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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
04b0bc87f829277b9806bb11cd8837fb56d6784b | 188 | py | Python | app/api/v2/views/home_resource.py | jomasim/heroku-devops | baaa639f6288673cc902d8fe0df211a7eeac08e2 | [
"MIT"
] | null | null | null | app/api/v2/views/home_resource.py | jomasim/heroku-devops | baaa639f6288673cc902d8fe0df211a7eeac08e2 | [
"MIT"
] | 14 | 2018-10-27T20:55:42.000Z | 2018-11-19T17:19:47.000Z | app/api/v2/views/home_resource.py | jomasim/store-api-v2 | ee569a17911b0cfbf67b644bd454fd4b895af95f | [
"MIT"
] | null | null | null | from flask import redirect
from flask_restful import Resource
class HomeController(Resource):
''' redirect to api docs '''
def get(self):
redirect('https://storeapiv2.docs.apiary.io') | 26.857143 | 47 | 0.760638 | 25 | 188 | 5.68 | 0.72 | 0.126761 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.006061 | 0.12234 | 188 | 7 | 47 | 26.857143 | 0.854545 | 0.106383 | 0 | 0 | 0 | 0 | 0.204969 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.2 | false | 0 | 0.4 | 0 | 0.8 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 4 |
04d19a7eb12c45998447667f143a68b8e5972a10 | 227 | py | Python | tests/test_input.py | AgnezIO/agnez | b923b09b3c124ad41e233b45c63f2749b5f31617 | [
"BSD-3-Clause"
] | 50 | 2015-12-27T21:30:23.000Z | 2021-10-14T13:43:50.000Z | tests/test_input.py | AgnezIO/agnez | b923b09b3c124ad41e233b45c63f2749b5f31617 | [
"BSD-3-Clause"
] | 3 | 2016-01-06T17:04:15.000Z | 2016-08-06T23:19:49.000Z | tests/test_input.py | AgnezIO/agnez | b923b09b3c124ad41e233b45c63f2749b5f31617 | [
"BSD-3-Clause"
] | 6 | 2016-03-04T20:25:27.000Z | 2019-01-12T21:45:17.000Z | import numpy as np
from agnez import image_sequence
def test_image_sequence():
I = np.eye(28)[np.newaxis].repeat(10, axis=0)
R = image_sequence(I.reshape(10, 28*28), shape=(28, 28))
assert R.shape == (28, 28*10)
| 22.7 | 60 | 0.669604 | 40 | 227 | 3.7 | 0.55 | 0.263514 | 0.189189 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.112299 | 0.176211 | 227 | 9 | 61 | 25.222222 | 0.679144 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.166667 | 1 | 0.166667 | false | 0 | 0.333333 | 0 | 0.5 | 0 | 0 | 0 | 0 | null | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 4 |
04d49378aff80cd8dc24d396db7e3fbff5f46371 | 295 | py | Python | Python_do_zero_Guanabara/05_VáriavelCompostas/desafio/74_desafio.py | HenriqueSOliver/Projetos_Python | f18c5a343ad1b746a12bd372298b2debe9bc65ec | [
"MIT"
] | null | null | null | Python_do_zero_Guanabara/05_VáriavelCompostas/desafio/74_desafio.py | HenriqueSOliver/Projetos_Python | f18c5a343ad1b746a12bd372298b2debe9bc65ec | [
"MIT"
] | null | null | null | Python_do_zero_Guanabara/05_VáriavelCompostas/desafio/74_desafio.py | HenriqueSOliver/Projetos_Python | f18c5a343ad1b746a12bd372298b2debe9bc65ec | [
"MIT"
] | null | null | null |
from random import randint
v = (randint(1, 10), randint(1, 10), randint(1, 10), randint(1, 10), randint(1, 10))
print(f'Eu sorteei os valores : ', end='')
for n in v:
print(f'{n} ', end='')
print(f'\nO menor valor digitado foi {min(v)}')
print(f'O maior valor digitado foi {max(v)}')
| 24.583333 | 84 | 0.620339 | 53 | 295 | 3.45283 | 0.490566 | 0.218579 | 0.273224 | 0.371585 | 0.273224 | 0.273224 | 0.273224 | 0.273224 | 0.273224 | 0.273224 | 0 | 0.061983 | 0.179661 | 295 | 11 | 85 | 26.818182 | 0.694215 | 0 | 0 | 0 | 0 | 0 | 0.341297 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.142857 | 0 | 0.142857 | 0.571429 | 0 | 0 | 0 | null | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 4 |
04e585e1d1eef46d18789958bca438de01e67a3d | 1,080 | py | Python | messages/serializers.py | sharebears/pulsar-messages | 723faa7be560f97f9a349e23b395239ccc10161f | [
"MIT"
] | null | null | null | messages/serializers.py | sharebears/pulsar-messages | 723faa7be560f97f9a349e23b395239ccc10161f | [
"MIT"
] | null | null | null | messages/serializers.py | sharebears/pulsar-messages | 723faa7be560f97f9a349e23b395239ccc10161f | [
"MIT"
] | null | null | null | from core.mixins import Attribute, Serializer
from messages.permissions import MessagePermissions
class PrivateConversationSerializer(Serializer):
id = Attribute(permission=MessagePermissions.VIEW_OTHERS)
topic = Attribute(permission=MessagePermissions.VIEW_OTHERS)
last_response_time = Attribute(permission=MessagePermissions.VIEW_OTHERS)
read = Attribute(permission=MessagePermissions.VIEW_OTHERS)
sticky = Attribute(permission=MessagePermissions.VIEW_OTHERS)
messages = Attribute(
nested=False, permission=MessagePermissions.VIEW_OTHERS
)
messages_count = Attribute(permission=MessagePermissions.VIEW_OTHERS)
members = Attribute(permission=MessagePermissions.VIEW_OTHERS)
class PrivateMessageSerializer(Serializer):
# These are essentially permissioned in the conversation, since messages
# are never rendered outside of a conversation. No need to run the checks
# again.
id = Attribute()
conv_id = Attribute()
user = Attribute(nested=('id', 'username'))
time = Attribute()
contents = Attribute()
| 40 | 77 | 0.775926 | 107 | 1,080 | 7.719626 | 0.457944 | 0.271186 | 0.309927 | 0.368039 | 0.46368 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.15 | 1,080 | 26 | 78 | 41.538462 | 0.899782 | 0.137963 | 0 | 0 | 0 | 0 | 0.010787 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.105263 | 0 | 0.894737 | 0 | 0 | 0 | 0 | null | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 4 |
b6f5f3a74d70ba6bcad1c10d8813d697ebec4cf1 | 93 | py | Python | TaiyoInfo/apps.py | triangular-opensource/Taiyo | 944ac6d1d1411fe34f293d0a3dade958e9319d63 | [
"MIT"
] | null | null | null | TaiyoInfo/apps.py | triangular-opensource/Taiyo | 944ac6d1d1411fe34f293d0a3dade958e9319d63 | [
"MIT"
] | 2 | 2021-12-13T16:43:27.000Z | 2021-12-15T07:28:43.000Z | TaiyoInfo/apps.py | triangular-opensource/Taiyo | 944ac6d1d1411fe34f293d0a3dade958e9319d63 | [
"MIT"
] | null | null | null | from django.apps import AppConfig
class TaiyoinfoConfig(AppConfig):
name = 'TaiyoInfo'
| 15.5 | 33 | 0.763441 | 10 | 93 | 7.1 | 0.9 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.16129 | 93 | 5 | 34 | 18.6 | 0.910256 | 0 | 0 | 0 | 0 | 0 | 0.096774 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.333333 | 0 | 1 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 4 |
b6fb327db8c154c692dfe060ba586a924373f0a7 | 148 | py | Python | pycrostates/io/__init__.py | mscheltienne/pycrostates | be87adf69c94b2b179064f337acd8a49d01c305d | [
"BSD-3-Clause"
] | 1 | 2021-12-14T09:58:57.000Z | 2021-12-14T09:58:57.000Z | pycrostates/io/__init__.py | mscheltienne/pycrostates | be87adf69c94b2b179064f337acd8a49d01c305d | [
"BSD-3-Clause"
] | null | null | null | pycrostates/io/__init__.py | mscheltienne/pycrostates | be87adf69c94b2b179064f337acd8a49d01c305d | [
"BSD-3-Clause"
] | null | null | null | """IO module for reading and writing data."""
from .meas_info import ChInfo
from .reader import read_cluster
__all__ = ("ChInfo", "read_cluster")
| 21.142857 | 45 | 0.743243 | 21 | 148 | 4.904762 | 0.761905 | 0.213592 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.141892 | 148 | 6 | 46 | 24.666667 | 0.811024 | 0.263514 | 0 | 0 | 0 | 0 | 0.174757 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.666667 | 0 | 0.666667 | 0 | 1 | 0 | 0 | null | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 4 |
8e04e066816c9f446d78e0c3c4b6c53ecbc5492d | 357 | py | Python | src/opendr/perception/object_detection_3d/__init__.py | makistsantekidis/opendr | 07dee3b59d3487b9c5a93d6946317178a02c9890 | [
"Apache-2.0"
] | 217 | 2020-04-10T16:39:36.000Z | 2022-03-30T15:39:04.000Z | src/opendr/perception/object_detection_3d/__init__.py | makistsantekidis/opendr | 07dee3b59d3487b9c5a93d6946317178a02c9890 | [
"Apache-2.0"
] | 79 | 2021-06-23T10:40:10.000Z | 2021-12-16T07:59:42.000Z | src/opendr/perception/object_detection_3d/__init__.py | makistsantekidis/opendr | 07dee3b59d3487b9c5a93d6946317178a02c9890 | [
"Apache-2.0"
] | 29 | 2021-12-16T09:26:13.000Z | 2022-03-29T15:19:18.000Z | from opendr.perception.object_detection_3d.voxel_object_detection_3d.voxel_object_detection_3d_learner import \
VoxelObjectDetection3DLearner
from opendr.perception.object_detection_3d.datasets.kitti import KittiDataset, LabeledPointCloudsDatasetIterator
__all__ = ['VoxelObjectDetection3DLearner', 'KittiDataset', 'LabeledPointCloudsDatasetIterator']
| 59.5 | 112 | 0.885154 | 32 | 357 | 9.40625 | 0.46875 | 0.199336 | 0.225914 | 0.172757 | 0.392027 | 0.392027 | 0.202658 | 0 | 0 | 0 | 0 | 0.017804 | 0.056022 | 357 | 5 | 113 | 71.4 | 0.875371 | 0 | 0 | 0 | 0 | 0 | 0.207283 | 0.173669 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.5 | 0 | 0.5 | 0 | 0 | 0 | 0 | null | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 4 |
8e069a00b101dd4b1064cb41e1b1978fd8ea5306 | 979 | py | Python | examples/precedences/comparisonsPrecedence.py | danielNaczo/Python3Parser | 295279610a59b5535c9127db369af856f1b60d88 | [
"Apache-2.0"
] | 9 | 2019-11-08T20:56:21.000Z | 2022-01-02T18:07:06.000Z | examples/precedences/comparisonsPrecedence.py | danielNaczo/Python3Parser | 295279610a59b5535c9127db369af856f1b60d88 | [
"Apache-2.0"
] | 4 | 2019-11-08T20:55:25.000Z | 2021-12-23T20:26:09.000Z | examples/precedences/comparisonsPrecedence.py | danielNaczo/Python3Parser | 295279610a59b5535c9127db369af856f1b60d88 | [
"Apache-2.0"
] | 1 | 2019-11-26T22:06:19.000Z | 2019-11-26T22:06:19.000Z | def bool1(a, b, c, d):
return a < (b < (c < d))
def bool2(a, b):
return a < b
def bool3(a, b, c, d):
return a < b < c < d
def bool4(a, b, c, d):
return ((a < b) < c) < d
def bool5(a, b, c, d):
return a < b > c == d
def bool6(a, b, c):
return a + (b * c)
def bool7(a, b, c):
return a + (b - c)
def bool8(a, b, c):
return a + (b < c)
def bool9(a, b, c, d):
return ((a < b) + 4) == ((c + 5) < d)
def bool10(a, b, c, d):
return (a < b + 4) == ((c + 5) < d)
def bool11(a, b, c, d):
return a < b + 4 == ((c + 5) < d)
def bool12(a, b):
return a < b + 4
def bool13(a, b, c, d):
return a < b + 4 == c + 5 < d
def bool14(a, b, c, d):
return a < b + 4 == (c + 5 < d)
def bool15(a, b, c, d):
return (a < b + 4) == c + 5 < d
def bool16(a, b, c, d):
return (a <= b >= (c != d))
def bool17(a, b, c, d):
return a in b not in (c is d)
def bool18(a, b, c, d):
return (a is not b) >= (c + d)
| 13.788732 | 41 | 0.426966 | 203 | 979 | 2.059113 | 0.142857 | 0.162679 | 0.172249 | 0.172249 | 0.684211 | 0.636364 | 0.583732 | 0.583732 | 0.476077 | 0.476077 | 0 | 0.063291 | 0.354443 | 979 | 70 | 42 | 13.985714 | 0.598101 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.5 | false | 0 | 0 | 0.5 | 1 | 0 | 0 | 0 | 0 | null | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 4 |
8e06bbec862b6b986874d778253f82a55f6d2be0 | 141 | py | Python | microservices/accommodations/accommModel.py | rjb75/xplored | 7e3e491fa5f06fad29d83bc552cc158257bbb337 | [
"MIT"
] | null | null | null | microservices/accommodations/accommModel.py | rjb75/xplored | 7e3e491fa5f06fad29d83bc552cc158257bbb337 | [
"MIT"
] | null | null | null | microservices/accommodations/accommModel.py | rjb75/xplored | 7e3e491fa5f06fad29d83bc552cc158257bbb337 | [
"MIT"
] | null | null | null | from enum import Enum
class OrderByTypeModel(str, Enum):
popularity = "popularity"
price = "price"
review_score = "review_score" | 23.5 | 34 | 0.70922 | 16 | 141 | 6.125 | 0.625 | 0.22449 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.198582 | 141 | 6 | 35 | 23.5 | 0.867257 | 0 | 0 | 0 | 0 | 0 | 0.190141 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.2 | 0 | 1 | 0 | 1 | 0 | 0 | null | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 4 |
8e28e8977f230b2fb65406516ac06d9d4d363cc1 | 55 | py | Python | pyxb/bundles/opengis/citygml/landUse.py | eLBati/pyxb | 14737c23a125fd12c954823ad64fc4497816fae3 | [
"Apache-2.0"
] | 123 | 2015-01-12T06:43:22.000Z | 2022-03-20T18:06:46.000Z | pyxb/bundles/opengis/citygml/landUse.py | eLBati/pyxb | 14737c23a125fd12c954823ad64fc4497816fae3 | [
"Apache-2.0"
] | 103 | 2015-01-08T18:35:57.000Z | 2022-01-18T01:44:14.000Z | pyxb/bundles/opengis/citygml/landUse.py | eLBati/pyxb | 14737c23a125fd12c954823ad64fc4497816fae3 | [
"Apache-2.0"
] | 54 | 2015-02-15T17:12:00.000Z | 2022-03-07T23:02:32.000Z | from pyxb.bundles.opengis.citygml.raw.landUse import *
| 27.5 | 54 | 0.818182 | 8 | 55 | 5.625 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.072727 | 55 | 1 | 55 | 55 | 0.882353 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 4 |
f3e44ef77d05b2d8fa949a5c97019c7b282f9caf | 501 | py | Python | inventory/admin.py | wilmerm/unolet-2022 | 18119a9381b763e38c888bafdb7f97028bd80ea1 | [
"BSD-3-Clause"
] | null | null | null | inventory/admin.py | wilmerm/unolet-2022 | 18119a9381b763e38c888bafdb7f97028bd80ea1 | [
"BSD-3-Clause"
] | null | null | null | inventory/admin.py | wilmerm/unolet-2022 | 18119a9381b763e38c888bafdb7f97028bd80ea1 | [
"BSD-3-Clause"
] | null | null | null | from django.contrib import admin
from .models import (Item, ItemFamily, ItemGroup, Movement)
@admin.register(Item)
class ItemAdmin(admin.ModelAdmin):
pass #readonly_fields = ("company", "code")
@admin.register(ItemFamily)
class ItemFamilyAdmin(admin.ModelAdmin):
pass #readonly_fields = ("company",)
@admin.register(ItemGroup)
class ItemGroupAdmin(admin.ModelAdmin):
pass #readonly_fields = ("company",)
@admin.register(Movement)
class MovementAdmin(admin.ModelAdmin):
pass
| 19.269231 | 59 | 0.748503 | 54 | 501 | 6.888889 | 0.407407 | 0.139785 | 0.204301 | 0.217742 | 0.392473 | 0.392473 | 0.284946 | 0.284946 | 0 | 0 | 0 | 0 | 0.127745 | 501 | 25 | 60 | 20.04 | 0.851259 | 0.193613 | 0 | 0.285714 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0.285714 | 0.142857 | 0 | 0.428571 | 0 | 0 | 0 | 0 | null | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 4 |
f3ed8bc8c5b29d462d52297c11336c0a636f2d87 | 161 | py | Python | Scripts/django-admin.py | srishti-yadav/poetrydj | 4f108fb79dce2bb4d1ef56b1977bad3d447fac62 | [
"bzip2-1.0.6"
] | null | null | null | Scripts/django-admin.py | srishti-yadav/poetrydj | 4f108fb79dce2bb4d1ef56b1977bad3d447fac62 | [
"bzip2-1.0.6"
] | null | null | null | Scripts/django-admin.py | srishti-yadav/poetrydj | 4f108fb79dce2bb4d1ef56b1977bad3d447fac62 | [
"bzip2-1.0.6"
] | null | null | null | #!c:\users\srish\projects\dev\trydj\scripts\python.exe
from django.core import management
if __name__ == "__main__":
management.execute_from_command_line()
| 26.833333 | 54 | 0.782609 | 22 | 161 | 5.227273 | 0.909091 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.093168 | 161 | 5 | 55 | 32.2 | 0.787671 | 0.329193 | 0 | 0 | 0 | 0 | 0.074766 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 0.333333 | 0 | 0.333333 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 4 |
f3f09ae1e4789ecb423f296e6ce06d26a458457e | 97 | py | Python | Morpheus/Fornecedores/apps.py | tr0v40/Morpheus-API | 5a0b61303c8334b4030130998ffddc3fddc0ef10 | [
"MIT"
] | null | null | null | Morpheus/Fornecedores/apps.py | tr0v40/Morpheus-API | 5a0b61303c8334b4030130998ffddc3fddc0ef10 | [
"MIT"
] | null | null | null | Morpheus/Fornecedores/apps.py | tr0v40/Morpheus-API | 5a0b61303c8334b4030130998ffddc3fddc0ef10 | [
"MIT"
] | null | null | null | from django.apps import AppConfig
class FonecedoresConfig(AppConfig):
name = 'Fonecedores'
| 16.166667 | 35 | 0.773196 | 10 | 97 | 7.5 | 0.9 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.154639 | 97 | 5 | 36 | 19.4 | 0.914634 | 0 | 0 | 0 | 0 | 0 | 0.113402 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.333333 | 0 | 1 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 4 |
f3f4c3be99ee7403a6129edd79f854d75e1afacc | 77 | py | Python | New_file.py | rs-DOS/Notes-and-Notebooks | 258b226089936a055d30753b7a85d522891a8f0a | [
"MIT"
] | null | null | null | New_file.py | rs-DOS/Notes-and-Notebooks | 258b226089936a055d30753b7a85d522891a8f0a | [
"MIT"
] | null | null | null | New_file.py | rs-DOS/Notes-and-Notebooks | 258b226089936a055d30753b7a85d522891a8f0a | [
"MIT"
] | 1 | 2022-01-01T04:26:44.000Z | 2022-01-01T04:26:44.000Z | #This is a new python file to check if the commits are being pushed to GitHub | 77 | 77 | 0.792208 | 16 | 77 | 3.8125 | 0.9375 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.194805 | 77 | 1 | 77 | 77 | 0.983871 | 0.987013 | 0 | null | 0 | null | 0 | 0 | null | 0 | 0 | 0 | null | 1 | null | true | 0 | 0 | null | null | null | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 4 |
6d1b505be9933b9774a91d2e0c33238a9453e896 | 107 | py | Python | src/manim_revealjs/__init__.py | RickDW/revealjs_manim | 41cea864f41b00e2db4b008e1c4a660dc128d20f | [
"MIT"
] | 8 | 2021-11-01T13:16:30.000Z | 2022-03-26T15:17:51.000Z | src/manim_revealjs/__init__.py | RickDW/manim-revealjs | 41cea864f41b00e2db4b008e1c4a660dc128d20f | [
"MIT"
] | null | null | null | src/manim_revealjs/__init__.py | RickDW/manim-revealjs | 41cea864f41b00e2db4b008e1c4a660dc128d20f | [
"MIT"
] | null | null | null | from manim_revealjs.presentationscene import PresentationScene, NORMAL, LOOP, \
COMPLETE_LOOP, NO_PAUSE | 53.5 | 79 | 0.831776 | 12 | 107 | 7.166667 | 0.833333 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.11215 | 107 | 2 | 80 | 53.5 | 0.905263 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 0.5 | 0 | 0.5 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 4 |
6d3332d7c22e75a6dca258f050cf78de7395850d | 199 | py | Python | dev/tools/docs/quick_rebuild_html_brian2.py | chbehrens/brian2 | 46b5264caa5375ae13084508b5c1049e0c9e019e | [
"BSD-2-Clause"
] | 2 | 2020-03-20T13:30:19.000Z | 2020-03-20T13:30:57.000Z | dev/tools/docs/quick_rebuild_html_brian2.py | chbehrens/brian2 | 46b5264caa5375ae13084508b5c1049e0c9e019e | [
"BSD-2-Clause"
] | 13 | 2015-10-05T15:33:42.000Z | 2015-11-18T08:31:42.000Z | dev/tools/docs/quick_rebuild_html_brian2.py | moritzaugustin/brian2 | d98ea0cb4af0c9426e71c8ee7659ddb13aea8593 | [
"BSD-2-Clause"
] | null | null | null | import os
import shutil
import sphinx
import sys
os.environ['BRIAN2_DOCS_QUICK_REBUILD'] = '1'
os.chdir('../../../docs_sphinx')
sys.exit(sphinx.main(['sphinx-build', '-b', 'html', '.', '../docs']))
| 22.111111 | 69 | 0.658291 | 28 | 199 | 4.535714 | 0.607143 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.01105 | 0.090452 | 199 | 8 | 70 | 24.875 | 0.690608 | 0 | 0 | 0 | 0 | 0 | 0.361809 | 0.125628 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 0.571429 | 0 | 0.571429 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 4 |
ed9b3d09a8be2edce743e08aef1c9433a98caa62 | 54 | py | Python | lino_book/projects/watch/__init__.py | lino-framework/lino_book | 4eab916832cd8f48ff1b9fc8c2789f0b437da0f8 | [
"BSD-2-Clause"
] | 3 | 2016-08-25T05:58:09.000Z | 2019-12-05T11:13:45.000Z | lino_book/projects/watch/__init__.py | lino-framework/lino_book | 4eab916832cd8f48ff1b9fc8c2789f0b437da0f8 | [
"BSD-2-Clause"
] | 18 | 2016-11-12T21:38:58.000Z | 2019-12-03T17:54:38.000Z | lino_book/projects/watch/__init__.py | lino-framework/lino_book | 4eab916832cd8f48ff1b9fc8c2789f0b437da0f8 | [
"BSD-2-Clause"
] | 9 | 2016-10-15T11:12:33.000Z | 2021-09-22T04:37:37.000Z | """
A demo application used by :doc:`/dev/watch`.
"""
| 13.5 | 45 | 0.611111 | 8 | 54 | 4.125 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.148148 | 54 | 3 | 46 | 18 | 0.717391 | 0.833333 | 0 | null | 0 | null | 0 | 0 | null | 0 | 0 | 0 | null | 1 | null | true | 0 | 0 | null | null | null | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 4 |
ed9fa318bc8b1e422530f7294c897d1a98a11b15 | 523 | py | Python | utilities.py | weAllWeGot/CardiB_api | ab4526aa45d4b72a55a25726884d0fc6bb8628ab | [
"MIT"
] | 3 | 2020-04-21T22:47:44.000Z | 2021-01-13T11:23:18.000Z | utilities.py | weAllWeGot/CardiB_api | ab4526aa45d4b72a55a25726884d0fc6bb8628ab | [
"MIT"
] | 8 | 2017-07-28T03:12:35.000Z | 2017-08-01T05:07:34.000Z | utilities.py | weAllWeGot/CardiB_api | ab4526aa45d4b72a55a25726884d0fc6bb8628ab | [
"MIT"
] | null | null | null | """
A number of useful functions that are not central to the logic of the api itself.
"""
import re
def contains_curse(sometext):
"""
Checks a particular string to see if it contains any
NSFW type words. curse words, things innapropriate
that you might find in lyrics or quotes
:param sometext: some text
:type sometext: Str
:returns: a boolean stating whether we have a curse word or not
:rtype: Boolean
"""
return re.search(r'hoe*|bitch*|fag*|puss*|nigg*|fuck*|cunt*|shit*|dick*|cock*',sometext.lower())
| 24.904762 | 97 | 0.726577 | 84 | 523 | 4.511905 | 0.77381 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.170172 | 523 | 20 | 98 | 26.15 | 0.873272 | 0.680688 | 0 | 0 | 0 | 0 | 0.405594 | 0.405594 | 0 | 0 | 0 | 0 | 0 | 1 | 0.333333 | false | 0 | 0.333333 | 0 | 1 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 4 |
eddde10d5db60d86114a510e6844623c2ad78302 | 45 | py | Python | config.py | locational/fn-prevalence-predictor | d4df1dbf647c4fdfdc4f50b28f216e938c74c598 | [
"MIT"
] | null | null | null | config.py | locational/fn-prevalence-predictor | d4df1dbf647c4fdfdc4f50b28f216e938c74c598 | [
"MIT"
] | 1 | 2021-05-07T07:18:03.000Z | 2021-05-07T07:18:03.000Z | config.py | locational/fn-prevalence-predictor | d4df1dbf647c4fdfdc4f50b28f216e938c74c598 | [
"MIT"
] | null | null | null | import tempfile
TEMP = tempfile.mkdtemp()
| 7.5 | 25 | 0.733333 | 5 | 45 | 6.6 | 0.8 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.177778 | 45 | 5 | 26 | 9 | 0.891892 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.5 | 0 | 0.5 | 0 | 1 | 1 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 4 |
6101615cb089d4c94f36fbdd6f4e1dfc290f432b | 1,999 | py | Python | utils/boilerplate/test_bat.py | cfginn/sap-simulation-package | 73314e5380cec5c61a9fe5ff5fbafa25b9e2beac | [
"MIT"
] | null | null | null | utils/boilerplate/test_bat.py | cfginn/sap-simulation-package | 73314e5380cec5c61a9fe5ff5fbafa25b9e2beac | [
"MIT"
] | null | null | null | utils/boilerplate/test_bat.py | cfginn/sap-simulation-package | 73314e5380cec5c61a9fe5ff5fbafa25b9e2beac | [
"MIT"
] | null | null | null |
import unittest
from pysapets.bat import Bat
from pysapets.animal import Animal
import pysapets.constants as constants
from unittest.mock import patch
from io import StringIO
from copy import deepcopy
class BatTest(unittest.TestCase):
def setUp(self):
self.bat = Bat()
self.friends = [self.bat, Animal(2, 2), Animal(2, 2), Animal(2, 2), Animal(2, 2)]
# test that get_type returns the correct type
def test_get_type(self):
self.assertEqual(self.bat.get_type(), constants.BAT)
# test that bat starts with base health of 2
def test_get_health(self):
self.assertEqual(self.bat.get_health(), 2)
# test that bat starts with base attack of 1
def test_get_attack(self):
self.assertEqual(self.bat.get_attack(), 1)
# test that initializing bat with additional health increases health
def test_init_add_health(self):
newBat = Bat(addHealth = 3)
self.assertEqual(newBat.get_health(), 2 + 3)
# test that initializing an bat with additional attack increases attack
def test_init_add_attack(self):
newBat = Bat(addAttack = 3)
self.assertEqual(newBat.get_attack(), 1 + 3)
# test that initializing bat with additional health and attack increases health and attack
def test_init_add_health_attack(self):
newBat = Bat(addHealth = 3, addAttack = 3)
self.assertEqual(newBat.get_health(), 2 + 3)
self.assertEqual(newBat.get_attack(), 1 + 3)
# test that bat ability has correct trigger
def test_get_ability_trigger(self):
self.assertEqual(self.bat.get_ability_trigger(), constants.START_OF_BATTLE)
# test that bat ability has correct triggeredBy
def test_get_ability_triggeredBy(self):
self.assertEqual(self.bat.get_ability_triggeredBy(), constants.PLAYER)
# TODO add relevant tests for bat ability
def test_run_ability(self):
pass
def test_run_ability_level_1(self):
pass
def test_run_ability_level_2(self):
pass
def test_run_ability_level_3(self):
pass
| 29.835821 | 92 | 0.729865 | 295 | 1,999 | 4.776271 | 0.210169 | 0.059617 | 0.035486 | 0.081618 | 0.520227 | 0.441448 | 0.297374 | 0.12704 | 0.080908 | 0.058197 | 0 | 0.016575 | 0.185093 | 1,999 | 67 | 93 | 29.835821 | 0.848373 | 0.242121 | 0 | 0.205128 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.014925 | 0.230769 | 1 | 0.333333 | false | 0.102564 | 0.179487 | 0 | 0.538462 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 4 |
610c75d8185987a09251cb02fe7fae37c227b969 | 306 | py | Python | Modulo-03/ex107/ex107.py | Matheus-Henrique-Burey/Curso-de-Python | 448aebaab96527affa1e45897a662bb0407c11c6 | [
"MIT"
] | null | null | null | Modulo-03/ex107/ex107.py | Matheus-Henrique-Burey/Curso-de-Python | 448aebaab96527affa1e45897a662bb0407c11c6 | [
"MIT"
] | null | null | null | Modulo-03/ex107/ex107.py | Matheus-Henrique-Burey/Curso-de-Python | 448aebaab96527affa1e45897a662bb0407c11c6 | [
"MIT"
] | null | null | null | import moeda
preso = float(input('Digite um preço:R$ '))
print(f'O dobro de {preso} é R$ {moeda.dobro(preso)}')
print(f'A metade de {preso} é R$ {moeda.metade(preso)}')
print(f'Almentando 10% de {preso} é R$ {moeda.almentar(preso, 10)}')
print(f'Desconto de 10% {preso} é R$ {moeda.diminuir(preso, 10)}')
| 38.25 | 68 | 0.673203 | 55 | 306 | 3.745455 | 0.4 | 0.116505 | 0.135922 | 0.23301 | 0.203884 | 0 | 0 | 0 | 0 | 0 | 0 | 0.029963 | 0.127451 | 306 | 7 | 69 | 43.714286 | 0.741573 | 0 | 0 | 0 | 0 | 0 | 0.728758 | 0.212418 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.166667 | 0 | 0.166667 | 0.666667 | 0 | 0 | 0 | null | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 4 |
b63729574ecbb04311a2d6eaa2a8937c163fef04 | 1,566 | py | Python | tensorflow/contrib/ffmpeg/__init__.py | ln0119/tensorflow-fast-rcnn | e937e6394818c9a320754237651d7fe083b1020d | [
"Apache-2.0"
] | 73 | 2017-01-05T09:06:08.000Z | 2021-11-06T14:00:50.000Z | tensorflow/contrib/ffmpeg/__init__.py | minhhoai2/tensorflow | da88903d5e29230d68d861053aa1dea1432c0696 | [
"Apache-2.0"
] | 8 | 2017-04-10T10:36:20.000Z | 2021-02-07T01:02:32.000Z | tensorflow/contrib/ffmpeg/__init__.py | minhhoai2/tensorflow | da88903d5e29230d68d861053aa1dea1432c0696 | [
"Apache-2.0"
] | 151 | 2016-11-10T09:01:15.000Z | 2022-01-18T08:13:49.000Z | # Copyright 2015 Google Inc. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ==============================================================================
# pylint: disable=g-short-docstring-punctuation
"""## Encoding and decoding audio using FFmpeg
TensorFlow provides Ops to decode and encode audio files using the
[FFmpeg](https://www.ffmpeg.org/) library. FFmpeg must be
locally [installed](https://ffmpeg.org/download.html) for these Ops to succeed.
Example:
```python
from tensorflow.contrib import ffmpeg
audio_binary = tf.read_file('song.mp3')
waveform = ffmpeg.decode_audio(
audio_binary, file_format='mp3', samples_per_second=44100, channel_count=2)
uncompressed_binary = ffmpeg.encode_audio(
waveform, file_format='wav', samples_per_second=44100)
```
@@decode_audio
@@encode_audio
"""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from tensorflow.contrib.ffmpeg.ffmpeg_ops import decode_audio
from tensorflow.contrib.ffmpeg.ffmpeg_ops import encode_audio
| 35.590909 | 80 | 0.745211 | 216 | 1,566 | 5.25 | 0.546296 | 0.05291 | 0.055556 | 0.028219 | 0.074074 | 0.074074 | 0.074074 | 0 | 0 | 0 | 0 | 0.015351 | 0.126437 | 1,566 | 43 | 81 | 36.418605 | 0.813596 | 0.826309 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0.2 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 4 |
b638b1294f4202f83e47ee60ec050a283f882de4 | 52 | py | Python | clients/python-aiohttp/generated/openapi_server/models/__init__.py | cliffano/pokeapi-clients | 92af296c68c3e94afac52642ae22057faaf071ee | [
"MIT"
] | null | null | null | clients/python-aiohttp/generated/openapi_server/models/__init__.py | cliffano/pokeapi-clients | 92af296c68c3e94afac52642ae22057faaf071ee | [
"MIT"
] | null | null | null | clients/python-aiohttp/generated/openapi_server/models/__init__.py | cliffano/pokeapi-clients | 92af296c68c3e94afac52642ae22057faaf071ee | [
"MIT"
] | null | null | null | # coding: utf-8
# import models into model package
| 13 | 34 | 0.730769 | 8 | 52 | 4.75 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.02381 | 0.192308 | 52 | 3 | 35 | 17.333333 | 0.880952 | 0.884615 | 0 | null | 0 | null | 0 | 0 | null | 0 | 0 | 0 | null | 1 | null | true | 0 | 0 | null | null | null | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 4 |
b63e049450159e0d3ecf17805c5708cc65e86904 | 126 | py | Python | src/main.py | Kladdkaka/flashback-scraper | ead4705f5c06e2124cda835501f12e139246cc25 | [
"MIT"
] | null | null | null | src/main.py | Kladdkaka/flashback-scraper | ead4705f5c06e2124cda835501f12e139246cc25 | [
"MIT"
] | null | null | null | src/main.py | Kladdkaka/flashback-scraper | ead4705f5c06e2124cda835501f12e139246cc25 | [
"MIT"
] | null | null | null | import typer
import scrape
app = typer.Typer()
app.add_typer(scrape.app, name="scrape")
if __name__ == "__main__":
app() | 15.75 | 40 | 0.698413 | 18 | 126 | 4.388889 | 0.444444 | 0.227848 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.150794 | 126 | 8 | 41 | 15.75 | 0.738318 | 0 | 0 | 0 | 0 | 0 | 0.110236 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.333333 | 0 | 0.333333 | 0 | 1 | 0 | 0 | null | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 4 |
b648299e1758f000bd967e3c304e42c256e94e3e | 202 | py | Python | Mundo 1/ex012.py | Alef-Martins/Exercicios_python_mundo-1 | df93c4a9d0e9f9fbfeaf85863c4597c92d3c703c | [
"MIT"
] | null | null | null | Mundo 1/ex012.py | Alef-Martins/Exercicios_python_mundo-1 | df93c4a9d0e9f9fbfeaf85863c4597c92d3c703c | [
"MIT"
] | null | null | null | Mundo 1/ex012.py | Alef-Martins/Exercicios_python_mundo-1 | df93c4a9d0e9f9fbfeaf85863c4597c92d3c703c | [
"MIT"
] | null | null | null | #Leia o preço de um produto e mostre seu novo preço com 5% de desconto
preco = float(input("informe o valor do produto: "))
print(f'O valor do produto com 5% de desconto é {preco - (preco * 5 /100)}') | 67.333333 | 76 | 0.69802 | 38 | 202 | 3.710526 | 0.605263 | 0.056738 | 0.085106 | 0.198582 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.03681 | 0.193069 | 202 | 3 | 76 | 67.333333 | 0.828221 | 0.341584 | 0 | 0 | 0 | 0 | 0.717557 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0 | 0 | 0 | 0.5 | 0 | 0 | 0 | null | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 4 |
b66570df107fac1fbd2724600454c3ae7bb2e539 | 585 | py | Python | test/main.py | petmo338/ignitioncontrol | 7b8a83c9f30aa5a69e04f23cb190a61d3002656b | [
"Apache-2.0"
] | 1 | 2016-01-05T17:51:40.000Z | 2016-01-05T17:51:40.000Z | test/main.py | petmo338/ignitioncontrol | 7b8a83c9f30aa5a69e04f23cb190a61d3002656b | [
"Apache-2.0"
] | null | null | null | test/main.py | petmo338/ignitioncontrol | 7b8a83c9f30aa5a69e04f23cb190a61d3002656b | [
"Apache-2.0"
] | 2 | 2018-07-03T17:51:22.000Z | 2021-02-05T17:23:13.000Z | # main.py -- put your code here!
from pyb import udelay, Pin
pin = Pin('X1', pyb.Pin.OUT_PP)
HIGHTIME = 6000
POSTIME = 1000
LOWTIME = 800
while True:
pyb.udelay(HIGHTIME)
pin.low()
pyb.udelay(LOWTIME)
pin.high()
pyb.udelay(POSTIME)
pin.low()
pyb.udelay(LOWTIME)
pin.high()
pyb.udelay(HIGHTIME - POSTIME - LOWTIME)
pin.low()
pyb.udelay(LOWTIME)
pin.high()
pyb.udelay(HIGHTIME)
pin.low()
pyb.udelay(LOWTIME)
pin.high()
pyb.udelay(HIGHTIME)
pin.low()
pyb.udelay(LOWTIME)
pin.high()
| 17.205882 | 44 | 0.594872 | 78 | 585 | 4.448718 | 0.307692 | 0.259366 | 0.129683 | 0.216138 | 0.639769 | 0.639769 | 0.639769 | 0.639769 | 0.639769 | 0.639769 | 0 | 0.028037 | 0.268376 | 585 | 34 | 45 | 17.205882 | 0.78271 | 0.051282 | 0 | 0.692308 | 0 | 0 | 0.00361 | 0 | 0 | 0 | 0 | 0.029412 | 0 | 1 | 0 | false | 0 | 0.038462 | 0 | 0.038462 | 0 | 0 | 0 | 0 | null | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 4 |
b66bed9e0c1620e6a1c93da57cc6f4a5d5f43763 | 311 | py | Python | firstfloor/admin.py | terratenff/jros-behz | 2a41adb1d07f76a0409669b26a47a8e444273b59 | [
"MIT"
] | null | null | null | firstfloor/admin.py | terratenff/jros-behz | 2a41adb1d07f76a0409669b26a47a8e444273b59 | [
"MIT"
] | 5 | 2021-03-30T12:26:54.000Z | 2021-09-22T17:57:00.000Z | firstfloor/admin.py | terratenff/jros-behz | 2a41adb1d07f76a0409669b26a47a8e444273b59 | [
"MIT"
] | null | null | null | from django.contrib import admin
from .models import Profile, FriendRequest, Comment, Discussion, DiscussionGroup, Event
admin.site.register(Profile)
admin.site.register(FriendRequest)
admin.site.register(Comment)
admin.site.register(Discussion)
admin.site.register(DiscussionGroup)
admin.site.register(Event)
| 31.1 | 87 | 0.836013 | 38 | 311 | 6.842105 | 0.368421 | 0.207692 | 0.392308 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.064309 | 311 | 9 | 88 | 34.555556 | 0.893471 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 0.25 | 0 | 0.25 | 0 | 0 | 0 | 0 | null | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 4 |
b6864ace85e04c5f83fa073f92d369ebaee3b58a | 89 | py | Python | config/local.py | Stephan-e/CSR-tracker | 780ce4c4d4f96a499803b25b3cc9869cfb275566 | [
"MIT"
] | null | null | null | config/local.py | Stephan-e/CSR-tracker | 780ce4c4d4f96a499803b25b3cc9869cfb275566 | [
"MIT"
] | null | null | null | config/local.py | Stephan-e/CSR-tracker | 780ce4c4d4f96a499803b25b3cc9869cfb275566 | [
"MIT"
] | null | null | null | def show_toolbar(request):
if request.is_ajax():
return False
return True | 22.25 | 26 | 0.662921 | 12 | 89 | 4.75 | 0.833333 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.258427 | 89 | 4 | 27 | 22.25 | 0.863636 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.25 | false | 0 | 0 | 0 | 0.75 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 4 |
b6869ab9206c1261b4b878fa05899234090a6962 | 243 | py | Python | model/case/mysql_case.py | waaaaaaz/TestRelay2 | 220d85fb0f53e468c5216336147609d5337cfb1c | [
"MIT"
] | null | null | null | model/case/mysql_case.py | waaaaaaz/TestRelay2 | 220d85fb0f53e468c5216336147609d5337cfb1c | [
"MIT"
] | 1 | 2021-06-02T02:40:03.000Z | 2021-06-02T02:40:03.000Z | model/case/mysql_case.py | waaaaaaz/TestRelay2 | 220d85fb0f53e468c5216336147609d5337cfb1c | [
"MIT"
] | null | null | null | # coding: utf-8
from base import Base
class MySQLCase(Base):
def __init__(self, case_unit, params):
super(MySQLCase, self).__init__(case_unit, params)
def exe(self):
pass
def get_params(self):
pass
| 12.789474 | 58 | 0.625514 | 32 | 243 | 4.40625 | 0.5625 | 0.113475 | 0.198582 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.005682 | 0.27572 | 243 | 18 | 59 | 13.5 | 0.795455 | 0.053498 | 0 | 0.25 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.375 | false | 0.25 | 0.125 | 0 | 0.625 | 0 | 0 | 0 | 0 | null | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 4 |
b68809944a43b6b5cf6ad319de29ebdbcbd7a65f | 159 | py | Python | django/tests/regressiontests/templates/views.py | jonaustin/advisoryscan | ba452c155f0d478450e0c91de5ea00f404e98616 | [
"MIT"
] | 2 | 2015-12-04T12:05:26.000Z | 2016-05-08T11:26:55.000Z | lib/django/tests/regressiontests/templates/views.py | Arachnid/google_appengine | 2e950619f5027f414131fafc3cc253af4875a0fe | [
"Apache-2.0"
] | null | null | null | lib/django/tests/regressiontests/templates/views.py | Arachnid/google_appengine | 2e950619f5027f414131fafc3cc253af4875a0fe | [
"Apache-2.0"
] | 1 | 2018-12-06T12:50:52.000Z | 2018-12-06T12:50:52.000Z | # Fake views for testing url reverse lookup
def index(request):
pass
def client(request, id):
pass
def client_action(request, id, action):
pass
| 14.454545 | 43 | 0.698113 | 23 | 159 | 4.782609 | 0.608696 | 0.127273 | 0.236364 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.220126 | 159 | 10 | 44 | 15.9 | 0.887097 | 0.257862 | 0 | 0.5 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.5 | false | 0.5 | 0 | 0 | 0.5 | 0 | 1 | 0 | 0 | null | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 4 |
b69784aee5558d0d2b97a626ef28c8d1e05c5c1c | 222 | py | Python | loren/parsers/json_parser.py | arap/loren | 3ce2f991039364371322eb69f157d1a088764e7a | [
"MIT"
] | 5 | 2021-09-24T12:22:12.000Z | 2022-03-11T10:28:11.000Z | loren/parsers/json_parser.py | arap/loren | 3ce2f991039364371322eb69f157d1a088764e7a | [
"MIT"
] | 4 | 2021-12-21T11:57:49.000Z | 2022-01-26T11:07:06.000Z | loren/parsers/json_parser.py | arap/loren | 3ce2f991039364371322eb69f157d1a088764e7a | [
"MIT"
] | 3 | 2021-09-27T08:29:21.000Z | 2021-10-08T14:14:00.000Z | import json
from typing import Dict, Any
from .base_parser import BaseParser
class JSONParser(BaseParser):
@staticmethod
def parse(file_contents: str) -> Dict[str, Any]:
return json.loads(file_contents)
| 20.181818 | 52 | 0.734234 | 29 | 222 | 5.517241 | 0.655172 | 0.15 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.184685 | 222 | 10 | 53 | 22.2 | 0.883978 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.142857 | false | 0 | 0.428571 | 0.142857 | 0.857143 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 4 |
fcb007af58ae907f07e57f965abbf3115f457e91 | 97 | py | Python | ifstools/__init__.py | mon/ifstools | cfcb369a0271d6c53df38b769c496ca8149d9a51 | [
"MIT"
] | 72 | 2017-12-15T17:47:38.000Z | 2022-03-27T05:57:55.000Z | ifstools/__init__.py | mon/ifstools | cfcb369a0271d6c53df38b769c496ca8149d9a51 | [
"MIT"
] | 19 | 2017-12-19T04:43:08.000Z | 2020-12-14T10:44:34.000Z | ifstools/__init__.py | mon/ifstools | cfcb369a0271d6c53df38b769c496ca8149d9a51 | [
"MIT"
] | 14 | 2017-12-15T20:43:14.000Z | 2020-12-29T22:07:47.000Z | from .ifstools import main
from .ifs import IFS
from .handlers import GenericFolder, GenericFile
| 24.25 | 48 | 0.824742 | 13 | 97 | 6.153846 | 0.615385 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.134021 | 97 | 3 | 49 | 32.333333 | 0.952381 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 4 |
fcbc0ddce5dff36777acb677abf73853073ce053 | 18,979 | py | Python | tests/test_data_types.py | mstump/mashumaro | 36fd948aead45e5509ea0ea04746a8906d4c5822 | [
"Apache-2.0"
] | null | null | null | tests/test_data_types.py | mstump/mashumaro | 36fd948aead45e5509ea0ea04746a8906d4c5822 | [
"Apache-2.0"
] | null | null | null | tests/test_data_types.py | mstump/mashumaro | 36fd948aead45e5509ea0ea04746a8906d4c5822 | [
"Apache-2.0"
] | null | null | null | import uuid
import collections
from enum import Enum
from datetime import datetime, date, time, timedelta
from dataclasses import dataclass
from queue import Queue
from typing import (
Hashable,
List,
Deque,
Tuple,
Set,
FrozenSet,
MutableSet,
ChainMap,
Dict,
Mapping,
MutableMapping,
Sequence,
Optional,
Any,
AnyStr,
Union,
TypeVar,
)
from mashumaro import DataClassDictMixin
from mashumaro.exceptions import UnserializableField, UnserializableDataError,\
MissingField
from .utils import same_types
from .entities import (
MyEnum,
MyIntEnum,
MyFlag,
MyIntFlag,
MyDataClass,
)
import pytest
class Fixture:
INT = 123
FLOAT = 1.23
BOOL = True
LIST = [1, 2, 3]
TUPLE = (1, 2, 3)
DEQUE = collections.deque([1, 2, 3])
SET = {1, 2, 3}
FROZEN_SET = frozenset([1, 2, 3])
CHAIN_MAP = collections.ChainMap({'a': 1, 'b': 2}, {'c': 3, 'd': 4})
MAPS_LIST = [{'a': 1, 'b': 2}, {'c': 3, 'd': 4}]
DICT = {'a': 1, 'b': 2}
BYTES = b'123'
BYTES_BASE64 = 'MTIz\n'
BYTE_ARRAY = bytearray(b'123')
STR = '123'
ENUM = MyEnum.a
INT_ENUM = MyIntEnum.a
FLAG = MyFlag.a
INT_FLAG = MyIntFlag.a
DATA_CLASS = MyDataClass(a=1, b=2)
NONE = None
DATETIME = datetime(2018, 10, 29, 12, 46, 55, 308495)
DATE = DATETIME.date()
TIME = DATETIME.time()
TIMEDELTA = timedelta(3.14159265358979323846)
UUID = uuid.UUID('3c25dd74-f208-46a2-9606-dd3919e975b7')
UUID_STR = '3c25dd74-f208-46a2-9606-dd3919e975b7'
inner_values = [
(int, Fixture.INT, Fixture.INT),
(float, Fixture.FLOAT, Fixture.FLOAT),
(bool, Fixture.BOOL, Fixture.BOOL),
(List[int], Fixture.LIST, Fixture.LIST),
(Deque[int], Fixture.DEQUE, Fixture.LIST),
(Tuple[int], Fixture.TUPLE, Fixture.LIST),
(Set[int], Fixture.SET, Fixture.LIST),
(FrozenSet[int], Fixture.FROZEN_SET, Fixture.LIST),
(ChainMap[str, int], Fixture.CHAIN_MAP, Fixture.MAPS_LIST),
(Dict[str, int], Fixture.DICT, Fixture.DICT),
(Mapping[str, int], Fixture.DICT, Fixture.DICT),
(MutableMapping[str, int], Fixture.DICT, Fixture.DICT),
(Sequence[int], Fixture.LIST, Fixture.LIST),
(bytes, Fixture.BYTES, Fixture.BYTES),
(bytearray, Fixture.BYTE_ARRAY, Fixture.BYTE_ARRAY),
(str, Fixture.STR, Fixture.STR),
(MyEnum, Fixture.ENUM, Fixture.ENUM),
(MyIntEnum, Fixture.INT_ENUM, Fixture.INT_ENUM),
(MyFlag, Fixture.FLAG, Fixture.FLAG),
(MyIntFlag, Fixture.INT_FLAG, Fixture.INT_FLAG),
(MyDataClass, Fixture.DATA_CLASS, Fixture.DICT),
(type(None), Fixture.NONE, Fixture.NONE),
(datetime, Fixture.DATETIME, Fixture.DATETIME),
(date, Fixture.DATE, Fixture.DATE),
(time, Fixture.TIME, Fixture.TIME),
(timedelta, Fixture.TIMEDELTA, Fixture.TIMEDELTA.total_seconds()),
(uuid.UUID, Fixture.UUID, Fixture.UUID_STR),
]
hashable_inner_values = [
(type_, value, value_dumped) for type_, value, value_dumped in inner_values
if isinstance(value, Hashable) and isinstance(value_dumped, Hashable)
]
generic_sequence_types = [List, Deque, Tuple, Set, FrozenSet]
generic_mapping_types = [Dict, Mapping, MutableMapping]
unsupported_field_types = [
list, collections.deque, tuple, set, frozenset,
collections.ChainMap, dict, Queue]
T = TypeVar('T', int, str)
unsupported_typing_primitives = [AnyStr, Union[int, str], T]
x_factory_mapping = {
List: list,
Deque: collections.deque,
Tuple: tuple,
Set: set,
FrozenSet: frozenset,
MutableSet: set,
Dict: lambda items: {k: v for k, v in items},
Mapping: lambda items: {k: v for k, v in items},
MutableMapping: lambda items: {k: v for k, v in items},
ChainMap: lambda items: collections.ChainMap(*({k: v} for k, v in items))
}
# noinspection PyCallingNonCallable
def check_one_arg_generic(type_, value_info, use_bytes, use_enum, use_datetime):
x_type, x_value, x_value_dumped = value_info
@dataclass
class DataClass(DataClassDictMixin):
x: type_[x_type]
x_factory = x_factory_mapping[type_]
x = x_factory([x_value for _ in range(3)])
instance = DataClass(x)
if x_value_dumped is Fixture.BYTES:
v_dumped = Fixture.BYTES if use_bytes else Fixture.BYTES_BASE64
elif x_value_dumped is Fixture.BYTE_ARRAY:
v_dumped = Fixture.BYTE_ARRAY if use_bytes else Fixture.BYTES_BASE64
elif isinstance(x_value_dumped, Enum):
v_dumped = x_value_dumped if use_enum else x_value_dumped.value
elif isinstance(x_value_dumped, (datetime, date, time)):
v_dumped = x_value_dumped if use_datetime \
else x_value_dumped.isoformat()
else:
v_dumped = x_value_dumped
dumped = {'x': list(x_factory([v_dumped for _ in range(3)]))}
instance_dumped = instance.to_dict(
use_bytes=use_bytes,
use_enum=use_enum,
use_datetime=use_datetime
)
instance_loaded = DataClass.from_dict(
dumped,
use_bytes=use_bytes,
use_enum=use_enum,
use_datetime=use_datetime
)
assert instance_dumped == dumped
assert instance_loaded == instance
instance_dumped = instance.to_dict(
use_bytes=use_bytes,
use_enum=use_enum,
use_datetime=use_datetime
)
instance_loaded = DataClass.from_dict(
dumped,
use_bytes=use_bytes,
use_enum=use_enum,
use_datetime=use_datetime
)
assert same_types(instance_dumped, dumped)
assert same_types(instance_loaded.x, x)
# noinspection PyCallingNonCallable
def check_two_args_generic(type_, key_info, value_info, use_bytes, use_enum,
use_datetime):
k_type, k_value, k_value_dumped = key_info
v_type, v_value, v_value_dumped = value_info
@dataclass
class DataClass(DataClassDictMixin):
x: type_[k_type, v_type]
x_factory = x_factory_mapping[type_]
x = x_factory([(k_value, v_value) for _ in range(3)])
instance = DataClass(x)
if k_value_dumped is Fixture.BYTES:
k_dumped = Fixture.BYTES if use_bytes else Fixture.BYTES_BASE64
# Fixture.BYTE_ARRAY is not hashable
# elif k_value_dumped is Fixture.BYTE_ARRAY:
# k_dumped = Fixture.BYTE_ARRAY if use_bytes else Fixture.BYTES_BASE64
elif isinstance(k_value_dumped, Enum):
k_dumped = k_value_dumped if use_enum else k_value_dumped.value
elif isinstance(k_value_dumped, (datetime, date, time)):
k_dumped = k_value_dumped if use_datetime \
else k_value_dumped.isoformat()
else:
k_dumped = k_value_dumped
if v_value_dumped is Fixture.BYTES:
v_dumped = Fixture.BYTES if use_bytes else Fixture.BYTES_BASE64
elif v_value_dumped is Fixture.BYTE_ARRAY:
v_dumped = Fixture.BYTE_ARRAY if use_bytes else Fixture.BYTES_BASE64
elif isinstance(v_value_dumped, Enum):
v_dumped = v_value_dumped if use_enum else v_value_dumped.value
elif isinstance(v_value_dumped, (datetime, date, time)):
v_dumped = v_value_dumped if use_datetime \
else v_value_dumped.isoformat()
else:
v_dumped = v_value_dumped
if type_ is ChainMap:
dumped = {'x': x_factory([(k_dumped, v_dumped) for _ in range(3)]).maps}
else:
dumped = {'x': x_factory([(k_dumped, v_dumped) for _ in range(3)])}
instance_dumped = instance.to_dict(
use_bytes=use_bytes,
use_enum=use_enum,
use_datetime=use_datetime
)
instance_loaded = DataClass.from_dict(
dumped,
use_bytes=use_bytes,
use_enum=use_enum,
use_datetime=use_datetime
)
assert instance_dumped == dumped
assert instance_loaded == instance
instance_dumped = instance.to_dict(
use_bytes=use_bytes,
use_enum=use_enum,
use_datetime=use_datetime
)
instance_loaded = DataClass.from_dict(
dumped,
use_bytes=use_bytes,
use_enum=use_enum,
use_datetime=use_datetime
)
assert same_types(instance_dumped, dumped)
assert same_types(instance_loaded.x, x)
@pytest.mark.parametrize('use_datetime', [True, False])
@pytest.mark.parametrize('use_enum', [True, False])
@pytest.mark.parametrize('use_bytes', [True, False])
@pytest.mark.parametrize('value_info', inner_values)
def test_one_level(value_info, use_bytes, use_enum, use_datetime):
x_type, x_value, x_value_dumped = value_info
@dataclass
class DataClass(DataClassDictMixin):
x: x_type
instance = DataClass(x_value)
if x_value_dumped is Fixture.BYTES:
v_dumped = Fixture.BYTES if use_bytes else Fixture.BYTES_BASE64
elif x_value_dumped is Fixture.BYTE_ARRAY:
v_dumped = Fixture.BYTE_ARRAY if use_bytes else Fixture.BYTES_BASE64
elif isinstance(x_value_dumped, Enum):
v_dumped = x_value_dumped if use_enum else x_value_dumped.value
elif isinstance(x_value_dumped, (datetime, date, time)):
v_dumped = x_value_dumped if use_datetime \
else x_value_dumped.isoformat()
else:
v_dumped = x_value_dumped
dumped = {'x': v_dumped}
instance_dumped = instance.to_dict(
use_bytes=use_bytes,
use_enum=use_enum,
use_datetime=use_datetime
)
instance_loaded = DataClass.from_dict(
dumped,
use_bytes=use_bytes,
use_enum=use_enum,
use_datetime=use_datetime
)
assert instance_dumped == dumped
assert instance_loaded == instance
instance_dumped = instance.to_dict(
use_bytes=use_bytes,
use_enum=use_enum,
use_datetime=use_datetime
)
instance_loaded = DataClass.from_dict(
dumped,
use_bytes=use_bytes,
use_enum=use_enum,
use_datetime=use_datetime
)
assert same_types(instance_dumped, dumped)
assert same_types(instance_loaded.x, x_value)
@pytest.mark.parametrize('use_datetime', [True, False])
@pytest.mark.parametrize('use_enum', [True, False])
@pytest.mark.parametrize('use_bytes', [True, False])
@pytest.mark.parametrize('value_info', inner_values)
def test_with_generic_list(value_info, use_bytes, use_enum, use_datetime):
check_one_arg_generic(List, value_info, use_bytes, use_enum, use_datetime)
@pytest.mark.parametrize('use_datetime', [True, False])
@pytest.mark.parametrize('use_enum', [True, False])
@pytest.mark.parametrize('use_bytes', [True, False])
@pytest.mark.parametrize('value_info', inner_values)
def test_with_generic_deque(value_info, use_bytes, use_enum, use_datetime):
check_one_arg_generic(Deque, value_info, use_bytes, use_enum, use_datetime)
@pytest.mark.parametrize('use_datetime', [True, False])
@pytest.mark.parametrize('use_enum', [True, False])
@pytest.mark.parametrize('use_bytes', [True, False])
@pytest.mark.parametrize('value_info', inner_values)
def test_with_generic_tuple(value_info, use_bytes, use_enum, use_datetime):
check_one_arg_generic(Tuple, value_info, use_bytes, use_enum, use_datetime)
@pytest.mark.parametrize('use_datetime', [True, False])
@pytest.mark.parametrize('use_enum', [True, False])
@pytest.mark.parametrize('use_bytes', [True, False])
@pytest.mark.parametrize('value_info', hashable_inner_values)
def test_with_generic_set(value_info, use_bytes, use_enum, use_datetime):
check_one_arg_generic(Set, value_info, use_bytes, use_enum, use_datetime)
@pytest.mark.parametrize('use_datetime', [True, False])
@pytest.mark.parametrize('use_enum', [True, False])
@pytest.mark.parametrize('use_bytes', [True, False])
@pytest.mark.parametrize('value_info', hashable_inner_values)
def test_with_generic_frozenset(value_info, use_bytes, use_enum, use_datetime):
check_one_arg_generic(
FrozenSet, value_info, use_bytes, use_enum, use_datetime)
@pytest.mark.parametrize('use_datetime', [True, False])
@pytest.mark.parametrize('use_enum', [True, False])
@pytest.mark.parametrize('use_bytes', [True, False])
@pytest.mark.parametrize('value_info', hashable_inner_values)
def test_with_generic_mutable_set(
value_info, use_bytes, use_enum, use_datetime):
check_one_arg_generic(
MutableSet, value_info, use_bytes, use_enum, use_datetime)
@pytest.mark.parametrize('use_datetime', [True, False])
@pytest.mark.parametrize('use_enum', [True, False])
@pytest.mark.parametrize('use_bytes', [True, False])
@pytest.mark.parametrize('value_info', inner_values)
@pytest.mark.parametrize('key_info', hashable_inner_values)
def test_with_generic_dict(
key_info, value_info, use_bytes, use_enum, use_datetime):
check_two_args_generic(
Dict, key_info, value_info, use_bytes, use_enum, use_datetime)
@pytest.mark.parametrize('use_datetime', [True, False])
@pytest.mark.parametrize('use_enum', [True, False])
@pytest.mark.parametrize('use_bytes', [True, False])
@pytest.mark.parametrize('value_info', inner_values)
@pytest.mark.parametrize('key_info', hashable_inner_values)
def test_with_generic_mapping(
key_info, value_info, use_bytes, use_enum, use_datetime):
check_two_args_generic(
Mapping, key_info, value_info, use_bytes, use_enum, use_datetime)
@pytest.mark.parametrize('use_datetime', [True, False])
@pytest.mark.parametrize('use_enum', [True, False])
@pytest.mark.parametrize('use_bytes', [True, False])
@pytest.mark.parametrize('value_info', inner_values)
@pytest.mark.parametrize('key_info', hashable_inner_values)
def test_with_generic_mutable_mapping(
key_info, value_info, use_bytes, use_enum, use_datetime):
check_two_args_generic(
MutableMapping, key_info, value_info, use_bytes, use_enum, use_datetime)
@pytest.mark.parametrize('use_datetime', [True, False])
@pytest.mark.parametrize('use_enum', [True, False])
@pytest.mark.parametrize('use_bytes', [True, False])
@pytest.mark.parametrize('value_info', inner_values)
@pytest.mark.parametrize('key_info', hashable_inner_values)
def test_with_generic_chain_map(
key_info, value_info, use_bytes, use_enum, use_datetime):
check_two_args_generic(
ChainMap, key_info, value_info, use_bytes, use_enum, use_datetime)
@pytest.mark.parametrize('x_type', unsupported_field_types)
@pytest.mark.parametrize('generic_type', generic_sequence_types)
def test_unsupported_generic_field_types(x_type, generic_type):
with pytest.raises(UnserializableField):
@dataclass
class _(DataClassDictMixin):
# noinspection PyTypeChecker
x: generic_type[x_type]
@pytest.mark.parametrize('x_type', unsupported_typing_primitives)
@pytest.mark.parametrize('generic_type', generic_sequence_types)
def test_unsupported_generic_typing_primitives(x_type, generic_type):
with pytest.raises(UnserializableDataError):
@dataclass
class _(DataClassDictMixin):
# noinspection PyTypeChecker
x: generic_type[x_type]
@pytest.mark.parametrize('x_type', unsupported_field_types)
def test_unsupported_field_types(x_type):
with pytest.raises(UnserializableField):
@dataclass
class _(DataClassDictMixin):
x: x_type
@pytest.mark.parametrize('x_type', unsupported_typing_primitives)
def test_unsupported_typing_primitives(x_type):
with pytest.raises(UnserializableDataError):
@dataclass
class _(DataClassDictMixin):
x: x_type
@pytest.mark.parametrize('generic_type', generic_mapping_types)
def test_data_class_as_mapping_key(generic_type):
@dataclass
class Key(DataClassDictMixin):
pass
with pytest.raises(UnserializableDataError):
@dataclass
class _(DataClassDictMixin):
x: generic_type[Key, int]
def test_data_class_as_chain_map_key():
@dataclass
class Key(DataClassDictMixin):
pass
with pytest.raises(UnserializableDataError):
@dataclass
class _(DataClassDictMixin):
x: ChainMap[Key, int]
@pytest.mark.parametrize('use_datetime', [True, False])
@pytest.mark.parametrize('use_enum', [True, False])
@pytest.mark.parametrize('use_bytes', [True, False])
@pytest.mark.parametrize('value_info', inner_values)
def test_with_any(value_info, use_bytes, use_enum, use_datetime):
@dataclass
class DataClass(DataClassDictMixin):
x: Any
x = value_info[1]
dumped = {'x': x}
instance = DataClass(x)
instance_dumped = instance.to_dict(
use_bytes=use_bytes,
use_enum=use_enum,
use_datetime=use_datetime
)
instance_loaded = DataClass.from_dict(
dumped,
use_bytes=use_bytes,
use_enum=use_enum,
use_datetime=use_datetime
)
assert instance_dumped == dumped
assert instance_loaded == instance
assert same_types(instance_dumped, dumped)
assert same_types(instance_loaded.x, x)
@pytest.mark.parametrize('use_datetime', [True, False])
@pytest.mark.parametrize('use_enum', [True, False])
@pytest.mark.parametrize('use_bytes', [True, False])
@pytest.mark.parametrize('value_info', inner_values)
def test_with_optional(value_info, use_bytes, use_enum, use_datetime):
x_type, x_value, x_value_dumped = value_info
@dataclass
class DataClass(DataClassDictMixin):
x: Optional[x_type] = None
for instance in [DataClass(x_value), DataClass()]:
if instance.x is None:
v_dumped = None
elif x_value_dumped is Fixture.BYTES:
v_dumped = Fixture.BYTES if use_bytes else Fixture.BYTES_BASE64
elif x_value_dumped is Fixture.BYTE_ARRAY:
v_dumped = Fixture.BYTE_ARRAY if use_bytes else Fixture.BYTES_BASE64
elif isinstance(x_value_dumped, Enum):
v_dumped = x_value_dumped if use_enum else x_value_dumped.value
elif isinstance(x_value_dumped, (datetime, date, time)):
v_dumped = x_value_dumped if use_datetime \
else x_value_dumped.isoformat()
else:
v_dumped = x_value_dumped
dumped = {'x': v_dumped}
instance_dumped = instance.to_dict(
use_bytes=use_bytes,
use_enum=use_enum,
use_datetime=use_datetime
)
instance_loaded = DataClass.from_dict(
dumped,
use_bytes=use_bytes,
use_enum=use_enum,
use_datetime=use_datetime
)
assert instance_dumped == dumped
assert instance_loaded == instance
instance_dumped = instance.to_dict(
use_bytes=use_bytes,
use_enum=use_enum,
use_datetime=use_datetime
)
instance_loaded = DataClass.from_dict(
dumped,
use_bytes=use_bytes,
use_enum=use_enum,
use_datetime=use_datetime
)
assert same_types(instance_dumped, dumped)
assert same_types(instance_loaded.x, instance.x)
def test_raises_missing_field():
@dataclass
class DataClass(DataClassDictMixin):
x: int
with pytest.raises(MissingField):
DataClass.from_dict({})
| 34.633212 | 80 | 0.701986 | 2,491 | 18,979 | 5.038137 | 0.058611 | 0.053546 | 0.105418 | 0.051394 | 0.772112 | 0.73753 | 0.718327 | 0.705498 | 0.685498 | 0.665498 | 0 | 0.010272 | 0.194689 | 18,979 | 547 | 81 | 34.696527 | 0.810848 | 0.014332 | 0 | 0.549894 | 0 | 0 | 0.037596 | 0.00385 | 0 | 0 | 0 | 0 | 0.042463 | 1 | 0.046709 | false | 0.004246 | 0.025478 | 0 | 0.186837 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 4 |
fcd6d6c5939dcbca2463ee8190aae2c3f87f2964 | 3,776 | py | Python | HashItOut/env/lib/python2.7/site-packages/aldryn_bootstrap3/migrations/0003_auto_20151113_1604.py | priyamshah112/Project-Descripton-Blog | 8e01016c6be79776c4f5ca75563fa3daa839e39e | [
"MIT"
] | null | null | null | HashItOut/env/lib/python2.7/site-packages/aldryn_bootstrap3/migrations/0003_auto_20151113_1604.py | priyamshah112/Project-Descripton-Blog | 8e01016c6be79776c4f5ca75563fa3daa839e39e | [
"MIT"
] | 2 | 2022-01-13T04:25:01.000Z | 2022-03-12T01:05:40.000Z | HashItOut/env/lib/python2.7/site-packages/aldryn_bootstrap3/migrations/0003_auto_20151113_1604.py | priyamshah112/Project-Descripton-Blog | 8e01016c6be79776c4f5ca75563fa3daa839e39e | [
"MIT"
] | 2 | 2017-10-18T13:30:28.000Z | 2020-04-30T23:05:43.000Z | # -*- coding: utf-8 -*-
from __future__ import unicode_literals
from django.db import models, migrations
import aldryn_bootstrap3.model_fields
class Migration(migrations.Migration):
dependencies = [
('aldryn_bootstrap3', '0002_bootstrap3fileplugin'),
]
operations = [
migrations.AddField(
model_name='boostrap3imageplugin',
name='override_height',
field=models.IntegerField(help_text='if this field is provided - it would be used across all devices instead of default for devices types. If aspect ration is selected - height will be calculated based on that.', null=True, verbose_name='override height', blank=True),
preserve_default=True,
),
migrations.AddField(
model_name='boostrap3imageplugin',
name='override_width',
field=models.IntegerField(help_text='if this field is provided - it would be used across all devices instead of default for devices types.', null=True, verbose_name='override width', blank=True),
preserve_default=True,
),
migrations.AlterField(
model_name='boostrap3buttonplugin',
name='btn_context',
field=aldryn_bootstrap3.model_fields.Context(default='default', max_length=255, verbose_name='context', choices=[('default', 'Default'), ('primary', 'Primary'), ('success', 'Success'), ('info', 'Info'), ('warning', 'Warning'), ('danger', 'Danger'), ('link', 'Link')]),
preserve_default=True,
),
migrations.AlterField(
model_name='boostrap3buttonplugin',
name='link_mailto',
field=models.EmailField(max_length=75, null=True, verbose_name='email address', blank=True),
preserve_default=True,
),
migrations.AlterField(
model_name='boostrap3buttonplugin',
name='txt_context',
field=aldryn_bootstrap3.model_fields.Context(default='', max_length=255, verbose_name='context', blank=True, choices=[('', 'Default'), ('primary', 'Primary'), ('success', 'Success'), ('info', 'Info'), ('warning', 'Warning'), ('danger', 'Danger'), ('muted ', 'Muted')]),
preserve_default=True,
),
migrations.AlterField(
model_name='boostrap3imageplugin',
name='aspect_ratio',
field=models.CharField(default='', max_length=10, verbose_name='aspect ratio', blank=True, choices=[('1x1', '1x1'), ('4x3', '4x3'), ('16x9', '16x9'), ('16x10', '16x10'), ('21x9', '21x9'), ('3x4', '3x4'), ('9x16', '9x16'), ('10x16', '10x16'), ('9x21', '9x21')]),
preserve_default=True,
),
migrations.AlterField(
model_name='bootstrap3carouselplugin',
name='aspect_ratio',
field=models.CharField(default='', max_length=10, verbose_name='aspect ratio', blank=True, choices=[('1x1', '1x1'), ('4x3', '4x3'), ('16x9', '16x9'), ('16x10', '16x10'), ('21x9', '21x9'), ('3x4', '3x4'), ('9x16', '9x16'), ('10x16', '10x16'), ('9x21', '9x21')]),
preserve_default=True,
),
migrations.AlterField(
model_name='bootstrap3carouselslideplugin',
name='link_mailto',
field=models.EmailField(max_length=75, null=True, verbose_name='email address', blank=True),
preserve_default=True,
),
migrations.AlterField(
model_name='bootstrap3listgroupitemplugin',
name='context',
field=aldryn_bootstrap3.model_fields.Context(default='', max_length=255, blank=True, choices=[('', 'Default'), ('primary', 'Primary'), ('success', 'Success'), ('info', 'Info'), ('warning', 'Warning'), ('danger', 'Danger')]),
preserve_default=True,
),
]
| 53.942857 | 281 | 0.612818 | 375 | 3,776 | 6.016 | 0.258667 | 0.035904 | 0.075798 | 0.102837 | 0.802748 | 0.778812 | 0.766401 | 0.66844 | 0.644947 | 0.614362 | 0 | 0.04809 | 0.223517 | 3,776 | 69 | 282 | 54.724638 | 0.721351 | 0.005561 | 0 | 0.650794 | 0 | 0.015873 | 0.292566 | 0.045297 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.047619 | 0 | 0.095238 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 4 |
fcead0bc6d47402988729215e289131e73663082 | 5,558 | py | Python | python/main.py | jonay2000/research-project | dcc7a1c70b53bb59388452ecaaba17d6564d9216 | [
"Apache-2.0",
"MIT"
] | 3 | 2021-08-23T18:00:44.000Z | 2022-02-09T06:00:50.000Z | python/main.py | jonay2000/research-project | dcc7a1c70b53bb59388452ecaaba17d6564d9216 | [
"Apache-2.0",
"MIT"
] | null | null | null | python/main.py | jonay2000/research-project | dcc7a1c70b53bb59388452ecaaba17d6564d9216 | [
"Apache-2.0",
"MIT"
] | 1 | 2021-06-15T11:38:45.000Z | 2021-06-15T11:38:45.000Z | import pathlib as pathlib
from mapfmclient import MapfBenchmarker, ProgressiveDescriptor, BenchmarkDescriptor, Problem, MarkedLocation
import pathlib
from python.algorithm import MapfAlgorithm
from python.mstar.rewrite import Config
from python.mstar.rewrite.config import GigaByte, MatchingStrategy
from python.solvers.configurable_mstar_solver import ConfigurableMStar
from python.solvers.mstar_od_solver import MStarOD
from python.solvers.prematch_mstar_solver_od import MStarOD as PrematchMStarOD
from python.solvers.prematch_mstar_solver import MStar as PrematchMStar
from python.solvers.visual_prematch_mstar_solver import MStar as VisualPrematchMStar
from python.solvers.prematch_recursive_mstar_solver_od import RMStarOD
from python.solvers.mstar_solver import MStar
from python.solvers.better_matching_astar import BetterMatchingAStar
this_dir = pathlib.Path(__file__).parent.absolute()
with open(this_dir / ".." / "token", "r") as f:
token = f.read()
def submit(algorithm: MapfAlgorithm):
benchmarker = MapfBenchmarker(
token,
# BenchmarkDescriptor(
# 2801,
# progressive_descriptor=ProgressiveDescriptor(
# min_agents=1,
# max_agents=6,
# num_teams=2,
# ),
# ),cp5
81,
algorithm.name,
algorithm.version,
True,
solver=algorithm.solve,
cores=1,
baseURL="https://mapf.nl",
)
benchmarker.run()
if __name__ == '__main__':
submit(BetterMatchingAStar())
# submit(RMStarOD())
# submit(PrematchMStarOD())
# submit(PrematchMStar())
# submit(VisualPrematchMStar())
# submit(MStar())
# submit(MStarOD())
# submit(ConfigurableMStar(Config(
# operator_decomposition=True,
# precompute_paths=False,
# precompute_heuristic=True,
# collision_avoidance_table=False,
# recursive=False,
# matching_strategy=MatchingStrategy.Prematch,
# max_memory_usage=3 * GigaByte,
# debug=False,
# )))
# m = MStar()
# s = m.solve(Problem(
# grid=[[1, 1, 1, 0, 1, 0, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1], [1, 1, 1, 0, 1, 0, 0, 1, 0, 0, 0, 1, 0, 1, 1, 1, 1, 0, 1, 0], [1, 0, 0, 0, 0, 0, 1, 1, 1, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0], [0, 1, 1, 1, 1, 0, 0, 1, 0, 0, 1, 0, 1, 0, 1, 1, 1, 0, 1, 0], [0, 0, 1, 1, 1, 0, 1, 1, 1, 0, 0, 0, 0, 1, 0, 1, 0, 1, 0, 0], [0, 1, 0, 1, 0, 0, 1, 0, 0, 0, 1, 0, 1, 1, 0, 0, 0, 0, 1, 0], [0, 0, 0, 0, 0, 1, 0, 1, 1, 0, 0, 1, 0, 1, 0, 1, 0, 1, 1, 0], [0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 1, 0], [0, 0, 1, 1, 1, 0, 1, 0, 1, 0, 0, 0, 1, 1, 0, 1, 0, 0, 0, 0], [1, 0, 0, 1, 1, 1, 0, 1, 1, 0, 1, 0, 1, 0, 0, 0, 1, 0, 1, 0], [0, 0, 1, 0, 1, 0, 0, 1, 0, 1, 1, 1, 0, 0, 1, 0, 1, 0, 1, 0], [1, 0, 0, 0, 0, 0, 1, 1, 0, 1, 1, 0, 1, 0, 0, 1, 0, 0, 0, 1], [0, 0, 1, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 1, 1], [1, 1, 0, 0, 0, 1, 1, 1, 0, 1, 0, 1, 1, 0, 0, 0, 0, 0, 0, 1], [0, 0, 0, 1, 1, 0, 1, 0, 0, 0, 1, 1, 1, 1, 0, 1, 0, 1, 1, 1], [0, 1, 0, 0, 0, 0, 0, 1, 0, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 1], [0, 0, 1, 0, 1, 0, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 0, 0], [0, 1, 0, 1, 1, 0, 1, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 1], [0, 0, 0, 0, 1, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1], [0, 1, 0, 1, 0, 0, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]],
# width=20,
# height=20,
# starts=[MarkedLocation(x=12, y=12, color=0), MarkedLocation(x=11, y=12, color=0), MarkedLocation(x=4, y=2, color=0)],
# goals=[MarkedLocation(x=9, y=12, color=0), MarkedLocation(x=0, y=15, color=0), MarkedLocation(x=2, y=13, color=0)],
# ))
# # s = m.solve(Problem(
# # grid=[
# # [0, 0, 0, 0, 1, 0, 1, 0, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1],
# # [1, 1, 1, 0, 1, 0, 0, 0, 0, 1, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1],
# # [1, 0, 0, 0, 0, 1, 0, 1, 0, 0, 1, 0, 0, 1, 1, 1, 1, 1, 0, 1],
# # [0, 1, 0, 1, 0, 0, 0, 0, 1, 0, 1, 1, 0, 0, 1, 1, 1, 0, 0, 0],
# # [0, 0, 0, 0, 1, 1, 1, 0, 0, 1, 1, 1, 0, 1, 0, 1, 0, 1, 1, 0],
# # [0, 1, 1, 1, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0],
# # [0, 1, 0, 1, 0, 1, 1, 0, 0, 1, 1, 1, 0, 1, 0, 1, 0, 1, 0, 1],
# # [0, 0, 0, 1, 1, 0, 1, 0, 1, 1, 1, 1, 1, 0, 0, 0, 1, 0, 1, 0],
# # [0, 1, 0, 0, 0, 0, 1, 0, 1, 1, 1, 1, 0, 1, 0, 1, 0, 0, 1, 0],
# # [1, 1, 1, 0, 1, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0],
# # [1, 1, 0, 1, 1, 0, 1, 0, 1, 1, 0, 1, 0, 1, 0, 1, 1, 0, 1, 0],
# # [1, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 0, 1],
# # [1, 0, 0, 0, 1, 0, 1, 0, 1, 0, 1, 1, 1, 1, 0, 0, 1, 0, 1, 0],
# # [1, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0],
# # [0, 0, 1, 0, 1, 0, 1, 1, 1, 0, 1, 0, 1, 0, 0, 1, 1, 0, 1, 1],
# # [1, 0, 1, 1, 0, 1, 0, 1, 0, 1, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0],
# # [1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 1, 1, 0, 1, 1, 0, 1, 0],
# # [0, 1, 1, 0, 1, 0, 1, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1],
# # [0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 1, 0, 1, 0, 1, 1, 1, 0, 1, 1],
# # [1, 0, 0, 0, 0, 1, 1, 0, 1, 1, 0, 0, 0, 1, 0, 0, 0, 0, 1, 1]
# # ],
# # width=20,
# # height=20,
# # starts=[MarkedLocation(x=19, y=13, color=0), MarkedLocation(x=1, y=16, color=0)],
# # goals=[MarkedLocation(x=6, y=5, color=0), MarkedLocation(x=12, y=15, color=0)],
# # ))
# print(s.paths)
| 55.029703 | 1,256 | 0.469054 | 1,106 | 5,558 | 2.316456 | 0.100362 | 0.169399 | 0.154567 | 0.118657 | 0.448478 | 0.41413 | 0.340359 | 0.340359 | 0.340359 | 0.306011 | 0 | 0.223664 | 0.306585 | 5,558 | 100 | 1,257 | 55.58 | 0.4411 | 0.687298 | 0 | 0 | 0 | 0 | 0.018811 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.032258 | false | 0 | 0.451613 | 0 | 0.483871 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 4 |
fcf170e9995593a80080ce345fe39acdc230fd5f | 159 | py | Python | harness/determined/common/schemas/expconf/__init__.py | gh-determined-ai/determined | 9a1ab33a3a356b69681b3351629fef4ab98ddb56 | [
"Apache-2.0"
] | 1,729 | 2020-04-27T17:36:40.000Z | 2022-03-31T05:48:39.000Z | harness/determined/common/schemas/expconf/__init__.py | ChrisW09/determined | 5c37bfe9cfcc69174ba29a3f1a115c3e9e3632e0 | [
"Apache-2.0"
] | 1,940 | 2020-04-27T17:34:14.000Z | 2022-03-31T23:02:28.000Z | harness/determined/common/schemas/expconf/__init__.py | ChrisW09/determined | 5c37bfe9cfcc69174ba29a3f1a115c3e9e3632e0 | [
"Apache-2.0"
] | 214 | 2020-04-27T19:57:28.000Z | 2022-03-29T08:17:16.000Z | from determined.common.schemas.expconf._validate import (
sanity_validation_errors,
completeness_validation_errors,
get_default,
get_schema,
)
| 22.714286 | 57 | 0.779874 | 17 | 159 | 6.882353 | 0.823529 | 0.273504 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.157233 | 159 | 6 | 58 | 26.5 | 0.873134 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 0.166667 | 0 | 0.166667 | 0 | 1 | 0 | 0 | null | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 4 |
1e0cd8347e7d4ee06c7d5e37ed3dd3f8a687bdda | 39 | py | Python | samples/sample.py | spoonshuge/daTool | c479f1a8e09ebcfa306591e1da750e5ec36b54ad | [
"MIT"
] | null | null | null | samples/sample.py | spoonshuge/daTool | c479f1a8e09ebcfa306591e1da750e5ec36b54ad | [
"MIT"
] | null | null | null | samples/sample.py | spoonshuge/daTool | c479f1a8e09ebcfa306591e1da750e5ec36b54ad | [
"MIT"
] | null | null | null | """
Put sample files in this dir...
""" | 13 | 31 | 0.589744 | 6 | 39 | 3.833333 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.179487 | 39 | 3 | 32 | 13 | 0.71875 | 0.794872 | 0 | null | 0 | null | 0 | 0 | null | 0 | 0 | 0 | null | 1 | null | true | 0 | 0 | null | null | null | 1 | 1 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 4 |
1e2061267b844a7ddf9e232ba8172a7dfdc679a9 | 572 | py | Python | Sources/Gotcha/main.py | KHUNerds/Gotcha | b0160da96d54cd48e5f9072d1acc4d491af0c577 | [
"MIT"
] | null | null | null | Sources/Gotcha/main.py | KHUNerds/Gotcha | b0160da96d54cd48e5f9072d1acc4d491af0c577 | [
"MIT"
] | null | null | null | Sources/Gotcha/main.py | KHUNerds/Gotcha | b0160da96d54cd48e5f9072d1acc4d491af0c577 | [
"MIT"
] | null | null | null | import MouseControl
import KeybordControl
if __name__ == "__main__":
print("HelloWorld")
# print(MouseControl.MousePosition())
# MouseControl.MouseMove(1006, 331)
# MouseControl.MouseClickLeft()
# MouseControl.MouseClickRight()
# MouseControl.MouseScroll(100)
# MouseControl.MouseDrag(100, 100, 2)
# KeybordControl.KeybordInputString("가나다라")
# KeybordControl.KeybordInputKeyDown('ctrl')
# KeybordControl.KeybordInputKeyPress('v', 3)
# KeybordControl.KeybordInputKeyUp('ctrl')
# KeybordControl.KeybordInputKeyPress('v', 3)
| 31.777778 | 49 | 0.727273 | 45 | 572 | 9.066667 | 0.577778 | 0.088235 | 0.186275 | 0.191176 | 0.196078 | 0 | 0 | 0 | 0 | 0 | 0 | 0.039095 | 0.15035 | 572 | 17 | 50 | 33.647059 | 0.800412 | 0.716783 | 0 | 0 | 0 | 0 | 0.12 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 0.5 | 0 | 0.5 | 0.25 | 0 | 0 | 0 | null | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 4 |
1e2da7f196f11cd703449df9612d1ef465e26ab7 | 108 | py | Python | functions/source/sagemaker-phc-2020-11-16-preprocess/sagemaker-phc-2020-11-16-preprocess.py | aws-quickstart/quickstart-phsa-ipac | b9f395df62100d2feb0783e226d33b73e5a6198d | [
"Apache-2.0"
] | 1 | 2021-10-30T16:35:38.000Z | 2021-10-30T16:35:38.000Z | functions/source/sagemaker-phc-2020-11-16-preprocess/sagemaker-phc-2020-11-16-preprocess.py | aws-quickstart/quickstart-phsa-ipac | b9f395df62100d2feb0783e226d33b73e5a6198d | [
"Apache-2.0"
] | 1 | 2022-02-23T17:56:05.000Z | 2022-02-23T17:56:05.000Z | functions/source/sagemaker-phc-2020-11-16-preprocess/sagemaker-phc-2020-11-16-preprocess.py | aws-quickstart/quickstart-phsa-ipac | b9f395df62100d2feb0783e226d33b73e5a6198d | [
"Apache-2.0"
] | 1 | 2021-10-30T16:35:29.000Z | 2021-10-30T16:35:29.000Z | import json
def lambda_handler(event, context):
return {
"taskInput": event['dataObject']
} | 18 | 40 | 0.638889 | 11 | 108 | 6.181818 | 0.909091 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.240741 | 108 | 6 | 41 | 18 | 0.829268 | 0 | 0 | 0 | 0 | 0 | 0.174312 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.2 | false | 0 | 0.2 | 0.2 | 0.6 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 4 |
1e3c3e0c912452c685b66d857b62602d7f9ca05d | 235 | py | Python | articles/fake_article.py | john-root/simple-python-mock-example | 92bcaac57324ccb4538dfe504d112f20a72bd968 | [
"Unlicense"
] | null | null | null | articles/fake_article.py | john-root/simple-python-mock-example | 92bcaac57324ccb4538dfe504d112f20a72bd968 | [
"Unlicense"
] | null | null | null | articles/fake_article.py | john-root/simple-python-mock-example | 92bcaac57324ccb4538dfe504d112f20a72bd968 | [
"Unlicense"
] | null | null | null | # The "fake" article entry point
# no dependencies etc.
class FakeArticle:
def __init__(self):
pass
def get_article(self, idx):
return {
"id": idx,
"title": "The test title"
} | 16.785714 | 37 | 0.531915 | 26 | 235 | 4.615385 | 0.769231 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.365957 | 235 | 14 | 38 | 16.785714 | 0.805369 | 0.217021 | 0 | 0 | 0 | 0 | 0.115385 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.25 | false | 0.125 | 0 | 0.125 | 0.5 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 4 |
1e56fd0548964078d4410bf3e3f997b7133ede04 | 884 | py | Python | Proctorexam/Classes/Document.py | gbaelen/ProctorExam-python-api-wrapper | 1ee346e36db1f4c98df2f1a74eefdb86ff453958 | [
"MIT"
] | null | null | null | Proctorexam/Classes/Document.py | gbaelen/ProctorExam-python-api-wrapper | 1ee346e36db1f4c98df2f1a74eefdb86ff453958 | [
"MIT"
] | null | null | null | Proctorexam/Classes/Document.py | gbaelen/ProctorExam-python-api-wrapper | 1ee346e36db1f4c98df2f1a74eefdb86ff453958 | [
"MIT"
] | 1 | 2019-12-17T12:55:06.000Z | 2019-12-17T12:55:06.000Z | class Document():
def __init__(self, connector=None):
self.connector = connector
@staticmethod
def generate_document_from_response(data, connector=None):
return Document(**data, connector=connector)
class DocumentList():
def __init__(self):
self.__id = 0
self.__documents = []
def __iter(self):
self.__id = 0
return self
def __next__(self):
if self.__id < len(self.__documents):
document = self.__documents[self.__id]
self.__id += 1
return document
else:
raise StopIteration
def __getitem__(self, key):
return self.__documents[key]
def add(self, document):
self.__documents.append(document)
def remove_at(self, index):
self.__documents.pop(index)
def size(self):
return len(self.__documents)
| 23.891892 | 62 | 0.61086 | 96 | 884 | 5.145833 | 0.354167 | 0.184211 | 0.044534 | 0.044534 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.004792 | 0.291855 | 884 | 36 | 63 | 24.555556 | 0.784345 | 0 | 0 | 0.071429 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.321429 | false | 0 | 0 | 0.107143 | 0.571429 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 4 |
1e6dd2185808183fd9842b3f666f1c21fd6d7e4b | 373 | py | Python | traceback_with_variables/activate_in_ipython_by_import.py | cclauss/traceback_with_variables | a2bbeb0629535a81f68e1c60a04a7db0ca7470ba | [
"MIT"
] | 550 | 2020-10-31T18:19:24.000Z | 2022-03-31T17:40:07.000Z | traceback_with_variables/activate_in_ipython_by_import.py | cclauss/traceback_with_variables | a2bbeb0629535a81f68e1c60a04a7db0ca7470ba | [
"MIT"
] | 20 | 2020-10-29T15:20:35.000Z | 2021-12-06T00:00:08.000Z | traceback_with_variables/activate_in_ipython_by_import.py | cclauss/traceback_with_variables | a2bbeb0629535a81f68e1c60a04a7db0ca7470ba | [
"MIT"
] | 24 | 2020-11-04T05:12:36.000Z | 2022-03-18T05:38:59.000Z | """
For the simplest usage possible. Just import it
"""
from traceback_with_variables.color import ColorSchemes
from traceback_with_variables.global_hooks import global_print_exc_in_ipython, Format, is_ipython_global
global_print_exc_in_ipython(fmt=Format(
custom_var_printers=[(is_ipython_global, lambda v: None)],
color_scheme=ColorSchemes.common
))
| 31.083333 | 105 | 0.801609 | 51 | 373 | 5.470588 | 0.607843 | 0.09319 | 0.121864 | 0.18638 | 0.164875 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.128686 | 373 | 11 | 106 | 33.909091 | 0.858462 | 0.126005 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 0.333333 | 0 | 0.333333 | 0.5 | 0 | 0 | 0 | null | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 1 | 0 | 4 |
1e84ce404c69ea2517aad282637914e3b0a29809 | 18,488 | py | Python | btd6_save_explorer/model/__init__.py | mriswithe/pybtd6 | da61149e2526a3a560a2d4f62b6372ee876fa84d | [
"MIT"
] | null | null | null | btd6_save_explorer/model/__init__.py | mriswithe/pybtd6 | da61149e2526a3a560a2d4f62b6372ee876fa84d | [
"MIT"
] | null | null | null | btd6_save_explorer/model/__init__.py | mriswithe/pybtd6 | da61149e2526a3a560a2d4f62b6372ee876fa84d | [
"MIT"
] | null | null | null | # generated by datamodel-codegen:
# filename: Profile.json
# timestamp: 2021-12-19T07:57:15+00:00
from __future__ import annotations
from typing import Any, Dict, List
from pydantic import BaseModel, Field
from .instamonkey import InstaTowers
from .maps import MapInfo
from .powers import PowersData
class TowerXp(BaseModel):
dart_monkey: float = Field(..., alias="DartMonkey")
tack_shooter: float = Field(..., alias="TackShooter")
glue_gunner: float = Field(..., alias="GlueGunner")
ice_monkey: float = Field(..., alias="IceMonkey")
bomb_shooter: float = Field(..., alias="BombShooter")
boomerang_monkey: float = Field(..., alias="BoomerangMonkey")
monkey_ace: float = Field(..., alias="MonkeyAce")
mortar_monkey: float = Field(..., alias="MortarMonkey")
sniper_monkey: float = Field(..., alias="SniperMonkey")
super_monkey: float = Field(..., alias="SuperMonkey")
ninja_monkey: float = Field(..., alias="NinjaMonkey")
monkey_village: float = Field(..., alias="MonkeyVillage")
engineer_monkey: float = Field(..., alias="EngineerMonkey")
sentry: float = Field(..., alias="Sentry")
spike_factory: float = Field(..., alias="SpikeFactory")
monkey_sub: float = Field(..., alias="MonkeySub")
wizard_monkey: float = Field(..., alias="WizardMonkey")
banana_farm: float = Field(..., alias="BananaFarm")
monkey_buccaneer: float = Field(..., alias="MonkeyBuccaneer")
alchemist: float = Field(..., alias="Alchemist")
natures_ward_totem: float = Field(..., alias="NaturesWardTotem")
phoenix: float = Field(..., alias="Phoenix")
heli_pilot: float = Field(..., alias="HeliPilot")
dartling_gunner: float = Field(..., alias="DartlingGunner")
druid: float = Field(..., alias="Druid")
buccaneer_lesser_plane: float = Field(..., alias="BuccaneerLesserPlane")
banana_farmer: float = Field(..., alias="BananaFarmer")
sentry_crushing: float = Field(..., alias="SentryCrushing")
sentry_cold: float = Field(..., alias="SentryCold")
sentry_energy: float = Field(..., alias="SentryEnergy")
sentry_boom: float = Field(..., alias="SentryBoom")
buccaneer_greater_plane: float = Field(..., alias="BuccaneerGreaterPlane")
sentry_paragon: float = Field(..., alias="SentryParagon")
cave_monkey: float = Field(..., alias="CaveMonkey")
buccaneer_lesser_plane_camo: float = Field(..., alias="BuccaneerLesserPlaneCamo")
sun_avatar_mini: float = Field(..., alias="SunAvatarMini")
spectre_va: float = Field(..., alias="SpectreVA")
perma_phoenix: float = Field(..., alias="PermaPhoenix")
marine: float = Field(..., alias="Marine")
_: float
lord_phoenix: float = Field(..., alias="LordPhoenix")
tech_bot: float = Field(..., alias="TechBot")
spectre_vc: float = Field(..., alias="SpectreVC")
true_sun_avatar_mini: float = Field(..., alias="TrueSunAvatarMini")
drone: float = Field(..., alias="Drone")
uav: float = Field(..., alias="UAV")
ucav: float = Field(..., alias="UCAV")
sacrificial_totem: float = Field(..., alias="SacrificialTotem")
pontoon: float = Field(..., alias="Pontoon")
ball_of_light__tower: float = Field(..., alias="BallOfLight-Tower")
portable_lake: float = Field(..., alias="PortableLake")
buccaneer_paragon_plane: float = Field(..., alias="BuccaneerParagonPlane")
class SelectedTowerSkinData(BaseModel):
quincy: str = Field(..., alias="Quincy")
gwendolin: str = Field(..., alias="Gwendolin")
obyn_greenfoot: str = Field(..., alias="ObynGreenfoot")
striker_jones: str = Field(..., alias="StrikerJones")
captain_churchill: str = Field(..., alias="CaptainChurchill")
benjamin: str = Field(..., alias="Benjamin")
ezili: str = Field(..., alias="Ezili")
pat_fusty: str = Field(..., alias="PatFusty")
adora: str = Field(..., alias="Adora")
admiral_brickell: str = Field(..., alias="AdmiralBrickell")
etienne: str = Field(..., alias="Etienne")
sauda: str = Field(..., alias="Sauda")
psi: str = Field(..., alias="Psi")
class AnalyticsInfo(BaseModel):
heroes_placed_by_name: Dict[str, Any] = Field(..., alias="heroesPlacedByName")
upgrades_purchased_by_tier: Dict[str, Any] = Field(
..., alias="upgradesPurchasedByTier"
)
hero_upgrades_purchased_by_tier: Dict[str, Any] = Field(
..., alias="heroUpgradesPurchasedByTier"
)
abilities_activated_by_name: Dict[str, Any] = Field(
..., alias="abilitiesActivatedByName"
)
hero_levels_by_name: Dict[str, Any] = Field(..., alias="heroLevelsByName")
hero_won_count: Dict[str, Any] = Field(..., alias="heroWonCount")
power_history: Dict[str, Any] = Field(..., alias="powerHistory")
monkey_type_wins: Dict[str, Any] = Field(..., alias="monkeyTypeWins")
game_id: int = Field(..., alias="gameID")
bloons_popped: int = Field(..., alias="bloonsPopped")
moabs_popped: int = Field(..., alias="moabsPopped")
bfbs_popped: int = Field(..., alias="bfbsPopped")
zomgs_popped: int = Field(..., alias="zomgsPopped")
ddts_popped: int = Field(..., alias="ddtsPopped")
bads_popped: int = Field(..., alias="badsPopped")
fortified_popped: int = Field(..., alias="fortifiedPopped")
purples_popped: int = Field(..., alias="purplesPopped")
camos_popped: int = Field(..., alias="camosPopped")
ceramics_popped: int = Field(..., alias="ceramicsPopped")
regrow_popped: int = Field(..., alias="regrowPopped")
lead_popped: int = Field(..., alias="leadPopped")
coop_cash_recieved: int = Field(..., alias="coopCashRecieved")
coop_cash_sent: int = Field(..., alias="coopCashSent")
total_towers_placed: int = Field(..., alias="totalTowersPlaced")
total_towers_sold: int = Field(..., alias="totalTowersSold")
total_powers_activated: int = Field(..., alias="totalPowersActivated")
total_upgrades_purchased: int = Field(..., alias="totalUpgradesPurchased")
total_abilities_activated: int = Field(..., alias="totalAbilitiesActivated")
times_hero_placed: int = Field(..., alias="timesHeroPlaced")
times_hero_sold: int = Field(..., alias="timesHeroSold")
times_game_restarted: int = Field(..., alias="timesGameRestarted")
third_level_hero_ability_used: bool = Field(..., alias="thirdLevelHeroAbilityUsed")
tenth_level_hero_ability_used: bool = Field(..., alias="tenthLevelHeroAbilityUsed")
reported_first_session: bool = Field(..., alias="reportedFirstSession")
reported_first_purchase: bool = Field(..., alias="reportedFirstPurchase")
class EventData(BaseModel):
event_id: str = Field(..., alias="eventId")
amount_collected: float = Field(..., alias="amountCollected")
amount_rewarded_for: float = Field(..., alias="amountRewardedFor")
amount_last_seen: float = Field(..., alias="amountLastSeen")
seed: float
featured_insta_charges: List[float] = Field(..., alias="featuredInstaCharges")
last_featured_instas_page_seen: float = Field(
..., alias="lastFeaturedInstasPageSeen"
)
class Model(BaseModel):
version: int
saved_by_game_version: str = Field(..., alias="savedByGameVersion")
tower_xp: TowerXp = Field(..., alias="towerXp")
acquired_upgrades: List[str] = Field(..., alias="acquiredUpgrades")
viewed_upgrades: List[str] = Field(..., alias="viewedUpgrades")
acquired_knowledge: List[str] = Field(..., alias="acquiredKnowledge")
paid_for_knowledge: List[str] = Field(..., alias="paidForKnowledge")
knowledge_disabled: bool = Field(..., alias="knowledgeDisabled")
new_knowledge_points: bool = Field(..., alias="newKnowledgePoints")
unlocked_towers: List[str] = Field(..., alias="unlockedTowers")
unlocked_heroes: List[str] = Field(..., alias="unlockedHeroes")
unlocked_tower_skins: List[str] = Field(..., alias="unlockedTowerSkins")
seen_unlocked_notification: List[str] = Field(..., alias="seenUnlockedNotification")
seen_unlocked_heroes: List[str] = Field(..., alias="seenUnlockedHeroes")
seen_new_hero_notification: List[str] = Field(..., alias="seenNewHeroNotification")
seen_new_tower_skin_notification: List[str] = Field(
..., alias="seenNewTowerSkinNotification"
)
map_info: MapInfo = Field(..., alias="mapInfo")
seen_events: List[str] = Field(..., alias="seenEvents")
paid_user_status: float = Field(..., alias="paidUserStatus")
rate_me_sku_version_number: str = Field(..., alias="rateMeSkuVersionNumber")
count_games_since_sku_rate_me_change: bool = Field(
..., alias="countGamesSinceSkuRateMeChange"
)
completed_games_since_sku_rate_me_change: int = Field(
..., alias="completedGamesSinceSkuRateMeChange"
)
completed_game: int = Field(..., alias="completedGame")
seen_pop_up_event_ids: List[str] = Field(..., alias="seenPopUpEventIds")
selected_tower_skin_data: SelectedTowerSkinData = Field(
..., alias="selectedTowerSkinData"
)
powers: Dict[str, Any]
powers_data: PowersData = Field(..., alias="powersData")
insta_towers: InstaTowers = Field(..., alias="instaTowers")
saved_maps: Dict[str, Any] = Field(..., alias="savedMaps")
guid: str
device_id: str = Field(..., alias="deviceID")
owner_id: str = Field(..., alias="ownerID")
trophies_wallet_id: str = Field(..., alias="trophiesWalletId")
unclaimed_trophies: List = Field(..., alias="unclaimedTrophies")
time_stamp: str = Field(..., alias="timeStamp")
monkey_money: float = Field(..., alias="monkeyMoney")
xp: float
rank: float
veteran_xp: float = Field(..., alias="veteranXp")
veteran_rank: float = Field(..., alias="veteranRank")
seen_veteran_rank_info: bool = Field(..., alias="seenVeteranRankInfo")
level_cap_was: int = Field(..., alias="levelCapWas")
trophies: float
lifetime_trophies: float = Field(..., alias="lifetimeTrophies")
knowledge_points: float = Field(..., alias="knowledgePoints")
primary_hero: str = Field(..., alias="primaryHero")
secondary_hero: Any = Field(..., alias="secondaryHero")
achievements_progress: dict[str, float] = Field(..., alias="achievementsProgress")
achievements_claimed: List[int] = Field(..., alias="achievementsClaimed")
achievements_seen: List[int] = Field(..., alias="achievementsSeen")
achievements_posted_to_x_box_live: List = Field(
..., alias="achievementsPostedToXBoxLive"
)
achievements_posted_to_google_play: List = Field(
..., alias="achievementsPostedToGooglePlay"
)
analytics_info: AnalyticsInfo = Field(..., alias="analyticsInfo")
analytics_kon_fuze: AnalyticsKonFuze = Field(..., alias="analyticsKonFuze")
highest_seen_round: int = Field(..., alias="highestSeenRound")
purchase: Purchase
gifts_received: List = Field(..., alias="giftsReceived")
daily_reward_index: int = Field(..., alias="dailyRewardIndex")
last_saved_utc_time: str = Field(..., alias="lastSavedUTCTime")
next_daily_reward_date_time: str = Field(..., alias="nextDailyRewardDateTime")
total_daily_challenges_completed: int = Field(
..., alias="totalDailyChallengesCompleted"
)
consecutive_daily_challenges_completed: int = Field(
..., alias="consecutiveDailyChallengesCompleted"
)
unique_completed_daily_challenge_ids: List = Field(
..., alias="uniqueCompletedDailyChallengeIds"
)
race_medal_data: Dict[str, Any] = Field(..., alias="raceMedalData")
boss_badge_data: Any = Field(..., alias="bossBadgeData")
boss_medals: BossMedals = Field(..., alias="bossMedals")
boss_leaderboard_medals: Dict[str, Any] = Field(..., alias="bossLeaderboardMedals")
boss_leaderboard_elite_medals: Dict[str, Any] = Field(
..., alias="bossLeaderboardEliteMedals"
)
seen_mini_race: bool = Field(..., alias="seenMiniRace")
total_races_entered: float = Field(..., alias="totalRacesEntered")
race_best_time_for_achievements: float = Field(
..., alias="raceBestTimeForAchievements"
)
challenge_editor_model: Any = Field(..., alias="challengeEditorModel")
completed_created_challenge: bool = Field(..., alias="completedCreatedChallenge")
submitted_challenge_editor_id: Any = Field(..., alias="submittedChallengeEditorID")
submitted_odyssey_editor_id: Any = Field(..., alias="submittedOdysseyEditorID")
seen_challenge_modified_popup: bool = Field(..., alias="seenChallengeModifiedPopup")
last_submitted_content_time: LastSubmittedContentTime = Field(
..., alias="lastSubmittedContentTime"
)
in_game_settings: InGameSettings = Field(..., alias="inGameSettings")
language_code: str = Field(..., alias="languageCode")
challenges_played: float = Field(..., alias="challengesPlayed")
challenges_shared: float = Field(..., alias="challengesShared")
wins_with_custom_hero_skin: float = Field(..., alias="winsWithCustomHeroSkin")
bill_greates: float = Field(..., alias="billGreates")
a_crate_time: float = Field(..., alias="aCrateTime")
collection_event_map_bonus_data: CollectionEventMapBonusData = Field(
..., alias="collectionEventMapBonusData"
)
odyssey_save_data: OdysseySaveData = Field(..., alias="odysseySaveData")
odyssey_editor_save_data: Any = Field(..., alias="odysseyEditorSaveData")
odysseys_editor_data: OdysseysEditorData = Field(..., alias="odysseysEditorData")
embarked_odyssey_editor_dcm: Any = Field(..., alias="embarkedOdysseyEditorDcm")
completed_odysseys: CompletedOdysseys = Field(..., alias="completedOdysseys")
total_completed_odysseys: float = Field(..., alias="totalCompletedOdysseys")
cancelled_facebook_friends_popup: bool = Field(
..., alias="cancelledFacebookFriendsPopup"
)
coop_quick_match_setting: int = Field(..., alias="coopQuickMatchSetting")
coop_match_set_to_private: bool = Field(..., alias="coopMatchSetToPrivate")
current_coop_game_details: Any = Field(..., alias="currentCoopGameDetails")
hotkeys_data: Any = Field(..., alias="hotkeysData")
hotkeys_data2: HotkeysData2 = Field(..., alias="hotkeysData2")
has_seen_new_double_cash: bool = Field(..., alias="hasSeenNewDoubleCash")
seen_big_bloons: bool = Field(..., alias="seenBigBloons")
unlocked_big_bloons: bool = Field(..., alias="unlockedBigBloons")
big_bloons_active: bool = Field(..., alias="bigBloonsActive")
seen_small_bloons: bool = Field(..., alias="seenSmallBloons")
unlocked_small_bloons: bool = Field(..., alias="unlockedSmallBloons")
small_bloons_active: bool = Field(..., alias="smallBloonsActive")
seen_big_towers: bool = Field(..., alias="seenBigTowers")
unlocked_big_towers: bool = Field(..., alias="unlockedBigTowers")
big_towers_active: bool = Field(..., alias="bigTowersActive")
seen_small_towers: bool = Field(..., alias="seenSmallTowers")
unlocked_small_towers: bool = Field(..., alias="unlockedSmallTowers")
small_towers_active: bool = Field(..., alias="smallTowersActive")
pat_wins_on10_release: int = Field(..., alias="patWinsOn10Release")
oompa_loompad: bool = Field(..., alias="oompaLoompad")
collection_event_data: CollectionEventData = Field(..., alias="collectionEventData")
saved_play_list: List = Field(..., alias="savedPlayList")
use_juke_box: bool = Field(..., alias="useJukeBox")
trophy_store_purchased_items: TrophyStorePurchasedItems = Field(
..., alias="trophyStorePurchasedItems"
)
named_monkey_names: Dict[str, Any] = Field(..., alias="namedMonkeyNames")
saved_stats: SavedStats = Field(..., alias="savedStats")
profile_avatar: str = Field(..., alias="profileAvatar")
profile_avatar_frame: Any = Field(..., alias="profileAvatarFrame")
profile_banner: str = Field(..., alias="profileBanner")
seen_profile_stats: bool = Field(..., alias="seenProfileStats")
saved_named_monkey_stats: Dict[str, Any] = Field(..., alias="savedNamedMonkeyStats")
stats_version: int = Field(..., alias="statsVersion")
trophy_store_seen: bool = Field(..., alias="trophyStoreSeen")
no_stone_unturned: float = Field(..., alias="noStoneUnturned")
mo_problems: float = Field(..., alias="moProblems")
full_speed: float = Field(..., alias="fullSpeed")
transformic_tonic_uses_on20_release: int = Field(
..., alias="transformicTonicUsesOn20Release"
)
player_challenges: Any = Field(..., alias="playerChallenges")
current_tower_gift_unlock_index: float = Field(
..., alias="currentTowerGiftUnlockIndex"
)
current_tower_gift_progress: float = Field(..., alias="currentTowerGiftProgress")
trophies_spent: int = Field(..., alias="trophiesSpent")
hosted_coop_games: int = Field(..., alias="hostedCoopGames")
collection_event_crates_opened: int = Field(
..., alias="collectionEventCratesOpened"
)
collection_event_crates_types_opened: CollectionEventCratesTypesOpened = Field(
..., alias="collectionEventCratesTypesOpened"
)
continues_used: float = Field(..., alias="continuesUsed")
blocked_hostnames: List = Field(..., alias="blockedHostnames")
seen_intermediate_unlock: bool = Field(..., alias="seenIntermediateUnlock")
seen_advanced_unlock: bool = Field(..., alias="seenAdvancedUnlock")
seen_expert_unlock: bool = Field(..., alias="seenExpertUnlock")
selected_content_tab: int = Field(..., alias="selectedContentTab")
golden_bloon_data: GoldenBloonData = Field(..., alias="goldenBloonData")
golden_bloons_popped: int = Field(..., alias="goldenBloonsPopped")
monkey_teams_wins: int = Field(..., alias="monkeyTeamsWins")
monkey_teams_data: MonkeyTeamsData = Field(..., alias="monkeyTeamsData")
gifted_achievements: List = Field(..., alias="giftedAchievements")
race_pass_count: float = Field(..., alias="racePassCount")
unverified_race_pass_claims: List = Field(..., alias="unverifiedRacePassClaims")
is_boss_ranked_selected: bool = Field(..., alias="isBossRankedSelected")
is_boss_elite_selected: bool = Field(..., alias="isBossEliteSelected")
bosses_event_data: List[BossesEventDatum] = Field(..., alias="bossesEventData")
played_daily_challenge_ids: List = Field(..., alias="playedDailyChallengeIds")
lost_daily_challenge_ids: List = Field(..., alias="lostDailyChallengeIds")
won_daily_challenge_ids: List = Field(..., alias="wonDailyChallengeIds")
has_completed_tutorial: bool = Field(..., alias="HasCompletedTutorial")
| 54.698225 | 88 | 0.693585 | 1,846 | 18,488 | 6.698267 | 0.324485 | 0.205419 | 0.094622 | 0.016983 | 0.110554 | 0.052568 | 0.018763 | 0.006955 | 0.006955 | 0 | 0 | 0.001842 | 0.148421 | 18,488 | 337 | 89 | 54.860534 | 0.783537 | 0.005193 | 0 | 0 | 1 | 0 | 0.21601 | 0.072112 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0.00625 | 0.01875 | 0 | 0.85625 | 0 | 0 | 0 | 0 | null | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 4 |
1e8c5a3cea51a0a74e1d13b299da1193d90c691c | 100 | py | Python | coyote_events/apps.py | hansenjacobs/coyte | 069d968a24dc72f47e8e9e01cebe5856d97ae8e0 | [
"MIT"
] | null | null | null | coyote_events/apps.py | hansenjacobs/coyte | 069d968a24dc72f47e8e9e01cebe5856d97ae8e0 | [
"MIT"
] | null | null | null | coyote_events/apps.py | hansenjacobs/coyte | 069d968a24dc72f47e8e9e01cebe5856d97ae8e0 | [
"MIT"
] | null | null | null | from django.apps import AppConfig
class CoyoteEventsConfig(AppConfig):
name = 'coyote_events'
| 16.666667 | 36 | 0.78 | 11 | 100 | 7 | 0.909091 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.15 | 100 | 5 | 37 | 20 | 0.905882 | 0 | 0 | 0 | 0 | 0 | 0.13 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.333333 | 0 | 1 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 4 |
1ee33f1b4a81ffee200e63e848af35cbfaffaa32 | 139 | py | Python | tools/test_mini.py | sourcery-ai-bot/PV_ENcoNet | 24f2cde258caf6a3fa82f2e1579de833727aac11 | [
"Apache-2.0"
] | 4 | 2021-02-18T10:22:11.000Z | 2021-12-31T06:11:04.000Z | tools/test_mini.py | sourcery-ai-bot/PV_ENcoNet | 24f2cde258caf6a3fa82f2e1579de833727aac11 | [
"Apache-2.0"
] | 3 | 2021-03-01T10:14:08.000Z | 2022-01-05T09:19:44.000Z | tools/test_mini.py | sourcery-ai-bot/PV_ENcoNet | 24f2cde258caf6a3fa82f2e1579de833727aac11 | [
"Apache-2.0"
] | 4 | 2021-02-21T06:14:08.000Z | 2021-05-06T07:04:56.000Z | import torch
a = torch.randn([3,100,3])
index = (torch.LongTensor([0,1]),torch.LongTensor([1,2])
a.index_put_(index), torch.Tensor([1,1])) | 27.8 | 56 | 0.683453 | 25 | 139 | 3.72 | 0.52 | 0.215054 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.085271 | 0.071942 | 139 | 5 | 57 | 27.8 | 0.635659 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | null | 0 | 0.25 | null | null | 0 | 1 | 0 | 0 | null | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 4 |
94c9e32e5e1ebdbb823bac6c30d1c587c1bf3dbe | 1,505 | py | Python | src/server/sol/deploy.py | TaibiaoGuo/bblog | d174b81b2b753bde6f0fd999425452d02d4a20d6 | [
"MIT"
] | null | null | null | src/server/sol/deploy.py | TaibiaoGuo/bblog | d174b81b2b753bde6f0fd999425452d02d4a20d6 | [
"MIT"
] | null | null | null | src/server/sol/deploy.py | TaibiaoGuo/bblog | d174b81b2b753bde6f0fd999425452d02d4a20d6 | [
"MIT"
] | null | null | null | # !/usr/bin python3
# encoding:utf-8
'''
@Time :2020/3/23 9:26 AM
@Author :TaibiaoGuo
@FileName :deploy
@Github :https://github.com/TaibiaoGuo
@Describe :
'''
from web3 import Web3, HTTPProvider
import sols
import os
true = True
false = False
web3 = Web3(HTTPProvider('ETH_PROVIDER'))
fromAddr = 'MAIN_ADDRESS'
privateKey = 'PRIVATE_KEY'
nonce = web3.eth.getTransactionCount(fromAddr)
gasPrice = web3.eth.gasPrice
rawTx = {
'from': fromAddr,
'nonce': nonce,
'gasPrice': gasPrice,
'gas': 300000,
'value': web3.toWei(0, 'ether'),
'data': '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'
}
def deploy(rawTx):
signedTx = web3.eth.account.signTransaction(rawTx, private_key=privateKey)
hashTx = web3.eth.sendRawTransaction(signedTx.rawTransaction).hex()
receipt = web3.eth.waitForTransactionReceipt(hashTx)
return receipt
if __name__ == '__main__':
receipt = deploy(rawTx)
print('address: ' + receipt['contractAddress'])
| 35.833333 | 582 | 0.807309 | 108 | 1,505 | 11.138889 | 0.592593 | 0.029094 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.386043 | 0.104983 | 1,505 | 41 | 583 | 36.707317 | 0.507053 | 0.10299 | 0 | 0 | 0 | 0 | 0.501124 | 0.425468 | 0 | 0 | 0.425468 | 0 | 0 | 1 | 0.038462 | false | 0 | 0.115385 | 0 | 0.192308 | 0.038462 | 0 | 0 | 1 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | null | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 4 |
94d2d00139888053dc1820eab60e08c6baacec48 | 919 | py | Python | GradientBoosting/Loss.py | nachiket273/ML_Algo_Implemented | 74ae47fdf620545fdf8c934c5997784faadaebb7 | [
"MIT"
] | 7 | 2020-08-03T13:43:53.000Z | 2022-02-18T20:38:51.000Z | GradientBoosting/Loss.py | nachiket273/ML_Algo_Implemented | 74ae47fdf620545fdf8c934c5997784faadaebb7 | [
"MIT"
] | null | null | null | GradientBoosting/Loss.py | nachiket273/ML_Algo_Implemented | 74ae47fdf620545fdf8c934c5997784faadaebb7 | [
"MIT"
] | 2 | 2020-09-06T21:54:16.000Z | 2022-01-22T19:59:33.000Z | import numpy as np
from scipy.special import logsumexp
class Loss(object):
def loss(self, y_true, y_pred):
raise NotImplementedError()
def grad(self, y_true, y_pred):
raise NotImplementedError()
class DevianceLoss(Loss):
def loss(self, y_true, y_pred):
n_classes = len(np.unique(y_true))
Y = np.zeros((y_true.shape[0], n_classes), dtype=np.float64)
for i in range(n_classes):
Y[:, i] = y_true == i
return np.average(-1 * (y_true * y_pred).sum(axis=1) + logsumexp(y_pred, axis=1))
def grad(self, y_true, y_pred, k=0):
return y_true - np.nan_to_num(np.exp(y_pred[:, k] -
logsumexp(y_pred, axis=1)))
class MSE(Loss):
def loss(self, y_true, y_pred):
return 0.5 * np.mean((y_true - y_pred.ravel()) ** 2.0)
def grad(self, y_true, y_pred):
return y_true - y_pred.ravel() | 30.633333 | 89 | 0.5963 | 147 | 919 | 3.52381 | 0.326531 | 0.125483 | 0.11583 | 0.173745 | 0.505792 | 0.374517 | 0.351351 | 0.096525 | 0 | 0 | 0 | 0.017804 | 0.266594 | 919 | 30 | 90 | 30.633333 | 0.750742 | 0 | 0 | 0.318182 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.272727 | false | 0 | 0.090909 | 0.136364 | 0.681818 | 0 | 0 | 0 | 0 | null | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 4 |
94d440102656318af096cff124c7165840edb669 | 925 | py | Python | setup.py | MG-RAST/autoskewer | 042e3325f01301d095d403e6e483d48bf2ca789a | [
"BSD-2-Clause"
] | 1 | 2017-01-23T12:05:02.000Z | 2017-01-23T12:05:02.000Z | setup.py | MG-RAST/autoskewer | 042e3325f01301d095d403e6e483d48bf2ca789a | [
"BSD-2-Clause"
] | 2 | 2019-01-15T15:36:36.000Z | 2019-08-23T17:08:37.000Z | setup.py | MG-RAST/autoskewer | 042e3325f01301d095d403e6e483d48bf2ca789a | [
"BSD-2-Clause"
] | 3 | 2017-01-18T21:27:17.000Z | 2018-08-28T17:03:52.000Z | #!/usr/bin/env python
import sys
from setuptools import setup
setup(name='autoskewer',
version='1.2',
description='wrapper for skewer',
author='W Trimble',
author_email='trimble@anl.gov',
url='https://github.com/MG-RAST/autoskewer',
packages=['autoskewer'],
data_files=[ ( "data", ["data/vectors-P5.1.bt2", "data/vectors-P5.2.bt2",
"data/vectors-P5.3.bt2", "data/vectors-P5.4.bt2",
"data/vectors-P7.1.bt2", "data/vectors-P7.2.bt2",
"data/vectors-P7.3.bt2", "data/vectors-P7.4.bt2",
"data/vectors-P7.fa", "data/vectors-P5.fa",
"data/vectors-P7.rev.1.bt2", "data/vectors-P7.rev.2.bt2",
"data/vectors-P5.rev.1.bt2", "data/vectors-P5.rev.2.bt2"]) ],
scripts=['autoskewer/autoskewer.py'],
install_requires=[]
)
| 38.541667 | 88 | 0.539459 | 118 | 925 | 4.20339 | 0.381356 | 0.310484 | 0.310484 | 0.193548 | 0.292339 | 0 | 0 | 0 | 0 | 0 | 0 | 0.05997 | 0.278919 | 925 | 23 | 89 | 40.217391 | 0.683658 | 0.021622 | 0 | 0 | 0 | 0 | 0.480089 | 0.323009 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 0.105263 | 0 | 0.105263 | 0 | 0 | 0 | 0 | null | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 4 |
94eabeccd93df46dd9a938024e6c017956e696ab | 7,169 | py | Python | pyfk/tests/gf/test_gf.py | ziyixi/pyfk | 2db56621cd4f9db5cf6a866fa0ca25fcb994b1d4 | [
"MIT"
] | 29 | 2019-09-08T03:43:55.000Z | 2022-03-16T06:13:08.000Z | pyfk/tests/gf/test_gf.py | ziyixi/pyfk | 2db56621cd4f9db5cf6a866fa0ca25fcb994b1d4 | [
"MIT"
] | 9 | 2020-12-16T01:52:44.000Z | 2022-03-22T14:04:27.000Z | pyfk/tests/gf/test_gf.py | ziyixi/pyfk | 2db56621cd4f9db5cf6a866fa0ca25fcb994b1d4 | [
"MIT"
] | 5 | 2021-02-17T14:46:32.000Z | 2022-01-24T02:43:03.000Z | from os.path import dirname, join
import numpy as np
import obspy
import pytest
from pyfk.config.config import Config, SeisModel, SourceModel
from pyfk.gf.gf import calculate_gf
from pyfk.tests.taup.test_taup import TestFunctionTaup
class TestFunctioncalculateGf(object):
@staticmethod
@pytest.mark.mpi_skip
def test_hk():
# * perl fk.pl -Mhk/15/k -N512/0.1 10 20 30
model_path = join(dirname(__file__), f"../data/hk")
model_data = np.loadtxt(model_path)
model_hk = SeisModel(model=model_data, use_kappa=True)
source_hk = SourceModel(sdep=15)
config_hk = Config(
model=model_hk,
source=source_hk,
npt=512,
dt=0.1,
receiver_distance=[
10,
20,
30])
result = calculate_gf(config_hk)
# * for all the gf in data/hk_gf, test if the results are close (in FK, it uses float but we are using double)
for irec, each_rec in enumerate([10, 20, 30]):
for icomn in range(9):
hk_gf_data = obspy.read(
join(
dirname(__file__),
f"../data/hk_gf/{each_rec}.grn.{icomn}"))[0]
coef = np.corrcoef(
hk_gf_data.data,
result[irec][icomn].data,
)[0, 1]
if np.isnan(coef):
coef = 1.0
assert coef > 0.99
@pytest.mark.mpi_skip
def test_big_array(self):
# model_data = TestFunctionTaup.gen_test_model("prem")
# there is a possibility that we write x=f(x) where x is a memoryview in the code
# this might cause segmentation fault
model_data = np.loadtxt(join(dirname(__file__), f"../data/hk"))
model_hk = SeisModel(model=model_data)
source_hk = SourceModel(sdep=16.5)
config_hk = Config(
model=model_hk,
source=source_hk,
npt=512,
dt=0.1,
receiver_distance=np.arange(10, 40, 10))
_ = calculate_gf(config_hk)
@pytest.mark.mpi_skip
def test_prem_ep(self):
model_data = TestFunctionTaup.gen_test_model("prem")
model_prem = SeisModel(model=model_data)
source_prem = SourceModel(sdep=16.5, srcType="ep")
config_prem = Config(
model=model_prem,
source=source_prem,
npt=512,
dt=5,
receiver_distance=[50])
gf = calculate_gf(config_prem)
for index, comnname in enumerate(["a", "b", "c"]):
gf_data = obspy.read(
join(
dirname(__file__),
f"../data/sync_prem_ep/50.grn.{comnname}"))[0]
coef = np.corrcoef(
gf_data.data,
gf[0][index].data,
)[0, 1]
if np.isnan(coef):
coef = 1.
assert coef > 0.99
@pytest.mark.mpi_skip
def test_prem_sf(self):
model_data = TestFunctionTaup.gen_test_model("prem")
model_prem = SeisModel(model=model_data)
source_prem = SourceModel(sdep=16.5, srcType="sf")
config_prem = Config(
model=model_prem,
source=source_prem,
npt=512,
dt=1,
receiver_distance=[50])
gf = calculate_gf(config_prem)
for index, comnname in enumerate(range(6)):
gf_data = obspy.read(
join(
dirname(__file__),
f"../data/sync_prem_sf/50.grn.{comnname}"))[0]
coef = np.corrcoef(
gf_data.data,
gf[0][index].data,
)[0, 1]
if np.isnan(coef):
coef = 1.
assert coef > 0.99
@pytest.mark.mpi_skip
def test_receiver_deeper(self):
model_data = TestFunctionTaup.gen_test_model("prem")
model_prem = SeisModel(model=model_data)
source_prem = SourceModel(sdep=16.5, srcType="dc")
config_prem = Config(
model=model_prem,
source=source_prem,
npt=512,
dt=1,
receiver_distance=[50],
rdep=20)
gf = calculate_gf(config_prem)
for index, comnname in enumerate(range(9)):
gf_data = obspy.read(
join(
dirname(__file__),
f"../data/sync_receiver_deeper/50_20.grn.{comnname}"))[0]
coef = np.corrcoef(
gf_data.data,
gf[0][index].data,
)[0, 1]
if np.isnan(coef):
coef = 1.
assert coef > 0.99
@pytest.mark.mpi_skip
def test_static_source(self):
model_data = TestFunctionTaup.gen_test_model("prem")
model_prem = SeisModel(model=model_data)
source_prem = SourceModel(sdep=16.5, srcType="dc")
config_prem = Config(
model=model_prem,
source=source_prem,
npt=1,
dt=1,
receiver_distance=[50])
gf = calculate_gf(config_prem)
ref_gf = [-0.242E-06, -0.103E-05, 0.000E+00, 0.236E-06,
0.118E-05, -0.548E-07, -0.942E-07, -0.156E-05, 0.285E-06]
coef = np.corrcoef(
gf,
ref_gf,
)[0, 1]
assert coef > 0.99999
@pytest.mark.mpi_skip
def test_smth(self):
model_data = TestFunctionTaup.gen_test_model("prem")
model_prem = SeisModel(model=model_data)
source_prem = SourceModel(sdep=16.5, srcType="dc")
config_prem = Config(
model=model_prem,
source=source_prem,
npt=512,
dt=0.1,
smth=8,
receiver_distance=[50])
gf = calculate_gf(config_prem)
for index, comnname in enumerate(range(9)):
gf_data = obspy.read(
join(
dirname(__file__),
f"../data/sync_smth/50.grn.{comnname}"))[0]
coef = np.corrcoef(
gf_data.data,
gf[0][index].data,
)[0, 1]
if np.isnan(coef):
coef = 1.
assert coef > 0.99
@pytest.mark.mpi_skip
def test_filter(self):
model_data = TestFunctionTaup.gen_test_model("prem")
model_prem = SeisModel(model=model_data)
source_prem = SourceModel(sdep=16.5, srcType="dc")
config_prem = Config(
model=model_prem,
source=source_prem,
npt=512,
dt=0.1,
smth=8,
filter=(0.1, 0.6),
receiver_distance=[50])
gf = calculate_gf(config_prem)
for index, comnname in enumerate(range(9)):
gf_data = obspy.read(
join(
dirname(__file__),
f"../data/sync_filter/50.grn.{comnname}"))[0]
coef = np.corrcoef(
gf_data.data,
gf[0][index].data,
)[0, 1]
if np.isnan(coef):
coef = 1.
assert coef > 0.99
| 34.138095 | 118 | 0.518482 | 860 | 7,169 | 4.109302 | 0.166279 | 0.048387 | 0.029428 | 0.038483 | 0.736842 | 0.735144 | 0.705433 | 0.681098 | 0.668364 | 0.65167 | 0 | 0.052269 | 0.372855 | 7,169 | 209 | 119 | 34.301435 | 0.733763 | 0.044497 | 0 | 0.704663 | 0 | 0 | 0.042665 | 0.034044 | 0 | 0 | 0 | 0 | 0.036269 | 1 | 0.041451 | false | 0 | 0.036269 | 0 | 0.082902 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 4 |
a200d5e6b4db10ebff3bdf66b8cfd54a9b27d9e3 | 92 | py | Python | hivs_dash/apps.py | tehamalab/hivs | db7dfa7f89174be07d42bd469fd23c8553c0eff2 | [
"MIT"
] | null | null | null | hivs_dash/apps.py | tehamalab/hivs | db7dfa7f89174be07d42bd469fd23c8553c0eff2 | [
"MIT"
] | null | null | null | hivs_dash/apps.py | tehamalab/hivs | db7dfa7f89174be07d42bd469fd23c8553c0eff2 | [
"MIT"
] | null | null | null | from django.apps import AppConfig
class HivsDashConfig(AppConfig):
name = 'hivs_dash'
| 15.333333 | 33 | 0.76087 | 11 | 92 | 6.272727 | 0.909091 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.163043 | 92 | 5 | 34 | 18.4 | 0.896104 | 0 | 0 | 0 | 0 | 0 | 0.097826 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.333333 | 0 | 1 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 4 |
a204fc2c8b426564d03b692ab69d4b87e00275c7 | 1,644 | py | Python | aiotdlib/api/functions/set_password.py | jraylan/aiotdlib | 4528fcfca7c5c69b54a878ce6ce60e934a2dcc73 | [
"MIT"
] | 37 | 2021-05-04T10:41:41.000Z | 2022-03-30T13:48:05.000Z | aiotdlib/api/functions/set_password.py | jraylan/aiotdlib | 4528fcfca7c5c69b54a878ce6ce60e934a2dcc73 | [
"MIT"
] | 13 | 2021-07-17T19:54:51.000Z | 2022-02-26T06:50:00.000Z | aiotdlib/api/functions/set_password.py | jraylan/aiotdlib | 4528fcfca7c5c69b54a878ce6ce60e934a2dcc73 | [
"MIT"
] | 7 | 2021-09-22T21:27:11.000Z | 2022-02-20T02:33:19.000Z | # =============================================================================== #
# #
# This file has been generated automatically!! Do not change this manually! #
# #
# =============================================================================== #
from __future__ import annotations
from pydantic import Field
from ..base_object import BaseObject
class SetPassword(BaseObject):
"""
Changes the password for the current user. If a new recovery email address is specified, then the change will not be applied until the new recovery email address is confirmed
:param old_password: Previous password of the user
:type old_password: :class:`str`
:param new_password: New password of the user; may be empty to remove the password
:type new_password: :class:`str`
:param new_hint: New password hint; may be empty
:type new_hint: :class:`str`
:param set_recovery_email_address: Pass true if the recovery email address must be changed
:type set_recovery_email_address: :class:`bool`
:param new_recovery_email_address: New recovery email address; may be empty
:type new_recovery_email_address: :class:`str`
"""
ID: str = Field("setPassword", alias="@type")
old_password: str
new_password: str
new_hint: str
set_recovery_email_address: bool
new_recovery_email_address: str
@staticmethod
def read(q: dict) -> SetPassword:
return SetPassword.construct(**q)
| 37.363636 | 178 | 0.57056 | 180 | 1,644 | 5.033333 | 0.372222 | 0.143488 | 0.220751 | 0.152318 | 0.145695 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.274331 | 1,644 | 43 | 179 | 38.232558 | 0.75943 | 0.683698 | 0 | 0 | 1 | 0 | 0.037296 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.076923 | false | 0.461538 | 0.230769 | 0.076923 | 0.923077 | 0 | 0 | 0 | 0 | null | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 4 |
bf3e294930c1e6880b8c7e71e0f01b86b2381594 | 185 | py | Python | src/javax/swing/text/__init__.py | thecesrom/7.9 | 6dc59a1e920382345837d620907578b35fe7e96b | [
"MIT"
] | 1 | 2022-03-16T05:59:14.000Z | 2022-03-16T05:59:14.000Z | src/javax/swing/text/__init__.py | ignition-api/7.9 | 8c9666d1ed83dc1c6470c9263a70cb83eeda5f1d | [
"MIT"
] | 3 | 2022-03-15T21:33:41.000Z | 2022-03-17T21:28:56.000Z | src/javax/swing/text/__init__.py | thecesrom/7.9 | 6dc59a1e920382345837d620907578b35fe7e96b | [
"MIT"
] | 1 | 2022-03-16T18:26:03.000Z | 2022-03-16T18:26:03.000Z | from java.awt import Container
class JTextComponent(Container):
_text = "Text"
def getText(self):
return self._text
def setText(self, t):
self._text = t
| 15.416667 | 32 | 0.632432 | 23 | 185 | 4.956522 | 0.608696 | 0.122807 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.275676 | 185 | 11 | 33 | 16.818182 | 0.850746 | 0 | 0 | 0 | 0 | 0 | 0.021622 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.285714 | false | 0 | 0.142857 | 0.142857 | 0.857143 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 4 |
bf3e29ad3837a39b173650b6e7d6224361cb3ee4 | 213 | py | Python | functions/solutions/solution0.py | sgennari/cmpt_100_tutorials | 8fd10ae7545282496c3cfe65fa9c8ffa55cd863c | [
"AFL-3.0"
] | null | null | null | functions/solutions/solution0.py | sgennari/cmpt_100_tutorials | 8fd10ae7545282496c3cfe65fa9c8ffa55cd863c | [
"AFL-3.0"
] | null | null | null | functions/solutions/solution0.py | sgennari/cmpt_100_tutorials | 8fd10ae7545282496c3cfe65fa9c8ffa55cd863c | [
"AFL-3.0"
] | null | null | null | def number_of_cents(change):
"""
>>> number_of_cents(1.25)
25
>>> number_of_cents(20.00)
0
"""
dollar_remainder = change % 1
cents = dollar_remainder * 100
return round(cents) | 17.75 | 34 | 0.596244 | 28 | 213 | 4.25 | 0.535714 | 0.201681 | 0.327731 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.090909 | 0.276995 | 213 | 12 | 35 | 17.75 | 0.681818 | 0.267606 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.25 | false | 0 | 0 | 0 | 0.5 | 0 | 1 | 0 | 0 | null | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 4 |
bf5e8f8bd586b691bbc918aec84e26ef4008e11d | 124 | py | Python | application/models/__init__.py | bobowang/flask-base | b8c68654fa5c07fbb2ada3d25587e9b0cbacf1af | [
"MIT"
] | null | null | null | application/models/__init__.py | bobowang/flask-base | b8c68654fa5c07fbb2ada3d25587e9b0cbacf1af | [
"MIT"
] | null | null | null | application/models/__init__.py | bobowang/flask-base | b8c68654fa5c07fbb2ada3d25587e9b0cbacf1af | [
"MIT"
] | null | null | null | from .role import Role
from .roles_users import RolesUsers
from .user import User
__all__ = ["Role", "User", "RolesUsers"]
| 20.666667 | 40 | 0.741935 | 17 | 124 | 5.117647 | 0.470588 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.145161 | 124 | 5 | 41 | 24.8 | 0.820755 | 0 | 0 | 0 | 0 | 0 | 0.145161 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.75 | 0 | 0.75 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 4 |
bf820d42877ed6c115e61891426000f58c489e57 | 110 | py | Python | modis/discord_modis/modules/!core/on_server_available.py | Benny84/discord-music-bot-modis | f98b15119d6e14475fa662a98158f4adfa2f49c0 | [
"Apache-2.0"
] | null | null | null | modis/discord_modis/modules/!core/on_server_available.py | Benny84/discord-music-bot-modis | f98b15119d6e14475fa662a98158f4adfa2f49c0 | [
"Apache-2.0"
] | null | null | null | modis/discord_modis/modules/!core/on_server_available.py | Benny84/discord-music-bot-modis | f98b15119d6e14475fa662a98158f4adfa2f49c0 | [
"Apache-2.0"
] | null | null | null | from . import api_core
async def on_server_available(server):
await api_core.update_server_data(server)
| 18.333333 | 45 | 0.8 | 17 | 110 | 4.823529 | 0.705882 | 0.170732 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.136364 | 110 | 5 | 46 | 22 | 0.863158 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 0.333333 | 0 | 0.333333 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 4 |
bfb74d6eb04880f7142dc1097332aabe3a2e87bb | 72 | py | Python | main.py | kagaya25/How-to-findout-the-latitude-and-longitude-using-python | e016925104901734d72e15bd78ea94c254588571 | [
"MIT"
] | 2 | 2020-11-01T08:39:33.000Z | 2020-11-01T08:44:05.000Z | main.py | kagaya25/How-to-findout-the-latitude-and-longitude-using-python | e016925104901734d72e15bd78ea94c254588571 | [
"MIT"
] | null | null | null | main.py | kagaya25/How-to-findout-the-latitude-and-longitude-using-python | e016925104901734d72e15bd78ea94c254588571 | [
"MIT"
] | null | null | null | import geocoder
g = geocoder.ip('me')
print(g.latlng)
print(g.city)
| 9 | 21 | 0.680556 | 12 | 72 | 4.083333 | 0.666667 | 0.244898 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.152778 | 72 | 7 | 22 | 10.285714 | 0.803279 | 0 | 0 | 0 | 0 | 0 | 0.028986 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.25 | 0 | 0.25 | 0.5 | 1 | 0 | 0 | null | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 4 |
bfbb2ad52164b0df438c3dadcc62183c3950a942 | 1,464 | py | Python | vkapi/fave.py | effordsbeard/vk-sdk | 719ef5a1ffa2a0c067dbea5014f40da54f86646b | [
"MIT"
] | null | null | null | vkapi/fave.py | effordsbeard/vk-sdk | 719ef5a1ffa2a0c067dbea5014f40da54f86646b | [
"MIT"
] | null | null | null | vkapi/fave.py | effordsbeard/vk-sdk | 719ef5a1ffa2a0c067dbea5014f40da54f86646b | [
"MIT"
] | null | null | null | from vk import VKAPI
class Fave(VKAPI):
method_class = 'fave'
def __init__(self, access_token=''):
super(Fave, self).__init__(access_token=access_token)
def add_group(self, **params):
self.set_method('addGroup')
return self.send(params)
def add_link(self, **params):
self.set_method('addLink')
return self.send(params)
def add_user(self, **params):
self.set_method('addUser')
return self.send(params)
def get_links(self, **params):
self.set_method('getLinks')
return self.send(params)
def get_market_items(self, **params):
self.set_method('getMarketItems')
return self.send(params)
def get_photos(self, **params):
self.set_method('getPhotos')
return self.send(params)
def get_posts(self, **params):
self.set_method('getPosts')
return self.send(params)
def get_users(self, **params):
self.set_method('getUsers')
return self.send(params)
def get_videos(self, **params):
self.set_method('getVideos')
return self.send(params)
def remove_group(self, **params):
self.set_method('removeGroup')
return self.send(params)
def remove_link(self, **params):
self.set_method('removeLink')
return self.send(params)
def remove_user(self, **params):
self.set_method('removeUser')
return self.send(params)
| 25.241379 | 61 | 0.624317 | 180 | 1,464 | 4.872222 | 0.233333 | 0.13683 | 0.191562 | 0.232611 | 0.68073 | 0.523375 | 0 | 0 | 0 | 0 | 0 | 0 | 0.247268 | 1,464 | 57 | 62 | 25.684211 | 0.795826 | 0 | 0 | 0.292683 | 0 | 0 | 0.077239 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.317073 | false | 0 | 0.02439 | 0 | 0.682927 | 0 | 0 | 0 | 0 | null | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 4 |
44aa79d03d5af5854bfb65e9d9fd6925929b2b32 | 31 | py | Python | example_snippets/multimenus_snippets/Snippets/SciPy/Special functions/Spheroidal Wave Functions/pro_rad1_cv Prolate spheroidal radial function pro_rad1 for precomputed characteristic value.py | kuanpern/jupyterlab-snippets-multimenus | 477f51cfdbad7409eab45abe53cf774cd70f380c | [
"BSD-3-Clause"
] | null | null | null | example_snippets/multimenus_snippets/Snippets/SciPy/Special functions/Spheroidal Wave Functions/pro_rad1_cv Prolate spheroidal radial function pro_rad1 for precomputed characteristic value.py | kuanpern/jupyterlab-snippets-multimenus | 477f51cfdbad7409eab45abe53cf774cd70f380c | [
"BSD-3-Clause"
] | null | null | null | example_snippets/multimenus_snippets/Snippets/SciPy/Special functions/Spheroidal Wave Functions/pro_rad1_cv Prolate spheroidal radial function pro_rad1 for precomputed characteristic value.py | kuanpern/jupyterlab-snippets-multimenus | 477f51cfdbad7409eab45abe53cf774cd70f380c | [
"BSD-3-Clause"
] | 1 | 2021-02-04T04:51:48.000Z | 2021-02-04T04:51:48.000Z | special.pro_rad1_cv(m,n,c,cv,x) | 31 | 31 | 0.774194 | 9 | 31 | 2.444444 | 0.888889 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.032258 | 0 | 31 | 1 | 31 | 31 | 0.677419 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 4 |
44b387699114bbf044782ae1fcaeba36444444e3 | 348 | py | Python | LandPortalEntities/lpentities/time.py | weso/landportal-importers | 6edfa3c301422bbe8c09cb877b1cbddbcd902463 | [
"Unlicense"
] | null | null | null | LandPortalEntities/lpentities/time.py | weso/landportal-importers | 6edfa3c301422bbe8c09cb877b1cbddbcd902463 | [
"Unlicense"
] | 8 | 2016-02-16T13:05:37.000Z | 2017-01-04T14:38:03.000Z | LandPortalEntities/lpentities/time.py | landportal/landbook-importers | f0e246f493329b9c5741c50f3a0495d27ee5c54b | [
"MIT"
] | null | null | null | '''
Created on 02/02/2014
@author: Miguel Otero
'''
from .dimension import Dimension
from abc import ABCMeta, abstractmethod
class Time(Dimension):
'''
classdocs
'''
__metaclass__ = ABCMeta
@abstractmethod
def get_time_string(self): pass
def get_dimension_string(self):
return self.get_time_string() | 17.4 | 39 | 0.675287 | 40 | 348 | 5.625 | 0.575 | 0.186667 | 0.115556 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.029963 | 0.232759 | 348 | 20 | 40 | 17.4 | 0.812734 | 0.155172 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.25 | false | 0.125 | 0.25 | 0.125 | 0.875 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 1 | 0 | 0 | 4 |
44b42f4530c2895ae1e521d3970450fcc13a1478 | 149 | py | Python | Exercicios/ex047.py | vincytarsis/Python | f98005917486bc191c85c971ec8e2c71fb9dd4c7 | [
"MIT"
] | null | null | null | Exercicios/ex047.py | vincytarsis/Python | f98005917486bc191c85c971ec8e2c71fb9dd4c7 | [
"MIT"
] | null | null | null | Exercicios/ex047.py | vincytarsis/Python | f98005917486bc191c85c971ec8e2c71fb9dd4c7 | [
"MIT"
] | null | null | null | """ Crie um programa que mostre na tela todos os números pares que estão no intervalo entre
1 a 50."""
for num in range(2, 50+1, 2):
print(num) | 29.8 | 91 | 0.684564 | 29 | 149 | 3.517241 | 0.827586 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.068376 | 0.214765 | 149 | 5 | 92 | 29.8 | 0.803419 | 0.637584 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.2 | 0 | 1 | 0 | false | 0 | 0 | 0 | 0 | 0.5 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 4 |
44baea2a21ece9295433eb2d4e9a91e62649aa7a | 221 | py | Python | src/words/helper/TokenTypeEnum.py | DavidStrootman/ATP | 72005be0ac75339bb5da037a7e98573e338d16db | [
"MIT"
] | 2 | 2021-08-20T17:56:15.000Z | 2021-08-21T01:04:08.000Z | src/words/helper/TokenTypeEnum.py | DavidStrootman/Words | 72005be0ac75339bb5da037a7e98573e338d16db | [
"MIT"
] | null | null | null | src/words/helper/TokenTypeEnum.py | DavidStrootman/Words | 72005be0ac75339bb5da037a7e98573e338d16db | [
"MIT"
] | null | null | null | from enum import Enum, unique
from typing import Tuple
@unique
class TokenTypeEnum(Enum):
@classmethod
def values(cls) -> Tuple[any, ...]:
return tuple(value.value for value in cls.__members__.values())
| 22.1 | 71 | 0.701357 | 29 | 221 | 5.206897 | 0.62069 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.190045 | 221 | 9 | 72 | 24.555556 | 0.843575 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.142857 | false | 0 | 0.285714 | 0.142857 | 0.714286 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 4 |
44c24c14c78509c2ff8353d66f264aed0f758d37 | 65 | py | Python | bin/test.py | UdSAES/modest-py | 5df9d27a4d0aac302af04a1edc0c9adaa03bf731 | [
"BSD-2-Clause"
] | null | null | null | bin/test.py | UdSAES/modest-py | 5df9d27a4d0aac302af04a1edc0c9adaa03bf731 | [
"BSD-2-Clause"
] | null | null | null | bin/test.py | UdSAES/modest-py | 5df9d27a4d0aac302af04a1edc0c9adaa03bf731 | [
"BSD-2-Clause"
] | 1 | 2020-04-16T09:49:38.000Z | 2020-04-16T09:49:38.000Z | #!/usr/bin/env python
from modestpy.test import run
run.tests()
| 13 | 29 | 0.738462 | 11 | 65 | 4.363636 | 0.909091 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.123077 | 65 | 4 | 30 | 16.25 | 0.842105 | 0.307692 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 0.5 | 0 | 0.5 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 4 |
44db910eea7c9346efe3057c47aaed3fe8488b3e | 117 | py | Python | materials/config.example.py | hicsail/materials | eb1770787193141cbc9a9e89f6be33ed7de05828 | [
"MIT"
] | 1 | 2015-12-04T19:53:55.000Z | 2015-12-04T19:53:55.000Z | materials/config.example.py | hicsail/materials | eb1770787193141cbc9a9e89f6be33ed7de05828 | [
"MIT"
] | null | null | null | materials/config.example.py | hicsail/materials | eb1770787193141cbc9a9e89f6be33ed7de05828 | [
"MIT"
] | null | null | null | config = {
'sqlalchemy.url': 'postgresql://scott:tiger@localhost:5432/mydatabase',
'sqlalchemy.echo': True
}
| 23.4 | 75 | 0.683761 | 12 | 117 | 6.666667 | 0.916667 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.039604 | 0.136752 | 117 | 4 | 76 | 29.25 | 0.752475 | 0 | 0 | 0 | 0 | 0 | 0.675214 | 0.42735 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 4 |
44eaa357f22d7fdd22b04a617641e0bae0de5b4e | 3,135 | py | Python | tests/kerascv/layers/losses/hard_neg_miner_test.py | tanzhenyu/keras-cv | b7208ee25735c492ccc171874e34076111dcf637 | [
"Apache-2.0"
] | null | null | null | tests/kerascv/layers/losses/hard_neg_miner_test.py | tanzhenyu/keras-cv | b7208ee25735c492ccc171874e34076111dcf637 | [
"Apache-2.0"
] | null | null | null | tests/kerascv/layers/losses/hard_neg_miner_test.py | tanzhenyu/keras-cv | b7208ee25735c492ccc171874e34076111dcf637 | [
"Apache-2.0"
] | null | null | null | import numpy as np
import tensorflow as tf
from kerascv.layers.losses.hard_neg_miner import HardNegativeMining
def test_more_negative_than_positive():
classification_losses = tf.constant([[0.1, 0.2, 0.3], [0.4, 0.5, 0.6]])
positive_mask = tf.constant([[0, 0, 0], [0, 0, 1]])
negative_mask = tf.constant([[1, 1, 1], [1, 1, 0]])
hard_miner_layer = HardNegativeMining()
losses = hard_miner_layer(classification_losses, positive_mask, negative_mask)
# n_positives is 1, while n_negatives is 5, so picking the top 3, which is .3, .4, .5
expected_out = np.asarray([0.3, 1.5]).astype(np.float32)
np.testing.assert_allclose(expected_out, losses)
def test_less_negative_than_positive():
classification_losses = tf.constant([[0.1, 0.2, 0.3], [0.4, 0.5, 0.6]])
positive_mask = tf.constant([[0, 1, 0], [0, 0, 1]])
negative_mask = tf.constant([[0, 0, 1], [1, 0, 0]])
hard_miner_layer = HardNegativeMining()
losses = hard_miner_layer(classification_losses, positive_mask, negative_mask)
# n_positives is 2, while n_negatives is 2, so pick all negative samples
expected_out = np.asarray([0.5, 1.0])
np.testing.assert_allclose(expected_out, losses)
def test_zero_negative_values():
classification_losses = tf.constant([[0.0, 0.0, 0.3], [0.0, 0.5, 0.6]])
positive_mask = tf.constant([[0, 0, 0], [0, 0, 1]])
negative_mask = tf.constant([[1, 1, 1], [1, 1, 0]])
hard_miner_layer = HardNegativeMining()
losses = hard_miner_layer(classification_losses, positive_mask, negative_mask)
# n_positives is 1, while n_negatives is 5, but only 2 of them are non-zero,
# so picking the 2, which is .3, .5
expected_out = np.asarray([0.3, 1.1]).astype(np.float32)
np.testing.assert_allclose(expected_out, losses)
def test_no_negatives():
classification_losses = tf.constant([[0.0, 0.0, 0.3], [0.0, 0.5, 0.6]])
positive_mask = tf.constant([[0, 0, 0], [0, 0, 1]])
negative_mask = tf.constant([[0, 0, 0], [0, 0, 0]])
hard_miner_layer = HardNegativeMining()
losses = hard_miner_layer(classification_losses, positive_mask, negative_mask)
# n_positives is 1, while n_negatives is 0
expected_out = np.asarray([0.0, 0.6]).astype(np.float32)
np.testing.assert_allclose(expected_out, losses)
def test_min_negative_examples():
classification_losses = tf.constant([[0.1, 0.2, 0.3], [0.4, 0.5, 0.6]])
positive_mask = tf.constant([[0, 0, 0], [0, 0, 1]])
negative_mask = tf.constant([[1, 1, 1], [1, 1, 0]])
hard_miner_layer = HardNegativeMining(
negative_positive_ratio=2, minimum_negative_examples=4
)
losses = hard_miner_layer(classification_losses, positive_mask, negative_mask)
# n_positives is 1, while n_negatives is 5, need at least 4 negative examples, 2., 3., 4., 5
expected_out = np.asarray([0.5, 1.5])
np.testing.assert_allclose(expected_out, losses)
def test_config_with_custom_name():
layer = HardNegativeMining(name="hard_example_miner")
config = layer.get_config()
layer_1 = HardNegativeMining.from_config(config)
np.testing.assert_equal(layer_1.name, layer.name)
| 45.434783 | 96 | 0.690909 | 502 | 3,135 | 4.099602 | 0.151394 | 0.037901 | 0.037901 | 0.029155 | 0.749757 | 0.739067 | 0.739067 | 0.726919 | 0.68999 | 0.644315 | 0 | 0.06598 | 0.163636 | 3,135 | 68 | 97 | 46.102941 | 0.718917 | 0.125997 | 0 | 0.52 | 0 | 0 | 0.006586 | 0 | 0 | 0 | 0 | 0 | 0.12 | 1 | 0.12 | false | 0 | 0.06 | 0 | 0.18 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 4 |
44fc0ec3b6d8604f81024e321849bf481bedfd41 | 825 | py | Python | ch_4/binomial_problems.py | ProhardONE/python_primer | 211e37c1f2fd169269fc4f3c08e8b7e5225f2ad0 | [
"MIT"
] | 51 | 2016-04-05T16:56:11.000Z | 2022-02-08T00:08:47.000Z | ch_4/binomial_problems.py | zhangxiao921207/python_primer | 211e37c1f2fd169269fc4f3c08e8b7e5225f2ad0 | [
"MIT"
] | null | null | null | ch_4/binomial_problems.py | zhangxiao921207/python_primer | 211e37c1f2fd169269fc4f3c08e8b7e5225f2ad0 | [
"MIT"
] | 47 | 2016-05-02T07:51:37.000Z | 2022-02-08T01:28:15.000Z | # Exercise 4.25
# Author: Noah Waterfield Price
from binomial_distribution import binomial
print 'What is the probability of gettinger two heads when \
flipping a coin 5 times?'
print '%.6f\n' % binomial(2, 5, 0.5)
print 'What is the probability of getting fours ones in a rown when \
throwing a die?'
print '%.6f\n' % binomial(4, 4, 1. / 6)
print 'What is the probability that a skier will experience a ski \
break during five\n competitions in a world championship?'
print '%.6f' % (1 - binomial(0, 5, 1. / 120))
"""
What is the probability of gettinger two heads when flipping a coin 5 times?
0.312500
What is the probability of getting fours ones in a rown when throwing a die?
0.000772
What is the probability that a skier will experience a ski break during five
competitions in a world championship?
0.040978
"""
| 30.555556 | 76 | 0.739394 | 142 | 825 | 4.288732 | 0.380282 | 0.059113 | 0.08867 | 0.197044 | 0.740558 | 0.627258 | 0.610837 | 0.610837 | 0.610837 | 0.610837 | 0 | 0.065089 | 0.180606 | 825 | 26 | 77 | 31.730769 | 0.835799 | 0.052121 | 0 | 0 | 0 | 0 | 0.033827 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | null | 0 | 0.1 | null | null | 0.6 | 0 | 0 | 0 | null | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 4 |
781746b3ae609835c752646af4bd766e4f564c5b | 231 | py | Python | projetoWeb/utils/views.py | marcosv2017/feitonaaula | e97fc122cdac5c172d16e794d3c977f50aaa54e9 | [
"MIT"
] | null | null | null | projetoWeb/utils/views.py | marcosv2017/feitonaaula | e97fc122cdac5c172d16e794d3c977f50aaa54e9 | [
"MIT"
] | null | null | null | projetoWeb/utils/views.py | marcosv2017/feitonaaula | e97fc122cdac5c172d16e794d3c977f50aaa54e9 | [
"MIT"
] | null | null | null | from django.shortcuts import render
from utils.utils import calculaMediaFinal
from django.http import HttpResponse
def media(resquest):
media = calculaMediaFinal(10,8)
return HttpResponse(media)
# Create your views here.
| 23.1 | 41 | 0.792208 | 29 | 231 | 6.310345 | 0.655172 | 0.10929 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.015228 | 0.147186 | 231 | 9 | 42 | 25.666667 | 0.913706 | 0.099567 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.166667 | false | 0 | 0.5 | 0 | 0.833333 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 4 |
7830713d774cc9f6c51f331162d871058d89c02d | 94 | py | Python | django_project/apps/ueditor/apps.py | gaohj/nzflask_bbs | 36a94c380b78241ed5d1e07edab9618c3e8d477b | [
"Apache-2.0"
] | 24 | 2017-07-30T14:57:01.000Z | 2021-05-24T06:09:14.000Z | apps/ueditor/apps.py | blackholll/loonblog | 63d1f06d04047f220f550de914e542f535bb61a3 | [
"MIT"
] | 27 | 2020-02-12T07:55:58.000Z | 2022-03-12T00:19:09.000Z | apps/ueditor/apps.py | blackholll/loonblog | 63d1f06d04047f220f550de914e542f535bb61a3 | [
"MIT"
] | 16 | 2017-08-07T15:46:51.000Z | 2022-01-06T06:46:24.000Z | from django.apps import AppConfig
class UeditorConfig(AppConfig):
name = 'apps.ueditor'
| 15.666667 | 33 | 0.755319 | 11 | 94 | 6.454545 | 0.818182 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.159574 | 94 | 5 | 34 | 18.8 | 0.898734 | 0 | 0 | 0 | 0 | 0 | 0.12766 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.333333 | 0 | 1 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 4 |
783c52132fc5df65a6f205a82e69a870319ee650 | 108 | py | Python | python/testData/paramInfo/RedefinedNewConstructorCall.py | jnthn/intellij-community | 8fa7c8a3ace62400c838e0d5926a7be106aa8557 | [
"Apache-2.0"
] | 2 | 2019-04-28T07:48:50.000Z | 2020-12-11T14:18:08.000Z | python/testData/paramInfo/RedefinedNewConstructorCall.py | Cyril-lamirand/intellij-community | 60ab6c61b82fc761dd68363eca7d9d69663cfa39 | [
"Apache-2.0"
] | 173 | 2018-07-05T13:59:39.000Z | 2018-08-09T01:12:03.000Z | python/testData/paramInfo/RedefinedNewConstructorCall.py | Cyril-lamirand/intellij-community | 60ab6c61b82fc761dd68363eca7d9d69663cfa39 | [
"Apache-2.0"
] | 2 | 2020-03-15T08:57:37.000Z | 2020-04-07T04:48:14.000Z | # signature of overridden __new__
class A(object):
def __new__(cls, a, b):
pass
A(<arg1>1, <arg2>2)
| 13.5 | 33 | 0.648148 | 18 | 108 | 3.444444 | 0.833333 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.046512 | 0.203704 | 108 | 7 | 34 | 15.428571 | 0.674419 | 0.287037 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | null | 0.25 | 0 | null | null | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 4 |
785b2c56c1427f5870d22550dba6cc44be21cc0d | 83 | py | Python | bdo_dsm2_app/wiin/apps.py | zackaryleady/DSM2_BDO_WIIN_Stand_Alone | 26a0e3084889e3da0c3f85a9e93e7032a5871106 | [
"MIT"
] | 1 | 2020-01-17T17:21:28.000Z | 2020-01-17T17:21:28.000Z | bdo_dsm2_app/wiin/apps.py | zackaryleady/DSM2_BDO_WIIN_Stand_Alone | 26a0e3084889e3da0c3f85a9e93e7032a5871106 | [
"MIT"
] | null | null | null | bdo_dsm2_app/wiin/apps.py | zackaryleady/DSM2_BDO_WIIN_Stand_Alone | 26a0e3084889e3da0c3f85a9e93e7032a5871106 | [
"MIT"
] | null | null | null | from django.apps import AppConfig
class WiinConfig(AppConfig):
name = 'wiin'
| 13.833333 | 33 | 0.73494 | 10 | 83 | 6.1 | 0.9 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.180723 | 83 | 5 | 34 | 16.6 | 0.897059 | 0 | 0 | 0 | 0 | 0 | 0.048193 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.333333 | 0 | 1 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 4 |
789ab3342756e877c8f06cd772f70f382b05d0fb | 13,912 | py | Python | analysis/Graham/scripts/project_functions.py | data301-2020-winter1/course-project-group_6008 | ce3b5ccc48afe6775d831da49defcd0e4fd78c07 | [
"MIT"
] | null | null | null | analysis/Graham/scripts/project_functions.py | data301-2020-winter1/course-project-group_6008 | ce3b5ccc48afe6775d831da49defcd0e4fd78c07 | [
"MIT"
] | 1 | 2020-12-06T00:15:53.000Z | 2020-12-06T00:15:53.000Z | analysis/Graham/scripts/project_functions.py | data301-2020-winter1/course-project-group_6008 | ce3b5ccc48afe6775d831da49defcd0e4fd78c07 | [
"MIT"
] | null | null | null | {
"cells": [
{
"cell_type": "code",
"execution_count": 15,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Name</th>\n",
" <th>Games Played</th>\n",
" <th>MIN</th>\n",
" <th>PTS</th>\n",
" <th>FGM</th>\n",
" <th>FGA</th>\n",
" <th>FG%</th>\n",
" <th>3PM</th>\n",
" <th>3PA</th>\n",
" <th>3P%</th>\n",
" <th>...</th>\n",
" <th>BLK</th>\n",
" <th>TOV</th>\n",
" <th>PF</th>\n",
" <th>EFF</th>\n",
" <th>AST/TOV</th>\n",
" <th>STL/TOV</th>\n",
" <th>Collage</th>\n",
" <th>Experience</th>\n",
" <th>Height</th>\n",
" <th>Pos</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>426</th>\n",
" <td>Shawne Williams</td>\n",
" <td>63</td>\n",
" <td>1087</td>\n",
" <td>341</td>\n",
" <td>121</td>\n",
" <td>300</td>\n",
" <td>40.3</td>\n",
" <td>64</td>\n",
" <td>178</td>\n",
" <td>36.0</td>\n",
" <td>...</td>\n",
" <td>21</td>\n",
" <td>30</td>\n",
" <td>135</td>\n",
" <td>383</td>\n",
" <td>1.47</td>\n",
" <td>0.83</td>\n",
" <td>Western Michigan University</td>\n",
" <td>0</td>\n",
" <td>207.5</td>\n",
" <td>PF</td>\n",
" </tr>\n",
" <tr>\n",
" <th>414</th>\n",
" <td>Sean Kilpatrick</td>\n",
" <td>4</td>\n",
" <td>72</td>\n",
" <td>22</td>\n",
" <td>7</td>\n",
" <td>20</td>\n",
" <td>35.0</td>\n",
" <td>4</td>\n",
" <td>13</td>\n",
" <td>30.8</td>\n",
" <td>...</td>\n",
" <td>0</td>\n",
" <td>2</td>\n",
" <td>3</td>\n",
" <td>20</td>\n",
" <td>2.00</td>\n",
" <td>1.50</td>\n",
" <td>University of Cincinnati</td>\n",
" <td>0</td>\n",
" <td>190.0</td>\n",
" <td>SG</td>\n",
" </tr>\n",
" <tr>\n",
" <th>199</th>\n",
" <td>JaMychal Green</td>\n",
" <td>24</td>\n",
" <td>164</td>\n",
" <td>62</td>\n",
" <td>27</td>\n",
" <td>47</td>\n",
" <td>57.4</td>\n",
" <td>0</td>\n",
" <td>6</td>\n",
" <td>0.0</td>\n",
" <td>...</td>\n",
" <td>5</td>\n",
" <td>14</td>\n",
" <td>25</td>\n",
" <td>85</td>\n",
" <td>0.29</td>\n",
" <td>0.36</td>\n",
" <td>University of Alabama</td>\n",
" <td>0</td>\n",
" <td>202.5</td>\n",
" <td>PF</td>\n",
" </tr>\n",
" <tr>\n",
" <th>197</th>\n",
" <td>James Michael McAdoo</td>\n",
" <td>15</td>\n",
" <td>137</td>\n",
" <td>62</td>\n",
" <td>24</td>\n",
" <td>44</td>\n",
" <td>54.5</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0.0</td>\n",
" <td>...</td>\n",
" <td>9</td>\n",
" <td>6</td>\n",
" <td>21</td>\n",
" <td>78</td>\n",
" <td>0.33</td>\n",
" <td>0.83</td>\n",
" <td>University of North Carolina</td>\n",
" <td>0</td>\n",
" <td>202.5</td>\n",
" <td>PF</td>\n",
" </tr>\n",
" <tr>\n",
" <th>193</th>\n",
" <td>James Ennis III</td>\n",
" <td>62</td>\n",
" <td>1051</td>\n",
" <td>312</td>\n",
" <td>101</td>\n",
" <td>247</td>\n",
" <td>40.9</td>\n",
" <td>31</td>\n",
" <td>95</td>\n",
" <td>32.6</td>\n",
" <td>...</td>\n",
" <td>17</td>\n",
" <td>39</td>\n",
" <td>89</td>\n",
" <td>378</td>\n",
" <td>1.23</td>\n",
" <td>0.64</td>\n",
" <td>California State University, Long Beach</td>\n",
" <td>0</td>\n",
" <td>197.5</td>\n",
" <td>SF</td>\n",
" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>389</th>\n",
" <td>Raymond Felton</td>\n",
" <td>29</td>\n",
" <td>281</td>\n",
" <td>108</td>\n",
" <td>43</td>\n",
" <td>106</td>\n",
" <td>40.6</td>\n",
" <td>10</td>\n",
" <td>34</td>\n",
" <td>29.4</td>\n",
" <td>...</td>\n",
" <td>4</td>\n",
" <td>18</td>\n",
" <td>17</td>\n",
" <td>106</td>\n",
" <td>2.28</td>\n",
" <td>0.61</td>\n",
" <td>University of North Carolina</td>\n",
" <td>9</td>\n",
" <td>182.5</td>\n",
" <td>PG</td>\n",
" </tr>\n",
" <tr>\n",
" <th>325</th>\n",
" <td>Marvin Williams</td>\n",
" <td>78</td>\n",
" <td>2035</td>\n",
" <td>577</td>\n",
" <td>210</td>\n",
" <td>495</td>\n",
" <td>42.4</td>\n",
" <td>95</td>\n",
" <td>265</td>\n",
" <td>35.8</td>\n",
" <td>...</td>\n",
" <td>36</td>\n",
" <td>60</td>\n",
" <td>146</td>\n",
" <td>798</td>\n",
" <td>1.67</td>\n",
" <td>1.15</td>\n",
" <td>University of North Carolina</td>\n",
" <td>9</td>\n",
" <td>202.5</td>\n",
" <td>PF</td>\n",
" </tr>\n",
" <tr>\n",
" <th>205</th>\n",
" <td>Jarrett Jack</td>\n",
" <td>80</td>\n",
" <td>2241</td>\n",
" <td>957</td>\n",
" <td>359</td>\n",
" <td>817</td>\n",
" <td>43.9</td>\n",
" <td>39</td>\n",
" <td>146</td>\n",
" <td>26.7</td>\n",
" <td>...</td>\n",
" <td>13</td>\n",
" <td>191</td>\n",
" <td>143</td>\n",
" <td>987</td>\n",
" <td>1.95</td>\n",
" <td>0.39</td>\n",
" <td>Georgia Institute of Technology</td>\n",
" <td>9</td>\n",
" <td>187.5</td>\n",
" <td>PG</td>\n",
" </tr>\n",
" <tr>\n",
" <th>206</th>\n",
" <td>Jason Maxiell</td>\n",
" <td>61</td>\n",
" <td>878</td>\n",
" <td>203</td>\n",
" <td>81</td>\n",
" <td>192</td>\n",
" <td>42.2</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0.0</td>\n",
" <td>...</td>\n",
" <td>44</td>\n",
" <td>29</td>\n",
" <td>96</td>\n",
" <td>317</td>\n",
" <td>0.66</td>\n",
" <td>0.62</td>\n",
" <td>University of Cincinnati</td>\n",
" <td>9</td>\n",
" <td>197.5</td>\n",
" <td>PF</td>\n",
" </tr>\n",
" <tr>\n",
" <th>49</th>\n",
" <td>Brandon Bass</td>\n",
" <td>82</td>\n",
" <td>1929</td>\n",
" <td>866</td>\n",
" <td>344</td>\n",
" <td>683</td>\n",
" <td>50.4</td>\n",
" <td>9</td>\n",
" <td>32</td>\n",
" <td>28.1</td>\n",
" <td>...</td>\n",
" <td>32</td>\n",
" <td>83</td>\n",
" <td>140</td>\n",
" <td>974</td>\n",
" <td>1.25</td>\n",
" <td>0.49</td>\n",
" <td>Louisiana State University</td>\n",
" <td>9</td>\n",
" <td>200.0</td>\n",
" <td>PF</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>350 rows × 28 columns</p>\n",
"</div>"
],
"text/plain": [
" Name Games Played MIN PTS FGM FGA FG% 3PM 3PA \\\n",
"426 Shawne Williams 63 1087 341 121 300 40.3 64 178 \n",
"414 Sean Kilpatrick 4 72 22 7 20 35.0 4 13 \n",
"199 JaMychal Green 24 164 62 27 47 57.4 0 6 \n",
"197 James Michael McAdoo 15 137 62 24 44 54.5 0 0 \n",
"193 James Ennis III 62 1051 312 101 247 40.9 31 95 \n",
".. ... ... ... ... ... ... ... ... ... \n",
"389 Raymond Felton 29 281 108 43 106 40.6 10 34 \n",
"325 Marvin Williams 78 2035 577 210 495 42.4 95 265 \n",
"205 Jarrett Jack 80 2241 957 359 817 43.9 39 146 \n",
"206 Jason Maxiell 61 878 203 81 192 42.2 0 0 \n",
"49 Brandon Bass 82 1929 866 344 683 50.4 9 32 \n",
"\n",
" 3P% ... BLK TOV PF EFF AST/TOV STL/TOV \\\n",
"426 36.0 ... 21 30 135 383 1.47 0.83 \n",
"414 30.8 ... 0 2 3 20 2.00 1.50 \n",
"199 0.0 ... 5 14 25 85 0.29 0.36 \n",
"197 0.0 ... 9 6 21 78 0.33 0.83 \n",
"193 32.6 ... 17 39 89 378 1.23 0.64 \n",
".. ... ... ... ... ... ... ... ... \n",
"389 29.4 ... 4 18 17 106 2.28 0.61 \n",
"325 35.8 ... 36 60 146 798 1.67 1.15 \n",
"205 26.7 ... 13 191 143 987 1.95 0.39 \n",
"206 0.0 ... 44 29 96 317 0.66 0.62 \n",
"49 28.1 ... 32 83 140 974 1.25 0.49 \n",
"\n",
" Collage Experience Height Pos \n",
"426 Western Michigan University 0 207.5 PF \n",
"414 University of Cincinnati 0 190.0 SG \n",
"199 University of Alabama 0 202.5 PF \n",
"197 University of North Carolina 0 202.5 PF \n",
"193 California State University, Long Beach 0 197.5 SF \n",
".. ... ... ... ... \n",
"389 University of North Carolina 9 182.5 PG \n",
"325 University of North Carolina 9 202.5 PF \n",
"205 Georgia Institute of Technology 9 187.5 PG \n",
"206 University of Cincinnati 9 197.5 PF \n",
"49 Louisiana State University 9 200.0 PF \n",
"\n",
"[350 rows x 28 columns]"
]
},
"execution_count": 15,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"import pandas as pd\n",
"def load_and_process(url_or_path_to_csv_file):\n",
"\n",
" df = (pd.read_csv(url_or_path_to_csv_file)\n",
" .drop(columns = ['BMI','Weight','Team','Birth_Place','Birthdate','Age'])\n",
" .dropna()\n",
" .replace('R', '0')\n",
" .sort_values('Experience', ascending = True)\n",
" )\n",
" return df\n",
"load_and_process('../../../data/raw/players_stats.csv')"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.8.3"
}
},
"nbformat": 4,
"nbformat_minor": 4
}
| 34.181818 | 92 | 0.303695 | 1,743 | 13,912 | 2.407344 | 0.156627 | 0.165157 | 0.262154 | 0.044328 | 0.31387 | 0.264538 | 0.259771 | 0.137512 | 0.124166 | 0.108913 | 0 | 0.128245 | 0.449037 | 13,912 | 406 | 93 | 34.26601 | 0.419048 | 0 | 0 | 0.362069 | 0 | 0 | 0.687177 | 0.017467 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 0.002463 | 0 | 0.002463 | 0 | 0 | 0 | 0 | null | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 4 |
789b36f0e861ab67c4973ba8789d4a1de4dc2bbc | 19,124 | py | Python | tests/unit/result/test_result_command.py | broadinstitute/carrot_cli | c3a580753e76e2f7fa3c0423fe7073754cc1ba8b | [
"BSD-3-Clause"
] | null | null | null | tests/unit/result/test_result_command.py | broadinstitute/carrot_cli | c3a580753e76e2f7fa3c0423fe7073754cc1ba8b | [
"BSD-3-Clause"
] | 18 | 2021-06-04T19:44:52.000Z | 2022-02-23T19:34:47.000Z | tests/unit/result/test_result_command.py | broadinstitute/carrot_cli | c3a580753e76e2f7fa3c0423fe7073754cc1ba8b | [
"BSD-3-Clause"
] | null | null | null | import json
from click.testing import CliRunner
import logging
import mockito
import pytest
from carrot_cli.__main__ import main_entry as carrot
from carrot_cli.config import manager as config
from carrot_cli.rest import results, template_results
@pytest.fixture(autouse=True)
def unstub():
yield
mockito.unstub()
@pytest.fixture(autouse=True)
def no_email():
mockito.when(config).load_var_no_error("email").thenReturn(None)
@pytest.fixture(
params=[
{
"args": ["result", "find_by_id", "cd987859-06fe-4b1a-9e96-47d4f36bf819"],
"return": json.dumps(
{
"created_at": "2020-09-16T18:48:06.371563",
"created_by": "adora@example.com",
"result_type": "file",
"description": "This result will save Etheria",
"name": "Sword of Protection result",
"result_id": "cd987859-06fe-4b1a-9e96-47d4f36bf819",
},
indent=4,
sort_keys=True,
),
},
{
"args": ["result", "find_by_id", "cd987859-06fe-4b1a-9e96-47d4f36bf819"],
"return": json.dumps(
{
"title": "No result found",
"status": 404,
"detail": "No result found with the specified ID",
},
indent=4,
sort_keys=True,
),
},
]
)
def find_by_id_data(request):
# Set all requests to return None so only the one we expect will return a value
mockito.when(results).find_by_id(...).thenReturn(None)
# Mock up request response
mockito.when(results).find_by_id(request.param["args"][2]).thenReturn(
request.param["return"]
)
return request.param
def test_find_by_id(find_by_id_data):
runner = CliRunner()
result = runner.invoke(carrot, find_by_id_data["args"])
assert result.output == find_by_id_data["return"] + "\n"
@pytest.fixture(
params=[
{
"args": [
"result",
"find",
"--result_id",
"cd987859-06fe-4b1a-9e96-47d4f36bf819",
"--name",
"Sword of Protection result",
"--description",
"This result will save Etheria",
"--result_type",
"numeric",
"--created_by",
"adora@example.com",
"--created_before",
"2020-10-00T00:00:00.000000",
"--created_after",
"2020-09-00T00:00:00.000000",
"--sort",
"asc(name)",
"--limit",
1,
"--offset",
0,
],
"params": [
"cd987859-06fe-4b1a-9e96-47d4f36bf819",
"Sword of Protection result",
"This result will save Etheria",
"numeric",
"adora@example.com",
"2020-10-00T00:00:00.000000",
"2020-09-00T00:00:00.000000",
"asc(name)",
1,
0,
],
"return": json.dumps(
{
"created_at": "2020-09-16T18:48:06.371563",
"created_by": "adora@example.com",
"result_type": "numeric",
"description": "This result will save Etheria",
"name": "Sword of Protection result",
"result_id": "cd987859-06fe-4b1a-9e96-47d4f36bf819",
},
indent=4,
sort_keys=True,
),
},
{
"args": [
"result",
"find",
"--result_id",
"986325ba-06fe-4b1a-9e96-47d4f36bf819",
],
"params": [
"986325ba-06fe-4b1a-9e96-47d4f36bf819",
"",
"",
"",
"",
"",
"",
"",
20,
0,
],
"return": json.dumps(
{
"title": "No results found",
"status": 404,
"detail": "No results found with the specified parameters",
},
indent=4,
sort_keys=True,
),
},
]
)
def find_data(request):
# Set all requests to return None so only the one we expect will return a value
mockito.when(results).find(...).thenReturn(None)
# Mock up request response
mockito.when(results).find(
request.param["params"][0],
request.param["params"][1],
request.param["params"][2],
request.param["params"][3],
request.param["params"][4],
request.param["params"][5],
request.param["params"][6],
request.param["params"][7],
request.param["params"][8],
request.param["params"][9],
).thenReturn(request.param["return"])
return request.param
def test_find(find_data):
runner = CliRunner()
result = runner.invoke(carrot, find_data["args"])
assert result.output == find_data["return"] + "\n"
@pytest.fixture(
params=[
{
"args": [
"result",
"create",
"--name",
"Sword of Protection result",
"--description",
"This result will save Etheria",
"--result_type",
"numeric",
"--created_by",
"adora@example.com",
],
"params": [
"Sword of Protection result",
"This result will save Etheria",
"numeric",
"adora@example.com",
],
"return": json.dumps(
{
"created_at": "2020-09-16T18:48:06.371563",
"created_by": "adora@example.com",
"result_type": "numeric",
"description": "This result will save Etheria",
"name": "Sword of Protection result",
"result_id": "cd987859-06fe-4b1a-9e96-47d4f36bf819",
},
indent=4,
sort_keys=True,
),
},
{
"args": [
"result",
"create",
"--name",
"Sword of Protection result",
"--description",
"This result will save Etheria",
"--result_type",
"numeric",
],
"params": [],
"logging": "No email config variable set. If a value is not specified for --created by, "
"there must be a value set for email.",
},
{
"args": ["result", "create"],
"params": [],
"return": "Usage: carrot_cli result create [OPTIONS]\n"
"Try 'carrot_cli result create --help' for help.\n"
"\n"
"Error: Missing option '--name'.",
},
]
)
def create_data(request):
# Set all requests to return None so only the one we expect will return a value
mockito.when(results).create(...).thenReturn(None)
# Mock up request response only if we expect it to get that far
if len(request.param["params"]) > 0:
mockito.when(results).create(
request.param["params"][0],
request.param["params"][1],
request.param["params"][2],
request.param["params"][3],
).thenReturn(request.param["return"])
return request.param
def test_create(create_data, caplog):
runner = CliRunner()
result = runner.invoke(carrot, create_data["args"])
if "logging" in create_data:
assert create_data["logging"] in caplog.text
else:
assert result.output == create_data["return"] + "\n"
@pytest.fixture(
params=[
{
"args": [
"result",
"update",
"cd987859-06fe-4b1a-9e96-47d4f36bf819",
"--description",
"This new result replaced the broken one",
"--name",
"New Sword of Protection result",
],
"params": [
"cd987859-06fe-4b1a-9e96-47d4f36bf819",
"New Sword of Protection result",
"This new result replaced the broken one",
],
"return": json.dumps(
{
"created_at": "2020-09-16T18:48:06.371563",
"created_by": "adora@example.com",
"result_type": "file",
"description": "This new result replaced the broken one",
"name": "New Sword of Protection result",
"result_id": "cd987859-06fe-4b1a-9e96-47d4f36bf819",
},
indent=4,
sort_keys=True,
),
},
{
"args": ["result", "update"],
"params": [],
"return": "Usage: carrot_cli result update [OPTIONS] ID\n"
"Try 'carrot_cli result update --help' for help.\n"
"\n"
"Error: Missing argument 'ID'.",
},
]
)
def update_data(request):
# Set all requests to return None so only the one we expect will return a value
mockito.when(results).update(...).thenReturn(None)
# Mock up request response only if we expect it to get that far
if len(request.param["params"]) > 0:
mockito.when(results).update(
request.param["params"][0],
request.param["params"][1],
request.param["params"][2],
).thenReturn(request.param["return"])
return request.param
def test_update(update_data):
runner = CliRunner()
result = runner.invoke(carrot, update_data["args"])
assert result.output == update_data["return"] + "\n"
@pytest.fixture(
params=[
{
"args": ["result", "delete", "cd987859-06fe-4b1a-9e96-47d4f36bf819"],
"id": "cd987859-06fe-4b1a-9e96-47d4f36bf819",
"find_return": json.dumps(
{
"created_at": "2020-09-16T18:48:06.371563",
"created_by": "adora@example.com",
"result_type": "file",
"description": "This new result replaced the broken one",
"name": "New Sword of Protection result",
"result_id": "cd987859-06fe-4b1a-9e96-47d4f36bf819",
},
indent=4,
sort_keys=True,
),
"email": "adora@example.com",
"return": json.dumps(
{"message": "Successfully deleted 1 row"}, indent=4, sort_keys=True
),
},
{
"args": ["result", "delete", "-y", "cd987859-06fe-4b1a-9e96-47d4f36bf819"],
"id": "cd987859-06fe-4b1a-9e96-47d4f36bf819",
"find_return": json.dumps(
{
"created_at": "2020-09-16T18:48:06.371563",
"created_by": "adora@example.com",
"result_type": "file",
"description": "This new result replaced the broken one",
"name": "New Sword of Protection result",
"result_id": "cd987859-06fe-4b1a-9e96-47d4f36bf819",
},
indent=4,
sort_keys=True,
),
"email": "catra@example.com",
"return": json.dumps(
{"message": "Successfully deleted 1 row"}, indent=4, sort_keys=True
),
},
{
"args": ["result", "delete", "cd987859-06fe-4b1a-9e96-47d4f36bf819"],
"id": "cd987859-06fe-4b1a-9e96-47d4f36bf819",
"find_return": json.dumps(
{
"created_at": "2020-09-16T18:48:06.371563",
"created_by": "adora@example.com",
"result_type": "file",
"description": "This new result replaced the broken one",
"name": "New Sword of Protection result",
"result_id": "cd987859-06fe-4b1a-9e96-47d4f36bf819",
},
indent=4,
sort_keys=True,
),
"email": "catra@example.com",
"return": json.dumps(
{"message": "Successfully deleted 1 row"}, indent=4, sort_keys=True
),
"interactive": {
"input": "y",
"message": "Result with id cd987859-06fe-4b1a-9e96-47d4f36bf819 was created by adora@example.com. "
"Are you sure you want to delete? [y/N]: y\n",
},
},
{
"args": ["result", "delete", "cd987859-06fe-4b1a-9e96-47d4f36bf819"],
"id": "cd987859-06fe-4b1a-9e96-47d4f36bf819",
"find_return": json.dumps(
{
"created_at": "2020-09-16T18:48:06.371563",
"created_by": "adora@example.com",
"result_type": "file",
"description": "This new result replaced the broken one",
"name": "New Sword of Protection result",
"result_id": "cd987859-06fe-4b1a-9e96-47d4f36bf819",
},
indent=4,
sort_keys=True,
),
"email": "catra@example.com",
"return": "",
"interactive": {
"input": "n",
"message": "Result with id cd987859-06fe-4b1a-9e96-47d4f36bf819 was created by adora@example.com. "
"Are you sure you want to delete? [y/N]: n",
},
"logging": "Okay, aborting delete operation",
},
{
"args": ["result", "delete", "cd987859-06fe-4b1a-9e96-47d4f36bf819"],
"id": "cd987859-06fe-4b1a-9e96-47d4f36bf819",
"find_return": json.dumps(
{
"title": "No result found",
"status": 404,
"detail": "No result found with the specified ID",
},
indent=4,
sort_keys=True,
),
"email": "adora@example.com",
"return": json.dumps(
{
"title": "No result found",
"status": 404,
"detail": "No result found with the specified ID",
},
indent=4,
sort_keys=True,
),
},
]
)
def delete_data(request):
# We want to load the value from "email" from config
mockito.when(config).load_var("email").thenReturn(request.param["email"])
# Set all requests to return None so only the one we expect will return a value
mockito.when(results).delete(...).thenReturn(None)
mockito.when(results).find_by_id(...).thenReturn(None)
# Mock up request response
mockito.when(results).delete(request.param["id"]).thenReturn(
request.param["return"]
)
mockito.when(results).find_by_id(request.param["id"]).thenReturn(
request.param["find_return"]
)
return request.param
def test_delete(delete_data, caplog):
caplog.set_level(logging.INFO)
runner = CliRunner()
# Include interactive input and expected message if this test should trigger interactive stuff
if "interactive" in delete_data:
expected_output = (
delete_data["interactive"]["message"] + delete_data["return"] + "\n"
)
result = runner.invoke(
carrot, delete_data["args"], input=delete_data["interactive"]["input"]
)
assert result.output == expected_output
else:
result = runner.invoke(carrot, delete_data["args"])
assert result.output == delete_data["return"] + "\n"
# If we expect logging that we want to check, make sure it's there
if "logging" in delete_data:
assert delete_data["logging"] in caplog.text
@pytest.fixture(
params=[
{
"args": [
"result",
"map_to_template",
"3d1bfbab-d9ec-46c7-aa8e-9c1d1808f2b8",
"cd987859-06fe-4b1a-9e96-47d4f36bf819",
"out_horde_tanks",
"--created_by",
"adora@example.com",
],
"params": [
"cd987859-06fe-4b1a-9e96-47d4f36bf819",
"3d1bfbab-d9ec-46c7-aa8e-9c1d1808f2b8",
"out_horde_tanks",
"adora@example.com",
],
"return": json.dumps(
{
"template_id": "cd987859-06fe-4b1a-9e96-47d4f36bf819",
"result_id": "3d1bfbab-d9ec-46c7-aa8e-9c1d1808f2b8",
"result_key": "out_horde_tanks",
"created_at": "2020-09-24T19:07:59.311462",
"created_by": "rogelio@example.com",
},
indent=4,
sort_keys=True,
),
},
{
"args": [
"result",
"map_to_template",
"3d1bfbab-d9ec-46c7-aa8e-9c1d1808f2b8",
"cd987859-06fe-4b1a-9e96-47d4f36bf819",
"out_horde_tanks",
],
"params": [],
"logging": "No email config variable set. If a value is not specified for --created by, "
"there must be a value set for email.",
},
{
"args": ["result", "map_to_template"],
"params": [],
"return": "Usage: carrot_cli result map_to_template [OPTIONS] ID TEMPLATE_ID RESULT_KEY\n"
"Try 'carrot_cli result map_to_template --help' for help.\n"
"\n"
"Error: Missing argument 'ID'.",
},
]
)
def map_to_template_data(request):
# Set all requests to return None so only the one we expect will return a value
mockito.when(template_results).create_map(...).thenReturn(None)
# Mock up request response only if we expect it to get that far
if len(request.param["params"]) > 0:
mockito.when(template_results).create_map(
request.param["params"][0],
request.param["params"][1],
request.param["params"][2],
request.param["params"][3],
).thenReturn(request.param["return"])
return request.param
def test_map_to_template(map_to_template_data, caplog):
runner = CliRunner()
result = runner.invoke(carrot, map_to_template_data["args"])
if "logging" in map_to_template_data:
assert map_to_template_data["logging"] in caplog.text
else:
assert result.output == map_to_template_data["return"] + "\n"
| 35.089908 | 115 | 0.487764 | 1,861 | 19,124 | 4.908651 | 0.105857 | 0.053859 | 0.042036 | 0.084072 | 0.832293 | 0.775479 | 0.704215 | 0.675096 | 0.632841 | 0.622989 | 0 | 0.089384 | 0.382817 | 19,124 | 544 | 116 | 35.154412 | 0.684572 | 0.048996 | 0 | 0.639279 | 0 | 0.004008 | 0.330637 | 0.089924 | 0 | 0 | 0 | 0 | 0.02004 | 1 | 0.028056 | false | 0 | 0.016032 | 0 | 0.056112 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 4 |
78a423cb7230ea949084c2f335b8d7a0ab098f63 | 171 | py | Python | ipping.py | restlessankyyy/Python | c46ea72cda782ce21738e4792c436637b66d12a8 | [
"bzip2-1.0.6"
] | null | null | null | ipping.py | restlessankyyy/Python | c46ea72cda782ce21738e4792c436637b66d12a8 | [
"bzip2-1.0.6"
] | null | null | null | ipping.py | restlessankyyy/Python | c46ea72cda782ce21738e4792c436637b66d12a8 | [
"bzip2-1.0.6"
] | null | null | null | import os
hostname ="127.0.0.1"
response = os.system("ping -n 1 "+hostname)
if response ==0:
print (hostname, "is up!")
else:
print(hostname,"is down")
| 19 | 44 | 0.602339 | 26 | 171 | 3.961538 | 0.615385 | 0.252427 | 0.291262 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.060606 | 0.22807 | 171 | 8 | 45 | 21.375 | 0.719697 | 0 | 0 | 0 | 0 | 0 | 0.196319 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.142857 | 0 | 0.142857 | 0.285714 | 1 | 0 | 0 | null | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 4 |
78aa95b766f729ebf201ef15c63ab80e29b3a8d7 | 503 | py | Python | test_package.py | fangohr/micromagnetics | 87ea834234f44c2728a4f9ec77f900313ba083d3 | [
"BSD-2-Clause"
] | null | null | null | test_package.py | fangohr/micromagnetics | 87ea834234f44c2728a4f9ec77f900313ba083d3 | [
"BSD-2-Clause"
] | null | null | null | test_package.py | fangohr/micromagnetics | 87ea834234f44c2728a4f9ec77f900313ba083d3 | [
"BSD-2-Clause"
] | null | null | null | import numpy as np
def test_can_import():
import micromagnetictestcases
micromagnetictestcases
def test_can_access_macrospin_solution():
import micromagnetictestcases
# random test point
assert np.array([1.]) == \
micromagnetictestcases.macrospin.solution(0.1, 1, 1, [0])
def test_can_access_domainwall_solution():
import micromagnetictestcases
assert np.allclose(
micromagnetictestcases.domainwall.solution(1, 1, 1, 1),
np.array([0.46211716]))
| 23.952381 | 65 | 0.72167 | 56 | 503 | 6.303571 | 0.357143 | 0.028329 | 0.084986 | 0.090652 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.046455 | 0.186879 | 503 | 20 | 66 | 25.15 | 0.816626 | 0.033797 | 0 | 0.230769 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.153846 | 1 | 0.230769 | true | 0 | 0.384615 | 0 | 0.615385 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 4 |
78b0de680ae93be2025bf7594a096a0ee793fdb5 | 188 | py | Python | nmr/gui/__init__.py | jnejc/Mercury_control | a3ac73a18257c4ac804a20553f049b74977289c2 | [
"MIT"
] | null | null | null | nmr/gui/__init__.py | jnejc/Mercury_control | a3ac73a18257c4ac804a20553f049b74977289c2 | [
"MIT"
] | null | null | null | nmr/gui/__init__.py | jnejc/Mercury_control | a3ac73a18257c4ac804a20553f049b74977289c2 | [
"MIT"
] | null | null | null |
print("Importing log package")
import gui.main
__all__ = [
'main'
]
#pep-8 79 char line limit :)
#123456789112345678921234567893123456789412345678951234567896123456789712345678 | 17.090909 | 79 | 0.771277 | 16 | 188 | 8.8125 | 0.9375 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.50625 | 0.148936 | 188 | 11 | 79 | 17.090909 | 0.375 | 0.558511 | 0 | 0 | 0 | 0 | 0.308642 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.4 | 0 | 0.4 | 0.2 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 4 |
78cef0408113bed1982e52229c6435540e3749e8 | 103 | py | Python | DQM/SiStripMonitorDigi/python/SiStripMonitorDigi_RealData_cfi.py | ckamtsikis/cmssw | ea19fe642bb7537cbf58451dcf73aa5fd1b66250 | [
"Apache-2.0"
] | 852 | 2015-01-11T21:03:51.000Z | 2022-03-25T21:14:00.000Z | DQM/SiStripMonitorDigi/python/SiStripMonitorDigi_RealData_cfi.py | ckamtsikis/cmssw | ea19fe642bb7537cbf58451dcf73aa5fd1b66250 | [
"Apache-2.0"
] | 30,371 | 2015-01-02T00:14:40.000Z | 2022-03-31T23:26:05.000Z | DQM/SiStripMonitorDigi/python/SiStripMonitorDigi_RealData_cfi.py | ckamtsikis/cmssw | ea19fe642bb7537cbf58451dcf73aa5fd1b66250 | [
"Apache-2.0"
] | 3,240 | 2015-01-02T05:53:18.000Z | 2022-03-31T17:24:21.000Z | import FWCore.ParameterSet.Config as cms
from DQM.SiStripMonitorDigi.SiStripMonitorDigi_cfi import *
| 20.6 | 59 | 0.854369 | 12 | 103 | 7.25 | 0.833333 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.097087 | 103 | 4 | 60 | 25.75 | 0.935484 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 4 |
1524b1c0bd1e15a47c39710f19e9f56e0cd9a055 | 127 | py | Python | app/schemas/__init__.py | scott2b/Starlight | b5454e3ff50b35dd322065f204220cedd8e5da95 | [
"MIT"
] | null | null | null | app/schemas/__init__.py | scott2b/Starlight | b5454e3ff50b35dd322065f204220cedd8e5da95 | [
"MIT"
] | 1 | 2020-12-08T22:17:20.000Z | 2020-12-08T22:17:20.000Z | app/schemas/__init__.py | scott2b/Starlight | b5454e3ff50b35dd322065f204220cedd8e5da95 | [
"MIT"
] | 1 | 2020-12-08T19:27:30.000Z | 2020-12-08T19:27:30.000Z | #from .msg import Msg
#from .token import Token, TokenPayload
#from .user import User, UserCreate, UserInDB, UserUpdateRequest
| 31.75 | 64 | 0.795276 | 16 | 127 | 6.3125 | 0.5625 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.125984 | 127 | 3 | 65 | 42.333333 | 0.90991 | 0.952756 | 0 | null | 0 | null | 0 | 0 | null | 0 | 0 | 0 | null | 1 | null | true | 0 | 0 | null | null | null | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 4 |
152bca5cb033bf8cd61e479a27808ee8612e0dc7 | 162 | py | Python | pyras/controllers/hecras/hecrasgeometry/ras500.py | solomonvimal/pyras | 5819d19eddc9165ac5179f4651f25fd5ecee70a3 | [
"MIT"
] | 11 | 2015-06-04T16:42:45.000Z | 2021-06-06T18:10:34.000Z | pyras/controllers/hecras/hecrasgeometry/ras500.py | solomonvimal/pyras | 5819d19eddc9165ac5179f4651f25fd5ecee70a3 | [
"MIT"
] | null | null | null | pyras/controllers/hecras/hecrasgeometry/ras500.py | solomonvimal/pyras | 5819d19eddc9165ac5179f4651f25fd5ecee70a3 | [
"MIT"
] | 10 | 2018-07-24T09:01:23.000Z | 2021-08-31T16:44:12.000Z |
from . import ras41
class Geometry(ras41.Geometry):
"""HECRAS Geomerty version RAS500"""
def __init__(self):
super(Geometry, self).__init__()
| 16.2 | 40 | 0.666667 | 18 | 162 | 5.555556 | 0.722222 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.054688 | 0.209877 | 162 | 9 | 41 | 18 | 0.726563 | 0.185185 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.25 | false | 0 | 0.25 | 0 | 0.75 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 4 |
1591f7cbaea5be1ce887052786b5f9c72af1e8de | 344 | py | Python | agent/win/vdi-agent-1.93.3-win_x64/python/Lib/site-packages/win32ctypes/pywin32/__init__.py | dnegorov/skala-tools | d26f03b20282ed45e718b7c10318ec40611b41eb | [
"MIT"
] | null | null | null | agent/win/vdi-agent-1.93.3-win_x64/python/Lib/site-packages/win32ctypes/pywin32/__init__.py | dnegorov/skala-tools | d26f03b20282ed45e718b7c10318ec40611b41eb | [
"MIT"
] | null | null | null | agent/win/vdi-agent-1.93.3-win_x64/python/Lib/site-packages/win32ctypes/pywin32/__init__.py | dnegorov/skala-tools | d26f03b20282ed45e718b7c10318ec40611b41eb | [
"MIT"
] | null | null | null | #
# (C) Copyright 2014 Enthought, Inc., Austin, TX
# All right reserved.
#
# This file is open source software distributed according to the terms in
# LICENSE.txt
#
from win32ctypes.pywin32 import pywintypes
from win32ctypes.pywin32 import win32api
from win32ctypes.pywin32 import win32cred
__all__ = ['win32api', 'win32cred', 'pywintypes']
| 22.933333 | 73 | 0.770349 | 43 | 344 | 6.069767 | 0.72093 | 0.172414 | 0.252874 | 0.321839 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.081633 | 0.145349 | 344 | 14 | 74 | 24.571429 | 0.806122 | 0.436047 | 0 | 0 | 0 | 0 | 0.145161 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.75 | 0 | 0.75 | 0 | 0 | 0 | 0 | null | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 4 |
1594ab1edbefc90bb1dbf640e1fcc39b49f2d0aa | 254 | py | Python | lennonwall/models.py | peterhychan/lennon_wall | f918a4d69d9feb7bcf9d03c4636d2e3084c06d5a | [
"MIT"
] | 1 | 2021-01-29T11:35:36.000Z | 2021-01-29T11:35:36.000Z | lennonwall/models.py | peterhychan/lennon_wall | f918a4d69d9feb7bcf9d03c4636d2e3084c06d5a | [
"MIT"
] | null | null | null | lennonwall/models.py | peterhychan/lennon_wall | f918a4d69d9feb7bcf9d03c4636d2e3084c06d5a | [
"MIT"
] | null | null | null | from datetime import datetime
from lennonwall import db
class Message(db.Model):
id=db.Column(db.Integer, primary_key=True)
name=db.Column(db.String(50))
body=db.Column(db.String(200))
time=db.Column(db.DateTime, default=datetime.utcnow, index=True) | 31.75 | 65 | 0.779528 | 42 | 254 | 4.690476 | 0.547619 | 0.162437 | 0.203046 | 0.162437 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.021459 | 0.082677 | 254 | 8 | 65 | 31.75 | 0.824034 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.285714 | 0 | 1 | 0 | 0 | 0 | 0 | null | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 4 |
ec8179918e119473c723d83f0ac28fdc9e9ae6ac | 89 | py | Python | dml/CNN/__init__.py | Edelweiss35/deep-machine-learning | b1e4b133609f303be77de824601925f448a94764 | [
"WTFPL"
] | 708 | 2015-01-07T20:17:58.000Z | 2022-03-07T02:30:42.000Z | dml/CNN/__init__.py | Edelweiss35/deep-machine-learning | b1e4b133609f303be77de824601925f448a94764 | [
"WTFPL"
] | 2 | 2016-12-15T03:15:57.000Z | 2021-06-16T01:25:13.000Z | dml/CNN/__init__.py | Edelweiss35/deep-machine-learning | b1e4b133609f303be77de824601925f448a94764 | [
"WTFPL"
] | 333 | 2015-01-09T06:51:46.000Z | 2022-01-16T08:49:58.000Z | import numpy as np
import scipy as sp
from .CNN import CNNC,LayerC
__all__ = ['CNNC'
]
| 11.125 | 28 | 0.719101 | 15 | 89 | 4 | 0.733333 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.202247 | 89 | 7 | 29 | 12.714286 | 0.84507 | 0 | 0 | 0 | 0 | 0 | 0.044944 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.6 | 0 | 0.6 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 4 |
ec95c770d18b3575f0d41fc4222c2276975f90c7 | 74 | py | Python | ImageSeeker/utils/__init__.py | entbappy/ImageSeeker-Package | e50f45e5195f006352775d48c3e9b454cf22bc3e | [
"MIT"
] | 5 | 2021-09-19T07:31:34.000Z | 2021-12-02T20:24:43.000Z | ImageSeeker/utils/__init__.py | entbappy/ImageSeeker-Package | e50f45e5195f006352775d48c3e9b454cf22bc3e | [
"MIT"
] | null | null | null | ImageSeeker/utils/__init__.py | entbappy/ImageSeeker-Package | e50f45e5195f006352775d48c3e9b454cf22bc3e | [
"MIT"
] | 3 | 2021-09-21T15:57:47.000Z | 2021-11-30T09:11:16.000Z | '''
@author: Bappy Ahmed
Email: entbappy73@gmail.com
Date: 06-sep-2021
''' | 14.8 | 27 | 0.702703 | 11 | 74 | 4.727273 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.121212 | 0.108108 | 74 | 5 | 28 | 14.8 | 0.666667 | 0.891892 | 0 | null | 0 | null | 0 | 0 | null | 0 | 0 | 0 | null | 1 | null | true | 0 | 0 | null | null | null | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 4 |
ec9ba515d95b0ef468db1373cb533ea15e3c2857 | 30,061 | py | Python | bomeba0/templates/aminoacids.py | aloctavodia/bomeba0 | e212986d8ee60be1da91d63a7a889db14ec851c3 | [
"Apache-2.0"
] | null | null | null | bomeba0/templates/aminoacids.py | aloctavodia/bomeba0 | e212986d8ee60be1da91d63a7a889db14ec851c3 | [
"Apache-2.0"
] | 28 | 2017-06-01T15:46:33.000Z | 2021-07-01T18:28:36.000Z | bomeba0/templates/aminoacids.py | aloctavodia/bomeba0 | e212986d8ee60be1da91d63a7a889db14ec851c3 | [
"Apache-2.0"
] | 6 | 2017-09-30T13:26:08.000Z | 2022-02-13T10:01:18.000Z | from collections import namedtuple
import numpy as np
"""
Templates for amino acidic residues
"""
AA_info = namedtuple('AA_info', 'coords atom_names bonds bb sc offset')
A_info = AA_info(coords=np.array([[-0.75, -1.26, -0.51],
[-0.04, 0.03, -0.48],
[1.47, -0.14, -0.46],
[2.04, -1.21, -0.48],
[-0.5, 0.86, 0.73],
[-0.07, -2.02, -0.5],
[-0.27, 0.58, -1.4],
[-1.59, 1.01, 0.69],
[-0.26, 0.35, 1.66],
[-0.02, 1.84, 0.74]]),
atom_names=['N', 'CA', 'C', 'O', 'CB',
'H', 'HA', 'HB1', 'HB2', 'HB3'],
bb=[0, 1, 2, 3, 5, 6],
sc=[4, 7, 8, 9],
bonds=[(0, 1), (0, 5), (1, 2), (1, 4), (1, 6),
(2, 3), (4, 7), (4, 8), (4, 9)],
offset=10)
R_info = AA_info(coords=np.array([[-0.07, -3.66, 2.53],
[0.51, -2.96, 1.34],
[2.04, -2.96, 1.38],
[2.67, -3.46, 2.27],
[-0.07, -1.52, 1.29],
[0.2, -0.77, -0.05],
[-0.38, 0.65, -0.],
[-0.14, 1.37, -1.3],
[-0.49, 2.57, -1.61],
[-1.11, 3.37, -0.79],
[-0.21, 3.05, -2.81],
[0.61, -4.02, 3.2],
[0.22, -3.52, 0.45],
[0.34, -0.95, 2.13],
[-1.15, -1.57, 1.45],
[-0.25, -1.33, -0.88],
[1.27, -0.71, -0.25],
[0.08, 1.22, 0.81],
[-1.45, 0.62, 0.2],
[0.34, 0.81, -2.],
[-1.35, 3.05, 0.16],
[-1.39, 4.32, -1.01],
[0.28, 2.45, -3.46],
[-0.48, 4.01, -3.04]]),
atom_names=['N', 'CA', 'C', 'O', 'CB', 'CG', 'CD', 'NE', 'CZ', 'NH1', 'NH2', 'H', 'HA',
'HB2', 'HB3', 'HG2', 'HG3', 'HD2', 'HD3', 'HE', 'HH11', 'HH12', 'HH21', 'HH22'],
bb=[0, 1, 2, 3, 11, 12],
sc=[4, 5, 6, 7, 8, 9, 10, 13, 14, 15,
16, 17, 18, 19, 20, 21, 22, 23],
bonds=[(0, 1), (0, 11), (1, 2), (1, 4), (1, 12), (2, 3), (4, 5), (4, 13), (4, 14), (5, 6), (5, 15), (5, 16),
(6, 7), (6, 17), (6, 18), (7, 8), (7, 19), (8, 9), (8, 10), (9, 20), (9, 21), (10, 22), (10, 23)],
offset=24)
N_info = AA_info(coords=np.array([[0.15, -1.78, -0.63],
[0.76, -0.44, -0.59],
[2.28, -0.5, -0.63],
[2.93, -1.53, -0.6],
[0.3, 0.37, 0.64],
[-1.21, 0.48, 0.76],
[-1.84, 1.38, -0.01],
[-1.85, -0.21, 1.53],
[0.87, -2.5, -0.61],
[0.47, 0.1, -1.5],
[0.73, 1.37, 0.61],
[0.68, -0.11, 1.55],
[-2.85, 1.45, 0.04],
[-1.33, 1.96, -0.66]]),
atom_names=['N', 'CA', 'C', 'O', 'CB', 'CG', 'ND2',
'OD1', 'H', 'HA', 'HB2', 'HB3', 'HD21', 'HD22'],
bb=[0, 1, 2, 3, 8, 9],
sc=[4, 5, 6, 7, 10, 11, 12, 13],
bonds=[(0, 1), (0, 8), (1, 2), (1, 4), (1, 9), (2, 3), (4, 5),
(4, 10), (4, 11), (5, 6), (5, 7), (6, 12), (6, 13)],
offset=14)
D_info = AA_info(coords=np.array([[-0.67, -1.84, -0.63],
[-0.06, -0.49, -0.62],
[1.46, -0.53, -0.62],
[2.11, -1.56, -0.64],
[-0.58, 0.33, 0.59],
[-0.08, 1.77, 0.62],
[-0., 2.38, -0.43],
[0.17, 2.25, 1.71],
[0.06, -2.55, -0.64],
[-0.34, 0.03, -1.54],
[-0.29, -0.16, 1.51],
[-1.67, 0.36, 0.56]]),
atom_names=['N', 'CA', 'C', 'O', 'CB', 'CG',
'OD1', 'OD2', 'H', 'HA', 'HB2', 'HB3'],
bb=[0, 1, 2, 3, 8, 9],
sc=[4, 5, 6, 7, 10, 11],
bonds=[(0, 1), (0, 8), (1, 2), (1, 4), (1, 9), (2, 3),
(4, 5), (4, 10), (4, 11), (5, 6), (5, 7)],
offset=12)
C_info = AA_info(coords=np.array([[-0.72, -1.62, -0.64],
[-0.12, -0.27, -0.64],
[1.39, -0.31, -0.63],
[2.05, -1.33, -0.62],
[-0.67, 0.53, 0.56],
[-0.17, 2.29, 0.55],
[0.01, -2.32, -0.65],
[-0.41, 0.24, -1.56],
[-0.32, 0.08, 1.5],
[-1.76, 0.5, 0.54],
[0.79, 2.19, 1.49]]),
atom_names=['N', 'CA', 'C', 'O', 'CB',
'SG', 'H', 'HA', 'HB2', 'HB3', 'HG'],
bb=[0, 1, 2, 3, 6, 7],
sc=[4, 5, 8, 9, 10],
bonds=[(0, 1), (0, 6), (1, 2), (1, 4), (1, 7),
(2, 3), (4, 5), (4, 8), (4, 9), (5, 10)],
offset=11)
E_info = AA_info(coords=np.array([[-0.55, -2.38, -1.05],
[0.04, -1.01, -1.02],
[1.56, -1.05, -1.05],
[2.19, -2.09, -1.05],
[-0.48, -0.21, 0.21],
[0.01, 1.27, 0.29],
[-0.41, 2.11, 1.49],
[-1.17, 1.52, 2.39],
[-0.01, 3.23, 1.6],
[0.12, -3.15, -1.04],
[-0.26, -0.48, -1.95],
[-0.18, -0.74, 1.12],
[-1.58, -0.22, 0.2],
[-0.31, 1.83, -0.58],
[1.1, 1.31, 0.31]]),
atom_names=['N', 'CA', 'C', 'O', 'CB', 'CG', 'CD',
'OE1', 'OE2', 'H', 'HA', 'HB2', 'HB3', 'HG2', 'HG3'],
bb=[0, 1, 2, 3, 9, 10],
sc=[4, 5, 6, 7, 8, 11, 12, 13, 14],
bonds=[(0, 1), (0, 9), (1, 2), (1, 4), (1, 10), (2, 3), (4, 5),
(4, 11), (4, 12), (5, 6), (5, 13), (5, 14), (6, 7), (6, 8)],
offset=15)
Q_info = AA_info(coords=np.array([[-0.39, -2.48, -1.42],
[0.22, -1.13, -1.37],
[1.74, -1.19, -1.41],
[2.39, -2.22, -1.38],
[-0.29, -0.37, -0.12],
[0.19, 1.11, -0.04],
[-0.26, 1.91, 1.18],
[-1.02, 1.3, 2.12],
[0.09, 3.06, 1.34],
[0.33, -3.2, -1.4],
[-0.07, -0.6, -2.28],
[0.02, -0.91, 0.77],
[-1.39, -0.38, -0.15],
[-0.14, 1.65, -0.93],
[1.28, 1.13, -0.04],
[-1.28, 1.82, 2.94],
[-1.3, 0.34, 2.01]]),
atom_names=['N', 'CA', 'C', 'O', 'CB', 'CG', 'CD', 'NE2',
'OE1', 'H', 'HA', 'HB2', 'HB3', 'HG2', 'HG3', 'HE21', 'HE22'],
bb=[0, 1, 2, 3, 9, 10],
sc=[4, 5, 6, 7, 8, 11, 12, 13, 14, 15, 16],
bonds=[(0, 1), (0, 9), (1, 2), (1, 4), (1, 10), (2, 3), (4, 5), (4, 11),
(4, 12), (5, 6), (5, 13), (5, 14), (6, 7), (6, 8), (7, 15), (7, 16)],
offset=17)
G_info = AA_info(coords=np.array([[-1.25, 0.2, -0.25],
[0.2, 0.29, -0.51],
[1.04, -0.41, 0.54],
[0.6, -0.99, 1.5],
[-1.42, -0.33, 0.61],
[0.43, -0.17, -1.47],
[0.51, 1.34, -0.52]]),
atom_names=['N', 'CA', 'C', 'O', 'H', 'HA2', 'HA3'],
bb=[0, 1, 2, 3, 4, 5, 6],
sc=[],
bonds=[(0, 1), (0, 4), (1, 2), (1, 5), (1, 6), (2, 3)],
offset=7)
H_info = AA_info(coords=np.array([[0.48, -2.42, -1.17],
[1.07, -1.1, -0.85],
[2.58, -1.1, -0.89],
[3.22, -2.11, -1.12],
[0.58, -0.67, 0.57],
[-0.26, 0.58, 0.55],
[-1.64, 0.55, 0.39],
[0.19, 1.83, 0.69],
[-0.95, 2.55, 0.61],
[-2.06, 1.81, 0.42],
[1.15, -3.17, -1.33],
[0.75, -0.38, -1.62],
[1.41, -0.53, 1.25],
[-0.03, -1.48, 1.],
[-2.26, -0.33, 0.25],
[-0.89, 3.63, 0.69],
[-3.07, 2.19, 0.33]]),
atom_names=['N', 'CA', 'C', 'O', 'CB', 'CG', 'CD2', 'ND1',
'CE1', 'NE2', 'H', 'HA', 'HB2', 'HB3', 'HD2', 'HE1', 'HE2'],
bb=[0, 1, 2, 3, 10, 11],
sc=[4, 5, 6, 7, 8, 9, 12, 13, 14, 15, 16],
bonds=[(0, 1), (0, 10), (1, 2), (1, 4), (1, 11), (2, 3), (4, 5), (4, 12),
(4, 13), (5, 6), (5, 7), (6, 9), (6, 14), (7, 8), (8, 9), (8, 15), (9, 16)],
offset=17)
I_info = AA_info(coords=np.array([[0.35, -2.2, -1.14],
[0.87, -0.81, -1.13],
[2.39, -0.8, -1.14],
[3.1, -1.79, -1.14],
[0.3, 0.03, 0.06],
[-1.26, -0.04, 0.14],
[0.75, 1.51, 0.02],
[-1.85, 0.5, 1.47],
[1.11, -2.88, -1.16],
[0.58, -0.33, -2.07],
[0.7, -0.42, 0.98],
[-1.6, -1.07, 0.05],
[-1.7, 0.51, -0.69],
[1.84, 1.61, 0.05],
[0.39, 2.02, -0.88],
[0.38, 2.06, 0.89],
[-1.43, -0.04, 2.33],
[-1.66, 1.57, 1.61],
[-2.93, 0.36, 1.49]]),
atom_names=['N', 'CA', 'C', 'O', 'CB', 'CG1', 'CG2', 'CD1', 'H', 'HA',
'HB', 'HG12', 'HG13', 'HG21', 'HG22', 'HG23', 'HD11', 'HD12', 'HD13'],
bb=[0, 1, 2, 3, 8, 9],
sc=[4, 5, 6, 7, 10, 11, 12, 13, 14, 15, 16, 17, 18],
bonds=[(0, 1), (0, 8), (1, 2), (1, 4), (1, 9), (2, 3), (4, 5), (4, 6), (4, 10),
(5, 7), (5, 11), (5, 12), (6, 13), (6, 14), (6, 15), (7, 16), (7, 17), (7, 18)],
offset=19)
L_info = AA_info(coords=np.array([[0.63, -2.16, -0.9],
[1.25, -0.81, -0.9],
[2.77, -0.86, -0.91],
[3.41, -1.9, -0.9],
[0.75, 0.03, 0.31],
[-0.79, 0.2, 0.44],
[-1.11, 1.13, 1.64],
[-1.45, 0.77, -0.84],
[1.33, -2.9, -0.91],
[0.98, -0.29, -1.82],
[1.21, 1.02, 0.27],
[1.12, -0.44, 1.23],
[-1.24, -0.77, 0.65],
[-0.69, 0.73, 2.57],
[-0.7, 2.13, 1.49],
[-2.19, 1.23, 1.79],
[-1., 1.72, -1.13],
[-1.35, 0.06, -1.67],
[-2.52, 0.93, -0.68]]),
atom_names=['N', 'CA', 'C', 'O', 'CB', 'CG', 'CD1', 'CD2', 'H', 'HA',
'HB2', 'HB3', 'HG', 'HD11', 'HD12', 'HD13', 'HD21', 'HD22', 'HD23'],
bb=[0, 1, 2, 3, 8, 9],
sc=[4, 5, 6, 7, 10, 11, 12, 13, 14, 15, 16, 17, 18],
bonds=[(0, 1), (0, 8), (1, 2), (1, 4), (1, 9), (2, 3), (4, 5), (4, 10), (4, 11),
(5, 6), (5, 7), (5, 12), (6, 13), (6, 14), (6, 15), (7, 16), (7, 17), (7, 18)],
offset=19)
K_info = AA_info(coords=np.array([[-4.94e-01, -3.60e+00, -1.67e+00],
[1.09e-01, -2.26e+00, -1.68e+00],
[1.62e+00, -2.32e+00, -1.73e+00],
[2.28e+00, -3.33e+00, -1.62e+00],
[-3.98e-01, -1.46e+00, -4.42e-01],
[1.06e-01, -1.00e-03, -4.40e-01],
[-3.72e-01, 7.71e-01, 8.00e-01],
[2.11e-01, 2.19e+00, 8.10e-01],
[-3.47e-01, 3.07e+00, 1.89e+00],
[2.46e-01, -4.30e+00, -1.69e+00],
[-2.06e-01, -1.74e+00, -2.59e+00],
[-7.70e-02, -1.97e+00, 4.71e-01],
[-1.49e+00, -1.46e+00, -4.51e-01],
[-2.38e-01, 5.00e-01, -1.35e+00],
[1.20e+00, 8.00e-03, -4.58e-01],
[-6.10e-02, 2.36e-01, 1.71e+00],
[-1.47e+00, 8.16e-01, 8.01e-01],
[-1.10e-02, 2.70e+00, -1.29e-01],
[1.30e+00, 2.13e+00, 9.27e-01],
[-4.74e-01, 2.51e+00, 2.76e+00],
[2.81e-01, 3.86e+00, 2.10e+00],
[-1.27e+00, 3.44e+00, 1.62e+00]]),
atom_names=['N', 'CA', 'C', 'O', 'CB', 'CG', 'CD', 'CE', 'NZ', 'H', 'HA',
'HB2', 'HB3', 'HG2', 'HG3', 'HD2', 'HD3', 'HE2', 'HE3', 'HZ1', 'HZ2', 'HZ3'],
bb=[0, 1, 2, 3, 9, 10],
sc=[4, 5, 6, 7, 8, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21],
bonds=[(0, 1), (0, 9), (1, 2), (1, 4), (1, 10), (2, 3), (4, 5), (4, 11), (4, 12), (5, 6), (5, 13),
(5, 14), (6, 7), (6, 15), (6, 16), (7, 8), (7, 17), (7, 18), (8, 19), (8, 20), (8, 21)],
offset=22)
M_info = AA_info(coords=np.array([[1., -1.99, -1.18],
[1.53, -0.61, -1.18],
[3.04, -0.58, -1.22],
[3.76, -1.56, -1.15],
[1.02, 0.18, 0.05],
[-0.52, 0.32, 0.08],
[-1.04, 1.47, 1.4],
[-2.82, 1.13, 1.44],
[1.78, -2.65, -1.19],
[1.2, -0.1, -2.1],
[1.46, 1.18, 0.03],
[1.35, -0.31, 0.96],
[-0.97, -0.65, 0.26],
[-0.88, 0.71, -0.88],
[-3.25, 1.3, 0.45],
[-2.98, 0.1, 1.75],
[-3.3, 1.81, 2.16]]),
atom_names=['N', 'CA', 'C', 'O', 'CB', 'CG', 'SD', 'CE', 'H',
'HA', 'HB2', 'HB3', 'HG2', 'HG3', 'HE1', 'HE2', 'HE3'],
bb=[0, 1, 2, 3, 8, 9],
sc=[4, 5, 6, 7, 10, 11, 12, 13, 14, 15, 16],
bonds=[(0, 1), (0, 8), (1, 2), (1, 4), (1, 9), (2, 3), (4, 5), (4, 10),
(4, 11), (5, 6), (5, 12), (5, 13), (6, 7), (7, 14), (7, 15), (7, 16)],
offset=17)
F_info = AA_info(coords=np.array([[1.34, -1.84, -1.06],
[1.9, -0.47, -1.04],
[3.41, -0.47, -1.1],
[4.11, -1.47, -1.04],
[1.42, 0.32, 0.21],
[-0.1, 0.39, 0.34],
[-0.79, -0.61, 1.03],
[-0.82, 1.46, -0.2],
[-2.18, -0.57, 1.14],
[-2.21, 1.5, -0.09],
[-2.89, 0.49, 0.58],
[2.09, -2.53, -1.06],
[1.57, 0.06, -1.93],
[1.82, 1.33, 0.17],
[1.83, -0.14, 1.11],
[-0.25, -1.44, 1.47],
[-0.31, 2.26, -0.74],
[-2.71, -1.37, 1.66],
[-2.77, 2.33, -0.52],
[-3.98, 0.51, 0.66]]),
atom_names=['N', 'CA', 'C', 'O', 'CB', 'CG', 'CD1', 'CD2', 'CE1', 'CE2',
'CZ', 'H', 'HA', 'HB2', 'HB3', 'HD1', 'HD2', 'HE1', 'HE2', 'HZ'],
bb=[0, 1, 2, 3, 11, 12],
sc=[4, 5, 6, 7, 8, 9, 10, 13, 14, 15, 16, 17, 18, 19],
bonds=[(0, 1), (0, 11), (1, 2), (1, 4), (1, 12), (2, 3), (4, 5), (4, 13), (4, 14), (5, 6),
(5, 7), (6, 8), (6, 15), (7, 9), (7, 16), (8, 10), (8, 17), (9, 10), (9, 18), (10, 19)],
offset=20)
P_info = AA_info(coords=np.array([[0.73, -0.63, 1.11],
[1.17, 0.41, 0.14],
[1.07, 1.82, 0.72],
[0.6, 2.1, 1.8],
[0.27, 0.24, -1.09],
[-1.04, -0.26, -0.49],
[-0.57, -1.17, 0.65],
[2.22, 0.26, -0.14],
[0.69, -0.53, -1.75],
[0.14, 1.16, -1.66],
[-1.65, -0.8, -1.22],
[-1.62, 0.58, -0.09],
[-0.42, -2.18, 0.28],
[-1.29, -1.18, 1.47]]),
atom_names=['N', 'CA', 'C', 'O', 'CB', 'CG', 'CD',
'HA', 'HB2', 'HB3', 'HG2', 'HG3', 'HD2', 'HD3'],
bb=[0, 1, 2, 3, 7],
sc=[4, 5, 6, 8, 9, 10, 11, 12, 13],
bonds=[(0, 1), (0, 6), (1, 2), (1, 4), (1, 7), (2, 3), (4, 5),
(4, 8), (4, 9), (5, 6), (5, 10), (5, 11), (6, 12), (6, 13)],
offset=14)
S_info = AA_info(coords=np.array([[-0.66, -1.27, -0.65],
[0.01, 0.04, -0.69],
[1.52, -0.08, -0.71],
[2.12, -1.14, -0.71],
[-0.47, 0.93, 0.48],
[-0.02, 0.42, 1.73],
[0.04, -2.01, -0.72],
[-0.25, 0.54, -1.63],
[-1.56, 0.96, 0.47],
[-0.09, 1.94, 0.34],
[-0.38, -0.48, 1.86]]),
atom_names=['N', 'CA', 'C', 'O', 'CB',
'OG', 'H', 'HA', 'HB2', 'HB3', 'HG'],
bb=[0, 1, 2, 3, 6, 7],
sc=[4, 5, 8, 9, 10],
bonds=[(0, 1), (0, 6), (1, 2), (1, 4), (1, 7),
(2, 3), (4, 5), (4, 8), (4, 9), (5, 10)],
offset=11)
T_info = AA_info(coords=np.array([[-0.55, -2.02, -0.81],
[0.11, -0.69, -0.81],
[1.63, -0.81, -0.83],
[2.23, -1.87, -0.79],
[-0.38, 0.14, 0.42],
[0.23, 1.56, 0.53],
[-1.79, 0.31, 0.35],
[0.13, -2.78, -0.82],
[-0.16, -0.17, -1.72],
[-0.13, -0.41, 1.33],
[-2.07, 0.79, 1.15],
[-0.19, 2.08, 1.4],
[1.32, 1.53, 0.67],
[0., 2.16, -0.36]]),
atom_names=['N', 'CA', 'C', 'O', 'CB', 'CG2', 'OG1',
'H', 'HA', 'HB', 'HG1', 'HG21', 'HG22', 'HG23'],
bb=[0, 1, 2, 3, 7, 8],
sc=[4, 5, 6, 9, 10, 11, 12, 13],
bonds=[(0, 1), (0, 7), (1, 2), (1, 4), (1, 8), (2, 3), (4, 5),
(4, 6), (4, 9), (5, 11), (5, 12), (5, 13), (6, 10)],
offset=14)
W_info = AA_info(coords=np.array([[1.58, -2.74, -0.43],
[2.2, -1.39, -0.43],
[3.71, -1.44, -0.46],
[4.36, -2.47, -0.42],
[1.71, -0.57, 0.79],
[0.2, -0.32, 0.78],
[-0.75, -1.07, 1.46],
[-0.5, 0.65, 0.1],
[-1.84, 0.48, 0.37],
[-0.05, 1.67, -0.75],
[-2., -0.58, 1.2],
[-2.8, 1.31, -0.21],
[-1.01, 2.51, -1.33],
[-2.38, 2.33, -1.06],
[2.29, -3.47, -0.41],
[1.91, -0.87, -1.35],
[2.23, 0.38, 0.84],
[1.98, -1.11, 1.7],
[-0.59, -1.94, 2.09],
[-2.96, -0.99, 1.56],
[1., 1.81, -0.96],
[-3.87, 1.16, -0.01],
[-0.7, 3.3, -2.],
[-3.1, 2.99, -1.53]]),
atom_names=['N', 'CA', 'C', 'O', 'CB', 'CG', 'CD1', 'CD2', 'CE2', 'CE3', 'NE1', 'CZ2',
'CZ3', 'CH2', 'H', 'HA', 'HB2', 'HB3', 'HD1', 'HE1', 'HE3', 'HZ2', 'HZ3', 'HH2'],
bb=[0, 1, 2, 3, 14, 15],
sc=[4, 5, 6, 7, 8, 9, 10, 11, 12, 13,
16, 17, 18, 19, 20, 21, 22, 23],
bonds=[(0, 1), (0, 14), (1, 2), (1, 4), (1, 15), (2, 3), (4, 5), (4, 16), (4, 17), (5, 6), (5, 7), (6, 10), (6, 18),
(7, 8), (7, 9), (8, 10), (8, 11), (9, 12), (9, 20), (10, 19), (11, 13), (11, 21), (12, 13), (12, 22), (13, 23)],
offset=24)
Y_info = AA_info(coords=np.array([[-0.84, -2.19, 1.38],
[0.62, -2.08, 1.12],
[1.44, -2.84, 2.14],
[0.98, -3.39, 3.12],
[1.08, -0.6, 1.08],
[0.41, 0.26, 0.02],
[0.83, 0.23, -1.31],
[-0.63, 1.14, 0.38],
[0.21, 1.03, -2.27],
[-1.24, 1.94, -0.57],
[-0.82, 1.89, -1.9],
[-1.42, 2.68, -2.84],
[-1.05, -2.73, 2.23],
[0.85, -2.55, 0.16],
[2.16, -0.56, 0.92],
[0.92, -0.16, 2.07],
[1.64, -0.43, -1.61],
[-0.96, 1.19, 1.42],
[0.54, 1., -3.31],
[-2.04, 2.61, -0.27],
[-2.12, 3.21, -2.41]]),
atom_names=['N', 'CA', 'C', 'O', 'CB', 'CG', 'CD1', 'CD2', 'CE1', 'CE2',
'CZ', 'OH', 'H', 'HA', 'HB2', 'HB3', 'HD1', 'HD2', 'HE1', 'HE2', 'HH'],
bb=[0, 1, 2, 3, 12, 13],
sc=[4, 5, 6, 7, 8, 9, 10, 11, 14, 15, 16, 17, 18, 19, 20],
bonds=[(0, 1), (0, 12), (1, 2), (1, 4), (1, 13), (2, 3), (4, 5), (4, 14), (4, 15), (5, 6), (5, 7),
(6, 8), (6, 16), (7, 9), (7, 17), (8, 10), (8, 18), (9, 10), (9, 19), (10, 11), (11, 20)],
offset=21)
V_info = AA_info(coords=np.array([[-0.13, -2.06, -0.86],
[0.43, -0.69, -0.82],
[1.95, -0.72, -0.85],
[2.63, -1.73, -0.84],
[-0.12, 0.08, 0.42],
[0.53, 1.48, 0.61],
[-1.65, 0.27, 0.34],
[0.63, -2.74, -0.87],
[0.13, -0.17, -1.73],
[0.11, -0.51, 1.31],
[0.35, 2.13, -0.25],
[0.09, 1.97, 1.49],
[1.6, 1.41, 0.79],
[-2.17, -0.68, 0.23],
[-2.02, 0.74, 1.26],
[-1.93, 0.92, -0.49]]),
atom_names=['N', 'CA', 'C', 'O', 'CB', 'CG1', 'CG2', 'H', 'HA',
'HB', 'HG11', 'HG12', 'HG13', 'HG21', 'HG22', 'HG23'],
bb=[0, 1, 2, 3, 7, 8],
sc=[4, 5, 6, 9, 10, 11, 12, 13, 14, 15],
bonds=[(0, 1), (0, 7), (1, 2), (1, 4), (1, 8), (2, 3), (4, 5), (4, 6),
(4, 9), (5, 10), (5, 11), (5, 12), (6, 13), (6, 14), (6, 15)],
offset=16)
B_info = AA_info(coords=np.array([[ 1.12, 0.22, -0.24],
[ 1.74, -0.73, -0.65],
[-0.34, 0.14, 0.17],
[-0.47, -0.57, 0.98],
[-0.68, 1.12, 0.5 ],
[-0.95, -0.17, -0.69]]),
atom_names = ['C', 'O', 'CH3', 'HH31', 'HH32', 'HH33'],
bb = [0, 2],
sc = [1, 3, 4, 5],
bonds = [(0, 1), (0, 2), (2, 3), (2, 4), (2, 5)],
offset = 6)
Z_info = AA_info(coords=np.array([[ 2.23, 0.97, -0.68],
[ 3.68, 0.81, -0.52],
[ 1.91, 1.81, -0.21],
[ 3.93, 0.74, 0.55],
[ 4.02, -0.09, -1.03],
[ 4.2 , 1.68, -0.94]]),
atom_names = ['N', 'CH3', 'H', 'HH31', 'HH32', 'HH33'],
bb = [0, 2],
sc = [1, 3, 4, 5],
bonds = [(0, 1), (0, 2), (1, 3), (1, 4), (1, 5)],
offset = 6)
templates_aa = {'A': A_info, 'C': C_info, 'D': D_info, 'E': E_info,
'F': F_info, 'G': G_info, 'H': H_info, 'I': I_info,
'K': K_info, 'L': L_info, 'M': M_info, 'N': N_info,
'P': P_info, 'Q': Q_info, 'R': R_info, 'S': S_info,
'T': T_info, 'V': V_info, 'W': W_info, 'Y': Y_info,
'B': B_info, 'Z': Z_info}
one_to_three_aa = {'A': 'ALA', 'C': 'CYS', 'D': 'ASP', 'E': 'GLU', 'F': 'PHE',
'G': 'GLY', 'H': 'HIS', 'I': 'ILE', 'K': 'LYS', 'L': 'LEU',
'M': 'MET', 'N': 'ASN', 'P': 'PRO', 'Q': 'GLN', 'R': 'ARG',
'S': 'SER', 'T': 'THR', 'V': 'VAL', 'W': 'TRP', 'Y': 'TYR',
'B': 'ACE', 'Z': 'NME'}
three_to_one_aa = {val: key for key, val in one_to_three_aa.items()}
| 55.979516 | 136 | 0.225142 | 3,847 | 30,061 | 1.733039 | 0.078503 | 0.014099 | 0.041398 | 0.052797 | 0.375881 | 0.346033 | 0.319484 | 0.236538 | 0.215839 | 0.180591 | 0 | 0.339011 | 0.554705 | 30,061 | 536 | 137 | 56.083955 | 0.159047 | 0 | 0 | 0.097804 | 0 | 0 | 0.031181 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.003992 | 0 | 0.003992 | 0 | 0 | 0 | 1 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 4 |
eca23bda4d6550f1bffe92bb44ac0ae79732979c | 61 | py | Python | Variables and TypeCasting/Hello Friends.py | AshishJangra27/Python-Elite-Batch-GFG | 7b25f2083944ad152d9460924b0a061ba39b7246 | [
"Apache-2.0"
] | 1 | 2022-02-13T13:16:22.000Z | 2022-02-13T13:16:22.000Z | Variables and TypeCasting/Hello Friends.py | AshishJangra27/Python-Elite-Batch-GFG | 7b25f2083944ad152d9460924b0a061ba39b7246 | [
"Apache-2.0"
] | null | null | null | Variables and TypeCasting/Hello Friends.py | AshishJangra27/Python-Elite-Batch-GFG | 7b25f2083944ad152d9460924b0a061ba39b7246 | [
"Apache-2.0"
] | null | null | null | print(type("Ashish"))
print(123)
print(3.14)
print(True)
| 12.2 | 22 | 0.655738 | 10 | 61 | 4 | 0.7 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.113208 | 0.131148 | 61 | 4 | 23 | 15.25 | 0.641509 | 0 | 0 | 0 | 0 | 0 | 0.105263 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 4 |
ecb219b2826a9feace1d8e0765581982026bd303 | 146 | py | Python | example/main.py | hejingsong/sge-server | 0eecdf55db0093723182aa394db42f71a4431230 | [
"MIT"
] | null | null | null | example/main.py | hejingsong/sge-server | 0eecdf55db0093723182aa394db42f71a4431230 | [
"MIT"
] | null | null | null | example/main.py | hejingsong/sge-server | 0eecdf55db0093723182aa394db42f71a4431230 | [
"MIT"
] | null | null | null | #! /usr/bin/env python
#-*- coding:utf-8 -*-
def start(request, response):
response.end("<H1>Hello SgeServer.</H1>")
return True
| 18.25 | 46 | 0.59589 | 19 | 146 | 4.578947 | 0.894737 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.025862 | 0.205479 | 146 | 7 | 47 | 20.857143 | 0.724138 | 0.280822 | 0 | 0 | 0 | 0 | 0.260417 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.333333 | false | 0 | 0 | 0 | 0.666667 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 4 |
ecbf4dfb5895f611ecb3e06c39e5fc831b7b6287 | 85 | py | Python | public/index.py | jacksonsr45/new_app_python | 338d1ca1bea72cbc10efa5d915139af58e2dc7ce | [
"MIT"
] | null | null | null | public/index.py | jacksonsr45/new_app_python | 338d1ca1bea72cbc10efa5d915139af58e2dc7ce | [
"MIT"
] | null | null | null | public/index.py | jacksonsr45/new_app_python | 338d1ca1bea72cbc10efa5d915139af58e2dc7ce | [
"MIT"
] | null | null | null | from vendor.load import NewApp
class Main:
def __init__(self):
NewApp() | 14.166667 | 30 | 0.658824 | 11 | 85 | 4.727273 | 0.909091 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.258824 | 85 | 6 | 31 | 14.166667 | 0.825397 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.25 | false | 0 | 0.25 | 0 | 0.75 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 4 |
ecd40bb1a9b6f4d15f18f8eaa1051e3b2a510d0f | 165 | py | Python | backend/api/urls.py | kennyudekwu/dog-breed-classification | 51213ae2b15c4ec7b241c5c83ccd99bf82e7b612 | [
"MIT"
] | null | null | null | backend/api/urls.py | kennyudekwu/dog-breed-classification | 51213ae2b15c4ec7b241c5c83ccd99bf82e7b612 | [
"MIT"
] | null | null | null | backend/api/urls.py | kennyudekwu/dog-breed-classification | 51213ae2b15c4ec7b241c5c83ccd99bf82e7b612 | [
"MIT"
] | 2 | 2021-07-13T01:04:03.000Z | 2021-07-13T09:30:04.000Z | from django.urls import path
from django.urls.resolvers import URLPattern
from . import views
urlpatterns = [
path('predict/', views.result, name="inferece")
]
| 20.625 | 51 | 0.745455 | 21 | 165 | 5.857143 | 0.619048 | 0.162602 | 0.227642 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.145455 | 165 | 7 | 52 | 23.571429 | 0.87234 | 0 | 0 | 0 | 0 | 0 | 0.09697 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.5 | 0 | 0.5 | 0 | 1 | 0 | 0 | null | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 4 |
ecd4d146b9af550ed9d82e639aaa1b5dbdddee0c | 622 | py | Python | src/denoiser/losses/__init__.py | Hguimaraes/3Denoiser | 000ab990640c77407cb27af2c031396d97b02a1c | [
"MIT"
] | null | null | null | src/denoiser/losses/__init__.py | Hguimaraes/3Denoiser | 000ab990640c77407cb27af2c031396d97b02a1c | [
"MIT"
] | null | null | null | src/denoiser/losses/__init__.py | Hguimaraes/3Denoiser | 000ab990640c77407cb27af2c031396d97b02a1c | [
"MIT"
] | 1 | 2022-03-11T00:12:44.000Z | 2022-03-11T00:12:44.000Z | from denoiser.losses.metrics import task1_metric
from denoiser.losses.perceptual import PFPL
from denoiser.losses.perceptual import DeepFeatureLoss
from denoiser.losses.perceptual import CompoundedPerceptualLoss
from denoiser.losses.mrstft_loss import MultiResolutionSTFTLoss
from denoiser.losses.spectral_loss import STFTMagnitudeLoss
from denoiser.losses.spectral_loss import LogSTFTMagnitudeLoss
from denoiser.losses.wave_loss import WaveLoss
__all__ = [
'PFPL', 'DeepFeatureLoss', 'CompoundedPerceptualLoss', 'MultiResolutionSTFTLoss',
'STFTMagnitudeLoss', 'LogSTFTMagnitudeLoss', 'WaveLoss', 'task1_metric'
] | 47.846154 | 85 | 0.848875 | 63 | 622 | 8.222222 | 0.31746 | 0.185328 | 0.277992 | 0.162162 | 0.335907 | 0.138996 | 0 | 0 | 0 | 0 | 0 | 0.003509 | 0.083601 | 622 | 13 | 86 | 47.846154 | 0.905263 | 0 | 0 | 0 | 0 | 0 | 0.197432 | 0.075441 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.666667 | 0 | 0.666667 | 0 | 0 | 0 | 0 | null | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 4 |
ecf463d6007954e259fb8b7564a2b2cfabe0e154 | 279 | py | Python | mofa/assistants/migrations/0005_merge_20200114_1611.py | BoxInABoxICT/BoxPlugin | ad351978faa37ab867a86d2f4023a2b3e5a2ce19 | [
"Apache-2.0"
] | null | null | null | mofa/assistants/migrations/0005_merge_20200114_1611.py | BoxInABoxICT/BoxPlugin | ad351978faa37ab867a86d2f4023a2b3e5a2ce19 | [
"Apache-2.0"
] | 5 | 2020-06-06T01:07:51.000Z | 2021-06-09T18:52:55.000Z | mofa/assistants/migrations/0005_merge_20200114_1611.py | BoxInABoxICT/BoxPlugin | ad351978faa37ab867a86d2f4023a2b3e5a2ce19 | [
"Apache-2.0"
] | null | null | null | # Generated by Django 2.2.6 on 2020-01-14 15:11
from django.db import migrations
class Migration(migrations.Migration):
dependencies = [
('assistants', '0004_auto_20200113_1333'),
('assistants', '0004_auto_20200113_1046'),
]
operations = [
]
| 18.6 | 50 | 0.655914 | 33 | 279 | 5.363636 | 0.757576 | 0.158192 | 0.20339 | 0.293785 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.217593 | 0.225806 | 279 | 14 | 51 | 19.928571 | 0.601852 | 0.16129 | 0 | 0 | 1 | 0 | 0.284483 | 0.198276 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.125 | 0 | 0.5 | 0 | 0 | 0 | 0 | null | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 4 |
01f79a4868d7b55e4b71a3121061ff36b0407b41 | 1,055 | py | Python | FusionIIIT/applications/office_module/admin.py | 29rj/Fusion | bc2941a67532e183adeb0bc4042df0b182b9e3aa | [
"bzip2-1.0.6"
] | 29 | 2019-02-20T15:35:33.000Z | 2022-03-22T11:10:57.000Z | FusionIIIT/applications/office_module/admin.py | 29rj/Fusion | bc2941a67532e183adeb0bc4042df0b182b9e3aa | [
"bzip2-1.0.6"
] | 409 | 2019-01-17T19:30:51.000Z | 2022-03-31T16:28:45.000Z | FusionIIIT/applications/office_module/admin.py | 29rj/Fusion | bc2941a67532e183adeb0bc4042df0b182b9e3aa | [
"bzip2-1.0.6"
] | 456 | 2019-01-12T11:01:13.000Z | 2022-03-30T17:06:52.000Z | from django.contrib import admin
from .models import *
admin.site.register(Requisitions)
admin.site.register(Filemovement)
admin.site.register(stock)
admin.site.register(apply_for_purchase)
admin.site.register(quotations)
admin.site.register(Registrar_File)
admin.site.register(registrar_create_doc)
admin.site.register(registrar_general_section)
admin.site.register(registrar_purchase_sales_section)
admin.site.register(registrar_finance_section)
admin.site.register(registrar_establishment_section)
admin.site.register(registrar_director_section)
admin.site.register(Assistantship)
admin.site.register(hostel_allotment)
admin.site.register(hostel_capacity)
# registering Dean RSPC project management models
admin.site.register(Project_Registration)
admin.site.register(Project_Extension)
admin.site.register(Project_Closure)
admin.site.register(Project_Reallocation)
admin.site.register(Member)
admin.site.register(Registrar)
admin.site.register(vendor)
admin.site.register(purchase_commitee)
admin.site.register(LTC) | 32.96875 | 54 | 0.835071 | 133 | 1,055 | 6.451128 | 0.315789 | 0.251748 | 0.475524 | 0.242424 | 0.153846 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.070142 | 1,055 | 32 | 55 | 32.96875 | 0.874618 | 0.04455 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 0.076923 | 0 | 0.076923 | 0 | 0 | 0 | 0 | null | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 4 |
bf009cfa9b3afe48d2c5113a442b1735e479c699 | 1,987 | py | Python | darzalib/PacketBodyReader.py | swrlly/Midnight | b4375002761a13a09a6c3085e9b34384b28227ba | [
"MIT"
] | 2 | 2021-11-18T13:38:52.000Z | 2021-11-19T04:15:24.000Z | darzalib/PacketBodyReader.py | swrlly/Midnight | b4375002761a13a09a6c3085e9b34384b28227ba | [
"MIT"
] | null | null | null | darzalib/PacketBodyReader.py | swrlly/Midnight | b4375002761a13a09a6c3085e9b34384b28227ba | [
"MIT"
] | null | null | null | import struct
class PacketBodyReader:
def __init__(self, data):
# start from the beginning of the body, always assume no headers if you're starting to read
self.index = 0
self.buffer = data
def BytesLeft(self):
return len(self.buffer) - self.index
def ReadByte(self):
self.index += 1
return self.buffer[self.index - 1]
def ReadFloat(self):
tmp = struct.unpack("<f", self.buffer[self.index : self.index + 4])[0]
self.index += 4
return tmp
def ReadDouble(self):
tmp = struct.unpack("<d", self.buffer[self.index : self.index + 4])[0]
self.index += 4
return tmp
def ReadInt16(self):
tmp = struct.unpack("<h", self.buffer[self.index : self.index + 2])[0]
self.index += 2
return tmp
def ReadUInt16(self):
tmp = struct.unpack("<H", self.buffer[self.index : self.index + 2])[0]
self.index += 2
return tmp
def ReadInt32(self):
tmp = struct.unpack("<i", self.buffer[self.index : self.index + 4])[0]
self.index += 4
return tmp
def ReadUInt32(self):
tmp = struct.unpack("<I", self.buffer[self.index : self.index + 4])[0]
self.index += 4
return tmp
def ReadInt64(self):
tmp = struct.unpack("<q", self.buffer[self.index : self.index + 8])[0]
self.index += 8
return tmp
def ReadUInt64(self):
tmp = struct.unpack("<Q", self.buffer[self.index : self.index + 8])[0]
self.index += 8
return tmp
def ReadBoolean(self):
tmp = struct.unpack("<?", self.buffer[self.index : self.index + 1])[0]
self.index += 1
return tmp
def ReadString8(self):
"""
length: 8 bit unsigned integer
"""
length = self.ReadByte()
return self.ReadStringBytes(length)
def ReadString16(self):
length = self.ReadUInt16()
return self.ReadStringBytes(length)
def ReadString32(self):
length = self.ReadUInt32()
return self.ReadStringBytes(length)
def ReadStringBytes(self, length):
tmp = struct.unpack("<{}s".format(length), self.buffer[self.index : self.index + length])[0].decode()
self.index += length
return tmp
| 24.530864 | 103 | 0.669351 | 290 | 1,987 | 4.572414 | 0.213793 | 0.230769 | 0.126697 | 0.171946 | 0.523379 | 0.446456 | 0.404223 | 0.404223 | 0.404223 | 0.404223 | 0 | 0.032357 | 0.175642 | 1,987 | 80 | 104 | 24.8375 | 0.777167 | 0.060896 | 0 | 0.389831 | 0 | 0 | 0.011866 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.271186 | false | 0 | 0.016949 | 0.016949 | 0.559322 | 0 | 0 | 0 | 0 | null | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 4 |
bf23bc2fbb5f634738b11ad2600d9614a6ba935b | 143 | py | Python | src/bin/ntlm3/compat.py | amanttr/splunk-website-monitoring | 4c8093eebda32892c173e23a1e535cded1311ebd | [
"MIT"
] | 208 | 2015-01-08T18:14:02.000Z | 2022-03-31T02:45:42.000Z | src/bin/ntlm3/compat.py | amanttr/splunk-website-monitoring | 4c8093eebda32892c173e23a1e535cded1311ebd | [
"MIT"
] | 279 | 2015-01-16T16:30:35.000Z | 2020-03-31T11:57:47.000Z | src/bin/ntlm3/compat.py | amanttr/splunk-website-monitoring | 4c8093eebda32892c173e23a1e535cded1311ebd | [
"MIT"
] | 164 | 2015-01-21T13:49:05.000Z | 2021-12-01T18:13:05.000Z |
def _long(value):
try:
return long(value)
except NameError: # we're Python 3, we don't have longs
return int(value)
| 17.875 | 60 | 0.601399 | 21 | 143 | 4.047619 | 0.761905 | 0.211765 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.010101 | 0.307692 | 143 | 7 | 61 | 20.428571 | 0.848485 | 0.244755 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.2 | false | 0 | 0 | 0 | 0.6 | 0 | 1 | 0 | 0 | null | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 4 |
bf351a83f522449bc9020fd8a236537067fe9c7e | 10,611 | py | Python | tiff/test_parcels.py | anatoliy-kuznetsov/terrain | 4d20b836f62f136589c56cae05e77c5ebe48e4c2 | [
"MIT"
] | null | null | null | tiff/test_parcels.py | anatoliy-kuznetsov/terrain | 4d20b836f62f136589c56cae05e77c5ebe48e4c2 | [
"MIT"
] | null | null | null | tiff/test_parcels.py | anatoliy-kuznetsov/terrain | 4d20b836f62f136589c56cae05e77c5ebe48e4c2 | [
"MIT"
] | 2 | 2021-02-05T23:15:13.000Z | 2021-04-10T18:22:44.000Z | import logging
import unittest
import numpy
from tiff import parcels
class TestParcels(unittest.TestCase):
def test_build_flanges(self):
dataset = numpy.ones((20, 22))
config = {
"model": {
"surface_thickness_millimeters": 1.0,
"flange_thickness_millimeters": 1000.0,
},
"printer": {
"xy_resolution_microns": 1000.0,
}
}
parcel_shape = (7, 6)
with_flanges = parcels.build_flanges(config, dataset, parcel_shape, logging.getLogger("test"))
expected = numpy.array([
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 1, 1, 1, 1, 0, 0, 1, 1, 1, 1, 0, 0, 1, 1, 1, 1, 0, 0, 1, 1, 0],
[0, 1, 1, 1, 1, 0, 0, 1, 1, 1, 1, 0, 0, 1, 1, 1, 1, 0, 0, 1, 1, 0],
[0, 1, 1, 1, 1, 0, 0, 1, 1, 1, 1, 0, 0, 1, 1, 1, 1, 0, 0, 1, 1, 0],
[0, 1, 1, 1, 1, 0, 0, 1, 1, 1, 1, 0, 0, 1, 1, 1, 1, 0, 0, 1, 1, 0],
[0, 1, 1, 1, 1, 0, 0, 1, 1, 1, 1, 0, 0, 1, 1, 1, 1, 0, 0, 1, 1, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 1, 1, 1, 1, 0, 0, 1, 1, 1, 1, 0, 0, 1, 1, 1, 1, 0, 0, 1, 1, 0],
[0, 1, 1, 1, 1, 0, 0, 1, 1, 1, 1, 0, 0, 1, 1, 1, 1, 0, 0, 1, 1, 0],
[0, 1, 1, 1, 1, 0, 0, 1, 1, 1, 1, 0, 0, 1, 1, 1, 1, 0, 0, 1, 1, 0],
[0, 1, 1, 1, 1, 0, 0, 1, 1, 1, 1, 0, 0, 1, 1, 1, 1, 0, 0, 1, 1, 0],
[0, 1, 1, 1, 1, 0, 0, 1, 1, 1, 1, 0, 0, 1, 1, 1, 1, 0, 0, 1, 1, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 1, 1, 1, 1, 0, 0, 1, 1, 1, 1, 0, 0, 1, 1, 1, 1, 0, 0, 1, 1, 0],
[0, 1, 1, 1, 1, 0, 0, 1, 1, 1, 1, 0, 0, 1, 1, 1, 1, 0, 0, 1, 1, 0],
[0, 1, 1, 1, 1, 0, 0, 1, 1, 1, 1, 0, 0, 1, 1, 1, 1, 0, 0, 1, 1, 0],
[0, 1, 1, 1, 1, 0, 0, 1, 1, 1, 1, 0, 0, 1, 1, 1, 1, 0, 0, 1, 1, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
]).astype(numpy.float32)
numpy.testing.assert_array_equal(with_flanges, expected)
def test_parcels(self):
# we want to be able to visually identify if there's an item not in the correct parcel, so we can create
# a 2D array here where the X and Y coordinates are visually distinct by shifting one of them out by two
# orders of magnitude, so the value mod 100 is one index and the value / 100 is the other - this array
# will look like:
# [ 0, 1, 2, 3 ... 20, 21] - row 0
# [ 100, 101, 102, 103 ... 1020, 1021] - row 1
# ...
# [ 1900, 1901, 1912, 1913 ... 1920, 1921] - row 19
dataset = numpy.arange(20).reshape(20, 1) * 100 + numpy.arange(22)
actual = [parcel for index, parcel in parcels.parcels(dataset, (7, 6))]
expected = [
[[0, 1, 2, 3, 4, 5],
[100, 101, 102, 103, 104, 105],
[200, 201, 202, 203, 204, 205],
[300, 301, 302, 303, 304, 305],
[400, 401, 402, 403, 404, 405],
[500, 501, 502, 503, 504, 505],
[600, 601, 602, 603, 604, 605]],
[[6, 7, 8, 9, 10, 11],
[106, 107, 108, 109, 110, 111],
[206, 207, 208, 209, 210, 211],
[306, 307, 308, 309, 310, 311],
[406, 407, 408, 409, 410, 411],
[506, 507, 508, 509, 510, 511],
[606, 607, 608, 609, 610, 611]],
[[12, 13, 14, 15, 16, 17],
[112, 113, 114, 115, 116, 117],
[212, 213, 214, 215, 216, 217],
[312, 313, 314, 315, 316, 317],
[412, 413, 414, 415, 416, 417],
[512, 513, 514, 515, 516, 517],
[612, 613, 614, 615, 616, 617]],
[[18, 19, 20, 21],
[118, 119, 120, 121],
[218, 219, 220, 221],
[318, 319, 320, 321],
[418, 419, 420, 421],
[518, 519, 520, 521],
[618, 619, 620, 621]],
[[700, 701, 702, 703, 704, 705],
[800, 801, 802, 803, 804, 805],
[900, 901, 902, 903, 904, 905],
[1000, 1001, 1002, 1003, 1004, 1005],
[1100, 1101, 1102, 1103, 1104, 1105],
[1200, 1201, 1202, 1203, 1204, 1205],
[1300, 1301, 1302, 1303, 1304, 1305]],
[[706, 707, 708, 709, 710, 711],
[806, 807, 808, 809, 810, 811],
[906, 907, 908, 909, 910, 911],
[1006, 1007, 1008, 1009, 1010, 1011],
[1106, 1107, 1108, 1109, 1110, 1111],
[1206, 1207, 1208, 1209, 1210, 1211],
[1306, 1307, 1308, 1309, 1310, 1311]],
[[712, 713, 714, 715, 716, 717],
[812, 813, 814, 815, 816, 817],
[912, 913, 914, 915, 916, 917],
[1012, 1013, 1014, 1015, 1016, 1017],
[1112, 1113, 1114, 1115, 1116, 1117],
[1212, 1213, 1214, 1215, 1216, 1217],
[1312, 1313, 1314, 1315, 1316, 1317]],
[[718, 719, 720, 721],
[818, 819, 820, 821],
[918, 919, 920, 921],
[1018, 1019, 1020, 1021],
[1118, 1119, 1120, 1121],
[1218, 1219, 1220, 1221],
[1318, 1319, 1320, 1321]],
[[1400, 1401, 1402, 1403, 1404, 1405],
[1500, 1501, 1502, 1503, 1504, 1505],
[1600, 1601, 1602, 1603, 1604, 1605],
[1700, 1701, 1702, 1703, 1704, 1705],
[1800, 1801, 1802, 1803, 1804, 1805],
[1900, 1901, 1902, 1903, 1904, 1905]],
[[1406, 1407, 1408, 1409, 1410, 1411],
[1506, 1507, 1508, 1509, 1510, 1511],
[1606, 1607, 1608, 1609, 1610, 1611],
[1706, 1707, 1708, 1709, 1710, 1711],
[1806, 1807, 1808, 1809, 1810, 1811],
[1906, 1907, 1908, 1909, 1910, 1911]],
[[1412, 1413, 1414, 1415, 1416, 1417],
[1512, 1513, 1514, 1515, 1516, 1517],
[1612, 1613, 1614, 1615, 1616, 1617],
[1712, 1713, 1714, 1715, 1716, 1717],
[1812, 1813, 1814, 1815, 1816, 1817],
[1912, 1913, 1914, 1915, 1916, 1917]],
[[1418, 1419, 1420, 1421],
[1518, 1519, 1520, 1521],
[1618, 1619, 1620, 1621],
[1718, 1719, 1720, 1721],
[1818, 1819, 1820, 1821],
[1918, 1919, 1920, 1921]]
]
self.assertEqual(len(actual), len(expected))
for i in range(len(actual)):
numpy.testing.assert_array_equal(actual[i], expected[i])
def test_parcel_with_flanges(self):
dataset = numpy.ones((20, 22))
config = {
"model": {
"surface_thickness_millimeters": 1.0,
"flange_thickness_millimeters": 1000.0,
},
"printer": {
"xy_resolution_microns": 1000.0,
}
}
parcel_shape = (7, 6)
with_flanges = parcels.build_flanges(config, dataset, parcel_shape, logging.getLogger("test"))
actual = [parcel for index, parcel in parcels.parcels(with_flanges, parcel_shape)]
expected = [
[[0., 0., 0., 0., 0., 0.],
[0., 1., 1., 1., 1., 0.],
[0., 1., 1., 1., 1., 0.],
[0., 1., 1., 1., 1., 0.],
[0., 1., 1., 1., 1., 0.],
[0., 1., 1., 1., 1., 0.],
[0., 0., 0., 0., 0., 0.]],
[[0., 0., 0., 0., 0., 0.],
[0., 1., 1., 1., 1., 0.],
[0., 1., 1., 1., 1., 0.],
[0., 1., 1., 1., 1., 0.],
[0., 1., 1., 1., 1., 0.],
[0., 1., 1., 1., 1., 0.],
[0., 0., 0., 0., 0., 0.]],
[[0., 0., 0., 0., 0., 0.],
[0., 1., 1., 1., 1., 0.],
[0., 1., 1., 1., 1., 0.],
[0., 1., 1., 1., 1., 0.],
[0., 1., 1., 1., 1., 0.],
[0., 1., 1., 1., 1., 0.],
[0., 0., 0., 0., 0., 0.]],
[[0., 0., 0., 0.],
[0., 1., 1., 0.],
[0., 1., 1., 0.],
[0., 1., 1., 0.],
[0., 1., 1., 0.],
[0., 1., 1., 0.],
[0., 0., 0., 0.]],
[[0., 0., 0., 0., 0., 0.],
[0., 1., 1., 1., 1., 0.],
[0., 1., 1., 1., 1., 0.],
[0., 1., 1., 1., 1., 0.],
[0., 1., 1., 1., 1., 0.],
[0., 1., 1., 1., 1., 0.],
[0., 0., 0., 0., 0., 0.]],
[[0., 0., 0., 0., 0., 0.],
[0., 1., 1., 1., 1., 0.],
[0., 1., 1., 1., 1., 0.],
[0., 1., 1., 1., 1., 0.],
[0., 1., 1., 1., 1., 0.],
[0., 1., 1., 1., 1., 0.],
[0., 0., 0., 0., 0., 0.]],
[[0., 0., 0., 0., 0., 0.],
[0., 1., 1., 1., 1., 0.],
[0., 1., 1., 1., 1., 0.],
[0., 1., 1., 1., 1., 0.],
[0., 1., 1., 1., 1., 0.],
[0., 1., 1., 1., 1., 0.],
[0., 0., 0., 0., 0., 0.]],
[[0., 0., 0., 0.],
[0., 1., 1., 0.],
[0., 1., 1., 0.],
[0., 1., 1., 0.],
[0., 1., 1., 0.],
[0., 1., 1., 0.],
[0., 0., 0., 0.]],
[[0., 0., 0., 0., 0., 0.],
[0., 1., 1., 1., 1., 0.],
[0., 1., 1., 1., 1., 0.],
[0., 1., 1., 1., 1., 0.],
[0., 1., 1., 1., 1., 0.],
[0., 0., 0., 0., 0., 0.]],
[[0., 0., 0., 0., 0., 0.],
[0., 1., 1., 1., 1., 0.],
[0., 1., 1., 1., 1., 0.],
[0., 1., 1., 1., 1., 0.],
[0., 1., 1., 1., 1., 0.],
[0., 0., 0., 0., 0., 0.]],
[[0., 0., 0., 0., 0., 0.],
[0., 1., 1., 1., 1., 0.],
[0., 1., 1., 1., 1., 0.],
[0., 1., 1., 1., 1., 0.],
[0., 1., 1., 1., 1., 0.],
[0., 0., 0., 0., 0., 0.]],
[[0., 0., 0., 0.],
[0., 1., 1., 0.],
[0., 1., 1., 0.],
[0., 1., 1., 0.],
[0., 1., 1., 0.],
[0., 0., 0., 0.]]]
self.assertEqual(len(actual), len(expected))
for i in range(len(actual)):
numpy.testing.assert_array_equal(actual[i], expected[i])
if __name__ == '__main__':
unittest.main()
| 43.134146 | 112 | 0.358496 | 1,614 | 10,611 | 2.330235 | 0.332714 | 0.198883 | 0.207392 | 0.258442 | 0.433395 | 0.425951 | 0.425951 | 0.425951 | 0.403616 | 0.403616 | 0 | 0.400866 | 0.412025 | 10,611 | 245 | 113 | 43.310204 | 0.201955 | 0.044671 | 0 | 0.545852 | 0 | 0 | 0.019352 | 0.015403 | 0 | 0 | 0 | 0 | 0.021834 | 1 | 0.0131 | false | 0 | 0.017467 | 0 | 0.034935 | 0.008734 | 0 | 0 | 0 | null | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 4 |
170cc493b2846ff1b8972d6102d4eda217d210a6 | 244 | py | Python | Reading Data/lesson-4-tsv-with-the-simpsons-episodes/main.py | danielgarm/Data-Science-and-Machine-Learning | fa3e85cc42eb2e9f964ab5abb34d1c93e16d1cd9 | [
"MIT"
] | null | null | null | Reading Data/lesson-4-tsv-with-the-simpsons-episodes/main.py | danielgarm/Data-Science-and-Machine-Learning | fa3e85cc42eb2e9f964ab5abb34d1c93e16d1cd9 | [
"MIT"
] | 2 | 2022-01-11T21:04:51.000Z | 2022-01-11T21:05:05.000Z | Reading Data/lesson-4-tsv-with-the-simpsons-episodes/main.py | danielgarm/Data-Science-and-Machine-Learning | fa3e85cc42eb2e9f964ab5abb34d1c93e16d1cd9 | [
"MIT"
] | null | null | null | import numpy as np
import pandas as pd
col_names = ['Title', 'Air date', 'Production code', 'Season', 'Number in season',
'Number in series', 'US viewers (million)', 'Views', 'IMDB rating']
| 34.857143 | 82 | 0.536885 | 28 | 244 | 4.642857 | 0.821429 | 0.184615 | 0.215385 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.336066 | 244 | 7 | 83 | 34.857143 | 0.802469 | 0 | 0 | 0 | 0 | 0 | 0.416327 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.5 | 0 | 0.5 | 0 | 1 | 0 | 0 | null | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 4 |
1723983d1ec47843ac0f63f2b78b9010c2f43e7a | 38 | py | Python | Vamei/loop/forDemo.py | YangPhy/learnPython | 5507fa1a0d2878fc663d62509af8ff959955f822 | [
"MIT"
] | 5 | 2020-05-18T06:54:52.000Z | 2021-05-29T23:17:41.000Z | Vamei/loop/forDemo.py | YangPhy/learnPython | 5507fa1a0d2878fc663d62509af8ff959955f822 | [
"MIT"
] | null | null | null | Vamei/loop/forDemo.py | YangPhy/learnPython | 5507fa1a0d2878fc663d62509af8ff959955f822 | [
"MIT"
] | 1 | 2020-05-17T22:47:49.000Z | 2020-05-17T22:47:49.000Z | for a in [3,4,4,'life']:
print(a)
| 12.666667 | 24 | 0.5 | 9 | 38 | 2.111111 | 0.777778 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.103448 | 0.236842 | 38 | 2 | 25 | 19 | 0.551724 | 0 | 0 | 0 | 0 | 0 | 0.105263 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0 | 0 | 0 | 0.5 | 1 | 1 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 4 |
172497c62b216455042f9d6f02342c18c924c2ab | 155 | py | Python | mymetric.py | sararidder/hiring-engineers | 9d752e1167a81f8994c85d16dcaa8fbf7d1b1e1e | [
"Apache-2.0"
] | 1 | 2020-03-22T00:07:06.000Z | 2020-03-22T00:07:06.000Z | mymetric.py | sararidder/hiring-engineers | 9d752e1167a81f8994c85d16dcaa8fbf7d1b1e1e | [
"Apache-2.0"
] | null | null | null | mymetric.py | sararidder/hiring-engineers | 9d752e1167a81f8994c85d16dcaa8fbf7d1b1e1e | [
"Apache-2.0"
] | null | null | null | import random
from checks import AgentCheck
class RandomCheck(AgentCheck):
def check(self, instance):
self.gauge('my_metric', random.randint(0, 1000))
| 25.833333 | 51 | 0.774194 | 21 | 155 | 5.666667 | 0.809524 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.036496 | 0.116129 | 155 | 5 | 52 | 31 | 0.832117 | 0 | 0 | 0 | 0 | 0 | 0.058065 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.2 | false | 0 | 0.4 | 0 | 0.8 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 4 |
172839006443da3f1492e8b14df5fdb6c2815c25 | 90 | py | Python | Symmetric Difference.py | jibinmathew691993/PythonHackerrank | 14ab5b620435a006d5ccff17536bc01acd7c22dc | [
"MIT"
] | null | null | null | Symmetric Difference.py | jibinmathew691993/PythonHackerrank | 14ab5b620435a006d5ccff17536bc01acd7c22dc | [
"MIT"
] | null | null | null | Symmetric Difference.py | jibinmathew691993/PythonHackerrank | 14ab5b620435a006d5ccff17536bc01acd7c22dc | [
"MIT"
] | null | null | null | a,b = [set(input().split()) for _ in range(4)][1::2]
print(*sorted(a^b,key=int), sep="\n") | 45 | 52 | 0.577778 | 19 | 90 | 2.684211 | 0.894737 | 0.078431 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.036585 | 0.088889 | 90 | 2 | 53 | 45 | 0.585366 | 0 | 0 | 0 | 0 | 0 | 0.021978 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 0 | 0 | 0 | 0.5 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 4 |
1728ef58b09ac1210472081192050110f5f93784 | 22 | py | Python | indeterminatebeam/version.py | JesseBonanno/IndeterminateBeam | c28814cd0529d323f862df496faa19e75be4742d | [
"MIT"
] | 13 | 2021-04-07T15:24:02.000Z | 2022-03-17T15:43:09.000Z | indeterminatebeam/version.py | JesseBonanno/IndeterminateBeam | c28814cd0529d323f862df496faa19e75be4742d | [
"MIT"
] | 25 | 2020-12-17T21:19:13.000Z | 2022-01-11T08:49:14.000Z | indeterminatebeam/version.py | JesseBonanno/IndeterminateBeam | c28814cd0529d323f862df496faa19e75be4742d | [
"MIT"
] | 4 | 2021-01-10T16:54:03.000Z | 2021-12-26T22:26:43.000Z | __version__ = 'v2.1.6' | 22 | 22 | 0.681818 | 4 | 22 | 2.75 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.15 | 0.090909 | 22 | 1 | 22 | 22 | 0.4 | 0 | 0 | 0 | 0 | 0 | 0.26087 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 4 |
177a193b8eb436cf9912a15257f51a4102b19d0a | 150 | py | Python | social_auth/backends/contrib/linkedin.py | merutak/django-social-auth | 3a6e4414da0e969fcaf625a891852a3b2d7627c0 | [
"BSD-2-Clause",
"BSD-3-Clause"
] | 863 | 2015-01-01T00:42:07.000Z | 2022-03-30T02:47:18.000Z | social_auth/backends/contrib/linkedin.py | merutak/django-social-auth | 3a6e4414da0e969fcaf625a891852a3b2d7627c0 | [
"BSD-2-Clause",
"BSD-3-Clause"
] | 101 | 2015-01-08T00:28:16.000Z | 2022-03-07T03:11:19.000Z | social_auth/backends/contrib/linkedin.py | merutak/django-social-auth | 3a6e4414da0e969fcaf625a891852a3b2d7627c0 | [
"BSD-2-Clause",
"BSD-3-Clause"
] | 256 | 2015-01-02T16:55:36.000Z | 2022-03-04T11:10:47.000Z | from social.backends.linkedin import LinkedinOAuth as LinkedinBackend, \
LinkedinOAuth2 as LinkedinOAuth2Backend
| 50 | 76 | 0.66 | 11 | 150 | 9 | 0.909091 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.019417 | 0.313333 | 150 | 2 | 77 | 75 | 0.941748 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 0.5 | 0 | 0.5 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 4 |
178d10ce2e9486134b984e3c2337bcbb8911a174 | 955 | py | Python | pybrain/structure/modules/__init__.py | sveilleux1/pybrain | 1e1de73142c290edb84e29ca7850835f3e7bca8b | [
"BSD-3-Clause"
] | 2,208 | 2015-01-02T02:14:41.000Z | 2022-03-31T04:45:46.000Z | pybrain/structure/modules/__init__.py | sveilleux1/pybrain | 1e1de73142c290edb84e29ca7850835f3e7bca8b | [
"BSD-3-Clause"
] | 91 | 2015-01-08T16:42:16.000Z | 2021-12-11T19:16:35.000Z | pybrain/structure/modules/__init__.py | sveilleux1/pybrain | 1e1de73142c290edb84e29ca7850835f3e7bca8b | [
"BSD-3-Clause"
] | 786 | 2015-01-02T15:18:20.000Z | 2022-02-23T23:42:40.000Z | from pybrain.structure.modules.biasunit import BiasUnit
from pybrain.structure.modules.gate import GateLayer, DoubleGateLayer, MultiplicationLayer, SwitchLayer
from pybrain.structure.modules.gaussianlayer import GaussianLayer
from pybrain.structure.modules.linearlayer import LinearLayer
from pybrain.structure.modules.lstm import LSTMLayer
from pybrain.structure.modules.mdlstm import MDLSTMLayer
from pybrain.structure.modules.mdrnnlayer import MdrnnLayer
from pybrain.structure.modules.sigmoidlayer import SigmoidLayer
from pybrain.structure.modules.softmax import SoftmaxLayer, PartialSoftmaxLayer
from pybrain.structure.modules.statedependentlayer import StateDependentLayer
from pybrain.structure.modules.tanhlayer import TanhLayer
from pybrain.structure.modules.kohonen import KohonenMap
from pybrain.structure.modules.table import Table
from pybrain.structure.modules.module import Module
from pybrain.structure.modules.relulayer import ReluLayer
| 59.6875 | 103 | 0.881675 | 109 | 955 | 7.724771 | 0.266055 | 0.195962 | 0.356295 | 0.480998 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.067016 | 955 | 15 | 104 | 63.666667 | 0.945006 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | null | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 4 |
179bf6f6aa0bf85f6780a8706b3a9e68f172d2bb | 169 | py | Python | Aula02/Aula02Listas.py | leonardogt4/Curso-Introdu-o-a-Python---Univali | 7f2a7c46b8ddf72391e58f22099d3d8ec91cbf7b | [
"MIT"
] | 2 | 2019-03-08T21:21:03.000Z | 2019-03-08T21:21:16.000Z | Aula02/Aula02Listas.py | leonardogt4/Curso-Introdu-o-a-Python---Univali | 7f2a7c46b8ddf72391e58f22099d3d8ec91cbf7b | [
"MIT"
] | null | null | null | Aula02/Aula02Listas.py | leonardogt4/Curso-Introdu-o-a-Python---Univali | 7f2a7c46b8ddf72391e58f22099d3d8ec91cbf7b | [
"MIT"
] | null | null | null | #!usr/bin/python
lista = ['física', 'química', 1997, 2000]
print("Valor do indice 2:")
print (lista[2])
lista[2] = 2001;
print("Valor do índice 2:")
print (lista[2])
| 15.363636 | 41 | 0.639053 | 27 | 169 | 4 | 0.555556 | 0.166667 | 0.222222 | 0.222222 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.118056 | 0.147929 | 169 | 10 | 42 | 16.9 | 0.631944 | 0.088757 | 0 | 0.333333 | 0 | 0 | 0.324503 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0 | 0 | 0 | 0.666667 | 1 | 0 | 0 | null | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 4 |
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