPRECEATED! Contains several tools to convert, load, save and plot data """ import warnings import os import copy import pandas as pd import...
34.969052
117
0.636872
2,497
18,079
4.429315
0.161394
0.053707
0.014919
0.015913
0.242767
0.194846
0.165371
0.149458
0.142224
0.135895
0
0.004557
0.271752
18,079
516
118
35.036822
0.835485
0.44571
0
0.230415
0
0
0.037895
0
0
0
0
0.005814
0.013825
1
0.069124
false
0.009217
0.059908
0
0.21659
0.004608
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
4363297eb771b020c864cdfbc69be70aff1727b6
2,052
py
Python
toontown/coghq/boardbothq/BoardOfficeManagerAI.py
LittleNed/toontown-stride
1252a8f9a8816c1810106006d09c8bdfe6ad1e57
[ "Apache-2.0" ]
1
2018-06-16T23:06:38.000Z
2018-06-16T23:06:38.000Z
toontown/coghq/boardbothq/BoardOfficeManagerAI.py
NoraTT/Historical-Commits-Project-Altis-Source
fe88e6d07edf418f7de6ad5b3d9ecb3d0d285179
[ "Apache-2.0" ]
null
null
null
toontown/coghq/boardbothq/BoardOfficeManagerAI.py
NoraTT/Historical-Commits-Project-Altis-Source
fe88e6d07edf418f7de6ad5b3d9ecb3d0d285179
[ "Apache-2.0" ]
4
2019-06-20T23:45:23.000Z
2020-10-14T20:30:15.000Z
from direct.directnotify import DirectNotifyGlobal import DistributedBoardOfficeAI from toontown.toonbase import ToontownGlobals from toontown.coghq.boardbothq import BoardOfficeLayout from direct.showbase import DirectObject import random class BoardOfficeManagerAI(DirectObject.DirectObject): notify = DirectNotif...
41.04
141
0.639376
187
2,052
6.973262
0.358289
0.023006
0.020706
0.03681
0.11273
0.062117
0.062117
0
0
0
0
0.002714
0.281676
2,052
49
142
41.877551
0.881954
0
0
0.119048
0
0
0.070175
0
0
0
0
0
0
1
0.071429
false
0
0.166667
0.02381
0.357143
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
436393af32e8421a7a3401c8eb82314850e79873
2,144
py
Python
ansiblemetrics/utils.py
radon-h2020/AnsibleMetrics
8a8e27d9b54fc1578d00526c8663184a2e686cb2
[ "Apache-2.0" ]
1
2020-04-24T16:09:14.000Z
2020-04-24T16:09:14.000Z
ansiblemetrics/utils.py
radon-h2020/AnsibleMetrics
8a8e27d9b54fc1578d00526c8663184a2e686cb2
[ "Apache-2.0" ]
null
null
null
ansiblemetrics/utils.py
radon-h2020/AnsibleMetrics
8a8e27d9b54fc1578d00526c8663184a2e686cb2
[ "Apache-2.0" ]
null
null
null
from typing import Union def key_value_list(d: Union[dict, list], key=None) -> list: """ This function iterates over all the key-value pairs of a dictionary and returns a list of tuple (key, value) where the key contain only primitive value (i.e., no list or dict), e.g., string, number etc. d -- a diction...
25.831325
206
0.564366
301
2,144
3.950166
0.199336
0.083263
0.070648
0.035324
0.541632
0.541632
0.518923
0.471825
0.392767
0.335576
0
0
0.333022
2,144
82
207
26.146341
0.831469
0.215951
0
0.470588
0
0
0
0
0
0
0
0
0
1
0.058824
false
0
0.019608
0
0.254902
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
4364ccde24cc2af35ff42479b35b005f175a3209
24,502
py
Python
phy/gui/actions.py
ycanerol/phy
7a247f926dd5bf5d8ab95fe138e8f4a0db11b068
[ "BSD-3-Clause" ]
118
2019-06-03T06:19:43.000Z
2022-03-25T00:05:26.000Z
phy/gui/actions.py
ycanerol/phy
7a247f926dd5bf5d8ab95fe138e8f4a0db11b068
[ "BSD-3-Clause" ]
761
2015-01-08T11:17:41.000Z
2019-05-27T16:12:08.000Z
phy/gui/actions.py
ycanerol/phy
7a247f926dd5bf5d8ab95fe138e8f4a0db11b068
[ "BSD-3-Clause" ]
70
2019-05-30T11:05:26.000Z
2022-03-30T11:51:23.000Z
# -*- coding: utf-8 -*- """Actions and snippets.""" # ----------------------------------------------------------------------------- # Imports # ----------------------------------------------------------------------------- import inspect from functools import partial, wraps import logging import re import sys import...
35.305476
99
0.587952
2,938
24,502
4.792716
0.141253
0.022655
0.01811
0.009445
0.212201
0.128116
0.111356
0.088346
0.081812
0.056956
0
0.002845
0.282793
24,502
693
100
35.356421
0.798441
0.324218
0
0.198939
0
0
0.064941
0.003771
0
0
0
0
0.02122
1
0.106101
false
0.007958
0.02122
0.002653
0.249337
0.023873
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
436637ae94348f41cc38697c102e03126553cd4f
807
py
Python
PP4E-Examples-1.4/Examples/PP4E/Tools/cleanpyc.py
AngelLiang/PP4E
3a7f63b366e1e4700b4d2524884696999a87ba9d
[ "MIT" ]
null
null
null
PP4E-Examples-1.4/Examples/PP4E/Tools/cleanpyc.py
AngelLiang/PP4E
3a7f63b366e1e4700b4d2524884696999a87ba9d
[ "MIT" ]
null
null
null
PP4E-Examples-1.4/Examples/PP4E/Tools/cleanpyc.py
AngelLiang/PP4E
3a7f63b366e1e4700b4d2524884696999a87ba9d
[ "MIT" ]
null
null
null
""" delete all .pyc bytecode files in a directory tree: use the command line arg as root if given, else current working dir """ import os, sys findonly = False rootdir = os.getcwd() if len(sys.argv) == 1 else sys.argv[1] found = removed = 0 for (thisDirLevel, subsHere, filesHere) in os.walk(rootdir): for filename...
31.038462
65
0.553903
96
807
4.645833
0.59375
0.03139
0.035874
0
0
0
0
0
0
0
0
0.012915
0.328377
807
25
66
32.28
0.809963
0.14746
0
0
0
0
0.048529
0
0
0
0
0
0
1
0
false
0
0.055556
0
0.055556
0.166667
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
43670f7c99a2ebd5fc17181669e6be4597ca4939
25,401
py
Python
apps/controllerx/cx_core/type/light_controller.py
clach04/controllerx
b5cd92d3371c352c50f7d5ba7dae4538d7c15dfe
[ "MIT" ]
null
null
null
apps/controllerx/cx_core/type/light_controller.py
clach04/controllerx
b5cd92d3371c352c50f7d5ba7dae4538d7c15dfe
[ "MIT" ]
null
null
null
apps/controllerx/cx_core/type/light_controller.py
clach04/controllerx
b5cd92d3371c352c50f7d5ba7dae4538d7c15dfe
[ "MIT" ]
null
null
null
from typing import Any, Dict, Optional, Type, Union from cx_const import Light, PredefinedActionsMapping from cx_core.color_helper import get_color_wheel from cx_core.controller import action from cx_core.feature_support.light import LightSupport from cx_core.integration import EventData from cx_core.integration.decon...
37.686944
117
0.565332
2,526
25,401
5.4327
0.112035
0.101436
0.046491
0.036071
0.478102
0.37193
0.28077
0.213364
0.174525
0.163521
0
0.004411
0.357427
25,401
673
118
37.742942
0.836233
0.074761
0
0.470389
0
0
0.054828
0.008555
0
0
0
0
0
1
0.00846
false
0
0.021997
0.005076
0.093063
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
436a1ebb3d99a1475a443393df66a840b227b6bf
4,916
py
Python
src/command_modules/azure-cli-security/azure/cli/command_modules/security/_params.py
jfcoz/azure-cli
8459ef3fd3c76d9f99defd95d4c980923891fa6d
[ "MIT" ]
1
2019-10-01T10:29:15.000Z
2019-10-01T10:29:15.000Z
src/command_modules/azure-cli-security/azure/cli/command_modules/security/_params.py
jfcoz/azure-cli
8459ef3fd3c76d9f99defd95d4c980923891fa6d
[ "MIT" ]
3
2019-07-12T22:10:38.000Z
2019-07-12T22:10:49.000Z
src/command_modules/azure-cli-security/azure/cli/command_modules/security/_params.py
jfcoz/azure-cli
8459ef3fd3c76d9f99defd95d4c980923891fa6d
[ "MIT" ]
1
2019-06-21T05:08:09.000Z
2019-06-21T05:08:09.000Z
# -------------------------------------------------------------------------------------------- # Copyright (c) Microsoft Corporation. All rights reserved. # Licensed under the MIT License. See License.txt in the project root for license information. # --------------------------------------------------------------------...
47.728155
198
0.621237
516
4,916
5.666667
0.24031
0.076607
0.082763
0.109097
0.392955
0.198358
0.147743
0.147743
0.121067
0.121067
0
0
0.240236
4,916
102
199
48.196078
0.782865
0.086859
0
0.246753
0
0
0.267753
0.027914
0
0
0
0
0
1
0.012987
false
0
0.038961
0
0.051948
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
436a53c20b8a7b3181b33290aeb94d9c5458f945
1,558
py
Python
tests/models/test_transformers.py
Alicegaz/torchok
7b8f95df466a25b1ad8ee93bed1a3c7516440cf4
[ "Apache-2.0" ]
8
2021-10-12T05:39:20.000Z
2022-03-31T10:55:01.000Z
tests/models/test_transformers.py
Alicegaz/torchok
7b8f95df466a25b1ad8ee93bed1a3c7516440cf4
[ "Apache-2.0" ]
1
2022-03-30T19:23:42.000Z
2022-03-30T19:23:42.000Z
tests/models/test_transformers.py
Alicegaz/torchok
7b8f95df466a25b1ad8ee93bed1a3c7516440cf4
[ "Apache-2.0" ]
5
2021-11-17T07:38:28.000Z
2022-01-31T10:46:36.000Z
import unittest import torch from parameterized import parameterized from src.constructor import create_backbone from src.models.backbones.utils import list_models from .test_segmentation import example_backbones def inp(bsize, in_ch, w, h): return torch.ones(bsize, in_ch, w, h) class TestBackboneCorrectness(...
38.95
99
0.717587
205
1,558
5.24878
0.331707
0.066915
0.064126
0.080855
0.604089
0.469331
0.469331
0.469331
0.438662
0.438662
0
0.003837
0.163671
1,558
39
100
39.948718
0.821949
0
0
0.333333
0
0
0.030167
0
0
0
0
0
0
1
0.166667
false
0
0.2
0.033333
0.433333
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
436d01399c03b77d98f4cf23e9025181a7999308
3,767
py
Python
app/app.py
shaswat01/Disaster_Response_ETL
c441514fb5231d193cd4b29afad00fe0f3513562
[ "MIT" ]
null
null
null
app/app.py
shaswat01/Disaster_Response_ETL
c441514fb5231d193cd4b29afad00fe0f3513562
[ "MIT" ]
null
null
null
app/app.py
shaswat01/Disaster_Response_ETL
c441514fb5231d193cd4b29afad00fe0f3513562
[ "MIT" ]
null
null
null
import nltk import json import plotly import pandas as pd import plotly.graph_objects as go from nltk.stem import WordNetLemmatizer from nltk.tokenize import word_tokenize nltk.download(['punkt','wordnet']) from flask import Flask from flask import render_template, request, jsonify from plotly.graph_objs import Bar, H...
25.281879
131
0.528537
386
3,767
5.056995
0.411917
0.020492
0.012295
0.025615
0
0
0
0
0
0
0
0.007383
0.352801
3,767
148
132
25.452703
0.793273
0.120255
0
0.174757
0
0
0.137094
0.010312
0
0
0
0
0
1
0.038835
false
0
0.116505
0
0.184466
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
436d1a37515679503cc50623874a3539d00946be
4,659
py
Python
tools/mo/openvino/tools/mo/front/mxnet/mx_reshape_reverse.py
pazamelin/openvino
b7e8ef910d7ed8e52326d14dc6fd53b71d16ed48
[ "Apache-2.0" ]
1
2019-09-22T01:05:07.000Z
2019-09-22T01:05:07.000Z
tools/mo/openvino/tools/mo/front/mxnet/mx_reshape_reverse.py
pazamelin/openvino
b7e8ef910d7ed8e52326d14dc6fd53b71d16ed48
[ "Apache-2.0" ]
58
2020-11-06T12:13:45.000Z
2022-03-28T13:20:11.000Z
tools/mo/openvino/tools/mo/front/mxnet/mx_reshape_reverse.py
pazamelin/openvino
b7e8ef910d7ed8e52326d14dc6fd53b71d16ed48
[ "Apache-2.0" ]
2
2019-09-20T01:33:37.000Z
2019-09-20T08:42:11.000Z
# Copyright (C) 2018-2021 Intel Corporation # SPDX-License-Identifier: Apache-2.0 import numpy as np from openvino.tools.mo.front.mxnet.mx_reshape_to_reshape import MXReshapeToReshape from openvino.tools.mo.ops.Reverse import Reverse from openvino.tools.mo.ops.mxreshape import MXReshape from openvino.tools.mo.front.c...
59.730769
127
0.69457
598
4,659
5.137124
0.192308
0.042318
0.042318
0.046875
0.593099
0.484701
0.37207
0.257813
0.166667
0.152344
0
0.017483
0.201975
4,659
77
128
60.506494
0.808768
0.087787
0
0
0
0
0.040986
0
0
0
0
0
0
1
0.037037
false
0
0.222222
0.018519
0.351852
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
436dafbd787a4e7854f10318324bcf64277e6432
6,480
py
Python
Python/Simulation/Numerical_Methods/test_cubic_spline_solve.py
MattMarti/Lambda-Trajectory-Sim
4155f103120bd49221776cc3b825b104f36817f2
[ "MIT" ]
null
null
null
Python/Simulation/Numerical_Methods/test_cubic_spline_solve.py
MattMarti/Lambda-Trajectory-Sim
4155f103120bd49221776cc3b825b104f36817f2
[ "MIT" ]
null
null
null
Python/Simulation/Numerical_Methods/test_cubic_spline_solve.py
MattMarti/Lambda-Trajectory-Sim
4155f103120bd49221776cc3b825b104f36817f2
[ "MIT" ]
null
null
null
import unittest; import numpy as np; import scipy as sp; from cubic_spline_solve import cubic_spline_solve; from cubic_spline_fun import cubic_spline_fun; class Test_cubic_spline_solve(unittest.TestCase): ''' Test_cubicsplineSolve Test case for the cubic spline solver function. This function just solv...
37.241379
78
0.564352
795
6,480
4.525786
0.197484
0.073374
0.080044
0.100056
0.651473
0.629516
0.61284
0.611451
0.444692
0.423013
0
0.036954
0.310957
6,480
174
79
37.241379
0.768869
0.194907
0
0.48
0
0
0.009957
0
0
0
0
0
0.14
1
0.05
false
0
0.05
0
0.13
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
4370bea6e2a16934ad57aff4637712bbcfdb6bc4
331
py
Python
1805_number_of_different_integers_in_a_string.py
hotternative/leetcode
d0ec225abc2ada1398666641c7872f3eb889e7ed
[ "MIT" ]
null
null
null
1805_number_of_different_integers_in_a_string.py
hotternative/leetcode
d0ec225abc2ada1398666641c7872f3eb889e7ed
[ "MIT" ]
null
null
null
1805_number_of_different_integers_in_a_string.py
hotternative/leetcode
d0ec225abc2ada1398666641c7872f3eb889e7ed
[ "MIT" ]
null
null
null
from string import ascii_lowercase ts = 'a123bc34d8ef34' cur = [] res = set() for c in ts: if c in ascii_lowercase: if cur: s = ''.join(cur) res.add(int(s)) cur = [] else: cur.append(c) else: if cur: s = ''.join(cur) res.add(int(s)) pri...
13.24
34
0.480363
45
331
3.488889
0.466667
0.11465
0.076433
0.127389
0.292994
0.292994
0.292994
0.292994
0.292994
0
0
0.039216
0.383686
331
24
35
13.791667
0.730392
0
0
0.588235
0
0
0.042683
0
0
0
0
0
0
1
0
false
0
0.058824
0
0.058824
0.058824
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
4371e6643a58d749ad832f8647f0481df0293c7c
1,087
py
Python
app.py
ahmedriaz9908/memeapiiz
eef98f837f2ec83edc3dd004f19dcefda9b582a5
[ "MIT" ]
null
null
null
app.py
ahmedriaz9908/memeapiiz
eef98f837f2ec83edc3dd004f19dcefda9b582a5
[ "MIT" ]
null
null
null
app.py
ahmedriaz9908/memeapiiz
eef98f837f2ec83edc3dd004f19dcefda9b582a5
[ "MIT" ]
null
null
null
from flask import Flask, render_template, jsonify from reddit_handler import * app = Flask(__name__) meme_subreddits = ['izlam'] @app.route('/') def index(): return render_template('index.html') @app.route('/meme') def one_post(): sub = random.choice(meme_subreddits) re = get_posts(sub...
20.12963
84
0.601656
146
1,087
4.308219
0.308219
0.133545
0.127186
0.09539
0.303657
0.303657
0.303657
0.303657
0.18442
0.18442
0
0.020631
0.24195
1,087
53
85
20.509434
0.742718
0
0
0.235294
0
0
0.10058
0
0
0
0
0
0
1
0.147059
false
0
0.058824
0.058824
0.352941
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
4372f137c065f7fda02b994b61b1b4bd3b7965e5
1,775
py
Python
pyrite/llvm.py
iahuang/pyrite
0db83aad6aa8f245edf13d393f65d408eb956c4d
[ "MIT" ]
null
null
null
pyrite/llvm.py
iahuang/pyrite
0db83aad6aa8f245edf13d393f65d408eb956c4d
[ "MIT" ]
1
2022-03-28T00:35:11.000Z
2022-03-29T21:17:06.000Z
pyrite/llvm.py
iahuang/pyrite
0db83aad6aa8f245edf13d393f65d408eb956c4d
[ "MIT" ]
null
null
null
import shutil from pyrite import fs from pyrite.command_line import run_command from pyrite.errors import UserError from pyrite.globals import Globals from os.path import join class LLVMInterface: _clang_path: str def __init__(self): self._clang_path = self._get_clang_path() def _get_clang_path(s...
29.583333
127
0.60507
213
1,775
4.826291
0.41784
0.070039
0.066148
0.061284
0.05642
0.05642
0
0
0
0
0
0
0.316056
1,775
59
128
30.084746
0.846787
0.132958
0
0.108108
0
0
0.138889
0
0
0
0
0
0
1
0.108108
false
0
0.162162
0
0.378378
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
43741937702bf1405a4a4845184d5f67e95b3dd1
526
py
Python
bag_recursive.py
eduardogerentklein/Algoritmos-Geneticos
499836ac4867240ee3777dcdd554081a480cb8c9
[ "MIT" ]
null
null
null
bag_recursive.py
eduardogerentklein/Algoritmos-Geneticos
499836ac4867240ee3777dcdd554081a480cb8c9
[ "MIT" ]
null
null
null
bag_recursive.py
eduardogerentklein/Algoritmos-Geneticos
499836ac4867240ee3777dcdd554081a480cb8c9
[ "MIT" ]
null
null
null
maxWeight = 30 value = [15, 7, 10, 5, 8, 17] weight = [15, 3, 2, 5, 9, 20] def bag(pos, selected): # calcula o total totalValue = 0 pesoTotal = 0 for i in selected: totalValue += value[i] pesoTotal += weight[i] if pesoTotal > maxWeight: return (0,0) if pos >= len(weight): return (totalValue, pesoT...
18.137931
41
0.629278
77
526
4.298701
0.480519
0.054381
0.042296
0
0
0
0
0
0
0
0
0.083538
0.226236
526
29
42
18.137931
0.72973
0.028517
0
0
0
0
0
0
0
0
0
0
0
1
0.047619
false
0
0
0
0.238095
0.047619
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
43785386d2679f8fabe7de8f8acd7359d1da2540
5,112
py
Python
task3/task3_xgb_cv.py
meck93/intro_ml
903710b13e9eed8b45fdbd9957c2fb49b2981f62
[ "MIT" ]
null
null
null
task3/task3_xgb_cv.py
meck93/intro_ml
903710b13e9eed8b45fdbd9957c2fb49b2981f62
[ "MIT" ]
null
null
null
task3/task3_xgb_cv.py
meck93/intro_ml
903710b13e9eed8b45fdbd9957c2fb49b2981f62
[ "MIT" ]
null
null
null
from sklearn.metrics import accuracy_score from sklearn.model_selection import train_test_split from sklearn.preprocessing import StandardScaler from sklearn.feature_selection import f_classif, SelectKBest import numpy as np import pandas as pd import os mingw_path = 'C:\\Program Files\\mingw-w64\\x86_64-7.2.0-posix...
32.35443
150
0.714593
762
5,112
4.536745
0.23622
0.041655
0.032398
0.023141
0.372867
0.306624
0.273648
0.234596
0.18166
0.140006
0
0.020559
0.153169
5,112
157
151
32.56051
0.778009
0.382042
0
0
0
0.015625
0.17188
0.021283
0
0
0
0
0
1
0
false
0
0.125
0
0.125
0.078125
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
4378f461808522c0661a502153858f383b5e6b02
1,369
py
Python
discovery-provider/src/queries/get_plays_metrics.py
atticwip/audius-protocol
9758e849fae01508fa1d27675741228b11533e6e
[ "Apache-2.0" ]
429
2019-08-14T01:34:07.000Z
2022-03-30T06:31:38.000Z
discovery-provider/src/queries/get_plays_metrics.py
SNOmad1/audius-protocol
3d5fc2bf688265eb529060f1f3234ef2b95ed231
[ "Apache-2.0" ]
998
2019-08-14T01:52:37.000Z
2022-03-31T23:17:22.000Z
discovery-provider/src/queries/get_plays_metrics.py
SNOmad1/audius-protocol
3d5fc2bf688265eb529060f1f3234ef2b95ed231
[ "Apache-2.0" ]
73
2019-10-04T04:24:16.000Z
2022-03-24T16:27:30.000Z
import logging import time from sqlalchemy import func, desc from src.models import Play from src.utils import db_session logger = logging.getLogger(__name__) def get_plays_metrics(args): """ Returns metrics for play counts Args: args: dict The parsed args from the request args.start_tim...
27.938776
82
0.646457
180
1,369
4.733333
0.4
0.032864
0.052817
0.042254
0.161972
0.100939
0.100939
0.100939
0.100939
0.100939
0
0.001955
0.252739
1,369
48
83
28.520833
0.83089
0.252739
0
0
0
0
0.075587
0
0
0
0
0
0
1
0.068966
false
0
0.172414
0
0.310345
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0