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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
f98794c5de420ea8b8bf082e75a34db43b866731
| 92
|
py
|
Python
|
__init__.py
|
edmw/python-app
|
df18c3fc949f6f5407cc96e2af80073217a6c358
|
[
"MIT"
] | null | null | null |
__init__.py
|
edmw/python-app
|
df18c3fc949f6f5407cc96e2af80073217a6c358
|
[
"MIT"
] | null | null | null |
__init__.py
|
edmw/python-app
|
df18c3fc949f6f5407cc96e2af80073217a6c358
|
[
"MIT"
] | null | null | null |
# coding: utf-8
__version__ = "1.0.0"
from .script import Script
from .error import Error
| 13.142857
| 26
| 0.717391
| 15
| 92
| 4.133333
| 0.666667
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.052632
| 0.173913
| 92
| 6
| 27
| 15.333333
| 0.763158
| 0.141304
| 0
| 0
| 0
| 0
| 0.064935
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 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
| 0
| 0
| 1
| 0
| 1
| 0
|
0
| 4
|
f9a5c9a53223e83bbc34026586a75629cc223b52
| 318
|
py
|
Python
|
viberbot/api/bot_configuration.py
|
TeamCodeCreator/ViberBot
|
aefd6742ddab47546698f8a2a17a21a32a3a417d
|
[
"Apache-2.0"
] | 169
|
2016-12-01T00:06:23.000Z
|
2022-03-30T02:55:09.000Z
|
viberbot/api/bot_configuration.py
|
TeamCodeCreator/ViberBot
|
aefd6742ddab47546698f8a2a17a21a32a3a417d
|
[
"Apache-2.0"
] | 2
|
2017-05-24T08:11:02.000Z
|
2020-12-30T12:25:17.000Z
|
viberbot/api/bot_configuration.py
|
Micuk/viber-bot-python
|
c090e40a2270f3fec5b5cd34f83334a5797d2bdd
|
[
"Apache-2.0"
] | 80
|
2017-01-16T15:35:01.000Z
|
2022-01-26T22:11:32.000Z
|
class BotConfiguration(object):
def __init__(self, auth_token, name, avatar):
self._auth_token = auth_token
self._name = name
self._avatar = avatar
@property
def name(self):
return self._name
@property
def avatar(self):
return self._avatar
@property
def auth_token(self):
return self._auth_token
| 17.666667
| 46
| 0.738994
| 44
| 318
| 5
| 0.272727
| 0.204545
| 0.177273
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.166667
| 318
| 17
| 47
| 18.705882
| 0.830189
| 0
| 0
| 0.214286
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.285714
| false
| 0
| 0
| 0.214286
| 0.571429
| 0
| 0
| 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
| 0
| 0
| 0
| 1
| 1
| 0
|
0
| 4
|
f9acbc7dcee90f890e1512dc0aa3cc5ca2980834
| 145
|
py
|
Python
|
src/nodes/arithmetics/MULModel.py
|
LukasTinnes/Grim
|
dcb4ea8db4644e43e35c5dc40bf6c28a529016af
|
[
"Unlicense"
] | 2
|
2021-05-27T00:56:23.000Z
|
2021-06-19T04:08:30.000Z
|
src/nodes/arithmetics/MULModel.py
|
LukasTinnes/Grim
|
dcb4ea8db4644e43e35c5dc40bf6c28a529016af
|
[
"Unlicense"
] | null | null | null |
src/nodes/arithmetics/MULModel.py
|
LukasTinnes/Grim
|
dcb4ea8db4644e43e35c5dc40bf6c28a529016af
|
[
"Unlicense"
] | null | null | null |
from nodes.arithmetics.BaseDataModel import BaseDataModel
class MULModel(BaseDataModel):
name = "Mul"
def compute(self):
pass
| 16.111111
| 57
| 0.710345
| 15
| 145
| 6.866667
| 0.866667
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.213793
| 145
| 8
| 58
| 18.125
| 0.903509
| 0
| 0
| 0
| 0
| 0
| 0.02069
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.2
| false
| 0.2
| 0.2
| 0
| 0.8
| 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
| 0
| 1
| 0
|
0
| 4
|
f9b2c209b645c96bd794590949d1f2b0a0989fab
| 7,928
|
py
|
Python
|
evalml/tests/utils_tests/test_woodwork_utils.py
|
RG4421/evalml
|
33c62abe6d107d1da2f54e9e44a90f18aaf916a9
|
[
"BSD-3-Clause"
] | null | null | null |
evalml/tests/utils_tests/test_woodwork_utils.py
|
RG4421/evalml
|
33c62abe6d107d1da2f54e9e44a90f18aaf916a9
|
[
"BSD-3-Clause"
] | 13
|
2021-03-04T19:29:09.000Z
|
2022-03-07T01:00:43.000Z
|
evalml/tests/utils_tests/test_woodwork_utils.py
|
RG4421/evalml
|
33c62abe6d107d1da2f54e9e44a90f18aaf916a9
|
[
"BSD-3-Clause"
] | null | null | null |
import numpy as np
import pandas as pd
import woodwork as ww
from evalml.utils import _convert_woodwork_types_wrapper, infer_feature_types
def test_convert_woodwork_types_wrapper_with_nan():
y = _convert_woodwork_types_wrapper(pd.Series([1, 2, None], dtype="Int64"))
pd.testing.assert_series_equal(y, pd.Series([1, 2, np.nan], dtype="float64"))
y = _convert_woodwork_types_wrapper(pd.array([1, 2, None], dtype="Int64"))
pd.testing.assert_series_equal(y, pd.Series([1, 2, np.nan], dtype="float64"))
y = _convert_woodwork_types_wrapper(pd.Series(["a", "b", None], dtype="string"))
pd.testing.assert_series_equal(y, pd.Series(["a", "b", np.nan], dtype="object"))
y = _convert_woodwork_types_wrapper(pd.array(["a", "b", None], dtype="string"))
pd.testing.assert_series_equal(y, pd.Series(["a", "b", np.nan], dtype="object"))
y = _convert_woodwork_types_wrapper(pd.Series([True, False, None], dtype="boolean"))
pd.testing.assert_series_equal(y, pd.Series([True, False, np.nan]))
y = _convert_woodwork_types_wrapper(pd.array([True, False, None], dtype="boolean"))
pd.testing.assert_series_equal(y, pd.Series([True, False, np.nan]))
def test_convert_woodwork_types_wrapper():
y = _convert_woodwork_types_wrapper(pd.Series([1, 2, 3], dtype="Int64"))
pd.testing.assert_series_equal(y, pd.Series([1, 2, 3], dtype="int64"))
y = _convert_woodwork_types_wrapper(pd.array([1, 2, 3], dtype="Int64"))
pd.testing.assert_series_equal(y, pd.Series([1, 2, 3], dtype="int64"))
y = _convert_woodwork_types_wrapper(pd.Series(["a", "b", "a"], dtype="string"))
pd.testing.assert_series_equal(y, pd.Series(["a", "b", "a"], dtype="object"))
y = _convert_woodwork_types_wrapper(pd.array(["a", "b", "a"], dtype="string"))
pd.testing.assert_series_equal(y, pd.Series(["a", "b", "a"], dtype="object"))
y = _convert_woodwork_types_wrapper(pd.Series([True, False, True], dtype="boolean"))
pd.testing.assert_series_equal(y, pd.Series([True, False, True], dtype="bool"))
y = _convert_woodwork_types_wrapper(pd.array([True, False, True], dtype="boolean"))
pd.testing.assert_series_equal(y, pd.Series([True, False, True], dtype="bool"))
def test_convert_woodwork_types_wrapper_series_name():
name = "my series name"
series_with_name = pd.Series([1, 2, 3], name=name)
y = _convert_woodwork_types_wrapper(series_with_name)
assert y.name == name
def test_convert_woodwork_types_wrapper_dataframe():
X = pd.DataFrame({"Int series": pd.Series([1, 2, 3], dtype="Int64"),
"Int array": pd.array([1, 2, 3], dtype="Int64"),
"Int series with nan": pd.Series([1, 2, None], dtype="Int64"),
"Int array with nan": pd.array([1, 2, None], dtype="Int64"),
"string series": pd.Series(["a", "b", "a"], dtype="string"),
"string array": pd.array(["a", "b", "a"], dtype="string"),
"string series with nan": pd.Series(["a", "b", None], dtype="string"),
"string array with nan": pd.array(["a", "b", None], dtype="string"),
"boolean series": pd.Series([True, False, True], dtype="boolean"),
"boolean array": pd.array([True, False, True], dtype="boolean"),
"boolean series with nan": pd.Series([True, False, None], dtype="boolean"),
"boolean array with nan": pd.array([True, False, None], dtype="boolean")
})
X_expected = pd.DataFrame({"Int series": pd.Series([1, 2, 3], dtype="int64"),
"Int array": pd.array([1, 2, 3], dtype="int64"),
"Int series with nan": pd.Series([1, 2, np.nan], dtype="float64"),
"Int array with nan": pd.array([1, 2, np.nan], dtype="float64"),
"string series": pd.Series(["a", "b", "a"], dtype="object"),
"string array": pd.array(["a", "b", "a"], dtype="object"),
"string series with nan": pd.Series(["a", "b", np.nan], dtype="object"),
"string array with nan": pd.array(["a", "b", np.nan], dtype="object"),
"boolean series": pd.Series([True, False, True], dtype="bool"),
"boolean array": pd.array([True, False, True], dtype="bool"),
"boolean series with nan": pd.Series([True, False, np.nan], dtype="object"),
"boolean array with nan": pd.array([True, False, np.nan], dtype="object")
})
pd.testing.assert_frame_equal(X_expected, _convert_woodwork_types_wrapper(X))
def testinfer_feature_types():
X_dt = ww.DataTable(pd.DataFrame([[1, 2], [3, 4]]))
pd.testing.assert_frame_equal(X_dt.to_dataframe(), infer_feature_types(X_dt).to_dataframe())
X_dc = ww.DataColumn(pd.Series([1, 2, 3, 4]))
pd.testing.assert_series_equal(X_dc.to_series(), infer_feature_types(X_dc).to_series())
X_pd = pd.DataFrame({0: pd.Series([1, 2], dtype="Int64"),
1: pd.Series([3, 4], dtype="Int64")})
pd.testing.assert_frame_equal(X_pd, infer_feature_types(X_pd).to_dataframe())
X_pd = pd.Series([1, 2, 3, 4], dtype="Int64")
pd.testing.assert_series_equal(X_pd, infer_feature_types(X_pd).to_series())
X_list = [1, 2, 3, 4]
X_expected = ww.DataColumn(pd.Series(X_list))
pd.testing.assert_series_equal(X_expected.to_series(), infer_feature_types(X_list).to_series())
assert X_list == [1, 2, 3, 4]
X_np = np.array([1, 2, 3, 4])
X_expected = ww.DataColumn(pd.Series(X_np))
pd.testing.assert_series_equal(X_expected.to_series(), infer_feature_types(X_np).to_series())
assert np.array_equal(X_np, np.array([1, 2, 3, 4]))
X_np = np.array([[1, 2], [3, 4]])
X_expected = ww.DataTable(pd.DataFrame(X_np))
pd.testing.assert_frame_equal(X_expected.to_dataframe(), infer_feature_types(X_np).to_dataframe())
assert np.array_equal(X_np, np.array([[1, 2], [3, 4]]))
def testinfer_feature_types_series_name():
name = "column with name"
X_pd = pd.Series([1, 2, 3, 4], dtype="Int64", name=name)
X_dc = infer_feature_types(X_pd)
assert X_dc.name == name
pd.testing.assert_series_equal(X_pd, X_dc.to_series())
def test_infer_feature_types_dataframe():
X_pd = pd.DataFrame({0: pd.Series([1, 2]),
1: pd.Series([3, 4])})
pd.testing.assert_frame_equal(X_pd, infer_feature_types(X_pd).to_dataframe(), check_dtype=False)
X_pd = pd.DataFrame({0: pd.Series([1, 2], dtype="Int64"),
1: pd.Series([3, 4], dtype="Int64")})
pd.testing.assert_frame_equal(X_pd, infer_feature_types(X_pd).to_dataframe())
X_expected = X_pd.copy()
X_expected[0] = X_expected[0].astype("category")
pd.testing.assert_frame_equal(X_expected, infer_feature_types(X_pd, {0: "categorical"}).to_dataframe())
pd.testing.assert_frame_equal(X_expected, infer_feature_types(X_pd, {0: ww.logical_types.Categorical}).to_dataframe())
def test_infer_feature_types_series():
X_pd = pd.Series([1, 2, 3, 4])
X_expected = X_pd.astype("Int64")
pd.testing.assert_series_equal(X_expected, infer_feature_types(X_pd).to_series())
X_pd = pd.Series([1, 2, 3, 4], dtype="Int64")
pd.testing.assert_series_equal(X_pd, infer_feature_types(X_pd).to_series())
X_pd = pd.Series([1, 2, 3, 4], dtype="Int64")
X_expected = X_pd.astype("category")
pd.testing.assert_series_equal(X_expected, infer_feature_types(X_pd, "categorical").to_series())
X_pd = pd.Series([1, 2, 3, 4], dtype="Int64")
X_expected = X_pd.astype("category")
pd.testing.assert_series_equal(X_expected, infer_feature_types(X_pd, ww.logical_types.Categorical).to_series())
| 51.816993
| 122
| 0.625757
| 1,167
| 7,928
| 4.005141
| 0.054841
| 0.078733
| 0.093068
| 0.044929
| 0.878477
| 0.831836
| 0.760804
| 0.704964
| 0.570817
| 0.525888
| 0
| 0.027339
| 0.201816
| 7,928
| 152
| 123
| 52.157895
| 0.711283
| 0
| 0
| 0.245614
| 0
| 0
| 0.104188
| 0
| 0
| 0
| 0
| 0
| 0.298246
| 1
| 0.070175
| false
| 0
| 0.035088
| 0
| 0.105263
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 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
| 4
|
f9d3fbf562a501b99215b9a5b620bbc804612b11
| 35
|
py
|
Python
|
tests.py
|
nightlxight/delightfully
|
e48d3ddfab555195fa0a35c4b14c63c9ebc94be2
|
[
"MIT"
] | null | null | null |
tests.py
|
nightlxight/delightfully
|
e48d3ddfab555195fa0a35c4b14c63c9ebc94be2
|
[
"MIT"
] | null | null | null |
tests.py
|
nightlxight/delightfully
|
e48d3ddfab555195fa0a35c4b14c63c9ebc94be2
|
[
"MIT"
] | null | null | null |
x = 10
print(x)
"""
tests here
"""
| 5.833333
| 10
| 0.514286
| 6
| 35
| 3
| 0.833333
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.074074
| 0.228571
| 35
| 6
| 11
| 5.833333
| 0.592593
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0
| 0
| 0
| 0.5
| 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
| 0
| 0
| 0
| 0
| 0
| 1
|
0
| 4
|
dda33bc1bc8944486466c39abfdb88938c236caa
| 321
|
py
|
Python
|
IMLearn/learners/regressors/__init__.py
|
roeykelner/IML.HUJI
|
ce818fed67dc0f34b0474030f062374481967b38
|
[
"MIT"
] | null | null | null |
IMLearn/learners/regressors/__init__.py
|
roeykelner/IML.HUJI
|
ce818fed67dc0f34b0474030f062374481967b38
|
[
"MIT"
] | null | null | null |
IMLearn/learners/regressors/__init__.py
|
roeykelner/IML.HUJI
|
ce818fed67dc0f34b0474030f062374481967b38
|
[
"MIT"
] | null | null | null |
from .linear_regression import LinearRegression
from .polynomial_fitting import PolynomialFitting
from .ridge_regression import RidgeRegression
from .lasso_regression import LassoRegression
__all__ = ["LinearRegression",
"PolynomialFitting",
"RidgeRegression",
"LassoRegression"]
| 35.666667
| 50
| 0.747664
| 25
| 321
| 9.28
| 0.52
| 0.206897
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.196262
| 321
| 9
| 51
| 35.666667
| 0.899225
| 0
| 0
| 0
| 0
| 0
| 0.200637
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 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
| 0
| 0
| 1
| 0
| 0
| 0
|
0
| 4
|
ddae756c181d468345752bb0e72066e92ae88441
| 251
|
py
|
Python
|
flashcards/admin.py
|
YellowAndGreen/Anki2
|
53165465b94ce4d27f3683e030564c8f4289f57f
|
[
"MIT"
] | null | null | null |
flashcards/admin.py
|
YellowAndGreen/Anki2
|
53165465b94ce4d27f3683e030564c8f4289f57f
|
[
"MIT"
] | null | null | null |
flashcards/admin.py
|
YellowAndGreen/Anki2
|
53165465b94ce4d27f3683e030564c8f4289f57f
|
[
"MIT"
] | null | null | null |
from django.contrib import admin
from .models import Card
# Register your models here.
@admin.register(Card)
class CardAdmin(admin.ModelAdmin):
list_display = ['id', 'group', 'question']
# prepopulated_fields = {'slug': ('title',)}
| 25.1
| 49
| 0.681275
| 29
| 251
| 5.827586
| 0.758621
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.179283
| 251
| 9
| 50
| 27.888889
| 0.820388
| 0.2749
| 0
| 0
| 0
| 0
| 0.088235
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.4
| 0
| 0.8
| 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
| 0
| 1
| 0
| 1
| 0
|
0
| 4
|
ddb618a1fbd6d56ff06549c89e7caf661f63d3c3
| 1,410
|
gyp
|
Python
|
test/napi/binding.gyp
|
legendecas/ShadowNode
|
02047fc9eca51aef5974d95c5ec58f2ea89983fe
|
[
"Apache-2.0"
] | 1,144
|
2018-12-18T09:46:47.000Z
|
2022-03-07T14:51:46.000Z
|
test/napi/binding.gyp
|
yorkie/fringejs
|
b03929d5500fd0823fdc3bc37c9b82ba88cc3f6d
|
[
"Apache-2.0"
] | 281
|
2018-02-13T18:50:54.000Z
|
2019-01-26T06:17:56.000Z
|
test/napi/binding.gyp
|
yorkie/fringejs
|
b03929d5500fd0823fdc3bc37c9b82ba88cc3f6d
|
[
"Apache-2.0"
] | 129
|
2018-12-18T09:46:50.000Z
|
2022-03-30T07:30:13.000Z
|
{
"targets": [
{
"target_name": "napi_test",
"sources": [ "napi.test.c" ]
},
{
"target_name": "napi_arguments",
"sources": [ "napi_arguments.c" ]
},
{
"target_name": "napi_async",
"sources": [ "napi_async.cc" ]
},
{
"target_name": "napi_construct",
"sources": [ "napi_construct.c" ]
},
{
"target_name": "napi_error",
"sources": [ "napi_error.c" ]
},
{
"target_name": "napi_fatal_error",
"sources": [ "napi_fatal_error.c" ]
},
{
"target_name": "napi_make_callback_recurse",
"sources": [ "napi_make_callback_recurse.cc" ]
},
{
"target_name": "napi_make_callback",
"sources": [ "napi_make_callback.c" ]
},
{
"target_name": "napi_object_wrap",
"sources": [ "napi_object_wrap.c" ]
},
{
"target_name": "napi_reference",
"sources": [ "napi_reference.c" ]
},
{
"target_name": "napi_new_target",
"sources": [ "napi_new_target.c" ]
},
{
"target_name": "napi_string",
"sources": [ "napi_string.c" ]
},
{
"target_name": "napi_thread_safe",
"sources": [ "napi_thread_safe.c" ]
},
{
"target_name": "napi_tsfn",
"sources": [ "napi_tsfn.c" ]
},
{
"target_name": "napi_typedarray",
"sources": [ "napi_typedarray.c" ]
}
]
}
| 21.692308
| 52
| 0.509929
| 135
| 1,410
| 4.896296
| 0.185185
| 0.226929
| 0.3177
| 0.272315
| 0.118003
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.304255
| 1,410
| 64
| 53
| 22.03125
| 0.673802
| 0
| 0
| 0
| 0
| 0
| 0.521277
| 0.039007
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0
| 0
| 0
| 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
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
ddb7fdc6374ab3cb1a7ddcb785b6ca2e792c41a8
| 176
|
py
|
Python
|
backend/sourcebans/forms.py
|
b3none/Tensor
|
6c70c7d3ade6eabe4162d0b9eef0923c79ea1eba
|
[
"MIT"
] | null | null | null |
backend/sourcebans/forms.py
|
b3none/Tensor
|
6c70c7d3ade6eabe4162d0b9eef0923c79ea1eba
|
[
"MIT"
] | null | null | null |
backend/sourcebans/forms.py
|
b3none/Tensor
|
6c70c7d3ade6eabe4162d0b9eef0923c79ea1eba
|
[
"MIT"
] | 3
|
2021-09-06T18:01:52.000Z
|
2021-10-18T02:49:53.000Z
|
from django import forms
from .models import SbProtests, SbBans
class BanProtest(forms.Form):
reason = forms.CharField(widget=forms.Textarea)
email = forms.EmailField()
| 22
| 49
| 0.772727
| 23
| 176
| 5.956522
| 0.73913
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.130682
| 176
| 7
| 50
| 25.142857
| 0.888889
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | null | 0
| 0.4
| null | null | 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
| 1
| 0
| 0
| 0
| 1
| 0
| 0
| 0
|
0
| 4
|
ddd8942144a5ccd72bbefdbc4ff5b0c0d15cfc8c
| 944
|
py
|
Python
|
moteur/models.py
|
fideledegni/eeia-moteur-recherche
|
7db64c3a8decb04cf92ac32ba473cd92eb1136bb
|
[
"MIT"
] | null | null | null |
moteur/models.py
|
fideledegni/eeia-moteur-recherche
|
7db64c3a8decb04cf92ac32ba473cd92eb1136bb
|
[
"MIT"
] | null | null | null |
moteur/models.py
|
fideledegni/eeia-moteur-recherche
|
7db64c3a8decb04cf92ac32ba473cd92eb1136bb
|
[
"MIT"
] | null | null | null |
from django.db import models
from datetime import timedelta
from django.utils import timezone
class Search(models.Model):
search_text = models.CharField(max_length=200)
search_date = models.DateTimeField('search date')
clicked_article_1 = models.CharField(max_length=200)
clicked_article_2 = models.CharField(max_length=200)
clicked_article_3 = models.CharField(max_length=200)
def was_searched_recently(self):
return self.search_date >= timezone.now() - timedelta(days=1)
def __str__(self):
return self.search_text
# def default_top_search_texts():
# return []
class Article(models.Model):
name = models.CharField(max_length=200)
image_name = models.CharField(max_length=50)
description = models.CharField(max_length=500)
def get_top_search_texts(self):
st = Search.objects.filter(clicked_article_1=self.name)
return list(s.search_text for s in st)
def __str__(self):
return self.name
| 29.5
| 65
| 0.762712
| 135
| 944
| 5.059259
| 0.362963
| 0.153734
| 0.18448
| 0.245974
| 0.34407
| 0.120059
| 0.120059
| 0
| 0
| 0
| 0
| 0.030788
| 0.139831
| 944
| 31
| 66
| 30.451613
| 0.810345
| 0.045551
| 0
| 0.090909
| 0
| 0
| 0.012249
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.181818
| false
| 0
| 0.136364
| 0.136364
| 0.954545
| 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
| 0
| 0
| 0
| 1
| 1
| 0
|
0
| 4
|
fb1ae75bc728fbb7f8ce7ce360309a76aa954a2d
| 162
|
py
|
Python
|
exercicios-python/curso-python/ex024.py
|
PabloLanza/curso-python3
|
34cf44a2467fa239ba4019e085833002ad9b76a1
|
[
"MIT"
] | null | null | null |
exercicios-python/curso-python/ex024.py
|
PabloLanza/curso-python3
|
34cf44a2467fa239ba4019e085833002ad9b76a1
|
[
"MIT"
] | null | null | null |
exercicios-python/curso-python/ex024.py
|
PabloLanza/curso-python3
|
34cf44a2467fa239ba4019e085833002ad9b76a1
|
[
"MIT"
] | null | null | null |
num = int(input('Digite um número: '))
n = num % 2
if n == 0:
print('O número {} é par.'.format(num))
else:
print('O número {} é ímpar.'.format(num))
| 23.142857
| 45
| 0.555556
| 27
| 162
| 3.333333
| 0.62963
| 0.133333
| 0.266667
| 0.288889
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.016129
| 0.234568
| 162
| 7
| 46
| 23.142857
| 0.709677
| 0
| 0
| 0
| 0
| 0
| 0.343558
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0
| 0
| 0
| 0.333333
| 1
| 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
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
fb1c137100f61c8469bd4863a381ade4a38b57cc
| 2,895
|
py
|
Python
|
vector_common/vector_ros/src/vector_joint_interface/angles.py
|
si-machines/vector_v1
|
6a9111e0d8eb00827c8a97878f939509a433194b
|
[
"BSD-3-Clause"
] | null | null | null |
vector_common/vector_ros/src/vector_joint_interface/angles.py
|
si-machines/vector_v1
|
6a9111e0d8eb00827c8a97878f939509a433194b
|
[
"BSD-3-Clause"
] | null | null | null |
vector_common/vector_ros/src/vector_joint_interface/angles.py
|
si-machines/vector_v1
|
6a9111e0d8eb00827c8a97878f939509a433194b
|
[
"BSD-3-Clause"
] | 1
|
2020-12-29T21:17:20.000Z
|
2020-12-29T21:17:20.000Z
|
"""--------------------------------------------------------------------
COPYRIGHT 2016 Stanley Innovation Inc.
Software License Agreement:
The software supplied herewith by Stanley Innovation Inc. (the "Company")
for its licensed SI Vector Platform is intended and supplied to you,
the Company's customer, for use solely and exclusively with Stanley Innovation
products. The software is owned by the Company and/or its supplier, and is
protected under applicable copyright laws. All rights are reserved. Any use in
violation of the foregoing restrictions may subject the user to criminal
sanctions under applicable laws, as well as to civil liability for the
breach of the terms and conditions of this license. The Company may
immediately terminate this Agreement upon your use of the software with
any products that are not Stanley Innovation products.
The software was written using Python programming language. Your use
of the software is therefore subject to the terms and conditions of the
OSI- approved open source license viewable at http://www.python.org/.
You are solely responsible for ensuring your compliance with the Python
open source license.
You shall indemnify, defend and hold the Company harmless from any claims,
demands, liabilities or expenses, including reasonable attorneys fees, incurred
by the Company as a result of any claim or proceeding against the Company
arising out of or based upon:
(i) The combination, operation or use of the software by you with any hardware,
products, programs or data not supplied or approved in writing by the Company,
if such claim or proceeding would have been avoided but for such combination,
operation or use.
(ii) The modification of the software by or on behalf of you
(iii) Your use of the software.
THIS SOFTWARE IS PROVIDED IN AN "AS IS" CONDITION. NO WARRANTIES,
WHETHER EXPRESS, IMPLIED OR STATUTORY, INCLUDING, BUT NOT LIMITED
TO, IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A
PARTICULAR PURPOSE APPLY TO THIS SOFTWARE. THE COMPANY SHALL NOT,
IN ANY CIRCUMSTANCES, BE LIABLE FOR SPECIAL, INCIDENTAL OR
CONSEQUENTIAL DAMAGES, FOR ANY REASON WHATSOEVER.
\file angles.py
\brief This module contains a collection of angle operations for
rotational calculations
\Platform: Linux/ROS Indigo
--------------------------------------------------------------------"""
import math
M_PI = math.pi
def deg_to_rad(degrees):
return degrees * (M_PI / 180.0)
def rad_to_deg(rads):
return rads * (180.0 / M_PI)
def wrap_angle(angle_rad):
ret = ( angle_rad + math.pi) % (2 * math.pi ) - math.pi
return ret
def get_smallest_difference_to_cont_angle(des_norm,pres_cont):
present =( pres_cont + math.pi) % (2 * math.pi )
desired =( des_norm + math.pi) % (2 * math.pi )
return round(wrap_angle(desired-present),4)
| 38.6
| 83
| 0.724007
| 424
| 2,895
| 4.896226
| 0.45283
| 0.043353
| 0.03131
| 0.030829
| 0.104528
| 0
| 0
| 0
| 0
| 0
| 0
| 0.006757
| 0.182038
| 2,895
| 74
| 84
| 39.121622
| 0.869932
| 0.828325
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.307692
| false
| 0
| 0.076923
| 0.153846
| 0.692308
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 1
| 0
|
0
| 4
|
fb392949dbfa1ed4d25cf9f9b09a91bc82bb43f6
| 354
|
py
|
Python
|
gravpy/noise.py
|
transientlunatic/grasshopper
|
1d3822427970d200341ff9d2823949fb4b27e001
|
[
"0BSD"
] | 3
|
2020-09-26T01:27:13.000Z
|
2020-09-30T05:47:42.000Z
|
gravpy/noise.py
|
transientlunatic/gravpy
|
1d3822427970d200341ff9d2823949fb4b27e001
|
[
"0BSD"
] | null | null | null |
gravpy/noise.py
|
transientlunatic/gravpy
|
1d3822427970d200341ff9d2823949fb4b27e001
|
[
"0BSD"
] | null | null | null |
import astropy.units as u
import astropy.constants as c
import matplotlib.pyplot as plt
import numpy as np
from scipy import interpolate
import scipy.integrate as integrate
import numpy.linalg as la
import os
class NoiseSource(object):
"""
This is the base class for all noise sources which we might want to define or plot.
"""
pass
| 18.631579
| 87
| 0.751412
| 56
| 354
| 4.75
| 0.696429
| 0.097744
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.206215
| 354
| 18
| 88
| 19.666667
| 0.946619
| 0.234463
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0.1
| 0.8
| 0
| 0.9
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 1
| 0
| 1
| 0
|
0
| 4
|
3485348ee803bcd90af8b5d66b7662ef0ffadb21
| 1,978
|
py
|
Python
|
2019/10/test_part1.py
|
maguesse/adventofcode
|
126f0baac4cf35bbfc31f1306682586cf0e5883e
|
[
"MIT"
] | null | null | null |
2019/10/test_part1.py
|
maguesse/adventofcode
|
126f0baac4cf35bbfc31f1306682586cf0e5883e
|
[
"MIT"
] | null | null | null |
2019/10/test_part1.py
|
maguesse/adventofcode
|
126f0baac4cf35bbfc31f1306682586cf0e5883e
|
[
"MIT"
] | null | null | null |
import main
def solve(data):
obj = main.Day10(data)
return obj.solve_part1()
def test_field1():
data = ['.#..#',
'.....',
'#####',
'....#',
'...##']
assert ((3,4), 8) == solve(data)
def test_field2():
data = ['......#.#.', '#..#.#....',
'..#######.',
'.#.#.###..',
'.#..#.....',
'..#....#.#',
'#..#....#.',
'.##.#..###',
'##...#..#.',
'.#....####',]
assert ((5,8), 33) == solve(data)
def test_field3():
data = ['#.#...#.#.',
'.###....#.',
'.#....#...',
'##.#.#.#.#',
'....#.#.#.',
'.##..###.#',
'..#...##..',
'..##....##',
'......#...',
'.####.###.']
assert ((1,2), 35) == solve(data)
def test_field4():
data = ['.#..#..###',
'####.###.#',
'....###.#.',
'..###.##.#',
'##.##.#.#.',
'....###..#',
'..#.#..#.#',
'#..#.#.###',
'.##...##.#',
'.....#.#..',]
assert ((6,3), 41) == solve(data)
def test_field5():
data = ['.#..##.###...#######',
'##.############..##.',
'.#.######.########.#',
'.###.#######.####.#.',
'#####.##.#.##.###.##',
'..#####..#.#########',
'####################',
'#.####....###.#.#.##',
'##.#################',
'#####.##.###..####..',
'..######..##.#######',
'####.##.####...##..#',
'.#####..#.######.###',
'##...#.##########...',
'#.##########.#######',
'.####.#.###.###.#.##',
'....##.##.###..#####',
'.#.#.###########.###',
'#.#.#.#####.####.###',
'###.##.####.##.#..##',]
assert ((11,13), 210) == solve(data)
| 25.037975
| 40
| 0.123862
| 63
| 1,978
| 3.793651
| 0.460317
| 0.225941
| 0.200837
| 0.267782
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.02453
| 0.381699
| 1,978
| 78
| 41
| 25.358974
| 0.170891
| 0
| 0
| 0
| 0
| 0
| 0.366532
| 0
| 0
| 0
| 0
| 0
| 0.073529
| 1
| 0.088235
| false
| 0
| 0.014706
| 0
| 0.117647
| 0
| 0
| 0
| 0
| null | 1
| 1
| 1
| 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
| 0
|
0
| 4
|
34efb8fb61ed89d53b2d533188f6d50e7ae8df7a
| 283
|
py
|
Python
|
linode/objects/account/__init__.py
|
awiddersheim/linode-api-python
|
4bb0dba0cc76321b9ca760e85d164b750cc95fa6
|
[
"BSD-3-Clause"
] | null | null | null |
linode/objects/account/__init__.py
|
awiddersheim/linode-api-python
|
4bb0dba0cc76321b9ca760e85d164b750cc95fa6
|
[
"BSD-3-Clause"
] | null | null | null |
linode/objects/account/__init__.py
|
awiddersheim/linode-api-python
|
4bb0dba0cc76321b9ca760e85d164b750cc95fa6
|
[
"BSD-3-Clause"
] | null | null | null |
from .user import User
from .event import Event
from .oauth_client import OAuthClient
from .settings import AccountSettings
from .user_grant import UserGrants
from .invoice import Invoice
from .invoiceitem import InvoiceItem
from .payment import Payment
from .account import Account
| 28.3
| 37
| 0.840989
| 38
| 283
| 6.210526
| 0.394737
| 0.067797
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.127208
| 283
| 9
| 38
| 31.444444
| 0.955466
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 0
| 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
| 4
|
34f95d5f4ec63200909c903f0bc32d2a93e94c4f
| 218
|
py
|
Python
|
coinpayments/admin.py
|
unilot/pre-ico
|
6d4bd6648b3a1fbc169bd3e331385736d3974046
|
[
"MIT"
] | 1
|
2018-08-03T03:32:32.000Z
|
2018-08-03T03:32:32.000Z
|
coinpayments/admin.py
|
unilot/pre-ico
|
6d4bd6648b3a1fbc169bd3e331385736d3974046
|
[
"MIT"
] | 8
|
2020-02-11T21:44:14.000Z
|
2022-01-13T00:33:35.000Z
|
coinpayments/admin.py
|
unilot/pre-ico
|
6d4bd6648b3a1fbc169bd3e331385736d3974046
|
[
"MIT"
] | 1
|
2018-02-17T12:52:46.000Z
|
2018-02-17T12:52:46.000Z
|
from django.contrib import admin
from . import models
class TransactionAdmin(admin.ModelAdmin):
list_display = ('txn_id', 'user', 'currency', 'amount',)
admin.site.register(models.Transaction, TransactionAdmin)
| 24.222222
| 60
| 0.761468
| 25
| 218
| 6.56
| 0.76
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.114679
| 218
| 8
| 61
| 27.25
| 0.849741
| 0
| 0
| 0
| 0
| 0
| 0.110092
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.4
| 0
| 0.8
| 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
| 0
| 1
| 0
| 1
| 0
|
0
| 4
|
9b67cfec47cfcc38b2a4a0ce2940de7243bc2895
| 229
|
py
|
Python
|
tests/backends/base/test_features.py
|
ni-ning/django
|
2e7ba6057cfc82a15a22b6021cd60cf307152e2d
|
[
"CNRI-Python-GPL-Compatible",
"BSD-3-Clause"
] | 61,676
|
2015-01-01T00:05:13.000Z
|
2022-03-31T20:37:54.000Z
|
tests/backends/base/test_features.py
|
ni-ning/django
|
2e7ba6057cfc82a15a22b6021cd60cf307152e2d
|
[
"CNRI-Python-GPL-Compatible",
"BSD-3-Clause"
] | 8,884
|
2015-01-01T00:12:05.000Z
|
2022-03-31T19:53:11.000Z
|
tests/backends/base/test_features.py
|
mustafa0x/django
|
d7394cfa13a4d1a02356e3a83e10ec100fbb9948
|
[
"BSD-3-Clause",
"0BSD"
] | 33,143
|
2015-01-01T02:04:52.000Z
|
2022-03-31T19:42:46.000Z
|
from django.db import connection
from django.test import SimpleTestCase
class TestDatabaseFeatures(SimpleTestCase):
def test_nonexistent_feature(self):
self.assertFalse(hasattr(connection.features, 'nonexistent'))
| 25.444444
| 69
| 0.799127
| 24
| 229
| 7.541667
| 0.666667
| 0.110497
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.126638
| 229
| 8
| 70
| 28.625
| 0.905
| 0
| 0
| 0
| 0
| 0
| 0.048035
| 0
| 0
| 0
| 0
| 0
| 0.2
| 1
| 0.2
| false
| 0
| 0.4
| 0
| 0.8
| 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
| 0
| 1
| 0
| 1
| 0
|
0
| 4
|
9b8a25f6fef9889562d72bbff5889eb9aacee087
| 87
|
py
|
Python
|
photeo/apps.py
|
AjayRajNelapudi/Voteo
|
3d7d742b5e4a99b7b67068ca3a3baf7796bb6012
|
[
"MIT"
] | null | null | null |
photeo/apps.py
|
AjayRajNelapudi/Voteo
|
3d7d742b5e4a99b7b67068ca3a3baf7796bb6012
|
[
"MIT"
] | 8
|
2020-02-12T03:18:58.000Z
|
2021-06-10T19:37:39.000Z
|
photeo/apps.py
|
AjayRajNelapudi/Voteo
|
3d7d742b5e4a99b7b67068ca3a3baf7796bb6012
|
[
"MIT"
] | null | null | null |
from django.apps import AppConfig
class PhoteoConfig(AppConfig):
name = 'photeo'
| 14.5
| 33
| 0.747126
| 10
| 87
| 6.5
| 0.9
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.172414
| 87
| 5
| 34
| 17.4
| 0.902778
| 0
| 0
| 0
| 0
| 0
| 0.068966
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.333333
| 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
| 0
| 0
| 1
| 0
| 1
| 0
|
0
| 4
|
9ba25ce33306bf432ea64144dadb380bf07c9f49
| 1,067
|
py
|
Python
|
Chapter3/exercise8.py
|
ion-training/python-practical-programming
|
1b048da3c681ba534a6f0a8e3e1c3dc89f73694c
|
[
"MIT"
] | null | null | null |
Chapter3/exercise8.py
|
ion-training/python-practical-programming
|
1b048da3c681ba534a6f0a8e3e1c3dc89f73694c
|
[
"MIT"
] | null | null | null |
Chapter3/exercise8.py
|
ion-training/python-practical-programming
|
1b048da3c681ba534a6f0a8e3e1c3dc89f73694c
|
[
"MIT"
] | null | null | null |
# Complete the examples in the docstring and then write the body of the following function:
# The Questions
# Q1. What do you name the function?
# Q2. What are the parameters, and what types of information do they refer to?
# Q3. What calculations are you doing with that information?
# Q4. What information does the function return?
# Q5. Does it work like you expect it to?
# Implementation
# 1 Examples and function name
# 2 Header: Decide param names and types, and return type. Write header of the func.
# 3 Description: short description of the function for others to read
# 4 Body: write body of the function
# 5 Test: run examples to make sure you function body is correct
import math
def weeks_elapsed(day1, day2):
""" (int, int) -> int
day1 and day2 are days in the same year. Return the number of full weeks
that have elapsed between the two days.
>>> weeks_elapsed(3, 20)
2
>>> weeks_elapsed(20, 3)
2
>>> weeks_elapsed(8, 5)
0
>>> weeks_elapsed(40, 61)
3
"""
return math.floor(abs(day2 - day1) / 7)
| 32.333333
| 91
| 0.701968
| 173
| 1,067
| 4.300578
| 0.49711
| 0.080645
| 0.024194
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.039807
| 0.223055
| 1,067
| 32
| 92
| 33.34375
| 0.85766
| 0.837863
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.333333
| false
| 0
| 0.333333
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 1
| 0
| 1
| 0
|
0
| 4
|
9baeb2257997a0577914c527f314dc3bab93266e
| 245
|
py
|
Python
|
lego/utils/decorators.py
|
ollfkaih/lego
|
b15aacaf09efe90e7f984d25b0e7bddbe12647e8
|
[
"MIT"
] | 45
|
2017-10-24T12:09:06.000Z
|
2021-11-03T21:21:03.000Z
|
lego/utils/decorators.py
|
ollfkaih/lego
|
b15aacaf09efe90e7f984d25b0e7bddbe12647e8
|
[
"MIT"
] | 980
|
2017-10-24T12:29:07.000Z
|
2022-03-31T04:04:31.000Z
|
lego/utils/decorators.py
|
wahello/lego
|
a0b02f3abc997fe96326e9c9c05b49847170041b
|
[
"MIT"
] | 23
|
2018-04-11T16:34:22.000Z
|
2021-11-23T12:28:30.000Z
|
from django.utils.functional import cached_property
class abakus_cached_property(cached_property):
def __init__(self, func, name=None, delete_on_save=True):
super().__init__(func, name)
self.delete_on_save = delete_on_save
| 30.625
| 61
| 0.759184
| 34
| 245
| 4.941176
| 0.588235
| 0.25
| 0.214286
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.155102
| 245
| 7
| 62
| 35
| 0.811594
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.2
| false
| 0
| 0.2
| 0
| 0.6
| 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
| 0
| 0
| 0
| 0
| 1
| 0
|
0
| 4
|
fd04123f405555fd4d327f0b477d463988896922
| 93
|
py
|
Python
|
Task/Loops-Continue/Python/loops-continue.py
|
mullikine/RosettaCodeData
|
4f0027c6ce83daa36118ee8b67915a13cd23ab67
|
[
"Info-ZIP"
] | 5
|
2021-01-29T20:08:05.000Z
|
2022-03-22T06:16:05.000Z
|
Task/Loops-Continue/Python/loops-continue.py
|
seanwallawalla-forks/RosettaCodeData
|
9ad63ea473a958506c041077f1d810c0c7c8c18d
|
[
"Info-ZIP"
] | null | null | null |
Task/Loops-Continue/Python/loops-continue.py
|
seanwallawalla-forks/RosettaCodeData
|
9ad63ea473a958506c041077f1d810c0c7c8c18d
|
[
"Info-ZIP"
] | 1
|
2021-04-13T04:19:31.000Z
|
2021-04-13T04:19:31.000Z
|
for i in xrange(1,11):
if i % 5 == 0:
print i
continue
print i, ",",
| 15.5
| 22
| 0.430108
| 15
| 93
| 2.666667
| 0.733333
| 0.3
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.09434
| 0.430108
| 93
| 5
| 23
| 18.6
| 0.660377
| 0
| 0
| 0
| 0
| 0
| 0.010753
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | null | 0
| 0
| null | null | 0.4
| 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
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
fd27e36bab45ebb879ec07ac91cfe06f75aa813b
| 208
|
py
|
Python
|
watch/core/apps.py
|
ResonantGeoData/RD-WATCH
|
d40b3d7927b9c999b9809291ee97f27d361c4c3a
|
[
"Apache-2.0"
] | 2
|
2022-01-24T21:43:47.000Z
|
2022-01-28T05:22:12.000Z
|
watch/core/apps.py
|
ResonantGeoData/RD-WATCH
|
d40b3d7927b9c999b9809291ee97f27d361c4c3a
|
[
"Apache-2.0"
] | 42
|
2021-07-01T20:12:50.000Z
|
2022-03-22T17:38:30.000Z
|
watch/core/apps.py
|
ResonantGeoData/RD-WATCH
|
d40b3d7927b9c999b9809291ee97f27d361c4c3a
|
[
"Apache-2.0"
] | null | null | null |
from django.apps import AppConfig
class CoreConfig(AppConfig):
name = 'watch.core'
verbose_name = 'ResonantGeoData WATCH: Core'
def ready(self):
import watch.core.signals # noqa: F401
| 20.8
| 48
| 0.692308
| 25
| 208
| 5.72
| 0.72
| 0.188811
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.018405
| 0.216346
| 208
| 9
| 49
| 23.111111
| 0.858896
| 0.048077
| 0
| 0
| 0
| 0
| 0.188776
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.166667
| false
| 0
| 0.333333
| 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
| 0
| 0
| 1
| 0
| 1
| 0
|
0
| 4
|
fd391650bba99a22d3fd3f7a8a55b5d27a3bc7ac
| 2,085
|
py
|
Python
|
hwtLib/tests/pyUtils/fileUtils_test.py
|
optical-o/hwtLib
|
edad621f5ad4cdbea20a5751ff4468979afe2f77
|
[
"MIT"
] | 24
|
2017-02-23T10:00:50.000Z
|
2022-01-28T12:20:21.000Z
|
hwtLib/tests/pyUtils/fileUtils_test.py
|
optical-o/hwtLib
|
edad621f5ad4cdbea20a5751ff4468979afe2f77
|
[
"MIT"
] | 32
|
2017-04-28T10:29:34.000Z
|
2021-04-27T09:16:43.000Z
|
hwtLib/tests/pyUtils/fileUtils_test.py
|
optical-o/hwtLib
|
edad621f5ad4cdbea20a5751ff4468979afe2f77
|
[
"MIT"
] | 8
|
2019-09-19T03:34:36.000Z
|
2022-01-21T06:56:58.000Z
|
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
import errno
import os
from os.path import join
from tempfile import TemporaryDirectory
import unittest
from hwt.pyUtils.fileHelpers import find_files
class FileUtilsTC(unittest.TestCase):
def mkFile(self, d, fileName):
fileName = join(d, fileName)
if not os.path.exists(os.path.dirname(fileName)):
try:
os.makedirs(os.path.dirname(fileName))
except OSError as exc:
# Guard against race condition
if exc.errno != errno.EEXIST:
raise
open(fileName, 'w').close()
return fileName
def assertFound(self, directory, pattern, fileNames, recursive=True):
f = set(find_files(directory, pattern, recursive=recursive))
self.assertEqual(f, set(fileNames))
def test_basic(self):
with TemporaryDirectory() as d:
self.assertFound(d, "*", {})
a = self.mkFile(d, "a.a")
self.assertFound(d, "*", {a})
self.assertFound(d, "*.a", {a})
self.assertFound(d, "*.*", {a})
self.assertFound(d, "a.*", {a})
self.assertFound(d, "b.*", {})
self.assertFound(d, "*.b", {})
self.assertFound(d, "", {})
a2 = self.mkFile(d, "a2.a")
self.assertFound(d, "*", {a, a2})
self.assertFound(d, "*.a", {a, a2})
self.assertFound(d, "*.*", {a, a2})
self.assertFound(d, "a.*", {a})
a3 = self.mkFile(d, join("a", "b", "c", "d.a"))
self.assertFound(d, "*", {a, a2, a3})
self.assertFound(d, "*.a", {a, a2, a3})
self.assertFound(d, "*.*", {a, a2, a3})
self.assertFound(d, "a.*", {a})
self.assertFound(d, "*", {a, a2}, recursive=False)
if __name__ == "__main__":
suite = unittest.TestSuite()
# suite.addTest(FrameTmplTC('test_sWithStartPadding'))
suite.addTest(unittest.makeSuite(FileUtilsTC))
runner = unittest.TextTestRunner(verbosity=3)
runner.run(suite)
| 32.578125
| 73
| 0.543885
| 237
| 2,085
| 4.734177
| 0.337553
| 0.227273
| 0.242424
| 0.212121
| 0.28877
| 0.270053
| 0.263815
| 0.229947
| 0.229947
| 0.214795
| 0
| 0.010774
| 0.28777
| 2,085
| 63
| 74
| 33.095238
| 0.744781
| 0.059952
| 0
| 0.06383
| 0
| 0
| 0.030675
| 0
| 0
| 0
| 0
| 0
| 0.404255
| 1
| 0.06383
| false
| 0
| 0.12766
| 0
| 0.234043
| 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
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
fd4de65b282992f7c10fe53ba0b9068648a93a33
| 276
|
py
|
Python
|
ubcs_auxiliary/threading.py
|
vstadnytskyi/auxiliary
|
3916af3a147f72071388278385d484b9eacbc66b
|
[
"BSD-3-Clause"
] | null | null | null |
ubcs_auxiliary/threading.py
|
vstadnytskyi/auxiliary
|
3916af3a147f72071388278385d484b9eacbc66b
|
[
"BSD-3-Clause"
] | 1
|
2019-10-16T16:40:27.000Z
|
2019-10-16T16:40:27.000Z
|
ubcs_auxiliary/threading.py
|
vstadnytskyi/auxiliary
|
3916af3a147f72071388278385d484b9eacbc66b
|
[
"BSD-3-Clause"
] | 1
|
2020-01-18T05:57:41.000Z
|
2020-01-18T05:57:41.000Z
|
from .multithreading import *
import warnings
warnings.simplefilter('always', DeprecationWarning)
warnings.warn("The 'ubcs_auxiliary.threading' class was renamed to 'ubcs_auxiliary.multithreading' to make room for 'multithreading' and 'multiprocessing'", DeprecationWarning )
| 55.2
| 177
| 0.826087
| 30
| 276
| 7.533333
| 0.7
| 0.115044
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.086957
| 276
| 4
| 178
| 69
| 0.896825
| 0
| 0
| 0
| 0
| 0.25
| 0.525362
| 0.206522
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.5
| 0
| 0.5
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 4
|
fd4eb1176b36c3448731abb909b438f0f69fa2df
| 119
|
py
|
Python
|
templates/_app_name_/manage/stores.py
|
opreaalex/skeletout
|
5cd9772ddc7062c0d1fb02bc1a9b0a97b7ef68d9
|
[
"MIT"
] | null | null | null |
templates/_app_name_/manage/stores.py
|
opreaalex/skeletout
|
5cd9772ddc7062c0d1fb02bc1a9b0a97b7ef68d9
|
[
"MIT"
] | null | null | null |
templates/_app_name_/manage/stores.py
|
opreaalex/skeletout
|
5cd9772ddc7062c0d1fb02bc1a9b0a97b7ef68d9
|
[
"MIT"
] | null | null | null |
# -*- coding: utf-8 -*-
"""
_app_name_.manage.stores
~~~~~~~~~~~~~~~~~~~~~~
store management commands
"""
| 14.875
| 29
| 0.462185
| 10
| 119
| 5.2
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.010638
| 0.210084
| 119
| 7
| 30
| 17
| 0.542553
| 0.815126
| 0
| null | 0
| 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
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
b5d2bf02f820e4daf26db95dccfc0adc9ba806b8
| 166
|
py
|
Python
|
tests/test_minifigs.py
|
Brickster/brickset-cli
|
b3f3bebe81e0b65547046d88250a0d32e5348749
|
[
"MIT"
] | null | null | null |
tests/test_minifigs.py
|
Brickster/brickset-cli
|
b3f3bebe81e0b65547046d88250a0d32e5348749
|
[
"MIT"
] | null | null | null |
tests/test_minifigs.py
|
Brickster/brickset-cli
|
b3f3bebe81e0b65547046d88250a0d32e5348749
|
[
"MIT"
] | 1
|
2021-06-29T03:50:56.000Z
|
2021-06-29T03:50:56.000Z
|
import unittest
class TestMinifigs(unittest.TestCase):
def test_getMinifigs(self):
self.fail()
def test_updateMinifigs(self):
self.fail()
| 15.090909
| 38
| 0.674699
| 18
| 166
| 6.111111
| 0.611111
| 0.127273
| 0.218182
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.228916
| 166
| 10
| 39
| 16.6
| 0.859375
| 0
| 0
| 0.333333
| 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
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 1
| 0
|
0
| 4
|
b5f09dff3feaefe53a976b2c34afdd253de3da06
| 610
|
py
|
Python
|
tests/multivariate/test_necessary_conditional_entropy.py
|
Ejjaffe/dit
|
c9d206f03d1de5a0a298b1d0ea9d79ea5e789ee1
|
[
"BSD-3-Clause"
] | 1
|
2020-03-13T10:30:11.000Z
|
2020-03-13T10:30:11.000Z
|
tests/multivariate/test_necessary_conditional_entropy.py
|
Ejjaffe/dit
|
c9d206f03d1de5a0a298b1d0ea9d79ea5e789ee1
|
[
"BSD-3-Clause"
] | null | null | null |
tests/multivariate/test_necessary_conditional_entropy.py
|
Ejjaffe/dit
|
c9d206f03d1de5a0a298b1d0ea9d79ea5e789ee1
|
[
"BSD-3-Clause"
] | null | null | null |
"""
Tests for dit.multivariate.necessary_conditional_entropy.
"""
import pytest
from dit.distconst import uniform
from dit.multivariate.necessary_conditional_entropy import necessary_conditional_entropy
def test_1():
"""
"""
d = uniform(['0000', '0001', '0010', '0100', '0101', '1000', '1001', '1010'])
assert necessary_conditional_entropy(d, [0, 1], [2, 3]) == pytest.approx(0.68872187554086695)
assert necessary_conditional_entropy(d, [2, 3], [0, 1]) == pytest.approx(0.68872187554086695)
assert necessary_conditional_entropy(d, [1], [2, 3]) == pytest.approx(0.68872187554086695)
| 33.888889
| 97
| 0.711475
| 75
| 610
| 5.613333
| 0.4
| 0.285036
| 0.384798
| 0.235154
| 0.698337
| 0.617577
| 0.389549
| 0.304038
| 0.304038
| 0
| 0
| 0.184906
| 0.131148
| 610
| 17
| 98
| 35.882353
| 0.609434
| 0.093443
| 0
| 0
| 0
| 0
| 0.059925
| 0
| 0
| 0
| 0
| 0
| 0.375
| 1
| 0.125
| false
| 0
| 0.375
| 0
| 0.5
| 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
| 0
| 0
| 1
| 0
| 0
| 0
|
0
| 4
|
bd0eac843078a4dfd46377d3f10b07d9b5c3c164
| 127
|
py
|
Python
|
__init__.py
|
andyceo/pylibs
|
df2eec6f9903e27ab02a82688378207eedb1b419
|
[
"MIT"
] | 1
|
2019-10-28T08:56:41.000Z
|
2019-10-28T08:56:41.000Z
|
__init__.py
|
andyceo/pylibs
|
df2eec6f9903e27ab02a82688378207eedb1b419
|
[
"MIT"
] | null | null | null |
__init__.py
|
andyceo/pylibs
|
df2eec6f9903e27ab02a82688378207eedb1b419
|
[
"MIT"
] | null | null | null |
#!/usr/bin/python3
import os
import sys
sys.path.append(os.path.dirname(os.path.abspath(__file__)))
from config import config
| 18.142857
| 59
| 0.779528
| 21
| 127
| 4.52381
| 0.619048
| 0.126316
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.008621
| 0.086614
| 127
| 6
| 60
| 21.166667
| 0.810345
| 0.133858
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.75
| 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
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 4
|
bd46b4804cb59f1e89481b70d7da0b3aa44630c4
| 125
|
py
|
Python
|
30-Days-Of-Python/30-Days-Of-Python/my_module.py
|
zhaobingwang/python-samples
|
d59f84d2b967cc793cb9b8999f8cdef349fd6fd5
|
[
"MIT"
] | null | null | null |
30-Days-Of-Python/30-Days-Of-Python/my_module.py
|
zhaobingwang/python-samples
|
d59f84d2b967cc793cb9b8999f8cdef349fd6fd5
|
[
"MIT"
] | null | null | null |
30-Days-Of-Python/30-Days-Of-Python/my_module.py
|
zhaobingwang/python-samples
|
d59f84d2b967cc793cb9b8999f8cdef349fd6fd5
|
[
"MIT"
] | null | null | null |
def generate_full_name(firstname, lastname):
space = ' '
fullname = firstname + space + lastname
return fullname
| 25
| 44
| 0.696
| 13
| 125
| 6.538462
| 0.692308
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.224
| 125
| 4
| 45
| 31.25
| 0.876289
| 0
| 0
| 0
| 1
| 0
| 0.008
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.25
| false
| 0
| 0
| 0
| 0.5
| 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
| 0
| 0
|
0
| 4
|
9520815fc23c2cd96ae0cc285b907dd88c922aa2
| 31
|
py
|
Python
|
mihifepe/fdr/__init__.py
|
cloudbopper/feature-importance-analysis
|
7f03e4413d1e42e9265d790cb64c41f34dbea5ab
|
[
"MIT"
] | 1
|
2019-11-01T12:31:45.000Z
|
2019-11-01T12:31:45.000Z
|
mihifepe/fdr/__init__.py
|
cloudbopper/feature-importance-analysis
|
7f03e4413d1e42e9265d790cb64c41f34dbea5ab
|
[
"MIT"
] | 10
|
2018-11-14T17:44:39.000Z
|
2020-01-02T03:25:14.000Z
|
mihifepe/fdr/__init__.py
|
cloudbopper/mihifepe
|
7f03e4413d1e42e9265d790cb64c41f34dbea5ab
|
[
"MIT"
] | 3
|
2018-11-14T04:17:17.000Z
|
2020-01-04T20:32:00.000Z
|
"""Hierarchical FDR control"""
| 15.5
| 30
| 0.709677
| 3
| 31
| 7.333333
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.096774
| 31
| 1
| 31
| 31
| 0.785714
| 0.774194
| 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
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
953462eaa8b3d03e1f053ecc9a8d6ecf62e1d004
| 143
|
py
|
Python
|
webgen/testing123.py
|
francis-chris5/Useful-Python-Tools
|
122ae3d8db02ccc9dacfd0262fc1b7c3c4357326
|
[
"MIT"
] | null | null | null |
webgen/testing123.py
|
francis-chris5/Useful-Python-Tools
|
122ae3d8db02ccc9dacfd0262fc1b7c3c4357326
|
[
"MIT"
] | null | null | null |
webgen/testing123.py
|
francis-chris5/Useful-Python-Tools
|
122ae3d8db02ccc9dacfd0262fc1b7c3c4357326
|
[
"MIT"
] | null | null | null |
x = 3
y = 4
def Double(x):
return 2 * x
def Product(x, y):
return x * y
def SayHi():
print("Hello World!!!")
| 8.9375
| 28
| 0.454545
| 22
| 143
| 2.954545
| 0.590909
| 0.061538
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.034884
| 0.398601
| 143
| 15
| 29
| 9.533333
| 0.72093
| 0
| 0
| 0
| 0
| 0
| 0.110236
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.375
| false
| 0
| 0
| 0.25
| 0.625
| 0.125
| 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
| 1
| 0
| 0
| 0
| 1
| 1
| 0
|
0
| 4
|
1f191d86b7669f2865e1bdd6b93169c000cd9c03
| 19,542
|
py
|
Python
|
utils.py
|
nishiwen1214/electra4zero-shot
|
c4af8dad0854c9e309081e102158fc65e50f802a
|
[
"MIT"
] | 1
|
2022-03-23T11:13:20.000Z
|
2022-03-23T11:13:20.000Z
|
utils.py
|
nishiwen1214/electra4zero-shot
|
c4af8dad0854c9e309081e102158fc65e50f802a
|
[
"MIT"
] | null | null | null |
utils.py
|
nishiwen1214/electra4zero-shot
|
c4af8dad0854c9e309081e102158fc65e50f802a
|
[
"MIT"
] | null | null | null |
#! /usr/bin/env python
# -*- coding: utf-8 -*-
# __author__ = "Shiwen Ni"
# Date: 2021/12/12
import csv
import json
import random
class Datasets():
def __init__(self, dataset_name=""):
self.dataset_name = dataset_name
self.patterns = []
self.train_path, self.dev_path, self.test_path = "", "", ""
if (dataset_name == 'SST-2'):
self.train_path = r"./datasets/GLUE/SST-2/train.tsv"
self.dev_path = r"./datasets/GLUE/SST-2/train.tsv"
self.test_path = r"./datasets/GLUE/SST-2/dev.tsv"
self.metric = 'Acc'
self.label_texts = ['terrible','great']
self.templates = ["This movie is [label]!!"]
self.patterns = [[template.replace('[label]', label) for label in self.label_texts] for template in
self.templates]
elif (dataset_name == 'CoLA'):
self.train_path = r"./datasets/GLUE/CoLA/train.tsv"
self.dev_path = r"./datasets/GLUE/CoLA/train.tsv"
self.test_path = r"./datasets/GLUE/CoLA/dev.tsv"
self.metric = 'Matthews'
self.label_texts = ["wrong", "correct"]
self.templates = ["The grammar of the following sentence is [label],"]
self.patterns = [[template.replace('[label]', label) for label in self.label_texts] for template in
self.templates]
elif (dataset_name == 'MR'):
self.train_path = r"./datasets/others/MR/train.csv"
self.dev_path = r"./datasets/others/MR/train.csv"
self.test_path = r"./datasets/others/MR/test.csv"
self.metric = 'Acc'
self.label_texts = ["terrible", "great"]
self.templates = ["It was [label]!"]
self.patterns = [[template.replace('[label]', label) for label in self.label_texts] for template in
self.templates]
elif (dataset_name == 'CR'):
self.train_path = r"./datasets/others/CR/train.csv"
self.dev_path = r"./datasets/others/CR/train.csv"
self.test_path = r"./datasets/others/CR/test.csv"
self.metric = 'Acc'
self.label_texts = ["hate", "love"]
self.templates = ["I really [label] this product."]
self.patterns = [[template.replace('[label]', label) for label in self.label_texts] for template in
self.templates]
elif (dataset_name == 'MPQA'):
self.train_path = r"./datasets/others/MPQA/train.csv"
self.dev_path = r"./datasets/others/MPQA/train.csv"
self.test_path = r"./datasets/others/MPQA/test.csv"
self.metric = 'Acc'
self.label_texts = ["not", "really"]
self.templates = ["[label] good,"]
self.patterns = [[template.replace('[label]', label) for label in self.label_texts] for template in
self.templates]
elif (dataset_name == 'Subj'):
self.train_path = r"./datasets/others/Subj/train.csv"
self.dev_path = r"./datasets/others/Subj/train.csv"
self.test_path = r"./datasets/others/Subj/test.csv"
self.metric = 'Acc'
self.label_texts = ['Objectively',"Subjectively"]
self.templates = ["[label] speaking."]
self.patterns = [[template.replace('[label]', label) for label in self.label_texts] for template in
self.templates]
elif (dataset_name == 'TREC'):
self.train_path = r"./datasets/others/TREC/train.csv"
self.dev_path = r"./datasets/others/TREC/train.csv"
self.test_path = r"./datasets/others/TREC/test.csv"
self.metric = 'Acc'
self.label_texts = ["definition", "entity", "meaning", "person", "place", "number"]
self.templates = ["The answer is about a [label],"]
self.patterns = [[template.replace('[label]', label) for label in self.label_texts] for template in
self.templates]
elif (dataset_name == 'SST-5'):
self.train_path = r"./datasets/others/SST-5/train.csv"
self.dev_path = r"./datasets/others/SST-5/train.csv"
self.test_path = r"./datasets/others/SST-5/test.csv"
self.metric = 'Acc'
self.label_texts = ["terrible", "bad", "okay", "good", "perfect"]
self.templates = ["This movie is [label]."]
self.patterns = [[template.replace('[label]', label) for label in self.label_texts] for template in
self.templates]
elif (dataset_name == "QQP"):
self.train_path = r"./datasets/GLUE/QQP/train.tsv"
self.dev_path = r"./datasets/GLUE/QQP/train.tsv"
self.test_path = r"./datasets/GLUE/QQP/dev.tsv"
self.labels = [0, 1]
self.metric = 'F1'
self.label_texts = ["no", "yes"]
self.templates = ["? [label],"]
self.patterns = [[template.replace('[label]', label) for label in self.label_texts] for template in
self.templates]
elif (dataset_name == "MRPC"):
self.train_path = r"./datasets/GLUE/MRPC/msr_paraphrase_train.txt"
self.dev_path = r"./datasets/GLUE/MRPC/msr_paraphrase_train.txt"
self.test_path = r"./datasets/GLUE/MRPC/msr_paraphrase_test.txt"
self.labels = [0, 1]
self.metric = 'F1'
self.label_texts = ["no", "yes"]
self.templates = ["[label],"]
self.patterns = [[template.replace('[label]', label) for label in self.label_texts] for template in
self.templates]
elif (dataset_name == "QNLI"):
self.train_path = r"./datasets/GLUE/QNLI/train.tsv"
self.dev_path = r"./datasets/GLUE/QNLI/train.tsv"
self.test_path = r"./datasets/GLUE/QNLI/dev.tsv"
self.metric = 'Acc'
self.text2id = {"not_entailment": 0, "entailment": 1}
self.labels = [0, 1]
self.label_texts = ["no", "yes"]
self.templates = ["? [label]!"]
self.patterns = [[template.replace('[label]', label) for label in self.label_texts] for template in
self.templates]
elif (dataset_name == "WNLI"):
self.train_path = r"./datasets/GLUE/WNLI/train.tsv"
self.dev_path = r"./datasets/GLUE/WNLI/train.tsv"
self.test_path = r"./datasets/GLUE/WNLI/dev.tsv"
self.metric = 'Acc'
self.labels = [0, 1]
self.label_texts = ["no", "yes"]
self.templates = ["? [label],"]
self.patterns = [[template.replace('[label]', label) for label in self.label_texts] for template in
self.templates]
elif (dataset_name == "MNLI-mm"):
self.train_path = r"./datasets/GLUE/MNLI/train.tsv"
self.dev_path = r"./datasets/GLUE/MNLI/dev_matched.tsv"
self.test_path = r"./datasets/GLUE/MNLI/dev_matched.tsv"
self.metric = 'Acc'
self.text2id = {"contradiction": 0, "neutral": 1, "entailment": 2}
self.labels = [0, 1, 2]
self.label_texts = ["no", "maybe", "yes"]
self.templates = ["? [label],"]
self.patterns = [[template.replace('[label]', label) for label in self.label_texts] for template in
self.templates]
elif (dataset_name == "MNLI"):
self.train_path = r"./datasets/GLUE/MNLI/train.tsv"
self.dev_path = r"./datasets/GLUE/MNLI/dev_mismatched.tsv"
self.test_path = r"./datasets/GLUE/MNLI/dev_mismatched.tsv"
self.metric = 'Acc'
self.text2id = {"contradiction": 0, "neutral": 1, "entailment": 2}
self.labels = [0, 1, 2]
self.label_texts = ["no", "maybe", "yes"]
self.templates = ["? [label],"]
self.patterns = [[template.replace('[label]', label) for label in self.label_texts] for template in
self.templates]
elif (dataset_name == "SNLI"):
self.train_path = r"./datasets/others/SNLI/train.tsv"
self.dev_path = r"./datasets/others/SNLI/dev.tsv"
self.test_path = r"./datasets/others/SNLI/test.tsv"
self.metric = 'Acc'
self.text2id = {"contradiction": 0, "neutral": 1, "entailment": 2}
self.labels = [0, 1, 2]
self.label_texts = ["no", "maybe", "yes"]
self.templates = ["? [label],"]
self.patterns = [[template.replace('[label]', label) for label in self.label_texts] for template in
self.templates]
elif (dataset_name == "RTE"):
self.train_path = r"./datasets/GLUE/RTE/train.tsv"
self.dev_path = r"./datasets/GLUE/RTE/train.tsv"
self.test_path = r"./datasets/GLUE/RTE/dev.tsv"
self.metric = 'Acc'
self.text2id = { "not_entailment": 0, "entailment": 1}
self.labels = [0, 1]
self.label_texts = ["no", "yes"]
self.templates = ["? [label]!"]
self.patterns = [[template.replace('[label]', label) for label in self.label_texts] for template in
self.templates]
elif (dataset_name == "STS-B"):
self.train_path = r"./datasets/GLUE/STS-B/train.tsv"
self.dev_path = r"./datasets/GLUE/STS-B/train.tsv"
self.test_path = r"./datasets/GLUE/STS-B/dev.tsv"
self.metric = 'Pear'
self.label_texts = ["no"]
self.templates = ["? [label]!!"]
self.patterns = [[template.replace('[label]', label) for label in self.label_texts] for template in
self.templates]
def load_data(self, filename, sample_num=-1, is_train=False, is_shuffle=False):
D = []
if (self.dataset_name == "QQP"):
with open(filename, encoding='utf-8') as f:
for i, l in enumerate(f.readlines()):
if (i == 0):
continue
rows = l.strip().split('\t')
text_a = rows[-3]
text_b = rows[-2]
label = rows[-1]
text_a = text_a
D.append((text_a + "[SEP]" + text_b, int(label)))
elif (self.dataset_name == "MRPC"):
with open(filename, encoding='utf-8') as f:
for i, l in enumerate(f.readlines()):
if (i == 0):
continue
rows = l.strip().split('\t')
text_a = rows[-1]
text_b = rows[-2]
label = rows[0]
text_a = text_a
D.append((text_a + "[SEP]" + text_b, int(label)))
elif (self.dataset_name == "QNLI"):
with open(filename, encoding='utf-8') as f:
for i, l in enumerate(f.readlines()):
if (i == 0):
continue
rows = l.strip().split('\t')
text_a = rows[-3]
text_b = rows[-2]
label = rows[-1]
text_a = text_a
D.append((text_a + "[SEP]" + text_b, self.text2id[label] ))
elif (self.dataset_name == "WNLI"):
with open(filename, encoding='utf-8') as f:
for i, l in enumerate(f.readlines()):
if (i == 0):
continue
rows = l.strip().split('\t')
text_a = rows[-3]
text_b = rows[-2]
label = rows[-1]
D.append(("Sentence 1:" +text_a + "[SEP]" + "Sentence 2:" +text_b, int(label)))
elif (self.dataset_name == "MNLI"):
with open(filename, encoding='utf-8') as f:
for i, l in enumerate(f.readlines()):
if (i == 0):
continue
rows = l.strip().split('\t')
text_a = rows[-8]
text_b = rows[-7]
label = rows[-1]
text_a = text_a
D.append(( text_a + "[SEP]"+ text_b, self.text2id[label]))
elif (self.dataset_name == "MNLI-mm"):
with open(filename, encoding='utf-8') as f:
for i, l in enumerate(f.readlines()):
if (i == 0):
continue
rows = l.strip().split('\t')
text_a = rows[-8]
text_b = rows[-7]
label = rows[-1]
text_a = text_a
D.append((text_a + "[SEP]" + text_b, self.text2id[label]))
elif (self.dataset_name == "SNLI"):
with open(filename, encoding='utf-8') as f:
for i, l in enumerate(f.readlines()):
if (i == 0):
continue
rows = l.strip().split('\t')
text_a = rows[-8]
text_b = rows[-7]
label = rows[-1]
text_a = text_a
D.append((text_a + "[SEP]" + text_b, self.text2id[label]))
elif (self.dataset_name == "RTE"):
with open(filename, encoding='utf-8') as f:
for i, l in enumerate(f.readlines()):
if (i == 0):
continue
rows = l.strip().split('\t')
text_a = rows[-3]
text_b = rows[-2]
label = rows[-1]
D.append((text_a + "[SEP]" + text_b , self.text2id[label]))
elif (self.dataset_name == "CoLA"):
with open(filename, encoding='utf-8') as f:
for i, l in enumerate(f.readlines()):
if (i == 0):
continue
rows = l.strip().split('\t')
text = rows[-1]
label = rows[-3]
D.append((text, int(label)))
elif (self.dataset_name == "STS-B"):
with open(filename, encoding='utf-8') as f:
for i, l in enumerate(f.readlines()):
if (i == 0):
continue
rows = l.strip().split('\t')
text_a = rows[-3]
text_b = rows[-2]
score = rows[-1]
text_a = text_a
D.append((text_a + "[SEP]" + text_b, float(score)))
elif (self.dataset_name == "SST-2"):
with open(filename, encoding='utf-8') as f:
for i, l in enumerate(f.readlines()):
if (i == 0):
continue
rows = l.strip().split('\t')
text = rows[-2]
label = rows[-1]
D.append((text, int(label)))
elif (self.dataset_name == "SST-5"):
with open(filename, encoding='utf-8') as f:
for i, l in enumerate(f.readlines()):
text = l[2:]
label = l[0]
D.append((text, int(label)))
elif (self.dataset_name == "MR"):
with open(filename, encoding='utf-8') as f:
for i, l in enumerate(f.readlines()):
text = l[2:]
text = text.lstrip('"').rstrip('"')
label = l[0]
D.append((text, int(label)))
elif (self.dataset_name == "CR"):
with open(filename, encoding='utf-8') as f:
for i, l in enumerate(f.readlines()):
text = l[2:]
text = text.lstrip('"').rstrip('"')
label = l[0]
D.append((text, int(label)))
elif (self.dataset_name == "MPQA"):
with open(filename, encoding='utf-8') as f:
for i, l in enumerate(f.readlines()):
text = l[2:]
text = text.lstrip('"').rstrip('"')
label = l[0]
D.append((text, int(label)))
elif (self.dataset_name == "Subj"):
with open(filename, encoding='utf-8') as f:
for i, l in enumerate(f.readlines()):
text = l[2:]
text = text.lstrip('"').rstrip('"')
label = l[0]
D.append((text, int(label)))
elif (self.dataset_name == "TREC"):
with open(filename, encoding='utf-8') as f:
for i, l in enumerate(f.readlines()):
text = l[2:]
text = text.lstrip('"').rstrip('"')
label = l[0]
D.append((text, int(label)))
# Shuffle the dataset.
if (is_shuffle):
random.seed(1)
random.shuffle(D)
# Set the number of samples.
if (sample_num == -1):
# -1 for all the samples
return D
else:
return D[:sample_num + 1]
class Model():
def __init__(self, model_name=""):
self.model_name = model_name
self.config_path, self.checkpoint_path, self.dict_path = "", "", ""
if (model_name == 'electra-small'):
self.config_path = './models/electra_small/small_discriminator_config.json'
self.checkpoint_path = './models/electra_small/electra_small'
self.dict_path = './models/electra_small/vocab.txt'
elif (model_name == 'electra-base'):
self.config_path = './models/electra_base/base_discriminator_config.json'
self.checkpoint_path = './models/electra_base/electra_base'
self.dict_path = './models/electra_base/vocab.txt'
elif (model_name == 'electra-large'):
self.config_path = './models/electra_large/large_discriminator_config.json'
self.checkpoint_path = './models/electra_large/electra_large'
self.dict_path = './models/electra_large/vocab.txt'
def read_labels(label_file_path):
labels_text = []
text2id = {}
with open(label_file_path, 'r', encoding='utf-8') as f:
for index, line in enumerate(f.readlines()):
label = line.strip('\n')
labels_text.append(label)
text2id[label] = index
return labels_text, text2id
def sample_dataset(data: list, k_shot: int, label_num=-1):
if(k_shot==-1):
return data
label_set = set()
label2samples = {}
for d in data:
(text, label) = d
label_set.add(label)
if (label in label2samples):
label2samples[label].append(d)
else:
label2samples[label] = [d]
if (label_num != -1):
assert len(label_set) == label_num
new_data = []
for label in label_set:
if (isinstance(label, float)):
random.seed(0)
new_data = random.sample(data, k_shot)
random.shuffle(new_data)
return new_data
random.seed(0)
new_data += random.sample(label2samples[label], k_shot)
random.seed(0)
random.shuffle(new_data)
return new_data
| 44.013514
| 111
| 0.496009
| 2,253
| 19,542
| 4.182867
| 0.07945
| 0.027589
| 0.070352
| 0.054117
| 0.824597
| 0.800509
| 0.764962
| 0.745013
| 0.603565
| 0.557831
| 0
| 0.0125
| 0.361376
| 19,542
| 443
| 112
| 44.112867
| 0.742628
| 0.007983
| 0
| 0.561538
| 0
| 0
| 0.162134
| 0.101914
| 0
| 0
| 0
| 0
| 0.002564
| 1
| 0.012821
| false
| 0
| 0.007692
| 0
| 0.041026
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 0
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| null | 0
| 0
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| 0
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| 0
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| 0
| 0
| 0
| 0
|
0
| 4
|
1f2b7592d36799c1d3fd4acf167b3f3b12ce6737
| 77
|
py
|
Python
|
Lib/site-packages/pyvel/games/__init__.py
|
raychorn/svn_Python-2.5.1
|
425005b1b489ba44ec0bb989e077297e8953d9be
|
[
"PSF-2.0"
] | null | null | null |
Lib/site-packages/pyvel/games/__init__.py
|
raychorn/svn_Python-2.5.1
|
425005b1b489ba44ec0bb989e077297e8953d9be
|
[
"PSF-2.0"
] | null | null | null |
Lib/site-packages/pyvel/games/__init__.py
|
raychorn/svn_Python-2.5.1
|
425005b1b489ba44ec0bb989e077297e8953d9be
|
[
"PSF-2.0"
] | null | null | null |
r"""This package contains sample
game handlers for PyVel"""
import tictactoe
| 19.25
| 32
| 0.792208
| 11
| 77
| 5.545455
| 1
| 0
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| 0
| 0.12987
| 77
| 3
| 33
| 25.666667
| 0.910448
| 0.675325
| 0
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| 0
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| true
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| 0.5
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| null | 0
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| 1
| 0
| 0
| 0
|
0
| 4
|
1f619e165346a19503b9e12ff64729e2ebcadf5a
| 125
|
py
|
Python
|
CRUD_Django/crudapp/admin.py
|
chandansau/CRUD-Django
|
a4ee0fb9d3bb91d62ec951c96a56cab01fb76f16
|
[
"MIT"
] | 1
|
2019-01-19T06:53:15.000Z
|
2019-01-19T06:53:15.000Z
|
CRUD_Django/crudapp/admin.py
|
chandansau/CRUD-Django
|
a4ee0fb9d3bb91d62ec951c96a56cab01fb76f16
|
[
"MIT"
] | null | null | null |
CRUD_Django/crudapp/admin.py
|
chandansau/CRUD-Django
|
a4ee0fb9d3bb91d62ec951c96a56cab01fb76f16
|
[
"MIT"
] | null | null | null |
from django.contrib import admin
from .models import products
# Register your models here.
admin.site.register(products)
| 25
| 33
| 0.792
| 17
| 125
| 5.823529
| 0.647059
| 0
| 0
| 0
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| 0
| 0
| 0
| 0
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| 0
| 0.144
| 125
| 4
| 34
| 31.25
| 0.925234
| 0.208
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| 0
| true
| 0
| 0.666667
| 0
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| null | 0
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| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 4
|
1f70626b71a172c53996cb63f24a27129652f722
| 624
|
py
|
Python
|
sdk/python/pulumi_k0s/config/vars.py
|
ydkn/pulumi-k0s
|
e562e26fba6a7ceb33d8b0da71543ac5b9215b49
|
[
"Apache-2.0"
] | null | null | null |
sdk/python/pulumi_k0s/config/vars.py
|
ydkn/pulumi-k0s
|
e562e26fba6a7ceb33d8b0da71543ac5b9215b49
|
[
"Apache-2.0"
] | null | null | null |
sdk/python/pulumi_k0s/config/vars.py
|
ydkn/pulumi-k0s
|
e562e26fba6a7ceb33d8b0da71543ac5b9215b49
|
[
"Apache-2.0"
] | null | null | null |
# coding=utf-8
# *** WARNING: this file was generated by pulumigen. ***
# *** Do not edit by hand unless you're certain you know what you are doing! ***
import warnings
import pulumi
import pulumi.runtime
from typing import Any, Mapping, Optional, Sequence, Union, overload
from .. import _utilities
import types
__config__ = pulumi.Config('k0s')
class _ExportableConfig(types.ModuleType):
@property
def no_drain(self) -> Optional[bool]:
return __config__.get_bool('noDrain')
@property
def skip_downgrade_check(self) -> Optional[bool]:
return __config__.get_bool('skipDowngradeCheck')
| 24.96
| 80
| 0.722756
| 79
| 624
| 5.468354
| 0.683544
| 0.055556
| 0.074074
| 0.101852
| 0.162037
| 0.162037
| 0.162037
| 0
| 0
| 0
| 0
| 0.003876
| 0.173077
| 624
| 24
| 81
| 26
| 0.833333
| 0.233974
| 0
| 0.142857
| 1
| 0
| 0.059197
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.142857
| false
| 0
| 0.428571
| 0.142857
| 0.785714
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
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| 0
| 0
| 0
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| 0
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| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 1
| 0
|
0
| 4
|
1f813a18cdb1ae587107cf0ec026a8a841b5bc17
| 145
|
py
|
Python
|
main.py
|
zguangyu/epen
|
e7d7c3cbac546af1fa8556ea2d1859a4c9507097
|
[
"MIT"
] | 1
|
2015-11-01T13:00:41.000Z
|
2015-11-01T13:00:41.000Z
|
main.py
|
zguangyu/epen
|
e7d7c3cbac546af1fa8556ea2d1859a4c9507097
|
[
"MIT"
] | null | null | null |
main.py
|
zguangyu/epen
|
e7d7c3cbac546af1fa8556ea2d1859a4c9507097
|
[
"MIT"
] | null | null | null |
from epen import app
from flask.ext.script import Manager
app.debug = True
manager = Manager(app)
if __name__ == '__main__':
manager.run()
| 16.111111
| 36
| 0.724138
| 21
| 145
| 4.619048
| 0.666667
| 0.206186
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.172414
| 145
| 8
| 37
| 18.125
| 0.808333
| 0
| 0
| 0
| 0
| 0
| 0.055172
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.333333
| 0
| 0.333333
| 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
| 1
| 0
| 0
| 0
|
0
| 4
|
2f26c296ff02f8db95b067cc396cc7baa3148840
| 824
|
py
|
Python
|
test.py
|
AlcindoSchleder/flaskWeb
|
1f9ba3a3ac8546c24126124d4c34335825b94df9
|
[
"MIT"
] | null | null | null |
test.py
|
AlcindoSchleder/flaskWeb
|
1f9ba3a3ac8546c24126124d4c34335825b94df9
|
[
"MIT"
] | null | null | null |
test.py
|
AlcindoSchleder/flaskWeb
|
1f9ba3a3ac8546c24126124d4c34335825b94df9
|
[
"MIT"
] | 1
|
2019-08-16T23:42:05.000Z
|
2019-08-16T23:42:05.000Z
|
# -*- coding: utf-8 -*-
from unittest import TestCase
from workspaces.home.service import ValidationInput as VI
class TestInput(TestCase):
def test_CheckStringValue(self):
vi = VI()
self.assertEqual(vi.CheckStringValue('121426')['status'], 401)
self.assertEqual(vi.CheckStringValue('523563')['status'], 200)
self.assertEqual(vi.CheckStringValue('552523')['status'], 401)
self.assertEqual(vi.CheckStringValue('112233')['status'], 200)
self.assertEqual(vi.CheckStringValue('AG7688')['status'], 401)
self.assertEqual(vi.CheckStringValue('543F67')['status'], 401)
self.assertEqual(vi.CheckStringValue('1987878')['status'], 401)
self.assertEqual(vi.CheckStringValue('002398')['status'], 401)
# run test
if __name__ == '__main__':
unittest.main()
| 39.238095
| 71
| 0.682039
| 87
| 824
| 6.356322
| 0.402299
| 0.216998
| 0.245931
| 0.477396
| 0.531646
| 0.531646
| 0
| 0
| 0
| 0
| 0
| 0.102158
| 0.156553
| 824
| 21
| 72
| 39.238095
| 0.693525
| 0.036408
| 0
| 0
| 0
| 0
| 0.132576
| 0
| 0
| 0
| 0
| 0
| 0.533333
| 1
| 0.066667
| false
| 0
| 0.133333
| 0
| 0.266667
| 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
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
2f5d40423aecdf0792b97f9d59d64a3b5e86254d
| 145
|
py
|
Python
|
week8/practice8_5.py
|
INYEONGKIM/programming-fundamentals
|
498fda3cd6cabf5eb3dcc6d8f098d5584bfdddb5
|
[
"MIT"
] | null | null | null |
week8/practice8_5.py
|
INYEONGKIM/programming-fundamentals
|
498fda3cd6cabf5eb3dcc6d8f098d5584bfdddb5
|
[
"MIT"
] | null | null | null |
week8/practice8_5.py
|
INYEONGKIM/programming-fundamentals
|
498fda3cd6cabf5eb3dcc6d8f098d5584bfdddb5
|
[
"MIT"
] | null | null | null |
def more(message):
answer = input(message)
while not (answer=="y" or answer=="n"):
answer = input(message)
return answer=="y"
| 29
| 43
| 0.6
| 19
| 145
| 4.578947
| 0.578947
| 0.252874
| 0.413793
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.234483
| 145
| 5
| 44
| 29
| 0.783784
| 0
| 0
| 0.4
| 0
| 0
| 0.020548
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.2
| false
| 0
| 0
| 0
| 0.4
| 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
| 0
| 0
| 0
| 0
|
0
| 4
|
2f7f4a12ae26841128c1d281fce651932f3cb713
| 76
|
py
|
Python
|
learn2learn/text/datasets/__init__.py
|
Brikwerk/learn2learn
|
7997c13c26ec627d13ce77ba98427260df78ada8
|
[
"MIT"
] | 1,774
|
2019-09-05T20:41:16.000Z
|
2022-03-30T09:49:02.000Z
|
learn2learn/text/datasets/__init__.py
|
Kostis-S-Z/learn2learn
|
c0b7c088f15986880b136ec27059644ac513db60
|
[
"MIT"
] | 196
|
2019-09-05T08:11:31.000Z
|
2022-03-31T12:08:25.000Z
|
learn2learn/text/datasets/__init__.py
|
Kostis-S-Z/learn2learn
|
c0b7c088f15986880b136ec27059644ac513db60
|
[
"MIT"
] | 266
|
2019-09-13T10:17:54.000Z
|
2022-03-28T07:17:21.000Z
|
#!/usr/bin/env python3
from .news_classification import NewsClassification
| 19
| 51
| 0.828947
| 9
| 76
| 6.888889
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.014493
| 0.092105
| 76
| 3
| 52
| 25.333333
| 0.884058
| 0.276316
| 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
| 0
| 0
|
0
| 4
|
2f966187086e68a3077dfb79b701a86578035579
| 770
|
py
|
Python
|
lec4.py
|
csalette/isat252
|
cb9a0938b652ac0bf366f7b22a6ec662840bfcbb
|
[
"MIT"
] | null | null | null |
lec4.py
|
csalette/isat252
|
cb9a0938b652ac0bf366f7b22a6ec662840bfcbb
|
[
"MIT"
] | null | null | null |
lec4.py
|
csalette/isat252
|
cb9a0938b652ac0bf366f7b22a6ec662840bfcbb
|
[
"MIT"
] | null | null | null |
"""
Lecture 4
"""
#my_tuple = 'a','b','c','d','e'
#print(my_tuple)
#print(my_tuple[1]) # using index numbers to find the letters we want
#print(my_tuple[0:3]) # using slicing to find multiple letters at once
#print(my_tuple[:])
#my_2nd_tuple = ('a','b','c','d','e') #as long as you have he commas, it is a tuple.
#print(my_2nd_tuple)
#test = ('a',)
#print(type(test,))
#my_car = {
#'color':'red',
#'maker':'toyota',
#'year':2015
#}
#print(my_car)
#print(my_car['year'])
#print(my_car['color'])
#print(my_car.items())
#print(my_car.keys())
#print(my_car.values())
#print(my_car.get('year'))
#my_car['model']='corolla'
#print(my_car)
#my_car['year']='2020'
#print(my_car)
#print(len(my_car))
#print('color' in my_car)
| 22
| 84
| 0.605195
| 128
| 770
| 3.460938
| 0.414063
| 0.221219
| 0.20316
| 0.036117
| 0.045147
| 0.045147
| 0
| 0
| 0
| 0
| 0
| 0.021705
| 0.162338
| 770
| 35
| 85
| 22
| 0.665116
| 0.848052
| 0
| null | 0
| null | 0
| 0
| null | 0
| 0
| 0
| null | 1
| null | true
| 0
| 0
| null | null | null | 0
| 0
| 0
| null | 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
2f9b98d36c82b795929ec96534a9ee7da37e5c3a
| 4,225
|
py
|
Python
|
tests/test_device.py
|
dmulcahey/aioflo
|
0c7e2befc1bc38cd4274f5e75627e4b8b516a93a
|
[
"MIT"
] | 9
|
2020-05-21T02:31:00.000Z
|
2021-10-21T21:24:06.000Z
|
tests/test_device.py
|
dmulcahey/aioflo
|
0c7e2befc1bc38cd4274f5e75627e4b8b516a93a
|
[
"MIT"
] | 48
|
2020-01-16T17:22:47.000Z
|
2022-03-01T18:06:20.000Z
|
tests/test_device.py
|
dmulcahey/aioflo
|
0c7e2befc1bc38cd4274f5e75627e4b8b516a93a
|
[
"MIT"
] | 1
|
2020-07-24T11:41:52.000Z
|
2020-07-24T11:41:52.000Z
|
"""Define tests for device-related endpoints."""
import json
import aiohttp
import pytest
from aioflo import async_get_api
from .common import TEST_DEVICE_ID, TEST_EMAIL_ADDRESS, TEST_PASSWORD, load_fixture
@pytest.mark.asyncio
async def test_get_device_info(aresponses, auth_success_response):
"""Test successfully retrieving device info."""
aresponses.add(
"api.meetflo.com",
"/api/v1/users/auth",
"post",
aresponses.Response(text=json.dumps(auth_success_response), status=200),
)
aresponses.add(
"api-gw.meetflo.com",
"/api/v2/devices/98765",
"get",
aresponses.Response(text=load_fixture("device_info_response.json"), status=200),
)
async with aiohttp.ClientSession() as session:
api = await async_get_api(TEST_EMAIL_ADDRESS, TEST_PASSWORD, session=session)
device_info = await api.device.get_info(TEST_DEVICE_ID)
assert device_info["fwVersion"] == "6.1.1"
assert device_info["isConnected"] is True
assert device_info["macAddress"] == "111111111111"
assert device_info["nickname"] == "Smart Water Shutoff"
@pytest.mark.asyncio
async def test_device_run_health_test(aresponses, auth_success_response):
"""Test successfully running a health test."""
aresponses.add(
"api.meetflo.com",
"/api/v1/users/auth",
"post",
aresponses.Response(text=json.dumps(auth_success_response), status=200),
)
aresponses.add(
"api-gw.meetflo.com",
"/api/v2/devices/98765/healthTest/run",
"post",
aresponses.Response(text=load_fixture("health_test_response.json"), status=200),
)
async with aiohttp.ClientSession() as session:
api = await async_get_api(TEST_EMAIL_ADDRESS, TEST_PASSWORD, session=session)
health_test_response = await api.device.run_health_test(TEST_DEVICE_ID)
assert health_test_response["roundId"] == "123456789-369258147"
assert health_test_response["deviceId"] == "xxxxx"
assert health_test_response["status"] == "pending"
assert health_test_response["type"] == "manual"
@pytest.mark.asyncio
async def test_device_valve_open(aresponses, auth_success_response):
"""Test successfully opening the valve."""
aresponses.add(
"api.meetflo.com",
"/api/v1/users/auth",
"post",
aresponses.Response(text=json.dumps(auth_success_response), status=200),
)
aresponses.add(
"api-gw.meetflo.com",
"/api/v2/devices/98765",
"post",
aresponses.Response(
text=load_fixture("device_open_valve_response.json"), status=200
),
)
async with aiohttp.ClientSession() as session:
api = await async_get_api(TEST_EMAIL_ADDRESS, TEST_PASSWORD, session=session)
device_info = await api.device.open_valve(TEST_DEVICE_ID)
assert device_info["isConnected"] is True
assert device_info["macAddress"] == "111111111111"
assert device_info["nickname"] == "Smart Water Shutoff"
assert device_info["valve"]["target"] == "open"
assert device_info["valve"]["lastKnown"] == "closed"
@pytest.mark.asyncio
async def test_device_valve_close(aresponses, auth_success_response):
"""Test successfully closing the valve."""
aresponses.add(
"api.meetflo.com",
"/api/v1/users/auth",
"post",
aresponses.Response(text=json.dumps(auth_success_response), status=200),
)
aresponses.add(
"api-gw.meetflo.com",
"/api/v2/devices/98765",
"post",
aresponses.Response(
text=load_fixture("device_close_valve_response.json"), status=200
),
)
async with aiohttp.ClientSession() as session:
api = await async_get_api(TEST_EMAIL_ADDRESS, TEST_PASSWORD, session=session)
device_info = await api.device.close_valve(TEST_DEVICE_ID)
assert device_info["isConnected"] is True
assert device_info["macAddress"] == "111111111111"
assert device_info["nickname"] == "Smart Water Shutoff"
assert device_info["valve"]["target"] == "closed"
assert device_info["valve"]["lastKnown"] == "open"
| 36.422414
| 88
| 0.670296
| 501
| 4,225
| 5.431138
| 0.173653
| 0.073502
| 0.082323
| 0.066887
| 0.807056
| 0.774715
| 0.659684
| 0.646821
| 0.61742
| 0.61742
| 0
| 0.032547
| 0.207337
| 4,225
| 115
| 89
| 36.73913
| 0.779934
| 0.009941
| 0
| 0.621053
| 0
| 0
| 0.19325
| 0.053
| 0
| 0
| 0
| 0
| 0.189474
| 1
| 0
| false
| 0.052632
| 0.052632
| 0
| 0.052632
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
|
0
| 4
|
85ccc4830462844d174058a44140747f6376b581
| 457
|
py
|
Python
|
src/btmonitor/auth/rsa_utils.py
|
uudisaru/btmonitor
|
2c32476d1e589a5689054da0906447252ac0868c
|
[
"MIT"
] | null | null | null |
src/btmonitor/auth/rsa_utils.py
|
uudisaru/btmonitor
|
2c32476d1e589a5689054da0906447252ac0868c
|
[
"MIT"
] | null | null | null |
src/btmonitor/auth/rsa_utils.py
|
uudisaru/btmonitor
|
2c32476d1e589a5689054da0906447252ac0868c
|
[
"MIT"
] | null | null | null |
from cryptography.hazmat.backends import default_backend
from cryptography.hazmat.primitives import serialization
def is_encrypted_rsa_key(private_key: str) -> bool:
return 'RSA' in private_key and 'ENCRYPTED' in private_key
def decrypt_private_key(private_key: str, enc_pwd: str):
return serialization.load_pem_private_key(
bytes(private_key, 'utf-8'),
password=bytes(enc_pwd, 'utf-8'),
backend=default_backend(),
)
| 30.466667
| 62
| 0.746171
| 62
| 457
| 5.225806
| 0.467742
| 0.216049
| 0.135802
| 0.098765
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.005222
| 0.161926
| 457
| 14
| 63
| 32.642857
| 0.840731
| 0
| 0
| 0
| 0
| 0
| 0.04814
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.2
| false
| 0.1
| 0.2
| 0.2
| 0.6
| 0
| 0
| 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
| 0
| 0
| 1
| 0
| 1
| 1
| 0
|
0
| 4
|
85de4a2d9e779ad3304e8b9af95a481de36be036
| 175
|
py
|
Python
|
tests/conftest.py
|
estevaoreis25/lispy
|
a1ae65d5862bc9f8a32940e9a9d50d4664f66a26
|
[
"MIT"
] | 5
|
2019-11-01T20:07:50.000Z
|
2020-10-06T17:40:47.000Z
|
tests/conftest.py
|
estevaoreis25/lispy
|
a1ae65d5862bc9f8a32940e9a9d50d4664f66a26
|
[
"MIT"
] | 5
|
2019-10-28T20:16:51.000Z
|
2019-10-28T20:51:55.000Z
|
tests/conftest.py
|
GabrielTiveron/lispy
|
12cc0a382151be75249e152e52ead2cb34d38ac4
|
[
"MIT"
] | 34
|
2019-10-22T17:25:53.000Z
|
2020-10-06T17:40:41.000Z
|
import pytest
from pathlib import Path
examples_path = Path(__file__).parent / 'examples'
@pytest.fixture
def example():
return lambda p: open(examples_path / p).read()
| 19.444444
| 51
| 0.742857
| 24
| 175
| 5.166667
| 0.666667
| 0.193548
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.148571
| 175
| 9
| 51
| 19.444444
| 0.832215
| 0
| 0
| 0
| 0
| 0
| 0.045455
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.166667
| false
| 0
| 0.333333
| 0.166667
| 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
| 0
| 0
| 1
| 1
| 0
| 0
|
0
| 4
|
85df6a022411e66d190b2a33e8d9a560b5ffd0f0
| 95
|
py
|
Python
|
tests/unit/all_Unit.py
|
cmontellanob/PruebasIntegracioncmb
|
d27fa8bca2d108b93b019af7f1603c9de9e00b2f
|
[
"Apache-2.0"
] | null | null | null |
tests/unit/all_Unit.py
|
cmontellanob/PruebasIntegracioncmb
|
d27fa8bca2d108b93b019af7f1603c9de9e00b2f
|
[
"Apache-2.0"
] | null | null | null |
tests/unit/all_Unit.py
|
cmontellanob/PruebasIntegracioncmb
|
d27fa8bca2d108b93b019af7f1603c9de9e00b2f
|
[
"Apache-2.0"
] | null | null | null |
import nose
import sys
argv = sys.argv[:]
argv.insert(1, "--verbosity=2")
nose.main(argv=argv)
| 15.833333
| 31
| 0.705263
| 16
| 95
| 4.1875
| 0.5625
| 0.208955
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.023529
| 0.105263
| 95
| 6
| 32
| 15.833333
| 0.764706
| 0
| 0
| 0
| 0
| 0
| 0.135417
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 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
| 0
| 0
| 1
| 0
| 0
| 0
|
0
| 4
|
85e6737066b2e379055bb225e4e293925837a1f0
| 271
|
py
|
Python
|
photos/models.py
|
Nightlyanon/PortfolioAPI
|
dde8f2dd72ec57765dad2803db05c3ee59e2592c
|
[
"MIT"
] | null | null | null |
photos/models.py
|
Nightlyanon/PortfolioAPI
|
dde8f2dd72ec57765dad2803db05c3ee59e2592c
|
[
"MIT"
] | null | null | null |
photos/models.py
|
Nightlyanon/PortfolioAPI
|
dde8f2dd72ec57765dad2803db05c3ee59e2592c
|
[
"MIT"
] | null | null | null |
from django.db import models
class Photo(models.Model):
name = models.CharField(max_length=100)
message = models.CharField(max_length=100, blank=True)
art = models.ImageField(blank=False, null=False)
created_at = models.DateTimeField(auto_now_add=True)
| 30.111111
| 58
| 0.752768
| 38
| 271
| 5.236842
| 0.684211
| 0.150754
| 0.180905
| 0.241206
| 0.271357
| 0
| 0
| 0
| 0
| 0
| 0
| 0.025751
| 0.140221
| 271
| 8
| 59
| 33.875
| 0.828326
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.166667
| 0
| 1
| 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
| 0
| 0
| 0
| 0
| 1
| 0
|
0
| 4
|
85e7bcadf6279ee2d748dc3683556fd67cd71567
| 122
|
py
|
Python
|
tests/base.py
|
anfema/django-questionnaire-core
|
82151cf14d00b5a83cb478cc07f9143fd57382c9
|
[
"MIT"
] | null | null | null |
tests/base.py
|
anfema/django-questionnaire-core
|
82151cf14d00b5a83cb478cc07f9143fd57382c9
|
[
"MIT"
] | 2
|
2019-01-30T16:05:15.000Z
|
2021-06-10T14:45:57.000Z
|
tests/base.py
|
anfema/django-questionnaire-core
|
82151cf14d00b5a83cb478cc07f9143fd57382c9
|
[
"MIT"
] | 2
|
2019-01-17T12:09:47.000Z
|
2019-01-30T15:59:01.000Z
|
from django.test import TestCase
# Create your tests here.
class TestCaseBase(TestCase):
fixtures = ('test1.json',)
| 17.428571
| 32
| 0.729508
| 15
| 122
| 5.933333
| 0.933333
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.009804
| 0.163934
| 122
| 6
| 33
| 20.333333
| 0.862745
| 0.188525
| 0
| 0
| 0
| 0
| 0.103093
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.333333
| 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
| 0
| 0
| 1
| 0
| 1
| 0
|
0
| 4
|
c82b1ab92ec09b77676d639843eec68448e3eefc
| 183
|
py
|
Python
|
functions/retorno_valor_simples.py
|
Brunokrk/Learning-Python
|
36a3b1c4782dbb21af189760a451fd2e9c083bb6
|
[
"MIT"
] | null | null | null |
functions/retorno_valor_simples.py
|
Brunokrk/Learning-Python
|
36a3b1c4782dbb21af189760a451fd2e9c083bb6
|
[
"MIT"
] | null | null | null |
functions/retorno_valor_simples.py
|
Brunokrk/Learning-Python
|
36a3b1c4782dbb21af189760a451fd2e9c083bb6
|
[
"MIT"
] | null | null | null |
def get_formated_name (first_name, last_name):
full_name = first_name + " "+last_name
return full_name.title()
musician = get_formated_name('jimi', 'hendrix')
print(musician)
| 30.5
| 47
| 0.743169
| 26
| 183
| 4.846154
| 0.5
| 0.174603
| 0.238095
| 0.269841
| 0.333333
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.136612
| 183
| 6
| 48
| 30.5
| 0.797468
| 0
| 0
| 0
| 0
| 0
| 0.065217
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.2
| false
| 0
| 0
| 0
| 0.4
| 0.2
| 1
| 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
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
c8306bbaf5465aee17785404d69ae3d11d8e8693
| 235
|
py
|
Python
|
colosseumrl/__init__.py
|
carletonz/colosseumrl
|
878f0459731511d716672aee8a5adafcb96cf0a7
|
[
"MIT"
] | 8
|
2019-06-04T00:22:30.000Z
|
2022-02-14T15:27:17.000Z
|
colosseumrl/__init__.py
|
carletonz/colosseumrl
|
878f0459731511d716672aee8a5adafcb96cf0a7
|
[
"MIT"
] | 1
|
2019-07-23T03:32:59.000Z
|
2019-07-23T06:16:35.000Z
|
colosseumrl/__init__.py
|
carletonz/colosseumrl
|
878f0459731511d716672aee8a5adafcb96cf0a7
|
[
"MIT"
] | 3
|
2020-01-13T08:09:27.000Z
|
2021-11-14T01:30:25.000Z
|
name = "colosseumrl"
from .BaseEnvironment import BaseEnvironment
from .ClientEnvironment import ClientEnvironment
from .config import get_environment, available_environments
from .RLApp import RLApp, create_rl_agent, launch_rl_agent
| 33.571429
| 59
| 0.859574
| 27
| 235
| 7.259259
| 0.592593
| 0.071429
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.097872
| 235
| 6
| 60
| 39.166667
| 0.924528
| 0
| 0
| 0
| 0
| 0
| 0.046809
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.8
| 0
| 0.8
| 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
| 0
| 1
| 0
| 1
| 0
|
0
| 4
|
c83a6f0ddefed2fc1383dae3ad9425a4eba1b58d
| 827
|
py
|
Python
|
pcoll/ordered_dict.py
|
thorwhalen/ut
|
353a4629c35a2cca76ef91a4d5209afe766433b4
|
[
"MIT"
] | 4
|
2016-12-17T20:06:10.000Z
|
2021-11-19T04:45:29.000Z
|
pcoll/ordered_dict.py
|
thorwhalen/ut
|
353a4629c35a2cca76ef91a4d5209afe766433b4
|
[
"MIT"
] | 11
|
2021-01-06T05:35:11.000Z
|
2022-03-11T23:28:31.000Z
|
pcoll/ordered_dict.py
|
thorwhalen/ut
|
353a4629c35a2cca76ef91a4d5209afe766433b4
|
[
"MIT"
] | 3
|
2015-06-12T10:44:16.000Z
|
2021-07-26T18:39:47.000Z
|
__author__ = 'thor'
import collections
from collections import OrderedDict
def sort_by_keys(d, reverse=False):
return OrderedDict(sorted(list(d.items()), key=lambda t: t[0], reverse=reverse))
def sort_by_value(d, reverse=False):
return OrderedDict(sorted(list(d.items()), key=lambda t: t[1], reverse=reverse))
def sort_by_function(d, fun, reverse=False):
return OrderedDict(sorted(list(d.items()), key=fun, reverse=reverse))
def ordered_counter(x, sort_by=None, reverse=False):
d = OrderedDict(collections.Counter(x))
if sort_by is not None:
if sort_by == 'count':
d = sort_by_keys(d, reverse=reverse)
elif sort_by == 'value':
d = sort_by_value(d, reverse=reverse)
else:
d = sort_by_function(d, fun=sort_by, reverse=reverse)
return d
| 28.517241
| 84
| 0.673519
| 121
| 827
| 4.421488
| 0.289256
| 0.123364
| 0.050467
| 0.162617
| 0.542056
| 0.302804
| 0.302804
| 0.302804
| 0.302804
| 0.213084
| 0
| 0.003017
| 0.198307
| 827
| 28
| 85
| 29.535714
| 0.803922
| 0
| 0
| 0
| 0
| 0
| 0.016929
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.210526
| false
| 0
| 0.105263
| 0.157895
| 0.526316
| 0
| 0
| 0
| 0
| null | 0
| 0
| 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
| 4
|
c8404cf600f95e818397cbf96cea0d5d707a390c
| 87
|
py
|
Python
|
weigth/apps.py
|
MarioDavidov/heroku_workout
|
50727305f7e6f05527d3a5fff5e8d27843435985
|
[
"MIT"
] | null | null | null |
weigth/apps.py
|
MarioDavidov/heroku_workout
|
50727305f7e6f05527d3a5fff5e8d27843435985
|
[
"MIT"
] | null | null | null |
weigth/apps.py
|
MarioDavidov/heroku_workout
|
50727305f7e6f05527d3a5fff5e8d27843435985
|
[
"MIT"
] | null | null | null |
from django.apps import AppConfig
class WeigthConfig(AppConfig):
name = 'weigth'
| 14.5
| 33
| 0.747126
| 10
| 87
| 6.5
| 0.9
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.172414
| 87
| 5
| 34
| 17.4
| 0.902778
| 0
| 0
| 0
| 0
| 0
| 0.068966
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.333333
| 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
| 0
| 0
| 1
| 0
| 1
| 0
|
0
| 4
|
c85ca39087bcc2189d190f20b1946675e6b74e74
| 1,968
|
py
|
Python
|
django/researchdata/serializers.py
|
linguindic/linguindic-website
|
545c64bc55b9502ef3db8ac00172d6240495b526
|
[
"MIT"
] | 1
|
2020-09-22T10:07:52.000Z
|
2020-09-22T10:07:52.000Z
|
django/researchdata/serializers.py
|
linguindic/linguindic-website
|
545c64bc55b9502ef3db8ac00172d6240495b526
|
[
"MIT"
] | null | null | null |
django/researchdata/serializers.py
|
linguindic/linguindic-website
|
545c64bc55b9502ef3db8ac00172d6240495b526
|
[
"MIT"
] | null | null | null |
from rest_framework import serializers
from . import models
# Select List models
class SlLinguisticTraditionGroupSerializer(serializers.ModelSerializer):
class Meta:
model = models.SlLinguisticTraditionGroup
fields = '__all__'
class SlReferencePublisherSerializer(serializers.ModelSerializer):
class Meta:
model = models.SlReferencePublisher
fields = '__all__'
class SlReferenceTypeSerializer(serializers.ModelSerializer):
class Meta:
model = models.SlReferenceType
fields = '__all__'
class SlTextGroupSerializer(serializers.ModelSerializer):
class Meta:
model = models.SlTextGroup
fields = '__all__'
class SlTextTypeSerializer(serializers.ModelSerializer):
class Meta:
model = models.SlTextType
fields = '__all__'
# Main models
class AuthorSerializer(serializers.ModelSerializer):
class Meta:
model = models.Author
fields = '__all__'
class LinguisticFieldSerializer(serializers.ModelSerializer):
class Meta:
model = models.LinguisticField
fields = '__all__'
class LinguisticNotionSerializer(serializers.ModelSerializer):
class Meta:
model = models.LinguisticNotion
fields = '__all__'
class LinguisticTraditionSerializer(serializers.ModelSerializer):
class Meta:
model = models.LinguisticTradition
fields = '__all__'
class ReferenceSerializer(serializers.ModelSerializer):
class Meta:
model = models.Reference
fields = '__all__'
class SanskritWordSerializer(serializers.ModelSerializer):
class Meta:
model = models.SanskritWord
fields = '__all__'
class TextSerializer(serializers.ModelSerializer):
class Meta:
model = models.Text
fields = '__all__'
class TextPassageSerializer(serializers.ModelSerializer):
class Meta:
model = models.TextPassage
fields = '__all__'
| 19.68
| 72
| 0.704776
| 156
| 1,968
| 8.551282
| 0.262821
| 0.253373
| 0.302099
| 0.341079
| 0.448276
| 0.448276
| 0
| 0
| 0
| 0
| 0
| 0
| 0.227642
| 1,968
| 99
| 73
| 19.878788
| 0.877632
| 0.015244
| 0
| 0.481481
| 0
| 0
| 0.047028
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0.037037
| 0.037037
| 0
| 0.518519
| 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
| 0
| 0
| 0
| 0
| 1
| 0
|
0
| 4
|
c85ef4bd89feab210e6b90670912ed7c5edfbb41
| 191
|
py
|
Python
|
mlir/dialects/__init__.py
|
paul-tqh-nguyen/pymlir
|
f61817351a191d9edcfb675653d7fcc5d3b0fe77
|
[
"BSD-3-Clause"
] | 3
|
2021-03-08T18:41:50.000Z
|
2021-08-06T20:27:20.000Z
|
mlir/dialects/__init__.py
|
paul-tqh-nguyen/pymlir
|
f61817351a191d9edcfb675653d7fcc5d3b0fe77
|
[
"BSD-3-Clause"
] | 4
|
2021-03-03T18:59:13.000Z
|
2021-05-11T23:43:04.000Z
|
mlir/dialects/__init__.py
|
paul-tqh-nguyen/pymlir
|
f61817351a191d9edcfb675653d7fcc5d3b0fe77
|
[
"BSD-3-Clause"
] | 5
|
2021-03-03T15:45:29.000Z
|
2021-08-06T20:27:28.000Z
|
from .affine import affine
from .standard import standard
from .loop import loop
from .linalg import linalg
from .llvm import llvm
STANDARD_DIALECTS = [affine, standard, loop, linalg, llvm]
| 23.875
| 58
| 0.790576
| 27
| 191
| 5.555556
| 0.296296
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.146597
| 191
| 7
| 59
| 27.285714
| 0.920245
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.833333
| 0
| 0.833333
| 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
| 0
| 1
| 0
| 1
| 0
|
0
| 4
|
c0922ca2ce7e14a8d6daca7f10f714f195de6643
| 46
|
py
|
Python
|
apicem_config.py
|
ralfraij/apicem-ll-sample-code
|
adb0988af7b506610b218db7136ec58354572f4b
|
[
"Apache-2.0"
] | 1
|
2018-06-28T00:11:16.000Z
|
2018-06-28T00:11:16.000Z
|
apicem_config.py
|
ralfraij/apicem-ll-sample-code
|
adb0988af7b506610b218db7136ec58354572f4b
|
[
"Apache-2.0"
] | null | null | null |
apicem_config.py
|
ralfraij/apicem-ll-sample-code
|
adb0988af7b506610b218db7136ec58354572f4b
|
[
"Apache-2.0"
] | null | null | null |
# Define apic-em ip
apicem_ip = '10.10.20.55'
| 15.333333
| 25
| 0.673913
| 10
| 46
| 3
| 0.8
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.205128
| 0.152174
| 46
| 2
| 26
| 23
| 0.564103
| 0.369565
| 0
| 0
| 0
| 0
| 0.407407
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
c0a57f543d52ac757c6c93dd8028c81587e4a3fb
| 14,210
|
py
|
Python
|
test/test_matrix.py
|
knowledge-technologies/spyct
|
058e7380f353a06bf312613472e82fc5abd65315
|
[
"BSD-3-Clause"
] | 2
|
2020-11-27T15:05:52.000Z
|
2021-10-14T16:01:25.000Z
|
test/test_matrix.py
|
knowledge-technologies/spyct
|
058e7380f353a06bf312613472e82fc5abd65315
|
[
"BSD-3-Clause"
] | null | null | null |
test/test_matrix.py
|
knowledge-technologies/spyct
|
058e7380f353a06bf312613472e82fc5abd65315
|
[
"BSD-3-Clause"
] | null | null | null |
import pytest
import numpy as np
from hypothesis import given, assume, note, settings, HealthCheck
import utils
import spyct._matrix as smatrix
@given(utils.real_ndarrays_nan(utils.random_matrix_shapes()))
def test_ndarray_to_DMatrix_to_ndarray(matrix):
result = smatrix.ndarray_to_DMatrix(matrix).to_ndarray()
note('original: {}'.format(matrix))
note('result: {}'.format(result))
np.testing.assert_equal(result, matrix)
@given(utils.real_ndarrays(utils.random_matrix_shapes()))
def test_csr_to_SMatrix_to_csr(matrix):
csr = utils.make_csr(matrix)
result = smatrix.csr_to_SMatrix(csr).to_csr()
np.testing.assert_equal(result.data, csr.data)
np.testing.assert_equal(result.indptr, csr.indptr)
np.testing.assert_equal(result.indices, csr.indices)
@given(utils.matrix_vector_pair())
def test_multiply_sparse_sparse(pair):
matrix, vector = pair
n = vector.shape[0]
indices = np.random.choice(n, size=n//2, replace=False).astype(np.intp)
indices.sort()
smat = utils.make_csr(matrix)
svec = np.zeros_like(vector)
svec[indices] = vector[indices]
target = np.matmul(smat.A, svec)
note('matrix: {}'.format(smat.A))
note('vector: {}'.format(vector))
note('indices: {}'.format(indices))
note('target: {}'.format(target))
scores = np.empty(matrix.shape[0], dtype='f')
smatrix.multiply_sparse_sparse(smatrix.csr_to_SMatrix(smat),
smatrix.memview_to_SMatrix(vector[indices], n, indices),
scores)
note('scores: {}'.format(scores))
assert utils.arrays_almost_equal(target, scores)
### DMatrix tests ################################################################
@given(utils.real_ndarrays_nan(utils.random_matrix_shapes()))
def test_DMatrix_copy(matrix):
copy = smatrix.ndarray_to_DMatrix(matrix).copy().to_ndarray()
np.testing.assert_equal(matrix, copy)
@settings(suppress_health_check=[HealthCheck.filter_too_much])
@given(utils.matrix_slice(0))
def test_DMatrix_take_rows(matrix_rows):
matrix, rows = matrix_rows
result = smatrix.ndarray_to_DMatrix(matrix).take_rows(rows).to_ndarray()
note('target: {}'.format(matrix[rows]))
note('result: {}'.format(result))
np.testing.assert_equal(matrix[rows], result)
@given(utils.matrix_slice(1))
def test_DMatrix_take_columns(matrix_columns):
matrix, columns = matrix_columns
result = smatrix.ndarray_to_DMatrix(matrix).take_columns(columns).to_ndarray()
note('target: {}'.format(matrix[:, columns]))
note('result: {}'.format(result))
np.testing.assert_equal(matrix[:, columns], result)
@given(utils.matrix_vector_pair())
def test_DMatrix_self_dot_vector(pair):
matrix, vector = pair
result = np.empty(shape=matrix.shape[0], dtype='f')
smatrix.ndarray_to_DMatrix(matrix).self_dot_vector(vector, result)
note('result: {} target:{}'.format(result, matrix.dot(vector)))
assert utils.arrays_almost_equal(result, matrix.dot(vector))
@given(utils.vector_matrix_pair())
def test_DMatrix_vector_dot_self(pair):
vector, matrix = pair
result = np.empty(shape=matrix.shape[1], dtype='f')
smatrix.ndarray_to_DMatrix(matrix).vector_dot_self(vector, result)
note('result: {} target:{}'.format(result, vector.dot(matrix)))
assert utils.arrays_almost_equal(result, vector.dot(matrix))
@pytest.mark.filterwarnings('ignore::RuntimeWarning')
@given(utils.real_ndarrays_nan(utils.random_matrix_shapes()))
def test_DMatrix_column_means_nan(matrix):
matrix = utils.clip_matrix_values(matrix)
means = np.empty(shape=matrix.shape[1], dtype='f')
smatrix.ndarray_to_DMatrix(matrix).column_means_nan(means)
matrix = matrix.astype('d')
target_means = np.nan_to_num(np.nanmean(matrix, axis=0))
note('real: {} target: {}'.format(means, target_means))
assert utils.arrays_almost_equal(means, target_means, eps=1e-2)
@pytest.mark.filterwarnings('ignore::RuntimeWarning')
@given(utils.real_ndarrays(utils.random_matrix_shapes()))
def test_DMatrix_column_means(matrix):
means = np.empty(shape=matrix.shape[1], dtype='f')
smatrix.ndarray_to_DMatrix(matrix).column_means(means)
matrix = matrix.astype('d')
target_means = np.mean(matrix, axis=0)
note('real: {} target: {}'.format(means, target_means))
assert utils.arrays_almost_equal(means, target_means, eps=1e-2)
@pytest.mark.filterwarnings('ignore::RuntimeWarning')
@given(utils.real_ndarrays_nan(utils.random_matrix_shapes()))
def test_DMatrix_column_stds_nan(matrix):
matrix = utils.clip_matrix_values(matrix)
means = np.empty(shape=matrix.shape[1], dtype='f')
stds = np.empty(shape=matrix.shape[1], dtype='f')
smatrix.ndarray_to_DMatrix(matrix).column_stds_nan(0, means, stds)
matrix = matrix.astype('d')
target_means = np.nan_to_num(np.nanmean(matrix, axis=0))
target_stds = np.nan_to_num(np.nanstd(matrix, axis=0))
note('means real: {} target: {}'.format(means, target_means))
note('stds real: {} target: {}'.format(stds, target_stds))
assert utils.arrays_almost_equal(means, target_means, eps=1e-2)
assert utils.arrays_almost_equal(stds, target_stds, eps=1e-2)
@pytest.mark.filterwarnings('ignore::RuntimeWarning')
@given(utils.real_ndarrays(utils.random_matrix_shapes()))
def test_DMatrix_column_stds(matrix):
means = np.empty(shape=matrix.shape[1], dtype='f')
stds = np.empty(shape=matrix.shape[1], dtype='f')
smatrix.ndarray_to_DMatrix(matrix).column_stds(0, means, stds)
matrix = matrix.astype('d')
note('means real: {} target: {}'.format(means, np.mean(matrix, axis=0)))
note('stds real: {} target: {}'.format(stds, np.std(matrix, axis=0)))
assert utils.arrays_almost_equal(means, np.mean(matrix, axis=0), eps=1e-2)
assert utils.arrays_almost_equal(stds, np.std(matrix, axis=0), eps=1e-2)
@given(utils.real_ndarrays_nan(utils.random_matrix_shapes()))
def test_DMatrix_impute_missing(matrix):
target = np.nan_to_num(matrix, nan=10)
result = smatrix.ndarray_to_DMatrix(matrix)
result.impute_missing(10)
result = result.to_ndarray()
assert utils.arrays_almost_equal(target, result)
@given(utils.real_ndarrays_nan(utils.random_matrix_shapes()))
def test_DMatrix_nonmissing_matrix(matrix):
target = (~np.isnan(matrix)).astype('f')
result = smatrix.ndarray_to_DMatrix(matrix).nonmissing_matrix().to_ndarray()
assert utils.arrays_almost_equal(target, result)
@given(utils.real_ndarrays(utils.random_matrix_shapes()))
def test_DMatrix_unstandardize_inverts_standardize(matrix):
means = np.empty(shape=matrix.shape[1], dtype='f')
stds = np.empty(shape=matrix.shape[1], dtype='f')
m = smatrix.ndarray_to_DMatrix(matrix)
m.column_stds(1, means, stds)
m.standardize_columns(means, stds)
m.unstandardize_columns(means, stds)
result = m.to_ndarray()
note('result: {}'.format(result))
assert utils.arrays_almost_equal(matrix, result)
@given(utils.real_ndarrays_nan(utils.random_matrix_shapes()))
def test_DMatrix_min_nonnan_in_column(matrix):
result = smatrix.ndarray_to_DMatrix(matrix).min_nonnan_in_column()
target = matrix.shape[0] - np.isnan(matrix).sum(axis=0).max()
note('result: {} target: {}'.format(result, target))
assert utils.values_almost_equal(result, target)
@given(utils.real_ndarrays_nan(utils.random_matrix_shapes()))
def test_DMatrix_row_vector(matrix):
m = smatrix.ndarray_to_DMatrix(matrix)
for row in range(matrix.shape[0]):
assert utils.arrays_almost_equal(np.asarray(m.row_vector(row)), matrix[row])
@given(utils.real_ndarrays(utils.random_matrix_shapes()))
def test_DMatrix_cluster_rows_mse(matrix):
assume(matrix.shape[0] >= 2)
c0 = matrix[0]
c1 = matrix[1]
d0 = np.sqrt(np.sum((matrix - c0) * (matrix - c0), axis=1))
d1 = np.sqrt(np.sum((matrix - c1) * (matrix - c1), axis=1))
target = (d1 < d0).astype('f')
target[d1 == d0] = -1.
result = np.empty(matrix.shape[0], dtype='f')
smatrix.ndarray_to_DMatrix(matrix).cluster_rows_mse(c0, c1, result)
note('result: {}'.format(result))
note('target: {}'.format(target))
assert utils.arrays_almost_equal(target, result)
@given(utils.real_ndarrays(utils.random_matrix_shapes()))
def test_DMatrix_cluster_rows_dot(matrix):
assume(matrix.shape[0] >= 2)
c0 = matrix[0]
c1 = matrix[1]
s0 = matrix.dot(c0) / (np.linalg.norm(c0) + 1e-8)
s1 = matrix.dot(c1) / (np.linalg.norm(c1) + 1e-8)
target = (s1 >= s0).astype('f')
note(str(s0))
note(str(s1))
result = np.empty(matrix.shape[0], dtype='f')
smatrix.ndarray_to_DMatrix(matrix).cluster_rows_dot(c0, c1, result, 1e-4, np.empty(matrix.shape[0], dtype='f'))
note('result: {}'.format(result))
note('target: {}'.format(target))
assert utils.arrays_almost_equal(target, result)
### SMatrix tests ################################################################
@given(utils.real_ndarrays_nan(utils.random_matrix_shapes()))
def test_SMatrix_copy(matrix):
csr = utils.make_csr(matrix)
copy = smatrix.csr_to_SMatrix(csr).copy().to_csr()
np.testing.assert_equal(csr.A, copy.A)
@settings(suppress_health_check=[HealthCheck.filter_too_much])
@given(utils.matrix_slice(0))
def test_SMatrix_take_rows(matrix_rows):
matrix, rows = matrix_rows
matrix = utils.make_csr(matrix)
result = smatrix.csr_to_SMatrix(matrix).take_rows(rows).to_csr()
note('target: {}'.format(matrix[rows].A))
note('result: {}'.format(result.A))
np.testing.assert_equal(matrix[rows].A, result.A)
@given(utils.matrix_slice(1))
def test_SMatrix_take_columns(matrix_columns):
matrix, columns = matrix_columns
matrix = utils.make_csr(matrix)
result = smatrix.csr_to_SMatrix(matrix).take_columns(columns).to_csr()
note('target: {}'.format(matrix[:, columns].A))
note('result: {}'.format(result.A))
np.testing.assert_equal(matrix[:, columns].A, result.A)
@given(utils.matrix_vector_pair())
def test_SMatrix_self_dot_vector(pair):
matrix, vector = pair
matrix = utils.make_csr(matrix)
result = np.empty(shape=matrix.shape[0], dtype='f')
smatrix.csr_to_SMatrix(matrix).self_dot_vector(vector, result)
target = matrix.A.dot(vector)
note('result: {} target:{}'.format(result, target))
assert utils.arrays_almost_equal(result, target)
@given(utils.vector_matrix_pair())
def test_SMatrix_vector_dot_self(pair):
vector, matrix = pair
matrix = utils.make_csr(matrix)
result = np.empty(shape=matrix.shape[1], dtype='f')
smatrix.csr_to_SMatrix(matrix).vector_dot_self(vector, result)
target = vector.dot(matrix.A)
note('result: {} target:{}'.format(result, target))
assert utils.arrays_almost_equal(result, target)
@pytest.mark.filterwarnings('ignore::RuntimeWarning')
@given(utils.real_ndarrays(utils.random_matrix_shapes()))
def test_SMatrix_column_means(matrix):
matrix = utils.make_csr(matrix)
means = np.empty(shape=matrix.shape[1], dtype='f')
smatrix.csr_to_SMatrix(matrix).column_means(means)
matrix = matrix.A.astype('d')
target_means = np.mean(matrix, axis=0)
note('real: {} target: {}'.format(means, target_means))
assert utils.arrays_almost_equal(means, target_means, eps=1e-2)
@pytest.mark.filterwarnings('ignore::RuntimeWarning')
@given(utils.real_ndarrays(utils.random_matrix_shapes()))
def test_SMatrix_column_stds(matrix):
means = np.empty(shape=matrix.shape[1], dtype='f')
stds = np.empty(shape=matrix.shape[1], dtype='f')
matrix = utils.make_csr(matrix)
smatrix.csr_to_SMatrix(matrix).column_stds(0, means, stds)
matrix = matrix.A.astype('d')
note('means real: {} target: {}'.format(means, np.mean(matrix, axis=0)))
note('stds real: {} target: {}'.format(stds, np.std(matrix, axis=0)))
assert utils.arrays_almost_equal(means, np.mean(matrix, axis=0), eps=1e-2)
assert utils.arrays_almost_equal(stds, np.std(matrix, axis=0), eps=1e-2)
@given(utils.real_ndarrays(utils.random_matrix_shapes()))
def test_SMatrix_unstandardize_inverts_standardize(matrix):
matrix = utils.make_csr(matrix)
means = np.empty(shape=matrix.shape[1], dtype='f')
stds = np.empty(shape=matrix.shape[1], dtype='f')
m = smatrix.csr_to_SMatrix(matrix)
m.column_stds(1, means, stds)
m.standardize_columns(means, stds)
m.unstandardize_columns(means, stds)
result = m.to_csr()
note('result: {}'.format(result.A))
assert utils.arrays_almost_equal(matrix.A, result.A)
@given(utils.real_ndarrays_nan(utils.random_matrix_shapes()))
def test_SMatrix_row_vector(matrix):
matrix = utils.make_csr(matrix)
dense = matrix.A
m = smatrix.csr_to_SMatrix(matrix)
for row in range(matrix.shape[0]):
assert utils.arrays_almost_equal(np.asarray(m.row_vector(row)), dense[row])
@given(utils.real_ndarrays(utils.random_matrix_shapes()))
def test_SMatrix_cluster_rows_mse(matrix):
assume(matrix.shape[0] >= 2)
matrix = utils.make_csr(matrix)
dense = matrix.A
c0 = dense[0]
c1 = dense[1]
d0 = np.sqrt(np.sum((dense - c0) * (dense - c0), axis=1))
d1 = np.sqrt(np.sum((dense - c1) * (dense - c1), axis=1))
target = (d1 < d0).astype('f')
target[d1 == d0] = -1.
result = np.empty(matrix.shape[0], dtype='f')
smatrix.csr_to_SMatrix(matrix).cluster_rows_mse(c0, c1, result)
note('result: {}'.format(result))
note('target: {}'.format(target))
assert utils.arrays_almost_equal(target, result)
@given(utils.real_ndarrays(utils.random_matrix_shapes()))
def test_DMatrix_cluster_rows_dot(matrix):
assume(matrix.shape[0] >= 2)
matrix = utils.make_csr(matrix)
dense = matrix.A
c0 = dense[0]
c1 = dense[1]
s0 = dense.dot(c0) / (np.linalg.norm(c0) + 1e-8)
s1 = dense.dot(c1) / (np.linalg.norm(c1) + 1e-8)
target = (s1 >= s0).astype('f')
note(str(s0))
note(str(s1))
result = np.empty(matrix.shape[0], dtype='f')
smatrix.csr_to_SMatrix(matrix).cluster_rows_dot(c0, c1, result, 1e-4, np.empty(matrix.shape[0], dtype='f'))
note('result: {}'.format(result))
note('target: {}'.format(target))
assert utils.arrays_almost_equal(target, result)
| 38.198925
| 115
| 0.702674
| 2,022
| 14,210
| 4.726508
| 0.065282
| 0.035681
| 0.042691
| 0.057759
| 0.85665
| 0.825154
| 0.741551
| 0.679083
| 0.631684
| 0.605525
| 0
| 0.01333
| 0.134201
| 14,210
| 371
| 116
| 38.301887
| 0.763472
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| 0.052264
| 0.009399
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| 0
| 0
| 0
| 0.119863
| 1
| 0.10274
| false
| 0
| 0.017123
| 0
| 0.119863
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
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| null | 0
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|
0
| 4
|
c0f399404616cbba7be88cee28892789ce335429
| 257
|
py
|
Python
|
bot.py
|
msujithk/Binance-Zerodha-Bot
|
ce979905550ebdb0f0e5403a7941e11c8dc41415
|
[
"MIT"
] | null | null | null |
bot.py
|
msujithk/Binance-Zerodha-Bot
|
ce979905550ebdb0f0e5403a7941e11c8dc41415
|
[
"MIT"
] | null | null | null |
bot.py
|
msujithk/Binance-Zerodha-Bot
|
ce979905550ebdb0f0e5403a7941e11c8dc41415
|
[
"MIT"
] | null | null | null |
from break_out_strategy import BreakOutStrategy
class Bot:
def __init__(self, adapter):
self.break_out_strategy = BreakOutStrategy(adapter)
def start_publish(self):
raise NotImplementedError("start_publish method not implemented")
| 28.555556
| 73
| 0.762646
| 29
| 257
| 6.413793
| 0.655172
| 0.086022
| 0.172043
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.175097
| 257
| 8
| 74
| 32.125
| 0.877358
| 0
| 0
| 0
| 0
| 0
| 0.140625
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.333333
| false
| 0
| 0.166667
| 0
| 0.666667
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
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| 0
| null | 0
| 0
| 0
| 0
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| 1
| 0
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| 0
| 0
| 1
| 0
|
0
| 4
|
23b189ae57118d80dcc0e247c5b39bc160930e89
| 92
|
py
|
Python
|
alunos/apps.py
|
lslopes/SchoolProjetobackand
|
099517566b0948ba19f31427ed9caf441bf5d696
|
[
"Apache-2.0"
] | null | null | null |
alunos/apps.py
|
lslopes/SchoolProjetobackand
|
099517566b0948ba19f31427ed9caf441bf5d696
|
[
"Apache-2.0"
] | 10
|
2020-03-24T17:01:46.000Z
|
2022-03-11T23:46:25.000Z
|
alunos/apps.py
|
lslopes/SchoolProjetobackand
|
099517566b0948ba19f31427ed9caf441bf5d696
|
[
"Apache-2.0"
] | null | null | null |
from django.apps import AppConfig
class AlunosConfig(AppConfig):
name = 'alunos'
| 15.333333
| 34
| 0.706522
| 10
| 92
| 6.5
| 0.9
| 0
| 0
| 0
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| 0.217391
| 92
| 5
| 35
| 18.4
| 0.902778
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| null | 0
| 0
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| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
|
0
| 4
|
23e30de97b738bcd962feb2c603694f120dec2c1
| 315
|
py
|
Python
|
py_moysklad/entities/attached_file.py
|
upmarket-cc/py_moysklad
|
e026e611344c38f8a8d4f428781fcfb315aaaa60
|
[
"MIT"
] | null | null | null |
py_moysklad/entities/attached_file.py
|
upmarket-cc/py_moysklad
|
e026e611344c38f8a8d4f428781fcfb315aaaa60
|
[
"MIT"
] | null | null | null |
py_moysklad/entities/attached_file.py
|
upmarket-cc/py_moysklad
|
e026e611344c38f8a8d4f428781fcfb315aaaa60
|
[
"MIT"
] | null | null | null |
import typing
from dataclasses import dataclass
from datetime import datetime
from py_moysklad.entities.attachment import Attachment
if typing.TYPE_CHECKING:
from py_moysklad.entities.agents.employee import Employee
@dataclass
class AttachedFile(Attachment):
created: datetime
createdBy: "Employee"
| 21
| 61
| 0.815873
| 37
| 315
| 6.864865
| 0.513514
| 0.047244
| 0.110236
| 0.173228
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.136508
| 315
| 14
| 62
| 22.5
| 0.933824
| 0
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| 0
| 0
| 0.025397
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.5
| 0
| 0.8
| 0
| 0
| 0
| 0
| null | 0
| 0
| 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
| 4
|
23ed2d3be27920cfb16311d9436c5d170993d041
| 542
|
py
|
Python
|
config.py
|
HankChen7773/Wedding_Bot_imgUpload
|
386baf2674cbae7ef2736cf95b40eb13bd608f44
|
[
"MIT"
] | null | null | null |
config.py
|
HankChen7773/Wedding_Bot_imgUpload
|
386baf2674cbae7ef2736cf95b40eb13bd608f44
|
[
"MIT"
] | null | null | null |
config.py
|
HankChen7773/Wedding_Bot_imgUpload
|
386baf2674cbae7ef2736cf95b40eb13bd608f44
|
[
"MIT"
] | null | null | null |
# imgur key
client_id = '3cb7dabd0f805d6'
client_secret = '30a9fb858f64bf4acc1651988e2fbc62e4fedaed'
album_id = 'LeVFO62'
album_id_lucky = '2aAnwnt'
access_token = '52945d677b3e985c5e82ba7d1fbd96f52648a1bb'
refresh_token = '46d87ffac8daa7d8ecd34c85b9db4c64dbc2c582'
# line bot key
line_channel_access_token = 'ozBtsH1AXPn/0cgAA2HymGPHm5Hx4QYECJ1jU3VuvTOttBCLZe1cwh5DBf8kJBI4H53gH4nIy8fdm1JYHPFRI8+BvNieQ8CcPiMsiv3dz4XKyRFRF2HsCLrH2rs7IIokniUSUL3rgJ2vAL4uNwuglgdB04t89/1O/w1cDnyilFU='
line_channel_secret = 'd5f3e8acb95897d9414f807fa60a1204'
| 45.166667
| 202
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| 0.24902
| 0.059041
| 542
| 11
| 203
| 49.272727
| 0.666667
| 0.04059
| 0
| 0
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| 0
| 0.682785
| 0.626692
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| null | 0
| 0
| 0
| 0
| 0
| 0
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|
0
| 4
|
23faccc5fc96a95edc45dd99e482b7dfd5d7e93d
| 25,515
|
py
|
Python
|
main.py
|
soniyanaik1177/Virtua-Try-On-
|
d104003a33dfc82083e5956804632cf1a83eeb79
|
[
"MIT"
] | 8
|
2021-05-29T11:11:20.000Z
|
2022-02-17T04:38:41.000Z
|
main.py
|
chefpr7/Try-First
|
efaf7636cc0ff06dcec70ee300462d931c4e9d5c
|
[
"MIT"
] | 14
|
2021-05-28T05:53:39.000Z
|
2022-03-12T01:05:21.000Z
|
main.py
|
chefpr7/Try-First
|
efaf7636cc0ff06dcec70ee300462d931c4e9d5c
|
[
"MIT"
] | 9
|
2021-05-20T09:05:57.000Z
|
2022-02-17T04:38:47.000Z
|
import os
import urllib.request
import time
import glob
import cv2
from app import app
from app2 import app2
from flask import Flask, flash, request, redirect, url_for, render_template, send_from_directory
from werkzeug.utils import secure_filename
from flask_caching import Cache
from PIL import Image
from script import predict
from evaluate import execute
from pose_parser import pose_parse
from wsize import women_size_predict
from wsize1 import women_size_predict1
from msize import men_size_predict
import mask_the_face
# from mask_the_face import execu0te_mask_face
#================ALLOWED FORMATS FOR IMAGE UPLOADS===========
ALLOWED_EXTENSIONS = set(['png', 'jpg', 'jpeg', 'gif'])
cache = Cache()
def allowed_file(filename):
return '.' in filename and filename.rsplit('.', 1)[1].lower() in ALLOWED_EXTENSIONS
# ============ REDIRECT HOME PAGE==========================
@app.route('/')
def index():
return render_template('index.html')
# ============ REDIRECT ABOUT PAGE=========================
@app.route('/about/')
def about():
return render_template('about.html')
# ============ REDIRECT SERVICE: TRY-ON====================
@app.route('/services_tryon/')
def services_tryon():
return render_template('services_tryon.html')
# ============ REDIRECT BLOG===============================
@app.route('/blog/')
def blog():
return render_template('blog.html')
# ============ REDIRECT CONTACT===========================
@app.route('/contact/')
def contact():
return render_template('contact.html')
# ==========================================================================================================================================================================
# ============================================================================ REDIRECT SERVICE: SIZE PREDICTOR=============================================================
@app.route('/services_sizep/')
def services_sizep():
GO = "False"
return render_template('services_sizep.html')
# ============ FUNCTION TO INPUT & PROCESS SIZE PREDICTION ===========
@app.route("/process_size", methods=['GET','POST'])
def your_size():
if request.method=="POST":
if 'file' not in request.files:
flash('No file part')
return redirect({{url_for('services_sizep')}})
file = request.files['file']
gender = request.form.get('gender')
height = request.form['height']
unit = request.form.get('unit')
Go = "False"
if file.filename == '':
flash('No image selected for uploading')
return redirect(request.url)
if file and allowed_file(file.filename) and gender and height and unit:
filename = secure_filename(file.filename)
file.save(os.path.join(app.config['UPLOAD_FOLDER2'], filename))
i_path = 'static/size/'
file_path = os.path.join(i_path,filename)
if gender == 'Female':
size = women_size_predict(file_path, height, unit)
else:
size = men_size_predict(file_path, height, unit)
return render_template('services_sizep.html', size=size)
else:
flash('Allowed image types are -> png, jpg, jpeg, gif')
return redirect(url_for('services_sizep'))
# size=None
Go = "True"
return redirect(url_for('services_sizep'))
# =============fUNCTION TO DISPLAY SIZE=====================
@app.route('/display_size/<size>')
def display_size(size):
if Go == "True":
GO = "True"
# time.sleep(5)
return str(size)
# ================================================================================================================================================================
# ======================================================1. REDIRECT CASUALS ======================================================================================
@app.route('/casuals/')
def casuals():
text = "none"
fish = glob.glob('./output/second/TOM/val/*')
for f in fish:
os.remove(f)
fish = glob.glob('./static/outputs/output_f/*')
for f in fish:
os.remove(f)
cloth = ['Casual-Yellow', 'Casual-Pink', 'Casual-Violet', 'Casual-White', 'Dark_ORANGE', 'Flowers-White', 'Grey_North' , 'Multicolo-White', 'Pine-Grey', 'Sky_Blue', 'TheNORTHface', 'Yellow62']
for i in range(len(cloth)):
cloth[i] = (str(cloth[i])+".jpg")
return render_template('casuals.html', casuals = cloth, text=text)
# ============1. FUNCTION TO DISPALY CASUALS =================
@app.route('/static/Database/val/cloth/<casuals>')
def display_casuals(casuals):
# time.wait(10)
return send_from_directory(app2.config['OUTPUT_FOLDER2'], casuals)
# ============1. FUNCTION TO INPUT AND PROCESS TRY ON ==========
@app.route('/casual_form', methods=['POST'])
def upload_image():
cache.init_app(app2)
with app2.app_context():
cache.clear()
fish = glob.glob('./static/Database/val/person/*')
for f in fish:
os.remove(f)
fish = glob.glob('./static/size/*')
for f in fish:
os.remove(f)
cloth = ['Casual-Yellow', 'Casual-Pink', 'Casual-Violet', 'Casual-White', 'Dark_ORANGE', 'Flowers-White', 'Grey_North' , 'Light-Pink', 'Multicolo-White', 'Sky_Blue', 'TheNORTHface', 'Yellow62']
for i in range(len(cloth)):
cloth[i] = (str(cloth[i])+".jpg")
if request.method=="POST":
if 'file' not in request.files:
flash('No file part')
return redirect(request.url)
text = "casualss"
file = request.files['file']
height = request.form['height']
unit = request.form.get('unit')
if file.filename == '':
flash('No image selected for uploading')
return redirect(request.url)
if file and allowed_file(file.filename) and text and height and unit:
filename = secure_filename(file.filename)
file.save(os.path.join(app.config['UPLOAD_FOLDER2'], filename))
i_path = 'static/size/'
file_path = os.path.join(i_path,filename)
size, file = women_size_predict1(file_path, height, unit)
file = Image.fromarray(file, 'RGB')
#
file.save(os.path.join(app.config['UPLOAD_FOLDER1'], filename))
i_path = 'static/Database/val/person/'
input_img = text+'.jpg'
os.rename(i_path+filename , i_path+input_img)
filename = text+'.jpg'
o_path = './output/second/TOM/val'
# fish = glob.glob('./output/second/TOM/val/*')
fish = glob.glob('./static/outputs/output_f/*')
for f in fish:
os.remove(f)
time.sleep(10)
#
#
#
#
pose_parse(text)
valpair_file = 'static/Database/val_pairs.txt'
for i in range(len(cloth)):
with open(valpair_file , "w") as f:
f.write(text+'.jpg '+ cloth[i] )
f.close()
predict()
im = Image.open(os.path.join(o_path,cloth[i]))
width, height = im.size
left = width / 3
top = 2 * height / 3
right = 2 * width / 3
bottom = height
im = im.crop((left, top, right, bottom))
newsize = (200, 270)
im = im.resize(newsize)
im.save(os.path.join(app2.config['OUTPUT_FOLDER3'],cloth[i]))
#
#
#
return render_template('casuals.html', casuals=cloth, text= text, size = size)
else:
flash('Allowed image types are -> png, jpg, jpeg, gif')
return redirect(request.url)
return render_template('casuals.html')
# =================1. OUTPUT CASUALS TRYON======================
@app.route('/static/outputs/output_f/<casuals>')
def display_output1(casuals):
return send_from_directory(app2.config['OUTPUT_FOLDER3'], casuals)
# =============================================================================================================================================================================
# =================================================================================2. REDIRECT SPORTS =========================================================================
@app.route('/sports/')
def sports():
cache.init_app(app2)
with app2.app_context():
cache.clear()
text = "none"
fish = glob.glob('./output/second/TOM/val/*')
for f in fish:
os.remove(f)
fish = glob.glob('./static/outputs/output_f/*')
for f in fish:
os.remove(f)
sport_cloth = ['ADIDAS-BW', 'ADIDAS_Black', 'FILA_grey', 'FILA-Pink', 'IVY-Black', 'NIKE-grey' ]
for i in range(len(sport_cloth)):
sport_cloth[i] = (str(sport_cloth[i])+".jpg")
return render_template('sports.html', sports = sport_cloth, text=text)
# ============2. FUNCTION TO DISPALY SPORTS =================
@app.route('/static/Database/val/cloth/<sports>')
def display_sports(sports):
return send_from_directory(app2.config['OUTPUT_FOLDER2'], sports)
# ===========2.FUNCTION TO INPUT AND PROCESS TRY ON ==========
@app.route('/sports_form', methods=['POST'])
def upload_image2():
cache.init_app(app2)
with app2.app_context():
cache.clear()
fish = glob.glob('./static/Database/val/person/*')
for f in fish:
os.remove(f)
fish = glob.glob('./static/size/*')
for f in fish:
os.remove(f)
sport_cloth = ['ADIDAS-BW', 'ADIDAS_Black', 'FILA_grey', 'FILA-Pink', 'IVY-Black', 'NIKE-grey' ]
for i in range(len(sport_cloth)):
sport_cloth[i] = (str(sport_cloth[i])+".jpg")
if request.method=="POST":
if 'file' not in request.files:
flash('No file part')
return redirect(request.url)
text = "sportss"
file = request.files['file']
height = request.form['height']
unit = request.form.get('unit')
Go = "False"
if file.filename == '':
flash('No image uploaded for size prediction.')
return redirect(request.url)
if file and allowed_file(file.filename) and height and unit:
filename = secure_filename(file.filename)
file.save(os.path.join(app.config['UPLOAD_FOLDER2'], filename))
i_path = 'static/size/'
file_path = os.path.join(i_path,filename)
size, file = women_size_predict1(file_path, height, unit)
file = Image.fromarray(file, 'RGB')
#
file.save(os.path.join(app.config['UPLOAD_FOLDER1'], filename))
i_path = 'static/Database/val/person/'
input_img = text+'.jpg'
os.rename(i_path+filename , i_path+input_img)
filename = text+'.jpg'
o_path = './output/second/TOM/val'
# fish = glob.glob('./output/second/TOM/val/*')
fish = glob.glob('./static/outputs/output_f/*')
for f in fish:
os.remove(f)
time.sleep(10)
#
#
#
#
pose_parse(text)
valpair_file = 'static/Database/val_pairs.txt'
for i in range(len(sport_cloth)):
with open(valpair_file , "w") as f:
f.write(text+'.jpg '+ sport_cloth[i] )
f.close()
predict()
im = Image.open(os.path.join(o_path,sport_cloth[i]))
width, height = im.size
left = width / 3
top = 2 * height / 3
right = 2 * width / 3
bottom = height
im = im.crop((left, top, right, bottom))
newsize = (200, 270)
im = im.resize(newsize)
im.save(os.path.join(app2.config['OUTPUT_FOLDER3'],sport_cloth[i]))
#
#
#
return render_template('sports.html', sports=sport_cloth, text= text, size=size)
else:
flash('Allowed image types are -> png, jpg, jpeg, gif')
return redirect(request.url)
return render_template('sports.html')
# =================2. OUTPUT SPORTS TRYON======================
@app.route('/static/outputs/output_f/<sports>')
def display_output2(sports):
return send_from_directory(app2.config['OUTPUT_FOLDER3'], sports)
# =======================================================================================================================================================================
# ===========================================================3. REDIRECT BRANDS =========================================================================================
@app.route('/brands/')
def brands():
text = "none"
fish = glob.glob('./output/second/TOM/val/*')
for f in fish:
os.remove(f)
fish = glob.glob('./static/outputs/output_f/*')
for f in fish:
os.remove(f)
brand_cloth = ['Pink-Flayrd', 'Blue-flayrd', 'Flayerd-Yellow', 'Bluish-Flayrd','NIKE-black', 'RED-Flayrd']#'
for i in range(len(brand_cloth)):
brand_cloth[i] = (str(brand_cloth[i])+".jpg")
return render_template('brands.html', brands = brand_cloth, text=text)
# ============3. FUNCTION TO DISPALY BRANDS =================
@app.route('/static/Database/val/cloth/<brands>')
def display_brands(brands):
# time.wait(10)
return send_from_directory(app2.config['OUTPUT_FOLDER2'], brands)
# ===========3.FUNCTION TO INPUT AND PROCESS TRY ON ==========
@app.route('/brands_form', methods=['POST'])
def upload_image3():
cache.init_app(app2)
with app2.app_context():
cache.clear()
fish = glob.glob('./static/Database/val/person/*')
for f in fish:
os.remove(f)
fish = glob.glob('./static/size/*')
for f in fish:
os.remove(f)
brand_cloth = ['Pink-Flayrd', 'Blue-flayrd', 'Flayerd-Yellow', 'Bluish-Flayrd','NIKE-black', 'RED-Flayrd']#'
for i in range(len(brand_cloth)):
brand_cloth[i] = (str(brand_cloth[i])+".jpg")
if request.method=="POST":
text = "brandss"
file = request.files['file']
height = request.form['height']
unit = request.form.get('unit')
if file.filename == '':
flash('No image selected for uploading')
return redirect(request.url)
if file and allowed_file(file.filename) and height and unit:
filename = secure_filename(file.filename)
file.save(os.path.join(app.config['UPLOAD_FOLDER2'], filename))
i_path = 'static/size/'
file_path = os.path.join(i_path,filename)
size, file = women_size_predict1(file_path, height, unit)
file = Image.fromarray(file, 'RGB')
#
file.save(os.path.join(app.config['UPLOAD_FOLDER1'], filename))
i_path = 'static/Database/val/person/'
input_img = text+'.jpg'
os.rename(i_path+filename , i_path+input_img)
filename = text+'.jpg'
o_path = './output/second/TOM/val'
# fish = glob.glob('./output/second/TOM/val/*')
fish = glob.glob('./static/outputs/output_f/*')
for f in fish:
os.remove(f)
time.sleep(10)
#
#
#
#
pose_parse(text)
valpair_file = 'static/Database/val_pairs.txt'
for i in range(len(brand_cloth)):
with open(valpair_file , "w") as f:
f.write(text+'.jpg '+ brand_cloth[i] )
f.close()
predict()
im = Image.open(os.path.join(o_path,brand_cloth[i]))
width, height = im.size
left = width / 3
top = 2 * height / 3
right = 2 * width / 3
bottom = height
im = im.crop((left, top, right, bottom))
newsize = (200, 270)
im = im.resize(newsize)
im.save(os.path.join(app2.config['OUTPUT_FOLDER3'],brand_cloth[i]))
#
#
#
return render_template('brands.html', brands=brand_cloth, text= text, size=size)
else:
flash('Allowed image types are -> png, jpg, jpeg, gif')
return redirect(request.url)
return render_template('brands.html')
# =================3. OUTPUT BRANDS TRYON======================
@app.route('/static/outputs/output_f/<brands>')
def display_output3(brands):
return send_from_directory(app2.config['OUTPUT_FOLDER3'], brands)
# =========================================================================================================================================================================
# =====================================================================4. REDIRECT PARTY ==================================================================================
@app.route('/party/')
def party():
cache.init_app(app2)
with app2.app_context():
cache.clear()
text = "none"
fish = glob.glob('./output/second/TOM/val/*')
for f in fish:
os.remove(f)
fish = glob.glob('./static/outputs/output_f/*')
for f in fish:
os.remove(f)
party = ['Orach-Flayrd', 'MultiColor', 'Butterfly_p','Waved-Black' ,'Shimm' ,'Wavy-Red','Wavy-Pink', 'Reddish-KNOTS']
for i in range(len(party)):
party[i] = (str(party[i])+".jpg")
return render_template('party_wear.html', party = party, text=text)
# ===================================================4. FUNCTION TO DISPALY PARTY ==========================================================
@app.route('/static/Database/val/cloth/<party>')
def display_party(party):
time.wait(10)
return send_from_directory(app2.config['OUTPUT_FOLDER2'], party)
# =================================================4. FUNCTION TO INPUT AND PROCESS TRY ON ===================================================
@app.route('/party_form', methods=['POST'])
def upload_image4():
cache.init_app(app2)
with app2.app_context():
cache.clear()
fish = glob.glob('./static/Database/val/person/*')
for f in fish:
os.remove(f)
fish = glob.glob('./static/size/*')
for f in fish:
os.remove(f)
party = ['Orach-Flayrd', 'MultiColor', 'Butterfly_p','Waved-Black' ,'Shimm', 'Wavy-Red','Wavy-Pink', 'Reddish-KNOTS']
for i in range(len(party)):
party[i] = (str(party[i])+".jpg")
if request.method=="POST":
text = "palty"
file = request.files['file']
height = request.form['height']
unit = request.form.get('unit')
Go = "False"
if file.filename == '':
flash('No image uploaded for trying clothes.')
return redirect(request.url)
if file and allowed_file(file.filename) and height and unit and text:
filename = secure_filename(file.filename)
file.save(os.path.join(app.config['UPLOAD_FOLDER2'], filename))
i_path = 'static/size/'
file_path = os.path.join(i_path,filename)
size, file = women_size_predict1(file_path, height, unit)
file = Image.fromarray(file, 'RGB')
#
file.save(os.path.join(app.config['UPLOAD_FOLDER1'], filename))
i_path = 'static/Database/val/person/'
input_img = text+'.jpg'
os.rename(i_path+filename , i_path+input_img)
filename = text+'.jpg'
o_path = './output/second/TOM/val'
# fish = glob.glob('./output/second/TOM/val/*')
fish = glob.glob('./static/outputs/output_f/*')
for f in fish:
os.remove(f)
time.sleep(10) #
#
#
#
pose_parse(text)
valpair_file = 'static/Database/val_pairs.txt'
for i in range(len(party)):
with open(valpair_file , "w") as f:
f.write(text+'.jpg '+ party[i] )
f.close()
predict()
im = Image.open(os.path.join(o_path,party[i]))
width, height = im.size
left = width / 3
top = 2 * height / 3
right = 2 * width / 3
bottom = height
im = im.crop((left, top, right, bottom))
newsize = (200, 270)
im = im.resize(newsize)
im.save(os.path.join(app2.config['OUTPUT_FOLDER3'],party[i]))
#
#
#
##
##
return render_template('party_wear.html', party=party, text= text, size=size)
else:
flash('Allowed image types are -> png, jpg, jpeg, gif')
return redirect(request.url)
return render_template('party_wear.html')
# =====================================================4. OUTPUT PARTY TRYON=================================================================
@app.route('/static/output/<party>')
def display_output4(party):
time.sleep(10)
return send_from_directory(app2.config['OUTPUT_FOLDER3'], party)
#------------------------------------------------------------------------------------------------------------------------------------------
#----------------------------------------------------5. T-Shirt Form-----------------------------------------------------------------------
# -----------------------------------------------------------------------------------------------------------------------------------------
@app.route('/tshirt/')
def tshirt():
cache.init_app(app2)
with app2.app_context():
cache.clear()
text = "none"
fish = glob.glob('./output/second/TOM/val/*')
for f in fish:
os.remove(f)
fish = glob.glob('./static/outputs/output_f/*')
for f in fish:
os.remove(f)
tshirt = ['POLO_Black', 'POLO-blue', 'POLO-Blue', 'POLO-BLue', 'POLO-orach', 'POLO-Violet']
for i in range(len(tshirt)):
tshirt[i] = (str(tshirt[i])+".jpg")
return render_template('tshirt.html', tshirt = tshirt, text=text)
# ===================================================5. FUNCTION TO DISPALY T-shirt ==========================================================
@app.route('/static/Database/val/cloth/<tshirt>')
def display_tshirt(tshirt):
time.wait(5)
return send_from_directory(app2.config['OUTPUT_FOLDER2'], tshirt)
# =================================================5. FUNCTION TO INPUT AND PROCESS TRY ON ===================================================
@app.route('/tshirt_form', methods=['POST'])
def upload_image5():
cache.init_app(app2)
with app2.app_context():
cache.clear()
fish = glob.glob('./static/Database/val/person/*')
for f in fish:
os.remove(f)
fish = glob.glob('./static/size/*')
for f in fish:
os.remove(f)
tshirt = ['POLO_Black', 'POLO-blue', 'POLO-Blue', 'POLO-BLue', 'POLO-orach', 'POLO-Violet']
for i in range(len(tshirt)):
tshirt[i] = (str(tshirt[i])+".jpg")
if request.method=="POST":
text = "tshirtss"
file = request.files['file']
file1 = request.files['file1']
height = request.form['height']
unit = request.form.get('unit')
Go = "False"
if file.filename == '':
flash('No image uploaded for size prediction.')
return redirect(request.url)
if file1.filename == '':
flash('No image uploaded for trying clothes.')
return redirect(request.url)
if file and allowed_file(file.filename) and file1 and allowed_file(file1.filename) and height and unit and text:
filename = secure_filename(file.filename)
filename1 = secure_filename(file1.filename)
file1.save(os.path.join(app.config['UPLOAD_FOLDER2'], filename1))
i_path = 'static/size/'
file_path = os.path.join(i_path,filename1)
size = women_size_predict(file_path, height, unit)
#
file.save(os.path.join(app.config['UPLOAD_FOLDER1'], filename))
i_path = 'static/Database/val/person/'
input_img = text+'.jpg'
os.rename(i_path+filename , i_path+input_img)
filename = text+'.jpg'
o_path = './output/second/TOM/val'
# time.sleep(10) #
#
#
#
pose_parse(text)
valpair_file = 'static/Database/val_pairs.txt'
for i in range(len(tshirt)):
with open(valpair_file , "w") as f:
f.write(text+'.jpg '+ tshirt[i] )
f.close()
predict()
im = Image.open(os.path.join(o_path,tshirt[i]))
width, height = im.size
left = width / 3
top = 2 * height / 3
right = 2 * width / 3
bottom = height
im = im.crop((left, top, right, bottom))
newsize = (200, 270)
im = im.resize(newsize)
im.save(os.path.join(app2.config['OUTPUT_FOLDER3'],tshirt[i]))
#
#
#
##
##
return render_template('tshirt.html', tshirt=tshirt, text=text, size=size)
else:
flash('Allowed image types are -> png, jpg, jpeg, gif')
return redirect(request.url)
return render_template('tshirt.html')
# =====================================================5. T-SHIRT TRYON=================================================================
@app.route('/static/outputs/output_f/<tshirt>')
def display_output5(tshirt):
time.sleep(5)
return send_from_directory(app2.config['OUTPUT_FOLDER3'], tshirt)
#------------------------------------------------------ Mask the Face -------------------------------------------------------------------------
@app.route('/faceMask/')
def facemask():
cache.init_app(app2)
with app2.app_context():
cache.clear()
text = "none"
fish = glob.glob('./static/outputs/output_mask/*')
for f in fish:
os.remove(f)
fish = glob.glob('MaskTheFace/data/*')
for f in fish:
os.remove(f)
return render_template('facemask.html', text=text)
@app.route('/facemask_form', methods=['POST'])
def upload_image6():
cache.init_app(app2)
with app2.app_context():
cache.clear()
fish = glob.glob('./static/outputs/output_mask/*')
for f in fish:
os.remove(f)
fish = glob.glob('MaskTheFace/data/*')
for f in fish:
os.remove(f)
if request.method=="POST":
text = "Face-Mask"
file = request.files['file']
if file.filename == '':
flash('No image uploaded for size prediction.')
return redirect(request.url)
if file and allowed_file(file.filename) and text:
filename = secure_filename(file.filename)
file.save(os.path.join(app.config['UPLOAD_FOLDER3'], filename))
#
i_path = 'MaskTheFace/data/'
input_img = text+'.jpg'
os.rename(i_path+filename , i_path+input_img)
zpath = os.path.join(i_path, input_img)
print(i_path)
# time.sleep(10) #
#
opath = 'static/outputs/output_mask/'
mask_type = ['N95', 'surgical', 'cloth', 'N95', 'surgical', 'cloth', 'N95', 'surgical', 'cloth', 'N95', 'surgical', 'cloth', 'cloth']
mask_color = ["#fc1c1a","#177ABC","#94B6D2","#A5AB81","#DD8047","#6b425e","#e26d5a","#c92c48","#6a506d","#ffc900","#ffffff","#000000","#49ff00"]
out_files = []
for i in range(13):
mask_the_face.run_function(zpath, mask_type[i], '', '0', mask_color[i], '0','', 'verbose', 'write_original_image')
out_files.append(text+"_" + str(mask_type[i])+'.jpg')
im = Image.open(os.path.join(i_path,out_files[-1]))
im.save(os.path.join(app2.config['OUTPUT_FOLDER4'],out_files[-1]))
new_name = text + str(i) + '.jpg'
os.rename(opath+out_files[-1], opath+new_name)
out_files[-1] = new_name
return render_template('facemask.html', text=text, out_files = out_files)
else:
flash('Allowed image types are -> png, jpg, jpeg, gif')
return redirect(request.url)
return render_template('facemask.html')
@app.route('/static/outputs/output_mask/<out_files>')
def display_output6(out_files):
time.sleep(50)
return send_from_directory(app2.config['OUTPUT_FOLDER4'], out_files)
# ====================================================== FLASK APP RUN & DEBUG===================================================================
if __name__ == "__main__":
app.run(debug=True, use_reloader=True)
| 33.440367
| 195
| 0.575661
| 3,198
| 25,515
| 4.475922
| 0.085679
| 0.011527
| 0.026827
| 0.019561
| 0.792441
| 0.769317
| 0.741442
| 0.718388
| 0.684714
| 0.654324
| 0
| 0.012076
| 0.146463
| 25,515
| 762
| 196
| 33.484252
| 0.645192
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| 0.065729
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| 0.021505
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| 0.001792
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| 0
| 0
|
0
| 4
|
9b02d6fe015d4aaa881b0a0e7b3238abcf387618
| 108
|
py
|
Python
|
.idea/fileTemplates/internal/Python Script.py
|
AbbieZ/Fraudiscern
|
ae30c58a62129e05e219ad48309ceb7f5d944bba
|
[
"Apache-2.0"
] | 2
|
2021-07-28T15:11:22.000Z
|
2022-02-19T03:12:36.000Z
|
.idea/fileTemplates/internal/Python Script.py
|
AbbieZ/Fraudiscern
|
ae30c58a62129e05e219ad48309ceb7f5d944bba
|
[
"Apache-2.0"
] | null | null | null |
.idea/fileTemplates/internal/Python Script.py
|
AbbieZ/Fraudiscern
|
ae30c58a62129e05e219ad48309ceb7f5d944bba
|
[
"Apache-2.0"
] | 2
|
2021-07-05T15:22:08.000Z
|
2021-07-08T01:54:10.000Z
|
# !/usr/bin/env python
# -*- coding: utf-8 -*-
"""
@author:
@file: ${NAME}.py
@time: ${DATE}
@version:
"""
| 12
| 23
| 0.518519
| 14
| 108
| 4
| 1
| 0
| 0
| 0
| 0
| 0
| 0
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| 0
| 0.010989
| 0.157407
| 108
| 9
| 24
| 12
| 0.604396
| 0.888889
| 0
| null | 0
| null | 0
| 0
| null | 0
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| 0
| null | 1
| null | true
| 0
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| null | null | null | 1
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| 0
| 0
| 0
| 0
|
0
| 4
|
9b10e096ca3401393f59084889ced4e2a1d32af2
| 83
|
py
|
Python
|
core/srlegacy/__init__.py
|
MakuZo/nutrigo
|
e50e10d497bcf9e01294565d42012d777f5c98d0
|
[
"MIT"
] | 30
|
2019-03-28T18:01:58.000Z
|
2022-02-26T02:19:28.000Z
|
core/srlegacy/__init__.py
|
MakuZo/nutrigo
|
e50e10d497bcf9e01294565d42012d777f5c98d0
|
[
"MIT"
] | 8
|
2019-06-06T19:33:08.000Z
|
2022-02-10T13:10:34.000Z
|
core/srlegacy/__init__.py
|
MakuZo/nutrigo
|
e50e10d497bcf9e01294565d42012d777f5c98d0
|
[
"MIT"
] | 10
|
2019-04-04T19:19:28.000Z
|
2021-06-05T05:29:40.000Z
|
"""
Contains scripts that were used to import USDA's Standard Legacy database.
"""
| 20.75
| 74
| 0.746988
| 12
| 83
| 5.166667
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.156627
| 83
| 3
| 75
| 27.666667
| 0.885714
| 0.891566
| 0
| null | 0
| null | 0
| 0
| null | 0
| 0
| 0
| null | 1
| null | true
| 0
| 0
| null | null | null | 1
| 0
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| null | 0
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| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
9b1d9256d4c04bb11138e2a4b40c9a9956c32d2e
| 335
|
py
|
Python
|
rklearn/__init__.py
|
rejux/rklearn-lib
|
56bc4f087a8c971cb545d65b0c1f9bafaaec3d67
|
[
"MIT"
] | null | null | null |
rklearn/__init__.py
|
rejux/rklearn-lib
|
56bc4f087a8c971cb545d65b0c1f9bafaaec3d67
|
[
"MIT"
] | null | null | null |
rklearn/__init__.py
|
rejux/rklearn-lib
|
56bc4f087a8c971cb545d65b0c1f9bafaaec3d67
|
[
"MIT"
] | null | null | null |
##################
## __init__.py ##
##################
# Import the python top file/modules for this package
# When this package is loaded, we want the following modules to be
# automatically imported
import rklearn.perceptron
import rklearn.adaline
import rklearn.plotters
import rklearn.opendata_loaders
import rklearn.tfoo_v1
| 20.9375
| 66
| 0.713433
| 42
| 335
| 5.547619
| 0.690476
| 0.27897
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.003448
| 0.134328
| 335
| 15
| 67
| 22.333333
| 0.8
| 0.456716
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
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| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 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
| 4
|
f196895b0ab310bfbc203ece7aa7d2bd8beb582c
| 78
|
py
|
Python
|
thirdparty/stylegan3_ops/__init__.py
|
STomoya/animeface
|
37b3cd26097d7874559d4c152e41e5712b7a1a42
|
[
"MIT"
] | 61
|
2020-06-06T08:25:09.000Z
|
2022-03-28T13:30:10.000Z
|
thirdparty/stylegan3_ops/ops/__init__.py
|
OrigamiXx/animeface
|
8724006df99ba7ef369e837d8294350ea733611b
|
[
"MIT"
] | 13
|
2020-07-02T02:41:14.000Z
|
2021-05-09T14:24:58.000Z
|
thirdparty/stylegan3_ops/ops/__init__.py
|
OrigamiXx/animeface
|
8724006df99ba7ef369e837d8294350ea733611b
|
[
"MIT"
] | 8
|
2020-10-03T18:51:16.000Z
|
2022-02-05T18:18:01.000Z
|
# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
| 39
| 77
| 0.74359
| 10
| 78
| 5.9
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.060606
| 0.153846
| 78
| 1
| 78
| 78
| 0.818182
| 0.948718
| 0
| null | 0
| null | 0
| 0
| null | 0
| 0
| 0
| null | 0
| null | null | 0
| 0
| null | null | null | 1
| 0
| 0
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| 0
| 0
| 0
| 0
| 0
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| 0
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| null | 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
f1bf7f456c0b963980275559ec00f3f3ff524134
| 172
|
py
|
Python
|
pyweibo/__init__.py
|
YIDAMU/pyweibo
|
60c944ac5db7de090c607551c8004bb645c0cfdd
|
[
"MIT"
] | null | null | null |
pyweibo/__init__.py
|
YIDAMU/pyweibo
|
60c944ac5db7de090c607551c8004bb645c0cfdd
|
[
"MIT"
] | null | null | null |
pyweibo/__init__.py
|
YIDAMU/pyweibo
|
60c944ac5db7de090c607551c8004bb645c0cfdd
|
[
"MIT"
] | null | null | null |
from .client import Client, UploadClient
from .auth import Auth
from .reader import LocalFileReader, AppInfoInputReader, TokenInputReader
from .token import Token, AppInfo
| 34.4
| 73
| 0.837209
| 20
| 172
| 7.2
| 0.55
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.116279
| 172
| 4
| 74
| 43
| 0.947368
| 0
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| 0
| 0
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| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 4
|
f1f5331fad13c0c12983d5dd006b73b18ff07f06
| 53
|
py
|
Python
|
exam_grading/initialize_notebook.py
|
valgarf/exam-grading
|
ae6f62fb71c40a16ede6297c8c59d6fb2521b1d7
|
[
"MIT"
] | null | null | null |
exam_grading/initialize_notebook.py
|
valgarf/exam-grading
|
ae6f62fb71c40a16ede6297c8c59d6fb2521b1d7
|
[
"MIT"
] | null | null | null |
exam_grading/initialize_notebook.py
|
valgarf/exam-grading
|
ae6f62fb71c40a16ede6297c8c59d6fb2521b1d7
|
[
"MIT"
] | null | null | null |
from . import exam_data
data = exam_data.ExamData()
| 13.25
| 27
| 0.754717
| 8
| 53
| 4.75
| 0.625
| 0.421053
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.150943
| 53
| 3
| 28
| 17.666667
| 0.844444
| 0
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| 0
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| 1
| 0
| false
| 0
| 0.5
| 0
| 0.5
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| 0
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
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| 0
| 0
| 0
| 1
| 0
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| 0
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| 0
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| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
|
0
| 4
|
7b16093f5831e373f522687d0fa6629fb723f377
| 5,395
|
py
|
Python
|
contrib/pc3/info/ipaw/pc3/LoadSql.py
|
celiafish/VisTrails
|
d8cb575b8b121941de190fe608003ad1427ef9f6
|
[
"BSD-3-Clause"
] | 83
|
2015-01-05T14:50:50.000Z
|
2021-09-17T19:45:26.000Z
|
contrib/pc3/info/ipaw/pc3/LoadSql.py
|
celiafish/VisTrails
|
d8cb575b8b121941de190fe608003ad1427ef9f6
|
[
"BSD-3-Clause"
] | 254
|
2015-01-02T20:39:19.000Z
|
2018-11-28T17:16:44.000Z
|
contrib/pc3/info/ipaw/pc3/LoadSql.py
|
celiafish/VisTrails
|
d8cb575b8b121941de190fe608003ad1427ef9f6
|
[
"BSD-3-Clause"
] | 40
|
2015-04-17T16:46:36.000Z
|
2021-09-28T22:43:24.000Z
|
class LoadSql(object):
CREATE_DETECTION_TABLE = \
"""
CREATE TABLE P2Detection(
`objID` bigint NOT NULL,
detectID bigint NOT NULL,
ippObjID bigint NOT NULL,
ippDetectID bigint NOT NULL,
filterID smallint NOT NULL,
imageID bigint NOT NULL,
obsTime float NOT NULL DEFAULT -999,
xPos real NOT NULL DEFAULT -999,
yPos real NOT NULL DEFAULT -999,
xPosErr real NOT NULL DEFAULT -999,
yPosErr real NOT NULL DEFAULT -999,
instFlux real NOT NULL DEFAULT -999,
instFluxErr real NOT NULL DEFAULT -999,
psfWidMajor real NOT NULL DEFAULT -999,
psfWidMinor real NOT NULL DEFAULT -999,
psfTheta real NOT NULL DEFAULT -999,
psfLikelihood real NOT NULL DEFAULT -999,
psfCf real NOT NULL DEFAULT -999,
infoFlag int NOT NULL DEFAULT -999,
htmID float NOT NULL DEFAULT -999,
zoneID float NOT NULL DEFAULT -999,
assocDate date NOT NULL DEFAULT '28881231',
modNum smallint NOT NULL DEFAULT 0,
ra float NOT NULL,
`dec` float NOT NULL,
raErr real NOT NULL DEFAULT 0,
decErr real NOT NULL DEFAULT 0,
cx float NOT NULL DEFAULT -999,
cy float NOT NULL DEFAULT -999,
cz float NOT NULL DEFAULT -999,
peakFlux real NOT NULL DEFAULT -999,
calMag real NOT NULL DEFAULT -999,
calMagErr real NOT NULL DEFAULT -999,
calFlux real NOT NULL DEFAULT -999,
calFluxErr real NOT NULL DEFAULT -999,
calColor real NOT NULL DEFAULT -999,
calColorErr real NOT NULL DEFAULT -999,
sky real NOT NULL DEFAULT -999,
skyErr real NOT NULL DEFAULT -999,
sgSep real NOT NULL DEFAULT -999,
dataRelease smallint NOT NULL,
CONSTRAINT PK_P2Detection_objID_detectID PRIMARY KEY
(
`objID`,
detectID
))
"""
CREATE_FRAME_META_TABLE = \
"""
CREATE TABLE P2FrameMeta(
frameID int NOT NULL PRIMARY KEY,
surveyID smallint NOT NULL,
filterID smallint NOT NULL,
cameraID smallint NOT NULL,
telescopeID smallint NOT NULL,
analysisVer smallint NOT NULL,
p1Recip smallint NOT NULL DEFAULT -999,
p2Recip smallint NOT NULL DEFAULT -999,
p3Recip smallint NOT NULL DEFAULT -999,
nP2Images smallint NOT NULL DEFAULT -999,
astroScat real NOT NULL DEFAULT -999,
photoScat real NOT NULL DEFAULT -999,
nAstRef int NOT NULL DEFAULT -999,
nPhoRef int NOT NULL DEFAULT -999,
expStart float NOT NULL DEFAULT -999,
expTime real NOT NULL DEFAULT -999,
airmass real NOT NULL DEFAULT -999,
raBore float NOT NULL DEFAULT -999,
decBore float NOT NULL DEFAULT -999
)
"""
CREATE_IMAGE_META_TABLE = \
"""
CREATE TABLE P2ImageMeta(
imageID bigint NOT NULL PRIMARY KEY,
frameID int NOT NULL,
ccdID smallint NOT NULL,
photoCalID int NOT NULL,
filterID smallint NOT NULL,
bias real NOT NULL DEFAULT -999,
biasScat real NOT NULL DEFAULT -999,
sky real NOT NULL DEFAULT -999,
skyScat real NOT NULL DEFAULT -999,
nDetect int NOT NULL DEFAULT -999,
magSat real NOT NULL DEFAULT -999,
completMag real NOT NULL DEFAULT -999,
astroScat real NOT NULL DEFAULT -999,
photoScat real NOT NULL DEFAULT -999,
nAstRef int NOT NULL DEFAULT -999,
nPhoRef int NOT NULL DEFAULT -999,
nx smallint NOT NULL DEFAULT -999,
ny smallint NOT NULL DEFAULT -999,
psfFwhm real NOT NULL DEFAULT -999,
psfModelID int NOT NULL DEFAULT -999,
psfSigMajor real NOT NULL DEFAULT -999,
psfSigMinor real NOT NULL DEFAULT -999,
psfTheta real NOT NULL DEFAULT -999,
psfExtra1 real NOT NULL DEFAULT -999,
psfExtra2 real NOT NULL DEFAULT -999,
apResid real NOT NULL DEFAULT -999,
dapResid real NOT NULL DEFAULT -999,
detectorID smallint NOT NULL DEFAULT -999,
qaFlags int NOT NULL DEFAULT -999,
detrend1 bigint NOT NULL DEFAULT -999,
detrend2 bigint NOT NULL DEFAULT -999,
detrend3 bigint NOT NULL DEFAULT -999,
detrend4 bigint NOT NULL DEFAULT -999,
detrend5 bigint NOT NULL DEFAULT -999,
detrend6 bigint NOT NULL DEFAULT -999,
detrend7 bigint NOT NULL DEFAULT -999,
detrend8 bigint NOT NULL DEFAULT -999,
photoZero real NOT NULL DEFAULT -999,
photoColor real NOT NULL DEFAULT -999,
projection1 varchar(8000) NOT NULL DEFAULT '-999',
projection2 varchar(8000) NOT NULL DEFAULT '-999',
crval1 float NOT NULL DEFAULT -999,
crval2 float NOT NULL DEFAULT -999,
crpix1 float NOT NULL DEFAULT -999,
crpix2 float NOT NULL DEFAULT -999,
pc001001 float NOT NULL DEFAULT -999,
pc001002 float NOT NULL DEFAULT -999,
pc002001 float NOT NULL DEFAULT -999,
pc002002 float NOT NULL DEFAULT -999,
polyOrder int NOT NULL DEFAULT -999,
pca1x3y0 float NOT NULL DEFAULT -999,
pca1x2y1 float NOT NULL DEFAULT -999,
pca1x1y2 float NOT NULL DEFAULT -999,
pca1x0y3 float NOT NULL DEFAULT -999,
pca1x2y0 float NOT NULL DEFAULT -999,
pca1x1y1 float NOT NULL DEFAULT -999,
pca1x0y2 float NOT NULL DEFAULT -999,
pca2x3y0 float NOT NULL DEFAULT -999,
pca2x2y1 float NOT NULL DEFAULT -999,
pca2x1y2 float NOT NULL DEFAULT -999,
pca2x0y3 float NOT NULL DEFAULT -999,
pca2x2y0 float NOT NULL DEFAULT -999,
pca2x1y1 float NOT NULL DEFAULT -999,
pca2x0y2 float NOT NULL DEFAULT -999
)
"""
| 36.452703
| 55
| 0.685449
| 742
| 5,395
| 4.969003
| 0.19407
| 0.235422
| 0.394901
| 0.461079
| 0.649308
| 0.162191
| 0.122593
| 0.122593
| 0.122593
| 0.122593
| 0
| 0.102971
| 0.263763
| 5,395
| 147
| 56
| 36.70068
| 0.825277
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| null | 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
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| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
|
0
| 4
|
7b18efbc785ed3ae684ae7ed423b42a40f49686d
| 424
|
py
|
Python
|
Bio/motifs/applications/__init__.py
|
bioinf-mcb/biopython
|
1a1f4a7ee4e0efba517d3d607c56c27e72e399cc
|
[
"BSD-3-Clause"
] | 2
|
2021-03-04T16:57:06.000Z
|
2021-08-11T01:42:29.000Z
|
Bio/motifs/applications/__init__.py
|
cosign070128/biopython
|
2f02e34ba76306e9c27eec9e051809bec2cece9b
|
[
"BSD-3-Clause"
] | 14
|
2021-03-26T20:54:22.000Z
|
2021-04-06T17:18:53.000Z
|
Bio/motifs/applications/__init__.py
|
cosign070128/biopython
|
2f02e34ba76306e9c27eec9e051809bec2cece9b
|
[
"BSD-3-Clause"
] | 3
|
2020-05-17T19:43:05.000Z
|
2020-06-04T20:44:38.000Z
|
# Copyright 2009 by Bartek Wilczynski. All rights reserved.
# Revisions copyright 2009 by Peter Cock.
#
# This file is part of the Biopython distribution and governed by your
# choice of the "Biopython License Agreement" or the "BSD 3-Clause License".
# Please see the LICENSE file that should have been included as part of this
# package.
"""Motif command line tool wrappers."""
from ._xxmotif import XXmotifCommandline
| 35.333333
| 76
| 0.773585
| 62
| 424
| 5.274194
| 0.758065
| 0.079511
| 0.091743
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.025496
| 0.167453
| 424
| 11
| 77
| 38.545455
| 0.90085
| 0.851415
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
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| 0
| null | 0
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| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 4
|
9e4eff7b8cf0a0bbeff3ca989880d9c84a991088
| 1,437
|
py
|
Python
|
respyabc/tests/test_respyabc.py
|
manuhuth/respyabc
|
1da7478775099028249983d2e098f7b3fcd562bb
|
[
"MIT"
] | null | null | null |
respyabc/tests/test_respyabc.py
|
manuhuth/respyabc
|
1da7478775099028249983d2e098f7b3fcd562bb
|
[
"MIT"
] | null | null | null |
respyabc/tests/test_respyabc.py
|
manuhuth/respyabc
|
1da7478775099028249983d2e098f7b3fcd562bb
|
[
"MIT"
] | 2
|
2021-05-07T12:58:07.000Z
|
2021-09-16T11:48:34.000Z
|
"""Tests to check if :func:`respyabc.respyabc()` function runs."""
from respyabc.tools import prepare_test_respyabc
from respyabc.tools import prepare_test_respyabc_model_selection
def test_delta_choice_frequencies():
parameter_true = {"delta_delta": 0.95}
prepare_test_respyabc(
parameter_true=parameter_true,
prior_low=0.9,
prior_size=0.09,
descriptives="choice_frequencies",
)
def test_wage_a_constant_choice_frequencies():
parameter_true = {"wage_a_constant": 9.21}
prepare_test_respyabc(
parameter_true=parameter_true,
prior_low=9,
prior_size=0.9,
descriptives="choice_frequencies",
)
def test_delta_wage_moments():
parameter_true = {"delta_delta": 0.95}
prepare_test_respyabc(
parameter_true=parameter_true,
prior_low=0.9,
prior_size=0.09,
descriptives="wage_moments",
)
def test_wage_a_constant_wage_moments():
parameter_true = {"wage_a_constant": 9.21}
prepare_test_respyabc(
parameter_true=parameter_true,
prior_low=9,
prior_size=0.9,
descriptives="wage_moments",
)
def test_delta_choice_frequencies_model_selection():
parameter_true = {"delta_delta": 0.95}
prepare_test_respyabc_model_selection(
parameter_true=parameter_true,
prior_low=0.9,
prior_size=0.09,
descriptives="choice_frequencies",
)
| 26.127273
| 66
| 0.693807
| 178
| 1,437
| 5.174157
| 0.191011
| 0.211726
| 0.144408
| 0.141151
| 0.887079
| 0.700326
| 0.700326
| 0.609121
| 0.609121
| 0.560261
| 0
| 0.03183
| 0.212944
| 1,437
| 54
| 67
| 26.611111
| 0.782493
| 0.041754
| 0
| 0.690476
| 0
| 0
| 0.102845
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.119048
| false
| 0
| 0.047619
| 0
| 0.166667
| 0
| 0
| 0
| 0
| null | 1
| 0
| 0
| 1
| 1
| 1
| 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
| 4
|
9e60173a382ab3ecafd358dc7a6e09c387bb9fe5
| 3,246
|
py
|
Python
|
freezing/kaa_freeze.py
|
tnhung2011/kaa
|
e6a8819a5ecba04b7db8303bd5736b5a7c9b822d
|
[
"Unlicense"
] | 82
|
2015-01-26T15:34:03.000Z
|
2021-12-03T14:34:23.000Z
|
freezing/kaa_freeze.py
|
tnhung2011/kaa
|
e6a8819a5ecba04b7db8303bd5736b5a7c9b822d
|
[
"Unlicense"
] | 34
|
2015-02-09T08:13:05.000Z
|
2021-04-08T08:19:05.000Z
|
freezing/kaa_freeze.py
|
tnhung2011/kaa
|
e6a8819a5ecba04b7db8303bd5736b5a7c9b822d
|
[
"Unlicense"
] | 15
|
2015-05-21T07:41:17.000Z
|
2021-10-16T13:33:22.000Z
|
# check issue 11824 and issue 16047 to use freeze.
# ~/python332/bin/python3 ~/python332/Tools/freeze/freeze.py -o build -m kaa.py
import encodings
import encodings.aliases
import encodings.ascii
import encodings.base64_codec
import encodings.big5
import encodings.big5hkscs
import encodings.bz2_codec
import encodings.charmap
import encodings.cp037
import encodings.cp1006
import encodings.cp1026
import encodings.cp1140
import encodings.cp1250
import encodings.cp1251
import encodings.cp1252
import encodings.cp1253
import encodings.cp1254
import encodings.cp1255
import encodings.cp1256
import encodings.cp1257
import encodings.cp1258
import encodings.cp424
import encodings.cp437
import encodings.cp500
import encodings.cp720
import encodings.cp737
import encodings.cp775
import encodings.cp850
import encodings.cp852
import encodings.cp855
import encodings.cp856
import encodings.cp857
import encodings.cp858
import encodings.cp860
import encodings.cp861
import encodings.cp862
import encodings.cp863
import encodings.cp864
import encodings.cp865
import encodings.cp866
import encodings.cp869
import encodings.cp874
import encodings.cp875
import encodings.cp932
import encodings.cp949
import encodings.cp950
import encodings.euc_jis_2004
import encodings.euc_jisx0213
import encodings.euc_jp
import encodings.euc_kr
import encodings.gb18030
import encodings.gb2312
import encodings.gbk
import encodings.hex_codec
import encodings.hp_roman8
import encodings.hz
import encodings.idna
import encodings.iso2022_jp
import encodings.iso2022_jp_1
import encodings.iso2022_jp_2
import encodings.iso2022_jp_2004
import encodings.iso2022_jp_3
import encodings.iso2022_jp_ext
import encodings.iso2022_kr
import encodings.iso8859_1
import encodings.iso8859_10
import encodings.iso8859_11
import encodings.iso8859_13
import encodings.iso8859_14
import encodings.iso8859_15
import encodings.iso8859_16
import encodings.iso8859_2
import encodings.iso8859_3
import encodings.iso8859_4
import encodings.iso8859_5
import encodings.iso8859_6
import encodings.iso8859_7
import encodings.iso8859_8
import encodings.iso8859_9
import encodings.johab
import encodings.koi8_r
import encodings.koi8_u
import encodings.latin_1
import encodings.mac_arabic
import encodings.mac_centeuro
import encodings.mac_croatian
import encodings.mac_cyrillic
import encodings.mac_farsi
import encodings.mac_greek
import encodings.mac_iceland
import encodings.mac_latin2
import encodings.mac_roman
import encodings.mac_romanian
import encodings.mac_turkish
import encodings.palmos
import encodings.ptcp154
import encodings.punycode
import encodings.quopri_codec
import encodings.raw_unicode_escape
import encodings.rot_13
import encodings.shift_jis
import encodings.shift_jis_2004
import encodings.shift_jisx0213
import encodings.tis_620
import encodings.undefined
import encodings.unicode_escape
import encodings.unicode_internal
import encodings.utf_16
import encodings.utf_16_be
import encodings.utf_16_le
import encodings.utf_32
import encodings.utf_32_be
import encodings.utf_32_le
import encodings.utf_7
import encodings.utf_8
import encodings.utf_8_sig
import encodings.uu_codec
import encodings.zlib_codec
import kaa.cui.main
import sys
del sys.path[:]
kaa.cui.main.run()
| 25.359375
| 79
| 0.874615
| 465
| 3,246
| 5.939785
| 0.301075
| 0.64084
| 0.119479
| 0.052136
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.106269
| 0.081023
| 3,246
| 127
| 80
| 25.559055
| 0.819645
| 0.038817
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.983607
| 0
| 0.983607
| 0
| 0
| 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
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 4
|
9e67ccf03651a3730bf608835cc7550f845219d1
| 16
|
py
|
Python
|
htmlq/version.py
|
dealfonso/htmlq
|
e5028841dc65bc24f3719d3ac44da245912b25ed
|
[
"Apache-2.0"
] | null | null | null |
htmlq/version.py
|
dealfonso/htmlq
|
e5028841dc65bc24f3719d3ac44da245912b25ed
|
[
"Apache-2.0"
] | null | null | null |
htmlq/version.py
|
dealfonso/htmlq
|
e5028841dc65bc24f3719d3ac44da245912b25ed
|
[
"Apache-2.0"
] | null | null | null |
VERSION="0.1.8"
| 8
| 15
| 0.625
| 4
| 16
| 2.5
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.2
| 0.0625
| 16
| 1
| 16
| 16
| 0.466667
| 0
| 0
| 0
| 0
| 0
| 0.3125
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0
| 0
| 0
| 0
| 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
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
9e6b0aa2a40be3ccf8e035026648d9db484440a7
| 132
|
py
|
Python
|
grout_server/apps.py
|
azavea/ashlar-server
|
4a9a6cb87b082845c30da0d2aa0cfc97f985d820
|
[
"Apache-2.0"
] | 1
|
2018-07-13T20:13:34.000Z
|
2018-07-13T20:13:34.000Z
|
grout_server/apps.py
|
azavea/grout-server
|
4a9a6cb87b082845c30da0d2aa0cfc97f985d820
|
[
"Apache-2.0"
] | 22
|
2018-07-17T17:13:33.000Z
|
2018-08-23T19:37:29.000Z
|
grout-server/grout_server/apps.py
|
jeancochrane/philly-fliers
|
2f2e3b9f4511933dbf1501701b54754ee524a1e6
|
[
"MIT"
] | null | null | null |
from django.apps import AppConfig
class GroutServerConfig(AppConfig):
name = 'grout_server'
verbose_name = 'Grout Server'
| 18.857143
| 35
| 0.75
| 15
| 132
| 6.466667
| 0.733333
| 0.185567
| 0.309278
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.174242
| 132
| 6
| 36
| 22
| 0.889908
| 0
| 0
| 0
| 0
| 0
| 0.181818
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.25
| 0
| 1
| 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
| 0
| 0
| 0
| 0
| 1
| 0
|
0
| 4
|
9eaacf0aa06c187da67be7fbb03c576b7a47ed29
| 384
|
py
|
Python
|
starkit/evolutionkit/base.py
|
dchu808/starkit
|
1940683ef231cee54be2c703d4a7611a3991d8b7
|
[
"BSD-3-Clause"
] | 12
|
2018-05-15T14:59:27.000Z
|
2022-01-11T16:44:43.000Z
|
starkit/evolutionkit/base.py
|
dchu808/starkit
|
1940683ef231cee54be2c703d4a7611a3991d8b7
|
[
"BSD-3-Clause"
] | 27
|
2018-03-13T10:45:38.000Z
|
2020-08-03T20:47:31.000Z
|
starkit/evolutionkit/base.py
|
dchu808/starkit
|
1940683ef231cee54be2c703d4a7611a3991d8b7
|
[
"BSD-3-Clause"
] | 17
|
2018-03-13T10:06:53.000Z
|
2019-06-27T02:02:10.000Z
|
from astropy import modeling
class GridConnector(modeling.Model):
inputs = tuple('teff', 'logg', 'mh', 'radius')
outputs = ('wavelength', 'flux')
def __init__(self, grid, **kwargs):
super(GridConnector, self).__init__(**kwargs)
self.grid = grid
def evaluate(self, teff, logg, mh, radius):
return self.grid.evaluate(teff, logg, mh, radius)
| 25.6
| 57
| 0.640625
| 45
| 384
| 5.288889
| 0.533333
| 0.10084
| 0.12605
| 0.201681
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.210938
| 384
| 14
| 58
| 27.428571
| 0.785479
| 0
| 0
| 0
| 0
| 0
| 0.078329
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.222222
| false
| 0
| 0.111111
| 0.111111
| 0.777778
| 0
| 0
| 0
| 0
| null | 0
| 0
| 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
| 4
|
7b46be6b074b191714c94badd36174b22f1d020a
| 623
|
py
|
Python
|
ds_discovery/__init__.py
|
project-hadron/discovery-transition-ds
|
08229ca3b7617b42ce2dd8e47ff93876c0843810
|
[
"BSD-3-Clause"
] | 2
|
2020-09-21T17:24:16.000Z
|
2021-05-28T18:02:54.000Z
|
ds_discovery/__init__.py
|
project-hadron/discovery-transition-ds
|
08229ca3b7617b42ce2dd8e47ff93876c0843810
|
[
"BSD-3-Clause"
] | null | null | null |
ds_discovery/__init__.py
|
project-hadron/discovery-transition-ds
|
08229ca3b7617b42ce2dd8e47ff93876c0843810
|
[
"BSD-3-Clause"
] | 1
|
2021-07-23T13:52:04.000Z
|
2021-07-23T13:52:04.000Z
|
# bring definitions to the top level
from ds_discovery.components.synthetic_builder import SyntheticBuilder
from ds_discovery.components.transitioning import Transition
from ds_discovery.components.wrangling import Wrangle
from ds_discovery.components.feature_catalog import FeatureCatalog
from ds_discovery.components.event_book_portfolio import EventBookPortfolio
from ds_discovery.components.data_drift import DataDrift
from ds_discovery.components.models_builder import ModelsBuilder
from ds_discovery.components.controller import Controller
# release version number picked up in the setup.py
__version__ = "3.02.085"
| 47.923077
| 75
| 0.87801
| 81
| 623
| 6.530864
| 0.518519
| 0.090737
| 0.226843
| 0.378072
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.010508
| 0.083467
| 623
| 12
| 76
| 51.916667
| 0.915937
| 0.133226
| 0
| 0
| 0
| 0
| 0.014898
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.888889
| 0
| 0.888889
| 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
| 0
| 0
| 1
| 0
| 1
| 0
|
0
| 4
|
7b69cf826ee02104f743976bc184e7309f0c62e9
| 27
|
py
|
Python
|
wdmtoolbox/__init__.py
|
JLisin/wdmtoolbox
|
3a61fa935627c7a451920a6c039370d57c53bdbc
|
[
"BSD-3-Clause"
] | null | null | null |
wdmtoolbox/__init__.py
|
JLisin/wdmtoolbox
|
3a61fa935627c7a451920a6c039370d57c53bdbc
|
[
"BSD-3-Clause"
] | null | null | null |
wdmtoolbox/__init__.py
|
JLisin/wdmtoolbox
|
3a61fa935627c7a451920a6c039370d57c53bdbc
|
[
"BSD-3-Clause"
] | null | null | null |
"""Package __init__.py."""
| 13.5
| 26
| 0.62963
| 3
| 27
| 4.333333
| 1
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| 0
| 0.074074
| 27
| 1
| 27
| 27
| 0.52
| 0.740741
| 0
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| 0
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| null | 0
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| 0
| 0
| 0
| 0
|
0
| 4
|
7b7f4ccb03dfbc1a4f52aff4f12e63ea17fb00dc
| 1,287
|
py
|
Python
|
integrationtest/vm/simulator/suite_setup.py
|
hyhhui/zstack-woodpecker
|
ac36ae033cc521e2f877763de3ff55e4762e3ae0
|
[
"Apache-2.0"
] | 2
|
2016-03-23T08:45:44.000Z
|
2017-06-26T02:40:46.000Z
|
integrationtest/vm/simulator/suite_setup.py
|
KevinDavidMitnick/zstack-woodpecker
|
96257faaf3c362168d008bdb47002025ad669b24
|
[
"Apache-2.0"
] | null | null | null |
integrationtest/vm/simulator/suite_setup.py
|
KevinDavidMitnick/zstack-woodpecker
|
96257faaf3c362168d008bdb47002025ad669b24
|
[
"Apache-2.0"
] | 2
|
2020-03-12T03:11:28.000Z
|
2021-07-26T01:57:58.000Z
|
'''
@author: Frank
'''
from zstackwoodpecker import test_util
import os.path
from zstacklib.utils import linux
from zstacklib.utils import http
from zstacktestagent.plugins import host as host_plugin
from zstacktestagent import testagent
import zstackwoodpecker.operations.deploy_operations as deploy_operations
import zstackwoodpecker.operations.config_operations as config_operations
import zstackwoodpecker.test_lib as test_lib
def test():
#This vlan creation is not a must, if testing is under nested virt env. But it is required on physical host without enough physcial network devices and your test execution machine is not the same one as Host machine.
#linux.create_vlan_eth("eth0", 10, "10.0.0.200", "255.255.255.0")
#linux.create_vlan_eth("eth0", 11, "10.0.1.200", "255.255.255.0")
#If test execution machine is not the same one as Host machine, deploy work is needed to separated to 2 steps(deploy_test_agent, execute_plan_without_deploy_test_agent). And it can not directly call SetupAction.run()
test_lib.setup_plan.deploy_test_agent()
test_lib.setup_plan.execute_plan_without_deploy_test_agent()
deploy_operations.deploy_initial_database(test_lib.deploy_config)
test_util.test_pass('Suite Setup Success')
| 44.37931
| 222
| 0.78244
| 195
| 1,287
| 4.974359
| 0.425641
| 0.036082
| 0.061856
| 0.049485
| 0.239175
| 0.16701
| 0.098969
| 0.098969
| 0.098969
| 0.098969
| 0
| 0.037443
| 0.149184
| 1,287
| 28
| 223
| 45.964286
| 0.848402
| 0.445998
| 0
| 0
| 0
| 0
| 0.028274
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.071429
| true
| 0.071429
| 0.642857
| 0
| 0.714286
| 0
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| null | 0
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| 0
| 0
| 0
| 0
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| 0
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| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 1
| 0
| 1
| 0
|
0
| 4
|
7b8b281402aaf0a10dc7b67619d5fa0ddc5842d9
| 106
|
py
|
Python
|
fastNLP/modules/decoder/__init__.py
|
h00Jiang/fastNLP
|
79ddb469d81946c87a3d066122a8a3aba6e40f3a
|
[
"Apache-2.0"
] | 1
|
2019-04-10T03:37:18.000Z
|
2019-04-10T03:37:18.000Z
|
fastNLP/modules/decoder/__init__.py
|
TTTREE/fastNLP
|
ef82c1f10000752db32a5fa323668b94bcb940a1
|
[
"Apache-2.0"
] | 1
|
2018-09-30T13:30:51.000Z
|
2018-09-30T13:30:51.000Z
|
fastNLP/modules/decoder/__init__.py
|
TTTREE/fastNLP
|
ef82c1f10000752db32a5fa323668b94bcb940a1
|
[
"Apache-2.0"
] | null | null | null |
from .CRF import ConditionalRandomField
from .MLP import MLP
__all__ = ["ConditionalRandomField", "MLP"]
| 21.2
| 43
| 0.783019
| 11
| 106
| 7.181818
| 0.545455
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.122642
| 106
| 4
| 44
| 26.5
| 0.849462
| 0
| 0
| 0
| 0
| 0
| 0.235849
| 0.207547
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 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
| 0
| 0
| 1
| 0
| 1
| 0
|
0
| 4
|
7bb5692bd2ff291bc423963670a1c02e2b7dc2ba
| 219
|
py
|
Python
|
exercicios/exer003.py
|
franklinperseuDS/Python
|
16a8545ce3aa873f5e758e3db5f04f60887f9dfc
|
[
"MIT"
] | null | null | null |
exercicios/exer003.py
|
franklinperseuDS/Python
|
16a8545ce3aa873f5e758e3db5f04f60887f9dfc
|
[
"MIT"
] | null | null | null |
exercicios/exer003.py
|
franklinperseuDS/Python
|
16a8545ce3aa873f5e758e3db5f04f60887f9dfc
|
[
"MIT"
] | null | null | null |
#Adicionar dois números e mostrar a soma
print("==========Exercicio 3 ==========")
numero1 = int(input("Digite um número: "))
numero2 = int(input("Digite outro número: "))
print(numero1,"+",numero2,"=",numero1+numero2)
| 36.5
| 46
| 0.648402
| 27
| 219
| 5.259259
| 0.666667
| 0.112676
| 0.197183
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.035714
| 0.105023
| 219
| 6
| 46
| 36.5
| 0.688776
| 0.178082
| 0
| 0
| 0
| 0
| 0.405556
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0
| 0
| 0
| 0.5
| 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
| 0
| 0
| 0
| 0
| 0
| 1
|
0
| 4
|
c8de8b2a21f6ef5adbaa8f341317e751c4886c35
| 55
|
py
|
Python
|
lib/TermColors.py
|
Monofraps/Mocca
|
0f4a1f5690fad457aaf4ea26d3d0271b34c6e187
|
[
"MIT"
] | null | null | null |
lib/TermColors.py
|
Monofraps/Mocca
|
0f4a1f5690fad457aaf4ea26d3d0271b34c6e187
|
[
"MIT"
] | 4
|
2015-01-09T18:02:51.000Z
|
2015-01-10T01:06:58.000Z
|
lib/TermColors.py
|
Monofraps/Mocca
|
0f4a1f5690fad457aaf4ea26d3d0271b34c6e187
|
[
"MIT"
] | null | null | null |
INFO = '\033[94m'
FAIL = '\033[91;1m'
ENDC = '\033[0m'
| 13.75
| 19
| 0.545455
| 10
| 55
| 3
| 0.8
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.326087
| 0.163636
| 55
| 3
| 20
| 18.333333
| 0.326087
| 0
| 0
| 0
| 0
| 0
| 0.454545
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 1
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
cdc6a885a6d2e755390d469a46ad8c5b25ec2097
| 76
|
py
|
Python
|
deepinpy/forwards/mcmri/__init__.py
|
han20192019/deepinpy
|
0fbdfc9cd81f4d698bb1d5e361ef1223a2c8dd1d
|
[
"MIT"
] | 30
|
2020-03-07T04:36:03.000Z
|
2021-12-15T06:28:12.000Z
|
deepinpy/forwards/mcmri/__init__.py
|
han20192019/deepinpy
|
0fbdfc9cd81f4d698bb1d5e361ef1223a2c8dd1d
|
[
"MIT"
] | 13
|
2020-03-14T06:12:20.000Z
|
2021-05-20T04:33:58.000Z
|
deepinpy/forwards/mcmri/__init__.py
|
han20192019/deepinpy
|
0fbdfc9cd81f4d698bb1d5e361ef1223a2c8dd1d
|
[
"MIT"
] | 22
|
2020-02-28T18:20:54.000Z
|
2022-02-16T11:21:58.000Z
|
"""
Deep inverse problems in Python
Multi-channel MRI forward operator
"""
| 12.666667
| 34
| 0.75
| 10
| 76
| 5.7
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.157895
| 76
| 5
| 35
| 15.2
| 0.890625
| 0.881579
| 0
| null | 0
| 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
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
a82819a923245cf8fbe6948928525a66448497f3
| 143
|
py
|
Python
|
office365/sharepoint/request_context.py
|
juguerre/Office365-REST-Python-Client
|
dbadaddb14e7bad199499c898cdef1ada9694fc9
|
[
"MIT"
] | null | null | null |
office365/sharepoint/request_context.py
|
juguerre/Office365-REST-Python-Client
|
dbadaddb14e7bad199499c898cdef1ada9694fc9
|
[
"MIT"
] | null | null | null |
office365/sharepoint/request_context.py
|
juguerre/Office365-REST-Python-Client
|
dbadaddb14e7bad199499c898cdef1ada9694fc9
|
[
"MIT"
] | null | null | null |
from office365.runtime.client_object import ClientObject
class RequestContext(ClientObject):
def get_remote_context(self):
pass
| 17.875
| 56
| 0.776224
| 16
| 143
| 6.75
| 0.9375
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.02521
| 0.167832
| 143
| 7
| 57
| 20.428571
| 0.882353
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.25
| false
| 0.25
| 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
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
| 0
|
0
| 4
|
b52c22fb5a68932a3b86b5f58a7a0f21fd90d955
| 50
|
py
|
Python
|
tests/__init__.py
|
SamuelMarks/runtime-type-checker
|
bf4a06701acc07f3aa547aa71467f1bd595fbe8b
|
[
"MIT"
] | 4
|
2021-02-25T12:47:28.000Z
|
2021-12-22T08:04:01.000Z
|
tests/__init__.py
|
SamuelMarks/runtime-type-checker
|
bf4a06701acc07f3aa547aa71467f1bd595fbe8b
|
[
"MIT"
] | 3
|
2020-10-25T13:36:20.000Z
|
2021-06-15T11:03:41.000Z
|
tests/__init__.py
|
SamuelMarks/runtime-type-checker
|
bf4a06701acc07f3aa547aa71467f1bd595fbe8b
|
[
"MIT"
] | 1
|
2020-10-23T00:55:21.000Z
|
2020-10-23T00:55:21.000Z
|
"""Unit test package for runtime_type_checker."""
| 25
| 49
| 0.76
| 7
| 50
| 5.142857
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.1
| 50
| 1
| 50
| 50
| 0.8
| 0.86
| 0
| null | 0
| 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
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
b53278efee843a04498d898aabd17a825f902596
| 225
|
py
|
Python
|
main/extensions.py
|
Curiouspaul1/Ecolead
|
1c5008b9ad9a6611b76bf61539ae3af9da06afc5
|
[
"MIT"
] | null | null | null |
main/extensions.py
|
Curiouspaul1/Ecolead
|
1c5008b9ad9a6611b76bf61539ae3af9da06afc5
|
[
"MIT"
] | null | null | null |
main/extensions.py
|
Curiouspaul1/Ecolead
|
1c5008b9ad9a6611b76bf61539ae3af9da06afc5
|
[
"MIT"
] | null | null | null |
from flask_sqlalchemy import SQLAlchemy
from flask_marshmallow import Marshmallow
from flask_bcrypt import Bcrypt
from flask_migrate import Migrate
ma = Marshmallow()
db = SQLAlchemy()
bcrypt_ = Bcrypt()
migrate = Migrate()
| 22.5
| 41
| 0.817778
| 28
| 225
| 6.392857
| 0.321429
| 0.201117
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.128889
| 225
| 9
| 42
| 25
| 0.913265
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.5
| 0
| 0.5
| 0
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| 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
| 1
| 0
| 0
| 0
|
0
| 4
|
b565b5308c6468e57ec2d70b663f90a8d585d365
| 177
|
py
|
Python
|
seedstar_casestudy_one/emaillist/forms.py
|
elayira/seedstar_casestudy_one
|
a1ed30f464546f1d9de5c1eb353585a720990bc2
|
[
"MIT"
] | null | null | null |
seedstar_casestudy_one/emaillist/forms.py
|
elayira/seedstar_casestudy_one
|
a1ed30f464546f1d9de5c1eb353585a720990bc2
|
[
"MIT"
] | null | null | null |
seedstar_casestudy_one/emaillist/forms.py
|
elayira/seedstar_casestudy_one
|
a1ed30f464546f1d9de5c1eb353585a720990bc2
|
[
"MIT"
] | null | null | null |
from django.forms import ModelForm
from .models import EmailList
class EmailListForm(ModelForm):
class Meta:
model = EmailList
fields = ['name', 'email']
| 17.7
| 34
| 0.677966
| 19
| 177
| 6.315789
| 0.736842
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.237288
| 177
| 9
| 35
| 19.666667
| 0.888889
| 0
| 0
| 0
| 0
| 0
| 0.050847
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.333333
| 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
| 0
| 0
| 1
| 0
| 1
| 0
|
0
| 4
|
b57931e2d2dee7d225fcdc2fa9ee448d21ae0eb8
| 572
|
py
|
Python
|
gweld/__init__.py
|
ieuanjones/gweld
|
903cd5619822f8448dd3b071dbbdeb5ff89b76aa
|
[
"MIT"
] | null | null | null |
gweld/__init__.py
|
ieuanjones/gweld
|
903cd5619822f8448dd3b071dbbdeb5ff89b76aa
|
[
"MIT"
] | null | null | null |
gweld/__init__.py
|
ieuanjones/gweld
|
903cd5619822f8448dd3b071dbbdeb5ff89b76aa
|
[
"MIT"
] | 2
|
2020-04-18T11:17:57.000Z
|
2020-04-18T11:20:19.000Z
|
from gweld.data import Data
from gweld.data_set import DataSet
from gweld.style.text_style import TextStyle
from gweld.style.circle_text_style import CircleTextStyle
from gweld.style.style import Style
from gweld.elements.vis_element import VisElement
from gweld.elements.text_element import TextElement
from gweld.elements.axis_element import AxisElement
from gweld.elements.bg_element import BGElement
from gweld.charts.chart import Chart
from gweld.charts.bar import Bar
from gweld.charts.pie import Pie
from gweld.charts.line import Line
from gweld.vis import Vis
| 30.105263
| 57
| 0.851399
| 89
| 572
| 5.382022
| 0.280899
| 0.263048
| 0.141962
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.104895
| 572
| 18
| 58
| 31.777778
| 0.935547
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 0
| 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
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 4
|
b5910c3e61f752a72eef40f121c2ce1aacda79d3
| 76
|
py
|
Python
|
example_snippets/multimenus_snippets/Snippets/NumPy/Pretty printing/Print $N$ elements at each end of a summary.py
|
kuanpern/jupyterlab-snippets-multimenus
|
477f51cfdbad7409eab45abe53cf774cd70f380c
|
[
"BSD-3-Clause"
] | null | null | null |
example_snippets/multimenus_snippets/Snippets/NumPy/Pretty printing/Print $N$ elements at each end of a summary.py
|
kuanpern/jupyterlab-snippets-multimenus
|
477f51cfdbad7409eab45abe53cf774cd70f380c
|
[
"BSD-3-Clause"
] | null | null | null |
example_snippets/multimenus_snippets/Snippets/NumPy/Pretty printing/Print $N$ elements at each end of a summary.py
|
kuanpern/jupyterlab-snippets-multimenus
|
477f51cfdbad7409eab45abe53cf774cd70f380c
|
[
"BSD-3-Clause"
] | 1
|
2021-02-04T04:51:48.000Z
|
2021-02-04T04:51:48.000Z
|
with printoptions(threshold=5, edgeitems=4):
print(np.random.random(10))
| 38
| 44
| 0.75
| 11
| 76
| 5.181818
| 0.909091
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.057971
| 0.092105
| 76
| 2
| 45
| 38
| 0.768116
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0
| 0
| 0
| 1
| 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
| 0
| 0
| 0
| 1
|
0
| 4
|
b5a9c66b94d0c7027220e3333efdb755dfe9e90b
| 284
|
py
|
Python
|
grb/defense/base.py
|
Stanislas0/grb
|
96fc521f57fdb06ab6a3c442fcf4a8bc97894829
|
[
"MIT"
] | null | null | null |
grb/defense/base.py
|
Stanislas0/grb
|
96fc521f57fdb06ab6a3c442fcf4a8bc97894829
|
[
"MIT"
] | null | null | null |
grb/defense/base.py
|
Stanislas0/grb
|
96fc521f57fdb06ab6a3c442fcf4a8bc97894829
|
[
"MIT"
] | null | null | null |
from abc import ABCMeta, abstractmethod
class Defense(metaclass=ABCMeta):
@abstractmethod
def defense(self, model, adj, features, **kwargs):
"""
:param model:
:param features:
:param adj:
:param kwargs:
:return:
"""
| 17.75
| 54
| 0.56338
| 26
| 284
| 6.153846
| 0.615385
| 0.2625
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.327465
| 284
| 15
| 55
| 18.933333
| 0.837696
| 0.232394
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.25
| false
| 0
| 0.25
| 0
| 0.75
| 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
| 0
| 0
| 0
| 0
| 1
| 0
|
0
| 4
|
a93f19338fdf1a1d68df0c34c709ad504c3dd257
| 382
|
py
|
Python
|
phare/quefaire/views.py
|
decaruju/phare
|
7b17806a6ed9ec1e5863fd65b39391a7a8d9b219
|
[
"MIT"
] | null | null | null |
phare/quefaire/views.py
|
decaruju/phare
|
7b17806a6ed9ec1e5863fd65b39391a7a8d9b219
|
[
"MIT"
] | null | null | null |
phare/quefaire/views.py
|
decaruju/phare
|
7b17806a6ed9ec1e5863fd65b39391a7a8d9b219
|
[
"MIT"
] | null | null | null |
from django.shortcuts import render_to_response, render
from django.template import RequestContext
from django.http import HttpResponse
from ressources.models import Ressource
# Create your views here.
def que_faire(request):
return render(request, 'que_faire.html')
def que_faire_detail(request, sujet):
if(sujet=='innondation'):
return render(request, 'innondation.html')
| 25.466667
| 55
| 0.803665
| 51
| 382
| 5.901961
| 0.54902
| 0.099668
| 0.07309
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.109948
| 382
| 14
| 56
| 27.285714
| 0.885294
| 0.060209
| 0
| 0
| 0
| 0
| 0.114846
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.222222
| false
| 0
| 0.444444
| 0.111111
| 0.888889
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 1
| 1
| 1
| 0
|
0
| 4
|
a955c6158d635760ce39f427d85c3039834e8548
| 315
|
py
|
Python
|
tests/clipping_area/model_test.py
|
tyrasd/osmaxx
|
da4454083d17b2ef8b0623cad62e39992b6bd52a
|
[
"MIT"
] | 27
|
2015-03-30T14:17:26.000Z
|
2022-02-19T17:30:44.000Z
|
tests/clipping_area/model_test.py
|
tyrasd/osmaxx
|
da4454083d17b2ef8b0623cad62e39992b6bd52a
|
[
"MIT"
] | 483
|
2015-03-09T16:58:03.000Z
|
2022-03-14T09:29:06.000Z
|
tests/clipping_area/model_test.py
|
tyrasd/osmaxx
|
da4454083d17b2ef8b0623cad62e39992b6bd52a
|
[
"MIT"
] | 6
|
2015-04-07T07:38:30.000Z
|
2020-04-01T12:45:53.000Z
|
import pytest
@pytest.mark.django_db()
def test_osmosis_polygon_file_string_property_returns_osmosis_polygon_file(persisted_valid_clipping_area):
# this actually assures we are testing the asserts in persisted_valid_clipping_area, if
# at some point that fixture should be unused at other places
pass
| 35
| 106
| 0.825397
| 47
| 315
| 5.191489
| 0.808511
| 0.114754
| 0.147541
| 0.213115
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.139683
| 315
| 8
| 107
| 39.375
| 0.900369
| 0.460317
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.25
| false
| 0.25
| 0.25
| 0
| 0.5
| 0
| 0
| 0
| 0
| null | 0
| 0
| 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
| 1
| 0
| 1
| 0
| 0
| 0
| 0
|
0
| 4
|
8d94aee4f83b63b4268b40e16d3f3525c439153d
| 97
|
py
|
Python
|
models/__init__.py
|
dduarte-odoogap/license_white_list
|
2877b27213f64a4c8884437fd9e7e720dace3706
|
[
"Adobe-Glyph"
] | null | null | null |
models/__init__.py
|
dduarte-odoogap/license_white_list
|
2877b27213f64a4c8884437fd9e7e720dace3706
|
[
"Adobe-Glyph"
] | null | null | null |
models/__init__.py
|
dduarte-odoogap/license_white_list
|
2877b27213f64a4c8884437fd9e7e720dace3706
|
[
"Adobe-Glyph"
] | null | null | null |
# Copyright 2021 OdooGAP (http://www.odoogap.com)
# @author Diogo Duarte
from . import ir_module
| 24.25
| 49
| 0.752577
| 14
| 97
| 5.142857
| 0.928571
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.047619
| 0.134021
| 97
| 3
| 50
| 32.333333
| 0.809524
| 0.701031
| 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
| 0
| 0
|
0
| 4
|
a5ce4658a4584ed69e7cf2a1e94a7d2bb3a059d2
| 26
|
py
|
Python
|
08_String/Step01/8_1_sang.py
|
StudyForCoding/BEAKJOON
|
84e1c5e463255e919ccf6b6a782978c205420dbf
|
[
"MIT"
] | null | null | null |
08_String/Step01/8_1_sang.py
|
StudyForCoding/BEAKJOON
|
84e1c5e463255e919ccf6b6a782978c205420dbf
|
[
"MIT"
] | 3
|
2020-11-04T05:38:53.000Z
|
2021-03-02T02:15:19.000Z
|
08_String/Step01/8_1_sang.py
|
StudyForCoding/BEAKJOON
|
84e1c5e463255e919ccf6b6a782978c205420dbf
|
[
"MIT"
] | null | null | null |
s = input()
print(ord(s))
| 8.666667
| 13
| 0.576923
| 5
| 26
| 3
| 0.8
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.153846
| 26
| 2
| 14
| 13
| 0.681818
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0
| 0
| 0
| 0.5
| 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
| 0
| 0
| 0
| 0
| 0
| 1
|
0
| 4
|
a5dffb2965d0d02672663a7b60b6478a1afd25e2
| 63
|
py
|
Python
|
tests/test.py
|
notfresh/md2
|
8db851e3662e87d6bb428a4f789da0e0aac02124
|
[
"MIT"
] | null | null | null |
tests/test.py
|
notfresh/md2
|
8db851e3662e87d6bb428a4f789da0e0aac02124
|
[
"MIT"
] | null | null | null |
tests/test.py
|
notfresh/md2
|
8db851e3662e87d6bb428a4f789da0e0aac02124
|
[
"MIT"
] | null | null | null |
from md_helper import md
if __name__ == '__main__':
md()
| 10.5
| 26
| 0.650794
| 9
| 63
| 3.555556
| 0.777778
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.238095
| 63
| 5
| 27
| 12.6
| 0.666667
| 0
| 0
| 0
| 0
| 0
| 0.129032
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.333333
| 0
| 0.333333
| 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
| 0
| 0
|
0
| 4
|
a5e03e43be1a255f600b41c0cd3bde08fcdb4bb7
| 98
|
py
|
Python
|
haproxy/datadog_checks/haproxy/__init__.py
|
Siecje/integrations-core
|
b2f3ea4145b25394be0b274093d1f0723e8f968d
|
[
"BSD-3-Clause"
] | 1
|
2020-08-08T02:01:01.000Z
|
2020-08-08T02:01:01.000Z
|
haproxy/datadog_checks/haproxy/__init__.py
|
Siecje/integrations-core
|
b2f3ea4145b25394be0b274093d1f0723e8f968d
|
[
"BSD-3-Clause"
] | null | null | null |
haproxy/datadog_checks/haproxy/__init__.py
|
Siecje/integrations-core
|
b2f3ea4145b25394be0b274093d1f0723e8f968d
|
[
"BSD-3-Clause"
] | 1
|
2019-03-06T14:30:52.000Z
|
2019-03-06T14:30:52.000Z
|
from . import haproxy
HAProxy = haproxy.HAProxy
__all__ = [
'__version__',
'HAProxy'
]
| 9.8
| 25
| 0.642857
| 9
| 98
| 6.111111
| 0.555556
| 0.763636
| 0.763636
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.244898
| 98
| 9
| 26
| 10.888889
| 0.743243
| 0
| 0
| 0
| 0
| 0
| 0.183673
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.166667
| 0
| 0.166667
| 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
| 0
| 0
| 0
| 0
|
0
| 4
|
570c6d9a7c3251f611254eb8281999d12001f753
| 370
|
py
|
Python
|
db/fields.py
|
hnzlmnn/dora
|
1c7375491af03d3ea8557e68b18afc6f916f65d7
|
[
"BSD-3-Clause"
] | 6
|
2020-03-10T14:57:42.000Z
|
2021-05-19T19:14:54.000Z
|
db/fields.py
|
hnzlmnn/dora
|
1c7375491af03d3ea8557e68b18afc6f916f65d7
|
[
"BSD-3-Clause"
] | null | null | null |
db/fields.py
|
hnzlmnn/dora
|
1c7375491af03d3ea8557e68b18afc6f916f65d7
|
[
"BSD-3-Clause"
] | 3
|
2020-03-08T16:02:11.000Z
|
2020-07-24T10:56:01.000Z
|
import binascii
from peewee import CharField
class BytesField(CharField):
field_type = 'char'
def __init__(self, max_length, *args, **kwargs):
super().__init__(*args, max_length=max_length * 2, **kwargs)
def db_value(self, value):
return binascii.b2a_hex(value)
def python_value(self, value):
return binascii.a2b_hex(value)
| 21.764706
| 68
| 0.681081
| 48
| 370
| 4.916667
| 0.541667
| 0.114407
| 0.118644
| 0.169492
| 0.237288
| 0
| 0
| 0
| 0
| 0
| 0
| 0.010239
| 0.208108
| 370
| 16
| 69
| 23.125
| 0.795222
| 0
| 0
| 0
| 0
| 0
| 0.010811
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.3
| false
| 0
| 0.2
| 0.2
| 0.9
| 0
| 0
| 0
| 0
| null | 0
| 0
| 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
| 4
|
572e638885682ff76f28054ce61a522c7288540a
| 96
|
py
|
Python
|
applications/events_news/apps.py
|
samay-rgb/alumni
|
f147ca04c3b9e24307321df5f26e9f7db26fefe3
|
[
"MIT"
] | 5
|
2019-10-15T14:48:39.000Z
|
2022-02-19T05:14:51.000Z
|
applications/events_news/apps.py
|
samay-rgb/alumni
|
f147ca04c3b9e24307321df5f26e9f7db26fefe3
|
[
"MIT"
] | 10
|
2019-12-14T06:08:30.000Z
|
2022-03-13T16:01:05.000Z
|
applications/events_news/apps.py
|
samay-rgb/alumni
|
f147ca04c3b9e24307321df5f26e9f7db26fefe3
|
[
"MIT"
] | 10
|
2019-10-06T13:45:25.000Z
|
2022-02-10T17:33:39.000Z
|
from django.apps import AppConfig
class EventsNewsConfig(AppConfig):
name = 'events_news'
| 16
| 34
| 0.770833
| 11
| 96
| 6.636364
| 0.909091
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.15625
| 96
| 5
| 35
| 19.2
| 0.901235
| 0
| 0
| 0
| 0
| 0
| 0.114583
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.333333
| 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
| 0
| 0
| 1
| 0
| 1
| 0
|
0
| 4
|
5743ebc74351b5f8b99d80c57ea36a68c8871573
| 180
|
py
|
Python
|
Alerts.py
|
aycabozyell/WARMON
|
faeb3e1879be43591b0d6c3137e04e3b6b9d5fe9
|
[
"MIT"
] | null | null | null |
Alerts.py
|
aycabozyell/WARMON
|
faeb3e1879be43591b0d6c3137e04e3b6b9d5fe9
|
[
"MIT"
] | null | null | null |
Alerts.py
|
aycabozyell/WARMON
|
faeb3e1879be43591b0d6c3137e04e3b6b9d5fe9
|
[
"MIT"
] | null | null | null |
class Alerts:
def _init_ (self,Alert_Id, Alert_Name, Alert_Code):
self.Alert_Id= AlertId
self.Alert_Name = Alert_Name
self.Alert_Code = Alert_Code
| 25.714286
| 55
| 0.661111
| 25
| 180
| 4.36
| 0.4
| 0.330275
| 0.201835
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.266667
| 180
| 6
| 56
| 30
| 0.825758
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.2
| false
| 0
| 0
| 0
| 0.4
| 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
| 0
| 0
| 0
| 0
|
0
| 4
|
938c3ad3fed24bedfcab1d1e49f3c1cf5eb82bb7
| 151
|
py
|
Python
|
exercícios/EX_CursoEmVideo/ex005.py
|
jose-carlos-code/CursoEmvideo-python
|
8c9b82db2c2b906f6d8f2359a680b9b3af25da43
|
[
"MIT"
] | 1
|
2021-01-11T15:10:36.000Z
|
2021-01-11T15:10:36.000Z
|
exercícios/EX_CursoEmVideo/ex005.py
|
jose-carlos-code/CursoEmvideo-python
|
8c9b82db2c2b906f6d8f2359a680b9b3af25da43
|
[
"MIT"
] | null | null | null |
exercícios/EX_CursoEmVideo/ex005.py
|
jose-carlos-code/CursoEmvideo-python
|
8c9b82db2c2b906f6d8f2359a680b9b3af25da43
|
[
"MIT"
] | null | null | null |
n = int(input('me diga um numero: '))
s = n + 1
a = n - 1
print ('o sucessor de {} e {}'. format(n, s))
print ('o antecessor de {} e {}'.format(n, a))
| 25.166667
| 46
| 0.536424
| 29
| 151
| 2.793103
| 0.586207
| 0.049383
| 0.222222
| 0.246914
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.017094
| 0.225166
| 151
| 5
| 47
| 30.2
| 0.675214
| 0
| 0
| 0
| 0
| 0
| 0.417219
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0
| 0
| 0
| 0.4
| 1
| 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
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
938c4415d5369522a7601e22e521ee80617d3db0
| 175
|
py
|
Python
|
ocp_resources/console_plugin.py
|
dshchedr/openshift-python-wrapper
|
b3f743e33e3bde4bbc24247776a77aefdbd4061d
|
[
"Apache-2.0"
] | null | null | null |
ocp_resources/console_plugin.py
|
dshchedr/openshift-python-wrapper
|
b3f743e33e3bde4bbc24247776a77aefdbd4061d
|
[
"Apache-2.0"
] | null | null | null |
ocp_resources/console_plugin.py
|
dshchedr/openshift-python-wrapper
|
b3f743e33e3bde4bbc24247776a77aefdbd4061d
|
[
"Apache-2.0"
] | null | null | null |
from ocp_resources.resource import Resource
class ConsolePlugin(Resource):
"""
ConsolePlugin object.
"""
api_group = Resource.ApiGroup.CONSOLE_OPENSHIFT_IO
| 17.5
| 54
| 0.737143
| 18
| 175
| 6.944444
| 0.777778
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.182857
| 175
| 9
| 55
| 19.444444
| 0.874126
| 0.12
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.333333
| 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
| 0
| 0
| 1
| 0
| 1
| 0
|
0
| 4
|
939ba73bd6abdd8b2e050cf3eebcc7e9298e7a61
| 1,091
|
py
|
Python
|
database/postgres/detect.py
|
Relintai/rcpp_framework
|
6416ecc5e0c88115f209cd63945a29c0e16a8e99
|
[
"MIT"
] | 1
|
2020-11-27T21:35:43.000Z
|
2020-11-27T21:35:43.000Z
|
database/postgres/detect.py
|
Relintai/rcpp_framework
|
6416ecc5e0c88115f209cd63945a29c0e16a8e99
|
[
"MIT"
] | null | null | null |
database/postgres/detect.py
|
Relintai/rcpp_framework
|
6416ecc5e0c88115f209cd63945a29c0e16a8e99
|
[
"MIT"
] | 1
|
2020-12-28T07:43:09.000Z
|
2020-12-28T07:43:09.000Z
|
import os
import platform
import sys
def is_active():
return True
def get_name():
return "pgsql"
def can_build():
if os.name == "posix" or sys.platform == "darwin":
x11_error = os.system("pkg-config --version > /dev/null")
if x11_error:
return False
libpg_error = os.system("pkg-config libpq --modversion --silence-errors > /dev/null ")
if libpg_error:
print("postgres not found!")
return False
print("postgres found!")
return True
#todo
return False
def get_opts():
from SCons.Variables import BoolVariable, EnumVariable
return [
EnumVariable("debug_symbols", "Add debugging symbols to release/release_debug builds", "yes", ("yes", "no")),
]
def get_flags():
return []
def configure(env):
env.ParseConfig("pkg-config libpq --cflags --libs")
env.Append(CPPDEFINES=["PGSQL_PRESENT"])
# Link those statically for portability
#if env["use_static_cpp"]:
#env.Append(LINKFLAGS=["-static-libgcc", "-static-libstdc++"])
| 19.482143
| 117
| 0.618698
| 130
| 1,091
| 5.084615
| 0.553846
| 0.027231
| 0.039334
| 0.048412
| 0.066566
| 0
| 0
| 0
| 0
| 0
| 0
| 0.004908
| 0.252979
| 1,091
| 55
| 118
| 19.836364
| 0.806135
| 0.117324
| 0
| 0.172414
| 0
| 0
| 0.271116
| 0.021898
| 0
| 0
| 0
| 0.018182
| 0
| 1
| 0.206897
| false
| 0
| 0.137931
| 0.103448
| 0.62069
| 0.068966
| 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
| 0
| 0
| 1
| 1
| 0
|
0
| 4
|
f52c94c594613ecb40affc00f75bbc97ce2f6373
| 5,839
|
py
|
Python
|
hiku/types.py
|
popravich/hiku
|
4ce6b46302de61fc17016ddf3af3f378b3fce119
|
[
"BSD-3-Clause"
] | null | null | null |
hiku/types.py
|
popravich/hiku
|
4ce6b46302de61fc17016ddf3af3f378b3fce119
|
[
"BSD-3-Clause"
] | null | null | null |
hiku/types.py
|
popravich/hiku
|
4ce6b46302de61fc17016ddf3af3f378b3fce119
|
[
"BSD-3-Clause"
] | 1
|
2022-01-20T17:03:23.000Z
|
2022-01-20T17:03:23.000Z
|
from abc import abstractmethod, ABCMeta
from collections import OrderedDict
from .compat import with_metaclass
class GenericMeta(type):
def __repr__(cls):
return cls.__name__
def __eq__(cls, other):
return (cls.__class__ is other.__class__
and cls.__dict__ == other.__dict__)
def __ne__(cls, other):
return not cls.__eq__(other)
def accept(cls, visitor):
raise NotImplementedError(type(cls))
class AnyMeta(GenericMeta):
def accept(cls, visitor):
return visitor.visit_any(cls)
class Any(with_metaclass(AnyMeta, object)):
pass
class BooleanMeta(GenericMeta):
def accept(cls, visitor):
return visitor.visit_boolean(cls)
class Boolean(with_metaclass(BooleanMeta, object)):
pass
class StringMeta(GenericMeta):
def accept(cls, visitor):
return visitor.visit_string(cls)
class String(with_metaclass(StringMeta, object)):
pass
class IntegerMeta(GenericMeta):
def accept(cls, visitor):
return visitor.visit_integer(cls)
class Integer(with_metaclass(IntegerMeta, object)):
pass
class FloatMeta(GenericMeta):
def accept(cls, visitor):
return visitor.visit_float(cls)
class Float(with_metaclass(FloatMeta, object)):
pass
class TypingMeta(GenericMeta):
__final__ = False
def __cls_init__(cls, *args):
raise NotImplementedError(type(cls))
def __cls_repr__(cls):
raise NotImplementedError(type(cls))
def __getitem__(cls, parameters):
if cls.__final__:
raise TypeError('Cannot substitute parameters in {!r}'.format(cls))
type_ = cls.__class__(cls.__name__, cls.__bases__, dict(cls.__dict__))
type_.__cls_init__(parameters)
type_.__final__ = True
return type_
def __repr__(self):
if self.__final__:
return self.__cls_repr__()
else:
return super(TypingMeta, self).__repr__()
class OptionalMeta(TypingMeta):
def __cls_init__(cls, type_):
cls.__type__ = type_
def __cls_repr__(self):
return '{}[{!r}]'.format(self.__name__, self.__type__)
def accept(cls, visitor):
return visitor.visit_optional(cls)
class Optional(with_metaclass(OptionalMeta, object)):
pass
class SequenceMeta(TypingMeta):
def __cls_init__(cls, item_type):
cls.__item_type__ = item_type
def __cls_repr__(self):
return '{}[{!r}]'.format(self.__name__, self.__item_type__)
def accept(cls, visitor):
return visitor.visit_sequence(cls)
class Sequence(with_metaclass(SequenceMeta, object)):
pass
class MappingMeta(TypingMeta):
def __cls_init__(cls, params):
cls.__key_type__, cls.__value_type__ = params
def __cls_repr__(self):
return '{}[{!r}, {!r}]'.format(self.__name__, self.__key_type__,
self.__value_type__)
def accept(cls, visitor):
return visitor.visit_mapping(cls)
class Mapping(with_metaclass(MappingMeta, object)):
pass
class RecordMeta(TypingMeta):
def __cls_init__(cls, field_types):
cls.__field_types__ = OrderedDict(field_types)
def __cls_repr__(self):
return '{}[{!r}]'.format(self.__name__, dict(self.__field_types__))
def accept(cls, visitor):
return visitor.visit_record(cls)
class Record(with_metaclass(RecordMeta, object)):
pass
class CallableMeta(TypingMeta):
def __cls_init__(cls, arg_types):
cls.__arg_types__ = arg_types
def __cls_repr__(self):
return '{}[{}]'.format(self.__name__,
', '.join(map(repr, self.__arg_types__)))
def accept(cls, visitor):
return visitor.visit_callable(cls)
class Callable(with_metaclass(CallableMeta, object)):
pass
class TypeRefMeta(TypingMeta):
def __cls_init__(cls, name):
cls.__type_name__ = name
def __cls_repr__(self):
return '{}[{!r}]'.format(self.__name__, self.__type_name__)
def accept(cls, visitor):
return visitor.visit_typeref(cls)
class TypeRef(with_metaclass(TypeRefMeta, object)):
pass
class AbstractTypeVisitor(with_metaclass(ABCMeta, object)):
def visit(self, obj):
return obj.accept(self)
@abstractmethod
def visit_any(self, obj):
pass
@abstractmethod
def visit_boolean(self, obj):
pass
@abstractmethod
def visit_string(self, obj):
pass
@abstractmethod
def visit_integer(self, obj):
pass
@abstractmethod
def visit_float(self, obj):
pass
@abstractmethod
def visit_typeref(self, obj):
pass
@abstractmethod
def visit_optional(self, obj):
pass
@abstractmethod
def visit_sequence(self, obj):
pass
@abstractmethod
def visit_mapping(self, obj):
pass
@abstractmethod
def visit_record(self, obj):
pass
@abstractmethod
def visit_callable(self, obj):
pass
class TypeVisitor(AbstractTypeVisitor):
def visit_any(self, obj):
pass
def visit_boolean(self, obj):
pass
def visit_string(self, obj):
pass
def visit_integer(self, obj):
pass
def visit_float(self, obj):
pass
def visit_typeref(self, obj):
pass
def visit_optional(self, obj):
self.visit(obj.__type__)
def visit_sequence(self, obj):
self.visit(obj.__item_type__)
def visit_mapping(self, obj):
self.visit(obj.__key_type__)
self.visit(obj.__value_type__)
def visit_record(self, obj):
for value_type in obj.__field_types__.values():
self.visit(value_type)
def visit_callable(self, obj):
for arg_type in obj.__arg_types__:
self.visit(arg_type)
| 20.705674
| 79
| 0.653194
| 675
| 5,839
| 5.142222
| 0.128889
| 0.053011
| 0.053875
| 0.065687
| 0.47191
| 0.351772
| 0.18669
| 0.17603
| 0.048401
| 0.038317
| 0
| 0
| 0.246275
| 5,839
| 281
| 80
| 20.779359
| 0.788684
| 0
| 0
| 0.471264
| 0
| 0
| 0.015414
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.310345
| false
| 0.16092
| 0.017241
| 0.12069
| 0.62069
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 1
| 0
|
0
| 4
|
f530538e3383fecefabfbfc99cba284ed0051169
| 231
|
py
|
Python
|
vidgear_noperm/gears/asyncio/__init__.py
|
egeakman/vidgearnoperm
|
3483b1fd813a93494dcec4f2919a23371e47277f
|
[
"Apache-2.0"
] | 4
|
2021-07-14T00:55:18.000Z
|
2022-01-30T10:26:56.000Z
|
vidgear_noperm/gears/asyncio/__init__.py
|
Antalya-ISAS/vidgear_noperm
|
3483b1fd813a93494dcec4f2919a23371e47277f
|
[
"Apache-2.0"
] | null | null | null |
vidgear_noperm/gears/asyncio/__init__.py
|
Antalya-ISAS/vidgear_noperm
|
3483b1fd813a93494dcec4f2919a23371e47277f
|
[
"Apache-2.0"
] | 1
|
2021-07-19T20:33:45.000Z
|
2021-07-19T20:33:45.000Z
|
from .webgear import WebGear
from .webgear_rtc import WebGear_RTC
from .netgear_async import NetGear_Async
__all__ = ["WebGear", "NetGear_Async", "WebGear_RTC"]
__author__ = "Ege Akman (@egeakman) <egeakmanegeakman@hotmail.com>"
| 28.875
| 67
| 0.787879
| 29
| 231
| 5.793103
| 0.482759
| 0.178571
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.108225
| 231
| 7
| 68
| 33
| 0.815534
| 0
| 0
| 0
| 0
| 0
| 0.359307
| 0.12987
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.6
| 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
| 0
| 0
| 1
| 0
| 1
| 0
|
0
| 4
|
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