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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
e6017a5092bc8f5d1e4a0cfdb930c0da3b7bd988
| 8,317
|
py
|
Python
|
MLDataClassifiers/dl_classification_color_concept_multiple_color_space.py
|
herleraja/WiCoSens
|
f31bcfd73900f76073510ec8e40e753bbcdbb404
|
[
"Apache-2.0"
] | null | null | null |
MLDataClassifiers/dl_classification_color_concept_multiple_color_space.py
|
herleraja/WiCoSens
|
f31bcfd73900f76073510ec8e40e753bbcdbb404
|
[
"Apache-2.0"
] | null | null | null |
MLDataClassifiers/dl_classification_color_concept_multiple_color_space.py
|
herleraja/WiCoSens
|
f31bcfd73900f76073510ec8e40e753bbcdbb404
|
[
"Apache-2.0"
] | null | null | null |
import dl_classification as dl_clf
import ml_utils
import numpy as np
# source_dir_path = ml_utils.get_source_dir_path()
source_dir_path_color_space_one = "./datarecording_discrete/color_concept_latest/xyz/"
source_dir_path_color_space_two = "./datarecording_discrete/color_concept_latest/hsv/"
source_dir_path_color_space_three = "./datarecording_discrete/color_concept_latest/rgb/"
config_save_load_dir_path = "./configs/color_concept_latest/multiple_color_space/"
input_shape = 18 # 18 for 3 color space, 12 for two color space
if __name__ == "__main__":
train_bottom_data_color_space_one, train_bottom_labels_raw, train_bottom_labels = ml_utils.parse_file(
source_dir_path_color_space_one + 'train_bottom.csv', start_column=4, end_column=10)
train_left_data_color_space_one, train_left_labels_raw, train_left_labels = ml_utils.parse_file(
source_dir_path_color_space_one + 'train_left.csv', start_column=7, end_column=13)
train_right_data_color_space_one, train_right_labels_raw, train_right_labels = ml_utils.parse_file(
source_dir_path_color_space_one + 'train_right.csv', start_column=7, end_column=13)
test_bottom_data_color_space_one, test_bottom_labels_raw, test_bottom_labels = ml_utils.parse_file(
source_dir_path_color_space_one + 'test_bottom.csv', start_column=4, end_column=10)
test_left_data_color_space_one, test_left_labels_raw, test_left_labels = ml_utils.parse_file(
source_dir_path_color_space_one + 'test_left.csv', start_column=7, end_column=13)
test_right_data_color_space_one, test_right_labels_raw, test_right_labels = ml_utils.parse_file(
source_dir_path_color_space_one + 'test_right.csv', start_column=7, end_column=13)
train_bottom_data_color_space_two, train_bottom_labels_raw, train_bottom_labels = ml_utils.parse_file(
source_dir_path_color_space_two + 'train_bottom.csv', start_column=4, end_column=10)
train_left_data_color_space_two, train_left_labels_raw, train_left_labels = ml_utils.parse_file(
source_dir_path_color_space_two + 'train_left.csv', start_column=7, end_column=13)
train_right_data_color_space_two, train_right_labels_raw, train_right_labels = ml_utils.parse_file(
source_dir_path_color_space_two + 'train_right.csv', start_column=7, end_column=13)
test_bottom_data_color_space_two, test_bottom_labels_raw, test_bottom_labels = ml_utils.parse_file(
source_dir_path_color_space_two + 'test_bottom.csv', start_column=4, end_column=10)
test_left_data_color_space_two, test_left_labels_raw, test_left_labels = ml_utils.parse_file(
source_dir_path_color_space_two + 'test_left.csv', start_column=7, end_column=13)
test_right_data_color_space_two, test_right_labels_raw, test_right_labels = ml_utils.parse_file(
source_dir_path_color_space_two + 'test_right.csv', start_column=7, end_column=13)
if input_shape == 18:
train_bottom_data_color_space_three, train_bottom_labels_raw, train_bottom_labels = ml_utils.parse_file(
source_dir_path_color_space_three + 'train_bottom.csv', start_column=4, end_column=10)
train_left_data_color_space_three, train_left_labels_raw, train_left_labels = ml_utils.parse_file(
source_dir_path_color_space_three + 'train_left.csv', start_column=7, end_column=13)
train_right_data_color_space_three, train_right_labels_raw, train_right_labels = ml_utils.parse_file(
source_dir_path_color_space_three + 'train_right.csv', start_column=7, end_column=13)
test_bottom_data_color_space_three, test_bottom_labels_raw, test_bottom_labels = ml_utils.parse_file(
source_dir_path_color_space_three + 'test_bottom.csv', start_column=4, end_column=10)
test_left_data_color_space_three, test_left_labels_raw, test_left_labels = ml_utils.parse_file(
source_dir_path_color_space_three + 'test_left.csv', start_column=7, end_column=13)
test_right_data_color_space_three, test_right_labels_raw, test_right_labels = ml_utils.parse_file(
source_dir_path_color_space_three + 'test_right.csv', start_column=7, end_column=13)
train_bottom_data = np.concatenate(
(train_bottom_data_color_space_one, train_bottom_data_color_space_two, train_bottom_data_color_space_three),
axis=1)
train_left_data = np.concatenate(
(train_left_data_color_space_one, train_left_data_color_space_two, train_left_data_color_space_three),
axis=1)
train_right_data = np.concatenate(
(train_right_data_color_space_one, train_right_data_color_space_two, train_right_data_color_space_three),
axis=1)
test_bottom_data = np.concatenate(
(test_bottom_data_color_space_one, test_bottom_data_color_space_two, test_bottom_data_color_space_three),
axis=1)
test_left_data = np.concatenate(
(test_left_data_color_space_one, test_left_data_color_space_two, test_left_data_color_space_three), axis=1)
test_right_data = np.concatenate(
(test_right_data_color_space_one, test_right_data_color_space_two, test_right_data_color_space_three),
axis=1)
else:
train_bottom_data = np.concatenate((train_bottom_data_color_space_one, train_bottom_data_color_space_two),
axis=1)
train_left_data = np.concatenate((train_left_data_color_space_one, train_left_data_color_space_two), axis=1)
train_right_data = np.concatenate((train_right_data_color_space_one, train_right_data_color_space_two), axis=1)
test_bottom_data = np.concatenate((test_bottom_data_color_space_one, test_bottom_data_color_space_two), axis=1)
test_left_data = np.concatenate((test_left_data_color_space_one, test_left_data_color_space_two), axis=1)
test_right_data = np.concatenate((test_right_data_color_space_one, test_right_data_color_space_two), axis=1)
# earlyStopping = keras.callbacks.EarlyStopping(monitor='val_loss', patience=10, verbose=1, mode='auto')
model_bottom = dl_clf.build_model(5, input_shape)
history_bottom = model_bottom.fit(train_bottom_data, train_bottom_labels, epochs=20,
validation_data=(test_bottom_data, test_bottom_labels), batch_size=500, verbose=2)
model_left = dl_clf.build_model(7, input_shape)
history_left = model_left.fit(train_left_data, train_left_labels, epochs=20,
validation_data=(test_left_data, test_left_labels), batch_size=500, verbose=2)
model_right = dl_clf.build_model(8, input_shape)
history_right = model_right.fit(train_right_data, train_right_labels, epochs=20,
validation_data=(test_right_data, test_right_labels), batch_size=500, verbose=2)
ml_utils.save_model(model_bottom, 'model_bottom.h5', config_save_load_dir_path)
ml_utils.save_model(model_left, 'model_left.h5', config_save_load_dir_path)
ml_utils.save_model(model_right, 'model_right.h5', config_save_load_dir_path)
test_predicted_bottom_res = model_bottom.predict(test_bottom_data, batch_size=1)
print('\n****************Classification result for Bottom************************')
ml_utils.display_result(test_bottom_labels_raw, test_predicted_bottom_res.argmax(axis=1),
'Bottom') # Print the classification result
# for result in test_predicted_bottom_res:
# ml_utils.display_confidence(result)
test_predicted_left_res = model_left.predict(test_left_data, batch_size=1)
print('\n****************Classification result for Left************************')
ml_utils.display_result(test_left_labels_raw, test_predicted_left_res.argmax(axis=1),
'Left') # Print the classification result
# for result in test_predicted_left_res:
# ml_utils.display_confidence(result)
test_predicted_right_res = model_right.predict(test_right_data, batch_size=1)
print('\n****************Classification result for Right************************')
ml_utils.display_result(test_right_labels_raw, test_predicted_right_res.argmax(axis=1),
'Right') # Print the classification result
# for result in test_predicted_right_res:
# ml_utils.display_confidence(result)
| 66.007937
| 120
| 0.765661
| 1,244
| 8,317
| 4.541801
| 0.07717
| 0.127434
| 0.118938
| 0.066903
| 0.843009
| 0.792566
| 0.737168
| 0.704248
| 0.66531
| 0.609381
| 0
| 0.015224
| 0.147048
| 8,317
| 125
| 121
| 66.536
| 0.781224
| 0.063605
| 0
| 0.063158
| 0
| 0
| 0.096077
| 0.049518
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.031579
| 0
| 0.031579
| 0.031579
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 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
| 0
| 0
| 0
| 0
| 0
|
0
| 5
|
e61d4cb64f9add1b220b438815aa8254e952f834
| 95
|
py
|
Python
|
third/emoji_demo.py
|
gottaegbert/penter
|
8cbb6be3c4bf67c7c69fa70e597bfbc3be4f0a2d
|
[
"MIT"
] | 13
|
2020-01-04T07:37:38.000Z
|
2021-08-31T05:19:58.000Z
|
third/emoji_demo.py
|
gottaegbert/penter
|
8cbb6be3c4bf67c7c69fa70e597bfbc3be4f0a2d
|
[
"MIT"
] | 3
|
2020-06-05T22:42:53.000Z
|
2020-08-24T07:18:54.000Z
|
third/emoji_demo.py
|
gottaegbert/penter
|
8cbb6be3c4bf67c7c69fa70e597bfbc3be4f0a2d
|
[
"MIT"
] | 9
|
2020-10-19T04:53:06.000Z
|
2021-08-31T05:20:01.000Z
|
from emoji import emojize
print(emojize(":thumbs_up:"))
# https://github.com/carpedm20/emoji
| 15.833333
| 36
| 0.747368
| 13
| 95
| 5.384615
| 0.846154
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.023256
| 0.094737
| 95
| 5
| 37
| 19
| 0.790698
| 0.357895
| 0
| 0
| 0
| 0
| 0.192982
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.5
| 0
| 0.5
| 0.5
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 1
|
0
| 5
|
e62c27b3fe3513eda2bf109dcdb7ea0da19b70cf
| 281
|
py
|
Python
|
Leetcode9.py
|
cherytony/test1
|
506ce4cab6f641beff817c81d7a616db29a7131d
|
[
"Apache-2.0"
] | null | null | null |
Leetcode9.py
|
cherytony/test1
|
506ce4cab6f641beff817c81d7a616db29a7131d
|
[
"Apache-2.0"
] | null | null | null |
Leetcode9.py
|
cherytony/test1
|
506ce4cab6f641beff817c81d7a616db29a7131d
|
[
"Apache-2.0"
] | null | null | null |
class Solution:
def isPalindrome(self,x):
# if x > 0 :
# r = int(str(x)[::-1])
#
# if r ==x:
# return True
# else:
# return False
#
# else:
# return False
| 18.733333
| 35
| 0.320285
| 25
| 281
| 3.6
| 0.64
| 0.222222
| 0.333333
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.016393
| 0.565836
| 281
| 15
| 36
| 18.733333
| 0.721311
| 0.441281
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | null | 0
| 0
| null | null | 0
| 1
| 0
| 0
| null | 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 5
|
050551001ea2cbc3bb46a4a0d1cf37d38ef44710
| 449
|
py
|
Python
|
snakemake/configs/ornithorhynchus_anatinus_SRP007412_single.py
|
saketkc/EE-546-project
|
fb7eacd90f6c0a2cb3061837ec5427a14f521aa5
|
[
"BSD-2-Clause"
] | 1
|
2020-11-02T07:05:09.000Z
|
2020-11-02T07:05:09.000Z
|
snakemake/configs/ornithorhynchus_anatinus_SRP007412_single.py
|
saketkc/EE-546-project
|
fb7eacd90f6c0a2cb3061837ec5427a14f521aa5
|
[
"BSD-2-Clause"
] | null | null | null |
snakemake/configs/ornithorhynchus_anatinus_SRP007412_single.py
|
saketkc/EE-546-project
|
fb7eacd90f6c0a2cb3061837ec5427a14f521aa5
|
[
"BSD-2-Clause"
] | null | null | null |
RAWDATA_DIR = '/staging/as/skchoudh/rna-seq-datasets/single/ornithorhynchus_anatinus/SRP007412'
OUT_DIR = '/staging/as/skchoudh/rna-seq-output/ornithorhynchus_anatinus/SRP007412'
CDNA_FA_GZ = '/home/cmb-panasas2/skchoudh/genomes/ornithorhynchus_anatinus/cdna/Ornithorhynchus_anatinus.OANA5.cdna.all.fa.gz'
CDNA_IDX = '/home/cmb-panasas2/skchoudh/genomes/ornithorhynchus_anatinus/cdna/Ornithorhynchus_anatinus.OANA5.cdna.all.kallisto.index'
| 74.833333
| 137
| 0.830735
| 58
| 449
| 6.241379
| 0.448276
| 0.381215
| 0.066298
| 0.110497
| 0.651934
| 0.651934
| 0.508287
| 0.508287
| 0.508287
| 0.508287
| 0
| 0.037383
| 0.046771
| 449
| 5
| 138
| 89.8
| 0.808411
| 0
| 0
| 0
| 0
| 0.5
| 0.848214
| 0.848214
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 1
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 5
|
051ead77d256fe11805dc474f5b972978b2ae452
| 82
|
py
|
Python
|
neverlose/models/base/response.py
|
neverlosecc/api-wrapper
|
9593e2539f5dfda58ae10b3f58cf7dd35d7cc7fe
|
[
"MIT"
] | 2
|
2021-03-29T17:14:17.000Z
|
2021-05-15T03:42:44.000Z
|
neverlose/models/base/response.py
|
neverlosecc/api-wrapper
|
9593e2539f5dfda58ae10b3f58cf7dd35d7cc7fe
|
[
"MIT"
] | null | null | null |
neverlose/models/base/response.py
|
neverlosecc/api-wrapper
|
9593e2539f5dfda58ae10b3f58cf7dd35d7cc7fe
|
[
"MIT"
] | null | null | null |
from pydantic import BaseModel
class BaseResponse(BaseModel):
success: bool
| 13.666667
| 30
| 0.780488
| 9
| 82
| 7.111111
| 0.888889
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.170732
| 82
| 5
| 31
| 16.4
| 0.941176
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 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
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
056c60b80c24239c4e8e076bda83bcf6add55bb3
| 146
|
py
|
Python
|
cats/admin.py
|
jiz148/django-tutorial
|
6471bfe1f4e94fd1e7da1531ae1247804deb7871
|
[
"MIT"
] | null | null | null |
cats/admin.py
|
jiz148/django-tutorial
|
6471bfe1f4e94fd1e7da1531ae1247804deb7871
|
[
"MIT"
] | null | null | null |
cats/admin.py
|
jiz148/django-tutorial
|
6471bfe1f4e94fd1e7da1531ae1247804deb7871
|
[
"MIT"
] | null | null | null |
from django.contrib import admin
from .models import Breed, Cat
# Register your models here.
admin.site.register(Breed)
admin.site.register(Cat)
| 20.857143
| 32
| 0.794521
| 22
| 146
| 5.272727
| 0.545455
| 0.155172
| 0.293103
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.116438
| 146
| 6
| 33
| 24.333333
| 0.899225
| 0.178082
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.5
| 0
| 0.5
| 0
| 1
| 0
| 0
| null | 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 5
|
e95375b4801be688246f48392ae31678a7ad67eb
| 85
|
py
|
Python
|
django_api_example/tasks/admin.py
|
amrox/django-api-example
|
6c68e43078bb5e858ddea84d44a943ec9d7808b4
|
[
"MIT"
] | 17
|
2015-03-31T20:23:08.000Z
|
2021-06-08T00:46:57.000Z
|
django_api_example/tasks/admin.py
|
amrox/django-api-example
|
6c68e43078bb5e858ddea84d44a943ec9d7808b4
|
[
"MIT"
] | null | null | null |
django_api_example/tasks/admin.py
|
amrox/django-api-example
|
6c68e43078bb5e858ddea84d44a943ec9d7808b4
|
[
"MIT"
] | 4
|
2015-05-18T14:24:52.000Z
|
2022-02-18T06:52:52.000Z
|
from models import Task
from django.contrib import admin
admin.site.register(Task)
| 14.166667
| 32
| 0.811765
| 13
| 85
| 5.307692
| 0.692308
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.129412
| 85
| 5
| 33
| 17
| 0.932432
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.666667
| 0
| 0.666667
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
e98768fa403a6351fffcd3895fcaaa6f9f3d3b5b
| 75
|
py
|
Python
|
iterate_task.py
|
Nivratti/bing_image_downloader
|
9b30d07a2e8733fb255ab6b27499870b942b97c5
|
[
"MIT"
] | null | null | null |
iterate_task.py
|
Nivratti/bing_image_downloader
|
9b30d07a2e8733fb255ab6b27499870b942b97c5
|
[
"MIT"
] | null | null | null |
iterate_task.py
|
Nivratti/bing_image_downloader
|
9b30d07a2e8733fb255ab6b27499870b942b97c5
|
[
"MIT"
] | null | null | null |
import os, sys
import shutil
from pathlib import Path
import pandas as pd
| 12.5
| 24
| 0.8
| 13
| 75
| 4.615385
| 0.769231
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.186667
| 75
| 5
| 25
| 15
| 0.983607
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
e9b230b9bb624aa2a11c31674f9c3d58de29814a
| 129
|
py
|
Python
|
truffletopia/__init__.py
|
wesleybeckner/truffletopia
|
574caf24b41126d3d71c45b49cfd44820c42fa7e
|
[
"MIT"
] | null | null | null |
truffletopia/__init__.py
|
wesleybeckner/truffletopia
|
574caf24b41126d3d71c45b49cfd44820c42fa7e
|
[
"MIT"
] | null | null | null |
truffletopia/__init__.py
|
wesleybeckner/truffletopia
|
574caf24b41126d3d71c45b49cfd44820c42fa7e
|
[
"MIT"
] | null | null | null |
from __future__ import absolute_import, division, print_function
from .version import __version__
from .truffletopia import *
| 32.25
| 65
| 0.829457
| 15
| 129
| 6.466667
| 0.6
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.131783
| 129
| 3
| 66
| 43
| 0.866071
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0.333333
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
75669275652b7c8d3e3d8a169edb423121ebe99f
| 157
|
py
|
Python
|
env/lib/python3.8/site-packages/liststyle/admin.py
|
angels101/practice-django-framework-api-
|
0a888c75126940c33bc7afc14b8d1496c586512f
|
[
"MIT"
] | null | null | null |
env/lib/python3.8/site-packages/liststyle/admin.py
|
angels101/practice-django-framework-api-
|
0a888c75126940c33bc7afc14b8d1496c586512f
|
[
"MIT"
] | null | null | null |
env/lib/python3.8/site-packages/liststyle/admin.py
|
angels101/practice-django-framework-api-
|
0a888c75126940c33bc7afc14b8d1496c586512f
|
[
"MIT"
] | null | null | null |
from django.contrib.admin.views.main import ChangeList
class ListStyleAdminMixin(object):
def get_row_css(self, obj, index):
return ''
| 22.428571
| 54
| 0.694268
| 19
| 157
| 5.631579
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.216561
| 157
| 6
| 55
| 26.166667
| 0.869919
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.25
| false
| 0
| 0.25
| 0.25
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 1
| 0
|
0
| 5
|
7580078c7f20a034097af3f07e2e70b94dbdfbb3
| 1,592
|
py
|
Python
|
implementations/general/danbooru_portrait.py
|
wonwizard/animeface
|
b022f500803278733a4bdf911feaff884fa3a5db
|
[
"MIT"
] | 2
|
2021-05-04T06:14:42.000Z
|
2022-02-28T10:55:39.000Z
|
implementations/general/danbooru_portrait.py
|
wonwizard/animeface
|
b022f500803278733a4bdf911feaff884fa3a5db
|
[
"MIT"
] | null | null | null |
implementations/general/danbooru_portrait.py
|
wonwizard/animeface
|
b022f500803278733a4bdf911feaff884fa3a5db
|
[
"MIT"
] | null | null | null |
import random
import glob
from .dataset_base import Image, ImageXDoG, make_default_transform
class DanbooruPortraitDataset(Image):
'''Danbooru Portrait Dataset
'''
def __init__(self, image_size, transform=None, num_images=None):
if transform is None:
transform = make_default_transform(image_size, 1.2)
super().__init__(transform)
if num_images is not None:
assert 0 < num_images <= len(self.images) and isinstance(num_images, int)
random.shuffle(self.images)
self.images = self.images[:num_images]
def _load(self):
image_paths = glob.glob('/usr/src/data/danbooru/portraits/portraits/*')
return image_paths
class XDoGDanbooruPortraitDataset(ImageXDoG):
'''Image + XDoG Danbooru Portrait Dataset
'''
def __init__(self, image_size, transform=None, num_images=None):
if transform is None:
transform = make_default_transform(image_size, 1.2, hflip=False)
super().__init__(transform)
if num_images is not None:
assert 0 < num_images <= len(self.images) and isinstance(num_images, int)
random.shuffle(self.images)
self.images = self.images[:num_images]
self.xdogs = [path.replace('portraits/portraits', 'portraits/xdog') for path in self.images]
def _load(self):
image_paths = glob.glob('/usr/src/data/danbooru/portraits/portraits/*')
xdog_paths = [path.replace('portraits/portraits', 'portraits/xdog') for path in image_paths]
return image_paths, xdog_paths
| 39.8
| 104
| 0.670226
| 195
| 1,592
| 5.235897
| 0.261538
| 0.088149
| 0.054848
| 0.078355
| 0.761998
| 0.761998
| 0.761998
| 0.761998
| 0.761998
| 0.662096
| 0
| 0.00487
| 0.226131
| 1,592
| 39
| 105
| 40.820513
| 0.823864
| 0.043342
| 0
| 0.62069
| 0
| 0
| 0.102258
| 0.058433
| 0
| 0
| 0
| 0
| 0.068966
| 1
| 0.137931
| false
| 0
| 0.103448
| 0
| 0.37931
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 5
|
75801221ff9e7a3132795404ef76523030d9742b
| 207
|
py
|
Python
|
vispy/util/ordereddict.py
|
MatthieuDartiailh/vispy
|
09d429be361a148b0614a192f56d4070c624072c
|
[
"BSD-3-Clause"
] | null | null | null |
vispy/util/ordereddict.py
|
MatthieuDartiailh/vispy
|
09d429be361a148b0614a192f56d4070c624072c
|
[
"BSD-3-Clause"
] | null | null | null |
vispy/util/ordereddict.py
|
MatthieuDartiailh/vispy
|
09d429be361a148b0614a192f56d4070c624072c
|
[
"BSD-3-Clause"
] | null | null | null |
# -*- coding: utf-8 -*-
from sys import version_info
if version_info[0] > 2 or version_info[1] >= 7:
from collections import OrderedDict
else:
from ..ext.py24_ordereddict import OrderedDict # noqa
| 25.875
| 58
| 0.710145
| 30
| 207
| 4.766667
| 0.666667
| 0.230769
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.04142
| 0.183575
| 207
| 7
| 59
| 29.571429
| 0.804734
| 0.125604
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.6
| 0
| 0.6
| 0
| 0
| 0
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
7598d0d7b7e570296f576ef7af7b186ea87cf570
| 91
|
py
|
Python
|
app/train.py
|
jennyluciav/aws-ml-lambda-tf
|
c28b45a408d87592639ced9976c9313faa2dc265
|
[
"MIT"
] | null | null | null |
app/train.py
|
jennyluciav/aws-ml-lambda-tf
|
c28b45a408d87592639ced9976c9313faa2dc265
|
[
"MIT"
] | null | null | null |
app/train.py
|
jennyluciav/aws-ml-lambda-tf
|
c28b45a408d87592639ced9976c9313faa2dc265
|
[
"MIT"
] | 2
|
2021-06-23T00:31:09.000Z
|
2021-06-24T23:43:05.000Z
|
from model import ModelWrapper
model_wrapper = ModelWrapper()
model_wrapper.train()
| 15.166667
| 31
| 0.769231
| 10
| 91
| 6.8
| 0.6
| 0.5
| 0.705882
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.164835
| 91
| 5
| 32
| 18.2
| 0.894737
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.333333
| 0
| 0.333333
| 0
| 1
| 0
| 0
| null | 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
|
0
| 5
|
75dc33110a02a0ef796412ef1a1bc2f67fe6b1d3
| 264
|
py
|
Python
|
python/anyascii/_data/_2d3.py
|
casept/anyascii
|
d4f426b91751254b68eaa84c6cd23099edd668e6
|
[
"ISC"
] | null | null | null |
python/anyascii/_data/_2d3.py
|
casept/anyascii
|
d4f426b91751254b68eaa84c6cd23099edd668e6
|
[
"ISC"
] | null | null | null |
python/anyascii/_data/_2d3.py
|
casept/anyascii
|
d4f426b91751254b68eaa84c6cd23099edd668e6
|
[
"ISC"
] | null | null | null |
b=' Zong Dao Ai Wei'
| 264
| 264
| 0.049242
| 5
| 264
| 2.6
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.939394
| 264
| 1
| 264
| 264
| 0.8125
| 0
| 0
| 0
| 0
| 0
| 0.981132
| 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
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 5
|
f938fcd839377220797a8b450c9e5308dd773c1a
| 17
|
py
|
Python
|
file9.py
|
karwinski/QA-and-Git
|
ec927de5dfb1de62cf46c112b45c751b64e3ccde
|
[
"MIT"
] | 1
|
2017-12-18T16:01:29.000Z
|
2017-12-18T16:01:29.000Z
|
file9.py
|
karwinski/QA-and-Git
|
ec927de5dfb1de62cf46c112b45c751b64e3ccde
|
[
"MIT"
] | null | null | null |
file9.py
|
karwinski/QA-and-Git
|
ec927de5dfb1de62cf46c112b45c751b64e3ccde
|
[
"MIT"
] | null | null | null |
print("file9");
| 5.666667
| 15
| 0.588235
| 2
| 17
| 5
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.066667
| 0.117647
| 17
| 2
| 16
| 8.5
| 0.6
| 0
| 0
| 0
| 0
| 0
| 0.3125
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0
| 0
| 0
| 1
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 1
|
0
| 5
|
f953b5021b2b6a337a4070803427b71b6970b12d
| 506
|
py
|
Python
|
arrow/commands/cmd_cannedkeys.py
|
GMOD/python-apollo3
|
c1c47e985d95c8995374f6daa5c2e52b6d94ee0d
|
[
"MIT"
] | 5
|
2017-06-27T19:41:57.000Z
|
2021-06-05T13:36:11.000Z
|
arrow/commands/cmd_cannedkeys.py
|
galaxy-genome-annotation/python-apollo
|
1257e050ee3fc0a7f7ab8a8c780aefee5c8143f8
|
[
"MIT"
] | 28
|
2017-07-24T15:10:37.000Z
|
2021-09-03T11:56:35.000Z
|
arrow/commands/cmd_cannedkeys.py
|
MoffMade/python-apollo
|
3cc61458cf5c20bd44fde656b8364417b915cfb8
|
[
"MIT"
] | 10
|
2017-05-10T19:13:44.000Z
|
2021-08-09T04:52:33.000Z
|
import click
from arrow.commands.cannedkeys.add_key import cli as add_key
from arrow.commands.cannedkeys.delete_key import cli as delete_key
from arrow.commands.cannedkeys.get_keys import cli as get_keys
from arrow.commands.cannedkeys.show_key import cli as show_key
from arrow.commands.cannedkeys.update_key import cli as update_key
@click.group()
def cli():
pass
cli.add_command(add_key)
cli.add_command(delete_key)
cli.add_command(get_keys)
cli.add_command(show_key)
cli.add_command(update_key)
| 26.631579
| 66
| 0.83004
| 87
| 506
| 4.597701
| 0.218391
| 0.1125
| 0.2125
| 0.3375
| 0.225
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.096838
| 506
| 18
| 67
| 28.111111
| 0.875274
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.071429
| true
| 0.071429
| 0.428571
| 0
| 0.5
| 0
| 0
| 0
| 0
| null | 0
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 1
| 0
| 0
| 0
|
0
| 5
|
f959b18bf8f141da5514d2eca241d1779bf440aa
| 183
|
py
|
Python
|
by-session/ta-921/j3/func1.py
|
amiraliakbari/sharif-mabani-python
|
5d14a08d165267fe71c28389ddbafe29af7078c5
|
[
"MIT"
] | 2
|
2015-04-29T20:59:35.000Z
|
2018-09-26T13:33:43.000Z
|
by-session/ta-921/j3/func1.py
|
amiraliakbari/sharif-mabani-python
|
5d14a08d165267fe71c28389ddbafe29af7078c5
|
[
"MIT"
] | null | null | null |
by-session/ta-921/j3/func1.py
|
amiraliakbari/sharif-mabani-python
|
5d14a08d165267fe71c28389ddbafe29af7078c5
|
[
"MIT"
] | null | null | null |
def print1():
print 'A'
print 'B'
def print2():
print 'a'
print 'b'
def print3():
print '1'
print '2'
print1()
print3()
print3()
print2()
| 10.166667
| 14
| 0.47541
| 22
| 183
| 3.954545
| 0.409091
| 0.137931
| 0.252874
| 0.275862
| 0.344828
| 0
| 0
| 0
| 0
| 0
| 0
| 0.077586
| 0.36612
| 183
| 17
| 15
| 10.764706
| 0.672414
| 0
| 0
| 0.153846
| 0
| 0
| 0.036145
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | null | 0
| 0
| null | null | 1
| 1
| 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
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 1
|
0
| 5
|
f966d81b1806e8b4a6364af7ea00ea9df1539d63
| 84
|
py
|
Python
|
lib_path.py
|
MarcDorval/libtclpy
|
57ae2356eb75930880cdf86afedc28b1fbf3b21c
|
[
"BSD-3-Clause"
] | null | null | null |
lib_path.py
|
MarcDorval/libtclpy
|
57ae2356eb75930880cdf86afedc28b1fbf3b21c
|
[
"BSD-3-Clause"
] | null | null | null |
lib_path.py
|
MarcDorval/libtclpy
|
57ae2356eb75930880cdf86afedc28b1fbf3b21c
|
[
"BSD-3-Clause"
] | null | null | null |
import os
import sys
print('"' + os.path.dirname(sys.executable) + '\libs"', end='')
| 28
| 63
| 0.654762
| 12
| 84
| 4.583333
| 0.75
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.107143
| 84
| 3
| 63
| 28
| 0.733333
| 0
| 0
| 0
| 0
| 0
| 0.082353
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.666667
| 0
| 0.666667
| 0.333333
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
f97128d64d845512ce1bd9e6c7216eb277c18aa8
| 304
|
py
|
Python
|
src/telliot_core/queries/__init__.py
|
QuintusTheFifth/telliot-core
|
e22bc3b98d368fa91528f4a273ef26eddfefacaf
|
[
"MIT"
] | 9
|
2021-12-15T07:03:34.000Z
|
2022-03-30T20:16:45.000Z
|
src/telliot_core/queries/__init__.py
|
QuintusTheFifth/telliot-core
|
e22bc3b98d368fa91528f4a273ef26eddfefacaf
|
[
"MIT"
] | 76
|
2021-11-11T10:06:11.000Z
|
2022-03-30T18:50:48.000Z
|
src/telliot_core/queries/__init__.py
|
QuintusTheFifth/telliot-core
|
e22bc3b98d368fa91528f4a273ef26eddfefacaf
|
[
"MIT"
] | 7
|
2021-12-17T03:39:23.000Z
|
2022-03-29T08:53:43.000Z
|
""" TODO: Remove these imports. They only remain to avoid breaking
telliot-feed-examples, until it starts importing from the api module.
"""
from telliot_core.queries.legacy_query import LegacyRequest
from telliot_core.queries.price.spot_price import SpotPrice
__all__ = ["LegacyRequest", "SpotPrice"]
| 38
| 69
| 0.802632
| 41
| 304
| 5.756098
| 0.756098
| 0.09322
| 0.127119
| 0.186441
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.115132
| 304
| 7
| 70
| 43.428571
| 0.877323
| 0.4375
| 0
| 0
| 0
| 0
| 0.134969
| 0
| 0
| 0
| 0
| 0.142857
| 0
| 1
| 0
| false
| 0
| 0.666667
| 0
| 0.666667
| 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
| 1
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
f974a663db18cecee8c23c312f965b9577d0926c
| 138
|
py
|
Python
|
nipype/workflows/fmri/spm/__init__.py
|
abelalez/nipype
|
878271bd906768f11c4cabd04e5d1895551ce8a7
|
[
"Apache-2.0"
] | 8
|
2019-05-29T09:38:30.000Z
|
2021-01-20T03:36:59.000Z
|
nipype/workflows/fmri/spm/__init__.py
|
abelalez/nipype
|
878271bd906768f11c4cabd04e5d1895551ce8a7
|
[
"Apache-2.0"
] | 12
|
2021-03-09T03:01:16.000Z
|
2022-03-11T23:59:36.000Z
|
nipype/workflows/fmri/spm/__init__.py
|
abelalez/nipype
|
878271bd906768f11c4cabd04e5d1895551ce8a7
|
[
"Apache-2.0"
] | 2
|
2017-09-23T16:22:00.000Z
|
2019-08-01T14:18:52.000Z
|
# -*- coding: utf-8 -*-
from .preprocess import (create_spm_preproc, create_vbm_preproc,
create_DARTEL_template)
| 34.5
| 64
| 0.637681
| 15
| 138
| 5.466667
| 0.8
| 0.317073
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.009804
| 0.26087
| 138
| 3
| 65
| 46
| 0.794118
| 0.152174
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.5
| 0
| 0.5
| 0
| 1
| 0
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 5
|
f978b14364d8c517a6d9cd9d38638bde9ecebe1d
| 123
|
py
|
Python
|
xmstring/strcmp.py
|
xmake-io/pxmake
|
c5ca995e1afa840d54b513e8b2f193de463a3606
|
[
"Apache-2.0"
] | 1
|
2021-08-15T21:26:10.000Z
|
2021-08-15T21:26:10.000Z
|
xmstring/strcmp.py
|
xmake-io/pxmake
|
c5ca995e1afa840d54b513e8b2f193de463a3606
|
[
"Apache-2.0"
] | null | null | null |
xmstring/strcmp.py
|
xmake-io/pxmake
|
c5ca995e1afa840d54b513e8b2f193de463a3606
|
[
"Apache-2.0"
] | null | null | null |
from xmtrace import xmtrace
@xmtrace
def xm_string_strcmp(lua, s1, s2):
return -1 if s1 < s2 else 1 if s2 < s1 else 0
| 20.5
| 49
| 0.699187
| 24
| 123
| 3.5
| 0.625
| 0.095238
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.094737
| 0.227642
| 123
| 5
| 50
| 24.6
| 0.789474
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.25
| false
| 0
| 0.25
| 0.25
| 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
| 0
| 0
| 1
| 1
| 0
|
0
| 5
|
f9a57de9c4f49f9b5d19dbffa6ae161831da7e3a
| 50
|
py
|
Python
|
python/testData/completion/asName/a.after.py
|
truthiswill/intellij-community
|
fff88cfb0dc168eea18ecb745d3e5b93f57b0b95
|
[
"Apache-2.0"
] | 2
|
2019-04-28T07:48:50.000Z
|
2020-12-11T14:18:08.000Z
|
python/testData/completion/asName/a.after.py
|
truthiswill/intellij-community
|
fff88cfb0dc168eea18ecb745d3e5b93f57b0b95
|
[
"Apache-2.0"
] | 173
|
2018-07-05T13:59:39.000Z
|
2018-08-09T01:12:03.000Z
|
python/testData/completion/asName/a.after.py
|
truthiswill/intellij-community
|
fff88cfb0dc168eea18ecb745d3e5b93f57b0b95
|
[
"Apache-2.0"
] | 2
|
2020-03-15T08:57:37.000Z
|
2020-04-07T04:48:14.000Z
|
import importSource
importSource.arguments_vector
| 16.666667
| 29
| 0.92
| 5
| 50
| 9
| 0.8
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.06
| 50
| 3
| 29
| 16.666667
| 0.957447
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
dddc930346967d49b4034f2aa9f7cbd23747df27
| 189
|
py
|
Python
|
atopa/teacher/admin.py
|
clbravo/atopa_app
|
99c17bd83b0564635c284c46df11fcbfb00fc64b
|
[
"MIT"
] | null | null | null |
atopa/teacher/admin.py
|
clbravo/atopa_app
|
99c17bd83b0564635c284c46df11fcbfb00fc64b
|
[
"MIT"
] | 10
|
2020-06-06T00:49:41.000Z
|
2021-12-22T18:13:00.000Z
|
atopa/teacher/admin.py
|
clbravo/atopa_app
|
99c17bd83b0564635c284c46df11fcbfb00fc64b
|
[
"MIT"
] | null | null | null |
# -*- coding: utf-8 -*-
from __future__ import unicode_literals
from django.contrib import admin
from . import models
# Register your models here.
admin.site.register(models.UserProfile)
| 21
| 39
| 0.772487
| 25
| 189
| 5.64
| 0.68
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.006098
| 0.132275
| 189
| 8
| 40
| 23.625
| 0.853659
| 0.253968
| 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
| 1
| 0
|
0
| 5
|
dde004d0ba6d779419d5fdf5d45b7a95ec31c29d
| 83
|
py
|
Python
|
python/settings.py
|
ucla-hci/journal
|
14a6e065ed135f7fdaec6dbd9f762a058da877f9
|
[
"MIT"
] | 1
|
2019-11-17T21:55:00.000Z
|
2019-11-17T21:55:00.000Z
|
python/settings.py
|
ucla-hci/journal
|
14a6e065ed135f7fdaec6dbd9f762a058da877f9
|
[
"MIT"
] | null | null | null |
python/settings.py
|
ucla-hci/journal
|
14a6e065ed135f7fdaec6dbd9f762a058da877f9
|
[
"MIT"
] | null | null | null |
API_USER_NAME="apikey"
API_PASSWORD="qTmPPPacTaWbnPrN-_bUSi1r2I_NH2VZIdEGaURRmwJW"
| 27.666667
| 59
| 0.891566
| 9
| 83
| 7.666667
| 0.888889
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.037037
| 0.024096
| 83
| 2
| 60
| 41.5
| 0.814815
| 0
| 0
| 0
| 0
| 0
| 0.60241
| 0.53012
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0.5
| 0
| 0
| 0
| 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
| 1
| 1
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
|
0
| 5
|
ddee08c86195f4c39728ba9a46d1f15ab2daa4da
| 42
|
py
|
Python
|
aulas Zero/print.py
|
haller218/PythonZero
|
b6dd1650d127eb2f985a316d86160cefbfd42bda
|
[
"MIT"
] | null | null | null |
aulas Zero/print.py
|
haller218/PythonZero
|
b6dd1650d127eb2f985a316d86160cefbfd42bda
|
[
"MIT"
] | null | null | null |
aulas Zero/print.py
|
haller218/PythonZero
|
b6dd1650d127eb2f985a316d86160cefbfd42bda
|
[
"MIT"
] | null | null | null |
print ("Ola")
print ("Mundo")
print ("!")
| 10.5
| 15
| 0.547619
| 5
| 42
| 4.6
| 0.6
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.142857
| 42
| 3
| 16
| 14
| 0.638889
| 0
| 0
| 0
| 0
| 0
| 0.214286
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0
| 0
| 0
| 1
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 1
|
0
| 5
|
ddfdc87c467d6bc4897bb6015baf9212cfaeb0f1
| 106
|
py
|
Python
|
trext/datamodules/__init__.py
|
sergevkim/TextTranslation
|
986ac2c7da8b681dc6ede0b8cd6f87ce8f9f3559
|
[
"MIT"
] | 1
|
2020-11-08T18:24:46.000Z
|
2020-11-08T18:24:46.000Z
|
trext/datamodules/__init__.py
|
sergevkim/TextTranslation
|
986ac2c7da8b681dc6ede0b8cd6f87ce8f9f3559
|
[
"MIT"
] | null | null | null |
trext/datamodules/__init__.py
|
sergevkim/TextTranslation
|
986ac2c7da8b681dc6ede0b8cd6f87ce8f9f3559
|
[
"MIT"
] | null | null | null |
from .de_en_datamodule import DeEnDataModule
from .de_en_buckets_datamodule import DeEnBucketsDataModule
| 26.5
| 59
| 0.896226
| 13
| 106
| 6.923077
| 0.615385
| 0.133333
| 0.177778
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.084906
| 106
| 3
| 60
| 35.333333
| 0.927835
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
348b6be9ac56470b9a3334ff7a6de7b5a9e1285f
| 162
|
py
|
Python
|
src/pram/model/__init__.py
|
momacs/pram
|
d2de43ea447d13a65d814f781ec86889754f76fe
|
[
"BSD-3-Clause"
] | 10
|
2019-01-18T19:11:54.000Z
|
2022-03-16T08:39:36.000Z
|
src/pram/model/__init__.py
|
momacs/pram
|
d2de43ea447d13a65d814f781ec86889754f76fe
|
[
"BSD-3-Clause"
] | 2
|
2019-02-19T15:10:44.000Z
|
2019-02-26T04:26:24.000Z
|
src/pram/model/__init__.py
|
momacs/pram
|
d2de43ea447d13a65d814f781ec86889754f76fe
|
[
"BSD-3-Clause"
] | 3
|
2019-02-19T15:11:08.000Z
|
2021-08-20T11:51:04.000Z
|
from .model import Model, Solver, MCSolver, ODESolver
from .epi import SEIRModelParams, SEI2RModelParams, SISModel, SIRModel, SIRSModel, SEIRModel, SEQIHRModel
| 54
| 107
| 0.814815
| 17
| 162
| 7.764706
| 0.823529
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.006993
| 0.117284
| 162
| 2
| 108
| 81
| 0.916084
| 0
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| 0
| 0
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| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
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| 1
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| 1
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| 1
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| 0
| null | 0
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| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
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| 0
| 0
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| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
34d1125590425c3436ea6fb24117cb4ce1bb0de8
| 1,959
|
py
|
Python
|
tests/cli/test_utils.py
|
fabianSorn/widgetmark
|
93adf4ac15606036b2c64a871ea8ae1eb145a2ba
|
[
"MIT"
] | null | null | null |
tests/cli/test_utils.py
|
fabianSorn/widgetmark
|
93adf4ac15606036b2c64a871ea8ae1eb145a2ba
|
[
"MIT"
] | null | null | null |
tests/cli/test_utils.py
|
fabianSorn/widgetmark
|
93adf4ac15606036b2c64a871ea8ae1eb145a2ba
|
[
"MIT"
] | null | null | null |
import widgetmark
from widgetmark.cli.cli_view import _get_bar_color, Color
# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Bar Graph printing ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
class ColorTestsUseCase(widgetmark.UseCase):
backend = widgetmark.GuiBackend.QT
goal = 50.0
minimum = 40.0
tolerance = 0.1
repeat = 1
def setup_widget(self):
return None
def operate(self):
pass
def test_color_yellow():
result = widgetmark.UseCaseResult(
use_case=ColorTestsUseCase(),
operations_per_second=43.4,
)
assert _get_bar_color(result) == Color.YELLOW
def test_color_min_yellow():
result = widgetmark.UseCaseResult(
use_case=ColorTestsUseCase(),
operations_per_second=36,
)
assert _get_bar_color(result) == Color.YELLOW
def test_color_green():
result = widgetmark.UseCaseResult(
use_case=ColorTestsUseCase(),
operations_per_second=47.4,
)
assert _get_bar_color(result) == Color.GREEN
def test_color_min_green():
result = widgetmark.UseCaseResult(
use_case=ColorTestsUseCase(),
operations_per_second=45,
)
assert _get_bar_color(result) == Color.GREEN
def test_color_bigger_than_goal():
result = widgetmark.UseCaseResult(
use_case=ColorTestsUseCase(),
operations_per_second=64.4,
)
assert _get_bar_color(result) == Color.GREEN
def test_color_red():
result = widgetmark.UseCaseResult(
use_case=ColorTestsUseCase(),
operations_per_second=21.2,
)
assert _get_bar_color(result) == Color.RED
def test_color_zero():
result = widgetmark.UseCaseResult(
use_case=ColorTestsUseCase(),
operations_per_second=0.0,
)
assert _get_bar_color(result) == Color.RED
def test_negative():
result = widgetmark.UseCaseResult(
use_case=ColorTestsUseCase(),
operations_per_second=-5.4,
)
assert _get_bar_color(result) == Color.RED
| 23.047059
| 79
| 0.665135
| 221
| 1,959
| 5.570136
| 0.262443
| 0.043867
| 0.080422
| 0.207961
| 0.760357
| 0.760357
| 0.760357
| 0.73355
| 0.73355
| 0.437855
| 0
| 0.018893
| 0.216437
| 1,959
| 84
| 80
| 23.321429
| 0.783062
| 0.039306
| 0
| 0.4
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.133333
| 1
| 0.166667
| false
| 0.016667
| 0.033333
| 0.016667
| 0.316667
| 0
| 0
| 0
| 0
| null | 0
| 0
| 1
| 0
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 5
|
551c9806114b5c6873e3e49edd4b00ce5daa117e
| 60
|
py
|
Python
|
src/graph_transpiler/webdnn/backend/webgpu/attributes/__init__.py
|
steerapi/webdnn
|
1df51cc094e5a528cfd3452c264905708eadb491
|
[
"MIT"
] | 1
|
2021-04-09T15:55:35.000Z
|
2021-04-09T15:55:35.000Z
|
src/graph_transpiler/webdnn/backend/webgpu/attributes/__init__.py
|
steerapi/webdnn
|
1df51cc094e5a528cfd3452c264905708eadb491
|
[
"MIT"
] | null | null | null |
src/graph_transpiler/webdnn/backend/webgpu/attributes/__init__.py
|
steerapi/webdnn
|
1df51cc094e5a528cfd3452c264905708eadb491
|
[
"MIT"
] | null | null | null |
from webdnn.backend.webgpu.attributes import lstm_optimized
| 30
| 59
| 0.883333
| 8
| 60
| 6.5
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.066667
| 60
| 1
| 60
| 60
| 0.928571
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
9b3f64063634694081ef26d6048b7aa5d8e76b4e
| 38
|
py
|
Python
|
Lezione 1/ciao.py
|
pietro2356/CorsoCrittografiaAFP
|
57c8de876abf8dce3e96f39b543e48a498079de4
|
[
"MIT"
] | 1
|
2022-01-13T13:22:38.000Z
|
2022-01-13T13:22:38.000Z
|
Lezione 1/ciao.py
|
pietro2356/CorsoCrittografiaAFP
|
57c8de876abf8dce3e96f39b543e48a498079de4
|
[
"MIT"
] | null | null | null |
Lezione 1/ciao.py
|
pietro2356/CorsoCrittografiaAFP
|
57c8de876abf8dce3e96f39b543e48a498079de4
|
[
"MIT"
] | null | null | null |
def ciao():
print("Hello")
ciao()
| 9.5
| 18
| 0.552632
| 5
| 38
| 4.2
| 0.8
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.210526
| 38
| 4
| 19
| 9.5
| 0.7
| 0
| 0
| 0
| 0
| 0
| 0.128205
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.333333
| true
| 0
| 0
| 0
| 0.333333
| 0.333333
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| 0
| 0
| 0
| 0
|
0
| 5
|
9b58fcca622e93bbeef7ecd5a43576355d1e06f6
| 902
|
py
|
Python
|
applications/view/admin/__init__.py
|
wangyuan02605/webcloud
|
e57a2713125b751ee8bb8da29b789e2044e789aa
|
[
"MIT"
] | 5
|
2021-12-13T14:52:08.000Z
|
2022-03-15T08:59:32.000Z
|
applications/view/admin/__init__.py
|
wangyuan02605/webcloud
|
e57a2713125b751ee8bb8da29b789e2044e789aa
|
[
"MIT"
] | null | null | null |
applications/view/admin/__init__.py
|
wangyuan02605/webcloud
|
e57a2713125b751ee8bb8da29b789e2044e789aa
|
[
"MIT"
] | 1
|
2022-01-21T04:43:58.000Z
|
2022-01-21T04:43:58.000Z
|
from flask import Flask
from applications.view.admin.admin_log import admin_log
from applications.view.admin.dict import admin_dict
from applications.view.admin.index import admin_bp
from applications.view.admin.file import admin_file
from applications.view.admin.power import admin_power
from applications.view.admin.role import admin_role
from applications.view.admin.user import admin_user
from applications.view.admin.monitor import admin_monitor_bp
from applications.view.admin.task import admin_task
def register_admin_views(app: Flask):
app.register_blueprint(admin_bp)
app.register_blueprint(admin_user)
app.register_blueprint(admin_file)
app.register_blueprint(admin_monitor_bp)
app.register_blueprint(admin_log)
app.register_blueprint(admin_power)
app.register_blueprint(admin_role)
app.register_blueprint(admin_dict)
app.register_blueprint(admin_task)
| 37.583333
| 60
| 0.834812
| 130
| 902
| 5.546154
| 0.161538
| 0.199723
| 0.249653
| 0.312067
| 0.149792
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.100887
| 902
| 23
| 61
| 39.217391
| 0.889026
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.05
| false
| 0
| 0.5
| 0
| 0.55
| 0.45
| 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
| 1
|
0
| 5
|
9b6700af21394488c2381cff198f5f35bf35e99a
| 82
|
py
|
Python
|
ws/handler/event/appliance/__init__.py
|
fabaff/automate-ws
|
a9442f287692787e3f253e1ff23758bec8f3902e
|
[
"MIT"
] | null | null | null |
ws/handler/event/appliance/__init__.py
|
fabaff/automate-ws
|
a9442f287692787e3f253e1ff23758bec8f3902e
|
[
"MIT"
] | 1
|
2021-12-21T11:34:47.000Z
|
2021-12-21T11:34:47.000Z
|
ws/handler/event/appliance/__init__.py
|
fabaff/automate-ws
|
a9442f287692787e3f253e1ff23758bec8f3902e
|
[
"MIT"
] | 1
|
2021-12-21T10:10:13.000Z
|
2021-12-21T10:10:13.000Z
|
from ws.handler.event.appliance import event, light, sound, sprinkler, thermostat
| 41
| 81
| 0.817073
| 11
| 82
| 6.090909
| 0.909091
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.097561
| 82
| 1
| 82
| 82
| 0.905405
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
9b716b17ccaf2199e470ad98f6cc402bc67c4b70
| 90
|
py
|
Python
|
modoboa/core/checks/__init__.py
|
HarshCasper/modoboa
|
a00baa0593107992f545ee3e89cd4346b9615a96
|
[
"0BSD"
] | 1,602
|
2016-12-15T14:25:34.000Z
|
2022-03-31T16:49:25.000Z
|
modoboa/core/checks/__init__.py
|
sebageek/modoboa
|
57f5d57ea60a57e8dcac970085dfc07082481fc6
|
[
"0BSD"
] | 1,290
|
2016-12-14T15:39:05.000Z
|
2022-03-31T13:49:09.000Z
|
modoboa/core/checks/__init__.py
|
sebageek/modoboa
|
57f5d57ea60a57e8dcac970085dfc07082481fc6
|
[
"0BSD"
] | 272
|
2016-12-22T11:58:18.000Z
|
2022-03-17T15:57:24.000Z
|
# Import these to force registration of checks
from . import settings_checks # NOQA:F401
| 30
| 46
| 0.788889
| 13
| 90
| 5.384615
| 0.846154
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.04
| 0.166667
| 90
| 2
| 47
| 45
| 0.893333
| 0.6
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
9b8d29dc80fd2145ebde1c69bcc20726150589e9
| 51
|
py
|
Python
|
venv/lib/python3.9/site-packages/__init__.py
|
lyushher/YBrowser
|
49ec6e5e60d645ea80d81860f77ca6b06d5e20aa
|
[
"MIT"
] | 9
|
2021-07-25T22:45:52.000Z
|
2021-11-13T03:39:05.000Z
|
venv/lib/python3.9/site-packages/__init__.py
|
lyushher/YBrowser
|
49ec6e5e60d645ea80d81860f77ca6b06d5e20aa
|
[
"MIT"
] | null | null | null |
venv/lib/python3.9/site-packages/__init__.py
|
lyushher/YBrowser
|
49ec6e5e60d645ea80d81860f77ca6b06d5e20aa
|
[
"MIT"
] | null | null | null |
from . import scraper
from .browser import Browser
| 17
| 28
| 0.803922
| 7
| 51
| 5.857143
| 0.571429
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.156863
| 51
| 2
| 29
| 25.5
| 0.953488
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
fd3721e576688b548e98250d3e7be4c3ebadbee6
| 72
|
py
|
Python
|
bibletext/models/__init__.py
|
richardbolt/django-bibletext
|
c060bb54e2a55795509f7b73301faf2df4b2d27d
|
[
"BSD-3-Clause"
] | 4
|
2015-09-09T02:22:56.000Z
|
2021-02-12T03:13:10.000Z
|
bibletext/models/__init__.py
|
richardbolt/django-bibletext
|
c060bb54e2a55795509f7b73301faf2df4b2d27d
|
[
"BSD-3-Clause"
] | null | null | null |
bibletext/models/__init__.py
|
richardbolt/django-bibletext
|
c060bb54e2a55795509f7b73301faf2df4b2d27d
|
[
"BSD-3-Clause"
] | 2
|
2016-03-05T11:25:19.000Z
|
2021-04-20T18:30:37.000Z
|
from bibles import *
from kjv import KJV
from scripture import Scripture
| 24
| 31
| 0.833333
| 11
| 72
| 5.454545
| 0.454545
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.152778
| 72
| 3
| 31
| 24
| 0.983607
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
fd5d681f700ed90ccfaa53fb97f8bd759a847060
| 426
|
py
|
Python
|
LoopStructural/datasets/__init__.py
|
vpicavet/LoopStructural
|
cde34fabc53b4d5cb0f8e22f53a574fac44dfbd6
|
[
"MIT"
] | null | null | null |
LoopStructural/datasets/__init__.py
|
vpicavet/LoopStructural
|
cde34fabc53b4d5cb0f8e22f53a574fac44dfbd6
|
[
"MIT"
] | null | null | null |
LoopStructural/datasets/__init__.py
|
vpicavet/LoopStructural
|
cde34fabc53b4d5cb0f8e22f53a574fac44dfbd6
|
[
"MIT"
] | null | null | null |
from ._base import load_claudius
from ._base import load_grose2017
from ._base import load_grose2018
from ._base import load_grose2019
from ._base import load_laurent2016
from ._base import load_noddy_single_fold
from ._base import load_intrusion
from ._base import normal_vector_headers
from ._base import strike_dip_headers
from ._base import value_headers
from ._base import load_unconformity
from ._base import load_duplex
| 35.5
| 41
| 0.861502
| 64
| 426
| 5.296875
| 0.328125
| 0.283186
| 0.495575
| 0.477876
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| 0
| 0
| 0
| 0
| 0
| 0.042216
| 0.110329
| 426
| 12
| 42
| 35.5
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| 0
| 0
|
0
| 5
|
fd5f2d186c1e64084a9639f212943b6f1f6cabe0
| 62
|
py
|
Python
|
experiments/char_rnn/pt_rnn/__init__.py
|
slyubomirsky/relay-bench-1
|
abe5a262ee7ded76748130d0fcfbc80e570311c1
|
[
"Apache-2.0"
] | 7
|
2019-10-03T22:41:18.000Z
|
2020-05-31T18:52:15.000Z
|
experiments/char_rnn/pt_rnn/__init__.py
|
slyubomirsky/relay-bench-1
|
abe5a262ee7ded76748130d0fcfbc80e570311c1
|
[
"Apache-2.0"
] | 14
|
2019-10-18T19:13:53.000Z
|
2021-09-08T01:36:37.000Z
|
experiments/char_rnn/pt_rnn/__init__.py
|
slyubomirsky/relay-bench-1
|
abe5a262ee7ded76748130d0fcfbc80e570311c1
|
[
"Apache-2.0"
] | 4
|
2019-10-03T21:34:03.000Z
|
2022-02-23T10:29:49.000Z
|
from .char_rnn_generator import RNN
from .util import samples
| 20.666667
| 35
| 0.83871
| 10
| 62
| 5
| 0.7
| 0
| 0
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| 0.129032
| 62
| 2
| 36
| 31
| 0.925926
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| 1
| 0
|
0
| 5
|
b5e025e90ae5e4b9d0af22158f36b82768e39a2d
| 124
|
py
|
Python
|
evennia/contrib/tutorials/talking_npc/__init__.py
|
davidrideout/evennia
|
879eea55acdf4fe5cdc96ba8fd0ab5ccca4ae84b
|
[
"BSD-3-Clause"
] | null | null | null |
evennia/contrib/tutorials/talking_npc/__init__.py
|
davidrideout/evennia
|
879eea55acdf4fe5cdc96ba8fd0ab5ccca4ae84b
|
[
"BSD-3-Clause"
] | null | null | null |
evennia/contrib/tutorials/talking_npc/__init__.py
|
davidrideout/evennia
|
879eea55acdf4fe5cdc96ba8fd0ab5ccca4ae84b
|
[
"BSD-3-Clause"
] | null | null | null |
"""
Talking NPC - Griatch 2011, grungies1138 2016
"""
from .talking_npc import CmdTalk, TalkingCmdSet, TalkingNPC # noqa
| 17.714286
| 67
| 0.741935
| 14
| 124
| 6.5
| 0.857143
| 0.21978
| 0
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| 0
| 0
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| 0
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| 0
| 0.115385
| 0.16129
| 124
| 6
| 68
| 20.666667
| 0.759615
| 0.41129
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| null | 0
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| 0
| 1
| 0
| 0
| 0
|
0
| 5
|
b5e69500503f975c9deb2984c54cc343c38a65d2
| 8,471
|
py
|
Python
|
parser/team23/grammar/parsetab.py
|
wendychamale/tytus
|
e5e6d9349f609360370edcfbb65b8c93b21f1bab
|
[
"MIT"
] | null | null | null |
parser/team23/grammar/parsetab.py
|
wendychamale/tytus
|
e5e6d9349f609360370edcfbb65b8c93b21f1bab
|
[
"MIT"
] | null | null | null |
parser/team23/grammar/parsetab.py
|
wendychamale/tytus
|
e5e6d9349f609360370edcfbb65b8c93b21f1bab
|
[
"MIT"
] | null | null | null |
# parsetab.py
# This file is automatically generated. Do not edit.
# pylint: disable=W,C,R
_tabversion = '3.10'
_lr_method = 'LALR'
_lr_signature = 'leftIGUALDADDESIGUALDADleftMAYORMENORMAYORIGUALMENORIGUALleftSUMARESTAleftMULTIPLICACIONDIVISIONleftPAR_ABREPAR_CIERRALLAVE_ABRELLAVE_CIERRACADENA DECIMAL DESIGUALDAD DIVISION ELSE ENTERO ID IF IGUALDAD IMPRIMIR LLAVE_ABRE LLAVE_CIERRA MAYOR MAYORIGUAL MENOR MENORIGUAL MULTIPLICACION PAR_ABRE PAR_CIERRA PUNTOCOMA RESTA SUMA WHILEinit : instruccionesinstrucciones : instrucciones instruccioninstrucciones : instruccion instruccion : imprimir_\n | if_statement\n | while_statementexpresion_ : expresion_ SUMA expresion_\n | expresion_ RESTA expresion_\n | expresion_ MULTIPLICACION expresion_\n | expresion_ DIVISION expresion_\n | expresion_ IGUALDAD expresion_\n | expresion_ DESIGUALDAD expresion_\n | expresion_ MAYOR expresion_\n | expresion_ MENOR expresion_\n | expresion_ MAYORIGUAL expresion_\n | expresion_ MENORIGUAL expresion_\n | expif_statement : IF PAR_ABRE expresion_ PAR_CIERRA statement else_statementelse_statement : ELSE statement\n | ELSE if_statement\n | while_statement : WHILE PAR_ABRE expresion_ PAR_CIERRA statementstatement : LLAVE_ABRE instrucciones LLAVE_CIERRA\n | LLAVE_ABRE LLAVE_CIERRAimprimir_ : IMPRIMIR PAR_ABRE expresion_ PAR_CIERRA PUNTOCOMAexp : primitivoprimitivo : ENTEROprimitivo : DECIMALprimitivo : CADENAprimitivo : varsvars : ID'
_lr_action_items = {'IMPRIMIR':([0,2,3,4,5,6,10,37,48,49,50,51,53,54,55,56,57,],[7,7,-3,-4,-5,-6,-2,-25,-21,7,-22,-18,7,-24,-19,-20,-23,]),'IF':([0,2,3,4,5,6,10,37,48,49,50,51,52,53,54,55,56,57,],[8,8,-3,-4,-5,-6,-2,-25,-21,8,-22,-18,8,8,-24,-19,-20,-23,]),'WHILE':([0,2,3,4,5,6,10,37,48,49,50,51,53,54,55,56,57,],[9,9,-3,-4,-5,-6,-2,-25,-21,9,-22,-18,9,-24,-19,-20,-23,]),'$end':([1,2,3,4,5,6,10,37,48,50,51,54,55,56,57,],[0,-1,-3,-4,-5,-6,-2,-25,-21,-22,-18,-24,-19,-20,-23,]),'LLAVE_CIERRA':([3,4,5,6,10,37,48,49,50,51,53,54,55,56,57,],[-3,-4,-5,-6,-2,-25,-21,54,-22,-18,57,-24,-19,-20,-23,]),'PAR_ABRE':([7,8,9,],[11,12,13,]),'ENTERO':([11,12,13,25,26,27,28,29,30,31,32,33,34,],[17,17,17,17,17,17,17,17,17,17,17,17,17,]),'DECIMAL':([11,12,13,25,26,27,28,29,30,31,32,33,34,],[18,18,18,18,18,18,18,18,18,18,18,18,18,]),'CADENA':([11,12,13,25,26,27,28,29,30,31,32,33,34,],[19,19,19,19,19,19,19,19,19,19,19,19,19,]),'ID':([11,12,13,25,26,27,28,29,30,31,32,33,34,],[21,21,21,21,21,21,21,21,21,21,21,21,21,]),'PAR_CIERRA':([14,15,16,17,18,19,20,21,22,23,38,39,40,41,42,43,44,45,46,47,],[24,-17,-26,-27,-28,-29,-30,-31,35,36,-7,-8,-9,-10,-11,-12,-13,-14,-15,-16,]),'SUMA':([14,15,16,17,18,19,20,21,22,23,38,39,40,41,42,43,44,45,46,47,],[25,-17,-26,-27,-28,-29,-30,-31,25,25,-7,-8,-9,-10,25,25,25,25,25,25,]),'RESTA':([14,15,16,17,18,19,20,21,22,23,38,39,40,41,42,43,44,45,46,47,],[26,-17,-26,-27,-28,-29,-30,-31,26,26,-7,-8,-9,-10,26,26,26,26,26,26,]),'MULTIPLICACION':([14,15,16,17,18,19,20,21,22,23,38,39,40,41,42,43,44,45,46,47,],[27,-17,-26,-27,-28,-29,-30,-31,27,27,27,27,-9,-10,27,27,27,27,27,27,]),'DIVISION':([14,15,16,17,18,19,20,21,22,23,38,39,40,41,42,43,44,45,46,47,],[28,-17,-26,-27,-28,-29,-30,-31,28,28,28,28,-9,-10,28,28,28,28,28,28,]),'IGUALDAD':([14,15,16,17,18,19,20,21,22,23,38,39,40,41,42,43,44,45,46,47,],[29,-17,-26,-27,-28,-29,-30,-31,29,29,-7,-8,-9,-10,-11,-12,-13,-14,-15,-16,]),'DESIGUALDAD':([14,15,16,17,18,19,20,21,22,23,38,39,40,41,42,43,44,45,46,47,],[30,-17,-26,-27,-28,-29,-30,-31,30,30,-7,-8,-9,-10,-11,-12,-13,-14,-15,-16,]),'MAYOR':([14,15,16,17,18,19,20,21,22,23,38,39,40,41,42,43,44,45,46,47,],[31,-17,-26,-27,-28,-29,-30,-31,31,31,-7,-8,-9,-10,31,31,-13,-14,-15,-16,]),'MENOR':([14,15,16,17,18,19,20,21,22,23,38,39,40,41,42,43,44,45,46,47,],[32,-17,-26,-27,-28,-29,-30,-31,32,32,-7,-8,-9,-10,32,32,-13,-14,-15,-16,]),'MAYORIGUAL':([14,15,16,17,18,19,20,21,22,23,38,39,40,41,42,43,44,45,46,47,],[33,-17,-26,-27,-28,-29,-30,-31,33,33,-7,-8,-9,-10,33,33,-13,-14,-15,-16,]),'MENORIGUAL':([14,15,16,17,18,19,20,21,22,23,38,39,40,41,42,43,44,45,46,47,],[34,-17,-26,-27,-28,-29,-30,-31,34,34,-7,-8,-9,-10,34,34,-13,-14,-15,-16,]),'PUNTOCOMA':([24,],[37,]),'LLAVE_ABRE':([35,36,52,],[49,49,49,]),'ELSE':([48,54,57,],[52,-24,-23,]),}
_lr_action = {}
for _k, _v in _lr_action_items.items():
for _x,_y in zip(_v[0],_v[1]):
if not _x in _lr_action: _lr_action[_x] = {}
_lr_action[_x][_k] = _y
del _lr_action_items
_lr_goto_items = {'init':([0,],[1,]),'instrucciones':([0,49,],[2,53,]),'instruccion':([0,2,49,53,],[3,10,3,10,]),'imprimir_':([0,2,49,53,],[4,4,4,4,]),'if_statement':([0,2,49,52,53,],[5,5,5,56,5,]),'while_statement':([0,2,49,53,],[6,6,6,6,]),'expresion_':([11,12,13,25,26,27,28,29,30,31,32,33,34,],[14,22,23,38,39,40,41,42,43,44,45,46,47,]),'exp':([11,12,13,25,26,27,28,29,30,31,32,33,34,],[15,15,15,15,15,15,15,15,15,15,15,15,15,]),'primitivo':([11,12,13,25,26,27,28,29,30,31,32,33,34,],[16,16,16,16,16,16,16,16,16,16,16,16,16,]),'vars':([11,12,13,25,26,27,28,29,30,31,32,33,34,],[20,20,20,20,20,20,20,20,20,20,20,20,20,]),'statement':([35,36,52,],[48,50,55,]),'else_statement':([48,],[51,]),}
_lr_goto = {}
for _k, _v in _lr_goto_items.items():
for _x, _y in zip(_v[0], _v[1]):
if not _x in _lr_goto: _lr_goto[_x] = {}
_lr_goto[_x][_k] = _y
del _lr_goto_items
_lr_productions = [
("S' -> init","S'",1,None,None,None),
('init -> instrucciones','init',1,'p_init','execute.py',125),
('instrucciones -> instrucciones instruccion','instrucciones',2,'p_instrucciones_lista','execute.py',129),
('instrucciones -> instruccion','instrucciones',1,'p_instrucciones_instruccion','execute.py',134),
('instruccion -> imprimir_','instruccion',1,'p_instruccion','execute.py',138),
('instruccion -> if_statement','instruccion',1,'p_instruccion','execute.py',139),
('instruccion -> while_statement','instruccion',1,'p_instruccion','execute.py',140),
('expresion_ -> expresion_ SUMA expresion_','expresion_',3,'p_expresion_','execute.py',144),
('expresion_ -> expresion_ RESTA expresion_','expresion_',3,'p_expresion_','execute.py',145),
('expresion_ -> expresion_ MULTIPLICACION expresion_','expresion_',3,'p_expresion_','execute.py',146),
('expresion_ -> expresion_ DIVISION expresion_','expresion_',3,'p_expresion_','execute.py',147),
('expresion_ -> expresion_ IGUALDAD expresion_','expresion_',3,'p_expresion_','execute.py',148),
('expresion_ -> expresion_ DESIGUALDAD expresion_','expresion_',3,'p_expresion_','execute.py',149),
('expresion_ -> expresion_ MAYOR expresion_','expresion_',3,'p_expresion_','execute.py',150),
('expresion_ -> expresion_ MENOR expresion_','expresion_',3,'p_expresion_','execute.py',151),
('expresion_ -> expresion_ MAYORIGUAL expresion_','expresion_',3,'p_expresion_','execute.py',152),
('expresion_ -> expresion_ MENORIGUAL expresion_','expresion_',3,'p_expresion_','execute.py',153),
('expresion_ -> exp','expresion_',1,'p_expresion_','execute.py',154),
('if_statement -> IF PAR_ABRE expresion_ PAR_CIERRA statement else_statement','if_statement',6,'p_if_instr','execute.py',170),
('else_statement -> ELSE statement','else_statement',2,'p_else_instr','execute.py',174),
('else_statement -> ELSE if_statement','else_statement',2,'p_else_instr','execute.py',175),
('else_statement -> <empty>','else_statement',0,'p_else_instr','execute.py',176),
('while_statement -> WHILE PAR_ABRE expresion_ PAR_CIERRA statement','while_statement',5,'p_while_instr','execute.py',184),
('statement -> LLAVE_ABRE instrucciones LLAVE_CIERRA','statement',3,'p_statement','execute.py',188),
('statement -> LLAVE_ABRE LLAVE_CIERRA','statement',2,'p_statement','execute.py',189),
('imprimir_ -> IMPRIMIR PAR_ABRE expresion_ PAR_CIERRA PUNTOCOMA','imprimir_',5,'p_imprimir_instr','execute.py',194),
('exp -> primitivo','exp',1,'p_exp_primitivo','execute.py',198),
('primitivo -> ENTERO','primitivo',1,'p_exp_entero','execute.py',202),
('primitivo -> DECIMAL','primitivo',1,'p_exp_decimal','execute.py',207),
('primitivo -> CADENA','primitivo',1,'p_exp_cadena','execute.py',211),
('primitivo -> vars','primitivo',1,'p_exp_variables','execute.py',215),
('vars -> ID','vars',1,'p_exp_id','execute.py',219),
]
| 136.629032
| 2,761
| 0.647739
| 1,525
| 8,471
| 3.433443
| 0.118689
| 0.053285
| 0.021772
| 0.02903
| 0.440031
| 0.406226
| 0.3856
| 0.258594
| 0.239687
| 0.204927
| 0
| 0.228727
| 0.088537
| 8,471
| 61
| 2,762
| 138.868852
| 0.449424
| 0.009916
| 0
| 0.039216
| 1
| 0.019608
| 0.477929
| 0.037938
| 0
| 0
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| 0
| 1
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| false
| 0
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| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 1
| 1
| 0
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| 1
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| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 5
|
b5eee5f9113d468d36f5b2aecd6fe752b7b17cb7
| 30
|
py
|
Python
|
python/class_calling_itself.py
|
robotlightsyou/test
|
015f13943fc402d8ce86c5f6d2f5a7d032b3340a
|
[
"MIT"
] | 2
|
2019-05-26T15:09:34.000Z
|
2021-09-12T08:01:23.000Z
|
python/class_calling_itself.py
|
robotlightsyou/test
|
015f13943fc402d8ce86c5f6d2f5a7d032b3340a
|
[
"MIT"
] | null | null | null |
python/class_calling_itself.py
|
robotlightsyou/test
|
015f13943fc402d8ce86c5f6d2f5a7d032b3340a
|
[
"MIT"
] | 1
|
2021-04-11T20:28:21.000Z
|
2021-04-11T20:28:21.000Z
|
class Test:
TEST = Test()
| 10
| 17
| 0.566667
| 4
| 30
| 4.25
| 0.5
| 0.941176
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.3
| 30
| 2
| 18
| 15
| 0.809524
| 0
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| 0
| 0
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| 1
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| false
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| 0
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| 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
| 5
|
bd17baed38f738943c0c1803e928c48e0e9aa364
| 267
|
py
|
Python
|
tests/context.py
|
Pythonimous/pyml
|
3ecb86140501bf278e46102f8873d2b0228a94f5
|
[
"BSD-3-Clause"
] | null | null | null |
tests/context.py
|
Pythonimous/pyml
|
3ecb86140501bf278e46102f8873d2b0228a94f5
|
[
"BSD-3-Clause"
] | null | null | null |
tests/context.py
|
Pythonimous/pyml
|
3ecb86140501bf278e46102f8873d2b0228a94f5
|
[
"BSD-3-Clause"
] | null | null | null |
# -*- coding: utf-8 -*-
import sys
import os
sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), '..')))
print(sys.path[0])
# TODO: разберись с https://github.com/navdeep-G/samplemod/commit/48f4c8dba40cb2fe03a74a7a4d7d979892601ddc
import pyml
| 29.666667
| 106
| 0.745318
| 38
| 267
| 5.131579
| 0.684211
| 0.092308
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.105691
| 0.078652
| 267
| 8
| 107
| 33.375
| 0.686992
| 0.47191
| 0
| 0
| 0
| 0
| 0.014493
| 0
| 0
| 0
| 0
| 0.125
| 0
| 1
| 0
| true
| 0
| 0.6
| 0
| 0.6
| 0.2
| 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
| 1
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
bd1aad8a273c362fb4fb0317d78380a2f4d87464
| 47
|
py
|
Python
|
skanalytics/reporting/exception.py
|
jimmyskull/skanalytics
|
1027bf3648b65b96a69bbf2d42e591cc9f76fe76
|
[
"MIT"
] | null | null | null |
skanalytics/reporting/exception.py
|
jimmyskull/skanalytics
|
1027bf3648b65b96a69bbf2d42e591cc9f76fe76
|
[
"MIT"
] | null | null | null |
skanalytics/reporting/exception.py
|
jimmyskull/skanalytics
|
1027bf3648b65b96a69bbf2d42e591cc9f76fe76
|
[
"MIT"
] | null | null | null |
class ReportingException(Exception):
pass
| 11.75
| 36
| 0.765957
| 4
| 47
| 9
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.170213
| 47
| 3
| 37
| 15.666667
| 0.923077
| 0
| 0
| 0
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| 0
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| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0.5
| 0
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| 1
| 0
| null | 0
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| 0
| 0
|
0
| 5
|
bd1e617956a494811e97cf195d3cd3f79fb2669d
| 25,141
|
py
|
Python
|
bts/models/regression.py
|
benlau6/hierarchy-bayesian-modeling-time-series-sensor
|
b30f405f865daf973e59a99f24281cd49baac7df
|
[
"MIT"
] | null | null | null |
bts/models/regression.py
|
benlau6/hierarchy-bayesian-modeling-time-series-sensor
|
b30f405f865daf973e59a99f24281cd49baac7df
|
[
"MIT"
] | null | null | null |
bts/models/regression.py
|
benlau6/hierarchy-bayesian-modeling-time-series-sensor
|
b30f405f865daf973e59a99f24281cd49baac7df
|
[
"MIT"
] | 1
|
2021-08-02T06:20:14.000Z
|
2021-08-02T06:20:14.000Z
|
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
import numpy as np
import statsmodels.api as sm
import pymc3 as pm
import theano.tensor as tt
import arviz as az
from scipy import stats as sts
import warnings
import abc
warnings.simplefilter(action="ignore", category=FutureWarning)
class BayesModel(metaclass=abc.ABCMeta):
def __init__(self, y, t, dt, num_samples=1000, num_burnin=2000, threshold_t=7):
self.model = pm.Model()
self.y = y
self.t = t
self.dt = dt
self.N = y.shape[0]
self.threshold_t = threshold_t
self.num_samples = num_samples
self.num_burnin = num_burnin
self.trace = []
self.ppc = []
@classmethod
def from_df(cls, df, target, num_samples=1000, num_burnin=2000, threshold_t=24):
fig, axes = plt.subplots(1, 2, figsize=(16, 4))
# check difference
sns.scatterplot(data=df, x=df.index, y=df[target], ax=axes[0])
axes[0].set_title('pre-preprocessing')
# preprocessing
#self.df = self.df.assign(week=self.df.index.isocalendar().week)
#self.df[target] = self.df.groupby(['week'])[target].transform(lambda x: x.clip(x.quantile(0.05), x.quantile(0.95)))
#self.df = self.df.drop(['week'], axis=1)
df = df.resample('h').mean().dropna()
# check difference
sns.scatterplot(data=df, x=df.index, y=df.columns[0], ax=axes[1])
axes[1].set_title('post-preprocessing')
#fig.autofmt_xdate(rotation=90)
#axes[0].set_xticks(axes[0].get_xticks()[::2])
#axes[1].set_xticks(axes[1].get_xticks()[::2])
fig.tight_layout()
y = df.values.flatten()
dt = df.index
t = cls.dt2t(dt)
return cls(y, t, dt, num_samples=num_samples, num_burnin=num_burnin, threshold_t=threshold_t)
@classmethod
def from_csv(cls, path, index, target, unique_cols, unique_vals, num_samples=1000, num_burnin=2000, threshold_t=24):
df = pd.read_csv(path, usecols=[index, *unique_cols, target])
for col, val in zip(unique_cols, unique_vals):
mask = df[col] == val
df = df[mask]
df = df.drop(unique_cols, axis=1)
df[index] = pd.to_datetime(df[index])
df = df.set_index(index)
return cls.from_df(df, target, num_samples=num_samples, num_burnin=num_burnin, threshold_t=threshold_t)
@staticmethod
def sample_data(N=100, sp_loc=0.7, mu_1=1440, mu_2=1445, beta_1=0.03, beta_2=0.1, sigma_1=0.3, sigma_2=0.6):
N = N
sp = int(N*sp_loc)
t = np.arange(0, N)
eps_1 = np.random.normal(0, sigma_1, sp)
eps_2 = np.random.normal(0, sigma_2, N-sp)
y_1 = mu_1+beta_1*t[:sp] + eps_1
y_2 = mu_2+beta_2*(t[sp:]-sp) + eps_2
y = np.concatenate((y_1, y_2))
start = pd.to_datetime('2021-06-01')
dt = start + pd.TimedeltaIndex(t, unit='hour')
_, ax = plt.subplots(figsize=(12, 6))
sns.scatterplot(y=y, x=dt, ax=ax)
plt.show()
return y, t, dt
@staticmethod
def dt2t(dt):
return ((dt - dt[0]).total_seconds().astype(int)//3600).values
def t2dt(self, t):
# t to datetime
return self.dt[0] + pd.Timedelta(hours=t)
def fit(self):
with self.model:
self.trace = pm.sample(self.num_samples, tune=self.num_burnin, return_inferencedata=True)
def _get_posterior_parm(self, arr, parm, val_type='float', stats='mean'):
N = len(arr)
if stats == 'median':
#arr = np.round(trace['switch'][samples//2:]).astype(int)
#counts = np.bincount(arr)
#switchpoint_post = np.argmax(counts)
parm_p = np.median(arr[parm][N//2:])
elif stats == 'mean':
parm_p = np.mean(arr[parm][N//2:])
if val_type == 'int':
parm_p = np.round(parm_p).astype(int)
return parm_p
def plot_trace(self):
with self.model:
pm.plot_trace(self.trace)
plt.show()
@abc.abstractmethod
def define_model(self):
return NotImplemented
@abc.abstractmethod
def plot_posterior_predictive(self):
return NotImplemented
#def plot_linear_model(self):
# with self.model:
# switchpoint_post = self._get_posterior_parm(self.trace, 'switch', val_type='int')
# mu_1_post = self._get_posterior_parm(self.trace, 'mu_1')
# mu_2_post = self._get_posterior_parm(self.trace, 'mu_2')
# beta_1_post = self._get_posterior_parm(self.trace, 'beta_1')
# beta_2_post = self._get_posterior_parm(self.trace, 'beta_2')
# sigma_1_post = self._get_posterior_parm(self.trace, 'sigma_1')
# sigma_2_post = self._get_posterior_parm(self.trace, 'sigma_2')
# sigma_sensor_post = self._get_posterior_parm(self.trace, 'sigma_sensor')
# y1_post = mu_1_post+beta_1_post*self.t[:switchpoint_post]
# y2_post = mu_2_post+beta_2_post*(self.t[switchpoint_post:]-switchpoint_post)
# y_post = np.concatenate((y1_post, y2_post))
# sns.scatterplot(data=self.y)
# plt.plot(range(switchpoint_post), y1_post, color='red')
# plt.plot(range(switchpoint_post, self.t), y2_post, color='red')
# plt.fill_between(range(switchpoint_post), y1_post-2*(sigma_1_post+sigma_sensor_post), y1_post+2*(sigma_1_post+sigma_sensor_post), alpha=.3)
# plt.fill_between(range(switchpoint_post, self.N), y2_post-2*(sigma_2_post+sigma_sensor_post), y2_post+2*(sigma_2_post+sigma_sensor_post), alpha=.3)
# plt.axvline(x=switchpoint_post, ls='--', c='blue')
# plt.title(f'RMSE: {rmse:.2f}')
# plt.show()
class BaseLineModel(BayesModel):
def define_model(self):
clipped_y = np.clip(self.y, *np.nanquantile(self.y, (0.1, 0.9)))
coeff_std = np.nanstd(np.diff(clipped_y, n=1, axis=0))
y_mean = np.nanmean(self.y)
y_std = np.nanstd(self.y)
with self.model:
# intercept
mu_ = pm.Normal("y_mu", mu=y_mean, sigma=y_std)
# coefficient
beta_ = pm.HalfNormal('y_beta', sigma=coeff_std)
# error term
sigma_ = pm.HalfNormal("sigma_", sigma=y_std*2, testval=y_std)
nu = pm.Gamma('nu', alpha=2, beta=0.1)
# likelihood
y_obs = pm.StudentT("obs", nu=nu, mu=mu_+beta_*self.t, sigma=sigma_, observed=self.y)
def plot_posterior_predictive(self):
with self.model:
self.ppc = pm.sample_posterior_predictive(self.trace, var_names=["y_mu", "y_beta", "obs"])
xs = np.tile(self.t, (self.ppc[list(self.ppc)[0]].shape[0], 1))
mu_pp = (self.ppc["y_mu"][:,None] + self.ppc["y_beta"][:,None] * xs)
mu_hpd = az.hdi(mu_pp)
obs_hpd = az.hdi(self.ppc['obs'])
_, ax = plt.subplots(figsize=(16, 8))
ax.plot(self.dt, self.y, "o", ms=4, alpha=0.4, label="Data")
ax.fill_between(self.dt, obs_hpd[:,0], obs_hpd[:,1], color='lightblue', alpha=0.8, label="Obs y 94% HPD")
ax.plot(self.dt, mu_pp.mean(0), color='darkorange', alpha=0.6, label="Mean y")
ax.fill_between(self.dt, mu_hpd[:,0], mu_hpd[:,1], color='orange', alpha=0.8, label="Mean y 94% HPD")
ax.set_xlabel("datetime")
ax.set_ylabel("y")
ax.set_title("Continous Posterior predictive checks")
ax.legend(ncol=2, fontsize=10)
plt.show()
class SwitchPointBasicModel(BayesModel):
def define_model(self):
clipped_y = np.clip(self.y, *np.nanquantile(self.y, (0.1, 0.9)))
early_coeff_std = np.nanstd(np.diff(clipped_y[:self.N//2], n=1, axis=0))
late_coeff_std = np.nanstd(np.diff(clipped_y[self.N//2:], n=1, axis=0))
early_p50 = np.nanquantile(self.y[:self.N//2], 0.5)
late_p50 = np.nanquantile(self.y[self.N//2:], 0.5)
early_std = np.nanstd(self.y[:self.N//2])
late_std = np.nanstd(self.y[self.N//2:])
sensor_mu = np.nanstd(np.clip(self.y, *np.nanquantile(self.y, (0.25, 0.75))))
sensor_std = np.nanstd(self.y)
with self.model:
# switch, weight, time multiplier with coefficient
switchpoint = pm.Uniform("switch", lower=self.threshold_t, upper=self.t[-1] - self.threshold_t, testval=self.t[-1]//2)
w = pm.math.sigmoid(2*(self.t-switchpoint))
t_ = (1-w)*self.t + w*(self.t-switchpoint)
# intercept
mu_1 = pm.Normal("mu_1", mu=early_p50, sigma=early_std)
mu_2 = pm.Normal("mu_2", mu=late_p50, sigma=late_std)
mu_ = pm.Deterministic("y_mu", (1-w)*mu_1 + w*mu_2)
# error term
#sigma_sensor = pm.HalfNormal("sigma_sensor", sigma=2*sensor_std, testval=sensor_mu)
#sigma_sensor = sensor_std
sigma_1 = pm.HalfNormal("sigma_1", sigma=early_std*2, testval=early_std)
sigma_2 = pm.HalfCauchy("sigma_2", beta=late_std*2, testval=late_std)
sigma_ = pm.Deterministic("y_sigma", (1-w)*(sigma_1) + w*(sigma_2))
nu = pm.Gamma('nu', alpha=2, beta=0.1)
# likelihood
y_obs = pm.StudentT("obs", nu=nu, mu=mu_, sigma=sigma_, observed=self.y)
def plot_posterior_predictive(self):
with self.model:
self.ppc = pm.sample_posterior_predictive(self.trace, var_names=["y_mu", "obs", "switch"])
mu_pp = (self.ppc["y_mu"])
mu_hpd = az.hdi(mu_pp)
obs_hpd = az.hdi(self.ppc['obs'])
switchpoint_pp = self._get_posterior_parm(self.ppc, 'switch', val_type='int')
sp_hpd = az.hdi(self.ppc['switch'])
_, ax = plt.subplots(figsize=(16, 8))
ax.plot(self.dt, self.y, "o", ms=4, alpha=0.4, label="Data")
ax.fill_between(self.dt, obs_hpd[:,0], obs_hpd[:,1], color='lightblue', alpha=0.8, label="Obs y 94% HPD")
ax.plot(self.dt, mu_pp.mean(0), color='darkorange', alpha=0.6, label="Mean y")
ax.fill_between(self.dt, mu_hpd[:,0], mu_hpd[:,1], color='orange', alpha=0.8, label="Mean y 94% HPD")
ax.axvline(x=self.t2dt(switchpoint_pp), ls='--', c='black', label='switchpoint')
ax.axvline(x=self.t2dt(sp_hpd[0]), ls='--', c='grey', label='switchpoint 94% HPD')
ax.axvline(x=self.t2dt(sp_hpd[1]), ls='--', c='grey')
ax.set_xlabel("datetime")
ax.set_ylabel("y")
ax.set_title("Continous Posterior predictive checks")
ax.legend(ncol=2, fontsize=10)
plt.show()
class SwitchPointModel(BayesModel):
def define_model(self):
clipped_y = np.clip(self.y, *np.nanquantile(self.y, (0.1, 0.9)))
early_coeff_std = np.nanstd(np.diff(clipped_y[:self.N//2], n=1, axis=0))
late_coeff_std = np.nanstd(np.diff(clipped_y[self.N//2:], n=1, axis=0))
early_p10 = np.nanquantile(self.y[:self.N//2], 0.1)
late_p10 = np.nanquantile(self.y[self.N//2:], 0.1)
early_std = np.nanstd(self.y[:self.N//2])
late_std = np.nanstd(self.y[self.N//2:])
sensor_mu = np.nanstd(np.clip(self.y, *np.nanquantile(self.y, (0.25, 0.75))))
sensor_std = np.nanstd(self.y)
with self.model:
# switch, weight, time multiplier with coefficient
switchpoint = pm.Uniform("switch", lower=self.threshold_t, upper=self.t[-1] - self.threshold_t, testval=self.t[-1]//2)
w = pm.math.sigmoid(2*(self.t-switchpoint))
t_ = (1-w)*self.t + w*(self.t-switchpoint)
# intercept
mu_1 = pm.Normal("mu_1", mu=early_p10, sigma=early_std)
mu_2 = pm.Normal("mu_2", mu=late_p10, sigma=late_std)
mu_ = pm.Deterministic("y_mu", (1-w)*mu_1 + w*mu_2)
# coefficient
beta_1 = pm.HalfNormal('beta_1', sigma=early_coeff_std)
beta_2 = pm.HalfCauchy('beta_2', beta=late_coeff_std)
beta_ = pm.Deterministic("y_beta", (1-w)*beta_1 + w*beta_2)
# error term
sigma_sensor = pm.HalfNormal("sigma_sensor", sigma=2*sensor_std, testval=sensor_mu)
sigma_1 = pm.HalfNormal("sigma_1", sigma=early_std*2, testval=early_std)
sigma_2 = pm.HalfCauchy("sigma_2", beta=late_std*2, testval=late_std)
sigma_ = pm.Deterministic("y_sigma", (1-w)*(sigma_1+sigma_sensor) + w*(sigma_2+sigma_sensor))
nu = pm.Gamma('nu', alpha=2, beta=0.1)
# likelihood
y_obs = pm.StudentT("obs", nu=nu, mu=mu_+beta_*t_, sigma=sigma_, observed=self.y)
def plot_posterior_predictive(self):
with self.model:
self.ppc = pm.sample_posterior_predictive(self.trace, var_names=["y_mu", "y_beta", "obs", "switch"])
xs = np.tile(self.t, (self.ppc[list(self.ppc)[0]].shape[0], 1))
xs_mask = xs - self.ppc['switch'][:,None] > 0
for x, mask, switchpoint in zip(xs, xs_mask, self.ppc['switch']):
x[mask] = x[mask] - switchpoint
mu_pp = (self.ppc["y_mu"] + self.ppc["y_beta"] * xs)
mu_hpd = az.hdi(mu_pp)
obs_hpd = az.hdi(self.ppc['obs'])
switchpoint_pp = self._get_posterior_parm(self.ppc, 'switch', val_type='int')
sp_hpd = az.hdi(self.ppc['switch'])
_, ax = plt.subplots(figsize=(16, 8))
ax.plot(self.dt, self.y, "o", ms=4, alpha=0.4, label="Data")
ax.fill_between(self.dt, obs_hpd[:,0], obs_hpd[:,1], color='lightblue', alpha=0.8, label="Obs y 94% HPD")
ax.plot(self.dt, mu_pp.mean(0), color='darkorange', alpha=0.6, label="Mean y")
ax.fill_between(self.dt, mu_hpd[:,0], mu_hpd[:,1], color='orange', alpha=0.8, label="Mean y 94% HPD")
ax.axvline(x=self.t2dt(switchpoint_pp), ls='--', c='black', label='switchpoint')
ax.axvline(x=self.t2dt(sp_hpd[0]), ls='--', c='grey', label='switchpoint 94% HPD')
ax.axvline(x=self.t2dt(sp_hpd[1]), ls='--', c='grey')
ax.set_xlabel("datetime")
ax.set_ylabel("y")
ax.set_title("Continous Posterior predictive checks")
ax.legend(ncol=2, fontsize=10)
plt.show()
class SwitchPointNonCenteredModel(BayesModel):
def define_model(self):
clipped_y = np.clip(self.y, *np.nanquantile(self.y, (0.1, 0.9)))
early_coeff_std = np.nanstd(np.diff(clipped_y[:self.N//2], n=1, axis=0))
late_coeff_std = np.nanstd(np.diff(clipped_y[self.N//2:], n=1, axis=0))
early_p10 = np.nanquantile(self.y[:self.N//2], 0.1)
late_p10 = np.nanquantile(self.y[self.N//2:], 0.1)
early_std = np.nanstd(self.y[:self.N//2])
late_std = np.nanstd(self.y[self.N//2:])
sensor_mu = np.nanstd(np.clip(self.y, *np.nanquantile(self.y, (0.25, 0.75))))
sensor_std = np.nanstd(self.y)
with self.model:
# switch, weight, time multiplier with coefficient
switchpoint = pm.Uniform("switch", lower=self.threshold_t, upper=self.t[-1] - self.threshold_t, testval=self.t[-1]//2)
w = pm.math.sigmoid(2*(self.t-switchpoint))
t_ = (1-w)*self.t + w*(self.t-switchpoint)
# intercept
mu_1 = pm.Normal("mu_1", mu=early_p10, sigma=early_std)
mu_2 = pm.Normal("mu_2", mu=late_p10, sigma=late_std)
mu_ = pm.Deterministic("y_mu", (1-w)*mu_1 + w*mu_2)
# coefficient
beta_1 = pm.HalfNormal('beta_1', sigma=early_coeff_std)
beta_2 = pm.HalfCauchy('beta_2', beta=late_coeff_std)
beta_ = pm.Deterministic("y_beta", (1-w)*beta_1 + w*beta_2)
# error term
sigma_sensor = pm.HalfNormal("sigma_sensor", sigma=2*sensor_std, testval=sensor_mu)
sigma_1 = pm.HalfNormal("sigma_1", sigma=early_std*2, testval=early_std)
sigma_2 = pm.HalfCauchy("sigma_2", beta=late_std*2, testval=late_std)
sigma_ = pm.Deterministic("y_sigma", (1-w)*sigma_1+sigma_sensor + w*sigma_2+sigma_sensor)
nu = pm.Gamma('nu', alpha=2, beta=0.1)
# likelihood
y_obs = pm.StudentT("obs", nu=nu, mu=mu_+beta_*t_, sigma=sigma_, observed=self.y)
def plot_posterior_predictive(self):
with self.model:
self.ppc = pm.sample_posterior_predictive(self.trace, var_names=["y_mu", "y_beta", "obs", "switch"])
xs = np.tile(self.t, (self.ppc[list(self.ppc)[0]].shape[0], 1))
xs_mask = xs - self.ppc['switch'][:,None] > 0
for x, mask, switchpoint in zip(xs, xs_mask, self.ppc['switch']):
x[mask] = x[mask] - switchpoint
mu_pp = (self.ppc["y_mu"] + self.ppc["y_beta"] * xs)
mu_hpd = az.hdi(mu_pp)
obs_hpd = az.hdi(self.ppc['obs'])
switchpoint_pp = self._get_posterior_parm(self.ppc, 'switch', val_type='int')
sp_hpd = az.hdi(self.ppc['switch'])
_, ax = plt.subplots(figsize=(16, 8))
ax.plot(self.dt, self.y, "o", ms=4, alpha=0.4, label="Data")
ax.fill_between(self.dt, obs_hpd[:,0], obs_hpd[:,1], color='lightblue', alpha=0.8, label="Obs y 94% HPD")
ax.plot(self.dt, mu_pp.mean(0), color='darkorange', alpha=0.6, label="Mean y")
ax.fill_between(self.dt, mu_hpd[:,0], mu_hpd[:,1], color='orange', alpha=0.8, label="Mean y 94% HPD")
ax.axvline(x=self.t2dt(switchpoint_pp), ls='--', c='black', label='switchpoint')
ax.axvline(x=self.t2dt(sp_hpd[0]), ls='--', c='grey', label='switchpoint 94% HPD')
ax.axvline(x=self.t2dt(sp_hpd[1]), ls='--', c='grey')
ax.set_xlabel("datetime")
ax.set_ylabel("y")
ax.set_title("Continous Posterior predictive checks")
ax.legend(ncol=2, fontsize=10)
plt.show()
class SwitchPointDiscreteModel(BayesModel):
def define_model(self):
clipped_y = np.clip(self.y, *np.nanquantile(self.y, (0.1, 0.9)))
early_coeff_std = np.nanstd(np.diff(clipped_y[:self.N//2], n=1, axis=0))
late_coeff_std = np.nanstd(np.diff(clipped_y[self.N//2:], n=1, axis=0))
early_p10 = np.nanquantile(self.y[:self.N//2], 0.1)
late_p10 = np.nanquantile(self.y[self.N//2:], 0.1)
early_std = np.nanstd(self.y[:self.N//2])
late_std = np.nanstd(self.y[self.N//2:])
sensor_mu = np.nanstd(np.clip(self.y, *np.nanquantile(self.y, (0.25, 0.75))))
sensor_std = np.nanstd(self.y)
with self.model:
# switch, weight, time multiplier with coefficient
switchpoint = pm.DiscreteUniform("switch", lower=self.threshold_t, upper=self.t[-1] - self.threshold_t, testval=self.t[-1]//2)
t_ = pm.math.switch(self.t<switchpoint, self.t, self.t-switchpoint)
# to be examine, for multiple change point
#w1 = pm.math.sigmoid(2*(t-sp1))
#w2 = pm.math.sigmoid(2*(t-sp2))
#t_ = (1-w1)*t + w1*((1-w2)*(t-sp1) + w2*(t-sp2))
# intercept
mu_1 = pm.Normal("mu_1", mu=early_p10, sigma=early_std)
mu_2 = pm.Normal("mu_2", mu=late_p10, sigma=late_std)
mu_ = pm.Deterministic("y_mu", pm.math.switch(self.t<switchpoint, mu_1, mu_2))
# coefficient
beta_1 = pm.HalfNormal('beta_1', sigma=early_coeff_std)
beta_2 = pm.HalfCauchy('beta_2', beta=late_coeff_std)
beta_ = pm.Deterministic("y_beta", pm.math.switch(self.t<switchpoint, beta_1, beta_2))
# error term
sigma_sensor = pm.HalfNormal("sigma_sensor", sigma=2*sensor_std, testval=sensor_mu)
sigma_1 = pm.HalfNormal("sigma_1", sigma=early_std*2, testval=early_std)
sigma_2 = pm.HalfCauchy("sigma_2", beta=late_std*2, testval=late_std)
sigma_ = pm.math.switch(self.t<switchpoint, sigma_1+sigma_sensor, sigma_2+sigma_sensor)
nu = pm.Gamma('nu', alpha=2, beta=0.1)
# likelihood
y_obs = pm.StudentT("obs", nu=nu, mu=mu_+beta_*t_, sigma=sigma_, observed=self.y)
def plot_posterior_predictive(self):
with self.model:
self.ppc = pm.sample_posterior_predictive(self.trace, var_names=["y_mu", "y_beta", "obs", "switch"])
xs = np.tile(self.t, (self.ppc[list(self.ppc)[0]].shape[0], 1))
xs_mask = xs - self.ppc['switch'][:,None] > 0
for x, mask, switchpoint in zip(xs, xs_mask, self.ppc['switch']):
x[mask] = x[mask] - switchpoint
mu_pp = (self.ppc["y_mu"] + self.ppc["y_beta"] * xs)
mu_hpd = az.hdi(mu_pp)
obs_hpd = az.hdi(self.ppc['obs'])
switchpoint_pp = self._get_posterior_parm(self.ppc, 'switch', val_type='int')
sp_hpd = az.hdi(self.ppc['switch'])
_, ax = plt.subplots(figsize=(16, 8))
ax.plot(self.dt, self.y, "o", ms=4, alpha=0.4, label="Data")
ax.fill_between(self.dt, obs_hpd[:,0], obs_hpd[:,1], color='lightblue', alpha=0.8, label="Obs y 94% HPD")
ax.plot(self.dt, mu_pp.mean(0), color='darkorange', alpha=0.6, label="Mean y")
ax.fill_between(self.dt, mu_hpd[:,0], mu_hpd[:,1], color='orange', alpha=0.8, label="Mean y 94% HPD")
ax.axvline(x=self.t2dt(switchpoint_pp), ls='--', c='black', label='switchpoint')
ax.axvline(x=self.t2dt(sp_hpd[0]), ls='--', c='grey', label='switchpoint 94% HPD')
ax.axvline(x=self.t2dt(sp_hpd[1]), ls='--', c='grey')
ax.set_xlabel("datetime")
ax.set_ylabel("y")
ax.set_title("Continous Posterior predictive checks")
ax.legend(ncol=2, fontsize=10)
plt.show()
class GaussianProcessModel(BayesModel):
def define_model(self):
clipped_y = np.clip(self.y, *np.nanquantile(self.y, (0.1, 0.9)))
early_coeff_std = np.nanstd(np.diff(clipped_y[:self.N//2], n=1, axis=0))
late_coeff_std = np.nanstd(np.diff(clipped_y[self.N//2:], n=1, axis=0))
early_p10 = np.nanquantile(self.y[:self.N//2], 0.1)
late_p10 = np.nanquantile(self.y[self.N//2:], 0.1)
early_std = np.nanstd(self.y[:self.N//2])
late_std = np.nanstd(self.y[self.N//2:])
sensor_mu = np.nanstd(np.clip(self.y, *np.nanquantile(self.y, (0.25, 0.75))))
sensor_std = np.nanstd(self.y)
with self.model:
## intercept
#sigma_ = pm.HalfNormal("sigma_", sigma=early_std*2, testval=early_std)
#mu_drift = pm.Normal('mu_drift', mu=early_p10, sigma=early_std)
#mu_ = pm.GaussianRandomWalk('mu_', mu=mu_drift, sd=sigma_, shape=self.y.shape[0])
#
## error term
#
#
#nu = pm.Gamma('nu', alpha=2, beta=0.1)
## likelihood
#y_obs = pm.StudentT("obs", nu=nu, mu=mu_, sigma=sigma_sensor, observed=self.y)
sigma_sensor = pm.HalfNormal("sigma_sensor", sigma=2*sensor_std, testval=sensor_mu)
sigma_ = pm.HalfCauchy('sigma_', beta=self.y.std())
mu_drift = pm.Normal('mu_drift', mu=self.y.mean(), sigma=self.y.std())
mu_ = pm.GaussianRandomWalk('y_mu', mu=mu_drift, sd=sigma_, shape=self.y.size)
nu = pm.Gamma('nu', alpha=2, beta=0.1)
y_obs = pm.StudentT('obs', mu=mu_, sigma=sigma_sensor, nu=nu, observed=self.y)
def plot_posterior_predictive(self):
with self.model:
self.ppc = pm.sample_posterior_predictive(self.trace, var_names=["y_mu", "obs"])
mu_pp = self.ppc["y_mu"]
mu_hpd = az.hdi(mu_pp)
obs_hpd = az.hdi(self.ppc['obs'])
_, ax = plt.subplots(figsize=(16, 8))
ax.plot(self.dt, self.y, "o", ms=4, alpha=0.4, label="Data")
ax.fill_between(self.dt, obs_hpd[:,0], obs_hpd[:,1], color='lightblue', alpha=0.8, label="Obs y 94% HPD")
ax.plot(self.dt, mu_pp.mean(0), color='darkorange', alpha=0.6, label="Mean y")
ax.fill_between(self.dt, mu_hpd[:,0], mu_hpd[:,1], color='orange', alpha=0.8, label="Mean y 94% HPD")
ax.set_xlabel("datetime")
ax.set_ylabel("y")
ax.set_title("Continous Posterior predictive checks")
ax.legend(ncol=2, fontsize=10)
plt.show()
| 47.796578
| 160
| 0.571338
| 3,720
| 25,141
| 3.678763
| 0.077151
| 0.025575
| 0.013153
| 0.015345
| 0.787139
| 0.763098
| 0.74958
| 0.742273
| 0.71414
| 0.694556
| 0
| 0.035602
| 0.267094
| 25,141
| 526
| 161
| 47.796578
| 0.707099
| 0.117975
| 0
| 0.681818
| 0
| 0
| 0.067653
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.065341
| false
| 0
| 0.03125
| 0.011364
| 0.139205
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 5
|
bd2a7d45db7d5b2e8ab5865988a10638d3564d86
| 1,404
|
py
|
Python
|
restrain_jit/becython/stack_vm_instructions.py
|
thautwarm/restrain-jit
|
f76b3e9ae8a34d2eef87a42cc87197153f14634c
|
[
"MIT"
] | 116
|
2019-09-18T15:43:09.000Z
|
2022-02-18T15:28:08.000Z
|
restrain_jit/becython/stack_vm_instructions.py
|
thautwarm/restrain-jit
|
f76b3e9ae8a34d2eef87a42cc87197153f14634c
|
[
"MIT"
] | 6
|
2019-09-18T16:12:49.000Z
|
2021-02-03T13:01:42.000Z
|
restrain_jit/becython/stack_vm_instructions.py
|
thautwarm/restrain-jit
|
f76b3e9ae8a34d2eef87a42cc87197153f14634c
|
[
"MIT"
] | 8
|
2019-09-19T07:15:05.000Z
|
2022-01-19T19:40:10.000Z
|
from enum import Enum, auto as _auto
import abc
import typing as t
from dataclasses import dataclass
from restrain_jit.becython.representations import *
class Instr:
pass
@dataclass(frozen=True, order=True)
class A:
lhs:t.Optional[str]
rhs:Instr
pass
@dataclass(frozen=True, order=True)
class SetLineno(Instr):
lineno:int
pass
@dataclass(frozen=True, order=True)
class App(Instr):
f:Repr
args:t.List[Repr]
pass
@dataclass(frozen=True, order=True)
class Ass(Instr):
reg:Reg
val:Repr
pass
@dataclass(frozen=True, order=True)
class Load(Instr):
reg:Reg
pass
@dataclass(frozen=True, order=True)
class Store(Instr):
reg:Reg
val:Repr
pass
@dataclass(frozen=True, order=True)
class JmpIf(Instr):
label:object
cond:Repr
pass
@dataclass(frozen=True, order=True)
class JmpIfPush(Instr):
label:object
cond:Repr
leave:Repr
pass
@dataclass(frozen=True, order=True)
class Jmp(Instr):
label:object
pass
@dataclass(frozen=True, order=True)
class Label(Instr):
label:object
pass
@dataclass(frozen=True, order=True)
class Peek(Instr):
offset:int
pass
@dataclass(frozen=True, order=True)
class Return(Instr):
val:Repr
pass
@dataclass(frozen=True, order=True)
class Push(Instr):
val:Repr
pass
@dataclass(frozen=True, order=True)
class Pop(Instr):
pass
| 13.764706
| 51
| 0.685897
| 195
| 1,404
| 4.928205
| 0.25641
| 0.189386
| 0.276795
| 0.335068
| 0.709677
| 0.663892
| 0.663892
| 0.62539
| 0.326743
| 0.326743
| 0
| 0
| 0.203704
| 1,404
| 101
| 52
| 13.90099
| 0.859571
| 0
| 0
| 0.608696
| 0
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| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0.217391
| 0.072464
| 0
| 0.57971
| 0
| 0
| 0
| 0
| null | 0
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| 0
| 1
| 0
|
0
| 5
|
bd2d42a708e8e77cb927260a1b2aad36ae2e30fb
| 157
|
py
|
Python
|
src/yeelight_atmosphere/exception.py
|
NikSavilov/yeelight-atmosphere
|
8860c2869380be50a6305b5b2aa77ed3636145d3
|
[
"MIT"
] | null | null | null |
src/yeelight_atmosphere/exception.py
|
NikSavilov/yeelight-atmosphere
|
8860c2869380be50a6305b5b2aa77ed3636145d3
|
[
"MIT"
] | 7
|
2021-11-13T13:07:21.000Z
|
2021-11-19T16:30:37.000Z
|
src/yeelight_atmosphere/exception.py
|
NikSavilov/yeelight-atmosphere
|
8860c2869380be50a6305b5b2aa77ed3636145d3
|
[
"MIT"
] | null | null | null |
"""
Exceptions module.
"""
from yeelight import BulbException
class BulbConnectionLostException(BulbException):
""" Raises when connection is lost """
| 17.444444
| 49
| 0.751592
| 14
| 157
| 8.428571
| 0.928571
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.146497
| 157
| 8
| 50
| 19.625
| 0.880597
| 0.318471
| 0
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| 0
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| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.5
| 0
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| 1
| 0
| 0
| null | 0
| 0
| 0
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| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
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| 0
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| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
1f9eb83ee3e0121409cacbc36d536559eb3d4a5c
| 124
|
py
|
Python
|
scripts/tnaCompile.py
|
j-vm/feup-tne-PowerTAC
|
036c88485d538b2e127ea285e4df79107b891611
|
[
"MIT"
] | null | null | null |
scripts/tnaCompile.py
|
j-vm/feup-tne-PowerTAC
|
036c88485d538b2e127ea285e4df79107b891611
|
[
"MIT"
] | null | null | null |
scripts/tnaCompile.py
|
j-vm/feup-tne-PowerTAC
|
036c88485d538b2e127ea285e4df79107b891611
|
[
"MIT"
] | null | null | null |
from runAgent import compile_and_move
AGENT_NAME = "temporaryName"
VERSION = "1.7.0"
compile_and_move(AGENT_NAME, VERSION)
| 20.666667
| 37
| 0.806452
| 19
| 124
| 4.947368
| 0.684211
| 0.212766
| 0.297872
| 0.404255
| 0.489362
| 0
| 0
| 0
| 0
| 0
| 0
| 0.027027
| 0.104839
| 124
| 6
| 38
| 20.666667
| 0.81982
| 0
| 0
| 0
| 0
| 0
| 0.144
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.25
| 0
| 0.25
| 0
| 1
| 0
| 0
| null | 1
| 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
| 5
|
1f9fc3ad20a682d3e8eaa70d5cafa1a8aab35dcb
| 44
|
py
|
Python
|
xknx/config/entries/__init__.py
|
onkelbeh/xknx
|
b7c7427b77b1a709aef8e25b39bbbb62ace6f708
|
[
"MIT"
] | 1
|
2020-12-27T13:54:34.000Z
|
2020-12-27T13:54:34.000Z
|
xknx/config/entries/__init__.py
|
onkelbeh/xknx
|
b7c7427b77b1a709aef8e25b39bbbb62ace6f708
|
[
"MIT"
] | 1
|
2021-02-17T23:54:32.000Z
|
2021-02-17T23:54:32.000Z
|
xknx/config/entries/__init__.py
|
mielune/xknx
|
57c248c386f2ae150d983f72a5a8da684097265d
|
[
"MIT"
] | null | null | null |
"""Support for dedicated config entries."""
| 22
| 43
| 0.727273
| 5
| 44
| 6.4
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.113636
| 44
| 1
| 44
| 44
| 0.820513
| 0.840909
| 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
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
|
0
| 5
|
1fa24983c75083741e7b2aac162d627c70b7f1e5
| 507
|
py
|
Python
|
solution/emas_initializer.py
|
Hoobie/pyage-styblinski-tang
|
aaf703c8eb95d8c18d414cf194425f7e59712481
|
[
"MIT"
] | null | null | null |
solution/emas_initializer.py
|
Hoobie/pyage-styblinski-tang
|
aaf703c8eb95d8c18d414cf194425f7e59712481
|
[
"MIT"
] | null | null | null |
solution/emas_initializer.py
|
Hoobie/pyage-styblinski-tang
|
aaf703c8eb95d8c18d414cf194425f7e59712481
|
[
"MIT"
] | null | null | null |
from random import uniform
from pyage.core.emas import EmasAgent
from solution.genotype import VectorGenotype
def emas_initializer(energy=10, size=100, lowerbound=0.0, upperbound=1.0):
agents = {}
for i in range(size):
agent = EmasAgent(VectorGenotype(uniform(lowerbound, upperbound), uniform(lowerbound, upperbound), uniform(lowerbound, upperbound), uniform(lowerbound, upperbound), uniform(lowerbound, upperbound)), energy)
agents[agent.get_address()] = agent
return agents
| 39
| 214
| 0.753452
| 60
| 507
| 6.333333
| 0.5
| 0.223684
| 0.355263
| 0.357895
| 0.355263
| 0.355263
| 0.355263
| 0.355263
| 0.355263
| 0.355263
| 0
| 0.020737
| 0.143984
| 507
| 13
| 215
| 39
| 0.854839
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.111111
| false
| 0
| 0.333333
| 0
| 0.555556
| 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
| 1
| 0
|
0
| 5
|
1fcd2371b504b06fcff4f6e9230b94a608473994
| 83
|
py
|
Python
|
reverse_client/exceptions.py
|
tchar/webshell-client
|
29612488cf7ef59fa67db732a10c3396407ff154
|
[
"MIT"
] | 1
|
2021-12-07T22:17:18.000Z
|
2021-12-07T22:17:18.000Z
|
reverse_client/exceptions.py
|
tchar/webshell-client
|
29612488cf7ef59fa67db732a10c3396407ff154
|
[
"MIT"
] | null | null | null |
reverse_client/exceptions.py
|
tchar/webshell-client
|
29612488cf7ef59fa67db732a10c3396407ff154
|
[
"MIT"
] | null | null | null |
class ShellException(Exception): pass
class ShellInternalInterrupt(Exception): pass
| 41.5
| 45
| 0.86747
| 8
| 83
| 9
| 0.625
| 0.361111
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.060241
| 83
| 2
| 45
| 41.5
| 0.923077
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 1
| 0
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| 1
| 0
| 1
| 0
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| 0
| 0
| 0
|
0
| 5
|
1fffea70af558ca7f3b9320b2339855c0907564b
| 147
|
py
|
Python
|
models/__init__.py
|
uncleguanghui/bitcoin_toolkit
|
c5898d841201ccd3271adee43f7d116e6333e0d8
|
[
"MIT"
] | null | null | null |
models/__init__.py
|
uncleguanghui/bitcoin_toolkit
|
c5898d841201ccd3271adee43f7d116e6333e0d8
|
[
"MIT"
] | 1
|
2020-10-12T01:52:50.000Z
|
2021-06-22T10:29:10.000Z
|
models/__init__.py
|
uncleguanghui/bitcoin_toolkit
|
c5898d841201ccd3271adee43f7d116e6333e0d8
|
[
"MIT"
] | 1
|
2021-03-26T15:18:26.000Z
|
2021-03-26T15:18:26.000Z
|
from .address import Address
from .transaction import Transaction
from .output import Output
from .block import Block
from .bitcoin import Bitcoin
| 24.5
| 36
| 0.829932
| 20
| 147
| 6.1
| 0.35
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.136054
| 147
| 5
| 37
| 29.4
| 0.96063
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
95040a6c4d7516bdc20c7152e850557e8d61e336
| 335
|
py
|
Python
|
aux/protocol/http/auth/basic.py
|
bischjer/auxiliary
|
e42d8a4af43c9bd4d816c03edc2465640635b46b
|
[
"BSD-3-Clause"
] | null | null | null |
aux/protocol/http/auth/basic.py
|
bischjer/auxiliary
|
e42d8a4af43c9bd4d816c03edc2465640635b46b
|
[
"BSD-3-Clause"
] | null | null | null |
aux/protocol/http/auth/basic.py
|
bischjer/auxiliary
|
e42d8a4af43c9bd4d816c03edc2465640635b46b
|
[
"BSD-3-Clause"
] | null | null | null |
from base64 import b64encode
class BasicAuthenticator(object):
def __init__(self, credentials):
self.credentials = credentials
def __call__(self):
return {"Basic":"%s" % b64encode(b'%s%s' % (self.credentials.username,
self.credentials.password))}
| 22.333333
| 81
| 0.570149
| 30
| 335
| 6.1
| 0.6
| 0.327869
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.026549
| 0.325373
| 335
| 14
| 82
| 23.928571
| 0.783186
| 0
| 0
| 0
| 0
| 0
| 0.032836
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.285714
| false
| 0.142857
| 0.142857
| 0.142857
| 0.714286
| 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
| 1
| 0
| 1
| 1
| 0
|
0
| 5
|
951be236b64c7d5d013f60ecefdb39cfffafbc12
| 275
|
py
|
Python
|
src/infi/pyutils/exceptions.py
|
jasonjorge/infi.asi
|
78a4c34a421102f99b959a659cf7303804627d9b
|
[
"BSD-3-Clause"
] | 1
|
2022-02-12T20:30:55.000Z
|
2022-02-12T20:30:55.000Z
|
src/infi/pyutils/exceptions.py
|
jasonjorge/infi.asi
|
78a4c34a421102f99b959a659cf7303804627d9b
|
[
"BSD-3-Clause"
] | 5
|
2015-11-08T14:50:42.000Z
|
2020-06-23T14:42:33.000Z
|
src/infi/pyutils/exceptions.py
|
jasonjorge/infi.asi
|
78a4c34a421102f99b959a659cf7303804627d9b
|
[
"BSD-3-Clause"
] | 4
|
2015-02-22T09:06:59.000Z
|
2022-02-12T20:30:55.000Z
|
class ReflectionException(Exception):
pass
class SignatureException(ReflectionException):
pass
class MissingArguments(SignatureException):
pass
class UnknownArguments(SignatureException):
pass
class InvalidKeywordArgument(ReflectionException):
pass
| 16.176471
| 50
| 0.796364
| 20
| 275
| 10.95
| 0.4
| 0.164384
| 0.246575
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.149091
| 275
| 16
| 51
| 17.1875
| 0.935897
| 0
| 0
| 0.5
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0.5
| 0
| 0
| 0.5
| 0
| 1
| 0
| 1
| 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
| 0
| 1
| 1
| 0
| 0
| 0
| 0
|
0
| 5
|
1f118ac1da09f3b1bd1fd5332ec578e95fb3d4b3
| 569
|
py
|
Python
|
ts/nni_manager/test/core/dummy_tuner.py
|
dutxubo/nni
|
c16f4e1c89b54b8b80661ef0072433d255ad2d24
|
[
"MIT"
] | 9,680
|
2019-05-07T01:42:30.000Z
|
2022-03-31T16:48:33.000Z
|
ts/nni_manager/test/core/dummy_tuner.py
|
dutxubo/nni
|
c16f4e1c89b54b8b80661ef0072433d255ad2d24
|
[
"MIT"
] | 1,957
|
2019-05-06T21:44:21.000Z
|
2022-03-31T09:21:53.000Z
|
ts/nni_manager/test/core/dummy_tuner.py
|
dutxubo/nni
|
c16f4e1c89b54b8b80661ef0072433d255ad2d24
|
[
"MIT"
] | 1,571
|
2019-05-07T06:42:55.000Z
|
2022-03-31T03:19:24.000Z
|
# Copyright (c) Microsoft Corporation.
# Licensed under the MIT license.
from nni.tuner import Tuner
class DummyTuner(Tuner):
def generate_parameters(self, parameter_id):
return 'unit-test-parm'
def generate_multiple_parameters(self, parameter_id_list):
return ['unit-test-param1', 'unit-test-param2']
def receive_trial_result(self, parameter_id, parameters, value):
pass
def receive_customized_trial_result(self, parameter_id, parameters, value):
pass
def update_search_space(self, search_space):
pass
| 27.095238
| 79
| 0.720562
| 71
| 569
| 5.549296
| 0.535211
| 0.13198
| 0.152284
| 0.126904
| 0.243655
| 0.243655
| 0.243655
| 0.243655
| 0.243655
| 0
| 0
| 0.004357
| 0.193322
| 569
| 20
| 80
| 28.45
| 0.854031
| 0.119508
| 0
| 0.25
| 1
| 0
| 0.092369
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.416667
| false
| 0.25
| 0.083333
| 0.166667
| 0.75
| 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
| 1
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 1
| 0
|
0
| 5
|
1f418e87211666ae0b6509dc62fb065f7fbfe1a6
| 143
|
py
|
Python
|
tests/test_KSS/conftest.py
|
bigdata-ustc/EduSim
|
849eed229c24615e5f2c3045036311e83c22ea68
|
[
"MIT"
] | 18
|
2019-11-11T03:45:35.000Z
|
2022-02-09T15:31:51.000Z
|
tests/test_KSS/conftest.py
|
ghzhao78506/EduSim
|
cb10e952eb212d8a9344143f889207b5cd48ba9d
|
[
"MIT"
] | 3
|
2020-10-23T01:05:57.000Z
|
2021-03-16T12:12:24.000Z
|
tests/test_KSS/conftest.py
|
bigdata-ustc/EduSim
|
849eed229c24615e5f2c3045036311e83c22ea68
|
[
"MIT"
] | 6
|
2020-06-09T21:32:00.000Z
|
2022-03-12T00:25:18.000Z
|
# coding: utf-8
# 2019/11/27 @ tongshiwei
import pytest
import gym
@pytest.fixture(scope="module")
def env():
return gym.make('KSS-v2')
| 13
| 31
| 0.678322
| 22
| 143
| 4.409091
| 0.863636
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.083333
| 0.160839
| 143
| 10
| 32
| 14.3
| 0.725
| 0.258741
| 0
| 0
| 0
| 0
| 0.116505
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.2
| true
| 0
| 0.4
| 0.2
| 0.8
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 1
| 1
| 0
|
0
| 5
|
1f6fb393f1484ef291228861383ed7ead9e5064a
| 125
|
py
|
Python
|
cvk/admin.py
|
cvk007/ML_Model
|
8437257cc84c7a0ac42e7b6728431494f145882b
|
[
"MIT"
] | null | null | null |
cvk/admin.py
|
cvk007/ML_Model
|
8437257cc84c7a0ac42e7b6728431494f145882b
|
[
"MIT"
] | null | null | null |
cvk/admin.py
|
cvk007/ML_Model
|
8437257cc84c7a0ac42e7b6728431494f145882b
|
[
"MIT"
] | null | null | null |
from django.contrib import admin
from cvk.models import feedback
admin.site.register(feedback)
# Register your models here.
| 20.833333
| 32
| 0.816
| 18
| 125
| 5.666667
| 0.666667
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.12
| 125
| 5
| 33
| 25
| 0.927273
| 0.208
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.666667
| 0
| 0.666667
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
1f91234660d31d0847e1385fb79af761fe686ebe
| 92
|
py
|
Python
|
binlog2sql/binlog2sql/__init__.py
|
sivarki/hjarnuc
|
4acc9437af0f0fdc44d68dd0d6923e1039a4911b
|
[
"Apache-2.0"
] | 2
|
2021-05-27T04:07:25.000Z
|
2021-09-03T02:56:39.000Z
|
binlog2sql/binlog2sql/__init__.py
|
sivarki/hjarnuc
|
4acc9437af0f0fdc44d68dd0d6923e1039a4911b
|
[
"Apache-2.0"
] | null | null | null |
binlog2sql/binlog2sql/__init__.py
|
sivarki/hjarnuc
|
4acc9437af0f0fdc44d68dd0d6923e1039a4911b
|
[
"Apache-2.0"
] | 1
|
2019-02-20T01:27:46.000Z
|
2019-02-20T01:27:46.000Z
|
'''
binlog2sql:
Parse MySQL binlog to SQL you want.
'''
from .binlog2sql import Binlog2sql
| 13.142857
| 35
| 0.73913
| 12
| 92
| 5.666667
| 0.833333
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.038961
| 0.163043
| 92
| 6
| 36
| 15.333333
| 0.844156
| 0.51087
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
2f23033c3fba81b64d632f9fb1e2b5038a6f48a8
| 56
|
py
|
Python
|
aif360/sklearn/detectors/__init__.py
|
IBM/AIF-360
|
9eae52000c92bbc9279f8ee4bdb7a7c5ac585359
|
[
"Apache-2.0"
] | 982
|
2018-09-12T17:19:11.000Z
|
2020-07-13T21:26:24.000Z
|
aif360/sklearn/detectors/__init__.py
|
IBM/AIF-360
|
9eae52000c92bbc9279f8ee4bdb7a7c5ac585359
|
[
"Apache-2.0"
] | 109
|
2018-09-12T20:39:43.000Z
|
2020-07-09T20:12:00.000Z
|
aif360/sklearn/detectors/__init__.py
|
IBM/AIF-360
|
9eae52000c92bbc9279f8ee4bdb7a7c5ac585359
|
[
"Apache-2.0"
] | 335
|
2018-09-13T15:35:09.000Z
|
2020-07-06T10:56:12.000Z
|
from aif360.sklearn.detectors.detectors import bias_scan
| 56
| 56
| 0.892857
| 8
| 56
| 6.125
| 0.875
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.056604
| 0.053571
| 56
| 1
| 56
| 56
| 0.867925
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
2f77e1f6726adb94470778c88030cfacfb7bd000
| 2,218
|
py
|
Python
|
webscrape/application/utils.py
|
kmvicky/webscrape
|
92ca9100e21de276ed8470621e1e3a7a6495d54d
|
[
"MIT"
] | null | null | null |
webscrape/application/utils.py
|
kmvicky/webscrape
|
92ca9100e21de276ed8470621e1e3a7a6495d54d
|
[
"MIT"
] | null | null | null |
webscrape/application/utils.py
|
kmvicky/webscrape
|
92ca9100e21de276ed8470621e1e3a7a6495d54d
|
[
"MIT"
] | null | null | null |
"""Get a list of Messages from the user's mailbox.
"""
from apiclient import errors
def ListMessagesMatchingQuery(service, user_id, query=''):
"""List all Messages of the user's mailbox matching the query.
Args:
service: Authorized Gmail API service instance.
user_id: User's email address. The special value "me"
can be used to indicate the authenticated user.
query: String used to filter messages returned.
Eg.- 'from:user@some_domain.com' for Messages from a particular sender.
Returns:
List of Messages that match the criteria of the query. Note that the
returned list contains Message IDs, you must use get with the
appropriate ID to get the details of a Message.
"""
try:
response = service.users().messages().list(userId=user_id,q=query).execute()
messages = []
if 'messages' in response:
messages.extend(response['messages'])
while 'nextPageToken' in response:
page_token = response['nextPageToken']
response = service.users().messages().list(userId=user_id, q=query,pageToken=page_token).execute()
messages.extend(response['messages'])
return messages
except Exception as e:
print ('An error occurred:', e)
def ListMessagesWithLabels(service, user_id, label_ids=[]):
"""List all Messages of the user's mailbox with label_ids applied.
Args:
service: Authorized Gmail API service instance.
user_id: User's email address. The special value "me"
can be used to indicate the authenticated user.
label_ids: Only return Messages with these labelIds applied.
Returns:
List of Messages that have all required Labels applied. Note that the
returned list contains Message IDs, you must use get with the
appropriate id to get the details of a Message.
"""
try:
response = service.users().messages().list(userId=user_id,labelIds=label_ids).execute()
messages = []
if 'messages' in response:
messages.extend(response['messages'])
while 'nextPageToken' in response:
page_token = response['nextPageToken']
response = service.users().messages().list(userId=user_id,labelIds=label_ids,pageToken=page_token).execute()
messages.extend(response['messages'])
return messages
except Exception as e:
print ('An error occurred:',e)
| 34.123077
| 111
| 0.744364
| 313
| 2,218
| 5.217252
| 0.29393
| 0.029394
| 0.04899
| 0.068585
| 0.763013
| 0.732394
| 0.732394
| 0.732394
| 0.693203
| 0.693203
| 0
| 0
| 0.157349
| 2,218
| 65
| 112
| 34.123077
| 0.873729
| 0.525248
| 0
| 0.740741
| 0
| 0
| 0.121537
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.074074
| false
| 0
| 0.037037
| 0
| 0.185185
| 0.074074
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 1
| 1
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 5
|
2f8c52b08dd940f71291f75f34451e3b26091852
| 17
|
py
|
Python
|
z/Zhpy.py
|
wenzzai/hello-world
|
e94109a7f48df4c689442e1c1af7d39878d5b3dd
|
[
"MIT"
] | 2
|
2021-12-06T17:56:37.000Z
|
2022-01-21T01:44:16.000Z
|
z/Zhpy.py
|
wenzzai/hello-world
|
e94109a7f48df4c689442e1c1af7d39878d5b3dd
|
[
"MIT"
] | 2
|
2022-03-01T10:57:53.000Z
|
2022-03-01T12:45:49.000Z
|
z/Zhpy.py
|
wenzzai/hello-world
|
e94109a7f48df4c689442e1c1af7d39878d5b3dd
|
[
"MIT"
] | 1
|
2022-03-16T00:20:21.000Z
|
2022-03-16T00:20:21.000Z
|
印出 'Hello World'
| 8.5
| 16
| 0.705882
| 3
| 17
| 4
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.176471
| 17
| 1
| 17
| 17
| 0.857143
| 0
| 0
| 0
| 0
| 0
| 0.647059
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | null | 0
| 0
| null | null | 0
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| null | 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 5
|
2f959305098809716563348d572e9232723091f6
| 131
|
py
|
Python
|
tests/not_imported_directly.py
|
mike0sv/pyjackson
|
87d2bffa03703ed6b5dabf8098b37f92a067531a
|
[
"Apache-2.0"
] | 20
|
2019-09-20T15:14:42.000Z
|
2020-08-05T09:59:30.000Z
|
tests/not_imported_directly.py
|
mike0sv/pyjackson
|
87d2bffa03703ed6b5dabf8098b37f92a067531a
|
[
"Apache-2.0"
] | null | null | null |
tests/not_imported_directly.py
|
mike0sv/pyjackson
|
87d2bffa03703ed6b5dabf8098b37f92a067531a
|
[
"Apache-2.0"
] | 1
|
2020-08-13T11:29:36.000Z
|
2020-08-13T11:29:36.000Z
|
from tests.conftest import RootClass
class ChildClass(RootClass):
def __init__(self, field: str):
self.field = field
| 18.714286
| 36
| 0.709924
| 16
| 131
| 5.5625
| 0.75
| 0.202247
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.206107
| 131
| 6
| 37
| 21.833333
| 0.855769
| 0
| 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
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 1
| 0
|
0
| 5
|
c80aef2f1462bbf20cb3140ddf058accfde16214
| 52
|
py
|
Python
|
app/models/exceptions/ResponseErrorCodeNotZero.py
|
luisalvesmartins/TAPO-P100
|
02bc929a87bbe4681739b14a716f6cef2b159fd1
|
[
"MIT"
] | null | null | null |
app/models/exceptions/ResponseErrorCodeNotZero.py
|
luisalvesmartins/TAPO-P100
|
02bc929a87bbe4681739b14a716f6cef2b159fd1
|
[
"MIT"
] | 1
|
2021-06-23T09:21:40.000Z
|
2021-07-02T17:21:12.000Z
|
app/models/exceptions/ResponseErrorCodeNotZero.py
|
luisalvesmartins/TAPO-P100
|
02bc929a87bbe4681739b14a716f6cef2b159fd1
|
[
"MIT"
] | null | null | null |
class ResponseErrorCodeNotZero(Exception):
pass
| 17.333333
| 42
| 0.807692
| 4
| 52
| 10.5
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.134615
| 52
| 2
| 43
| 26
| 0.933333
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0.5
| 0
| 0
| 0.5
| 0
| 1
| 0
| 1
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| 0
| 0
| 0
|
0
| 5
|
c8125710bba645f59eb48a24cefd8a3f0d6f42a2
| 290
|
py
|
Python
|
plotplayer/helpers/__init__.py
|
Jman420/plotplayer
|
3a224fc38c2825c4166e7534970a792f0e96bd84
|
[
"Apache-2.0"
] | null | null | null |
plotplayer/helpers/__init__.py
|
Jman420/plotplayer
|
3a224fc38c2825c4166e7534970a792f0e96bd84
|
[
"Apache-2.0"
] | 7
|
2018-06-20T19:44:45.000Z
|
2022-03-11T23:18:57.000Z
|
plotplayer/helpers/__init__.py
|
Jman420/plotplayer
|
3a224fc38c2825c4166e7534970a792f0e96bd84
|
[
"Apache-2.0"
] | 2
|
2018-04-08T14:36:13.000Z
|
2018-06-20T19:41:42.000Z
|
"""
PlotPlayer Helpers Subpackage contains various generic miscellaneous modules and methods to
ease development.
Public Modules:
* file_helper - Contains methods for interacting with the local file system
* ui_helper - Contains methods for providing generic UI elements & dialogs
"""
| 32.222222
| 91
| 0.796552
| 36
| 290
| 6.361111
| 0.722222
| 0.122271
| 0.183406
| 0.209607
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.158621
| 290
| 8
| 92
| 36.25
| 0.938525
| 0.968966
| 0
| null | 0
| null | 0
| 0
| null | 0
| 0
| 0
| null | 1
| null | true
| 0
| 0
| null | null | null | 0
| 0
| 0
| null | 0
| 1
| 1
| 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
| 5
|
c8197d1e970c3ca29e165a8d3c59fa019e53b65d
| 163
|
py
|
Python
|
yolox/models/__init__.py
|
kadirnar/yolox-lite
|
a493db0ac636eb507c3511fd24c974a9698c07f5
|
[
"MIT"
] | null | null | null |
yolox/models/__init__.py
|
kadirnar/yolox-lite
|
a493db0ac636eb507c3511fd24c974a9698c07f5
|
[
"MIT"
] | 1
|
2022-03-02T23:30:42.000Z
|
2022-03-02T23:30:42.000Z
|
yolox/models/__init__.py
|
kadirnar/yolox-lite
|
a493db0ac636eb507c3511fd24c974a9698c07f5
|
[
"MIT"
] | null | null | null |
from .darknet import CSPDarknet, Darknet
from .yolo_fpn import YOLOFPN
from .yolo_head import YOLOXHead
from .yolo_pafpn import YOLOPAFPN
from .yolox import YOLOX
| 27.166667
| 40
| 0.834356
| 24
| 163
| 5.541667
| 0.5
| 0.180451
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.128834
| 163
| 5
| 41
| 32.6
| 0.93662
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
c84cc384ad4a2967c2f453ccd06f349d762753cb
| 1,516
|
py
|
Python
|
dexplo/_date_funcs.py
|
dexplo/dexplo
|
2a522437d3bf848260f9772e7a8f705f534c2e2c
|
[
"BSD-3-Clause"
] | 78
|
2018-01-25T21:07:17.000Z
|
2020-11-07T00:19:13.000Z
|
dexplo/_date_funcs.py
|
dexplo/dexplo
|
2a522437d3bf848260f9772e7a8f705f534c2e2c
|
[
"BSD-3-Clause"
] | null | null | null |
dexplo/_date_funcs.py
|
dexplo/dexplo
|
2a522437d3bf848260f9772e7a8f705f534c2e2c
|
[
"BSD-3-Clause"
] | 8
|
2018-04-15T15:28:51.000Z
|
2022-03-22T10:37:54.000Z
|
import numpy as np
from ._libs import math as _math
from . import _utils
def max_date(arr, axis, **kwargs):
return arr.max(axis=axis)
def min_date(arr, axis, **kwargs):
return arr.min(axis=axis)
def any_date(arr, axis, **kwargs):
return (~np.isnat(arr)).sum(axis=axis) > 0
def all_date(arr, axis, **kwargs):
return (~np.isnat(arr)).sum(axis=axis) == arr.shape[0]
def argmax_date(arr, axis, **kwargs):
return arr.argmax(axis=axis)
def argmin_date(arr, axis, **kwargs):
return arr.argmin(axis=axis)
def count_date(arr, axis, **kwargs):
return (~np.isnat(arr)).sum(axis=axis)
def cummax_date(arr, axis, **kwargs):
return np.maximum.accumulate(arr, axis=axis)
def cummin_date(arr, axis, **kwargs):
return np.minimum.accumulate(arr, axis=axis)
def nunique_date(arr, axis, **kwargs):
return _math.nunique_int(arr.view('int64'), axis=axis)
def mode_date(arr, axis, **kwargs):
kind = arr.dtype.kind
return _math.mode_int(arr.view('int64'), axis=axis, **kwargs).astype(_utils._DT[kind])
## These below will only work for timedeltas
def sum_date(arr, axis, **kwargs):
return arr.sum(axis=axis)
def median_date(arr, axis, **kwargs):
return np.median(arr, axis=axis)
def mean_date(arr, axis, **kwargs):
return arr.mean(axis=axis)
def prod_date(arr, axis, **kwargs):
return arr.prod(axis=axis)
def cumsum_date(arr, axis, **kwargs):
return np.cumsum(arr, axis=axis)
def cumprod_date(arr, axis, **kwargs):
return np.cumprod(arr, axis=axis)
| 25.694915
| 90
| 0.686016
| 241
| 1,516
| 4.207469
| 0.211618
| 0.151874
| 0.184418
| 0.28501
| 0.565089
| 0.478304
| 0.130178
| 0.130178
| 0.130178
| 0.130178
| 0
| 0.004666
| 0.151715
| 1,516
| 58
| 91
| 26.137931
| 0.783826
| 0.027045
| 0
| 0
| 0
| 0
| 0.006793
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.447368
| false
| 0
| 0.078947
| 0.421053
| 0.973684
| 0
| 0
| 0
| 0
| null | 0
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 1
| 0
|
0
| 5
|
c075f6f9782cffb89e911a35c252107b2eae4de7
| 98
|
py
|
Python
|
website/apps/message/admin.py
|
jivanyan/salesior
|
9787b15befb3e39a3e848407bb58fa14d4cafde5
|
[
"CC0-1.0"
] | 3
|
2015-07-15T07:01:29.000Z
|
2020-03-29T09:12:39.000Z
|
message/admin.py
|
28harishkumar/Social-website-django
|
0b72ce34241112b87921ef095f6f47d4f958117c
|
[
"MIT"
] | null | null | null |
message/admin.py
|
28harishkumar/Social-website-django
|
0b72ce34241112b87921ef095f6f47d4f958117c
|
[
"MIT"
] | null | null | null |
from django.contrib import admin
from message.models import Message
admin.site.register(Message)
| 19.6
| 34
| 0.836735
| 14
| 98
| 5.857143
| 0.642857
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.102041
| 98
| 4
| 35
| 24.5
| 0.931818
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.666667
| 0
| 0.666667
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
c082cc0125c3c58ef3a6d42897bf2a1b3f3369f9
| 87
|
py
|
Python
|
tests/test_datafellows.py
|
redwardstern/datafellows
|
9a559fbf470fdb9c407a9f49e0f8bdad1cd74f00
|
[
"BSD-2-Clause"
] | null | null | null |
tests/test_datafellows.py
|
redwardstern/datafellows
|
9a559fbf470fdb9c407a9f49e0f8bdad1cd74f00
|
[
"BSD-2-Clause"
] | null | null | null |
tests/test_datafellows.py
|
redwardstern/datafellows
|
9a559fbf470fdb9c407a9f49e0f8bdad1cd74f00
|
[
"BSD-2-Clause"
] | null | null | null |
import datafellows
def test_main():
assert datafellows # use your library here
| 12.428571
| 47
| 0.735632
| 11
| 87
| 5.727273
| 0.909091
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.218391
| 87
| 6
| 48
| 14.5
| 0.926471
| 0.241379
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.333333
| 1
| 0.333333
| true
| 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
| 1
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 5
|
c093e79b3adf01a892c36384fd42ad77534ad2e3
| 70
|
py
|
Python
|
src/introducao/02_investigando_objeto.py
|
SamuelPossamai/material_auxilio_conceitos_python
|
44c15e72f7409441fe0db38288dac782f0cbc94d
|
[
"MIT"
] | 1
|
2022-02-08T23:39:11.000Z
|
2022-02-08T23:39:11.000Z
|
src/introducao/02_investigando_objeto.py
|
SamuelPossamai/material_auxilio_conceitos_python
|
44c15e72f7409441fe0db38288dac782f0cbc94d
|
[
"MIT"
] | null | null | null |
src/introducao/02_investigando_objeto.py
|
SamuelPossamai/material_auxilio_conceitos_python
|
44c15e72f7409441fe0db38288dac782f0cbc94d
|
[
"MIT"
] | null | null | null |
a = []
print(type(a))
#help(a)
#print(dir(a))
#print(type(type(a)))
| 8.75
| 21
| 0.557143
| 13
| 70
| 3
| 0.384615
| 0.461538
| 0.512821
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.128571
| 70
| 7
| 22
| 10
| 0.639344
| 0.571429
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0
| 0
| 0
| 0.5
| 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
| 1
|
0
| 5
|
c0c645b898c215fd0ff4330d52973dd491756d2e
| 83
|
py
|
Python
|
photo/qt/__init__.py
|
RKrahl/photo-tools
|
0bf0b4405e5cd6e5fcab9a64ac1591ea097dcf27
|
[
"Apache-2.0"
] | null | null | null |
photo/qt/__init__.py
|
RKrahl/photo-tools
|
0bf0b4405e5cd6e5fcab9a64ac1591ea097dcf27
|
[
"Apache-2.0"
] | 46
|
2016-01-03T15:11:18.000Z
|
2020-05-09T19:46:03.000Z
|
photo/qt/__init__.py
|
RKrahl/photo-tools
|
0bf0b4405e5cd6e5fcab9a64ac1591ea097dcf27
|
[
"Apache-2.0"
] | null | null | null |
"""GUI elements based on PySide.
"""
from photo.qt.imageViewer import ImageViewer
| 16.6
| 44
| 0.759036
| 11
| 83
| 5.727273
| 0.909091
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.13253
| 83
| 4
| 45
| 20.75
| 0.875
| 0.349398
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
c0d4615478ccd32c4548c6aa9237b615a0a673b2
| 179
|
py
|
Python
|
scrywarden/config/__init__.py
|
chasebrewsky/scrywarden
|
c6a5a81d14016ca58625df68594ef52dd328a0dd
|
[
"MIT"
] | 1
|
2020-12-13T00:49:51.000Z
|
2020-12-13T00:49:51.000Z
|
scrywarden/config/__init__.py
|
chasebrewsky/scrywarden
|
c6a5a81d14016ca58625df68594ef52dd328a0dd
|
[
"MIT"
] | null | null | null |
scrywarden/config/__init__.py
|
chasebrewsky/scrywarden
|
c6a5a81d14016ca58625df68594ef52dd328a0dd
|
[
"MIT"
] | null | null | null |
"""Module containing utilities for retrieving configuration values."""
from .base import Config, parse_config
from .settings import Setting, SettingDict, SettingList, SettingKey
| 35.8
| 70
| 0.815642
| 20
| 179
| 7.25
| 0.85
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.111732
| 179
| 4
| 71
| 44.75
| 0.91195
| 0.357542
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
8d07d3f580b31f92cbba7b8a08c4e771700df290
| 838
|
py
|
Python
|
metrics.py
|
sy2616/DATA
|
8d2314b23c9757c8f54a85a01b451aaa29054912
|
[
"Apache-2.0"
] | 2
|
2020-08-08T02:02:04.000Z
|
2020-12-22T09:12:09.000Z
|
metrics.py
|
sy2616/DATA
|
8d2314b23c9757c8f54a85a01b451aaa29054912
|
[
"Apache-2.0"
] | null | null | null |
metrics.py
|
sy2616/DATA
|
8d2314b23c9757c8f54a85a01b451aaa29054912
|
[
"Apache-2.0"
] | null | null | null |
import numpy as np
def accuracy_score(y_true,y_predict):
assert y_true.shape[0]==y_predict.shape[0],\
'the size of y_true must be equal to the sze of y_predict'
return sum(y_true==y_predict)/len(y_true)
def mean_squared_error(y_ture,y_predict):
assert len(y_ture)==len(y_predict),\
'the size of y_ture must be equal to the size of y_predict'
return np.sum((y_ture-y_predict)**2)/len(y_ture)
def root_mean_squared_error(y_ture,y_predict):
return squr(mean_squared_error(y_ture,y_predict))
def mean_absolute_error(y_ture,y_predict):
assert len(y_ture)==len(y_predict),\
'the size of y_ture must be equal to the size of y_predict'
return np.sum(np.absolute(y_ture-y_predict))/len(y_ture)
def r2_score(y_ture,y_predict):
return 1-mean_squared_error(y_ture,y_predict)/np.var(y_ture)
| 38.090909
| 67
| 0.738663
| 162
| 838
| 3.518519
| 0.216049
| 0.224561
| 0.084211
| 0.182456
| 0.587719
| 0.515789
| 0.515789
| 0.34386
| 0.34386
| 0.34386
| 0
| 0.007022
| 0.150358
| 838
| 22
| 68
| 38.090909
| 0.793539
| 0
| 0
| 0.235294
| 0
| 0
| 0.202622
| 0
| 0
| 0
| 0
| 0
| 0.176471
| 1
| 0.294118
| false
| 0
| 0.058824
| 0.117647
| 0.647059
| 0
| 0
| 0
| 0
| null | 1
| 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
| 5
|
2391e837f9b052eff281141e801abf009da64583
| 671
|
py
|
Python
|
urllib/Cookie/CookieBasic.py
|
pengchenyu111/SpiderLearning
|
d1fca1c7f46bfb22ad23f9396d0f2e2301ec4534
|
[
"Apache-2.0"
] | 3
|
2020-11-21T13:13:46.000Z
|
2020-12-03T05:43:32.000Z
|
urllib/Cookie/CookieBasic.py
|
pengchenyu111/SpiderLearning
|
d1fca1c7f46bfb22ad23f9396d0f2e2301ec4534
|
[
"Apache-2.0"
] | null | null | null |
urllib/Cookie/CookieBasic.py
|
pengchenyu111/SpiderLearning
|
d1fca1c7f46bfb22ad23f9396d0f2e2301ec4534
|
[
"Apache-2.0"
] | 1
|
2020-12-03T05:43:53.000Z
|
2020-12-03T05:43:53.000Z
|
import http.cookiejar, urllib.request
# 获取百度返回的Cookie
cookie = http.cookiejar.CookieJar()
handler = urllib.request.HTTPCookieProcessor(cookie)
opener = urllib.request.build_opener(handler)
response = opener.open('http://www.baidu.com')
print('------http://www.baidu.com--------')
for item in cookie:
print(item.name + '=' + item.value)
# 返回自己服务器的Cookie
print('------http://127.0.0.1:5000/writeCookie--------')
cookie = http.cookiejar.CookieJar()
handler = urllib.request.HTTPCookieProcessor(cookie)
opener = urllib.request.build_opener(handler)
response = opener.open('http://127.0.0.1:5000/writeCookie')
for item in cookie:
print(item.name + '=' + item.value)
| 33.55
| 59
| 0.716841
| 85
| 671
| 5.635294
| 0.329412
| 0.135699
| 0.079332
| 0.11691
| 0.80167
| 0.80167
| 0.80167
| 0.705637
| 0.705637
| 0.551148
| 0
| 0.032787
| 0.090909
| 671
| 19
| 60
| 35.315789
| 0.752459
| 0.041729
| 0
| 0.666667
| 0
| 0
| 0.2125
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.066667
| 0
| 0.066667
| 0.266667
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 5
|
23e0e5c7fea788ff45d3c2a315d2f89bd63c1dfe
| 60
|
py
|
Python
|
lampy/std/__init__.py
|
Lgneous/Lampy
|
a009a81b6e55d4203928899e8043b533c02aeba2
|
[
"MIT"
] | 6
|
2018-12-22T08:08:58.000Z
|
2019-03-02T05:00:03.000Z
|
lampy/std/__init__.py
|
Lgneous/FPython
|
a009a81b6e55d4203928899e8043b533c02aeba2
|
[
"MIT"
] | 2
|
2019-03-19T06:01:43.000Z
|
2019-03-19T06:04:28.000Z
|
lampy/std/__init__.py
|
Lgneous/Ignite
|
a009a81b6e55d4203928899e8043b533c02aeba2
|
[
"MIT"
] | null | null | null |
from .std import *
from . import std
__all__ = std.__all__
| 12
| 21
| 0.716667
| 9
| 60
| 3.888889
| 0.444444
| 0.342857
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.2
| 60
| 4
| 22
| 15
| 0.729167
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.666667
| 0
| 0.666667
| 0
| 1
| 0
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
23f105d45171de16e7e0052b26eaace18c9605f4
| 99
|
py
|
Python
|
opsdroid/connector/gitlab/__init__.py
|
jacobtomlinson/ops-bot
|
8b20dd634467097e2dc75af2371e7dec4bbb8960
|
[
"Apache-2.0"
] | 1
|
2017-08-26T18:31:53.000Z
|
2017-08-26T18:31:53.000Z
|
opsdroid/connector/gitlab/__init__.py
|
jacobtomlinson/ops-bot
|
8b20dd634467097e2dc75af2371e7dec4bbb8960
|
[
"Apache-2.0"
] | 8
|
2022-03-01T13:43:05.000Z
|
2022-03-05T22:51:43.000Z
|
opsdroid/connector/gitlab/__init__.py
|
jacobtomlinson/ops-bot
|
8b20dd634467097e2dc75af2371e7dec4bbb8960
|
[
"Apache-2.0"
] | null | null | null |
"""Import Gitlab connector."""
from .connector import ConnectorGitlab, GitlabPayload # noqa: F401
| 33
| 67
| 0.767677
| 10
| 99
| 7.6
| 0.8
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.034483
| 0.121212
| 99
| 2
| 68
| 49.5
| 0.83908
| 0.363636
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
9b01b69e4c671d941ba1f641562338ea1f95bffc
| 272
|
py
|
Python
|
CursoEmVideo/Aula16/ex074.py
|
lucashsouza/Desafios-Python
|
abb5b11ebdfd4c232b4f0427ef41fd96013f2802
|
[
"MIT"
] | null | null | null |
CursoEmVideo/Aula16/ex074.py
|
lucashsouza/Desafios-Python
|
abb5b11ebdfd4c232b4f0427ef41fd96013f2802
|
[
"MIT"
] | null | null | null |
CursoEmVideo/Aula16/ex074.py
|
lucashsouza/Desafios-Python
|
abb5b11ebdfd4c232b4f0427ef41fd96013f2802
|
[
"MIT"
] | null | null | null |
from random import randint
n1, n2, n3, n4, n5 = randint(0, 9), randint(0, 9), randint(0, 9), randint(0, 9), randint(0, 9)
tup = n1, n2, n3, n4, n5
print(f'Os valores sorteados foram {tup}')
print(f'O maior número é {max(tup)}')
print(f'O menor número é {min(tup)}')
| 38.857143
| 95
| 0.636029
| 53
| 272
| 3.264151
| 0.471698
| 0.231214
| 0.260116
| 0.369942
| 0.375723
| 0.260116
| 0.260116
| 0.260116
| 0.260116
| 0.260116
| 0
| 0.089286
| 0.176471
| 272
| 6
| 96
| 45.333333
| 0.683036
| 0
| 0
| 0
| 0
| 0
| 0.323308
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.166667
| 0
| 0.166667
| 0.5
| 0
| 0
| 0
| null | 1
| 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
| 1
|
0
| 5
|
9b03c418cf867f922121599295a41f604e1a4153
| 66
|
py
|
Python
|
Python/List Comprehension One Liner.py
|
RDxR10/Hacktoberfest-2020-FizzBuzz
|
c9a8e3a0ac1ff9886c013a6b5628b7f64eb0d342
|
[
"Unlicense"
] | 80
|
2020-10-01T00:32:34.000Z
|
2021-01-08T21:56:09.000Z
|
Python/List Comprehension One Liner.py
|
RDxR10/Hacktoberfest-2020-FizzBuzz
|
c9a8e3a0ac1ff9886c013a6b5628b7f64eb0d342
|
[
"Unlicense"
] | 672
|
2020-09-30T22:53:47.000Z
|
2020-11-01T12:39:59.000Z
|
Python/List Comprehension One Liner.py
|
RDxR10/Hacktoberfest-2020-FizzBuzz
|
c9a8e3a0ac1ff9886c013a6b5628b7f64eb0d342
|
[
"Unlicense"
] | 618
|
2020-09-30T22:21:12.000Z
|
2020-10-31T21:28:06.000Z
|
[print("Fizz"*(i%3==0)+"Buzz"*(i%5==0) or i) for i in range(101)]
| 33
| 65
| 0.545455
| 16
| 66
| 2.25
| 0.75
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.118644
| 0.106061
| 66
| 1
| 66
| 66
| 0.491525
| 0
| 0
| 0
| 0
| 0
| 0.121212
| 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
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 1
|
0
| 5
|
9b17fd77dd376b476ec261f14257b37156a30df7
| 46
|
py
|
Python
|
src/kvt/callbacks/__init__.py
|
Ynakatsuka/nishika-22
|
72994cab16486b3a26686642ad72a29b6761b46d
|
[
"BSD-2-Clause"
] | 4
|
2022-02-01T05:04:53.000Z
|
2022-02-02T04:16:31.000Z
|
src/kvt/callbacks/__init__.py
|
Ynakatsuka/nishika-22
|
72994cab16486b3a26686642ad72a29b6761b46d
|
[
"BSD-2-Clause"
] | null | null | null |
src/kvt/callbacks/__init__.py
|
Ynakatsuka/nishika-22
|
72994cab16486b3a26686642ad72a29b6761b46d
|
[
"BSD-2-Clause"
] | null | null | null |
# flake8: noqa
from .autoclip import AutoClip
| 15.333333
| 30
| 0.782609
| 6
| 46
| 6
| 0.833333
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.025641
| 0.152174
| 46
| 2
| 31
| 23
| 0.897436
| 0.26087
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 5
|
9b211b29391623a5a5c9e80c905e1bd3f8caec2b
| 130
|
py
|
Python
|
facturador/usuario/admin.py
|
crodriguezud/Facturador
|
1a1e08072ae1d54f3f7963cdd202444618a0fa2e
|
[
"Apache-2.0"
] | null | null | null |
facturador/usuario/admin.py
|
crodriguezud/Facturador
|
1a1e08072ae1d54f3f7963cdd202444618a0fa2e
|
[
"Apache-2.0"
] | 9
|
2020-06-05T17:25:18.000Z
|
2022-03-11T23:15:36.000Z
|
facturador/usuario/admin.py
|
crodriguezud/Facturador
|
1a1e08072ae1d54f3f7963cdd202444618a0fa2e
|
[
"Apache-2.0"
] | null | null | null |
from django.contrib import admin
from .models import Usuario, Cliente
admin.site.register(Usuario)
admin.site.register(Cliente)
| 18.571429
| 36
| 0.815385
| 18
| 130
| 5.888889
| 0.555556
| 0.169811
| 0.320755
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.1
| 130
| 6
| 37
| 21.666667
| 0.905983
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.5
| 0
| 0.5
| 0
| 1
| 0
| 0
| null | 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 5
|
f1ab6c6b62a01a77b6086426a9a429f459997497
| 92
|
py
|
Python
|
src/utils/sqlite.py
|
dasoncheng/intelligence
|
dd5af83c8071025c2934037b40b985aab98726d8
|
[
"Apache-2.0"
] | null | null | null |
src/utils/sqlite.py
|
dasoncheng/intelligence
|
dd5af83c8071025c2934037b40b985aab98726d8
|
[
"Apache-2.0"
] | null | null | null |
src/utils/sqlite.py
|
dasoncheng/intelligence
|
dd5af83c8071025c2934037b40b985aab98726d8
|
[
"Apache-2.0"
] | null | null | null |
import sqlite3
conn = sqlite3.connect('test.db')
def get_sqlite_name():
return "sdf"
| 11.5
| 33
| 0.695652
| 13
| 92
| 4.769231
| 0.923077
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.026316
| 0.173913
| 92
| 7
| 34
| 13.142857
| 0.789474
| 0
| 0
| 0
| 0
| 0
| 0.108696
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.25
| false
| 0
| 0.25
| 0.25
| 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
| 0
| 0
| 1
| 1
| 0
|
0
| 5
|
f1ad9efa89fdfcdf813173f61899dad148e554c3
| 80
|
py
|
Python
|
SSB.py
|
niazi911/ssb
|
c73171ae563ead3b3946cc1e1ba792221bd0f7be
|
[
"Apache-2.0"
] | null | null | null |
SSB.py
|
niazi911/ssb
|
c73171ae563ead3b3946cc1e1ba792221bd0f7be
|
[
"Apache-2.0"
] | null | null | null |
SSB.py
|
niazi911/ssb
|
c73171ae563ead3b3946cc1e1ba792221bd0f7be
|
[
"Apache-2.0"
] | null | null | null |
print(' Project is under maintinace, wait for update. Thanks for patience')
| 26.666667
| 77
| 0.7375
| 11
| 80
| 5.363636
| 0.909091
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.1875
| 80
| 2
| 78
| 40
| 0.907692
| 0
| 0
| 0
| 0
| 0
| 0.85
| 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
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 1
|
0
| 5
|
f1d1d4d5ab39826c929d0e4e26595e2384bcc209
| 150
|
py
|
Python
|
watson/mail/backends/__init__.py
|
watsonpy/watson-mail
|
8e40b5786970845ec56a6f93134908236ad0612c
|
[
"BSD-3-Clause"
] | null | null | null |
watson/mail/backends/__init__.py
|
watsonpy/watson-mail
|
8e40b5786970845ec56a6f93134908236ad0612c
|
[
"BSD-3-Clause"
] | 1
|
2017-07-16T21:37:37.000Z
|
2017-07-20T07:52:57.000Z
|
watson/mail/backends/__init__.py
|
watsonpy/watson-mail
|
8e40b5786970845ec56a6f93134908236ad0612c
|
[
"BSD-3-Clause"
] | null | null | null |
# -*- coding: utf-8 -*-
from watson.mail.backends.sendmail import Sendmail
from watson.mail.backends.smtp import SMTP
__all__ = ('Sendmail', 'SMTP')
| 25
| 50
| 0.726667
| 20
| 150
| 5.25
| 0.55
| 0.190476
| 0.266667
| 0.419048
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.007576
| 0.12
| 150
| 5
| 51
| 30
| 0.787879
| 0.14
| 0
| 0
| 0
| 0
| 0.094488
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.666667
| 0
| 0.666667
| 0
| 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
| 1
| 0
| 0
| 0
|
0
| 5
|
f1ec104b912a2d888cc3fd26d47d277687eee222
| 35
|
py
|
Python
|
combat/__init__.py
|
afrendeiro/combat
|
1f7d0bbcd221c9f35feff68855f6a697f3626df1
|
[
"MIT"
] | 2
|
2019-10-29T02:24:38.000Z
|
2021-02-14T00:54:06.000Z
|
combat/__init__.py
|
afrendeiro/combat
|
1f7d0bbcd221c9f35feff68855f6a697f3626df1
|
[
"MIT"
] | null | null | null |
combat/__init__.py
|
afrendeiro/combat
|
1f7d0bbcd221c9f35feff68855f6a697f3626df1
|
[
"MIT"
] | 1
|
2019-08-06T10:39:39.000Z
|
2019-08-06T10:39:39.000Z
|
from .combat import combat
combat
| 8.75
| 26
| 0.8
| 5
| 35
| 5.6
| 0.6
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.171429
| 35
| 3
| 27
| 11.666667
| 0.965517
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.5
| 0
| 0.5
| 0
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 5
|
f1f109aec1120f5711128a43f68ebf400a0dbf26
| 2,490
|
py
|
Python
|
itests/fe/group_leave_test.py
|
aneeq009/merou
|
7a87b43aaf64244932fa460842132a2d9329e704
|
[
"Apache-2.0"
] | 58
|
2017-05-26T06:46:24.000Z
|
2022-03-25T20:55:51.000Z
|
itests/fe/group_leave_test.py
|
aneeq009/merou
|
7a87b43aaf64244932fa460842132a2d9329e704
|
[
"Apache-2.0"
] | 74
|
2017-06-16T17:48:37.000Z
|
2022-03-28T23:09:54.000Z
|
itests/fe/group_leave_test.py
|
aneeq009/merou
|
7a87b43aaf64244932fa460842132a2d9329e704
|
[
"Apache-2.0"
] | 43
|
2017-05-20T22:11:51.000Z
|
2022-03-25T00:24:56.000Z
|
from __future__ import annotations
from typing import TYPE_CHECKING
import pytest
from selenium.common.exceptions import NoSuchElementException
from itests.pages.groups import GroupLeavePage, GroupViewPage
from itests.setup import frontend_server
from tests.url_util import url
if TYPE_CHECKING:
from py.path import LocalPath
from selenium.webdriver import Chrome
from tests.setup import SetupTest
def test_leave(tmpdir: LocalPath, setup: SetupTest, browser: Chrome) -> None:
with setup.transaction():
setup.add_user_to_group("gary@a.co", "some-group")
with frontend_server(tmpdir, "gary@a.co") as frontend_url:
browser.get(url(frontend_url, "/groups/some-group"))
view_page = GroupViewPage(browser)
assert view_page.find_member_row("gary@a.co")
view_page.click_leave_button()
leave_page = GroupLeavePage(browser)
assert leave_page.subheading == "Leave (some-group)"
leave_page.submit()
assert browser.current_url.endswith("/groups/some-group?refresh=yes")
with pytest.raises(NoSuchElementException):
view_page.find_member_row("gary@a.co")
def test_leave_as_owner(tmpdir: LocalPath, setup: SetupTest, browser: Chrome) -> None:
with setup.transaction():
setup.add_user_to_group("gary@a.co", "some-group", role="owner")
setup.add_user_to_group("zorkian@a.co", "some-group", role="np-owner")
with frontend_server(tmpdir, "gary@a.co") as frontend_url:
browser.get(url(frontend_url, "/groups/some-group"))
view_page = GroupViewPage(browser)
assert view_page.find_member_row("gary@a.co")
view_page.click_leave_button()
leave_page = GroupLeavePage(browser)
leave_page.submit()
assert browser.current_url.endswith("/groups/some-group?refresh=yes")
with pytest.raises(NoSuchElementException):
view_page.find_member_row("gary@a.co")
def test_leave_as_last_owner(tmpdir: LocalPath, setup: SetupTest, browser: Chrome) -> None:
with setup.transaction():
setup.add_user_to_group("gary@a.co", "some-group", role="owner")
setup.add_user_to_group("zorkian@a.co", "some-group", role="manager")
with frontend_server(tmpdir, "gary@a.co") as frontend_url:
browser.get(url(frontend_url, "/groups/some-group"))
view_page = GroupViewPage(browser)
with pytest.raises(NoSuchElementException):
view_page.click_leave_button()
| 36.086957
| 91
| 0.709237
| 325
| 2,490
| 5.215385
| 0.212308
| 0.021239
| 0.041298
| 0.041298
| 0.759882
| 0.750442
| 0.723304
| 0.723304
| 0.723304
| 0.723304
| 0
| 0
| 0.17751
| 2,490
| 68
| 92
| 36.617647
| 0.827637
| 0
| 0
| 0.625
| 0
| 0
| 0.128916
| 0.024096
| 0
| 0
| 0
| 0
| 0.104167
| 1
| 0.0625
| false
| 0
| 0.208333
| 0
| 0.270833
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 5
|
7b23b226e9bff7da94f752eccf83139ff0fd1c94
| 38
|
py
|
Python
|
src/api_status_monitor/producer/apireaders/__init__.py
|
jjaakola/bang-a-gong
|
d30f889c18eeaff3d62d47cd02e93516e4d24dd7
|
[
"MIT"
] | null | null | null |
src/api_status_monitor/producer/apireaders/__init__.py
|
jjaakola/bang-a-gong
|
d30f889c18eeaff3d62d47cd02e93516e4d24dd7
|
[
"MIT"
] | null | null | null |
src/api_status_monitor/producer/apireaders/__init__.py
|
jjaakola/bang-a-gong
|
d30f889c18eeaff3d62d47cd02e93516e4d24dd7
|
[
"MIT"
] | null | null | null |
from .apireaders import create_reader
| 19
| 37
| 0.868421
| 5
| 38
| 6.4
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.105263
| 38
| 1
| 38
| 38
| 0.941176
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 5
|
9e9b51bb50690dc800299983ef26d995a8f80761
| 411
|
py
|
Python
|
Aula34/aula34.py
|
marcelabbc07/TrabalhosPython
|
91734d13110e4dee12a532dfd7091e36394a6449
|
[
"MIT"
] | null | null | null |
Aula34/aula34.py
|
marcelabbc07/TrabalhosPython
|
91734d13110e4dee12a532dfd7091e36394a6449
|
[
"MIT"
] | null | null | null |
Aula34/aula34.py
|
marcelabbc07/TrabalhosPython
|
91734d13110e4dee12a532dfd7091e36394a6449
|
[
"MIT"
] | null | null | null |
#WEB
from flask import Flask
pessoa_controller=PessoaController()
app=Flask (__name__)
@app.route('/')
def inicio():
return render_template('index.html',titulo_app='nome')
@app.route('/Listar')
def listar():
return render_template('listar.html',titulo_app='nome',lista=pessoas)
@app.route('/Cadastrar')
def cadastrar():
return render_template('cadastrar.html',titulo_app='nome')
app.run(debug=True)
| 27.4
| 73
| 0.742092
| 55
| 411
| 5.345455
| 0.472727
| 0.081633
| 0.204082
| 0.173469
| 0.136054
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.087591
| 411
| 14
| 74
| 29.357143
| 0.784
| 0.007299
| 0
| 0
| 0
| 0
| 0.159705
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.230769
| false
| 0
| 0.076923
| 0.230769
| 0.538462
| 0
| 0
| 0
| 0
| null | 0
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 1
| 0
|
0
| 5
|
9ebfcd12d3dcb80174c64733789ecc5fa030a75d
| 43
|
py
|
Python
|
geofree/__init__.py
|
phygitalism/geometry-free-view-synthesis
|
00dc639c98dfb9246bee0009649c5be8f8b58e1e
|
[
"MIT"
] | 241
|
2021-04-16T01:09:06.000Z
|
2022-03-28T13:24:21.000Z
|
geofree/__init__.py
|
phygitalism/geometry-free-view-synthesis
|
00dc639c98dfb9246bee0009649c5be8f8b58e1e
|
[
"MIT"
] | 12
|
2021-04-21T17:24:31.000Z
|
2021-11-18T08:42:31.000Z
|
geofree/__init__.py
|
phygitalism/geometry-free-view-synthesis
|
00dc639c98dfb9246bee0009649c5be8f8b58e1e
|
[
"MIT"
] | 13
|
2021-04-22T09:59:22.000Z
|
2022-01-22T00:31:19.000Z
|
from geofree.util import pretrained_models
| 21.5
| 42
| 0.883721
| 6
| 43
| 6.166667
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.093023
| 43
| 1
| 43
| 43
| 0.948718
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 5
|
7b47a4815a00fc5bb0ff73fadd94a6a91d25ed0d
| 101
|
py
|
Python
|
__init__.py
|
areebbeigh/minja
|
698704c9816909eab144ed81e347e4e697b2493c
|
[
"BSD-3-Clause"
] | 2
|
2020-03-29T17:43:54.000Z
|
2020-07-06T05:53:17.000Z
|
__init__.py
|
areebbeigh/minja
|
698704c9816909eab144ed81e347e4e697b2493c
|
[
"BSD-3-Clause"
] | null | null | null |
__init__.py
|
areebbeigh/minja
|
698704c9816909eab144ed81e347e4e697b2493c
|
[
"BSD-3-Clause"
] | null | null | null |
__version__ = '0.1'
from minja.environment import Environment
from minja.utils import Markup, escape
| 25.25
| 41
| 0.811881
| 14
| 101
| 5.571429
| 0.714286
| 0.230769
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.022472
| 0.118812
| 101
| 3
| 42
| 33.666667
| 0.853933
| 0
| 0
| 0
| 0
| 0
| 0.029703
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.666667
| 0
| 0.666667
| 0
| 1
| 0
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
7b83f30bb59de365a0e1edda4bdf7622f316180f
| 239
|
py
|
Python
|
pyhtmlgui/lib/__init__.py
|
dirk-attraktor/pyHtmlGui
|
f3a1e076e147c165cb10c1f73b109bfd7a0d7c4f
|
[
"MIT"
] | null | null | null |
pyhtmlgui/lib/__init__.py
|
dirk-attraktor/pyHtmlGui
|
f3a1e076e147c165cb10c1f73b109bfd7a0d7c4f
|
[
"MIT"
] | null | null | null |
pyhtmlgui/lib/__init__.py
|
dirk-attraktor/pyHtmlGui
|
f3a1e076e147c165cb10c1f73b109bfd7a0d7c4f
|
[
"MIT"
] | null | null | null |
from .eventset import EventSet
from .weakfunctionreferences import WeakFunctionReferences
from .browser import Browser
from .observable import Observable
from .observableDict import ObservableDict
from .observableList import ObservableList
| 39.833333
| 58
| 0.878661
| 24
| 239
| 8.75
| 0.333333
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.096234
| 239
| 6
| 59
| 39.833333
| 0.972222
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
c8b9f04ccae9a02c38fedb657079c890af0c24db
| 148
|
py
|
Python
|
study_management/context_processors.py
|
jdkizer9/ls2_app
|
8b4c37b44a673d1919a0e52b72f529b7e1abd2e3
|
[
"Apache-2.0"
] | null | null | null |
study_management/context_processors.py
|
jdkizer9/ls2_app
|
8b4c37b44a673d1919a0e52b72f529b7e1abd2e3
|
[
"Apache-2.0"
] | 7
|
2020-02-05T04:57:01.000Z
|
2022-02-10T06:51:23.000Z
|
study_management/context_processors.py
|
jdkizer9/ls2_app
|
8b4c37b44a673d1919a0e52b72f529b7e1abd2e3
|
[
"Apache-2.0"
] | null | null | null |
from . import settings
def application_version_processor(requests):
return {
'application_version': settings.APPLICATION_VERSION,
}
| 24.666667
| 60
| 0.743243
| 14
| 148
| 7.571429
| 0.642857
| 0.509434
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.182432
| 148
| 6
| 61
| 24.666667
| 0.876033
| 0
| 0
| 0
| 0
| 0
| 0.127517
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.2
| false
| 0
| 0.2
| 0.2
| 0.6
| 0
| 1
| 0
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
|
0
| 5
|
c8ce06bbd5b1f46a97ae6d58c317a668b279f3f4
| 94
|
py
|
Python
|
Python/NeonOcean.S4.Order/NeonOcean/S4/Order/_Entry.py
|
NeonOcean/Order
|
7e7cbdb26e98bb276c7b27cedc75164634e64148
|
[
"CC-BY-4.0"
] | null | null | null |
Python/NeonOcean.S4.Order/NeonOcean/S4/Order/_Entry.py
|
NeonOcean/Order
|
7e7cbdb26e98bb276c7b27cedc75164634e64148
|
[
"CC-BY-4.0"
] | null | null | null |
Python/NeonOcean.S4.Order/NeonOcean/S4/Order/_Entry.py
|
NeonOcean/Order
|
7e7cbdb26e98bb276c7b27cedc75164634e64148
|
[
"CC-BY-4.0"
] | null | null | null |
from __future__ import annotations
from NeonOcean.S4.Order import Loading
Loading.LoadAll()
| 15.666667
| 38
| 0.829787
| 12
| 94
| 6.166667
| 0.75
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.012048
| 0.117021
| 94
| 5
| 39
| 18.8
| 0.879518
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.666667
| 0
| 0.666667
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
7406e864d672d5c9521f4b1ceb78c7fd1649f17e
| 771
|
py
|
Python
|
tests/end_to_end/scenarios/simple_channel_list.py
|
norayr/biboumi
|
805671032d25ee6ce09ed75e8a385c04e9563cdd
|
[
"Zlib"
] | 68
|
2015-01-29T21:07:37.000Z
|
2022-03-20T14:48:07.000Z
|
tests/end_to_end/scenarios/simple_channel_list.py
|
norayr/biboumi
|
805671032d25ee6ce09ed75e8a385c04e9563cdd
|
[
"Zlib"
] | 5
|
2016-10-24T18:34:30.000Z
|
2021-08-31T13:30:37.000Z
|
tests/end_to_end/scenarios/simple_channel_list.py
|
norayr/biboumi
|
805671032d25ee6ce09ed75e8a385c04e9563cdd
|
[
"Zlib"
] | 13
|
2015-12-11T15:19:05.000Z
|
2021-08-31T13:24:35.000Z
|
from scenarios import *
scenario = (
scenarios.multiple_channels_join.scenario,
send_stanza("<iq from='{jid_one}/{resource_one}' id='id1' to='{irc_server_one}' type='get'><query xmlns='http://jabber.org/protocol/disco#items'/></iq>"),
expect_stanza("/iq[@type='result']/disco_items:query",
"/iq/disco_items:query/rsm:set/rsm:count[text()='3']",
"/iq/disco_items:query/rsm:set/rsm:first",
"/iq/disco_items:query/rsm:set/rsm:last",
"/iq/disco_items:query/disco_items:item[@jid='#foo%{irc_server_one}']",
"/iq/disco_items:query/disco_items:item[@jid='#bar%{irc_server_one}']",
"/iq/disco_items:query/disco_items:item[@jid='#baz%{irc_server_one}']"),
)
| 51.4
| 158
| 0.613489
| 104
| 771
| 4.317308
| 0.394231
| 0.244989
| 0.233853
| 0.227171
| 0.454343
| 0.454343
| 0.454343
| 0.280624
| 0.2049
| 0.2049
| 0
| 0.00319
| 0.18677
| 771
| 14
| 159
| 55.071429
| 0.712919
| 0
| 0
| 0
| 0
| 0.083333
| 0.657588
| 0.546044
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.083333
| 0
| 0.083333
| 0
| 0
| 0
| 0
| null | 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 5
|
cdd0d0f81539165312fe95ceaae7b681d772f4fa
| 1,953
|
py
|
Python
|
test/test_reporting_api.py
|
cvent/octopus-deploy-api-client
|
0e03e842e1beb29b132776aee077df570b88366a
|
[
"Apache-2.0"
] | null | null | null |
test/test_reporting_api.py
|
cvent/octopus-deploy-api-client
|
0e03e842e1beb29b132776aee077df570b88366a
|
[
"Apache-2.0"
] | null | null | null |
test/test_reporting_api.py
|
cvent/octopus-deploy-api-client
|
0e03e842e1beb29b132776aee077df570b88366a
|
[
"Apache-2.0"
] | null | null | null |
# coding: utf-8
"""
Octopus Server API
No description provided (generated by Swagger Codegen https://github.com/swagger-api/swagger-codegen) # noqa: E501
OpenAPI spec version: 2019.6.7+Branch.tags-2019.6.7.Sha.aa18dc6809953218c66f57eff7d26481d9b23d6a
Generated by: https://github.com/swagger-api/swagger-codegen.git
"""
from __future__ import absolute_import
import unittest
import octopus_deploy_swagger_client
from octopus_deploy_client.reporting_api import ReportingApi # noqa: E501
from octopus_deploy_swagger_client.rest import ApiException
class TestReportingApi(unittest.TestCase):
"""ReportingApi unit test stubs"""
def setUp(self):
self.api = octopus_deploy_client.reporting_api.ReportingApi() # noqa: E501
def tearDown(self):
pass
def test_custom_action_response_descriptor_octopus_server_web_api_actions_deployments_by_project_report_responder(self):
"""Test case for custom_action_response_descriptor_octopus_server_web_api_actions_deployments_by_project_report_responder
"""
pass
def test_custom_action_response_descriptor_octopus_server_web_api_actions_deployments_by_project_report_responder_spaces(self):
"""Test case for custom_action_response_descriptor_octopus_server_web_api_actions_deployments_by_project_report_responder_spaces
"""
pass
def test_custom_action_response_descriptor_octopus_server_web_api_actions_deployments_xml_responder(self):
"""Test case for custom_action_response_descriptor_octopus_server_web_api_actions_deployments_xml_responder
"""
pass
def test_custom_action_response_descriptor_octopus_server_web_api_actions_deployments_xml_responder_spaces(self):
"""Test case for custom_action_response_descriptor_octopus_server_web_api_actions_deployments_xml_responder_spaces
"""
pass
if __name__ == '__main__':
unittest.main()
| 33.101695
| 136
| 0.794675
| 241
| 1,953
| 5.904564
| 0.282158
| 0.082221
| 0.112439
| 0.168658
| 0.664793
| 0.621223
| 0.621223
| 0.567814
| 0.567814
| 0.567814
| 0
| 0.028829
| 0.147465
| 1,953
| 58
| 137
| 33.672414
| 0.825826
| 0.443932
| 0
| 0.25
| 1
| 0
| 0.007759
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.3
| false
| 0.25
| 0.25
| 0
| 0.6
| 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
| 1
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 1
| 0
|
0
| 5
|
cdf8cf181de16d25fec7ec5f36dca963d64cde05
| 37
|
py
|
Python
|
sample/__init__.py
|
PARC-Consulting/Kafka_LogProducer
|
fbd53185da374e1e10f6f3e5ef3bc836ebda5122
|
[
"BSD-2-Clause"
] | null | null | null |
sample/__init__.py
|
PARC-Consulting/Kafka_LogProducer
|
fbd53185da374e1e10f6f3e5ef3bc836ebda5122
|
[
"BSD-2-Clause"
] | null | null | null |
sample/__init__.py
|
PARC-Consulting/Kafka_LogProducer
|
fbd53185da374e1e10f6f3e5ef3bc836ebda5122
|
[
"BSD-2-Clause"
] | null | null | null |
from core import checklog
checklog()
| 12.333333
| 25
| 0.810811
| 5
| 37
| 6
| 0.8
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.135135
| 37
| 3
| 26
| 12.333333
| 0.9375
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.5
| 0
| 0.5
| 0
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 5
|
cdfc6122f82b969f0d55910d2bfb128e971cf675
| 75
|
py
|
Python
|
connectwise/service/boardstatuses/__init__.py
|
punkrokk/connectwise-rest-api-python
|
f8b2b3c7668b407935e38b8af9d0b5d3b14d9fb2
|
[
"Apache-2.0"
] | 7
|
2017-01-24T06:41:47.000Z
|
2021-04-16T17:34:43.000Z
|
connectwise/service/boardstatuses/__init__.py
|
punkrokk/connectwise-rest-api-python
|
f8b2b3c7668b407935e38b8af9d0b5d3b14d9fb2
|
[
"Apache-2.0"
] | 2
|
2019-10-30T21:32:59.000Z
|
2019-11-01T18:56:39.000Z
|
connectwise/service/boardstatuses/__init__.py
|
punkrokk/connectwise-rest-api-python
|
f8b2b3c7668b407935e38b8af9d0b5d3b14d9fb2
|
[
"Apache-2.0"
] | 7
|
2017-10-17T18:41:18.000Z
|
2019-11-12T20:02:14.000Z
|
from connectwise.service.boardstatuses.get import get_boardstatuses as get
| 37.5
| 74
| 0.88
| 10
| 75
| 6.5
| 0.7
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.08
| 75
| 1
| 75
| 75
| 0.942029
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
a804e1bf7b6242c8104960f730eeb0232923fe93
| 196
|
py
|
Python
|
tests/test_module.py
|
gadomski/noaa-climate-normals
|
2047cd62efa11b231bb97a78c94fa56d2d44c864
|
[
"Apache-2.0"
] | null | null | null |
tests/test_module.py
|
gadomski/noaa-climate-normals
|
2047cd62efa11b231bb97a78c94fa56d2d44c864
|
[
"Apache-2.0"
] | null | null | null |
tests/test_module.py
|
gadomski/noaa-climate-normals
|
2047cd62efa11b231bb97a78c94fa56d2d44c864
|
[
"Apache-2.0"
] | null | null | null |
import unittest
import stactools.noaa_climate_normals
class TestModule(unittest.TestCase):
def test_version(self):
self.assertIsNotNone(stactools.noaa_climate_normals.__version__)
| 19.6
| 72
| 0.806122
| 22
| 196
| 6.772727
| 0.636364
| 0.174497
| 0.268456
| 0.362416
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.127551
| 196
| 9
| 73
| 21.777778
| 0.871345
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.2
| 1
| 0.2
| false
| 0
| 0.4
| 0
| 0.8
| 0
| 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
| 1
| 0
| 0
| 0
|
0
| 5
|
b5588e2cf5b9951af48d825fa2f0a363304a8470
| 99
|
py
|
Python
|
flaskProject/configuration.py
|
SoerenMLS/SecretSanta
|
f75242c824851f5f323c6353d9c79e643292b041
|
[
"MIT"
] | null | null | null |
flaskProject/configuration.py
|
SoerenMLS/SecretSanta
|
f75242c824851f5f323c6353d9c79e643292b041
|
[
"MIT"
] | null | null | null |
flaskProject/configuration.py
|
SoerenMLS/SecretSanta
|
f75242c824851f5f323c6353d9c79e643292b041
|
[
"MIT"
] | null | null | null |
from os import environ
class Config:
SECRET_KEY = environ.get('SECRET_KEY') or 'development'
| 16.5
| 59
| 0.737374
| 14
| 99
| 5.071429
| 0.785714
| 0.253521
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.171717
| 99
| 5
| 60
| 19.8
| 0.865854
| 0
| 0
| 0
| 0
| 0
| 0.212121
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.333333
| 0
| 1
| 0
| 1
| 0
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
b5710b5feb5db8d208c0e8aaa3cb85b8d0e1d30b
| 136
|
py
|
Python
|
ocommerce/store_app/admin.py
|
vanedta36/golf
|
d46fae82cb25fe4ca012b4b0ba9714b8e6e29124
|
[
"bzip2-1.0.6"
] | null | null | null |
ocommerce/store_app/admin.py
|
vanedta36/golf
|
d46fae82cb25fe4ca012b4b0ba9714b8e6e29124
|
[
"bzip2-1.0.6"
] | null | null | null |
ocommerce/store_app/admin.py
|
vanedta36/golf
|
d46fae82cb25fe4ca012b4b0ba9714b8e6e29124
|
[
"bzip2-1.0.6"
] | null | null | null |
from django.contrib import admin
from .models import Product
# Register your models here.
#admin zenithjr
admin.site.register(Product)
| 19.428571
| 32
| 0.808824
| 19
| 136
| 5.789474
| 0.631579
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.125
| 136
| 7
| 33
| 19.428571
| 0.92437
| 0.294118
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.666667
| 0
| 0.666667
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
b592574da69913806ede857ffe480ea028dab81a
| 382
|
py
|
Python
|
cashflows/__init__.py
|
hagarciag/cashflows
|
ca3c7733ec3aeabfeb9b53d7d542eb23843fb1df
|
[
"MIT"
] | 54
|
2017-10-15T09:30:35.000Z
|
2022-03-18T22:54:41.000Z
|
cashflows/__init__.py
|
hagarciag/cashflows
|
ca3c7733ec3aeabfeb9b53d7d542eb23843fb1df
|
[
"MIT"
] | 2
|
2020-10-29T21:27:31.000Z
|
2021-09-18T23:51:34.000Z
|
cashflows/__init__.py
|
hagarciag/cashflows
|
ca3c7733ec3aeabfeb9b53d7d542eb23843fb1df
|
[
"MIT"
] | 22
|
2017-02-15T16:27:56.000Z
|
2021-12-19T01:34:00.000Z
|
from cashflows.analysis import *
from cashflows.tvmm import *
from cashflows.bond import *
from cashflows.common import *
from cashflows.currency import *
from cashflows.depreciation import *
from cashflows.rate import *
from cashflows.inflation import *
from cashflows.loan import *
from cashflows.savings import *
from cashflows.taxing import *
from cashflows.utilityfun import *
| 29.384615
| 36
| 0.811518
| 48
| 382
| 6.458333
| 0.3125
| 0.503226
| 0.674194
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.125654
| 382
| 12
| 37
| 31.833333
| 0.928144
| 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
| 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
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
a908749aec9baacaa0e70c2f6c4ab0dc03e60705
| 53
|
py
|
Python
|
tvdb_api/client/__init__.py
|
h3llrais3r/tvdbapi-v2-client
|
1210df9dd5869ccc5b63149b1b80630310a14f40
|
[
"MIT"
] | 2
|
2021-01-24T07:45:22.000Z
|
2021-11-15T11:29:25.000Z
|
tvdb_api/client/__init__.py
|
h3llrais3r/tvdb_api_v2
|
1210df9dd5869ccc5b63149b1b80630310a14f40
|
[
"MIT"
] | null | null | null |
tvdb_api/client/__init__.py
|
h3llrais3r/tvdb_api_v2
|
1210df9dd5869ccc5b63149b1b80630310a14f40
|
[
"MIT"
] | 1
|
2020-05-07T10:16:15.000Z
|
2020-05-07T10:16:15.000Z
|
# coding: utf-8
from .tvdb_client import TvdbClient
| 13.25
| 35
| 0.773585
| 8
| 53
| 5
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.022222
| 0.150943
| 53
| 3
| 36
| 17.666667
| 0.866667
| 0.245283
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
a9257bce0364bfbbe65ecc86eeab1d75c6a6615a
| 51
|
py
|
Python
|
cmt/__init__.py
|
mwtoews/pymt
|
81a8469b0d0d115d21186ec1d1c9575690d51850
|
[
"MIT"
] | 38
|
2017-06-30T17:10:53.000Z
|
2022-01-05T07:38:03.000Z
|
cmt/__init__.py
|
mwtoews/pymt
|
81a8469b0d0d115d21186ec1d1c9575690d51850
|
[
"MIT"
] | 96
|
2017-04-04T18:52:41.000Z
|
2021-11-01T21:30:48.000Z
|
cmt/__init__.py
|
mwtoews/pymt
|
81a8469b0d0d115d21186ec1d1c9575690d51850
|
[
"MIT"
] | 15
|
2017-05-23T15:40:16.000Z
|
2021-06-14T21:30:28.000Z
|
import sys
import pymt
sys.modules["cmt"] = pymt
| 8.5
| 25
| 0.705882
| 8
| 51
| 4.5
| 0.625
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.176471
| 51
| 5
| 26
| 10.2
| 0.857143
| 0
| 0
| 0
| 0
| 0
| 0.058824
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.666667
| 0
| 0.666667
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
a99ed6f6f9b3861c1cd431b083c9a71cde91be84
| 2,036
|
py
|
Python
|
histogrammar/__init__.py
|
sbrugman/histogrammar-python
|
33cb32a01c2eb1a72d0978c65850e03101548c69
|
[
"Apache-2.0"
] | 30
|
2016-09-25T16:36:06.000Z
|
2021-07-20T09:09:09.000Z
|
histogrammar/__init__.py
|
sbrugman/histogrammar-python
|
33cb32a01c2eb1a72d0978c65850e03101548c69
|
[
"Apache-2.0"
] | 15
|
2016-07-26T19:41:31.000Z
|
2021-02-07T16:30:11.000Z
|
histogrammar/__init__.py
|
sbrugman/histogrammar-python
|
33cb32a01c2eb1a72d0978c65850e03101548c69
|
[
"Apache-2.0"
] | 8
|
2016-09-19T20:48:37.000Z
|
2021-02-07T15:00:24.000Z
|
# flake8: noqa
#!/usr/bin/env python
# Copyright 2016 DIANA-HEP
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from histogrammar.defs import Factory, Container
from histogrammar.primitives.average import Average
from histogrammar.primitives.bag import Bag
from histogrammar.primitives.bin import Bin
from histogrammar.primitives.categorize import Categorize
from histogrammar.primitives.centrallybin import CentrallyBin
from histogrammar.primitives.collection import Collection, Branch, Index, Label, UntypedLabel
from histogrammar.primitives.count import Count
from histogrammar.primitives.deviate import Deviate
from histogrammar.primitives.fraction import Fraction
from histogrammar.primitives.irregularlybin import IrregularlyBin
from histogrammar.primitives.minmax import Minimize, Maximize
from histogrammar.primitives.select import Select
from histogrammar.primitives.sparselybin import SparselyBin
from histogrammar.primitives.stack import Stack
from histogrammar.primitives.sum import Sum
from histogrammar.convenience import Histogram
from histogrammar.convenience import SparselyHistogram
from histogrammar.convenience import Profile
from histogrammar.convenience import SparselyProfile
from histogrammar.convenience import ProfileErr
from histogrammar.convenience import SparselyProfileErr
from histogrammar.convenience import TwoDimensionallyHistogram
from histogrammar.convenience import TwoDimensionallySparselyHistogram
# handy monkey patch functions for pandas and spark dataframes
import histogrammar.dfinterface
| 42.416667
| 93
| 0.845285
| 249
| 2,036
| 6.911647
| 0.453815
| 0.223126
| 0.226612
| 0.153399
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.004964
| 0.109528
| 2,036
| 47
| 94
| 43.319149
| 0.944291
| 0.314342
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 0
| 0
| 0
| null | 1
| 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
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
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