xszheng2020/the_stack_dedup_python_hits_5 · Datasets at Hugging Face

2ce4398f64596457bf066f0c9f07a0dc77efb150

627

py

Python

pcbhdl/test/library/test_package.py

pcbhdl/pcbhdl

08d8ffa29645e5bea2b8a51c9a47cd0ec6215f8c

[ "0BSD" ]

null

pcbhdl/test/library/test_package.py

pcbhdl/pcbhdl

08d8ffa29645e5bea2b8a51c9a47cd0ec6215f8c

[ "0BSD" ]

null

pcbhdl/test/library/test_package.py

pcbhdl/pcbhdl

08d8ffa29645e5bea2b8a51c9a47cd0ec6215f8c

[ "0BSD" ]

null

import unittest from pcbhdl.library.package.passive import * class TestPackage(unittest.TestCase): def test_eia_two_terminal(self): pkg = EIA_I_0603 self.assertEqual(pkg.name, "EIA_I_0603") self.assertEqual(pkg.pads[0].name, "1") self.assertEqual(pkg.pads[0].center, (-0.9, 0.0)) self.assertEqual(pkg.pads[0].width, 0.8) self.assertEqual(pkg.pads[0].height, 1.0) self.assertEqual(pkg.pads[1].name, "2") self.assertEqual(pkg.pads[1].center, (0.9, 0.0)) self.assertEqual(pkg.pads[1].width, 0.8) self.assertEqual(pkg.pads[1].height, 1.0)

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fa05302b2ed25605b5ee0bf6d728d5e72eddf34a

102

py

Python

If_Instructions/testes_condicionais.py

Brunokrk/Learning-Python

36a3b1c4782dbb21af189760a451fd2e9c083bb6

[ "MIT" ]

null

If_Instructions/testes_condicionais.py

Brunokrk/Learning-Python

36a3b1c4782dbb21af189760a451fd2e9c083bb6

[ "MIT" ]

null

If_Instructions/testes_condicionais.py

Brunokrk/Learning-Python

36a3b1c4782dbb21af189760a451fd2e9c083bb6

[ "MIT" ]

null

# = atribuição, == comparação car='panamera' print(car=='panamera') car='audi' print(car=='panamera')

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fa0885b982196169f9ef5831a96342c9f23d949a

1,119

py

Python

ezgoogleapi/__init__.py

rrwielema/ezgoogleapi

9aa8f22f51cb437b329bc2cfe668ade9e8477d15

[ "MIT" ]

null

ezgoogleapi/__init__.py

rrwielema/ezgoogleapi

9aa8f22f51cb437b329bc2cfe668ade9e8477d15

[ "MIT" ]

null

ezgoogleapi/__init__.py

rrwielema/ezgoogleapi

9aa8f22f51cb437b329bc2cfe668ade9e8477d15

[ "MIT" ]

null

from ezgoogleapi.analytics.body import Body from ezgoogleapi.analytics.daterange import (TODAY, YESTERDAY, LAST_WEEK, LAST_7_DAYS, THIS_MONTH, LAST_MONTH, LAST_90_DAYS, LAST_YEAR, CURRENT_QUARTER, LAST_QUARTER, quarter, weeks, last_weeks, last_days) from ezgoogleapi.analytics.query import Query from ezgoogleapi.analytics.variable_names import VariableName, NameDatabase from ezgoogleapi.bigquery.base import BigQuery from ezgoogleapi.bigquery.schema import schema, SchemaTypes from ezgoogleapi.sheets import SpreadSheet, Permission

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5

fa2293947b7cb8c7a7134d73556bad03b40de805

58

py

Python

masks.py

chrisnbattista/multi-agent-kinetics

01af3bbd8a44038e7e8744975000e5474fa1124b

[ "MIT" ]

1

2021-01-13T22:26:53.000Z

masks.py

chrisnbattista/multi-agent-kinetics

01af3bbd8a44038e7e8744975000e5474fa1124b

[ "MIT" ]

null

masks.py

chrisnbattista/multi-agent-kinetics

01af3bbd8a44038e7e8744975000e5474fa1124b

[ "MIT" ]

null

def threshold_distance_mask(r, h): return r < h

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5

fa2d3b73ce0f5262a750e63f7b5a444709dcb71d

208

py

Python

dbus_curio/__init__.py

hugosenari/dbus_curio

080541b683862767ca3506d7514ce22ca2a64a60

[ "BSD-3-Clause" ]

null

dbus_curio/__init__.py

hugosenari/dbus_curio

080541b683862767ca3506d7514ce22ca2a64a60

[ "BSD-3-Clause" ]

null

dbus_curio/__init__.py

hugosenari/dbus_curio

080541b683862767ca3506d7514ce22ca2a64a60

[ "BSD-3-Clause" ]

null

from .auth import auth from .connection import system_bus, session_bus __all__ = [auth, system_bus, session_bus] __author__ = """Hugo Sena Ribeiro""" __email__ = 'hugosenari@gmail.com' __version__ = '0.1.0'

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null

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5

fa37bef14d060ae89bd3d5837191f583b5a70f11

86

py

Python

lib/train/__init__.py

ishine/TextNormSeq2Seq

585b6a7f17910876c76240ff82ee811c66e23104

[ "MIT" ]

36

2019-04-20T15:06:45.000Z

2022-03-03T22:42:57.000Z

lib/train/__init__.py

ishine/TextNormSeq2Seq

585b6a7f17910876c76240ff82ee811c66e23104

[ "MIT" ]

5

2019-06-06T14:48:54.000Z

2021-06-05T15:40:09.000Z

lib/train/__init__.py

ishine/TextNormSeq2Seq

585b6a7f17910876c76240ff82ee811c66e23104

[ "MIT" ]

13

2019-05-11T02:59:54.000Z

2022-03-23T18:24:10.000Z

from .optim import Optim from .trainer import Trainer from .evaluator import Evaluator

28.666667

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0.127907

86

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0

5

fa40e10c762a167c9fb3851f9638fc190f6d8ab9

70

py

Python

polyglotdb/query/lexicon/__init__.py

msonderegger/PolyglotDB

583fd8ec14c2e34807b45b9f15fa19cffa130bfa

[ "MIT" ]

25

2016-01-28T20:47:07.000Z

2021-11-29T16:13:07.000Z

polyglotdb/query/lexicon/__init__.py

msonderegger/PolyglotDB

583fd8ec14c2e34807b45b9f15fa19cffa130bfa

[ "MIT" ]

120

2016-04-07T17:55:09.000Z

2022-03-24T18:30:10.000Z

polyglotdb/query/lexicon/__init__.py

PhonologicalCorpusTools/PolyglotDB

7640212c7062cf44ae911081241ce83a26ced2eb

[ "MIT" ]

10

2015-12-03T20:06:58.000Z

2021-02-11T03:02:48.000Z

from .query import LexiconQuery from .attributes import LexiconNode

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5

fa68c6b1ab6e5681ed93f03163086a7c29e77ba6

111

py

Python

pymoon/core/utils/extension_checker.py

hassanMuhamad/pymoon

4f5f0e7b6e7382740f8bafa4abcd1044ae9c8993

[ "MIT" ]

1

2019-11-09T15:54:47.000Z

pymoon/core/utils/extension_checker.py

hassanMuhamad/pymoon

4f5f0e7b6e7382740f8bafa4abcd1044ae9c8993

[ "MIT" ]

null

pymoon/core/utils/extension_checker.py

hassanMuhamad/pymoon

4f5f0e7b6e7382740f8bafa4abcd1044ae9c8993

[ "MIT" ]

1

2019-11-12T19:23:07.000Z

# !TODO: # - Module that checks the file extension # @entry: file Object || image Object # return a flag

22.2

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111

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27.75

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5

3af9fb490bf23cc6735909c0e37e8bf5dcd7ed4a

2,738

py

Python

testsuite/tests/NA17-007__Ada_runtime_units/run_test.py

AdaCore/style_checker

17108ebfc44375498063ecdad6c6e4430458e60a

[ "CNRI-Python" ]

2

2017-10-22T18:04:26.000Z

2020-03-06T11:07:41.000Z

testsuite/tests/NA17-007__Ada_runtime_units/run_test.py

AdaCore/style_checker

17108ebfc44375498063ecdad6c6e4430458e60a

[ "CNRI-Python" ]

null

testsuite/tests/NA17-007__Ada_runtime_units/run_test.py

AdaCore/style_checker

17108ebfc44375498063ecdad6c6e4430458e60a

[ "CNRI-Python" ]

4

2018-05-22T12:08:54.000Z

2020-12-14T15:25:27.000Z

def test_a_cohama_adb(style_checker): """Style check test against a-cohama.adb.""" style_checker.set_year(2006) p = style_checker.run_style_checker('trunk/gnat', 'a-cohama.adb') style_checker.assertEqual(p.status, 0, p.image) style_checker.assertRunOutputEmpty(p) def test_a_cohamb_adb(style_checker): """Style check test against a-cohamb.adb.""" p = style_checker.run_style_checker('trunk/gnat', 'a-cohamb.adb') style_checker.assertNotEqual(p.status, 0, p.image) style_checker.assertRunOutputEqual(p, """\ a-cohamb.adb: Copyright notice missing, must occur before line 24 """) def test_a_cohata_ads(style_checker): """Style check test against a-cohata.ads.""" style_checker.set_year(2006) p = style_checker.run_style_checker('trunk/gnat', 'a-cohata.ads') style_checker.assertEqual(p.status, 0, p.image) style_checker.assertRunOutputEmpty(p) def test_a_except_ads(style_checker): """Style check test against a-except.ads.""" style_checker.set_year(2006) p = style_checker.run_style_checker('trunk/gnat', 'a-except.ads') style_checker.assertNotEqual(p.status, 0, p.image) style_checker.assertRunOutputEqual(p, """\ a-except.ads:9: Copyright notice must include current year (found 2005, expected 2006) """) def test_exceptions_ads(style_checker): """Style check test against exceptions.ads.""" style_checker.set_year(2006) p = style_checker.run_style_checker('trunk/gnat', 'exceptions.ads') style_checker.assertNotEqual(p.status, 0, p.image) style_checker.assertRunOutputEqual(p, """\ exceptions.ads:9: Copyright notice must include current year (found 2005, expected 2006) """) def test_a_zttest_ads(style_checker): """Style check test against a-zttest.ads """ p = style_checker.run_style_checker('trunk/gnat', 'a-zttest.ads') style_checker.assertEqual(p.status, 0, p.image) style_checker.assertRunOutputEmpty(p) def test_directio_ads(style_checker): """Style check test against directio.ads """ p = style_checker.run_style_checker('trunk/gnat', 'directio.ads') style_checker.assertEqual(p.status, 0, p.image) style_checker.assertRunOutputEmpty(p) def test_i_c_ads(style_checker): """Style check test against i-c.ads """ p = style_checker.run_style_checker('trunk/gnat', 'i-c.ads') style_checker.assertEqual(p.status, 0, p.image) style_checker.assertRunOutputEmpty(p) def test_s_taprop_linux_adb(style_checker): """Style check test s-taprop-linux.adb """ style_checker.set_year(2010) p = style_checker.run_style_checker('trunk/gnat', 's-taprop-linux.adb') style_checker.assertEqual(p.status, 0, p.image) style_checker.assertRunOutputEmpty(p)

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5

d70dd97d8b6ac934b5ce51383051085fea06a455

147

py

Python

doctor/email_info.py

JuliasBright/SendMoney

d13e2df81bf75a9154abfc57d897a416b4950e80

[ "CC0-1.0" ]

1

2021-01-29T16:57:42.000Z

doctor/email_info.py

JuliasBright/SendMoney

d13e2df81bf75a9154abfc57d897a416b4950e80

[ "CC0-1.0" ]

null

doctor/email_info.py

JuliasBright/SendMoney

d13e2df81bf75a9154abfc57d897a416b4950e80

[ "CC0-1.0" ]

null

EMAIL_HOST = 'smtp.gmail.com' EMAIL_PORT = 587 EMAIL_HOST_USER = 'findadoctor2@gmail.com' EMAIL_HOST_PASSWORD = 'Qwerty1@' EMAIL_USE_TLS = True

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d71cec00e2775c2beaa2f807471ba48d7733f3b6

53

py

Python

sakt/__init__.py

scaomath/kaggle-riiid-test

6c99deccc33def7e5d0c982b0a9a19612138e893

[ "MIT" ]

null

sakt/__init__.py

scaomath/kaggle-riiid-test

6c99deccc33def7e5d0c982b0a9a19612138e893

[ "MIT" ]

null

sakt/__init__.py

scaomath/kaggle-riiid-test

6c99deccc33def7e5d0c982b0a9a19612138e893

[ "MIT" ]

null

from .sakt import * # from .train_sakt_final import *

26.5

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5

d728e3cecdc03bd70055ff453f1a6b1c2d084baf

35

py

Python

python/helpers/tests/generator3_tests/data/SkeletonGeneration/segmentation_fault_handling/sigsegv.py

tgodzik/intellij-community

f5ef4191fc30b69db945633951fb160c1cfb7b6f

[ "Apache-2.0" ]

2

2019-04-28T07:48:50.000Z

2020-12-11T14:18:08.000Z

python/helpers/tests/generator3_tests/data/SkeletonGeneration/segmentation_fault_handling/sigsegv.py

tgodzik/intellij-community

f5ef4191fc30b69db945633951fb160c1cfb7b6f

[ "Apache-2.0" ]

2

2022-02-19T09:45:05.000Z

2022-02-27T20:32:55.000Z

python/helpers/tests/generator3_tests/data/SkeletonGeneration/segmentation_fault_handling/sigsegv.py

tgodzik/intellij-community

f5ef4191fc30b69db945633951fb160c1cfb7b6f

[ "Apache-2.0" ]

2

2020-03-15T08:57:37.000Z

2020-04-07T04:48:14.000Z

import ctypes ctypes.string_at(0)

8.75

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d7384bab319ea3a2b2fa3683c41accb902076fd2

5,062

py

Python

armstrong/core/arm_content/tests/video/backends/youtube.py

cirlabs/armstrong.core.arm_content

91b2022bc19f0ddb10402d928c9b68c9faf242b6

[ "Apache-2.0" ]

null

armstrong/core/arm_content/tests/video/backends/youtube.py

cirlabs/armstrong.core.arm_content

91b2022bc19f0ddb10402d928c9b68c9faf242b6

[ "Apache-2.0" ]

null

armstrong/core/arm_content/tests/video/backends/youtube.py

cirlabs/armstrong.core.arm_content

91b2022bc19f0ddb10402d928c9b68c9faf242b6

[ "Apache-2.0" ]

null

from ..._utils import * from ....fields.video import EmbeddedVideo from ....video.backends import helpers from ....video.backends.youtube import YouTubeBackend class YouTubeBackendTestCase(ArmContentTestCase): def generate_random_url(self): random_id = str(random.randint(100, 200)) url = "http://youtube.com/watch?v=%s" % random_id return random_id, url def test_returns_tuple_with_url_as_first_value(self): random_id = str(random.randint(100, 200)) url = "http://youtube.com/watch?v=%s" % random_id backend = YouTubeBackend() video = EmbeddedVideo(url, backend) self.assertEqual("http", video.url.scheme) self.assertEqual("youtube.com", video.url.netloc) def test_returns_tuple_with_id_as_second_value(self): random_id = str(random.randint(100, 200)) url = "http://youtube.com/watch?v=%s" % random_id backend = YouTubeBackend() video = EmbeddedVideo(url, backend) self.assertEqual(random_id, video.id) def test_returns_the_expected_html_when_embed_is_called(self): random_id = str(random.randint(100, 200)) url = "http://youtube.com/watch?v=%s" % random_id backend = YouTubeBackend() video = EmbeddedVideo(url, backend) expected = "".join([ '<iframe title="YouTube video player" ', 'width="640" height="390" ', 'src="http://www.youtube.com/embed/%s" ', 'frameborder="0" allowfullscreen></iframe>']) % random_id self.assertEqual(expected, backend.embed(video)) def test_embed_width_can_be_set_with_a_kwarg(self): random_width = random.randint(1000, 2000) random_id = str(random.randint(100, 200)) url = "http://youtube.com/watch?v=%s" % random_id backend = YouTubeBackend() video = EmbeddedVideo(url, backend) expected = "".join([ '<iframe title="YouTube video player" ', 'width="%d" height="390" ' % random_width, 'src="http://www.youtube.com/embed/%s" ', 'frameborder="0" allowfullscreen></iframe>']) % random_id self.assertRegexpMatches(backend.embed(video, width=random_width), r'width="%d"' % random_width) def test_embed_height_can_be_set_with_a_kwarg(self): random_height = random.randint(1000, 2000) random_id = str(random.randint(100, 200)) url = "http://youtube.com/watch?v=%s" % random_id backend = YouTubeBackend() video = EmbeddedVideo(url, backend) expected = "".join([ '<iframe title="YouTube video player" ', 'width="%d" height="390" ' % random_height, 'src="http://www.youtube.com/embed/%s" ', 'frameborder="0" allowfullscreen></iframe>']) % random_id self.assertRegexpMatches(backend.embed(video, height=random_height), r'height="%d"' % random_height) def test_embed_width_and_height_can_be_strings(self): random_height = str(random.randint(1000, 2000)) random_width = str(random.randint(1000, 2000)) random_id = str(random.randint(100, 200)) url = "http://youtube.com/watch?v=%s" % random_id backend = YouTubeBackend() video = EmbeddedVideo(url, backend) expected = "".join([ '<iframe title="YouTube video player" ', 'width="%s" height="%s" ' % (random_width, random_height), 'src="http://www.youtube.com/embed/%s" ', 'frameborder="0" allowfullscreen></iframe>']) % random_id self.assertRegexpMatches(backend.embed(video, width=random_width), r'width="%s"' % random_width) self.assertRegexpMatches(backend.embed(video, height=random_height), r'height="%s"' % random_height) def test_height_defaults_to_configured_if_not_provided(self): random_height = random.randint(1000, 2000) settings = fudge.Fake() settings.has_attr(ARMSTRONG_EMBED_VIDEO_HEIGHT=random_height) settings.has_attr(ARMSTRONG_EMBED_VIDEO_WIDTH="does not matter") with fudge.patched_context(helpers, 'settings', settings): random_id, url = self.generate_random_url() backend = YouTubeBackend() video = EmbeddedVideo(url, backend) self.assertRegexpMatches(backend.embed(video), r'height="%s"' % random_height) def test_width_defaults_to_configured_if_not_provided(self): random_width = random.randint(1000, 2000) settings = fudge.Fake() settings.has_attr(ARMSTRONG_EMBED_VIDEO_WIDTH=random_width) settings.has_attr(ARMSTRONG_EMBED_VIDEO_HEIGHT="does not matter") with fudge.patched_context(helpers, 'settings', settings): random_id, url = self.generate_random_url() backend = YouTubeBackend() video = EmbeddedVideo(url, backend) self.assertRegexpMatches(backend.embed(video), r'width="%s"' % random_width)

43.264957

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5,062

5.280342

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0.046617

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1

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null

0

5

d777d0ce4abc3f4a312ab70f3c81ea83b57f9821

659

py

Python

xautodl/spaces/__init__.py

Joey61Liuyi/AutoDL-Projects

2092e144920e82d74753a7ac31e1890a150d41cf

[ "MIT" ]

817

2020-01-15T00:23:41.000Z

2022-03-31T14:52:03.000Z

xautodl/spaces/__init__.py

Joey61Liuyi/AutoDL-Projects

2092e144920e82d74753a7ac31e1890a150d41cf

[ "MIT" ]

77

2020-01-14T14:02:45.000Z

2022-03-25T07:06:02.000Z

xautodl/spaces/__init__.py

Joey61Liuyi/AutoDL-Projects

2092e144920e82d74753a7ac31e1890a150d41cf

[ "MIT" ]

176

2020-01-15T10:39:41.000Z

2022-03-31T04:24:53.000Z

##################################################### # Copyright (c) Xuanyi Dong [GitHub D-X-Y], 2021.01 # ##################################################### # Define complex searc space for AutoDL # ##################################################### from .basic_space import Categorical from .basic_space import Continuous from .basic_space import Integer from .basic_space import Space from .basic_space import VirtualNode from .basic_op import has_categorical from .basic_op import has_continuous from .basic_op import is_determined from .basic_op import get_determined_value from .basic_op import get_min from .basic_op import get_max

36.611111

53

0.60698

78

659

4.897436

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0.259162

0.172775

0.267016

0.26178

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0.116844

659

17

54

38.764706

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1

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true

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null

0

1

0

1

0

1

0

5

ad22ee4b2f00653cb78df13760d28f833e71da87

63

py

Python

text processing in python/process_beta.py

TheBrownViking20/DSstuff

d915f48e88c22baa81cf8f6114615c6d1bd3faa9

[ "MIT" ]

3

2018-02-12T14:18:50.000Z

2018-05-31T19:06:54.000Z

text processing in python/process_beta.py

TheBrownViking20/DSstuff

d915f48e88c22baa81cf8f6114615c6d1bd3faa9

[ "MIT" ]

null

text processing in python/process_beta.py

TheBrownViking20/DSstuff

d915f48e88c22baa81cf8f6114615c6d1bd3faa9

[ "MIT" ]

1

2018-05-31T19:06:56.000Z

import os import glob from process_alpha import text_process

10.5

38

0.84127

10

63

5.1

0.7

0

0.15873

63

5

39

12.6

0.962264

0

1

0

true

0

1

0

1

0

1

0

null

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1

0

null

0

1

0

1

0

1

0

5

ad26e96ed1f6ff28f3015be9815a17e2a5553345

63

py

Python

torchcam/cams/__init__.py

alexandrosstergiou/torch-cam

7a95e145341edde0bd26aedf38efd06bb0c2d2a6

[ "MIT" ]

749

2020-03-24T09:32:23.000Z

2022-03-31T17:30:00.000Z

torchcam/cams/__init__.py

alexandrosstergiou/torch-cam

7a95e145341edde0bd26aedf38efd06bb0c2d2a6

[ "MIT" ]

118

2020-03-24T01:21:31.000Z

2022-03-31T12:41:37.000Z

torchcam/cams/__init__.py

alexandrosstergiou/torch-cam

7a95e145341edde0bd26aedf38efd06bb0c2d2a6

[ "MIT" ]

81

2020-05-20T01:18:32.000Z

2022-03-31T07:55:58.000Z

from .cam import * from .gradcam import * from .utils import *

15.75

22

0.714286

9

63

5

0.555556

0.444444

0

0.190476

63

3

23

21

0.882353

0

1

0

true

0

1

0

1

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null

1

0

1

0

null

0

1

0

1

0

5

ad521a5b0f34caf9230158f86bc5692bade3762d

420

py

Python

tests/resources/xmpp_handlers.py

pombreda/tipfy

900e5a31a5d24107efa8dfacd89fd69d207cf470

[ "BSD-3-Clause" ]

23

2015-02-15T22:35:04.000Z

2021-11-17T11:39:24.000Z

tests/resources/xmpp_handlers.py

iki/tipfy

20a4d20eb68d2caa8f0a8f51caf5b8a075efa9c3

[ "BSD-3-Clause" ]

null

tests/resources/xmpp_handlers.py

iki/tipfy

20a4d20eb68d2caa8f0a8f51caf5b8a075efa9c3

[ "BSD-3-Clause" ]

3

2016-03-21T15:57:28.000Z

2020-11-26T02:26:19.000Z

from tipfy.appengine.xmpp import BaseHandler, CommandHandler class XmppHandler(CommandHandler): def foo_command(self, message): message.reply('Foo command!') def bar_command(self, message): message.reply('Bar command!') def text_message(self, message): super(XmppHandler, self).text_message(message) message.reply(message.body) class XmppHandler2(BaseHandler): pass

23.333333

60

0.707143

47

420

6.234043

0.446809

0.191126

0.194539

0.170648

0.204778

0

0.002941

0.190476

420

17

61

24.705882

0.858824

0

0.057143

0

1

0.272727

false

0.090909

0

0.545455

0

null

0

1

0

null

0

1

0

1

0

1

0

5

ad7296db40a28ad8b4f7434f61946ea883e0fc99

6,057

py

Python

python_modules/libraries/dagster-bash/dagster_bash/solids.py

flowersw/dagster

0de6baf2bd6a41bfacf0be532b954e23305fb6b4

[ "Apache-2.0" ]

3

2020-09-09T04:10:23.000Z

2021-11-08T02:10:42.000Z

python_modules/libraries/dagster-bash/dagster_bash/solids.py

flowersw/dagster

0de6baf2bd6a41bfacf0be532b954e23305fb6b4

[ "Apache-2.0" ]

2

2021-05-11T13:36:27.000Z

2021-09-03T01:53:11.000Z

python_modules/libraries/dagster-bash/dagster_bash/solids.py

flowersw/dagster

0de6baf2bd6a41bfacf0be532b954e23305fb6b4

[ "Apache-2.0" ]

null

import os from dagster import ( Enum, EnumValue, Failure, Field, InputDefinition, Noneable, Nothing, OutputDefinition, Permissive, check, solid, ) from .utils import execute, execute_script_file def bash_command_solid(bash_command, name='bash_solid', input_defs=None, **kwargs): '''This function is a factory which constructs a solid that will execute a Bash command. Any kwargs passed to this function will be passed along to the underlying :func:`@solid <dagster.solid>` decorator. However, note that overriding ``config`` or ``output_defs`` is not supported. You might consider using :func:`@composite_solid <dagster.composite_solid>` to wrap this solid in the cases where you'd like to configure the bash solid with different config fields. Examples: .. literalinclude:: ../../../../../python_modules/libraries/dagster-bash/dagster_bash_tests/example_bash_command_solid.py :language: python Args: bash_command (str): The shell command to execute. name (str, optional): The name of this solid. Defaults to "bash_solid". input_defs (List[InputDefinition], optional): input definitions for the solid. Defaults to a single Nothing input. Raises: Failure: Raised when the shell command returns a non-zero exit code. Returns: SolidDefinition: Returns the constructed solid definition. ''' check.str_param(bash_command, 'bash_command') name = check.str_param(name, 'name') check.opt_list_param(input_defs, 'input_defs', of_type=InputDefinition) if 'output_defs' in kwargs: raise TypeError('Overriding output_defs for bash solid is not supported.') if 'config' in kwargs: raise TypeError('Overriding config for bash solid is not supported.') @solid( name=name, description=kwargs.pop('description', 'A solid to invoke a bash command.'), input_defs=input_defs or [InputDefinition('start', Nothing)], output_defs=[OutputDefinition(str, 'result')], config=bash_solid_config(), **kwargs ) def _bash_solid(context): output, return_code = execute( bash_command=bash_command, log=context.log, **context.solid_config ) if return_code: raise Failure( description='Bash command execution failed with output: {output}'.format( output=output ) ) return output return _bash_solid def bash_script_solid(bash_script_path, name='bash_script_solid', input_defs=None, **kwargs): '''This function is a factory which constructs a solid that will execute a Bash command read from a script file. Any kwargs passed to this function will be passed along to the underlying :func:`@solid <dagster.solid>` decorator. However, note that overriding ``config`` or ``output_defs`` is not supported. You might consider using :func:`@composite_solid <dagster.composite_solid>` to wrap this solid in the cases where you'd like to configure the bash solid with different config fields. Examples: .. literalinclude:: ../../../../../python_modules/libraries/dagster-bash/dagster_bash_tests/example_bash_script_solid.py :language: python Args: bash_script_path (str): The script file to execute. name (str, optional): The name of this solid. Defaults to "bash_script_solid". input_defs (List[InputDefinition], optional): input definitions for the solid. Defaults to a single Nothing input. Raises: Failure: Raised when the shell command returns a non-zero exit code. Returns: SolidDefinition: Returns the constructed solid definition. ''' check.str_param(bash_script_path, 'bash_script_path') name = check.str_param(name, 'name') check.opt_list_param(input_defs, 'input_defs', of_type=InputDefinition) if 'output_defs' in kwargs: raise TypeError('Overriding output_defs for bash solid is not supported.') if 'config' in kwargs: raise TypeError('Overriding config for bash solid is not supported.') @solid( name=name, description=kwargs.pop('description', 'A solid to invoke a bash command.'), input_defs=input_defs or [InputDefinition('start', Nothing)], output_defs=[OutputDefinition(str, 'result')], config=bash_solid_config(), **kwargs ) def _bash_script_solid(context): output, return_code = execute_script_file( bash_script_path=bash_script_path, log=context.log, **context.solid_config ) if return_code: raise Failure( description='Bash command execution failed with output: {output}'.format( output=output ) ) return output return _bash_script_solid def bash_solid_config(): return { 'env': Field( Noneable(Permissive()), default_value=os.environ.copy(), is_required=False, description='An optional dict of environment variables to pass to the subprocess. ' 'Defaults to using os.environ.copy().', ), 'output_logging': Field( Enum( name='OutputType', enum_values=[ EnumValue('STREAM', description='Stream script stdout/stderr.'), EnumValue( 'BUFFER', description='Buffer bash script stdout/stderr, then log upon completion.', ), EnumValue('NONE', description='No logging'), ], ), is_required=False, default_value='BUFFER', ), 'cwd': Field( Noneable(str), default_value=None, is_required=False, description='Working directory in which to execute bash script', ), }

33.65

125

0.63827

704

6,057

5.338068

0.204545

0.040979

0.022352

0.019159

0.75785

0.753592

0.705695

0

0.272247

6,057

179

126

33.837989

0.852541

0.348853

0

0.431373

0

0.222575

0

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0.04902

false

0.009804

0.029412

0.009804

0.127451

0

null

0

1

0

null

0

5

ad8cae38854595ad8b6907c8ae142b4f150b0508

1,847

py

Python

angalabiri/shop/forms/cartform.py

dark-codr/ebiangala

0af3de29b2afa71df3e138cd16ecddc69fbd597d

[ "MIT" ]

1

2021-03-25T14:06:23.000Z

angalabiri/shop/forms/cartform.py

dark-codr/ebiangala

0af3de29b2afa71df3e138cd16ecddc69fbd597d

[ "MIT" ]

5

2021-09-08T03:08:46.000Z

2022-03-12T00:56:35.000Z

angalabiri/shop/forms/cartform.py

me-edavids/ebiangala

0af3de29b2afa71df3e138cd16ecddc69fbd597d

[ "MIT" ]

null

from django import forms from crispy_forms.helper import FormHelper from crispy_forms.layout import ( Column, HTML, Field, Fieldset, Layout, Row, Submit, BaseInput, ) from crispy_forms.bootstrap import InlineField, UneditableField from crispy_forms import layout PRODUCT_QUANTITY_CHOICES = [(i, str(i)) for i in range(1, 200)] class CartAddProductForm(forms.Form): quantity = forms.TypedChoiceField( choices=PRODUCT_QUANTITY_CHOICES, coerce=int, required=False, widget=forms.TextInput(attrs={'class': 'qty', 'style':'width:60px; padding: 8.7px;'}) ) update = forms.BooleanField( widget=forms.HiddenInput(), initial=False, required=False ) def __init__(self, *args, **kwargs): super().__init__(*args, **kwargs) self.helper = FormHelper() self.helper.layout = Layout( BaseInput("quantity", value=1, style="width:50px;", add_class="qty"), Submit("Add To Cart", "Add to Cart", css_class="add-to-cart button m-0"), ) # class ListCartAddProductForm(forms.Form): # quantity = forms.TypedChoiceField( # choices=PRODUCT_QUANTITY_CHOICES, # coerce=int, # required=False, # widget=forms.TextInput(attrs={'class': 'qty', 'style':'width:60px; padding: 8.7px;'}) # ) # update = forms.BooleanField( # widget=forms.HiddenInput(), initial=False, required=False # ) # def __init__(self, *args, **kwargs): # super().__init__(*args, **kwargs) # self.helper = FormHelper() # self.helper.layout = Layout( # BaseInput("quantity", value=1, style="width:50px;", add_class="qty"), # Submit("Add To Cart", "Add To Cart", css_class="add-to-cart button m-0"), # ) # <i class="icon-shopping-cart"></i>

29.790323

95

0.623714

209

1,847

5.368421

0.325359

0.026738

0.048128

0.039216

0.705882

0

0.014094

0.231727

1,847

61

96

30.278689

0.776603

0.400108

0

0.097337

0

1

0.03125

false

0

0.15625

0

0.28125

0

null

0

1

0

null

0

5

d100f2edb9ccb5ba2c2151a7d3f00ada35be2feb

71

py

Python

newtonnet/train/hooks/__init__.py

THGLab/NewtonNet

fcf2af848a1c998bd08096dcefb58a5610eda03c

[ "MIT" ]

null

newtonnet/train/hooks/__init__.py

THGLab/NewtonNet

fcf2af848a1c998bd08096dcefb58a5610eda03c

[ "MIT" ]

null

newtonnet/train/hooks/__init__.py

THGLab/NewtonNet

fcf2af848a1c998bd08096dcefb58a5610eda03c

[ "MIT" ]

null

""" """ from newtonnet.train.hooks.visualizers import VizMolVectors3D

14.2

61

0.774648

7

71

7.857143

1

0

0.015625

0.098592

71

5

61

14.2

0.84375

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

d12632ef89add1fa673d803e3bfa1f49a08e0895

643

py

Python

arrow/commands/cmd_remote.py

trstickland/python-apollo

04cccf2923e6977b2cfb6ebb2ff7e5227b740bcb

[ "MIT" ]

5

2017-06-27T19:41:57.000Z

2021-06-05T13:36:11.000Z

arrow/commands/cmd_remote.py

trstickland/python-apollo

04cccf2923e6977b2cfb6ebb2ff7e5227b740bcb

[ "MIT" ]

28

2017-07-24T15:10:37.000Z

2021-09-03T11:56:35.000Z

arrow/commands/cmd_remote.py

trstickland/python-apollo

04cccf2923e6977b2cfb6ebb2ff7e5227b740bcb

[ "MIT" ]

10

2017-05-10T19:13:44.000Z

2021-08-09T04:52:33.000Z

import click from arrow.commands.remote.add_organism import cli as add_organism from arrow.commands.remote.add_track import cli as add_track from arrow.commands.remote.delete_organism import cli as delete_organism from arrow.commands.remote.delete_track import cli as delete_track from arrow.commands.remote.update_organism import cli as update_organism from arrow.commands.remote.update_track import cli as update_track @click.group() def cli(): pass cli.add_command(add_organism) cli.add_command(add_track) cli.add_command(delete_organism) cli.add_command(delete_track) cli.add_command(update_organism) cli.add_command(update_track)

30.619048

72

0.846034

103

643

5.048544

0.165049

0.103846

0.196154

0.265385

0.388462

0

0.087092

643

20

73

32.15

0.88586

0

1

0.0625

true

0.0625

0.4375

0

0.5

0

null

0

1

0

null

0

1

0

5

d12bc0140faaf024fcd4675dbbb0883ad1aa6148

37

py

Python

CodeForces/A2OJ Ladder/demo5.py

dimitrov-dimitar/competitive-programming

f2b022377baf6d4beff213fc513907b774c12352

[ "MIT" ]

null

CodeForces/A2OJ Ladder/demo5.py

dimitrov-dimitar/competitive-programming

f2b022377baf6d4beff213fc513907b774c12352

[ "MIT" ]

null

CodeForces/A2OJ Ladder/demo5.py

dimitrov-dimitar/competitive-programming

f2b022377baf6d4beff213fc513907b774c12352

[ "MIT" ]

null

for i in range(100000): print(i)

12.333333

23

0.621622

7

37

3.285714

0.857143

0

0.214286

0.243243

37

2

24

18.5

0.607143

0

1

0

false

0

0.5

1

0

null

0

1

0

1

0

null

0

1

0

5

d134d6e171e2027b009af41fac2481ff27123790

91

py

Python

uol_os_reports.py

LCBRU/reporter

8cb0ae403346e375a5e99d1d4df375cf2d5f3b81

[ "MIT" ]

null

uol_os_reports.py

LCBRU/reporter

8cb0ae403346e375a5e99d1d4df375cf2d5f3b81

[ "MIT" ]

null

uol_os_reports.py

LCBRU/reporter

8cb0ae403346e375a5e99d1d4df375cf2d5f3b81

[ "MIT" ]

null

#!/usr/bin/env python3 import reporter.uol_os_reports from runner import run run()

13

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0.725275

14

91

4.571429

0.857143

0

0.013514

0.186813

91

6

32

15.166667

0.851351

0.230769

0

1

0

true

0

0.666667

0

0.666667

0

1

0

null

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null

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1

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1

0

1

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d140214440afa91487170cb9f734112e88307afb

160

py

Python

plugins/__init__.py

SeaSeaEm/SpueBox

303dc0be7c5b9cd7906ff4297fd565e15bda95ef

[ "MIT" ]

9

2018-11-12T19:03:07.000Z

2021-12-02T10:25:18.000Z

plugins/__init__.py

SeaSeaEm/SpueBox

303dc0be7c5b9cd7906ff4297fd565e15bda95ef

[ "MIT" ]

3

2018-08-13T21:47:09.000Z

2021-05-09T02:28:35.000Z

plugins/__init__.py

SeaSeaEm/SpueBox

303dc0be7c5b9cd7906ff4297fd565e15bda95ef

[ "MIT" ]

6

2018-09-12T19:30:17.000Z

2021-12-02T16:42:40.000Z

from .administrative import AdministrativePlugin from .musicplayer import MusicPlayerPlugin from .tag import TagPlugin from .randomgame import RandomGamePlugin

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d15e4faa0172854d2a82bdc0f069ffca02dcadff

97

py

Python

astropop/polarimetry/__init__.py

rudnerlq/astropop

37688c6b91fa9718202a1c4e85c99049f591a3fc

[ "BSD-3-Clause" ]

3

2020-06-15T18:09:15.000Z

2020-06-16T00:58:21.000Z

astropop/polarimetry/__init__.py

rudnerlq/astropop

37688c6b91fa9718202a1c4e85c99049f591a3fc

[ "BSD-3-Clause" ]

null

astropop/polarimetry/__init__.py

rudnerlq/astropop

37688c6b91fa9718202a1c4e85c99049f591a3fc

[ "BSD-3-Clause" ]

null

# Licensed under a 3-clause BSD style license - see LICENSE.rst from .dualbeam import * # noqa

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d16d7715394a6e6026fdc4126de3d845f6dee494

142

py

Python

minigest/tributi/models/accertamento_rata/__init__.py

ctrlmaniac/minigest

2bfceb57e41c872e4112e24d0e6991164846888b

[ "MIT" ]

null

minigest/tributi/models/accertamento_rata/__init__.py

ctrlmaniac/minigest

2bfceb57e41c872e4112e24d0e6991164846888b

[ "MIT" ]

1

2021-09-22T19:10:20.000Z

minigest/tributi/models/accertamento_rata/__init__.py

ctrlmaniac/minigest

2bfceb57e41c872e4112e24d0e6991164846888b

[ "MIT" ]

null

from .erario import AccertamentoRataSezErario from .rata import AccertamentoRata __all__ = ["AccertamentoRataSezErario", "AccertamentoRata"]

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d16dd530bbca19d1da92c43ca3702f32d6787337

249

py

Python

laia/models/htr/__init__.py

basbeu/PyLaia

d14458484b56622204b1730a7d53220c5d0f1bc1

[ "MIT" ]

2

2020-09-10T13:31:17.000Z

2021-07-31T09:44:17.000Z

laia/models/htr/__init__.py

basbeu/PyLaia

d14458484b56622204b1730a7d53220c5d0f1bc1

[ "MIT" ]

1

2020-12-06T18:11:52.000Z

2020-12-06T18:19:38.000Z

laia/models/htr/__init__.py

basbeu/PyLaia

d14458484b56622204b1730a7d53220c5d0f1bc1

[ "MIT" ]

2

2020-04-20T13:40:56.000Z

2020-10-17T11:59:55.000Z

from __future__ import absolute_import from laia.models.htr.conv_block import ConvBlock from laia.models.htr.dummy_model import DummyModel from laia.models.htr.laia_crnn import LaiaCRNN from laia.models.htr.gated_crnn import GatedConv2d, GatedCRNN

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5.394737

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249

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5

0f313b49f16cdc2b083aeda3d79142c275779667

76

py

Python

jacdac/matrix_keypad/__init__.py

microsoft/jacdac-python

712ad5559e29065f5eccb5dbfe029c039132df5a

[ "MIT" ]

1

2022-02-15T21:30:36.000Z

jacdac/matrix_keypad/__init__.py

microsoft/jacdac-python

712ad5559e29065f5eccb5dbfe029c039132df5a

[ "MIT" ]

null

jacdac/matrix_keypad/__init__.py

microsoft/jacdac-python

712ad5559e29065f5eccb5dbfe029c039132df5a

[ "MIT" ]

1

2022-02-08T19:32:45.000Z

# Autogenerated file. from .client import MatrixKeypadClient # type: ignore

25.333333

53

0.802632

8

76

7.625

1

0

0.131579

76

2

54

38

0.924242

0.421053

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true

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1

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null

0

1

0

1

0

5

0f41dd0e8a10cc049d632ffea1ca4b19a1b5cfc6

16

py

Python

openml_data_integration/protobuf_generator/openml_40646/myconstants.py

tuix/tutorials

733d35a8a39df079e8c2432c441b70785ab08440

[ "Apache-2.0" ]

8

2020-04-21T13:29:04.000Z

2021-12-13T08:59:09.000Z

openml_data_integration/protobuf_generator/openml_40646/myconstants.py

tuix/tutorials

733d35a8a39df079e8c2432c441b70785ab08440

[ "Apache-2.0" ]

3

2021-04-27T11:03:04.000Z

2021-05-24T18:22:57.000Z

openml_data_integration/protobuf_generator/openml_40646/myconstants.py

tuix/tutorials

733d35a8a39df079e8c2432c441b70785ab08440

[ "Apache-2.0" ]

6

2020-07-06T08:23:25.000Z

2021-11-24T10:39:34.000Z

DATA_ID = 40646

8

15

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16

3.666667

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0.1875

16

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0

1

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1

0

1

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null

0

5

0f49b9c489972d64861be13715b8a2ece606e158

172

py

Python

testing/util.py

bbhunter/fuzz-lightyear

75c1318d2f747a4fac6b55a46649c944528769ba

[ "Apache-2.0" ]

169

2019-11-06T20:30:16.000Z

2022-01-22T15:55:19.000Z

testing/util.py

bbhunter/fuzz-lightyear

75c1318d2f747a4fac6b55a46649c944528769ba

[ "Apache-2.0" ]

29

2019-09-24T19:44:03.000Z

2021-10-01T09:29:30.000Z

testing/util.py

bbhunter/fuzz-lightyear

75c1318d2f747a4fac6b55a46649c944528769ba

[ "Apache-2.0" ]

27

2019-12-27T19:57:28.000Z

2021-12-08T05:38:10.000Z

import re # Source: https://stackoverflow.com/a/14693789 _ansi_escape = re.compile(r'\x1b\[[0-?]*[ -/]*[@-~]') def uncolor(text): return _ansi_escape.sub('', text)

17.2

53

0.633721

23

172

4.565217

0.826087

0.190476

0

0.066667

0.127907

172

9

54

19.111111

0.633333

0.255814

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0.25

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0

1

0

null

0

1

0

1

0

5

0f4faf6715384d47dd264801d3c572e7baf256e3

14,472

py

Python

cli/test/test_runner_slurm.py

vipulchhabra99/popper

9bbbe3340daea7161230a219fe2381603ba2a622

[ "MIT" ]

null

cli/test/test_runner_slurm.py

vipulchhabra99/popper

9bbbe3340daea7161230a219fe2381603ba2a622

[ "MIT" ]

null

cli/test/test_runner_slurm.py

vipulchhabra99/popper

9bbbe3340daea7161230a219fe2381603ba2a622

[ "MIT" ]

null

import os import unittest import tempfile from testfixtures import compare, Replacer, replace from testfixtures.popen import MockPopen from testfixtures.mock import call from popper.config import ConfigLoader from popper.runner import WorkflowRunner from popper.parser import WorkflowParser from popper.runner_slurm import SlurmRunner, DockerRunner, SingularityRunner from popper.cli import log as log from .test_common import PopperTest from box import Box def mock_kill(pid, sig): return 0 class TestSlurmSlurmRunner(PopperTest): def setUp(self): log.setLevel("CRITICAL") self.Popen = MockPopen() replacer = Replacer() replacer.replace("popper.runner_host.Popen", self.Popen) self.addCleanup(replacer.restore) def tearDown(self): log.setLevel("NOTSET") def test_tail_output(self): self.Popen.set_command("tail -f slurm-x.out", returncode=0) with SlurmRunner(config=ConfigLoader.load()) as sr: self.assertEqual(sr._tail_output("slurm-x.out"), 0) self.assertEqual(len(sr._out_stream_pid), 1) def test_stop_running_tasks(self): self.Popen.set_command("scancel --name job_a", returncode=0) with SlurmRunner(config=ConfigLoader.load()) as sr: sr._spawned_jobs.add("job_a") sr.stop_running_tasks() compare( call.Popen( ["scancel", "--name", "job_a"], cwd=os.getcwd(), env=None, preexec_fn=os.setsid, stderr=-2, stdout=-1, universal_newlines=True, ), self.Popen.all_calls[0], ) @replace("popper.runner_slurm.os.kill", mock_kill) def test_submit_batch_job(self, mock_kill): config = ConfigLoader.load(workspace_dir="/w") self.Popen.set_command( "sbatch --wait " f"--job-name popper_sample_{config.wid} " f"--output /tmp/popper/slurm/popper_sample_{config.wid}.out " f"/tmp/popper/slurm/popper_sample_{config.wid}.sh", returncode=0, ) self.Popen.set_command( f"tail -f /tmp/popper/slurm/popper_sample_{config.wid}.out", returncode=0 ) step = Box({"id": "sample"}, default_box=True) with SlurmRunner(config=config) as sr: sr._submit_batch_job(["ls -la"], step) with open(f"/tmp/popper/slurm/popper_sample_{config.wid}.sh", "r") as f: content = f.read() self.assertEqual(content, "#!/bin/bash\nls -la") self.assertEqual(len(sr._spawned_jobs), 0) self.assertEqual(sr._out_stream_thread.is_alive(), False) call_tail = call.Popen( ["tail", "-f", f"/tmp/popper/slurm/popper_sample_{config.wid}.out"], cwd=os.getcwd(), env=None, preexec_fn=os.setsid, stderr=-2, stdout=-1, universal_newlines=True, ) call_sbatch = call.Popen( [ "sbatch", "--wait", "--job-name", f"popper_sample_{config.wid}", "--output", f"/tmp/popper/slurm/popper_sample_{config.wid}.out", f"/tmp/popper/slurm/popper_sample_{config.wid}.sh", ], cwd=os.getcwd(), env=None, preexec_fn=os.setsid, stderr=-2, stdout=-1, universal_newlines=True, ) self.assertEqual(call_tail in self.Popen.all_calls, True) self.assertEqual(call_sbatch in self.Popen.all_calls, True) @replace("popper.runner_slurm.os.kill", mock_kill) def test_submit_job_failure(self, mock_kill): config_dict = { "engine": {"name": "docker", "options": {}}, "resource_manager": {"name": "slurm", "options": {}}, } config = ConfigLoader.load(workspace_dir="/w", config_file=config_dict) self.Popen.set_command( f"sbatch --wait --job-name popper_1_{config.wid} " f"--output /tmp/popper/slurm/popper_1_{config.wid}.out " f"/tmp/popper/slurm/popper_1_{config.wid}.sh", returncode=12, ) self.Popen.set_command( f"tail -f /tmp/popper/slurm/popper_1_{config.wid}.out", returncode=0 ) with WorkflowRunner(config) as r: wf_data = { "steps": [ { "uses": "popperized/bin/sh@master", "runs": ["cat"], "args": ["README.md"], } ] } self.assertRaises(SystemExit, r.run, WorkflowParser.parse(wf_data=wf_data)) call_tail = call.Popen( ["tail", "-f", f"/tmp/popper/slurm/popper_1_{config.wid}.out"], cwd=os.getcwd(), env=None, preexec_fn=os.setsid, stderr=-2, stdout=-1, universal_newlines=True, ) call_sbatch = call.Popen( [ "sbatch", "--wait", "--job-name", f"popper_1_{config.wid}", "--output", f"/tmp/popper/slurm/popper_1_{config.wid}.out", f"/tmp/popper/slurm/popper_1_{config.wid}.sh", ], cwd=os.getcwd(), env=None, preexec_fn=os.setsid, stderr=-2, stdout=-1, universal_newlines=True, ) self.assertEqual(call_tail in self.Popen.all_calls, True) self.assertEqual(call_sbatch in self.Popen.all_calls, True) def test_dry_run(self): config = ConfigLoader.load( engine_name="docker", resman_name="slurm", dry_run=True, ) with WorkflowRunner(config) as r: wf_data = { "steps": [ { "uses": "popperized/bin/sh@master", "runs": ["cat"], "args": ["README.md"], } ] } r.run(WorkflowParser.parse(wf_data=wf_data)) self.assertEqual(self.Popen.all_calls, []) class TestSlurmDockerRunner(unittest.TestCase): def setUp(self): log.setLevel("CRITICAL") self.Popen = MockPopen() replacer = Replacer() replacer.replace("popper.runner_host.Popen", self.Popen) self.addCleanup(replacer.restore) def tearDown(self): log.setLevel("NOTSET") def test_create_cmd(self): config = {"workspace_dir": "/w"} with DockerRunner(config=ConfigLoader.load(**config)) as drunner: step = Box({"args": ["-two", "-flags"]}, default_box=True) cmd = drunner._create_cmd(step, "foo:1.9", "container_name") expected = ( "docker create" " --name container_name" " --workdir /workspace" " -v /w:/workspace" " -v /var/run/docker.sock:/var/run/docker.sock" " foo:1.9 -two -flags" ) self.assertEqual(expected, cmd) config_dict = { "engine": { "name": "docker", "options": { "privileged": True, "hostname": "popper.local", "domainname": "www.example.org", "volumes": ["/path/in/host:/path/in/container"], "environment": {"FOO": "bar"}, }, }, "resource_manager": {"name": "slurm"}, } config = {"workspace_dir": "/w", "config_file": config_dict} with DockerRunner(config=ConfigLoader.load(**config)) as drunner: step = Box({"args": ["-two", "-flags"]}, default_box=True) cmd = drunner._create_cmd(step, "foo:1.9", "container_name") expected = ( "docker create --name container_name " "--workdir /workspace " "-v /w:/workspace " "-v /var/run/docker.sock:/var/run/docker.sock " "-v /path/in/host:/path/in/container " "-e FOO=bar --privileged --hostname popper.local " "--domainname www.example.org " "foo:1.9 -two -flags" ) self.assertEqual(expected, cmd) @replace("popper.runner_slurm.os.kill", mock_kill) def test_run(self, mock_kill): config_dict = { "engine": { "name": "docker", "options": { "privileged": True, "hostname": "popper.local", "domainname": "www.example.org", "volumes": ["/path/in/host:/path/in/container"], "environment": {"FOO": "bar"}, }, }, "resource_manager": {"name": "slurm"}, } config = ConfigLoader.load(workspace_dir="/w", config_file=config_dict) self.Popen.set_command( f"sbatch --wait --job-name popper_1_{config.wid} " f"--output /tmp/popper/slurm/popper_1_{config.wid}.out " f"/tmp/popper/slurm/popper_1_{config.wid}.sh", returncode=0, ) self.Popen.set_command( f"tail -f /tmp/popper/slurm/popper_1_{config.wid}.out", returncode=0 ) with WorkflowRunner(config) as r: wf_data = { "steps": [ { "uses": "popperized/bin/sh@master", "runs": ["cat"], "args": ["README.md"], } ] } r.run(WorkflowParser.parse(wf_data=wf_data)) with open(f"/tmp/popper/slurm/popper_1_{config.wid}.sh", "r") as f: # fmt: off expected = f"""#!/bin/bash docker rm -f popper_1_{config.wid} || true docker build -t popperized/bin:master {os.environ['HOME']}/.cache/popper/{config.wid}/github.com/popperized/bin/sh docker create --name popper_1_{config.wid} --workdir /workspace --entrypoint cat -v /w:/workspace -v /var/run/docker.sock:/var/run/docker.sock -v /path/in/host:/path/in/container -e FOO=bar --privileged --hostname popper.local --domainname www.example.org popperized/bin:master README.md docker start --attach popper_1_{config.wid}""" # fmt: on actual = f.read() self.maxDiff = None self.assertEqual(expected, actual) class TestSlurmSingularityRunner(unittest.TestCase): def setUp(self): self.Popen = MockPopen() replacer = Replacer() replacer.replace("popper.runner_host.Popen", self.Popen) self.addCleanup(replacer.restore) def tearDown(self): log.setLevel("NOTSET") def test_create_cmd(self): config = ConfigLoader.load(workspace_dir="/w") with SingularityRunner(config=config) as sr: step = Box({"args": ["-two", "-flags"]}, default_box=True) sr._setup_singularity_cache() sr._container = os.path.join(sr._singularity_cache, "c1.sif") cmd = sr._create_cmd(step, "c1.sif") expected = ( "singularity run" " --userns --pwd /workspace" " --bind /w:/workspace" f' {os.environ["HOME"]}/.cache/popper/singularity/{config.wid}/c1.sif' " -two -flags" ) self.assertEqual(expected, cmd) config_dict = { "engine": { "name": "singularity", "options": { "hostname": "popper.local", "ipc": True, "bind": ["/path/in/host:/path/in/container"], }, }, "resource_manager": {"name": "slurm"}, } config = ConfigLoader.load(workspace_dir="/w", config_file=config_dict) with SingularityRunner(config=config) as sr: step = Box({"args": ["-two", "-flags"]}, default_box=True) sr._setup_singularity_cache() sr._container = os.path.join(sr._singularity_cache, "c2.sif") cmd = sr._create_cmd(step, "c2.sif") # fmt: off expected = f"singularity run --userns --pwd /workspace --bind /w:/workspace --bind /path/in/host:/path/in/container --hostname popper.local --ipc {os.environ['HOME']}/.cache/popper/singularity/{config.wid}/c2.sif -two -flags" # fmt: on self.assertEqual(expected, cmd) @replace("popper.runner_slurm.os.kill", mock_kill) def test_slurm_singularity_run(self, mock_kill): config_dict = { "engine": { "name": "singularity", "options": { "hostname": "popper.local", "bind": ["/path/in/host:/path/in/container"], }, }, "resource_manager": {"name": "slurm"}, } config = ConfigLoader.load(workspace_dir="/w", config_file=config_dict) # fmt: off self.Popen.set_command( f"sbatch --wait --job-name popper_1_{config.wid} --output /tmp/popper/slurm/popper_1_{config.wid}.out /tmp/popper/slurm/popper_1_{config.wid}.sh", returncode=0, ) # fmt: on self.Popen.set_command( f"tail -f /tmp/popper/slurm/popper_1_{config.wid}.out", returncode=0 ) with WorkflowRunner(config) as r: wf_data = {"steps": [{"uses": "popperized/bin/sh@master", "args": ["ls"],}]} r.run(WorkflowParser.parse(wf_data=wf_data)) with open(f"/tmp/popper/slurm/popper_1_{config.wid}.sh", "r") as f: # fmt: off expected = f"""#!/bin/bash singularity run --userns --pwd /workspace --bind /w:/workspace --bind /path/in/host:/path/in/container --hostname popper.local {os.environ['HOME']}/.cache/popper/singularity/{config.wid}/popper_1_{config.wid}.sif ls""" # fmt: on actual = f.read() self.assertEqual(expected, actual)

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0.787133

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0.099398

0

null

0

1

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null

0

5

0f693181fb5752447a3c08c3bd7693332134f9e4

55

py

Python

cycy/__main__.py

Magnetic/cycy

494282a37b5f7d1eaa17b8d01796df8302da2a81

[ "MIT" ]

26

2015-03-25T15:34:20.000Z

2019-03-22T09:26:30.000Z

cycy/__main__.py

DeloitteHux/cycy

494282a37b5f7d1eaa17b8d01796df8302da2a81

[ "MIT" ]

1

2017-05-21T14:00:08.000Z

2017-05-21T14:44:42.000Z

cycy/__main__.py

Magnetic/cycy

494282a37b5f7d1eaa17b8d01796df8302da2a81

[ "MIT" ]

4

2016-12-05T12:59:49.000Z

2018-11-02T05:59:43.000Z

import sys from cycy.target import main main(sys.argv)

13.75

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1

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1

0

5

0f943657c9b39b0f6febd186c26d29592154fc9c

97

py

Python

Rest Django Framework/myproject/webapp/admin.py

PaulMarcelo/Python

66a9fa21d2d803f5b06d285c705812251dc6d234

[ "Apache-2.0" ]

null

Rest Django Framework/myproject/webapp/admin.py

PaulMarcelo/Python

66a9fa21d2d803f5b06d285c705812251dc6d234

[ "Apache-2.0" ]

null

Rest Django Framework/myproject/webapp/admin.py

PaulMarcelo/Python

66a9fa21d2d803f5b06d285c705812251dc6d234

[ "Apache-2.0" ]

null

from django.contrib import admin from . models import employees admin.site.register(employees)

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7e1f3993233edb8b38978703eeff6dbb7ca28b97

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py

Python

src/reader.py

epogrebnyak/data-rosstat-boo-light

6b07f3e630fadbe18510e52c01797fd6c4e9aaa4

[ "MIT" ]

null

src/reader.py

epogrebnyak/data-rosstat-boo-light

6b07f3e630fadbe18510e52c01797fd6c4e9aaa4

[ "MIT" ]

null

src/reader.py

epogrebnyak/data-rosstat-boo-light

6b07f3e630fadbe18510e52c01797fd6c4e9aaa4

[ "MIT" ]

null

from itertools import islice from collections import OrderedDict import os import pandas as pd import settings import streams import row_parser from inspect_columns import Columns from logs import print_elapsed_time COLUMNS = Columns.COLUMNS VALID_ROW_WIDTH = len(COLUMNS) def _raw_rows(year): path = settings.url_local_path(year) return streams.yield_csv_rows(path) def has_valid_length(_row, n=VALID_ROW_WIDTH): return len(_row) == n def raw_rows(year): return filter(has_valid_length, _raw_rows(year)) def as_dict(row, columns=COLUMNS): return OrderedDict(zip(columns, row)) def _raw_dicts(year): return map(as_dict, _raw_rows(year)) def has_inn(_dict): return _dict['inn'] def raw_dicts(year): return filter(has_inn, _raw_dicts(year)) assert next(raw_rows(2012)) assert next(raw_dicts(2017)) class Dataset: dtypes = row_parser.DTYPES colnames = row_parser.COLNAMES def __init__(self, year: int): self.year = year # FIXME: this is untrivial - the function accepts a dict and produces a list def rows(self): gen = raw_dicts(self.year) return map(row_parser.parse_row_to_list, gen) def dicts(self): gen = raw_dicts(self.year) return map(row_parser.parse_row_to_dict, gen) # FIXME: make separate functions # @staticmethod # def nth(gen, n): # return next(islice(gen, n, n + 1)) # # def nth_row(self, n=0): # return self.nth(self.rows(), n) # # def nth_dict(self, n=0): # return self.nth(self.dicts(), n) @property def path(self): return settings.csv_path_processed(self.year) def to_csv(self): if not os.path.exists(self.path): print(f"{self.year}: Saving large file to", self.path) streams.rows_to_csv(path = self.path, stream = self.rows(), cols = self.colnames) else: print(f"{self.year}: File already exists:", self.path) @print_elapsed_time def read_dataframe(self): print("Reading {} dataframe...".format(self.year)) with open(self.path, 'r', encoding='utf-8') as f: return pd.read_csv(f, dtype=self.dtypes) #class Subset: # def __init__(self, year: int, inns: list): # self.dataset = Dataset(year) # self.inns = [str(x) for x in inns] # # def dicts(self): # for d in self.dataset.dicts(): # inn = str(d['inn']) # if inn in self.inns: # self.inns.remove(inn) # yield d # if not self.inns: # break # # def not_found(self): # return "\n".join(sorted(k.inns)) # # def to_csv(self, filename): # path = tempfile(filename) # if not os.path.exists(path): # dicts_to_csv(path = path, # dict_stream = self.dicts(), # column_names = self.dataset.colnames) # return path #if __name__ == "__main__": # # create model dataset # stream = list(islice(RawDataset(2012).rows(), 0, 500)) # path = tempfile('reference_dataset.txt') # to_csv(path, stream, cols=None) # # TODO: place at # # # #Subset(2015, 'test1').to_csv() # d = Dataset(2012) # a = next(Dataset(2016).dicts()) # z = next(RawDataset(2016).get_rows()) # import random # ix = [random.choice(range(100)) for _ in range(5)] # inns = [d.nth_dict(i)['inn'] for i in ix] # inns = ['2224102690', '2204026804', '2222057509', '2204026730', '2207007165'] # s = Subset(2012, inns) # #gen = s.dicts() # #print(list(gen)) # s.to_csv("sample5.csv") # # #df = Dataset(2016).read_dataframe() # #Dataset(2016).to_csv() # # FIXME: results in MemoryError # # doc = """6125021399 #6165111610 #5501092795 #3252005997 #2617013243 #0214005782 #6125028404 #7840322535 #2723127073 #7726311464 #6432005430 #2460222454 #2009002493 #2460205089 #7707049388 #7713591359 #4027083322 #7601000640 #7702347870 #1627005779 #6135006840 #2320102816 #5007035121 #7801499923 #2502039781 #2465102746 #7709756135 #7614005035 #2721162072 #7725027605 #7704753638 #2310119472 #7709758887 #6234028965 #6312034863 #7727541830 #2312153550 #7328063237 #1661028712 #7734046851 #4501122913 #7701897582 #1834051678 #4003034171 #2317044843 #7714175986 #7606053324 #7735128151 #7206025040 #6320002223 #2420002597 #1327000226 #6125022025 #3327823181 #1646021952 #1650161470 #4703038767 #7710884741 #7713730490 #1650206314 #2320153289 #2317010611 #5029140480 #7830002705 #2320126091 #6313036408 #2325014338 #4807013380 #7813173683 #6906011193 #4715019631 #2721167592 #5030062677 #7425756540 #2319037591 #7116145872 #5010032360 #6163082392 #1659032038 #7712094033 #5029006702 #2130001337 #7707327050 #7611020204 #7724791423 #7714005350 #1434045743 #7706273281 #7731084175 #4713008017 #6315376946 #7817312063 #7708624200 #7714046028 #6167081833 #4214018010 #3013015987 #0522016027 #2277011020 #7743816842 #7801435581 #7718532879 #5614023224 #1216015989 #7718226550 #7705620334 #7707131554 #4027077632 #5307006883 #2342016712 #7701513162 #5614054173 #2127007427 #3815011264 #2130009512 #6453010174 #2130181337 #6450079058 #7707296041 #8300005580 #7105514574 #5032172562 #0710005596 #2709001880 #3663075863 #5402480282 #3904612524 #6123015784 #7724674670 #7708320240 #4214000252 #5040066582 #6453076256 #3917016350 #7842012360 #5604009492 #7705514093 #6230004963 #5616009708 #7702334864 #5032124142 #5613001002 #3437006665 #5040058775 #2703000858 #2011002420 #7730589568 #3837049102 #5614018560 #1616016850 #6623029538 #7730052050 #7731644035 #7839395419 #7731644035 #6659190900 #2902060361 #7327016379 #7709413138 #7708710924 #7725638925 #7708304859 #7717163097 #7724736609 #7714619159 #5032178356 #7728278043 #3663029916 #7702326045 #7729355614 #7722787661 #9909391333 #9909391291 #9909391260 #7708201998 #9909001382 #9909378244 #9909439151 #9909012056""" # # inns = doc.split("\n") # k = Subset(2016, inns) # k.to_csv('179.csv') # # """Not finished: # # subsets as Excel files # manageable, smaller files # Expert 200 # #""" # # #

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0

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5

7e3b5d9d272b6bcbd3ac425a5dfc3806c55d4ab9

65

py

Python

core/base/pydantic.py

cleiveliu/django-template

01c6d03a66fe869e7155f8189b5b79570f36ba44

[ "MIT" ]

null

core/base/pydantic.py

cleiveliu/django-template

01c6d03a66fe869e7155f8189b5b79570f36ba44

[ "MIT" ]

null

core/base/pydantic.py

cleiveliu/django-template

01c6d03a66fe869e7155f8189b5b79570f36ba44

[ "MIT" ]

null

from pydantic import BaseModel, ValidationError, EmailStr, Field

32.5

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5

7e4f35e358bde7ea8bb926ca03727c4ce868d8c8

131

py

Python

codewof/programming/content/en/string-concatenation/solution.py

taskmaker1/codewof

92d52cd3ee91f0f311ff01a92cf6ec07e5593b8d

[ "MIT" ]

3

2019-08-29T04:11:22.000Z

2021-06-22T16:05:51.000Z

codewof/programming/content/en/string-concatenation/solution.py

taskmaker1/codewof

92d52cd3ee91f0f311ff01a92cf6ec07e5593b8d

[ "MIT" ]

265

2019-05-30T03:51:46.000Z

2022-03-31T01:05:12.000Z

codewof/programming/content/en/string-concatenation/solution.py

samuelsandri/codewof

c9b8b378c06b15a0c42ae863b8f46581de04fdfc

[ "MIT" ]

7

2019-06-29T12:13:37.000Z

2021-09-06T06:49:14.000Z

string_1 = input("String 1? ") string_2 = input("String 2? ") string_3 = input("String 3? ") print(string_1 + string_2 + string_3)

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5

7e6ec91a7e0cd9768d10af045025dc822a62b0f1

192

py

Python

primeira_lista/ex002.py

PedroSantana2/exercicios-em-python

e0a98e699ba49873f67438fd9092dc3ab0ca719c

[ "MIT" ]

1

2021-03-16T03:58:39.000Z

primeira_lista/ex002.py

PedroSantana2/exercicios-em-python

e0a98e699ba49873f67438fd9092dc3ab0ca719c

[ "MIT" ]

null

primeira_lista/ex002.py

PedroSantana2/exercicios-em-python

e0a98e699ba49873f67438fd9092dc3ab0ca719c

[ "MIT" ]

null

''' Faça um Programa que peça um número e então mostre a mensagem: O número informado foi [número]. ''' numero = input('Digite um número: ') print('O número informado foi: {}'.format(numero))

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7e8e70033287aa44e9302ffd4212483e44b7d6d1

1,242

py

Python

coderdojochi/migrations/0019_auto_20180815_1658.py

rgroves/weallcode-website

ead60d3272dbbfe610b2d500978d1de44aef6386

[ "MIT" ]

15

2019-05-04T00:24:00.000Z

2021-08-21T16:34:05.000Z

coderdojochi/migrations/0019_auto_20180815_1658.py

rgroves/weallcode-website

ead60d3272dbbfe610b2d500978d1de44aef6386

[ "MIT" ]

73

2019-04-24T15:53:42.000Z

2021-08-06T20:41:41.000Z

coderdojochi/migrations/0019_auto_20180815_1658.py

rgroves/weallcode-website

ead60d3272dbbfe610b2d500978d1de44aef6386

[ "MIT" ]

20

2019-04-26T20:13:08.000Z

2021-06-21T14:53:21.000Z

# Generated by Django 2.0.6 on 2018-08-15 21:58 from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('coderdojochi', '0018_auto_20180606_0838'), ] operations = [ migrations.AddField( model_name='guardian', name='birthday', field=models.DateTimeField(null=True), ), migrations.AddField( model_name='guardian', name='gender', field=models.CharField(max_length=255, null=True), ), migrations.AddField( model_name='guardian', name='race_ethnicity', field=models.ManyToManyField(to='coderdojochi.RaceEthnicity'), ), migrations.AddField( model_name='mentor', name='birthday', field=models.DateTimeField(null=True), ), migrations.AddField( model_name='mentor', name='gender', field=models.CharField(max_length=255, null=True), ), migrations.AddField( model_name='mentor', name='race_ethnicity', field=models.ManyToManyField(to='coderdojochi.RaceEthnicity'), ), ]

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0e733b7632db76bc324daa1d1bcc7ba5d8556c2b

37

py

Python

tests/__init__.py

sizumita/dpybrew

bdf9e42f238ef16229d1ae05aa213ffb3a32b3af

[ "MIT" ]

1

2020-06-20T14:49:39.000Z

tests/__init__.py

sizumita/dpybrew

bdf9e42f238ef16229d1ae05aa213ffb3a32b3af

[ "MIT" ]

3

2020-03-29T12:57:06.000Z

2020-03-30T13:40:00.000Z

tests/__init__.py

sizumita/dpybrew

bdf9e42f238ef16229d1ae05aa213ffb3a32b3af

[ "MIT" ]

1

2020-03-30T09:42:59.000Z

"""Unit test package for dpybrew."""

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0e788c71030fd04ef2f56a23799722c9816c5d1f

120

py

Python

hght/__init__.py

zephenryus/botw-hght

48f7a933c183b55a4ee0852594281aaab1ad16c1

[ "MIT" ]

null

hght/__init__.py

zephenryus/botw-hght

48f7a933c183b55a4ee0852594281aaab1ad16c1

[ "MIT" ]

null

hght/__init__.py

zephenryus/botw-hght

48f7a933c183b55a4ee0852594281aaab1ad16c1

[ "MIT" ]

null

from .read_hght import read_hght from .write_hght import write_hght, compile_hght from .generate_map import generate_map

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5

0e835dded92b27c09fa90189998b2e3d72cbbdaf

32

py

Python

Beta/Return Even Whatever Youve Been Given.py

mwk0408/codewars_solutions

9b4f502b5f159e68024d494e19a96a226acad5e5

[ "MIT" ]

6

2020-09-03T09:32:25.000Z

2020-12-07T04:10:01.000Z

Beta/Return Even Whatever Youve Been Given.py

mwk0408/codewars_solutions

9b4f502b5f159e68024d494e19a96a226acad5e5

[ "MIT" ]

1

2021-12-13T15:30:21.000Z

Beta/Return Even Whatever Youve Been Given.py

mwk0408/codewars_solutions

9b4f502b5f159e68024d494e19a96a226acad5e5

[ "MIT" ]

null

def always_even(n): return n-n%2

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null

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1

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5

7d37344389f31e522356ccc53dea0e08b94ec7b4

530

py

Python

AI/home/views.py

Phong940253/math-word-problem

e8410944c9d2aafce949811025e8f164fee6c74c

[ "MIT" ]

1

2021-05-12T19:29:04.000Z

AI/home/views.py

Phong940253/math-word-problem

e8410944c9d2aafce949811025e8f164fee6c74c

[ "MIT" ]

null

AI/home/views.py

Phong940253/math-word-problem

e8410944c9d2aafce949811025e8f164fee6c74c

[ "MIT" ]

null

from django.shortcuts import render from django.http import HttpResponse from .EngineCKB import Engine def home(request): return render(request, 'page/page.html') def thread(request): return render(request, 'page/thread.html') def about(request): return render(request, 'page/aboutus.html') def result(request): if request.method == 'POST': test = request.POST["search"] engine = Engine(test) print(engine.res) return render(request, 'page/result.html', {'engine': engine.res})

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null

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1

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1

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7d42cb74709f216bc7143ceae9c2e943b2e06644

265

py

Python

deepext_with_lightning/models/classification/__init__.py

pei223/deepext_with_lightning

e40ac19844a05864f803431d8ef4a534286a0950

[ "MIT" ]

1

2021-02-25T14:30:08.000Z

deepext_with_lightning/models/classification/__init__.py

pei223/deepext_with_lightning

e40ac19844a05864f803431d8ef4a534286a0950

[ "MIT" ]

null

deepext_with_lightning/models/classification/__init__.py

pei223/deepext_with_lightning

e40ac19844a05864f803431d8ef4a534286a0950

[ "MIT" ]

null

from .mobilenet_v3.mobilenet_v3 import MobileNetV3 from .efficientnet.efficientnet import EfficientNet from .abn.attention_branch_network import AttentionBranchNetwork from .customnet.custom_classification import CustomClassificationNetwork from . import functions

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1

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1

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5

7d492fc930eb7f9403cd953775800f86d6c58f1c

117

py

Python

setup.py

kreneskyp/ixian

80133e9106e23eeb562c0112dd70bcdfb61986f9

[ "Apache-2.0" ]

null

setup.py

kreneskyp/ixian

80133e9106e23eeb562c0112dd70bcdfb61986f9

[ "Apache-2.0" ]

null

setup.py

kreneskyp/ixian

80133e9106e23eeb562c0112dd70bcdfb61986f9

[ "Apache-2.0" ]

null

from setuptools import setup setup(setup_requires=["pbr"], pbr=True, long_description_content_type="text/markdown")

29.25

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null

0

1

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1

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5

adb3fcf64508ba7e71978a1988d1dc68df75c64c

38

py

Python

regex_builder/errors.py

Zomatree/regex-builder

a83377dd50ba9557126a8d0a6d5a987df4fccad3

[ "MIT" ]

3

2020-07-27T10:15:02.000Z

2021-01-13T00:12:40.000Z

regex_builder/errors.py

Zomatree/regex-builder

a83377dd50ba9557126a8d0a6d5a987df4fccad3

[ "MIT" ]

null

regex_builder/errors.py

Zomatree/regex-builder

a83377dd50ba9557126a8d0a6d5a987df4fccad3

[ "MIT" ]

1

2021-01-13T00:13:49.000Z

class NotSection(Exception): pass

12.666667

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1

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1

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5

adb413dc26c8d62d378d338a8568409207560a51

193

py

Python

models/amenity.py

kemboy-254/AirBnB_clone

45bfb47cd8a47a7db85f0cfc266b09e88e8fbad7

[ "MIT" ]

null

models/amenity.py

kemboy-254/AirBnB_clone

45bfb47cd8a47a7db85f0cfc266b09e88e8fbad7

[ "MIT" ]

2

2020-07-01T17:02:43.000Z

2020-07-12T19:57:08.000Z

models/amenity.py

kemboy-254/AirBnB_clone

45bfb47cd8a47a7db85f0cfc266b09e88e8fbad7

[ "MIT" ]

4

2020-07-07T15:17:00.000Z

2021-11-11T12:15:00.000Z

#!/usr/bin/python3 """New class inherit from BaseModel""" from models.base_model import BaseModel class Amenity(BaseModel): """Class Amenity that inherit from BaseModel""" name = ""

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null

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1

0

5

adbbb936de507ba25fabc7e08662900411a58564

47

py

Python

specter/__main__.py

breekristensen/Specter

1f5a729b0aa16242add8c1c754efa268335e3944

[ "MIT" ]

18

2015-03-19T17:01:31.000Z

2020-01-03T18:30:09.000Z

specter/__main__.py

breekristensen/Specter

1f5a729b0aa16242add8c1c754efa268335e3944

[ "MIT" ]

52

2015-01-19T05:10:59.000Z

2020-04-16T17:41:19.000Z

specter/__main__.py

breekristensen/Specter

1f5a729b0aa16242add8c1c754efa268335e3944

[ "MIT" ]

11

2015-07-14T16:23:07.000Z

2021-09-09T20:59:24.000Z

from specter.runner import activate activate()

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0.106383

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bc114fccbc460740d090660db9f5c058ab088e00

177

py

Python

backend/entities/i_serializable.py

GroupLe/grouple-face-tagger

5fd87c074dc50a5fc341e9f30774094a1616a87f

[ "MIT" ]

null

backend/entities/i_serializable.py

GroupLe/grouple-face-tagger

5fd87c074dc50a5fc341e9f30774094a1616a87f

[ "MIT" ]

19

2021-07-22T11:18:17.000Z

2021-08-20T10:12:17.000Z

backend/entities/i_serializable.py

GroupLe/grouple-face-tagger

5fd87c074dc50a5fc341e9f30774094a1616a87f

[ "MIT" ]

1

2021-07-29T11:56:03.000Z

from typing import Dict class ISerializable: def __init__(self, *args, **kwargs): raise NotImplemented def to_json(self) -> Dict: raise NotImplemented

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0.333333

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null

0

1

0

1

0

5

bc1f200d52558487f8dc500d0e5294712a331bd6

50

py

Python

my_app/__main__.py

fschuch/fastapi_project

7897a83fe6e802cbcb0e2f3757aa008989c07bcb

[ "MIT" ]

null

my_app/__main__.py

fschuch/fastapi_project

7897a83fe6e802cbcb0e2f3757aa008989c07bcb

[ "MIT" ]

null

my_app/__main__.py

fschuch/fastapi_project

7897a83fe6e802cbcb0e2f3757aa008989c07bcb

[ "MIT" ]

null

import uvicorn from . import app uvicorn.run(app)

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null

0

1

0

1

0

1

0

5

70bc2f94c57e57184fba73ddd7b2039bcd304441

107

py

Python

settings.py

jwross24/twitoff

6d89c361ae9235f606b224deef22b1a5d27a0117

[ "MIT" ]

null

settings.py

jwross24/twitoff

6d89c361ae9235f606b224deef22b1a5d27a0117

[ "MIT" ]

3

2021-09-08T01:44:01.000Z

2022-03-12T00:18:17.000Z

settings.py

jwross24/twitoff

6d89c361ae9235f606b224deef22b1a5d27a0117

[ "MIT" ]

1

2021-05-08T07:02:06.000Z

"""Allow the application to see the environment variables.""" from dotenv import load_dotenv load_dotenv()

26.75

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107

5.533333

0.733333

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0

0.121495

107

3

62

35.666667

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0.514019

0

1

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true

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null

0

1

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1

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5

cb3bb3477d42809580b10cbc396a6f56151088aa

135

py

Python

pynetlinux/util.py

youviewtv/pynetlinux

e3f16978855c6649685f0c43d4c3fcf768427ae5

[ "BSD-3-Clause" ]

69

2015-01-07T01:34:41.000Z

2022-03-29T01:40:59.000Z

pynetlinux/util.py

youviewtv/pynetlinux

e3f16978855c6649685f0c43d4c3fcf768427ae5

[ "BSD-3-Clause" ]

5

2015-03-18T03:19:56.000Z

2021-03-02T23:54:07.000Z

pynetlinux/util.py

youviewtv/pynetlinux

e3f16978855c6649685f0c43d4c3fcf768427ae5

[ "BSD-3-Clause" ]

37

2015-01-25T21:13:05.000Z

2022-03-10T06:41:26.000Z

import sys PY2 = sys.version_info[0] == 2 PY3 = sys.version_info[0] == 3 if PY3: binary_type = bytes else: binary_type = str

13.5

30

0.651852

23

135

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0.238095

0.333333

0.357143

0

0.067308

0.22963

135

9

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false

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0

1

0

null

1

0

1

0

null

0

5

cb666be8979f576507aedd5b90ecaf5dcdbc0fc6

306

py

Python

main.py

Eli-pixel/Etext

b30413867c4d67f6ece441c4654bcc94c4f4588e

[ "MIT" ]

1

2020-06-01T14:31:50.000Z

main.py

Eli-pixel/Etext

b30413867c4d67f6ece441c4654bcc94c4f4588e

[ "MIT" ]

null

main.py

Eli-pixel/Etext

b30413867c4d67f6ece441c4654bcc94c4f4588e

[ "MIT" ]

null

from ecolor import slow_color, slow_print, ecolor ecolor("This is red text", "red") ecolor("This is bold blue text", "bold_blue") slow_print("This is slow_print", 0.025) slow_color("This is slow_print but colorful", "blue", 0.025) slow_color("This is slow_print but colorful and bold", "bold_blue", 0.025)

43.714286

74

0.748366

55

306

3.981818

0.309091

0.205479

0.136986

0.205479

0.356164

0

0.04461

0.120915

306

6

75

51

0.769517

0

0.496732

0

1

0

true

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0.166667

0.666667

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1

0

null

0

1

0

1

0

5

cb9b503e3afe08ac14f1874cd147712dba6dd8a0

12,692

py

Python

hostmanager/tomato/migrations/0006_users3.py

dswd/ToMaTo

355fd3a8c7f95dc72c62383b3edfa8f6c0396bf4

[ "BSD-4-Clause-UC" ]

2

2016-11-10T06:12:05.000Z

2016-11-10T06:12:10.000Z

hostmanager/tomato/migrations/0006_users3.py

dswd/ToMaTo

355fd3a8c7f95dc72c62383b3edfa8f6c0396bf4

[ "BSD-4-Clause-UC" ]

2

2015-01-19T16:00:24.000Z

2015-01-20T11:33:56.000Z

hostmanager/tomato/migrations/0006_users3.py

dswd/ToMaTo

355fd3a8c7f95dc72c62383b3edfa8f6c0396bf4

[ "BSD-4-Clause-UC" ]

1

2016-11-10T06:12:15.000Z

# -*- coding: utf-8 -*- import datetime from south.db import db from south.v2 import SchemaMigration from django.db import models class Migration(SchemaMigration): def forwards(self, orm): # Removing unique constraint on 'Network', fields ['bridge'] db.delete_unique('tomato_network', ['bridge']) # Changing field 'Network.owner' db.alter_column('tomato_network', 'owner_id', self.gf('django.db.models.fields.related.ForeignKey')(to=orm['tomato.User'])) # Adding unique constraint on 'Network', fields ['owner', 'bridge'] db.create_unique('tomato_network', ['owner_id', 'bridge']) # Deleting field 'Element.owner_str' db.delete_column('tomato_element', 'owner_str') # Changing field 'Element.owner' db.alter_column('tomato_element', 'owner_id', self.gf('django.db.models.fields.related.ForeignKey')(to=orm['tomato.User'])) # Deleting field 'Connection.owner_str' db.delete_column('tomato_connection', 'owner_str') # Changing field 'Connection.owner' db.alter_column('tomato_connection', 'owner_id', self.gf('django.db.models.fields.related.ForeignKey')(to=orm['tomato.User'])) # Changing field 'Template.owner' db.alter_column('tomato_template', 'owner_id', self.gf('django.db.models.fields.related.ForeignKey')(to=orm['tomato.User'])) # Adding unique constraint on 'Template', fields ['owner', 'tech', 'name'] db.create_unique('tomato_template', ['owner_id', 'tech', 'name']) def backwards(self, orm): # Removing unique constraint on 'Template', fields ['owner', 'tech', 'name'] db.delete_unique('tomato_template', ['owner_id', 'tech', 'name']) # Removing unique constraint on 'Network', fields ['owner', 'bridge'] db.delete_unique('tomato_network', ['owner_id', 'bridge']) # Changing field 'Network.owner' db.alter_column('tomato_network', 'owner_id', self.gf('django.db.models.fields.related.ForeignKey')(null=False, to=orm['tomato.User'])) # Adding unique constraint on 'Network', fields ['bridge'] db.create_unique('tomato_network', ['bridge']) # User chose to not deal with backwards NULL issues for 'Element.owner_str' raise RuntimeError("Cannot reverse this migration. 'Element.owner_str' and its values cannot be restored.") # Changing field 'Element.owner' db.alter_column('tomato_element', 'owner_id', self.gf('django.db.models.fields.related.ForeignKey')(null=False, to=orm['tomato.User'])) # User chose to not deal with backwards NULL issues for 'Connection.owner_str' raise RuntimeError("Cannot reverse this migration. 'Connection.owner_str' and its values cannot be restored.") # Changing field 'Connection.owner' db.alter_column('tomato_connection', 'owner_id', self.gf('django.db.models.fields.related.ForeignKey')(null=False, to=orm['tomato.User'])) # Changing field 'Template.owner' db.alter_column('tomato_template', 'owner_id', self.gf('django.db.models.fields.related.ForeignKey')(null=False, to=orm['tomato.User'])) models = { 'tomato.bridge': { 'Meta': {'object_name': 'Bridge', '_ormbases': ['tomato.Connection']}, 'connection_ptr': ('django.db.models.fields.related.OneToOneField', [], {'to': "orm['tomato.Connection']", 'unique': 'True', 'primary_key': 'True'}) }, 'tomato.connection': { 'Meta': {'object_name': 'Connection'}, 'attrs': ('tomato.lib.db.JSONField', [], {}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'owner': ('django.db.models.fields.related.ForeignKey', [], {'related_name': "'connections'", 'to': "orm['tomato.User']"}), 'state': ('django.db.models.fields.CharField', [], {'max_length': '20'}), 'type': ('django.db.models.fields.CharField', [], {'max_length': '20'}), 'usageStatistics': ('django.db.models.fields.related.OneToOneField', [], {'related_name': "'connection'", 'unique': 'True', 'null': 'True', 'to': "orm['tomato.UsageStatistics']"}) }, 'tomato.element': { 'Meta': {'object_name': 'Element'}, 'attrs': ('tomato.lib.db.JSONField', [], {}), 'connection': ('django.db.models.fields.related.ForeignKey', [], {'related_name': "'elements'", 'null': 'True', 'to': "orm['tomato.Connection']"}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'owner': ('django.db.models.fields.related.ForeignKey', [], {'related_name': "'elements'", 'to': "orm['tomato.User']"}), 'parent': ('django.db.models.fields.related.ForeignKey', [], {'related_name': "'children'", 'null': 'True', 'to': "orm['tomato.Element']"}), 'state': ('django.db.models.fields.CharField', [], {'max_length': '20'}), 'timeout': ('django.db.models.fields.FloatField', [], {}), 'type': ('django.db.models.fields.CharField', [], {'max_length': '20'}), 'usageStatistics': ('django.db.models.fields.related.OneToOneField', [], {'related_name': "'element'", 'unique': 'True', 'null': 'True', 'to': "orm['tomato.UsageStatistics']"}) }, 'tomato.external_network': { 'Meta': {'object_name': 'External_Network', '_ormbases': ['tomato.Element']}, 'element_ptr': ('django.db.models.fields.related.OneToOneField', [], {'to': "orm['tomato.Element']", 'unique': 'True', 'primary_key': 'True'}), 'network': ('django.db.models.fields.related.ForeignKey', [], {'related_name': "'instances'", 'null': 'True', 'to': "orm['tomato.Network']"}) }, 'tomato.fixed_bridge': { 'Meta': {'object_name': 'Fixed_Bridge', '_ormbases': ['tomato.Connection']}, 'connection_ptr': ('django.db.models.fields.related.OneToOneField', [], {'to': "orm['tomato.Connection']", 'unique': 'True', 'primary_key': 'True'}) }, 'tomato.kvmqm': { 'Meta': {'object_name': 'KVMQM', '_ormbases': ['tomato.Element']}, 'element_ptr': ('django.db.models.fields.related.OneToOneField', [], {'to': "orm['tomato.Element']", 'unique': 'True', 'primary_key': 'True'}), 'template': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['tomato.Template']", 'null': 'True'}) }, 'tomato.kvmqm_interface': { 'Meta': {'object_name': 'KVMQM_Interface', 'db_table': "'tomato_kvm_interface'", '_ormbases': ['tomato.Element']}, 'element_ptr': ('django.db.models.fields.related.OneToOneField', [], {'to': "orm['tomato.Element']", 'unique': 'True', 'primary_key': 'True'}) }, 'tomato.network': { 'Meta': {'unique_together': "(('bridge', 'owner'),)", 'object_name': 'Network', '_ormbases': ['tomato.Resource']}, 'bridge': ('django.db.models.fields.CharField', [], {'max_length': '20'}), 'kind': ('django.db.models.fields.CharField', [], {'max_length': '50'}), 'owner': ('django.db.models.fields.related.ForeignKey', [], {'related_name': "'networks'", 'to': "orm['tomato.User']"}), 'preference': ('django.db.models.fields.IntegerField', [], {'default': '0'}), 'resource_ptr': ('django.db.models.fields.related.OneToOneField', [], {'to': "orm['tomato.Resource']", 'unique': 'True', 'primary_key': 'True'}) }, 'tomato.openvz': { 'Meta': {'object_name': 'OpenVZ', '_ormbases': ['tomato.Element']}, 'element_ptr': ('django.db.models.fields.related.OneToOneField', [], {'to': "orm['tomato.Element']", 'unique': 'True', 'primary_key': 'True'}), 'template': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['tomato.Template']", 'null': 'True'}) }, 'tomato.openvz_interface': { 'Meta': {'object_name': 'OpenVZ_Interface', '_ormbases': ['tomato.Element']}, 'element_ptr': ('django.db.models.fields.related.OneToOneField', [], {'to': "orm['tomato.Element']", 'unique': 'True', 'primary_key': 'True'}) }, 'tomato.repy': { 'Meta': {'object_name': 'Repy', '_ormbases': ['tomato.Element']}, 'element_ptr': ('django.db.models.fields.related.OneToOneField', [], {'to': "orm['tomato.Element']", 'unique': 'True', 'primary_key': 'True'}), 'template': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['tomato.Template']", 'null': 'True'}) }, 'tomato.repy_interface': { 'Meta': {'object_name': 'Repy_Interface', '_ormbases': ['tomato.Element']}, 'element_ptr': ('django.db.models.fields.related.OneToOneField', [], {'to': "orm['tomato.Element']", 'unique': 'True', 'primary_key': 'True'}) }, 'tomato.resource': { 'Meta': {'object_name': 'Resource'}, 'attrs': ('tomato.lib.db.JSONField', [], {}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'type': ('django.db.models.fields.CharField', [], {'max_length': '20'}) }, 'tomato.resourceinstance': { 'Meta': {'unique_together': "(('num', 'type'),)", 'object_name': 'ResourceInstance'}, 'attrs': ('tomato.lib.db.JSONField', [], {}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'num': ('django.db.models.fields.IntegerField', [], {}), 'ownerConnection': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['tomato.Connection']", 'null': 'True'}), 'ownerElement': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['tomato.Element']", 'null': 'True'}), 'type': ('django.db.models.fields.CharField', [], {'max_length': '20'}) }, 'tomato.template': { 'Meta': {'unique_together': "(('tech', 'name', 'owner'),)", 'object_name': 'Template', '_ormbases': ['tomato.Resource']}, 'name': ('django.db.models.fields.CharField', [], {'max_length': '50'}), 'owner': ('django.db.models.fields.related.ForeignKey', [], {'related_name': "'templates'", 'to': "orm['tomato.User']"}), 'preference': ('django.db.models.fields.IntegerField', [], {'default': '0'}), 'resource_ptr': ('django.db.models.fields.related.OneToOneField', [], {'to': "orm['tomato.Resource']", 'unique': 'True', 'primary_key': 'True'}), 'tech': ('django.db.models.fields.CharField', [], {'max_length': '20'}) }, 'tomato.tinc': { 'Meta': {'object_name': 'Tinc', '_ormbases': ['tomato.Element']}, 'element_ptr': ('django.db.models.fields.related.OneToOneField', [], {'to': "orm['tomato.Element']", 'unique': 'True', 'primary_key': 'True'}) }, 'tomato.udp_tunnel': { 'Meta': {'object_name': 'UDP_Tunnel', '_ormbases': ['tomato.Element']}, 'element_ptr': ('django.db.models.fields.related.OneToOneField', [], {'to': "orm['tomato.Element']", 'unique': 'True', 'primary_key': 'True'}) }, 'tomato.usagerecord': { 'Meta': {'object_name': 'UsageRecord'}, 'begin': ('django.db.models.fields.FloatField', [], {}), 'cputime': ('django.db.models.fields.FloatField', [], {}), 'diskspace': ('django.db.models.fields.FloatField', [], {}), 'end': ('django.db.models.fields.FloatField', [], {}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'measurements': ('django.db.models.fields.IntegerField', [], {}), 'memory': ('django.db.models.fields.FloatField', [], {}), 'statistics': ('django.db.models.fields.related.ForeignKey', [], {'related_name': "'records'", 'to': "orm['tomato.UsageStatistics']"}), 'traffic': ('django.db.models.fields.FloatField', [], {}), 'type': ('django.db.models.fields.CharField', [], {'max_length': '10'}) }, 'tomato.usagestatistics': { 'Meta': {'object_name': 'UsageStatistics'}, 'attrs': ('tomato.lib.db.JSONField', [], {}), 'begin': ('django.db.models.fields.FloatField', [], {}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}) }, 'tomato.user': { 'Meta': {'object_name': 'User'}, 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'name': ('django.db.models.fields.CharField', [], {'unique': 'True', 'max_length': '20'}) } } complete_apps = ['tomato']

65.087179

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null

0

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null

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5

cbb33ca1055aecac56a595340359148d7cd30307

163

py

Python

run.py

gaolycn/ssr-panel-sanic

73739710dbd6206d8febbf57e02eebc6b3082095

[ "MIT" ]

9

2017-07-11T08:36:48.000Z

2021-03-24T02:34:53.000Z

run.py

gaolycn/ssr-panel-sanic

73739710dbd6206d8febbf57e02eebc6b3082095

[ "MIT" ]

null

run.py

gaolycn/ssr-panel-sanic

73739710dbd6206d8febbf57e02eebc6b3082095

[ "MIT" ]

7

2017-07-11T08:36:51.000Z

2018-04-27T00:59:19.000Z

from ssr_panel import app if __name__ == '__main__': app.run(host=app.config.HOST, port=app.config.PORT, workers=app.config.WORKERS, debug=app.config.DEBUG)

27.166667

107

0.748466

26

163

4.346154

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0.318584

0

0.110429

163

5

108

32.6

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0.04908

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1

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true

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null

0

1

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5

cbc7a2a51f62b1b9e80be750bdddaab95b56a85c

6,044

py

Python

python/oneflow/test/modules/test_add.py

Zhangchangh/oneflow

4ea3935458cc83dcea0abd88dd613f09c57dc01a

[ "Apache-2.0" ]

null

python/oneflow/test/modules/test_add.py

Zhangchangh/oneflow

4ea3935458cc83dcea0abd88dd613f09c57dc01a

[ "Apache-2.0" ]

null

python/oneflow/test/modules/test_add.py

Zhangchangh/oneflow

4ea3935458cc83dcea0abd88dd613f09c57dc01a

[ "Apache-2.0" ]

null

""" Copyright 2020 The OneFlow Authors. All rights reserved. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. """ import unittest from collections import OrderedDict import numpy as np from test_util import GenArgList import oneflow as flow import oneflow.unittest def _test_add_forward(test_case, shape, device): x = flow.Tensor(np.random.randn(*shape), device=flow.device(device)) y = flow.Tensor(np.random.randn(*shape), device=flow.device(device)) of_out = flow.add(x, y) np_out = np.add(x.numpy(), y.numpy()) test_case.assertTrue(np.allclose(of_out.numpy(), np_out, 0.0001, 0.0001)) x = 5 y = flow.Tensor(np.random.randn(*shape), device=flow.device(device)) of_out = flow.add(x, y) np_out = np.add(x, y.numpy()) test_case.assertTrue(np.allclose(of_out.numpy(), np_out, 0.0001, 0.0001)) x = flow.Tensor(np.random.randn(*shape), device=flow.device(device)) y = 5 of_out = flow.add(x, y) np_out = np.add(x.numpy(), y) test_case.assertTrue(np.allclose(of_out.numpy(), np_out, 0.0001, 0.0001)) x = flow.Tensor(np.random.randn(*shape), device=flow.device(device)) y = flow.Tensor(np.array([5.0]), device=flow.device(device)) of_out = flow.add(x, y) np_out = np.add(x.numpy(), y.numpy()) test_case.assertTrue(np.allclose(of_out.numpy(), np_out, 0.0001, 0.0001)) x = flow.Tensor(np.random.randn(1, 1), device=flow.device(device)) y = flow.Tensor(np.random.randn(*shape), device=flow.device(device)) of_out = flow.add(x, y) np_out = np.add(x.numpy(), y.numpy()) test_case.assertTrue(np.allclose(of_out.numpy(), np_out, 0.0001, 0.0001)) def _test_add_backward(test_case, shape, device): x = 5 y = flow.Tensor( np.random.randn(*shape), requires_grad=True, device=flow.device(device) ) of_out = flow.add(x, y).sum() of_out.backward() test_case.assertTrue( np.allclose(y.grad.numpy(), np.ones(shape=shape), 0.0001, 0.0001) ) def _test_inplace_add(test_case, shape, device): np_x = np.random.randn(*shape) of_x = flow.Tensor( np_x, dtype=flow.float32, device=flow.device(device), requires_grad=True ) of_x_inplace = of_x + 1 id_old = id(of_x_inplace) of_x_inplace.add_(5) test_case.assertEqual(id_old, id(of_x_inplace)) np_out = np_x + 1 + 5 test_case.assertTrue(np.allclose(of_x_inplace.numpy(), np_out, 1e-05, 1e-05)) of_x_inplace = of_x_inplace.sum() of_x_inplace.backward() test_case.assertTrue(np.allclose(of_x.grad.numpy(), np.ones(shape), 1e-05, 1e-05)) of_x = flow.Tensor( np_x, dtype=flow.float32, device=flow.device(device), requires_grad=True ) of_y = flow.Tensor( np.random.randn(*shape), device=flow.device(device), requires_grad=False ) of_x_inplace = of_x + 1 id_old = id(of_x_inplace) of_x_inplace.add_(of_y) test_case.assertEqual(id_old, id(of_x_inplace)) np_out = np_x + 1 + of_y.numpy() test_case.assertTrue(np.allclose(of_x_inplace.numpy(), np_out, 1e-05, 1e-05)) of_x_inplace = of_x_inplace.sum() of_x_inplace.backward() test_case.assertTrue(np.allclose(of_x.grad.numpy(), np.ones(shape), 1e-05, 1e-05)) of_x = flow.Tensor( np_x, dtype=flow.float32, device=flow.device(device), requires_grad=True ) of_y = flow.Tensor( np.random.randn(*shape), device=flow.device(device), requires_grad=False ) of_x_inplace = of_x + 1 id_old = id(of_x_inplace) of_x_inplace += of_y test_case.assertEqual(id_old, id(of_x_inplace)) np_out = np_x + 1 + of_y.numpy() test_case.assertTrue(np.allclose(of_x_inplace.numpy(), np_out, 1e-05, 1e-05)) of_x_inplace = of_x_inplace.sum() of_x_inplace.backward() test_case.assertTrue(np.allclose(of_x.grad.numpy(), np.ones(shape), 1e-05, 1e-05)) of_x = flow.Tensor( np_x, dtype=flow.float32, device=flow.device(device), requires_grad=True ) of_y = flow.Tensor(np.array([5.0]), device=flow.device(device), requires_grad=False) of_x_inplace = of_x + 1 id_old = id(of_x_inplace) of_x_inplace.add_(of_y) test_case.assertEqual(id_old, id(of_x_inplace)) np_out = np_x + 6 test_case.assertTrue(np.allclose(of_x_inplace.numpy(), np_out, 1e-05, 1e-05)) of_x_inplace = of_x_inplace.sum() of_x_inplace.backward() test_case.assertTrue(np.allclose(of_x.grad.numpy(), np.ones(shape), 1e-05, 1e-05)) of_x = flow.Tensor( np_x, dtype=flow.float32, device=flow.device(device), requires_grad=True ) np_y = np.random.randn(*shape[:-1], 1) of_y = flow.Tensor(np_y, device=flow.device(device), requires_grad=False) of_x_inplace = of_x + 1 id_old = id(of_x_inplace) of_x_inplace.add_(of_y) test_case.assertEqual(id_old, id(of_x_inplace)) np_out = np_x + 1 + np_y test_case.assertTrue(np.allclose(of_x_inplace.numpy(), np_out, 1e-05, 1e-05)) of_x_inplace = of_x_inplace.sum() of_x_inplace.backward() test_case.assertTrue(np.allclose(of_x.grad.numpy(), np.ones(shape), 1e-05, 1e-05)) @flow.unittest.skip_unless_1n1d() class TestAddModule(flow.unittest.TestCase): def test_add(test_case): arg_dict = OrderedDict() arg_dict["test_fun"] = [ _test_add_forward, _test_add_backward, _test_inplace_add, ] arg_dict["shape"] = [(2, 3), (2, 3, 4), (2, 3, 4, 5)] arg_dict["device"] = ["cpu", "cuda"] for arg in GenArgList(arg_dict): arg[0](test_case, *arg[1:]) if __name__ == "__main__": unittest.main()

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1ddb8a6ddd3a847ffbfe1b5d9dcc96687e24154a

3,658

bzl

Python

antlir/bzl/image/feature/symlink.bzl

facebookincubator/fs_image

3515a24bb0e93176a5584bdc8839464fa28390d7

[ "MIT" ]

9

2019-12-02T20:17:35.000Z

2020-06-13T16:34:25.000Z

antlir/bzl/image/feature/symlink.bzl

facebookincubator/fs_image

3515a24bb0e93176a5584bdc8839464fa28390d7

[ "MIT" ]

19

2019-11-22T23:30:04.000Z

2020-07-16T18:05:48.000Z

antlir/bzl/image/feature/symlink.bzl

facebookincubator/fs_image

3515a24bb0e93176a5584bdc8839464fa28390d7

[ "MIT" ]

4

2019-12-04T19:03:28.000Z

2020-06-13T16:34:29.000Z

# Copyright (c) Meta Platforms, Inc. and affiliates. # # This source code is licensed under the MIT license found in the # LICENSE file in the root directory of this source tree. load("//antlir/bzl:shape.bzl", "shape") load("//antlir/bzl:target_helpers.bzl", "antlir_dep") load("//antlir/bzl:target_tagger.bzl", "new_target_tagger", "target_tagger_to_feature") load(":symlink.shape.bzl", "symlink_t") def _build_symlink_feature(link_target, link_name, symlinks_to_arg): symlink_spec = shape.new( symlink_t, dest = link_name, source = link_target, ) return target_tagger_to_feature( new_target_tagger(), items = struct(**{symlinks_to_arg: [symlink_spec]}), # The `fake_macro_library` docblock explains this self-dependency extra_deps = [antlir_dep("bzl/image/feature:symlink")], ) def feature_ensure_dir_symlink(link_target, link_name): """ The operation follows rsync convention for a destination (`link_name`): `ends/in/slash/` means "write into this directory", `does/not/end/with/slash` means "write with the specified filename": - `feature.ensure_dir_symlink("/d", "/e/")` symlinks directory `/d` to `/e/d` - `feature.ensure_dir_symlink("/a", "/b/c")` symlinks directory `/a` to `/b/c` Both arguments are mandatory: - `link_target` is the image-absolute source file/dir of the symlink. This file must exist as we do not support dangling symlinks. IMPORTANT: The emitted symlink will be **relative** by default, enabling easier inspection if images via `buck-image-out`. If this is a problem for you, we can add an `absolute` boolean kwarg. - `link_name` is an image-absolute path. A trailing / is significant. A `link_name` that does NOT end in / is a full path in the new image, ending with a filename for the new symlink. As with `image.clone`, a traling / means that `link_name` must be a pre-existing directory in the image (e.g. created via `image.ensure_dirs_exist`), and the actual link will be placed at `link_name/(basename of link_target)`. This item is indempotent: it is a no-op if a symlink already exists that matches the spec. """ return _build_symlink_feature(link_target, link_name, "symlinks_to_dirs") def feature_ensure_file_symlink(link_target, link_name): """ The operation follows rsync convention for a destination (`link_name`): `ends/in/slash/` means "write into this directory", `does/not/end/with/slash` means "write with the specified filename": - `feature.ensure_file_symlink("/d", "/e/")` symlinks file `/d` to `/e/d` - `feature.ensure_file_symlink("/a", "/b/c")` symlinks file `/a` to `/b/c` Both arguments are mandatory: - `link_target` is the image-absolute source file/dir of the symlink. This file must exist as we do not support dangling symlinks. IMPORTANT: The emitted symlink will be **relative** by default, enabling easier inspection if images via `buck-image-out`. If this is a problem for you, we can add an `absolute` boolean kwarg. - `link_name` is an image-absolute path. A trailing / is significant. A `link_name` that does NOT end in / is a full path in the new image, ending with a filename for the new symlink. As with `image.clone`, a traling / means that `link_name` must be a pre-existing directory in the image (e.g. created via `image.ensure_dirs_exist`), and the actual link will be placed at `link_name/(basename of link_target)`. This item is indempotent: it is a no-op if a symlink already exists that matches the spec. """ return _build_symlink_feature(link_target, link_name, "symlinks_to_files")

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null

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5

1df4b1273460f2b25a0da391abeadf33a24a8abc

39

py

Python

run.py

beenje/aiolegomac

4bf780749e018750c5644fea3e84f09444c43d3d

[ "BSD-2-Clause" ]

1

2017-12-29T14:24:34.000Z

run.py

beenje/aiolegomac

4bf780749e018750c5644fea3e84f09444c43d3d

[ "BSD-2-Clause" ]

5

2021-03-18T20:23:21.000Z

2022-03-11T23:16:41.000Z

run.py

beenje/aiolegomac

4bf780749e018750c5644fea3e84f09444c43d3d

[ "BSD-2-Clause" ]

null

from aiolegomac.app import run run()

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380164c29263d89e69a77897dc813b50f3c4f768

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py

Python

tools/graph_bag/scripts/test_rmse_utilities.py

limenutt/astrobee

9241e67e6692810d6e275abb3165b6d02f4ca5ef

[ "Apache-2.0" ]

629

2017-08-31T23:09:00.000Z

2022-03-30T11:55:40.000Z

tools/graph_bag/scripts/test_rmse_utilities.py

limenutt/astrobee

9241e67e6692810d6e275abb3165b6d02f4ca5ef

[ "Apache-2.0" ]

269

2018-05-05T12:31:16.000Z

2022-03-30T22:04:11.000Z

tools/graph_bag/scripts/test_rmse_utilities.py

limenutt/astrobee

9241e67e6692810d6e275abb3165b6d02f4ca5ef

[ "Apache-2.0" ]

248

2017-08-31T23:20:56.000Z

2022-03-30T22:29:16.000Z

#!/usr/bin/python # # Copyright (c) 2017, United States Government, as represented by the # Administrator of the National Aeronautics and Space Administration. # # All rights reserved. # # The Astrobee platform is licensed under the Apache License, Version 2.0 # (the "License"); you may not use this file except in compliance with the # License. You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, WITHOUT # WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the # License for the specific language governing permissions and limitations # under the License. import math import unittest import numpy as np import poses import rmse_utilities def make_poses(times, xs, ys, zs): new_poses = poses.Poses("", "") new_poses.times = times new_poses.positions.xs = xs new_poses.positions.ys = ys new_poses.positions.zs = zs return new_poses class TestRMSESequence(unittest.TestCase): def test_prune_missing_timestamps_beginning_set(self): a_times = np.arange(10.0) xs = np.arange(10.0) ys = np.arange(10.0) + 1.0 zs = np.arange(10.0) + 2.0 b_times = np.arange(5.0) poses_a = make_poses(a_times, xs, ys, zs) poses_b = make_poses(b_times, xs, ys, zs) trimmed_a, trimmed_b = rmse_utilities.get_same_timestamp_poses(poses_a, poses_b) self.assertEqual(len(trimmed_a.times), len(trimmed_b.times)) self.assertEqual(len(trimmed_a.times), 5) self.assertTrue(np.allclose(trimmed_a.times, b_times, rtol=0)) self.assertTrue(np.allclose(trimmed_a.positions.xs, b_times, rtol=0)) self.assertTrue(np.allclose(trimmed_a.positions.ys, b_times + 1, rtol=0)) self.assertTrue(np.allclose(trimmed_a.positions.zs, b_times + 2, rtol=0)) def test_prune_missing_timestamps_middle_set(self): a_times = np.arange(10.0) xs = np.arange(10.0) ys = np.arange(10.0) + 1.0 zs = np.arange(10.0) + 2.0 b_times = np.arange(3.0, 7.0) poses_a = make_poses(a_times, xs, ys, zs) poses_b = make_poses(b_times, xs, ys, zs) trimmed_a, trimmed_b = rmse_utilities.get_same_timestamp_poses(poses_a, poses_b) self.assertEqual(len(trimmed_a.times), len(trimmed_b.times)) self.assertEqual(len(trimmed_a.times), 4) self.assertTrue(np.allclose(trimmed_a.times, b_times, rtol=0)) self.assertTrue(np.allclose(trimmed_a.positions.xs, b_times, rtol=0)) self.assertTrue(np.allclose(trimmed_a.positions.ys, b_times + 1, rtol=0)) self.assertTrue(np.allclose(trimmed_a.positions.zs, b_times + 2, rtol=0)) def test_prune_missing_timestamps_end_set(self): a_times = np.arange(10.0) xs = np.arange(10.0) ys = np.arange(10.0) + 1.0 zs = np.arange(10.0) + 2.0 b_times = np.arange(7.0, 10.0) poses_a = make_poses(a_times, xs, ys, zs) poses_b = make_poses(b_times, xs, ys, zs) trimmed_a, trimmed_b = rmse_utilities.get_same_timestamp_poses(poses_a, poses_b) self.assertEqual(len(trimmed_a.times), len(trimmed_b.times)) self.assertEqual(len(trimmed_a.times), 3) self.assertTrue(np.allclose(trimmed_a.times, b_times, rtol=0)) self.assertTrue(np.allclose(trimmed_a.positions.xs, b_times, rtol=0)) self.assertTrue(np.allclose(trimmed_a.positions.ys, b_times + 1, rtol=0)) self.assertTrue(np.allclose(trimmed_a.positions.zs, b_times + 2, rtol=0)) def test_prune_missing_timestamps_scattered_set(self): a_times = np.arange(10.0) xs = np.arange(10.0) ys = np.arange(10.0) + 1.0 zs = np.arange(10.0) + 2.0 b_times = np.array([1.0, 5.0, 6.0, 9.0]) poses_a = make_poses(a_times, xs, ys, zs) poses_b = make_poses(b_times, xs, ys, zs) trimmed_a, trimmed_b = rmse_utilities.get_same_timestamp_poses(poses_a, poses_b) self.assertEqual(len(trimmed_a.times), len(trimmed_b.times)) self.assertTrue(np.allclose(trimmed_a.times, b_times, rtol=0)) self.assertTrue(np.allclose(trimmed_a.positions.xs, b_times, rtol=0)) self.assertTrue(np.allclose(trimmed_a.positions.ys, b_times + 1, rtol=0)) self.assertTrue(np.allclose(trimmed_a.positions.zs, b_times + 2, rtol=0)) def test_prune_missing_timestamps_disjoint_set(self): a_times = np.arange(10.0) xs = np.arange(10.0) ys = np.arange(10.0) + 1.0 zs = np.arange(10.0) + 2.0 b_times = np.arange(11, 20) poses_a = make_poses(a_times, xs, ys, zs) poses_b = make_poses(b_times, xs, ys, zs) trimmed_a, trimmed_b = rmse_utilities.get_same_timestamp_poses(poses_a, poses_b) self.assertEqual(len(trimmed_a.times), 0) self.assertEqual(len(trimmed_b.times), 0) def test_prune_missing_timestamps_some_overlap(self): a_times = np.arange(10.0) xs = np.arange(10.0) ys = np.arange(10.0) + 1.0 zs = np.arange(10.0) + 2.0 b_times = np.arange(8.0, 20.0) poses_a = make_poses(a_times, xs, ys, zs) poses_b = make_poses(b_times, xs, ys, zs) expected_time_range = np.arange(8.0, 10.0) trimmed_a, trimmed_b = rmse_utilities.get_same_timestamp_poses(poses_a, poses_b) self.assertEqual(len(trimmed_a.times), len(trimmed_b.times)) self.assertTrue(np.allclose(trimmed_a.times, trimmed_b.times, rtol=0)) self.assertTrue(np.allclose(trimmed_a.times, expected_time_range, rtol=0)) self.assertTrue( np.allclose(trimmed_a.positions.xs, expected_time_range, rtol=0) ) self.assertTrue( np.allclose(trimmed_a.positions.ys, expected_time_range + 1, rtol=0) ) self.assertTrue( np.allclose(trimmed_a.positions.zs, expected_time_range + 2, rtol=0) ) def test_rmse_same_poses(self): a_times = np.arange(10.0) xs = np.arange(10.0) ys = np.arange(10.0) + 1.0 zs = np.arange(10.0) + 2.0 poses_a = make_poses(a_times, xs, ys, zs) poses_b = make_poses(a_times, xs, ys, zs) rmse = rmse_utilities.rmse_timestamped_poses(poses_a, poses_b) self.assertTrue(np.isclose(rmse, 0, rtol=0)) def test_rmse_off_by_one(self): a_times = np.arange(10.0) xs = np.arange(10.0) ys = np.arange(10.0) + 1.0 zs = np.arange(10.0) + 2.0 poses_a = make_poses(a_times, xs, ys, zs) poses_b = make_poses(a_times, xs + 1, ys, zs) rmse = rmse_utilities.rmse_timestamped_poses(poses_a, poses_b) self.assertTrue(np.isclose(rmse, 1.0, rtol=0)) def test_rmse_all_off_by_one(self): a_times = np.arange(10.0) xs = np.arange(10.0) ys = np.arange(10.0) + 1.0 zs = np.arange(10.0) + 2.0 poses_a = make_poses(a_times, xs, ys, zs) poses_b = make_poses(a_times, xs + 1, ys + 1, zs + 1) rmse = rmse_utilities.rmse_timestamped_poses(poses_a, poses_b) self.assertTrue(np.isclose(rmse, math.sqrt(3.0), rtol=0)) if __name__ == "__main__": unittest.main()

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381ff9151357b8a545a0467f150806d9d897afa1

161

py

Python

handlers/__init__.py

dragondjf/cqssl

86d4d69654c79650646d7672d580abf9dccf6c98

[ "Apache-2.0" ]

null

handlers/__init__.py

dragondjf/cqssl

86d4d69654c79650646d7672d580abf9dccf6c98

[ "Apache-2.0" ]

null

handlers/__init__.py

dragondjf/cqssl

86d4d69654c79650646d7672d580abf9dccf6c98

[ "Apache-2.0" ]

null

#!/usr/bin/env python # -*- coding: utf-8 -*- from .task import task from .mainhandler import MainHandler from .websockerhandler import WebSocketManagerHandler

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383fecd42d9412dba0da8104dc4c13bda2a0f420

121

py

Python

mastermind_django_files/front_end/admin.py

chodges7/mastermind-capstone

39bce35c1a4abf4b5bbde8927713b25451463c85

[ "MIT" ]

null

mastermind_django_files/front_end/admin.py

chodges7/mastermind-capstone

39bce35c1a4abf4b5bbde8927713b25451463c85

[ "MIT" ]

null

mastermind_django_files/front_end/admin.py

chodges7/mastermind-capstone

39bce35c1a4abf4b5bbde8927713b25451463c85

[ "MIT" ]

null

from django.contrib import admin from .models import Games, Stats admin.site.register(Games) admin.site.register(Stats)

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Python

tests/integration/workflows/nodejs_npm_esbuild/test_nodejs_npm_with_esbuild.py

awslabs/aws-lambda-builders

b317c5da6a981f83adee4631c5710cea14e60beb

[ "Apache-2.0" ]

180

2018-11-09T04:51:19.000Z

2020-08-06T21:43:20.000Z

tests/integration/workflows/nodejs_npm_esbuild/test_nodejs_npm_with_esbuild.py

awslabs/aws-lambda-builders

b317c5da6a981f83adee4631c5710cea14e60beb

[ "Apache-2.0" ]

108

2018-11-08T18:34:51.000Z

2020-08-12T17:59:41.000Z

tests/integration/workflows/nodejs_npm_esbuild/test_nodejs_npm_with_esbuild.py

awslabs/aws-lambda-builders

b317c5da6a981f83adee4631c5710cea14e60beb

[ "Apache-2.0" ]

91

2018-11-08T22:58:00.000Z

2020-08-17T21:15:31.000Z

import os import shutil import tempfile from unittest import TestCase from aws_lambda_builders.builder import LambdaBuilder from aws_lambda_builders.exceptions import WorkflowFailedError from aws_lambda_builders.workflows.nodejs_npm.npm import SubprocessNpm from aws_lambda_builders.workflows.nodejs_npm.utils import OSUtils from aws_lambda_builders.workflows.nodejs_npm_esbuild.esbuild import EsbuildExecutionError from aws_lambda_builders.workflows.nodejs_npm_esbuild.utils import EXPERIMENTAL_FLAG_ESBUILD from parameterized import parameterized class TestNodejsNpmWorkflowWithEsbuild(TestCase): """ Verifies that `nodejs_npm` workflow works by building a Lambda using NPM """ TEST_DATA_FOLDER = os.path.join(os.path.dirname(__file__), "testdata") def setUp(self): self.artifacts_dir = tempfile.mkdtemp() self.scratch_dir = tempfile.mkdtemp() self.dependencies_dir = tempfile.mkdtemp() self.no_deps = os.path.join(self.TEST_DATA_FOLDER, "no-deps-esbuild") self.builder = LambdaBuilder(language="nodejs", dependency_manager="npm-esbuild", application_framework=None) def tearDown(self): shutil.rmtree(self.artifacts_dir) shutil.rmtree(self.scratch_dir) @parameterized.expand([("nodejs12.x",), ("nodejs14.x",), ("nodejs16.x",)]) def test_doesnt_build_without_feature_flag(self, runtime): source_dir = os.path.join(self.TEST_DATA_FOLDER, "with-deps-esbuild") with self.assertRaises(EsbuildExecutionError) as context: self.builder.build( source_dir, self.artifacts_dir, self.scratch_dir, os.path.join(source_dir, "package.json"), runtime=runtime, ) self.assertEqual(str(context.exception), "Esbuild Failed: Feature flag must be enabled to use this workflow") @parameterized.expand([("nodejs12.x",), ("nodejs14.x",), ("nodejs16.x",)]) def test_builds_javascript_project_with_dependencies(self, runtime): source_dir = os.path.join(self.TEST_DATA_FOLDER, "with-deps-esbuild") options = {"entry_points": ["included.js"]} self.builder.build( source_dir, self.artifacts_dir, self.scratch_dir, os.path.join(source_dir, "package.json"), runtime=runtime, options=options, experimental_flags=[EXPERIMENTAL_FLAG_ESBUILD], ) expected_files = {"included.js", "included.js.map"} output_files = set(os.listdir(self.artifacts_dir)) self.assertEqual(expected_files, output_files) @parameterized.expand([("nodejs12.x",), ("nodejs14.x",), ("nodejs16.x",)]) def test_builds_javascript_project_with_multiple_entrypoints(self, runtime): source_dir = os.path.join(self.TEST_DATA_FOLDER, "with-deps-esbuild-multiple-entrypoints") options = {"entry_points": ["included.js", "included2.js"]} self.builder.build( source_dir, self.artifacts_dir, self.scratch_dir, os.path.join(source_dir, "package.json"), runtime=runtime, options=options, experimental_flags=[EXPERIMENTAL_FLAG_ESBUILD], ) expected_files = {"included.js", "included.js.map", "included2.js", "included2.js.map"} output_files = set(os.listdir(self.artifacts_dir)) self.assertEqual(expected_files, output_files) @parameterized.expand([("nodejs12.x",), ("nodejs14.x",), ("nodejs16.x",)]) def test_builds_typescript_projects(self, runtime): source_dir = os.path.join(self.TEST_DATA_FOLDER, "with-deps-esbuild-typescript") options = {"entry_points": ["included.ts"]} self.builder.build( source_dir, self.artifacts_dir, self.scratch_dir, os.path.join(source_dir, "package.json"), runtime=runtime, options=options, experimental_flags=[EXPERIMENTAL_FLAG_ESBUILD], ) expected_files = {"included.js", "included.js.map"} output_files = set(os.listdir(self.artifacts_dir)) self.assertEqual(expected_files, output_files) @parameterized.expand([("nodejs12.x",), ("nodejs14.x",), ("nodejs16.x",)]) def test_builds_with_external_esbuild(self, runtime): osutils = OSUtils() npm = SubprocessNpm(osutils) source_dir = os.path.join(self.TEST_DATA_FOLDER, "no-deps-esbuild") esbuild_dir = os.path.join(self.TEST_DATA_FOLDER, "esbuild-binary") npm.run(["ci"], cwd=esbuild_dir) binpath = npm.run(["bin"], cwd=esbuild_dir) options = {"entry_points": ["included.js"]} self.builder.build( source_dir, self.artifacts_dir, self.scratch_dir, os.path.join(source_dir, "package.json"), runtime=runtime, options=options, executable_search_paths=[binpath], experimental_flags=[EXPERIMENTAL_FLAG_ESBUILD], ) expected_files = {"included.js", "included.js.map"} output_files = set(os.listdir(self.artifacts_dir)) self.assertEqual(expected_files, output_files) @parameterized.expand([("nodejs12.x",), ("nodejs14.x",), ("nodejs16.x",)]) def test_no_options_passed_to_esbuild(self, runtime): source_dir = os.path.join(self.TEST_DATA_FOLDER, "with-deps-esbuild") with self.assertRaises(WorkflowFailedError) as context: self.builder.build( source_dir, self.artifacts_dir, self.scratch_dir, os.path.join(source_dir, "package.json"), runtime=runtime, experimental_flags=[EXPERIMENTAL_FLAG_ESBUILD], ) self.assertEqual(str(context.exception), "NodejsNpmEsbuildBuilder:EsbuildBundle - entry_points not set ({})") @parameterized.expand([("nodejs12.x",), ("nodejs14.x",), ("nodejs16.x",)]) def test_bundle_with_implicit_file_types(self, runtime): source_dir = os.path.join(self.TEST_DATA_FOLDER, "implicit-file-types") options = {"entry_points": ["included", "implicit"]} self.builder.build( source_dir, self.artifacts_dir, self.scratch_dir, os.path.join(source_dir, "package.json"), runtime=runtime, options=options, experimental_flags=[EXPERIMENTAL_FLAG_ESBUILD], ) expected_files = {"included.js.map", "implicit.js.map", "implicit.js", "included.js"} output_files = set(os.listdir(self.artifacts_dir)) self.assertEqual(expected_files, output_files) @parameterized.expand([("nodejs12.x",), ("nodejs14.x",), ("nodejs16.x",)]) def test_bundles_project_without_dependencies(self, runtime): source_dir = os.path.join(self.TEST_DATA_FOLDER, "no-package-esbuild") options = {"entry_points": ["included"]} osutils = OSUtils() npm = SubprocessNpm(osutils) esbuild_dir = os.path.join(self.TEST_DATA_FOLDER, "esbuild-binary") npm.run(["ci"], cwd=esbuild_dir) binpath = npm.run(["bin"], cwd=esbuild_dir) self.builder.build( source_dir, self.artifacts_dir, self.scratch_dir, os.path.join(source_dir, "package.json"), runtime=runtime, options=options, experimental_flags=[EXPERIMENTAL_FLAG_ESBUILD], executable_search_paths=[binpath], ) expected_files = {"included.js.map", "included.js"} output_files = set(os.listdir(self.artifacts_dir)) self.assertEqual(expected_files, output_files) @parameterized.expand([("nodejs12.x",), ("nodejs14.x",), ("nodejs16.x",)]) def test_builds_project_with_remote_dependencies_without_download_dependencies_with_dependencies_dir(self, runtime): source_dir = os.path.join(self.TEST_DATA_FOLDER, "with-deps-no-node_modules") options = {"entry_points": ["included.js"]} osutils = OSUtils() npm = SubprocessNpm(osutils) esbuild_dir = os.path.join(self.TEST_DATA_FOLDER, "esbuild-binary") npm.run(["ci"], cwd=esbuild_dir) binpath = npm.run(["bin"], cwd=esbuild_dir) self.builder.build( source_dir, self.artifacts_dir, self.scratch_dir, os.path.join(source_dir, "package.json"), options=options, runtime=runtime, dependencies_dir=self.dependencies_dir, download_dependencies=False, experimental_flags=[EXPERIMENTAL_FLAG_ESBUILD], executable_search_paths=[binpath], ) expected_files = {"included.js.map", "included.js"} output_files = set(os.listdir(self.artifacts_dir)) self.assertEqual(expected_files, output_files) @parameterized.expand([("nodejs12.x",), ("nodejs14.x",), ("nodejs16.x",)]) def test_builds_project_with_remote_dependencies_with_download_dependencies_and_dependencies_dir(self, runtime): source_dir = os.path.join(self.TEST_DATA_FOLDER, "with-deps-no-node_modules") options = {"entry_points": ["included.js"]} self.builder.build( source_dir, self.artifacts_dir, self.scratch_dir, os.path.join(source_dir, "package.json"), runtime=runtime, options=options, dependencies_dir=self.dependencies_dir, download_dependencies=True, experimental_flags=[EXPERIMENTAL_FLAG_ESBUILD], ) expected_files = {"included.js.map", "included.js"} output_files = set(os.listdir(self.artifacts_dir)) self.assertEqual(expected_files, output_files) expected_modules = "minimal-request-promise" output_modules = set(os.listdir(os.path.join(self.dependencies_dir, "node_modules"))) self.assertIn(expected_modules, output_modules) expected_dependencies_files = {"node_modules"} output_dependencies_files = set(os.listdir(os.path.join(self.dependencies_dir))) self.assertNotIn(expected_dependencies_files, output_dependencies_files) @parameterized.expand([("nodejs12.x",), ("nodejs14.x",), ("nodejs16.x",)]) def test_builds_project_with_remote_dependencies_without_download_dependencies_without_dependencies_dir( self, runtime ): source_dir = os.path.join(self.TEST_DATA_FOLDER, "with-deps-no-node_modules") with self.assertRaises(EsbuildExecutionError) as context: self.builder.build( source_dir, self.artifacts_dir, self.scratch_dir, os.path.join(source_dir, "package.json"), runtime=runtime, dependencies_dir=None, download_dependencies=False, experimental_flags=[EXPERIMENTAL_FLAG_ESBUILD], ) self.assertEqual(str(context.exception), "Esbuild Failed: Lambda Builders encountered and invalid workflow") @parameterized.expand([("nodejs12.x",), ("nodejs14.x",), ("nodejs16.x",)]) def test_builds_project_without_combine_dependencies(self, runtime): source_dir = os.path.join(self.TEST_DATA_FOLDER, "with-deps-no-node_modules") options = {"entry_points": ["included.js"]} self.builder.build( source_dir, self.artifacts_dir, self.scratch_dir, os.path.join(source_dir, "package.json"), runtime=runtime, options=options, dependencies_dir=self.dependencies_dir, download_dependencies=True, combine_dependencies=False, experimental_flags=[EXPERIMENTAL_FLAG_ESBUILD], ) expected_files = {"included.js.map", "included.js"} output_files = set(os.listdir(self.artifacts_dir)) self.assertEqual(expected_files, output_files) expected_modules = "minimal-request-promise" output_modules = set(os.listdir(os.path.join(self.dependencies_dir, "node_modules"))) self.assertIn(expected_modules, output_modules) expected_dependencies_files = {"node_modules"} output_dependencies_files = set(os.listdir(os.path.join(self.dependencies_dir))) self.assertNotIn(expected_dependencies_files, output_dependencies_files) @parameterized.expand([("nodejs12.x",), ("nodejs14.x",), ("nodejs16.x",)]) def test_builds_javascript_project_with_external(self, runtime): source_dir = os.path.join(self.TEST_DATA_FOLDER, "with-deps-esbuild-externals") options = {"entry_points": ["included.js"], "external": ["minimal-request-promise"]} self.builder.build( source_dir, self.artifacts_dir, self.scratch_dir, os.path.join(source_dir, "package.json"), runtime=runtime, options=options, experimental_flags=[EXPERIMENTAL_FLAG_ESBUILD], ) expected_files = {"included.js", "included.js.map"} output_files = set(os.listdir(self.artifacts_dir)) self.assertEqual(expected_files, output_files) with open(str(os.path.join(self.artifacts_dir, "included.js"))) as f: js_file = f.read() # Check that the module has been require() instead of bundled self.assertIn('require("minimal-request-promise")', js_file) @parameterized.expand([("nodejs12.x",), ("nodejs14.x",), ("nodejs16.x",)]) def test_builds_javascript_project_with_loader(self, runtime): osutils = OSUtils() source_dir = os.path.join(self.TEST_DATA_FOLDER, "no-deps-esbuild-loader") options = {"entry_points": ["included.js"], "loader": [".reference=json"]} self.builder.build( source_dir, self.artifacts_dir, self.scratch_dir, os.path.join(source_dir, "package.json"), runtime=runtime, options=options, experimental_flags=[EXPERIMENTAL_FLAG_ESBUILD], ) expected_files = {"included.js", "included.js.map"} output_files = set(os.listdir(self.artifacts_dir)) self.assertEqual(expected_files, output_files) included_js_path = os.path.join(self.artifacts_dir, "included.js") # check that the .reference file is correctly bundled as code by running the result self.assertEqual( osutils.check_output(included_js_path), str.encode( "===\n" "The Muses\n" "===\n" "\n" "\tcalliope: eloquence and heroic poetry\n" "\terato: lyric or erotic poetry\n" "\tmelpomene: tragedy\n" "\tpolymnia: sacred poetry\n" "\tterpsichore: dance\n" "\tthalia: comedy\n" "\turania: astronomy and astrology" ), )

40.848238

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1,654

15,073

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0.04361

0.798074

0.782166

0.761714

0.738556

0

0.00759

0.239567

15,073

368

121

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0

0.097315

0

null

0

1

0

null

0

5

3849630253ce2c38d780907a24dc85a17d990961

114

py

Python

plugins/trivia/questions.py

wuhoodude/Bappybot

c7f0bf42678758d2d042b48f843c8c341b737e70

[ "MIT" ]

7

2015-06-08T17:57:16.000Z

2017-12-14T09:09:01.000Z

plugins/trivia/questions.py

wuhoodude/Bappybot

c7f0bf42678758d2d042b48f843c8c341b737e70

[ "MIT" ]

8

2015-06-08T19:51:50.000Z

2021-12-13T19:46:10.000Z

plugins/trivia/questions.py

wuhoodude/Bappybot

c7f0bf42678758d2d042b48f843c8c341b737e70

[ "MIT" ]

21

2015-06-08T17:06:42.000Z

2020-07-23T07:21:12.000Z

class QuestionGenerator: def makeQuestion(self): return {'a':'42','q':'What is the meaning of life?'}

28.5

60

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1

0

5

6972d734b43870c7374651044827d478299981f4

83

py

Python

test/Inputs/getmtime.py

xjc90s/swift

cafe5ccbd1b7aa9cc9c837c5be2cdf3d5acd8a49

[ "Apache-2.0" ]

1

2022-03-27T15:28:07.000Z

test/Inputs/getmtime.py

xjc90s/swift

cafe5ccbd1b7aa9cc9c837c5be2cdf3d5acd8a49

[ "Apache-2.0" ]

null

test/Inputs/getmtime.py

xjc90s/swift

cafe5ccbd1b7aa9cc9c837c5be2cdf3d5acd8a49

[ "Apache-2.0" ]

null

#!/usr/bin/env python3 import os import sys print(os.path.getmtime(sys.argv[1]))

11.857143

36

0.722892

15

83

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0.8

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null

0

1

0

1

0

1

0

5

697ee74dc4e53951274bc0c01e25d38b373fccbe

102

py

Python

run.py

Divisibility/l5r-game-master-tool

8eb746163256931cdbaff1fde5c66f399906835b

[ "MIT" ]

2

2018-09-04T18:32:27.000Z

2018-12-04T14:11:51.000Z

run.py

Divisibility/l5r-game-master-tool

8eb746163256931cdbaff1fde5c66f399906835b

[ "MIT" ]

null

run.py

Divisibility/l5r-game-master-tool

8eb746163256931cdbaff1fde5c66f399906835b

[ "MIT" ]

null

#!/usr/bin/env python from gmt import app app.run(debug=app.config['DEBUG'], port=app.config['PORT'])

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102

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102

3

60

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null

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5

6992c115a9faa2fb70414a73636ce6b97a3a5b33

21

py

Python

olive/scripts/calibration/__init__.py

liuyenting/olive-core

b532b29e29fe9f167369f66b8d922f5f644f9309

[ "Apache-2.0" ]

null

olive/scripts/calibration/__init__.py

liuyenting/olive-core

b532b29e29fe9f167369f66b8d922f5f644f9309

[ "Apache-2.0" ]

null

olive/scripts/calibration/__init__.py

liuyenting/olive-core

b532b29e29fe9f167369f66b8d922f5f644f9309

[ "Apache-2.0" ]

null

from .aotf import *

10.5

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5

69a238f8632b12f2eaad7859e1eeb823b11b56c5

128

py

Python

ggcg/gen/__init__.py

FreNeS1/ggcg

814aa152d911d62da9771381fc4e74e4ca8ba762

[ "MIT" ]

1

2020-07-09T12:43:09.000Z

ggcg/gen/__init__.py

FreNeS1/ggcg

814aa152d911d62da9771381fc4e74e4ca8ba762

[ "MIT" ]

4

2020-11-13T18:55:07.000Z

2022-02-10T01:49:56.000Z

ggcg/gen/__init__.py

FreNeS1/ggcg

814aa152d911d62da9771381fc4e74e4ca8ba762

[ "MIT" ]

null

"""Generator package. Contains the logic to simplify, modify and regenerate new computational graphs based on existing ones."""

42.666667

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119

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0

1

0

null

0

1

0

5

69a506ea3ed9f1e8132122e3a5a8d3e9bed70e45

112

py

Python

order/admin.py

YatharthVats/Dishes-API

0dd40a3d2c8d14cc01260b8f5348c839f46dff7a

[ "MIT" ]

null

order/admin.py

YatharthVats/Dishes-API

0dd40a3d2c8d14cc01260b8f5348c839f46dff7a

[ "MIT" ]

null

order/admin.py

YatharthVats/Dishes-API

0dd40a3d2c8d14cc01260b8f5348c839f46dff7a

[ "MIT" ]

null

from django.contrib import admin from .models import Dish # Register your models here. admin.site.register(Dish)

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1

0

1

0

1

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5

69a969504b2937315d39e7a3d48eace064c99059

8,123

py

Python

networks.py

Blupblupblup/Deep-MSVDD-PyTorch

2a97b44b13925e57b166b3353cfaf1e262bc0b60

[ "MIT" ]

null

networks.py

Blupblupblup/Deep-MSVDD-PyTorch

2a97b44b13925e57b166b3353cfaf1e262bc0b60

[ "MIT" ]

null

networks.py

Blupblupblup/Deep-MSVDD-PyTorch

2a97b44b13925e57b166b3353cfaf1e262bc0b60

[ "MIT" ]

null

import torch import torch.nn as nn import torch.nn.functional as F """ architectures from: - https://github.com/lukasruff/Deep-SAD-PyTorch/blob/master/src/networks/mnist_LeNet.py - https://github.com/lukasruff/Deep-SAD-PyTorch/blob/master/src/networks/fmnist_LeNet.py - https://github.com/lukasruff/Deep-SAD-PyTorch/blob/master/src/networks/cifar10_LeNet.py one should note that F.leaky_relu() uses leakiness alpha = 0.01 and not 0.1 as indicated in the paper http://proceedings.mlr.press/v80/ruff18a/ruff18a.pdf """ ############# ### MNIST ### ############# class MNIST_LeNet(nn.Module): def __init__(self, rep_dim=32): super().__init__() self.rep_dim = rep_dim self.pool = nn.MaxPool2d(2, 2) self.conv1 = nn.Conv2d(1, 8, 5, bias=False, padding=2) self.bn1 = nn.BatchNorm2d(8, eps=1e-04, affine=False) self.conv2 = nn.Conv2d(8, 4, 5, bias=False, padding=2) self.bn2 = nn.BatchNorm2d(4, eps=1e-04, affine=False) self.fc1 = nn.Linear(4 * 7 * 7, self.rep_dim, bias=False) def forward(self, x): x = x.view(-1, 1, 28, 28) x = self.conv1(x) x = self.pool(F.leaky_relu(self.bn1(x))) x = self.conv2(x) x = self.pool(F.leaky_relu(self.bn2(x))) x = x.view(int(x.size(0)), -1) x = self.fc1(x) return x class MNIST_LeNet_Decoder(nn.Module): def __init__(self, rep_dim=32): super().__init__() self.rep_dim = rep_dim # Decoder network self.deconv1 = nn.ConvTranspose2d(2, 4, 5, bias=False, padding=2) self.bn3 = nn.BatchNorm2d(4, eps=1e-04, affine=False) self.deconv2 = nn.ConvTranspose2d(4, 8, 5, bias=False, padding=3) self.bn4 = nn.BatchNorm2d(8, eps=1e-04, affine=False) self.deconv3 = nn.ConvTranspose2d(8, 1, 5, bias=False, padding=2) def forward(self, x): x = x.view(int(x.size(0)), int(self.rep_dim / 16), 4, 4) x = F.interpolate(F.leaky_relu(x), scale_factor=2) x = self.deconv1(x) x = F.interpolate(F.leaky_relu(self.bn3(x)), scale_factor=2) x = self.deconv2(x) x = F.interpolate(F.leaky_relu(self.bn4(x)), scale_factor=2) x = self.deconv3(x) x = torch.sigmoid(x) return x.squeeze() class MNIST_LeNet_Autoencoder(nn.Module): def __init__(self, rep_dim=32): super().__init__() self.rep_dim = rep_dim self.encoder = MNIST_LeNet(rep_dim=rep_dim) self.decoder = MNIST_LeNet_Decoder(rep_dim=rep_dim) def forward(self, x): x = self.encoder(x) x = self.decoder(x) return x #################### ### FashionMNIST ### #################### class FashionMNIST_LeNet(nn.Module): def __init__(self, rep_dim=64): super().__init__() self.rep_dim = rep_dim self.pool = nn.MaxPool2d(2, 2) self.conv1 = nn.Conv2d(1, 16, 5, bias=False, padding=2) self.bn2d1 = nn.BatchNorm2d(16, eps=1e-04, affine=False) self.conv2 = nn.Conv2d(16, 32, 5, bias=False, padding=2) self.bn2d2 = nn.BatchNorm2d(32, eps=1e-04, affine=False) self.fc1 = nn.Linear(32 * 7 * 7, 128, bias=False) self.bn1d1 = nn.BatchNorm1d(128, eps=1e-04, affine=False) self.fc2 = nn.Linear(128, self.rep_dim, bias=False) def forward(self, x): x = x.view(-1, 1, 28, 28) x = self.conv1(x) x = self.pool(F.leaky_relu(self.bn2d1(x))) x = self.conv2(x) x = self.pool(F.leaky_relu(self.bn2d2(x))) x = x.view(int(x.size(0)), -1) x = F.leaky_relu(self.bn1d1(self.fc1(x))) x = self.fc2(x) return x class FashionMNIST_LeNet_Decoder(nn.Module): def __init__(self, rep_dim=64): super().__init__() self.rep_dim = rep_dim self.fc3 = nn.Linear(self.rep_dim, 128, bias=False) self.bn1d2 = nn.BatchNorm1d(128, eps=1e-04, affine=False) self.deconv1 = nn.ConvTranspose2d(8, 32, 5, bias=False, padding=2) self.bn2d3 = nn.BatchNorm2d(32, eps=1e-04, affine=False) self.deconv2 = nn.ConvTranspose2d(32, 16, 5, bias=False, padding=3) self.bn2d4 = nn.BatchNorm2d(16, eps=1e-04, affine=False) self.deconv3 = nn.ConvTranspose2d(16, 1, 5, bias=False, padding=2) def forward(self, x): x = self.bn1d2(self.fc3(x)) x = x.view(int(x.size(0)), int(128 / 16), 4, 4) x = F.interpolate(F.leaky_relu(x), scale_factor=2) x = self.deconv1(x) x = F.interpolate(F.leaky_relu(self.bn2d3(x)), scale_factor=2) x = self.deconv2(x) x = F.interpolate(F.leaky_relu(self.bn2d4(x)), scale_factor=2) x = self.deconv3(x) x = torch.sigmoid(x) return x.squeeze() class FashionMNIST_LeNet_Autoencoder(nn.Module): def __init__(self, rep_dim=64): super().__init__() self.rep_dim = rep_dim self.encoder = FashionMNIST_LeNet(rep_dim=rep_dim) self.decoder = FashionMNIST_LeNet_Decoder(rep_dim=rep_dim) def forward(self, x): x = self.encoder(x) x = self.decoder(x) return x ############### ### CIFAR10 ### ############### class CIFAR10_LeNet(nn.Module): def __init__(self, rep_dim=128): super().__init__() self.rep_dim = rep_dim self.pool = nn.MaxPool2d(2, 2) self.conv1 = nn.Conv2d(3, 32, 5, bias=False, padding=2) self.bn2d1 = nn.BatchNorm2d(32, eps=1e-04, affine=False) self.conv2 = nn.Conv2d(32, 64, 5, bias=False, padding=2) self.bn2d2 = nn.BatchNorm2d(64, eps=1e-04, affine=False) self.conv3 = nn.Conv2d(64, 128, 5, bias=False, padding=2) self.bn2d3 = nn.BatchNorm2d(128, eps=1e-04, affine=False) self.fc1 = nn.Linear(128 * 4 * 4, self.rep_dim, bias=False) def forward(self, x): # x = x.view(-1, 3, 32, 32) x = torch.transpose(x,1,3) x = self.conv1(x) x = self.pool(F.leaky_relu(self.bn2d1(x))) x = self.conv2(x) x = self.pool(F.leaky_relu(self.bn2d2(x))) x = self.conv3(x) x = self.pool(F.leaky_relu(self.bn2d3(x))) x = x.view(int(x.size(0)), -1) x = self.fc1(x) return x class CIFAR10_LeNet_Decoder(nn.Module): def __init__(self, rep_dim=128): super().__init__() self.rep_dim = rep_dim self.deconv1 = nn.ConvTranspose2d(int(self.rep_dim / (4 * 4)), 128, 5, bias=False, padding=2) nn.init.xavier_uniform_(self.deconv1.weight, gain=nn.init.calculate_gain('leaky_relu')) self.bn2d4 = nn.BatchNorm2d(128, eps=1e-04, affine=False) self.deconv2 = nn.ConvTranspose2d(128, 64, 5, bias=False, padding=2) nn.init.xavier_uniform_(self.deconv2.weight, gain=nn.init.calculate_gain('leaky_relu')) self.bn2d5 = nn.BatchNorm2d(64, eps=1e-04, affine=False) self.deconv3 = nn.ConvTranspose2d(64, 32, 5, bias=False, padding=2) nn.init.xavier_uniform_(self.deconv3.weight, gain=nn.init.calculate_gain('leaky_relu')) self.bn2d6 = nn.BatchNorm2d(32, eps=1e-04, affine=False) self.deconv4 = nn.ConvTranspose2d(32, 3, 5, bias=False, padding=2) nn.init.xavier_uniform_(self.deconv4.weight, gain=nn.init.calculate_gain('leaky_relu')) def forward(self, x): x = x.view(int(x.size(0)), int(self.rep_dim / (4 * 4)), 4, 4) x = F.leaky_relu(x) x = self.deconv1(x) x = F.interpolate(F.leaky_relu(self.bn2d4(x)), scale_factor=2) x = self.deconv2(x) x = F.interpolate(F.leaky_relu(self.bn2d5(x)), scale_factor=2) x = self.deconv3(x) x = F.interpolate(F.leaky_relu(self.bn2d6(x)), scale_factor=2) x = self.deconv4(x) x = torch.sigmoid(x) return torch.transpose(x,1,3) class CIFAR10_LeNet_Autoencoder(nn.Module): def __init__(self, rep_dim=128): super().__init__() self.rep_dim = rep_dim self.encoder = CIFAR10_LeNet(rep_dim=rep_dim) self.decoder = CIFAR10_LeNet_Decoder(rep_dim=rep_dim) def forward(self, x): x = self.encoder(x) x = self.decoder(x) return x

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1,245

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3.801606

0.101205

0.020283

0.052821

0.053243

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0

null

0

1

0

null

0

5

69ee385c0f3fa68eed3f5076ffc48b0e49e7da0a

130

py

Python

norns/enemy/admin.py

the-norns/norns

8856626fb6937452c123e4629a5888a49a82c349

[ "MIT" ]

null

norns/enemy/admin.py

the-norns/norns

8856626fb6937452c123e4629a5888a49a82c349

[ "MIT" ]

62

2018-05-19T22:18:01.000Z

2018-05-26T00:13:21.000Z

norns/enemy/admin.py

the-norns/norns

8856626fb6937452c123e4629a5888a49a82c349

[ "MIT" ]

3

2018-05-19T18:54:28.000Z

2018-05-21T02:14:47.000Z

from django.contrib import admin from .models import Enemy, EnemyType admin.site.register(Enemy) admin.site.register(EnemyType)

18.571429

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0.815385

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130

5.888889

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0.320755

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0.1

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null

0

1

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1

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5

386272c0d0660b67c49d9b5845133dcbc214c0e7

84

py

Python

tests/test_sample.py

whs2k/tweetCarousel

fd9bf32388573c373491d7259d8a7c4452af0c9a

[ "MIT" ]

null

tests/test_sample.py

whs2k/tweetCarousel

fd9bf32388573c373491d7259d8a7c4452af0c9a

[ "MIT" ]

null

tests/test_sample.py

whs2k/tweetCarousel

fd9bf32388573c373491d7259d8a7c4452af0c9a

[ "MIT" ]

null

def add_up(nums): return sum(nums) def test_answer(): assert add_up([1,2,2]) == 5

16.8

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0.666667

17

84

3.117647

0.705882

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0.055556

0.142857

84

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null

0

1

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1

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5

388f68464a39af7ea5cc19e6d513b120737b0064

270

py

Python

tfn/tools/loaders/__init__.py

UPEIChemistry/TFN_Layers

5c25583ee4108a13af8e73eabd3c448f42cb70a0

[ "MIT" ]

2

2021-06-24T00:27:10.000Z

2021-09-19T06:50:28.000Z

tfn/tools/loaders/__init__.py

UPEIChemistry/TFN_Layers

5c25583ee4108a13af8e73eabd3c448f42cb70a0

[ "MIT" ]

4

2019-10-10T18:36:37.000Z

2019-10-10T18:37:55.000Z

tfn/tools/loaders/__init__.py

UPEIChemistry/TFN_Layers

5c25583ee4108a13af8e73eabd3c448f42cb70a0

[ "MIT" ]

null

""" Sub-package containg all loader classes """ from .data_loader import DataLoader from .qm9_loader import QM9DataDataLoader from .iso17_loader import ISO17DataLoader from .ts_loader import TSLoader from .sn2_loader import SN2Loader from .isom_loader import IsomLoader

27

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9

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1

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1

0

1

0

5

3896c529bb2366c6b7d2f1c4920fc05bd72675e7

382

py

Python

fastapi_mvc/commands/__init__.py

rszamszur/fastapi-mvc

98670eda3b485cfe25850773dcc1ae7ae5feced9

[ "MIT" ]

98

2021-12-21T18:45:07.000Z

2022-03-27T08:48:37.000Z

fastapi_mvc/commands/__init__.py

rszamszur/fastapi-mvc

98670eda3b485cfe25850773dcc1ae7ae5feced9

[ "MIT" ]

48

2021-12-21T16:06:56.000Z

2022-03-26T17:28:57.000Z

fastapi_mvc/commands/__init__.py

rszamszur/fastapi-mvc

98670eda3b485cfe25850773dcc1ae7ae5feced9

[ "MIT" ]

16

2022-01-05T14:21:50.000Z

2022-02-13T17:55:07.000Z

"""Command design pattern. The ``fastapi-mvc.commands`` submodule implements command design pattern. Resources: 1. https://refactoring.guru/design-patterns/command """ from fastapi_mvc.commands.base import Command from fastapi_mvc.commands.invoker import Invoker from fastapi_mvc.commands.run_generator import RunGenerator from fastapi_mvc.commands.run_shell import RunShell

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382

12

74

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null

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null

0

1

0

1

0

1

0

5

38b28cf76888a648b452e934a33a7d0a458b67ed

1,069

py

Python

or_suite/envs/general_test.py

JasmineSamadi/ORSuite

e2b2b0a5b497ea6566e794dcef1f176081fca4ce

[ "MIT" ]

4

2021-12-01T10:56:17.000Z

2022-02-06T17:07:43.000Z

or_suite/envs/general_test.py

JasmineSamadi/ORSuite

e2b2b0a5b497ea6566e794dcef1f176081fca4ce

[ "MIT" ]

2

2021-08-11T13:25:01.000Z

2022-03-20T19:23:23.000Z

or_suite/envs/general_test.py

JasmineSamadi/ORSuite

e2b2b0a5b497ea6566e794dcef1f176081fca4ce

[ "MIT" ]

2

2021-07-27T02:39:37.000Z

2022-02-14T21:03:15.000Z

import gym import numpy as np import sys from scipy.stats import poisson import env_configs import pytest from stable_baselines3.common.env_checker import check_env import general_test_helpers def test_ambulance_metric(): general_test_helpers.test_env( 'Ambulance-v0', env_configs.ambulance_metric_default_config) def test_ambulance_graph(): general_test_helpers.test_env( 'Ambulance-v1', env_configs.ambulance_graph_default_config) def test_resource(): general_test_helpers.test_env( 'Resource-v0', env_configs.resource_allocation_default_config) def test_bandit(): general_test_helpers.test_env( 'Bandit-v0', env_configs.finite_bandit_default_config) def test_vaccine(): general_test_helpers.test_env( 'Vaccine-v0', env_configs.vaccine_default_config1) def test_rideshare(): general_test_helpers.test_env( 'Rideshare-v0', env_configs.rideshare_graph_default_config) def test_oil(): general_test_helpers.test_env( 'Oil-v0', env_configs.oil_environment_default_config)

23.23913

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144

1,069

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0.187256

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0.315995

0.088427

0

0.009868

0.146866

1,069

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1

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null

0

1

0

1

0

5

2a3b5d9b8da087bf208f6fc1a6ee076594aff76d

308

py

Python

poop/hfdp/adapter/ducks/challenge/drone_adapter.py

cassiobotaro/poop

fc218fbf638c50da8ea98dab7de26ad2a52e83f5

[ "MIT" ]

37

2020-12-27T00:13:07.000Z

2022-01-31T19:30:18.000Z

poop/hfdp/adapter/ducks/challenge/drone_adapter.py

cassiobotaro/poop

fc218fbf638c50da8ea98dab7de26ad2a52e83f5

[ "MIT" ]

null

poop/hfdp/adapter/ducks/challenge/drone_adapter.py

cassiobotaro/poop

fc218fbf638c50da8ea98dab7de26ad2a52e83f5

[ "MIT" ]

7

2020-12-26T22:33:47.000Z

2021-11-07T01:29:59.000Z

from poop.hfdp.adapter.ducks.challenge.drone import Drone class DroneAdapter: def __init__(self, drone: Drone) -> None: self.__drone = drone def quack(self) -> None: self.__drone.beep() def fly(self) -> None: self.__drone.spin_rotors() self.__drone.take_off()

22

57

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39

308

4.692308

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0.245902

0.213115

0.185792

0

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308

13

58

23.692308

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0

1

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false

0

0.111111

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0.555556

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null

1

0

null

0

1

0

1

0

5

2a55f2bcb6b545b671fc907e0d9b0d8583e77a56

2,084

py

Python

tests/test_convert.py

vikpe/exex-cli

e8b639882e8db3cb6eb3e873b4327a0f9c864f44

[ "MIT" ]

2

2021-11-14T05:47:24.000Z

2021-12-27T13:58:27.000Z

tests/test_convert.py

vikpe/exex-cli

e8b639882e8db3cb6eb3e873b4327a0f9c864f44

[ "MIT" ]

null

tests/test_convert.py

vikpe/exex-cli

e8b639882e8db3cb6eb3e873b4327a0f9c864f44

[ "MIT" ]

null

from exex_cli import convert def test_to_string(): assert convert.to_string(None) == "" assert convert.to_string("None") == "None" assert convert.to_string(0) == "0" assert convert.to_string(1) == "1" assert convert.to_string("a") == "a" assert convert.to_string(False) == "False" assert convert.to_string("False") == "False" assert convert.to_string([]) == "" def test_to_strings(): assert convert.to_strings(None) == "" assert convert.to_strings("None") == "None" assert convert.to_strings(0) == "0" assert convert.to_strings(1) == "1" assert convert.to_strings("a") == "a" assert convert.to_strings(False) == "False" assert convert.to_strings("False") == "False" assert convert.to_strings([]) == "" assert convert.to_strings(["a"]) == ["a"] assert convert.to_strings([1]) == ["1"] assert convert.to_strings([["a", 1], ["b", 2]]) == [["a", "1"], ["b", "2"]] def test_to_csv(): assert convert.to_csv(None) == "\n" assert convert.to_csv("None") == "None\n" assert convert.to_csv(0) == "0\n" assert convert.to_csv(1) == "1\n" assert convert.to_csv("a") == "a\n" assert convert.to_csv(False) == "False\n" assert convert.to_csv("False") == "False\n" assert convert.to_csv([]) == "\n" assert convert.to_csv(["a"]) == "a\n" assert convert.to_csv(["a", "b", 3]) == "a,b,3\n" assert convert.to_csv([["a", "b", 3]]) == "a,b,3\n" assert convert.to_csv([1]) == "1\n" assert convert.to_csv([["a", 1], ["b", 2]]) == "a,1\nb,2\n" def test_to_json(): def strip_whitespace(val): import re pattern = re.compile(r"\s+") return re.sub(pattern, "", val) def json_no_whitespace(val): return strip_whitespace(convert.to_json(val)) assert json_no_whitespace(["a"]) == '["a"]' assert json_no_whitespace(["a", "b", 3]) == '["a","b",3]' assert json_no_whitespace([["a", "b", 3]]) == '[["a","b",3]]' assert json_no_whitespace([1]) == "[1]" assert json_no_whitespace([["a", 1], ["b", 2]]) == '[["a",1],["b",2]]'

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0.417755

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0.809399

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0

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2,084

59

80

35.322034

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0

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0.770833

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false

0

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0.020833

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0

null

1

0

null

0

1

0

5

2a7d2a6598d374b4ef6188db24c8f653e8b7d102

25

py

Python

miner/__init__.py

chrisedebo/nice-py-switcher

fc1a24ab220e65f87c7561dc5404a2003634ddbf

[ "MIT" ]

null

miner/__init__.py

chrisedebo/nice-py-switcher

fc1a24ab220e65f87c7561dc5404a2003634ddbf

[ "MIT" ]

null

miner/__init__.py

chrisedebo/nice-py-switcher

fc1a24ab220e65f87c7561dc5404a2003634ddbf

[ "MIT" ]

3

2018-02-23T19:42:18.000Z

2022-03-31T02:51:14.000Z

#Miner plugin definition

12.5

24

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3

25

7

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0.12

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1

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0.954545

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0

null

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null

0

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1

null

true

0

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0

null

0

1

0

1

0

null

0

1

0

5

2a8403ad1f20768706782bc6163b24d0fe72e6af

20

py

Python

lib/ui/__init__.py

mattermccrea/expensive-skeleton-free

feb32387457da0cd34d2e36dcf568efc786c634d

[ "Apache-2.0" ]

null

lib/ui/__init__.py

mattermccrea/expensive-skeleton-free

feb32387457da0cd34d2e36dcf568efc786c634d

[ "Apache-2.0" ]

null

lib/ui/__init__.py

mattermccrea/expensive-skeleton-free

feb32387457da0cd34d2e36dcf568efc786c634d

[ "Apache-2.0" ]

null

# this is init file

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aa783baa904aa30270a896b768683b8426882e6f

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py

Python

data_structures/linked_list/doubly_linked/__init__.py

kwahome/data-structures-and-algos

535b23c63bf384d63c1ebc08d1c32d3dd808297c

[ "Apache-2.0" ]

null

data_structures/linked_list/doubly_linked/__init__.py

kwahome/data-structures-and-algos

535b23c63bf384d63c1ebc08d1c32d3dd808297c

[ "Apache-2.0" ]

null

data_structures/linked_list/doubly_linked/__init__.py

kwahome/data-structures-and-algos

535b23c63bf384d63c1ebc08d1c32d3dd808297c

[ "Apache-2.0" ]

null

from .linked_list import DoublyLinkedList, Node

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5

aa9784c94b8e97334b939009da1f5d45b9e3e694

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py

Python

venv/Lib/site-packages/lunr/exceptions.py

star10919/drf

77c005794087484d72ffc0d76612a6ac9845821e

[ "BSD-3-Clause" ]

2

2021-06-18T07:48:14.000Z

2021-06-21T11:55:01.000Z

venv/Lib/site-packages/lunr/exceptions.py

star10919/drf

77c005794087484d72ffc0d76612a6ac9845821e

[ "BSD-3-Clause" ]

null

venv/Lib/site-packages/lunr/exceptions.py

star10919/drf

77c005794087484d72ffc0d76612a6ac9845821e

[ "BSD-3-Clause" ]

null

from __future__ import unicode_literals class BaseLunrException(Exception): pass class QueryParseError(BaseLunrException): pass

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2aab127318c802a89f8dee2aa4c6426be3c779fd

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py

Python

src/models/jaxgp/mean.py

jejjohnson/uncertain_gps

8f71a74dc38640dcf2113eb742229d991ead041d

[ "MIT" ]

9

2020-02-23T16:23:58.000Z

2022-03-07T06:43:45.000Z

src/models/jaxgp/mean.py

jejjohnson/uncertain_gps

8f71a74dc38640dcf2113eb742229d991ead041d

[ "MIT" ]

null

src/models/jaxgp/mean.py

jejjohnson/uncertain_gps

8f71a74dc38640dcf2113eb742229d991ead041d

[ "MIT" ]

1

2022-02-25T04:37:18.000Z

import jax.numpy as jnp def zero_mean(x): return jnp.zeros(x.shape[0])

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2ab14394a782679c9b1f520e50a6f6505815bfda

87

py

Python

myparser/config.py

kbondar17/declarations-parser

8afae82be47e62b57cb02386beed8f1b64a9c627

[ "MIT" ]

null

myparser/config.py

kbondar17/declarations-parser

8afae82be47e62b57cb02386beed8f1b64a9c627

[ "MIT" ]

null

myparser/config.py

kbondar17/declarations-parser

8afae82be47e62b57cb02386beed8f1b64a9c627

[ "MIT" ]

null

import configparser from dotenv import dotenv_values config = dotenv_values(".env")

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2abf3d058a68f7a241f46f980a6970a510207010

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py

Python

nose2/tests/functional/support/scenario/module_import_err/pkg/test_attribute_err.py

benj-pml/nose2

b8c66e6f13319ab1b4a43a367b2ffac4cce90b70

[ "BSD-2-Clause" ]

null

nose2/tests/functional/support/scenario/module_import_err/pkg/test_attribute_err.py

benj-pml/nose2

b8c66e6f13319ab1b4a43a367b2ffac4cce90b70

[ "BSD-2-Clause" ]

null

nose2/tests/functional/support/scenario/module_import_err/pkg/test_attribute_err.py

benj-pml/nose2

b8c66e6f13319ab1b4a43a367b2ffac4cce90b70

[ "BSD-2-Clause" ]

null

from nose2.compat import unittest def test_foo(): pass class TestFoo(unittest.TestCase): def test_foo(self): pass

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2ac1ff96a2eb086e7b21c0cc742f98d0ea38b5ed

112

py

Python

src/hotels/utils.py

bee-travels/data-generator

a27d446daa24b93b5c0ecba9e1b3a8228815023e

[ "Apache-2.0" ]

2

2021-06-23T03:52:09.000Z

2021-07-26T06:14:15.000Z

src/destination/utils.py

bee-travels/data-generator

a27d446daa24b93b5c0ecba9e1b3a8228815023e

[ "Apache-2.0" ]

1

2020-04-16T17:28:50.000Z

src/hotels/utils.py

bee-travels/data-generator

a27d446daa24b93b5c0ecba9e1b3a8228815023e

[ "Apache-2.0" ]

2

2021-07-26T06:59:04.000Z

2022-01-14T06:58:04.000Z

import json def load_json(file_name): with open(file_name) as json_data: return json.load(json_data)

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555

py

Python

exercises/bob/example.py

kishankj/python

82042de746128127502e109111e6c4e8ab002af6

[ "MIT" ]

1,177

2017-06-21T20:24:06.000Z

2022-03-29T02:30:55.000Z

exercises/bob/example.py

kishankj/python

82042de746128127502e109111e6c4e8ab002af6

[ "MIT" ]

1,890

2017-06-18T20:06:10.000Z

2022-03-31T18:35:51.000Z

exercises/bob/example.py

kishankj/python

82042de746128127502e109111e6c4e8ab002af6

[ "MIT" ]

1,095

2017-06-26T23:06:19.000Z

2022-03-29T03:25:38.000Z

def response(hey_bob): hey_bob = hey_bob.strip() if _is_silence(hey_bob): return 'Fine. Be that way!' if _is_shouting(hey_bob): if _is_question(hey_bob): return "Calm down, I know what I'm doing!" else: return 'Whoa, chill out!' elif _is_question(hey_bob): return 'Sure.' else: return 'Whatever.' def _is_silence(hey_bob): return hey_bob == '' def _is_shouting(hey_bob): return hey_bob.isupper() def _is_question(hey_bob): return hey_bob.endswith('?')

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2d4888b027ef333ce4ca3219620e90288bda458a

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py

Python

longest_increasing_subsequence/_implementation.py

mCodingLLC/longest_increasing_subsequence

65ede89d4e76bc6086bbe1eb1440123df698d1ae

[ "MIT" ]

7

2021-03-23T10:38:35.000Z

2022-03-01T15:38:52.000Z

longest_increasing_subsequence/_implementation.py

mCodingLLC/longest_increasing_subsequence

65ede89d4e76bc6086bbe1eb1440123df698d1ae

[ "MIT" ]

null

longest_increasing_subsequence/_implementation.py

mCodingLLC/longest_increasing_subsequence

65ede89d4e76bc6086bbe1eb1440123df698d1ae

[ "MIT" ]

3

2021-03-23T10:38:36.000Z

2021-10-09T14:06:57.000Z

"""Implementation of the longest increasing subsequence algorithm.""" import operator from bisect import bisect_right, bisect_left from typing import TypeVar, Optional, List, Any, Iterator, Sequence, Callable T = TypeVar('T') def longest_increasing_subsequence(seq: Sequence[T], strict=False, key: Callable = None) -> List[T]: """ Returns the longest increasing subsequence of the given sequence. There may be other increasing subsequences of the same length. >>> longest_increasing_subsequence([0, 8, 4, 12, 2, 10, 6, 14, 1, 9, 5, 13, 3, 11, 7, 15]) [0, 2, 6, 9, 11, 15] >>> longest_increasing_subsequence([0, 0, 1, 2, 3, 2, 1, 0, 0]) [0, 0, 1, 2, 2] >>> longest_increasing_subsequence([0, 0, 1, 2, 3], strict=True) [0, 1, 2, 3] >>> longest_increasing_subsequence(['A', 'B', 'CC', 'D', 'EEE'], key=len) ['A', 'B', 'D', 'EEE'] >>> "".join(longest_increasing_subsequence('aababbbdccddd')) 'aaabbbccddd' :param seq: A sequence-like container of comparable objects. :param strict: Whether the subsequence must be strictly increasing. :param key: If not None, values in sequence are compared by comparing their keys. :return: The longest increasing subsequence in seq as a list. """ return _longest_monotone_subsequence(seq, True, strict, key) def longest_decreasing_subsequence(seq: Sequence[T], strict=False, key: Callable = None) -> List[T]: """ Returns the longest decreasing subsequence of the given sequence. There may be other decreasing subsequences of the same length. >>> longest_decreasing_subsequence([0, 8, 4, 12, 2, 10, 6, 14, 1, 9, 5, 13, 3, 11, 7, 15]) [12, 10, 9, 5, 3] >>> longest_decreasing_subsequence([0, 0, 1, 2, 3, 2, 1, 0, 0]) [3, 2, 1, 0, 0] >>> longest_decreasing_subsequence([0, 0, 1, 2, 3, 2, 1, 0, 0], strict=True) [3, 2, 1, 0] :param seq: A sequence-like container of comparable objects. :param strict: Whether the subsequence must be strictly decreasing. :param key: If not None, values in sequence are compared by comparing their keys. :return: The longest decreasing subsequence in seq as a list. """ try: return _longest_monotone_subsequence(seq, False, strict, key, True) except TypeError: pass return _longest_monotone_subsequence(seq, False, strict, key, False) def longest_increasing_subsequence_indices(seq: Sequence[T], strict=False, key: Callable = None) -> List[int]: """ Returns the indices of the longest increasing subsequence of the given sequence. There may be other increasing subsequences of the same length. >>> longest_increasing_subsequence_indices([0, 8, 4, 12, 2, 10, 6, 14, 1, 9, 5, 13, 3, 11, 7, 15]) [0, 4, 6, 9, 13, 15] >>> longest_increasing_subsequence_indices([0, 0, 1, 2, 3, 2, 1, 0, 0]) [0, 1, 2, 3, 5] >>> longest_increasing_subsequence_indices([0, 0, 1, 2, 3, 2, 1, 0, 0], strict=True) [0, 2, 3, 4] :param seq: A sequence-like container of comparable objects. :param strict: Whether the subsequence must be strictly increasing. :param key: If not None, values in sequence are compared by comparing their keys. :return: A list of indices of the longest increasing subsequence in seq. """ return _longest_monotone_subsequence_indices(seq, True, strict, key) def longest_decreasing_subsequence_indices(seq: Sequence[T], strict=False, key: Callable = None) -> List[int]: """ Returns the indices of the longest decreasing subsequence of the given sequence. There may be other decreasing subsequences of the same length. >>> longest_decreasing_subsequence_indices([0, 8, 4, 12, 2, 10, 6, 14, 1, 9, 5, 13, 3, 11, 7, 15]) [3, 5, 9, 10, 12] >>> longest_decreasing_subsequence_indices([0, 0, 1, 2, 3, 2, 1, 0, 0]) [4, 5, 6, 7, 8] >>> longest_decreasing_subsequence_indices([0, 0, 1, 2, 3, 2, 1, 0, 0], strict=True) [4, 5, 6, 7] :param seq: A sequence-like container of comparable objects. :param strict: Whether the subsequence must be strictly decreasing. :param key: If not None, values in sequence are compared by comparing their keys. :return: A list of indices of the longest decreasing subsequence in seq. """ try: return _longest_monotone_subsequence_indices(seq, False, strict, key, True) except TypeError: pass return _longest_monotone_subsequence_indices(seq, False, strict, key, False) def _longest_monotone_subsequence(seq: Sequence[T], increasing=True, strict=False, key: Callable = None, assume_negatable=True) -> List[T]: """ Returns the a list of the longest increasing (respectively decreasing) subsequence of the given sequence. There may be other increasing (respectively decreasing) subsequences of the same length. This is not a public function, use a longest_increasing_* or longest_decreasing_* function instead. :param seq: A sequence-like container of comparable objects. :param increasing: Whether the subsequence should be increasing or decreasing. :param strict: Whether the subsequence must be strictly monotone. :param key: If not None, values in sequence are compared by comparing their keys. :param assume_negatable: If True (the default), assume that negation (unary -) is defined and is order-reversing on objects or keys. For non-negatable types, set this option to False. :return: An iterator of indices of the longest monotone subsequence in seq. """ return [seq[idx] for idx in _longest_monotone_subsequence_indices_iter(seq, increasing, strict, key, assume_negatable)] def _longest_monotone_subsequence_indices(seq: Sequence[T], increasing=True, strict=False, key: Callable = None, assume_negatable=True) -> List[int]: """ Gives a list of the indices of the longest increasing (respectively decreasing) subsequence of the given sequence. There may be other increasing (respectively decreasing) subsequences of the same length. This is not a public function, use a longest_increasing_* or longest_decreasing_* function instead. :param seq: A sequence-like container of comparable objects. :param increasing: Whether the subsequence should be increasing or decreasing. :param strict: Whether the subsequence must be strictly monotone. :param key: If not None, values in sequence are compared by comparing their keys. :param assume_negatable: If True (the default), assume that negation (unary -) is defined and is order-reversing on objects or keys. For non-negatable types, set this option to False. :return: An iterator of indices of the longest monotone subsequence in seq. """ return list(_longest_monotone_subsequence_indices_iter(seq, increasing, strict, key, assume_negatable)) def _longest_monotone_subsequence_indices_iter(seq: Sequence[T], increasing=True, strict=False, key: Callable = None, assume_negatable=True) -> Iterator[int]: """ Yields the indices of the longest increasing (respectively decreasing) subsequence of the given sequence. There may be other monotone subsequences of the same length. This is not a public function, use a longest_increasing_* or longest_decreasing_* function instead. :param seq: A sequence-like container of comparable objects. :param increasing: Whether the subsequence should be increasing or decreasing. :param strict: Whether the subsequence must be strictly monotone. :param key: If not None, values in sequence are compared by comparing their keys. :param assume_negatable: If True (the default), assume that negation (unary -) is defined and is order-reversing on objects or keys. For non-negatable types, set this option to False. :return: An iterator of indices of the longest monotone subsequence in seq. """ if not seq: return (_ for _ in []) idx_prev_longest: List[Optional[int]] = [] idx_min_of_len_plus1: List[int] = [] # the index of the smallest value ending a subsequence of a given length+1 val_min_of_len_plus1: List[Any] = [] # the smallest value ending a subsequence of a given length+1 bisect = bisect_right if not strict else bisect_left key_fn = _choose_key_function(key, increasing, assume_negatable) keys = seq if key_fn is None else map(key_fn, seq) for i, curr_key in enumerate(keys): len_longest_extendable = bisect(val_min_of_len_plus1, curr_key) if len_longest_extendable == len(val_min_of_len_plus1): idx_min_of_len_plus1.append(i) val_min_of_len_plus1.append(curr_key) elif curr_key < val_min_of_len_plus1[len_longest_extendable]: idx_min_of_len_plus1[len_longest_extendable] = i val_min_of_len_plus1[len_longest_extendable] = curr_key idx_longest_extendable = idx_min_of_len_plus1[len_longest_extendable - 1] if len_longest_extendable else None idx_prev_longest.append(idx_longest_extendable) longest_subsequence_indices = _make_subsequence_indices(prev_indices=idx_prev_longest, terminal_idx=idx_min_of_len_plus1[-1]) return longest_subsequence_indices class _OrderReversed: """ A wrapper around any object that swaps its < and > operators (without touching the actual object). >>> _OrderReversed(0) > _OrderReversed(1) True >>> repr(_OrderReversed(0)) '_OrderReversed(0)' """ __slots__ = ('obj',) def __init__(self, o): self.obj = o def __lt__(self, other): return self.obj > other.obj def __gt__(self, other): return self.obj < other.obj def __repr__(self): return f'{self.__class__.__name__}({self.obj!r})' def _choose_key_function(key: Optional[Callable], increasing: bool, assume_negatable: bool) -> Optional[Callable]: """ Gives back the key function with its order optionally reversed. None represents the identity function. >>> _choose_key_function(None, True, True) is None True >>> _choose_key_function(None, True, False) is None True >>> fn = _choose_key_function(None, False, True) >>> fn(0) > fn(1) True >>> fn = _choose_key_function(None, False, False) >>> fn(0) > fn(1) True >>> fn = _choose_key_function(len, True, False) >>> fn("X") < fn("AA") True >>> fn = _choose_key_function(len, True, True) >>> fn("X") < fn("AA") True >>> fn = _choose_key_function(len, False, False) >>> fn("AA") < fn("X") True """ if key is None: if increasing: key_fn = None elif assume_negatable: key_fn = operator.neg else: def key_fn(v): return _OrderReversed(v) else: orig_key = key if increasing: key_fn = orig_key elif assume_negatable: def key_fn(v): return -orig_key(v) else: def key_fn(v): return _OrderReversed(orig_key(v)) return key_fn def _make_reversed_subsequence_indices(prev_indices: List[Optional[int]], terminal_idx: int) -> Iterator[int]: """ Given a list of indices representing pointers to parent, and given a terminal pointer, yields indices from the terminal to the root. >>> list(_make_reversed_subsequence_indices([None, 0, 0, 1, 2, 1], 5)) [5, 1, 0] """ idx: Optional[int] = terminal_idx while idx is not None: yield idx idx = prev_indices[idx] def _make_subsequence_indices(prev_indices: List[Optional[int]], terminal_idx: int) -> Iterator[int]: """ Given a list of indices representing pointers to parent, and given a terminal pointer, yields indices from the root to the terminal index. >>> list(_make_subsequence_indices([None, 0, 0, 1, 2, 1], 5)) [0, 1, 5] """ return reversed(list(_make_reversed_subsequence_indices(prev_indices, terminal_idx)))

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2d5011c10a3c49eaed53c90bf000cdcefd5ebfbc

51

py

Python

visualdet3d/networks/detectors/__init__.py

tamnguyenvan/visualdet3d-tf

0c5b88e1aa61a75c1a8e3e1032aa7bcbd04b3bea

[ "Apache-2.0" ]

null

visualdet3d/networks/detectors/__init__.py

tamnguyenvan/visualdet3d-tf

0c5b88e1aa61a75c1a8e3e1032aa7bcbd04b3bea

[ "Apache-2.0" ]

null

visualdet3d/networks/detectors/__init__.py

tamnguyenvan/visualdet3d-tf

0c5b88e1aa61a75c1a8e3e1032aa7bcbd04b3bea

[ "Apache-2.0" ]

null

from .yolostereo3d_detector import YOLOStereo3DCore

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2d77f1fde3a230ee5bcd78349c99a210bca0f69e

644

py

Python

aula7_classes_calculadora2.py

clovisdanielcosta/dio-python

764eaac06320c0531c3038e301eb4c002fe8afce

[ "MIT" ]

null

aula7_classes_calculadora2.py

clovisdanielcosta/dio-python

764eaac06320c0531c3038e301eb4c002fe8afce

[ "MIT" ]

null

aula7_classes_calculadora2.py

clovisdanielcosta/dio-python

764eaac06320c0531c3038e301eb4c002fe8afce

[ "MIT" ]

null

# Sem passar valores pelo init class Calculadora: # def __init__(self): # pass def soma(self, valor_a, valor_b): return valor_a + valor_b def subtracao(self, valor_a, valor_b): return valor_a - valor_b def multiplicacao(self, valor_a, valor_b): return valor_a * valor_b def divisao(self, valor_a, valor_b): return valor_a / valor_b if __name__ == '__main__': # Instanciando uma classe calculadora = Calculadora() print(calculadora.soma(10, 2)) print(calculadora.subtracao(10, 2)) print(calculadora.multiplicacao(10, 2)) print(calculadora.divisao(10, 2))

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0.6

0.266667

0

null

0

1

0

null

0

1

0

1

0

5

2da8aa8abcf15d665df739a031acd23037c32e66

148

py

Python

Python/Programming Fundamentals/Text Processing/13. Substring.py

teodoramilcheva/softuni-software-engineering

98dc9faa66f42570f6538fd7ef186d2bd1d39bff

[ "MIT" ]

null

Python/Programming Fundamentals/Text Processing/13. Substring.py

teodoramilcheva/softuni-software-engineering

98dc9faa66f42570f6538fd7ef186d2bd1d39bff

[ "MIT" ]

null

Python/Programming Fundamentals/Text Processing/13. Substring.py

teodoramilcheva/softuni-software-engineering

98dc9faa66f42570f6538fd7ef186d2bd1d39bff

[ "MIT" ]

null

first_str = input() second_str = input() while first_str in second_str: second_str = second_str.replace(first_str, '') print(second_str)

21.142857

51

0.716216

22

148

4.454545

0.363636

0.459184

0.306122

0.367347

0

0.175676

148

7

52

21.142857

0.803279

0

1

0

false

0

0.2

1

0

null

1

0

1

0

null

0

5

2dec5ea7bf0248390057b295993ff4db6ec688e2

29

py

Python

editor.py

Commander07/Magnitude

2b793d0d9946f6b35c5935ae5921592e287bbbe7

[ "MIT" ]

6

2020-12-06T20:21:39.000Z

2021-06-29T06:37:40.000Z

editor.py

Commander07/Magnitude

2b793d0d9946f6b35c5935ae5921592e287bbbe7

[ "MIT" ]

null

editor.py

Commander07/Magnitude

2b793d0d9946f6b35c5935ae5921592e287bbbe7

[ "MIT" ]

null

import editor editor.start()

9.666667

14

0.793103

4

29

5.75

0.75

0

0.103448

29

2

15

14.5

0.884615

0

1

0

true

0

0.5

0

0.5

0

1

0

null

0

1

0

null

0

1

0

1

0

5

930840abae58f570788e4a4d4e3d260f0cec9bf1

156

py

Python

bayesiancoresets/coreset/__init__.py

trevorcampbell/hilbert-coresets

63354127953a432c0f35087cf5b75166f652a5f5

[ "MIT" ]

118

2018-02-10T21:33:57.000Z

2022-03-22T14:20:53.000Z

bayesiancoresets/coreset/__init__.py

trevorcampbell/hilbert-coresets

63354127953a432c0f35087cf5b75166f652a5f5

[ "MIT" ]

3

2018-09-07T16:13:22.000Z

2020-04-11T14:35:47.000Z

bayesiancoresets/coreset/__init__.py

trevorcampbell/hilbert-coresets

63354127953a432c0f35087cf5b75166f652a5f5

[ "MIT" ]

30

2018-03-11T02:37:55.000Z

2022-01-31T14:51:37.000Z

from .hilbert import HilbertCoreset from .sampling import UniformSamplingCoreset from .sparsevi import SparseVICoreset from .bpsvi import BatchPSVICoreset

26

44

0.865385

16

156

8.4375

0.625

0

0.108974

156

5

45

31.2

0.971223

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

9311781e5801a866e09b81d5366ba3fdcafbd49f

100

py

Python

src/modeling/__init__.py

clazaro97chosen/American-Community-Survey-Project

ac3f8c1231ea71bdd7fc7b8eceb8e69cd6d7b842

[ "MIT" ]

2

2019-07-22T20:53:47.000Z

2019-07-23T07:35:00.000Z

src/modeling/__init__.py

clazaro97chosen/American-Community-Survey-Project

ac3f8c1231ea71bdd7fc7b8eceb8e69cd6d7b842

[ "MIT" ]

null

src/modeling/__init__.py

clazaro97chosen/American-Community-Survey-Project

ac3f8c1231ea71bdd7fc7b8eceb8e69cd6d7b842

[ "MIT" ]

null

from .model_tryout import * from .prep_or_featureselection import * from .train_and_predict import *

33.333333

39

0.83

14

100

5.571429

0.714286

0.25641

0

0.11

100

3

40

33.333333

0.876404

0

1

0

true

0

1

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

5

9319d7925b2fbbe3bce92f3722a80861d80dbfcd

307

py

Python

Part_2_intermediate/mod_2/lesson_5/homework_3/shop/product.py

Mikma03/InfoShareacademy_Python_Courses

3df1008c8c92831bebf1625f960f25b39d6987e6

[ "MIT" ]

null

Part_2_intermediate/mod_2/lesson_5/homework_3/shop/product.py

Mikma03/InfoShareacademy_Python_Courses

3df1008c8c92831bebf1625f960f25b39d6987e6

[ "MIT" ]

null

Part_2_intermediate/mod_2/lesson_5/homework_3/shop/product.py

Mikma03/InfoShareacademy_Python_Courses

3df1008c8c92831bebf1625f960f25b39d6987e6

[ "MIT" ]

null

class Product: def __init__(self, name, category_name, unit_price): self.name = name self.category_name = category_name self.unit_price = unit_price def __str__(self): return f"Nazwa: {self.name} | Kategoria: {self.category_name} | Cena: {self.unit_price} PLN/szt"

30.7

104

0.664495

41

307

4.585366

0.414634

0.255319

0.170213

0

0.228013

307

9

105

34.111111

0.793249

0

0.142857

0.28013

0

1

0.285714

false

0

0.142857

0.571429

0

null

1

0

1

0

null

0

1

0

1

0

5

9331b255e437ab7681f4ec5d2447a1cee9ae7991

163

py

Python

diet/admin.py

EspeIgira/Health-Diet

a0314beb787e981a50946c64f6da30bd34897cc3

[ "MIT" ]

null

diet/admin.py

EspeIgira/Health-Diet

a0314beb787e981a50946c64f6da30bd34897cc3

[ "MIT" ]

null

diet/admin.py

EspeIgira/Health-Diet

a0314beb787e981a50946c64f6da30bd34897cc3

[ "MIT" ]

null

from django.contrib import admin from .models import Image,Category,Comment admin.site.register(Image) admin.site.register(Category) admin.site.register(Comment)

23.285714

42

0.828221

23

163

5.869565

0.478261

0.2

0.377778

0

0.07362

163

6

43

27.166667

0.89404

0

1

0

true

0

0.4

0

0.4

0

1

0

null

0

1

0

1

0

null

0

1

0

1

0

5

9358369c31df4ae4a01b224b2e773a052a7a8a91

43

py

Python

lib/pyfrc/wpilib/__init__.py

VikingRobotics/pyfrc

8db0f778586684cc6477a4c0b9600621a1a6a78f

[ "MIT" ]

1

2015-12-23T04:25:19.000Z

lib/pyfrc/wpilib/__init__.py

VikingRobotics/pyfrc

8db0f778586684cc6477a4c0b9600621a1a6a78f

[ "MIT" ]

null

lib/pyfrc/wpilib/__init__.py

VikingRobotics/pyfrc

8db0f778586684cc6477a4c0b9600621a1a6a78f

[ "MIT" ]

null

from .core import * from ..main import run

14.333333

22

0.72093

7

43

4.428571

0.714286

0

0.186047

43

2

23

21.5

0.885714

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

5

fa85cc4a201b5e86ee944f20d89b535ab601281b

46

py

Python

MYgames_package/MYgames/__main__.py

MandiYang/MYgames

9e6f56d35b1dba9c77c2703d9497f52a15d7773a

[ "MIT" ]

1

2021-04-06T10:51:44.000Z

MYgames_package/MYgames/__main__.py

MandiYang/MYgames

9e6f56d35b1dba9c77c2703d9497f52a15d7773a

[ "MIT" ]

null

MYgames_package/MYgames/__main__.py

MandiYang/MYgames

9e6f56d35b1dba9c77c2703d9497f52a15d7773a

[ "MIT" ]

null

print('Hello') print('Package name: MYgames')

15.333333

30

0.717391

6

46

5.5

0.833333

0

0.086957

46

2

31

23

0.785714

0

0.565217

0

1

0

true

0

1

0

null

0

1

0

null

0

1

0

1

0

5

facf749e9986898c70d727ba5e4ef521e3a8fe89

201

py

Python

replica/contrib/whisper/urls.py

underlost/Replica

2f092d3fc215b950fa6e409980a3f3e7c3633f7c

[ "MIT" ]

null

replica/contrib/whisper/urls.py

underlost/Replica

2f092d3fc215b950fa6e409980a3f3e7c3633f7c

[ "MIT" ]

null

replica/contrib/whisper/urls.py

underlost/Replica

2f092d3fc215b950fa6e409980a3f3e7c3633f7c

[ "MIT" ]

null

from __future__ import absolute_import from django.conf.urls import * from django.views.generic import TemplateView from django.views.decorators.cache import cache_page urlpatterns = patterns('', )

20.1

52

0.81592

26

201

6.076923

0.576923

0.189873

0.202532

0

0.114428

201

9

53

22.333333

0.88764

0

1

0

false

0

0.666667

0

0.666667

0

1

0

null

0

1

0

1

0

null

0

1

0

1

0

5

faec3380f42e1e36b9d15f0c84d075132519f2d2

53

py

Python

pun/__main__.py

Unviray/pun

ee943e0bb6f659913a9ce6403ebb375582327a11

[ "MIT" ]

2

2020-05-12T18:44:18.000Z

2020-05-16T19:56:31.000Z

pun/__main__.py

Unviray/pun

ee943e0bb6f659913a9ce6403ebb375582327a11

[ "MIT" ]

null

pun/__main__.py

Unviray/pun

ee943e0bb6f659913a9ce6403ebb375582327a11

[ "MIT" ]

null

import sys from .cli import main sys.exit(main())

7.571429

21

0.698113

9

53

4.111111

0.666667

0

0.188679

53

6

22

8.833333

0.860465

0

1

0

true

0

0.666667

0

0.666667

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

877e42200d3c70035d99f65300fe05e8d2cbdc0d

654

py

Python

Node3D/base/data/Math.py

ArnoChenFx/Node3D

30fe58cced3a8580eb129475925eb797e6065067

[ "MIT" ]

3

2020-09-09T15:42:46.000Z

2021-07-24T13:58:56.000Z

Node3D/base/data/Math.py

ArnoChenFx/Node3D

30fe58cced3a8580eb129475925eb797e6065067

[ "MIT" ]

null

Node3D/base/data/Math.py

ArnoChenFx/Node3D

30fe58cced3a8580eb129475925eb797e6065067

[ "MIT" ]

1

2021-10-17T12:21:39.000Z

import numpy as np def clamp(value, min, max): return np.clip(value, min, max) def lerp(a, b, fraction): fraction = clamp(fraction, 0, 1) return a * (1 - fraction) + b * fraction def fit(value, omin, omax, nmin, nmax): v = (value - omin) / (omax - omin) return v * (nmax - nmin) + nmin def fit01(value, min, max): return value * (max - min) + min def fit10(value, min, max): return (1.0 - value) * (max - min) + min def fit11(value, min, max): return fit(value, -1, 1, min, max) def fit_to_01(value, min, max): return (value - min) / (max - min) def fit_11_to_01(value): return (value + 1.0) * 0.5

18.166667

44

0.588685

106

654

3.584906

0.283019

0.126316

0.202632

0.223684

0.192105

0

0.047131

0.253823

654

35

45

18.685714

0.731557

0

1

0.421053

false

0

0.052632

0.315789

0.894737

0

null

0

1

0

null

0

1

0

1

0

5

87c002aa3b675c02715b1c61fecb47896095690b

17,669

py

Python

tests/ut/python/mindrecord/test_tfrecord_to_mr.py

shaolei-wang/mindspore

2d50a43be9d17269f6adb41e51b8f7a540ebc9f1

[ "Apache-2.0" ]

1

2020-06-20T06:22:41.000Z

tests/ut/python/mindrecord/test_tfrecord_to_mr.py

shaolei-wang/mindspore

2d50a43be9d17269f6adb41e51b8f7a540ebc9f1

[ "Apache-2.0" ]

null

tests/ut/python/mindrecord/test_tfrecord_to_mr.py

shaolei-wang/mindspore

2d50a43be9d17269f6adb41e51b8f7a540ebc9f1

[ "Apache-2.0" ]

null

# Copyright 2020 Huawei Technologies Co., Ltd. # # 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. """test tfrecord to mindrecord tool""" import collections from importlib import import_module import os import numpy as np import pytest from mindspore import log as logger from mindspore.mindrecord import FileReader from mindspore.mindrecord import TFRecordToMR SupportedTensorFlowVersion = '2.1.0' try: tf = import_module("tensorflow") # just used to convert tfrecord to mindrecord except ModuleNotFoundError: logger.warning("tensorflow module not found.") tf = None TFRECORD_DATA_DIR = "../data/mindrecord/testTFRecordData" TFRECORD_FILE_NAME = "test.tfrecord" MINDRECORD_FILE_NAME = "test.mindrecord" PARTITION_NUM = 1 def verify_data(transformer, reader): """Verify the data by read from mindrecord""" tf_iter = transformer.tfrecord_iterator() mr_iter = reader.get_next() count = 0 for tf_item, mr_item in zip(tf_iter, mr_iter): count = count + 1 assert len(tf_item) == 6 assert len(mr_item) == 6 for key, value in tf_item.items(): logger.info("key: {}, tfrecord: value: {}, mindrecord: value: {}".format(key, value, mr_item[key])) if isinstance(value, np.ndarray): assert (value == mr_item[key]).all() else: assert value == mr_item[key] assert count == 10 def generate_tfrecord(): def create_int_feature(values): if isinstance(values, list): feature = tf.train.Feature(int64_list=tf.train.Int64List(value=list(values))) # values: [int, int, int] else: feature = tf.train.Feature(int64_list=tf.train.Int64List(value=[values])) # values: int return feature def create_float_feature(values): if isinstance(values, list): feature = tf.train.Feature(float_list=tf.train.FloatList(value=list(values))) # values: [float, float] else: feature = tf.train.Feature(float_list=tf.train.FloatList(value=[values])) # values: float return feature def create_bytes_feature(values): if isinstance(values, bytes): feature = tf.train.Feature(bytes_list=tf.train.BytesList(value=[values])) # values: bytes else: # values: string feature = tf.train.Feature(bytes_list=tf.train.BytesList(value=[bytes(values, encoding='utf-8')])) return feature writer = tf.io.TFRecordWriter(os.path.join(TFRECORD_DATA_DIR, TFRECORD_FILE_NAME)) example_count = 0 for i in range(10): file_name = "000" + str(i) + ".jpg" image_bytes = bytes(str("aaaabbbbcccc" + str(i)), encoding="utf-8") int64_scalar = i float_scalar = float(i) int64_list = [i, i+1, i+2, i+3, i+4, i+1234567890] float_list = [float(i), float(i+1), float(i+2.8), float(i+3.2), float(i+4.4), float(i+123456.9), float(i+98765432.1)] features = collections.OrderedDict() features["file_name"] = create_bytes_feature(file_name) features["image_bytes"] = create_bytes_feature(image_bytes) features["int64_scalar"] = create_int_feature(int64_scalar) features["float_scalar"] = create_float_feature(float_scalar) features["int64_list"] = create_int_feature(int64_list) features["float_list"] = create_float_feature(float_list) tf_example = tf.train.Example(features=tf.train.Features(feature=features)) writer.write(tf_example.SerializeToString()) example_count += 1 writer.close() logger.info("Write {} rows in tfrecord.".format(example_count)) def test_tfrecord_to_mindrecord(): """test transform tfrecord to mindrecord.""" if not tf or tf.__version__ < SupportedTensorFlowVersion: # skip the test logger.warning("Module tensorflow is not found or version wrong, \ please use pip install it / reinstall version >= {}.".format(SupportedTensorFlowVersion)) return generate_tfrecord() assert os.path.exists(os.path.join(TFRECORD_DATA_DIR, TFRECORD_FILE_NAME)) feature_dict = {"file_name": tf.io.FixedLenFeature([], tf.string), "image_bytes": tf.io.FixedLenFeature([], tf.string), "int64_scalar": tf.io.FixedLenFeature([], tf.int64), "float_scalar": tf.io.FixedLenFeature([], tf.float32), "int64_list": tf.io.FixedLenFeature([6], tf.int64), "float_list": tf.io.FixedLenFeature([7], tf.float32), } if os.path.exists(MINDRECORD_FILE_NAME): os.remove(MINDRECORD_FILE_NAME) if os.path.exists(MINDRECORD_FILE_NAME + ".db"): os.remove(MINDRECORD_FILE_NAME + ".db") tfrecord_transformer = TFRecordToMR(os.path.join(TFRECORD_DATA_DIR, TFRECORD_FILE_NAME), MINDRECORD_FILE_NAME, feature_dict, ["image_bytes"]) tfrecord_transformer.transform() assert os.path.exists(MINDRECORD_FILE_NAME) assert os.path.exists(MINDRECORD_FILE_NAME + ".db") fr_mindrecord = FileReader(MINDRECORD_FILE_NAME) verify_data(tfrecord_transformer, fr_mindrecord) os.remove(MINDRECORD_FILE_NAME) os.remove(MINDRECORD_FILE_NAME + ".db") os.remove(os.path.join(TFRECORD_DATA_DIR, TFRECORD_FILE_NAME)) def test_tfrecord_to_mindrecord_scalar_with_1(): """test transform tfrecord to mindrecord.""" if not tf or tf.__version__ < SupportedTensorFlowVersion: # skip the test logger.warning("Module tensorflow is not found or version wrong, \ please use pip install it / reinstall version >= {}.".format(SupportedTensorFlowVersion)) return generate_tfrecord() assert os.path.exists(os.path.join(TFRECORD_DATA_DIR, TFRECORD_FILE_NAME)) feature_dict = {"file_name": tf.io.FixedLenFeature([], tf.string), "image_bytes": tf.io.FixedLenFeature([], tf.string), "int64_scalar": tf.io.FixedLenFeature([1], tf.int64), "float_scalar": tf.io.FixedLenFeature([1], tf.float32), "int64_list": tf.io.FixedLenFeature([6], tf.int64), "float_list": tf.io.FixedLenFeature([7], tf.float32), } if os.path.exists(MINDRECORD_FILE_NAME): os.remove(MINDRECORD_FILE_NAME) if os.path.exists(MINDRECORD_FILE_NAME + ".db"): os.remove(MINDRECORD_FILE_NAME + ".db") tfrecord_transformer = TFRecordToMR(os.path.join(TFRECORD_DATA_DIR, TFRECORD_FILE_NAME), MINDRECORD_FILE_NAME, feature_dict, ["image_bytes"]) tfrecord_transformer.transform() assert os.path.exists(MINDRECORD_FILE_NAME) assert os.path.exists(MINDRECORD_FILE_NAME + ".db") fr_mindrecord = FileReader(MINDRECORD_FILE_NAME) verify_data(tfrecord_transformer, fr_mindrecord) os.remove(MINDRECORD_FILE_NAME) os.remove(MINDRECORD_FILE_NAME + ".db") os.remove(os.path.join(TFRECORD_DATA_DIR, TFRECORD_FILE_NAME)) def test_tfrecord_to_mindrecord_scalar_with_1_list_small_len_exception(): """test transform tfrecord to mindrecord.""" if not tf or tf.__version__ < SupportedTensorFlowVersion: # skip the test logger.warning("Module tensorflow is not found or version wrong, \ please use pip install it / reinstall version >= {}.".format(SupportedTensorFlowVersion)) return generate_tfrecord() assert os.path.exists(os.path.join(TFRECORD_DATA_DIR, TFRECORD_FILE_NAME)) feature_dict = {"file_name": tf.io.FixedLenFeature([], tf.string), "image_bytes": tf.io.FixedLenFeature([], tf.string), "int64_scalar": tf.io.FixedLenFeature([1], tf.int64), "float_scalar": tf.io.FixedLenFeature([1], tf.float32), "int64_list": tf.io.FixedLenFeature([6], tf.int64), "float_list": tf.io.FixedLenFeature([2], tf.float32), } if os.path.exists(MINDRECORD_FILE_NAME): os.remove(MINDRECORD_FILE_NAME) if os.path.exists(MINDRECORD_FILE_NAME + ".db"): os.remove(MINDRECORD_FILE_NAME + ".db") with pytest.raises(ValueError): tfrecord_transformer = TFRecordToMR(os.path.join(TFRECORD_DATA_DIR, TFRECORD_FILE_NAME), MINDRECORD_FILE_NAME, feature_dict, ["image_bytes"]) tfrecord_transformer.transform() if os.path.exists(MINDRECORD_FILE_NAME): os.remove(MINDRECORD_FILE_NAME) if os.path.exists(MINDRECORD_FILE_NAME + ".db"): os.remove(MINDRECORD_FILE_NAME + ".db") os.remove(os.path.join(TFRECORD_DATA_DIR, TFRECORD_FILE_NAME)) def test_tfrecord_to_mindrecord_list_with_diff_type_exception(): """test transform tfrecord to mindrecord.""" if not tf or tf.__version__ < SupportedTensorFlowVersion: # skip the test logger.warning("Module tensorflow is not found or version wrong, \ please use pip install it / reinstall version >= {}.".format(SupportedTensorFlowVersion)) return generate_tfrecord() assert os.path.exists(os.path.join(TFRECORD_DATA_DIR, TFRECORD_FILE_NAME)) feature_dict = {"file_name": tf.io.FixedLenFeature([], tf.string), "image_bytes": tf.io.FixedLenFeature([], tf.string), "int64_scalar": tf.io.FixedLenFeature([1], tf.int64), "float_scalar": tf.io.FixedLenFeature([1], tf.float32), "int64_list": tf.io.FixedLenFeature([6], tf.float32), "float_list": tf.io.FixedLenFeature([7], tf.float32), } if os.path.exists(MINDRECORD_FILE_NAME): os.remove(MINDRECORD_FILE_NAME) if os.path.exists(MINDRECORD_FILE_NAME + ".db"): os.remove(MINDRECORD_FILE_NAME + ".db") with pytest.raises(ValueError): tfrecord_transformer = TFRecordToMR(os.path.join(TFRECORD_DATA_DIR, TFRECORD_FILE_NAME), MINDRECORD_FILE_NAME, feature_dict, ["image_bytes"]) tfrecord_transformer.transform() if os.path.exists(MINDRECORD_FILE_NAME): os.remove(MINDRECORD_FILE_NAME) if os.path.exists(MINDRECORD_FILE_NAME + ".db"): os.remove(MINDRECORD_FILE_NAME + ".db") os.remove(os.path.join(TFRECORD_DATA_DIR, TFRECORD_FILE_NAME)) def test_tfrecord_to_mindrecord_list_without_bytes_type(): """test transform tfrecord to mindrecord.""" if not tf or tf.__version__ < SupportedTensorFlowVersion: # skip the test logger.warning("Module tensorflow is not found or version wrong, \ please use pip install it / reinstall version >= {}.".format(SupportedTensorFlowVersion)) return generate_tfrecord() assert os.path.exists(os.path.join(TFRECORD_DATA_DIR, TFRECORD_FILE_NAME)) feature_dict = {"file_name": tf.io.FixedLenFeature([], tf.string), "image_bytes": tf.io.FixedLenFeature([], tf.string), "int64_scalar": tf.io.FixedLenFeature([1], tf.int64), "float_scalar": tf.io.FixedLenFeature([1], tf.float32), "int64_list": tf.io.FixedLenFeature([6], tf.int64), "float_list": tf.io.FixedLenFeature([7], tf.float32), } if os.path.exists(MINDRECORD_FILE_NAME): os.remove(MINDRECORD_FILE_NAME) if os.path.exists(MINDRECORD_FILE_NAME + ".db"): os.remove(MINDRECORD_FILE_NAME + ".db") tfrecord_transformer = TFRecordToMR(os.path.join(TFRECORD_DATA_DIR, TFRECORD_FILE_NAME), MINDRECORD_FILE_NAME, feature_dict) tfrecord_transformer.transform() assert os.path.exists(MINDRECORD_FILE_NAME) assert os.path.exists(MINDRECORD_FILE_NAME + ".db") fr_mindrecord = FileReader(MINDRECORD_FILE_NAME) verify_data(tfrecord_transformer, fr_mindrecord) os.remove(MINDRECORD_FILE_NAME) os.remove(MINDRECORD_FILE_NAME + ".db") os.remove(os.path.join(TFRECORD_DATA_DIR, TFRECORD_FILE_NAME)) def test_tfrecord_to_mindrecord_scalar_with_2_exception(): """test transform tfrecord to mindrecord.""" if not tf or tf.__version__ < SupportedTensorFlowVersion: # skip the test logger.warning("Module tensorflow is not found or version wrong, \ please use pip install it / reinstall version >= {}.".format(SupportedTensorFlowVersion)) return generate_tfrecord() assert os.path.exists(os.path.join(TFRECORD_DATA_DIR, TFRECORD_FILE_NAME)) feature_dict = {"file_name": tf.io.FixedLenFeature([], tf.string), "image_bytes": tf.io.FixedLenFeature([], tf.string), "int64_scalar": tf.io.FixedLenFeature([2], tf.int64), "float_scalar": tf.io.FixedLenFeature([1], tf.float32), "int64_list": tf.io.FixedLenFeature([6], tf.int64), "float_list": tf.io.FixedLenFeature([7], tf.float32), } if os.path.exists(MINDRECORD_FILE_NAME): os.remove(MINDRECORD_FILE_NAME) if os.path.exists(MINDRECORD_FILE_NAME + ".db"): os.remove(MINDRECORD_FILE_NAME + ".db") tfrecord_transformer = TFRecordToMR(os.path.join(TFRECORD_DATA_DIR, TFRECORD_FILE_NAME), MINDRECORD_FILE_NAME, feature_dict, ["image_bytes"]) with pytest.raises(ValueError): tfrecord_transformer.transform() if os.path.exists(MINDRECORD_FILE_NAME): os.remove(MINDRECORD_FILE_NAME) if os.path.exists(MINDRECORD_FILE_NAME + ".db"): os.remove(MINDRECORD_FILE_NAME + ".db") os.remove(os.path.join(TFRECORD_DATA_DIR, TFRECORD_FILE_NAME)) def test_tfrecord_to_mindrecord_scalar_string_with_1_exception(): """test transform tfrecord to mindrecord.""" if not tf or tf.__version__ < SupportedTensorFlowVersion: # skip the test logger.warning("Module tensorflow is not found or version wrong, \ please use pip install it / reinstall version >= {}.".format(SupportedTensorFlowVersion)) return generate_tfrecord() assert os.path.exists(os.path.join(TFRECORD_DATA_DIR, TFRECORD_FILE_NAME)) feature_dict = {"file_name": tf.io.FixedLenFeature([1], tf.string), "image_bytes": tf.io.FixedLenFeature([], tf.string), "int64_scalar": tf.io.FixedLenFeature([1], tf.int64), "float_scalar": tf.io.FixedLenFeature([1], tf.float32), "int64_list": tf.io.FixedLenFeature([6], tf.int64), "float_list": tf.io.FixedLenFeature([7], tf.float32), } if os.path.exists(MINDRECORD_FILE_NAME): os.remove(MINDRECORD_FILE_NAME) if os.path.exists(MINDRECORD_FILE_NAME + ".db"): os.remove(MINDRECORD_FILE_NAME + ".db") with pytest.raises(ValueError): tfrecord_transformer = TFRecordToMR(os.path.join(TFRECORD_DATA_DIR, TFRECORD_FILE_NAME), MINDRECORD_FILE_NAME, feature_dict, ["image_bytes"]) tfrecord_transformer.transform() if os.path.exists(MINDRECORD_FILE_NAME): os.remove(MINDRECORD_FILE_NAME) if os.path.exists(MINDRECORD_FILE_NAME + ".db"): os.remove(MINDRECORD_FILE_NAME + ".db") os.remove(os.path.join(TFRECORD_DATA_DIR, TFRECORD_FILE_NAME)) def test_tfrecord_to_mindrecord_scalar_bytes_with_10_exception(): """test transform tfrecord to mindrecord.""" if not tf or tf.__version__ < SupportedTensorFlowVersion: # skip the test logger.warning("Module tensorflow is not found or version wrong, \ please use pip install it / reinstall version >= {}.".format(SupportedTensorFlowVersion)) return generate_tfrecord() assert os.path.exists(os.path.join(TFRECORD_DATA_DIR, TFRECORD_FILE_NAME)) feature_dict = {"file_name": tf.io.FixedLenFeature([], tf.string), "image_bytes": tf.io.FixedLenFeature([10], tf.string), "int64_scalar": tf.io.FixedLenFeature([1], tf.int64), "float_scalar": tf.io.FixedLenFeature([1], tf.float32), "int64_list": tf.io.FixedLenFeature([6], tf.int64), "float_list": tf.io.FixedLenFeature([7], tf.float32), } if os.path.exists(MINDRECORD_FILE_NAME): os.remove(MINDRECORD_FILE_NAME) if os.path.exists(MINDRECORD_FILE_NAME + ".db"): os.remove(MINDRECORD_FILE_NAME + ".db") with pytest.raises(ValueError): tfrecord_transformer = TFRecordToMR(os.path.join(TFRECORD_DATA_DIR, TFRECORD_FILE_NAME), MINDRECORD_FILE_NAME, feature_dict, ["image_bytes"]) tfrecord_transformer.transform() if os.path.exists(MINDRECORD_FILE_NAME): os.remove(MINDRECORD_FILE_NAME) if os.path.exists(MINDRECORD_FILE_NAME + ".db"): os.remove(MINDRECORD_FILE_NAME + ".db") os.remove(os.path.join(TFRECORD_DATA_DIR, TFRECORD_FILE_NAME))

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app/views.py

configuresystems/restful-api-with-flask

b6e4da905446fac8f899653a6f7a5408d6419fc4

[ "MIT" ]

2

2015-05-07T18:39:12.000Z

2016-07-01T20:06:06.000Z

app/views.py

configuresystems/restful-api-with-flask

b6e4da905446fac8f899653a6f7a5408d6419fc4

[ "MIT" ]

null

app/views.py

configuresystems/restful-api-with-flask

b6e4da905446fac8f899653a6f7a5408d6419fc4

[ "MIT" ]

2

2016-03-02T05:33:51.000Z

2021-02-24T02:28:26.000Z

"""So that we can modularize our application, we will use this as our our master file for application endpoints""" from .modules.todo import views

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