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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
11253f9e8c933e308984a766e8dda8785aed7c20
| 993
|
py
|
Python
|
test_add_number.py
|
PIETRO-ing/automated_test
|
e2c4295516400d3fadd4549b048a27a462fdef63
|
[
"MIT"
] | null | null | null |
test_add_number.py
|
PIETRO-ing/automated_test
|
e2c4295516400d3fadd4549b048a27a462fdef63
|
[
"MIT"
] | null | null | null |
test_add_number.py
|
PIETRO-ing/automated_test
|
e2c4295516400d3fadd4549b048a27a462fdef63
|
[
"MIT"
] | null | null | null |
import add_number
def test_conv_ls():
assert add_number.conv_ls(987) == [9,8,7]
assert add_number.conv_ls(0), [0]
def test_conv_nmbr():
assert add_number.conv_nmbr([9,8,7]) == 987
def test_delete_neg():
assert add_number.delete_neg(-987,5) == [5,9,8,7]
assert add_number.delete_neg(-12354,5) == [5,1,2,3,5,4]
def test_add_integer():
assert add_number.add_integer([9,7,8,9],5) == [9,7,8,9,5]
assert add_number.add_integer([1,2,3],5) == [5,1,2,3]
assert add_number.add_integer([0],5) ==[5,0]
assert add_number.add_integer([9,1,7,8],5) == [9,5,1,7,8]
def test_solution():
assert add_number.solution(0) == 50
assert add_number.solution(123) == 5123
assert add_number.solution(9157) == 95157
assert add_number.solution(98789) == 987895
assert add_number.solution(0) == 50
assert add_number.solution(-123) == -5123
assert add_number.solution(-9898989) == -59898989
assert add_number.solution(-91789) == -591789
| 31.03125
| 61
| 0.660624
| 171
| 993
| 3.625731
| 0.204678
| 0.26129
| 0.41129
| 0.296774
| 0.604839
| 0.396774
| 0.254839
| 0.254839
| 0.254839
| 0.254839
| 0
| 0.159613
| 0.16717
| 993
| 31
| 62
| 32.032258
| 0.590085
| 0
| 0
| 0.086957
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.73913
| 1
| 0.217391
| true
| 0
| 0.043478
| 0
| 0.26087
| 0
| 0
| 0
| 0
| null | 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 0
| 1
| 1
| 0
| 0
| 0
| 0
| 0
|
0
| 6
|
113bd26ea0903502161d6993e93fa1a7873f6589
| 7,217
|
py
|
Python
|
simulations/old/player_model/create_micro_experiment_files.py
|
hawkrobe/fish
|
2000e46c397f7c95bba8ecb0c6afd26013929ff8
|
[
"MIT"
] | 1
|
2015-12-11T16:51:08.000Z
|
2015-12-11T16:51:08.000Z
|
simulations/old/player_model/create_micro_experiment_files.py
|
hawkrobe/fish
|
2000e46c397f7c95bba8ecb0c6afd26013929ff8
|
[
"MIT"
] | 3
|
2020-02-11T21:36:11.000Z
|
2020-11-01T21:25:17.000Z
|
simulations/old/player_model/create_micro_experiment_files.py
|
hawkrobe/couzin_replication
|
ff491639954f0652d6b4b2a318477bb54c38fadf
|
[
"MIT"
] | null | null | null |
import os
import numpy as np
import pandas as pd
import config
from rectangular_world import RectangularWorld
n_players = 5
out_dir = '../../experiments/'
try:
os.makedirs(out_dir)
except:
pass
world = RectangularWorld(None, config.GAME_LENGTH)
length = int(world.game_length)
def make_experiment(experiment, positions, goal_pos, bot_goal_pos):
player_bg_file = out_dir + experiment + '_player_bg.csv'
bot_bg_file = out_dir + experiment + '_bot_bg.csv'
init_pos_file = out_dir + experiment + '_init.csv'
pd.DataFrame(positions, columns = ['x_pos','y_pos']).to_csv(init_pos_file, index = False)
pd.DataFrame(goal_pos, columns = ['x_pos','y_pos']).to_csv(player_bg_file, index = False)
pd.DataFrame(bot_goal_pos, columns = ['x_pos','y_pos']).to_csv(bot_bg_file, index = False)
positions = {}
positions['spot'] = [[100,50],
np.array([400,200]) + np.random.normal(size = 2)*5,
np.array([400,200]) + np.random.normal(size = 2)*5,
np.array([80,200]) + np.random.normal(size = 2)*5,
np.array([80,200]) + np.random.normal(size = 2)*5]
positions['wall'] = [[100,0],
np.array([400,280]),
np.array([410,280]),
np.array([80,200]) + np.random.normal(size = 2)*5,
np.array([80,200]) + np.random.normal(size = 2)*5]
goal = {'far':{}, 'close':{}}
goal['far']['spot'] = np.array([np.array([400,200]) for i in range(length)])
goal['close']['spot'] = np.array([np.array([100,50]) for i in range(length)])
goal['far']['wall'] = np.array([np.array([405,280]) for i in range(length)])
goal['close']['wall'] = np.array([np.array([100,0]) for i in range(length)])
for bg in ['spot', 'wall']:
for bot_bg in ['spot', 'wall']:
for loc in ['far', 'close']:
experiment = bg + '-' + bot_bg + '-' + loc
pos = [positions[bg][0]]
pos += positions[bot_bg][1:]
make_experiment(experiment, np.array(pos), goal[loc][bg], goal['far'][bot_bg])
# ##
# experiment = 'start-apart-come-together'
# positions = np.array([[100,50],
# np.array([400,200]) + np.random.normal(size = 2)*5,
# np.array([400,200]) + np.random.normal(size = 2)*5,
# np.array([80,200]) + np.random.normal(size = 2)*5,
# np.array([80,200]) + np.random.normal(size = 2)*5])
# goal_pos = np.array([np.array([400,200]) for i in range(length)])
# bot_goal_pos = np.array([np.array([400,200]) for i in range(length)])
# make_experiment(experiment, positions, goal_pos, bot_goal_pos)
# ##
# experiment = 'start-apart-stay-apart'
# positions = np.array([[100,50],
# np.array([400,200]) + np.random.normal(size = 2)*5,
# np.array([400,200]) + np.random.normal(size = 2)*5,
# np.array([80,200]) + np.random.normal(size = 2)*5,
# np.array([80,200]) + np.random.normal(size = 2)*5])
# goal_pos = np.array([np.array([100,50]) for i in range(length)])
# bot_goal_pos = np.array([np.array([400,200]) for i in range(length)])
# make_experiment(experiment, positions, goal_pos, bot_goal_pos)
# ##
# experiment = 'start-apart-come-together-alt'
# positions = np.array([[100,0],
# np.array([400,280]),
# np.array([410,280]),
# np.array([80,200]) + np.random.normal(size = 2)*5,
# np.array([80,200]) + np.random.normal(size = 2)*5])
# goal_pos = np.array([np.array([405,280]) for i in range(length)])
# bot_goal_pos = np.array([np.array([405,280]) for i in range(length)])
# make_experiment(experiment, positions, goal_pos, bot_goal_pos)
# ##
# experiment = 'start-apart-stay-apart-alt'
# positions = np.array([[100,0],
# np.array([400,280]),
# np.array([410,280]),
# np.array([80,200]) + np.random.normal(size = 2)*5,
# np.array([80,200]) + np.random.normal(size = 2)*5])
# goal_pos = np.array([np.array([100,0]) for i in range(length)])
# bot_goal_pos = np.array([np.array([405,280]) for i in range(length)])
# make_experiment(experiment, positions, goal_pos, bot_goal_pos)
# ##
# experiment = 'start-apart-come-together-mismatch'
# positions = np.array([[100,50],
# np.array([400,200]) + np.random.normal(size = 2)*5,
# np.array([400,200]) + np.random.normal(size = 2)*5,
# np.array([80,200]) + np.random.normal(size = 2)*5,
# np.array([80,200]) + np.random.normal(size = 2)*5])
# goal_pos = np.array([np.array([400,200]) for i in range(length)])
# bot_goal_pos = np.array([np.array([405,280]) for i in range(length)])
# make_experiment(experiment, positions, goal_pos, bot_goal_pos)
# ##
# experiment = 'start-apart-stay-apart-mismatch'
# positions = np.array([[100,50],
# np.array([400,200]) + np.random.normal(size = 2)*5,
# np.array([400,200]) + np.random.normal(size = 2)*5,
# np.array([80,200]) + np.random.normal(size = 2)*5,
# np.array([80,200]) + np.random.normal(size = 2)*5])
# goal_pos = np.array([np.array([100,50]) for i in range(length)])
# bot_goal_pos = np.array([np.array([405,280]) for i in range(length)])
# make_experiment(experiment, positions, goal_pos, bot_goal_pos)
# ##
# experiment = 'start-apart-come-together-alt-mismatch'
# positions = np.array([[100,0],
# np.array([400,280]),
# np.array([410,280]),
# np.array([80,200]) + np.random.normal(size = 2)*5,
# np.array([80,200]) + np.random.normal(size = 2)*5])
# goal_pos = np.array([np.array([405,280]) for i in range(length)])
# bot_goal_pos = np.array([np.array([400,200]) for i in range(length)])
# make_experiment(experiment, positions, goal_pos, bot_goal_pos)
# ##
# experiment = 'start-apart-stay-apart-alt-mismatch'
# positions = np.array([[100,0],
# np.array([400,280]),
# np.array([410,280]),
# np.array([80,200]) + np.random.normal(size = 2)*5,
# np.array([80,200]) + np.random.normal(size = 2)*5])
# goal_pos = np.array([np.array([100,0]) for i in range(length)])
# bot_goal_pos = np.array([np.array([400,200]) for i in range(length)])
# make_experiment(experiment, positions, goal_pos, bot_goal_pos)
# experiment = 'start-together-come-apart'
# positions = np.array([[400,200],
# np.array([400,200]) + np.random.normal(size = 2)*5,
# np.array([400,200]) + np.random.normal(size = 2)*5,
# np.array([80,200]) + np.random.normal(size = 2)*5,
# np.array([80,200]) + np.random.normal(size = 2)*5])
# goal_pos = np.array([np.array([100,50]) for i in range(length)])
# bot_goal_pos = np.array([np.array([400,200]) for i in range(length)])
# make_experiment(experiment, positions, goal_pos, bot_goal_pos)
| 37.201031
| 94
| 0.563531
| 1,038
| 7,217
| 3.812139
| 0.073218
| 0.173364
| 0.094516
| 0.14607
| 0.86328
| 0.816528
| 0.815517
| 0.805914
| 0.805914
| 0.779631
| 0
| 0.089174
| 0.244839
| 7,217
| 193
| 95
| 37.393782
| 0.636881
| 0.677705
| 0
| 0.139535
| 0
| 0
| 0.071719
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.023256
| false
| 0.023256
| 0.116279
| 0
| 0.139535
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
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| null | 0
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| 0
| 0
|
0
| 6
|
114ee8e6b7274d5fbe9a34ef4d3616c369119150
| 42
|
py
|
Python
|
mgeconvert/backend/ir_to_onnx/__init__.py
|
Zhiy-Zhang/mgeconvert
|
55550c3f065697919b355455e0070b96398bbe19
|
[
"Apache-2.0"
] | 42
|
2020-12-19T04:16:11.000Z
|
2022-03-31T02:40:20.000Z
|
mgeconvert/backend/ir_to_onnx/__init__.py
|
Zhiy-Zhang/mgeconvert
|
55550c3f065697919b355455e0070b96398bbe19
|
[
"Apache-2.0"
] | 37
|
2021-01-04T11:05:38.000Z
|
2022-03-22T08:48:14.000Z
|
mgeconvert/backend/ir_to_onnx/__init__.py
|
Zhiy-Zhang/mgeconvert
|
55550c3f065697919b355455e0070b96398bbe19
|
[
"Apache-2.0"
] | 9
|
2021-01-04T12:17:11.000Z
|
2022-01-18T09:50:50.000Z
|
from .onnx_converter import OnnxConverter
| 21
| 41
| 0.880952
| 5
| 42
| 7.2
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.095238
| 42
| 1
| 42
| 42
| 0.947368
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
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| 1
| 0
| null | 0
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| 1
| 0
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| 0
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| 0
| 0
| 0
| 0
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| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 6
|
fed70e9f4b98e4367e9704a63da414c6f2ac9d73
| 211
|
py
|
Python
|
conch/analysis/__init__.py
|
mmcauliffe/Conch
|
7668612d7a610d0f5ae3332f990e71b26c5e8b34
|
[
"MIT"
] | 33
|
2015-06-10T19:36:54.000Z
|
2017-09-18T23:57:46.000Z
|
conch/analysis/__init__.py
|
mmcauliffe/Conch
|
7668612d7a610d0f5ae3332f990e71b26c5e8b34
|
[
"MIT"
] | 5
|
2015-03-22T07:05:21.000Z
|
2017-08-16T03:48:19.000Z
|
conch/analysis/__init__.py
|
mmcauliffe/Conch
|
7668612d7a610d0f5ae3332f990e71b26c5e8b34
|
[
"MIT"
] | 10
|
2015-04-29T05:51:51.000Z
|
2017-07-12T18:52:18.000Z
|
from .pitch import ReaperPitchTrackFunction, PraatPitchTrackFunction, PitchTrackFunction
from .mfcc import PraatMfccFunction, MfccFunction
from .formants import PraatFormantTrackFunction, FormantTrackFunction
| 35.166667
| 88
| 0.881517
| 16
| 211
| 11.625
| 0.75
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.085308
| 211
| 6
| 89
| 35.166667
| 0.963731
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 1
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
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| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 6
|
fee60049ba61cf282804c3bc3250a12b7df2793c
| 39,718
|
py
|
Python
|
BTC_Alpha_0503_input_list.py
|
chenhq/Data-Mining-on-BTC-Trading-Statistics
|
f221e72a0551c77b3ab2dcb6c4448d0c743b54cc
|
[
"MIT"
] | 8
|
2020-08-04T06:28:52.000Z
|
2022-03-07T08:02:59.000Z
|
BTC_Alpha_0503_input_list.py
|
zie225/Data-Mining-on-BTC-Trading-Statistics
|
f221e72a0551c77b3ab2dcb6c4448d0c743b54cc
|
[
"MIT"
] | null | null | null |
BTC_Alpha_0503_input_list.py
|
zie225/Data-Mining-on-BTC-Trading-Statistics
|
f221e72a0551c77b3ab2dcb6c4448d0c743b54cc
|
[
"MIT"
] | 4
|
2020-08-04T06:28:42.000Z
|
2022-01-20T00:35:56.000Z
|
# coding: utf-8
# 我觉得变量太多的alpha factor我暂时搁置，以及我觉得rank函数比较奇怪，因为range太大了，是否需要设置一个窗口呢？
#
#
# ## Dropped Index:
# - Alpha30(要用到fama三因子)
# - Alpha75(要用到BENCHMARKINDEX)
# - Alpha143(要用到SELF函数)
# - Alpha149(要用到BENCHMARKINDEX)
# - Alpha181(要用到BENCHMARKINDEX)
# - Alpha182(要用到BENCHMARKINDEX)
### 对于：？较为复杂的表达式，我都先用一些中间变量存储中间运算的结果，以下均采用这一做法，不赘述
import numpy as np, pandas as pd, matplotlib.pyplot as plt
from scipy.stats.stats import pearsonr
from scipy.stats.stats import spearmanr
from BTC_Alpha_func import *
def Alpha1(para_list):
return -1 * CORR(RANK(DELTA(LOG(VOLUME),para_list[0])), RANK((CLOSE-OPEN)/OPEN), para_list[1])
def Alpha2(para_list):
return (-1 * DELTA((((CLOSE - LOW) - (HIGH - CLOSE)) / (HIGH - LOW)), para_list[0])).fillna(0)
def Alpha3(para_list):
cache = CLOSE - ((~(CLOSE>DELAY(CLOSE,para_list[0])))*MIN(LOW,DELAY(CLOSE,para_list[0]))\
+ (~(CLOSE>DELAY(CLOSE,para_list[0])))*MAX(HIGH,DELAY(CLOSE,para_list[0])))
return SUM((~(CLOSE==DELAY(CLOSE,1)) * cache), para_list[1])
#这里保留1,是因为我觉得Volume/mean(volume,window_size)还是有明确的概念的
def Alpha4(para_list):
#tail计算的是倒数第二个冒号后面的结果
tail = (((VOLUME / MEAN(VOLUME,para_list[0])) <= 1) * 1\
- ~((VOLUME / MEAN(VOLUME,para_list[0])) <= 1) * (-1))
#med计算的是中间的一个判断句（第1个冒号之后）的结果
med = ((SUM(CLOSE, para_list[1]) / para_list[1]) < ((SUM(CLOSE, para_list[2]) / para_list[2]) - STD(CLOSE, para_list[2]))) * 1\
+ ~(((SUM(CLOSE, para_list[1]) / para_list[1]) < ((SUM(CLOSE, para_list[2]) / para_list[2]) - STD(CLOSE, para_list[2])))) * tail
return (((SUM(CLOSE, para_list[2]) / para_list[2]) + STD(CLOSE, para_list[2])) < (SUM(CLOSE, para_list[1]) / para_list[1])) * (-1)\
+ ~(((SUM(CLOSE, para_list[2]) / para_list[2]) + STD(CLOSE, para_list[2])) < (SUM(CLOSE, para_list[1]) / para_list[1])) * med
def Alpha5(para_list):
return (-1 * TSMAX(CORR(TSRANK(VOLUME, para_list[0]), TSRANK(HIGH, para_list[0]), para_list[0]), para_list[1]))
#here para_list[0] is a float between(0,1)
def Alpha6(para_list):
return (RANK(SIGN(DELTA((((OPEN * para_list[0]) + (HIGH * (1.0-para_list[0])))), para_list[1])))* (-1))
def Alpha7(para_list):
return ((RANK(MAX((VWAP - CLOSE), para_list[0])) + RANK(MIN((VWAP - CLOSE), para_list[0]))) * RANK(DELTA(VOLUME, para_list[0])))
#here para_list[0] is a float between(0,1)
def Alpha8(para_list):
return RANK(DELTA(((((HIGH + LOW) / 2) * para_list[0]) + (VWAP * (1.0-para_list[0]))), para_list[1]) * -1)
#所有的SMA我都加上了assert，我其实在函数里也已经加上了assert，以下不赘述
def Alpha9(para_list):
assert para_list[2] <= para_list[1]
return SMA(((HIGH+LOW)/2-(DELAY(HIGH,para_list[0])+DELAY(LOW,para_list[0]))/2)*(HIGH-LOW)/VOLUME,para_list[1],para_list[2])
#para_list[2] 原来就是平方的，这里先改成了para_list[2]
def Alpha10(para_list):
return RANK(MAX((STD(RET, para_list[0]) * (RET < 0) + (CLOSE * (~(RET < 0)))**para_list[2], para_list[1])))
def Alpha11(para_list):
return SUM(((CLOSE-LOW)-(HIGH-CLOSE))/(HIGH-LOW)*VOLUME, para_list[0])
def Alpha12(para_list):
return (RANK((OPEN - (SUM(VWAP, para_list[0]) / para_list[0])))) * (-1 * (RANK(ABS((CLOSE - VWAP)))))
#para_list[0]原来就是开方的，这里也先改了
def Alpha13(para_list):
return (((HIGH * LOW)**para_list[0]) - VWAP) #这个是取调和平均的 我们就算他不用优化把= =
def Alpha14(para_list):
return CLOSE-DELAY(CLOSE, para_list[0])
#这里的1.0保留
def Alpha15(para_list):
return OPEN/DELAY(CLOSE,para_list[0])-1.0
def Alpha16(para_list):
return (-1 * TSMAX(RANK(CORR(RANK(VOLUME), RANK(VWAP), para_list[0])), para_list[0]))
def Alpha17(para_list):
return RANK((VWAP - MAX(VWAP, para_list[0])))**(DELTA(CLOSE, para_list[1]))
def Alpha18(para_list):
return CLOSE/DELAY(CLOSE,para_list[0])
def Alpha19(para_list):
return (CLOSE <= DELAY(CLOSE,para_list[0])) * (CLOSE - DELAY(CLOSE,para_list[0]))/DELAY(CLOSE,para_list[0])\
+ (CLOSE > DELAY(CLOSE,para_list[0])) * (CLOSE - DELAY(CLOSE,para_list[0])/CLOSE)
#100.0保留，表示百分数，以下同
def Alpha20(para_list):
return (CLOSE-DELAY(CLOSE,para_list[0]))/DELAY(CLOSE,para_list[0])*100.0
def Alpha21(para_list):
return REGBETA(MEAN(CLOSE,para_list[0]),SEQUENCE(para_list[0]),para_list[0])
def Alpha22(para_list):
return MEAN((CLOSE-MEAN(CLOSE,para_list[0]))/MEAN(CLOSE,para_list[0])\
-DELAY((CLOSE-MEAN(CLOSE,para_list[0]))/MEAN(CLOSE,para_list[0]),para_list[1]),para_list[2])
def Alpha23(para_list):
return SMA((CLOSE> DELAY(CLOSE,para_list[0]))*STD(CLOSE,para_list[1]),para_list[1],para_list[2])\
/(SMA((CLOSE> DELAY(CLOSE,para_list[0]))*STD(CLOSE,para_list[1]),para_list[1],para_list[2])\
+SMA((CLOSE<=DELAY(CLOSE,para_list[0]))*STD(CLOSE,para_list[1]),para_list[1],para_list[2]))*100.0
def Alpha24(para_list):
return SMA(CLOSE-DELAY(CLOSE,para_list[0]),para_list[0],para_list[1])
def Alpha25(para_list):
return ((-1 * RANK((DELTA(CLOSE,para_list[0]) * (1 - RANK(DECAYLINEAR((VOLUME / MEAN(VOLUME,para_list[1])), para_list[2])))))) * (1.0 + RANK(SUM(RET, para_list[3]))))
def Alpha26(para_list):
return (((SUM(CLOSE, para_list[0]) / para_list[0]) - CLOSE)) + ((CORR(VWAP, DELAY(CLOSE, para_list[1]), para_list[2])))
def Alpha27(para_list):
return WMA((CLOSE-DELAY(CLOSE,para_list[0]))/DELAY(CLOSE,para_list[0])*100.0\
+(CLOSE-DELAY(CLOSE,para_list[1]))/DELAY(CLOSE,para_list[1])*100.0,para_list[2])
#这里的para_list[3]原先设置为9，para_list[4],para_list[5]分别的设置为3和2
def Alpha28(para_list):
return para_list[4]*SMA((CLOSE-TSMIN(LOW,para_list[0]))/(TSMAX(HIGH,para_list[0])-TSMIN(LOW,para_list[0]))*100,para_list[1],para_list[2])\
-para_list[5]*SMA(SMA((CLOSE-TSMIN(LOW,para_list[0]))/(MAX( HIGH,para_list[3])-TSMAX(LOW,para_list[0]))*100,para_list[1],para_list[2]),para_list[1],para_list[2])
def Alpha29(para_list):
return (CLOSE-DELAY(CLOSE,para_list[0]))/DELAY(CLOSE,para_list[0])*VOLUME
def Alpha30(para_list):
return CLOSE - CLOSE
def Alpha31(para_list):
return (CLOSE-MEAN(CLOSE,para_list[0]))/MEAN(CLOSE,para_list[0])*100.0
def Alpha32(para_list):
return (-1 * SUM(RANK(CORR(RANK(HIGH), RANK(VOLUME), para_list[0])), para_list[0]))
def Alpha33(para_list):
return ((((-1 * TSMIN(LOW, para_list[0])) + DELAY(TSMIN(LOW, para_list[0]), para_list[0])) * RANK(((SUM(RET, para_list[1]) - SUM(RET, para_list[2])) / (para_list[3]))))* TSRANK(VOLUME, para_list[0]))
def Alpha34(para_list):
return MEAN(CLOSE,para_list[0])/CLOSE
#here para_list[2] is a float between(0,1)
def Alpha35(para_list):
return (-MIN(RANK(DECAYLINEAR(DELTA(OPEN, para_list[0]), para_list[1])),\
RANK(DECAYLINEAR(CORR((VOLUME), ((OPEN * para_list[2]) + (OPEN *(1-para_list[2]))), para_list[3]),para_list[4]))))
def Alpha36(para_list):
return RANK(SUM(CORR(RANK(VOLUME), RANK(VWAP), para_list[0]), para_list[1]))
def Alpha37(para_list):
return (- RANK(((SUM(OPEN, para_list[0]) * SUM(RET, para_list[0]))\
- DELAY((SUM(OPEN, para_list[0]) * SUM(RET, para_list[0])), para_list[1]))))
def Alpha38(para_list):
return ((SUM(HIGH, para_list[0])/para_list[0]) < HIGH) * (-1.0 * DELTA(HIGH, para_list[1]))
def Alpha39(para_list):
return (-(RANK(DECAYLINEAR(DELTA((CLOSE), para_list[0]),para_list[1]))\
-RANK(DECAYLINEAR(CORR(((VWAP * para_list[2]) + (OPEN * (1-para_list[2]))), SUM(MEAN(VOLUME,para_list[3]), para_list[4]), para_list[5]), para_list[6]))))
def Alpha40(para_list):
return SUM((CLOSE > DELAY(CLOSE,para_list[0]))*VOLUME, para_list[1])\
/SUM((CLOSE<= DELAY(CLOSE,para_list[0]))*VOLUME, para_list[1])*100.0
def Alpha41(para_list):
return (RANK(-MAX(DELTA((VWAP), para_list[0]), para_list[1])))
def Alpha42(para_list):
return ((-RANK(STD(HIGH, para_list[0]))) * CORR(HIGH, VOLUME, para_list[0]))
def Alpha43(para_list):
return SUM(VOLUME * (CLOSE>DELAY(CLOSE,para_list[0]))\
-VOLUME *(~(CLOSE>DELAY(CLOSE,para_list[0]))) * (CLOSE<DELAY(CLOSE,para_list[0])), para_list[1])
def Alpha44(para_list):
return TSRANK(DECAYLINEAR(CORR(LOW, MEAN(VOLUME,para_list[0]), para_list[1]), para_list[2]), para_list[3])\
+ TSRANK(DECAYLINEAR(DELTA(VWAP, para_list[4]), para_list[5]), para_list[6])
def Alpha45(para_list):
return RANK(DELTA(CLOSE * para_list[0] + OPEN * (1-para_list[0]), para_list[1]))\
* RANK(CORR(VWAP, MEAN(VOLUME, para_list[2]), para_list[3]))
#这里4.0也有很明确的概念，就是表示4个window的平均值
def Alpha46(para_list):
return (MEAN(CLOSE,para_list[0])\
+ MEAN(CLOSE,para_list[1])\
+ MEAN(CLOSE,para_list[2])\
+ MEAN(CLOSE,para_list[3]))/(4.0*CLOSE)
def Alpha47(para_list):
return SMA((TSMAX(HIGH,para_list[0])-CLOSE)/(TSMAX(HIGH,para_list[0]) - TSMIN(LOW,para_list[0]))*100.0, para_list[1], para_list[2])
def Alpha48(para_list):
return (-(RANK(SIGN(CLOSE - DELAY(CLOSE, para_list[0]))\
+ SIGN(DELAY(CLOSE, para_list[0]) - DELAY(CLOSE, para_list[1]))\
+ SIGN(DELAY(CLOSE, para_list[1]) - DELAY(CLOSE, para_list[2])))\
* SUM(VOLUME, para_list[1] + para_list[2])) / SUM(VOLUME, para_list[3]))
def Alpha49(para_list):
dividend = SUM(MAX(ABS(HIGH-DELAY(HIGH,para_list[0])),ABS(LOW-DELAY(LOW,para_list[0]))),para_list[1])
divisor = SUM(~((HIGH+LOW) >= (DELAY(HIGH,para_list[0]) + DELAY(LOW,para_list[0])))\
*MAX(ABS(HIGH-DELAY(HIGH,para_list[0])),ABS(LOW-DELAY(LOW,para_list[0]))),para_list[1])
return divisor/dividend
def Alpha50(para_list):
subtend = SUM(~((HIGH+LOW) <= (DELAY(HIGH,para_list[0]) + DELAY(LOW,para_list[0])))\
*MAX(ABS(HIGH-DELAY(HIGH,para_list[0])),ABS(LOW-DELAY(LOW,para_list[0]))),para_list[1])\
/(SUM(MAX(ABS(HIGH-DELAY(HIGH,para_list[0])),ABS(LOW-DELAY(LOW,para_list[0]))),para_list[1]))
minuend = SUM(~((HIGH+LOW) >= (DELAY(HIGH,para_list[0]) + DELAY(LOW,para_list[0])))\
*MAX(ABS(HIGH-DELAY(HIGH,para_list[0])),ABS(LOW-DELAY(LOW,para_list[0]))),para_list[1])\
/(SUM(MAX(ABS(HIGH-DELAY(HIGH,para_list[0])),ABS(LOW-DELAY(LOW,para_list[0]))),para_list[1]))
return subtend - minuend
def Alpha51(para_list):
return SUM(~((HIGH+LOW) <= (DELAY(HIGH,para_list[0]) + DELAY(LOW,para_list[0])))\
*MAX(ABS(HIGH-DELAY(HIGH,para_list[0])),ABS(LOW-DELAY(LOW,para_list[0]))),para_list[1])\
/(SUM(MAX(ABS(HIGH-DELAY(HIGH,para_list[0])),ABS(LOW-DELAY(LOW,para_list[0]))),para_list[1]))
def Alpha52(para_list):
return SUM(MAX(0, HIGH-DELAY((HIGH+LOW+CLOSE)/3,para_list[0])), para_list[1])\
/SUM(MAX(0, DELAY((HIGH+LOW+CLOSE)/3,para_list[0]) - LOW),para_list[1])* 100.0
def Alpha53(para_list):
return COUNT(CLOSE>DELAY(CLOSE,para_list[0]),para_list[1])/para_list[1]*100.0
def Alpha54(para_list):
return (-RANK((STD(ABS(CLOSE - OPEN), para_list[0]) + (CLOSE - OPEN)) + CORR(CLOSE, OPEN, para_list[0])))
#part_B1_value中有/2，/4算是decay sum吧。。，我也替换成了两个参数
def Alpha55(para_list):
part_C_value = MAX(ABS(HIGH-DELAY(CLOSE,para_list[0])),\
ABS(LOW- DELAY(CLOSE,para_list[0])))
part_A_value = (CLOSE+(CLOSE-OPEN)/2.0-DELAY(OPEN,para_list[0]))
part_B1_cond = (ABS(HIGH-DELAY(CLOSE,para_list[0])) > ABS(LOW -DELAY(CLOSE,para_list[0])))\
&(ABS(HIGH-DELAY(CLOSE,para_list[0])) > ABS(HIGH-DELAY(LOW, para_list[0])))
part_B2_cond = (ABS(LOW- DELAY(CLOSE,para_list[0])) > ABS(HIGH-DELAY(LOW, para_list[0])))\
&(ABS(LOW- DELAY(CLOSE,para_list[0])) > ABS(HIGH-DELAY(CLOSE,para_list[0])))
part_B1_value= ABS(HIGH-DELAY(CLOSE,para_list[0])) + ABS(LOW -DELAY(CLOSE,para_list[0]))/para_list[1]\
+ ABS(DELAY(CLOSE,para_list[0])-DELAY(OPEN, para_list[0]))/para_list[2]
part_B2nvalue= (ABS(HIGH-DELAY(LOW ,para_list[0])) + ABS(DELAY(CLOSE,para_list[0])-DELAY(OPEN,para_list[0]))/para_list[2])
part_B_value = (part_B1_cond | (~part_B1_cond) & part_B2_cond) * part_B1_value\
+ ((~part_B1_cond) & (~part_B2_cond)) * part_B2nvalue
return SUM(part_A_value/part_B_value*part_C_value, para_list[1])
#这个signal是返回一个bool list，与原文对照过了，表达式一致，很迷
def Alpha56(paralist):
return RANK((OPEN - TSMIN(OPEN, para_list[0]))) < RANK((RANK(CORR(SUM(((HIGH + LOW)/2.0), para_list[1]), SUM(MEAN(VOLUME,para_list[2]), para_list[3]), para_list[4]))**para_list[5]))
def Alpha57(para_list):
return SMA((CLOSE-TSMIN(LOW,para_list[0]))/(TSMAX(HIGH,para_list[0])-TSMIN(LOW,para_list[0])),para_list[1],para_list[2])
def Alpha58(para_list):
return COUNT(CLOSE>DELAY(CLOSE,para_list[0]),para_list[1])/para_list[1]
def Alpha59(para_list):
return SUM((CLOSE!=DELAY(CLOSE,para_list[0]))*CLOSE\
- ((CLOSE>DELAY(CLOSE,para_list[0]))* MIN(LOW, DELAY(CLOSE,para_list[0]))\
+ ~(CLOSE>DELAY(CLOSE,para_list[0]) * MAX(HIGH,DELAY(CLOSE,para_list[0])))), para_list[1])
def Alpha60(para_list):
return SUM(((CLOSE-LOW)-(HIGH-CLOSE))/(HIGH-LOW)*VOLUME,para_list[0])
def Alpha61(para_list):
return (-MAX(RANK(DECAYLINEAR(DELTA(VWAP,para_list[0]),para_list[1])),\
RANK(DECAYLINEAR(RANK(CORR(LOW,MEAN(VOLUME,para_list[2]), para_list[3])),para_list[4]))))
def Alpha62(para_list):
return (-CORR(HIGH, RANK(VOLUME), para_list[0]))
def Alpha63(para_list):
return (SMA(MAX(CLOSE-DELAY(CLOSE,para_list[0]),0),para_list[1],para_list[2])\
/SMA(ABS(CLOSE-DELAY(CLOSE,para_list[0])) ,para_list[1],para_list[2]))
def Alpha64(para_list):
return -MAX(RANK(DECAYLINEAR(CORR(RANK(VWAP), RANK(VOLUME), para_list[0]),para_list[0])),\
RANK(DECAYLINEAR(MAX(CORR(RANK(CLOSE), RANK(MEAN(VOLUME,para_list[1])), para_list[0]), para_list[2]), para_list[3])))
def Alpha65(para_list):
return MEAN(CLOSE,para_list[0])/CLOSE
def Alpha66(para_list):
return (CLOSE-MEAN(CLOSE,para_list[0]))/MEAN(CLOSE,para_list[0])
def Alpha67(para_list):
return SMA(MAX(CLOSE-DELAY(CLOSE,),0),para_list[1],para_list[2])\
/SMA(ABS(CLOSE-DELAY(CLOSE,para_list[0])),para_list[1],para_list[2])
def Alpha68(para_list):
return SMA(((HIGH+LOW)/2-(DELAY(HIGH,para_list[0])+DELAY(LOW,para_list[0]))/para_list[0])*(HIGH-LOW)/VOLUME,para_list[1],para_list[2])
def Alpha69(para_list):
cache= (SUM(DTM,para_list[0])>SUM(DBM,para_list[0])) * (SUM(DTM,para_list[0])- SUM(DBM,para_list[0]))/SUM(DTM,para_list[0]) +(~(SUM(DTM,para_list[0])>SUM(DBM,para_list[0])) & (SUM(DTM,para_list[0])!=SUM(DBM,para_list[0])) * (SUM(DTM,para_list[0])- SUM(DBM,para_list[0]))/SUM(DBM,para_list[0]))
return cache.fillna(method='ffill').fillna(method='bfill')
def Alpha70(para_list):
return STD(AMOUNT,para_list[0])
def Alpha71(para_list):
return (CLOSE-MEAN(CLOSE,para_list[0]))/MEAN(CLOSE,para_list[0])
def Alpha72(para_list):
return SMA((TSMAX(HIGH,para_list[0])-CLOSE)/(TSMAX(HIGH,para_list[0])-TSMIN(LOW,para_list[0])),para_list[1],para_list[2])
def Alpha73(para_list):
return (TSRANK(DECAYLINEAR(DECAYLINEAR(CORR(CLOSE, VOLUME,para_list[0]),para_list[1]),para_list[2]),para_list[3])-RANK(DECAYLINEAR(CORR(VWAP, MEAN(VOLUME,30),4),3))) * -1
#para_list[0] is a float between (0,1)
def Alpha74(para_list):
return RANK(CORR(SUM(((LOW * para_list[0]) + VWAP*(1-para_list[0])), para_list[1]), SUM(MEAN(VOLUME,para_list[2]),para_list[1]), para_list[3])) + RANK(CORR(RANK(VWAP), RANK(VOLUME), para_list[4]))
def Alpha75(para_list):
return CLOSE - CLOSE
def Alpha76(para_list):
return STD(ABS((CLOSE/DELAY(CLOSE,para_list[0])-1.0))/VOLUME,para_list[1])/MEAN(ABS((CLOSE/DELAY(CLOSE,para_list[0])-1.0))/VOLUME,para_list[1])
def Alpha77(para_list):
return MIN(RANK(DECAYLINEAR(((((HIGH + LOW) / 2) + HIGH) - (VWAP+HIGH)),para_list[0])),RANK(DECAYLINEAR(CORR(((HIGH + LOW) / 2), MEAN(VOLUME,para_list[1]),para_list[2]),para_list[3])))
#here para_list[1] is a float
def Alpha78(para_list):
return ((HIGH+LOW+CLOSE)/3-MEAN((HIGH+LOW+CLOSE)/3,para_list[0]))/(para_list[1]*MEAN(ABS(CLOSE-MEAN((HIGH+LOW+CLOSE)/3,para_list[0])),para_list[0]))
def Alpha79(para_list):
return SMA(MAX(CLOSE-DELAY(CLOSE,para_list[0]),0),para_list[1],para_list[2])\
/SMA(ABS(CLOSE-DELAY(CLOSE,para_list[0])) ,para_list[1],para_list[2])
def Alpha80(para_list):
return (VOLUME-DELAY(VOLUME,para_list[0]))/DELAY(VOLUME,para_list[0])
def Alpha81(para_list):
return SMA(VOLUME,para_list[0],para_list[1])
def Alpha82(para_list):
return SMA((TSMAX(HIGH,para_list[0])-CLOSE)/(TSMAX(HIGH,para_list[0])-TSMIN(LOW,para_list[0])),para_list[1],para_list[2])
def Alpha83(para_list):
return (-RANK(COVIANCE(RANK(HIGH), RANK(VOLUME), para_list[0])))
def Alpha84(para_list):
return SUM((CLOSE>DELAY(CLOSE,para_list[0]))*VOLUME+\
(~(CLOSE>DELAY(CLOSE,para_list[0]))&(CLOSE<DELAY(CLOSE,para_list[0])))*(-VOLUME),para_list[1])
def Alpha85(para_list):
return TSRANK((VOLUME / MEAN(VOLUME,para_list[0])),para_list[0])\
* TSRANK((-1 * DELTA(CLOSE, para_list[1])), para_list[2])
#para_list[0] is a float
def Alpha86(para_list):
return ( para_list[0] < (((DELAY(CLOSE, para_list[1]) - DELAY(CLOSE, para_list[2])) / para_list[2]) - ((DELAY(CLOSE, para_list[3]) - CLOSE) / para_list[3]))) *(-1.0)\
+ (~(para_list[0] < (((DELAY(CLOSE, para_list[1]) - DELAY(CLOSE, para_list[2])) / para_list[2]) - ((DELAY(CLOSE, para_list[3]) - CLOSE) / para_list[3]))))\
* ((((( DELAY(CLOSE, para_list[1]) - DELAY(CLOSE, para_list[2])) / para_list[2]) - ((DELAY(CLOSE, para_list[3]) - CLOSE) / para_list[3])) < 0) * 1.0\
+ (~((((DELAY(CLOSE, para_list[1]) - DELAY(CLOSE, para_list[2])) / para_list[2]) - ((DELAY(CLOSE, para_list[3]) - CLOSE) / para_list[3])) < 0)) *(-1.0))
#LOW*0.9 + LOW*0.1 难道不就是LOW吗？改为HIGH*para_list[4] + LOW*(1-para_list[4])，因此para_list[4] is a float between 0 and 1
def Alpha87(para_list):
return (-(RANK(DECAYLINEAR(DELTA(VWAP, para_list[0]), para_list[1]))\
+ TSRANK(DECAYLINEAR((((LOW) - VWAP) / (OPEN - ((HIGH*para_list[4] + LOW*(1-para_list[4])) / 2))), para_list[2]), para_list[3])))
def Alpha88(para_list):
return (CLOSE-DELAY(CLOSE,para_list[0]))/DELAY(CLOSE,para_list[0])
def Alpha89(para_list):
return (SMA(CLOSE,para_list[0],para_list[3])\
-SMA(CLOSE,para_list[1],para_list[4])\
-SMA(SMA(CLOSE,para_list[0],para_list[3])\
-SMA(CLOSE,para_list[1],para_list[4]),para_list[2],para_list[5]))
def Alpha90(para_list):
return (-RANK(CORR(RANK(VWAP), RANK(VOLUME), para_list[0])))
def Alpha91(para_list):
return (-(RANK((CLOSE - MAX(CLOSE, para_list[0])))\
*RANK(CORR((MEAN(VOLUME,para_list[1])), LOW, para_list[0]))))
#para_list[0] is a float between 0 and 1
def Alpha92(para_list):
return -MAX(RANK(DECAYLINEAR(DELTA(((CLOSE* para_list[0])+ (VWAP*(1-para_list[0]))),para_list[1]),para_list[2])),\
TSRANK(DECAYLINEAR(ABS(CORR((MEAN(VOLUME,para_list[3])), CLOSE, para_list[4])), para_list[5]), para_list[6]))
def Alpha93(para_list):
return SUM(~(OPEN>=DELAY(OPEN,para_list[0]))*MAX((OPEN-LOW),(OPEN-DELAY(OPEN,para_list[0]))),para_list[1])
def Alpha94(para_list):
return SUM((CLOSE>DELAY(CLOSE,para_list[0])*VOLUME\
+ (~(CLOSE>DELAY(CLOSE,para_list[0])))*(-VOLUME)*(CLOSE<DELAY(CLOSE,para_list[0]))),para_list[1])
def Alpha95(para_list):
return STD(AMOUNT,para_list[0])
def Alpha96(para_list):
return SMA(SMA((CLOSE-TSMIN(LOW,para_list[0]))/(TSMAX(HIGH,para_list[0])-TSMIN(LOW,para_list[0])),para_list[1],para_list[2]),para_list[3],para_list[4])
#跟Alpha95重复
def Alpha97(para_list):
return STD(VOLUME,para_list[0])
#para_list[2] is a float
def Alpha98(para_list):
condition = ((DELTA((SUM(CLOSE, para_list[0]) / para_list[0]), para_list[0]) / DELAY(CLOSE, para_list[0])) <= para_list[2])
return -(condition * ((CLOSE - TSMIN(CLOSE, para_list[0])))\
+(~condition) * DELTA(CLOSE, para_list[1]))
def Alpha99(para_list):
return (-RANK(COVIANCE(RANK(CLOSE), RANK(VOLUME), para_list[0])))
#跟97，95重复
def Alpha100(para_list):
return STD(VOLUME,para_list[0])
'''just return True & False, para_list[4] is a float between 0 and 1'''
def Alpha101(para_list):
return (-(RANK(CORR(CLOSE, SUM(MEAN(VOLUME,para_list[0]), para_list[1]), para_list[2])) <
RANK(CORR(RANK(((HIGH * para_list[4]) + (VWAP * (1-para_list[4])))), RANK(VOLUME), para_list[3]))))
def Alpha102(para_list):
return SMA(MAX(VOLUME-DELAY(VOLUME,para_list[0]),0),para_list[1],para_list[2])\
/SMA(ABS(VOLUME-DELAY(VOLUME,para_list[0])) ,para_list[1],para_list[2])
def Alpha103(para_list):
return ((para_list[0]-LOWDAY(LOW,para_list[0]))/para_list[0])
def Alpha104(para_list):
return (-(DELTA(CORR(HIGH, VOLUME, para_list[0]), para_list[0]) * RANK(STD(CLOSE, para_list[1]))))
def Alpha105(para_list):
return (-1 * CORR(RANK(OPEN), RANK(VOLUME), para_list[0]))
def Alpha106(para_list):
return CLOSE-DELAY(CLOSE,para_list[0])
def Alpha107(para_list):
return -RANK(OPEN - DELAY(HIGH, para_list[0]))\
* RANK(OPEN - DELAY(CLOSE, para_list[0]))\
* RANK(OPEN - DELAY(LOW, para_list[0]))
def Alpha108(para_list):
return (-(RANK((HIGH - MIN(HIGH, para_list[0])))**RANK(CORR((VWAP), (MEAN(VOLUME,para_list[1])), para_list[2]))))
def Alpha109(para_list):
return SMA(HIGH-LOW,para_list[0],para_list[1])/SMA(SMA(HIGH-LOW,para_list[0],para_list[1]),para_list[0],para_list[1])
def Alpha110(para_list):
return SUM(MAX(0,HIGH-DELAY(CLOSE,para_list[0])),para_list[1])\
/SUM(MAX(0,-LOW+DELAY(CLOSE,para_list[0])),para_list[1])
def Alpha111(para_list):
return SMA(VOLUME*((CLOSE-LOW)-(HIGH-CLOSE))/(HIGH-LOW),para_list[0],para_list[2])\
-SMA(VOLUME*((CLOSE-LOW)-(HIGH-CLOSE))/(HIGH-LOW),para_list[1],para_list[3])
def Alpha112(para_list):
return (SUM((CLOSE-DELAY(CLOSE,para_list[0])>0) * (CLOSE-DELAY(CLOSE,para_list[1])),para_list[2])\
-SUM((CLOSE-DELAY(CLOSE,para_list[0])<0) * ABS(CLOSE-DELAY(CLOSE,para_list[1])),para_list[2]))\
/(SUM((CLOSE-DELAY(CLOSE,para_list[0])>0) * (CLOSE-DELAY(CLOSE,para_list[1])),para_list[2])\
+SUM((CLOSE-DELAY(CLOSE,para_list[0])<0) * ABS(CLOSE-DELAY(CLOSE,para_list[1])),para_list[2]))
def Alpha113(para_list):
return -(RANK(SUM(DELAY(CLOSE, para_list[0]), para_list[1]) / para_list[1]) * CORR(CLOSE, VOLUME, para_list[2]))\
* RANK(CORR(SUM( CLOSE, para_list[0]), SUM(CLOSE, para_list[1]), para_list[2]))
def Alpha114(para_list):
return ((RANK(DELAY(((HIGH - LOW) / (SUM(CLOSE, para_list[0]) / para_list[0])), para_list[1])) * RANK(RANK(VOLUME)))
/ (((HIGH - LOW) / (SUM(CLOSE, para_list[0]) / para_list[0])) / (VWAP - CLOSE)))
#para_list[0] is a float between 0 and 1
def Alpha115(para_list):
return RANK(CORR(((HIGH * para_list[0]) + (CLOSE * (1-para_list[0]))), MEAN(VOLUME, para_list[1]),para_list[2]))\
**RANK(CORR(TSRANK(((HIGH + LOW) / 2), para_list[3]), TSRANK(VOLUME, para_list[4]), para_list[5]))
def Alpha116(para_list):
return REGBETA(CLOSE,SEQUENCE(para_list[0]),para_list[0])
def Alpha117(para_list):
return ((TSRANK(VOLUME, para_list[0]) * (1 - TSRANK(((CLOSE + HIGH) - LOW), para_list[1])))* (1 - TSRANK(RET, para_list[0])))
def Alpha118(para_list):
return SUM(HIGH-OPEN,para_list[0])/SUM(OPEN-LOW,para_list[0])
def Alpha119(para_list):
return (RANK(DECAYLINEAR(CORR(VWAP, SUM(MEAN(VOLUME,para_list[0]), para_list[1]), para_list[2]),para_list[3]))\
-RANK(DECAYLINEAR(TSRANK(MIN(CORR(RANK(OPEN), RANK(MEAN(VOLUME,para_list[4])), para_list[5]), para_list[6]), para_list[7]), para_list[8])))
def Alpha120(para_list):
return (RANK((VWAP - CLOSE)) / RANK((VWAP + CLOSE)))
def Alpha121(para_list):
return -RANK(VWAP - MIN(VWAP, para_list[0]))**TSRANK(CORR(TSRANK(VWAP, para_list[1]), TSRANK(MEAN(VOLUME,para_list[2]), para_list[3]), para_list[4]), para_list[5])
def Alpha122(para_list):
return (SMA(SMA(SMA(np.log(CLOSE),para_list[0],para_list[1]),para_list[0],para_list[1]),para_list[0],para_list[1])\
/DELAY(SMA(SMA(SMA(np.log(CLOSE),para_list[0],para_list[1]),para_list[0],para_list[1]),para_list[0],para_list[1]),para_list[2])) - 1.0
'''输出的是bool type'''
def Alpha123(para_list):
return (-(RANK(CORR(SUM((HIGH + LOW) /2, para_list[0]), SUM(MEAN(VOLUME,para_list[1]), para_list[2]), para_list[3]))< RANK(CORR(LOW, VOLUME, para_list[4]))))
def Alpha124(para_list):
return (CLOSE - VWAP) / DECAYLINEAR(RANK(TSMAX(CLOSE, para_list[0])),para_list[1])
def Alpha125(para_list):
return (RANK(DECAYLINEAR(CORR((VWAP), MEAN(VOLUME,para_list[0]),para_list[1]), para_list[2]))\
/RANK(DECAYLINEAR(DELTA(((CLOSE * 0.5) + (VWAP * 0.5)), para_list[3]), para_list[4])))
def Alpha126():
return (CLOSE+HIGH+LOW)/3
#原来是平方再开方的，这里我就直接取ABS了
def Alpha127(para_list):
return ABS(MEAN(((CLOSE-MAX(CLOSE,para_list[0]))/(MAX(CLOSE,para_list[0]))), para_list[0]))
def Alpha128(para_list):
return 100-(100/(1+SUM(((HIGH+LOW+CLOSE)/3>DELAY((HIGH+LOW+CLOSE)/3,para_list[0]))*(HIGH+LOW+CLOSE)/3*VOLUME,para_list[1])/
SUM(((HIGH+LOW+CLOSE)/3<DELAY((HIGH+LOW+CLOSE)/3,para_list[0]))*(HIGH+LOW+CLOSE)/3*VOLUME,para_list[1])))
def Alpha129(para_list):
return SUM((CLOSE-DELAY(CLOSE,para_list[0])<0) * ABS(CLOSE-DELAY(CLOSE,para_list[0])),para_list[1])
def Alpha130(para_list):
return (RANK(DECAYLINEAR(CORR(((HIGH + LOW) / 2),MEAN(VOLUME,para_list[0]),para_list[1]),para_list[2]))\
/RANK(DECAYLINEAR(CORR(RANK(VWAP), RANK(VOLUME), para_list[3]),para_list[4])))
def Alpha131(para_list):
return (RANK(DELAY(VWAP, para_list[0]))**TSRANK(CORR(CLOSE,MEAN(VOLUME,para_list[1]), para_list[2]), para_list[2]))
def Alpha132(para_list):
return MEAN(AMOUNT,para_list[0])
def Alpha133(para_list):
return ((para_list[0]-HIGHDAY(HIGH,para_list[0]))/para_list[0])\
-((para_list[0]-LOWDAY(LOW ,para_list[0]))/para_list[0])
def Alpha134(para_list):
return (CLOSE-DELAY(CLOSE,para_list[0]))/DELAY(CLOSE,para_list[0])*VOLUME
def Alpha135(para_list):
return SMA(DELAY(CLOSE/DELAY(CLOSE,para_list[0]),para_list[1]),para_list[0],para_list[2])
def Alpha136(para_list):
return ((-RANK(DELTA(RET, para_list[0]))) * CORR(OPEN, VOLUME, para_list[1]))
#这个就是Alpha55把最外面那层sum()去掉,那其实就相当于.rolling.sum(window=1)的情形，此处也算作是重复计算
def Alpha55(para_list):
part_C_value = MAX(ABS(HIGH-DELAY(CLOSE,para_list[0])),\
ABS(LOW- DELAY(CLOSE,para_list[0])))
part_A_value = (CLOSE+(CLOSE-OPEN)/2-DELAY(OPEN,para_list[0]))
part_B1_cond = (ABS(HIGH-DELAY(CLOSE,para_list[0])) > ABS(LOW -DELAY(CLOSE,para_list[0])))\
&(ABS(HIGH-DELAY(CLOSE,para_list[0])) > ABS(HIGH-DELAY(LOW, para_list[0])))
part_B2_cond = (ABS(LOW- DELAY(CLOSE,para_list[0])) > ABS(HIGH-DELAY(LOW, para_list[0])))\
&(ABS(LOW- DELAY(CLOSE,para_list[0])) > ABS(HIGH-DELAY(CLOSE,para_list[0])))
part_B1_value= ABS(HIGH-DELAY(CLOSE,para_list[0]))\
+ ABS(LOW -DELAY(CLOSE,para_list[0]))/para_list[1]\
+ ABS(DELAY(CLOSE,para_list[0])\
-DELAY(OPEN, para_list[0]))/para_list[2]
'''
part_B2pvalue= ABS(LOW -DELAY(CLOSE,1))\
+ ABS(HIGH -DELAY(CLOSE,1))/2\
+ ABS(DELAY(CLOSE,1)-DELAY(OPEN ,1))/4 #same of the previous one
'''
part_B2nvalue= (ABS(HIGH-DELAY(LOW ,para_list[0])) + ABS(DELAY(CLOSE,para_list[0])-DELAY(OPEN,para_list[0]))/para_list[2])
part_B_value = (part_B1_cond | (~part_B1_cond) & part_B2_cond) * part_B1_value\
+ ((~part_B1_cond) & (~part_B2_cond)) * part_B2nvalue
return part_A_value/part_B_value*part_C_value
#here para_list[0] is a float between 0 and 1
def Alpha138(para_list):
return (-(RANK(DECAYLINEAR(DELTA((((LOW * para_list[0]) + (VWAP * (1-para_list[0])))), para_list[1]), para_list[2]))\
-TSRANK(DECAYLINEAR(TSRANK(CORR(TSRANK(LOW, para_list[3]), TSRANK(MEAN(VOLUME,para_list[4]), para_list[5]),para_list[6]),para_list[7]),para_list[8]),para_list[9])))
def Alpha139(para_list):
return (-CORR(OPEN, VOLUME, para_list[0]))
def Alpha140(para_list):
return MIN(RANK(DECAYLINEAR(((RANK(OPEN) + RANK(LOW)) - (RANK(HIGH) + RANK(CLOSE))),para_list[0])),\
TSRANK(DECAYLINEAR(CORR(TSRANK(CLOSE, para_list[1]), TSRANK(MEAN(VOLUME, para_list[2]),para_list[3]),para_list[4]),para_list[5]),para_list[5]))
def Alpha141(para_list):
return (-RANK(CORR(RANK(HIGH), RANK(MEAN(VOLUME,para_list[0])), para_list[1])))
def Alpha142(para_list):
return (((-RANK(TSRANK(CLOSE, para_list[0]))) * RANK(DELTA(DELTA(CLOSE,para_list[1]), para_list[1]))) * RANK(TSRANK((VOLUME/MEAN(VOLUME,para_list[2])), para_list[3])))
#Alpha143,没有定义SELF函数
def Alpha143(para_list):
return CLOSE - CLOSE
def Alpha144(para_list):
return SUMIF(ABS(CLOSE/DELAY(CLOSE,para_list[0])-1)/AMOUNT,para_list[1],CLOSE<DELAY(CLOSE,para_list[0]))/COUNT(CLOSE<DELAY(CLOSE,para_list[0]),para_list[1])
def Alpha145(para_list):
return (MEAN(VOLUME,para_list[0])-MEAN(VOLUME,para_list[1]))/MEAN(VOLUME,para_list[2])
#里面有一个square我就不改了- -
def Alpha146(para_list):
return MEAN((CLOSE-DELAY(CLOSE,para_list[0]))/DELAY(CLOSE,para_list[0])\
-SMA((CLOSE-DELAY(CLOSE,para_list[0]))/DELAY(CLOSE,para_list[0]), para_list[1],para_list[4]),para_list[2])\
* ((CLOSE-DELAY(CLOSE,para_list[0]))/DELAY(CLOSE,para_list[0])\
-SMA((CLOSE-DELAY(CLOSE,para_list[0]))/DELAY(CLOSE,para_list[0]), para_list[1],para_list[4]))\
/SMA(((CLOSE-DELAY(CLOSE,para_list[0]))/DELAY(CLOSE,para_list[0])\
-((CLOSE-DELAY(CLOSE,para_list[0]))/DELAY(CLOSE,para_list[0])\
-SMA(( CLOSE-DELAY(CLOSE,para_list[0]))/DELAY(CLOSE,para_list[0]),para_list[3],para_list[4])))**2,para_list[1],para_list[4])
def Alpha147(para_list):
return REGBETA(MEAN(CLOSE,para_list[0]), SEQUENCE(para_list[0]), para_list[0])
'''这里返回的也是个bool'''
def Alpha148(para_list):
return -(RANK(CORR((OPEN), SUM(MEAN(VOLUME,para_list[0]), para_list[1]), para_list[2])) < RANK((OPEN - TSMIN(OPEN, para_list[3]))))
#Alpha149, BANCHMARKCLOSE没有定义，所以这个index空着
def Alpha149(para_list):
return CLOSE - CLOSE
def Alpha150(para_list):
return (CLOSE+HIGH+LOW)/3*VOLUME
def Alpha151(para_list):
return SMA(CLOSE-DELAY(CLOSE,para_list[0]),para_list[0],para_list[1])
def Alpha152(para_list):
return SMA(MEAN(DELAY(SMA(DELAY(CLOSE/DELAY(CLOSE,para_list[0]),para_list[1]),para_list[0],para_list[1]),para_list[0]),para_list[2])\
-MEAN(DELAY(SMA(DELAY(CLOSE/DELAY(CLOSE,para_list[0]),para_list[1]),para_list[0],para_list[1]),para_list[0]),para_list[3]),para_list[0],para_list[1])
#这里取的window是成倍数的，我不认为他们是独立的，因此我只用了一个parameter来描述
def Alpha153(para_list):
return (MEAN(CLOSE, para_list[0])\
+MEAN(CLOSE,2*para_list[0])\
+MEAN(CLOSE,4*para_list[0])\
+MEAN(CLOSE,8*para_list[0]))/4
#这个返回的也是一个bool
def Alpha154(para_list):
return (((VWAP - MIN(VWAP, para_list[0]))) < (CORR(VWAP, MEAN(VOLUME,para_list[1]), para_list[2])))
def Alpha155(para_list):
return SMA(VOLUME,para_list[0],para_list[3])\
-SMA(VOLUME,para_list[1],para_list[4])\
-SMA(\
SMA(VOLUME,para_list[0],para_list[3])\
-SMA(VOLUME,para_list[1],para_list[4]),\
para_list[2],para_list[5])
#para_list[3] is a float between 0 and 1
def Alpha156(para_list):
return -MAX(RANK(DECAYLINEAR(DELTA(VWAP, para_list[0]), para_list[1])),\
RANK(DECAYLINEAR((-(DELTA(((OPEN * para_list[3]) + (LOW * (1-para_list[3]))), para_list[2])\
/((OPEN * para_list[3]) + (LOW * (1-para_list[3]))))), para_list[1])))
def Alpha157(para_list):
return (MIN(PROD(RANK(RANK(LOG(SUM(TSMIN(RANK(RANK(-RANK(DELTA((CLOSE - para_list[0]), para_list[1])))), para_list[2]), para_list[3])))), para_list[4]), para_list[5]) + TSRANK(DELAY((-RET), para_list[6]), para_list[7]))
def Alpha158(para_list):
return ((HIGH-SMA(CLOSE,para_list[0],para_list[1]))-(LOW-SMA(CLOSE,para_list[0],para_list[1])))/CLOSE
def Alpha159(para_list):
return (CLOSE-SUM(MIN(LOW, DELAY(CLOSE,para_list[3])),para_list[0]))\
/SUM(MAX(HIGH,DELAY(CLOSE,para_list[3]))-MIN(LOW,DELAY(CLOSE,para_list[3])),para_list[0])*para_list[1]*para_list[2]\
+(CLOSE-SUM(MIN(LOW, DELAY(CLOSE,para_list[3])),para_list[1]))\
/SUM(MAX(HIGH,DELAY(CLOSE,para_list[3]))-MIN(LOW,DELAY(CLOSE,para_list[3])),para_list[1])*para_list[1]*para_list[2]\
+(CLOSE-SUM(MIN(LOW, DELAY(CLOSE,para_list[3])),para_list[2]))\
/SUM(MAX(HIGH,DELAY(CLOSE,para_list[3]))-MIN(LOW,DELAY(CLOSE,para_list[3])),para_list[2])*para_list[1]*para_list[2]\
/(para_list[0]*para_list[1]+para_list[1]*para_list[2]+para_list[2]*para_list[0])
def Alpha160(para_list):
return SMA((CLOSE<=DELAY(CLOSE,para_list[0]))*STD(CLOSE,para_list[1]),para_list[1],para_list[2])
def Alpha161(para_list):
return MEAN(MAX(MAX((HIGH-LOW),ABS(DELAY(CLOSE,para_list[0])-HIGH)),ABS(DELAY(CLOSE,para_list[0])-LOW)),para_list[1])
def Alpha162(para_list):
return (SMA(MAX(CLOSE-DELAY(CLOSE,para_list[0]),0),para_list[1],para_list[2])\
/SMA(ABS(CLOSE-DELAY(CLOSE,para_list[0])) ,para_list[1],para_list[2])\
-MIN(SMA(MAX(CLOSE-DELAY(CLOSE,para_list[0]),0),para_list[1],para_list[2])\
/SMA(ABS(CLOSE-DELAY(CLOSE,para_list[0])) ,para_list[1],para_list[2]),para_list[1]))\
/(MAX(SMA(MAX(CLOSE-DELAY(CLOSE,para_list[0]),0),para_list[1],para_list[2])
/SMA(ABS(CLOSE-DELAY(CLOSE,para_list[0])) ,para_list[1],para_list[2]),para_list[1])\
-MIN(SMA(MAX(CLOSE-DELAY(CLOSE,para_list[0]),0),para_list[1],para_list[2])\
/SMA(ABS(CLOSE-DELAY(CLOSE,para_list[0])) ,para_list[1],para_list[2]),para_list[1]))
def Alpha163(para_list):
return RANK(((((-RET) * MEAN(VOLUME,para_list[0])) * VWAP) * (HIGH - CLOSE)))
def Alpha164(para_list):
return SMA((((CLOSE>DELAY(CLOSE,para_list[0]))*1/(CLOSE-DELAY(CLOSE,para_list[0]))+ ~(CLOSE>DELAY(CLOSE,para_list[0]))*1)
- MIN(((CLOSE>DELAY(CLOSE,para_list[0]))*1/(CLOSE-DELAY(CLOSE,para_list[0]))+ ~(CLOSE>DELAY(CLOSE,para_list[0]))*1),para_list[1]))/(HIGH-LOW),para_list[2],2)
def Alpha165(para_list):
return SUMAC(CLOSE-MEAN(CLOSE,para_list[0]),para_list[0])\
- SUMAC(CLOSE-MEAN(CLOSE,para_list[0]),para_list[0])/STD(CLOSE,para_list[0])
#**1.5保留 不然120**120估计太大了
def Alpha166(para_list):
return -para_list[0]*((para_list[1])**1.5)*SUM((CLOSE/DELAY(CLOSE,para_list[2])-MEAN(CLOSE/DELAY(CLOSE,para_list[3])-1,para_list[4])),para_list[5]) /((20-1)*(20-2)*((SUM((CLOSE/DELAY(CLOSE,1))**2,20))**1.5))
def Alpha167(para_list):
return SUM((CLOSE-DELAY(CLOSE,para_list[0])>0)*(CLOSE-DELAY(CLOSE,para_list[0])),para_list[1])
def Alpha168(para_list):
return (-VOLUME/MEAN(VOLUME,para_list[0]))
def Alpha169(para_list):
return SMA(MEAN(DELAY(SMA(CLOSE-DELAY(CLOSE,para_list[0]),para_list[1],para_list[0]),para_list[5]),para_list[2])\
-MEAN(DELAY(SMA(CLOSE-DELAY(CLOSE,para_list[0]),para_list[1],para_list[0]),para_list[5]),para_list[3]),para_list[4],para_list[5])
def Alpha170(para_list): #rank * rank - rank almost还是rank
return ((RANK((1 / CLOSE)) * VOLUME / MEAN(VOLUME, para_list[0]))* (HIGH * RANK(HIGH - CLOSE)) / (SUM(HIGH, para_list[1]) / para_list[1])) - RANK(VWAP - DELAY(VWAP, para_list[1]))
def Alpha171(para_list):
return -((LOW - CLOSE) * (OPEN**para_list[0])) / ((CLOSE - HIGH) * (CLOSE**para_list[0]))
def Alpha172(para_list):
return MEAN(ABS(SUM((LD>0 & LD>HD)*LD,para_list[0])/SUM(TR,para_list[1])\
-SUM((HD>0 & HD>LD)*HD,para_list[0])/SUM(TR,para_list[1]))\
/(SUM((LD>0 & LD>HD)*LD,para_list[0])/SUM(TR,para_list[1])\
+SUM((HD>0 & HD>LD)*HD,para_list[0])/SUM(TR,para_list[1])),para_list[2])
#3-2+1或许是某种玄学，没改
def Alpha173(para_list):
return 3*SMA(CLOSE,para_list[0],para_list[1])\
-2*SMA(SMA(CLOSE,para_list[0],para_list[1]),para_list[0],para_list[1])\
+SMA(SMA(SMA(np.log(CLOSE),para_list[0],para_list[1]),para_list[0],para_list[1]),para_list[0],para_list[1])
def Alpha174(para_list):
return SMA((CLOSE>DELAY(CLOSE,para_list[0]))*STD(CLOSE,para_list[1]),para_list[1],para_list[2])
def Alpha175(para_list):
return MEAN(MAX(MAX((HIGH-LOW),ABS(DELAY(CLOSE,para_list[0])-HIGH)),ABS(DELAY(CLOSE,para_list[0])-LOW)),para_list[1])
def Alpha176(para_list):
return CORR(RANK((CLOSE - TSMIN(LOW, para_list[0])) / (TSMAX(HIGH, para_list[0]) - TSMIN(LOW,para_list[0]))), RANK(VOLUME), para_list[1])
def Alpha177(para_list):
return ((para_list[0]-HIGHDAY(HIGH,para_list[0]))/para_list[0])
def Alpha178(para_list):
return (CLOSE-DELAY(CLOSE,para_list[0]))/DELAY(CLOSE,para_list[0])*VOLUME
def Alpha179(para_list):
return (RANK(CORR(VWAP, VOLUME, para_list[0])) * RANK(CORR(RANK(LOW), RANK(MEAN(VOLUME,para_list[1])), para_list[2])))
def Alpha180(para_list):
return (MEAN(VOLUME,para_list[0]) < VOLUME) * (-TSRANK(ABS(DELTA(CLOSE, para_list[1])), para_list[2])) * SIGN(DELTA(CLOSE, para_list[1]))\
+ ~(MEAN(VOLUME,para_list[0]) < VOLUME) * (-VOLUME)
#Alpha181 drop for the BENCHMARKINDEX
def Alpha181(para_list):
return CLOSE - CLOSE
#Alpha182 drop for the BENCHMARKINDEX
def Alpha182(para_list):
return CLOSE - CLOSE
def Alpha183(para_list):
return MAX(SUMAC(CLOSE-MEAN(CLOSE,para_list[0]),para_list[0]),para_list[0])\
-MIN(SUMAC(CLOSE-MEAN(CLOSE,para_list[0]),para_list[0]),para_list[0])/STD(CLOSE,para_list[0])
def Alpha184(para_list):
return (RANK(CORR(DELAY((OPEN - CLOSE), para_list[0]), CLOSE, para_list[1])) + RANK((OPEN - CLOSE)))
#**2也没动
def Alpha185(para_list):
return RANK((-((1 - (OPEN / CLOSE))**2)))
def Alpha186(para_list):
return (MEAN(ABS(SUM(((LD>0) & (LD>HD))*LD,para_list[0])/SUM(TR,para_list[0])\
-SUM(((HD>0) & (HD>LD))*HD,para_list[0])/SUM(TR,para_list[0]))\
/(SUM(((LD>0) & (LD>HD))*LD,para_list[0])/SUM(TR,para_list[0])\
+SUM(((HD>0) & (HD>LD))*HD,para_list[0])/SUM(TR,para_list[0])),para_list[1])\
+DELAY(MEAN(ABS(SUM(((LD>0) & (LD>HD))*LD,para_list[0])/SUM(TR,para_list[0])\
-SUM(((HD>0) & (HD>LD))*HD,para_list[0])/SUM(TR,para_list[0]))\
/(SUM(((LD>0) & (LD>HD))*LD,para_list[0])/SUM(TR,para_list[0])\
+SUM(((HD>0) & (HD>LD))*HD,para_list[0])/SUM(TR,para_list[0])),para_list[1]),para_list[1]))/2
def Alpha187(para_list):
return SUM(~(OPEN<=DELAY(OPEN,para_list[0])) * MAX((HIGH-OPEN),(OPEN-DELAY(OPEN,para_list[0]))),para_list[1])
def Alpha188(para_list):
return ((HIGH-LOW-SMA(HIGH-LOW,para_list[0],2))/SMA(HIGH-LOW,para_list[0],2))
def Alpha189(para_list):
return MEAN(ABS(CLOSE-MEAN(CLOSE,para_list[0])),para_list[0])
''' Alpha190我很无奈。。。
def Alpha190(para_list):
return
LOG((COUNT(CLOSE/DELAY(CLOSE)-1>((CLOSE/DELAY(CLOSE,19))^(1/20)-1),20)-1)\
*(SUMIF(((CLOSE/DELAY(CLOSE)-1-(CLOSE/DELAY(CLOSE,19))^(1/20)-1))^2,20,\
CLOSE/DELAY(CLOSE)-1<(CLOSE/DELAY(CLOSE,19))^(1/20)1))\
/((COUNT((CLOSE/DELAY(CLOSE)-1<(CLOSE/DELAY(CLOSE,19))^(1/20)-1),20))\
*(SUMIF(( CLOSE/DELAY(CLOSE)-1-((CLOSE/DELAY(CLOSE,19))^(1/20)-1))^2,20,\
CLOSE/DELAY(CLOSE)-1>(CLOSE/DELAY(CLOSE,19))^(1/20)-1))) )
'''
def Alpha191(para_list):
return ((CORR(MEAN(VOLUME,para_list[0]), LOW, para_list[1]) + ((HIGH + LOW) / 2)) - CLOSE)
| 46.892562
| 361
| 0.653935
| 6,562
| 39,718
| 3.772935
| 0.059585
| 0.369012
| 0.173035
| 0.10744
| 0.810001
| 0.729461
| 0.659544
| 0.622425
| 0.57339
| 0.531909
| 0
| 0.052682
| 0.134977
| 39,718
| 846
| 362
| 46.947991
| 0.667928
| 0.04109
| 0
| 0.124535
| 0
| 0
| 0.000269
| 0
| 0
| 0
| 0
| 0
| 0.001859
| 1
| 0.35316
| false
| 0
| 0.007435
| 0.336431
| 0.713755
| 0
| 0
| 0
| 0
| null | 1
| 0
| 0
| 1
| 1
| 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
| 6
|
3a464fdcdd14c68d6dfa36a41a88c3c9f484dd45
| 171
|
py
|
Python
|
python/shekels/server/__init__.py
|
theNewFlesh/shekels
|
dbfe308df454390c07f54158abf32ce23561c145
|
[
"MIT"
] | 1
|
2021-12-27T17:23:32.000Z
|
2021-12-27T17:23:32.000Z
|
python/shekels/server/__init__.py
|
theNewFlesh/shekels
|
dbfe308df454390c07f54158abf32ce23561c145
|
[
"MIT"
] | null | null | null |
python/shekels/server/__init__.py
|
theNewFlesh/shekels
|
dbfe308df454390c07f54158abf32ce23561c145
|
[
"MIT"
] | null | null | null |
import shekels.server.api
import shekels.server.app
import shekels.server.components
import shekels.server.event_listener
import shekels.server.server_tools # noqa: F401
| 28.5
| 48
| 0.847953
| 24
| 171
| 5.958333
| 0.458333
| 0.454545
| 0.664336
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.019108
| 0.081871
| 171
| 5
| 49
| 34.2
| 0.89172
| 0.05848
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 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
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 6
|
28b2877f0c69b5c8f1ece02e5ea90b6946df0407
| 102
|
py
|
Python
|
pyseries/metrics/tests/__init__.py
|
flaviovdf/pyseries
|
59c8a321790d2398d71305710b7d322ce2d8eaaf
|
[
"BSD-3-Clause"
] | 7
|
2015-04-12T00:27:39.000Z
|
2018-08-10T13:17:48.000Z
|
pyseries/metrics/tests/__init__.py
|
flaviovdf/pyseries
|
59c8a321790d2398d71305710b7d322ce2d8eaaf
|
[
"BSD-3-Clause"
] | null | null | null |
pyseries/metrics/tests/__init__.py
|
flaviovdf/pyseries
|
59c8a321790d2398d71305710b7d322ce2d8eaaf
|
[
"BSD-3-Clause"
] | 4
|
2015-04-15T03:14:30.000Z
|
2018-11-09T22:06:32.000Z
|
# -*- coding: utf8
from __future__ import division, print_function
'''Tests for the metrics module'''
| 25.5
| 47
| 0.745098
| 13
| 102
| 5.461538
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.011364
| 0.137255
| 102
| 3
| 48
| 34
| 0.795455
| 0.156863
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 1
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 1
|
0
| 6
|
e93a57f3dcbd5b0ce492cb218c9595429caf454a
| 209
|
py
|
Python
|
compiler/extensions/python/runtime/src/zserio/exception.py
|
dkBrazz/zserio
|
29dd8145b7d851fac682d3afe991185ea2eac318
|
[
"BSD-3-Clause"
] | 86
|
2018-09-06T09:30:53.000Z
|
2022-03-27T01:12:36.000Z
|
compiler/extensions/python/runtime/src/zserio/exception.py
|
dkBrazz/zserio
|
29dd8145b7d851fac682d3afe991185ea2eac318
|
[
"BSD-3-Clause"
] | 362
|
2018-09-04T20:21:24.000Z
|
2022-03-30T15:14:38.000Z
|
compiler/extensions/python/runtime/src/zserio/exception.py
|
dkBrazz/zserio
|
29dd8145b7d851fac682d3afe991185ea2eac318
|
[
"BSD-3-Clause"
] | 20
|
2018-09-10T15:59:02.000Z
|
2021-12-01T15:38:22.000Z
|
"""
The module implements exceptions for Zserio python runtime library.
"""
class PythonRuntimeException(Exception):
"""
Exception thrown in case of an error in Zserio python runtime library.
"""
| 23.222222
| 74
| 0.727273
| 24
| 209
| 6.333333
| 0.75
| 0.157895
| 0.25
| 0.342105
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.191388
| 209
| 8
| 75
| 26.125
| 0.899408
| 0.660287
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0
| 0
| 1
| 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
| 1
| 0
| 0
| 0
| 1
| 0
|
0
| 6
|
e942b5a79e94ed63dbf87b2ce293941e08a477e1
| 6,071
|
py
|
Python
|
tests/testBridge.py
|
1696012928/RoomAI
|
37be09590489ab5f7c85083173e83ea31c40b76c
|
[
"MIT"
] | 1
|
2018-03-02T00:49:31.000Z
|
2018-03-02T00:49:31.000Z
|
tests/testBridge.py
|
1696012928/RoomAI
|
37be09590489ab5f7c85083173e83ea31c40b76c
|
[
"MIT"
] | null | null | null |
tests/testBridge.py
|
1696012928/RoomAI
|
37be09590489ab5f7c85083173e83ea31c40b76c
|
[
"MIT"
] | null | null | null |
#!/bin/python
import unittest
import roomai.bridge
import roomai
import roomai.common
from functools import cmp_to_key
class BridgeTester(unittest.TestCase):
def testInit(self):
env = roomai.bridge.BridgeEnv()
env.init()
def testForward(self):
env = roomai.bridge.BridgeEnv()
infos, public_state, person_states, private_state = env.init()
xxx = 0
self.assertEqual(len(infos),5)
for i in range(4):
self.assertEqual(len(person_states[i].hand_cards_dict.keys()), 52 / 4)
self.assertNotEqual(len(person_states[public_state.turn].available_actions),0)
self.assertEqual(len(person_states[public_state.turn].available_actions), 36)
def testAction(self):
action = roomai.bridge.BridgeAction.lookup("bidding_bid_A_Heart")
self.assertEqual(action.stage, "bidding")
self.assertEqual(action.bidding_option,"bid")
self.assertEqual(action.bidding_card.point, "A")
self.assertEqual(action.bidding_card.suit,"Heart")
self.assertEqual(action.playing_card,None)
xxx = 0
print (xxx)
def testAGame(self):
env = roomai.bridge.BridgeEnv()
allcards = list(roomai.bridge.AllBridgePlayingPokerCards.values())
allcards.sort(key = cmp_to_key(roomai.common.PokerCard.compare))
infos, public_state, person_states, private_state = env.init({"start_turn":0})
for i in range(4):
print (i,person_states[i].hand_cards_dict, len(person_states[i].hand_cards_dict))
self.assertEqual(len(person_states[i].hand_cards_dict),13)
self.assertEqual(public_state.turn, 0)
#### bidding stage
action = roomai.bridge.BridgeAction.lookup("bidding_bid_A_Heart")
infos, public_state, person_states, private_state = env.forward(action)
action = roomai.bridge.BridgeAction.lookup("bidding_pass")
infos, public_state, person_states, private_state = env.forward(action)
infos, public_state, person_states, private_state = env.forward(action)
infos, public_state, person_states, private_state = env.forward(action)
self.assertEqual(public_state.stage, "playing")
self.assertEqual(public_state.turn,1)
#### playing_stage
count = 0
while env.public_state.is_terminal == False:
action = list(env.person_states[env.public_state.turn].available_actions.values())[0]
count += 1
env.forward(action)
self.assertEqual(count,13 * 4)
print (env.public_state.scores)
#self.assertTrue(env.public_state.scores[0] == 50)
#self.assertTrue(env.public_state.scores[1] == 0)
print (env.public_state.scores)
# self.assertEqual(env.public_state.scores[1],350)
def testAGame1(self):
env = roomai.bridge.BridgeEnv()
allcards = list(roomai.bridge.AllBridgePlayingPokerCards.values())
allcards.sort(key = cmp_to_key(roomai.common.PokerCard.compare))
infos, public_state, person_states, private_state = env.init({"start_turn":0, "backward_enable":True})
for i in range(4):
print (i,person_states[i].hand_cards_dict, len(person_states[i].hand_cards_dict))
self.assertEqual(len(person_states[i].hand_cards_dict),13)
self.assertEqual(public_state.turn, 0)
#### bidding stage
action = roomai.bridge.BridgeAction.lookup("bidding_bid_A_Heart")
infos, public_state, person_states, private_state = env.forward(action)
action = roomai.bridge.BridgeAction.lookup("bidding_double")
infos, public_state, person_states, private_state = env.forward(action)
action = roomai.bridge.BridgeAction.lookup("bidding_pass")
infos, public_state, person_states, private_state = env.forward(action)
infos, public_state, person_states, private_state = env.forward(action)
infos, public_state, person_states, private_state = env.forward(action)
self.assertEqual(public_state.stage, "playing")
self.assertEqual(public_state.turn,1)
self.assertEqual(public_state.playing_magnification,2)
#### playing_stage
count = 0
while env.public_state.is_terminal == False:
action = list(env.person_states[env.public_state.turn].available_actions.values())[0]
count += 1
if count == 13 * 4:
xx = 0
env.forward(action)
self.assertEqual(count,13 * 4)
#self.assertTrue(env.public_state.scores[0] == 0)
#self.assertTrue(env.public_state.scores[1] > 0)
print (env.public_state.scores)
#self.assertEqual(env.public_state.scores[1],100 + 200 * 2 + (7-3) * 300)
if __name__ == "__main__":
import time
start = time.time()
for iter in range(1000):
env = roomai.bridge.BridgeEnv()
allcards = list(roomai.bridge.AllBridgePlayingPokerCards.values())
allcards.sort(key = cmp_to_key(roomai.common.PokerCard.compare))
infos, public_state, person_states, private_state = env.init({"allcards":allcards, "start_turn":0})
#### bidding stage
action = roomai.bridge.BridgeAction.lookup("bidding_bid_A_Heart")
infos, public_state, person_states, private_state = env.forward(action)
action = roomai.bridge.BridgeAction.lookup("bidding_double")
infos, public_state, person_states, private_state = env.forward(action)
action = roomai.bridge.BridgeAction.lookup("bidding_pass")
infos, public_state, person_states, private_state = env.forward(action)
infos, public_state, person_states, private_state = env.forward(action)
infos, public_state, person_states, private_state = env.forward(action)
#### playing_stage
count = 0
while env.public_state.is_terminal == False:
action = list(env.person_states[env.public_state.turn].available_actions.values())[0]
env.forward(action)
end = time.time()
print (end-start)
| 44.639706
| 110
| 0.674353
| 746
| 6,071
| 5.27748
| 0.142091
| 0.117348
| 0.073152
| 0.100584
| 0.847092
| 0.809754
| 0.803404
| 0.785624
| 0.742443
| 0.706121
| 0
| 0.015227
| 0.210344
| 6,071
| 135
| 111
| 44.97037
| 0.806008
| 0.068522
| 0
| 0.660194
| 0
| 0
| 0.041074
| 0
| 0
| 0
| 0
| 0
| 0.194175
| 1
| 0.048544
| false
| 0.029126
| 0.058252
| 0
| 0.116505
| 0.067961
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 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
| 6
|
3abd51ee19262e6d5fe302883f26d00368192548
| 207
|
py
|
Python
|
exercise_3.py
|
LazyCoder48/python_exercises
|
7612d1f1afd378291a577b7e995ca433e10aa15f
|
[
"MIT"
] | null | null | null |
exercise_3.py
|
LazyCoder48/python_exercises
|
7612d1f1afd378291a577b7e995ca433e10aa15f
|
[
"MIT"
] | 1
|
2020-05-27T09:51:45.000Z
|
2020-05-27T10:59:27.000Z
|
exercise_3.py
|
LazyCoder48/python_exercises
|
7612d1f1afd378291a577b7e995ca433e10aa15f
|
[
"MIT"
] | null | null | null |
'''
Write a Python program to display the current date and time.
Sample Output :
Current date and time :
2014-07-05 14:34:14
'''
import datetime
print(datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S"))
| 20.7
| 60
| 0.700483
| 36
| 207
| 4.027778
| 0.777778
| 0.151724
| 0.193103
| 0.248276
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.078212
| 0.135266
| 207
| 9
| 61
| 23
| 0.731844
| 0.57971
| 0
| 0
| 0
| 0
| 0.21519
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.5
| 0
| 0.5
| 0.5
| 0
| 0
| 0
| null | 0
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 1
|
0
| 6
|
c93af25c8f28e0d714f45e74a7d5a5ebf33d7f6b
| 115
|
py
|
Python
|
conventor/conventor.py
|
Jerryyang2001/math-clear
|
76de0bd86a7761d86fa35162f1b8cb342a1836fb
|
[
"MIT"
] | null | null | null |
conventor/conventor.py
|
Jerryyang2001/math-clear
|
76de0bd86a7761d86fa35162f1b8cb342a1836fb
|
[
"MIT"
] | null | null | null |
conventor/conventor.py
|
Jerryyang2001/math-clear
|
76de0bd86a7761d86fa35162f1b8cb342a1836fb
|
[
"MIT"
] | null | null | null |
import string
from typing import Dict, List
def convent(document: List[string], config: Dict) -> string:
pass
| 19.166667
| 60
| 0.730435
| 16
| 115
| 5.25
| 0.6875
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| 0
| 0
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| 0
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| 115
| 6
| 61
| 19.166667
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| 0.25
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| 0.25
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| null | 0
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| null | 0
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| 0
| 0
| 0
| 1
| 0
| 1
| 1
| 0
| 1
| 0
|
0
| 6
|
c9554ebcc3a5ccc60688985b0b6e21f628ba85c2
| 7,324
|
py
|
Python
|
patch_tracking/tests/issue_test.py
|
openeuler-mirror/patch-tracking
|
6217cbabdcc85d71eaeecce3bf85380258ed2053
|
[
"MulanPSL-1.0"
] | null | null | null |
patch_tracking/tests/issue_test.py
|
openeuler-mirror/patch-tracking
|
6217cbabdcc85d71eaeecce3bf85380258ed2053
|
[
"MulanPSL-1.0"
] | null | null | null |
patch_tracking/tests/issue_test.py
|
openeuler-mirror/patch-tracking
|
6217cbabdcc85d71eaeecce3bf85380258ed2053
|
[
"MulanPSL-1.0"
] | null | null | null |
# pylint: disable=R0801
'''
Automated testing of the Issue interface, GET requests
'''
import unittest
import json
from patch_tracking.app import app
from patch_tracking.api.business import create_issue
from patch_tracking.database import reset_db
from patch_tracking.api.constant import ResponseCode
class TestIssue(unittest.TestCase):
'''
Automated testing of the Issue interface, GET requests
'''
def setUp(self) -> None:
'''
Prepare the environment
:return:
'''
self.client = app.test_client()
reset_db.reset()
def test_none_data(self):
'''
In the absence of data, the GET interface queries all the data
:return:
'''
with app.app_context():
resp = self.client.get("/issue")
resp_dict = json.loads(resp.data)
self.assertIn("code", resp_dict, msg="Error in data format return")
self.assertEqual(ResponseCode.SUCCESS, resp_dict.get("code"), msg="Error in status code return")
self.assertIn("msg", resp_dict, msg="Error in data format return")
self.assertEqual(
ResponseCode.CODE_MSG_MAP.get(ResponseCode.SUCCESS),
resp_dict.get("msg"),
msg="Error in status code return"
)
self.assertIn("data", resp_dict, msg="Error in data format return")
self.assertIsNotNone(resp_dict.get("data"), msg="Error in data information return")
self.assertEqual(resp_dict.get("data"), [], msg="Error in data information return")
def test_query_inserted_data(self):
'''
The GET interface queries existing data
:return:
'''
with app.app_context():
data_insert = {"issue": "A", "repo": "A", "branch": "A"}
create_issue(data_insert)
resp = self.client.get("/issue?repo=A&branch=A")
resp_dict = json.loads(resp.data)
self.assertIn("code", resp_dict, msg="Error in data format return")
self.assertEqual(ResponseCode.SUCCESS, resp_dict.get("code"), msg="Error in status code return")
self.assertIn("msg", resp_dict, msg="Error in data format return")
self.assertEqual(
ResponseCode.CODE_MSG_MAP.get(ResponseCode.SUCCESS),
resp_dict.get("msg"),
msg="Error in status code return"
)
self.assertIn("data", resp_dict, msg="Error in data format return")
self.assertIsNotNone(resp_dict.get("data"), msg="Error in data information return")
self.assertIn(data_insert, resp_dict.get("data"), msg="Error in data information return")
def test_find_all_data(self):
'''
The GET interface queries all the data
:return:
'''
with app.app_context():
data_insert_c = {"issue": "C", "repo": "C", "branch": "C"}
data_insert_d = {"issue": "D", "repo": "D", "branch": "D"}
create_issue(data_insert_c)
create_issue(data_insert_d)
resp = self.client.get("/issue")
resp_dict = json.loads(resp.data)
self.assertIn("code", resp_dict, msg="Error in data format return")
self.assertEqual(ResponseCode.SUCCESS, resp_dict.get("code"), msg="Error in status code return")
self.assertIn("msg", resp_dict, msg="Error in data format return")
self.assertEqual(
ResponseCode.CODE_MSG_MAP.get(ResponseCode.SUCCESS),
resp_dict.get("msg"),
msg="Error in status code return"
)
self.assertIn("data", resp_dict, msg="Error in data format return")
self.assertIsNotNone(resp_dict.get("data"), msg="Error in data information return")
self.assertIn(data_insert_c, resp_dict.get("data"), msg="Error in data information return")
self.assertIn(data_insert_d, resp_dict.get("data"), msg="Error in data information return")
def test_find_nonexistent_data(self):
'''
The GET interface queries data that does not exist
:return:
'''
with app.app_context():
resp = self.client.get("/issue?repo=aa&branch=aa")
resp_dict = json.loads(resp.data)
self.assertIn("code", resp_dict, msg="Error in data format return")
self.assertEqual(ResponseCode.SUCCESS, resp_dict.get("code"), msg="Error in status code return")
self.assertIn("msg", resp_dict, msg="Error in data format return")
self.assertEqual(
ResponseCode.CODE_MSG_MAP.get(ResponseCode.SUCCESS),
resp_dict.get("msg"),
msg="Error in status code return"
)
self.assertIn("data", resp_dict, msg="Error in data format return")
self.assertIsNotNone(resp_dict.get("data"), msg="Error in data information return")
self.assertEqual(resp_dict.get("data"), [], msg="Error in data information return")
def test_get_error_parameters(self):
'''
The get interface passes in the wrong parameter
:return:
'''
with app.app_context():
data_insert = {"issue": "BB", "repo": "BB", "branch": "BB"}
create_issue(data_insert)
resp = self.client.get("/issue?oper=BB&chcnsrb=BB")
resp_dict = json.loads(resp.data)
self.assertIn("code", resp_dict, msg="Error in data format return")
self.assertEqual(
ResponseCode.INPUT_PARAMETERS_ERROR, resp_dict.get("code"), msg="Error in status code return"
)
self.assertIn("msg", resp_dict, msg="Error in data format return")
self.assertEqual(
ResponseCode.CODE_MSG_MAP.get(ResponseCode.INPUT_PARAMETERS_ERROR),
resp_dict.get("msg"),
msg="Error in status code return"
)
self.assertIn("data", resp_dict, msg="Error in data format return")
self.assertEqual(resp_dict.get("data"), None, msg="Error in data information return")
def test_get_interface_uppercase(self):
'''
The get interface uppercase
:return:
'''
with app.app_context():
data_insert = {"issue": "CCC", "repo": "CCC", "branch": "CCC"}
create_issue(data_insert)
resp = self.client.get("/issue?RrPo=CCC&brANch=CCC")
resp_dict = json.loads(resp.data)
self.assertIn("code", resp_dict, msg="Error in data format return")
self.assertEqual(
ResponseCode.INPUT_PARAMETERS_ERROR, resp_dict.get("code"), msg="Error in status code return"
)
self.assertIn("msg", resp_dict, msg="Error in data format return")
self.assertEqual(
ResponseCode.CODE_MSG_MAP.get(ResponseCode.INPUT_PARAMETERS_ERROR),
resp_dict.get("msg"),
msg="Error in status code return"
)
self.assertIn("data", resp_dict, msg="Error in data format return")
self.assertEqual(resp_dict.get("data"), None, msg="Error in data information return")
if __name__ == '__main__':
unittest.main()
| 38.145833
| 109
| 0.597624
| 879
| 7,324
| 4.831627
| 0.101251
| 0.088533
| 0.096539
| 0.095597
| 0.830939
| 0.830939
| 0.813045
| 0.813045
| 0.761243
| 0.727808
| 0
| 0.000763
| 0.284134
| 7,324
| 191
| 110
| 38.34555
| 0.80927
| 0.06663
| 0
| 0.652174
| 0
| 0
| 0.2321
| 0.014715
| 0
| 0
| 0
| 0
| 0.356522
| 1
| 0.06087
| false
| 0
| 0.052174
| 0
| 0.121739
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 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
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| 0
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| 0
| 0
| 0
| 0
|
0
| 6
|
c95a4c9b39901ff3b497b38f3bd354cc410393f1
| 8,370
|
py
|
Python
|
tests/test_codec.py
|
xkortex/ulid
|
96bdb1daad7ce96f6db8c91ac0410b66d2e1c4c1
|
[
"Apache-2.0"
] | 303
|
2017-06-15T14:41:41.000Z
|
2022-03-28T11:46:50.000Z
|
tests/test_codec.py
|
xkortex/ulid
|
96bdb1daad7ce96f6db8c91ac0410b66d2e1c4c1
|
[
"Apache-2.0"
] | 387
|
2017-06-16T14:47:31.000Z
|
2022-03-24T05:55:44.000Z
|
tests/test_codec.py
|
xkortex/ulid
|
96bdb1daad7ce96f6db8c91ac0410b66d2e1c4c1
|
[
"Apache-2.0"
] | 21
|
2017-06-16T20:00:33.000Z
|
2022-03-23T04:14:04.000Z
|
"""
test_codec
~~~~~~~~~~
Tests for the :mod:`~ulid.codec` module.
"""
import datetime
import time
import pytest
from ulid import base32, codec, ulid
UNSUPPORTED_TIMESTAMP_TYPE_EXC_REGEX = (r'Expected datetime, int, float, str, memoryview, Timestamp'
r', ULID, bytes, or bytearray')
TIMESTAMP_SIZE_EXC_REGEX = r'Expects timestamp to be 48 bits'
UNSUPPORTED_RANDOMNESS_TYPE_EXC_REGEX = r'Expected int, float, str, memoryview, Randomness, ULID, bytes, or bytearray'
RANDOMNESS_SIZE_EXC_REGEX = r'Expects randomness to be 80 bits'
@pytest.fixture(scope='session', params=[
list,
dict,
set,
tuple,
type(None)
])
def unsupported_type(request):
"""
Fixture that yields types that a cannot be converted to a timestamp/randomness.
"""
return request.param
@pytest.fixture(scope='session', params=[bytes, bytearray, memoryview])
def buffer_type(request):
"""
Fixture that yields types that support the buffer protocol.
"""
return request.param
def test_decode_timestamp_datetime_returns_timestamp_instance():
"""
Assert that :func:`~ulid.codec.decode_timestamp` returns a new :class:`~ulid.ulid.Timestamp` instance
from the given Unix time from epoch in seconds as an :class:`~datetime.datetime`.
"""
value = datetime.datetime.now()
instance = codec.decode_timestamp(value)
assert isinstance(instance, ulid.Timestamp)
assert int(instance.timestamp) == int(value.timestamp())
def test_decode_timestamp_int_returns_timestamp_instance():
"""
Assert that :func:`~ulid.codec.decode_timestamp` returns a new :class:`~ulid.ulid.Timestamp` instance
from the given Unix time from epoch in seconds as an :class:`~int`.
"""
value = int(time.time())
instance = codec.decode_timestamp(value)
assert isinstance(instance, ulid.Timestamp)
assert int(instance.timestamp) == value
def test_decode_timestamp_float_returns_timestamp_instance():
"""
Assert that :func:`~ulid.codec.decode_timestamp` returns a new :class:`~ulid.ulid.Timestamp` instance
from the given Unix time from epoch in seconds as a :class:`~float`.
"""
value = float(time.time())
instance = codec.decode_timestamp(value)
assert isinstance(instance, ulid.Timestamp)
assert int(instance.timestamp) == int(value)
def test_decode_timestamp_str_returns_timestamp_instance(valid_bytes_48):
"""
Assert that :func:`~ulid.codec.decode_timestamp` returns a new :class:`~ulid.ulid.Timestamp` instance
from the given timestamp as a :class:`~str`.
"""
value = base32.encode_timestamp(valid_bytes_48)
instance = codec.decode_timestamp(value)
assert isinstance(instance, ulid.Timestamp)
assert instance.str == value
def test_decode_timestamp_bytes_returns_timestamp_instance(buffer_type, valid_bytes_48):
"""
Assert that :func:`~ulid.codec.decode_timestamp` returns a new :class:`~ulid.ulid.Timestamp` instance
from the given timestamp as an object that supports the buffer protocol.
"""
value = buffer_type(valid_bytes_48)
instance = codec.decode_timestamp(value)
assert isinstance(instance, ulid.Timestamp)
assert instance.bytes == value
def test_decode_timestamp_timestamp_returns_timestamp_instance(valid_bytes_48):
"""
Assert that :func:`~ulid.codec.decode_timestamp` returns a new :class:`~ulid.ulid.Timestamp` instance
from the given timestamp as a :class:`~ulid.ulid.Timestamp`.
"""
value = ulid.Timestamp(valid_bytes_48)
instance = codec.decode_timestamp(value)
assert isinstance(instance, ulid.Timestamp)
assert instance == value
def test_decode_timestamp_ulid_returns_timestamp_instance(valid_bytes_128):
"""
Assert that :func:`~ulid.codec.decode_timestamp` returns a new :class:`~ulid.ulid.Timestamp` instance
from the given timestamp as a :class:`~ulid.ulid.ULID`.
"""
value = ulid.ULID(valid_bytes_128)
instance = codec.decode_timestamp(value)
assert isinstance(instance, ulid.Timestamp)
assert instance == value.timestamp()
def test_decode_timestamp_with_unsupported_type_raises(unsupported_type):
"""
Assert that :func:`~ulid.codec.decode_timestamp` raises a :class:`~ValueError` when given
a type it cannot compute a timestamp value from.
"""
with pytest.raises(ValueError) as ex:
codec.decode_timestamp(unsupported_type())
assert ex.match(UNSUPPORTED_TIMESTAMP_TYPE_EXC_REGEX)
def test_decode_timestamp_with_incorrect_size_bytes_raises(valid_bytes_128):
"""
Assert that :func:`~ulid.codec.decode_timestamp` raises a :class:`~ValueError` when given
a type that cannot be represented as exactly 48 bits.
"""
with pytest.raises(ValueError) as ex:
codec.decode_timestamp(valid_bytes_128)
assert ex.match(TIMESTAMP_SIZE_EXC_REGEX)
def test_decode_randomness_int_returns_randomness_instance(valid_bytes_80):
"""
Assert that :func:`~ulid.codec.decode_randomness` returns a new :class:`~ulid.ulid.Randomness` instance
from the given random values as an :class:`~int`.
"""
value = int.from_bytes(valid_bytes_80, byteorder='big')
instance = codec.decode_randomness(value)
assert isinstance(instance, ulid.Randomness)
assert instance.int == value
def test_decode_randomness_float_returns_randomness_instance(valid_bytes_80):
"""
Assert that :func:`~ulid.codec.decode_randomness` returns a new :class:`~ulid.ulid.Randomness` instance
from the given random values as an :class:`~float`.
"""
value = float(int.from_bytes(valid_bytes_80, byteorder='big'))
instance = codec.decode_randomness(value)
assert isinstance(instance, ulid.Randomness)
assert instance.int == int(value)
def test_decode_randomness_str_returns_randomness_instance(valid_bytes_80):
"""
Assert that :func:`~ulid.codec.decode_randomness` returns a new :class:`~ulid.ulid.Randomness` instance
from the given random values as an :class:`~str`.
"""
value = base32.encode_randomness(valid_bytes_80)
instance = codec.decode_randomness(value)
assert isinstance(instance, ulid.Randomness)
assert instance.str == value
def test_decode_randomness_bytes_returns_randomness_instance(buffer_type, valid_bytes_80):
"""
Assert that :func:`~ulid.codec.decode_randomness` returns a new :class:`~ulid.ulid.Randomness` instance
from the given random values as an object that supports the buffer protocol.
"""
value = buffer_type(valid_bytes_80)
instance = codec.decode_randomness(value)
assert isinstance(instance, ulid.Randomness)
assert instance.bytes == value
def test_decode_randomness_randomness_returns_randomness_instance(valid_bytes_80):
"""
Assert that :func:`~ulid.codec.decode_randomness` returns a new :class:`~ulid.ulid.Randomness` instance
from the given random values as a :class:`~ulid.ulid.Randomness`.
"""
value = ulid.Randomness(valid_bytes_80)
instance = codec.decode_randomness(value)
assert isinstance(instance, ulid.Randomness)
assert instance == value
def test_decode_randomness_ulid_returns_randomness_instance(valid_bytes_128):
"""
Assert that :func:`~ulid.codec.decode_randomness` returns a new :class:`~ulid.ulid.Randomness` instance
from the given random values as a :class:`~ulid.ulid.ULID`.
"""
value = ulid.ULID(valid_bytes_128)
instance = codec.decode_randomness(value)
assert isinstance(instance, ulid.Randomness)
assert instance == value.randomness()
def test_decode_randomness_with_unsupported_type_raises(unsupported_type):
"""
Assert that :func:`~ulid.codec.decode_randomness` raises a :class:`~ValueError` when given
a type it cannot compute a randomness value from.
"""
with pytest.raises(ValueError) as ex:
codec.decode_randomness(unsupported_type())
assert ex.match(UNSUPPORTED_RANDOMNESS_TYPE_EXC_REGEX)
def test_decode_randomness_with_incorrect_size_bytes_raises(valid_bytes_128):
"""
Assert that :func:`~ulid.codec.decode_randomness` raises a :class:`~ValueError` when given
a type that cannot be represented as exactly 80 bits.
"""
with pytest.raises(ValueError) as ex:
codec.decode_randomness(valid_bytes_128)
assert ex.match(RANDOMNESS_SIZE_EXC_REGEX)
| 37.2
| 118
| 0.73644
| 1,085
| 8,370
| 5.470046
| 0.087558
| 0.063016
| 0.060657
| 0.051559
| 0.874473
| 0.798484
| 0.733277
| 0.705981
| 0.705981
| 0.684414
| 0
| 0.009989
| 0.162724
| 8,370
| 224
| 119
| 37.366071
| 0.836901
| 0.348746
| 0
| 0.392157
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| 0
| 0.047657
| 0
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| 0
| 0.294118
| 1
| 0.186275
| false
| 0
| 0.039216
| 0
| 0.245098
| 0
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| 0
| null | 0
| 0
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| 1
| 1
| 1
| 1
| 1
| 0
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| null | 0
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| 0
| 0
| 0
|
0
| 6
|
6e57c4db4eed8db69cb069238e220bb9edaa4c09
| 55
|
py
|
Python
|
videokf/__init__.py
|
averdones/video-kf
|
65a81a0b5352e3ad4d7f394f32772e911de4abbc
|
[
"MIT"
] | 6
|
2021-01-24T13:38:41.000Z
|
2022-03-03T09:46:36.000Z
|
videokf/__init__.py
|
averdones/video-kf
|
65a81a0b5352e3ad4d7f394f32772e911de4abbc
|
[
"MIT"
] | 1
|
2020-12-29T11:39:47.000Z
|
2021-01-06T18:25:07.000Z
|
videokf/__init__.py
|
averdones/video-kf
|
65a81a0b5352e3ad4d7f394f32772e911de4abbc
|
[
"MIT"
] | null | null | null |
from videokf.extract_keyframes import extract_keyframes
| 55
| 55
| 0.927273
| 7
| 55
| 7
| 0.714286
| 0.653061
| 0
| 0
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| 0.942308
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| 1
| 0
|
0
| 6
|
6e580a92265c13697bec98e4a7efb59bae4585b4
| 222
|
py
|
Python
|
backend/common/databases/messages/end_tournament_message.py
|
MuChin708/Tosurnament
|
13e493a5ac3f7b0af94d7f509d3711b9fa6e94c1
|
[
"MIT"
] | null | null | null |
backend/common/databases/messages/end_tournament_message.py
|
MuChin708/Tosurnament
|
13e493a5ac3f7b0af94d7f509d3711b9fa6e94c1
|
[
"MIT"
] | null | null | null |
backend/common/databases/messages/end_tournament_message.py
|
MuChin708/Tosurnament
|
13e493a5ac3f7b0af94d7f509d3711b9fa6e94c1
|
[
"MIT"
] | null | null | null |
"""End tournament message table"""
from .base_message import BaseAuthorLockMessage
class EndTournamentMessage(BaseAuthorLockMessage):
"""End tournament message class"""
__tablename__ = "end_tournament_message"
| 22.2
| 50
| 0.783784
| 20
| 222
| 8.35
| 0.55
| 0.233533
| 0.359281
| 0
| 0
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| 0
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| 0
| 0
| 0
| 0.130631
| 222
| 9
| 51
| 24.666667
| 0.865285
| 0.256757
| 0
| 0
| 0
| 0
| 0.142857
| 0.142857
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.333333
| 0
| 1
| 0
| 1
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| 0
| null | 1
| 1
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| 0
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| 1
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| null | 0
| 0
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| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
|
0
| 6
|
6e8ea3cba04832322cacf6320599aa6f6f39270f
| 22
|
py
|
Python
|
selfbot/__init__.py
|
TibebeJS/tg-selfbot
|
ad36399597b7277768649d6645d57611a2928259
|
[
"MIT"
] | 1
|
2021-03-05T12:03:53.000Z
|
2021-03-05T12:03:53.000Z
|
selfbot/__init__.py
|
TibebeJS/tg-selfbot
|
ad36399597b7277768649d6645d57611a2928259
|
[
"MIT"
] | null | null | null |
selfbot/__init__.py
|
TibebeJS/tg-selfbot
|
ad36399597b7277768649d6645d57611a2928259
|
[
"MIT"
] | 1
|
2021-01-14T18:03:11.000Z
|
2021-01-14T18:03:11.000Z
|
from .selfbot import *
| 22
| 22
| 0.772727
| 3
| 22
| 5.666667
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.136364
| 22
| 1
| 22
| 22
| 0.894737
| 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
| 1
| 0
|
0
| 6
|
6eba6e6449b9e3125ffff4cd16b950b53aaf2387
| 149
|
py
|
Python
|
tests/context.py
|
vinod-iref/awfleet
|
5cf86eea025e69b74d5aa3793d74f73284292fc3
|
[
"MIT"
] | null | null | null |
tests/context.py
|
vinod-iref/awfleet
|
5cf86eea025e69b74d5aa3793d74f73284292fc3
|
[
"MIT"
] | null | null | null |
tests/context.py
|
vinod-iref/awfleet
|
5cf86eea025e69b74d5aa3793d74f73284292fc3
|
[
"MIT"
] | null | null | null |
import os
import sys
sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), '..')))
from lib import Demand
from lib import Spot
| 21.285714
| 82
| 0.744966
| 26
| 149
| 4.115385
| 0.538462
| 0.168224
| 0.242991
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.007519
| 0.107383
| 149
| 7
| 83
| 21.285714
| 0.796992
| 0
| 0
| 0
| 0
| 0
| 0.013333
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.8
| 0
| 0.8
| 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
| 1
| 0
|
0
| 6
|
6ed3866635e440a9035c5f28f1703f7ff6f61684
| 76
|
py
|
Python
|
plenum/test/input_validation/test_message_base.py
|
steptan/indy-plenum
|
488bf63c82753a74a92ac6952da784825ffd4a3d
|
[
"Apache-2.0"
] | null | null | null |
plenum/test/input_validation/test_message_base.py
|
steptan/indy-plenum
|
488bf63c82753a74a92ac6952da784825ffd4a3d
|
[
"Apache-2.0"
] | null | null | null |
plenum/test/input_validation/test_message_base.py
|
steptan/indy-plenum
|
488bf63c82753a74a92ac6952da784825ffd4a3d
|
[
"Apache-2.0"
] | 1
|
2020-01-24T09:36:13.000Z
|
2020-01-24T09:36:13.000Z
|
def test_correct_message():
pass
def test_incorrect_field():
pass
| 10.857143
| 27
| 0.710526
| 10
| 76
| 5
| 0.7
| 0.28
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.210526
| 76
| 6
| 28
| 12.666667
| 0.833333
| 0
| 0
| 0.5
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.5
| true
| 0.5
| 0
| 0
| 0.5
| 0
| 1
| 0
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 1
| 1
| 0
| 0
| 0
| 0
|
0
| 6
|
6ee5e84ad46e024f3ca4eaeb6d14f0b48e5fd110
| 3,362
|
py
|
Python
|
deep_qa/training/losses.py
|
richarajpal/deep_qa
|
d918335a1bed71b9cfccf1d5743321cee9c61952
|
[
"Apache-2.0"
] | 459
|
2017-02-08T13:40:17.000Z
|
2021-12-12T12:57:48.000Z
|
deep_qa/training/losses.py
|
richarajpal/deep_qa
|
d918335a1bed71b9cfccf1d5743321cee9c61952
|
[
"Apache-2.0"
] | 176
|
2017-01-26T01:19:41.000Z
|
2018-04-22T19:16:01.000Z
|
deep_qa/training/losses.py
|
richarajpal/deep_qa
|
d918335a1bed71b9cfccf1d5743321cee9c61952
|
[
"Apache-2.0"
] | 154
|
2017-01-26T01:00:30.000Z
|
2021-02-05T10:44:42.000Z
|
from keras import backend as K
from ..tensors.backend import VERY_NEGATIVE_NUMBER, VERY_LARGE_NUMBER
def ranking_loss(y_pred, y_true):
"""
Using this loss trains the model to give scores to all correct elements in y_true that are
higher than all scores it gives to incorrect elements in y_true.
For example, let ``y_true = [0, 0, 1, 1, 0]``, and let ``y_pred = [-1, 1, 2, 0, -2]``. We will
find the lowest score assigned to correct elements in ``y_true`` (``0`` in this case), and the
highest score assigned to incorrect elements in ``y_true`` (``1`` in this case). We will then
compute a sigmoided loss given these values: ``-K.sigmoid(0 - 1)`` (we're minimizing the loss,
so the negative sign in front of the sigmoid means we want the correct element to have a higher
score than the incorrect element).
Note that the way we do this uses ``K.max()`` and ``K.min()`` over the elements in ``y_true``,
which means that if you have a lot of values in here, you'll only get gradients backpropping
through two of them (the ones on the margin). This could be an inefficient use of your
computation time. Think carefully about the data that you're using with this loss function.
Because of the way masking works with Keras loss functions, also, you need to be sure that any
masked elements in ``y_pred`` have very negative values before they get passed into this loss
function.
"""
correct_elements = y_pred + (1.0 - y_true) * VERY_LARGE_NUMBER
lowest_scoring_correct = K.min(correct_elements, axis=-1)
incorrect_elements = y_pred + y_true * VERY_NEGATIVE_NUMBER
highest_scoring_incorrect = K.max(incorrect_elements, axis=-1)
return K.mean(-K.sigmoid(lowest_scoring_correct - highest_scoring_incorrect))
def ranking_loss_with_margin(y_pred, y_true):
"""
Using this loss trains the model to give scores to all correct elements in y_true that are
higher than all scores it gives to incorrect elements in y_true, plus a margin.
For example, let ``y_true = [0, 0, 1, 1, 0]``, and let ``y_pred = [-1, 1, 2, 0, -2]``. We will
find the lowest score assigned to correct elements in ``y_true`` (``0`` in this case), and the
highest score assigned to incorrect elements in ``y_true`` (``1`` in this case). We will then
compute a hinge loss given these values: ``K.maximum(0.0, 1 + 1 - 0)``.
Note that the way we do this uses ``K.max()`` and ``K.min()`` over the elements in ``y_true``,
which means that if you have a lot of values in here, you'll only get gradients backpropping
through two of them (the ones on the margin). This could be an inefficient use of your
computation time. Think carefully about the data that you're using with this loss function.
Because of the way masking works with Keras loss functions, also, you need to be sure that any
masked elements in ``y_pred`` have very negative values before they get passed into this loss
function.
"""
correct_elements = y_pred + (1.0 - y_true) * VERY_LARGE_NUMBER
lowest_scoring_correct = K.min(correct_elements, axis=-1)
incorrect_elements = y_pred + y_true * VERY_NEGATIVE_NUMBER
highest_scoring_incorrect = K.max(incorrect_elements, axis=-1)
return K.mean(K.maximum(0.0, 1.0 + highest_scoring_incorrect - lowest_scoring_correct))
| 58.982456
| 99
| 0.713266
| 567
| 3,362
| 4.109347
| 0.222222
| 0.038627
| 0.056652
| 0.064378
| 0.839485
| 0.812017
| 0.812017
| 0.812017
| 0.812017
| 0.812017
| 0
| 0.016009
| 0.201071
| 3,362
| 56
| 100
| 60.035714
| 0.851452
| 0.695419
| 0
| 0.571429
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.142857
| false
| 0
| 0.142857
| 0
| 0.428571
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 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
| 6
|
42ce8c171d12e2b73a1f4ffd5e7ffd73d86c7cd2
| 157
|
py
|
Python
|
src/sentry/analytics/events/__init__.py
|
AlexWayfer/sentry
|
ef935cda2b2e960bd602fda590540882d1b0712d
|
[
"BSD-3-Clause"
] | 4
|
2019-05-27T13:55:07.000Z
|
2021-03-30T07:05:09.000Z
|
src/sentry/analytics/events/__init__.py
|
AlexWayfer/sentry
|
ef935cda2b2e960bd602fda590540882d1b0712d
|
[
"BSD-3-Clause"
] | 196
|
2019-06-10T08:34:10.000Z
|
2022-02-22T01:26:13.000Z
|
src/sentry/analytics/events/__init__.py
|
AlexWayfer/sentry
|
ef935cda2b2e960bd602fda590540882d1b0712d
|
[
"BSD-3-Clause"
] | 2
|
2021-01-26T09:53:39.000Z
|
2022-03-22T09:01:47.000Z
|
from __future__ import absolute_import, print_function
from sentry.utils.imports import import_submodules
import_submodules(globals(), __name__, __path__)
| 26.166667
| 54
| 0.853503
| 19
| 157
| 6.210526
| 0.684211
| 0.271186
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.089172
| 157
| 5
| 55
| 31.4
| 0.825175
| 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 | 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
| 6
|
42cfbf5bec38b2dcc6e91d58015699dd4942776d
| 170
|
py
|
Python
|
pitch.py
|
hktxt/CBI
|
abbaf84333dce80fa60449a9fce53bc4ed544deb
|
[
"MIT"
] | null | null | null |
pitch.py
|
hktxt/CBI
|
abbaf84333dce80fa60449a9fce53bc4ed544deb
|
[
"MIT"
] | null | null | null |
pitch.py
|
hktxt/CBI
|
abbaf84333dce80fa60449a9fce53bc4ed544deb
|
[
"MIT"
] | null | null | null |
import pitch
p = pitch.find_pitch(r'"D:\project\Cornell-Birdcall-Identification\data\birdsong-recognition\train_audio_resampled\aldfly\XC2628.wav"')
print('pitch =', p)
| 34
| 135
| 0.794118
| 24
| 170
| 5.5
| 0.833333
| 0.090909
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.024845
| 0.052941
| 170
| 5
| 136
| 34
| 0.795031
| 0
| 0
| 0
| 0
| 0.333333
| 0.684211
| 0.643275
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.333333
| 0
| 0.333333
| 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
| 1
| 1
| 1
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
|
0
| 6
|
42f696134c0b3c54d1ddac4ee131a7ee80ac1d99
| 27
|
py
|
Python
|
sentence_transformers/datasets/sampler/__init__.py
|
dd-dos/sentence-transformers
|
8f9c36b788e15141f723d80fea67ed16785cd18e
|
[
"Apache-2.0"
] | 31
|
2021-04-06T16:20:30.000Z
|
2022-02-16T08:29:24.000Z
|
sentence_transformers/datasets/sampler/__init__.py
|
dd-dos/sentence-transformers
|
8f9c36b788e15141f723d80fea67ed16785cd18e
|
[
"Apache-2.0"
] | 5
|
2021-07-02T04:37:04.000Z
|
2021-07-21T00:02:58.000Z
|
sentence_transformers/datasets/sampler/__init__.py
|
dd-dos/sentence-transformers
|
8f9c36b788e15141f723d80fea67ed16785cd18e
|
[
"Apache-2.0"
] | 5
|
2021-07-04T06:02:02.000Z
|
2021-07-21T08:32:10.000Z
|
from .LabelSampler import *
| 27
| 27
| 0.814815
| 3
| 27
| 7.333333
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.111111
| 27
| 1
| 27
| 27
| 0.916667
| 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
| 1
| 0
|
0
| 6
|
6e17affa818028a097949b5eba199028194d33d0
| 26
|
py
|
Python
|
plotly/graph_objs/layout/xaxis/rangeslider/__init__.py
|
gnestor/plotly.py
|
a8ae062795ddbf9867b8578fe6d9e244948c15ff
|
[
"MIT"
] | 12
|
2020-04-18T18:10:22.000Z
|
2021-12-06T10:11:15.000Z
|
plotly/graph_objs/layout/xaxis/rangeslider/__init__.py
|
Vesauza/plotly.py
|
e53e626d59495d440341751f60aeff73ff365c28
|
[
"MIT"
] | 27
|
2020-04-28T21:23:12.000Z
|
2021-06-25T15:36:38.000Z
|
plotly/graph_objs/layout/xaxis/rangeslider/__init__.py
|
Vesauza/plotly.py
|
e53e626d59495d440341751f60aeff73ff365c28
|
[
"MIT"
] | 6
|
2020-04-18T23:07:08.000Z
|
2021-11-18T07:53:06.000Z
|
from ._yaxis import YAxis
| 13
| 25
| 0.807692
| 4
| 26
| 5
| 0.75
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.153846
| 26
| 1
| 26
| 26
| 0.909091
| 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
| 1
| 0
|
0
| 6
|
6e20a5edc4f076f29f6331d7ea718a042ca4aab6
| 1,422
|
py
|
Python
|
python/problem-008.py
|
mbuhot/mbuhot-euler-solutions
|
30066543cfd2d84976beb0605839750b64f4b8ef
|
[
"MIT"
] | 1
|
2015-12-18T13:25:41.000Z
|
2015-12-18T13:25:41.000Z
|
python/problem-008.py
|
mbuhot/mbuhot-euler-solutions
|
30066543cfd2d84976beb0605839750b64f4b8ef
|
[
"MIT"
] | null | null | null |
python/problem-008.py
|
mbuhot/mbuhot-euler-solutions
|
30066543cfd2d84976beb0605839750b64f4b8ef
|
[
"MIT"
] | null | null | null |
#! /usr/bin/env python3
# Largest product in a series
# Problem 8
# Find the greatest product of five consecutive digits in the 1000-digit number.
digits = """
73167176531330624919225119674426574742355349194934
96983520312774506326239578318016984801869478851843
85861560789112949495459501737958331952853208805511
12540698747158523863050715693290963295227443043557
66896648950445244523161731856403098711121722383113
62229893423380308135336276614282806444486645238749
30358907296290491560440772390713810515859307960866
70172427121883998797908792274921901699720888093776
65727333001053367881220235421809751254540594752243
52584907711670556013604839586446706324415722155397
53697817977846174064955149290862569321978468622482
83972241375657056057490261407972968652414535100474
82166370484403199890008895243450658541227588666881
16427171479924442928230863465674813919123162824586
17866458359124566529476545682848912883142607690042
24219022671055626321111109370544217506941658960408
07198403850962455444362981230987879927244284909188
84580156166097919133875499200524063689912560717606
05886116467109405077541002256983155200055935729725
71636269561882670428252483600823257530420752963450""".replace('\n', '')
slices = (digits[i:i+5] for i in range(0, len(digits)-5))
maxProd = 0
for slice in slices:
prod = 1
for digit in slice:
prod = prod * int(digit)
maxProd = max(prod, maxProd)
print("max product:", maxProd)
| 37.421053
| 80
| 0.890295
| 84
| 1,422
| 15.071429
| 0.678571
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.764172
| 0.06962
| 1,422
| 37
| 81
| 38.432432
| 0.192744
| 0.09775
| 0
| 0
| 0
| 0
| 0.808444
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0
| 6
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2817b8606d44ef90bd6355767649a377eaa5000a
| 18,448
|
py
|
Python
|
src/baseline.py
|
ZihengZZH/bipolar-disorder
|
deef966d65014175d6cb8f35320b2b33bfadfd13
|
[
"MIT"
] | 17
|
2019-08-07T11:21:01.000Z
|
2022-03-01T00:57:09.000Z
|
src/baseline.py
|
ZihengZZH/bipolar-disorder
|
deef966d65014175d6cb8f35320b2b33bfadfd13
|
[
"MIT"
] | 5
|
2020-01-28T22:56:27.000Z
|
2022-02-10T00:15:53.000Z
|
src/baseline.py
|
ZihengZZH/bipolar-disorder
|
deef966d65014175d6cb8f35320b2b33bfadfd13
|
[
"MIT"
] | 5
|
2019-11-22T07:10:32.000Z
|
2022-03-25T08:20:48.000Z
|
import os
import json
import numpy as np
import scipy.sparse as sp
from src.model.linear_svm import LinearSVM
from src.model.random_forest import RandomForest
from src.metric.uar import get_UAR, get_post_probability, get_late_fusion_UAR
from src.utils.io import load_proc_baseline_feature, save_UAR_results
from src.utils.io import save_post_probability, load_post_probability
from src.utils.io import save_cv_results
from src.utils.preprocess import upsample
from src.utils.preprocess import k_fold_cv
'''
BASELINE CLASSIFICATION (py) PROVIDED BY AVEC2018
features | computed level
-------- | --------------
MFCCs | frame level
eGeMAPS | turn level
DeepSpectrum | activations in ALEXNET
BoAW | window size (2s)
FAUs | session level
BoVW | window size (11s)
'''
class BaseLine():
"""
Baseline system in BD classification, based on SVM/RF using LLDs and fusion
---
Attributes
-----------
model_name: str
model for BaseLine() instance, SVM or RF
feature_name: str
feature for BaseLine() instance, MFCC/eGeMAPS/Deep/BoAW/FAU/BoVW
test: bool
whether to test BaseLine() or not
----------------------------------------------------------------------
Functions
-----------
run(): public
main function
run_[MFCC,eGeMAPS,DeepSpectrum,BoAW,AU,BoVW](): public
run classifier on specified feature (single modality)
run_fusion(): public
run late fusion on a pair of specified features
"""
def __init__(self, model_name, feature_name, test=False):
# para model: determine the model in baseline system
# para name: determine the feature in baseline system
self.model_name = model_name
self.feature_name = feature_name
self.test = test
print("\nbaseline system initialized, model %s feature %s" % (self.model_name, self.feature_name))
def run(self):
"""main function of BaseLine() instance
"""
if self.feature_name == 'FUSE':
feature_name_1 = ''
feature_name_2 = ''
self.run_fusion(feature_name_1, feature_name_2)
elif self.feature_name == 'MFCC':
self.run_MFCC()
elif self.feature_name == 'eGeMAPS':
self.run_eGeMAPS()
elif self.feature_name == 'Deep':
self.run_DeepSpectrum()
elif self.feature_name == 'BoAW':
self.run_BoAW()
elif self.feature_name == 'AU':
self.run_AU()
elif self.feature_name == 'BoVW':
self.run_BoVW()
def run_MFCC(self):
"""run classifier on MFCC feature (single modality)
"""
print("\nbuilding a classifier on MFCC features (both frame-level and session-level)")
X_train, y_train, train_inst, X_dev, y_dev, dev_inst = load_proc_baseline_feature('MFCC', verbose=True)
if self.model_name == 'RF_cv':
y_train, y_dev = np.ravel(y_train), np.ravel(y_dev)
train_inst, dev_inst = np.ravel(train_inst), np.ravel(dev_inst)
X = np.vstack((X_train, X_dev))
y = np.hstack((y_train, y_dev))
inst = np.hstack((train_inst, dev_inst))
assert len(X) == len(y) == len(inst)
cv_ids = k_fold_cv(len(X))
cv_res = []
for (ids_train, ids_dev) in cv_ids:
X_train = X[ids_train]
y_train = y[ids_train]
X_dev = X[ids_dev]
y_dev = y[ids_dev]
dev_inst = inst[ids_dev]
RF_MFCC = RandomForest(self.feature_name, X_train, y_train, X_dev, y_dev, baseline=True, test=self.test)
RF_MFCC.run()
y_pred_train, y_pred_dev = RF_MFCC.evaluate()
_, session_res = get_UAR(y_pred_dev, y_dev, dev_inst, self.model_name, self.feature_name, 'baseline', baseline=True, test=True)
cv_res.append(session_res)
save_cv_results(cv_res, self.model_name, self.feature_name, 'baseline')
print("\nupsampling training data to address class imbalance")
X_train, y_train, train_inst = upsample(X_train, y_train, train_inst)
print("\nobtaining sparse matrix for better classification")
# X_train = sp.csr_matrix(np.vstack((X_train, X_dev)))
# X_dev = sp.csr_matrix(X_dev)
# y_train = np.hstack((y_train, y_dev))
X_train, X_dev = sp.csr_matrix(X_train), sp.csr_matrix(X_dev)
if self.model_name == 'SVM':
SVM_MFCC = LinearSVM(self.feature_name, X_train, y_train, X_dev, y_dev, baseline=True, test=self.test)
SVM_MFCC.run()
y_pred_train, y_pred_dev = SVM_MFCC.evaluate()
elif self.model_name == 'RF':
RF_MFCC = RandomForest(self.feature_name, X_train, y_train, X_dev, y_dev, baseline=True, test=self.test)
RF_MFCC.run()
y_pred_train, y_pred_dev = RF_MFCC.evaluate()
get_UAR(y_pred_train, y_train, train_inst, self.model_name, self.feature_name, 'baseline', baseline=True, train_set=True, test=self.test)
get_UAR(y_pred_dev, y_dev, dev_inst, self.model_name, self.feature_name, 'baseline', baseline=True, test=self.test)
if not self.test:
get_post_probability(y_pred_dev, y_dev, dev_inst, np.array([]), self.model_name, self.feature_name)
def run_eGeMAPS(self):
"""run classifier on eGeMAPS feature (single modality)
"""
print("\nbuilding a classifier on eGeMAPS features (both frame-level and session-level)")
X_train, y_train, train_inst, X_dev, y_dev, dev_inst = load_proc_baseline_feature('eGeMAPS', verbose=True)
if self.model_name == 'RF_cv':
X = np.vstack((X_train, X_dev))
y = np.hstack((y_train, y_dev))
assert len(X) == len(y)
cv_ids = k_fold_cv(len(X))
cv_res = []
for (ids_train, ids_dev) in cv_ids:
X_train = X[ids_train]
y_train = y[ids_train]
X_dev = X[ids_dev]
y_dev = y[ids_dev]
RF_MFCC = RandomForest(self.feature_name, X_train, y_train, X_dev, y_dev, baseline=True, test=self.test)
RF_MFCC.run()
y_pred_train, y_pred_dev = RF_MFCC.evaluate()
_, session_res = get_UAR(y_pred_dev, y_dev, dev_inst, self.model_name, self.feature_name, 'baseline', baseline=True, test=True)
cv_res.append(session_res)
save_cv_results(cv_res, self.model_name, self.feature_name, 'baseline')
print("\nupsampling training data to address class imbalance")
X_train, y_train, train_inst = upsample(X_train, y_train, train_inst)
print("\nobtaining sparse matrix for better classification")
# X_train = sp.csr_matrix(np.vstack((X_train, X_dev)))
# X_dev = sp.csr_matrix(X_dev)
# y_train = np.hstack((y_train, y_dev))
X_train, X_dev = sp.csr_matrix(X_train), sp.csr_matrix(X_dev)
if self.model_name == 'SVM':
SVM_eGeMAPS = LinearSVM(self.feature_name, X_train, y_train, X_dev, y_dev, baseline=True, test=self.test)
SVM_eGeMAPS.run()
y_pred_train, y_pred_dev = SVM_eGeMAPS.evaluate()
elif self.model_name == 'RF':
RF_eGeMAPS = RandomForest(self.feature_name, X_train, y_train, X_dev, y_dev, baseline=True, test=self.test)
RF_eGeMAPS.run()
y_pred_train, y_pred_dev = RF_eGeMAPS.evaluate()
get_UAR(y_pred_train, y_train, train_inst, self.model_name, self.feature_name, 'baseline', baseline=True, train_set=True, test=self.test)
get_UAR(y_pred_dev, y_dev, dev_inst, self.model_name, self.feature_name, 'baseline', baseline=True, test=self.test)
if not self.test:
get_post_probability(y_pred_dev, y_dev, dev_inst, np.array([]), self.model_name, self.feature_name)
def run_DeepSpectrum(self):
"""run classifier on DeepSpectrum feature (single modality)
"""
print("\nbuilding a classifier on Deep features (both frame-level and session-level)")
X_train, y_train, train_inst, X_dev, y_dev, dev_inst = load_proc_baseline_feature('Deep', verbose=True)
if self.model_name == 'RF_cv':
X = np.vstack((X_train, X_dev))
y = np.hstack((y_train, y_dev))
assert len(X) == len(y)
cv_ids = k_fold_cv(len(X))
cv_res = []
for (ids_train, ids_dev) in cv_ids:
X_train = X[ids_train]
y_train = y[ids_train]
X_dev = X[ids_dev]
y_dev = y[ids_dev]
RF_MFCC = RandomForest(self.feature_name, X_train, y_train, X_dev, y_dev, baseline=True, test=self.test)
RF_MFCC.run()
y_pred_train, y_pred_dev = RF_MFCC.evaluate()
_, session_res = get_UAR(y_pred_dev, y_dev, dev_inst, self.model_name, self.feature_name, 'baseline', baseline=True, test=True)
cv_res.append(session_res)
save_cv_results(cv_res, self.model_name, self.feature_name, 'baseline')
print("\nupsampling training data to address class imbalance")
X_train, y_train, train_inst = upsample(X_train, y_train, train_inst)
print("\nobtaining sparse matrix for better classification")
# X_train = sp.csr_matrix(np.vstack((X_train, X_dev)))
# X_dev = sp.csr_matrix(X_dev)
# y_train = np.hstack((y_train, y_dev))
X_train, X_dev = sp.csr_matrix(X_train), sp.csr_matrix(X_dev)
if self.model_name == 'SVM':
SVM_Deep = LinearSVM(self.feature_name, X_train, y_train, X_dev, y_dev, baseline=True, test=self.test)
SVM_Deep.run()
y_pred_train, y_pred_dev = SVM_Deep.evaluate()
elif self.model_name == 'RF':
RF_Deep = RandomForest(self.feature_name, X_train, y_train, X_dev, y_dev, baseline=True, test=self.test)
RF_Deep.run()
y_pred_train, y_pred_dev = RF_Deep.evaluate()
get_UAR(y_pred_train, y_train, train_inst, self.model_name, self.feature_name, 'baseline', baseline=True, train_set=True, test=self.test)
get_UAR(y_pred_dev, y_dev, dev_inst, self.model_name, self.feature_name, 'baseline', baseline=True, test=self.test)
if not self.test:
get_post_probability(y_pred_dev, y_dev, dev_inst, np.array([]), self.model_name, self.feature_name)
def run_BoAW(self):
"""run classifier on BoAW feature (single modality)
"""
print("\nbuilding a classifier on BoAW features (both frame-level and session-level)")
X_train, y_train, train_inst, X_dev, y_dev, dev_inst = load_proc_baseline_feature('BoAW', verbose=True)
if self.model_name == 'RF_cv':
y_train, y_dev = np.ravel(y_train), np.ravel(y_dev)
X = np.vstack((X_train, X_dev))
y = np.hstack((y_train, y_dev))
assert len(X) == len(y)
cv_ids = k_fold_cv(len(X))
cv_res = []
for (ids_train, ids_dev) in cv_ids:
X_train = X[ids_train]
y_train = y[ids_train]
X_dev = X[ids_dev]
y_dev = y[ids_dev]
RF_MFCC = RandomForest(self.feature_name, X_train, y_train, X_dev, y_dev, baseline=True, test=self.test)
RF_MFCC.run()
y_pred_train, y_pred_dev = RF_MFCC.evaluate()
_, session_res = get_UAR(y_pred_dev, y_dev, dev_inst, self.model_name, self.feature_name, 'baseline', baseline=True, test=True)
cv_res.append(session_res)
save_cv_results(cv_res, self.model_name, self.feature_name, 'baseline')
print("\nupsampling training data to address class imbalance")
X_train, y_train, train_inst = upsample(X_train, y_train, train_inst)
print("\nobtaining sparse matrix for better classification")
# X_train = sp.csr_matrix(np.vstack((X_train, X_dev)))
# X_dev = sp.csr_matrix(X_dev)
# y_train = np.hstack((y_train, y_dev))
X_train, X_dev = sp.csr_matrix(X_train), sp.csr_matrix(X_dev)
if self.model_name == 'SVM':
SVM_BoAW = LinearSVM(self.feature_name, X_train, y_train, X_dev, y_dev, baseline=True, test=self.test)
SVM_BoAW.run()
y_pred_train, y_pred_dev = SVM_BoAW.evaluate()
elif self.model_name == 'RF':
RF_BoAW = RandomForest(self.feature_name, X_train, y_train, X_dev, y_dev, baseline=True, test=self.test)
RF_BoAW.run()
y_pred_train, y_pred_dev = RF_BoAW.evaluate()
get_UAR(y_pred_train, y_train, train_inst, self.model_name, self.feature_name, 'baseline', baseline=True, train_set=True, test=self.test)
get_UAR(y_pred_dev, y_dev, dev_inst, self.model_name, self.feature_name, 'baseline', baseline=True, test=self.test)
if not self.test:
get_post_probability(y_pred_dev, y_dev, dev_inst, np.array([]), self.model_name, self.feature_name)
def run_AU(self):
"""run classifier on AU feature (single modality)
"""
print("\nbuilding a classifier on AU features (already session-level)")
X_train, y_train, _, X_dev, y_dev, _ = load_proc_baseline_feature('AU', verbose=True)
if self.model_name == 'RF_cv':
X = np.vstack((X_train, X_dev))
y = np.hstack((y_train, y_dev))
assert len(X) == len(y)
cv_ids = k_fold_cv(len(X))
cv_res = []
for (ids_train, ids_dev) in cv_ids:
X_train = X[ids_train]
y_train = y[ids_train]
X_dev = X[ids_dev]
y_dev = y[ids_dev]
RF_MFCC = RandomForest(self.feature_name, X_train, y_train, X_dev, y_dev, baseline=True, test=self.test)
RF_MFCC.run()
y_pred_train, y_pred_dev = RF_MFCC.evaluate()
_, session_res = get_UAR(y_pred_dev, y_dev, np.array([]), self.model_name, self.feature_name, 'baseline', baseline=True, test=True)
cv_res.append(session_res)
save_cv_results(cv_res, self.model_name, self.feature_name, 'baseline')
print("\nupsampling training data to address class imbalance")
X_train, y_train, _ = upsample(X_train, y_train, np.array([]))
print("\nobtaining sparse matrix for better classification")
# X_train = sp.csr_matrix(np.vstack((X_train, X_dev)))
# X_dev = sp.csr_matrix(X_dev)
# y_train = np.hstack((y_train, y_dev))
X_train, X_dev = sp.csr_matrix(X_train), sp.csr_matrix(X_dev)
if self.model_name == 'SVM':
SVM_AU = LinearSVM(self.feature_name, X_train, y_train, X_dev, y_dev, baseline=True, test=self.test)
SVM_AU.run()
y_pred_train, y_pred_dev = SVM_AU.evaluate()
session_prob = SVM_AU.get_session_probability()
elif self.model_name == 'RF':
RF_AU = RandomForest(self.feature_name, X_train, y_train, X_dev, y_dev, baseline=True, test=self.test)
RF_AU.run()
y_pred_train, y_pred_dev = RF_AU.evaluate()
session_prob = RF_AU.get_session_probability()
get_UAR(y_pred_train, y_train, np.array([]), self.model_name, self.feature_name, 'baseline', baseline=True, train_set=True, test=self.test)
get_UAR(y_pred_dev, y_dev, np.array([]), self.model_name, self.feature_name, 'baseline', baseline=True, test=self.test)
def run_BoVW(self):
"""run classifier on BoVW feature (single modality)
"""
print("\nbuilding a classifier on BoVW features (both frame-level and session-level)")
X_train, y_train, train_inst, X_dev, y_dev, dev_inst = load_proc_baseline_feature('BoVW', verbose=True)
if self.model_name == 'RF_cv':
X = np.vstack((X_train, X_dev))
y = np.hstack((y_train, y_dev))
assert len(X) == len(y)
cv_ids = k_fold_cv(len(X))
cv_res = []
for (ids_train, ids_dev) in cv_ids:
X_train = X[ids_train]
y_train = y[ids_train]
X_dev = X[ids_dev]
y_dev = y[ids_dev]
RF_MFCC = RandomForest(self.feature_name, X_train, y_train, X_dev, y_dev, baseline=True, test=self.test)
RF_MFCC.run()
y_pred_train, y_pred_dev = RF_MFCC.evaluate()
_, session_res = get_UAR(y_pred_dev, y_dev, dev_inst, self.model_name, self.feature_name, 'baseline', baseline=True, test=True)
cv_res.append(session_res)
save_cv_results(cv_res, self.model_name, self.feature_name, 'baseline')
print("\nupsampling training data to address class imbalance")
X_train, y_train, train_inst = upsample(X_train, y_train, train_inst)
print("\nobtaining sparse matrix for better classification")
# X_train = sp.csr_matrix(np.vstack((X_train, X_dev)))
# X_dev = sp.csr_matrix(X_dev)
# y_train = np.hstack((y_train, y_dev))
X_train, X_dev = sp.csr_matrix(X_train), sp.csr_matrix(X_dev)
if self.model_name == 'SVM':
SVM_BoVW = LinearSVM(self.feature_name, X_train, y_train, X_dev, y_dev, baseline=True, test=self.test)
SVM_BoVW.run()
y_pred_train, y_pred_dev = SVM_BoVW.evaluate()
elif self.model_name == 'RF':
RF_BoVW = RandomForest(self.feature_name, X_train, y_train, X_dev, y_dev, baseline=True, test=self.test)
RF_BoVW.run()
y_pred_train, y_pred_dev = RF_BoVW.evaluate()
get_UAR(y_pred_train, y_train, train_inst, self.model_name, self.feature_name, 'baseline', baseline=True, train_set=True, test=self.test)
get_UAR(y_pred_dev, y_dev, dev_inst, self.model_name, self.feature_name, 'baseline', baseline=True, test=self.test)
if not self.test:
get_post_probability(y_pred_dev, y_dev, dev_inst, np.array([]), self.model_name, self.feature_name)
def run_fusion(self, feature_name_1, feature_name_2):
"""run late fusion on a pair of specified features
"""
get_late_fusion_UAR(self.model_name, feature_name_1, feature_name_2, baseline=True)
| 50.404372
| 147
| 0.624458
| 2,682
| 18,448
| 3.973154
| 0.054437
| 0.048423
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| 0.040541
| 0.823667
| 0.806963
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| 0.714152
| 0.706832
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0
| 6
|
28527ea7a40d384462fec700b58f5014bdfe9a25
| 135
|
py
|
Python
|
arraytool/src/misc/__init__.py
|
markuskreitzer/arraytool
|
e8d50a4a062dae4d9551daf75c808d2733b6563c
|
[
"CNRI-Python"
] | 1
|
2021-07-26T14:14:58.000Z
|
2021-07-26T14:14:58.000Z
|
arraytool/src/misc/__init__.py
|
elec3647/arraytool
|
e8d50a4a062dae4d9551daf75c808d2733b6563c
|
[
"CNRI-Python"
] | null | null | null |
arraytool/src/misc/__init__.py
|
elec3647/arraytool
|
e8d50a4a062dae4d9551daf75c808d2733b6563c
|
[
"CNRI-Python"
] | 1
|
2022-03-27T01:32:47.000Z
|
2022-03-27T01:32:47.000Z
|
# Author: Srinivasa Rao Zinka (srinivas . zinka [at] gmail . com)
# Copyright (c) 2014 Srinivasa Rao Zinka
# License: New BSD License.
| 33.75
| 65
| 0.718519
| 19
| 135
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| 0.736842
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| 3
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0
| 6
|
95b5f4ef00b10b855ec304c3b3bd2ab5448ef815
| 31
|
py
|
Python
|
tests/test_functional.py
|
TheAustinator/peep-dis
|
c278c364a1e09c1eeb3a6f686ad6c303036904e6
|
[
"MIT"
] | 8
|
2019-04-11T21:14:39.000Z
|
2020-10-26T22:17:27.000Z
|
tests/test_functional.py
|
alvinjamur/peep-dis
|
c278c364a1e09c1eeb3a6f686ad6c303036904e6
|
[
"MIT"
] | 2
|
2019-04-16T23:26:01.000Z
|
2019-05-08T02:47:48.000Z
|
tests/test_functional.py
|
alvinjamur/peep-dis
|
c278c364a1e09c1eeb3a6f686ad6c303036904e6
|
[
"MIT"
] | 1
|
2019-10-16T01:51:51.000Z
|
2019-10-16T01:51:51.000Z
|
from peepdis.core import peep
| 10.333333
| 29
| 0.806452
| 5
| 31
| 5
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.16129
| 31
| 2
| 30
| 15.5
| 0.961538
| 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
| 1
| 0
|
0
| 6
|
2529b144514c39938507a138ddaa5225bdd64c32
| 77,404
|
py
|
Python
|
exceptions/intro_objects.py
|
hugmyndakassi/hvmi
|
fa49a34ba32b327c462224db1cf58d96a076a224
|
[
"Apache-2.0"
] | 677
|
2020-07-30T13:59:36.000Z
|
2022-03-24T11:02:00.000Z
|
exceptions/intro_objects.py
|
hugmyndakassi/hvmi
|
fa49a34ba32b327c462224db1cf58d96a076a224
|
[
"Apache-2.0"
] | 38
|
2020-08-11T13:59:36.000Z
|
2022-02-17T15:03:48.000Z
|
exceptions/intro_objects.py
|
fengjixuchui/hvmi
|
72488e8432d26547876a052d24ea44c3e18279a7
|
[
"Apache-2.0"
] | 55
|
2020-07-30T14:11:03.000Z
|
2022-03-09T05:40:44.000Z
|
#
# Copyright (c) 2020 Bitdefender
# SPDX-License-Identifier: Apache-2.0
#
import struct
import re
from abc import ABCMeta, abstractmethod
import excfg
import crc32
# Note: We cannot use os.path here since it's os specific and we must be able to run
# this both on windows & linux
DEFAULT_FLAGS = {
"SignatureFlags": "32 64",
"UserExceptionFlags": "32 64",
"KernelExceptionFlags": "32 64",
"HeaderMagic": 0x414E5845, # 'EXNA'
}
IMAGE_BASE_NAME_LEN = 14
LIX_COMM_LEN = 15
SIG_IDS = dict()
def is_path(name):
""" Returns True if the given name is a path. Does not validate if the path
is correct except basic invalid characters. """
if name is None or len(name) < 3:
return False
# if ('"' in name) or ('<' in name) or ('>' in name) or \
# ('|' in name) or ('*' in name):
# return False
if name.startswith("\\") or name.startswith("/"):
# \sysroot\etc\a.exe, /home/user/a.out, \??\C:\Program Files\a.exe, etc.
return True
if str.isalpha(name[0]) and name[1] == ":" and name[2] == "\\":
# C:\Program Files, D:\Program Files, etc.
return True
return False
def get_name_from_path(path):
""" Given a path, returns the name of the file (the last part in the path).
The path must not end with a separator ('\\' on windows, '/' on linux).
Returns a string containing the name. """
if not is_path(path):
return path
last = path.rfind("\\")
if last == -1:
last = path.rfind("/")
if last == -1:
raise ValueError("Path %s is not containing any name!" % path)
if last == len(path) - 1:
raise ValueError("Path %s ends with separator!" % path)
return path[last + 1 :]
def unsigned(val):
return int(val & 0xFFFFFFFF)
def cmp_unsigned(val1, val2):
""" Compares 'val1' and 'val2' as unsigned numbers. Respects the
unix 'cmp' function return values (-1, 0, 1). """
val1 = unsigned(val1)
val2 = unsigned(val2)
if val1 > val2:
return 1
if val1 < val2:
return -1
return 0
def cmp_string(val1, val2):
""" Compares 'val1' and 'val2' as unsigned numbers. Respects the
unix 'cmp' function return values (-1, 0, 1). """
if val1 > val2:
return 1
if val1 < val2:
return -1
return 0
def get_binary_name(name, cls, wide=True, trim=0):
""" Returns the binary hash of the given name. This function also checks
the predefined names in the config file based on the `cls` argument.
If `wide` is True, then it will convert the name to the wide (utf-16)
format.
If trim is != 0, then it will trim the name to `trim` chars. """
if not name:
return int(-1)
if cls is KernelException:
predefined = excfg.get("Predefined", "kernel-mode")
elif cls is UserException:
predefined = excfg.get("Predefined", "user-mode")
elif cls is KernelUserException:
predefined = excfg.get("Predefined", "kenrel-user-mode")
elif cls is Signature:
predefined = excfg.get("Predefined", "signature")
else:
raise ValueError("Invalid class %s" % cls)
if name in predefined:
return predefined[name]
if trim:
return crc32.crc32(name[:trim], wide=wide)
return crc32.crc32(name, wide=wide)
def get_binary_flags(flags, cls):
""" Returns the binary representation of the given flags.
If the `cls` is a UserException then it will use the values from 'user-mode'
config flags and the 'common' ones.
If the `cls` is a KernelException then it will use the values from
'kernel-mode' config flags and the 'common' ones.
If the `cls` is a UserException then it will use the values from
'signatures' config flags. The 'common' ones are ignored. """
cfg_cflags = excfg.get("Flags", "common")
if cls is KernelException:
cfg_flags = excfg.get("Flags", "kernel-mode")
elif cls is UserException or cls is UserGlobException:
cfg_flags = excfg.get("Flags", "user-mode")
elif cls is KernelUserException:
cfg_flags = excfg.get("Flags", "user-mode")
cfg_flags.update(excfg.get("Flags", "kernel-mode"))
cfg_flags.update(excfg.get("Flags", "kernel-user-mode"))
elif cls is Signature:
cfg_flags = excfg.get("Flags", "signatures")
cfg_cflags = []
else:
raise ValueError("Invalid class %s" % cls)
bin_flags = 0
for flag in flags.split(" "):
if flag in cfg_flags:
bin_flags = bin_flags | cfg_flags[flag]
elif flag in cfg_cflags:
bin_flags = bin_flags | cfg_cflags[flag]
else:
raise ValueError("Invalid flag " + flag)
return bin_flags
def get_sig_id(sig_id, sig_type, create_new=True):
""" If we don't have this signature in the hash_map, then add it this way;
if we request the id of a signature at different times and from different
functions, we will get either a new one, or the old one. """
if sig_type == 0 and sig_id not in SIG_IDS:
raise ValueError("invalid signature type")
if sig_id not in SIG_IDS:
if not create_new:
raise ValueError("Signature %s not present!" % sig_id)
new_id = len(SIG_IDS) + 1
new_id += (sig_type << 22)
SIG_IDS[sig_id] = new_id
elif create_new:
raise ValueError("Duplicated signature found", sig_id)
return SIG_IDS[sig_id]
def get_binary_signatures(signatures):
""" Returns a sorted list containing the binary id of each signature. For
more details see `get_sig_id`. """
if not signatures:
return []
return sorted([get_sig_id(sig, 0, False) for sig in signatures])
class IntroObject(metaclass=ABCMeta):
""" Just an interface containing method for dumping objects in binary
or textual form. """
@abstractmethod
def get_binary_header(self):
""" Returns the binary header, dependent on the object type. """
raise NotImplementedError
@abstractmethod
def get_binary(self):
""" Returns the binary contents, dependent on the object type. """
raise NotImplementedError
def _cmp(self, other):
""" Will be replaced below, and each of '__lt__', etc. will call the
proper '_cmp' method. """
raise NotImplementedError
def __lt__(self, other):
return self._cmp(other) < 0
def __le__(self, other):
return self._cmp(other) <= 0
def __gt__(self, other):
return self._cmp(other) > 0
def __ge__(self, other):
return self._cmp(other) > 0
def __eq__(self, other):
return self._cmp(other) == 0
def __ne__(self, other):
return self._cmp(other) != 0
class IntroFileHeader(IntroObject):
""" Represent the header of the exceptions file. This is written only once,
at the begining. """
def __init__(self, km_count, um_count, kum_count, umgb_count, sig_count, build):
self.km_count = km_count
self.um_count = um_count
self.kum_count = kum_count
self.umgb_count = umgb_count
self.sig_count = sig_count
self.build = build
def get_binary(self):
""" Returns a binary string containing the values from the tuple.
The format is as follows:
- HeaderMagic[32]
- VersionMajor[16]
- VersionMinor[16]
- KernelExceptionsCount[32]
- UserExceptionsCount[32]
- SignaturesCount[32]
- BuildNumber[32]
- UserGlobExceptionCount[32]
- Reserved1[2 * 32] """
return struct.pack(
"<IHHIIIIIII",
DEFAULT_FLAGS["HeaderMagic"],
excfg.get("Version", "Major"),
excfg.get("Version", "Minor"),
self.km_count,
self.um_count,
self.sig_count,
self.build,
self.umgb_count,
self.kum_count,
0,
)
def _cmp(self, other):
""" Not implemented in this class. """
return NotImplemented
def get_binary_header(self):
""" Not implemented in this class. """
return NotImplemented
class KernelException(IntroObject):
""" Represents a kernel-mode exception. For more details about it's
implementation see `get_binary`. """
def _validate_args(self):
""" Validates that the values are good. If they are missing, they will
be initialized with the default values.
Raises ValueError if anything is not valid. """
if not self.originator and self.object_type not in ("token-privs", "security-descriptor", "acl-edit", "sud-modification"):
raise ValueError("originator cannot be missing!")
if not self.object_type:
raise ValueError("object type cannot be missing!")
if not self.victim and self.object_type in (
"driver",
"driver imports",
"driver code",
"driver data",
"driver resources",
"drvobj",
"fastio",
"driver exports",
"token-privs",
"security-descriptor",
"acl-edit",
"sud-modification"
):
raise ValueError("Type %s requires a victim name!" % self.object_type)
if self.victim and self.object_type in ("msr", "ssdt", "cr4", "idt", "idt-reg", "gdt-reg", "infinity-hook", "hal-perf-counter", "interrupt-obj"):
raise ValueError("Type %s must miss victim name!" % self.object_type)
if self.flags is None:
# if no flags are given, then use the default ones
self.flags = DEFAULT_FLAGS["KernelExceptionFlags"]
elif not any(arch in self.flags for arch in ["32", "64"]):
self.flags += " 32 64"
flagsl = self.flags.split(" ")
if self.object_type == "cr4":
if ("smep" not in flagsl) and ("smap" not in flagsl):
raise ValueError("Type cr4 must flags must contain smap/smep!")
if not any(word in flagsl for word in ("read", "write", "exec")):
self.flags += " write"
if ("non-driver" in flagsl) and ("return-drv" not in flagsl):
# non-driver implies return-drv
self.flags += " return-drv"
if "return-drv" in flagsl:
raise ValueError('"return-drv" is now obsolete. Please use "return"!')
# We moved return to the common area, so add return-drv if needed (for now)
if "return" in flagsl:
self.flags += " return-drv"
if "integrity" in flagsl and self.object_type in ("token-privs", "sud-modification"):
if self.originator:
raise ValueError("Type %s with integrity flag must not have originator!" % self.object_type)
self.originator = "-"
self.originator_name = "-"
elif self.object_type in ("token-privs",) and not self.originator:
raise ValueError("Originator cannot be missing for %s without integrity flag!" % self.object_type)
if self.object_type in ("security-descriptor", "acl-edit"):
if "integrity" in flagsl:
if self.originator:
raise ValueError("Type %s with integrity flag must not have originator!" % self.object_type)
self.originator = "-"
self.originator_name = "-"
else:
raise ValueError("%s only works with integrity flag for now!" % self.object_type)
# sanitize the input
if "linux" in self.flags:
self.victim = self.victim if self.victim else "*"
else:
self.originator = self.originator.lower()
self.originator_name = self.originator_name.lower()
# for sud fields we need case sensitive hashes
if self.object_type in ("sud-modification",):
self.victim = self.victim if self.victim else "*"
else:
self.victim = self.victim.lower() if self.victim else "*"
def _complete_binary_args(self):
""" Complete self.binary dictionary with the binary representations
of the self fields.
'originator' field will be separeted into path + name. If only a name
is given then path will be equal with the name. """
self.binary["object"] = excfg.get("Types", "kernel-mode")[self.object_type]
if self.originator != self.originator_name:
bin_name = get_binary_name(self.originator_name, KernelException)
else:
bin_name = get_binary_name(self.originator_name, KernelException)
self.binary["name"] = bin_name
self.binary["path"] = -1
if self.object_type in ("sud-modification"):
self.binary["victim"] = get_binary_name(self.victim, KernelException, wide=False)
elif self.object_type in ("token-privs", "security-descriptor", "acl-edit"):
self.binary["victim"] = get_binary_name(self.victim, KernelException, wide=False, trim=IMAGE_BASE_NAME_LEN)
else:
self.binary["victim"] = get_binary_name(self.victim, KernelException)
self.binary["flags"] = get_binary_flags(self.flags, KernelException)
self.binary["signatures"] = get_binary_signatures(self.signatures)
def __init__(self, originator=None, object_type=None, victim=None, flags=None, signatures=None, **kwargs):
self.originator = originator
self.originator_name = get_name_from_path(self.originator)
self.object_type = object_type
self.victim = victim
self.flags = flags
self.signatures = signatures
self.binary = {}
self._validate_args()
self._complete_binary_args()
def _cmp(self, other):
""" Compares two KernelExceptions. The fields are compared in order:
- originator path, originator name, object, victim, flags
- signatures is ignored! """
value = cmp_unsigned(self.binary["path"], other.binary["path"])
if value:
return value
value = cmp_unsigned(self.binary["name"], other.binary["name"])
if value:
return value
value = cmp_unsigned(self.binary["object"], other.binary["object"])
if value:
return value
value = cmp_unsigned(self.binary["victim"], other.binary["victim"])
if value:
return value
value = cmp_unsigned(self.binary["flags"], other.binary["flags"])
if value:
return value
return 0
def __str__(self):
ret_str = "'%s' (%08x), '%s' (%08x), '%s' (%08x), '%s' (%02d), '%s' (%08x)" % (
self.originator,
self.binary["path"],
self.originator_name,
self.binary["name"],
self.victim,
self.binary["victim"],
self.object_type,
self.binary["object"],
self.flags,
self.binary["flags"],
)
if self.signatures:
ret_str += ", %r (%r)" % (self.signatures, self.binary["signatures"])
return ret_str
def get_binary_header(self):
""" Returns a binary string representing the header of the user-mode
exception.
The format it's as follows:
- type[8] = 1
- size[16] = 20 + len(sigs) * 4 """
sigs = len(self.signatures) if self.signatures else 0
return struct.pack("<BH", 1, 20 + (sigs * 4))
def get_binary(self):
""" Returns a binary string containing the binary representation of the
kernel-mode exception.
The format it's as follows:
- name[32]
- path[32]
- victim[32],
- flags[32]
- reserved[8]
- type[8]
- sig_count[16]
- sigs-array[32 * sig_count]
name, path - a CRC32 will be applied to them
victim - same as name and path
object_type - the corresponding value in the hash map
flags - an OR with the values from the hash map
signatures - the strings will be converted into unique numeric ids """
packed_sigs = bytes()
for sig in self.binary["signatures"]:
packed_sigs += struct.pack("<I", int(sig & 0xFFFFFFFF))
# The '& 0xffffffff' is a quick hack to force unsigned numbers
return (
struct.pack(
"<IIIIBBH",
unsigned(self.binary["name"]),
unsigned(self.binary["path"]),
unsigned(self.binary["victim"]),
unsigned(self.binary["flags"]),
0, # The reserved byte
unsigned(self.binary["object"]),
unsigned(len(self.binary["signatures"])),
)
+ packed_sigs
)
class UserException(IntroObject):
""" Represents a user-mode exception. For more details about it's
implementation see `get_binary`. """
def _validate_args(self):
""" Validates that the values are good. If they are missing, they will
be initialized with the default values.
Raises ValueError if anything is not valid. """
if not self.originator:
raise ValueError("Originator cannot be missing!")
if not self.object_type:
raise ValueError("Object type cannot be missing!")
if not self.victim and self.object_type in ("process", "module", "module imports"):
raise ValueError("Type %s requires a victim name!" % self.object_type)
if self.victim and self.victim != "*" and self.object_type == "nx_zone":
raise ValueError("Type %s must miss victim name!" % self.object_type)
if not self.process and self.object_type in ("module", "module imports"):
raise ValueError("Process cannot be missing for %s!" % self.object_type)
if self.process and self.object_type == "process":
raise ValueError("Process must be missing for %s!" % self.object_type)
if self.flags is None:
self.flags = DEFAULT_FLAGS["UserExceptionFlags"]
elif not any(arch in self.flags for arch in ["32", "64"]):
self.flags += " 32 64"
flagsl = self.flags.split(" ")
if not any(word in flagsl for word in ['read', 'write', 'exec']):
if self.object_type == 'nx_zone' or self.object_type == 'process-creation' or self.object_type == 'process-creation-dpi':
self.flags += ' exec'
else:
self.flags += " write"
flagsl = self.flags.split(" ")
# a small sanity check
if self.object_type == "nx_zone" and "exec" not in flagsl:
raise ValueError("nx_zone must have exec flag set: %s" % self.flags)
# sanitize the input
if "linux" in self.flags:
self.victim = self.victim if self.victim else "*"
self.process = self.process if self.process else None
else:
self.originator = self.originator.lower()
self.victim = self.victim.lower() if self.victim else "*"
self.process = self.process.lower() if self.process else None
def _complete_binary_args(self):
""" Complete self.binary dictionary with the binary representations
of the self fields. """
self.binary["object"] = excfg.get("Types", "user-mode")[self.object_type]
if self.object_type in (
'process', 'thread-context', 'peb32', 'peb64', 'apc-thread', 'process-creation', 'process-creation-dpi', 'instrumentation-callback') and 'module-load' not in self.flags:
if "linux" in self.flags:
self.binary['originator'] = get_binary_name(self.originator, UserException,
wide=False, trim=LIX_COMM_LEN)
else:
self.binary['originator'] = get_binary_name(self.originator, UserException,
wide=False, trim=IMAGE_BASE_NAME_LEN)
else:
self.binary["originator"] = get_binary_name(self.originator, UserException)
if self.object_type in ('process', 'thread-context', 'peb32', 'peb64', 'apc-thread', 'process-creation', 'double-agent', 'process-creation-dpi', 'instrumentation-callback'):
if "linux" in self.flags:
self.binary['victim'] = get_binary_name(self.victim, UserException,
wide=False, trim=LIX_COMM_LEN)
else:
self.binary['victim'] = get_binary_name(self.victim, UserException,
wide=False, trim=IMAGE_BASE_NAME_LEN)
else:
self.binary["victim"] = get_binary_name(self.victim, UserException)
if self.process:
self.binary["process"] = get_binary_name(
self.process, UserException, wide=False, trim=IMAGE_BASE_NAME_LEN
)
else:
self.binary["process"] = 0
self.binary["flags"] = get_binary_flags(self.flags, UserException)
self.binary["signatures"] = get_binary_signatures(self.signatures)
def _fix_name(self, name):
if not name:
return name
if name[0] == "*" and "\\x" in name:
new_name = b""
i = 0
while i < len(name):
# Let it crash in case i + 4 > len(name)... it's invalid after all
if name[i] == "\\" and name[i + 1] == "x":
new_name += bytes([int(name[i + 2 : i + 4], 16)])
i += 4
continue
else:
new_name += name[i].encode()
i += 1
return new_name
return name
def _fix_json_names(self):
self.originator = self._fix_name(self.originator)
self.victim = self._fix_name(self.victim)
self.process = self._fix_name(self.process)
def __init__(
self,
originator,
object_type,
victim=None,
process=None,
flags=None,
signatures=None,
**kwargs
):
self.originator = originator
self.object_type = object_type
self.victim = victim
self.process = process
self.flags = flags
self.signatures = signatures
self.binary = {}
self._validate_args()
self._fix_json_names()
self._complete_binary_args()
def _cmp(self, other):
""" Compares two UserExceptions by the binary value of the fields.
The fields are compared in the following order:
- originator, object, victim, process, flags.
- signatures is ignored! """
value = cmp_unsigned(self.binary["originator"], other.binary["originator"])
if value:
return value
value = cmp_unsigned(self.binary["object"], other.binary["object"])
if value:
return value
value = cmp_unsigned(self.binary["victim"], other.binary["victim"])
if value:
return value
value = cmp_unsigned(self.binary["process"], other.binary["process"])
if value:
return value
value = cmp_unsigned(self.binary["flags"], other.binary["flags"])
if value:
return value
return 0
def __str__(self):
ret_str = "'%s' (%08x), '%s' (%08x), '%s' (%08x), '%s' (%02d), '%s' (%08x)" % (
self.originator,
self.binary["originator"],
self.victim,
self.binary["victim"],
self.process,
self.binary["process"],
self.object_type,
self.binary["object"],
self.flags,
self.binary["flags"],
)
if self.signatures:
ret_str += ", %r (%r)" % (self.signatures, self.binary["signatures"])
return ret_str
def get_binary_header(self):
""" Returns a binary string representing the header of the user-mode
exception.
The format it's as follows:
- type[8] = 2
- size[16] = 20 + len(sigs) * 4 """
sigs = len(self.signatures) if self.signatures else 0
return struct.pack("<BH", 2, 20 + (sigs * 4))
def get_binary(self):
""" Returns a binary string containing the binary representation of the
user-mode exception.
The format it's as follows:
- originator[32]
- victim[32]
- process[32],
- flags[32]
- reserved[8]
- type[8]
- sig_count[8]
- sigs-array[32 * sig_count]
process - truncated to 15 chars (including NULL terminator)
victim - if object_type is 'process' then it will be truncated same as 'process'
originator, - same as victim
object_type - the corresponding value in the hash map
flags - an OR with the values from the hash map
signatures - the strings will be converted into unique numeric ids """
packed_sigs = bytes()
for sig in self.binary["signatures"]:
packed_sigs += struct.pack("<I", unsigned(sig))
if "ignore" in self.flags:
print(self)
# The '& 0xffffffff' is a quick hack to force unsigned numbers
return (
struct.pack(
"<IIIIBBH",
unsigned(self.binary["originator"]),
unsigned(self.binary["victim"]),
unsigned(self.binary["process"]),
unsigned(self.binary["flags"]),
0, # The reserved byte
unsigned(self.binary["object"]),
unsigned(len(self.binary["signatures"])),
)
+ packed_sigs
)
class UserApcException(IntroObject):
""" Represents a user-mode exception. For more details about it's
implementation see `get_binary`. """
def _validate_args(self):
""" Validates that the values are good. If they are missing, they will
be initialized with the default values.
Raises ValueError if anything is not valid. """
if not self.originator:
raise ValueError("Originator cannot be missing!")
if not self.object_type:
raise ValueError("Object type cannot be missing!")
if not self.victim and self.object_type in ("process", "module", "module imports"):
raise ValueError("Type %s requires a victim name!" % self.object_type)
if self.victim and self.object_type == "nx_zone":
raise ValueError("Type %s must miss victim name!" % self.object_type)
if not self.process and self.object_type in ("module", "module imports"):
raise ValueError("Process cannot be missing for %s!" % self.object_type)
if self.process and self.object_type == "process":
raise ValueError("Process must be missing for %s!" % self.object_type)
if self.flags is None:
self.flags = DEFAULT_FLAGS["UserExceptionFlags"]
elif not any(arch in self.flags for arch in ["32", "64"]):
self.flags += " 32 64"
flagsl = self.flags.split(" ")
if not any(word in flagsl for word in ["read", "write", "exec"]):
if self.object_type == "nx_zone":
self.flags += " exec"
else:
self.flags += " write"
flagsl = self.flags.split(" ")
# a small sanity check
if self.object_type == "nx_zone" and "exec" not in flagsl:
raise ValueError("nx_zone must have exec flag set: %s" % self.flags)
# sanitize the input
if "linux" in self.flags:
self.victim = self.victim if self.victim else "*"
self.process = self.process if self.process else None
else:
self.originator = self.originator.lower()
self.victim = self.victim.lower() if self.victim else "*"
self.process = self.process.lower() if self.process else None
def _complete_binary_args(self):
""" Complete self.binary dictionary with the binary representations
of the self fields. """
self.binary["object"] = excfg.get("Types", "user-mode")[self.object_type]
if (
self.object_type in ("process", "thread-context", "peb32", "peb64", "apc-thread", "double-agent", "instrumentation-callback")
and "module-load" not in self.flags
):
self.binary["originator"] = get_binary_name(
self.originator, UserException, wide=False, trim=IMAGE_BASE_NAME_LEN
)
else:
self.binary["originator"] = get_binary_name(self.originator, UserException)
if self.object_type in ("process", "thread-context", "peb32", "peb64", "apc-thread", "double-agent", "instrumentation-callback"):
self.binary["victim"] = get_binary_name(
self.victim, UserException, wide=False, trim=IMAGE_BASE_NAME_LEN
)
else:
self.binary["victim"] = get_binary_name(self.victim, UserException)
if self.process:
self.binary["process"] = get_binary_name(
self.process, UserException, wide=False, trim=IMAGE_BASE_NAME_LEN
)
else:
self.binary["process"] = 0
self.binary["flags"] = get_binary_flags(self.flags, UserException)
self.binary["signatures"] = get_binary_signatures(self.signatures)
def __init__(
self,
originator,
object_type,
victim=None,
process=None,
flags=None,
signatures=None,
**kwargs
):
self.originator = originator
self.object_type = object_type
self.victim = victim
self.process = process
self.flags = flags
self.signatures = signatures
self.binary = {}
self._validate_args()
self._complete_binary_args()
def _cmp(self, other):
""" Compares two UserExceptions by the binary value of the fields.
The fields are compared in the following order:
- originator, object, victim, process, flags.
- signatures is ignored! """
value = cmp_unsigned(self.binary["originator"], other.binary["originator"])
if value:
return value
value = cmp_unsigned(self.binary["object"], other.binary["object"])
if value:
return value
value = cmp_unsigned(self.binary["victim"], other.binary["victim"])
if value:
return value
value = cmp_unsigned(self.binary["process"], other.binary["process"])
if value:
return value
value = cmp_unsigned(self.binary["flags"], other.binary["flags"])
if value:
return value
return 0
def __str__(self):
ret_str = "'%s' (%08x), '%s' (%08x), '%s' (%08x), '%s' (%02d), '%s' (%08x)" % (
self.originator,
self.binary["originator"],
self.victim,
self.binary["victim"],
self.process,
self.binary["process"],
self.object_type,
self.binary["object"],
self.flags,
self.binary["flags"],
)
if self.signatures:
ret_str += ", %r (%r)" % (self.signatures, self.binary["signatures"])
return ret_str
def get_binary_header(self):
""" Returns a binary string representing the header of the user-mode
exception.
The format it's as follows:
- type[8] = 9
- size[16] = 20 + len(sigs) * 4 """
sigs = len(self.signatures) if self.signatures else 0
return struct.pack("<BH", 9, 20 + (sigs * 4))
def get_binary(self):
""" Returns a binary string containing the binary representation of the
user-mode exception.
The format it's as follows:
- originator[32]
- victim[32]
- process[32],
- flags[32]
- reserved[8]
- type[8]
- sig_count[8]
- sigs-array[32 * sig_count]
process - truncated to 15 chars (including NULL terminator)
victim - if object_type is 'process' then it will be truncated same as 'process'
originator, - same as victim
object_type - the corresponding value in the hash map
flags - an OR with the values from the hash map
signatures - the strings will be converted into unique numeric ids """
packed_sigs = bytes()
for sig in self.binary["signatures"]:
packed_sigs += struct.pack("<I", unsigned(sig))
if "ignore" in self.flags:
print(self)
# The '& 0xffffffff' is a quick hack to force unsigned numbers
return (
struct.pack(
"<IIIIBBH",
unsigned(self.binary["originator"]),
unsigned(self.binary["victim"]),
unsigned(self.binary["process"]),
unsigned(self.binary["flags"]),
0, # The reserved byte
unsigned(self.binary["object"]),
unsigned(len(self.binary["signatures"])),
)
+ packed_sigs
)
class UserGlobException(IntroObject):
""" Represents a user-mode exception (glob match). For more details about it's
implementation see `get_binary`. """
def _validate_glob(self, pattern):
pattern_chars = re.sub(r"\[[^]]+\]|\?", "", pattern)
items = re.findall(r"\[[^]]+\]|\?", pattern)
if len(pattern_chars) + len(items) > IMAGE_BASE_NAME_LEN:
raise ValueError("Pattern too long: %s" % pattern)
def _validate_args(self):
""" Validates that the values are good. If they are missing, they will
be initialized with the default values.
Raises ValueError if anything is not valid. """
glob_items = ["*", "[", "]", "?", "\\\\"]
if not self.originator:
raise ValueError("Originator cannot be missing!")
if not self.object_type:
raise ValueError("Object type cannot be missing!")
if not self.victim and self.object_type in ("process", "module", "module imports"):
raise ValueError("Type %s requires a victim name!" % self.object_type)
if self.victim and self.object_type == "nx_zone":
raise ValueError("Type %s must miss victim name!" % self.object_type)
if not self.process and self.object_type in ("module", "module imports"):
raise ValueError("Process cannot be missing for %s!" % self.object_type)
if self.process and self.object_type == "process":
raise ValueError("Process must be missing for %s!" % self.object_type)
self.process = self.process if self.process else ""
if not any(item in self.originator + self.victim + self.process for item in glob_items):
raise ValueError(
"At least one field (process, originator, victim) must contain glob items(*, ?, [, ] )."
)
if self.process:
self._validate_glob(self.process)
if self.victim:
self._validate_glob(self.victim)
if self.originator:
self._validate_glob(self.originator)
if self.flags is None:
self.flags = DEFAULT_FLAGS["UserExceptionFlags"]
elif not any(arch in self.flags for arch in ["32", "64"]):
self.flags += " 32 64"
flagsl = self.flags.split(" ")
if not any(word in flagsl for word in ["read", "write", "exec"]):
if self.object_type == "nx_zone" or self.object_type == 'process-creation' or self.object_type == 'process-creation-dpi':
self.flags += " exec"
else:
self.flags += " write"
flagsl = self.flags.split(" ")
# a small sanity check
if self.object_type == "nx_zone" and "exec" not in flagsl:
raise ValueError("nx_zone must have exec flag set: %s" % self.flags)
self.victim = self.victim if self.victim else "*"
self.process = self.process if self.process != "" else "*"
def _complete_binary_args(self):
""" Complete self.binary dictionary with the binary representations
of the self fields. """
self.binary["object"] = excfg.get("Types", "user-mode")[self.object_type]
if self.object_type in ("process", "thread-context") and "module-load" not in self.flags:
self.binary["originator"] = self.originator
else:
self.binary["originator"] = self.originator
if self.object_type in ("process", "thread-context"):
self.binary["victim"] = self.victim
else:
self.binary["victim"] = self.victim
if self.process:
self.binary["process"] = self.process
else:
self.binary["process"] = "*"
self.binary["flags"] = get_binary_flags(self.flags, UserGlobException)
self.binary["signatures"] = get_binary_signatures(self.signatures)
def __init__(
self,
originator,
object_type,
victim=None,
process=None,
flags=None,
signatures=None,
**kwargs
):
self.originator = originator
self.object_type = object_type
self.victim = victim
self.process = process
self.flags = flags
self.signatures = signatures
self.binary = {}
self._validate_args()
self._complete_binary_args()
def _cmp(self, other):
""" Compares two UserGlobException by the binary value of the fields.
The fields are compared in the following order:
- originator, object, victim, process, flags.
- signatures is ignored! """
value = cmp_string(self.binary["originator"], other.binary["originator"])
if value:
return value
value = cmp_string(self.binary["object"], other.binary["object"])
if value:
return value
value = cmp_string(self.binary["victim"], other.binary["victim"])
if value:
return value
value = cmp_string(self.binary["process"], other.binary["process"])
if value:
return value
value = cmp_unsigned(self.binary["flags"], other.binary["flags"])
if value:
return value
return 0
def __str__(self):
ret_str = "'%s' (%s), '%s' (%s), '%s' (%s), '%s' (%02d), '%s' (%08x)" % (
self.originator,
self.binary["originator"],
self.victim,
self.binary["victim"],
self.process,
self.binary["process"],
self.object_type,
self.binary["object"],
self.flags,
self.binary["flags"],
)
if self.signatures:
ret_str += ", %r (%r)" % (self.signatures, self.binary["signatures"])
return ret_str
def get_binary_header(self):
""" Returns a binary string representing the header of the user-mode (glob match)
exception.
The format it's as follows:
- type[8] = 6
- size[16] = 8 + len(originator) + len(victim) + len(process) len(sigs) * 4 """
sigs = len(self.signatures) if self.signatures else 0
len_victim = len(self.victim) + 1 if self.victim else 0
len_originator = len(self.originator) + 1 if self.originator else 0
len_process = len(self.process) + 1 if self.process else 0
size = 8 + len_originator + len_victim + len_process
return struct.pack("<BH", 6, size + (sigs * 4))
def get_binary(self):
""" Returns a binary string containing the binary representation of the
user-mode exception (glob match).
The format it's as follows:
- flags[32]
- reserved[8]
- type[8]
- sig_count[8]
- originator[32]
- victim[32]
- process[32],
- sigs-array[32 * sig_count]
process - regex
victim - regex
originator - regex
object_type - the corresponding value in the hash map
flags - an OR with the values from the hash map
signatures - the strings will be converted into unique numeric ids """
packed_sigs = bytes()
for sig in self.binary["signatures"]:
packed_sigs += struct.pack("<I", unsigned(sig))
if "ignore" in self.flags:
print(self)
# The '& 0xffffffff' is a quick hack to force unsigned numbers
return (
struct.pack(
"<IBBH%ds%ds%ds"
% (
len(self.binary["originator"]) + 1, # add NULL-terminator
len(self.binary["victim"]) + 1, # add NULL-terminator
len(self.binary["process"]) + 1,
), # add NULL-terminator
unsigned(self.binary["flags"]),
0, # The reserved byte
unsigned(self.binary["object"]),
unsigned(len(self.binary["signatures"])),
bytes(self.binary["originator"], "utf-8"),
bytes(self.binary["victim"], "utf-8"),
bytes(self.binary["process"], "utf-8"),
)
+ packed_sigs
)
class KernelUserException(IntroObject):
""" Represents a kernel-user exception. For more details about it's
implementation see `get_binary`. """
def _validate_args(self):
""" Validates that the values are good. If they are missing, they will
be initialized with the default values.
Raises ValueError if anything is not valid. """
if not self.originator:
raise ValueError("Originator cannot be missing!")
if not self.object_type:
raise ValueError("Object type cannot be missing!")
if not self.victim:
raise ValueError("Victim cannot be missing!" % self.object_type)
if self.flags is None:
# if no flags are given, then use the default ones
self.flags = DEFAULT_FLAGS["KernelExceptionFlags"]
elif not any(arch in self.flags for arch in ["32", "64"]):
self.flags += " 32 64"
flagsl = self.flags.split(" ")
if not any(word in flagsl for word in ("read", "write", "exec")):
self.flags += " write"
if ("non-driver" in flagsl) and ("return-drv" not in flagsl):
# non-driver implies return-drv
self.flags += " return-drv"
if "return" in flagsl:
self.flags += " return-drv"
if "user" in flagsl and "kernel" in flagsl:
raise ValueError("Both user and kernel injection flags were given!")
if "linux" in self.flags:
self.victim = self.victim if self.victim else "*"
self.originator = self.originator if self.originator else "*"
self.process = self.process if self.process else "*"
else:
self.originator = self.originator.lower()
self.victim = self.victim.lower() if self.victim else "*"
self.process = self.process.lower() if self.process else "*"
def _complete_binary_args(self):
""" Complete self.binary dictionary with the binary representations
of the self fields.
'originator' field will be separeted into path + name. If only a name
is given then path will be equal with the name. """
self.binary["object"] = excfg.get("Types", "kernel-user-mode")[self.object_type]
if "user" in self.flags:
self.binary["originator"] = get_binary_name(self.originator, UserException, wide=False, trim=IMAGE_BASE_NAME_LEN)
else:
self.binary["originator"] = get_binary_name(self.originator, KernelException)
self.binary["victim"] = get_binary_name(self.victim, UserException)
self.binary["flags"] = get_binary_flags(self.flags, KernelUserException)
self.binary["signatures"] = get_binary_signatures(self.signatures)
self.binary["process"] = get_binary_name(self.process, UserException, wide=False, trim=IMAGE_BASE_NAME_LEN)
def __init__(self, process=None, originator=None, object_type=None, victim=None, flags=None, signatures=None, **kwargs):
self.originator = originator
self.object_type = object_type
self.process = process
self.victim = victim
self.flags = flags
self.signatures = signatures
self.binary = {}
self._validate_args()
self._complete_binary_args()
def _cmp(self, other):
""" Compares two KernelExceptions. The fields are compared in order:
- originator path, originator name, object, victim, flags
- signatures is ignored! """
value = cmp_unsigned(self.binary["originator"], other.binary["originator"])
if value:
return value
value = cmp_unsigned(self.binary["process"], other.binary["process"])
if value:
return value
value = cmp_unsigned(self.binary["object"], other.binary["object"])
if value:
return value
value = cmp_unsigned(self.binary["victim"], other.binary["victim"])
if value:
return value
value = cmp_unsigned(self.binary["flags"], other.binary["flags"])
if value:
return value
return 0
def __str__(self):
ret_str = "'%s' (%08x), '%s' (%08x), '%s' (%08x), '%s' (%02d), '%s' (%08x)" % (
self.process,
self.binary["process"],
self.originator,
self.binary["originator"],
self.victim,
self.binary["victim"],
self.object_type,
self.binary["object"],
self.flags,
self.binary["flags"],
)
if self.signatures:
ret_str += ", %r (%r)" % (self.signatures, self.binary["signatures"])
return ret_str
def get_binary_header(self):
""" Returns a binary string representing the header of the user-mode
exception.
The format it's as follows:
- type[8] = 1
- size[16] = 20 + len(sigs) * 4 """
sigs = len(self.signatures) if self.signatures else 0
return struct.pack("<BH", 14, 20 + (sigs * 4))
def get_binary(self):
""" Returns a binary string containing the binary representation of the
kernel-mode exception.
The format it's as follows:
- name[32]
- path[32]
- victim[32],
- flags[32]
- reserved[8]
- type[8]
- sig_count[16]
- sigs-array[32 * sig_count]
name, path - a CRC32 will be applied to them
victim - same as name and path
object_type - the corresponding value in the hash map
flags - an OR with the values from the hash map
signatures - the strings will be converted into unique numeric ids """
packed_sigs = bytes()
for sig in self.binary["signatures"]:
packed_sigs += struct.pack("<I", int(sig & 0xFFFFFFFF))
# The '& 0xffffffff' is a quick hack to force unsigned numbers
return (
struct.pack(
"<IIIIBBH",
unsigned(self.binary["originator"]),
unsigned(self.binary["victim"]),
unsigned(self.binary["process"]),
unsigned(self.binary["flags"]),
0, # The reserved byte
unsigned(self.binary["object"]),
unsigned(len(self.binary["signatures"])),
)
+ packed_sigs
)
class Signature(IntroObject):
""" Represents an exception signature. For more details about it's implementation see it's
subclasses. """
def _cmp(self, other):
pass
def get_binary_header(self):
pass
def get_binary(self):
pass
class ExportSignature(Signature):
""" Represents an export signature. For more details about it's implementation see
`get_binary`. """
def _validate_args(self):
""" Validates that the values are good. If they are missing, they will
be initialized with the default values. """
if not self.sig_id:
raise ValueError("id is required!")
if not self.hashes:
raise ValueError("hashes is required!")
if not self.library:
raise ValueError("library is required!")
if not self.flags:
self.flags = DEFAULT_FLAGS["SignatureFlags"]
elif not any(arch in self.flags for arch in ["32", "64"]):
self.flags += " 32 64"
def _complete_binary_args(self):
""" Complete self.binary dictionary with the binary representations
of the self fields. """
self.binary["id"] = get_sig_id(self.sig_id, excfg.get("SignatureType", "export"))
self.binary["flags"] = get_binary_flags(self.flags, Signature)
self.binary["library"] = get_binary_name(self.library, UserException, wide=True)
self.binary["hashes"] = []
for hl in self.hashes:
int_hash_list = []
int_hash_list.append(
{
"name": get_binary_name(hl["name"], Signature, wide=False),
"delta": int(hl["delta"]),
}
)
self.binary["hashes"].append(int_hash_list)
def __init__(self, sig_id, hashes, library, flags=None, **kwargs):
self.sig_id = sig_id
self.library = library
self.hashes = hashes
self.flags = flags
self.binary = {}
self._validate_args()
self._complete_binary_args()
def _cmp(self, other):
""" Signatures must have an unique ID. So we can safely compare them
based on ID only. """
return cmp_unsigned(self.binary["id"], other.binary["id"])
def __str__(self):
return "'%s' (%03d), '%s' (%08x), '%s' (%08x), %r" % (
self.sig_id,
self.binary["id"],
self.library,
self.binary["library"],
self.flags,
self.binary["flags"],
self.binary["hashes"],
)
def get_binary_header(self):
""" Returns a binary string representing the header of the signature
The format it's as follows:
- type[8] = 3
- size[16] = 12/10 + len(hashes) + hash_size * total_size_of_hashes """
struct_size = 16
hashes_size = len(self.hashes) * 8
return struct.pack("<BH", 4, struct_size + hashes_size)
def get_binary(self):
""" Returns a binary string containing the binary representation of the
signature.
The format it's as follows:
- id[32]
- flags[32]
- score[8]
- hash_list_count[8]
- hash-list-array[32 * hash_count] """
packed_hashes = bytes()
for hash_list in self.binary["hashes"]:
for helem in hash_list:
packed_hashes += struct.pack("<HHI", helem["delta"], 0, unsigned(helem["name"]))
return (
struct.pack(
"<IIIBBBB",
unsigned(self.binary["id"]),
unsigned(self.binary["flags"]),
unsigned(self.binary["library"]),
unsigned(len(self.binary["hashes"])),
0,
0,
0,
)
+ packed_hashes
)
class ValueSignature(Signature):
""" Represents a value signature. For more details about it's
implementation see `get_binary`. """
def _validate_args(self):
""" Validates that the values are good. If they are missing, they will
be initialized with the default values. """
if not self.sig_id:
raise ValueError("id is required!")
if self.score == 0:
raise ValueError("score is required!")
if not self.hashes:
raise ValueError("hashes is required!")
if not self.flags:
self.flags = DEFAULT_FLAGS["SignatureFlags"]
elif not any(arch in self.flags for arch in ["32", "64"]):
self.flags += " 32 64"
def _complete_binary_args(self):
""" Complete self.binary dictionary with the binary representations
of the self fields. """
self.binary["id"] = get_sig_id(self.sig_id, excfg.get("SignatureType", "value"))
self.binary["flags"] = get_binary_flags(self.flags, Signature)
self.binary["hashes"] = []
for hlist in self.hashes:
int_hash_list = []
inj_hash = hlist
inj_hash["hash"] = int(hlist["hash"], 16)
int_hash_list.append(inj_hash)
self.binary["hashes"].append(int_hash_list)
def __init__(self, sig_id, hashes, score=0, flags=None, **kwargs):
self.sig_id = sig_id
self.score = score
self.hashes = hashes
self.flags = flags
self.binary = {}
self._validate_args()
self._complete_binary_args()
def _cmp(self, other):
""" Signatures must have an unique ID. So we can safely compare them
based on ID only. """
return cmp_unsigned(self.binary["id"], other.binary["id"])
def __str__(self):
return "'%s' (%03d), '%s' (%08x), %02d, %r" % (
self.sig_id,
self.binary["id"],
self.flags,
self.binary["flags"],
self.score,
self.binary["hashes"],
)
def get_binary_header(self):
""" Returns a binary string representing the header of the signature
The format it's as follows:
- type[8] = 3
- size[16] = 12/10 + len(hashes) + hash_size * total_size_of_hashes """
struct_size = 12
hashes_size = len(self.hashes) * 12
return struct.pack("<BH", 5, struct_size + hashes_size)
def get_binary(self):
""" Returns a binary string containing the binary representation of the
signature.
The format it's as follows:
- id[32]
- flags[32]
- score[8]
- hash_list_count[8]
- hash-list-array[32 * hash_count] """
packed_hashes = bytes()
for hash_list in self.binary["hashes"]:
for he in hash_list:
packed_hashes += struct.pack("<HHII", he["offset"], he["size"], 0, he["hash"])
return (
struct.pack(
"<IIBBBB",
unsigned(self.binary["id"]),
unsigned(self.binary["flags"]),
unsigned(self.score),
unsigned(len(self.binary["hashes"])),
0,
0,
)
+ packed_hashes
)
class CbSignature(Signature):
""" Represents a codeblocks signature. For more details about it's
implementation see `get_binary`. """
def _validate_args(self):
""" Validates that the values are good. If they are missing, they will
be initialized with the default values. """
if not self.sig_id:
raise ValueError("id is required!")
if self.score == 0:
raise ValueError("score is required!")
if not self.hashes:
raise ValueError("hashes is required!")
if not self.flags:
self.flags = DEFAULT_FLAGS["SignatureFlags"]
elif not any(arch in self.flags for arch in ["32", "64"]):
self.flags += " 32 64"
def _complete_binary_args(self):
""" Complete self.binary dictionary with the binary representations
of the self fields. """
self.binary["id"] = get_sig_id(self.sig_id, excfg.get("SignatureType", "codeblocks"))
self.binary["flags"] = get_binary_flags(self.flags, Signature)
self.binary["hashes"] = []
for hl in self.hashes:
int_hash_list = []
for he in hl:
int_hash_list.append(int(he, 16))
int_hash_list.sort()
self.binary["hashes"].append(int_hash_list)
def __init__(self, sig_id, hashes, score=0, flags=None, **kwargs):
self.sig_id = sig_id
self.score = score
self.hashes = hashes
self.flags = flags
self.binary = {}
self._validate_args()
self._complete_binary_args()
def _cmp(self, other):
""" Signatures must have an unique ID. So we can safely compare them
based on ID only. """
return cmp_unsigned(self.binary["id"], other.binary["id"])
def __str__(self):
return "'%s' (%03d), '%s' (%08x), %02d, %r" % (
self.sig_id,
self.binary["id"],
self.flags,
self.binary["flags"],
self.score,
self.binary["hashes"],
)
def get_binary_header(self):
""" Returns a binary string representing the header of the signature
The format it's as follows:
- type[8] = 3
- size[16] = 12/10 + len(hashes) + hash_size * total_size_of_hashes """
struct_size = 10
hashes_size = 0
for hash_list in self.hashes:
hashes_size += len(hash_list) * 4
hashes_size += len(self.hashes)
return struct.pack("<BH", 3, struct_size + hashes_size)
def get_binary(self):
""" Returns a binary string containing the binary representation of the
signature.
The format it's as follows:
- id[32]
- flags[32]
- score[8]
- hash_list_count[8]
- hash-list-array[32 * hash_count] """
packed_hashes = bytes()
for hash_list in self.binary["hashes"]:
packed_hashes += struct.pack("B", len(hash_list))
for helem in hash_list:
packed_hashes += struct.pack("<I", helem)
return (
struct.pack(
"<IIBB",
unsigned(self.binary["id"]),
unsigned(self.binary["flags"]),
unsigned(self.score),
unsigned(len(self.binary["hashes"])),
)
+ packed_hashes
)
class ValueCodeSignature(Signature):
""" Represents a value code extended(pattern) signature. For more details about it's
implementation see `get_binary`. """
def _validate_args(self):
""" Validates that the values are good. If they are missing, they will
be initialized with the default values. """
if not self.sig_id:
raise ValueError("id is required!")
if not self.offset:
self.offset = 0
if self.offset > 32767:
raise ValueError("required offset >= 32767 (MAX_INT16)")
if self.offset < -32768:
raise ValueError("required offset <= -32768 (MIN_INT16)")
if not self.pattern:
raise ValueError("pattern is required!")
if not self.flags:
self.flags = DEFAULT_FLAGS["SignatureFlags"]
elif not any(arch in self.flags for arch in ["32", "64"]):
self.flags += " 32 64"
def _complete_binary_args(self):
""" Complete self.binary dictionary with the binary representations
of the self fields. """
self.binary["id"] = get_sig_id(self.sig_id, excfg.get("SignatureType", "value-code"))
self.binary["flags"] = get_binary_flags(self.flags, Signature)
self.binary["pattern"] = list()
for pattern_elem in self.pattern:
self.binary["pattern"].append(int(pattern_elem, 16))
def __init__(self, sig_id, pattern, offset, flags=None, **kwargs):
self.sig_id = sig_id
self.offset = offset
self.pattern = pattern
self.flags = flags
self.binary = {}
self._validate_args()
self._complete_binary_args()
def _cmp(self, other):
""" Signatures must have an unique ID. So we can safely compare them
based on ID only. """
return cmp_unsigned(self.binary["id"], other.binary["id"])
def __str__(self):
return "'%s' (%03d), '%s' (%08x), %02d, %r" % (
self.sig_id,
self.binary["id"],
self.flags,
self.binary["flags"],
self.offset,
self.binary["pattern"],
)
def get_binary_header(self):
""" Returns a binary string representing the header of the signature
The format it's as follows:
- type[8] = 8
- size[16] = 12 + pattern_items * sizeof_pattern_item """
struct_size = 12
pattern_size = len(self.pattern) * 2
print(pattern_size)
return struct.pack("<BH", 8, struct_size + pattern_size)
def get_binary(self):
""" Returns a binary string containing the binary representation of the
signature.
The format it's as follows:
- id[32]
- flags[32]
- offset[16]
- length[16]
- pattern-array[16 * pattern_items] """
packed_pattern = bytes()
for pattern_elem in self.binary["pattern"]:
packed_pattern += struct.pack("<H", pattern_elem)
return (
struct.pack(
"<IIhH",
unsigned(self.binary["id"]),
unsigned(self.binary["flags"]),
self.offset,
unsigned(len(self.binary["pattern"])),
)
+ packed_pattern
)
class IdtSignature(Signature):
""" Represents an idt signature. For more details about it's
implementation see `get_binary`. """
def _validate_args(self):
""" Validates that the values are good. If they are missing, they will
be initialized with the default values. """
if not self.sig_id:
raise ValueError("id is required!")
if self.entry is None:
raise ValueError("entry is required!")
if not self.flags:
self.flags = DEFAULT_FLAGS["SignatureFlags"]
elif not any(arch in self.flags for arch in ["32", "64"]):
self.flags += " 32 64"
def _complete_binary_args(self):
""" Complete self.binary dictionary with the binary representations
of the self fields. """
self.binary["id"] = get_sig_id(self.sig_id, excfg.get("SignatureType", "idt"))
self.binary["flags"] = get_binary_flags(self.flags, Signature)
self.binary["entry"] = self.entry
def __init__(self, sig_id, entry, flags=None, **kwargs):
self.sig_id = sig_id
self.entry = entry
self.flags = flags
self.binary = {}
self._validate_args()
self._complete_binary_args()
def _cmp(self, other):
""" Signatures must have an unique ID. So we can safely compare them
based on ID only. """
return cmp_unsigned(self.binary["id"], other.binary["id"])
def __str__(self):
return "'%s' (%03d), '%s' (%08x), %02d, (%02d)" % (
self.sig_id,
self.binary["id"],
self.flags,
self.binary["flags"],
self.entry,
self.binary["entry"],
)
def get_binary_header(self):
""" Returns a binary string representing the header of the signature
The format it's as follows:
- type[8] = 10
- size[16] = 10/12"""
struct_size = 12
return struct.pack("<BH", 10, struct_size)
def get_binary(self):
""" Returns a binary string containing the binary representation of the
signature.
The format it's as follows:
- id[32]
- flags[32]
- entry[1]
- _reserved[3]
"""
return struct.pack(
"<IIBBBB",
unsigned(self.binary["id"]),
unsigned(self.binary["flags"]),
unsigned(self.entry),
0,
0,
0,
)
class VersionOsSignature(Signature):
""" Represents a version os signature. For more details about it's
implementation see `get_binary`. """
def _validate_args(self):
""" Validates that the values are good. If they are missing, they will
be initialized with the default values. """
if not self.sig_id:
raise ValueError('id is required!')
if self.minimum is None:
raise ValueError('minimum version is required!')
if '.' in self.minimum and '.' not in self.maximum:
raise ValueError('invalid os version format!')
if '.' not in self.minimum and '.' in self.maximum:
raise ValueError('invalid os version format!')
if '.' in self.minimum and len(self.minimum.split('.')) != 3:
raise ValueError('invalid os version format!')
if self.maximum is None:
raise ValueError('maximum version is required!')
if '.' in self.maximum and len(self.maximum.split('.')) != 3:
raise ValueError('invalid os version format!')
if not self.flags:
self.flags = DEFAULT_FLAGS['SignatureFlags']
elif not any(arch in self.flags for arch in ['32', '64']):
self.flags += ' 32 64'
def _complete_binary_args(self):
""" Complete self.binary dictionary with the binary representations
of the self fields. """
self.binary['id'] = self.binary["id"] = get_sig_id(self.sig_id, excfg.get("SignatureType", "version-os"))
self.binary['flags'] = get_binary_flags(self.flags, Signature)
if '.' in self.minimum:
values = list()
for item in self.minimum.split('.'):
if item == '*':
values.append(0)
else:
values.append(unsigned(int(item)))
self.binary["minimum"] = {"version" : values[0], "patch" : values[1], "sublevel" :
values[2]}
else:
if self.minimum == '*':
self.binary['minimum'] = {"value" : 0}
else:
self.binary['minimum'] = {"value" : unsigned(int(self.minimum))}
if '.' in self.maximum:
values = list()
for item in self.maximum.split('.'):
if item == '*':
values.append(0xffff)
else:
values.append(unsigned(int(item)))
self.binary["maximum"] = {"version" : values[0], "patch" : values[1], "sublevel" :
values[2]}
else:
if self.maximum == '*':
self.binary['maximum'] = {"value" : 0xffff}
else:
self.binary['maximum'] = {"value" : unsigned(int(self.maximum))}
def __init__(self, sig_id, minimum, maximum, flags=None, **kwargs):
self.sig_id = sig_id
self.minimum = minimum
self.maximum = maximum
self.flags = flags
self.binary = {}
self._validate_args()
self._complete_binary_args()
def _cmp(self, other):
""" Signatures must have an unique ID. So we can safely compare them
based on ID only. """
return cmp_unsigned(self.binary['id'], other.binary['id'])
def __str__(self):
if 'value' in self.binary['minimum']:
return "'%s' (%04d), '%s' (%04x), %s (0x%04x), '%s' (0x%04x)" % (self.sig_id, self.binary['id'],
self.flags, self.binary['flags'],
self.minimum, self.binary['minimum']['value'],
self.maximum, self.binary['maximum']['value'])
else:
return "'%s' (%04d), '%s' (%04x), '%s' (%d.%d.%d), '%s' (%d.%d.%d)" % (self.sig_id, self.binary['id'],
self.flags, self.binary['flags'], self.minimum, self.binary['minimum']['version'],
self.binary['minimum']['patch'], self.binary['minimum']['sublevel'],
self.maximum, self.binary['maximum']['version'], self.binary['maximum']['patch'], self.binary['maximum']['sublevel'])
def get_binary_header(self):
""" Returns a binary string representing the header of the signature
The format it's as follows:
- type[8] = 11
- size[16] = 10/12"""
struct_size = 24
return struct.pack('<BH', 11, struct_size)
def get_binary(self):
""" Returns a binary string containing the binary representation of the
signature.
The format it's as follows:
- id[32]
- flags[32]
- minimum[32]
- maximum[32]
"""
if 'value' in self.binary["minimum"]:
return struct.pack('<IIQQ',
unsigned(self.binary['id']),
unsigned(self.binary['flags']),
unsigned(self.binary['minimum']['value']),
unsigned(self.binary['maximum']['value']))
else:
return struct.pack('<IIBBHHBBBBHHBB',
unsigned(self.binary['id']),
unsigned(self.binary['flags']),
unsigned(self.binary['minimum']['version']),
unsigned(self.binary['minimum']['patch']),
unsigned(self.binary['minimum']['sublevel']),
0,
0,
0,
unsigned(self.binary['maximum']['version']),
unsigned(self.binary['maximum']['patch']),
unsigned(self.binary['maximum']['sublevel']),
0xffff,
0,
0)
class VersionIntroSignature(Signature):
""" Represents a version os signature. For more details about it's
implementation see `get_binary`. """
def _validate_args(self):
""" Validates that the values are good. If they are missing, they will
be initialized with the default values. """
if not self.sig_id:
raise ValueError('id is required!')
if self.minimum is None:
raise ValueError('minimum version is required!')
if '.' not in self.minimum:
raise ValueError('invalid intro version format!')
if len(self.minimum.split('.')) != 3:
raise ValueError('invalid intro version format!')
if self.maximum is None:
raise ValueError('maximum version is required!')
if '.' not in self.maximum:
raise ValueError('invalid intro version format!')
if len(self.maximum.split('.')) != 3:
raise ValueError('invalid intro version format!')
if not self.flags:
self.flags = DEFAULT_FLAGS['SignatureFlags']
elif not any(arch in self.flags for arch in ['32', '64']):
self.flags += ' 32 64'
def _complete_binary_args(self):
""" Complete self.binary dictionary with the binary representations
of the self fields. """
self.binary['id'] = self.binary["id"] = get_sig_id(self.sig_id, excfg.get("SignatureType", "version-intro"))
self.binary['flags'] = get_binary_flags(self.flags, Signature)
if '.' in self.minimum:
values = list()
for item in self.minimum.split('.'):
if item == '*':
values.append(0)
else:
values.append(unsigned(int(item)))
self.binary["minimum"] = {"major" : values[0], "minor" : values[1], "revision":
values[2]}
if '.' in self.maximum:
values = list()
for item in self.maximum.split('.'):
if item == '*':
values.append(0xffff)
else:
values.append(unsigned(int(item)))
self.binary["maximum"] = {"major" : values[0], "minor" : values[1], "revision":
values[2]}
def __init__(self, sig_id, minimum, maximum, flags=None, **kwargs):
self.sig_id = sig_id
self.minimum = minimum
self.maximum = maximum
self.flags = flags
self.binary = {}
self._validate_args()
self._complete_binary_args()
def _cmp(self, other):
""" Signatures must have an unique ID. So we can safely compare them
based on ID only. """
return cmp_unsigned(self.binary['id'], other.binary['id'])
def __str__(self):
return "'%s' (%03d), '%s' (%08x), '%s' (%d.%d.%d), '%s' (%d.%d.%d)" % (self.sig_id, self.binary['id'],
self.flags, self.binary['flags'], self.minimum, self.binary['minimum']["major"], self.binary["minimum"]["minor"], self.binary["minimum"]["revision"],
self.maximum, self.binary['maximum']["major"], self.binary["maximum"]['minor'], self.binary["maximum"]["revision"])
def get_binary_header(self):
""" Returns a binary string representing the header of the signature
The format it's as follows:
- type[8] = 12
- size[16] = 10/12"""
struct_size = 24
return struct.pack('<BH', 12, struct_size)
def get_binary(self):
""" Returns a binary string containing the binary representation of the
signature.
The format it's as follows:
- id[32]
- flags[32]
- min[32]
- max[32]
"""
return struct.pack('<IIHHHHHHHH',
unsigned(self.binary['id']),
unsigned(self.binary['flags']),
unsigned(self.binary['minimum']['major']),
unsigned(self.binary['minimum']['minor']),
unsigned(self.binary['minimum']['revision']),
0x0,
unsigned(self.binary['maximum']['major']),
unsigned(self.binary['maximum']['minor']),
unsigned(self.binary['maximum']['revision']),
0xffff)
class ProcessCreationSignature(Signature):
""" Represents a process-creaation signature. For more details about it's
implementation see `get_binary`. """
def _validate_args(self):
""" Validates that the values are good. If they are missing, they will
be initialized with the default values. """
if not self.sig_id:
raise ValueError('id is required!')
if self.create_mask is None:
raise ValueError('create-mask is required!')
if not self.flags:
self.flags = DEFAULT_FLAGS['SignatureFlags']
elif not any(arch in self.flags for arch in ['32', '64']):
self.flags += ' 32 64'
def _complete_binary_args(self):
""" Complete self.binary dictionary with the binary representations
of the self fields. """
self.binary['id'] = get_sig_id(self.sig_id, excfg.get("SignatureType", "process-creation"))
self.binary['flags'] = get_binary_flags(self.flags, Signature)
self.binary['create-mask'] = 0
for flag in self.create_mask:
print(excfg.get("ProcessCreationFlags", flag))
self.binary['create-mask'] = self.binary['create-mask'] | int(excfg.get("ProcessCreationFlags", flag), 16)
def __init__(self, sig_id, create_mask, flags=None, **kwargs):
self.sig_id = sig_id
self.create_mask = create_mask
self.flags = flags
self.binary = {}
self._validate_args()
self._complete_binary_args()
def _cmp(self, other):
""" Signatures must have an unique ID. So we can safely compare them
based on ID only. """
return cmp_unsigned(self.binary['id'], other.binary['id'])
def __str__(self):
return "'%s' (%04d), '%s' (%08x), '%s' (0x%08x) " % (self.sig_id, self.binary['id'],
self.flags, self.binary['flags'], self.create_mask, self.binary["create-mask"])
def get_binary_header(self):
""" Returns a binary string representing the header of the signature
The format it's as follows:
- type[8] = 12
- size[16] = 10/12"""
struct_size = 24
return struct.pack('<BH', 13, struct_size)
def get_binary(self):
""" Returns a binary string containing the binary representation of the
signature.
The format it's as follows:
- id[32]
- flags[32]
- create-mask[32]
"""
return struct.pack('<IIIIII',
unsigned(self.binary['id']),
unsigned(self.binary['flags']),
unsigned(self.binary["create-mask"]),
0,
0,
0)
| 33.551799
| 181
| 0.56488
| 9,079
| 77,404
| 4.708999
| 0.055623
| 0.068533
| 0.035787
| 0.014245
| 0.807359
| 0.781629
| 0.761444
| 0.743082
| 0.726288
| 0.700419
| 0
| 0.014441
| 0.317425
| 77,404
| 2,306
| 182
| 33.566349
| 0.794753
| 0.200778
| 0
| 0.671365
| 0
| 0.005935
| 0.131812
| 0.001623
| 0
| 0
| 0.001234
| 0
| 0
| 1
| 0.088279
| false
| 0.002226
| 0.008902
| 0.010386
| 0.192137
| 0.003709
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 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
| 6
|
2545505f7c90154483d1da4b42ffe51b4f247ee4
| 16,783
|
py
|
Python
|
psono/restapi/tests/mfa_yubikey_otp.py
|
dirigeant/psono-server
|
a18c5b3c4d8bbbe4ecf1615b210d99fb77752205
|
[
"Apache-2.0",
"CC0-1.0"
] | 48
|
2018-04-19T15:50:58.000Z
|
2022-01-23T15:58:11.000Z
|
psono/restapi/tests/mfa_yubikey_otp.py
|
dirigeant/psono-server
|
a18c5b3c4d8bbbe4ecf1615b210d99fb77752205
|
[
"Apache-2.0",
"CC0-1.0"
] | 9
|
2018-09-13T14:56:18.000Z
|
2020-01-17T16:44:33.000Z
|
psono/restapi/tests/mfa_yubikey_otp.py
|
dirigeant/psono-server
|
a18c5b3c4d8bbbe4ecf1615b210d99fb77752205
|
[
"Apache-2.0",
"CC0-1.0"
] | 11
|
2019-09-20T11:53:47.000Z
|
2021-07-18T22:41:31.000Z
|
from django.urls import reverse
from django.conf import settings
from django.contrib.auth.hashers import make_password
from django.utils import timezone
from datetime import timedelta
from rest_framework import status
from restapi import models
from ..utils import encrypt_with_db_secret
from .base import APITestCaseExtended
from mock import patch
import binascii
import random
import string
import os
import hashlib
import json
import nacl.encoding
import nacl.utils
import nacl.secret
def yubico_verify_true(yubikey_otp):
"""
utils.yubikey_authenticate function that will always return True
:param yubikey_otp: Yubikey OTP
:type yubikey_otp: str
:return: True
:rtype: Boolean
"""
# Take exactly 1 argument which we will happily ignore afterwards
assert yubikey_otp
return True
def yubico_verify_false(yubikey_otp):
"""
utils.yubikey_authenticate function that will always return False
:param yubikey_otp: Yubikey OTP
:type yubikey_otp: str
:return: True
:rtype: Boolean
"""
# Take exactly 1 argument which we will happily ignore afterwards
assert yubikey_otp
return False
class YubikeyOTPVerifyTests(APITestCaseExtended):
def setUp(self):
self.test_email = ''.join(random.choice(string.ascii_lowercase) for _ in range(10)) + 'test@example.com'
self.test_email_bcrypt = 'a'
self.test_username = ''.join(random.choice(string.ascii_lowercase) for _ in range(10)) + 'test@psono.pw'
self.test_authkey = binascii.hexlify(os.urandom(settings.AUTH_KEY_LENGTH_BYTES)).decode()
self.test_public_key = binascii.hexlify(os.urandom(settings.USER_PUBLIC_KEY_LENGTH_BYTES)).decode()
self.test_private_key = binascii.hexlify(os.urandom(settings.USER_PRIVATE_KEY_LENGTH_BYTES)).decode()
self.test_private_key_nonce = binascii.hexlify(os.urandom(settings.NONCE_LENGTH_BYTES)).decode()
self.test_secret_key = binascii.hexlify(os.urandom(settings.USER_SECRET_KEY_LENGTH_BYTES)).decode()
self.test_secret_key_nonce = binascii.hexlify(os.urandom(settings.NONCE_LENGTH_BYTES)).decode()
self.test_user_sauce = 'd22f5797cfd438f212bb0830da488f0555487697ad4041bbcbf5b08bc297e117'
self.test_user_obj = models.User.objects.create(
email=self.test_email,
email_bcrypt=self.test_email_bcrypt,
username=self.test_username,
authkey=make_password(self.test_authkey),
public_key=self.test_public_key,
private_key=self.test_private_key,
private_key_nonce=self.test_private_key_nonce,
secret_key=self.test_secret_key,
secret_key_nonce=self.test_secret_key_nonce,
user_sauce=self.test_user_sauce,
is_email_active=True
)
self.token = ''.join(random.choice(string.ascii_lowercase) for _ in range(64))
db_token = models.Token.objects.create(
key= hashlib.sha512(self.token.encode()).hexdigest(),
user=self.test_user_obj,
secret_key = binascii.hexlify(os.urandom(32)).decode(),
valid_till=timezone.now() + timedelta(seconds=10),
)
self.yubikey_token = 'fdnjhhfdkljhfdjhfdkljhfdjklhfdkjlhfdg'
self.yubikey_id = self.yubikey_token[:12]
self.yubikey = models.Yubikey_OTP.objects.create(
user=self.test_user_obj,
title= 'Dummy Title',
yubikey_id = encrypt_with_db_secret(str(self.yubikey_id))
)
# encrypt authorization validator with session key
secret_box = nacl.secret.SecretBox(db_token.secret_key, encoder=nacl.encoding.HexEncoder)
authorization_validator_nonce = nacl.utils.random(nacl.secret.SecretBox.NONCE_SIZE)
authorization_validator_nonce_hex = nacl.encoding.HexEncoder.encode(authorization_validator_nonce)
encrypted = secret_box.encrypt(json.dumps({}).encode("utf-8"), authorization_validator_nonce)
authorization_validator = encrypted[len(authorization_validator_nonce):]
authorization_validator_hex = nacl.encoding.HexEncoder.encode(authorization_validator)
self.authorization_validator = json.dumps({
'text': authorization_validator_hex.decode(),
'nonce': authorization_validator_nonce_hex.decode(),
})
def test_get_authentication_yubikey_otp_verify(self):
"""
Tests GET method on authentication_yubikey_otp_verify
"""
url = reverse('authentication_yubikey_otp_verify')
data = {}
self.client.force_authenticate(user=self.test_user_obj)
response = self.client.get(url, data)
self.assertEqual(response.status_code, status.HTTP_405_METHOD_NOT_ALLOWED)
def test_put_authentication_yubikey_otp_verify(self):
"""
Tests PUT method on authentication_yubikey_otp_verify
"""
url = reverse('authentication_yubikey_otp_verify')
data = {}
self.client.force_authenticate(user=self.test_user_obj)
response = self.client.put(url, data)
self.assertEqual(response.status_code, status.HTTP_405_METHOD_NOT_ALLOWED)
def test_delete_authentication_yubikey_otp_verify(self):
"""
Tests DELETE method on authentication_yubikey_otp_verify
"""
url = reverse('authentication_yubikey_otp_verify')
data = {}
self.client.force_authenticate(user=self.test_user_obj)
response = self.client.delete(url, data)
self.assertEqual(response.status_code, status.HTTP_405_METHOD_NOT_ALLOWED)
@patch('restapi.utils.yubikey.settings', YUBIKEY_CLIENT_ID='123', YUBIKEY_SECRET_KEY='T3VoIHlvdSBmb3VuZCBtZT8=')
@patch('restapi.utils.yubikey.Yubico.verify', side_effect=yubico_verify_true)
def test_post_authentication_yubikey_otp_verify_correct(self, settings_fct, yubico_verify_true_fct):
"""
Tests POST method on authentication_yubikey_otp_verify
"""
url = reverse('authentication_yubikey_otp_verify')
data = {
'token': self.token,
'yubikey_otp': self.yubikey_token,
}
self.client.credentials(HTTP_AUTHORIZATION='Token ' + self.token, HTTP_AUTHORIZATION_VALIDATOR=self.authorization_validator)
response = self.client.post(url, data)
self.assertEqual(response.status_code, status.HTTP_200_OK)
@patch('restapi.utils.yubikey.settings', YUBIKEY_CLIENT_ID=None, YUBIKEY_SECRET_KEY=None)
def test_post_authentication_yubikey_otp_verify_no_yubikey_support(self, settings_fct):
"""
Tests POST method on authentication_yubikey_otp_verify
"""
url = reverse('authentication_yubikey_otp_verify')
data = {
'token': self.token,
'yubikey_otp': self.yubikey_token,
}
self.client.credentials(HTTP_AUTHORIZATION='Token ' + self.token, HTTP_AUTHORIZATION_VALIDATOR=self.authorization_validator)
response = self.client.post(url, data)
self.assertEqual(response.status_code, status.HTTP_400_BAD_REQUEST)
self.assertEqual(response.data.get('non_field_errors'), [u'Server does not support YubiKeys.'])
@patch('restapi.utils.yubikey.settings', YUBIKEY_CLIENT_ID='123', YUBIKEY_SECRET_KEY='T3VoIHlvdSBmb3VuZCBtZT8=')
@patch('restapi.utils.yubikey.Yubico.verify', side_effect=yubico_verify_false)
def test_post_authentication_yubikey_otp_verify_yubikey_incorrect(self, settings_fct, yubico_verify_false_fct):
"""
Tests POST method on authentication_yubikey_otp_verify while the yubikey is incorrect
"""
url = reverse('authentication_yubikey_otp_verify')
data = {
'token': self.token,
'yubikey_otp': self.yubikey_token,
}
self.client.credentials(HTTP_AUTHORIZATION='Token ' + self.token, HTTP_AUTHORIZATION_VALIDATOR=self.authorization_validator)
response = self.client.post(url, data)
self.assertEqual(response.status_code, status.HTTP_400_BAD_REQUEST)
self.assertEqual(response.data.get('non_field_errors'), [u'YubiKey OTP incorrect.'])
@patch('restapi.utils.yubikey.settings', YUBIKEY_CLIENT_ID='123', YUBIKEY_SECRET_KEY='T3VoIHlvdSBmb3VuZCBtZT8=')
@patch('restapi.utils.yubikey.Yubico.verify', side_effect=yubico_verify_true)
def test_post_authentication_yubikey_otp_verify_not_attached_to_this_account(self, settings_fct, yubico_verify_true_fct):
"""
Tests POST method on authentication_yubikey_otp_verify while the yubikey_otp token is note whitelisted for the
user that owns this token
"""
url = reverse('authentication_yubikey_otp_verify')
data = {
'token': self.token,
'yubikey_otp': '12345678',
}
self.client.credentials(HTTP_AUTHORIZATION='Token ' + self.token, HTTP_AUTHORIZATION_VALIDATOR=self.authorization_validator)
response = self.client.post(url, data)
self.assertEqual(response.status_code, status.HTTP_400_BAD_REQUEST)
self.assertEqual(response.data.get('non_field_errors'), [u'YubiKey OTP not attached to this account.'])
class YubikeyOTPTests(APITestCaseExtended):
def setUp(self):
self.test_email = ''.join(random.choice(string.ascii_lowercase) for _ in range(10)) + 'test@example.com'
self.test_email_bcrypt = 'a'
self.test_username = ''.join(random.choice(string.ascii_lowercase) for _ in range(10)) + 'test@psono.pw'
self.test_authkey = binascii.hexlify(os.urandom(settings.AUTH_KEY_LENGTH_BYTES)).decode()
self.test_public_key = binascii.hexlify(os.urandom(settings.USER_PUBLIC_KEY_LENGTH_BYTES)).decode()
self.test_private_key = binascii.hexlify(os.urandom(settings.USER_PRIVATE_KEY_LENGTH_BYTES)).decode()
self.test_private_key_nonce = binascii.hexlify(os.urandom(settings.NONCE_LENGTH_BYTES)).decode()
self.test_secret_key = binascii.hexlify(os.urandom(settings.USER_SECRET_KEY_LENGTH_BYTES)).decode()
self.test_secret_key_nonce = binascii.hexlify(os.urandom(settings.NONCE_LENGTH_BYTES)).decode()
self.test_user_sauce = '32a34bd9d7ae7fde45906bce0e7b04c3f81e4b6c05d888468e717e173ee6655a'
self.test_user_obj = models.User.objects.create(
email=self.test_email,
email_bcrypt=self.test_email_bcrypt,
username=self.test_username,
authkey=make_password(self.test_authkey),
public_key=self.test_public_key,
private_key=self.test_private_key,
private_key_nonce=self.test_private_key_nonce,
secret_key=self.test_secret_key,
secret_key_nonce=self.test_secret_key_nonce,
user_sauce=self.test_user_sauce,
is_email_active=True
)
def test_get_user_yubikey_otp(self):
"""
Tests GET method on yubikey_otp
"""
yubikey = models.Yubikey_OTP.objects.create(
user=self.test_user_obj,
title= 'My Sweet Title',
yubikey_id = '1234'
)
url = reverse('user_yubikey_otp')
data = {}
self.client.force_authenticate(user=self.test_user_obj)
response = self.client.get(url, data)
self.assertEqual(response.data, {
"yubikey_otps":[{
"id":yubikey.id,
"active":yubikey.active,
"title":"My Sweet Title"
}]
})
self.assertEqual(response.status_code, status.HTTP_200_OK)
def test_put_user_yubikey_otp_with_no_valid_yubikey(self):
"""
Tests PUT method on user_yubikey_otp with no valid yubikey
"""
url = reverse('user_yubikey_otp')
data = {
'title': 'asdu5zz53',
'yubikey_otp': '123456789',
}
self.client.force_authenticate(user=self.test_user_obj)
response = self.client.put(url, data)
self.assertEqual(response.status_code, status.HTTP_400_BAD_REQUEST)
self.assertNotEqual(response.data.get('yubikey_otp', False), False)
def test_put_user_yubikey_otp_no_yubikey_otp(self):
"""
Tests PUT method on user_yubikey_otp with no yubikey_otp
"""
url = reverse('user_yubikey_otp')
data = {
'title': 'asdu5zz53',
}
self.client.force_authenticate(user=self.test_user_obj)
response = self.client.put(url, data)
self.assertEqual(response.status_code, status.HTTP_400_BAD_REQUEST)
def test_put_user_yubikey_otp_no_title(self):
"""
Tests PUT method on user_yubikey_otp with no title
"""
url = reverse('user_yubikey_otp')
data = {
'yubikey_otp': '123456789',
}
self.client.force_authenticate(user=self.test_user_obj)
response = self.client.put(url, data)
self.assertEqual(response.status_code, status.HTTP_400_BAD_REQUEST)
def test_post_user_yubikey_otp_no_parameters(self):
"""
Tests POST method on user_yubikey_otp
"""
url = reverse('user_yubikey_otp')
data = {}
self.client.force_authenticate(user=self.test_user_obj)
response = self.client.post(url, data)
self.assertEqual(response.status_code, status.HTTP_400_BAD_REQUEST)
@patch('restapi.utils.yubikey.settings', YUBIKEY_CLIENT_ID='123', YUBIKEY_SECRET_KEY='T3VoIHlvdSBmb3VuZCBtZT8=')
@patch('restapi.utils.yubikey.Yubico.verify', side_effect=yubico_verify_true)
def test_activate_yubikey_otp_success(self, settings_fct, yubico_verify_true_fct):
"""
Tests POST method on user_yubikey_otp to activate a duo
"""
yubikey_token = 'fdnjhhfdkljhfdjhfdkljhfdjklhfdkjlhfdg'
yubikey_id = yubikey_token[:12]
yubikey = models.Yubikey_OTP.objects.create(
user=self.test_user_obj,
title= 'Dummy Title',
yubikey_id = encrypt_with_db_secret(str(yubikey_id))
)
url = reverse('user_yubikey_otp')
data = {
'yubikey_id': yubikey.id,
'yubikey_otp': yubikey_token,
}
self.client.force_authenticate(user=self.test_user_obj)
response = self.client.post(url, data)
self.assertEqual(response.status_code, status.HTTP_200_OK)
db_yubikey = models.Yubikey_OTP.objects.get(pk=yubikey.id)
self.assertTrue(db_yubikey.active)
def test_delete_user_yubikey_otp(self):
"""
Tests DELETE method on user_yubikey_otp
"""
yubikey = models.Yubikey_OTP.objects.create(
user=self.test_user_obj,
title= 'My Sweet Title',
yubikey_id = '1234'
)
url = reverse('user_yubikey_otp')
data = {
'yubikey_otp_id': yubikey.id
}
self.client.force_authenticate(user=self.test_user_obj)
response = self.client.delete(url, data)
self.assertEqual(response.status_code, status.HTTP_200_OK)
self.client.force_authenticate(user=self.test_user_obj)
response = self.client.get(url, data)
self.assertEqual(response.data, {
"yubikey_otps":[]
})
self.assertEqual(response.status_code, status.HTTP_200_OK)
def test_delete_user_yubikey_otp_no_yubikey_otp_id (self):
"""
Tests DELETE method on user_yubikey_otp with no google_authenticator_id
"""
url = reverse('user_yubikey_otp')
data = {
}
self.client.force_authenticate(user=self.test_user_obj)
response = self.client.delete(url, data)
self.assertEqual(response.status_code, status.HTTP_400_BAD_REQUEST)
def test_delete_user_yubikey_otp_yubikey_otp_id_no_uuid(self):
"""
Tests DELETE method on user_yubikey_otp with yubikey_otp_id not being a uuid
"""
url = reverse('user_yubikey_otp')
data = {
'yubikey_otp_id': '12345'
}
self.client.force_authenticate(user=self.test_user_obj)
response = self.client.delete(url, data)
self.assertEqual(response.status_code, status.HTTP_400_BAD_REQUEST)
def test_delete_user_yubikey_otp_yubikey_otp_id_not_exist(self):
"""
Tests DELETE method on user_yubikey_otp with yubikey_otp_id not existing
"""
url = reverse('user_yubikey_otp')
data = {
'yubikey_otp_id': '7e866c32-3e4d-4421-8a7d-3ac62f980fd3'
}
self.client.force_authenticate(user=self.test_user_obj)
response = self.client.delete(url, data)
self.assertEqual(response.status_code, status.HTTP_400_BAD_REQUEST)
| 35.557203
| 132
| 0.686886
| 2,009
| 16,783
| 5.42011
| 0.106023
| 0.079897
| 0.036
| 0.028928
| 0.826522
| 0.799522
| 0.779135
| 0.746717
| 0.727799
| 0.71136
| 0
| 0.019025
| 0.220163
| 16,783
| 471
| 133
| 35.632696
| 0.812958
| 0.091342
| 0
| 0.621818
| 0
| 0
| 0.108008
| 0.057825
| 0
| 0
| 0
| 0
| 0.098182
| 1
| 0.076364
| false
| 0.010909
| 0.069091
| 0
| 0.16
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 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
| 6
|
6c0c384abf8d7e530cd981b75453eb2f097df849
| 31
|
py
|
Python
|
simple_learning/optim/__init__.py
|
JA-Bar/simple-learning
|
c59ce4231a4ca6d4c0359eeff85ca43c85e0348f
|
[
"MIT"
] | null | null | null |
simple_learning/optim/__init__.py
|
JA-Bar/simple-learning
|
c59ce4231a4ca6d4c0359eeff85ca43c85e0348f
|
[
"MIT"
] | null | null | null |
simple_learning/optim/__init__.py
|
JA-Bar/simple-learning
|
c59ce4231a4ca6d4c0359eeff85ca43c85e0348f
|
[
"MIT"
] | null | null | null |
from .all_optimizers import *
| 10.333333
| 29
| 0.774194
| 4
| 31
| 5.75
| 1
| 0
| 0
| 0
| 0
| 0
| 0
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| 0
| 0
| 0
| 0
| 0.16129
| 31
| 2
| 30
| 15.5
| 0.884615
| 0
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| true
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| 0
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| 0
| 0
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| 1
| 0
| 1
| 0
|
0
| 6
|
6c4fa5ac60c0d3e4f76a97b31f6dfcc596de89b4
| 42,360
|
py
|
Python
|
tests/test_api_import.py
|
Pauliceia/ws
|
8966cfd80299f22468afe9a2a1156740bf237270
|
[
"MIT"
] | null | null | null |
tests/test_api_import.py
|
Pauliceia/ws
|
8966cfd80299f22468afe9a2a1156740bf237270
|
[
"MIT"
] | 2
|
2021-02-08T20:26:34.000Z
|
2021-04-30T20:43:28.000Z
|
tests/test_api_import.py
|
Pauliceia/ws
|
8966cfd80299f22468afe9a2a1156740bf237270
|
[
"MIT"
] | 1
|
2018-10-29T14:55:06.000Z
|
2018-10-29T14:55:06.000Z
|
#!/usr/bin/env python
# -*- coding: utf-8 -*-
from os import path as os_path
from random import randint
from unittest import TestCase
from util.tester import UtilTester
from util.common import FILES_PATH
os_path_sep_join = os_path.sep.join
class TestAPIImport(TestCase):
def setUp(self):
# create a tester passing the unittest self
self.tester = UtilTester(self)
# DO LOGIN
self.tester.auth_login("miguel@admin.com", "miguel")
self.f_table_name = "points_" + str(randint(0, 100))
##################################################
# create a new layer
##################################################
layer = {
'type': 'Layer',
'properties': {'layer_id': -1, 'f_table_name': self.f_table_name, 'name': 'Points',
'description': '', 'source_description': '',
'reference': [1050], 'keyword': [1041]}
}
layer = self.tester.api_layer_create(layer)
self.layer_id = layer["properties"]["layer_id"]
##################################################
# create a new changeset
##################################################
changeset = {
'properties': {'changeset_id': -1, 'layer_id': self.layer_id},
'type': 'Changeset'
}
self.changeset_id = self.tester.api_changeset_create(changeset)
def tearDown(self):
##################################################
# remove the layer
##################################################
# CLOSE THE CHANGESET
close_changeset = {
'properties': {'changeset_id': self.changeset_id, 'description': 'Import points.shp'},
'type': 'ChangesetClose'
}
self.tester.api_changeset_close(close_changeset)
# DELETE THE CHANGESET (the changeset is automatically removed when delete a layer)
# self.tester.api_changeset_delete(changeset_id=changeset_id)
# REMOVE THE layer AFTER THE TESTS
self.tester.api_layer_delete(self.layer_id)
# it is not possible to find the layer that just deleted
expected = {'type': 'FeatureCollection', 'features': []}
self.tester.api_layer(expected, layer_id=self.layer_id)
# DO LOGOUT AFTER THE TESTS
self.tester.auth_logout()
# import - create
def test_post_import_shp_places_5_points_4326(self):
##################################################
# import the shapefile with the created layer (the feature table will be the shapefile)
##################################################
file_name = "places_5_points_4326.zip"
with open(os_path_sep_join([FILES_PATH, file_name]), mode='rb') as file: # rb = read binary
binary_file_content = file.read()
self.tester.api_import_shp_create(binary_file_content, f_table_name=self.f_table_name,
file_name=file_name, changeset_id=self.changeset_id)
# dados_prefeitura_sp
def test_post_import_shp_DEINFO_CENTRAIS_MECANIZADAS_5533(self):
##################################################
# import the shapefile with the created layer (the feature table will be the shapefile)
##################################################
file_name = "DEINFO_CENTRAIS_MECANIZADAS_5533.zip"
file_name_path = "shp_originals/dados_prefeitura_sp/ok/" + file_name
with open(os_path_sep_join([FILES_PATH, file_name_path]), mode='rb') as file: # rb = read binary
binary_file_content = file.read()
self.tester.api_import_shp_create(binary_file_content, f_table_name=self.f_table_name,
file_name=file_name, changeset_id=self.changeset_id)
def test_post_import_shp_LAYER_BACIA_HIDROGRAFIA_29193(self):
##################################################
# import the shapefile with the created layer (the feature table will be the shapefile)
##################################################
file_name = "LAYER_BACIA_HIDROGRAFIA_29193.zip"
file_name_path = "shp_originals/dados_prefeitura_sp/ok/" + file_name
with open(os_path_sep_join([FILES_PATH, file_name_path]), mode='rb') as file: # rb = read binary
binary_file_content = file.read()
self.tester.api_import_shp_create(binary_file_content, f_table_name=self.f_table_name,
file_name=file_name, changeset_id=self.changeset_id)
def test_post_import_shp_LAYER_CEMITERIOS_29193(self):
##################################################
# import the shapefile with the created layer (the feature table will be the shapefile)
##################################################
file_name = "LAYER_CEMITERIOS_29193.zip"
file_name_path = "shp_originals/dados_prefeitura_sp/ok/" + file_name
with open(os_path_sep_join([FILES_PATH, file_name_path]), mode='rb') as file: # rb = read binary
binary_file_content = file.read()
self.tester.api_import_shp_create(binary_file_content, f_table_name=self.f_table_name,
file_name=file_name, changeset_id=self.changeset_id)
def test_post_import_shp_LAYER_CENTRAL_COOPERATIVA_4326(self):
##################################################
# import the shapefile with the created layer (the feature table will be the shapefile)
##################################################
file_name = "LAYER_CENTRAL_COOPERATIVA_4326.zip"
file_name_path = "shp_originals/dados_prefeitura_sp/ok/" + file_name
with open(os_path_sep_join([FILES_PATH, file_name_path]), mode='rb') as file: # rb = read binary
binary_file_content = file.read()
self.tester.api_import_shp_create(binary_file_content, f_table_name=self.f_table_name,
file_name=file_name, changeset_id=self.changeset_id)
def test_post_import_shp_LAYER_DISTRITO_SP_29193(self):
##################################################
# import the shapefile with the created layer (the feature table will be the shapefile)
##################################################
file_name = "LAYER_DISTRITO_SP_29193.zip"
file_name_path = "shp_originals/dados_prefeitura_sp/ok/" + file_name
with open(os_path_sep_join([FILES_PATH, file_name_path]), mode='rb') as file: # rb = read binary
binary_file_content = file.read()
self.tester.api_import_shp_create(binary_file_content, f_table_name=self.f_table_name,
file_name=file_name, changeset_id=self.changeset_id)
def test_post_import_shp_shopping_2014_29193(self):
##################################################
# import the shapefile with the created layer (the feature table will be the shapefile)
##################################################
file_name = "shopping_2014_29193.zip"
file_name_path = "shp_originals/dados_prefeitura_sp/" + file_name
with open(os_path_sep_join([FILES_PATH, file_name_path]), mode='rb') as file: # rb = read binary
binary_file_content = file.read()
self.tester.api_import_shp_create(binary_file_content, f_table_name=self.f_table_name,
file_name=file_name, changeset_id=self.changeset_id)
# Ferla's Shapefile files
def test_post_import_shp_Area_alagada_4326(self):
##################################################
# import the shapefile with the created layer (the feature table will be the shapefile)
##################################################
file_name = "Area alagada_4326.zip"
file_name_path = "shp_originals/ferla/" + file_name
with open(os_path_sep_join([FILES_PATH, file_name_path]), mode='rb') as file: # rb = read binary
binary_file_content = file.read()
self.tester.api_import_shp_create(binary_file_content, f_table_name=self.f_table_name,
file_name=file_name, changeset_id=self.changeset_id)
def test_post_import_shp_SF_4326(self):
file_name = "SF.zip"
file_name_path = "shp_originals/ferla/with_myshapes_folder/" + file_name
with open(os_path_sep_join([FILES_PATH, file_name_path]), mode='rb') as file: # rb = read binary
binary_file_content = file.read()
self.tester.api_import_shp_create(binary_file_content, f_table_name=self.f_table_name,
file_name=file_name, changeset_id=self.changeset_id)
def test_post_import_shp_2019_09_26_cn_original(self):
file_name = "2019_09_26_cn_original.zip"
file_name_path = "shp_originals/ferla/" + file_name
with open(os_path_sep_join([FILES_PATH, file_name_path]), mode='rb') as file: # rb = read binary
binary_file_content = file.read()
self.tester.api_import_shp_create(binary_file_content, f_table_name=self.f_table_name,
file_name=file_name, changeset_id=self.changeset_id)
def test_post_import_shp_Sarah_Feldman_adaptada_atributos_com_acentos_4326(self):
##################################################
# import the shapefile with the created layer (the feature table will be the shapefile)
##################################################
file_name = "Sarah_Feldman_adaptada_atributos_com_acentos_4326.zip"
file_name_path = "shp_originals/ferla/" + file_name
with open(os_path_sep_join([FILES_PATH, file_name_path]), mode='rb') as file: # rb = read binary
binary_file_content = file.read()
self.tester.api_import_shp_create(binary_file_content, f_table_name=self.f_table_name,
file_name=file_name, changeset_id=self.changeset_id)
# def test_post_import_shp_Sarah_Feldman_adaptada_4326_sem_acento_coluna(self):
# ##################################################
# # import the shapefile with the created layer (the feature table will be the shapefile)
# ##################################################
# file_name = "Sarah_Feldman_adaptada_4326_sem_acento_coluna.zip"
# file_name_path = "shp_originals/ferla/" + file_name
# with open(os_path_sep_join([FILES_PATH, file_name_path]), mode='rb') as file: # rb = read binary
# binary_file_content = file.read()
#
# self.tester.api_import_shp_create(binary_file_content, f_table_name=self.f_table_name,
# file_name=file_name, changeset_id=self.changeset_id)
# Cintia's Shapefile files
def test_post_import_shp_homosp_4326(self):
##################################################
# import the shapefile with the created layer (the feature table will be the shapefile)
##################################################
file_name = "homosp.zip"
file_name_path = "shp_originals/cintia/" + file_name
with open(os_path_sep_join([FILES_PATH, file_name_path]), mode='rb') as file: # rb = read binary
binary_file_content = file.read()
self.tester.api_import_shp_create(binary_file_content, f_table_name=self.f_table_name,
file_name=file_name, changeset_id=self.changeset_id)
def test_post_import_shp_industrias_do_bom_retiro_4326(self):
##################################################
# import the shapefile with the created layer (the feature table will be the shapefile)
##################################################
file_name = "industrias_do_bom_retiro.zip"
file_name_path = "shp_originals/cintia/" + file_name
with open(os_path_sep_join([FILES_PATH, file_name_path]), mode='rb') as file: # rb = read binary
binary_file_content = file.read()
self.tester.api_import_shp_create(binary_file_content, f_table_name=self.f_table_name,
file_name=file_name, changeset_id=self.changeset_id)
def test_post_import_shp_Recenseamento_Demographico_do_Estado_de_Sao_Paulo_4326(self):
##################################################
# import the shapefile with the created layer (the feature table will be the shapefile)
##################################################
file_name = "Recenseamento Demographico do Estado de Sao Paulo.zip"
file_name_path = "shp_originals/cintia/" + file_name
with open(os_path_sep_join([FILES_PATH, file_name_path]), mode='rb') as file: # rb = read binary
binary_file_content = file.read()
self.tester.api_import_shp_create(binary_file_content, f_table_name=self.f_table_name,
file_name=file_name, changeset_id=self.changeset_id)
def test_post_import_shp_Teste_boletins_4326(self):
##################################################
# import the shapefile with the created layer (the feature table will be the shapefile)
##################################################
file_name = "Teste boletins.zip"
file_name_path = "shp_originals/cintia/" + file_name
with open(os_path_sep_join([FILES_PATH, file_name_path]), mode='rb') as file: # rb = read binary
binary_file_content = file.read()
self.tester.api_import_shp_create(binary_file_content, f_table_name=self.f_table_name,
file_name=file_name, changeset_id=self.changeset_id)
# Cintia's test Shapefile files
def test_post_import_shp_camadas_de_teste_teste_em_3857(self):
##################################################
# import the shapefile with the created layer (the feature table will be the shapefile)
##################################################
file_name = "teste em 3857.zip"
file_name_path = "shp_originals/cintia/camadas_de_teste/" + file_name
with open(os_path_sep_join([FILES_PATH, file_name_path]), mode='rb') as file: # rb = read binary
binary_file_content = file.read()
self.tester.api_import_shp_create(binary_file_content, f_table_name=self.f_table_name,
file_name=file_name, changeset_id=self.changeset_id)
def test_post_import_shp_camadas_de_teste_teste_em_4326(self):
##################################################
# import the shapefile with the created layer (the feature table will be the shapefile)
##################################################
file_name = "teste em 4326.zip"
file_name_path = "shp_originals/cintia/camadas_de_teste/" + file_name
with open(os_path_sep_join([FILES_PATH, file_name_path]), mode='rb') as file: # rb = read binary
binary_file_content = file.read()
self.tester.api_import_shp_create(binary_file_content, f_table_name=self.f_table_name,
file_name=file_name, changeset_id=self.changeset_id)
def test_post_import_shp_camadas_de_teste_teste_reprojetado_de_3857_para_4326(self):
##################################################
# import the shapefile with the created layer (the feature table will be the shapefile)
##################################################
file_name = "teste_reprojetado_de_3857_para_4326.zip"
file_name_path = "shp_originals/cintia/camadas_de_teste/" + file_name
with open(os_path_sep_join([FILES_PATH, file_name_path]), mode='rb') as file: # rb = read binary
binary_file_content = file.read()
self.tester.api_import_shp_create(binary_file_content, f_table_name=self.f_table_name,
file_name=file_name, changeset_id=self.changeset_id)
# def test_post_import_shp_Area_alagada_problema(self):
# ##################################################
# # import the shapefile with the created layer (the feature table will be the shapefile)
# ##################################################
# file_name = "Area alagada_problema.zip"
# file_name_path = "shp_originals/ferla/" + file_name
# with open(os_path_sep_join([FILES_PATH, file_name_path]), mode='rb') as file: # rb = read binary
# binary_file_content = file.read()
# self.tester.api_import_shp_create(binary_file_content, f_table_name=self.f_table_name,
# file_name=file_name, changeset_id=self.changeset_id)
"""
class TestAPIManualTests(TestCase):
def setUp(self):
# create a tester passing the unittest self
self.tester = UtilTester(self)
# DO LOGIN
self.tester.auth_login("miguel@admin.com", "miguel")
self.folder_name_shp_originals = "files/shp_originals/"
self.f_table_name = "points_" + str(randint(0, 100))
##################################################
# create a new layer
##################################################
layer = {
'type': 'Layer',
'properties': {'layer_id': -1, 'f_table_name': self.f_table_name, 'name': 'Points',
'description': '', 'source_description': '',
'reference': [1050], 'keyword': [1041]}
}
layer = self.tester.api_layer_create(layer)
self.layer_id = layer["properties"]["layer_id"]
##################################################
# create a new changeset
##################################################
changeset = {
'properties': {'changeset_id': -1, 'layer_id': self.layer_id},
'type': 'Changeset'
}
self.changeset_id = self.tester.api_changeset_create(changeset)
def tearDown(self):
##################################################
# remove the layer
##################################################
# CLOSE THE CHANGESET
close_changeset = {
'properties': {'changeset_id': self.changeset_id, 'description': 'Import points.shp'},
'type': 'ChangesetClose'
}
self.tester.api_changeset_close(close_changeset)
# DELETE THE CHANGESET (the changeset is automatically removed when delete a layer)
# self.tester.api_changeset_delete(changeset_id=changeset_id)
# REMOVE THE layer AFTER THE TESTS
self.tester.api_layer_delete(self.layer_id)
# it is not possible to find the layer that just deleted
expected = {'type': 'FeatureCollection', 'features': []}
self.tester.api_layer(expected, layer_id=self.layer_id)
# DO LOGOUT AFTER THE TESTS
self.tester.auth_logout()
# the tests under are manual tests
# def test_post_import_shp_ref_urbana_2013(self):
# ##################################################
# # import the shapefile with the created layer (the feature table will be the shapefile)
# ##################################################
# file_name = "ref_urbana_2013.zip"
# with open(self.folder_name_shp_originals + 'shp_pesado/' + file_name, mode='rb') as file: # rb = read binary
# binary_file_content = file.read()
#
# self.tester.api_import_shp_create(binary_file_content, f_table_name=self.f_table_name, file_name=file_name,
# changeset_id=self.changeset_id)
#
# def test_post_import_shp_sp_mun(self):
# ##################################################
# # import the shapefile with the created layer (the feature table will be the shapefile)
# ##################################################
# file_name = "sp_mun.zip"
# with open(self.folder_name_shp_originals + 'shp_pesado/' + file_name, mode='rb') as file: # rb = read binary
# binary_file_content = file.read()
#
# self.tester.api_import_shp_create(binary_file_content, f_table_name=self.f_table_name, file_name=file_name,
# changeset_id=self.changeset_id)
#
# def test_post_import_shp_sp_mun97_region(self):
# ##################################################
# # import the shapefile with the created layer (the feature table will be the shapefile)
# ##################################################
# file_name = "sp_mun97_region.zip"
# with open(self.folder_name_shp_originals + 'shp_pesado/' + file_name, mode='rb') as file: # rb = read binary
# binary_file_content = file.read()
#
# self.tester.api_import_shp_create(binary_file_content, f_table_name=self.f_table_name, file_name=file_name,
# changeset_id=self.changeset_id)
#
# def test_post_import_shp_ugrhi5_base_cont(self):
# ##################################################
# # import the shapefile with the created layer (the feature table will be the shapefile)
# ##################################################
# file_name = "ugrhi5_base_cont.zip"
# with open(self.folder_name_shp_originals + 'shp_pesado/' + file_name, mode='rb') as file: # rb = read binary
# binary_file_content = file.read()
#
# self.tester.api_import_shp_create(binary_file_content, f_table_name=self.f_table_name, file_name=file_name,
# changeset_id=self.changeset_id)
#
# def test_post_import_shp_teste_peso_file_with_98_mb(self):
# ##################################################
# # import the shapefile with the created layer (the feature table will be the shapefile)
# ##################################################
# file_name = "teste_peso.zip"
# with open(self.folder_name_shp_originals + 'shp_pesado/' + file_name, mode='rb') as file: # rb = read binary
# binary_file_content = file.read()
#
# self.tester.api_import_shp_create(binary_file_content, f_table_name=self.f_table_name, file_name=file_name,
# changeset_id=self.changeset_id)
# dá erro de importação na OGR relacionado a encoding, porém a OGR não retorna um status de erro para
# o console. Portanto, o VGIMWS não consegue saber que foi um erro.
# def test_post_import_shp_DEINFO_CORTICO_2015(self):
# ##################################################
# # import the shapefile with the created layer (the feature table will be the shapefile)
# ##################################################
# file_name = "DEINFO_CORTICO_2015.zip"
# file_name_path = "shp_originals/dados_prefeitura_sp/dentro_sp/" + file_name
# with open(os_path_sep_join([FILES_PATH, file_name_path]), mode='rb') as file: # rb = read binary
# binary_file_content = file.read()
#
# self.tester.api_import_shp_create(binary_file_content, f_table_name=self.f_table_name,
# file_name=file_name,
# changeset_id=self.changeset_id)
# a função ST_Contains diz que esse Shapefile está fora do Bounding Box de SP.
# def test_post_import_shp_DEINFO_DECLIVIDADE(self):
# ##################################################
# # import the shapefile with the created layer (the feature table will be the shapefile)
# ##################################################
# file_name = "DEINFO_DECLIVIDADE.zip"
# file_name_path = "shp_originals/dados_prefeitura_sp/dentro_sp/" + file_name
# with open(os_path_sep_join([FILES_PATH, file_name_path]), mode='rb') as file: # rb = read binary
# binary_file_content = file.read()
#
# self.tester.api_import_shp_create(binary_file_content, f_table_name=self.f_table_name,
# file_name=file_name,
# changeset_id=self.changeset_id)
"""
class TestAPIImportError(TestCase):
def setUp(self):
# create a tester passing the unittest self
self.tester = UtilTester(self)
# DO LOGIN
self.tester.auth_login("miguel@admin.com", "miguel")
self.f_table_name = "layer_test"
##################################################
# create a new layer
##################################################
self.layer = {
'type': 'Layer',
'properties': {'layer_id': -1, 'f_table_name': self.f_table_name, 'name': 'Points',
'description': '', 'source_description': '',
'reference': [1050], 'keyword': [1041]}
}
self.layer = self.tester.api_layer_create(self.layer)
self.layer_id = self.layer["properties"]["layer_id"]
##################################################
# create a new changeset
##################################################
changeset = {
'properties': {'changeset_id': -1, 'layer_id': self.layer_id},
'type': 'Changeset'
}
self.changeset_id = self.tester.api_changeset_create(changeset)
def tearDown(self):
##################################################
# remove the layer
##################################################
# CLOSE THE CHANGESET
close_changeset = {
'properties': {'changeset_id': self.changeset_id, 'description': 'Import'},
'type': 'ChangesetClose'
}
self.tester.api_changeset_close(close_changeset)
# REMOVE THE layer AFTER THE TESTS
self.tester.api_layer_delete(self.layer_id)
# it is not possible to find the layer that just deleted
expected = {'type': 'FeatureCollection', 'features': []}
self.tester.api_layer(expected, layer_id=self.layer_id)
# DO LOGOUT AFTER THE TESTS
self.tester.auth_logout()
# import - create error
def test_post_import_shp_error_400_bad_request_file_name_is_not_zip(self):
##################################################
# try to import the shapefile, but the zip doesn't have a shapefile
##################################################
file_name = "folder_with_nothing.zip"
with open(os_path_sep_join([FILES_PATH, file_name]), mode='rb') as file: # rb = read binary
binary_file_content = file.read()
self.tester.api_import_shp_create_error_400_bad_request(binary_file_content, f_table_name=self.f_table_name,
file_name="folder_with_nothing",
changeset_id=self.changeset_id)
def test_post_import_shp_error_400_bad_request_argument_is_missing(self):
##################################################
# import the shapefile with the created layer (the feature table will be the shapefile)
##################################################
file_name = "points.zip"
with open(os_path_sep_join([FILES_PATH, file_name]), mode='rb') as file: # rb = read binary
binary_file_content = file.read()
# try to import without binary_file_content
self.tester.api_import_shp_create_error_400_bad_request("", f_table_name=self.f_table_name,
file_name=file_name, changeset_id=self.changeset_id)
# try to import without f_table_name
self.tester.api_import_shp_create_error_400_bad_request(binary_file_content,
file_name=file_name, changeset_id=self.changeset_id)
# try to import without file_name
self.tester.api_import_shp_create_error_400_bad_request(binary_file_content, f_table_name=self.f_table_name,
changeset_id=self.changeset_id)
# try to import without changeset_id
self.tester.api_import_shp_create_error_400_bad_request(binary_file_content, f_table_name=self.f_table_name,
file_name=file_name)
def test_post_import_shp_error_400_bad_request_f_table_name_has_special_chars_or_it_starts_with_number(self):
##################################################
# try to import the shapefile, but the zip doesn't have a shapefile
##################################################
file_name = "points.zip"
list_f_table_name = [
"*)layer", "lay+-er", "layer_(/", "837_layer", "0_layer",
" new_layer", "new_layer ", "new layer"
]
for f_table_name in list_f_table_name:
with open(os_path_sep_join([FILES_PATH, file_name]), mode='rb') as file: # rb = read binary
binary_file_content = file.read()
self.tester.api_import_shp_create_error_400_bad_request(binary_file_content, f_table_name=f_table_name,
file_name="points",
changeset_id=self.changeset_id)
def test_post_import_shp_error_400_bad_request_invalid_prj_file_epsg_not_found(self):
file_name = "places_5_points_with_bad_prj.zip"
with open(os_path_sep_join([FILES_PATH, file_name]), mode='rb') as file: # rb = read binary
binary_file_content = file.read()
self.tester.api_import_shp_create_error_400_bad_request(binary_file_content, f_table_name=self.f_table_name,
file_name=file_name, changeset_id=self.changeset_id)
def test_post_import_shp_error_400_bad_request_prj_is_empty(self):
##################################################
# import the shapefile with the created layer (the feature table will be the shapefile)
##################################################
file_name = "points__prj_is_empty.zip"
with open(os_path_sep_join([FILES_PATH, file_name]), mode='rb') as file: # rb = read binary
binary_file_content = file.read()
self.tester.api_import_shp_create_error_400_bad_request(binary_file_content, f_table_name=self.f_table_name,
file_name=file_name, changeset_id=self.changeset_id)
def test_post_import_shp_error_403_forbidden_invalid_user_tries_to_create_a_feature_table(self):
f_table_name = "layer_1002"
file_name = "points.zip"
with open(os_path_sep_join([FILES_PATH, file_name]), mode='rb') as file: # rb = read binary
binary_file_content = file.read()
self.tester.api_import_shp_create_error_403_forbidden(binary_file_content, f_table_name=f_table_name,
file_name=file_name,changeset_id=self.changeset_id)
def test_post_import_shp_error_404_not_found_f_table_name_doesnt_exist(self):
f_table_name = "address"
file_name = "points.zip"
with open(os_path_sep_join([FILES_PATH, file_name]), mode='rb') as file: # rb = read binary
binary_file_content = file.read()
self.tester.api_import_shp_create_error_404_not_found(binary_file_content, f_table_name=f_table_name,
file_name=file_name, changeset_id=self.changeset_id)
def test_post_import_shp_error_404_not_found_not_found_shp(self):
##################################################
# import the shapefile with the created layer (the feature table will be the shapefile)
##################################################
file_name = "points_without_shp.zip"
with open(os_path_sep_join([FILES_PATH, file_name]), mode='rb') as file: # rb = read binary
binary_file_content = file.read()
self.tester.api_import_shp_create_error_404_not_found(binary_file_content, f_table_name=self.f_table_name,
file_name=file_name, changeset_id=self.changeset_id)
def test_post_import_shp_error_404_not_found_not_found_prj(self):
##################################################
# import the shapefile with the created layer (the feature table will be the shapefile)
##################################################
file_name = "points_without_prj.zip"
with open(os_path_sep_join([FILES_PATH, file_name]), mode='rb') as file: # rb = read binary
binary_file_content = file.read()
self.tester.api_import_shp_create_error_404_not_found(binary_file_content, f_table_name=self.f_table_name,
file_name=file_name, changeset_id=self.changeset_id)
def test_post_import_shp_error_404_not_found_not_found_dbf(self):
##################################################
# import the shapefile with the created layer (the feature table will be the shapefile)
##################################################
file_name = "points_without_dbf.zip"
with open(os_path_sep_join([FILES_PATH, file_name]), mode='rb') as file: # rb = read binary
binary_file_content = file.read()
self.tester.api_import_shp_create_error_404_not_found(binary_file_content, f_table_name=self.f_table_name,
file_name=file_name, changeset_id=self.changeset_id)
def test_post_import_shp_error_404_not_found_not_found_shx(self):
##################################################
# import the shapefile with the created layer (the feature table will be the shapefile)
##################################################
file_name = "points_without_shx.zip"
with open(os_path_sep_join([FILES_PATH, file_name]), mode='rb') as file: # rb = read binary
binary_file_content = file.read()
self.tester.api_import_shp_create_error_404_not_found(binary_file_content, f_table_name=self.f_table_name,
file_name=file_name, changeset_id=self.changeset_id)
def test_post_import_shp_error_409_conflict_file_is_not_a_zip_file(self):
##################################################
# import the shapefile with the created layer (the feature table will be the shapefile)
##################################################
wrong_file_name = "points.zip"
with open(os_path_sep_join([FILES_PATH, 'text.txt']), mode='rb') as file: # rb = read binary
binary_file_content = file.read()
self.tester.api_import_shp_create_error_409_conflict(binary_file_content, f_table_name=self.f_table_name,
file_name=wrong_file_name, changeset_id=self.changeset_id)
def test_post_import_shp_error_409_conflict_f_table_name_is_reserved_name(self):
##################################################
# import the shapefile with the created layer (the feature table will be the shapefile)
##################################################
file_name = "points.zip"
list_invalid_f_table_name = ["abort", "access"]
for invalid_f_table_name in list_invalid_f_table_name:
with open(os_path_sep_join([FILES_PATH, file_name]), mode='rb') as file: # rb = read binary
binary_file_content = file.read()
self.tester.api_import_shp_create_error_409_conflict(binary_file_content, file_name=file_name,
f_table_name=invalid_f_table_name,
changeset_id=self.changeset_id)
def test_post_import_shp_error_409_conflict_shapefile_is_not_inside_default_city(self):
##################################################
# import the shapefile with the created layer (the feature table will be the shapefile)
##################################################
file_name = "points.zip"
with open(os_path_sep_join([FILES_PATH, file_name]), mode='rb') as file: # rb = read binary
binary_file_content = file.read()
self.tester.api_import_shp_create_error_409_conflict(binary_file_content, f_table_name=self.f_table_name,
file_name=file_name, changeset_id=self.changeset_id)
def test_post_import_shp_error_500_internal_server_error_dbf_file_has_an_empty_column(self):
##################################################
# the Shapefile has an empty column name and fiona and OGR don't understand it
##################################################
file_name = "SarahFeldman_completa_arrumada__dbf_has_an_empty_column.zip"
file_name_path = "other/" + file_name
with open(os_path_sep_join([FILES_PATH, file_name_path]), mode='rb') as file: # rb = read binary
binary_file_content = file.read()
self.tester.api_import_shp_create_error_500_internal_server_error(binary_file_content, f_table_name=self.f_table_name,
file_name=file_name, changeset_id=self.changeset_id)
# def test_post_import_shp_error_500_internal_server_there_are_invalid_geometries_inside_the_shapefile(self):
# f_table_name = "layer_test"
#
# ##################################################
# # create a new layer
# ##################################################
# layer = {
# 'type': 'Layer',
# 'properties': {'layer_id': -1, 'f_table_name': f_table_name, 'name': 'Points',
# 'description': '', 'source_description': '',
# 'reference': [1050], 'keyword': [1041]}
# }
# layer = self.tester.api_layer_create(layer)
# layer_id = layer["properties"]["layer_id"]
#
# ##################################################
# # create a new changeset
# ##################################################
# changeset = {
# 'properties': {'changeset_id': -1, 'layer_id': layer_id},
# 'type': 'Changeset'
# }
# self.changeset_id = self.tester.api_changeset_create(changeset)
#
# ##################################################
# # import the shapefile with the created layer (the feature table will be the shapefile)
# ##################################################
# file_name = "sp_bacia_hidrografica.zip"
#
# with open(self.folder_name_shp_originals + file_name, mode='rb') as file: # rb = read binary
# binary_file_content = file.read()
#
# self.tester.api_import_shp_create_error_500_internal_server_error(binary_file_content,
# f_table_name=f_table_name,
# file_name=file_name,
# changeset_id=changeset_id)
#
# ##################################################
# # remove the layer
# ##################################################
# # CLOSE THE CHANGESET
# close_changeset = {
# 'properties': {'changeset_id': changeset_id, 'description': 'Import points.shp'},
# 'type': 'ChangesetClose'
# }
# self.tester.api_changeset_close(close_changeset)
#
# # REMOVE THE layer AFTER THE TESTS
# self.tester.api_layer_delete(layer_id)
#
# # it is not possible to find the layer that just deleted
# expected = {'type': 'FeatureCollection', 'features': []}
# self.tester.api_layer(expected, layer_id=layer_id)
class TestAPIImportErrorWithoutLogin(TestCase):
def setUp(self):
# create a tester passing the unittest self
self.tester = UtilTester(self)
self.f_table_name = "points"
self.changeset_id = 1005
# import - create error
def test_post_import_shp_error_401_unauthorized(self):
##################################################
# import the shapefile with the created layer (the feature table will be the shapefile)
##################################################
file_name = "points.zip"
with open(os_path_sep_join([FILES_PATH, file_name]), mode='rb') as file: # rb = read binary
binary_file_content = file.read()
self.tester.api_import_shp_create_error_401_unauthorized(binary_file_content, f_table_name=self.f_table_name,
file_name=file_name, changeset_id=self.changeset_id)
# Putting the unittest main() function here is not necessary,
# because this file will be called by run_tests.py
| 53.283019
| 130
| 0.55118
| 4,740
| 42,360
| 4.538608
| 0.061814
| 0.082927
| 0.054386
| 0.033189
| 0.912518
| 0.898294
| 0.892995
| 0.877795
| 0.872589
| 0.866871
| 0
| 0.011555
| 0.258404
| 42,360
| 794
| 131
| 53.350126
| 0.673267
| 0.172923
| 0
| 0.628665
| 0
| 0
| 0.089972
| 0.044748
| 0
| 0
| 0
| 0
| 0
| 1
| 0.127036
| false
| 0
| 0.263844
| 0
| 0.400651
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 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
| 6
|
6c76448bd7d818bf59678b74ffab1b4c596086a1
| 20
|
py
|
Python
|
tests/sample-import/foo/foo_d.py
|
schettino72/import-deps
|
f1238c67219293f5d05c434b78d968c68498d4eb
|
[
"MIT"
] | 9
|
2018-07-24T00:40:23.000Z
|
2021-08-29T23:46:54.000Z
|
tests/sample-import/foo/foo_d.py
|
schettino72/import-deps
|
f1238c67219293f5d05c434b78d968c68498d4eb
|
[
"MIT"
] | null | null | null |
tests/sample-import/foo/foo_d.py
|
schettino72/import-deps
|
f1238c67219293f5d05c434b78d968c68498d4eb
|
[
"MIT"
] | 1
|
2019-04-27T12:15:52.000Z
|
2019-04-27T12:15:52.000Z
|
from . import foo_c
| 10
| 19
| 0.75
| 4
| 20
| 3.5
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.2
| 20
| 1
| 20
| 20
| 0.875
| 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
| 1
| 0
|
0
| 6
|
6c76f4d83c3f39168c4bafb8e26f193c755c8c8a
| 39
|
py
|
Python
|
vulnapp/uploader/models/__init__.py
|
Fufuhu/VulnAppSample
|
d6a9ab667b2b5628a649d57cd97b1979bdd986f8
|
[
"Apache-2.0"
] | 1
|
2021-09-06T07:07:47.000Z
|
2021-09-06T07:07:47.000Z
|
vulnapp/uploader/models/__init__.py
|
Fufuhu/VulnAppSample
|
d6a9ab667b2b5628a649d57cd97b1979bdd986f8
|
[
"Apache-2.0"
] | null | null | null |
vulnapp/uploader/models/__init__.py
|
Fufuhu/VulnAppSample
|
d6a9ab667b2b5628a649d57cd97b1979bdd986f8
|
[
"Apache-2.0"
] | null | null | null |
from .uploaded_file import UploadedFile
| 39
| 39
| 0.897436
| 5
| 39
| 6.8
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.076923
| 39
| 1
| 39
| 39
| 0.944444
| 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
| 1
| 0
|
0
| 6
|
665e3853351cda0ad5f62e40841e7a462d1c926d
| 173
|
py
|
Python
|
codeforces/educational_92/a.py
|
leetcode-notes/daily-algorithms-practice
|
2a03499ed0b403d79f6c8451c9a839991b23e188
|
[
"Unlicense"
] | null | null | null |
codeforces/educational_92/a.py
|
leetcode-notes/daily-algorithms-practice
|
2a03499ed0b403d79f6c8451c9a839991b23e188
|
[
"Unlicense"
] | null | null | null |
codeforces/educational_92/a.py
|
leetcode-notes/daily-algorithms-practice
|
2a03499ed0b403d79f6c8451c9a839991b23e188
|
[
"Unlicense"
] | null | null | null |
def gcd(a, b):
if min(a, b) == 0:
return max(a, b)
a_1 = max(a, b) % min(a, b)
return gcd(a_1, min(a, b))
def lcm(a, b):
return (a * b) // gcd(a, b)
| 21.625
| 31
| 0.450867
| 38
| 173
| 2
| 0.289474
| 0.236842
| 0.197368
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.025641
| 0.323699
| 173
| 8
| 32
| 21.625
| 0.623932
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.285714
| false
| 0
| 0
| 0.142857
| 0.714286
| 0
| 0
| 0
| 0
| null | 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 1
| 0
|
0
| 6
|
667c3e725b29158738dca0cc5fee22a3bef5df5b
| 228
|
py
|
Python
|
test_data/files/binary_downloader_tests.py
|
aleksul/pytest-motor
|
20dd246fce777f0e21d1d03244e494e818a3dd52
|
[
"MIT"
] | 4
|
2021-07-10T15:21:01.000Z
|
2021-07-17T12:11:06.000Z
|
test_data/files/binary_downloader_tests.py
|
aleksul/pytest-motor
|
20dd246fce777f0e21d1d03244e494e818a3dd52
|
[
"MIT"
] | 47
|
2021-07-12T13:59:19.000Z
|
2022-01-31T20:49:03.000Z
|
test_data/files/binary_downloader_tests.py
|
aleksul/pytest-motor
|
20dd246fce777f0e21d1d03244e494e818a3dd52
|
[
"MIT"
] | 4
|
2021-07-13T19:38:47.000Z
|
2021-07-17T13:14:46.000Z
|
"""A test file with a multiple tests for mongodb binary downloader."""
from pathlib import Path
def test_binary_downloads(mongod_binary: Path) -> None:
"""Tests if mongod_binary exists"""
assert mongod_binary.exists()
| 28.5
| 70
| 0.745614
| 32
| 228
| 5.15625
| 0.65625
| 0.218182
| 0.218182
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.157895
| 228
| 7
| 71
| 32.571429
| 0.859375
| 0.412281
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.333333
| 1
| 0.333333
| false
| 0
| 0.333333
| 0
| 0.666667
| 0
| 0
| 0
| 0
| null | 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 1
| 0
| 1
| 0
|
0
| 6
|
66af9d30a977d482ec8d3c486f8d15ca0af8ea81
| 154
|
py
|
Python
|
lsld2/__init__.py
|
Xiaoy01/lsld2
|
b8079ad92cb186b899a83b5e00618b4d715592db
|
[
"MIT"
] | null | null | null |
lsld2/__init__.py
|
Xiaoy01/lsld2
|
b8079ad92cb186b899a83b5e00618b4d715592db
|
[
"MIT"
] | null | null | null |
lsld2/__init__.py
|
Xiaoy01/lsld2
|
b8079ad92cb186b899a83b5e00618b4d715592db
|
[
"MIT"
] | null | null | null |
# from fit import FitCLI, fit, fit_sat
# from . import fit # works weirdly
from .fit import FitCLI, fit, fit_sat
__all__ = ["FitCLI", "fit", "fit_sat"]
| 25.666667
| 38
| 0.688312
| 24
| 154
| 4.125
| 0.333333
| 0.272727
| 0.363636
| 0.454545
| 0.565657
| 0.565657
| 0.565657
| 0
| 0
| 0
| 0
| 0
| 0.181818
| 154
| 5
| 39
| 30.8
| 0.785714
| 0.454545
| 0
| 0
| 0
| 0
| 0.2
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.5
| 0
| 0.5
| 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
| 1
| 0
| 0
| 0
|
0
| 6
|
66bb46bb315f47405eb4413d6fef71a68d455bb7
| 44
|
py
|
Python
|
ifree/__init__.py
|
linzhenyuyuchen/ifree
|
87b3cee58d3c87bd148170d77f9f360820e29489
|
[
"MIT"
] | 3
|
2021-07-23T05:58:31.000Z
|
2021-12-30T13:18:07.000Z
|
ifree/__init__.py
|
linzhenyuyuchen/ifree
|
87b3cee58d3c87bd148170d77f9f360820e29489
|
[
"MIT"
] | 1
|
2021-07-23T06:24:26.000Z
|
2021-07-23T06:25:15.000Z
|
ifree/__init__.py
|
linzhenyuyuchen/ifree
|
87b3cee58d3c87bd148170d77f9f360820e29489
|
[
"MIT"
] | null | null | null |
import ifree.processing
import ifree.dicom
| 11
| 23
| 0.840909
| 6
| 44
| 6.166667
| 0.666667
| 0.594595
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.113636
| 44
| 3
| 24
| 14.666667
| 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 | 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
| 6
|
66be3a08e48fb62d5154dd3aa0c96b6659a63e65
| 142
|
py
|
Python
|
my_test.py
|
Athenian-CT-Fall2020/100-years-maleich
|
217c19d79cdc6b8bc14419ba6a7d418fccbc82a5
|
[
"Apache-2.0"
] | null | null | null |
my_test.py
|
Athenian-CT-Fall2020/100-years-maleich
|
217c19d79cdc6b8bc14419ba6a7d418fccbc82a5
|
[
"Apache-2.0"
] | null | null | null |
my_test.py
|
Athenian-CT-Fall2020/100-years-maleich
|
217c19d79cdc6b8bc14419ba6a7d418fccbc82a5
|
[
"Apache-2.0"
] | null | null | null |
from my_code import year_100
def test_inc():
assert 2105 == year_100(15)
assert 2120 == year_100(0)
assert 2095 == year_100(25)
| 17.75
| 31
| 0.669014
| 24
| 142
| 3.708333
| 0.666667
| 0.314607
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.263636
| 0.225352
| 142
| 7
| 32
| 20.285714
| 0.545455
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.6
| 1
| 0.2
| true
| 0
| 0.2
| 0
| 0.4
| 0
| 1
| 0
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
|
0
| 6
|
66d6146a7dd97b6065e045596d05dcd72e2ee829
| 130
|
py
|
Python
|
mmdet/ops/psroi_pool/__init__.py
|
qinr/MRDet
|
44b608ec6007db204dcb6b82eff9e356fc7b56d0
|
[
"Apache-2.0"
] | 8
|
2021-05-25T10:49:00.000Z
|
2021-11-28T04:01:02.000Z
|
mmdet/ops/psroi_pool/__init__.py
|
qinr/MRDet
|
44b608ec6007db204dcb6b82eff9e356fc7b56d0
|
[
"Apache-2.0"
] | null | null | null |
mmdet/ops/psroi_pool/__init__.py
|
qinr/MRDet
|
44b608ec6007db204dcb6b82eff9e356fc7b56d0
|
[
"Apache-2.0"
] | 2
|
2021-07-22T12:53:37.000Z
|
2021-12-17T12:53:51.000Z
|
from .functions.psroi_pool import psroi_pool
from .modules.psroi_pool import PSRoIPool
__all__ = ['psroi_pool', 'PSRoIPool']
| 26
| 45
| 0.776923
| 17
| 130
| 5.470588
| 0.470588
| 0.387097
| 0.322581
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.130769
| 130
| 4
| 46
| 32.5
| 0.823009
| 0
| 0
| 0
| 0
| 0
| 0.150794
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.666667
| 0
| 0.666667
| 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
| 1
| 0
|
0
| 6
|
dd71ce8054c06a085ebf6892e3bb54fed7947d76
| 7,948
|
py
|
Python
|
tests/test_caps_text.py
|
memfault/pyprctl
|
3795c7b1d2e2af88079a972f676217bc518f19a8
|
[
"MIT"
] | 3
|
2021-04-21T10:25:35.000Z
|
2021-12-25T08:28:13.000Z
|
tests/test_caps_text.py
|
memfault/pyprctl
|
3795c7b1d2e2af88079a972f676217bc518f19a8
|
[
"MIT"
] | 1
|
2021-06-10T22:18:57.000Z
|
2021-06-10T22:18:57.000Z
|
tests/test_caps_text.py
|
memfault/pyprctl
|
3795c7b1d2e2af88079a972f676217bc518f19a8
|
[
"MIT"
] | 1
|
2021-06-09T11:55:03.000Z
|
2021-06-09T11:55:03.000Z
|
import pytest
import pyprctl
ALL_CAPS_SET = set(pyprctl.Cap)
def test_capstate_to_text() -> None:
assert str(pyprctl.CapState()) == "="
assert str(pyprctl.CapState(effective={pyprctl.Cap.CHOWN})) == "cap_chown=e"
assert str(pyprctl.CapState(effective=ALL_CAPS_SET - {pyprctl.Cap.CHOWN})) == "=e cap_chown-e"
assert (
str(
pyprctl.CapState(
effective=ALL_CAPS_SET - {pyprctl.Cap.CHOWN},
permitted=ALL_CAPS_SET,
)
)
== "=ep cap_chown-e"
)
assert (
str(
pyprctl.CapState(
effective=ALL_CAPS_SET,
inheritable=ALL_CAPS_SET,
permitted=ALL_CAPS_SET,
)
)
== "=eip"
)
assert (
str(
pyprctl.CapState(
effective=ALL_CAPS_SET,
inheritable=ALL_CAPS_SET - {pyprctl.Cap.CHOWN},
permitted=ALL_CAPS_SET - {pyprctl.Cap.SYS_CHROOT},
)
)
== "=eip cap_chown-i cap_sys_chroot-p"
)
assert (
str(
pyprctl.CapState(
effective=ALL_CAPS_SET - {pyprctl.Cap.CHOWN},
inheritable={pyprctl.Cap.CHOWN},
permitted=ALL_CAPS_SET,
)
)
== "=ep cap_chown+i cap_chown-e"
)
assert (
str(
pyprctl.CapState(
effective=ALL_CAPS_SET - {pyprctl.Cap.CHOWN},
inheritable=ALL_CAPS_SET - {pyprctl.Cap.CHOWN},
permitted=ALL_CAPS_SET - {pyprctl.Cap.CHOWN},
)
)
== "=eip cap_chown-eip"
)
def test_capstate_from_text() -> None:
empty_state = pyprctl.CapState()
assert pyprctl.CapState.from_text("") == empty_state
assert pyprctl.CapState.from_text("=") == empty_state
assert pyprctl.CapState.from_text("all=") == empty_state
assert pyprctl.CapState.from_text("all=eip all-eip") == empty_state
assert pyprctl.CapState.from_text("all+eip all-eip") == empty_state
assert pyprctl.CapState.from_text("cap_chown=e") == pyprctl.CapState(
effective={pyprctl.Cap.CHOWN}, permitted=set(), inheritable=set()
)
# Case-insensitive
assert pyprctl.CapState.from_text("ALL=") == empty_state
assert pyprctl.CapState.from_text("CAP_CHOWN=e") == pyprctl.CapState(
effective={pyprctl.Cap.CHOWN}, permitted=set(), inheritable=set()
)
assert pyprctl.CapState.from_text("cap_chown=ei") == pyprctl.CapState(
effective={pyprctl.Cap.CHOWN}, permitted=set(), inheritable={pyprctl.Cap.CHOWN}
)
assert pyprctl.CapState.from_text("cap_chown+ei") == pyprctl.CapState(
effective={pyprctl.Cap.CHOWN}, permitted=set(), inheritable={pyprctl.Cap.CHOWN}
)
assert pyprctl.CapState.from_text("cap_chown=ei cap_chown-i") == pyprctl.CapState(
effective={pyprctl.Cap.CHOWN}, permitted=set(), inheritable=set()
)
with pytest.raises(ValueError, match="Invalid capability set clause"):
pyprctl.CapState.from_text("cap_chown")
with pytest.raises(ValueError, match="Repeated flag characters"):
pyprctl.CapState.from_text("cap_chown+-e")
with pytest.raises(ValueError, match="Repeated flag characters"):
pyprctl.CapState.from_text("cap_chown++e")
with pytest.raises(ValueError, match="Invalid character"):
pyprctl.CapState.from_text("cap_chown=E")
with pytest.raises(ValueError, match="Invalid character"):
pyprctl.CapState.from_text("cap_chown=o")
with pytest.raises(ValueError, match="Unknown capability"):
pyprctl.CapState.from_text("cap_noexist=e")
with pytest.raises(ValueError, match="Unknown capability"):
pyprctl.CapState.from_text("noexist=e")
with pytest.raises(ValueError, match="Unknown capability"):
pyprctl.CapState.from_text("chown=e")
def test_capstate_to_from_text() -> None:
for capstate in [
pyprctl.CapState(),
pyprctl.CapState(effective=set(pyprctl.Cap)),
pyprctl.CapState(
permitted=set(pyprctl.Cap), inheritable={pyprctl.Cap.CHOWN, pyprctl.Cap.SYS_CHROOT}
),
pyprctl.CapState(
permitted=set(pyprctl.Cap),
inheritable=set(pyprctl.Cap) - {pyprctl.Cap.CHOWN, pyprctl.Cap.SYS_CHROOT},
),
]:
assert pyprctl.CapState.from_text(str(capstate)) == capstate
def test_filecaps_to_text() -> None:
assert (
str(pyprctl.FileCaps(effective=False, permitted=set(), inheritable=set(), rootid=None))
== "="
)
assert (
str(
pyprctl.FileCaps(
effective=False, permitted=ALL_CAPS_SET, inheritable=set(), rootid=None
)
)
== "=p"
)
assert (
str(
pyprctl.FileCaps(
effective=False, permitted=ALL_CAPS_SET, inheritable=ALL_CAPS_SET, rootid=0
)
)
== "=ip"
)
assert (
str(
pyprctl.FileCaps(
effective=True, permitted=ALL_CAPS_SET, inheritable=ALL_CAPS_SET, rootid=None
)
)
== "=eip"
)
assert (
str(
pyprctl.FileCaps(effective=True, permitted=ALL_CAPS_SET, inheritable=set(), rootid=None)
)
== "=ep"
)
assert (
str(
pyprctl.FileCaps(effective=True, permitted=set(), inheritable=ALL_CAPS_SET, rootid=None)
)
== "=i"
)
def test_filecaps_from_text() -> None:
empty_state = pyprctl.FileCaps(effective=False, permitted=set(), inheritable=set(), rootid=None)
assert pyprctl.FileCaps.from_text("") == empty_state
assert pyprctl.FileCaps.from_text("=") == empty_state
assert pyprctl.FileCaps.from_text("all=eip") == pyprctl.FileCaps(
effective=True, permitted=ALL_CAPS_SET, inheritable=ALL_CAPS_SET, rootid=None
)
assert pyprctl.FileCaps.from_text("all=ip") == pyprctl.FileCaps(
effective=False, permitted=ALL_CAPS_SET, inheritable=ALL_CAPS_SET, rootid=None
)
with pytest.raises(
ValueError, match="non-empty effective set that is not equal to permitted set"
):
pyprctl.FileCaps.from_text("all=eip cap_chown-p")
with pytest.raises(
ValueError, match="non-empty effective set that is not equal to permitted set"
):
pyprctl.FileCaps.from_text("all=eip cap_chown-e")
with pytest.raises(
ValueError, match="non-empty effective set that is not equal to permitted set"
):
pyprctl.FileCaps.from_text("cap_chown+p cap_sys_chroot+e")
with pytest.raises(
ValueError, match="non-empty effective set that is not equal to permitted set"
):
pyprctl.FileCaps.from_text("cap_chown+ep cap_sys_chroot+p")
with pytest.raises(
ValueError, match="non-empty effective set that is not equal to permitted set"
):
pyprctl.FileCaps.from_text("cap_chown+ep cap_sys_chroot+e")
def test_filecaps_to_from_text() -> None:
for filecaps in [
pyprctl.FileCaps(permitted=set(), inheritable=set(), effective=False, rootid=None),
pyprctl.FileCaps(
permitted=set(pyprctl.Cap), inheritable=set(), effective=False, rootid=None
),
pyprctl.FileCaps(
permitted=set(pyprctl.Cap),
inheritable={pyprctl.Cap.CHOWN, pyprctl.Cap.SYS_CHROOT},
effective=False,
rootid=None,
),
pyprctl.FileCaps(
permitted=set(pyprctl.Cap),
inheritable=set(pyprctl.Cap) - {pyprctl.Cap.CHOWN, pyprctl.Cap.SYS_CHROOT},
effective=True,
rootid=None,
),
]:
print(repr(filecaps))
print(repr(pyprctl.FileCaps.from_text(str(filecaps))))
print(str(filecaps))
print(pyprctl.FileCaps.from_text(str(filecaps)))
assert pyprctl.FileCaps.from_text(str(filecaps)) == filecaps
| 31.919679
| 100
| 0.618143
| 901
| 7,948
| 5.285239
| 0.067703
| 0.072239
| 0.054599
| 0.096598
| 0.897312
| 0.880302
| 0.815834
| 0.792734
| 0.776564
| 0.776564
| 0
| 0.00017
| 0.258807
| 7,948
| 248
| 101
| 32.048387
| 0.808182
| 0.002013
| 0
| 0.438424
| 0
| 0
| 0.11652
| 0
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| 0
| 0
| 0
| 0.152709
| 1
| 0.029557
| false
| 0
| 0.009852
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| 0.039409
| 0.019704
| 0
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| 0
| null | 0
| 0
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| 1
| 1
| 1
| 1
| 1
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| 0
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| 0
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| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 6
|
dd872efe1ef10a613409539e20d6cbc90bffc2c8
| 156
|
py
|
Python
|
app.py
|
suricats/surirobot-api-services
|
b23b440649a759d638cbc8644acc4aeb7f118674
|
[
"MIT"
] | null | null | null |
app.py
|
suricats/surirobot-api-services
|
b23b440649a759d638cbc8644acc4aeb7f118674
|
[
"MIT"
] | 1
|
2019-05-22T16:17:59.000Z
|
2019-09-05T13:09:03.000Z
|
app.py
|
suricats/surirobot-api-services
|
b23b440649a759d638cbc8644acc4aeb7f118674
|
[
"MIT"
] | 1
|
2019-07-02T09:40:28.000Z
|
2019-07-02T09:40:28.000Z
|
#!/usr/bin/env python3
from dotenv import load_dotenv, find_dotenv
# Load .env
load_dotenv(find_dotenv())
from api.server import app
app.run(debug=False)
| 17.333333
| 43
| 0.775641
| 26
| 156
| 4.5
| 0.576923
| 0.17094
| 0.239316
| 0.34188
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.007246
| 0.115385
| 156
| 8
| 44
| 19.5
| 0.84058
| 0.198718
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| 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
| 1
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| 0
| 0
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| 0
| 0
| 0
| 0
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| 0
| 1
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| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 6
|
dd8bd99685a77c6182b96f88559fc22419d13986
| 6,827
|
py
|
Python
|
src/chaos_service/main.py
|
glimsil/chaos-service
|
0f4f9fa3e1202ae869a1915e38a1607b2c34f626
|
[
"BSD-2-Clause"
] | null | null | null |
src/chaos_service/main.py
|
glimsil/chaos-service
|
0f4f9fa3e1202ae869a1915e38a1607b2c34f626
|
[
"BSD-2-Clause"
] | null | null | null |
src/chaos_service/main.py
|
glimsil/chaos-service
|
0f4f9fa3e1202ae869a1915e38a1607b2c34f626
|
[
"BSD-2-Clause"
] | null | null | null |
import click
from flask import Flask
from chaos_service.api import api, config
from chaos_service.config.config_storage import ConfigStorage
@click.group()
@click.version_option("0.0.1")
def cli():
"""
First version of chaos service.
"""
@cli.command()
@click.option('--start-at-request', help='Start returning 500 error at request number N. (This is the default option starting at 10)', required=False)
@click.option('--chance-of-sucess', help='Probability of returning error(0-100). If 100 informed it has 100 percent of chance of returning 200.', required=False)
@click.option('--chance-of-sucess-until-hit', help='Probability of starting to return error(0-100). If 100 informed it has 100 percent of chance of returning 200. When the first error hits, the next calls will be errors', required=False)
def bad_request(start_at_request, chance_of_sucess, chance_of_sucess_until_hit):
"""Start api for to test bad request failures."""
config.create_config("bad_request", start_at_request, chance_of_sucess, chance_of_sucess_until_hit)
app = Flask(__name__)
app.register_blueprint(api)
app.run(port=8080)
@cli.command()
@click.option('--start-at-request', help='Start returning 500 error at request number N. (This is the default option starting at 10)', required=False)
@click.option('--chance-of-sucess', help='Probability of returning error(0-100). If 100 informed it has 100 percent of chance of returning 200.', required=False)
@click.option('--chance-of-sucess-until-hit', help='Probability of starting to return error(0-100). If 100 informed it has 100 percent of chance of returning 200. When the first error hits, the next calls will be errors', required=False)
def internal_server_error(start_at_request, chance_of_sucess, chance_of_sucess_until_hit):
"""Start api to test internal server error failures."""
config.create_config("internal_server_error", start_at_request, chance_of_sucess, chance_of_sucess_until_hit)
app = Flask(__name__)
app.register_blueprint(api)
app.run(port=8080)
@cli.command()
@click.option('--start-at-request', help='Start returning 502 error at request number N. (This is the default option starting at 10)', required=False)
@click.option('--chance-of-sucess', help='Probability of returning error(0-100). If 100 informed it has 100 percent of chance of returning 200.', required=False)
@click.option('--chance-of-sucess-until-hit', help='Probability of starting to return error(0-100). If 100 informed it has 100 percent of chance of returning 200. When the first error hits, the next calls will be errors', required=False)
def bad_gateway(start_at_request, chance_of_sucess, chance_of_sucess_until_hit):
"""Start api for to test bad gateway failures."""
config.create_config("bad_gateway", start_at_request, chance_of_sucess, chance_of_sucess_until_hit)
app = Flask(__name__)
app.register_blueprint(api)
app.run(port=8080)
@cli.command()
@click.option('--start-at-request', help='Start returning 503 error at request number N. (This is the default option starting at 10)', required=False)
@click.option('--chance-of-sucess', help='Probability of returning error(0-100). If 100 informed it has 100 percent of chance of returning 200.', required=False)
@click.option('--chance-of-sucess-until-hit', help='Probability of starting to return error(0-100). If 100 informed it has 100 percent of chance of returning 200. When the first error hits, the next calls will be errors', required=False)
def service_unavailable(start_at_request, chance_of_sucess, chance_of_sucess_until_hit):
"""Start api for to test service unavailable failures."""
config.create_config("service_unavailable", start_at_request, chance_of_sucess, chance_of_sucess_until_hit)
app = Flask(__name__)
app.register_blueprint(api)
app.run(port=8080)
@cli.command()
@click.option('--start-at-request', help='Start returning 504 error at request number N. (This is the default option starting at 10)', required=False)
@click.option('--chance-of-sucess', help='Probability of returning error(0-100). If 100 informed it has 100 percent of chance of returning 200.', required=False)
@click.option('--chance-of-sucess-until-hit', help='Probability of starting to return error(0-100). If 100 informed it has 100 percent of chance of returning 200. When the first error hits, the next calls will be errors', required=False)
def gateway_timeout(start_at_request, chance_of_sucess, chance_of_sucess_until_hit):
"""Start api for to test gateway timeout failures."""
config.create_config("gateway_timeout", start_at_request, chance_of_sucess, chance_of_sucess_until_hit)
app = Flask(__name__)
app.register_blueprint(api)
app.run(port=8080)
@cli.command()
@click.option('--start-at-request', help='Start returning 500 error at request number N. (This is the default option starting at 10)', required=False)
@click.option('--chance-of-sucess', help='Probability of returning error(0-100). If 100 informed it has 100 percent of chance of returning 200.', required=False)
@click.option('--chance-of-sucess-until-hit', help='Probability of starting to return error(0-100). If 100 informed it has 100 percent of chance of returning 200. When the first error hits, the next calls will be errors', required=False)
def connection_refused(start_at_request, chance_of_sucess, chance_of_sucess_until_hit):
"""Start api to test connection refused failures. It will shut down the server when error criteria appers."""
config.create_config("connection_refused", start_at_request, chance_of_sucess, chance_of_sucess_until_hit)
app = Flask(__name__)
app.register_blueprint(api)
app.run(port=8080)
@cli.command()
@click.option('--start-at-request', help='Start returning 500 error at request number N.', required=False)
@click.option('--chance-of-sucess', help='Probability of returning error(0-100). If 100 informed it has 100 percent of chance of returning status 200 OK. (For chaos this is the default option with 90 percent of success rate)', required=False)
@click.option('--chance-of-sucess-until-hit', help='Probability of starting to return error(0-100). If 100 informed it has 100 percent of chance of returning 200. When the first error hits, the next calls will be errors', required=False)
def chaos(start_at_request, chance_of_sucess, chance_of_sucess_until_hit):
"""Start api to test all types of failures randomically. It will shut down the server when error criteria appers."""
if(start_at_request is None and chance_of_sucess is None and chance_of_sucess_until_hit is None):
chance_of_sucess = 90
config.create_config("chaos", start_at_request, chance_of_sucess, chance_of_sucess_until_hit)
app = Flask(__name__)
app.register_blueprint(api)
app.run(port=8080)
| 72.62766
| 242
| 0.767541
| 1,081
| 6,827
| 4.679001
| 0.087882
| 0.093318
| 0.124555
| 0.082641
| 0.899565
| 0.883353
| 0.874259
| 0.874259
| 0.874259
| 0.874259
| 0
| 0.04196
| 0.127289
| 6,827
| 94
| 243
| 72.62766
| 0.806982
| 0.070895
| 0
| 0.611111
| 0
| 0.194444
| 0.491975
| 0.034483
| 0
| 0
| 0
| 0
| 0
| 1
| 0.111111
| false
| 0
| 0.055556
| 0
| 0.166667
| 0.097222
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 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
| 6
|
b088c406c08be7e77a5c636e5778fdee364997d3
| 135
|
py
|
Python
|
model/GAT_model.py
|
kw-lee/pytorch-DCRNN
|
49fbf64705360f2d2586a94fb1bde1b2f9599a70
|
[
"MIT"
] | null | null | null |
model/GAT_model.py
|
kw-lee/pytorch-DCRNN
|
49fbf64705360f2d2586a94fb1bde1b2f9599a70
|
[
"MIT"
] | null | null | null |
model/GAT_model.py
|
kw-lee/pytorch-DCRNN
|
49fbf64705360f2d2586a94fb1bde1b2f9599a70
|
[
"MIT"
] | null | null | null |
import torch
import numpy as np
import torch.nn as nn
import torch.nn.functional as F
import math
from matplotlib import pyplot as plt
| 19.285714
| 36
| 0.814815
| 25
| 135
| 4.4
| 0.52
| 0.3
| 0.236364
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.162963
| 135
| 6
| 37
| 22.5
| 0.973451
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 1
| 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
| 6
|
b08f085d366e1878731d18d4f8e0b96ebe4a57d9
| 275
|
py
|
Python
|
src/models/stochastic/bbb/utils_bbb.py
|
tjiagoM/quantised-bayesian-nets
|
c6ff1db376c366633afa2845b7527cc144ffd3b2
|
[
"BSD-3-Clause"
] | 13
|
2021-02-23T09:48:10.000Z
|
2021-12-30T18:04:30.000Z
|
src/models/stochastic/bbb/utils_bbb.py
|
tjiagoM/quantised-bayesian-nets
|
c6ff1db376c366633afa2845b7527cc144ffd3b2
|
[
"BSD-3-Clause"
] | 1
|
2021-06-15T16:24:36.000Z
|
2021-06-15T16:24:36.000Z
|
src/models/stochastic/bbb/utils_bbb.py
|
tjiagoM/quantised-bayesian-nets
|
c6ff1db376c366633afa2845b7527cc144ffd3b2
|
[
"BSD-3-Clause"
] | 1
|
2021-06-15T14:53:20.000Z
|
2021-06-15T14:53:20.000Z
|
import torch
def kl_divergence(mu, sigma, mu_prior, sigma_prior):
kl = 0.5 * (2 * torch.log(sigma_prior / sigma) - 1 + (sigma / sigma_prior).pow(2) + ((mu_prior - mu) / sigma_prior).pow(2)).sum()
return kl
def softplusinv(x):
return torch.log(torch.exp(x)-1.)
| 34.375
| 134
| 0.647273
| 46
| 275
| 3.717391
| 0.413043
| 0.233918
| 0.152047
| 0.163743
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.030973
| 0.178182
| 275
| 8
| 135
| 34.375
| 0.725664
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.333333
| false
| 0
| 0.166667
| 0.166667
| 0.833333
| 0
| 0
| 0
| 0
| null | 1
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 1
| 0
|
0
| 6
|
b097b951548a3dad50a25e24982520e9614949b0
| 126
|
py
|
Python
|
benchmarks/python/tests/ewise.multiply.py
|
kgryte/micro-benchmarks-numeric-computing
|
9efc5d18d36b7437e5a7c9d41eb8e41a798617b8
|
[
"MIT"
] | 1
|
2015-11-28T16:50:04.000Z
|
2015-11-28T16:50:04.000Z
|
benchmarks/python/tests/ewise.multiply.py
|
kgryte/micro-benchmarks-numeric-computing
|
9efc5d18d36b7437e5a7c9d41eb8e41a798617b8
|
[
"MIT"
] | null | null | null |
benchmarks/python/tests/ewise.multiply.py
|
kgryte/micro-benchmarks-numeric-computing
|
9efc5d18d36b7437e5a7c9d41eb8e41a798617b8
|
[
"MIT"
] | null | null | null |
#!/usr/bin/python
# coding: utf-8
import numpy as np
def test():
"""Performs element-wise multiplication."""
pass
| 11.454545
| 47
| 0.642857
| 17
| 126
| 4.764706
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| 0.206349
| 126
| 10
| 48
| 12.6
| 0.8
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| 0.333333
| true
| 0.333333
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| 1
| 1
| 1
| 0
| 1
| 0
|
0
| 6
|
9fedd6b5a21086dbe8af9d7e03cfceeb854380c5
| 34
|
py
|
Python
|
govapi/__init__.py
|
SiraArduino/govapi
|
f0307b2ab50d466624574f87eebed8a750deb481
|
[
"MIT"
] | 1
|
2021-09-27T00:28:25.000Z
|
2021-09-27T00:28:25.000Z
|
govapi/__init__.py
|
SiraArduino/govapi
|
f0307b2ab50d466624574f87eebed8a750deb481
|
[
"MIT"
] | 2
|
2021-09-07T15:55:16.000Z
|
2021-09-29T07:12:27.000Z
|
govapi/__init__.py
|
SiraArduino/govapi
|
f0307b2ab50d466624574f87eebed8a750deb481
|
[
"MIT"
] | 1
|
2021-09-29T06:40:35.000Z
|
2021-09-29T06:40:35.000Z
|
from govapi.govapi import GovAPI
| 17
| 33
| 0.823529
| 5
| 34
| 5.6
| 0.6
| 0
| 0
| 0
| 0
| 0
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| 0.147059
| 34
| 1
| 34
| 34
| 0.965517
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| null | 0
| 0
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| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 6
|
9ff498d718f83f7c748d1016f96054bc674bcbd5
| 176
|
py
|
Python
|
awkwardql/interface.py
|
lgray/AwkwardQL
|
53802afa248740893512d01b8b7365a2e3a34367
|
[
"BSD-3-Clause"
] | 1
|
2019-12-28T21:11:22.000Z
|
2019-12-28T21:11:22.000Z
|
awkwardql/interface.py
|
lgray/AwkwardQL
|
53802afa248740893512d01b8b7365a2e3a34367
|
[
"BSD-3-Clause"
] | 3
|
2020-01-08T07:01:57.000Z
|
2020-01-08T15:54:48.000Z
|
awkwardql/interface.py
|
lgray/AwkwardQL
|
53802afa248740893512d01b8b7365a2e3a34367
|
[
"BSD-3-Clause"
] | 1
|
2020-01-08T06:50:13.000Z
|
2020-01-08T06:50:13.000Z
|
from . import interpreter
def query(func):
def wrapped(dataset, verbose=False):
return interpreter.run(func.__doc__, dataset, verbose=verbose)
return wrapped
| 22
| 70
| 0.721591
| 21
| 176
| 5.857143
| 0.619048
| 0.227642
| 0
| 0
| 0
| 0
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| 0
| 0
| 0.1875
| 176
| 7
| 71
| 25.142857
| 0.86014
| 0
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| 0.4
| false
| 0
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| 0
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| 1
| 0
|
0
| 6
|
b00d9a355471699c16e8e13923ea7c0796a916e7
| 4,950
|
py
|
Python
|
.c9/metadata/environment/line_bitcoin.py
|
Grawor/cloud9
|
a7106f124c2c9386cef66983839164db6881a2a5
|
[
"MIT"
] | null | null | null |
.c9/metadata/environment/line_bitcoin.py
|
Grawor/cloud9
|
a7106f124c2c9386cef66983839164db6881a2a5
|
[
"MIT"
] | 2
|
2020-06-05T19:36:02.000Z
|
2021-03-31T19:03:15.000Z
|
.c9/metadata/environment/line_bitcoin.py
|
Grawor/auto_bot
|
a7106f124c2c9386cef66983839164db6881a2a5
|
[
"MIT"
] | null | null | null |
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| 4,950
| 4,950
| 0.566263
| 712
| 4,950
| 3.922753
| 0.130618
| 0.09488
| 0.208736
| 0.154672
| 0.622986
| 0.547798
| 0.433942
| 0.425707
| 0.359828
| 0.269961
| 0
| 0.087475
| 0
| 4,950
| 1
| 4,950
| 4,950
| 0.476768
| 0
| 0
| 0
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| 0
| 0.477479
| 0.023632
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| null | 0
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| 1
| 0
| 0
| 0
| 0
| 0
|
0
| 6
|
c6636eaa2f7a2fce7182628bb8300e511d9298fe
| 217
|
py
|
Python
|
hypothesis/util/data/numpy/__init__.py
|
boyali/hypothesis-sre
|
f44d25eb281d49663d49d134ee73ad542849714b
|
[
"BSD-3-Clause"
] | 45
|
2019-02-13T14:16:35.000Z
|
2022-02-23T21:30:02.000Z
|
hypothesis/util/data/numpy/__init__.py
|
boyali/hypothesis-sre
|
f44d25eb281d49663d49d134ee73ad542849714b
|
[
"BSD-3-Clause"
] | 1
|
2020-01-13T08:29:50.000Z
|
2020-01-22T10:28:02.000Z
|
hypothesis/util/data/numpy/__init__.py
|
boyali/hypothesis-sre
|
f44d25eb281d49663d49d134ee73ad542849714b
|
[
"BSD-3-Clause"
] | 8
|
2019-04-23T14:25:08.000Z
|
2021-07-28T15:05:31.000Z
|
from .storage import InMemoryStorage
from .storage import PersistentStorage
from .simulation_dataset import SimulationDataset
from .util import compute_final_shape
from .util import merge
from .dataset import Dataset
| 31
| 49
| 0.861751
| 27
| 217
| 6.814815
| 0.481481
| 0.119565
| 0.184783
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.110599
| 217
| 6
| 50
| 36.166667
| 0.953368
| 0
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| true
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| null | 0
| 1
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| 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
| 6
|
c666daffd43ef9c3bc1095b037b46089eb1d680c
| 39
|
py
|
Python
|
uncluster/cluster_massloss/__init__.py
|
adrn/uncluster
|
0e487f7cc17426bbd03ff1f02000bc3437075ab3
|
[
"MIT"
] | null | null | null |
uncluster/cluster_massloss/__init__.py
|
adrn/uncluster
|
0e487f7cc17426bbd03ff1f02000bc3437075ab3
|
[
"MIT"
] | 1
|
2017-01-23T14:54:41.000Z
|
2017-01-23T14:54:41.000Z
|
uncluster/cluster_massloss/__init__.py
|
adrn/uncluster
|
0e487f7cc17426bbd03ff1f02000bc3437075ab3
|
[
"MIT"
] | null | null | null |
from .core import solve_mass_evolution
| 19.5
| 38
| 0.871795
| 6
| 39
| 5.333333
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.102564
| 39
| 1
| 39
| 39
| 0.914286
| 0
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| 0
| null | 0
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| 1
| 0
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| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 6
|
c6a591b2def0395c93fcf55d039ee081e5f9b406
| 33
|
py
|
Python
|
farm_management/animals/permissions/__init__.py
|
alexanders0/farm-management
|
53ed821bbbed312848cf331f8f961ef16c59fb99
|
[
"MIT"
] | 1
|
2021-07-11T23:26:10.000Z
|
2021-07-11T23:26:10.000Z
|
farm_management/animals/permissions/__init__.py
|
alexanders0/farm-management
|
53ed821bbbed312848cf331f8f961ef16c59fb99
|
[
"MIT"
] | 1
|
2021-07-13T02:09:37.000Z
|
2021-07-17T09:30:15.000Z
|
farm_management/animals/permissions/__init__.py
|
alexanders0/farm-management
|
53ed821bbbed312848cf331f8f961ef16c59fb99
|
[
"MIT"
] | null | null | null |
from .animals import IsLandOwner
| 16.5
| 32
| 0.848485
| 4
| 33
| 7
| 1
| 0
| 0
| 0
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| 0
| 0
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| 0.121212
| 33
| 1
| 33
| 33
| 0.965517
| 0
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| null | 0
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| null | 0
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| 0
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| 1
| 0
| 1
| 0
|
0
| 6
|
c6c938b1ee0b1d9f8942af40f6539d38b5459eca
| 19,112
|
py
|
Python
|
pytests/tuqquery/tuq_window_clause.py
|
sumedhpb/testrunner
|
9ff887231c75571624abc31a3fb5248110e01203
|
[
"Apache-2.0"
] | 14
|
2015-02-06T02:47:57.000Z
|
2020-03-14T15:06:05.000Z
|
pytests/tuqquery/tuq_window_clause.py
|
sumedhpb/testrunner
|
9ff887231c75571624abc31a3fb5248110e01203
|
[
"Apache-2.0"
] | 3
|
2019-02-27T19:29:11.000Z
|
2021-06-02T02:14:27.000Z
|
pytests/tuqquery/tuq_window_clause.py
|
sumedhpb/testrunner
|
9ff887231c75571624abc31a3fb5248110e01203
|
[
"Apache-2.0"
] | 108
|
2015-03-26T08:58:49.000Z
|
2022-03-21T05:21:39.000Z
|
from remote.remote_util import RemoteMachineShellConnection
from .tuq import QueryTests
import time
from deepdiff import DeepDiff
from membase.api.exception import CBQError
class QueryWindowClauseTests(QueryTests):
def setUp(self):
super(QueryWindowClauseTests, self).setUp()
self.log.info("============== QueryWindowClauseTests setup has started ==============")
self.function_name = self.input.param("function_name", "CUME_DIST")
if self.load_sample:
self.rest.load_sample("travel-sample")
init_time = time.time()
while True:
next_time = time.time()
query_response = self.run_cbq_query("SELECT COUNT(*) FROM `" + self.bucket_name + "`")
self.log.info(f"{self.bucket_name}+ count: {query_response['results'][0]['$1']}")
if query_response['results'][0]['$1'] == 31591:
break
if next_time - init_time > 600:
break
time.sleep(2)
self.wait_for_all_indexes_online()
self.log.info("============== QueryWindowClauseTests setup has completed ==============")
self.log_config_info()
def suite_setUp(self):
super(QueryWindowClauseTests, self).suite_setUp()
self.log.info("============== QueryWindowClauseTests suite_setup has started ==============")
self.log.info("============== QueryWindowClauseTests suite_setup has completed ==============")
def tearDown(self):
self.log.info("============== QueryWindowClauseTests tearDown has started ==============")
travel_sample = self.get_bucket_from_name("travel-sample")
if travel_sample:
self.delete_bucket(travel_sample)
self.log.info("============== QueryWindowClauseTests tearDown has completed ==============")
super(QueryWindowClauseTests, self).tearDown()
def suite_tearDown(self):
self.log.info("============== QueryWindowClauseTests suite_tearDown has started ==============")
self.log.info("============== QueryWindowClauseTests suite_tearDown has completed ==============")
super(QueryWindowClauseTests, self).suite_tearDown()
def test_window_single(self):
window_clause_query = "SELECT d.id, d.destinationairport, \
AVG(d.distance) OVER ( window1 ) AS `rank` \
FROM `travel-sample` AS d WHERE d.type='route' \
WINDOW window1 AS (PARTITION BY d.destinationairport) \
ORDER BY 1 \
LIMIT 5"
window_query = "SELECT d.id, d.destinationairport, \
AVG(d.distance) OVER ( PARTITION BY d.destinationairport ) AS `rank` \
FROM `travel-sample` AS d WHERE d.type='route' \
ORDER BY 1 \
LIMIT 5"
window_clause_query_results = self.run_cbq_query(window_clause_query)
window_query_results = self.run_cbq_query(window_query)
self.assertEqual(window_clause_query_results['results'], window_query_results['results'])
def test_window_unused(self):
window_query = "SELECT d.id, d.destinationairport \
FROM `travel-sample` AS d WHERE d.type='route' \
WINDOW window1 AS (PARTITION BY d.destinationairport ORDER by d.distance) \
LIMIT 5"
self.run_cbq_query(window_query)
def test_window_multiple(self):
window_clause_query = "SELECT d.id, d.destinationairport, \
ROW_NUMBER() OVER ( w1 ) AS `row`, \
AVG(d.distance) OVER w1 AS `avg`, \
AVG(d.distance) OVER ( PARTITION BY d.destinationairport ORDER BY d.distance NULLS LAST ) AS `average`, \
LEAD(r.distance, 1, 'No next distance') OVER ( w3 ) AS `next-distance` \
FROM `travel-sample` AS d \
WHERE d.type='route' \
WINDOW w1 AS (PARTITION BY d.destinationairport ORDER BY d.distance NULLS LAST), \
w2 AS (PARTITION BY d.sourceairport ORDER BY d.distance), \
w3 AS (PARTITION BY r.airline ORDER BY r.distance NULLS LAST) \
ORDER BY 1 \
LIMIT 7"
window_query = "SELECT d.id, d.destinationairport, \
ROW_NUMBER() OVER ( PARTITION BY d.destinationairport ORDER BY d.distance NULLS LAST ) AS `row`, \
AVG(d.distance) OVER ( PARTITION BY d.destinationairport ORDER BY d.distance NULLS LAST ) AS `avg`, \
AVG(d.distance) OVER ( PARTITION BY d.destinationairport ORDER BY d.distance NULLS LAST ) AS `average`, \
LEAD(r.distance, 1, 'No next distance') OVER ( PARTITION BY r.airline ORDER BY r.distance NULLS LAST ) AS `next-distance` \
FROM `travel-sample` AS d \
WHERE d.type='route' \
ORDER BY 1 \
LIMIT 7"
window_clause_query_results = self.run_cbq_query(window_clause_query)
window_query_results = self.run_cbq_query(window_query)
self.assertEqual(window_clause_query_results['results'], window_query_results['results'])
def test_window_order(self):
window_clause_query = "SELECT d.id, d.destinationairport, \
CUME_DIST() OVER ( window1 ) AS `rank` \
FROM `travel-sample` AS d WHERE d.type='route' \
WINDOW window1 AS (PARTITION BY d.destinationairport ORDER by d.distance) \
ORDER BY 1 \
LIMIT 5"
window_query = "SELECT d.id, d.destinationairport, \
CUME_DIST() OVER ( PARTITION BY d.destinationairport ORDER by d.distance ) AS `rank` \
FROM `travel-sample` AS d WHERE d.type='route' \
ORDER BY 1 \
LIMIT 5"
window_clause_query_results = self.run_cbq_query(window_clause_query)
window_query_results = self.run_cbq_query(window_query)
self.assertEqual(window_clause_query_results['results'], window_query_results['results'])
def test_window_name_order(self):
window_clause_query = "SELECT d.id, d.destinationairport, \
CUME_DIST() OVER ( window1 ORDER by d.distance ) AS `rank` \
FROM `travel-sample` AS d WHERE d.type='route' \
WINDOW window1 AS (PARTITION BY d.destinationairport) \
ORDER BY 1 \
LIMIT 5"
window_query = "SELECT d.id, d.destinationairport, \
CUME_DIST() OVER ( PARTITION BY d.destinationairport ORDER by d.distance ) AS `rank` \
FROM `travel-sample` AS d WHERE d.type='route' \
ORDER BY 1 \
LIMIT 5"
window_clause_query_results = self.run_cbq_query(window_clause_query)
window_query_results = self.run_cbq_query(window_query)
self.assertEqual(window_clause_query_results['results'], window_query_results['results'])
def test_window_name_frame(self):
window_clause_query = "SELECT r.sourceairport, r.destinationairport, r.distance, \
NTH_VALUE(r.distance, 2) FROM FIRST OVER ( \
window1 \
ROWS BETWEEN UNBOUNDED PRECEDING AND UNBOUNDED FOLLOWING \
) AS `shortest_distance_but_1` \
FROM `travel-sample` AS r \
WHERE r.type='route' \
WINDOW window1 AS ( PARTITION BY r.sourceairport ORDER BY r.distance) \
ORDER BY 1 \
LIMIT 7"
window_query = "SELECT r.sourceairport, r.destinationairport, r.distance, \
NTH_VALUE(r.distance, 2) FROM FIRST OVER ( \
PARTITION BY r.sourceairport \
ORDER BY r.distance \
ROWS BETWEEN UNBOUNDED PRECEDING AND UNBOUNDED FOLLOWING \
) AS `shortest_distance_but_1` \
FROM `travel-sample` AS r \
WHERE r.type='route' \
ORDER BY 1 \
LIMIT 7"
window_clause_query_results = self.run_cbq_query(window_clause_query)
window_query_results = self.run_cbq_query(window_query)
self.assertEqual(window_clause_query_results['results'], window_query_results['results'])
def test_window_name_order_frame(self):
window_clause_query = "SELECT r.sourceairport, r.destinationairport, r.distance, \
NTH_VALUE(r.distance, 2) FROM FIRST OVER ( \
window1 \
ORDER BY r.distance \
ROWS BETWEEN UNBOUNDED PRECEDING AND UNBOUNDED FOLLOWING \
) AS `shortest_distance_but_1` \
FROM `travel-sample` AS r \
WHERE r.type='route' \
WINDOW window1 AS ( PARTITION BY r.sourceairport ) \
ORDER BY 1 \
LIMIT 7"
window_query = "SELECT r.sourceairport, r.destinationairport, r.distance, \
NTH_VALUE(r.distance, 2) FROM FIRST OVER ( \
PARTITION BY r.sourceairport \
ORDER BY r.distance \
ROWS BETWEEN UNBOUNDED PRECEDING AND UNBOUNDED FOLLOWING \
) AS `shortest_distance_but_1` \
FROM `travel-sample` AS r \
WHERE r.type='route' \
ORDER BY 1 \
LIMIT 7"
window_clause_query_results = self.run_cbq_query(window_clause_query)
window_query_results = self.run_cbq_query(window_query)
self.assertEqual(window_clause_query_results['results'], window_query_results['results'])
def test_window_no_parenthesis(self):
window_clause_query = "SELECT d.id, d.destinationairport, \
CUME_DIST() OVER window_name_with_no_parenthesis AS `rank` \
FROM `travel-sample` AS d WHERE d.type='route' \
WINDOW window_name_with_no_parenthesis AS (PARTITION BY d.destinationairport ORDER by d.distance) \
ORDER BY 1 \
LIMIT 5"
window_query = "SELECT d.id, d.destinationairport, \
CUME_DIST() OVER ( PARTITION BY d.destinationairport ORDER by d.distance ) AS `rank` \
FROM `travel-sample` AS d WHERE d.type='route' \
ORDER BY 1 \
LIMIT 5"
window_clause_query_results = self.run_cbq_query(window_clause_query)
window_query_results = self.run_cbq_query(window_query)
self.assertEqual(window_clause_query_results['results'], window_query_results['results'])
def test_window_name_function(self):
window_function = {
'CUME_DIST': {
'arg':'', 'select_list': 'd.id, d.destinationairport',
'wdef': 'PARTITION BY d.destinationairport ORDER BY d.distance NULLS LAST', 'frame_clause': '',
'from_where': '`travel-sample` AS d WHERE d.type=\'route\''
},
'DENSE_RANK': {
'arg':'', 'select_list': 'a.airportname, a.geo.alt',
'wdef': 'PARTITION BY a.country ORDER BY a.geo.alt NULLS LAST', 'frame_clause': '',
'from_where': '`travel-sample` AS a WHERE a.type=\'airport\''
},
'FIRST_VALUE': {
'arg':'r.distance', 'select_list': 'r.sourceairport, r.destinationairport, r.distance',
'wdef': 'PARTITION BY r.sourceairport ORDER BY r.distance', 'frame_clause': '',
'from_where': '`travel-sample` AS r WHERE r.type=\'route\''
},
'LAG': {
'arg':'r.distance, 1, "No previous distance"', 'select_list': 'r.airline, r.id, r.distance',
'wdef': 'PARTITION BY r.airline ORDER BY r.distance NULLS LAST', 'frame_clause': '',
'from_where': '`travel-sample` AS r WHERE r.type=\'route\''
},
'LAST_VALUE': {
'arg':'r.distance', 'select_list': 'r.sourceairport, r.destinationairport, r.distance',
'wdef': 'PARTITION BY r.sourceairport ORDER BY r.distance', 'frame_clause': 'ROWS BETWEEN UNBOUNDED PRECEDING AND UNBOUNDED FOLLOWING',
'from_where': '`travel-sample` AS r WHERE r.type=\'route\''
},
'LEAD': {
'arg': 'r.distance, 1, "No next distance"', 'select_list': 'r.airline, r.id, r.distance',
'wdef': 'PARTITION BY r.airline ORDER BY r.distance NULLS LAST', 'frame_clause': '',
'from_where': '`travel-sample` AS r WHERE r.type=\'route\''
},
'NTH_VALUE': {
'arg': 'r.distance, 2', 'select_list': 'r.sourceairport, r.destinationairport, r.distance',
'wdef': 'PARTITION BY r.sourceairport ORDER BY r.distance', 'frame_clause': 'ROWS BETWEEN UNBOUNDED PRECEDING AND UNBOUNDED FOLLOWING',
'from_where': '`travel-sample` AS r WHERE r.type=\'route\''
},
'NTILE': {
'arg': 3, 'select_list': 'r.airline, r.distance',
'wdef': 'PARTITION BY r.airline ORDER BY r.distance', 'frame_clause': '',
'from_where': '`travel-sample` AS r WHERE r.type=\'route\''
},
'PERCENT_RANK': {
'arg':'', 'select_list': 'd.id, d.destinationairport',
'wdef': 'PARTITION BY d.destinationairport ORDER BY d.distance NULLS LAST', 'frame_clause': '',
'from_where': '`travel-sample` AS d WHERE d.type=\'route\''
},
'RANK': {
'arg':'', 'select_list': 'a.airportname, a.geo.alt',
'wdef': 'PARTITION BY a.country ORDER BY a.geo.alt NULLS LAST', 'frame_clause': '',
'from_where': '`travel-sample` AS a WHERE a.type=\'airport\''
},
'RATIO_TO_REPORT': {
'arg':'d.distance', 'select_list': 'd.id, d.destinationairport',
'wdef': 'PARTITION BY d.destinationairport', 'frame_clause': '',
'from_where': '`travel-sample` AS d WHERE d.type=\'route\''
},
'ROW_NUMBER': {
'arg':'', 'select_list': 'd.id, d.destinationairport',
'wdef': 'PARTITION BY d.destinationairport ORDER BY d.distance NULLS LAST', 'frame_clause': '',
'from_where': '`travel-sample` AS d WHERE d.type=\'route\''
}
}
function = self.function_name
select_list = window_function[function]['select_list']
arg = window_function[function]['arg']
from_where = window_function[function]['from_where']
window_definition = window_function[function]['wdef']
frame_clause = window_function[function]['frame_clause']
# run query with window function
window_clause_query = f"SELECT {select_list}, {function}({arg}) OVER (window_name {frame_clause}) AS {function}_col FROM {from_where} WINDOW window_name AS ( {window_definition} ) LIMIT 7"
window_query = f"SELECT {select_list}, {function}({arg}) OVER ( {window_definition} {frame_clause}) AS {function}_col FROM {from_where} LIMIT 7"
window_clause_query_results = self.run_cbq_query(window_clause_query)
window_query_results = self.run_cbq_query(window_query)
self.assertEqual(window_clause_query_results['results'], window_query_results['results'])
def test_window_prepared(self):
prepare_window_query = "PREPARE window_query as SELECT d.id, d.destinationairport, CUME_DIST() OVER ( `Window-1` ) AS `rank` FROM `travel-sample` AS d WHERE d.type='route' WINDOW `Window-1` AS (PARTITION by d.destinationairport ORDER BY d.distance) limit 5"
self.run_cbq_query(prepare_window_query)
self.run_cbq_query(query="EXECUTE window_query")
def test_neg_non_unique(self):
error_code = 6500
error_message = "Duplicate window clause alias window1."
window_query = "SELECT d.id, d.destinationairport, \
CUME_DIST() OVER ( window1 ) AS `rank` \
FROM `travel-sample` AS d WHERE d.type='route' \
WINDOW window1 AS (PARTITION BY d.destinationairport ORDER by d.distance), \
window1 AS (PARTITION BY d.destinationairport)"
try:
self.run_cbq_query(window_query)
except CBQError as ex:
error = self.process_CBQE(ex)
self.assertEqual(error['code'], error_code)
self.assertEqual(error['msg'], error_message)
def test_neg_non_exists(self):
error_code = 6500
error_message = "Window window2 not in the scope of window clause"
window_query = "SELECT d.id, d.destinationairport, \
CUME_DIST() OVER ( window2 ) AS `rank` \
FROM `travel-sample` AS d WHERE d.type='route' \
WINDOW window1 AS (PARTITION BY d.destinationairport ORDER by d.distance)"
try:
self.run_cbq_query(window_query)
except CBQError as ex:
error = self.process_CBQE(ex)
self.assertEqual(error['code'], error_code)
self.assertEqual(error['msg'], error_message)
def test_neg_order(self):
error_code = 6500
error_message = "Window window1 shall not have a window ordering clause"
window_query = "SELECT d.id, d.destinationairport, \
CUME_DIST() OVER ( window1 ORDER BY d.distance NULLS LAST) AS `rank` \
FROM `travel-sample` AS d WHERE d.type='route' \
WINDOW window1 AS (PARTITION BY d.destinationairport ORDER by d.distance)"
try:
self.run_cbq_query(window_query)
except CBQError as ex:
error = self.process_CBQE(ex)
self.assertEqual(error['code'], error_code)
self.assertEqual(error['msg'], error_message)
def test_neg_frame(self):
error_code = 6500
error_message = "Window window1 shall not have a window framing clause"
window_query = "SELECT r.sourceairport, r.destinationairport, r.distance, \
LAST_VALUE(r.distance) OVER (window1) AS `longest_distance` \
FROM `travel-sample` AS r \
WHERE r.type='route' \
WINDOW window1 AS (PARTITION BY r.sourceairport ORDER BY r.distance ROWS BETWEEN UNBOUNDED PRECEDING AND UNBOUNDED FOLLOWING)"
try:
self.run_cbq_query(window_query)
except CBQError as ex:
error = self.process_CBQE(ex)
self.assertEqual(error['code'], error_code)
self.assertEqual(error['msg'], error_message)
def test_neg_partition(self):
error_code = 6500
error_message = "Window window1 shall not have a window partitioning clause"
window_query = "SELECT d.id, d.destinationairport, \
CUME_DIST() OVER ( window1 PARTITION BY d.destinationairport) AS `rank` \
FROM `travel-sample` AS d WHERE d.type='route' \
WINDOW window1 AS (PARTITION BY d.destinationairport ORDER by d.distance)"
try:
self.run_cbq_query(window_query)
except CBQError as ex:
error = self.process_CBQE(ex)
self.assertEqual(error['code'], error_code)
self.assertEqual(error['msg'], error_message)
| 54.605714
| 265
| 0.601612
| 2,243
| 19,112
| 4.945609
| 0.0749
| 0.032182
| 0.041648
| 0.033805
| 0.861084
| 0.845037
| 0.805823
| 0.779951
| 0.771478
| 0.742721
| 0
| 0.008333
| 0.284219
| 19,112
| 349
| 266
| 54.762178
| 0.802558
| 0.00157
| 0
| 0.609231
| 0
| 0.030769
| 0.214256
| 0.015514
| 0
| 0
| 0
| 0
| 0.055385
| 1
| 0.058462
| false
| 0
| 0.015385
| 0
| 0.076923
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 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
| 6
|
c6cbd8436b384ec3d158da183103663cb14287f0
| 72
|
py
|
Python
|
deepchem/models/jax_models/__init__.py
|
medjebbar/deepchem
|
d636878164abb0562e3f5a9f2f187d3b5a5a097b
|
[
"MIT"
] | 1
|
2021-05-27T13:14:48.000Z
|
2021-05-27T13:14:48.000Z
|
deepchem/models/jax_models/__init__.py
|
medjebbar/deepchem
|
d636878164abb0562e3f5a9f2f187d3b5a5a097b
|
[
"MIT"
] | null | null | null |
deepchem/models/jax_models/__init__.py
|
medjebbar/deepchem
|
d636878164abb0562e3f5a9f2f187d3b5a5a097b
|
[
"MIT"
] | 1
|
2021-09-07T06:48:35.000Z
|
2021-09-07T06:48:35.000Z
|
# flake8:noqa
from deepchem.models.jax_models.jax_model import JaxModel
| 24
| 57
| 0.847222
| 11
| 72
| 5.363636
| 0.818182
| 0.305085
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.015152
| 0.083333
| 72
| 2
| 58
| 36
| 0.878788
| 0.152778
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 6
|
c6f1ad51008a97a4ead3fdcfa20b665a1daa48ba
| 97
|
py
|
Python
|
ifttt_sim/__init__.py
|
UT-MPC/ConflictDetection
|
f960a349e32ff861932fbc331daf6cd40369617f
|
[
"BSD-3-Clause"
] | null | null | null |
ifttt_sim/__init__.py
|
UT-MPC/ConflictDetection
|
f960a349e32ff861932fbc331daf6cd40369617f
|
[
"BSD-3-Clause"
] | null | null | null |
ifttt_sim/__init__.py
|
UT-MPC/ConflictDetection
|
f960a349e32ff861932fbc331daf6cd40369617f
|
[
"BSD-3-Clause"
] | null | null | null |
from .Applet import *
from .Trigger import *
from .Action import *
from .ContextInterval import *
| 24.25
| 30
| 0.762887
| 12
| 97
| 6.166667
| 0.5
| 0.405405
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.154639
| 97
| 4
| 30
| 24.25
| 0.902439
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 6
|
05a1bb56b3e981f9e800f99e0670a3dde2417874
| 50
|
py
|
Python
|
lesson1/sys.py
|
rnavarych/python_lessons
|
259630e43fce84247f80d4e163e7d7c90d104112
|
[
"MIT"
] | null | null | null |
lesson1/sys.py
|
rnavarych/python_lessons
|
259630e43fce84247f80d4e163e7d7c90d104112
|
[
"MIT"
] | null | null | null |
lesson1/sys.py
|
rnavarych/python_lessons
|
259630e43fce84247f80d4e163e7d7c90d104112
|
[
"MIT"
] | null | null | null |
import sys
print(sys.platform)
print(sys.version)
| 12.5
| 19
| 0.8
| 8
| 50
| 5
| 0.625
| 0.4
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.08
| 50
| 4
| 20
| 12.5
| 0.869565
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.333333
| 0
| 0.333333
| 0.666667
| 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
| 1
|
0
| 6
|
af0c75da8009bb928daef94d9d40029357b8611b
| 6,522
|
py
|
Python
|
lighthouse/tests/test_lighthouse.py
|
chrroberts-pure/integrations-extras
|
d2ff09d5cdc50ad1d2a826ea5404cddca0198afa
|
[
"BSD-3-Clause"
] | null | null | null |
lighthouse/tests/test_lighthouse.py
|
chrroberts-pure/integrations-extras
|
d2ff09d5cdc50ad1d2a826ea5404cddca0198afa
|
[
"BSD-3-Clause"
] | null | null | null |
lighthouse/tests/test_lighthouse.py
|
chrroberts-pure/integrations-extras
|
d2ff09d5cdc50ad1d2a826ea5404cddca0198afa
|
[
"BSD-3-Clause"
] | null | null | null |
import os
import pytest
from mock import MagicMock
from datadog_checks.base.errors import CheckException
from datadog_checks.lighthouse import LighthouseCheck
HERE = os.path.dirname(os.path.abspath(__file__))
def mock_get_lighthouse_report(cmd, lgr, re=False):
if "https" not in cmd[1]:
return "", "error", 1
elif "404" in cmd[1]:
with open(os.path.join(HERE, 'lighthouse_example_invalid_response.json'), 'r') as f:
return f.read(), "", 0
else:
# example lighthouse report json for https://docs.datadoghq.com
with open(os.path.join(HERE, 'lighthouse_example_valid_response.json'), 'r') as f:
return f.read(), "", 0
@pytest.mark.integration
def test_check(aggregator, instance):
instance = {'url': 'https://www.google.com', 'name': 'google'}
lighthouse_check = LighthouseCheck('lighthouse', {}, {})
LighthouseCheck._get_lighthouse_report = MagicMock(side_effect=mock_get_lighthouse_report)
lighthouse_check.check(instance)
tags = []
tags.append("url:{0}".format(instance["url"]))
tags.append("name:{0}".format(instance["name"]))
aggregator.assert_metric(name="lighthouse.accessibility", value=92, tags=tags)
aggregator.assert_metric(name="lighthouse.best_practices", value=100, tags=tags)
aggregator.assert_metric(name="lighthouse.performance", value=55, tags=tags)
aggregator.assert_metric(name="lighthouse.pwa", value=30, tags=tags)
aggregator.assert_metric(name="lighthouse.seo", value=89, tags=tags)
aggregator.assert_metric(name="lighthouse.bootup_time", value=2198, tags=tags)
aggregator.assert_metric(name="lighthouse.cumulative_layout_shift", value=0.01, tags=tags)
aggregator.assert_metric(name="lighthouse.dom_size", value=2721, tags=tags)
aggregator.assert_metric(name="lighthouse.first_contentful_paint", value=2154, tags=tags)
aggregator.assert_metric(name="lighthouse.largest_contentful_paint", value=3910, tags=tags)
aggregator.assert_metric(name="lighthouse.mainthread_work_breakdown", value=3568, tags=tags)
aggregator.assert_metric(name="lighthouse.max_potential_fid", value=208, tags=tags)
aggregator.assert_metric(name="lighthouse.modern_image_formats", value=0, tags=tags)
aggregator.assert_metric(name="lighthouse.render_blocking_resources", value=890, tags=tags)
aggregator.assert_metric(name="lighthouse.server_response_time", value=276, tags=tags)
aggregator.assert_metric(name="lighthouse.speed_index", value=4442, tags=tags)
aggregator.assert_metric(name="lighthouse.time_to_interactive", value=10632.5, tags=tags)
aggregator.assert_metric(name="lighthouse.total_blocking_time", value=926, tags=tags)
aggregator.assert_metric(name="lighthouse.unused_css_rules", value=530, tags=tags)
aggregator.assert_metric(name="lighthouse.unused_javascript", value=1200, tags=tags)
aggregator.assert_metric(name="lighthouse.uses_optimized_images", value=0, tags=tags)
aggregator.assert_all_metrics_covered()
@pytest.mark.integration
def test_missing_url_instance_check(aggregator, instance):
# incomplete instance in yaml missing url
incomplete_instance = {'name': 'datadoghq'}
lighthouse_check = LighthouseCheck('lighthouse', {}, {})
LighthouseCheck._get_lighthouse_report = MagicMock(side_effect=mock_get_lighthouse_report)
with pytest.raises(CheckException):
lighthouse_check.check(incomplete_instance)
@pytest.mark.integration
def test_missing_name_instance_check(aggregator, instance):
# incomplete instance in yaml missing name
incomplete_instance = {'url': 'https://www.datadoghq.com'}
lighthouse_check = LighthouseCheck('lighthouse', {}, {})
LighthouseCheck._get_lighthouse_report = MagicMock(side_effect=mock_get_lighthouse_report)
with pytest.raises(CheckException):
lighthouse_check.check(incomplete_instance)
def test_malformed_url_instance_check(aggregator, instance):
# example malformed url
malformed_instance = {'url': 'htp://www.datadoghq.comz', 'name': 'malformed_url'}
lighthouse_check = LighthouseCheck('lighthouse', {}, {})
LighthouseCheck._get_lighthouse_report = MagicMock(side_effect=mock_get_lighthouse_report)
with pytest.raises(CheckException):
lighthouse_check.check(malformed_instance)
def test_invalid_response_check(aggregator, instance):
# an example 404 response, will skip check but not throw error
instance = {'url': 'https://httpstat.us/404', 'name': '404 response'}
lighthouse_check = LighthouseCheck('lighthouse', {}, {})
LighthouseCheck._get_lighthouse_report = MagicMock(side_effect=mock_get_lighthouse_report)
lighthouse_check.check(instance)
aggregator.assert_metric(name="lighthouse.accessibility", count=0, at_least=0)
aggregator.assert_metric(name="lighthouse.best_practices", count=0, at_least=0)
aggregator.assert_metric(name="lighthouse.performance", count=0, at_least=0)
aggregator.assert_metric(name="lighthouse.pwa", count=0, at_least=0)
aggregator.assert_metric(name="lighthouse.seo", count=0, at_least=0)
aggregator.assert_metric(name="lighthouse.bootup_time", count=0, at_least=0)
aggregator.assert_metric(name="lighthouse.cumulative_layout_shift", count=0, at_least=0)
aggregator.assert_metric(name="lighthouse.dom_size", count=0, at_least=0)
aggregator.assert_metric(name="lighthouse.first_contentful_paint", count=0, at_least=0)
aggregator.assert_metric(name="lighthouse.largest_contentful_paint", count=0, at_least=0)
aggregator.assert_metric(name="lighthouse.mainthread_work_breakdown", count=0, at_least=0)
aggregator.assert_metric(name="lighthouse.max_potential_fid", count=0, at_least=0)
aggregator.assert_metric(name="lighthouse.modern_image_formats", count=0, at_least=0)
aggregator.assert_metric(name="lighthouse.render_blocking_resources", count=0, at_least=0)
aggregator.assert_metric(name="lighthouse.server_response_time", count=0, at_least=0)
aggregator.assert_metric(name="lighthouse.speed_index", count=0, at_least=0)
aggregator.assert_metric(name="lighthouse.time_to_interactive", count=0, at_least=0)
aggregator.assert_metric(name="lighthouse.total_blocking_time", count=0, at_least=0)
aggregator.assert_metric(name="lighthouse.unused_css_rules", count=0, at_least=0)
aggregator.assert_metric(name="lighthouse.unused_javascript", count=0, at_least=0)
aggregator.assert_metric(name="lighthouse.uses_optimized_images", count=0, at_least=0)
| 53.02439
| 96
| 0.766789
| 838
| 6,522
| 5.720764
| 0.181384
| 0.143513
| 0.192741
| 0.227785
| 0.801627
| 0.785148
| 0.735503
| 0.632874
| 0.428869
| 0.391322
| 0
| 0.021713
| 0.110242
| 6,522
| 122
| 97
| 53.459016
| 0.804412
| 0.034499
| 0
| 0.23913
| 0
| 0
| 0.234144
| 0.183437
| 0
| 0
| 0
| 0
| 0.467391
| 1
| 0.065217
| false
| 0
| 0.054348
| 0
| 0.152174
| 0
| 0
| 0
| 0
| null | 0
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 6
|
af309b4b340361420525be544e964ea428f9fb64
| 42
|
py
|
Python
|
libs/detection/__init__.py
|
tamnguyenvan/mobilenetv3-face-gender
|
b8a6587a06f06f0fc01c5b8627d4a76361176608
|
[
"Apache-2.0"
] | null | null | null |
libs/detection/__init__.py
|
tamnguyenvan/mobilenetv3-face-gender
|
b8a6587a06f06f0fc01c5b8627d4a76361176608
|
[
"Apache-2.0"
] | null | null | null |
libs/detection/__init__.py
|
tamnguyenvan/mobilenetv3-face-gender
|
b8a6587a06f06f0fc01c5b8627d4a76361176608
|
[
"Apache-2.0"
] | null | null | null |
from .ssd import *
from .ssdlite import *
| 14
| 22
| 0.714286
| 6
| 42
| 5
| 0.666667
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.190476
| 42
| 2
| 23
| 21
| 0.882353
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
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| 1
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| 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
| 1
| 0
|
0
| 6
|
af3611ccf6c7a2fcef996e1ac3dce81ddb3c52cf
| 26
|
py
|
Python
|
extraction/models/__init__.py
|
nutalk/Gabor-Filter
|
f1ffb6efbda66645e704160d49ea5b32afb5f70b
|
[
"Apache-2.0"
] | null | null | null |
extraction/models/__init__.py
|
nutalk/Gabor-Filter
|
f1ffb6efbda66645e704160d49ea5b32afb5f70b
|
[
"Apache-2.0"
] | null | null | null |
extraction/models/__init__.py
|
nutalk/Gabor-Filter
|
f1ffb6efbda66645e704160d49ea5b32afb5f70b
|
[
"Apache-2.0"
] | null | null | null |
from .fcn32s import FCN32
| 13
| 25
| 0.807692
| 4
| 26
| 5.25
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.181818
| 0.153846
| 26
| 1
| 26
| 26
| 0.772727
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
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| 0
| 1
| 0
| true
| 0
| 1
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| 1
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| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
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| 0
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| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 6
|
af7215aa7ec35176b8d27add9f0093b8e4667312
| 38
|
py
|
Python
|
sequential_inference/envs/robosuite_envs/wipe/__init__.py
|
cvoelcker/sequential_inference
|
acdc23aa8fdbfc76ded771e82a4abcdd081a3280
|
[
"MIT"
] | null | null | null |
sequential_inference/envs/robosuite_envs/wipe/__init__.py
|
cvoelcker/sequential_inference
|
acdc23aa8fdbfc76ded771e82a4abcdd081a3280
|
[
"MIT"
] | null | null | null |
sequential_inference/envs/robosuite_envs/wipe/__init__.py
|
cvoelcker/sequential_inference
|
acdc23aa8fdbfc76ded771e82a4abcdd081a3280
|
[
"MIT"
] | null | null | null |
from .wipe_located import WipeLocated
| 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
| 1
| 0
|
0
| 6
|
afaabf96859e9621a4cf9f1e9db0d85461936e7a
| 16
|
py
|
Python
|
python/testData/psi/EmptySuperclassList.py
|
jnthn/intellij-community
|
8fa7c8a3ace62400c838e0d5926a7be106aa8557
|
[
"Apache-2.0"
] | 2
|
2019-04-28T07:48:50.000Z
|
2020-12-11T14:18:08.000Z
|
python/testData/psi/EmptySuperclassList.py
|
jnthn/intellij-community
|
8fa7c8a3ace62400c838e0d5926a7be106aa8557
|
[
"Apache-2.0"
] | 173
|
2018-07-05T13:59:39.000Z
|
2018-08-09T01:12:03.000Z
|
python/testData/psi/EmptySuperclassList.py
|
jnthn/intellij-community
|
8fa7c8a3ace62400c838e0d5926a7be106aa8557
|
[
"Apache-2.0"
] | 2
|
2020-03-15T08:57:37.000Z
|
2020-04-07T04:48:14.000Z
|
class A(): pass
| 8
| 15
| 0.625
| 3
| 16
| 3.333333
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.1875
| 16
| 1
| 16
| 16
| 0.769231
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 1
| 0
| 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
| 1
| 0
| 0
| 1
| 0
|
0
| 6
|
bb5e1517281a77730d997e30a32ec3170c9d93c2
| 9,878
|
py
|
Python
|
build_arrays.py
|
lauziere/exacthgm
|
55d4d7808856b1945c9c9aed3493ae66166aea11
|
[
"MIT"
] | null | null | null |
build_arrays.py
|
lauziere/exacthgm
|
55d4d7808856b1945c9c9aed3493ae66166aea11
|
[
"MIT"
] | null | null | null |
build_arrays.py
|
lauziere/exacthgm
|
55d4d7808856b1945c9c9aed3493ae66166aea11
|
[
"MIT"
] | null | null | null |
import numpy as np
import pandas as pd
import os
from features import *
from util import *
# Handle datasets
def merge_data(key_list, array_list):
all_keys = np.array([kl[i] for kl in key_list for i in range(len(kl))])
all_keys_idxs = np.argsort(all_keys)
all_keys_sorted = np.sort(all_keys)
all_arrays = np.array([al[i] for al in array_list for i in range(len(al))])
all_arrays_shape = all_arrays.shape
n = len(all_arrays)
sorted_arrays = np.empty(all_arrays_shape)
for j in all_keys_idxs:
this_idx = all_keys_idxs[j]
sorted_arrays[j] = all_arrays[this_idx]
return all_keys_sorted, sorted_arrays
def merge_data_LOO(key_list, array_list):
num_sets = len(key_list)
key_list_LOO = []
array_list_LOO = []
for i in range(num_sets):
remaining_keys = [key_list[j] for j in range(num_sets) if j!=i]
remaining_arrays = [array_list[j] for j in range(num_sets) if j!=i]
a,b = merge_data(remaining_keys, remaining_arrays)
key_list_LOO.append(a)
array_list_LOO.append(b)
return key_list_LOO, array_list_LOO
if __name__ == '__main__':
# base_dir = os.path.abspath('.')
base_dir = '/data/lauzierean/Untwisting'
home = os.path.join(base_dir, 'exacthgm')
data_dir = os.path.join(home, 'Data')
resources = os.path.join(home, 'Resources')
resources_QAP = os.path.join(resources,'QAP')
resources_Pairs = os.path.join(resources,'Pairs')
resources_Full = os.path.join(resources,'Full')
# twitches = [5, 8, 23] + [11, 52, 50] + [15, 12, 11] + [37] + [9, 15, 13] + [1, 4, 1]
# hatches = [85, 106, 136] + [102, 138, 140] + [104, 101, 126] + [114] + [93, 96, 93] + [86, 95, 95]
# twitches = np.array(twitches)
# hatches = np.array(hatches)
# twitch_hatch = np.vstack([twitches, hatches])
# out_path_twitch_hatch = os.path.join(resources, 'twitch_hatch.npy')
# np.save(out_path_twitch_hatch, twitch_hatch)
step = .05
# First do the n=20 nuclei case:
num_cells = 20
num_pairs = int(num_cells/2)
tl = [(i,i+1) for i in range(0,num_cells,2)][::-1]
key_list = np.load(os.path.join(data_dir, 'keys_20.npy'), allow_pickle=True)
array_list = np.load(os.path.join(data_dir, 'arrays_20.npy'), allow_pickle=True)
# Get LOO arrays to get statistics
keys_LOO, arrays_LOO = merge_data_LOO(key_list, array_list)
# QAP
widths = get_pair_arrays(keys_LOO, arrays_LOO)
widths_pairs = [a[:,1:] for a in widths]
side_lens = get_side_lens(keys_LOO, arrays_LOO)
left_sides, right_sides = side_lens
feature_list_widths = [widths]
means_widths, sigma_invs_widths = get_doubles_statistics_QAP(keys_LOO, feature_list_widths, step)
feature_list_pairs = [widths_pairs, left_sides, right_sides]
means_pairs, sigma_invs_pairs = get_doubles_statistics_QAP(keys_LOO, feature_list_pairs, step)
op_means_widths = os.path.join(resources_QAP, 'means_widths.npy')
op_sigma_invs_widths = os.path.join(resources_QAP, 'sigma_invs_widths.npy')
op_means_pairs = os.path.join(resources_QAP, 'means_pairs.npy')
op_sigma_invs_pairs = os.path.join(resources_QAP, 'sigma_invs_pairs.npy')
np.save(op_means_widths, means_widths)
np.save(op_sigma_invs_widths, sigma_invs_widths)
np.save(op_means_pairs, means_pairs)
np.save(op_sigma_invs_pairs, sigma_invs_pairs)
# Pairs
# Degree 4 features:
pair_dist_ratios = get_pair_ratio_arrays(keys_LOO, arrays_LOO)
pair_dist_ratios = [a[:,1:] for a in pair_dist_ratios]
cos_sims = get_cos_sims(keys_LOO, arrays_LOO)
lateral_axial_twists = get_lateral_axial_twists(keys_LOO, arrays_LOO)
axial_twists = get_axial_twists(keys_LOO, arrays_LOO)
feature_list_pairs = [cos_sims, lateral_axial_twists, axial_twists]
means_pairs, sigma_invs_pairs = get_doubles_statistics(keys_LOO, feature_list_pairs, step)
# Degree 6 features:
midpoints, midpoint_distances, bend_angles, bend_angle_sums = get_bend_angles(keys_LOO, arrays_LOO)
midpoint_distances = [a[:,1:] for a in midpoint_distances]
plane_angles = get_plane_intersection_angles(keys_LOO, arrays_LOO)
feature_list_triples = [pair_dist_ratios, midpoint_distances, bend_angles, plane_angles]
means_triples, sigma_invs_triples = get_doubles_statistics(keys_LOO, feature_list_triples, step)
op_means_pairs = os.path.join(resources_Pairs, 'means_pairs.npy')
op_sigma_invs_pairs = os.path.join(resources_Pairs, 'sigma_invs_pairs.npy')
op_means_triples = os.path.join(resources_Pairs, 'means_triples.npy')
op_sigma_invs_triples = os.path.join(resources_Pairs, 'sigma_invs_triples.npy')
np.save(op_means_pairs, means_pairs)
np.save(op_sigma_invs_pairs, sigma_invs_pairs)
np.save(op_means_triples, means_triples)
np.save(op_sigma_invs_triples, sigma_invs_triples)
# Full
means_partial_sequence, sigma_invs_partial_sequence = get_partial_sequence_statistics(keys_LOO, feature_list_pairs, feature_list_triples, step, num_pairs)
mean_cost_estimates, sigma_inv_cost_estimates = get_sequence_cost_estimate_statistics(key_list, array_list, step, means_partial_sequence, sigma_invs_partial_sequence, tl)
op_means_seq = os.path.join(resources_Full, 'means_sequence.npy')
op_sigma_invs_seq = os.path.join(resources_Full, 'sigma_invs_sequence.npy')
op_mean_cost_estimates = os.path.join(resources_Full, 'mean_cost_estimates.npy')
op_sigma_cost_estimates = os.path.join(resources_Full, 'sigma_inv_cost_estimates.npy')
np.save(op_means_seq, means_partial_sequence)
np.save(op_sigma_invs_seq, sigma_invs_partial_sequence)
np.save(op_mean_cost_estimates, mean_cost_estimates)
np.save(op_sigma_cost_estimates, sigma_inv_cost_estimates)
# Now 22 cell case:
num_cells = 22
num_pairs = int(num_cells/2)
tl = [(i,i+1) for i in range(0,num_cells,2)][::-1]
key_list = np.load(os.path.join(data_dir, 'keys_22.npy'), allow_pickle=True)
array_list = np.load(os.path.join(data_dir, 'arrays_22.npy'), allow_pickle=True)
# Get LOO arrays to get statistics
keys_LOO, arrays_LOO = merge_data_LOO(key_list, array_list)
# QAP
widths = get_pair_arrays(keys_LOO, arrays_LOO)
widths_pairs = [a[:,1:] for a in widths]
side_lens = get_side_lens(keys_LOO, arrays_LOO)
left_sides, right_sides = side_lens
feature_list_widths = [widths]
means_widths, sigma_invs_widths = get_doubles_statistics_QAP(keys_LOO, feature_list_widths, step)
feature_list_pairs = [widths_pairs, left_sides, right_sides]
means_pairs, sigma_invs_pairs = get_doubles_statistics_QAP(keys_LOO, feature_list_pairs, step)
op_means_widths = os.path.join(resources_QAP, 'means_widths_Q.npy')
op_sigma_invs_widths = os.path.join(resources_QAP, 'sigma_invs_widths_Q.npy')
op_means_pairs = os.path.join(resources_QAP, 'means_pairs_Q.npy')
op_sigma_invs_pairs = os.path.join(resources_QAP, 'sigma_invs_pairs_Q.npy')
np.save(op_means_widths, means_widths)
np.save(op_sigma_invs_widths, sigma_invs_widths)
np.save(op_means_pairs, means_pairs)
np.save(op_sigma_invs_pairs, sigma_invs_pairs)
# Pairs
# Degree 4 features:
pair_dist_ratios = get_pair_ratio_arrays(keys_LOO, arrays_LOO)
pair_dist_ratios = [a[:,1:] for a in pair_dist_ratios]
cos_sims = get_cos_sims(keys_LOO, arrays_LOO)
lateral_axial_twists = get_lateral_axial_twists(keys_LOO, arrays_LOO)
axial_twists = get_axial_twists(keys_LOO, arrays_LOO)
feature_list_pairs = [cos_sims, lateral_axial_twists, axial_twists]
means_pairs, sigma_invs_pairs = get_doubles_statistics(keys_LOO, feature_list_pairs, step)
# Degree 6 features:
midpoints, midpoint_distances, bend_angles, bend_angle_sums = get_bend_angles(keys_LOO, arrays_LOO)
midpoint_distances = [a[:,1:] for a in midpoint_distances]
plane_angles = get_plane_intersection_angles(keys_LOO, arrays_LOO)
feature_list_triples = [pair_dist_ratios, midpoint_distances, bend_angles, plane_angles]
means_triples, sigma_invs_triples = get_doubles_statistics(keys_LOO, feature_list_triples, step)
op_means_pairs = os.path.join(resources_Pairs, 'means_pairs_Q.npy')
op_sigma_invs_pairs = os.path.join(resources_Pairs, 'sigma_invs_pairs_Q.npy')
op_means_triples = os.path.join(resources_Pairs, 'means_triples_Q.npy')
op_sigma_invs_triples = os.path.join(resources_Pairs, 'sigma_invs_triples_Q.npy')
np.save(op_means_pairs, means_pairs)
np.save(op_sigma_invs_pairs, sigma_invs_pairs)
np.save(op_means_triples, means_triples)
np.save(op_sigma_invs_triples, sigma_invs_triples)
# Full
means_partial_sequence, sigma_invs_partial_sequence = get_partial_sequence_statistics(keys_LOO, feature_list_pairs, feature_list_triples, step, num_pairs)
mean_cost_estimates, sigma_inv_cost_estimates = get_sequence_cost_estimate_statistics(key_list, array_list, step, means_partial_sequence, sigma_invs_partial_sequence, tl)
op_means_seq = os.path.join(resources_Full, 'means_sequence_Q.npy')
op_sigma_invs_seq = os.path.join(resources_Full, 'sigma_invs_sequence_Q.npy')
op_mean_cost_estimates = os.path.join(resources_Full, 'mean_cost_estimates_Q.npy')
op_sigma_cost_estimates = os.path.join(resources_Full, 'sigma_inv_cost_estimates_Q.npy')
np.save(op_means_seq, means_partial_sequence)
np.save(op_sigma_invs_seq, sigma_invs_partial_sequence)
np.save(op_mean_cost_estimates, mean_cost_estimates)
np.save(op_sigma_cost_estimates, sigma_inv_cost_estimates)
| 43.707965
| 175
| 0.728791
| 1,503
| 9,878
| 4.360612
| 0.107784
| 0.071407
| 0.053403
| 0.081172
| 0.840555
| 0.831858
| 0.81477
| 0.810497
| 0.810497
| 0.810497
| 0
| 0.012888
| 0.175238
| 9,878
| 226
| 176
| 43.707965
| 0.79158
| 0.067726
| 0
| 0.524823
| 0
| 0
| 0.06875
| 0.035156
| 0
| 0
| 0
| 0
| 0
| 1
| 0.014184
| false
| 0
| 0.035461
| 0
| 0.06383
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 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
| 6
|
bb6eef236881bdd27b233cbe887ce5a57611e5c4
| 337
|
py
|
Python
|
foolbox/models/__init__.py
|
SamplingAndEnsemblingSolvers/foolbox
|
788ea92b314cd974b39047000ed692a48c7e5bf1
|
[
"MIT"
] | 2,292
|
2017-06-14T23:20:34.000Z
|
2022-03-30T01:53:35.000Z
|
foolbox/models/__init__.py
|
SamplingAndEnsemblingSolvers/foolbox
|
788ea92b314cd974b39047000ed692a48c7e5bf1
|
[
"MIT"
] | 630
|
2017-06-15T06:34:51.000Z
|
2022-03-30T05:11:05.000Z
|
foolbox/models/__init__.py
|
SamplingAndEnsemblingSolvers/foolbox
|
788ea92b314cd974b39047000ed692a48c7e5bf1
|
[
"MIT"
] | 482
|
2017-06-14T13:43:05.000Z
|
2022-03-29T11:10:41.000Z
|
from .base import Model # noqa: F401
from .base import TransformBoundsWrapper # noqa: F401
from .pytorch import PyTorchModel # noqa: F401
from .tensorflow import TensorFlowModel # noqa: F401
from .jax import JAXModel # noqa: F401
from .numpy import NumPyModel # noqa: F401
from .wrappers import ThresholdingWrapper # noqa: F401
| 33.7
| 55
| 0.765579
| 42
| 337
| 6.142857
| 0.404762
| 0.217054
| 0.27907
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.075269
| 0.172107
| 337
| 9
| 56
| 37.444444
| 0.849462
| 0.225519
| 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
| 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
| 6
|
bb7c350c45a92171535266e3af65010af472ba57
| 39
|
py
|
Python
|
lib/appointments/__init__.py
|
jayrav13/presidency
|
f18721d5df9af161cc01f503b6657d9b06fea0e9
|
[
"MIT"
] | 14
|
2016-11-05T03:43:26.000Z
|
2021-03-25T14:55:19.000Z
|
lib/appointments/__init__.py
|
jayrav13/presidency
|
f18721d5df9af161cc01f503b6657d9b06fea0e9
|
[
"MIT"
] | 5
|
2017-01-30T21:39:34.000Z
|
2021-06-10T19:30:57.000Z
|
lib/appointments/__init__.py
|
jayrav13/presidency
|
f18721d5df9af161cc01f503b6657d9b06fea0e9
|
[
"MIT"
] | 2
|
2016-11-22T08:36:07.000Z
|
2017-01-28T16:36:29.000Z
|
from .appointments import Appointments
| 19.5
| 38
| 0.871795
| 4
| 39
| 8.5
| 0.75
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.102564
| 39
| 1
| 39
| 39
| 0.971429
| 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
| 1
| 0
|
0
| 6
|
bbb1a3f2c8c24b4eb466044601cbc0d6de034fce
| 77
|
py
|
Python
|
code/example code/introducing-python-master/1st_edition/net/fab1.py
|
ChouHsuan-Cheng/Learning_Python_Base
|
857873466463e6b20f24b1e8946c837c318f2536
|
[
"CNRI-Python"
] | null | null | null |
code/example code/introducing-python-master/1st_edition/net/fab1.py
|
ChouHsuan-Cheng/Learning_Python_Base
|
857873466463e6b20f24b1e8946c837c318f2536
|
[
"CNRI-Python"
] | null | null | null |
code/example code/introducing-python-master/1st_edition/net/fab1.py
|
ChouHsuan-Cheng/Learning_Python_Base
|
857873466463e6b20f24b1e8946c837c318f2536
|
[
"CNRI-Python"
] | null | null | null |
def iso():
from datetime import date
print(date.today().isoformat())
| 19.25
| 35
| 0.662338
| 10
| 77
| 5.1
| 0.9
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.194805
| 77
| 3
| 36
| 25.666667
| 0.822581
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.333333
| true
| 0
| 0.333333
| 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
| 1
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 6
|
a5253bd4c755f89a862a37ce5cc078a7242f8fad
| 235
|
py
|
Python
|
src/op_utils/__init__.py
|
rakshify/pyWM
|
6eecb0a420fe348e999e01316ce2c1f2d7c8fc7f
|
[
"MIT"
] | null | null | null |
src/op_utils/__init__.py
|
rakshify/pyWM
|
6eecb0a420fe348e999e01316ce2c1f2d7c8fc7f
|
[
"MIT"
] | null | null | null |
src/op_utils/__init__.py
|
rakshify/pyWM
|
6eecb0a420fe348e999e01316ce2c1f2d7c8fc7f
|
[
"MIT"
] | null | null | null |
from src.op_utils.basic_utils import method_map
from src.op_utils.compound_utils import method_map as compound_map
from src.op_utils.file_utils import method_map as file_map
method_map.update(compound_map)
method_map.update(file_map)
| 33.571429
| 66
| 0.868085
| 43
| 235
| 4.395349
| 0.27907
| 0.238095
| 0.142857
| 0.222222
| 0.412698
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.080851
| 235
| 6
| 67
| 39.166667
| 0.875
| 0
| 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
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 6
|
3c1a4f51228e2641a7d4e2e43c746c685d389412
| 116
|
py
|
Python
|
WeatherPy/api_keys.py
|
BluecellChen/python-api-challenge
|
2f4f13ab30605e79f99da006ec540354e6af6690
|
[
"ADSL"
] | null | null | null |
WeatherPy/api_keys.py
|
BluecellChen/python-api-challenge
|
2f4f13ab30605e79f99da006ec540354e6af6690
|
[
"ADSL"
] | null | null | null |
WeatherPy/api_keys.py
|
BluecellChen/python-api-challenge
|
2f4f13ab30605e79f99da006ec540354e6af6690
|
[
"ADSL"
] | null | null | null |
# OpenWeatherMap API Key
api_key = "eb1466db7ae3a93e6f626541f5ba5d90"
#api_key = "0bd030fc740da7bfa74a2132d1baafb2"
| 29
| 45
| 0.844828
| 9
| 116
| 10.666667
| 0.555556
| 0.1875
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.330189
| 0.086207
| 116
| 3
| 46
| 38.666667
| 0.575472
| 0.568966
| 0
| 0
| 0
| 0
| 0.680851
| 0.680851
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 6
|
3c211ceb642dbcbe125688d2caa88e8dd561c34a
| 35
|
py
|
Python
|
python/testData/inspections/ChainedComparison1_after.py
|
jnthn/intellij-community
|
8fa7c8a3ace62400c838e0d5926a7be106aa8557
|
[
"Apache-2.0"
] | 2
|
2019-04-28T07:48:50.000Z
|
2020-12-11T14:18:08.000Z
|
python/testData/inspections/ChainedComparison1_after.py
|
Cyril-lamirand/intellij-community
|
60ab6c61b82fc761dd68363eca7d9d69663cfa39
|
[
"Apache-2.0"
] | 173
|
2018-07-05T13:59:39.000Z
|
2018-08-09T01:12:03.000Z
|
python/testData/inspections/ChainedComparison1_after.py
|
Cyril-lamirand/intellij-community
|
60ab6c61b82fc761dd68363eca7d9d69663cfa39
|
[
"Apache-2.0"
] | 2
|
2020-03-15T08:57:37.000Z
|
2020-04-07T04:48:14.000Z
|
if e < a <= b < c <= d:
print "q"
| 17.5
| 23
| 0.371429
| 8
| 35
| 1.625
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.371429
| 35
| 2
| 24
| 17.5
| 0.590909
| 0
| 0
| 0
| 0
| 0
| 0.027778
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | null | 0
| 0
| null | null | 0.5
| 1
| 1
| 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
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 1
|
0
| 6
|
3c397b7bdebd7b55187a79abe11759bae981545d
| 91
|
py
|
Python
|
src/rbx2/rbx2_utils/src/rbx2_utils/srv/__init__.py
|
fujy/ROS-Project
|
b5e3b43c5eb5d3c1d984648f0f61710eea3a1bb8
|
[
"MIT"
] | 9
|
2017-08-22T13:07:13.000Z
|
2021-07-13T10:02:29.000Z
|
src/rbx2/rbx2_utils/src/rbx2_utils/srv/__init__.py
|
vcdanda/ROS-Turtlebot2
|
f24356486f55933d52e25a81715f1571aace0224
|
[
"MIT"
] | 1
|
2017-12-14T06:46:58.000Z
|
2017-12-14T06:46:58.000Z
|
src/rbx2/rbx2_utils/src/rbx2_utils/srv/__init__.py
|
vcdanda/ROS-Turtlebot2
|
f24356486f55933d52e25a81715f1571aace0224
|
[
"MIT"
] | 5
|
2018-02-07T14:09:28.000Z
|
2021-01-08T20:41:52.000Z
|
from ._OldLaunchProcess import *
from ._KillProcess import *
from ._LaunchProcess import *
| 22.75
| 32
| 0.802198
| 9
| 91
| 7.777778
| 0.555556
| 0.285714
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.131868
| 91
| 3
| 33
| 30.333333
| 0.886076
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 6
|
3c93cce5a9be4056963eb3578ff51c1da96a4031
| 209
|
py
|
Python
|
mikuai/__init__.py
|
Sebidev/MikuAi
|
8e84280a38ac45ca9ec18b2e972e29cecfba3337
|
[
"BSD-3-Clause"
] | null | null | null |
mikuai/__init__.py
|
Sebidev/MikuAi
|
8e84280a38ac45ca9ec18b2e972e29cecfba3337
|
[
"BSD-3-Clause"
] | null | null | null |
mikuai/__init__.py
|
Sebidev/MikuAi
|
8e84280a38ac45ca9ec18b2e972e29cecfba3337
|
[
"BSD-3-Clause"
] | null | null | null |
# __init__.py
from mikuai.dialog import *
from mikuai.model import *
from mikuai.nltk_utils import *
from mikuai.train import *
from mikuai.transmit import *
from mikuai.tts import *
from mikuai.test import *
| 23.222222
| 31
| 0.779904
| 31
| 209
| 5.096774
| 0.419355
| 0.443038
| 0.607595
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.143541
| 209
| 9
| 32
| 23.222222
| 0.882682
| 0.052632
| 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
| 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
| 6
|
b1ed71e13055ae214eb81e8886d2c34328d541ea
| 902
|
py
|
Python
|
tests/integration_tests/test_deployment.py
|
jbushman/deployment-client
|
c0ae1762e8a098b3c1d9211a1810b2f0c0cb7bfa
|
[
"Apache-2.0"
] | null | null | null |
tests/integration_tests/test_deployment.py
|
jbushman/deployment-client
|
c0ae1762e8a098b3c1d9211a1810b2f0c0cb7bfa
|
[
"Apache-2.0"
] | null | null | null |
tests/integration_tests/test_deployment.py
|
jbushman/deployment-client
|
c0ae1762e8a098b3c1d9211a1810b2f0c0cb7bfa
|
[
"Apache-2.0"
] | null | null | null |
import requests
def test_post_rollout(base_url):
data = {
"deployment_id": 1,
"versionlock": [
"eig-hp-core_lib-20200527-1.5299e2c.el7.noarch",
"eig-hp-hp_common-20200527-1.bfc6a82.el7.noarch",
"eig-hp-hp_web-20200929-1.e3729c0.el7.noarch",
],
}
response = requests.post(base_url + "/rollout", json=data)
print(response.text)
assert response.status_code == 201
def test_post_rollback(base_url):
data = {
"deployment_id": 1,
"yum_rollback_id": 5,
"versionlock": [
"eig-hp-core_lib-20200527-1.5299e2c.el7.noarch",
"eig-hp-hp_common-20200527-1.bfc6a82.el7.noarch",
"eig-hp-hp_web-20200929-1.e3729c0.el7.noarch",
],
}
response = requests.post(base_url + "/rollback", json=data)
print(response.text)
assert response.status_code == 201
| 29.096774
| 63
| 0.607539
| 114
| 902
| 4.631579
| 0.324561
| 0.056818
| 0.090909
| 0.106061
| 0.848485
| 0.848485
| 0.757576
| 0.757576
| 0.757576
| 0.757576
| 0
| 0.140533
| 0.250554
| 902
| 30
| 64
| 30.066667
| 0.640533
| 0
| 0
| 0.692308
| 0
| 0
| 0.385809
| 0.297118
| 0
| 0
| 0
| 0
| 0.076923
| 1
| 0.076923
| false
| 0
| 0.038462
| 0
| 0.115385
| 0.076923
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 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
| 6
|
b1f2d589eb0e1dfa765f4d38622e339879bc9dad
| 184
|
py
|
Python
|
coursera/python_programming_basics/1_week_01.py
|
anklav24/Python-Education
|
49ebcfabda1376390ee71e1fe321a51e33831f9e
|
[
"Apache-2.0"
] | null | null | null |
coursera/python_programming_basics/1_week_01.py
|
anklav24/Python-Education
|
49ebcfabda1376390ee71e1fe321a51e33831f9e
|
[
"Apache-2.0"
] | null | null | null |
coursera/python_programming_basics/1_week_01.py
|
anklav24/Python-Education
|
49ebcfabda1376390ee71e1fe321a51e33831f9e
|
[
"Apache-2.0"
] | null | null | null |
print('Hello, world.')
print('Hello, Python!')
print(2 + 3)
print('2' * 3)
print(f'2 + 3 = {2 + 3}')
print('1', '2', '3', sep=' + ', end=' ')
print('=', 1 + 2 + 3, end='')
print('!')
| 18.4
| 40
| 0.461957
| 30
| 184
| 2.833333
| 0.333333
| 0.141176
| 0.247059
| 0.282353
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.093333
| 0.184783
| 184
| 9
| 41
| 20.444444
| 0.473333
| 0
| 0
| 0
| 0
| 0
| 0.282609
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| null | 0
| 1
| 1
| 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
| 6
|
5900d22d07d046187ccd5ec08b259d619bfc97c8
| 96
|
py
|
Python
|
venv/lib/python3.8/site-packages/numpy/core/tests/test_mem_overlap.py
|
Retraces/UkraineBot
|
3d5d7f8aaa58fa0cb8b98733b8808e5dfbdb8b71
|
[
"MIT"
] | 2
|
2022-03-13T01:58:52.000Z
|
2022-03-31T06:07:54.000Z
|
venv/lib/python3.8/site-packages/numpy/core/tests/test_mem_overlap.py
|
DesmoSearch/Desmobot
|
b70b45df3485351f471080deb5c785c4bc5c4beb
|
[
"MIT"
] | 19
|
2021-11-20T04:09:18.000Z
|
2022-03-23T15:05:55.000Z
|
venv/lib/python3.8/site-packages/numpy/core/tests/test_mem_overlap.py
|
DesmoSearch/Desmobot
|
b70b45df3485351f471080deb5c785c4bc5c4beb
|
[
"MIT"
] | null | null | null |
/home/runner/.cache/pip/pool/fe/8b/1c/1334ca44556857d625f975f5f8d16ee1ae93857fdf08465af744784cab
| 96
| 96
| 0.895833
| 9
| 96
| 9.555556
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.427083
| 0
| 96
| 1
| 96
| 96
| 0.46875
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| null | null | 0
| 0
| null | null | 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 1
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 1
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 6
|
3cc66bb1651cdfa73664674b4b37f47c867cef59
| 48
|
py
|
Python
|
pacote/outroModulo.py
|
Mopanc/Angry-birds
|
76a0f22954ac248fc598978fa3d8373844aefe97
|
[
"MIT"
] | 1
|
2021-04-25T23:17:45.000Z
|
2021-04-25T23:17:45.000Z
|
pacote/outroModulo.py
|
Mopanc/pythonbirds-simples
|
76a0f22954ac248fc598978fa3d8373844aefe97
|
[
"MIT"
] | null | null | null |
pacote/outroModulo.py
|
Mopanc/pythonbirds-simples
|
76a0f22954ac248fc598978fa3d8373844aefe97
|
[
"MIT"
] | null | null | null |
from modulo import soma as s
print(s(7, 8))
| 6.857143
| 28
| 0.645833
| 10
| 48
| 3.1
| 0.9
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.055556
| 0.25
| 48
| 6
| 29
| 8
| 0.805556
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.5
| 0
| 0.5
| 0.5
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 1
|
0
| 6
|
59d2117558f3955c20079bca1baa811d7a4ed19c
| 187
|
py
|
Python
|
brd_mod/main.py
|
benrdavison/brd_mod
|
d496c5faece564f3758c25ed99a8240cde0ccf81
|
[
"MIT"
] | null | null | null |
brd_mod/main.py
|
benrdavison/brd_mod
|
d496c5faece564f3758c25ed99a8240cde0ccf81
|
[
"MIT"
] | null | null | null |
brd_mod/main.py
|
benrdavison/brd_mod
|
d496c5faece564f3758c25ed99a8240cde0ccf81
|
[
"MIT"
] | null | null | null |
import pandas as pd
import sys
import os
from brd_mod.brdstats import *
from brd_mod.brdgeo import *
from brd_mod.brdecon import *
if __name__ == "__main__":
print("test")
| 15.583333
| 31
| 0.705882
| 28
| 187
| 4.321429
| 0.607143
| 0.173554
| 0.247934
| 0.264463
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.213904
| 187
| 12
| 32
| 15.583333
| 0.823129
| 0
| 0
| 0
| 0
| 0
| 0.067797
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.75
| 0
| 0.75
| 0.125
| 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
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 6
|
ab8213d99a8dc4b4addf13b3f60074b1e7fb2f88
| 2,117
|
py
|
Python
|
utils/visualization.py
|
jonatanbarkan/CausalInference
|
c58af08811206cc25c7bbc156ef533161ecd3184
|
[
"Apache-2.0"
] | null | null | null |
utils/visualization.py
|
jonatanbarkan/CausalInference
|
c58af08811206cc25c7bbc156ef533161ecd3184
|
[
"Apache-2.0"
] | 4
|
2021-06-02T00:56:17.000Z
|
2022-01-13T02:08:21.000Z
|
utils/visualization.py
|
jonatanbarkan/CausalInference
|
c58af08811206cc25c7bbc156ef533161ecd3184
|
[
"Apache-2.0"
] | null | null | null |
import matplotlib.pyplot as plt
import seaborn as sns
import pandas as pd
import os
sns.set_style("whitegrid")
def make_separate_plots(logged_values, plot_path: str, model_name: str):
file_path = os.path.join(plot_path, f'{model_name}_accuracy')
fig, ax = plt.subplots(dpi=300)
plot_titles = list(logged_values.keys())
dict_hierarchy = {(plot_title, plot_type): values for plot_title, train_val_dict in logged_values.items() for
plot_type, values in train_val_dict.items()}
df_plot = pd.DataFrame(dict_hierarchy)
# df_plot.set_index(pd.Index(range(1, df_plot.shape[0] + 1)), inplace=True)
for i, plot_title in enumerate(plot_titles):
sns.lineplot(data=df_plot[plot_title], ax=ax)
ax.set_title(plot_title)
ax.set_ylabel('' if plot_title.lower() in ['symmetry'] else r'1-acc')
ax.set_ylim(-0.01, 1.01)
ax.set_xlabel('Epochs')
# plt.tight_layout()
plt.savefig(file_path + f'_{plot_title}_accuracy.png')
ax.cla()
df_plot.to_csv(os.path.join(plot_path, f'{model_name}_accuracy.csv'))
def make_plots(logged_values, plot_path: str, model_name: str):
file_path = os.path.join(plot_path, f'{model_name}_accuracy.png')
fig, ax = plt.subplots(4, sharex=True, dpi=300)
ax = ax.flat
plot_titles = list(logged_values.keys())
dict_hierarchy = {(plot_title, plot_type): values for plot_title, train_val_dict in logged_values.items() for
plot_type, values in train_val_dict.items()}
df_plot = pd.DataFrame(dict_hierarchy)
# df_plot.set_index(pd.Index(range(1, df_plot.shape[0] + 1)), inplace=True)
for i, plot_title in enumerate(plot_titles):
sns.lineplot(data=df_plot[plot_title])
# ax[i].set_title(plot_title)
ax[i].set_title(plot_title)
ax[i].set_ylabel('' if plot_title.lower() in ['symmetry'] else r'1-acc')
ax[i].set_ylim(-0.05, 1.05)
ax[-1].set_xlabel('Epochs')
plt.tight_layout()
plt.savefig(file_path)
plt.close(fig)
df_plot.to_csv(os.path.join(plot_path, f'{model_name}_accuracy.csv'))
| 42.34
| 113
| 0.679735
| 341
| 2,117
| 3.953079
| 0.237537
| 0.093472
| 0.040801
| 0.041543
| 0.81454
| 0.800445
| 0.800445
| 0.800445
| 0.800445
| 0.800445
| 0
| 0.016213
| 0.184223
| 2,117
| 49
| 114
| 43.204082
| 0.764331
| 0.091639
| 0
| 0.307692
| 0
| 0
| 0.088113
| 0.063608
| 0
| 0
| 0
| 0
| 0
| 1
| 0.051282
| false
| 0
| 0.102564
| 0
| 0.153846
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 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
| 6
|
abb180241ed1d75edbab3cb2d63e3f967b6cb146
| 61
|
py
|
Python
|
server/webserver/views/resources/__init__.py
|
htl-anichstrasse/HTLCatcher
|
de973e9298cb6d8f042792aae99f4cdc7382c0d4
|
[
"MIT"
] | 5
|
2019-12-04T09:55:43.000Z
|
2020-10-10T19:01:13.000Z
|
server/webserver/views/resources/__init__.py
|
bemoty/HTLCatcher
|
de973e9298cb6d8f042792aae99f4cdc7382c0d4
|
[
"MIT"
] | 12
|
2019-11-27T07:15:28.000Z
|
2021-07-12T21:17:55.000Z
|
server/webserver/views/resources/__init__.py
|
htl-anichstrasse/htl-catcher
|
de973e9298cb6d8f042792aae99f4cdc7382c0d4
|
[
"MIT"
] | null | null | null |
from .add import *
from .remove import *
from .fetch import *
| 20.333333
| 21
| 0.721311
| 9
| 61
| 4.888889
| 0.555556
| 0.454545
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.180328
| 61
| 3
| 22
| 20.333333
| 0.88
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 6
|
abb8784b30c9310588f63e607def7b09df28ce08
| 50
|
py
|
Python
|
structures/generation/__init__.py
|
EladSharony/Mechanics
|
078f97bea84114fc1db6fe9700b92b96b18a0d5e
|
[
"MIT"
] | 24
|
2021-02-23T13:53:14.000Z
|
2022-03-29T16:40:56.000Z
|
structures/generation/__init__.py
|
EladSharony/Mechanics
|
078f97bea84114fc1db6fe9700b92b96b18a0d5e
|
[
"MIT"
] | 2
|
2021-04-23T12:30:32.000Z
|
2022-03-31T10:51:12.000Z
|
structures/generation/__init__.py
|
EladSharony/Mechanics
|
078f97bea84114fc1db6fe9700b92b96b18a0d5e
|
[
"MIT"
] | 12
|
2021-04-11T20:44:03.000Z
|
2022-03-30T19:23:58.000Z
|
from .gen_warren import generate_warren_structure
| 25
| 49
| 0.9
| 7
| 50
| 6
| 0.857143
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.08
| 50
| 1
| 50
| 50
| 0.913043
| 0
| 0
| 0
| 1
| 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
| 1
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 6
|
abd53381acc5acdf1b8252db3d75451d62416886
| 35
|
py
|
Python
|
data/__init__.py
|
phasorhand/PyTorchText
|
dcadcba44af0c3731b82d9db1c77f2968d4feac0
|
[
"MIT"
] | 1,136
|
2017-08-16T08:49:04.000Z
|
2022-03-25T09:49:41.000Z
|
data/__init__.py
|
LydonL/PyTorchText
|
dcadcba44af0c3731b82d9db1c77f2968d4feac0
|
[
"MIT"
] | 13
|
2017-08-29T10:13:03.000Z
|
2019-12-19T05:37:17.000Z
|
data/__init__.py
|
LydonL/PyTorchText
|
dcadcba44af0c3731b82d9db1c77f2968d4feac0
|
[
"MIT"
] | 383
|
2017-08-16T08:45:55.000Z
|
2022-03-30T06:34:09.000Z
|
from .fold_dataset import FoldData
| 35
| 35
| 0.857143
| 5
| 35
| 5.8
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.114286
| 35
| 1
| 35
| 35
| 0.935484
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 6
|
f9fde9f01f671f4c1eff239deb358bbd14f24b50
| 88
|
py
|
Python
|
app/auth/__init__.py
|
Sundaybrian/crystal-pitches
|
283bca14397c1ab3599fce1e236eaa3f9933e009
|
[
"MIT"
] | null | null | null |
app/auth/__init__.py
|
Sundaybrian/crystal-pitches
|
283bca14397c1ab3599fce1e236eaa3f9933e009
|
[
"MIT"
] | null | null | null |
app/auth/__init__.py
|
Sundaybrian/crystal-pitches
|
283bca14397c1ab3599fce1e236eaa3f9933e009
|
[
"MIT"
] | null | null | null |
from flask import Blueprint
auth=Blueprint('auth',__name__)
from . import views,forms
| 14.666667
| 31
| 0.784091
| 12
| 88
| 5.416667
| 0.666667
| 0.4
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.125
| 88
| 6
| 32
| 14.666667
| 0.844156
| 0
| 0
| 0
| 0
| 0
| 0.044944
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.666667
| 0
| 0.666667
| 0.666667
| 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
| 1
|
0
| 6
|
e6284da10457188f974e741a92076e0fc79a15aa
| 61
|
py
|
Python
|
src/Python3/41078/classfy02.py
|
umyuu/Sample
|
66e8cd725b682db4c9bf93fb80786eea8cbad19d
|
[
"MIT"
] | null | null | null |
src/Python3/41078/classfy02.py
|
umyuu/Sample
|
66e8cd725b682db4c9bf93fb80786eea8cbad19d
|
[
"MIT"
] | null | null | null |
src/Python3/41078/classfy02.py
|
umyuu/Sample
|
66e8cd725b682db4c9bf93fb80786eea8cbad19d
|
[
"MIT"
] | null | null | null |
# -*- coding: UTF-8 -*
def input_data2():
return None
| 8.714286
| 22
| 0.557377
| 8
| 61
| 4.125
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.044444
| 0.262295
| 61
| 6
| 23
| 10.166667
| 0.688889
| 0.327869
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.5
| true
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0
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05184d71c4340feab34b844ba7fbeabf7acaf1bd
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py
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Python
|
registry/token/__init__.py
|
brianhlin/open-science-pool-registry
|
7d06e8a893720fe91c7f1cbcbe780106b35effeb
|
[
"Apache-2.0"
] | null | null | null |
registry/token/__init__.py
|
brianhlin/open-science-pool-registry
|
7d06e8a893720fe91c7f1cbcbe780106b35effeb
|
[
"Apache-2.0"
] | 46
|
2020-05-11T14:20:41.000Z
|
2020-09-18T18:15:17.000Z
|
registry/token/__init__.py
|
brianhlin/open-science-pool-registry
|
7d06e8a893720fe91c7f1cbcbe780106b35effeb
|
[
"Apache-2.0"
] | 5
|
2020-11-17T16:41:48.000Z
|
2022-01-08T16:21:09.000Z
|
from .views import token_bp
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0
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05205692cd9db29041cd2e4b6fc303ef292e2554
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py
|
Python
|
run_demo.py
|
leotmc/simcse
|
e0b62fcef5dadeeef55aef3b640ab219860c201b
|
[
"MIT"
] | null | null | null |
run_demo.py
|
leotmc/simcse
|
e0b62fcef5dadeeef55aef3b640ab219860c201b
|
[
"MIT"
] | null | null | null |
run_demo.py
|
leotmc/simcse
|
e0b62fcef5dadeeef55aef3b640ab219860c201b
|
[
"MIT"
] | null | null | null |
# # # # run with pytorch
# # # import torch
# # # from scipy.spatial.distance import cosine
# # # from transformers import AutoModel, AutoTokenizer
# # #
# # # # Import our models. The package will take care of downloading the models automatically
# # # tokenizer = AutoTokenizer.from_pretrained("result/unsup-simcse-bert-base-uncased")
# # # model = AutoModel.from_pretrained("result/unsup-simcse-bert-base-uncased")
# # #
# # # # Tokenize input texts
# # # texts = [
# # # "今天天气真好",
# # # "天上乌云密布",
# # # "今天的天气挺不错的"
# # # ]
# # # inputs = tokenizer(texts, padding=True, truncation=True, return_tensors="pt")
# # #
# # # # Get the embeddings
# # # with torch.no_grad():
# # # embeddings = model(**inputs, output_hidden_states=True, return_dict=True).pooler_output
# # #
# # # # Calculate cosine similarities
# # # # Cosine similarities are in [-1, 1]. Higher means more similar
# # # cosine_sim_0_1 = 1 - cosine(embeddings[0], embeddings[1])
# # # cosine_sim_0_2 = 1 - cosine(embeddings[0], embeddings[2])
# # #
# # # print("Cosine similarity between \"%s\" and \"%s\" is: %.3f" % (texts[0], texts[1], cosine_sim_0_1))
# # # print("Cosine similarity between \"%s\" and \"%s\" is: %.3f" % (texts[0], texts[2], cosine_sim_0_2))
# #
# # pass
# #
# # # # # run with tensorflow
# # # from scipy.spatial.distance import cosine
# # # from transformers import TFAutoModel, AutoTokenizer
# # #
# # # # Import our models. The package will take care of downloading the models automatically
# # # tokenizer = AutoTokenizer.from_pretrained("result/unsup-simcse-bert-base-uncased")
# # # model = TFAutoModel.from_pretrained("result/unsup-simcse-bert-base-uncased", from_pt=True)
# # #
# # # # Tokenize input texts
# # # texts = [
# # # "今天天气真好",
# # # "天上乌云密布",
# # # "今天的天气挺不错的"
# # # ]
# # # inputs = tokenizer(texts, padding=True, truncation=True, return_tensors="tf")
# # # # Get the embeddings
# # # embeddings = model(**inputs, output_hidden_states=True, return_dict=True).pooler_output
# # #
# # # # Calculate cosine similarities
# # # # Cosine similarities are in [-1, 1]. Higher means more similar
# # # cosine_sim_0_1 = 1 - cosine(embeddings[0], embeddings[1])
# # # cosine_sim_0_2 = 1 - cosine(embeddings[0], embeddings[2])
# # #
# # # print("Cosine similarity between \"%s\" and \"%s\" is: %.3f" % (texts[0], texts[1], cosine_sim_0_1))
# # # print("Cosine similarity between \"%s\" and \"%s\" is: %.3f" % (texts[0], texts[2], cosine_sim_0_2))
# # #
# # # pass
# # # # run with tensorflow serving
# # # from transformers import TFAutoModel, AutoTokenizer
# # # tokenizer = AutoTokenizer.from_pretrained("/home/homay/leoliu/SimCSE/result/huawei-6l-unsup")
# # # model = TFAutoModel.from_pretrained("/home/homay/leoliu/SimCSE/result/huawei-6l-unsup", from_pt=True)
# # # model.summary()
# # # model.save_pretrained('output', saved_model=True)
# #
# # pass
# from transformers import BertTokenizerFast
# import requests
# import json
# #
# #
# # """
# # {
# # "predictions": [
# # {
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# # }
# # ]
# # }
# # """
# #
# #
# sentences = ["今天天气很好。", "床前明月光", "疑是地上霜", "大江东去", "千古风流人物", "故垒西边"]
# # sentences = '今天天气很好'
#
#
# """
# {
# 'input_ids': [101, 791, 1921, 1921, 3698, 2523, 1962, 102],
# 'token_type_ids': [0, 0, 0, 0, 0, 0, 0, 0],
# 'attention_mask': [1, 1, 1, 1, 1, 1, 1, 1]
# }
#
# {
# 'input_ids': [101, 791, 1921, 1921, 3698, 2523, 1962, 102, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
# 'input_mask': [1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
# 'segment_ids': [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
# 'label_ids': 0
# }
# """
#
#
# tokenizer = BertTokenizerFast.from_pretrained("/home/homay/leoliu/SimCSE/result/unsup/huawei-6l-unsup")
# batch = tokenizer(sentences, padding=True, pad_to_multiple_of=100)
# batch = dict(batch)
# instances = []
# num_sentences = len(sentences)
# for i in range(num_sentences):
# instance = {key: batch[key][i] for key in batch.keys()}
# instances.append(instance)
# input_data = {"instances": instances}
# r = requests.post("http://192.168.50.180:8501/v1/models/simcse_unsup_encoder/labels/huawei_6L:predict", data=json.dumps(input_data))
# print(r.text)
# #
# #
# # from tokenizers import Tokenizer
# # tokenizer = Tokenizer.from_file("/home/homay/leoliu/SimCSE/result/huawei-6l-unsup/tokenizer.json")
# # encoded = tokenizer.encode_batch(sentences)
# #
# # from transformers.models.bert.tokenization_bert_fast import BertTokenizerFast
#
#
# pass
# # # prepare chinese snli dataset
# # import os
# # import ujson as json
# # import pandas as pd
# # from collections import defaultdict
# #
# #
# # def json2csv(data_dir):
# # files = os.listdir(data_dir)
# # files = [os.path.join(data_dir, f) for f in files if f.endswith('jsonl')]
# # nli_data = defaultdict(dict)
# # sentences1, sentences2, hard_neg_sentences = [], [], []
# # for file in files:
# # for i, line in enumerate(open(file, 'r', encoding='utf-8')):
# # line = line.strip()
# # if not line:
# # continue
# # data = json.loads(line)
# # s1, s2, label = data['sentence1'], data['sentence2'], data['gold_label']
# # if label == 'contradiction':
# # nli_data[s1]['hard_neg'] = s2
# # elif label == 'entailment':
# # nli_data[s1]['entailment'] = s2
# # if i % 10000 == 0:
# # print(f'successfully processed {i} items.')
# # # with open('/home/homay/leoliu/nli_data.json', 'w', encoding='utf-8') as f:
# # # json.dump(nli_data, f, ensure_ascii=False, indent=4)
# # for key, value in nli_data.items():
# # if value.get('entailment') is None or value.get('hard_neg') is None:
# # continue
# # sentences1.append(key)
# # sentences2.append(value['entailment'])
# # hard_neg_sentences.append(value['hard_neg'])
# # df = pd.DataFrame(
# # data=zip(sentences1, sentences2, hard_neg_sentences),
# # columns=['sent0', 'sent1', 'hard_neg']
# # )
# # df.to_csv('/home/homay/leoliu/SimCSE/data/cn_nli.csv', index=False)
# #
# #
# # if __name__ == '__main__':
# # # json_file = '/home/homay/leoliu/SimCSE/data/cnsd_multil_train.jsonl'
# # # json_data = json2csv(json_file)
# # # print('*')
# # data_dir = '/home/homay/leoliu/datasets/senteval_cn/NLI'
# # json2csv(data_dir)
pass
# use t5-pegasus-small-chinese to do text summary
import json
import jieba
import requests
import tensorflow as tf
from transformers import BertTokenizerFast
from transformers.models.mt5.modeling_mt5 import MT5ForConditionalGeneration
from transformers.models.mt5.modeling_tf_mt5 import TFMT5ForConditionalGeneration
model_path = '/home/homay/leoliu/huggingface_models/t5-pegasus-small-chinese'
class T5PegasusTokenizer(BertTokenizerFast):
def __init__(self, *args, **kwargs):
super(T5PegasusTokenizer, self).__init__(*args, **kwargs)
def _tokenize(self, text, *args, **kwargs):
split_tokens = []
for token in jieba.cut(text, HMM=False):
if token in self.vocab:
split_tokens.append(token)
else:
split_tokens.extend(super()._tokenize(token))
return split_tokens
"""@tf.function(
input_signature=[
{
"input_ids": tf.TensorSpec((None, None), tf.int32, name="input_ids"),
"attention_mask": tf.TensorSpec((None, None), tf.int32, name="attention_mask"),
"decoder_input_ids": tf.TensorSpec((None, None), tf.int32, name="decoder_input_ids"),
"decoder_attention_mask": tf.TensorSpec((None, None), tf.int32, name="decoder_attention_mask"),
}
]
)
def serving(self, inputs):
# output = self.call(inputs)
outputs = self.generate(inputs)
return self.serving_output(output)
"""
model = MT5ForConditionalGeneration.from_pretrained(model_path)
tokenizer = T5PegasusTokenizer.from_pretrained(model_path)
text = '基督教的《圣经》又名《新旧约全书》，由《旧约》《新约》组成。《旧约》一共有三十九卷，以古希伯来文（含亚兰文）写成，由犹太教教士依据犹太教的' \
'教义编纂而成，囊括了犹太及邻近民族从公元前12世纪至公元前2世纪的人文历史资料。《新约》一共27卷。《旧约全书》即犹太教的圣经，是基督教承自犹' \
'太教的，但《旧约全书》和《希伯来圣经》有所差异，书目的顺序也不同。'
ids = tokenizer.encode(text, return_tensors='pt')
print('*')
output = model.generate(
ids,
decoder_start_token_id=tokenizer.cls_token_id,
eos_token_id=tokenizer.sep_token_id,
max_length=150
).numpy()[0]
print(''.join(tokenizer.decode(output[1:])).replace(' ', ''))
pass
# transformer t5 pytorch model to tensorflow model
# import jieba
# from transformers import TFAutoModel
# from transformers import BertTokenizerFast
#
#
# class T5PegasusTokenizer(BertTokenizerFast):
#
# def __init__(self, *args, **kwargs):
# super(T5PegasusTokenizer, self).__init__(*args, **kwargs)
#
# def _tokenize(self, text, *args, **kwargs):
# split_tokens = []
# for token in jieba.cut(text, HMM=False):
# if token in self.vocab:
# split_tokens.append(token)
# else:
# split_tokens.extend(super()._tokenize(token))
# return split_tokens
#
#
# model_path = '/home/homay/leoliu/huggingface_models/t5-pegasus-small-chinese'
# tokenizer = T5PegasusTokenizer.from_pretrained(model_path)
# model = TFAutoModel.from_pretrained(model_path, from_pt=True)
# model.summary()
# print('*')
# model.save_pretrained('/home/homay/leoliu/temp', saved_model=True)
pass
# # serving t5-pegasus
# import json
# import jieba
# import requests
# from transformers import BertTokenizerFast
# # from transformers.models.mt5 import MT5ForConditionalGeneration, T5Tokenizer
# # from transformers.models.mt5 import TFMT5ForConditionalGeneration
#
#
# class T5PegasusTokenizer(BertTokenizerFast):
#
# def __init__(self, *args, **kwargs):
# super(T5PegasusTokenizer, self).__init__(*args, **kwargs)
#
# def _tokenize(self, text, *args, **kwargs):
# split_tokens = []
# for token in jieba.cut(text, HMM=False):
# if token in self.vocab:
# split_tokens.append(token)
# else:
# split_tokens.extend(super()._tokenize(token))
# return split_tokens
#
#
# sentences = ['11月2日0—24时，31个省（自治区、直辖市）和新疆生产建设兵团报告新增确诊病例109例。其中境外输入病例16例（上海5例，广东4例，云南2例，辽宁1例，浙江1例，山东1例，广西1例，四川1例），含3例由无症状感染者转为确诊病例（辽宁1例，浙江1例，四川1例）；本土病例93例（黑龙江35例，均在黑河市；河北14例，均在石家庄市；甘肃14例，其中天水市13例、兰州市1例；北京9例，均在昌平区；内蒙古6例，均在阿拉善盟；重庆4例，其中九龙坡区2例、巴南区1例、长寿区1例；青海4例，均在西宁市；江西2例，均在上饶市；云南2例，均在德宏傣族景颇族自治州；宁夏2例，均在银川市；四川1例，在成都市），含1例由无症状感染者转为确诊病例（在北京）。无新增死亡病例。新增疑似病例1例，为境外输入病例（在上海）。']
# tokenizer = T5PegasusTokenizer.from_pretrained("/home/homay/leoliu/huggingface_models/t5-pegasus-small-chinese")
# batch = tokenizer(sentences, padding=True, pad_to_multiple_of=100)
# batch = dict(batch)
# instances = []
# num_sentences = len(sentences)
# for i in range(num_sentences):
# instance = {key: batch[key][i] for key in batch.keys()}
# instance['decoder_input_ids'] = instance['input_ids']
# instance['decoder_attention_mask'] = instance['attention_mask']
# instance.pop('token_type_ids')
# instances.append(instance)
#
# input_data = {"instances": instances}
# r = requests.post("http://192.168.50.180:8501/v1/models/t5-pegasus-generator/labels/small:predict", data=json.dumps(input_data))
# res = json.loads(r.text)
# print(res)
pass
# from transformers import MT5Model, T5Tokenizer
# model_path = '/home/homay/leoliu/huggingface_models/mt5-small'
# model = MT5Model.from_pretrained(model_path)
# tokenizer = T5Tokenizer.from_pretrained(model_path)
# article = "UN Offizier sagt, dass weiter verhandelt werden muss in Syrien."
# summary = "Weiter Verhandlung in Syrien."
# inputs = tokenizer(article, return_tensors="pt")
# with tokenizer.as_target_tokenizer():
# labels = tokenizer(summary, return_tensors="pt")
#
# outputs = model(input_ids=inputs["input_ids"], decoder_input_ids=labels["input_ids"])
# hidden_states = outputs.last_hidden_state
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0
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0521fd9d2a6ae533551f5fbef36ccbff6d43da00
| 89
|
py
|
Python
|
Solutions/gigasecond.py
|
matthijskrul/PythonExercism
|
7f0fbd340cf32f7bb88b0c32287729968720ee1c
|
[
"MIT"
] | null | null | null |
Solutions/gigasecond.py
|
matthijskrul/PythonExercism
|
7f0fbd340cf32f7bb88b0c32287729968720ee1c
|
[
"MIT"
] | null | null | null |
Solutions/gigasecond.py
|
matthijskrul/PythonExercism
|
7f0fbd340cf32f7bb88b0c32287729968720ee1c
|
[
"MIT"
] | null | null | null |
import datetime
def add(moment):
return moment + datetime.timedelta(seconds=10**9)
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| 1
| 0.333333
| false
| 0
| 0.333333
| 0.333333
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 1
| 1
| 1
| 0
|
0
| 6
|
05334f73aaef1bfb6da9535d7fb43ac60e10c219
| 87
|
py
|
Python
|
sokoapp/contests/tests/test_app/models.py
|
Mercy-Nekesa/sokoapp
|
6c7bc4c1278b7223226124a49fc33c5b8b6b617a
|
[
"MIT"
] | 1
|
2019-04-01T05:52:37.000Z
|
2019-04-01T05:52:37.000Z
|
sokoapp/contests/tests/test_app/models.py
|
Mercy-Nekesa/sokoapp
|
6c7bc4c1278b7223226124a49fc33c5b8b6b617a
|
[
"MIT"
] | 1
|
2015-03-11T16:18:12.000Z
|
2015-03-11T16:18:12.000Z
|
sokoapp/contests/tests/test_app/models.py
|
Mercy-Nekesa/sokoapp
|
6c7bc4c1278b7223226124a49fc33c5b8b6b617a
|
[
"MIT"
] | null | null | null |
from referee.models import TimePeriodBase
class TimePeriod(TimePeriodBase):
pass
| 14.5
| 41
| 0.804598
| 9
| 87
| 7.777778
| 0.888889
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.149425
| 87
| 5
| 42
| 17.4
| 0.945946
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0.333333
| 0.333333
| 0
| 0.666667
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 1
| 0
| 1
| 0
|
0
| 6
|
0579eee2c917b4f2d31a3f3e1666ecb279aece4a
| 2,835
|
py
|
Python
|
cases/migrations/0003_visualcases_visualcountry_visualdeaths_visualrecovered.py
|
testyourcodenow/core
|
05865b02ff7e60ffd3b30652161b3523046b9696
|
[
"MIT"
] | 1
|
2020-05-10T06:40:58.000Z
|
2020-05-10T06:40:58.000Z
|
cases/migrations/0003_visualcases_visualcountry_visualdeaths_visualrecovered.py
|
testyourcodenow/core
|
05865b02ff7e60ffd3b30652161b3523046b9696
|
[
"MIT"
] | 25
|
2020-05-03T08:10:38.000Z
|
2021-09-22T18:59:29.000Z
|
cases/migrations/0003_visualcases_visualcountry_visualdeaths_visualrecovered.py
|
testyourcodenow/core
|
05865b02ff7e60ffd3b30652161b3523046b9696
|
[
"MIT"
] | 10
|
2020-05-03T08:25:56.000Z
|
2020-06-03T06:49:34.000Z
|
# Generated by Django 3.0.6 on 2020-05-27 14:05
from django.db import migrations, models
import django.db.models.deletion
class Migration(migrations.Migration):
dependencies = [
('cases', '0002_auto_20200506_2202'),
]
operations = [
migrations.CreateModel(
name='VisualCountry',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('name', models.CharField(max_length=255)),
('time_created', models.DateTimeField(auto_now_add=True)),
('last_updated', models.DateTimeField(auto_now=True)),
],
options={
'ordering': ['name'],
},
),
migrations.CreateModel(
name='VisualRecovered',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('time_created', models.DateTimeField(auto_now_add=True)),
('last_updated', models.DateTimeField(auto_now=True)),
('date', models.DateField(null=True)),
('recovered', models.IntegerField(null=True)),
('country', models.OneToOneField(on_delete=django.db.models.deletion.CASCADE, to='cases.VisualCountry')),
],
options={
'ordering': ['-date'],
},
),
migrations.CreateModel(
name='VisualDeaths',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('time_created', models.DateTimeField(auto_now_add=True)),
('last_updated', models.DateTimeField(auto_now=True)),
('date', models.DateField(null=True)),
('deaths', models.IntegerField(null=True)),
('country', models.OneToOneField(on_delete=django.db.models.deletion.CASCADE, to='cases.VisualCountry')),
],
options={
'ordering': ['-date'],
},
),
migrations.CreateModel(
name='VisualCases',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('time_created', models.DateTimeField(auto_now_add=True)),
('last_updated', models.DateTimeField(auto_now=True)),
('date', models.DateField(null=True)),
('cases', models.IntegerField(null=True)),
('country', models.OneToOneField(on_delete=django.db.models.deletion.CASCADE, to='cases.VisualCountry')),
],
options={
'ordering': ['-date'],
},
),
]
| 41.086957
| 121
| 0.549206
| 257
| 2,835
| 5.906615
| 0.252918
| 0.100132
| 0.121212
| 0.137022
| 0.77141
| 0.77141
| 0.77141
| 0.77141
| 0.77141
| 0.77141
| 0
| 0.017312
| 0.307231
| 2,835
| 68
| 122
| 41.691176
| 0.755601
| 0.015873
| 0
| 0.66129
| 1
| 0
| 0.12769
| 0.00825
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.032258
| 0
| 0.080645
| 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
| 1
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 6
|
e984bfa5007be7c3d48abef446cdd58f820f9469
| 72
|
py
|
Python
|
test.py
|
masspvn/git_test
|
c01d7aa3d2c81095691e9007d5715c4a16d132dc
|
[
"MIT"
] | null | null | null |
test.py
|
masspvn/git_test
|
c01d7aa3d2c81095691e9007d5715c4a16d132dc
|
[
"MIT"
] | null | null | null |
test.py
|
masspvn/git_test
|
c01d7aa3d2c81095691e9007d5715c4a16d132dc
|
[
"MIT"
] | 1
|
2018-05-27T13:47:13.000Z
|
2018-05-27T13:47:13.000Z
|
# This is a test function
def test_original():
print("Test original")
| 18
| 25
| 0.722222
| 11
| 72
| 4.636364
| 0.727273
| 0.470588
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.166667
| 72
| 3
| 26
| 24
| 0.85
| 0.319444
| 0
| 0
| 0
| 0
| 0.276596
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.5
| true
| 0
| 0
| 0
| 0.5
| 0.5
| 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
| 1
| 0
| 0
| 0
| 0
| 1
|
0
| 6
|
758a87f8fa1a92d7624e1a7300b0c35f54aff9a1
| 42
|
py
|
Python
|
tornado/run_test.py
|
nikicc/anaconda-recipes
|
9c611a5854bf41bbc5e7ed9853dc71c0851a62ef
|
[
"BSD-3-Clause"
] | 130
|
2015-07-28T03:41:21.000Z
|
2022-03-16T03:07:41.000Z
|
tornado/run_test.py
|
nikicc/anaconda-recipes
|
9c611a5854bf41bbc5e7ed9853dc71c0851a62ef
|
[
"BSD-3-Clause"
] | 119
|
2015-08-01T00:54:06.000Z
|
2021-01-05T13:00:46.000Z
|
tornado/run_test.py
|
nikicc/anaconda-recipes
|
9c611a5854bf41bbc5e7ed9853dc71c0851a62ef
|
[
"BSD-3-Clause"
] | 72
|
2015-07-29T02:35:56.000Z
|
2022-02-26T14:31:15.000Z
|
from tornado.httpserver import HTTPServer
| 21
| 41
| 0.880952
| 5
| 42
| 7.4
| 0.8
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.095238
| 42
| 1
| 42
| 42
| 0.973684
| 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
| 1
| 0
|
0
| 6
|
75db45555eb68147173cb80f8c0908dfedb23120
| 47
|
py
|
Python
|
analytics/__init__.py
|
mesarcik/DL4DI
|
7bb85c31daff9aab06318879520070ddffa5f439
|
[
"Apache-2.0"
] | 1
|
2021-02-17T04:27:49.000Z
|
2021-02-17T04:27:49.000Z
|
analytics/__init__.py
|
laofei177/DL4DI
|
744b9f24bd0b9d02e15362e508eb46ec455be9b7
|
[
"Apache-2.0"
] | null | null | null |
analytics/__init__.py
|
laofei177/DL4DI
|
744b9f24bd0b9d02e15362e508eb46ec455be9b7
|
[
"Apache-2.0"
] | 2
|
2020-09-07T00:46:44.000Z
|
2020-12-31T15:08:56.000Z
|
# INIT FILE
from .svm import get_svm_analytics
| 15.666667
| 34
| 0.808511
| 8
| 47
| 4.5
| 0.875
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.148936
| 47
| 2
| 35
| 23.5
| 0.9
| 0.191489
| 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
| 1
| 0
|
0
| 6
|
75e7d350275bd2a5c9d13b2f086e16943db283c7
| 34
|
py
|
Python
|
pinger/db/__init__.py
|
aatrubilin/pinger
|
bef10e09c266889fcdda2a79ddbd9fb944bdaeda
|
[
"MIT"
] | 5
|
2020-05-29T09:15:07.000Z
|
2020-05-29T11:41:40.000Z
|
pinger/db/__init__.py
|
aatrubilin/pinger
|
bef10e09c266889fcdda2a79ddbd9fb944bdaeda
|
[
"MIT"
] | null | null | null |
pinger/db/__init__.py
|
aatrubilin/pinger
|
bef10e09c266889fcdda2a79ddbd9fb944bdaeda
|
[
"MIT"
] | 2
|
2020-09-20T15:30:37.000Z
|
2021-03-22T07:08:22.000Z
|
from .base import init_db, get_db
| 17
| 33
| 0.794118
| 7
| 34
| 3.571429
| 0.857143
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.147059
| 34
| 1
| 34
| 34
| 0.862069
| 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
| 1
| 0
|
0
| 6
|
75e8c9563e32d47b2391987d92673903d9f8504b
| 254
|
py
|
Python
|
Connection.py
|
tantonas/pythonServer
|
ef41367a69af35dfaf9b2e1d98ffe1f3142de441
|
[
"MIT"
] | null | null | null |
Connection.py
|
tantonas/pythonServer
|
ef41367a69af35dfaf9b2e1d98ffe1f3142de441
|
[
"MIT"
] | null | null | null |
Connection.py
|
tantonas/pythonServer
|
ef41367a69af35dfaf9b2e1d98ffe1f3142de441
|
[
"MIT"
] | null | null | null |
class Connection:
def __init__(self, unique,ip, hostname):
self.ip = ip
self.hostname = hostname
self.unique = unique
def __str__(self):
return str({"ip":self.ip, "hostname": self.hostname, "unique": self.unique})
| 31.75
| 84
| 0.61811
| 31
| 254
| 4.806452
| 0.322581
| 0.201342
| 0.187919
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.248032
| 254
| 8
| 84
| 31.75
| 0.780105
| 0
| 0
| 0
| 0
| 0
| 0.062745
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.285714
| false
| 0
| 0
| 0.142857
| 0.571429
| 0
| 0
| 0
| 0
| null | 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 1
| 0
|
0
| 6
|
ddb0c0878ae3dd0fcbabcea09329562afd4fe037
| 250
|
py
|
Python
|
src/logChunk/installDependencies.py
|
saledouble/gitcproc
|
009d614fa1a56dc75acb0277ecc98ea27e91750b
|
[
"BSD-3-Clause"
] | null | null | null |
src/logChunk/installDependencies.py
|
saledouble/gitcproc
|
009d614fa1a56dc75acb0277ecc98ea27e91750b
|
[
"BSD-3-Clause"
] | 3
|
2020-11-12T14:42:22.000Z
|
2021-01-13T22:30:23.000Z
|
src/logChunk/installDependencies.py
|
saledouble/gitcproc
|
009d614fa1a56dc75acb0277ecc98ea27e91750b
|
[
"BSD-3-Clause"
] | 2
|
2020-11-11T22:27:28.000Z
|
2021-01-13T21:07:14.000Z
|
import os
os.system("pip3 install GitPython")
os.system("pip3 install PyYAML")
os.system("pip3 install nltk")
os.system("python3 -m nltk.downloader stopwords")
os.system("python3 -m nltk.downloader wordnet")
os.system("pip3 install psycopg2-binary")
| 31.25
| 49
| 0.772
| 37
| 250
| 5.216216
| 0.405405
| 0.248705
| 0.248705
| 0.393782
| 0.310881
| 0.310881
| 0
| 0
| 0
| 0
| 0
| 0.030702
| 0.088
| 250
| 7
| 50
| 35.714286
| 0.815789
| 0
| 0
| 0
| 0
| 0
| 0.624
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.142857
| 0
| 0.142857
| 0
| 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
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
|
0
| 6
|
fb1ecdec580811d1ec9bd2a0618b77e7246e2b98
| 105
|
py
|
Python
|
ch6/5 interact dropdown.py
|
PacktPublishing/Learning-Jupyter
|
734ef16ade5f9874e5187e483746524a675bf915
|
[
"MIT"
] | 11
|
2017-02-02T08:47:32.000Z
|
2021-09-15T18:04:01.000Z
|
ch6/5 interact dropdown.py
|
PacktPublishing/Learning-Jupyter
|
734ef16ade5f9874e5187e483746524a675bf915
|
[
"MIT"
] | 2
|
2016-12-02T04:43:11.000Z
|
2016-12-02T04:43:57.000Z
|
ch6/5 interact dropdown.py
|
PacktPublishing/Learning-Jupyter
|
734ef16ade5f9874e5187e483746524a675bf915
|
[
"MIT"
] | 8
|
2016-12-02T04:39:10.000Z
|
2018-04-01T22:58:19.000Z
|
from ipywidgets import interact
def myfunction(x):
return x
interact(myfunction, x=('red','green'));
| 21
| 40
| 0.72381
| 14
| 105
| 5.428571
| 0.714286
| 0.289474
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.133333
| 105
| 4
| 41
| 26.25
| 0.835165
| 0
| 0
| 0
| 0
| 0
| 0.07619
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.25
| false
| 0
| 0.25
| 0.25
| 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
| 1
| 1
| 0
|
0
| 6
|
34960fa4a26339626ed99e310585a80818e70ef2
| 118
|
py
|
Python
|
test/io/test_colvars.py
|
jakublala/starpolymers
|
0ea17eed27bf5846674a93afd143257c74be5e7b
|
[
"MIT"
] | 6
|
2018-06-21T14:13:39.000Z
|
2022-03-24T18:28:40.000Z
|
test/io/test_colvars.py
|
jakublala/starpolymers
|
0ea17eed27bf5846674a93afd143257c74be5e7b
|
[
"MIT"
] | 10
|
2020-05-13T23:37:43.000Z
|
2022-03-21T12:19:55.000Z
|
test/io/test_colvars.py
|
jakublala/starpolymers
|
0ea17eed27bf5846674a93afd143257c74be5e7b
|
[
"MIT"
] | 3
|
2020-07-23T17:15:42.000Z
|
2022-03-21T19:43:05.000Z
|
import starpolymers.io.colvars as colvars
def test_create():
return
if __name__ == '__main__':
test_create()
| 16.857143
| 41
| 0.720339
| 15
| 118
| 5
| 0.8
| 0.266667
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.177966
| 118
| 7
| 42
| 16.857143
| 0.773196
| 0
| 0
| 0
| 0
| 0
| 0.067227
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.2
| true
| 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
| 1
| 0
| 0
| 1
| 1
| 0
|
0
| 6
|
9b2f33d1dab5ca798fd6b5457fc2978d2741e3b1
| 34
|
py
|
Python
|
pyblazing/apiv2/__init__.py
|
paulhendricks/pyBlazing
|
792d286054ec4ae8a0546d57ef758a60812d24c3
|
[
"Apache-2.0"
] | 1
|
2019-08-13T17:14:53.000Z
|
2019-08-13T17:14:53.000Z
|
pyblazing/apiv2/__init__.py
|
zhw1058/pyBlazing
|
c0d38d4886c4f3639123fef9dd6ba758739796c7
|
[
"Apache-2.0"
] | null | null | null |
pyblazing/apiv2/__init__.py
|
zhw1058/pyBlazing
|
c0d38d4886c4f3639123fef9dd6ba758739796c7
|
[
"Apache-2.0"
] | 1
|
2019-08-13T17:14:44.000Z
|
2019-08-13T17:14:44.000Z
|
from .context import make_context
| 17
| 33
| 0.852941
| 5
| 34
| 5.6
| 0.8
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.117647
| 34
| 1
| 34
| 34
| 0.933333
| 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
| 1
| 0
|
0
| 6
|
9b3711a4fb939f0a50c722b198735ce956fa3703
| 21
|
py
|
Python
|
example_project/some_modules/third_modules/a190.py
|
Yuriy-Leonov/cython_imports_limit_issue
|
2f9e7c02798fb52185dabfe6ce3811c439ca2839
|
[
"MIT"
] | null | null | null |
example_project/some_modules/third_modules/a190.py
|
Yuriy-Leonov/cython_imports_limit_issue
|
2f9e7c02798fb52185dabfe6ce3811c439ca2839
|
[
"MIT"
] | null | null | null |
example_project/some_modules/third_modules/a190.py
|
Yuriy-Leonov/cython_imports_limit_issue
|
2f9e7c02798fb52185dabfe6ce3811c439ca2839
|
[
"MIT"
] | null | null | null |
class A190:
pass
| 7
| 11
| 0.619048
| 3
| 21
| 4.333333
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.214286
| 0.333333
| 21
| 2
| 12
| 10.5
| 0.714286
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0.5
| 0
| 0
| 0.5
| 0
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 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
| 6
|
9bc061242e89e288381c8f51decfe64c0b75c99e
| 42
|
py
|
Python
|
foundation/backend/controller/__init__.py
|
tbone255/foundation
|
ca76fdd9b5345fead2d200f829eb67ba77bc865e
|
[
"MIT"
] | null | null | null |
foundation/backend/controller/__init__.py
|
tbone255/foundation
|
ca76fdd9b5345fead2d200f829eb67ba77bc865e
|
[
"MIT"
] | null | null | null |
foundation/backend/controller/__init__.py
|
tbone255/foundation
|
ca76fdd9b5345fead2d200f829eb67ba77bc865e
|
[
"MIT"
] | null | null | null |
from .base import *
from .mixins import *
| 14
| 21
| 0.714286
| 6
| 42
| 5
| 0.666667
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.190476
| 42
| 2
| 22
| 21
| 0.882353
| 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
| 1
| 0
|
0
| 6
|
fd04296d1b05a985d19e1b4136854d50622d799b
| 25
|
py
|
Python
|
app/gws/gis/ows/formats/__init__.py
|
ewie/gbd-websuite
|
6f2814c7bb64d11cb5a0deec712df751718fb3e1
|
[
"Apache-2.0"
] | 3
|
2020-07-24T10:10:18.000Z
|
2022-03-16T10:22:04.000Z
|
app/gws/gis/ows/formats/__init__.py
|
ewie/gbd-websuite
|
6f2814c7bb64d11cb5a0deec712df751718fb3e1
|
[
"Apache-2.0"
] | 28
|
2020-03-03T17:35:58.000Z
|
2021-07-12T12:05:47.000Z
|
app/gws/gis/ows/formats/__init__.py
|
ewie/gbd-websuite
|
6f2814c7bb64d11cb5a0deec712df751718fb3e1
|
[
"Apache-2.0"
] | 1
|
2021-02-22T14:32:10.000Z
|
2021-02-22T14:32:10.000Z
|
from .reader import read
| 12.5
| 24
| 0.8
| 4
| 25
| 5
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.16
| 25
| 1
| 25
| 25
| 0.952381
| 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
| 1
| 0
|
0
| 6
|
fd1d5c75a3a62125e830256fc8e3446e8bba7601
| 22
|
py
|
Python
|
SPGPylibs/PHItools/cmilos/__init__.py
|
vivivum/SPGPylibs
|
29b3ecd4de522fe98dd423928a861d9bc75f2c18
|
[
"MIT"
] | 3
|
2021-04-22T10:10:49.000Z
|
2021-10-19T09:11:34.000Z
|
SPGPylibs/PHItools/cmilos/__init__.py
|
vivivum/SPGPylibs
|
29b3ecd4de522fe98dd423928a861d9bc75f2c18
|
[
"MIT"
] | null | null | null |
SPGPylibs/PHItools/cmilos/__init__.py
|
vivivum/SPGPylibs
|
29b3ecd4de522fe98dd423928a861d9bc75f2c18
|
[
"MIT"
] | 3
|
2021-04-22T10:15:58.000Z
|
2022-03-11T18:48:47.000Z
|
from .pymilos import *
| 22
| 22
| 0.772727
| 3
| 22
| 5.666667
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.136364
| 22
| 1
| 22
| 22
| 0.894737
| 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
| 1
| 0
|
0
| 6
|
fd28de1a9ce8108223d8442cfcbfe4e99046b99e
| 2,795
|
py
|
Python
|
tests/test_fn.py
|
shigeyukioba/matchernet
|
5aec7abd3b157846ca406e3c5103e3a1bebc711e
|
[
"Apache-2.0"
] | 1
|
2020-02-26T13:34:23.000Z
|
2020-02-26T13:34:23.000Z
|
tests/test_fn.py
|
shigeyukioba/matchernet
|
5aec7abd3b157846ca406e3c5103e3a1bebc711e
|
[
"Apache-2.0"
] | 39
|
2019-11-28T07:48:48.000Z
|
2020-05-23T14:13:38.000Z
|
tests/test_fn.py
|
shigeyukioba/matchernet
|
5aec7abd3b157846ca406e3c5103e3a1bebc711e
|
[
"Apache-2.0"
] | 1
|
2020-05-22T05:11:14.000Z
|
2020-05-22T05:11:14.000Z
|
import unittest
import numpy as np
from matchernet.fn import LinearFn, LinearFnXU
class TestLinearFn(unittest.TestCase):
def setUp(self):
self.x = np.array([10, 20, 30], dtype=np.float32)
self.test_A_patterns = [
np.array([[1, 2, 3], [4, 5, 6]], dtype=np.float32),
np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]], dtype=np.float32),
np.array([[1, 2, np.inf]], dtype=np.float32)
]
def test_linear_dot(self):
for A in self.test_A_patterns:
f = LinearFn(A)
expected_dot = np.dot(A, self.x)
with self.subTest():
actual_dot = f.value(self.x)
self.assertIsNone(np.testing.assert_array_equal(expected_dot, actual_dot))
def test_linear_x(self):
for A in self.test_A_patterns:
f = LinearFn(A)
expected_dx = A
with self.subTest():
actual_dx = f.x(self.x)
self.assertIsNone(np.testing.assert_array_equal(expected_dx, actual_dx))
class TestLinearFnXU(unittest.TestCase):
def setUp(self):
self.x = np.array([10, 20, 30], dtype=np.float32)
self.u = np.array([5, 15, 25], dtype=np.float32)
self.test_A_patterns = [
np.array([[1, 2, 3], [4, 5, 6]], dtype=np.float32),
np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]], dtype=np.float32),
np.array([[1, 2, np.inf]], dtype=np.float32)
]
self.test_B_patterns = [
np.array([[6, 5, 4], [3, 2, 1]], dtype=np.float32),
np.array([[9, 8, 7], [6, 5, 4], [3, 2, 1]], dtype=np.float32),
np.array([[np.inf, 2, 3]], dtype=np.float32)
]
def test_linear_XU_dot(self):
for A, B in zip(self.test_A_patterns, self.test_B_patterns):
f = LinearFnXU(A, B)
expected_dot = np.dot(A, self.x) + np.dot(B, self.u)
with self.subTest():
actual_dot = f.value(self.x, self.u)
self.assertIsNone(np.testing.assert_array_equal(expected_dot, actual_dot))
def test_linear_XU_dx(self):
for A, B in zip(self.test_A_patterns, self.test_B_patterns):
f = LinearFnXU(A, B)
expected_dx = A
with self.subTest():
actual_dx = f.x(self.x, self.u)
self.assertIsNone(np.testing.assert_array_equal(expected_dx, actual_dx))
def test_linear_XU_du(self):
for A, B in zip(self.test_A_patterns, self.test_B_patterns):
f = LinearFnXU(A, B)
expected_du = B
with self.subTest():
actual_du = f.u(self.x, self.u)
self.assertIsNone(np.testing.assert_array_equal(expected_du, actual_du))
if __name__ == '__main__':
unittest.main()
| 37.266667
| 90
| 0.557424
| 408
| 2,795
| 3.639706
| 0.151961
| 0.056566
| 0.113131
| 0.080135
| 0.835017
| 0.82963
| 0.802694
| 0.783838
| 0.783838
| 0.783838
| 0
| 0.046891
| 0.298032
| 2,795
| 74
| 91
| 37.77027
| 0.70999
| 0
| 0
| 0.532258
| 0
| 0
| 0.002862
| 0
| 0
| 0
| 0
| 0
| 0.080645
| 1
| 0.112903
| false
| 0
| 0.048387
| 0
| 0.193548
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 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
| 6
|
fd29f602fa879061823bb996d136f3494cdcded3
| 164
|
py
|
Python
|
src/pyprerender/__init__.py
|
thingiesmm/pyprerender
|
b990e2916977fe7281b97d505e3c3e7b7777fa96
|
[
"MIT"
] | 3
|
2020-07-28T17:19:09.000Z
|
2020-09-11T01:56:42.000Z
|
src/pyprerender/__init__.py
|
thingiesmm/pyprerender
|
b990e2916977fe7281b97d505e3c3e7b7777fa96
|
[
"MIT"
] | null | null | null |
src/pyprerender/__init__.py
|
thingiesmm/pyprerender
|
b990e2916977fe7281b97d505e3c3e7b7777fa96
|
[
"MIT"
] | null | null | null |
from pyprerender.Chrome import Chrome
from pyprerender.BaseEventHandler import BaseEventHandler
from pyprerender.ParseHTMLEventHandler import ParseHTMLEventHandler
| 41
| 67
| 0.908537
| 15
| 164
| 9.933333
| 0.4
| 0.302013
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.073171
| 164
| 3
| 68
| 54.666667
| 0.980263
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 6
|
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