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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
656ac88a30aabd5ff916cfe1185c9c545d4edbba
| 155
|
py
|
Python
|
config/__init__.py
|
zhouhongf/spider_pdf
|
c059f0003b5c8a2dab1e735ff456ba2bc9c799ac
|
[
"MIT"
] | 1
|
2021-11-27T06:40:45.000Z
|
2021-11-27T06:40:45.000Z
|
config/__init__.py
|
zhouhongf/spider_pdf
|
c059f0003b5c8a2dab1e735ff456ba2bc9c799ac
|
[
"MIT"
] | null | null | null |
config/__init__.py
|
zhouhongf/spider_pdf
|
c059f0003b5c8a2dab1e735ff456ba2bc9c799ac
|
[
"MIT"
] | 1
|
2022-01-15T07:48:38.000Z
|
2022-01-15T07:48:38.000Z
|
from .config import Config
from .log import Logger
from .decorators import singleton
from .document import Document
from .bank_dict import BankDict
| 22.142857
| 34
| 0.793548
| 21
| 155
| 5.809524
| 0.52381
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| 0.174194
| 155
| 6
| 35
| 25.833333
| 0.953125
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| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
65cbc226f1629bb6f2c4af8857c919f931c0bc1b
| 96
|
py
|
Python
|
venv/lib/python3.8/site-packages/yapf/yapflib/pytree_visitor.py
|
Retraces/UkraineBot
|
3d5d7f8aaa58fa0cb8b98733b8808e5dfbdb8b71
|
[
"MIT"
] | 2
|
2022-03-13T01:58:52.000Z
|
2022-03-31T06:07:54.000Z
|
venv/lib/python3.8/site-packages/yapf/yapflib/pytree_visitor.py
|
DesmoSearch/Desmobot
|
b70b45df3485351f471080deb5c785c4bc5c4beb
|
[
"MIT"
] | 19
|
2021-11-20T04:09:18.000Z
|
2022-03-23T15:05:55.000Z
|
venv/lib/python3.8/site-packages/yapf/yapflib/pytree_visitor.py
|
DesmoSearch/Desmobot
|
b70b45df3485351f471080deb5c785c4bc5c4beb
|
[
"MIT"
] | null | null | null |
/home/runner/.cache/pip/pool/ab/31/fe/df84ea3c0efbe98408895bfadd27d84653aec49887db1df29cbc6c8661
| 96
| 96
| 0.895833
| 9
| 96
| 9.555556
| 1
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| 0
| 0
| 0.354167
| 0
| 96
| 1
| 96
| 96
| 0.541667
| 0
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| null | null | 0
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| 0
| null | 0
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| 0
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| 0
| 0
|
0
| 5
|
65cce00ab531c32d8cd37e967c83f82595017722
| 434
|
py
|
Python
|
src/euler_python_package/euler_python/medium/p454.py
|
wilsonify/euler
|
5214b776175e6d76a7c6d8915d0e062d189d9b79
|
[
"MIT"
] | null | null | null |
src/euler_python_package/euler_python/medium/p454.py
|
wilsonify/euler
|
5214b776175e6d76a7c6d8915d0e062d189d9b79
|
[
"MIT"
] | null | null | null |
src/euler_python_package/euler_python/medium/p454.py
|
wilsonify/euler
|
5214b776175e6d76a7c6d8915d0e062d189d9b79
|
[
"MIT"
] | null | null | null |
def problem454():
"""
In the following equation x, y, and n are positive integers.
1 1 1
─ + ─ = ─
x y n
For a limit L we define F(L) as the number of solutions which satisfy x <
y ≤ L.
We can verify that F(15) = 4 and F(1000) = 1069.
Find F(10^12).
"""
pass
| 22.842105
| 80
| 0.384793
| 57
| 434
| 3
| 0.701754
| 0.035088
| 0
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| 0
| 0.105
| 0.539171
| 434
| 18
| 81
| 24.111111
| 0.73
| 0.817972
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| true
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| null | 0
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| 1
| 1
| 0
| 0
| 0
| 0
|
0
| 5
|
65ce7c234d26a3ed41952a49375f5d697175ae99
| 79
|
py
|
Python
|
framework/CodeInterfaces/AccelerateCFD/OpenFoamPP/__init__.py
|
FlanFlanagan/raven
|
bd7fca18af94376a28e2144ba1da72c01c8d343c
|
[
"Apache-2.0"
] | 159
|
2017-03-24T21:07:06.000Z
|
2022-03-20T13:44:40.000Z
|
framework/CodeInterfaces/AccelerateCFD/OpenFoamPP/__init__.py
|
FlanFlanagan/raven
|
bd7fca18af94376a28e2144ba1da72c01c8d343c
|
[
"Apache-2.0"
] | 1,667
|
2017-03-27T14:41:22.000Z
|
2022-03-31T19:50:06.000Z
|
framework/CodeInterfaces/AccelerateCFD/OpenFoamPP/__init__.py
|
wanghy-anl/raven
|
ef1372364a2776385931763f2b28fdf2930c77b9
|
[
"Apache-2.0"
] | 95
|
2017-03-24T21:05:03.000Z
|
2022-03-08T17:30:22.000Z
|
from .fieldParser import parseInternalField, parseBoundaryField, parseFieldAll
| 39.5
| 78
| 0.886076
| 6
| 79
| 11.666667
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.075949
| 79
| 1
| 79
| 79
| 0.958904
| 0
| 0
| 0
| 0
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| 0
| 0
| 0
| 0
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| 0
| true
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| null | 0
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| null | 0
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| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 5
|
02b114ff089739282bc888de3fd217feeb38299d
| 113
|
py
|
Python
|
contest/abc127/A.py
|
mola1129/atcoder
|
1d3b18cb92d0ba18c41172f49bfcd0dd8d29f9db
|
[
"MIT"
] | null | null | null |
contest/abc127/A.py
|
mola1129/atcoder
|
1d3b18cb92d0ba18c41172f49bfcd0dd8d29f9db
|
[
"MIT"
] | null | null | null |
contest/abc127/A.py
|
mola1129/atcoder
|
1d3b18cb92d0ba18c41172f49bfcd0dd8d29f9db
|
[
"MIT"
] | null | null | null |
A,B = map(int,input().split())
if A >= 13:
print(B)
elif A >= 6:
print(B//2)
else:
print(0)
| 12.555556
| 31
| 0.460177
| 20
| 113
| 2.6
| 0.7
| 0.230769
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.064935
| 0.318584
| 113
| 8
| 32
| 14.125
| 0.61039
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0
| 0
| 0
| 0.428571
| 1
| 0
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 1
|
0
| 5
|
02c525f46fcfaf62c2c6ea17596325c98454758e
| 174
|
py
|
Python
|
build/win/start.py
|
patrizia21/DemonEditor
|
8d485a999360d2d38300b381af63ee8264719bb8
|
[
"MIT"
] | 1
|
2020-09-07T17:54:49.000Z
|
2020-09-07T17:54:49.000Z
|
build/win/start.py
|
patrizia21/DemonEditor
|
8d485a999360d2d38300b381af63ee8264719bb8
|
[
"MIT"
] | 1
|
2021-11-09T15:21:47.000Z
|
2021-11-09T15:21:47.000Z
|
build/win/start.py
|
patrizia21/DemonEditor
|
8d485a999360d2d38300b381af63ee8264719bb8
|
[
"MIT"
] | 1
|
2021-06-13T11:21:42.000Z
|
2021-06-13T11:21:42.000Z
|
#!/usr/bin/env python3
if __name__ == "__main__":
from multiprocessing import freeze_support
from app.ui.main import start_app
freeze_support()
start_app()
| 19.333333
| 46
| 0.712644
| 23
| 174
| 4.869565
| 0.652174
| 0.232143
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.007143
| 0.195402
| 174
| 8
| 47
| 21.75
| 0.792857
| 0.12069
| 0
| 0
| 0
| 0
| 0.052632
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.4
| 0
| 0.4
| 0
| 1
| 0
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
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| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 5
|
02e6c93b9569a409d0365b26768c7bd39a8d4ac9
| 115
|
py
|
Python
|
papermerge/__init__.py
|
hactar/papermerge
|
4bc8eed55f2dea0731770a9ea70722cb7d3de81c
|
[
"Apache-2.0"
] | null | null | null |
papermerge/__init__.py
|
hactar/papermerge
|
4bc8eed55f2dea0731770a9ea70722cb7d3de81c
|
[
"Apache-2.0"
] | null | null | null |
papermerge/__init__.py
|
hactar/papermerge
|
4bc8eed55f2dea0731770a9ea70722cb7d3de81c
|
[
"Apache-2.0"
] | null | null | null |
from papermerge.core.utils import get_version
VERSION = (1, 4, 2, 'alpha', 0)
__version__ = get_version(VERSION)
| 19.166667
| 45
| 0.73913
| 17
| 115
| 4.647059
| 0.705882
| 0.253165
| 0.43038
| 0
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| 0
| 0
| 0
| 0
| 0.040404
| 0.13913
| 115
| 5
| 46
| 23
| 0.757576
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| 0.043478
| 0
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| false
| 0
| 0.333333
| 0
| 0.333333
| 0
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| null | 1
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| null | 0
| 0
| 0
| 0
| 0
| 0
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| 0
| 1
| 0
| 0
| 0
|
0
| 5
|
02f4fd32a60dc113e9174b2a34e7228d8b327a7d
| 26
|
py
|
Python
|
python-cookie-cutter/templates/setup_env.py
|
sirmax666/python-cookie-cutter
|
22f6dd50736dec59ec3266ff31c4d44a0787c14c
|
[
"MIT"
] | null | null | null |
python-cookie-cutter/templates/setup_env.py
|
sirmax666/python-cookie-cutter
|
22f6dd50736dec59ec3266ff31c4d44a0787c14c
|
[
"MIT"
] | null | null | null |
python-cookie-cutter/templates/setup_env.py
|
sirmax666/python-cookie-cutter
|
22f6dd50736dec59ec3266ff31c4d44a0787c14c
|
[
"MIT"
] | null | null | null |
# Setup environment script
| 26
| 26
| 0.846154
| 3
| 26
| 7.333333
| 1
| 0
| 0
| 0
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| 0
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| 0.115385
| 26
| 1
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| 26
| 0.956522
| 0.923077
| 0
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| null | true
| 0
| 0
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| null | 0
| 0
| 0
| 0
| 0
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| 1
| 0
| 0
| 0
| 0
| 0
|
0
| 5
|
f326da86b0c93b5f7486fe8d3afa7337f989d918
| 225
|
py
|
Python
|
pydriver/evaluation/__init__.py
|
lpltk/pydriver
|
37f3d2bd288112e0e92ee3e525b5c042f3cea349
|
[
"MIT"
] | 43
|
2015-09-01T16:09:20.000Z
|
2020-09-02T02:15:21.000Z
|
pydriver/evaluation/__init__.py
|
eborboihuc/pydriver
|
37f3d2bd288112e0e92ee3e525b5c042f3cea349
|
[
"MIT"
] | 10
|
2016-04-04T08:17:45.000Z
|
2020-07-28T07:12:26.000Z
|
pydriver/evaluation/__init__.py
|
eborboihuc/pydriver
|
37f3d2bd288112e0e92ee3e525b5c042f3cea349
|
[
"MIT"
] | 10
|
2016-05-18T18:36:32.000Z
|
2018-11-24T10:58:08.000Z
|
# -*- coding: utf-8 -*-
"""
Module for evaluating detection performance.
.. automodule:: pydriver.evaluation.evaluation
"""
from __future__ import absolute_import, division
from .evaluation import Evaluator, EvaluatorPoint
| 22.5
| 49
| 0.768889
| 23
| 225
| 7.304348
| 0.782609
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.005051
| 0.12
| 225
| 9
| 50
| 25
| 0.843434
| 0.511111
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
b824e3731c637269ec76a50755642be934e808f5
| 100
|
py
|
Python
|
Python/sqlalchemy-core/check_version.py
|
egustafson/sandbox
|
9804e966347b33558b0497a04edb1a591d2d7773
|
[
"Apache-2.0"
] | 2
|
2019-09-27T21:25:26.000Z
|
2019-12-29T11:26:54.000Z
|
Python/sqlalchemy-core/check_version.py
|
egustafson/sandbox
|
9804e966347b33558b0497a04edb1a591d2d7773
|
[
"Apache-2.0"
] | 7
|
2020-08-11T17:32:14.000Z
|
2020-08-11T17:32:39.000Z
|
Python/sqlalchemy-core/check_version.py
|
egustafson/sandbox
|
9804e966347b33558b0497a04edb1a591d2d7773
|
[
"Apache-2.0"
] | 2
|
2016-07-18T10:55:50.000Z
|
2020-08-19T01:46:08.000Z
|
# -*- coding: utf-8 -*-
#
import sqlalchemy
print("SQLAlchemy v{}".format(sqlalchemy.__version__))
| 16.666667
| 54
| 0.69
| 11
| 100
| 5.909091
| 0.818182
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.011236
| 0.11
| 100
| 5
| 55
| 20
| 0.719101
| 0.21
| 0
| 0
| 0
| 0
| 0.184211
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.5
| 0
| 0.5
| 0.5
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 1
|
0
| 5
|
b83a84220bad6e46620eb1679cdb218c83a406a1
| 74
|
py
|
Python
|
scripts/test/test/basic.py
|
cedar101/quepy-ko
|
532744e50d9754befeea2eff6a261fa9cd095473
|
[
"BSD-3-Clause"
] | null | null | null |
scripts/test/test/basic.py
|
cedar101/quepy-ko
|
532744e50d9754befeea2eff6a261fa9cd095473
|
[
"BSD-3-Clause"
] | null | null | null |
scripts/test/test/basic.py
|
cedar101/quepy-ko
|
532744e50d9754befeea2eff6a261fa9cd095473
|
[
"BSD-3-Clause"
] | null | null | null |
# coding: utf-8
"""
Basic queries for test quepy.
"""
from dsl import *
| 9.25
| 29
| 0.635135
| 11
| 74
| 4.272727
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.017241
| 0.216216
| 74
| 7
| 30
| 10.571429
| 0.793103
| 0.594595
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
b214eef77185bfaf227f32aa7ef962bcf1ecbf1b
| 121
|
py
|
Python
|
main.py
|
tvarney/GameBreaker
|
9b6a2840635caf2f3027ff2fcaca4120e0e90f99
|
[
"MIT"
] | null | null | null |
main.py
|
tvarney/GameBreaker
|
9b6a2840635caf2f3027ff2fcaca4120e0e90f99
|
[
"MIT"
] | null | null | null |
main.py
|
tvarney/GameBreaker
|
9b6a2840635caf2f3027ff2fcaca4120e0e90f99
|
[
"MIT"
] | null | null | null |
import gamebreaker.image
import gamebreaker.neopets.buzzer as buzzer
if __name__ == "__main__":
buzzer.run()
| 17.285714
| 44
| 0.719008
| 14
| 121
| 5.642857
| 0.714286
| 0.43038
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.190083
| 121
| 6
| 45
| 20.166667
| 0.806122
| 0
| 0
| 0
| 0
| 0
| 0.070175
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.5
| 0
| 0.5
| 0
| 1
| 0
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 5
|
b222c30c75bd4a4b50ab84313ce7232525a32394
| 108,961
|
py
|
Python
|
python/protobufs/services/registry/responses_pb2.py
|
getcircle/protobuf-registry
|
20ad8463b7ac6e2cf279c08bcd3e953993fe9153
|
[
"MIT"
] | null | null | null |
python/protobufs/services/registry/responses_pb2.py
|
getcircle/protobuf-registry
|
20ad8463b7ac6e2cf279c08bcd3e953993fe9153
|
[
"MIT"
] | null | null | null |
python/protobufs/services/registry/responses_pb2.py
|
getcircle/protobuf-registry
|
20ad8463b7ac6e2cf279c08bcd3e953993fe9153
|
[
"MIT"
] | null | null | null |
# Generated by the protocol buffer compiler. DO NOT EDIT!
# source: protobufs/services/registry/responses.proto
from google.protobuf import descriptor as _descriptor
from google.protobuf import message as _message
from google.protobuf import reflection as _reflection
from google.protobuf import symbol_database as _symbol_database
from google.protobuf import descriptor_pb2
# @@protoc_insertion_point(imports)
_sym_db = _symbol_database.Default()
from service_protobufs import soa_pb2 as service__protobufs_dot_soa__pb2
from protobufs.services.user.actions import create_user_pb2 as protobufs_dot_services_dot_user_dot_actions_dot_create__user__pb2
from protobufs.services.user.actions import authenticate_user_pb2 as protobufs_dot_services_dot_user_dot_actions_dot_authenticate__user__pb2
from protobufs.services.user.actions import get_user_pb2 as protobufs_dot_services_dot_user_dot_actions_dot_get__user__pb2
from protobufs.services.user.actions import complete_authorization_pb2 as protobufs_dot_services_dot_user_dot_actions_dot_complete__authorization__pb2
from protobufs.services.user.actions import get_identities_pb2 as protobufs_dot_services_dot_user_dot_actions_dot_get__identities__pb2
from protobufs.services.user.actions import bulk_create_users_pb2 as protobufs_dot_services_dot_user_dot_actions_dot_bulk__create__users__pb2
from protobufs.services.user.actions import record_device_pb2 as protobufs_dot_services_dot_user_dot_actions_dot_record__device__pb2
from protobufs.services.user.actions import request_access_pb2 as protobufs_dot_services_dot_user_dot_actions_dot_request__access__pb2
from protobufs.services.user.actions import delete_identity_pb2 as protobufs_dot_services_dot_user_dot_actions_dot_delete__identity__pb2
from protobufs.services.user.actions import logout_pb2 as protobufs_dot_services_dot_user_dot_actions_dot_logout__pb2
from protobufs.services.user.actions import get_authentication_instructions_pb2 as protobufs_dot_services_dot_user_dot_actions_dot_get__authentication__instructions__pb2
from protobufs.services.user.actions import get_integration_authentication_instructions_pb2 as protobufs_dot_services_dot_user_dot_actions_dot_get__integration__authentication__instructions__pb2
from protobufs.services.user.actions import get_active_devices_pb2 as protobufs_dot_services_dot_user_dot_actions_dot_get__active__devices__pb2
from protobufs.services.user.actions import bulk_update_users_pb2 as protobufs_dot_services_dot_user_dot_actions_dot_bulk__update__users__pb2
from protobufs.services.organization.actions import create_organization_pb2 as protobufs_dot_services_dot_organization_dot_actions_dot_create__organization__pb2
from protobufs.services.organization.actions import get_team_pb2 as protobufs_dot_services_dot_organization_dot_actions_dot_get__team__pb2
from protobufs.services.organization.actions import get_organization_pb2 as protobufs_dot_services_dot_organization_dot_actions_dot_get__organization__pb2
from protobufs.services.organization.actions import create_location_pb2 as protobufs_dot_services_dot_organization_dot_actions_dot_create__location__pb2
from protobufs.services.organization.actions import update_location_pb2 as protobufs_dot_services_dot_organization_dot_actions_dot_update__location__pb2
from protobufs.services.organization.actions import get_locations_pb2 as protobufs_dot_services_dot_organization_dot_actions_dot_get__locations__pb2
from protobufs.services.organization.actions import get_location_pb2 as protobufs_dot_services_dot_organization_dot_actions_dot_get__location__pb2
from protobufs.services.organization.actions import enable_integration_pb2 as protobufs_dot_services_dot_organization_dot_actions_dot_enable__integration__pb2
from protobufs.services.organization.actions import get_integration_pb2 as protobufs_dot_services_dot_organization_dot_actions_dot_get__integration__pb2
from protobufs.services.organization.actions import disable_integration_pb2 as protobufs_dot_services_dot_organization_dot_actions_dot_disable__integration__pb2
from protobufs.services.organization.actions import update_team_pb2 as protobufs_dot_services_dot_organization_dot_actions_dot_update__team__pb2
from protobufs.services.organization.actions import add_direct_reports_pb2 as protobufs_dot_services_dot_organization_dot_actions_dot_add__direct__reports__pb2
from protobufs.services.organization.actions import get_location_members_pb2 as protobufs_dot_services_dot_organization_dot_actions_dot_get__location__members__pb2
from protobufs.services.organization.actions import get_profile_reporting_details_pb2 as protobufs_dot_services_dot_organization_dot_actions_dot_get__profile__reporting__details__pb2
from protobufs.services.organization.actions import get_team_reporting_details_pb2 as protobufs_dot_services_dot_organization_dot_actions_dot_get__team__reporting__details__pb2
from protobufs.services.organization.actions import set_manager_pb2 as protobufs_dot_services_dot_organization_dot_actions_dot_set__manager__pb2
from protobufs.services.organization.actions import add_location_members_pb2 as protobufs_dot_services_dot_organization_dot_actions_dot_add__location__members__pb2
from protobufs.services.organization.actions import get_teams_pb2 as protobufs_dot_services_dot_organization_dot_actions_dot_get__teams__pb2
from protobufs.services.organization.actions import get_descendants_pb2 as protobufs_dot_services_dot_organization_dot_actions_dot_get__descendants__pb2
from protobufs.services.organization.actions import get_sso_pb2 as protobufs_dot_services_dot_organization_dot_actions_dot_get__sso__pb2
from protobufs.services.organization.actions import get_teams_for_profile_ids_pb2 as protobufs_dot_services_dot_organization_dot_actions_dot_get__teams__for__profile__ids__pb2
from protobufs.services.profile.actions import create_profile_pb2 as protobufs_dot_services_dot_profile_dot_actions_dot_create__profile__pb2
from protobufs.services.profile.actions import get_extended_profile_pb2 as protobufs_dot_services_dot_profile_dot_actions_dot_get__extended__profile__pb2
from protobufs.services.profile.actions import get_profile_pb2 as protobufs_dot_services_dot_profile_dot_actions_dot_get__profile__pb2
from protobufs.services.profile.actions import update_profile_pb2 as protobufs_dot_services_dot_profile_dot_actions_dot_update__profile__pb2
from protobufs.services.profile.actions import get_profiles_pb2 as protobufs_dot_services_dot_profile_dot_actions_dot_get__profiles__pb2
from protobufs.services.profile.actions import bulk_create_profiles_pb2 as protobufs_dot_services_dot_profile_dot_actions_dot_bulk__create__profiles__pb2
from protobufs.services.profile.actions import bulk_update_profiles_pb2 as protobufs_dot_services_dot_profile_dot_actions_dot_bulk__update__profiles__pb2
from protobufs.services.profile.actions import profile_exists_pb2 as protobufs_dot_services_dot_profile_dot_actions_dot_profile__exists__pb2
from protobufs.services.profile.actions import get_reporting_details_pb2 as protobufs_dot_services_dot_profile_dot_actions_dot_get__reporting__details__pb2
from protobufs.services.search.actions import search_pb2 as protobufs_dot_services_dot_search_dot_actions_dot_search__pb2
from protobufs.services.search.actions import search_v2_pb2 as protobufs_dot_services_dot_search_dot_actions_dot_search__v2__pb2
from protobufs.services.search.actions import update_entities_pb2 as protobufs_dot_services_dot_search_dot_actions_dot_update__entities__pb2
from protobufs.services.search.actions import delete_entities_pb2 as protobufs_dot_services_dot_search_dot_actions_dot_delete__entities__pb2
from protobufs.services.search.actions import create_index_pb2 as protobufs_dot_services_dot_search_dot_actions_dot_create__index__pb2
from protobufs.services.search.actions import track_recent_pb2 as protobufs_dot_services_dot_search_dot_actions_dot_track__recent__pb2
from protobufs.services.search.actions import get_recents_pb2 as protobufs_dot_services_dot_search_dot_actions_dot_get__recents__pb2
from protobufs.services.search.actions import delete_recent_pb2 as protobufs_dot_services_dot_search_dot_actions_dot_delete__recent__pb2
from protobufs.services.media.actions import start_image_upload_pb2 as protobufs_dot_services_dot_media_dot_actions_dot_start__image__upload__pb2
from protobufs.services.media.actions import complete_image_upload_pb2 as protobufs_dot_services_dot_media_dot_actions_dot_complete__image__upload__pb2
from protobufs.services.notification.actions import register_device_pb2 as protobufs_dot_services_dot_notification_dot_actions_dot_register__device__pb2
from protobufs.services.notification.actions import get_preferences_pb2 as protobufs_dot_services_dot_notification_dot_actions_dot_get__preferences__pb2
from protobufs.services.notification.actions import update_preference_pb2 as protobufs_dot_services_dot_notification_dot_actions_dot_update__preference__pb2
from protobufs.services.notification.actions import send_notification_pb2 as protobufs_dot_services_dot_notification_dot_actions_dot_send__notification__pb2
from protobufs.services.notification.actions import no_search_results_pb2 as protobufs_dot_services_dot_notification_dot_actions_dot_no__search__results__pb2
from protobufs.services.history.actions import record_action_pb2 as protobufs_dot_services_dot_history_dot_actions_dot_record__action__pb2
from protobufs.services.payment.actions import store_token_pb2 as protobufs_dot_services_dot_payment_dot_actions_dot_store__token__pb2
from protobufs.services.post.actions import create_post_pb2 as protobufs_dot_services_dot_post_dot_actions_dot_create__post__pb2
from protobufs.services.post.actions import get_post_pb2 as protobufs_dot_services_dot_post_dot_actions_dot_get__post__pb2
from protobufs.services.post.actions import get_posts_pb2 as protobufs_dot_services_dot_post_dot_actions_dot_get__posts__pb2
from protobufs.services.post.actions import update_post_pb2 as protobufs_dot_services_dot_post_dot_actions_dot_update__post__pb2
from protobufs.services.post.actions import delete_post_pb2 as protobufs_dot_services_dot_post_dot_actions_dot_delete__post__pb2
from protobufs.services.post.actions import create_collection_pb2 as protobufs_dot_services_dot_post_dot_actions_dot_create__collection__pb2
from protobufs.services.post.actions import update_collection_pb2 as protobufs_dot_services_dot_post_dot_actions_dot_update__collection__pb2
from protobufs.services.post.actions import delete_collection_pb2 as protobufs_dot_services_dot_post_dot_actions_dot_delete__collection__pb2
from protobufs.services.post.actions import add_to_collections_pb2 as protobufs_dot_services_dot_post_dot_actions_dot_add__to__collections__pb2
from protobufs.services.post.actions import remove_from_collections_pb2 as protobufs_dot_services_dot_post_dot_actions_dot_remove__from__collections__pb2
from protobufs.services.post.actions import get_collection_pb2 as protobufs_dot_services_dot_post_dot_actions_dot_get__collection__pb2
from protobufs.services.post.actions import get_collections_pb2 as protobufs_dot_services_dot_post_dot_actions_dot_get__collections__pb2
from protobufs.services.post.actions import reorder_collection_pb2 as protobufs_dot_services_dot_post_dot_actions_dot_reorder__collection__pb2
from protobufs.services.post.actions import get_collection_items_pb2 as protobufs_dot_services_dot_post_dot_actions_dot_get__collection__items__pb2
from protobufs.services.post.actions import reorder_collections_pb2 as protobufs_dot_services_dot_post_dot_actions_dot_reorder__collections__pb2
from protobufs.services.post.actions import remove_from_collection_pb2 as protobufs_dot_services_dot_post_dot_actions_dot_remove__from__collection__pb2
from protobufs.services.feature.actions import get_flags_pb2 as protobufs_dot_services_dot_feature_dot_actions_dot_get__flags__pb2
from protobufs.services.file.actions import start_upload_pb2 as protobufs_dot_services_dot_file_dot_actions_dot_start__upload__pb2
from protobufs.services.file.actions import complete_upload_pb2 as protobufs_dot_services_dot_file_dot_actions_dot_complete__upload__pb2
from protobufs.services.file.actions import delete_pb2 as protobufs_dot_services_dot_file_dot_actions_dot_delete__pb2
from protobufs.services.file.actions import get_files_pb2 as protobufs_dot_services_dot_file_dot_actions_dot_get__files__pb2
from protobufs.services.file.actions import upload_pb2 as protobufs_dot_services_dot_file_dot_actions_dot_upload__pb2
from protobufs.services.file.actions import get_file_pb2 as protobufs_dot_services_dot_file_dot_actions_dot_get__file__pb2
from protobufs.services.team.actions import add_members_pb2 as protobufs_dot_services_dot_team_dot_actions_dot_add__members__pb2
from protobufs.services.team.actions import create_team_pb2 as protobufs_dot_services_dot_team_dot_actions_dot_create__team__pb2
from protobufs.services.team.actions import get_team_pb2 as protobufs_dot_services_dot_team_dot_actions_dot_get__team__pb2
from protobufs.services.team.actions import get_members_pb2 as protobufs_dot_services_dot_team_dot_actions_dot_get__members__pb2
from protobufs.services.team.actions import join_team_pb2 as protobufs_dot_services_dot_team_dot_actions_dot_join__team__pb2
from protobufs.services.team.actions import leave_team_pb2 as protobufs_dot_services_dot_team_dot_actions_dot_leave__team__pb2
from protobufs.services.team.actions import remove_members_pb2 as protobufs_dot_services_dot_team_dot_actions_dot_remove__members__pb2
from protobufs.services.team.actions import update_members_pb2 as protobufs_dot_services_dot_team_dot_actions_dot_update__members__pb2
from protobufs.services.team.actions import update_team_pb2 as protobufs_dot_services_dot_team_dot_actions_dot_update__team__pb2
from protobufs.services.team.actions import get_teams_pb2 as protobufs_dot_services_dot_team_dot_actions_dot_get__teams__pb2
DESCRIPTOR = _descriptor.FileDescriptor(
name='protobufs/services/registry/responses.proto',
package='services.registry.responses',
syntax='proto2',
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_sym_db.RegisterFileDescriptor(DESCRIPTOR)
_USER = _descriptor.Descriptor(
name='User',
full_name='services.registry.responses.User',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
],
extensions=[
_descriptor.FieldDescriptor(
name='create_user', full_name='services.registry.responses.User.create_user', index=0,
number=100, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=True, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='authenticate_user', full_name='services.registry.responses.User.authenticate_user', index=1,
number=102, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=True, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='get_user', full_name='services.registry.responses.User.get_user', index=2,
number=103, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=True, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='complete_authorization', full_name='services.registry.responses.User.complete_authorization', index=3,
number=108, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=True, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='get_identities', full_name='services.registry.responses.User.get_identities', index=4,
number=109, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=True, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='bulk_create_users', full_name='services.registry.responses.User.bulk_create_users', index=5,
number=110, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=True, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='record_device', full_name='services.registry.responses.User.record_device', index=6,
number=111, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=True, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='request_access', full_name='services.registry.responses.User.request_access', index=7,
number=112, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=True, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='delete_identity', full_name='services.registry.responses.User.delete_identity', index=8,
number=113, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=True, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='logout', full_name='services.registry.responses.User.logout', index=9,
number=114, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=True, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='get_authentication_instructions', full_name='services.registry.responses.User.get_authentication_instructions', index=10,
number=115, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=True, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='get_active_devices', full_name='services.registry.responses.User.get_active_devices', index=11,
number=116, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=True, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='bulk_update_users', full_name='services.registry.responses.User.bulk_update_users', index=12,
number=118, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=True, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='get_integration_authentication_instructions', full_name='services.registry.responses.User.get_integration_authentication_instructions', index=13,
number=119, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=True, extension_scope=None,
options=None),
],
nested_types=[],
enum_types=[
],
options=None,
is_extendable=False,
syntax='proto2',
extension_ranges=[],
oneofs=[
],
serialized_start=5521,
serialized_end=6993,
)
_ORGANIZATION = _descriptor.Descriptor(
name='Organization',
full_name='services.registry.responses.Organization',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
],
extensions=[
_descriptor.FieldDescriptor(
name='create_organization', full_name='services.registry.responses.Organization.create_organization', index=0,
number=200, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=True, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='get_organization', full_name='services.registry.responses.Organization.get_organization', index=1,
number=201, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=True, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='get_team', full_name='services.registry.responses.Organization.get_team', index=2,
number=202, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=True, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='create_location', full_name='services.registry.responses.Organization.create_location', index=3,
number=203, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=True, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='update_location', full_name='services.registry.responses.Organization.update_location', index=4,
number=204, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=True, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='get_locations', full_name='services.registry.responses.Organization.get_locations', index=5,
number=205, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=True, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='get_location', full_name='services.registry.responses.Organization.get_location', index=6,
number=206, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=True, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='enable_integration', full_name='services.registry.responses.Organization.enable_integration', index=7,
number=209, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=True, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='get_integration', full_name='services.registry.responses.Organization.get_integration', index=8,
number=210, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=True, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='disable_integration', full_name='services.registry.responses.Organization.disable_integration', index=9,
number=211, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=True, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='update_team', full_name='services.registry.responses.Organization.update_team', index=10,
number=212, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=True, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='add_direct_reports', full_name='services.registry.responses.Organization.add_direct_reports', index=11,
number=213, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=True, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='get_location_members', full_name='services.registry.responses.Organization.get_location_members', index=12,
number=214, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=True, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='get_profile_reporting_details', full_name='services.registry.responses.Organization.get_profile_reporting_details', index=13,
number=215, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=True, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='get_team_reporting_details', full_name='services.registry.responses.Organization.get_team_reporting_details', index=14,
number=216, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=True, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='set_manager', full_name='services.registry.responses.Organization.set_manager', index=15,
number=217, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=True, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='add_location_members', full_name='services.registry.responses.Organization.add_location_members', index=16,
number=218, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=True, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='get_teams', full_name='services.registry.responses.Organization.get_teams', index=17,
number=219, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=True, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='get_descendants', full_name='services.registry.responses.Organization.get_descendants', index=18,
number=220, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=True, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='get_sso', full_name='services.registry.responses.Organization.get_sso', index=19,
number=221, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=True, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='get_teams_for_profile_ids', full_name='services.registry.responses.Organization.get_teams_for_profile_ids', index=20,
number=222, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=True, extension_scope=None,
options=None),
],
nested_types=[],
enum_types=[
],
options=None,
is_extendable=False,
syntax='proto2',
extension_ranges=[],
oneofs=[
],
serialized_start=6996,
serialized_end=9305,
)
_PROFILE = _descriptor.Descriptor(
name='Profile',
full_name='services.registry.responses.Profile',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
],
extensions=[
_descriptor.FieldDescriptor(
name='create_profile', full_name='services.registry.responses.Profile.create_profile', index=0,
number=300, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=True, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='get_extended_profile', full_name='services.registry.responses.Profile.get_extended_profile', index=1,
number=301, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=True, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='get_profile', full_name='services.registry.responses.Profile.get_profile', index=2,
number=302, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=True, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='update_profile', full_name='services.registry.responses.Profile.update_profile', index=3,
number=306, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=True, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='get_profiles', full_name='services.registry.responses.Profile.get_profiles', index=4,
number=307, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=True, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='bulk_create_profiles', full_name='services.registry.responses.Profile.bulk_create_profiles', index=5,
number=312, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=True, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='bulk_update_profiles', full_name='services.registry.responses.Profile.bulk_update_profiles', index=6,
number=313, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=True, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='profile_exists', full_name='services.registry.responses.Profile.profile_exists', index=7,
number=315, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=True, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='get_reporting_details', full_name='services.registry.responses.Profile.get_reporting_details', index=8,
number=317, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=True, extension_scope=None,
options=None),
],
nested_types=[],
enum_types=[
],
options=None,
is_extendable=False,
syntax='proto2',
extension_ranges=[],
oneofs=[
],
serialized_start=9308,
serialized_end=10320,
)
_SEARCH = _descriptor.Descriptor(
name='Search',
full_name='services.registry.responses.Search',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
],
extensions=[
_descriptor.FieldDescriptor(
name='search', full_name='services.registry.responses.Search.search', index=0,
number=400, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=True, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='search_v2', full_name='services.registry.responses.Search.search_v2', index=1,
number=401, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=True, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='update_entities', full_name='services.registry.responses.Search.update_entities', index=2,
number=402, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=True, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='delete_entities', full_name='services.registry.responses.Search.delete_entities', index=3,
number=403, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=True, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='create_index', full_name='services.registry.responses.Search.create_index', index=4,
number=404, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=True, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='track_recent', full_name='services.registry.responses.Search.track_recent', index=5,
number=405, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=True, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='get_recents', full_name='services.registry.responses.Search.get_recents', index=6,
number=406, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=True, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='delete_recent', full_name='services.registry.responses.Search.delete_recent', index=7,
number=407, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=True, extension_scope=None,
options=None),
],
nested_types=[],
enum_types=[
],
options=None,
is_extendable=False,
syntax='proto2',
extension_ranges=[],
oneofs=[
],
serialized_start=10323,
serialized_end=11077,
)
_MEDIA = _descriptor.Descriptor(
name='Media',
full_name='services.registry.responses.Media',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
],
extensions=[
_descriptor.FieldDescriptor(
name='start_image_upload', full_name='services.registry.responses.Media.start_image_upload', index=0,
number=600, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=True, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='complete_image_upload', full_name='services.registry.responses.Media.complete_image_upload', index=1,
number=601, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=True, extension_scope=None,
options=None),
],
nested_types=[],
enum_types=[
],
options=None,
is_extendable=False,
syntax='proto2',
extension_ranges=[],
oneofs=[
],
serialized_start=11080,
serialized_end=11303,
)
_NOTIFICATION = _descriptor.Descriptor(
name='Notification',
full_name='services.registry.responses.Notification',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
],
extensions=[
_descriptor.FieldDescriptor(
name='register_device', full_name='services.registry.responses.Notification.register_device', index=0,
number=1300, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=True, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='get_preferences', full_name='services.registry.responses.Notification.get_preferences', index=1,
number=1301, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=True, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='update_preference', full_name='services.registry.responses.Notification.update_preference', index=2,
number=1302, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=True, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='send_notification', full_name='services.registry.responses.Notification.send_notification', index=3,
number=1303, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=True, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='no_search_results', full_name='services.registry.responses.Notification.no_search_results', index=4,
number=1304, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=True, extension_scope=None,
options=None),
],
nested_types=[],
enum_types=[
],
options=None,
is_extendable=False,
syntax='proto2',
extension_ranges=[],
oneofs=[
],
serialized_start=11306,
serialized_end=11862,
)
_HISTORY = _descriptor.Descriptor(
name='History',
full_name='services.registry.responses.History',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
],
extensions=[
_descriptor.FieldDescriptor(
name='record_action', full_name='services.registry.responses.History.record_action', index=0,
number=1400, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=True, extension_scope=None,
options=None),
],
nested_types=[],
enum_types=[
],
options=None,
is_extendable=False,
syntax='proto2',
extension_ranges=[],
oneofs=[
],
serialized_start=11864,
serialized_end=11970,
)
_PAYMENT = _descriptor.Descriptor(
name='Payment',
full_name='services.registry.responses.Payment',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
],
extensions=[
_descriptor.FieldDescriptor(
name='store_token', full_name='services.registry.responses.Payment.store_token', index=0,
number=1500, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=True, extension_scope=None,
options=None),
],
nested_types=[],
enum_types=[
],
options=None,
is_extendable=False,
syntax='proto2',
extension_ranges=[],
oneofs=[
],
serialized_start=11972,
serialized_end=12074,
)
_POST = _descriptor.Descriptor(
name='Post',
full_name='services.registry.responses.Post',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
],
extensions=[
_descriptor.FieldDescriptor(
name='create_post', full_name='services.registry.responses.Post.create_post', index=0,
number=1600, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=True, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='update_post', full_name='services.registry.responses.Post.update_post', index=1,
number=1601, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=True, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='get_post', full_name='services.registry.responses.Post.get_post', index=2,
number=1602, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=True, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='get_posts', full_name='services.registry.responses.Post.get_posts', index=3,
number=1603, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=True, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='delete_post', full_name='services.registry.responses.Post.delete_post', index=4,
number=1604, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=True, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='create_collection', full_name='services.registry.responses.Post.create_collection', index=5,
number=1605, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=True, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='update_collection', full_name='services.registry.responses.Post.update_collection', index=6,
number=1606, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=True, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='delete_collection', full_name='services.registry.responses.Post.delete_collection', index=7,
number=1607, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=True, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='add_to_collections', full_name='services.registry.responses.Post.add_to_collections', index=8,
number=1608, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=True, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='remove_from_collections', full_name='services.registry.responses.Post.remove_from_collections', index=9,
number=1609, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=True, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='get_collection', full_name='services.registry.responses.Post.get_collection', index=10,
number=1610, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=True, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='get_collections', full_name='services.registry.responses.Post.get_collections', index=11,
number=1611, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=True, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='reorder_collection', full_name='services.registry.responses.Post.reorder_collection', index=12,
number=1612, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=True, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='get_collection_items', full_name='services.registry.responses.Post.get_collection_items', index=13,
number=1613, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=True, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='reorder_collections', full_name='services.registry.responses.Post.reorder_collections', index=14,
number=1614, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=True, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='remove_from_collection', full_name='services.registry.responses.Post.remove_from_collection', index=15,
number=1615, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=True, extension_scope=None,
options=None),
],
nested_types=[],
enum_types=[
],
options=None,
is_extendable=False,
syntax='proto2',
extension_ranges=[],
oneofs=[
],
serialized_start=12077,
serialized_end=13671,
)
_FEATURE = _descriptor.Descriptor(
name='Feature',
full_name='services.registry.responses.Feature',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
],
extensions=[
_descriptor.FieldDescriptor(
name='get_flags', full_name='services.registry.responses.Feature.get_flags', index=0,
number=1700, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=True, extension_scope=None,
options=None),
],
nested_types=[],
enum_types=[
],
options=None,
is_extendable=False,
syntax='proto2',
extension_ranges=[],
oneofs=[
],
serialized_start=13673,
serialized_end=13771,
)
_FILE = _descriptor.Descriptor(
name='File',
full_name='services.registry.responses.File',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
],
extensions=[
_descriptor.FieldDescriptor(
name='start_upload', full_name='services.registry.responses.File.start_upload', index=0,
number=1800, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=True, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='complete_upload', full_name='services.registry.responses.File.complete_upload', index=1,
number=1801, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=True, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='delete', full_name='services.registry.responses.File.delete', index=2,
number=1802, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=True, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='get_files', full_name='services.registry.responses.File.get_files', index=3,
number=1803, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=True, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='upload', full_name='services.registry.responses.File.upload', index=4,
number=1804, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=True, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='get_file', full_name='services.registry.responses.File.get_file', index=5,
number=1805, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=True, extension_scope=None,
options=None),
],
nested_types=[],
enum_types=[
],
options=None,
is_extendable=False,
syntax='proto2',
extension_ranges=[],
oneofs=[
],
serialized_start=13774,
serialized_end=14300,
)
_TEAM = _descriptor.Descriptor(
name='Team',
full_name='services.registry.responses.Team',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
],
extensions=[
_descriptor.FieldDescriptor(
name='add_members', full_name='services.registry.responses.Team.add_members', index=0,
number=1900, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=True, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='create_team', full_name='services.registry.responses.Team.create_team', index=1,
number=1901, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=True, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='get_team', full_name='services.registry.responses.Team.get_team', index=2,
number=1902, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=True, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='get_members', full_name='services.registry.responses.Team.get_members', index=3,
number=1903, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=True, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='join_team', full_name='services.registry.responses.Team.join_team', index=4,
number=1904, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=True, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='leave_team', full_name='services.registry.responses.Team.leave_team', index=5,
number=1905, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=True, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='remove_members', full_name='services.registry.responses.Team.remove_members', index=6,
number=1906, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=True, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='update_members', full_name='services.registry.responses.Team.update_members', index=7,
number=1907, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=True, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='update_team', full_name='services.registry.responses.Team.update_team', index=8,
number=1908, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=True, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='get_teams', full_name='services.registry.responses.Team.get_teams', index=9,
number=1909, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=True, extension_scope=None,
options=None),
],
nested_types=[],
enum_types=[
],
options=None,
is_extendable=False,
syntax='proto2',
extension_ranges=[],
oneofs=[
],
serialized_start=14303,
serialized_end=15205,
)
DESCRIPTOR.message_types_by_name['User'] = _USER
DESCRIPTOR.message_types_by_name['Organization'] = _ORGANIZATION
DESCRIPTOR.message_types_by_name['Profile'] = _PROFILE
DESCRIPTOR.message_types_by_name['Search'] = _SEARCH
DESCRIPTOR.message_types_by_name['Media'] = _MEDIA
DESCRIPTOR.message_types_by_name['Notification'] = _NOTIFICATION
DESCRIPTOR.message_types_by_name['History'] = _HISTORY
DESCRIPTOR.message_types_by_name['Payment'] = _PAYMENT
DESCRIPTOR.message_types_by_name['Post'] = _POST
DESCRIPTOR.message_types_by_name['Feature'] = _FEATURE
DESCRIPTOR.message_types_by_name['File'] = _FILE
DESCRIPTOR.message_types_by_name['Team'] = _TEAM
User = _reflection.GeneratedProtocolMessageType('User', (_message.Message,), dict(
DESCRIPTOR = _USER,
__module__ = 'protobufs.services.registry.responses_pb2'
# @@protoc_insertion_point(class_scope:services.registry.responses.User)
))
_sym_db.RegisterMessage(User)
Organization = _reflection.GeneratedProtocolMessageType('Organization', (_message.Message,), dict(
DESCRIPTOR = _ORGANIZATION,
__module__ = 'protobufs.services.registry.responses_pb2'
# @@protoc_insertion_point(class_scope:services.registry.responses.Organization)
))
_sym_db.RegisterMessage(Organization)
Profile = _reflection.GeneratedProtocolMessageType('Profile', (_message.Message,), dict(
DESCRIPTOR = _PROFILE,
__module__ = 'protobufs.services.registry.responses_pb2'
# @@protoc_insertion_point(class_scope:services.registry.responses.Profile)
))
_sym_db.RegisterMessage(Profile)
Search = _reflection.GeneratedProtocolMessageType('Search', (_message.Message,), dict(
DESCRIPTOR = _SEARCH,
__module__ = 'protobufs.services.registry.responses_pb2'
# @@protoc_insertion_point(class_scope:services.registry.responses.Search)
))
_sym_db.RegisterMessage(Search)
Media = _reflection.GeneratedProtocolMessageType('Media', (_message.Message,), dict(
DESCRIPTOR = _MEDIA,
__module__ = 'protobufs.services.registry.responses_pb2'
# @@protoc_insertion_point(class_scope:services.registry.responses.Media)
))
_sym_db.RegisterMessage(Media)
Notification = _reflection.GeneratedProtocolMessageType('Notification', (_message.Message,), dict(
DESCRIPTOR = _NOTIFICATION,
__module__ = 'protobufs.services.registry.responses_pb2'
# @@protoc_insertion_point(class_scope:services.registry.responses.Notification)
))
_sym_db.RegisterMessage(Notification)
History = _reflection.GeneratedProtocolMessageType('History', (_message.Message,), dict(
DESCRIPTOR = _HISTORY,
__module__ = 'protobufs.services.registry.responses_pb2'
# @@protoc_insertion_point(class_scope:services.registry.responses.History)
))
_sym_db.RegisterMessage(History)
Payment = _reflection.GeneratedProtocolMessageType('Payment', (_message.Message,), dict(
DESCRIPTOR = _PAYMENT,
__module__ = 'protobufs.services.registry.responses_pb2'
# @@protoc_insertion_point(class_scope:services.registry.responses.Payment)
))
_sym_db.RegisterMessage(Payment)
Post = _reflection.GeneratedProtocolMessageType('Post', (_message.Message,), dict(
DESCRIPTOR = _POST,
__module__ = 'protobufs.services.registry.responses_pb2'
# @@protoc_insertion_point(class_scope:services.registry.responses.Post)
))
_sym_db.RegisterMessage(Post)
Feature = _reflection.GeneratedProtocolMessageType('Feature', (_message.Message,), dict(
DESCRIPTOR = _FEATURE,
__module__ = 'protobufs.services.registry.responses_pb2'
# @@protoc_insertion_point(class_scope:services.registry.responses.Feature)
))
_sym_db.RegisterMessage(Feature)
File = _reflection.GeneratedProtocolMessageType('File', (_message.Message,), dict(
DESCRIPTOR = _FILE,
__module__ = 'protobufs.services.registry.responses_pb2'
# @@protoc_insertion_point(class_scope:services.registry.responses.File)
))
_sym_db.RegisterMessage(File)
Team = _reflection.GeneratedProtocolMessageType('Team', (_message.Message,), dict(
DESCRIPTOR = _TEAM,
__module__ = 'protobufs.services.registry.responses_pb2'
# @@protoc_insertion_point(class_scope:services.registry.responses.Team)
))
_sym_db.RegisterMessage(Team)
_USER.extensions_by_name['create_user'].message_type = protobufs_dot_services_dot_user_dot_actions_dot_create__user__pb2._RESPONSEV1
service__protobufs_dot_soa__pb2.ActionResultV1.RegisterExtension(_USER.extensions_by_name['create_user'])
_USER.extensions_by_name['authenticate_user'].message_type = protobufs_dot_services_dot_user_dot_actions_dot_authenticate__user__pb2._RESPONSEV1
service__protobufs_dot_soa__pb2.ActionResultV1.RegisterExtension(_USER.extensions_by_name['authenticate_user'])
_USER.extensions_by_name['get_user'].message_type = protobufs_dot_services_dot_user_dot_actions_dot_get__user__pb2._RESPONSEV1
service__protobufs_dot_soa__pb2.ActionResultV1.RegisterExtension(_USER.extensions_by_name['get_user'])
_USER.extensions_by_name['complete_authorization'].message_type = protobufs_dot_services_dot_user_dot_actions_dot_complete__authorization__pb2._RESPONSEV1
service__protobufs_dot_soa__pb2.ActionResultV1.RegisterExtension(_USER.extensions_by_name['complete_authorization'])
_USER.extensions_by_name['get_identities'].message_type = protobufs_dot_services_dot_user_dot_actions_dot_get__identities__pb2._RESPONSEV1
service__protobufs_dot_soa__pb2.ActionResultV1.RegisterExtension(_USER.extensions_by_name['get_identities'])
_USER.extensions_by_name['bulk_create_users'].message_type = protobufs_dot_services_dot_user_dot_actions_dot_bulk__create__users__pb2._RESPONSEV1
service__protobufs_dot_soa__pb2.ActionResultV1.RegisterExtension(_USER.extensions_by_name['bulk_create_users'])
_USER.extensions_by_name['record_device'].message_type = protobufs_dot_services_dot_user_dot_actions_dot_record__device__pb2._RESPONSEV1
service__protobufs_dot_soa__pb2.ActionResultV1.RegisterExtension(_USER.extensions_by_name['record_device'])
_USER.extensions_by_name['request_access'].message_type = protobufs_dot_services_dot_user_dot_actions_dot_request__access__pb2._RESPONSEV1
service__protobufs_dot_soa__pb2.ActionResultV1.RegisterExtension(_USER.extensions_by_name['request_access'])
_USER.extensions_by_name['delete_identity'].message_type = protobufs_dot_services_dot_user_dot_actions_dot_delete__identity__pb2._RESPONSEV1
service__protobufs_dot_soa__pb2.ActionResultV1.RegisterExtension(_USER.extensions_by_name['delete_identity'])
_USER.extensions_by_name['logout'].message_type = protobufs_dot_services_dot_user_dot_actions_dot_logout__pb2._RESPONSEV1
service__protobufs_dot_soa__pb2.ActionResultV1.RegisterExtension(_USER.extensions_by_name['logout'])
_USER.extensions_by_name['get_authentication_instructions'].message_type = protobufs_dot_services_dot_user_dot_actions_dot_get__authentication__instructions__pb2._RESPONSEV1
service__protobufs_dot_soa__pb2.ActionResultV1.RegisterExtension(_USER.extensions_by_name['get_authentication_instructions'])
_USER.extensions_by_name['get_active_devices'].message_type = protobufs_dot_services_dot_user_dot_actions_dot_get__active__devices__pb2._RESPONSEV1
service__protobufs_dot_soa__pb2.ActionResultV1.RegisterExtension(_USER.extensions_by_name['get_active_devices'])
_USER.extensions_by_name['bulk_update_users'].message_type = protobufs_dot_services_dot_user_dot_actions_dot_bulk__update__users__pb2._REQUESTV1
service__protobufs_dot_soa__pb2.ActionResultV1.RegisterExtension(_USER.extensions_by_name['bulk_update_users'])
_USER.extensions_by_name['get_integration_authentication_instructions'].message_type = protobufs_dot_services_dot_user_dot_actions_dot_get__integration__authentication__instructions__pb2._RESPONSEV1
service__protobufs_dot_soa__pb2.ActionResultV1.RegisterExtension(_USER.extensions_by_name['get_integration_authentication_instructions'])
_ORGANIZATION.extensions_by_name['create_organization'].message_type = protobufs_dot_services_dot_organization_dot_actions_dot_create__organization__pb2._RESPONSEV1
service__protobufs_dot_soa__pb2.ActionResultV1.RegisterExtension(_ORGANIZATION.extensions_by_name['create_organization'])
_ORGANIZATION.extensions_by_name['get_organization'].message_type = protobufs_dot_services_dot_organization_dot_actions_dot_get__organization__pb2._RESPONSEV1
service__protobufs_dot_soa__pb2.ActionResultV1.RegisterExtension(_ORGANIZATION.extensions_by_name['get_organization'])
_ORGANIZATION.extensions_by_name['get_team'].message_type = protobufs_dot_services_dot_organization_dot_actions_dot_get__team__pb2._RESPONSEV1
service__protobufs_dot_soa__pb2.ActionResultV1.RegisterExtension(_ORGANIZATION.extensions_by_name['get_team'])
_ORGANIZATION.extensions_by_name['create_location'].message_type = protobufs_dot_services_dot_organization_dot_actions_dot_create__location__pb2._RESPONSEV1
service__protobufs_dot_soa__pb2.ActionResultV1.RegisterExtension(_ORGANIZATION.extensions_by_name['create_location'])
_ORGANIZATION.extensions_by_name['update_location'].message_type = protobufs_dot_services_dot_organization_dot_actions_dot_update__location__pb2._RESPONSEV1
service__protobufs_dot_soa__pb2.ActionResultV1.RegisterExtension(_ORGANIZATION.extensions_by_name['update_location'])
_ORGANIZATION.extensions_by_name['get_locations'].message_type = protobufs_dot_services_dot_organization_dot_actions_dot_get__locations__pb2._RESPONSEV1
service__protobufs_dot_soa__pb2.ActionResultV1.RegisterExtension(_ORGANIZATION.extensions_by_name['get_locations'])
_ORGANIZATION.extensions_by_name['get_location'].message_type = protobufs_dot_services_dot_organization_dot_actions_dot_get__location__pb2._RESPONSEV1
service__protobufs_dot_soa__pb2.ActionResultV1.RegisterExtension(_ORGANIZATION.extensions_by_name['get_location'])
_ORGANIZATION.extensions_by_name['enable_integration'].message_type = protobufs_dot_services_dot_organization_dot_actions_dot_enable__integration__pb2._RESPONSEV1
service__protobufs_dot_soa__pb2.ActionResultV1.RegisterExtension(_ORGANIZATION.extensions_by_name['enable_integration'])
_ORGANIZATION.extensions_by_name['get_integration'].message_type = protobufs_dot_services_dot_organization_dot_actions_dot_get__integration__pb2._RESPONSEV1
service__protobufs_dot_soa__pb2.ActionResultV1.RegisterExtension(_ORGANIZATION.extensions_by_name['get_integration'])
_ORGANIZATION.extensions_by_name['disable_integration'].message_type = protobufs_dot_services_dot_organization_dot_actions_dot_disable__integration__pb2._RESPONSEV1
service__protobufs_dot_soa__pb2.ActionResultV1.RegisterExtension(_ORGANIZATION.extensions_by_name['disable_integration'])
_ORGANIZATION.extensions_by_name['update_team'].message_type = protobufs_dot_services_dot_organization_dot_actions_dot_update__team__pb2._RESPONSEV1
service__protobufs_dot_soa__pb2.ActionResultV1.RegisterExtension(_ORGANIZATION.extensions_by_name['update_team'])
_ORGANIZATION.extensions_by_name['add_direct_reports'].message_type = protobufs_dot_services_dot_organization_dot_actions_dot_add__direct__reports__pb2._RESPONSEV1
service__protobufs_dot_soa__pb2.ActionResultV1.RegisterExtension(_ORGANIZATION.extensions_by_name['add_direct_reports'])
_ORGANIZATION.extensions_by_name['get_location_members'].message_type = protobufs_dot_services_dot_organization_dot_actions_dot_get__location__members__pb2._RESPONSEV1
service__protobufs_dot_soa__pb2.ActionResultV1.RegisterExtension(_ORGANIZATION.extensions_by_name['get_location_members'])
_ORGANIZATION.extensions_by_name['get_profile_reporting_details'].message_type = protobufs_dot_services_dot_organization_dot_actions_dot_get__profile__reporting__details__pb2._RESPONSEV1
service__protobufs_dot_soa__pb2.ActionResultV1.RegisterExtension(_ORGANIZATION.extensions_by_name['get_profile_reporting_details'])
_ORGANIZATION.extensions_by_name['get_team_reporting_details'].message_type = protobufs_dot_services_dot_organization_dot_actions_dot_get__team__reporting__details__pb2._RESPONSEV1
service__protobufs_dot_soa__pb2.ActionResultV1.RegisterExtension(_ORGANIZATION.extensions_by_name['get_team_reporting_details'])
_ORGANIZATION.extensions_by_name['set_manager'].message_type = protobufs_dot_services_dot_organization_dot_actions_dot_set__manager__pb2._RESPONSEV1
service__protobufs_dot_soa__pb2.ActionResultV1.RegisterExtension(_ORGANIZATION.extensions_by_name['set_manager'])
_ORGANIZATION.extensions_by_name['add_location_members'].message_type = protobufs_dot_services_dot_organization_dot_actions_dot_add__location__members__pb2._RESPONSEV1
service__protobufs_dot_soa__pb2.ActionResultV1.RegisterExtension(_ORGANIZATION.extensions_by_name['add_location_members'])
_ORGANIZATION.extensions_by_name['get_teams'].message_type = protobufs_dot_services_dot_organization_dot_actions_dot_get__teams__pb2._RESPONSEV1
service__protobufs_dot_soa__pb2.ActionResultV1.RegisterExtension(_ORGANIZATION.extensions_by_name['get_teams'])
_ORGANIZATION.extensions_by_name['get_descendants'].message_type = protobufs_dot_services_dot_organization_dot_actions_dot_get__descendants__pb2._RESPONSEV1
service__protobufs_dot_soa__pb2.ActionResultV1.RegisterExtension(_ORGANIZATION.extensions_by_name['get_descendants'])
_ORGANIZATION.extensions_by_name['get_sso'].message_type = protobufs_dot_services_dot_organization_dot_actions_dot_get__sso__pb2._RESPONSEV1
service__protobufs_dot_soa__pb2.ActionResultV1.RegisterExtension(_ORGANIZATION.extensions_by_name['get_sso'])
_ORGANIZATION.extensions_by_name['get_teams_for_profile_ids'].message_type = protobufs_dot_services_dot_organization_dot_actions_dot_get__teams__for__profile__ids__pb2._RESPONSEV1
service__protobufs_dot_soa__pb2.ActionResultV1.RegisterExtension(_ORGANIZATION.extensions_by_name['get_teams_for_profile_ids'])
_PROFILE.extensions_by_name['create_profile'].message_type = protobufs_dot_services_dot_profile_dot_actions_dot_create__profile__pb2._RESPONSEV1
service__protobufs_dot_soa__pb2.ActionResultV1.RegisterExtension(_PROFILE.extensions_by_name['create_profile'])
_PROFILE.extensions_by_name['get_extended_profile'].message_type = protobufs_dot_services_dot_profile_dot_actions_dot_get__extended__profile__pb2._RESPONSEV1
service__protobufs_dot_soa__pb2.ActionResultV1.RegisterExtension(_PROFILE.extensions_by_name['get_extended_profile'])
_PROFILE.extensions_by_name['get_profile'].message_type = protobufs_dot_services_dot_profile_dot_actions_dot_get__profile__pb2._RESPONSEV1
service__protobufs_dot_soa__pb2.ActionResultV1.RegisterExtension(_PROFILE.extensions_by_name['get_profile'])
_PROFILE.extensions_by_name['update_profile'].message_type = protobufs_dot_services_dot_profile_dot_actions_dot_update__profile__pb2._RESPONSEV1
service__protobufs_dot_soa__pb2.ActionResultV1.RegisterExtension(_PROFILE.extensions_by_name['update_profile'])
_PROFILE.extensions_by_name['get_profiles'].message_type = protobufs_dot_services_dot_profile_dot_actions_dot_get__profiles__pb2._RESPONSEV1
service__protobufs_dot_soa__pb2.ActionResultV1.RegisterExtension(_PROFILE.extensions_by_name['get_profiles'])
_PROFILE.extensions_by_name['bulk_create_profiles'].message_type = protobufs_dot_services_dot_profile_dot_actions_dot_bulk__create__profiles__pb2._RESPONSEV1
service__protobufs_dot_soa__pb2.ActionResultV1.RegisterExtension(_PROFILE.extensions_by_name['bulk_create_profiles'])
_PROFILE.extensions_by_name['bulk_update_profiles'].message_type = protobufs_dot_services_dot_profile_dot_actions_dot_bulk__update__profiles__pb2._RESPONSEV1
service__protobufs_dot_soa__pb2.ActionResultV1.RegisterExtension(_PROFILE.extensions_by_name['bulk_update_profiles'])
_PROFILE.extensions_by_name['profile_exists'].message_type = protobufs_dot_services_dot_profile_dot_actions_dot_profile__exists__pb2._RESPONSEV1
service__protobufs_dot_soa__pb2.ActionResultV1.RegisterExtension(_PROFILE.extensions_by_name['profile_exists'])
_PROFILE.extensions_by_name['get_reporting_details'].message_type = protobufs_dot_services_dot_profile_dot_actions_dot_get__reporting__details__pb2._RESPONSEV1
service__protobufs_dot_soa__pb2.ActionResultV1.RegisterExtension(_PROFILE.extensions_by_name['get_reporting_details'])
_SEARCH.extensions_by_name['search'].message_type = protobufs_dot_services_dot_search_dot_actions_dot_search__pb2._RESPONSEV1
service__protobufs_dot_soa__pb2.ActionResultV1.RegisterExtension(_SEARCH.extensions_by_name['search'])
_SEARCH.extensions_by_name['search_v2'].message_type = protobufs_dot_services_dot_search_dot_actions_dot_search__v2__pb2._RESPONSEV1
service__protobufs_dot_soa__pb2.ActionResultV1.RegisterExtension(_SEARCH.extensions_by_name['search_v2'])
_SEARCH.extensions_by_name['update_entities'].message_type = protobufs_dot_services_dot_search_dot_actions_dot_update__entities__pb2._RESPONSEV1
service__protobufs_dot_soa__pb2.ActionResultV1.RegisterExtension(_SEARCH.extensions_by_name['update_entities'])
_SEARCH.extensions_by_name['delete_entities'].message_type = protobufs_dot_services_dot_search_dot_actions_dot_delete__entities__pb2._RESPONSEV1
service__protobufs_dot_soa__pb2.ActionResultV1.RegisterExtension(_SEARCH.extensions_by_name['delete_entities'])
_SEARCH.extensions_by_name['create_index'].message_type = protobufs_dot_services_dot_search_dot_actions_dot_create__index__pb2._RESPONSEV1
service__protobufs_dot_soa__pb2.ActionResultV1.RegisterExtension(_SEARCH.extensions_by_name['create_index'])
_SEARCH.extensions_by_name['track_recent'].message_type = protobufs_dot_services_dot_search_dot_actions_dot_track__recent__pb2._RESPONSEV1
service__protobufs_dot_soa__pb2.ActionResultV1.RegisterExtension(_SEARCH.extensions_by_name['track_recent'])
_SEARCH.extensions_by_name['get_recents'].message_type = protobufs_dot_services_dot_search_dot_actions_dot_get__recents__pb2._RESPONSEV1
service__protobufs_dot_soa__pb2.ActionResultV1.RegisterExtension(_SEARCH.extensions_by_name['get_recents'])
_SEARCH.extensions_by_name['delete_recent'].message_type = protobufs_dot_services_dot_search_dot_actions_dot_delete__recent__pb2._RESPONSEV1
service__protobufs_dot_soa__pb2.ActionResultV1.RegisterExtension(_SEARCH.extensions_by_name['delete_recent'])
_MEDIA.extensions_by_name['start_image_upload'].message_type = protobufs_dot_services_dot_media_dot_actions_dot_start__image__upload__pb2._RESPONSEV1
service__protobufs_dot_soa__pb2.ActionResultV1.RegisterExtension(_MEDIA.extensions_by_name['start_image_upload'])
_MEDIA.extensions_by_name['complete_image_upload'].message_type = protobufs_dot_services_dot_media_dot_actions_dot_complete__image__upload__pb2._RESPONSEV1
service__protobufs_dot_soa__pb2.ActionResultV1.RegisterExtension(_MEDIA.extensions_by_name['complete_image_upload'])
_NOTIFICATION.extensions_by_name['register_device'].message_type = protobufs_dot_services_dot_notification_dot_actions_dot_register__device__pb2._RESPONSEV1
service__protobufs_dot_soa__pb2.ActionResultV1.RegisterExtension(_NOTIFICATION.extensions_by_name['register_device'])
_NOTIFICATION.extensions_by_name['get_preferences'].message_type = protobufs_dot_services_dot_notification_dot_actions_dot_get__preferences__pb2._RESPONSEV1
service__protobufs_dot_soa__pb2.ActionResultV1.RegisterExtension(_NOTIFICATION.extensions_by_name['get_preferences'])
_NOTIFICATION.extensions_by_name['update_preference'].message_type = protobufs_dot_services_dot_notification_dot_actions_dot_update__preference__pb2._RESPONSEV1
service__protobufs_dot_soa__pb2.ActionResultV1.RegisterExtension(_NOTIFICATION.extensions_by_name['update_preference'])
_NOTIFICATION.extensions_by_name['send_notification'].message_type = protobufs_dot_services_dot_notification_dot_actions_dot_send__notification__pb2._RESPONSEV1
service__protobufs_dot_soa__pb2.ActionResultV1.RegisterExtension(_NOTIFICATION.extensions_by_name['send_notification'])
_NOTIFICATION.extensions_by_name['no_search_results'].message_type = protobufs_dot_services_dot_notification_dot_actions_dot_no__search__results__pb2._RESPONSEV1
service__protobufs_dot_soa__pb2.ActionResultV1.RegisterExtension(_NOTIFICATION.extensions_by_name['no_search_results'])
_HISTORY.extensions_by_name['record_action'].message_type = protobufs_dot_services_dot_history_dot_actions_dot_record__action__pb2._RESPONSEV1
service__protobufs_dot_soa__pb2.ActionResultV1.RegisterExtension(_HISTORY.extensions_by_name['record_action'])
_PAYMENT.extensions_by_name['store_token'].message_type = protobufs_dot_services_dot_payment_dot_actions_dot_store__token__pb2._RESPONSEV1
service__protobufs_dot_soa__pb2.ActionResultV1.RegisterExtension(_PAYMENT.extensions_by_name['store_token'])
_POST.extensions_by_name['create_post'].message_type = protobufs_dot_services_dot_post_dot_actions_dot_create__post__pb2._RESPONSEV1
service__protobufs_dot_soa__pb2.ActionResultV1.RegisterExtension(_POST.extensions_by_name['create_post'])
_POST.extensions_by_name['update_post'].message_type = protobufs_dot_services_dot_post_dot_actions_dot_update__post__pb2._RESPONSEV1
service__protobufs_dot_soa__pb2.ActionResultV1.RegisterExtension(_POST.extensions_by_name['update_post'])
_POST.extensions_by_name['get_post'].message_type = protobufs_dot_services_dot_post_dot_actions_dot_get__post__pb2._RESPONSEV1
service__protobufs_dot_soa__pb2.ActionResultV1.RegisterExtension(_POST.extensions_by_name['get_post'])
_POST.extensions_by_name['get_posts'].message_type = protobufs_dot_services_dot_post_dot_actions_dot_get__posts__pb2._RESPONSEV1
service__protobufs_dot_soa__pb2.ActionResultV1.RegisterExtension(_POST.extensions_by_name['get_posts'])
_POST.extensions_by_name['delete_post'].message_type = protobufs_dot_services_dot_post_dot_actions_dot_delete__post__pb2._RESPONSEV1
service__protobufs_dot_soa__pb2.ActionResultV1.RegisterExtension(_POST.extensions_by_name['delete_post'])
_POST.extensions_by_name['create_collection'].message_type = protobufs_dot_services_dot_post_dot_actions_dot_create__collection__pb2._RESPONSEV1
service__protobufs_dot_soa__pb2.ActionResultV1.RegisterExtension(_POST.extensions_by_name['create_collection'])
_POST.extensions_by_name['update_collection'].message_type = protobufs_dot_services_dot_post_dot_actions_dot_update__collection__pb2._RESPONSEV1
service__protobufs_dot_soa__pb2.ActionResultV1.RegisterExtension(_POST.extensions_by_name['update_collection'])
_POST.extensions_by_name['delete_collection'].message_type = protobufs_dot_services_dot_post_dot_actions_dot_delete__collection__pb2._RESPONSEV1
service__protobufs_dot_soa__pb2.ActionResultV1.RegisterExtension(_POST.extensions_by_name['delete_collection'])
_POST.extensions_by_name['add_to_collections'].message_type = protobufs_dot_services_dot_post_dot_actions_dot_add__to__collections__pb2._RESPONSEV1
service__protobufs_dot_soa__pb2.ActionResultV1.RegisterExtension(_POST.extensions_by_name['add_to_collections'])
_POST.extensions_by_name['remove_from_collections'].message_type = protobufs_dot_services_dot_post_dot_actions_dot_remove__from__collections__pb2._RESPONSEV1
service__protobufs_dot_soa__pb2.ActionResultV1.RegisterExtension(_POST.extensions_by_name['remove_from_collections'])
_POST.extensions_by_name['get_collection'].message_type = protobufs_dot_services_dot_post_dot_actions_dot_get__collection__pb2._RESPONSEV1
service__protobufs_dot_soa__pb2.ActionResultV1.RegisterExtension(_POST.extensions_by_name['get_collection'])
_POST.extensions_by_name['get_collections'].message_type = protobufs_dot_services_dot_post_dot_actions_dot_get__collections__pb2._RESPONSEV1
service__protobufs_dot_soa__pb2.ActionResultV1.RegisterExtension(_POST.extensions_by_name['get_collections'])
_POST.extensions_by_name['reorder_collection'].message_type = protobufs_dot_services_dot_post_dot_actions_dot_reorder__collection__pb2._RESPONSEV1
service__protobufs_dot_soa__pb2.ActionResultV1.RegisterExtension(_POST.extensions_by_name['reorder_collection'])
_POST.extensions_by_name['get_collection_items'].message_type = protobufs_dot_services_dot_post_dot_actions_dot_get__collection__items__pb2._RESPONSEV1
service__protobufs_dot_soa__pb2.ActionResultV1.RegisterExtension(_POST.extensions_by_name['get_collection_items'])
_POST.extensions_by_name['reorder_collections'].message_type = protobufs_dot_services_dot_post_dot_actions_dot_reorder__collections__pb2._RESPONSEV1
service__protobufs_dot_soa__pb2.ActionResultV1.RegisterExtension(_POST.extensions_by_name['reorder_collections'])
_POST.extensions_by_name['remove_from_collection'].message_type = protobufs_dot_services_dot_post_dot_actions_dot_remove__from__collection__pb2._RESPONSEV1
service__protobufs_dot_soa__pb2.ActionResultV1.RegisterExtension(_POST.extensions_by_name['remove_from_collection'])
_FEATURE.extensions_by_name['get_flags'].message_type = protobufs_dot_services_dot_feature_dot_actions_dot_get__flags__pb2._RESPONSEV1
service__protobufs_dot_soa__pb2.ActionResultV1.RegisterExtension(_FEATURE.extensions_by_name['get_flags'])
_FILE.extensions_by_name['start_upload'].message_type = protobufs_dot_services_dot_file_dot_actions_dot_start__upload__pb2._RESPONSEV1
service__protobufs_dot_soa__pb2.ActionResultV1.RegisterExtension(_FILE.extensions_by_name['start_upload'])
_FILE.extensions_by_name['complete_upload'].message_type = protobufs_dot_services_dot_file_dot_actions_dot_complete__upload__pb2._RESPONSEV1
service__protobufs_dot_soa__pb2.ActionResultV1.RegisterExtension(_FILE.extensions_by_name['complete_upload'])
_FILE.extensions_by_name['delete'].message_type = protobufs_dot_services_dot_file_dot_actions_dot_delete__pb2._RESPONSEV1
service__protobufs_dot_soa__pb2.ActionResultV1.RegisterExtension(_FILE.extensions_by_name['delete'])
_FILE.extensions_by_name['get_files'].message_type = protobufs_dot_services_dot_file_dot_actions_dot_get__files__pb2._RESPONSEV1
service__protobufs_dot_soa__pb2.ActionResultV1.RegisterExtension(_FILE.extensions_by_name['get_files'])
_FILE.extensions_by_name['upload'].message_type = protobufs_dot_services_dot_file_dot_actions_dot_upload__pb2._RESPONSEV1
service__protobufs_dot_soa__pb2.ActionResultV1.RegisterExtension(_FILE.extensions_by_name['upload'])
_FILE.extensions_by_name['get_file'].message_type = protobufs_dot_services_dot_file_dot_actions_dot_get__file__pb2._RESPONSEV1
service__protobufs_dot_soa__pb2.ActionResultV1.RegisterExtension(_FILE.extensions_by_name['get_file'])
_TEAM.extensions_by_name['add_members'].message_type = protobufs_dot_services_dot_team_dot_actions_dot_add__members__pb2._RESPONSEV1
service__protobufs_dot_soa__pb2.ActionResultV1.RegisterExtension(_TEAM.extensions_by_name['add_members'])
_TEAM.extensions_by_name['create_team'].message_type = protobufs_dot_services_dot_team_dot_actions_dot_create__team__pb2._RESPONSEV1
service__protobufs_dot_soa__pb2.ActionResultV1.RegisterExtension(_TEAM.extensions_by_name['create_team'])
_TEAM.extensions_by_name['get_team'].message_type = protobufs_dot_services_dot_team_dot_actions_dot_get__team__pb2._RESPONSEV1
service__protobufs_dot_soa__pb2.ActionResultV1.RegisterExtension(_TEAM.extensions_by_name['get_team'])
_TEAM.extensions_by_name['get_members'].message_type = protobufs_dot_services_dot_team_dot_actions_dot_get__members__pb2._RESPONSEV1
service__protobufs_dot_soa__pb2.ActionResultV1.RegisterExtension(_TEAM.extensions_by_name['get_members'])
_TEAM.extensions_by_name['join_team'].message_type = protobufs_dot_services_dot_team_dot_actions_dot_join__team__pb2._RESPONSEV1
service__protobufs_dot_soa__pb2.ActionResultV1.RegisterExtension(_TEAM.extensions_by_name['join_team'])
_TEAM.extensions_by_name['leave_team'].message_type = protobufs_dot_services_dot_team_dot_actions_dot_leave__team__pb2._RESPONSEV1
service__protobufs_dot_soa__pb2.ActionResultV1.RegisterExtension(_TEAM.extensions_by_name['leave_team'])
_TEAM.extensions_by_name['remove_members'].message_type = protobufs_dot_services_dot_team_dot_actions_dot_remove__members__pb2._RESPONSEV1
service__protobufs_dot_soa__pb2.ActionResultV1.RegisterExtension(_TEAM.extensions_by_name['remove_members'])
_TEAM.extensions_by_name['update_members'].message_type = protobufs_dot_services_dot_team_dot_actions_dot_update__members__pb2._RESPONSEV1
service__protobufs_dot_soa__pb2.ActionResultV1.RegisterExtension(_TEAM.extensions_by_name['update_members'])
_TEAM.extensions_by_name['update_team'].message_type = protobufs_dot_services_dot_team_dot_actions_dot_update__team__pb2._RESPONSEV1
service__protobufs_dot_soa__pb2.ActionResultV1.RegisterExtension(_TEAM.extensions_by_name['update_team'])
_TEAM.extensions_by_name['get_teams'].message_type = protobufs_dot_services_dot_team_dot_actions_dot_get__teams__pb2._RESPONSEV1
service__protobufs_dot_soa__pb2.ActionResultV1.RegisterExtension(_TEAM.extensions_by_name['get_teams'])
DESCRIPTOR.has_options = True
DESCRIPTOR._options = _descriptor._ParseOptions(descriptor_pb2.FileOptions(), b'\n0com.rhlabs.protobufs.services.registry.responses')
# @@protoc_insertion_point(module_scope)
| 80.295505
| 18,970
| 0.840842
| 14,768
| 108,961
| 5.711742
| 0.038123
| 0.053775
| 0.066863
| 0.076893
| 0.882894
| 0.837583
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| 0.662197
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| 0.068915
| 108,961
| 1,356
| 18,971
| 80.35472
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0
| 5
|
b22312ac1d4f8b5af20ce5813049059576bb0f25
| 191
|
py
|
Python
|
EasyVision/vision/__init__.py
|
foxis/EasyVision
|
ffb2ce1a93fdace39c6bcc13c8ae518cec76919e
|
[
"MIT",
"BSD-3-Clause"
] | 7
|
2018-12-27T07:45:31.000Z
|
2021-06-17T03:49:15.000Z
|
EasyVision/vision/__init__.py
|
itohio/EasyVision
|
de6a4bb9160cd08278ae9c5738497132a4cd3202
|
[
"MIT",
"BSD-3-Clause"
] | null | null | null |
EasyVision/vision/__init__.py
|
itohio/EasyVision
|
de6a4bb9160cd08278ae9c5738497132a4cd3202
|
[
"MIT",
"BSD-3-Clause"
] | 3
|
2019-08-21T03:36:56.000Z
|
2021-10-08T16:12:53.000Z
|
# -*- coding: utf-8 -*-
from .base import Image, Frame
from .exceptions import *
from .videocapture import VideoCapture
from .pyrocapture import PyroCapture
from .images import ImagesReader
| 23.875
| 38
| 0.774869
| 23
| 191
| 6.434783
| 0.565217
| 0
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| 0
| 0.006098
| 0.141361
| 191
| 7
| 39
| 27.285714
| 0.896341
| 0.109948
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| 1
| 0
|
0
| 5
|
b27a15fdbc94027b89fe9a0b6e6adc7f64315ac4
| 283
|
py
|
Python
|
bitmovin/resources/models/manifests/hls/__init__.py
|
camberbridge/bitmovin-python
|
3af4c6e79b0291fda05fd1ceeb5bed1bba9f3c95
|
[
"Unlicense"
] | null | null | null |
bitmovin/resources/models/manifests/hls/__init__.py
|
camberbridge/bitmovin-python
|
3af4c6e79b0291fda05fd1ceeb5bed1bba9f3c95
|
[
"Unlicense"
] | null | null | null |
bitmovin/resources/models/manifests/hls/__init__.py
|
camberbridge/bitmovin-python
|
3af4c6e79b0291fda05fd1ceeb5bed1bba9f3c95
|
[
"Unlicense"
] | null | null | null |
from .hls_manifest import HlsManifest
from .audio_media import AudioMedia
from .video_media import VideoMedia
from .subtitles_media import SubtitlesMedia
from .closed_captions_media import ClosedCaptionsMedia
from .variant_stream import VariantStream
from .vtt_media import VttMedia
| 35.375
| 54
| 0.876325
| 36
| 283
| 6.666667
| 0.555556
| 0.229167
| 0
| 0
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| 0.09894
| 283
| 7
| 55
| 40.428571
| 0.941176
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| 1
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|
0
| 5
|
b282781cc71135bd1e5d663cffe572f229a6487b
| 69
|
py
|
Python
|
bayom_e/__init__.py
|
dkauf42/bayota
|
104ba91746231be10419390a9d7ed8f2593a21bc
|
[
"BSD-3-Clause"
] | 1
|
2021-07-23T18:09:55.000Z
|
2021-07-23T18:09:55.000Z
|
bayom_e/__init__.py
|
dkauf42/bayota
|
104ba91746231be10419390a9d7ed8f2593a21bc
|
[
"BSD-3-Clause"
] | null | null | null |
bayom_e/__init__.py
|
dkauf42/bayota
|
104ba91746231be10419390a9d7ed8f2593a21bc
|
[
"BSD-3-Clause"
] | null | null | null |
from bayom_e import data_handling, model_handling, solution_handling
| 34.5
| 68
| 0.884058
| 10
| 69
| 5.7
| 0.8
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.086957
| 69
| 1
| 69
| 69
| 0.904762
| 0
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| 0
| 1
| 0
|
0
| 5
|
b2a657989cf03f166fa0efe4ba7fd64618b90080
| 166
|
py
|
Python
|
app_template/recommender/movierecommender/views.py
|
ibm-developer-skills-network/oroir-Build-a-Personal-Movie-Recommender-with-Django
|
fbc681cdea067c0cee91c158c632f83cff9db936
|
[
"Apache-2.0"
] | null | null | null |
app_template/recommender/movierecommender/views.py
|
ibm-developer-skills-network/oroir-Build-a-Personal-Movie-Recommender-with-Django
|
fbc681cdea067c0cee91c158c632f83cff9db936
|
[
"Apache-2.0"
] | null | null | null |
app_template/recommender/movierecommender/views.py
|
ibm-developer-skills-network/oroir-Build-a-Personal-Movie-Recommender-with-Django
|
fbc681cdea067c0cee91c158c632f83cff9db936
|
[
"Apache-2.0"
] | null | null | null |
from . import views
from .models import Movie
from django.shortcuts import render
# HINT: Create a view to provide movie recommendations list for the HTML template
| 23.714286
| 81
| 0.801205
| 25
| 166
| 5.32
| 0.8
| 0
| 0
| 0
| 0
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| 0
| 0
| 0.168675
| 166
| 6
| 82
| 27.666667
| 0.963768
| 0.475904
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| null | 0
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| 0
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| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
a249ff12f6889cf8a446390177bde9c79ea29f9f
| 63
|
py
|
Python
|
mlib/requests/__init__.py
|
tmunzer/Mist_library
|
5d44325dc5b59483d9d6803f31fe1568762b04ca
|
[
"MIT"
] | 13
|
2020-04-21T21:11:56.000Z
|
2021-07-15T21:42:41.000Z
|
mlib/requests/__init__.py
|
tmunzer/mist_library
|
812828a6486f59850a12dda4f81dbfd76929ed6b
|
[
"MIT"
] | null | null | null |
mlib/requests/__init__.py
|
tmunzer/mist_library
|
812828a6486f59850a12dda4f81dbfd76929ed6b
|
[
"MIT"
] | 2
|
2020-06-18T20:07:51.000Z
|
2020-08-13T16:43:32.000Z
|
from . import orgs
from . import sites
from .route import route
| 21
| 24
| 0.777778
| 10
| 63
| 4.9
| 0.5
| 0.408163
| 0
| 0
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| 0
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| 0
| 0.174603
| 63
| 3
| 24
| 21
| 0.942308
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| 1
| 0
| 0
| 0
|
0
| 5
|
a24a7261491e1b966181407da147f2eb3bc5356a
| 1,271
|
py
|
Python
|
tests/test_rtd_poetry.py
|
dbrnz/rtd-poetry
|
b4c834a43201639765b595aeb1b6b5645d22f192
|
[
"MIT"
] | 1
|
2019-05-05T18:28:41.000Z
|
2019-05-05T18:28:41.000Z
|
tests/test_rtd_poetry.py
|
dbrnz/rtd-poetry
|
b4c834a43201639765b595aeb1b6b5645d22f192
|
[
"MIT"
] | 3
|
2019-05-05T18:16:24.000Z
|
2021-01-09T16:17:59.000Z
|
tests/test_rtd_poetry.py
|
dbrnz/rtd-poetry
|
b4c834a43201639765b595aeb1b6b5645d22f192
|
[
"MIT"
] | 2
|
2020-07-06T17:33:49.000Z
|
2021-07-06T03:56:29.000Z
|
import os
import subprocess
from pathlib import Path
from . import chdir
def test_does_not_install_dev_requirements_normally(virtualenv):
result = virtualenv(['-m', 'pip', 'install', '--upgrade', 'pip'])
assert result.returncode == 0
env = os.environ.copy()
env.pop('READTHEDOCS', None)
with chdir(Path(__file__).parent / '..'):
result = virtualenv(['-m', 'pip', 'install', '.'], env=env)
assert result.returncode == 0
result = virtualenv(['-m', 'pip', 'freeze'], stdout=subprocess.PIPE)
assert result.returncode == 0
output = result.stdout.decode('utf-8')
assert 'rtd-poetry' in output
assert 'pytest' not in output
def test_installs_dev_requirements_if_rtd_env_is_set(virtualenv):
result = virtualenv(['-m', 'pip', 'install', '--upgrade', 'pip'])
assert result.returncode == 0
env = os.environ.copy()
env['READTHEDOCS'] = 'True'
with chdir(Path(__file__).parent / '..'):
result = virtualenv(['-m', 'pip', 'install', '.'], env=env)
assert result.returncode == 0
result = virtualenv(['-m', 'pip', 'freeze'], stdout=subprocess.PIPE)
assert result.returncode == 0
output = result.stdout.decode('utf-8')
assert 'rtd-poetry' in output
assert 'pytest' in output
| 31
| 72
| 0.645948
| 155
| 1,271
| 5.154839
| 0.309677
| 0.12015
| 0.12766
| 0.150188
| 0.750939
| 0.750939
| 0.750939
| 0.750939
| 0.750939
| 0.750939
| 0
| 0.007729
| 0.185681
| 1,271
| 40
| 73
| 31.775
| 0.764251
| 0
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| 0.666667
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| 0.132179
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| 0.333333
| 1
| 0.066667
| false
| 0
| 0.133333
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| 0.2
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| 0
| 0
| 0
|
0
| 5
|
a28c7acfd5412834f2e721677d536976a68e97d6
| 176
|
py
|
Python
|
cgkit/scaffolds/game.py
|
50m-regent/CGKit
|
077062e78518596b9dcf21681bdb58f93bdef23c
|
[
"MIT"
] | null | null | null |
cgkit/scaffolds/game.py
|
50m-regent/CGKit
|
077062e78518596b9dcf21681bdb58f93bdef23c
|
[
"MIT"
] | 5
|
2020-06-19T06:31:27.000Z
|
2020-06-21T04:25:50.000Z
|
cgkit/scaffolds/game.py
|
50m-regent/CGKit
|
077062e78518596b9dcf21681bdb58f93bdef23c
|
[
"MIT"
] | null | null | null |
from random import randint
class Game:
def __init__(self, players=[]):
self.players = players
def init(self):
self.turn = randint(0, len(players) - 1)
| 22
| 48
| 0.625
| 23
| 176
| 4.608696
| 0.608696
| 0.132075
| 0.207547
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.015267
| 0.255682
| 176
| 8
| 48
| 22
| 0.793893
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.333333
| false
| 0
| 0.166667
| 0
| 0.666667
| 0
| 1
| 0
| 0
| null | 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
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| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 1
| 0
|
0
| 5
|
a2bef5fb752d6b1fb08c41b394f289ca3d9c2bf1
| 383
|
py
|
Python
|
JanggiGame/Engine/helpers/__init__.py
|
MohamedAl-Hussein/janggi-game
|
0664a408563b824c0b665d755ff9b232b6f24644
|
[
"MIT"
] | null | null | null |
JanggiGame/Engine/helpers/__init__.py
|
MohamedAl-Hussein/janggi-game
|
0664a408563b824c0b665d755ff9b232b6f24644
|
[
"MIT"
] | null | null | null |
JanggiGame/Engine/helpers/__init__.py
|
MohamedAl-Hussein/janggi-game
|
0664a408563b824c0b665d755ff9b232b6f24644
|
[
"MIT"
] | null | null | null |
from .command import MoveCommand
from .command_manager import CommandManager
from .obstacle_detection_strategy import IObstacleDetectionStrategy, IllegalDestinationStrategy, \
IllegalPathStrategy, InsidePalaceStrategy
from .path_generation_strategy import IPathGenerationStrategy, BranchPathStrategy, LinearDiagonalPathStrategy, \
LinearPathStrategy
from .stack import Stack
| 47.875
| 112
| 0.872063
| 31
| 383
| 10.612903
| 0.645161
| 0.066869
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.093995
| 383
| 7
| 113
| 54.714286
| 0.948127
| 0
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| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.714286
| 0
| 0.714286
| 0
| 0
| 0
| 1
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
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| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
a2c1e57e1ffc69499c9be4cf8e41edc7eea09fa7
| 62
|
py
|
Python
|
tests/__init__.py
|
bilts/harmony-service-lib-py
|
6eb358539adab9510d75158737de2b55fba85f91
|
[
"Apache-2.0"
] | 5
|
2021-03-25T23:27:24.000Z
|
2022-01-10T01:23:41.000Z
|
tests/__init__.py
|
bilts/harmony-service-lib-py
|
6eb358539adab9510d75158737de2b55fba85f91
|
[
"Apache-2.0"
] | 4
|
2021-03-01T21:23:22.000Z
|
2021-07-19T15:38:59.000Z
|
tests/__init__.py
|
bilts/harmony-service-lib-py
|
6eb358539adab9510d75158737de2b55fba85f91
|
[
"Apache-2.0"
] | 4
|
2021-02-25T19:55:36.000Z
|
2021-10-01T18:35:09.000Z
|
import os
os.environ['ENV'] = os.environ.get('ENV') or 'test'
| 20.666667
| 51
| 0.66129
| 11
| 62
| 3.727273
| 0.636364
| 0.439024
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.112903
| 62
| 2
| 52
| 31
| 0.745455
| 0
| 0
| 0
| 0
| 0
| 0.16129
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.5
| 0
| 0.5
| 0
| 1
| 0
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 5
|
a2c43ede13bcf8aa1ce8292df9f5e1df575e77b6
| 41,594
|
py
|
Python
|
model.py
|
machelreid/vcdm
|
a9e281229747d2fe052f741a44f2b2510482c29b
|
[
"MIT"
] | 10
|
2020-10-24T09:18:02.000Z
|
2022-02-14T22:55:45.000Z
|
model.py
|
machelreid/vcdm
|
a9e281229747d2fe052f741a44f2b2510482c29b
|
[
"MIT"
] | null | null | null |
model.py
|
machelreid/vcdm
|
a9e281229747d2fe052f741a44f2b2510482c29b
|
[
"MIT"
] | 3
|
2021-02-03T13:57:48.000Z
|
2022-03-23T16:06:58.000Z
|
import transformers
import torch
import torch.nn as nn
import torch.nn.functional as F
from allennlp.modules.span_extractors import (
EndpointSpanExtractor,
SelfAttentiveSpanExtractor,
)
from allennlp.modules.scalar_mix import ScalarMix
from utils import sequence_mask, find_subtensor, batched_span_select
from dotmap import DotMap
import random
from beam import BeamSearch
from onmt.modules import GlobalAttention
from onmt.translate import GNMTGlobalScorer
from torch.distributions.bernoulli import Bernoulli
from torch.distributions import Normal
from torch.distributions.kl import kl_divergence
from attention import Attention
class DefinitionProbing(nn.Module):
def __init__(
self,
encoder,
encoder_pretrained,
encoder_frozen,
decoder_hidden,
embeddings,
max_layer=12,
src_pad_idx=0,
encoder_hidden=None,
variational=None,
latent_size=None,
scalar_mix=False,
aggregator="mean",
teacher_forcing_p=0.3,
classification=None,
attentional=False,
definition_encoder=None,
word_dropout_p=None,
decoder_num_layers=None,
):
super(DefinitionProbing, self).__init__()
self.embeddings = embeddings
self.variational = variational
self.encoder_hidden = encoder_hidden
self.decoder_hidden = decoder_hidden
self.decoder_num_layers = decoder_num_layers
self.encoder = encoder
self.latent_size = latent_size
self.src_pad_idx = src_pad_idx
if encoder_pretrained:
self.encoder_hidden = self.encoder.config.hidden_size
if encoder_frozen:
for param in self.encoder.parameters():
param.requires_grad = False
self.max_layer = max_layer
self.aggregator = aggregator
if self.aggregator == "span":
self.span_extractor = SelfAttentiveSpanExtractor(self.encoder_hidden)
self.context_feed_forward = nn.Linear(self.encoder_hidden, self.encoder_hidden)
self.scalar_mix = None
if scalar_mix:
self.scalar_mix = ScalarMix(self.max_layer + 1)
self.global_scorer = GNMTGlobalScorer(
alpha=2, beta=None, length_penalty="avg", coverage_penalty=None
)
self.decoder = LSTM_Decoder(
embeddings.tgt,
hidden=self.decoder_hidden,
encoder_hidden=self.encoder_hidden,
num_layers=self.decoder_num_layers,
word_dropout=word_dropout_p,
teacher_forcing_p=teacher_forcing_p,
attention="general" if attentional else None,
dropout=DotMap({"input": 0.5, "output": 0.5}),
decoder="VDM" if self.variational else "LSTM",
variational=self.variational,
latent_size=self.latent_size,
)
self.target_kl = 1.0
if self.variational:
self.definition_encoder = definition_encoder
self.definition_feed_forward = nn.Linear(
self.encoder_hidden, self.encoder_hidden
)
self.mean_layer = nn.Linear(self.latent_size, self.latent_size)
self.logvar_layer = nn.Linear(self.latent_size, self.latent_size)
self.w_z_post = nn.Sequential(
nn.Linear(self.encoder_hidden * 2, self.latent_size), nn.Tanh()
)
self.mean_prime_layer = nn.Linear(self.latent_size, self.latent_size)
self.logvar_prime_layer = nn.Linear(self.latent_size, self.latent_size)
self.w_z_prior = nn.Sequential(
nn.Linear(self.encoder_hidden, self.latent_size), nn.Tanh()
)
self.z_project = nn.Sequential(
nn.Linear(self.latent_size, self.decoder_hidden), nn.Tanh()
)
def forward(
self,
input,
seq_lens,
span_token_ids,
target,
target_lens,
definition=None,
definition_lens=None,
classification_labels=None,
sentence_mask=None,
):
batch_size, tgt_len = target.shape
# (batch_size,seq_len,hidden_size), (batch_size,hidden_size), (num_layers,batch_size,seq_len,hidden_size)
last_hidden_layer, sentence_representation, all_hidden_layers = self.encoder(
input, attention_mask=sequence_mask(seq_lens), token_type_ids=sentence_mask
)
cosine_loss = None
loss = None
KLD = None
fake_loss_kl = None
if self.aggregator == "cls":
cls_hidden = last_hidden_layer[:, 0, :].squeeze(1)
span_representation = self.context_feed_forward(cls_hidden)
hidden_states = last_hidden_layer
else:
span_ids = self._id_extractor(
tokens=span_token_ids, batch=input, lens=seq_lens
)
span_representation, hidden_states = self._span_aggregator(
all_hidden_layers if self.scalar_mix is not None else last_hidden_layer,
sequence_mask(seq_lens),
span_ids,
)
span_representation = self.context_feed_forward(span_representation)
if self.variational:
(
definition_last_hidden_layer,
_,
definition_all_hidden_layers,
) = self.definition_encoder(
definition, attention_mask=sequence_mask(definition_lens)
)
definition_representation = self.definition_feed_forward(
definition_last_hidden_layer[:, 0]
)
post_project = self.w_z_post(
torch.cat([span_representation, definition_representation], -1)
)
prior_project = self.w_z_prior(span_representation)
mu = self.mean_layer(post_project)
logvar = self.logvar_layer(post_project)
mu_prime = self.mean_prime_layer(prior_project)
logvar_prime = self.logvar_prime_layer(prior_project)
z = mu + torch.exp(logvar * 0.5) * torch.randn_like(logvar)
span_representation = self.z_project(z)
KLD = kl_divergence(
Normal(mu, torch.exp(logvar * 0.5)),
Normal(mu_prime, torch.exp(logvar_prime * 0.5)),
)
kl_mask = (KLD > (self.target_kl / self.latent_size)).float()
fake_loss_kl = (kl_mask * KLD).sum(dim=1)
predictions, logits = self.decoder(
target, target_lens, span_representation, hidden_states, seq_lens,
)
if self.variational:
loss = (
F.cross_entropy(
logits.view(batch_size * (tgt_len - 1), -1),
target[:, 1:].contiguous().view(-1),
ignore_index=self.embeddings.tgt.padding_idx,
reduction="none",
)
.view(batch_size, tgt_len - 1)
.sum(1)
)
perplexity = F.cross_entropy(
logits.view(batch_size * (tgt_len - 1), -1),
target[:, 1:].contiguous().view(-1),
ignore_index=self.embeddings.tgt.padding_idx,
reduction="mean",
).exp()
else:
loss = F.cross_entropy(
logits.view(batch_size * (tgt_len - 1), -1),
target[:, 1:].contiguous().view(-1),
ignore_index=self.embeddings.tgt.padding_idx,
)
perplexity = loss.exp()
return DotMap(
{
"predictions": predictions,
"logits": logits,
"loss": loss,
"perplexity": perplexity,
"fake_kl": fake_loss_kl,
"kl": KLD,
"cosine_loss": cosine_loss,
}
)
def _validate(
self,
input,
seq_lens,
span_token_ids,
target,
target_lens,
decode_strategy,
definition=None,
definition_lens=None,
sentence_mask=None,
):
batch_size, tgt_len = target.shape
# (batch_size,seq_len,hidden_size), (batch_size,hidden_size), (num_layers,batch_size,seq_len,hidden_size)
last_hidden_layer, pooled_representation, all_hidden_layers = self.encoder(
input, attention_mask=sequence_mask(seq_lens), token_type_ids=sentence_mask
)
KLD = None
mu_prime = None
if self.aggregator == "cls":
cls_hidden = last_hidden_layer[:, 0]
cls_hidden_forwarded = self.cls_feed_forward(cls_hidden)
span_representation = cls_hidden_forwarded
hidden_states = last_hidden_layer
else:
span_ids = self._id_extractor(
tokens=span_token_ids, batch=input, lens=seq_lens
)
span_representation, hidden_states = self._span_aggregator(
all_hidden_layers if self.scalar_mix is not None else last_hidden_layer,
sequence_mask(seq_lens),
span_ids,
)
span_representation = self.context_feed_forward(span_representation)
if self.variational:
(
definition_last_hidden_layer,
_,
definition_all_hidden_layers,
) = self.definition_encoder(
definition, attention_mask=sequence_mask(definition_lens)
)
definition_representation = self.definition_feed_forward(
definition_last_hidden_layer[:, 0]
)
post_project = self.w_z_post(
torch.cat([span_representation, definition_representation], -1)
)
prior_project = self.w_z_prior(span_representation)
mu = self.mean_layer(post_project)
logvar = self.logvar_layer(post_project)
mu_prime = self.mean_prime_layer(prior_project)
logvar_prime = self.logvar_prime_layer(prior_project)
hidden_states = last_hidden_layer
KLD = (
kl_divergence(
Normal(mu, torch.exp(logvar * 0.5)),
Normal(mu_prime, torch.exp(logvar_prime * 0.5)),
)
.sum(1)
.mean()
)
span_representation = self.z_project(mu_prime)
memory_bank = hidden_states if self.decoder.attention else None
_, logits = self.decoder(
target, target_lens, span_representation, memory_bank, seq_lens,
)
loss = F.cross_entropy(
logits.view(batch_size * (tgt_len - 1), -1),
target[:, 1:].contiguous().view(-1),
ignore_index=self.embeddings.tgt.padding_idx,
)
ppl = loss.exp()
beam_results = self._strategic_decode(
target,
target_lens,
decode_strategy,
memory_bank,
seq_lens,
span_representation,
)
return DotMap(
{
"predictions": beam_results["predictions"],
"logits": logits.view(batch_size * (tgt_len - 1), -1),
"loss": loss,
"perplexity": ppl,
"kl": KLD,
}
)
def _strategic_decode(
self,
target,
target_lens,
decode_strategy,
memory_bank,
memory_lengths,
span_representation,
):
"""Translate a batch of sentences step by step using cache.
Args:
batch: a batch of sentences, yield by data iterator.
src_vocabs (list): list of torchtext.data.Vocab if can_copy.
decode_strategy (DecodeStrategy): A decode strategy to use for
generate translation step by step.
Returns:
results (dict): The translation results.
"""
parallel_paths = decode_strategy.parallel_paths # beam_size
# (0) Prep the components of the search.
# use_src_map = self.copy_attn
batch_size, max_len = target.shape
# Initialize the hidden states
self.decoder.init_state(
span_representation, encoder_hidden=memory_bank, src_lens=memory_lengths
)
results = {
"predictions": None,
"scores": None,
"attention": None,
# "gold_score": self._gold_score(
# batch, memory_bank, src_lengths, src_vocabs, use_src_map,
# enc_states, batch_size, src)
}
# (2) prep decode_strategy. Possibly repeat src objects.
src_map = None # batch.src_map if use_src_map else None
fn_map_state, memory_bank, memory_lengths, src_map = decode_strategy.initialize(
memory_bank, memory_lengths, src_map, device="cuda"
)
if fn_map_state is not None:
self.decoder.map_state(fn_map_state)
# (3) Begin decoding step by step:
for step in range(decode_strategy.max_length):
decoder_input = decode_strategy.current_predictions
logits, attn = self.decoder.generate(
decoder_input, memory_bank, memory_lengths
)
decode_strategy.advance(F.log_softmax(logits, 1), attn)
any_finished = decode_strategy.is_finished.any()
if any_finished:
decode_strategy.update_finished()
if decode_strategy.done:
break
select_indices = decode_strategy.select_indices
if any_finished:
# Reorder states.
if memory_bank is not None:
if isinstance(memory_bank, tuple):
memory_bank = tuple(
x.index_select(0, select_indices) for x in memory_bank
)
else:
memory_bank = memory_bank.index_select(0, select_indices)
memory_lengths = memory_lengths.index_select(0, select_indices)
if src_map is not None:
src_map = src_map.index_select(1, select_indices)
if parallel_paths > 1 or any_finished:
self.decoder.map_state(
lambda state, dim: state.index_select(dim, select_indices)
)
results["scores"] = decode_strategy.scores
results["predictions"] = decode_strategy.predictions
results["attention"] = decode_strategy.attention
# if self.decoder.attention:
# results["alignment"] = self._align_forward(
# batch, decode_strategy.predictions
# )
# else:
# results["alignment"] = [[] for _ in range(batch_size)]
return results
def _span_aggregator(
self, hidden_states, input_mask, span_ids, layer_no: int = None,
):
if layer_no is not None:
hidden_states = hidden_states[layer_no]
if isinstance(hidden_states, tuple):
hidden_states = hidden_states[: self.max_layer + 1]
hidden_states = self.scalar_mix(hidden_states, mask=input_mask)
if self.aggregator == "span":
span = self.span_extractor(hidden_states, span_ids).squeeze(
1
) # As we will only be extracting one span per sequence
elif self.aggregator == "mean":
extracted_embeddings, span_mask = batched_span_select(
hidden_states, span_ids
)
extracted_embeddings = (
extracted_embeddings * span_mask.type(torch.float).unsqueeze(-1)
).squeeze(1)
lengths = (span_mask == True).sum(-1) + 1e-20 # To avoid zero division
span = extracted_embeddings.sum(1) / lengths
return span, hidden_states
def _id_extractor(self, tokens, batch, lens):
"""
Extracts span indices given a sequence, if none found returns the span as the start and end of sequence as the span
"""
with torch.no_grad():
output_ids = []
for w in tokens:
output_ids.append(
torch.tensor(
list(filter((self.src_pad_idx).__ne__, w.tolist()))[1:-1]
)
)
output_indices = []
for i in range(batch.shape[0]):
tensor = find_subtensor(output_ids[i], batch[i])
if tensor is None:
tensor = torch.tensor([1, lens[i].item() - 1]).to("cuda")
output_indices.append(tensor)
return torch.stack(output_indices).unsqueeze(1)
class LSTM_Decoder(nn.Module):
def __init__(
self,
embeddings=None,
hidden=None,
encoder_hidden=None,
num_layers=1,
teacher_forcing_p=0.0,
attention=None,
dropout=None,
char_encoder_hidden=None,
char_attention=None,
word_dropout=None,
encoder_feeding=False,
variational=False,
decoder="LSTM",
latent_size=None,
):
super(LSTM_Decoder, self).__init__()
# TODO Use Fairseq attention
self.embeddings = embeddings
self.hidden = hidden
self.embedding_dropout = nn.Dropout(dropout.input)
self.hidden_state_dropout = nn.Dropout(dropout.output)
self.word_dropout_p = word_dropout if word_dropout is not None else 0.0
self.variational = variational
if self.variational:
encoder_feeding = True
self.encoder_hidden_proj = lambda x: x
else:
self.encoder_hidden_proj = (
nn.Linear(encoder_hidden, hidden, bias=False)
if (encoder_hidden != hidden or encoder_hidden is None)
else lambda x: x
)
self.lstm_decoder = nn.ModuleList()
self.num_layers = num_layers
self.input_feeding_size = 0 # latent_size if self.variational else 0
if decoder == "LSTM":
decoder_cell = [nn.LSTMCell] * self.num_layers
elif decoder == "VDM":
if self.num_layers == 1:
decoder_cell = [VDM_LSTMCell]
else:
decoder_cell = [nn.LSTMCell] * (self.num_layers - 1) + [VDM_LSTMCell]
for i in range(self.num_layers):
if i == 0:
self.lstm_decoder.append(
decoder_cell[i](
self.embeddings.embedding_dim + self.input_feeding_size,
self.hidden,
)
)
else:
self.lstm_decoder.append(decoder_cell[i](self.hidden, self.hidden))
self.teacher_forcing_p = teacher_forcing_p
self.state = {
"hidden": [None] * self.num_layers,
"cell": [None] * self.num_layers,
"latent": [None] * self.num_layers,
}
self.attention = attention
self.proj_layer = nn.Linear(self.hidden, self.embeddings.num_embeddings)
if attention is not None:
self.enc_hidden_att_komp = (
nn.Linear(encoder_hidden, hidden, bias=False)
if (encoder_hidden != hidden or encoder_hidden is None)
else lambda x: x
)
self.attention = Attention(
self.hidden, attn_type=attention, attn_func="softmax",
)
self.char_attention = char_attention
if char_attention is not None:
self.char_hidden_att_komp = (
nn.Linear(char_encoder_hidden, hidden, bias=False)
if (char_encoder_hidden != hidden or char_encoder_hidden is None)
else lambda x: x
)
self.char_attention = GlobalAttention(
self.hidden, attn_type=attention, attn_func="softmax"
)
self.proj_layer = nn.Linear(self.hidden * 2, self.embeddings.num_embeddings)
def forward(
self,
input_ids,
lens=None,
initial_state=None,
encoder_hidden=None,
src_lens=None,
character_encoder_hidden=None,
character_lens=None,
):
self.init_state(initial_state, encoder_hidden, src_lens)
input_ids = self.word_dropout(input_ids, lens)
all_logits = []
all_preds = []
for i in range(input_ids.shape[1] - 1):
p = random.random()
input_id = (
all_preds[-1]
if (p <= self.teacher_forcing_p and all_preds and self.training)
else input_ids[:, i]
)
logits, attn = self.generate(
input_id,
encoder_hidden,
src_lens,
character_encoder_hidden,
character_lens,
)
all_logits.append(logits)
pred = torch.argmax(F.softmax(logits, 1), 1)
all_preds.append(pred)
# batch_size, seq_len
all_logits = torch.stack(all_logits, 1).contiguous()
all_preds = torch.stack(all_preds, 1).contiguous()
return all_preds, all_logits
def generate(
self,
input_id,
encoder_hidden=None,
src_lens=None,
character_encoder_hidden=None,
char_lens=None,
):
input = self.embedding_dropout(self.embeddings(input_id))
for i, rnn in enumerate(self.lstm_decoder):
if isinstance(rnn, VDM_LSTMCell):
# vdm lstm cell
hidden, cell = rnn(
input,
(
self.state["hidden"][i],
self.state["cell"][i],
self.latent,
self.context,
),
)
else:
# recurrent cell
hidden, cell = rnn(
input, (self.state["hidden"][i], self.state["cell"][i])
)
# hidden state becomes the input to the next layer
input = self.hidden_state_dropout(hidden)
# save state for next time step
self.state["hidden"][i] = hidden
self.state["cell"][i] = cell
out = hidden
_att = None
if self.attention is not None:
_enc = self.enc_hidden_att_komp(encoder_hidden)
_hidden = hidden
out, _att, self.context = self.attention(_hidden, _enc, src_lens)
if self.char_attention is not None:
_enc = self.char_hidden_att_komp(character_encoder_hidden)
_hidden = hidden
hidden, att = self.char_attention(_hidden, _enc, char_lens)
out = torch.cat([out, hidden], -1)
logits = self.proj_layer(out)
return logits, _att
def init_state(self, initial_state, encoder_hidden=None, src_lens=None):
if initial_state is None:
self.state["hidden"] = [None] * self.num_layers
self.state["cell"] = [None] * self.num_layers
else:
self.state["hidden"] = [
self.encoder_hidden_proj(initial_state)
] * self.num_layers
self.state["cell"] = [
self.encoder_hidden_proj(initial_state)
] * self.num_layers
if self.variational:
self.latent = initial_state # latent_variable
self.context = self.attention(
initial_state, self.enc_hidden_att_komp(encoder_hidden), src_lens
)[2]
def map_state(self, fn):
self.state["hidden"] = [fn(h, 0) for h in self.state["hidden"]]
self.state["cell"] = [fn(c, 0) for c in self.state["cell"]]
if self.variational:
self.latent = fn(self.latent, 0)
self.context = fn(self.context, 0)
def word_dropout(self, input, lens):
if not self.training:
return input
output = []
for inp, _len in zip(input, lens):
word_dropout = Bernoulli(1 - self.word_dropout_p).sample(
inp[1 : _len - 1].shape
)
inp = inp.cpu()
inp[1 : _len - 1] = inp[1 : _len - 1] * word_dropout.type(torch.LongTensor)
inp[1 : _len - 1][inp[1 : _len - 1] == 0] = self.embeddings.unk_idx
inp = inp.cuda()
output.append(inp)
return torch.stack(output, 0).cuda()
class VDM_LSTMCell(nn.Module):
def __init__(self, input_dim, hidden_dim):
super(VDM_LSTMCell, self).__init__()
self.w_i = nn.Linear(input_dim, hidden_dim * 4)
self.w_h = nn.Linear(hidden_dim, hidden_dim * 4)
self.w_z = nn.Linear(hidden_dim, hidden_dim * 4)
self.w_c = nn.Linear(hidden_dim, hidden_dim * 4)
def forward(self, input, hidden):
hx, cx, zx, context_x = hidden
gates = self.w_i(input) + self.w_h(hx) + self.w_z(zx) + self.w_c(context_x)
ingate, forgetgate, cellgate, outgate = gates.chunk(4, 1)
ingate = torch.sigmoid(ingate)
forgetgate = torch.sigmoid(forgetgate)
cellgate = torch.tanh(cellgate)
outgate = torch.sigmoid(outgate)
cy = (forgetgate * cx) + (ingate * cellgate)
hy = outgate * torch.tanh(cy)
return hy, cy
class VDM_GRUCell(nn.Module):
def __init__(self, input_dim, hidden_dim):
super(VDM_LSTMCell, self).__init__()
self.w_i = nn.Linear(input_dim, hidden_dim * 3)
self.w_h = nn.Linear(hidden_dim, hidden_dim * 3)
self.w_z = nn.Linear(hidden_dim, hidden_dim * 3)
self.w_c = nn.Linear(hidden_dim, hidden_dim * 3)
def forward(self, input, hidden):
hx, zx, cx = hidden
gi = self.w_i(input)
gh = self.w_h(hx)
gz = self.w_z(zx)
gc = self.w_c(cx)
i_r, i_i, i_n = gi.chunk(3, 1)
h_r, h_h, h_n = gh.chunk(3, 1)
z_r, z_z, z_n = gz.chunk(3, 1)
c_r, c_c, c_n = gc.chunk(3, 1)
resetgate = torch.sigmoid(i_r + h_r + z_r + c_r)
inputgate = torch.sigmoid(i_i + h_i + z_i + c_i)
newgate = torch.tanh(i_n + (resetgate * h_n) + c_n + z_n)
hy = newgate + inputgate * (hidden - newgate)
return hy, cy
class LSTM_Encoder(nn.Module):
def __init__(
self, embeddings, hidden, num_layers, input_dropout=0.5, output_dropout=0.5,
):
super(LSTM_Encoder, self).__init__()
self.bidirectional = True
self.embed = embeddings
self.hidden = hidden
self.num_layers = num_layers
self.encoder = nn.LSTM(
self.embed.embedding_dim,
self.hidden,
num_layers=self.num_layers,
batch_first=True,
bidirectional=True,
)
self.input_dropout = nn.Dropout(input_dropout)
self.output_dropout = nn.Dropout(output_dropout)
def forward(self, seq, seq_len, initial_state=None):
embedded_seq = self.embed(seq)
embedded_seq = self.input_dropout(embedded_seq)
encoder_input = nn.utils.rnn.pack_padded_sequence(
embedded_seq, seq_len, batch_first=True, enforce_sorted=False
)
if initial_state is not None:
encoder_hidden, (h_0, c_0) = self.encoder(
encoder_input,
(
initial_state.unsqueeze(0).repeat(self.num_layers * 2, 1, 1),
initial_state.unsqueeze(0).repeat(self.num_layers * 2, 1, 1),
),
)
else:
encoder_hidden, (h_0, c_0) = self.encoder(encoder_input)
encoder_hidden, _ = nn.utils.rnn.pad_packed_sequence(
encoder_hidden, batch_first=True
)
encoder_hidden = self.output_dropout(encoder_hidden)
h_0 = self.output_dropout(h_0)
final_hidden = (
torch.cat(
h_0.view(self.num_layers, 2, seq.shape[0], self.hidden)[-1].chunk(2),
-1,
).squeeze(0),
encoder_hidden,
)
return final_hidden, encoder_hidden
class DefinitionProbingLSTM(nn.Module):
def __init__(
self,
encoder,
decoder_hidden,
embeddings,
max_layer=12,
src_pad_idx=0,
encoder_hidden=None,
latent_size=None,
scalar_mix=False,
aggregator="mean",
teacher_forcing_p=0.3,
classification=None,
attentional=False,
definition_encoder=None,
word_dropout_p=None,
decoder_num_layers=2,
):
super(DefinitionProbingLSTM, self).__init__()
self.embeddings = embeddings
self.encoder_hidden = encoder_hidden
self.decoder_hidden = decoder_hidden
self.decoder_num_layers = decoder_num_layers
self.encoder = encoder
self.latent_size = latent_size
self.src_pad_idx = src_pad_idx
self.aggregator = aggregator
self.context_feed_forward = nn.Linear(self.encoder_hidden, self.encoder_hidden)
self.scalar_mix = None
if scalar_mix:
self.scalar_mix = ScalarMix(self.max_layer + 1)
self.global_scorer = GNMTGlobalScorer(
alpha=2, beta=None, length_penalty="avg", coverage_penalty=None
)
self.definition_encoder = LSTM_Encoder(
self.embeddings._def,
self.encoder_hidden,
self.encoder_num_layers,
self.dropout_dict.src,
self.dropout_dict.src,
)
self.context_encoder = LSTM_Encoder(
self.embeddings.src,
self.encoder_hidden,
self.encoder_num_layers,
self.dropout_dict.src,
self.dropout_dict.src,
)
self.decoder = LSTM_Decoder(
embeddings.tgt,
hidden=self.decoder_hidden,
encoder_hidden=self.encoder_hidden,
num_layers=self.decoder_num_layers,
word_dropout=word_dropout_p,
teacher_forcing_p=teacher_forcing_p,
attention="general" if attentional else None,
dropout=DotMap({"input": 0.5, "output": 0.5}),
decoder="VDM" if self.variational else "LSTM",
variational=self.variational,
latent_size=self.latent_size,
)
self.target_kl = 1.0
self.definition_feed_forward = nn.Linear(
self.encoder_hidden, self.encoder_hidden
)
self.mean_layer = nn.Linear(self.latent_size, self.latent_size)
self.logvar_layer = nn.Linear(self.latent_size, self.latent_size)
self.w_z_post = nn.Sequential(
nn.Linear(self.encoder_hidden * 2, self.latent_size), nn.Tanh()
)
self.mean_prime_layer = nn.Linear(self.latent_size, self.latent_size)
self.logvar_prime_layer = nn.Linear(self.latent_size, self.latent_size)
self.w_z_prior = nn.Sequential(
nn.Linear(self.encoder_hidden, self.latent_size), nn.Tanh()
)
self.z_project = nn.Sequential(
nn.Linear(self.latent_size, self.decoder_hidden), nn.Tanh()
)
def forward(
self,
input,
seq_lens,
span_token_ids,
target,
target_lens,
definition=None,
definition_lens=None,
classification_labels=None,
sentence_mask=None,
):
batch_size, tgt_len = target.shape
# (batch_size,seq_len,hidden_size), (batch_size,hidden_size), (num_layers,batch_size,seq_len,hidden_size)
_, last_hidden_layer = self.context_encoder(input, seq_lens, initial_state=None)
definition_representation, _ = self.definition_encoder(
definition, definition_lens, initial_state=None
)
span_ids = self._id_extractor(tokens=span_token_ids, batch=input, lens=seq_lens)
span_representation, hidden_states = self._span_aggregator(
all_hidden_layers if self.scalar_mix is not None else last_hidden_layer,
sequence_mask(seq_lens),
span_ids,
)
span_representation = self.context_feed_forward(span_representation)
definition_representation = self.definition_feed_forward(
definition_representation
)
post_project = self.w_z_post(
torch.cat([span_representation, definition_representation], -1)
)
prior_project = self.w_z_prior(span_representation)
mu = self.mean_layer(post_project)
logvar = self.logvar_layer(post_project)
mu_prime = self.mean_prime_layer(prior_project)
logvar_prime = self.logvar_prime_layer(prior_project)
z = mu + torch.exp(logvar * 0.5) * torch.randn_like(logvar)
span_representation = self.z_project(z)
KLD = kl_divergence(
Normal(mu, torch.exp(logvar * 0.5)),
Normal(mu_prime, torch.exp(logvar_prime * 0.5)),
)
kl_mask = (KLD > (self.target_kl / self.latent_size)).float()
fake_loss_kl = (kl_mask * KLD).sum(dim=1)
predictions, logits = self.decoder(
target, target_lens, span_representation, hidden_states, seq_lens,
)
loss = (
F.cross_entropy(
logits.view(batch_size * (tgt_len - 1), -1),
target[:, 1:].contiguous().view(-1),
ignore_index=self.embeddings.tgt.padding_idx,
reduction="none",
)
.view(batch_size, tgt_len - 1)
.sum(1)
)
perplexity = F.cross_entropy(
logits.view(batch_size * (tgt_len - 1), -1),
target[:, 1:].contiguous().view(-1),
ignore_index=self.embeddings.tgt.padding_idx,
reduction="mean",
).exp()
return DotMap(
{
"predictions": predictions,
"logits": logits,
"loss": loss,
"perplexity": perplexity,
"fake_kl": fake_loss_kl,
"kl": KLD,
"cosine_loss": cosine_loss,
}
)
def _validate(
self,
input,
seq_lens,
span_token_ids,
target,
target_lens,
decode_strategy,
definition=None,
definition_lens=None,
sentence_mask=None,
):
batch_size, tgt_len = target.shape
# (batch_size,seq_len,hidden_size), (batch_size,hidden_size), (num_layers,batch_size,seq_len,hidden_size)
_, last_hidden_layer = self.context_encoder(input, seq_lens, initial_state=None)
definition_representation, _ = self.definition_encoder(
definition, definition_lens, initial_state=None
)
span_ids = self._id_extractor(tokens=span_token_ids, batch=input, lens=seq_lens)
span_representation, hidden_states = self._span_aggregator(
all_hidden_layers if self.scalar_mix is not None else last_hidden_layer,
sequence_mask(seq_lens),
span_ids,
)
span_representation = self.context_feed_forward(span_representation)
definition_representation = self.definition_feed_forward(
definition_representation
)
post_project = self.w_z_post(
torch.cat([span_representation, definition_representation], -1)
)
prior_project = self.w_z_prior(span_representation)
mu = self.mean_layer(post_project)
logvar = self.logvar_layer(post_project)
mu_prime = self.mean_prime_layer(prior_project)
logvar_prime = self.logvar_prime_layer(prior_project)
z = mu + torch.exp(logvar * 0.5) * torch.randn_like(logvar)
span_representation = self.z_project(z)
KLD = (
kl_divergence(
Normal(mu, torch.exp(logvar * 0.5)),
Normal(mu_prime, torch.exp(logvar_prime * 0.5)),
)
.sum(1)
.mean()
)
memory_bank = hidden_states if self.decoder.attention else None
_, logits = self.decoder(
target, target_lens, span_representation, memory_bank, seq_lens,
)
loss = F.cross_entropy(
logits.view(batch_size * (tgt_len - 1), -1),
target[:, 1:].contiguous().view(-1),
ignore_index=self.embeddings.tgt.padding_idx,
)
ppl = loss.exp()
beam_results = self._strategic_decode(
target,
target_lens,
decode_strategy,
memory_bank,
seq_lens,
span_representation,
)
return DotMap(
{
"predictions": beam_results["predictions"],
"logits": logits.view(batch_size * (tgt_len - 1), -1),
"loss": loss,
"perplexity": ppl,
"kl": KLD,
}
)
def _strategic_decode(
self,
target,
target_lens,
decode_strategy,
memory_bank,
memory_lengths,
span_representation,
):
"""Translate a batch of sentences step by step using cache.
Args:
batch: a batch of sentences, yield by data iterator.
src_vocabs (list): list of torchtext.data.Vocab if can_copy.
decode_strategy (DecodeStrategy): A decode strategy to use for
generate translation step by step.
Returns:
results (dict): The translation results.
"""
parallel_paths = decode_strategy.parallel_paths # beam_size
# (0) Prep the components of the search.
# use_src_map = self.copy_attn
batch_size, max_len = target.shape
# Initialize the hidden states
self.decoder.init_state(
span_representation, encoder_hidden=memory_bank, src_lens=memory_lengths
)
results = {
"predictions": None,
"scores": None,
"attention": None,
# "gold_score": self._gold_score(
# batch, memory_bank, src_lengths, src_vocabs, use_src_map,
# enc_states, batch_size, src)
}
# (2) prep decode_strategy. Possibly repeat src objects.
src_map = None # batch.src_map if use_src_map else None
fn_map_state, memory_bank, memory_lengths, src_map = decode_strategy.initialize(
memory_bank, memory_lengths, src_map, device="cuda"
)
if fn_map_state is not None:
self.decoder.map_state(fn_map_state)
# (3) Begin decoding step by step:
for step in range(decode_strategy.max_length):
decoder_input = decode_strategy.current_predictions
logits, attn = self.decoder.generate(
decoder_input, memory_bank, memory_lengths
)
decode_strategy.advance(F.log_softmax(logits, 1), attn)
any_finished = decode_strategy.is_finished.any()
if any_finished:
decode_strategy.update_finished()
if decode_strategy.done:
break
select_indices = decode_strategy.select_indices
if any_finished:
# Reorder states.
if memory_bank is not None:
if isinstance(memory_bank, tuple):
memory_bank = tuple(
x.index_select(0, select_indices) for x in memory_bank
)
else:
memory_bank = memory_bank.index_select(0, select_indices)
memory_lengths = memory_lengths.index_select(0, select_indices)
if src_map is not None:
src_map = src_map.index_select(1, select_indices)
if parallel_paths > 1 or any_finished:
self.decoder.map_state(
lambda state, dim: state.index_select(dim, select_indices)
)
results["scores"] = decode_strategy.scores
results["predictions"] = decode_strategy.predictions
results["attention"] = decode_strategy.attention
# if self.decoder.attention:
# results["alignment"] = self._align_forward(
# batch, decode_strategy.predictions
# )
# else:
# results["alignment"] = [[] for _ in range(batch_size)]
return results
def _span_aggregator(
self, hidden_states, input_mask, span_ids, layer_no: int = None,
):
if layer_no is not None:
hidden_states = hidden_states[layer_no]
if isinstance(hidden_states, tuple):
hidden_states = hidden_states[: self.max_layer + 1]
hidden_states = self.scalar_mix(hidden_states, mask=input_mask)
if self.aggregator == "span":
span = self.span_extractor(hidden_states, span_ids).squeeze(
1
) # As we will only be extracting one span per sequence
elif self.aggregator == "mean":
extracted_embeddings, span_mask = batched_span_select(
hidden_states, span_ids
)
extracted_embeddings = (
extracted_embeddings * span_mask.type(torch.float).unsqueeze(-1)
).squeeze(1)
lengths = (span_mask == True).sum(-1) + 1e-20 # To avoid zero division
span = extracted_embeddings.sum(1) / lengths
return span, hidden_states
| 36.012121
| 123
| 0.577848
| 4,675
| 41,594
| 4.850053
| 0.072727
| 0.035547
| 0.017289
| 0.015877
| 0.759196
| 0.737938
| 0.716503
| 0.705125
| 0.70045
| 0.682147
| 0
| 0.008021
| 0.334567
| 41,594
| 1,154
| 124
| 36.043328
| 0.811186
| 0.064769
| 0
| 0.619147
| 0
| 0
| 0.013519
| 0
| 0
| 0
| 0
| 0.000867
| 0
| 1
| 0.023933
| false
| 0
| 0.016649
| 0
| 0.063476
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 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
|
0
| 5
|
a2d8a3567aeb5c5cd27f8a611172d3a45939be44
| 371
|
py
|
Python
|
terra_sdk/core/distribution/__init__.py
|
CryptologyExchange/terra.py
|
8710ebf7c8129ec4f14e4be2e3b5b6bb77ea03e5
|
[
"MIT"
] | null | null | null |
terra_sdk/core/distribution/__init__.py
|
CryptologyExchange/terra.py
|
8710ebf7c8129ec4f14e4be2e3b5b6bb77ea03e5
|
[
"MIT"
] | null | null | null |
terra_sdk/core/distribution/__init__.py
|
CryptologyExchange/terra.py
|
8710ebf7c8129ec4f14e4be2e3b5b6bb77ea03e5
|
[
"MIT"
] | null | null | null |
from .msgs import (MsgFundCommunityPool, MsgSetWithdrawAddress,
MsgWithdrawDelegatorReward, MsgWithdrawValidatorCommission)
from .proposals import CommunityPoolSpendProposal
__all__ = [
"MsgFundCommunityPool",
"MsgSetWithdrawAddress",
"MsgWithdrawDelegatorReward",
"MsgWithdrawValidatorCommission",
"CommunityPoolSpendProposal",
]
| 30.916667
| 78
| 0.770889
| 17
| 371
| 16.588235
| 0.588235
| 0.29078
| 0.475177
| 0.687943
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.161725
| 371
| 11
| 79
| 33.727273
| 0.906752
| 0
| 0
| 0
| 0
| 0
| 0.331536
| 0.277628
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.2
| 0
| 0.2
| 0
| 1
| 0
| 1
| null | 1
| 1
| 1
| 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
|
0
| 5
|
a2ebcdd98b759e0c3016b3af6fbb1f763d50ed83
| 62
|
py
|
Python
|
regexp/__init__.py
|
Julien00859/regexp
|
4c08e643b7cf9c5db2919b6d96d864d4501a6560
|
[
"MIT"
] | 7
|
2019-06-12T19:48:07.000Z
|
2021-11-18T04:33:18.000Z
|
regexp/__init__.py
|
Julien00859/regexp
|
4c08e643b7cf9c5db2919b6d96d864d4501a6560
|
[
"MIT"
] | 1
|
2020-06-27T02:47:33.000Z
|
2020-06-30T09:43:24.000Z
|
regexp/__init__.py
|
Julien00859/regexp
|
4c08e643b7cf9c5db2919b6d96d864d4501a6560
|
[
"MIT"
] | 1
|
2020-01-09T23:34:25.000Z
|
2020-01-09T23:34:25.000Z
|
from .compile import compile
from .pattern import IGNORE_CASE
| 20.666667
| 32
| 0.83871
| 9
| 62
| 5.666667
| 0.666667
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.129032
| 62
| 2
| 33
| 31
| 0.944444
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
0c47f12f1458d181a2e6a191cd6f10031bf3de8e
| 59
|
py
|
Python
|
python/__init__.py
|
RECCAP2-ocean/scripts
|
a8af6552f025d0b698787de2e4abf0a76559aab2
|
[
"MIT"
] | null | null | null |
python/__init__.py
|
RECCAP2-ocean/scripts
|
a8af6552f025d0b698787de2e4abf0a76559aab2
|
[
"MIT"
] | 1
|
2022-03-18T16:58:40.000Z
|
2022-03-18T16:58:40.000Z
|
python/__init__.py
|
RECCAP2-ocean/scripts
|
a8af6552f025d0b698787de2e4abf0a76559aab2
|
[
"MIT"
] | 2
|
2022-03-04T09:03:46.000Z
|
2022-03-11T10:07:34.000Z
|
from . import viz
from . import data
from . import analysis
| 19.666667
| 22
| 0.762712
| 9
| 59
| 5
| 0.555556
| 0.666667
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.186441
| 59
| 3
| 22
| 19.666667
| 0.9375
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 5
|
0c4ac05bcd71ed3c0843c06a8ace1b0645f98c69
| 127
|
py
|
Python
|
classification/loader/__init__.py
|
GT-RIPL/UNO-IC
|
6a95f2c6bc52ad80bfb1da53fd046a3d4db310d0
|
[
"MIT"
] | 24
|
2020-11-11T03:49:50.000Z
|
2022-03-21T04:23:32.000Z
|
classification/loader/__init__.py
|
GT-RIPL/UNO-IC
|
6a95f2c6bc52ad80bfb1da53fd046a3d4db310d0
|
[
"MIT"
] | 1
|
2021-07-15T02:46:34.000Z
|
2021-07-15T02:46:34.000Z
|
classification/loader/__init__.py
|
GT-RIPL/UNO-IC
|
6a95f2c6bc52ad80bfb1da53fd046a3d4db310d0
|
[
"MIT"
] | 2
|
2021-02-04T01:28:19.000Z
|
2021-02-25T09:20:27.000Z
|
from loader.LT_loader import LT_Loader
def get_loader(name,**kargs):
return {
"place365": LT_Loader,
}[name]
| 15.875
| 38
| 0.653543
| 17
| 127
| 4.647059
| 0.588235
| 0.303797
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.030612
| 0.228346
| 127
| 7
| 39
| 18.142857
| 0.77551
| 0
| 0
| 0
| 0
| 0
| 0.062992
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.2
| false
| 0
| 0.2
| 0.2
| 0.6
| 0
| 1
| 0
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
|
0
| 5
|
a75b42855b632e050325c9d3517891cb094d086f
| 46
|
py
|
Python
|
pynma/__init__.py
|
AndreasDerFuchs/pynma
|
668634f4d37107efa27fe23e3b281fe3e3402e18
|
[
"MIT",
"Unlicense"
] | 13
|
2015-03-12T10:26:57.000Z
|
2021-08-03T15:34:42.000Z
|
pynma/__init__.py
|
AndreasDerFuchs/pynma
|
668634f4d37107efa27fe23e3b281fe3e3402e18
|
[
"MIT",
"Unlicense"
] | 3
|
2015-03-02T03:00:05.000Z
|
2018-10-15T06:01:18.000Z
|
pynma/__init__.py
|
AndreasDerFuchs/pynma
|
668634f4d37107efa27fe23e3b281fe3e3402e18
|
[
"MIT",
"Unlicense"
] | 7
|
2015-02-18T06:57:43.000Z
|
2021-08-03T15:34:44.000Z
|
#!/usr/bin/python
from .pynma import PyNMA
| 9.2
| 25
| 0.695652
| 7
| 46
| 4.571429
| 0.857143
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.173913
| 46
| 4
| 26
| 11.5
| 0.842105
| 0.347826
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 5
|
a75f5fa192db200d9c57dcdfe03e96a07d84ac3f
| 148
|
py
|
Python
|
txweb/lib/errors/__init__.py
|
devdave/txWeb
|
e447fbefd16134cb2f83323c04c20c41638d7da3
|
[
"MIT"
] | null | null | null |
txweb/lib/errors/__init__.py
|
devdave/txWeb
|
e447fbefd16134cb2f83323c04c20c41638d7da3
|
[
"MIT"
] | 4
|
2020-11-03T19:59:05.000Z
|
2021-06-02T03:22:25.000Z
|
txweb/lib/errors/__init__.py
|
devdave/txWeb
|
e447fbefd16134cb2f83323c04c20c41638d7da3
|
[
"MIT"
] | null | null | null |
"""
Error handlers for txweb
"""
from twisted.python.failure import Failure
from .default import DefaultHandler
from .debug import DebugHandler
| 21.142857
| 42
| 0.783784
| 18
| 148
| 6.444444
| 0.722222
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.148649
| 148
| 6
| 43
| 24.666667
| 0.920635
| 0.162162
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
a7620b64186f8a6da006530ca38d9205558cbbd0
| 90
|
py
|
Python
|
src/examplepackage/cli.py
|
rasmuse/python-package
|
f2ae40b71ac124eb6fd8bf71461c84ada8ea68e6
|
[
"MIT"
] | null | null | null |
src/examplepackage/cli.py
|
rasmuse/python-package
|
f2ae40b71ac124eb6fd8bf71461c84ada8ea68e6
|
[
"MIT"
] | null | null | null |
src/examplepackage/cli.py
|
rasmuse/python-package
|
f2ae40b71ac124eb6fd8bf71461c84ada8ea68e6
|
[
"MIT"
] | null | null | null |
import click
from .core import func
@click.command()
def main():
click.echo(func())
| 11.25
| 22
| 0.677778
| 13
| 90
| 4.692308
| 0.692308
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.177778
| 90
| 7
| 23
| 12.857143
| 0.824324
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.2
| true
| 0
| 0.4
| 0
| 0.6
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
a76cdfa778bca461dee31374a0e3d21549b9b261
| 288
|
py
|
Python
|
pos/admin.py
|
dushmshr/A
|
b8957c965370c0284ddf727a2938452acf7876e3
|
[
"Apache-2.0"
] | null | null | null |
pos/admin.py
|
dushmshr/A
|
b8957c965370c0284ddf727a2938452acf7876e3
|
[
"Apache-2.0"
] | 9
|
2020-03-24T15:35:03.000Z
|
2021-09-07T23:46:59.000Z
|
pos/admin.py
|
dushmshr/A
|
b8957c965370c0284ddf727a2938452acf7876e3
|
[
"Apache-2.0"
] | null | null | null |
from django.contrib import admin
from .models import Product, Cash, Order,ProductAdmin,Order_Item,Order_ItemAdmin
# Register your models here.
admin.site.register(Product,ProductAdmin)
admin.site.register(Cash)
admin.site.register(Order)
admin.site.register(Order_Item,Order_ItemAdmin)
| 28.8
| 80
| 0.833333
| 40
| 288
| 5.9
| 0.4
| 0.152542
| 0.288136
| 0.194915
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.072917
| 288
| 9
| 81
| 32
| 0.883895
| 0.090278
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.333333
| 0
| 0.333333
| 0
| 0
| 0
| 0
| null | 0
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 5
|
a7842fd495f97c0b9bd1238bc0ec8fab7ecdf916
| 39
|
py
|
Python
|
ubscrape/__main__.py
|
samuelstevens/pud
|
4d899fb55f25aea2d882fe3eb0136186e6ff411a
|
[
"MIT"
] | 6
|
2019-10-03T19:20:18.000Z
|
2021-01-30T00:49:36.000Z
|
ubscrape/__main__.py
|
samuelstevens/pud
|
4d899fb55f25aea2d882fe3eb0136186e6ff411a
|
[
"MIT"
] | 1
|
2021-06-02T00:23:20.000Z
|
2021-06-02T00:23:20.000Z
|
ubscrape/__main__.py
|
samuelstevens/pud
|
4d899fb55f25aea2d882fe3eb0136186e6ff411a
|
[
"MIT"
] | 3
|
2020-01-08T01:07:15.000Z
|
2020-01-25T17:02:12.000Z
|
from .command_line import main
main()
| 9.75
| 30
| 0.769231
| 6
| 39
| 4.833333
| 0.833333
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.153846
| 39
| 3
| 31
| 13
| 0.878788
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.5
| 0
| 0.5
| 0
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 5
|
a78962c23c1788724f6294523bdb55d8d252a03e
| 37
|
py
|
Python
|
queue_map_reduce/__init__.py
|
cherenkov-plenoscope/sun_grid_engine_map
|
79c933c5acbaaa0c34e1cc9659faa1f28e9d6470
|
[
"MIT"
] | null | null | null |
queue_map_reduce/__init__.py
|
cherenkov-plenoscope/sun_grid_engine_map
|
79c933c5acbaaa0c34e1cc9659faa1f28e9d6470
|
[
"MIT"
] | null | null | null |
queue_map_reduce/__init__.py
|
cherenkov-plenoscope/sun_grid_engine_map
|
79c933c5acbaaa0c34e1cc9659faa1f28e9d6470
|
[
"MIT"
] | null | null | null |
from .tools import map_reduce as map
| 18.5
| 36
| 0.810811
| 7
| 37
| 4.142857
| 0.857143
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.162162
| 37
| 1
| 37
| 37
| 0.935484
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 5
|
a793376d24e0e0398381088acccd90fa9c524794
| 951
|
py
|
Python
|
setup.py
|
RealCreepi/vowing
|
afcffc09421f0a0f31dc7a7c4138a0b06a141be8
|
[
"MIT"
] | 4
|
2021-03-30T17:10:32.000Z
|
2022-01-16T07:47:42.000Z
|
setup.py
|
RealCreepi/vowing
|
afcffc09421f0a0f31dc7a7c4138a0b06a141be8
|
[
"MIT"
] | null | null | null |
setup.py
|
RealCreepi/vowing
|
afcffc09421f0a0f31dc7a7c4138a0b06a141be8
|
[
"MIT"
] | null | null | null |
from distutils.core import setup
setup(
name = 'vowing',
packages = ['vowing'],
version = '0.3.5',
license = 'MIT',
description = "'Vowing' is an alternative to Python's built in async/await system that has been inspired by Javascript's Promise.",
author = 'Creepi',
url = 'https://github.com/RealCreepi/vowing',
keywords = ['async', 'threading', 'vowing', 'promise', 'javascript'],
classifiers=[
'Development Status :: 4 - Beta',
'Intended Audience :: Developers',
'Topic :: Software Development',
'License :: OSI Approved :: MIT License',
'Programming Language :: Python :: 3',
'Programming Language :: Python :: 3.4',
'Programming Language :: Python :: 3.5',
'Programming Language :: Python :: 3.6',
'Programming Language :: Python :: 3.7',
'Programming Language :: Python :: 3.8',
'Programming Language :: Python :: 3.9',
'Programming Language :: Python :: 3.10'
],
)
| 33.964286
| 133
| 0.62776
| 106
| 951
| 5.632075
| 0.575472
| 0.254606
| 0.335008
| 0.348409
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.026631
| 0.210305
| 951
| 28
| 134
| 33.964286
| 0.768309
| 0
| 0
| 0
| 0
| 0.04
| 0.668067
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.04
| 0
| 0.04
| 0
| 0
| 0
| 0
| null | 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
|
0
| 5
|
a7aad828e94f8b09a6d53c41ceef0261c9cc4705
| 87
|
py
|
Python
|
AUG16/10.py
|
Razdeep/PythonSnippets
|
76f9313894f511c487a99bc38bdf0fe5e594caf5
|
[
"MIT"
] | null | null | null |
AUG16/10.py
|
Razdeep/PythonSnippets
|
76f9313894f511c487a99bc38bdf0fe5e594caf5
|
[
"MIT"
] | null | null | null |
AUG16/10.py
|
Razdeep/PythonSnippets
|
76f9313894f511c487a99bc38bdf0fe5e594caf5
|
[
"MIT"
] | null | null | null |
# greatest of three
def greatest(a,b,c):
return max(a,b,c)
print(greatest(2,4,3))
| 14.5
| 22
| 0.655172
| 18
| 87
| 3.166667
| 0.722222
| 0.070175
| 0.105263
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.041096
| 0.16092
| 87
| 6
| 22
| 14.5
| 0.739726
| 0.195402
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.333333
| false
| 0
| 0
| 0.333333
| 0.666667
| 0.333333
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 1
| 0
|
0
| 5
|
a7b76da5b92ce078dded119047a650cdf72fb8da
| 138
|
py
|
Python
|
src/search/admin.py
|
papeclem/Rifa-public
|
7cd32656b73a6bcc7f5b309fbe025fe7d76c12b8
|
[
"MIT"
] | 1
|
2021-09-06T12:53:37.000Z
|
2021-09-06T12:53:37.000Z
|
src/search/admin.py
|
papeclem/Rifa-public
|
7cd32656b73a6bcc7f5b309fbe025fe7d76c12b8
|
[
"MIT"
] | null | null | null |
src/search/admin.py
|
papeclem/Rifa-public
|
7cd32656b73a6bcc7f5b309fbe025fe7d76c12b8
|
[
"MIT"
] | null | null | null |
from django.contrib import admin
from search.models import Product, Category
admin.site.register(Product)
admin.site.register(Category)
| 19.714286
| 43
| 0.826087
| 19
| 138
| 6
| 0.578947
| 0.157895
| 0.298246
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.094203
| 138
| 6
| 44
| 23
| 0.912
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.5
| 0
| 0.5
| 0
| 1
| 0
| 0
| null | 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 5
|
a7ca1866c248fc05bc77d9e962533142ad7d4e1b
| 261
|
py
|
Python
|
lib/gsiLib/gsiHelper.py
|
sumedhpb/TAF
|
fc6f4cb8dc0b8234393f2e52a7b4a1aa723d9449
|
[
"Apache-2.0"
] | 9
|
2019-02-19T05:55:00.000Z
|
2022-01-20T10:37:28.000Z
|
lib/gsiLib/gsiHelper.py
|
sumedhpb/TAF
|
fc6f4cb8dc0b8234393f2e52a7b4a1aa723d9449
|
[
"Apache-2.0"
] | 2
|
2019-02-19T07:28:54.000Z
|
2019-06-18T11:22:29.000Z
|
lib/gsiLib/gsiHelper.py
|
sumedhpb/TAF
|
fc6f4cb8dc0b8234393f2e52a7b4a1aa723d9449
|
[
"Apache-2.0"
] | 155
|
2018-11-13T14:57:07.000Z
|
2022-03-28T11:53:22.000Z
|
import mode
if mode.java:
# from GsiHelper_JavaSDK import GsiHelper as GsiLib
pass
elif mode.cli:
# from GsiHelper_CLI import GsiHelper as GsiLib
pass
else:
from GsiHelper_Rest import GsiHelper as GsiLib
class GsiHelper(GsiLib):
pass
| 17.4
| 55
| 0.735632
| 36
| 261
| 5.25
| 0.416667
| 0.206349
| 0.269841
| 0.365079
| 0.285714
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.226054
| 261
| 14
| 56
| 18.642857
| 0.935644
| 0.363985
| 0
| 0.333333
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0.333333
| 0.222222
| 0
| 0.333333
| 0
| 0
| 0
| 0
| null | 1
| 1
| 1
| 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
| 1
| 1
| 0
| 0
| 0
| 0
|
0
| 5
|
ac0611edc99335395e3e812bfcf77c9b87b4da53
| 95
|
py
|
Python
|
api/users/admin.py
|
fujikawahiroaki/webspecimanager
|
d46a4feec0c695d5231b21e3311f4adbe25435cb
|
[
"BSD-2-Clause"
] | null | null | null |
api/users/admin.py
|
fujikawahiroaki/webspecimanager
|
d46a4feec0c695d5231b21e3311f4adbe25435cb
|
[
"BSD-2-Clause"
] | 10
|
2020-12-07T08:54:30.000Z
|
2022-03-13T12:23:03.000Z
|
api/users/admin.py
|
fujikawahiroaki/webspecimanager
|
d46a4feec0c695d5231b21e3311f4adbe25435cb
|
[
"BSD-2-Clause"
] | null | null | null |
from django.contrib import admin
from .models import UserProfile
admin.register(UserProfile)
| 15.833333
| 32
| 0.831579
| 12
| 95
| 6.583333
| 0.666667
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.115789
| 95
| 5
| 33
| 19
| 0.940476
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.666667
| 0
| 0.666667
| 0
| 1
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| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
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| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
ac4cf970e4a9f2d8b9917641ead3f7242f309f6b
| 21
|
py
|
Python
|
stream/__init__.py
|
wishful-project/stream_pipe
|
025e91d005bead0e77a5089b74d9bb003821ebf2
|
[
"MIT"
] | null | null | null |
stream/__init__.py
|
wishful-project/stream_pipe
|
025e91d005bead0e77a5089b74d9bb003821ebf2
|
[
"MIT"
] | null | null | null |
stream/__init__.py
|
wishful-project/stream_pipe
|
025e91d005bead0e77a5089b74d9bb003821ebf2
|
[
"MIT"
] | null | null | null |
from .stream import *
| 21
| 21
| 0.761905
| 3
| 21
| 5.333333
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.142857
| 21
| 1
| 21
| 21
| 0.888889
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 5
|
ac6e6c29fe2b2a8244c7e064010a05bc31e37756
| 46
|
py
|
Python
|
client/exceptions.py
|
camerongray1515/Chaac
|
532b3b4d13cca1bdd3ea11a3b0da59d800480117
|
[
"MIT"
] | null | null | null |
client/exceptions.py
|
camerongray1515/Chaac
|
532b3b4d13cca1bdd3ea11a3b0da59d800480117
|
[
"MIT"
] | null | null | null |
client/exceptions.py
|
camerongray1515/Chaac
|
532b3b4d13cca1bdd3ea11a3b0da59d800480117
|
[
"MIT"
] | null | null | null |
class InvalidPluginError(Exception):
pass
| 15.333333
| 36
| 0.782609
| 4
| 46
| 9
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.152174
| 46
| 2
| 37
| 23
| 0.923077
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0.5
| 0
| 0
| 0.5
| 0
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| 0
| 0
| 0
|
0
| 5
|
ac7772c8e42991ed5d0f226e26efe234ae3060cd
| 194
|
py
|
Python
|
LeetCode/01_Easy/lc_231.py
|
Zubieta/CPP
|
fb4a3cbf2e4edcc590df15663cd28fb9ecab679c
|
[
"MIT"
] | 8
|
2017-03-02T07:56:45.000Z
|
2021-08-07T20:20:19.000Z
|
LeetCode/01_Easy/lc_231.py
|
zubie7a/Algorithms
|
fb4a3cbf2e4edcc590df15663cd28fb9ecab679c
|
[
"MIT"
] | null | null | null |
LeetCode/01_Easy/lc_231.py
|
zubie7a/Algorithms
|
fb4a3cbf2e4edcc590df15663cd28fb9ecab679c
|
[
"MIT"
] | 1
|
2021-08-07T20:20:20.000Z
|
2021-08-07T20:20:20.000Z
|
# 231 - Power Of Two (Easy)
# https://leetcode.com/problems/power-of-two/submissions/
class Solution:
def isPowerOfTwo(self, n: int) -> bool:
return n and (n & (n-1)) == 0
| 24.25
| 57
| 0.597938
| 28
| 194
| 4.142857
| 0.785714
| 0.12069
| 0.172414
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.034014
| 0.242268
| 194
| 7
| 58
| 27.714286
| 0.755102
| 0.417526
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.333333
| false
| 0
| 0
| 0.333333
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 1
| 0
|
0
| 5
|
3bbcfecf3128c86e18c7274ce769d2d131525629
| 6,251
|
py
|
Python
|
bigflow_python/python/bigflow/test/schema_split_string_to_types_test.py
|
advancedxy/bigflow_python
|
8a244b483404fde7afc42eee98bc964da8ae03e2
|
[
"Apache-2.0"
] | 1,236
|
2017-11-14T11:10:10.000Z
|
2022-03-08T11:54:41.000Z
|
bigflow_python/python/bigflow/test/schema_split_string_to_types_test.py
|
advancedxy/bigflow_python
|
8a244b483404fde7afc42eee98bc964da8ae03e2
|
[
"Apache-2.0"
] | 38
|
2017-11-14T16:29:12.000Z
|
2020-01-23T08:32:04.000Z
|
bigflow_python/python/bigflow/test/schema_split_string_to_types_test.py
|
advancedxy/bigflow_python
|
8a244b483404fde7afc42eee98bc964da8ae03e2
|
[
"Apache-2.0"
] | 184
|
2017-11-27T07:23:36.000Z
|
2022-03-14T02:54:16.000Z
|
#!/usr/bin/env python
# -*- coding: utf-8 -*-
########################################################################
#
# Copyright (c) 2016 Baidu, 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 agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
########################################################################
"""
"""
import unittest
from bigflow import base
from bigflow import input
from bigflow import output
from bigflow import schema
from bigflow import transforms
from bigflow.test import test_base
class TestSchemaSplitStringToTypes(test_base.PipelineBasedTest):
def test_split_string_to_types(self):
"""
replace python split string to types function with
cpp implementation.
"""
# "|a|b||c|d||e|f||" => ("", "a", "b", "", "c", "d", "", "e", "f", "", "")
input_path = "./testdata/input_schema_split_string_to_types_2.txt"
data = self._pipeline.read(input.SchemaTextFile(input_path, columns=11, separator="|"))
result = data.get()[0]
except_data = ("", "a", "b", "", "c", "d", "", "e", "f", "", "")
self.assertEqual(result, except_data)
# columns is list with fileds name
input_path = "./testdata/input_schema_split_string_to_types.txt"
data = self._pipeline.read(input.SchemaTextFile(input_path,
columns = ["name", "age", "height"], separator = "|"))
result = data.get()
except_data = [
{'age': '15', 'name': 'xiaoming', 'height': '170'},
{'age': '16', 'name': 'xiaohong', 'height': '175'}
]
self.assertEqual(sorted(result), sorted(except_data))
# columns is list with fields name and fields type
data = self._pipeline.read(input.SchemaTextFile(input_path,
columns = [("name", str), ("age", int), ("height", int)], separator = "|"))
result = data.get()
except_data = [
{'age': 15, 'name': 'xiaoming', 'height': 170},
{'age': 16, 'name': 'xiaohong', 'height': 175}
]
self.assertEqual(sorted(result), sorted(except_data))
# columns is integer equal to the count of fields
data = self._pipeline.read(input.SchemaTextFile(input_path,
columns = 3, separator = "|"))
result = data.get()
except_data = [
('xiaoming', '15', '170'),
('xiaohong', '16', '175'),
]
self.assertEqual(sorted(result), sorted(except_data))
def test_split_string_to_types_ignore_overflow(self):
"""
replace python split string to types function with
cpp implementation with ignore overflow.
"""
# columns is list with fileds name
input_path = "./testdata/input_schema_split_string_to_types_ignore_overflow.txt"
data = self._pipeline.read(input.SchemaTextFile(input_path,
columns = ["name", "age"], separator = "|", ignore_overflow = True))
result = data.get()
except_data = [
{'age': '15', 'name': 'xiaoming'},
{'age': '16', 'name': 'xiaohong'}
]
self.assertEqual(sorted(result), sorted(except_data))
# columns is list with fields name and fields type
data = self._pipeline.read(input.SchemaTextFile(input_path,
columns = [("name", str), ("age", int)], separator = "|",
ignore_overflow = True))
result = data.get()
except_data = [
{'age': 15, 'name': 'xiaoming'},
{'age': 16, 'name': 'xiaohong'}
]
self.assertEqual(sorted(result), sorted(except_data))
# columns is integer equal to the count of fields
data = self._pipeline.read(input.SchemaTextFile(input_path,
columns = 2, separator = "|", ignore_overflow = True))
result = data.get()
except_data = [
('xiaoming', '15'),
('xiaohong', '16'),
]
self.assertEqual(sorted(result), sorted(except_data))
def test_split_string_to_types_ignore_illegal_line(self):
"""
replace python split string to types function with
cpp implementation with ignore illegal line.
"""
# columns is list with fileds name
input_path = "./testdata/input_schema_split_string_to_types_ignore_illegal_line.txt"
data = self._pipeline.read(input.SchemaTextFile(input_path,
columns = ["name", "age", "height"], separator = "|",
ignore_illegal_line = True))
result = data.get()
except_data = [
{'age': '15', 'name': 'xiaoming', 'height': '170'},
{'age': '16', 'name': 'xiaohong', 'height': '175'}
]
self.assertEqual(sorted(result), sorted(except_data))
# columns is list with fields name and fields type
data = self._pipeline.read(input.SchemaTextFile(input_path,
columns = [("name", str), ("age", int), ("height", int)], separator = "|",
ignore_illegal_line = True))
result = data.get()
except_data = [
{'age': 15, 'name': 'xiaoming', 'height': 170},
{'age': 16, 'name': 'xiaohong', 'height': 175}
]
self.assertEqual(sorted(result), sorted(except_data))
# columns is integer equal to the count of fields
data = self._pipeline.read(input.SchemaTextFile(input_path,
columns = 3, separator = "|", ignore_illegal_line = True))
result = data.get()
except_data = [
('xiaoming', '15', '170'),
('xiaohong', '16', '175'),
]
self.assertEqual(sorted(result), sorted(except_data))
if __name__ == "__main__":
unittest.main()
| 39.563291
| 95
| 0.571908
| 686
| 6,251
| 5.056851
| 0.204082
| 0.057654
| 0.037475
| 0.051888
| 0.767656
| 0.767656
| 0.747766
| 0.741424
| 0.738541
| 0.710868
| 0
| 0.019218
| 0.267477
| 6,251
| 157
| 96
| 39.815287
| 0.738371
| 0.214046
| 0
| 0.520833
| 0
| 0
| 0.139535
| 0.050388
| 0
| 0
| 0
| 0
| 0.104167
| 1
| 0.03125
| false
| 0
| 0.072917
| 0
| 0.114583
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 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
|
0
| 5
|
3bc39833534f5d9317c9e37e71a0c320faadd4c1
| 144
|
py
|
Python
|
inplace_abn/__init__.py
|
karolmajek/inplace_abn
|
2531acf1dd7a1e7b064cedb6e3f14caf7e4e31f5
|
[
"BSD-3-Clause"
] | 1
|
2022-03-09T14:36:43.000Z
|
2022-03-09T14:36:43.000Z
|
inplace_abn/__init__.py
|
karolmajek/inplace_abn
|
2531acf1dd7a1e7b064cedb6e3f14caf7e4e31f5
|
[
"BSD-3-Clause"
] | null | null | null |
inplace_abn/__init__.py
|
karolmajek/inplace_abn
|
2531acf1dd7a1e7b064cedb6e3f14caf7e4e31f5
|
[
"BSD-3-Clause"
] | null | null | null |
from ._version import version as __version__
from .abn import ABN, InPlaceABN, InPlaceABNSync
from .group import active_group, set_active_group
| 36
| 49
| 0.840278
| 20
| 144
| 5.65
| 0.5
| 0.19469
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.118056
| 144
| 3
| 50
| 48
| 0.889764
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
3bce36da3e2d78db75eee3178bb7a72ca0a7e345
| 44
|
py
|
Python
|
disney/__init__.py
|
truthiswill/wait4disney
|
39375ba535c5ca06aaf296a79ec342dd26f59669
|
[
"Apache-2.0"
] | 106
|
2017-04-13T02:44:46.000Z
|
2022-01-26T06:46:27.000Z
|
disney/__init__.py
|
truthiswill/wait4disney
|
39375ba535c5ca06aaf296a79ec342dd26f59669
|
[
"Apache-2.0"
] | 8
|
2018-04-20T04:49:24.000Z
|
2021-12-22T03:04:29.000Z
|
disney/__init__.py
|
truthiswill/wait4disney
|
39375ba535c5ca06aaf296a79ec342dd26f59669
|
[
"Apache-2.0"
] | 20
|
2016-09-07T08:38:25.000Z
|
2021-11-30T04:11:25.000Z
|
from disney import log
log.setup_logging()
| 11
| 22
| 0.795455
| 7
| 44
| 4.857143
| 0.857143
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.136364
| 44
| 3
| 23
| 14.666667
| 0.894737
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.5
| 0
| 0.5
| 0
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 5
|
ce04fdd7370bf061dbecd267de68a4689d9b2d21
| 4,838
|
py
|
Python
|
tests/test_dynamodb_progress.py
|
mapbox/watchbot-progress-py
|
b9658db6d2bb5588e05b6d4e2d48baf88809e68d
|
[
"MIT"
] | 1
|
2018-06-20T21:07:37.000Z
|
2018-06-20T21:07:37.000Z
|
tests/test_dynamodb_progress.py
|
mapbox/watchbot-progress-py
|
b9658db6d2bb5588e05b6d4e2d48baf88809e68d
|
[
"MIT"
] | 17
|
2017-07-25T23:34:57.000Z
|
2018-12-07T17:13:09.000Z
|
tests/test_dynamodb_progress.py
|
mapbox/watchbot-progress-py
|
b9658db6d2bb5588e05b6d4e2d48baf88809e68d
|
[
"MIT"
] | 3
|
2017-11-18T11:09:46.000Z
|
2021-02-23T10:32:35.000Z
|
from mock import patch
import pytest
from watchbot_progress.backends.dynamodb import DynamoProgress as WatchbotProgress
from watchbot_progress.errors import JobDoesNotExist
parts = [
{'source': 'a.tif'},
{'source': 'b.tif'},
{'source': 'c.tif'}]
@patch('watchbot_progress.backends.dynamodb.boto3.resource')
def test_status(client, monkeypatch):
monkeypatch.setenv('WorkTopic', 'abc123')
monkeypatch.setenv('ProgressTable', 'arn::table/foo')
item = {'Item': {'total': 4, 'error': True}}
client.return_value.Table.return_value.get_item.return_value = item
s = WatchbotProgress().status('123')
assert s['failed']
item = {'Item': {'total': 4, 'metadata': True}}
client.return_value.Table.return_value.get_item.return_value = item
s = WatchbotProgress().status('123')
assert s['metadata']
item = {'Item': {'total': 4, 'reduceSent': True}}
client.return_value.Table.return_value.get_item.return_value = item
s = WatchbotProgress().status('123')
assert s['reduceSent']
@patch('watchbot_progress.backends.dynamodb.boto3.resource')
@pytest.mark.parametrize('mock_item, expected', [
({'Item': {'parts': [0, 1, 2, 3], 'total': 4}}, 0),
({'Item': {'parts': [2, 3], 'total': 4}}, 0.5),
({'Item': {'parts': [], 'total': 4}}, 1),
({'Item': {'total': 4}}, 1)
])
def test_status_progress(client, mock_item, expected, monkeypatch):
monkeypatch.setenv('WorkTopic', 'abc123')
monkeypatch.setenv('ProgressTable', 'arn::table/foo')
client.return_value.Table.return_value.get_item.return_value = mock_item
s = WatchbotProgress().status('123')
assert s['progress'] == expected
@patch('watchbot_progress.backends.dynamodb.boto3.resource')
def test_set_total(client, monkeypatch):
monkeypatch.setenv('WorkTopic', 'abc123')
monkeypatch.setenv('ProgressTable', 'arn::table/foo')
client.return_value.Table.return_value.update_item.return_value = None
WatchbotProgress().set_total('123', parts)
@patch('watchbot_progress.backends.dynamodb.boto3.resource')
def test_fail_job(client, monkeypatch):
monkeypatch.setenv('WorkTopic', 'abc123')
monkeypatch.setenv('ProgressTable', 'arn::table/foo')
client.return_value.Table.return_value.update_item.return_value = None
WatchbotProgress().fail_job('123', 'Failed because it is bad')
@patch('watchbot_progress.backends.dynamodb.boto3.resource')
def test_complete_part(client, monkeypatch):
monkeypatch.setenv('WorkTopic', 'abc123')
monkeypatch.setenv('ProgressTable', 'arn::table/foo')
item = {'Attributes': {'parts': [], 'total': 4}}
client.return_value.Table.return_value.update_item.return_value = item
s = WatchbotProgress().complete_part('123', 1)
assert s is True
@patch('watchbot_progress.backends.dynamodb.boto3.resource')
def test_incomplete_part(client, monkeypatch):
monkeypatch.setenv('WorkTopic', 'abc123')
monkeypatch.setenv('ProgressTable', 'arn::table/foo')
item = {'Attributes': {'parts': [1, 2], 'total': 4}}
client.return_value.Table.return_value.update_item.return_value = item
s = WatchbotProgress().complete_part('123', 1)
assert s is False
@patch('watchbot_progress.backends.dynamodb.boto3.resource')
def test_set_metadata(client, monkeypatch):
monkeypatch.setenv('WorkTopic', 'abc123')
monkeypatch.setenv('ProgressTable', 'arn::table/foo')
item = 'sentinel'
client.return_value.Table.return_value.update_item.return_value = item
WatchbotProgress().set_metadata('123', {'a': 1})
assert client.called
@patch('watchbot_progress.backends.dynamodb.boto3.resource')
def test_set_list_jobs(client, monkeypatch):
monkeypatch.setenv('WorkTopic', 'abc123')
monkeypatch.setenv('ProgressTable', 'arn::table/foo')
item = {'id': '123', 'total': 4, 'error': True}
client.return_value.Table.return_value.scan.return_value = {'Items': [item]}
client.return_value.Table.return_value.get_item.return_value = {'Item': item}
jobs = list(WatchbotProgress().list_jobs())
assert len(jobs) == 1
assert jobs[0]['jobid'] == '123'
jobs = list(WatchbotProgress().list_jobs(status=False))
assert len(jobs) == 1
assert jobs[0] == '123'
@patch('watchbot_progress.backends.dynamodb.boto3.resource')
def test_set_list_pending(client, monkeypatch):
monkeypatch.setenv('WorkTopic', 'abc123')
monkeypatch.setenv('ProgressTable', 'arn::table/foo')
item = {'id': '123', 'parts': [0, 1, 2]}
client.return_value.Table.return_value.get_item.return_value = {'Item': item}
parts = list(WatchbotProgress().list_pending_parts('123'))
assert len(parts) == 3
client.return_value.Table.return_value.get_item.return_value = {}
with pytest.raises(JobDoesNotExist):
parts = list(WatchbotProgress().list_pending_parts('123'))
| 35.837037
| 82
| 0.70401
| 588
| 4,838
| 5.630952
| 0.139456
| 0.129568
| 0.066747
| 0.086379
| 0.794926
| 0.77016
| 0.77016
| 0.702205
| 0.702205
| 0.633343
| 0
| 0.027394
| 0.132286
| 4,838
| 134
| 83
| 36.104478
| 0.761315
| 0
| 0
| 0.484536
| 0
| 0
| 0.241422
| 0.093014
| 0
| 0
| 0
| 0
| 0.123711
| 1
| 0.092784
| false
| 0
| 0.041237
| 0
| 0.134021
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 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
|
0
| 5
|
ce1c5de22fb334dabcce65dd09f6d89c9e77c68f
| 11
|
py
|
Python
|
new.py
|
nortics/python
|
3093a5c3cf3e8813d40a6253e8526459c848bb70
|
[
"MIT"
] | null | null | null |
new.py
|
nortics/python
|
3093a5c3cf3e8813d40a6253e8526459c848bb70
|
[
"MIT"
] | null | null | null |
new.py
|
nortics/python
|
3093a5c3cf3e8813d40a6253e8526459c848bb70
|
[
"MIT"
] | null | null | null |
print('ok')
| 11
| 11
| 0.636364
| 2
| 11
| 3.5
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 11
| 1
| 11
| 11
| 0.636364
| 0
| 0
| 0
| 0
| 0
| 0.166667
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0
| 0
| 0
| 1
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 1
|
0
| 5
|
ce2388993d03f8daa154a1153eeaf6f83d49ddf2
| 159
|
py
|
Python
|
hurricane/utils/id.py
|
DarkmatterVale/hurricane
|
94e9e56fcc6d73f5f76ad1fe9e3e4f248549fe7b
|
[
"MIT"
] | 1
|
2017-01-13T00:17:09.000Z
|
2017-01-13T00:17:09.000Z
|
hurricane/utils/id.py
|
DarkmatterVale/hurricane
|
94e9e56fcc6d73f5f76ad1fe9e3e4f248549fe7b
|
[
"MIT"
] | null | null | null |
hurricane/utils/id.py
|
DarkmatterVale/hurricane
|
94e9e56fcc6d73f5f76ad1fe9e3e4f248549fe7b
|
[
"MIT"
] | null | null | null |
import uuid
def generate_task_id():
"""
Generate a unique id (in integer format).
"""
new_id = uuid.uuid4()
return new_id.int % 10000000
| 15.9
| 45
| 0.622642
| 22
| 159
| 4.318182
| 0.727273
| 0.105263
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.076923
| 0.264151
| 159
| 9
| 46
| 17.666667
| 0.735043
| 0.257862
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.25
| false
| 0
| 0.25
| 0
| 0.75
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 1
| 0
|
0
| 5
|
ce3660a946ababc795525fcf964ef5635182f334
| 221
|
py
|
Python
|
leads/admin.py
|
Bigfoot2049/djangoProjectVersion0.1
|
17387e66a0c4ccba92e60acaee4fb1184bae02d3
|
[
"MIT"
] | null | null | null |
leads/admin.py
|
Bigfoot2049/djangoProjectVersion0.1
|
17387e66a0c4ccba92e60acaee4fb1184bae02d3
|
[
"MIT"
] | null | null | null |
leads/admin.py
|
Bigfoot2049/djangoProjectVersion0.1
|
17387e66a0c4ccba92e60acaee4fb1184bae02d3
|
[
"MIT"
] | null | null | null |
from django.contrib import admin
from .models import User, Agent, Customer, Lead
# Register your models here.
admin.site.register(User)
admin.site.register(Agent)
admin.site.register(Customer)
admin.site.register(Lead)
| 22.1
| 47
| 0.79638
| 32
| 221
| 5.5
| 0.4375
| 0.204545
| 0.386364
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.099548
| 221
| 9
| 48
| 24.555556
| 0.884422
| 0.117647
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.333333
| 0
| 0.333333
| 0
| 0
| 0
| 0
| null | 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 5
|
cbeebcfebebfea43f4708cd6bff9f769d845ba83
| 63
|
py
|
Python
|
game_core/app/orm/__init__.py
|
meseta/advent-of-code-2020
|
a6871b2efa99c38d5d13d872e53a8e9649f8322b
|
[
"MIT"
] | 1
|
2020-12-30T11:25:17.000Z
|
2020-12-30T11:25:17.000Z
|
game_core/app/orm/__init__.py
|
meseta/advent-of-code-2020
|
a6871b2efa99c38d5d13d872e53a8e9649f8322b
|
[
"MIT"
] | 13
|
2020-12-29T19:08:20.000Z
|
2021-02-01T04:27:36.000Z
|
game_core/app/orm/__init__.py
|
meseta/advent-of-code-2020
|
a6871b2efa99c38d5d13d872e53a8e9649f8322b
|
[
"MIT"
] | 1
|
2020-12-27T19:57:16.000Z
|
2020-12-27T19:57:16.000Z
|
from .orm import Orm
from .sentinels import OrmNotFound, NoKey
| 21
| 41
| 0.809524
| 9
| 63
| 5.666667
| 0.666667
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.142857
| 63
| 2
| 42
| 31.5
| 0.944444
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
02120706aea17f4712816d0cdbdee97b69749641
| 104
|
py
|
Python
|
src/features/__init__.py
|
AC297R-Wayfair-NLP/wayfair_nlp_public
|
9d3628f14f0e3e75f386a2c2f63aed93681ef686
|
[
"MIT"
] | 2
|
2021-01-11T21:16:54.000Z
|
2021-12-16T16:39:14.000Z
|
src/features/__init__.py
|
AC297R-Wayfair-NLP/wayfair_nlp_public
|
9d3628f14f0e3e75f386a2c2f63aed93681ef686
|
[
"MIT"
] | null | null | null |
src/features/__init__.py
|
AC297R-Wayfair-NLP/wayfair_nlp_public
|
9d3628f14f0e3e75f386a2c2f63aed93681ef686
|
[
"MIT"
] | null | null | null |
from ._sentiment import Sentiment
from ._returnability import Returnability
from ._topics import Topics
| 26
| 41
| 0.855769
| 12
| 104
| 7.166667
| 0.416667
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.115385
| 104
| 3
| 42
| 34.666667
| 0.934783
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
027b4a4b022c7d92e8a7ae05ea87bfbc712e38ef
| 128
|
py
|
Python
|
.idea/VirtualEnvironment/Lib/site-packages/tests/outcomes/input_handle/exception_while_reading/main.py
|
Vladpetr/NewsPortal
|
cd4127fbc09d9c8f5e65c8ae699856c6d380a320
|
[
"Apache-2.0"
] | null | null | null |
.idea/VirtualEnvironment/Lib/site-packages/tests/outcomes/input_handle/exception_while_reading/main.py
|
Vladpetr/NewsPortal
|
cd4127fbc09d9c8f5e65c8ae699856c6d380a320
|
[
"Apache-2.0"
] | 5
|
2021-04-08T22:02:15.000Z
|
2022-02-10T14:53:45.000Z
|
.idea/VirtualEnvironment/Lib/site-packages/tests/outcomes/input_handle/exception_while_reading/main.py
|
Vladpetr/NewsPortal
|
cd4127fbc09d9c8f5e65c8ae699856c6d380a320
|
[
"Apache-2.0"
] | null | null | null |
def get():
return int(input())
def get_num():
return get()
def get_line():
return get_num()
print(get_line())
| 9.142857
| 23
| 0.59375
| 19
| 128
| 3.789474
| 0.421053
| 0.25
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.242188
| 128
| 13
| 24
| 9.846154
| 0.742268
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.428571
| true
| 0
| 0
| 0.428571
| 0.857143
| 0.142857
| 1
| 0
| 0
| null | 1
| 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
| 1
| 1
| 0
| 0
| 1
| 0
| 0
|
0
| 5
|
65f9a62b4a0c9f742be5e98d6c720534548713ca
| 33,675
|
py
|
Python
|
Experiments_Synthetic/run_method.py
|
markus93/fit-on-the-test
|
e8e4ddda1ba52582920bdf0585314702c8b65892
|
[
"MIT"
] | null | null | null |
Experiments_Synthetic/run_method.py
|
markus93/fit-on-the-test
|
e8e4ddda1ba52582920bdf0585314702c8b65892
|
[
"MIT"
] | null | null | null |
Experiments_Synthetic/run_method.py
|
markus93/fit-on-the-test
|
e8e4ddda1ba52582920bdf0585314702c8b65892
|
[
"MIT"
] | null | null | null |
import gc
from keras import backend as K
import tensorflow as tf
from sklearn.metrics import log_loss
from binnings import *
from kde import KDE_estimator
from data_generation import generate_data
from pycalib.models import IsotonicCalibration, SigmoidCalibration
from betacal import BetaCalibration
from piecewise_linear import node_scores_xy_with_crossvalidation
import pwlf
from pwlf_cv import node_scores_pwlf_with_crossvalidation
from sklearn.preprocessing import PolynomialFeatures
from sklearn.pipeline import make_pipeline
from sklearn.linear_model import LinearRegression
def construct_data_row(n_folds=None, binning_name=None, n_bins=None,
c_hat_distance_p=None, c_hat_distance_p_debiased=None,
c_hat_distance_p_square=None, c_hat_distance_p_square_debiased=None,
c_hat_distance_c=None, c_hat_distance_c_square=None,
test_c_hat_distance_p=None, test_c_hat_distance_p_debiased=None,
test_c_hat_distance_p_square=None, test_c_hat_distance_p_square_debiased=None,
test_c_hat_distance_c=None, test_c_hat_distance_c_square=None):
return {
"n_folds": n_folds,
"binning": binning_name,
"n_bins": n_bins,
"c_hat_distance_p": c_hat_distance_p,
"c_hat_distance_p_debiased": c_hat_distance_p_debiased,
"c_hat_distance_p_square": c_hat_distance_p_square,
"c_hat_distance_p_square_debiased": c_hat_distance_p_square_debiased,
"c_hat_distance_c": c_hat_distance_c,
"c_hat_distance_c_square": c_hat_distance_c_square,
"test_c_hat_distance_p": test_c_hat_distance_p,
"test_c_hat_distance_p_debiased": test_c_hat_distance_p_debiased,
"test_c_hat_distance_p_square": test_c_hat_distance_p_square,
"test_c_hat_distance_p_square_debiased": test_c_hat_distance_p_square_debiased,
"test_c_hat_distance_c": test_c_hat_distance_c,
"test_c_hat_distance_c_square": test_c_hat_distance_c_square
}
def construct_data_row_from_raw_data(n_folds=None, binning_name=None, n_bins=None,
c_hat=None, p=None, c=None,
c_hat_test=None, p_test=None, c_test=None):
c_hat_diff_p = c_hat - p
c_hat_diff_c = c_hat - c
c_hat_diff_p_test = c_hat_test - p_test
c_hat_diff_c_test = c_hat_test - c_test
return construct_data_row(n_folds=n_folds, binning_name=binning_name, n_bins=n_bins,
c_hat_distance_p=np.mean(np.abs(c_hat_diff_p)),
c_hat_distance_p_debiased=np.mean(np.abs(c_hat_diff_p)),
c_hat_distance_p_square=np.mean(np.square(c_hat_diff_p)),
c_hat_distance_p_square_debiased=np.mean(np.square(c_hat_diff_p)),
c_hat_distance_c=np.mean(np.abs(c_hat_diff_c)),
c_hat_distance_c_square=np.mean(np.square(c_hat_diff_c)),
test_c_hat_distance_p=np.mean(np.abs(c_hat_diff_p_test)),
test_c_hat_distance_p_debiased=np.mean(np.abs(c_hat_diff_p_test)),
test_c_hat_distance_p_square=np.mean(np.square(c_hat_diff_p_test)),
test_c_hat_distance_p_square_debiased=np.mean(np.square(c_hat_diff_p_test)),
test_c_hat_distance_c=np.mean(np.abs(c_hat_diff_c_test)),
test_c_hat_distance_c_square=np.mean(np.square(c_hat_diff_c_test))
)
def construct_data_row_from_binning(binning, n_folds, p_test, c_test, name_addition=""):
c_hat = binning.eval_slope_1(binning.p)
c_hat_test = binning.eval_slope_1(p_test)
c_hat_diff_p_test = c_hat_test - p_test
c_hat_diff_c_test = c_hat_test - c_test
return construct_data_row(n_folds=n_folds, binning_name=binning.binning_name + name_addition, n_bins=binning.n_bins,
c_hat_distance_p=binning.ECE_abs,
c_hat_distance_p_debiased=binning.ECE_abs_debiased,
c_hat_distance_p_square=binning.ECE_square,
c_hat_distance_p_square_debiased=binning.ECE_square_debiased,
c_hat_distance_c=np.mean(np.abs(c_hat - binning.c)),
c_hat_distance_c_square=np.mean(np.square(c_hat - binning.c)),
test_c_hat_distance_p=np.mean(np.abs(c_hat_diff_p_test)),
test_c_hat_distance_p_debiased=np.mean(np.abs(c_hat_diff_p_test)),
test_c_hat_distance_p_square=np.mean(np.square(c_hat_diff_p_test)),
test_c_hat_distance_p_square_debiased=np.mean(np.square(c_hat_diff_p_test)),
test_c_hat_distance_c=np.mean(np.abs(c_hat_diff_c_test)),
test_c_hat_distance_c_square=np.mean(np.square(c_hat_diff_c_test))
)
def construct_metadata_row_from_fit_model_data(model_name, n_nodes, n_nodes_trick, cv_folds, node_scores,
node_loss, node_ECEs_abs, node_ECEs_square, all_weights,
weights_final, weights_trick, all_cv_scores, last_epoch):
return {"binning": model_name,
"n_bins": n_nodes,
"n_bins_trick": n_nodes_trick,
"cv_folds": cv_folds,
"node_scores": node_scores,
"node_train_loss": node_loss,
"cv_score": np.min(node_scores),
"node_ECEs_abs": node_ECEs_abs,
"node_ECEs_square": node_ECEs_square,
"model_weights": all_weights,
"model_weights_final": weights_final,
"model_weights_trick": weights_trick,
"all_cv_scores": all_cv_scores,
"last_epoch": last_epoch
}
def cv_trick(bin_scores):
optimal = np.argmin(bin_scores)
pos_new = np.argmin(bin_scores)
min_bin_score = np.min(bin_scores)
max_diff = min_bin_score * 0.001
for pos in range(optimal - 1, -1, -1):
new_min_cand = bin_scores[pos]
if new_min_cand <= min_bin_score + max_diff:
pos_new = pos
return pos_new
def gc_model(model):
# Garbage collect
del model.model
del model
gc.collect()
K.clear_session()
tf.compat.v1.reset_default_graph()
def run_PW_NN_nonCV_method(method, p, y, c, p_test, c_test):
n_cv_folds = method["n_cv_folds"]
monotonic = method["monotonic"]
fn_method = method["fn_method"]
seed = method["seed"]
equal_size = method["equal_size"]
use_ce_loss = method["use_ce_loss"]
logit_scale = method["logit_scale"]
logistic_out = method["logistic_out"]
nn_number = method["nn_number"]
n_bins = method["n_bins"]
lr = method["lr"]
patience = method["patience"]
n_nodes = n_bins - 1
n_data = len(p)
name_addition = method["name_addition"]
add_to_name_mono = "_monotonic" if monotonic else ""
add_to_name_logit = "_logit" if logit_scale else ""
add_to_name_loss = "_ce" if use_ce_loss else "_bs"
add_to_name_lr = f"_lr{lr}"
add_to_name_patience = f"_p{patience}"
model_name = "PW_NN" + str(nn_number) + add_to_name_mono + name_addition + add_to_name_logit + add_to_name_loss + add_to_name_lr + add_to_name_patience
model = fn_method(k=n_nodes, max_epochs=1500, random_state=seed, equal_size=equal_size, monotonic=monotonic,
use_ce_loss=use_ce_loss, logit_scale=logit_scale, logistic_out=logistic_out, lr=lr, patience=patience)
h = model.fit(p, y, verbose=False, batch_size=min(n_data // 4, 512))
last_epoch = len(h.history['loss'])
weights_final = model.model.get_weights()
c_hat = model.predict(p)
c_hat_test = model.predict(p_test)
data_row = construct_data_row_from_raw_data(n_folds=n_cv_folds, binning_name=model_name,
n_bins=n_bins, c_hat=c_hat, p=p, c=c,
c_hat_test=c_hat_test, p_test=p_test, c_test=c_test)
gc_model(model) # Garbage collection
return data_row, last_epoch, weights_final
def run_PW_NN_CV_method(method, p, y, c, p_test, c_test):
n_cv_folds = method["n_cv_folds"]
monotonic = method["monotonic"]
max_nodes = method["max_nodes"]
fn_method = method["fn_method"]
seed = method["seed"]
equal_size = method["equal_size"]
use_ce_loss = method["use_ce_loss"]
logit_scale = method["logit_scale"]
logistic_out = method["logistic_out"]
nn_number = method["nn_number"]
lr = method["lr"]
patience = method["patience"]
n_data = len(p)
add_to_name_mono = "_monotonic" if monotonic else ""
add_to_name_logit = "_logit" if logit_scale else ""
add_to_name_loss = "_ce" if use_ce_loss else "_bs"
add_to_name_lr = f"_lr{lr}"
add_to_name_patience = f"_p{patience}"
model_name = "PW_NN" + str(nn_number) + add_to_name_mono + add_to_name_logit + add_to_name_loss + add_to_name_lr + add_to_name_patience
start_cv = time()
node_scores, all_weights, all_cv_scores, node_ECEs_square, node_ECEs_abs, node_loss = node_scores_xy_with_crossvalidation(
method=fn_method, p_hat=p, y=y,
n_splits=n_cv_folds, seed=seed,
max_nodes=min(n_data // 200, max_nodes), equal_size=equal_size,
monotonic=monotonic,
use_ce_loss=use_ce_loss,
logit_scale=logit_scale,
logistic_out=logistic_out,
lr=lr,
patience=patience
)
print("Cross-validation took %f seconds" % (time() - start_cv))
n_nodes = np.argmin(node_scores)
n_bins = n_nodes + 1
method["n_bins"] = n_bins
method["name_addition"] = ""
data_row, last_epoch, weights_final = run_PW_NN_nonCV_method(method=method, p=p, y=y, c=c, p_test=p_test,
c_test=c_test)
n_nodes_tr = cv_trick(node_scores)
n_bins_tr = n_nodes_tr + 1
method["n_bins"] = n_bins_tr
method["name_addition"] = "tr"
data_row_tr, last_epoch_tr, weights_final_tr = run_PW_NN_nonCV_method(method=method, p=p, y=y, c=c, p_test=p_test,
c_test=c_test)
metadata_row = construct_metadata_row_from_fit_model_data(model_name=model_name, n_nodes=n_nodes,
n_nodes_trick=n_nodes_tr, cv_folds=n_cv_folds,
node_scores=node_scores,
node_loss=node_loss, node_ECEs_abs=node_ECEs_abs,
node_ECEs_square=node_ECEs_square,
all_weights=all_weights,
weights_final=weights_final,
weights_trick=weights_final_tr,
all_cv_scores=all_cv_scores, last_epoch=last_epoch)
return data_row, data_row_tr, metadata_row
def run_PW_NN_sweep_method(method, p, y, c, p_test, c_test):
max_nodes = method["max_nodes"]
fn_method = method["fn_method"]
seed = method["seed"]
equal_size = method["equal_size"]
nn_number = method["nn_number"]
use_ce_loss = method["use_ce_loss"]
logit_scale = method["logit_scale"]
logistic_out = method["logistic_out"]
lr = method["lr"]
patience = method["patience"]
n_data = len(p)
add_to_name_logit = "_logit" if logit_scale else ""
add_to_name_loss = "_ce" if use_ce_loss else "_bs"
add_to_name_lr = f"_lr{lr}"
add_to_name_patience = f"_p{patience}"
model_name = "PW_NN" + str(nn_number) + "_sweep" + add_to_name_logit + add_to_name_loss + add_to_name_lr + add_to_name_patience
assert (not method["monotonic"]), "Trying to sweep monotonic PW_NN method"
all_weights = []
for n_nodes in range(max_nodes + 1):
model = fn_method(k=n_nodes, max_epochs=1500, random_state=seed, equal_size=equal_size, monotonic=False,
use_ce_loss=use_ce_loss, logit_scale=logit_scale, logistic_out=logistic_out, lr=lr, patience=patience)
h = model.fit(p, y, verbose=False, batch_size=min(n_data // 4, 512))
last_epoch = len(h.history['loss'])
print("Last epoch", last_epoch)
weights = model.model.get_weights()
all_weights.append(weights)
if nn_number == 5:
y_w = np.array(weights[-3]) # weights for y # Weights for first and last breakpoint is not used.
else:
y_w = np.array(weights[-1]) # weights for y
if not np.all((y_w[1:] - y_w[:-1]) > 0):
print("N_nodes %i is not monotonic" % n_nodes)
break
else:
model_last = model
last_last_epoch = last_epoch
print("Get predictions for n_nodes %i!" % (n_nodes - 1))
c_hat = model_last.predict(p)
c_hat_test = model_last.predict(p_test)
data_row = construct_data_row_from_raw_data(n_folds=None, binning_name=model_name,
n_bins=model_last.k + 1, c_hat=c_hat, p=p, c=c,
c_hat_test=c_hat_test, p_test=p_test, c_test=c_test)
node_loss = np.mean(np.square(c_hat - y))
weights_final = model_last.model.get_weights()
metadata_row = construct_metadata_row_from_fit_model_data(model_name=model_name, n_nodes=model_last.k,
n_nodes_trick=None, cv_folds=None, node_scores=None,
node_loss=node_loss, node_ECEs_abs=None,
node_ECEs_square=None, all_weights=all_weights,
weights_final=weights_final, weights_trick=None,
all_cv_scores=None, last_epoch=last_last_epoch)
gc_model(model)
return data_row, metadata_row
def run_PW_NN_method(method, p, y, c, p_test, c_test):
n_cv_folds = method["n_cv_folds"]
use_sweep = method["use_sweep"]
if use_sweep:
data_row, metadata_row = run_PW_NN_sweep_method(method=method, p=p, y=y, c=c, p_test=p_test, c_test=c_test)
return [data_row], [metadata_row]
elif n_cv_folds is None:
data_row, _, _ = run_PW_NN_nonCV_method(method=method, p=p, y=y, c=c, p_test=p_test, c_test=c_test)
return [data_row], []
else:
data_row, data_row_tr, metadata_row = run_PW_NN_CV_method(method=method, p=p, y=y, c=c, p_test=p_test,
c_test=c_test)
return [data_row, data_row_tr], [metadata_row]
def run_binning_CV_method(method, p, y, c, p_test, c_test):
method_name = method["method_name"]
n_cv_folds = method["n_cv_folds"]
name_addition = f"_CV{n_cv_folds}"
assert (method_name == "eq_width" or method_name == "eq_size"), "Method name incorrect in CV binning!"
use_eq_width = method_name == "eq_width"
if use_eq_width:
binning_method = EqualWidthBinning
else:
binning_method = EqualSizeBinning
bin_scores, all_cv_scores = binning_n_bins_with_crossvalidation(p=p, y=y, use_eq_width=use_eq_width,
n_splits=n_cv_folds)
n_bins = np.argmin(bin_scores)
n_bins_tr = cv_trick(bin_scores)
binning_cv = binning_method(p, y, c, n_bins)
binning_cv_tr = binning_method(p, y, c, n_bins_tr)
data_row_cv = construct_data_row_from_binning(binning=binning_cv, n_folds=n_cv_folds, p_test=p_test, c_test=c_test,
name_addition=name_addition)
data_row_cv_tr = construct_data_row_from_binning(binning=binning_cv_tr, n_folds=n_cv_folds, p_test=p_test,
c_test=c_test,
name_addition=name_addition + "tr")
return data_row_cv, data_row_cv_tr
def run_binning_nonCV_method(method, p, y, c, p_test, c_test):
method_name = method["method_name"]
n_bins = method["n_bins"]
if method_name == "eq_size":
binning = EqualSizeBinning(p, y, c, n_bins)
name_addition = f"_{n_bins}"
elif method_name == "eq_width":
binning = EqualWidthBinning(p, y, c, n_bins)
name_addition = f"_{n_bins}"
elif method_name == "monotonic_eq_size":
binning = MonotonicEqualSizeBinning(p, y, c)
name_addition = ""
return construct_data_row_from_binning(binning, n_folds=None, p_test=p_test, c_test=c_test,
name_addition=name_addition)
def run_binning_method(method, p, y, c, p_test, c_test):
n_cv_folds = method["n_cv_folds"]
if n_cv_folds is None:
data_row = run_binning_nonCV_method(method=method, p=p, y=y, c=c, p_test=p_test, c_test=c_test)
return [data_row], []
else:
data_row_cv, data_row_cv_tr = run_binning_CV_method(method=method, p=p, y=y, c=c, p_test=p_test, c_test=c_test)
return [data_row_cv, data_row_cv_tr], []
def run_kde_method(p, y, c, calibration_function, p_test, c_test):
kde_estimator = KDE_estimator(p=p, y=y, c=c, calibration_function=calibration_function, p_test=p_test,
c_test=c_test)
data_row_pointwise = construct_data_row(n_folds=None, binning_name="kde_pointwise", n_bins=None,
c_hat_distance_p=kde_estimator.pointwise_ece_abs,
c_hat_distance_p_debiased=kde_estimator.pointwise_ece_abs,
c_hat_distance_p_square=kde_estimator.pointwise_ece_sq,
c_hat_distance_p_square_debiased=kde_estimator.pointwise_ece_sq,
c_hat_distance_c=kde_estimator.pointwise_c_hat_dist_c_abs,
c_hat_distance_c_square=kde_estimator.pointwise_c_hat_dist_c_sq,
test_c_hat_distance_p=kde_estimator.pointwise_ece_abs_test,
test_c_hat_distance_p_debiased=kde_estimator.pointwise_ece_abs_test,
test_c_hat_distance_p_square=kde_estimator.pointwise_ece_sq_test,
test_c_hat_distance_p_square_debiased=kde_estimator.pointwise_ece_sq_test,
test_c_hat_distance_c=kde_estimator.pointwise_c_hat_dist_c_abs_test,
test_c_hat_distance_c_square=kde_estimator.pointwise_c_hat_dist_c_sq_test
)
data_row_integral = construct_data_row(n_folds=None, binning_name="kde_integral", n_bins=None,
c_hat_distance_p=kde_estimator.integral_ece_abs,
c_hat_distance_p_debiased=kde_estimator.integral_ece_abs,
c_hat_distance_p_square=kde_estimator.integral_ece_sq,
c_hat_distance_p_square_debiased=kde_estimator.integral_ece_sq,
c_hat_distance_c=kde_estimator.integral_c_hat_dist_c_abs,
c_hat_distance_c_square=kde_estimator.integral_c_hat_dist_c_sq,
test_c_hat_distance_p=None,
test_c_hat_distance_p_debiased=None,
test_c_hat_distance_p_square=None,
test_c_hat_distance_p_square_debiased=None,
test_c_hat_distance_c=None,
test_c_hat_distance_c_square=None
)
return [data_row_pointwise, data_row_integral], []
def run_isotonic(p, y, c, p_test, c_test):
isotonic = IsotonicCalibration()
isotonic.fit(p, y)
c_hat = isotonic.predict(p)
c_hat_test = isotonic.predict(p_test)
data_row = construct_data_row_from_raw_data(n_folds=None, binning_name="isotonic",
n_bins=len(isotonic.X_thresholds_) - 1,
c_hat=c_hat, p=p, c=c,
c_hat_test=c_hat_test, p_test=p_test, c_test=c_test)
return [data_row], []
def run_platt(p, y, c, p_test, c_test):
p_clipped = np.clip(p, 1e-8, 1 - 1e-8)
p_logit = np.log(p_clipped / (1 - p_clipped))
p_clipped_test = np.clip(p_test, 1e-8, 1 - 1e-8)
p_logit_test = np.log(p_clipped_test / (1 - p_clipped_test))
platt = SigmoidCalibration()
platt.fit(p_logit.reshape(-1, 1), y)
c_hat = platt.predict_proba(p_logit.reshape(-1, 1))
c_hat_test = platt.predict_proba(p_logit_test.reshape(-1, 1))
data_row = construct_data_row_from_raw_data(n_folds=None, binning_name="platt", n_bins=None,
c_hat=c_hat, p=p, c=c,
c_hat_test=c_hat_test, p_test=p_test, c_test=c_test)
return [data_row], []
def run_beta(p, y, c, p_test, c_test):
bc = BetaCalibration(parameters="abm")
bc.fit(p.reshape(-1, 1), y)
c_hat = bc.predict(p.reshape(-1, 1))
c_hat_test = bc.predict(p_test.reshape(-1, 1))
data_row = construct_data_row_from_raw_data(n_folds=None, binning_name="beta", n_bins=None,
c_hat=c_hat, p=p, c=c,
c_hat_test=c_hat_test, p_test=p_test, c_test=c_test)
return [data_row], []
def run_brier_score(p, y):
brier_score = np.mean(np.square(p - y))
data_row = construct_data_row(n_folds=None, binning_name="brier_score", n_bins=None,
c_hat_distance_p=brier_score,
c_hat_distance_p_debiased=brier_score,
c_hat_distance_p_square=brier_score,
c_hat_distance_p_square_debiased=brier_score,
c_hat_distance_c=brier_score,
c_hat_distance_c_square=brier_score)
return [data_row], []
def run_cross_entropy_loss(p, y):
cross_entropy_loss = log_loss(y, p)
data_row = construct_data_row(n_folds=None, binning_name="cross_entropy_loss", n_bins=None,
c_hat_distance_p=cross_entropy_loss,
c_hat_distance_p_debiased=cross_entropy_loss,
c_hat_distance_p_square=cross_entropy_loss,
c_hat_distance_p_square_debiased=cross_entropy_loss,
c_hat_distance_c=cross_entropy_loss,
c_hat_distance_c_square=cross_entropy_loss)
return [data_row], []
def run_pwlf_nonCV_method(method, p, y, c, p_test, c_test):
n_cv_folds = method["n_cv_folds"]
n_bins = method["n_bins"]
degree = method["degree"]
name_addition = method["name_addition"]
model_name = "pwlf_d" + str(degree) + name_addition
if n_bins == 1:
model = make_pipeline(PolynomialFeatures(degree), LinearRegression())
model.fit(p.reshape(-1, 1), y)
c_hat = model.predict(p.reshape(-1, 1))
c_hat_test = model.predict(p_test.reshape(-1, 1))
else:
model = pwlf.PiecewiseLinFit(p, y, degree=degree)
model.fit(n_bins)
c_hat = model.predict(p)
c_hat_test = model.predict(p_test)
data_row = construct_data_row_from_raw_data(n_folds=n_cv_folds, binning_name=model_name,
n_bins=n_bins, c_hat=c_hat, p=p, c=c,
c_hat_test=c_hat_test, p_test=p_test, c_test=c_test)
return data_row
def run_pwlf_CV_method(method, p, y, c, p_test, c_test):
n_cv_folds = method["n_cv_folds"]
max_nodes = method["max_nodes"]
seed = method["seed"]
n_data = len(p)
degree = method["degree"]
model_name = "pwlf_d" + str(degree)
start_cv = time()
node_scores, all_weights, all_cv_scores, node_ECEs_square, node_ECEs_abs, node_loss = node_scores_pwlf_with_crossvalidation(
p_hat=p, y=y,
n_splits=n_cv_folds, seed=seed,
max_nodes=min(n_data // 20, max_nodes), degree=degree)
print("Cross-validation took %f seconds" % (time() - start_cv))
n_bins = np.argmin(node_scores)
method["n_bins"] = n_bins
method["name_addition"] = ""
data_row = run_pwlf_nonCV_method(method=method, p=p, y=y, c=c, p_test=p_test, c_test=c_test)
n_bins_tr = cv_trick(node_scores)
method["n_bins"] = n_bins_tr
method["name_addition"] = "tr"
data_row_tr = run_pwlf_nonCV_method(method=method, p=p, y=y, c=c, p_test=p_test, c_test=c_test)
metadata_row = construct_metadata_row_from_fit_model_data(model_name=model_name, n_nodes=n_bins,
n_nodes_trick=n_bins_tr, cv_folds=n_cv_folds,
node_scores=node_scores,
node_loss=node_loss, node_ECEs_abs=node_ECEs_abs,
node_ECEs_square=node_ECEs_square,
all_weights=all_weights,
weights_final=None,
weights_trick=None,
all_cv_scores=all_cv_scores, last_epoch=None)
return data_row, data_row_tr, metadata_row
def run_pwlf_sweep_method(method, p, y, c, p_test, c_test):
max_nodes = method["max_nodes"]
degree = method["degree"]
model_name = "pwlf_d" + str(degree) + "_sweep"
all_weights = []
for n_nodes in range(1, max_nodes + 1):
if n_nodes == 1:
model = make_pipeline(PolynomialFeatures(degree), LinearRegression())
model.fit(p.reshape(-1, 1), y)
y_w = np.array([0, 1]) # weights for y
else:
model = pwlf.PiecewiseLinFit(p, y, degree=degree)
breaks = model.fit(n_nodes)
y_w = np.array(model.predict(breaks)) # weights for y
print(y_w)
if not np.all((y_w[1:] - y_w[:-1]) > 0):
print("N_nodes %i is not monotonic" % n_nodes)
break
else:
model_last = model
if n_nodes <= 2:
c_hat = model_last.predict(p.reshape(-1, 1))
c_hat_test = model_last.predict(p_test.reshape(-1, 1))
else:
c_hat = model_last.predict(p)
c_hat_test = model_last.predict(p_test)
data_row = construct_data_row_from_raw_data(n_folds=None, binning_name=model_name,
n_bins=n_nodes - 1, c_hat=c_hat, p=p, c=c,
c_hat_test=c_hat_test, p_test=p_test, c_test=c_test)
node_loss = np.mean(np.square(c_hat - y))
metadata_row = construct_metadata_row_from_fit_model_data(model_name=model_name, n_nodes=n_nodes - 1,
n_nodes_trick=None, cv_folds=None, node_scores=None,
node_loss=node_loss, node_ECEs_abs=None,
node_ECEs_square=None, all_weights=all_weights,
weights_final=None, weights_trick=None,
all_cv_scores=None, last_epoch=None)
return data_row, metadata_row
def run_pwlf_method(method, p, y, c, p_test, c_test):
n_cv_folds = method["n_cv_folds"]
use_sweep = method["use_sweep"]
if use_sweep:
data_row, metadata_row = run_pwlf_sweep_method(method=method, p=p, y=y, c=c, p_test=p_test, c_test=c_test)
return [data_row], [metadata_row]
elif n_cv_folds is None:
data_row, _, _ = run_pwlf_nonCV_method(method=method, p=p, y=y, c=c, p_test=p_test, c_test=c_test)
return [data_row], []
else:
data_row, data_row_tr, metadata_row = run_pwlf_CV_method(method=method, p=p, y=y, c=c, p_test=p_test,
c_test=c_test)
return [data_row, data_row_tr], [metadata_row]
def run_kce_method(p, y):
from pycalibration import calerrors as ce
skce_unbiased = ce.UnbiasedSKCE(ce.tensor(ce.RBFKernel(), ce.RBFKernel()))
skce_blockunbiased = ce.BlockUnbiasedSKCE(ce.tensor(ce.RBFKernel(), ce.RBFKernel()))
skce = ce.BiasedSKCE(ce.tensor(ce.RBFKernel(), ce.RBFKernel()))
skce_p = p
skce_y = np.array(y, dtype=bool)
skce_estimate = skce(skce_p, skce_y)
skce_unbiased_estimate = skce_unbiased(skce_p, skce_y)
skce_blockunbiased_estimate = skce_blockunbiased(skce_p, skce_y)
data_row = construct_data_row(n_folds=None, binning_name="KCE", n_bins=None,
c_hat_distance_p=None,
c_hat_distance_p_debiased=None,
c_hat_distance_p_square=skce_estimate,
c_hat_distance_p_square_debiased=skce_unbiased_estimate,
c_hat_distance_c=None,
c_hat_distance_c_square=None,
test_c_hat_distance_p=None,
test_c_hat_distance_p_debiased=None,
test_c_hat_distance_p_square=None,
test_c_hat_distance_p_square_debiased=None,
test_c_hat_distance_c=None,
test_c_hat_distance_c_square=None)
data_row_block = construct_data_row(n_folds=None, binning_name="KCE_block", n_bins=None,
c_hat_distance_p=None,
c_hat_distance_p_debiased=None,
c_hat_distance_p_square=skce_estimate,
c_hat_distance_p_square_debiased=skce_blockunbiased_estimate,
c_hat_distance_c=None,
c_hat_distance_c_square=None,
test_c_hat_distance_p=None,
test_c_hat_distance_p_debiased=None,
test_c_hat_distance_p_square=None,
test_c_hat_distance_p_square_debiased=None,
test_c_hat_distance_c=None,
test_c_hat_distance_c_square=None)
return [data_row, data_row_block], []
def run_method(method, p, y, c, calibration_function, p_test, c_test):
method_name = method["method_name"]
if method_name == "PW_NN":
return run_PW_NN_method(method=method, p=p, y=y, c=c, p_test=p_test, c_test=c_test)
elif method_name == "pwlf":
return run_pwlf_method(method=method, p=p, y=y, c=c, p_test=p_test, c_test=c_test)
elif method_name == "KDE":
return run_kde_method(p=p, y=y, c=c, calibration_function=calibration_function, p_test=p_test, c_test=c_test)
elif method_name == "KCE":
return run_kce_method(p=p, y=y)
elif method_name == "isotonic":
return run_isotonic(p=p, y=y, c=c, p_test=p_test, c_test=c_test)
elif method_name == "platt":
return run_platt(p=p, y=y, c=c, p_test=p_test, c_test=c_test)
elif method_name == "beta":
return run_beta(p=p, y=y, c=c, p_test=p_test, c_test=c_test)
elif method_name == "brier_score":
return run_brier_score(p=p, y=y)
elif method_name == "cross_entropy_loss":
return run_cross_entropy_loss(p=p, y=y)
else:
return run_binning_method(method=method, p=p, y=y, c=c, p_test=p_test, c_test=c_test)
| 47.765957
| 156
| 0.581856
| 4,600
| 33,675
| 3.792826
| 0.048478
| 0.048146
| 0.082536
| 0.059609
| 0.806958
| 0.76185
| 0.737319
| 0.687855
| 0.65805
| 0.619476
| 0
| 0.004108
| 0.334996
| 33,675
| 704
| 157
| 47.833807
| 0.774984
| 0.004246
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| 0.420863
| 1
| 0
| 0.051615
| 0.008166
| 0
| 0
| 0
| 0
| 0.003597
| 1
| 0.044964
| false
| 0
| 0.028777
| 0.003597
| 0.142086
| 0.01259
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 5
|
5a05ad43dfccbc87b5a8f91f8fe5c5284bd6090b
| 496
|
py
|
Python
|
d8_stack.py
|
DK2K00/100DaysOfCode
|
68a9422b8b0b3aa233b1e11e310a6a58453e35c1
|
[
"MIT"
] | null | null | null |
d8_stack.py
|
DK2K00/100DaysOfCode
|
68a9422b8b0b3aa233b1e11e310a6a58453e35c1
|
[
"MIT"
] | null | null | null |
d8_stack.py
|
DK2K00/100DaysOfCode
|
68a9422b8b0b3aa233b1e11e310a6a58453e35c1
|
[
"MIT"
] | null | null | null |
class Stack():
def __init__(self):
self.items = []
def push(self, item):
return self.items.append(item)
def pop(self):
return self.items.pop()
def IsEmpty(self):
return self.items == []
def length(self):
return len(self.items)
def peek(self):
return self.items[len(self.items) - 1]
s = Stack()
s.IsEmpty()
s.push(10)
s.length()
s.push(20)
s.push(30)
s.length()
s.peek()
s.pop()
s.IsEmpty()
s.pop()
s.pop()
s.IsEmpty()
| 15.030303
| 46
| 0.570565
| 75
| 496
| 3.72
| 0.266667
| 0.225806
| 0.215054
| 0.204301
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.018868
| 0.252016
| 496
| 33
| 47
| 15.030303
| 0.733154
| 0
| 0
| 0.307692
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.230769
| false
| 0
| 0
| 0.192308
| 0.461538
| 0
| 0
| 0
| 0
| null | 1
| 1
| 1
| 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
| 1
| 0
| 0
| 0
| 1
| 0
| 0
|
0
| 5
|
5a2b54f2dda2533c926958ff24c687c5fd82a902
| 725
|
py
|
Python
|
tests/db_tests/test_automatic_naming.py
|
Anyesh/workoutizer
|
5cfdef5d08f63d59d6d7d7922540566f6500753b
|
[
"MIT"
] | 45
|
2020-10-23T13:01:34.000Z
|
2022-03-07T08:48:16.000Z
|
tests/db_tests/test_automatic_naming.py
|
MakhmudovMurod/workoutizer
|
1509b711b43875c5f01d62ddbc182b0ee5e23dd2
|
[
"MIT"
] | 62
|
2020-10-06T19:18:12.000Z
|
2022-01-13T19:25:34.000Z
|
tests/db_tests/test_automatic_naming.py
|
MakhmudovMurod/workoutizer
|
1509b711b43875c5f01d62ddbc182b0ee5e23dd2
|
[
"MIT"
] | 12
|
2020-10-07T12:44:00.000Z
|
2021-09-13T06:36:24.000Z
|
from wkz import models
def test_automatic_naming_of_activity__gpx_with_coordinates(import_one_activity):
import_one_activity("example.gpx")
activity = models.Activity.objects.get()
assert activity.name == "Evening Jogging in Heidelberg"
def test_automatic_naming_of_activity__fit_with_coordinates(import_one_activity):
import_one_activity("hike_with_coordinates_muggenbrunn.fit")
activity = models.Activity.objects.get()
assert activity.name == "Noon Hiking in Aftersteg"
def test_automatic_naming_of_activity__fit_no_coordinates(import_one_activity):
import_one_activity("swim_no_coordinates.fit")
activity = models.Activity.objects.get()
assert activity.name == "Noon Swimming"
| 31.521739
| 81
| 0.802759
| 94
| 725
| 5.755319
| 0.340426
| 0.099815
| 0.18854
| 0.121996
| 0.756007
| 0.756007
| 0.696858
| 0.484288
| 0.210721
| 0.210721
| 0
| 0
| 0.118621
| 725
| 22
| 82
| 32.954545
| 0.846635
| 0
| 0
| 0.230769
| 0
| 0
| 0.188966
| 0.082759
| 0
| 0
| 0
| 0
| 0.230769
| 1
| 0.230769
| false
| 0
| 0.538462
| 0
| 0.769231
| 0
| 0
| 0
| 0
| null | 0
| 1
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
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| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
5a32fb64effb444bb99625e6d525fd605e7d75ad
| 167
|
py
|
Python
|
H2H/Location/admin.py
|
saefty/happy2help_backend
|
da4bbd8d18a122ec87fc9ebc655864f3789fd8a7
|
[
"MIT"
] | null | null | null |
H2H/Location/admin.py
|
saefty/happy2help_backend
|
da4bbd8d18a122ec87fc9ebc655864f3789fd8a7
|
[
"MIT"
] | 3
|
2020-02-11T23:35:05.000Z
|
2021-06-10T21:05:39.000Z
|
H2H/Location/admin.py
|
saefty/happy2help_backend
|
da4bbd8d18a122ec87fc9ebc655864f3789fd8a7
|
[
"MIT"
] | null | null | null |
from django.contrib import admin
# Register your models here.
from .models import Location
@admin.register(Location)
class LocationAdmin(admin.ModelAdmin):
pass
| 18.555556
| 38
| 0.790419
| 21
| 167
| 6.285714
| 0.666667
| 0.19697
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.137725
| 167
| 9
| 39
| 18.555556
| 0.916667
| 0.155689
| 0
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| 0
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| 0
| 0
| 0
| 0
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| 0
| true
| 0.2
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| 0
| null | 0
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| null | 0
| 0
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| 1
| 1
| 0
| 0
| 0
|
0
| 5
|
5a783ac1cba837862ce771983bb9fe009be2b44e
| 22,482
|
py
|
Python
|
db/data/2008/10/process.py
|
nataliemcmullen/WikiMiney
|
562177a74179cb28469604f4fb9d021cebeed0a6
|
[
"MIT"
] | 1
|
2020-11-18T19:20:58.000Z
|
2020-11-18T19:20:58.000Z
|
db/data/2008/10/process.py
|
nataliemcmullen/WikiMiney
|
562177a74179cb28469604f4fb9d021cebeed0a6
|
[
"MIT"
] | null | null | null |
db/data/2008/10/process.py
|
nataliemcmullen/WikiMiney
|
562177a74179cb28469604f4fb9d021cebeed0a6
|
[
"MIT"
] | null | null | null |
from __future__ import with_statement
import os
urls = [
"pagecounts-20081001-000000",
"pagecounts-20081001-010000",
"pagecounts-20081001-020000",
"pagecounts-20081001-030000",
"pagecounts-20081001-040000",
"pagecounts-20081001-050001",
"pagecounts-20081001-060000",
"pagecounts-20081001-070000",
"pagecounts-20081001-080000",
"pagecounts-20081001-090000",
"pagecounts-20081001-100000",
"pagecounts-20081001-110001",
"pagecounts-20081001-120000",
"pagecounts-20081001-130000",
"pagecounts-20081001-140000",
"pagecounts-20081001-150000",
"pagecounts-20081001-160000",
"pagecounts-20081001-170001",
"pagecounts-20081001-180000",
"pagecounts-20081001-190000",
"pagecounts-20081001-200000",
"pagecounts-20081001-210000",
"pagecounts-20081001-220000",
"pagecounts-20081001-230001",
"pagecounts-20081002-000000",
"pagecounts-20081002-010000",
"pagecounts-20081002-020000",
"pagecounts-20081002-030000",
"pagecounts-20081002-040000",
"pagecounts-20081002-050001",
"pagecounts-20081002-060000",
"pagecounts-20081002-070000",
"pagecounts-20081002-080000",
"pagecounts-20081002-090000",
"pagecounts-20081002-100000",
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"pagecounts-20081002-120000",
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"pagecounts-20081003-030000",
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"pagecounts-20081003-060000",
"pagecounts-20081003-070000",
"pagecounts-20081003-080000",
"pagecounts-20081003-090000",
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"pagecounts-20081003-110001",
"pagecounts-20081003-120000",
"pagecounts-20081003-130000",
"pagecounts-20081003-140000",
"pagecounts-20081003-150000",
"pagecounts-20081003-160001",
"pagecounts-20081003-170000",
"pagecounts-20081003-180000",
"pagecounts-20081003-190000",
"pagecounts-20081003-200000",
"pagecounts-20081003-210000",
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"pagecounts-20081003-230000",
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"pagecounts-20081004-180000",
"pagecounts-20081004-190000",
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"pagecounts-20081004-210000",
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"pagecounts-20081004-230000",
"pagecounts-20081005-000000",
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"pagecounts-20081031-060001",
"pagecounts-20081031-070000",
"pagecounts-20081031-080000",
"pagecounts-20081031-090000",
"pagecounts-20081031-100000",
"pagecounts-20081031-110000",
"pagecounts-20081031-120001",
"pagecounts-20081031-130000",
"pagecounts-20081031-140000",
"pagecounts-20081031-150000",
"pagecounts-20081031-160000",
"pagecounts-20081031-170000",
"pagecounts-20081031-180001",
"pagecounts-20081031-190000",
"pagecounts-20081031-200000",
"pagecounts-20081031-210000",
"pagecounts-20081031-220000",
"pagecounts-20081031-230000",
]
base = "http://dumps.wikimedia.org/other/pagecounts-raw/"
tail = "2008/2008-10/"
print "Unzipping..."
os.system("gunzip *.gz")
i = 0
for url in urls:
if not os.path.isfile("en-" + url):
f_size = os.stat(url).st_size
if not os.path.isfile(url) or f_size < 100L:
os.system("rm " + url)
os.system("curl -O %s.gz" % (base + tail + url))
os.system("gunzip " + url + ".gz")
with open(url, "r") as full:
new = open("en-" + url, "w")
for line in full:
if line[0:2] == "en":
new.write(line)
new.close()
i = i + 1
print "%d of %d complete" % (i, len(urls))
if os.path.isfile(url):
os.system("rm " + url)
if os.stat("en-" + url).st_size < 100L:
print url
| 29.698811
| 57
| 0.791656
| 2,298
| 22,482
| 7.741079
| 0.059617
| 0.025184
| 0.002024
| 0.001237
| 0.001911
| 0
| 0
| 0
| 0
| 0
| 0
| 0.470386
| 0.040966
| 22,482
| 756
| 58
| 29.738095
| 0.354668
| 0
| 0
| 0.002663
| 0
| 0
| 0.842496
| 0.836136
| 0
| 0
| 0
| 0
| 0
| 0
| null | null | 0
| 0.002663
| null | null | 0.003995
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| null | 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 5
|
ce53fa48fbb40222df0ce6b8db9f2070f6a97ead
| 576
|
py
|
Python
|
messaging/querysets.py
|
ChrisMarsh82/iogt
|
8141421a79b73bd038880a3be92fa6809adced13
|
[
"BSD-2-Clause"
] | 20
|
2021-04-29T12:36:25.000Z
|
2022-03-27T12:17:41.000Z
|
messaging/querysets.py
|
ChrisMarsh82/iogt
|
8141421a79b73bd038880a3be92fa6809adced13
|
[
"BSD-2-Clause"
] | 892
|
2021-02-02T13:56:06.000Z
|
2022-03-31T11:25:44.000Z
|
messaging/querysets.py
|
ChrisMarsh82/iogt
|
8141421a79b73bd038880a3be92fa6809adced13
|
[
"BSD-2-Clause"
] | 28
|
2021-02-19T19:28:37.000Z
|
2022-03-11T11:46:00.000Z
|
from django.db.models import QuerySet
class ThreadQuerySet(QuerySet):
def of_user(self, user):
return self.filter(user_threads__user=user)
def inbox(self):
return self.filter(user_threads__is_active=True)
def deleted(self):
return self.filter(user_threads__is_active=False)
def unread(self):
return self.filter(
user_threads__is_active=True,
user_threads__is_read=False
)
def order_by_latest(self):
return self.filter(last_message_at__isnull=False).order_by('-last_message_at')
| 26.181818
| 86
| 0.692708
| 77
| 576
| 4.805195
| 0.38961
| 0.135135
| 0.216216
| 0.216216
| 0.410811
| 0.337838
| 0.337838
| 0.337838
| 0.232432
| 0
| 0
| 0
| 0.222222
| 576
| 21
| 87
| 27.428571
| 0.825893
| 0
| 0
| 0
| 0
| 0
| 0.027778
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.333333
| false
| 0
| 0.066667
| 0.333333
| 0.8
| 0
| 0
| 0
| 0
| null | 0
| 1
| 1
| 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
| 1
| 0
| 0
| 0
| 1
| 1
| 0
|
0
| 5
|
ce8cb0347bf913c70c898838f88a083e65cfce6a
| 15
|
py
|
Python
|
Scripts/Python/wasup.py
|
SPal-14/ProjectMRU
|
cf7effdf7eb310da445a5ecbf958760c27706ca8
|
[
"CC0-1.0"
] | 9
|
2020-10-06T08:12:28.000Z
|
2020-10-24T20:32:46.000Z
|
Scripts/Python/wasup.py
|
SPal-14/ProjectMRU
|
cf7effdf7eb310da445a5ecbf958760c27706ca8
|
[
"CC0-1.0"
] | 5
|
2020-10-09T04:54:43.000Z
|
2020-10-31T06:31:03.000Z
|
Scripts/Python/wasup.py
|
SPal-14/ProjectMRU
|
cf7effdf7eb310da445a5ecbf958760c27706ca8
|
[
"CC0-1.0"
] | 33
|
2020-10-05T20:02:12.000Z
|
2020-10-31T05:05:48.000Z
|
print('wasup!')
| 15
| 15
| 0.666667
| 2
| 15
| 5
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 15
| 1
| 15
| 15
| 0.666667
| 0
| 0
| 0
| 0
| 0
| 0.375
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0
| 0
| 0
| 1
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 1
|
0
| 5
|
0cbc68c8cc5980029686ca9a4b39e1c647cc8101
| 20
|
py
|
Python
|
dir1/my_code1.py
|
BinHan-Code/pyneta
|
95805b799c32190c9c2474df367baaeed89bdea7
|
[
"Apache-2.0"
] | null | null | null |
dir1/my_code1.py
|
BinHan-Code/pyneta
|
95805b799c32190c9c2474df367baaeed89bdea7
|
[
"Apache-2.0"
] | null | null | null |
dir1/my_code1.py
|
BinHan-Code/pyneta
|
95805b799c32190c9c2474df367baaeed89bdea7
|
[
"Apache-2.0"
] | null | null | null |
print ("Hello Han")
| 10
| 19
| 0.65
| 3
| 20
| 4.333333
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.15
| 20
| 1
| 20
| 20
| 0.764706
| 0
| 0
| 0
| 0
| 0
| 0.45
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0
| 0
| 0
| 1
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 1
|
0
| 5
|
0cc5dd8c84eb0ca0302d1ff8cad5cbeb470b3937
| 230
|
py
|
Python
|
alqlab_customization/alqlab/doctype/material_order/test_material_order.py
|
Suraj787/alqlab_customization
|
0c88cb626d3ab9c06111647c206eb5d660085e03
|
[
"MIT"
] | null | null | null |
alqlab_customization/alqlab/doctype/material_order/test_material_order.py
|
Suraj787/alqlab_customization
|
0c88cb626d3ab9c06111647c206eb5d660085e03
|
[
"MIT"
] | null | null | null |
alqlab_customization/alqlab/doctype/material_order/test_material_order.py
|
Suraj787/alqlab_customization
|
0c88cb626d3ab9c06111647c206eb5d660085e03
|
[
"MIT"
] | 1
|
2021-04-03T19:29:00.000Z
|
2021-04-03T19:29:00.000Z
|
# -*- coding: utf-8 -*-
# Copyright (c) 2021, bizmap technologies,pune and Contributors
# See license.txt
from __future__ import unicode_literals
# import frappe
import unittest
class TestMaterialOrder(unittest.TestCase):
pass
| 20.909091
| 63
| 0.773913
| 28
| 230
| 6.178571
| 0.892857
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.025126
| 0.134783
| 230
| 10
| 64
| 23
| 0.844221
| 0.491304
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0.25
| 0.5
| 0
| 0.75
| 0
| 1
| 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
| 1
| 1
| 1
| 0
| 1
| 0
|
0
| 5
|
0ccd3df42b1a71506781bb8ecf7c1a71a725498a
| 94
|
py
|
Python
|
AI/model.py
|
mayfieldmobster/DECI
|
c2c9165aeec7344048dd9479049dc490033881d5
|
[
"MIT"
] | 1
|
2021-12-19T01:09:12.000Z
|
2021-12-19T01:09:12.000Z
|
AI/model.py
|
mayfieldmobster/DECI
|
c2c9165aeec7344048dd9479049dc490033881d5
|
[
"MIT"
] | null | null | null |
AI/model.py
|
mayfieldmobster/DECI
|
c2c9165aeec7344048dd9479049dc490033881d5
|
[
"MIT"
] | null | null | null |
def dataset():
pass
def model():
pass
def loss():
pass
def opt():
pass
| 5.875
| 14
| 0.5
| 12
| 94
| 3.916667
| 0.5
| 0.446809
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.37234
| 94
| 16
| 15
| 5.875
| 0.79661
| 0
| 0
| 0.5
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.5
| true
| 0.5
| 0
| 0
| 0.5
| 0
| 1
| 0
| 0
| null | 1
| 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
| 1
| 1
| 1
| 0
| 0
| 0
| 0
|
0
| 5
|
0ce2e2a9f722c4854b651b0cb4c5b9b7c6c9bb9a
| 176
|
py
|
Python
|
backend/Contraband/query/admin.py
|
X3NOSIZ/WikiContrib
|
f8061de4cbfcbb524c5f95a47f127d7607d7f3da
|
[
"MIT"
] | null | null | null |
backend/Contraband/query/admin.py
|
X3NOSIZ/WikiContrib
|
f8061de4cbfcbb524c5f95a47f127d7607d7f3da
|
[
"MIT"
] | null | null | null |
backend/Contraband/query/admin.py
|
X3NOSIZ/WikiContrib
|
f8061de4cbfcbb524c5f95a47f127d7607d7f3da
|
[
"MIT"
] | null | null | null |
from contraband.admin import admin_site as admin
from .models import Query, QueryFilter, QueryUser
admin.register(Query)
admin.register(QueryFilter)
admin.register(QueryUser)
| 25.142857
| 49
| 0.835227
| 23
| 176
| 6.347826
| 0.478261
| 0.267123
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.090909
| 176
| 6
| 50
| 29.333333
| 0.9125
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.4
| 0
| 0.4
| 0
| 1
| 0
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 5
|
0cfc8b56a267db9f12c4fc3a8d7da0fb5b5b7106
| 85
|
py
|
Python
|
DataStructures-Algorithms/Udacity-Python-DSA/03-Recursion/factorial.py
|
shoaibur/SWE
|
1e114a2750f2df5d6c50b48c8e439224894d65da
|
[
"MIT"
] | 1
|
2020-11-14T18:28:13.000Z
|
2020-11-14T18:28:13.000Z
|
DataStructures-Algorithms/Udacity-Python-DSA/03-Recursion/factorial.py
|
shoaibur/SWE
|
1e114a2750f2df5d6c50b48c8e439224894d65da
|
[
"MIT"
] | null | null | null |
DataStructures-Algorithms/Udacity-Python-DSA/03-Recursion/factorial.py
|
shoaibur/SWE
|
1e114a2750f2df5d6c50b48c8e439224894d65da
|
[
"MIT"
] | null | null | null |
def factorial(n):
if n <= 1: return n
return factorial(n-1) + factorial(n-2)
| 21.25
| 42
| 0.611765
| 15
| 85
| 3.466667
| 0.466667
| 0.576923
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.046154
| 0.235294
| 85
| 3
| 43
| 28.333333
| 0.753846
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.333333
| false
| 0
| 0
| 0
| 0.666667
| 0
| 1
| 0
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 1
| 0
|
0
| 5
|
0b2635e609a47d6cc2a4b4540b36006a7c26d7a4
| 226
|
py
|
Python
|
Python_Projects/Python_MySQL/FTD_SQL_stored_procedure/scripts/state_data_imports_6d_HS.py
|
YangLiu928/NDP_Projects
|
d2ebfa7b95a0003481dde1361c6ab563ac94f2e6
|
[
"MIT"
] | null | null | null |
Python_Projects/Python_MySQL/FTD_SQL_stored_procedure/scripts/state_data_imports_6d_HS.py
|
YangLiu928/NDP_Projects
|
d2ebfa7b95a0003481dde1361c6ab563ac94f2e6
|
[
"MIT"
] | 12
|
2015-11-11T15:50:16.000Z
|
2015-12-15T19:05:57.000Z
|
Python_Projects/Python_MySQL/Foreign_Trade_Data_Pipe_Delimination/scripts/state_data_imports_6d_HS.py
|
YangLiu928/NDP_Projects
|
d2ebfa7b95a0003481dde1361c6ab563ac94f2e6
|
[
"MIT"
] | null | null | null |
import process_data
data_folder = '../data/state_data_imports_6d_HS/'
output_folder = '../output/state_data_imports_6d_HS/'
date = '0902'
process_data.process_ISTHS6(data_folder, output_folder, date)
print 'task completed'
| 22.6
| 61
| 0.79646
| 33
| 226
| 5
| 0.454545
| 0.133333
| 0.193939
| 0.218182
| 0.242424
| 0
| 0
| 0
| 0
| 0
| 0
| 0.033981
| 0.088496
| 226
| 9
| 62
| 25.111111
| 0.76699
| 0
| 0
| 0
| 0
| 0
| 0.380531
| 0.300885
| 0
| 0
| 0
| 0
| 0
| 0
| null | null | 0
| 0.5
| null | null | 0.166667
| 0
| 0
| 0
| null | 0
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 0
| 0
| 0
|
0
| 5
|
0b45600cbea9b460d6e80369c03fbcca2285b951
| 63
|
py
|
Python
|
jupyter/calysto_hy/__init__.py
|
rz4/MinoTauro
|
25515b13f61e8fa62d5ebf24ec9d22c2de021071
|
[
"MIT"
] | 6
|
2020-01-21T05:58:14.000Z
|
2022-01-20T16:30:27.000Z
|
jupyter/calysto_hy/__init__.py
|
rz4/HyTorch
|
25515b13f61e8fa62d5ebf24ec9d22c2de021071
|
[
"MIT"
] | null | null | null |
jupyter/calysto_hy/__init__.py
|
rz4/HyTorch
|
25515b13f61e8fa62d5ebf24ec9d22c2de021071
|
[
"MIT"
] | null | null | null |
from .kernel import CalystoHy
from .version import __version__
| 21
| 32
| 0.84127
| 8
| 63
| 6.125
| 0.625
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.126984
| 63
| 2
| 33
| 31.5
| 0.890909
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
0b716847c119f3dc83123324f74d1f9286762f76
| 29
|
py
|
Python
|
tests/__init__.py
|
avi-08/flask-app
|
2d05a889301d6918805d43a652b3752541e77f33
|
[
"MIT"
] | null | null | null |
tests/__init__.py
|
avi-08/flask-app
|
2d05a889301d6918805d43a652b3752541e77f33
|
[
"MIT"
] | null | null | null |
tests/__init__.py
|
avi-08/flask-app
|
2d05a889301d6918805d43a652b3752541e77f33
|
[
"MIT"
] | null | null | null |
def set_data(data):
pass
| 9.666667
| 20
| 0.655172
| 5
| 29
| 3.6
| 0.8
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.241379
| 29
| 2
| 21
| 14.5
| 0.818182
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.5
| false
| 0.5
| 0
| 0
| 0.5
| 0
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
| 0
|
0
| 5
|
0b71c4afc2c60484ea7bb2c7691b5385e83b5420
| 400
|
py
|
Python
|
slixmpp/plugins/xep_0092/__init__.py
|
anirudhrata/slixmpp
|
1fcee0e80a212eeb274d2f560e69099d8a61bf7f
|
[
"BSD-3-Clause"
] | 86
|
2016-07-04T13:26:02.000Z
|
2022-02-19T10:26:21.000Z
|
slixmpp/plugins/xep_0092/__init__.py
|
anirudhrata/slixmpp
|
1fcee0e80a212eeb274d2f560e69099d8a61bf7f
|
[
"BSD-3-Clause"
] | 10
|
2016-09-30T18:55:41.000Z
|
2020-05-01T14:22:47.000Z
|
slixmpp/plugins/xep_0092/__init__.py
|
anirudhrata/slixmpp
|
1fcee0e80a212eeb274d2f560e69099d8a61bf7f
|
[
"BSD-3-Clause"
] | 45
|
2016-09-30T18:48:41.000Z
|
2022-03-18T21:39:33.000Z
|
# Slixmpp: The Slick XMPP Library
# Copyright (C) 2010 Nathanael C. Fritz, Lance J.T. Stout
# This file is part of Slixmpp.
# See the file LICENSE for copying permission.
from slixmpp.plugins.base import register_plugin
from slixmpp.plugins.xep_0092 import stanza
from slixmpp.plugins.xep_0092.stanza import Version
from slixmpp.plugins.xep_0092.version import XEP_0092
register_plugin(XEP_0092)
| 28.571429
| 57
| 0.8075
| 63
| 400
| 5.015873
| 0.539683
| 0.110759
| 0.227848
| 0.199367
| 0.237342
| 0
| 0
| 0
| 0
| 0
| 0
| 0.068966
| 0.13
| 400
| 13
| 58
| 30.769231
| 0.83908
| 0.405
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.8
| 0
| 0.8
| 0
| 0
| 0
| 0
| null | 0
| 1
| 1
| 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
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
0b72c4d2a24dc097243e22bebe8f80944a9065c2
| 121
|
py
|
Python
|
backend/server/api/admin.py
|
jckw/notebin
|
53e0acdcdcb563541df2a78e2ab3e8c22c4cb91d
|
[
"MIT"
] | null | null | null |
backend/server/api/admin.py
|
jckw/notebin
|
53e0acdcdcb563541df2a78e2ab3e8c22c4cb91d
|
[
"MIT"
] | null | null | null |
backend/server/api/admin.py
|
jckw/notebin
|
53e0acdcdcb563541df2a78e2ab3e8c22c4cb91d
|
[
"MIT"
] | null | null | null |
from django.contrib import admin
from .models import Folder, Note
admin.site.register(Folder)
admin.site.register(Note)
| 20.166667
| 32
| 0.809917
| 18
| 121
| 5.444444
| 0.555556
| 0.183673
| 0.346939
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.099174
| 121
| 5
| 33
| 24.2
| 0.899083
| 0
| 0
| 0
| 0
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| 0
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| 0
| 0
| 0
| 1
| 0
| true
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| 0.5
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| 0.5
| 0
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| 0
| 0
| null | 0
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| 0
| 0
|
0
| 5
|
0b9d04bbb262a506b0ddef6195ad420cfb6aca1f
| 26
|
py
|
Python
|
arm_now/__init__.py
|
fr0zn/arm_now
|
7251c24ca3aefcc4e01c12a4d2bc980d9f6fbc28
|
[
"MIT"
] | 810
|
2017-05-31T09:34:42.000Z
|
2022-03-27T22:43:34.000Z
|
arm_now/__init__.py
|
fr0zn/arm_now
|
7251c24ca3aefcc4e01c12a4d2bc980d9f6fbc28
|
[
"MIT"
] | 46
|
2018-03-27T20:10:27.000Z
|
2022-02-19T20:26:47.000Z
|
arm_now/__init__.py
|
fr0zn/arm_now
|
7251c24ca3aefcc4e01c12a4d2bc980d9f6fbc28
|
[
"MIT"
] | 104
|
2017-05-31T08:31:29.000Z
|
2021-11-26T09:09:47.000Z
|
from .arm_now import main
| 13
| 25
| 0.807692
| 5
| 26
| 4
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
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| 0
| 0.153846
| 26
| 1
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| 26
| 0.909091
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| 1
| 0
| 0
| 0
|
0
| 5
|
0ba0f72548b2eafcecb400c12869bde20c49990a
| 177
|
py
|
Python
|
evkit/rl/algo/__init__.py
|
jozhang97/Side-tuning
|
dea345691fb7ee0230150fe56ddd644efdffa6ac
|
[
"MIT"
] | 56
|
2020-01-12T05:45:59.000Z
|
2022-03-17T15:04:15.000Z
|
evkit/rl/algo/__init__.py
|
jozhang97/Side-tuning
|
dea345691fb7ee0230150fe56ddd644efdffa6ac
|
[
"MIT"
] | 7
|
2019-12-16T21:58:34.000Z
|
2022-02-10T00:16:29.000Z
|
evkit/rl/algo/__init__.py
|
jozhang97/Side-tuning
|
dea345691fb7ee0230150fe56ddd644efdffa6ac
|
[
"MIT"
] | 2
|
2020-02-29T14:51:23.000Z
|
2020-03-07T03:23:27.000Z
|
from .a2c_acktr import A2C_ACKTR
from .ppo import PPO
from .ppo_replay import PPOReplay
from .deepq import QLearner
from .ppo_curiosity import PPOCuriosity, PPOReplayCuriosity
| 25.285714
| 59
| 0.841808
| 25
| 177
| 5.8
| 0.48
| 0.144828
| 0
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| 0
| 0
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| 0
| 0
| 0.012903
| 0.124294
| 177
| 6
| 60
| 29.5
| 0.922581
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| 1
| 0
| 1
| 0
|
0
| 5
|
0bb589ae12861fe47b0e547911f34e98f265d6ad
| 42
|
py
|
Python
|
tests/__init__.py
|
TheByteStuff/RemoteSyslog_Service
|
a46df0c561c9ed9b1e4b2e9ca458f13593883785
|
[
"MIT"
] | 6
|
2021-06-03T18:49:43.000Z
|
2021-09-19T12:40:31.000Z
|
tests/__init__.py
|
TheByteStuff/RemoteSyslog_Service
|
a46df0c561c9ed9b1e4b2e9ca458f13593883785
|
[
"MIT"
] | 2
|
2021-05-19T02:24:10.000Z
|
2021-06-29T14:47:15.000Z
|
tests/__init__.py
|
TheByteStuff/RemoteSyslog_Service
|
a46df0c561c9ed9b1e4b2e9ca458f13593883785
|
[
"MIT"
] | null | null | null |
"""Tests for remote_syslog integration."""
| 42
| 42
| 0.761905
| 5
| 42
| 6.2
| 1
| 0
| 0
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| 0.071429
| 42
| 1
| 42
| 42
| 0.794872
| 0.857143
| 0
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| null | true
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| null | null | null | 1
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| 0
|
0
| 5
|
e7ed9e7c3d86df8ff4bbf688222682f20b8584ce
| 168
|
py
|
Python
|
absentismo/admin.py
|
jjmartinr01/gauss3
|
1c71c44430e0f15fb2f3f83d32ad66bb1b7e3e94
|
[
"MIT"
] | null | null | null |
absentismo/admin.py
|
jjmartinr01/gauss3
|
1c71c44430e0f15fb2f3f83d32ad66bb1b7e3e94
|
[
"MIT"
] | null | null | null |
absentismo/admin.py
|
jjmartinr01/gauss3
|
1c71c44430e0f15fb2f3f83d32ad66bb1b7e3e94
|
[
"MIT"
] | null | null | null |
from django.contrib import admin
from absentismo.models import *
# Register your models here.
admin.site.register(ExpedienteAbsentismo)
admin.site.register(Actuacion)
| 24
| 41
| 0.827381
| 21
| 168
| 6.619048
| 0.619048
| 0.129496
| 0.244604
| 0
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| 0
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| 0
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| 0.095238
| 168
| 7
| 42
| 24
| 0.914474
| 0.154762
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| 0
| 0
|
0
| 5
|
f03190c2c6f15b1a1dd8cccba5c6a5d51068c971
| 332
|
py
|
Python
|
pyprojects/discrete-backprop/tf_assert.py
|
abhmul/projects-repo
|
6d3a8110ce69219e769e0e56d14fbe394f6389c6
|
[
"MIT"
] | null | null | null |
pyprojects/discrete-backprop/tf_assert.py
|
abhmul/projects-repo
|
6d3a8110ce69219e769e0e56d14fbe394f6389c6
|
[
"MIT"
] | null | null | null |
pyprojects/discrete-backprop/tf_assert.py
|
abhmul/projects-repo
|
6d3a8110ce69219e769e0e56d14fbe394f6389c6
|
[
"MIT"
] | null | null | null |
import tensorflow as tf
def is_signs(tensor):
tf.Assert(tf.reduce_all((tensor == 1) | (tensor == -1)), [tensor])
def is_signs_or_zero(tensor):
tf.Assert(tf.reduce_all((tensor == 1) | (tensor == -1) | (tensor == 0)), [tensor])
def is_binary(tensor):
tf.Assert(tf.reduce_all((tensor == 0) | (tensor == 1)), [tensor])
| 25.538462
| 86
| 0.623494
| 50
| 332
| 3.98
| 0.32
| 0.175879
| 0.326633
| 0.241206
| 0.60804
| 0.60804
| 0.60804
| 0.452261
| 0.452261
| 0.452261
| 0
| 0.025271
| 0.165663
| 332
| 13
| 87
| 25.538462
| 0.693141
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| 1
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| 0
| 0
| 1
| 0
|
0
| 5
|
f039f436203e073ec4a2509fa07cafbec9723386
| 40
|
py
|
Python
|
pug/dj/crawlnmine/crawlnmine/settings/dev.py
|
hobson/pug-dj
|
55678b08755a55366ce18e7d3b8ea8fa4491ab04
|
[
"MIT"
] | null | null | null |
pug/dj/crawlnmine/crawlnmine/settings/dev.py
|
hobson/pug-dj
|
55678b08755a55366ce18e7d3b8ea8fa4491ab04
|
[
"MIT"
] | 5
|
2021-09-07T23:53:24.000Z
|
2022-03-11T23:22:04.000Z
|
pug/dj/crawlnmine/crawlnmine/settings/dev.py
|
hobson/pug-dj
|
55678b08755a55366ce18e7d3b8ea8fa4491ab04
|
[
"MIT"
] | 1
|
2015-04-23T14:45:04.000Z
|
2015-04-23T14:45:04.000Z
|
from crawlnmine.settings.common import *
| 40
| 40
| 0.85
| 5
| 40
| 6.8
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
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| 0
| 0.075
| 40
| 1
| 40
| 40
| 0.918919
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| 0
| 1
| 0
| 0
| 0
|
0
| 5
|
f0697174d5823f541ace1b8d541201aa6159c526
| 58
|
py
|
Python
|
ecosystem/__init__.py
|
IceKhan13/ecosystem
|
3310043c343c634831f55aa5f9671bdea021740b
|
[
"Apache-2.0"
] | 13
|
2021-08-11T06:58:01.000Z
|
2022-02-01T12:23:51.000Z
|
ecosystem/__init__.py
|
IceKhan13/ecosystem
|
3310043c343c634831f55aa5f9671bdea021740b
|
[
"Apache-2.0"
] | 79
|
2021-08-09T20:57:33.000Z
|
2022-03-24T09:22:07.000Z
|
ecosystem/__init__.py
|
mickahell/ecosystem
|
ae6879f13df22c98f26f242feddb049a69895ef0
|
[
"Apache-2.0"
] | 7
|
2021-08-16T21:25:10.000Z
|
2022-03-22T15:32:43.000Z
|
"""Ecosystem main module."""
from .manager import Manager
| 19.333333
| 28
| 0.741379
| 7
| 58
| 6.142857
| 0.857143
| 0
| 0
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| 0
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| 0.12069
| 58
| 2
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| 29
| 0.843137
| 0.37931
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| null | 0
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| 0
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| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
f072f86c9151458a09975338fc3cebc1ff9456cf
| 131
|
py
|
Python
|
backend/test/test.py
|
wooshifu/Blog
|
a8ad6a7e1e1bb312b64f54414e5d945b73df5e1d
|
[
"MIT"
] | null | null | null |
backend/test/test.py
|
wooshifu/Blog
|
a8ad6a7e1e1bb312b64f54414e5d945b73df5e1d
|
[
"MIT"
] | 3
|
2021-05-07T11:38:25.000Z
|
2022-02-26T10:26:47.000Z
|
backend/test/test.py
|
wooshifu/Blog
|
a8ad6a7e1e1bb312b64f54414e5d945b73df5e1d
|
[
"MIT"
] | null | null | null |
from unittest import TestCase
class My(TestCase):
def setUp(self) -> None:
pass
def test_my(self):
pass
| 13.1
| 29
| 0.603053
| 17
| 131
| 4.588235
| 0.705882
| 0
| 0
| 0
| 0
| 0
| 0
| 0
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| 0
| 0
| 0
| 0.312977
| 131
| 9
| 30
| 14.555556
| 0.866667
| 0
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| 0.333333
| 0
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| false
| 0.333333
| 0.166667
| 0
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| null | 0
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| 1
| 0
| 0
| 1
| 0
|
0
| 5
|
f07a8bd47542c4702d524b2a97ca75ec1368d3b9
| 9,307
|
py
|
Python
|
profiling/company/company.py
|
PHFeres/sexta-do-python
|
b00545652e5c2a889aa6596e3000bde2e2e2e543
|
[
"MIT"
] | 5
|
2021-04-16T19:13:28.000Z
|
2022-03-10T18:54:37.000Z
|
profiling/company/company.py
|
PHFeres/sexta-do-python
|
b00545652e5c2a889aa6596e3000bde2e2e2e543
|
[
"MIT"
] | null | null | null |
profiling/company/company.py
|
PHFeres/sexta-do-python
|
b00545652e5c2a889aa6596e3000bde2e2e2e543
|
[
"MIT"
] | 4
|
2021-04-16T17:55:39.000Z
|
2021-09-23T21:26:01.000Z
|
"""
Company Class
"""
import pandas as pd
import numpy as np
from tqdm import tqdm
class Company:
"""
Company Class
"""
def __init__(self, num_representatives, range_and_commission_rate):
"""
Create a company with a certain number of employees and fixed commission rates.
Args:
num_representatives: (int) number of company representatives.
range_and_commission_rate: (list) list of tuples with ranges and commission values respectively.
"""
self.num_representatives = num_representatives
self.range_and_commission_rate = range_and_commission_rate
def calc_commission_rate(self, sale_percentage):
"""
This function returns the commission rate the employee
will earn based on their sales percentage.
Args:
sale_percentage: (float) sales percentage of a representatives.
Returns:
rate: (float) commission rate.
"""
for limit, percentage_rate in self.range_and_commission_rate:
if limit < sale_percentage:
rate = percentage_rate / 100
else:
rate = percentage_rate / 100
break
return rate
def financial_projections(self, sales_target_values, sales_target_prob,
average_percentage_to_target,
standard_deviation_percentage_to_target,
num_simulations=50):
"""
Creates financial projection for total comission, total sales and total sales target for the company.
Args:
sales_target_values: (list) List of target sales values.
sales_target_prob: (list) List with distribution of target sales values.
average_percentage_to_target: (float) Avarage value of sales percentage to the representatives.
standard_deviation_percentage_to_target: (float) Standard deviation of sales percentage to the repreentatives.
num_simulations: Number of simulation tests.
Returns:
projections: (Dataframe) Dataframe with total comission, total sales and total sales target.
"""
all_stats = []
for i in tqdm(range(num_simulations)):
# Choose random inputs for the sales targets and percent to target
sales_target = np.random.choice(sales_target_values,
self.num_representatives,
p=sales_target_prob)
pct_to_target = np.random.normal(average_percentage_to_target,
standard_deviation_percentage_to_target,
self.num_representatives).round(2)
# Build the dataframe based on the inputs and number of reps
df = pd.DataFrame(index=range(self.num_representatives),
data={'Pct_To_Target': pct_to_target,
'Sales_Target': sales_target})
# Back into the sales number using the percent to target rate
df['Sales'] = df['Pct_To_Target'] * df['Sales_Target']
# Determine the commissions rate and calculate it
df1 = pd.DataFrame(columns=["Commission_Rate", 'Commission_Amount'])
for j in range(len(df)):
commission_rate = self.calc_commission_rate(df['Pct_To_Target'][j])
commission_amount = commission_rate * df['Sales'][j]
df1.loc[j] = [commission_rate, commission_amount]
df = pd.concat([df, df1], axis=1)
# We want to track sales,commission amounts and sales targets over all the simulations
all_stats.append([df['Sales'].sum().round(0),
df['Commission_Amount'].sum().round(0),
df['Sales_Target'].sum().round(0)])
return pd.DataFrame.from_records(all_stats, columns=['Sales',
'Commission_Amount',
'Sales_Target'])
def financial_projections_1(self, sales_target_values, sales_target_prob,
average_percentage_to_target,
standard_deviation_percentage_to_target,
num_simulations=50):
"""
Creates financial projection for total comission, total sales and total sales target for the company.
Args:
sales_target_values: (list) List of target sales values.
sales_target_prob: (list) List with distribution of target sales values.
average_percentage_to_target: (float) Avarage value of sales percentage to the representatives.
standard_deviation_percentage_to_target: (float) Standard deviation of sales percentage to the repreentatives.
num_simulations: Number of simulation tests.
Returns:
projections: (Dataframe) Dataframe with total comission, total sales and total sales target.
"""
all_stats = []
for i in tqdm(range(num_simulations)):
# Choose random inputs for the sales targets and percent to target
sales_target = np.random.choice(sales_target_values,
self.num_representatives,
p=sales_target_prob)
pct_to_target = np.random.normal(average_percentage_to_target,
standard_deviation_percentage_to_target,
self.num_representatives).round(2)
# Build the dataframe based on the inputs and number of reps
df = pd.DataFrame(index=range(self.num_representatives),
data={'Pct_To_Target': pct_to_target,
'Sales_Target': sales_target})
# Back into the sales number using the percent to target rate
df['Sales'] = df['Pct_To_Target'] * df['Sales_Target']
# Determine the commissions rate and calculate it
df['Commission_Rate'] = df['Pct_To_Target'].apply(self.calc_commission_rate)
df['Commission_Amount'] = df['Commission_Rate'] * df['Sales']
# We want to track sales,commission amounts and sales targets over all the simulations
all_stats.append([df['Sales'].sum().round(0),
df['Commission_Amount'].sum().round(0),
df['Sales_Target'].sum().round(0)])
return pd.DataFrame.from_records(all_stats, columns=['Sales',
'Commission_Amount',
'Sales_Target'])
def financial_projections_2(self, sales_target_values, sales_target_prob,
average_percentage_to_target,
standard_deviation_percentage_to_target,
num_simulations=50):
"""
Creates financial projection for total comission, total sales and total sales target for the company.
Args:
sales_target_values: (list) List of target sales values.
sales_target_prob: (list) List with distribution of target sales values.
average_percentage_to_target: (float) Avarage value of sales percentage to the representatives.
standard_deviation_percentage_to_target: (float) Standard deviation of sales percentage to the repreentatives.
num_simulations: Number of simulation tests.
Returns:
projections: (Dataframe) Dataframe with total comission, total sales and total sales target.
"""
all_stats = np.zeros((num_simulations, 3))
for i in tqdm(range(num_simulations)):
# Choose random inputs for the sales targets and percent to target
sales_target = np.random.choice(sales_target_values,
self.num_representatives,
p=sales_target_prob)
pct_to_target = np.random.normal(average_percentage_to_target,
standard_deviation_percentage_to_target,
self.num_representatives).round(2)
# Build the dataframe based on the inputs and number of reps
sales = sales_target * pct_to_target
# Determine the commissions rate and calculate it
commission_rate = np.array([self.calc_commission_rate(xi) for xi in pct_to_target])
commission_amount = commission_rate * sales
# We want to track sales,commission amounts and sales targets over all the simulations
all_stats[i, :] = [sales.sum(), commission_amount.sum(), sales_target.sum()]
return pd.DataFrame.from_records(all_stats, columns=['Sales',
'Commission_Amount',
'Sales_Target'])
| 49.243386
| 122
| 0.582572
| 978
| 9,307
| 5.306748
| 0.130879
| 0.084778
| 0.062428
| 0.043353
| 0.796146
| 0.765703
| 0.755299
| 0.755299
| 0.746243
| 0.746243
| 0
| 0.004652
| 0.353282
| 9,307
| 188
| 123
| 49.505319
| 0.857618
| 0.348985
| 0
| 0.662791
| 0
| 0
| 0.069924
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.05814
| false
| 0
| 0.034884
| 0
| 0.151163
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
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| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 5
|
b2bd6a5577430ff146a1e167055596f1251fc074
| 115
|
py
|
Python
|
python/w3school/import.py
|
mp5maker/library
|
b4d2eea70ae0da9d917285569031edfb4d8ab9fc
|
[
"MIT"
] | null | null | null |
python/w3school/import.py
|
mp5maker/library
|
b4d2eea70ae0da9d917285569031edfb4d8ab9fc
|
[
"MIT"
] | 23
|
2020-08-15T15:18:32.000Z
|
2022-02-26T13:49:05.000Z
|
python/w3school/import.py
|
mp5maker/library
|
b4d2eea70ae0da9d917285569031edfb4d8ab9fc
|
[
"MIT"
] | null | null | null |
from modules.settings import configuration
""" Modules is the folder, settings is the file"""
print(configuration)
| 28.75
| 50
| 0.791304
| 15
| 115
| 6.066667
| 0.666667
| 0.10989
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.121739
| 115
| 3
| 51
| 38.333333
| 0.90099
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| 1
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| true
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| 0.5
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| 0
| 0
| 0
| 0
| 0
| 0
| 1
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| 0
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| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 1
|
0
| 5
|
b2d44c7687fd2e08d99072d23c1a65f94bec0f39
| 11
|
py
|
Python
|
ledfx/__init__.py
|
danhartfiction/LedFx
|
eaf40ab180ef7e8f4f769193b35b3ffd5fe2a340
|
[
"MIT"
] | 419
|
2018-07-13T11:45:14.000Z
|
2022-02-10T05:23:00.000Z
|
ledfx/__init__.py
|
carlonoelle/LedFx
|
7aa28855ef5b0491b7ca34ed635da7ba38083daf
|
[
"MIT"
] | 131
|
2018-07-20T09:46:26.000Z
|
2022-01-09T22:22:30.000Z
|
ledfx/__init__.py
|
carlonoelle/LedFx
|
7aa28855ef5b0491b7ca34ed635da7ba38083daf
|
[
"MIT"
] | 122
|
2018-07-21T17:01:18.000Z
|
2022-02-10T17:09:12.000Z
|
"""ledfx"""
| 11
| 11
| 0.454545
| 1
| 11
| 5
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 11
| 1
| 11
| 11
| 0.454545
| 0.454545
| 0
| null | 0
| null | 0
| 0
| null | 0
| 0
| 0
| null | 1
| null | true
| 0
| 0
| null | null | null | 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
|
0
| 5
|
b2fc6a496aed78b8951bbd09c45855670983c74a
| 265
|
py
|
Python
|
app/api/__init__.py
|
felbinger/FlaskBasic
|
803fc5b07638e7d85eddccd00ca20567e57519f0
|
[
"MIT"
] | 2
|
2019-12-18T17:45:52.000Z
|
2020-04-21T12:45:32.000Z
|
app/api/__init__.py
|
felbinger/FlaskBasic
|
803fc5b07638e7d85eddccd00ca20567e57519f0
|
[
"MIT"
] | null | null | null |
app/api/__init__.py
|
felbinger/FlaskBasic
|
803fc5b07638e7d85eddccd00ca20567e57519f0
|
[
"MIT"
] | null | null | null |
from .user import User, UserResource, VerificationResource, ResetResource
from .totp import TOTPResource
from .role import Role, RoleResource
from .authentication import AuthResource, RefreshResource, require_admin, require_token
from .upload import UploadResource
| 44.166667
| 87
| 0.85283
| 29
| 265
| 7.724138
| 0.62069
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.101887
| 265
| 5
| 88
| 53
| 0.941176
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
65036d460bdf81fce390ad01182db3eb95ee5f1b
| 443
|
py
|
Python
|
pyta/overlays/donchian_channels.py
|
gslinger/pyta
|
d69cde971d43ef813c0bb96ce97bc7b4a22baf42
|
[
"MIT"
] | 1
|
2021-10-10T08:00:21.000Z
|
2021-10-10T08:00:21.000Z
|
pyta/overlays/donchian_channels.py
|
gslinger/pyta
|
d69cde971d43ef813c0bb96ce97bc7b4a22baf42
|
[
"MIT"
] | null | null | null |
pyta/overlays/donchian_channels.py
|
gslinger/pyta
|
d69cde971d43ef813c0bb96ce97bc7b4a22baf42
|
[
"MIT"
] | null | null | null |
import pandas as pd
#
from pyta.helper import highest, lowest
# TODO merge?
# TODO docstring
def donchian_channel_lower(l: pd.Series, n: int = 20) -> pd.Series:
return lowest(l, n)
def donchian_channel_upper(h: pd.Series, n: int = 20) -> pd.Series:
return highest(h, n)
def donchian_channel_basis(h: pd.Series, l: pd.Series, n: int = 20) -> pd.Series:
return (donchian_channel_upper(h, n) + donchian_channel_lower(l, n)) / 2
| 24.611111
| 81
| 0.69526
| 73
| 443
| 4.082192
| 0.356164
| 0.187919
| 0.181208
| 0.120805
| 0.288591
| 0.288591
| 0.288591
| 0.288591
| 0.194631
| 0
| 0
| 0.019126
| 0.173815
| 443
| 17
| 82
| 26.058824
| 0.795082
| 0.058691
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.058824
| 0
| 1
| 0.375
| false
| 0
| 0.25
| 0.375
| 1
| 0
| 0
| 0
| 0
| null | 0
| 1
| 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
| 1
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 1
| 0
|
0
| 5
|
6530c8216eb758933654411cb4b1c2da8abd66af
| 163
|
py
|
Python
|
torchmeta/utils/__init__.py
|
imkevinkuo/PMAML-ECAI20
|
504c14f121a50991f37a692a9be0eb181f28dfc7
|
[
"MIT"
] | 1
|
2022-03-03T20:29:39.000Z
|
2022-03-03T20:29:39.000Z
|
torchmeta/utils/__init__.py
|
imkevinkuo/PMAML-ECAI20
|
504c14f121a50991f37a692a9be0eb181f28dfc7
|
[
"MIT"
] | null | null | null |
torchmeta/utils/__init__.py
|
imkevinkuo/PMAML-ECAI20
|
504c14f121a50991f37a692a9be0eb181f28dfc7
|
[
"MIT"
] | 1
|
2022-03-05T21:21:58.000Z
|
2022-03-05T21:21:58.000Z
|
from torchmeta.utils import data
from torchmeta.utils.gradient_based import gradient_update_parameters
__all__ = [
'data',
'gradient_update_parameters'
]
| 20.375
| 69
| 0.791411
| 19
| 163
| 6.315789
| 0.526316
| 0.216667
| 0.3
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.141104
| 163
| 7
| 70
| 23.285714
| 0.857143
| 0
| 0
| 0
| 0
| 0
| 0.184049
| 0.159509
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.333333
| 0
| 0.333333
| 0
| 1
| 0
| 0
| null | 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
|
0
| 5
|
e8e409f8139ed4883dbea53d1347daa5961e4b70
| 29
|
py
|
Python
|
app/traveller_app/career_driver.py
|
jango2106/traveller
|
5b046dd5e20e49716953b79c98e41d055c7114ec
|
[
"Apache-2.0"
] | null | null | null |
app/traveller_app/career_driver.py
|
jango2106/traveller
|
5b046dd5e20e49716953b79c98e41d055c7114ec
|
[
"Apache-2.0"
] | 6
|
2021-01-02T00:33:50.000Z
|
2022-02-19T07:05:46.000Z
|
app/traveller_app/career_driver.py
|
jango2106/traveller
|
5b046dd5e20e49716953b79c98e41d055c7114ec
|
[
"Apache-2.0"
] | null | null | null |
class CareerDriver:
pass
| 9.666667
| 19
| 0.724138
| 3
| 29
| 7
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.241379
| 29
| 2
| 20
| 14.5
| 0.954545
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0.5
| 0
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| 0.5
| 0
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| 0
| 0
| 0
|
0
| 5
|
e8e73e3753c5cf5c92c975321f7b4cd3e2e12aaf
| 57
|
py
|
Python
|
sggm/data/emnist/__init__.py
|
pierresegonne/SGGM
|
46663a722384b4ee2b3358261d6eb626a16ca51a
|
[
"Apache-2.0"
] | 4
|
2020-10-27T13:56:54.000Z
|
2021-05-23T19:16:15.000Z
|
sggm/data/emnist/__init__.py
|
pierresegonne/SGGM
|
46663a722384b4ee2b3358261d6eb626a16ca51a
|
[
"Apache-2.0"
] | 16
|
2021-03-29T09:59:56.000Z
|
2022-03-12T01:00:38.000Z
|
sggm/data/emnist/__init__.py
|
pierresegonne/SGGM
|
46663a722384b4ee2b3358261d6eb626a16ca51a
|
[
"Apache-2.0"
] | null | null | null |
from sggm.data.emnist.datamodule import EMNISTDataModule
| 28.5
| 56
| 0.877193
| 7
| 57
| 7.142857
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.070175
| 57
| 1
| 57
| 57
| 0.943396
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| 0
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| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
333f01c1602576b7bc9d96bf99292878cc66e884
| 96
|
py
|
Python
|
datavalidation/libraries/marshmallow/__init__.py
|
lifus/data-validation-benchmark
|
fca70230da3cb9e60ac4014b4a4c7c77b78027da
|
[
"Apache-2.0"
] | null | null | null |
datavalidation/libraries/marshmallow/__init__.py
|
lifus/data-validation-benchmark
|
fca70230da3cb9e60ac4014b4a4c7c77b78027da
|
[
"Apache-2.0"
] | null | null | null |
datavalidation/libraries/marshmallow/__init__.py
|
lifus/data-validation-benchmark
|
fca70230da3cb9e60ac4014b4a4c7c77b78027da
|
[
"Apache-2.0"
] | null | null | null |
from .wrapper import MarshmallowWrapper as Wrapper
from .schemas import INSTANCES as VALIDATORS
| 32
| 50
| 0.854167
| 12
| 96
| 6.833333
| 0.666667
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.125
| 96
| 2
| 51
| 48
| 0.97619
| 0
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| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
334c540a23d76cbcc8a5425b0135296ff6366fcd
| 49,120
|
py
|
Python
|
appengine/monorail/api/v3/api_proto/users_prpc_pb2.py
|
fknittel/git-retry-build
|
4d57dd6e8b7567daeb24b55f66bc5becd3d459f3
|
[
"BSD-3-Clause"
] | null | null | null |
appengine/monorail/api/v3/api_proto/users_prpc_pb2.py
|
fknittel/git-retry-build
|
4d57dd6e8b7567daeb24b55f66bc5becd3d459f3
|
[
"BSD-3-Clause"
] | 4
|
2022-03-17T18:58:21.000Z
|
2022-03-17T18:58:22.000Z
|
appengine/monorail/api/v3/api_proto/users_prpc_pb2.py
|
fknittel/git-retry-build
|
4d57dd6e8b7567daeb24b55f66bc5becd3d459f3
|
[
"BSD-3-Clause"
] | null | null | null |
# Generated by the pRPC protocol buffer compiler plugin. DO NOT EDIT!
# source: api/v3/api_proto/users.proto
import base64
import zlib
from google.protobuf import descriptor_pb2
# Includes description of the api/v3/api_proto/users.proto and all of its transitive
# dependencies. Includes source code info.
FILE_DESCRIPTOR_SET = descriptor_pb2.FileDescriptorSet()
FILE_DESCRIPTOR_SET.ParseFromString(zlib.decompress(base64.b64decode(
'eJzkvQt4ZMdxHsozD2BwFgsczC5JcMjVHg4fCyzx2F1SD+6KorEAdgkKCyADLClKEcGDwQEw3M'
'HMeM7MgiBFW4qvrUix/dmxKFHWg7Yk26IsW9HDurbvlWVf29ex9YVO7nXs5JOtKH5JsWJFDztR'
'HPn61l9d3afPDPZBinSSe2V/XEydPnWqq6urq6urqt1fudO9KWhUJi/eOUn/rDaa9VZ9sh2FzW'
'iC/87v267X6s2gUp24eGfh8Ga9vlkN0XRyoxJW11fXwq3gYqXeVK0LN1gNmmFUbzfLoTy6Zc/P'
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'AdDju+M9J3uvA3UwfdPFEwUW6utTcnyvXtSbT+4lSqxO2K97kHTwet8pagiTSeY24WzyNClL4C'
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'uj6s/h+Lkbhg')))
_INDEX = {
f.name: {
'descriptor': f,
'services': {s.name: s for s in f.service},
}
for f in FILE_DESCRIPTOR_SET.file
}
UsersServiceDescription = {
'file_descriptor_set': FILE_DESCRIPTOR_SET,
'file_descriptor': _INDEX[u'api/v3/api_proto/users.proto']['descriptor'],
'service_descriptor': _INDEX[u'api/v3/api_proto/users.proto']['services'][u'Users'],
}
| 78.717949
| 86
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| 0.001803
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| 0.903326
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| false
| 0
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| 0
| 0.004886
| 0
| 0
| 0
| 1
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
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| 0
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| 1
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 5
|
335cebb683406b05c650663b988913feac824b7a
| 6,779
|
py
|
Python
|
tests/test_dice_interface/test_explainer_base.py
|
soundarya98/DiCE
|
44705b87de22bb6ce20f0b10ccb1d5b5586f0ff6
|
[
"MIT"
] | null | null | null |
tests/test_dice_interface/test_explainer_base.py
|
soundarya98/DiCE
|
44705b87de22bb6ce20f0b10ccb1d5b5586f0ff6
|
[
"MIT"
] | null | null | null |
tests/test_dice_interface/test_explainer_base.py
|
soundarya98/DiCE
|
44705b87de22bb6ce20f0b10ccb1d5b5586f0ff6
|
[
"MIT"
] | null | null | null |
import pandas as pd
import pytest
from dice_ml.utils.exception import UserConfigValidationException
from dice_ml.explainer_interfaces.explainer_base import ExplainerBase
class TestExplainerBaseBinaryClassification:
def _verify_feature_importance(self, feature_importance):
if feature_importance is not None:
for key in feature_importance:
assert feature_importance[key] >= 0.0 and feature_importance[key] <= 1.0
@pytest.mark.parametrize("desired_class, binary_classification_exp_object",
[(1, 'random'), (1, 'genetic'), (1, 'kdtree')],
indirect=['binary_classification_exp_object'])
def test_zero_totalcfs(self, desired_class, binary_classification_exp_object, sample_custom_query_1):
exp = binary_classification_exp_object # explainer object
with pytest.raises(UserConfigValidationException):
exp.generate_counterfactuals(
query_instances=[sample_custom_query_1],
total_CFs=0,
desired_class=desired_class)
@pytest.mark.parametrize("desired_class, binary_classification_exp_object",
[(1, 'random')],
indirect=['binary_classification_exp_object'])
def test_local_feature_importance(self, desired_class, binary_classification_exp_object,
sample_custom_query_1, sample_counterfactual_example_dummy):
exp = binary_classification_exp_object # explainer object
sample_custom_query = pd.concat([sample_custom_query_1, sample_custom_query_1])
cf_explanations = exp.generate_counterfactuals(
query_instances=sample_custom_query,
total_CFs=15,
desired_class=desired_class)
cf_explanations.cf_examples_list[0].final_cfs_df = sample_counterfactual_example_dummy.copy()
cf_explanations.cf_examples_list[0].final_cfs_df_sparse = sample_counterfactual_example_dummy.copy()
cf_explanations.cf_examples_list[0].final_cfs_df.drop([0, 1, 2], inplace=True)
cf_explanations.cf_examples_list[0].final_cfs_df_sparse.drop([0, 1, 2], inplace=True)
cf_explanations.cf_examples_list[1].final_cfs_df = sample_counterfactual_example_dummy.copy()
cf_explanations.cf_examples_list[1].final_cfs_df_sparse = sample_counterfactual_example_dummy.copy()
cf_explanations.cf_examples_list[1].final_cfs_df.drop([0], inplace=True)
cf_explanations.cf_examples_list[1].final_cfs_df_sparse.drop([0], inplace=True)
local_importances = exp.local_feature_importance(
query_instances=None,
cf_examples_list=cf_explanations.cf_examples_list)
for local_importance in local_importances.local_importance:
self._verify_feature_importance(local_importance)
@pytest.mark.parametrize("desired_class, binary_classification_exp_object",
[(1, 'random')],
indirect=['binary_classification_exp_object'])
def test_global_feature_importance(self, desired_class, binary_classification_exp_object,
sample_custom_query_10, sample_counterfactual_example_dummy):
exp = binary_classification_exp_object # explainer object
cf_explanations = exp.generate_counterfactuals(
query_instances=sample_custom_query_10,
total_CFs=15,
desired_class=desired_class)
cf_explanations.cf_examples_list[0].final_cfs_df = sample_counterfactual_example_dummy.copy()
cf_explanations.cf_examples_list[0].final_cfs_df_sparse = sample_counterfactual_example_dummy.copy()
cf_explanations.cf_examples_list[0].final_cfs_df.drop([0, 1, 2, 3, 4], inplace=True)
cf_explanations.cf_examples_list[0].final_cfs_df_sparse.drop([0, 1, 2, 3, 4], inplace=True)
for index in range(1, len(cf_explanations.cf_examples_list)):
cf_explanations.cf_examples_list[index].final_cfs_df = sample_counterfactual_example_dummy.copy()
cf_explanations.cf_examples_list[index].final_cfs_df_sparse = sample_counterfactual_example_dummy.copy()
global_importance = exp.global_feature_importance(
query_instances=None,
cf_examples_list=cf_explanations.cf_examples_list)
self._verify_feature_importance(global_importance.summary_importance)
@pytest.mark.parametrize("desired_class, binary_classification_exp_object_out_of_order",
[(1, 'random'), (1, 'genetic'), (1, 'kdtree')],
indirect=['binary_classification_exp_object_out_of_order'])
def test_columns_out_of_order(self, desired_class, binary_classification_exp_object_out_of_order, sample_custom_query_1):
exp = binary_classification_exp_object_out_of_order # explainer object
exp._generate_counterfactuals(
query_instance=sample_custom_query_1,
total_CFs=0,
desired_class=desired_class,
desired_range=None,
permitted_range=None,
features_to_vary='all')
class TestExplainerBaseMultiClassClassification:
@pytest.mark.parametrize("desired_class, multi_classification_exp_object",
[(1, 'random'), (1, 'genetic'), (1, 'kdtree')],
indirect=['multi_classification_exp_object'])
def test_zero_totalcfs(self, desired_class, multi_classification_exp_object, sample_custom_query_1):
exp = multi_classification_exp_object # explainer object
with pytest.raises(UserConfigValidationException):
exp.generate_counterfactuals(
query_instances=[sample_custom_query_1],
total_CFs=0,
desired_class=desired_class)
class TestExplainerBaseRegression:
@pytest.mark.parametrize("desired_class, regression_exp_object",
[(1, 'random'), (1, 'genetic'), (1, 'kdtree')],
indirect=['regression_exp_object'])
def test_zero_totalcfs(self, desired_class, regression_exp_object, sample_custom_query_1):
exp = regression_exp_object # explainer object
with pytest.raises(UserConfigValidationException):
exp.generate_counterfactuals(
query_instances=[sample_custom_query_1],
total_CFs=0,
desired_class=desired_class)
class TestExplainerBase:
def test_instantiating_explainer_base(self, public_data_object):
with pytest.raises(TypeError):
ExplainerBase(data_interface=public_data_object)
| 52.960938
| 125
| 0.691105
| 753
| 6,779
| 5.759628
| 0.138114
| 0.066405
| 0.106064
| 0.094074
| 0.77496
| 0.747982
| 0.741757
| 0.729306
| 0.712474
| 0.644916
| 0
| 0.013828
| 0.231893
| 6,779
| 127
| 126
| 53.377953
| 0.81909
| 0.014899
| 0
| 0.441176
| 0
| 0
| 0.084995
| 0.057862
| 0
| 0
| 0
| 0
| 0.009804
| 1
| 0.078431
| false
| 0
| 0.147059
| 0
| 0.264706
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 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
|
0
| 5
|
335d5095ff4aa34eb7f50384443224f213167191
| 48
|
py
|
Python
|
unasync_cli/__main__.py
|
leynier/unasync-cli
|
19e5b6a20f230587a25e6bcac2c56b1765fc2e35
|
[
"MIT"
] | 1
|
2021-10-21T00:53:47.000Z
|
2021-10-21T00:53:47.000Z
|
unasync_cli/__main__.py
|
leynier/unasync-cli
|
19e5b6a20f230587a25e6bcac2c56b1765fc2e35
|
[
"MIT"
] | 1
|
2021-10-21T02:47:06.000Z
|
2021-10-21T02:47:06.000Z
|
unasync_cli/__main__.py
|
leynier/unasync-cli
|
19e5b6a20f230587a25e6bcac2c56b1765fc2e35
|
[
"MIT"
] | null | null | null |
from .main import app
app(prog_name="unasync")
| 12
| 24
| 0.75
| 8
| 48
| 4.375
| 0.875
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.125
| 48
| 3
| 25
| 16
| 0.833333
| 0
| 0
| 0
| 0
| 0
| 0.145833
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.5
| 0
| 0.5
| 0
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 5
|
33708cd0a0f4292850286618aea638f4eb35c294
| 132
|
py
|
Python
|
metrics_tools/endpoint_base.py
|
Jonnyblacklabel/metrics_tools
|
87634e22c49aaf0c3b767c94126248e640efc1cd
|
[
"MIT"
] | null | null | null |
metrics_tools/endpoint_base.py
|
Jonnyblacklabel/metrics_tools
|
87634e22c49aaf0c3b767c94126248e640efc1cd
|
[
"MIT"
] | null | null | null |
metrics_tools/endpoint_base.py
|
Jonnyblacklabel/metrics_tools
|
87634e22c49aaf0c3b767c94126248e640efc1cd
|
[
"MIT"
] | null | null | null |
class BaseEndpoint():
def __repr__(self):
return f'<metrics.tools Endpoint [{self.endpoint}]>'
if __name__ == '__main__':
pass
| 18.857143
| 54
| 0.704545
| 16
| 132
| 5.0625
| 0.875
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.136364
| 132
| 7
| 55
| 18.857143
| 0.710526
| 0
| 0
| 0
| 0
| 0
| 0.37594
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.2
| false
| 0.2
| 0
| 0.2
| 0.6
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 1
| 0
|
0
| 5
|
682ae20e0a3cbd003aee4509451f2cc9efee9503
| 96
|
py
|
Python
|
python/fastcampus_python_all_in_one/1.python_basic/section4.py
|
RollLife/oddmentsLabs
|
82ee4d2413edc153a89f31a7a70328949cb069a5
|
[
"MIT"
] | null | null | null |
python/fastcampus_python_all_in_one/1.python_basic/section4.py
|
RollLife/oddmentsLabs
|
82ee4d2413edc153a89f31a7a70328949cb069a5
|
[
"MIT"
] | null | null | null |
python/fastcampus_python_all_in_one/1.python_basic/section4.py
|
RollLife/oddmentsLabs
|
82ee4d2413edc153a89f31a7a70328949cb069a5
|
[
"MIT"
] | null | null | null |
# list
a = 'orange'
print(a[::-1])
print(a[1:4:2])
b = [1,2,3,34,5, 1]
print(b.count(1))
| 6.857143
| 19
| 0.489583
| 22
| 96
| 2.136364
| 0.545455
| 0.255319
| 0.297872
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.155844
| 0.197917
| 96
| 13
| 20
| 7.384615
| 0.454545
| 0.041667
| 0
| 0
| 0
| 0
| 0.066667
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0
| 0
| 0
| 0.6
| 1
| 0
| 0
| null | 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
|
0
| 5
|
68529c94b99f52dcfc4af7e84dfb3c9335491681
| 160
|
py
|
Python
|
tests/test_TypewriterPrint.py
|
radroid/typerwriter-effect
|
586b7949b42e125950b991304006a198449f82fc
|
[
"MIT"
] | 1
|
2020-07-24T06:39:52.000Z
|
2020-07-24T06:39:52.000Z
|
tests/test_TypewriterPrint.py
|
radroid/typerwriter-effect
|
586b7949b42e125950b991304006a198449f82fc
|
[
"MIT"
] | null | null | null |
tests/test_TypewriterPrint.py
|
radroid/typerwriter-effect
|
586b7949b42e125950b991304006a198449f82fc
|
[
"MIT"
] | null | null | null |
from TypewriterPrint import TypewriterPrint as tp
import pytest
def test_speed_error():
with pytest.raises(UserWarning):
tp.print_tw("hi", 21000)
| 20
| 49
| 0.74375
| 21
| 160
| 5.52381
| 0.809524
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.037879
| 0.175
| 160
| 7
| 50
| 22.857143
| 0.840909
| 0
| 0
| 0
| 0
| 0
| 0.0125
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.2
| true
| 0
| 0.4
| 0
| 0.6
| 0.2
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
687a97f763147fe67a32b559ff60663ec1b85519
| 675
|
py
|
Python
|
button.py
|
geraldzm/Connect4
|
cd025d93352bdab04261b49c33abc96f4dc289ec
|
[
"MIT"
] | null | null | null |
button.py
|
geraldzm/Connect4
|
cd025d93352bdab04261b49c33abc96f4dc289ec
|
[
"MIT"
] | null | null | null |
button.py
|
geraldzm/Connect4
|
cd025d93352bdab04261b49c33abc96f4dc289ec
|
[
"MIT"
] | null | null | null |
from gameObject import GameObject
from pygame import Rect
# Maneja todos los botones
class Button(GameObject):
def __init__(self, x, y, width, height, icon=None):
super().__init__(x, y, icon)
self._rect = Rect(x, y, width, height)
self.width = width
self.height = height
# E: poitn(x,y)
# S: boolean
# D: true si x, y estan dentro de el rectangulo
def inRect(self, point):
return self._rect.collidepoint(point)
# D: si click entonces pasa a este metodo
def clicked(self):
pass
# S: Rect
# D: retorna el rectangulo que compone el boton
def getRect(self):
return self._rect
| 23.275862
| 55
| 0.626667
| 95
| 675
| 4.336842
| 0.526316
| 0.024272
| 0.033981
| 0.063107
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.281481
| 675
| 28
| 56
| 24.107143
| 0.849485
| 0.28
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.035714
| 0
| 1
| 0.285714
| false
| 0.071429
| 0.142857
| 0.142857
| 0.642857
| 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
| 1
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 1
| 0
|
0
| 5
|
6881d17ed6f544c4df8b6c7b700a273b5463afa9
| 76
|
py
|
Python
|
aas_core_codegen/xsd/__init__.py
|
aas-core-works/aas-core-codegen
|
afec2cf363b6cb69816e7724a2b58626e2165869
|
[
"MIT"
] | 5
|
2021-12-29T12:55:34.000Z
|
2022-03-01T17:57:21.000Z
|
aas_core_codegen/xsd/__init__.py
|
aas-core-works/aas-core-codegen
|
afec2cf363b6cb69816e7724a2b58626e2165869
|
[
"MIT"
] | 10
|
2021-12-29T02:15:55.000Z
|
2022-03-09T11:04:22.000Z
|
aas_core_codegen/xsd/__init__.py
|
aas-core-works/aas-core-codegen
|
afec2cf363b6cb69816e7724a2b58626e2165869
|
[
"MIT"
] | 2
|
2021-12-29T01:42:12.000Z
|
2022-02-15T13:46:33.000Z
|
"""Generate XML Schema Definition (XSD) corresponding to the meta-model."""
| 38
| 75
| 0.75
| 10
| 76
| 5.7
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.118421
| 76
| 1
| 76
| 76
| 0.850746
| 0.907895
| 0
| null | 1
| null | 0
| 0
| null | 0
| 0
| 0
| null | 1
| null | true
| 0
| 0
| null | null | null | 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 0
| 0
| 1
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
|
0
| 5
|
d7a3595b02463b831ebe47d7035960d0cd4dc1d1
| 77
|
py
|
Python
|
Step1_Training_MSI_MSS/__init__.py
|
Gaskell-1206/MSI_vs_MSS_Classification
|
be6fd8a6961624367b2bb0e1299219e940f6f418
|
[
"MIT"
] | null | null | null |
Step1_Training_MSI_MSS/__init__.py
|
Gaskell-1206/MSI_vs_MSS_Classification
|
be6fd8a6961624367b2bb0e1299219e940f6f418
|
[
"MIT"
] | null | null | null |
Step1_Training_MSI_MSS/__init__.py
|
Gaskell-1206/MSI_vs_MSS_Classification
|
be6fd8a6961624367b2bb0e1299219e940f6f418
|
[
"MIT"
] | null | null | null |
from .train_tile_level_classification import MSI_MSS_Module, MSI_MSS_dataset
| 38.5
| 76
| 0.909091
| 12
| 77
| 5.25
| 0.833333
| 0.190476
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.064935
| 77
| 1
| 77
| 77
| 0.875
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
d7cc26e8f812fe941665c27fb5eb9c83596d8554
| 217
|
py
|
Python
|
ignition/templating/__init__.py
|
sonali-pitre/ignition
|
03c4bc7eac53159a1c7dbe2519eb2e366bd82304
|
[
"Apache-2.0"
] | 1
|
2019-09-02T15:23:08.000Z
|
2019-09-02T15:23:08.000Z
|
ignition/templating/__init__.py
|
sonali-pitre/ignition
|
03c4bc7eac53159a1c7dbe2519eb2e366bd82304
|
[
"Apache-2.0"
] | 62
|
2019-09-16T14:51:32.000Z
|
2020-07-08T13:28:50.000Z
|
ignition/templating/__init__.py
|
sonali-pitre/ignition
|
03c4bc7eac53159a1c7dbe2519eb2e366bd82304
|
[
"Apache-2.0"
] | 4
|
2021-08-17T14:38:54.000Z
|
2022-02-09T14:33:57.000Z
|
from .jinja_template import JinjaTemplate
from .resource_context_builder import ResourceContextBuilder, SYSTEM_PROPERTIES_KEY, DEPLOYMENT_LOCATION_KEY
from .exceptions import TemplatingError
from .syntax import Syntax
| 54.25
| 108
| 0.894009
| 25
| 217
| 7.48
| 0.68
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.078341
| 217
| 4
| 109
| 54.25
| 0.935
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
d7de9ae8be43687f4bf12456aefce1a12b5c9bb5
| 65
|
py
|
Python
|
ytcomment_trends/controllers/google_api/__init__.py
|
386jp/ytcomment_trends
|
e924e3ebe71e67c40bac5f67de2927716d5bc0ac
|
[
"MIT"
] | null | null | null |
ytcomment_trends/controllers/google_api/__init__.py
|
386jp/ytcomment_trends
|
e924e3ebe71e67c40bac5f67de2927716d5bc0ac
|
[
"MIT"
] | 3
|
2022-02-08T02:28:42.000Z
|
2022-02-10T03:30:57.000Z
|
ytcomment_trends/controllers/google_api/__init__.py
|
386jp/ytcomment_trends
|
e924e3ebe71e67c40bac5f67de2927716d5bc0ac
|
[
"MIT"
] | null | null | null |
from .auth import GoogleAPIAuth
from .youtube import get_comments
| 32.5
| 33
| 0.861538
| 9
| 65
| 6.111111
| 0.777778
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.107692
| 65
| 2
| 33
| 32.5
| 0.948276
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
cc0a811d95467ede10b4a9f3dcc041c30ca5fa11
| 75
|
py
|
Python
|
examples/path.py
|
scalabli/quo
|
70b6d4129ee705930f1f8a792fc4c9247d973f9d
|
[
"MIT"
] | 3
|
2022-03-13T13:22:35.000Z
|
2022-03-18T08:22:51.000Z
|
examples/path.py
|
scalabli/quo
|
70b6d4129ee705930f1f8a792fc4c9247d973f9d
|
[
"MIT"
] | 1
|
2022-03-21T16:29:54.000Z
|
2022-03-21T16:29:54.000Z
|
examples/path.py
|
scalabli/quo
|
70b6d4129ee705930f1f8a792fc4c9247d973f9d
|
[
"MIT"
] | null | null | null |
from quo.console import Console
console = Console()
console.find("quo")
| 10.714286
| 31
| 0.733333
| 10
| 75
| 5.5
| 0.5
| 0.763636
| 0.763636
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.146667
| 75
| 6
| 32
| 12.5
| 0.859375
| 0
| 0
| 0
| 0
| 0
| 0.040541
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.333333
| 0
| 0.333333
| 0
| 1
| 0
| 0
| null | 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
|
0
| 5
|
cc105ca657ef9d440bae608c80e519ef4d2f0bb8
| 148
|
py
|
Python
|
aoc_solver/lang/__init__.py
|
tcollier/aoc_solver
|
de63dbebd323d8a46deeab1f7fc45d20f70cfdae
|
[
"MIT"
] | 2
|
2021-12-14T18:13:16.000Z
|
2021-12-14T18:42:45.000Z
|
aoc_solver/lang/__init__.py
|
tcollier/aoc_solver
|
de63dbebd323d8a46deeab1f7fc45d20f70cfdae
|
[
"MIT"
] | null | null | null |
aoc_solver/lang/__init__.py
|
tcollier/aoc_solver
|
de63dbebd323d8a46deeab1f7fc45d20f70cfdae
|
[
"MIT"
] | null | null | null |
import os, pkgutil
for _, module, _ in pkgutil.iter_modules([os.path.dirname(__file__)]):
__import__(".".join(["aoc_solver", "lang", module]))
| 29.6
| 70
| 0.689189
| 19
| 148
| 4.736842
| 0.789474
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.114865
| 148
| 4
| 71
| 37
| 0.687023
| 0
| 0
| 0
| 0
| 0
| 0.101351
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.666667
| 0
| 0.666667
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
cc171f33ddb03dbda485cb098eb3facf301b5949
| 423
|
py
|
Python
|
tests/unit_tests/test_component/marketplace/spacewire_gateway_hvs_h8823/test_spacewire_gateway_utils_crc_8.py
|
ismaelJimenez/mamba_server
|
e6e2343291a0df24f226bde0d13e5bfa74cc3650
|
[
"MIT"
] | null | null | null |
tests/unit_tests/test_component/marketplace/spacewire_gateway_hvs_h8823/test_spacewire_gateway_utils_crc_8.py
|
ismaelJimenez/mamba_server
|
e6e2343291a0df24f226bde0d13e5bfa74cc3650
|
[
"MIT"
] | null | null | null |
tests/unit_tests/test_component/marketplace/spacewire_gateway_hvs_h8823/test_spacewire_gateway_utils_crc_8.py
|
ismaelJimenez/mamba_server
|
e6e2343291a0df24f226bde0d13e5bfa74cc3650
|
[
"MIT"
] | null | null | null |
from mamba.core.rmap_utils.crc_8 import crc_8
def test_crc_8():
# Test patterns from ECSS-E-50-11
assert crc_8(b'\x01\x02\x03\x04\x05\x06\x07\x08') == b'\xb0'
assert crc_8(
b'\x53\x70\x61\x63\x65\x57\x69\x72\x65\x20\x69\x73\x20\x62\x65\x61\x75\x74\x69\x66\x75\x6C\x21\x21'
) == b'\x84'
assert crc_8(
b'\x10\x56\xC3\x95\xA5\x75\x38\x63\x2F\x86\x7B\x01\x32\xDE\x35\x7A'
) == b'\x18'
| 32.538462
| 107
| 0.635934
| 87
| 423
| 3
| 0.655172
| 0.091954
| 0.114943
| 0.126437
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.29096
| 0.163121
| 423
| 12
| 108
| 35.25
| 0.446328
| 0.073286
| 0
| 0.222222
| 0
| 0.222222
| 0.523077
| 0.492308
| 0
| 0
| 0
| 0
| 0.333333
| 1
| 0.111111
| true
| 0
| 0.111111
| 0
| 0.222222
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
|
0
| 5
|
0bd97e185e2a7e7a926b20d5e2b384878337ede6
| 78
|
py
|
Python
|
dpark/__init__.py
|
congmo/dpark
|
3c7c43052a152e8966c9d0d5b786ef8d0bf5f51e
|
[
"BSD-3-Clause"
] | 1
|
2015-04-18T07:47:16.000Z
|
2015-04-18T07:47:16.000Z
|
dpark/__init__.py
|
congmo/dpark
|
3c7c43052a152e8966c9d0d5b786ef8d0bf5f51e
|
[
"BSD-3-Clause"
] | null | null | null |
dpark/__init__.py
|
congmo/dpark
|
3c7c43052a152e8966c9d0d5b786ef8d0bf5f51e
|
[
"BSD-3-Clause"
] | null | null | null |
from context import DparkContext, parser as optParser
from bagel import Bagel
| 26
| 53
| 0.846154
| 11
| 78
| 6
| 0.727273
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.141026
| 78
| 2
| 54
| 39
| 0.985075
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
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