Datasets:
xszheng2020
/
the_stack_dedup_python_hits_5

Dataset card Data Studio Files
xet
Community
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
a93a2fbb98ba25230620d5665acaa51b8ee8dcfc
204
py
Python
sources/losses.py
mocurin/itis-lab-01
29c32a348600d8580684aa026b4f92a93244304b
[ "MIT" ]
null
null
null
sources/losses.py
mocurin/itis-lab-01
29c32a348600d8580684aa026b4f92a93244304b
[ "MIT" ]
null
null
null
sources/losses.py
mocurin/itis-lab-01
29c32a348600d8580684aa026b4f92a93244304b
[ "MIT" ]
null
null
null
"""Common loss functions package""" from typing import Callable # Type hinting Loss = Callable[[float, float], float] def difference(result: float, target: float) -> float: return target - result
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a93c3dc7ec9385cb761e3e9d18968da66458b74e
94
py
Python
app/auth.py
gomes-fdr/test-avidity
7bf3d1ce12fdcd118b2691e31b0345f9801c6ff1
[ "MIT" ]
null
null
null
app/auth.py
gomes-fdr/test-avidity
7bf3d1ce12fdcd118b2691e31b0345f9801c6ff1
[ "MIT" ]
null
null
null
app/auth.py
gomes-fdr/test-avidity
7bf3d1ce12fdcd118b2691e31b0345f9801c6ff1
[ "MIT" ]
null
null
null
import os def setup(): os.environ['PUBLIC_KEY'] = '' os.environ['PRIVATE_KEY'] = ''
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a94789e377e1c6d164ea509c145e1f73e513639f
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py
Python
Exercise10.py
JBCFurtado/Rabiscos_Em_Python
a1a5be9391e1bbbb301b8a7776043f7ea77e24da
[ "MIT" ]
null
null
null
Exercise10.py
JBCFurtado/Rabiscos_Em_Python
a1a5be9391e1bbbb301b8a7776043f7ea77e24da
[ "MIT" ]
null
null
null
Exercise10.py
JBCFurtado/Rabiscos_Em_Python
a1a5be9391e1bbbb301b8a7776043f7ea77e24da
[ "MIT" ]
null
null
null
for i in range(2004, 2097, 4): print(i)
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a953f0a75123c0639cdfb7e1683c1feb21b80492
78
py
Python
tests/conftest.py
wayfair-incubator/gbq
6843c999a9969c3a70c562b43efb349f2adc4ad6
[ "MIT" ]
6
2021-01-16T00:56:39.000Z
2022-01-01T18:19:54.000Z
tests/conftest.py
wayfair-incubator/gbq
6843c999a9969c3a70c562b43efb349f2adc4ad6
[ "MIT" ]
229
2021-01-14T17:36:41.000Z
2022-03-31T08:09:43.000Z
tests/conftest.py
wayfair-incubator/gbq
6843c999a9969c3a70c562b43efb349f2adc4ad6
[ "MIT" ]
1
2022-02-04T07:44:28.000Z
2022-02-04T07:44:28.000Z
import pytest # noqa: F401 from tests.fixtures import * # noqa: F403, F401
19.5
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a956e5a1d3e1c84351357d9c9408f16ab16d0889
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py
Python
examples/mitigation_examples/michaelsDemandSettingsRunner.py
supermihi/scgen
844144b8fb59de6a81c305ebcf0e39cf5af7c01d
[ "MIT" ]
1
2020-07-29T13:48:32.000Z
2020-07-29T13:48:32.000Z
examples/mitigation_examples/michaelsDemandSettingsRunner.py
supermihi/scgen
844144b8fb59de6a81c305ebcf0e39cf5af7c01d
[ "MIT" ]
2
2020-11-17T20:27:57.000Z
2021-01-11T15:41:10.000Z
examples/mitigation_examples/michaelsDemandSettingsRunner.py
supermihi/scgen
844144b8fb59de6a81c305ebcf0e39cf5af7c01d
[ "MIT" ]
1
2020-11-16T12:59:40.000Z
2020-11-16T12:59:40.000Z
from examples.exampleRunner import runExample runExample("mitigation_examples/michaelsDemandSettings.json")
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a961c1c3c646c915821478c5b1adb25590f1308f
46
py
Python
gamesystem/__init__.py
raymag/GameSystem
30cc4a174913e639a157edd830d73a73f5b5629b
[ "MIT" ]
3
2020-07-22T16:40:03.000Z
2021-08-18T08:39:40.000Z
gamesystem/__init__.py
raymag/GameSystem
30cc4a174913e639a157edd830d73a73f5b5629b
[ "MIT" ]
36
2020-07-24T11:18:41.000Z
2020-08-05T21:51:51.000Z
gamesystem/__init__.py
raymag/GameSystem
30cc4a174913e639a157edd830d73a73f5b5629b
[ "MIT" ]
null
null
null
# from .character import Attributes, Character
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5
a97e22499bb105457941bb858f47aef0fb8ca624
6,497
py
Python
asm_6502/parsetab.py
CyberZHG/mos-6502-restricted-assembler
a492a82dc9cc30225264fe777180aad5d0b4201a
[ "MIT" ]
null
null
null
asm_6502/parsetab.py
CyberZHG/mos-6502-restricted-assembler
a492a82dc9cc30225264fe777180aad5d0b4201a
[ "MIT" ]
null
null
null
asm_6502/parsetab.py
CyberZHG/mos-6502-restricted-assembler
a492a82dc9cc30225264fe777180aad5d0b4201a
[ "MIT" ]
null
null
null
# parsetab.py # This file is automatically generated. Do not edit. # pylint: disable=W,C,R _tabversion = '3.10' _lr_method = 'LALR' _lr_signature = "left+-leftCUR/rightUMINUSBIN BIT CHAR CUR DEC HEX KEYWORD LABEL NEWLINE PSEUDO REGISTERstat : LABEL KEYWORD stat_valstat : KEYWORD stat_valstat : stat NEWLINE statstat :stat_val : REGISTERstat_val : arithmeticstat_val :stat_val : '(' arithmetic ')'stat_val : arithmetic ',' REGISTERstat_val : '(' arithmetic ',' REGISTER ')'stat_val : '(' arithmetic ')' ',' REGISTERstat_val : BIT arithmeticstat_val : '#' arithmeticstat_val : arithmetic_listarithmetic_list : arithmetic ',' arithmetic_list\n | arithmeticarithmetic : '-' arithmetic %prec UMINUSarithmetic : integerarithmetic : LABELarithmetic : CURarithmetic : '[' arithmetic ']'arithmetic : arithmetic '+' arithmetic\n | arithmetic '-' arithmetic\n | arithmetic CUR arithmetic\n | arithmetic '/' arithmetic\n integer : DEC\n | HEX\n | BIN\n | CHAR\n " _lr_action_items = {'LABEL':([0,3,4,5,9,10,11,13,17,24,25,26,27,28,44,],[2,15,2,15,15,15,15,15,15,15,15,15,15,15,15,]),'KEYWORD':([0,2,4,],[3,5,3,]),'NEWLINE':([0,1,3,4,5,6,7,8,12,14,15,16,18,19,20,21,22,23,30,31,32,34,35,36,37,38,39,40,41,43,47,48,],[-4,4,-7,-4,-7,-2,-5,-6,-14,-18,-19,-20,-26,-27,-28,-29,4,-1,-12,-13,-17,-16,-9,-15,-22,-23,-24,-25,-8,-21,-11,-10,]),'$end':([0,1,3,4,5,6,7,8,12,14,15,16,18,19,20,21,22,23,30,31,32,34,35,36,37,38,39,40,41,43,47,48,],[-4,0,-7,-4,-7,-2,-5,-6,-14,-18,-19,-20,-26,-27,-28,-29,-3,-1,-12,-13,-17,-16,-9,-15,-22,-23,-24,-25,-8,-21,-11,-10,]),'REGISTER':([3,5,24,42,45,],[7,7,35,46,47,]),'(':([3,5,],[9,9,]),'BIT':([3,5,],[10,10,]),'#':([3,5,],[11,11,]),'-':([3,5,8,9,10,11,13,14,15,16,17,18,19,20,21,24,25,26,27,28,29,30,31,32,33,34,37,38,39,40,43,44,],[13,13,26,13,13,13,13,-18,-19,-20,13,-26,-27,-28,-29,13,13,13,13,13,26,26,26,-17,26,26,-22,-23,-24,-25,-21,13,]),'CUR':([3,5,8,9,10,11,13,14,15,16,17,18,19,20,21,24,25,26,27,28,29,30,31,32,33,34,37,38,39,40,43,44,],[16,16,27,16,16,16,16,-18,-19,-20,16,-26,-27,-28,-29,16,16,16,16,16,27,27,27,-17,27,27,27,27,-24,-25,-21,16,]),'[':([3,5,9,10,11,13,17,24,25,26,27,28,44,],[17,17,17,17,17,17,17,17,17,17,17,17,17,]),'DEC':([3,5,9,10,11,13,17,24,25,26,27,28,44,],[18,18,18,18,18,18,18,18,18,18,18,18,18,]),'HEX':([3,5,9,10,11,13,17,24,25,26,27,28,44,],[19,19,19,19,19,19,19,19,19,19,19,19,19,]),'BIN':([3,5,9,10,11,13,17,24,25,26,27,28,44,],[20,20,20,20,20,20,20,20,20,20,20,20,20,]),'CHAR':([3,5,9,10,11,13,17,24,25,26,27,28,44,],[21,21,21,21,21,21,21,21,21,21,21,21,21,]),',':([8,14,15,16,18,19,20,21,29,32,34,37,38,39,40,41,43,],[24,-18,-19,-20,-26,-27,-28,-29,42,-17,44,-22,-23,-24,-25,45,-21,]),'+':([8,14,15,16,18,19,20,21,29,30,31,32,33,34,37,38,39,40,43,],[25,-18,-19,-20,-26,-27,-28,-29,25,25,25,-17,25,25,-22,-23,-24,-25,-21,]),'/':([8,14,15,16,18,19,20,21,29,30,31,32,33,34,37,38,39,40,43,],[28,-18,-19,-20,-26,-27,-28,-29,28,28,28,-17,28,28,28,28,-24,-25,-21,]),')':([14,15,16,18,19,20,21,29,32,37,38,39,40,43,46,],[-18,-19,-20,-26,-27,-28,-29,41,-17,-22,-23,-24,-25,-21,48,]),']':([14,15,16,18,19,20,21,32,33,37,38,39,40,43,],[-18,-19,-20,-26,-27,-28,-29,-17,43,-22,-23,-24,-25,-21,]),} _lr_action = {} for _k, _v in _lr_action_items.items(): for _x,_y in zip(_v[0],_v[1]): if not _x in _lr_action: _lr_action[_x] = {} _lr_action[_x][_k] = _y del _lr_action_items _lr_goto_items = {'stat':([0,4,],[1,22,]),'stat_val':([3,5,],[6,23,]),'arithmetic':([3,5,9,10,11,13,17,24,25,26,27,28,44,],[8,8,29,30,31,32,33,34,37,38,39,40,34,]),'arithmetic_list':([3,5,24,44,],[12,12,36,36,]),'integer':([3,5,9,10,11,13,17,24,25,26,27,28,44,],[14,14,14,14,14,14,14,14,14,14,14,14,14,]),} _lr_goto = {} for _k, _v in _lr_goto_items.items(): for _x, _y in zip(_v[0], _v[1]): if not _x in _lr_goto: _lr_goto[_x] = {} _lr_goto[_x][_k] = _y del _lr_goto_items _lr_productions = [ ("S' -> stat","S'",1,None,None,None), ('stat -> LABEL KEYWORD stat_val','stat',3,'p_stat_with_label','grammar.py',226), ('stat -> KEYWORD stat_val','stat',2,'p_stat_without_label','grammar.py',232), ('stat -> stat NEWLINE stat','stat',3,'p_stat_repeat','grammar.py',238), ('stat -> <empty>','stat',0,'p_stat_empty','grammar.py',244), ('stat_val -> REGISTER','stat_val',1,'p_stat_val_accumulator','grammar.py',250), ('stat_val -> arithmetic','stat_val',1,'p_stat_val_direct','grammar.py',260), ('stat_val -> <empty>','stat_val',0,'p_stat_val_empty','grammar.py',266), ('stat_val -> ( arithmetic )','stat_val',3,'p_stat_val_indirect','grammar.py',272), ('stat_val -> arithmetic , REGISTER','stat_val',3,'p_stat_val_indexed','grammar.py',278), ('stat_val -> ( arithmetic , REGISTER )','stat_val',5,'p_stat_val_indexed_indirect','grammar.py',287), ('stat_val -> ( arithmetic ) , REGISTER','stat_val',5,'p_stat_val_indirect_indexed','grammar.py',296), ('stat_val -> BIT arithmetic','stat_val',2,'p_stat_val_immediate_bit','grammar.py',305), ('stat_val -> # arithmetic','stat_val',2,'p_stat_val_immediate','grammar.py',320), ('stat_val -> arithmetic_list','stat_val',1,'p_stat_val_list','grammar.py',326), ('arithmetic_list -> arithmetic , arithmetic_list','arithmetic_list',3,'p_arithmetic_list','grammar.py',332), ('arithmetic_list -> arithmetic','arithmetic_list',1,'p_arithmetic_list','grammar.py',333), ('arithmetic -> - arithmetic','arithmetic',2,'p_arithmetic_uminus','grammar.py',342), ('arithmetic -> integer','arithmetic',1,'p_arithmetic_direct','grammar.py',351), ('arithmetic -> LABEL','arithmetic',1,'p_arithmetic_label','grammar.py',357), ('arithmetic -> CUR','arithmetic',1,'p_arithmetic_cur','grammar.py',363), ('arithmetic -> [ arithmetic ]','arithmetic',3,'p_arithmetic_paren','grammar.py',369), ('arithmetic -> arithmetic + arithmetic','arithmetic',3,'p_arithmetic_binary_op','grammar.py',375), ('arithmetic -> arithmetic - arithmetic','arithmetic',3,'p_arithmetic_binary_op','grammar.py',376), ('arithmetic -> arithmetic CUR arithmetic','arithmetic',3,'p_arithmetic_binary_op','grammar.py',377), ('arithmetic -> arithmetic / arithmetic','arithmetic',3,'p_arithmetic_binary_op','grammar.py',378), ('integer -> DEC','integer',1,'p_integer','grammar.py',402), ('integer -> HEX','integer',1,'p_integer','grammar.py',403), ('integer -> BIN','integer',1,'p_integer','grammar.py',404), ('integer -> CHAR','integer',1,'p_integer','grammar.py',405), ]
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a9916a6c7d77d5a1cea5f581480327693daee89b
58,640
py
Python
fn_misp/fn_misp/util/customize.py
rudimeyer/resilient-community-apps
7a46841ba41fa7a1c421d4b392b0a3ca9e36bd00
[ "MIT" ]
1
2020-08-25T03:43:07.000Z
2020-08-25T03:43:07.000Z
fn_misp/fn_misp/util/customize.py
rudimeyer/resilient-community-apps
7a46841ba41fa7a1c421d4b392b0a3ca9e36bd00
[ "MIT" ]
1
2019-07-08T16:57:48.000Z
2019-07-08T16:57:48.000Z
fn_misp/fn_misp/util/customize.py
rudimeyer/resilient-community-apps
7a46841ba41fa7a1c421d4b392b0a3ca9e36bd00
[ "MIT" ]
null
null
null
# -*- coding: utf-8 -*- """Generate the Resilient customizations required for fn_misp""" from __future__ import print_function from resilient_circuits.util import * def codegen_reload_data(): """Parameters to codegen used to generate the fn_misp package""" reload_params = {"package": u"fn_misp", "incident_fields": [u"misp_event_id"], "action_fields": [], "function_params": [u"misp_analysis_level", u"misp_attribute_type", u"misp_attribute_value", u"misp_distribution", u"misp_event_id", u"misp_event_name", u"misp_sighting", u"misp_threat_level"], "datatables": [], "message_destinations": [u"fn_misp"], "functions": [u"misp_create_attribute", u"misp_create_event", u"misp_create_sighting", u"misp_search_attribute", u"misp_sighting_list"], "phases": [], "automatic_tasks": [], "scripts": [], "workflows": [u"example_misp_create_attribute", u"example_misp_create_event", u"example_misp_create_sighting", u"example_misp_search_attribute", u"example_misp_sighting_list"], "actions": [u"Example: Create MISP Attribute", u"Example: Create MISP Event", u"Example: Create MISP Sighting", u"Example: MISP Search Attribute", u"Example: MISP Sighting List"] } return reload_params def customization_data(client=None): """Produce any customization definitions (types, fields, message destinations, etc) that should be installed by `resilient-circuits customize` """ # This import data contains: # Incident fields: # misp_event_id # Function inputs: # misp_analysis_level # misp_attribute_type # misp_attribute_value # misp_distribution # misp_event_id # misp_event_name # misp_sighting # misp_threat_level # Message Destinations: # fn_misp # Functions: # misp_create_attribute # misp_create_event # misp_create_sighting # misp_search_attribute # misp_sighting_list # Workflows: # example_misp_create_attribute # example_misp_create_event # example_misp_create_sighting # example_misp_search_attribute # example_misp_sighting_list # Rules: # Example: Create MISP Attribute # Example: Create MISP Event # Example: Create MISP Sighting # Example: MISP Search Attribute # Example: MISP Sighting List yield ImportDefinition(u""" eyJzZXJ2ZXJfdmVyc2lvbiI6IHsibWFqb3IiOiAzMSwgIm1pbm9yIjogMCwgImJ1aWxkX251bWJl ciI6IDQyNTQsICJ2ZXJzaW9uIjogIjMxLjAuNDI1NCJ9LCAiZXhwb3J0X2Zvcm1hdF92ZXJzaW9u IjogMiwgImlkIjogMTksICJleHBvcnRfZGF0ZSI6IDE1NTM0NDg0OTU4ODQsICJmaWVsZHMiOiBb eyJpZCI6IDI3OSwgIm5hbWUiOiAibWlzcF9ldmVudF9pZCIsICJ0ZXh0IjogIk1JU1AgRXZlbnQg SWQiLCAicHJlZml4IjogInByb3BlcnRpZXMiLCAidHlwZV9pZCI6IDAsICJ0b29sdGlwIjogIiIs ICJwbGFjZWhvbGRlciI6ICIiLCAiaW5wdXRfdHlwZSI6ICJ0ZXh0IiwgImhpZGVfbm90aWZpY2F0 aW9uIjogZmFsc2UsICJjaG9zZW4iOiBmYWxzZSwgImRlZmF1bHRfY2hvc2VuX2J5X3NlcnZlciI6 IGZhbHNlLCAiYmxhbmtfb3B0aW9uIjogZmFsc2UsICJpbnRlcm5hbCI6IGZhbHNlLCAidXVpZCI6 ICJkMTdmYWVkMC0yMjAyLTQwMjYtOGY1Ni1hMTI3YThkNGE5ODAiLCAib3BlcmF0aW9ucyI6IFtd LCAib3BlcmF0aW9uX3Blcm1zIjoge30sICJ2YWx1ZXMiOiBbXSwgInJlYWRfb25seSI6IGZhbHNl LCAiY2hhbmdlYWJsZSI6IHRydWUsICJyaWNoX3RleHQiOiBmYWxzZSwgImV4cG9ydF9rZXkiOiAi 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a99e3bfc49def14162d05a4c84b5c54435af2582
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py
Python
utils/hook_rull_export_v3.py
jinghao1/Dongtai-Base-Image
8f5de833cdc3dab6822a990663a201d3325dffd7
[ "Apache-2.0" ]
null
null
null
utils/hook_rull_export_v3.py
jinghao1/Dongtai-Base-Image
8f5de833cdc3dab6822a990663a201d3325dffd7
[ "Apache-2.0" ]
null
null
null
utils/hook_rull_export_v3.py
jinghao1/Dongtai-Base-Image
8f5de833cdc3dab6822a990663a201d3325dffd7
[ "Apache-2.0" ]
null
null
null
###################################################################### # @author : bidaya0 (bidaya0@$HOSTNAME) # @file : hook_type_rull_sql # @created : 星期五 10月 22, 2021 21:41:12 CST # # @description : ###################################################################### with open('complitejava.sql', 'r') as fp: sql = fp.readlines() hook_type_dict = {} hook_strategy_pair = [] hook_strategy_dict = {} for i in sql: if i.startswith( 'INSERT INTO iast_hook_type (id, `type`, name, value, create_time, update_time, created_by, enable, name_en, name_zh, language_id, strategy_id) VALUES(' ): a = i.replace( 'INSERT INTO iast_hook_type (id, `type`, name, value, create_time, update_time, created_by, enable, name_en, name_zh, language_id, strategy_id) VALUES(', '').replace(');\n', '') id_, type_, name, value, create_time, update_time, created_by, enable, name_en, name_zh, language_id, strategy_id = res = a.split( ',') print(res) hook_type_dict[int(id_)] ='''INSERT IGNORE INTO `iast_hook_type` (`type`, `name`, `value`, `create_time` , `update_time`, `created_by`, `enable`, `name_en`, `name_zh` , `language_id`) SELECT {type_}, {name}, {value}, {create_time} , {update_time}, {created_by}, {enable}, {name_en}, {name_zh} , {language_id} FROM DUAL WHERE NOT EXISTS (SELECT `id` FROM iast_hook_type WHERE `type`={type_} AND `name`= {name} AND value = {value} AND update_time={update_time} AND create_time={create_time} AND `created_by`={created_by} AND enable = {enable} AND name_en = {name_en}AND name_zh = {name_zh} AND language_id = {language_id} LIMIT 1); SET @HOOK_TYPE_ID = (SELECT `id` FROM iast_hook_type WHERE `type`={type_} AND `name`= {name} AND value = {value} AND update_time={update_time} AND create_time={create_time} AND `created_by`={created_by} AND enable = {enable} AND name_en = {name_en}AND name_zh = {name_zh} AND language_id = {language_id} LIMIT 1); '''.format( type_=type_, name=name, value=value, create_time=create_time, update_time=update_time, created_by=created_by, enable=enable, name_en=name_en, name_zh=name_zh, language_id=language_id) elif i.startswith( 'INSERT INTO iast_hook_strategy (id, value, source, target, inherit, track, create_time, update_time, created_by, enable) VALUES(' ): a = i.replace( 'INSERT INTO iast_hook_strategy (id, value, source, target, inherit, track, create_time, update_time, created_by, enable) VALUES(', '').replace(');', '') print(a.split(',')) id_, value, source, target, inherit, track, create_time, update_time, created_by, enable = res = a.split( ',') print(res) hook_strategy_dict[int(id_)] = '''INSERT IGNORE INTO iast_hook_strategy (value, source, target, inherit, track, create_time, update_time, created_by, enable) SELECT {value}, {source}, {target}, {inherit}, {track}, {create_time}, {update_time}, {created_by}, {enable} FROM DUAL WHERE NOT EXISTS (SELECT `id` FROM iast_hook_strategy WHERE `value`={value} AND `source`={source} AND `target`={target} AND `inherit`={inherit} AND `track`={track} AND `create_time`= {create_time} AND `update_time`= {update_time} AND `created_by`={created_by} AND `enable` = {enable} LIMIT 1); SET @IAST_HOOK_STRATEGY_ID = (SELECT `id` FROM iast_hook_strategy WHERE `value`={value} AND `source`={source} AND `target`={target} AND `inherit`={inherit} AND `track`={track} AND `create_time`= {create_time} AND `update_time`= {update_time} AND `created_by`={created_by} AND `enable` = {enable} LIMIT 1); '''.format(value=value, source=source, target=target, inherit=inherit, track=track, create_time=create_time, update_time=update_time, created_by=created_by, enable=enable) elif i.startswith( 'INSERT INTO iast_hook_strategy_type (id, hookstrategy_id, hooktype_id) VALUES(' ): a = i.replace( 'INSERT INTO iast_hook_strategy_type (id, hookstrategy_id, hooktype_id) VALUES(', '').replace(');', '') id_, hookstrategy_id, hooktype_id = res = a.split(',') hook_strategy_pair.append([int(hookstrategy_id), int(hooktype_id)]) for k, v in hook_strategy_pair: res = hook_type_dict[int(v)] print(hook_strategy_dict[int(k)]) print( 'INSERT INTO iast_hook_strategy_type (hookstrategy_id, hooktype_id) VALUES (@IAST_HOOK_STRATEGY_ID, @HOOK_TYPE_ID);' )
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5
8d319d0d34c2d81f3d45a5a600bb6bc28b50033c
5,067
py
Python
Morocco model/dashboard/scripts/read_data.py
KTH-dESA/FAO
74459217a9e8ad8107b1d3a96fd52eebd93daebd
[ "MIT" ]
3
2020-09-17T11:12:52.000Z
2021-03-31T09:24:02.000Z
Morocco model/dashboard/scripts/read_data.py
KTH-dESA/FAO
74459217a9e8ad8107b1d3a96fd52eebd93daebd
[ "MIT" ]
101
2019-10-02T10:16:28.000Z
2021-06-05T06:42:55.000Z
Morocco model/dashboard/scripts/read_data.py
KTH-dESA/FAO
74459217a9e8ad8107b1d3a96fd52eebd93daebd
[ "MIT" ]
2
2020-02-23T13:28:00.000Z
2021-03-31T10:02:46.000Z
import os.path import pandas as pd import yaml import boto3, gzip from decouple import config from_server = True server = 'souss-massa-project' AWS_ACCESS_ID = config('AWS_ACCESS_ID') AWS_SECRET_KEY = config('AWS_SECRET_KEY') AWS_REGION = config('AWS_REGION') resource = boto3.resource( 's3', aws_access_key_id=AWS_ACCESS_ID, aws_secret_access_key=AWS_SECRET_KEY, region_name=AWS_REGION ) def get_path(path, from_server): if from_server: return ('/').join(path) else: return os.path.join(*path) def load_summary_data(path, name, from_server=from_server): if from_server: path = server return pd.read_csv(get_path([path, 'data', name], from_server)) # def load_data(path, scenario, climate, phaseout_year, pv_level, # files='all', from_server=from_server): # if from_server: # path = server # init_year = 2020 # end_year = 2050 # butane_scenario = f'{phaseout_year}' if phaseout_year != 2050 else 'None' # if not climate: # climate = ['Trend'] # data = get_path([path, 'data', scenario, climate[0]], from_server) # # lcoe = os.path.join(data_folder, scenario, climate[0], level) # # if files == 'all': # files = ['results.gz', 'wwtp_data.gz', 'desal_data.gz', # 'butane.gz', 'production_data.gz'] # # if isinstance(files, str): # files = [files] # # if len(files) == 1: # if files[0] == 'butane.gz': # dff = pd.read_csv(get_path([data, # 'Butane Calculations', # butane_scenario, # f'{pv_level}', # files[0]], from_server)) # else: # dff = pd.read_csv(get_path([data, files[0]], from_server)) # # dff = dff.loc[(dff.Year >= init_year) & (dff.Year <= end_year)] # output = dff # else: # output = [] # for file in files: # if file == 'butane.gz': # dff = pd.read_csv(get_path([data, # 'Butane Calculations', # butane_scenario, # f'{pv_level}', # file], from_server)) # else: # dff = pd.read_csv(get_path([data, file], from_server)) # # dff = dff.loc[(dff.Year >= init_year) & (dff.Year <= end_year)] # output.append(dff) # return output def load_data(path, scenario, climate, phaseout_year, pv_level, files='all', from_server=from_server): if from_server: path = server butane_scenario = f'{phaseout_year}' if phaseout_year != 2050 else 'None' if not climate: climate = ['Trend'] data = get_path(['data', scenario, climate[0]], from_server) if files == 'all': files = ['results.gz', 'wwtp_data.gz', 'desal_data.gz', 'butane.gz', 'production_data.gz'] if isinstance(files, str): files = [files] if len(files) == 1: if files[0] == 'butane.gz': obj = resource.Object(server, get_path([data, 'Butane Calculations', butane_scenario, f'{pv_level}', files[0]], from_server)) with gzip.GzipFile(fileobj=obj.get()["Body"]) as gzipfile: dff = pd.read_csv(gzipfile) else: obj = resource.Object(server, get_path([data, files[0]], from_server)) with gzip.GzipFile(fileobj=obj.get()["Body"]) as gzipfile: dff = pd.read_csv(gzipfile) #dff = dff.loc[(dff.Year >= init_year) & (dff.Year <= end_year)] output = dff else: output = [] for file in files: if file == 'butane.gz': obj = resource.Object(server, get_path([data, 'Butane Calculations', butane_scenario, f'{pv_level}', file], from_server)) with gzip.GzipFile(fileobj=obj.get()["Body"]) as gzipfile: dff = pd.read_csv(gzipfile) else: obj = resource.Object(server, get_path([data, file], from_server)) with gzip.GzipFile(fileobj=obj.get()["Body"]) as gzipfile: dff = pd.read_csv(gzipfile) #dff = dff.loc[(dff.Year >= init_year) & (dff.Year <= end_year)] output.append(dff) return output def get_language(language): file = f"assets/{language}.yaml" with open(file, 'rt', encoding='utf8') as yml: language_dic = yaml.load(yml, Loader=yaml.FullLoader) return language_dic
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5
8d86af43f005efe8820d18d5bf4acfa93465fac9
247
py
Python
bot/core/models/sqlalchemy/DiscordServer.py
ah-khalil/PatriotDiscordBot
638ad16da60800bd399d81791f8ebc1625abf7e2
[ "MIT" ]
null
null
null
bot/core/models/sqlalchemy/DiscordServer.py
ah-khalil/PatriotDiscordBot
638ad16da60800bd399d81791f8ebc1625abf7e2
[ "MIT" ]
15
2020-07-14T15:04:20.000Z
2020-10-25T05:41:50.000Z
bot/core/models/sqlalchemy/DiscordServer.py
ah-khalil/PatriotDiscordBot
638ad16da60800bd399d81791f8ebc1625abf7e2
[ "MIT" ]
null
null
null
from bot.core.startup import Base from sqlalchemy import Column, Integer class DiscordServer(Base): __tablename__ = "Discord_Server" id = Column(Integer, autoincrement=True, primary_key=True) server_id = Column(Integer, unique=True)
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5
a5d22fea4a922833be76ca8d45fc80ac2890bfee
204
py
Python
exercises/01.python-for-everybody/chapter04/ex01.py
Fabricio-Lopees/computer-science-learning
e8cfcd468f9fdbaa1cacf803d0dade04a99eb19a
[ "MIT" ]
null
null
null
exercises/01.python-for-everybody/chapter04/ex01.py
Fabricio-Lopees/computer-science-learning
e8cfcd468f9fdbaa1cacf803d0dade04a99eb19a
[ "MIT" ]
null
null
null
exercises/01.python-for-everybody/chapter04/ex01.py
Fabricio-Lopees/computer-science-learning
e8cfcd468f9fdbaa1cacf803d0dade04a99eb19a
[ "MIT" ]
null
null
null
# Exercise 1: Run the program on your system and see what numbers you get. Run the program more than once and see what numbers you get. # random.randint(5, 10) import random; print(random.randint(5, 10));
51
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0.621622
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0.168831
0.220779
0.298701
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0.040936
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204
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0.859649
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0
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0
5
a5e066f343dc54655f3fe60f94a42a9e1a0ec602
629
py
Python
projects/ninety_nine_bottles.py
tteddy7/PythonProjects
d2b4f9d4575ecf9bb555d24361fb3a30ba12e625
[ "MIT" ]
3
2019-05-04T03:31:19.000Z
2022-01-16T07:53:42.000Z
projects/ninety_nine_bottles.py
tteddy7/PythonProjects
d2b4f9d4575ecf9bb555d24361fb3a30ba12e625
[ "MIT" ]
null
null
null
projects/ninety_nine_bottles.py
tteddy7/PythonProjects
d2b4f9d4575ecf9bb555d24361fb3a30ba12e625
[ "MIT" ]
null
null
null
"""99 bottles lyrics generator. By Ted Silbernagel """ if __name__ == '__main__': # Start at 99 and work backwards for i in range(99, 0, -1): if i == 2: print('2 bottles of beer on the wall, 2 bottles of beer!') print('Take one down, pass it around, 1 bottle of beer on the wall!') elif i == 1: print('1 bottle of beer on the wall, 1 bottle of beer!') print('Take it down, pass it around, no more bottles of beer on the wall!') else: print(f'{i} bottles of beer on the wall, {i} bottles of beer!') print(f'Take one down, pass it around, {i - 1} bottles of beer on the wall!')
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0.139535
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0.170543
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0.459948
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0
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0
0
1
0
5
573e782c80042976eba1a855e62901aa313d03de
6,943
py
Python
library/qqai/nlp.py
gbraad/awesome-mpython
b73c0cc710cf4b48c306172c54126040672561e0
[ "MIT" ]
17
2019-10-15T06:10:06.000Z
2022-03-25T02:09:04.000Z
library/qqai/nlp.py
gbraad/awesome-mpython
b73c0cc710cf4b48c306172c54126040672561e0
[ "MIT" ]
null
null
null
library/qqai/nlp.py
gbraad/awesome-mpython
b73c0cc710cf4b48c306172c54126040672561e0
[ "MIT" ]
7
2019-12-01T15:04:54.000Z
2021-12-21T09:15:03.000Z
from qqai.base import * class Nlp(QQAIBase): """自然语言""" def text_translate_ailab(self,text,type=0): """文本翻译（AI Lab）""" self.api = 'https://api.ai.qq.com/fcgi-bin/nlp/nlp_texttrans' self.params = {'app_id': self.app_id, 'time_stamp': self._time_stamp(), 'nonce_str': self._time_stamp(), 'type': type, 'text': text, } self.params['sign'] = self.get_sign(self.params) s = self.call_api(self.params) contants = s.read() s.close() return json.loads(contants) def text_translate_fanyi(self,text,source='auto', target='en'): """文本翻译（翻译君）""" self.api = 'https://api.ai.qq.com/fcgi-bin/nlp/nlp_texttranslate' self.params = {'app_id': self.app_id, 'time_stamp': self._time_stamp(), 'nonce_str': self._time_stamp(), 'text': text, 'source': source, 'target': target, } self.params['sign'] = self.get_sign(self.params) s = self.call_api(self.params) contants = s.read() s.close() return json.loads(contants) def text_detect(self, text,candidate_langs=None, force=0): """语种识别""" self.api = 'https://api.ai.qq.com/fcgi-bin/nlp/nlp_textdetect' if candidate_langs is None: candidate_langs = ['zh', 'en', 'jp', 'kr'] if type(candidate_langs) == str: candidate_langs_param = candidate_langs else: candidate_langs_param = '|'.join(candidate_langs) self.params = {'app_id': self.app_id, 'time_stamp': self._time_stamp(), 'nonce_str': self._time_stamp(), 'text': text, 'candidate_langs': candidate_langs_param, 'force': force } self.params['sign'] = self.get_sign(self.params) s = self.call_api(self.params) contants = s.read() s.close() return json.loads(contants) def image_translate(self,image_path, scene='doc', source='auto', target='auto'): """图片翻译""" self.api = 'https://api.ai.qq.com/fcgi-bin/nlp/nlp_imagetranslate' self.params = {'app_id': self.app_id, 'time_stamp': self._time_stamp(), 'nonce_str': self._time_stamp(), 'image': self.get_base64(image_path), 'session_id': self._time_stamp(), 'scene': scene, 'source': source, 'target': target, } self.params['sign'] = self.get_sign(self.params) s = self.call_api(self.params) contants = s.read() s.close() return json.loads(contants) def text_chat(self,question): """图片翻译""" self.api = 'https://api.ai.qq.com/fcgi-bin/nlp/nlp_textchat' self.params = {'app_id': self.app_id, 'time_stamp': self._time_stamp(), 'nonce_str': self._time_stamp(), 'session': self._time_stamp(), 'question': question } self.params['sign'] = self.get_sign(self.params) s = self.call_api(self.params) contants = s.read() s.close() return json.loads(contants) # class Text(QQAIBase): # """基础文本分析""" # def word_seg(self, text): # """"分词""" # self.api = 'https://api.ai.qq.com/fcgi-bin/nlp/nlp_wordseg' # self.params = {'app_id': self.app_id, # 'time_stamp': self._time_stamp(), # 'nonce_str': self._time_stamp(), # 'text': text # } # self.params['sign'] = self.get_sign(self.params) # s = self.call_api(self.params) # contants = s.read() # s.close() # return json.loads(contants) # def word_pos(self, text): # """"词性标注""" # self.api = 'https://api.ai.qq.com/fcgi-bin/nlp/nlp_wordpos' # self.params = {'app_id': self.app_id, # 'time_stamp': self._time_stamp(), # 'nonce_str': self._time_stamp(), # 'text': text # } # self.params['sign'] = self.get_sign(self.params) # s = self.call_api(self.params) # contants = s.read() # s.close() # return json.loads(contants) # def word_ner(self, text): # """"专有名词识别""" # self.api = 'https://api.ai.qq.com/fcgi-bin/nlp/nlp_wordner' # self.params = {'app_id': self.app_id, # 'time_stamp': self._time_stamp(), # 'nonce_str': self._time_stamp(), # 'text': text # } # self.params['sign'] = self.get_sign(self.params) # s = self.call_api(self.params) # contants = s.read() # s.close() # return json.loads(contants) # def word_syn(self, text): # """"同义词识别""" # self.api = 'https://api.ai.qq.com/fcgi-bin/nlp/nlp_wordsyn' # self.params = {'app_id': self.app_id, # 'time_stamp': self._time_stamp(), # 'nonce_str': self._time_stamp(), # 'text': text # } # self.params['sign'] = self.get_sign(self.params) # s = self.call_api(self.params) # contants = s.read() # s.close() # return json.loads(contants) # def word_com(self, text): # """"意图成分识别""" # self.api = 'https://api.ai.qq.com/fcgi-bin/nlp/nlp_wordcom' # self.params = {'app_id': self.app_id, # 'time_stamp': self._time_stamp(), # 'nonce_str': self._time_stamp(), # 'text': text # } # self.params['sign'] = self.get_sign(self.params) # s = self.call_api(self.params) # contants = s.read() # s.close() # return json.loads(contants) # def text_polar(self, text): # """"情感分析识别""" # self.api = 'https://api.ai.qq.com/fcgi-bin/nlp/nlp_textpolar' # self.params = {'app_id': self.app_id, # 'time_stamp': self._time_stamp(), # 'nonce_str': self._time_stamp(), # 'text': text # } # self.params['sign'] = self.get_sign(self.params) # s = self.call_api(self.params) # contants = s.read() # s.close() # return json.loads(contants)
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0.099016
0.052364
0.761028
0.761028
0.761028
0.761028
0.761028
0.761028
0
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0.373758
6,943
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0.064103
false
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0.012821
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py
Python
src/data/lookup.py
JoeIOU/metedata_fusion_tools
3cf45338c4ae28e043142bf728ee6c91749ff72e
[ "Apache-2.0" ]
null
null
null
src/data/lookup.py
JoeIOU/metedata_fusion_tools
3cf45338c4ae28e043142bf728ee6c91749ff72e
[ "Apache-2.0" ]
null
null
null
src/data/lookup.py
JoeIOU/metedata_fusion_tools
3cf45338c4ae28e043142bf728ee6c91749ff72e
[ "Apache-2.0" ]
null
null
null
# ######lookup.py # lookup多值或者选择其他实体，如客户、产品等 from mdata import metadata as md from privilege import user_mngt as ur from config.config import cfg as config logger = config.logger MD_LOOKUP_METADATA_ENTITY_NAME = "data_lookup_set" def insert_lookup_data(user_id, tenant_id, data_list): rr = md.get_md_entities_id_by_code([MD_LOOKUP_METADATA_ENTITY_NAME]) re = None if rr is not None and len(rr) > 0: entity_id = rr[0].get("md_entity_id") if entity_id is not None: re = md.insert_execute(user_id, tenant_id, entity_id, data_list) if re is None: logger.warning( "insert_lookup_data,insert nothing,tables=[{}],data:{}.".format(MD_LOOKUP_METADATA_ENTITY_NAME, data_list)) return re def update_lookup_data(user_id, tenant_id, md_entity_id, md_field_id, data_id, data_list): rr = md.get_md_entities_id_by_code([MD_LOOKUP_METADATA_ENTITY_NAME]) re = None entity_id = None if rr is not None and len(rr) > 0: entity_id = rr[0].get("md_entity_id") if data_list is None or len(data_list) <= 0: return None md_dict = data_list[0] if entity_id is not None: where_list = [] where_dict = {} where_dict["data_id"] = data_id where_dict["md_entity_id"] = md_entity_id where_dict["lookup_key"] = md_field_id where_list.append(where_dict) re = md.delete_execute(user_id, tenant_id, entity_id, where_list) re = md.insert_execute(user_id, tenant_id, entity_id, data_list) if re is None: logger.warning( "update_lookup_data,insert nothing,tables=[{}],data:{}.".format(MD_LOOKUP_METADATA_ENTITY_NAME, data_list)) return re def delete_lookup_data(user_id, tenant_id, md_entity_id, md_field_id, data_id): rr = md.get_md_entities_id_by_code([MD_LOOKUP_METADATA_ENTITY_NAME]) re = None entity_id = None if rr is not None and len(rr) > 0: entity_id = rr[0].get("md_entity_id") where_list = [] if entity_id is not None: where_dict = {} where_dict["data_id"] = data_id where_dict["md_entity_id"] = md_entity_id where_dict["lookup_key"] = md_field_id where_list.append(where_dict) re = md.delete_execute(user_id, tenant_id, entity_id, where_list) if re is None: logger.warning( "delete_lookup_data,insert nothing,tables=[{}],data:{}.".format(MD_LOOKUP_METADATA_ENTITY_NAME, where_list)) return re def query_lookup_data(user_id, tenant_id, where_dict): rr = md.get_md_entities_id_by_code([MD_LOOKUP_METADATA_ENTITY_NAME]) re = None if rr is not None and len(rr) > 0: entity_id = rr[0].get("md_entity_id") if entity_id is not None: re = md.query_execute(user_id, tenant_id, entity_id, where_dict) return re if __name__ == '__main__': # ##insert the lookup data user = ur.get_user("test1") user_id = user.get("user_id") tenant_id = user.get("tenant_id") data_list = [] data = {} md_entity_id = 30001 md_field_id = 40005 data_id = 800001 data["data_id"] = data_id data["md_entity_id"] = md_entity_id data["lookup_classify_id"] = 123 data["lookup_key"] = md_field_id data["lookup_value"] = "bbb" data_list.append(data) data = {} data["data_id"] = data_id data["md_entity_id"] = md_entity_id data["lookup_classify_id"] = 123 data["lookup_key"] = md_field_id data["lookup_value"] = "aaa" data_list.append(data) # insert_lookup_data(user_id, tenant_id,data_list) re = update_lookup_data(user_id, tenant_id, md_entity_id, md_field_id, data_id, data_list) # re = delete_lookup_data(user_id, tenant_id, md_entity_id, md_field_id, data_id) # ##query the lookup data where_dict = {"md_entity_id": 30041, "lookup_key": 40005} re1 = query_lookup_data(user_id, tenant_id, where_dict) logger.info("result:{}".format(re1))
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363
py
Python
multivar_horner/__init__.py
jannikmi/multivar_horner
7d385163e96ee29fd25404906b96432566f2e139
[ "MIT" ]
4
2021-08-18T23:44:59.000Z
2022-01-18T18:06:41.000Z
multivar_horner/__init__.py
jannikmi/multivar_horner
7d385163e96ee29fd25404906b96432566f2e139
[ "MIT" ]
3
2021-07-15T00:43:16.000Z
2021-12-13T09:28:57.000Z
multivar_horner/__init__.py
jannikmi/multivar_horner
7d385163e96ee29fd25404906b96432566f2e139
[ "MIT" ]
1
2022-02-15T06:38:15.000Z
2022-02-15T06:38:15.000Z
# -*- coding:utf-8 -*- from multivar_horner.classes.abstract_poly import load_pickle from multivar_horner.classes.horner_poly import HornerMultivarPolynomial, HornerMultivarPolynomialOpt from multivar_horner.classes.regular_poly import MultivarPolynomial __all__ = ["HornerMultivarPolynomial", "MultivarPolynomial", "HornerMultivarPolynomialOpt", "load_pickle"]
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9e065ba7319605d71b78592feb839970ce7c96f7
164
py
Python
contextlib2/_typeshed.py
jazzband/contextlib2
0828b5a3322a148de8fdaf7443fefda983e7e9c8
[ "PSF-2.0" ]
34
2016-07-28T15:05:28.000Z
2022-02-05T16:48:46.000Z
contextlib2/_typeshed.py
jazzband/contextlib2
0828b5a3322a148de8fdaf7443fefda983e7e9c8
[ "PSF-2.0" ]
39
2016-07-27T15:36:41.000Z
2022-01-10T12:49:55.000Z
contextlib2/_typeshed.py
jazzband/contextlib2
0828b5a3322a148de8fdaf7443fefda983e7e9c8
[ "PSF-2.0" ]
14
2016-07-30T09:24:42.000Z
2022-01-14T10:58:26.000Z
from typing import TypeVar # pragma: no cover # Use for "self" annotations: # def __enter__(self: Self) -> Self: ... Self = TypeVar("Self") # pragma: no cover
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9e1a1da7337a48b52127f42b2badbe53bbd69a77
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py
Python
office365/sharepoint/publishing/translation/translation_status.py
theodoriss/Office365-REST-Python-Client
3bd7a62dadcd3f0a0aceeaff7584fff3fd44886e
[ "MIT" ]
null
null
null
office365/sharepoint/publishing/translation/translation_status.py
theodoriss/Office365-REST-Python-Client
3bd7a62dadcd3f0a0aceeaff7584fff3fd44886e
[ "MIT" ]
null
null
null
office365/sharepoint/publishing/translation/translation_status.py
theodoriss/Office365-REST-Python-Client
3bd7a62dadcd3f0a0aceeaff7584fff3fd44886e
[ "MIT" ]
null
null
null
from office365.runtime.client_value import ClientValue from office365.sharepoint.base_entity import BaseEntity class TranslationStatus(ClientValue): pass class TranslationStatusCollection(BaseEntity): pass
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f50bb68b06f849cb13da15a8c57032913daa028d
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py
Python
activities/admin.py
studentisgss/booking
e0e28f42cf2a466688b4ea3787eb28dbc0980cac
[ "MIT" ]
7
2015-12-11T19:18:39.000Z
2020-10-30T12:50:19.000Z
activities/admin.py
studentisgss/booking
e0e28f42cf2a466688b4ea3787eb28dbc0980cac
[ "MIT" ]
119
2015-11-03T22:21:09.000Z
2021-03-17T21:36:49.000Z
activities/admin.py
studentisgss/booking
e0e28f42cf2a466688b4ea3787eb28dbc0980cac
[ "MIT" ]
null
null
null
from django.contrib import admin from activities.models import * # Register your models here. admin.site.register(Activity)
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f5337998a5f59d7b2a8dec69f03f1704e995b0ff
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py
Python
utils/text/__init__.py
goztrk/django-htk
c56bf112e5d627780d2f4288460eae5cce80fa9e
[ "MIT" ]
206
2015-10-15T07:05:08.000Z
2021-02-19T11:48:36.000Z
utils/text/__init__.py
goztrk/django-htk
c56bf112e5d627780d2f4288460eae5cce80fa9e
[ "MIT" ]
8
2017-10-16T10:18:31.000Z
2022-03-09T14:24:27.000Z
utils/text/__init__.py
goztrk/django-htk
c56bf112e5d627780d2f4288460eae5cce80fa9e
[ "MIT" ]
61
2015-10-15T08:12:44.000Z
2022-03-10T12:25:06.000Z
# HTK Imports from htk.utils.text.general import *
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f5542f400322baea2a9d1dbc793bd98147a0e62a
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py
Python
Alignment/LaserAlignment/test/createScenario.py
ckamtsikis/cmssw
ea19fe642bb7537cbf58451dcf73aa5fd1b66250
[ "Apache-2.0" ]
852
2015-01-11T21:03:51.000Z
2022-03-25T21:14:00.000Z
Alignment/LaserAlignment/test/createScenario.py
ckamtsikis/cmssw
ea19fe642bb7537cbf58451dcf73aa5fd1b66250
[ "Apache-2.0" ]
30,371
2015-01-02T00:14:40.000Z
2022-03-31T23:26:05.000Z
Alignment/LaserAlignment/test/createScenario.py
ckamtsikis/cmssw
ea19fe642bb7537cbf58451dcf73aa5fd1b66250
[ "Apache-2.0" ]
3,240
2015-01-02T05:53:18.000Z
2022-03-31T17:24:21.000Z
import FWCore.ParameterSet.Config as cms process = cms.Process( "createScenario" ) # source process.source = cms.Source( "EmptySource" ) process.maxEvents = cms.untracked.PSet( input = cms.untracked.int32( 1 ) ) # db output process.load( "CondCore.DBCommon.CondDBCommon_cfi" ) process.CondDBCommon.connect = 'sqlite_file:Alignments_S.db' process.PoolDBOutputService = cms.Service( "PoolDBOutputService", process.CondDBCommon, toPut = cms.VPSet( cms.PSet( record = cms.string( 'TrackerAlignmentRcd' ), tag = cms.string( 'Alignments' ) ), cms.PSet( record = cms.string( 'TrackerAlignmentErrorExtendedRcd' ), tag = cms.string( 'AlignmentErrorsExtended' ) ) ) ) # geometry process.load( "Geometry.CMSCommonData.cmsIdealGeometryXML_cfi" ) process.load( "Geometry.TrackerNumberingBuilder.trackerNumberingGeometry_cfi" ) process.misalignmentProducer = cms.ESProducer("MisalignedTrackerESProducer", seed = cms.int32( 123456 ), saveToDbase = cms.untracked.bool( True ), distribution = cms.string( 'fixed' ), # 'gaussian' or 'fixed' or... ## TIB+ TIB2 = cms.PSet( dY = cms.double( 0.0 ), dX = cms.double( 0.0 ), phiXlocal = cms.double( 0.000 ), phiYlocal = cms.double( 0.000 ), phiZlocal = cms.double( 0.000 ) ), ## TIB- TIB1 = cms.PSet( dY = cms.double( 0.0 ), dX = cms.double( 0.0 ), phiXlocal = cms.double( 0.000 ), phiYlocal = cms.double( 0.000 ), phiZlocal = cms.double( 0.000 ) ), ## TOB+ TOB2 = cms.PSet( dY = cms.double( 0.0 ), dX = cms.double( 0.0 ), phiXlocal = cms.double( 0.000 ), phiYlocal = cms.double( 0.000 ), phiZlocal = cms.double( 0.000 ) ), ## TOB- TOB1 = cms.PSet( dY = cms.double( 0.0 ), dX = cms.double( 0.0 ), phiXlocal = cms.double( 0.000 ), phiYlocal = cms.double( 0.000 ), phiZlocal = cms.double( 0.000 ) ), ## TEC+ TEC1 = cms.PSet( phiXlocal = cms.double( 0.0 ), phiYlocal = cms.double( 0.0 ), phiZlocal = cms.double( 0.0 ), dX = cms.double( 0.0 ), dY = cms.double( 0.0 ), TECDisk1 = cms.PSet( dX = cms.double( 0.0 ), dY = cms.double( 0.0 ), phiZlocal = cms.double( 0.000 ) ), TECDisk2 = cms.PSet( dX = cms.double( 0.0 ), dY = cms.double( 0.0 ), phiZlocal = cms.double( 0.000 ) ), TECDisk3 = cms.PSet( dX = cms.double( 0.0 ), dY = cms.double( 0.0 ), phiZlocal = cms.double( 0.000 ) ), TECDisk4 = cms.PSet( dX = cms.double( 0.0 ), dY = cms.double( 0.0 ), phiZlocal = cms.double( 0.000 ) ), TECDisk5 = cms.PSet( dX = cms.double( 0.0 ), dY = cms.double( 0.0 ), phiZlocal = cms.double( 0.000 ) ), TECDisk6 = cms.PSet( dX = cms.double( 0.0 ), dY = cms.double( 0.0 ), phiZlocal = cms.double( 0.000 ) ), TECDisk7 = cms.PSet( dX = cms.double( 0.0 ), dY = cms.double( 0.0 ), phiZlocal = cms.double( 0.000 ) ), TECDisk8 = cms.PSet( dX = cms.double( 0.0 ), dY = cms.double( 0.0 ), phiZlocal = cms.double( 0.000 ) ), TECDisk9 = cms.PSet( dX = cms.double( 0.0 ), dY = cms.double( 0.0 ), phiZlocal = cms.double( 0.000 ) ) ), ## TEC- TEC2 = cms.PSet( phiXlocal = cms.double( 0.0 ), phiYlocal = cms.double( 0.0 ), phiZlocal = cms.double( 0.0 ), dX = cms.double( 0.0 ), dY = cms.double( 0.0 ), TECDisk1 = cms.PSet( dX = cms.double( 0.0 ), dY = cms.double( 0.0 ), phiZlocal = cms.double( 0.000 ) ), TECDisk2 = cms.PSet( dX = cms.double( 0.0 ), dY = cms.double( 0.0 ), phiZlocal = cms.double( 0.000 ) ), TECDisk3 = cms.PSet( dX = cms.double( 0.0 ), dY = cms.double( 0.0 ), phiZlocal = cms.double( 0.000 ) ), TECDisk4 = cms.PSet( dX = cms.double( 0.0 ), dY = cms.double( 0.0 ), phiZlocal = cms.double( 0.000 ) ), TECDisk5 = cms.PSet( dX = cms.double( 0.0 ), dY = cms.double( 0.0 ), phiZlocal = cms.double( 0.000 ) ), TECDisk6 = cms.PSet( dX = cms.double( 0.0 ), dY = cms.double( 0.0 ), phiZlocal = cms.double( 0.000 ) ), TECDisk7 = cms.PSet( dX = cms.double( 0.0 ), dY = cms.double( 0.0 ), phiZlocal = cms.double( 0.000 ) ), TECDisk8 = cms.PSet( dX = cms.double( 0.0 ), dY = cms.double( 0.0 ), phiZlocal = cms.double( 0.000 ) ), TECDisk9 = cms.PSet( dX = cms.double( 0.0 ), dY = cms.double( 0.0 ), phiZlocal = cms.double( 0.000 ) ) ) ) process.test = cms.EDAnalyzer( "TestAnalyzer", fileName = cms.untracked.string( 'misaligned.root' ) ) process.p1 = cms.Path( process.test )
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py
Python
gokart/__init__.py
saya-kawakami/gokart
a3fb3d57741957e1e74c4757b86a111f7e2c82fd
[ "MIT" ]
null
null
null
gokart/__init__.py
saya-kawakami/gokart
a3fb3d57741957e1e74c4757b86a111f7e2c82fd
[ "MIT" ]
null
null
null
gokart/__init__.py
saya-kawakami/gokart
a3fb3d57741957e1e74c4757b86a111f7e2c82fd
[ "MIT" ]
null
null
null
from gokart.info import make_tree_info, tree_info from gokart.pandas_type_config import PandasTypeConfig from gokart.parameter import ExplicitBoolParameter, ListTaskInstanceParameter, TaskInstanceParameter from gokart.run import run from gokart.task import TaskOnKart from gokart.testing import test_run from gokart.workspace_management import delete_local_unnecessary_outputs
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py
Python
tests/integration/runtimes/test_network_failures.py
sthagen/jina-ai-jina
a854da4f7cbafcf5d699a505dacfa4f27014fb62
[ "Apache-2.0" ]
null
null
null
tests/integration/runtimes/test_network_failures.py
sthagen/jina-ai-jina
a854da4f7cbafcf5d699a505dacfa4f27014fb62
[ "Apache-2.0" ]
null
null
null
tests/integration/runtimes/test_network_failures.py
sthagen/jina-ai-jina
a854da4f7cbafcf5d699a505dacfa4f27014fb62
[ "Apache-2.0" ]
null
null
null
import multiprocessing import time import pytest from jina import Client, Document, Executor, requests from jina.parsers import set_gateway_parser, set_pod_parser from jina.serve.runtimes.asyncio import AsyncNewLoopRuntime from jina.serve.runtimes.gateway.http import HTTPGatewayRuntime from jina.serve.runtimes.worker import WorkerRuntime from .test_runtimes import _create_gateway_runtime, _create_head_runtime class DummyExec(Executor): @requests(on='/foo') def foo(self, *args, **kwargs): pass def _create_worker_runtime(port, name='', executor=None): args = set_pod_parser().parse_args([]) args.port = port args.uses = 'DummyExec' args.name = name if executor: args.uses = executor with WorkerRuntime(args) as runtime: runtime.run_forever() def _create_worker(port): # create a single worker runtime p = multiprocessing.Process(target=_create_worker_runtime, args=(port,)) p.start() time.sleep(0.1) return p def _create_gateway(port, graph, pod_addr, protocol, retries=-1): # create a single worker runtime # create a single gateway runtime p = multiprocessing.Process( target=_create_gateway_runtime, args=(graph, pod_addr, port, protocol, retries), ) p.start() time.sleep(0.1) return p def _create_head(port, connection_list_dict, polling, retries=-1): p = multiprocessing.Process( target=_create_head_runtime, args=(port, connection_list_dict, 'head', polling, None, None, retries), ) p.start() time.sleep(0.1) return p def _send_request(gateway_port, protocol): """send request to gateway and see what happens""" c = Client(host='localhost', port=gateway_port, protocol=protocol) return c.post( '/foo', inputs=[Document(text='hi') for _ in range(2)], request_size=1, return_responses=True, ) def _test_error(gateway_port, error_ports, protocol): if not isinstance(error_ports, list): error_ports = [error_ports] with pytest.raises(ConnectionError) as err_info: # assert correct error is thrown _send_request(gateway_port, protocol) # assert error message contains the port(s) of the broken executor(s) for port in error_ports: assert str(port) in err_info.value.args[0] @pytest.mark.parametrize( 'fail_before_endpoint_discovery', [True, False] ) # if not before, then after @pytest.mark.parametrize('protocol', ['http', 'websocket', 'grpc']) @pytest.mark.asyncio async def test_runtimes_headless_topology( port_generator, protocol, fail_before_endpoint_discovery ): # create gateway and workers manually, then terminate worker process to provoke an error worker_port = port_generator() gateway_port = port_generator() graph_description = '{"start-gateway": ["pod0"], "pod0": ["end-gateway"]}' pod_addresses = f'{{"pod0": ["0.0.0.0:{worker_port}"]}}' worker_process = _create_worker(worker_port) gateway_process = _create_gateway( gateway_port, graph_description, pod_addresses, protocol ) time.sleep(1.0) AsyncNewLoopRuntime.wait_for_ready_or_shutdown( timeout=5.0, ctrl_address=f'0.0.0.0:{worker_port}', ready_or_shutdown_event=multiprocessing.Event(), ) AsyncNewLoopRuntime.wait_for_ready_or_shutdown( timeout=5.0, ctrl_address=f'0.0.0.0:{gateway_port}', ready_or_shutdown_event=multiprocessing.Event(), ) if ( fail_before_endpoint_discovery ): # kill worker before having sent the first request, so before endpoint discov. worker_process.terminate() worker_process.join() try: if fail_before_endpoint_discovery: # here worker is already dead before the first request, so endpoint discovery will fail # ----------- 1. test that useful errors are given when endpoint discovery fails ----------- # we have to do this in a new process because otherwise grpc will be sad and everything will crash :( p = multiprocessing.Process( target=_test_error, args=(gateway_port, worker_port, protocol) ) p.start() p.join() assert ( p.exitcode == 0 ) # if exitcode != 0 then test in other process did not pass and this should fail else: # just ping the Flow without having killed a worker before. This (also) performs endpoint discovery p = multiprocessing.Process( target=_send_request, args=(gateway_port, protocol) ) p.start() p.join() # only now do we kill the worker, after having performed successful endpoint discovery # so in this case, the actual request will fail, not the discovery, which is handled differently by Gateway worker_process.terminate() # kill worker worker_process.join() assert not worker_process.is_alive() # ----------- 2. test that gateways remain alive ----------- # just do the same again, expecting the same failure p = multiprocessing.Process( target=_test_error, args=(gateway_port, worker_port, protocol) ) p.start() p.join() assert ( p.exitcode == 0 ) # if exitcode != 0 then test in other process did not pass and this should fail except Exception: assert False finally: # clean up runtimes gateway_process.terminate() worker_process.terminate() gateway_process.join() worker_process.join() @pytest.mark.parametrize('protocol', ['grpc', 'http', 'websocket']) @pytest.mark.asyncio async def test_runtimes_replicas(port_generator, protocol): # create gateway and workers manually, then terminate worker process to provoke an error worker_ports = [port_generator() for _ in range(3)] worker0_port, worker1_port, worker2_port = worker_ports gateway_port = port_generator() graph_description = '{"start-gateway": ["pod0"], "pod0": ["end-gateway"]}' pod_addresses = f'{{"pod0": ["0.0.0.0:{worker0_port}", "0.0.0.0:{worker1_port}", "0.0.0.0:{worker2_port}"]}}' worker_processes = [] for p in worker_ports: worker_processes.append(_create_worker(p)) time.sleep(0.1) AsyncNewLoopRuntime.wait_for_ready_or_shutdown( timeout=5.0, ctrl_address=f'0.0.0.0:{p}', ready_or_shutdown_event=multiprocessing.Event(), ) gateway_process = _create_gateway( gateway_port, graph_description, pod_addresses, protocol ) AsyncNewLoopRuntime.wait_for_ready_or_shutdown( timeout=5.0, ctrl_address=f'0.0.0.0:{gateway_port}', ready_or_shutdown_event=multiprocessing.Event(), ) worker_processes[0].terminate() # kill 'middle' worker worker_processes[0].join() try: # await _send_request(gateway_port, protocol) # ----------- 1. test that useful errors are given ----------- # we have to do this in a new process because otherwise grpc will be sad and everything will crash :( p = multiprocessing.Process( target=_test_error, args=(gateway_port, worker0_port, protocol) ) p.start() p.join() assert ( p.exitcode == 0 ) # if exitcode != 0 then test in other process did not pass and this should fail # no retry in the case with replicas, because round robin retry mechanism will pick different replica now except Exception: assert False finally: # clean up runtimes gateway_process.terminate() gateway_process.join() for p in worker_processes: p.terminate() p.join() @pytest.mark.parametrize('terminate_head', [True, False]) @pytest.mark.parametrize('protocol', ['http', 'websocket', 'grpc']) @pytest.mark.asyncio async def test_runtimes_headful_topology(port_generator, protocol, terminate_head): # create gateway and workers manually, then terminate worker process to provoke an error worker_port = port_generator() gateway_port = port_generator() head_port = port_generator() graph_description = '{"start-gateway": ["pod0"], "pod0": ["end-gateway"]}' pod_addresses = f'{{"pod0": ["0.0.0.0:{head_port}"]}}' connection_list_dict = {'0': [f'127.0.0.1:{worker_port}']} head_process = _create_head(head_port, connection_list_dict, 'ANY') worker_process = _create_worker(worker_port) gateway_process = _create_gateway( gateway_port, graph_description, pod_addresses, protocol ) time.sleep(1.0) AsyncNewLoopRuntime.wait_for_ready_or_shutdown( timeout=5.0, ctrl_address=f'0.0.0.0:{head_port}', ready_or_shutdown_event=multiprocessing.Event(), ) AsyncNewLoopRuntime.wait_for_ready_or_shutdown( timeout=5.0, ctrl_address=f'0.0.0.0:{worker_port}', ready_or_shutdown_event=multiprocessing.Event(), ) AsyncNewLoopRuntime.wait_for_ready_or_shutdown( timeout=5.0, ctrl_address=f'0.0.0.0:{gateway_port}', ready_or_shutdown_event=multiprocessing.Event(), ) # terminate pod, either head or worker behind the head if terminate_head: head_process.terminate() head_process.join() error_port = head_port else: worker_process.terminate() # kill worker worker_process.join() error_port = worker_port error_port = ( head_port if protocol == 'websocket' else error_port ) # due to error msg length constraints ws will always report the head address try: # ----------- 1. test that useful errors are given ----------- # we have to do this in a new process because otherwise grpc will be sad and everything will crash :( p = multiprocessing.Process( target=_test_error, args=(gateway_port, error_port, protocol) ) p.start() p.join() assert ( p.exitcode == 0 ) # if exitcode != 0 then test in other process did not pass and this should fail # ----------- 2. test that gateways remain alive ----------- # just do the same again, expecting the same outcome p = multiprocessing.Process( target=_test_error, args=(gateway_port, error_port, protocol) ) p.start() p.join() assert ( p.exitcode == 0 ) # if exitcode != 0 then test in other process did not pass and this should fail except Exception: raise finally: # clean up runtimes gateway_process.terminate() worker_process.terminate() head_process.terminate() gateway_process.join() worker_process.join() head_process.join() def _send_gql_request(gateway_port): """send request to gateway and see what happens""" mutation = ( f'mutation {{' + '''docs(data: {text: "abcd"}) { id } } ''' ) c = Client(host='localhost', port=gateway_port, protocol='http') return c.mutate(mutation=mutation) def _test_gql_error(gateway_port, error_port): with pytest.raises(ConnectionError) as err_info: # assert correct error is thrown _send_gql_request(gateway_port) # assert error message contains useful info assert str(error_port) in err_info.value.args[0] def _create_gqlgateway_runtime(graph_description, pod_addresses, port): with HTTPGatewayRuntime( set_gateway_parser().parse_args( [ '--graph-description', graph_description, '--deployments-addresses', pod_addresses, '--port', str(port), '--expose-graphql-endpoint', ] ) ) as runtime: runtime.run_forever() def _create_gqlgateway(port, graph, pod_addr): # create a single worker runtime # create a single gateway runtime p = multiprocessing.Process( target=_create_gqlgateway_runtime, args=(graph, pod_addr, port), ) p.start() time.sleep(0.1) return p @pytest.mark.asyncio async def test_runtimes_graphql(port_generator): # create gateway and workers manually, then terminate worker process to provoke an error protocol = 'http' worker_port = port_generator() gateway_port = port_generator() graph_description = '{"start-gateway": ["pod0"], "pod0": ["end-gateway"]}' pod_addresses = f'{{"pod0": ["0.0.0.0:{worker_port}"]}}' worker_process = _create_worker(worker_port) gateway_process = _create_gqlgateway(gateway_port, graph_description, pod_addresses) time.sleep(1.0) AsyncNewLoopRuntime.wait_for_ready_or_shutdown( timeout=5.0, ctrl_address=f'0.0.0.0:{worker_port}', ready_or_shutdown_event=multiprocessing.Event(), ) AsyncNewLoopRuntime.wait_for_ready_or_shutdown( timeout=5.0, ctrl_address=f'0.0.0.0:{gateway_port}', ready_or_shutdown_event=multiprocessing.Event(), ) worker_process.terminate() # kill worker worker_process.join() try: # ----------- 1. test that useful errors are given ----------- # we have to do this in a new process because otherwise grpc will be sad and everything will crash :( p = multiprocessing.Process( target=_test_gql_error, args=(gateway_port, worker_port) ) p.start() p.join() assert ( p.exitcode == 0 ) # if exitcode != 0 then test in other process did not pass and this should fail # ----------- 2. test that gateways remain alive ----------- # just do the same again, expecting the same outcome p = multiprocessing.Process( target=_test_gql_error, args=(gateway_port, worker_port) ) p.start() p.join() assert ( p.exitcode == 0 ) # if exitcode != 0 then test in other process did not pass and this should fail except Exception: raise finally: # clean up runtimes gateway_process.terminate() worker_process.terminate() gateway_process.join() worker_process.join() @pytest.mark.asyncio async def test_replica_retry(port_generator): # test that if one replica is down, the other replica(s) will be used # create gateway and workers manually, then terminate worker process to provoke an error worker_ports = [port_generator() for _ in range(3)] worker0_port, worker1_port, worker2_port = worker_ports gateway_port = port_generator() graph_description = '{"start-gateway": ["pod0"], "pod0": ["end-gateway"]}' pod_addresses = f'{{"pod0": ["0.0.0.0:{worker0_port}", "0.0.0.0:{worker1_port}", "0.0.0.0:{worker2_port}"]}}' worker_processes = [] for p in worker_ports: worker_processes.append(_create_worker(p)) time.sleep(0.1) AsyncNewLoopRuntime.wait_for_ready_or_shutdown( timeout=5.0, ctrl_address=f'0.0.0.0:{p}', ready_or_shutdown_event=multiprocessing.Event(), ) gateway_process = _create_gateway( gateway_port, graph_description, pod_addresses, 'grpc' ) AsyncNewLoopRuntime.wait_for_ready_or_shutdown( timeout=5.0, ctrl_address=f'0.0.0.0:{gateway_port}', ready_or_shutdown_event=multiprocessing.Event(), ) try: # ----------- 1. ping Flow once to trigger endpoint discovery ----------- # we have to do this in a new process because otherwise grpc will be sad and everything will crash :( p = multiprocessing.Process(target=_send_request, args=(gateway_port, 'grpc')) p.start() p.join() assert p.exitcode == 0 # kill second worker, which would be responsible for the second call (round robin) worker_processes[1].terminate() worker_processes[1].join() # ----------- 2. test that redundant replicas take over ----------- # we have to do this in a new process because otherwise grpc will be sad and everything will crash :( p = multiprocessing.Process(target=_send_request, args=(gateway_port, 'grpc')) p.start() p.join() assert p.exitcode == 0 except Exception: assert False finally: # clean up runtimes gateway_process.terminate() gateway_process.join() for p in worker_processes: p.terminate() p.join() @pytest.mark.asyncio async def test_replica_retry_all_fail(port_generator): # test that if one replica is down, the other replica(s) will be used # create gateway and workers manually, then terminate worker process to provoke an error worker_ports = [port_generator() for _ in range(3)] worker0_port, worker1_port, worker2_port = worker_ports gateway_port = port_generator() graph_description = '{"start-gateway": ["pod0"], "pod0": ["end-gateway"]}' pod_addresses = f'{{"pod0": ["0.0.0.0:{worker0_port}", "0.0.0.0:{worker1_port}", "0.0.0.0:{worker2_port}"]}}' worker_processes = [] for p in worker_ports: worker_processes.append(_create_worker(p)) time.sleep(0.1) AsyncNewLoopRuntime.wait_for_ready_or_shutdown( timeout=5.0, ctrl_address=f'0.0.0.0:{p}', ready_or_shutdown_event=multiprocessing.Event(), ) gateway_process = _create_gateway( gateway_port, graph_description, pod_addresses, 'grpc' ) AsyncNewLoopRuntime.wait_for_ready_or_shutdown( timeout=5.0, ctrl_address=f'0.0.0.0:{gateway_port}', ready_or_shutdown_event=multiprocessing.Event(), ) try: # ----------- 1. ping Flow once to trigger endpoint discovery ----------- # we have to do this in a new process because otherwise grpc will be sad and everything will crash :( p = multiprocessing.Process(target=_send_request, args=(gateway_port, 'grpc')) p.start() p.join() assert p.exitcode == 0 # kill all workers for p in worker_processes: p.terminate() p.join() # ----------- 2. test that call fails with informative error message ----------- # we have to do this in a new process because otherwise grpc will be sad and everything will crash :( p = multiprocessing.Process( target=_test_error, args=(gateway_port, worker_ports, 'grpc') ) p.start() p.join() assert p.exitcode == 0 except Exception: assert False finally: # clean up runtimes gateway_process.terminate() gateway_process.join() for p in worker_processes: p.terminate() p.join() def _test_custom_retry(gateway_port, error_ports, protocol, retries, capfd): with pytest.raises(ConnectionError) as err_info: _send_request(gateway_port, protocol) out, err = capfd.readouterr() if retries > 0: # do as many retries as specified for i in range(retries): assert f'retry attempt {i+1}/{retries}' in out elif retries == 0: # do no retries assert 'retry attempt' not in out elif retries < 0: # use default retry policy, doing at least 3 retries for i in range(3): assert f'retry attempt {i+1}' in out @pytest.mark.parametrize('retries', [-1, 0, 5]) def test_custom_num_retries(port_generator, retries, capfd): # test that the user can set the number of grpc retries for failed calls # if negative number is given, test that default policy applies: hit every replica at least once # create gateway and workers manually, then terminate worker process to provoke an error num_replicas = 3 worker_ports = [port_generator() for _ in range(num_replicas)] worker0_port, worker1_port, worker2_port = worker_ports gateway_port = port_generator() graph_description = '{"start-gateway": ["pod0"], "pod0": ["end-gateway"]}' pod_addresses = f'{{"pod0": ["0.0.0.0:{worker0_port}", "0.0.0.0:{worker1_port}", "0.0.0.0:{worker2_port}"]}}' worker_processes = [] for p in worker_ports: worker_processes.append(_create_worker(p)) time.sleep(0.1) AsyncNewLoopRuntime.wait_for_ready_or_shutdown( timeout=5.0, ctrl_address=f'0.0.0.0:{p}', ready_or_shutdown_event=multiprocessing.Event(), ) gateway_process = _create_gateway( gateway_port, graph_description, pod_addresses, 'grpc', retries=retries ) AsyncNewLoopRuntime.wait_for_ready_or_shutdown( timeout=5.0, ctrl_address=f'0.0.0.0:{gateway_port}', ready_or_shutdown_event=multiprocessing.Event(), ) try: # ----------- 1. ping Flow once to trigger endpoint discovery ----------- # we have to do this in a new process because otherwise grpc will be sad and everything will crash :( p = multiprocessing.Process(target=_send_request, args=(gateway_port, 'grpc')) p.start() p.join() assert p.exitcode == 0 # kill all workers for p in worker_processes: p.terminate() p.join() # ----------- 2. test that call will be retried the appropriate number of times ----------- # we have to do this in a new process because otherwise grpc will be sad and everything will crash :( p = multiprocessing.Process( target=_test_custom_retry, args=(gateway_port, worker_ports, 'grpc', retries, capfd), ) p.start() p.join() assert p.exitcode == 0 except Exception: assert False finally: # clean up runtimes gateway_process.terminate() gateway_process.join() for p in worker_processes: p.terminate() p.join() @pytest.mark.parametrize('retries', [-1, 0, 5]) def test_custom_num_retries_headful(port_generator, retries, capfd): # create gateway and workers manually, then terminate worker process to provoke an error worker_port = port_generator() gateway_port = port_generator() head_port = port_generator() graph_description = '{"start-gateway": ["pod0"], "pod0": ["end-gateway"]}' pod_addresses = f'{{"pod0": ["0.0.0.0:{head_port}"]}}' connection_list_dict = {'0': [f'127.0.0.1:{worker_port}']} head_process = _create_head(head_port, connection_list_dict, 'ANY', retries=retries) worker_process = _create_worker(worker_port) gateway_process = _create_gateway( gateway_port, graph_description, pod_addresses, 'grpc', retries=retries ) time.sleep(1.0) AsyncNewLoopRuntime.wait_for_ready_or_shutdown( timeout=5.0, ctrl_address=f'0.0.0.0:{head_port}', ready_or_shutdown_event=multiprocessing.Event(), ) AsyncNewLoopRuntime.wait_for_ready_or_shutdown( timeout=5.0, ctrl_address=f'0.0.0.0:{worker_port}', ready_or_shutdown_event=multiprocessing.Event(), ) AsyncNewLoopRuntime.wait_for_ready_or_shutdown( timeout=5.0, ctrl_address=f'0.0.0.0:{gateway_port}', ready_or_shutdown_event=multiprocessing.Event(), ) try: # ----------- 1. ping Flow once to trigger endpoint discovery ----------- # we have to do this in a new process because otherwise grpc will be sad and everything will crash :( p = multiprocessing.Process(target=_send_request, args=(gateway_port, 'grpc')) p.start() p.join() assert p.exitcode == 0 # kill worker worker_process.terminate() worker_process.join() # ----------- 2. test that call will be retried the appropriate number of times ----------- # we have to do this in a new process because otherwise grpc will be sad and everything will crash :( p = multiprocessing.Process( target=_test_custom_retry, args=(gateway_port, worker_port, 'grpc', retries, capfd), ) p.start() p.join() assert p.exitcode == 0 except Exception: assert False finally: # clean up runtimes gateway_process.terminate() gateway_process.join() worker_process.terminate() worker_process.join() head_process.terminate() head_process.join()
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27558141d96366819dc3a1908d66fccfc565ce32
11,752
py
Python
src/cluster_eval.py
Mohamed-Ibrahim-124/Image-Segmentaion
ef203b22ba98603f62c1b5e1b99b05cb03db21c1
[ "MIT" ]
null
null
null
src/cluster_eval.py
Mohamed-Ibrahim-124/Image-Segmentaion
ef203b22ba98603f62c1b5e1b99b05cb03db21c1
[ "MIT" ]
null
null
null
src/cluster_eval.py
Mohamed-Ibrahim-124/Image-Segmentaion
ef203b22ba98603f62c1b5e1b99b05cb03db21c1
[ "MIT" ]
null
null
null
import resource_reader as reader from kmeans import kmeans, draw_clusters from spectral_clustering import _spectral_clustering, rbf, knn, normalize from eval import fmeasure, conditional_entropy import numpy as np from os import path, makedirs, environ from itertools import islice, tee from scipy.misc import imshow, imread, imresize KMEANS_DIR = "../kmeans_eval" SPECTRAL_DIR = "../spectral_eval" def _evaluate_kmeans(dir, data, ground_truth, name, resolution, k_clusters, recompute=False): """ Apply kmeans on given data then evaluate f-measure and conditional entropy for given ground truths. :param dir: path for directory to store output :type dir: str :param data: data samples :type data: np.matrix, shape(n_samples, n_features) :param ground_truth: iterator for ground truths obtained from resource reader :type ground_truth: iterator :param name: file name to store data output :type name: str :param resolution: image resolution :type resolution: int :param k_clusters: number of clusters :type k_clusters: int :param recompute: force compute assignments and evaluation files even if they already exist. :type recompute: bool """ assert path.exists(dir), 'Given directory is not found' assigns_file = path.join(dir, name) + '_' + str(resolution) + '.npy' eval_file = path.join(dir, name) + '_' + str(resolution) + '.eval' if not path.exists(assigns_file) or not path.exists(eval_file) or recompute: # computing and saving assignments _, assigns = kmeans(data, k=k_clusters) del _, data np.save(assigns_file, assigns) # computing and saving evaluations f_measures = [] entropies = [] for seg, _ in ground_truth: seg = seg.flatten() f_measures.append(fmeasure(assigns, seg)) entropies.append(conditional_entropy(assigns, seg)) f_measures = np.asarray(f_measures) entropies = np.asarray(entropies) np.savetxt(eval_file, np.vstack((f_measures, entropies))) def _evaluate_spectral(dir, data, ground_truth, name, resolution, k_clusters, sim_func, sim_arg, recompute=False): """ Apply Spectral Clustering on given data then evaluate f-measure and conditional entropy for given ground truths. :param temp_dir: path for directory to store output :type temp_dir: str :param data: data samples :type data: np.matrix, shape(n_samples, n_features) :param ground_truth: iterator for ground truths obtained from resource reader :type ground_truth: iterator :param name: file name to store data output :type name: str :param resolution: image resolution :type resolution: int :param k_clusters: numbers of clusters :type k_clusters: list(int) :param sim_func: can be rbf or knn :type sim_func: function :param sim_arg: gammas in case of rbf or n_neighbours in case of knn :type sim_arg: list(float) for gamma, list(int) for n_neighbours :param recompute: force compute assignments and evaluation files even if they already exist. :type recompute: bool """ for arg in sim_arg: eigen_vectors = None for k in k_clusters: temp_dir = path.join(dir, str(k), str(sim_func).split()[1], str(arg)) if not path.exists(temp_dir): makedirs(temp_dir) assigns_file = path.join(temp_dir, name) + '_' + str(resolution) + '.npy' eval_file = path.join(temp_dir, name) + '_' + str(resolution) + '.eval' if not path.exists(assigns_file) or not path.exists(eval_file) or recompute: if eigen_vectors is None: eigen_vectors = _spectral_clustering(data, sim_func, arg) normalized_data = normalize(eigen_vectors[:, :k]) # computing and saving assignments _, assigns = kmeans(normalized_data, 5, 0.0001, k=k) del _, normalized_data np.save(assigns_file, assigns) # computing and saving evaluations f_measures = [] entropies = [] ground_truth, gt = tee(ground_truth) for seg, _ in gt: seg = seg.flatten() f_measures.append(fmeasure(assigns, seg)) entropies.append(conditional_entropy(assigns, seg)) f_measures = np.asarray(f_measures) entropies = np.asarray(entropies) np.savetxt(eval_file, np.vstack((f_measures, entropies))) def evaluate_kmeans(dir, k_clusters, recompute=False): """ Apply Spectral Clustering on given data then evaluate f-measure and conditional entropy for given ground truths. :param dir: path for directory to store output :type dir: str :param k_clusters: number of clusters :type k_clusters: int :param recompute: force compute assignments and evaluation files even if they already exist. :type recompute: bool """ dir = path.join(dir, str(k_clusters)) if not path.exists(dir): makedirs(dir) for image, ground_truth, name in islice(reader.request_data(), 100): _evaluate_kmeans(dir, image.reshape(image.shape[0] * image.shape[1], image.shape[2]), ground_truth, name, image.shape[0], k_clusters, recompute) def evaluate_spectral(dir, k_clusters, sim_func, sim_arg, recompute=False): """ Apply Spectral Clustering on given data then evaluate f-measure and conditional entropy for given ground truths. :param dir: path for directory to store output :type dir: str :param k_clusters: numbers of clusters :type k_clusters: list(int) :param sim_func: can be rbf or knn :type sim_func: function :param sim_arg: gammas in case of rbf or n_neighbours in case of knn :type sim_arg: list(float) for gamma, list(int) for n_neighbours :param recompute: force compute assignments and evaluation files even if they already exist. :type recompute: bool """ for image, ground_truth, name in islice(reader.request_data(), 1): _evaluate_spectral(dir, image.reshape(image.shape[0] * image.shape[1], image.shape[2]), ground_truth, name, image.shape[0], k_clusters, sim_func, sim_arg, recompute) def load_eval_data(path): """ :param path: path to evaluation file :type path: str :return: (f_measure, conditional_entropies) :rtype: (nd-array, nd-array) """ temp = np.loadtxt(path) # return f_measures, entropies return temp[0, :], temp[1, :] def read_kmeans_eval(name, k, resolution): """ :param name: image name :type name: str :param k: number of clusters :type k: int :param resolution: resolution of the image to load evaluation for. :type resolution: int :return: assignments, (f_measure, conditional_entropies) :rtype: nd-array, (nd-array, nd-array) """ dir = path.join(KMEANS_DIR, str(k)) name = str(name).split('.')[0] + '_' + str(resolution) assert path.exists(path.join(dir, name + '.npy')), 'Assignments file is missing or not found' assert path.exists(path.join(dir, name + '.eval')), 'Evaluation file is missing or not found' return np.load(path.join(dir, name + '.npy')), load_eval_data(path.join(dir, name + '.eval')) def read_spectral_eval(name, k, resolution, sim_func, sim_arg): """ :param name: image name :type name: str :param k: number of clusters :type k: int :param resolution: resolution of the image to load evaluation for. :type resolution: int :param sim_func: can be rbf or knn :type sim_func: function :param sim_arg: gamma in case of rbf and n_neighbours in case of knn :type sim_arg: float for gamma, int for n_neighbours :return: assignments, (f_measure, conditional_entropies) :rtype: nd-array, (nd-array, nd-array) """ dir = path.join(SPECTRAL_DIR, str(k), str(sim_func).split()[1], str(sim_arg)) name = str(name).split('.')[0] + '_' + str(resolution) assert path.exists(path.join(dir, name + '.npy')), 'Assignments file is missing or not found' assert path.exists(path.join(dir, name + '.eval')), 'Evaluation file is missing or not found' return np.load(path.join(dir, name + '.npy')), load_eval_data(path.join(dir, name + '.eval')) def big_picture_eval(): from visualize_data import show_images, visualize_data from itertools import islice, chain from spectral_clustering import knn, spectral_clustering img_pre_reshape = lambda img : img.reshape(img.shape[0] * img.shape[1], img.shape[2]) img_original = lambda img : img.reshape(reader.RES[0], reader.RES[1]) for img, gt_iter, fname in islice(reader.request_data(), 5): print(0) output = kmeans(img_pre_reshape(img), k=5)[1] visualize_data( img_original(output), gt_iter, fname ) for img, gt_iter, fname in islice(reader.request_data(), 5): print(1) spectral_output = spectral_clustering( img_pre_reshape(img), k=5, sim_func=knn, sim_arg=5)[1] visualize_data( img_original(spectral_output), gt_iter, fname ) for img, gt_iter,fname in islice(reader.request_data(), 5): print(2) spectral_output = spectral_clustering( img_pre_reshape(img), k=5, sim_func=knn, sim_arg=5)[1] kmeans_output = kmeans(img_pre_reshape(img), k=5)[1] show_images([img_original(kmeans_output),img_original(spectral_output)]) def avg_eval(path): f_measures, entropies = load_eval_data(path) return np.sum(f_measures) / f_measures.size, np.sum(entropies) / entropies.size def avg_kmeans_eval(name, k, resolution): f_measures, entropies = read_kmeans_eval(name, k, resolution)[1] return np.sum(f_measures) / f_measures.size, np.sum(entropies) / entropies.size def avg_spectral_eval(name, k, resolution, sim_func, sim_arg): f_measures, entropies = read_spectral_eval(name, k, resolution, sim_func, sim_arg)[1] return np.sum(f_measures) / f_measures.size, np.sum(entropies) / entropies.size def total_avg_kmeans(name, resolution): f_sum = entropy_sum = f_length = entropy_length =0 for k in [3, 5, 7, 9, 11]: f_measures, entropies = read_kmeans_eval(name, k, resolution)[1] f_sum += np.sum(f_measures) entropy_sum += np.sum(entropies) f_length += f_measures.size entropy_length += entropies.size return f_sum / f_length, entropy_sum / entropy_length def total_avg_spectral(name, resolution, sim_func, sim_arg): f_sum = entropy_sum = f_length = entropy_length = 0 for k in [3, 5, 7, 9, 11]: f_measures, entropies = read_spectral_eval(name, k, resolution, sim_func, sim_arg)[1] f_sum += np.sum(f_measures) entropy_sum += np.sum(entropies) f_length += f_measures.size entropy_length += entropies.size return f_sum / f_length, entropy_sum / entropy_length if __name__ == '__main__': # environ['MKL_DYNAMIC'] = 'false' # counter = 0 # for k in [3, 5, 7, 9, 11]: # evaluate_kmeans(KMEANS_DIR, k) # evaluate_spectral(SPECTRAL_DIR, [3, 5, 7, 9, 11], rbf, [1, 10]) # evaluate_spectral(SPECTRAL_DIR, [3, 5, 7, 9, 11], knn, [5]) # for k in [3, 5, 7, 9, 11]: # x = read_spectral_eval('100039', k, 100, rbf, 10) # imshow(imresize(draw_clusters(x[0], k, (100, 100)), (500, 500))) # print(x[1]) # print(avg_spectral_eval('100039', k, 100, rbf, 10)) big_picture_eval()
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Python
Plugins/UnrealEnginePython/Binaries/Win64/Lib/site-packages/tensorflow/__init__.py
JustinACoder/H22-GR3-UnrealAI
361eb9ef1147f8a2991e5f98c4118cd823184adf
[ "MIT" ]
6
2022-02-04T18:12:24.000Z
2022-03-21T23:57:12.000Z
Lib/site-packages/tensorflow/_api/v1/__init__.py
shfkdroal/Robot-Learning-in-Mixed-Adversarial-and-Collaborative-Settings
1fa4cd6a566c8745f455fc3d2273208f21f88ced
[ "bzip2-1.0.6" ]
null
null
null
Lib/site-packages/tensorflow/_api/v1/__init__.py
shfkdroal/Robot-Learning-in-Mixed-Adversarial-and-Collaborative-Settings
1fa4cd6a566c8745f455fc3d2273208f21f88ced
[ "bzip2-1.0.6" ]
1
2022-02-08T03:53:23.000Z
2022-02-08T03:53:23.000Z
# Copyright 2015 The TensorFlow Authors. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # ============================================================================== """Bring in all of the public TensorFlow interface into this module.""" from __future__ import absolute_import as _absolute_import from __future__ import division as _division from __future__ import print_function as _print_function import os as _os # pylint: disable=g-bad-import-order from tensorflow.python import pywrap_tensorflow # pylint: disable=unused-import try: # Add `estimator` attribute to allow access to estimator APIs via # "tf.estimator..." from tensorflow.python.estimator.api import estimator # pylint: disable=g-import-not-at-top # Add `estimator` to the __path__ to allow "from tensorflow.estimator..." # style imports. from tensorflow.python.estimator import api as estimator_api # pylint: disable=g-import-not-at-top __path__ += [_os.path.dirname(estimator_api.__file__)] del estimator_api except (ImportError, AttributeError): print('tf.estimator package not installed.') from tensorflow._api.v1 import app from tensorflow._api.v1 import bitwise from tensorflow._api.v1 import compat from tensorflow._api.v1 import data from tensorflow._api.v1 import debugging from tensorflow._api.v1 import distributions from tensorflow._api.v1 import dtypes from tensorflow._api.v1 import errors from tensorflow._api.v1 import feature_column from tensorflow._api.v1 import gfile from tensorflow._api.v1 import graph_util from tensorflow._api.v1 import image from tensorflow._api.v1 import initializers from tensorflow._api.v1 import io from tensorflow._api.v1 import keras from tensorflow._api.v1 import layers from tensorflow._api.v1 import linalg from tensorflow._api.v1 import logging from tensorflow._api.v1 import losses from tensorflow._api.v1 import manip from tensorflow._api.v1 import math from tensorflow._api.v1 import metrics from tensorflow._api.v1 import nn from tensorflow._api.v1 import profiler from tensorflow._api.v1 import python_io from tensorflow._api.v1 import quantization from tensorflow._api.v1 import random from tensorflow._api.v1 import resource_loader from tensorflow._api.v1 import saved_model from tensorflow._api.v1 import sets from tensorflow._api.v1 import sparse from tensorflow._api.v1 import spectral from tensorflow._api.v1 import strings from tensorflow._api.v1 import summary from tensorflow._api.v1 import sysconfig from tensorflow._api.v1 import test from tensorflow._api.v1 import train from tensorflow._api.v1 import user_ops from tensorflow.python import AggregationMethod from tensorflow.python import Assert from tensorflow.python import AttrValue from tensorflow.python import ConditionalAccumulator from tensorflow.python import ConditionalAccumulatorBase from tensorflow.python import ConfigProto from tensorflow.python import Constant as constant_initializer from tensorflow.python import DType from tensorflow.python import DeviceSpec from tensorflow.python import Dimension from tensorflow.python import Event from tensorflow.python import FIFOQueue from tensorflow.python import FixedLenFeature from tensorflow.python import FixedLenSequenceFeature from tensorflow.python import FixedLengthRecordReader from tensorflow.python import GPUOptions from tensorflow.python import GlorotNormal as glorot_normal_initializer from tensorflow.python import GlorotUniform as glorot_uniform_initializer from tensorflow.python import GradientTape from tensorflow.python import Graph from tensorflow.python import GraphDef from tensorflow.python import GraphKeys from tensorflow.python import GraphOptions from tensorflow.python import HistogramProto from tensorflow.python import IdentityReader from tensorflow.python import IndexedSlices from tensorflow.python import InteractiveSession from tensorflow.python import LMDBReader from tensorflow.python import LogMessage from tensorflow.python import MetaGraphDef from tensorflow.python import NameAttrList from tensorflow.python import NoGradient from tensorflow.python import NoGradient as NotDifferentiable from tensorflow.python import NodeDef from tensorflow.python import Ones as ones_initializer from tensorflow.python import OpError from tensorflow.python import Operation from tensorflow.python import OptimizerOptions from tensorflow.python import Orthogonal as orthogonal_initializer from tensorflow.python import PaddingFIFOQueue from tensorflow.python import Print from tensorflow.python import PriorityQueue from tensorflow.python import QueueBase from tensorflow.python import RandomNormal as random_normal_initializer from tensorflow.python import RandomShuffleQueue from tensorflow.python import RandomUniform as random_uniform_initializer from tensorflow.python import ReaderBase from tensorflow.python import RegisterGradient from tensorflow.python import RunMetadata from tensorflow.python import RunOptions from tensorflow.python import Session from tensorflow.python import SessionLog from tensorflow.python import SparseConditionalAccumulator from tensorflow.python import SparseFeature from tensorflow.python import SparseTensor from tensorflow.python import SparseTensorValue from tensorflow.python import Summary from tensorflow.python import SummaryMetadata from tensorflow.python import TFRecordReader from tensorflow.python import Tensor from tensorflow.python import TensorArray from tensorflow.python import TensorInfo from tensorflow.python import TensorShape from tensorflow.python import TextLineReader from tensorflow.python import TruncatedNormal as truncated_normal_initializer from tensorflow.python import UniformUnitScaling as uniform_unit_scaling_initializer from tensorflow.python import VarLenFeature from tensorflow.python import VariableAggregation from tensorflow.python import VariableScope from tensorflow.python import VariableSynchronization from tensorflow.python import VariableV1 as Variable from tensorflow.python import VarianceScaling as variance_scaling_initializer from tensorflow.python import WholeFileReader from tensorflow.python import Zeros as zeros_initializer from tensorflow.python import abs from tensorflow.python import accumulate_n from tensorflow.python import acos from tensorflow.python import acosh from tensorflow.python import add from tensorflow.python import add_check_numerics_ops from tensorflow.python import add_n from tensorflow.python import add_to_collection from tensorflow.python import add_to_collections from tensorflow.python import all_variables from tensorflow.python import angle from tensorflow.python import arg_max from tensorflow.python import arg_min from tensorflow.python import argmax from tensorflow.python import argmin from tensorflow.python import as_dtype from tensorflow.python import as_string from tensorflow.python import asin from tensorflow.python import asinh from tensorflow.python import assert_equal from tensorflow.python import assert_greater from tensorflow.python import assert_greater_equal from tensorflow.python import assert_integer from tensorflow.python import assert_less from tensorflow.python import assert_less_equal from tensorflow.python import assert_near from tensorflow.python import assert_negative from tensorflow.python import assert_non_negative from tensorflow.python import assert_non_positive from tensorflow.python import assert_none_equal from tensorflow.python import assert_positive from tensorflow.python import assert_proper_iterable from tensorflow.python import assert_rank from tensorflow.python import assert_rank_at_least from tensorflow.python import assert_rank_in from tensorflow.python import assert_same_float_dtype from tensorflow.python import assert_scalar from tensorflow.python import assert_type from tensorflow.python import assert_variables_initialized from tensorflow.python import assign from tensorflow.python import assign_add from tensorflow.python import assign_sub from tensorflow.python import atan from tensorflow.python import atan2 from tensorflow.python import atanh from tensorflow.python import batch_gather from tensorflow.python import batch_to_space from tensorflow.python import batch_to_space_nd from tensorflow.python import betainc from tensorflow.python import bincount from tensorflow.python import bitcast from tensorflow.python import boolean_mask from tensorflow.python import broadcast_dynamic_shape from tensorflow.python import broadcast_static_shape from tensorflow.python import broadcast_to from tensorflow.python import case from tensorflow.python import cast from tensorflow.python import ceil from tensorflow.python import check_numerics from tensorflow.python import cholesky from tensorflow.python import cholesky_solve from tensorflow.python import clip_by_average_norm from tensorflow.python import clip_by_global_norm from tensorflow.python import clip_by_norm from tensorflow.python import clip_by_value from tensorflow.python import colocate_with from tensorflow.python import complex from tensorflow.python import concat from tensorflow.python import cond from tensorflow.python import confusion_matrix from tensorflow.python import conj from tensorflow.python import constant from tensorflow.python import container from tensorflow.python import control_dependencies from tensorflow.python import convert_to_tensor from tensorflow.python import convert_to_tensor_or_indexed_slices from tensorflow.python import convert_to_tensor_or_sparse_tensor from tensorflow.python import cos from tensorflow.python import cosh from tensorflow.python import count_nonzero from tensorflow.python import count_up_to from tensorflow.python import create_partitioned_variables from tensorflow.python import cross from tensorflow.python import cumprod from tensorflow.python import cumsum from tensorflow.python import custom_gradient from tensorflow.python import decode_base64 from tensorflow.python import decode_compressed from tensorflow.python import decode_csv from tensorflow.python import decode_json_example from tensorflow.python import decode_raw from tensorflow.python import delete_session_tensor from tensorflow.python import depth_to_space from tensorflow.python import dequantize from tensorflow.python import deserialize_many_sparse from tensorflow.python import device from tensorflow.python import diag from tensorflow.python import diag_part from tensorflow.python import digamma from tensorflow.python import div from tensorflow.python import div_no_nan from tensorflow.python import divide from tensorflow.python import dynamic_partition from tensorflow.python import dynamic_stitch from tensorflow.python import edit_distance from tensorflow.python import einsum from tensorflow.python import enable_eager_execution from tensorflow.python import encode_base64 from tensorflow.python import equal from tensorflow.python import erf from tensorflow.python import erfc from tensorflow.python import executing_eagerly from tensorflow.python import exp from tensorflow.python import expand_dims from tensorflow.python import expm1 from tensorflow.python import extract_image_patches from tensorflow.python import extract_volume_patches from tensorflow.python import eye from tensorflow.python import fake_quant_with_min_max_args from tensorflow.python import fake_quant_with_min_max_args_gradient from tensorflow.python import fake_quant_with_min_max_vars from tensorflow.python import fake_quant_with_min_max_vars_gradient from tensorflow.python import fake_quant_with_min_max_vars_per_channel from tensorflow.python import fake_quant_with_min_max_vars_per_channel_gradient from tensorflow.python import fft from tensorflow.python import fft2d from tensorflow.python import fft3d from tensorflow.python import fill from tensorflow.python import fixed_size_partitioner from tensorflow.python import floor from tensorflow.python import floor_div from tensorflow.python import floor_mod as floormod from tensorflow.python import floor_mod as mod from tensorflow.python import floordiv from tensorflow.python import foldl from tensorflow.python import foldr from tensorflow.python import gather from tensorflow.python import gather_nd from tensorflow.python import get_collection from tensorflow.python import get_collection_ref from tensorflow.python import get_default_graph from tensorflow.python import get_default_session from tensorflow.python import get_local_variable from tensorflow.python import get_seed from tensorflow.python import get_session_handle from tensorflow.python import get_session_tensor from tensorflow.python import get_variable from tensorflow.python import get_variable_scope from tensorflow.python import global_norm from tensorflow.python import global_variables from tensorflow.python import global_variables_initializer from tensorflow.python import gradients from tensorflow.python import greater from tensorflow.python import greater_equal from tensorflow.python import group from tensorflow.python import guarantee_const from tensorflow.python import hessians from tensorflow.python import histogram_fixed_width from tensorflow.python import histogram_fixed_width_bins from tensorflow.python import identity from tensorflow.python import identity_n from tensorflow.python import ifft from tensorflow.python import ifft2d from tensorflow.python import ifft3d from tensorflow.python import igamma from tensorflow.python import igammac from tensorflow.python import imag from tensorflow.python import import_graph_def from tensorflow.python import initialize_all_tables from tensorflow.python import initialize_all_variables from tensorflow.python import initialize_local_variables from tensorflow.python import initialize_variables from tensorflow.python import invert_permutation from tensorflow.python import is_finite from tensorflow.python import is_inf from tensorflow.python import is_nan from tensorflow.python import is_non_decreasing from tensorflow.python import is_numeric_tensor from tensorflow.python import is_strictly_increasing from tensorflow.python import is_variable_initialized from tensorflow.python import lbeta from tensorflow.python import less from tensorflow.python import less_equal from tensorflow.python import lgamma from tensorflow.python import lin_space from tensorflow.python import lin_space as linspace from tensorflow.python import load_file_system_library from tensorflow.python import load_library from tensorflow.python import load_op_library from tensorflow.python import local_variables from tensorflow.python import local_variables_initializer from tensorflow.python import log from tensorflow.python import log1p from tensorflow.python import log_sigmoid from tensorflow.python import logical_and from tensorflow.python import logical_not from tensorflow.python import logical_or from tensorflow.python import logical_xor from tensorflow.python import make_ndarray from tensorflow.python import make_template from tensorflow.python import make_tensor_proto from tensorflow.python import map_fn from tensorflow.python import matching_files from tensorflow.python import matmul from tensorflow.python import matrix_band_part from tensorflow.python import matrix_determinant from tensorflow.python import matrix_diag from tensorflow.python import matrix_diag_part from tensorflow.python import matrix_inverse from tensorflow.python import matrix_set_diag from tensorflow.python import matrix_solve from tensorflow.python import matrix_solve_ls from tensorflow.python import matrix_transpose from tensorflow.python import matrix_triangular_solve from tensorflow.python import maximum from tensorflow.python import meshgrid from tensorflow.python import min_max_variable_partitioner from tensorflow.python import minimum from tensorflow.python import model_variables from tensorflow.python import moving_average_variables from tensorflow.python import multinomial from tensorflow.python import multiply from tensorflow.python import name_scope from tensorflow.python import negative from tensorflow.python import no_op from tensorflow.python import no_regularizer from tensorflow.python import norm from tensorflow.python import not_equal from tensorflow.python import one_hot from tensorflow.python import ones from tensorflow.python import ones_like from tensorflow.python import op_scope from tensorflow.python import pad from tensorflow.python import parallel_stack from tensorflow.python import parse_example from tensorflow.python import parse_single_example from tensorflow.python import parse_single_sequence_example from tensorflow.python import parse_tensor from tensorflow.python import placeholder from tensorflow.python import placeholder_with_default from tensorflow.python import polygamma from tensorflow.python import pow from tensorflow.python import py_func from tensorflow.python import qr from tensorflow.python import quantize from tensorflow.python import quantize_v2 from tensorflow.python import quantized_concat from tensorflow.python import random_crop from tensorflow.python import random_gamma from tensorflow.python import random_normal from tensorflow.python import random_poisson from tensorflow.python import random_shuffle from tensorflow.python import random_uniform from tensorflow.python import range from tensorflow.python import rank from tensorflow.python import read_file from tensorflow.python import real from tensorflow.python import real_div as realdiv from tensorflow.python import reciprocal from tensorflow.python import reduce_all from tensorflow.python import reduce_any from tensorflow.python import reduce_join from tensorflow.python import reduce_logsumexp from tensorflow.python import reduce_max from tensorflow.python import reduce_mean from tensorflow.python import reduce_min from tensorflow.python import reduce_prod from tensorflow.python import reduce_sum from tensorflow.python import register_tensor_conversion_function from tensorflow.python import report_uninitialized_variables from tensorflow.python import required_space_to_batch_paddings from tensorflow.python import reset_default_graph from tensorflow.python import reshape from tensorflow.python import reverse from tensorflow.python import reverse as reverse_v2 from tensorflow.python import reverse_sequence from tensorflow.python import rint from tensorflow.python import roll from tensorflow.python import round from tensorflow.python import rsqrt from tensorflow.python import saturate_cast from tensorflow.python import scalar_mul from tensorflow.python import scan from tensorflow.python import scatter_add from tensorflow.python import scatter_div from tensorflow.python import scatter_max from tensorflow.python import scatter_min from tensorflow.python import scatter_mul from tensorflow.python import scatter_nd from tensorflow.python import scatter_nd_add from tensorflow.python import scatter_nd_sub from tensorflow.python import scatter_nd_update from tensorflow.python import scatter_sub from tensorflow.python import scatter_update from tensorflow.python import searchsorted from tensorflow.python import segment_max from tensorflow.python import segment_mean from tensorflow.python import segment_min from tensorflow.python import segment_prod from tensorflow.python import segment_sum from tensorflow.python import self_adjoint_eig from tensorflow.python import self_adjoint_eigvals from tensorflow.python import sequence_mask from tensorflow.python import serialize_many_sparse from tensorflow.python import serialize_sparse from tensorflow.python import serialize_tensor from tensorflow.python import set_random_seed from tensorflow.python import setdiff1d from tensorflow.python import shape from tensorflow.python import shape_n from tensorflow.python import sigmoid from tensorflow.python import sign from tensorflow.python import sin from tensorflow.python import sinh from tensorflow.python import size from tensorflow.python import slice from tensorflow.python import space_to_batch from tensorflow.python import space_to_batch_nd from tensorflow.python import space_to_depth from tensorflow.python import sparse_add from tensorflow.python import sparse_concat from tensorflow.python import sparse_fill_empty_rows from tensorflow.python import sparse_mask from tensorflow.python import sparse_mat_mul as sparse_matmul from tensorflow.python import sparse_maximum from tensorflow.python import sparse_merge from tensorflow.python import sparse_minimum from tensorflow.python import sparse_placeholder from tensorflow.python import sparse_reduce_max from tensorflow.python import sparse_reduce_max_sparse from tensorflow.python import sparse_reduce_sum from tensorflow.python import sparse_reduce_sum_sparse from tensorflow.python import sparse_reorder from tensorflow.python import sparse_reset_shape from tensorflow.python import sparse_reshape from tensorflow.python import sparse_retain from tensorflow.python import sparse_segment_mean from tensorflow.python import sparse_segment_sqrt_n from tensorflow.python import sparse_segment_sum from tensorflow.python import sparse_slice from tensorflow.python import sparse_softmax from tensorflow.python import sparse_split from tensorflow.python import sparse_tensor_dense_matmul from tensorflow.python import sparse_tensor_to_dense from tensorflow.python import sparse_to_dense from tensorflow.python import sparse_to_indicator from tensorflow.python import sparse_transpose from tensorflow.python import split from tensorflow.python import sqrt from tensorflow.python import square from tensorflow.python import squared_difference from tensorflow.python import squeeze from tensorflow.python import stack from tensorflow.python import stop_gradient from tensorflow.python import strided_slice from tensorflow.python import string_join from tensorflow.python import string_split from tensorflow.python import string_strip from tensorflow.python import string_to_hash_bucket from tensorflow.python import string_to_hash_bucket_fast from tensorflow.python import string_to_hash_bucket_strong from tensorflow.python import string_to_number from tensorflow.python import substr from tensorflow.python import subtract from tensorflow.python import svd from tensorflow.python import tables_initializer from tensorflow.python import tan from tensorflow.python import tanh from tensorflow.python import tensordot from tensorflow.python import tile from tensorflow.python import timestamp from tensorflow.python import to_bfloat16 from tensorflow.python import to_complex128 from tensorflow.python import to_complex64 from tensorflow.python import to_double from tensorflow.python import to_float from tensorflow.python import to_int32 from tensorflow.python import to_int64 from tensorflow.python import trace from tensorflow.python import trainable_variables from tensorflow.python import transpose from tensorflow.python import truediv from tensorflow.python import truncate_div as truncatediv from tensorflow.python import truncate_mod as truncatemod from tensorflow.python import truncated_normal from tensorflow.python import tuple from tensorflow.python import unique from tensorflow.python import unique_with_counts from tensorflow.python import unravel_index from tensorflow.python import unsorted_segment_max from tensorflow.python import unsorted_segment_mean from tensorflow.python import unsorted_segment_min from tensorflow.python import unsorted_segment_prod from tensorflow.python import unsorted_segment_sqrt_n from tensorflow.python import unsorted_segment_sum from tensorflow.python import unstack from tensorflow.python import variable_axis_size_partitioner from tensorflow.python import variable_op_scope from tensorflow.python import variable_scope from tensorflow.python import variables_initializer from tensorflow.python import verify_tensor_all_finite from tensorflow.python import where from tensorflow.python import while_loop from tensorflow.python import write_file from tensorflow.python import zeros from tensorflow.python import zeros_like from tensorflow.python import zeta from tensorflow.python.framework.dtypes import QUANTIZED_DTYPES from tensorflow.python.framework.dtypes import bfloat16 from tensorflow.python.framework.dtypes import bool from tensorflow.python.framework.dtypes import complex128 from tensorflow.python.framework.dtypes import complex64 from tensorflow.python.framework.dtypes import double from tensorflow.python.framework.dtypes import float16 from tensorflow.python.framework.dtypes import float32 from tensorflow.python.framework.dtypes import float64 from tensorflow.python.framework.dtypes import half from tensorflow.python.framework.dtypes import int16 from tensorflow.python.framework.dtypes import int32 from tensorflow.python.framework.dtypes import int64 from tensorflow.python.framework.dtypes import int8 from tensorflow.python.framework.dtypes import qint16 from tensorflow.python.framework.dtypes import qint32 from tensorflow.python.framework.dtypes import qint8 from tensorflow.python.framework.dtypes import quint16 from tensorflow.python.framework.dtypes import quint8 from tensorflow.python.framework.dtypes import resource from tensorflow.python.framework.dtypes import string from tensorflow.python.framework.dtypes import uint16 from tensorflow.python.framework.dtypes import uint32 from tensorflow.python.framework.dtypes import uint64 from tensorflow.python.framework.dtypes import uint8 from tensorflow.python.framework.dtypes import variant from tensorflow.python.framework.ops import init_scope from tensorflow.python.framework.versions import COMPILER_VERSION from tensorflow.python.framework.versions import COMPILER_VERSION as __compiler_version__ from tensorflow.python.framework.versions import CXX11_ABI_FLAG from tensorflow.python.framework.versions import CXX11_ABI_FLAG as __cxx11_abi_flag__ from tensorflow.python.framework.versions import GIT_VERSION from tensorflow.python.framework.versions import GIT_VERSION as __git_version__ from tensorflow.python.framework.versions import GRAPH_DEF_VERSION from tensorflow.python.framework.versions import GRAPH_DEF_VERSION_MIN_CONSUMER from tensorflow.python.framework.versions import GRAPH_DEF_VERSION_MIN_PRODUCER from tensorflow.python.framework.versions import MONOLITHIC_BUILD from tensorflow.python.framework.versions import MONOLITHIC_BUILD as __monolithic_build__ from tensorflow.python.framework.versions import VERSION from tensorflow.python.framework.versions import VERSION as __version__ from tensorflow.python.ops.array_ops import newaxis from tensorflow.python.ops.check_ops import ensure_shape from tensorflow.python.ops.gen_string_ops import regex_replace from tensorflow.python.ops.logging_ops import print_v2 as print from tensorflow.python.ops.state_ops import batch_scatter_update from tensorflow.python.ops.variable_scope import AUTO_REUSE from tensorflow.python.ops.variable_scope import disable_resource_variables from tensorflow.python.ops.variable_scope import enable_resource_variables from tensorflow.python.ops.variable_scope import variable_creator_scope_v1 as variable_creator_scope _names_with_underscore = ['__version__', '__git_version__', '__compiler_version__', '__cxx11_abi_flag__', '__monolithic_build__'] __all__ = [_s for _s in dir() if not _s.startswith('_')] __all__.extend([_s for _s in _names_with_underscore]) from tensorflow.python.util.lazy_loader import LazyLoader # pylint: disable=g-import-not-at-top contrib = LazyLoader('contrib', globals(), 'tensorflow.contrib') del LazyLoader # The templated code that replaces the placeholder above sometimes # sets the __all__ variable. If it does, we have to be sure to add # "contrib". if '__all__' in vars(): vars()['__all__'].append('contrib') from tensorflow.python.platform import flags # pylint: disable=g-import-not-at-top app.flags = flags # pylint: disable=undefined-variable # Make sure directory containing top level submodules is in # the __path__ so that "from tensorflow.foo import bar" works. _tf_api_dir = _os.path.dirname(_os.path.dirname(app.__file__)) # pylint: disable=undefined-variable if _tf_api_dir not in __path__: __path__.append(_tf_api_dir) # These symbols appear because we import the python package which # in turn imports from tensorflow.core and tensorflow.python. They # must come from this module. So python adds these symbols for the # resolution to succeed. # pylint: disable=undefined-variable try: del python del core except NameError: # Don't fail if these modules are not available. # For e.g. we are using this file for compat.v1 module as well and # 'python', 'core' directories are not under compat/v1. pass # pylint: enable=undefined-variable
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27888e8d4af68bc02e5cc3ec6cc2b2a9ec3a4f1a
740
py
Python
pyradiator/content_providers/content_provider_loader.py
crashmaster/pyradiator
355611bae1b6a78d8d65bf065efefbe0f393cc21
[ "MIT" ]
null
null
null
pyradiator/content_providers/content_provider_loader.py
crashmaster/pyradiator
355611bae1b6a78d8d65bf065efefbe0f393cc21
[ "MIT" ]
null
null
null
pyradiator/content_providers/content_provider_loader.py
crashmaster/pyradiator
355611bae1b6a78d8d65bf065efefbe0f393cc21
[ "MIT" ]
null
null
null
import logging from importlib import import_module LOGGER = logging.getLogger(__name__) def load_content_provider(content_provider_name): module_name = content_provider_name_to_module_name(content_provider_name) module = import_module(module_name) class_name = content_provider_name_to_class_name(content_provider_name) content_provider = getattr(module, class_name) LOGGER.debug("Content provider %s loaded", class_name) return content_provider def content_provider_name_to_module_name(content_provider_name): return "pyradiator.content_providers.{}".format(content_provider_name) def content_provider_name_to_class_name(content_provider_name): return content_provider_name.title().replace("_", "")
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27e2c21279b8862d560e14469c608f343617bcf8
414
py
Python
wbia_pie_v2/__main__.py
dylanirion/wbia-plugin-pie-v2
8ae37c2ad218e5e888bb1aea039f1b04a3fe9d8d
[ "Apache-2.0" ]
null
null
null
wbia_pie_v2/__main__.py
dylanirion/wbia-plugin-pie-v2
8ae37c2ad218e5e888bb1aea039f1b04a3fe9d8d
[ "Apache-2.0" ]
null
null
null
wbia_pie_v2/__main__.py
dylanirion/wbia-plugin-pie-v2
8ae37c2ad218e5e888bb1aea039f1b04a3fe9d8d
[ "Apache-2.0" ]
1
2021-04-05T23:46:11.000Z
2021-04-05T23:46:11.000Z
# -*- coding: utf-8 -*- def main(): # nocover import wbia_pie_v2 print('Looks like the imports worked') print('wbia_pie_v2 = {!r}'.format(wbia_pie_v2)) print('wbia_pie_v2.__file__ = {!r}'.format(wbia_pie_v2.__file__)) print('wbia_pie_v2.__version__ = {!r}'.format(wbia_pie_v2.__version__)) if __name__ == '__main__': """ CommandLine: python -m wbia_pie_v2 """ main()
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27f410257fd7b9104a04bfd669b7f8d14b7541fa
129
py
Python
Blob_Lib/assimp-5.2.3/assimp/port/PyAssimp/pyassimp/material.py
antholuo/Blob_Traffic
5d6acf88044e9abc63c0ff356714179eaa4b75bf
[ "MIT" ]
null
null
null
Blob_Lib/assimp-5.2.3/assimp/port/PyAssimp/pyassimp/material.py
antholuo/Blob_Traffic
5d6acf88044e9abc63c0ff356714179eaa4b75bf
[ "MIT" ]
null
null
null
Blob_Lib/assimp-5.2.3/assimp/port/PyAssimp/pyassimp/material.py
antholuo/Blob_Traffic
5d6acf88044e9abc63c0ff356714179eaa4b75bf
[ "MIT" ]
null
null
null
version https://git-lfs.github.com/spec/v1 oid sha256:a3f076e31347712e2e38719d3c9a2cf9c6735453f9f2e372fe4cc86df4ede972 size 2409
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7e000de5f29498b41a4c8a315e8b54ab17a095ca
227
py
Python
application.py
Dannyky/pythonflaskhelloworld
db57f0d799ac193afdee7926ca4173495fbf5421
[ "MIT" ]
null
null
null
application.py
Dannyky/pythonflaskhelloworld
db57f0d799ac193afdee7926ca4173495fbf5421
[ "MIT" ]
1
2020-02-23T14:05:08.000Z
2020-02-23T14:05:08.000Z
application.py
Dannyky/pythonflaskhelloworld
db57f0d799ac193afdee7926ca4173495fbf5421
[ "MIT" ]
1
2020-04-23T19:18:21.000Z
2020-04-23T19:18:21.000Z
from flask import Flask,render_template,redirect, url_for, request import gspread from oauth2client.service_account import ServiceAccountCredentials app = Flask(__name__) @app.route("/") def hello(): return "Hello World!"
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7e1280db0c8ba189ea9b38226a44103a9c532241
170
py
Python
debutizer/upstreams/__init__.py
velovix/debutizer
a56f269881e70cd50feea32134b2fa0e0d93a20c
[ "BSD-3-Clause" ]
2
2022-03-08T01:53:20.000Z
2022-03-08T01:53:26.000Z
debutizer/upstreams/__init__.py
velovix/debutizer
a56f269881e70cd50feea32134b2fa0e0d93a20c
[ "BSD-3-Clause" ]
64
2021-10-19T01:03:43.000Z
2022-01-02T18:42:46.000Z
debutizer/upstreams/__init__.py
velovix/debutizer
a56f269881e70cd50feea32134b2fa0e0d93a20c
[ "BSD-3-Clause" ]
null
null
null
from .base import Upstream from .git import GitUpstream from .local import LocalUpstream from .null import NullUpstream from .source_package import SourcePackageUpstream
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5
fd761a7a940ee6b3c0e36cff8ab42bca20450e2f
149
py
Python
matching/__init__.py
coasxu/FedMA
21f4d32338fd2563ebd97c737e3b9f4f470029d9
[ "MIT" ]
254
2020-02-14T07:45:36.000Z
2022-03-30T01:36:07.000Z
matching/__init__.py
coasxu/FedMA
21f4d32338fd2563ebd97c737e3b9f4f470029d9
[ "MIT" ]
14
2020-05-01T18:21:06.000Z
2022-02-21T03:50:52.000Z
matching/__init__.py
coasxu/FedMA
21f4d32338fd2563ebd97c737e3b9f4f470029d9
[ "MIT" ]
72
2020-02-20T12:16:25.000Z
2022-02-19T09:59:59.000Z
from . import gaus_marginal_matching, pfnm, pfnm_communication, utils __all__ = ['gaus_marginal_matching', 'sgpfnmd', 'pfnm_communication', 'utils']
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fd7b0a0e7a8bdbd3662ead95a4c2331740acb525
34
py
Python
tests/commons_test/__main__.py
Aigeruth/bazel-playground
4a62d91deb74bbd19e47cae9cdf7faec404be590
[ "MIT" ]
null
null
null
tests/commons_test/__main__.py
Aigeruth/bazel-playground
4a62d91deb74bbd19e47cae9cdf7faec404be590
[ "MIT" ]
null
null
null
tests/commons_test/__main__.py
Aigeruth/bazel-playground
4a62d91deb74bbd19e47cae9cdf7faec404be590
[ "MIT" ]
null
null
null
from unittest import main main()
8.5
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true
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5
fd9b436c970f5abde4d992d251c8f8cc72df29a9
5,044
py
Python
core/tests/test_trezor.crypto.pbkdf2.py
Kayuii/trezor-crypto
6556616681a4e2d7e18817e8692d4f6e041dee01
[ "MIT" ]
null
null
null
core/tests/test_trezor.crypto.pbkdf2.py
Kayuii/trezor-crypto
6556616681a4e2d7e18817e8692d4f6e041dee01
[ "MIT" ]
1
2019-02-08T00:22:42.000Z
2019-02-13T09:41:54.000Z
core/tests/test_trezor.crypto.pbkdf2.py
Kayuii/trezor-crypto
6556616681a4e2d7e18817e8692d4f6e041dee01
[ "MIT" ]
2
2019-02-07T23:57:09.000Z
2020-10-21T07:07:27.000Z
from common import * from trezor.crypto import pbkdf2 class TestCryptoPbkdf2(unittest.TestCase): # vectors from https://stackoverflow.com/questions/5130513/pbkdf2-hmac-sha2-test-vectors def test_pbkdf2_hmac_sha256(self): P = b'password' S = b'salt' dk = pbkdf2(pbkdf2.HMAC_SHA256, P, S, 1).key() self.assertEqual(dk, unhexlify('120fb6cffcf8b32c43e7225256c4f837a86548c92ccc35480805987cb70be17b')) dk = pbkdf2(pbkdf2.HMAC_SHA256, P, S, 2).key() self.assertEqual(dk, unhexlify('ae4d0c95af6b46d32d0adff928f06dd02a303f8ef3c251dfd6e2d85a95474c43')) dk = pbkdf2(pbkdf2.HMAC_SHA256, P, S, 4096).key() self.assertEqual(dk, unhexlify('c5e478d59288c841aa530db6845c4c8d962893a001ce4e11a4963873aa98134a')) P = b'passwordPASSWORDpassword' S = b'saltSALTsaltSALTsaltSALTsaltSALTsalt' dk = pbkdf2(pbkdf2.HMAC_SHA256, P, S, 4096).key() self.assertEqual(dk, unhexlify('348c89dbcbd32b2f32d814b8116e84cf2b17347ebc1800181c4e2a1fb8dd53e1')) def test_pbkdf2_hmac_sha256_update(self): P = b'password' S = b'salt' p = pbkdf2(pbkdf2.HMAC_SHA256, P, S) p.update(1) dk = p.key() self.assertEqual(dk, unhexlify('120fb6cffcf8b32c43e7225256c4f837a86548c92ccc35480805987cb70be17b')) p = pbkdf2(pbkdf2.HMAC_SHA256, P, S) p.update(1) p.update(1) dk = p.key() self.assertEqual(dk, unhexlify('ae4d0c95af6b46d32d0adff928f06dd02a303f8ef3c251dfd6e2d85a95474c43')) p = pbkdf2(pbkdf2.HMAC_SHA256, P, S) for i in range(32): p.update(128) dk = p.key() self.assertEqual(dk, unhexlify('c5e478d59288c841aa530db6845c4c8d962893a001ce4e11a4963873aa98134a')) P = b'passwordPASSWORDpassword' S = b'saltSALTsaltSALTsaltSALTsaltSALTsalt' p = pbkdf2(pbkdf2.HMAC_SHA256, P, S) for i in range(64): p.update(64) dk = p.key() self.assertEqual(dk, unhexlify('348c89dbcbd32b2f32d814b8116e84cf2b17347ebc1800181c4e2a1fb8dd53e1')) # vectors from https://stackoverflow.com/questions/15593184/pbkdf2-hmac-sha-512-test-vectors def test_pbkdf2_hmac_sha512(self): P = b'password' S = b'salt' dk = pbkdf2(pbkdf2.HMAC_SHA512, P, S, 1).key() self.assertEqual(dk, unhexlify('867f70cf1ade02cff3752599a3a53dc4af34c7a669815ae5d513554e1c8cf252c02d470a285a0501bad999bfe943c08f050235d7d68b1da55e63f73b60a57fce')) dk = pbkdf2(pbkdf2.HMAC_SHA512, P, S, 2).key() self.assertEqual(dk, unhexlify('e1d9c16aa681708a45f5c7c4e215ceb66e011a2e9f0040713f18aefdb866d53cf76cab2868a39b9f7840edce4fef5a82be67335c77a6068e04112754f27ccf4e')) dk = pbkdf2(pbkdf2.HMAC_SHA512, P, S, 4096).key() self.assertEqual(dk, unhexlify('d197b1b33db0143e018b12f3d1d1479e6cdebdcc97c5c0f87f6902e072f457b5143f30602641b3d55cd335988cb36b84376060ecd532e039b742a239434af2d5')) P = b'passwordPASSWORDpassword' S = b'saltSALTsaltSALTsaltSALTsaltSALTsalt' dk = pbkdf2(pbkdf2.HMAC_SHA512, P, S, 4096).key() self.assertEqual(dk, unhexlify('8c0511f4c6e597c6ac6315d8f0362e225f3c501495ba23b868c005174dc4ee71115b59f9e60cd9532fa33e0f75aefe30225c583a186cd82bd4daea9724a3d3b8')) def test_pbkdf2_hmac_sha512_update(self): P = b'password' S = b'salt' p = pbkdf2(pbkdf2.HMAC_SHA512, P, S) p.update(1) dk = p.key() self.assertEqual(dk, unhexlify('867f70cf1ade02cff3752599a3a53dc4af34c7a669815ae5d513554e1c8cf252c02d470a285a0501bad999bfe943c08f050235d7d68b1da55e63f73b60a57fce')) p = pbkdf2(pbkdf2.HMAC_SHA512, P, S) p.update(1) p.update(1) dk = p.key() self.assertEqual(dk, unhexlify('e1d9c16aa681708a45f5c7c4e215ceb66e011a2e9f0040713f18aefdb866d53cf76cab2868a39b9f7840edce4fef5a82be67335c77a6068e04112754f27ccf4e')) p = pbkdf2(pbkdf2.HMAC_SHA512, P, S) for i in range(32): p.update(128) dk = p.key() self.assertEqual(dk, unhexlify('d197b1b33db0143e018b12f3d1d1479e6cdebdcc97c5c0f87f6902e072f457b5143f30602641b3d55cd335988cb36b84376060ecd532e039b742a239434af2d5')) P = b'passwordPASSWORDpassword' S = b'saltSALTsaltSALTsaltSALTsaltSALTsalt' p = pbkdf2(pbkdf2.HMAC_SHA512, P, S) for i in range(64): p.update(64) dk = p.key() self.assertEqual(dk, unhexlify('8c0511f4c6e597c6ac6315d8f0362e225f3c501495ba23b868c005174dc4ee71115b59f9e60cd9532fa33e0f75aefe30225c583a186cd82bd4daea9724a3d3b8')) def test_key_multi(self): P = b'password' S = b'salt' p = pbkdf2(pbkdf2.HMAC_SHA256, P, S, 16) k0 = p.key() k1 = p.key() k2 = p.key() self.assertEqual(k0, k1) self.assertEqual(k0, k2) p = pbkdf2(pbkdf2.HMAC_SHA512, P, S, 16) k0 = p.key() k1 = p.key() k2 = p.key() self.assertEqual(k0, k1) self.assertEqual(k0, k2) if __name__ == '__main__': unittest.main()
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fdb14611831de0463133e8ad04c2702ffd813813
250
py
Python
data/__init__.py
thepabloaguilar/enforcement-service
789b149da0af4ecc972fb242c92c0f182a41f431
[ "BSD-3-Clause" ]
null
null
null
data/__init__.py
thepabloaguilar/enforcement-service
789b149da0af4ecc972fb242c92c0f182a41f431
[ "BSD-3-Clause" ]
null
null
null
data/__init__.py
thepabloaguilar/enforcement-service
789b149da0af4ecc972fb242c92c0f182a41f431
[ "BSD-3-Clause" ]
null
null
null
from data.repository.rancher import RancherRepository from data.repository.enforcement import EnforcementRepository from data.repository.cluster import ClusterRepository __all__ = ['RancherRepository', 'EnforcementRepository', 'ClusterRepository']
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5
fdb28efd0674a5f3e8d5c65efbdbb9adb67aae91
75
py
Python
mytorch/__init__.py
Felicia980317/mytorch
e463122c0d402878ec5b4c5a823a0feeba8fdbfe
[ "Apache-2.0" ]
null
null
null
mytorch/__init__.py
Felicia980317/mytorch
e463122c0d402878ec5b4c5a823a0feeba8fdbfe
[ "Apache-2.0" ]
null
null
null
mytorch/__init__.py
Felicia980317/mytorch
e463122c0d402878ec5b4c5a823a0feeba8fdbfe
[ "Apache-2.0" ]
null
null
null
from . import layers, loss, utils, activations, dataloader, paradataloader
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fdc65966ab1840ec806ad883ee2c09ec08898628
55
py
Python
tests/files/gte.py
docmarionum1/py65c
cd59ef25d2759b63efa5655f529fd31564cc31b0
[ "WTFPL" ]
12
2015-08-03T05:16:18.000Z
2020-09-12T12:38:16.000Z
tests/files/gte.py
docmarionum1/py65c
cd59ef25d2759b63efa5655f529fd31564cc31b0
[ "WTFPL" ]
null
null
null
tests/files/gte.py
docmarionum1/py65c
cd59ef25d2759b63efa5655f529fd31564cc31b0
[ "WTFPL" ]
null
null
null
a = 5 >= 3 b = 5 >= 4 c = 5 >= 5 d = 5 >= 6 e = 5 >= 7
9.166667
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5
fdd21d873958956e4b0083b81f33da8cbc7a92e0
51
py
Python
neointerface/__init__.py
GSK-Biostatistics/neointerface
f816eb3a7557c25387be4d4fb2552973706abc8b
[ "Apache-2.0" ]
9
2021-12-06T10:57:52.000Z
2022-02-23T10:36:14.000Z
neointerface/__init__.py
GSK-Biostatistics/neointerface
f816eb3a7557c25387be4d4fb2552973706abc8b
[ "Apache-2.0" ]
2
2021-12-13T09:15:57.000Z
2022-01-04T15:41:11.000Z
neointerface/__init__.py
GSK-Biostatistics/neointerface
f816eb3a7557c25387be4d4fb2552973706abc8b
[ "Apache-2.0" ]
2
2021-12-06T09:48:18.000Z
2021-12-15T23:23:03.000Z
from neointerface.neointerface import NeoInterface
25.5
50
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51
9.2
0.6
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5
fddc9420f46d2ab9b7babad4956884927d411644
33
py
Python
single_state/features/__init__.py
jiayeguo/sams_dunbrack
9f8bcffdabd1fcbd59c398e52763c22dcd1868df
[ "MIT" ]
8
2019-02-11T19:30:53.000Z
2022-01-26T02:14:41.000Z
single_state/features/__init__.py
jiayeguo/sams_dunbrack
9f8bcffdabd1fcbd59c398e52763c22dcd1868df
[ "MIT" ]
6
2019-02-11T05:25:05.000Z
2019-02-25T05:52:55.000Z
single_state/features/__init__.py
choderalab/sams_dunbrack
9f8bcffdabd1fcbd59c398e52763c22dcd1868df
[ "MIT" ]
2
2019-07-03T09:42:11.000Z
2019-07-03T12:24:14.000Z
from .featurize import featurize
16.5
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5
e30ada92131676d9c5dec099c00a3d3e66d6ea17
599
py
Python
simkit/examples/entitycreator.py
ahbuss/SimPyKit
325fa4a8df3de551f0f5665d46d8e8fe7fa5d2cf
[ "Apache-2.0" ]
4
2018-12-14T23:55:09.000Z
2022-02-19T13:41:33.000Z
simkit/examples/entitycreator.py
ahbuss/SimPyKit
325fa4a8df3de551f0f5665d46d8e8fe7fa5d2cf
[ "Apache-2.0" ]
2
2019-07-28T02:35:40.000Z
2020-04-27T21:55:06.000Z
simkit/examples/entitycreator.py
ahbuss/SimPyKit
325fa4a8df3de551f0f5665d46d8e8fe7fa5d2cf
[ "Apache-2.0" ]
2
2019-07-28T00:52:05.000Z
2022-01-11T22:44:51.000Z
from simkit.base import SimEntityBase from simkit.base import Entity from simkit.base import Priority class EntityCreator(SimEntityBase): def __init__(self, interarrival_time_generator): SimEntityBase.__init__(self) self.interarrival_time_generator = interarrival_time_generator def run(self): self.schedule('generate', self.interarrival_time_generator.generate()) def generate(self): self.schedule('generate', self.interarrival_time_generator.generate()) self.schedule('arrival', 0.0, Entity()) def doArrival(self, entity): pass
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0.289786
0.289786
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0
1
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1
0
0
5
e355b19019909f85418986db062223693648895e
87
py
Python
auth-api/main.py
dlavery/auth
9f37b4be2eeda2446b7d3abd44c7b45918486e0b
[ "MIT" ]
null
null
null
auth-api/main.py
dlavery/auth
9f37b4be2eeda2446b7d3abd44c7b45918486e0b
[ "MIT" ]
null
null
null
auth-api/main.py
dlavery/auth
9f37b4be2eeda2446b7d3abd44c7b45918486e0b
[ "MIT" ]
null
null
null
from app import app import routes if __name__ == '__main__': app.run(debug=False)
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5
e36a7833164b42ace3ef786eb9bcbc2ea9952cf4
804
py
Python
sunless_web/migrations/0029_auto_20180528_1543.py
bluedisk/SunlessSeaKo
1e6d498ff7e735b8d272dd0bca6c17741a2faedb
[ "MIT" ]
2
2019-02-19T11:53:29.000Z
2021-02-18T23:57:20.000Z
sunless_web/migrations/0029_auto_20180528_1543.py
bluedisk/SunlessSeaKo
1e6d498ff7e735b8d272dd0bca6c17741a2faedb
[ "MIT" ]
4
2018-05-26T13:18:27.000Z
2018-05-26T13:19:50.000Z
sunless_web/migrations/0029_auto_20180528_1543.py
bluedisk/SunlessSeaKo
1e6d498ff7e735b8d272dd0bca6c17741a2faedb
[ "MIT" ]
null
null
null
# Generated by Django 2.0.5 on 2018-05-28 06:43 from django.db import migrations class Migration(migrations.Migration): dependencies = [ ('sunless_web', '0028_auto_20180528_1518'), ] operations = [ migrations.RenameField( model_name='entity', old_name='create_at', new_name='created_at', ), migrations.RenameField( model_name='entity', old_name='update_at', new_name='updated_at', ), migrations.RenameField( model_name='noun', old_name='create_at', new_name='created_at', ), migrations.RenameField( model_name='noun', old_name='update_at', new_name='updated_at', ), ]
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5
8b567d775a8e8554367cdc6357fe0b42ab0d461d
68
py
Python
poocoin_trending/models/enums/__init__.py
kkristof200/py_poocoin_trending
87e29e0c639c519776cef61afe45be25bfc40c1b
[ "MIT" ]
null
null
null
poocoin_trending/models/enums/__init__.py
kkristof200/py_poocoin_trending
87e29e0c639c519776cef61afe45be25bfc40c1b
[ "MIT" ]
null
null
null
poocoin_trending/models/enums/__init__.py
kkristof200/py_poocoin_trending
87e29e0c639c519776cef61afe45be25bfc40c1b
[ "MIT" ]
null
null
null
from .sorting import Sorting from .time_interval import TimeInterval
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5
8b6e41297da11f9ca60fdb087844354656b81393
93
py
Python
python/ray/rllib/bc/__init__.py
cnheider/ray
9b33f3a7b7d799378decc2b7ef065e279599825d
[ "Apache-2.0" ]
2
2017-12-19T08:18:51.000Z
2018-01-19T02:42:28.000Z
python/ray/rllib/bc/__init__.py
cnheider/ray
9b33f3a7b7d799378decc2b7ef065e279599825d
[ "Apache-2.0" ]
5
2018-01-04T22:54:34.000Z
2018-02-06T23:48:20.000Z
python/ray/rllib/bc/__init__.py
cnheider/ray
9b33f3a7b7d799378decc2b7ef065e279599825d
[ "Apache-2.0" ]
3
2018-01-04T21:18:42.000Z
2019-01-20T05:34:33.000Z
from ray.rllib.bc.bc import BCAgent, DEFAULT_CONFIG __all__ = ["BCAgent", "DEFAULT_CONFIG"]
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5
8b81dc250da19d9dab9dd7986f28a2d20c2991b4
59
py
Python
ongoing_development/__init__.py
beenjammin/BASGRA_NZ_PY
36df7680773206c446645cd1f253180ae45e8dd6
[ "MIT" ]
null
null
null
ongoing_development/__init__.py
beenjammin/BASGRA_NZ_PY
36df7680773206c446645cd1f253180ae45e8dd6
[ "MIT" ]
null
null
null
ongoing_development/__init__.py
beenjammin/BASGRA_NZ_PY
36df7680773206c446645cd1f253180ae45e8dd6
[ "MIT" ]
2
2021-02-11T22:44:57.000Z
2022-03-31T02:08:17.000Z
""" Author: Matt Hanson Created: 21/10/2020 10:53 AM """
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5
8bd57fd16d7b3d757b10a74dbd652c8a21ee6c9d
41
py
Python
biosearch/pubmed/load.py
biosearch/biosearch
5aeb8a59a8728732fba9ea4113bc05d78e4bfbad
[ "Apache-2.0" ]
2
2019-03-29T20:41:02.000Z
2019-10-08T20:59:56.000Z
biosearch/pubmed/load.py
biosearch/biosearch
5aeb8a59a8728732fba9ea4113bc05d78e4bfbad
[ "Apache-2.0" ]
2
2021-03-31T19:15:04.000Z
2021-12-13T20:00:15.000Z
biosearch/pubmed/load.py
biosearch/biosearch
5aeb8a59a8728732fba9ea4113bc05d78e4bfbad
[ "Apache-2.0" ]
null
null
null
# Code to load pubmed into Elasticsearch
20.5
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41
5.5
1
0
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1
41
41
0.970588
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5
473fae5331f031428d01b993a72851d5ab456944
57
py
Python
textattack/goal_functions/text/__init__.py
cclauss/TextAttack
98b8d6102aa47bf3c41afedace0215d48f8ed046
[ "MIT" ]
2
2021-02-22T12:15:27.000Z
2021-05-02T15:22:05.000Z
textattack/goal_functions/text/__init__.py
53X/TextAttack
e6a7969abc1e28a2a8a7e2ace709b78eb9dc94be
[ "MIT" ]
null
null
null
textattack/goal_functions/text/__init__.py
53X/TextAttack
e6a7969abc1e28a2a8a7e2ace709b78eb9dc94be
[ "MIT" ]
1
2021-11-12T05:26:21.000Z
2021-11-12T05:26:21.000Z
from .non_overlapping_output import NonOverlappingOutput
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5
474570113a8cdd97177b640eb88902d3293042e1
6,838
py
Python
emtf_nnet/keras/quantization/default_quantize_configs.py
jiafulow/emtf-nnet
70a6c747c221178f9db940197ea886bdb60bf3ba
[ "Apache-2.0" ]
null
null
null
emtf_nnet/keras/quantization/default_quantize_configs.py
jiafulow/emtf-nnet
70a6c747c221178f9db940197ea886bdb60bf3ba
[ "Apache-2.0" ]
null
null
null
emtf_nnet/keras/quantization/default_quantize_configs.py
jiafulow/emtf-nnet
70a6c747c221178f9db940197ea886bdb60bf3ba
[ "Apache-2.0" ]
null
null
null
# The following source code was originally obtained from: # https://github.com/tensorflow/model-optimization/blob/v0.7.0/tensorflow_model_optimization/python/core/quantization/keras/default_8bit/default_8bit_quantize_configs.py # https://github.com/tensorflow/model-optimization/blob/v0.7.0/tensorflow_model_optimization/python/core/quantization/keras/default_8bit/default_8bit_quantize_registry.py # ============================================================================== # Copyright 2019 The TensorFlow Authors. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # ============================================================================== """Default quantization configs.""" import tensorflow as tf from tensorflow_model_optimization.python.core.quantization.keras import quantize_config from tensorflow_model_optimization.python.core.quantization.keras import quantizers from .quantizers import FixedRangeQuantizer class NoOpQuantizeConfig(quantize_config.QuantizeConfig): """QuantizeConfig which does not quantize any part of the layer.""" def get_weights_and_quantizers(self, layer): return [] def get_activations_and_quantizers(self, layer): return [] def set_quantize_weights(self, layer, quantize_weights): pass def set_quantize_activations(self, layer, quantize_activations): pass def get_output_quantizers(self, layer): return [] def get_config(self): return {} class DefaultInputQuantizeConfig(quantize_config.QuantizeConfig): """QuantizeConfig which only quantizes the inputs to a layer.""" def get_weights_and_quantizers(self, layer): return [] def get_activations_and_quantizers(self, layer): return [] def set_quantize_weights(self, layer, quantize_weights): pass def set_quantize_activations(self, layer, quantize_activations): pass def get_output_quantizers(self, layer): quantizer = quantizers.AllValuesQuantizer( num_bits=8, per_axis=False, symmetric=False, narrow_range=False) return [quantizer] def get_config(self): return {} #FIXME: hardcoded layer name and quantizer class DefaultOutputQuantizeConfig(quantize_config.QuantizeConfig): """QuantizeConfig which only quantizes the outputs from a layer.""" def get_weights_and_quantizers(self, layer): return [] def get_activations_and_quantizers(self, layer): return [] def set_quantize_weights(self, layer, quantize_weights): pass def set_quantize_activations(self, layer, quantize_activations): pass def get_output_quantizers(self, layer): if layer.name == 'preprocessing': quantizer = FixedRangeQuantizer(num_bits=14, num_int_bits=4, narrow_range=True) elif layer.name == 'activation' or layer.name == 'activation_1' or layer.name == 'activation_2': quantizer = FixedRangeQuantizer(num_bits=14, num_int_bits=1, narrow_range=True) else: quantizer = quantizers.MovingAverageQuantizer( num_bits=8, per_axis=False, symmetric=False, narrow_range=False) return [quantizer] def get_config(self): return {} #FIXME: hardcoded layer name and quantizer class DefaultDenseQuantizeConfig(quantize_config.QuantizeConfig): """QuantizeConfig which quantizes the weights and activations of a layer.""" def get_weights_and_quantizers(self, layer): if layer.name == 'dense_final': quantizer = FixedRangeQuantizer(num_bits=12, num_int_bits=3) else: quantizer = quantizers.LastValueQuantizer( num_bits=8, per_axis=False, symmetric=True, narrow_range=True) return [(layer.kernel, quantizer)] def get_activations_and_quantizers(self, layer): if layer.name == 'dense_final': quantizer = FixedRangeQuantizer(num_bits=14, num_int_bits=1) else: quantizer = quantizers.MovingAverageQuantizer( num_bits=8, per_axis=False, symmetric=False, narrow_range=False) return [(layer.activation, quantizer)] def set_quantize_weights(self, layer, quantize_weights): layer.kernel = quantize_weights[0] layer.folded_kernel = quantize_weights[0] def set_quantize_activations(self, layer, quantize_activations): layer.activation = quantize_activations[0] def get_output_quantizers(self, layer): return [] def get_config(self): return {} #FIXME: hardcoded layer name and quantizer class DefaultDenseFoldQuantizeConfig(quantize_config.QuantizeConfig): """QuantizeConfig which keeps the quantizers for the weights and activations of a layer.""" def get_weights_and_quantizers(self, layer): weight = layer.kernel weight_name = layer.kernel.name.split(':')[0].split('/')[-1] if layer.name == 'dense': quantizer = FixedRangeQuantizer(num_bits=10, num_int_bits=4) elif layer.name == 'dense_1': quantizer = FixedRangeQuantizer(num_bits=10, num_int_bits=4) elif layer.name == 'dense_2': quantizer = FixedRangeQuantizer(num_bits=10, num_int_bits=4) else: quantizer = quantizers.LastValueQuantizer( num_bits=8, per_axis=False, symmetric=True, narrow_range=True) quantizer_vars = quantizer.build(weight.shape, weight_name, layer) layer._quantize_weight_vars = [(weight, quantizer, quantizer_vars)] # Hack to set initial m_by_n sparsity mask layer._initial_m_by_n_mask = tf.cast( tf.cast(weight, tf.bool), weight.dtype) return [] def get_activations_and_quantizers(self, layer): activation = layer.activation activation_name = 'post_activation' if layer.name == 'dense': quantizer = FixedRangeQuantizer(num_bits=12, num_int_bits=3) elif layer.name == 'dense_1': quantizer = FixedRangeQuantizer(num_bits=12, num_int_bits=3) elif layer.name == 'dense_2': quantizer = FixedRangeQuantizer(num_bits=12, num_int_bits=3) else: quantizer = quantizers.MovingAverageQuantizer( num_bits=8, per_axis=False, symmetric=False, narrow_range=False) quantizer_vars = quantizer.build(None, activation_name, layer) layer._quantize_activation_vars = [(activation, quantizer, quantizer_vars)] return [] def set_quantize_weights(self, layer, quantize_weights): pass def set_quantize_activations(self, layer, quantize_activations): pass def get_output_quantizers(self, layer): return [] def get_config(self): return {}
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5
475525e4e171bbb56d35cb22eb8028d1b6264211
45
py
Python
scripts/example.py
elespike/publisher
99e7d68dcf3863127325fe501a54d02bb718176d
[ "MIT" ]
1
2019-04-14T16:07:02.000Z
2019-04-14T16:07:02.000Z
scripts/example.py
elespike/publisher
99e7d68dcf3863127325fe501a54d02bb718176d
[ "MIT" ]
null
null
null
scripts/example.py
elespike/publisher
99e7d68dcf3863127325fe501a54d02bb718176d
[ "MIT" ]
null
null
null
#! /usr/bin/python3 print('Python example')
11.25
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5
476b87623bf1ddcc44e5cd7b11f16976beebbcd2
140
py
Python
exchange/admin.py
YaseminGrcn/django-exchange
bb4e125ee5ef3ea4e9cb70da89f4833d8a440eeb
[ "MIT" ]
null
null
null
exchange/admin.py
YaseminGrcn/django-exchange
bb4e125ee5ef3ea4e9cb70da89f4833d8a440eeb
[ "MIT" ]
2
2017-07-21T19:37:28.000Z
2017-07-21T19:37:37.000Z
exchange/admin.py
YaseminGrcn/django-exchange
bb4e125ee5ef3ea4e9cb70da89f4833d8a440eeb
[ "MIT" ]
1
2018-06-23T14:39:07.000Z
2018-06-23T14:39:07.000Z
from django.contrib import admin from models import Currency, ExchangeRate admin.site.register(Currency) admin.site.register(ExchangeRate)
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0.555556
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5
4782cf7c12ca8f1b156b010f2e53f92328d9d280
131
py
Python
battery_checker/__init__.py
code-byter/low-battery-notification
867764406df2730f3c844a63d9b0b7713606a544
[ "MIT" ]
2
2020-11-12T22:35:00.000Z
2021-03-28T12:19:39.000Z
battery_checker/__init__.py
code-byter/low-battery-notification
867764406df2730f3c844a63d9b0b7713606a544
[ "MIT" ]
null
null
null
battery_checker/__init__.py
code-byter/low-battery-notification
867764406df2730f3c844a63d9b0b7713606a544
[ "MIT" ]
null
null
null
from battery_checker.main import check_status check_status.low = False check_status.empty = False check_status.is_charging = False
26.2
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5
46
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5
4794ab8054b63a4c29384ec8a42a7ab3966fa2b4
116
py
Python
bk_test.py
dwbxm/Python-1
63f0d5088ed7abfad9c7b0a8cc35cba7d63acb41
[ "MIT" ]
null
null
null
bk_test.py
dwbxm/Python-1
63f0d5088ed7abfad9c7b0a8cc35cba7d63acb41
[ "MIT" ]
null
null
null
bk_test.py
dwbxm/Python-1
63f0d5088ed7abfad9c7b0a8cc35cba7d63acb41
[ "MIT" ]
null
null
null
#! /usr/bin/env python if __name == "__main__": print("lbk jenkins test") print("lbk changes test status")
19.333333
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5
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5
47c59740e401d87a6b5c5c55c7460d7a11c66337
1,866
py
Python
Genetic algorithm.py
Munaze/Machine-learning-deep-learning-projects
9d77ce45ebc7cc4f74dfe0b06b5dcf0732cc212f
[ "MIT" ]
null
null
null
Genetic algorithm.py
Munaze/Machine-learning-deep-learning-projects
9d77ce45ebc7cc4f74dfe0b06b5dcf0732cc212f
[ "MIT" ]
null
null
null
Genetic algorithm.py
Munaze/Machine-learning-deep-learning-projects
9d77ce45ebc7cc4f74dfe0b06b5dcf0732cc212f
[ "MIT" ]
null
null
null
from tpot import TPOT from sklearn.cross_validation import train_test_split import pandas as pd import numpy as np telescope = pd.read_csv("MAGIC Gamma Telescope Data.csv") telescope_shuffle = telescope.iloc[np.random.permutation(len[telescope])] tele = telescope_shuffle.reset_index(drop = True) tele['Class'] = tele['Class'].map({'g':0, 'h':1}) tele_class = tele['Class'].values training_indices, validation_indices = training_indices,testing_indices = train_test_split(tele.index, stratify = tele_class,train_size = 0.75,test_size = 0.25) tpot = TPOT(generation = 5,verbosity =2) tpot.fit(tele.drop('Class',axis =1).loc[training_indices].values, tele.loc[training_indices,'Class'].values) tpot.score(tele.drop('Class', axis =1).loc[validation_indices].values, tele.loc[validation_indices,'Class'].values) ''' #load the data telescope=pd.read_csv('MAGIC Gamma Telescope Data.csv') #clean the data telescope_shuffle=telescope.iloc[np.random.permutation(len(telescope))] tele=telescope_shuffle.reset_index(drop=True) #Store 2 classes tele['Class']=tele['Class'].map({'g':0, 'h':1}) tele_class = tele['Class'].values #Split training, testing, and validation data training_indices, validation_indices = training_indices, testing_indices = train_test_split(tele.index, stratify= tele_class, train_size=0.75, test_size=0.25) #Let Genetic Programming find best ML model and hyperparameters tpot = TPOTClassifier(generations=5, verbosity=2) tpot.fit(tele.drop('Class', axis=1).loc[training_indices].values, tele.loc[training_indicss, 'Class'].values) #Score the accuracy tpot.score(tele.drop('Class', axis=1).loc[validation_indices].values, tele.loc[validation_indices, 'Class'].values) #Export the generated code tpot.export('pipeline.py') '''
36.588235
148
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1,866
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0.724792
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0.724792
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9a096c694f2f0242d8c0f03372bda889b2ee63e0
123
py
Python
python/8kyu/is_it_event.py
Sigmanificient/codewars
b34df4bf55460d312b7ddf121b46a707b549387a
[ "MIT" ]
3
2021-06-08T01:57:13.000Z
2021-06-26T10:52:47.000Z
python/8kyu/is_it_event.py
Sigmanificient/codewars
b34df4bf55460d312b7ddf121b46a707b549387a
[ "MIT" ]
null
null
null
python/8kyu/is_it_event.py
Sigmanificient/codewars
b34df4bf55460d312b7ddf121b46a707b549387a
[ "MIT" ]
2
2021-06-10T21:20:13.000Z
2021-06-30T10:13:26.000Z
"""Kata url: https://www.codewars.com/kata/555a67db74814aa4ee0001b5.""" def is_even(n: int) -> int: return not n % 2
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0
5
9a256c0f84955a085d6c3e318ef67eca785a40b7
128
py
Python
loganalyzer/__init__.py
Farzin-Negahbani/Namira_LogAnalyzer
291b91df43e4744ea887f10fc45fb17a15545c7b
[ "MIT" ]
5
2019-02-12T13:54:12.000Z
2020-01-13T09:28:54.000Z
loganalyzer/__init__.py
Farzin-Negahbani/namira_LogAnalyzer
291b91df43e4744ea887f10fc45fb17a15545c7b
[ "MIT" ]
null
null
null
loganalyzer/__init__.py
Farzin-Negahbani/namira_LogAnalyzer
291b91df43e4744ea887f10fc45fb17a15545c7b
[ "MIT" ]
2
2018-11-26T09:41:12.000Z
2019-02-12T13:56:15.000Z
from .Game import Game from .Parser import Parser from .Analyzer import Analyzer from .Agent import Agent from .Team import Team
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9a39cc1aa3fb4d1fe01770c178d18b0138b83f4e
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py
Python
tests/core/pyspec/eth2spec/test/bellatrix/fork/test_bellatrix_fork_random.py
sifraitech/eth2.0-specs
1bfefe301da592375e2e02f65849a96aadec1936
[ "CC0-1.0" ]
497
2021-08-19T01:22:07.000Z
2022-03-30T21:40:40.000Z
tests/core/pyspec/eth2spec/test/bellatrix/fork/test_bellatrix_fork_random.py
sifraitech/eth2.0-specs
1bfefe301da592375e2e02f65849a96aadec1936
[ "CC0-1.0" ]
133
2021-08-18T16:47:29.000Z
2022-03-31T22:31:56.000Z
tests/core/pyspec/eth2spec/test/bellatrix/fork/test_bellatrix_fork_random.py
sifraitech/eth2.0-specs
1bfefe301da592375e2e02f65849a96aadec1936
[ "CC0-1.0" ]
98
2021-08-31T09:19:27.000Z
2022-03-27T05:07:04.000Z
from random import Random from eth2spec.test.context import ( with_phases, with_custom_state, with_presets, spec_test, with_state, low_balances, misc_balances, large_validator_set, ) from eth2spec.test.utils import with_meta_tags from eth2spec.test.helpers.constants import ( ALTAIR, BELLATRIX, MINIMAL, ) from eth2spec.test.helpers.bellatrix.fork import ( BELLATRIX_FORK_TEST_META_TAGS, run_fork_test, ) from eth2spec.test.helpers.random import randomize_state @with_phases(phases=[ALTAIR], other_phases=[BELLATRIX]) @spec_test @with_state @with_meta_tags(BELLATRIX_FORK_TEST_META_TAGS) def test_bellatrix_fork_random_0(spec, phases, state): randomize_state(spec, state, rng=Random(1010)) yield from run_fork_test(phases[BELLATRIX], state) @with_phases(phases=[ALTAIR], other_phases=[BELLATRIX]) @spec_test @with_state @with_meta_tags(BELLATRIX_FORK_TEST_META_TAGS) def test_bellatrix_fork_random_1(spec, phases, state): randomize_state(spec, state, rng=Random(2020)) yield from run_fork_test(phases[BELLATRIX], state) @with_phases(phases=[ALTAIR], other_phases=[BELLATRIX]) @spec_test @with_state @with_meta_tags(BELLATRIX_FORK_TEST_META_TAGS) def test_bellatrix_fork_random_2(spec, phases, state): randomize_state(spec, state, rng=Random(3030)) yield from run_fork_test(phases[BELLATRIX], state) @with_phases(phases=[ALTAIR], other_phases=[BELLATRIX]) @spec_test @with_state @with_meta_tags(BELLATRIX_FORK_TEST_META_TAGS) def test_bellatrix_fork_random_3(spec, phases, state): randomize_state(spec, state, rng=Random(4040)) yield from run_fork_test(phases[BELLATRIX], state) @with_phases(phases=[ALTAIR], other_phases=[BELLATRIX]) @spec_test @with_custom_state(balances_fn=low_balances, threshold_fn=lambda spec: spec.config.EJECTION_BALANCE) @with_meta_tags(BELLATRIX_FORK_TEST_META_TAGS) def test_bellatrix_fork_random_low_balances(spec, phases, state): randomize_state(spec, state, rng=Random(5050)) yield from run_fork_test(phases[BELLATRIX], state) @with_phases(phases=[ALTAIR], other_phases=[BELLATRIX]) @spec_test @with_custom_state(balances_fn=misc_balances, threshold_fn=lambda spec: spec.config.EJECTION_BALANCE) @with_meta_tags(BELLATRIX_FORK_TEST_META_TAGS) def test_bellatrix_fork_random_misc_balances(spec, phases, state): randomize_state(spec, state, rng=Random(6060)) yield from run_fork_test(phases[BELLATRIX], state) @with_phases(phases=[ALTAIR], other_phases=[BELLATRIX]) @with_presets([MINIMAL], reason="mainnet config leads to larger validator set than limit of public/private keys pre-generated") @spec_test @with_custom_state(balances_fn=large_validator_set, threshold_fn=lambda spec: spec.config.EJECTION_BALANCE) @with_meta_tags(BELLATRIX_FORK_TEST_META_TAGS) def test_bellatrix_fork_random_large_validator_set(spec, phases, state): randomize_state(spec, state, rng=Random(7070)) yield from run_fork_test(phases[BELLATRIX], state)
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7bd6673da58c2489bc56e9de7bdcd433319b4f95
38
py
Python
tests/__init__.py
NicholasDeKock/autoesda
5ca60d5d72161dc7c551e48b845efe10efccbfe7
[ "BSD-3-Clause" ]
null
null
null
tests/__init__.py
NicholasDeKock/autoesda
5ca60d5d72161dc7c551e48b845efe10efccbfe7
[ "BSD-3-Clause" ]
9
2022-02-13T09:55:37.000Z
2022-02-16T12:16:06.000Z
tests/__init__.py
NicholasDeKock/autoESDA
fc1c759cd3c6d3f05e8279c0dd634cf7a841c4fb
[ "BSD-3-Clause" ]
null
null
null
"""Unit test package for autoesda."""
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7bd907e6c0c8a18c1c5bfde178fd84065669626d
89
py
Python
books/admin.py
fabricioifc/ifcarros
f2b3597929760e7ab0d2a349a60a70b3f2c1265b
[ "Apache-2.0" ]
1
2020-04-29T13:09:07.000Z
2020-04-29T13:09:07.000Z
books/admin.py
RikuSun/OhsihaOIKEA
7df06fd5c904067a1e0c3db58fa904fd2b7065b6
[ "MIT" ]
null
null
null
books/admin.py
RikuSun/OhsihaOIKEA
7df06fd5c904067a1e0c3db58fa904fd2b7065b6
[ "MIT" ]
null
null
null
from django.contrib import admin from books.models import Book admin.site.register(Book)
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5.285714
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5
7bf2569cb81ea27e90c6863ab7a35deead3dd74d
205
py
Python
docs/live/ctype.py
aristanetworks/ctypegen
379f8e5c712c8deb0ed27cbf005d7706fa11e6e8
[ "Apache-2.0" ]
17
2018-06-12T10:07:42.000Z
2022-03-23T14:03:33.000Z
docs/live/ctype.py
aristanetworks/ctypegen
379f8e5c712c8deb0ed27cbf005d7706fa11e6e8
[ "Apache-2.0" ]
4
2018-10-29T17:55:34.000Z
2021-10-08T07:19:12.000Z
docs/live/ctype.py
aristanetworks/ctypegen
379f8e5c712c8deb0ed27cbf005d7706fa11e6e8
[ "Apache-2.0" ]
7
2018-12-20T19:35:45.000Z
2021-05-18T03:42:17.000Z
#! /usr/bin/env python from CTypeGen import generate import paths generate([ paths.libc ], "libcgen.py", [], ["_IO_fgets", "_IO_puts"]) generate([ paths.testme ], "testmegen.py", [], ["functionToTest"])
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0
0
5
7bf6d92f6a57d6d1e9d77d0830365e7bae9c2b37
138
py
Python
dearpypixl/plotting.py
Atlamillias/pixl-engine
c4217a3a65e01e49d05bf7f07946d65484f6e1da
[ "MIT" ]
6
2021-08-28T03:22:19.000Z
2021-10-14T22:04:04.000Z
dearpypixl/plotting.py
Atlamillias/pixl-engine
c4217a3a65e01e49d05bf7f07946d65484f6e1da
[ "MIT" ]
1
2021-07-29T16:51:28.000Z
2021-08-03T00:24:11.000Z
dearpypixl/plotting.py
Atlamillias/pixl-engine
c4217a3a65e01e49d05bf7f07946d65484f6e1da
[ "MIT" ]
null
null
null
import dearpypixl.appitems.plotting from dearpypixl.appitems.plotting import * __all__ = [ *dearpypixl.appitems.plotting.__all__, ]
17.25
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7.142857
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7
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5
7bfe4bf37d7320ddb6b59a88ee767cace06ccf01
43
py
Python
loadtests/completion_api/__init__.py
edx/edx-load-tests
1a6dc891d2fb72575f354521988a531489f30032
[ "Apache-2.0" ]
18
2016-01-31T13:29:56.000Z
2019-02-08T18:08:49.000Z
loadtests/completion_api/__init__.py
raccoongang/edx-load-tests
1a6dc891d2fb72575f354521988a531489f30032
[ "Apache-2.0" ]
92
2015-07-31T20:16:51.000Z
2019-08-09T14:32:12.000Z
loadtests/completion_api/__init__.py
edx/edx-load-tests
1a6dc891d2fb72575f354521988a531489f30032
[ "Apache-2.0" ]
15
2015-08-19T15:23:58.000Z
2018-02-01T19:47:38.000Z
from locustfile import CompletionApiLocust
21.5
42
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9.75
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5
d0325bd603bcd719d9e8386f2a67b8e4712de360
309
py
Python
footrecon/__init__.py
tasooshi/footrecon
1fecec87ae94ae3baa3d15c30c2b3bddc261d706
[ "MIT" ]
null
null
null
footrecon/__init__.py
tasooshi/footrecon
1fecec87ae94ae3baa3d15c30c2b3bddc261d706
[ "MIT" ]
4
2021-11-25T13:29:50.000Z
2021-11-26T21:21:16.000Z
footrecon/__init__.py
tasooshi/footrecon
1fecec87ae94ae3baa3d15c30c2b3bddc261d706
[ "MIT" ]
1
2022-01-13T18:15:21.000Z
2022-01-13T18:15:21.000Z
from footrecon.core.modules import Session from footrecon.modules.audio import * from footrecon.modules.bluetooth import * from footrecon.modules.satnav import * from footrecon.modules.camera import * from footrecon.modules.wireless import * name = 'Footrecon' name_lower = name.lower() __version__ = '0.5'
25.75
42
0.796117
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309
6.025
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1
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0
5
d055086bb3d7299c5f78fc30ea34322babe4f4a5
247
py
Python
openapi2jsonschema/log.py
haemyung/openapi2jsonschema
8412aeaee94d25ad39fc665ce798123b54fdb0cc
[ "Apache-2.0" ]
106
2019-04-25T08:23:14.000Z
2022-03-31T17:11:09.000Z
openapi2jsonschema/log.py
haemyung/openapi2jsonschema
8412aeaee94d25ad39fc665ce798123b54fdb0cc
[ "Apache-2.0" ]
220
2020-02-04T18:49:22.000Z
2022-03-31T19:08:42.000Z
openapi2jsonschema/log.py
haemyung/openapi2jsonschema
8412aeaee94d25ad39fc665ce798123b54fdb0cc
[ "Apache-2.0" ]
46
2019-05-03T10:55:04.000Z
2022-03-07T14:45:17.000Z
#!/usr/bin/env python import click def info(message): click.echo(click.style(message, fg="green")) def debug(message): click.echo(click.style(message, fg="yellow")) def error(message): click.echo(click.style(message, fg="red"))
15.4375
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0.680162
36
247
4.666667
0.472222
0.214286
0.285714
0.375
0.625
0.625
0.625
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0
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0.1417
247
15
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0
null
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0
0
0
1
0
0
5
d065e4a71169cae83315a26882596bccfed4e275
26
py
Python
plastering/inferencers/__init__.py
PeterYang21/plastering
7c7a21b2f18df78a9d8ec29f3d1d9f47d82c658f
[ "MIT" ]
null
null
null
plastering/inferencers/__init__.py
PeterYang21/plastering
7c7a21b2f18df78a9d8ec29f3d1d9f47d82c658f
[ "MIT" ]
null
null
null
plastering/inferencers/__init__.py
PeterYang21/plastering
7c7a21b2f18df78a9d8ec29f3d1d9f47d82c658f
[ "MIT" ]
null
null
null
from .inferencer import *
13
25
0.769231
3
26
6.666667
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d089a4fc3f8498055d29cdf56e12db1b75438a15
81
py
Python
web/olga/charts/tests/__init__.py
raccoongang/acceptor
fdc1504912b502c8d789d5478eba8cc1a491934b
[ "Apache-2.0" ]
5
2017-10-20T05:52:59.000Z
2020-02-25T10:46:33.000Z
web/olga/charts/tests/__init__.py
raccoongang/OLGA
fdc1504912b502c8d789d5478eba8cc1a491934b
[ "Apache-2.0" ]
233
2017-08-14T10:56:16.000Z
2021-04-07T01:09:17.000Z
web/olga/charts/tests/__init__.py
raccoongang/acceptor
fdc1504912b502c8d789d5478eba8cc1a491934b
[ "Apache-2.0" ]
2
2018-03-16T22:22:57.000Z
2018-06-15T20:02:56.000Z
# pylint: disable-all # flake8: noqa from olga.charts.tests.test_views import *
16.2
42
0.753086
12
81
5
1
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0.014286
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4
43
20.25
0.842857
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1
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1
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0
5
d0b0a4cc3f8e7f5179d4cac7bd18cb694fedcd42
248
py
Python
tests/test_lesson2_odd_occurrences_in_array.py
ardenn/codility
45f8d5ae7de92cfde60a3f3f5ebee2a233273bd4
[ "MIT" ]
null
null
null
tests/test_lesson2_odd_occurrences_in_array.py
ardenn/codility
45f8d5ae7de92cfde60a3f3f5ebee2a233273bd4
[ "MIT" ]
null
null
null
tests/test_lesson2_odd_occurrences_in_array.py
ardenn/codility
45f8d5ae7de92cfde60a3f3f5ebee2a233273bd4
[ "MIT" ]
null
null
null
from solutions.lesson2_odd_occurrences_in_array import solution def test_multiple_pairs_of_same_element(): assert solution([9, 3, 9, 3, 9, 7, 9]) == 7 def test_single_pairs_of_same_element(): assert solution([9, 3, 8, 3, 8, 7, 9]) == 7
24.8
63
0.71371
43
248
3.790698
0.511628
0.03681
0.134969
0.220859
0.417178
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0.417178
0.417178
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0.16129
248
9
64
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1
0
0
0
1
0
0
5
d0f1a1dbb4c4e0d1e14e80e655d653d2af9595af
3,660
py
Python
tests/test_inmem.py
kiri-ai/kiri-search
78a0f78b11b73cca8934054498d5713773d3e93a
[ "Apache-2.0" ]
null
null
null
tests/test_inmem.py
kiri-ai/kiri-search
78a0f78b11b73cca8934054498d5713773d3e93a
[ "Apache-2.0" ]
null
null
null
tests/test_inmem.py
kiri-ai/kiri-search
78a0f78b11b73cca8934054498d5713773d3e93a
[ "Apache-2.0" ]
null
null
null
from kiri import Kiri, Document, ChunkedDocument from kiri.search import SearchResult import pytest def get_docs(): doc1 = Document("Hello I am a document. This is a sentence") doc2 = Document("Hello I am another document. This is another sentence") docs = [doc1, doc2] return docs def get_chunked_docs(chunking_level=1): doc1 = ChunkedDocument( "Hello I am a document. This is a sentence", chunking_level=chunking_level) doc2 = ChunkedDocument( "Hello I am another document. This is another sentence", chunking_level=chunking_level) docs = [doc1, doc2] return docs def test_init(): kiri = Kiri(local=True) def test_upload(): kiri = Kiri(local=True) docs = get_docs() kiri.upload(docs) assert docs[0].vector is not None, "Document not vectorised" assert docs[1].vector is not None, "Document not vectorised" assert len(kiri._store.documents) == 2, "Incorrect number of documents in mem" def test_upload_chunked(): kiri = Kiri(local=True) docs = get_chunked_docs(chunking_level=1) kiri.upload(docs) assert len(kiri._store.documents) == 2, "Incorrect number of documents in mem" for doc in docs: assert doc.vector is not None, "Document not vectorised" assert len(doc.chunk_vectors) == 2, "Invalid number of chunk vectors" def test_upload_dup_id(): kiri = Kiri(local=True) docs = get_docs() for doc in docs: doc.id = "123" with pytest.raises(ValueError): kiri.upload(docs) def test_upload_mixed_type(): kiri = Kiri(local=True) docs = [Document("a"), ChunkedDocument("b")] with pytest.raises(ValueError): kiri.upload(docs) def test_search(): kiri = Kiri(local=True) docs = get_docs() kiri.upload(docs) results = kiri.search("another") assert len(results.results) == 2, "Invalid number of search results" def test_search_max_results(): kiri = Kiri(local=True) docs = get_docs() kiri.upload(docs) results = kiri.search("another", max_results=1) assert len(results.results) == 1, "Invalid number of search results" def test_search_ids(): kiri = Kiri(local=True) docs = get_docs() docs[0].id = "123" kiri.upload(docs) results = kiri.search("another", ids=["123"]) assert len(results.results) == 1, "Invalid number of search results" def test_search_chunk(): kiri = Kiri(local=True) docs = get_chunked_docs() kiri.upload(docs) results = kiri.search("another") assert len(results.results) == 2, "Invalid number of search results" def test_search_max_results_chunk(): kiri = Kiri(local=True) docs = get_chunked_docs() kiri.upload(docs) results = kiri.search("another", max_results=1) assert len(results.results) == 1, "Invalid number of search results" def test_search_ids_chunk(): kiri = Kiri(local=True) docs = get_chunked_docs() docs[0].id = "123" kiri.upload(docs) results = kiri.search("another", ids=["123"]) assert len(results.results) == 1, "Invalid number of search results" def test_qa(): kiri = Kiri(local=True) docs = get_docs() kiri.upload(docs) results = kiri.qa("another?") assert isinstance(results, list) for result in results: assert type(result[0]) == str assert isinstance(result[1], SearchResult) def test_qa_chunk(): kiri = Kiri(local=True) docs = get_chunked_docs() kiri.upload(docs) results = kiri.qa("another?") assert isinstance(results, list) for result in results: assert type(result[0]) == str assert isinstance(result[1], SearchResult)
27.518797
95
0.669672
502
3,660
4.766932
0.135458
0.038028
0.070623
0.092353
0.831174
0.800669
0.762223
0.740493
0.708316
0.556623
0
0.015267
0.212568
3,660
132
96
27.727273
0.815059
0
0
0.69
0
0
0.171311
0
0
0
0
0
0.18
1
0.15
false
0
0.03
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0.2
0
0
0
0
null
0
0
0
1
1
1
1
1
0
0
0
0
0
0
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0
0
0
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0
0
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null
0
0
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0
0
0
0
0
0
0
0
0
0
5
efc0fd71253051fbda442a767c2d1edc4eaf2248
381
py
Python
test/python/WMCore_t/REST_t/Format_t.py
khurtado/WMCore
f74e252412e49189a92962945a94f93bec81cd1e
[ "Apache-2.0" ]
21
2015-11-19T16:18:45.000Z
2021-12-02T18:20:39.000Z
test/python/WMCore_t/REST_t/Format_t.py
khurtado/WMCore
f74e252412e49189a92962945a94f93bec81cd1e
[ "Apache-2.0" ]
5,671
2015-01-06T14:38:52.000Z
2022-03-31T22:11:14.000Z
test/python/WMCore_t/REST_t/Format_t.py
khurtado/WMCore
f74e252412e49189a92962945a94f93bec81cd1e
[ "Apache-2.0" ]
67
2015-01-21T15:55:38.000Z
2022-02-03T19:53:13.000Z
from WMCore.REST.Format import RESTFormat from WMCore.REST.Format import XMLFormat from WMCore.REST.Format import JSONFormat from WMCore.REST.Format import RawFormat from WMCore.REST.Format import DigestETag from WMCore.REST.Format import MD5ETag from WMCore.REST.Format import SHA1ETag RESTFormat() XMLFormat("app") JSONFormat() RawFormat() DigestETag('md5') MD5ETag() SHA1ETag()
25.4
41
0.824147
51
381
6.156863
0.27451
0.22293
0.312102
0.44586
0.579618
0
0
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0.014451
0.091864
381
14
42
27.214286
0.893064
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true
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0
1
0
1
0
0
0
0
5
ef334e36e6f3b98d0505feea811dec6ffecb5edf
29
py
Python
Tests/(Experiments)/runtslots.py
jwilk/Pyrex
83dfbae1261788933472e3f9c501ad74c61a37c5
[ "Apache-2.0" ]
5
2019-05-26T20:48:36.000Z
2021-07-09T01:38:38.000Z
Tests/(Experiments)/runtslots.py
jwilk/Pyrex
83dfbae1261788933472e3f9c501ad74c61a37c5
[ "Apache-2.0" ]
null
null
null
Tests/(Experiments)/runtslots.py
jwilk/Pyrex
83dfbae1261788933472e3f9c501ad74c61a37c5
[ "Apache-2.0" ]
1
2022-02-10T07:14:58.000Z
2022-02-10T07:14:58.000Z
import tslots tslots.probe()
9.666667
14
0.793103
4
29
5.75
0.75
0
0
0
0
0
0
0
0
0
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0
0.103448
29
2
15
14.5
0.884615
0
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true
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0
0
0
1
0
1
0
0
0
0
5
ef4026caa6011517270fd2f1ea5357de4aa806c9
105
py
Python
tests/test_edgar_frames.py
cowboycodeman/tidyxbrl
b669184815a293c5415d259b9edb57cdc95088c3
[ "MIT" ]
null
null
null
tests/test_edgar_frames.py
cowboycodeman/tidyxbrl
b669184815a293c5415d259b9edb57cdc95088c3
[ "MIT" ]
null
null
null
tests/test_edgar_frames.py
cowboycodeman/tidyxbrl
b669184815a293c5415d259b9edb57cdc95088c3
[ "MIT" ]
null
null
null
import tidyxbrl tidyxbrl.edgar_frames(urldescriptor = 'us-gaap/NonoperatingIncomeExpense/USD/CY2019Q1I')
35
88
0.857143
11
105
8.090909
0.909091
0
0
0
0
0
0
0
0
0
0
0.05
0.047619
105
3
88
35
0.84
0
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0.443396
0.443396
0
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true
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null
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null
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1
0
1
0
0
0
0
5
ef5b8fca57606af79ad815079ad15662ccf53bb9
1,475
py
Python
tests/palindrome_number.py
henryvalbuena/challenges
9b305153ee60cfb1fd28d42aa638fc43071b0245
[ "MIT" ]
null
null
null
tests/palindrome_number.py
henryvalbuena/challenges
9b305153ee60cfb1fd28d42aa638fc43071b0245
[ "MIT" ]
null
null
null
tests/palindrome_number.py
henryvalbuena/challenges
9b305153ee60cfb1fd28d42aa638fc43071b0245
[ "MIT" ]
null
null
null
from unittest import TestCase from problems.palinrome_number import Solution class TestChallenges(TestCase): """Base test cases for coding challenges""" def setUp(self): self.res = Solution().isPalindrome def test_case_1(self): self.assertTrue(self.res(111)) def test_case_2(self): self.assertTrue(self.res(121)) def test_case_3(self): self.assertFalse(self.res(123)) def test_case_4(self): self.assertFalse(self.res(-32134123123)) def test_case_5(self): self.assertTrue(self.res(0)) def test_case_6(self): self.assertFalse(self.res(10)) def test_case_7(self): self.assertFalse(self.res(None)) def test_case_8(self): self.assertTrue(self.res(123454321)) def test_case_9(self): self.assertTrue(self.res(99)) def test_case_10(self): self.assertTrue(self.res(7777)) def test_case_11(self): self.assertFalse(self.res(12)) def test_case_12(self): self.assertTrue(self.res(00)) def test_case_13(self): self.assertTrue(self.res(1)) def test_case_14(self): self.assertTrue(self.res(5)) def test_case_15(self): self.assertFalse(self.res(21120)) def test_case_16(self): self.assertFalse(self.res(123554321)) def test_case_17(self): self.assertFalse(self.res(111201111))
24.583333
49
0.621017
196
1,475
4.494898
0.27551
0.163451
0.212259
0.224745
0.491487
0
0
0
0
0
0
0.084559
0.262373
1,475
59
50
25
0.725184
0.025085
0
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1
0.461538
false
0
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0
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null
0
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1
0
0
0
0
1
0
0
5
ef629b9ec7eb10b5996e22c39aa5fed511c26d62
84
py
Python
tests/data/templates.py
jakearchibald/pystache
b7de415288c2c2a71bdae4d87cbff1f2978b419a
[ "MIT" ]
1
2017-04-01T21:14:38.000Z
2017-04-01T21:14:38.000Z
tests/data/templates.py
jakearchibald/pystache
b7de415288c2c2a71bdae4d87cbff1f2978b419a
[ "MIT" ]
null
null
null
tests/data/templates.py
jakearchibald/pystache
b7de415288c2c2a71bdae4d87cbff1f2978b419a
[ "MIT" ]
null
null
null
# coding: utf-8 class SayHello(object): def to(self): return "World"
10.5
23
0.583333
11
84
4.454545
1
0
0
0
0
0
0
0
0
0
0
0.016667
0.285714
84
7
24
12
0.8
0.154762
0
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0.072464
0
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1
0.333333
false
0
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1
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null
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0
0
0
1
1
0
0
5
323517bbae4ee7e9aae30e108eab36eec66e5a3d
22
py
Python
examples/test.py
Barrio-Bots/Bots
670703c79ffca4e369e0eae9df687100cd3dee91
[ "MIT" ]
null
null
null
examples/test.py
Barrio-Bots/Bots
670703c79ffca4e369e0eae9df687100cd3dee91
[ "MIT" ]
null
null
null
examples/test.py
Barrio-Bots/Bots
670703c79ffca4e369e0eae9df687100cd3dee91
[ "MIT" ]
null
null
null
print("Hello, Docs!")
11
21
0.636364
3
22
4.666667
1
0
0
0
0
0
0
0
0
0
0
0
0.090909
22
1
22
22
0.7
0
0
0
0
0
0.545455
0
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0
0
1
0
true
0
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1
1
0
null
0
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null
0
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0
0
0
1
0
0
0
0
1
0
5
3236e573d51caeeaf53e6de40324991b2c38aa91
164
py
Python
spark_deploy/internal/defaults/start.py
Sebastiaan-Alvarez-Rodriguez/spark-deploy
1e2f6da38576089a63fa910f2efc75ade563364a
[ "MIT" ]
null
null
null
spark_deploy/internal/defaults/start.py
Sebastiaan-Alvarez-Rodriguez/spark-deploy
1e2f6da38576089a63fa910f2efc75ade563364a
[ "MIT" ]
null
null
null
spark_deploy/internal/defaults/start.py
Sebastiaan-Alvarez-Rodriguez/spark-deploy
1e2f6da38576089a63fa910f2efc75ade563364a
[ "MIT" ]
1
2021-10-05T12:25:25.000Z
2021-10-05T12:25:25.000Z
# start default values def workdir(): return '~/spark_workdir' def retries(): return 5 def masterport(): return 7077 def webuiport(): return 8080
13.666667
28
0.664634
20
164
5.4
0.65
0
0
0
0
0
0
0
0
0
0
0.071429
0.231707
164
12
29
13.666667
0.785714
0.121951
0
0
0
0
0.104895
0
0
0
0
0
0
1
0.5
true
0
0
0.5
1
0
1
0
0
null
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1
1
0
0
1
1
0
0
5
32733f75557a39d92ca9cd2eabb09a19cd707916
151
py
Python
src/aves/visualization/tables/__init__.py
sergioangulo/aves
43a14ec9c82929136a39590b15fe7f92182aae20
[ "CC-BY-3.0" ]
34
2020-10-23T08:57:03.000Z
2022-03-23T17:07:20.000Z
src/aves/visualization/tables/__init__.py
sergioangulo/aves
43a14ec9c82929136a39590b15fe7f92182aae20
[ "CC-BY-3.0" ]
3
2021-12-02T22:42:25.000Z
2021-12-10T02:37:01.000Z
src/aves/visualization/tables/__init__.py
sergioangulo/aves
43a14ec9c82929136a39590b15fe7f92182aae20
[ "CC-BY-3.0" ]
11
2021-03-25T02:40:34.000Z
2022-01-03T22:41:29.000Z
from .bars import * from .scatter import * from .boxplot import boxplot from .areas import streamgraph, stacked_areas from .bubbles import bubble_plot
25.166667
45
0.807947
21
151
5.714286
0.52381
0.166667
0
0
0
0
0
0
0
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0.139073
151
5
46
30.2
0.923077
0
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true
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0
1
0
1
0
0
5
329676ed478aa9f63b475df160b5b0ff042a0e76
72
py
Python
callhorizons/__init__.py
mwcraig/callhorizons
84df04f8d820e48eed4c00e13982a2ca912d93a8
[ "MIT" ]
null
null
null
callhorizons/__init__.py
mwcraig/callhorizons
84df04f8d820e48eed4c00e13982a2ca912d93a8
[ "MIT" ]
null
null
null
callhorizons/__init__.py
mwcraig/callhorizons
84df04f8d820e48eed4c00e13982a2ca912d93a8
[ "MIT" ]
1
2018-10-02T15:13:19.000Z
2018-10-02T15:13:19.000Z
"""__init__ file for CALLHORIZONS module""" from callhorizons import *
18
43
0.763889
8
72
6.375
0.875
0
0
0
0
0
0
0
0
0
0
0
0.138889
72
3
44
24
0.822581
0.513889
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0
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true
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null
0
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0
1
0
1
0
1
0
0
5
329a3810a421a4e6c48cba01265e1f1f8917b06d
150
py
Python
src/api/domain/schedule/DeleteJob/DeleteJobRequest.py
PythonDataIntegrator/pythondataintegrator
6167778c36c2295e36199ac0d4d256a4a0c28d7a
[ "MIT" ]
14
2020-12-19T15:06:13.000Z
2022-01-12T19:52:17.000Z
src/api/domain/schedule/DeleteJob/DeleteJobRequest.py
PythonDataIntegrator/pythondataintegrator
6167778c36c2295e36199ac0d4d256a4a0c28d7a
[ "MIT" ]
43
2021-01-06T22:05:22.000Z
2022-03-10T10:30:30.000Z
src/api/domain/schedule/DeleteJob/DeleteJobRequest.py
PythonDataIntegrator/pythondataintegrator
6167778c36c2295e36199ac0d4d256a4a0c28d7a
[ "MIT" ]
4
2020-12-18T23:10:09.000Z
2021-04-02T13:03:12.000Z
from dataclasses import dataclass from infrastructure.cqrs.ICommand import ICommand @dataclass class DeleteJobRequest(ICommand): Id: int = None
18.75
49
0.806667
17
150
7.117647
0.705882
0
0
0
0
0
0
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0
0
0
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0.14
150
7
50
21.428571
0.937985
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true
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null
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null
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0
1
0
1
0
1
0
0
5
0879e73b6342e8407b7016f1d7c1d74b1149187e
143
py
Python
src/check_jsonschema/loaders/errors.py
dsch/check-jsonschema
5fef4772955061c598338feaf40ef676a4dd180b
[ "Apache-2.0" ]
3
2022-03-02T17:41:42.000Z
2022-03-18T00:17:33.000Z
src/check_jsonschema/loaders/errors.py
dsch/check-jsonschema
5fef4772955061c598338feaf40ef676a4dd180b
[ "Apache-2.0" ]
5
2022-03-15T11:16:00.000Z
2022-03-30T14:20:17.000Z
src/check_jsonschema/loaders/errors.py
dsch/check-jsonschema
5fef4772955061c598338feaf40ef676a4dd180b
[ "Apache-2.0" ]
2
2022-03-16T02:56:43.000Z
2022-03-30T09:35:32.000Z
class BadFileTypeError(ValueError): pass class SchemaParseError(ValueError): pass class UnsupportedUrlScheme(ValueError): pass
13
39
0.762238
12
143
9.083333
0.5
0.385321
0.348624
0
0
0
0
0
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0
0
0
0.174825
143
10
40
14.3
0.923729
0
0
0.5
0
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0
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0
0
0
1
0
true
0.5
0
0
0.5
0
1
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0
null
1
1
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0
0
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0
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0
0
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0
0
0
0
null
0
0
0
0
0
0
1
1
0
0
0
0
0
5
087c9394e58463eee84388f863540174488dcffc
173
py
Python
data/data_generator.py
zzh237/quanthmc
8126691b43bddc2b1a96f73ab35d04d1af200d7a
[ "MIT" ]
null
null
null
data/data_generator.py
zzh237/quanthmc
8126691b43bddc2b1a96f73ab35d04d1af200d7a
[ "MIT" ]
null
null
null
data/data_generator.py
zzh237/quanthmc
8126691b43bddc2b1a96f73ab35d04d1af200d7a
[ "MIT" ]
null
null
null
import numpy as np import torch class data_generator(): def __init__(self, classification_data): self.data = classification_data.train_test_data()
19.222222
58
0.699422
21
173
5.333333
0.666667
0.321429
0
0
0
0
0
0
0
0
0
0
0.231214
173
8
59
21.625
0.842105
0
0
0
0
0
0
0
0
0
0
0
0
1
0.2
false
0
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0
0.8
0
1
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0
null
1
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0
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0
0
1
0
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0
0
0
0
0
null
0
0
0
0
0
0
0
0
1
0
1
0
0
5
08a08bc077a4735ae00d42a1da830df93754cf02
160
py
Python
selfbot/types/__init__.py
TibebeJS/tg-selfbot
ad36399597b7277768649d6645d57611a2928259
[ "MIT" ]
1
2021-03-05T12:03:53.000Z
2021-03-05T12:03:53.000Z
selfbot/types/__init__.py
TibebeJS/tg-selfbot
ad36399597b7277768649d6645d57611a2928259
[ "MIT" ]
null
null
null
selfbot/types/__init__.py
TibebeJS/tg-selfbot
ad36399597b7277768649d6645d57611a2928259
[ "MIT" ]
1
2021-01-14T18:03:11.000Z
2021-01-14T18:03:11.000Z
from .argument import Argument from .sub_command import SubCommand from .argument_parser import CustomArgumentParser from .userbot_command import UserbotCommand
40
49
0.88125
19
160
7.263158
0.526316
0.173913
0
0
0
0
0
0
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0
0.09375
160
4
50
40
0.951724
0
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0
true
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1
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0
null
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0
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0
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null
0
0
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0
0
0
1
0
1
0
1
0
0
5
3e9ad3977dcf0ecdb0d5ed98d51af534d211ebce
262
py
Python
Configuration/Eras/python/Era_Run2_25ns_HIPM_cff.py
ckamtsikis/cmssw
ea19fe642bb7537cbf58451dcf73aa5fd1b66250
[ "Apache-2.0" ]
852
2015-01-11T21:03:51.000Z
2022-03-25T21:14:00.000Z
Configuration/Eras/python/Era_Run2_25ns_HIPM_cff.py
ckamtsikis/cmssw
ea19fe642bb7537cbf58451dcf73aa5fd1b66250
[ "Apache-2.0" ]
30,371
2015-01-02T00:14:40.000Z
2022-03-31T23:26:05.000Z
Configuration/Eras/python/Era_Run2_25ns_HIPM_cff.py
ckamtsikis/cmssw
ea19fe642bb7537cbf58451dcf73aa5fd1b66250
[ "Apache-2.0" ]
3,240
2015-01-02T05:53:18.000Z
2022-03-31T17:24:21.000Z
import FWCore.ParameterSet.Config as cms from Configuration.Eras.Era_Run2_25ns_cff import Run2_25ns from Configuration.Eras.Modifier_tracker_apv_vfp30_2016_cff import tracker_apv_vfp30_2016 Run2_25ns_HIPM = cms.ModifierChain(Run2_25ns, tracker_apv_vfp30_2016)
37.428571
89
0.889313
41
262
5.243902
0.487805
0.148837
0.209302
0.265116
0
0
0
0
0
0
0
0.122951
0.068702
262
6
90
43.666667
0.758197
0
0
0
0
0
0
0
0
0
0
0
0
1
0
false
0
0.75
0
0.75
0
0
0
0
null
0
1
1
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
1
0
1
0
0
5
3ea14d024edfb9701d885e8becd0a638800a7875
56
py
Python
01_Fundamentals/02_07.py
AnmolTomer/lynda_programming_foundations
2f1269f2984ae8707acd80017b892ff4cceb0ee9
[ "MIT" ]
null
null
null
01_Fundamentals/02_07.py
AnmolTomer/lynda_programming_foundations
2f1269f2984ae8707acd80017b892ff4cceb0ee9
[ "MIT" ]
null
null
null
01_Fundamentals/02_07.py
AnmolTomer/lynda_programming_foundations
2f1269f2984ae8707acd80017b892ff4cceb0ee9
[ "MIT" ]
null
null
null
print("For the 10,000th time in my life! Hello World !")
56
56
0.714286
11
56
3.636364
1
0
0
0
0
0
0
0
0
0
0
0.106383
0.160714
56
1
56
56
0.744681
0
0
0
0
0
0.824561
0
0
0
0
0
0
1
0
true
0
0
0
0
1
1
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
1
0
null
0
0
0
0
0
0
1
0
0
0
0
1
0
5
3eb0e462b9605b7461ad9584f6adb0f5e3bfa219
54
py
Python
kobodl/__main__.py
tamaracks/kobo-book-downloader
16921a19567df137bb3e1b0cb92b75826b703bdc
[ "Unlicense" ]
126
2020-04-01T04:41:20.000Z
2022-03-24T07:18:28.000Z
kobodl/__main__.py
tamaracks/kobo-book-downloader
16921a19567df137bb3e1b0cb92b75826b703bdc
[ "Unlicense" ]
48
2020-04-01T23:14:48.000Z
2022-03-03T10:16:12.000Z
kobodl/__main__.py
tamaracks/kobo-book-downloader
16921a19567df137bb3e1b0cb92b75826b703bdc
[ "Unlicense" ]
21
2020-04-02T11:21:41.000Z
2022-03-28T18:12:20.000Z
import sys from kobodl import cli cli(sys.argv[1:])
9
22
0.722222
10
54
3.9
0.7
0
0
0
0
0
0
0
0
0
0
0.022222
0.166667
54
5
23
10.8
0.844444
0
0
0
0
0
0
0
0
0
0
0
0
1
0
true
0
0.666667
0
0.666667
0
1
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
1
0
1
0
1
0
0
5
3edcfea6c406609bcf318286ffb483d1e1ab7998
452
py
Python
zlzzlzz2l/0209/2445.py
Kwak-JunYoung/154Algoritm-5weeks
fa18ae5f68a1ee722a30a05309214247f7fbfda4
[ "MIT" ]
3
2022-01-24T03:06:32.000Z
2022-01-30T08:43:58.000Z
zlzzlzz2l/0209/2445.py
Kwak-JunYoung/154Algoritm-5weeks
fa18ae5f68a1ee722a30a05309214247f7fbfda4
[ "MIT" ]
null
null
null
zlzzlzz2l/0209/2445.py
Kwak-JunYoung/154Algoritm-5weeks
fa18ae5f68a1ee722a30a05309214247f7fbfda4
[ "MIT" ]
2
2022-01-24T02:27:40.000Z
2022-01-30T08:57:03.000Z
N = int(input()) for i in range(1, N + 1): print("*" * i, end="") for _ in range(N - i, 0, -1): print(" ", end="") for _ in range(N - i, 0, -1): print(" ", end="") print("*" * i, end="") print("") for t in range(N-1, 0, -1): print("*" * t, end="") for _ in range(N - t, 0, -1): print(" ", end="") for _ in range(N - t, 0, -1): print(" ", end="") print("*" * t, end="") print("")
23.789474
33
0.389381
68
452
2.529412
0.176471
0.244186
0.232558
0.302326
0.604651
0.546512
0.546512
0.546512
0.546512
0.546512
0
0.043189
0.334071
452
19
34
23.789474
0.528239
0
0
0.823529
0
0
0.01766
0
0
0
0
0
0
1
0
false
0
0
0
0
0.588235
0
0
0
null
1
1
1
0
0
0
0
0
0
0
0
0
0
0
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0
0
1
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
1
0
5
3ef40ca4db4b4bfb733289eaf8568c41fa9eaefa
4,097
py
Python
src/tdd/test_patient.py
tborzyszkowski/TestAutomationInPython
843c71df796588e181466d9b9b549f03dd907a6e
[ "MIT" ]
2
2020-10-08T09:44:12.000Z
2021-10-08T08:32:19.000Z
src/tdd/test_patient.py
tborzyszkowski/TestAutomationInPython
843c71df796588e181466d9b9b549f03dd907a6e
[ "MIT" ]
null
null
null
src/tdd/test_patient.py
tborzyszkowski/TestAutomationInPython
843c71df796588e181466d9b9b549f03dd907a6e
[ "MIT" ]
1
2020-10-19T14:08:00.000Z
2020-10-19T14:08:00.000Z
# See: Unit Testing with Python By Emily Bache @ pluralsight.com import unittest from src.tdd.patient import Patient from src.tdd.prescription import Prescription from src.tdd.test_prescription import days_ago class TestPatient(unittest.TestCase): def test_no_clash_with_no_prescriptions(self): patient = Patient(prescriptions=[]) self.assertSetEqual(set(), patient.clash([])) def test_no_clash_with_one_irrelevant_prescription(self): patient = Patient(prescriptions=[Prescription("Codeine", dispense_date = days_ago(days=2), days_supply=2)]) self.assertSetEqual(set(), patient.clash(["Prozac"])) def test_one_clash_with_one_prescription(self): patient = Patient(prescriptions=[Prescription("Codeine", dispense_date = days_ago(days=2), days_supply=2)]) self.assertSetEqual({days_ago(days=2), days_ago(days=1)}, patient.clash(["Codeine"])) def test_clash_with_two_different_prescriptions(self): patient = Patient(prescriptions=[Prescription("Codeine", dispense_date = days_ago(days=2), days_supply=2), Prescription("Prozac", dispense_date = days_ago(days=2), days_supply=2)]) self.assertSetEqual({days_ago(days=2), days_ago(days=1)}, patient.clash(["Codeine", "Prozac"])) def test_clash_with_two_prescriptions_for_same_medication(self): patient = Patient(prescriptions=[Prescription("Codeine", dispense_date = days_ago(days=2), days_supply=2), Prescription("Codeine", dispense_date = days_ago(days=3), days_supply=2)]) self.assertSetEqual({days_ago(days=3), days_ago(days=2), days_ago(days=1)}, patient.clash(["Codeine"])) def test_no_days_taking_for_irrelevant_prescription(self): patient = Patient(prescriptions=[Prescription("Codeine", dispense_date = days_ago(days=2), days_supply=2)]) self.assertSetEqual(set(), patient.days_taking("Prozac")) def test_days_taking(self): patient = Patient(prescriptions=[Prescription("Codeine", dispense_date = days_ago(days=2), days_supply=2), Prescription("Codeine", dispense_date = days_ago(days=3), days_supply=2)]) self.assertSetEqual({days_ago(days=3), days_ago(days=2), days_ago(days=1)}, patient.days_taking("Codeine")) def test_clash_overlapping_today(self): patient = Patient(prescriptions=[Prescription("Codeine", dispense_date = days_ago(days=2), days_supply=3), Prescription("Prozac", dispense_date = days_ago(days=2), days_supply=3)]) self.assertSetEqual({days_ago(days=2), days_ago(days=1)}, patient.clash(["Codeine", "Prozac"]))
53.907895
87
0.459849
338
4,097
5.313609
0.142012
0.093541
0.140869
0.093541
0.793987
0.703786
0.703786
0.703786
0.703786
0.702673
0
0.015165
0.45277
4,097
75
88
54.626667
0.785905
0.015133
0
0.622951
0
0
0.033226
0
0
0
0
0
0.131148
1
0.131148
false
0
0.065574
0
0.213115
0
0
0
0
null
0
0
0
0
1
1
1
1
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
5
f5c1ed4410095741b3019906d74bac1f7af0808d
59
py
Python
social/backends/runkeeper.py
raccoongang/python-social-auth
81c0a542d158772bd3486d31834c10af5d5f08b0
[ "BSD-3-Clause" ]
1,987
2015-01-01T16:12:45.000Z
2022-03-29T14:24:25.000Z
social/backends/runkeeper.py
raccoongang/python-social-auth
81c0a542d158772bd3486d31834c10af5d5f08b0
[ "BSD-3-Clause" ]
731
2015-01-01T22:55:25.000Z
2022-03-10T15:07:51.000Z
virtual/lib/python3.6/site-packages/social/backends/runkeeper.py
dennismwaniki67/awards
80ed10541f5f751aee5f8285ab1ad54cfecba95f
[ "MIT" ]
1,082
2015-01-01T16:27:26.000Z
2022-03-22T21:18:33.000Z
from social_core.backends.runkeeper import RunKeeperOAuth2
29.5
58
0.898305
7
59
7.428571
1
0
0
0
0
0
0
0
0
0
0
0.018182
0.067797
59
1
59
59
0.927273
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
0
0
null
0
0
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0
0
0
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0
0
0
0
0
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1
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
1
0
1
0
1
0
0
5
eb2de6a07d1e0d05f55cb9b5174880ac8bcf5313
32
py
Python
FreeFlowLearning/API/Database/__init__.py
TeamNightSky/FreeFlowLearning
5b09361742d90f682a8db2578f4836535d5955bf
[ "Apache-2.0" ]
null
null
null
FreeFlowLearning/API/Database/__init__.py
TeamNightSky/FreeFlowLearning
5b09361742d90f682a8db2578f4836535d5955bf
[ "Apache-2.0" ]
null
null
null
FreeFlowLearning/API/Database/__init__.py
TeamNightSky/FreeFlowLearning
5b09361742d90f682a8db2578f4836535d5955bf
[ "Apache-2.0" ]
null
null
null
from .db import DatabaseManager
16
31
0.84375
4
32
6.75
1
0
0
0
0
0
0
0
0
0
0
0
0.125
32
1
32
32
0.964286
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
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5
de1c8fc1a1d9b0d95a690ca2824cb8c620159461
127
py
Python
part_2-mvc_structures/app/controllers/MyController.py
perogeremmer/latihan-flask
4a0098d8f23595d2b092b35b2f9b15f8abcf8ff5
[ "Naumen", "Condor-1.1", "MS-PL" ]
1
2021-09-18T17:48:34.000Z
2021-09-18T17:48:34.000Z
part_8-pattern-design/app/controllers/MyController.py
perogeremmer/latihan-flask
4a0098d8f23595d2b092b35b2f9b15f8abcf8ff5
[ "Naumen", "Condor-1.1", "MS-PL" ]
null
null
null
part_8-pattern-design/app/controllers/MyController.py
perogeremmer/latihan-flask
4a0098d8f23595d2b092b35b2f9b15f8abcf8ff5
[ "Naumen", "Condor-1.1", "MS-PL" ]
null
null
null
from flask_restful import Resource class MyController(Resource): def get(self): return {'message': 'Hello World!'}
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5
de496629e95498c12c31e3436bf1668bb6501e51
204
py
Python
imagemagick.py
Kronika-Polskiej-Demosceny/dvp
499f0129745ef5e4bfa26b4836c589db7be8a92d
[ "CC0-1.0" ]
null
null
null
imagemagick.py
Kronika-Polskiej-Demosceny/dvp
499f0129745ef5e4bfa26b4836c589db7be8a92d
[ "CC0-1.0" ]
null
null
null
imagemagick.py
Kronika-Polskiej-Demosceny/dvp
499f0129745ef5e4bfa26b4836c589db7be8a92d
[ "CC0-1.0" ]
null
null
null
import sh def check_binaries(): sh.ensure('convert') def convert(from_path, to_path, filters=[]): result = sh.execute(['convert', from_path, *filters, to_path]) # TODO: Error handling
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de5fb099743f59317333cec007d8d07ec3548aee
40
py
Python
src/fontman/_errors.py
nschloe/fontman
8709e101c76f519935f092fc108cd9d775726528
[ "MIT" ]
19
2021-07-24T03:27:41.000Z
2022-02-07T14:54:17.000Z
src/fontman/_errors.py
nschloe/fontman
8709e101c76f519935f092fc108cd9d775726528
[ "MIT" ]
1
2021-07-29T18:55:10.000Z
2021-07-31T17:36:09.000Z
src/fontman/_errors.py
nschloe/fontman
8709e101c76f519935f092fc108cd9d775726528
[ "MIT" ]
1
2022-01-15T02:49:48.000Z
2022-01-15T02:49:48.000Z
class FontmanError(Exception): pass
13.333333
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decde91f1f0cf228292e76e04f441c56820fa629
185
py
Python
django/AlpsSnow/blog/admin.py
AlpsSnow/Knowledge-Box
b2b2881026dc92e868ce3965f2d938ce5573ea12
[ "MIT" ]
1
2019-10-29T09:13:09.000Z
2019-10-29T09:13:09.000Z
django/AlpsSnow/blog/admin.py
mutou8bit/Knowledge-Box
b2b2881026dc92e868ce3965f2d938ce5573ea12
[ "MIT" ]
null
null
null
django/AlpsSnow/blog/admin.py
mutou8bit/Knowledge-Box
b2b2881026dc92e868ce3965f2d938ce5573ea12
[ "MIT" ]
null
null
null
from django.contrib import admin # Register your models here. from .models import Category, Tag, Post admin.site.register(Category) admin.site.register(Tag) admin.site.register(Post)
20.555556
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ded5a6d8ae1e4ce5f7e3c98d7bc87a15d8b092e4
65
py
Python
pro6/__init__.py
anthonyeden/Pro6-Utils
b31dfbf5bd94f987b33705992da9948fcf01eeb4
[ "MIT" ]
1
2021-04-28T03:43:38.000Z
2021-04-28T03:43:38.000Z
pro6/__init__.py
anthonyeden/Pro6-Utils
b31dfbf5bd94f987b33705992da9948fcf01eeb4
[ "MIT" ]
null
null
null
pro6/__init__.py
anthonyeden/Pro6-Utils
b31dfbf5bd94f987b33705992da9948fcf01eeb4
[ "MIT" ]
1
2020-01-21T07:28:31.000Z
2020-01-21T07:28:31.000Z
from pro6 import document, library, playlist, preferences, util
21.666667
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dee50dd12bb4209f7c1fe57ed28be1d86110f9c6
138
py
Python
src/clustering/clustering/__init__.py
juhuntenburg/pipelines
9904065cccb8e316cece5451f595a24774f07bd5
[ "MIT" ]
13
2019-03-10T23:13:06.000Z
2022-02-08T08:49:28.000Z
src/clustering/clustering/__init__.py
juhuntenburg/pipelines
9904065cccb8e316cece5451f595a24774f07bd5
[ "MIT" ]
1
2015-03-31T20:42:08.000Z
2015-04-03T23:58:58.000Z
src/clustering/clustering/__init__.py
NeuroanatomyAndConnectivity/pipelines
9904065cccb8e316cece5451f595a24774f07bd5
[ "MIT" ]
18
2015-01-08T13:27:40.000Z
2021-06-22T03:35:45.000Z
import concat import utils import consensus import cluster import similarity #import visualization import mask_volume import mask_surface
15.333333
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6.611111
0.555556
0.168067
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8
22
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5
7205b7d5919a9c1672cee8e367bd40d226ad3df1
191
py
Python
spec/fixtures/nose/test_method.py
nguyenmv2/vim-test
3560f81ccdd15f1dbb9c13ad2f67052441dd31b8
[ "Vim" ]
764
2020-04-25T16:03:30.000Z
2022-03-31T18:59:04.000Z
spec/fixtures/nose/test_method.py
nguyenmv2/vim-test
3560f81ccdd15f1dbb9c13ad2f67052441dd31b8
[ "Vim" ]
161
2020-04-25T09:53:22.000Z
2022-03-30T03:06:49.000Z
spec/fixtures/nose/test_method.py
nguyenmv2/vim-test
3560f81ccdd15f1dbb9c13ad2f67052441dd31b8
[ "Vim" ]
132
2020-04-26T21:36:17.000Z
2022-03-23T23:10:54.000Z
def test_numbers(): assert 1 == 1 def test_foo(): class CustomException(Exception): pass mocker.patch('some.module', side_effect=CustomException()) assert something
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5
7240ad59950bd29d5ebc61af63288131648b60fa
255
py
Python
aiotfm/utils/__init__.py
Robotex/aiotfm
d2e6e8ed6f93b82789b1d466576daa0b74450108
[ "MIT" ]
null
null
null
aiotfm/utils/__init__.py
Robotex/aiotfm
d2e6e8ed6f93b82789b1d466576daa0b74450108
[ "MIT" ]
null
null
null
aiotfm/utils/__init__.py
Robotex/aiotfm
d2e6e8ed6f93b82789b1d466576daa0b74450108
[ "MIT" ]
null
null
null
from aiotfm.utils.shakikoo import shakikoo from aiotfm.utils.date import Date from aiotfm.utils.get_keys import get_keys, Keys from aiotfm.utils.locale import Translation, Locale __all__ = ['shakikoo', 'Date', 'get_keys', 'Translation', 'Locale', 'Keys']
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5
9d3494b851bde159b11f23a87cd0be37beb5e66e
211
py
Python
src/utils/common_routines.py
SoupySoups/isometric
dea0a892670a5e49549900ec1cbfb72625fe607f
[ "MIT" ]
1
2022-03-27T05:52:39.000Z
2022-03-27T05:52:39.000Z
src/utils/common_routines.py
SoupySoups/isometric
dea0a892670a5e49549900ec1cbfb72625fe607f
[ "MIT" ]
null
null
null
src/utils/common_routines.py
SoupySoups/isometric
dea0a892670a5e49549900ec1cbfb72625fe607f
[ "MIT" ]
1
2022-03-27T05:52:41.000Z
2022-03-27T05:52:41.000Z
def quit() -> None: """Quits the application.""" import pygame from src.managers.core.logging_manager import logging_manager logging_manager().log.info("Quitting.") pygame.quit() exit()
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9d3fd5a69687055d2cc26f88275b1d5d3c938074
9,446
py
Python
tests/test_network_parsing.py
geoDavey/pyrosm
9b28714680e93c1f12cf2dc457fbc7d0db1f2798
[ "MIT" ]
null
null
null
tests/test_network_parsing.py
geoDavey/pyrosm
9b28714680e93c1f12cf2dc457fbc7d0db1f2798
[ "MIT" ]
null
null
null
tests/test_network_parsing.py
geoDavey/pyrosm
9b28714680e93c1f12cf2dc457fbc7d0db1f2798
[ "MIT" ]
null
null
null
import pytest from pyrosm import get_data @pytest.fixture def test_pbf(): pbf_path = get_data("test_pbf") return pbf_path @pytest.fixture def helsinki_pbf(): pbf_path = get_data("helsinki_pbf") return pbf_path @pytest.fixture def test_output_dir(): import os, tempfile return os.path.join(tempfile.gettempdir(), "pyrosm_test_results") def test_filter_network_by_walking(test_pbf): from pyrosm import OSM from geopandas import GeoDataFrame from shapely.geometry import LineString osm = OSM(filepath=test_pbf) gdf = osm.get_network(network_type="walking") assert isinstance(gdf.loc[0, 'geometry'], LineString) assert isinstance(gdf, GeoDataFrame) # Test shape assert gdf.shape == (265, 20) required_cols = ['access', 'bridge', 'foot', 'highway', 'lanes', 'lit', 'maxspeed', 'name', 'oneway', 'ref', 'service', 'surface', 'id', 'geometry', 'tags', 'osm_type'] for col in required_cols: assert col in gdf.columns # Should not include 'motorway' ways by default assert "motorway" not in gdf["highway"].unique() def test_filter_network_by_driving(test_pbf): from pyrosm import OSM from geopandas import GeoDataFrame from shapely.geometry import LineString osm = OSM(filepath=test_pbf) gdf = osm.get_network(network_type="driving") assert isinstance(gdf.loc[0, 'geometry'], LineString) assert isinstance(gdf, GeoDataFrame) # Test shape assert gdf.shape == (207, 18) required_cols = ['access', 'bridge', 'highway', 'int_ref', 'lanes', 'lit', 'maxspeed', 'name', 'oneway', 'ref', 'service', 'surface', 'id', 'geometry', 'tags', 'osm_type'] for col in required_cols: assert col in gdf.columns # Should not include 'footway' or 'path' ways by default assert "footway" not in gdf["highway"].unique() assert "path" not in gdf["highway"].unique() def test_filter_network_by_driving_with_service_roads(test_pbf): from pyrosm import OSM from geopandas import GeoDataFrame from shapely.geometry import LineString osm = OSM(filepath=test_pbf) gdf = osm.get_network(network_type="driving+service") assert isinstance(gdf.loc[0, 'geometry'], LineString) assert isinstance(gdf, GeoDataFrame) # Test shape assert gdf.shape == (207, 18) required_cols = ['access', 'bridge', 'highway', 'int_ref', 'lanes', 'lit', 'maxspeed', 'name', 'oneway', 'ref', 'service', 'surface', 'id', 'geometry', 'tags', 'osm_type'] for col in required_cols: assert col in gdf.columns # Should not include 'footway' or 'path' ways by default assert "footway" not in gdf["highway"].unique() assert "path" not in gdf["highway"].unique() def test_filter_network_by_cycling(test_pbf): from pyrosm import OSM from geopandas import GeoDataFrame from shapely.geometry import LineString osm = OSM(filepath=test_pbf) gdf = osm.get_network(network_type="cycling") assert isinstance(gdf.loc[0, 'geometry'], LineString) assert isinstance(gdf, GeoDataFrame) # Test shape assert gdf.shape == (290, 20) required_cols = ['access', 'bicycle', 'bridge', 'foot', 'highway', 'lanes', 'lit', 'maxspeed', 'name', 'oneway', 'ref', 'service', 'surface', 'tunnel', 'id', 'geometry', 'tags', 'osm_type'] for col in required_cols: assert col in gdf.columns # Should not include 'motorway' or 'motorway_link' ways by default assert "motorway" not in gdf["highway"].unique() assert "motorway_link" not in gdf["highway"].unique() def test_filter_network_by_all(test_pbf): from pyrosm import OSM from geopandas import GeoDataFrame from shapely.geometry import LineString osm = OSM(filepath=test_pbf) gdf = osm.get_network(network_type="all") assert isinstance(gdf.loc[0, 'geometry'], LineString) assert isinstance(gdf, GeoDataFrame) # Test shape assert gdf.shape == (331, 21) required_cols = ['access', 'bicycle', 'bridge', 'foot', 'highway', 'lanes', 'lit', 'maxspeed', 'name', 'oneway', 'ref', 'service', 'surface', 'tunnel', 'id', 'geometry', 'tags', 'osm_type'] for col in required_cols: assert col in gdf.columns def test_saving_network_to_shapefile(test_pbf, test_output_dir): import os from pyrosm import OSM import geopandas as gpd import shutil if not os.path.exists(test_output_dir): os.makedirs(test_output_dir) temp_path = os.path.join(test_output_dir, "pyrosm_test.shp") osm = OSM(filepath=test_pbf) gdf = osm.get_network(network_type="cycling") gdf.to_file(temp_path) # Ensure it can be read and matches with original one gdf2 = gpd.read_file(temp_path) cols = gdf.columns for col in cols: assert gdf[col].tolist() == gdf2[col].tolist() # Clean up shutil.rmtree(test_output_dir) def test_parse_network_with_bbox(test_pbf): from pyrosm import OSM from geopandas import GeoDataFrame from shapely.geometry import LineString bounds = [26.94, 60.525, 26.96, 60.535] # Init with bounding box osm = OSM(filepath=test_pbf, bounding_box=bounds) gdf = osm.get_network() assert isinstance(gdf.loc[0, 'geometry'], LineString) assert isinstance(gdf, GeoDataFrame) # Test shape assert gdf.shape == (74, 20) required_cols = ['access', 'bridge', 'foot', 'highway', 'lanes', 'lit', 'maxspeed', 'name', 'oneway', 'ref', 'service', 'surface', 'id', 'geometry', 'tags', 'osm_type'] for col in required_cols: assert col in gdf.columns # Should not include 'motorway' ways by default assert "motorway" not in gdf["highway"].unique() # The total bounds of the result should not be larger than the filter # (allow some rounding error) result_bounds = gdf.total_bounds for coord1, coord2 in zip(bounds, result_bounds): assert round(coord2, 3) >= round(coord1, 3) def test_parse_network_with_shapely_bbox(test_pbf): from pyrosm import OSM from geopandas import GeoDataFrame from shapely.geometry import LineString, box bounds = box(*[26.94, 60.525, 26.96, 60.535]) # Init with bounding box osm = OSM(filepath=test_pbf, bounding_box=bounds) gdf = osm.get_network() assert isinstance(gdf.loc[0, 'geometry'], LineString) assert isinstance(gdf, GeoDataFrame) # Test shape assert gdf.shape == (74, 20) required_cols = ['access', 'bridge', 'foot', 'highway', 'lanes', 'lit', 'maxspeed', 'name', 'oneway', 'ref', 'service', 'surface', 'id', 'geometry', 'tags', 'osm_type'] for col in required_cols: assert col in gdf.columns # Should not include 'motorway' ways by default assert "motorway" not in gdf["highway"].unique() # The total bounds of the result should not be larger than the filter # (allow some rounding error) result_bounds = gdf.total_bounds for coord1, coord2 in zip(bounds.bounds, result_bounds): assert round(coord2, 3) >= round(coord1, 3) def test_passing_incorrect_bounding_box(test_pbf): from pyrosm import OSM wrong_format = "[26.94, 60.525, 26.96, 60.535]" try: osm = OSM(filepath=test_pbf, bounding_box=wrong_format) except ValueError as e: if "bounding_box should be" in str(e): pass else: raise(e) except Exception as e: raise e def test_passing_incorrect_net_type(test_pbf): from pyrosm import OSM osm = OSM(filepath=test_pbf) try: osm.get_network("wrong_network") except ValueError as e: if "'network_type' should be one of the following" in str(e): pass else: raise(e) except Exception as e: raise e try: osm.get_network(42) except ValueError as e: if "'network_type' should be one of the following" in str(e): pass else: raise(e) except Exception as e: raise e def test_reading_network_from_area_without_data(helsinki_pbf): from pyrosm import OSM from geopandas import GeoDataFrame # Bounding box for area that does not have any data bbox = [24.940514, 60.173849, 24.942, 60.175892] osm = OSM(filepath=helsinki_pbf, bounding_box=bbox) # The tool should warn if no buildings were found with pytest.warns(UserWarning) as w: gdf = osm.get_network() # Check the warning text if "could not find any network data" in str(w): pass # Result should be None assert gdf is None def test_adding_extra_attribute(helsinki_pbf): from pyrosm import OSM from geopandas import GeoDataFrame osm = OSM(filepath=helsinki_pbf) gdf = osm.get_network() extra_col = "wikidata" extra = osm.get_network(extra_attributes=[extra_col]) # The extra should have one additional column compared to the original one assert extra.shape[1] == gdf.shape[1]+1 # Should have same number of rows assert extra.shape[0] == gdf.shape[0] assert extra_col in extra.columns assert len(extra[extra_col].dropna().unique()) > 0 assert isinstance(gdf, GeoDataFrame)
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c22286b865960635a7d908ea46693d39d0482e41
106
py
Python
apps/document/admin.py
LHerdy/People_Manager
e35ba2333a26e1cf35b7234af10f3c849eaa0270
[ "MIT" ]
null
null
null
apps/document/admin.py
LHerdy/People_Manager
e35ba2333a26e1cf35b7234af10f3c849eaa0270
[ "MIT" ]
1
2021-08-15T15:02:10.000Z
2021-08-15T15:02:25.000Z
apps/document/admin.py
LHerdy/People_Manager
e35ba2333a26e1cf35b7234af10f3c849eaa0270
[ "MIT" ]
null
null
null
from django.contrib import admin from apps.document.models import Document admin.site.register(Document)
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c249442c034c1eef2f49a7667c6420edfeecad86
262
py
Python
test/shared/utils.py
Epsuchti/mobydq
b52f0914d414bcf4fa4001061ce38c5d7e0f863b
[ "Apache-2.0" ]
null
null
null
test/shared/utils.py
Epsuchti/mobydq
b52f0914d414bcf4fa4001061ce38c5d7e0f863b
[ "Apache-2.0" ]
null
null
null
test/shared/utils.py
Epsuchti/mobydq
b52f0914d414bcf4fa4001061ce38c5d7e0f863b
[ "Apache-2.0" ]
null
null
null
from datetime import datetime def get_test_case_name(): """Generate unique name for unit test case.""" # If not unique enough, replace with an uuid test_case_name = 'test ' + datetime.now().strftime("%Y-%m-%d %H:%M:%S.%f") return test_case_name
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dfb2ee486db3c9ad828c9764319c275a4b967733
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py
Python
vk_handle_bot/__init__.py
CodeSQRT/vk-handle-bot
d3d3280edb850b3d53a59efbe5144c0e45d1ec06
[ "MIT" ]
2
2019-03-08T23:29:33.000Z
2019-03-24T19:31:17.000Z
vk_handle_bot/__init__.py
CodeSQRT/vk-handle-bot
d3d3280edb850b3d53a59efbe5144c0e45d1ec06
[ "MIT" ]
2
2019-03-09T11:25:10.000Z
2019-03-09T11:27:47.000Z
vk_handle_bot/__init__.py
CodeSQRT/vk-handle-bot
d3d3280edb850b3d53a59efbe5144c0e45d1ec06
[ "MIT" ]
null
null
null
from vk_handle_bot.bot import VkBot, KeyboardColor
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5f0227ffd10ff69301927c8c2e761f51553b52dc
5,765
py
Python
pygromos/simulations/modules/preset_simulation_modules.py
katzberger/PyGromosTools
a6a7e6b80818337d1634f3f1cca2854666b157c2
[ "MIT" ]
null
null
null
pygromos/simulations/modules/preset_simulation_modules.py
katzberger/PyGromosTools
a6a7e6b80818337d1634f3f1cca2854666b157c2
[ "MIT" ]
null
null
null
pygromos/simulations/modules/preset_simulation_modules.py
katzberger/PyGromosTools
a6a7e6b80818337d1634f3f1cca2854666b157c2
[ "MIT" ]
null
null
null
import numpy as np from typing import Tuple from pygromos.files.gromos_system import Gromos_System from pygromos.data.simulation_parameters_templates import template_emin, template_md, template_sd from pygromos.simulations.modules.general_simulation_modules import simulation from pygromos.simulations.hpc_queuing.job_scheduling.workers.analysis_workers import simulation_analysis from pygromos.simulations.hpc_queuing.submission_systems._submission_system import _SubmissionSystem from pygromos.simulations.hpc_queuing.submission_systems.local import LOCAL """ Simulations """ def emin(in_gromos_system: Gromos_System, step_name: str = "emin", override_project_dir: str=None, in_imd_path=None, submission_system: _SubmissionSystem = LOCAL(), simulation_runs: int = 1, equilibration_runs: int = 0, previous_simulation_run: int = None, _template_imd_path:str=template_emin, analysis_script: callable = simulation_analysis.do) -> Tuple[Gromos_System, int]: template_emin_control_dict = simulation_analysis.template_control_dict template_emin_control_dict['concat']['cat_trc'] = False template_emin_control_dict['concat']['cat_tre'] = False template_emin_control_dict['concat']['cat_trg'] = False if(hasattr(in_gromos_system.imd, "WRITETRAJ")): if(in_gromos_system.imd.WRITETRAJ.NTWX>0): template_emin_control_dict['concat']['cat_trc'] = False if(in_gromos_system.imd.WRITETRAJ.NTWE>0): template_emin_control_dict['concat']['cat_tre'] = False if(in_gromos_system.imd.WRITETRAJ.NTWG>0): template_emin_control_dict['concat']['cat_trg'] = False return simulation(in_gromos_simulation_system=in_gromos_system, override_project_dir=override_project_dir, previous_simulation_run=previous_simulation_run, step_name=step_name, in_imd_path=in_imd_path, submission_system=submission_system, simulation_runs=simulation_runs, equilibration_runs=equilibration_runs, analysis_control_dict = template_emin_control_dict, analysis_script=analysis_script, _template_imd_path=_template_imd_path) def md(in_gromos_system: Gromos_System, step_name: str = "md", override_project_dir: str=None, in_imd_path=None, submission_system: _SubmissionSystem = LOCAL(), simulation_runs: int = 1, equilibration_runs: int = 0, previous_simulation_run: int = None, _template_imd_path:str=template_md, analysis_script: callable = simulation_analysis.do) -> Tuple[Gromos_System, int]: return simulation(in_gromos_simulation_system=in_gromos_system, override_project_dir=override_project_dir, previous_simulation_run=previous_simulation_run, step_name=step_name, in_imd_path=in_imd_path, submission_system=submission_system, simulation_runs=simulation_runs, equilibration_runs=equilibration_runs, analysis_script=analysis_script, _template_imd_path=_template_imd_path) def sd(in_gromos_system: Gromos_System, step_name: str = "sd", override_project_dir: str=None, in_imd_path=None, submission_system: _SubmissionSystem = LOCAL(), simulation_runs: int = 1, equilibration_runs: int = 0, previous_simulation_run: int = None, _template_imd_path:str=template_sd, analysis_script: callable = simulation_analysis.do) -> Tuple[Gromos_System, int]: return simulation(in_gromos_simulation_system=in_gromos_system, override_project_dir=override_project_dir, previous_simulation_run=previous_simulation_run, step_name=step_name, in_imd_path=in_imd_path, submission_system=submission_system, simulation_runs=simulation_runs, equilibration_runs=equilibration_runs, analysis_script=analysis_script, _template_imd_path=_template_imd_path) def thermalisation(in_gromos_system: Gromos_System, temperatures = np.linspace(60, 300, 4), step_name: str = "eq_therm", override_project_dir: str=None, in_imd_path=None, submission_system: _SubmissionSystem = LOCAL(), simulation_runs: int = 1, equilibration_runs: int = 0, previous_simulation_run: int = None, _template_imd_path:str=template_sd, analysis_script: callable = simulation_analysis.do) -> Tuple[Gromos_System, int]: for runID, temperature in enumerate(temperatures): print("run", runID, "T: ", temperature) # adapt temperature in_gromos_system.imd.MULTIBATH.TEMP0 = [temperature for x in range(in_gromos_system.imd.MULTIBATH.NBATHS)] # turn off the posres for the last run. if (runID + 1 == len(temperatures)): in_gromos_system.imd.POSITIONRES.NTPOR = 0 in_gromos_system.imd.POSITIONRES.CPOR = 0 # Last run return simulation(in_gromos_simulation_system=in_gromos_system, override_project_dir=override_project_dir, previous_simulation_run=previous_simulation_run, step_name=step_name, in_imd_path=in_imd_path, submission_system=submission_system, simulation_runs=simulation_runs, equilibration_runs=equilibration_runs, analysis_script=analysis_script, _template_imd_path=_template_imd_path) else: simulation(in_gromos_simulation_system=in_gromos_system, override_project_dir=override_project_dir, previous_simulation_run=previous_simulation_run, step_name=step_name, in_imd_path=in_imd_path, submission_system=submission_system, simulation_runs=simulation_runs, equilibration_runs=equilibration_runs, analysis_script=analysis_script, _template_imd_path=_template_imd_path)
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