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
719dfe0474b8ecd5fc17e742fde14046441220ad
37
py
Python
jesse/exchanges/__init__.py
noenfugler/jesse
217a3168620a755c1a9576d9deb27105db7dccf8
[ "MIT" ]
3,999
2018-11-09T10:38:51.000Z
2022-03-31T12:29:12.000Z
jesse/exchanges/__init__.py
noenfugler/jesse
217a3168620a755c1a9576d9deb27105db7dccf8
[ "MIT" ]
172
2020-04-16T16:19:08.000Z
2022-03-28T13:28:55.000Z
jesse/exchanges/__init__.py
noenfugler/jesse
217a3168620a755c1a9576d9deb27105db7dccf8
[ "MIT" ]
495
2019-03-01T21:48:53.000Z
2022-03-30T15:35:19.000Z
from .sandbox.Sandbox import Sandbox
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py
Python
double_speed.py
astrofitz/tokyo
78f1aa9b2ce78d453e403b8d00d685ecda5f3c51
[ "BSD-3-Clause" ]
16
2015-01-13T21:22:35.000Z
2020-01-20T23:44:28.000Z
double_speed.py
astrofitz/tokyo
78f1aa9b2ce78d453e403b8d00d685ecda5f3c51
[ "BSD-3-Clause" ]
null
null
null
double_speed.py
astrofitz/tokyo
78f1aa9b2ce78d453e403b8d00d685ecda5f3c51
[ "BSD-3-Clause" ]
3
2016-06-18T13:55:15.000Z
2021-09-30T18:51:02.000Z
#!/usr/bin/env python import double_speed # test runs automatically on import
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py
Python
0_PythonFundamental/1_05_sequencelist.py
hnwarid/DQLabAcademy
e03d82f97536ae103b6abc65db0ae16520fb68c7
[ "MIT" ]
null
null
null
0_PythonFundamental/1_05_sequencelist.py
hnwarid/DQLabAcademy
e03d82f97536ae103b6abc65db0ae16520fb68c7
[ "MIT" ]
null
null
null
0_PythonFundamental/1_05_sequencelist.py
hnwarid/DQLabAcademy
e03d82f97536ae103b6abc65db0ae16520fb68c7
[ "MIT" ]
null
null
null
contoh_list = [1, 'dua', 3, 4.0, 5] print(contoh_list[0]) print(contoh_list[3]) contoh_list = [1, 'dua', 3, 4.0, 5] contoh_list[3] = 'empat' print(contoh_list[3])
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py
Python
RL/model.py
namabilly/iLOCuS
761fe4162a9fb551f43d887c3ae9d448c3cc8c14
[ "MIT" ]
7
2020-05-28T02:16:22.000Z
2021-12-20T12:20:47.000Z
RL/model.py
namabilly/iLOCuS
761fe4162a9fb551f43d887c3ae9d448c3cc8c14
[ "MIT" ]
null
null
null
RL/model.py
namabilly/iLOCuS
761fe4162a9fb551f43d887c3ae9d448c3cc8c14
[ "MIT" ]
2
2020-05-18T03:44:34.000Z
2020-06-08T12:58:55.000Z
import tensorflow as tf from keras.models import Model from keras.layers import (Activation, Convolution2D, Dense, Flatten, Input, Dropout, Conv2DTranspose, Lambda, Concatenate, Reshape, LeakyReLU, ReLU) # def create_model(look_back_steps, input_shape, num_actions, model_name='q_network'): # with tf.name_scope(model_name): # input_img = Input(shape = (look_back_steps + 3,) + input_shape) # # input_loc = Input(shape = [1] ) # # input_loc = Lambda(lambda x: expand_dims(x, axis=1))(input_loc) # # print(input_loc.shape) # # Input shape = (batch, look_back_steps + 5, 84, 84) # # input_loc = input_img[:,-1,0,0] # # # embeddings = [] # # for i in range(look_back_steps + 4): # # ch_i = Lambda(lambda x: x[:,i,:,:])(input_img) # # embeddings.append(embedding(ch_i, input_shape, 128, 'embed_'+str(i))) # # # embed_feat = Concatenate(axis=1)(embeddings) # deconv1 = Conv2DTranspose(32, (5, 5), strides=(2, 2), # input_shape=[look_back_steps + 4,input_shape[0],input_shape[1]], # data_format='channels_first')(input_img) # deconv1 = LeakyReLU(alpha=0.2)(deconv1) # deconv2 = Conv2DTranspose(128, (5, 5), strides=(2, 2), # input_shape=[look_back_steps + 4, input_shape[0], input_shape[1]], # data_format='channels_first')(deconv1) # deconv2 = LeakyReLU(alpha=0.2)(deconv2) # conv1 = Convolution2D(64, (5,5), data_format='channels_first', strides=(2,2), padding='valid')(deconv2) # conv1 = LeakyReLU(alpha=0.2)(conv1) # # (batch, 32, 5, 5) # # conv2 = Convolution2D(128, (3,3), data_format='channels_first', strides=(1,1), padding='valid')(conv1) # conv2 = LeakyReLU(alpha=0.2)(conv2) # # (batch, 128, 3, 3) # # flat = Flatten()(conv2) # full = Dense(250)(flat) # # full = LeakyReLU(alpha=0.2)(full) # # # # embed_feat = Concatenate(axis=1)([full, input_loc]) # # print(embed_feat.shape) # # full = Dense(num_actions)(embed_feat) # output layer has node number = num_actions # out = LeakyReLU(alpha=0.2)(full) # model = Model(input = input_img, output = out) # return model def create_model(look_back_steps, input_shape, num_actions, model_name='q_network'): with tf.name_scope(model_name): input_img = Input(shape=(look_back_steps + 3,) + input_shape) # Input shape = (batch, look_back_steps + 5, 84, 84) # embeddings = [] # for i in range(look_back_steps + 4): # ch_i = Lambda(lambda x: x[:,i,:,:])(input_img) # embeddings.append(embedding(ch_i, input_shape, 128, 'embed_'+str(i))) # embed_feat = Concatenate(axis=1)(embeddings) # deconv1 = Conv2DTranspose(32, (5, 5), strides=(2, 2), # input_shape=[look_back_steps + 4, input_shape[0], input_shape[1]], # data_format='channels_first')(input_img) # deconv1 = LeakyReLU(alpha=0.2)(deconv1) # deconv2 = Conv2DTranspose(128, (5, 5), strides=(2, 2), # input_shape=[look_back_steps + 4, input_shape[0], input_shape[1]], # data_format='channels_first')(deconv1) # deconv2 = LeakyReLU(alpha=0.2)(deconv2) # conv1 = Convolution2D(64, (5, 5), data_format='channels_first', strides=(2, 2), padding='valid')(deconv2) # conv1 = LeakyReLU(alpha=0.2)(conv1) # # (batch, 32, 5, 5) # # conv2 = Convolution2D(128, (3, 3), data_format='channels_first', strides=(1, 1), padding='valid')(conv1) # conv2 = LeakyReLU(alpha=0.2)(conv2) # (batch, 128, 3, 3) flat = Flatten()(input_img) full = Dense(1280)(flat) full = LeakyReLU(alpha=0.2)(full) full = Dense(2560)(full) full = LeakyReLU(alpha=0.2)(full) out = Dense(25*num_actions)(full) # output layer has node number = num_actions # out = LeakyReLU(alpha=0.2)(full) model = Model(input=input_img, output=out) return model def embedding(input_placeholder, input_shape, embedding_dim, layer_name): with tf.name_scope(layer_name): # input_placeholder shape: (batch, 1, 15, 15) reshaped = Reshape(target_shape=(1,)+input_shape)(input_placeholder) conv1 = Convolution2D(4, (3,3), data_format='channels_first', strides=(1,1), padding='valid')(reshaped) conv1 = LeakyReLU(alpha=0.1)(conv1) # conv1 shape: (batch, 4, 7, 7) return conv1
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py
Python
ConfigEnv/__init__.py
Nydareld/ConfigEnv
c4894d235d2f005b65fe2e5153d5acee2c7a65e4
[ "MIT" ]
null
null
null
ConfigEnv/__init__.py
Nydareld/ConfigEnv
c4894d235d2f005b65fe2e5153d5acee2c7a65e4
[ "MIT" ]
3
2018-09-12T13:04:56.000Z
2018-09-24T15:09:31.000Z
ConfigEnv/__init__.py
Nydareld/ConfigEnv
c4894d235d2f005b65fe2e5153d5acee2c7a65e4
[ "MIT" ]
null
null
null
from .Config import Config from .FileFormatException import FileFormatException
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68
py
Python
models/stylegan2/__init__.py
Aitical/ADspeech2face
2e811ff8cc7333729f4b77d1b1067296253e8e38
[ "MIT" ]
1
2022-01-27T14:19:04.000Z
2022-01-27T14:19:04.000Z
models/stylegan2/__init__.py
Aitical/ADspeech2face
2e811ff8cc7333729f4b77d1b1067296253e8e38
[ "MIT" ]
null
null
null
models/stylegan2/__init__.py
Aitical/ADspeech2face
2e811ff8cc7333729f4b77d1b1067296253e8e38
[ "MIT" ]
null
null
null
from .model import Generator, Discriminator, EqualLinear, StyledConv
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py
Python
objectModel/Python/cdm/utilities/symbol_set.py
aaron-emde/CDM
9472e9c7694821ac4a9bbe608557d2e65aabc73e
[ "CC-BY-4.0", "MIT" ]
null
null
null
objectModel/Python/cdm/utilities/symbol_set.py
aaron-emde/CDM
9472e9c7694821ac4a9bbe608557d2e65aabc73e
[ "CC-BY-4.0", "MIT" ]
3
2021-05-11T23:57:12.000Z
2021-08-04T05:03:05.000Z
objectModel/Python/cdm/utilities/symbol_set.py
aaron-emde/CDM
9472e9c7694821ac4a9bbe608557d2e65aabc73e
[ "CC-BY-4.0", "MIT" ]
null
null
null
# ---------------------------------------------------------------------- # Copyright (c) Microsoft Corporation. # All rights reserved. # ---------------------------------------------------------------------- # TODO: Consider just inheriting from Python's set type -MPL class SymbolSet: def __init__(self): self._symbol_set_collection = set() @property def size(self): return len(self._symbol_set_collection) def add(self, new_symbol): self._symbol_set_collection.add(new_symbol) def merge(self, sym_set): if sym_set is not None: self._symbol_set_collection = self._symbol_set_collection.union(sym_set) def copy(self): return self._symbol_set_collection.copy() def __iter__(self): return iter(self._symbol_set_collection)
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461623f42e3e08d7dbd58a3be3826f30ec7c47c1
96
py
Python
Codewars/CorrectTheMistakesOfTheCharacterRecognitionSoftware.py
SelvorWhim/competitive
b9daaf21920d6f7669dc0c525e903949f4e33b62
[ "Unlicense" ]
null
null
null
Codewars/CorrectTheMistakesOfTheCharacterRecognitionSoftware.py
SelvorWhim/competitive
b9daaf21920d6f7669dc0c525e903949f4e33b62
[ "Unlicense" ]
null
null
null
Codewars/CorrectTheMistakesOfTheCharacterRecognitionSoftware.py
SelvorWhim/competitive
b9daaf21920d6f7669dc0c525e903949f4e33b62
[ "Unlicense" ]
null
null
null
fix = {'5':'S', '0':'O', '1':'I'} def correct(s): return "".join(fix.get(c, c) for c in s)
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py
Python
hrm_api/ideas/factories/generators/__init__.py
unknowncoder05/HRM
2a0ad62373fdaefafe533727b2d586d8f6327e87
[ "MIT" ]
null
null
null
hrm_api/ideas/factories/generators/__init__.py
unknowncoder05/HRM
2a0ad62373fdaefafe533727b2d586d8f6327e87
[ "MIT" ]
null
null
null
hrm_api/ideas/factories/generators/__init__.py
unknowncoder05/HRM
2a0ad62373fdaefafe533727b2d586d8f6327e87
[ "MIT" ]
null
null
null
from .full_idea import idea_generator
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py
Python
tests/elements/cmake.py
gtristan/buildstream-plugins
96206318b2cade5329a64b0f15b362ed57222086
[ "Apache-2.0" ]
null
null
null
tests/elements/cmake.py
gtristan/buildstream-plugins
96206318b2cade5329a64b0f15b362ed57222086
[ "Apache-2.0" ]
null
null
null
tests/elements/cmake.py
gtristan/buildstream-plugins
96206318b2cade5329a64b0f15b362ed57222086
[ "Apache-2.0" ]
null
null
null
# Pylint doesn't play well with fixtures and dependency injection from pytest # pylint: disable=redefined-outer-name import os import pytest from buildstream._testing.runcli import cli_integration as cli # pylint: disable=unused-import from buildstream._testing.integration import integration_cache # pylint: disable=unused-import from buildstream._testing.integration import assert_contains from buildstream._testing._utils.site import HAVE_SANDBOX pytestmark = pytest.mark.integration DATA_DIR = os.path.join(os.path.dirname(os.path.realpath(__file__)), "cmake") @pytest.mark.datafiles(DATA_DIR) @pytest.mark.skipif(not HAVE_SANDBOX, reason="Only available with a functioning sandbox") def test_cmake_build(cli, datafiles): project = str(datafiles) checkout = os.path.join(cli.directory, "checkout") element_name = "cmakehello.bst" result = cli.run(project=project, args=["build", element_name]) assert result.exit_code == 0 result = cli.run( project=project, args=["artifact", "checkout", element_name, "--directory", checkout], ) assert result.exit_code == 0 assert_contains(checkout, ["/usr", "/usr/bin", "/usr/bin/hello"]) @pytest.mark.datafiles(DATA_DIR) @pytest.mark.skipif(not HAVE_SANDBOX, reason="Only available with a functioning sandbox") def test_cmake_confroot_build(cli, datafiles): project = str(datafiles) checkout = os.path.join(cli.directory, "checkout") element_name = "cmakeconfroothello.bst" result = cli.run(project=project, args=["build", element_name]) assert result.exit_code == 0 result = cli.run( project=project, args=["artifact", "checkout", element_name, "--directory", checkout], ) assert result.exit_code == 0 assert_contains(checkout, ["/usr", "/usr/bin", "/usr/bin/hello"]) @pytest.mark.datafiles(DATA_DIR) @pytest.mark.skipif(not HAVE_SANDBOX, reason="Only available with a functioning sandbox") def test_cmake_run(cli, datafiles): project = str(datafiles) element_name = "cmakehello.bst" result = cli.run(project=project, args=["build", element_name]) assert result.exit_code == 0 result = cli.run(project=project, args=["shell", element_name, "/usr/bin/hello"]) assert result.exit_code == 0 assert ( result.output == """Hello World! This is hello. """ )
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1ced5beda187c06484e155a6fc3d30aeb0da289b
746
py
Python
src/study/190128_deco.py
jaeorin/Python
366f84b96cfa0ae7dabf7fdfd48c18535997e2f4
[ "MIT" ]
null
null
null
src/study/190128_deco.py
jaeorin/Python
366f84b96cfa0ae7dabf7fdfd48c18535997e2f4
[ "MIT" ]
null
null
null
src/study/190128_deco.py
jaeorin/Python
366f84b96cfa0ae7dabf7fdfd48c18535997e2f4
[ "MIT" ]
null
null
null
import datetime def iot_function1(): print("==========================") print(datetime.datetime.now()) print("iot function1 start") print(datetime.datetime.now()) def iot_function2(): print("==========================") print(datetime.datetime.now()) print("iot function2 start") print(datetime.datetime.now()) def iot_function3(): print("==========================") print(datetime.datetime.now()) print("iot function3 start") print(datetime.datetime.now()) def iot_function4(): print("==========================") print(datetime.datetime.now()) print("iot function4 start") print(datetime.datetime.now()) iot_function1() iot_function2() iot_function3() iot_function4()
20.722222
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70
py
Python
generator/__init__.py
milogert/bggrss
37d32eb65747b3831346f93a4f6aabd666d81d78
[ "MIT" ]
null
null
null
generator/__init__.py
milogert/bggrss
37d32eb65747b3831346f93a4f6aabd666d81d78
[ "MIT" ]
106
2019-10-10T13:45:24.000Z
2021-07-14T20:06:31.000Z
generator/__init__.py
milogert/bggrss
37d32eb65747b3831346f93a4f6aabd666d81d78
[ "MIT" ]
null
null
null
from generator import generator, renderer, bgg print(dir(generator))
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131
py
Python
src/django_cloudtask/urls.py
adamchainz/django-cloudtask
e9663c66cd96e7a633d119157fd9a7fa2ca0072a
[ "BSD-3-Clause" ]
22
2020-12-27T14:32:38.000Z
2022-02-06T20:33:14.000Z
src/django_cloudtask/urls.py
adamchainz/django-cloudtask
e9663c66cd96e7a633d119157fd9a7fa2ca0072a
[ "BSD-3-Clause" ]
2
2020-11-03T00:45:12.000Z
2020-12-28T23:36:05.000Z
src/django_cloudtask/urls.py
adamchainz/django-cloudtask
e9663c66cd96e7a633d119157fd9a7fa2ca0072a
[ "BSD-3-Clause" ]
2
2020-12-27T11:15:20.000Z
2021-06-04T13:50:21.000Z
from django.urls import path from .views import execute_task urlpatterns = [path("execute/", execute_task, name="task-execute")]
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e8017f9ba45ded6769d20b0867c9bff100ecc5f3
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py
Python
bspump/ipc/datagram.py
thatch/BitSwanPump
98a5b8d09f9b59d5361611cee0bd45e7b4c69e3f
[ "BSD-3-Clause" ]
null
null
null
bspump/ipc/datagram.py
thatch/BitSwanPump
98a5b8d09f9b59d5361611cee0bd45e7b4c69e3f
[ "BSD-3-Clause" ]
null
null
null
bspump/ipc/datagram.py
thatch/BitSwanPump
98a5b8d09f9b59d5361611cee0bd45e7b4c69e3f
[ "BSD-3-Clause" ]
null
null
null
import asyncio import logging import socket from ..abc.source import Source from ..abc.sink import Sink # L = logging.getLogger(__name__) # class DatagramSource(Source): ConfigDefaults = { 'address': '127.0.0.1:8888', # IPv4, IPv6 or unix socket path 'max_packet_size': 64 * 1024, } def __init__(self, app, pipeline, id=None, config=None): super().__init__(app, pipeline, id=id, config=config) self.Loop = app.Loop # Create a UDP socket self.Address = str(self.Config['address']) if ":" in self.Address: host, port = self.Address.rsplit(":", maxsplit=1) (family, socktype, proto, canonname, sockaddr) = socket.getaddrinfo(host, port)[0] self.Socket = socket.socket(family, socket.SOCK_DGRAM) self.Socket.setblocking(False) self.Socket.setsockopt(socket.SOL_SOCKET, socket.SO_REUSEADDR, 1) self.Socket.setsockopt(socket.SOL_SOCKET, socket.SO_REUSEPORT, 1) self.Socket.bind(sockaddr) else: self.Socket = socket.socket(socket.AF_UNIX, socket.SOCK_DGRAM) self.Socket.setblocking(False) self.Socket.setsockopt(socket.SOL_SOCKET, socket.SO_REUSEADDR, 1) self.Socket.setsockopt(socket.SOL_SOCKET, socket.SO_REUSEPORT, 1) self.Socket.bind(self.Address) self.MaxPacketSize = int(self.Config['max_packet_size']) async def main(self): task = asyncio.ensure_future(self._receive(), loop=self.Loop) await self.stopped() task.cancel() await task self.Socket.close() async def _receive(self): while True: try: await self.Pipeline.ready() event = await self.Loop.sock_recv(self.Socket, self.MaxPacketSize) await self.Pipeline.ready() await self.process(event) except asyncio.CancelledError: break except Exception: L.exception(f"Error in datagram source.") raise class DatagramSink(Sink): ConfigDefaults = { 'address': '127.0.0.1:8888', # IPv4, IPv6 or unix socket path 'max_packet_size': 64 * 1024, } def __init__(self, app, pipeline, id=None, config=None): super().__init__(app, pipeline, id=id, config=config) self.Loop = app.Loop # Create a UDP socket self.Address = str(self.Config['address']) if ":" in self.Address: host, port = self.Address.rsplit(":", maxsplit=1) (family, socktype, proto, canonname, sockaddr) = socket.getaddrinfo(host, port)[0] self.Socket = socket.socket(family, socket.SOCK_DGRAM) self.Socket.setblocking(False) self.Socket.setsockopt(socket.SOL_SOCKET, socket.SO_REUSEADDR, 1) self.Socket.setsockopt(socket.SOL_SOCKET, socket.SO_REUSEPORT, 1) self.Socket.connect(sockaddr) else: self.Socket = socket.socket(socket.AF_UNIX, socket.SOCK_DGRAM) self.Socket.setblocking(False) self.Socket.setsockopt(socket.SOL_SOCKET, socket.SO_REUSEADDR, 1) self.Socket.setsockopt(socket.SOL_SOCKET, socket.SO_REUSEPORT, 1) self.Socket.connect(self.Address) self.MaxPacketSize = int(self.Config['max_packet_size']) def process(self, context, event): self.Socket.send(event)
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5
e8055095c827b1ba8ad9fa7faf22a6eaefca2e09
190
py
Python
prettyqt/core/threadpool.py
phil65/PrettyQt
26327670c46caa039c9bd15cb17a35ef5ad72e6c
[ "MIT" ]
7
2019-05-01T01:34:36.000Z
2022-03-08T02:24:14.000Z
prettyqt/core/threadpool.py
phil65/PrettyQt
26327670c46caa039c9bd15cb17a35ef5ad72e6c
[ "MIT" ]
141
2019-04-16T11:22:01.000Z
2021-04-14T15:12:36.000Z
prettyqt/core/threadpool.py
phil65/PrettyQt
26327670c46caa039c9bd15cb17a35ef5ad72e6c
[ "MIT" ]
5
2019-04-17T11:48:19.000Z
2021-11-21T10:30:19.000Z
from __future__ import annotations from prettyqt import core from prettyqt.qt import QtCore QtCore.QThreadPool.__bases__ = (core.Object,) class ThreadPool(QtCore.QThreadPool): pass
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138
py
Python
omnipod/records/__init__.py
mattprintz/omnipod
39aa16385ad7628821f77bfdd8b3bf629a1e389b
[ "MIT" ]
null
null
null
omnipod/records/__init__.py
mattprintz/omnipod
39aa16385ad7628821f77bfdd8b3bf629a1e389b
[ "MIT" ]
null
null
null
omnipod/records/__init__.py
mattprintz/omnipod
39aa16385ad7628821f77bfdd8b3bf629a1e389b
[ "MIT" ]
null
null
null
from .generic import IBFRecord, EEPromRecord from .profiles import Profile from .programs import BasalPrograms from .log_records import *
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py
Python
src/mbed_tools/cli/__init__.py
rwalton-arm/mbed-tools
131605540f4829116f977695a47dc10b3ac96450
[ "Apache-2.0" ]
null
null
null
src/mbed_tools/cli/__init__.py
rwalton-arm/mbed-tools
131605540f4829116f977695a47dc10b3ac96450
[ "Apache-2.0" ]
null
null
null
src/mbed_tools/cli/__init__.py
rwalton-arm/mbed-tools
131605540f4829116f977695a47dc10b3ac96450
[ "Apache-2.0" ]
null
null
null
# # Copyright (C) 2020 Arm Mbed. All rights reserved. # SPDX-License-Identifier: Apache-2.0 # """mbed_tools command line interface.""" from mbed_tools.cli.main import cli, LOGGER
22.5
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5
1c20d29499c60a956b35798816d9ad8b15b4a2bf
1,354
py
Python
tests/utils/test_anglecalculations.py
mfbehrens99/sailsim
800d71ec966345b0819a28921e14deb141bb3a35
[ "MIT" ]
2
2021-01-13T13:31:41.000Z
2022-03-10T10:17:29.000Z
tests/utils/test_anglecalculations.py
mfbehrens99/sailsim
800d71ec966345b0819a28921e14deb141bb3a35
[ "MIT" ]
37
2021-01-08T07:49:01.000Z
2022-02-08T22:22:50.000Z
tests/utils/test_anglecalculations.py
mfbehrens99/sailsim
800d71ec966345b0819a28921e14deb141bb3a35
[ "MIT" ]
1
2021-01-03T15:07:29.000Z
2021-01-03T15:07:29.000Z
"""Test module sailsim.utils.anglecalculations.""" from pytest import approx from math import pi from sailsim.utils.anglecalculations import angleKeepInterval, directionKeepInterval def testAngleKeepInterval(): assert angleKeepInterval( 0 + 0 * pi) == approx( 0) assert angleKeepInterval( 0 + 2 * pi) == approx( 0) assert angleKeepInterval( 0 - 2 * pi) == approx( 0) assert angleKeepInterval( 1 + 0 * pi) == approx( 1) assert angleKeepInterval( 1 + 2 * pi) == approx( 1) assert angleKeepInterval( 1 - 2 * pi) == approx( 1) assert angleKeepInterval(-1 + 0 * pi) == approx(-1) assert angleKeepInterval(-1 + 2 * pi) == approx(-1) assert angleKeepInterval(-1 - 2 * pi) == approx(-1) def testDirectionKeepInterval(): assert directionKeepInterval( 0 + 0 * pi) == approx(0) assert directionKeepInterval( 0 + 2 * pi) == approx(0) assert directionKeepInterval( 0 - 2 * pi) == approx(0) assert directionKeepInterval( 1 + 0 * pi) == approx(1) assert directionKeepInterval( 1 + 2 * pi) == approx(1) assert directionKeepInterval( 1 - 2 * pi) == approx(1) assert directionKeepInterval( 3 + 0 * pi) == approx(3) assert directionKeepInterval( 3 + 2 * pi) == approx(3) assert directionKeepInterval( 3 - 2 * pi) == approx(3) assert directionKeepInterval(-1 + 0 * pi) == approx(-1 + 2 * pi)
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0
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0
0
0
0
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0
0
0
0
0
null
0
0
0
1
0
0
1
0
0
0
0
0
0
5
1c68302ee3e8356fbf69ab8d745eb2e9280c9dad
712
py
Python
pycontrast/networks/SGCN/skeleton_meta.py
hongfz16/HCMoCo
140968c66b72034ee2dff610a69be464d8e5866b
[ "MIT" ]
28
2022-03-22T05:23:05.000Z
2022-03-29T07:45:23.000Z
pycontrast/networks/SGCN/skeleton_meta.py
hongfz16/HCMoCo
140968c66b72034ee2dff610a69be464d8e5866b
[ "MIT" ]
1
2022-03-29T17:23:56.000Z
2022-03-30T02:35:41.000Z
pycontrast/networks/SGCN/skeleton_meta.py
hongfz16/HCMoCo
140968c66b72034ee2dff610a69be464d8e5866b
[ "MIT" ]
null
null
null
import numpy as np class mpii_skeleton: parents_data = [1, 2, 6, 6, 3, 4, -1, 6, 7, 8, 11, 12, 8, 8, 13, 14] def parents(): return mpii_skeleton.parents_data def num_joints(): return len(mpii_skeleton.parents_data) class coco_reduce_skeleton: # Reduce: 0 - r ankle, 1 - r knee, 2 - r hip, 3 - l hip, 4 - l knee, # 5 - l ankle, 6 - head top, # 7 - r wrist, 8 - r elbow, 9 - r shoulder, 10 - l shoulder, # 11 - l elbow, 12 - l wrist parents_data = [1, 2, 9, 10, 3, 4, -1, 8, 9, 6, 6, 10, 11] def parents(): return coco_reduce_skeleton.parents_data def num_joints(): return len(coco_reduce_skeleton.parents_data)
29.666667
72
0.574438
118
712
3.322034
0.347458
0.168367
0.242347
0.17602
0.303571
0.204082
0.204082
0.204082
0
0
0
0.104839
0.303371
712
23
73
30.956522
0.685484
0.285112
0
0.307692
0
0
0
0
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0
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0
0
1
0.307692
false
0
0.076923
0.307692
1
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null
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null
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1
0
0
0
1
1
0
0
5
98e1b0358fc99041b0229d9e2e9dfb62cf70c3a7
23
py
Python
buildmimic/bigquery/mimic-iv-dummy-file2.py
briangow/mimic-iv
cd8288d4c20becc474a8661827013213d4e6447b
[ "MIT" ]
null
null
null
buildmimic/bigquery/mimic-iv-dummy-file2.py
briangow/mimic-iv
cd8288d4c20becc474a8661827013213d4e6447b
[ "MIT" ]
61
2021-04-29T17:14:40.000Z
2021-05-14T14:11:12.000Z
buildmimic/bigquery/mimic-iv-dummy-file2.py
briangow/mimic-iv
cd8288d4c20becc474a8661827013213d4e6447b
[ "MIT" ]
null
null
null
# MIMIC-IV dummy file 2
23
23
0.73913
5
23
3.4
1
0
0
0
0
0
0
0
0
0
0
0.052632
0.173913
23
1
23
23
0.842105
0.913043
0
null
0
null
0
0
null
0
0
0
null
1
null
true
0
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null
null
null
1
1
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null
0
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0
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0
0
0
0
0
1
0
0
0
1
0
0
0
0
0
0
null
0
0
0
0
0
0
1
0
0
0
0
0
0
5
98e65d4e640969e84299b942c4a4c5c0b5b4a5e0
28,690
py
Python
Quartz/QuartzCore/_metadata.py
EnjoyLifeFund/macHighSierra-py36-pkgs
5668b5785296b314ea1321057420bcd077dba9ea
[ "BSD-3-Clause", "BSD-2-Clause", "MIT" ]
null
null
null
Quartz/QuartzCore/_metadata.py
EnjoyLifeFund/macHighSierra-py36-pkgs
5668b5785296b314ea1321057420bcd077dba9ea
[ "BSD-3-Clause", "BSD-2-Clause", "MIT" ]
null
null
null
Quartz/QuartzCore/_metadata.py
EnjoyLifeFund/macHighSierra-py36-pkgs
5668b5785296b314ea1321057420bcd077dba9ea
[ "BSD-3-Clause", "BSD-2-Clause", "MIT" ]
null
null
null
# This file is generated by objective.metadata # # Last update: Sat Jul 22 14:57:27 2017 import objc, sys if sys.maxsize > 2 ** 32: def sel32or64(a, b): return b else: def sel32or64(a, b): return a if sys.byteorder == 'little': def littleOrBig(a, b): return a else: def littleOrBig(a, b): return b misc = { } misc.update({'CATransform3D': objc.createStructType('CATransform3D', sel32or64(b'{CATransform3D=ffffffffffffffff}', b'{CATransform3D=dddddddddddddddd}'), ['m11', 'm12', 'm13', 'm14', 'm21', 'm22', 'm23', 'm24', 'm31', 'm32', 'm33', 'm34', 'm41', 'm42', 'm43', 'm44'])}) constants = '''$CIDetectorAccuracy$CIDetectorAccuracyHigh$CIDetectorAccuracyLow$CIDetectorAspectRatio$CIDetectorEyeBlink$CIDetectorFocalLength$CIDetectorImageOrientation$CIDetectorMaxFeatureCount$CIDetectorMinFeatureSize$CIDetectorNumberOfAngles$CIDetectorReturnSubFeatures$CIDetectorSmile$CIDetectorTracking$CIDetectorTypeFace$CIDetectorTypeQRCode$CIDetectorTypeRectangle$CIDetectorTypeText$CIFeatureTypeFace$CIFeatureTypeQRCode$CIFeatureTypeRectangle$CIFeatureTypeText$kCAAlignmentCenter$kCAAlignmentJustified$kCAAlignmentLeft$kCAAlignmentNatural$kCAAlignmentRight$kCAAnimationCubic$kCAAnimationCubicPaced$kCAAnimationDiscrete$kCAAnimationLinear$kCAAnimationPaced$kCAAnimationRotateAuto$kCAAnimationRotateAutoReverse$kCAEmitterBehaviorAlignToMotion$kCAEmitterBehaviorAttractor$kCAEmitterBehaviorColorOverLife$kCAEmitterBehaviorDrag$kCAEmitterBehaviorLight$kCAEmitterBehaviorSimpleAttractor$kCAEmitterBehaviorValueOverLife$kCAEmitterBehaviorWave$kCAEmitterLayerAdditive$kCAEmitterLayerBackToFront$kCAEmitterLayerCircle$kCAEmitterLayerCuboid$kCAEmitterLayerLine$kCAEmitterLayerOldestFirst$kCAEmitterLayerOldestLast$kCAEmitterLayerOutline$kCAEmitterLayerPoint$kCAEmitterLayerPoints$kCAEmitterLayerRectangle$kCAEmitterLayerSphere$kCAEmitterLayerSurface$kCAEmitterLayerUnordered$kCAEmitterLayerVolume$kCAFillModeBackwards$kCAFillModeBoth$kCAFillModeForwards$kCAFillModeFrozen$kCAFillModeRemoved$kCAFillRuleEvenOdd$kCAFillRuleNonZero$kCAFilterLinear$kCAFilterNearest$kCAFilterTrilinear$kCAGradientLayerAxial$kCAGravityBottom$kCAGravityBottomLeft$kCAGravityBottomRight$kCAGravityCenter$kCAGravityLeft$kCAGravityResize$kCAGravityResizeAspect$kCAGravityResizeAspectFill$kCAGravityRight$kCAGravityTop$kCAGravityTopLeft$kCAGravityTopRight$kCALineCapButt$kCALineCapRound$kCALineCapSquare$kCALineJoinBevel$kCALineJoinMiter$kCALineJoinRound$kCAMediaTimingFunctionDefault$kCAMediaTimingFunctionEaseIn$kCAMediaTimingFunctionEaseInEaseOut$kCAMediaTimingFunctionEaseOut$kCAMediaTimingFunctionLinear$kCAOnOrderIn$kCAOnOrderOut$kCARendererColorSpace$kCAScrollBoth$kCAScrollHorizontally$kCAScrollNone$kCAScrollVertically$kCATransactionAnimationDuration$kCATransactionAnimationTimingFunction$kCATransactionCompletionBlock$kCATransactionDisableActions$kCATransition$kCATransitionFade$kCATransitionFromBottom$kCATransitionFromLeft$kCATransitionFromRight$kCATransitionFromTop$kCATransitionMoveIn$kCATransitionPush$kCATransitionReveal$kCATruncationEnd$kCATruncationMiddle$kCATruncationNone$kCATruncationStart$kCAValueFunctionRotateX$kCAValueFunctionRotateY$kCAValueFunctionRotateZ$kCAValueFunctionScale$kCAValueFunctionScaleX$kCAValueFunctionScaleY$kCAValueFunctionScaleZ$kCAValueFunctionTranslate$kCAValueFunctionTranslateX$kCAValueFunctionTranslateY$kCAValueFunctionTranslateZ$kCIActiveKeys$kCIApplyOptionColorSpace$kCIApplyOptionDefinition$kCIApplyOptionExtent$kCIApplyOptionUserInfo$kCIAttributeClass$kCIAttributeDefault$kCIAttributeDescription$kCIAttributeDisplayName$kCIAttributeFilterAvailable_Mac$kCIAttributeFilterAvailable_iOS$kCIAttributeFilterCategories$kCIAttributeFilterDisplayName$kCIAttributeFilterName$kCIAttributeIdentity$kCIAttributeMax$kCIAttributeMin$kCIAttributeName$kCIAttributeReferenceDocumentation$kCIAttributeSliderMax$kCIAttributeSliderMin$kCIAttributeType$kCIAttributeTypeAngle$kCIAttributeTypeBoolean$kCIAttributeTypeColor$kCIAttributeTypeCount$kCIAttributeTypeDistance$kCIAttributeTypeGradient$kCIAttributeTypeImage$kCIAttributeTypeInteger$kCIAttributeTypeOffset$kCIAttributeTypeOpaqueColor$kCIAttributeTypePosition$kCIAttributeTypePosition3$kCIAttributeTypeRectangle$kCIAttributeTypeScalar$kCIAttributeTypeTime$kCIAttributeTypeTransform$kCICategoryBlur$kCICategoryBuiltIn$kCICategoryColorAdjustment$kCICategoryColorEffect$kCICategoryCompositeOperation$kCICategoryDistortionEffect$kCICategoryFilterGenerator$kCICategoryGenerator$kCICategoryGeometryAdjustment$kCICategoryGradient$kCICategoryHalftoneEffect$kCICategoryHighDynamicRange$kCICategoryInterlaced$kCICategoryNonSquarePixels$kCICategoryReduction$kCICategorySharpen$kCICategoryStillImage$kCICategoryStylize$kCICategoryTileEffect$kCICategoryTransition$kCICategoryVideo$kCIContextCacheIntermediates$kCIContextHighQualityDownsample$kCIContextOutputColorSpace$kCIContextOutputPremultiplied$kCIContextPriorityRequestLow$kCIContextUseSoftwareRenderer$kCIContextWorkingColorSpace$kCIContextWorkingFormat$kCIFilterGeneratorExportedKey$kCIFilterGeneratorExportedKeyName$kCIFilterGeneratorExportedKeyTargetObject$kCIFormatA16@i$kCIFormatA8@i$kCIFormatABGR8@i$kCIFormatARGB8@i$kCIFormatAf@i$kCIFormatAh@i$kCIFormatBGRA8@i$kCIFormatL16@i$kCIFormatL8@i$kCIFormatLA16@i$kCIFormatLA8@i$kCIFormatLAf@i$kCIFormatLAh@i$kCIFormatLf@i$kCIFormatLh@i$kCIFormatR16@i$kCIFormatR8@i$kCIFormatRG16@i$kCIFormatRG8@i$kCIFormatRGBA16@i$kCIFormatRGBA8@i$kCIFormatRGBAf@i$kCIFormatRGBAh@i$kCIFormatRGf@i$kCIFormatRGh@i$kCIFormatRf@i$kCIFormatRh@i$kCIImageApplyOrientationProperty$kCIImageAutoAdjustCrop$kCIImageAutoAdjustEnhance$kCIImageAutoAdjustFeatures$kCIImageAutoAdjustLevel$kCIImageAutoAdjustRedEye$kCIImageAuxiliaryDepth$kCIImageAuxiliaryDisparity$kCIImageColorSpace$kCIImageNearestSampling$kCIImageProperties$kCIImageProviderTileSize$kCIImageProviderUserInfo$kCIImageRepresentationAVDepthData$kCIImageRepresentationDepthImage$kCIImageRepresentationDisparityImage$kCIImageTextureFormat$kCIImageTextureTarget$kCIInputAllowDraftModeKey$kCIInputAngleKey$kCIInputAspectRatioKey$kCIInputBackgroundImageKey$kCIInputBaselineExposureKey$kCIInputBiasKey$kCIInputBoostKey$kCIInputBoostShadowAmountKey$kCIInputBrightnessKey$kCIInputCenterKey$kCIInputColorKey$kCIInputColorNoiseReductionAmountKey$kCIInputContrastKey$kCIInputDecoderVersionKey$kCIInputDepthImageKey$kCIInputDisableGamutMapKey$kCIInputDisparityImageKey$kCIInputEVKey$kCIInputEnableChromaticNoiseTrackingKey$kCIInputEnableSharpeningKey$kCIInputEnableVendorLensCorrectionKey$kCIInputExtentKey$kCIInputGradientImageKey$kCIInputIgnoreImageOrientationKey$kCIInputImageKey$kCIInputImageOrientationKey$kCIInputIntensityKey$kCIInputLinearSpaceFilter$kCIInputLuminanceNoiseReductionAmountKey$kCIInputMaskImageKey$kCIInputMoireAmountKey$kCIInputNeutralChromaticityXKey$kCIInputNeutralChromaticityYKey$kCIInputNeutralLocationKey$kCIInputNeutralTemperatureKey$kCIInputNeutralTintKey$kCIInputNoiseReductionAmountKey$kCIInputNoiseReductionContrastAmountKey$kCIInputNoiseReductionDetailAmountKey$kCIInputNoiseReductionSharpnessAmountKey$kCIInputRadiusKey$kCIInputRefractionKey$kCIInputSaturationKey$kCIInputScaleFactorKey$kCIInputScaleKey$kCIInputShadingImageKey$kCIInputSharpnessKey$kCIInputTargetImageKey$kCIInputTimeKey$kCIInputTransformKey$kCIInputVersionKey$kCIInputWeightsKey$kCIInputWidthKey$kCIOutputImageKey$kCIOutputNativeSizeKey$kCISamplerAffineMatrix$kCISamplerColorSpace$kCISamplerFilterLinear$kCISamplerFilterMode$kCISamplerFilterNearest$kCISamplerWrapBlack$kCISamplerWrapClamp$kCISamplerWrapMode$kCISupportedDecoderVersionsKey$kCIUIParameterSet$kCIUISetAdvanced$kCIUISetBasic$kCIUISetDevelopment$kCIUISetIntermediate$''' constants = constants + '$CATransform3DIdentity@%s$'%(sel32or64('{CATransform3D=ffffffffffffffff}', '{CATransform3D=dddddddddddddddd}'),) enums = '''$CA_WARN_DEPRECATED@1$CIDataMatrixCodeECCVersion000@0$CIDataMatrixCodeECCVersion050@50$CIDataMatrixCodeECCVersion080@80$CIDataMatrixCodeECCVersion100@100$CIDataMatrixCodeECCVersion140@140$CIDataMatrixCodeECCVersion200@200$CIQRCodeErrorCorrectionLevelH@72$CIQRCodeErrorCorrectionLevelL@76$CIQRCodeErrorCorrectionLevelM@77$CIQRCodeErrorCorrectionLevelQ@81$CIRenderDestinationAlphaNone@0$CIRenderDestinationAlphaPremultiplied@1$CIRenderDestinationAlphaUnpremultiplied@2$kCAConstraintHeight@7$kCAConstraintMaxX@2$kCAConstraintMaxY@6$kCAConstraintMidX@1$kCAConstraintMidY@5$kCAConstraintMinX@0$kCAConstraintMinY@4$kCAConstraintWidth@3$kCALayerBottomEdge@4$kCALayerHeightSizable@16$kCALayerLeftEdge@1$kCALayerMaxXMargin@4$kCALayerMaxXMaxYCorner@8$kCALayerMaxXMinYCorner@2$kCALayerMaxYMargin@32$kCALayerMinXMargin@1$kCALayerMinXMaxYCorner@4$kCALayerMinXMinYCorner@1$kCALayerMinYMargin@8$kCALayerNotSizable@0$kCALayerRightEdge@2$kCALayerTopEdge@8$kCALayerWidthSizable@2$''' misc.update({}) functions={'CATransform3DIsAffine': (sel32or64(b'B{CATransform3D=ffffffffffffffff}', b'B{CATransform3D=dddddddddddddddd}'),), 'CATransform3DInvert': (sel32or64(b'{CATransform3D=ffffffffffffffff}{CATransform3D=ffffffffffffffff}', b'{CATransform3D=dddddddddddddddd}{CATransform3D=dddddddddddddddd}'),), 'CATransform3DIsIdentity': (sel32or64(b'B{CATransform3D=ffffffffffffffff}', b'B{CATransform3D=dddddddddddddddd}'),), 'CATransform3DMakeScale': (sel32or64(b'{CATransform3D=ffffffffffffffff}fff', b'{CATransform3D=dddddddddddddddd}ddd'),), 'CATransform3DTranslate': (sel32or64(b'{CATransform3D=ffffffffffffffff}{CATransform3D=ffffffffffffffff}fff', b'{CATransform3D=dddddddddddddddd}{CATransform3D=dddddddddddddddd}ddd'),), 'CATransform3DEqualToTransform': (sel32or64(b'B{CATransform3D=ffffffffffffffff}{CATransform3D=ffffffffffffffff}', b'B{CATransform3D=dddddddddddddddd}{CATransform3D=dddddddddddddddd}'),), 'CATransform3DRotate': (sel32or64(b'{CATransform3D=ffffffffffffffff}{CATransform3D=ffffffffffffffff}ffff', b'{CATransform3D=dddddddddddddddd}{CATransform3D=dddddddddddddddd}dddd'),), 'CACurrentMediaTime': (b'd',), 'CATransform3DMakeRotation': (sel32or64(b'{CATransform3D=ffffffffffffffff}ffff', b'{CATransform3D=dddddddddddddddd}dddd'),), 'CATransform3DConcat': (sel32or64(b'{CATransform3D=ffffffffffffffff}{CATransform3D=ffffffffffffffff}{CATransform3D=ffffffffffffffff}', b'{CATransform3D=dddddddddddddddd}{CATransform3D=dddddddddddddddd}{CATransform3D=dddddddddddddddd}'),), 'CATransform3DScale': (sel32or64(b'{CATransform3D=ffffffffffffffff}{CATransform3D=ffffffffffffffff}fff', b'{CATransform3D=dddddddddddddddd}{CATransform3D=dddddddddddddddd}ddd'),), 'CATransform3DMakeTranslation': (sel32or64(b'{CATransform3D=ffffffffffffffff}fff', b'{CATransform3D=dddddddddddddddd}ddd'),), 'CATransform3DGetAffineTransform': (sel32or64(b'{CGAffineTransform=ffffff}{CATransform3D=ffffffffffffffff}', b'{CGAffineTransform=dddddd}{CATransform3D=dddddddddddddddd}'),), 'CATransform3DMakeAffineTransform': (sel32or64(b'{CATransform3D=ffffffffffffffff}{CGAffineTransform=ffffff}', b'{CATransform3D=dddddddddddddddd}{CGAffineTransform=dddddd}'),)} r = objc.registerMetaDataForSelector objc._updatingMetadata(True) try: r(b'CAAnimation', b'isRemovedOnCompletion', {'retval': {'type': b'Z'}}) r(b'CAAnimation', b'setEnabled:', {'arguments': {2: {'type': 'Z'}}}) r(b'CAAnimation', b'setRemovedOnCompletion:', {'arguments': {2: {'type': b'Z'}}}) r(b'CAAnimation', b'shouldArchiveValueForKey:', {'retval': {'type': b'Z'}}) r(b'CAEmitterBehavior', b'isEnabled', {'retval': {'type': b'Z'}}) r(b'CAEmitterBehavior', b'setEnabled:', {'arguments': {2: {'type': b'Z'}}}) r(b'CAEmitterCell', b'isEnabled', {'retval': {'type': b'Z'}}) r(b'CAEmitterCell', b'setEnabled:', {'arguments': {2: {'type': b'Z'}}}) r(b'CAEmitterCell', b'shouldArchiveValueForKey:', {'retval': {'type': b'Z'}}) r(b'CAEmitterLayer', b'preservesDepth', {'retval': {'type': b'Z'}}) r(b'CAEmitterLayer', b'setPreservesDepth:', {'arguments': {2: {'type': b'Z'}}}) r(b'CALayer', b'containsPoint:', {'retval': {'type': b'Z'}}) r(b'CALayer', b'contentsAreFlipped', {'retval': {'type': b'Z'}}) r(b'CALayer', b'drawsAsynchronously', {'retval': {'type': b'Z'}}) r(b'CALayer', b'isDoubleSided', {'retval': {'type': b'Z'}}) r(b'CALayer', b'isGeometryFlipped', {'retval': {'type': b'Z'}}) r(b'CALayer', b'isHidden', {'retval': {'type': b'Z'}}) r(b'CALayer', b'isOpaque', {'retval': {'type': b'Z'}}) r(b'CALayer', b'masksToBounds', {'retval': {'type': b'Z'}}) r(b'CALayer', b'needsDisplay', {'retval': {'type': b'Z'}}) r(b'CALayer', b'needsDisplayForKey:', {'retval': {'type': b'Z'}}) r(b'CALayer', b'needsDisplayOnBoundsChange', {'retval': {'type': b'Z'}}) r(b'CALayer', b'needsLayout', {'retval': {'type': b'Z'}}) r(b'CALayer', b'setDoubleSided:', {'arguments': {2: {'type': b'Z'}}}) r(b'CALayer', b'setDrawsAsynchronously:', {'arguments': {2: {'type': b'Z'}}}) r(b'CALayer', b'setGeometryFlipped:', {'arguments': {2: {'type': b'Z'}}}) r(b'CALayer', b'setHidden:', {'arguments': {2: {'type': b'Z'}}}) r(b'CALayer', b'setMasksToBounds:', {'arguments': {2: {'type': b'Z'}}}) r(b'CALayer', b'setNeedsDisplayOnBoundsChange:', {'arguments': {2: {'type': b'Z'}}}) r(b'CALayer', b'setOpaque:', {'arguments': {2: {'type': b'Z'}}}) r(b'CALayer', b'setShouldRasterize:', {'arguments': {2: {'type': b'Z'}}}) r(b'CALayer', b'setWantsExtendedDynamicRangeContent:', {'arguments': {2: {'type': 'Z'}}}) r(b'CALayer', b'shouldArchiveValueForKey:', {'retval': {'type': b'Z'}}) r(b'CALayer', b'shouldRasterize', {'retval': {'type': b'Z'}}) r(b'CALayer', b'wantsExtendedDynamicRangeContent', {'retval': {'type': 'Z'}}) r(b'CAMetalLayer', b'allowsNextDrawableTimeout', {'retval': {'type': 'Z'}}) r(b'CAMetalLayer', b'displaySyncEnabled', {'retval': {'type': 'Z'}}) r(b'CAMetalLayer', b'framebufferOnly', {'retval': {'type': 'Z'}}) r(b'CAMetalLayer', b'presentsWithTransaction', {'retval': {'type': 'Z'}}) r(b'CAMetalLayer', b'setAllowsNextDrawableTimeout:', {'arguments': {2: {'type': 'Z'}}}) r(b'CAMetalLayer', b'setDisplaySyncEnabled:', {'arguments': {2: {'type': 'Z'}}}) r(b'CAMetalLayer', b'setFramebufferOnly:', {'arguments': {2: {'type': 'Z'}}}) r(b'CAMetalLayer', b'setPresentsWithTransaction:', {'arguments': {2: {'type': 'Z'}}}) r(b'CAMetalLayer', b'setWantsExtendedDynamicRangeContent:', {'arguments': {2: {'type': 'Z'}}}) r(b'CAMetalLayer', b'wantsExtendedDynamicRangeContent', {'retval': {'type': 'Z'}}) r(b'CAOpenGLLayer', b'canDrawInCGLContext:pixelFormat:forLayerTime:displayTime:', {'retval': {'type': b'Z'}, 'arguments': {5: {'type': sel32or64(b'^{_CVTimeStamp=IiqQdq{CVSMPTETime=ssLLLssss}QQ}', b'^{_CVTimeStamp=IiqQdq{CVSMPTETime=ssIIIssss}QQ}'), 'type_modifier': b'n'}}}) r(b'CAOpenGLLayer', b'drawInCGLContext:pixelFormat:forLayerTime:displayTime:', {'arguments': {5: {'type': sel32or64(b'^{_CVTimeStamp=IiqQdq{CVSMPTETime=ssLLLssss}QQ}', b'^{_CVTimeStamp=IiqQdq{CVSMPTETime=ssIIIssss}QQ}'), 'type_modifier': b'n'}}}) r(b'CAOpenGLLayer', b'isAsynchronous', {'retval': {'type': b'Z'}}) r(b'CAOpenGLLayer', b'setAsynchronous:', {'arguments': {2: {'type': b'Z'}}}) r(b'CAOpenGLLayer', b'setWantsExtendedDynamicRangeContent:', {'arguments': {2: {'type': 'Z'}}}) r(b'CAOpenGLLayer', b'wantsExtendedDynamicRangeContent', {'retval': {'type': 'Z'}}) r(b'CAPropertyAnimation', b'isAdditive', {'retval': {'type': b'Z'}}) r(b'CAPropertyAnimation', b'isCumulative', {'retval': {'type': b'Z'}}) r(b'CAPropertyAnimation', b'setAdditive:', {'arguments': {2: {'type': b'Z'}}}) r(b'CAPropertyAnimation', b'setCumulative:', {'arguments': {2: {'type': b'Z'}}}) r(b'CARenderer', b'beginFrameAtTime:timeStamp:', {'arguments': {3: {'type': sel32or64(b'^{_CVTimeStamp=IiqQdq{CVSMPTETime=ssLLLssss}QQ}', b'^{_CVTimeStamp=IiqQdq{CVSMPTETime=ssIIIssss}QQ}'), 'type_modifier': b'n'}}}) r(b'CARenderer', b'rendererWithCGLContext:options:', {'arguments': {2: {'type': '^{_CGLContextObject=}'}}}) r(b'CAReplicatorLayer', b'preservesDepth', {'retval': {'type': b'Z'}}) r(b'CAReplicatorLayer', b'setPreservesDepth:', {'arguments': {2: {'type': b'Z'}}}) r(b'CATextLayer', b'allowsFontSubpixelQuantization', {'retval': {'type': 'Z'}}) r(b'CATextLayer', b'font', {'retval': {'type': b'@'}}) r(b'CATextLayer', b'isWrapped', {'retval': {'type': b'Z'}}) r(b'CATextLayer', b'setAllowsFontSubpixelQuantization:', {'arguments': {2: {'type': 'Z'}}}) r(b'CATextLayer', b'setFont:', {'arguments': {2: {'type': b'@'}}}) r(b'CATextLayer', b'setWrapped:', {'arguments': {2: {'type': b'Z'}}}) r(b'CATransaction', b'completionBlock', {'retval': {'callable': {'retval': {'type': b'v'}, 'arguments': {0: {'type': b'^v'}}}}}) r(b'CATransaction', b'disableActions', {'retval': {'type': b'Z'}}) r(b'CATransaction', b'setCompletionBlock:', {'arguments': {2: {'callable': {'retval': {'type': b'v'}, 'arguments': {0: {'type': b'^v'}}}}}}) r(b'CATransaction', b'setDisableActions:', {'arguments': {2: {'type': b'Z'}}}) r(b'CIAztecCodeDescriptor', b'isCompact', {'retval': {'type': 'Z'}}) r(b'CIColor', b'components', {'retval': {'c_array_of_variable_length': True}}) r(b'CIContext', b'createCGImage:fromRect:format:colorSpace:deferred:', {'retval': {'already_cfretained': True}, 'arguments': {6: {'type': 'Z'}}}) r(b'CIContext', b'createCGLayerWithSize:info:', {'retval': {'already_cfretained': True}}) r(b'CIContext', b'prepareRender:fromRect:toDestination:atPoint:error:', {'retval': {'type': 'Z'}, 'arguments': {6: {'type_modifier': b'o'}}}) r(b'CIContext', b'render:toBitmap:rowBytes:bounds:format:colorSpace:', {'arguments': {3: {'type_modifier': b'o', 'c_array_of_variable_length': True}}}) r(b'CIContext', b'startTaskToClear:error:', {'arguments': {3: {'type_modifier': b'o'}}}) r(b'CIContext', b'startTaskToRender:fromRect:toDestination:atPoint:error:', {'arguments': {6: {'type_modifier': b'o'}}}) r(b'CIContext', b'startTaskToRender:toDestination:error:', {'arguments': {4: {'type_modifier': b'o'}}}) r(b'CIFaceFeature', b'hasFaceAngle', {'retval': {'type': b'Z'}}) r(b'CIFaceFeature', b'hasLeftEyePosition', {'retval': {'type': b'Z'}}) r(b'CIFaceFeature', b'hasMouthPosition', {'retval': {'type': b'Z'}}) r(b'CIFaceFeature', b'hasRightEyePosition', {'retval': {'type': b'Z'}}) r(b'CIFaceFeature', b'hasSmile', {'retval': {'type': b'Z'}}) r(b'CIFaceFeature', b'hasTrackingFrameCount', {'retval': {'type': b'Z'}}) r(b'CIFaceFeature', b'hasTrackingID', {'retval': {'type': b'Z'}}) r(b'CIFaceFeature', b'leftEyeClosed', {'retval': {'type': b'Z'}}) r(b'CIFaceFeature', b'rightEyeClosed', {'retval': {'type': b'Z'}}) r(b'CIFilter', b'apply:', {'c_array_delimited_by_null': True, 'variadic': True}) r(b'CIFilter', b'filterArrayFromSerializedXMP:inputImageExtent:error:', {'arguments': {4: {'type_modifier': b'o'}}}) r(b'CIFilter', b'filterWithName:keysAndValues:', {'c_array_delimited_by_null': True, 'variadic': True}) r(b'CIFilter', b'isEnabled', {'retval': {'type': b'Z'}}) r(b'CIFilter', b'setEnabled:', {'arguments': {2: {'type': b'Z'}}}) r(b'CIFilterGenerator', b'writeToURL:atomically:', {'retval': {'type': b'Z'}, 'arguments': {3: {'type': b'Z'}}}) r(b'CIFilterShape', b'transformBy:interior:', {'arguments': {3: {'type': b'Z'}}}) r(b'CIImage', b'imageWithTexture:size:flipped:colorSpace:', {'arguments': {4: {'type': b'Z'}}}) r(b'CIImage', b'imageWithTexture:size:flipped:options:', {'arguments': {4: {'type': b'Z'}}}) r(b'CIImage', b'initWithTexture:size:flipped:colorSpace:', {'arguments': {4: {'type': b'Z'}}}) r(b'CIImage', b'initWithTexture:size:flipped:options:', {'arguments': {4: {'type': b'Z'}}}) r(b'CIImage', b'writeHEIFRepresentationOfImage:toURL:format:colorSpace:options:error:', {'retval': {'type': 'Z'}, 'arguments': {7: {'type_modifier': b'o'}}}) r(b'CIContext', b'writeHEIFRepresentationOfImage:toURL:format:colorSpace:options:error:', {'retval': {'type': 'Z'}, 'arguments': {7: {'type_modifier': b'o'}}}) r(b'CIImage', b'writeJPEGRepresentationOfImage:toURL:colorSpace:options:error:', {'retval': {'type': 'Z'}, 'arguments': {6: {'type_modifier': b'o'}}}) r(b'CIContext', b'writeJPEGRepresentationOfImage:toURL:colorSpace:options:error:', {'retval': {'type': 'Z'}, 'arguments': {6: {'type_modifier': b'o'}}}) r(b'CIImage', b'writePNGRepresentationOfImage:toURL:format:colorSpace:options:error:', {'retval': {'type': 'Z'}, 'arguments': {7: {'type_modifier': b'o'}}}) r(b'CIContext', b'writePNGRepresentationOfImage:toURL:format:colorSpace:options:error:', {'retval': {'type': 'Z'}, 'arguments': {7: {'type_modifier': b'o'}}}) r(b'CIImageProcessorKernel', b'applyWithExtent:inputs:arguments:error:', {'arguments': {5: {'type_modifier': b'o'}}}) r(b'CIImageProcessorKernel', b'processWithInputs:arguments:output:error:', {'retval': {'type': 'Z'}, 'arguments': {5: {'type_modifier': b'o'}}}) r(b'CIKernel', b'applyWithExtent:roiCallback:arguments:', {'arguments': {3: {'callable': {'retval': {'type': sel32or64(b'{_NSRect={_NSPoint=ff}{_NSSize=ff}}', b'{CGRect={CGPoint=dd}{CGSize=dd}}')}, 'arguments': {0: {'type': b'^v'}, 1: {'type': b'i'}, 2: {'type': sel32or64(b'{_NSRect={_NSPoint=ff}{_NSSize=ff}}', b'{CGRect={CGPoint=dd}{CGSize=dd}}')}}}}}}) r(b'CIKernel', b'kernelWithFunctionName:fromMetalLibraryData:error:', {'arguments': {4: {'type_modifier': b'o'}}}) r(b'CIKernel', b'kernelWithFunctionName:fromMetalLibraryData:outputPixelFormat:error:', {'arguments': {5: {'type_modifier': b'o'}}}) r(b'CIKernel', b'setROISelector:', {'arguments': {2: {'sel_of_type': sel32or64(b'{CGRect={CGPoint=ff}{CGSize=ff}}@:i{CGRect={CGPoint=ff}{CGSize=ff}}@', b'{CGRect={CGPoint=dd}{CGSize=dd}}@:i{CGRect={CGPoint=dd}{CGSize=dd}}@')}}}) r(b'CIPDF417CodeDescriptor', b'isCompact', {'retval': {'type': 'Z'}}) r(b'CIPlugIn', b'loadPlugIn:allowExecutableCode:', {'arguments': {3: {'type': b'Z'}}}) r(b'CIPlugIn', b'loadPlugIn:allowNonExecutable:', {'arguments': {3: {'type': b'Z'}}}) r(b'CIRenderDestination', b'blendsInDestinationColorSpace', {'retval': {'type': 'Z'}}) r(b'CIRenderDestination', b'initWithWidth:height:pixelFormat:commandBuffer:mtlTextureProvider:', {'arguments': {6: {'callable': {'retval': {'type': b'@'}, 'arguments': {0: {'type': b'^v'}}}}}}) r(b'CIRenderDestination', b'isClamped', {'retval': {'type': 'Z'}}) r(b'CIRenderDestination', b'isDithered', {'retval': {'type': 'Z'}}) r(b'CIRenderDestination', b'isFlipped', {'retval': {'type': 'Z'}}) r(b'CIRenderDestination', b'setBlendsInDestinationColorSpace:', {'arguments': {2: {'type': 'Z'}}}) r(b'CIRenderDestination', b'setClamped:', {'arguments': {2: {'type': 'Z'}}}) r(b'CIRenderDestination', b'setDithered:', {'arguments': {2: {'type': 'Z'}}}) r(b'CIRenderDestination', b'setFlipped:', {'arguments': {2: {'type': 'Z'}}}) r(b'CIRenderTask', b'waitUntilCompletedAndReturnError:', {'arguments': {2: {'type_modifier': b'o'}}}) r(b'CISampler', b'initWithImage:keysAndValues:', {'c_array_delimited_by_null': True, 'variadic': True}) r(b'CISampler', b'samplerWithImage:keysAndValues:', {'c_array_delimited_by_null': True, 'variadic': True}) r(b'CIVector', b'initWithValues:count:', {'arguments': {2: {'type_modifier': b'n', 'c_array_length_in_arg': 3}}}) r(b'CIVector', b'vectorWithValues:count:', {'arguments': {2: {'type_modifier': b'n', 'c_array_length_in_arg': 3}}}) r(b'CIWarpKernel', b'applyWithExtent:roiCallback:inputImage:arguments:', {'arguments': {3: {'callable': {'retval': {'type': sel32or64(b'{_NSRect={_NSPoint=ff}{_NSSize=ff}}', b'{CGRect={CGPoint=dd}{CGSize=dd}}')}, 'arguments': {0: {'type': b'^v'}, 1: {'type': b'i'}, 2: {'type': sel32or64(b'{_NSRect={_NSPoint=ff}{_NSSize=ff}}', b'{CGRect={CGPoint=dd}{CGSize=dd}}')}}}}}}) r(b'NSObject', b'actionForLayer:forKey:', {'retval': {'type': b'@'}, 'arguments': {2: {'type': b'@'}, 3: {'type': b'@'}}}) r(b'NSObject', b'animationDidStart:', {'retval': {'type': b'v'}, 'arguments': {2: {'type': b'@'}}}) r(b'NSObject', b'animationDidStop:finished:', {'retval': {'type': b'v'}, 'arguments': {2: {'type': b'@'}, 3: {'type': b'Z'}}}) r(b'NSObject', b'autoreverses', {'required': True, 'retval': {'type': b'Z'}}) r(b'NSObject', b'baseAddress', {'retval': {'type': '^v', 'c_array_of_variable_length': True}}) r(b'NSObject', b'beginTime', {'required': True, 'retval': {'type': b'd'}}) r(b'NSObject', b'bytesPerRow', {'retval': {'type': 'L'}}) r(b'NSObject', b'displayLayer:', {'retval': {'type': b'v'}, 'arguments': {2: {'type': b'@'}}}) r(b'NSObject', b'drawLayer:inContext:', {'retval': {'type': b'v'}, 'arguments': {2: {'type': b'@'}, 3: {'type': b'^{CGContext=}'}}}) r(b'NSObject', b'duration', {'required': True, 'retval': {'type': b'd'}}) r(b'NSObject', b'fillMode', {'required': True, 'retval': {'type': b'@'}}) r(b'NSObject', b'filterWithName:', {'required': True, 'retval': {'type': b'@'}, 'arguments': {2: {'type': b'@'}}}) r(b'NSObject', b'format', {'retval': {'type': sel32or64(b'i', b'q')}}) r(b'NSObject', b'invalidateLayoutOfLayer:', {'retval': {'type': b'v'}, 'arguments': {2: {'type': b'@'}}}) r(b'NSObject', b'layoutSublayersOfLayer:', {'retval': {'type': b'v'}, 'arguments': {2: {'type': b'@'}}}) r(b'NSObject', b'load:', {'required': True, 'retval': {'type': b'Z'}, 'arguments': {2: {'type': b'^v'}}}) r(b'NSObject', b'preferredSizeOfLayer:', {'retval': {'type': sel32or64(b'{CGSize=ff}', b'{CGSize=dd}')}, 'arguments': {2: {'type': b'@'}}}) r(b'NSObject', b'provideImageData:bytesPerRow:origin::size::userInfo:', {'retval': {'type': b'v'}, 'arguments': {2: {'type': b'^v', 'type_modifier': b'o', 'c_array_of_variable_length': True}, 3: {'type': sel32or64(b'L', b'Q')}, 4: {'type': sel32or64(b'L', b'Q')}, 5: {'type': sel32or64(b'L', b'Q')}, 6: {'type': sel32or64(b'L', b'Q')}, 7: {'type': sel32or64(b'L', b'Q')}, 8: {'type': b'@'}}}) r(b'NSObject', b'region', {'retval': {'type': sel32or64(b'{CGRect={CGPoint=ff}{CGSize=ff}}', b'{CGRect={CGPoint=dd}{CGSize=dd}}')}}) r(b'NSObject', b'repeatCount', {'required': True, 'retval': {'type': b'f'}}) r(b'NSObject', b'repeatDuration', {'required': True, 'retval': {'type': b'd'}}) r(b'NSObject', b'runActionForKey:object:arguments:', {'required': True, 'retval': {'type': b'v'}, 'arguments': {2: {'type': b'@'}, 3: {'type': b'@'}, 4: {'type': b'@'}}}) r(b'NSObject', b'setAutoreverses:', {'required': True, 'retval': {'type': b'v'}, 'arguments': {2: {'type': b'Z'}}}) r(b'NSObject', b'setBeginTime:', {'required': True, 'retval': {'type': b'v'}, 'arguments': {2: {'type': b'd'}}}) r(b'NSObject', b'setDuration:', {'required': True, 'retval': {'type': b'v'}, 'arguments': {2: {'type': b'd'}}}) r(b'NSObject', b'setFillMode:', {'required': True, 'retval': {'type': b'v'}, 'arguments': {2: {'type': b'@'}}}) r(b'NSObject', b'setRepeatCount:', {'required': True, 'retval': {'type': b'v'}, 'arguments': {2: {'type': b'f'}}}) r(b'NSObject', b'setRepeatDuration:', {'required': True, 'retval': {'type': b'v'}, 'arguments': {2: {'type': b'd'}}}) r(b'NSObject', b'setSpeed:', {'required': True, 'retval': {'type': b'v'}, 'arguments': {2: {'type': b'f'}}}) r(b'NSObject', b'setTimeOffset:', {'required': True, 'retval': {'type': b'v'}, 'arguments': {2: {'type': b'd'}}}) r(b'NSObject', b'speed', {'required': True, 'retval': {'type': b'f'}}) r(b'NSObject', b'timeOffset', {'required': True, 'retval': {'type': b'd'}}) finally: objc._updatingMetadata(False) protocols={'CAAnimationDelegate': objc.informal_protocol('CAAnimationDelegate', [objc.selector(None, b'animationDidStart:', b'v@:@', isRequired=False), objc.selector(None, b'animationDidStop:finished:', b'v@:@Z', isRequired=False)]), 'CALayerDelegate': objc.informal_protocol('CALayerDelegate', [objc.selector(None, b'drawLayer:inContext:', b'v@:@^{CGContext=}', isRequired=False), objc.selector(None, b'actionForLayer:forKey:', b'@@:@@', isRequired=False), objc.selector(None, b'displayLayer:', b'v@:@', isRequired=False), objc.selector(None, b'layoutSublayersOfLayer:', b'v@:@', isRequired=False)]), 'CIImageProvider': objc.informal_protocol('CIImageProvider', [objc.selector(None, b'provideImageData:bytesPerRow:origin::size::userInfo:', sel32or64(b'v@:^vLLLLL@', b'v@:^vQQQQQ@'), isRequired=False)]), 'CALayoutManager': objc.informal_protocol('CALayoutManager', [objc.selector(None, b'preferredSizeOfLayer:', sel32or64(b'{CGSize=ff}@:@', b'{CGSize=dd}@:@'), isRequired=False), objc.selector(None, b'layoutSublayersOfLayer:', b'v@:@', isRequired=False), objc.selector(None, b'invalidateLayoutOfLayer:', b'v@:@', isRequired=False)])} expressions = {} # END OF FILE
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5
c705d9f52c3b02a03f542d80f95e1f26757cd546
270
py
Python
main/tasks.py
nmota/public-contracts
b809df82147e5e4fa746416c0f9d51db2c6db05a
[ "BSD-3-Clause" ]
null
null
null
main/tasks.py
nmota/public-contracts
b809df82147e5e4fa746416c0f9d51db2c6db05a
[ "BSD-3-Clause" ]
null
null
null
main/tasks.py
nmota/public-contracts
b809df82147e5e4fa746416c0f9d51db2c6db05a
[ "BSD-3-Clause" ]
null
null
null
import django_rq from django_rq import job import contracts.tasks import law.tasks import deputies.tasks @job def update(): django_rq.enqueue(law.tasks.update) django_rq.enqueue(contracts.tasks.update) django_rq.enqueue(deputies.tasks.recompute_analysis)
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c70f9bc9923fae8735cd90b24e72f574dc9bfd66
5,186
py
Python
tools/Vitis-AI-Quantizer/vai_q_pytorch/nndct_shared/quantization/commander.py
hito0512/Vitis-AI
996459fb96cb077ed2f7e789d515893b1cccbc95
[ "Apache-2.0" ]
1
2022-02-17T22:13:23.000Z
2022-02-17T22:13:23.000Z
tools/Vitis-AI-Quantizer/vai_q_pytorch/nndct_shared/quantization/commander.py
hito0512/Vitis-AI
996459fb96cb077ed2f7e789d515893b1cccbc95
[ "Apache-2.0" ]
null
null
null
tools/Vitis-AI-Quantizer/vai_q_pytorch/nndct_shared/quantization/commander.py
hito0512/Vitis-AI
996459fb96cb077ed2f7e789d515893b1cccbc95
[ "Apache-2.0" ]
null
null
null
# # Copyright 2019 Xilinx Inc. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # import math from nndct_shared.utils import BaseCommander from nndct_shared.base import NNDCT_OP from nndct_shared import nndct_graph as graph_utils class QuantConfigerCommander(BaseCommander): def create_commands(self): # def SoftFuseClamp(graph, quant_groups): # return graph_utils.group_up(graph, quant_groups, NNDCT_OP.CLAMP) def SoftFuseBatchSpaceNdToConv(graph, quant_groups): return graph_utils.group_up(graph, quant_groups, NNDCT_OP.BATCH_TO_SPACE_ND, NNDCT_OP.CONV2D) def SoftFuseConvToSpaceBatchNd(graph, quant_groups): return graph_utils.group_up(graph, quant_groups, NNDCT_OP.CONV2D, NNDCT_OP.SPACE_TO_BATCH_ND) def SoftFuseHardtanh(graph, quant_groups): return graph_utils.group_up(graph, quant_groups, NNDCT_OP.HARDTANH) def SoftFuseRelu(graph, quant_groups): return graph_utils.group_up(graph, quant_groups, NNDCT_OP.RELU) def SoftFuseLeakyRelu(graph, quant_groups): return graph_utils.group_up(graph, quant_groups, NNDCT_OP.LEAKY_RELU) def SoftFuseRelu6(graph, quant_groups): return graph_utils.group_up(graph, quant_groups, NNDCT_OP.RELU6) def SoftFuseReluk(graph, quant_groups): return graph_utils.group_up(graph, quant_groups, NNDCT_OP.RELUK) def SoftFuseChannelScale(graph, quant_groups): return graph_utils.group_up(graph, quant_groups, NNDCT_OP.CHANNEL_SCALE) def SoftFuseFlatten(graph, quant_groups): return graph_utils.group_up(graph, quant_groups, NNDCT_OP.FLATTEN) def SoftFuseSqueeze(graph, quant_groups): return graph_utils.group_up(graph, quant_groups, NNDCT_OP.SQUEEZE) def SoftFusePixelShuffle(graph, quant_groups): return graph_utils.group_up(graph, quant_groups, NNDCT_OP.PIXEL_SHUFFLE) def SoftFuseReshape(graph, quant_groups): def is_reshape_parent(node): if node.op.type == NNDCT_OP.SHAPE: return False elif node.op.type in [NNDCT_OP.MULTIPLY]: for p in graph.parents(node.name): return is_reshape_parent(p) else: return True for n in graph.nodes: if not n.in_quant_part: continue for p in graph.parents(n.name): if is_reshape_parent(p): if quant_groups[ n.name][0] == n.name and n.op.type == NNDCT_OP.RESHAPE: start_node = quant_groups[p.name][0] groups = graph_utils.glue_group_members(graph, quant_groups, start_node, n.name) return quant_groups def SoftFuseSplit(graph, quant_groups): return graph_utils.group_up(graph, quant_groups, NNDCT_OP.SPLIT) def SoftFuseStrideSlice(graph, quant_groups): return graph_utils.group_up(graph, quant_groups, NNDCT_OP.STRIDED_SLICE) def SoftFuseTranspose(graph, quant_groups): return graph_utils.group_up(graph, quant_groups, NNDCT_OP.TRANSPOSE) def SoftFuseTile(graph, quant_groups): return graph_utils.group_up(graph, quant_groups, NNDCT_OP.TILE) def SoftFuseUpSampling(graph, quant_groups): return graph_utils.group_up(graph, quant_groups, NNDCT_OP.UP_SAMPLING) def SoftFuseDropout(graph, quant_groups): return graph_utils.group_up(graph, quant_groups, NNDCT_OP.DROPOUT) def SoftFuseContiguous(graph, quant_groups): return graph_utils.group_up(graph, quant_groups, NNDCT_OP.CONTIGUOUS) def SoftFuseChunk(graph, quant_groups): return graph_utils.group_up(graph, quant_groups, NNDCT_OP.CHUNK) def SoftFusePermute(graph, quant_groups): return graph_utils.group_up(graph, quant_groups, NNDCT_OP.PERMUTE) def SoftFuseDivide(graph, quant_groups): return graph_utils.group_up(graph, quant_groups, NNDCT_OP.DIV) def SoftFuseExp(graph, quant_groups): return graph_utils.group_up(graph, quant_groups, NNDCT_OP.EXP) def SoftFuseExpand(graph, quant_groups): return graph_utils.group_up(graph, quant_groups, NNDCT_OP.EXPAND) def SoftFuseInplaceCopy(graph, quant_groups): return graph_utils.group_up(graph, quant_groups, NNDCT_OP.INPLACE_COPY) def SoftFuseRepeat(graph, quant_groups): return graph_utils.group_up(graph, quant_groups, NNDCT_OP.REPEAT) # def SoftFuseSelect(graph, quant_groups): # return graph_utils.group_up(graph, quant_groups, NNDCT_OP.SELECT) def SoftFuseUnsqueeze(graph, quant_groups): return graph_utils.group_up(graph, quant_groups, NNDCT_OP.UNSQUEEZE) return locals()
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c71504ccff0df55650d28a540ed98e6a02a69b48
522
py
Python
pylxd/models/__init__.py
AdamIsrael/pylxd
d5d47a4d1185b4956e997d70e09d649ea73ba26b
[ "Apache-2.0" ]
null
null
null
pylxd/models/__init__.py
AdamIsrael/pylxd
d5d47a4d1185b4956e997d70e09d649ea73ba26b
[ "Apache-2.0" ]
null
null
null
pylxd/models/__init__.py
AdamIsrael/pylxd
d5d47a4d1185b4956e997d70e09d649ea73ba26b
[ "Apache-2.0" ]
null
null
null
from pylxd.models.cluster import (Cluster, ClusterMember) # NOQA from pylxd.models.certificate import Certificate # NOQA from pylxd.models.container import Container, Snapshot # NOQA from pylxd.models.image import Image # NOQA from pylxd.models.network import Network # NOQA from pylxd.models.operation import Operation # NOQA from pylxd.models.profile import Profile # NOQA from pylxd.models.storage_pool import ( # NOQA StoragePool, # NOQA StorageResources, # NOQA StorageVolume, # NOQA ) # NOQA
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5
c763243bff5f87a536413fe4f3fe2a9034e6aafb
601
py
Python
src/counter.py
lifelongjourney/pipeline
93cc50fec3bdd77a5bbbbdd3d332dc00b0ab3020
[ "Apache-2.0" ]
1
2021-12-11T11:00:38.000Z
2021-12-11T11:00:38.000Z
src/counter.py
lifelongjourney/pipeline
93cc50fec3bdd77a5bbbbdd3d332dc00b0ab3020
[ "Apache-2.0" ]
null
null
null
src/counter.py
lifelongjourney/pipeline
93cc50fec3bdd77a5bbbbdd3d332dc00b0ab3020
[ "Apache-2.0" ]
null
null
null
from multiprocessing import Value class AtomicCounter(object): def __init__(self, init_value=0): self._val = Value('i', init_value) def increase(self, incr=1): with self._val.get_lock(): self._val.value += incr return self._val.value def decrease(self, decr=1): with self._val.get_lock(): self._val.value -= decr return self._val.value @property def value(self): with self._val.get_lock(): return self._val.value @property def lock(self): return self._val.get_lock()
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5
c77fd6f3f56c4caed16a281df0654ae13b5775af
80
py
Python
python/testData/paramInfo/StarredParamAndArg.py
truthiswill/intellij-community
fff88cfb0dc168eea18ecb745d3e5b93f57b0b95
[ "Apache-2.0" ]
2
2019-04-28T07:48:50.000Z
2020-12-11T14:18:08.000Z
python/testData/paramInfo/StarredParamAndArg.py
truthiswill/intellij-community
fff88cfb0dc168eea18ecb745d3e5b93f57b0b95
[ "Apache-2.0" ]
173
2018-07-05T13:59:39.000Z
2018-08-09T01:12:03.000Z
python/testData/paramInfo/StarredParamAndArg.py
truthiswill/intellij-community
fff88cfb0dc168eea18ecb745d3e5b93f57b0b95
[ "Apache-2.0" ]
2
2020-03-15T08:57:37.000Z
2020-04-07T04:48:14.000Z
def foo(a, b, *c): pass x = (5,6) foo(<arg1>1, <arg2>2, <arg3>4, <arg4>*x)
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c7852ac36a7aaaa4fd8614c9117a8d39993e7df0
171
py
Python
examples/hookiocli.py
Marak/hook.io-sdk-python
722b04eb0832ef712d5dcd491899996088e1aa8b
[ "Unlicense" ]
1
2021-06-15T11:52:44.000Z
2021-06-15T11:52:44.000Z
examples/hookiocli.py
Marak/hook.io-sdk-python
722b04eb0832ef712d5dcd491899996088e1aa8b
[ "Unlicense" ]
null
null
null
examples/hookiocli.py
Marak/hook.io-sdk-python
722b04eb0832ef712d5dcd491899996088e1aa8b
[ "Unlicense" ]
null
null
null
import sys from pkg_resources import load_entry_point if __name__ == '__main__': sys.exit(load_entry_point('hookio', 'console_scripts', 'hookiocli')(sys.argv))
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5
c7e7310619d963b59af9cac2a3fe9f2a78da2b18
29,314
py
Python
test/geometry/test_conversions.py
aardvarkkrill/kornia
e36ca3d15883a1dbbb0e7413719c0965a4b63cee
[ "ECL-2.0", "Apache-2.0" ]
null
null
null
test/geometry/test_conversions.py
aardvarkkrill/kornia
e36ca3d15883a1dbbb0e7413719c0965a4b63cee
[ "ECL-2.0", "Apache-2.0" ]
null
null
null
test/geometry/test_conversions.py
aardvarkkrill/kornia
e36ca3d15883a1dbbb0e7413719c0965a4b63cee
[ "ECL-2.0", "Apache-2.0" ]
1
2021-05-15T03:22:24.000Z
2021-05-15T03:22:24.000Z
from typing import Optional import pytest import numpy as np import kornia from kornia.testing import tensor_to_gradcheck_var, create_eye_batch import torch from torch.autograd import gradcheck from torch.testing import assert_allclose # based on: # https://github.com/ceres-solver/ceres-solver/blob/master/internal/ceres/rotation_test.cc#L271 class TestAngleAxisToQuaternion: def test_smoke(self, device, dtype): angle_axis = torch.zeros(3) quaternion = kornia.angle_axis_to_quaternion(angle_axis) assert quaternion.shape == (4,) @pytest.mark.parametrize("batch_size", (1, 3, 8)) def test_smoke_batch(self, batch_size, device, dtype): angle_axis = torch.zeros(batch_size, 3, device=device, dtype=dtype) quaternion = kornia.angle_axis_to_quaternion(angle_axis) assert quaternion.shape == (batch_size, 4) def test_zero_angle(self, device, dtype): angle_axis = torch.tensor([0., 0., 0.], device=device, dtype=dtype) expected = torch.tensor([1., 0., 0., 0.], device=device, dtype=dtype) quaternion = kornia.angle_axis_to_quaternion(angle_axis) assert_allclose(quaternion, expected, atol=1e-4, rtol=1e-4) def test_small_angle(self, device, dtype): theta = 1e-2 angle_axis = torch.tensor([theta, 0., 0.], device=device, dtype=dtype) expected = torch.tensor([np.cos(theta / 2), np.sin(theta / 2), 0., 0.], device=device, dtype=dtype) quaternion = kornia.angle_axis_to_quaternion(angle_axis) assert_allclose(quaternion, expected, atol=1e-4, rtol=1e-4) def test_x_rotation(self, device, dtype): half_sqrt2 = 0.5 * np.sqrt(2) angle_axis = torch.tensor([kornia.pi / 2, 0., 0.], device=device, dtype=dtype) expected = torch.tensor([half_sqrt2, half_sqrt2, 0., 0.], device=device, dtype=dtype) quaternion = kornia.angle_axis_to_quaternion(angle_axis) assert_allclose(quaternion, expected, atol=1e-4, rtol=1e-4) def test_gradcheck(self, device, dtype): eps = 1e-12 angle_axis = torch.tensor([0., 0., 0.], device=device, dtype=dtype) + eps angle_axis = tensor_to_gradcheck_var(angle_axis) # evaluate function gradient assert gradcheck(kornia.angle_axis_to_quaternion, (angle_axis,), raise_exception=True) class TestRotationMatrixToQuaternion: @pytest.mark.parametrize("batch_size", (1, 3, 8)) def test_smoke_batch(self, batch_size, device, dtype): matrix = torch.zeros(batch_size, 3, 3, device=device, dtype=dtype) quaternion = kornia.rotation_matrix_to_quaternion(matrix) assert quaternion.shape == (batch_size, 4) def test_identity(self, device, dtype): matrix = torch.tensor([ [1., 0., 0.], [0., 1., 0.], [0., 0., 1.], ], device=device, dtype=dtype) expected = torch.tensor( [0., 0., 0., 1.], device=device, dtype=dtype) quaternion = kornia.rotation_matrix_to_quaternion(matrix) assert_allclose(quaternion, expected, atol=1e-4, rtol=1e-4) def test_rot_x_45(self, device, dtype): matrix = torch.tensor([ [1., 0., 0.], [0., 0., -1.], [0., 1., 0.], ], device=device, dtype=dtype) pi_half2 = torch.cos(kornia.pi / 4).to(device=device, dtype=dtype) expected = torch.tensor( [pi_half2, 0., 0., pi_half2], device=device, dtype=dtype) quaternion = kornia.rotation_matrix_to_quaternion(matrix) assert_allclose(quaternion, expected, atol=1e-4, rtol=1e-4) def test_back_and_forth(self, device, dtype): matrix = torch.tensor([ [1., 0., 0.], [0., 0., -1.], [0., 1., 0.], ], device=device, dtype=dtype) quaternion = kornia.rotation_matrix_to_quaternion(matrix) matrix_hat = kornia.quaternion_to_rotation_matrix(quaternion) assert_allclose(matrix, matrix_hat) def test_corner_case(self, device, dtype): matrix = torch.tensor([ [-0.7799533010, -0.5432914495, 0.3106555045], [0.0492402576, -0.5481169224, -0.8349509239], [0.6238971353, -0.6359263659, 0.4542570710] ], device=device, dtype=dtype) quaternion_true = torch.tensor([0.280136495828629, -0.440902262926102, 0.834015488624573, 0.177614107728004], device=device, dtype=dtype) quaternion = kornia.rotation_matrix_to_quaternion(matrix) torch.set_printoptions(precision=10) assert_allclose(quaternion_true, quaternion) def test_gradcheck(self, device, dtype): matrix = torch.eye(3, device=device, dtype=dtype) matrix = tensor_to_gradcheck_var(matrix) # evaluate function gradient assert gradcheck(kornia.rotation_matrix_to_quaternion, (matrix,), raise_exception=True) @pytest.mark.skip(reason="turn off all jit for a while") def test_jit(self, device, dtype): op = kornia.quaternion_log_to_exp op_script = torch.jit.script(op) quaternion = torch.tensor([0., 0., 1.], device=device, dtype=dtype) actual = op_script(quaternion) expected = op(quaternion) assert_allclose(actual, expected, atol=1e-4, rtol=1e-4) class TestQuaternionToRotationMatrix: @pytest.mark.parametrize("batch_size", (1, 3, 8)) def test_smoke_batch(self, batch_size, device, dtype): quaternion = torch.zeros(batch_size, 4, device=device, dtype=dtype) matrix = kornia.quaternion_to_rotation_matrix(quaternion) assert matrix.shape == (batch_size, 3, 3) def test_unit_quaternion(self, device, dtype): quaternion = torch.tensor([0., 0., 0., 1.], device=device, dtype=dtype) expected = torch.tensor([ [1., 0., 0.], [0., 1., 0.], [0., 0., 1.], ], device=device, dtype=dtype) matrix = kornia.quaternion_to_rotation_matrix(quaternion) assert_allclose(matrix, expected, atol=1e-4, rtol=1e-4) def test_x_rotation(self, device, dtype): quaternion = torch.tensor([1., 0., 0., 0.], device=device, dtype=dtype) expected = torch.tensor([ [1., 0., 0.], [0., -1., 0.], [0., 0., -1.], ], device=device, dtype=dtype) matrix = kornia.quaternion_to_rotation_matrix(quaternion) assert_allclose(matrix, expected, atol=1e-4, rtol=1e-4) def test_y_rotation(self, device, dtype): quaternion = torch.tensor([0., 1., 0., 0.], device=device, dtype=dtype) expected = torch.tensor([ [-1., 0., 0.], [0., 1., 0.], [0., 0., -1.], ], device=device, dtype=dtype) matrix = kornia.quaternion_to_rotation_matrix(quaternion) assert_allclose(matrix, expected, atol=1e-4, rtol=1e-4) def test_z_rotation(self, device, dtype): quaternion = torch.tensor([0., 0., 1., 0.], device=device, dtype=dtype) expected = torch.tensor([ [-1., 0., 0.], [0., -1., 0.], [0., 0., 1.], ], device=device, dtype=dtype) matrix = kornia.quaternion_to_rotation_matrix(quaternion) assert_allclose(matrix, expected, atol=1e-4, rtol=1e-4) def test_gradcheck(self, device, dtype): quaternion = torch.tensor([0., 0., 0., 1.], device=device, dtype=dtype) quaternion = tensor_to_gradcheck_var(quaternion) # evaluate function gradient assert gradcheck(kornia.quaternion_to_rotation_matrix, (quaternion,), raise_exception=True) @pytest.mark.skip(reason="turn off all jit for a while") def test_jit(self, device, dtype): @torch.jit.script def op_script(input): return kornia.quaternion_to_rotation_matrix(input) quaternion = torch.tensor([0., 0., 1., 0.], device=device, dtype=dtype) actual = op_script(quaternion) expected = kornia.quaternion_to_rotation_matrix(quaternion) assert_allclose(actual, expected, atol=1e-4, rtol=1e-4) class TestQuaternionLogToExp: @pytest.mark.parametrize("batch_size", (1, 3, 8)) def test_smoke_batch(self, batch_size, device, dtype): quaternion_log = torch.zeros(batch_size, 3, device=device, dtype=dtype) quaternion_exp = kornia.quaternion_log_to_exp(quaternion_log) assert quaternion_exp.shape == (batch_size, 4) def test_unit_quaternion(self, device, dtype): quaternion_log = torch.tensor([0., 0., 0.], device=device, dtype=dtype) expected = torch.tensor([0., 0., 0., 1.], device=device, dtype=dtype) assert_allclose(kornia.quaternion_log_to_exp(quaternion_log), expected) def test_pi_quaternion(self, device, dtype): one = torch.tensor(1., device=device, dtype=dtype) quaternion_log = torch.tensor([1., 0., 0.], device=device, dtype=dtype) expected = torch.tensor([torch.sin(one), 0., 0., torch.cos(one)], device=device, dtype=dtype) assert_allclose(kornia.quaternion_log_to_exp(quaternion_log), expected) def test_back_and_forth(self, device, dtype): quaternion_log = torch.tensor([0., 0., 0.], device=device, dtype=dtype) quaternion_exp = kornia.quaternion_log_to_exp(quaternion_log) quaternion_log_hat = kornia.quaternion_exp_to_log(quaternion_exp) assert_allclose(quaternion_log, quaternion_log_hat) def test_gradcheck(self, device, dtype): quaternion = torch.tensor([0., 0., 1.], device=device, dtype=dtype) quaternion = tensor_to_gradcheck_var(quaternion) # evaluate function gradient assert gradcheck(kornia.quaternion_log_to_exp, (quaternion,), raise_exception=True) @pytest.mark.skip(reason="turn off all jit for a while") def test_jit(self, device, dtype): op = kornia.quaternion_log_to_exp op_script = torch.jit.script(op) quaternion = torch.tensor([0., 0., 1.], device=device, dtype=dtype) actual = op_script(quaternion) expected = op(quaternion) assert_allclose(actual, expected, atol=1e-4, rtol=1e-4) class TestQuaternionExpToLog: @pytest.mark.parametrize("batch_size", (1, 3, 8)) def test_smoke_batch(self, batch_size, device, dtype): quaternion_exp = torch.zeros(batch_size, 4, device=device, dtype=dtype) quaternion_log = kornia.quaternion_exp_to_log(quaternion_exp) assert quaternion_log.shape == (batch_size, 3) def test_unit_quaternion(self, device, dtype): quaternion_exp = torch.tensor([0., 0., 0., 1.], device=device, dtype=dtype) expected = torch.tensor([0., 0., 0.], device=device, dtype=dtype) assert_allclose(kornia.quaternion_exp_to_log(quaternion_exp), expected, atol=1e-4, rtol=1e-4) def test_pi_quaternion(self, device, dtype): quaternion_exp = torch.tensor([1., 0., 0., 0.], device=device, dtype=dtype) expected = torch.tensor([kornia.pi / 2, 0., 0.], device=device, dtype=dtype) assert_allclose(kornia.quaternion_exp_to_log(quaternion_exp), expected, atol=1e-4, rtol=1e-4) def test_back_and_forth(self, device, dtype): quaternion_exp = torch.tensor([1., 0., 0., 0.], device=device, dtype=dtype) quaternion_log = kornia.quaternion_exp_to_log(quaternion_exp) quaternion_exp_hat = kornia.quaternion_log_to_exp(quaternion_log) assert_allclose(quaternion_exp, quaternion_exp_hat, atol=1e-4, rtol=1e-4) def test_gradcheck(self, device, dtype): quaternion = torch.tensor([1., 0., 0., 0.], device=device, dtype=dtype) quaternion = tensor_to_gradcheck_var(quaternion) # evaluate function gradient assert gradcheck(kornia.quaternion_exp_to_log, (quaternion,), raise_exception=True) @pytest.mark.skip(reason="turn off all jit for a while") def test_jit(self, device, dtype): op = kornia.quaternion_exp_to_log op_script = torch.jit.script(op) quaternion = torch.tensor([0., 0., 1., 0.], device=device, dtype=dtype) actual = op_script(quaternion) expected = op(quaternion) assert_allclose(actual, expected, atol=1e-4, rtol=1e-4) class TestQuaternionToAngleAxis: def test_smoke(self, device, dtype): quaternion = torch.zeros(4, device=device, dtype=dtype) angle_axis = kornia.quaternion_to_angle_axis(quaternion) assert angle_axis.shape == (3,) @pytest.mark.parametrize("batch_size", (1, 3, 8)) def test_smoke_batch(self, batch_size, device, dtype): quaternion = torch.zeros(batch_size, 4, device=device, dtype=dtype) angle_axis = kornia.quaternion_to_angle_axis(quaternion) assert angle_axis.shape == (batch_size, 3) def test_unit_quaternion(self, device, dtype): quaternion = torch.tensor([1., 0., 0., 0.], device=device, dtype=dtype) expected = torch.tensor([0., 0., 0.], device=device, dtype=dtype) angle_axis = kornia.quaternion_to_angle_axis(quaternion) assert_allclose(angle_axis, expected, atol=1e-4, rtol=1e-4) def test_y_rotation(self, device, dtype): quaternion = torch.tensor([0., 0., 1., 0.], device=device, dtype=dtype) expected = torch.tensor([0., kornia.pi, 0.], device=device, dtype=dtype) angle_axis = kornia.quaternion_to_angle_axis(quaternion) assert_allclose(angle_axis, expected, atol=1e-4, rtol=1e-4) def test_z_rotation(self, device, dtype): quaternion = torch.tensor([np.sqrt(3) / 2, 0., 0., 0.5], device=device, dtype=dtype) expected = torch.tensor([0., 0., kornia.pi / 3], device=device, dtype=dtype) angle_axis = kornia.quaternion_to_angle_axis(quaternion) assert_allclose(angle_axis, expected, atol=1e-4, rtol=1e-4) def test_small_angle(self, device, dtype): theta = 1e-2 quaternion = torch.tensor([np.cos(theta / 2), np.sin(theta / 2), 0., 0.], device=device, dtype=dtype) expected = torch.tensor([theta, 0., 0.], device=device, dtype=dtype) angle_axis = kornia.quaternion_to_angle_axis(quaternion) assert_allclose(angle_axis, expected, atol=1e-4, rtol=1e-4) def test_gradcheck(self, device, dtype): eps = 1e-12 quaternion = torch.tensor([1., 0., 0., 0.], device=device, dtype=dtype) + eps quaternion = tensor_to_gradcheck_var(quaternion) # evaluate function gradient assert gradcheck(kornia.quaternion_to_angle_axis, (quaternion,), raise_exception=True) def test_pi(): assert_allclose(kornia.pi, 3.141592) @pytest.mark.parametrize("batch_shape", [ (2, 3), (1, 2, 3), (2, 3, 3), (5, 5, 3), ]) def test_rad2deg(batch_shape, device, dtype): # generate input data x_rad = kornia.pi * torch.rand(batch_shape, device=device, dtype=dtype) # convert radians/degrees x_deg = kornia.rad2deg(x_rad) x_deg_to_rad = kornia.deg2rad(x_deg) # compute error assert_allclose(x_rad, x_deg_to_rad) # evaluate function gradient assert gradcheck(kornia.rad2deg, (tensor_to_gradcheck_var(x_rad),), raise_exception=True) @pytest.mark.parametrize("batch_shape", [ (2, 3), (1, 2, 3), (2, 3, 3), (5, 5, 3), ]) def test_deg2rad(batch_shape, device, dtype): # generate input data x_deg = 180. * torch.rand(batch_shape, device=device, dtype=dtype) # convert radians/degrees x_rad = kornia.deg2rad(x_deg) x_rad_to_deg = kornia.rad2deg(x_rad) assert_allclose(x_deg, x_rad_to_deg, atol=1e-4, rtol=1e-4) assert gradcheck(kornia.deg2rad, (tensor_to_gradcheck_var(x_deg),), raise_exception=True) class TestPolCartConversions: def test_smoke(self, device, dtype): x = torch.ones(1, 1, 1, 1, device=device, dtype=dtype) assert kornia.pol2cart(x, x) is not None assert kornia.cart2pol(x, x) is not None @pytest.mark.parametrize("batch_shape", [ (2, 3), (1, 2, 3), (2, 3, 3), (5, 5, 3), ]) def test_pol2cart(self, batch_shape, device, dtype): # generate input data rho = torch.rand(batch_shape, dtype=dtype) phi = kornia.pi * torch.rand(batch_shape, dtype=dtype) rho = rho.to(device) phi = phi.to(device) # convert pol/cart x_pol2cart, y_pol2cart = kornia.pol2cart(rho, phi) rho_pol2cart, phi_pol2cart = kornia.cart2pol(x_pol2cart, y_pol2cart, 0) assert_allclose(rho, rho_pol2cart) assert_allclose(phi, phi_pol2cart) assert gradcheck(kornia.pol2cart, (tensor_to_gradcheck_var(rho), tensor_to_gradcheck_var(phi), ), raise_exception=True) @pytest.mark.parametrize("batch_shape", [ (2, 3), (1, 2, 3), (2, 3, 3), (5, 5, 3), ]) def test_cart2pol(self, batch_shape, device, dtype): # generate input data x = torch.rand(batch_shape, dtype=dtype) y = torch.rand(batch_shape, dtype=dtype) x = x.to(device) y = y.to(device) # convert cart/pol rho_cart2pol, phi_cart2pol = kornia.cart2pol(x, y, 0) x_cart2pol, y_cart2pol = kornia.pol2cart(rho_cart2pol, phi_cart2pol) assert_allclose(x, x_cart2pol) assert_allclose(y, y_cart2pol) assert gradcheck(kornia.cart2pol, (tensor_to_gradcheck_var(x), tensor_to_gradcheck_var(y), ), raise_exception=True) class TestConvertPointsToHomogeneous: def test_convert_points(self, device, dtype): # generate input data points_h = torch.tensor([ [1., 2., 1.], [0., 1., 2.], [2., 1., 0.], [-1., -2., -1.], [0., 1., -2.], ], device=device, dtype=dtype) expected = torch.tensor([ [1., 2., 1., 1.], [0., 1., 2., 1.], [2., 1., 0., 1.], [-1., -2., -1., 1.], [0., 1., -2., 1.], ], device=device, dtype=dtype) # to euclidean points = kornia.convert_points_to_homogeneous(points_h) assert_allclose(points, expected, atol=1e-4, rtol=1e-4) def test_convert_points_batch(self, device, dtype): # generate input data points_h = torch.tensor([[ [2., 1., 0.], ], [ [0., 1., 2.], ], [ [0., 1., -2.], ]], device=device, dtype=dtype) expected = torch.tensor([[ [2., 1., 0., 1.], ], [ [0., 1., 2., 1.], ], [ [0., 1., -2., 1.], ]], device=device, dtype=dtype) # to euclidean points = kornia.convert_points_to_homogeneous(points_h) assert_allclose(points, expected, atol=1e-4, rtol=1e-4) @pytest.mark.parametrize("batch_shape", [ (2, 3), (1, 2, 3), (2, 3, 3), (5, 5, 3), ]) def test_gradcheck(self, batch_shape, device, dtype): points_h = torch.rand(batch_shape, device=device, dtype=dtype) # evaluate function gradient points_h = tensor_to_gradcheck_var(points_h) # to var assert gradcheck(kornia.convert_points_to_homogeneous, (points_h,), raise_exception=True) @pytest.mark.skip(reason="turn off all jit for a while") def test_jit(self, device, dtype): op = kornia.convert_points_to_homogeneous op_script = torch.jit.script(op) points_h = torch.zeros(1, 2, 3, device=device, dtype=dtype) actual = op_script(points_h) expected = op(points_h) assert_allclose(actual, expected, atol=1e-4, rtol=1e-4) class TestConvertAtoH: def test_convert_points(self, device, dtype): # generate input data A = torch.tensor([ [1., 0., 0.], [0., 1., 0.], ], device=device, dtype=dtype).view(1, 2, 3) expected = torch.tensor([ [1., 0., 0.], [0., 1., 0.], [0., 0., 1.], ], device=device, dtype=dtype).view(1, 3, 3) # to euclidean H = kornia.geometry.conversions.convert_affinematrix_to_homography(A) assert_allclose(H, expected) @pytest.mark.parametrize("batch_shape", [ (10, 2, 3), (16, 2, 3)]) def test_gradcheck(self, batch_shape, device, dtype): points_h = torch.rand(batch_shape, device=device, dtype=dtype) # evaluate function gradient points_h = tensor_to_gradcheck_var(points_h) # to var assert gradcheck(kornia.convert_affinematrix_to_homography, (points_h,), raise_exception=True) @pytest.mark.skip(reason="turn off all jit for a while") def test_jit(self, device, dtype): op = kornia.convert_affinematrix_to_homography op_script = torch.jit.script(op) points_h = torch.zeros(1, 2, 3, device=device, dtype=dtype) actual = op_script(points_h) expected = op(points_h) assert_allclose(actual, expected, atol=1e-4, rtol=1e-4) class TestConvertPointsFromHomogeneous: @pytest.mark.parametrize("batch_shape", [ (2, 3), (1, 2, 3), (2, 3, 3), (5, 5, 3), ]) def test_cardinality(self, device, dtype, batch_shape): points_h = torch.rand(batch_shape, device=device, dtype=dtype) points = kornia.convert_points_from_homogeneous(points_h) assert points.shape == points.shape[:-1] + (2,) def test_points(self, device, dtype): # generate input data points_h = torch.tensor([ [1., 2., 1.], [0., 1., 2.], [2., 1., 0.], [-1., -2., -1.], [0., 1., -2.], ], device=device, dtype=dtype) expected = torch.tensor([ [1., 2.], [0., 0.5], [2., 1.], [1., 2.], [0., -0.5], ], device=device, dtype=dtype) # to euclidean points = kornia.convert_points_from_homogeneous(points_h) assert_allclose(points, expected, atol=1e-4, rtol=1e-4) def test_points_batch(self, device, dtype): # generate input data points_h = torch.tensor([[ [2., 1., 0.], ], [ [0., 1., 2.], ], [ [0., 1., -2.], ]], device=device, dtype=dtype) expected = torch.tensor([[ [2., 1.], ], [ [0., 0.5], ], [ [0., -0.5], ]], device=device, dtype=dtype) # to euclidean points = kornia.convert_points_from_homogeneous(points_h) assert_allclose(points, expected, atol=1e-4, rtol=1e-4) def test_gradcheck(self, device, dtype): points_h = torch.ones(1, 10, 3, device=device, dtype=dtype) # evaluate function gradient points_h = tensor_to_gradcheck_var(points_h) # to var assert gradcheck(kornia.convert_points_from_homogeneous, (points_h,), raise_exception=True) @pytest.mark.skip("RuntimeError: Jacobian mismatch for output 0 with respect to input 0,") def test_gradcheck_zvec_zeros(self, device, dtype): # generate input data points_h = torch.tensor([ [1., 2., 0.], [0., 1., 0.1], [2., 1., 0.1], ], device=device, dtype=dtype) # evaluate function gradient points_h = tensor_to_gradcheck_var(points_h) # to var assert gradcheck(kornia.convert_points_from_homogeneous, (points_h,), raise_exception=True) def test_jit(self, device, dtype): op = kornia.convert_points_from_homogeneous op_script = torch.jit.script(op) points_h = torch.zeros(1, 2, 3, device=device, dtype=dtype) actual = op_script(points_h) expected = op(points_h) assert_allclose(actual, expected, atol=1e-4, rtol=1e-4) @pytest.mark.parametrize("batch_size", [1, 2, 5]) def test_angle_axis_to_rotation_matrix(batch_size, device, dtype): # generate input data angle_axis = torch.rand(batch_size, 3, device=device, dtype=dtype) eye_batch = create_eye_batch(batch_size, 3, device=device, dtype=dtype) # apply transform rotation_matrix = kornia.angle_axis_to_rotation_matrix(angle_axis) rotation_matrix_eye = torch.matmul( rotation_matrix, rotation_matrix.transpose(1, 2)) assert_allclose(rotation_matrix_eye, eye_batch, atol=1e-4, rtol=1e-4) # evaluate function gradient angle_axis = tensor_to_gradcheck_var(angle_axis) # to var assert gradcheck(kornia.angle_axis_to_rotation_matrix, (angle_axis,), raise_exception=True) '''@pytest.mark.parametrize("batch_size", [1, 2, 5]) def test_rotation_matrix_to_angle_axis_gradcheck(batch_size, device_type): # generate input data rmat = torch.rand(batch_size, 3, 3).to(torch.device(device_type)) # evaluate function gradient rmat = tensor_to_gradcheck_var(rmat) # to var assert gradcheck(kornia.rotation_matrix_to_angle_axis, (rmat,), raise_exception=True)''' '''def test_rotation_matrix_to_angle_axis(device_type): device = torch.device(device_type) rmat_1 = torch.tensor([[-0.30382753, -0.95095137, -0.05814062], [-0.71581715, 0.26812278, -0.64476041], [0.62872461, -0.15427791, -0.76217038]]) rvec_1 = torch.tensor([1.50485376, -2.10737739, 0.7214174]) rmat_2 = torch.tensor([[0.6027768, -0.79275544, -0.09054801], [-0.67915707, -0.56931658, 0.46327563], [-0.41881476, -0.21775548, -0.88157628]]) rvec_2 = torch.tensor([-2.44916812, 1.18053411, 0.4085298]) rmat = torch.stack([rmat_2, rmat_1], dim=0, device=device, dtype=dtype) rvec = torch.stack([rvec_2, rvec_1], dim=0, device=device, dtype=dtype) assert_allclose(kornia.rotation_matrix_to_angle_axis(rmat), rvec)''' class TestNormalizePixelCoordinates: def test_tensor_bhw2(self, device, dtype): height, width = 3, 4 grid = kornia.utils.create_meshgrid( height, width, normalized_coordinates=False, device=device).to(dtype=dtype) expected = kornia.utils.create_meshgrid( height, width, normalized_coordinates=True, device=device).to(dtype=dtype) grid_norm = kornia.normalize_pixel_coordinates( grid, height, width) assert_allclose(grid_norm, expected, atol=1e-4, rtol=1e-4) def test_list(self, device, dtype): height, width = 3, 4 grid = kornia.utils.create_meshgrid( height, width, normalized_coordinates=False, device=device).to(dtype=dtype) grid = grid.contiguous().view(-1, 2) expected = kornia.utils.create_meshgrid( height, width, normalized_coordinates=True, device=device).to(dtype=dtype) expected = expected.contiguous().view(-1, 2) grid_norm = kornia.normalize_pixel_coordinates( grid, height, width) assert_allclose(grid_norm, expected, atol=1e-4, rtol=1e-4) @pytest.mark.skip(reason="turn off all jit for a while") def test_jit(self, device, dtype): op = kornia.normalize_pixel_coordinates op_script = torch.jit.script(op) height, width = 3, 4 grid = kornia.utils.create_meshgrid( height, width, normalized_coordinates=True, device=device).to(dtype=dtype) actual = op_script(grid, height, width) expected = op(grid, height, width) assert_allclose(actual, expected, atol=1e-4, rtol=1e-4) class TestDenormalizePixelCoordinates: def test_tensor_bhw2(self, device, dtype): height, width = 3, 4 grid = kornia.utils.create_meshgrid( height, width, normalized_coordinates=True, device=device).to(dtype=dtype) expected = kornia.utils.create_meshgrid( height, width, normalized_coordinates=False, device=device).to(dtype=dtype) grid_norm = kornia.denormalize_pixel_coordinates( grid, height, width) assert_allclose(grid_norm, expected, atol=1e-4, rtol=1e-4) def test_list(self, device, dtype): height, width = 3, 4 grid = kornia.utils.create_meshgrid( height, width, normalized_coordinates=True, device=device).to(dtype=dtype) grid = grid.contiguous().view(-1, 2) expected = kornia.utils.create_meshgrid( height, width, normalized_coordinates=False, device=device).to(dtype=dtype) expected = expected.contiguous().view(-1, 2) grid_norm = kornia.denormalize_pixel_coordinates( grid, height, width) assert_allclose(grid_norm, expected, atol=1e-4, rtol=1e-4) @pytest.mark.skip(reason="turn off all jit for a while") def test_jit(self, device, dtype): op = kornia.denormalize_pixel_coordinates op_script = torch.jit.script(op) height, width = 3, 4 grid = kornia.utils.create_meshgrid( height, width, normalized_coordinates=True, device=device).to(dtype=dtype) actual = op_script(grid, height, width) expected = op(grid, height, width) assert_allclose(actual, expected, atol=1e-4, rtol=1e-4)
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Python
Chapter 02/ch2_40.py
bpbpublications/TEST-YOUR-SKILLS-IN-PYTHON-LANGUAGE
f6a4194684515495d00aa38347a725dd08f39a0c
[ "MIT" ]
null
null
null
Chapter 02/ch2_40.py
bpbpublications/TEST-YOUR-SKILLS-IN-PYTHON-LANGUAGE
f6a4194684515495d00aa38347a725dd08f39a0c
[ "MIT" ]
null
null
null
Chapter 02/ch2_40.py
bpbpublications/TEST-YOUR-SKILLS-IN-PYTHON-LANGUAGE
f6a4194684515495d00aa38347a725dd08f39a0c
[ "MIT" ]
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import math print(math.e) # using print() to print the result
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Python
test/test_chapter3.py
laikuaut/lang_100_knock
359d68cd28cd453f1fe484c56b6381927f513c21
[ "MIT" ]
null
null
null
test/test_chapter3.py
laikuaut/lang_100_knock
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[ "MIT" ]
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null
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test/test_chapter3.py
laikuaut/lang_100_knock
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#!/usr/bin/env python # coding: utf-8 import unittest import glob from util import util from nlp100.chapter3.Q020 import * from nlp100.chapter3.Q021 import * from nlp100.chapter3.Q022 import * from nlp100.chapter3.Q023 import * from nlp100.chapter3.Q024 import * from nlp100.chapter3.Q025 import * from nlp100.chapter3.Q026 import * from nlp100.chapter3.Q027 import * from nlp100.chapter3.Q028 import * from nlp100.chapter3.Q029 import * class Test_Chapter3(unittest.TestCase): def test_Q_020(self): util.exe_cmd('rm data/Britain.txt') Q_020() with open('data/Britain.txt', 'r') as result_f, \ open('test/data/Britain.json', 'r') as current_f: current_data = json.loads(current_f.readline()) result = result_f.read().rstrip() self.assertEqual(result, current_data['text']) def test_Q_021(self): current = ['[[Category:イギリス|*]]', '[[Category:英連邦王国|*]]', '[[Category:G8加盟国]]', '[[Category:欧州連合加盟国]]', '[[Category:海洋国家]]', '[[Category:君主国]]', '[[Category:島国|くれいとふりてん]]', '[[Category:1801年に設立された州・地域]]'] result = Q_021() self.assertEqual(result, current) def test_Q_022(self): current = [ 'イギリス|*', '英連邦王国|*', 'G8加盟国', '欧州連合加盟国', '海洋国家', '君主国', '島国|くれいとふりてん', '1801年に設立された州・地域'] self.assertEqual(Q_022(), current) def test_Q_023(self): current = [('国名',1), ('歴史',1), ('地理',1), ('気候',2), ('政治',1), ('外交と軍事',1), ('地方行政区分',1), ('主要都市',2), ('科学技術',1), ('経済',1), ('鉱業',2), ('農業',2), ('貿易',2), ('通貨',2), ('企業',2), ('交通',1), ('道路',2), ('鉄道',2), ('海運',2), ('航空',2), ('通信',1), ('国民',1), ('言語',2), ('宗教',2), (' 婚姻 ',2), ('教育',2), ('文化',1), ('食文化',2), ('文学',2), (' 哲学 ',2), ('音楽',2), ('イギリスのポピュラー音楽',3), ('映画',2), ('コメディ',2), ('国花',2), ('世界遺産',2), ('祝祭日',2), ('スポーツ',1), ('サッカー',2), ('競馬',2), ('モータースポーツ',2), ('脚注',1), ('関連項目',1), ('外部リンク',1)] self.assertEqual(Q_023(), current) def test_Q_024(self): current = [ "Royal Coat of Arms of the United Kingdom.svg", "Battle of Waterloo 1815.PNG", "The British Empire.png", "Uk topo en.jpg", "BenNevis2005.jpg", "Elizabeth II greets NASA GSFC employees, May 8, 2007 edit.jpg", "Palace of Westminster, London - Feb 2007.jpg", "David Cameron and Barack Obama at the G20 Summit in Toronto.jpg", "Soldiers Trooping the Colour, 16th June 2007.jpg", "Scotland Parliament Holyrood.jpg", "London.bankofengland.arp.jpg", "City of London skyline from London City Hall - Oct 2008.jpg", "Oil platform in the North SeaPros.jpg", "Eurostar at St Pancras Jan 2008.jpg", "Heathrow T5.jpg", "Anglospeak.svg", "CHANDOS3.jpg", "The Fabs.JPG", "Wembley Stadium, illuminated.jpg" ] self.assertEqual(Q_024(), current) def test_Q_025(self): current = { '略名' : 'イギリス\n', '日本語国名' : 'グレートブリテン及び北アイルランド連合王国\n', '公式国名' : '{{lang|en|United Kingdom of Great Britain and Northern Ireland}}<ref>英語以外での正式国名:<br/>\n' \ '*{{lang|gd|An Rìoghachd Aonaichte na Breatainn Mhòr agus Eirinn mu Thuath}}（[[スコットランド・ゲール語]]）<br/>\n' \ '*{{lang|cy|Teyrnas Gyfunol Prydain Fawr a Gogledd Iwerddon}}（[[ウェールズ語]]）<br/>\n' \ '*{{lang|ga|Ríocht Aontaithe na Breataine Móire agus Tuaisceart na hÉireann}}（[[アイルランド語]]）<br/>\n' \ '*{{lang|kw|An Rywvaneth Unys a Vreten Veur hag Iwerdhon Glédh}}（[[コーンウォール語]]）<br/>\n' \ '*{{lang|sco|Unitit Kinrick o Great Breetain an Northren Ireland}}（[[スコットランド語]]）<br/>\n' \ '**{{lang|sco|Claught Kängrick o Docht Brätain an Norlin Airlann}}、{{lang|sco|Unitet Kängdom o Great Brittain an Norlin Airlann}}（アルスター・スコットランド語）</ref>\n', '国旗画像' : 'Flag of the United Kingdom.svg\n', '国章画像' : '[[ファイル:Royal Coat of Arms of the United Kingdom.svg|85px|イギリスの国章]]\n', '国章リンク' : '（[[イギリスの国章|国章]]）\n', '標語' : '{{lang|fr|Dieu et mon droit}}<br/>（[[フランス語]]:神と私の権利）\n', '国歌' : '[[女王陛下万歳|神よ女王陛下を守り給え]]\n', '位置画像' : 'Location_UK_EU_Europe_001.svg\n', '公用語' : '[[英語]]（事実上）\n', '首都' : '[[ロンドン]]\n', '最大都市' : 'ロンドン\n', '元首等肩書' : '[[イギリスの君主|女王]]\n', '元首等氏名' : '[[エリザベス2世]]\n', '首相等肩書' : '[[イギリスの首相|首相]]\n', '首相等氏名' : '[[デーヴィッド・キャメロン]]\n', '面積順位' : '76\n', '面積大きさ' : '1 E11\n', '面積値' : '244,820\n', '水面積率' : '1.3%\n', '人口統計年' : '2011\n', '人口順位' : '22\n', '人口大きさ' : '1 E7\n', '人口値' : '63,181,775<ref>[http://esa.un.org/unpd/wpp/Excel-Data/population.htm United Nations Department of Economic and Social Affairs>Population Division>Data>Population>Total Population]</ref>\n', '人口密度値' : '246\n', 'GDP統計年元' : '2012\n', 'GDP値元' : '1兆5478億<ref name="imf-statistics-gdp">[http://www.imf.org/external/pubs/ft/weo/2012/02/weodata/weorept.aspx?pr.x=70&pr.y=13&sy=2010&ey=2012&scsm=1&ssd=1&sort=country&ds=.&br=1&c=112&s=NGDP%2CNGDPD%2CPPPGDP%2CPPPPC&grp=0&a= IMF>Data and Statistics>World Economic Outlook Databases>By Countrise>United Kingdom]</ref>\n', 'GDP統計年MER' : '2012\n', 'GDP順位MER' : '5\n', 'GDP値MER' : '2兆4337億<ref name="imf-statistics-gdp" />\n', 'GDP統計年' : '2012\n', 'GDP順位' : '6\n', 'GDP値' : '2兆3162億<ref name="imf-statistics-gdp" />\n', 'GDP/人' : '36,727<ref name="imf-statistics-gdp" />\n', '建国形態' : '建国\n', '確立形態1' : '[[イングランド王国]]／[[スコットランド王国]]<br />（両国とも[[連合法 (1707年)|1707年連合法]]まで）\n', '確立年月日1' : '[[927年]]／[[843年]]\n', '確立形態2' : '[[グレートブリテン王国]]建国<br />（[[連合法 (1707年)|1707年連合法]]）\n', '確立年月日2' : '[[1707年]]\n', '確立形態3' : '[[グレートブリテン及びアイルランド連合王国]]建国<br />（[[連合法 (1800年)|1800年連合法]]）\n', '確立年月日3' : '[[1801年]]\n', '確立形態4' : "現在の国号「'''グレートブリテン及び北アイルランド連合王国'''」に変更\n", '確立年月日4' : '[[1927年]]\n', '通貨' : '[[スターリング・ポンド|UKポンド]] (&pound;)\n', '通貨コード' : 'GBP\n', '時間帯' : '±0\n', '夏時間' : '+1\n', 'ISO 3166-1' : 'GB / GBR\n', 'ccTLD' : '[[.uk]] / [[.gb]]<ref>使用は.ukに比べ圧倒的少数。</ref>\n', '国際電話番号' : '44\n', '注記' : '<references />\n' } result = Q_025() for key in result.keys(): self.assertEqual(result[key], current[key]) def test_Q_026(self): current = { '略名' : 'イギリス\n', '日本語国名' : 'グレートブリテン及び北アイルランド連合王国\n', '公式国名' : '{{lang|en|United Kingdom of Great Britain and Northern Ireland}}<ref>英語以外での正式国名:<br/>\n' \ '*{{lang|gd|An Rìoghachd Aonaichte na Breatainn Mhòr agus Eirinn mu Thuath}}（[[スコットランド・ゲール語]]）<br/>\n' \ '*{{lang|cy|Teyrnas Gyfunol Prydain Fawr a Gogledd Iwerddon}}（[[ウェールズ語]]）<br/>\n' \ '*{{lang|ga|Ríocht Aontaithe na Breataine Móire agus Tuaisceart na hÉireann}}（[[アイルランド語]]）<br/>\n' \ '*{{lang|kw|An Rywvaneth Unys a Vreten Veur hag Iwerdhon Glédh}}（[[コーンウォール語]]）<br/>\n' \ '*{{lang|sco|Unitit Kinrick o Great Breetain an Northren Ireland}}（[[スコットランド語]]）<br/>\n' \ '**{{lang|sco|Claught Kängrick o Docht Brätain an Norlin Airlann}}、{{lang|sco|Unitet Kängdom o Great Brittain an Norlin Airlann}}（アルスター・スコットランド語）</ref>\n', '国旗画像' : 'Flag of the United Kingdom.svg\n', '国章画像' : '[[ファイル:Royal Coat of Arms of the United Kingdom.svg|85px|イギリスの国章]]\n', '国章リンク' : '（[[イギリスの国章|国章]]）\n', '標語' : '{{lang|fr|Dieu et mon droit}}<br/>（[[フランス語]]:神と私の権利）\n', '国歌' : '[[女王陛下万歳|神よ女王陛下を守り給え]]\n', '位置画像' : 'Location_UK_EU_Europe_001.svg\n', '公用語' : '[[英語]]（事実上）\n', '首都' : '[[ロンドン]]\n', '最大都市' : 'ロンドン\n', '元首等肩書' : '[[イギリスの君主|女王]]\n', '元首等氏名' : '[[エリザベス2世]]\n', '首相等肩書' : '[[イギリスの首相|首相]]\n', '首相等氏名' : '[[デーヴィッド・キャメロン]]\n', '面積順位' : '76\n', '面積大きさ' : '1 E11\n', '面積値' : '244,820\n', '水面積率' : '1.3%\n', '人口統計年' : '2011\n', '人口順位' : '22\n', '人口大きさ' : '1 E7\n', '人口値' : '63,181,775<ref>[http://esa.un.org/unpd/wpp/Excel-Data/population.htm United Nations Department of Economic and Social Affairs>Population Division>Data>Population>Total Population]</ref>\n', '人口密度値' : '246\n', 'GDP統計年元' : '2012\n', 'GDP値元' : '1兆5478億<ref name="imf-statistics-gdp">[http://www.imf.org/external/pubs/ft/weo/2012/02/weodata/weorept.aspx?pr.x=70&pr.y=13&sy=2010&ey=2012&scsm=1&ssd=1&sort=country&ds=.&br=1&c=112&s=NGDP%2CNGDPD%2CPPPGDP%2CPPPPC&grp=0&a= IMF>Data and Statistics>World Economic Outlook Databases>By Countrise>United Kingdom]</ref>\n', 'GDP統計年MER' : '2012\n', 'GDP順位MER' : '5\n', 'GDP値MER' : '2兆4337億<ref name="imf-statistics-gdp" />\n', 'GDP統計年' : '2012\n', 'GDP順位' : '6\n', 'GDP値' : '2兆3162億<ref name="imf-statistics-gdp" />\n', 'GDP/人' : '36,727<ref name="imf-statistics-gdp" />\n', '建国形態' : '建国\n', '確立形態1' : '[[イングランド王国]]／[[スコットランド王国]]<br />（両国とも[[連合法 (1707年)|1707年連合法]]まで）\n', '確立年月日1' : '[[927年]]／[[843年]]\n', '確立形態2' : '[[グレートブリテン王国]]建国<br />（[[連合法 (1707年)|1707年連合法]]）\n', '確立年月日2' : '[[1707年]]\n', '確立形態3' : '[[グレートブリテン及びアイルランド連合王国]]建国<br />（[[連合法 (1800年)|1800年連合法]]）\n', '確立年月日3' : '[[1801年]]\n', '確立形態4' : '現在の国号「グレートブリテン及び北アイルランド連合王国」に変更\n', '確立年月日4' : '[[1927年]]\n', '通貨' : '[[スターリング・ポンド|UKポンド]] (&pound;)\n', '通貨コード' : 'GBP\n', '時間帯' : '±0\n', '夏時間' : '+1\n', 'ISO 3166-1' : 'GB / GBR\n', 'ccTLD' : '[[.uk]] / [[.gb]]<ref>使用は.ukに比べ圧倒的少数。</ref>\n', '国際電話番号' : '44\n', '注記' : '<references />\n' } result = Q_026() for key in result.keys(): self.assertEqual(result[key], current[key]) def test_Q_027(self): current = { '略名' : 'イギリス\n', '日本語国名' : 'グレートブリテン及び北アイルランド連合王国\n', '公式国名' : '{{lang|en|United Kingdom of Great Britain and Northern Ireland}}<ref>英語以外での正式国名:<br/>\n' \ '*{{lang|gd|An Rìoghachd Aonaichte na Breatainn Mhòr agus Eirinn mu Thuath}}（スコットランド・ゲール語）<br/>\n' \ '*{{lang|cy|Teyrnas Gyfunol Prydain Fawr a Gogledd Iwerddon}}（ウェールズ語）<br/>\n' \ '*{{lang|ga|Ríocht Aontaithe na Breataine Móire agus Tuaisceart na hÉireann}}（アイルランド語）<br/>\n' \ '*{{lang|kw|An Rywvaneth Unys a Vreten Veur hag Iwerdhon Glédh}}（コーンウォール語）<br/>\n' \ '*{{lang|sco|Unitit Kinrick o Great Breetain an Northren Ireland}}（スコットランド語）<br/>\n' \ '**{{lang|sco|Claught Kängrick o Docht Brätain an Norlin Airlann}}、{{lang|sco|Unitet Kängdom o Great Brittain an Norlin Airlann}}（アルスター・スコットランド語）</ref>\n', '国旗画像' : 'Flag of the United Kingdom.svg\n', '国章画像' : '[[ファイル:Royal Coat of Arms of the United Kingdom.svg|85px|イギリスの国章]]\n', '国章リンク' : '（国章）\n', '標語' : '{{lang|fr|Dieu et mon droit}}<br/>（フランス語:神と私の権利）\n', '国歌' : '神よ女王陛下を守り給え\n', '位置画像' : 'Location_UK_EU_Europe_001.svg\n', '公用語' : '英語（事実上）\n', '首都' : 'ロンドン\n', '最大都市' : 'ロンドン\n', '元首等肩書' : '女王\n', '元首等氏名' : 'エリザベス2世\n', '首相等肩書' : '首相\n', '首相等氏名' : 'デーヴィッド・キャメロン\n', '面積順位' : '76\n', '面積大きさ' : '1 E11\n', '面積値' : '244,820\n', '水面積率' : '1.3%\n', '人口統計年' : '2011\n', '人口順位' : '22\n', '人口大きさ' : '1 E7\n', '人口値' : '63,181,775<ref>[http://esa.un.org/unpd/wpp/Excel-Data/population.htm United Nations Department of Economic and Social Affairs>Population Division>Data>Population>Total Population]</ref>\n', '人口密度値' : '246\n', 'GDP統計年元' : '2012\n', 'GDP値元' : '1兆5478億<ref name="imf-statistics-gdp">[http://www.imf.org/external/pubs/ft/weo/2012/02/weodata/weorept.aspx?pr.x=70&pr.y=13&sy=2010&ey=2012&scsm=1&ssd=1&sort=country&ds=.&br=1&c=112&s=NGDP%2CNGDPD%2CPPPGDP%2CPPPPC&grp=0&a= IMF>Data and Statistics>World Economic Outlook Databases>By Countrise>United Kingdom]</ref>\n', 'GDP統計年MER' : '2012\n', 'GDP順位MER' : '5\n', 'GDP値MER' : '2兆4337億<ref name="imf-statistics-gdp" />\n', 'GDP統計年' : '2012\n', 'GDP順位' : '6\n', 'GDP値' : '2兆3162億<ref name="imf-statistics-gdp" />\n', 'GDP/人' : '36,727<ref name="imf-statistics-gdp" />\n', '建国形態' : '建国\n', '確立形態1' : 'イングランド王国／スコットランド王国<br />（両国とも1707年連合法まで）\n', '確立年月日1' : '927年／843年\n', '確立形態2' : 'グレートブリテン王国建国<br />（1707年連合法）\n', '確立年月日2' : '1707年\n', '確立形態3' : 'グレートブリテン及びアイルランド連合王国建国<br />（1800年連合法）\n', '確立年月日3' : '1801年\n', '確立形態4' : '現在の国号「グレートブリテン及び北アイルランド連合王国」に変更\n', '確立年月日4' : '1927年\n', '通貨' : 'UKポンド (&pound;)\n', '通貨コード' : 'GBP\n', '時間帯' : '±0\n', '夏時間' : '+1\n', 'ISO 3166-1' : 'GB / GBR\n', 'ccTLD' : '.uk / .gb<ref>使用は.ukに比べ圧倒的少数。</ref>\n', '国際電話番号' : '44\n', '注記' : '<references />\n' } result = Q_027() for key in result.keys(): self.assertEqual(result[key], current[key]) def test_Q_028(self): current = { '略名' : 'イギリス\n', '日本語国名' : 'グレートブリテン及び北アイルランド連合王国\n', '公式国名' : 'United Kingdom of Great Britain and Northern Ireland\n', '国旗画像' : 'Flag of the United Kingdom.svg\n', '国章画像' : 'Royal Coat of Arms of the United Kingdom.svg\n', '国章リンク' : '（国章）\n', '標語' : 'Dieu et mon droit（フランス語:神と私の権利）\n', '国歌' : '神よ女王陛下を守り給え\n', '位置画像' : 'Location_UK_EU_Europe_001.svg\n', '公用語' : '英語（事実上）\n', '首都' : 'ロンドン\n', '最大都市' : 'ロンドン\n', '元首等肩書' : '女王\n', '元首等氏名' : 'エリザベス2世\n', '首相等肩書' : '首相\n', '首相等氏名' : 'デーヴィッド・キャメロン\n', '面積順位' : '76\n', '面積大きさ' : '1 E11\n', '面積値' : '244,820\n', '水面積率' : '1.3%\n', '人口統計年' : '2011\n', '人口順位' : '22\n', '人口大きさ' : '1 E7\n', '人口値' : '63,181,775\n', '人口密度値' : '246\n', 'GDP統計年元' : '2012\n', 'GDP値元' : '1兆5478億\n', 'GDP統計年MER' : '2012\n', 'GDP順位MER' : '5\n', 'GDP値MER' : '2兆4337億\n', 'GDP統計年' : '2012\n', 'GDP順位' : '6\n', 'GDP値' : '2兆3162億\n', 'GDP/人' : '36,727\n', '建国形態' : '建国\n', '確立形態1' : 'イングランド王国／スコットランド王国（両国とも1707年連合法まで）\n', '確立年月日1' : '927年／843年\n', '確立形態2' : 'グレートブリテン王国建国（1707年連合法）\n', '確立年月日2' : '1707年\n', '確立形態3' : 'グレートブリテン及びアイルランド連合王国建国（1800年連合法）\n', '確立年月日3' : '1801年\n', '確立形態4' : '現在の国号「グレートブリテン及び北アイルランド連合王国」に変更\n', '確立年月日4' : '1927年\n', '通貨' : 'UKポンド (&pound;)\n', '通貨コード' : 'GBP\n', '時間帯' : '±0\n', '夏時間' : '+1\n', 'ISO 3166-1' : 'GB / GBR\n', 'ccTLD' : '.uk / .gb\n', '国際電話番号' : '44\n', '注記' : '\n' } result = Q_028() for key in result.keys(): self.assertEqual(result[key], current[key]) def test_Q_029(self): self.assertEqual(Q_029(), 'https://upload.wikimedia.org/wikipedia/en/a/ae/Flag_of_the_United_Kingdom.svg') if __name__ == '__main__': unittest.main()
45.305263
341
0.475139
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17,216
4.057884
0.226547
0.00664
0.015494
0.029513
0.78394
0.780005
0.776808
0.761313
0.74422
0.716675
0
0.069723
0.331029
17,216
379
342
45.424802
0.634801
0.001975
0
0.584022
0
0.041322
0.516123
0.12858
0
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0.027548
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0.027548
false
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0.066116
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null
0
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1
1
1
1
1
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5
40009c62c55e2f2c0a2ff3eadb52ec643b0da208
224
py
Python
diffstar/tests/test_stars.py
ArgonneCPAC/diffstar
4d15a5b2fd2faa86311c543a151fee73a14bd7f1
[ "BSD-3-Clause" ]
2
2021-12-01T00:47:22.000Z
2021-12-01T03:15:35.000Z
diffstar/tests/test_stars.py
ArgonneCPAC/diffstar
4d15a5b2fd2faa86311c543a151fee73a14bd7f1
[ "BSD-3-Clause" ]
null
null
null
diffstar/tests/test_stars.py
ArgonneCPAC/diffstar
4d15a5b2fd2faa86311c543a151fee73a14bd7f1
[ "BSD-3-Clause" ]
null
null
null
""" """ from ..stars import DEFAULT_SFR_PARAMS, _SFR_PARAM_BOUNDS def test_sfh_parameter_bounds(): for key, val in DEFAULT_SFR_PARAMS.items(): assert _SFR_PARAM_BOUNDS[key][0] < val < _SFR_PARAM_BOUNDS[key][1]
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5
40074593eb22707c49ed2db34cd19bd4bc406466
29
py
Python
.history/src/Simulador_20200707125832.py
eduardodut/Trabalho_final_estatistica_cd
fbedbbea6bdd7a79e1d62030cde0fab4e93fc338
[ "MIT" ]
null
null
null
.history/src/Simulador_20200707125832.py
eduardodut/Trabalho_final_estatistica_cd
fbedbbea6bdd7a79e1d62030cde0fab4e93fc338
[ "MIT" ]
null
null
null
.history/src/Simulador_20200707125832.py
eduardodut/Trabalho_final_estatistica_cd
fbedbbea6bdd7a79e1d62030cde0fab4e93fc338
[ "MIT" ]
null
null
null
class Simulador(): pass
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5
40217dae1512925ba0f386cb5d40b13d23dee81c
7,362
py
Python
tests/test_feap_base.py
basic-ph/feat
0660a34e5eeeab920d1ce8e139ab486e63bd419b
[ "MIT" ]
2
2020-07-13T11:59:19.000Z
2020-07-13T12:02:05.000Z
tests/test_feap_base.py
basic-ph/feat
0660a34e5eeeab920d1ce8e139ab486e63bd419b
[ "MIT" ]
null
null
null
tests/test_feap_base.py
basic-ph/feat
0660a34e5eeeab920d1ce8e139ab486e63bd419b
[ "MIT" ]
null
null
null
"""This module contains tests regarding simple problems resolved using FEAP software from University of California, Berkeley. Results obtained with this program are used as validation comparing them with those obtained using feat python code. This file is used for testing the base module. """ import logging import meshio import numpy as np import pytest from scipy import sparse from scipy.sparse import linalg from feat import base from feat import boundary as bc from feat import vector def test_feap_1(): #LOGGING main_log = logging.getLogger(__name__) main_log.setLevel(logging.DEBUG) main_handler = logging.StreamHandler() # main_log handler main_handler.setLevel(logging.DEBUG) main_formatter = logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(message)s') # main_log formatter main_handler.setFormatter(main_formatter) main_log.addHandler(main_handler) feat_log = logging.getLogger("feat") feat_log.setLevel(logging.DEBUG) feat_handler = logging.StreamHandler() feat_handler.setLevel(logging.DEBUG) feat_formatter = logging.Formatter('%(name)s - %(levelname)s - %(message)s') feat_handler.setFormatter(feat_formatter) feat_log.addHandler(feat_handler) # SETTINGS mesh_path = "tests/data/msh/feap_1.msh" main_log.info("MESH FILE: %s", mesh_path) # DATA element_type = "triangle" load_condition = "plane strain" # "plane stress" or "plane strain" thickness = 1 main_log.info("LOAD CONDITION: %s", load_condition) main_log.info("THICKNESS: %s", thickness) # MATERIAL cheese = base.Material("cheese", 70, 0.3, load_condition) #FIXME main_log.info("MATERIALS: TODO") # MESH mesh = meshio.read(mesh_path) elements = mesh.cells_dict[element_type] nodal_coord = mesh.points[:,:2] print(type(nodal_coord)) print(nodal_coord) num_elements = elements.shape[0] num_nodes = nodal_coord.shape[0] material_map = mesh.cell_data_dict["gmsh:physical"][element_type] - 1 # element-material map main_log.info("MESH INFO: %d elements, %d nodes", num_elements, num_nodes) # BOUNDARY CONDITIONS INSTANCES left_side = bc.DirichletBC("left side", mesh, [0], 0.0) bl_corner = bc.DirichletBC("bottom left corner", mesh, [1], 0.0) right_side = bc.DirichletBC("right side", mesh, [0], 1.0) main_log.info("BOUNDARY CONDITIONS: TODO") # ASSEMBLY E_material = base.compute_E_material(num_elements, material_map, mesh.field_data, cheese) K = np.zeros((num_nodes * 2, num_nodes * 2)) R = np.zeros(num_nodes * 2) K = base.assembly(K, num_elements, elements, nodal_coord, material_map, E_material, thickness, element_type) main_log.debug("STIFFNESS MATRIX (K) BEFORE BC:\n %s\n", K) # contrained dof rows of K are saved now reaction_dof = bc.dirichlet_dof(left_side, bl_corner) K_rows = K[reaction_dof, :] # BOUNDARY CONDITIONS APPLICATION K, R = bc.apply_dirichlet(K, R, left_side, bl_corner, right_side) main_log.debug("STIFFNESS MATRIX (K) AFTER BC:\n %s\n", K) main_log.debug("LOAD VECTOR (R) BEFORE BC:\n %s\n", R) # SOLVER D = np.linalg.solve(K, R) main_log.info("DISPLACEMENTS VECTOR (D):\n %s\n", D) reactions = np.dot(K_rows, D) main_log.debug("REACTIONS (dirichlet dofs):\n %s\n", reactions) modulus = base.compute_modulus(nodal_coord, right_side, reactions, thickness) main_log.info("RESULTING ELASTIC MODULUS: %f", modulus) comparable_dofs = [0, 1, 2, 4, 5, 6, 7] D_true = np.array([ 0.0, 0.0, 1.0, np.NaN, 1.0, -4.28571429e-01, 0.0, -4.28571429e-01, ]) reactions_true = np.array([-3.84615385e+01, -3.84615385e+01, -7.10542736e-15]) np.testing.assert_allclose(reactions_true, reactions) np.testing.assert_allclose(D_true[comparable_dofs], D[comparable_dofs]) @pytest.mark.parametrize( "poisson,D_true,reactions_true", [ ( 0.3, np.array([0.0, 0.0, 7.28e-02, 2.76e-01, 0.0, 8.0e-03]), np.array([-0.64, 0.24, -0.4]), ), ( 0.0, np.array([0.0, 0.0, 1.04e-01, 2.3815385e-01, 0.0, 4.307692e-02]), np.array([-0.64, 0.24, -0.4]), ) ], ) def test_feap_2(poisson, D_true, reactions_true): # LOGGING main_log = logging.getLogger(__name__) main_log.setLevel(logging.DEBUG) main_handler = logging.StreamHandler() # main_log handler main_handler.setLevel(logging.DEBUG) main_formatter = logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(message)s') # main_log formatter main_handler.setFormatter(main_formatter) main_log.addHandler(main_handler) feat_log = logging.getLogger("feat") feat_log.setLevel(logging.DEBUG) feat_handler = logging.StreamHandler() feat_handler.setLevel(logging.DEBUG) feat_formatter = logging.Formatter('%(name)s - %(levelname)s - %(message)s') feat_handler.setFormatter(feat_formatter) feat_log.addHandler(feat_handler) # SETTINGS mesh_path = "tests/data/msh/feap_2.msh" main_log.info("MESH FILE: %s", mesh_path) # DATA element_type = "triangle" load_condition = "plane strain" # "plane stress" or "plane strain" thickness = 1 main_log.info("LOAD CONDITION: %s", load_condition) main_log.info("THICKNESS: %s", thickness) # MATERIAL rubber = base.Material("rubber", 10, poisson, load_condition) #FIXME main_log.info("MATERIALS: TODO") # MESH mesh = meshio.read(mesh_path) elements = mesh.cells_dict[element_type] nodal_coord = mesh.points[:,:2] num_elements = elements.shape[0] num_nodes = nodal_coord.shape[0] material_map = mesh.cell_data_dict["gmsh:physical"][element_type] - 1 # element-material map main_log.info("MESH INFO: %d elements, %d nodes", num_elements, num_nodes) # BOUNDARY CONDITIONS INSTANCES left_side = bc.DirichletBC("left side", mesh, [0], 0.0) b_corner = bc.DirichletBC("bottom corner", mesh, [1], 0.0) r_corner_x = bc.NeumannBC("right corner", mesh, [0], 0.4) r_corner_y = bc.NeumannBC("right corner", mesh, [1], 0.4) main_log.info("BOUNDARY CONDITIONS: TODO") # ASSEMBLY E_material = base.compute_E_material(num_elements, material_map, mesh.field_data, rubber) main_log.debug("E array:\n %s\n", E_material) K = np.zeros((num_nodes * 2, num_nodes * 2)) R = np.zeros(num_nodes * 2) K = base.assembly(K, num_elements, elements, nodal_coord, material_map, E_material, thickness, element_type) main_log.debug("STIFFNESS MATRIX (K) BEFORE BC:\n %s\n", K) # contrained dof rows of K are saved now reaction_dof = bc.dirichlet_dof(left_side, b_corner) K_rows = K[reaction_dof, :] # BOUNDARY CONDITIONS APPLICATION K, R = bc.apply_dirichlet(K, R, left_side, b_corner) R = bc.apply_neumann(R, r_corner_x, r_corner_y) main_log.debug("STIFFNESS MATRIX (K) AFTER BC:\n %s\n", K) main_log.debug("LOAD VECTOR (R) BEFORE BC:\n %s\n", R) # SOLVER D = np.linalg.solve(K, R) main_log.info("DISPLACEMENTS VECTOR (D):\n %s\n", D) reactions = np.dot(K_rows, D) main_log.debug("REACTIONS (dirichlet dofs):\n %s\n", reactions) np.testing.assert_allclose(D_true, D) np.testing.assert_allclose(reactions_true, reactions)
36.994975
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0.678892
1,075
7,362
4.461395
0.170233
0.049625
0.034404
0.006255
0.77794
0.751251
0.748957
0.713511
0.707256
0.707256
0
0.031701
0.190166
7,362
199
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36.994975
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false
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0.014184
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null
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5
403c6843245ecd18b2594cd30a38fa251a9082ba
50
py
Python
nitorch/io/volumes/tiff/__init__.py
liamchalcroft/nitorch
0de179aff97244a82213c528f0d6393725c868c9
[ "MIT" ]
46
2020-07-31T10:14:05.000Z
2022-03-24T12:51:46.000Z
nitorch/io/volumes/tiff/__init__.py
liamchalcroft/nitorch
0de179aff97244a82213c528f0d6393725c868c9
[ "MIT" ]
36
2020-10-06T19:01:38.000Z
2022-02-03T18:07:35.000Z
nitorch/io/volumes/tiff/__init__.py
liamchalcroft/nitorch
0de179aff97244a82213c528f0d6393725c868c9
[ "MIT" ]
6
2021-01-05T14:59:05.000Z
2021-11-18T18:26:45.000Z
from .array import TiffArray from . import array
12.5
28
0.78
7
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5.571429
0.571429
0
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3
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1
0
1
0
0
5
40572a47cd6ddc72fba3874e28ff4a458b198bc9
23,001
py
Python
partialView/test/test_partialView.py
robzenn92/EpTODocker
7e3f17bf2d914ee8aa5c7d6393cb65d48177bd71
[ "MIT" ]
null
null
null
partialView/test/test_partialView.py
robzenn92/EpTODocker
7e3f17bf2d914ee8aa5c7d6393cb65d48177bd71
[ "MIT" ]
26
2017-10-23T08:04:00.000Z
2021-06-10T18:46:22.000Z
partialView/test/test_partialView.py
robzenn92/EpTODocker
7e3f17bf2d914ee8aa5c7d6393cb65d48177bd71
[ "MIT" ]
null
null
null
#!/usr/bin/env python2 import os import json import unittest from partialView.partialView import PartialView, PodDescriptor class TestPartialView(unittest.TestCase): @classmethod def setUpClass(cls): pass def setUp(self): self.partialView = PartialView("172.0.1.0") self.descriptors = [] self.ips = ["172.0.1.1", "172.0.1.2", "172.0.1.3", "172.0.1.4", "172.0.1.5"] for ip in self.ips: self.descriptors.append(PodDescriptor(ip)) # Limit should be equal to VIEW_LIMIT and shuffle_length should be equal to SHUFFLE_LENGTH def test_set_up_ok(self): self.assertEqual(self.partialView.limit, int(os.environ['VIEW_LIMIT'])) self.assertEqual(self.partialView.shuffle_length, int(os.environ['SHUFFLE_LENGTH'])) # Initial partialView should be empty def test_initial_partial_view_empty(self): self.assertEqual(self.partialView.size, 0) self.assertTrue(self.partialView.is_empty()) # Method is_full should return false if partial view is not full def test_initial_partial_view_should_not_be_full(self): self.assertFalse(self.partialView.is_full()) # Method is_full should return true if partial view is full def test_is_full_should_return_true_if_full(self): for i in range(self.partialView.limit): self.partialView.add_peer(self.descriptors[i]) self.assertTrue(self.partialView.is_full()) self.assertEqual(self.partialView.size, self.partialView.limit) # Method add_peer should return false if peer already contained def test_add_peer_should_return_false_if_peer_already_contained(self): peer = PodDescriptor("A new IP") self.partialView.add_peer(peer) size = self.partialView.size duplicated = PodDescriptor("A new IP") success = self.partialView.add_peer(duplicated) self.assertFalse(success) self.assertEqual(self.partialView.size, size) self.assertEqual(self.partialView.size, len(self.partialView.peer_list)) # Method add_peer should not allow to insert a self entry def test_add_peer_should_not_allow_self_entry(self): ip = "my ip" p1 = PartialView(ip) peer = PodDescriptor(ip) size = self.partialView.size success = p1.add_peer(peer) self.assertFalse(success) self.assertFalse(p1.contains_ip(ip)) self.assertEqual(p1.size, size) # Method add_peer should allow to insert a self entry if forced def test_add_peer_with_allow_self_should_allow_self_entry(self): ip = "my ip" p1 = PartialView(ip) peer = PodDescriptor(ip) size = self.partialView.size success = p1.add_peer(peer, True) self.assertTrue(success) self.assertTrue(p1.contains_ip(ip)) self.assertEqual(p1.size, size + 1) # Method add_peer should increment size if view is not full def test_add_peer_should_increment_size_if_not_full(self): size = self.partialView.size peer = PodDescriptor("A new IP") self.partialView.add_peer(peer) self.assertTrue(self.partialView.contains(peer)) self.assertEqual(self.partialView.size, size + 1) self.assertEqual(self.partialView.size, len(self.partialView.peer_list)) # Method add_peer should not increment size if view is full def test_add_peer_should_not_increment_size_if_full(self): peer = PodDescriptor("A new IP") for i in range(self.partialView.limit): self.partialView.add_peer(self.descriptors[i]) size = self.partialView.size success = self.partialView.add_peer(peer) self.assertFalse(success) self.assertFalse(self.partialView.contains(peer)) self.assertEqual(self.partialView.size, size) self.assertEqual(self.partialView.size, len(self.partialView.peer_list)) # Method add_peer_ip should return false if peer already contained def test_add_peer_ip_should_return_false_if_peer_already_contained(self): peer = "A new IP" self.partialView.add_peer_ip(peer) size = self.partialView.size duplicated = "A new IP" success = self.partialView.add_peer_ip(duplicated) self.assertFalse(success) self.assertEqual(self.partialView.size, size) self.assertEqual(self.partialView.size, len(self.partialView.peer_list)) # Method add_peer_ip should not allow to insert a self entry def test_add_peer_ip_should_not_allow_self_entry(self): ip = "my ip" p1 = PartialView(ip) size = self.partialView.size success = p1.add_peer_ip(ip) self.assertFalse(success) self.assertFalse(p1.contains_ip(ip)) self.assertEqual(p1.size, size) # Method add_peer_ip should allow to insert a self entry if forced def test_add_peer_ip_with_allow_self_should_allow_self_entry(self): ip = "my ip" p1 = PartialView(ip) size = self.partialView.size success = p1.add_peer_ip(ip, True) self.assertTrue(success) self.assertTrue(p1.contains_ip(ip)) self.assertEqual(p1.size, size + 1) # Method add_peer_ip should increment size if view is not full def test_add_peer_ip_should_increment_size_if_not_full(self): size = self.partialView.size peer = "A new IP" self.partialView.add_peer_ip(peer) self.assertTrue(self.partialView.contains_ip(peer)) self.assertEqual(self.partialView.size, size + 1) self.assertEqual(self.partialView.size, len(self.partialView.peer_list)) # Method add_peer_ip should not increment size if view is full def test_add_peer_ip_should_not_increment_size_if_full(self): peer = "A new IP" for i in range(self.partialView.limit): self.partialView.add_peer(self.descriptors[i]) size = self.partialView.size success = self.partialView.add_peer_ip(peer) self.assertFalse(success) self.assertFalse(self.partialView.contains_ip(peer)) self.assertEqual(self.partialView.size, size) self.assertEqual(self.partialView.size, len(self.partialView.peer_list)) # Initial age should be zero def test_initial_age_peer(self): self.partialView.add_peer(PodDescriptor("172.0.1.5")) self.assertEqual(self.partialView.peer_list[0].age, 0) # Initial age should be zero def test_initial_age_peer_ip(self): self.partialView.add_peer_ip("172.0.1.5") self.assertEqual(self.partialView.peer_list[0].age, 0) # Method get_peer_ip_list should return a list of ips def test_get_peer_ip_list_returns_ips(self): for ip in self.ips: self.partialView.add_peer_ip(ip) self.assertEqual(self.partialView.get_peer_ip_list(), self.ips[:self.partialView.limit]) # Initial age should be zero def test_partial_view_size_limit(self): for ip in self.ips: self.partialView.add_peer_ip(ip) self.assertEqual(self.partialView.size, self.partialView.limit) self.assertTrue(self.partialView.is_full()) for i in range(self.partialView.limit): self.assertEqual(self.partialView.peer_list[i].ip, self.ips[i]) def test_contains_return_true_if_contained(self): for descr in self.descriptors: self.partialView.add_peer(descr) for descr in self.descriptors[:self.partialView.size]: self.assertTrue(self.partialView.contains(descr)) for descr in self.descriptors[self.partialView.size:]: self.assertFalse(self.partialView.contains(descr)) def test_contains_ip_return_true_if_contained(self): for ip in self.ips: self.partialView.add_peer_ip(ip) for ip in self.ips[:self.partialView.size]: self.assertTrue(self.partialView.contains_ip(ip)) for ip in self.ips[self.partialView.size:]: self.assertFalse(self.partialView.contains_ip(ip)) # Age should be incremented by one def test_increment(self): self.partialView.add_peer(PodDescriptor("172.0.1.5", 1)) self.partialView.add_peer(PodDescriptor("172.0.1.7", 3)) self.partialView.increment() self.assertEqual(self.partialView.peer_list[0].age, 2) self.assertEqual(self.partialView.peer_list[1].age, 4) # Sort should sort view by peer's age def test_sort(self): self.partialView.add_peer(PodDescriptor("172.0.1.5", 2)) self.partialView.add_peer(PodDescriptor("172.0.1.4", 3)) self.partialView.add_peer(PodDescriptor("172.0.1.8", 1)) self.partialView.sort() self.assertEqual(self.partialView.peer_list[0].ip, "172.0.1.8") self.assertEqual(self.partialView.peer_list[1].ip, "172.0.1.5") self.assertEqual(self.partialView.peer_list[2].ip, "172.0.1.4") # Method sample_descriptors should return an empty list if view is empty def test_sample_descriptors_should_return_empty_list_if_empty_view(self): sample = self.partialView.sample_descriptors(3) self.assertEqual(len(sample), 0) self.assertEqual(sample, []) self.assertTrue(isinstance(sample, list)) # Method sample_descriptors should return a list of size element if the view's size is less than the limit given as parameter def test_sample_descriptors_should_return_less_than_limit_peers_if_size_less_than_limit(self): self.partialView.add_peer(PodDescriptor("172.0.1.5", 2)) self.partialView.add_peer(PodDescriptor("172.0.1.4", 3)) size = self.partialView.size sample = self.partialView.sample_descriptors(3) self.assertEqual(len(sample), size) # Method sample_descriptors should return a list of limit peers despite the size of the the view is greater then limit def test_sample_descriptors_should_return_no_more_than_limit_peers(self): self.partialView.add_peer(PodDescriptor("172.0.1.5", 2)) self.partialView.add_peer(PodDescriptor("172.0.1.4", 3)) self.partialView.add_peer(PodDescriptor("172.0.1.9", 4)) limit = 2 size = self.partialView.size sample = self.partialView.sample_descriptors(limit) self.assertNotEqual(limit, size) self.assertEqual(len(sample), limit) # Method sample_descriptors should return a list of 1 peer and avoid the peer given as parameter def test_sample_descriptors_with_avoid_peer_more_than_limit(self): to_avoid = PodDescriptor("172.0.1.9", 4) self.partialView.add_peer(PodDescriptor("172.0.1.5", 2)) self.partialView.add_peer(PodDescriptor("172.0.1.4", 3)) self.partialView.add_peer(to_avoid) limit = 1 sample = self.partialView.sample_descriptors(limit, to_avoid) self.assertEqual(len(sample), limit) self.assertFalse(to_avoid in sample) # Method sample_descriptors should return a list of 2 peers and avoid the peer given as parameter def test_sample_descriptors_with_avoid_peer_less_than_limit(self): to_avoid = PodDescriptor("172.0.1.9", 4) self.partialView.add_peer(PodDescriptor("172.0.1.5", 2)) self.partialView.add_peer(PodDescriptor("172.0.1.4", 3)) self.partialView.add_peer(to_avoid) limit = 3 sample = self.partialView.sample_descriptors(limit, to_avoid) self.assertEqual(len(sample), 2) self.assertFalse(to_avoid in sample) # Method sample_descriptors should return a list of 3 peers if the peer to avoid is not contained in the view def test_sample_descriptors_with_avoid_peer_not_in_view(self): to_avoid = PodDescriptor("172.0.1.9", 4) self.partialView.add_peer(PodDescriptor("172.0.1.5", 2)) self.partialView.add_peer(PodDescriptor("172.0.1.4", 3)) self.partialView.add_peer(PodDescriptor("172.0.1.10", 8)) limit = 3 sample = self.partialView.sample_descriptors(limit, to_avoid) self.assertEqual(len(sample), limit) self.assertFalse(to_avoid in sample) # Method sample_ips should return a list of 3 ips def test_sample_ips_should_return_a_list_of_ips(self): self.partialView.add_peer(PodDescriptor("172.0.1.5", 2)) self.partialView.add_peer(PodDescriptor("172.0.1.4", 3)) self.partialView.add_peer(PodDescriptor("172.0.1.10", 8)) limit = 3 sample = self.partialView.sample_ips(limit) self.assertIn("172.0.1.5", sample) self.assertIn("172.0.1.4", sample) self.assertIn("172.0.1.10", sample) # Method sample_ips should return a list of 3 ips loadable by epto # def test_sample_ips_should_return_a_list_of_ips_loadable_by_epto(self): # self.partialView.add_peer(PodDescriptor("172.0.1.5", 2)) # self.partialView.add_peer(PodDescriptor("172.0.1.4", 3)) # self.partialView.add_peer(PodDescriptor("172.0.1.10", 8)) # sample = json.dumps(self.partialView.sample_ips(2)) # # EpTO's code when EpTO invokes get_k_view() # view = [ip.encode('ascii', 'ignore') for ip in json.loads(sample)] # for destination in view: # self.assertIsInstance(destination, str) # self.assertIn(destination, self.partialView.get_peer_ip_list()) # Test the exchange of views. # P1 plays the role of P while P2 plays the role of Q described in comments def test_exchange_views(self): p1 = PartialView("First IP", 4, 3) p1.add_peer(PodDescriptor("172.0.1.6", 0)) p1.add_peer(PodDescriptor("172.0.1.3", 2)) p1.add_peer(PodDescriptor("172.0.1.5", 3)) p1.add_peer(PodDescriptor("Second IP", 5)) p2 = PartialView("Second IP", 4, 3) p2.add_peer(PodDescriptor("172.0.1.3", 0)) p2.add_peer(PodDescriptor("172.0.1.5", 1)) p2.add_peer(PodDescriptor("172.0.1.2", 2)) p2.add_peer(PodDescriptor("172.0.1.1", 4)) ######################## # P1 starts the exchange ######################## # 1) Increase by one the age of all neighbors p1.increment() # 2) Select neighbor Q with the highest age among all neighbors. oldest = p1.get_oldest_peer() # 3) Select l - 1 other random neighbors (meaning avoid oldest). request = p1.select_neighbors_for_request(oldest) # 4) Replace Q's entry with a new entry of age 0 and with P's address. request.add_peer_ip(p1.ip, allow_self_ip=True) self.assertTrue(request.is_full()) self.assertEqual(request.size, p1.shuffle_length) ################################################ # P2 receives neighbors and prepares a reply ################################################ reply = p2.select_neighbors_for_reply() self.assertTrue(request.is_full()) self.assertEqual(request.size, p1.shuffle_length) # Note that in p1 the oldest is p2 # p1 and p2 know two peers in common # p2 does not have an entry with p1's ip # p1.merge should: # - Discard 172.0.1.3 and 172.0.1.5 # - Put in unknown list 172.0.1.2, 172.0.1.1 # 6) I remove the oldest peer from my view p1.remove_peer(oldest) p1.merge(request, reply) self.assertTrue(p1.is_full()) for peer in reply.get_peer_list(): self.assertTrue(p1.contains(peer)) self.assertLessEqual(self.partialView.size, self.partialView.limit) # Test the exchange of views. # P1 plays the role of P while P2 plays the role of Q described in comments # def test_exchange_views_2(self): # # p1 = PartialView("First IP", 4, 3) # p1.add_peer(PodDescriptor("172.0.1.6", 0)) # p1.add_peer(PodDescriptor("172.0.1.3", 2)) # p1.add_peer(PodDescriptor("172.0.1.5", 3)) # p1.add_peer(PodDescriptor("Second IP", 5)) # # p2 = PartialView("Second IP", 4, 3) # p2.add_peer(PodDescriptor("172.0.1.3", 0)) # p2.add_peer(PodDescriptor("172.0.1.5", 1)) # p2.add_peer(PodDescriptor("172.0.1.2", 2)) # p2.add_peer(PodDescriptor("First IP", 4)) # # ######################## # # P1 starts the exchange # ######################## # # # 1) Increase by one the age of all neighbors # p1.increment() # # 2) Select neighbor Q with the highest age among all neighbors. # oldest = p1.get_oldest_peer() # # 3) Select l - 1 other random neighbors (meaning avoid oldest). # request = p1.select_neighbors_for_request(oldest) # # 4) Replace Q's entry with a new entry of age 0 and with P's address. # request.add_peer_ip(p1.ip, allow_self_ip=True) # # self.assertTrue(request.is_full()) # self.assertEqual(request.size, p1.shuffle_length) # # ################################################ # # P2 receives neighbors and prepares a reply # ################################################ # # reply = p2.select_neighbors_for_reply() # # self.assertTrue(request.is_full()) # self.assertEqual(request.size, p1.shuffle_length) # # # Note that in p1 the oldest is p2 # # p1 and p2 know two peers in common # # p2 does have an entry with p1's ip # # p1.merge should: # # - Discard 172.0.1.3 and 172.0.1.5 because are well known # # - Discard First IP because self ip is not allowed # # # 6) I remove the oldest peer from my view # p1.remove_peer(oldest) # p1.merge(request, reply) # # for peer in reply.get_peer_list(): # if peer != p1.ip: # self.assertTrue(p1.contains(peer)) # # self.assertLessEqual(self.partialView.size, self.partialView.limit) # Method get_oldest_peer should return a PodDescriptor def test_get_oldest_peer_should_return_none_if_empty_view(self): oldest = self.partialView.get_oldest_peer() self.assertEqual(oldest, None) # Method get_oldest_peer should return a PodDescriptor def test_get_oldest_peer_should_return_a_pod_descriptor(self): self.partialView.add_peer(PodDescriptor("172.0.1.6", 2)) self.partialView.add_peer(PodDescriptor("172.0.1.4", 1)) self.partialView.add_peer(PodDescriptor("172.0.1.5", 4)) oldest = self.partialView.get_oldest_peer() self.assertTrue(isinstance(oldest, PodDescriptor)) # Method get_oldest_peer should return the peer with the highest age def test_get_oldest_peer(self): self.partialView.add_peer(PodDescriptor("172.0.1.6", 2)) self.partialView.add_peer(PodDescriptor("172.0.1.4", 1)) self.partialView.add_peer(PodDescriptor("172.0.1.5", 4)) oldest = self.partialView.get_oldest_peer() self.assertEqual(oldest.ip, "172.0.1.5") self.assertEqual(oldest.age, 4) def test_select_neighbors_for_request_should_return_a_non_full_view(self): oldest = PodDescriptor("172.0.1.4", 1) self.partialView.add_peer(PodDescriptor("172.0.1.6", 2)) self.partialView.add_peer(oldest) self.partialView.add_peer(PodDescriptor("172.0.1.5", 4)) neighbors = self.partialView.select_neighbors_for_request(oldest) self.assertFalse(neighbors.is_full()) self.assertEqual(neighbors.size, neighbors.shuffle_length - 1) def test_select_neighbors_for_request_should_not_contain_oldest_peer(self): oldest = PodDescriptor("172.0.1.4", 1) self.partialView.add_peer(PodDescriptor("172.0.1.6", 2)) self.partialView.add_peer(oldest) self.partialView.add_peer(PodDescriptor("172.0.1.5", 4)) neighbors = self.partialView.select_neighbors_for_request(oldest) self.assertFalse(neighbors.contains(oldest)) def test_select_neighbors_for_request_and_add_peer_should_return_full_view(self): oldest = PodDescriptor("172.0.1.4", 1) self.partialView.add_peer(PodDescriptor("172.0.1.6", 2)) self.partialView.add_peer(oldest) self.partialView.add_peer(PodDescriptor("172.0.1.5", 4)) neighbors = self.partialView.select_neighbors_for_request(oldest) neighbors.add_peer_ip(self.partialView.ip, allow_self_ip=True) self.assertEqual(neighbors.size, self.partialView.shuffle_length) self.assertTrue(neighbors.is_full()) def test_select_neighbors_for_reply_should_return_a_full_view(self): oldest = PodDescriptor("172.0.1.4", 1) self.partialView.add_peer(PodDescriptor("172.0.1.6", 2)) self.partialView.add_peer(oldest) self.partialView.add_peer(PodDescriptor("172.0.1.5", 4)) neighbors = self.partialView.select_neighbors_for_reply(oldest) self.assertTrue(neighbors.is_full()) self.assertEqual(neighbors.size, neighbors.shuffle_length) def test_select_neighbors_for_reply_should_contain_avoid_peer_if_size_eq_shuffle_length(self): oldest = PodDescriptor("172.0.1.4", 1) self.partialView.add_peer(PodDescriptor("172.0.1.6", 2)) self.partialView.add_peer(oldest) neighbors = self.partialView.select_neighbors_for_reply(oldest) self.assertTrue(neighbors.is_full()) self.assertEqual(neighbors.size, neighbors.shuffle_length) def test_select_neighbors_for_reply_should_not_contain_oldest_peer(self): oldest = PodDescriptor("172.0.1.4", 1) self.partialView.add_peer(PodDescriptor("172.0.1.6", 2)) self.partialView.add_peer(oldest) self.partialView.add_peer(PodDescriptor("172.0.1.5", 4)) neighbors = self.partialView.select_neighbors_for_reply(oldest) self.assertFalse(neighbors.contains(oldest)) def test_empty_partial_view_to_json(self): jsonized = self.partialView.to_json() self.assertEqual(jsonized, {"ip": "172.0.1.0", "limit": 3, "shuffle_length": 2, "peer_list": [], "size": 0}) def test_unmarshal_partial_view(self): for ip in self.ips: self.partialView.add_peer_ip(ip) jsonized = self.partialView.to_json() partial_view = PartialView.from_dict(jsonized) self.assertIsInstance(partial_view, PartialView) for peer in partial_view.peer_list: self.assertIsInstance(peer, PodDescriptor) self.assertEqual(partial_view.ip, self.partialView.ip) self.assertEqual(partial_view.size, 3) self.assertEqual(partial_view.limit, 3) for i in range(self.partialView.limit): self.assertEqual(partial_view.peer_list[i].ip, self.descriptors[i].ip) self.assertEqual(partial_view.peer_list[i].age, self.descriptors[i].age) # Every time the view size is checked if it is equal to the actual size def tearDown(self): self.assertEqual(len(self.partialView.peer_list), self.partialView.size) if __name__ == '__main__': unittest.main()
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40940b4893d075c559e3320262f58f18fcc38d2f
242
py
Python
core/views.py
menezesluiz/Django_Framework
a23319167b4e9e11ea96f39a74727e1a38e0ce9f
[ "MIT" ]
null
null
null
core/views.py
menezesluiz/Django_Framework
a23319167b4e9e11ea96f39a74727e1a38e0ce9f
[ "MIT" ]
null
null
null
core/views.py
menezesluiz/Django_Framework
a23319167b4e9e11ea96f39a74727e1a38e0ce9f
[ "MIT" ]
null
null
null
from django.shortcuts import render def index(request): context = { 'curso': 'Programação Web com Django Framework' } return render(request, 'index.html') def contato(request): return render(request, 'contato.html')
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409ec6bfb8dab2359666ec8ce7e81fb33589dafd
161
py
Python
projects/Gruul/gruul/__init__.py
sm047/detectron2
1036cce320ce0f2adbce7f143566462d3222bd5a
[ "Apache-2.0" ]
5
2020-06-16T11:31:22.000Z
2021-11-08T03:07:47.000Z
projects/Gruul/gruul/__init__.py
fangchengji/detectron2
1036cce320ce0f2adbce7f143566462d3222bd5a
[ "Apache-2.0" ]
null
null
null
projects/Gruul/gruul/__init__.py
fangchengji/detectron2
1036cce320ce0f2adbce7f143566462d3222bd5a
[ "Apache-2.0" ]
null
null
null
#!/usr/bin/env python3 # @Time : 27/5/20 3:33 PM # @Author : fangcheng.ji # @FileName: __init__.py from .classification_network import ClassificationNetwork
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5
40b6f94e0e6eeefca3f101cdd081e7c9c3114b40
2,541
py
Python
DjangoAPI/MyApi/ImageProcessing_By_AWS.py
sni710/Django_api
a40d049586d9396c3b1bea4cd82177c573b24c17
[ "Apache-2.0" ]
2
2020-08-27T11:26:35.000Z
2021-03-20T16:27:20.000Z
DjangoAPI/MyApi/ImageProcessing_By_AWS.py
ankit98040/Django-ML-Project
3e50f51e56aa34bb8a7ae31f4955a10e57176ea7
[ "Apache-2.0" ]
null
null
null
DjangoAPI/MyApi/ImageProcessing_By_AWS.py
ankit98040/Django-ML-Project
3e50f51e56aa34bb8a7ae31f4955a10e57176ea7
[ "Apache-2.0" ]
null
null
null
import boto3 import requests import cv2 def ObjectDetection(imagePath, Service): session = boto3.Session(profile_name="default") Service = session.client("rekognition") image = open(imagePath, "rb").read() #read in byte imgH, imgW = cv2.imread(imagePath).shape[:2] MyImage = cv2.imread(imagePath) response = Service.detect_labels(Image = {"Bytes": image}) #response = Service.recognize_celebrities(Image={"Bytes": image}) for objects in response["Labels"]: if objects["Instances"]: for boxs in objects["Instances"]: objectName = objects["Name"] box = boxs["BoundingBox"] x = int(imgW * box["Left"]) y = int(imgH * box["Top"]) w = int(imgW * box["Width"]) h = int(imgH * box["Height"]) print(x,y,w,h) MyImage = cv2.rectangle(MyImage, (x,y), (x+w, y+h), (0,200,13), 2) MyImage = cv2.putText(MyImage, objectName, (x,y-20), cv2.FONT_HERSHEY_SIMPLEX, 0.9, [0,0,255], 2) while True: cv2.imshow("This is the image you selected", MyImage) if cv2.waitKey(1) == ord("q"): break #print(objects["Name"], "---", objects["Confidence"]) def Celebrities_Detection(imagePath, Service): session = boto3.Session(profile_name="default") Service = session.client("rekognition") image = open(imagePath, "rb").read() #read in byte imgH, imgW = cv2.imread(imagePath).shape[:2] MyImage = cv2.imread(imagePath) #response = Service.detect_labels(Image = {"Bytes": image}) response = Service.recognize_celebrities(Image={"Bytes": image}) for objects in response["CelebrityFaces"]: CelName = objects["Name"] Face = objects["Face"] objectName = objects["Name"] box = Face["BoundingBox"] x = int(imgW * box["Left"]) y = int(imgH * box["Top"]) w = int(imgW * box["Width"]) h = int(imgH * box["Height"]) print(x,y,w,h) MyImage = cv2.rectangle(MyImage, (x,y), (x+w, y+h), (0,200,13), 2) MyImage = cv2.putText(MyImage, CelName, (x,y), cv2.FONT_HERSHEY_SIMPLEX, 0.9, [0,0,255], 2) while True: cv2.imshow("This is the image you selected", MyImage) if cv2.waitKey(1) == ord("q"): break image = "/Users/ankit/Desktop/Projects/DJANGO/Django-ML-Project/DjangoAPI/MyApi/ima1.jpg" ObjectDetection(image, "Object Detection") Celebrities_Detection(image, "Object Detection")
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40c24dcd9a39e668e9455810445f2b4c4eb4133a
369
py
Python
backend/ecomm/comm_app/serializer.py
Aradhya-Tripathi/symmetrical-chainsaw
2e5f552b478c67ea34bd594b918620b3cf520881
[ "MIT" ]
null
null
null
backend/ecomm/comm_app/serializer.py
Aradhya-Tripathi/symmetrical-chainsaw
2e5f552b478c67ea34bd594b918620b3cf520881
[ "MIT" ]
12
2021-05-08T21:01:47.000Z
2021-05-14T23:07:03.000Z
backend/ecomm/comm_app/serializer.py
saxenabhishek/symmetrical-chainsaw
9b7f77b4d39867f410929d776d5b363518f71429
[ "MIT" ]
1
2021-06-01T21:00:13.000Z
2021-06-01T21:00:13.000Z
from rest_framework import serializers from django.contrib.auth.models import User class CreateUserSerializer(serializers.ModelSerializer): class Meta: model = User fields = ["username", "email", "password"] class AuthUserSerializer(serializers.ModelSerializer): class Meta: model = User fields = ["email", "password"]
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5
40cbe21ccd5453bf35ab6f553a773b46094496aa
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py
Python
free_style/tf_play/bench/test/load.py
yudongqiu/gomoku
4a95f2a5008f31fed5cb92c6bd6d55f9669ddd06
[ "MIT" ]
3
2018-06-12T09:03:41.000Z
2019-01-14T05:34:57.000Z
free_style/tf_play/bench/test/load.py
yudongqiu/gomoku
4a95f2a5008f31fed5cb92c6bd6d55f9669ddd06
[ "MIT" ]
null
null
null
free_style/tf_play/bench/test/load.py
yudongqiu/gomoku
4a95f2a5008f31fed5cb92c6bd6d55f9669ddd06
[ "MIT" ]
null
null
null
import tensorflow as tf import tflearn import random import numpy as np X = np.random.random([10,4,4,2]) Y = [[0] for x in X] g1 = tf.Graph() #with g1.as_default(): if True: input_layer = tflearn.input_data(shape=[None, 4, 4, 2]) net = tflearn.conv_2d(input_layer, 256, 3, activation=None) net = tflearn.batch_normalization(net) net = tflearn.activation(net, activation='relu') # block 2 tmp = tflearn.conv_2d(net, 256, 3, activation=None) tmp = tflearn.batch_normalization(tmp) tmp = tflearn.activation(tmp, activation='relu') tmp = tflearn.conv_2d(tmp, 256, 3, activation=None) tmp = tflearn.batch_normalization(tmp) net = tflearn.activation(net + tmp, activation='relu') final = tflearn.fully_connected(net, 1, activation='tanh') sgd = tflearn.optimizers.SGD(learning_rate=0.01, lr_decay=0.95, decay_step=200000) regression = tflearn.regression(final, optimizer=sgd, loss='mean_square', metric='R2') m = tflearn.DNN(regression) m.load('m1') # # # tf.reset_default_graph() # input_layer = tflearn.input_data(shape=[None, 4, 4, 2]) # net = tflearn.conv_2d(input_layer, 128, 3, activation=None) # net = tflearn.batch_normalization(net) # net = tflearn.activation(net, activation='relu') # # block 2 # tmp = tflearn.conv_2d(net, 128, 3, activation=None) # tmp = tflearn.batch_normalization(tmp) # net = tflearn.activation(net + tmp, activation='relu') # final = tflearn.fully_connected(net, 1, activation='tanh') # sgd = tflearn.optimizers.SGD(learning_rate=0.01, lr_decay=0.95, decay_step=200000) # regression = tflearn.regression(final, optimizer=sgd, loss='mean_square', metric='R2') # m2 = tflearn.DNN(regression) print(m.predict( X )) # # m2.load('test2') # print(m2.pridict(X))
34.411765
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0.704274
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1,755
4.696498
0.276265
0.06628
0.053853
0.076222
0.757249
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0.757249
0.757249
0.757249
0.714167
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0.049202
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1,755
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92
35.1
0.753324
0.404558
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0.030273
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0.166667
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0.041667
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5
40d541d5260375a555b2f6267cc6cb0899b4e4c4
126
py
Python
measurement/array-operations/vsquaresquare.py
quepas/performance-estimation-array-operations
b209ba5efebf5dee60ec5fca0fa711ca2e766e17
[ "MIT" ]
null
null
null
measurement/array-operations/vsquaresquare.py
quepas/performance-estimation-array-operations
b209ba5efebf5dee60ec5fca0fa711ca2e766e17
[ "MIT" ]
null
null
null
measurement/array-operations/vsquaresquare.py
quepas/performance-estimation-array-operations
b209ba5efebf5dee60ec5fca0fa711ca2e766e17
[ "MIT" ]
null
null
null
import numpy as np # Compute double element-wise square of vector def vsquaresquare(V): R = np.power(np.power(V, 2), 2)
18
46
0.698413
22
126
4
0.772727
0.159091
0
0
0
0
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0.019608
0.190476
126
6
47
21
0.843137
0.349206
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0.333333
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0
1
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0
5
905100c11b368587b755761b0305166ee0292372
8,019
py
Python
tests/integration/loading/test_loading_component.py
ohaibbq/dash-core-components
b7d1ebee327cf1b1938569a07cb5bf0dae4ecc54
[ "MIT" ]
1
2020-08-15T07:04:25.000Z
2020-08-15T07:04:25.000Z
tests/integration/loading/test_loading_component.py
ohaibbq/dash-core-components
b7d1ebee327cf1b1938569a07cb5bf0dae4ecc54
[ "MIT" ]
null
null
null
tests/integration/loading/test_loading_component.py
ohaibbq/dash-core-components
b7d1ebee327cf1b1938569a07cb5bf0dae4ecc54
[ "MIT" ]
null
null
null
from multiprocessing import Lock import dash from dash.dependencies import Input, Output import dash_core_components as dcc import dash_html_components as html def test_ldcp001_loading_component_initialization(dash_dcc): lock = Lock() app = dash.Dash(__name__) app.layout = html.Div( [dcc.Loading([html.Div(id="div-1")], className="loading")], id="root" ) @app.callback(Output("div-1", "children"), [Input("root", "n_clicks")]) def updateDiv(children): with lock: return "content" with lock: dash_dcc.start_server(app) dash_dcc.find_element(".loading .dash-spinner") # ensure inner component is also mounted dash_dcc.wait_for_text_to_equal("#div-1", "") dash_dcc.wait_for_text_to_equal("#div-1", "content") assert not dash_dcc.get_logs() def test_ldcp002_loading_component_action(dash_dcc): lock = Lock() app = dash.Dash(__name__) app.layout = html.Div( [dcc.Loading([html.Div(id="div-1")], className="loading")], id="root" ) @app.callback(Output("div-1", "children"), [Input("root", "n_clicks")]) def updateDiv(n_clicks): if n_clicks is not None: with lock: return "changed" return "content" with lock: dash_dcc.start_server(app) dash_dcc.wait_for_text_to_equal("#div-1", "content") dash_dcc.find_element("#root").click() dash_dcc.find_element(".loading .dash-spinner") # mounted but hidden, so looks like no text dash_dcc.wait_for_text_to_equal("#div-1", "") dash_dcc.wait_for_text_to_equal("#div-1", "changed") assert not dash_dcc.get_logs() def test_ldcp003_multiple_loading_components(dash_dcc): lock = Lock() app = dash.Dash(__name__) app.layout = html.Div( [ dcc.Loading([html.Button(id="btn-1")], className="loading-1"), dcc.Loading([html.Button(id="btn-2")], className="loading-2"), ], id="root", ) @app.callback(Output("btn-1", "children"), [Input("btn-2", "n_clicks")]) def updateDiv(n_clicks): if n_clicks is not None: with lock: return "changed 1" return "content 1" @app.callback(Output("btn-2", "children"), [Input("btn-1", "n_clicks")]) def updateDiv(n_clicks): if n_clicks is not None: with lock: return "changed 2" return "content 2" dash_dcc.start_server(app) dash_dcc.wait_for_text_to_equal("#btn-1", "content 1") dash_dcc.wait_for_text_to_equal("#btn-2", "content 2") with lock: dash_dcc.find_element("#btn-1").click() dash_dcc.find_element(".loading-2 .dash-spinner") dash_dcc.wait_for_text_to_equal("#btn-2", "") dash_dcc.wait_for_text_to_equal("#btn-2", "changed 2") with lock: dash_dcc.find_element("#btn-2").click() dash_dcc.find_element(".loading-1 .dash-spinner") dash_dcc.wait_for_text_to_equal("#btn-1", "") dash_dcc.wait_for_text_to_equal("#btn-1", "changed 1") assert not dash_dcc.get_logs() def test_ldcp004_nested_loading_components(dash_dcc): lock = Lock() app = dash.Dash(__name__) app.layout = html.Div( [ dcc.Loading( [ html.Button(id="btn-1"), dcc.Loading([html.Button(id="btn-2")], className="loading-2"), ], className="loading-1", ) ], id="root", ) @app.callback(Output("btn-1", "children"), [Input("btn-2", "n_clicks")]) def updateDiv(n_clicks): if n_clicks is not None: with lock: return "changed 1" return "content 1" @app.callback(Output("btn-2", "children"), [Input("btn-1", "n_clicks")]) def updateDiv(n_clicks): if n_clicks is not None: with lock: return "changed 2" return "content 2" dash_dcc.start_server(app) dash_dcc.wait_for_text_to_equal("#btn-1", "content 1") dash_dcc.wait_for_text_to_equal("#btn-2", "content 2") with lock: dash_dcc.find_element("#btn-1").click() dash_dcc.find_element(".loading-2 .dash-spinner") dash_dcc.wait_for_text_to_equal("#btn-2", "") dash_dcc.wait_for_text_to_equal("#btn-2", "changed 2") with lock: dash_dcc.find_element("#btn-2").click() dash_dcc.find_element(".loading-1 .dash-spinner") dash_dcc.wait_for_text_to_equal("#btn-1", "") dash_dcc.wait_for_text_to_equal("#btn-1", "changed 1") assert not dash_dcc.get_logs() def test_ldcp005_dynamic_loading_component(dash_dcc): lock = Lock() app = dash.Dash(__name__, suppress_callback_exceptions=True) app.layout = html.Div([html.Button(id="btn-1"), html.Div(id="div-1")]) @app.callback(Output("div-1", "children"), [Input("btn-1", "n_clicks")]) def updateDiv(n_clicks): if n_clicks is None: return with lock: return html.Div( [ html.Button(id="btn-2"), dcc.Loading([html.Button(id="btn-3")], className="loading-1"), ] ) @app.callback(Output("btn-3", "children"), [Input("btn-2", "n_clicks")]) def updateDynamic(n_clicks): if n_clicks is None: return "content" with lock: return "changed" dash_dcc.start_server(app) dash_dcc.find_element("#btn-1") dash_dcc.wait_for_text_to_equal("#div-1", "") dash_dcc.find_element("#btn-1").click() dash_dcc.find_element("#div-1 #btn-2") dash_dcc.wait_for_text_to_equal("#btn-3", "content") with lock: dash_dcc.find_element("#btn-2").click() dash_dcc.find_element(".loading-1 .dash-spinner") dash_dcc.wait_for_text_to_equal("#btn-3", "") dash_dcc.wait_for_text_to_equal("#btn-3", "changed") assert not dash_dcc.get_logs() def test_ldcp006_children_identity(dash_dcc): lock = Lock() app = dash.Dash(__name__) app.layout = html.Div( [ html.Button("click", id="btn"), dcc.Loading(dcc.Graph(id="graph"), className="loading"), ] ) @app.callback(Output("graph", "figure"), [Input("btn", "n_clicks")]) def update_graph(n): with lock: bars = list(range(2, (n or 0) + 5)) return { "data": [{"type": "bar", "x": bars, "y": bars}], "layout": {"width": 400, "height": 400}, } def get_graph_visibility(): return dash_dcc.driver.execute_script( "var gd_ = document.querySelector('.js-plotly-plot');" "return getComputedStyle(gd_).visibility;" ) with lock: dash_dcc.start_server(app) dash_dcc.find_element(".loading .dash-spinner") dash_dcc.find_element("#graph .js-plotly-plot") dash_dcc.driver.execute_script( "window.gd = document.querySelector('.js-plotly-plot');" "window.gd.__test__ = 'boo';" ) assert get_graph_visibility() == "hidden" test_identity = ( "var gd_ = document.querySelector('.js-plotly-plot');" "return gd_ === window.gd && gd_.__test__ === 'boo';" ) assert len(dash_dcc.find_elements(".js-plotly-plot .bars path")) == 3 assert dash_dcc.driver.execute_script(test_identity) assert get_graph_visibility() == "visible" with lock: dash_dcc.find_element("#btn").click() dash_dcc.find_element(".loading .dash-spinner") assert len(dash_dcc.find_elements(".js-plotly-plot .bars path")) == 3 assert dash_dcc.driver.execute_script(test_identity) assert get_graph_visibility() == "hidden" assert len(dash_dcc.find_elements(".js-plotly-plot .bars path")) == 4 assert dash_dcc.driver.execute_script(test_identity) assert get_graph_visibility() == "visible"
28.537367
82
0.599701
1,065
8,019
4.240376
0.110798
0.102303
0.056023
0.065102
0.809123
0.780115
0.752879
0.735828
0.676484
0.643933
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0.018288
0.249906
8,019
280
83
28.639286
0.732502
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0.020035
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false
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0.025253
0.005051
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5
905fb6d02acdb52f8e03d76c7891f3630034af6d
88
py
Python
code/default/python27/1.0/lib/noarch/front_base/host_manager.py
wuyongwen/XX-Net
313aefd862b8f230f7c61dc29db1b2b93a17e6ab
[ "BSD-2-Clause" ]
null
null
null
code/default/python27/1.0/lib/noarch/front_base/host_manager.py
wuyongwen/XX-Net
313aefd862b8f230f7c61dc29db1b2b93a17e6ab
[ "BSD-2-Clause" ]
null
null
null
code/default/python27/1.0/lib/noarch/front_base/host_manager.py
wuyongwen/XX-Net
313aefd862b8f230f7c61dc29db1b2b93a17e6ab
[ "BSD-2-Clause" ]
null
null
null
class HostManagerBase(object): def get_sni_host(self, ip): return "", ""
12.571429
31
0.602273
10
88
5.1
1
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0
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0.261364
88
6
32
14.666667
0.784615
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0.333333
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0
0
1
1
0
0
5
90983149a6e0eb9b57fd9a75d0a487b1fcd45c54
140
py
Python
client/asot_client/__init__.py
lun-4/asot
24d556af9695f7ac2f059bc7776fc59945a7ec0f
[ "BSD-3-Clause" ]
1
2021-08-01T21:20:52.000Z
2021-08-01T21:20:52.000Z
client/asot_client/__init__.py
lun-4/asot
24d556af9695f7ac2f059bc7776fc59945a7ec0f
[ "BSD-3-Clause" ]
null
null
null
client/asot_client/__init__.py
lun-4/asot
24d556af9695f7ac2f059bc7776fc59945a7ec0f
[ "BSD-3-Clause" ]
null
null
null
# asot: Localhost tunneling # Copyright 2021, Luna and asot contributors # SPDX-License-Identifier: BSD-3-Clause from .cli import main_cli
23.333333
44
0.785714
20
140
5.45
0.9
0
0
0
0
0
0
0
0
0
0
0.041322
0.135714
140
5
45
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0.859504
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0
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true
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0
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0
0
0
1
0
1
0
1
0
0
5
90caae54bed6781fd730bfab97ec5def8c409688
42,783
py
Python
vspk/v4_0/nulink.py
mohaimenhasan/vspk-python
4c7b297427048340b250cc3c74d9214dc0d4bde1
[ "BSD-3-Clause" ]
null
null
null
vspk/v4_0/nulink.py
mohaimenhasan/vspk-python
4c7b297427048340b250cc3c74d9214dc0d4bde1
[ "BSD-3-Clause" ]
null
null
null
vspk/v4_0/nulink.py
mohaimenhasan/vspk-python
4c7b297427048340b250cc3c74d9214dc0d4bde1
[ "BSD-3-Clause" ]
null
null
null
# -*- coding: utf-8 -*- # # Copyright (c) 2015, Alcatel-Lucent Inc, 2017 Nokia # All rights reserved. # # Redistribution and use in source and binary forms, with or without # modification, are permitted provided that the following conditions are met: # * Redistributions of source code must retain the above copyright # notice, this list of conditions and the following disclaimer. # * Redistributions in binary form must reproduce the above copyright # notice, this list of conditions and the following disclaimer in the # documentation and/or other materials provided with the distribution. # * Neither the name of the copyright holder nor the names of its contributors # may be used to endorse or promote products derived from this software without # specific prior written permission. # # THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND # ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED # WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE # DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY # DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES # (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; # LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND # ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT # (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS # SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. from .fetchers import NUDemarcationServicesFetcher from .fetchers import NUMetadatasFetcher from .fetchers import NUNextHopAddressFetcher from .fetchers import NUGlobalMetadatasFetcher from .fetchers import NUOverlayAddressPoolsFetcher from bambou import NURESTObject class NULink(NURESTObject): """ Represents a Link in the VSD Notes: This object represents the link between a source and destination domain in service chaining """ __rest_name__ = "link" __resource_name__ = "links" ## Constants CONST_ASSOCIATED_DESTINATION_TYPE_AVATAR = "AVATAR" CONST_ASSOCIATED_DESTINATION_TYPE_KEYSERVER_NOTIFICATION = "KEYSERVER_NOTIFICATION" CONST_ASSOCIATED_DESTINATION_TYPE_MONITORING_PORT = "MONITORING_PORT" CONST_ASSOCIATED_DESTINATION_TYPE_STATIC_ROUTE = "STATIC_ROUTE" CONST_ASSOCIATED_DESTINATION_TYPE_METADATA_TAG = "METADATA_TAG" CONST_ASSOCIATED_DESTINATION_TYPE_VCENTER_FETCH_DATACENTERS = "VCENTER_FETCH_DATACENTERS" CONST_ASSOCIATED_DESTINATION_TYPE_INGRESS_ACL_TEMPLATE_ENTRY = "INGRESS_ACL_TEMPLATE_ENTRY" CONST_ASSOCIATED_DESTINATION_TYPE_KEYSERVER_MONITOR = "KEYSERVER_MONITOR" CONST_ASSOCIATED_DESTINATION_TYPE_EVPN_BGP_COMMUNITY_TAG_SEQ_NO = "EVPN_BGP_COMMUNITY_TAG_SEQ_NO" CONST_ASSOCIATED_DESTINATION_TYPE_PERMITTED_ACTION = "PERMITTED_ACTION" CONST_ASSOCIATED_DESTINATION_TYPE_INGRESS_ACL_TEMPLATE = "INGRESS_ACL_TEMPLATE" CONST_ASSOCIATED_DESTINATION_TYPE_DOMAIN = "DOMAIN" CONST_ASSOCIATED_DESTINATION_TYPE_VPORT_GATEWAY_RESPONSE = "VPORT_GATEWAY_RESPONSE" CONST_ASSOCIATED_DESTINATION_TYPE_USER = "USER" CONST_ASSOCIATED_DESTINATION_TYPE_NSGATEWAY_CONFIG = "NSGATEWAY_CONFIG" CONST_ASSOCIATED_DESTINATION_TYPE_NEXT_HOP = "NEXT_HOP" CONST_ASSOCIATED_DESTINATION_TYPE_INGRESS_ACL_ENTRY = "INGRESS_ACL_ENTRY" CONST_ASSOCIATED_DESTINATION_TYPE_VPORT_MEDIATION_REQUEST = "VPORT_MEDIATION_REQUEST" CONST_ASSOCIATED_DESTINATION_TYPE_INGRESS_EXT_SERVICE = "INGRESS_EXT_SERVICE" CONST_ASSOCIATED_DESTINATION_TYPE_STATS_POLICY = "STATS_POLICY" CONST_ASSOCIATED_DESTINATION_TYPE_GATEWAY_CONFIG_RESP = "GATEWAY_CONFIG_RESP" CONST_ASSOCIATED_DESTINATION_TYPE_VSG_REDUNDANT_PORT = "VSG_REDUNDANT_PORT" CONST_ASSOCIATED_DESTINATION_TYPE_IP_BINDING = "IP_BINDING" CONST_ASSOCIATED_DESTINATION_TYPE_POLICY_GROUP = "POLICY_GROUP" CONST_ASSOCIATED_DESTINATION_TYPE_POLICING_POLICY = "POLICING_POLICY" CONST_ASSOCIATED_DESTINATION_TYPE_RTRD_SEQUENCENO = "RTRD_SEQUENCENO" CONST_ASSOCIATED_DESTINATION_TYPE_EVPN_BGP_COMMUNITY_TAG_ENTRY = "EVPN_BGP_COMMUNITY_TAG_ENTRY" CONST_ASSOCIATED_DESTINATION_TYPE_JOB = "JOB" CONST_ASSOCIATED_DESTINATION_TYPE_KEYSERVER_MONITOR_ENCRYPTED_SEED = "KEYSERVER_MONITOR_ENCRYPTED_SEED" CONST_ASSOCIATED_DESTINATION_TYPE_VMWARE_VCENTER_CLUSTER = "VMWARE_VCENTER_CLUSTER" CONST_ASSOCIATED_DESTINATION_TYPE_CONTAINER_INTERFACE = "CONTAINER_INTERFACE" CONST_ASSOCIATED_DESTINATION_TYPE_FLOATINGIP = "FLOATINGIP" CONST_ASSOCIATED_DESTINATION_TYPE_INGRESS_ADV_FWD = "INGRESS_ADV_FWD" CONST_ASSOCIATED_DESTINATION_TYPE_MULTI_NIC_VPORT = "MULTI_NIC_VPORT" CONST_ASSOCIATED_DESTINATION_TYPE_BACK_HAUL_SERVICE_RESP = "BACK_HAUL_SERVICE_RESP" CONST_ASSOCIATED_DESTINATION_TYPE_PORT_TEMPLATE = "PORT_TEMPLATE" CONST_ASSOCIATED_DESTINATION_TYPE_EGRESS_ACL = "EGRESS_ACL" CONST_ASSOCIATED_DESTINATION_TYPE_INFRASTRUCTURE_VSC_PROFILE = "INFRASTRUCTURE_VSC_PROFILE" CONST_ASSOCIATED_DESTINATION_TYPE_HEALTH_REQ = "HEALTH_REQ" CONST_ASSOCIATED_DESTINATION_TYPE_HOSTINTERFACE = "HOSTINTERFACE" CONST_ASSOCIATED_DESTINATION_TYPE_ROUTING_POL_MED_RESPONSE = "ROUTING_POL_MED_RESPONSE" CONST_ASSOCIATED_DESTINATION_TYPE_CHILD_ENTITY_POLICY_CHANGE = "CHILD_ENTITY_POLICY_CHANGE" CONST_ASSOCIATED_DESTINATION_TYPE_INGRESS_ACL = "INGRESS_ACL" CONST_ASSOCIATED_DESTINATION_TYPE_SHARED_RESOURCE = "SHARED_RESOURCE" CONST_ASSOCIATED_DESTINATION_TYPE_SITE_RES = "SITE_RES" CONST_ACCEPTANCE_CRITERIA_SUBNETS_ONLY = "SUBNETS_ONLY" CONST_ASSOCIATED_DESTINATION_TYPE_INGRESS_ADV_FWD_ENTRY = "INGRESS_ADV_FWD_ENTRY" CONST_ASSOCIATED_DESTINATION_TYPE_VM_RESYNC = "VM_RESYNC" CONST_ENTITY_SCOPE_GLOBAL = "GLOBAL" CONST_ASSOCIATED_DESTINATION_TYPE_STATIC_ROUTE_RESP = "STATIC_ROUTE_RESP" CONST_ASSOCIATED_DESTINATION_TYPE_EGRESS_QOS_MR = "EGRESS_QOS_MR" CONST_ASSOCIATED_DESTINATION_TYPE_IKE_GATEWAY_CONNECTION = "IKE_GATEWAY_CONNECTION" CONST_ASSOCIATED_DESTINATION_TYPE_CUSTOMER_VRF_SEQUENCENO = "CUSTOMER_VRF_SEQUENCENO" CONST_ASSOCIATED_DESTINATION_TYPE_PATNATPOOL = "PATNATPOOL" CONST_ASSOCIATED_DESTINATION_TYPE_PUBLIC_NETWORK = "PUBLIC_NETWORK" CONST_ASSOCIATED_DESTINATION_TYPE_VPORTTAG = "VPORTTAG" CONST_ASSOCIATED_DESTINATION_TYPE_NSPORT = "NSPORT" CONST_ASSOCIATED_DESTINATION_TYPE_NSGATEWAY = "NSGATEWAY" CONST_ASSOCIATED_DESTINATION_TYPE_REDUNDANT_GW_GRP = "REDUNDANT_GW_GRP" CONST_ASSOCIATED_DESTINATION_TYPE_IKE_PSK = "IKE_PSK" CONST_ASSOCIATED_DESTINATION_TYPE_GROUP = "GROUP" CONST_ASSOCIATED_DESTINATION_TYPE_APPD_FLOW_FORWARDING_POLICY = "APPD_FLOW_FORWARDING_POLICY" CONST_ASSOCIATED_DESTINATION_TYPE_DISKSTATS = "DISKSTATS" CONST_ASSOCIATED_DESTINATION_TYPE_GATEWAY_SERVICE_CONFIG_RESP = "GATEWAY_SERVICE_CONFIG_RESP" CONST_ASSOCIATED_DESTINATION_TYPE_NSGATEWAY_TEMPLATE = "NSGATEWAY_TEMPLATE" CONST_ASSOCIATED_DESTINATION_TYPE_GATEWAY_STATE = "GATEWAY_STATE" CONST_ASSOCIATED_DESTINATION_TYPE_INFRASTRUCTURE_GATEWAY_PROFILE = "INFRASTRUCTURE_GATEWAY_PROFILE" CONST_ASSOCIATED_DESTINATION_TYPE_APPD_FLOW = "APPD_FLOW" CONST_ASSOCIATED_DESTINATION_TYPE_SERVICE_GATEWAY_RESPONSE = "SERVICE_GATEWAY_RESPONSE" CONST_ASSOCIATED_DESTINATION_TYPE_UNSUPPORTED = "UNSUPPORTED" CONST_ASSOCIATED_DESTINATION_TYPE_GATEWAY_SECURITY = "GATEWAY_SECURITY" CONST_ASSOCIATED_DESTINATION_TYPE_NEXT_HOP_RESP = "NEXT_HOP_RESP" CONST_ASSOCIATED_DESTINATION_TYPE_SUBNET_TEMPLATE = "SUBNET_TEMPLATE" CONST_ASSOCIATED_DESTINATION_TYPE_ACLENTRY_LOCATION = "ACLENTRY_LOCATION" CONST_ASSOCIATED_DESTINATION_TYPE_ENTITY_METADATA_BINDING = "ENTITY_METADATA_BINDING" CONST_ASSOCIATED_DESTINATION_TYPE_IKE_GATEWAY_CONFIG = "IKE_GATEWAY_CONFIG" CONST_ASSOCIATED_DESTINATION_TYPE_VSP = "VSP" CONST_ASSOCIATED_DESTINATION_TYPE_ZFB_REQUEST = "ZFB_REQUEST" CONST_ASSOCIATED_DESTINATION_TYPE_VM_INTERFACE = "VM_INTERFACE" CONST_ASSOCIATED_DESTINATION_TYPE_INFRASTRUCTURE_PORT_PROFILE = "INFRASTRUCTURE_PORT_PROFILE" CONST_ASSOCIATED_DESTINATION_TYPE_PORT = "PORT" CONST_ASSOCIATED_DESTINATION_TYPE_KEYSERVER_MONITOR_SEED = "KEYSERVER_MONITOR_SEED" CONST_ASSOCIATED_DESTINATION_TYPE_QOS_PRIMITIVE = "QOS_PRIMITIVE" CONST_ASSOCIATED_DESTINATION_TYPE_SYSTEM_CONFIG = "SYSTEM_CONFIG" CONST_ASSOCIATED_DESTINATION_TYPE_FLOATINGIP_ACL_ENTRY = "FLOATINGIP_ACL_ENTRY" CONST_TYPE_HUB_AND_SPOKE = "HUB_AND_SPOKE" CONST_ASSOCIATED_DESTINATION_TYPE_MACRO_GROUP_MED = "MACRO_GROUP_MED" CONST_ASSOCIATED_DESTINATION_TYPE_NSG_NOTIFICATION = "NSG_NOTIFICATION" CONST_ASSOCIATED_DESTINATION_TYPE_LICENSE = "LICENSE" CONST_ASSOCIATED_DESTINATION_TYPE_PATMAPPER = "PATMAPPER" CONST_ASSOCIATED_DESTINATION_TYPE_KEYSERVER_MEMBER = "KEYSERVER_MEMBER" CONST_ASSOCIATED_DESTINATION_TYPE_VLAN_CONFIG_RESPONSE = "VLAN_CONFIG_RESPONSE" CONST_ASSOCIATED_DESTINATION_TYPE_GATEWAY_CONFIG = "GATEWAY_CONFIG" CONST_ASSOCIATED_DESTINATION_TYPE_VM_DESCRIPTION = "VM_DESCRIPTION" CONST_ASSOCIATED_DESTINATION_TYPE_SYSTEM_MONITORING = "SYSTEM_MONITORING" CONST_ASSOCIATED_DESTINATION_TYPE_IKE_ENCRYPTION_PROFILE_REQUEST = "IKE_ENCRYPTION_PROFILE_REQUEST" CONST_ASSOCIATED_DESTINATION_TYPE_LINK = "LINK" CONST_ASSOCIATED_DESTINATION_TYPE_EXPORTIMPORT = "EXPORTIMPORT" CONST_ASSOCIATED_DESTINATION_TYPE_GATEWAY_VPORT_CONFIG = "GATEWAY_VPORT_CONFIG" CONST_ASSOCIATED_DESTINATION_TYPE_POLICY_GROUP_TEMPLATE = "POLICY_GROUP_TEMPLATE" CONST_ASSOCIATED_DESTINATION_TYPE_RATE_LIMITER = "RATE_LIMITER" CONST_ASSOCIATED_DESTINATION_TYPE_PORT_VLAN_CONFIG_RESPONSE = "PORT_VLAN_CONFIG_RESPONSE" CONST_ASSOCIATED_DESTINATION_TYPE_VMWARE_VCENTER_VRS_CONFIG = "VMWARE_VCENTER_VRS_CONFIG" CONST_ASSOCIATED_DESTINATION_TYPE_CONTAINER = "CONTAINER" CONST_ASSOCIATED_DESTINATION_TYPE_SUBNET = "SUBNET" CONST_ASSOCIATED_DESTINATION_TYPE_PERMISSION = "PERMISSION" CONST_ASSOCIATED_DESTINATION_TYPE_VIRTUAL_IP = "VIRTUAL_IP" CONST_ASSOCIATED_DESTINATION_TYPE_NSG_INFO = "NSG_INFO" CONST_ASSOCIATED_DESTINATION_TYPE_BOOTSTRAP_ACTIVATION = "BOOTSTRAP_ACTIVATION" CONST_ASSOCIATED_DESTINATION_TYPE_GATEWAY_VPORT_CONFIG_RESP = "GATEWAY_VPORT_CONFIG_RESP" CONST_ASSOCIATED_DESTINATION_TYPE_FLOATINGIP_ACL = "FLOATINGIP_ACL" CONST_ASSOCIATED_DESTINATION_TYPE_ZFB_AUTO_ASSIGNMENT = "ZFB_AUTO_ASSIGNMENT" CONST_ASSOCIATED_DESTINATION_TYPE_ZONE = "ZONE" CONST_ASSOCIATED_DESTINATION_TYPE_INFRASTRUCTURE_CONFIG = "INFRASTRUCTURE_CONFIG" CONST_ASSOCIATED_DESTINATION_TYPE_VMWARE_VCENTER_EAM_CONFIG = "VMWARE_VCENTER_EAM_CONFIG" CONST_ASSOCIATED_DESTINATION_TYPE_POLICY_DECISION = "POLICY_DECISION" CONST_ASSOCIATED_DESTINATION_TYPE_SERVICES_GATEWAY_RESPONSE = "SERVICES_GATEWAY_RESPONSE" CONST_ASSOCIATED_DESTINATION_TYPE_VLAN = "VLAN" CONST_ASSOCIATED_DESTINATION_TYPE_VMWARE_REMOVE_CLUSTER_INSCOPE = "VMWARE_REMOVE_CLUSTER_INSCOPE" CONST_ASSOCIATED_DESTINATION_TYPE_ADDRESS_RANGE_STATE = "ADDRESS_RANGE_STATE" CONST_ASSOCIATED_DESTINATION_TYPE_SYSTEM_CONFIG_REQ = "SYSTEM_CONFIG_REQ" CONST_ASSOCIATED_DESTINATION_TYPE_SUBNET_ENTRY = "SUBNET_ENTRY" CONST_ASSOCIATED_DESTINATION_TYPE_VCENTER_FETCH_CLUSTERS = "VCENTER_FETCH_CLUSTERS" CONST_ASSOCIATED_DESTINATION_TYPE_LIBVIRT_INTERFACE = "LIBVIRT_INTERFACE" CONST_ASSOCIATED_DESTINATION_TYPE_GATEWAY_SECURED_DATA = "GATEWAY_SECURED_DATA" CONST_ASSOCIATED_DESTINATION_TYPE_BGP_NEIGHBOR = "BGP_NEIGHBOR" CONST_ASSOCIATED_DESTINATION_TYPE_VMWARE_VCENTER_DATACENTER = "VMWARE_VCENTER_DATACENTER" CONST_ASSOCIATED_DESTINATION_TYPE_FETCH_HYPERVISOR_PROPERTIES = "FETCH_HYPERVISOR_PROPERTIES" CONST_TYPE_OVERLAY_ADDRESS_TRANSLATION = "OVERLAY_ADDRESS_TRANSLATION" CONST_ASSOCIATED_DESTINATION_TYPE_EGRESS_QOS_PRIMITIVE = "EGRESS_QOS_PRIMITIVE" CONST_ASSOCIATED_DESTINATION_TYPE_ESI_SEQUENCENO = "ESI_SEQUENCENO" CONST_ASSOCIATED_DESTINATION_TYPE_INGRESS_ADV_FWD_TEMPLATE = "INGRESS_ADV_FWD_TEMPLATE" CONST_ASSOCIATED_DESTINATION_TYPE_IKE_GATEWAY_PROFILE = "IKE_GATEWAY_PROFILE" CONST_ASSOCIATED_DESTINATION_TYPE_IKE_CERTIFICATE = "IKE_CERTIFICATE" CONST_ASSOCIATED_DESTINATION_TYPE_VMWARE_VRS_REDEPLOYMENT_POLICY = "VMWARE_VRS_REDEPLOYMENT_POLICY" CONST_ASSOCIATED_DESTINATION_TYPE_INGRESS_EXT_SERVICE_TEMPLATE_ENTRY = "INGRESS_EXT_SERVICE_TEMPLATE_ENTRY" CONST_ASSOCIATED_DESTINATION_TYPE_BGP_NEIGHBOR_MED_RESPONSE = "BGP_NEIGHBOR_MED_RESPONSE" CONST_ASSOCIATED_DESTINATION_TYPE_NSPORT_STATIC_CONFIG = "NSPORT_STATIC_CONFIG" CONST_ASSOCIATED_DESTINATION_TYPE_BGP_PROFILE = "BGP_PROFILE" CONST_ASSOCIATED_DESTINATION_TYPE_ENTERPRISE_SECURED_DATA = "ENTERPRISE_SECURED_DATA" CONST_ENTITY_SCOPE_ENTERPRISE = "ENTERPRISE" CONST_ASSOCIATED_DESTINATION_TYPE_L2DOMAIN_TEMPLATE = "L2DOMAIN_TEMPLATE" CONST_ASSOCIATED_DESTINATION_TYPE_APPD_TIER = "APPD_TIER" CONST_ASSOCIATED_DESTINATION_TYPE_GEO_VM_EVENT = "GEO_VM_EVENT" CONST_ASSOCIATED_DESTINATION_TYPE_ENTERPRISE_SECURITY = "ENTERPRISE_SECURITY" CONST_ASSOCIATED_DESTINATION_TYPE_DSCP_FORWARDING_CLASS_TABLE = "DSCP_FORWARDING_CLASS_TABLE" CONST_ASSOCIATED_DESTINATION_TYPE_GATEWAY_TEMPLATE = "GATEWAY_TEMPLATE" CONST_ASSOCIATED_DESTINATION_TYPE_VRS = "VRS" CONST_ASSOCIATED_DESTINATION_TYPE_EGRESS_ACL_ENTRY = "EGRESS_ACL_ENTRY" CONST_ASSOCIATED_DESTINATION_TYPE_VPORT = "VPORT" CONST_ASSOCIATED_DESTINATION_TYPE_GROUPKEY_ENCRYPTION_PROFILE = "GROUPKEY_ENCRYPTION_PROFILE" CONST_ASSOCIATED_DESTINATION_TYPE_APPD_APPLICATION = "APPD_APPLICATION" CONST_ASSOCIATED_DESTINATION_TYPE_IKE_ENCRYPTION_PROFILE = "IKE_ENCRYPTION_PROFILE" CONST_ASSOCIATED_DESTINATION_TYPE_RTRD_ENTITY = "RTRD_ENTITY" CONST_ASSOCIATED_DESTINATION_TYPE_ZFB_GLOBAL = "ZFB_GLOBAL" CONST_ASSOCIATED_DESTINATION_TYPE_RD_SEQUENCENO = "RD_SEQUENCENO" CONST_ASSOCIATED_DESTINATION_TYPE_GATEWAY = "GATEWAY" CONST_ASSOCIATED_DESTINATION_TYPE_DOMAIN_FLOATING_IP_ACL_TEMPLATE = "DOMAIN_FLOATING_IP_ACL_TEMPLATE" CONST_ASSOCIATED_DESTINATION_TYPE_VMWARE_ADD_CLUSTER_INSCOPE = "VMWARE_ADD_CLUSTER_INSCOPE" CONST_ASSOCIATED_DESTINATION_TYPE_VPORTTAGTEMPLATE = "VPORTTAGTEMPLATE" CONST_ASSOCIATED_DESTINATION_TYPE_SITE = "SITE" CONST_ASSOCIATED_DESTINATION_TYPE_GATEWAY_SECURITY_RESPONSE = "GATEWAY_SECURITY_RESPONSE" CONST_ASSOCIATED_DESTINATION_TYPE_WAN_SERVICE = "WAN_SERVICE" CONST_ASSOCIATED_DESTINATION_TYPE_GATEWAY_SECURITY_REQUEST = "GATEWAY_SECURITY_REQUEST" CONST_ASSOCIATED_DESTINATION_TYPE_FLOATING_IP_ACL_TEMPLATE = "FLOATING_IP_ACL_TEMPLATE" CONST_ASSOCIATED_DESTINATION_TYPE_APPD_FLOW_SECURITY_POLICY = "APPD_FLOW_SECURITY_POLICY" CONST_TYPE_SERVICE_CHAINING = "SERVICE_CHAINING" CONST_ASSOCIATED_DESTINATION_TYPE_BGPPEER = "BGPPEER" CONST_ASSOCIATED_DESTINATION_TYPE_NSPORT_VLAN_CONFIG = "NSPORT_VLAN_CONFIG" CONST_ASSOCIATED_DESTINATION_TYPE_SYSTEM_CONFIG_RESP = "SYSTEM_CONFIG_RESP" CONST_ASSOCIATED_DESTINATION_TYPE_IKE_SUBNET = "IKE_SUBNET" CONST_ASSOCIATED_DESTINATION_TYPE_LDAP_CONFIG = "LDAP_CONFIG" CONST_ASSOCIATED_DESTINATION_TYPE_VPORT_TAG_BASE = "VPORT_TAG_BASE" CONST_ASSOCIATED_DESTINATION_TYPE_MC_LIST = "MC_LIST" CONST_ASSOCIATED_DESTINATION_TYPE_ENTERPRISE_CONFIG = "ENTERPRISE_CONFIG" CONST_ASSOCIATED_DESTINATION_TYPE_DOMAIN_CONFIG_RESP = "DOMAIN_CONFIG_RESP" CONST_ASSOCIATED_DESTINATION_TYPE_NODE_EXECUTION_ERROR = "NODE_EXECUTION_ERROR" CONST_ASSOCIATED_DESTINATION_TYPE_STATSSERVER = "STATSSERVER" CONST_ASSOCIATED_DESTINATION_TYPE_ALARM = "ALARM" CONST_ASSOCIATED_DESTINATION_TYPE_NETWORK_LAYOUT = "NETWORK_LAYOUT" CONST_ASSOCIATED_DESTINATION_TYPE_EVENT_LOG = "EVENT_LOG" CONST_ASSOCIATED_DESTINATION_TYPE_APPLICATION = "APPLICATION" CONST_ASSOCIATED_DESTINATION_TYPE_NETWORK_ELEMENT = "NETWORK_ELEMENT" CONST_ASSOCIATED_DESTINATION_TYPE_VSD_COMPONENT = "VSD_COMPONENT" CONST_ASSOCIATED_DESTINATION_TYPE_ZONE_TEMPLATE = "ZONE_TEMPLATE" CONST_ASSOCIATED_DESTINATION_TYPE_APPD_SERVICE = "APPD_SERVICE" CONST_ASSOCIATED_DESTINATION_TYPE_DSCP_FORWARDING_CLASS_MAPPING = "DSCP_FORWARDING_CLASS_MAPPING" CONST_ASSOCIATED_DESTINATION_TYPE_PAT_IP_ENTRY = "PAT_IP_ENTRY" CONST_ASSOCIATED_DESTINATION_TYPE_METADATA = "METADATA" CONST_ASSOCIATED_DESTINATION_TYPE_DHCP_ALLOC_MESSAGE = "DHCP_ALLOC_MESSAGE" CONST_ASSOCIATED_DESTINATION_TYPE_EGRESS_ACL_TEMPLATE = "EGRESS_ACL_TEMPLATE" CONST_ASSOCIATED_DESTINATION_TYPE_AUTO_DISC_GATEWAY = "AUTO_DISC_GATEWAY" CONST_ASSOCIATED_DESTINATION_TYPE_GEO_VM_REQ = "GEO_VM_REQ" CONST_ASSOCIATED_DESTINATION_TYPE_GEO_VM_RES = "GEO_VM_RES" CONST_ASSOCIATED_DESTINATION_TYPE_PORT_PUSH = "PORT_PUSH" CONST_ASSOCIATED_DESTINATION_TYPE_VIRTUAL_MACHINE = "VIRTUAL_MACHINE" CONST_ASSOCIATED_DESTINATION_TYPE_CONTAINER_RESYNC = "CONTAINER_RESYNC" CONST_ASSOCIATED_DESTINATION_TYPE_BGP_PROFILE_MED_RESPONSE = "BGP_PROFILE_MED_RESPONSE" CONST_ASSOCIATED_DESTINATION_TYPE_EAM_VRS_METRICS = "EAM_VRS_METRICS" CONST_ASSOCIATED_DESTINATION_TYPE_VNID_SEQUENCENO = "VNID_SEQUENCENO" CONST_ASSOCIATED_DESTINATION_TYPE_DHCP_OPTION = "DHCP_OPTION" CONST_ASSOCIATED_DESTINATION_TYPE_PORT_RANGE_MED = "PORT_RANGE_MED" CONST_ASSOCIATED_DESTINATION_TYPE_NSREDUNDANT_GW_GRP = "NSREDUNDANT_GW_GRP" CONST_ASSOCIATED_DESTINATION_TYPE_ROUTING_POLICY = "ROUTING_POLICY" CONST_ASSOCIATED_DESTINATION_TYPE_CERTIFICATE = "CERTIFICATE" CONST_ASSOCIATED_DESTINATION_TYPE_GATEWAY_SECURITY_PROFILE_REQUEST = "GATEWAY_SECURITY_PROFILE_REQUEST" CONST_ASSOCIATED_DESTINATION_TYPE_STATISTICS = "STATISTICS" CONST_ASSOCIATED_DESTINATION_TYPE_INGRESS_ADV_FWD_TEMPLATE_ENTRY = "INGRESS_ADV_FWD_TEMPLATE_ENTRY" CONST_ASSOCIATED_DESTINATION_TYPE_ENDPOINT = "ENDPOINT" CONST_ASSOCIATED_DESTINATION_TYPE_ENTERPRISE_PERMISSION = "ENTERPRISE_PERMISSION" CONST_ASSOCIATED_DESTINATION_TYPE_LINKED_DOMAIN_RESP = "LINKED_DOMAIN_RESP" CONST_ASSOCIATED_DESTINATION_TYPE_PORTMAPPING = "PORTMAPPING" CONST_ASSOCIATED_DESTINATION_TYPE_ENTERPRISE = "ENTERPRISE" CONST_ASSOCIATED_DESTINATION_TYPE_VPORT_MIRROR = "VPORT_MIRROR" CONST_ASSOCIATED_DESTINATION_TYPE_NSPORT_TEMPLATE = "NSPORT_TEMPLATE" CONST_ASSOCIATED_DESTINATION_TYPE_HSC = "HSC" CONST_ASSOCIATED_DESTINATION_TYPE_MIRROR_DESTINATION = "MIRROR_DESTINATION" CONST_ASSOCIATED_DESTINATION_TYPE_DC_CONFIG = "DC_CONFIG" CONST_ASSOCIATED_DESTINATION_TYPE_BOOTSTRAP = "BOOTSTRAP" CONST_TYPE_BORDER_ROUTER = "BORDER_ROUTER" CONST_ASSOCIATED_DESTINATION_TYPE_NETWORK_POLICY_GROUP = "NETWORK_POLICY_GROUP" CONST_ASSOCIATED_DESTINATION_TYPE_VPRN_LABEL_SEQUENCENO = "VPRN_LABEL_SEQUENCENO" CONST_ASSOCIATED_DESTINATION_TYPE_VPN_CONNECT = "VPN_CONNECT" CONST_ASSOCIATED_DESTINATION_TYPE_UPLINK_RD = "UPLINK_RD" CONST_ASSOCIATED_DESTINATION_TYPE_VLAN_TEMPLATE = "VLAN_TEMPLATE" CONST_ASSOCIATED_DESTINATION_TYPE_PORT_MR = "PORT_MR" CONST_ASSOCIATED_DESTINATION_TYPE_PATCONFIG_CONFIG_RESP = "PATCONFIG_CONFIG_RESP" CONST_ASSOCIATED_DESTINATION_TYPE_NETWORK_MACRO_GROUP = "NETWORK_MACRO_GROUP" CONST_ASSOCIATED_DESTINATION_TYPE_VMWARE_RELOAD_CONFIG = "VMWARE_RELOAD_CONFIG" CONST_ASSOCIATED_DESTINATION_TYPE_MC_RANGE = "MC_RANGE" CONST_ASSOCIATED_DESTINATION_TYPE_INGRESS_EXT_SERVICE_ENTRY = "INGRESS_EXT_SERVICE_ENTRY" CONST_ASSOCIATED_DESTINATION_TYPE_DOMAIN_FLOATING_IP_ACL_TEMPLATE_ENTRY = "DOMAIN_FLOATING_IP_ACL_TEMPLATE_ENTRY" CONST_ASSOCIATED_DESTINATION_TYPE_FLOATING_IP_ACL_TEMPLATE_ENTRY = "FLOATING_IP_ACL_TEMPLATE_ENTRY" CONST_ASSOCIATED_DESTINATION_TYPE_APPD_EXTERNAL_APP_SERVICE = "APPD_EXTERNAL_APP_SERVICE" CONST_ACCEPTANCE_CRITERIA_ALL = "ALL" CONST_ASSOCIATED_DESTINATION_TYPE_GATEWAY_SERVICE_CONFIG = "GATEWAY_SERVICE_CONFIG" CONST_ASSOCIATED_DESTINATION_TYPE_STATS_COLLECTOR = "STATS_COLLECTOR" CONST_ASSOCIATED_DESTINATION_TYPE_L2DOMAIN_SHARED = "L2DOMAIN_SHARED" CONST_ASSOCIATED_DESTINATION_TYPE_DOMAIN_CONFIG = "DOMAIN_CONFIG" CONST_ASSOCIATED_DESTINATION_TYPE_PORT_VLAN_CONFIG = "PORT_VLAN_CONFIG" CONST_ASSOCIATED_DESTINATION_TYPE_ADDRESS_RANGE = "ADDRESS_RANGE" CONST_ASSOCIATED_DESTINATION_TYPE_BGP_DAMPENING_MED_RESPONSE = "BGP_DAMPENING_MED_RESPONSE" CONST_ASSOCIATED_DESTINATION_TYPE_INGRESS_EXT_SERVICE_TEMPLATE = "INGRESS_EXT_SERVICE_TEMPLATE" CONST_ASSOCIATED_DESTINATION_TYPE_LOCATION = "LOCATION" CONST_ASSOCIATED_DESTINATION_TYPE_SITE_REQ = "SITE_REQ" CONST_ASSOCIATED_DESTINATION_TYPE_STATS_TCA = "STATS_TCA" CONST_ASSOCIATED_DESTINATION_TYPE_CONTAINER_DESCRIPTION = "CONTAINER_DESCRIPTION" CONST_ASSOCIATED_DESTINATION_TYPE_SUBNET_MAC_ENTRY = "SUBNET_MAC_ENTRY" CONST_ASSOCIATED_DESTINATION_TYPE_EGRESS_QOS_QUEUE_MR = "EGRESS_QOS_QUEUE_MR" CONST_ASSOCIATED_DESTINATION_TYPE_NS_REDUNDANT_PORT = "NS_REDUNDANT_PORT" CONST_ASSOCIATED_DESTINATION_TYPE_SERVICE_VRF_SEQUENCENO = "SERVICE_VRF_SEQUENCENO" CONST_ASSOCIATED_DESTINATION_TYPE_ZFB_AUTO_ASSIGNMENT_VALUE = "ZFB_AUTO_ASSIGNMENT_VALUE" CONST_ASSOCIATED_DESTINATION_TYPE_NATMAPENTRY = "NATMAPENTRY" CONST_ASSOCIATED_DESTINATION_TYPE_LICENSE_STATUS = "LICENSE_STATUS" CONST_ASSOCIATED_DESTINATION_TYPE_DHCP_CONFIG_RESP = "DHCP_CONFIG_RESP" CONST_ASSOCIATED_DESTINATION_TYPE_VMWARE_VCENTER = "VMWARE_VCENTER" CONST_ASSOCIATED_DESTINATION_TYPE_VMWARE_VCENTER_HYPERVISOR = "VMWARE_VCENTER_HYPERVISOR" CONST_ASSOCIATED_DESTINATION_TYPE_VSD = "VSD" CONST_ASSOCIATED_DESTINATION_TYPE_SHAPING_POLICY = "SHAPING_POLICY" CONST_ASSOCIATED_DESTINATION_TYPE_BRIDGEINTERFACE = "BRIDGEINTERFACE" CONST_ASSOCIATED_DESTINATION_TYPE_VSC = "VSC" CONST_ASSOCIATED_DESTINATION_TYPE_ENTERPRISE_NETWORK = "ENTERPRISE_NETWORK" CONST_ASSOCIATED_DESTINATION_TYPE_ENTERPRISE_PROFILE = "ENTERPRISE_PROFILE" CONST_ASSOCIATED_DESTINATION_TYPE_BULKSTATISTICS = "BULKSTATISTICS" CONST_ASSOCIATED_DESTINATION_TYPE_EXTERNAL_SERVICE = "EXTERNAL_SERVICE" CONST_ASSOCIATED_DESTINATION_TYPE_KEYSERVER_MONITOR_SEK = "KEYSERVER_MONITOR_SEK" CONST_ASSOCIATED_DESTINATION_TYPE_SUBNET_POOL_ENTRY = "SUBNET_POOL_ENTRY" CONST_ASSOCIATED_DESTINATION_TYPE_IKE_GATEWAY_CONNECTION_REQUEST = "IKE_GATEWAY_CONNECTION_REQUEST" CONST_ASSOCIATED_DESTINATION_TYPE_CLOUD_MGMT_SYSTEM = "CLOUD_MGMT_SYSTEM" CONST_ASSOCIATED_DESTINATION_TYPE_GATEWAY_SECURITY_PROFILE_RESPONSE = "GATEWAY_SECURITY_PROFILE_RESPONSE" CONST_ASSOCIATED_DESTINATION_TYPE_IKE_GATEWAY = "IKE_GATEWAY" CONST_ASSOCIATED_DESTINATION_TYPE_VIRTUAL_MACHINE_REPORT = "VIRTUAL_MACHINE_REPORT" CONST_ASSOCIATED_DESTINATION_TYPE_ENTERPRISE_CONFIG_RESP = "ENTERPRISE_CONFIG_RESP" CONST_ASSOCIATED_DESTINATION_TYPE_DOMAIN_TEMPLATE = "DOMAIN_TEMPLATE" CONST_ASSOCIATED_DESTINATION_TYPE_MC_CHANNEL_MAP = "MC_CHANNEL_MAP" CONST_ASSOCIATED_DESTINATION_TYPE_VMWARE_VRS_ADDRESS_RANGE = "VMWARE_VRS_ADDRESS_RANGE" CONST_ASSOCIATED_DESTINATION_TYPE_VMWARE_VCENTER_VRS_BASE_CONFIG = "VMWARE_VCENTER_VRS_BASE_CONFIG" CONST_ASSOCIATED_DESTINATION_TYPE_EGRESS_ACL_TEMPLATE_ENTRY = "EGRESS_ACL_TEMPLATE_ENTRY" CONST_ASSOCIATED_DESTINATION_TYPE_L2DOMAIN = "L2DOMAIN" def __init__(self, **kwargs): """ Initializes a Link instance Notes: You can specify all parameters while calling this methods. A special argument named `data` will enable you to load the object from a Python dictionary Examples: >>> link = NULink(id=u'xxxx-xxx-xxx-xxx', name=u'Link') >>> link = NULink(data=my_dict) """ super(NULink, self).__init__() # Read/Write Attributes self._last_updated_by = None self._acceptance_criteria = None self._read_only = None self._entity_scope = None self._associated_destination_id = None self._associated_destination_name = None self._associated_destination_type = None self._associated_source_id = None self._associated_source_name = None self._associated_source_type = None self._external_id = None self._type = None self.expose_attribute(local_name="last_updated_by", remote_name="lastUpdatedBy", attribute_type=str, is_required=False, is_unique=False) self.expose_attribute(local_name="acceptance_criteria", remote_name="acceptanceCriteria", attribute_type=str, is_required=False, is_unique=False, choices=[u'ALL', u'SUBNETS_ONLY']) self.expose_attribute(local_name="read_only", remote_name="readOnly", attribute_type=bool, is_required=False, is_unique=False) self.expose_attribute(local_name="entity_scope", remote_name="entityScope", attribute_type=str, is_required=False, is_unique=False, choices=[u'ENTERPRISE', u'GLOBAL']) self.expose_attribute(local_name="associated_destination_id", remote_name="associatedDestinationID", attribute_type=str, is_required=False, is_unique=False) self.expose_attribute(local_name="associated_destination_name", remote_name="associatedDestinationName", attribute_type=str, is_required=False, is_unique=False) self.expose_attribute(local_name="associated_destination_type", remote_name="associatedDestinationType", attribute_type=str, is_required=False, is_unique=False, choices=[u'ACLENTRY_LOCATION', u'ADDRESS_RANGE', u'ADDRESS_RANGE_STATE', u'ALARM', u'APPD_APPLICATION', u'APPD_EXTERNAL_APP_SERVICE', u'APPD_FLOW', u'APPD_FLOW_FORWARDING_POLICY', u'APPD_FLOW_SECURITY_POLICY', u'APPD_SERVICE', u'APPD_TIER', u'APPLICATION', u'AUTO_DISC_GATEWAY', u'AVATAR', u'BACK_HAUL_SERVICE_RESP', u'BGP_DAMPENING_MED_RESPONSE', u'BGP_NEIGHBOR', u'BGP_NEIGHBOR_MED_RESPONSE', u'BGP_PROFILE', u'BGP_PROFILE_MED_RESPONSE', u'BGPPEER', u'BOOTSTRAP', u'BOOTSTRAP_ACTIVATION', u'BRIDGEINTERFACE', u'BULKSTATISTICS', u'CERTIFICATE', u'CHILD_ENTITY_POLICY_CHANGE', u'CLOUD_MGMT_SYSTEM', u'CONTAINER', u'CONTAINER_DESCRIPTION', u'CONTAINER_INTERFACE', u'CONTAINER_RESYNC', u'CUSTOMER_VRF_SEQUENCENO', u'DC_CONFIG', u'DHCP_ALLOC_MESSAGE', u'DHCP_CONFIG_RESP', u'DHCP_OPTION', u'DISKSTATS', u'DOMAIN', u'DOMAIN_CONFIG', u'DOMAIN_CONFIG_RESP', u'DOMAIN_FLOATING_IP_ACL_TEMPLATE', u'DOMAIN_FLOATING_IP_ACL_TEMPLATE_ENTRY', u'DOMAIN_TEMPLATE', u'DSCP_FORWARDING_CLASS_MAPPING', u'DSCP_FORWARDING_CLASS_TABLE', u'EAM_VRS_METRICS', u'EGRESS_ACL', u'EGRESS_ACL_ENTRY', u'EGRESS_ACL_TEMPLATE', u'EGRESS_ACL_TEMPLATE_ENTRY', u'EGRESS_QOS_MR', u'EGRESS_QOS_PRIMITIVE', u'EGRESS_QOS_QUEUE_MR', u'ENDPOINT', u'ENTERPRISE', u'ENTERPRISE_CONFIG', u'ENTERPRISE_CONFIG_RESP', u'ENTERPRISE_NETWORK', u'ENTERPRISE_PERMISSION', u'ENTERPRISE_PROFILE', u'ENTERPRISE_SECURED_DATA', u'ENTERPRISE_SECURITY', u'ENTITY_METADATA_BINDING', u'ESI_SEQUENCENO', u'EVENT_LOG', u'EVPN_BGP_COMMUNITY_TAG_ENTRY', u'EVPN_BGP_COMMUNITY_TAG_SEQ_NO', u'EXPORTIMPORT', u'EXTERNAL_SERVICE', u'FETCH_HYPERVISOR_PROPERTIES', u'FLOATING_IP_ACL_TEMPLATE', u'FLOATING_IP_ACL_TEMPLATE_ENTRY', u'FLOATINGIP', u'FLOATINGIP_ACL', u'FLOATINGIP_ACL_ENTRY', u'GATEWAY', u'GATEWAY_CONFIG', u'GATEWAY_CONFIG_RESP', u'GATEWAY_SECURED_DATA', u'GATEWAY_SECURITY', u'GATEWAY_SECURITY_PROFILE_REQUEST', u'GATEWAY_SECURITY_PROFILE_RESPONSE', u'GATEWAY_SECURITY_REQUEST', u'GATEWAY_SECURITY_RESPONSE', u'GATEWAY_SERVICE_CONFIG', u'GATEWAY_SERVICE_CONFIG_RESP', u'GATEWAY_STATE', u'GATEWAY_TEMPLATE', u'GATEWAY_VPORT_CONFIG', u'GATEWAY_VPORT_CONFIG_RESP', u'GEO_VM_EVENT', u'GEO_VM_REQ', u'GEO_VM_RES', u'GROUP', u'GROUPKEY_ENCRYPTION_PROFILE', u'HEALTH_REQ', u'HOSTINTERFACE', u'HSC', u'IKE_CERTIFICATE', u'IKE_ENCRYPTION_PROFILE', u'IKE_ENCRYPTION_PROFILE_REQUEST', u'IKE_GATEWAY', u'IKE_GATEWAY_CONFIG', u'IKE_GATEWAY_CONNECTION', u'IKE_GATEWAY_CONNECTION_REQUEST', u'IKE_GATEWAY_PROFILE', u'IKE_PSK', u'IKE_SUBNET', u'INFRASTRUCTURE_CONFIG', u'INFRASTRUCTURE_GATEWAY_PROFILE', u'INFRASTRUCTURE_PORT_PROFILE', u'INFRASTRUCTURE_VSC_PROFILE', u'INGRESS_ACL', u'INGRESS_ACL_ENTRY', u'INGRESS_ACL_TEMPLATE', u'INGRESS_ACL_TEMPLATE_ENTRY', u'INGRESS_ADV_FWD', u'INGRESS_ADV_FWD_ENTRY', u'INGRESS_ADV_FWD_TEMPLATE', u'INGRESS_ADV_FWD_TEMPLATE_ENTRY', u'INGRESS_EXT_SERVICE', u'INGRESS_EXT_SERVICE_ENTRY', u'INGRESS_EXT_SERVICE_TEMPLATE', u'INGRESS_EXT_SERVICE_TEMPLATE_ENTRY', u'IP_BINDING', u'JOB', u'KEYSERVER_MEMBER', u'KEYSERVER_MONITOR', u'KEYSERVER_MONITOR_ENCRYPTED_SEED', u'KEYSERVER_MONITOR_SEED', u'KEYSERVER_MONITOR_SEK', u'KEYSERVER_NOTIFICATION', u'L2DOMAIN', u'L2DOMAIN_SHARED', u'L2DOMAIN_TEMPLATE', u'LDAP_CONFIG', u'LIBVIRT_INTERFACE', u'LICENSE', u'LICENSE_STATUS', u'LINK', u'LINKED_DOMAIN_RESP', u'LOCATION', u'MACRO_GROUP_MED', u'MC_CHANNEL_MAP', u'MC_LIST', u'MC_RANGE', u'METADATA', u'METADATA_TAG', u'MIRROR_DESTINATION', u'MONITORING_PORT', u'MULTI_NIC_VPORT', u'NATMAPENTRY', u'NETWORK_ELEMENT', u'NETWORK_LAYOUT', u'NETWORK_MACRO_GROUP', u'NETWORK_POLICY_GROUP', u'NEXT_HOP', u'NEXT_HOP_RESP', u'NODE_EXECUTION_ERROR', u'NS_REDUNDANT_PORT', u'NSG_INFO', u'NSG_NOTIFICATION', u'NSGATEWAY', u'NSGATEWAY_CONFIG', u'NSGATEWAY_TEMPLATE', u'NSPORT', u'NSPORT_STATIC_CONFIG', u'NSPORT_TEMPLATE', u'NSPORT_VLAN_CONFIG', u'NSREDUNDANT_GW_GRP', u'PAT_IP_ENTRY', u'PATCONFIG_CONFIG_RESP', u'PATMAPPER', u'PATNATPOOL', u'PERMISSION', u'PERMITTED_ACTION', u'POLICING_POLICY', u'POLICY_DECISION', u'POLICY_GROUP', u'POLICY_GROUP_TEMPLATE', u'PORT', u'PORT_MR', u'PORT_PUSH', u'PORT_RANGE_MED', u'PORT_TEMPLATE', u'PORT_VLAN_CONFIG', u'PORT_VLAN_CONFIG_RESPONSE', u'PORTMAPPING', u'PUBLIC_NETWORK', u'QOS_PRIMITIVE', u'RATE_LIMITER', u'RD_SEQUENCENO', u'REDUNDANT_GW_GRP', u'ROUTING_POL_MED_RESPONSE', u'ROUTING_POLICY', u'RTRD_ENTITY', u'RTRD_SEQUENCENO', u'SERVICE_GATEWAY_RESPONSE', u'SERVICE_VRF_SEQUENCENO', u'SERVICES_GATEWAY_RESPONSE', u'SHAPING_POLICY', u'SHARED_RESOURCE', u'SITE', u'SITE_REQ', u'SITE_RES', u'STATIC_ROUTE', u'STATIC_ROUTE_RESP', u'STATISTICS', u'STATS_COLLECTOR', u'STATS_POLICY', u'STATS_TCA', u'STATSSERVER', u'SUBNET', u'SUBNET_ENTRY', u'SUBNET_MAC_ENTRY', u'SUBNET_POOL_ENTRY', u'SUBNET_TEMPLATE', u'SYSTEM_CONFIG', u'SYSTEM_CONFIG_REQ', u'SYSTEM_CONFIG_RESP', u'SYSTEM_MONITORING', u'UNSUPPORTED', u'UPLINK_RD', u'USER', u'VCENTER_FETCH_CLUSTERS', u'VCENTER_FETCH_DATACENTERS', u'VIRTUAL_IP', u'VIRTUAL_MACHINE', u'VIRTUAL_MACHINE_REPORT', u'VLAN', u'VLAN_CONFIG_RESPONSE', u'VLAN_TEMPLATE', u'VM_DESCRIPTION', u'VM_INTERFACE', u'VM_RESYNC', u'VMWARE_ADD_CLUSTER_INSCOPE', u'VMWARE_RELOAD_CONFIG', u'VMWARE_REMOVE_CLUSTER_INSCOPE', u'VMWARE_VCENTER', u'VMWARE_VCENTER_CLUSTER', u'VMWARE_VCENTER_DATACENTER', u'VMWARE_VCENTER_EAM_CONFIG', u'VMWARE_VCENTER_HYPERVISOR', u'VMWARE_VCENTER_VRS_BASE_CONFIG', u'VMWARE_VCENTER_VRS_CONFIG', u'VMWARE_VRS_ADDRESS_RANGE', u'VMWARE_VRS_REDEPLOYMENT_POLICY', u'VNID_SEQUENCENO', u'VPN_CONNECT', u'VPORT', u'VPORT_GATEWAY_RESPONSE', u'VPORT_MEDIATION_REQUEST', u'VPORT_MIRROR', u'VPORT_TAG_BASE', u'VPORTTAG', u'VPORTTAGTEMPLATE', u'VPRN_LABEL_SEQUENCENO', u'VRS', u'VSC', u'VSD', u'VSD_COMPONENT', u'VSG_REDUNDANT_PORT', u'VSP', u'WAN_SERVICE', u'ZFB_AUTO_ASSIGNMENT', u'ZFB_AUTO_ASSIGNMENT_VALUE', u'ZFB_GLOBAL', u'ZFB_REQUEST', u'ZONE', u'ZONE_TEMPLATE']) self.expose_attribute(local_name="associated_source_id", remote_name="associatedSourceID", attribute_type=str, is_required=False, is_unique=False) self.expose_attribute(local_name="associated_source_name", remote_name="associatedSourceName", attribute_type=str, is_required=False, is_unique=False) self.expose_attribute(local_name="associated_source_type", remote_name="associatedSourceType", attribute_type=str, is_required=False, is_unique=False) self.expose_attribute(local_name="external_id", remote_name="externalID", attribute_type=str, is_required=False, is_unique=True) self.expose_attribute(local_name="type", remote_name="type", attribute_type=str, is_required=False, is_unique=False, choices=[u'BORDER_ROUTER', u'HUB_AND_SPOKE', u'OVERLAY_ADDRESS_TRANSLATION', u'SERVICE_CHAINING']) # Fetchers self.demarcation_services = NUDemarcationServicesFetcher.fetcher_with_object(parent_object=self, relationship="child") self.metadatas = NUMetadatasFetcher.fetcher_with_object(parent_object=self, relationship="child") self.next_hop_address = NUNextHopAddressFetcher.fetcher_with_object(parent_object=self, relationship="child") self.global_metadatas = NUGlobalMetadatasFetcher.fetcher_with_object(parent_object=self, relationship="child") self.overlay_address_pools = NUOverlayAddressPoolsFetcher.fetcher_with_object(parent_object=self, relationship="child") self._compute_args(**kwargs) # Properties @property def last_updated_by(self): """ Get last_updated_by value. Notes: ID of the user who last updated the object. This attribute is named `lastUpdatedBy` in VSD API. """ return self._last_updated_by @last_updated_by.setter def last_updated_by(self, value): """ Set last_updated_by value. Notes: ID of the user who last updated the object. This attribute is named `lastUpdatedBy` in VSD API. """ self._last_updated_by = value @property def acceptance_criteria(self): """ Get acceptance_criteria value. Notes: A route filtering criteria enum. Defaults to ALL. This attribute is named `acceptanceCriteria` in VSD API. """ return self._acceptance_criteria @acceptance_criteria.setter def acceptance_criteria(self, value): """ Set acceptance_criteria value. Notes: A route filtering criteria enum. Defaults to ALL. This attribute is named `acceptanceCriteria` in VSD API. """ self._acceptance_criteria = value @property def read_only(self): """ Get read_only value. Notes: This is set to true if a link has been created in the opposite direction This attribute is named `readOnly` in VSD API. """ return self._read_only @read_only.setter def read_only(self, value): """ Set read_only value. Notes: This is set to true if a link has been created in the opposite direction This attribute is named `readOnly` in VSD API. """ self._read_only = value @property def entity_scope(self): """ Get entity_scope value. Notes: Specify if scope of entity is Data center or Enterprise level This attribute is named `entityScope` in VSD API. """ return self._entity_scope @entity_scope.setter def entity_scope(self, value): """ Set entity_scope value. Notes: Specify if scope of entity is Data center or Enterprise level This attribute is named `entityScope` in VSD API. """ self._entity_scope = value @property def associated_destination_id(self): """ Get associated_destination_id value. Notes: This is the ID of the domain receiving the routes from the source. This can only be set for links of type OVERLAY_ADDRESS_TRANSLATION. This attribute is named `associatedDestinationID` in VSD API. """ return self._associated_destination_id @associated_destination_id.setter def associated_destination_id(self, value): """ Set associated_destination_id value. Notes: This is the ID of the domain receiving the routes from the source. This can only be set for links of type OVERLAY_ADDRESS_TRANSLATION. This attribute is named `associatedDestinationID` in VSD API. """ self._associated_destination_id = value @property def associated_destination_name(self): """ Get associated_destination_name value. Notes: None This attribute is named `associatedDestinationName` in VSD API. """ return self._associated_destination_name @associated_destination_name.setter def associated_destination_name(self, value): """ Set associated_destination_name value. Notes: None This attribute is named `associatedDestinationName` in VSD API. """ self._associated_destination_name = value @property def associated_destination_type(self): """ Get associated_destination_type value. Notes: Type of the entity type for the source This attribute is named `associatedDestinationType` in VSD API. """ return self._associated_destination_type @associated_destination_type.setter def associated_destination_type(self, value): """ Set associated_destination_type value. Notes: Type of the entity type for the source This attribute is named `associatedDestinationType` in VSD API. """ self._associated_destination_type = value @property def associated_source_id(self): """ Get associated_source_id value. Notes: The ID of the domain receiving the routes from another domain This attribute is named `associatedSourceID` in VSD API. """ return self._associated_source_id @associated_source_id.setter def associated_source_id(self, value): """ Set associated_source_id value. Notes: The ID of the domain receiving the routes from another domain This attribute is named `associatedSourceID` in VSD API. """ self._associated_source_id = value @property def associated_source_name(self): """ Get associated_source_name value. Notes: None This attribute is named `associatedSourceName` in VSD API. """ return self._associated_source_name @associated_source_name.setter def associated_source_name(self, value): """ Set associated_source_name value. Notes: None This attribute is named `associatedSourceName` in VSD API. """ self._associated_source_name = value @property def associated_source_type(self): """ Get associated_source_type value. Notes: This is the source object type for the associatedSourceID This attribute is named `associatedSourceType` in VSD API. """ return self._associated_source_type @associated_source_type.setter def associated_source_type(self, value): """ Set associated_source_type value. Notes: This is the source object type for the associatedSourceID This attribute is named `associatedSourceType` in VSD API. """ self._associated_source_type = value @property def external_id(self): """ Get external_id value. Notes: External object ID. Used for integration with third party systems This attribute is named `externalID` in VSD API. """ return self._external_id @external_id.setter def external_id(self, value): """ Set external_id value. Notes: External object ID. Used for integration with third party systems This attribute is named `externalID` in VSD API. """ self._external_id = value @property def type(self): """ Get type value. Notes: This is used to distinguish between different type of links: hub and spoke, ip address, VNS border router links. """ return self._type @type.setter def type(self, value): """ Set type value. Notes: This is used to distinguish between different type of links: hub and spoke, ip address, VNS border router links. """ self._type = value
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5
90dc6096fa655c4be4d6dcceee0580dafe9e34ee
434
py
Python
python/tests/arthoolbox/conftest.py
ArthurVal/toolbox
857a42043183797582b7f05a78937f224f515ec6
[ "MIT" ]
null
null
null
python/tests/arthoolbox/conftest.py
ArthurVal/toolbox
857a42043183797582b7f05a78937f224f515ec6
[ "MIT" ]
null
null
null
python/tests/arthoolbox/conftest.py
ArthurVal/toolbox
857a42043183797582b7f05a78937f224f515ec6
[ "MIT" ]
null
null
null
#!/usr/bin/env python3 """conftest.py file use to configurate pytest for the arthoolbox lib """ import pytest ############################################################################### # PYTEST - HOOKS # ############################################################################### # TEST - ARTHOOLBOX FIXTURES #
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py
Python
AutomatedTesting/Gem/PythonTests/assetpipeline/wwise_bank_dependency_tests/bank_info_parser_tests.py
aaarsene/o3de
37e3b0226958974defd14dd6d808e8557dcd7345
[ "Apache-2.0", "MIT" ]
1
2021-09-13T00:01:12.000Z
2021-09-13T00:01:12.000Z
AutomatedTesting/Gem/PythonTests/assetpipeline/wwise_bank_dependency_tests/bank_info_parser_tests.py
aaarsene/o3de
37e3b0226958974defd14dd6d808e8557dcd7345
[ "Apache-2.0", "MIT" ]
null
null
null
AutomatedTesting/Gem/PythonTests/assetpipeline/wwise_bank_dependency_tests/bank_info_parser_tests.py
aaarsene/o3de
37e3b0226958974defd14dd6d808e8557dcd7345
[ "Apache-2.0", "MIT" ]
1
2021-07-20T11:07:25.000Z
2021-07-20T11:07:25.000Z
""" Copyright (c) Contributors to the Open 3D Engine Project. For complete copyright and license terms please see the LICENSE at the root of this distribution. SPDX-License-Identifier: Apache-2.0 OR MIT """ import os import pytest import sys soundbanks_xml_filename = 'SoundbanksInfo.xml' @pytest.fixture def soundbank_metadata_generator_setup_fixture(workspace): resources = dict() resources['tests_dir'] = os.path.dirname(os.path.realpath(__file__)) return resources def success_case_test(test_folder, expected_dependencies_dict, bank_info, expected_result_code=0): """ Test Steps: 1. Make sure the return code is what was expected, and that the expected number of banks were returned. 2. Validate bank is in the expected dependencies dictionary. 3. Validate the path to output the metadata file to was assembled correctly. 4. Validate metadata object for this bank is set, and that it has an object assigned to its dependencies field and its includedEvents field 5. Validate metadata object has the correct number of dependencies, and validated that every expected dependency exists in the dependencies list of the metadata object. 6. Validate metadata object has the correct number of events, and validate that every expected event exists in the events of the metadata object. """ expected_bank_count = len(expected_dependencies_dict) banks, result_code = bank_info.generate_metadata( os.path.join(test_folder, soundbanks_xml_filename), test_folder) # Make sure the return code is what was expected, and that the expected number of banks were returned. assert result_code is expected_result_code assert len(banks) is expected_bank_count for bank_index in range(expected_bank_count): bank = banks[bank_index] # Find a bank of this name in the expected dependencies dictionary. assert bank.path in expected_dependencies_dict # Make sure the path to output the metadata file to was assembled correctly. expected_metadata_filepath = os.path.splitext(os.path.join(test_folder, bank.path))[0] + \ bank_info.metadata_file_extension assert bank.metadata_path == expected_metadata_filepath # Make sure the metadata object for this bank is set, and that it has an object assigned to # its dependencies field and its includedEvents field assert bank.metadata_object assert bank.metadata_object['dependencies'] is not None assert bank.metadata_object['includedEvents'] is not None # Make sure the generated metadata object has the correct number of dependencies, and validated that every # expected dependency exists in the dependencies list of the metadata object. assert len(bank.metadata_object['dependencies']) is len(expected_dependencies_dict[bank.path]['dependencies']) for dependency in expected_dependencies_dict[bank.path]['dependencies']: assert dependency in bank.metadata_object['dependencies'] # Make sure the generated metadata object has the correct number of events, and validate that every expected # event exists in the events list of the metadata object. assert len(bank.metadata_object['includedEvents']) is len(expected_dependencies_dict[bank.path]['events']) for event in expected_dependencies_dict[bank.path]['events']: assert event in bank.metadata_object['includedEvents'] def get_bank_info(workspace): sys.path.append( os.path.join(workspace.paths.engine_root(), 'Gems', 'AudioEngineWwise', 'Tools')) from WwiseAuthoringScripts import bank_info_parser as bank_info_module return bank_info_module @pytest.mark.usefixtures("workspace") @pytest.mark.SUITE_periodic @pytest.mark.parametrize("project", ["AutomatedTesting"]) class TestSoundBankMetadataGenerator: def test_NoMetadataTooFewBanks_ReturnCodeIsError(self, workspace, soundbank_metadata_generator_setup_fixture): """ Trying to generate metadata for banks in a folder with one or fewer banks and no metadata is not possible and should fail. Test Steps: 1. Setup testing environment with only 1 bank file 2. Get Sound Bank Info 3. Attempt to generate sound bank metadata 4. Verify that proper error code is returned """ # test_assets_folder = os.path.join(soundbank_metadata_generator_setup_fixture['tests_dir'], 'assets', 'test_NoMetadataTooFewBanks_ReturnCodeIsError') if not os.path.isdir(test_assets_folder): os.makedirs(test_assets_folder) bank_info = get_bank_info(workspace) banks, error_code = bank_info.generate_metadata( os.path.join(test_assets_folder, soundbanks_xml_filename), test_assets_folder) os.rmdir(test_assets_folder) assert error_code is 2, 'Metadata was generated when there were fewer than two banks in the target directory.' def test_NoMetadataNoContentBank_NoMetadataGenerated(self, workspace, soundbank_metadata_generator_setup_fixture): """ Test Steps: 1. Setup testing environment 2. No expected dependencies 3. Call success case test """ test_assets_folder = os.path.join(soundbank_metadata_generator_setup_fixture['tests_dir'], 'assets', 'test_NoMetadataNoContentBank_NoMetadataGenerated') expected_dependencies = dict() success_case_test(test_assets_folder, expected_dependencies, get_bank_info(workspace)) def test_NoMetadataOneContentBank_NoStreamedFiles_OneDependency(self, workspace, soundbank_metadata_generator_setup_fixture): """ When no Wwise metadata is present, and there is only one content bank in the target directory with no wem files, then only the content bank should have metadata associated with it. The generated metadata should only describe a dependency on the init bank. Test Steps: 1. Setup testing environment 2. Get current bank info 3. Build expected dependencies 4. Call success case test """ test_assets_folder = os.path.join(soundbank_metadata_generator_setup_fixture['tests_dir'], 'assets', 'test_NoMetadataOneContentBank_NoStreamedFiles_OneDependency') bank_info = get_bank_info(workspace) expected_dependencies = {'Content.bnk': {'dependencies': [bank_info.init_bank_path], 'events': []},} success_case_test(test_assets_folder, expected_dependencies, get_bank_info(workspace)) def test_NoMetadataOneContentBank_StreamedFiles_MultipleDependencies(self, workspace, soundbank_metadata_generator_setup_fixture): """ When no Wwise metadata is present, and there is only one content bank in the target directory with wem files present, then only the content bank should have metadata associated with it. The generated metadata should describe a dependency on the init bank and all wem files in the folder. Test Steps: 1. Setup testing environment 2. Get current bank info 3. Build expected dependencies 4. Call success case test """ test_assets_folder = os.path.join(soundbank_metadata_generator_setup_fixture['tests_dir'], 'assets', 'test_NoMetadataOneContentBank_StreamedFiles_MultipleDependencies') bank_info = get_bank_info(workspace) expected_dependencies = { 'Content.bnk': { 'dependencies': [ bank_info.init_bank_path, '590205561.wem', '791740036.wem' ], 'events': [] } } success_case_test(test_assets_folder, expected_dependencies, get_bank_info(workspace)) def test_NoMetadataMultipleBanks_OneDependency_ReturnCodeIsWarning(self, workspace, soundbank_metadata_generator_setup_fixture): """ When no Wwise metadata is present, and there are multiple content banks in the target directory with wem files present, there is no way to tell which bank requires which wem files. A warning should be emitted, stating that the full dependency graph could not be created, and only dependencies on the init bank are described in the generated metadata files. Test Steps: 1. Setup testing environment 2. Get current bank info 3. Build expected dependencies 4. Call success case test """ test_assets_folder = os.path.join(soundbank_metadata_generator_setup_fixture['tests_dir'], 'assets', 'test_NoMetadataMultipleBanks_OneDependency_ReturnCodeIsWarning') bank_info = get_bank_info(workspace) expected_dependencies = { 'test_bank1.bnk': {'dependencies': [bank_info.init_bank_path], 'events': []}, 'test_bank2.bnk': {'dependencies': [bank_info.init_bank_path], 'events': []} } success_case_test(test_assets_folder, expected_dependencies, get_bank_info(workspace), expected_result_code=1) def test_OneContentBank_NoStreamedFiles_OneDependency(self, workspace, soundbank_metadata_generator_setup_fixture): """ Wwise metadata describes one content bank that contains all media needed by its events. Generated metadata describes a dependency only on the init bank. Test Steps: 1. Setup testing environment 2. Get current bank info 3. Build expected dependencies 4. Call success case test """ test_assets_folder = os.path.join(soundbank_metadata_generator_setup_fixture['tests_dir'], 'assets', 'test_OneContentBank_NoStreamedFiles_OneDependency') bank_info = get_bank_info(workspace) expected_dependencies = { 'test_bank1.bnk': { 'dependencies': [bank_info.init_bank_path], 'events': ['test_event_1_bank1_embedded_target'] } } success_case_test(test_assets_folder, expected_dependencies, get_bank_info(workspace)) def test_OneContentBank_StreamedFiles_MultipleDependencies(self, workspace, soundbank_metadata_generator_setup_fixture): """ Wwise metadata describes one content bank that references streamed media files needed by its events. Generated metadata describes dependencies on the init bank and wems named by the IDs of referenced streamed media. Test Steps: 1. Setup testing environment 2. Get current bank info 3. Build expected dependencies 4. Call success case test """ test_assets_folder = os.path.join(soundbank_metadata_generator_setup_fixture['tests_dir'], 'assets', 'test_OneContentBank_StreamedFiles_MultipleDependencies') bank_info = get_bank_info(workspace) expected_dependencies = { 'test_bank1.bnk': { 'dependencies': [ bank_info.init_bank_path, '590205561.wem', '791740036.wem' ], 'events': [ 'test_event_1_bank1_embedded_target', 'test_event_2_bank1_streamed_target' ] } } success_case_test(test_assets_folder, expected_dependencies, get_bank_info(workspace)) def test_MultipleContentBanks_NoStreamedFiles_OneDependency(self, workspace, soundbank_metadata_generator_setup_fixture): """ Wwise metadata describes multiple content banks. Each bank contains all media needed by its events. Generated metadata describes each bank having a dependency only on the init bank. Test Steps: 1. Setup testing environment 2. Get current bank info 3. Build expected dependencies 4. Call success case test """ test_assets_folder = os.path.join(soundbank_metadata_generator_setup_fixture['tests_dir'], 'assets', 'test_MultipleContentBanks_NoStreamedFiles_OneDependency') bank_info = get_bank_info(workspace) expected_dependencies = { 'test_bank1.bnk': { 'dependencies': [bank_info.init_bank_path], 'events': ['test_event_1_bank1_embedded_target'] }, 'test_bank2.bnk': { 'dependencies': [bank_info.init_bank_path], 'events': ['test_event_3_bank2_embedded_target', 'test_event_4_bank2_streamed_target'] } } success_case_test(test_assets_folder, expected_dependencies, get_bank_info(workspace)) def test_MultipleContentBanks_Bank1StreamedFiles(self, workspace, soundbank_metadata_generator_setup_fixture): """ Wwise metadata describes multiple content banks. Bank 1 references streamed media files needed by its events, while bank 2 contains all media need by its events. Test Steps: 1. Setup testing environment 2. Get current bank info 3. Build expected dependencies 4. Call success case test """ test_assets_folder = os.path.join(soundbank_metadata_generator_setup_fixture['tests_dir'], 'assets', 'test_MultipleContentBanks_Bank1StreamedFiles') bank_info = get_bank_info(workspace) expected_dependencies = { 'test_bank1.bnk': { 'dependencies': [ bank_info.init_bank_path, '590205561.wem' ], 'events': ['test_event_1_bank1_embedded_target', 'test_event_2_bank1_streamed_target'] }, 'test_bank2.bnk': { 'dependencies': [bank_info.init_bank_path], 'events': ['test_event_3_bank2_embedded_target', 'test_event_4_bank2_streamed_target'] } } success_case_test(test_assets_folder, expected_dependencies, get_bank_info(workspace)) def test_MultipleContentBanks_SplitBanks_OnlyBankDependenices(self, workspace, soundbank_metadata_generator_setup_fixture): """ Wwise metadata describes multiple content banks. Bank 3 events require media that is contained in bank 4. Generated metadata describes each bank having a dependency on the init bank, while bank 3 has an additional dependency on bank 4. Test Steps: 1. Setup testing environment 2. Get current bank info 3. Build expected dependencies 4. Call success case test """ test_assets_folder = os.path.join(soundbank_metadata_generator_setup_fixture['tests_dir'], 'assets', 'test_MultipleContentBanks_SplitBanks_OnlyBankDependenices') bank_info = get_bank_info(workspace) expected_dependencies = { 'test_bank3.bnk': { 'dependencies': [ bank_info.init_bank_path, 'test_bank4.bnk' ], 'events': ['test_event_5_bank3_embedded_target_bank4'] }, 'test_bank4.bnk': {'dependencies': [bank_info.init_bank_path], 'events': []} } success_case_test(test_assets_folder, expected_dependencies, get_bank_info(workspace)) def test_MultipleContentBanks_ReferencedEvent_MediaEmbeddedInBank(self, workspace, soundbank_metadata_generator_setup_fixture): """ Wwise metadata describes multiple content banks. Bank 1 contains all media required by its events, while bank 5 contains a reference to an event in bank 1, but no media for that event. Generated metadata describes both banks having a dependency on the init bank, while bank 5 has an additional dependency on bank 1. Test Steps: 1. Setup testing environment 2. Get current bank info 3. Build expected dependencies 4. Call success case test """ test_assets_folder = os.path.join(soundbank_metadata_generator_setup_fixture['tests_dir'], 'assets', 'test_MultipleContentBanks_ReferencedEvent_MediaEmbeddedInBank') bank_info = get_bank_info(workspace) expected_dependencies = { 'test_bank1.bnk': { 'dependencies': [bank_info.init_bank_path], 'events': ['test_event_1_bank1_embedded_target'] }, 'test_bank5.bnk': { 'dependencies': [ bank_info.init_bank_path, 'test_bank1.bnk' ], 'events': ['test_event_1_bank1_embedded_target', 'test_event_7_bank5_referenced_event_bank1_embedded'] } } success_case_test(test_assets_folder, expected_dependencies, get_bank_info(workspace)) def test_MultipleContentBanks_ReferencedEvent_MediaStreamed(self, workspace, soundbank_metadata_generator_setup_fixture): """ Wwise metadata describes multiple content banks. Bank 1 references streamed media files needed by its events, while bank 5 contains a reference to an event in bank 1. This causes bank 5 to also describe a reference to the streamed media file referenced by the event from bank 1. Generated metadata describes both banks having dependencies on the init bank, as well as the wem named by the ID of referenced streamed media. Test Steps: 1. Setup testing environment 2. Get current bank info 3. Build expected dependencies 4. Call success case test """ test_assets_folder = os.path.join(soundbank_metadata_generator_setup_fixture['tests_dir'], 'assets', 'test_MultipleContentBanks_ReferencedEvent_MediaStreamed') bank_info = get_bank_info(workspace) expected_dependencies = { 'test_bank1.bnk': { 'dependencies': [ bank_info.init_bank_path, '590205561.wem' ], 'events': ['test_event_2_bank1_streamed_target'] }, 'test_bank5.bnk': { 'dependencies': [ bank_info.init_bank_path, '590205561.wem' ], 'events': ['test_event_2_bank1_streamed_target', 'test_event_8_bank5_referenced_event_bank1_streamed'] } } success_case_test(test_assets_folder, expected_dependencies, get_bank_info(workspace)) def test_MultipleContentBanks_ReferencedEvent_MixedSources(self, workspace, soundbank_metadata_generator_setup_fixture): """ Wwise metadata describes multiple content banks. Bank 1 references a streamed media files needed by one of its events, and contains all media needed for its other events, while bank 5 contains a reference to two events in bank 1: one that requires streamed media, and one that requires media embedded in bank 1. Generated metadata describes both banks having dependencies on the init bank and the wem named by the ID of referenced streamed media, while bank 5 has an additional dependency on bank 1. Test Steps: 1. Setup testing environment 2. Get current bank info 3. Build expected dependencies 4. Call success case test """ test_assets_folder = os.path.join(soundbank_metadata_generator_setup_fixture['tests_dir'], 'assets', 'test_MultipleContentBanks_ReferencedEvent_MixedSources') bank_info = get_bank_info(workspace) expected_dependencies = { 'test_bank1.bnk': { 'dependencies': [ bank_info.init_bank_path, '590205561.wem' ], 'events': ['test_event_1_bank1_embedded_target', 'test_event_2_bank1_streamed_target'] }, 'test_bank5.bnk': { 'dependencies': [ bank_info.init_bank_path, 'test_bank1.bnk', '590205561.wem' ], 'events': [ 'test_event_1_bank1_embedded_target', 'test_event_2_bank1_streamed_target', 'test_event_7_bank5_referenced_event_bank1_embedded', 'test_event_8_bank5_referenced_event_bank1_streamed' ] } } success_case_test(test_assets_folder, expected_dependencies, get_bank_info(workspace)) def test_MultipleContentBanks_VaryingDependencies_MixedSources(self, workspace, soundbank_metadata_generator_setup_fixture): """ Wwise metadata describes multiple content banks that have varying dependencies on each other, and dependencies on streamed media files. Test Steps: 1. Setup testing environment 2. Get current bank info 3. Build expected dependencies 4. Call success case test """ test_assets_folder = os.path.join(soundbank_metadata_generator_setup_fixture['tests_dir'], 'assets', 'test_MultipleContentBanks_VaryingDependencies_MixedSources') bank_info = get_bank_info(workspace) expected_dependencies = { 'test_bank1.bnk': { 'dependencies': [ bank_info.init_bank_path, '590205561.wem' ], 'events': ['test_event_1_bank1_embedded_target', 'test_event_2_bank1_streamed_target'] }, 'test_bank2.bnk': { 'dependencies': [bank_info.init_bank_path], 'events': ['test_event_3_bank2_embedded_target', 'test_event_4_bank2_streamed_target'] }, 'test_bank3.bnk': { 'dependencies': [ bank_info.init_bank_path, '791740036.wem', 'test_bank4.bnk' ], 'events': ['test_event_5_bank3_embedded_target_bank4', 'test_event_6_bank3_streamed_target_bank4'] }, 'test_bank4.bnk': {'dependencies': [bank_info.init_bank_path], 'events': []}, 'test_bank5.bnk': { 'dependencies': [ bank_info.init_bank_path, 'test_bank1.bnk', '590205561.wem' ], 'events': [ 'test_event_1_bank1_embedded_target', 'test_event_2_bank1_streamed_target', 'test_event_7_bank5_referenced_event_bank1_embedded', 'test_event_8_bank5_referenced_event_bank1_streamed' ] }, 'test_bank6.bnk': { 'dependencies': [bank_info.init_bank_path], 'events': [ 'test_event_3_bank2_embedded_target', 'test_event_4_bank2_streamed_target', 'test_event_9_bank6_referenced_event_bank2_embedded', 'test_event_10_bank6_referenced_event_bank2_streamed' ] }, } success_case_test(test_assets_folder, expected_dependencies, get_bank_info(workspace))
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5
290afce313a2f8fb3f4f228703adf862079f1f0b
48
py
Python
Python/Tests/TestData/Grammar/InvalidUnicodeLiteral26Up.py
techkey/PTVS
8355e67eedd8e915ca49bd38a2f36172696fd903
[ "Apache-2.0" ]
695
2019-05-06T23:49:37.000Z
2022-03-30T01:56:00.000Z
Python/Tests/TestData/Grammar/InvalidUnicodeLiteral26Up.py
techkey/PTVS
8355e67eedd8e915ca49bd38a2f36172696fd903
[ "Apache-2.0" ]
1,672
2019-05-06T21:09:38.000Z
2022-03-31T23:16:04.000Z
Python/Tests/TestData/Grammar/InvalidUnicodeLiteral26Up.py
techkey/PTVS
8355e67eedd8e915ca49bd38a2f36172696fd903
[ "Apache-2.0" ]
186
2019-05-13T03:17:37.000Z
2022-03-31T16:24:05.000Z
from __future__ import unicode_literals '\uTEST'
24
39
0.854167
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6
1
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0
0
0
1
0
0
0
0
5
291ad2a68aa957958e5ac3e38b28cff3d12fb746
37
py
Python
gwrappy/errors.py
hairizuanbinnoorazman/gwrappy
aae569eb87d0aeac6126ccceac8a208b8dfdcf51
[ "Apache-2.0" ]
5
2016-09-21T10:27:05.000Z
2017-03-13T11:37:16.000Z
gwrappy/errors.py
hairizuanbinnoorazman/gwrappy
aae569eb87d0aeac6126ccceac8a208b8dfdcf51
[ "Apache-2.0" ]
1
2021-11-15T17:46:52.000Z
2021-11-15T17:46:52.000Z
gwrappy/errors.py
hairizuanbinnoorazman/gwrappy
aae569eb87d0aeac6126ccceac8a208b8dfdcf51
[ "Apache-2.0" ]
2
2016-09-21T10:34:59.000Z
2017-04-05T10:38:10.000Z
from googleapiclient.errors import *
18.5
36
0.837838
4
37
7.75
1
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0.939394
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1
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5
2928b414f307fab10cd91f8e49a12103be2dc292
104
py
Python
adafruit_rgb_display/__init__.py
philippkeller/Adafruit_CircuitPython_RGB_Display
0f6ca4d2cb78c0a69a4025b4b59780c4afb967b8
[ "MIT" ]
null
null
null
adafruit_rgb_display/__init__.py
philippkeller/Adafruit_CircuitPython_RGB_Display
0f6ca4d2cb78c0a69a4025b4b59780c4afb967b8
[ "MIT" ]
null
null
null
adafruit_rgb_display/__init__.py
philippkeller/Adafruit_CircuitPython_RGB_Display
0f6ca4d2cb78c0a69a4025b4b59780c4afb967b8
[ "MIT" ]
1
2020-04-30T15:20:37.000Z
2020-04-30T15:20:37.000Z
"""Auto imports for Adafruit_CircuitPython_RGB_Display""" from adafruit_rgb_display.rgb import color565
34.666667
57
0.855769
14
104
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null
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0
1
0
0
0
0
5
293af42b6c68c1bb12ca954e472e8777a47b35e2
69
py
Python
01-Hola-Mundo/holamundo.py
wparedesgt/Master-Python
b0e8963a5a95d479ef929c2d482be50a1959a18f
[ "BSD-3-Clause" ]
null
null
null
01-Hola-Mundo/holamundo.py
wparedesgt/Master-Python
b0e8963a5a95d479ef929c2d482be50a1959a18f
[ "BSD-3-Clause" ]
null
null
null
01-Hola-Mundo/holamundo.py
wparedesgt/Master-Python
b0e8963a5a95d479ef929c2d482be50a1959a18f
[ "BSD-3-Clause" ]
null
null
null
print("#############") print("Hola Mundo !!!") print("#############")
23
23
0.347826
5
69
4.8
0.6
0
0
0
0
0
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0
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0
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69
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24
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true
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5
2942924e85fb4eea725f38fb6c5e7e5e9d37e073
555
py
Python
tools/leetcode.022.Generate Parentheses/leetcode.022.Generate Parentheses.submission3.py
tedye/leetcode
975d7e3b8cb9b6be9e80e07febf4bcf6414acd46
[ "MIT" ]
4
2015-10-10T00:30:55.000Z
2020-07-27T19:45:54.000Z
tools/leetcode.022.Generate Parentheses/leetcode.022.Generate Parentheses.submission3.py
tedye/leetcode
975d7e3b8cb9b6be9e80e07febf4bcf6414acd46
[ "MIT" ]
null
null
null
tools/leetcode.022.Generate Parentheses/leetcode.022.Generate Parentheses.submission3.py
tedye/leetcode
975d7e3b8cb9b6be9e80e07febf4bcf6414acd46
[ "MIT" ]
null
null
null
class Solution: # @param an integer # @return a list of string def generateParenthesis(self, n): if n == 0: return [""] l = set() self.generateHelper(l,n,n,"") return list(l) def generateHelper(self,l,left,right,current): if left == right == 0: l.add(current) return if left > 0: self.generateHelper(l,left-1,right,current+'(') if right > 0 and left < right: self.generateHelper(l,left,right-1,current+')')
555
555
0.513514
66
555
4.318182
0.378788
0.126316
0.2
0.161404
0
0
0
0
0
0
0
0.016854
0.358559
555
1
555
555
0.783708
0.075676
0
0
1
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0.003914
0
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0.142857
false
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0.357143
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null
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0
0
0
0
0
0
0
0
0
5
2961f8be00b18bed3e37dc74aff149e534f4c8a4
119
py
Python
python3/problem0010.py
Furisuke/ProjectEuler
6f91e35fa394300d3f3761e4ab8c20824e4711ac
[ "MIT" ]
1
2015-12-19T09:43:02.000Z
2015-12-19T09:43:02.000Z
python3/problem0010.py
Furisuke/ProjectEuler
6f91e35fa394300d3f3761e4ab8c20824e4711ac
[ "MIT" ]
null
null
null
python3/problem0010.py
Furisuke/ProjectEuler
6f91e35fa394300d3f3761e4ab8c20824e4711ac
[ "MIT" ]
null
null
null
from problem0003 import primes from itertools import takewhile print(sum(takewhile(lambda x: x < 2000000, primes())))
23.8
54
0.781513
16
119
5.8125
0.6875
0
0
0
0
0
0
0
0
0
0
0.105769
0.12605
119
4
55
29.75
0.788462
0
0
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0
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0
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0
true
0
0.666667
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0.666667
0.333333
1
0
0
null
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1
0
1
0
1
0
0
5
461c41c0011838f90970c110da5e7f653a1ffdc3
234
py
Python
classify_predict/__init__.py
dinckaniskan/ML-Inferencing-Durable-Function-Workflow
396be4be2ee093bc3fa4a8a6f325e10bc4ce95e4
[ "MIT" ]
null
null
null
classify_predict/__init__.py
dinckaniskan/ML-Inferencing-Durable-Function-Workflow
396be4be2ee093bc3fa4a8a6f325e10bc4ce95e4
[ "MIT" ]
null
null
null
classify_predict/__init__.py
dinckaniskan/ML-Inferencing-Durable-Function-Workflow
396be4be2ee093bc3fa4a8a6f325e10bc4ce95e4
[ "MIT" ]
null
null
null
""" """ import logging from .predict import predict_image_from_url def main(imageUrl: str) -> str: logging.info('Running prediction on: ' + imageUrl) results = predict_image_from_url(imageUrl) return results
19.5
55
0.688034
28
234
5.535714
0.571429
0.154839
0.206452
0.245161
0
0
0
0
0
0
0
0
0.213675
234
12
56
19.5
0.842391
0
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0
0
0
0.106481
0
0
0
0
0
0
1
0.166667
false
0
0.333333
0
0.666667
0
1
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0
null
0
1
1
0
0
0
0
0
0
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0
0
0
null
0
0
0
0
0
0
0
0
1
0
1
0
0
5
465bc3e3d2772da7cf9aa762d35583f530de8f19
13,090
py
Python
tests/components/wiz/test_config_flow.py
wstewart15/core
854d7d49367d560406d6099a5ba56a0be6c0b9c7
[ "Apache-2.0" ]
null
null
null
tests/components/wiz/test_config_flow.py
wstewart15/core
854d7d49367d560406d6099a5ba56a0be6c0b9c7
[ "Apache-2.0" ]
null
null
null
tests/components/wiz/test_config_flow.py
wstewart15/core
854d7d49367d560406d6099a5ba56a0be6c0b9c7
[ "Apache-2.0" ]
null
null
null
"""Test the WiZ Platform config flow.""" from unittest.mock import patch import pytest from pywizlight.exceptions import WizLightConnectionError, WizLightTimeOutError from homeassistant import config_entries from homeassistant.components import dhcp from homeassistant.components.wiz.config_flow import CONF_DEVICE from homeassistant.components.wiz.const import DOMAIN from homeassistant.const import CONF_HOST from homeassistant.data_entry_flow import RESULT_TYPE_ABORT, RESULT_TYPE_FORM from . import ( FAKE_BULB_CONFIG, FAKE_DIMMABLE_BULB, FAKE_EXTENDED_WHITE_RANGE, FAKE_IP, FAKE_MAC, FAKE_RGBW_BULB, FAKE_RGBWW_BULB, FAKE_SOCKET, FAKE_SOCKET_CONFIG, TEST_CONNECTION, TEST_SYSTEM_INFO, _patch_discovery, _patch_wizlight, ) from tests.common import MockConfigEntry DHCP_DISCOVERY = dhcp.DhcpServiceInfo( hostname="wiz_abcabc", ip=FAKE_IP, macaddress=FAKE_MAC, ) INTEGRATION_DISCOVERY = { "ip_address": FAKE_IP, "mac_address": FAKE_MAC, } async def test_form(hass): """Test we get the form.""" result = await hass.config_entries.flow.async_init( DOMAIN, context={"source": config_entries.SOURCE_USER} ) assert result["type"] == "form" assert result["errors"] == {} # Patch functions with _patch_wizlight(), patch( "homeassistant.components.wiz.async_setup_entry", return_value=True, ) as mock_setup_entry, patch( "homeassistant.components.wiz.async_setup", return_value=True ) as mock_setup: result2 = await hass.config_entries.flow.async_configure( result["flow_id"], TEST_CONNECTION, ) await hass.async_block_till_done() assert result2["type"] == "create_entry" assert result2["title"] == "WiZ Dimmable White ABCABC" assert result2["data"] == { CONF_HOST: "1.1.1.1", } assert len(mock_setup.mock_calls) == 1 assert len(mock_setup_entry.mock_calls) == 1 async def test_user_flow_enters_dns_name(hass): """Test we reject dns names and want ips.""" result = await hass.config_entries.flow.async_init( DOMAIN, context={"source": config_entries.SOURCE_USER} ) assert result["type"] == "form" assert result["errors"] == {} result2 = await hass.config_entries.flow.async_configure( result["flow_id"], {CONF_HOST: "ip.only"}, ) await hass.async_block_till_done() assert result2["type"] == RESULT_TYPE_FORM assert result2["errors"] == {"base": "no_ip"} with _patch_wizlight(), patch( "homeassistant.components.wiz.async_setup_entry", return_value=True, ) as mock_setup_entry, patch( "homeassistant.components.wiz.async_setup", return_value=True ) as mock_setup: result3 = await hass.config_entries.flow.async_configure( result2["flow_id"], TEST_CONNECTION, ) await hass.async_block_till_done() assert result3["type"] == "create_entry" assert result3["title"] == "WiZ Dimmable White ABCABC" assert result3["data"] == { CONF_HOST: "1.1.1.1", } assert len(mock_setup.mock_calls) == 1 assert len(mock_setup_entry.mock_calls) == 1 @pytest.mark.parametrize( "side_effect, error_base", [ (WizLightTimeOutError, "bulb_time_out"), (WizLightConnectionError, "no_wiz_light"), (Exception, "unknown"), (ConnectionRefusedError, "cannot_connect"), ], ) async def test_user_form_exceptions(hass, side_effect, error_base): """Test all user exceptions in the flow.""" result = await hass.config_entries.flow.async_init( DOMAIN, context={"source": config_entries.SOURCE_USER} ) with patch( "homeassistant.components.wiz.wizlight.getBulbConfig", side_effect=side_effect, ): result2 = await hass.config_entries.flow.async_configure( result["flow_id"], TEST_CONNECTION, ) assert result2["type"] == "form" assert result2["errors"] == {"base": error_base} async def test_form_updates_unique_id(hass): """Test a duplicate id aborts and updates existing entry.""" entry = MockConfigEntry( domain=DOMAIN, unique_id=TEST_SYSTEM_INFO["id"], data={CONF_HOST: "dummy"}, ) entry.add_to_hass(hass) result = await hass.config_entries.flow.async_init( DOMAIN, context={"source": config_entries.SOURCE_USER} ) with _patch_wizlight(): result2 = await hass.config_entries.flow.async_configure( result["flow_id"], TEST_CONNECTION, ) await hass.async_block_till_done() assert result2["type"] == "abort" assert result2["reason"] == "already_configured" assert entry.data[CONF_HOST] == FAKE_IP @pytest.mark.parametrize( "source, data", [ (config_entries.SOURCE_DHCP, DHCP_DISCOVERY), (config_entries.SOURCE_INTEGRATION_DISCOVERY, INTEGRATION_DISCOVERY), ], ) async def test_discovered_by_dhcp_connection_fails(hass, source, data): """Test we abort on connection failure.""" with patch( "homeassistant.components.wiz.wizlight.getBulbConfig", side_effect=WizLightTimeOutError, ): result = await hass.config_entries.flow.async_init( DOMAIN, context={"source": source}, data=data ) await hass.async_block_till_done() assert result["type"] == RESULT_TYPE_ABORT assert result["reason"] == "cannot_connect" @pytest.mark.parametrize( "source, data, device, bulb_type, extended_white_range, name", [ ( config_entries.SOURCE_DHCP, DHCP_DISCOVERY, FAKE_BULB_CONFIG, FAKE_DIMMABLE_BULB, FAKE_EXTENDED_WHITE_RANGE, "WiZ Dimmable White ABCABC", ), ( config_entries.SOURCE_INTEGRATION_DISCOVERY, INTEGRATION_DISCOVERY, FAKE_BULB_CONFIG, FAKE_DIMMABLE_BULB, FAKE_EXTENDED_WHITE_RANGE, "WiZ Dimmable White ABCABC", ), ( config_entries.SOURCE_DHCP, DHCP_DISCOVERY, FAKE_BULB_CONFIG, FAKE_RGBW_BULB, FAKE_EXTENDED_WHITE_RANGE, "WiZ RGBW Tunable ABCABC", ), ( config_entries.SOURCE_INTEGRATION_DISCOVERY, INTEGRATION_DISCOVERY, FAKE_BULB_CONFIG, FAKE_RGBW_BULB, FAKE_EXTENDED_WHITE_RANGE, "WiZ RGBW Tunable ABCABC", ), ( config_entries.SOURCE_DHCP, DHCP_DISCOVERY, FAKE_BULB_CONFIG, FAKE_RGBWW_BULB, FAKE_EXTENDED_WHITE_RANGE, "WiZ RGBWW Tunable ABCABC", ), ( config_entries.SOURCE_INTEGRATION_DISCOVERY, INTEGRATION_DISCOVERY, FAKE_BULB_CONFIG, FAKE_RGBWW_BULB, FAKE_EXTENDED_WHITE_RANGE, "WiZ RGBWW Tunable ABCABC", ), ( config_entries.SOURCE_DHCP, DHCP_DISCOVERY, FAKE_SOCKET_CONFIG, FAKE_SOCKET, None, "WiZ Socket ABCABC", ), ( config_entries.SOURCE_INTEGRATION_DISCOVERY, INTEGRATION_DISCOVERY, FAKE_SOCKET_CONFIG, FAKE_SOCKET, None, "WiZ Socket ABCABC", ), ], ) async def test_discovered_by_dhcp_or_integration_discovery( hass, source, data, device, bulb_type, extended_white_range, name ): """Test we can configure when discovered from dhcp or discovery.""" with _patch_wizlight( device=device, extended_white_range=extended_white_range, bulb_type=bulb_type ): result = await hass.config_entries.flow.async_init( DOMAIN, context={"source": source}, data=data ) await hass.async_block_till_done() assert result["type"] == RESULT_TYPE_FORM assert result["step_id"] == "discovery_confirm" with patch( "homeassistant.components.wiz.async_setup_entry", return_value=True, ) as mock_setup_entry, patch( "homeassistant.components.wiz.async_setup", return_value=True ) as mock_setup: result2 = await hass.config_entries.flow.async_configure( result["flow_id"], {}, ) await hass.async_block_till_done() assert result2["type"] == "create_entry" assert result2["title"] == name assert result2["data"] == { CONF_HOST: "1.1.1.1", } assert len(mock_setup.mock_calls) == 1 assert len(mock_setup_entry.mock_calls) == 1 @pytest.mark.parametrize( "source, data", [ (config_entries.SOURCE_DHCP, DHCP_DISCOVERY), (config_entries.SOURCE_INTEGRATION_DISCOVERY, INTEGRATION_DISCOVERY), ], ) async def test_discovered_by_dhcp_or_integration_discovery_updates_host( hass, source, data ): """Test dhcp or discovery updates existing host.""" entry = MockConfigEntry( domain=DOMAIN, unique_id=TEST_SYSTEM_INFO["id"], data={CONF_HOST: "dummy"}, ) entry.add_to_hass(hass) with _patch_wizlight(): result = await hass.config_entries.flow.async_init( DOMAIN, context={"source": source}, data=data ) await hass.async_block_till_done() assert result["type"] == RESULT_TYPE_ABORT assert result["reason"] == "already_configured" assert entry.data[CONF_HOST] == FAKE_IP async def test_setup_via_discovery(hass): """Test setting up via discovery.""" result = await hass.config_entries.flow.async_init( DOMAIN, context={"source": config_entries.SOURCE_USER} ) await hass.async_block_till_done() assert result["type"] == "form" assert result["step_id"] == "user" assert not result["errors"] with _patch_discovery(): result2 = await hass.config_entries.flow.async_configure(result["flow_id"], {}) await hass.async_block_till_done() assert result2["type"] == "form" assert result2["step_id"] == "pick_device" assert not result2["errors"] # test we can try again result = await hass.config_entries.flow.async_init( DOMAIN, context={"source": config_entries.SOURCE_USER} ) assert result["type"] == "form" assert result["step_id"] == "user" assert not result["errors"] with _patch_discovery(): result2 = await hass.config_entries.flow.async_configure(result["flow_id"], {}) await hass.async_block_till_done() assert result2["type"] == "form" assert result2["step_id"] == "pick_device" assert not result2["errors"] with _patch_wizlight(), patch( "homeassistant.components.wiz.async_setup", return_value=True ) as mock_setup, patch( "homeassistant.components.wiz.async_setup_entry", return_value=True ) as mock_setup_entry: result3 = await hass.config_entries.flow.async_configure( result["flow_id"], {CONF_DEVICE: FAKE_MAC}, ) await hass.async_block_till_done() assert result3["type"] == "create_entry" assert result3["title"] == "WiZ Dimmable White ABCABC" assert result3["data"] == { CONF_HOST: "1.1.1.1", } assert len(mock_setup.mock_calls) == 1 assert len(mock_setup_entry.mock_calls) == 1 # ignore configured devices result = await hass.config_entries.flow.async_init( DOMAIN, context={"source": config_entries.SOURCE_USER} ) assert result["type"] == "form" assert result["step_id"] == "user" assert not result["errors"] with _patch_discovery(): result2 = await hass.config_entries.flow.async_configure(result["flow_id"], {}) await hass.async_block_till_done() assert result2["type"] == "abort" assert result2["reason"] == "no_devices_found" async def test_setup_via_discovery_cannot_connect(hass): """Test setting up via discovery and we fail to connect to the discovered device.""" result = await hass.config_entries.flow.async_init( DOMAIN, context={"source": config_entries.SOURCE_USER} ) await hass.async_block_till_done() assert result["type"] == "form" assert result["step_id"] == "user" assert not result["errors"] with _patch_discovery(): result2 = await hass.config_entries.flow.async_configure(result["flow_id"], {}) await hass.async_block_till_done() assert result2["type"] == "form" assert result2["step_id"] == "pick_device" assert not result2["errors"] with patch( "homeassistant.components.wiz.wizlight.getBulbConfig", side_effect=WizLightTimeOutError, ), _patch_discovery(): result3 = await hass.config_entries.flow.async_configure( result["flow_id"], {CONF_DEVICE: FAKE_MAC}, ) await hass.async_block_till_done() assert result3["type"] == "abort" assert result3["reason"] == "cannot_connect"
31.24105
88
0.649351
1,498
13,090
5.371162
0.099466
0.071091
0.042878
0.062888
0.796793
0.792941
0.766468
0.763734
0.757892
0.716754
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0.006872
0.244079
13,090
418
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31.315789
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false
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0
0
0
0
0
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5
46a76abc9e955dea1371346aeb0beb632e52b606
65
py
Python
Validation/RecoTau/python/dataTypes/ValidateTausOnFastSimZTT_cff.py
ckamtsikis/cmssw
ea19fe642bb7537cbf58451dcf73aa5fd1b66250
[ "Apache-2.0" ]
852
2015-01-11T21:03:51.000Z
2022-03-25T21:14:00.000Z
Validation/RecoTau/python/dataTypes/ValidateTausOnFastSimZTT_cff.py
ckamtsikis/cmssw
ea19fe642bb7537cbf58451dcf73aa5fd1b66250
[ "Apache-2.0" ]
30,371
2015-01-02T00:14:40.000Z
2022-03-31T23:26:05.000Z
Validation/RecoTau/python/dataTypes/ValidateTausOnFastSimZTT_cff.py
ckamtsikis/cmssw
ea19fe642bb7537cbf58451dcf73aa5fd1b66250
[ "Apache-2.0" ]
3,240
2015-01-02T05:53:18.000Z
2022-03-31T17:24:21.000Z
from Validation.RecoTau.dataTypes.ValidateTausOnZTT_cff import *
32.5
64
0.876923
7
65
8
1
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65
65
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1
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1
0
1
0
0
5
46b12d2d5b14df7d24373961bd4041fa2a5e20c9
1,587
py
Python
PythonLibrary/GlobalUtilities/test_List_Time_Zone.py
ashishp100194/timezone_api_automation
8a896f2d790d0a0916067bf2c3e3d4d4193921dd
[ "Apache-2.0" ]
1
2020-07-13T04:22:55.000Z
2020-07-13T04:22:55.000Z
PythonLibrary/GlobalUtilities/test_List_Time_Zone.py
ashishp100194/timezone_api_automation
8a896f2d790d0a0916067bf2c3e3d4d4193921dd
[ "Apache-2.0" ]
null
null
null
PythonLibrary/GlobalUtilities/test_List_Time_Zone.py
ashishp100194/timezone_api_automation
8a896f2d790d0a0916067bf2c3e3d4d4193921dd
[ "Apache-2.0" ]
null
null
null
from BaseClass import BaseClass from Variables import Variables def test_List_Time_Zone_TC1(): Base=BaseClass() Base.Timezone("List_Time_Zone", "List_Time_Zone_TC1") def test_List_Time_Zone_TC2(): Base=BaseClass() Base.Timezone("List_Time_Zone", "List_Time_Zone_TC2") def test_List_Time_Zone_TC3(): Base=BaseClass() Base.Timezone("List_Time_Zone", "List_Time_Zone_TC3") def test_List_Time_Zone_TC4(): Base = BaseClass() Base.Timezone("List_Time_Zone", "List_Time_Zone_TC4",Variables["api_base_url"], Variables['Invalid_Key']) def test_List_Time_Zone_TC5(): Base=BaseClass() Base.Timezone("List_Time_Zone", "List_Time_Zone_TC5") def test_List_Time_Zone_TC6(): Base=BaseClass() Base.Timezone("List_Time_Zone", "List_Time_Zone_TC6") def test_List_Time_Zone_TC7(): Base=BaseClass() Base.Timezone("List_Time_Zone", "List_Time_Zone_TC7") def test_List_Time_Zone_TC8(): Base=BaseClass() Base.Timezone("List_Time_Zone", "List_Time_Zone_TC8") def test_List_Time_Zone_TC9(): Base=BaseClass() Base.Timezone("List_Time_Zone", "List_Time_Zone_TC9") def test_List_Time_Zone_TC10(): Base=BaseClass() Base.Timezone("List_Time_Zone", "List_Time_Zone_TC10") def execute_List_Time_Zone(): test_List_Time_Zone_TC1() test_List_Time_Zone_TC2() test_List_Time_Zone_TC3() test_List_Time_Zone_TC4() test_List_Time_Zone_TC5() test_List_Time_Zone_TC6() test_List_Time_Zone_TC7() test_List_Time_Zone_TC8() test_List_Time_Zone_TC9() test_List_Time_Zone_TC10() execute_List_Time_Zone()
28.339286
109
0.760555
244
1,587
4.377049
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0.47191
0.299625
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0.458802
0.458802
0.458802
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0.129175
1,587
56
110
28.339286
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1
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5
d3bbf96679a2eb2d7fdd5cb3f7928ce05a1a392b
171
py
Python
tests/web_platform/css_flexbox_1/test_flexbox_item_vertical_align.py
jonboland/colosseum
cbf974be54fd7f6fddbe7285704cfaf7a866c5c5
[ "BSD-3-Clause" ]
71
2015-04-13T09:44:14.000Z
2019-03-24T01:03:02.000Z
tests/web_platform/css_flexbox_1/test_flexbox_item_vertical_align.py
jonboland/colosseum
cbf974be54fd7f6fddbe7285704cfaf7a866c5c5
[ "BSD-3-Clause" ]
35
2019-05-06T15:26:09.000Z
2022-03-28T06:30:33.000Z
tests/web_platform/css_flexbox_1/test_flexbox_item_vertical_align.py
jonboland/colosseum
cbf974be54fd7f6fddbe7285704cfaf7a866c5c5
[ "BSD-3-Clause" ]
139
2015-05-30T18:37:43.000Z
2019-03-27T17:14:05.000Z
from tests.utils import W3CTestCase class TestFlexbox_ItemVerticalAlign(W3CTestCase): vars().update(W3CTestCase.find_tests(__file__, 'flexbox_item-vertical-align'))
28.5
82
0.818713
19
171
7
0.842105
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0.019108
0.081871
171
5
83
34.2
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true
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0
1
0
1
0
1
0
0
5
d3d7b4004eaeb5ecb5d00ad47a267af9f3ce2beb
191
py
Python
tests/app2.py
gilbrookie/cmdr
ee31e5b75a01f00e45f8181bf78017f232f0287e
[ "ISC" ]
null
null
null
tests/app2.py
gilbrookie/cmdr
ee31e5b75a01f00e45f8181bf78017f232f0287e
[ "ISC" ]
null
null
null
tests/app2.py
gilbrookie/cmdr
ee31e5b75a01f00e45f8181bf78017f232f0287e
[ "ISC" ]
null
null
null
#!/usr/bin/python from data import CmdrOverrideParams, TestCmd1, TestCmd2 CmdrOverrideParams.register_cmd(TestCmd1()) CmdrOverrideParams.register_cmd(TestCmd2()) CmdrOverrideParams.start()
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d3ed28c21aae68c440ca66b6e9019548948e52a0
72
py
Python
main.py
franneck94/Digits-Recognition-Tensorflow
eb3ec8fa4cff64d2f135a40e0104369cd4dd190a
[ "MIT" ]
16
2018-01-28T12:03:52.000Z
2020-12-21T13:31:49.000Z
main.py
franneck94/Digits-Recognition-Tensorflow
eb3ec8fa4cff64d2f135a40e0104369cd4dd190a
[ "MIT" ]
null
null
null
main.py
franneck94/Digits-Recognition-Tensorflow
eb3ec8fa4cff64d2f135a40e0104369cd4dd190a
[ "MIT" ]
11
2017-11-20T20:51:06.000Z
2020-03-11T13:48:49.000Z
from drawer import main_gui if __name__ == "__main__": main_gui()
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5
312c0d0a38f5bf686cd815e99383545825f1ce7c
65
py
Python
Pipeline/main/Strategy/Close/lib/__init__.py
simonydbutt/b2a
0bf4a6de8547d73ace22967780442deeaff2d5c6
[ "MIT" ]
2
2018-07-01T03:36:24.000Z
2020-02-13T17:22:46.000Z
Pipeline/main/Strategy/Close/lib/__init__.py
simonydbutt/b2a
0bf4a6de8547d73ace22967780442deeaff2d5c6
[ "MIT" ]
null
null
null
Pipeline/main/Strategy/Close/lib/__init__.py
simonydbutt/b2a
0bf4a6de8547d73ace22967780442deeaff2d5c6
[ "MIT" ]
null
null
null
from Pipeline.main.Strategy.Close.lib.ProfitRun import ProfitRun
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1
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0
5
3186a0791f2f06075bf3619bc6dcdd62813bdcec
152
py
Python
pseudo-codes/lcm.py
Varshaav16/off-net-learner
ab50af11acc0cbbada54a5d9b9239d2c329cc0c2
[ "MIT" ]
null
null
null
pseudo-codes/lcm.py
Varshaav16/off-net-learner
ab50af11acc0cbbada54a5d9b9239d2c329cc0c2
[ "MIT" ]
null
null
null
pseudo-codes/lcm.py
Varshaav16/off-net-learner
ab50af11acc0cbbada54a5d9b9239d2c329cc0c2
[ "MIT" ]
null
null
null
def gcd(a: int, b: int) -> int : if a == 0: return b return gcd(b % a, a) def lcm(a: int, b: int) -> int: return (a / gcd(a,b))* b
21.714286
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0.460526
30
152
2.333333
0.3
0.114286
0.142857
0.228571
0.314286
0
0
0
0
0
0
0.01
0.342105
152
7
33
21.714286
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0
0
1
1
0
0
5
31b1403c264fe5238638d606fb79d288e1b60822
241
py
Python
fractalis/analytics/__init__.py
thehyve/Fractalis
5591112e5bc994eea5baf3d28caa7e5dfee85a57
[ "Apache-2.0" ]
7
2018-06-01T12:17:26.000Z
2019-08-23T13:15:34.000Z
fractalis/analytics/__init__.py
thehyve/Fractalis
5591112e5bc994eea5baf3d28caa7e5dfee85a57
[ "Apache-2.0" ]
6
2018-11-02T10:00:04.000Z
2021-09-13T14:15:36.000Z
fractalis/analytics/__init__.py
LCSB-BioCore/Fractalis
a9f7f8da7675b55c5996d2f32d7baa7313b0350e
[ "Apache-2.0" ]
3
2018-08-02T16:42:50.000Z
2018-12-14T18:16:22.000Z
from fractalis.utils import list_classes_with_base_class from fractalis.analytics.task import AnalyticTask TASK_REGISTRY = list_classes_with_base_class('fractalis.analytics.tasks', AnalyticTask)
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0.159509
0.184049
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5
31bd2b7849e6827df261c952de7c09de81a89d14
756
py
Python
SBMLDiagrams/__init__.py
SunnyXu/SBMLDiagrams
a7a9dccf42f544d6f48bc097d4dc7ebf5f4e2d41
[ "MIT" ]
null
null
null
SBMLDiagrams/__init__.py
SunnyXu/SBMLDiagrams
a7a9dccf42f544d6f48bc097d4dc7ebf5f4e2d41
[ "MIT" ]
50
2021-12-03T22:43:18.000Z
2022-03-30T22:15:09.000Z
SBMLDiagrams/__init__.py
sys-bio/SBMLDiagrams
ff951ff987fadf61a25d239966134e7bbfa1ff1a
[ "MIT" ]
2
2022-01-30T00:47:44.000Z
2022-03-03T01:13:24.000Z
# try: # from . import _version # except: # from SBMLDiagrams import _version # __version__ = _version.__version__ try: from . import visualizeSBML from . import drawNetwork from . import processSBML from . import editSBML from . import exportSBML from . import styleSBML from. import visualizeInfo except: from SBMLDiagrams import visualizeSBML from SBMLDiagrams import drawNetwork from SBMLDiagrams import processSBML from SBMLDiagrams import editSBML from SBMLDiagrams import exportSBML from SBMLDiagrams import styleSBML from SBMLDiagrams import visualizeInfo from SBMLDiagrams._version import __version__ from SBMLDiagrams.processSBML import * from SBMLDiagrams.visualizeSBML import *
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1
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1
0
0
5
7361d7a18499fca17dcae5e9cf6e4d4b77325d64
135
py
Python
generators/app/templates/_project/_data/inputs_test.py
jrabary/generator-tf
ef376fcd0f2b968b5b7e18a2d68950243f376432
[ "Apache-2.0" ]
null
null
null
generators/app/templates/_project/_data/inputs_test.py
jrabary/generator-tf
ef376fcd0f2b968b5b7e18a2d68950243f376432
[ "Apache-2.0" ]
null
null
null
generators/app/templates/_project/_data/inputs_test.py
jrabary/generator-tf
ef376fcd0f2b968b5b7e18a2d68950243f376432
[ "Apache-2.0" ]
null
null
null
import tensorflow as tf class InputsTest(tf.test.TestCase): def test_inputs(self): # Write your inputs unit test here pass
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0.725926
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135
4.85
0.8
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0
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8
39
16.875
0.906542
0.237037
0
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0
0
0
0
0
0
1
0.25
false
0.25
0.25
0
0.75
0
1
0
0
null
0
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null
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1
0
0
1
0
0
5
b4070315564b3b80bf9cce6119d3c04ee2fabcfa
248
py
Python
bcdp/__init__.py
kinow/bcdp
f4366a307672d84ed7992f3bb68a04303a107c56
[ "Apache-2.0" ]
5
2020-02-17T10:24:32.000Z
2021-09-16T14:58:00.000Z
bcdp/__init__.py
kinow/bcdp
f4366a307672d84ed7992f3bb68a04303a107c56
[ "Apache-2.0" ]
1
2020-04-16T22:17:45.000Z
2020-04-16T22:17:45.000Z
bcdp/__init__.py
kinow/bcdp
f4366a307672d84ed7992f3bb68a04303a107c56
[ "Apache-2.0" ]
2
2020-02-05T23:28:32.000Z
2020-04-04T09:33:00.000Z
from .adapters import * from .bounds import * from .ensemble import * from .extractors import * from .regridder import * from .sources import * __all__ = ['adapters', 'bounds', 'ensemble', 'extractors', 'regridder', 'sources']
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248
6.36
0.36
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0.21371
248
9
50
27.555556
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null
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0
5
b40a2f804928a9a8e0271eb3eac438c02a005b69
235
py
Python
atest/testdata/running/pass_execution_library.py
phil-davis/robotframework
4d4ce686cbe01e293bb86ea6ff34330e8c45fc43
[ "ECL-2.0", "Apache-2.0" ]
7,073
2015-01-01T17:19:16.000Z
2022-03-31T22:01:29.000Z
atest/testdata/running/pass_execution_library.py
phil-davis/robotframework
4d4ce686cbe01e293bb86ea6ff34330e8c45fc43
[ "ECL-2.0", "Apache-2.0" ]
2,412
2015-01-02T09:29:05.000Z
2022-03-31T13:10:46.000Z
atest/testdata/running/pass_execution_library.py
phil-davis/robotframework
4d4ce686cbe01e293bb86ea6ff34330e8c45fc43
[ "ECL-2.0", "Apache-2.0" ]
2,298
2015-01-03T02:47:15.000Z
2022-03-31T02:00:16.000Z
from robot.errors import PassExecution from robot.libraries.BuiltIn import BuiltIn def raise_pass_execution_exception(msg): raise PassExecution(msg) def call_pass_execution_method(msg): BuiltIn().pass_execution(msg, 'lol')
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5.83871
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10
44
23.5
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0.833333
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1
0
1
0
0
5
b476de8f289343219a3df99392d4ce3e75b0b357
173
py
Python
agent/bin/boot_time.py
kemoycampbell/atomic-monitor
29d2fcf8d12bd6ac76f71d5f509fb515b006a44e
[ "MIT" ]
null
null
null
agent/bin/boot_time.py
kemoycampbell/atomic-monitor
29d2fcf8d12bd6ac76f71d5f509fb515b006a44e
[ "MIT" ]
null
null
null
agent/bin/boot_time.py
kemoycampbell/atomic-monitor
29d2fcf8d12bd6ac76f71d5f509fb515b006a44e
[ "MIT" ]
1
2020-04-26T19:16:49.000Z
2020-04-26T19:16:49.000Z
from uptime import boottime class BootTime: # get system boot time def get_boot_time(self): # datetime of boot return boottime().strftime('%x %X')
19.222222
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0.647399
23
173
4.782609
0.695652
0.145455
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0.265896
173
8
44
21.625
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0.213873
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1
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0
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1
1
0
0
5
b47a40973471868c3ded6523c3ab1317b47bd99a
251
py
Python
openprocurement/tender/twostage/validation.py
leits/openprocurement.tender.twostage
2cacf77364bf7ebf74fedf6ddabc8ac600b6d73f
[ "Apache-2.0" ]
null
null
null
openprocurement/tender/twostage/validation.py
leits/openprocurement.tender.twostage
2cacf77364bf7ebf74fedf6ddabc8ac600b6d73f
[ "Apache-2.0" ]
2
2021-03-26T00:35:15.000Z
2022-03-21T22:21:08.000Z
openprocurement/tender/twostage/validation.py
leits/openprocurement.tender.twostage
2cacf77364bf7ebf74fedf6ddabc8ac600b6d73f
[ "Apache-2.0" ]
null
null
null
# -*- coding: utf-8 -*- from openprocurement.api.validation import validate_data from openprocurement.tender.twostage.models import Qualification def validate_patch_qualification_data(request): return validate_data(request, Qualification, True)
31.375
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0.816733
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251
6.896552
0.655172
0.19
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0.004425
0.099602
251
7
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35.857143
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1
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0
5
b47a43e0754a3d5a0e29fbc01cf1f1fbd0c1f635
237
py
Python
Bot/1_Find/AI/_Value_Investing.py
ReedGraff/High-Low
c8ba0339d7818e344cacf9a73a83d24dc539c2ca
[ "MIT" ]
1
2022-01-06T05:50:53.000Z
2022-01-06T05:50:53.000Z
Bot/1_Find/AI/_Value_Investing.py
ReedGraff/High-Low
c8ba0339d7818e344cacf9a73a83d24dc539c2ca
[ "MIT" ]
null
null
null
Bot/1_Find/AI/_Value_Investing.py
ReedGraff/High-Low
c8ba0339d7818e344cacf9a73a83d24dc539c2ca
[ "MIT" ]
null
null
null
def Value_Investing(self, training_data, testing_data=""): if testing_data == "": percent_taken = 30 index = ((100 - percent_taken) / 100) * len(training_data) testing_data = training_data[index:] return 0
39.5
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237
4.965517
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0.25
0.263889
0.319444
0
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0.049724
0.236287
237
6
67
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0.745856
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0
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0
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0
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0
0
0
0
0
0
0
0
0
5
81ec2f644ff2098c451506963f7e53c59a0ba80f
1,931
py
Python
api_login/models.py
archkwon/python-django-restful-mysql
a8097c08057de9656cb40266420fcffebb11bdb6
[ "MIT" ]
null
null
null
api_login/models.py
archkwon/python-django-restful-mysql
a8097c08057de9656cb40266420fcffebb11bdb6
[ "MIT" ]
null
null
null
api_login/models.py
archkwon/python-django-restful-mysql
a8097c08057de9656cb40266420fcffebb11bdb6
[ "MIT" ]
null
null
null
from django.db import models class UserVeriCodeModel(models.Model): uniq_id = models.CharField(primary_key=True, max_length=50, verbose_name='고유아이디') user_mobile_no = models.CharField(max_length=20, blank=True, null=True, verbose_name='휴대폰번호') verification_code = models.CharField(max_length=20, blank=True, null=True, verbose_name='SMS인증코드') cre_date = models.DateTimeField(auto_now_add=True, verbose_name='등록일자') upt_date = models.DateTimeField(auto_now=True, verbose_name='수정일자') class Meta: managed = False db_table = 'tb_tacar_veri_code' verbose_name = "SMS인증번호코드" verbose_name_plural = "SMS인증번호코드" class NaverCloudLogModel(models.Model): uniq_id = models.CharField(primary_key=True, max_length=50, verbose_name='고유아이디') user_mobile_no = models.CharField(max_length=20, blank=True, null=True, verbose_name='휴대폰번호') api_type = models.CharField(max_length=20, blank=True, null=True, verbose_name='API타입') response_json = models.TextField(blank=True, null=True, verbose_name='응답Json파일') cre_date = models.DateTimeField(auto_now_add=True, verbose_name='등록일자') upt_date = models.DateTimeField(auto_now=True, verbose_name='수정일자') class Meta: managed = False db_table = 'tb_tacar_naver_log' verbose_name = "네이버클라우드로그정보" verbose_name_plural = "네이버클라우드로그정보" class UserPurposeInfoModel(models.Model): uniq_id = models.CharField(primary_key=True, max_length=50, verbose_name='고유아이디') user_mobile_no = models.CharField(max_length=20, blank=True, null=True, verbose_name='휴대폰번호') purpose_code = models.CharField(max_length=10, blank=True, null=True, verbose_name='가입목적') cre_date = models.DateTimeField(auto_now_add=True, verbose_name='등록일자') upt_date = models.DateTimeField(auto_now=True, verbose_name='수정일자') class Meta: managed = False db_table = 'tb_tacar_purpose_info'
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5
c316d440063b325879c1842fe7990c9669b67191
86
py
Python
deletefb/exceptions.py
mIcHyAmRaNe/DeleteFB
e8896b1a2c834b0b0cc9404a20225a138e37b303
[ "MIT" ]
2,905
2019-03-30T02:45:34.000Z
2022-02-11T23:08:32.000Z
deletefb/exceptions.py
mIcHyAmRaNe/DeleteFB
e8896b1a2c834b0b0cc9404a20225a138e37b303
[ "MIT" ]
131
2019-05-20T21:52:05.000Z
2022-01-09T11:58:40.000Z
deletefb/exceptions.py
mIcHyAmRaNe/DeleteFB
e8896b1a2c834b0b0cc9404a20225a138e37b303
[ "MIT" ]
249
2019-05-20T19:26:56.000Z
2022-01-25T02:59:00.000Z
class UnknownOSException(Exception): pass class ChromeError(Exception): pass
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5
5eddd41fc903f23c5ff489f5db219a6d12f5ee1f
64
py
Python
google_screener_data_extract/__init__.py
spidezad/google_screener_data_extract
8efe14e73918808182d8745ef38c38f1ac686f6e
[ "BSD-3-Clause" ]
28
2015-09-27T21:11:23.000Z
2021-05-17T06:33:20.000Z
google_screener_data_extract/__init__.py
spidezad/google_screener_data_extract
8efe14e73918808182d8745ef38c38f1ac686f6e
[ "BSD-3-Clause" ]
1
2015-10-18T23:11:03.000Z
2018-03-27T05:58:10.000Z
google_screener_data_extract/__init__.py
spidezad/google_screener_data_extract
8efe14e73918808182d8745ef38c38f1ac686f6e
[ "BSD-3-Clause" ]
24
2016-01-14T09:53:48.000Z
2018-05-17T02:00:56.000Z
from .google_screener_data_extract import GoogleStockDataExtract
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0
5
5ee658096625597fad01df8c6e2f1a6d8f4daff4
60
py
Python
nilearn/input_data/nifti_labels_masker.py
ctw/nilearn
932eee9c69cd8fbf40ee6af5cee77f8f93b25da3
[ "BSD-2-Clause" ]
null
null
null
nilearn/input_data/nifti_labels_masker.py
ctw/nilearn
932eee9c69cd8fbf40ee6af5cee77f8f93b25da3
[ "BSD-2-Clause" ]
null
null
null
nilearn/input_data/nifti_labels_masker.py
ctw/nilearn
932eee9c69cd8fbf40ee6af5cee77f8f93b25da3
[ "BSD-2-Clause" ]
null
null
null
from nilearn.maskers.nifti_labels_masker import * # noqa
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0.783333
8
60
5.625
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0.882353
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1
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1
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1
0
0
5
5ef0bf6299faa97cf0ddbf361c29415874359823
146
py
Python
build_gpcr/management/commands/build_prepare_new_structures.py
pszgaspar/protwis
4989a67175ef3c95047d795c843cf6b9cf4141fa
[ "Apache-2.0" ]
21
2016-01-20T09:33:14.000Z
2021-12-20T19:19:45.000Z
build_gpcr/management/commands/build_prepare_new_structures.py
pszgaspar/protwis
4989a67175ef3c95047d795c843cf6b9cf4141fa
[ "Apache-2.0" ]
75
2016-02-26T16:29:58.000Z
2022-03-21T12:35:13.000Z
build_gpcr/management/commands/build_prepare_new_structures.py
pszgaspar/protwis
4989a67175ef3c95047d795c843cf6b9cf4141fa
[ "Apache-2.0" ]
77
2016-01-22T08:44:26.000Z
2022-02-01T15:54:56.000Z
from build.management.commands.build_prepare_new_structures import Command as PrepareNewStructures class Command(PrepareNewStructures): pass
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5
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5
5efede0d604cc0869f77281508b97a4744c06bd9
164
py
Python
test_libs.py
AgenttiX/fys2029-project
26dc885064721f40db10fad4405f3366f2cfdf4a
[ "Apache-2.0" ]
1
2021-05-21T14:39:07.000Z
2021-05-21T14:39:07.000Z
test_libs.py
AgenttiX/fys2029-project
26dc885064721f40db10fad4405f3366f2cfdf4a
[ "Apache-2.0" ]
1
2021-05-25T12:52:49.000Z
2021-05-25T12:52:49.000Z
test_libs.py
AgenttiX/fys2029-project
26dc885064721f40db10fad4405f3366f2cfdf4a
[ "Apache-2.0" ]
null
null
null
# This file is for testing whether the TensorFlow imports work, without having to start a Jupyter server. import tensorflow as tf import tensorflow_quantum as tfq
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5
6f0251f62e82dc53713159cf139162f5e487ee79
152
py
Python
online_gp/mlls/__init__.py
wjmaddox/online_gp
3bff4c347263a9b8b1f0aa801a986f4aaa019a66
[ "Apache-2.0" ]
31
2021-03-05T00:51:34.000Z
2022-02-07T09:52:20.000Z
online_gp/mlls/__init__.py
wjmaddox/online_gp
3bff4c347263a9b8b1f0aa801a986f4aaa019a66
[ "Apache-2.0" ]
1
2021-11-24T07:18:28.000Z
2021-11-24T12:07:20.000Z
online_gp/mlls/__init__.py
wjmaddox/online_gp
3bff4c347263a9b8b1f0aa801a986f4aaa019a66
[ "Apache-2.0" ]
1
2021-05-19T19:12:36.000Z
2021-05-19T19:12:36.000Z
from .streaming_added_loss_term import StreamingAddedLossTerm from .batched_woodbury_marginal_log_likelihood import BatchedWoodburyMarginalLogLikelihood
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5
6f0263f302229b3951f557f5a63bb60359554c37
119
py
Python
eoflow/tasks/__init__.py
JDESLOIRES/eo-flow
def495e9292809656b906cfd6b8e7389ff9cea61
[ "MIT" ]
80
2019-09-11T08:53:03.000Z
2022-03-29T05:32:02.000Z
eoflow/tasks/__init__.py
JDESLOIRES/eo-flow
def495e9292809656b906cfd6b8e7389ff9cea61
[ "MIT" ]
12
2019-10-11T11:00:56.000Z
2022-01-31T10:43:40.000Z
eoflow/tasks/__init__.py
JDESLOIRES/eo-flow
def495e9292809656b906cfd6b8e7389ff9cea61
[ "MIT" ]
21
2019-09-11T08:12:57.000Z
2022-03-07T01:05:05.000Z
from .train import TrainTask, TrainAndEvaluateTask from .predict import PredictTask from .evaluate import EvaluateTask
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null
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1
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1
0
0
5
6f0cfca7dad80bd1a90a6e3ae4594d1afd447046
3,071
py
Python
src/test/stock_data_analysis_module/indicators/test_rate_of_change.py
Freitacr/ML-StockAnalysisProject
37411c1204ecf69040ba2a1658013e4bf71eef9d
[ "MIT" ]
null
null
null
src/test/stock_data_analysis_module/indicators/test_rate_of_change.py
Freitacr/ML-StockAnalysisProject
37411c1204ecf69040ba2a1658013e4bf71eef9d
[ "MIT" ]
6
2018-01-05T16:42:09.000Z
2021-03-18T00:20:18.000Z
src/test/stock_data_analysis_module/indicators/test_rate_of_change.py
Freitacr/ML-StockAnalysisProject
37411c1204ecf69040ba2a1658013e4bf71eef9d
[ "MIT" ]
1
2021-03-21T04:49:51.000Z
2021-03-21T04:49:51.000Z
import unittest import numpy as np from stock_data_analysis_module.indicators import rate_of_change class RateOfChangeTestCase(unittest.TestCase): def __init__(self, *args): super().__init__(*args) self._empty_sequence = [] self._empty_ndarray = np.zeros((0,)) self._example_a = [1, 1, 2, 3, 4, 5] self._example_b = [1, -1, 1, -1, 1, -1] self._a_2_result = [100, 200, 100, (2/3) * 100] self._b_2_result = [0, 0, 0, 0] self._a_3_result = [200, 300, 150] def test_invalid_length(self): with self.assertRaises(ValueError): rate_of_change.rate_of_change(self._empty_ndarray, 10) with self.assertRaises(ValueError): rate_of_change.rate_of_change(self._empty_sequence, 10) def test_standard_example(self): result = rate_of_change.rate_of_change(self._example_a, period=2) if len(result) != len(self._a_2_result): self.fail("Unexpected results from rate of change calculation with " "the sequence %s.\nExpected: %s\nActual: %s" % (str(self._example_a), str(self._a_2_result), str(result))) for i in range(len(result)): if result[i] != self._a_2_result[i]: self.fail("Unexpected results from rate of change calculation with " "the sequence %s.\nExpected: %s\nActual: %s" % (str(self._example_a), str(self._a_2_result), str(result))) def test_standard_example_2(self): result = rate_of_change.rate_of_change(self._example_b, period=2) if len(result) != len(self._b_2_result): self.fail("Unexpected results from rate of change calculation with " "the sequence %s.\nExpected: %s\nActual: %s" % (str(self._example_b), str(self._b_2_result), str(result))) for i in range(len(result)): if result[i] != self._b_2_result[i]: self.fail("Unexpected results from rate of change calculation with " "the sequence %s.\nExpected: %s\nActual: %s" % (str(self._example_b), str(self._b_2_result), str(result))) def test_standard_example_3(self): result = rate_of_change.rate_of_change(self._example_a, period=3) if len(result) != len(self._a_3_result): self.fail("Unexpected results from rate of change calculation with " "the sequence %s.\nExpected: %s\nActual: %s" % (str(self._example_a), str(self._a_3_result), str(result))) for i in range(len(result)): if result[i] != self._a_3_result[i]: self.fail("Unexpected results from rate of change calculation with " "the sequence %s.\nExpected: %s\nActual: %s" % (str(self._example_a), str(self._a_3_result), str(result))) if __name__ == '__main__': unittest.main()
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5
6f245077d2c2559a5a0020b6347c2e2bf1a57062
3,860
py
Python
QCPU_Setup/DWave-library/dist-packages/dwave_networkx2/algorithms/max_cut.py
cogrpar/qcpuWARE
9b8233e830f8cfacbef787781b2279e42f26fec5
[ "Apache-2.0" ]
1
2022-02-01T14:40:05.000Z
2022-02-01T14:40:05.000Z
QCPU_Setup/DWave-library/dist-packages/dwave_networkx2/algorithms/max_cut.py
cogrpar/qcpuWARE
9b8233e830f8cfacbef787781b2279e42f26fec5
[ "Apache-2.0" ]
null
null
null
QCPU_Setup/DWave-library/dist-packages/dwave_networkx2/algorithms/max_cut.py
cogrpar/qcpuWARE
9b8233e830f8cfacbef787781b2279e42f26fec5
[ "Apache-2.0" ]
1
2022-02-01T14:40:31.000Z
2022-02-01T14:40:31.000Z
from dwave_networkx.exceptions import DWaveNetworkXException from dwave_networkx.utils import binary_quadratic_model_sampler __all__ = ["maximum_cut", "weighted_maximum_cut"] @binary_quadratic_model_sampler(1) def maximum_cut(G, sampler=None, **sampler_args): """Returns an approximate maximum cut. Defines an Ising problem with ground states corresponding to a maximum cut and uses the sampler to sample from it. A maximum cut is a subset S of the vertices of G such that the number of edges between S and the complementary subset is as large as possible. Parameters ---------- G : NetworkX graph sampler A binary quadratic model sampler. A sampler is a process that samples from low energy states in models defined by an Ising equation or a Quadratic Unconstrained Binary Optimization Problem (QUBO). A sampler is expected to have a 'sample_qubo' and 'sample_ising' method. A sampler is expected to return an iterable of samples, in order of increasing energy. If no sampler is provided, one must be provided using the `set_default_sampler` function. sampler_args Additional keyword parameters are passed to the sampler. Returns ------- S : set A maximum cut of G. Notes ----- Samplers by their nature may not return the optimal solution. This function does not attempt to confirm the quality of the returned sample. """ # In order to form the Ising problem, we want to increase the # energy by 1 for each edge between two nodes of the same color. # The linear biases can all be 0. h = {v: 0. for v in G} J = {(u, v): 1 for u, v in G.edges} # draw the lowest energy sample from the sampler response = sampler.sample_ising(h, J, **sampler_args) sample = next(iter(response)) return set(v for v in G if sample[v] >= 0) def weighted_maximum_cut(G, sampler=None, **sampler_args): """Returns an approximate weighted maximum cut. Defines an Ising problem with ground states corresponding to a weighted maximum cut and uses the sampler to sample from it. A weighted maximum cut is a subset S of the vertices of G that maximizes the sum of the edge weights between S and its complementary subset. Parameters ---------- G : NetworkX graph Each edge in G should have a numeric 'weight' attribute. sampler A binary quadratic model sampler. A sampler is a process that samples from low energy states in models defined by an Ising equation or a Quadratic Unconstrained Binary Optimization Problem (QUBO). A sampler is expected to have a 'sample_qubo' and 'sample_ising' method. A sampler is expected to return an iterable of samples, in order of increasing energy. If no sampler is provided, one must be provided using the `set_default_sampler` function. sampler_args Additional keyword parameters are passed to the sampler. Returns ------- S : set A maximum cut of G. Notes ----- Samplers by their nature may not return the optimal solution. This function does not attempt to confirm the quality of the returned sample. """ # In order to form the Ising problem, we want to increase the # energy by 1 for each edge between two nodes of the same color. # The linear biases can all be 0. h = {v: 0. for v in G} try: J = {(u, v): G[u][v]['weight'] for u, v in G.edges} except KeyError: raise DWaveNetworkXException("edges must have 'weight' attribute") # draw the lowest energy sample from the sampler response = sampler.sample_ising(h, J, **sampler_args) sample = next(iter(response)) return set(v for v in G if sample[v] >= 0)
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5
6f63117da26d35a7dfe144611363181514a5ece3
222
py
Python
leetcode/google/tagged/medium/validate_binary_search_tree_test.py
alvinctk/google-tech-dev-guide
9d7759bea1f44673c2de4f25a94b27368928a59f
[ "Apache-2.0" ]
26
2019-06-07T05:29:47.000Z
2022-03-19T15:32:27.000Z
leetcode/google/tagged/medium/validate_binary_search_tree_test.py
alvinctk/google-tech-dev-guide
9d7759bea1f44673c2de4f25a94b27368928a59f
[ "Apache-2.0" ]
null
null
null
leetcode/google/tagged/medium/validate_binary_search_tree_test.py
alvinctk/google-tech-dev-guide
9d7759bea1f44673c2de4f25a94b27368928a59f
[ "Apache-2.0" ]
6
2019-10-10T06:39:28.000Z
2020-05-12T19:50:55.000Z
[2,1,3] [5,1,4,null,null,3,6] [2,1,4,null,null,3,6] [2,1,4,null,null,8,6] [] [1, 1, 1] [0, 1] [0, 1, 3] [10,5,15,null,null,6,20] [10,5,15,3,11,12,20] [3,null,30,10,null,null,15,null,45] [3,null,30,10,null,null,15,null,19]
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5
489c8b7fc77b584ea69c38066aa27e09cc4e0b15
68
py
Python
lib/python/abcutils/__init__.py
gcodebackups/helgemathee-alembic-softimage
fb8c5f09f35ea899a272f9cab0dd2f887317c043
[ "RSA-MD" ]
null
null
null
lib/python/abcutils/__init__.py
gcodebackups/helgemathee-alembic-softimage
fb8c5f09f35ea899a272f9cab0dd2f887317c043
[ "RSA-MD" ]
null
null
null
lib/python/abcutils/__init__.py
gcodebackups/helgemathee-alembic-softimage
fb8c5f09f35ea899a272f9cab0dd2f887317c043
[ "RSA-MD" ]
1
2015-11-24T18:58:38.000Z
2015-11-24T18:58:38.000Z
from Path import Path from CMakeCache import CMakeCache, CacheEntry
22.666667
45
0.852941
9
68
6.444444
0.555556
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2
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5
48a1f9a8e738e97b2bdd80fe016f7aab4096c1ca
209
py
Python
200Python/demo/01basic-hello/02basic/dict_set.py
lyliyongblue/JavaCoder
a04a350ec675a3a8b15c99da5cc89397dbbc97ef
[ "Apache-2.0" ]
null
null
null
200Python/demo/01basic-hello/02basic/dict_set.py
lyliyongblue/JavaCoder
a04a350ec675a3a8b15c99da5cc89397dbbc97ef
[ "Apache-2.0" ]
null
null
null
200Python/demo/01basic-hello/02basic/dict_set.py
lyliyongblue/JavaCoder
a04a350ec675a3a8b15c99da5cc89397dbbc97ef
[ "Apache-2.0" ]
null
null
null
scores = {'AA': 10, 'BB': 20, "CC": 30} print("AA score:", scores['AA']) print("Before BB score:", scores['BB']) scores['BB'] = 100 print("After BB score:", scores["BB"]) age = {1, 2, 3} print(age)
20.9
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209
3.454545
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9
41
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0
0
0
1
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5
48ad3be834fd184aced1bedc40472fe60a92d916
435
py
Python
server-src/directMessages.py
Artingl/Fluffy
e51ca77651a67ea6206dcbfa0a3436c032f3a3ed
[ "Apache-2.0" ]
null
null
null
server-src/directMessages.py
Artingl/Fluffy
e51ca77651a67ea6206dcbfa0a3436c032f3a3ed
[ "Apache-2.0" ]
null
null
null
server-src/directMessages.py
Artingl/Fluffy
e51ca77651a67ea6206dcbfa0a3436c032f3a3ed
[ "Apache-2.0" ]
null
null
null
import datetime import sqlalchemy import db class directMessages(db.SqlAlchemyBase): __tablename__ = 'directMessages' id = sqlalchemy.Column(sqlalchemy.Integer, primary_key=True, autoincrement=True) users = sqlalchemy.Column(sqlalchemy.String, index=True, nullable=True) content = sqlalchemy.Column(sqlalchemy.String, default='{}') info = sqlalchemy.Column(sqlalchemy.String, default='{"state":{}, "title":""}')
33.461538
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0.744828
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435
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12
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1
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1
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5
d2942132aaddb326056ef36f3ab9a2deb335c799
118
py
Python
apps/app_a.py
nelsoncardenas/cerate_many_docker_images
14b57f5fd12c993d0c8776545e88973cf297eef2
[ "MIT" ]
null
null
null
apps/app_a.py
nelsoncardenas/cerate_many_docker_images
14b57f5fd12c993d0c8776545e88973cf297eef2
[ "MIT" ]
null
null
null
apps/app_a.py
nelsoncardenas/cerate_many_docker_images
14b57f5fd12c993d0c8776545e88973cf297eef2
[ "MIT" ]
null
null
null
import numpy import pandas import pyarrow import click if __name__ == "__main__": print("This is app_a running!")
16.857143
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118
4.647059
0.823529
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7
35
16.857143
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0
1
0
1
0
0
5
d2ce1af5632f270ac28413fd4bc05870c9ad09a9
150
py
Python
tests/test_app.py
PXMYH/doctor
fac85ea02a96d986c69b3ac27a7444c10287cff4
[ "MIT" ]
null
null
null
tests/test_app.py
PXMYH/doctor
fac85ea02a96d986c69b3ac27a7444c10287cff4
[ "MIT" ]
null
null
null
tests/test_app.py
PXMYH/doctor
fac85ea02a96d986c69b3ac27a7444c10287cff4
[ "MIT" ]
null
null
null
#!/usr/bin/env python3 # -*- coding: utf-8 -*- import pytest @pytest.mark.skip(reason="function not ready yet, todo") def test_version(): pass
15
56
0.666667
22
150
4.5
0.954545
0
0
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0
0.015873
0.16
150
9
57
16.666667
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true
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1
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5
d2e54c138c93710f1556d10b67ab7919a25b7c00
156
py
Python
__main__.py
aldenso/pulumi_docker_demo
4bfd5d374c62b927e0fff0ea39695c7efa9469c5
[ "MIT" ]
null
null
null
__main__.py
aldenso/pulumi_docker_demo
4bfd5d374c62b927e0fff0ea39695c7efa9469c5
[ "MIT" ]
null
null
null
__main__.py
aldenso/pulumi_docker_demo
4bfd5d374c62b927e0fff0ea39695c7efa9469c5
[ "MIT" ]
null
null
null
import pulumi import infra pulumi.export('image', infra.my_image) pulumi.export('container', infra.container) pulumi.export('dockerfile', infra.dockerfile)
26
45
0.801282
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156
6.2
0.4
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0.064103
156
6
45
26
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null
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0
0
0
1
0
1
0
0
0
0
5
96218ff962d029dbf39837f84299562348e8bbcf
87
py
Python
app/hello/__init__.py
washiz99/python-flask-hello
9d602d53c85c38fd1f5fb191630df096f9cef88d
[ "MIT" ]
null
null
null
app/hello/__init__.py
washiz99/python-flask-hello
9d602d53c85c38fd1f5fb191630df096f9cef88d
[ "MIT" ]
null
null
null
app/hello/__init__.py
washiz99/python-flask-hello
9d602d53c85c38fd1f5fb191630df096f9cef88d
[ "MIT" ]
null
null
null
from flask import Blueprint hello = Blueprint('hello', __name__) from . import views
14.5
36
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87
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0.636364
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5
96247f0ee1665b2fa401a2b05798d31a0f4c6819
38
py
Python
tests/components/stream/__init__.py
domwillcode/home-assistant
f170c80bea70c939c098b5c88320a1c789858958
[ "Apache-2.0" ]
30,023
2016-04-13T10:17:53.000Z
2020-03-02T12:56:31.000Z
tests/components/stream/__init__.py
jagadeeshvenkatesh/core
1bd982668449815fee2105478569f8e4b5670add
[ "Apache-2.0" ]
31,101
2020-03-02T13:00:16.000Z
2022-03-31T23:57:36.000Z
tests/components/stream/__init__.py
jagadeeshvenkatesh/core
1bd982668449815fee2105478569f8e4b5670add
[ "Apache-2.0" ]
11,956
2016-04-13T18:42:31.000Z
2020-03-02T09:32:12.000Z
"""The tests for stream platforms."""
19
37
0.684211
5
38
5.2
1
0
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0
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38
1
38
38
0.787879
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true
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5
824a86a0ac80d0b8829c8f880dc614ee1f1a703a
536
py
Python
src/genie/libs/parser/iosxe/tests/ShowEnvFan/cli/equal/golden_output_expected.py
balmasea/genieparser
d1e71a96dfb081e0a8591707b9d4872decd5d9d3
[ "Apache-2.0" ]
204
2018-06-27T00:55:27.000Z
2022-03-06T21:12:18.000Z
src/genie/libs/parser/iosxe/tests/ShowEnvFan/cli/equal/golden_output_expected.py
balmasea/genieparser
d1e71a96dfb081e0a8591707b9d4872decd5d9d3
[ "Apache-2.0" ]
468
2018-06-19T00:33:18.000Z
2022-03-31T23:23:35.000Z
src/genie/libs/parser/iosxe/tests/ShowEnvFan/cli/equal/golden_output_expected.py
balmasea/genieparser
d1e71a96dfb081e0a8591707b9d4872decd5d9d3
[ "Apache-2.0" ]
309
2019-01-16T20:21:07.000Z
2022-03-30T12:56:41.000Z
expected_output = { 'switch': { "1": { 'fan': { "1": { 'state': 'ok' }, "2": { 'state': 'ok' }, "3": { 'state': 'ok' } }, 'power_supply': { "1": { 'state': 'not present' }, "2": { 'state': 'ok' } } } } }
20.615385
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536
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5
826374d576e75c8a49672752bd228090e03e0a7c
88
py
Python
dev_server/context_api.py
PlatformOfTrust/code-samples-validator
75fa24d93ccafaa51f7e1c0ebae447ac2bf933e0
[ "MIT" ]
null
null
null
dev_server/context_api.py
PlatformOfTrust/code-samples-validator
75fa24d93ccafaa51f7e1c0ebae447ac2bf933e0
[ "MIT" ]
null
null
null
dev_server/context_api.py
PlatformOfTrust/code-samples-validator
75fa24d93ccafaa51f7e1c0ebae447ac2bf933e0
[ "MIT" ]
1
2020-04-28T09:54:33.000Z
2020-04-28T09:54:33.000Z
import bottle app = bottle.Bottle() @app.get('/') def list_contexts(): return {}
9.777778
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0.625
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4.909091
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0.333333
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5
8272d16d8ed4370478973c544cdfd623819a5ec8
93
py
Python
homebrain/core/__init__.py
ErikBjare/Homebrain
7e4dcc9d0e5f5ef6bde3d2cf31639527166ab124
[ "MIT" ]
1
2015-12-03T18:42:54.000Z
2015-12-03T18:42:54.000Z
homebrain/core/__init__.py
ErikBjare/Homebrain
7e4dcc9d0e5f5ef6bde3d2cf31639527166ab124
[ "MIT" ]
14
2015-12-02T22:21:12.000Z
2019-11-06T10:26:08.000Z
homebrain/core/__init__.py
ErikBjare/Homebrain
7e4dcc9d0e5f5ef6bde3d2cf31639527166ab124
[ "MIT" ]
null
null
null
from .events import Event from .agents import Agent, PausableAgent from . import decorators
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py
Python
lib/__init__.py
JohnEskimSmith/export-elasticmq
dadb6e9ac01d9e7593702d6b1b780d6c140cd3d3
[ "MIT" ]
null
null
null
lib/__init__.py
JohnEskimSmith/export-elasticmq
dadb6e9ac01d9e7593702d6b1b780d6c140cd3d3
[ "MIT" ]
null
null
null
lib/__init__.py
JohnEskimSmith/export-elasticmq
dadb6e9ac01d9e7593702d6b1b780d6c140cd3d3
[ "MIT" ]
null
null
null
#!/usr/bin/env python # -*- coding: utf-8 -*- __author__ = "SAI" __license__ = "GPLv3" __email__ = "andrew.foma@gmail.com" __status__ = "Dev" from .upload_settings import * from .upload_records import * from .upload_utils import * from .upload_sqs import * from .upload_parse_multi_records import * from .upload_files_utils import *
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82e7a11b4e3671736342f1de0fd9b639f7b78e3b
15,043
py
Python
applications/ParticleMechanicsApplication/tests/test_generate_mpm_particle.py
lkusch/Kratos
e8072d8e24ab6f312765185b19d439f01ab7b27b
[ "BSD-4-Clause" ]
null
null
null
applications/ParticleMechanicsApplication/tests/test_generate_mpm_particle.py
lkusch/Kratos
e8072d8e24ab6f312765185b19d439f01ab7b27b
[ "BSD-4-Clause" ]
null
null
null
applications/ParticleMechanicsApplication/tests/test_generate_mpm_particle.py
lkusch/Kratos
e8072d8e24ab6f312765185b19d439f01ab7b27b
[ "BSD-4-Clause" ]
null
null
null
from __future__ import print_function, absolute_import, division import KratosMultiphysics import KratosMultiphysics.ParticleMechanicsApplication as KratosParticle import KratosMultiphysics.KratosUnittest as KratosUnittest class TestGenerateMPMParticle(KratosUnittest.TestCase): def _generate_particle_element_and_check(self, current_model, dimension, geometry_element, num_particle, expected_num_particle): KratosMultiphysics.Logger.GetDefaultOutput().SetSeverity(KratosMultiphysics.Logger.Severity.WARNING) # Initialize model part ## Material model part definition material_point_model_part = current_model.CreateModelPart("dummy_name") material_point_model_part.ProcessInfo.SetValue(KratosMultiphysics.DOMAIN_SIZE, dimension) ## Initial material model part definition initial_mesh_model_part = current_model.CreateModelPart("Initial_dummy_name") initial_mesh_model_part.ProcessInfo.SetValue(KratosMultiphysics.DOMAIN_SIZE, dimension) ## Grid model part definition grid_model_part = current_model.CreateModelPart("Background_Grid") grid_model_part.ProcessInfo.SetValue(KratosMultiphysics.DOMAIN_SIZE, dimension) # Create element and nodes for background grids sub_background = grid_model_part.CreateSubModelPart("test_background") self._create_nodes(sub_background, dimension, geometry_element) self._create_elements(sub_background,dimension, geometry_element) # Create element and nodes for initial meshes sub_mp = initial_mesh_model_part.CreateSubModelPart("test") sub_mp.GetProperties()[1].SetValue(KratosParticle.PARTICLES_PER_ELEMENT, num_particle) self._create_nodes(sub_mp, dimension, geometry_element) self._create_elements(sub_mp,dimension, geometry_element) # Generate MP Elements KratosParticle.GenerateMaterialPointElement(grid_model_part, initial_mesh_model_part, material_point_model_part, False) # Check total number of element particle_counter = material_point_model_part.NumberOfElements() self.assertEqual(expected_num_particle,particle_counter) def _generate_particle_element_and_check_mp_volume(self, current_model, dimension, geometry_element, num_particle, expected_mp_volume): KratosMultiphysics.Logger.GetDefaultOutput().SetSeverity(KratosMultiphysics.Logger.Severity.WARNING) # Initialize model part ## Material model part definition material_point_model_part = current_model.CreateModelPart("dummy_name") material_point_model_part.ProcessInfo.SetValue(KratosMultiphysics.DOMAIN_SIZE, dimension) ## Initial material model part definition initial_mesh_model_part = current_model.CreateModelPart("Initial_dummy_name") initial_mesh_model_part.ProcessInfo.SetValue(KratosMultiphysics.DOMAIN_SIZE, dimension) ## Grid model part definition grid_model_part = current_model.CreateModelPart("Background_Grid") grid_model_part.ProcessInfo.SetValue(KratosMultiphysics.DOMAIN_SIZE, dimension) # Create element and nodes for background grids sub_background = grid_model_part.CreateSubModelPart("test_background") self._create_nodes(sub_background, dimension, geometry_element) self._create_elements(sub_background,dimension, geometry_element) # Create element and nodes for initial meshes sub_mp = initial_mesh_model_part.CreateSubModelPart("test") sub_mp.GetProperties()[1].SetValue(KratosParticle.PARTICLES_PER_ELEMENT, num_particle) self._create_nodes(sub_mp, dimension, geometry_element) self._create_elements(sub_mp,dimension, geometry_element) # Generate MP Elements KratosParticle.GenerateMaterialPointElement(grid_model_part, initial_mesh_model_part, material_point_model_part, False) # Check volume of first material point for mp in material_point_model_part.Elements: mp_volume = mp.CalculateOnIntegrationPoints(KratosParticle.MP_VOLUME, grid_model_part.ProcessInfo)[0] self.assertEqual(expected_mp_volume,mp_volume) break def _create_nodes(self, initial_mp, dimension, geometry_element): if geometry_element == "Triangle": initial_mp.CreateNewNode(1, 0.0, 0.0, 0.0) initial_mp.CreateNewNode(2, 1.0, 0.0, 0.0) initial_mp.CreateNewNode(3, 0.0, 1.0, 0.0) if (dimension == 3): initial_mp.CreateNewNode(4, 0.0, 0.0, 1.0) elif geometry_element == "TriangleSkew": initial_mp.CreateNewNode(1, 0.0, 0.0, 0.0) initial_mp.CreateNewNode(2, 2.0, 0.0, 0.0) initial_mp.CreateNewNode(3, 0.0, 1.0, 0.0) if (dimension == 3): initial_mp.CreateNewNode(4, 0.0, 0.0, 1.0) elif geometry_element == "Quadrilateral": initial_mp.CreateNewNode(1, -0.5, -0.5, 0.0) initial_mp.CreateNewNode(2, 0.5, -0.5, 0.0) initial_mp.CreateNewNode(3, 0.5, 0.5, 0.0) initial_mp.CreateNewNode(4, -0.5, 0.5, 0.0) if (dimension == 3): initial_mp.CreateNewNode(5, -0.5, -0.5, 1.0) initial_mp.CreateNewNode(6, 0.5, -0.5, 1.0) initial_mp.CreateNewNode(7, 0.5, 0.5, 1.0) initial_mp.CreateNewNode(8, -0.5, 0.5, 1.0) elif geometry_element == "QuadrilateralSkew": initial_mp.CreateNewNode(1, -0.5, -0.5, 0.0) initial_mp.CreateNewNode(2, 1.5, -0.5, 0.0) initial_mp.CreateNewNode(3, 0.5, 0.5, 0.0) initial_mp.CreateNewNode(4, -0.5, 0.5, 0.0) if (dimension == 3): initial_mp.CreateNewNode(5, -0.5, -0.5, 1.0) initial_mp.CreateNewNode(6, 0.5, -0.5, 1.0) initial_mp.CreateNewNode(7, 0.5, 0.5, 1.0) initial_mp.CreateNewNode(8, -0.5, 0.5, 1.0) def _create_elements(self, initial_mp, dimension, geometry_element): if geometry_element == "Triangle" or geometry_element == "TriangleSkew": if (dimension == 2): initial_mp.CreateNewElement("Element2D3N", 1, [1,2,3], initial_mp.GetProperties()[1]) if (dimension == 3): initial_mp.CreateNewElement("Element3D4N", 1, [1,2,3,4], initial_mp.GetProperties()[1]) elif geometry_element == "Quadrilateral" or geometry_element == "QuadrilateralSkew": if (dimension == 2): initial_mp.CreateNewElement("Element2D4N", 1, [1,2,3,4], initial_mp.GetProperties()[1]) if (dimension == 3): initial_mp.CreateNewElement("Element3D8N", 1, [1,2,3,4,5,6,7,8], initial_mp.GetProperties()[1]) KratosMultiphysics.VariableUtils().SetFlag(KratosMultiphysics.ACTIVE, True, initial_mp.Elements) def test_GenerateMPMParticleTriangle2D1P(self): current_model = KratosMultiphysics.Model() self._generate_particle_element_and_check(current_model, dimension=2, geometry_element="Triangle", num_particle=1, expected_num_particle=1) def test_GenerateMPMParticleTriangle2D3P(self): current_model = KratosMultiphysics.Model() self._generate_particle_element_and_check(current_model, dimension=2, geometry_element="Triangle", num_particle=3, expected_num_particle=3) def test_GenerateMPMParticleTriangle2D6P(self): current_model = KratosMultiphysics.Model() self._generate_particle_element_and_check(current_model, dimension=2, geometry_element="Triangle", num_particle=6, expected_num_particle=6) def test_GenerateMPMParticleTriangle2D12P(self): current_model = KratosMultiphysics.Model() self._generate_particle_element_and_check(current_model, dimension=2, geometry_element="Triangle", num_particle=12, expected_num_particle=12) def test_GenerateMPMParticleTriangle2D16P(self): current_model = KratosMultiphysics.Model() self._generate_particle_element_and_check(current_model, dimension=2, geometry_element="Triangle", num_particle=16, expected_num_particle=16) def test_GenerateMPMParticleTriangle2D33P(self): current_model = KratosMultiphysics.Model() self._generate_particle_element_and_check(current_model, dimension=2, geometry_element="Triangle", num_particle=33, expected_num_particle=33) def test_GenerateMPMParticleTriangle2DDefault(self): current_model = KratosMultiphysics.Model() self._generate_particle_element_and_check(current_model, dimension=2, geometry_element="Triangle", num_particle=50, expected_num_particle=3) def test_GenerateMPMParticleTriangle3D1P(self): current_model = KratosMultiphysics.Model() self._generate_particle_element_and_check(current_model, dimension=3, geometry_element="Triangle", num_particle=1, expected_num_particle=1) def test_GenerateMPMParticleTriangle3D4P(self): current_model = KratosMultiphysics.Model() self._generate_particle_element_and_check(current_model, dimension=3, geometry_element="Triangle", num_particle=3, expected_num_particle=4) def test_GenerateMPMParticleTriangle3D14P(self): current_model = KratosMultiphysics.Model() self._generate_particle_element_and_check(current_model, dimension=3, geometry_element="Triangle", num_particle=6, expected_num_particle=14) def test_GenerateMPMParticleTriangle3D24P(self): current_model = KratosMultiphysics.Model() self._generate_particle_element_and_check(current_model, dimension=3, geometry_element="Triangle", num_particle=12, expected_num_particle=24) def test_GenerateMPMParticleTriangle3DDefault(self): current_model = KratosMultiphysics.Model() self._generate_particle_element_and_check(current_model, dimension=3, geometry_element="Triangle", num_particle=50, expected_num_particle=4) def test_GenerateMPMParticleQuadrilateral2D1P(self): current_model = KratosMultiphysics.Model() self._generate_particle_element_and_check(current_model, dimension=2, geometry_element="Quadrilateral", num_particle=1, expected_num_particle=1) def test_GenerateMPMParticleQuadrilateral2D4P(self): current_model = KratosMultiphysics.Model() self._generate_particle_element_and_check(current_model, dimension=2, geometry_element="Quadrilateral", num_particle=4, expected_num_particle=4) def test_GenerateMPMParticleQuadrilateral2D9P(self): current_model = KratosMultiphysics.Model() self._generate_particle_element_and_check(current_model, dimension=2, geometry_element="Quadrilateral", num_particle=9, expected_num_particle=9) def test_GenerateMPMParticleQuadrilateral2D16P(self): current_model = KratosMultiphysics.Model() self._generate_particle_element_and_check(current_model, dimension=2, geometry_element="Quadrilateral", num_particle=16, expected_num_particle=16) def test_GenerateMPMParticleQuadrilateral2DDefault(self): current_model = KratosMultiphysics.Model() self._generate_particle_element_and_check(current_model, dimension=2, geometry_element="Quadrilateral", num_particle=50, expected_num_particle=4) def test_GenerateMPMParticleQuadrilateral3D1P(self): current_model = KratosMultiphysics.Model() self._generate_particle_element_and_check(current_model, dimension=3, geometry_element="Quadrilateral", num_particle=1, expected_num_particle=1) def test_GenerateMPMParticleQuadrilateral3D8P(self): current_model = KratosMultiphysics.Model() self._generate_particle_element_and_check(current_model, dimension=3, geometry_element="Quadrilateral", num_particle=4, expected_num_particle=8) def test_GenerateMPMParticleQuadrilateral3D27P(self): current_model = KratosMultiphysics.Model() self._generate_particle_element_and_check(current_model, dimension=3, geometry_element="Quadrilateral", num_particle=9, expected_num_particle=27) def test_GenerateMPMParticleQuadrilateral3D64P(self): current_model = KratosMultiphysics.Model() self._generate_particle_element_and_check(current_model, dimension=3, geometry_element="Quadrilateral", num_particle=16, expected_num_particle=64) def test_GenerateMPMParticleQuadrilateral3DDefault(self): current_model = KratosMultiphysics.Model() self._generate_particle_element_and_check(current_model, dimension=3, geometry_element="Quadrilateral", num_particle=50, expected_num_particle=8) # Tests for the correct computation of material point volume in the material point generator def test_GenerateMPMParticleQuadrilateral2DSkew(self): current_model = KratosMultiphysics.Model() self._generate_particle_element_and_check_mp_volume(current_model, dimension=2, geometry_element="QuadrilateralSkew", num_particle=4, expected_mp_volume=0.44716878364870316) def test_GenerateMPMParticleQuadrilateral3DSkew(self): current_model = KratosMultiphysics.Model() self._generate_particle_element_and_check_mp_volume(current_model, dimension=3, geometry_element="QuadrilateralSkew", num_particle=4, expected_mp_volume=0.20275105849101815) def test_GenerateMPMParticleTriangle2DSkew(self): current_model = KratosMultiphysics.Model() self._generate_particle_element_and_check_mp_volume(current_model, dimension=2, geometry_element="TriangleSkew", num_particle=3, expected_mp_volume=0.3333333333333333) def test_GenerateMPMParticleTriangle3DSkew(self): current_model = KratosMultiphysics.Model() self._generate_particle_element_and_check_mp_volume(current_model, dimension=3, geometry_element="TriangleSkew", num_particle=3, expected_mp_volume=0.08333333333333333) def test_GenerateMPMParticleQuadrilateral2DNotSkew(self): current_model = KratosMultiphysics.Model() self._generate_particle_element_and_check_mp_volume(current_model, dimension=2, geometry_element="Quadrilateral", num_particle=4, expected_mp_volume=0.25) def test_GenerateMPMParticleQuadrilateral3DNotSkew(self): current_model = KratosMultiphysics.Model() self._generate_particle_element_and_check_mp_volume(current_model, dimension=3, geometry_element="Quadrilateral", num_particle=4, expected_mp_volume=0.12499999999999993) def test_GenerateMPMParticleTriangle2DNotSkew(self): current_model = KratosMultiphysics.Model() self._generate_particle_element_and_check_mp_volume(current_model, dimension=2, geometry_element="Triangle", num_particle=3, expected_mp_volume=0.16666666666666666) def test_GenerateMPMParticleTriangle3DNotSkew(self): current_model = KratosMultiphysics.Model() self._generate_particle_element_and_check_mp_volume(current_model, dimension=3, geometry_element="Triangle", num_particle=3, expected_mp_volume=0.041666666666666664) if __name__ == '__main__': KratosUnittest.main()
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7d84ba6e8daa7f46d81022d38abe49ae28dad7b3
73
py
Python
app/jwt_helpers/__init__.py
docusign/eg-03-python-auth-code-grant
e92913e25f753fb6b52fc3da6bc4b76c49c75b37
[ "MIT" ]
7
2019-05-09T05:17:35.000Z
2020-05-06T14:27:51.000Z
app/jwt_helpers/__init__.py
docusign/eg-03-python-auth-code-grant
e92913e25f753fb6b52fc3da6bc4b76c49c75b37
[ "MIT" ]
1
2019-06-25T23:06:34.000Z
2019-06-25T23:06:34.000Z
app/jwt_helpers/__init__.py
docusign/eg-03-python-auth-code-grant
e92913e25f753fb6b52fc3da6bc4b76c49c75b37
[ "MIT" ]
8
2019-06-21T23:57:48.000Z
2020-02-11T18:58:34.000Z
from .jwt_helper import create_api_client, get_jwt_token, get_private_key
73
73
0.890411
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4.461538
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7d8a18703ea07662fcb7b8d49335b94c1ff36ed7
570
py
Python
tests/test_sexp.py
gitoleg/bap-ida-python
f1cdd95578c331f1f3fba2150c2e2d134b8897f0
[ "MIT" ]
81
2016-06-10T19:07:12.000Z
2022-03-23T08:15:41.000Z
tests/test_sexp.py
gitoleg/bap-ida-python
f1cdd95578c331f1f3fba2150c2e2d134b8897f0
[ "MIT" ]
22
2016-06-16T19:35:59.000Z
2020-12-10T14:53:38.000Z
tests/test_sexp.py
gitoleg/bap-ida-python
f1cdd95578c331f1f3fba2150c2e2d134b8897f0
[ "MIT" ]
29
2016-06-10T18:26:04.000Z
2022-02-14T06:15:30.000Z
from bap.utils.sexp import parse def test_parse(): assert parse('()') == [] assert parse('hello') == 'hello' assert parse('"hello world"') == '"hello world"' assert parse('(hello world)') == ['hello', 'world'] assert parse('(() () ())') == [[], [], []] assert parse("hi'") == "hi'" assert parse('hello"') == 'hello"' assert parse('(hello\" cruel world\")') == ['hello"', 'cruel', 'world"'] assert parse('(a (b c) c (d (e f) g) h') == [ 'a', ['b', 'c'], 'c', ['d', ['e', 'f'], 'g'], 'h' ]
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5
7da69b07b172a6afb3ffe8fcb055417415d0f60a
121
py
Python
tests/test_nothing.py
thundergolfer/PyGrobid
04e55f5f0e11537f367e281718a519d225ce2f70
[ "Apache-2.0" ]
1
2021-09-11T21:29:57.000Z
2021-09-11T21:29:57.000Z
tests/test_nothing.py
thundergolfer-old/PyGrobid
04e55f5f0e11537f367e281718a519d225ce2f70
[ "Apache-2.0" ]
null
null
null
tests/test_nothing.py
thundergolfer-old/PyGrobid
04e55f5f0e11537f367e281718a519d225ce2f70
[ "Apache-2.0" ]
null
null
null
# This test is here so we don't get a non-zero code from Pytest in Travis CI build. def test_dummy(): assert 5 == 5
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7db30e571f8c55b8142793cce2416c315c6d4319
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py
Python
predict_live.py
hulsmeier/best_voxelnet_ever
aeefd32711a5c986c6099d53c5a2efdf9e01ea48
[ "MIT" ]
null
null
null
predict_live.py
hulsmeier/best_voxelnet_ever
aeefd32711a5c986c6099d53c5a2efdf9e01ea48
[ "MIT" ]
null
null
null
predict_live.py
hulsmeier/best_voxelnet_ever
aeefd32711a5c986c6099d53c5a2efdf9e01ea48
[ "MIT" ]
null
null
null
#!/usr/bin/env python # -*- coding:UTF-8 -*- import glob import argparse import os import time import tensorflow.compat.v1 as tf import socket import struct import win32pipe, win32file, pywintypes from config import cfg from model import RPN3D from utils import * from utils.kitti_loader import iterate_data, sample_test_data parser = argparse.ArgumentParser(description='testing') parser.add_argument('-d', '--decrease', type=bool, nargs='?', default=False, help='set the flag to True if decrease model') parser.add_argument('-m', '--minimize', type=bool, nargs='?', default=False, help='set the flag to True if minimize model') args = parser.parse_args() res_dir = os.path.join('.', './predictions') save_model_dir = os.path.join('.', 'save_model', 'default') os.makedirs(res_dir, exist_ok=True) os.makedirs(os.path.join(res_dir, 'data'), exist_ok=True) serverIPAddress = '127.0.0.1' serverPortNumber = 44444 def main(_): with tf.Graph().as_default(): gpu_options = tf.GPUOptions( per_process_gpu_memory_fraction=cfg.GPU_MEMORY_FRACTION, visible_device_list=cfg.GPU_AVAILABLE, allow_growth=True ) config = tf.ConfigProto( gpu_options=gpu_options, device_count={"GPU": cfg.GPU_USE_COUNT,}, allow_soft_placement=True, ) with tf.Session(config=config) as sess: model = RPN3D( cls=cfg.DETECT_OBJ, decrease=args.decrease, minimize=args.minimize, single_batch_size=1, avail_gpus=cfg.GPU_AVAILABLE.split(',') ) # param init/restore if tf.train.get_checkpoint_state(save_model_dir): print("Reading model parameters from %s" % save_model_dir) model.saver.restore(sess, tf.train.latest_checkpoint(save_model_dir)) f = open(r'\\.\pipe\LidarData', 'r+b', 0) while True: n = struct.unpack('I', f.read(4))[0] data = f.read(n) f.seek(0) f_lidar = data batch = sample_data_live(f_lidar) results = model.predict_step_live(sess, batch) # # #for result in zip(results): # # # labels = box3d_to_label([result[:, 1:8]], [result[:, 0]], [result[:, -1]], coordinate='lidar')[0] # # # print('write out {} objects'.format(len(labels))) print('write out {} objects'.format(len(results))) if __name__ == '__main__': tf.app.run(main) ##!/usr/bin/env python ## -*- coding:UTF-8 -*- #import glob #import argparse #import os #import time #import tensorflow as tf #import socket #import struct #from config import cfg #from model import RPN3D #from utils import * #from utils.kitti_loader import iterate_data, sample_test_data #parser = argparse.ArgumentParser(description='testing') #parser.add_argument('-d', '--decrease', type=bool, nargs='?', default=False, # help='set the flag to True if decrease model') #parser.add_argument('-m', '--minimize', type=bool, nargs='?', default=False, # help='set the flag to True if minimize model') #args = parser.parse_args() #res_dir = os.path.join('.', './predictions') #save_model_dir = os.path.join('.', 'save_model', 'default') #os.makedirs(res_dir, exist_ok=True) #os.makedirs(os.path.join(res_dir, 'data'), exist_ok=True) #serverIPAddress = '127.0.0.1' #serverPortNumber = 44444 #def main(_): # with tf.Graph().as_default(): # gpu_options = tf.GPUOptions( # per_process_gpu_memory_fraction=cfg.GPU_MEMORY_FRACTION, # visible_device_list=cfg.GPU_AVAILABLE, # allow_growth=True # ) # config = tf.ConfigProto( # gpu_options=gpu_options, # device_count={"GPU": cfg.GPU_USE_COUNT,}, # allow_soft_placement=True, # ) # with tf.Session(config=config) as sess: # model = RPN3D( # cls=cfg.DETECT_OBJ, # decrease=args.decrease, # minimize=args.minimize, # single_batch_size=1, # avail_gpus=cfg.GPU_AVAILABLE.split(',') # ) # # param init/restore # if tf.train.get_checkpoint_state(save_model_dir): # print("Reading model parameters from %s" % save_model_dir) # model.saver.restore(sess, tf.train.latest_checkpoint(save_model_dir)) # with socket.socket(socket.AF_INET, socket.SOCK_STREAM) as clientSocket: # connectedToServer = False # while connectedToServer == False: # try: # clientSocket.connect((serverIPAddress, serverPortNumber)) # connectedToServer = True # except Exception as e: # print("Waiting for server...") # while True: # print("Waiting for data...") # numberOfBytesReceived = 0 # messageSizeReceived = False # currentMessageSize = 0 # bytesFromClient = b'' # newBytesFromClient = clientSocket.recv(1000024) # print(len(newBytesFromClient)) # while len(newBytesFromClient) > 0: # numberOfBytesReceived += len(newBytesFromClient) # bytesFromClient += newBytesFromClient # if(bytesFromClient == b''): # break # if messageSizeReceived == False: # if numberOfBytesReceived >= 4: # currentMessageSize = struct.unpack('i', bytesFromClient[:4])[0] # messageSizeReceived = True # else: # continue # if numberOfBytesReceived >= currentMessageSize + 4: # f_lidar = bytesFromClient[:currentMessageSize] # batch = sample_data_live(f_lidar) # results = model.predict_step_live(sess, batch) # #for result in zip(results): # # labels = box3d_to_label([result[:, 1:8]], [result[:, 0]], [result[:, -1]], coordinate='lidar')[0] # # print('write out {} objects'.format(len(labels))) # print('write out {} objects'.format(len(results))) # break # newBytesFromClient = clientSocket.recv(1000024) #if __name__ == '__main__': # tf.app.run(main)
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5
7dcbce74b688ffe7ed28feae607be9ea474e56c7
4,441
py
Python
tests/test_management.py
fsecada01/django-unused-media
ee177edb359e641e010671977fc336880a0a3862
[ "MIT" ]
2
2021-12-02T11:41:02.000Z
2021-12-27T12:01:53.000Z
venv/Lib/site-packages/tests/test_management.py
serenasensini/TheRedCode_Docker-per-Django-e-Postgres
78a2ca1f09ab956a6936d14a5fd99336ff39f472
[ "BSD-3-Clause" ]
null
null
null
venv/Lib/site-packages/tests/test_management.py
serenasensini/TheRedCode_Docker-per-Django-e-Postgres
78a2ca1f09ab956a6936d14a5fd99336ff39f472
[ "BSD-3-Clause" ]
null
null
null
# -*- coding: utf-8 -*- import mock import six from preggy import expect from django.core.management import call_command from .base import BaseTestCase class TestManagementCommand(BaseTestCase): def test_command_call(self): expect(call_command('cleanup_unused_media', interactive=False)).Not.to_be_an_error() def test_command_nothing_to_delete(self): stdout = six.StringIO() call_command('cleanup_unused_media', interactive=False, stdout=stdout) expect(stdout.getvalue().split('\n'))\ .to_include(u'Nothing to delete. Exit') def test_command_not_interactive(self): self._media_create('file.txt') stdout = six.StringIO() call_command('cleanup_unused_media', interactive=False, stdout=stdout) expect(stdout.getvalue().split('\n'))\ .to_include(u'Remove {}'.format(self._media_abs_path(u'file.txt')))\ .to_include(u'Done. Total files removed: 1') expect(self._media_exists('file.txt')).to_be_false() @mock.patch('six.moves.input', return_value='n') def test_command_interactive_n(self, mock_input): self._media_create(u'file.txt') stdout = six.StringIO() call_command('cleanup_unused_media', interactive=True, stdout=stdout) expect(stdout.getvalue().split('\n'))\ .to_include(u'Interrupted by user. Exit.') expect(self._media_exists(u'file.txt')).to_be_true() @mock.patch('six.moves.input', return_value='Y') def test_command_interactive_y(self, mock_input): self._media_create(u'file.txt') stdout = six.StringIO() call_command('cleanup_unused_media', interactive=True, stdout=stdout) expect(stdout.getvalue().split('\n')) \ .to_include(u'Remove {}'.format(self._media_abs_path(u'file.txt'))) \ .to_include(u'Done. Total files removed: 1') expect(self._media_exists(u'file.txt')).to_be_false() @mock.patch('six.moves.input', return_value='Y') def test_command_interactive_y_with_ascii(self, mock_input): self._media_create(u'Тест.txt') expected_string = u'Remove {}'.format(self._media_abs_path(u'Тест.txt')) if six.PY2: expected_string = expected_string.encode('utf-8') stdout = six.StringIO() call_command('cleanup_unused_media', interactive=True, stdout=stdout) expect(stdout.getvalue().split('\n')) \ .to_include(expected_string) \ .to_include(u'Done. Total files removed: 1') expect(self._media_exists(u'Тест.txt')).to_be_false() @mock.patch('django_unused_media.management.commands.cleanup_unused_media.remove_empty_dirs') def test_command_do_not_remove_dirs(self, mock_remove_empty_dirs): self._media_create(u'sub1/sub2/sub3/notused.txt') call_command('cleanup_unused_media', interactive=False) mock_remove_empty_dirs.assert_not_called() @mock.patch('django_unused_media.management.commands.cleanup_unused_media.remove_empty_dirs') def test_command_remove_dirs(self, mock_remove_empty_dirs): self._media_create(u'sub1/sub2/sub3/notused.txt') call_command('cleanup_unused_media', interactive=False, remove_empty_dirs=True) mock_remove_empty_dirs.assert_called_once() def test_command_dry_run(self): self._media_create('file.txt') stdout = six.StringIO() call_command('cleanup_unused_media', interactive=False, dry_run=True, stdout=stdout) expect(stdout.getvalue().split('\n')) \ .to_include(self._media_abs_path(u'file.txt')) \ .to_include(u'Total files will be removed: 1') \ .to_include(u'Dry run. Exit.') expect(self._media_exists('file.txt')).to_be_true() @mock.patch('six.moves.input', return_value='Y') def test_command_interactive_y_verbosity_0(self, mock_input): self._media_create(u'file.txt') stdout = six.StringIO() call_command('cleanup_unused_media', interactive=True, stdout=stdout, verbosity=0) expect(stdout.getvalue().split('\n')) \ .Not.to_include(u'Files to remove:') \ .Not.to_include(self._media_abs_path(u'file.txt')) \ .Not.to_include(u'Remove {}'.format(self._media_abs_path(u'file.txt'))) \ .to_include(u'Done. Total files removed: 1') expect(self._media_exists(u'file.txt')).to_be_false()
39.300885
97
0.677775
594
4,441
4.754209
0.148148
0.063739
0.076487
0.084986
0.793201
0.763456
0.759207
0.733003
0.714943
0.695467
0
0.004425
0.185769
4,441
112
98
39.651786
0.776549
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0.04708
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false
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5
814525ab201eae8cf04fea2013e429ce025ca6dc
55
py
Python
prefetch/__init__.py
ValHayot/rollingprefetch
dacb8b5e741461c268d960ace46e22a926a4339f
[ "MIT" ]
1
2021-11-15T22:06:27.000Z
2021-11-15T22:06:27.000Z
prefetch/__init__.py
ValHayot/rollingprefetch
dacb8b5e741461c268d960ace46e22a926a4339f
[ "MIT" ]
1
2021-07-28T21:47:24.000Z
2021-08-24T02:52:36.000Z
prefetch/__init__.py
ValHayot/rollingprefetch
dacb8b5e741461c268d960ace46e22a926a4339f
[ "MIT" ]
null
null
null
from .core import S3PrefetchFileSystem, S3PrefetchFile
27.5
54
0.872727
5
55
9.6
1
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